MEMBRANE-LOCALIZED TRANSCRIPTION REGULATORS: UNDERSTANDING POST-TRANSLATIONAL REGULATION AND SINGLE-MOLECULE DYNAMICS OF TCPP IN VIBRIO CHOLERAE By Lucas Maurice Demey A DISSERTATION Submitted to Michigan State University in partial fulfillment of the requirements for the degree of Microbiology and Molecular Genetics – Doctor of Philosophy 2022 ABSTRACT MEMBRANE-LOCALIZED TRANSCRIPTION REGULATORS: UNDERSTANDING POST-TRANSLATIONAL REGULATION AND SINGLE-MOLECULE DYNAMICS OF TCPP IN VIBRIO CHOLERAE By Lucas Maurice Demey Vibrio cholerae is a Gram-negative gastrointestinal pathogen that has evolved an elegant regulatory system to precisely time production of essential virulence factors. A key step in this regulatory system is the transcription of a soluble AraC-like transcription factor, ToxT. ToxR and TcpP, two membrane-localized transcription regulators (MLTRs), positively regulate toxT. Much work has contributed to our understanding of TcpP and ToxR regulation, yet major gaps remain in our knowledge of these MLTRs. MLTRs are unique one-component signal transduction systems because they respond to extracellular stimuli by influencing gene transcription from their location in the cytoplasmic membrane. In Chapter 2, I explore the prevalence and diversity of MLTRs within prokaryotes to enhance our understanding of TcpP and ToxR. I show that MLTRs are far more common among prokaryotes than previously anticipated and that MLTRs are an understudied class of transcription regulators. In Chapter 3, I describe the use of super-resolution single-molecule tracking to investigate how TcpP, a model MLTR, identifies the toxT promoter. I provide evidence that TcpP binds to the toxT promoter independent of ToxR, and TcpP transitions to a specific diffusion state. The data support the first biophysical model for how TcpP-like MLTRs locate their target promoters. TcpP is subject to a form of post-translational regulation known as regulated intramembrane proteolysis (RIP). RIP of TcpP results in its complete inactivation, resulting in loss of virulence factor production. TcpH inhibits RIP of TcpP under certain pH and temperature conditions. In Chapter 4, I describe the mechanism TcpH employs to inhibit TcpP RIP while V. cholerae is present in the mouse gastrointestinal tract. I demonstrate that the dietary fatty acid α-linolenic acid enhances inhibition. I also show that α-linolenic acid promotes TcpH-mediated inhibition of TcpP RIP by increasing association of both proteins with detergent-resistant membrane (DRM) domains. My work provides the first evidence that DRMs influence virulence factor transcription in V. cholerae and that a dietary fatty acid promotes V. cholerae pathogenesis. “Two things that remain eternally true and complement each other, in my view are: don’t snuff out your inspiration and power of imagination, don’t become a slave to the model; and the other, take a model and study it, for otherwise your inspiration won’t take on material form.” ― Vincent van Gogh iv ACKNOWLEDGEMENTS First, I would like to thank Vic for deciding to take a chance on me and for introducing me to TcpP and TcpH. From the start to the end of my PhD journey Vic has helped me to become a better communicator, better writer, a critical thinker, and a leader. While these skills have helped me to become a better scientist, these skills have all translated into almost every aspect of my life and have forever changed me for the better. I would also like to thank my committee members, Neal Hammer, Heedeok Hong, Lee Kroos, Chris Waters, who both challenged me and encouraged me throughout my graduate career. Of course, I also need to thank the entire DiRita lab who have been my rock. They were there through all my ups and downs, encouraging me when needed, and imploring me to focus on one topic at a time when I found a new paper I loved. First, I would like to thank Rhia who is the heart of the lab and keeps everything together in the midst of all the chaos that comes with research. I would also like to thank Ted and Beth who took to brunt of my science ranting. Ted and Beth (aka, Bethanol) are both selfless people who always take time to help and to offer advice. Lastly, but not least, I would like to thank Ritam who has always been an endless source of encouragement and a steadfast friend. To the DiRita lab, I entered the MMG department with the goal of earning a PhD, but I will be leaving with you as lifelong friends. Outside of MSU I also was privileged to have support from my mother, father, sister, and brother-in-law who encouraged me throughout graduate school. Last, but not v least, I need to thank John Nelson. Whether he knows it or not, John was really my first scientific mentor. Every day John was pushing me to question the status quo and to think outside of the box. Working for John was the best thing I could have ever done to prepare for my PhD journey. I am eternally grateful for what I learned while working for John. vi TABLE OF CONTENTS LIST OF TABLES x LIST OF FIGURES xi KEY TO ABBREVIATIONS xiv Chapter 1 – Introduction 1 1.1 – Vibrio cholerae 2 1.2 – V. cholerae Pathogenesis 3 1.3 – Regulation of the Virulence Cascade 4 1.4 – Concluding Remarks 9 Chapter 2 – Membrane-Localized Transcription Regulators within Prokaryotes 12 2.1 – Abstract 13 2.2 – Introduction 13 2.3 – Materials and Methods 18 2.3.1 – MLTR screen using the MIST database 18 2.3.2 – MLTR domain and gene neighborhood analysis 18 2.4 – Results 19 2.4.1 – The Vibrio genus 19 2.4.2 – The Salmonella and Escherichia Genera 24 2.4.3 – The Yersinia Genus 30 2.4.4 – The Enterococcus and Lactobacillus genera 34 2.4.5 – The Staphylococcus genus 40 2.5 – Discussion 43 Chapter 3 – Independent Promoter Recognition by TcpP Precedes Cooperative Promoter Activation by TcpP and ToxR 45 3.1 – Preface 46 3.2 – Abstract 46 3.3 – Introduction 47 3.4 – Materials and Methods 50 3.4.1 – Bacterial strains and growth conditions 50 3.4.2 – Plasmid construction 50 3.4.3 – Bacterial strain construction 51 3.4.4 – Growth Curves 51 3.4.5 – Real-time quantitative PCR (RT-qPCR) 52 3.4.6 – Protein electrophoresis and immunodetection 52 3.4.7 – Single-Molecule Microscopy 53 3.4.8 – Data Analysis 54 3.5 – Results 54 vii 3.5.1 – Single-molecule tracking of TcpP-PAmCherry is useful to study promoter identification, but cannot probe regulated-intramembrane proteolysis 54 3.5.2 – Baseline Dynamics of TcpP-PAmCherry 56 3.5.3 – Mutation of the toxTpro Decreases the Slow Diffusion State Occupancy 60 3.5.4 –ToxR Promotes TcpP-PAmCherry Association with the Slow and Fast Diffusion States 63 3.5.5 – Mutation of the TcpP Helix-Turn-Helix Domain Reduces the Percentage of Slowly Diffusing TcpP-PAmCherry 68 3.6 – Discussion 69 Chapter 4 – Co-Association of TcpP and TcpH within Detergent-Resistant Membranes Stimulates TcpH-Dependent Inhibition of Regulated Intramembrane Proteolysis of TcpP in Vibrio cholerae 75 4.1 – Abstract 76 4.2 – Introduction 77 4.3 – Methods and Materials 79 4.3.1 – Bacterial strains, plasmids, and growth conditions 79 4.3.2 – Plasmid construction 81 4.3.3 – Mutant construction 81 4.3.4 – Growth curves 82 4.3.5 – Western blots 82 4.3.6 – Enzyme Linked-Immunosorbent Assay (ELISA) 83 4.3.7 – Infant Mouse Colonization 83 4.3.8 – Real-time quantitative PCR (RT-qPCR) 84 4.3.9 – β-Galactosidase activity assay 84 4.3.10 – Subcellular Fractionation 85 4.3.11 – Triton X-100 Subcellular Fractionation 86 4.3.12 – Co-affinity precipitation 87 4.4 – Results 88 4.4.1 – TcpH Maintains in vitro Activity Upon Alteration of its Transmembrane and Periplasmic Domains 88 4.4.2 – TcpH TM domain is Critical for Colonization of Infant Mice 91 4.4.3 – The TcpH Transmembrane Domain Protects TcpP from RIP 93 4.4.4 – toxT Transcription is Enhanced with Crude Bile and is Dependent on the TcpH Transmembrane Domain 94 4.4.5 – α-Linolenic Acid Enhances toxT Transcription by Promoting TcpH-Dependent Enhanced RIP Inhibition 96 4.4.6 – Co-Association of TcpP and TcpH with Detergent-Resistant Membranes is Required for Enhanced RIP Inhibition 101 4.4.7 – TcpP and TcpH Interaction is critical for inhibition of RIP 105 4.4.8 – Miltefosine Functions Synergistically with α-Linolenic acid 109 4.5 – Discussion 110 Chapter 5– Concluding Remarks 118 5.1 – Conclusions and Significance 119 5.2 – Future Directions 121 viii APPENDICES 127 APPENDIX A: Supplemental Material for Chapter 2 128 APPENDIX B: Distribution of Membrane-Localized Transcription Regulators within the Prokaryotic Domain 142 APPENDIX C: Supplemental Material for Chapter 3 154 APPENDIX D: Supplemental Material for Chapter 4 170 APPENDIX E: Identifying Regions within TcpH Critical for its Function 198 APPENDIX F: Defining the Mechanism of Action of Toxtazin A and Toxtazin B 211 APPENDIX G: Heterogeneous Single-Cell toxT Transcription 217 REFERENCES 222 ix LIST OF TABLES Table A.1: Characterized MLTRs and their known cellular response and associated proteins ....................................................................................................................... 129 Table A.2: Membrane localized transcription regulators (MLTRs) within the Vibrio genus .................................................................................................................................... 131 Table A.3: Membrane localized transcription regulators (MLTRs) within the Escherichia and Salmonella genera ............................................................................................... 133 Table A.4: Membrane localized transcription regulators (MLTRs) within the Yersinia genus .......................................................................................................................... 134 Table A.5: Membrane localized transcription regulators (MLTRs) within the Enterococcus genus .......................................................................................................................... 135 Table A.6: Membrane localized transcription regulators (MLTRs) within the Lactobacillus genus .......................................................................................................................... 138 Table A.7: Membrane localized transcription regulators (MLTRs) within the Staphylococcus genus ................................................................................................ 140 Table B.1: Distribution of MLTRs within Bacterial Phyla.............................................. 150 Table C.1: Chapter 3 strain list .................................................................................... 165 Table C.2: Chapter 3 primer list .................................................................................. 168 Table D.1: Chapter 4 strain list .................................................................................... 188 Table D.2: Chapter 4 primer list .................................................................................. 193 x LIST OF FIGURES Figure 1.1: The Virulence cascade in V. cholerae .......................................................... 5 Figure 2.1: Prokaryotic Signal transduction systems ..................................................... 15 Figure 2.2: Characterized membrane localized transcription regulators (MLTRs) within Prokaryotes ................................................................................................................... 17 Figure 2.3: Representative MLTRs identified within the Vibrio genus ........................... 20 Figure 2.4: Representative MLTRs identified within the Escherichia and Salmonella genera ........................................................................................................................... 26 Figure 2.5: Representative MLTRs identified within the Yersinia genus ....................... 31 Figure 2.6: Representative MLTRs identified within the Enterococcus and Lactobacillus genera ........................................................................................................................... 35 Figure 2.7: Representative Staphylococcus MLTRs identified ...................................... 42 Figure 3.1: Single-molecule diffusion dynamics of TcpP-PAm ...................................... 58 Figure 3.2: TcpP-PAmCherry diffusion dynamics within live V. cholerae cells containing mutated regions of the toxT promoter (toxTpro) ............................................................ 61 Figure 3.3: TcpP-PAmCherry diffusion dynamics within live V. cholerae cells lacking ToxRS and regions of the toxT promoter ...................................................................... 65 Figure 3.4: Mutation of the DNA binding domain within TcpP reduces the number of TcpP molecules within the slow diffusion state ....................................................................... 67 Figure 4.1: TcpH transmembrane and periplasmic constructs protect TcpP, support toxT transcription, and virulence factor production ................................................................ 90 Figure 4.2: TcpH transmembrane constructs have a colonization defect in infant mice 93 Figure 4.3: α-Linolenic acid stimulates toxT transcription, elevated TcpP levels, and does not increase tcpP transcription ...................................................................................... 98 Figure 4.4: TcpP and TcpH abundance increases in detergent resistant membranes in the presence of α-linolenic acid ................................................................................... 103 Figure 4.5: TcpP and TcpH interaction is critical for TcpH-dependent inhibition of RIP .................................................................................................................................... 108 xi Figure 4.6: α-Linolenic acid stimulates co-association of TcpP and TcpH within detergent resistant membranes thereby enhancing TcpH inhibition of RIP ................................. 113 Figure C.1: Possible membrane localized transcription regulators (MLTRs) within Gram- negative and Gram-positive bacteria ........................................................................... 155 Figure C.2: Biochemical characterization of tcpP-PAm strains ................................... 156 Figure C.3: TcpH protects TcpP-PAm from proteolysis ............................................... 157 Figure C.4: toxT transcription profile in tcpP-PAm strains ........................................... 158 Figure C.5: PAmCherry does not promote dimerization of TcpP ................................. 159 Figure C.6: tcpP-PAm strains have growth dynamics similar to WT ........................... 160 Figure C.7: Complementation and overexpression of ToxR in tcpP-PAm strains ....... 161 Figure C.8: TcpP-PAmCherry transition plots ............................................................ 162 Figure C.9: ToxR overexpression reduces virulence factor production ....................... 164 Figure D.1: TcpH transmembrane and periplasmic constructs growth dynamics are similar to WT........................................................................................................................... 175 Figure D.2: TcpH transmembrane and periplasmic constructs support toxT transcription and CtxB production .................................................................................................... 176 Figure D.3: TcpH transmembrane and periplasmic constructs display WT growth in adult mice feces ................................................................................................................... 177 Figure D.4: TcpH transmembrane constructs inhibit RIP of TcpP ............................... 178 Figure D.5: Crude bile stimulates toxT transcription in a TcpH dependent manner .... 179 Figure D.6: α-Linolenic acid stimulates toxT transcription in a TcpH dependent manner .................................................................................................................................... 180 Figure D.7: ɑ-Linolenic acid stimulates toxT transcription in a dose dependent manner .................................................................................................................................... 181 Figure D.8: toxT transcription is stimulated by crude bile and α-linolenic acid, but tcpP transcription does not change ..................................................................................... 182 Figure D.9: TcpP levels are elevated in the presence of crude bile and α-linolenic acid .................................................................................................................................... 183 Figure D.10: α-Linolenic acid promotes association of TcpP and TcpH with detergent resistant membranes (DRM) ....................................................................................... 184 xii Figure D.11: α-Linolenic acid does not promote non-specific protein association with detergent resistant membranes ................................................................................... 185 Figure D.12: Hsv-His(6x) tagged TcpP constructs remain functional ......................... 186 Figure D.13: Miltefosine and α-linolenic acid function synergistically to stimulate toxT transcription................................................................................................................. 187 Figure E.1: TcpH transmembrane and periplasmic constructs remain functional in vitro .................................................................................................................................... 201 Figure E.2: Residues within region 136-103 in the periplasmic domain of TcpH are critical for protecting TcpP under non-virulence inducing conditions ...................................... 203 Figure E.3: Overexpression of TcpH transmembrane and periplasmic constructs allows for visualization via western blot .................................................................................. 204 Figure E.4: TcpH transmembrane and periplasmic constructs Infant mouse colonization and growth in adult mice feces .................................................................................... 207 Figure E.5: TcpH transmembrane constructs inhibit RIP of TcpP and CtxBTcpH remains localized to the cytoplasmic membrane....................................................................... 209 Figure F.1: Characterization of toxtazin A and B mechanism of action ....................... 215 Figure G.1: Single-cell toxT transcription is heterogenous in V. cholerae ................... 219 Figure G.2: TcpP is sensitive to an unknown protease upon mutation of tsp and yaeL .................................................................................................................................... 220 xiii KEY TO ABBREVIATIONS 3,3',5,5'-tetramentylbenzidine TSB Accessory Cholera Enterotoxin Ace Avian pathogenic E. coli APEC CAAX Proteases and Bacteriocin-Processing metalloproteases CPBP Cellulose polysaccharide locus bcs CFU Colony forming units Cholera toxin CtxAB Cyclic adenosine monophosphate cAMP Cyclic di-peptide cyclic phenylalanine-proline cyc-phe-pro Detergent resistant membranes DRM Detergent soluble membranes DSM Diaminopimelic acid DAP Diarrheagenic E. coli DEC Dithiobis-succinimidyl propionate DPS DNA Deoxyribonucleic acid DMSO Dimethyl sulfoxide Enteroaggregative E. coli EAEC Enterohemorrhagic E. coli EHEC/STEC Enteroinvasive E. coli EIEC Enteropathogenic E. coli EPEC Enterotoxigenic E. coli ETEC xiv Enzyme Linked-Immunosorbent Assay ELISA ETT2 E. coli type III secretion system 2 Global Regulator of Virulence protein A GrvA Guanine nucleotide-binding regulatory protein Gsα Histone-like nucleoid structuring protein H-NS Isopropyl β-d-1-thiogalactopyranoside IPTG Lactic acid bacteria LAB Locus of enterocyte effacement LEE Lysogeny Broth LB Membrane localized transcription regulators MLTRs Microbial Signal Transduction Database MIST Monosialoganglioside GM1 Multifunctional Auto processing Repeats-in-toxin RTX Multi-transmembrane domain MLTR MT-MLTR Nitric oxide NO Nitrogen assimilation control Nac Non-virulence inducing non-Vir Ind Non-virulence-inducing conditions LB pH 8.5, 37˚C, shaking at 210rpm Optical density O.D.600nm Periplasmic domain Peri Photoactivatable mCherry PAmCherry Poly-unsaturated fatty acids PUFA Regulated Intramembrane Proteolysis RIP xv Salmonella pathogenicity island 1 SPI-1 Salmonella pathogenicity island 2 SPI-2 Salmonella pathogenicity island 3 SPI-3 Salmonella typhimurium fimbriae operon stf Single-Molecule Analysis by Unsupervised Gibbs sampling SMAUG Super-resolution single-molecule tracking SMT Tail-specific protease Tsp Thiosulfate-citrate-bile salts-sucrose agar TCBS Toxin co-regulated pilus Tcp toxT promoter toxTpro Transmembrane TM Triton insoluble TI Triton soluble TS Type three secretion system T3SS Untranslated region UTR Uropathogenic E. coli UPEC Uropygial gland Preen gland Virulence-inducing Vir Ind Virulence-inducing conditions LB pH 6.5, 110 rpm, 30˚C Vibrio Pathogenicity Island 1 VPI-1 Vibrio seventh pandemic island I VPS-1 Vibrio seventh pandemic island 2 VSP-2 WT Wild type xvi Y. enterocolitica chromosomally encoded T3SS Ysa Y. enterocolitica plasmid that encoded a T3SS Ysc xvii Chapter 1 – Introduction 1 1.1 – Vibrio cholerae V. cholerae is a Gram-negative free-living marine bacterium that is the agent of the diarrheal disease cholera. Cholera is a life-threatening disease that has been a recurring problem around the world since 1817 when the first of seven recorded cholera pandemics began and continues to pose a significant global burden killing ~95,000 people annually (1–3). Treatment of V. cholerae infection currently involves oral rehydration therapy, and antibiotic therapy (4–6). To reduce the burden of V. cholerae several vaccines have been developed (7–10). However, despite treatment options and vaccine development these conventional methods to combat V. cholerae have been ineffective at reducing the incidence of cholera cases (11–14). To add insult to injury, changes in global climate and temperature are anticipated to allow V. cholerae to proliferate in new geographical areas leading to more cholera cases (15). Thus, there is a need for novel treatment methods to combat V. cholerae infections. Identification and development of these novel treatment methods will require a deeper understanding of the pathogenesis of V. cholerae. Thus, the aim of this work has been to deepen our understanding of virulence gene regulation in V. cholerae. The first six Cholera pandemics were dominated by the Classical biotype of V. cholerae and was supplanted by the El Tor biotype during the seventh pandemic. Classical and El Tor biotypes differ in the severity of disease and their proliferation in aquatic environments with El Tor biotypes causing milder disease and better survival in aquatic environments (16). El tor and Classical biotypes also differ by their sensitivity to polymyxin B, acetylmethylcarbinol synthesis, phage sensitivity, hemolysis of sheep enterocytes, chicken erythrocytes agglutination, and their ctxB and tcpA alleles (17, 18). 2 In addition, El Tor biotypes acquired the Vibrio seventh pandemic island I and 2 (VPS-1 and VSP-2) (19). Despite these differences, many genes involved in regulation of virulence factor production are highly conserved between Classical and El Tor biotypes, with intergenic mutations driving differences in virulence factor transcription (20). 1.2 – V. cholerae Pathogenesis V. cholerae infections occur via the fecal-oral route, typically from consumption of undercooked contaminated food or water (21, 22). Once ingested, V. cholerae cells must survive the acidic stomach environment to reach the small intestine. Once inside the lumen of the small intestine, V. cholerae cells proceed to colonize the middle and distal portions of the small intestine, where they must penetrate the thick mucus layer to reach the epithelial crypt, the primary site of infection (23–25). To proliferate, V. cholerae employs a number of virulence factors to establish colonization, suppress the host immune response, and to manipulate host cells to proliferate. To colonize the small intestine, V. cholerae cells must compete with the host microbiota via direct killing mediated by the type-6 secretion system, stimulate permeability of the mucus layer (via Hemagglutinin Protease, Neuraminidase, and the Zonula Occludens Toxin), and colonize epithelial cells promoted by the Toxin co-regulated pilus (Tcp) via an unknown mechanism (26–32). In addition to colonization, V. cholerae cells must also resist the host-immune response. Host cells are known to produce nitric oxide (NO) in response to bacterial infections, and V. cholerae cells sense NO via NorR and detoxify NO via HmpA (33). In addition, V. cholerae also reduces the innate epithelial immune defense and mucosal inflammation by secreting membrane vesicles which carry small RNAs (e.g., miR-146a) that inhibit host immunomodulatory micro-RNAs (34). V. cholerae further 3 modulates the host immune response by suppressing chemokine and cytokine mediated recruitment of innate immune cells normally induced in response to cytoskeleton damage via the Multifunctional Autoprocessing Repeats-in-toxin (RTX) (35). Once at the site of infection, V. cholerae cells stimulate fluid accumulation via secretion of cholera toxin (CtxAB) and Accessory Cholera Enterotoxin (Ace). CtxAB is secreted from V. cholerae cells and binds to host monosialoganglioside (GM1) (36). Upon binding to host GM1 CtxAB enters host epithelial cells via endocytosis and activates a subunit of the guanine nucleotide-binding regulatory protein (Gsα) (36). This leads to stimulation of adenylate cyclase activity yielding high levels of cyclic adenosine monophosphate (cAMP) (36). This in turn leads to the inactivation of NHE3 H+/Na+ transporters and stimulates secretion of Cl- via the cystic fibrosis transmembrane conductance regulator (36). The net effect is an increase in NaCl, as well as Cl-, HCO−3, Na+, K+, and H2O, secretion and a reduction of NaCl absorption resulting in watery diarrhea (36). Ace stimulates Ca2+ dependent Cl−/HCO3− cotransporters in host cells independent of cAMP (37, 38). Ace mediated fluid accumulation appears to have a role early during infection before CtxAB fluid accumulation dominates. 1.3 – Regulation of the Virulence Cascade Transcription of tcpA-F and ctxAB is regulated by ToxT, an AraC like transcription factor (39–42) (Figure 1.1). In the small intestinal lumen, unsaturated fatty acids directly bind to the N-terminal domain of ToxT preventing dimerization and subsequent transcription of tcpA-F and ctxAB by ToxT (43–46). Inhibition of ToxT activity by unsaturated fatty acids also reduces degradation of ToxT in the cytoplasm (47, 48). 4 Unsaturated fatty acids serve as a cue to regulate ToxT activity to prevent premature virulence factor transcription and protect the pool of ToxT within the cytoplasm (48). As V. cholerae inches closer to the epithelial brush border the concentration of bicarbonate increases, reaching maximal concentration at the surface of epithelial cells due to active secretion of bicarbonate from host cells (49). Bicarbonate stimulates ToxT activity by promoting dimerization of ToxT monomers and also inhibits unsaturated fatty acid antagonism of ToxT activity (50). The available literature indicates that virulence factor transcription occurs maximally at the surface of epithelial cells. Figure 1.1: The Virulence cascade in V. cholerae. Dimerization ToxT stimulates its activity and ability to stimulate ctxAB and tcp transcription (50, 51). Unsaturated fatty acids, such as α-linolenic acid, inhibit dimerization of ToxT and thereby its activity (43– 46). Bicarbonate promotes dimerization of ToxT molecules (50). Transcription of toxT is stimulated by ToxR and TcpP and indirectly by their associated proteins, ToxS and TcpH respectively (39–41, 52–57). Currently, it remains unclear how TcpP and ToxR co-localize to the toxT promoter while localized to the cytoplasmic (indicated by 1). In addition to identifying the toxT promoter, it is currently not understood how TcpH protects TcpP from Regulated Intramembrane Proteolysis (RIP) in vivo or in vitro (indicated by 2). Once localized to the cytoplasmic membrane, TcpP is prone to RIP, which is stimulated or inhibited by culture conditions (56, 58, 59). Stimulation of RIP of 5 Figure 1.1 (cont’d) TcpP occurs under non-virulence inducing conditions (i.e., LB pH 8.5, 210rpm, 37 °C) in a two-step process. RIP of TcpP is initiated by Tsp, cleaving the periplasmic domain of TcpP, and secondly by YaeL removing the cytoplasmic domain from the membrane (58, 59). tcpP and tcpH are also subject to significant transcriptional regulation. tcpPH transcription is negatively regulated by both PepA (under alkaline pH) and catabolite repressor protein (CRP, when levels of cyclic AMP are high) (60–62). tcpPH transcription is stimulated by AphA, AphB and OhrR, and their activity is further enhanced by low oxygen concentrations (O2) further increasing tcpPH transcripts (63– 65). At high cell density aphA transcription is inhibited by HapR (66). At low cell density translation of HapR mRNAs is inhibited by the Quorum regulatory RNAs (Qrr), which are upregulated at low cell density, in association with Hfq (67, 68). In addition to post-translational regulation of ToxT, transcription of toxT is highly regulated and is positively stimulated by TcpP and ToxR, two membrane localized transcription regulators (39–41, 52–55). TcpP and ToxR are bitopic membrane proteins that each contain a cytoplasmic OmpR family DNA-binding domain, a single transmembrane domain, and a periplasmic domain (69). Both ToxR and TcpP bind to the promoter region of the toxT, -180 to -60 and -55 to -37 respectively (55, 70, 71). TcpP is absolutely essential for toxT transcription while loss of toxR can be overcome by overexpression of tcpP (39, 55). ToxR is more promiscuous relative to TcpP in its specificity for binding DNA sequences (71–73). It is thought that one of the major biological roles of ToxR is to antagonize the histone-like nucleoid structuring protein (H- NS) to derepress transcription of H-NS target genes (72). It is thought that one mechanism by which ToxR cooperates with TcpP to stimulate toxT transcription is by antagonizing H-NS binding to the toxT promoter. However, there are still questions regarding how ToxR and TcpP cooperate to stimulate toxT transcription. There are several models for cooperative activation of the toxT promoter by TcpP and ToxR (71). Several models ascribe ToxR’s major role as recruiting TcpP molecules to the toxT promoter, and this role is supported by evidence that heterodimerization of TcpP and 6 ToxR, stimulated by anaerobic conditions, stimulates toxT transcription (71, 74). However, data also support an alternative promoter alteration model in which ToxR promotes toxT activation by altering the promoter topology promoting TcpP binding without direct recruitment of TcpP by ToxR (71). In this model heterodimerization of TcpP and ToxR would not have an obvious role. Homodimerization of TcpP (stimulated by taurocholate) molecules has been shown to be critical for toxT transcription and suggests that TcpP-ToxR heterodimers disassociate prior to interaction with the toxT promoter (75– 78). As there is data supporting multiple models of cooperativity between TcpP and ToxR it remains unclear how these MLTRs function together to stimulate toxT transcription. Independent of cooperativity, TcpP and ToxR are also sensitive to a form of post- translational regulation known as Regulated Intramembrane Proteolysis (RIP) (56, 58, 59, 79, 80). For both TcpP and ToxR RIP is a two-step process where their periplasmic domains undergo proteolysis first via a site-1 protease/s (TcpP: Tsp, ToxR: DegS and DegP) and their transmembrane domains secondly by a site-2 protease (YaeL, also referred to as RseP) which inactivates both TcpP and ToxR (56, 58, 59, 79, 80). Conditions that promote RIP of TcpP and ToxR inhibit toxT transcription. RIP of TcpP and ToxR is inhibited by their associated proteins, ToxS and TcpH respectively, under specific conditions (56, 58, 59, 81, 82). ToxR has been reported to undergo RIP under nutrient limiting conditions, alkaline pH, and in the absence of ToxS (80, 83). Conditions that stimulate RIP of ToxR occur during stationary phase, and RIP of ToxR is critical for V. cholerae cells to enter a viable but non-culturable state, which is thought to be important for survival of V. cholerae in the environment (80). ToxS has been shown to inhibit RIP of ToxR by directly associating with ToxR molecules in response to bile salts (such as 7 deoxycholate) (81, 83–85). RIP of TcpP is stimulated by alkaline pH (pH 8.5) and high temperature (37°C), and RIP of TcpP is inhibited by low temperature and mild acidity (30°C and pH 6.5) (56, 58, 59). Similar to ToxS, TcpH is a membrane localized protein which protects TcpP from RIP under specific in vitro conditions (56, 58, 59). Currently, it is not clear how TcpH inhibits RIP of TcpP nor is it clear what signals in vivo promote TcpH antagonism of RIP. In addition to post-translational regulation, TcpP transcription is also heavily regulated. Transcription of tcpPH is stimulated by AphA and AphB in response to low pH and anoxic conditions (63, 64). Furthermore, AphA transcription is also modulated by cell density of V. cholerae (66). Under low cell density LuxO is phosphorylated in response to low concentrations of autoinducers (cholerae autoinducer-1 [CAI-1] and autoinducer-2 [AI-2]) and stimulates transcription of several small regulatory RNAs, qrr1-4 (67, 68). These regulatory RNAs inhibit translation of HapR thereby relieving repression of aphA (66–68). tcpPH transcription is also stimulated by OrhR under anoxic conditions (65). Together, AphAB and OrhR function to stimulate transcription of tcpPH at low cell density, mildly acidic pH, and anaerobic conditions (Figure 1.1). Transcription of tcpPH is also responsive to nutrient conditions. Under nutrient limiting conditions levels of cAMP are high leading to activation of cAMP receptor protein (CRP). Upon activation of CRP via binding to cAMP, cAMP-CRP inhibits transcription of both the toxT and tcpPH (60, 61). Conversely, under nutrient rich environments, such as the human gastrointestinal tract, cAMP-CRP levels are low releasing repression of toxT and tcpPH (60, 61). tcpPH transcription is further fine-tuned by PepA, which represses transcription of tcpPH under alkaline pH (62). 8 Taken together, the current body of literature suggests that during the early phase of infection cues in the lumen of the gastrointestinal environment (e.g., acidic pH, low oxygen availability, bile salts, and abundant nutrient availability) elevate tcpPH transcription, promote TcpP and ToxR homo/hetero-dimerization, and thereby promote toxT transcription. While in the lumen of the small intestine, ToxT is inhibited by high concentrations of unsaturated fatty acids. Once V. cholerae reaches the surface of epithelial cells, where bicarbonate concentrations are high, bicarbonate competes with unsaturated fatty acids to stimulate activation of ToxT and thereby downstream virulence factor transcription (i.e., ctxAB and tcpA-F). 1.4 – Concluding Remarks V. cholerae is a life-threatening pathogen that continues to pose a major global health burden. V. cholerae continues to be a major burden around the globe despite the availability of conventional treatment options. There is a critical need to develop a deeper understanding of V. cholerae pathogenesis. There remain major gaps in our knowledge regarding regulation of toxT transcription and the function of MLTRs in general. TcpP and ToxR are unique transcription factors as they are localized to the membrane (i.e., MLTRs). Currently, there are also major questions regarding how membrane localized transcription regulators (MLTRs) in general function from the membrane because only a few DNA binding transcription factors are capable of influencing gene transcription from the membrane. For example, Enterohemorrhagic Escherichia coli is a foodborne human gastrointestinal pathogen that stimulates virulence gene transcription in response to mechanical stimuli via GrlA, a membrane bound 9 transcription factor (86). While localized to the membrane GrlA is not fully active and requires cytoplasmic localization after mechanical stimuli (86). Secondly, within Salmonella typhimurium PutA is a bifunctional transcription factor that represses transcription of putP (a proline permease) and catalyzes the oxidation of proline (87). In the absence of proline, PutA is localized to the cytoplasm where it can repress putP transcription, and in the presence of proline PutA becomes sequestered to the cytoplasmic membrane to oxidize proline and is unable to repress putP (87). MLTRs are poorly studied and as such their distribution among bacteria is not understood. To better understand how MLTRs function from the membrane, we conducted a computational screen to identify MLTRs within other bacteria to gain an appreciation for the diversity, conservation, and overall prevalence of MLTRs within bacteria. A summary of our findings is presented in Chapter 2. Currently, we do not have a complete understanding of how ToxR and TcpP function cooperatively to stimulate toxT transcription. There are several models for how TcpP and ToxR function to stimulate toxT transcription such as the hand-holding model which states that ToxR displaces H-NS by binding downstream of the toxT promoter and recruits TcpP molecules via direct interaction between their cytoplasmic domains (71). Similar to the hand holding model, the catch and release model proposes that ToxR displaces H-NS from the toxT promoter and brings TcpP to the toxT promoter via direct interaction (71). However, this model suggests that ToxR-TcpP interaction disengages when ToxR binds to the toxT promoter allowing TcpP to bind to the proximal region of the toxT promoter (71). Thirdly, the membrane recruitment model posits that ToxR recruits TcpP, without direct interaction, to a region within the membrane proximal to the toxT 10 promoter to more efficiently interact with the promoter (71). Lastly, the promoter alteration model hypothesizes that ToxR does not recruit TcpP to the toxT promoter directly but rather that ToxR promotes TcpP interaction with the toxT promoter by altering the DNA architecture of the toxT promoter (71). To decipher the mechanism of cooperativity between TcpP and ToxR, and to gain a deeper understanding for how MLTRs function from the membrane, we measured the dynamics of single TcpP molecules within live V. cholerae cells to gain insights into how TcpP finds the toxT promoter. This work is presented in Chapter 3. In addition to not understanding how TcpP and ToxR function from the membrane, we lack a complete understanding of how RIP of TcpP is regulated. As TcpP is essential for toxT transcription, we reasoned that RIP of TcpP must be inhibited in vivo, so we set out to gain a deeper understanding of this regulation. In Chapter 4 we demonstrate that RIP of TcpP is modulated by a dietary fatty acid, α-linolenic acid. More specifically, we demonstrate that TcpH and TcpP associate with detergent-resistant membranes in the presence of α-linolenic acid, and this event corresponds with antagonism of TcpP RIP and elevated toxT transcription. 11 Chapter 2 – Membrane-Localized Transcription Regulators within Prokaryotes 12 2.1 – Abstract To adapt and proliferate bacteria must sense and respond to the ever-changing extracellular environment. One-component transcription regulators are the major tool bacteria employ to adapt their gene transcription to match their changing environment. Membrane-localized transcription regulators (MLTRs) are a family of one-component transcription regulators that respond to extracellular information and influence gene transcription from the cytoplasmic membrane. How MLTRs function to influence transcription of their target genes while localized to the cytoplasmic membrane remains an enigma. To better understand why and how MLTRs localize and function in the cytoplasmic membrane we attempted to understand the prevalence of MLTRs within the Escherichia, Salmonella, Yersinia, Vibrio, Staphylococcus, Enterococcus, and Lactobacillus genera. Here we show that MLTRs are highly diverse, horizontally transmissible, and highly prevalent among Gram-positive and Gram-negative bacteria. Our work demonstrates that MLTRs are more common than previously thought, and yet MLTRs remain poorly understood. 2.2 – Introduction Signal transduction is the process whereby microorganisms regulate their cellular programs according to their extracellular environment. Microorganisms are known to transduce information from outside the cell to the cytoplasm via two-component, one- component, and anti-sigma factor signal transduction systems (88–91). Two-component signal transduction cascades are typically composed of a membrane localized receptor that transfers a phosphate, when stimulated, to a soluble response regulator resulting in 13 a cellular response, and anti-sigma factors are composed of a membrane localized protein that sequesters an alternative sigma factor, which is an essential component of RNA polymerase and directs it to specific promoters to stimulate transcription, is released from the cytoplasmic membrane, via proteolysis of the anti-sigma factor, under suitable conditions (Figure 2.1) (88–92). One-component signal transduction systems are composed of a single protein that directly detects a stimuli and is then able to directly influence a cellular response (Figure 2.1) (88, 89, 92). Prior studies have revealed that the vast majority of signal transduction systems in bacteria are one-component signal transduction systems (89, 93). The vast majority of one-component signal transduction systems harbor DNA-binding domains or diguanylate/diadenylyl cyclase, or phosphodiesterase, domains which synthesize or breakdown nucleotide second messengers (89, 93–95). A majority of one-component regulators are predicted to be localized within the cytoplasm, presumably to have unimpeded access to their DNA target(s) (89). Nonetheless, there are one-component regulators that are localized to the cytoplasmic membrane, otherwise known as membrane localized transcription regulators (MLTRs) (Table A.1). Localization to cytoplasmic membrane has been shown to be critical for some MLTRs to influence transcription of their target genes (54, 96). MLTRs are counterintuitive as it would presumably inhibit, or greatly reduce, the ability of a one-component regulator to bind to its target promoter. This is thought to be the main driver that led to the evolution of two-component signal transduction systems. There is evidence of evolution of MLTRs from two-component systems. Within Pseudomonas aeruginosa, PilS, the membrane localized histidine kinase, and PilR, the response regulator, together regulate activity of 14 RpoN (97). Neisseria gonorrhoeae was found to encode Rsp, with the membrane localized receptor of pilS at its N-terminus and the pilR DNA binding domain at its C- terminus, and Rsp represses pilA transcription (98). There is clearly an evolutionary pressure for MLTRs within microorganisms, but what constitutes this evolutionary pressure is still unclear. Figure 2.1: Prokaryotic signal transduction systems. Signal transduction is known to occur via two-component systems (on the left) and one-component systems (middle and right). Two-component signal transduction systems are commonly composed of a membrane localized histidine kinase that detects an extracellular signal (indicated by the black pentagon) and transfers a phosphate group (indicated by the blue circle) to a soluble response regulator which can influence gene transcription. One-component systems contain both a sensory domain and an output domain, most commonly a DNA binding domain, that influences gene transcription. Canonical one-component systems are localized in the cytoplasm where they are able to respond to a stimuli (indicated by the yellow circle) and directly diffuse to their target promoters to influence gene transcription. Membrane localized transcription regulators (MLTRs) are non-canonical one-component regulators that manage to respond to an extracellular stimuli to influence gene transcription of their target genes while maintaining their localization in the cytoplasmic membrane. 15 Functional MLTRs are found within prokaryotes and archaea. Due to differences in cellular physiology MLTRs require liberation from the cytoplasmic membrane within eukaryotes, due to the separation of the cytoplasmic membrane and their genomes by the nucleus. Within archaea, MLTRs have only been found to regulate motility and pilin gene transcription in response to dangerous temperatures and nutrient limiting conditions (99, 100). MLTRs are better studied within prokaryotes and have been found to regulate bile salt resistance, toxin production, antibiotic resistance, acid resistance, natural competence, pilin/fimbriae transcription, type-3 secretion systems, biofilm formation, metabolism, and have been implicated in modulation of the human immune system (Figure 2.2 and Table A.1) (52, 71, 101–114). Currently, it remains unclear why MLTRs are localized to the cytoplasmic membrane and how they function from the cytoplasmic membrane. In part, this is due to a lack of information regarding their prevalence. To gain a deeper understanding of MLTRs we utilized the MIST database to gain a better understanding of how prevalent MLTRs are within specific prokaryotic genera. Here we describe our findings and review what is currently known about identified MLTRs. In collaboration with the Jouline lab, we also performed an unbiased screen to identify MLTRs across the prokaryotic domain by screening 10,933 bacterial genomes, present in the MIST database. This ongoing work is presented in Appendix B. 16 Figure 2.2: Characterized membrane localized transcription regulators (MLTRs) within Prokaryotes. MLTRs within Gram-negative(A) and Gram-positive (B) bacteria. DNA binding domains are localized to the cytoplasm for all MLTRs, and the DNA binding domain family for each MLTR is also indicated. 17 2.3 – Materials and Methods 2.3.1 – MLTR screen using the MIST database Species from the genus Vibrio, Salmonella, Escherichia, Yersinia, Enterococcus, Lactobacillus, and Staphylococcus were included in our analysis. The MIST database does not contain every species within each of the aforementioned genera. As such our analysis is not a comprehensive analysis of each of the mentioned genera. Candidate membrane localized transcription regulators (MLTRs) sequences were acquired from the MIST database (115). Candidate MLTRs were selected based on the presence of a DNA binding domain and at least one transmembrane domain. Of note, the MIST database did not define ToxR, a known MLTR, as having a transmembrane domain. As such, ToxR sequences for V. cholerae 01 El Tor, V. cholerae 0395, and V. parahaemolyticus were acquired manually from NCBI and included in downstream analysis. Finally, MLTRs presented here likely are an underestimate of the true number of MLTRs within these bacteria. Once the candidate MLTRs were acquired the topology of the candidate MLTRs were predicted using the TMHMM server (116). Candidate MLTRs with their DNA binding domain predicted to be localized outside of the cytoplasm were dropped from our analysis. Candidate MLTRs with predicted cytoplasmic DNA binding domains were included in further analysis. See Supplemental File 2.1 for the sequences of MLTRs identified here. 2.3.2 – MLTR domain and gene neighborhood analysis Predicted MLTRs were separated by genera and follow up phylogenetic analysis of predicted MLTRs were done using the TREND server (117). Predicted MLTRs were 18 aligned using the FFT-NS-2 algorithm, and phylogenetic trees were generated using the maximum likelihood method with 100 bootstrap replicates. We also interrogated the gene neighborhood using the TREND server with the same settings. Candidate TcpH and ToxS-like genes were identified by their proximity to a MLTR (i.e., overlapping reading frames or immediately upstream or downstream) and the presence of an N-terminal transmembrane domain. MLTRs that clustered with known MLTRs were considered to be related and have similar functions. BLAST was also used to confirm the degree of similarity between MLTRs (118, 119). 2.4 – Results 2.4.1 – The Vibrio genus ToxR was the first identified MLTR and is an ancestral gene conserved within the Vibrio and Photobacterium genus (53, 120, 121). Members of the Vibrio genus are Gram- negative, rod-shaped, mesophilic, and inhabit marine and freshwater environments (122, 123). ToxR is well known for its role in regulating transcription of virulence factors and bile salt resistance in V. cholerae via regulation of toxT, cxtAB, leuO, and ompUT (39– 41, 55, 70, 71, 104, 105, 124–129). ToxR has also been implicated in regulating virulence gene transcription in other pathogenic Vibrio spp. directly, via regulation of ctxAB, tdh, vvhA, or indirectly by promoting biofilm formation and bile resistance (126, 130, 131). However, the ToxR regulon has been shown to regulate a diverse set of phenotypes and has a clear role in non-pathogenic Vibrio spp. such as regulating hydrostatic pressure response (72, 120). TcpP was later identified within the Vibrio Pathogenicity Island 1 (VPI- 1) to promote, in coordination with ToxR, toxT transcription, and has not been shown to 19 directly regulate additional genes (39, 52, 54, 55, 132). Among the 14 members of the Vibrio genus that were screened for MLTRs, using the MIST database, a total of 70 MLTRs were identified (Figure 2.3 and Table A.2). Of those MLTRs identified, ~23% were found to be ToxR and TcpP homologs. Given that ToxR has been suggested to be an ancestral MLTR within the Vibrio genus we anticipated many MLTRs bearing homology to ToxR. However, V. campbellii, V. fluvialis, and V. proteolyticus were found to encode two copies of ToxR (Table A.2). V. fluvialis is an emerging pathogen capable of causing gastrointestinal and extragastrointestinal diseases, including acute cholecystitis (133). It remains unclear if multiple copies of ToxR within V. fluvialis, V. campbellii, or V. proteolyticus promote bile salt resistance, but given our current knowledge of ToxR it remains possible. Figure 2.3: Representative MLTRs identified within the Vibrio genus. Ovals represent protein domains identified and gray squares represent transmembrane domains, see Supplemental Figure 2.1 for view of protein domains. The black line represents the total coding sequence of the MLTR. See Supplemental Figure 2.1 for complete phylogenetic information. 20 Similarly, Vibrio fischeri was found to encode two TcpP homologs (VFA0473 and VFA0860) (Table A.2). Prior work Identified VFA0473 (HtbR) as a TcpP homolog and revealed that it plays a role in the symbiotic relationship between V. fischeri and Euprymna scolopes, the Hawiian bobtail squid (134). V. fischeri is a bioluminescent bacterium that colonizes the light organs of E. scolopes to metabolize nutrients provided in exchange for luminescing at night to provide E. scolopes camouflage (135–137). V. fischeri cells are guided to the E. scolopes light organ by following a gradient of N- acetylated sugars where they colonize the light organ and utilize carbon provided by E. scolopes to proliferate (138). The symbiotic relationship between E. scolopes and V. fischeri undergoes daily cycles, growth of V. fischeri during the day, V. fischeri cells luminesce at night, and V. fischeri cells are shed at dawn (139–142). Upon exiting the light organ, V. fischeri cells upregulate numerous genes including HbtR (VFA0473) and HbtC, homologs of TcpP and TcpH, respectively (143). It was found that HbtR represses litR, via an unknown mechanism, resulting in an increase in motility, chemotaxis, and a reduction in synthesis of extracellular polysaccharides, thus helping V. fischeri cells return to a planktonic lifestyle (134). Given the low sequence homology between HbtRC and TcpPH (~26%) it is likely that both TcpPH and HbtRC were acquired by V. cholerae and V. fischeri independently (134). Within V. cholerae, tcpPH are encoded within a horizontally acquired pathogenicity island (VPI-1 that encodes the Toxin co-regulated pilus (TCP) operon (144, 145). V. fischeri also encodes the TCP gene cluster found within the VPI-1, but eight of the TCP genes are scattered within V. fischeri’s genome (146). Secondly, the TCP genes within V. fischeri have similar GC content to the rest of its genome and lack any flanking insertion elements that are consistent with horizontal gene 21 transfer (146). This suggests that the TCP genes, including hbtRC were not recently acquired by V. fischeri via horizontal gene transfer and leave the possibility that the TCP gene cluster originated within V. fischeri (146). The second TcpP homolog within V. fischeri (VFA0860) remains uncharacterized, but a Tn seq screen designed to identify genes essential for pellicle formation in response to L-arabinose revealed that disruption of this VF_A0860 inhibits pellicle formation in V. fischeri (147). Pellicle formation in V. fischeri in the presence of L-arabinose was dependent on the cellulose polysaccharide locus (bcs) as well as motility (147). Deletion of VFA0860 did not inhibit motility of V. fischeri but did inhibit pellicle formation in the presence of L-arabinose indicating that VFA0860 may regulate genes within the bcs locus (147). In addition to ToxR and TcpP, we also Identified several ToxR-like MLTRs (VtrA/VtrB and VttrA/VttrB) that been identified and implicated in regulation of a type three secretion system (T3SS) within V. parahaemolyticus (VtrA and VtrB) and non-01/0139 V. cholerae (VttrA and VttrB) respectively (101, 102, 148, 149). V. parahaemolyticus contains two sets of gene clusters that encode type three secretion systems (T3SSI and T3SSII) and non-01/0139 V. cholerae also encode a T3SS (150–153). Within V. parahaemolyticus and non-01/0139 V. cholerae VtrA/VttrA promote transcription of vtrB/vttrB in response to bile salts, and in turn VtrB/VttrB stimulate transcription of genes within their respective T3SS (102, 154). Within V. parahaemolyticus, vtrA is co- transcribed with vtrC, a TcpH/ToxS like protein, and in the presence of bile salts, the periplasmic domains of VtrA and VtrC form a beta-barrel complex, bridged by a bile salt, to form a heterodimeric complex that stimulates oligomerization of VtrA and thereby 22 increases vtrB transcription (154, 155). Given the similarity between VtrA/VttrA, VttrA is also thought to function similarly with their associated TcpH/ToxS homolog. From our MLTR search we also found a striking number (20% of MLTRs) of CadC- like MLTRs within pathogenic and non-pathogenic Vibrio spp. (Table A.2). V. cholerae, like many gastrointestinal pathogens, must survive the acidic conditions within the stomach to reach the nutrient rich gastrointestinal tract. CadC is a MLTR that regulates acid resistance in many Gram-negative organisms (Escherichia coli, Salmonella enterica, Vibrio vulnificus, Vibrio cholerae, and Klebsiella pneumoniae) (107, 156–163). Activity of CadC is inhibited by LysP (a lysine permease) while concentrations of lysine are low, and CadC remains inactive until extracellular pH is low (~pH 5.8) which stimulates LysP proteolysis, without altering subcellular localization, thereby activating CadC (159, 164, 165). Upon activation, CadC stimulates transcription of cadAB, and this results in the conversion of intracellular lysine to cadaverine which is subsequently transported out of the cell by CadB, increasing extracellular pH (107, 166). TfoS is the only MLTR that was present in all Vibrio spp. analyzed here (Table A.2). TfoS is a MLTR that regulates natural competence within Vibrio spp. (110, 167). Natural competence is a process by which a bacterium imports exogenous DNA and incorporates the DNA into its genome via homologous recombination (168, 169). Chitin has been shown to be critical for the induction of natural competence in several Vibrio spp. (168–170). Chitin is one of the most abundant biopolymers in the ocean and is the major component of copepod exoskeletons, which serve as the environmental reservoir for many Vibrio spp. (171–175). In V. cholerae, TfoS directly binds chitin via its periplasmic domain, inducing dimerization of TfoS, which promotes transcription of tfoR 23 (110, 167). Once expressed, TfoR interferes with translational suppression of tfoX mRNA to thereby promote its translation (110). Once translated TfoX is then able to stimulate the transcription of genes required for DNA uptake (110). Of the MLTRs identified ~28% displayed no sequence similarity to known Vibrio MLTRs despite the majority possessing similar structural features to ToxR/TcpP/CadC/VttrA/VtrA (i.e., cytoplasmic DNA binding domain, single transmembrane domain, and a periplasmic domain) (Table A.2). In addition, we identified a novel multi-transmembrane domain MLTR (MT-MLTR) that encodes an AraC-like helix- turn-helix domain (Table A.2). AraC-like transcription regulators have been implicated in regulating pathways for metabolism of a variety of sugars and function primarily as transcription activators (176). Currently, there are no homologs with known functions. However, based on the presence of this MT-MLTR within pathogenic and non-pathogenic Vibrio spp. it is likely not involved in virulence gene regulation. These data indicate that the role of the MT-MLTR is likely to regulate genes important for specific environmental conditions. 2.4.2 – The Salmonella and Escherichia Genera Salmonella spp. are rod-shaped, Gram-negative, mesophiles, and facultative intracellular bacterium that can cause severe gastrointestinal disease (177, 178). Specific Salmonella spp. (such as S. enterica serovar Typhi and S. enterica serovar Typhimurium) are capable of causing typhoid fever or non-typhoidal Salmonella infections which collectively cause 106-123 million infections and 655,000-755,000 deaths per year (179, 180). Escherichia spp. are facultative anaerobic, Gram-negative, bacilli, and are natural 24 inhabitants of the intestines of humans and many warm-blooded animals (179, 180). Among Escherichia spp., E. coli is the most highly associated with human disease and is capable of causing a range of gastrointestinal diseases (179). E. coli strains capable of causing diarrheal disease are called diarrheagenic E. coli (DEC) (179, 180). The DEC pathotypes are classified as enteropathogenic E. coli (EPEC), enterohemorrhagic (Shiga toxin-producing) E. coli (EHEC/STEC), enteroaggregative E. coli (EAEC), enterotoxigenic E. coli (ETEC), and enteroinvasive E. coli (EIEC) (179). To respond to acidic conditions of the gastrointestinal tract and to promote colonization, S. enterica and E. coli both encode characterized CadC and MarT-like MLTRs (107, 165, 181–186). To determine if additional MLTRs are present within members of the Enterobacteriaceae family, we screened for MLTRs within the available genomes within the genus of Salmonella and Escherichia within the MIST database. Across 8 species, we identified a total of 35 MLTRs with only 13 MLTRs homologous to CadC or MarT. The remaining MLTRs were either uncharacterized (~46%) or were VtrB homologs (17%) (Figure 2.4 and Table A.3). Below is a summary of the current knowledge of MarT-like MLTRs within Salmonella and Escherichia spp. followed by a summary of our findings of the additional MLTRs within members of the Enterobacteriaceae. 25 Figure 2.4: Representative MLTRs identified within the Escherichia and Salmonella genera. Ovals represent protein domains identified and grey squares represent transmembrane domains. The black line represents the total coding sequence of the MLTR. See Supplemental Figure 2.2 for complete phylogenetic tree with phylogenetic information and clear view of protein domain names. Salmonella enterica serovar Typhimurium encodes three pathogenicity islands (Salmonella pathogenicity island 1-3 (SPI-1, SPI-2, SPI-3)) that contribute to its pathogenesis (187–190). SPI-1 and SPI-2 encode type III secretion systems (T3SS) that promote host cell invasion, promote systemic infection, support replication within macrophages, and induce programmed cell death of macrophages (189, 191–193). SPI- 3 does not encode a T3SS, but it has also been shown to contribute to Salmonella pathogenesis by promoting fibronectin binding, which is critical for the formation of host extracellular matrix (i.e., clot formation) (182, 190). A gene encoded within SPI-3, misL, is thought to assist gastrointestinal colonization by increasing binding to fibronectin which is at high concentrations at sites where intestinal damage/erosion has occurred (182, 194). Binding to fibronectin could thereby promote colonization of Salmonella spp. at sites of active infection/inflammation (182, 194). Secondly, during inflammation epithelial cells 26 are known to increase fibronectin secretion, and this is also correlated with enhanced Salmonella invasion (194). It was previously shown that MisL, encoded within SPI-3, is an outer membrane protein that directly binds to fibronectin (182, 194). Furthermore, it was found that MarT, a MLTR, positively regulates MisL by H-NS antagonism (181). In addition, MarT was also found to function as a general regulator of biofilm formation via an unknown mechanism (183). Within E. coli, GrvA (the Global Regulator of Virulence protein A) and YqeI are MLTRs with homology to MarT and are also important for gastrointestinal colonization of E. coli pathotypes (184, 186). EHEC also utilizes a T3SS, encoded with in the locus of enterocyte effacement (LEE), to manipulate host cells to promote proliferation, and also a second, often incomplete, T3SS encoded with in an additional pathogenicity island designated ETT2 (for E. coli type III secretion system 2) (195–200). While typically non- functional, ETT2 still contributes to the pathogenesis of several E. coli pathotypes (avian pathogenic E. coli (APEC), uropathogenic E. coli (UPEC), and EHEC). Within APEC and UPEC ETT2 was shown to be critical for motility, serum resistance, and cell adhesion (186, 199, 201, 202). GrvA indirectly promotes transcription of LEE in response to bicarbonate (184, 203). Transcription of the LEE operon is stimulated by Ler, and during low pH the glutamate-dependent acid resistance system represses ler transcription via GadE (184, 204–206). ler remains repressed until GrvA represses gadE transcription, in response to high concentrations of bicarbonate, and thereby promotes ler transcription (184, 203). Given that bicarbonate levels are highest at the surface of epithelial cells, GrvA likely 27 represses gadE, thereby stimulating ler transcription, at the surface of epithelial cells, which is also the primary site of EHEC infection (203). YqeI is encoded within the ETT2 pathogenicity island and is widely distributed among pathogenic and non-pathogenic E. coli (186, 195–199). YeqI appears to differentially regulate many genes (>580) involved in many biological pathways (such as motility, adhesion, and environmental signal transduction) in Avian pathogenic E. coli (APEC) (186). As such, YeqI was shown to be critical for systemic infection of APEC in chickens (186). This is likely due to a combination of reduced adhesion to DF-1 chicken fibroblast cells, reduced flagella synthesis, and reduced resistance to serum (186). Currently, it is unclear if YeqI is regulated by environmental signals like other MLTRs (such as ToxR and TcpP). However, downstream of YqeI is a single pass transmembrane protein, yqeJ (EC3705), whose reading frame overlaps with YqeI. Both TcpP and ToxR have associated single pass transmembrane proteins (TcpH and ToxS respectively) that function to increase stability and reduce degradation of their associated membrane- localized transcription activators (MLTRs) (83, 96, 207). The function of yqeJ remains unknown but given its association with a MLTR and domain topology it likely functions to protect or stabilize YqeI and reduce its proteolysis. Furthermore, it was recently shown that Nac (nitrogen assimilation control) transcription regulator stimulates transcription of yqeJ (185). Nac is known to play an important role in acid resistance in E. coli species (208). Taken together, it is possible that transcription of yqeJ during acidic conditions promotes YqeI function, possibly via inhibition of proteolysis. There were several VtrB-like MLTRs within Salmonella spp. (Table A.3). VtrB and VttrB are MLTRs that are known to positively regulate transcription of T3SS within Vibrio 28 spp. (101, 102, 148, 149). Salmonella enterica serovar Typhimurium utilizes two T3SS within SPI-1 and SPI-2 (189, 191–193). However, these VtrB-like homologs have not been shown to regulate T3SS within Salmonella. They are encoded either upstream or downstream of chaperone-usher type 1 fimbriae genes which members of the chaperone- usher fimbriae family which are adhesive organelles that are highly diverse among Escherichia and Salmonella spp. (Table A.3) (209). Thus, it is possible that these uncharacterized MLTRs regulate fimbriae gene transcription contributing to pathogenesis or adhesion of Salmonella cells to surfaces. None of the VtrB or uncharacterized MLTRs were found to be encoded upstream of downstream of any potential tcpH/toxS-like genes (Table A.3). This suggests that these MLTRs may not be regulated by proteolysis, or do not require an accessory protein to inhibit proteolysis like TcpP and ToxR. A majority of MLTRs identified within Salmonella and Escherichia spp. are uncharacterized. RS07670, RS12930, and RS11315 are homologs to STM1575 which was found to influence motility within Salmonella enterica serotype typhimurium (210, 211). These MLTRs are TetR type regulators which have an N-terminal DNA binding domain along with a C-terminal domain that typically binds to a ligand (212, 213). The TetR family of transcription regulators are known to regulate efflux pumps that promote antibiotic resistance they also bind to a diverse set of ligands (such as heme, biotin, amino acids, fatty acids, uracil, citric acid, nicotinic acid, etc.) (212, 213). Currently, it is unclear if RS07670, RS12930, and RS11315 do regulate motility or if they bind to any ligand. However, as RS07670, RS12930, and RS11315 are TetR regulators, the localization of their C-termini to the cytoplasmic membrane suggests that they interact with a hydrophobic ligand. 29 Secondly, a separate clade of MLTRs, RS00160, STM0031, RS01180, RS20780, and RS19320, was found to have homology to STM14_0039 which has been implicated as possible T3SS regulator upon computational analysis (214). STM0031 was found to be important for bovine enteric infection in Salmonella (215). This further suggests that these potential MLTRs contribute to Salmonella virulence and suggests that it is via regulation of T3SS. 2.4.3 – The Yersinia Genus Yersinia spp. are Gram-negative, bacilli shaped, facultative, and non-spore forming bacteria (216). Yersinia spp. are known to be the etiological agent of the bubonic plague (i.e., Yersinia pestis) and can also cause self-limiting gastrointestinal disease (i.e., Yersinia enterocolitica) (216). In addition, Yersinia ruckeri is a zoonotic pathogen that primarily infects fish and is the cause of enteric red mouth disease in salmon species (217–219). Within the Yersinia genus there have only been two MLTRs identified PsaE and PypB which have been shown to regulate fimbriae and a type IVb pilin respectively (220–225). Our analysis revealed a total of 14 MLTRs within Y. pestis, Y. enterocolitica, and Y. ruckeri with ~36% of the identified MLTRs bearing similarity to PsaE or PypB ( Figure 2.5 and Table A.4). 30 Figure 2.5: Representative MLTRs identified within the Yersinia genus. Ovals represent protein domains identified and grey squares represent transmembrane domains. The black line represents the total coding sequence of the MLTR. See Supplemental Figure 2.3 for complete phylogenetic tree with phylogenetic information and for a clear view of protein domain names. Within Y. pestis, the psa locus encodes genes that are critical for the pathogenesis of Y. pestis (226). PsaA, the major subunit of the fimbriae, is positively regulated by high temperature as well as acidic pH, and has been shown to promote host cell adherence and inhibit phagocytosis (222, 225, 227–229). psaA is regulated directly by PsaE and indirectly by PsaF (222, 230). PsaE is a MLTR, similar to ToxR and TcpP, and functions to stimulate psaA transcription from the cytoplasmic membrane (222, 224). PsaF is important for stability of PsaE and may also enhance the ability of PsaE to stimulate PsaA transcription (221, 230). Levels of both PsaE and PsaF are regulated by temperature and pH. psaE mRNA encodes an RNA thermometer within its 5’ untranslated region (UTR) which at high temperature (such as 37℃) stabilizes (230). Translation of psaF mRNA also requires high temperature but is independent of the psaE 5’ UTR (221). The exact mechanism of temperature regulation of psaF translation remains unclear (221). Similar 31 to ToxR and TcpP, pH post-translationally regulates levels of PsaE and PsaF (230). Recently, PsaF was shown to sense pH via histidine residues within its periplasmic domain which in turn modulate its ability to protect PsaE from degradation (221). The precise mechanism by which pH influences PsaF function is not known, but it is thought that pH influences the overall structure of PsaF via its periplasmic histidine residues (230). Similar to other enteric pathogens Y. enterocolitica must adhere to host cells to cause disease. Y. enterocolitica relies on Myf, a fimbriae similar to CS3 within enterotoxigenic E. coli (231, 232). MyfA, the major Myf subunit, is a homolog of PsaA, and is also positively regulated by high temperature and low pH (231). Similar to psaA, myfA also appears to be regulated by a MLTR and its associated protein, MyfEF (233). MyfE and MyfF appear to be homologs of PsaE and PsaF respectively. As anticipated, we identified both PsaE (YPO_1301) and MyfE (YE1450) within Y. pestis and Y. enterocolitica (Table A.4). Y. ruckeri is not known to encode pili similar to PsaA or MyfA. However, genome analysis of Y. ruckeri revealed that it encodes a fimbriae gene cluster (the stf operon) that is associated with differences in host range and virulence within S. typhimurium (234, 235). Upstream of the stf operon within Y. ruckeri is a MLTR (RS16705) that is a homolog of MarT (Table A.4). Currently, it is unclear if RS16705 regulates the stf operon in Y. ruckeri but given its proximity to the stf operon it remains a possibility. In addition, several CadC-like MLTRs were identified within Y. pestis, Y. enterocolitica and Y. ruckeri (Table A.4). Of note, RS06955, YPO0804, and YPO0804 are not located upstream or downstream of cadAB, which are known to be associated with 32 cadC. To the best of our knowledge, CadC-like MLTRs have not been characterized within Yersinia spp., but based on homology we anticipate that CadC coordinates acid resistance within Yersinia spp. Early studies on virulence within Y.pestis and Y. enterocolitica led to the discovery of a large virulence plasmid that encoded a T3SS (the Ysc system) that was critical to virulence of Y. pestis and Y. enterocolitica (236). Highly virulent strains of Y. enterocolitica biovar 1B were found to encode a second chromosomally encoded T3SS (Ysa) that contributed to its virulence that is similar to the T3SS found within the SPI-1 within Salmonella spp. (236–238). Genomic analysis of Y. ruckeri revealed that it also encodes the ysa system, and within the ysa system a MLTR (RS13670), bearing homology to PypB, is encoded (239). RS13670 shares sequence similarity to PypB which is a MLTR that has not been reported to regulate genes within the ysa locus (220). PypB (YE3623) is a MLTR that stimulates transcription of the tad (tight adherence) operon within Y. enterocolitica that encodes a Flp type IVb pillin which have been shown to promote microcolony formation, potent biofilms, and to possess promiscuous binding specificity for surfaces (220). Y. ruckeri encodes a second homolog of PypB (RS07490) that is encoded upstream of the tad operon in Y. ruckeri. In addition to homologs of known MLTRs, we also identified several uncharacterized MLTRs with striking similarity to VtrB/PypB but lack sufficient sequence similarity to any characterized transcription factors (Table A.4). Perhaps the most interesting of the uncharacterized MLTRs is YE0935 (an AraC MT-MLTR) which is also found within the Vibrio genus. The role of this MT-MLTR remains obscure. 33 2.4.4 – The Enterococcus and Lactobacillus genera Lactic acid bacteria (LAB) are strictly fermentative, aerotolerant, acid tolerant, organotrophs that produce lactic acid as a major metabolic byproduct of glucose (240, 241). LAB utilize a large array of carbohydrates to gain energy which results in the production of lactic acid, in addition to other byproducts (240, 241). Members of the Enterococcus and Lactobacillus genera are LAB. Enterococci are mesophilic non-spore forming Gram-positive ovoid shaped bacterium that grow in pairs or associate in chains (240). Enterococci cells are also resistant to desiccation and facultative anaerobes (240). Lactobacilli are Gram-positive fermentative anaerobic non-spore forming bacteria that have complex nutritional requirements (240). Members of the Lactobacilli and Enterococci genera are known to colonize the human gastrointestinal tract and are capable of causing severe disease (240). Only a handful of MLTRs have been identified and characterized within Enterococci and Lactobacilli spp. (such as BcrR, BreG, and AguR (106, 242, 243). Using the MIST database, we identified 171 potential MLTRs within Enterococci and Lactobacilli spp. (105 MLTRs and 66 MLTRs respectively) (Figure 2.6, Table A.5, and Table A.6). Surprisingly, BcrR, BreG, and AguR made up only ~16% of identified MLTRs within Enterococci spp. and Lactobacilli spp. (Table A.5 and Table A.6). Homologs of previously identified MLTRs were found within Enterococci and Lactobacilli (i.e., MtbS, MmsR, LP_2991 and HcrR) encompassing ~14.6% of identified MLTRs (Table A.5 and Table A.6). The majority of MLTRs identified within Enterococci and Lactobacilli are uncharacterized (~68%) (Table A.5 and Table A.6). Below is a summary of the current literature surrounding characterized MLTRs within Enterococci and Lactobacilli along with a summary of our findings regarding the uncharacterized MLTRs. 34 Figure 2.6: Representative MLTRs identified within the Enterococcus and Lactobacillus genera. Ovals represent protein domains identified and grey squares represent transmembrane domains. The black line represents the total coding 35 Figure 2.6 (cont’d) sequence of the MLTR. See Supplemental Figure 2.4 for complete phylogenetic tree and for a clear view of protein domain names. Enterococcus faecalis is a human pathogen commonly associated with nosocomial infections and is commonly found to be resistant to multiple antibiotics, such as vancomycin (244). Bacitracin is a common topical antimicrobial, and it is also used to treat vancomycin resistant E. faecalis (245). Bacitracin resistance in E. faecalis and Clostridium perfringens is regulated by BcrR a MLTR (106, 246). BcrR stimulates transcription of the bcrABD operon upon binding to bacitracin and requires membrane localization to function (106, 247, 248). bcrA and bcrB encode the ATP-binding domain and the membrane spanning domain of the bacitracin ABC transporter (249). It has been shown that the bcrABD, bcrR, and other genes involved in antibiotic resistance are transmitted between Enterococcus spp. via pheromone responsive conjugative plasmids(250–252). Our analysis indicates that BcrR is also present in Lactobacillus spp. (Table A.5 and Table A.6). Similar to BcrR, BreG is a multi-transmembrane domain MLTR that also regulates synthesis of an antibacterial compound and is also encoded within a plasmid (242, 253). LAB are known to use bacteriocins (antibacterial polypeptides) to compete for carbohydrates by inhibiting growth of competing bacteria (242, 254, 255). Lactobacillus brevis is a plant-associated LAB that produces two bacteriocins (174A-β and 174A-γ) (242). Synthesis of 174A-β and 174A-γ in L. brevis is catalyzed by breBC which are encoded within a large plasmid (242, 253). breBC are upregulated by BreG, an MLTR with four C-terminal transmembrane domains (242, 253). However, it remains unclear what stimulates BreG activity and BreG transcription in L. brevis. 36 A common feature among LAB is their ability to tolerate acidic conditions, which is necessary given the nature of their metabolism (240). One method of acid resistance employed by Enterococci and Lactobacilli is the agmatine deiminase system. Within this system, agmatine is imported into the cell via AguD, an agmatine-putrescine antiporter, and agmatine is then broken down into putrescine and carbamoyl phosphate by AguAB, and finally AguC removes a phosphate from carbamoyl phosphate generating ATP, CO 2, and NH3 (256, 257). AguR stimulates transcription of aguBDAC in response to agmatine within Enterococcus faecalis (243). Within Lactococcus lactis and Streptococcus mutans AguR stimulates aguBDAC transcription in response to both agmatine and low pH (257– 259). The current literature suggests that within S. mutans, AguR and AguD function similar to CadC and LysP, where AguR and AguD interact in the absence of agmatine inhibiting transcription of the aguBDAC gene cluster (257). Micro-array data indicate that the AguR regulon is much larger than previously anticipated. Deletion of aguR resulted in downregulation of 49 genes and upregulation of 41 genes indicating that AguR may have additional regulatory functions (260). Lactobacilli are known constituents of the human gastrointestinal tract and have been shown to have immunomodulatory roles. L. plantarum is a well-studied immunomodulatory Lactobacilli that has been used as a probiotic to treat irritable bowel disease, inflammatory bowel disease, and with some success treating allergies (261– 265). L. plantarum has been shown to promote expansion of regulatory dendritic cells, promote transcription of anti-inflammatory cytokine IL-10, and promote the expansion of regulatory T-cells (266–270). Characterization of genes important for L. plantarum immunomodulatory effects revealed that the LamBDCA quorum sensing system, 37 plantaricin (i.e., bacteriocin) synthesis and its transport, a transcription regulator lp_2291, and the N-acetyl-glucosamine/galactosamine phosphotransferase system are critical for L. plantarum’s immunomodulatory effects (114, 267). A prior study identified lp_2291 (an MLTR) as a gene involved in modulating pro-inflammatory cytokine production in dendritic cells (114). It was found that lp_2291 represses gctA3, a putative teichoic acid and lipoteichoic acid glycosylation enzyme (114). Modification of lipoteichoic acid (LTA), such as with D-alanyl, has been shown to have effects on cytokine production, and lack of modification of LTA with D-alanyl increases IL-10 secretion (271). These data indicate that lp_2991 reduces inflammation by repressing gctA3 thereby reducing the pro- inflammatory nature of its LTA. Currently it is unclear what influences lp_2991 to repress or derepress gctA3 transcription. Our analysis revealed that some Enterococcus and Lactobacillus spp. encode MtbS homologs (Table A.5 and Table A.6). MtbS is an MLTR recently identified in Staphylococcus aureus that has a cryptic role as it promotes soft tissue infection but inhibits skin infection (272). Given that MtbS is not conserved among Enterococcus and Lactobacillus spp., this suggests that MtbS was acquired individually by these bacteria, likely by horizontal gene transfer. Of note, Enterococcus phoeniculicola was found to encode four MtbS homologs (Table A.5). E. phoeniculicola was isolated from the uropygial gland (preen gland) of the Red-billed Wood hoopoe, Phoeniculus purpureus, which secretes oils that protect it from bacterial pathogens and predators (273–276). The preen gland is primarily used for maintenance of feathers, waterproofing, and secreting predator deterring odors (274, 277, 278). Antibiotic treatment altered the secretions from the preen gland indicating that bacteria within the preen gland modified the secreted oils 38 which inhibited bacterial growth (273). E. pheniculicola is implicated in modifying the preen gland secretions (273). In addition to the four MtbS-like MLTRs, E. pheniculicola has an additional eight MLTRs within its genome (Table A.5). The role of these MLTRs remains unclear. However, given that the preen gland is known to secrete hydrophobic chemicals (i.e., mono and diester waxes, squalene, and alcohols) it is possible that MLTRs are uniquely positioned to sense and respond to the presence of these hydrophobic compounds (277, 278). Two unique Lactobacilli MLTRs, RS06015 and RS09530, were found to be homologs of HcrR and MmsR respectively (Table A.6). HcrR is known to positively regulate hcrAB which catalyze the metabolism of hydroxycinnamic acids which are abundant in plants and are utilized by L. planetarium (111, 279). MmsR is a regulator of isobutyryl-CoA metabolism in Pseudomonas aeruginosa and Pseudomonas putida (112). Metabolism of isobutyryl-CoA occurs via methylmalonate semialdehyde dehydrogenase (MmsA) RS09530 and 3-hydroxyisobutyrate dehydrogenase (MmsB) producing propionyl-CoA and CO2 (112). mmsA and mmsB are encoded downstream of MmsR, an AraC-type family of regulator, which stimulates transcription of mmsAB but the conditions that promote MmsR function are unknown (112). Both Enterococci and Lactobacilli spp. were found to encode MLTRs that are associated with plasmids (Table A.5 and Table A.6). LMIV_p072 and HA1_16002 are predicted MLTRs that have been shown to be encoded within plasmids pLMIV and pF262C respectively (280–282). pLMIV is a Listeria-associated plasmid and pF262C is associated with Clostridium perfringens (280–282). pLMIV has also been incorporated into the genome of pathogenic Listeria within hypervariable hotspot 9 (282). However, 39 neither pLMIV nor pF262C have been shown to have a clear role in virulence for Listeria spp. or Clostridium perfringens. Thus, it is possible that these plasmid-associated MLTRs may have a role in promoting environmental persistence or proliferation. 2.4.5 – The Staphylococcus genus Staphylococcus spp. are Gram-positive, non-motile, non-spore forming, catalase- positive, cocci, and are facultative anaerobic (283). Staphylococcus spp. are natural commensal members of human skin, skin glands, and mucous membranes of humans, other mammals, and birds (283). Staphylococcus aureus is a highly studied member of the Staphylococcus genus as it is an opportunistic pathogen commonly associated with skin infection, sepsis, endocarditis, osteomyelitis, and necrotizing fasciitis in humans (113). S. aureus employs a large number of virulence factors and regulatory proteins to cause disease (see review for more information: (284)). Recently, an MLTR, MbtS, was shown in S. aureus to contribute to its pathogenesis via an unknown mechanism (285). In addition, MbtS was also found to be sensitive to degradation by a membrane bound metalloprotease (FtsH) (285). FtsH degrades cytoplasmic membrane proteins that are denatured or loosely folded and is critical for survival of S. aureus cells undergoing cellular stress (286, 287). FtsH has been shown to be critical for virulence of S. aureus (288). However, FtsH does not directly regulate transcription of virulence factors. Complementation of ΔftsH with mbtS does not restore virulence of S. aureus in a sepsis model or systemic infection (285). Thus, MbtS likely requires FtsH to be liberated from the cytoplasmic membrane to complete its regulatory duties. MbtS also likely functions as a transcription activator and repressor. Loss of mbtS lead to a decrease in transcription of 9 genes (such as phosphate transport genes, glycine dehydrogenase, 40 aminomethyltransferase, and several tRNAs) and an increase in transcription of 8 genes (such as Staphopain A, serine proteases SplA-F, and glycyl-tRNA synthase genes) (285). MbtS potentially regulates many more genes (<200), but to a much lower degree (i.e., 1.4-fold difference) (285). MbtS was found to autoregulate, and this is dependent on FtsH (285). Currently, it is unknown if MbtS recognizes any host or environmental factors to influence its transcription regulation activity. MbtS does not have any known associated protein, like ToxS, TcpH, or PsaF, to inhibit its proteolysis. MbtS is a unique MLTR as it contains three transmembrane domains and virtually no extracellular domain. Given that FtsH is needed for complete MtbS activity, it is possible that MtbS is activated via proteolysis by FtsH and that the biophysical properties of the cytoplasmic membrane affect MtbS sensitivity to FtsH. A second MLTR, NanR, has also been described within S. aureus and was found to regulate sialic acid (N-acetylneuraminic acid) metabolism by repressing nanERKAT until it binds sialic acid (113). Upon screening for MLTRs within the Staphylococcus genus we found that only ~23% of all MLTRs identified were homologs of MtbS or NanR (Figure 2.7 and Table A.7). Many of the uncharacterized MLTRs have no associated TcpH/ToxS like genes (Table A.7). RS01135, RS03175, and RS07860 were found to be associated with CAAX Proteases and Bacteriocin-Processing (CPBP) metalloproteases (Table A.7). CPBP metalloproteases are spread throughout all domains of life and thought to be involved in bacteriocin maturation (289). CPBP metalloproteases cleave C-terminal tripeptide ‘AAX’ from target proteins (290). It is thought that CPBP metalloproteases promote secretion of bacteriocins or possibly degrade bacteriocins (289). Several CPBP metalloproteases were found within bacteriocin operons and have been shown to confer immunity to 41 bacteriocins in L. planetarium and L. lactobacillus (291–293). Currently, there is no data to suggest that RS01135, RS03175, and RS07860 are involved in regulating bacteriocin biosynthesis. Figure 2.7: Representative Staphylococcus MLTRs identified. Ovals represent protein domains identified and grey squares represent transmembrane domains. The black line represents the total coding sequence of the MLTR. See Supplemental Figure 2.5 for complete phylogenetic tree with phylogenetic information and for a clear view of protein domain names. 42 2.5 – Discussion Here we investigated the prevalence of MLTRs and reviewed the current knowledge of MLTRs within Prokaryotes. We focused our analysis on species closely related to bacteria with previously characterized MLTRs. We found that MLTRs are widespread among Gram-negative and Gram-positive bacteria and that their domain structure is highly diverse. Our analysis revealed that MLTRs within Gram-negatives are more likely to be associated with TcpH- and ToxS-like proteins than MLTRs within Gram- positive bacteria. Surprisingly, Gram-positives appear to be enriched for MLTRs with multiple transmembrane domains. It is currently unclear as to why MLTRs within Gram- positive bacteria are more likely to have multiple transmembrane domains. From our work, and prior work, it is clear that MLTRs can be acquired from horizontal gene transfer, with many MLTRs within Gram-positives associating with plasmids. MLTRs do not appear to have a common regulon. A survey of the literature indicates that MLTRs can influence metabolism, motility, biofilm formation, antibiotic resistance, acid resistance, natural competence, and the human inflammatory response (52, 71, 101–114). Nonetheless, from the work presented here MLTRs within Gram-positive and Gram-negative bacteria are clearly associated with regulating pilin, fimbriae, or T3SS. It remains unclear if this association is due to the fact that pathogenic bacteria are studied more intensely than environmental bacteria, or if this is a trend that is common among all bacteria. Further work is required to understand this. A major remaining question regarding MLTRs is: why are they localized to the cytoplasmic membrane? Several possibilities exist such as, MLTRs respond to a hydrophobic ligand, their ligand cannot penetrate the cytoplasmic membrane, a 43 membrane-localized cofactor is required for activity, and MLTRs respond to the cytoplasmic membrane itself (i.e., membrane fluidity, lipid domains, or specific phospholipids influence activity). From our targeted analysis it is clear that the vast majority of MLTRs are uncharacterized and underscores the lack of knowledge we have regarding MLTRs. This work demonstrates the diversity of domain architecture among MLTRs and also reveals distinct differences among MLTR structure within Gram-negative and Gram-positive bacteria. 44 Chapter 3 – Independent Promoter Recognition by TcpP Precedes Cooperative Promoter Activation by TcpP and ToxR 45 3.1 – Preface Contents of this chapter were published in the journal mBio in 2021 (Citation: Calkins AL, Demey LM, Karslake JD, Donarski ED, Biteen JS, DiRita VJ. Independent Promoter Recognition by TcpP Precedes Cooperative Promoter Activation by TcpP and ToxR. mBio. 2021 Oct 26;12(5):e0221321. doi: 10.1128/mBio.02213-21. Epub 2021 Sep 7. PMID: 34488449.). Per American Society for Microbiology guidelines “An ASM author also retains the right to reuse the full article in his/her dissertation or thesis.”. 3.2 – Abstract Cholera is a diarrheal disease caused by the Gram-negative bacterium Vibrio cholerae. To reach the surface of intestinal epithelial cells, proliferate, and cause disease, V. cholerae tightly regulates the production of virulence factors such as cholera toxin (ctxAB) and the toxin co-regulated pilus (tcpA-F). ToxT is directly responsible for regulating these major virulence factors while TcpP and ToxR indirectly regulate virulence factor production by stimulating toxT transcription. TcpP and ToxR are membrane- localized transcription regulators (MLTRs) required to activate toxT transcription. To gain a deeper understanding of how MLTRs identify promoter DNA while in the membrane, we tracked the dynamics of single TcpP-PAmCherry molecules in live cells using photoactivated localization microscopy and identified heterogeneous diffusion patterns. Our results provide evidence that: 1) TcpP exists in three biophysical states (fast diffusion, intermediate diffusion, and slow diffusion); 2) TcpP transitions between these different diffusion states; 3) TcpP molecules in the slow diffusion state are interacting with the toxT promoter; and 4) ToxR is not essential for TcpP to localize the toxT promoter. These data 46 refine the current model of cooperativity between TcpP and ToxR in stimulating toxT transcription and demonstrate that TcpP locates the toxT promoter independent of ToxR. 3.3 – Introduction The Gram-negative bacterium Vibrio cholerae infects millions of people each year, causing the diarrheal disease cholera resulting in ~100,000 deaths annually (294, 295), despite treatments available to combat infection, including vaccines, antibiotic therapy, and oral rehydration therapy (7–9, 296–300). With changing climate and growing cases of antibiotic resistant V. cholerae, the number of annual cholera infections is projected to continue to increase (15). Thus, gaining deeper insight into the pathogenesis of V. cholerae will facilitate development of alternative methods of treatment, thereby reducing the global burden of cholera. Upon ingestion, typically from contaminated water or food, V. cholerae colonizes the crypts of the villi in the distal portion of the small intestine and stimulates production of virulence factors essential for disease progression, such as the toxin co-regulated pilus and cholera toxin (TCP and CtxAB, respectively) (22–25, 31, 301). Transcription of tcp and ctxAB is directly activated by ToxT (39–42). Transcription of toxT is highly regulated and positively stimulated by ToxR and TcpP, two MLTRs, which directly bind to the toxT promoter (toxTpro), with binding sites at −104 to −68 and −55 to −37, respectively (39, 52–55, 70, 71, 82). TcpP and ToxR are bitopic membrane proteins, each containing a cytoplasmic DNA-binding domain (within the PhoB and OmpR families respectively), a single transmembrane domain, and a periplasmic domain (69). ToxR appears to have an accessory role in toxT regulation. Evidence supporting the model that ToxR assists TcpP to toxT transcription includes: 1) TcpP binds downstream of ToxR, closer than ToxR to 47 the putative RNA polymerase binding site on toxTpro; and 2) overexpression of TcpP results in ToxR-independent toxT transcription activation (39, 55, 70, 71). Furthermore, we have previously measured the single-molecule dynamics of TcpP and noted that deletion of toxR decreases but does not eliminate the prevalence of TcpP-DNA binding events (302). However, it remains unclear how TcpP and ToxR identify the toxTpro from the cytoplasmic membrane. Signal transduction pathways in prokaryotes consist of one-component and two- component regulatory systems that manage cellular processes in response to extracellular information such as pH, temperature, chemical gradients, and nutrients (88, 89, 303). One-component regulatory systems combine their input and output functions in a single protein. MLTRs are a unique family of one-component regulators as they function from the cytoplasmic membrane, whereas the majority (~97%) of one-component regulators are localized in the cytoplasm (89). These one-component MLTRs like TcpP and ToxR comprise a sensor domain and an output domain that are separated by a transmembrane domain. MLTRs have been experimentally characterized in other, Gram- positive and Gram-negative, pathogenic bacteria and have been shown to regulate genes important for pathogenesis (such as capsule production, acid tolerance, antibiotic resistance, virulence gene regulation, and natural competence) (107, 110, 181, 190, 249, 285, 304–307). Using the Microbial Signal Transduction Database (MIST), we collected candidate MLTRs from 20 bacterial species and found that the prevalence and diversity of MLTRs is much higher than previously anticipated (Figure C.1). This data indicates that MLTRs are more common among bacteria than previously appreciated. Yet, it remains unclear how MLTRs identify specific promoter(s) while localized to the 48 cytoplasmic membrane. Some challenges emerge in understanding how MLTRs affect their function of activating transcription in response to external stimuli. For example, diffusion of these regulators is constrained to the cytoplasmic membrane. Additionally, the chromosome structure, which is not static, is known to influence association of a MLTR to its target sequence (308–317). How MLTRs locate their target sequences while bound to the membrane represents a major gap in our knowledge. Here, we investigated the subcellular single-molecule dynamics of TcpP-PAmCherry to understand how TcpP localizes to the toxTpro and to develop a general model for how MLTRs identify their DNA targets. Our approach was to apply super-resolution single-molecule tracking (SMT) in living cells. Previous work demonstrated that TcpP molecules exhibit heterogeneous diffusion patterns (302, 318). Here, we expand upon this earlier work to study the effect of specific mutations, that alter TcpP binding to DNA or the potential association of TcpP with ToxR, on TcpP subcellular mobility. By tracking the movement of TcpP-PAmCherry molecules within single living V. cholerae cells, we determined the distributions of the heterogeneous motions of TcpP and detected changes in these diffusion coefficients in response to targeted genetic alterations. From this data, we identify three biophysical states (fast diffusion, intermediate diffusion, and slow diffusion), we propose a biological role corresponding to each state, and we suggest an alternative model of toxT activation where TcpP independently identifies the toxTpro prior to assistance from ToxR. 49 3.4 – Materials and Methods 3.4.1 – Bacterial strains and growth conditions Escherichia coli and V. cholerae strains used here can be found in Table B.1. Unless otherwise stated, E. coli and V. cholerae cells were grown on Lysogeny Broth (LB) plates, or in LB broth at 210 rpm, at 37˚C. LB was prepared according to previous descriptions (319). To stimulate virulence, V. cholerae cells were diluted from overnight cultures in LB broth and subcultured into virulence-inducing conditions: (LB pH 6.5, 110 rpm, 30 ˚C; filter sterilized). Here, the LB pH was adjusted by adding HCl (1 N) to pH 6.5 (+/- 0.05) and then the media was filter-sterilized to maintain pH. Where appropriate, antibiotics and cell wall intermediates were added at the following concentrations: streptomycin (100 µg ml−1), ampicillin (100 µg ml−1), and diaminopimelic acid (DAP) (300 µM). 3.4.2 – Plasmid construction Plasmid vectors were purified using the Qiagen mini prep kit. Plasmid inserts were amplified from V. cholerae genomic DNA using Phusion high-fidelity polymerase (Thermo Scientific). Splicing by overlap extension was used to combine the entire plasmid insert sequences together (Table B.2). Plasmid vector was digested by restriction digestion using KpnI-HiFi and XbaI (New England BioLabs) at 37˚C for 2 hrs. After digestion the plasmid vector and insert were added to Gibson assembly master mix (1.5 µl insert, 0.5 µl vector, 2 µl master mix) (New England BioLabs) and incubated at 50˚C for 1 hr. Assembled plasmid was electroporated into E. coli λpir cells and recovered on LB plates with ampicillin and DAP. 50 3.4.3 – Bacterial strain construction Strain construction follows the protocol outlined in reference (320). Briefly, E. coli λpir harboring the pKAS plasmid and the donor V. cholerae strain were incubated in LB (broth or agar) supplemented with DAP overnight at 37˚C. The remaining cells were then spread on LB plates containing ampicillin or TCBS plates containing ampicillin. Counter selection for loss of the pKAS construct by V. cholerae cells was done by incubating cells in LB broth for 2 hrs and then for 2 hrs with 2500 µg ml−1 streptomycin (both at 37 ˚C, 210 rpm). 20 µl of this culture was spread onto LB plates containing 2500 µg ml−1 of streptomycin and incubated overnight at 37 ˚C. Streptomycin-resistant colonies were screened for the chromosomal mutation of interest via colony polymerase chain reaction (PCR) using Taq DNA Polymerases (Thermo Fisher). Genomic DNA was purified from possible mutants and sequenced (Genewiz) to validate the exchange. Because tcpP and tcpH are encoded by on overlapping open reading frames, tcpH was cloned downstream of PAmCherry to maintain its transcription, and a stop codon was introduced within the first three codons of the native tcpH coding sequence to prevent out-of-frame translation of PAmCherry. 3.4.4 – Growth Curves V. cholerae strains were initially grown on LB plates containing streptomycin (100 µg ml−1) overnight at 37˚C, then an individual colony was picked and grown overnight in LB broth at 37˚C. V. cholerae cells were diluted to an optical density (OD600) of 0.01 from the overnight LB broth into a 96 well plate (Cell Pro) with 200 ul of virulence-inducing 51 media per well. The plate was then incubated at 30˚C with shaking every 30 min before each measurement in a SPECTROstar Omega plate reader (BMG LABTECH). 3.4.5 – Real-time quantitative PCR (RT-qPCR) RNA was extracted from V. cholerae cells grown under virulence-inducing conditions. RNA was preserved by resuspending pellet cells in 1 ml Trizol (Sigma aldrich) and then purified using an RNeasy kit (Qiagen). RNA was further purified with Turbo DNase treatment. RNA quantity and quality were measured via UV-Vis spectrophotometry (NanoDrop ND-1000) and by detection of large and small ribosomal subunits via 2% agarose gel. RNA was then converted to cDNA using Superscript III reverse transcriptase (Thermo Scientific). RT-qPCR was performed using 5 ng of cDNA in SYBR green master mix (Applied Biosystems). RecA was used as a housekeeping gene of reference to calculate the threshold values (ΔΔCT) (321, 322). See Table B.2 for primers. 3.4.6 – Protein electrophoresis and immunodetection After lysis, total protein concentration samples were measured via Bradford assay. Samples were subsequently diluted to 0.5 µg total protein/µl. All SDS page gels contained 12.5 % acrylamide and were run at 90 – 120 volts for 1.5 hrs. Proteins were transferred to nitrocellulose membranes using a semi-dry electroblotter (Fisher Scientific) overnight at 35 mA or for 2 hrs at 200mA. Membranes were blocked with 5 % non-fat milk, 2 % bovine serum albumin in Tris-buffered saline, 0.5 % Tween-20 (TBST) for 1 hr. Membranes were then incubated with primary antibody (α-TcpA 1:100,000; α-TcpP 52 1:1,000; α-TcpH 1:500; α-ToxR 1:50,000; α-mCherry 1:1,000) diluted in TBST and non- fat Milk (2.5 % w/vol) for an additional hour at room temp with shaking. Membranes were then washed 3 times with TBST. Secondary antibody (Goat anti-Rabbit IgG-HRP 1:2,000) (Sigma) was diluted in TBST and non-fat milk (2.5 % w/vol). Secondary antibody was incubated with the membranes for an additional hour at room temperature with shaking. Membranes were washed again with TBST 3 times and then incubated with SuperSignal HRP Chemiluminescence substrate (Thermo Fisher). Membranes were imaged with an Amersham Imager 600. 3.4.7 – Single-Molecule Microscopy V. cholerae strains were grown on LB plates containing streptomycin (100 µg ml−1) overnight at 37 ˚C, then an individual colony was picked and grown overnight in LB broth at 37 ˚C. V. cholerae cells were diluted from LB broth into virulence-inducing conditions and grown until they reached mid log-phase. They were then washed and concentrated in M9 minimal media with 0.4 % glycerol. A 1.5 μl droplet of concentrated cells was placed onto an agarose pad (2 % agarose in M9, spread and flattened on a microscope slide) and covered with a coverslip. Cells were imaged at room temperature using an Olympus IX71 inverted epifluorescence microscope with a 100x 1.40 NA oil-immersion objective, a 405-nm laser (Coherent Cube 405-100; 50 W/cm2) for photoactivation and a co-aligned 561-nm laser (Coherent-Sapphire 561-50; 210 W/cm2) for fluorescence excitation. Fluorescence emission was filtered with appropriate filters and captured on a 512 by 512 pixel Photometrics Evolve EMCCD camera. To prevent higher-order excitation during photoactivation, a pair of Uniblitz shutters controlled the laser beams such that samples 53 were exposed to only one laser at a time. During imaging, the cells were given a 40-ms dose of 405-nm light every 90 s. Images were collected continuously every 40 ms and acquisitions lasted 5 – 7 min each. 3.4.8 – Data Analysis Recorded single-molecule positions were detected and localized based on point spread function fitting using home-built code, SMALL-LABS (323). This program reduces biases due to background subtraction, increasing the precision of each molecule localization. Subsequent localizations of the same molecule were then connected into trajectories using the Hungarian algorithm (323–325). All trajectories from each movie for a given condition were combined and analyzed together using the Single-Molecule Analysis by Unsupervised Gibbs sampling (SMAUG) algorithm (318). This algorithm considers the collection of steps in all trajectories and uses a Bayesian statistical framework to estimate the parameters of interest: number of mobility states, diffusion coefficient, weight fraction, transition probabilities between states, and noise. 3.5 – Results 3.5.1 – Single-molecule tracking of TcpP-PAmCherry is useful to study promoter identification, but cannot probe regulated-intramembrane proteolysis To investigate the dynamics of individual TcpP molecules, we generated a V. cholerae strain in which the wild type tcpP allele is replaced with one expressing TcpP fused at its C-terminus to a photoactivatable fluorescent protein, PAmCherry (tcpP- PAmCherry). Levels and activity of TcpP are controlled by a two-step proteolytic process 54 known as regulated intramembrane proteolysis (RIP) (56, 58, 59). Under RIP-permissive conditions (defined as LB pH 8.5, 37˚C, shaking at 210rpm) the C-terminus of TcpP becomes sensitive to proteolysis by Tsp, a site-1 protease, and YaeL, a site-2 protease; this sensitivity results in the inability of the cell to activate toxT transcription. Under RIP non-permissive conditions (defined as LB pH 6.5, 30˚C, shaking at 110rpm), TcpP is protected from RIP by TcpH (56, 58, 59). We investigated whether we could assess RIP dynamics using single-molecule tracking. Like wild-type TcpP, TcpP-PAmCherry was sensitive to RIP in the absence of TcpH, indicated by lower levels of TcpP-PAmCherry in tcpP-PAmCherryΔtcpH relative to tcpP-PAmCherry (Figure C.2A). Secondly, in both tcpP-PAmCherry and tcpP- PAmCherryΔtcpH a smaller species of TcpP-PAmCherry was observed, referred to as TcpP-PAm* (Figure C.2A). A similar result has been observed for native TcpP in ΔyaeL cells and indicates RIP (59). Complementation of tcpP-PAmCherryΔtcpH with plasmid- encoded tcpH resulted in a band with the mass of native TcpP (~29KDa), (Figure C.3). These data indicate that TcpP-PAmCherry resists RIP in a TcpH-dependent fashion similar to native TcpP. As expected, native TcpP was not detected in the absence of TcpH. These data indicate that: 1) TcpP-PAmCherry is sensitive to RIP; 2) TcpH can protect TcpP-PAmCherry from RIP; and 3) addition of PAmCherry to the C-terminus of TcpP reduces RIP of TcpP-PAmCherry relative to TcpP. These conclusions are supported by similar levels of TcpA, CtxB, and toxT transcription in tcpP-PAmCherry and tcpP-PAmCherryΔtcpH (318); (Figures C.2A and Figure C.4). Notwithstanding the detectable levels of TcpP-PAmCherry on immunoblots of total proteins from tcpP- PAmCherryΔtcpH, we observed almost no TcpP-PAmCherry molecules in our single- 55 molecule tracking experiments. As a result, we are unable to collect sufficient data to perform any analysis of tcpP-PAmCherryΔtcpH cells. Though we cannot determine how RIP influences TcpP-PAmCherry single-molecule dynamics, fusion of PAmCherry to the C-terminus of TcpP does not affect its ability to stimulate toxT transcription (Figure C.4). In addition, activity of TcpP is influenced by homodimerization, mediated by a periplasmic cysteine residue (C207) (77, 78). We sought to determine if addition of PAmCherry to the C-terminus of TcpP promotes its ability to dimerize. To test this, we measured toxT transcription in both tcpP-PAmCherry and tcpPC207S-PAmCherry cells (Figure C.5). We found that PAmCherry does not compensate for loss of C207, suggesting that it does not stimulate dimerization of TcpP-PAmCherry. This data indicates that PAmCherry does not simulate dimerization of TcpP-PAmCherry. Lastly, addition of PAmCherry to the C- terminus of TcpP does not affect the growth rate of V. cholerae (Figure C.6). Therefore, TcpP-PAmCherry is an effective tool to understand how TcpP locates the toxTpro from its position in the membrane. 3.5.2 – Baseline Dynamics of TcpP-PAmCherry Single-Molecule Analysis by Unsupervised Gibbs sampling (SMAUG) characterizes the motion of molecules based on the collection of measured displacements (steps) in their single-molecule trajectories. SMAUG estimates the biophysical descriptors of a system by embedding a Gibbs sampler in a Markov Chain Monte Carlo framework. This non-parametric Bayesian analysis approach determines the most likely number of mobility states and the average diffusion coefficient of single molecules in each state, the population of each state, and the probability of transitioning between different mobility states over the course of a single trajectory (318). In our 56 previous study, we determined that TcpP-PAmCherry molecules in V. cholerae cells transition between multiple biophysical states: fast diffusion, intermediate diffusion, and slow diffusion (318). Here, we collected a new robust set of TcpP-PAmCherry tracking data in living V. cholerae cells (54,454 steps collected from 7601 trajectories) to further refine our analysis and to assign biochemical mechanisms to these biophysical observations (a sample of these tracks is shown in Figure 3.1B). Consistent with our previous results, we ascertained that TcpP-PAmCherry exists in three distinct states (slow diffusion, intermediate diffusion, and fast diffusion; blue, orange, and purple, respectively, in Figure 3.1C). Furthermore, we determined that TcpP-PAmCherry molecules do not freely transition between all the diffusion states: we observe that TcpP-PAmCherry molecules can transition between the fast state (purple) and the intermediate state (orange) and between the intermediate state (orange) and the slow state (blue) freely, but there is no significant probability of transitions directly from the fast diffusion state (purple) to the slow diffusion state (blue) on successive steps (Figure 3.1D). Thus, the intermediate diffusion state represents a critical biochemical intermediate between the slow and fast diffusion states. 57 Figure 3.1: Single-molecule diffusion dynamics of TcpP-PAm. A) Model of tcpP- PAmCherry. B) Representative single-molecule trajectory maps overlaid on reverse- contrast bright-field image of V. cholerae TcpP-PAmCherry. Only trajectories lasting 0.20 s (5 frames) are shown. Trajectories shown in a variety of colors to show diversity of motion observed. Scale bar: 1 µm. C) Average single-molecule diffusion coefficients and weight fraction estimates for TcpP-PAmCherry in live V. cholerae cells grown under virulence-inducing conditions. Single-step analysis identifies three distinct diffusion states (fast – purple, intermediate – orange, and slow – blue, respectively). Each point represents the average single-molecule diffusion coefficient vs. weight fraction of TcpP- PAmCherry molecules in each distinct mobility state at each saved iteration of the Bayesian algorithm after convergence. The dataset contains 54,454 steps from 7,601 trajectories. Inset: percentage (weight fraction) of TcpP-PAmCherry in each diffusion state. Colors as in panel. D) Based on the identification of three distinct diffusion states for TcpP-PAmCherry (three circles with colors as in c and with average single-molecule diffusion coefficient, D, indicated in μm2/s), the average probabilities of transitioning between mobility states at each step are indicated as arrows between those two circles, and the circle areas are proportional to the weight fractions. Low significance transition 58 Figure 3.1 (cont’d) probabilities less than 4% are not displayed; for instance, the probability of TcpP- PAmCherry molecules transitioning from the fast diffusion state to the slow diffusion state is 1%. Numbers above the arrows indicate the probability of transition. The high transition probability of TcpP-PAmCherry molecules from the intermediate diffusion state to the fast diffusion state (50%) is unexpected, as the fast diffusion state represents the smallest population of TcpP-PAmCherry molecules (9%), with a low probability (8%) of TcpP-PAmCherry molecules transitioning from the fast diffusion state back to the intermediate diffusion state (Figure 3.1D). While we cannot directly determine how RIP influences the dynamics of TcpP-PAmCherry, the stark difference in the transition probabilities and the populations of TcpP-PAmCherry in the fast and intermediate diffusion states suggests that fast diffusing TcpP-PAmCherry molecules are potentially sensitive to some form of degradation. Given this baseline for the dynamics of TcpP-PAmCherry, we hypothesize that: 1) the three diffusion states (slow, intermediate, and fast) are features of TcpP-PAmCherry molecules with three biologically distinct roles; 2) the slow diffusion state is occupied by TcpP-PAmCherry molecules interacting with DNA, such as the toxTpro; and 3) the intermediate diffusion state is influenced by ToxR. We further explore these three hypotheses with V. cholerae mutants below. 59 3.5.3 – Mutation of the toxTpro Decreases the Slow Diffusion State Occupancy We hypothesized that the slow TcpP-PAmCherry diffusion state encompasses molecules specifically interacting with DNA at its binding site in the toxTpro. The molecular weight of chromosomal DNA (chromosome 1: 2.96 Mbp) is much higher than that of any protein. Thus, binding of TcpP-PAmCherry to this promoter on the chromosome should result in an extremely low apparent diffusion rate. To test our hypothesis, we removed key binding sites for TcpP (−55 to −37) and both ToxR and TcpP (−112 to +1) in the toxTpro, generating tcpP-PAmCherry toxTpro∆(−55–+1) and tcpP- PAmCherry toxTpro∆(−112–+1) (Figure 3.2), both of which resulted in a drastic reduction in TcpA production, similar to that of a ∆tcpP mutant (Figure C.2A). toxT transcription was reduced in tcpP-PAmCherry toxTpro∆(−112–+1), but not in tcpP-PAmCherry toxTpro∆(−55–+1) (Figure C.4). It is possible that the toxTpro∆(−55–+1) mutation causes TcpP-PAmCherry and ToxR to stimulate transcription of a non-functional toxT mRNA. Regardless, loss of either region of the toxTpro results in loss of production of the TcpA virulence factor. 60 Figure 3.2: TcpP-PAmCherry diffusion dynamics within live V. cholerae cells containing mutated regions of the toxT promoter (toxTpro). A) and C) Model of toxTpro mutations in tcpP-PAmCherry toxTpro∆(−112–+1) and tcpP-PAmCherry toxTpro∆(−55–+1), respectively. B) and D) Average single-molecule diffusion coefficients and weight fraction estimates for TcpP-PAmCherry in live V. cholerae tcpP- PAmCherry toxTpro∆(−112–+1) (B) and V. cholerae tcpP-PAmCherry toxTpro∆(−55– +1) (D) grown under virulence-inducing conditions. Single-step analysis identifies five and three distinct diffusion states (fast – purple, intermediate – orange, light orange, and yellow, and slow – blue, respectively). Each point represents the average single- molecule diffusion coefficient vs. weight fraction of TcpP-PAmCherry molecules in each distinct mobility state at each saved iteration of the Bayesian algorithm after convergence. The dataset contains 104,341 steps from 21,274 trajectories for b and 75,841 steps from 11,624 trajectories for d. The data for TcpP-PAmCherry diffusion in wild type V. cholerae cells (Figure 3.1C) are provided for reference (cross hairs). Insets: Percentage (weight fraction) of TcpP-PAmCherry in each diffusion state. Colors as in panel. 61 Relative to the wild type (Figure 3.1), deleting both the ToxR and TcpP binding sites (toxTpro∆(−112–+1)) reduces the percentage of slow diffusing TcpP-PAmCherry to very low levels (7%; Figure 3.2B). Thus, TcpP-PAmCherry in the slow diffusion state requires toxTpro; therefore, we propose molecules in this state are bound to toxTpro. On the other hand, loss of the TcpP binding site alone (toxTpro∆(−55–+1)) reduces the percentage of slow TcpP-PAmCherry molecules only subtly (from 43% to 34%; Figure 3.2D). This result is consistent with earlier observations demonstrating that association with ToxR can restore the function of TcpP variants otherwise unable to bind the toxTpro (39, 55). Furthermore, our single-step analysis of TcpP-PAmCherry in the toxTpro∆(−112– +1) cells indicates five distinct TcpP-PAmCherry diffusion states, an increase from three states in the wild type (Figure 3.2B). In particular, the percentage of TcpP-PAmCherry molecules within the intermediate state overall increased (48% to 78%), but our analysis showed that these moderate moving molecules in fact cluster into three distinct sub-states (yellow, light orange, and orange, in Figure 3.2B). These intermediate TcpP-PAmCherry diffusion sub-states appear when TcpP-PAmCherry is unable to associate with the toxTpro. Though large-scale changes in the chromosome structure following the promoter deletion may play a role, these intermediate TcpP-PAmCherry diffusion sub-states may represent true biochemical interactions that are too short-lived to precisely distinguish and identify due to our current time resolution of 40 ms/acquisition. Further investigation is required to understand the specific biological roles of these sub-states, but indeed as discussed below, we detect these intermediate sub-states in all the other mutants studied here (Figure 3.3 and Figure 3.4). 62 3.5.4 –ToxR Promotes TcpP-PAmCherry Association with the Slow and Fast Diffusion States ToxR is a critical regulator of toxT transcription through its role supporting TcpP interaction with the toxTpro (39, 55, 70). Prior studies have shown that TcpP and ToxR interact in response to low oxygen concentrations, and ToxR antagonizes H-NS from the toxTpro (55, 72, 132). Several models for TcpP-mediated toxT transcription implicate ToxR in recruitment of TcpP molecules to the toxTpro (39, 54, 55, 70, 71, 302). Another model invokes “promoter alteration” to suggest that ToxR promotes TcpP-toxTpro interaction by displacing the histone-like protein (H-NS) and altering DNA topology rather than recruiting TcpP molecules to the toxTpro (71). To examine the role of ToxR in the motion and localization of TcpP-PAmCherry, we deleted toxR, and its accessory protein toxS, in both the tcpP-PAmCherry and the tcpP-PAmCherry toxTpro∆(−55–+1) backgrounds, resulting in tcpP-PAmCherry ∆toxRS and tcpP-PAmCherry ∆toxRS toxTpro∆(−55–+1) genotypes. We found that tcpP- PAmCherry ∆toxRS and tcpP-PAmCherry ∆toxRS toxTpro∆(−55–+1) cells could activate toxT transcription, but only tcpP-PAmCherry ∆toxRS supported virulence factor production (Figures C.2AB and Figure C.4). Complementation of tcpP-PAmCherry ∆toxRS with toxR did not change overall levels of TcpA (Figure C.7). Complementation of tcpP-PAmCherry ∆toxRS toxTpro∆(−55–+1) with ToxR did not restore TcpA to WT levels (Figure C.7). These data show that TcpP-PAmCherry can stimulate toxT transcription and bind to the toxTpro independent of ToxR. WT TcpP can stimulate toxT transcription independent of ToxR, but only upon TcpP overexpression (39, 55). Due to reduced sensitivity of TcpP-PAmCherry to RIP, we measure higher levels of TcpP- 63 PAmCherry relative to TcpP (Figure C.2A). This observation suggests that cooperativity between ToxR and TcpP is only necessary when levels of TcpP are low (i.e., when TcpP is sensitive to RIP). The percentage of slowly diffusing TcpP-PAmCherry molecules depends on toxRS, as deleting toxRS reduces this population in tcpP-PAmCherry ∆toxRS from 43% to 20% (Figure 3.3B). This toxRS dependence is maintained even in the absence of the TcpP binding site within the toxT promoter; the slow population in tcpP-PAmCherry ∆toxRS toxTpro∆(−55–+1) is reduced to 8% from 34% in tcpP-PAmCherry toxTpro∆(−55– +1) (Figure 3.3D). Indeed, the TcpP-PAmCherry dynamics are very similar for tcpP- PAmCherry toxTpro∆(−112–+1) (Figure 3.2B) and tcpP-PAmCherry ∆toxRS toxTpro∆(−55–+1) (Figure 3.3D). The major difference between TcpP-PAmCherry diffusion dynamics is the loss of the light orange intermediate diffusion sub-state in tcpP- PAmCherry ∆toxRS toxTpro∆(−55–+1) (Figure 3.3D). These data indicate that, in addition to the slow diffusion state, the presence of ToxR is critical for TcpP-PAmCherry molecules to exist in one of the intermediate sub-state diffusion states (i.e., the light orange diffusion state). 64 Figure 3.3: TcpP-PAmCherry diffusion dynamics within live V. cholerae cells lacking ToxRS and regions of the toxT promoter. A), C), and E) Model of tcpP- PAmCherry ∆toxRS, tcpP-PAmCherry ∆toxRS toxTpro∆(−55–+1), and tcpP- PAmCherry pMMB66eh-toxR, respectively. B), D) and F) Average single-molecule diffusion coefficients and weight fraction estimates for TcpP-PAmCherry in live V. cholerae tcpP-PAmCherry ∆toxRS (B), V. cholerae tcpP-PAmCherry ∆toxRS 65 Figure 3.3 (cont’d) toxTpro∆(−55–+1) (D), and tcpP-PAmCherry pMMB66eh-toxR (F) grown under virulence-inducing conditions. tcpP-PAmCherry pMMB66eh-toxR was grown in the presence of 1mM IPTG. Single-step analysis identifies four distinct diffusion states (fast – purple, intermediate – yellow and orange, and slow – blue, respectively). Each point represents the average single-molecule diffusion coefficient vs. weight fraction of TcpP- PAmCherry molecules in each distinct mobility state at each saved iteration of the Bayesian algorithm after convergence. The dataset contains 80,005 steps from 11,069 trajectories for b, 58,577 steps from 11,314 trajectories for d, and 134,071 steps from 19,509 trajectories for f. The data for TcpP-PAmCherry diffusion in wild type V. cholerae cells (Figure 3.1C) are provided for reference (cross hairs). As shown in Figure 3.1D, we found that TcpP-PAmCherry molecules do not freely transition between all the diffusion states: the intermediate diffusion state is an important diffusion state for TcpP-PAmCherry molecules to transition between the fast and the slow diffusion states. Since the ToxR-TcpP interaction is proposed to enable TcpP to associate with the transcription complex at toxTpro (39, 55), we reasoned that ToxR is responsible for the preferred intermediate-to-slow state transition of TcpP-PAmCherry. However, in ∆toxRS (Figure 3.3B) like in the wild-type (Figure 3.1C), only TcpP-PAmCherry molecules in the slowest of the intermediate diffusion sub-states were likely to transition to the slow diffusion state (orange and blue diffusion states, respectively, Figure C.8B). These transition probabilities suggest that ToxR is not responsible for the restricted transition of TcpP-PAmCherry between the slow and fast diffusion states. Furthermore, the absence of ToxR reduced the probability of TcpP-PAmCherry entering the fast diffusion state and increased the probability of TcpP-PAmCherry leaving the fast diffusion state (Figure 3.1D and Figure C.8B). Taken together, these data indicated that ToxR sequesters a portion of the total TcpP-PAmCherry population away from the toxTpro. We reasoned that increased levels of ToxR might sequester TcpP molecules to an inactive state 66 (represented by the intermediate diffusion state). To test this hypothesis, we overexpressed ToxR in a tcpP-PAmCherry background and quantified virulence factor transcription (i.e., TcpA) (Figure C.9). We found that elevated ToxR levels reduced virulence factor levels in both WT and tcpP-PAmCherry cells. Furthermore, overexpression of ToxR also decreased the percentage of TcpP-PAmCherry in the slow diffusion state (17% vs 43%) and resulted the formation of a sub-intermediate diffusion state, similar to tcpP-PAmCherry ∆toxRS (Figure C.4B). These data suggest that elevated levels of ToxR can repress toxT transcription by reducing the percentage of TcpP molecules entering the slow diffusion state. Figure 3.4: Mutation of the DNA binding domain within TcpP reduces the number of TcpP molecules within the slow diffusion state. A) Model of tcpP-[K94E]- PAmCherry. B) Diffusion dynamics of a DNA binding deficient TcpP-PAmCherry variant within live V. cholerae cells. Average single-molecule diffusion coefficients and weight fraction estimates for TcpP-[K94E]-PAmCherry in live V. cholerae tcpP-[K94E]- PAmCherry grown under virulence-inducing conditions. Single-step analysis identifies four distinct diffusion states (fast – purple, intermediate – yellow and orange, and slow – blue, respectively). Each point represents the average single-molecule diffusion coefficient vs. weight fraction of TcpP-[K94E]-PAmCherry molecules in each distinct mobility state at each saved iteration of the Bayesian algorithm after convergence. The dataset contains 52,565 steps from 8,056 trajectories. The data for TcpP-PAmCherry 67 Figure 3.4 (cont’d) diffusion in wild type V. cholerae cells (Figure 3.1C) are provided for reference (cross hairs). Inset: Percentage (weight fraction) of TcpP-[K94E]-PAmCherry in each diffusion state. Colors as in panel. 3.5.5 – Mutation of the TcpP Helix-Turn-Helix Domain Reduces the Percentage of Slowly Diffusing TcpP-PAmCherry Based on results shown in Figure 3.1C, we proposed that TcpP-PAmCherry molecules in the slow diffusion state are bound to toxTpro, and we found that removing the toxTpro binding sites (Figure 3.2) or eliminating toxR (Figure 3.3) significantly reduces this bound state population. Previous studies demonstrated that TcpP does not require DNA binding capability to activate toxT transcription if ToxR is present (39, 55). To examine this finding further by SMT, we used a tcpP-PAMCherry allele with a mutation (K94E) that inhibits TcpP from binding to the toxTpro (55). This mutation results in greatly reduced toxT transcription and TcpA levels (Figures C.2A and Figure C.4). The levels of TcpP[K94E]-PAmCherry is elevated compared with TcpP-PAmCherry (Figure C.2A), consistent with earlier evidence that the K94E substitution increases TcpP stability (55). In addition to TcpP[K94E]-PAmCherry being unable to stimulate toxT transcription, a lower percentage of TcpP[K94E]-PAmCherry molecules are detected in the slowest- diffusing state than for TcpP-PAmCherry (15% vs. 43%; Figure 3.4B). Furthermore, TcpP[K94E]-PAmCherry molecules have an additional intermediate diffusion sub-state, similar to both tcpP-PAmCherry ∆toxRS and tcpP-PAmCherry ∆toxRS toxTpro∆(−55–+1) (Figure 3.4B). 68 3.6 – Discussion How MLTRs find their target sequences from the membrane represents a major gap in knowledge. Here, we started to address this by investigating single-molecule dynamics of TcpP-PAmCherry. Taken together with previous work, the data presented here demonstrate that TcpP-PAmCherry molecules diffuse in at least three distinct biophysical states (fast, intermediate, and slow diffusion), but do not freely transition between all diffusion states (318). We hypothesized that each of these biochemical states have distinct biological roles. Specifically, we hypothesized that the slow diffusion state represented TcpP-PAmCherry molecules interacting with the toxTpro. To test this hypothesis, we made targeted deletions to the toxTpro and of toxRS, and we mutated the TcpP DNA binding domain (K94E). Our biophysical measurements of these mutations support the hypothesis that the slow diffusion state is occupied by TcpP-PAmCherry molecules interacting specifically with DNA at toxTpro. Additionally, we observed that TcpP-PAmCherry molecules only transition to the slow diffusion state from the intermediate diffusion state, and that ToxR is not responsible for this transition specificity. These data support a modified promoter alteration model (71) in which ToxR binds to the distal region of the toxTpro to promote TcpP binding to the proximal region of the toxTpro or, in the absence of its binding site, ToxR directly interacts with TcpP to stimulate toxT transcription. Our data do not suggest that ToxR directs or recruits TcpP to the toxTpro. While ToxR is critical for TcpP to stimulate toxT transcription (39, 52, 55), our data demonstrate that TcpP-PAmCherry can support toxT transcription and virulence factor production without ToxR, which may be a consequence of the greater stability of TcpP- PAmCherry compared to native TcpP (Figure C.2A and Figure C.4). Moreover, our single- 69 molecule imaging finds a higher percentage of the TcpP-PAmCherry molecules in the slow diffusion state in tcpP-PAmCherry ∆toxRS cells compared to tcpP-PAmCherry ∆toxRS toxTpro∆(−55–+1) (Figure 3.3). In addition, prior DNAse I foot printing experiments have demonstrated that in cells lacking toxR TcpP protects a larger region of the toxTpro (−100 to −32), i.e., TcpP protects most of the ToxR binding and TcpP binding sites in ∆toxRS (39). Taken together, these results indicate that: 1) ToxR is not essential for TcpP to locate the toxTpro; and 2) TcpP is able to interact with the toxTpro independent of ToxR. In addition, our data show that ∆toxRS reduces the percentage of DNA-bound TcpP-PAmCherry but does not decrease the probability of TcpP-PAmCherry molecules transitioning from the intermediate state to the bound state (Figure 3.3 and Figure C.8B). Despite a reduction in the percentage of DNA-bound TcpP-PAmCherry, TcpP-PAmCherry stimulates WT toxT transcription independent of ToxR (Figure C.4). These data support the promoter alteration model (71) in which, rather than ToxR recruiting TcpP to the toxTpro, ToxR assists TcpP to stimulate toxT transcription once TcpP independently associates with the toxTpro. Counterintuitively, in the absence of ToxRS TcpP-PAmCherry molecules have a lower probability of exiting the slow diffusion state (Figure C.8B). Given that RIP of TcpP-PAmCherry impedes our ability to image TcpP-PAmCherry, these data suggest that TcpP-PAmCherry molecules might be sensitive to RIP while interacting with the toxTpro, and that ToxRS may inhibit RIP of TcpP while interacting with the toxTpro. If this is the case, given that we are unable to image TcpP-PAmCherry molecules that are sensitive to RIP, it might explain why we observe a lower percentage of TcpP-PAmCherry molecules in the slow diffusion state and yet we observe WT toxT transcription in the absence of ToxRS. However, future 70 experiments are required to determine if ToxRS inhibits RIP of TcpP while interacting with the toxTpro. Under certain conditions ToxR can negatively influence toxT transcription. In response to stationary-phase accumulation of the cyclic di-peptide cyclic phenylalanine- proline (cyc-phe-pro), ToxR stimulates production of LeuO, resulting in down-regulation of the tcpP regulator aphA (326, 327). Our data suggests that ToxR can also reduce toxT transcription by influencing TcpP-PAmCherry single molecule dynamics (Figure C.8B). Deletion of toxRS reduces the overall probability of TcpP-PAmCherry molecules transitioning between the intermediate and fast diffusion states (Figure C.8B). Moreover, elevated levels of ToxR reduce both the percentage of TcpP-PAmCherry in the slow diffusion state and virulence factor production (Figure 3.3F and Figure C.9), suggesting that ToxR can antagonize toxT transcription by promoting transition of TcpP molecules to the fast or sub-intermediate diffusion states. A similar phenotype has been reported previously (39). Lastly, prior electrophoretic mobility shift assays also indicate that ToxR can sequester TcpP from the toxTpro. In ∆toxRS cells TcpP is able to bind to the toxTpro -73⎼+45 (toxTpro lacking the ToxR binding region), but not in the presence of ToxR molecules (39). It remains unclear how ToxR sequesters TcpP-PAmCherry molecules from the slow diffusion state. However, we hypothesize that ToxR promotes TcpP molecules to transition away from the slow diffusion state to prevent aberrant toxT transcription. Follow-up experiments are required to test this hypothesis. Currently, the biological roles of the intermediate diffusion states (or intermediate diffusion sub-states) are unclear, but the intermediate states are certainly important, as TcpP molecules transition to the toxTpro-bound state from them. There is nearly a 10- 71 fold difference in diffusion coefficients between the slow and intermediate diffusion states (0.044 µm2/sec vs. 0.006 µm2/sec respectively; Figure 3.1C). This difference cannot be explained by dimerization or interaction of ToxR and TcpP-PAmCherry alone: the mobility of membrane-localized proteins scales linearly with the number of transmembrane helices, such that increasing the number of transmembrane helices via dimerization from one to two would only reduce the diffusion coefficient by a factor of two (328). One possibility is that TcpP-PAmCherry molecules undergo fast diffusion in less protein dense areas of the cytoplasmic membrane relative to TcpP-PAmCherry molecules undergoing intermediate diffusion. Prior single molecule analysis of 209 membrane localized proteins in Bacillus subtilis revealed that only 6% of all membrane proteins imaged were homogeneously distributed throughout the cytoplasmic membrane (328, 329). Heterogeneous distribution of membrane localized proteins in B. subtilis suggests that similar distribution of membrane localized proteins in V. cholerae can occur. It remains unclear as to why the vast majority of these membrane localized proteins in B. subtilis have heterogeneous diffusion dynamics. One possibility is that these membrane localized proteins have different preferences for lipid ordered and lipid disordered membrane domains. Prior studies have demonstrated that transmembrane domain properties (e.g., surface area, length, and post-translational modifications) are major factors in determining lipid ordered or lipid disordered membrane domain preference (330). We are currently exploring if lipid ordered and lipid disordered membrane domains influence diffusion dynamics of TcpP molecules within the fast and intermediate diffusion states. Alternatively, it is possible that the diffusion coefficients of TcpP-PAmCherry molecules in the intermediate state are undergoing non-specific interactions with DNA 72 whereas the slowest TcpP-PAmCherry molecules are specifically bound at toxTpro. Our data show that there are some slow moving TcpP-PAmCherry molecules when major regions of the toxTpro are deleted or when key residues within the DNA binding domain of TcpP are mutated (i.e., tcpP[K94E]-PAmCherry; Figure 3.2 and 3.4). When considering our alternative model of non-specific DNA binding by TcpP, our data suggest two possibilities: 1) TcpP-PAmCherry molecules in the slow diffusion state represent TcpP molecules that make both specific and non-specific interactions with DNA; or 2) TcpP- PAmCherry molecules in the slow diffusion state interact specifically with non-toxTpro DNA (i.e., TcpP regulates additional genes). Several genes appear to have altered gene transcription upon deletion of tcpPH (331). However, these experiments have yet to be replicated. Thus, future experiments would be required to test these hypotheses. These results provide deep insights that further expand the model of cooperativity between ToxR and TcpP-PAmCherry. Our data demonstrate that ToxR assists TcpP to associate with the toxTpro even in the absence of the TcpP binding site, further supporting the established model of cooperativity between TcpP and ToxR. The data also show that TcpP can locate the toxTpro, interact with the toxTpro, and stimulate toxT transcription independent of ToxR. This supports the promoter alteration model in which TcpP molecules independently associate with the toxTpro while ToxR enhances this association by altering toxTpro topology to stimulate toxT transcription. In addition to independently associating with the toxTpro, these data show that ToxR promotes transition of TcpP molecules to the fast and sub-intermediate diffusion states, shifting the equilibrium of TcpP molecules away from the toxTpro. The mechanism by which ToxR promotes transition of TcpP molecules away from the slow diffusion state is currently 73 unclear but will be the subject of future investigation. Given that toxT transcription is highly regulated, we speculate that sequestration of TcpP molecules from the toxTpro is yet another mechanism to fine tune toxT transcription. It is probable that other MLTRs, found in both Gram-negative and Gram-positive bacteria, have similar biophysical properties (Figure C.1). Continued exploration of MLTR biophysical properties could be leveraged to develop alternative strategies to inhibit MLTRs to treat bacterial infections without exacerbating the global antibiotic resistance crisis. 74 Chapter 4 – Co-Association of TcpP and TcpH within Detergent-Resistant Membranes Stimulates TcpH-Dependent Inhibition of Regulated Intramembrane Proteolysis of TcpP in Vibrio cholerae 75 4.1 – Abstract Vibrio cholerae is a Gram-negative gastrointestinal pathogen responsible for the diarrheal disease cholera. V. cholerae produces virulence factors such as cholera enterotoxin (CT) and the toxin co-regulated pilus (TCP) to cause disease. Transcription of these is activated directly by a transcription regulator, ToxT, and indirectly by two single-pass membrane-localized transcription regulators (MLTR), ToxR and TcpP, that promote the transcription of toxT. TcpP abundance and activity are controlled via TcpH, a single-pass transmembrane protein, and a two-step proteolytic process known as Regulated Intramembrane Proteolysis (RIP). The mechanism of TcpH mediated protection of TcpP represents a major gap in our understanding of V. cholerae pathogenesis. Absence of tcpH leads to unimpeded degradation of TcpP in vitro and a colonization defect in a neonate mouse model of V. cholerae colonization. Here, we show that TcpH protects TcpP from RIP via direct interaction. We also demonstrate that a dietary fatty acid, α-linolenic acid, promotes TcpH-dependent inhibition of RIP via co- association of TcpP and TcpH molecules within detergent-resistant membranes (DRMs) (also known as lipid rafts). Taken together our data support a model where V. cholerae cells utilize exogenous α-linolenic acid to remodel their phospholipid bilayer in vivo leading to co-association of TcpP and TcpH within DRMs where RIP of TcpP is strongly inhibited by TcpH thereby promoting V. cholerae pathogenesis. 76 4.2 – Introduction V. cholerae tightly regulates transcription of its virulence factors, such as cholera toxin (CtxAB) and the toxin co-regulated pilus (TcpA-F) to reach the optimal site of infection, the crypt of intestinal villi (332–337). Transcription of these essential virulence factors is regulated by ToxT, an AraC-like transcription factor (338–341). Similarly, transcription of toxT is highly regulated and positively stimulated by TcpP and ToxR, two membrane-localized transcription regulators (MLTR) (342–345). TcpP and ToxR are bitopic membrane proteins that each contain a cytoplasmic DNA-binding domain, a single transmembrane domain, and a periplasmic domain (346). Both ToxR and TcpP directly bind to the promoter region of toxT, at -180 to -60 and -55 to -37, respectively (340, 347, 348). While ToxR directly binds to the toxT promoter, ToxR alone is unable to directly stimulate toxT transcription (340). However, TcpP is required for toxT transcription, presumably because TcpP facilitates transcription through direct interaction with RNA polymerase due to its binding sequence being near the -35 site (340, 347). Unlike ToxR, transcription of tcpP is tightly regulated by multiple transcription factors, further demonstrating the critical importance of TcpP (60–63, 65, 67, 349, 350). TcpP is also post-translationally regulated by two proteases, Tail-specific protease (Tsp) and YaeL, through a process known as Regulated Intramembrane Proteolysis (RIP) (96, 351, 352). RIP is a form of gene regulation conserved across all domains of life that allows organisms to rapidly respond to extracellular cues, commonly by liberating a transcription factor or a sigma factor, from membrane sequestration (353). Two well- characterized systems controlled by RIP mechanisms are the extracytoplasmic stress 77 response in E. coli and regulation of sporulation in Bacillus subtilis. These systems require RIP of RseA and SpoIVFB to release their respective sigma factors (σE and pro-σK) from the membrane to influence gene transcription(354–360). Similarly, both systems have their respective TcpH analog, RseB and BofA, which function to prevent RIP of RseA and SpoIVFB via different mechanisms (355, 361–366). Regulation of TcpP by this mechanism diverges from these canonical systems because transcription activity of TcpP is not activated by RIP but is rather inactivated by RIP, which removes TcpP from the cytoplasmic membrane thereby leading to a decrease in toxT transcription (96, 351, 352). Our current understanding of RIP of TcpP remains limited. Under RIP-permissive conditions in vitro (e.g. LB pH 8.5, 37°C, 210rpm), TcpP is sensitive to proteolysis by tail- specific protease (Tsp; site-1 protease), and subsequently by YaeL protease (site-2 protease) (96, 351, 352). RIP of TcpP is inhibited by its associated protein, TcpH, under specific in vitro conditions (e.g. LB pH 6.5, 30℃, 110rpm) (96, 351, 352). Without TcpH present, TcpP is constitutively sensitive to RIP (96, 351, 352). However, the mechanism by which TcpH inhibits RIP and how TcpH-dependent RIP inhibition is modulated by extracellular stimuli remains unknown. In this report we provide evidence that TcpH protects TcpP from RIP via direct interaction. Furthermore, we explore the role of the membrane in regulating TcpP-TcpH association and present data that the two molecules interact within both detergent- resistant and detergent-soluble membranes (DRM and DSM, respectively). DRM and DSM (I.e., lipid-ordered and lipid-disordered membrane domains) are known to form in both eukaryotic and prokaryotic organisms (367–372). In prokaryotes, lipid-ordered membrane domains are small phospholipid domains (~10-200 nm) that exist within both 78 inner and outer membranes (373). They are composed of saturated phospholipids and hopanoids (or cholesterol in eukaryotic cells) that tightly interact, resulting in a structured membrane region with low fluidity. Conversely, lipid-disordered membrane domains are enriched in unsaturated phospholipids resulting in high fluidity (367–369, 371–380). Due to these differences lipid-ordered and lipid-disordered membrane domains can be separated based on solubility in non-ionic detergents, and we refer to them as detergent- resistant membranes (DRM) and detergent-soluble membranes (DSM), respectively. Our data suggest that in vivo TcpP and TcpH preferentially associate with DRMs. This leads to enhanced inhibition of RIP by TcpH, thereby resulting in elevated TcpP levels, and toxT transcription. We also show that utilization of exogenous α-linolenic acid, a long chain poly-unsaturated fatty acid present in vivo, stimulates TcpP and TcpH association within DRMs. Data generated here support a model where, once V. cholerae cells enter the gastrointestinal tract, cellular uptake of α-linolenic acid results in modification of the phospholipid profile and leads to an increase the abundance of TcpP and TcpH molecules within DRMs thereby stimulating inhibition of RIP. 4.3 – Methods and Materials 4.3.1 – Bacterial strains, plasmids, and growth conditions All V. cholerae strains used in this study were of the classical biotype (0395) (See Table D.1 for a complete list of bacterial strains). Unless otherwise stated Escherichia coli and V. cholerae were grown at 37ºC in Luria-Bertani (LB) with vigorous shaking (210 rpm). LB was prepared as previously described (381). To stimulate virulence factor production, V. cholerae strains were subcultured, to an O.D. of 0.01, from an overnight 79 LB culture and grown under virulence inducing conditions (Vir Ind; 30ºC, LB pH 6.5, and 110 rpm) or non-virulence inducing conditions (non-Vir Ind; 37ºC, LB pH 8.5, and 210 rpm). Media used for both Vir Ind and non-Vir Ind were sterilized using 1L 0.22 µm vacuum filtration units (Sigma) following pH adjustment. Ex-vivo mouse fecal experiments with sterile and non-sterile mouse fecal media were conducted aerobically at 37°C in 48 well plates (Sigma) with shaking (210 rpms). Sterile mice fecal samples were collected from C57 Black female mice on 4 separate days and stored at -80°C. After collection mice fecal samples were homogenized, via mortar and pestle, and then suspended in M9 minimal media. The final concentration of mice fecal media was 9% w/v. The mice fecal media was then spun down (2450xg for 10 min) to remove insoluble material. The supernatant was collected, and filter sterilized using a 0.45 µM syringe filter (Sigma). Non-sterile mice fecal samples were collected from C57 Black female mice on three separate days. Mice fecal matter was directly resuspended in M9 media to a final concentration of 9% w/v. Mice fecal media was then incubated at room temperature for 1 hour while shaking on a table top shaker. Mice fecal media was spun down (2450xg for 10 min). The supernatant was collected and used directly for the growth curve. V. cholerae cell density was determined by counting CFU’s on LB agar plates supplemented with streptomycin. Microbiota in mice fecal matter were not found to be resistant to streptomycin. Unless otherwise stated, antibiotics were used at the following concentrations: ampicillin (100 µg/ml), chloramphenicol (30 µg/ml), and streptomycin (100 µg/ml). Overexpression of constructs by pBAD18 was induced by culturing strains in LB containing 0.1% arabinose. 80 4.3.2 – Plasmid construction Briefly, DNA fragments 500 bp upstream and downstream of the target gene were amplified using Phusion high-fidelity polymerase (Thermo Scientific) (see Table D.2 for list of primers used). Insert fragments containing desired mutations were connected by splicing via overlap extension PCR. Plasmid vectors (pKAS32 and pBAD18) were isolated from bacterial strains using the Qiagen Miniprep kit. Plasmid vectors were then digested with KpnI-HiFi and XbaI (New England BioLabs) at 37ºC for 2 hours. Insert and vector fragments were then added to Gibson assembly master mix (New England BioLabs) and incubated at 50ºC for 30 minutes. Plasmids were then introduced to E. coli ET12567 ∆dapA (λpir +) by electroporation. pKAS32 plasmids were then transferred to V. cholerae strains via mating on LB agar plates at 30ºC overnight. pBAD18 plasmids were introduced into V. cholerae strains via electroporation. 4.3.3 – Mutant construction Mutants were constructed as previously described (320). V. cholerae harboring pKAS32 derivatives were grown in 2 ml LB for 2 hours at 37ºC. Streptomycin was then added to cultures to a final concentration of 2500 µg/ml and incubated for an additional 2 hours. After a total of 4 hours of incubation, 20 µl of culture was spread on LB agar plates containing streptomycin (2500 µg/ml) and incubated at 37ºC overnight. Colonies that were resistant to streptomycin were screened via colony PCR to confirm presence of the desired mutation. Genomic DNA was then isolated from potential mutants and the region of interest was then amplified via PCR and validated by sequencing (GeneWiz). 81 4.3.4 – Growth curves V. cholerae strains were subcultured from an overnight culture to a final optical density (600 nm) of 0.01 in 200 µl of virulence inducing media per well of a 96 well plate. The plate was then incubated at 30ºC in a SPECTROstar Omega plate reader (BMG LABTECH), with shaking and optical density measurements every 30 minutes. 4.3.5 – Western blots After whole cell lysis, the total protein concentration of each sample was measured via Bradford assay (Sigma Aldrich). Samples were subsequently diluted to a final concentration of 0.5 µg total protein/µl. All SDS page gels contained 12.5% acrylamide and were run at 90-120 volts for 1.5 hours. Proteins were transferred to nitrocellulose membranes using a semi dry electroblotter (Fisher Scientific) overnight at 35 mA or for 2 hours at 200mA. Membranes were blocked with 15 ml of blocking buffer (5% non-fat milk, 2% bovine serum albumin, 0.5% Tween-20, in Tris-buffered saline) for 1 hour at room temperature. Primary antibodies were diluted in 5% non-fat milk and Tris-buffered saline (α-TcpH 1:500, α-TcpP 1:1,000, α-RNA polymerase β’ 1:1,000 and α-TcpA 1:100,000) and incubated with the membranes for 1 hour at room temperature. Membranes were washed three times for 5-15 minutes with Tris-buffered saline. Secondary antibodies (Sigma Aldrich) were diluted in 5% non-fat milk in Tris-buffered saline (Goat anti-Rabbit IgG-HRP 1:2,000 and Mouse anti-Rabbit IgG-HRP 1:2,000) and incubated as before. Membranes were washed three times for 5-15 minutes with Tris-buffered saline and then incubated with SuperSignal HRP Chemiluminescence substrate (Thermo Fisher). Membranes were imaged with an Amersham Imager 600. 82 4.3.6 – Enzyme Linked-Immunosorbent Assay (ELISA) ELISAs were performed as previously described (382). V. cholerae cells were subcultured from overnight cultures to an optical density of 0.01 in 10 ml of LB pH 6.5. Cultures were incubated at 30 ºC for a total of 24 hours. Cells were collected by centrifugation at 2450X g for 15 minutes. 1 ml of culture supernatant was collected and the remaining supernatant was discarded. All steps of EILSA were performed at room temperature. 10 µl of culture supernatant was added to 140 µl PBS-T (phosphate buffered saline, 0.05% Tween-20, 0.1% BSA) in row A of plates coated with GM1 (monosialotetrahexosylganglioside). Samples were diluted (1:3) down each column and incubated at room temperature for 1 hour. Plates were then washed with PBS-T three times. Primary (α-CtxB 1:8000, Sigma Aldrich) and secondary antibody (Goat anti-Rabbit IgG-HRP 1:5,000, Sigma Aldrich) were diluted in PBS-T. 100 µl of diluted antibody was added to each well and incubated for 1 hour at room temperature. Plates were again washed with PBS-T as before. 100 µl of TBS (3,3',5,5'-tetramentylbenzidine, Sigma) was added to each well and incubated for 5-10 minutes. The reaction stopped by addition of 100 µl of 2M sulfuric acid and the optical density (450 nm) was measured for each well using SPECTROstar Omega plate reader (BMG LABTECH). 4.3.7 – Infant Mouse Colonization Infant mouse colonization experiments were performed as previously described (383). Briefly, three- to six- day old CD-1 mice (Charles River, Wilmington, MA) were orogastrically inoculated with ~1x106 bacterial cells after 2 hours of separation from their 83 mothers. Infant mice were kept at 30ºC in sterile bedding and euthanized about 21 hours after infection. Mouse intestines (small and large) were weighed in 3 ml PBS and homogenized. Homogenates were then serially diluted in PBS, spread on LB plates containing streptomycin, and incubated at 37ºC overnight. 4.3.8 – Real-time quantitative PCR (RT-qPCR) RT-qPCR experiments were performed as previously described (384). RNA was preserved by resuspending V. cholerae cells in 1 ml of Trizol (Sigma Aldrich) and then extracted from cells using an RNEasy kit (Qiagen) according to manufacturer’s instructions. RNA was then treated with Turbo DNase for 30 minutes at 37ºC. After DNase treatment, RNA quality was determined by detection of large and small ribosomal subunits via 2% agarose gel. RNA quantity was then measured using a Nanodrop spectrophotometer (Thermo Scientific). cDNA was generated from DNase treated RNA using Superscript III reverse transcriptase (Thermo Scientific) as previously described (384). 5 ng of cDNA was used with SYBR green master mix (Applied Biosystems) to perform the RT-qPCR. recA was used as a housekeeping gene of reference to calculate the threshold values (ΔΔCT) (385). See Table D.2 for primers. 4.3.9 – β-Galactosidase activity assay V. cholerae cells were subcultured from overnight cultures to an optical density of 0.01 in 50 ml of LB pH 6.5. V. cholerae strains were grown for 4 hours under Vir Ind conditions. Following incubation cultures were centrifuged (2450 X g 15 minutes), 84 resuspended in 1 ml LB, and then 200 µl of the culture resuspension was transferred to fresh media (Vir Ind, Vir Ind supplemented with crude bile/ cholate and deoxycholate (purified bile)/ α-linolenic acid, or non-Vir Ind). Cultures were grown for an additional 4 hours under their indicated condition. At the indicated time point (4 hours or 8 hours) 1.5 ml of culture was removed, centrifuged (4000 X g 15 minutes), and resuspended in 1 ml of Z-buffer (Na2HPO4 60mM, NaH2PO4 40mM, KCl 10mM, MgSO4 1mM, β- mercaptoethanol 50mM, pH7.0). β-galactosidase activity and Miller units were determined as previously described (386). 4.3.10 – Subcellular Fractionation Cells were fractionated following the Tris-sucrose-EDTA method (200mM Tris-HCl pH 8.5, 500mM sucrose, 1mM EDTA, pH 8.0) (387). V. cholerae cells were subcultured from overnight cultures to an optical density of 0.01 in 50 ml of LB pH 6.5. After 2 hours of incubation, plasmids were induced by the addition of arabinose (final concentration of 0.1%) at 30ºC with mild shaking (110 rpm), and then cultured for an additional 5 hours. All steps of the fractionation procedure were performed on ice as follows (387). Spheroplast fractions (i.e., cytoplasm and the cytoplasmic membrane) were resuspended in 500 µl 0.45% NaCl. To lyse the spheroplasts 50 µl of 10% SDS were added, and samples were then boiled for 5-10 minutes. Periplasmic fractions were concentrated using trichloroacetic acid (TCA) (387, 388). Pelleted whole cells were resuspended in 50- 200 µl of resuspension buffer (50mM Tris-HCl, 50mM EDTA, pH 8.0). Cells were then lysed by the addition of lysis buffer (10mM Tris-HCl, 1% SDS) and boiled for 5-10 minutes. All fractions were stored at -20 ºC until use. 85 Soluble and insoluble fractionation of V. cholerae cells was performed as described by Miller et. al., with modifications (342). Initial steps of the Tris-sucrose-EDTA extraction were followed regarding growth and collection of V. cholerae cells. Following collection, cells were resuspended in 10 ml of lysis buffer (10 mM Tris HCl pH 8.0, 750mM sucrose, EDTA-free protease inhibitor, 2mM EDTA, 50 µg/ml lysozyme, 10 U/ml DNase 1) and incubated on ice for 20 minutes. Cells underwent two rounds of lysis via French press (7,000-10,000 psi). Cellular debris was removed by centrifugation (1200 X g for 10 minutes) and supernatant was retained. Insoluble (i.e., the inner and outer membrane) and soluble fractions were separated by ultracentrifugation (100,000 x g for 2 hours at 4 ºC). The pellet, containing the membrane fraction, was collected and resuspended in 500 µl 5mM EDTA and 25% sucrose. The insoluble membrane fraction underwent a second round of ultracentrifugation and was then collected. All samples were stored at -80ºC until further use. 4.3.11 – Triton X-100 Subcellular Fractionation V. cholerae cells were subcultured from overnight cultures to an optical density of 0.01 in 50 ml of LB pH 6.5 and grown under Vir Ind for 6-8 hours. Cells were then pelleted by centrifugation (2450 X g 15 minutes), and resuspended in 500 µl of phosphate buffered saline (pH 7.4). Cells were then pelleted by centrifugation (2450 X g 15 minutes). For spheroplast fractionation, cells were resuspended in 100 µl of 200mM Tris HCl. After resuspension, components were added sequentially to each sample: 200 µl of 200mM Tris HCl and 1M sucrose, 20 µl of 10mM EDTA, 20 µl of lysozyme (10mg/ml), 10 µl of protease inhibitor cocktail (Sigma), and 600 µl of H2O. Samples were then incubated 86 at room temperature for 30 minutes. After room temperature incubation 700 µl of 2% Triton X-100, 50mM Tris HCl, and 10mM MgCl2 was added. For gentle cell lysis, pelleted cells were resuspended in 5 ml of Triton X-100 buffer (1% Triton X-100, 10mM imidazole, 500mM HEPES, 10% glycerol, 2M MgCl2). Samples then underwent three rounds of freeze-thaw lysis in 180 proof ethanol at -80ºC. Triton X-100 soluble and insoluble membrane fractions were then separated by ultracentrifugation (100,000 X g 1 hour). The supernatant (i.e., the Triton X-100 soluble fraction; TS) and the pellet (i.e., the Triton X-100 insoluble fraction; TI) were collected. The TI fraction was resuspended in 500µl of 2% SDS and 10mM imidazole. The TS fraction was concentrated using Amicon protein concentrators with a 10KDa cutoff (Sigma). 4.3.12 – Co-affinity precipitation For co-affinity precipitation experiments V. cholerae cells were grown as described in the Triton X-100 Subcellular Fractionation section. After cells were suspended in PBS, proteins were cross linked by adding 1mM Dithiobis(succinimidyl propionate) (DPS) to cell suspensions and samples were incubated on ice for 30 minutes. DPS was quenched by adding Tris HCl pH 8.5 to final concentration of 1M and incubating cells on ice for an additional 15 minutes. Cells were then pelleted by centrifugation (2450 X g 15 minutes) and TI and TS fractions were collected via the gentle cell lysis method discussed in the Triton X-100 Subcellular Fractionation section. TI fractions were resuspended in 5ml of 2% sodium dodecyl-sulfate and 10mM imidazole. After collection of TI and TS fractions 100 µl of His-affinity gel (i.e., Ni-NTA Magnetic Agarose Beads) (ZYMO Research) and 87 10 µl of protease inhibitor cocktail (Sigma) was added to the TI and TS fractions and samples were incubated on a rocking platform overnight at 4ºC. TI samples were then incubated at 40ºC for 20 minutes to completely solubilize the sample. Samples were then centrifuged (2450 X g 15 minutes) and Ni-NTA agarose beads were washed three times with either Triton X-100 buffer or 2% sodium dodecyl-sulfate and 10mM imidazole. between wash steps TI Ni-NTA agarose beads were incubated at 40ºC for 5 minutes. Equal volume of laemmli buffer was added to each sample (BIO-RAD) and then boiled for 5 minutes. Boiled samples were then used directly for western blot analysis. 4.4 – Results 4.4.1 – TcpH Maintains in vitro Activity Upon Alteration of its Transmembrane and Periplasmic Domains To identify regions within TcpH that are critical for its role in protecting TcpP from RIP we constructed chimeric transmembrane domain fusions (TM) and periplasmic TcpH deletion constructs (Peri). We generated several tcpH constructs (as described in Experimental Procedures), but due to stability issues only two TM and one Peri constructs [ToxSTcpH, EpsMTcpH, and TcpH∆119-103, respectively] are discussed; the allele encoding each was recombined into the V. cholerae genome so as not disrupt the tcpP coding sequence are under normal tcpPH transcriptional control (Figure 4.1A). Growth dynamics of the resulting strains were unaffected in comparison with wild-type V. cholerae in virulence inducing (Vir Ind) conditions (Figure D.1A). We evaluated the constructs also by measuring TcpP levels, toxT transcription, and TcpA and CtxB production in vitro (Figure 4.1B and Figure D.2). All the TcpH constructs protected TcpP similar to WT TcpH 88 or better than ΔtcpH (Figure 4.1B). This suggests that the TcpH constructs are capable of inhibiting RIP of TcpP and thereby the TcpH TM and Peri constructs support TcpP function to stimulate toxT transcription. 89 Figure 4.1: TcpH transmembrane and periplasmic constructs protect TcpP, support toxT transcription, and virulence factor production. A) Diagram of TcpH 90 Figure 4.1 (cont’d) transmembrane constructs (EpsMTcpH and ToxSTcpH) and periplasmic construct (TcpH∆119-103). TcpH has a single transmembrane domain (also a Sec signal sequence), at its N-terminus, and two periplasmic cysteine residues (C114 and C132), represented by “s”. The transmembrane domain of TcpH was replaced with the transmembrane domain of ToxS (ToxSTcpH) and EpsM (EpsMTcpH) as both ToxS and EpsM are known to be localized to the cytoplasmic membrane with similar domain topology at TcpH (207, 389). As the majority of TcpH is localized in the periplasm, we also reasoned that the periplasmic domain was critical for TcpH function. In-frame deletion of periplasmic residues are indicated by a dashed line, based on TcpH secondary structure. B and C) in vitro characterization of TcpH transmembrane and periplasmic chromosomal constructs grown under virulence inducing conditions. B) Western blots of whole-cell lysates probed with α-TcpP (top), α-TcpH (middle), and α-TcpA (bottom). In addition, CtxB levels and toxT transcription were also determined for the TcpH transmembrane and periplasmic constructs. Average CtxB levels and toxT fold change (relative to WT) for each strain are indicated below the western blot. See Figure D.2 for full view of the data. See Figure E.1 for full view of western blots in panel B. 4.4.2 – TcpH TM domain is Critical for Colonization of Infant Mice In vitro experiments indicate that the TM and Peri domain of TcpH can withstand considerable modifications and still maintain function. Thus, we tested the fitness of the TcpH TM and Peri constructs in vivo. We infected infant mice with the TcpH TM and Peri constructs (Figure 4.2A). Despite TcpH-dependent virulence gene transcription profiles of strains expressing ToxSTcpH, and EpsMTcpH being analogous to cells expressing wild- type TcpH in vitro, these strains colonized infant mice to significantly lower levels than wild type, more closely resembling a ΔtcpH strain (Figure 4.2A). TcpH∆119-103 supported the same level of TcpH-dependent virulence gene transcription in vitro as both ToxSTcpH and EpsMTcpH, but colonized infant mice to a similar degree as wild type (Figure 4.2A). The inocula of ToxSTcpH and EpsMTcpH used to infect infant mice produced similar levels of TcpA compared to wild type (Figure 4.2B). We concluded that the colonization defects of the TM TcpH constructs were likely due to an inability of strains lacking the natural 91 TcpH transmembrane domain to express colonization factors – particularly TcpA – in vivo. To determine whether the presence of other microbes in the gastrointestinal tract might influence the ability of strains expressing TcpH with altered TM domains to support virulence gene transcription, we cultured wild type and the TcpH constructs (TM and Peri) aerobically in both filter sterilized and non-sterile (I.e., non-filtered) mouse fecal media for 21hrs at 37°C (Figure D.3). All strains exhibited similar growth rates and final cell densities in both filter sterilized and non-sterile mice fecal media (Figure D.3). In addition, we quantified TcpA levels in cell lysates after 21 hours of growth in sterile mouse fecal media. While the growth rates were very similar between wild type and strains expressing altered TcpH proteins, the strains expressing ToxSTcpH and EpsMTcpH produced TcpA levels below that of wild type (Figure 4.2C). The strain expressing the TcpH protein with a periplasmic deletion was unaffected for TcpA transcription (Figure 4.2C). Taken together, these data suggest that the TcpH transmembrane domain is critical for TcpH to respond to cues present in the gastrointestinal tract and protect TcpP from RIP, thereby supporting downstream virulence factor production. Due to their WT levels of colonization and ability to support WT levels of TcpA synthesis in mouse fecal media we chose to exclude the TcpH Peri construct from further experiments. 92 Figure 4.2: TcpH transmembrane constructs have a colonization defect in infant mice. A) Colony forming units per gram of 3-6 day old infant mouse intestine. Infant mice were orally infected with ~1x10 ^6 cells and intestines were harvested 21 hours post infection. Mouse intestines were homogenized, serially diluted, and plated on LB plates containing streptomycin. Asterisk indicates a p-value of less than 0.05. A Mann- Whitney U test was used to determine statistical significance between WT and each TcpH transmembrane construct. The horizontal line indicates the average CFU/gm of intestine and is an average of 5-11biological replicates. Error bars indicate the standard error of the mean. B) Western blots of initial inoculums used to infect infant mice in panel A. C) Relative TcpA levels after 21 h of aerobic growth in sterile mice fecal media (9% w/v). TcpA levels were determined via densitometry, calculated using ImageJ. Averages represent three biological replicates. Error bars represent standard deviation of the mean. A one-tailed Student’s t-test was used to determine statistical significance. * Indicates a p-value less than 0.05 and that there is a statistical difference between WT and the indicated sample. 4.4.3 – The TcpH Transmembrane Domain Protects TcpP from RIP Our data suggests that inhibition of RIP is critical for WT colonization and that TcpP is subject to RIP in vivo when TcpH lacks its normal transmembrane domain. While the TM TcpH constructs do support higher levels of TcpP than a ∆tcpH mutant, it was still unclear if the TM TcpH constructs specifically inhibited RIP of TcpP. In the absence of 93 TcpH, TcpP is sensitive to degradation and undergoes RIP. Loss of both tcpH and yaeL leads to the formation of TcpP*, an intermediate degradation product formed by cleavage of TcpP by Tsp alone. TcpP* lacks most of its periplasmic domain and therefore has a lower molecular weight (19 KDa) compared to WT TcpP (~29 KDa), thus allowing us to determine the RIP status of TcpP via western blot. Inhibition of RIP of TcpP, by a functional TcpH, can be observed by the presence of a full sized TcpP band and no TcpP* band. Alternatively, when RIP is left unchecked, the smaller TcpP* band accumulates. When TcpH, ToxSTcpH, or EpsMTcpH constructs were ectopically expressed in a ∆tcpH/∆yaeL mutant background only full length TcpP was observed (Figure D.4). These data show that RIP of TcpP is inhibited by all TM constructs. Given the in vivo data, these data further suggest that the TM TcpH constructs are unable to inhibit RIP of TcpP in vivo. 4.4.4 – toxT Transcription is Enhanced with Crude Bile and is Dependent on the TcpH Transmembrane Domain Data presented here and other published data indicate that TcpH-dependent RIP inhibition is affected by different in vitro and in vivo environmental signals and that the trans-membrane domain of TcpH is critical for that function (96, 351, 352). Vibrio species use exogenous fatty acids present in bile via the VolA and FadL/FadD pathways (390– 394), resulting in modification of phospholipid composition in Vibrio species, and influencing growth rate, biofilm formation, and motility (394, 395). Given that TcpH and TcpP require membrane localization, we hypothesized that phospholipid changes, stimulated by fatty acids present in the gastrointestinal tract, would stimulate inhibition of RIP via TcpH. 94 To test this we supplemented media with Bovine Crude Bile (0.4%), which contains various fatty acids that have been shown to be incorporated into the bacterial membrane (394), and measured toxT transcription using a plasmid-based transcription reporter (pBH6119-toxT::GFP). In wild type cells, toxT transcription was elevated in the presence of crude bile, while TcpH TM constructs did not support increased toxT transcription (Figure D.5A). This suggested that native TcpH is responding to changes in phospholipid composition to inhibit RIP of TcpP, and that TcpH with the altered transmembrane domain is unable to respond and/or sense the same change. As a negative control, we also measured toxT transcription under non-inducing conditions, known to stimulate RIP of TcpP (96, 351, 352), in these conditions toxT transcription was indeed reduced (Figure D.5A). In addition, we measured toxT transcription in ∆tcpP and ∆tcpH cells with and without crude bile present, and we observed no increase in toxT transcription (Figure D.5A). This indicates that our toxT transcription reporter is accurate, and that the conditions used here do not promote TcpP function in the absence of TcpH. Secondly, we measured toxT transcript levels in WT cells grown in the presence of crude bile via RT-qPCR (Figure D.5B). Similar to our transcription reporter, we observed an increase in toxT transcription. While toxT transcription is elevated in the presence of α-linolenic acid in WT cells, the fold increase in toxT transcription is not the same for both methods used (Figure D.5AB). We believe the difference in the fold increase in toxT transcription when quantifying toxT mRNA, via RT-qPCR, or GFP fluorescence, from the toxT::GFP reporter, is due to the maturation time of GFP molecules (~30 minutes). Additionally, it is unknown if α-linolenic can reduce fluorescence of GFP directly or reduce translation of GFP mRNAs via direct interaction. These are also potential mechanisms could lead to overall 95 reduced increase in toxT transcription observed via the toxT::GFP reporter. Regardless, both methods used to quantify toxT transcription, RT-qPCR and the toxT::GFP reporter, demonstrate that there is a statistically significant increase in toxT transcription in WT cells in the presence of α-linolenic. Lastly, we found that native TcpH and TcpH with an altered TM have similar growth rates in crude bile supplemented Vir Ind media (Figure D.1B). These data support a hypothesis that TcpH responds to host stimuli, specifically fatty acids or constituents of crude bile, and antagonizes RIP of TcpP which in turn leads to increased toxT transcription. Given that elevated toxT transcription requires TcpH to have its native transmembrane domain, we hypothesize that TcpH senses changes in phospholipid composition or membrane fluidity, via its transmembrane domain, to inhibit RIP of TcpP. 4.4.5 – α-Linolenic Acid Enhances toxT Transcription by Promoting TcpH-Dependent Enhanced RIP Inhibition Crude Bile is a mixture of saturated and unsaturated fatty acids, as well as bile salts (e.g., cholate and deoxycholate). We sought to determine whether bile salts or fatty acids in crude bile were responsible for elevated toxT transcription in WT. To test this, we supplemented virulence inducing media with cholate/deoxycholate (Purified Bile) (100µM of each), palmitic acid (500µM), stearic acid (500µM), linoleic (500µM), α-linolenic acid (500µM), arachidonic acid (500µM), and docosahexaenoic acid (500µM). Using the toxT::GFP transcription reporter plasmid, we observed elevated toxT transcription in wild type cells with only crude bile or α-linolenic acid present (Figure 4.3A). Addition of crude bile or α-linolenic acid did not result in increased toxT transcription in ∆tcpH or ∆tcpP cells (Figure 4.3A), demonstrating that TcpH is still needed to inhibit RIP and TcpP is 96 necessary to promote toxT transcription. Lastly, none of the purified components of crude bile resulted in statistically significant increased levels of toxT transcription in cells expressing EpsMTcpH or ToxSTcpH (Figure 4.3A and Figure D.6, respectively). In addition, we also found that α-linolenic acid stimulates toxT transcription in a dose-dependent manner (Figure D.7). To confirm our results, we measured toxT mRNA levels using RT- PCR in WT cells grown under the same conditions. Consistent with the reporter plasmid data, we found that toxT mRNA was elevated in the presence of α-linolenic acid (~2.5 fold) (Figure D.8A). There was no difference in growth rate between WT and the TcpH TM constructs when cultured with α-linolenic acid (Figure D.1D). Considering that cells expressing ToxSTcpH and EpsMTcpH do not colonize mice as well as those expressing native TcpH, these data suggest that TcpH responds to changes in phospholipid composition or membrane fluidity stimulated by α-linolenic acid, and that modifying the TM domain of TcpH renders the protein unable to respond to these changes to enhance inhibition of RIP. 97 Figure 4.3: α-Linolenic acid stimulates toxT transcription, elevated TcpP levels, and does not increase tcpP transcription. A) toxT transcription in WT (black bars) and EpsMTcpH (gray bars) was determined using a plasmid based toxT::GFP transcription reporter. See supplemental methods for information on how V. cholerae 98 Figure 4.3 (cont’d) cells were cultured. toxT transcription was determined by measuring GFP fluorescence (excitation 488nm and emission 515nm) and optical density (600nm). The data here are an average of three or more biological replicates and error bars represent the standard error of the mean. Two-tailed Student’s t-test was used to determine statistical significance. * Indicates a p-value of less than 0.05. B) TcpP levels in WT (black bars) and EpsMTcpH (gray bars) relative to WT cells cultured under virulence inducing conditions (see supplemental methods for details on growth conditions). Densitometry, calculated by ImageJ, was used to determine relative abundance of TcpP. Averages represent three biological replicates. Error bars represent standard error of the mean. Two-tailed Student’s t-test was used to determine statistical significance. * Indicates a p-value of less than 0.05. C) tcpP transcription in WT V. cholerae cells using RT-qPCR, determined via ∆∆CT method. Cells were incubated in Vir Ind for 4hrs and then transferred to indicated conditions for an additional 4hrs. RNA was collected at the 8hr time point. tcpP transcription is relative to WT Vir Ind. Averages represent three biological replicates and error bars represent standard error of the mean. We reasoned that enhanced toxT transcription in the presence of crude bile or α- linolenic acid was due to inhibition of RIP, leading in turn to elevated levels of TcpP. Thus, we quantified TcpP levels under virulence inducing conditions supplemented with crude bile or α-linolenic acid (Figure 4.3B, see Figure D.9 for a view of western blots used to quantify TcpP levels). TcpP levels in wild type cells were significantly elevated in the presence of crude bile or α-linolenic acid (Figure 4.3B). In contrast, TcpP levels in cells expressing EpsMTcpH grown with or without α-linolenic acid were similar (Figure 4.3B). Furthermore, loss of TcpH led to degradation of TcpP under all conditions indicating that Tsp and YaeL activity is not inhibited by the addition of crude bile or α-linolenic acid (Figure D.9). We conclude that i) elevated toxT transcription in the presence of crude bile or α-linolenic acid is due to enhanced inhibition of RIP via TcpH and ii) that altering the phospholipid composition of the cells with exogenous crude bile or α-linolenic acid enhances the TcpH function in RIP inhibition through a mechanism that requires the native transmembrane domain. 99 As TcpP levels are elevated upon supplementation of crude bile or α-linolenic acid, we considered it possible that elevated tcpP transcription could also contribute to elevated TcpP levels. In support of this, linoleic acid has been shown to rapidly diffuse into the cytoplasm of V. cholerae (46, 396). To determine if tcpP transcription is influenced by crude bile or α-linolenic acid we measured tcpP transcription in wild type V. cholerae cells using both RT-PCR and a transcription reporter, tcpP::lacZ. Neither crude bile nor linoleic acid supplementation led to increased tcpP transcription (Figure 4.3C and Figure D.8B). These data indicate that crude bile and α-linolenic acid influence TcpP levels post- transcriptionally supporting the hypothesis that these conditions lead to RIP inhibition by TcpH. We analyzed the fatty acid profile of phospholipids from V. cholerae cells cultured with and without α-linolenic acid to determine if α-linolenic acid is incorporated into the cytoplasmic membrane under our conditions (Figure D.8C). In the presence of α-linolenic acid more than 80% of acyl chains within V. cholerae were 18:3. This is consistent with prior published data (394, 395) and demonstrates that under our conditions V. cholerae cells are remodeling the fatty acid content of their phospholipids. Given that the vast majority of fatty acids detected are 18:3, this data suggests that V. cholerae cells are directly utilizing exogenous α-linolenic acid for phospholipid synthesis (Figure D.8D). 100 4.4.6 – Co-Association of TcpP and TcpH with Detergent-Resistant Membranes is Required for Enhanced RIP Inhibition Collectively these data demonstrate that under conditions that modify phospholipid composition, TcpP levels are enhanced, and toxT transcription is increased. Elevated levels of TcpP are due to enhanced inhibition of RIP by TcpH rather than increased tcpP transcription, and this inhibitory function requires the native TcpH TM domain. In addition to α-linolenic acid, arachidonic and docosahexaenoic acid modify phospholipid composition in V. cholerae (394). Despite causing similar changes to the phospholipid profile, these polyunsaturated fatty acids do not have a significant effect on toxT transcription (Figure 4.3A and Figure D.6). These data indicate the phospholipid profile is not predictive of TcpH dependent inhibition of RIP. Exogenous fatty acids can be utilized directly as acyl chains in de novo phospholipid synthesis (397, 398). Thus, while gross phospholipid composition can remain similar upon supplementation of α- linolenic, arachidonic, and docosahexaenoic acid, (i.e., relative abundance of cardiolipin, phosphatidylglycerol, and phosphatidylethanolamine) the overall biophysical properties of the cytoplasmic membrane (I.e., membrane fluidity) can differ due to differences in acyl chain composition. We reasoned that the differences in observed TcpH-dependent enhanced RIP inhibition could be due to differences in the biophysical properties of the cytoplasmic membrane (I.e., membrane fluidity). Poly-unsaturated fatty acids (PUFA), such as omega-3 fatty acids, have been shown to influence lipid-ordered membrane domains within the cytoplasmic membrane of T-cells (399, 400). Lipid-ordered membrane domains, also called lipid rafts, are regions of the membrane that are enriched in saturated fatty acids, cholesterol (or hopanoids for 101 some bacterial species), and proteins with specific TM domain qualities (typically long TM domain(s) and low surface area) (372, 379, 401). As a result, lipid ordered membrane domains tend to be thicker and less fluid than other areas of the membrane (372). n3- PUFA (i.e., omega-3 fatty acids) increase the size and stability of lipid-ordered membrane domains (372, 399, 400). We hypothesized that TcpP and TcpH molecules are able to associate within lipid-ordered membrane domains and that α-linolenic acid supplementation increases association of TcpP and TcpH molecules with the lipid- ordered membrane domain. Lipid ordered membrane domains, also known as detergent resistant membranes (DRMs), were discovered due to their insolubility in Triton X-100 (376, 402). Triton X-100 has been used in both eukaryotic and prokaryotic organisms to isolate lipid ordered and disordered membrane domains (367–372). Thus, to test our hypotheses we utilized Triton X-100 to separate lipid ordered and lipid disordered membrane domains from cellular lysates. Under Vir Ind conditions, TcpP and TcpH associate with Triton X-100 insoluble (TI; considered to be enriched with lipid ordered membrane domains) and Triton X-100 soluble membrane fractions (TS; considered to be enriched with lipid disordered membrane domains) (Figure 4.4AB). Supplementation with α-linolenic acid resulted in an increase of both TcpP and TcpH in the TI fraction (Figure 4.4AB and Figure D.10). These data support the hypothesis that α-linolenic acid promotes enhanced RIP inhibition by increasing association of TcpP and TcpH with Triton X-100 insoluble membrane domains. Similar to TcpH, EpsMTcpH also associated with both the TI and TS membrane fractions (Figure 4.4CD). In contrast to native TcpH, there was no observable increase in EpsMTcpH 102 levels in the TI fraction upon supplementation of α-linolenic acid (Figure 4.4CD). These data suggest that EpsMTcpH is unable to support enhanced RIP inhibition due to an inability to increase association with lipid ordered membrane domains. Figure 4.4: TcpP and TcpH abundance increases in detergent resistant membranes in the presence of α-linolenic acid. A) Percentage of total TcpP molecules within the Triton soluble (i.e., TS; lipid disordered) and Triton insoluble (i.e., TI; lipid ordered) fractions in WT cells. Percentage of TcpP within the TI and TS fractions was calculated by normalizing to the total amount TcpP in both the TI and TS fractions. Non-normalized TcpP levels were measured via densitometry using ImageJ. B) 103 Figure 4.4 (cont’d) Relative levels of TcpH within the TI and TS membrane fractions measured via densitometry using ImageJ. C) Relative levels of EpsMTcpH in TS and TI fractions measured via densitometry using ImageJ. B and C) Black bars indicate TI and TS membrane fractions collected by spheroplast lysis, and gray bars indicate TI and TS samples collected using a gentle freeze thaw lysis. Cells that were cultured in α-linolenic acid (LA, 500µM) are indicated by +. TcpH and EpsMTcpH levels were normalized to a non-specific band (19KDa) that is equally distributed within TI and TS fractions (see panel D and Figure D.11A). D) Representative western blots of EpsMTcpH TI and TS membrane fractions. Black arrows mark the TcpH bands, and red arrows mark the non- specific band that serves as a loading control. The data here are an average of three or more biological replicates, and error bars represent the standard error of the mean. A two-tailed student's T-test was used to determine statistical significance. * indicates a p-value less than 0.05, and NS indicates a lack of statistical significance (i.e., p-value greater than 0.05). Prior studies revealed that studying lipid ordered membrane domains with this biochemical method can yield dramatically different results with changes in detergent concentration and temperature (403). To determine if our results were robust, we performed the same experiments with an alternative biochemical method to extract lipid ordered membrane domains. By altering the lysis method and the temperature at which cell lysis occurs we found the same TI and TS association trend for TcpH and EpsMTcpH with and without α-linolenic acid present (Figure 4.4BC). We found a shift in the percentage of TcpP molecules present in the TI and TS fraction (~40% of TcpP molecules were present in the TI fraction and the remaining ~60% was present in the TS) under Vir Ind conditions (Figure D.10B). However, upon supplementation of α-linolenic acid to Vir Ind conditions, we found TcpP molecules maintained their preference for the TI fraction despite the change in our extraction method (Figure D.10B). All told, these data suggest that enhanced RIP inhibition occurs due to increased association of both TcpP and TcpH with the TI fraction, and that the TM domain of TcpH drives this association with the TI fraction upon α-linolenic acid supplementation. 104 Excluding EpsMTcpH, it remained unclear if α-linolenic acid supplementation induced a general association of membrane proteins to the TI fraction. To test this, we quantified levels of a loading control, a 19KDa non-specific band, in TI and TS fractions with and without α-linolenic acid (Figure D.11A). We found that there was no change in TI or TS abundance of the loading control with α-linolenic acid supplementation (Figure D.11). These data indicate that α-linolenic acid supplementation does not induce a general association of proteins with the TI fraction. In addition, we took an unbiased approach and characterized the proteome of the TI and TS fractions collected from WT cells (Supplemental File 4.1). Similarly, we found that α-linolenic acid supplementation does not induce a general association with the TI fraction for all proteins detected. Furthermore, we also found that with α-linolenic acid supplementation the TI fraction had a higher association of 16:0 fatty acids and lower association of 18:3 fatty acids than the TS fraction (Figure D.11B). This is consistent with prior studies that indicate that lipid ordered membrane domains are enriched with saturated fatty acids (377). 4.4.7 – TcpP and TcpH Interaction is critical for inhibition of RIP Our data indicate that increased association of TcpP and TcpH molecules in the TI fraction results in enhanced RIP inhibition. The mechanism underlying this RIP inhibition remains unclear. Prior studies have indicated that lipid-ordered membrane domains (which are also Triton insoluble) function as protein concentrators and thereby promote interaction between membrane localized proteins (50). We hypothesized that enhanced co-association within the TI fraction increased RIP inhibition due to direct interaction between TcpP and TcpH. To test direct TcpP-TcpH interaction, we used a co- affinity precipitation approach. We genetically fused a His(6x)-Hsv or Hsv-His(6x) tag to 105 the C-terminus and N-terminus, respectively, of TcpP, resulting in tcpP-His-Hsv and Hsv- His-tcpP. We could then extract TcpP from membrane fractions using NTA-Ni beads and identify TcpH and TcpP in elution fractions with ɑ-TcpH and ɑ-Hsv antibody. Proteins tagged at the amino-terminus are described with the tag noted first (e.g., Hsv-His-TcpP), while those tagged at the carboxy-terminus are described with the tag noted second (e.g., TcpP-His-Hsv). First, we tested if both the N- and C- terminally-tagged proteins (Hsv-His-TcpP and TcpP-His-Hsv, respectively) function like native TcpP by measuring CtxB production after induction of the fusion proteins with arabinose under Vir Ind conditions. CtxB production was similar to that from cells expressing native TcpP, irrespective of which terminus the tag was placed (Figure D12). Co-precipitation experiments indicated that the C-terminally-tagged TcpP could associate with TcpH, while the N-terminally-tagged TcpP could not (Figure 4.5AB). Physical interaction between the C-terminally tagged TcpP and TcpH also correlated to protection from RIP, as determined by assessing the stability of the tagged proteins in cells expressing the first-site RIP protease Tsp but lacking the second protease YaeL. In such cells, the product of Tsp action on TcpP accumulates in the cell because the second- site protease YaeL is not present to eliminate it (26, 27). We observed greater accumulation of TcpP degradation intermediates (between 24KDa and 19KDa) in cells expressing N-terminally-tagged-TcpP compared to those expressing C-terminally-tagged TcpP (Figure 4.5C). The 24 kDa TcpP degradation intermediate from N-terminally-tagged TcpP is also observed in cells expressing native TcpP in the absence of TcpH (Figure 4.5CD). Considering that the N-terminally-tagged TcpP is sensitive to RIP even with TcpH 106 present suggests a defect in its association with TcpH and its recognition by the RIP proteases. Despite this defect, N-terminally-tagged TcpP is capable of supporting WT CtxB production (Figure D12). We believe that this is the result of overexpression of N- terminally-tagged TcpP. Native expression of TcpP leads to accumulation of only TcpP* in a ΔtcpH ΔyaeL background (Figure D.4), but overexpression of TcpP in a ΔtcpP ΔtcpH ΔyaeL background yields both full length and TcpP* (Figure 4.5D). These data indicate that artificial elevation of TcpP levels, via overexpression, can outpace RIP of TcpP. These data also indicate that TcpP-His-Hsv, compared to Hsv-His-TcpP, is less sensitive to RIP in the presence of TcpH. Prior studies have demonstrated that modification of the C-terminus of TcpP can lead to TcpH-independent resistance to RIP (78). To determine if the addition of His-Hsv to the C-terminus of TcpP promotes resistance to RIP independent of TcpH we expressed tcpP-His-Hsv and tcpP in a ΔtcpP ΔtcpH ΔyaeL background. We found that TcpP* accumulated in both tcpP or tcpP-His- Hsv expressing cells (~17KDa) (Figure 4.5D). These data show that addition of His(6x)- Hsv to the C-terminus of TcpP does not abrogate the need for TcpH to protect TcpP-His- Hsv from RIP (Figure 4.5D). In summary, our data indicates that TcpP and TcpH interact and that TcpP-TcpH interaction is important for inhibition of RIP of TcpP. It remains unclear why Hsv-His-TcpP is unable to interact with TcpH. Our prior single-molecule tracking studies indicate that TcpP may be sensitive to RIP while interacting with the toxT promoter (74). The Hsv tag is enriched with negatively charged amino acids (Hsv amino acid sequence: QPELAPEDPED). Given that DNA has an intrinsic negative charge, the addition of Hsv-His(6x) to the N-terminus of TcpP may promote a conformation that is similar to the conformation that TcpP molecules adopt 107 when actively interacting with DNA. It remains unclear if this is the case and requires additional experiments to test this hypothesis. Figure 4.5: TcpP and TcpH interaction is critical for TcpH-dependent inhibition of RIP. A and B) Co-affinity precipitation of ectopically expressed tcpP-His-HsV (A), Hsv- His-tcpP (B). The data here represent three biological replicates. Triton soluble (TS). C) Ectopic transcription of Hsv-His-tcpP and tcpP-His-HsV in ΔyaeL cells under virulence inducing conditions. Hsv-His-TcpP is more sensitive to RIP than TcpP-His- Hsv, as seen by accumulation of TcpP degradation intermediates between 26 and 19 kDa. D) Ectopic transcription of tcpP and tcpP-His-HsV in ΔtcpP ΔtcpH ΔyaeL cells under virulence inducing conditions. Samples were probed with α-TcpP (top) and α- Hsv (bottom) antibodies. TcpP-His-Hsv remains sensitive to RIP as accumulation of TcpP* is observed in tcpP-His-Hsv expressing cells, similar to TcpP. *: indicates accumulation of TcpP*. A-D) tcpP constructs were all ectopically expressed from pBAD18 using arabinose (Ara 0.1% w/v). + indicates arabinose was added to the culture. Samples presented here represent three biological replicates. 108 4.4.8 – Miltefosine Functions Synergistically with α-Linolenic acid Staphylococcus aureus relies on lipid ordered membrane domains to recruit and promote oligomerization of flotillin, which in turn promotes antibiotic resistance (45). Miltefosine, a drug used to treat Leishmaniasis and certain types of cancers, inhibited flotillin association with lipid ordered membrane domains in S. aureus (45, 75). Our data indicate that α-linolenic acid enhances toxT transcription by promoting association of TcpP and TcpH molecules within lipid ordered membrane domains. We hypothesized that miltefosine treatment would inhibit TcpH dependent enhanced RIP inhibition in the presence of α-linolenic acid. Instead, we observed that miltefosine alone functioned similar to α-linolenic acid (Figure D.13A). Treatment with both miltefosine and α-linolenic acid resulted in a ~7-fold increase in TcpP levels relative to Vir Ind conditions (Figure D.13B). Our data also demonstrate that miltefosine also promoted association of TcpP molecules with the TI fraction like α-linolenic acid (Figure D.13C). Miltefosine did not promote toxT transcription in ΔtcpH and EpsMTcpH cells (Figure D.13A). Taken together, these data indicate that miltefosine functions synergistically with α-linolenic acid to increase levels of TcpP in V. cholerae and is not effective at inhibiting lipid ordered domain formation in V. cholerae. Miltefosine is known to associate with lipid ordered domains and requires lipid ordered domains to enter cells (76, 77). Secondly, miltefosine has also been shown to increase membrane fluidity (78). Other n3-PUFA, similar to α-linolenic acid, are also capable of increasing membrane fluidity, and they have been shown to drive aggregation and stabilization of lipid ordered membrane domains (47, 69, 70). Given that miltefosine and α-linolenic acid function synergistically to promote TcpH-dependent 109 antagonism of RIP, these data suggest that α-linolenic acid promotes lipid ordered domain aggregation, and thereby increases lipid ordered domain size in V. cholerae cells. 4.5 – Discussion Canonical RIP systems act by releasing an anti-sigma factor from the cytoplasmic membrane to influence gene transcription. Many membrane localized transcription regulators (MLTRs), in addition to TcpP and ToxR, are sensitive to RIP (e.g., CadC) (165, 272). However, RIP of MLTRs, such as TcpP, results in their inactivation, typically leading to decreased gene transcription. The fundamental mechanisms of RIP for TcpP are understood, in terms of the primary proteases that work in the two-step pathway (351, 352), but many of the regulatory mechanisms influencing these have been less well understood. It is clear that TcpH is essential to inhibit RIP of TcpP, and that its ability to protect TcpP from RIP changes in response to temperature and pH (96, 351, 352). ToxR is a well-studied MLTR, similar to TcpP and is sensitive to RIP (57, 404). ToxR is protected from RIP by ToxS, a single pass transmembrane protein analogous to TcpH (80, 343). Prior work indicates that: i) ToxR undergoes RIP during late stationary phase (i.e., alkaline pH and nutrient limiting conditions); ii) ToxS antagonizes RIP of ToxR via direct interaction; and iii) deoxycholate increases interaction between ToxR and ToxS (79, 83, 85, 405). Similar to what is understood about ToxR, our data indicate that RIP of TcpP is inhibited by direct interaction with TcpH. Our data indicate that α-linolenic acid, a host dietary fatty acid, plays a role in inhibiting RIP by increasing the local concentration of TcpP and TcpH within detergent resistant membranes (DRM) (I.e., lipid ordered membrane domains). Whether this fatty acid plays any role in ToxR RIP inhibition remains to be discovered. 110 α-Linolenic acid is an essential omega-3 fatty acid used to synthesize arachidonic and docosahexaenoic acid humans and mice (406, 407). α-Linolenic acid is acquired via dietary supplementation and is present in milk, meats, dairy products, soybean oil, and plant seeds (e.g., pomegranate, tung seeds, rapeseed, flak seed, and marigold seeds) (408–414). It is considered a beneficial dietary fatty acid as it is a precursor to omega-3, omega-6, and conjugated α-linolenic acids, and has health benefits ranging from anti- carcinogenic, anti-atherogenic, anti-inflammatory, improved memory, and anti-diabetic activity (415–423). V. cholerae uses exogenous long-chain fatty acids, such as α-linolenic acid, to remodel its phospholipid composition (394, 395). Long-chain fatty acids are transported across the outer membrane by FadL into the periplasmic space where FadD covalently modifies the fatty acids by adding an acyl-CoA group, resulting in formation of long-chain fatty acyl-CoA (LCFA-CoA) (390–393). LCFA-CoAs then bind to FadR, the principal regulator of fatty acid biosynthesis in V. cholerae, resulting in a conformational change inhibiting FadR from binding to DNA (424–426). This leads to decreased biosynthesis of unsaturated fatty acids (i.e., decrease in fabAB transcription) and increased transcription, due to a lack of repression by FadR, of genes required for transport, activation, and beta-oxidation of long-chain fatty acids (i.e, fadL, fadD, fadBA, fadE, and fadH) (424–426). Utilization of exogenous fatty acids remodels phospholipid composition in Vibrio spp. (394, 395, 427) and has an impact on pathogenicity, motility, and antibiotic resistance via unknown mechanisms (395). Our work demonstrates that: i) toxT transcription is enhanced in the presence of α-linolenic acid; ii) TcpP levels are significantly elevated in the presence of α-linolenic acid; iii) the tcpP transcript level is not 111 increased with exogenous α-linolenic acid; iiiv) TcpP and TcpH avidly associate within detergent resistant membranes (DRM; hypothesized to be lipid-ordered domains) in the presence of α-linolenic acid; v) TcpP and TcpH interaction is important for inhibition of RIP; and vi) enhanced toxT transcription in the presence of α-linolenic acid is dependent on co-association of TcpP and TcpH in the DRM membrane fraction. Our data support a model where, once present in the gastrointestinal tract, V. cholerae cells take up and incorporate α-linolenic acid into phospholipids, thereby altering the composition of the cytoplasmic membrane. This influences TcpH and TcpP molecules to increase their association with lipid ordered membrane domains via an unknown mechanism. N-3 polyunsaturated lipids (i.e., omega-3 fatty acids) are known to increase lipid ordered domain size in eukaryotes by promoting aggregation of existing lipid ordered membrane microdomains (399, 400). As lipid ordered membrane domains are known to be relatively small in size (10-200 nm) (373), this may lead to an increase in the local concentration of TcpP and TcpH molecules thereby allowing TcpH to enhance RIP inhibition of TcpP via direct interaction with TcpP (Figure 4.6). 112 Figure 4.6: α-Linolenic acid stimulates co-association of TcpP and TcpH within detergent resistant membranes thereby enhancing TcpH inhibition of RIP. Under virulence inducing (Vir Ind) conditions (LB pH6.5, 30⁰C, 110rpm) TcpH inhibits RIP of TcpP and toxT transcription is stimulated. Under these conditions, TcpP and TcpH 113 Figure 4.6 (cont’d) molecules are associated with lipid-ordered (blue) and lipid-disordered (red) membrane domains. A) in WT cells TcpP and TcpH molecules associate with both lipid ordered and lipid disordered membrane domains, and C) a similar trend is observed for TcpH transmembrane constructs (TMTcpH). B and D) When α-linolenic acid is present V. cholerae cells have been shown to uptake it (via FadL/FadD) and this leads to changes in the overall phospholipid profile of V. cholerae, indicated by the blue and orange phospholipids (391, 392, 428, 429). Polyunsaturated fatty acids, such as α-linolenic acid, have also been shown to increase lipid ordered domain size by stimulating aggregation of small lipid ordered domains (430, 431). B) Under these conditions, a majority of TcpP and TcpH molecules transition to lipid ordered membrane domains leading to enhanced inhibition of RIP by TcpH. The net result of α-linolenic acid supplementation is an increase in toxT transcription, indicated by an increase in red toxT mRNA. D) Modification of TcpH transmembrane domain prevents TcpH molecules from transitioning to lipid ordered domains in the presence of α-linolenic acid, likely due to increased surface area and shorter length of the transmembrane domain. This inhibits TcpH from enhanced inhibition of RIP and does not result in an increase in toxT transcription. Previous studies have investigated the role of exogenous fatty acids on the pathogenesis of V. cholerae. These concluded that FadD is required for wild-type toxT transcription through a mechanism involving its effect on TcpP levels (432, 433). These prior publications support our model as accumulation of α-linolenic acid in the periplasmic space or within the cytoplasmic membrane, due to loss of fadD, results in a reduction in TcpP levels, rather than an increase (432, 433). This work indicates that free α-linolenic acid (i.e., not incorporated in phospholipids) within the periplasmic space, cytoplasm, or within the cytoplasmic membrane, does not promote TcpH mediated inhibition of RIP. When considering this with the data presented here, this indicates that α-linolenic acid needs to be incorporated into the cytoplasmic membrane as a phospholipid to have any effect on TcpH function. Lipid ordered and lipid disordered membrane domains were discovered due to the insolubility of the lipid ordered membrane domain (initially referred to as detergent 114 resistant membranes) in Triton X-100 and other non-ionic detergents (376, 402). This biochemical method has been used to separate lipid ordered (DRM) and lipid disordered (DSM) membrane domains in many Eukarya and Bacteria, including Gram-negative and Gram-positive bacteria (367–372). Data generated from the biochemical-based separation of lipid ordered and lipid disordered membrane domains has been verified by alternative methods (e.g., fluorescent microscopy, single-molecule tracking, and synthetic membrane vesicles) (434). Due to a lack of literature on lipid ordered and lipid disordered membrane domains in V. cholerae, we performed additional experiments to determine if our biochemical extraction method faithfully enriched for lipid ordered membrane domains and lipid disordered membrane domains within the DRM and DSM (I.e., TI and TS) respectively. In the presence of α-linolenic acid, we found that the TI fraction had a higher association of 16:0 fatty acids and a lower association of 18:3 fatty acids compared to the TS fraction (Figure D.11B). These characteristics are consistent with lipid ordered membrane domain and suggest that the TI and TS fractions presented here are enriched in lipid ordered and lipid disordered membrane domains respectively. Transmembrane domain length and surface area are major factors in determining the preference of a protein for lipid ordered (enriched with proteins having longer TM domain and low surface area) or lipid disordered (enriched with proteins having shorter TM domain and high surface area) membrane domains (435). We demonstrated that native TcpH and TcpP increase localization within the lipid ordered membrane domain in the presence of α-linolenic acid while EpsMTcpH does not (Figure 4.4). EpsMTcpH has a shorter TM domain than TcpH (20 amino acids vs 22 amino acids) and a higher overall surface area (108 Å2 vs 92 Å2), see reference for TM domain surface area calculations 115 (436). Thus, we hypothesize that the TM domain properties of EpsMTcpH molecules inhibit its transition from the TS fraction to the TI fraction in the presence of α-linolenic acid. Alternatively, it is also possible that TcpH, and not EpsMTcpH, undergoes post-translational modification (e.g., palmitoylation) within its TM domain. We view this as unlikely as TcpH is not predicted to have a palmitoylation site within its TM domain. In addition, it also appears that the surface area of the transmembrane domain of TcpP influences its function. Prior analysis of TcpP transmembrane domain revealed that mutation of L152 and W162/S163 with alanine (which reduces the overall surface area of the transmembrane domain) increased toxT transcription (437). It remains unclear why these mutations increase TcpP function, but given the data presented here, it is possible that TcpPL152A and TcpP W162A/S163A may have a greater propensity than TcpP to associate within DRMs (i.e., lipid ordered membrane domain). Based on our data and the literature, we hypothesize that phospholipid remodeling of V. cholerae occurs in the lumen during the initial stages of infection. Our data suggests that this remodeling promotes TcpH mediated inhibition of RIP and promotes toxT transcription. However, unsaturated fatty acids are also known to inhibit degradation and activity of ToxT (i.e., inhibit tcpA-F and ctxAB transcription) (46, 396). This likely prevents premature transcription of TCP which is known to stimulate microcolony formation and thereby could inhibit penetration of the mucus layer (438). Bicarbonate, which is present at high concentrations at the surface of epithelial cells, competes with unsaturated fatty acids to activate ToxT once V. cholerae reaches the surface of epithelial cells, its primary site of infection (48, 50, 439). There is also evidence that bicarbonate represses toxT transcription (439). This indicates that transcription of toxT, stimulated by enhanced RIP 116 antagonism, during early infection (i.e., the lumen) is critical for V. cholerae to cause disease. This adds a new level of regulation to the ToxR regulon and yet another dietary host factor that modulates toxT transcription in V. cholerae. α-linolenic acid represents the first in vivo signal that modulates RIP of TcpP, and, to the best of our knowledge, the first evidence that lipid ordered and lipid disordered membrane domains exist in V. cholerae. The data presented here further expands our knowledge of the complex virulence regulatory cascade in V. cholerae. 117 Chapter 5– Concluding Remarks 118 5.1 – Conclusions and Significance Signal transduction is essential for organisms to respond and adapt to their environments. Mechanisms of signal transduction in prokaryotic organisms are composed of one-component, two-component, and anti-sigma factor signal transduction systems (88–91). Membrane localized transcription regulators (MLTRs) are unique one- component regulators that manage to influence gene transcription from the cytoplasmic membrane. Within V. cholerae, two MLTRs, TcpP and ToxR, positively regulate toxT transcription thereby promoting virulence (39–41, 52–55). Due to their sub-cellular localization both TcpP and ToxR are sensitive to Regulated Intramembrane Proteolysis (RIP) (56, 58, 59, 80, 440). Prior to the work presented in Chapter 2 and Appendix B the prevalence and diversity of MLTRs within the prokaryotic domain was not known. We demonstrate that MLTRs are more prevalent and diverse among prokaryotes than previously understood. Our analysis revealed that MLTRs in Gram-negative bacteria are more likely to have a TcpH/ToxS-like associated protein, and MLTRs within Gram-positive organisms are more likely to have more than one transmembrane domain. Our data indicate that specific genera are enriched with MLTRs. This work emphasizes that MLTRs represent a class of one-component regulators that are understudied and represents a large gap in our knowledge of signal transduction in the prokaryotic domain. One of the fundamental questions regarding MLTRs is how they manage to influence gene transcription from the cytoplasmic membrane. Using TcpP as a model MLTR, we addressed this gap in knowledge in Chapter 3 by using super-resolution single- molecule tracking (SMT) to measure the biophysical properties of individual TcpP molecules. We found that TcpP molecules exist in three biophysical states (fast, 119 intermediate, and slow), and we also found that TcpP molecules are unable to transition directly between the slow and fast diffusion states. Secondly, we found that the native level of ToxR does not drive the ordered transition of TcpP molecules between its diffusion states. Artificial elevation of the ToxR level was found to promote transition of TcpP molecules away from the toxT promoter, reducing downstream virulence factor production. Our data describe the first biophysical model of promoter association between an MLTR and its target promoter. Lastly, the unusual localization of MLTRs exposes them to unique forms of post- translational regulation compared to cytoplasmically-localized one-component regulators. TcpP and ToxR are both sensitive to Regulated Intramembrane Proteolysis (RIP), which is a form of post-translational regulation (56, 58, 59, 80, 440). Prior to this work, it was clear that RIP of TcpP is inhibited in vivo, but it was unknown what signals in vivo contributed to this. In Chapter 4, we present data demonstrating that α-linolenic acid, a dietary fatty acid, promotes inhibition of TcpP RIP via co-association of TcpP and TcpH within detergent-resistant membrane domains. These data are the first to identify an in vivo signal that stimulates inhibition of TcpP RIP, the first data indicating that detergent- resistant membranes influence signal transduction within V. cholerae, and the first direct evidence that TcpH inhibits RIP of TcpP via direct interaction. 120 5.2 – Future Directions The work presented here demonstrates that there remain major gaps in our knowledge regarding MLTRs. Gaining deeper insight into MLTR function will increase our knowledge of bacterial signal transduction. To understand MLTRs at a deeper level we first need to understand what genes can be regulated by MLTRs. The bacterial chromosome is an ordered and dynamic structure that is not thought to be freely available to the cytoplasmic membrane (308–317). Furthermore, the evolution of two-component signal transduction regulators implies that there are genes unavailable to the cytoplasmic membrane. We hypothesize that genes directly regulated by MLTRs are encoded near genes for integral membrane proteins and that transertion of the neighboring membrane protein drives association of the target gene and its MLTR. To test this hypothesis bioinformatic analysis of the genetic neighborhood of MLTR genes across bacterial species would be critical. In addition, experimental evidence would also be required. Alteration of the genetic coordinates of the toxT promoter to different areas of the chromosome with distant (>10 Kbp) or close to integral membrane proteins within V. cholerae would also be required. Currently, we have a working model for how TcpP, and possibly other single pass MLTRs, functions to find the toxT promoter from the work presented in Chapter 3. In the future we plan to investigate how host factors (such as bile salts, bicarbonate, temperature, pH, dietary fatty acids, and microbiota derived chemicals and proteins) influence TcpP single molecule dynamics. However, this requires that we have a deeper understanding of the biological role of the intermediate diffusion state. 121 One possibility is that TcpP molecules are non-specifically interacting with chromosomal DNA within the intermediate diffusion state. Given that there is no definitive evidence that TcpP directly regulates genes in addition to toxT, combined with the fact that deletion of the entire toxT promoter or mutation of the DNA binding domain of TcpP (i.e., TcpP[K94E]) has little effect on the intermediate diffusion state, we view this hypothesis as unlikely. However, this hypothesis could be tested by increasing the number of toxT promoter copies, either plasmid encoded or on the chromosome. If the intermediate diffusion state is occupied by TcpP molecules non-specifically interacting with DNA then the overall occupancy of this diffusion state would reduce by increasing the number of specific promoter targets (i.e., the toxT promoter). Secondly, if the intermediate diffusion state is occupied by TcpP molecules interacting with DNA then by restricting interaction between the cytoplasmic membrane and chromosomal DNA, via treatment of cells with chloramphenicol, this would also reduce the total percentage of TcpP molecules within the intermediate diffusion state. However, it is also possible that TcpP molecules within the intermediate diffusion state do not interact with DNA at all. SMT studies have consistently shown that TcpP molecules must enter the intermediate diffusion state to interact with the toxT promoter. This suggests that the conformation of the cytoplasmic domain of TcpP molecules in the fast diffusion state is fundamentally different from TcpP molecules within the intermediate diffusion state. Considering this hypothesis, this raises two additional hypotheses regarding how the transmembrane domain may impact the cytoplasmic domain of TcpP molecules in the intermediate diffusion state: 1) TcpP molecules within the intermediate diffusion state are associated with detergent resistant membrane (DRM) domains (i.e., 122 lipid rafts) and, due to reduced membrane fluidity and increased membrane thickness, this alters the conformation of the cytoplasmic DNA-binding domain thereby promoting interaction with the toxT promoter; and 2) TcpP molecules within the intermediate diffusion state associate with an unknown high molecular weight membrane localized protein complex, composed of one or more proteins, and this in turn influences the conformation of the cytoplasmic DNA-binding domain thereby promoting interaction with the toxT promoter. Testing these hypotheses will require a range of different experiments. Regarding our primary hypothesis, defining the regions of the chromosome TcpP is capable of interacting with, likely via chromatin immunoprecipitation sequencing (ChiP), will be critical to determine if TcpP is capable of regulating additional genes. To investigate the biological role of the intermediate diffusion state, defining the protein interaction network of TcpP molecules, using a combination of coimmunoprecipitation and proteomics, will be critical to decipher the biological function of the intermediate diffusion state. Interaction between TcpP and high molecular weight membrane localized protein(s) would indicate that these interactions occur within the intermediate diffusion state. To determine if this potential TcpP-protein interaction is relevant to biophysical dynamics of TcpP molecules, deletion of the gene encoding the high molecular weight protein(s) followed by investigation of TcpP single molecule dynamics will be required. If interaction between TcpP and an unknown high molecular weight protein is promoting transition of TcpP molecules from the intermediate diffusion state to the slow diffusion state, I would minimally expect the rate of transition between the intermediate and slow diffusion state to decrease upon deletion of the gene for the 123 high molecular weight protein. It is also likely that, if critical for TcpP molecules to efficiently interact with the toxT promoter, deletion of this unknown high molecular weight protein would result in the loss of the intermediate diffusion state altogether and thereby reduce virulence factor production. Lastly, it is also possible that TcpP molecules within the intermediate diffusion state alter the conformation of their DNA binding domain due to local membrane properties. In Chapter 4, we demonstrate that TcpP molecules are capable of associating with DRM and detergent soluble membranes (DSM). DRM are also known as lipid ordered membrane domains (i.e., lipid rafts), and these membrane domains have been described as possessing a lower degree of membrane fluidity and an increase in thickness relative to detergent soluble membranes. To test this hypothesis, alteration of the TcpP transmembrane domain (i.e., decrease the total length and increase the overall surface area) will be required to reduce the affinity of TcpP molecules with DRM. If association of TcpP molecules within DRM is critical for transition of TcpP molecules from the intermediate diffusion state to the slow diffusion state then alteration of the TcpP transmembrane domain (i.e., decrease the total length and increase the overall surface area) will reduce the rate of transition between these biophysical states. Additionally, this would also reduce toxT transcription and production of downstream virulence factors. From the work presented here we have uncovered substantial knowledge regarding how TcpP locates the toxT promoter. From work discussed in Chapter 4, we have also gained significant insights into the mechanism by which TcpH inhibits RIP of TcpP. Our data indicate that TcpH protects TcpP from RIP via direct interaction, interaction between TcpP and TcpH likely occurs in both DRM and DSM, and that TcpP- 124 TcpH interaction occurs via different mechanisms within DRM and DSM. More specifically, our data suggest that the C-terminus of TcpP must be available for TcpP- TcpH interaction to occur and for elevated toxT transcription in the presence of α-linolenic acid. Due to low specificity of our TcpP and TcpH anti-serum we are unable to perform coimmunoprecipitation experiments with native TcpP and TcpH. Thus, we require a different approach to determine if TcpP and TcpH molecules interact via different residues within DRM and DSM. Future experiments to define the precise mechanism of interaction between TcpP and TcpH within DRM and DSM will require purification of TcpP-His-Hsv, TcpH-His-Hsv, and Hsv-His-Tsp. Prior to cleavage of the His-Hsv tag, the TcpP-His-Hsv and TcpH-His- Hsv molecules will be reconstituted together into synthetic liposomes. Once TcpP and TcpH molecules are reconstituted into liposomes, confirmation of function and orientation of TcpP and TcpH molecules will be required. To confirm the orientation of TcpP and TcpH within liposomes, liposomes containing TcpP-His-Hsv or TcpH-His-Hsv will be purified using anti-Hsv antibodies conjugated to A-sepharose beads. This purification will yield only liposomes containing TcpP or TcpH molecules with their C-termini on the exterior of the liposome. Once purified, the His-Hsv tag will be cleaved from TcpP-His- Hsv and TcpH-His-Hsv. To confirm TcpH function, purified Tsp will be added to TcpP/TcpH containing liposomes buffered with low pH (pH 6.5) or alkaline pH (pH8.5). If reconstituted TcpP molecules are resistant to Tsp proteolysis at low pH (in the presence of TcpH) and sensitive to Tsp proteolysis at alkaline pH it would indicate that purified TcpH remains functional. We will also test if purified TcpP molecules are able to interact with the toxT promoter using electromobility shift assays. If we are able to confirm that 125 TcpP and TcpH remain functional when purified and reconstituted into a liposome, this would allow us to manipulate the liposome environment to further test our hypothesis that association of TcpP and TcpH within DRMs enhances TcpH-dependent inhibition of RIP, and allow us to determine if TcpP and TcpH interact via different residues, by mutating specific residues, within DRM and DSM. 126 APPENDICES 127 APPENDIX A: Supplemental Material for Chapter 2 128 A.1 – Supplemental Tables and Figures Table A.1. Characterized MLTRs and their known cellular response and associated proteins. `: indicates this MLTR is not discussed at length in the main text. *: indicates that 01/0139 classical and El Tor biotypes encode tcpPH within their genomes. #: indicates that there are possible TcpH/ToxS-like gene that is uncharacterized immediately upstream or downstream of the indicated MLTR. Associated MLTR Organisms Cellular Response References Protein (39–41, 53, Bile salt resistance, cationic 55, 71, 72, Vibrio spp. antimicrobial peptides, 104, 120, ToxR Photobacterium pressure response, biofilm ToxS 124–127, spp. formation, and virulence 207, 441– factor transcription 443) Virulence factor (toxT Vibrio cholerae* transcription), motility, (52, 96, TcpP and Vibrio chemotaxis, and reduction TcpH 143, 351, fischeri of extracellular 352) polysaccharides Vibrio spp. (107, 156– Escherichia spp. 160, 163, CadC Acid resistance LysP Salmonella spp. 164, 166, Yersinia spp. 444, 445) TfoS Vibrio spp. Natural Competence Na (110, 167) (101, 102, VtrA/VttrA Vibrio spp. Type-3 secretion systems VtrC 148, 154, 155) Vibrio spp. (101, 102, VtrB/VttrB Type-3 secretion systems Na Salmonella spp. 149) Salmonella spp. (181, 190, MarT Fibronectin binding # Yersinia ruckeri 234, 235) Promotes transcription of GvrA Escherichia coli LEE in response to Na (184, 203) bicarbonate Serum resistance, flagella YqeI Escherichia coli synthesis, and host cell YqeJ (186) adhesion 129 Table A.1 (cont’d) (221, 224, PsaE Yersinia pestis Fimbriae transcription PsaF 230) Yersinia MyfE Fimbriae transcription MyfF (231–233) enterocolitica Yersinia Flp type IVb pillin PypB enterocolitica and # (239) transcription Yersinia ruckeri Enterococcus spp. (106, 246– BcrR Bacitracin resistance Na Lactobacillus 248) spp. Lactobacillus spp. BreG Bacteriocin synthesis Na (242, 253) Enterococcus spp. Enterococcus (243, 257– AguR Acid tolerance Na spp. 259) Enterococcus spp. LP_2991 Immune modulation Na (114, 267) Lactobacillus spp. Lactobacillus Hydroxycinnamic acid HcrR Na (103, 279) planatarium metabolism Lactobacillus MmsR Isobutyryl-CoA metabolism Na (112) bifermentans Staphylococcus spp. Enterococcus Virulence factors, phosphate MtbS Na (285) spp. transport, tRNAs, etc. Lactobacillus spp. Staphylococcus NanR Sialic acid metabolism Na (112, 113) spp. Type IV pilin, pigmentation, Pseudomonas iron uptake, amino acid WmpR` Na (446, 447) tunicate metabolism, biofilm formation, and anti-fouling 130 Table A.2: Membrane localized transcription regulators (MLTRs) within the Vibrio genus. Underlined MLTRs had a minimum percent identity of 25% or greater to their respective MLTR. MLTRs with “” were previously characterized. *: indicates that the MLTR has a TcpH/ToxS like gene immediately upstream or downstream of its coding sequence. &: indicates that the MLTR has an unknown multi-transmembrane (YitT-like) gene immediately upstream or downstream of its coding sequence. #: indicates that the MLTR has a similar primary sequence structure to TcpP, ToxR, and CadC but lacks sequence homology. # of MT- Uncharacte Organism ML TcpP ToxR CadC TfoS VtrA VtrB MLTR rized TR Vibrio VC0826 VCA0 cholerae 01 5 VC0984* VC0278 VC2080 * 926 El Tor Vibrio cholerae RS0710 AVK7916 RS1857 RS1370 RS015 5 0395 5* 0.1* 5 0 10 Classical Vibrio cholerae RS1576 RS0224 RS03 RS03 RS085 AM-19226 5 5 5 865* 800 60 (non- 01/0139) Vibrio cholerae RS1305 RC385 1 0 (non- 01/0139) Vibrio RS0097 RS0610 RS23 RS24 parahaemol 5 VP0820 0 0 940 000 yticus Vibrio SQA465 RS1021 RS1528 RS20210 4 alginolyticus 27.1 0 5 RS14510# 131 Table A.2 (cont’d) RS07705 Vibrio RS0099 RS0645 RS11 6 RS06270 RS25150 campbellii 0 0 600* * Vibrio RS1725 RS129 diazotrophic 3 RS02285 5 20 us VF_A04 VF_206 73* 0 VF_A08 VF_111 Vibrio 60* VF_0791 6 VF_083 9 VF_1086* fischeri * VF_A02 2 59$ VF_A03 04 RS26105 Vibrio RS3285 RS27 RS233 6 RS39125 RS33410* fluvialis 5 425 40 * Vibrio RS13720 RS0204 2 gazogenes * 0 RS1879 RS13975 0 RS1884 RS12645# 0 Vibrio RS1826 RS2290 11 RS12640# mediterranei 0 5 RS0537 RS06645*# 0& RS25540*# RS19560*# RS15940 Vibrio * RS0325 RS148 proteolyticu 5 RS18455 RS02825 5 70 s * Vibrio RS12130 RS1193 3 RS12725&# vulnificus * 0 132 Table A.3: Membrane localized transcription regulators (MLTRs) within the Escherichia and Salmonella genera. Underlined MLTRs had a minimum percent identity of 25% or greater to their respective MLTR. MLTRs with “” were previously characterized. *: indicates that the MLTR has a TcpH/ToxS like gene immediately upstream or downstream of its coding sequence. !: Fimbriae genes encoded immediately upstream or downstream of its coding sequence. #: indicates that the MLTR has a similar primary sequence structure to TcpP, ToxR, and CadC but lacks sequence homology. %: possible motility gene regulator (211). ^: Probable Type-3 secretion system regulator (214). STM1575 does contain a C-terminal transmembrane domain, but is predicted to encode a null protein within the MIST database and as such was not included in our analysis. Number Organism VtrB-like CadC-like MarT-Like Uncharacterized of MLTFs Escherichia coli ECs1274* 4 “ECs5115” ECs0796 O157:H7 ECs3704* RS07670 Salmonella enterica RS00085 subsp. enterica 6 RS00150! RS13195 RS18610* serovar Enteritidis RS00160^ RS07670% Salmonella enterica STM0017 subsp. enterica 4 STM0029 “STM3759*” serovar STM0031^ Typhimurium Salmonella enterica subsp. enterica 3 STY0035! STY2804 STY0017 serovar Typhi Salmonella enterica subsp. enterica 1 RS18300* serovar Paratyphi Salmonella enterica RS01180^ subsp. enterica 5 RS01170! RS14145 RS20100* RS01105 serovar Newport 133 Table A.4: Membrane localized transcription regulators (MLTRs) within the Yersinia genus. Underlined MLTRs had a minimum percent identity of 25% or greater to their respective MLTR. MLTRs with “” were previously characterized. *: indicates that the MLTR has a TcpH/ToxS like gene immediately upstream or downstream of its coding sequence. Numb MT- Uncharacteriz Organism er of PsaE MyfE MarT CadC PypB MLTR ed MLTR Yersinia YPO_130 YPO08 3 YPO0736* pestis 1* 04 Yersinia enterocoliti YE145 YE3340 “YE3632 YE093 ca subsp. 5 YE1942 0* * ” 5 enterocoliti ca RS0349 RS0749 Yersinia RS1670 5 0* 6 RS16645* ruckeri 5* RS0695 RS1367 5 0* 134 Table A.5: Membrane localized transcription regulators (MLTRs) within the Enterococcus genus. Underlined MLTRs had a minimum percent identity of 25% or greater to their respective MLTR. MLTRs that are bolded maintained high sequence identity to indicated MLTR, but lacked homology to their predicted extracellular domain. MLTRs with “” were previously characterized. *: indicates that the MLTR has a TcpH/ToxS like gene immediately upstream or downstream of its coding sequence. ~: indicates that there is a multi-transmembrane domain protein of unknown function directly upstream or downstream of the indicated MLTR. BcrR was not found within the E. faecalis genome within the MIST database. As such the BcrR sequence was obtained from NCBI and included in our analysis here. Number of Organism BcrR BreG MbtS AguR Lp_2991 Uncharacterized MLTFs Enterococcu 1 RS00345 s asini RS00615 Enterococcu s 3 RS02785 aquimarinus RS07540 RS08195 Enterococcu RS03755 4 s columbae RS08590 RS02640 Enterococcu RS0110 2 RS01715 s cecorum 0 RS12830/RS1051 Enterococcu RS05 RS134 0/RS15855*/RS15 s 8 555 05 110/RS07240/RS casseliflavus 15005 Enterococcu RS00645 2 s canis RS09835 Enterococcu 1 RS07360 s dispar Enterococcu 1 RS07030 s devriesei HMPREF0351_10 Enterococcu 607 2 s faecium HMPREF0351_12 753 135 Table A.5 (cont’d) Enterococcu EF073 EF1531 3 s faecalis 1 EF0600 RS00880 RS06585 Enterococcu RS143 RS162 8 RS02100 RS18200 s gilvus 65 65 RS10460 RS14805 Enterococcu RS1305 RS025 2 s hirae 5 70* Enterococcu s 1 RS11415 hermanniens is Enterococcu RS07770 s RS076 RS043 5 RS14655 haemoperoxi 75 35 RS10820 dus Enterococcu RS11 RS043 RS00315 4 s italicus 425 85 RS04425 Enterococcu 1 RS04320 s mundtii RS05900 Enterococcu RS03 s 4 RS09315 730~ massiliensis RS12565* RS20630 RS05940 Enterococcu RS22780 RS0629 RS21 RS118 RS104 s 11 RS07765 0~ 210 50~ 25 RS15880 malodoratus RS05495 RS12085~ RS09800 Enterococcu RS00180 s 6 thailandicus RS09185 136 Table A.5 (cont’d) RS04980 Enterococcu RS112 4 RS04765 s sulfureus 25 RS11240 Enterococcu s RS0681 2 RS02430 saccharolytic 0 us RS05980 Enterococcu RS05970 4 s rivorum RS00735 RS01425 RS02475 Enterococcu s RS095 RS049 RS09190 6 pseudoaviu 05 30 RS06660~ m RS13025 RS17 RS05900 RS17765 900 RS05 Enterococcu RS00705 RS13510 905 s 12 RS02265 RS03560 phoeniculicol a RS17685 RS17715 RS08900 RS02805 RS26705 RS03020 Enterococcu RS116 RS016 RS12270 RS02430 8 s pallens 55 10 RS09675 RS11665 137 Table A.6: Membrane localized transcription regulators (MLTRs) within the Lactobacillus genus. Underlined MLTRs had a minimum percent identity of 25% or greater to their respective MLTR. MLTRs that are bolded maintained high sequence identity to indicated MLTR, but lacked homology to their predicted extracellular domain. MLTRs with “” were previously characterized. *: indicates that the MLTR has a TcpH/ToxS like gene immediately upstream or downstream of its coding sequence. ~: indicates that there is a multi-transmembrane domain protein of unknown function directly upstream or downstream of the indicated MLTR. Numb Uncharacteri Organism er of BcrR BreG MbtS HcrR MmsR Lp_2991 zed MLTR Lactobacillu 1 RS00095 s animalis Lactobacillu RS01185~ s 2 amylovorus RS10235 Lactobacillu RS04890 s 2 amylophilus RS05100 Lactobacillu RS0955 1 s agilis 5 LBA0244~ Lactobacillu s 3 LBA1955 acidophilus LBA1936 Lactobacillu s 1 RS06700 acetotolera ns Lactobacillu RS0829 RS00895 3 s buchneri 0 RS11590 Lactobacillu RS2290 RS11990 RS21830 5 RS22905 s brevis 0 ~ RS21965 RS14570 Lactobacillu s RS0953 RS05925 7 RS05860 bifermentan 0 RS15695 s RS01745~ 138 Table A.6 (cont’d) Lactobacill RS11875 us RS1196 RS001 5 RS00280 coryniformi 5 60 s RS00240 RS06350 RS01610 Lactobacill RS087 RS0025 RS064 us 10 RS06300 20 0 35 farciminis RS03750 RS12580 Lactobacill us 1 RS08365 fermentum RS01145 Lactobacill 3 RS09185 us gasseri RS04740 Lactobacill 1 RS01600 us hilgardii Lactobacill RS0934 RS0934 3 RS08535 us reuteri 5 5 RS09095 Lactobacill RS0523 4 RS10010 us ruminis 5 RS02285 Lactobacill RS01090 2 us sakei RS09720 Lactobacill RS02445 RS0895 us 3 0 RS03380 sharpeae RS1205 RS1327 Lactobacill 0 0 RS060 us 6 RS03925 RS1327 15 "RS1205 plantarum 0~ 0" LSEI_1084 Lactobacill us 3 LSEI_2759 paracasei LSEI_0132 139 Table A.7: Membrane localized transcription regulators (MLTRs) within the Staphylococcus genus. 66 total MLTRs were identified in our search. Underlined MLTRs had a minimum percent identity of 25% or greater to their respective MLTR. MLTRs that are bolded maintained high sequence identity to indicated MLTR, but lacked homology to their predicted extracellular domain. MLTRs with “” were previously characterized. *: indicates that the MLTR has a TcpH/ToxS like gene immediately upstream or downstream of its coding sequence. ~: indicates that there is a multi- transmembrane domain protein of unknown function directly upstream or downstream of the indicated MLTR. #: indicates that a CPBP family metalloprotease is encoded immediately upstream or downstream of the indicated MLTR. Number of Organism MtbS NanR Uncharacterized MLTFs RS09735 Staphylococcus arlettae 2 RS10965 Staphylococcus aureus RS06710 3 "RS14925" str. Newman RS13825 Staphylococcus RS09160 2 auricularis RS00495 RS03660 Staphylococcus cohnii 5 RS04280 RS06235 RS11745 RS06375 Staphylococcus RS02300 2 condimenti RS00310 SE_p609 Staphylococcus 4 SE2409 SE0959 epidermidis SE2048 RS00830 Staphylococcus equorum 3 RS00040 RS00605 Staphylococcus 2 RS12330 RS09010 gallinarum Staphylococcus RS02640 3 RS12905 haemolyticus RS01135# RS10595 Staphylococcus hominis 4 RS00360 RS02415 RS10980 140 Table A.7 (cont’d) Staphylococcus hyicus 1 RS00530 RS10980 RS0101280 Staphylococcus lentus 4 RS0114085 RS0109075 RS07885 Staphylococcus 4 RS12095 RS02430 lugdunensis RS03175# Staphylococcus lutrae 1 RS06365 Staphylococcus RS0110280 2 massiliensis RS0103355 RS07660 Staphylococcus microti 3 RS00195 RS10565 Staphylococcus RS06300 2 pettenkoferi RS07860# Staphylococcus 1 RS12210 pseudintermedius Staphylococcus 3 RS02440 RS04325 RS01945 saprophyticus RS14815 Staphylococcus sciuri 3 RS26220~ RS14640 Staphylococcus simiae 1 RS05740 Staphylococcus simiae2 1 RS23340 Staphylococcus succinus 1 RS09190* RS0100350 Staphylococcus vitulinus 3 RS0105830 RS0106810 Staphylococcus warneri 2 RS24325 RS19740 RS03545 Staphylococcus xylosus 4 RS12090 RS08695 RS09645 141 APPENDIX B: Distribution of Membrane-Localized Transcription Regulators within the Prokaryotic Domain 142 B.1 – Introduction To gain a deeper understanding of membrane localized transcription regulators (MLTRs) we collaborated with Vadim Gumervo and Igor Jouline to mine the genomes within the Microbial Signal Transduction Database (MIST) database to gain a better understanding of the distribution and prevalence of MLTRs within the Prokaryotic domain. In Chapter 2 we focus on specific Prokaryotic genera that have been described to encode MLTRs in the literature. Here we expanded our analysis to all Prokaryotic genomes within the MIST database. Overall, we found that MLTRs are far more common and diverse within the Prokaryotic domain, similar as in Chapter 2. We also found that specific Prokaryotic genera are enriched with MLTRs. Below we summarize our findings. B.2 – Materials and Methods B.2.1 – Identification and Transmembrane Domain analysis of MLTRs within the MIST database MLTRs for a representative set of genomes were collected from MiST database by running a custom python script on the local computational cluster (449). For each genome all DNA-binding signal transduction proteins that contain transmembrane regions were retrieved. Transmembrane regions of the protein sequences were identified by running TMHMM, domains were verified using TREND and Pfam profile Hidden Markov Models (116, 450, 451). The average length, number of amino acids, and surface area for each MLTR transmembrane domain was calculated using a custom script. Of note, 143 the MIST database did not define ToxR, a known MLTR, as having a transmembrane domain. As such, this indicates that MLTRs presented here are a conservative estimate at the true prevalence of MLTRs within the bacterial domain. Sequences corresponding to transmembrane regions were extracted using a custom python script. Taxonomy information for the genomes was retrieved from GTDB and NCBI databases. B.3 – Results B.3.1 – Distribution of Membrane Localized Transcription Regulators in the Prokaryotic Domain To gain a deeper understanding of the prevalence and distribution of membrane localized transcription factors (MLTRs) within the Prokaryotic domain we mined the genomes of 10,933 bacterial species for genes that encoded a DNA binding domain and at least one transmembrane domain. We found that of the 9,306 out of 10,933 bacterial species screened (~85%) encoded at least one MLTR (Supplemental File B.1). Within these MLTR positive genomes we Identified a total of 48,918 MLTRs (Supplemental File B.2). On average bacterial genomes contain ~5 MLTRs (Supplemental File B.1). However, the number of MLTRs per genome varies dramatically with the range of MLTRs per genome is also quite broad with some bacterial species encoding only 1 MLTR and others encoding up to 158 MLTRs (Raoultibacter timonensis) (Supplemental File B.1). At the phylum level, the Bacteroides, Firmicutes, Proteobacteria, and Spirochaetes contained the most bacterial species that were enriched with MLTRs (Table B.1 and Supplemental Table B.1). Only a small fraction of bacterial genera (180 out of 2,342) are 144 enriched with MLTRs containing an average of 12 or more MLTRs per genome (Supplemental Table B.1). B.3.2 –Input and Output Domains within MLTRs Among the MLTRs identified ~96% of MLTRs were found to encode a Helix turn Helix DNA binding domains (Supplemental Table B.2 and Supplemental File B.2). The most common non-DNA/RNA binding domain within MLTRs is the response regulator domain commonly found within two component signal transduction systems (Supplemental Table B.3 and Supplemental File B.2) (452). Response regulators catalyze the transfer of a phosphate from a histidine kinase donor and also have intrinsic dephosphorylation activity (453). Response regulators are commonly multi-domain proteins typically containing a C-terminal effector domain that is commonly a DNA binding domain (453). Phosphorylation of the response regulator domain stabilizes a conformation that allows for activity of the effector domain (453). Additionally, among the top five most common non-DNA binding domains in MLTRs are the HATPase_c (an ATP cleavage domain), HisKA (a histidine kinase domain), and the Y_Y_Y domains (an extracellular domain found in two-component systems) (Supplemental Table B.3). These domains are all commonly found within two component signal transduction pathways (452, 454–456). In fact, ~9.5% of all MLTRs identified by our analysis contain domains commonly associated with two component regulatory systems, which we refer to as hybrid MLTRs (Supplemental File B.1 and B.2). Prior studies revealed that Bacteroides thetaiotaomicron contains 32 hybrid histidine kinases with DNA-binding domains (i.e., hybrid MLTRs) (457). Our data indicate that not only is the Bacteroides genus enriched with MLTRs but that a majority of the MLTRs within the Bacteroides genus are hybrid 145 MLTRs (~72%) (Supplemental File B.1 and B.2). It remains unclear if these hybrid MLTRs evolved from canonical two component regulatory systems. However, Prior studies indicate that hybrid two component regulatory systems, which do not encode DNA binding domains, were the result of recent evolutionary events and that canonical two component regulatory systems were adapted to generate these hybrid two component regulatory systems (458). Our data suggest that hybrid MLTRs are the product of recent evolutionary events as they are not conserved at the genus level and maintain domains only found within two component regulatory systems that would have no obvious role for a MLTR. B.3.3 – TM Domain Properties of MLTRs There is evidence that these hybrid MLTRs function to sense and respond to disaccharides (459). However, it is not obvious how a hybrid MLTR, or MLTRs in general, have a functional advantage over canonical two component regulatory systems, which are not restricted to the cytoplasmic membrane. Given that a majority of MLTRs within Bacteroides species are hybrid MLTRs, this implies that two component regulatory systems had already evolved to achieve this task. So why bring the response regulator and DNA-binding domain to the membrane? Currently the exact evolutionary pressure that selects for hybrid MLTRs, specifically within the Bacteroides genus, is not known. One possibility is that the cytoplasmic membrane itself serves as a signal to further fine tune these signal transduction pathways. It is generally recognized that the membrane environment in both bacterial and eukaryotic cells is not a homogenous environment. Direct evidence within Bacillus subtilis demonstrates that a vast majority of integral 146 membrane proteins are heterogeneously distributed within B. subtilis cells indicating that their diffusion within the cytoplasmic membrane is restricted (328, 329). Bacteria and Eukaryotes are both known to support lipid ordered and lipid disordered membrane domains within their membrane(s) (367, 368, 372). Generally speaking, liquid-ordered and liquid-disordered membrane domains differ by their overall fluidity and thickness, with liquid-ordered membrane domains having a lower fluidity and increased thickness, as a consequence of the phospholipid species that occupy these membrane environments (372, 373, 375, 377, 460, 461). These membrane domains have been shown to influence many signaling pathways in Eukaryotic cells, in particular T-cells (462). Association with liquid-ordered and liquid-disordered membrane domains is determined by the properties of the transmembrane domain with length and overall surface area of the transmembrane domain being the most critical factors (435). There is also evidence that dietary polyunsaturated fatty acids can influence formation and stability of lipid ordered membrane domains thereby influencing signal transduction (430, 463). Given that there is a clear evolutionary pressure to evolve MLTRs, we hypothesized that MLTRs may respond to their local membrane environment (i.e., liquid-ordered or liquid- disordered membrane domains) which can be influenced by extracellular conditions. As the overall length and surface area of transmembrane domains controls the association of membrane proteins within lipid ordered and lipid disordered membrane domains, we calculated the overall surface area for all transmembrane domains for MLTRs analyzed here (Supplemental File B.3). We found that a majority (~68%) of MLTR transmembrane domains have a surface area equal to or below 172 Å per amino acid (Supplemental File B.3). In Chapter 4 we demonstrate that TcpP, an MLTR that positively modulates 147 virulence in Vibrio cholerae, increases its association with detergent resistant membranes (i.e., liquid-ordered membrane domain) in the presence of ɑ-linolenic acid, a dietary fatty acid. The surface area of the TcpP transmembrane domain is 172 Å per amino acid. This indicates that a majority of MLTRs have the capacity to associate with liquid-ordered membrane domains. However, it does not rule out the possibility that MLTRs with transmembrane domain surface area above 172 Å per amino acid cannot associate with liquid-ordered membrane domains or are not influenced by liquid-ordered membrane domains. Due to a lack of information on liquid-ordered and liquid-disordered membrane domains in bacteria, particularly Gram-negative bacteria, and a lack of studies to understand transmembrane domain properties that influence protein association in bacterial membranes our analysis remains limited. B.4 – Discussion Our analysis has revealed that the abundance of MLTRs is far greater within the Prokaryotic domain than previously understood and suggests that they play a significant regulatory role in some bacterial genera. Among the top 10 genera most enriched for MLTRs (totaling to 1,272 MLTRs across the 15 species) there was little homology to characterized MLTRs (Supplemental Figure B.1). The majority of the genera most highly enriched with MLTRs belong to the Eggerthellaceae family which are members of mammalian gastrointestinal tracts (464–468). This family is composed of Gram-positive rods or cocci, anaerobic, nonmotile, non-spore forming, and are generally unable to utilize carbohydrates as an energy source (469). The majority of MLTRs within these species is a multi-transmembrane domain MLTR with a C-terminal LuxR-type DNA-binding HTH domain (Supplemental Figure B.1). The function of these MLTRs remains unknown but 148 given the abundance of these multi-transmembrane domain MLTRs within the genomes of these bacteria it is likely that they play an important regulatory role. Furthermore, a large number of MLTRs identified in our screen (~9.5%) contain domains commonly found in two-component regulatory systems suggesting that these hybrid MLTRs were originally two-component regulatory systems (Supplemental File B.1 and B.2). Taken together, our data suggest that there is an evolutionary pressure to evolve MLTRs in specific bacterial species, most of which are associated with mammalian gastrointestinal tracts. However, it remains unclear what these evolutionary pressure(s) are. Compared to the number of MLTRs identified by our analysis the number of experimentally validated MLTRs is extremely low indicating that a large fraction of MLTRs function remains to be understood (Table A.1). In support of this, the majority of MLTRs identified here (~56%) encode only a DNA binding domain and no additional domains of known function (Supplemental File B.4). Our data show that MLTRs are enriched within genera that are commonly associated with mammalian gastrointestinal tracts thus gaining deeper insights into the regulatory roles of these MLTRs will likely contribute to developing a more complete understanding of the gastrointestinal microbiome. 149 B.5 – Supplemental Figures and Tables Due to the size of Supplemental Figure B.1, Supplemental File B.1, Supplemental File B.2, Supplemental File B.3, Supplemental File B.4, Supplemental Table B.1, Supplemental Table B.2, and Supplemental Table B.3 these data are included as attachments and are not within this document. Table B.1: Distribution of MLTRs within Bacterial Phyla. # of phylum members # of phylum Percentage of enriched with members with phylum members GTDB Taxonomy MLTRs at least 1 MLTR enriched with MLTRs p__Acidobacteria 3 27 11.11111111 p__Actinobacteria 30 1625 1.846153846 p__Aquificae 0 8 0 p__Armatimonadetes 0 2 0 p__Bacteroidetes 555 1220 45.49180328 150 Table B.1 (cont’d) p__Balneolaeota 0 11 0 p__Caldiserica 0 1 0 p__Calditrichaeota 0 1 0 p__Chlamydiae 0 17 0 p__Chlorobi 0 13 0 p__Chloroflexi 0 28 0 p__Chrysiogenetes 0 2 0 p__Cyanobacteria 0 103 0 p__Deferribacteres 0 5 0 p__Deinococcus-Thermus 0 62 0 151 Table B.1 (cont’d) p__Dictyoglomi 0 2 0 p__Elusimicrobia 0 1 0 p__Firmicutes 191 1932 9.886128364 p__Fusobacteria 0 19 0 p__Ignavibacteriae 0 2 0 p__Kiritimatiellaeota 0 1 0 p__Lentisphaerae 0 2 0 p__Nitrospinae 0 1 0 p__Nitrospirae 0 9 0 p__Planctomycetes 0 29 0 152 Table B.1 (cont’d) p__Proteobacteria 81 3961 2.044938147 p__Rhodothermaeota 0 3 0 p__Spirochaetes 67 129 51.9379845 p__Synergistetes 0 9 0 p__Tenericutes 0 26 0 p__Thermodesulfobacteri a 0 6 0 p__Thermotogae 0 23 0 p__Verrucomicrobia 0 25 0 153 APPENDIX C: Supplemental Material for Chapter 3 154 C.1 – Supplemental Tables and Figures Figure C.1: Possible membrane localized transcription regulators (MLTRs) within Gram-negative and Gram-positive bacteria. Maximum likelihood phylogenetic tree of MLTRs collected from the MiST database, phylogenetic tree generated using the TREND server (449, 450). MLTRs displayed here represent a portion of the total MLTRs identified in our small survey. Genus and species information displayed on each branch followed by locus tag and gene designation, where applicable. Numbers next to branch points indicate the bootstrap value. Bootstrap values were generated from 100 replicates. The corresponding MLTRs genes are displayed on the right with their predicted domain(s) (in blue) and transmembrane domain(s) in gray. 155 Figure C.2: Biochemical characterization of tcpP-PAm strains. A and B) Western blots of cultures grown under virulence-inducing conditions for 6 hrs, see methods for primary antibody dilution. Photoactivatable mCherry (PAmCherry) is fused to the C- terminus of TcpP and is under the control of its endogenous promoter on the chromosome. Addition of PAmCherry to TcpP results in two species: TcpP- PAmCherry (~70KDa) and TcpP-PAmCherry* (~36KDa). Deletion of tcpH yields lower levels of TcpP-PAmCherry and TcpP-PAmCherry*, likely due to an increase in regulated intramembrane proteolysis (RIP). 156 Figure C.3: TcpH protects TcpP-PAm from proteolysis. Western blots of cultures grown under virulence-inducing conditions for 6 hrs with or without arabinose, see methods for primary antibody dilution. tcpP-PAmCherry ∆tcpH cells harbor an arabinose-inducible vector (pBAD18) encoding tcpH. Ectopic transcription of tcpH complemented deletion of tcpH. Complementation of tpcH also resulted in an additional TcpP band, ~29KDa, that corresponds to native TcpP. 157 Figure C.4: toxT transcription profile in tcpP-PAm strains. Average toxT fold change, relative to WT, across three biological replicates (determined via the ∆∆C T method) (322). mRNA was collected from cells after 2 hrs in virulence-inducing conditions, and error bars represent standard error of the mean. 158 Figure C.5: PAmCherry does not promote dimerization of TcpP. toxT transcription in V. cholerae cells determined using a plasmid based toxT::GFP transcriptional reporter. At each time point, toxT transcription was determined by measuring GFP fluorescence (excitation 488nm and emission 515nm) and optical density (600nm). The data here are an average of three biological replicates. Error bars represent the standard error of the mean. 159 Figure C.6: tcpP-PAm strains have growth dynamics similar to WT. in vitro growth curve under virulence-inducing conditions. Optical density (O.D.) values are the average of three biological replicates and error bars represent standard error of the mean. 160 Figure C.7: Complementation and overexpression of ToxR in tcpP-PAm strains. Western blots of cellular lysates collected after growth under virulence-inducing conditions for 6 hrs with or without IPTG, see methods for primary antibody dilution. ToxR does not stimulate TcpA production without TcpPH, and ToxR cannot complement TcpPK94E-PAmCherry or toxTpro∆(−55–+1). Low levels of ToxR were detected in tcpP-PAmCherry ∆toxRS and tcpP-PAmCherry ∆toxRS toxTpro∆(−55–+1) without IPTG, likely due to leaky transcription of toxRS at the IPTG promoter. Multiple copies of the lac promoter are known to result in leaky transcription due to insufficient levels of LacI (470, 471). 161 Figure C.8: TcpP-PAmCherry transition plots. Based on the identification of distinct diffusion states for TcpP-PAmCherry (circles with colors as in Figure 3.1C and with 162 Figure C.8 (cont’d) average single-molecule diffusion coefficient, D, indicated in μm2/s), the average probabilities of transitioning between mobility states at each step are indicated as arrows between those two circles, and the circle areas are proportional to the weight fractions. Low significance transition probabilities less than 4% are not displayed. Numbers above the arrows indicate the probability of transition. a) V. cholerae tcpP- PAmCherry toxTpro∆(−55–+1), corresponding to main text Figure 3.2D. b) V. cholerae tcpP-PAmCherry ∆toxRS, corresponding to main text Figure 3.3B. c) V. cholerae tcpP- PAmCherry ∆toxRS toxTpro∆(−55–+1), corresponding to main text Figure 3.3D. d) V. cholerae tcpP-PAmCherry pMMB66eh-toxR, corresponding to main text Figure 3.3F e) V. cholerae tcpP-K94E-PAmCherry, corresponding to main text Figure 3.4B. 163 Figure C.9: ToxR overexpression reduces virulence factor production. A) Western blots of cell lysates, three biological replicates, collected after 6 hrs of virulence-inducing conditions with or without IPTG. B) Densitometry analysis of the TcpA western blot in panel A. ImageJ was used to perform the densitometry analysis. Black bars: −IPTG; gray bars: +IPTG. Error bars represent standard deviation. One-tailed Student’s t-test was used to determine statistical significance. *indicates a P-value of 0.029. 164 Table C.1: Chapter 3 strain list. Strain Description Reference V. cholerae 0395 Wild type DiRita lab collection classical biotype V. cholerae ∆tcpH Isogenic deletion Beck, N.A., et. al. 2004. Journal of bacteriology, 186(24), p.8309. V. cholerae ∆tcpP Isogenic deletion Häse, C.C. and Mekalanos, J.J., 1998. Proceedings of the National Academy of Sciences, 95(2), pp.730-734. V. cholerae ∆toxRS Isogenic deletion DiRita lab collection 165 Table C.1 (cont’d) V. cholerae tcpP- Isogenic construct; TcpP-PAmCherry (C- This study PAmCherry terminal fusion), native tcpH start codon and 3rd amino acid mutated (ATG to GTG and AAA to TAA respectively), and both ribosomal binding site and coding sequence of tcpH cloned downstream of PAmCherry. V. cholerae tcpP- Isogenic construct This study PAmCherry ∆tcpH V. cholerae tcpP- Isogenic construct This study PAmCherry 𝛥toxRS V. cholerae tcpP- Isogenic construct This study PAmCherry ∆toxRS toxTpro∆(−55–+1) V. cholerae Isogenic construct This study tcpPK94E- PAmCherry 166 Table C.1 (cont’d) V. cholerae tcpP- Isogenic construct This study PAmCherry toxTpro∆(−55–+1) V. cholerae tcpP- Isogenic construct This study PAmCherry toxTpro∆(−112–+1) V. cholerae tcpP- Isogenic construct This Study PAmCherry pMMB66eh-toxR E. coli ET12567 Cloning vector recipient Allard, N., et. al. 2015. ∆dapA Canadian journal of microbiology, 61(8), pp.565-574. E. coli ET12567 Plasmid vector strain Skorupski, K. and ∆dapA pKAS32- Taylor, R.K., 1996. (empty vector) Gene, 169(1), pp.47- 52. 167 Table C.2: Chapter 3 primer list. Kpn1-HiFi restriction sites were included in forward primers and Xba1 restriction sites were included in all reverse primers to provide homology between insert and vector sequences. Description Sequence pKAS-TcpP promoter FW ctaacgttaacaaccggtacTTTCGAGTGATAGAAAAAG G pKAS-TcpP FW ctaacgttaacaaccggtacATGGGGTATGTCCGCGTG TcpP-PAmCherry FW atgcactaaaaatATGGTGAGCAAGGGCGAGGA ccttgctcaccatATTTTTAGTGCATTCTAATGTCTTCT TcpP-PAmCherry RV GTTC TcpH-PAmCherry FW ctaatgtcttCTTGTACAGCTCGTCCATGC gctgtacaagAAGACATTAGAATGCACAAAAAATTAA TcpH-PAmCherry RV AAG Downstream TcpH-PAmCherry RV tcatgataagaccCTTGTACAGCTCGTCCATGCC Downstream TcpH-PAmCherrycgagctgtacaagGGTCTTATCATGAGCCGCCTAG FW aaatttgcgcatgctagctatagttCTTGGTCTTTTTTAGATA pKAS-downstream TcpH RV ACGTAAGC TcpPK94E RV GATCAACGTCTCATGTTCATC TcpPK94E FW GATGAACATGAGACGTTGATC toxTpro ∆(−55–+1) RV tcccaatcatATCTTAAAATCGAAGTTAATATAAAACT AC 168 Table C.2 (cont’d) toxTpro ∆(−55–+1) FW gattttaagatATGATTGGGAAAAAATCTTTTC ctaacgttaacaaccggtacGTTGGTGGTGTTCCAGATA pKAS-toxTpro ∆(−112–+1) FW ATAC ttcccaatcaGTATTACATAAGAAAAACATAAAGTAA toxTpro ∆(−112–+1) RV CTCATG toxTpro ∆(−112–+1) FW tatgtaatacTGATTGGGAAAAAATCTTTTC tgcgcatgctagctatagttATCATCAGTAATAAATATAGA pKAS-toxTpro ∆(−112–+1) RV GTTATATTTTTTTTC recA FW ATTGAAGGCGAAATGGGCGATAG recA RV TACACATACAGTTGGATTGCTTG AGG toxT FW ACTGATGATCTTGATGCTATGGAG toxT RV CATCCGATTCGTTCTTAATTCACC 169 APPENDIX D: Supplemental Material for Chapter 4 170 D.1 – Supplemental Methods D.1.1 – Mass-spectroscopy methods Samples analyzed via Mass-spectroscopy were run on an SDS page gel (12.5% acrylamide) for 20 minutes at 100 volts. The mobilized protein was then excised from SDS page gel (using a methanol washed razor) and suspended in 5% methanol. Samples were then analyzed by the Michigan State University Proteomics core to identify all peptides within the samples. Below is a brief description of their methods. Gel bands were digested in-gel according to Shevchenko, et. al. with modifications (472). Briefly, gel bands were washed with 100mM ammonium bicarbonate and dehydrated using 100% acetonitrile. Sequencing grade modified trypsin was prepared to 0.01 µg/µL in 50mM ammonium bicarbonate and ~100 µL of this was added to each gel band so that the gel was completely submerged. Bands were then incubated at 37°C overnight. Peptides were extracted from the gel by water bath sonication in a solution of 60% acetonitrile and 1% TFA and vacuum dried to ~2 µL. Peptides were then re- suspended in 2% acetonitrile and 0.1% TFA to 20µL. From this, 5 µL were automatically injected by a Thermo EASYnLC 1200 onto a Thermo Acclaim PepMap RSLC C18 peptide trap (5µm, 0.1mm x 20mm) and washed with buffer A for ~5 min. Bound peptides were then eluted onto a Thermo Acclaim PepMap RSLC 0.075mm x 250mm C18 resolving column and eluted over 35min with a gradient of 8% B to 40% B in 24min, ramping to 90% B at 25 min and held at 90% B for the duration of the run (Buffer A = 99.9% Water, 0.1% Formic Acid, Buffer B = 80% Acetonitrile, 0.1% Formic Acid, 19.9% 171 Water) at a constant flow rate of 300 nL/min. Column temperature was maintained at 50°C using an integrated column heater (PRSO-V2). Eluted peptides were sprayed into a ThermoFisher Q-Exactive HF-X mass spectrometer using a FlexSpray spray ion source. Survey scans were taken in the Orbi trap (60000 resolution, determined at m/z 200) and the top 15 ions in each survey scan were then subjected to automatic higher energy collision induced dissociation (HCD) with fragment spectra acquired at 15,000 resolution. The resulting MS/MS spectra are converted to peak lists using Mascot Distiller, v2.7 (www.matrixscience.com) and searched against a database containing all V. cholerae strain ATCC39541/Classical Ogawa 395/0395 protein entries available from UniProt (downloaded from www.uniprot.org) appended with customer provided sequences and common laboratory contaminants (www.thegpm.org). Searches were performed using the Mascot searching algorithm, v 2.7, on an in-house server. The Mascot output was then analyzed using Scaffold, v4.11.0 (www.proteomesoftware.com) to probabilistically validate protein identifications. Assignments validated using the Scaffold 1% FDR confidence filter are considered true. D.1.2 – Fatty acid analysis Analysis of fatty acids from whole V. cholerae cells was done as previously described (473). Briefly, V. cholerae cells were grown with and without α-linolenic acid (500 µM) as described in section D.1.3 – Supplemental virulence inducing culture conditions. Cells were collected by centrifugation (2450 X g 15 minutes) and then washed with PBS. Cells were then lysed via addition of 300 μl of extraction solvent (composed of 172 methanol, chloroform and formic acid [20:10:1, v/v/v]). After lipids were extracted the Fatty Acyl Methylester (FAME) reactions were carried out as described (473). After the FAME reactions, fatty acid content was measured via Gas-Liquid Chromatography using a DB- 23 column (Agilent, part number: 122-2332). Molar values of each peak was then normalized to an internal standard (15:0) to calculate the total molar percentage of each fatty acid detected. D.1.3 – Supplemental virulence inducing culture conditions To test if crude bile (Ox gal, Sigma Aldrich), as well as components of crude bile, we opted to pretreat all V. cholerae strains under Vir Ind conditions before exposing cells to these additional factors. V. cholerae cells were subcultured from overnight cultures to an optical density (600 nm) of 0.01 in 100 ml of LB pH 6.5 in a 250 ml Erlenmeyer flask. V. cholerae strains were grown for 4 hours under Vir Ind conditions, centrifuged (2450 X g 15 minutes), resuspended in 0.8 ml LB. 200 µl of resuspended cells were transferred to 50 ml of fresh Vir Ind media in 125 ml Erlenmeyer flasks. The remaining 200 µl of cells were lysed and analyzed via western blot. A maximum of 4 different conditions were tested per strain per biological replicate due to limited incubator space. The following were supplemented to Vir Ind media: crude bile (CB; final concentration), α-linolenic acid (LA; final concentration 500µM), palmitic acid (PA; final concentration 500µM), purified bile salts cholate and deoxycholate (PB; final concentration 100µM). All compounds were purchased from Sigma Aldrich. CB and PB were solubilized in Vir Ind media and filter sterilized (0.22 µM) before addition to Vir Ind. LA and PA were dissolved in 1 ml of 173 Dimethyl sulfoxide (DMSO) and then added to Vir Ind media. LA and PA sterility were confirmed by spreading 100µl of DMSO solubilized LA and PA on LB agar plates (data not shown). 174 D.2 – Supplemental Tables and Figures Figure D.1: TcpH transmembrane and periplasmic constructs growth dynamics are similar to WT. A) Virulence inducing conditions growth curve of TcpH TM and Peri constructs respectively. B) Virulence inducing condition growth curve supplemented with crude bile (0.4%). C) Virulence inducing condition growth curve supplemented with purified bile salts (cholate/deoxycholate 100µM). D) Virulence inducing condition growth curve supplemented with α-linolenic acid (500µM). E) LB, 37°C, growth curve with 1mM to 100nM Miltefosine. 175 Figure D.2: TcpH transmembrane and periplasmic constructs support toxT transcription and CtxB production. A) Average toxT transcription of three biological replicates, determined via ∆∆CT method. toxT fold change is relative to WT V. cholerae (i.e., toxT transcription=1). B) CtxB levels, measured via ELISA, in culture supernatants collected from cultures incubated with V. cholerae cells cultured in virulence inducing conditions for 24hrs. Error bars represent standard error of the mean. 176 Figure D.3: TcpH transmembrane and periplasmic constructs display WT growth in adult mice feces. A) Filter sterilized mice fecal growth curve. B) Non-filtered (i.e, non-sterile) mice fecal growth curve. ΔtcpP was excluded from non-sterile mice fecal growth experiment due to limited supply of non-sterile mice fecal media. For all data presented here, averages represent three biological replicates. Error bars represent standard error of the mean. 177 Figure D.4: TcpH transmembrane constructs inhibit RIP of TcpP. Western blots of spheroplast fractions (cytoplasm and cytoplasmic membrane fractions). TcpH transmembrane constructs (ToxSTcpH and EpsMTcpH) and native TcpH were expressed from pBAD18 in ΔtcpH ΔyaeL background under virulence inducing conditions for 6hrs. All strains, excluding WT, are ΔtcpH ΔyaeL. ΔtcpH* harbors pBAD18 (empty vector). See Figure E.5 for full view of these western blots. 178 Figure D.5: Crude bile stimulates toxT transcription in a TcpH dependent manner. A) toxT transcription in TcpH transmembrane constructs in V. cholerae cells. toxT transcription was measured using a plasmid based toxT::GFP transcriptional reporter. The data here are an average of three or more biological replicates and error bars represent the standard error of the mean. Data for these strains for 4hr Vir Ind, Vir Ind, crude bile, and Non-Vir Ind can also be found in Figure D.6. B) toxT transcription in WT V. cholerae cells using RT-qPCR, determined via ∆∆CT method. Cells were incubated in Vir Ind for 4hrs and then transferred to indicated conditions for an additional 4hrs. RNA was collected at the 8hr time point. toxT transcription is relative to WT Vir Ind. Averages represent three biological replicates and error bars represent standard error of the mean. The data presented in panel B can also be found in Figure D.8A. 179 Figure D.6: α-Linolenic acid stimulates toxT transcription in a TcpH dependent manner. A) toxT transcription in WT (black bars), ΔtcpH (white bars), and ToxSTcpH (dark gray bars) was determined using a plasmid based toxT::GFP transcriptional reporter. The data here are an average of three or more biological replicates and error bars represent the standard error of the mean. Two-tailed Student’s t-test was used to determine statistical significance. *indicates a P-value of < 0.05. 180 Figure D.7: ɑ-Linolenic acid stimulates toxT transcription in a dose dependent manner. toxT transcription in WT (black bars), ΔtcpH (white bars), and EpsMTcpH (grey bars) was determined using a plasmid based toxT::GFP transcription reporter. Concentrations of ɑ-linolenic acid (LA) used are displayed below each bar. Lower concentrations of LA (50µM) were tested with control groups (ΔtcpH and EpsMTcpH) and were found to have similar levels of toxT transcription as virulence inducing conditions (Vir Ind), data not shown. Error bars represent standard deviation. A two-tailed Student’s t-test was used to determine statistical significance. *indicates a P-value of < 0.05. 181 Figure D.8: toxT transcription is stimulated by crude bile and α-linolenic acid, but tcpP transcription does not change. A) toxT transcription in WT V. cholerae cells using RT-qPCR, determined via ∆∆CT method. Cells were incubated in Vir Ind for 4hrs and then transferred to indicated conditions for an additional 4hrs. RNA was collected at the 8hr time point. toxT transcription is relative to WT Vir Ind. Averages represent three biological replicates and error bars represent standard error of the mean. B) tcpP transcription in WT V. cholerae cells determined using tcpP::lacZ transcription. tcpP transcription was determined by quantifying LacZ activity (i.e., calculating Miller Units). V. cholerae cells were grown as in panel A. Averages represent five biological replicates for panel B. Error bars represent the standard error of the mean. D) Percentage of fatty acids present in whole V. cholerae cells cultured with α-linolenic acid (gray bars) and without (black bars). Error bars represent the standard deviation, and the average values here represent two biological replicates. 182 Figure D.9: TcpP levels are elevated in the presence of crude bile and α-linolenic acid. Western blots used to quantify TcpP levels in Figure 4.3C. TcpP is approximately 29KDa. Bands above and below 29KDa are non-specific bands. 183 Figure D.10: α-Linolenic acid promotes association of TcpP and TcpH with detergent resistant membranes (DRM). Western blots of Triton X-100 soluble (lipid disordered) and Triton X-100 insoluble (lipid ordered) membrane fractions with and without α-linolenic acid supplementation (LA). A) Three Western blots probed with α- TcpP from WT V. cholerae cells. Samples in the top two western blots were collected using the spheroplast method of cell lysis, and samples in the bottom western blot were collected using the gentle cell lysis method. Samples were collected from three biological replicates. For gentle cell lysis samples, only two biological replicates were analyzed for the TI and TS+LA samples due to sample mishandling. B) Densitometry analysis of western blots in panel A. ImageJ was used to perform the densitometry analysis. Error bars represent the standard error. C) Four Western blots probed with α- TcpH from WT V. cholerae cells. Samples in the left two western blots were collected using the spheroplast method of cell lysis, and samples in the right two western blots were collected using the gentle cell lysis method. Samples were collected from three biological replicates. Arrows indicate TcpH specific bands. 184 Figure D.11: α-Linolenic acid does not promote non-specific protein association with detergent resistant membranes. A) Relative levels of the non-specific loading control in α-TcpH westerns is equally distributed among Triton soluble (i.e., TS; lipid disordered) and Triton insoluble (i.e., TI; lipid ordered) fractions. Addition of α-linolenic acid (LA, 500µM), indicated by +/-, does not change this distribution. Relative levels of the non-specific loading control were determined via densitometry analysis. Densitometry analysis was conducted using ImageJ. Error bars represent the standard error. B) Fatty acid analysis of Triton soluble (i.e., TS; lipid disordered) and Triton insoluble (i.e., TI; lipid ordered) fractions. Error bars represent the standard deviation, and the average values here represent two biological replicates. 185 Figure D.12: Hsv-His(6x) tagged TcpP constructs remain functional. CtxB levels, measured via ELISA, in culture supernatants collected from cultures incubated with V. cholerae cells cultured in virulence inducing conditions for 24hrs. Black bars represent WT cells. Light gray bars represent ∆tcpP complemented with pBAD18-Hsv-His(6x)- tcpP , and dark gray bars represent ∆tcpP complemented with pBAD18-tcpP-His(6x)- Hsv. tcpP constructs were ectopically expressed from pBAD18 using arabinose (Ara 0.1% w/v). + indicates arabinose was added to the culture. 186 Figure D.13: Miltefosine and α-linolenic acid function synergistically to stimulate toxT transcription. A) toxT transcription in WT (black bars), ΔtcpH (white bars), and EpsMTcpH (gray bars) was determined using a plasmid based toxT::GFP transcriptional reporter. Values displayed here are an average of three or more biological replicates. Error bars represent the standard error of the mean. A two-tailed Student’s t-test was used to determine statistical significance. *Indicates a P-value of < 0.05. Data from Non- Vir Ind, Vir Ind, DMSO, and α-linolenic acid (LA) conditions can be found in Figure 4.4A and Figure D.6. B) TcpP levels relative to WT V. cholerae cells grown in Vir Ind conditions for 8 hours. C) Percentage of TcpP molecules present in the TI (Triton insoluble; lipid ordered membrane domain) and TS (Triton soluble; lipid disordered membrane domain) membrane fractions within WT V. cholerae cells. B and C) Densitometry analysis was done using ImageJ to quantify TcpP levels. Averages represent three biological replicates, and error bars represent standard error of the mean. LA: α-linolenic acid (500µM) Mil: miltefosine (10µM). 187 Table D.1: Chapter 4 strain list. Strain Description Reference V. cholerae 0395 classical Wild type DiRita lab collection biotype V. cholerae ∆tcpH Isogenic deletion DiRita lab collection V. cholerae ∆tcpP Isogenic deletion DiRita lab collection V. cholerae ∆tcpH DiRita lab collection Overexpression plasmid pBAD18-empty vector vector V. cholerae ∆tcpH This study ∆tcpH complementation pBAD18 TcpH with ectopic tcpH V. cholerae ∆tcpPH This study ∆tcpH complementation pBAD18 CtxBTcpH with ectopic tcpH TM construct V. cholerae ∆tcpH; ∆yaeL This study Overexpression plasmid pBAD18-empty vector V. cholerae ∆tcpH; ∆yaeL This study ∆tcpH complementation pBAD18 CtxBTcpH with ectopic tcpH TM construct V. cholerae ∆tcpH; ∆yaeL This study ∆tcpH complementation pBAD18 ToxSTcpH with ectopic tcpH TM construct 188 Table D.1 (cont’d) V. cholerae ∆tcpH; ∆yaeL This study ∆tcpH complementation pBAD18 EpsMTcpH with ectopic tcpH TM construct V. cholerae ∆tcpH; This study ∆tcpH complementation ∆yaeL pBAD18 TcpH∆136- with ectopic tcpH Peri construct 119 V. cholerae ∆tcpH; This study ∆tcpH complementation ∆yaeL pBAD18 TcpH∆136- with ectopic tcpH Peri construct 103 V. cholerae This study N-terminal tcpP co- ∆tcpP pBAD18 Hsv- immuno precipitation construct His(6x)-tcpP V. cholerae ∆tcpP pBAD18 This study C-terminal tcpP co- tcpP-His(6x)-Hsv immuno precipitation construct V. cholerae ∆tcpH This study N-terminal tcpH co- pBAD18 Hsv-His(6x)-tcpH immuno precipitation construct V. cholerae ∆tcpH This study C-terminal tcpH co- pBAD18 tcpH-His(6x)-Hsv immuno precipitation construct 189 Table D.1 (cont’d) V. cholerae This study N-terminal tcpP co- ∆yaeL pBAD18 Hsv- immuno precipitation construct His(6x)-tcpP V. cholerae ∆yaeL This study C-terminal tcpP co- pBAD18 tcpP-His(6x)-Hsv immuno precipitation construct V. cholerae CtxBTcpH chromosomal construct This study V. cholerae ToxSTcpH chromosomal construct This study V. cholerae EpsMTcpH chromosomal construct This study V. cholerae TcpH∆136-119 chromosomal construct This study V. cholerae TcpH∆136-103 chromosomal construct This study V. cholerae TcpH∆119-103 chromosomal construct This study V. cholerae TcpH∆103-79 chromosomal construct This study V. cholerae TcpH∆79-55 chromosomal construct This study V. cholerae TcpHC114S isogenic mutant This study V. cholerae isogenic mutant This study TcpHC114S/C132S 190 Table D.1 (cont’d) V. cholerae pBH6119- toxT transcription reporter Anthouard R, and DiRita VJ. toxT::GFP mBio. 2013. V. cholerae ∆tcpH toxT transcription reporter This study pBH6119-toxT::GFP V. cholerae ∆tcpP toxT transcription reporter This study pBH6119-toxT::GFP V. cholerae CtxBTcpH toxT transcription reporter This study pBH6119-toxT::GFP V. cholerae ToxSTcpH toxT transcription reporter This study pBH6119-toxT::GFP V. cholerae EpsMTcpH toxT transcription reporter This study pBH6119-toxT::GFP V. cholerae TcpH∆136-119 toxT transcription reporter This study pBH6119-toxT::GFP V. cholerae TcpH∆136-103 toxT transcription reporter This study pBH6119-toxT::GFP V. cholerae TcpH∆119-103 toxT transcription reporter This study pBH6119-toxT::GFP 191 Table D.1 (cont’d) V. cholerae TcpH∆103-79 toxT transcription reporter This study pBH6119-toxT::GFP V. cholerae TcpH∆79-55 toxT transcription reporter This study pBH6119-toxT::GFP V. cholerae TcpHC114S toxT transcription reporter This study pBH6119-toxT::GFP V. cholerae toxT transcription reporter This study TcpHC114S/C132S pBH6119-toxT::GFP E. coli ET12567 ∆dapA Cloning vector recipient Allard, N., et. al. 2015. Canadian Journal of Microbiology, 61(8), pp.565- 574. E. coli ET12567 ∆dapA Plasmid vector strain DiRita lab collection pKAS32-empty vector E. coli ET12567 ∆dapA Plasmid vector strain DiRita lab collection pBAD18-empty vector 192 Table D.2: Chapter 4 primer list. Each primer contains Kpn1-HiFi (forward primers) and Xba1 (reverse primers) restriction sites. Description Sequence pKAS FW gcctctaaggttttaagt pKAS RV ctttcaaggtagcggttacc pBAD18 FW ctgtttctccatacccgtt pBAD18 RV ggctgaaaatcttctct pKAS-TcpP ctaacgttaacaaccggtactttcgagtgatagaaaaagg promoter FW pKAS-TcpP FW ctaacgttaacaaccggtacatggggtatgtccgcgtg pKAS-downstream aaatttgcgcatgctagctatagttcttggtcttttttagataacgtaagc TcpH RV TcpP-CtxBss FW atgcactaaaaattaaaagacattagaatgattaaattaaaatttgg TcpP-CtxBss RV aatttaatcattctaatgtcttttaatttttagtgcattctaatgtcttc CtxBss-TcpHperi tcttcagcatatgcacatggaccgatgcgacaaaaaaac FW CtxBss-TcpHperi gtcgcatcggtccatgtgcatatgctgaaga RV 193 Table D.2 (cont’d) TcpP-EpsMss RV tctaatgtcttttaatttttagtgcattctaatgtcttc EpsMss-TcpHperi gggaatatggccgatgcgacaaaaaaac FW EpsMss-TcpHperi gtcgcatcggccatattccccaataagc RV TcpP-ToxSss FW atgcactaaaaattaaaagacattagaatgcaaaatagacacatcg TcpP-ToxSss RV cgatgtgtctattttgcattctaatgtcttttaatttttagtgcattctaatgtcttc ToxSss-TcpHperi ttgggggagtccgatgcgacaaaaaaac FW ToxSss-TcpHperi tgcatgcctgcaggtcgactctaaaaatcgctttgacag RV TcpH∆136-119 FW cgccttcccttagggtcttatcatgagccgc TcpH∆136-119 RV tgataagaccctaagggaaggcgagaaaacaac TcpH∆136-103 FW tgattacaattagggtcttatcatgagccgc TcpH∆136-103 RV tgataagaccctaattgtaatcacggctcacattactttc TcpH∆119-103 FW tgattacaattacaagcagcttacggctg TcpH∆119-103 RV taagctgcttgtaattgtaatcacggctcac 194 Table D.2 (cont’d) TcpH∆103-79 FW tcaaacattggtgttgagtatttatcaactc TcpH∆103-79 RV tactcaacaccaatgtttgataacgtgtag TcpH∆79-55 FW taatctatccccagatcctagctctcag TcpH∆79-55 RV taggatctggggatagattaccttgataagtag TcpHC114S FW tcaactcggcaaaggtagttttctcgccttccc TcpHC114S RV gggaaggcgagaaaactacctttgccgagttga TcpHC132S FW ggttttccagtcaaagcgatttttag TcpHC132S RV ctaaaaatcgctttgactggaaaacc pBAD18-CtxBss agcgaattcgagctcggtaccaaagggagcattataagacattagaatgattaaattaa FW aatttgg pBAD18-ToxSss agcgaattcgagctcggtaccaaagggagcattatatgcaaaatagacacatcg RV pBAD18-EpsMss agcgaattcgagctcggtaccaaagggagcattatatgatgaaagaattattggctc FW pBAD18-TcpH FW agcgaattcgagctcggtaccaaagggagcattatatgcacaaaaaattaaaagcttg pBAD18-TcpH RV tgcatgcctgcaggtcgactctaaaaatcgctttgacag 195 Table D.2 (cont’d) pBAD18-TcpH∆136- tgcatgcctgcaggtcgactctaagggaaggcgagaaaacaac 119 RV pBAD18-TcpH∆136- tgcatgcctgcaggtcgactctaattgtaatcacggctcacattactttc 103 RV pBAD18 Hsv- ttcgagctcggtaccaaagggagcattatatgcagccggaactggcgccggaagatcc His(6x) FW g Hsv-His(6x)-TcpP ccggaagatccggaagattgccatcatcatcatcatcatatggggtatgtccgcgtg FW Hsv-His(6x)-TcpP cagttccggctgatgatgatgatgatgatgattttttgtgcattctaatgtcttc RV pBAD18-TcpP RV tgcatgcctgcaggtcgactttaattttttgtgcattctaatgtcttctgttc pKT25-TcpP FW ggctgcagggtcgactatggggtatgtccgc pKT25-TcpP RV attcttacttacttaggtacttaattttttgtgcattctaatgtcttctgttc pUT18C-TcpH FW aacgccactgcaggtcgactcagcggtggtggaggttcgaaatgcacaaaaaattaaa ag pUT18C-TcpH RV gatgaattcgagctcggtacctaaaaatcgctttgacaggaaaacc recA FW RT-qPCR attgaaggcgaaatgggcgatag 196 Table D.2 (cont’d) recA RV RT-qPCR tacacatacagttggattgcttg agg toxT FW RT-qPCR actgatgatcttgatgctatggag toxT RV RT-qPCR catccgattcgttcttaattcacc tcpP FW RT-qPCR tgagtgggggaagataaacg tcpP RV RT-qPCR ttggattgttatccccggta 197 APPENDIX E: Identifying Regions within TcpH Critical for its Function 198 E.1 – Introduction TcpP is essential for toxT transcription, presumably as TcpP facilitates transcription through direct interaction with RNA polymerase due to its binding sequence being near the -35 site (340, 347). Furthermore, TcpP is post-translationally regulated by two proteases, Tail-specific protease (Tsp) and YaeL, and this process is also known as Regulated Intramembrane Proteolysis (RIP) (96, 351, 352). The literature suggests that TcpP is constitutively sensitive to RIP, by Tsp and YaeL, and requires TcpH to inhibit RIP under specific conditions (96, 351, 352). However, the mechanism by which TcpH inhibits RIP of TcpP remains unclear. TcpP and TcpH both lack significant sequence similarity to other proteins with similar function. Thus, we aimed to understand how TcpH protects TcpP from RIP by identifying regions within that are critical for its function. To do this we generated chimeric transmembrane (TM) domain fusions and periplasmic (Peri) TcpH deletion constructs to identify regions within TcpH that are critical for its protective function. We generated a total of 10 chromosomal TcpH constructs, 3 TM and 7 Peri, that do not disrupt the coding sequence of TcpP and are subject to WT transcriptional control (Figure E.1A). Below we discuss our findings and outline future experiments to eventually identify specific residues within TcpH that are critical for its function. Some of the data presented in this section can also be found in Chapter 4 (specifically data with ToxSTcpH, EpsMTcpH, and TcpH∆119-103). This data has also been included in this section for direct comparison with TcpH constructs not discussed in Chapter 4 due to stability issues. 199 E.2 – Results E.2.1 – TcpH Maintains Remains Functional Upon Alteration of its Transmembrane and its Periplasmic Domains. TcpH has a single transmembrane domain (also a Sec signal sequence), at its N- terminus, and two periplasmic cysteine residues (C114 and C132), represented by “s”. TcpH sequence is highly conserved among V. cholerae strains. Thus, it was unclear what region of TcpH was critical to inhibit RIP. To that end, we took a broad approach and made modifications to the transmembrane and periplasmic domain of TcpH. To determine if the transmembrane domain of TcpH has a direct role in protecting TcpP the transmembrane domain of TcpH was replaced with the transmembrane domain of ToxS (ToxSTcpH) and EpsM (EpsMTcpH) as both ToxS and EpsM are known to be localized to the cytoplasmic membrane (207, 389). Additionally, we hypothesized that membrane localization of TcpH may not be essential for its function. To test this we replaced the native TcpH Sec signal sequence (which is not cleaved) with the Sec signal sequence from the B subunit of cholera toxin (ctxB), termed CtxBTcpH, that is cleaved and has also been utilized to localized proteins to the periplasmic space (474). A majority of TcpH coding sequence reside in the periplasmic space (residues 26-136). Thus, in-frame deletions of periplasmic regions were made based on TcpH secondary structure, resulting in TcpH∆136-119, TcpH∆136-103, TcpH∆119-103, TcpH∆103-79, and TcpH∆79-55 (Figure E.1A). In addition, prior studies have shown that C114 within the periplasmic domain of TcpH may have a role in inhibiting RIP of TcpP (475). To determine if C114 and C132 play a role in TcpH function we made point mutations to both C114 and C132 resulting in TcpH C114S and TcpHC114S/C132S (Figure E.1A). 200 Figure E.1: TcpH transmembrane and periplasmic constructs remain functional in vitro. A) Diagram of TcpH transmembrane constructs (CtxBTcpH, EpsMTcpH, and ToxSTcpH) and periplasmic constructs (TcpH∆136-119, TcpH∆119-103, TcpH∆103-79, and TcpH∆79-55). B and C) in vitro characterization of TcpH transmembrane and periplasmic chromosomal constructs grown under virulence inducing conditions. B) Western blots of whole-cell lysates probed with α-TcpP (top), α-TcpH (middle). C) Western blot of whole-cell lysates probed with α-TcpA. In addition, CtxB levels and toxT transcription were also determined for the TcpH transmembrane and periplasmic constructs. Average CtxB levels and toxT fold change (relative to WT) for each strain are indicated below the western blot. See Figure E.2 for full view of the data. 201 We evaluated the function of TcpH TM and specific Peri constructs by first measuring levels of TcpP, toxT transcription, and virulence factor (TcpA and CtxB) production in vitro (Figure E.1B). All of the TcpH constructs tested prevented complete degradation of TcpP, similar to WT TcpH (Figure E.1B). This suggests that the TcpH constructs are capable of inhibiting RIP of TcpP and thereby the TcpH TM and Peri constructs support TcpP function to stimulate toxT transcription. We also assessed the ability of TcpH TM and Peri constructs to support WT toxT transcription in the presence of crude bile (0.4%) (Figure E.2D). We found that TcpH Peri constructs were unable to support WT toxT transcription in the presence of crude bile, similar to ToxSTcpH and EpsMTcpH in Chapter 4. We found that toxT transcription was not significantly different for TcpH TM or Peri constructs compared to WT (Figure E.1C and Figure E.2A). Similar to toxT transcription, we found that all the TcpH constructs tested were able to support production of CtxB and TcpA, which are positively regulated by toxT, production better than ∆tcpH (Figure E.1C and Figure E.2B). However, CtxB levels did not reach that of WT for all of the TcpH Peri constructs tested (Figure E.1C and Figure E.2B). In addition, despite toxT transcription and TcpA production, TcpH Peri constructs TcpH∆136-103 and TcpH∆103-79, did not support WT production of CtxB (Figure E.1C and Figure E.2B). Currently, it is unclear as to why TcpH∆136-103 and TcpH∆103-79 do not support WT CtxB production in vitro. However, these data indicate that residues 136-103 and 103-79 are important, but not essential, for TcpH to inhibit RIP. 202 Figure E.2: Residues within region 136-103 in the periplasmic domain of TcpH are critical for protecting TcpP under non-virulence inducing conditions. A) Average toxT transcription of three biological replicates, determined via ∆∆CT method. toxT fold change is relative to WT V. cholerae (i.e., toxT transcription=1). B) CtxB levels, measured via ELISA, in culture supernatants collected from cultures incubated with V. cholerae cells cultured in virulence inducing conditions for 24hrs. C) Western blots of WCL collected after 6hrs of growth under virulence inducing conditions. D) toxT transcription in TcpH transmembrane and periplasmic constructs in V. cholerae cells. toxT transcription was measured using a plasmid based toxT::GFP transcriptional reporter. The data here are an average of three or more biological replicates and error bars represent the standard error of the mean. Furthermore, some of the TcpH constructs are not detectable via western blot (CtxBTcpH, ToxSTcpH, TcpH∆136-119, TcpH∆103-79, and TcpH∆79-55) (Figure E.1B). This was expected for TcpH103-79 and 79-55, as they lack the epitope for our TcpH antibody. However, since the remaining TcpH constructs still support WT TcpP levels and virulence factor production (Figure E.1), it is likely that these TcpH constructs are not detectable via western blot due to reduced stability compared to WT. To confirm that these TcpH 203 constructs are indeed translated, we overexpressed each construct from an arabinose inducible vector (pBAD18). Overexpression of these remaining TcpH constructs supported CtxB production and allowed for visualization of CtxBTcpH, ToxSTcpH, and TcpH∆136-119 via western blot (Figure E.3) suggesting that a lack of detection of the chromosomal TcpH constructs by western blot is due to decreased stability of the modified protein rather than a lack of translation. Figure E.3: Overexpression of TcpH transmembrane and periplasmic constructs allows for visualization via western blot. A) CtxB levels in culture supernatants after 24 hrs of incubation in virulence inducing conditions, measured by ELISA. White bars indicate samples that were induced with 0.1% arabinose (w/v) and black/gray bars indicate that no arabinose was added. B) Western blot of whole cell lysates collected 204 Figure E.3 (cont’d) after 8hrs and 24 hrs. Western blots probed with α-TcpP (Top) and α-TcpH (bottom) for both 8hr and 24hr time points. Samples with a black asterisk (*) indicate that strain carries an empty overexpression vector (pBAD18). These data show that, in vitro, the sequence of the TcpH TM domain sequence can be modified and without inhibiting its ability to inhibit RIP of TcpP. However, loss of some C-terminal regions of TcpH results in minor defects in CtxB production despite being able to protect TcpP. These data indicate that the Peri domain (particularly regions 136-119 and 103-79) of TcpH is important for inhibition of RIP of TcpP in vitro. In addition to the TcpH TM and Peri chromosomal constructs discussed above, we also characterized the function and the ability to support toxT transcription in TcpHC114S and TcpHC114S/C132S (Figure E.3CD). These data indicate that the periplasmic cysteine residues (C114 and C132) are not entirely essential for TcpH function in vitro. Taken together, this indicates that other non-cysteine residues within regions 136-119 are important for TcpH function in vitro. E.2.2 – TcpH Peri Constructs Display WT Colonization of Infant Mice In vitro experiments indicate that the TM and Peri domain of TcpH can withstand considerable modifications and still maintain function. However, in vitro virulence inducing conditions do not represent the conditions found in the gastrointestinal tract. Thus, we tested the fitness of the TcpH TM and Peri constructs in vivo. To accomplish this, we infected infant mice with the TcpH TM and Peri constructs (Figure E.4A). Overall, we found that the TcpH TM constructs were unable to colonize mice as well as WT, and we found that the Peri TcpH constructs colonized mice to WT levels. A detailed discussion 205 and additional data regarding the TM TcpH constructs can be found in Chapter 4. It remained possible that the TM TcpH constructs were sensitive to the gastrointestinal microbiota. To test this, we cultured WT and the TcpH constructs (TM and Peri) aerobically in both sterile and non-sterile mice fecal media (9% w/vol in M9 minimal media) for 21hrs at 37°C (Figure E.4BC). We found that WT and the TcpH TM and Peri constructs had similar growth rates and final cell densities in both sterile and non-sterile mice fecal media (Figure E.5BC). In addition, we also quantified TcpA levels in cell lysates after 21 hours of growth in sterile mice fecal media. While the growth rates were very similar between WT and the TcpH constructs, the TM TcpH constructs did not support WT levels of TcpA while the Peri TcpH constructs did (Figure E.4A). These data indicate that the TM domain of TcpH is critical for TcpH to respond to cues present in the gastrointestinal tract to protect TcpP from RIP and support downstream virulence factor production. 206 Figure E.4: TcpH transmembrane and periplasmic constructs Infant mouse colonization and growth in adult mice feces. A) Colony forming units per gram of 3- 6 day old infant mouse intestine infected with TM and Peri TcpH constructs following the same protocol in Figure 4.2A. Due to inclement weather during the pandemic we 207 Figure E.4 (cont’d) were unable to acquire a sufficient number of infant mice for the TcpH peri constructs. Asterisk indicates a p-value of less than 0.05. A mann-whitney U test was used to determine statistical significance between WT and each TcpH transmembrane construct. The horizontal line indicates the average CFU/gm of the intestine and is an average of 3-11 biological replicates. Error bars indicate the standard error of the mean. B) Filter sterilized mice fecal growth curve. D) Non-filtered (i.e., non-sterile) mice fecal growth curve. For all data presented here, averages represent three biological replicates. Error bars represent standard error of the mean. Two-tailed Student’s t-test was used to determine. E.2.3 – TcpH TM Constructs Specifically Inhibit RIP of TcpP In Chapter 4 we demonstrate that the ToxSTcpH and EpsMTcpH specifically inhibit RIP of TcpP (Figure D.4). Here we CtxBTcpH is also able to inhibit RIP of TcpP due to lack of accumulation of TcpP* (Figure E.5A). These data show that RIP of TcpP is inhibited by all TM constructs. Construction of CtxBTcpH was intended to localize the periplasmic domain of TcpH to the periplasm. To accomplish this, we replaced the predicted N- terminal transmembrane domain (residues 1-25) of TcpH with the Sec signal sequence from ctxB as it has been used to localize other proteins to the periplasmic space (476). However, we observed that TcpH, CtxBTcpH and ΔtcpP CtxBTcpH all associated within the membrane fraction (Figure E.5B). TcpH does not have any predicted “lipidation” motifs (palmitoylation, etc) indicating that CtxBTcpH may associate with an integral membrane protein (possibly via its cysteine residues), or that TcpH has a non-canonical transmembrane domain that was not predicted by sequence alone. Due to its unexpected sub-cellular localization we opted to exclude CtxBTcpH from additional experiments. 208 Figure E.5: TcpH transmembrane constructs inhibit RIP of TcpP and CtxBTcpH remains localized to the cytoplasmic membrane. A) Western blots of spheroplast fractions (cytoplasm and cytoplasmic membrane fractions). TcpH transmembrane constructs (ToxSTcpH and EpsMTcpH) and native TcpH were expressed from pBAD18 in ΔtcpH ΔyaeL background under virulence inducing conditions for 6hrs. All strains, excluding WT, are ΔtcpH ΔyaeL. ΔtcpH* harbors pBAD18 (empty vector). B) Cellular fractionation of V. cholerae cells (i.e., insoluble=membrane fraction) collected after 6hrs of growth under virulence inducing conditions, and cells were fractionated using a French Press (10,000 psi). Numbers above the western blot correspond to the following: 1=WT, 2=ΔtcpH, 3= CtxBTcpH, 4= ΔtcpP, CtxBTcpH, 5= empty lane. RNA polymerase was used as a control to determine if the cellular fraction contained soluble proteins. TcpH remains in the insoluble fraction (i.e., membrane fraction) in the absence of TcpP and upon modification of its transmembrane domain. Bands that are pink were overexposed. 209 E.3 – Future Directions Taken together these data indicate that, similar as in Chapter 4, that the transmembrane domain of TcpH is critical for its function in vivo and the periplasmic domain of TcpH is not critical for colonization of infant mice. This is somewhat surprising given that the majority of TcpH coding sequence is present in the periplasmic domain. From our studies in Chapter 4 we believe that the periplasmic domain is critical for TcpP- TcpH interaction. These data indicate that large portions of the periplasmic domain of TcpH can be lost without affecting colonization of the infant mouse. It is possible that these regions of the TcpH periplasmic domain are relevant in other animal models with mature immune systems and with an established diverse microbiota. Secondly, it is also possible that multiple regions within TcpH contribute to its ability to protect TcpP and larger deletions are required to affect function (e.g., TcpH∆136-103). Lastly, it is also possible that periplasmic deletions we generated, while decreasing stability of TcpH, also functioned to promote its ability to protect TcpP. If true, it would imply that there are regions within TcpH that actively inhibit its ability to protect TcpP from RIP. Future experiments will be required to test these hypotheses. Data presented in Chapter 4 indicate that TcpP-TcpH interaction is critical for inhibition of RIP. Thus, future experiments might include identifying peptides purified TcpH and TcpP recognize using a peptide array (477). These experiments would identify peptides that both TcpP and TcpH recognize thereby informing about what regions within TcpP and TcpH interact. This would allow for targeted point mutations within TcpP and TcpH that will likely yield variants that are more stable that the TcpH Peri constructs discussed above. 210 APPENDIX F: Defining the Mechanism of Action of Toxtazin A and Toxtazin B 211 F.1 – Introduction Vibrio cholerae is a Gram-negative gastrointestinal pathogen that causes the diarrheal disease cholera. Its two major virulence determinants are cholera toxin (ctxAB) and the toxin co-regulated pilus (tcpA-F), and they are regulated by ToxT, an AraC-like activator, and indirectly by ToxR and TcpP (23, 31, 39–42)(39–41, 52–55). Despite our extensive knowledge of V. cholerae pathogenicity mechanisms, cholera continues to persist and afflicts millions every year. Conventional methods to combat V. cholerae have been developed, including vaccines, oral-rehydration therapy, and antibiotic therapy (7– 10)(4–6). However, they have been ineffective at reducing the incidence of V. cholerae infections globally. Thus, new strategies are needed and targeting the toxT regulatory pathway is one such strategy as loss of ToxT, ToxR or TcpP severely attenuates V. cholerae in vivo. We identified two small molecules, toxtazin A and toxtazin B, that inhibit toxT transcription and significantly reduce toxin and pilus production (383). The Toxtazins do not inhibit growth of V. cholerae (383). Oral administration of toxtazin B was effective in vivo, decreasing colonization of V. cholerae strain O395 by approximately 1000-fold (383). The precise mechanism of action for both toxtazin A and B have yet to be determined. Currently, the data show that toxtazin A does not alter localization or DNA binding of both TcpP and ToxR, and yet still reduces toxT transcription considerably (383). Proteomics analysis showed that toxtazin A stimulates many proteins, including several involved in oxidative stress responses, and suggests that toxtazin A inhibits toxT via a novel regulatory mechanism (Anthouard R. and DiRita V. unpublished). Secondly, toxtazin B, on the other hand, inhibits toxT transcription by reducing levels of tcpP transcription (Anthouard R. and DiRita V. unpublished). The mechanism by which toxtazin 212 B affects tcpP transcription is not currently known and elucidating this mechanism will add new knowledge to our understanding of tcpP transcription regulatory mechanisms (Anthouard R. and DiRita V. unpublished). As toxtazin A had no effect on localization or DNA binding of ToxR and TcpP, we focused on identifying the mechanism of action of toxatzin A. F.2 – Results Prior experiments have revealed that Toxtazin A treated V. cholerae cells have an increase (~4 fold) in the abundance of proteins involved in cell redox homeostasis (35% of upregulated proteins), amino acid biosynthesis and transport (15% of upregulated proteins), and metabolic enzymes (20% of upregulated proteins) (unpublished work Anthouard et. al.). A protein that was of particular interest was malate synthase, which was not detected in DMSO treated cells (unpublished work Anthouard et. al.). Malate synthase produces malate and CoA from acetyl-CoA and glyoxylate. Previous work has established that central metabolism is critical for toxT transcription (478). Specifically, acetyl-CoA levels are hypothesized to directly correlate with toxT transcription (i.e., high levels of acetyl-CoA leads to elevated toxT transcription) (478). We hypothesized that elevated levels of malate synthase in toxtazin A treated cells inhibited toxT transcription by depleting the cell of acetyl-CoA levels. The mechanism by which acetyl-CoA stimulates toxT transcription is not known. Acetyl-CoA is essential for do novo fatty acid synthesis. Thus, it is possible that acetyl-CoA influences toxT transcription via de novo phospholipid synthesis. In Chapter 4 we present data that demonstrates that RIP of TcpP is influenced 213 by the cytoplasmic membrane. As toxtazin A has been shown to not reduce levels of TcpP, we hypothesized that toxtazin A would inhibit toxT transcription independent of RIP of TcpP. To test this, we measured toxT transcription in WT and in tcpP-PAmCherry cells. In Chapter 3 we demonstrate that TcpP-PAmCherry is resistant to RIP (Figure C.1A). We found that tcpP-PAmCherry cells were sensitive to toxtazin A (Figure F.1A). These data indicated that toxtazin A inhibits toxT transcription independent of RIP of TcpP. These data also showed that our toxtazin B stock was no longer effective at inhibiting virulence factor production in WT cells (Figure F.1A). Follow up studies with working with a malate synthase revealed that WT cells were also insensitive to toxtazin A. Taken together, these data indicated that our toxtazin A and B compounds had degraded while in cold storage. Unfortunately acquisition of fresh toxtazin A compound was not possible. An analog of toxtazin A (toxtazin A’) was available as a fresh powder, but was not effective at inhibiting toxT transcription, data not shown. Prior to our toxtazin A and B stocks becoming ineffective, we screened for spontaneous V. cholerae mutants that were insensitive to toxtazin A or toxtazin B. Synthesis of toxin co-regulated pilus (Tcp) is known to promote autoagglutination of V. cholerae cells (32). Thus, we selected for cells that stimulated synthesis of the Tcp in the presence of toxtazin A or B. To do this WT cells were inoculated in virulence inducing media and cultured for 8hrs with or without the toxtazin’s. Cultures were then incubated at room temperature under static conditions for an additional 16hrs. Cells that aggregated at the bottom of the flask were collected and inoculated into fresh virulence inducing media with toxtazin A or B. The cells were passaged for 5 days to in the presence of toxtazin A or B. After day 5 400 colonies were selected at random (200 toxtazin A and 214 200 toxtazin B passaged cells). The colonies were then cultured in virulence inducing conditions for 24hrs with and without toxtazin A or B and CtxB levels were quantified from culture supernatants. Out of 120 possible mutants we identified 6 toxtazin B and 1 toxtazin A insensitive mutants (Figure F.1B). Follow up validation of these possible mutants revealed that they remained sensitive to toxtazin A or toxtazin B (Figure F.1C). These data indicate that our screen was not sufficient to identify tolerant toxtazin A and B mutants. Figure F.1: Characterization of toxtazin A and B mechanism of action. A-C) CtxB levels collected after 24hrs from culture supernatants. Black bars represent virulence inducing conditions. White bars represent non-virulence inducing conditions. Red bars indicate virulence inducing conditions supplemented with 10μM toxtazin A. Blue bars 215 Figure F.1 (cont’d) virulence inducing conditions supplemented with 10μM toxtazin B. B) WT and possible toxtazin A and B tolerant cells were grown in LB with and without toxtazin A or B for 24hrs. After 24hrs CtxB levels were quantified for both conditions. Levels of CtxB produced by the indicated strain in the presence and absence of toxtazin A or B was used to calculate the ratio of inhibition (i.e., CtxB ug/ul/O.D.600nm produced in the presence of toxtazin A or B divided by CtxB ug/ul/O.D.600nm produced without toxtazin A or B). A ratio of inhibition below 1 indicates less CtxB was produced in the presence of toxtazin A or B. F.3 – Future Directions As we were unable to acquire active toxtazin A or active toxtazin A analogs, acquiring fresh toxtazin A is essential for defining the mechanism of action of toxtazin A. Future experiments will entail testing malate synthase mutants tolerance to toxtazin A. We hypothesize that a malate synthase mutant will be resistant to toxtazin A, and thereby synthesize WT levels of toxT transcripts. Secondly, we hypothesize that upregulation of malate synthase will inhibit toxT transcription independent of toxtazin A treatment. Acetyl- CoA is essential for de novo fatty acid synthesis in bacteria (479). As TcpP and ToxR are localized in the cytoplasmic membrane, it stands to reason that increased malate synthase activity influences the composition of phospholipids that compose the cytoplasmic membrane due to depletion of acetyl-CoA levels. Our data show that toxtazin A inhibits toxT transcription independent of RIP of TcpP. Thus, it remains possible that phospholipid composition can impede TcpP activity. Future experiments are aimed at testing this hypothesis. 216 APPENDIX G: Heterogeneous Single-Cell toxT Transcription 217 G.1 – Introduction It was previously demonstrated that TcpA transcription is highly heterogeneous among individual V. cholerae cells in vitro and in vivo, and it is driven by the toxT autoregulatory loop (337). The remaining question is why do these sub-population of V. cholerae cells continue to stimulate toxT transcription? We hypothesized that a sub- population of V. cholerae cells stimulates elevated toxT transcription, increasing the overall pool of ToxT within the cell, and this thereby drives heterogenous single-cell transcription of TcpA. G.2 – Results and Discussion In line with these data, we also see that toxT transcription is highly heterogeneous among single V. cholerae cells (Figure G.1). Furthermore, cells stimulate high toxT transcription independent of cell density, temperature, pH, RIP, direct cell contact, culture age, and the toxT autoregulatory loop (Figure G.1). However, TcpP and ToxR are required for heterogeneous toxT transcription (data not shown). Furthermore, addition of PAmCherry to the C-terminus of TcpP does not result in constitutive toxT transcription in all cells (Figure G.1). These data suggest that elevated toxT transcription within a sub- population of V. cholerae cells is due to TcpP and ToxR. At any time, a high percentage of the TcpP-PAmCherry molecules in the V. cholerae cells are in intermediate diffusion states and therefore are not actively associated with DNA/toxTpro, it remains possible that diffusion states of TcpP molecules differ between individual cells and promote high transition rates of TcpP molecules from the fast and intermediate diffusion states to the slow diffusion state via an unknown mechanism. 218 Figure G.1: Single-cell toxT transcription is heterogenous in V. cholerae. Cultures were grown under virulence inducing conditions (VIC) for 6hrs unless otherwise stated. A) TcpP-PAm. B) WT. Images on the left are phase contrast images of V. cholerae cells harboring pBH6119 (toxT::GFP) and images on the left are fluorescent images of the same cells. Heterogeneous toxT transcription as seen in WT cells was also observed in ΔtcpH, Δtsp, ΔyaeL, Δtsp ΔyaeL, 4- 24hrs VIC, and 4-24hrs under non-virulence inducing conditions, data not shown. ΔtcpP and ΔtoxR cells displayed no fluorescence whatsoever, data not shown. Regardless of the specific mechanism, we reasoned that heterogeneous diffusion dynamics of TcpP are important for heterogeneous toxT transcription among V. cholerae cells. Using an ectopic toxT::GFP transcriptional reporter, we observed that only a small percentage of WT V. cholerae cells have high toxT transcription. Furthermore, we found that heterogeneous toxT transcription is independent of cell density, temperature, pH, direct cell contact, culture age, and the toxT autoregulatory loop (Figure G.1). TcpP and ToxR are required to support heterogenous toxT transcription in V. cholerae cells, data not shown. Taken together, these results suggest heterogeneous transcription of toxT in 219 V. cholerae cells is due to TcpP and ToxR, not transcription or RIP of TcpP and ToxR. Currently, RIP of TcpP is only known to be mediated by Tsp and YaeL. Deletion of both tsp and yaeL results in a reduction in TcpA and TcpP levels under virulence inducing and non-virulence inducing conditions (Figure G.2). Secondly, an additional non-TcpP* band can be observed in overnight cultures of Δtsp ΔyaeL cells (Figure G.2A). This indicates that TcpP is undergoing proteolysis via an unknown protease and is only capable of degrading TcpP in the absence of both tsp and yaeL. Figure G.2: TcpP is sensitive to an unknown protease upon mutation of tsp and yaeL. A) overnight cultures of V. cholerae. B) 8hrs of growth under virulence inducing conditions or non-virulence inducing conditions (indicated at the bottom of the gel) supplemented with or without 12.5 µM batimastat. Levels of TcpP and TcpA were probed for each samples. Batimastat is a metalloprotease inhibitor that has been shown to inhibit RseP (a homolog of YaeL) within Escherichia coli (480). 220 G.3 – Future Directions Currently, the data indicate that toxT transcription is highly heterogeneous within V. cholerae cells. Our data show that heterogeneous toxT transcription is dependent on TcpP and ToxR, but it is independent of cell density, culture age, TcpH, RIP via Tsp and YaeL, pH, temperature, and direct cell contact. As discussed in Chapter 3, the intermediate and fast diffusion states of TcpP-PAmCherry are critical for this sub- population of V. cholerae cells to toxT transcription. As TcpP and ToxR are localized to the cytoplasmic membrane, we hypothesize that phospholipid composition within the sub- population of constitutive toxT expressing cells to differs and promotes the transition probability of TcpP molecules from the intermediate diffusion state to the slow diffusion state. Alternatively, heterogeneous single-cell toxT transcription could be mediated by downregulation of the unidentified protease within the sub-population of constitutive toxT expressing cells. Testing these hypotheses will be the subject of future research. 221 REFERENCES 222 REFERENCES 1. Centers for Disease Control and Prevention (CDC). 1993. Imported cholera associated with a newly described toxigenic Vibrio cholerae O139 strain--California, 1993. MMWR Morb Mortal Wkly Rep 42:501–503. 2. Ali M, Nelson AR, Lopez AL, Sack DA. 2015. Updated global burden of cholera in endemic countries. PLoS Negl Trop Dis 9:e0003832. 3. Gil AI, Louis VR, Rivera ING, Lipp E, Huq A, Lanata CF, Taylor DN, Russek-Cohen E, Choopun N, Bradley Sack R, Colwell RR. 2004. Occurrence and distribution of Vibrio cholerae in the coastal environment of Peru. Environmental Microbiology https://doi.org/10.1111/j.1462-2920.2004.00601.x. 4. Pierce NF, Banwell JG, Mitra RC, Caranasos GJ, Keimowitz RI, Mondal A, Manji PM. 1968. Effect of Intragastric Glucose-Electrolyte Infusion Upon Water and Electrolyte Balance in Asiatic Cholera. Gastroenterology https://doi.org/10.1016/s0016-5085(19)34043-0. 5. Hirschhorn N, Kinzie JL, Sachar DB, Northrup RS, Taylor JO, Ahmad SZ, Phillips RA. 1968. Decrease in net stool output in cholera during intestinal perfusion with glucose- containing solutions. N Engl J Med 279:176–181. 6. Wallace CK, Anderson PN, Brown TC, Khanra SR, Lewis GW, Pierce NF, Sanyal SN, Segre GV, Waldman RH. 1968. Optimal antibiotic therapy in cholera. Bull World Health Organ 39:239–245. 7. Jelinek T, Kollaritsch H. 2008. Vaccination with Dukoral®against travelers’ diarrhea (ETEC) and cholera. Expert Review of Vaccines. 8. Saha A, Chowdhury MI, Khanam F, Bhuiyan MS, Chowdhury F, Khan AI, Khan IA, Clemens J, Ali M, Cravioto A, Qadri F. 2011. Safety and immunogenicity study of a killed bivalent (O1 and O139) whole-cell oral cholera vaccine Shanchol, in Bangladeshi adults and children as young as 1 year of age. Vaccine 29:8285–8292. 9. Cabrera A, Lepage JE, Sullivan KM, Seed SM. 2017. Vaxchora: A Single-Dose Oral Cholera Vaccine. Ann Pharmacother 51:584–589. 10. Sinha R, Koley H, Nag D, Mitra S, Mukhopadhyay AK, Chattopadhyay B. 2015. Pentavalent outer membrane vesicles of Vibrio cholerae induce adaptive immune response and protective efficacy in both adult and passive suckling mice models. Microbes Infect 17:215– 227. 11. Hoge CW, Bodhidatta L, Echeverria P, Deesuwan M, Kitporka P. 1996. Epidemiologic Study of Vibrio cholerae O1 and O139 in Thailand: At the Advancing Edge of the Eighth Pandemic. American Journal of Epidemiology https://doi.org/10.1093/oxfordjournals.aje.a008737. 12. Swerdlow DL, Ries AA. 1993. Vibrio cholerae non-O1--the eighth pandemic? Lancet. 223 13. Nair GB, Faruque SM, Bhuiyan NA, Kamruzzaman M, Siddique AK, Sack DA. 2002. New variants of Vibrio cholerae O1 biotype El Tor with attributes of the classical biotype from hospitalized patients with acute diarrhea in Bangladesh. J Clin Microbiol 40:3296–3299. 14. Chunara R, Andrews JR, Brownstein JS. 2012. Social and news media enable estimation of epidemiological patterns early in the 2010 Haitian cholera outbreak. Am J Trop Med Hyg 86:39–45. 15. Chowdhury FR, Nur Z, Hassan N, von Seidlein L, Dunachie S. 2017. Pandemics, pathogenicity and changing molecular epidemiology of cholera in the era of global warming. Ann Clin Microbiol Antimicrob 16:10. 16. Mooi FR, Bik EM. 1997. The evolution of epidemic Vibrio cholerae strains. Trends Microbiol 5:161–165. 17. Faruque SM, Albert MJ, Mekalanos JJ. 1998. Epidemiology, genetics, and ecology of toxigenic Vibrio cholerae. Microbiol Mol Biol Rev 62:1301–1314. 18. Keasler SP, Hall RH. 1993. Detecting and biotyping Vibrio cholerae O1 with multiplex polymerase chain reaction. Lancet 341:1661. 19. Dziejman M, Balon E, Boyd D, Fraser CM, Heidelberg JF, Mekalanos JJ. 2002. Comparative genomic analysis of Vibrio cholerae: Genes that correlate with cholera endemic and pandemic disease. Proceedings of the National Academy of Sciences https://doi.org/10.1073/pnas.042667999. 20. Thomas S, Williams SG, Manning PA. 1995. Regulation of tcp genes in classical and E1 Tor strains of Vibrio cholerae O1. Gene https://doi.org/10.1016/0378-1119(95)00610-x. 21. Phillips RA. 1964. WATER AND ELECTROLYTE LOSSES IN CHOLERA. Fed Proc 23:705–712. 22. Nelson EJ, Harris JB, Morris JG Jr, Calderwood SB, Camilli A. 2009. Cholera transmission: the host, pathogen and bacteriophage dynamic. Nat Rev Microbiol 7:693–702. 23. Angelichio MJ, Spector J, Waldor MK, Camilli A. 1999. Vibrio cholerae intestinal population dynamics in the suckling mouse model of infection. Infect Immun 67:3733–3739. 24. Millet YA, Alvarez D, Ringgaard S, von Andrian UH, Davis BM, Waldor MK. 2014. Insights into Vibrio cholerae intestinal colonization from monitoring fluorescently labeled bacteria. PLoS Pathog 10:e1004405. 25. Camilli A, Beattie DT, Mekalanos JJ. 1994. Use of genetic recombination as a reporter of gene expression. Proceedings of the National Academy of Sciences. 26. Ho BT, Dong TG, Mekalanos JJ. 2014. A view to a kill: the bacterial type VI secretion system. Cell Host Microbe 15:9–21. 27. Wu Z, Nybom P, Magnusson KE. 2000. Distinct effects of Vibrio cholerae haemagglutinin/protease on the structure and localization of the tight junction-associated proteins occludin and ZO-1. Cell Microbiol 2:11–17. 28. Uzzau S, Lu R, Wang W, Fiore C, Fasano A. 2001. Purification and preliminary 224 characterization of the zonula occludens toxin receptor from human (CaCo2) and murine (IEC6) intestinal cell lines. FEMS Microbiol Lett 194:1–5. 29. Goldblum SE, Rai U, Tripathi A, Thakar M, De Leo L, Di Toro N, Not T, Ramachandran R, Puche AC, Hollenberg MD, Fasano A. 2011. The active Zot domain (aa 288–293) increases ZO‐1 and myosin 1C serine/threonine phosphorylation, alters interaction between ZO‐1 and its binding partners, and induces tight junction disassembly through proteinase activated receptor 2 activation. The FASEB Journal https://doi.org/10.1096/fj.10-158972. 30. Herrington DA, Hall RH, Losonsky G, Mekalanos JJ, Taylor RK, Levine MM. 1988. Toxin, toxin-coregulated pili, and the toxR regulon are essential for Vibrio cholerae pathogenesis in humans. J Exp Med 168:1487–1492. 31. Taylor RK, Miller VL, Furlong DB, Mekalanos JJ. 1987. Use of phoA gene fusions to identify a pilus colonization factor coordinately regulated with cholera toxin. Proc Natl Acad Sci U S A 84:2833–2837. 32. Chiang SL, Taylor RK, Koomey M, Mekalanos JJ. 1995. Single amino acid substitutions in the N-terminus of Vibrio cholerae TcpA affect colonization, autoagglutination, and serum resistance. Mol Microbiol 17:1133–1142. 33. Stern AM, Hay AJ, Liu Z, Desland FA, Zhang J, Zhong Z, Zhu J. 2012. The NorR regulon is critical for Vibrio cholerae resistance to nitric oxide and sustained colonization of the intestines. MBio 3:e00013–12. 34. Bitar A, Aung KM, Wai SN, Hammarström M-L. 2019. Vibrio cholerae derived outer membrane vesicles modulate the inflammatory response of human intestinal epithelial cells by inducing microRNA-146a. Sci Rep 9:7212. 35. Woida PJ, Satchell KJF. 2020. The MARTX toxin silences the inflammatory response to cytoskeletal damage before inducing actin cytoskeleton collapse. Sci Signal 13. 36. Bharati K, Ganguly NK. 2011. Cholera toxin: a paradigm of a multifunctional protein. Indian J Med Res 133:179–187. 37. Somarny WMZ, Mariana NS, Neela V, Rozita R, Raha AR. 2002. Optimization of Parameters for Accessory Cholera Enterotoxin (Ace) Protein Expression. Journal of Medical Sciences https://doi.org/10.3923/jms.2002.74.76. 38. Trucksis M, Conn TL, Wasserman SS, Sears CL. 2000. Vibrio cholerae ACE stimulates Ca(2+)-dependent Cl(-)/HCO(3)(-) secretion in T84 cells in vitro. Am J Physiol Cell Physiol 279:C567–77. 39. Krukonis ES, Yu RR, Dirita VJ. 2000. The Vibrio cholerae ToxR/TcpP/ToxT virulence cascade: distinct roles for two membrane-localized transcriptional activators on a single promoter. Mol Microbiol 38:67–84. 40. DiRita VJ, Parsot C, Jander G, Mekalanos JJ. 1991. Regulatory cascade controls virulence in Vibrio cholerae. Proc Natl Acad Sci U S A 88:5403–5407. 41. Higgins DE, DiRita VJ. 1994. Transcriptional control of toxT, a regulatory gene in the ToxR regulon of Vibrio cholerae. Mol Microbiol 14:17–29. 225 42. Higgins DE, Nazareno E, DiRita VJ. 1992. The virulence gene activator ToxT from Vibrio cholerae is a member of the AraC family of transcriptional activators. J Bacteriol 174:6974– 6980. 43. Plecha SC, Withey JH. 2015. Mechanism for inhibition of Vibrio cholerae ToxT activity by the unsaturated fatty acid components of bile. J Bacteriol 197:1716–1725. 44. Cruite JT, Kovacikova G, Clark KA, Woodbrey AK, Skorupski K, Jon Kull F. 2019. Structural basis for virulence regulation in Vibrio cholerae by unsaturated fatty acid components of bile. Communications Biology https://doi.org/10.1038/s42003-019-0686-x. 45. Childers BM, Cao X, Weber GG, Demeler B, Hart PJ, Klose KE. 2011. N-terminal residues of the Vibrio cholerae virulence regulatory protein ToxT involved in dimerization and modulation by fatty acids. J Biol Chem 286:28644–28655. 46. Withey JH, Nag D, Plecha SC, Sinha R, Koley H. 2015. Conjugated Linoleic Acid Reduces Cholera Toxin Production In vitro and In vivo by Inhibiting Vibrio cholerae ToxT Activity. Antimicrob Agents Chemother 59:7471–7476. 47. Abuaita BH, Withey JH. 2011. Termination of Vibrio cholerae virulence gene expression is mediated by proteolysis of the major virulence activator, ToxT. Mol Microbiol 81:1640– 1653. 48. Thomson JJ, Plecha SC, Withey JH. 2015. A small unstructured region in Vibrio cholerae ToxT mediates the response to positive and negative effectors and ToxT proteolysis. J Bacteriol 197:654–668. 49. Hogan DL, Ainsworth MA, Isenberg JI. 1994. Review article: gastroduodenal bicarbonate secretion. Aliment Pharmacol Ther 8:475–488. 50. Thomson JJ, Withey JH. 2014. Bicarbonate increases binding affinity of Vibrio cholerae ToxT to virulence gene promoters. J Bacteriol 196:3872–3880. 51. Shakhnovich EA, Hung DT, Pierson E, Lee K, Mekalanos JJ. 2007. Virstatin inhibits dimerization of the transcriptional activator ToxT. Proc Natl Acad Sci U S A 104:2372– 2377. 52. Häse CC, Mekalanos JJ. 1998. TcpP protein is a positive regulator of virulence gene expression in Vibrio cholerae. Proc Natl Acad Sci U S A 95:730–734. 53. Miller VL, Taylor RK, Mekalanos JJ. 1987. Cholera toxin transcriptional activator ToxR is a transmembrane DNA binding protein. Cell. 54. Crawford JA, Krukonis ES, DiRita VJ. 2003. Membrane localization of the ToxR winged- helix domain is required for TcpP-mediated virulence gene activation in Vibrio cholerae. Mol Microbiol 47:1459–1473. 55. Krukonis ES, DiRita VJ. 2003. DNA binding and ToxR responsiveness by the wing domain of TcpP, an activator of virulence gene expression in Vibrio cholerae. Mol Cell 12:157–165. 56. Beck NA, Krukonis ES, DiRita VJ. 2004. TcpH Influences Virulence Gene Expression in Vibrio cholerae by Inhibiting Degradation of the Transcription Activator TcpP. Journal of Bacteriology. 226 57. Almagro-Moreno S, Root MZ, Taylor RK. 2015. Role of ToxS in the proteolytic cascade of virulence regulator ToxR in Vibrio cholerae. Mol Microbiol 98:963–976. 58. Teoh WP, Matson JS, DiRita VJ. 2015. Regulated intramembrane proteolysis of the virulence activator TcpP in Vibrio cholerae is initiated by the tail-specific protease (Tsp). Mol Microbiol 97:822–831. 59. Matson JS, DiRita VJ. 2005. Degradation of the membrane-localized virulence activator TcpP by the YaeL protease in Vibrio cholerae. Proc Natl Acad Sci U S A 102:16403–16408. 60. Skorupski K, Taylor RK. 1997. Cyclic AMP and its receptor protein negatively regulate the coordinate expression of cholera toxin and toxin-coregulated pilus in Vibrio cholerae. Proc Natl Acad Sci U S A 94:265–270. 61. Kovacikova G, Skorupski K. 2001. Overlapping binding sites for the virulence gene regulators AphA, AphB and cAMP-CRP at the Vibrio cholerae tcpPH promoter. Molecular Microbiology https://doi.org/10.1046/j.1365-2958.2001.02518.x. 62. Behari J, Stagon L, Calderwood SB. 2001. pepA , a Gene Mediating pH Regulation of Virulence Genes in Vibrio cholerae. Journal of Bacteriology https://doi.org/10.1128/jb.183.1.178-188.2001. 63. Kovacikova G, Lin W, Skorupski K. 2010. The LysR-Type Virulence Activator AphB Regulates the Expression of Genes in Vibrio cholerae in Response to Low pH and Anaerobiosis. Journal of Bacteriology https://doi.org/10.1128/jb.00193-10. 64. Taylor JL, De Silva RS, Kovacikova G, Lin W, Taylor RK, Skorupski K, Jon Kull F. 2012. The crystal structure of AphB, a virulence gene activator from Vibrio cholerae, reveals residues that influence its response to oxygen and pH. Molecular Microbiology https://doi.org/10.1111/j.1365-2958.2011.07919.x. 65. Liu Z, Wang H, Zhou Z, Naseer N, Xiang F, Kan B, Goulian M, Zhu J. 2016. Differential Thiol-Based Switches Jump-Start Vibrio cholerae Pathogenesis. Cell Rep 14:347–354. 66. Kovacikova G, Skorupski K. 2002. Regulation of virulence gene expression in Vibrio cholerae by quorum sensing: HapR functions at the aphA promoter. Molecular Microbiology https://doi.org/10.1046/j.1365-2958.2002.03229.x. 67. Zhu J, Miller MB, Vance RE, Dziejman M, Bassler BL, Mekalanos JJ. 2002. Quorum- sensing regulators control virulence gene expression in Vibrio cholerae. Proc Natl Acad Sci U S A 99:3129–3134. 68. Ball AS, Chaparian RR, van Kessel JC. 2017. Quorum Sensing Gene Regulation by LuxR/HapR Master Regulators in Vibrios. J Bacteriol 199. 69. Martínez-Hackert E, Stock AM. 1997. Structural relationships in the OmpR family of winged-helix transcription factors. J Mol Biol 269:301–312. 70. Goss TJ, Seaborn CP, Gray MD, Krukonis ES. 2010. Identification of the TcpP-binding site in the toxT promoter of Vibrio cholerae and the role of ToxR in TcpP-mediated activation. Infect Immun 78:4122–4133. 71. Goss TJ, Morgan SJ, French EL, Krukonis ES. 2013. ToxR recognizes a direct repeat 227 element in the toxT, ompU, ompT, and ctxA promoters of Vibrio cholerae to regulate transcription. Infect Immun 81:884–895. 72. Kazi MI, Conrado AR, Mey AR, Payne SM, Davies BW. 2016. ToxR Antagonizes H-NS Regulation of Horizontally Acquired Genes to Drive Host Colonization. PLoS Pathog 12:e1005570. 73. Higgins DE, DiRita VJ. 1996. Genetic analysis of the interaction between Vibrio cholerae transcription activator ToxR and toxT promoter DNA. J Bacteriol 178:1080–1087. 74. Fan F, Liu Z, Jabeen N, Birdwell LD, Zhu J, Kan B. 2014. Enhanced interaction of Vibrio cholerae virulence regulators TcpP and ToxR under oxygen-limiting conditions. Infect Immun 82:1676–1682. 75. Bina TF, Kunkle DE, Bina XR, Mullet SJ, Wendell SG, Bina JE. 2021. Bile salts promote ToxR regulon activation during growth under virulence inducing conditions. Infect Immun IAI0044121. 76. Shi M, Li N, Xue Y, Zhong Z, Yang M. 2020. The 58th Cysteine of TcpP Is Essential for Vibrio cholerae Virulence Factor Production and Pathogenesis. Frontiers in Microbiology https://doi.org/10.3389/fmicb.2020.00118. 77. Hay AJ, Yang M, Xia X, Liu Z, Hammons J, Fenical W, Zhu J. 2017. Calcium Enhances Bile Salt-Dependent Virulence Activation in Vibrio cholerae. Infect Immun 85. 78. Yang M, Liu Z, Hughes C, Stern AM, Wang H, Zhong Z, Kan B, Fenical W, Zhu J. 2013. Bile salt-induced intermolecular disulfide bond formation activates Vibrio cholerae virulence. Proc Natl Acad Sci U S A 110:2348–2353. 79. Lembke M, Pennetzdorfer N, Tutz S, Koller M, Vorkapic D, Zhu J, Schild S, Reidl J. 2018. Proteolysis of ToxR is controlled by cysteine-thiol redox state and bile salts inVibrio cholerae. Molecular Microbiology https://doi.org/10.1111/mmi.14125. 80. Almagro-Moreno S, Kim TK, Skorupski K, Taylor RK. 2015. Proteolysis of virulence regulator ToxR is associated with entry of Vibrio cholerae into a dormant state. PLoS Genet 11:e1005145. 81. Gubensäk N, Wagner GE, Schrank E, Falsone FS, Berger TMI, Pavkov‐Keller T, Reidl J, Zangger K. 2021. The periplasmic domains of Vibriocholerae ToxR and ToxS are forming a strong heterodimeric complex independent on the redox state of ToxR cysteines. Molecular Microbiology https://doi.org/10.1111/mmi.14673. 82. Carroll PA, Tashima KT, Rogers MB, DiRita VJ, Calderwood SB. 1997. Phase variation in tcpH modulates expression of the ToxR regulon in Vibrio cholerae. Molecular Microbiology. 83. Midgett CR, Almagro-Moreno S, Pellegrini M, Taylor RK, Skorupski K, Kull FJ. 2017. Bile salts and alkaline pH reciprocally modulate the interaction between the periplasmic domains of Vibrio cholerae ToxR and ToxS. Mol Microbiol 105:258–272. 84. Midgett CR, Swindell RA, Pellegrini M, Kull FJ. 2020. Publisher Correction: A disulfide constrains the ToxR periplasmic domain structure, altering its interactions with ToxS and bile-salts. Sci Rep 10:12085. 228 85. Lembke M, Höfler T, Walter A-N, Tutz S, Fengler V, Schild S, Reidl J. 2020. Host stimuli and operator binding sites controlling protein interactions between virulence master regulator ToxR and ToxS in Vibrio cholerae. Mol Microbiol 114:262–278. 86. Sirisaengtaksin N, Odem MA, Bosserman RE, Flores EM, Krachler AM. 2020. TheE. colitranscription factor GrlA is regulated by subcellular compartmentalization and activated in response to mechanical stimuli. Proceedings of the National Academy of Sciences https://doi.org/10.1073/pnas.1917500117. 87. Muro-Pastor AM, Ostrovsky P, Maloy S. 1997. Regulation of gene expression by repressor localization: biochemical evidence that membrane and DNA binding by the PutA protein are mutually exclusive. J Bacteriol 179:2788–2791. 88. Parkinson JS, Kofoid EC. 1992. Communication modules in bacterial signaling proteins. Annu Rev Genet 26:71–112. 89. Ulrich LE, Koonin EV, Zhulin IB. 2005. One-component systems dominate signal transduction in prokaryotes. Trends Microbiol 13:52–56. 90. Paget MS. 2015. Bacterial Sigma Factors and Anti-Sigma Factors: Structure, Function and Distribution. Biomolecules 5:1245–1265. 91. Staroń A, Sofia HJ, Dietrich S, Ulrich LE, Liesegang H, Mascher T. 2009. The third pillar of bacterial signal transduction: classification of the extracytoplasmic function (ECF) sigma factor protein family. Mol Microbiol 74:557–581. 92. 2011. Two-Component Signaling Systems. Elsevier. 93. Zarrella TM, Bai G. 2020. The Many Roles of the Bacterial Second Messenger Cyclic di- AMP in Adapting to Stress Cues. J Bacteriol 203. 94. Römling U, Galperin MY, Gomelsky M. 2013. Cyclic di-GMP: the first 25 years of a universal bacterial second messenger. Microbiol Mol Biol Rev 77:1–52. 95. Hengge R, Gründling A, Jenal U, Ryan R, Yildiz F. 2016. Bacterial Signal Transduction by Cyclic Di-GMP and Other Nucleotide Second Messengers. Journal of Bacteriology https://doi.org/10.1128/jb.00331-15. 96. Beck NA, Krukonis ES, DiRita VJ. 2004. TcpH influences virulence gene expression in Vibrio cholerae by inhibiting degradation of the transcription activator TcpP. J Bacteriol 186:8309–8316. 97. Hobbs M, Collie ES, Free PD, Livingston SP, Mattick JS. 1993. PilS and PilR, a two- component transcriptional regulatory system controlling expression of type 4 fimbriae in Pseudomonas aeruginosa. Mol Microbiol 7:669–682. 98. Carrick CS, Fyfe JA, Davies JK. 2000. The genome of Neisseria gonorrhoeae retains the remnants of a two-component regulatory system that once controlled piliation. FEMS Microbiol Lett 186:197–201. 99. Bischof LF, Haurat MF, Albers S-V. 2019. Two membrane-bound transcription factors regulate expression of various type-IV-pili surface structures in Sulfolobus acidocaldarius. PeerJ https://doi.org/10.7717/peerj.6459. 229 100. Lassak K, Peeters E, Wróbel S, Albers S-V. 2013. The one-component system ArnR: a membrane-bound activator of the crenarchaeal archaellum. Mol Microbiol 88:125–139. 101. Kodama T, Gotoh K, Hiyoshi H, Morita M, Izutsu K, Akeda Y, Park K-S, Cantarelli VV, Dryselius R, Iida T, Honda T. 2010. Two regulators of Vibrio parahaemolyticus play important roles in enterotoxicity by controlling the expression of genes in the Vp-PAI region. PLoS One 5:e8678. 102. Alam A, Tam V, Hamilton E, Dziejman M. 2010. vttRA and vttRB Encode ToxR family proteins that mediate bile-induced expression of type three secretion system genes in a non-O1/non-O139 Vibrio cholerae strain. Infect Immun 78:2554–2570. 103. Miller KA, Hamilton E, Dziejman M. 2012. The Vibrio cholerae trh Gene Is Coordinately RegulatedIn vitrowith Type III Secretion System Genes by VttRA/VttRBbut Does Not Contribute to Caco2-BBE Cell Cytotoxicity. Infection and Immunity https://doi.org/10.1128/iai.00832-12. 104. Ante VM, Bina XR, Howard MF, Sayeed S, Taylor DL, Bina JE. 2015. Vibrio cholerae leuO Transcription Is Positively Regulated by ToxR and Contributes to Bile Resistance. J Bacteriol 197:3499–3510. 105. Provenzano D, Schuhmacher DA, Barker JL, Klose KE. 2000. The Virulence Regulatory Protein ToxR Mediates Enhanced Bile Resistance in Vibrio cholerae and Other Pathogenic Vibrio Species. Infection and Immunity https://doi.org/10.1128/iai.68.3.1491-1497.2000. 106. Manson JM, Keis S, Smith JMB, Cook GM. 2004. Acquired Bacitracin Resistance in Enterococcus faecalis Is Mediated by an ABC Transporter and a Novel Regulatory Protein, BcrR. Antimicrobial Agents and Chemotherapy. 107. Kuper C, Jung K. 2005. CadC-mediated activation of the cadBA promoter in Escherichia coli. J Mol Microbiol Biotechnol 10:26–39. 108. Gu D, Wang K, Lu T, Li L, Jiao X. 2021. Vibrio parahaemolyticus CadC regulates acid tolerance response to enhance bacterial motility and cytotoxicity. J Fish Dis 44:1155–1168. 109. Choi SH. 2008. Activation of the Vibrio vulnificus cadBA Operon by Leucine-Responsive Regulatory Protein is Mediated by CadC. Journal of Microbiology and Biotechnology https://doi.org/10.4014/jmb.0800.121. 110. Dalia AB, Lazinski DW, Camilli A. 2014. Identification of a membrane-bound transcriptional regulator that links chitin and natural competence in Vibrio cholerae. MBio 5:e01028–13. 111. Santamaría L, Reverón I, López de Felipe F, de Las Rivas B, Muñoz R. 2018. Unravelling the Reduction Pathway as an Alternative Metabolic Route to Hydroxycinnamate Decarboxylation in Lactobacillus plantarum. Appl Environ Microbiol 84. 112. Steele MI, Lorenz D, Hatter K, Park A, Sokatch JR. 1992. Characterization of the mmsAB operon of Pseudomonas aeruginosa PAO encoding methylmalonate-semialdehyde dehydrogenase and 3-hydroxyisobutyrate dehydrogenase. J Biol Chem 267:13585–13592. 113. Olson ME, King JM, Yahr TL, Horswill AR. 2013. Sialic acid catabolism in Staphylococcus aureus. J Bacteriol 195:1779–1788. 230 114. Meijerink M, van Hemert S, Taverne N, Wels M, de Vos P, Bron PA, Savelkoul HF, van Bilsen J, Kleerebezem M, Wells JM. 2010. Identification of genetic loci in Lactobacillus plantarum that modulate the immune response of dendritic cells using comparative genome hybridization. PLoS One 5:e10632. 115. Gumerov VM, Ortega DR, Adebali O, Ulrich LE, Zhulin IB. 2020. MiST 3.0: an updated microbial signal transduction database with an emphasis on chemosensory systems. Nucleic Acids Research https://doi.org/10.1093/nar/gkz988. 116. Krogh A, Larsson B, von Heijne G, Sonnhammer ELL. 2001. Predicting transmembrane protein topology with a hidden markov model: application to complete genomes11Edited by F. Cohen. Journal of Molecular Biology https://doi.org/10.1006/jmbi.2000.4315. 117. Gumerov VM, Zhulin IB. 2020. TREND: a platform for exploring protein function in prokaryotes based on phylogenetic, domain architecture and gene neighborhood analyses. Nucleic Acids Research https://doi.org/10.1093/nar/gkaa243. 118. Johnson M, Zaretskaya I, Raytselis Y, Merezhuk Y, McGinnis S, Madden TL. 2008. NCBI BLAST: a better web interface. Nucleic Acids Research https://doi.org/10.1093/nar/gkn201. 119. Korf I, Yandell M, Bedell J. 2003. BLAST. “O’Reilly Media, Inc.” 120. Welch TJ, Bartlett DH. 1998. Identification of a regulatory protein required for pressure- responsive gene expression in the deep-sea bacterium Photobacterium species strain SS9. Mol Microbiol 27:977–985. 121. Osorio CR, Klose KE. 2000. A region of the transmembrane regulatory protein ToxR that tethers the transcriptional activation domain to the cytoplasmic membrane displays wide divergence among Vibrio species. J Bacteriol 182:526–528. 122. Colwell RR, Huq A. 1994. Environmental reservoir of Vibrio cholerae. The causative agent of cholera. Ann N Y Acad Sci 740:44–54. 123. Baker-Austin C, Trinanes J, Gonzalez-Escalona N, Martinez-Urtaza J. 2017. Non-Cholera Vibrios: The Microbial Barometer of Climate Change. Trends Microbiol 25:76–84. 124. Bina XR, Howard MF, Ante VM, Bina JE. 2016. Vibrio cholerae LeuO Links the ToxR Regulon to Expression of Lipid A Remodeling Genes. Infect Immun 84:3161–3171. 125. Mey AR, Craig SA, Payne SM. 2012. Effects of amino acid supplementation on porin expression and ToxR levels in Vibrio cholerae. Infect Immun 80:518–528. 126. Hung DT, Mekalanos JJ. 2005. Bile acids induce cholera toxin expression in Vibrio cholerae in a ToxT-independent manner. Proc Natl Acad Sci U S A 102:3028–3033. 127. Provenzano D, Lauriano CM, Klose KE. 2001. Characterization of the role of the ToxR- modulated outer membrane porins OmpU and OmpT in Vibrio cholerae virulence. J Bacteriol 183:3652–3662. 128. Provenzano D, Klose KE. 2000. Altered expression of the ToxR-regulated porins OmpU and OmpT diminishes Vibrio cholerae bile resistance, virulence factor expression, and intestinal colonization. Proc Natl Acad Sci U S A 97:10220–10224. 231 129. Mathur J, Waldor MK. 2004. The Vibrio cholerae ToxR-Regulated Porin OmpU Confers Resistance to Antimicrobial Peptides. Infection and Immunity https://doi.org/10.1128/iai.72.6.3577-3583.2004. 130. Lin Z, Kumagai K, Baba K, Mekalanos JJ, Nishibuchi M. 1993. Vibrio parahaemolyticus has a homolog of the Vibrio cholerae toxRS operon that mediates environmentally induced regulation of the thermostable direct hemolysin gene. Journal of Bacteriology https://doi.org/10.1128/jb.175.12.3844-3855.1993. 131. Lee SE, Shin SH, Kim SY, Kim YR, Shin DH, Chung SS, Lee ZH, Lee JY, Jeong KC, Choi SH, Rhee JH. 2000. Vibrio vulnificus Has the Transmembrane Transcription Activator ToxRS Stimulating the Expression of the Hemolysin Gene vvhA. Journal of Bacteriology https://doi.org/10.1128/jb.182.12.3405-3415.2000. 132. Fan F, Liu Z, Jabeen N, Birdwell LD, Zhu J, Kan B. 2014. Enhanced interaction of Vibrio cholerae virulence regulators TcpP and ToxR under oxygen-limiting conditions. Infect Immun 82:1676–1682. 133. Zheng B, Jiang X, Cheng H, Guo L, Zhang J, Xu H, Yu X, Huang C, Ji J, Ying C, Feng Y, Xiao Y, Li L. 2017. Genome characterization of two bile-isolated Vibrio fluvialis strains: an insight into pathogenicity and bile salt adaption. Sci Rep 7:11827. 134. Bennett BD, Essock-Burns T, Ruby EG. 2020. HbtR, a Heterofunctional Homolog of the Virulence Regulator TcpP, Facilitates the Transition between Symbiotic and Planktonic Lifestyles in Vibrio fischeri. MBio 11. 135. Koch EJ, Miyashiro T, McFall-Ngai MJ, Ruby EG. 2014. Features governing symbiont persistence in the squid-vibrio association. Mol Ecol 23:1624–1634. 136. Visick KL, Foster J, Doino J, McFall-Ngai M, Ruby EG. 2000. Vibrio fischeri lux genes play an important role in colonization and development of the host light organ. J Bacteriol 182:4578–4586. 137. Moriano-Gutierrez S, Koch EJ, Bussan H, Romano K, Belcaid M, Rey FE, Ruby EG, McFall-Ngai MJ. 2019. Critical symbiont signals drive both local and systemic changes in diel and developmental host gene expression. Proc Natl Acad Sci U S A 116:7990–7999. 138. Mandel MJ, Schaefer AL, Brennan CA, Heath-Heckman EAC, DeLoney-Marino CR, McFall-Ngai MJ, Ruby EG. 2012. Squid-Derived Chitin Oligosaccharides Are a Chemotactic Signal during Colonization by Vibrio fischeri. Applied and Environmental Microbiology https://doi.org/10.1128/aem.00377-12. 139. Ruby EG, Asato LM. 1993. Growth and flagellation of Vibrio fischeri during initiation of the sepiolid squid light organ symbiosis. Arch Microbiol 159:160–167. 140. Graf J, Ruby EG. 1998. Host-derived amino acids support the proliferation of symbiotic bacteria. Proc Natl Acad Sci U S A 95:1818–1822. 141. Jones BW, Nishiguchi MK. 2004. Counterillumination in the Hawaiian bobtail squid, Euprymna scolopes Berry (Mollusca: Cephalopoda). Marine Biology https://doi.org/10.1007/s00227-003-1285-3. 232 142. Lee KH, Ruby EG. 1994. Effect of the Squid Host on the Abundance and Distribution of Symbiotic Vibrio fischeri in Nature. Appl Environ Microbiol 60:1565–1571. 143. Thompson LR, Nikolakakis K, Pan S, Reed J, Knight R, Ruby EG. 2017. Transcriptional characterization of Vibrio fischeri during colonization of juvenile Euprymna scolopes. Environ Microbiol 19:1845–1856. 144. Kovach ME, Shaffer MD, Peterson KM. 1996. A putative integrase gene defines the distal end of a large cluster of ToxR-regulated colonization genes in Vibrio cholerae. Microbiology 142 ( Pt 8):2165–2174. 145. Karaolis DK, Johnson JA, Bailey CC, Boedeker EC, Kaper JB, Reeves PR. 1998. A Vibrio cholerae pathogenicity island associated with epidemic and pandemic strains. Proc Natl Acad Sci U S A 95:3134–3139. 146. Ruby EG, Urbanowski M, Campbell J, Dunn A, Faini M, Gunsalus R, Lostroh P, Lupp C, McCann J, Millikan D, Schaefer A, Stabb E, Stevens A, Visick K, Whistler C, Greenberg EP. 2005. Complete genome sequence of Vibrio fischeri: a symbiotic bacterium with pathogenic congeners. Proc Natl Acad Sci U S A 102:3004–3009. 147. Visick KL, Quirke KP, McEwen SM. 2013. Arabinose induces pellicle formation by Vibrio fischeri. Appl Environ Microbiol 79:2069–2080. 148. Okada R, Matsuda S, Iida T. 2017. Vibrio parahaemolyticus VtrA is a membrane-bound regulator and is activated via oligomerization. PLoS One 12:e0187846. 149. Miller KA, Sofia MK, Weaver JWA, Seward CH, Dziejman M. 2016. Regulation by ToxR- Like Proteins Converges on vttRB Expression To Control Type 3 Secretion System- Dependent Caco2-BBE Cytotoxicity in Vibrio cholerae. J Bacteriol 198:1675–1682. 150. Dziejman M, Serruto D, Tam VC, Sturtevant D, Diraphat P, Faruque SM, Rahman MH, Heidelberg JF, Decker J, Li L, Montgomery KT, Grills G, Kucherlapati R, Mekalanos JJ. 2005. Genomic characterization of non-O1, non-O139 Vibrio cholerae reveals genes for a type III secretion system. Proc Natl Acad Sci U S A 102:3465–3470. 151. Chaand M, Miller KA, Sofia MK, Schlesener C, Weaver JWA, Sood V, Dziejman M. 2015. Type 3 Secretion System Island Encoded Proteins Required for Colonization by Non- O1/non-O139 Serogroup. Infect Immun 83:2862–2869. 152. Makino K, Oshima K, Kurokawa K, Yokoyama K, Uda T, Tagomori K, Iijima Y, Najima M, Nakano M, Yamashita A, Kubota Y, Kimura S, Yasunaga T, Honda T, Shinagawa H, Hattori M, Iida T. 2003. Genome sequence of Vibrio parahaemolyticus: a pathogenic mechanism distinct from that of V cholerae. Lancet 361:743–749. 153. Izutsu K, Kurokawa K, Tashiro K, Kuhara S, Hayashi T, Honda T, Iida T. 2008. Comparative Genomic Analysis Using Microarray Demonstrates a Strong Correlation between the Presence of the 80-Kilobase Pathogenicity Island and Pathogenicity in Kanagawa Phenomenon-Positive Vibrio parahaemolyticus Strains. Infection and Immunity https://doi.org/10.1128/iai.01535-07. 154. Li P, Rivera-Cancel G, Kinch LN, Salomon D, Tomchick DR, Grishin NV, Orth K. 2016. Bile salt receptor complex activates a pathogenic type III secretion system. Elife 5. 233 155. Rivera-Cancel G, Orth K. 2017. Biochemical basis for activation of virulence genes by bile salts in Vibrio parahaemolyticus. Gut Microbes 8:366–373. 156. Ante VM, Bina XR, Bina JE. 2015. The LysR-type regulator LeuO regulates the acid tolerance response in Vibrio cholerae. Microbiology 161:2434–2443. 157. Rhee JE, Jeong HG, Lee JH, Choi SH. 2006. AphB influences acid tolerance of Vibrio vulnificus by activating expression of the positive regulator CadC. J Bacteriol 188:6490– 6497. 158. Merrell DS, Scott Merrell D, Camilli A. 2000. Regulation of Vibrio cholerae Genes Required for Acid Tolerance by a Member of the “ToxR-Like” Family of Transcriptional Regulators. Journal of Bacteriology https://doi.org/10.1128/jb.182.19.5342-5350.2000. 159. Neely MN, Dell CL, Olson ER. 1994. Roles of LysP and CadC in mediating the lysine requirement for acid induction of the Escherichia coli cad operon. J Bacteriol 176:3278– 3285. 160. Casalino M, Prosseda G, Barbagallo M, Iacobino A, Ceccarini P, Latella MC, Nicoletti M, Colonna B. 2010. Interference of the CadC regulator in the arginine-dependent acid resistance system of Shigella and enteroinvasive E. coli. Int J Med Microbiol 300:289–295. 161. Lee YH, Kim BH, Kim JH, Yoon WS, Bang SH, Park YK. 2007. CadC Has a Global Translational Effect during Acid Adaptation in Salmonella enterica Serovar Typhimurium. Journal of Bacteriology https://doi.org/10.1128/jb.01277-06. 162. Lee YH, Kim JH. 2017. Direct interaction between the transcription factors CadC and OmpR involved in the acid stress response of Salmonella enterica. Journal of Microbiology https://doi.org/10.1007/s12275-017-7410-7. 163. Hsieh P-F, Lin H-H, Lin T-L, Wang J-T. 2010. CadC regulates cad and tdc operons in response to gastrointestinal stresses and enhances intestinal colonization of Klebsiella pneumoniae. J Infect Dis 202:52–64. 164. Tetsch L, Koller C, Haneburger I, Jung K. 2008. The membrane-integrated transcriptional activator CadC of Escherichia coli senses lysine indirectly via the interaction with the lysine permease LysP. Mol Microbiol 67:570–583. 165. Lee YH, Kim JH, Bang IS, Park YK. 2008. The membrane-bound transcriptional regulator CadC is activated by proteolytic cleavage in response to acid stress. J Bacteriol 190:5120– 5126. 166. Dell CL, Neely MN, Olson ER. 1994. Altered pH lysine signalling mutants of cadC, a gene encoding a membrane-bound transcriptional activator of the Escherichia coli cadBA operon. Molecular Microbiology https://doi.org/10.1111/j.1365-2958.1994.tb01262.x. 167. Debnath A, Mizuno T, Miyoshi S-I. 2020. Regulation of Chitin-Dependent Growth and Natural Competence in. Microorganisms 8. 168. Antonova ES, Hammer BK. 2015. Genetics of Natural Competence in Vibrio cholerae and other Vibrios. Microbiol Spectr 3. 169. Pollack-Berti A, Wollenberg MS, Ruby EG. 2010. Natural transformation of Vibrio fischeri 234 requires tfoX and tfoY. Environ Microbiol 12:2302–2311. 170. Gulig PA, Tucker MS, Thiaville PC, Joseph JL, Brown RN. 2009. USER friendly cloning coupled with chitin-based natural transformation enables rapid mutagenesis of Vibrio vulnificus. Appl Environ Microbiol 75:4936–4949. 171. Souza CP, Almeida BC, Colwell RR, Rivera ING. 2011. The importance of chitin in the marine environment. Mar Biotechnol 13:823–830. 172. Huq A, Small EB, West PA, Huq MI, Rahman R, Colwell RR. 1983. Ecological relationships between Vibrio cholerae and planktonic crustacean copepods. Appl Environ Microbiol 45:275–283. 173. Dumontet S, Krovacek K, Baloda SB, Grottoli R, Pasquale V, Vanucci S. 1996. Ecological relationship between Aeromonas and Vibrio spp. and planktonic copepods in the coastal marine environment in Southern Italy. Comparative Immunology, Microbiology and Infectious Diseases https://doi.org/10.1016/0147-9571(96)00012-4. 174. Herzig A. 1983. The ecological significance of the relationship between temperature and duration of embryonic development in planktonic freshwater copepods. Hydrobiologia https://doi.org/10.1007/bf00027423. 175. Kasuga T. 1986. An ecological study of Vibrio cholerae O-1 and Vibrio cholerae non O-1, with special regard to behavior in foodstuffs and living shellfish. Journal of Nippon Medical School https://doi.org/10.1272/jnms1923.53.388. 176. Martin RG, Rosner JL. 2001. The AraC transcriptional activators. Curr Opin Microbiol 4:132–137. 177. Popoff MY, Le Minor LE. 2015. Salmonella. Bergey’s Manual of Systematics of Archaea and Bacteria https://doi.org/10.1002/9781118960608.gbm01166. 178. Gut AM, Vasiljevic T, Yeager T, Donkor ON. 2018. Salmonella infection - prevention and treatment by antibiotics and probiotic yeasts: a review. Microbiology 164:1327–1344. 179. Bula-Rudas FJ, Rathore MH, Maraqa NF. 2015. Salmonella Infections in Childhood. Advances in Pediatrics https://doi.org/10.1016/j.yapd.2015.04.005. 180. Gomes TAT, Elias WP, Scaletsky ICA, Guth BEC, Rodrigues JF, Piazza RMF, Ferreira LCS, Martinez MB. 2016. Diarrheagenic Escherichia coli. Braz J Microbiol 47 Suppl 1:3–30. 181. Tükel C, Akçelik M, de Jong MF, Simsek O, Tsolis RM, Bäumler AJ. 2007. MarT activates expression of the MisL autotransporter protein of Salmonella enterica serotype Typhimurium. J Bacteriol 189:3922–3926. 182. Dorsey CW, Laarakker MC, Humphries AD, Weening EH, Bäumler AJ. 2005. Salmonella enterica serotype Typhimurium MisL is an intestinal colonization factor that binds fibronectin. Mol Microbiol 57:196–211. 183. Eran Z, Akçelik M, Yazıcı BC, Özcengiz G, Akçelik N. 2020. Regulation of biofilm formation by marT in Salmonella Typhimurium. Molecular Biology Reports https://doi.org/10.1007/s11033-020-05573-6. 235 184. Morgan JK, Carroll RK, Harro CM, Vendura KW, Shaw LN, Riordan JT. 2016. Global Regulator of Virulence A (GrvA) Coordinates Expression of Discrete Pathogenic Mechanisms in Enterohemorrhagic Escherichia coli through Interactions with GadW-GadE. J Bacteriol 198:394–409. 185. Aquino P, Honda B, Jaini S, Lyubetskaya A, Hosur K, Chiu JG, Ekladious I, Hu D, Jin L, Sayeg MK, Stettner AI, Wang J, Wong BG, Wong WS, Alexander SL, Ba C, Bensussen SI, Bernstein DB, Braff D, Cha S, Cheng DI, Cho JH, Chou K, Chuang J, Gastler DE, Grasso DJ, Greifenberger JS, Guo C, Hawes AK, Israni DV, Jain SR, Kim J, Lei J, Li H, Li D, Li Q, Mancuso CP, Mao N, Masud SF, Meisel CL, Mi J, Nykyforchyn CS, Park M, Peterson HM, Ramirez AK, Reynolds DS, Rim NG, Saffie JC, Su H, Su WR, Su Y, Sun M, Thommes MM, Tu T, Varongchayakul N, Wagner TE, Weinberg BH, Yang R, Yaroslavsky A, Yoon C, Zhao Y, Zollinger AJ, Stringer AM, Foster JW, Wade J, Raman S, Broude N, Wong WW, Galagan JE. 2017. Coordinated regulation of acid resistance in Escherichia coli. BMC Syst Biol 11:1. 186. Xue M, Xiao Y, Fu D, Raheem MA, Shao Y, Song X, Tu J, Xue T, Qi K. 2020. Transcriptional Regulator YqeI, Locating at ETT2 Locus, Affects the Pathogenicity of Avian Pathogenic. Animals (Basel) 10. 187. Hansen-Wester I, Hensel M. 2001. Salmonella pathogenicity islands encoding type III secretion systems. Microbes Infect 3:549–559. 188. Hensel M, Shea JE, Bäumler AJ, Gleeson C, Blattner F, Holden DW. 1997. Analysis of the boundaries of Salmonella pathogenicity island 2 and the corresponding chromosomal region of Escherichia coli K-12. J Bacteriol 179:1105–1111. 189. Shea JE, Hensel M, Gleeson C, Holden DW. 1996. Identification of a virulence locus encoding a second type III secretion system in Salmonella typhimurium. Proc Natl Acad Sci U S A 93:2593–2597. 190. Blanc-Potard AB, Solomon F, Kayser J, Groisman EA. 1999. The SPI-3 pathogenicity island of Salmonella enterica. J Bacteriol 181:998–1004. 191. Kyrova K, Stepanova H, Rychlik I, Faldyna M, Volf J. 2012. SPI-1 encoded genes of Salmonella Typhimurium influence differential polarization of porcine alveolar macrophages in vitro. BMC Vet Res 8:115. 192. Raffatellu M, Wilson RP, Chessa D, Andrews-Polymenis H, Tran QT, Lawhon S, Khare S, Adams LG, Bäumler AJ. 2005. SipA, SopA, SopB, SopD, and SopE2 contribute to Salmonella enterica serotype typhimurium invasion of epithelial cells. Infect Immun 73:146– 154. 193. Ochman H, Soncini FC, Solomon F, Groisman EA. 1996. Identification of a pathogenicity island required for Salmonella survival in host cells. Proc Natl Acad Sci U S A 93:7800– 7804. 194. Walia B, Castaneda FE, Wang L, Kolachala VL, Bajaj R, Roman J, Merlin D, Gewirtz AT, Sitaraman SV. 2004. Polarized fibronectin secretion induced by adenosine regulates bacterial-epithelial interaction in human intestinal epithelial cells. Biochem J 382:589–596. 195. Makino S-I, Tobe T, Asakura H, Watarai M, Ikeda T, Takeshi K, Sasakawa C. 2003. 236 Distribution of the secondary type III secretion system locus found in enterohemorrhagic Escherichia coli O157:H7 isolates among Shiga toxin-producing E. coli strains. J Clin Microbiol 41:2341–2347. 196. Ren C-P, Chaudhuri RR, Fivian A, Bailey CM, Antonio M, Barnes WM, Pallen MJ. 2004. The ETT2 gene cluster, encoding a second type III secretion system from Escherichia coli, is present in the majority of strains but has undergone widespread mutational attrition. J Bacteriol 186:3547–3560. 197. Wang S, Liu X, Xu X, Zhao Y, Yang D, Han X, Tian M, Ding C, Peng D, Yu S. 2016. Escherichia coli type III secretion system 2 (ETT2) is widely distributed in avian pathogenic Escherichia coli isolates from Eastern China. Epidemiol Infect 144:2824–2830. 198. Hartleib S, Prager R, Hedenström I, Löfdahl S, Tschäpe H. 2003. Prevalence of the new, SPI1-like, pathogenicity island ETT2 among Escherichia coli. International Journal of Medical Microbiology https://doi.org/10.1078/1438-4221-00224. 199. Ideses D, Gophna U, Paitan Y, Chaudhuri RR, Pallen MJ, Ron EZ. 2005. A degenerate type III secretion system from septicemic Escherichia coli contributes to pathogenesis. J Bacteriol 187:8164–8171. 200. McDaniel TK, Jarvis KG, Donnenberg MS, Kaper JB. 1995. A genetic locus of enterocyte effacement conserved among diverse enterobacterial pathogens. Proc Natl Acad Sci U S A 92:1664–1668. 201. Yao Y, Xie Y, Perace D, Zhong Y, Lu J, Tao J, Guo X, Kim KS. 2009. The type III secretion system is involved in the invasion and intracellular survival of Escherichia coli K1 in human brain microvascular endothelial cells. FEMS Microbiol Lett 300:18–24. 202. Shulman A, Yair Y, Biran D, Sura T, Otto A, Gophna U, Becher D, Hecker M, Ron EZ. 2018. The Escherichia coli Type III Secretion System 2 Has a Global Effect on Cell Surface. mBio https://doi.org/10.1128/mbio.01070-18. 203. Morgan JK, Vendura KW, Stevens SM, Riordan JT. 2013. RcsB determines the locus of enterocyte effacement (LEE) expression and adherence phenotype of Escherichia coli O157 : H7 spinach outbreak strain TW14359 and coordinates bicarbonate-dependent LEE activation with repression of motility. Microbiology 159:2342–2353. 204. Kailasan Vanaja S, Bergholz TM, Whittam TS. 2009. Characterization of the Escherichia coli O157:H7 Sakai GadE regulon. J Bacteriol 191:1868–1877. 205. Tree JJ, Roe AJ, Flockhart A, McAteer SP, Xu X, Shaw D, Mahajan A, Beatson SA, Best A, Lotz S, Woodward MJ, La Ragione R, Murphy KC, Leong JM, Gally DL. 2011. Transcriptional regulators of the GAD acid stress island are carried by effector protein- encoding prophages and indirectly control type III secretion in enterohemorrhagic Escherichia coli O157:H7. Mol Microbiol 80:1349–1365. 206. Elliott SJ, Sperandio V, Girón JA, Shin S, Mellies JL, Wainwright L, Hutcheson SW, McDaniel TK, Kaper JB. 2000. The Locus of Enterocyte Effacement (LEE)-Encoded Regulator Controls Expression of Both LEE- and Non-LEE-Encoded Virulence Factors in Enteropathogenic and Enterohemorrhagic Escherichia coli. Infection and Immunity https://doi.org/10.1128/iai.68.11.6115-6126.2000. 237 207. DiRita VJ, Mekalanos JJ. 1991. Periplasmic interaction between two membrane regulatory proteins, ToxR and ToxS, results in signal transduction and transcriptional activation. Cell https://doi.org/10.1016/0092-8674(91)90206-e. 208. Muse WB, Bender RA. 1998. The nac (nitrogen assimilation control) gene from Escherichia coli. J Bacteriol 180:1166–1173. 209. Wurpel DJ, Beatson SA, Totsika M, Petty NK, Schembri MA. 2013. Chaperone-Usher Fimbriae of Escherichia coli. PLoS ONE https://doi.org/10.1371/journal.pone.0052835. 210. Deditius JA, Felgner S, Spöring I, Kühne C, Frahm M, Rohde M, Weiß S, Erhardt M. 2015. Characterization of Novel Factors Involved in Swimming and Swarming Motility in Salmonella enterica Serovar Typhimurium. PLoS One 10:e0135351. 211. Bogomolnaya LM, Aldrich L, Ragoza Y, Talamantes M, Andrews KD, McClelland M, Andrews-Polymenis HL. 2014. Identification of novel factors involved in modulating motility of Salmonella enterica serotype typhimurium. PLoS One 9:e111513. 212. Cuthbertson L, Nodwell JR. 2013. The TetR Family of Regulators. Microbiology and Molecular Biology Reviews https://doi.org/10.1128/mmbr.00018-13. 213. Ramos JL, Martínez-Bueno M, Molina-Henares AJ, Terán W, Watanabe K, Zhang X, Gallegos MT, Brennan R, Tobes R. 2005. The TetR family of transcriptional repressors. Microbiol Mol Biol Rev 69:326–356. 214. Wang Y, Sun M ’an, Bao H, White AP. 2013. T3_MM: a Markov model effectively classifies bacterial type III secretion signals. PLoS One 8:e58173. 215. Elfenbein JR, Endicott-Yazdani T, Porwollik S, Bogomolnaya LM, Cheng P, Guo J, Zheng Y, Yang H-J, Talamantes M, Shields C, Maple A, Ragoza Y, DeAtley K, Tatsch T, Cui P, Andrews KD, McClelland M, Lawhon SD, Andrews-Polymenis H. 2013. Novel determinants of intestinal colonization of Salmonella enterica serotype typhimurium identified in bovine enteric infection. Infect Immun 81:4311–4320. 216. Bennett JE, Dolin R, Blaser MJ. 2019. Mandell, Douglas, and Bennett’s Principles and Practice of Infectious Diseases: 2-Volume Set. Elsevier. 217. Tobback E, Decostere A, Hermans K, Haesebrouck F, Chiers K. 2007. Yersinia ruckeri infections in salmonid fish. J Fish Dis 30:257–268. 218. Kumar G, Menanteau-Ledouble S, Saleh M, El-Matbouli M. 2015. Yersinia ruckeri, the causative agent of enteric redmouth disease in fish. Vet Res 46:103. 219. Furones MD, Rodgers CJ, Munn CB. 1993. Yersinia ruckeri, the causal agent of enteric redmouth disease (ERM) in fish. Annual Review of Fish Diseases https://doi.org/10.1016/0959-8030(93)90031-6. 220. Schilling J, Wagner K, Seekircher S, Greune L, Humberg V, Schmidt MA, Heusipp G. 2010. Transcriptional activation of the tad type IVb pilus operon by PypB in Yersinia enterocolitica. J Bacteriol 192:3809–3821. 221. Quinn JD, Weening EH, Miner TA, Miller VL. 2019. Temperature Control of Expression by PsaE and PsaF in Yersinia pestis. J Bacteriol 201. 238 222. Quinn JD, Weening EH, Miner TA, Miller VL. 2019. Temperature Control of psaA Expression by PsaE and PsaF in Yersinia pestis. Journal of Bacteriology https://doi.org/10.1128/jb.00217-19. 223. Li P, Wang X, Smith C, Shi Y, Wade JT, Sun W. 2021. Dissecting Locus Regulation in Yersinia pestis. J Bacteriol 203:e0023721. 224. Yang Y, Isberg RR. 1997. Transcriptional regulation of the Yersinia pseudotuberculosis pH6 antigen adhesin by two envelope-associated components. Mol Microbiol 24:499–510. 225. Price SB, Freeman MD, Yeh KS. 1995. Transcriptional analysis of the Yersinia pestis pH 6 antigen gene. J Bacteriol 177:5997–6000. 226. Lindler LE, Klempner MS, Straley SC. 1990. Yersinia pestis pH 6 antigen: genetic, biochemical, and virulence characterization of a protein involved in the pathogenesis of bubonic plague. Infect Immun 58:2569–2577. 227. Huang X-Z, Lindler LE. 2004. The pH 6 antigen is an antiphagocytic factor produced by Yersinia pestis independent of Yersinia outer proteins and capsule antigen. Infect Immun 72:7212–7219. 228. Zav’yalov VP, Abramov VM, Cherepanov PG, Spirina GV, Chernovskaya TV, Vasiliev AM, Zav’yalova GA. 1996. pH6 antigen (PsaA protein) of Yersinia pestis, a novel bacterial Fc- receptor. FEMS Immunol Med Microbiol 14:53–57. 229. Lindler LE, Tall BD. 1993. Yersinia pestis pH 6 antigen forms fimbriae and is induced by intracellular association with macrophages. Molecular Microbiology https://doi.org/10.1111/j.1365-2958.1993.tb01575.x. 230. Quinn JD, Weening EH, Miller VL. 2021. PsaF Is a Membrane-Localized pH Sensor That Regulates psaA Expression in Yersinia pestis. Journal of Bacteriology https://doi.org/10.1128/jb.00165-21. 231. Iriarte M, Vanooteghem JC, Delor I, Díaz R, Knutton S, Cornelis GR. 1993. The Myf fibrillae of Yersinia enterocolitica. Mol Microbiol 9:507–520. 232. Levine MM, Ristaino P, Marley G, Smyth C, Knutton S, Boedeker E, Black R, Young C, Clements ML, Cheney C. 1984. Coli surface antigens 1 and 3 of colonization factor antigen II-positive enterotoxigenic Escherichia coli: morphology, purification, and immune responses in humans. Infect Immun 44:409–420. 233. Iriarte M, Cornelis GR. 1995. MyfF, an element of the network regulating the synthesis of fibrillae in Yersinia enterocolitica. Journal of Bacteriology https://doi.org/10.1128/jb.177.3.738-744.1995. 234. Cascales D, Guijarro JA, García-Torrico AI, Méndez J. 2017. Comparative genome analysis reveals important genetic differences among serotype O1 and serotype O2 strains ofY. ruckeriand provides insights into host adaptation and virulence. MicrobiologyOpen https://doi.org/10.1002/mbo3.460. 235. Emmerth M, Goebel W, Miller SI, Hueck CJ. 1999. Genomic Subtraction Identifies Salmonella typhimurium Prophages, F-Related Plasmid Sequences, and a Novel Fimbrial 239 Operon, stf , Which Are Absent in Salmonella typhi. Journal of Bacteriology https://doi.org/10.1128/jb.181.18.5652-5661.1999. 236. Cornelis GR, Boland A, Boyd AP, Geuijen C, Iriarte M, Neyt C, Sory MP, Stainier I. 1998. The virulence plasmid of Yersinia, an antihost genome. Microbiol Mol Biol Rev 62:1315– 1352. 237. Foultier B, Troisfontaines P, Müller S, Opperdoes FR, Cornelis GR. 2002. Characterization of the ysa pathogenicity locus in the chromosome of Yersinia enterocolitica and phylogeny analysis of type III secretion systems. J Mol Evol 55:37–51. 238. Haller JC, Carlson S, Pederson KJ, Pierson DE. 2000. A chromosomally encoded type III secretion pathway in Yersinia enterocolitica is important in virulence. Mol Microbiol 36:1436–1446. 239. Liu T, Wang K-Y, Wang J, Chen D-F, Huang X-L, Ouyang P, Geng Y, He Y, Zhou Y, Min J. 2016. Genome Sequence of the Fish Pathogen Yersinia ruckeri SC09 Provides Insights into Niche Adaptation and Pathogenic Mechanism. Int J Mol Sci 17:557. 240. Holzapfel WHN, Wood BJB. 2012. The Genera of Lactic Acid Bacteria. Springer. 241. 2017. Biology of Microorganisms on Grapes, in Must and in Wine https://doi.org/10.1007/978-3-319-60021-5. 242. Noda M, Miyauchi R, Danshiitsoodol N, Matoba Y, Kumagai T, Sugiyama M. 2018. Expression of Genes Involved in Bacteriocin Production and Self-Resistance in Lactobacillus brevis 174A Is Mediated by Two Regulatory Proteins. Appl Environ Microbiol 84. 243. Suárez C, Espariz M, Blancato VS, Magni C. 2013. Expression of the Agmatine Deiminase Pathway in Enterococcus faecalis Is Activated by the AguR Regulator and Repressed by CcpA and PTSMan Systems. PLoS ONE https://doi.org/10.1371/journal.pone.0076170. 244. Růžičková M, Vítězová M, Kushkevych I. 2020. The characterization of Enterococcus genus: resistance mechanisms and inflammatory bowel disease. Open Medicine https://doi.org/10.1515/med-2020-0032. 245. O’Donovan CA, Fan-Havard P, Tecson-Tumang FT, Smith SM, Eng RH. 1994. Enteric eradication of vancomycin-resistant Enterococcus faecium with oral bacitracin. Diagn Microbiol Infect Dis 18:105–109. 246. Charlebois A, Jalbert L-A, Harel J, Masson L, Archambault M. 2012. Characterization of genes encoding for acquired bacitracin resistance in Clostridium perfringens. PLoS One 7:e44449. 247. Darnell RL, Nakatani Y, Knottenbelt MK, Gebhard S, Cook GM. 2019. Functional characterization of BcrR: a one-component transmembrane signal transduction system for bacitracin resistance. Microbiology 165:475–487. 248. Gauntlett JC, Gebhard S, Keis S, Manson JM, Pos KM, Cook GM. 2008. Molecular analysis of BcrR, a membrane-bound bacitracin sensor and DNA-binding protein from Enterococcus faecalis. J Biol Chem 283:8591–8600. 240 249. Matos R, Pinto VV, Ruivo M, de Fátima Silva Lopes M. 2009. Study on the dissemination of the bcrABDR cluster in Enterococcus spp. reveals that the BcrAB transporter is sufficient to confer high-level bacitracin resistance. International Journal of Antimicrobial Agents https://doi.org/10.1016/j.ijantimicag.2009.02.008. 250. Dufour M, Manson JM, Bremer PJ, Dufour J-P, Cook GM, Simmonds RS. 2007. Characterization of monolaurin resistance in Enterococcus faecalis. Appl Environ Microbiol 73:5507–5515. 251. Tremblay C-L, Archambault M. 2013. Interference in pheromone-responsive conjugation of a high-level bacitracin resistant Enterococcus faecalis plasmid of poultry origin. Int J Environ Res Public Health 10:4245–4260. 252. Shang Y, Li D, Shan X, Schwarz S, Zhang S-M, Chen Y-X, Ouyang W, Du X-D. 2019. Analysis of two pheromone-responsive conjugative multiresistance plasmids carrying the novel mobile optrA locus from Enterococcus faecalis. Infection and Drug Resistance https://doi.org/10.2147/idr.s206295. 253. Noda M, Miyauchi R, Danshiitsoodol N, Higashikawa F, Kumagai T, Matoba Y, Sugiyama M. 2015. Characterization and Mutational Analysis of a Two-Polypeptide Bacteriocin Produced by Citrus Iyo-Derived Lactobacillus brevis 174A. Biological & Pharmaceutical Bulletin https://doi.org/10.1248/bpb.b15-00505. 254. Jack RW, Tagg JR, Ray B. 1995. Bacteriocins of gram-positive bacteria. Microbiological reviews https://doi.org/10.1128/mmbr.59.2.171-200.1995. 255. David FL-R, Tania EVC, De la Fuente-Salcido Norma M. 2016. Bacteriocins of Gram- positive bacteria: Features and biotherapeutic approach. African Journal of Microbiology Research https://doi.org/10.5897/ajmr2016.8376. 256. Griswold AR, Chen Y-YM, Burne RA. 2004. Analysis of an agmatine deiminase gene cluster in Streptococcus mutans UA159. J Bacteriol 186:1902–1904. 257. Liu Y, Zeng L, Burne RA. 2009. AguR Is Required for Induction of the Streptococcus mutans Agmatine Deiminase System by Low pH and Agmatine. Applied and Environmental Microbiology https://doi.org/10.1128/aem.02145-08. 258. Del Rio B, Linares D, Ladero V, Redruello B, Fernandez M, Martin MC, Alvarez MA. 2016. Putrescine biosynthesis in Lactococcus lactis is transcriptionally activated at acidic pH and counteracts acidification of the cytosol. Int J Food Microbiol 236:83–89. 259. Linares DM, del Rio B, Redruello B, Ladero V, Cruz Martin M, de Jong A, Kuipers OP, Fernandez M, Alvarez MA. 2015. AguR, a Transmembrane Transcription Activator of the Putrescine Biosynthesis Operon in Lactococcus lactis, Acts in Response to the Agmatine Concentration. Applied and Environmental Microbiology https://doi.org/10.1128/aem.00959- 15. 260. Del Rio B, Linares DM, Redruello B, Martin MC, Fernandez M, de Jong A, Kuipers OP, Ladero V, Alvarez MA. 2015. Transcriptomic profile of aguR deletion mutant of Lactococcus lactis subsp. cremoris CECT 8666. Genom Data 6:228–230. 261. Fabia R, Ar’Rajab A, Johansson ML, Willén R, Andersson R, Molin G, Bengmark S. 1993. 241 The effect of exogenous administration of Lactobacillus reuteri R2LC and oat fiber on acetic acid-induced colitis in the rat. Scand J Gastroenterol 28:155–162. 262. Madsen KL, Doyle JS, Jewell LD, Tavernini MM, Fedorak RN. 1999. Lactobacillus species prevents colitis in interleukin 10 gene-deficient mice. Gastroenterology 116:1107–1114. 263. Mimura T. 2004. Once daily high dose probiotic therapy (VSL#3) for maintaining remission in recurrent or refractory pouchitis. Gut https://doi.org/10.1136/gut.53.1.108. 264. Rembacken BJ, Snelling AM, Hawkey PM, Chalmers DM, Axon AT. 1999. Non-pathogenic Escherichia coli versus mesalazine for the treatment of ulcerative colitis: a randomised trial. Lancet 354:635–639. 265. Kalliomäki M, Antoine J-M, Herz U, Rijkers GT, Wells JM, Mercenier A. 2010. Guidance for substantiating the evidence for beneficial effects of probiotics: prevention and management of allergic diseases by probiotics. J Nutr 140:713S–21S. 266. Dong H, Rowland I, Yaqoob P. 2012. Comparative effects of six probiotic strains on immune function in vitro. Br J Nutr 108:459–470. 267. van Hemert S, Meijerink M, Molenaar D, Bron PA, de Vos P, Kleerebezem M, Wells JM, Marco ML. 2010. Identification of Lactobacillus plantarum genes modulating the cytokine response of human peripheral blood mononuclear cells. BMC Microbiol 10:293. 268. Larché M, Robinson DS, Barry Kay A. 2003. The role of T lymphocytes in the pathogenesis of asthma. Journal of Allergy and Clinical Immunology https://doi.org/10.1067/mai.2003.169. 269. Smelt MJ, de Haan BJ, Bron PA, van Swam I, Meijerink M, Wells JM, Faas MM, de Vos P. 2013. Probiotics can generate FoxP3 T-cell responses in the small intestine and simultaneously inducing CD4 and CD8 T cell activation in the large intestine. PLoS One 8:e68952. 270. Smelt MJ, de Haan BJ, Bron PA, van Swam I, Meijerink M, Wells JM, Kleerebezem M, Faas MM, de Vos P. 2013. The impact of Lactobacillus plantarum WCFS1 teichoic acid D- alanylation on the generation of effector and regulatory T-cells in healthy mice. PLoS One 8:e63099. 271. Grangette C, Nutten S, Palumbo E, Morath S, Hermann C, Dewulf J, Pot B, Hartung T, Hols P, Mercenier A. 2005. Enhanced antiinflammatory capacity of a Lactobacillus plantarum mutant synthesizing modified teichoic acids. Proc Natl Acad Sci U S A 102:10321–10326. 272. Yeo W-S, Anokwute C, Marcadis P, Levitan M, Ahmed M, Bae Y, Kim K, Kostrominova T, Liu Q, Bae T. 2020. A Membrane-Bound Transcription Factor is Proteolytically Regulated by the AAA Protease FtsH in Staphylococcus aureus. Journal of Bacteriology https://doi.org/10.1128/jb.00019-20. 273. Law-Brown J, Meyers PR. 2003. Enterococcus phoeniculicola sp. nov., a novel member of the enterococci isolated from the uropygial gland of the Red-billed Woodhoopoe, Phoeniculus purpureus. International Journal of Systematic and Evolutionary Microbiology https://doi.org/10.1099/ijs.0.02334-0. 242 274. Law-Brown J. 2001. Chemical Defence in the Red-billed Woodhoopoe: Phoeniculus Purpureus. 275. Asnani MV, Ramachandran AV. 1993. Roles of adrenal and gonadal steroids and season in uropygial gland function in male pigeons, Columba livia. Gen Comp Endocrinol 92:213– 224. 276. Ligon JD, David Ligon J, Ligon SH. 1978. Communal breeding in green woodhoopoes as a case for reciprocity. Nature https://doi.org/10.1038/276496a0. 277. Jacob J, Ziswiler V. 1982. THE UROPYGIAL GLAND. Avian Biology https://doi.org/10.1016/b978-0-12-249406-2.50013-7. 278. Levy EM, Strain PM. 1982. The composition of the preen gland waxes of some marine birds: A word of caution for chemotaxonomists. Comparative Biochemistry and Physiology Part B: Comparative Biochemistry https://doi.org/10.1016/0305-0491(82)90043-8. 279. Shahidi F, Naczk M. 2003. Phenolics in Food and Nutraceuticals https://doi.org/10.1201/9780203508732. 280. Nowell VJ, Kropinski AM, Songer JG, MacInnes JI, Parreira VR, Prescott JF. 2012. Genome sequencing and analysis of a type A Clostridium perfringens isolate from a case of bovine clostridial abomasitis. PLoS One 7:e32271. 281. Bakker HC den, den Bakker HC, Bowen BM, Rodriguez-Rivera LD, Wiedmann M. 2012. FSL J1-208, a Virulent Uncommon Phylogenetic Lineage IV Listeria monocytogenes Strain with a Small Chromosome Size and a Putative Virulence Plasmid Carrying Internalin-Like Genes. Applied and Environmental Microbiology https://doi.org/10.1128/aem.06969-11. 282. Rychli K, Müller A, Zaiser A, Schoder D, Allerberger F, Wagner M, Schmitz-Esser S. 2014. Genome sequencing of Listeria monocytogenes “Quargel” listeriosis outbreak strains reveals two different strains with distinct in vitro virulence potential. PLoS One 9:e89964. 283. Götz F, Bannerman T, Schleifer K-H. 2006. The Genera Staphylococcus and Macrococcus. The Prokaryotes https://doi.org/10.1007/0-387-30744-3_1. 284. Jenul C, Horswill AR. 2019. Regulation of Staphylococcus aureus Virulence. Gram-Positive Pathogens https://doi.org/10.1128/9781683670131.ch41. 285. Yeo W-S, Anokwute C, Marcadis P, Levitan M, Ahmed M, Bae Y, Kim K, Kostrominova T, Liu Q, Bae T. 2020. A Membrane-Bound Transcription Factor is Proteolytically Regulated by the AAA+ Protease FtsH in Staphylococcus aureus. J Bacteriol 202. 286. Ito K, Akiyama Y. 2005. Cellular functions, mechanism of action, and regulation of FtsH protease. Annu Rev Microbiol 59:211–231. 287. Herman C, Prakash S, Lu CZ, Matouschek A, Gross CA. 2003. Lack of a robust unfoldase activity confers a unique level of substrate specificity to the universal AAA protease FtsH. Mol Cell 11:659–669. 288. Liu Q, Hu M, Yeo W-S, He L, Li T, Zhu Y, Meng H, Wang Y, Lee H, Liu X, Li M, Bae T. 2020. Author Correction: Rewiring of the FtsH regulatory network by a single nucleotide change in saeS of Staphylococcus aureus. Sci Rep 10:17555. 243 289. Pei J, Mitchell DA, Dixon JE, Grishin NV. 2011. Expansion of type II CAAX proteases reveals evolutionary origin of γ-secretase subunit APH-1. J Mol Biol 410:18–26. 290. Dolence JM, Steward LE, Dolence EK, Wong DH, Poulter CD. 2000. Studies with recombinant Saccharomyces cerevisiae CaaX prenyl protease Rce1p. Biochemistry 39:4096–4104. 291. Kjos M, Snipen L, Salehian Z, Nes IF, Diep DB. 2010. The abi proteins and their involvement in bacteriocin self-immunity. J Bacteriol 192:2068–2076. 292. Diep DB, Håvarstein LS, Nes IF. 1996. Characterization of the locus responsible for the bacteriocin production in Lactobacillus plantarum C11. J Bacteriol 178:4472–4483. 293. Rojo-Bezares B, Sáenz Y, Navarro L, Jiménez-Díaz R, Zarazaga M, Ruiz-Larrea F, Torres C. 2008. Characterization of a new organization of the plantaricin locus in the inducible bacteriocin-producing Lactobacillus plantarum J23 of grape must origin. Arch Microbiol 189:491–499. 294. Zuckerman JN, Rombo L, Fisch A. 2007. The true burden and risk of cholera: implications for prevention and control. The Lancet Infectious Diseases. 295. Baker-Austin C, Oliver JD, Alam M, Ali A, Waldor MK, Qadri F, Martinez-Urtaza J. 2018. Vibrio spp. infections. Nature Reviews Disease Primers. 296. Kim HB, Wang M, Ahmed S, Park CH, LaRocque RC, Faruque ASG, Salam MA, Khan WA, Qadri F, Calderwood SB, Jacoby GA, Hooper DC. 2010. Transferable quinolone resistance in Vibrio cholerae. Antimicrob Agents Chemother 54:799–803. 297. Glass RI, Huq MI, Lee JV, Threlfall EJ, Khan MR, Alim AR, Rowe B, Gross RJ. 1983. Plasmid-borne multiple drug resistance in Vibrio cholerae serogroup O1, biotype El Tor: evidence for a point-source outbreak in Bangladesh. J Infect Dis 147:204–209. 298. Pang B, Du P, Zhou Z, Diao B, Cui Z, Zhou H, Kan B. 2016. The Transmission and Antibiotic Resistance Variation in a Multiple Drug Resistance Clade of Vibrio cholerae Circulating in Multiple Countries in Asia. PLOS ONE. 299. Ramakrishna BS, Venkataraman S, Srinivasan P, Dash P, Young GP, Binder HJ. 2000. Amylase-resistant starch plus oral rehydration solution for cholera. N Engl J Med 342:308– 313. 300. Krishna BVS, Patil AB, Chandrasekhar MR. 2006. Fluoroquinolone-resistant Vibrio cholerae isolated during a cholera outbreak in India. Transactions of the Royal Society of Tropical Medicine and Hygiene. 301. Nielsen AT, Dolganov NA, Rasmussen T, Otto G, Miller MC, Felt SA, Torreilles S, Schoolnik GK. 2010. A bistable switch and anatomical site control Vibrio cholerae virulence gene expression in the intestine. PLoS Pathog 6:e1001102. 302. Haas BL, Matson JS, DiRita VJ, Biteen JS. 2015. Single-molecule tracking in live Vibrio cholerae reveals that ToxR recruits the membrane-bound virulence regulator TcpP to the toxT promoter. Mol Microbiol 96:4–13. 303. Haas BL, Matson JS, DiRita VJ, Biteen JS. 2014. Imaging live cells at the nanometer-scale 244 with single-molecule microscopy: obstacles and achievements in experiment optimization for microbiology. Molecules 19:12116–12149. 304. Hanson BR, Lowe BA, Neely MN. 2011. Membrane topology and DNA-binding ability of the Streptococcal CpsA protein. J Bacteriol 193:411–420. 305. Cieslewicz MJ, Kasper DL, Wang Y, Wessels MR. 2001. Functional analysis in type Ia group B Streptococcus of a cluster of genes involved in extracellular polysaccharide production by diverse species of streptococci. J Biol Chem 276:139–146. 306. Gebhard S, Gaballa A, Helmann JD, Cook GM. 2009. Direct stimulus perception and transcription activation by a membrane-bound DNA binding protein. Mol Microbiol 73:482– 491. 307. Hubbard TP, Chao MC, Abel S, Blondel CJ, Abel Zur Wiesch P, Zhou X, Davis BM, Waldor MK. 2016. Genetic analysis of Vibrio parahaemolyticus intestinal colonization. Proc Natl Acad Sci U S A 113:6283–6288. 308. Sobetzko P, Travers A, Muskhelishvili G. 2012. Gene order and chromosome dynamics coordinate spatiotemporal gene expression during the bacterial growth cycle. Proceedings of the National Academy of Sciences. 309. Browning DF, Grainger DC, Busby SJ. 2010. Effects of nucleoid-associated proteins on bacterial chromosome structure and gene expression. Curr Opin Microbiol 13:773–780. 310. Liu LF, Wang JC. 1987. Supercoiling of the DNA template during transcription. Proceedings of the National Academy of Sciences https://doi.org/10.1073/pnas.84.20.7024. 311. Harrington EW, Trun NJ. 1997. Unfolding of the bacterial nucleoid both in vivo and in vitro as a result of exposure to camphor. J Bacteriol 179:2435–2439. 312. Dorman CJ. 1991. DNA supercoiling and environmental regulation of gene expression in pathogenic bacteria. Infection and Immunity. 313. Badrinarayanan A, Le TBK, Laub MT. 2015. Bacterial Chromosome Organization and Segregation. Annual Review of Cell and Developmental Biology. 314. Brameyer S, Rösch TC, El Andari J, Hoyer E, Schwarz J, Graumann PL, Jung K. 2019. DNA-binding directs the localization of a membrane-integrated receptor of the ToxR family. Commun Biol 2:4. 315. Valens M, Penaud S, Rossignol M, Cornet F, Boccard F. 2004. Macrodomain organization of the Escherichia coli chromosome. The EMBO Journal. 316. Cagliero C, Grand RS, Jones MB, Jin DJ, O’Sullivan JM. 2013. Genome conformation capture reveals that the Escherichia coli chromosome is organized by replication and transcription. Nucleic Acids Res 41:6058–6071. 317. Le TBK, Imakaev MV, Mirny LA, Laub MT. 2013. High-resolution mapping of the spatial organization of a bacterial chromosome. Science 342:731–734. 318. Karslake JD, Donarski ED, Shelby SA, Demey LM, DiRita VJ, Veatch SL, Biteen JS. 2020. SMAUG: Analyzing single-molecule tracks with nonparametric Bayesian statistics. 245 Methods. 319. 2016. LB Liquid Medium. Cold Spring Harbor Protocols https://doi.org/10.1101/pdb.rec090928. 320. Skorupski K, Taylor RK. 1996. Positive selection vectors for allelic exchange. Gene https://doi.org/10.1016/0378-1119(95)00793-8. 321. Amin Marashi SM, Rajabnia R, Imani Fooladi AA, Hojati Z, Moghim S, Nasr Esfahani B. 2013. Determination of ctxAB expression in Vibrio cholerae Classical and El Tor strains using Real-Time PCR. Int J Mol Cell Med 2:9–13. 322. Schmittgen TD, Livak KJ. 2008. Analyzing real-time PCR data by the comparative C(T) method. Nat Protoc 3:1101–1108. 323. Isaacoff BP, Li Y, Lee SA, Biteen JS. 2019. SMALL-LABS: Measuring Single-Molecule Intensity and Position in Obscuring Backgrounds. Biophys J 116:975–982. 324. Liao Y, Schroeder JW, Gao B, Simmons LA, Biteen JS. 2015. Single-molecule motions and interactions in live cells reveal target search dynamics in mismatch repair. Proc Natl Acad Sci U S A 112:E6898–906. 325. Munkres J. 1957. Algorithms for the Assignment and Transportation Problems. Journal of the Society for Industrial and Applied Mathematics. 326. Park N-Y, Kim IH, Wen Y, Lee K-W, Lee S, Kim J-A, Jung K-H, Lee K-H, Kim K-S. 2019. Multi-Factor Regulation of the Master Modulator LeuO for the Cyclic-(Phe-Pro) Signaling Pathway in Vibrio vulnificus. Sci Rep 9:20135. 327. Bina XR, Taylor DL, Vikram A, Ante VM, Bina JE. 2013. Vibrio cholerae ToxR downregulates virulence factor production in response to cyclo(Phe-Pro). MBio 4:e00366– 13. 328. Ramadurai S, Holt A, Krasnikov V, van den Bogaart G, Killian JA, Poolman B. 2009. Lateral diffusion of membrane proteins. J Am Chem Soc 131:12650–12656. 329. Lucena D, Mauri M, Schmidt F, Eckhardt B, Graumann PL. 2018. Microdomain formation is a general property of bacterial membrane proteins and induces heterogeneity of diffusion patterns. BMC Biol 16:97. 330. Lorent JH, Diaz-Rohrer B, Lin X, Spring K, Gorfe AA, Levental KR, Levental I. 2018. Author Correction: Structural determinants and functional consequences of protein affinity for membrane rafts. Nat Commun 9:1805. 331. Bina J, Zhu J, Dziejman M, Faruque S, Calderwood S, Mekalanos J. 2003. ToxR regulon of Vibrio cholerae and its expression in vibrios shed by cholera patients. Proceedings of the National Academy of Sciences. 332. Angelichio MJ, Spector J, Waldor MK, Camilli A. 1999. Vibrio cholerae Intestinal Population Dynamics in the Suckling Mouse Model of Infection. Infection and Immunity https://doi.org/10.1128/iai.67.8.3733-3739.1999. 333. Millet YA, Alvarez D, Ringgaard S, von Andrian UH, Davis BM, Waldor MK. 2014. Insights 246 into Vibrio cholerae intestinal colonization from monitoring fluorescently labeled bacteria. PLoS Pathog 10:e1004405. 334. Taylor RK, Miller VL, Furlong DB, Mekalanos JJ. 1987. Use of phoA gene fusions to identify a pilus colonization factor coordinately regulated with cholera toxin. Proc Natl Acad Sci U S A 84:2833–2837. 335. Nelson EJ, Harris JB, Glenn Morris J, Calderwood SB, Camilli A. 2009. Cholera transmission: the host, pathogen and bacteriophage dynamic. Nature Reviews Microbiology https://doi.org/10.1038/nrmicro2204. 336. Camilli A, Beattie DT, Mekalanos JJ. 1994. Use of genetic recombination as a reporter of gene expression. Proc Natl Acad Sci U S A 91:2634–2638. 337. Nielsen AT, Dolganov NA, Rasmussen T, Otto G, Miller MC, Felt SA, Torreilles S, Schoolnik GK. 2010. A bistable switch and anatomical site control Vibrio cholerae virulence gene expression in the intestine. PLoS Pathog 6:e1001102. 338. Higgins DE, Nazareno E, DiRita VJ. 1992. The virulence gene activator ToxT from Vibrio cholerae is a member of the AraC family of transcriptional activators. Journal of Bacteriology https://doi.org/10.1128/jb.174.21.6974-6980.1992. 339. Higgins DE, DiRita VJ. 1994. Transcriptional control of toxT, a regulatory gene in the ToxR regulon of Vibrio cholerae. Mol Microbiol 14:17–29. 340. Krukonis ES, Yu RR, Dirita VJ. 2000. The Vibrio cholerae ToxR/TcpP/ToxT virulence cascade: distinct roles for two membrane-localized transcriptional activators on a single promoter. Mol Microbiol 38:67–84. 341. DiRita VJ, Parsot C, Jander G, Mekalanos JJ. 1991. Regulatory cascade controls virulence in Vibrio cholerae. Proc Natl Acad Sci U S A 88:5403–5407. 342. Miller VL, Taylor RK, Mekalanos JJ. 1987. Cholera toxin transcriptional activator toxR is a transmembrane DNA binding protein. Cell 48:271–279. 343. Crawford JA, Krukonis ES, DiRita VJ. 2003. Membrane localization of the ToxR winged- helix domain is required for TcpP-mediated virulence gene activation in Vibrio cholerae. Mol Microbiol 47:1459–1473. 344. Hase CC, Mekalanos JJ. 1998. TcpP protein is a positive regulator of virulence gene expression in Vibrio cholerae. Proceedings of the National Academy of Sciences https://doi.org/10.1073/pnas.95.2.730. 345. Carroll PA, Tashima KT, Rogers MB, DiRita VJ, Calderwood SB. 1997. Phase variation in tcpH modulates expression of the ToxR regulon in Vibrio cholerae. Mol Microbiol 25:1099– 1111. 346. Martıń ez-Hackert E, Stock AM. 1997. Structural relationships in the OmpR family of winged-helix transcription factors 1 1Edited by M. Gottesman. Journal of Molecular Biology https://doi.org/10.1006/jmbi.1997.1065. 347. Krukonis ES, DiRita VJ. 2003. DNA binding and ToxR responsiveness by the wing domain of TcpP, an activator of virulence gene expression in Vibrio cholerae. Mol Cell 12:157–165. 247 348. Goss TJ, Seaborn CP, Gray MD, Krukonis ES. 2010. Identification of the TcpP-Binding Site in the toxT Promoter of Vibrio cholerae and the Role of ToxR in TcpP-Mediated Activation. Infection and Immunity https://doi.org/10.1128/iai.00566-10. 349. Kovacikova G, Skorupski K. 2002. Regulation of virulence gene expression in Vibrio cholerae by quorum sensing: HapR functions at the aphA promoter. Mol Microbiol 46:1135– 1147. 350. Liu Z, Yang M, Peterfreund GL, Tsou AM, Selamoglu N, Daldal F, Zhong Z, Kan B, Zhu J. 2011. Vibrio cholerae anaerobic induction of virulence gene expression is controlled by thiol-based switches of virulence regulator AphB. Proc Natl Acad Sci U S A 108:810–815. 351. Teoh WP, Matson JS, DiRita VJ. 2015. Regulated intramembrane proteolysis of the virulence activator TcpP in Vibrio cholerae is initiated by the tail-specific protease (Tsp). Mol Microbiol 97:822–831. 352. Matson JS, DiRita VJ. 2005. Degradation of the membrane-localized virulence activator TcpP by the YaeL protease in Vibrio cholerae. Proc Natl Acad Sci U S A 102:16403–16408. 353. Brown MS, Ye J, Rawson RB, Goldstein JL. 2000. Regulated intramembrane proteolysis: a control mechanism conserved from bacteria to humans. Cell 100:391–398. 354. Peñas ADL, De Las Peñas A, Connolly L, Gross CA. 1997. The σ E ‐mediated response to extracytoplasmic stress in Escherichia coli is transduced by RseA and RseB, two negative regulators of σ E. Molecular Microbiology https://doi.org/10.1046/j.1365- 2958.1997.3611718.x. 355. Alba BM. 2002. DegS and YaeL participate sequentially in the cleavage of RseA to activate the sigma E-dependent extracytoplasmic stress response. Genes & Development https://doi.org/10.1101/gad.1008902. 356. Dartigalongue C, Missiakas D, Raina S. 2001. Characterization of theEscherichia coliςERegulon. Journal of Biological Chemistry https://doi.org/10.1074/jbc.m100464200. 357. Rhodius VA, Suh WC, Nonaka G, West J, Gross CA. 2005. Conserved and Variable Functions of the σE Stress Response in Related Genomes. PLoS Biology https://doi.org/10.1371/journal.pbio.0040002. 358. Zhou R, Kroos L. 2005. Serine proteases from two cell types target different components of a complex that governs regulated intramembrane proteolysis of pro-sigmaK during Bacillus subtilis development. Mol Microbiol 58:835–846. 359. Wakeley PR, Dorazi R, Hoa NT, Bowyer JR, Cutting SM. 2002. Proteolysis of SpoIVB is a critical determinant in signalling of Pro-σK processing in Bacillus subtilis. Molecular Microbiology https://doi.org/10.1046/j.1365-2958.2000.01946.x. 360. Kroos L, Yu YT. 2000. Regulation of sigma factor activity during Bacillus subtilis development. Curr Opin Microbiol 3:553–560. 361. Cezairliyan BO, Sauer RT. 2007. Inhibition of regulated proteolysis by RseB. Proc Natl Acad Sci U S A 104:3771–3776. 362. Wollmann P, Zeth K. 2007. The structure of RseB: a sensor in periplasmic stress response 248 of E. coli. J Mol Biol 372:927–941. 363. Wilken C, Kitzing K, Kurzbauer R, Ehrmann M, Clausen T. 2004. Crystal structure of the DegS stress sensor: How a PDZ domain recognizes misfolded protein and activates a protease. Cell 117:483–494. 364. Zhou R, Kroos L. 2004. BofA protein inhibits intramembrane proteolysis of pro-sigmaK in an intercompartmental signaling pathway during Bacillus subtilis sporulation. Proc Natl Acad Sci U S A 101:6385–6390. 365. Resnekov O. 1999. Role of the sporulation protein BofA in regulating activation of the Bacillus subtilis developmental transcription factor sigmaK. J Bacteriol 181:5384–5388. 366. Ricca E, Cutting S, Losick R. 1992. Characterization of bofA, a gene involved in intercompartmental regulation of pro-sigma K processing during sporulation in Bacillus subtilis. Journal of Bacteriology https://doi.org/10.1128/jb.174.10.3177-3184.1992. 367. Bramkamp M, Lopez D. 2015. Exploring the existence of lipid rafts in bacteria. Microbiol Mol Biol Rev 79:81–100. 368. Toledo A, Huang Z, Coleman JL, London E, Benach JL. 2018. Lipid rafts can form in the inner and outer membranes of Borrelia burgdorferi and have different properties and associated proteins. Mol Microbiol 108:63–76. 369. Huang Z, Zhang X-S, Blaser MJ, London E. 2019. Helicobacter pylori lipids can form ordered membrane domains (rafts). Biochim Biophys Acta Biomembr 1861:183050. 370. Koch G, Wermser C, Acosta IC, Kricks L, Stengel ST, Yepes A, Lopez D. 2017. Attenuating Staphylococcus aureus Virulence by Targeting Flotillin Protein Scaffold Activity. Cell Chem Biol 24:845–857.e6. 371. Lopez D, Kolter R. 2010. Functional microdomains in bacterial membranes. Genes & Development https://doi.org/10.1101/gad.1945010. 372. Sezgin E, Levental I, Mayor S, Eggeling C. 2017. The mystery of membrane organization: composition, regulation and roles of lipid rafts. Nat Rev Mol Cell Biol 18:361–374. 373. Pike LJ. 2006. Rafts defined: a report on the Keystone Symposium on Lipid Rafts and Cell Function. J Lipid Res 47:1597–1598. 374. Nicolau DV, Burrage K, Parton RG, Hancock JF. 2006. Identifying Optimal Lipid Raft Characteristics Required To Promote Nanoscale Protein-Protein Interactions on the Plasma Membrane. Molecular and Cellular Biology https://doi.org/10.1128/mcb.26.1.313-323.2006. 375. Simons K, Vaz WLC. 2004. Model systems, lipid rafts, and cell membranes. Annu Rev Biophys Biomol Struct 33:269–295. 376. Yu J, Fischman DA, Steck TL. 1973. Selective solubilization of proteins and phospholipids from red blood cell membranes by nonionic detergents. Journal of Supramolecular Structure https://doi.org/10.1002/jss.400010308. 377. Simons K, Ikonen E. 1997. Functional rafts in cell membranes. Nature 387:569–572. 249 378. Ourisson G, Rohmer M. 1992. Hopanoids. 2. Biohopanoids: a novel class of bacterial lipids. Accounts of Chemical Research https://doi.org/10.1021/ar00021a004. 379. Sáenz JP, Grosser D, Bradley AS, Lagny TJ, Lavrynenko O, Broda M, Simons K. 2015. Hopanoids as functional analogues of cholesterol in bacterial membranes. Proc Natl Acad Sci U S A 112:11971–11976. 380. Nickels JD, Chatterjee S, Stanley CB, Qian S, Cheng X, Myles DAA, Standaert RF, Elkins JG, Katsaras J. 2017. The in vivo structure of biological membranes and evidence for lipid domains. PLoS Biol 15:e2002214. 381. 2016. LB Liquid Medium. Cold Spring Harbor Protocols https://doi.org/10.1101/pdb.rec090928. 382. Lycke N, Tsuji T, Holmgren J. 1992. The adjuvant effect ofVibrio cholerae andEscherichia coli heat-labile enterotoxins is linked to their ADP-ribosyltransferase activity. European Journal of Immunology https://doi.org/10.1002/eji.1830220915. 383. Anthouard R, DiRita VJ. 2013. Small-molecule inhibitors of toxT expression in Vibrio cholerae. MBio 4. 384. Schmittgen TD, Livak KJ. 2008. Analyzing real-time PCR data by the comparative CT method. Nature Protocols https://doi.org/10.1038/nprot.2008.73. 385. Amin Marashi SM, Rajabnia R, Imani Fooladi AA, Hojati Z, Moghim S, Nasr Esfahani B. 2013. Determination of ctxAB expression in Vibrio cholerae Classical and El Tor strains using Real-Time PCR. Int J Mol Cell Med 2:9–13. 386. Miller JH, Cold Spring Harbor Laboratory. 1974. Experiments in Molecular Genetics. 387. Quan S, Hiniker A, Collet J-F, Bardwell JCA. 2013. Isolation of Bacteria Envelope Proteins. Methods in Molecular Biology https://doi.org/10.1007/978-1-62703-245-2_22. 388. Jiang L, He L, Fountoulakis M. 2004. Comparison of protein precipitation methods for sample preparation prior to proteomic analysis. Journal of Chromatography A https://doi.org/10.1016/j.chroma.2003.10.029. 389. Sandkvist M, Hough LP, Bagdasarian MM, Bagdasarian M. 1999. Direct Interaction of the EpsL and EpsM Proteins of the General Secretion Apparatus in Vibrio cholerae. Journal of Bacteriology https://doi.org/10.1128/jb.181.10.3129-3135.1999. 390. Kameda K, Nunn WD. 1981. Purification and characterization of acyl coenzyme A synthetase from Escherichia coli. J Biol Chem 256:5702–5707. 391. Klein K, Steinberg R, Fiethen B, Overath P. 1971. Fatty acid degradation in Escherichia coli. An inducible system for the uptake of fatty acids and further characterization of old mutants. Eur J Biochem 19:442–450. 392. Nunn WD, Simons RW. 1978. Transport of long-chain fatty acids by Escherichia coli: mapping and characterization of mutants in the fadL gene. Proc Natl Acad Sci U S A 75:3377–3381. 393. Nunn WD, Colburn RW, Black PN. 1986. Transport of long-chain fatty acids in Escherichia 250 coli. Evidence for role of fadL gene product as long-chain fatty acid receptor. J Biol Chem 261:167–171. 394. Giles DK, Hankins JV, Guan Z, Trent MS. 2011. Remodelling of the Vibrio cholerae membrane by incorporation of exogenous fatty acids from host and aquatic environments. Mol Microbiol 79:716–728. 395. Moravec AR, Siv AW, Hobby CR, Lindsay EN, Norbash LV, Shults DJ, Symes SJK, Giles DK. 2017. Exogenous Polyunsaturated Fatty Acids Impact Membrane Remodeling and Affect Virulence Phenotypes among Pathogenic Vibrio Species. Appl Environ Microbiol 83. 396. Plecha SC, Withey JH. 2015. Mechanism for Inhibition of Vibrio cholerae ToxT Activity by the Unsaturated Fatty Acid Components of Bile. Journal of Bacteriology https://doi.org/10.1128/jb.02409-14. 397. Jiang Y, Morgan-Kiss RM, Campbell JW, Chan CH, Cronan JE. 2010. Expression of Vibrio harveyi acyl-ACP synthetase allows efficient entry of exogenous fatty acids into the Escherichia coli fatty acid and lipid A synthetic pathways. Biochemistry 49:718–726. 398. Yao J, Rock CO. 2017. Exogenous fatty acid metabolism in bacteria. Biochimie https://doi.org/10.1016/j.biochi.2017.06.015. 399. Kim W, Fan Y-Y, Barhoumi R, Smith R, McMurray DN, Chapkin RS. 2008. n-3 Polyunsaturated Fatty Acids Suppress the Localization and Activation of Signaling Proteins at the Immunological Synapse in Murine CD4 T Cells by Affecting Lipid Raft Formation. The Journal of Immunology https://doi.org/10.4049/jimmunol.181.9.6236. 400. Chapkin RS, Wang N, Fan Y-Y, Lupton JR, Prior IA. 2008. Docosahexaenoic acid alters the size and distribution of cell surface microdomains. Biochimica et Biophysica Acta (BBA) - Biomembranes https://doi.org/10.1016/j.bbamem.2007.11.003. 401. Lorent JH, Diaz-Rohrer B, Lin X, Spring K, Gorfe AA, Levental KR, Levental I. 2017. Structural determinants and functional consequences of protein affinity for membrane rafts. Nature Communications https://doi.org/10.1038/s41467-017-01328-3. 402. Schuck S, Honsho M, Ekroos K, Shevchenko A, Simons K. 2003. Resistance of cell membranes to different detergents. Proceedings of the National Academy of Sciences https://doi.org/10.1073/pnas.0631579100. 403. Lichtenberg D, Goñi FM, Heerklotz H. 2005. Detergent-resistant membranes should not be identified with membrane rafts. Trends in Biochemical Sciences https://doi.org/10.1016/j.tibs.2005.06.004. 404. Miller VL, DiRita VJ, Mekalanos JJ. 1989. Identification of toxS, a regulatory gene whose product enhances toxR-mediated activation of the cholera toxin promoter. Journal of Bacteriology https://doi.org/10.1128/jb.171.3.1288-1293.1989. 405. Midgett CR, Swindell RA, Pellegrini M, Jon Kull F. 2020. A disulfide constrains the ToxR periplasmic domain structure, altering its interactions with ToxS and bile-salts. Scientific Reports https://doi.org/10.1038/s41598-020-66050-5. 406. Burdge GC. 2006. Metabolism of α-linolenic acid in humans. Prostaglandins, Leukotrienes 251 and Essential Fatty Acids https://doi.org/10.1016/j.plefa.2006.05.013. 407. Aluko RE. 2012. Functional Foods and Nutraceuticals. Springer Science & Business Media. 408. Destaillats F, Trottier JP, Galvez JMG, Angers P. 2005. Analysis of α-Linolenic Acid Biohydrogenation Intermediates in Milk Fat with Emphasis on Conjugated Linolenic Acids. Journal of Dairy Science https://doi.org/10.3168/jds.s0022-0302(05)73006-x. 409. Plourde M, Destaillats F, Chouinard PY, Angers P. 2007. Conjugated α-Linolenic Acid Isomers in Bovine Milk and Muscle. Journal of Dairy Science https://doi.org/10.3168/jds.2007-0157. 410. Bu DP, Wang JQ, Dhiman TR, Liu SJ. 2007. Effectiveness of Oils Rich in Linoleic and Linolenic Acids to Enhance Conjugated Linoleic Acid in Milk from Dairy Cows. Journal of Dairy Science https://doi.org/10.3168/jds.s0022-0302(07)71585-0. 411. Burdge GC, Calder PC. 2005. Conversion of α-linolenic acid to longer-chain polyunsaturated fatty acids in human adults. Reproduction Nutrition Development https://doi.org/10.1051/rnd:2005047. 412. Yang B, Chen H, Stanton C, Chen YQ, Zhang H, Chen W. 2017. Mining bifidobacteria from the neonatal gastrointestinal tract for conjugated linolenic acid production. Bioengineered 8:232–238. 413. Valenzuela R, Bascuñán K, Chamorro R, Barrera C, Sandoval J, Puigrredon C, Parraguez G, Orellana P, Gonzalez V, Valenzuela A. 2015. Modification of Docosahexaenoic Acid Composition of Milk from Nursing Women Who Received Alpha Linolenic Acid from Chia Oil during Gestation and Nursing. Nutrients 7:6405–6424. 414. Oosting A, Verkade HJ, Kegler D, van de Heijning BJM, van der Beek EM. 2015. Rapid and selective manipulation of milk fatty acid composition in mice through the maternal diet during lactation. J Nutr Sci 4:e19. 415. Dupertuis YM, Meguid MM, Pichard C. 2007. Colon cancer therapy: new perspectives of nutritional manipulations using polyunsaturated fatty acids. Current Opinion in Clinical Nutrition and Metabolic Care https://doi.org/10.1097/mco.0b013e3281e2c9d4. 416. Larsson SC, Kumlin M, Ingelman-Sundberg M, Wolk A. 2004. Dietary long-chain n−3 fatty acids for the prevention of cancer: a review of potential mechanisms. The American Journal of Clinical Nutrition https://doi.org/10.1093/ajcn/79.6.935. 417. Coakley M, Banni S, Johnson MC, Mills S, Devery R, Fitzgerald G, Paul Ross R, Stanton C. 2009. Inhibitory Effect of Conjugated α-Linolenic Acid from Bifidobacteria of Intestinal Origin on SW480 Cancer Cells. Lipids https://doi.org/10.1007/s11745-008-3269-z. 418. Suzuki R, Noguchi R, Ota T, Abe M, Miyashita K, Kawada T. 2001. Cytotoxic effect of conjugated trienoic fatty acids on mouse tumor and human monocytic leukemia cells. Lipids https://doi.org/10.1007/s11745-001-0746-0. 419. Wahle KWJ, Heys SD, Rotondo D. 2004. Conjugated linoleic acids: are they beneficial or detrimental to health? Progress in Lipid Research 252 https://doi.org/10.1016/j.plipres.2004.08.002. 420. Tricon S, Burdge GC, Williams CM, Calder PC, Yaqoob P. 2005. The effects of conjugated linoleic acid on human health-related outcomes. Proceedings of the Nutrition Society https://doi.org/10.1079/pns2005418. 421. Bhattacharya A, Banu J, Rahman M, Causey J, Fernandes G. 2006. Biological effects of conjugated linoleic acids in health and disease. The Journal of Nutritional Biochemistry https://doi.org/10.1016/j.jnutbio.2006.02.009. 422. Leikin-Frenkel A, Liraz-Zaltsman S, Hollander KS, Atrakchi D, Ravid O, Rand D, Kandel- Kfir M, Israelov H, Cohen H, Kamari Y, Shaish A, Harats D, Schnaider-Beeri M, Cooper I. 2021. Dietary alpha linolenic acid in pregnant mice and during weaning increases brain docosahexaenoic acid and improves recognition memory in the offspring. J Nutr Biochem 91:108597. 423. Zhuang P, Shou Q, Wang W, He L, Wang J, Chen J, Zhang Y, Jiao J. 2018. Essential Fatty Acids Linoleic Acid and α-Linolenic Acid Sex-Dependently Regulate Glucose Homeostasis in Obesity. Mol Nutr Food Res 62:e1800448. 424. Kovacikova G, Lin W, Taylor RK, Skorupski K. 2017. The Fatty Acid Regulator FadR Influences the Expression of the Virulence Cascade in the El Tor Biotype of Vibrio cholerae by Modulating the Levels of ToxT via Two Different Mechanisms. J Bacteriol 199. 425. Shi W, Kovacikova G, Lin W, Taylor RK, Skorupski K, Kull FJ. 2015. The 40-residue insertion in Vibrio cholerae FadR facilitates binding of an additional fatty acyl-CoA ligand. Nat Commun 6:6032. 426. Feng Y, Cronan JE. 2011. The Vibrio cholerae fatty acid regulatory protein, FadR, represses transcription of plsB, the gene encoding the first enzyme of membrane phospholipid biosynthesis. Mol Microbiol 81:1020–1033. 427. Yang S, Xi D, Wang X, Li Y, Li Y, Yan J, Cao B. 2020. Vibrio cholerae VC1741 (PsrA) enhances the colonization of the pathogen in infant mice intestines in the presence of the long-chain fatty acid, oleic acid. Microb Pathog 147:104443. 428. Giles DK, Hankins JV, Guan Z, Trent MS. 2011. Remodelling of the Vibrio cholerae membrane by incorporation of exogenous fatty acids from host and aquatic environments. Mol Microbiol 79:716–728. 429. Nunn WD, Colburn RW, Black PN. 1986. Transport of long-chain fatty acids in Escherichia coli. Evidence for role of fadL gene product as long-chain fatty acid receptor. J Biol Chem 261:167–171. 430. Kim W, Fan Y-Y, Barhoumi R, Smith R, McMurray DN, Chapkin RS. 2008. n-3 Polyunsaturated Fatty Acids Suppress the Localization and Activation of Signaling Proteins at the Immunological Synapse in Murine CD4 T Cells by Affecting Lipid Raft Formation. The Journal of Immunology https://doi.org/10.4049/jimmunol.181.9.6236. 431. Chapkin RS, Wang N, Fan Y-Y, Lupton JR, Prior IA. 2008. Docosahexaenoic acid alters the size and distribution of cell surface microdomains. Biochimica et Biophysica Acta (BBA) - Biomembranes https://doi.org/10.1016/j.bbamem.2007.11.003. 253 432. Chatterjee E, Chowdhury R. 2013. Reduced virulence of the Vibrio cholerae fadD mutant is due to induction of the extracytoplasmic stress response. Infect Immun 81:3935–3941. 433. Ray S, Chatterjee E, Chatterjee A, Paul K, Chowdhury R. 2011. A fadD mutant of Vibrio cholerae is impaired in the production of virulence factors and membrane localization of the virulence regulatory protein TcpP. Infect Immun 79:258–266. 434. Komura N, Suzuki KGN, Ando H, Konishi M, Koikeda M, Imamura A, Chadda R, Fujiwara TK, Tsuboi H, Sheng R, Cho W, Furukawa K, Furukawa K, Yamauchi Y, Ishida H, Kusumi A, Kiso M. 2016. Raft-based interactions of gangliosides with a GPI-anchored receptor. Nat Chem Biol 12:402–410. 435. Lorent J, Diaz-Rohrer BB, Lin X, Gorfe A, Levental KR, Levental I. 2018. Structural Determinants and Functional Consequences of Protein Association with Membrane Domains. Biophysical Journal https://doi.org/10.1016/j.bpj.2017.11.2103. 436. Yuan Z, Zhang F, Davis MJ, Bodén M, Teasdale RD. 2006. Predicting the solvent accessibility of transmembrane residues from protein sequence. J Proteome Res 5:1063– 1070. 437. Li N, Zheng Y, Shi M, Xue Y, Zhang T, Ji S, Yang M. 2019. TcpP L152A Constitutively Activating Virulence Gene Expression in Vibrio cholerae. Curr Microbiol 76:583–589. 438. Lim MS, Ng D, Zong Z, Arvai AS, Taylor RK, Tainer JA, Craig L. 2010. Vibrio cholerae El Tor TcpA crystal structure and mechanism for pilus-mediated microcolony formation. Mol Microbiol 77:755–770. 439. Abuaita BH, Withey JH. 2009. Bicarbonate Induces Vibrio cholerae virulence gene expression by enhancing ToxT activity. Infect Immun 77:4111–4120. 440. Lembke M, Pennetzdorfer N, Tutz S, Koller M, Vorkapic D, Zhu J, Schild S, Reidl J. 2018. Proteolysis of ToxR is controlled by cysteine-thiol redox state and bile salts in Vibrio cholerae. Mol Microbiol 110:796–810. 441. Mathur J, Waldor MK. 2004. The Vibrio cholerae ToxR-regulated porin OmpU confers resistance to antimicrobial peptides. Infect Immun 72:3577–3583. 442. Chen L, Qiu Y, Tang H, Hu LF, Yang WH, Zhu XJ, Huang XX, Wang T, Zhang YQ. 2018. ToxR Is Required for Biofilm Formation and Motility of Vibrio Parahaemolyticus. Biomed Environ Sci 31:848–850. 443. Provenzano D, Schuhmacher DA, Barker JL, Klose KE. 2000. The virulence regulatory protein ToxR mediates enhanced bile resistance in Vibrio cholerae and other pathogenic Vibrio species. Infect Immun 68:1491–1497. 444. Lee YH, Kim BH, Kim JH, Yoon WS, Bang SH, Park YK. 2007. CadC has a global translational effect during acid adaptation in Salmonella enterica serovar Typhimurium. J Bacteriol 189:2417–2425. 445. Lee YH, Kim JH. 2017. Direct interaction between the transcription factors CadC and OmpR involved in the acid stress response of Salmonella enterica. J Microbiol 55:966–972. 446. Stelzer S, Egan S, Larsen MR, Bartlett DH, Kjelleberg S. 2006. Unravelling the role of the 254 ToxR-like transcriptional regulator WmpR in the marine antifouling bacterium Pseudoalteromonas tunicata. Microbiology 152:1385–1394. 447. Egan S, James S, Kjelleberg S. 2002. Identification and characterization of a putative transcriptional regulator controlling the expression of fouling inhibitors in Pseudoalteromonas tunicata. Appl Environ Microbiol 68:372–378. 448. Bischof LF, Haurat MF, Albers S-V. 2019. Two membrane-bound transcription factors regulate expression of various type-IV-pili surface structures in. PeerJ 7:e6459. 449. Gumerov VM, Ortega DR, Adebali O, Ulrich LE, Zhulin IB. 2020. MiST 3.0: an updated microbial signal transduction database with an emphasis on chemosensory systems. Nucleic Acids Res 48:D459–D464. 450. Gumerov VM, Zhulin IB. 2020. TREND: a platform for exploring protein function in prokaryotes based on phylogenetic, domain architecture and gene neighborhood analyses. Nucleic Acids Res 48:W72–W76. 451. Mistry J, Chuguransky S, Williams L, Qureshi M, Salazar GA, Sonnhammer ELL, Tosatto SCE, Paladin L, Raj S, Richardson LJ, Finn RD, Bateman A. 2021. Pfam: The protein families database in 2021. Nucleic Acids Res 49:D412–D419. 452. Hoch JA. 2000. Two-component and phosphorelay signal transduction. Current Opinion in Microbiology https://doi.org/10.1016/s1369-5274(00)00070-9. 453. Gao R, Mack TR, Stock AM. 2007. Bacterial response regulators: versatile regulatory strategies from common domains. Trends in Biochemical Sciences https://doi.org/10.1016/j.tibs.2007.03.002. 454. Lowe EC, Basle A, Czjzek M, Firbank SJ, Bolam DN. 2012. A scissor blade-like closing mechanism implicated in transmembrane signaling in a Bacteroides hybrid two-component system. Proceedings of the National Academy of Sciences https://doi.org/10.1073/pnas.1200479109. 455. Wolanin PM, Thomason PA, Stock JB. 2002. Histidine protein kinases: key signal transducers outside the animal kingdom. Genome Biol 3:REVIEWS3013. 456. Dutta R, Inouye M. 2000. GHKL, an emergent ATPase/kinase superfamily. Trends Biochem Sci 25:24–28. 457. Xu J, Chiang HC, Bjursell MK, Gordon JI. 2004. Message from a human gut symbiont: sensitivity is a prerequisite for sharing. Trends Microbiol 12:21–28. 458. Zhang W, Shi L. 2005. Distribution and evolution of multiple-step phosphorelay in prokaryotes: lateral domain recruitment involved in the formation of hybrid-type histidine kinases. Microbiology 151:2159–2173. 459. Sonnenburg ED, Sonnenburg JL, Manchester JK, Hansen EE, Chiang HC, Gordon JI. 2006. A hybrid two-component system protein of a prominent human gut symbiont couples glycan sensing in vivo to carbohydrate metabolism. Proc Natl Acad Sci U S A 103:8834– 8839. 460. Nicolau DV Jr, Burrage K, Parton RG, Hancock JF. 2006. Identifying optimal lipid raft 255 characteristics required to promote nanoscale protein-protein interactions on the plasma membrane. Mol Cell Biol 26:313–323. 461. Yu J, Fischman DA, Steck TL. 1973. Selective solubilization of proteins and phospholipids from red blood cell membranes by nonionic detergents. J Supramol Struct 1:233–248. 462. Simons K, Toomre D. 2000. Lipid rafts and signal transduction. Nat Rev Mol Cell Biol 1:31– 39. 463. Chapkin RS, Wang N, Fan Y-Y, Lupton JR, Prior IA. 2008. Docosahexaenoic acid alters the size and distribution of cell surface microdomains. Biochim Biophys Acta 1778:466– 471. 464. Danylec N, Göbl A, Stoll DA, Hetzer B, Kulling SE, Huch M. 2018. Rubneribacter badeniensis gen. nov., sp. nov. and Enteroscipio rubneri gen. nov., sp. nov., new members of the Eggerthellaceae isolated from human faeces. Int J Syst Evol Microbiol 68:1533– 1540. 465. Beltrán D, Romo-Vaquero M, Espín JC, Tomás-Barberán FA, Selma MV. 2018. Ellagibacter isourolithinifaciens gen. nov., sp. nov., a new member of the family Eggerthellaceae, isolated from human gut. International Journal of Systematic and Evolutionary Microbiology https://doi.org/10.1099/ijsem.0.002735. 466. Clavel T, Charrier C, Braune A, Wenning M, Blaut M, Haller D. 2009. Isolation of bacteria from the ileal mucosa of TNFdeltaARE mice and description of Enterorhabdus mucosicola gen. nov., sp. nov. Int J Syst Evol Microbiol 59:1805–1812. 467. Clavel T, Duck W, Charrier C, Wenning M, Elson C, Haller D. 2010. Enterorhabdus caecimuris sp. nov., a member of the family Coriobacteriaceae isolated from a mouse model of spontaneous colitis, and emended description of the genus Enterorhabdus Clavel et al. 2009. International Journal of Systematic and Evolutionary Microbiology https://doi.org/10.1099/ijs.0.015016-0. 468. Lagkouvardos I, Pukall R, Abt B, Foesel BU, Meier-Kolthoff JP, Kumar N, Bresciani A, Martínez I, Just S, Ziegler C, Brugiroux S, Garzetti D, Wenning M, Bui TPN, Wang J, Hugenholtz F, Plugge CM, Peterson DA, Hornef MW, Baines JF, Smidt H, Walter J, Kristiansen K, Nielsen HB, Haller D, Overmann J, Stecher B, Clavel T. 2016. The Mouse Intestinal Bacterial Collection (miBC) provides host-specific insight into cultured diversity and functional potential of the gut microbiota. Nat Microbiol 1:16131. 469. Gupta RS. 2021. Eggerthellaceae. Bergey’s Manual of Systematics of Archaea and Bacteria https://doi.org/10.1002/9781118960608.fbm00384. 470. Dalia TN, Chlebek JL, Dalia AB. 2020. A modular chromosomally integrated toolkit for ectopic gene expression in Vibrio cholerae. Sci Rep 10:15398. 471. Muller-Hill B, Crapo L, Gilbert W. 1968. Mutants that make more lac repressor. Proceedings of the National Academy of Sciences https://doi.org/10.1073/pnas.59.4.1259. 472. Shevchenko A, Wilm M, Vorm O, Mann M. 1996. Mass Spectrometric Sequencing of Proteins from Silver-Stained Polyacrylamide Gels. Analytical Chemistry https://doi.org/10.1021/ac950914h. 256 473. Wang Z, Benning C. 2011. Arabidopsis thaliana polar glycerolipid profiling by thin layer chromatography (TLC) coupled with gas-liquid chromatography (GLC). J Vis Exp https://doi.org/10.3791/2518. 474. Jobling MG, Palmer LM, Erbe JL, Holmes RK. 1997. Construction and characterization of versatile cloning vectors for efficient delivery of native foreign proteins to the periplasm of Escherichia coli. Plasmid 38:158–173. 475. Morgan SJ, French EL, Thomson JJ, Seaborn CP, Shively CA, Krukonis ES. 2016. Formation of an Intramolecular Periplasmic Disulfide Bond in TcpP Protects TcpP and TcpH from Degradation in Vibrio cholerae. J Bacteriol 198:498–509. 476. Jobling MG, Palmer LM, Erbe JL, Holmes RK. 1997. Construction and characterization of versatile cloning vectors for efficient delivery of native foreign proteins to the periplasm of Escherichia coli. Plasmid 38:158–173. 477. Amartely H, Iosub-Amir A, Friedler A. 2014. Identifying protein-protein interaction sites using peptide arrays. J Vis Exp e52097. 478. Minato Y, Fassio SR, Wolfe AJ, Häse CC. 2013. Central metabolism controls transcription of a virulence gene regulator in Vibrio cholerae. Microbiology 159:792–802. 479. Hardie DG, Grahame Hardie D. 1989. Regulation of fatty acid synthesis via phosphorylation of acetyl-CoA carboxylase. Progress in Lipid Research https://doi.org/10.1016/0163-7827(89)90010-6. 480. Konovalova A, Grabowicz M, Balibar CJ, Malinverni JC, Painter RE, Riley D, Mann PA, Wang H, Garlisi CG, Sherborne B, Rigel NW, Ricci DP, Black TA, Roemer T, Silhavy TJ, Walker SS. 2018. Inhibitor of intramembrane protease RseP blocks the σE response causing lethal accumulation of unfolded outer membrane proteins. Proceedings of the National Academy of Sciences https://doi.org/10.1073/pnas.1806107115. 257