CHARACTERIZATION OF MAP3773C, FERRIC UPTAKE REGULATOR PROTEIN, IN IRON METABOLISM OF MYCOBACTERIUM AVIUM SUBSP. PARATUBERCULOSIS By Fernanda Miyagaki Shoyama A DISSERTATION Submitted to Michigan State University in partial fulfillment of the requirements for the degree of Comparative Medicine and Integrative Biology – Doctor of Philosophy 2020 ABSTRACT CHARACTERIZATION OF MAP3773C, FERRIC UPTAKE REGULATOR PROTEIN, IN IRON METABOLISM OF MYCOBACTERIUM AVIUM SUBSP. PARATUBERCULOSIS By Fernanda Miyagaki Shoyama Mycobacterium avium subsp. paratuberculosis (MAP) is the causative agent of Johne’s disease (JD) in ruminants, a chronic inflammation of the intestines characterized by persistent diarrhea that leads to malnutrition and muscular wasting (Rathnaiah et al., 2017). Unfortunately to date, reliable JD diagnostics are lacking. Culture of MAP from feces has been the most reliable method for diagnosis of JD, however MAP requires eight to sixteen weeks to produce colonies in culture, presenting a major hurdle to diagnosis (Bannantine et al., 2002). Currently, no current vaccine can protect animals against JD or prevent shedding of MAP (Garcia and Shalloo, 2015). These challenges establish a need for a better understanding of the MAP physiology during infection. Unlike other mycobacteria, MAP has a unique requirement for supplementation of an iron-binding siderophore (mycobactin J) for optimal growth in laboratory media. A whole genome sequence of MAP K10 revealed a truncation of the mbtA gene that was speculated to have led to its mycobactin dependency (Li et al., 2005). Zhu et al (2008) showed that MAP is able to transcribe all mycobactin synthesis genes in an intra-macrophage environment. Furthermore, several genes responsible for iron acquisition in infected tissues, including genes responsible for mycobactin biosynthesis have been shown to be upregulated in naturally infected tissues (Janagama et al., 2010). Its known that iron plays an important role in vital biological processes; however high intracellular concentration of free iron can lead to toxicity to the bacteria. As such, bacteria activate expression of specific group of genes that are controlled by a metal-sensing regulatory transcription factor. In 2009, Janagama and others identified and characterized the iron dependent regulator (IdeR) in MAP. In addition, in a MAP-specific genomic island, MAP carries three putative ferric uptake regulator (Fur) boxes, an iron regulated transcriptional control motif, (Stratmann et al., 2004). To date, nothing is known about the role of Fur in MAP. To elucidate the mechanisms of iron homeostasis in MAP, we investigated LSP15 using a transposon mutant MAP3776c. We demonstrated a phenotype for LSP15 genes in a culture model of cell entry and survival and suggest a function in epithelial cell pathogenesis, however further functional analysis with complementation by a MAP3776c::Tn strain would be necessary to confirm these findings. Additionally, full characterization of a Fur-like protein (MAP3773c) was performed. Using PRODORIC for computational analysis, 23 different pathways that were likely regulated by MAP3773c were identified. These findings were confirmed using a chromatin immunoprecipitation assay followed by high-throughput sequencing (ChIP-seq), that revealed 58 regions where Fur binds under iron replete and deplete conditions. From those, three were directed related to iron regulation MAP3638c (hemophore- like protein), MAP3736c (Fur box) and MAP3776c (ABC transporter). Using the Fur box consensus sequence, we confirmed binding specificity and Mn2+ availability by a chemiluminescent electrophoresis mobility shift assay (EMSA). A transcriptional profile of the parent MAP K10, deletion mutant of MAP3773c and the complemented strains was developed under iron replete and depleted conditions. However, under the current experimental conditions, we are unable to conclude if the lack of transcriptional responses in our study was indicative of a lack of FUR activity. Copyright by FERNANDA MIYAGAKI SHOYAMA 2020 This dissertation is dedicated to the memory of my mom, Lourdes Hitomi Miyagaki. Thank you for all your sacrifice, for all you did for me, and all you taught me so I could become the person I am today. And to my dad Wilson Nobuaki Shoyama, Thank you for always believing in me and for always encouraging me to follow my dreams v ACKNOWLEDGEMENTS My sincerest gratitude to my mentor and friend Dr. Srinand Sreevatsan. First for believing in me as a Scientist, but the most importantly, for always challenging me to be a critical thinker. Thank you for your guidance throughout my time in your lab as a technician and as grad student, always encouraging me to keep going, especially when experiments failed. I am also thankful for all the opportunities and doors that you opened for me, always providing me ways to improve my skills as a scientist. Finally, thank you for sharing your expertise and knowledge. I would like to thank Dr. John Bannantine for having me in his laboratory at USDA, and spending time at the bench with me. In addition, I am appreciative for his numerous data discussions on the phone. I am deeply grateful to Dr. Raul Barletta for the construction of the Fur mutant, for discussions on the manuscript, and for always being available to help and support during this journey. I thank the Comparative Medicine and Integrative Biology Grad Program at Michigan State. I appreciate Dr Colleen Hegg and Dimity Palazzola for all the support. I thank the Veterinary Medicine Grad Program at the University of Minnesota. I appreciate Dr Mark Rutherford and Dr Michael Murtaugh for all the support I thank my committee members: Dr. Linda Mansfield, Dr. Paul Coussens and Dr. Rob Abramovich for their advice on my research. I also appreciate Dr. Rob Abramovitch for teaching me new techniques and opening his lab to me to help my work progress. I acknowledge all the personnel from Sreevatsan lab since Minnesota. They include Dr. Elise Lamont for teaching me mycobacterial techniques, Dr. Sylvia Wanzala for always being kind and making sure we were always calm, and Anum Hadi for being the warrior with me when we vi moved to Michigan. I especially want to thank my friend Evan P. Brenner, not only for all the science discussion and experiment brainstorming, but also for always being my partner in crime in the lab and supporting me in this crazy grad student life. I acknowledge all the funding support I received throughout my PhD, MnDrive Global Food Ventures, USDA, Veterinary Population Medicine – University of Minnesota and CMIB Program. I thank my friends that Grad School gave me, Catalina, Irene, Whitney and Elaine, for being the fun, relaxing part of the PhD. I am extremely grateful for the unwavering support, patience, and love of my boyfriend Nathanael McNabb, always showing me the best in life and how to be a better person, but most importantly, making sure that I could see the world outside the grad student life. Finally, I would like to thank ALL my family. I am 100% sure this dissertation would not have been possible without their support; my parents and my grandparents for the love and endless support on education; my second moms: Mitie, Miuki, Yumie and Kaori, no words can express what you have done for me - thank you for always being there. Thank for my sisters, Leticia and Marina, for the virtual hugs and for always being the best cheerleaders. Lastly, thank you for my best friend, Jack, that started this journey with me and made my life so much happier. In addition, thank Jack and Breezy for the pure love you have always given me. vii TABLE OF CONTENTS LIST OF TABLES ………………………………………………………….…………………… xi LIST OF FIGURES ………………………………………………………….……..…………... xii CHAPTER ONE: INTRODUCTION.......……………………….........……….………........…… 1 REFERENCES ..................................................................................................................... 4 CHAPTER TWO: LITERATURE REVIEW…………………………………....……....…….…. 7 2.1 MYCOBACTERIUM AVIUM SUBSP. PARATUBERCULOSIS (MAP)........................... 7 2.1.1. MAP INVASION AND ESTABLISHMENT ..................................................... 7 2.1.2. ECONOMIC IMPACT......................................................................................... 9 2.1.3. CONTROL STRATEGIES FOR PARATUBERCULOSIS .............................. 10 2.1.3.1 VACCINE ............................................................................................... 11 2.1.3.2 DIAGNOSTIC TESTS ............................................................................ 13 2.1.3.3 ADDITIONAL CONTROL INTERVENTIONS .................................... 14 2.2 MAP GENOME ............................................................................................................ 15 2.3 IRON IN ALL ORGANISMS ....................................................................................... 18 2.4 IRON IN MAP .............................................................................................................. 21 2.4.1. IRON-DEPENDENT REGULATOR................................................................ 22 2.4.2. FERRIC UPTAKE REGULATOR .................................................................... 23 2.5 FINAL CONSIDERATIONS........................................................................................ 25 REFERENCES ................................................................................................................... 26 CHAPTER THREE: CHARACTERIZATION OF A MAP-SPECIFIC GENOMIC ISLAND USING A MAP3776C::Tn INSERTIONAL MUTANT .............................................................. 33 3.1 ABSTRACT .................................................................................................................. 33 3.2 INTRODUCTION ........................................................................................................ 34 3.3 MATERIALS AND METHODS .................................................................................. 36 3.3.1 BACTERIAL CULTURE AND CONDITIONS ................................................ 36 3.3.2 CONSTRUCTION OF MAP COMPLEMENTATION OF THE TRANSPOSON MUTANT STRAIN ..................................................................................................... 37 3.3.3 PREPARATION OF ELECTROCOMPETENT MYCOBACTERIA ................ 38 3.3.4 EXTRACTION OF RNA AND QPCR ............................................................... 38 3.3.5 MAC-T CELL INVASION ASSAY ................................................................... 39 3.3.6 CO-CULTURE ASSAY INVASION ASSAY ................................................... 40 3.3.7 SAMPLE PROCESSING ................................................................................... 40 3.3.8 RNA-SEQUENCING.......................................................................................... 41 3.3.9 RNA-SEQ ANALYSIS....................................................................................... 42 3.4 RESULTS ..................................................................................................................... 42 3.4.1 COMPUTATIONAL CHARACTERIZATION ................................................. 42 3.4.2 COMPLEMENTATION OF MAP3776C::TN ................................................... 43 3.4.3 EX VIVO PHENOTYPE OF THE TRANSPOSON MUTANT OF MAP3776C 45 viii 3.5 DISCUSSION ............................................................................................................... 47 3.6 CONCLUSIONS AND FUTURE DIRECTIONS ........................................................ 49 REFERENCES ................................................................................................................... 51 CHAPTER FOUR: ELUCIDATING THE REGULON OF A FUR-LIKE PROTEIN IN MYCOBACTERIUM AVIUM SUBSP. PARATUBERCULOSIS (MAP) ...................................... 55 4.1 ABSTRACT .................................................................................................................. 55 4.2 INTRODUCTION ........................................................................................................ 56 4.3 MATERIALS AND METHODS .................................................................................. 58 4.3.1 BACTERIAL STRAINS ..................................................................................... 58 4.3.2 PROTEIN EXPRESSION ................................................................................... 59 4.3.3 WESTERN BLOTTING...................................................................................... 59 4.3.4 COMPUTATIONAL PREDICTION OF FUR-REGULATED GENES ........... 60 4.3.5 CHROMATIN IMMUNOPRECIPITATION FOLLOWED BY SEQUENCING (CHIP-SEQ) ................................................................................................................. 60 4.3.6 CHIP-SEQ LIBRARY CONSTRUCTION AND SEQUENCING ..................... 61 4.3.7 CHIP-SEQ DATA ANALYSIS .......................................................................... 62 4.3.8 MOTIF DETECTION.......................................................................................... 62 4.3.9 ELECTROPHORETIC MOBILITY SHIFT ASSAY (EMSA) .......................... 62 4.4 RESULTS ..................................................................................................................... 63 4.4.1 GENOME-WIDE ANALYSIS OF FUR REGULON.......................................... 63 4.4.2 FUR BINDS TO FUR BOX MOTIF UNDER IRON REPLETE OR DEPLETE CONDITION ............................................................................................................... 67 4.4.3 VALIDATION OF MAP FUR-BINDING .......................................................... 69 4.5 DISCUSSION ............................................................................................................... 70 4.6 CONCLUDING REMARK AND FUTURE DIRECTIONS ........................................ 73 REFERENCES ................................................................................................................... 78 CHAPTER FIVE: ARE TRANSCRIPTIONAL RESPONSES OF MYCOBACTERIUM AVIUM SUBSP. PARATUBERCULOSIS TO IRON AVAILABILITY MEDIATED BY THE FERRIC UPTAKE REGULATOR? ........................................................................................................... 83 5.1 ABSTRACT .................................................................................................................. 83 5.2 INTRODUCTION ........................................................................................................ 84 5.3 MATERIALS AND METHODS .................................................................................. 85 5.3.1 BACTERIAL CULTURE AND CONDITIONS ................................................ 85 5.3.2 MAP3773C MUTANT ....................................................................................... 86 5.3.3 CONSTRUCTION OF MAP COMPLEMENTATION OF MUTANT STRAIN ...................................................................................................................................... 87 5.3.4 PREPARATION OF ELECTROCOMPETENT MYCOBACTERIA ................ 88 5.3.5 RNA EXTRACTION.......................................................................................... 88 5.3.6 RNA-SEQUENCING AND ANALYSIS............................................................ 89 5.4 RESULTS ..................................................................................................................... 90 5.4.1 GENERATION OF MAP3773C DELETION BY ALLELIC EXCHANGE ..... 90 5.4.2 GENOME-WIDE TRANSCRIPTOME ANALYSIS ......................................... 92 5.5 DISCUSSION ............................................................................................................... 97 5.6 CONCLUSIONS AND FUTURE DIRECTIONS ........................................................ 99 ix REFERENCES ................................................................................................................. 101 CHAPTER SIX: CONCLUSIONS AND FUTURE DIRECTIONS .......................................... 106 REFERENCES ................................................................................................................. 110 x LIST OF TABLES Table 1. List of genes regulated by Fur under iron replete condition FDR ≤ 10-50........................ 74 Table 2. List of genes regulated by Fur under iron deplete condition FDR ≤ 10-50....................... 76 Table 3. List of genes regulated by Fur under iron replete and deplete condition FDR ≤ 10-50..... 76 Table 4. List of genes regulated by Fur under iron replete (yellow) and iron deplete (gray) condition with no function assigned FDR ≤ 10-50........................................................................................... 77 Table 5. FIMO output. Most significant Fur box motif (SRYAATGAAAATSRTTWTC) derived from ChIP-seq binding in iron-replete (yellow) and deplete (gray) conditions …........................ 77 Table 6. PCR primers used to confirm MAP3773c deletion .........................................................92 xi LIST OF FIGURES Figure 1. Sequence alignment generated by Muscle shows that MAP3773c is a divergent fur ... 42 Figure 2. Conserved domains of MAP3773c generated by NCBI …………………………......... 43 Figure 3. Representation of MAP-specific genomic island, LSP15, highlighting MAP3776c upstream position in relation to MAP3773c …………….............................................................. 43 Figure 4. 1% Agarose gel showing PCR amplification of MAP3773c ......................................... 44 Figure 5. 1% Agarose gel showing PCR amplification of MAP3776c ......................................... 44 Figure 6. Representation of psM417 map ..................................................................................... 44 Figure 7. 1% Agarose gel showing PCR amplification of MAP3776c mutant and complemented strains ............................................................................................................................................ 45 Figure 8. MAC-T cell invasion comparisons of wild type (MAP K10, MAP 1018 and MAP 7565) vs MAP3776c::Tn ......................................................................................................................... 45 Figure 9. Differentially expressed genes identified by RNA-seq based on total read counts ....................................................................................................................................................... 46 Figure 10. In silico analysis of Fur regulon …………………...................................................... 64 Figure 11. Identification of MAP Fur protein ……………………………………....................... 64 Figure 12. Scaffold analysis of LC-MS/MS .................................................................................. 65 Figure 13. Western blot of Fur protein ……………………………………….............................. 65 Figure 14. Overview of the mapped sequences within the reference genome MAP K-10 under iron replete and deplete conditions generated by CLC genomic workbench ........................................ 65 Figure 15. Applying FDR ≤ 10-50, there are three ChIP peaks associated with iron regulation .... 66 Figure 16. MAP Fur binding to the region of MAP3776c under iron replete condition ............... 67 Figure 17. MAP Fur box analysis ……………….......................................................................... 67 Figure 18. A zoom-in of the MAP Fur box 3 …………………………………........................... 67 Figure 19. The enriched region of MAP Fur binding onto Fur Box 1 and 2 identified by ChIP-seq ....................................................................................................................................................... 68 xii Figure 20. EMSA analysis of MAP Fur binding to Fur box consensus DNA .............................. 69 Figure 21. EMSA analysis of Fur – Fur box binding activity is more efficient in the presence of Mn2+ .............................................................................................................................................. 70 Figure 22. MAP Fur binding is specific to Fur box consensus ..................................................... 70 Figure 23. Generation of MAP3773c mutant, diagram of MAP3773c deletion by allelic exchange ....................................................................................................................................................... 91 Figure 24. 0.8% Agarose gel of the three fragments of MAP3773c ORF confirming deletion generated by homologous recombination ..................................................................................... 91 Figure 25. 0.8% Agarose gel of the three fragments of Hygromycin ORF confirming deletion generated by homologous recombination ..................................................................................... 92 Figure 26. Representation of alignment to the MAP K10 genome ............................................... 94 Figure 27. Transcriptional analysis by RNA-Seq with a cutoff of 95%+ of reads aligning to MAP K10 ………………………………………………………........................................................... 94 Figure 28. Heatmap of sample-to-sample distance of transformed count matrix ......................... 95 Figure 29. Principal component analysis plot of replicates by sample type ................................ 95 Figure 30. Principal component analysis plot of only wild-type replicates ................................. 96 Figure 31. Meta-analysis of the top 10 unaligned reads by BLAST ............................................. 97 xiii CHAPTER ONE: INTRODUCTION Functional characterization of iron regulation by Mycobacterium avium subsp. paratuberculosis (MAP) has revealed that MAP employs a complex protein pathway in response to iron starvation in vitro or ex vivo. Previous work demonstrated that the iron-dependent repressor protein (IdeR) not only controls mycobactin synthesis genes inside macrophages (Zhu et al., 2008) but also regulates transcription of genes involved in iron acquisition (mbtB), iron storage (bfrA) and oxidative stress (Janagama et al., 2009). While expression of the ideR regulon varies with the concentration of intrabacterial iron, there seemed to be an external metal-sensing regulator missing for iron scavenging. It is known that MAP’s genome contains 6 unique genomic islands that are absent in other mycobacteria (Alexander et al., 2009). Transcriptional analysis by our laboratory suggests that two of these large sequence polymorphisms, LSP14 and LSP15, form a major genomic island that may play a role in iron homeostasis (Janagama et al., 2010). However, it is not clear whether the genes encoded in those MAP-specific LSPs contribute to the pathogenicity of MAP (Meißner et al., 2014). In 2014, Eckelt and others confirmed that LSP14 and LSP15 are involved in metal homeostasis. Furthermore, using a transposon mutant with a disruption in the LSP15 gene MAP3776c, Behr’s group showed that when compared to the wild-type strain, the mutant demonstrated increased iron uptake as well as higher intracellular iron concentrations, indicating that LSP15 genes contribute to iron acquisition by MAP (Wang et al., 2016). Corroborating the importance of LSP15 genes during infection, the same group showed that a disruption in MAP3776c reduces bacterial fitness by 10-fold in the mouse model (Wang et al., 2014). By bioinformatic analysis, LSP15 is predicted to encode an ATP-binding cassette (ABC) 1 transporter, a metal uptake regulator and a gene that may be involved in cobalamin synthesis (Alexander et al., 2009). Previous studies in our lab showed genes LSP15 were differentially regulated in infected bovine tissues, and interestingly, MAP3773c, a predicted ferric uptake regulator (fur) protein, was downregulated in the tissues and upregulated in experimentally infected macrophages (Janagama et al., 2010). The same result was reported in the ABC transporter operon (LSP14) that contains two fur binding boxes (Stratmann et al., 2004; Janagama et al., 2010). Thus, it is already known that both LSP14 and LSP15 are involved in iron homeostasis, but there is no information on whether or not Fur contributes to this regulation. Originally described in E. coli, Fur is an iron-responsive repressor protein that controls the expression of genes for siderophore biosynthesis and iron transportation (Hantke, 1981). It has been reported that intracellular iron concentrations in many bacteria are under the control of Fur (Guerinot, 1994). During infection, in a metal-depleted environment, Fur allows for efficient acquisition of iron, leading to enhanced fitness of the pathogen (Lamont, Xu and Sreevatsan, 2013). Supporting this critical role of Fur in virulence, a deletion of fur in numerous bacterial pathogens most often resulted in partial or complete attenuation in animal models of infection. For activation of responsive genes, one Fe2+ ion per monomer enables Fur dimerization and binding to a specific 19bp DNA sequence (the “Fur box”) that obstructs RNA polymerase and subsequent transcription (Lee and Helmann, 2007). Beside Fe(II), it has been reported in B. subtilis that binding of Mn(II) and Zn(II) can also activate Fur and are effective at triggering changes needed for DNA binding. Both metals are preferred and widely used in biochemical studies as the activating cofactor, since Fe(II) requires strict anaerobic conditions (Ma, Faulkner and Helmann, 2012). It is still unknown how MAP-Fur is activated. 2 The overall objective of the studies presented in this thesis was to elucidate the mechanism of iron homeostasis in Mycobacterium avium subsp. paratuberculosis. We hypothesize that MAP3773c (Fur), a gene likely acquired by horizontal gene transfer, encodes a protein that orchestrates metabolic pathways required for optimal environmental sensing of iron, providing an alternative iron pathway. Aim 1: Determine the Ferric Uptake Regulator (Fur) regulon in Mycobacterium avium subsp. paratuberculosis. Aim 2: Identify putative functions of MAP3773c in iron homeostasis. This thesis is organized into six chapters. Chapter 2 gives a basic understanding of the importance of investigating MAP and a literature review on the involvement of iron and pathogenesis. Chapter 3 provides characterization of LSP15 and MAP3773c phenotype using a transposon mutant MAP3776c. In this chapter, in vitro assays showed potential roles of MAP3776c in MAP cell invasion and further supports the reported involvement of LSP15 in intracellular survival. Chapter 4 provides a characterization of the Fur regulon in MAP using ChIP-seq to identify the regulon under iron-replete and -depleted conditions in vitro. Sequences were analyzed using CLC Genomics Workbench 12. Confirmation of physical binding of MAP3773c to the Fur box was carried out by chemiluminescent EMSA, using a labeled Fur box and a recombinant MAP Fur-like protein. Chapter 5 provides a comparative analysis of transcriptomes from MAP K10 (wild-type), fur deletion mutant and complemented strains under metal-replete and -depleted conditions. Chapter 6 summarizes the findings presented in this thesis and proposes future studies. 3 REFERENCES 4 REFERENCES Alexander DC, Turenne CY, Behr MA. Insertion and deletion events that define the pathogen Mycobacterium avium subsp. paratuberculosis. J Bacteriol. 2009; 191(3):1018-25. DOI: 10.1128/JB.01340-08 Eckelt, E., Jarek, M., Fromke, C., Meens, J., Goethe, R. (2014) Identification of a lineage specific zinc responsive genomic island in Mycobacterium avium subspecies paratuberculosis. BMC Genomics. 15:1076. doi: 10.1186/1471-2164-15-1076 Guerinot ML. (1994). Microbial iron transport. Annual Rev. Microbiol. 48,743-772. DOI:10.1146/annurev.mi.48.100194.003523 Hantke, K. (1981). Regulation of ferric iron transport in Escherichia coli K12: isolation of a constitutive mutant. Mol Gen Genet. 182, 288-92. DOI:10.1007/bf00269672 Janagama, H.K., Lamont, E.A., George, S., Bannantine, J.P., Xu, W.W., Tu, Z.J., Wells, S.J., Schefers, J., Sreevatsan, S. (2010) Primary transcriptomes of Mycobacterium avium subsp. paratuberculosis reveal proprietary pathways in tissue and macrophages. BMC Genomics. 11, 561. doi: 10.1186/1471-2164-11-561. Janagama, H.K., Senthilkumar, T.M., Bannantine, J.P., Rodriguez, G.M., Smith, I., Paustian, M.L., McGarvey, J.A., Sreevatsan, S. (2009) Identification and functional characterization of the iron- dependent regulator (IdeR) of Mycobacterium avium subsp. paratuberculosis. Microbiology. 155, 3683-90. doi: 10.1099/mic.0.031948-0. Lamont EA, Xu WW, Sreevatsan S. Host-Mycobacterium avium subsp. paratuberculosis interactome reveals a novel iron assimilation mechanism linked to nitric oxide stress during early infection. BMC Genomics. 2013; 14:694. DOI: 10.1186/1471-2164-14-694. Lee, J.W., Helmann, J.D. Functional specialization within the Fur family of metalloregulators. Biometals. 2007; (3-4):485-99. DOI: 10.1007/s10534-006-9070-7 Li, L., Bannantine, J.P., Zhang, Q., Amonsin, A., May, B.J., Alt, D., Banerji, N., Kanjilal, S., Kapur, V. (2005) The complete genome sequence of Mycobacterium avium subspecies paratuberculosis. Proc. Natl. Acad. Sci. USA. 102,12344-12349. DOI:10.1073/pnas.0505662102 Ma, Z., Faulkner, M.J., Helmann, J.D. (2012). Origins of specificity and cross-talk in metal ion sensing by Bacillus subtilis Fur. Molecular Microbiology. 86, 1144-1155. DOI:10.1111/mmi.12049 Meißner T, Eckelt E, Basler T, Meens J, Heinzmann J, Suwandi A, Oelemann WMR, Trenkamp 5 S, Holst O, Weiss SF, Bunk B, Spröer C, Gerlach GF, Goethe R. (2014) The Mycobacterium avium ssp. paratuberculosis specific mptD gene is required for maintenance of the metabolic homeostasis necessary for full virulence in mouse. Front. Cell. Infect. Microbiol. DOI: 10.3389/fcimb.2014.00110 Rathnaiah, G., Zinniel, D.K., Bannantine J.P., Stabel, J.R., Gröhn, Y.T., Collins, M.T., Barletta, R.G. (2017) Pathogenesis, Molecular Genetics, and Genomics of Mycobacterium avium subsp. paratuberculosis, the etiologic Agent of Johne’s Disease. Front Vet Sci. 4:187. doi:10.3389/fvets.2017.00187 Stratmann, J., Strommenger, B., Goethe, R., Dohmann, K., Gerlach, G.F., Stevenson, K., Li, L., Zhang, Q., Kapur, V., Bull, T. (2004) A 38-kilobase pathogenicity island specific for Mycobacterium avium subsp. paratuberculosis encodes cell surface proteins expressed in the host. Infect. Immun. 72, 1265–1274. DOI: 10.1128/IAI.72.3.1265- 1274.2004 Wang, J., Pritchard, J.R., Kreitmann, L., Montpetit, A., Behr, M.A. (2014) Disruption of Mycobacterium avium subsp. paratuberculosis-specific gene impairs in vivo fitness. BMC Genomics. 15:415. DOI:10.1186/1471-2164-15-415 Wang, J., Moolji, J., Dufort, A., Staffa, A., Domenech, P., Reed, M.B., Behr, M.A. (2016) Iron acquisition in Mycobacterium avium subsp. paratuberculosis. J. Bacteriol. 198:857–866. DOI:10.1128/JB.00922-15 Whittington, R., Donat, K., Weber, M.F., Kelton, D., Nielsen, S.S., Eisenber, S. (2019) Control of paratuberculosis: who, why and how. A review of 48 countries. BMC Veterinary Research. 15:198. DOI:10.1186/s12917-019-1943-4 Zhu, X., Tu, Z.J., Coussens, P.M., Kapur, V., Janagama, H., Naser, S., Sreevatsan, S. (2008) Transcriptional analysis of diverse strains Mycobacterium avium subspecies paratuberculosis in primary bovine monocyte derived macrophages. Microbes and Infection. 1274-1282. DOI:10.1016/j.micinf.2008.07.025 6 CHAPTER TWO: LITERATURE REVIEW 2.1. MYCOBACTERIUM AVIUM SUBSP. PARATUBERCULOSIS (MAP) Mycobacterium avium subsp. paratuberculosis (MAP) is the causative agent of paratuberculosis, also known as Johne’s disease (JD), a chronic enteritis affecting ruminants like cattle, sheep, and goats. Advanced stages of the disease are characterized by a malabsorption syndrome that leads to diarrhea, submandibular edema, malnutrition, anemia, lethargy, muscular wasting and death (Garcia and Shalloo, 2015). MAP is shed in feces of asymptomatic sub-clinical and/or clinically infected animals, establishing infection in new hosts via the fecal-oral route (Whittington and Sergeant, 2001). Primary infections occur in utero or during calfhood by direct contact with MAP via contaminated teats, colostrum/milk, pasture, feed, soil, and water (Windsor and Whittington, 2010). Disease detection is a difficult part of JD management, as most animals remain sub-clinical for several years after infection (Rathnaiah et al., 2017). However, animals in sub-clinical stages intermittently shed MAP, ranging from fewer than 103 CFU/g of feces, to millions or billions of bacteria into the environment (Garcia and Shalloo, 2015). Visible signs of advanced disease include weight loss and decreased milk production. At necropsy, thick and inflexible intestinal sections are observed. Histopathology reveals granuloma formation in the small intestine and regional lymph nodes (Bannantine and Bermudez, 2013). 2.1.1 MAP INVASION AND ESTABLISHMENT The host’s intestinal epithelium serves as the primary barrier against MAP. Upon ingestion, MAP translocates across the intestinal mucosa via microfold cells (M cells) or enterocytes located in the Peyer’s patches of the small intestines (Bannantine and Bermudez, 2013). 7 Although both routes serve as entry for MAP, studies have shown that M cells are the primary target for MAP infection (Secott and Wu, 2004; Ponnusamy et al., 2013). This predilection can be explained by a combination of the presence of fibronectin attachment proteins (FAPs) – a family of fibronectin-binding proteins in MAP’s cell wall – and the high density of the fibronectin receptor (β1 integrins) on the luminal surface of M cells (Secott, Lin and Wu, 2001; Secott and Wu, 2004; Everman et al., 2018). Secott and others showed that when expression of FAPs was attenuated in MAP, the selective invasion into M cells was completely eliminated (Secott and Wu, 2004). Whether the route of entry has any physiological significance or impact on the outcome of the disease is still unknown (Bermudez et al., 2010). After crossing the epithelial barrier, MAP encounters dendritic cells and subepithelial macrophages (Lei et al., 2007; Bermudez et al., 2010). Coussens and others showed that MAP may use intestinal dendritic cell invasion as a strategic maneuver, since the primary function of intestinal dendritic cells is to sample and present commensal bacteria through tight junctions to the gut-associated lymphoid tissue (Coussens et al., 2010; Coussens et al., 2020). Furthermore, in the lamina propria, MAP also interacts with macrophages. Macrophages play a critical role in the host-pathogen dynamic, serving not only as a central effector for mediating the destruction of MAP, but also as a protected environment for the survival, proliferation and dissemination of MAP. Upon entry into the macrophage phagosome, MAP activates host immune response and phagosomes undergo stepwise development towards late endosomes (Arsenault et al., 2014). The end result of phagosome–lysosome fusion is the destruction of MAP and presentation of antigens to T cells via major histocompatibility complex (MHC) (Coussens et al., 2020). However, most phagosomes containing MAP fail to mature, resulting in the blockage of phagosome–lysosome fusion (Cheville et al., 2001; Brumell and Scidmore, 2007). This blockade is essential to 8 restricting recognition of the pathogen by the host, allowing MAP unabated growth and persistence (Coussens et al., 2020). In vitro experiments with infected macrophages showed a downregulation of MHC molecule expression along with greater expression of IL-10 and transforming growth factor beta (TGFβ) (Weiss and Souza, 2005). Corroborating these findings, an upregulation of inhibitory cytokines is also reported in other mycobacterial diseases, such as tuberculosis, where patients with advanced disease produced higher levels of interleukin (IL)-10 and TGFβ (Redford et al., 2011). Studies in M. tuberculosis and MAP have shown that both cytokines play an important role in limiting the bactericidal capabilities of macrophages (Redford et al., 2011; Souza et al., 2013). Obligate intracellular pathogens must avoid premature host cell death by apoptosis and necrosis to allow replication and infection of neighboring cells (Magombedze et al., 2017). Therefore, the interaction between MAP and host cell dictates disease outcome. The ability of pathogenic bacteria to overcome varied stressors imposed by the host is a major virulence determinant (Danelishvili et al., 2010; Kabara and Coussens, 2012). Thus, deep investigations into the mechanisms MAP uses to survive and overcome hostile conditions can improve our in vitro culture methods and consequently yield better diagnostics. 2.1.2 ECONOMIC IMPACT Johne’s disease (JD) causes significant direct and indirect economic impacts in the US and worldwide. A survey published in 2007 showed that 68% of the US dairy herds have at least one cow infected with MAP (NAHMS). The economic impact of JD for a farmer will be dependent on the number of animals affected, infected, infectious (shedding bacteria), presenting clinical signs or in the sub-clinical stage (Garcia and Shalloo, 2015). Culling of animals that are shedding 9 MAP is one of the most efficient JD control strategies. This can impose substantial economic losses, not only by culling of the animal, but also through the increased costs of replacements and losses of genetics in the herds (Smith et al., 2010; Whittington et al., 2019). Additionally, JD imposes compounding economic consequences, predisposing animals to clinical mastitis and increasing susceptibility for developing lameness, digestive and respiratory diseases, reducing milk production, and impairing fertility (Raizman et al., 2007; Smith et al., 2010; Garcia and Shalloo, 2015; Rossi et al., 2017). An estimate of annual economic losses from MAP infections in US dairy herds is between $21 to $79 per cow (Garcia and Shalloo, 2015). The economic production losses caused by MAP go far beyond an infected farm, as indirect losses may also occur at trade markets, either at a domestic or international level (Kennedy et al., 2017). 2.1.3 CONTROL STRATEGIES FOR PARATUBERCULOSIS Unfortunately, the impact of JD goes beyond simple economic losses. As the disease progresses, animal health and welfare deteriorate. The chronic enteritis caused by MAP is characterized by diarrhea, progressive weight loss and muscle wasting despite a good appetite and normal body temperature (Garcia and Shalloo, 2015). In addition, there is a potential for public health impacts from MAP: studies have investigated its association with Crohn’s disease and sources for human exposure to the bacterium (Waddell et al., 2016; Barkema et al., 2017). As no treatment or cure is available, an effective control strategy is needed to reduce the spread and prevalence of disease (Barkema et al., 2017). 10 2.1.3.1 VACCINE Currently, there are no approved vaccines for use against JD in the United States, although options are available in other countries. Mycopar (Boehringer Ingelheim), a whole-cell vaccine comprised of an oil suspension of heat-killed MAP strain-18, was sold until 2019. Beside failing to offer complete protection against JD, Mycopar also causes severe granulomatous inflammation at the site of injection that may become abscessed, causing major discomfort to the animal (Uzonna et al., 2003). A second vaccine, Silirum (Zoetis Animal Health), contains heat- killed MAP 316F strain and is commercialized in Australia. Studies demonstrate Silirum is able to reduce prevalence of clinical disease, but the immune responses induced by Silirum lead to cross-reactivity with tuberculin skin testing and vaccinated animals test seropositive for bovine tuberculosis (Stringer et al., 2013; APVMA, 2014). A third vaccine also produced by Zoetis is Gudair. It also contains a heat-killed 316F strain and was developed for the control of ovine Johne’s disease. In a five-year study, despite seeing declines in prevalence of JD after vaccination, sheep flocks continued to shed MAP and were at risk of spreading MAP infection (Windsor et al., 2014). A paradigm in mycobacterial vaccine development is that an attenuated strain (devoid of critical survival-associated genes) would be safe and provide protection in terms of reduced disease, shedding of MAP and protect animals from new infection. With this in mind, a consortium of MAP scientists performed a three-phase vaccine candidate evaluation that provided great insights for future vaccination development (Bannantine et al., 2014a). Using the bovine monocyte-derived macrophage (MDM) model and an apoptosis study in macrophages, in Phase I, investigators evaluated different strains of MAP carrying deletions of critical housekeeping or putative virulence genes (Bannantine et al., 2014b; Lamont et al., 2014). A total of eight mutants 11 were identified as attenuated in the ex vivo macrophage model and were enrolled in Phase II, where tissue colonization of C57/BL6 mice was evaluated in a vaccination-challenge model (Bannantine et al., 2014b). In the last phase, five candidates were evaluated for their ability to reduce fecal shedding, tissue colonization and pathology in a baby goat model. One candidate was able to lower incidence and severity of infection (Hines et al., 2014) in the baby goat model. Concluding, the authors suggested that all investigations should be done in a natural host for MAP, as mouse models do not consistently reproduce MAP infection and infected mice do not show any clinical signs (Bannantine et al., 2014a). An optimal vaccine candidate is predicted to yield better outcomes if it is designed with more than one gene deletion (Bannantine et al., 2014a). Supporting this concept, macrophage infection assays with M. tuberculosis using a double knockout mutant (fbpA/sapM) showed greater attenuation and was more immunogenic than either single knockout (fbpA and sapM) in macrophages (Saikolappan et al., 2012). In addition, the same study showed that mice vaccinated with the double knockout strain elicited a stronger immune response when compared to the single knockout strains (Saikolappan et al., 2012). In summary, there is no ideal vaccine that can completely prevent infection, and no options currently exist for US farmers. Research on vaccine development for Johne’s disease has always been a challenge due to the high costs of experiments using natural host models, lack of a good standardized animal model for JD, and incomplete understanding of the immune correlates of protection (Bannantine et al., 2014a). 12 2.1.3.2 DIAGNOSTIC TESTS Since existing vaccines are impractical as a control strategy, early diagnosis of MAP infection remains critical to curtail its spread. Unfortunately, diagnostic tests for JD are also far from perfect. In general, samples can be analyzed by microscopy, through MAP isolation in culture media, or via identification of MAP DNA by PCR. Though acid-fast staining is simple and fast, it cannot differentiate between MAP and other acid-fast bacilli, making a second confirmatory test necessary. To date, MAP isolation by culture is considered the “gold standard” test for JD; however, as explained in detail in section 4 of this chapter, MAP grows extremely slowly, taking up to 8 weeks to form colonies on solid media and 8-16 weeks to grow in liquid. Isolation of MAP in culture media is labor-intensive, time-consuming, and expensive. Additionally, fecal samples need to be decontaminated prior to inoculation of mycobacterial culture medium (Foddai et al., 2009; Rathnaiah et al., 2017). Decontamination methods for slowly growing mycobacteria aim to destroy irrelevant and usually rapidly growing microorganisms, so prolonged incubation with specific antimicrobial agents in combination with sedimentation, centrifugation or filtration of the fecal samples are common methods to isolate MAP (Whittington, 2009). Comparatively, nucleic acid detection by PCR makes direct testing of fecal samples much faster. Furthermore, improvements are constantly being made to available methods, such as for real-time, nested and TaqMan PCRs. A majority of these assays are based upon the amplification of the multicopy (n = ~17) MAP IS900 genomic element. Another multicopy gene (ISMav2) has also been used. Indirect tests are based on a host immune response having been mounted against MAP. Indirect ELISA, for example, uses antigen to screen for MAP-specific antibodies in serum or milk. Older tests include agar gel immunodiffusion (AGID) and the complement fixation test (CFT). The 13 main disadvantage of immune-based tests is that they lack specificity, and results may vary depending on the species, age, and the experimental protocol used (Whittington et al., 2017). To develop more sensitive diagnostic tests, studies have focused on the discovery of novel antigens by MAP proteomic analyses (He and De Buck, 2010). In order to identify a large fraction of potential antigen candidates in a cost-effective manner, and by making use of close phylogenetic relationships, investigators probed a commercially available whole proteome analysis microarray from M. tuberculosis with serum from MAP-infected animals in different stages of the disease (Bannantine et al., 2017). Of the 500 MAP antigens detected, 47 were identified as potential candidates for diagnosis of early stages of JD infection (Bannantine et al., 2017; Li et al., 2017). In 2019, this list was updated with the addition of 49 new reactive antigens identified by MAP protein arrays, instead of Mycobacterium tuberculosis (Mtb) arrays as in the previous study (Li et al., 2019). Furthermore, Li and others were able to detect antigens specific to different stages of the disease in addition to those expressed throughout the infection (Li et al., 2019). Thus, the use of MAP-specific antigens as a sero-diagnostic tool has been shown to increase the sensitivity and specificity of detection and could potentially also distinguish the stage of the disease. 2.1.3.3 ADDITIONAL CONTROL INTERVENTIONS Johne’s disease requires control at the population level. In addition to early detection and immediate culling of infected animals, farmers need to implement good hygienic practices to prevent MAP exposure of neonates/young animals, such as improving calving area hygiene and management of colostrum/milk feeding to avoid fecal-oral transmission (Whittington et al., 2019). 14 In sum, no single measure alone is able to reduce infection. Using a nested compartmental (NC) modeling approach, researchers have shown that a combination of test and cull with frequent manure removal was more effective than limiting contacts between calf-adult cow, raising calves in a disease-free herd, or colostrum management (Konboon et al., 2018). However, each farm needs to customize and establish cost-effective best practices within their operations for reducing MAP prevalence. Improving hygiene would not only reduce the prevalence of infectious disease, it will also improve animal health and animal welfare. 2.2. MAP GENOME Mycobacterium avium subsp. paratuberculosis is a member of the M. avium complex, which also includes M. avium subsp. avium, M. intracellulare, and M. silvaticum, with over 90% similarity at the nucleotide level but major differences in terms of host tropism, microbiological phenotypes, and pathogenicity (Motiwala et al., 2006). In 2005, Li et al. described the complete genome of MAP K10, a bovine clinical isolate, providing a strong foundation for investigations into the genetics, evolution, physiology and virulence of MAP. MAP K10 has a single, circular genome of 4,829,781 base pairs, a GC content of 69.3%, and encodes 4,350 open reading frames (ORFs). They also identified 17 copies of the insertion sequence IS900, seven copies of IS1311 and three copies of ISMav2 (Li et al., 2005). All these insertion sequences were previously described (Collins et al.,1989; Whittington et al.,1998; Strommenger et al.,2006). However, the defined coordinates of these loci in the genome allowed investigators to use them as markers for genotyping and epidemiological purposes (Dombek et al., 2000). Comparative genome analysis by Li and others identified genes that are likely involved in the pathogenesis of MAP, including multiple genes that differed between MAP and other mycobacterial species and thought to be 15 involved in virulence, metabolism, and survival (2005). One of the most significant findings was a truncation observed in mbtA, a gene known to initiate the synthesis of mycobactins (Quadri et al., 1998; Li et al., 2005). When compared to Mycobacterium avium subsp. avium (Mav) and Mycobacterium tuberculosis (Mtb), mbtA in MAP is shorter, encoding 337 residues, while Mav encoded 565-residue polypeptides and Mtb 551-residues (Li et al., 2005). All these features might be linked to MAP-specific genes and specific genetic elements like the large sequence polymorphisms (LSPs). Mycobacterial genomics studies showed that genome reduction through the loss of LSPs is a major contributor for genetic diversity (Brosch et al., 2002). Numerous LSPs have been identified by a comparative genomic approach between MAP and Mav. There are LSPs present in the former but not in the latter and vice versa (Semret et al., 2005). The MAP genome includes six specific genomic insertions: LSPP4, LSPP11, LSPP12, LSPP14, LSPP15 and LSPP16; together they comprise ~125kb and 82 ORFs (Alexander et al., 2009). All these genetic elements are known to be essential for MAP survival in vitro, increasing MAP’s fitness as a obligate pathogen (Wang et al., 2014). The genomic deletion of LSPP8 is common to all MAP strains, while other deletions are suggestive for the two major lineages of MAP: the sheep strain and the cattle strain (Alexander et al., 2009). These two lineages have been described by extensive molecular strain typing and comparative genomic studies (Bannatine et al., 2012). MAP Type I (sheep) and MAP Type II (cattle) strains were first identified by restriction endonuclease analysis and DNA hybridization from fecal samples or intestinal tissues from cattle, sheep and goats (Collins, Gabric, de Lisle 1990). A Type III strain was originally described as an intermediate strain, but the existence of the third strain was not supported by LSP analysis (Alexander et al., 2009). Due to their high 16 genetic similarity with Type I isolates, the intermediate strain has since been classified as a sub- lineage of the MAP sheep strain (Castellanos, Domingues, Aranaz 2011). Identification of LSPs specific for or deleted from MAP provided a better understanding of the evolution of this intriguing pathogenic mycobacteria. Out of the six MAP-specific genomic islands, LSP 14 and 15 are predicted to encode several metal uptake systems. Additionally, Stratmann and others described a putative 38kb MAP-specific ABC transporter operon (mpt) locus comprising six ORFs designated mptABCDEF (2004) with highest similarity to other genera of the order Actinomycetales such as Salinispora or Bifidobacter and to a lesser extent to other mycobacteria (Meißner et al., 2014). Furthermore, the 38kb MAP-specific operon is immediately preceded by two Fur boxes and located on LSP14 (Stratmann et al., 2004; Alexander et al., 2009). In addition to the mpt operon, functional genomics revealed a fep cluster encoding a protein involved in the uptake of Fe3+ and a sid cluster encoding non-ribosome- dependent heterocyclic siderophore synthases (Stratmann et al., 2004). Separated by 4.8kb from LSPP14, LSPP15 contains another putative metal transport operon and includes a Fur-like transcriptional regulator (Alexander et al., 2009). In 2016, using transposon mutagenesis, Wang and others reported that LSPP15 was a horizontally transferred genomic island. Furthermore, with bioinformatics tools and in vitro experiments, they demonstrated that LSPP15 provides an alternative iron uptake system. The complete genome sequencing of MAP-K10 and other studies that followed provided basic insights on an alternative iron uptake system for MAP survival and virulence, but much remains unknown. Future studies investigating MAP transcriptional responses to iron availability can potentially identify crucial genes involved in pathogenesis that could be considered relevant targets for vaccine development, diagnostics, or improvements to in vitro MAP culture. 17 2.3. IRON IN ALL ORGANISMS Iron is the fourth most abundant element in the Earth and it is essential for plants, bacteria, animals and humans; it is involved in critical roles like oxygen transportation by haemoglobin, energy production by electron transfer in the mitochondrial respiration process, and DNA synthesis (Lasocki, Gaillard and Rineau, 2014). Furthermore, cells employ iron as a cofactor due to its flexible coordination chemistry and redox reactivity (Wang and Pantopoulos, 2011). Existing in both ferrous (Fe2+) and ferric (Fe3+) oxidation states gives iron the ability to act as a catalyst in various biological systems (Messenger and Barclay, 1983; Frawley and Fang, 2014). However, this catalytic activity can also potentiate iron toxicity, and thus, to prevent intoxication without also inducing iron limitation, iron levels must be tightly controlled (Hood and Skaar, 2012). In mammals, more than half of the total iron is found in the form of heme, a hydrophobic Fe- based compound that is used as a prosthetic group in proteins to perform essential biochemical processes (Nuñez, Sakamoto and Soares, 2018). Containing the bulk of iron, heme groups known as hemoglobin are a main target for mammalian pathogens, followed by ferritin, transferrin and myoglobin (Ganz and Nemeth, 2015). Although iron is one of the most abundant elements on Earth, upon exposure to oxygen, iron forms insoluble oxides (Fe3+) that are unavailable for absorption (Nuñez, Sakamoto and Soares, 2018). Mammals utilize Fe2+ from their diet and through conservation and recycling mechanisms (Nuñez, Sakamoto and Soares, 2018). Iron homeostasis is achieved through uptake and recycling systems such as enterocytes and splenic macrophages, hepatocytes functioning as storage elements, and through functional cooperation of erythroid cells involved with transportation, utilization and storage of iron (Gozzelino and Arosio, 2016; Muckenthaler et al., 2017). The master regulator of iron homeostasis in mammals 18 is a peptide hormone produced by the liver known as hepcidin (HEP) (Golonka, Yeoh and Vijay- Kumar, 2019). This peptide has microbicidal properties and it is strongly induced during inflammation and infections (Michels et al, 2015). As stated before, iron levels must be tightly controlled, as disruption of its homeostasis has been shown to be responsible in numerous human pathologies. For example, decreased levels of iron and subsequent depletion of its storage result in low supplementation of iron to organs – a condition known as anemia – characterized by a lack of iron within hemoglobin (Muckenthaler et al., 2017). On the other hand, an oversupply of iron is proportional in severity to iron deficiency, and can result in damage to the liver (hemochromatosis), endocrine glands and cardiac myocytes (Michels et al., 2015). Benefiting from the necessity for fine tuning, mammals limit access to essential metals as iron, limiting infection by pathogenic organisms through a process known as nutritional immunity (Hood and Skaar, 2012). During infection, the host can activate production of the cytokine interleukin (IL)-6 to induce expression of HEP that binds to ferroportin (Fpn), the sole mammalian cellular iron exporter, expressed by macrophages and duodenal epithelial cells (Golonka, Yeoh and Vijay-Kumar, 2019). Ferroportin exports iron into plasma from absorptive enterocytes, from macrophages that recycle the iron of senescent erythrocytes, and from hepatocytes that store iron (Ganz and Nemeth 2012). When HEP-Fpn interaction happens, it induces endocytosis and lysosomal degradation of both molecules, resulting in a rapid reduction of serum iron levels, a consequence of iron being trapped within macrophages (Nemeth et al., 2004; Rodriguez et al., 2014; Rishi, Wallace and Subramaniam, 2015). Although this mechanism is effective at limiting iron for extracellular pathogens and restricting their growth, studies have shown that it can also be beneficial for intracellular pathogens like Salmonella spp., Chlamydia spp., Legionella pneumophila and Mycobacterium tuberculosis 19 (Mtb) (Collins, 2008; Golonka, Yeoh and Vijay-Kumar, 2019). In response to systemic bacterial infection, macrophages themselves produce extra hepcidin, resulting in downregulation of ferroportin, increased levels of iron and intracellular bacterial growth (Collins, 2008; Paradkar et al., 2008). Pathogens require 1011-1012-fold higher concentrations of free iron than what is physiologically available within hosts (Andrews, Robinson and Rodríguez-Quiñones, 2003). Hosts utilize iron-binding proteins like lactoferrin, transferrin and siderocalin to deplete free-iron and supply the fuel for reactive oxygen species (ROS) generation, which enhances bactericidal activity through oxidative killing (Ganz, 2012; Golonka, Yeoh and Vijay-Kumar, 2019). To subvert host nutritional immunity, bacteria express specialized iron acquisition systems using iron-binding molecules known as siderophores (Golonka, Yeoh and Vijay-Kumar, 2019). Siderophores are iron chelators produced by bacteria, fungi, and plants. For bacteria, siderophores scavenge iron from the host and return it back to the pathogen. They are divided into three categories: catecholate, trihydroxamate and mixed siderophores, and the differences between them are associated with bacterial virulence (Golonka, Yeoh and Vijay-Kumar, 2019). In mycobacteria they known as are mycobactins and exochelins, in Listeria monocytogenes they are TF-like, and in most Gram-negative bacteria called ferric enterobactins (Schaible and Kayfmann, 2004). In the battle between host and pathogen, the immune system secretes lipocalins to sequester cateocholate-type siderophores (Lcn2), blocking iron availability for bacteria (Flo et al., 2004). In mammals, neutrophils as well as the liver and gut epithelia are the main sources of Lcn2, and although it is constitutively expressed throughout the body, its levels are increased during host nutritional immunity as an antimicrobial mechanism (Bachman, Miller and Weiser, 2009). Consequently, several pathogens such as K. pneumoniae, S. aureus, S. typhimurium and E. coli 20 express Lcn2-resistant or stealth siderophores (Bachman et al., 2012; Lu et al., 2019). Thus, the interaction of bacterial siderophores and Lcn2 is one of the factors that can determine pathogen virulence. In summary, the pathogen-host interplay and competition for cellular iron requires coordination of multiple biological processes and where both sides require iron homeostasis for survival. 2.4. IRON IN MAP Iron is essential for life, and MAP is additionally well-known for its unique iron requirements for in vitro growth. Unlike other pathogenic mycobacteria, MAP requires ferric mycobactin in order to grow in culture media (Lepper and Wilks, 1988). Mycobactins are siderophores, iron-binding compounds produced by mycobacteria that are responsible for the transportation of ferric iron from host to bacteria (Barclay, Ewing and Ratledge, 1985). Most mycobacteria produce siderophores containing two salicylates divided into subgroups based on lipid solubility: lipophilic and hydrophilic (LaMarca et al., 2004). The former is the cell-associated form of mycobactin, while the latter – also known as carboxymycobactin – is excreted from the cell (Byers, 2013). Studies in M. tuberculosis showed that a group of 10 genes, mbtA-mbtJ, are responsible for the production of mycobactin and carboxymycobactins to aid in transportation of iron into bacterial cells. In vitro assays showed their expression upregulated in response to low iron conditions (McMahon, Rush and Thomas, 2012; Reddy et al., 2013). A comparative genomic analysis of the MAP K10 genome showed a truncation in the mbtA gene. This 150bp truncation in mbtA was suggested as the likely cause for the in vitro mycobactin dependency of MAP (Li et al., 2005). However, studies showed that while the MAP sheep strain does not have an mbtA truncation, it is still unable to synthesize mycobactin (Wang et al., 2016). From 21 previous studies in our lab, we know that mbt operon promoter is active and genes are transcribed by MAP inside macrophages and in tissues of infected animals, but it’s still unknown what causes mycobactin dependence in vitro (Janagama et al., 2009; Janagama et al., 2010). 2.4.1. IRON-DEPENDENT REGULATOR In MAP, the mbt operon is directly involved in iron metabolism and regulated by the iron- dependent regulator protein (IdeR) (Janagama et al., 2009). IdeR is a global regulator of iron response and belongs to the diphtheria repressor (DtxR) family of transcription regulators. In the presence of iron, IdeR binds to a 19bp promoter sequence known as “iron box,” repressing transcription of iron acquisition genes and activating genes related to iron-storage (Rodriguez et al., 2002). In Mtb, genes regulated by IdeR were putative transporters, proteins involved in siderophore synthesis and iron storage, members of the PE/PPE family, a membrane protein involved in virulence, transcriptional regulators, and enzymes involved in lipid metabolism (Rodriguez et al., 2002). IdeR in MAP (MAP2827) has 93% amino acid identity to its ortholog in Mtb. Using a DNase footprinting assay in combination with a gel shift assay, Janagama and others (2009) confirmed that in the presence of iron, MAP2827 binds to the 19bp iron box on the MAP genome, repressing transcription of mbtB, an iron acquisition protein. On the other hand, analysis of MAP bfrA, encoding an iron storage protein, showed differential iron regulation between sheep and cattle strains, with the former presenting a defective iron storage system (Janagama et al., 2009; Janagama et al., 2010). The disruption of mbtE in the MAP sheep strain might be explained as adaptation to differences in metabolic pathways used by cattle and sheep (Wang et al., 2016). Janagama et al. (2010) also reported differences in metabolic pathways used by the two strains to 22 adapt to iron limitation condition, where aconitase, succinate dehydrogenase and superoxide dismutase downregulation was observed only in the cattle strain, suggesting that an iron-sparing response, repressing the expression of iron-rich proteins when iron is limiting, was exclusive to cattle strains of MAP. 2.4.2. FERRIC UPTAKE REGULATOR Adding to the complexity surrounding mycobactin and MAP, multiple investigators have suggested the existence of an alternative iron uptake mechanism (Stratmann et al., 2004; Eckelt et al., 2014; Wang et al., 2016). The mycobacterium paratuberculosis transporter (mpt) gene cluster was the main candidate, as it encodes two predicted transporters homologous to the iron uptake transporter (IrtAB) of Mtb: mptABC and mptDEF. (Stratmann et al., 2004). The IrtAB proteins are part of the iron acquisition machinery in M. tuberculosis, are involved in transport of iron into the cell, and are required for survival and virulence in iron-deficient conditions (Rodriguez and Smith, 2006). In addition, functional genomic analysis of the mpt operon in MAP showed similarities consistent with an involvement in molecular processes involved with iron uptake (Stratmann et al., 2004). These findings, in conjunction with the presence of two putative Fur boxes on the MAP genome, strongly suggest that this operon is involved in an alternative iron uptake mechanism. The ferric uptake regulator (Fur) protein, first described in E. coli, is well-known for controlling iron metabolism, regulating defenses against oxidative stresses in most prokaryotic organisms, and is considered the master regulator of iron homeostasis (Hantke, 1981; Ma, Faulkner and Helmann, 2012). The Fur protein in E. coli is a 17kDa polypeptide that recognizes a 19bp consensus sequence known as the “fur box” (GATAATGATwATCATTATC; w = A or T) found 23 in the promoter of regulated genes, and Fur acts as a transcriptional repressor of iron-regulated promoters (Escolar, Pérez-Martín and Lorenzo, 1999). Fur genes have been well-characterized in many Gram-negative bacteria: Yersinia, Salmonella, Campylobacter, Legionella, Helicobacter pylori and also in Gram-positive bacteria like Bacillus subtilis and Staphylococcus. Additionally, Fur shares its nomenclature with a superfamily of metal sensors: Zur (zinc uptake), Mur (manganese uptake), Nur (nickel uptake), PerR (peroxide stress response), and Irr (heme- dependent iron responsive regulator) (Lee and Helmann, 2007). To date, there have been characterizations of two Fur family members in MAP: FurA and FurB, also known as Per (peroxidase stress response) and Zur (zinc uptake repressor), respectively. Furthermore, the MAP genome contains a predicted Fur-like gene, MAP3773c in LSP15, a metal transport MAP-specific operon (Alexander et al., 2009; Eckelt et al., 2014; Eckelt et al., 2015). Mycobacterial furA is located upstream of katG, a catalase-peroxidase gene, and it has been proposed that FurA is involved in mycobacterial oxidative stress survival (Zahrt et al., 2001; Eckelt et al., 2015). Using a MAP furA deletion, Eckelt and others (2015) were able to confirm the role of FurA of MAP in intracellular survival and response to oxidative stress. They also showed that FurA provides activation of genes that contribute for MAP long term survival in macrophages. The MAP genome also contains furB, producing a protein responsible for zinc homeostasis in many bacteria. Using M. smegmatis as a heterologous model and studying zinc starvation, it was demonstrated that FurB was also responsible for the regulation of 70 MAP genes, with 45 of them present in the LSP14 and LSP15 genomic islands (Eckelt et al., 2014). Despite numerous studies of metal ion sensing by Fur family proteins in bacteria, not a lot information is known for MAP. 24 2.5. FINAL CONSIDERATIONS Mycobacterium avium subsp. paratuberculosis (MAP), the causative agent of Johne’s disease (JD), imposes significant economic losses around the world to the dairy cattle industry. While culling of JD-infected cattle is necessary to control transmission to other herds, this method is problematic, and when used alone, cannot fully address JD prevention and eradication. 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Woo, S.R., Heintz, J.A., Albrecht, R., Barletta, R.G. and Czuprynski, C.J. (2007) Life and death in bovine monocytes: the fate of Mycobacterium avium subsp. paratuberculosis. Microbial Pathogenesis 43, 106–113. 32 CHAPTER THREE: CHARACTERIZATION OF A MAP-SPECIFIC GENOMIC ISLAND USING A MAP3776C::Tn INSERTIONAL MUTANT 3.1 ABSTRACT One of the unique characteristics of Mycobacterium avium subsp. paratuberculosis (MAP), the causative agent of Johne’s disease (JD), is that it requires supplementation of a siderophore, mycobactin, for optimal growth in laboratory media – a functional characteristic that has been implicated for its fastidious nature and slow growth in culture media. Prior studies have characterized the function of a mycobacterium-specific transcriptional regulator, IdeR, in iron regulation by MAP strains. A second ferric uptake regulator (Fur)-like element (MAP3773c), discovered on a MAP-specific genomic island (LSP15), is upregulated in vivo in intestinal lesions. This gene is present is a 5 gene cluster (MAP3776c-MAP3772c) that has been proposed to function as an operon. The presence of a second MAP-specific iron regulator is intriguing and needs further functional elucidation. The objective of this study was to test whether the genes on LSP15 (specifically MAP3773c) provide an alternative iron regulatory phenotype in MAP. Multiple sequence alignments of well-studied Fur proteins (E. coli and S. typhimurium) against MAP3773c revealed significant amino acid similarity and conserved “Fur” domains, suggesting that it encoded a ferric uptake regulator. Relative gene expression of LSP15 in epithelial cells alone, macrophages alone, or in co-culture revealed an up regulation of MAP3773c in epithelial cells, alone or in co-culture, suggesting a possible role for MAP3773c in cellular invasion and subsequent survival. A loss of Fur transcription was demonstrated using a transposon mutant of the MAP3776c (MAP3776c::Tn), a gene, upstream of the Fur-like element (MAP3773c) located in the same putative operon likely leading to dysfunction of all downstream genes. Infection of epithelial cell (MAC-T) and its co-culture with monocyte-derived macrophages (MDMs), 33 revealed that the transposon mutant was invasion deficient and was depleted within 48 hr after cell entry. While this data suggests a likely phenotype for LSP15 genes in in vivo and ex vivo cell entry and survival suggesting a function in epithelial cell invasion of this organism, further functional analysis with complementation of MAP3776c::Tn strain would be necessary to confirm these findings, as transposon mutants are known for their polar effect. 3.2 INTRODUCTION Johne’s disease (JD), is a chronic enteritis of ruminants caused by infection with Mycobacterium avium subsp. paratuberculosis (MAP). MAP is a gram-positive, acid-fast bacillus, with a complex impermeable waxy cell wall composed of 60% lipids, including mycolic acids (Lombard 2011; Marino et al., 2017). Transmission of JD primarily occurs by the fecal-oral route through the ingestion of contaminated feces, water, colostrum, or milk. Infection usually occurs within the first months of life of the animal and remains sub-clinical for 2-5 years. While in sub-clinical stages, infected animal can shed 103 colonies/g of feces to millions or billions of bacteria to the environment (Whittington et al., 1998). JD has a significant economic impact in the dairy herds worldwide due to increased premature culling, replacement costs, decrease of milk production, reduced slaughter values, and increased susceptibility to other disease (Garcia and Shalloo, 2015). Control of the disease is difficult, as in addition to the lack of sensitivity and specificity of the diagnostic assays, currently available vaccines do not have a high efficacy that is necessary to control JD (Bannantine et al., 2014). Thus, in order to improve control strategies, there is a need to better understand the biology of MAP. The most distinctive phenotype of MAP is its inability to produce detectable mycobactin in vivo and in vitro, requiring mycobactin, a siderophore, in 34 laboratory cultivation medium for optimal growth. Initially, it was thought that the truncation on the MAP K10 genome of mbtA was the likely cause of the mycobactin dependence in vitro (Li et al., 2005). However, even without this truncation, sheep strain of MAP is unable to produce mycobactin, furthermore, additional studies have established that mbt operon promoter is active and these genes are transcribed by MAP in macrophages and in tissues of infected animals (Zhu et al., 2008; Janagama et al., 2009; Janagama et al., 2010; Wang et al., 2016). Since the complete genome sequencing of MAP K10, functional characterization of Iron dependent repressor protein (IdeR) in MAP demonstrated that IdeR not only controls mycobactin synthesis but also regulates transcription of genes involved in iron acquisition (mbtB), iron storage (bfrA) and oxidative stress (Janagama et al., 2009). Furthermore, two MAP-specific genomic islands, large sequence polymorphisms (LSPs) 14 and 15, encode several metal uptake systems (Stratmann et al., 2004; Alexander et al., 2009). In addition, LSPs 14 and 15 carry two ferric uptake regulator (fur) boxes and a Fur-like metal-dependent transcriptional regulator (Stratmann et al., 2004; Alexander et al., 2009). Interestingly, a deep sequencing of mRNA from MAP cultures confirmed the involvement of the lineage specific gene loci LSP14 and LSP15 in metal homeostasis (Eckelt et al., 2014). Bioinformatics analysis predicted that LSP15 encoded an ATP-binding cassette (ABC) transporter (MAP3776c), a metal uptake regulator (MAP3773c) and a gene that may be involved in cobalamin synthesis (MAP3772c) (Alexander, Turenne and Behr, 2009). Additionally, a disruption in MAP3776c showed 10-fold reduction in bacterial fitness in a mouse model suggesting the likely importance of the genes in the region of LSP15 during infection (Wang et al., 2014). Furthermore, previous work has demonstrated that genes located on LSP15 are differentially regulated in naturally infected bovine tissues, and 35 interestingly, MAP3773c, a ferric uptake regulator (Fur)-like protein, was downregulated in the tissues and upregulated in experimentally infected macrophages in vitro (Janagama et al., 2010). Fur is an iron responsive repressor that controls the expression of genes for siderophore biosynthesis and iron transportation (Hantke, 1981). Furthermore, it has been reported that intracellular iron concentrations in many bacteria are under the control of Fur (Guerinot, 1994). During infection, in a metal-depleted environment, Fur allows for efficient acquisition of iron leading to optimal fitness of the pathogen (Lamont, Xu and Sreevatsan, 2013). Supporting this critical role of Fur in virulence, a deletion of Fur in numerous bacterial pathogens most often resulted in partial or complete attenuation within animal models of infection (Ma, Faulkner and Helmann, 2012). In this study we investigated the phenotype of MAP3776c using a Tn insertional mutation of MAP3776c located on LSP15. 3.3 MATERIALS AND METHODS 3.3.1 BACTERIAL CULTURE AND CONDITIONS Mycobacterium avium subsp. paratuberculosis K10 and transposon insertion mutant MAP3776c (MAP3776c::Tn) strains were grown at 37°C shaking in Middlebrook 7H9 supplemented with 10% OADC (oleic acid, dextrose, catalase) enrichment medium (Thermo Fisher Scientific, Waltham, MA, United States), 0.05% Tween 80, and 2 mg of ferric mycobactin J (Allied Monitor Inc., Fayette, MO, United States) per liter. Antibiotics (μg/ml: kanamycin, 50; hygromycin, 100) were added when necessary. Iron-depleted with Tween 80 medium was prepared using Chelex 100 resin (Bio-Rad) (10 g/liter). E. coli TOP10F cells (Invitrogen, Carlsbad, CA, United States) were grown in LB medium 37°C with shaking at 200 RPM. 36 3.3.2 CONSTRUCTION OF MAP COMPLEMENTATION OF THE TRANSPOSON MUTANT STRAIN Complementation of MAP3776c function of MAP3776c::Tn was accomplished by cloning and transformation of the mutant with MAP3776c. MAP3776c gene was amplified from MAP K10 DNA, using primers 20 pmoles each primer (fwd: GTGAACCTGATCGCCAAGAT, rev: CTCGGTCTGCGTGTTGTAGA). PCR was carried out by standard methods. Briefly, 25 ng MAP K10 genomic DNA, HotStarTaq Master Mix (Qiagen, Germantown, MD, United States). PCR product was purified using PCR purification kit (Qiagen, Germantown, MD, United States). Sanger sequencing to confirm MAP3776c PCR product was performed at the University of Minnesota – Genomics Center. The constitutive plasmid pSM417 with Hsp60 promoter was used as a vector (Kugadas et al., 2016). Double digestion of MAP3776c and psM417 was performed using enzymes Pst-1 HF and BamHI-HF (New England Biolabs, Ipswich, MA, United States) followed by Quick ligation protocol (New England BioLabs). The ligation product MAP3776c-psM417 was added into the chemically competent E. coli TOP10 (Invitrogen, Carlsbald, CA) and single colonies were selected for Sanger sequencing. Electroporation was carried out following protocol described by Goude & Parish, 2008. A total of 0.5 μg purified MAP3776c-psM417 DNA was added into 0.2 mL of electro-competent MAP3776c::Tn cells for electroporation and subject to a single pulse of 2.5 kV, 25 μF, with the pulse-controller resistance set at 1000 (ohms) resistance. Cells were recovered with 10 mL of Middlebrook 7H9 supplemented with 10% OADC (oleic acid, dextrose, catalase) enrichment medium (Thermo Fisher Scientific, Waltham, MA, United States) (M7H9-OADC) and after 16 h 37 incubation at 37° C, cells were plated into solid medium M7H9-OADC containing kanamycin (50 μg/ml) and hygromycin (100 μg/ml) until colonies became visible. Single colonies were transferred to a liquid M7H9-OADC with kanamycin (50 μg/ml) and hygromycin (100 μg/ml) and incubated at 37° C until OD600 of ~0.5 was reached. Successful integration of MAP3776c was confirmed by PCR and sequencing. The transposon mutant was kindly provided by Dr. Marcel Behr for these studies (Wang et al., 2014). 3.3.3 PREPARATION OF ELECTROCOMPETENT MYCOBACTERIA To obtain electrocompetent MAP3776c::Tn, a single colony was used to inoculate 10 mL of M7H9-OADC medium containing kanamycin (50 μg/ml) and hygromycin (100 μg/ml) and incubated at 37° C until OD600 of ~0.5 was reached. Culture was combined with 100 mL of M7H9-OADC medium and antibiotics until OD600 of ~0.5 was reached. The day before cells were harvested 2 M glycine was added. The following day, cells were washed with 10 % glycerol with gradually decreasing volumes (50, 25, 10, 5 mL) and aliquoted into 220 μL and frozen at -80°C. Procedure was carried out following protocol described by Goude & Parish, 2008. 3.3.4 EXTRACTION OF RNA AND QPCR RNA extraction of each strain – MAP K10, MAP3776c::Tn and complemented strains, was performed as described (Kugadas et al., 2016). In brief, one milliliter of bacterial culture was collected to a 2 ml sterile screw-cap microcentrifuge tube and 2 ml of TRIzol reagent (Life Technologies, Carlsbad, CA, United States) and 0.6 ml of sterile RNase-free 0.1 mm zirconium beads (BioSpect Products, Burtlesville, OK, United States) were added to tube. Cells were 38 disrupted in MagNA Lyser (Roche Diagnostics, Sandhofer, Germany) at 7.000rpm for three pulses of 50 s with 1 min intervals on ice. The supernatant was transferred to a 1.5 ml sterile RNase-free microcentrifuge tube, followed by purification using Qiagen RNeasy miniprep (Qiagen, Germantown, MD, United States). DNase treatment with Ambion TurboDNA-free kit (Thermo Fisher Scientific, Waltham, MA, United States) was done according to manufacturer’s instructions. cDNA synthesis was performed using the Superscript III First Strand Synthesis SuperMix for qRT PCR (Invitrogen, Carlsbad, CA, United States). qPCR was conducted using LightCycler 480 II (Roche, Indianapolis, IN, United States) at a volume of 25 μL (5 μL extracted cDNA in 20 μL PCR master-mix). The PCR master-mix consisted of LightCycler 480 SYBR Green 1 Master Mix (Roche, Indianapolis, IN, United States), 0.2mM of each primer. 3.3.5 MAC-T CELL INVASION ASSAY To determine virulence phenotype of the MAP3776c::Tn strain (expected knocked down MAP3773c due to an upstream insertional deletion in the putative operon), we performed cell invasion assays with bovine mammary epithelial cells (MAC-T cells). MAC-T cells were kindly provided by Dr Luiz E. Bermudez. They were used in this experiment as this cell-line is considered a surrogate for intestinal epithelial and the source of the cell line, the mammary, is hypothesized to serve as a reservoir for MAP in vivo (Patel et al., 2006). Approximately 2.0x104 MAC-T cells were seeded into three T25 flasks (3 flasks per time point) and incubated for 4 days in DMEM containing 10% FBS at 37°C in a humidified chamber at 5% CO2. Once semiconfluency was reached, MAP was added to the well to allow infection for 3hr at 37°C in a humidified chamber at 5% CO2 followed by three washings with 1x D-PBS to remove any 39 nonadherent bacteria. The cells were incubated at 37°C in a humidified chamber for up to 48 hours and further processed for CFU count. CFUs were obtained by Flow Cytometry using the LIVE/DEAD BacLight Bacterial Viability and Counting kit (Thermo Fisher Scientific, Waltham, MA, United States). 3.3.6 CO-CULTURE ASSAY INVASION ASSAY Assay was conducted using method developed by Lamont, Xu and Sreevatsan (2013). Approximately 2.0 × 104 MAC-T cells were seeded on the apical side of 3.0 μm pore size transwell (12 well plate format) (Corning, Lowell, MA, United States) and incubated in DMEM with 10% FBS for 4 days at 37°C. Once MAC-T cells were 70% confluent, bovine MDMs were seeded at ~ 2.0 × 104 cells in the basolateral chamber and allowed to adhere for 2 h at 37°C. Upon completion of incubation, cells were gently washed 3× using 1X D-PBS to remove nonadherent cells and DMEM medium containing 10% FBS was replaced. MAC-T/bovine MDMs were incubated for additional 2 d. MAC-T cells were infected for 30 min with MAP K10 (OD600 = 1.0 and MOI of 10:1). All cells were further washed as before and transwells were removed from the supports and transferred to a new sterile 12 well plate where cells were lysed and transferred to a new microcentrifuge tube for RNA extraction. 3.3.7 SAMPLE PROCESSING RNA was extracted from two biological replication, each contained twelve samples composed of 4 uninfected host cell types (Macrophage and MAC-T under single cell type or co-cultured conditions), 4 infected host cell types (Macrophage and MAC-T under single cell type or co- cultured conditions), 2 pathogen samples from macrophages and MAC-T cells under single cell 40 type culture, and 2 pathogen samples from co-cultured macrophages and MAC-T cell. Followed by extraction, RNA was submitted to enrichment and amplification for MAP transcripts using MICROBEnrich (Ambion, Austin, TX) and MessageAmpII bacteria kit (Ambion, Austin, TX) per manufacturer’s instructions. Successful elimination of host RNA was determined by the RNA 6000 LabChip kit and Agilent Bioanalyzer (Caliper Technologies Corp., Hopkinton, MA and Agilent Technologies, Santa Clara, CA). RNA integrity and purity were analyzed by RiboGreen assay per manufacturer’s instructions (Invitrogen, Carlsbad, CA) and the Agilent Nanochip (Agilent Technologies, Santa Clara, CA). All RNA samples with RNA Integrity Number (RIN) of 5 or greater were submitted for RNA-seq. 3.3.8 RNA-SEQUENCING A total of 24 samples were submitted for sequencing. The RNA-Seq library was created using the mRNA Seq library preparation kit per manufacturer’s instructions (Illumina Inc., San Diego, CA). The purified library was later validated and quantified using the Agilent High Sensitivity Chip (Agilent Technologies, Santa Clara, CA), picogreen assay (Invitrogen, Carlsbad, CA), and KAPA qPCR (KAPA Biosystems, Woburn, MA) as described by the corresponding manufacturer. The Illumina cBOT (Illumina Inc., San Diego, CA) was used for cluster generation. Briefly, the template (samples in 8-plex) was immobilized to a random oligo lawn on the flow cell surface, which was later amplified, linearized, blocked and hybridized to the sequencing primer. The clustered flow cell was then transferred and loaded into the Illumina Genome Analyzer IIx (GaIIx) (Illumina Inc., San Diego, CA). Sequencing was conducted using pair-end chemistry. Twenty million reads (200 bp insert size) and 7.5 million reads (150 bp insert size) were recorded for each bovine and MAP samples, respectively. 41 3.3.9 RNA-SEQ ANALYSIS Computational analysis was carried out on the Galaxy platform at the Minnesota Supercomputing Institute at the University of Minnesota. Bovine FASTQ files were mapped to the B. taurus genome (Btau 4.0) using TopHat (v2.02) with 2 mismatch setting. The differential gene expression (DGE) was analyzed using Cufflinks (Cuffdiff program). MAP FASTQ files were mapped to the MAP K10 genome using Bowtie with 2 mismatch and the DGE was examined using edgeR program in BioConductor. DGE was determined by a q-value cutoff of 0.05 or p-value cutoff of 0.05 as determined by Cuffdiff and edgeR. 3.4 RESULTS 3.4.1 COMPUTATIONAL CHARACTERIZATION The sequence alignment produced by Muscle, showed that when compared to the well-studied Fur proteins of other bacteria, MAP3773c carried several missense mutations, however the biochemical properties of altered amino acids were similar (Fig. 1). In addition, NCBI database showed that MAP3773c has conserved most of the functions related to the Fur protein with a helix-turn-helix motif and a metal binding and a structural Zn (II) binding site (Fig. 2). Figure 1. Sequence alignment generated by Muscle shows that MAP3773c is a divergent fur. Asterisk indicates position that has a single, fully conserved residue; colon indicates conservation between groups of strongly similar properties and period indicates conservation between groups of similar properties. 42 Figure 2. Conserved domains of MAP3773c generated by NCBI. Figure shows that gene has metal binding site and structural Zn (II) binding site and confirmed to be a Fur-like protein. 3.4.2 COMPLEMENTATION OF MAP3776C::TN For initial investigations of MAP3773c function, we used the transposon insertion mutant of MAP3776c, located in the MAP-specific genomic island, LSP15 and upstream of MAP3773c (Fig. 3). In addition, analysis with PCR showed that disruption of MAP3776c leads to a loss of MAP3773c transcription in the transposon mutant strain (Fig. 4). For complementation of the transposon mutant, MAP3776c gene from MAP K10 (Fig. 5) was cloned downstream the hsp60 promoter (Phsp60) into the constitutive plasmid psM417 to form MAP3776c-psM417 plasmid (Fig 6). Next, MAP3776c-psM417 DNA was cloned into MAP3776c::Tn and restauration of MAP3776c expression was confirmed by PCR (Fig. 7). Figure 3. Representation of MAP-specific genomic island, LSP15, highlighting MAP3776c upstream position in relation to MAP3773c. Yellow tear drop represents location of transposon mutagenesis. 43 Figure 4. 1 % Agarose gel showing PCR amplification of MAP3773c. Lane 1. 1kb ladder; Lane 2. PCR amplification of MAP3773c (280bp) from MAP K10 DNA; Lane 3. Absence of PCR amplification of MAP3773c from transposon mutant. Figure 5. 1 % Agarose gel showing PCR amplification of MAP3776c. Lane 1. 1kb ladder; Lane 2. Blank; Lane 3. PCR amplification of MAP3776c (800bp) from MAP K10 DNA. Figure 6. Representation of psM417 map. Map indicates location where plasmid was cut (Pst-1 and BamHI) for MAP3776c insertion. 44 Figure 7. 1 % Agarose gel showing PCR amplification of MAP3776c mutant and complemented strains. Lane 1. 1kb ladder; Lane 2. PCR amplification of MAP3776c (800bp) from MAP K10 DNA; Lane 3. Absence of PCR amplification of MAP3776c from transposon mutant. Lane 3. PCR amplification of MAP3776c (800bp) from complemented strain; Lane 4. 1kb ladder. 3.4.3 EX VIVO PHENOTYPE OF THE TRANSPOSON MUTANT OF MAP3776C Epithelial cell (MAC-T cells) invasion assay was carried out to investigate the phenotype of the transposon mutant MAP3776c. The efficiencies of invasion and intracellular survival were measured up to 48 h post-infection. Cells were lysed and plated for CFU counts. Comparisons of the mutant against two cattle strains (MAP K10, MAP 1018) and one sheep strain (MAP7565), indicate that the mutant was attenuated in invasion efficiency as well as deficient in survival post invasion, suggesting that the MAP-specific genomic island, LSP15, may play a role virulence of MAP (Fig. 8). Figure 8. MAC-T cell invasion comparisons of wild type (MAP K10, MAP 1018 and MAP7565) vs MAP3776c::Tn. Cells were collected at each time pointed indicated in the graphic and plated for CFU count. MAP mutant showed low invasion efficiency throughout the 48 h. 45 Next, we investigated if MAP3776c (and likely MAP3773c) was involved in macrophage recruitment during MAP K10 infection in a co-culture system with MAC-T cells and Monocyte- derived macrophages (MDMs), recreating an early infection of MAP. If MAP induced macrophage recruitment, MDMs would permeate the transwell pores into the basolateral chamber. RNA-seq was conducted on MAC-T, macrophages alone, or co-culture, with or without MAP infection. Differential gene expression (DGE) of RNA-seq data from the in vitro experiment, revealed that MAP3773c gene expression was up regulated (p < 0.05) in MAC-T cells either in the presence of macrophages or in epithelium alone when compared to the corresponding uninfected control. The co-culture system provided us the ability to study MAP- host interactions, upregulation of MAP3773c in the early stages of infection suggests a possible role of MAP3773c in transepithelial migration of MAP (Fig. 9). Figure 9. Differentially expressed genes identified by RNA-seq based on total read counts. Fold Change (log10FC) of gene expression in the LSP15 after MAP infection compared to the corresponding uninfected control, genes shown have a P < 0.05. Each bar color represents different genes on the genomic island: MAP3772c (blue); MAP3773c (orange); MAP3774c (black); MAP3776c (green). There is an up regulation of MAP3773c in the first two scenarios, suggesting a possible role of MAP3773c in MAP survival inside the epithelium. 46 Epithelium alone VersusMacrophage aloneEpithelium v/s Macrophage inco-cultureEpithelium alone v/s Epitheliumin co-cultureMacrophage alone versusMacrophage CocultureMAP3772c-1.2665209140.6357937150.1217532830.176071006MAP3773c2.048944932.9048941220.038697543-0.159801049MAP3774c0.3204551180.553603967-0.3376783360.02475353MAP3776c1.8374408251.381992589-1.0157502410.336156445-1.5-1-0.500.511.522.533.5Log (fold change) 3.5 DISCUSSION The importance of a genomic island in the evolution and diversification of bacterial genomes has been studied in different organisms such as, E. coli, S. enterica, H. pylori, M. genitalium, B subtillus, and others (Orchman, Lawrence and Groisman, 2000). If a horizontal gene transfer (HGT) between unrelated species occurred and the new genomic region is retained by the recipient, it must confer an advantage and increase the fitness for colonizing hosts (Becq, Churlaud and Deschavanne, 2010). In MAP, previous characterization of LSP15 confirmed that they were acquired via HGT and its potential role in iron regulation and infection (Alexander, Turenne and Behr, 2009; Janagama et al., 2010; Wang et al., 2014). LSP15 contains 6 genes, one of them is MAP3773c, a putative ferric uptake regulator (Fur)-like transcription regulator confirmed by in silico amino acid similarity analysis. Confirming the transcriptional knockdown of expression of MAP3773c in the MAP3776c::Tn mutant (Fig. 4) provided us an alternate approach for initial investigations of the role of Fur in MAP that can likely lead to a better understanding of iron metabolism and its possible contribution on the MAP virulence. In this present study, the disrupted strain was complemented with a copy of MAP3776c cloned under the hsp60 promoter. Although we were able to restore MAP3776c gene expression through complementation assay (Fig. 5), further investigation using in vivo and ex vivo models is necessary to ensure that the observed mutant phenotype is actually due to the loss of MAP3776c and not secondary mutations or polar effects that can be generated by the transposon (DeNicola et al., 2015). In addition, it is been suggested that hsp60 promoters offers a strong expression that results in increased levels of the targeted gene (Sakthi and Narayanan, 2013; Seniya et al., 2020). Hence, further analysis with the complemented strain or using an in-frame deletion of MAP3773c and its complemented counterpart would be necessary to conclusively establish the 47 phenotype and therefore the function of MAP3773c. Additional experiments by complementing one (MAP3776c alone) or all genes (MAP3776c-MAP3772c) in the putative operon will also need to be performed to reconfirm these findings. In vitro models to study MAP have be shown to be useful to obtain insights into the host- pathogen interactions (Patel et al., 2006). Here, using bovine mammary epithelia cells (MAC-T cells) we were able to demonstrate that lack of LSP15 impaired the ability of MAP to invade and survive inside the cells. While both cattle strains (MAP K10, MAP 1018) and the sheep strain (MAP 7565) invaded and persisted in high numbers throughout the 48 h experiment, MAP3776c::Tn appeared to be attenuated (Fig. 8). Wang and others (2014), using an in vivo mouse model, demonstrated that disruption of LSP15 lead to reduced bacterial fitness and were severely depleted after infection – corroborating our findings of ex vivo attenuation. Whether this phenotype was directly due to loss in function of MAP3776c and its downstream genes or due to polar effects needs confirmation. Using a co-culture system where MAC-T cells and Monocyte-derived macrophages (MDMs) were cultured alone or together in a transwell system, wild type MAP phenotypes were analyzed (Fig. 9). While establishing this system, we have shown that MAP’s first interaction within the host at the intestinal epithelium interface is a dynamic process that can be harnessed by the pathogen to achieve survival and dissemination within the macrophage (Lamont et al., 2013). Our data showed that there is an upregulation of MAP3773c in epithelial cells in two different conditions (alone or in coculture with MDMs) (Fig. 9). These results suggest that MAP upregulates MAP3773c in MAC-T cells in co-culture with macrophages possibly as a likely survival strategy. In addition, Fur is known to regulate expression of genes involved in survival under iron-limiting conditions, including iron acquisition systems. Thus, we propose that while 48 the host creates a hostile environment by limiting iron, MAP upregulates MAP3773c to control iron homeostasis and improve its chances of survival. This will need confirmation using an in- frame deletion mutant of MAP3773c. 3.6 CONCLUSIONS AND FUTURE DIRECTIONS In this chapter, we investigated the MAP-specific genomic island, LSP15. Our co-culture in vitro experiment recreating an early infection of MAP demonstrated that MAP3773c has a potential contribution in MAP survival inside epithelial cells. However, a deeper investigation is needed to validate these findings and determine the role of Fur in MAP infection. While using the MAP3776c::Tn provided us new insights in the MAP-iron interaction, there are several gaps that need to be addressed. The transposon mutagenesis used in this chapter was generated using the MycoMarT7 transposon, a vector that carries the highly active C9 Himar1 transposase outside the inverted repeats, resulting in a more stable mutant. However, the use of a transposon mutant is still not ideal when characterizing the function of a specific gene (Rubin et al., 1999; Sassetti et al., 2001; Wang et al., 2014). The objective of a transposon is to move from one site to the next, even though the vector is considered stable, there is still the risk of instability in the phenotype of the strain carrying the transposon-derived mutation (Paustian and Kurtz, 1994). In addition, transposons can carry transcriptional terminators, thus when its “lands” in a gene in an operon, eliminates expression of all adjacent genes, mechanism often referred as polar effect (Hutchison III et al., 2019). Furthermore, when using insertional mutagenesis there is also the damage done to the genome by the process of transposition itself as transposons are mobilized from chromosomal integration site that can result in frameshift mutations, splicing alterations or promoter disruptions (DeNicola et al., 2015). 49 A more stable approach that can be used in order to confirm findings generated with the MAP3776c::Tn, is the construction of MAP3773c mutant with in-frame deletion using allelic exchange. Through homologous recombination, the cellular DNA repair mechanism aligns a targeting vector with its corresponding region of homology and cause recombination into the chromosome, the mutation generates a “loss of function” direct to a specific locus (Hall et al., 2009). Homologous recombination takes advantage of a cell’s own DNA repair machinery to replace the targeted locus with a replacement vector containing a drug selection marker flanked by two homology arms (Hall et al., 2009). In addition to homologous recombination, another system that can be used is the CRISPRi (clustered regularly interspaced short palindromic repeats interference) is a modification of the original CRISPR/Cas9 (crisper-associated protein 9) system, designed with a goal of gene silencing instead of knockouts. To date, there are two primary CRISPRi systems developed for Mycobacterium: codon-optimized dCas9 from S. pyogenes (Choudhary et al., 2015, Singh et al., 2016) and dCas9 from S. thermophilus (Rock et al., 2017). While both systems share the advantage of being anhydrotetracycline (ATc) inducible and fully reversible at any stage, the first using the more traditional S. pyogenes Cas9 shows less robust and specific gene knockdown than the second using S. thermophilus dCas9, with two vectors to select from to minimize toxicity from protein overexpression (Rathnaiah et al., 2020). The generation of mutations by molecular techniques is a useful way of advancing our understanding of iron regulation in MAP. A MAP3773c mutant will allow us to better understand Fur interaction with the network of genes that is deployed by MAP to maintain iron homeostasis. In addition, it would be interesting to investigate how Fur and IdeR work in a coordinate way to improve MAP survival inside the hostile environment or if Fur alone can improve MAP fitness. 50 REFERENCES 51 REFERENCES Alexander, D.C., Turenne, C.Y., Behr, M.A. (2009) Insertion and deletion events that define the pathogen Mycobacterium avium subsp. paratuberculosis. J Bacteriol. 191(3):1018- 25. DOI: 10.1128/JB.01340-08 Bannantine, J.P., Hinnes II, M.E., Bermudez, L.E., Talaat, A.M., Sreevatsan, S., Stabel, J.R., Change, Y.F., Coussens, P.M., Barletta, R.G., Davis, W.C., Collins, D.M., Grohn, Y.T., Kapur, V. (2014a). 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Zhu, X., Tu, Z.J., Coussens, P.M., Kapur, V., Janagama, H., Naser, S., Sreevatsan S. (2008) Transcriptional analysis of diverse strains Mycobacterium avium subspecies paratuberculosis in primary bovine monocyte derived macrophages. Microbes and Infection. 1274-1282. doi:10.1016/j.micinf.2008.07.025 54 CHAPTER FOUR: ELUCIDATING THE REGULON OF A FUR-LIKE PROTEIN IN MYCOBACTERIUM AVIUM SUBSP. PARATUBERCULOSIS (MAP) 4.1 ABSTRACT Intracellular iron concentration is tightly regulated to maintain cell viability. Iron plays important roles in electron transport, nucleic acid synthesis and oxidative stress. A Mycobacterium avium subsp. paratuberculosis (MAP)- specific genomic island carries a putative metal transport operon that includes MAP3773c, which encodes a Fur-like protein. Although well characterized as a global regulator of iron homeostasis in multiple bacteria, the function of Fur (ferric uptake regulator) in MAP is unknown as this organism also carries, IdeR (iron dependent regulator), a native iron regulatory protein specific to mycobacteria. Computational analysis using PRODORIC identified 23 different pathways involved in respiration, metabolism and virulence that were likely regulated by MAP3773c. Thus, chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) was performed to confirm the putative regulon of MAP3773c (Fur-like protein) in MAP. ChIP-Seq revealed enriched binding to 58 regions by Fur under iron replete and deplete conditions, located mostly within open reading frames (ORF). Three ChIP peaks were identified in genes that are directly related to iron regulation: MAP3638c (hemophore-like protein), MAP3736c (Fur box) and MAP3776c (ABC transporter). A Fur box consensus sequence was identified, and binding specificity and dependence on Mn2+ availability was confirmed by a chemiluminescent electrophoresis mobility shift assay (EMSA). The results confirmed that MAP3773c is a Fur ortholog that recognizes a 19-bp DNA sequence motif (Fur box) and it is involved in metal homeostasis. This work provides a regulatory network of MAP Fur binding sites during iron replete and deplete conditions and highlights unique properties of Fur regulon in MAP. 55 4.2 INTRODUCTION Mycobacterium avium subsp. paratuberculosis (MAP) is the causative agent of Johne’s disease (JD) in ruminants, a chronic and incurable chronic enteritis characterized by persistent diarrhea that leads to malnutrition and muscular wasting (Rathnaiah et al., 2017). JD is present worldwide and imposes significant economic losses to the dairy industry. (Garcia and Shalloo, 2015). Unfortunately to date, reliable JD diagnostics are still lacking. Culture of MAP from feces has been the most reliable method for diagnosis of JD, however MAP requires eight to sixteen weeks to produce colonies in culture, presenting a major hurdle to diagnosis (Bannantine et al., 2002). Unlike other mycobacteria, MAP has special iron requirements. For optimal growth in vitro, it requires supplementation of the siderophore mycobactin J. Whole genome sequencing of MAP K10 provided a potential explanation for this dependency, revealing a truncation of the mbtA gene, with MAP making a protein that is 151-156 amino acid shorter than M. tuberculosis or M. avium (Li et al., 2005). It has been suggested that this truncation impairs the production of mycobactin from the mbtA-J operon (Li et al., 2005; Wang et al., 2014). Despite this truncation, Zhu et al. (2008) showed that MAP is still able to transcribe mycobactin synthesis genes inside macrophages. To corroborate these findings, Janagama et al., described the upregulation of several genes responsible for iron acquisition in infected tissues, including genes responsible for mycobactin biosynthesis (Janagama et al., 2010). Iron is vital to fundamental biological processes; however, high intracellular concentrations of free iron are toxic to bacteria. As such, cells have developed tightly regulated processes for intracellular metal homeostasis (Eckelt et al., 2014). Bacteria control metal homeostasis by activating a set of genes regulated by metal-sensing transcription factors known as metalloregulatory proteins (Chandrangsu et al., 2017). In prokaryotes, there are two major 56 families of metalloregulators: diphtheria toxin (DtxR), and ferric uptake regulator (Fur) (Hantke, 2001). In 2009, Janagama and others identified and characterized MAP2827, an iron-dependent regulator (IdeR) in MAP. A member of the DtxR protein family, IdeR is involved in regulatory mechanisms to acquire, store or prevent excess accumulation of iron. The authors were able to confirm that MAP2827 was in fact IdeR and regulates genes involved in iron acquisition (mbtB) and iron storage (bfrA) (Janagama et al., 2009). However, in vitro iron stress showed that IdeR regulation is strain dependent – while IdeR from MAP cattle strain K10 regulates mycobactin synthesis and storage genes similar to IdeR from M. tb, IdeR from MAP sheep strain S397 shows deficiency in iron storage function, resulting in a strain more sensitive to iron fluctuations (Janagama et al., 2010). In addition to IdeR, MAP genome contains putative metal transport MAP-specific operon, large genomic polymorphisms (LSPs) 15, that includes a Fur-like transcriptional regulator, MAP3773c (Alexander et al., 2009). First identified in E.coli, Fur has been shown to respond to iron replete conditions to repress gene expression and allow sufficient concentration of intracellular iron for essential iron related activities (Hantke, 1981; Bagg and Neilands, 1987; Lee and Helmann, 2007). Similar to several representative of Fur family member, Fur protein requires binding of a divalent metal ion, either Fe2+ or Mn2+, for DNA-binding activation (Mills and Marletta, 2005; Lee and Helmann, 2007; Chandrangsu et al., 2017). Fur protein generally binds to a 19-bp inverted repeat sequence known as a “Fur box” (GATAATGATwATCATTATC; w = A or T), within the promoter of the regulated genes (Escola, Pérez-Martin and Lorenzo, 1999). In MAP, functional genomics suggested three Fur boxes located in a 38-kb MAP-specific genomic island (LSP14) (Stratmann et al., 2004; Alexander et al., 2009). MAP genome includes a total of six specific genomic insertions: LSP4, LSP11, LSP12, LSP14, LSP15 and LSP16 (Alexander et. 57 al.,2009). As these islands are not presented in any other mycobacteria, it has been proposed and confirmed that they were acquired via horizontal gene transfer (Alexander et. al.,2009; Wang et al., 2016). Furthermore, LSP14 and LSP15 encodes several predicted genes involved in metal uptake systems. To date, different studies have characterized Fur family members in MAP: FurA and FurB, also known as Per (peroxidase stress response) and Zur (zinc uptake repressor) respectively, however no information about the potential role of MAP3773c, Fur-like element, has been described (Eckelt et al., 2014; Eckelt et al., 2015). As a key virulence determinant, iron regulation in MAP and its role in pathogen survival and infection are important areas of research that may lead to advances in ability to improve culturing methods. To further elucidate the mechanisms of iron homeostasis in MAP, we investigated the putative function of the Fur-like gene (MAP3773c) in iron homeostasis in vitro. We applied in vivo ChIP-seq to confirm binding of MAP Fur as a transcription factor and to identify the regulon of genes under its control. 4.3 MATERIAL AND METHODS 4.3.1 BACTERIAL STRAINS MAP K10 strain was grown at 37°C without shaking in Middlebrook 7H9 supplemented with 10% OADC (oleic acid, dextrose, catalase) enrichment medium (Thermo Scientific, Waltham, MA), 0.05% tween 80 and 2 mg of ferric mycobactin J (Allied Monitor Inc, Fayette, MO) per liter. Antibiotics (g/ml: kanamycin, 20; hygromycin, 100; streptomycin, 20) were added when necessary. Competent E. coli BL21(DE3) (EMD Biosciences, Madison WI) and E. coli TOP10F cells (Invitrogen, Carlsbad, CA) were grown in LB medium 37°C with shaking at 200 RPM. 58 4.3.2 PROTEIN EXPRESSION To express MAP Fur protein, competent E. coli BL21(DE3) (EMD Biosciences, Madison WI) carrying MAP3773c on pET-24b(+) were growing in LB medium with 30µg/mL kanamycin. Cultures were kept at 37°C with shaking at 200 RPM for 4 h aerobic growth, until OD600 of 0.4 was obtained. Then protein expression was induced with addition of 0.1 M IPTG and shaking at 37°C for an additional 2 h. The expressed MAP3773c was extracted using B-PER (Bacterial Protein Extraction Reagent; Pierce Biotechnology, Rockford, IL), followed by purification using HisPur Ni-NTA resin columns per manufacturer’s protocol (Pierce Biotechnology, Rockford, IL). Purified protein was analyzed by SDS-PAGE and Western Blot using standard methods described previously (Bannantine and Paustin, 2006). The target band identified from the SDS- PAGE was excised for LC-MS/MS at Michigan State University Proteomics Facilities. Raw data were analyzed using Scaffold (Proteome Software, Portland, OR). 4.3.3 WESTERN BLOTTING MAP K10 were cultured until OD600 of ~0.5 was reached. For iron starvation, cultures were treated with 2,2’-bipyridyl (DIP, 200 μM final) for 2 hours shacking at 200 rpm at 37 °C. Cells from iron replete and deplete conditions were washed with 1x PBS and resuspended in freshly made buffer lysis buffer (20 mM HEPES; 50 mM KCl; 0.5 mM DTT; 10% glycerol; mini protease inhibitor), followed by cell lysing with MagNA Lyser (Roche Diagnostic, Sandhofer, Germany). For enrichment of Fur protein, samples were subjected to immunoprecipitation. Samples were incubated overnight with antibody for Fur detection at 4 °C on a rotating platform followed by 2 hours incubation (0.5 hour at 4 °C and 1.5 hours at RT) on a rotating platform. Samples were washed 2 times with IPP150 buffer (10 mM Tris-HCl; 150 mM NaCl, 0.1% 59 NP40) and 2 times with 1x TE (0.05 M Tris-HCl; 10mM EDTA) buffer. Beads were resuspended in elution buffer and incubated at 65 °C for 15 min. The samples were subjected to SDS-PAGE and transferred to Nitrocellulose Membrane, 0.2 µm (Bio-rad Laboratories, Hercules, CA). Custom-made antibody that binds the MAP Fur protein (Genscript, Piscataway, NJ) was used as primary antibody. Anti-Rabbit IgG (whole molecule)–Peroxidase antibody produced in goat (Sigma-Aldrich, St Louis, MO) was used as secondary antibody. The membrane was visualized with ChemiDoc MP Imaging System (Bio-rad Laboratories, Hercules, CA). 4.3.4 COMPUTATIONAL PREDICTION OF FUR-REGULATED GENES Virtual Footprint, part of The Prokaryotic Database of Gene Regulation (PRODORIC) (Münch et al. 2005), was used for prediction of Fur binding site. MAP K-10 genome was used as input DNA sequence, Fur box motif from E. coli was used as Position Weight Matrix and searches were limited to -300 to + 100 bases of each predicted ORF. 4.3.5 CHROMATIN IMMUNOPRECIPITATION FOLLOWED BY SEQUENCING (CHIP- SEQ) ChIP-enriched DNA samples were performed following the protocol developed by Jaini et al. (2013) using a custom-made antibody that binds the MAP Fur protein (Genscript, Piscataway, NJ). MAP K10 culture with OD600 of ~0.5 was used to generate ChIP-DNA. In order to avoid false positive, input DNA was used as control, this sample did not have ChIP enrichment. For iron starvation, cultures were treated with 2,2’-bipyridyl (DIP, 200 μM final) for 2 hours shacking at 200 rpm at 37 °C. Cells from iron replete and deplete conditions were washed with 60 1x PBS. Formaldehyde was added at a final concentration of 1% and incubated at RT for 20 min in a platform rocker. Crosslinking was quenched by adding 250 mM of glycine and incubating for 15 min. Cells were washed two times with ice-cold 1x PBS and resuspended in freshly made lysis buffer (20 mM HEPES; 50 mM KCl; 0.5 mM DTT; 10% glycerol; mini protease inhibitor), followed by cell lysing with MagNA Lyser (Roche Diagnostic, Sandhofer, Germany). Cells suspension were sonicated using Covaris M220 Focused-ultrasonicator (Covaris, Inc., Woburn, MA) for 18 min; 75.0 peak power; 20.0 duty factor and 200 cycles/ burst. Samples were incubated overnight with antibody for Fur detection at 4 °C on a rotating platform followed by 2 hours incubation (0.5 hour at 4 °C and 1.5 hours at RT) on a rotating platform. Samples were washed 2 times with IPP150 buffer (10 mM Tris-HCl; 150 mM NaCl, 0.1% NP40) and 2 times with 1x TE (0.05 M Tris-HCl; 10mM EDTA) buffer. Beads were resuspended in elution buffer and incubated at 65 °C for 15 min. 1 mg/ml of Proteinase K was added to each sample and incubated at 37 °C for 2 hours and transferred for 65 °C for overnight incubation. The DNA purification was performed using AmPurexp beads per manufacturer’s protocol (Beckman Coulter, Indianapolis, IN). Samples quality were analyzed by an Agilent 2100 Bioanalyzer (Agilent technologies, Santa Clara, CA). 4.3.6 CHIP-SEQ LIBRARY CONSTRUCTION AND SEQUENCING DNA fragments ~300bp were selected for library preparation and sequencing libraries prepared using NEXTflextm ChIP-seq kit (PerkinElmer, Austin, TX) as per manufacturer’s protocol. Prior and post library construction, chromatin immunoprecipitation products were quantified using Qubit fluorometer (Invitrogen, Carlsbad, CA) and Agilent 2100 Bioanalyzer (Agilent technologies, Santa Clara, CA). ChIP DNA replicates were pooled and sequenced. 61 Approximately 20M reads per sample were generated, providing 150-1000 depth of coverage. Sequencing was performed by ACGT, Inc (Chicago, IL). 4.3.7 CHIP-SEQ DATA ANALYSIS All analysis was done using CLC Genomics Workbench software 12.0 (QIAGEN, Aarhus, Denmark). Raw data generated from ChIP-seq were trimmed and mapped to the reference MAP K10 genome (NCBI accession number NC_002944). Using CLC shape-based peak caller, ChIP- enriched DNA were aligned onto Input DNA (no ChIP enrichment), when the sequence coverage of a genomic region in the enriched DNA exceeded the Input DNA, a ChIP peak score was called. A list of all ChIP peaks with their respective P-value was generated. The threshold for signal to noise ratio (ChIP-enriched DNA versus no enriched) was set based on false-discovery rate (FDR) value equal or smaller than 10-50. FDR was calculated using Bonferroni correction on R software based on the P-value generated by CLC Workbench. 4.3.8 MOTIF DETECTION A Fur binding motif was generated using Find Individual Motif Occurrences (FIMO), part of the MEME suit (Grant, Bailey & Noble, 2011), for all in-vivo binding sites identified in ChIP-seq analyses. A p-value of ≤ 0.001 was defined as statistical threshold for Fur binding motifs. 4.3.9 ELECTROPHORETIC MOBILITY SHIFT ASSAY (EMSA) Physical binding of MAP3773c to the promoter sequences of MAP Fur box 1 (MAP3736c) was carried out by EMSA. Promoter sequences containing Fur box motifs were amplified using 5’ biotin-labeled primer via PCR. Purification of PCR products were done using the QIAquick PCR 62 Purification kit (Qiagen, Germantown, MD). Recombinant MAP Fur protein was expressed as stated above. Binding reaction: 1x Binding Buffer (50 mM TrisHCl; 25% Glycerol; 10 g/ml Salmon testes DNA; 250 nM NaCl; 5mM DTT; 250 g/ml BSA; nuclease free water), 10 mM MnCl2, 0-10 nM MAP Fur protein, 0-4 pmol Unlabeled DNA, 20 fmol labeled DNA. The reactions were incubated for 30 min at room temperature followed by electrophoresis in a 5% native polyacrylamide gel (40% 19:1 Acrylamide; 50% Tris-Acetate (TA) buffer; 50% glycerol; 10% Ammonium persulfate (APS); 6% TEMED) using 1x TA Buffer (1 M Tris acetate, 0.5 M Glacial acetic acid) as running buffer. After electrophoresis, gels were transferred onto a Biodyne B Nylon membrane (Pierce, Biotechnology, Rockford, IL) and reactions were detected using chemiluminescence-based nucleic acid detection kit (Pierce, Biotechnology, Rockford, IL). 4.4 RESULTS 4.4.1 GENOME-WIDE ANALYSIS OF FUR REGULON Using computational prediction, PRODORIC (Münch et al. 2005), 26 different pathways involved in respiration, metabolism and virulence were identified as likely regulated by MAP3773c (Fig. 10). To confirm the findings from the in silico analysis and determine which genes are regulated by Fur in MAP, chromatin immunoprecipitation followed by deep sequencing (ChIP-seq) was performed. A custom-synthesized anti-Fur antibody capable of detecting the MAP Fur protein in its native form in MAP K10 (Fig. 13) was used to generate ChIP binding profiles for MAP K10 cultured under iron-replete and deplete conditions (Fig. 14). ChIP peaks were called when the sequence coverage of genomic regions in the different treatments is enriched when compared to ChIP-seq control sample where the immunoprecipitation step was omitted (Strino & Lappe 63 2016). Input DNA (no ChIP enrichment), had 34,907,295 (79.02% coverage against the MAP K10 genome) uniquely-mapped reads while ChIP-enriched DNA from iron-replete and iron- deplete conditions had 22,566,602 (55.66%) and 4,299,792 (14.73%) mapped reads respectively. Figure 10. In silico analysis of Fur regulon. Using PRODORIC for MAP K10 genome analysis to detect putative Fur binding and predict pathways regulated by MAP3773c. Solid lines represent pathways directly regulated by MAP3773c. Dashed lines indicated inter-related pathways. Figure 11. Identification of MAP Fur protein. Coomassie stain of SDS-PAGE analysis of Fur expression in E. coli system. Lane 1. Protein ladder; Lane 2. BL21(DE3) carrying empty vector pET24b(+); Lane 3. BL21(DE3) carrying MAP3773c on pET24b(+); Lane 4. BL21(DE3) carrying MAP3773c on pET24b(+) with addition of IPTG; Lane 5. Purified recombinant MAP3773c protein. 64 Figure 12. Scaffold analysis of LC-MS/MS. Data from excised band from lane 5 showing peptides hits (yellow highlights) to 35% of complete MAP Fur sequence. Figure 13. Western blot of Fur protein. Data showing immunoprecipitation of Fur protein by anti-Fur antibody from MAP K-10 cultured under iron-replete and deplete condition. Lane 1. Protein ladder; Lane 2. Pull down of MAP K-10 cultured under iron-replete condition using 1 g of anti-Fur antibody; Lane 3. Pull down of MAP K-10 cultured under iron-replete condition using 2 g of anti-Fur antibody; Lane 4. Pull down of MAP K-10 cultured under iron-deplete condition using 1 g of anti-Fur antibody. Applying a P-value at ≤ 0.001, the ChIP-seq assay identified nine Fur-binding sites out of 14 previously predicted by PRODORIC. ChIP-seq analysis revealed a total of 5,381 and 4,960 binding sites of Fur protein in the MAP K10 genome (signal to noise ratio) under iron-replete and iron-deplete conditions, respectively (Fig. 14). Figure 14. Overview of the mapped sequences within the reference genome MAP K-10 under iron replete and deplete conditions generated by CLC genomic workbench. After mapped onto the reference genome, iron replete and deplete samples were compared to control (input DNA) and signal-to-noise (S/N) ratio for peak calling was generated. Fur specifically binds various genomic loci under both conditions, but most of the ChIP peaks showed higher binding sites under iron-replete condition. Arrows indicate regions where ChIP peaks are associated with iron regulation. 65 Applying a false discovery rate (FDR) at ≤ 10-50, under iron replete conditions, a total of 43 significantly enriched regions were identified on the K10 genome (Table 1). Peaks were either localized between open reading frames (ORF) (27%; intergenic regions) and within annotated genes (73%). In contrast under chelation treatment (iron-depletion), 11 enriched regions were identified (Table 2), all showing binding sites within ORFs. Four ChIP peaks were present under both iron replete and deplete conditions simultaneously (Table 3). Diverse functions are encoded by genes where Fur bound on the MAP K10 genome: cell wall synthesis, energy metabolism, respiration and transcriptional/ translation regulation. Out of 58 genes (FDR ≤ 10-50) from both conditions (Table 1, 2 and 3), 11 are annotated as hypothetical proteins, two described as pseudogenes (Table 4) and three ChIP peaks are associated with iron regulation: MAP3638c, MAP3736c and MAP3776c. Interestingly, Fur bound upstream of MAP3776c, an ABC transporter, only under iron-replete condition and binding to MAP3638c (hemophore-like protein) was identified only under iron- deplete conditions (Fig. 15 and 16). Figure 15. Applying FDR ≤ 10-50, there are three ChIP peaks associated with iron regulation. MAP Fur protein binds to the region of MAP3638c, however only under iron-deplete condition binding is statically significant with peak score of 17.4 (MAP3638c). 66 Figure 16. MAP Fur binding to the region of MAP3776c under iron replete condition. Under iron-replete condition there is a strong binding of MAP Fur to the region of MAP3776c represented by a peak score of 32.51. 4.4.2 FUR BINDS TO FUR BOX MOTIF UNDER IRON REPLETE OR DEPLETE CONDITION Fur box consensus sequence was identified in ChIP-seq data using MEME-ChIP (Fig. 17). FIMO (Find Individual Motif Occurrences) analysis identified 15 occurrences of Fur box motif (P- value ≤ 0.001), 12 of them presented under iron replete conditions and three under iron deplete condition (Table 5). Figure 17. MAP Fur box analysis. The most significant motif derived from ChIP-seq binding sequence using MEME. Height of each letter represents the relative frequency of each base at a different position in the consensus sequence. Figure 18. A zoom-in of the MAP Fur box 3. Under both iron conditions there is no binding of MAP Fur to the region of Fur box 3 (MAP3739c). ChIP peak (9.46) outside the ORF has FDR higher than the threshold of FDR ≤ 10-50. 67 Figure 19. The enriched region of MAP Fur binding onto Fur Box 1 and 2 identified by ChIP- seq. ChIP peak showed higher occupancy under iron-deplete condition in the Fur Box 1 region. S/N denotes the signal-to-noise ratio for peak calling generated by CLC software. From previous studies, it is known that the MAP K10 genome contains three Fur box motifs (Stratmann et al., 2004). However, data from ChIP-seq showed that the Fur protein does not show significant binding (FDR  10-50) to the region of Fur box 3 (MAP3739c) (Fig. 18). The highest peak score from all ChIP-seq data was observed within and just upstream of MAP3736c, located on LSP14, MAP-specific genomic island (Alexander et al., 2009). Within MAP3736c (located between nucleotides 4158368 and 4159327), there are two putative Fur Boxes: Fur box 1 (located between nt 4158681 and 4158966 of the genome), and Fur box 2 (located between nt 4159132 and 4159456) (Stratmann et al., 2004). ChIP-seq analysis showed high binding in both regions, confirming the exact location (Fig. 19). When intracellular Fe2+ was depleted by the addition of 2,2-dipyridyl, MAP Fur bound with higher affinity to Fur box 1 region (peak score = 38.57) in contrast to a lower binding score for Fur box 2 (peak score = 12.54). While under replete conditions, where MAP was grown in a complete media, the opposite was observed, a lower MAP Fur binding in the Fur box 1 region (peak score = 19.63) and a higher peak in Fur box 2 region (peak score = 33.46). 68 4.4.3 VALIDATION OF MAP FUR-BINDING To confirm binding to the Fur promoter region, biotinylated or unlabeled PCR fragment including Fur box 1 identified by ChIP-seq was amplified and subjected to an electrophoretic mobility shift assay (EMSA) using purified MAP Fur protein (Fig. 11 and 12). Titration of Fur protein in the presence of Mn2+ and 20 fmol of DNA showed that binding is dose-dependent, as the Fur concentration was increased there was an increase of binding activity (Fig. 20). However, in the absence of Mn2+, Fur binding to DNA was not as efficient as in the presence of Mn2+ (Fig. 21). Furthermore, DNA-protein complex was specific to Fur binding site, as showed in the competition assay (Fig. 22), adding different concentration of excess unlabeled Fur box 1 probe competed with and abrogated labeled Fur box 1 probe binding to Fur protein. Figure 20. EMSA analysis of MAP Fur binding to Fur box consensus DNA. Binding activity is represented by band intensity. 20 fmol of MAP DNA including the Fur Box 1 consensus biotin labeled was run in a 5% native polyacrylamide gel with different concentration of MAP Fur protein and Mn2+; Protein-DNA binding is dose-dependent: titration of purified MAP Fur protein shows an increase of binding activity as more protein is added to the system. 69 Figure 21. EMSA analysis of Fur – Fur box binding activity is more efficient in the presence of Mn2+. No addition of Mn2+ (Lane 5) binding occurs with a lower band intensity when compared to sample with Mn2+ (Lane 1-4). Figure 22. MAP Fur binding is specific to Fur box consensus. Competitive EMSA, Fur protein was incubated with either biotin-labeled DNA probe or unlabeled DNA probe or with both. Biotin- labeled probe was detected using chemiluminescent-based nucleic acid detection kit. Addition of unlabeled DNA affects binding activity, showing binding specificity. 4.5 DISCUSSION In this study, a full characterization of the Ferric Uptake Regulator in MAP was performed. Fur and its involvement in iron homeostasis is well known in bacteria such as E. coli, B. subtilis and S. Typhimurium. This protein has been shown to work as a repressor, by blocking RNA polymerase binding to the promoter region of genes involved in iron homeostasis by repressing transcription (Escolar et al., 1997); but can also work as an activator by positively regulating 70 gene expression in response to iron through indirect mechanism involving repression of small regulatory RNA (Delany et al., 2001; Masse & Gottesman 2005). The current study confirmed by Western Blot (Fig. 11) and mass spectrometry (Fig. 12) that MAP3773c encodes a Fur-like protein in MAP. A regulatory network of MAP Fur binding sites was identified using three independent approaches: 1. In-silico (PRODORIC); 2. In vivo (ChIP-seq) and 3. In vitro (EMSA). In vivo and in vitro analyses established that Fur binding was responsive to iron availability. ChIP-seq analysis expanded the number of MAP Fur binding sites, from 14 genes predicted by PRODORIC to 58 enriched binding regions (FDR ≤ 10-50). Binding locations were distributed almost evenly between intragenic and intergenic regions. While binding of Fur in intragenic regions refute the definition of a transcriptional factor (Browning and Busby, 2004), recent ChIP-seq studies with M. tuberculosis, E.coli, Salmonella and Corynebacterium reported intragenic TF binding that play critical roles in transcription and significantly affect regulation of gene expression (Knapp et al., 2015; Fitzgerald et al., 2014; Dillon et al., 2012). Additionally, during characterization of the Fur regulon in Pseudomonas syringae, Butcher and others (2011) did not observe general differences between Fur binding to intergenic and intragenic sites. Both showed comparable binding affinity in P. syringae suggesting that, although 100% of MAP Fur binding under iron-deplete conditions are located in intragenic regions, MAP Fur can be biologically active and able to bind to specific DNA sequences to control gene expression. Iron regulation by Fur in MAP appears to be more complex than the classic model, where Fur acts as a repressor when sensing high intracellular Fe2+. It then forms the Fur-Fe2+ complex and binds to the Fur box sequence, which enables Fur transition from its inactive (apo-) to its activated (holo-) form (Hantke, 2001; Helmann, 2014). Additionally, data from the present study 71 showed that MAP uses Fur in the absence of intracellular Fe2+, a process known as apo- regulation. In low iron conditions apo-Fur protein bind to the promoters of its target genes and regulates transcription (Miles et al., 2010). The complexity of Fur regulation can be exemplified in the ChIP peak of MAP3736c, where apo- Fur binds to Fur box 1 under iron-deplete conditions and holo-Fur binds to Fur box 1 and 2 under iron-replete condition. The physiological significance of apo-Fur binding in MAP is unclear, however previous studies with H. pylori showed that when iron levels are low, genes responsible for iron storage are repressed by apo-Fur (Bereswill et al., 2000). Furthermore, additional studies in C. jejuni showed that gene expression controlled by Fur was decreased in the wild type strain under iron depleted condition and, in a Fur knockout strain, expression was increased (Holmes et al., 2005), indicating that apo-Fur plays an important role in iron metabolism. Corroborating this result, ChIP-seq analysis identified apo-Fur binding to MAP3638c, only under iron starvation. MAP3638c is a hemophore-like protein, suggesting that MAP likely uses heme as an additional iron source as previously described in M. tuberculosis (Tullius et al., 2011). Finally, to confirm and validate Fur-Fur box1 binding, an EMSA using PCR amplification of ChIP-seq-identified Fur box 1 and purified Fur-like protein (MAP3773c) was performed. The binding was dependent on the availability of Mn2+, a common surrogate metal which, unlike Fe2+, is stable in the presence of oxygen but promotes DNA binding and adopts the same coordination geometry as Fe2+ (Butcher et al., 2011). Additionally, a competitive gel shift assay confirmed specificity of MAP Fur binding to the Fur box 1 region. Taken together, the identification of consensus Fur box by ChIP-seq peaks combined with data from EMSA, confirms that iron regulation in MAP is also mediated by a Fur homolog that recognizes the 19bp DNA sequence, known as the Fur box. 72 In this current study, we were not able to confirm Fur box 3 (MAP3739c) region as a binding site for Fur protein as described by Stratmann and others (2004). Computational methods as used by the group predicted binding sites relying on data available 15 years ago, which was likely incomplete. Further, most computational predictions of transcription factors binding are prone to false discovery and need to be validated (Karimzadeh and Hoffman, 2018). By using directly and quantitatively sequencing in combination with specific antibody, as used in this currently study, ChIP-seq method provides a powerful strategy for identifying in vivo binding sites across the entire genome (Collas, 2019). 4.6 CONCLUDING REMARK AND FUTURE DIRECTIONS In this work, we characterized MAP3773c, the ferric uptake regulator in MAP, using ChIP-seq. A genomic view of the MAP Fur regulatory network was identified, and several putative binding sites involved during iron replete and deplete conditions were discovered. Although this study is not a full description of the Fur regulon, our findings indicate that MAP Fur is a global regulator that recognizes many target sites in the genome, either by apo- or holo- Fur. Further analysis of the complete MAP Fur regulon will combine ChIP-seq data analysis from this work with another genome-scale experiment will provide a full understanding of direct or indirect roles of Fur in response to iron availability. To have a complete understanding of the MAP iron stimulon model, future studies will involve the basic understanding of Fur-IdeR interactions and how one or the other may be functional in MAP under a variety of in vivo and environmental conditions. 73 Table 1. List of genes regulated by Fur under iron replete condition FDR ≤ 10-50. Gene MAP3776c Peak score 32.51 FDR.bonf 4.18E-228 MAP1134 23.71 1.61E-120 MAP4122 MAP2627c MAP1398 MAP1129 MAP3230c rpmG MAP2419 MAP2389c aroA MAP2370c MAP2011 MAP0130 MAP2640c 22.29 22.09 21.41 20.53 20.50 19.86 19.61 19.59 19.51 19.25 19.23 19.20 18.84 2.41E-106 2.16E-104 5.37E-98 5.64E-90 1.04E-89 4.49E-84 7.04E-82 1.03E-81 4.62E-81 7.14E-79 1.12E-78 1.93E-78 1.86E-75 MAP2620c 18.73 1.56E-74 MAP1360 18.70 2.47E-74 MAP2969c MAP0351 MAP3430 MAP2173c MAP2465c MAP0636 MAP2744c MAP0867c 18.65 18.64 18.53 18.46 18.36 18.19 17.74 17.61 6.83E-74 7.32E-74 6.66E-73 2.42E-72 1.50E-71 3.12E-70 1.03E-66 9.82E-66 function ABC transporter ATP- binding protein 16S rRNA m5C967 methyltransferase hypothetical protein hypothetical protein hypothetical protein lysoplasmalogenase AraC family transcriptional regulator 50S ribosomal protein L33 membrane protein amidohydrolase 3-phosphoshikimate 1- carboxyvinyltransferase short-chain dehydrogenase hypothetical protein ATP-binding protein CPBP family intramembrane metalloprotease nitrate reductase subunit alpha phenylalanine--tRNA ligase subunit beta hypothetical protein transcriptional regulator phosphomannomutase pseudo hypothetical protein CPBP family intramembrane metalloprotease catalase-related peroxidase LLM class F420-dependent oxidoreductase P-value 4.04E-232 1.55E-124 2.33E-110 2.09E-108 5.19E-102 5.46E-94 1.00E-93 4.34E-88 6.81E-86 9.96E-86 4.47E-85 6.90E-83 1.08E-82 1.87E-82 1.80E-79 1.51E-78 2.39E-78 6.61E-78 7.07E-78 6.44E-77 2.34E-76 1.45E-75 3.02E-74 9.97E-71 9.50E-70 74 16S rRNA (guanine(966)- N(2))-methyltransferase RsmD ANTAR domain-containing protein pyridoxamine 5'-phosphate oxidase membrane protein enoyl-CoA hydratase/isomerase family protein potassium transporter TrkA ribosome small subunit- dependent GTPase A pseudo long-chain-fatty-acid--CoA ligase lactate 2-monooxygenase esterase 1,4-alpha-glucan-branching protein short-chain dehydrogenase/reductase hypothetical protein 2,5-diketo-D-gluconic acid reductase nucleoside triphosphate pyrophosphohydrolase methylmalonyl Co-A mutase-associated GTPase MeaB hypothetical protein 1.35E-69 1.22E-68 7.77E-68 3.32E-67 4.51E-66 7.16E-66 7.81E-66 1.77E-63 4.76E-63 2.15E-61 2.32E-61 4.41E-61 3.10E-60 1.49E-58 4.21E-57 1.14E-56 6.61E-55 1.04E-54 Table 1 (cont’d) rsmD 17.59 1.40E-65 MAP_RS19330 17.47 1.27E-64 MAP2411 17.36 8.04E-64 MAP0357 MAP2395c MAP2479 rsgA MAP3477 MAP2747 MAP3486 MAP1560 MAP3063 17.28 17.13 17.10 17.10 16.78 16.72 16.49 16.49 16.45 3.43E-63 4.66E-62 7.40E-62 8.08E-62 1.83E-59 4.92E-59 2.23E-57 2.40E-57 4.56E-57 MAP3015 16.33 3.20E-56 MAP1161 dkgA 16.09 15.88 1.54E-54 4.35E-53 MAP0988 15.82 1.18E-52 MAP1227 15.56 6.84E-51 MAP3488c 15.53 1.08E-50 75 Table 2. List of genes regulated by Fur under iron deplete condition FDR ≤ 10-50. Gene Peak score MAP_RS1248 0 MAP3664 rrf MAP3638 MAP0182c MAP2957 MAP_RS1248 0 MAP3471c MAP_RS1458 5 MAP2961c MAP1420 19.48 18.75 18.04 17.74 16.39 16.15 16.11 15.79 15.51 15.50 15.44 FDR.bon f 7.85E-81 1.04E-74 4.50E-69 1.03E-66 1.25E-56 6.05E-55 1.17E-54 Function 23S ribosomal RNA glycosyl transferase 5S ribosomal RNA hemophore hypothetical protein peptidase M23 23S ribosomal RNA 1.76E-52 1.61E-50 hypothetical protein hypothetical protein P-value 7.59E-85 1.01E-78 4.35E-73 9.92E-71 1.20E-60 5.85E-59 1.13E-58 1.70E-56 1.56E-54 1.68E-50 DNA-protecting protein DprA 4.45E-50 non-ribosomal peptide synthetase 1.63E-54 4.30E-54 Table 3. List of genes regulated by Fur under iron replete and deplete condition FDR ≤ 10-50. n o i t c n u F e n e G MAP3736c ABC transporter ATP-binding protein MAP2381 acetoin dehydrogenase MAP2071c cyclohexanecarboxylate-CoA ligase MAP2840c diaminopimelate epimerase Peak score Replete Deplete Replete 38.74 33.46 FDR. Bonferroni 0.00 Deplete 9.02E-242 26.50 26.02 5.07E-151 1.70E-145 17.59 21.33 1.49E-65 3.10E-97 19.99 16.79 3.42E-85 1.39E-59 76 Table 4. List of genes regulated by Fur under iron replete (yellow) and iron deplete (gray) condition with no function assigned FDR ≤ 10-50. Gene MAP4122 MAP2627c MAP1398 MAP2011 MAP2969c MAP2173c MAP2465c MAP3477 MAP1161 MAP3488c MAP0182c MAP3471c MAP_RS1458 5 Peak score 22.29 22.09 21.41 19.23 18.65 18.46 18.36 16.78 16.09 15.53 16.39 15.79 15.51 FDR.bonf Binding location 2.41E-106 2.16E-104 5.37E-98 1.12E-78 6.83E-74 2.42E-72 1.50E-71 1.83E-59 1.54E-54 1.08E-50 1.25E-56 1.76E-52 1.61E-50 intragenic intergenic intergenic intragenic intragenic intragenic intragenic intragenic intragenic intergenic intragenic intragenic intragenic Function P-value hypothetical protein hypothetical protein hypothetical protein hypothetical protein hypothetical protein pseudo hypothetical protein pseudo hypothetical protein hypothetical protein hypothetical protein hypothetical protein hypothetical protein 2.33E-110 2.09E-108 5.19E-102 1.08E-82 6.61E-78 2.34E-76 1.45E-75 1.77E-63 1.49E-58 1.04E-54 1.20E-60 1.70E-56 1.56E-54 Table 5. FIMO output. Most significant Fur box motif (SRYAATGAAAATSRTTWTC) derived from ChIP-seq binding in iron-replete (yellow) and deplete (gray) conditions. Start 4158881 4216788 4213755 3880225 3880225 4213810 4219972 1029910 3341431 2676939 2718950 3880219 4071822 2752597 4158881 End 4158899 4216806 4213773 3880243 3880243 4213828 4219990 1029928 3341449 2676957 2718968 3880237 4071840 2752615 4158899 Strand + - + + - + - + - + - + + + + Gene Binding sequence GATAATGAAAATCGTTATC MAP3736c GTTAATGAAAATGATTATC MAP3772c CTTATTGAAAATGATTTTC MAP3770 GATAACGATAATCATTTTC MAP3490 GAAAATGATTATCGTTATC MAP3489c CGAGATGAAAATGATTCCC MAP3770 AGATATGAAAACGGTTATC MAP3776c GACGCTGAAAGTGCTTTGC MAP0988 GGTGACGAAAGTGGTTCTG MAP3004c GGTGATGACCAACGTTCCC MAP2382 CACAGGGAAATTGGTCCTG MAP2420c GCTGCTGATAACGATAATC MAP3490 CACCGCGAAAAGCGTTGTG MAP3665c CACACCGCAAAAGCTTTCC MAP2451c GATAATGAAAATCGTTATC MAP3736c 77 REFERENCES 78 REFERENCES Alexander, D.C., Turenne, C.Y., Behr, M.A. (2009) Insertion and deletion events that define the pathogen Mycobacterium avium subsp. paratuberculosis. J Bacteriol. 191(3):1018- 25. DOI: 10.1128/JB.01340-08 Bagg, A., and Neilands, J.B. 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Microbes and Infection. 1274-1282. doi:10.1016/j.micinf.2008.07.025 82 CHAPTER FIVE: ARE TRANSCRIPTIONAL RESPONSES OF MYCOBACTERIUM AVIUM SUBSP. PARATUBERCULOSIS TO IRON AVAILABILITY MEDIATED BY THE FERRIC UPTAKE REGULATOR? 5.1 ABSTRACT Mycobacterium avium subsp. paratuberculosis (MAP) requires supplementation of the siderophore mycobactin J for optimal growth in culture media. Recent studies characterized a Fur ortholog (MAP3773c) that recognizes a 19bp consensus Fur box in a metal-dependent manner. Furthermore, ChIP-seq analysis identified putative Fur binding sites on the MAP genome under iron replete and deplete conditions. In this study, we sought to determine transcriptomes of Mycobacterium avium subsp. paratuberculosis. An in-frame deletion of MAP3773c was accomplished using homologous recombination and genome-wide transcriptional differences were examined between parent, mutant, and complemented strains, under either iron-replete or -deplete conditions. In-frame deletion of MAP3773c was confirmed by PCR and sequencing. RNA samples with RNA integrity number greater than 7 were selected for RNA-Seq. Six biological replicates from each strain and condition were sequenced (n = 36 samples). Using a cutoff of 95% or more of reads aligning to the MAP K10 reference genome, 15 samples were then used for transcriptional profiling. Bioinformatic analysis showed no statistically significant differences in gene expression profiles between strains and iron conditions, but this may have been due to limited statistical power after dropping samples below the cutoff rather than a true lack of differences. While these transcriptional differences were not informative, the ChIP-seq data and the multiple networks linked to iron metabolism still suggest FurMAP likely plays a role in some cell stress responses. Additional work is needed to establish the regulation of FurMAP and understand its involvement in MAP survival and virulence. 83 5.2 INTRODUCTION Bacteria need ferrous iron for most of metabolic processes and basic survival. Pathogenic mycobacteria are no exception, and they experience a variety of additional stressors inside host cells, and their ability to maintain iron homeostasis under stress represents a major virulence determinant (Rodriguez and Smith, 2003). In mycobacteria, specialized iron-acquisition systems known as mycobactins are produced by a group of genes comprised of mbtA-mbtJ (McMahon, Rush and Thomas, 2012; Golonka, Yeoh and Vijay-Kumar, 2019). In Mycobacterium avium subsp. paratuberculosis (MAP), the mbt operon is directly involved in iron metabolism and regulated by the iron-dependent repressor protein (IdeR) (Janagama et al., 2009). In addition to IdeR, multiple investigators have suggested the existence of an alternative iron uptake mechanism (Stratmann et al., 2004; Eckelt et al., 2014; Wang et al., 2016). Located in the putative metal transport MAP-specific operon – large genomic polymorphism (LSP) 15 – is MAP3773c (Alexander et. al., 2009). In a recent study, we cloned, purified and performed full characterization of MAP3773c, confirming that it encodes a ferric uptake regulator (Fur) ortholog that recognizes a 19-bp DNA sequence motif (Fur box), and that it is involved in metal homeostasis (Shoyama et al., 2020). The transcriptional regulator Fur is well-known in other bacteria for controlling iron metabolism, regulating defenses against oxidative stress, and is considered the master regulator of iron homeostasis (Hantke, 1981; Ma, Faulkner and Helmann, 2012). In general, in an iron-replete environment, Fur binds to intracellular Fe2+ and forms the Fur–Fe2+ complex, transitioning Fur from its inactive (apo-) to its activated (holo-) form that recognizes the Fur box sequence (Hantke, 2001). This process results in the transcription repression of most its regulon by blocking the entry of RNA polymerase to the promoter region (Hantke, 2001). However, some studies have shown that Fur can also function as an activator of 84 gene expression (Pi and Helmann, 2018). Through an indirect mechanism mediated by a small regulatory RNA known as RhyB, Fur was demonstrated to positively regulate a set of genes that encode iron-containing proteins in E. coli, including ferritins, a superoxide dismutase, and some genes in the tricarboxylic acid (TCA) cycle (Masse and Gottesman, 2002). Furthermore, in Neisseria meningitidis, investigators showed that when Fur binds to operators located upstream of three promoters regulated by Fur and iron, it results in activation of transcription (Delany, Rappuoli and Scarlato, 2004). In contrast, when the binding site overlaps the promoter region, Fur triggers repression (Delany, Rappuoli and Scarlato, 2004). Whether Fur in Mycobacterium avium subsp. paratuberculosis (MAP) acts as an activator or repressor is still unknown. ChIP-seq analysis identified several putative binding sites and genes involved in iron homeostasis in MAP; in addition, MAP Fur was confirmed as a global regulator that recognizes many target sites in the genome, either under iron-replete or deplete conditions (Shoyama et al., 2020). In this study, we sought to determine transcription alterations regulated by FurMAP in response to iron limitation by RNA-Seq. We constructed an in-frame Fur mutant of MAP strain K10 through homologous recombination, and a complementation strain of this mutant background transformed with a Fur-bearing plasmid to help identify genes that were exclusively regulated by Fur. 5.3 MATERIALS AND METHODS 5.3.1 BACTERIAL CULTURE AND CONDITIONS Mycobacterium avium subsp. paratuberculosis K10, mutant MAP3773c (MAP3773c) and complemented strains were grown at 37°C shaking in Middlebrook 7H9 supplemented with 10% OADC (oleic acid, dextrose, catalase) enrichment medium (Thermo Fisher Scientific, Waltham, MA, United States), 0.05% Tween 80, and 2mg/L of ferric mycobactin J (Allied Monitor Inc., 85 Fayette, MO, United States). Antibiotics – 50μg/mL kanamycin, or 150μg/mL hygromycin – were added when necessary. E. coli TOP10F cells (Invitrogen, Carlsbad, CA, United States) were grown in LB medium 37°C with shaking at 200 RPM. 5.3.2 MAP3773C MUTANT The DNA sequence of MAP3773c was downloaded from the KEGG MAP genome site (http://www.genome.jp/dbget-bin/www_bget?mpa:MAP_3773c) and primers were designed to amplify the upstream region including 84bp of MAP3773c (MAP3773c UPS fwd: GCCTCGGTACCTGCCTCGGTCAATCCGGTAG; rev: CTCTCTAGAGTTCTCTTGCGCTCGCAGCAC) and a second set for the downstream region including 111bp of the MAP3773c coding C-terminus region (MAP3773c DWN fwd: CTCAAGCTTCGGCTAAGCCGCCAACATCA; REV: CTCCTCGAGCAAGTAGGTCGGCAATCGTG). The PCR product of MAP3773c UPS was cloned into the cosmid vector pYUB854 carrying hygromycin resistance (Bardarov et al., 2002). The PCR product of MAP3773c DWN was cloned into the resulting plasmid MAP3773c UPS+pYUB854, generating the recombinant cosmid pBUN445. This plasmid was cloned into the conditionally replicating shuttle phasmid vector phAE87. pBUN445+phAE87 was transfected to M. smegmatis MC2 155 and plated for phage plaques (mycobacteriophage) at 30C. Mycobacteriophage were electroporated into MAP cells and plated on selective media containing 150μg/mL hygromycin and incubated at 37C. 86 5.3.3 CONSTRUCTION OF MAP COMPLEMENTATION OF MUTANT STRAIN Complementation of the MAP3773c mutant was accomplished by cloning and transformation of the mutant with MAP3773c on a plasmid (pSM417). The MAP3773c gene was amplified using 20pmol of each primer (fwd: GTGAACCTGATCGCCAAGAT, rev: CTCGGTCTGCGTGTTGTAGA). PCR was carried out by standard methods with 25ng MAP K10 genomic DNA, HotStarTaq Master Mix (Qiagen, Germantown, MD, United States). PCR product was purified using PCR purification kit (Qiagen, Germantown, MD, United States). Sanger sequencing to confirm amplification of MAP3773c was performed at Michigan State University Genomics Core. The constitutive plasmid pSM417 with hsp60 promoter was used as a vector (Kugadas et al., 2016). Double digestion of MAP3773c and pSM417 was performed using enzymes PstI-HF and BamHI-HF (New England Biolabs, Ipswich, MA, United States) followed by quick ligation protocol (New England Biolabs). The ligation product MAP3776c- psM417 was added into the chemically competent E. coli TOP10 (Invitrogen, Carlsbald, CA) and single colonies were selected for Sanger sequencing. Electroporation was carried out following protocol described by Goude & Parish, 2008. A total of 0.5μg purified MAP3773c-pSM417 DNA was added into 0.2mL of electrocompetent MAP3776c::Tn cells for electroporation and subject to a single pulse of 2.5kV, 25μF, with the pulse-controller resistance set at 1000Ω. Cells were recovered with 10mL of Middlebrook 7H9 supplemented with 10% OADC (oleic acid, dextrose, catalase) enrichment medium (Thermo Fisher Scientific, Waltham, MA, United States) (M7H9-OADC) and after 16h incubation at 37°C, cells were plated on solid M7H9-OADC containing kanamycin (50μg/mL) and hygromycin (100μg/mL) until colonies became visible. 87 Single colonies were transferred to liquid M7H9-OADC with kanamycin (50μg/mL) and hygromycin (100μg/mL) and incubated at 37°C until OD600 of ~0.5 was reached. Successful integration of MAP3773c was confirmed by PCR and sequencing. 5.3.4 PREPARATION OF ELECTROCOMPETENT MYCOBACTERIA To obtain an electrocompetent MAP3773c mutant, procedures were carried out following protocols described by Goude & Parish, 2008. In summary, a single colony was used to inoculate 10mL of M7H9-OADC medium containing kanamycin (50μg/mL) and hygromycin (100μg/mL) and incubated at 37°C until OD600 of ~0.5 was reached. Culture was combined with 100mL of M7H9-OADC medium and antibiotics until OD600 of ~0.5 was reached. The day before cells were harvested, glycine was added to a final concentration of 2M. The following day, cells were washed with gradually decreasing volumes (50, 25, 10, 5mL) of 10% glycerol and 220μL was aliquoted and frozen at -80°C. 5.3.5 RNA EXTRACTION RNA extraction of each strain – MAP K10, MAP3773c mutant and complemented strain – was performed following a protocol developed by Rhode et al. (2007) with modifications. Five mL of bacterial culture with OD600 of ~0.5 was used. Iron starvation was accomplished by treating cultures with 2,2’-bipyridyl (DIP, 200μM final) for 2 hours shaking at 200rpm at 37°C (Thompson et al., 2002; Eckelt et al., 2014). Cells from iron-replete and -deplete conditions were washed with 1x PBS. GTC buffer (4M guanidine thiocyanate, 0.5% sodium N-lauryl sarcosine, 25mM sodium citrate (pH 7.00) and 0.1M beta-mercaptoethanol) was added to each sample followed by centrifugation at room temperature for 3500 x g for 10 min. Cells were resuspended 88 in 1mL of GTC buffer and transferred to a 1.7mL microcentrifuge tube. Cells were washed two times with 1mL PBS + 0.1% Tween80 and centrifuged at 12,500 rpm for 5 min at room temperature. Two-hundred μL of fresh 5mg/mL lysozyme was added to the bacterial pellet and incubated for 15 min at room temperature for cell lysis. Next, 750μL of Trizol reagent at 65°C was added (Life Technologies, Carlsbad, CA, United States) and transferred to a 2mL screw-cap tube with O-ring containing 0.5mL of 0.1mm glass beads, followed by complete cell lysis with MagNA Lyser (Roche Diagnostic, Sandhofer, Germany) for 2 min at max speed. After 2 min on ice, 200μL of chloroform was added and mixed by inverting the tube. Samples were centrifuged at 12,000 rpm for 15 min at room temperature. The aqueous phase was added to a new microcentrifuge tube containing 500μL of 100% RNase-free EtOH. A 700μL volume of sample was processed by Qiagen RNeasy kit DNase treatment with the Ambion TurboDNA-free kit (Thermo Fisher Scientific, Waltham, MA, United States) according to manufacturer’s instructions. To ensure RNA integrity, each sample was assessed using the Agilent RNA 6000 Nano kit with the Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA). Only RNA samples with an RNA integrity number (RIN) greater than 7 (an indication of high-quality RNA with little degradation) were used for RNA-Seq. 5.3.6 RNA-SEQUENCING AND ANALYSIS Six biological replicates from each strain (MAP K10, MAP3773c and complemented) in iron- replete and -deplete conditions were submitted for sequencing. Approximately 1μg of total RNA was used for library creation. The RNA-Seq library was prepared using the mRNA Seq Single Read Library preparation kit per manufacturer’s instructions (Illumina Inc., San Diego, CA). cDNA libraries were sequenced using Illumina sequencing technology (Illumina HiSeq 2500) in 89 five lanes of the sequencing flow cell. Libraries were prepared and sequenced at the Iowa State University DNA Facility (Ames, IA). Computational analysis was carried out on MSU’s High Performance Computing Center (HPCC) clusters. FASTQ files returned after sequencing were analyzed first by FastQC v0.11.7 to ensure quality scores were within acceptable parameters (Andrew, 2018). Trimmomatic v0.36 was used to trim adapters as well as any low-quality segments of reads (Bolger, Lohse and Usadel, 2014). Cleaned reads were processed using EDGE-pro v1.3.1, with necessary input files generated from the .gb file of NCBI reference sequence NC_002944.2 using the gb2ptt Perl script (Givan, 2009; Magoc, Wood and Salzberg, 2013). For differential expression analysis in R, output .rpkm files were initially processed by the edgeToDeseq.perl script included in the EDGE-pro package for use in the DESeq2 package (Love, Huber and Anders, 2014). Before analysis in DESeq2, the individual files for each run were checked for percent alignment to the MAP K10 genome, and samples with fewer than 95% of reads aligning by the Bowtie2-based aligner in EDGE-Pro were presumed contaminated and excluded. All runs were also double-checked by alternate alignment with the HISAT2 program, but all output confirmed Bowtie2-based aligning and supported the likely contamination of samples (Kim, Paggi and Park, 2019). DESeq2 was performed on the resulting dataset in R 4.0.0. 5.4 RESULTS 5.4.1 GENERATION OF MAP3773C DELETION BY ALLELIC EXCHANGE Using the specialized transducing mycobacteriophage developed by Bardarov et al. (2002), our group was able to successfully disrupt MAP3773c with the hygromycin reporter gene. Allelic 90 exchange is possible as a result of a double crossover between the homologous DNA arms flanking the disrupted gene (Bardarov et al., 2002). Analysis by PCR using locus-specific primers (Table 6) confirmed the configuration of the MAP3773c deletion allele (Fig. 23). A total of eight MAP K10 transductants carrying pBUN445+phAE87 showed bands indicating amplification of inner and outer sequences flanking MAP3773c (Fig. 24), an absence of the MAP3773c sequence itself (Fig. 25, lane 6), and the presence of hygromycin gene in its place (Fig. 25, lane 3), as would be expected for our desired recombination event. Figure 23. Generation of MAP3773c mutant, diagram of MAP3773c deletion by allelic exchange. Figure 24. 0.8% Agarose gel of the three fragments of MAP3773c ORF confirming deletion generated by homologous recombination. As indicated in Fig. 23, each color represents 91 Figure 24 (cont’d) individual fragments: blue: internal MAP3773c replaced by the hygromycin cassette (176bp); red: inner flank (314bp for MAP K10, 1989bp for mutant) and green: outer flank (553bp for MAP K10 and 2228bp for mutant). MAP K10 DNA was used as template (lane 1-3); MAP3773c mutant DNA was used as template (lane 4-6). No PCR product amplification as this region was replaced by hygromycin cassette (lane 6). Figure 25. 0.8% Agarose gel of the three fragments of Hygromycin ORF confirming deletion generated by homologous recombination. 0.8% agarose gel : Lane 1. PCR amplification of Hygromycin cassette (560 bp) from pYUB854- empty vector; Lane 2. Absence of PCR amplification for MAP K10; Lane 3. PCR amplification of pYUB854-MAP3773c (560 bp); Lane 4. 1kb ladder. Table 6. PCR primers used to confirm MAP3773c deletion. Primers Hygro-Fwd Hygro-Rev 5’ to 3’ Sequence AACACCTCGAAGTCGTGCAGGAAG CTACCTGGTGATGAGCCGGATGAC MAP3773c outer flank - Fwd CTCGGATCCAACGCGGAAGTGACGAGTAA MAP3773c outer flank - Rev CTCAAGCTTAGAACTCTGTGGCGGCATAA MAP3773c inner flank - Fwd AGCGGACCGTCTTAGAGGTG MAP3773c inner flank - Rev CGTCGGCGTAGTGATGTTGG Internal MAP3773c gene TCTTCGATGTCGACGGGTGTAAAGG Internal MAP3773c gene CCTGACCAGTGTTTACCGCATCTTG 5.4.2 GENOME-WIDE TRANSCRIPTOME ANALYSIS Genome-wide expression analysis using RNA-Seq was performed to elucidate the role of Fur in iron homeostasis in Mycobacterium avium subsp. paratuberculosis. The Fur mutant, parent and 92 complemented strain were investigated under iron-replete and -deplete conditions for gene expression patterns. FastQC reported values in the expected range for high-quality sequencing, supporting our use of the data for analysis. After alignment through the EDGE-pro and HISAT2 packages, low alignment values were reported for 21 out of the 36 samples sequenced, with some as low as ~16% of reads aligning to the MAP K10 genome. With a cutoff of 95%+ of reads aligning to MAP K10 (Fig. 26), the following 15 samples were used in the analysis (sample type/number of replicates): Wild-type replete/3; Wild-type deplete/3; Mutant replete/2; Mutant deplete/2; Complement replete/3; Complement deplete/2. Previously, Fur binding sites in MAP have been identified by in vivo ChIP-seq assay; however, quantifying expression level changes in genes controlled by Fur has not been performed. For simulating identical conditions as those used in ChIP-seq for consistency, iron starvation was achieved by incubating MAP strains with the cell membrane permeable iron chelator 2,2- bipyridyl (DIP) for two hours (Shoyama et al., 2020). We analyzed genes associated with binding of FurMAP and directly related to iron regulation: MAP3776c (ABC transporter), MAP3638 (hemophore-like protein), MAP3736c (Fur box) and MAP3837 (IdeR) (Shoyama et al., 2020). To determine relationships between Fur binding and transcript levels, we compared transcript levels in MAP K10, MAP3773c and complemented strains, under iron-replete and - deplete conditions relative to the control group (MAP K10 iron replete), but no statistically significant differences in any iron-related genes could be observed (Fig. 27). Corroborating these findings, after excluding runs with presumptive contamination, the DESeq2 R package showed no significant differences between any of our sample types when stratified by strain (WT, Mutant, Complemented) or treatment (Iron Replete/Iron Deplete) with adjusted P 93 values >> 0.05. A heatmap of sample-to-sample differences shows no obvious patterns between similar or different sample types or treatments (Fig. 28). Complementing this result, principle component analysis similarly shows random distribution of all samples with no distinct clustering visible (Fig. 29). Figure 26. Representation of alignment to the MAP K10 genome. Y-axis: log-transformed RPKM values; X-axis: sequential gene number across the genome. Circles are mean RPKM values for each gene, lines in the background are the values for all the replicates for this sample type. Figure 27. Transcriptional analysis by RNA-Seq with a cutoff of 95%+ of reads aligning to MAP K10. Gene expression of MAP3776c, MAP3638, MAP3736c and MAP2827 (IdeR) in 94 Figure 27 (cont’d) different strains and conditions were compared to MAP K10 under iron replete conditions. Bars represent the log2 fold change when compared to control (MAP K10 under iron replete condition), analyzed by DESeq2. Each bar color represents a different strain: MAP K10 (grey), MAP3773c mutant (black) and complemented strain (blue). Border color represents iron conditions, replete (black) and deplete (red). Figure 28. Heatmap of sample-to-sample distance of transformed count matrix. Distance- based hierarchical clustering is seen on the left and top of the figure with the labeling for the clustering on the right side of the figure. Each box in the grid represents the distance between the intersecting samples, with the darkest color representing no difference (e.g., the diagonal line comparing self-to-self samples) and lighter colors indicating greater distance. No trend is observed in the distances between and within sample groups. Generated using the deseq2, pheatmap, and rColorBrewer R packages. Figure 29. Principal component analysis plot of replicates by sample type. The distance on the X and Y axis represent the maximum data variance observable by created uncorrelated variables. 95 Figure 29 (cont’d) Salmon-colored points indicate iron replete samples, while cyan-colored points indicate iron deplete samples. The shape of each point indicates the genetic background of the sample. Sample types appear dispersed randomly across ~72% of variance with no obvious patterns correlating either treatment or genetic background to the variance displayed, suggesting no differences exist between these samples at a transcriptome-wide level. Created with deseq2 and ggplot2 R packages. Figure 30. Principal component analysis plot of only wild-type replicates. The distance on the X and Y axis represent the maximum data variance observable by created uncorrelated variables. Salmon-colored circles indicate iron replete samples, while cyan-colored circles indicate iron deplete samples. Sample types appear dispersed randomly across ~85% of variance with no obvious patterns correlating either treatment or genetic background to the variance displayed, suggesting no differences exist between these samples at a transcriptome-wide level. Created with deseq2 and ggplot2 R packages. 96 Figure 31. Meta-analysis of the top 10 unaligned reads by BLAST. 5.5 DISCUSSION High-throughput technologies allow researchers to investigate fine biological aspects of cell function and better understand diseases etiologies. In this study, we sought to elucidate iron regulation in MAP by integrating previously identified FurMAP binding sites to RNA-Seq. However, a comparative analysis of the transcriptomes from wild-type MAP K10, a Fur deletion mutant, and a complemented strain showed no significant effects at the transcriptional level under the studied conditions, despite Fur’s known MAP genome-binding as shown by ChIP-seq assays (Shoyama et al., 2020). The PCA analysis and distance matrix of our samples cast doubt on meaningful differences between sample types at a broader level (Fig. 29), and narrowing the analysis to only wild-type controls in iron-replete or iron-depleted conditions still shows a random clustering pattern (Fig. 30). Given that no repeatable differences were observed even 97 between wild-type controls, the lack of differential gene expression may not reflect biological reality. Possible explanations to this unexpected result may lie with the experimental design, and likely contamination of several replicates and subsequent exclusion from analysis severely restricted our statistical power. Preparation of RNA samples for sequencing is a multistep process involving reverse transcription, amplification, fragmentation, purification, and adaptor ligation (Auer and Doerge, 2010). In addition to these manipulations, next generation sequencing (NGS) is exquisitely sensitive as a molecular biology method, and one of the main challenges to high-throughput RNA-Seq is contamination (Nieuwenhuis et al., 2020). In our study, 21 out of 36 samples showed low alignment values when mapped against the MAP K10 reference genome, an indication of contamination that was supported by the meta-analysis by BLAST of reads that failed to align to the K10 genome (Fig. 31). Various types of contamination in sequencing runs have been reported in other studies – contamination has been seen in different points along the sequencing process, from the research laboratory where samples are being extracted, to the sequencing facility where libraries are being prepared and handled (Hadfield and Eldridge, 2014; Sangiovanni et al., 2019). Although quality control checks were done before sequencing and all samples were prepared in a DNA-free environment, treated with DNAse, and a run through a subtractive hybridization procedure by sample treatment with RiboMinus to deplete ribosomal RNA and enrich coding sequences, we still had 21 samples contaminated with exogenous material. Further investigation identifying these contaminating species can help imply at which sample preparation or library construction step it might be introduced into the sample, and thus give instruction on avoiding similar accidents in the future (Zhou et al., 2018). 98 Another additional challenge of high-throughput RNA-Seq is the variation within experiments. Besides processing date, technician, and reagent batch, other technical effects such as library preparation and technology-specific effects during the sequencing process can affect the final result (Fang and Cui, 2011; Nieuwenhuis et al., 2020). To overcome the limitations and improve the quality and reliability of differential expression (DE) detection by RNA-Seq, studies suggest that a low-replicate experiment may not provide a sufficiently detailed view of the DE to represent biology accurately; thus, multiple biological replicates are not only desirable but necessary (Fang and Cui, 2011; Robles et al., 2012). When we initially incorporated 6 biological replicates from each strain/treatment, our goal was to have enough power to detect DE. Instead, we ended up with fewer replicates (Wild-type replete/3; Wild-type deplete/3; Mutant replete/2; Mutant deplete/2; Complement replete/3; Complement deplete/2) that yielded potentially inadequate statistical power (Auer and Doerge, 2010; Fang and Cui 2011; Liu et al, 2014; Lamarre et al., 2018). Furthermore, as transcription is a highly dynamic biological process, performing a time-course RNA-Seq provides an opportunity to evaluate gene expression specific to different stages of growth and response after treatment (Thomas et al., 2018). Even though two hours after depletion was an informative time point for ChIP-seq, transcriptome responses could have occurred within minutes after depletion or days as shown in other studies using the same chelator (Brinkworth et al., 2018; Pandey et al., 2018). 5.6 CONCLUSIONS AND FUTURE DIRECTIONS Mycobacterium avium subsp. paratuberculosis and its special relationship with iron is well- known, and combined with the complex iron homeostasis problems that pathogenic bacteria face from hosts, the importance of a thorough understanding of iron metabolism is reinforced. 99 As the current RNA-Seq analysis were inconclusive due to limitations discussed above, future studies first will need to investigate the source of contamination during RNA processing and identify the optimal time for RNA extraction after iron depletion. 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ISBN 978-3-319-24277-4, https://ggplot2.tidyverse.org. Yuan, L., Li, X., Du, L., Su, K., Zhang, J., Liu, P., He, Q., Zhang, Z., Peng, D., Shen, L., Qiu, J., Li, Y. (2020) RcsAB and Fur Coregulate the iron-acquisition system via entC in Klebsiella pneumoniae NTUH-K2044 in Response to iron availability. Front. Cellular and Infec. Microbiology. (10) 282. Doi:10.3389/fcimb.2020.00282 Zhou, Q., Su, X., Jing, G., Chen, S., Ning, K. (2018). RNA-QC chain: comprehensive and fast quality control for RNA-seq data. BMC Genomics. (19):144. DOI: 10.1186/s12864-018-4503-6. 105 CHAPTER SIX: CONCLUSIONS AND FUTURE DIRECTIONS Conventional wisdom on cultivation Mycobacterium avium subsp. paratuberculosis (MAP) from primary clinical specimens (such as feces, rectal pinch, environmental samples or milk) suggests that MAP has special iron requirements. For optimal in vitro growth, it requires supplementation of the siderophore mycobactin J. Following whole-genome sequencing of MAP K10, multiple computational and functional studies investigated the role of iron in MAP survival (Stratmann et al., 2004; Li et al., 2005; Semret et al., 2005; Alexander et al., 2009; Janagama et al., 2010; Wang et al., 2014). Intracellular concentration of iron must be tightly regulated in order to maintain bacterial cell viability. In bacteria, iron metabolism is under control of two major metallogulators proteins: diphtheria toxin (DtxR) and ferric uptake regulator (Fur). Functional characterization of the iron dependent repressor protein (IdeR) in MAP, a member of DtxR family, showed that it not only controls mycobactin (mbt) synthesis but also regulates transcription of genes involved in iron acquisition (mbtB), iron storage (bfrA) and oxidative stress (Janagama et al., 2009). Furthermore, IdeR has been shown to be significantly different between cattle and sheep strains of MAP (Janagama et al., 2010). In addition to IdeR, computational analysis of MAP K10 genome, showed the presence of an alternative iron uptake mechanism in conjunction to the presence of two putative Fur boxes (Stratmann et al., 2004). The alternate iron regulator, Fur, is located on a MAP-specific genomic island (LSP15) and has been confirmed to be involved in metal homeostasis. The predicted ferric uptake regulator (MAP3773c) has been shown to be downregulated in infected intestinal tissues but upregulated in experimentally infected macrophages (Janagama et al., 2010). Thus, we hypothesized that MAP3773c (Fur) encodes a regulatory protein that orchestrates metabolic 106 pathways required for optimal environmental sensing of iron, providing an alternative iron pathway. We first performed in vitro studies using a transposon mutant of MAP3776c, located in the same genomic island (LSP15) as MAP3773c. Our data showed that knockdown of MAP3776c resulted in the knockdown of MAP3773c transcription. Interestingly, complementation of MAP3776c restored the transcription of MAP3776c and partial cell invasion phenotype. In vitro invasion assays of epithelial cell (MAC-T) and its co-culture with monocyte-derived macrophages (MDMs), revealed that the transposon mutant was invasion deficient and was depleted within 48 hr after cell entry. Whether this phenotype was related to lack of MAP3773c transcription or a mere response to MAP3776c disruption needs confirmation. MAP3773c was upregulated in wildtype MAP strains infecting epithelial cells under two different conditions (alone or in coculture with MDMs). Taken together, data presented in Chapter 3 suggests a likely role for LSP15 (and Fur) in in vivo and ex vivo cell entry and survival suggesting a function in invasion and virulence of this organism. Next, MAP3773c, the Fur ortholog was characterized. We showed a genomic view of the Fur regulatory network, using ChIP-seq analysis. Fifty-eight putative binding sites of Fur were identified both under iron replete and deplete conditions. Three binding regions were identified in genes that are directly related to iron regulation: MAP3638c (hemophore-like protein), MAP3736c (Fur box) and MAP3776c (ABC transporter). Using EMSA, specificity and dependence on Mn2+ availability for physical binding of Fur to the 19bp consensus Fur box was confirmed. To date, this is the first full characterization of FurMAP. Previously, other Fur family members in MAP have been investigated, FurA and FurB, also known as Per (peroxidase stress 107 response) and Zur (zinc uptake repressor) respectively, however no information about their potential roles in iron regulation have been described (Eckelt et al., 2014; Eckelt et al., 2015). ChIP-seq analysis of FurMAP provided potential targets of Fur-mediated gene regulation under iron-stress, however a functional investigation was needed to provide a better understanding on the role of Fur. Thus, an in-frame deletion of Fur was created using homologous recombination. A transcriptional profile of the parent MAP K10, deletion mutant and the complemented strains was developed under iron replete and depleted conditions. Comparison of gene expression differences of mutant against parent and complemented strains showed no differences or patterns that were associated with iron metabolism. Thus, under the current experimental conditions, we are unable to conclude if the lack of transcriptional responses in our study was indicative of a lack of FUR activity. While transcriptional differences were not informative, the ChIP-seq data combined with the multiple networks linked to iron metabolism still suggest FurMAP likely plays a role in stress responses. Fur has been extensively investigated in other bacteria, and in addition to its roles with iron-related genes, Fur is also known to regulate genes involved in DNA synthesis, energy metabolism, redox-stress resistance, tricarboxylic acid TCA cycle, and chemotaxis (Escolar, Martin and Lorenzo, 1999; Hantke, 2001; Fillat, 2014). Thus, disruption of Fur regulation is not exclusively related to iron homeostasis – as described in Klebsiella pneumoniae, it is possible that our identified FurMAP binding regions are related to the transcriptional regulation from other cell stresses regulated by FurMAP rather than being related to iron metabolism (Yuan et al., 2020). Additionally, MAP genome has two iron regulators identified: IdeR and Fur. IdeR was previously proposed to be the main regulator of MAP iron metabolism, so it is possible that IdeR 108 still regulates most iron-related functions while Fur may be involved in post-transcriptional control or may be triggered by alternative environmental cues (Janagama et al., 2009). In this thesis, we applied ChIP-seq and RNA-seq, to identify genes regulated by the transcription factor Fur in Mycobacterium avium subsp. paratuberculosis. In combination with transposon mutant MAP3776c and the in-frame deletion mutant MAP3773c, we analyzed the relationship between genotype and phenotype of MAP in response to iron stress. While ChIP-Seq and cell invasion data confirmed that LSP15 genes were likely associated with iron regulation in MAP, RNA-seq failed to show any associations. We propose that future studies include a dose- response and a time-course analysis to fully decipher the function of MAP3773c and LSP15 genes on iron metabolism in MAP. Titration of iron concentrations in culture media with or without oxidative and acidic stressors will likely provide a clear picture of iron metabolism and potentially the role of FUR in MAP survival. In addition, investigations targeting functional analysis induced by other stress conditions and understanding the relationship between Fur and IdeR will further our understanding a key virulence determinant of MAP. 109 REFERENCES 110 REFERENCES Alexander, D.C., Turenne, C.Y., Behr, M.A. (2009) Insertion and deletion events that define the pathogen Mycobacterium avium subsp. paratuberculosis. J Bacteriol. 191(3):1018- 25. DOI: 10.1128/JB.01340-08 Brinkworth, A.J., Wildung, M.R., Carabeo, R.A. (2018) Genomewide Transcriptional Responses of Iron-Starved Chlamydia trachomatis Reveal Prioritization of Metabolic Precursor Synthesis over Protein Translation. MSystems. 3(1):184-17. Doi:10.1128/mSystems.00184-17 Eckelt, E., Jarek, M., Fromke, C., Meens, J., Goethe, R. 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