DISSECTING THE ROLE OF PEROXISOME S IN MODULATING ENVIRONMENTAL STRESS RESPONSE AND PHOTOSYNTHESIS By Jiying Li A DISSERTATION Submitted to Michigan State University in partial fulfillment of the requirements for the degree of Genetics - Doctor of Philosophy 2015 ABSTRACT DISSECTING THE ROLE OF PEROXISOME S IN MODULATING ENVIRONMENTAL STRESS RESPONSE AND PHOTOSYNTHESIS By Jiying Li Peroxisomes are essential organelles that house a wide array of metabolic reactions important for plant growth and development. These organelles also interact with other organelles to support cellular functions. However, our knowledge regarding the role of peroxisomal proteins in various biological processes, including plant stress response and photosynthesis , is still incomplete. To address this question at the system s level, I exploited in silico analysis , mutant screens and in -depth physiological and biochemical characterizations. First, I used microarray data to generate a comprehensive view of transcript level changes for Arabidopsis peroxisomal genes during development and under abiot ic and biotic stress conditions . Second, mutants of LON2 protease and the photorespiratory enzyme hydroxypyruvate reductase 1 (HPR1) were identified to have enhanced susceptibility to drought, suggesting the involvement of peroxisomal quality control and photorespiration in drought resistance. Third, I conducted a comprehensive peroxisomal mutant screen, in which 147 mutants of 104 Arabidopsis genes encoding peroxisomal proteins were subjected to an automated screening system, the Dynamic Environment Phenotype Imager (DEPI). This screen identified multiple peroxisomal proteins required for robust photosynthesis efficiency under dynamically changing light, including peroxisomal biogenesis and div ision proteins, photorespiratory proteins, and a NAD+ transporter protein PXN, which was found to be an addition al player in photorespiration . Fourth, further characterization of the photorespiratory mutants provided insights into the molecular mechanisms regarding how the block ing of photorespiration alter s photosynthetic efficiency . My data supported an integrated model for the events that occur in the photorespiration mutants, where metabolites and molecules result ing from the block of photorespiration inhibit triose phosphate i somerase (TPI ) activity, compromise photosystem integrity, reduce photosystem subunit abundance, decrease proton efflux and diminish ATP synthase conductivity, induce cyclic electron flow ( CEF ) and activate energy dissipation . In s ummary, my work has provided significant insights into the connection between peroxisomal function and drought stress response and the links between photorespiration and photosynthesis. Knowledge gained from my dissertation research opens up new avenues to further investigate environmental stress response, photosy nthesis, photorespiration and interorganellar communication. iv ACKNOWLEDGEMENT S First of all, I want to thank my beloved grandm other, mother and father for their endless love, encouragement and support. I would not be the person I am today and I would not have achieved so much if it was not for their constant confidence in me. I want to express my special appreciation to Dr. Jianbing Yan , who influenced me a lot in my undergraduate study in China Agricultural University . His passion for science and his care for nurturing students enlighten ed my avid interest in science . I gratefully thank my advisor Dr. Jianping Hu for giving me the opportunity to study and do research in her lab. Jianping is a great mentor, not only because of her knowledge and guidance, but also because she allowed me the freedom to explore different directions in research . What I have learned from her will be a significant impact in my future career. I also want to acknowledge present and previous Hu lab members for their great help to improv e my critical thinking and experimental skills. I appreciate the precious time and suggestion s from my committee members: Drs. Kathy Osteryoung, Sheng Yang He, Christoph Benning and Thomas Sharkey, as well as the Genetic Program representative Dr. Barb Sears. I want to gratefully thank our collaborator s Drs . David Kramer, Thomas Sharkey and Jin Chen, as well as members in their lab s, for sharing knowledge, ideas and experimental devi ces. Other c olleagues at MSU also offered a great deal of help to me. I feel very fortunate to study at MSU. Besides its a cademic excellence, t he fame of MSU ™s football and basketball made me very proud of being a Spartan . I have made many good friends at MSU . The time we spent in sharing stories , travelling and playing v together will be forever memorable . Our friendship will be a lifelong treasure to me. Thank you all for being a part of my life. vi TABLE OF CONTENTS LIST OF TABLES ........................................................................................................... ix LIST OF FIGURES .......................................................................................................... x KEY TO ABBREVIATIONS ....................................................................................... xiii CHAPTER 1 ...................................................................................................................... 1 Literature review: Peroxisomal functions and photosynthesis ........................................ 1 1.1. Peroxisomal functions .............................................................................................. 2 1.1.1. Introduction ....................................................................................................... 2 1.1.2. Major peroxisomal metabolism ......................................................................... 3 1.1.3. The role of peroxisomes in stress response ....................................................... 9 1.2. Photosynthesis ........................................................................................................ 12 1.2.1. Introduction ..................................................................................................... 12 1.2.2. PSII .................................................................................................................. 13 1.2.3. PSI ................................................................................................................... 16 1.2.4. Cytochrome b6................................................................................................f 20 1.2.5. ATP synthase ................................................................................................... 21 1.2.6. Adaptive mechanisms to changing light conditions ........................................ 24 1.2.7. NPQ ................................................................................................................. 25 1.2.8. State transition ................................................................................................. 27 1.2.9. Cyclic electron flow ......................................................................................... 28 1.3. Aims of dissertation research ................................................................................. 31 APPENDIX ................................................................................................................... 33 REFERENCES .............................................................................................................. 40 CHAPTER 2 .................................................................................................................... 58 Using co -expression analysis and stress -based screens to uncover Arabidopsis peroxisomal proteins involved in drought response ...................................................... 58 2.1. Abstract .................................................................................................................. 59 2.2. Introduction ............................................................................................................ 61 2.3. Result ...................................................................................................................... 64 2.3.1. Co-expression analysis of genes that encode peroxisomal proteins during development and in response to stresses ................................................................... 64 2.3.2. A drought tolerance mutant screen revealed the role of the LON2 protease a nd the photorespiratory enzyme hydroxypyruvate reductase 1 (HPR1) in drought response ..................................................................................................................... 67 2.4. Discussion .............................................................................................................. 69 2.5. Materials and methods ........................................................................................... 73 2.5.1. Plant materials and growth conditions ............................................................. 73 2.5.2. Microarray data analysis and heatmap visualization ....................................... 73 2.5.3. Chlorophyll fluorescence measurements ......................................................... 74 2.5.4. Drought stress assays ....................................................................................... 74 2.6. Acknowledgement .................................................................................................. 76 vii APPENDIX ................................................................................................................... 77 REFERENCES ........................................................................................................... 101 CHAPTER 3 .................................................................................................................. 108 Dissecting the role of peroxisomal metabolism in modulating photosynthesis under dynamic light conditions ............................................................................................. 108 3.1. Abstract ................................................................................................................ 109 3.2. Introduction .......................................................................................................... 111 3.3. Result .................................................................................................................... 115 3.3.1. Collecting mutants for genes encoding peroxisomal proteins ....................... 115 3.3.2. Mutant screen and photosynthetic data analysis ............................................ 115 3.3.3. Peroxisomal biogenesis and division m utants exhibited reduced photosynthetic efficiency under various light conditions ................................................................ 117 3.3.4. Photorespiratory mutants displayed severe deficiencies in photosynthetic performance under high light and fluctuating light conditio ns ............................... 118 3.3.5. The peroxisomal NAD +........................................................................................................ PXN is involved in photosynthesis under fluctuating light conditions 122 3.3.6. Supply of CO 2.............................................................................................................. rescued the phenotypes the photorespiratory mutants and the pxn mutants 123 3.3.7. Rapid increase in proton motive force contributes to fast qE response in photorespiratory mutants ......................................................................................... 124 3.3.8. Activation of CEF in hpr1 under high light conditions ................................. 126 3.3.9. Interaction between photorespiration and excessive energy dissipation ....... 127 3.3.10. Elevated ROS burst, faster chlorophyll degradation and anthocyanin deficiency in the photorespiratory mutants under high light ................................... 129 3.3.11. Comprised integrity of photosynthetic complexes and decreased abundance of photosynthetic subunits in photorespiratory mutants under high light ............... 131 3.3.12. Evidence for the inhibition of triose phosphate isomerase and activation of the oxidative pentose phosphate pathway in hpr1 under high light ........................ 133 3.4. Discussion ............................................................................................................ 135 3.4.1. Photorespiration is the major peroxisomal function that connects to photosynthesis ......................................................................................................... 136 3.4.2. Various enzymes in photorespiration play quantitatively and kinetically different roles in photorespiration under dynamic light conditions ........................ 138 3.4.3. Highly elevated qE in photorespiratory mutants is due to rapid buildup of proton gradient across thylakoid membrane and largely dependent on PsbS and zeaxanthin ................................................................................................................ 139 3.4.4. Strong activation of CE F occurs in photorespiratory mutants under high light ................................................................................................................................. 141 3.4.5. Photorespiratory mutants exhibited compromised PS complex integrity, diminished PS subunit abundance and reduced stress resistance after HL treatment ................................................................................................................................. 142 3.4.6. Conclusions ................................................................................................... 143 3.5. Materials and methods ......................................................................................... 145 3.5.1. Plant materials and growth conditions ........................................................... 145 3.5.2. Fluorescence measurements, image processing and data analysis ................ 145 viii 3.5.3. In vivo spectroscopic assays .......................................................................... 146 3.5.4. Measurements of CEF ................................................................................... 147 3.5.5. 148Statistical analysis .......................................................................................... 3.5.6. Thylakoid membrane preparation .................................................................. 148 3.5.7. BN-PAGE and immunoblot analyses ............................................................ 149 3.5.8. Quantitative RT -PCR .................................................................................... 150 3.5.9. Measurement of chlorophyl l and anthocyanin .............................................. 150 3.5.10. In situ detection of H 2O2 ............................................................................. 151 3.5.11. Measurement of GAP and DHAP ............................................................... 151 3.6. Acknowledgement ................................................................................................ 152 APPENDIX ................................................................................................................. 154 REFERENCES ............................................................................................................ 202 CHAPTER 4 .................................................................................................................. 215 CONCLUSIONS AND FUTURE PERSPECTIVES ................................................. 215 4.1. Comprehensive view of transcriptional regulation on genes encoding peroxisomal proteins across developmental stages and under various environmental stresses ....... 216 4.2. LON2 protease and the photorespiratory enzyme hydroxypyruvate reductase 1 (HPR1) play important roles in drought response ....................................................... 218 4.3. PXN is an additional factor in photorespiration ................................................... 219 4.4. gox1 exhibited drastic photosynthetic phenotype under dynamics light conditions despite its normal growth in ambient air ..................................................................... 220 4.5. Metabolites and molecules resulting from blocking photorespiration have a large impact on photosynthetic complexes and processes ................................................... 221 REFERENCES ............................................................................................................ 224 ix LIST OF TABLES Table 2.1. Microarray datasets used in this study ......................................................... 88 Table 2.2. Arabidopsis peroxisomal gene list ............................................................... 92 Table 2.3. Mutants used in the primary screen for drought tolerance .......................... 99 Table 3.1. List of screened peroxisomal mutants ....................................................... 194 Table 3.2 . Primers used in this study .......................................................................... 201 x LIST OF FIGURES Figure 1.1. Some -oxidation enzymes ......................................................................................................................... 34 Figure 1.2. Peroxisomes play a central role in photorespiration ................................ .. 36 Figur e 1.3. Overview of photosynthetic complexes and processes on the thylakoid membrane ...................................................................................................................... 38 Figure 2.1. Heatmap of transcript levels of peroxisomal genes in various developmental stages ..................................................................................................... 78 Figure 2.2. Heatmap of transcript levels of peroxisomal genes under abiotic stresses 80 Figure 2.3. Heatmap of transcript levels of peroxisomal genes under biotic stresses .. 82 Figure 2.4. Total number of peroxisomal genes with significantly changed expression levels in response to stresses ......................................................................................... 84 Figure 2.5. Fv/Fm of the selected peroxisomal mutants after drought treatment ......... 85 Figure 2.6. Drought resistance phenotypes of lon2 and hpr1 mutants ......................... 86 Figure 3.1. Revealing photosynthetic phenotypes of peroxisomal mutants under dynamic light conditions using DEPI .......................................................................... 155 Figure 3.2. Phot osynthetic performance of the pex14 mutant under dynamically changing light conditions ............................................................................................ 157 Figure 3.3. Photosynthetic capabilities of peroxisomal division mutants under dynamically changing light conditions ........................................................................ 159 Figure 3.4. Gene expression analysis and growth appearance of photorespiratory mutants ........................................................................................................................ 161 Figure 3.5. Photosynthetic performance of photorespiratory mutants under high light and fluctuating light conditio ns................................................................................... 162 Figure 3.6. Chlorophyll fluorescence image of representative photorespiratory mutants under sinusoidal light on Day 2 ................................................................................... 164 Figure 3.7. Mutants of peroxisomal NAD + transporter PXN, pxn -1 and pxn -2, exhibited emerging phenotype under fluctuating light conditions. ............................. 166 xi Figure 3.8. Chlorophyll fluorescence image of pxn under 1 st half period of fluctuating light on Day 3 .............................................................................................................. 168 Figure 3.9. Supply of CO 2 rescued the emerging phenotype exhibited in the photorespiratory mutants and pxn mutants. ................................................................ . 170 Figure 3.10. Quantitative spectroscopic analysis of four photorespiratory mutants. . 172 Figure 3.11. Activation of CEF in hpr1 under high light conditions ......................... 173 Figure 3.12. qE measurement in hpr1 npq double mutants ........................................ 175 Figure 3.13. qE measurement of th e gox1 npq and plgg1 npq double mutants ......... 177 Figure 3.14. Photosynthetic measurements of hpr1 , npq1 and hpr1 npq1 under dynamically changing light conditions ........................................................................ 179 Figure 3.15. Photosynthetic measurements of hpr1 , npq2 and hpr1 npq2 under dynamically changing light conditions ........................................................................ 180 Figure 3.16. Photosynthetic measurements of hpr1 , npq4 and hpr1 npq4 under dynamically changing light conditions ........................................................................ 181 Figure 3.17. Photosynthetic measurements of gox1 , npq1 and gox1 npq1 under dynamically changing light conditions ........................................................................ 182 Figure 3.18. Photosynthetic measurements of gox1 , npq2 and gox1 npq2 under dynamically changing light conditions ........................................................................ 183 Figure 3.19. Photosynthetic measurements of gox1 , npq4 and gox1 npq4 under dynamically changing light conditions ........................................................................ 184 Figure 3.20. Photosyntheti c measurements of plgg1 , npq1 and plgg 1 npq1 under dynamically changing light conditions ........................................................................ 185 Figure 3.21. Photosynthetic measurements of plgg1 , npq2 and plgg 1 npq2 under dynamically changing light conditions ........................................................................ 186 Figure 3.22. Photosynthetic measurements of plgg1 , npq4 and plgg 1 npq4 under dynamically changing light conditions ........................................................................ 187 Figure 3.23. Adaptation of the photorespiratory mutants to long term HL stress. ..... 188 Figure 3.24. Analysis of the integrity of photosynthetic complexes and levels of photosynthetic subunits in photorespiratory mutants under high light ....................... 190 xii Figure 3.25. High light induction of GPT2 expression in photorespiratory mutants and change of the amount of GAP and DHAP in hpr1 ...................................................... 191 Figure 3.26. An integrated model for the role of photores piration in modulating photosynthesis ............................................................................................................. 192 xiii KEY TO ABBREVIATIONS ABA Abscisic Acid ABRC Arabidopsis Biological Resource Center AGT Alanine: G lyoxylate A minotransferase ATP Adenosine -5™-Triphosphate C Celsius CAT Catalase CBB Calvin -Benson -Bassham CEF Cyclic electron flow Cyt b6f Cytochrome b6DEPI Dynamic Environment Phenotype Imager f complex DHAP Dihydroxyacetone P hosphate DRP Dynamin Related Protein ER Endoplasmic Reticulum FA Fatty Acid FD Ferredoxin FNR FD-NADP +F oxidoreductase v/FmGAP Glyceraldehyde 3 -phosphate Maximum quantum yield GEO Gene Expression Omnibus GGT Glutamate: G lyoxylate A minotransferase gH+GL Growth Light ATP synthase conductivity GOX Glycolate Oxidase HL High Light HPR Hydroxypyruvate Reductase xiv IAA Indole -3-Acetic Acid IBA Indole -3-Butyric Acid JA Jasmonate Acid LHC Light Harvesting Complex NADH Nicotinamide Adenine Dinucleotide NADPH Nicotinamide Adenine Dinucleotide Phosphate NPQ Non-Photochemical Quench ing PC Plastocyanin PEX Peroxin P-glyc Phosphoglycolate PMDH Peroxisomal Malate Dehydrogenase pmf Proton Motive Force PQ Plastoquinone PSI Photosystem I PSII Photosystem II PXN Peroxisomal NAD +qE Energy -dependent quenching carrier qI Photoinhibition quenching ROS Reactive Oxygen Species SA Salicylic Acid SGT Serine: G lyoxylate A minotransferase TPI Triose Phosphate Isomerase vH+ Photosystem II operating efficiency Thylakoid membrane proton efflux CHAPTER 1 Literature review: Peroxisomal functions and photosynthesis 1.1 Peroxisomal function s 1.1.1 Introduction Peroxisomes are small and single membrane -bounded organelles found in virtually all eukaryotic cells. They were first described in 1954 ( Rhodin, 1954 ) and later isolated from rat liver cells in 1966 ( De Duve and Baudhuin, 1966 ). This organelle was named fiperoxisomefl after the discovery of several hydrogen peroxide (H 2O2) producing oxidases and H 2O2Fagarasanu et al., 2010 degrading catalase s enriched in it. In recent decades, peroxisomes have been extensively studied in different systems and increasingly recognized as an indispensable part of the s ubcellular compartmented system (; Hu et al., 2012 ; Islinger et al., 2012 ; Pieuchot and Jedd, 2012 ; Smith and Aitchison, 2013 ). Peroxisomes make critical contributions to cellular functions because of the metabolic reactions they house -oxidation of fatty acids (FAs) and related metabolites and detoxification of reactive oxygen species (ROS), most of which are oxidative reactions ( Fagarasanu et al., 2010 ; Pieuchot and Jedd, 2012 ). In humans, the physiolog ical significance of the peroxisome is exemplified by a series of severe neurological, hepatic and renal diseases caused by defects in peroxisome biogenesis and metabolism , including the Zellweger syndrome, neonatal adrenoleukodystrophy and infantile refsum disease ( Schrader and Fahimi, 2008 ; Waterham and Ebberink, 2012 ; Waterham and Wanders, 2012 ). P articipation of peroxisome s in antiviral response has been revealed recently , adding another important role of peroxisome s as a signaling platfor m for antiviral innate immunity (Dixit et al., 2010 ). In plants, peroxisomes harbor conserved metabolic proces -oxidation of FAs, production and scavenging of H 2O2, as well as plant specific reaction s, including photorespiration, metabolism of i ndole-3- butyric acid (IBA) to indole-3- acetic acid (IAA) and biosynthesis of jasmonate acid (JA) and others ( Hu et al., 2012 ; Kaur et al., 2009 ). Previ ous genetics studies have shown that mutations in peroxisomal proteins resulted in a wide range of plant growth and development defects, which indicates that peroxisomes play important roles in relevant biological processes, such as embryogenesis, seedling development, leaf senescence, stress response and others ( Hu et al., 2012 ; Kaur et al., 2009). 1.1.2 Major peroxisomal metabolism FA oxidation pathway : One of th e well -studied peroxisomal functions in plants is FA -oxidation, through which seed oil storage is br oken down to fuel seed germination and seedling development before autotrophic ability is fully established. Seed oil storage , in the form of triacylglycero l, is firstly degraded to fatty acid s before entering th e -oxidation cycle (Eastmond, 2006 ). The fatty acids and other substrates are imported into peroxisomes by the peroxisomal ABC transporter protein CTS/ PXA1/PED3 ( Footitt et al., 2002 ; Hayashi et al., 2002 ; Zolman et al., 2001 ) and subsequently activated by acyl -activating enzymes (AAEs) such as LACS6 and LACS7 (Fulda et al., 2 004) before entering the -oxidation cycle (Figure1.1) . The peroxisomal FA -oxidation cycle consists of four enzymatic steps ( Goepfert and Poirier, 2007 ). The first step is the oxidation of acyl -CoA with production of 2 -trans -enoyl -CoA, which is catalyzed by acyl -CoA oxi dase (ACX ) ( Adham et al., 2005 ; Froman et al., 200 0; Khan et al., 2012 ; Rylott et al., 2003 ). The second and third steps are successively catalyzed by multifunctional protein (MFP), which possesses enoyl -CoA hydratase and 3 -hydroxyacyl -CoA dehydrogenase activit ies thus can convert 2 -trans -enoyl -CoA to 3 -hydorxycayl -CoA and 3 -ketoacyl -CoA, respectively ( Richmond and Bleecker, 1999 ; Rylott et al., 2006 ). The last step is the cleava ge of 3 -ketoacyl -CoA with the generation of acyl -CoA and acetyl -CoA, catalyzed by 3 -ketoacyl -CoA thiolase (KAT) ( Germain et al., 2001 ; Wiszniewski et al., 2014 ). After a completed cycl e, the original acyl -CoA is shortened by two carbons and one molecule of acetyl -CoA is produced as the substrate for the glyoxylate cycle and gluconeogenesis ( Cornah et al., 2004 ). In Arabidopsis, there are 6 identified peroxisomal ACXs, which possess different but partially overlapping specificities on substrate chain length (Graham and Eastmond, 2002 ). Two genes encoding peroxisomal multifunction al proteins and three KATs have been identified in Arabidopsis. Many mutants of ACXs and FA -oxidation related peroxisomal proteins exhibit germination and early seedling developmental defects (Goepfert and Poirier, 2007), solidifying the essential role of p eroxisome s in seed germination and seedling establishment. Photorespiration pathway: Photorespiration is another essential metabolic process accomplished by the peroxisome, with the cooperation of chloroplasts and mitochondria (Figure 1.2) (Bauwe et al., 2010 ). Photorespiration begins with the production of phosphoglycolate, a product of Ru bisco oxygenase activity on ribulose -1,5-bisphosphate (RuBP), and ends with recycling phosphoglycerate back the Calvin -Benson- Bassham (CBB) cycle . Thus photorespiration is considered an altern ative carbon recycling pathway operating alongside the CBB cycle ( Sage et al., 2012 ). In chloroplast s, phosphoglycolate is dephosphorylated by phosphoglycolate phosphatase PGLP1 (Schwarte and Bauwe, 2007 ), and the glycolate generated is subsequently transported outside of the chloroplasts via a plastidic glycolate glycerate transporter PLGG1 (Pick et al., 2013 ). After entering the peroxisome, glycolate is subjected to oxidation by glycolate oxidase (GOX) ( Hofmann, 2011 ; Zelitch et al., 2009 ) to produce glyoxylate. Then a n amino group is introduced to glyoxylate by glutamate: glyoxylate aminotransferase (GGT) (Igarashi et al., 2003 ; Liepman and Olsen, 2003 ) to produce glycine, which is subsequently transported to mitochondria. In mitochondria , two molecules of glycine are converted to one molecule of serine by glycine decarboxylase (GDC) ( Engel et al., 2007 ; Timm et al., 2012 ) and serine hydro xymethyltransferase (SHMT) (Voll et al., 2006 ); meanwhile one molecule of carbon and one molecule of nitrogen are lost. Serine is transported back to peroxisome s and its amino group is removed by serine: glyoxylate aminotransferase (SG T) ( Somerville and Ogren, 1980 ) to generate hydroxypyruvate. The last step of photorespiration in the peroxisome is catalyzed by hydroxypyruvate reductase (HPR), which reduces hydroxypyruvate to glycerate (Timm et al., 2008 ). NADH generated by peroxisomal malate dehydrogenase (PMDH) facilitates the reduction reaction catalyzed by HPR ( Cousins et al., 2011 ). Glycerate is subsequently transported back to chloroplast by PLGG1, phosphorylated by glycerate kinase GLYK ( Boldt et al., 2005) to generate phosphoglycerate, and finally fed into the CBB cycle. To complete photorespiration, two molecules of glycolate are converted to one molecule of glycerate at the cost of one carbon and one ammonium in mitochondria ( Foyer et al., 2009 ). In total, five peroxisomal enzymes are found directly involved in photorespiratory metabolism , which are encoded by two GOX, two GGT , one HPR , three SGT and two PMDH genes (Sage et al., 2012 ). Mutation s in these genes cause typical photorespiratory phenotype , that is, mutants are strongly delayed in growth or even unviable in ambient air, but can be recovered to great extent by growing in high concentrations of CO 2Foyer et al., 2009 (). H2O2 detoxification: In addition to housing these two aforementioned metabolic pathways , peroxisomes are the major source of H 2O2, a by -product generated by the oxidative reactions catalyzed ACX, GOX and other oxidases. H 2O2Mittler et al., 2011 is an important signaling molecule in various stress conditions. However, if excessively accumulated and escaped to the cytosol , it could be a harmful reactive oxygen species (). To fine tune the equilibrium of peroxisomal H 2O2 concentration, an efficient H 2O2 detoxification system is implemented in the peroxisome. Catalase is the primary enzyme in degrading H 2O2 into H 2O and O 2Mhamdi et al., 2012 . There are three Arabidopsis catalases (; Takahashi et al., 1997 ), all of which reside in peroxisomes and have similar biochemical activit ies but different tissue -specific expression patterns. CAT2 is the major catalase in leaves, CAT 3 expression is mainly found in leaf vasculature, and CAT 1 shows particularly high expres sion in male reproductive tissues, such as anther, pollen, and stamen. Genetic evidence showed that cat2 knockout mutant exhibited significantly increased leaf lesion s Mhamdi et al., 2012 in various biotic and abiotic stress conditions (), cat1 and cat3 mutants also exhibited obvious but less severe phenotype under the same conditions ( Mhamdi et al., 2012 ). A n auxiliary peroxisomal ROS detoxification pathway employs ascorbate peroxidase (APX ), monohydroascorbate reductase MDAR, dehydroascorbate reductase (DHAR ) and glutathione reductase (GR) to degrade peroxisomal H 2O2Eastmond, 2007 ( ; Lisenbee et al., 2005 ). P erox isomal proteins such as glutathio ne sulfur reductase may also be involved in H 2O2Kaur et al., 2009 homeostasis ( ). JA biosynthesis : JA is a fatty -acid -derived phytohormone that can regulate a variety of developmental and stress response processes, including fertility, sex determination, root elongation, abiotic stress and defense against pathogens and wounding ( Fonseca et al., 2009 ). JA biosynthesis begin s in chloroplast s, where polyunsaturated fatty acids are converted to the JA precursor OPDA (12 -oxo- phytodienoic acid). After import into the peroxisome , OPDA is reduced by OPDA reductase OPR3 to genera te OPC8:0 [3-oxo-2- (2'-[ Z]- penenyl) cycopentane -1- octanoic acid ], which is the substrate for three subsequent rounds of -oxidation (Figure 1.1) (Wasternack and Hause, 2013 ). After being c atalyzed by the action of ACX1 and ACX5, AIM1, and PED1/KAT2, OPC8:0 is converted to OPC6:0 after the first round , OPC4:0 after the second round and JA after the third round. Genetic studies have shown that opcl1 , acx1 , aim1 and ped1 /kat2 mutants ha ve decreased levels of JA, disruption of ACX1 or PED/KAT2 result ed in comprised systematic response ( Cruz Castillo et al., 2004; Delker et al., 2007 ; Schilmiller et al., 2007 ), and tomato acx1 mutant exhibit ed reduced defense against chewing insects ( Li et al., 2005 ). After being exported to the cytosol, JA is modified to its bi oactive form JA -isoleucine to participate in JA signaling (Fonseca et al., 2009 ). Conversion of IBA to IAA : IAA (indole-3- acetic acid) is an active form of the phytohormone auxin, which regulates a plethora of processes, including cell division and elongation, leaf primordial development, phototropism, root development, fruit development and many others ( Abel and Theologis, 2010 ; Krupinski and Jonsson, 2010 ). Endogenous IAA level is modulated through biosynthesis, transport, storage, and inactivation ( Mano and Nemoto, 2012 ). An increasingly recognized aspect of IAA regulation is the peroxisomal conversion of IBA to IAA ( Strader and Bartel, 2011 ; Strader et al., 2010 ; Strader et al., 2011 ). IBA is structurally very similar to I AA, except that it has two more carbons in the side chain . IBA is imported into the peroxisome, activated by the add ition of a CoA group, and converted to IAA through -oxidation by the shortening of two carbons. Mutant s of genes involved in FA -oxidation, such as ABC transporter mutant cts /pxa1 /ped3 (Zolman et al., 2001 ), multifunction al protein mutant mfp2 and aim1 (Zolman et al., 2008 ), 3-ketoacyl -CoA thiolase mutant ped1 /kat2 (Zolman et al., 2008 ) and most of the acyl -CoA oxidase acx mutants ( Adham et al., 2005 ; Eastmond et al., 2000 ; Rylott et al., 2003 ), showed reduced IBA resistance. Several other peroxisomal proteins such as IBA -RESISTANT 1 (IBR1) , IBR3, IBR10 and Enoyl -CoA Hydratase 2 (ECH2 ), were suggested to act specifically i n the conversion of IBA to IAA . IBR1, IBR3 and IBR10 were discovered in forward genetic screens searching for IBA -resistant mutants, and the mutations were later mapped to genes encoding short -chain dehydrogenase/reductase, acyl -CoA dehydrogenases/oxidases and enoyl -CoA hydratase, respectively ( Hu et al., 2012 ). ECH2 encodes an enoyl -CoA hydratase, and the null mutant exhibited full resistance to IBA in dark -grown Arabidopsis seedlings ( Strader et al., 2011 ). Peroxisome biogenesis mutants, such as pex4 , pex5 , pex6 and pex7 , showed reduced IBA resistant phenotype s, further confirming the critical role of peroxisom es in IBA to IAA conversion ( Strader et al., 2011 ). 1.1.3 The role of peroxisomes in stress response In addition to their role in plant development and growth , recent evidence strongly suggests that peroxisomes also play a critical role in a series of biotic and abiotic stress responses (Bednarek et al., 2009 ; Lipka et al., 2005 ; McCartney et al., 2005 ; Rojas et al., 2012 ). Striking evidence for the role of peroxisomes in plant pathogen response came from microscopic observation that peroxisomes rapidly aggregate at the fungal p athogen penetration sites, implying that peroxisomes respond to certain signals from the pathogen attack (Lipka et al., 2005 ). Interestingly, upon stimulation by a fine needle, peroxisomes also converge d to the needle contact site in Arabidopsis epidermal cells (Hardham et al., 2008), suggesting that the physical pressure from the fungal pathogen penetration may induce peroxisome aggregation. At the molecular level, a peroxisomal protein called PEN2 has a major role in Arabidopsis broad -spectrum non -host resistance against fungal pathogens. PEN2 is a peroxisome -associated myrosinase catalyzing glucosinolate hydrolysis required for generating antimicrobial products. pen2 mutant shows significantly reduced callose deposition, increased pathogen penetration rate and enhanced disease susceptibility (Bednarek et al., 2009 ; Lipka et al., 2005 ). Besides PEN2, a peroxisome -associated calcium -dependent protein kinase CPK1 greatly enhances plant resistance to both fungal and bacterial pathogens in a salicylic acid ( SA)- dependent manner (Coca and San Segundo, 2010 ). Finally, both JA and SA control a wide range of signaling events in plant immunity (Afitlhile et al., 2005 ; Koo et al., 2006 ; Metraux, 2002 ; Schilmiller et al., 2007 ; Wasternack, 2007 ), and the peroxisomal enzymes involved in FA -oxidation are employed in JA and presumably SA biosynthe tic pathways ( Koo et al., 2006; Reumann, 2004 ), making peroxisomes a potential player in plant defense. Recently, multiple isoforms of the peroxisomal glycolate oxidase (GOX) have been found as essential component s of nonhost resistance against bacterial pathogen in both Arabidopsis and tobacco plants (Rojas et al., 2012 ). The H 2O2 produced in the GOX-catalyzed oxidation step is believed to be utilized as a key signaling molecule during pathogen response. Several peroxisomal photorespiration enzymes, such as SGT, GGT, and HPR, are also found to confer immune response in s oybean or Arabidopsis plants, possibly through photorespiratory H 2O2Okinaka et al., 2002 generation ( ; Taler et al., 2004 ; Verslues et al., 2007 ). Since H 2O2Chamnongpol et al., 1996 is produce d by many peroxisomal oxidative reactions, efficient ROS -scavenging systems consisting of catalases and ascorbate -glutathione cycle enzymes are implemented in the peroxisome. Suppression of CAT1 in tobacco resulted in lea f lesion under oxidative stress -inducing conditions, such as high light and drought stress ( ). Arabidopsis cat2 null mutant s exhibited enhanced leaf lesion under high light conditions ( Chamnongpol et al., 19 96). Exposure to H 2O2Sinclair et al., 2009 and UV light induce s pronounced tubule -shaped extension structure called peroxule and increased peroxisome abundance, suggesting that peroxisome s are actively responding to environmental stress signals by changing morphology and abundance ( ). Emerging evidence indicat ed the roles of peroxisomal proteins in stress response, therefore a peroxisome -centered study is desired to comprehensively study how peroxisom al metabol ism is connected to environmental stress response. The large amount of transcriptom ic, proteom ic and metabolom ic data accumulated in public database s could possibly shed light on which peroxisomal genes potential ly play critical roles under specific stress conditions ( Rhee et al., 2006 ; Schulze and Usadel, 2010 ; Sulpice and McKeown, 2015 ). The development of advanced high throughput phenotyping platform, combined with rich genetic resources, i.e. the availability of large collections of Arabidopsis mutants, may largely accelerate the discovery of those potential players (Fiorani and Schurr, 2013 ) . 1.2 Photosynthesis 1.2.1 Introduction Oxygenic photosynthesis, which converts sunlight energy to ATP and NADPH for CO 2 fixation and other dark -reaction -related metabolism, is the principal reaction that drives profound changes to our planet and the life on it. The primary reaction of oxygen ic photosynthesis is mediated by four protein complexes embedded in the thylakoid membrane , including photo system II (PSII), the cytochrome b6f complex (Cyt b6Nickelsen and Rengstl, 2013 f), photosystem I (PSI) and ATP synthase (Figure 1.3) . P igments and cofactors, such as chlorophylls, carotenoids, lipids and others, are associated with these protein complexes for a diverse array of criti cal functions. During the past few decades, many investigations were published regarding photosynthesis in different model system s, including cyanobacteria, algae and higher plants . Our knowledge about the structure and function of the photosynthetic complexes and the dynamic regulatory mechanisms are becoming more comprehensive and in depth ( ). In this section, the structure, function, and regulatory mechanism of the four major photosynth etic complexes , as well as the plas ticity of photosynthetic processes under dynamic environment al conditions, especial ly changing light conditions, will be reviewed. Light energy is captured by the light -harvesting complex (LHC) associated with PSII and PSI. The se antenna s ystems absorb light and channel the light excitation energy to the reaction center of PSII and PSI to generate a stable charge separation across the thylakoid membrane. In this way, PSII becomes highly oxidative and is able to split water molecule s to gene rate electron s, proton s and oxygen. The electron s will be transported through PSII, Cyt b6f and PSI, as well as small mobile electron carriers such as plastoquinone (PQ) and plastocyanin (PC), result ing in the reduction of ferredoxin (FD) and finally the production of NAPDH (Figure1.3) . In addition to the linear electron flow (LEF) from PSII to PSI, cyclic electron flow (CEF) also occurs, in which electrons are transported back to the PQ pool from the PSI. Both LEF and CEF are coupled with proton transfer from the stromal to the lumenal side of thylakoid membrane and the generation of proton gradient, which can drive the ATP synthase to produce ATP. The NAPDH and ATP produced in the oxygenic photosynthesi s will fuel the reactions of carbon assimilation and other cellular metabolism s (Nelson and Junge, 2015 ; Rochaix, 2014). 1.2.2 PSII PSII is a large membrane protein complex located in the thylakoid membrane of photosynthetic organisms ranging from cyanobacteria to higher plants. During the course of evolution, the core machinery for PSII has been mostly conserved . T he only major difference is in the light -capturing antenna system, which is named phycobilisome in cyanobacteria and light harvesting complex (LHC) in green algae and higher plants ( Shen, 2015; Suga et al., 2015 ). In cyanobacteria, the PSII complex consists of 20 subunits, of which 17 are transmembrane subunits and 3 are membrane -peripheral subunits, with a total molecular mass of 350 kDa . Among the transmembrane subunits, D1 and D2 constitute the core of PSII reaction center, with which all of the co -factors participat e in water splitting r eactions and electron transfer are associated. CP47 and CP43 are two transmembrane subunits surrounding D1 and D2, and bind to a number of chlorophyll molecules to serve an inner light harvesting function. Besides these four large subunits, the re are 13 other low- molecular -weight transmembrane subunits (<10 kDa each) that surround the PSII reaction center ( Shen, 2015 ; Suga et al., 2015 ). Three membrane -peripheral proteins are associated with the lumenal side of P SII and are required to maintain the water -splitting reaction. In cyanobacteria these proteins are PsbO, PsbU and PsbV; in green algae and higher plants, PsbU and PsbV are replaced with PsbQ and PsbP, respectively (Shen, 2015 ; Suga et al., 2015 ). P680 is t he chlorophyll cluster associated with the reaction center and consi sts of 4 chlorophyll molecules. Upon absorption of light, one of the four chlorophyll molecules become s excited and donates one electron to pheophytin. The electron is then transported from pheophytin to the primary and secondary plastoquinone electron acceptors, Q A and QB, respectively. The oxidized P680 oxid ize s the nearby D1 protein, which in turn oxidizes the Mn4CaO 5 cluster, where the water splitting reaction happens. Once the four electrons have been extracted from the Mn 4CaO 5Nickelsen and Rengstl, 2013 cluster, two water molec ules are split into four protons and one oxygen molecule, and the electron transport chain is thereby initiated in PSII ( ; Shen, 2015 ). The first crystal structure of the PSII dimer was obtained by Zouni et al . ( Zouni et al., 2000 ) from thermophilic cyanobacterium at the resolution of 3.8 Å . This initial structure of PS II provided information on the position of the major PSII subunits and the position of Mn 4CaO 5Ferreira et al., 2004 cluster that catalyzes the water -splitting reaction. In subsequent studies, the resolution of the PSII structure increased gradually to 3.5 Å ( ), 3.0 Å ( Loll et al., 2005 ), and 2.9 Å ( Gusko v et al., 2009 ), which continuously improved our understanding of the structure of the whole complex regarding the side -chain orientation of amino acid residue s and a number of cofactors. In 2011, the resolution was significantly improved to 1.9 Å ( Umena et al., 2011 ). At this resolutio n, the electron density of individual atoms in the Mn 4CaO 5Umena et al., 2011 cluster w as clearly separated, and the coordination environment of the metal cluster was revealed. The presence of a large number of water molecules associated with various residues in t he PSII dim er was also revealed (). Although we have extensive knowledge ab out PSII structure and function , relativel y little is known about the assembly process of the PSII complexes. Recent genetic and biochemical studies indicated that PSII assembly is a highly ordered process that involves many cofactor s (Nixon et al., 2010 ; Rokka et al., 2005 ). Basically, PSII grows outward from the reaction center (RC), which consists of the D1, D2, cyt b559 Boehm et al., 2011 and PsbI subunits ( ; Keren et al., 2005 ). The RC complex serves as a scaffold for incorporation of CP47 and CP43, with concomitant attachment of other subunits and assembly factors (Sugimoto and Takahashi, 2003 ; Wei et al., 2010 ). After attachment of CP43, a light -driven assembly of the oxygen -evolving Mn 4CaO 5Dasgupta et al., 2008 cluster occurs ( ). Furthermore, PsbO, PsbP and PsbQ - the subunits that stabilize the Mn 4CaO 5Bricker et al., 2012 cluster, are attached to the lumenal side ( ). However, how the rest of the subunits incorporates into the complex is still un known. Thereafter, the active PSII monomer s in the thylakoid membrane will form dimers , with attachment of facilitating subunits, such as PsbI, PsbM and PsbW, and the peripheral antenna ( Kouril et al., 2012 ; Shi et al., 2012 ). Since the water -splitting reaction is extremely oxidative, PSII is highly prone to photo oxidative damage. To maintain the photosynthetic yield of PSII, efficient repair systems have evolved (Aro et al., 2005 ; Kato and Sakamoto, 2009 ). D1 is the most vulnerable PSII subunit with a high turnover rate ( Jarvi et al., 2015 ). Upon light -induced photodamage, D1 is degraded by the FtsH and Deg protease s on both the stromal and lumenal sides of the thylakoid membrane ( Fristedt et al., 2009 ; Kapri -Pardes et al., 2007 ; Schuhmann and Adamska, 2012 ). The newly synthesized D1 subunit is inserted cotranslationally into the complex in the stroma lamellae on the thylakoid membrane. After the repair cycle, PSII moves back to the grana region. This repair cycle is driven by the phosphorylation and dephosphorylation of the PSII core complex ( Jarvi et al. , 2015). Further elucidation of PSII water -splitting mechanism, assembly process and regulatory pathway s will be importa nt for better understanding photosynthesis and designing artificial system s capable of using sunlight energy. 1.2.3 PSI PSI catalyzes the last step of electron transport, the oxidation of plastocyanin in the thylakoid lumen and the reduction of FD in the chloroplast stroma. After reduction of FD, electrons are distributed among five pathways, with the majority of the electr ons used for NADPH production when CBB cycle is active. Other electron sinks include the reduc ing reaction catalyzed by nitrite reductase and sulfite reductase for nitrogen and sulfur assimilation, CEF when ATP production from LEF is insufficient, direct t ransfer of electron s to O 2Carmeli et al., 2007 when PSI is overly reduced, and thioredoxin reduction useful for many chloroplast enzymes as well as the regeneration of antioxidative systems ( ; Schottler et al., 2011 ). Among the four photosynthetic complexes, PSI is the one that undergoes the most drastic evolutionary remodeling ( Amunts and Nelson, 2009 ). In cyanobacteria, PSI functions as a trimer, with associated phycobilisome resid ing on top of thylakoid membrane as an additional antenna system. In eukaryotes however , PSI functions as a monomer, with associated LHC located within the thylakoid membrane. Consisting of 12 protein subunits per monomer and bind ing to a total of 96 chlorophylls ( Jordan et al., 2001), PSI in cyanobacteria is significantly smaller than its counterpart in higher plants. The PSI monomer in higher plants contains 15 subunits that constitute the catalytically active PSI core complex, and at least four bound LHCs forming the PSI antenna system (Jordan et al., 2001 ). Recently, the high -resolution structure of the PSI-LHCI supercomplex was resolved at 3.3Å and the exact position s of 173 chlorophylls and 15 carotenoids were assigned ( Amunts et al., 2010 ). The PSI reaction center (RC) is composed of two large and essential subunits , PsaA and PsaB, which bind 80 chlorophylls an d the vast majority of the redox -active cofactors. The PsaA -PsaB heterodimer catalyses the light -induced charge separation at the chl orophyll a special pair P700, followed by electron transfer via chlorophyll A 0, phylloquinone A 1, and the [4Fe -4S] cluster FX to the final two [4Fe -4S] cluster s, FA and F B. FA and F BSchottler et al., 2011 are bound to the PsaC subunit, which is positioned on the stromal side of PSI. PsaC associates with PsaD and PsaE to form a so -called fistromal ridgefl of PSI, which can later form a large ternary c omplex with FD and FNR on the top of PSI (Figure 1.3) (). Due to this large ternary complex protruding into the stroma, PSI is predominately residing in the stroma lamellae and rarely found in the grana stacks (Albertsson, 2001 ). The oxidize d P700 chlorophyll a dimer is reduced by plastocyanin, which interacts with PsaB, PsaF and PsaN for efficient plastocyanin oxidation ( Haldrup et al., 1999 ). The antenna complex of PSI in higher plants consists of four LHC proteins (LHCA 1-4) that bind to the reaction center core complex in the form of two adjacent heterodimer s, L HCA 1/4 and L HCA 2/3. T hese two heterodimers are arranged in a half -moon- shaped belt around one side of PSI, and have interactions with multiple PSI subunits , and figapfl chlorophylls on the surface of the PSI core complex (Amunts et al., 2010). On the opposite side of the L HCA belt, a nose -shaped structure is formed by PsaH, PsaI, PsaL and possibly PasO subunits ( Nelson and Yocum, 2006 ). This part of PSI, which functions in PSI tr imer formation in cyanobacteria, has been completely remodeled during the evolution in higher plants. In higher plants, the nose -shaped structure forms a docking site for at least one LHCII trimer during an adjusting pr ocess called fistate transitionfl, whic h is essential when plants are exposed to fluctuating light conditions (Bellafiore et al., 2005 ). Be sides, two recently identified antenna protein s in Arabidopsis, LHCA 5 and L HCA 6, were suggested to involve in supercomplex formation of PSI -LHCI with the NDH complex, although their exact docking position on PSI is not determined because neither was presen t in the high -resolution crystal in PSI structur al analysis due to their substoichiometric amounts ( Ganeteg et al., 2004 ; Klimmek et al., 2006 ). The specific function o f Lhca5 and L hca6 remains to be investigated. Although the knowledge about structure and component s of PSI has become more comprehensive and detailed, the biogenesis process of PSI is not well understood ( Ozawa et al., 2010 ). There are two obstacles for discovering the sequence of subunit integration into nascent PSI. First, the PsaA -PsaB heterodimer already constitutes nearly half of the PSI molecular mass (165 out of 390 kDa ), which makes it extremely difficult to resolve the small units attached to the heterodimer. Second, PSI assembly happens very rapidly. Although direct experimental data is lacking for the rapid assembly pathway from PsaA -PsaB heter odimer to intermediate complex, speculations were made ( Ozawa et al., 20 10). In the speculated process, PsaC is the first subunit to assemble onto PsaA -PsaB heterodimer after its binding to two [4Fe -4S] cluster s inside the PsaA -PsaB heterodimer. Subsequently, both P saD and PsaE bind to PsaC to complete the final formation o f the stromal ridge ( Ishikita et al., 2006 ; Nelson and Yocum, 2006 ). All the afore mentioned PSI subunits are critical for the PSI supercomplex formation , because they provide scaffold for further binding of other subunits and LHCs and mutation s in any of these subunits result in severe or even complete loss of the PSI supercomplex ( Schottler et al., 2011). Auxiliary proteins also play a critical role in PSI biogenesis. These auxiliary proteins, also called assembly factors, refer to the proteins that are not an inte gral part of PSI but can affect PSI biogenesis at man y levels. Generally, they are divided into two functional categories: (i) proteins involved in cofactor synthesis and/or forming into nascent complex, and (ii) chaperones that function as scaffold for assembly proteins or mediate protein -protein interactio n within the complex ( Schottler et al., 2011 ). Alb 3 mediate s the first step of PSI assembly , i.e. membrane insertion of PsaA and PsaB, by directly interacting with them. Al b3 is a member of the conserved OxaI/YidC family of membrane protein insertase s; in its absence, accumulation of PSI supercomplex is strongly reduced ( Pasch et al., 2005 ; van der Laan et al., 2005 ). Ycf3 is a plastid -encoded soluble protein that interacts with PsaA and PsaD and plays a role in stromal ridge formation; its absence leads to a complete loss of PSI. E vidence also exists that Ycf3 may mediate the rate -limiting step of PSI assembly ( Albus et al., 2010 ; Naver et al., 2001 ). Other important chap erones include Y3IP1, Ycf4 and Pyg7, whose loss -of function mutants show severe or complete loss of the PSI supercomplex ( Albus et al., 2010 ; Ozawa et al., 2009 ; Stockel et al., 2006 ). Other proteins important for PSI assembly include those involved in co -factor biogenesis and attachment , s uch as Apo1 and Hcf101 , both of which are involved in the biogenesis of the PSI -specific cofactor phylloquinone (Gross et al., 2006 ; Lohmann et al., 2006 ). The identification of these assembly factors shed light on the intricate process of the regulatory pathway of PSI biogenesis, which seems considerably more complex than previously thought and thus need s further inve stigations. 1.2.4 Cytochrome b6 Cytochrome bf 6f is a PQH 2Hasan et al., 2013 - PC reductase found in the thylakoid membrane in chloroplasts of higher plants and green algae and in cyanobacteria. It catalyze s the oxidation of PQ and the electron transfer between PSII and PSI complexes , whereby the proton gradient across thylakoid membrane is generated by coupled proton transfer (Figure1.3) (). Cyt b6f is a homo -dimer , with each monomer composed of 8 subunits that include four large and four small subunits. The large subunits contain the 25 kDa cytochrome b6 (PetB) that has a high potential heme group, the 32 kDa cytochrome f (PetA) with a c -type cytoch rome, the 19 kDa Rieske iron -sulfer protein (PetC) that contains a [2Fe -2S] cluster, and the 17 kDa subunit IV (PetD). The small subunits rang e from 3 to 4 kDa in size and include PetG, PetL, PetM and PetN, which together make the total molecular weight to 217 kDa (Hasan et al., 2013 ; Stroebel et al., 2003 ). Cyt b6f contains seven prosthetic groups essential for electr on transfer within the complex. The inter -mononer space between the Cyt b6Baniulis et al., 2013f dimer is occupied by lipids, which direct the heme -to-heme electron transfer through modulation of the intra -protein environment ( ; Cramer et al., 2005 ). The electron transfer reaction occurs through the Q cycle, where the electron from the PQH 2 is transferred through high - and low - potential pathways to PC, PSI and finally to generate NADPH. In addition, attachment of FNR to Cyt b6f was recently found to be important for CEF. When NADP + is not sufficient to accept electron s from reduced FD, they are returned to PQ and then Cyt b6Baniulis et al., 2009 f to reduce PC . M eanwhile the electron transfer creates proton transfer from stroma to lumen ( ; Laisk et al., 2005 ; Munekage et al., 2004 ). ATP is produced without generation of NADPH in CEF , there fore it is speculated that CEF help s maintain the proper ratio of ATP to NADPH needed for carbon fixat ion, especially when the ATP/NADPH is low under environmental stresses (Munekage et al., 2004 ). 1.2.5 ATP synthase ATP synthase is ubiquitous on energy producing membrane s such as chloroplast thylakoid membrane, mitochondrial inner membrane, and bacterial plasma membrane , and participat e in photosynthesis and respiration. The electron transport in photosynthesis and respiration is coupled with generation of proton gradient across the membrane, which activates ATP synthase to produce ATP from ADP and phosphate. The ATP synthase holoenzyme is composed of the soluble membrane -peripheral sector F 1 and the hydrophobic membrane -spanning sector F OGroth and Pohl, 2001 ( ; Stock et al., 1999 ; von Ballmoos et al., 2009 ). F1 consists of five subunits in a stoichiometry of 33111 - - 3 located in the center axis as a rotary shaft. Three key catalytic sites for ATP synthesis are - Abrahams et al., 1994 subunit, functionally important to confer catalytic cooperation within the three catalytic sites (; Bowler et al., 2007 ) 3 Gresser et al., 1982 hexagon first postulated by P.D. Boyer based on the analysis of the catalytic sites ( ). In 1997, H. Noji et al. verified this speculation using video - 331 Noji et al., 1997 core subcomplex (). In this experiment, the F1 subunit from the thermophilic Bacillus PS3 was used, and later the rotation of the E. coli F 1Omote et al., 1999 () and chloroplast F 1 (CF 1Hisaboria et al., 1999 ) () was demonstrated using the same method, thereby the rotation model was confirmed in all major F 1The membrane -spanning F -ATPase s. O is composed of a 1b2c8- 14 . Different numbers of the c subunit were reported for complexes from different organelles, such as chloroplasts and mitochondria . A high resolution structure of the entire F OJunge and Nelson, 2015 is still lacking ( ). A common feature of the F O portion of ATP synthase from different organisms is the homo- oligomeric ring of the c -subunit, which is the only portion of F OMeier et al., 2005 with a high resolution structure (; Stock et al., 1999 ; Vollmar et al., 2009). The c -ring faces the a -subunit, which is a four -helix bundle plus one transmembrane helix. The a -subunit associates with two transmembrane helix es of the b -subunits that connect F O 3 hexagon of F 1. All three subunits are required for promoting proton conduction by F OMeier et al., 2005 . The c -subunit carries an ionizable residue in the middle of the membrane, around which the pocket for binding of proton is located. The copy number of c -subunits is believed to determine the proton -to-ATP ratio. Sinc e one proton binds to one c -subunit, the more c -subunits there are , the more protons are needed to produce one ATP. There are 8 c-subunits in bovine mitochondria, 10 in yeast mitochondria, and 14 in chloroplast s, which is consistent with the level of ATP demand in each organism. Organism s with higher proton motive force (PMF) benefit from running at high -speed gea r (low c -subunit number), while those expos ed to variable PMF (chloroplast) benefit from high torque and low -speed ge ar (high c -subunit numbe r) (; Stock et al., 1999 ; Vollmar et al., 2009 ). In higher plants, photosynthesis takes place in the thylakoid membrane, whereas respiration occurs in the crista membrane of mitochondria. To prevent futile consumption of chloroplast ATP by mitochondria, the chloroplast enzyme is downregulated in the dark (Petersen et al., 2012 ; Saroussi et al., 2012 ). Therefore, the low PMF under dark and high PMF under light constitutes a key regulation of ATP synth ase activity. Chloroplast F OF1Kim et al., 2011 is regulated by the thioredoxin -dependent thiol -activation. Two cysteine residues in the s of modulation ( ). In are involved in ATP synthase activity regulation (Saroussi et al., 2012 ). Last ly, the photosynthe tic t hylakoid membrane contains PSII, PSI, Cyt b6Menke, 1962 f, and ATP synthase with a relative ratio 2:2:1:1, thus it is highly crowded ( ; Stolz and Walz, 1988 ). Each thylakoid is a highly- folded spherical bleb, in which hundreds of electron transport chain complexes and ATP synthase molecules are electrically coupled with each other. Biochemical analyses and electron microscopy established the heterogeneous lateral distribution of t he membrane proteins (Figure1.3) ( Mustardy et al., 2008). PSI and ATP synthase are located mainly in the stroma lamellae, and also in the top and bottom surface of grana. PSII is almost exclusi vely found within the grana area , and Cyt b6Albertsson, 2001 f is found at the connection between grana and lamellae ( ; Daum et al., 2010 ). The separation of PSII and PSI are thought to be beneficial for efficient light distribu tion and to facilitate the PSII repair cycle ( Nel son and Junge, 2015 ). 1.2.6 Adaptive mechanisms to changing light conditions Due to diurnal and seasonal changes , p hotosynthetic organisms are subjected to a constantly changing environment. As one of the most important input for photosynthesis, light is shifting considerably in intensity and spectral quality. To adjust to changing light conditions , plants have evolved numerous biochemical and developmental processes, such as photoreceptor -dependent shade avoidance, movement of leaves and chloroplast s, and changing antenna size through genes expression regulation and proteolysis ( Rochaix, 2014). Other environmental parameters, such as CO 2 concentration, water availability, nutrient limitation and temperature variation can also significantly affect the need for ATP and NADPH ( Kaiser et al., 2015 ). Regulating the operation of the photosynthetic machinery accordingly is necessary to maintain optimal photosynthetic efficiency and protect organisms from photodamage ( Rochaix, 2014 ). One of the key components in the adaptive processes is the light harvesting complex, which is involve d in both efficient light capture for driving the primary photochemical reactions, and sensing and dissipating excessive light. To achieve this goal, photosynthetic organisms have developed two main strategies ( Horton and Ruban, 2005 ). The first strategy is to regulate the amount of absorbed light energy that is used for the photochemical reaction by dissipating excess ive absorbed energy as heat when light exceeds the capacit y of the photochemical machinery. This process is also called energy -dependent nonphotochemical quenching (qE -NPQ) ( Niyogi and Truong, 2013 ). The second strategy balances the excitation energy absorbed by LHCII and LHCI antenna systems and adjusts the electron transfer chain upon fluctuating light to optimize photosynthetic electron flow, by re -distributing of the mobile LHCII antenna between PSII and PSI. This process is calle d state transition ( Horton, 2012 ; Wollman, 2001 ). Both strategies will be discussed in detail . 1.2.7 NPQ Upon light absorption by the antenna system, a chlorophyll ( Chl) a molecule is excited to singlet -state ( 1Chl*). The energy released during the return of the singlet -state Chl a to ground state could be used for photochemistry, emitted as chlorophyll fluorescence, dissipated as heat, or used for generat ing triplet state ( 3Chl*), which is very dangerous to the organism because it could be used to generate high ly damaging singlet oxygen ( 1O2Muller et al., 2001 *) ( ). The heat dissipation process is associated with a decrease of chlorophyll fluorescence, it is there fore referred to as nonphotochemical quenching (NPQ). Based on the relaxation kinetics in the dark, there are at least three components of NPQ: (i) energy -dependent quenching ( qE), which depends on the proton gradient across the thylakoid membrane and relax es within seconds; (ii) qT, which is caused by state transitions and relaxes within minutes ; and (iii) qI, which is induced by photoinhibition of PSII and relaxes relatively slow (Goss and Lepetit, 2015 ). As mentioned above, qE is triggered by light -induced proton gradient across the thylakoid membrane . Proton deposition and decrease of pH in the thylakoid lumen lead to the activation of the violaxanthin de -epoxidase named NPQ1, which coverts violaxanthin to zeaxanthin (Havaux et al., 2000 ). This reaction is a part of the xanthophyll cycle, and it is reversible by zeaxanthin epoxidase named NPQ2 ( Niyogi et al., 1998 ). Z eaxanthin subsequently binds to LHCII and induces LHCII ™s conformational changes , thereby switch ing LHCII from the light -harvesting state to photoprotective state, in which light excitation energy is harmlessly dissipated as heat ( Johnson et al., 2008 ). Beside s the enzymes that are involved in zeaxanthin conversion in the xanthophyll cycle, several LHCII components have been found necessary for generation of NPQ in Arabidopsis (Ruban et al., 2007 ). The absence of CP29 or CP24 decreases qE by 30% and 50%, respectively (Andersson et al., 2001 ; Kovacs et al., 2006 ). L oss of the major L HCB 1 and LHCB 2 protein s decreases qE by 35% ( Andersson et al., 2003 ). These results confirmed that LHCII is the major site for qE, and also indicate d that additional components and sites exist for qE generation. Besides the npq1 and npq2 mutants, which were identified in a genetic screen of mutants with altered chlorophyll fluorescence properties, another component named Psb S (identified in mutant npq4) was found essential for qE generation (Li et al., 2000 ). Psb S belongs to a superfamily of LHC proteins and contains four transmembrane domains. It acts as a sensor of the lume nal pH and stimulates q E rapidly. The protonation of Psb S is presumably required for the activation Psb S-dependent activation of qE, and it is thought to promote rearrangement of the PSII supercomplex for efficient heat dissipation ( Holt et al., 2004 ; Li et al., 2000 ; Niyogi et al., 2005 ). Although PsbS is necessary for qE in vivo , isolated thylakoids lack ing Psb S still exhibit qE in the that direction protonation of the LHC antenna proteins by extremely high S ( Sylak -Glassman et al., 2014 ). 1.2.8 State transition The light harvesting systems of PSII and PSI have different chlorophyll composition s. LHCII is enriched in chlorophyll b, whereas LHCI is rich in chlorophyll a that can absorb far -red light ( Croce et al., 2002 ; Lama et al., 1984 ). Changes in light quality and quantity can thus alter the distribution of absorbed light excitation energy between PSII and PSI ( Yokono et al., 2011 ). Under fluctuating light conditions, the fistate transiti onfl is activated, during which the LHC system is able to sense the redox poise of the PQ pool through a signal network consisting of Cyt b6f, protein kinase and phosphatase . Specifically, upon over -excita tion of PSII relative to PSI, the PQ pool is high ly r educed ( Minagawa, 2011 ). The redox state of PQ is sensed by a protein kinase STN7, which is activated by binding of PQH 2 to Cyt b6Mullineaux and Emlyn -Jones, 2005 f and subsequently phosphorylates a portion of LHCII. The phosphorylated LHCII disassociate s from PSII and b inds to PSI, thereby readjusting the excitation energy between PSII and PSI and restor ing the redox poise of the PQ pool ( ). This process is reversible , where oxidation of the PQ pool by PSI absorbed light result s in deactivation of STN7 (Bellafiore et al., 2005 ) and the phosphatase PPH1 subsequently dephosphorylate s LHCII to return LHCII to PSII ( Shapiguzov et al., 2010 ). STN8 is a homologue of STN7 that carries partially overlapping function ( Vainonen et al., 2005 ) and its counterpart phosphatase called PBCP can dephosphorylate LHCII (Samol et al., 2012 ). Th us, the two kinases STN7 and STN8 and two phosphatases PPH1 and PBCP constitute the central system for state transition in higher plant. Recent studies indicate that the mobile LHCII without binding to PSII or PSI acts as a highly efficient antenna for PSI under various light conditions and remains associated with PSI after long -term acclimation. The mobile LHCII returns to PSII only under specific conditions, such as after a sudden increase in light intensity or when PSI is overexcited by far -red light ( Wientjes et al., 2013 ; Wientjesa et al., 2012 ). 1.2.9 Cyclic electron f low The ATP and NADPH generated in light reaction s are mainly consumed in CO 2 assimilation, which theoretically requires an ATP -to-NADPH ratio of 1.5. Photorespiration, which inevitably occurs in ambient air , raises this ratio to 1.66 (Osmond, 1981 ). However , the ATP -to-NADPH ratio provided by LEF is about 1.33, which is too low to sustain the CBB cycle and other metabolism (Kramer and Evans, 2011). CEF is considered a major compensation pathway to make up the deficiency of ATP supply in normal and many stress conditions. In this pathway (Figure1.3) , electro ns are recycled from NAD(P)H or FD to PQ, and the coupled proton transport to the lumen A main difference between CEF and LEF, is that CEF is exclusively involved in ATP synthesis whereas LEF generates both ATP and NADPH . In addition to ATP produc partially contributed by CEF, acts as a key factor in inducing rapid response to fluctuating light intensity and high light (Hasan et al., 2013 ; Heber and Walker, 1992 ; Iwai et al., 2010 ; Zhang et al., 2001 ). The mechanism of CEF remains a controversial subject . T wo major pathways have been proposed and studied (Figure1.3) . In the first pathway , electrons are transferr ed to PQ by the plastid encoded PQ reductases NDH s, which are homologues to subunits of the mitochondrial NADH dehydrogenase complex (complex I) (Matsubayashi et al., 1987 ). The cyanobacteria l ndhB mutant, which is defect ive in a subunit of the NDH complex , has impaired CEF activity ( Ogawa, 1991 ). Knockout lines of the tobacco NDH genes displayed clear alternation of electron transport ( Shikanai et al., 1998 ). Although no obvious growth phenotype was observed in NDH knockout tobacco lines under normal condition s,, the se mutants exhibited compromised tolerance to various environmental stresses, such as high light (Miyake et al., 2004 ), drought ( Hundhausen et al., 2005 ) and high and low temperature s ( Wang et al., 2006 ). These results suggested that the NDH complex is involved i n alleviating oxidative stress, which is probably generated from PSI associated excessive energy. The second key pathway is sensitive to antimycin and involves two thylakoid proteins, PGR5 (proton gradient regulation 5) and PGRL1 (PGR -like 1). PGR5 is a small soluble protein without any known motif like the typical electron -binding prosthetic motif, and thus is believed to be indirectly involved in CEF as a regulator (Munekage et al., 2004 ; Munekage et al., 2002 ). PGRL1 is a thylakoid transmembrane protein that physically interacts with PGR5 and transiently interacts with PSI, thus serv ing as an anchor protein to bring PGR5 to PSI ( DalCorso et al., 2008 ). Recently, PGRL1 has been biochemically characterized as the long -sought FD-PQ reductase (FQR) that accept s electron from FD in a PGR5 -de pendent manner, and reduces PQ in an antimycin -sensitive fashion ( Hertle et al., 2013). Genetic studies showed that pgr5 and pgrl1 mutants exhibited highly similar CEF perturbatio n, NPQ reduction, and lower P700 +Munekage et al., 2004 -to-P700 ratio under high light, which further confirm ed their participation in CEF (; Munekage et al., 2002 ). Meanwhile , NDH activity is not inhibited in pgr5 mutant background, suggesting that the PGR5 -PGRL1 pathway is independent of the NDH-dependent pathway (DalCorso et al., 2008 ; Kukuczka et al., 2014). The crr2 pgr5 double mutant, which is defective in both NDH - and PGR5 - dependent CEF, lost almost all of the PSI CEF activity, indicating that these two key pathways contribute to major production of CEF. Meanwhile, t he double mutant exhibited strongly delayed growth, suggesting that CEF around PSI is essential for efficient photosynthesis even under normal growth condition s (Hashimoto et al., 2003 ; Munekage et al., 2004 ). 1.3. Aims of dissertation research My dissertation is aimed at defining the role of peroxisomes in modulating environmental stress response and photosynthesis at a systems level. Progress in proteomics studies of peroxisomes and in silico analysis, followed by in vivo targeting verification largely increased the number of known peroxisomal proteins in Arabidopsis. Increasing evidence indicated the roles of peroxisomal proteins in environmental stress response, and the metabolic connections between peroxisomes and chlor oplasts, prompting us to check into these aspects systematically and in more depth. My first aim was to use transcriptomic analysis combined with mutant screens to identify peroxisomal proteins involved in stress response. In Chapter 2, I examined the tran scriptional regulation of all the genes encoding peroxisomal proteins in Arabidopsis across different developmental stages and under various environmental stress conditions. Developmental stage - and stress - specific gene expression patterns were identified . Two peroxisomal proteins, LON2 protease and the photorespiratory enzyme hydroxypyruvate reductase 1 (HPR1) , were found necessary in conferring robust drought resistance. My second aim was to investigate the role of peroxisomal metabolism in modulating ph otosynthesis. In Chapter 3, I used the Dynamic Environment Phenotype Imager (DEPI) to screen 147 mutants of 104 Arabidopsis genes encoding peroxisomal proteins , hoping to identify mutants with photosynthetic defects under dynamic light conditions. Our syst ematic screen identified a number of peroxisomal proteins required for robust photosynthesis efficiency under dynamically changing light . These include peroxisomal biogenesis and division proteins, photorespiratory proteins and an NAD + transporter protein PXN, which was later found to be an addition al player in photorespiration. Further characterization of photorespiratory mutants suggested an integrated model that depicts the molecular events that occur as a result of the block of photorespiration: 1) increased level of phosphoglycolate leads to the inhibition of the activity of an enzyme involved in CBB cycle; 2) decreased amount of glycerate slows down the CBB cycle, and leads to accumulation of unused stromal ATP. Accumu lation of stromal ATP inhibits ATP synthase conductivity and subsequent higher proton motive force ( pmf ) and qE; and 3) enhanced oxidative stress causes compromised photosystem integrity, reduced photosystem subunit abundance and enhanced photoinhibition. APPENDIX Figure 1.1. Some peroxisomal metabolic pathways share a core set of -oxidation enzymes. (Modified from Hu et al., 2012) FA -oxidation (center box) involves peroxisomal import of FAs by the ABC transporter CTS/PXA1/PED3, activation of FAs by acyl -activating enzyme s LACS6 and LACS7, -oxidation catalyzed by a core set of enzymes including acyl -CoA oxidase (ACX), multiple function protein (MFP) and 3-ketoacyl- CoA thiolase (KAT). After each cycle of -oxidation , the substrate is shortened by two carbons, which are used to generate acetyl -CoA for further energy -providing metabolism in gluconeogenesis. Metabolism of IBA to Figure 1.1. (cont™d) IAA (left box) and biosynthesis of JA (right box) utilize the core enzymes in FA -oxidation. After import and activation, IBA -CoA undergoes one round of FA -oxidation to produce IAA, and the JA intermediate, OPC8:0 -CoA, undergoes three rounds of -oxidation to generate JA. IAA and JA are then exported to the cytosol. Metabolites involved are shown in yellow boxes, and the key enzymes are shown in orange boxes. Blue arrow s indicate the metabolic flow, and dashed arrow s indicate further biologica l function of the metabolites. Figure 1.2. Peroxisomes play a central role in photorespiration. Photorespiration is accomplished by the cooperation of peroxisomes, chloroplasts and mitochondria. It starts with phosphoglycolate , which is the product of Rubisco oxygenase activity on ribulose -1,5- bisphosphate (RuBP), and ends with the production of phosphoglycerate as the substrate for the Calvin -Benson- Bassham (CBB) cycle. The enzymes directly involved in metabolic conversion and metabolite transport (in Figure 1.2. (cont™d) red boxes ) include phosphoglycolate phosphatase PGLP1 , glycolate glycerate transporter PLGG1, glycolate oxidase (GOX) , glutamate: glyoxylate aminotransferase (GGT) , serine hydro xymethyltransferase (SHMT), glycine decarboxylase (GDC) , serine: glyoxylate aminotransferase (SG T), hydroxypyruvate reductase (HPR) , peroxisomal malate dehydrogenase (PMDH) and glycerate kinase GLYK . Figure 1.3. Overview of photosynthetic complexes and processes on the thylakoid membrane. (Modified from Rochaix, 2014) Linear electron flow (LEF) and cyclic electron flow (CEF) are shown in red and blue curved lines, respectively, with arrows indicating the direction of the flow. The LEF involves major photosynthetic complexes photosystem II ( PSII ), cytochrome b6f complex (Cyt b6f), photosystem I (PSI) and the ATP synthase , as well as small mobile electron carriers such as plastoquinone (PQ) , plastocyanin (PC), ferredoxin (FD) and FD -NADP + oxidoreductase (FNR ). The electron is used to generate NADPH. CEF, on the other hand, is only driven by PSI. Besides complexes shared with LEF, CEF also involves specific components, including NADPH dehydrogenase complex (NDH), an unknown soluble protein PGR5 and a FD- PQ oxidoreductase PGRL 1. Both LEF and CEF contribute to Figure 1.3. (cont™d) proton transfer to the lumen, which creates proton gradient across the thylakoid membrane. ATP synthase is activated by the proton gradient and generate ATP from ADP and phosphate. NAPDH and ATP are used by the CBB cycle. Later al heterogeneity of the thyla koid membrane is shaped by preferential distribution of each complex. 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CHAPTER 2 Using co -expression analysis and stress- based s creens to uncover Arabidopsis peroxisomal proteins involved in drought r esponse _________________________ Data in this chapter has been published in: Li, J. and Hu, J. (2015) Using co -expression analysis and stress -based screens to uncover Arabidopsis peroxisomal proteins involved in drought response. PL oS ONE 10 (9): e0137762doi:10.1371/journal.pone.0137762 2.1. Abstract Peroxisomes are essential organelles that house a wide array of metabolic reactions important for plant growth and development. However, our knowledge regarding the role of peroxisomal proteins in various biological processes, including plant stress respon se, is still incomplete. Recent proteomic studies of plant peroxisomes significantly increased the number of known peroxisomal proteins and greatly facilitated the study of peroxisomes at the systems level. The objectives of this study were to determine whether genes that encode peroxisomal proteins with related functions are co -expressed in Arabidopsis and identify peroxisomal proteins involved in stress response using in silico analysis and mutant screens. Using microarray data from online databases, we performed hierarchical clustering analysis to generate a comprehensive view of transcript level changes for Arabidopsis peroxisomal genes during development and under abiotic and biotic stress conditions. Many genes involved in the same metabolic pathways exhibited co -expression, some genes known to be involved in stress response are regulated by the corresponding stress conditions, and function of some peroxisomal proteins could be predicted based on their co -expression pattern. Since drought caused express ion changes to the highest number of genes that encode peroxisomal proteins, we subjected a subset of Arabidopsis peroxisomal mutants to a drought stress assay. Mutants of the LON2 protease and the photorespiratory enzyme hydroxypyruvate reductase 1 (HPR1) showed enhanced susceptibility to drought, suggesting the involvement of peroxisomal quality control and photorespiration in drought resistance. Our study provided a global view of how genes that encode peroxisomal proteins respond to developmental and environmental cues and began to reveal additional peroxisomal proteins involved in stress response, thus opening up new avenues to investigate the role of peroxisomes in plant adaptation to environmental stresses. 2.2. Introduction Peroxisomes are small and single membrane -delimited organelles that house numerous oxidative reactions connected to metabolism and development. These organelles are dynamic in nature, as their abundance, morphology and protein composition can be remodeled in response to developmental and environmental cues to adapt to the need of the organism (Hu et al., 2012 ; Pieuchot and Jedd, 2012 ; Smith and Aitchison, 2013 ). Plant peroxisomes perform conserved functions such as -oxidation of fatty acids and related metabolites and detoxification of reactive oxygen species (ROS), as well as plant -specific functions including photorespiration and metabolism of hormones such as jasmonate (JA) and auxin. Peroxisomes are crucial to virtually every developmental stage in plants, from embryogenesis, seedling development, vegetative and reproductive development, to senescence, and were recently shown to be involved in plant response to biotic and abiotic str esses (Hu et al., 2012 ; Kaur et al., 2009b ). The number of known peroxisomal proteins has risen to ~170 in Arabidopsis, l argely due to recent peroxisomal proteome analyses followed by in vivo protein targeting verifications (Kaur and Hu, 2011 ). Peroxisomes possess many oxidative reactions that produce H 2O2Del Rio, 2011 , as well as ROS -scavenging enzymes such as catalase and ascorbate -glutathione cycle enzymes (; Kaur et al., 2009b ). ROS is a key component in stress responses Kotchoni and Gachomo, 2006 (). Willekens et al., 1997 Suppression of catalase 1 in tobacco resulted in necrotic lesions in high light and increased susceptibility to paraquat, salt and ozone (). Mutants of Arabidopsis catalase 2 develop photoperiod -dependent leaf lesions (Queval et al., 2007 ). Evidence from melon, Arabidopsis and tobacco suggested the involvement of several peroxisomal photorespiratory enzymes, e.g., hydroxypyruvate reductase (HPR), serine:glyoxylate aminotransferase (SGT), alanine:glyoxylate aminotransferase (AGT), and glycolate oxidase (GOX) in immune response, possibly through ROS production (Okinaka et al., 2002 ; Rojas et al., 2012a ; Taler et al., 2004 ). Peroxisomes are also involved in stress response through mechanisms other than ROS homeostasis. Arabidopsis Ca2+ Coca and San Segundo, 2010-dependent protein kinase CPK1 is physically associated with peroxisomes and functions in a SA -dependent signaling pathway that leads to plant resistance to both fungal and bacterial pathogens (; Dammann et al., 2003 ). Arabidopsis PEN2 is a peroxisome -associated myro sinase involved in callose deposition and glucosinolate hydrolysis necessary to generate antimicrobial products, thus is required for plant resistance against a broad spectrum of nonhost fungal pathogens, (Bednarek et al., 2009 ; Clay et al., 2009 ; Lipka et al., 2005 ; Maeda et al., 2009 ; Westphal et al., 2008 ). Furthermore, JA biosynthetic enzymes, some of which reside in peroxisomes, have been shown to affect systemic acquired resistance (SAR) to varying degrees (Spoel and Dong, 2012 ). It was sugges ted that the final step of SA biosynthesis, i.e., cinnamate to SA via the reduction of two carbons, may occur Œoxidation in the peroxisome (Reumann, 2004 ), thus making the peroxisome a potential player in SAR signaling. Interestingly, some virus species can hijack peroxisomes for viral RNA replication, causing the proliferation of peroxisome -like vesicle structures and leading to plant necrosis (McCartney et al., 2005 ; Rochon et al., 2014), which adds another layer of peroxisomal involvement in plant -pathogen interaction. Despite these findings, there are still substantial knowledge gaps in the role of peroxisomes in stress response and how the functions of these peroxisomal proteins may be connected. To further identify peroxisomal proteins involved in plant response to various stress conditions, a peroxisome -centered systematic approach is needed. Recent advances in genome -wide transcriptomic and gene ontolo gy enrichment analyses have provided valuable information on gene functions and mechanisms of biological processes. An important finding from these analyses is that genes functioning in the same pathway are often co -regulated by shared transcriptional regulatory systems and thus co -express across development and/or under many stress conditions (Schmid et al., 2005 ). To this end, we performed a genome -wide transcriptomic analysis of genes that encode peroxisomal proteins in Arabidopsis, trying to determine whether peroxisomal genes involved in the same biochemical pathways are co -expressed and whether we could identify new per oxisomal proteins involved in stress response using this type of in silico analysis. We followed up the in silico analysis with a pilot drought- based mutant screen, which identified the role of the peroxisomal LON2 protease and the photorespiratory enzyme hydroxypyruvate reductase 1 (HPR1) in drought resistance. Our study marks the beginning of systematic identifications of peroxisomal proteins involved in plant adaptation to stresses. 2.3. Result 2.3.1. Co-expression analysis of genes that encode peroxisom al proteins during development and in response to stresses Microarray datasets containing expression data of Arabidopsis peroxisomal genes from various tissues at different developmental stages and under biotic and abiotic stresses were downloaded from the AtGenExpress database and NCBI Gene Expression Omnibus (GE O) database, respectively (Table 2.1 ). Developmental data were obtained from different tissues from seedlings, adult and senescing leaves, flowers, and siliques and seeds at various maturation stages. Abiotic stress conditions included high light, cold, hypoxia, drought, salt , and the major stress hormone abscisic acid (ABA). Biotic stresses included the bacterial pathogen Pseudomonas syringae pv. tomato ( pst ) DC3000, fungal pathogen Botrytis cinerea , and Pathogen- Associated Molecular Patterns (PAMPs) such as the 22 -amino -acid fragment of bacterial flagellin , flg22, the 18- amino -acids fragment bacterial elongation factor, elf18, and the fungal elicitor chitin ( Table 2.1). Expression profiles of 160 peroxisomal genes (Table 2.2 ) were extracted from the whole-genome expression profile, clustered by hierarchical clustering analysis based on the extent of co -expression, and visualized by heatmaps. Not surprisingly, many peroxisomal genes that function in the same metabolic pathways are co -regulated during d evelopment ( Fig ure 2.1 ). For example, genes that encode glyoxylate cycle enzymes isocitrate lyase (ICL), malate synthase (MLS), and citrate synthase 1 (CSY1) are clustered together and co -up- regulated during seed maturation but co -repressed in other develo pmental stages ( Figure 2.1). This is consistent Œoxidation product acetyl -CoA to succinate and malate to be used for gluconeogenesis, is primarily if not exclusively active in seeds and early seedling development (Hu et al., 2012 ; Pracharoenwattana and Smith, 2008 ). In agreement with their roles in photo respiration, which recycles 2 -phospho glycolate produced by the oxygenase activity of Ru bisco back to the CBB cycle ( Bauwe et al., 2010), the expression of genes for the peroxisomal photorespiratory enzymes hydroxypyruvate reductase 1 (HPR1), glycolate oxidase 1 and 2 (GOX1 and GOX2, which are indistinguishable in microarrays due to high sequence identity), and peroxisomal malate d ehydrogenase MDH2 is high in vegetative tissues but diminished during seed development. In contrast to these three clustered genes, genes that encode two other photorespiratory enzymes, glutamate: glyoxylate aminotransferase 1 (GGT1) and alanine: glyoxylate aminotransferase 1 (AGT1), are expressed during seed development as well, indicating that photorespiration may not be the only process that these two enzymes participate. Interestingly, genes that encode the JA biosynthe tic enzymes 12-oxophytodienoate reductase 3 (OPR3) and OPC -8:0 CoA ligase 1 (OPCL1) , disease related protein PEN2, and the small heat shock protein ACD31.2 are clustered together and also co -expressed with the photorespiration genes HPR1 , GOX1/2 and MDH2 throughout development. This patter n indicates that these stress -related and development- related (in the case of JA biosynthesis) genes might be under similar regulatory circuitry as those photorespiration genes. As the major H 2O2 detoxification enzymes, the three catalases are mostly constitutively expressed throughout development (Figure 2.1 ). Transcriptional reprogramming during stresses is an important mechanism to confer stress tolerance (Gehan et al., 2015 ; Yamaguchi -Shinozaki and Shinozaki, 2006 ). Many genes that encode peroxisomal proteins are significantly regulated by abiotic stresses ( Figure 2.2A). Among them, the small heat shock protein -encoding gene AtHsp15.7 showed >150 -fold increase in expression under high light (Figure 2. 2B) and had to be removed from the heatmap in Figure 2.2A to prevent it from masking the changes in other genes in the heatmap. Genes encoding the peroxisomal proliferation factors PEX11b, PEX11c and PEX11d are all up -regulated by hypoxia (Figure 2. 2A), which is consistent with a previous finding that hypoxia stress can rapidly stimulate peroxisomal ext ension over endoplasmic reticulum (Sinclair et al., 2009 ). CAT2 and CAT3 expressions are also significantly up -regulated during drought stress (Figure 2. 2A), consistent with their role as major ROS detoxification enzymes in stress response (Kaur et al., 2009a ). The glyoxylate cycle genes ICL , MLS and CSY1 are again clustered ( Figure 2.2A), suggesting the tight regulation of this pathway by abiotic stress factors. Genes encoding the photorespiration enzymes GOX1/2, HPR1, MDH2, AGT1 and the chloroplast/peroxisome dual localized organelle division protein dynamic related protein 5B (DRP5 B) are clustered ( Figure 2. 2A), raising the interesting possibility that photorespiration and the proliferation of peroxisomes are co -regulated during plant adaptation to abiotic stresses. In response to biotic stresses, genes for some peroxisomal proteins previously shown to be involved in defense exhibited strong transcriptional reprogramming. For example, PEN2 ( Penetration 2 ) is induced by two PAMPs, flg22 and chitin (Figure 2. 3), support ing its major role as a myrosinase in PAMP -triggered immunity (Clay et al., 2009 ; Lipka et al., 2005 ). The two JA biosynthetic genes OPR3 and OPCL1 are co -up- regulated by flg22, chitin , P. syringae and B. cinerea (Figure 2. 3), consistent with JA™s role as an important defense hormone (Browse, 2009 ). Interestingly, photorespiratory genes such as HPR1 , CAT2 , GOX1/2 , MDH2 , AGT1 and GGT2 are co -down- regulated by elf18, P. syringae and B. cinerea ( Figure 2. 3), which is in agreement with the idea that photorespiration may play a defense role against pathogens through H 2O2Sorhagen et al., 2013 -dependent and -independent metabolism ( ). The peroxisomal elongation factor gene PEX11b is again co -expressed with several photorespiratory genes during biotic stresses (Figur e 2.3), which is in accordance with its co -expression with photorespiratory genes in response to light (Kaur et al., 2013 ) and the role of PEX11b in inducing peroxisomal proliferation during dark -to-light transition (Desai and Hu, 2008 ). This data also indicated a potential need to increase peroxisomal abundance during pathogen defense. 2.3.2. A drought tolerance mutant screen revealed the role of the LON2 protease and the photorespiratory enzyme hydroxypyruvate reductase 1 (HPR1) in drought response Based on the rule of figuilt -by-associationfl (Schmid et al., 2 005), those peroxisomal genes that showed significant up -regulation of transcript levels by some stresses may have a potential to play a role in these specific conditions. To test this hypothesis, we decided to choose a stress condition, under which significant regulation of expression is seen for the highest number of peroxisomal genes, to screen for mutants with altered response. Among the abiotic and biotic stress conditions examined, drought and the bacterial PAMP elf18 trigger expression changes to the highest number of peroxisomal genes ( Figure 2. 4). Drought is one of the most common environmental stresses that limit plant growth and development. Plants have evolved sophisticated adaptive drought tolerance mechanisms, including increased level of water transporting capacity, decrease of water evaporation , up-regulation of osmolytes and chaperone proteins, activation of Ca2+ Zhu, 2002 -dependent, ABA -dependent and other signaling pathways, and regulation of the transcript levels of the genes involved (). Mutant plants defective in these processes may exhibit increased drought sensitivity, such as increased water loss and ion leakage, decrease of photosynthesis rate, degradation of chlorophyll, and eventually cell death and plant withering (Zhu, 2002 ). As such, we used a drought tolerance assay as an initial screen to test the prediction from in silico analysis. We have a collection of Arabidopsis mutants, which has facilitated discovering functions of newly identified peroxisomal proteins in previous studies (Cassin -Ross and Hu, 2014a , b; Quan et al., 2013 ). To identify peroxisomal proteins involved in drought stress response, we first selected 26 mutants for 18 genes, most of which showed transcript level changes under drought or the drought stress hormone ABA. These included the up -regulated genes CAT2 , GOX3 , Hsp15.7 , CSY3 , Macrophage Migration Inhibitory Factor 1 (MIF1 ) and LON2 protease, and the down -regulated genes polyamine oxidase PAO2 , thiolase KAT5 and acyl -CoA activating enzyme AAE14. We also included mutants of proteins involved in major peroxisomal pathways (photorespiration and fatty acids -oxidation) but do not show obvious changes in transcript levels under drought , i.e. hpr1 , gox1 , acx3 , acx6 , and acx1 acx5 . Mutants of mildly regulated genes, such as peroxisomal NAD + For an efficient and quantitative drought tolerance assessment, we used the photosynthetic efficiency F transporter PXN and beta -hydroxyisobutyryl- CoA hydrolase CHY1 were assayed as well ( Table 2.3 ). v/Fm as a drought susceptibility indicator in our screen. Each mutant was grown in the same pot with the wild type plant for 3.5 weeks with periodic irrigation, followed by an 18 -day drought period, at the end of which F v/FmXiong et al., 2002 was measured. The positive control, ABA biosynthetic mutant aba1 ( ), and mutants for the LON2 protease and photorespiratory enzyme HPR1 , showed statistically significant decrease in F v/FmThe lon2 and hpr1 mutants were further analyzed to assess defects in drought resistance. Prior to drought treatment, lon2 and hpr1 mutants exhibited similar F after drought treatment ( Figure 2.5). v/Fm values to that of the wild type (Fig ures 2.6 A and 2.6 B), suggesting that the drought sensitive phenotypes we observed were specific to drought stress and not a result from general growth defect. Compared with watered plants and drought -treated wild type plants, drought -treated lon2-2 , hpr1-1 and hpr1-2 displayed an age -dependent gradient of photosynthetic defect, which was stronger in older leaves and milder in young leaves (Fig ure s 2.6 C and 2.6 D). These mutants also showed defects in other drought stress indicators, including reduced anthocyanin induction (Figure 2.6 F), accelerated chlorophyll degradation (Fig ure 2.6G), and lower relative water content (Figure 2.6 H). 2.4. Discussion We have constructed peroxisome -centered transcriptomic heatmaps using Arabidopsis microarray data from various developmental stages and under biotic and abiotic stresses. Results obtained from the in silico analysis not only showed correlation between protein function and expression regulation for many proteins with known function, but also provided information from which previously unknown roles may be inferred for some peroxisomal proteins. For example, out of the two peroxisomal MDH isoforms, MDH2 is tightly co -expressed with HPR1 and GOX1/2 , suggesting that MDH2 is the major MDH isoform that functions in photorespiration. Among all the genes analyzed, AtHsp15.7 , shows the strongest up -regulation by high light, suggesting that the small heat shock protein Hsp15.7, which was shown to be a stress -inducible constituent of the peroxisome (Ma et al., 2006 ), may facilitate the re -folding of proteins that have been partially unfolded or damaged under high light stress. Up -regulation of peroxisome elongation factors such as PEX11b, PEX11c and PEX11d under hypoxial and biotic stresses suggests that increased vo lume of peroxisome might be a mechanism for the plant to deal with enhanced oxidative stress. Finally, the fact that unknown protein UP6, Œoxidation ( Cassin -Ross and Hu, 2014b; Quan et al., 2010 ; Reumann et al., 2009 ), is strongly up -regulated during late seed developmental stages, indicates a possible role for this protein in seed maturation. Following the transcriptome analysis, we used a drought stress assay to test prom ising gene candidates, and identified LON2 and HPR1 as contributors to drought tolerance. HPR1 converts hydroxypyruvate to glycerate during photorespiration (Hu et al., 2012 ) . It is possible that drought induces stomatal closure, which limits the atmospheric uptake of CO 2, thus increasing the oxygenase activity of R ubisco and thus, photorespiration. In hpr1 , the accumulated photorespiratory metabolites may inhibit Rubisco activity and slow down the Calvin -Benson cycle due to decreased supply of glycerate , thus lead ing to accumulated NADPH and ROS that cause a series of oxidative damages. Mutants for the other two genes directly ( GOX1 ) or indirectly ( CAT2 ) involved in photorespiration did not show a drought phenotype, possibly due to their functional redundancy with GOX2 and CAT1/CAT3 , respectively. LON2 is a protease with unknown substrates and a role in peroxisomal matrix protein import and degradation (Farmer et al., 2013 ; Lingard and Bartel, 2009 ). Our transcriptomic analysis found LON2 to be up -regulated by ABA by 4 -fold, which is consistent with its 8 -fold induction by ABA in guard cells (Leonhardt et al., 200 4), suggesting that LON2 may play a role in drought response through ABA signaling and perox isomal protein quality control pathways. Since peroxisomal degradation via autophagy was shown to be enhanced in the lon2 mutant, especially in older leaves (Farmer et al., 2013 ; Goto -Yamada et al., 2014 ), it is possible that there are insufficient peroxisomes in the lon2 mutant to carry out photorespiration, which is critical for plant survival under drought conditions. This may also explain why lon2 and hpr1 display stronger phenotypes than the ABA biosynthetic mutant aba1 in the initial F v/Fm Although in silico analysis is powerful for function prediction, mutants for many genes whose transcript levels are regulated by drought did not exhibit obvious drought tolerance defects. Given the manageable size of the peroxisomal proteome and available mutants, stress -ba sed mutant screens should be a more direct way to identify peroxisomal proteins involved in stress response. In this initial screen , we identified strong drought sensitive phenotypes in the knockout mutants of the LON2 protease and the screen, because our screen mea sured photosynthetic efficiency, which is directly impacted by photorespiration deficiencies in these two peroxisomal mutants. photorespiratory enzyme HPR1, suggesting that future larger -scale screens would be promising to investigate the role of peroxisomes in plant adaptation to environmental stresses comprehensively. The next step would be to link these peroxisomal proteins with the global stress response networks. 2.5. Materials and m ethods 2.5.1. Plant materials and growth conditions Arabidopsis thaliana ecotype Col -0 was used as wild type (WT). T -DNA insertion mutant lines were obtained from the Arabidopsis Biological Resource Center (ABRC; http://www.arabidopsis.org/ ) and confirmed by PCR genotyping. Seeds were sown in the soil, stratified in the dark at 4 °C for 3 days, and plants were grown in a controlled growth chamber at 22 °C under long -day condi tions (16 hrs white light at 100 -2 s-1 and 8 hrs dark) for 3.5 weeks before drought treatment. 2.5.2. Microarray data analysis and heatmap visualization Microarray datasets containing expression data of Arabidopsis peroxisomal genes from various tissues at different developmental stages were obtained from the AtGenExpress database, and expression data under biotic and abiotic stresses were downloaded from NCBI Gene Expression Omnibus (GEO) database (Table 2.1 ). Peroxisomal gene expression data obtained from various developmental stages were directly extracted from the whole -genome data and used for generating the heatmap. For data on biotic and abiotic stre sses, log2 -normalized data were extracted for peroxisomal genes from the whole -genome expression profile, using methods previously described (Quan et al., 2013 ). Analysis was performed using the Bioconductor software ( Gentleman et al., 2004 ) with the statistical computing language R (version 2.15.2). Normalization of gene expression values was carried out with the robust multi -array average (RMA) algorithm (Irizarry et al., 2003 ) implemented in the Affy package of Bioconductor. Statistical significance of the differential expression values were assessed with Linear models for microarray (limm a) package (Smyth, 2004 ). Hierarchical clustering of the differentially expressed genes was visualized by creating heatmaps using the color palette package RColorBrewer and the gplots package ( Warnes et al., 2015 ). 2.5.3. Chlorophyll fluorescence measurements Chlorophyll fluorescence images of intact plants were obtained from a custom -designed plant imager chamber, using a previously described method (Attaran et al., 2014). Plants in the pots were placed in the imaging chamber in the dark for 20 min for dark adaptation before minimal chlorophyll fluorescence F o was measured . Later, maximal fluorescence F m was measured when a saturating pulse of light was applied. Fv/Fm= (F m-F o)/F mSchneider et al., 2012. Fluorescence images were analyzed by ImageJ (). 2.5.4. Drought stress assays For the drought tolerance screen, each selected mutant (two plants) and two WT plants were grown in the same pot under long day conditions (specified above) for 3.5 weeks, after which point plants stopped receiving water for 18 days b efore F v/Fm measurement was conducted. For the follow -up analysis of the lon2 and hpr1 mutants, Fv/Fm measurement was repeated in the same way as in the primary screen, and watered plants were added as the control. Leaf samples from the drought -treated and control plants were harvested for chlorophyll content measurement, relative water content (RWC) and a nthocyanin quantification as described previously ( Pandey et al., 2013 ). For chlorophyll measurement, rosette leaves were weighed and placed into 2 ml 80% acetone in the dark for 3 days. Absorbance at 645 nm and 663 nm was measured using a spectrophotometer. Total chlorophyll content = (22.22 x A 645 + 9.05 x A 663 To measure relative water content, rosette leaves were cut and immediately weighed as fresh weight (FW), and then placed in distilled deionized water at 4 °C in the dark for 24 hrs, and the weight was recorded as turgid weight (TW). Then the rosette leaf sample was placed at 60 °C for 2 days and the weight was recorded as dry weight (DW). Relative wate r content = (FW -DW) / (TW -DW) X 100%. ) µg/ml x 2 ml /leaf fresh weight in mg. For anthocyanin measurement, rosette leaves were weighed, frozen by liquid nitrogen, and ground to powder. After adding 2 ml extraction buffer ( 1% HCl in methanol), the samples were placed at 4 °C overnight. Later, an equal amount of chloroform was added, and the mixture was centrifuged for 5 min. After the top supernatant was transferred to a new tube, equal volume of 60 % extraction buffer was added . Absorbance of each tube at 530 nm and 657 nm were measured with a spectrophotometer. Anthocyanin content = (A 530 -A 657 ) /weight. 2.6. Acknowledgement We would like to thank David Hall for assistance with F v/Fm measurement, Dr. Jin Chen and Sahra Uygun for help with microarray data analysis, the Arabidopsis Biological Resource Center for providing the T -DNA insertion mutant lines, Dr. David Kramer for sharing the gox1 mutant and Dr. Gregg Howe for sharing the acx1 acx5 double mutant. No conflict of inte rest declared. APPENDIX Figure 2.1. Heatmap of transcript levels of peroxisomal genes in various developmental stages. Figure 2. 1. (c ont™d) Absolute gene expression values downloaded from the AtGenExpress database were used for heatmap generation. Genes discussed in the text are in red. Developmental stages include: 1. seedling_cotyledons; 2. seedling_hypocotyl; 3. seedling_leaves1+2; 4. adult_leaves; 5. senescing leaves; 6. flower; 7. silique_stage3; 8. silique_stage4; 9. silique_stage5; 10. seed_stage6; 11. seed_stage7; 12. seed_stage8; 13. seed_stage9; 14. seed_stage10. Figure 2.2. Heatmap of transcript levels of peroxisomal genes under abiotic stresses. Figure 2. 2. (c ont™d) Expression values are log2 normalized fold changes against untreated plants. (A) All genes are included, except AtHsp15.7 (Figure 2.2B) due to its significantly higher upregulation. Genes disc ussed in the text are in red. Genes subjected to mutant analysis are underscored. (B) Expression of the small heat shock protein gene AtHsp15.7 in response to abiotic stresses. FC, fold change. Figure 2.3. Heatmap of transcript levels of peroxisomal genes under biotic stresses. Figure 2. 3. (c ont™d) Expression values are log2 normalized fold changes against untreated plants. Genes disc ussed in the text are in red. Figure 2 .4. Total number of peroxisomal genes with significantly changed expression levels in response to stresses. (A) A biotic stresses. (B) Biotic stresses. Genes that have log2 normalized fold change >1 or < -1 are considered as significantly regulated. Figure 2.5. F v/FmMutants and wild type plants were grown in the same pot. The aba1 mutant (salk_059469) was used as a positive control. Two biological replicates were used for each genotype. Asterisk indicates p -value < 0.01 in Student™s t test. of the selected peroxisomal mutants after drought treatment. Figure 2.6. Drought resistance phenotypes of lon2 and hpr1 mutants. (A) Images of plants (left) and color -coded chlorophyll fluorescence that indicates F v/Fm values (right). (B) F v/Fm comparison between mutants and wild type. Four biological replicates of each genotype were used . No significant difference in F v/Fm was observed . (C) Plant images and color -coded chlorophyll fluorescence images that indicate F v/Fm values. (D- E) F v/Fm comparison between mutants and wild type. Two biological Figure 2.6. (c ont™d) replicates were used for each genotype under each condition. Asterisk , p < 0.01 in Students™ t test. (F-H) Quantification of anthocyanin (F), chlorophyll (G), and relative water content (H) in mutants and wild type plants. Three biological replicates were used for each genotype under each condition. Asterisk indicates p < 0.01 in Students™ t test; N.D, not detectable; D, drought; W, watered. Table 2.1 . Microarray datasets u sed in this s tudy Abbreviation in heatmap /figure legend Dataset series number Experiment design and description of used dataset Reference or link Developmental Abbreviation in Heatmap Stage# Stage description All data for Developmental stages were downloaded from AtGenExpress: http://arabidopsis.org/servlets/TairObject?type=expres sion_set&id=1006710873 seed ling_cotyledon 1 ATGE_1 development baseline Wt cotyledons 7 days continuous light soil seed ling_hypocotyl 2 ATGE_2 development baseline Wt hypocotyl 7 days continuous light soil seeding_leaves1+2 5 ATGE_5 development baseline Wt leaves 1 + 2 7 days continuous light soil adult_leaves 15 ATGE_15 development baseline Wt rosette leaf # 8 17 days continuous light soil senescing leaves 25 ATGE_25 development baseline Wt senescing leaves 35 days continuous light soil Flower 39 ATGE_39 development baseline Wt flowers stage 15 21+ days continuous light soil silique_stage3 76 ATGE_76 seed & silique development Wt siliques, w/ seeds stage 3; mid globular to early heart embryos 8 wk long day (16/8) soil silique_stage4 77 ATGE_77 seed & silique development Wt siliques, w/ seeds stage 4; early to late heart embryos 8 wk long day (16/8) soil silique_stage5 78 ATGE_78 seed & silique development Wt siliques, w/ seeds stage 5; late heart to mid torpedo embryos 8 wk long day (16/8) soil seed_stage6 79 ATGE_79 seed & silique development Wt seeds, stage 6, w/o siliques; mid to late torpedo embryos 8 wk long day (16/8) soil Table 2.1. (cont™d) seed_stage7 81 ATGE_81 seed & silique development Wt seeds, stage 7, w/o siliques; late torpedo to early walking -stick embryos 8 wk long day (16/8) soil seed_stage8 82 ATGE_82 seed & silique development Wt seeds, stage 8, w/o siliques; walking -stick to early curled cotyledons embryos 8 wk long day (16/8) soil seed_stage9 83 ATGE_83 seed & silique development Wt seeds, stage 9, w/o siliques; curled cotyledons to early green cotyledonsembryos 8 wk long day (16/8) soil seed_stage10 84 ATGE_84 seed & silique development Wt seeds, stage 10, w/o siliques; green cotyledons embryos 8 wk long day (16/8) soil abiotic stress HL_0.5hr, HL_2hr E-MTAB -403 Col -0 plants were grown in growth chambers for 3.5 weeks. Plant leaf tissue was incubated for at least 6 h in a LL growth chamber (light intensity /m 2·s, 22 °C) and then collected as control sample. The leaf tissue was expose d for 0.5 hr and 2 hr to light with an /m2Jung, H.S., Crisp, P.A., Estavillo, G.M., Cole, B., Hong, F., Mockler, T.C., Pogson, B.J., and Chory, J. (2013). Subset of heat -shock transcription factors required for the early response of Arabidopsis to excess light. Proc Natl Acad Sci U SA 110, 14474 -14479. ·s, (22 °C). cold_3hr, cold_6hr, cold_24hr GSE3326 The wild -type seeds were plated on MS agar plates supplemented with 3% sucrose. Seedlings were grown at 22 with 16 -h- light and 8 -h- dark cycles for 2 weeks before being harvested. To avoid variations due to circadian rhythm, all cold treatments were started at 12 PM at 0 under light and continued for 0 (untreated control), 3, 6, and 24 h. Lee, B.H., Henderson, D.A., and Zhu, J.K. (2005). The Arabidopsis cold -responsive transcriptome and its regulation by ICE1. Plant Cell 17, 3155 -3175. Table 2.1. (cont™d) hypoxia_2hr, hypoxia_9hr GSE9719 Seedlings grown in vertical orientation for 7 Œ14 d on solid Murashige ŒSkoog medium containing 1% sucrose were treated with mixed gases in humidified chambers. Seedlings were deprived of O 2 as well as CO 2Sorenson, R., and Bailey -Serres, J. (2014). Selective mRNA sequestration by OLIGOURIDYLATE -BINDING PROTEIN 1 contributes to translational control during hypoxia in Arabidopsis. Proc Natl Acad Sci US A 111, 2373-2378. in chambers which were purged with 99.99% Ar(gas), as control. Alternatively, treatment was with 2% O2, 370 ppm CO2, in a balan ce of N2 for 2hr and 9hr. Drought GSE10 643 Wild -type plants were grown under normal watering conditions for 24 days and then stressed by completely depriving of irrigation for 10 days. Zhang, Y., Xu, W., Li, Z., Deng, X.W., Wu, W., and Xue, Y. (2008). F -box protein DOR functions as a novel inhi bitory factor for abscisic acid -induced stomatal closure under drought stress in Arabidopsis. Plant Physiol 148, 2121 -2133. salt_4day GSE53308 Wild type Arabidopsis Col -0 plants were grown hydroponically and treated with or without 150mM NaCl and harvested after 4 days of treatment. Allu, A.D., Soja, A.M., Wu, A., Szymanski, J., and Balazadeh, S. (2014). Salt stress and senescence: identification of cross -talk regulatory components. J Exp Bot 65, 3993 -4008. salt_6day GSE16765 Arabidopsis Col -0 were grown in the growth chamber in the absence and presence of salt stress. Plants of 2 weeks were subject to salt treatment for 6 days and were used for RNA extraction. Chan, Z., Grumet, R., and Loescher, W. (2011). Global gene expression analysis of t ransgenic, mannitol -producing, and salt -tolerant Arabidopsis thaliana indicates widespread changes in abiotic and biotic stress -related genes. J Exp Bot 62, 4787 -4803. ABA RIKEN -GODA17& 21 Wild -type seedlings were treated with ABA and mock for 3 hr. Nemhauser, J.L., Hong, F., and Chory, J. (2006). Different plant hormones regulate similar processes through largely nonoverlapping transcriptional responses. Cell 126 , 467 -475. http://arabidopsis.org/servlets/TairObject?type=hyb_d escr_collection&id=1007964750 Table 2.1. (cont™d) biotic stress flg22_4hr GSE11807 Six -week old Col -0 plants were infiltrated with 1 Total RNA was extracted, biotinlabeled and hybridized to the Affymetrix ATH1 chip. Gene expression values from treated sample were compared to that of mock -treated sample Bethke G, Unthan T, Uhrig JF, Poschl Y, Gust AA, et al. (2009) Flg22 regulates the release of an ethylene response factor substrate from MAP kinase 6 in Arabidopsis thaliana via ethylene signaling. Proc Natl Acad Sci US A 106: 8067 -8072. elf18_2hr GSE34047 3-week old Col -0 plants were infiltrated with 10 Three biological replicates were included Pajerowska -Mukhtar KM, Wang W, Tada Y, Oka N, Tucker CL, et al. (2012) The HSF -like transcription factor TBF1 is a major molecular switch for plant growth -to-defense transition. Curr Biol 22: 103 -112. chitin_30min GSE28227 2-week old MS medium -grown seedlings were treated with chitooctaose at a final concentration similarly treated with an equivalent amount of ddH2O. Seedlings were harvested for RNA isolation. Three biological replic ates were conducted for the experiment http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=G SE28227 DC3K_7hr; DC3K_24hr GSE5520 4-week old Arabidopsis leaves were treated with bacterial pathogen Pseudomonas syringae pv. Tomato DC3000. The first leaf sample was treated with bacteria at the concentration of 10*8 bacteria/ml and sampled 7 hours later, and the second leaf sample was treated with bacteria at the concentration of 10*6 bacteria/ml and sampled 24 hours later Thilmony R, Underwood W, He SY (2006) Ge nome -wide transcriptional analysis of the Arabidopsis thaliana interaction with the plant pathogen Pseudomonas syringae pv. tomato DC3000 and the human pathogen Escherichia coli O157:H7. Plant J 46: 34 -53. BC_18hr; BC_48hr GSE5684 Adult Col -0 leaves were inoculated by placing 4 5- solution. Control leaves were spotted with droplets of 24g/L potato dextrose broth medium. Samples were collected at 18 hrs and 48 hrs after inoculation. http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=G SE5684 Table 2 .2. Arabidopsis peroxisomal g ene l ist 160 peroxisomal gene s have expression data and were used for co -expression analysis . The last eight genes do not have microarray probes. Order Gene n ame A.t Locus Microarray probe ID Annotation 1 ACH2 AT1G01710 261560_at acyl -CoA thioesterase family protein 2 PEX11c AT1G01820 261534_at PEX11c, peroxisome elongation 3 PEX6 AT1G03000 263170_at peroxin6 4 st4 AT1G04290 263661_at thioesterase family protein 5 KAT1 AT1G04710 264608_at 3-keto -acyl -CoA thiolase 1 6 ACX3 AT1G06290 260789_s_at acyl -CoA oxidase 3 7 ACX6 AT1G06310 259419_at acyl -CoA oxidase 6 8 ACD31.2 AT1G06460 262629_at alpha -crystallin domain 31.2 9 NDA1 AT1G07180 256057_at alternative NAD(P)H dehydrogenase 1 10 GLX1 AT1G11840 264372_at glyoxalase i homolog 1 11 GAPC2 AT1G13440 259361_at glyceraldehyde -3-phosphate dehydrogenase 12 UP6 AT1G16730 255763_at unknown protein 6 13 DHAR AT1G19570 261149_s_at dehydroascorbate reductase 1 14 4Cl3 AT1G20480 259569_at 4-coumaroyl -CoA synthase family protein 15 OPCL1 AT1G20510 259518_at opc-8:0 -CoA ligase1 16 AAE1 AT1G20560 259545_at acyl -activating enzyme 1 17 CAT3 AT1G20620 259544_at catalase 3 18 CAT1 AT1G20630 259517_at catalase 1 19 ATF1 AT1G21770 262499_at acyl -CoA n -acyltransferases 20 GGT1 AT1G23310 262988_at alanine -2-oxoglutarate aminotransferase 1 21 DEG15 AT1G28320 245687_at Endopeptidase 22 UP9 AT1G29120 260889_at unknown protein 9 23 PEX7 AT1G29260 260844_at peroxin 7 Table 2.2. (cont™d) 24 AAE14 AT1G30520 261801_at acyl -activating enzyme 14 25 PEX11a AT1G47750 261739_at PEX11a, peroxisome elongation 26 st1 AT1G48320 262237_at thioesterase family protein 27 pxPfkB AT1G49350 262398_at pfkb -type carbohydrate kinase family protein 28 NQR AT1G49670 261601_at involved in oxidative stress tolerance. 29 ICDH AT1G54340 262962_at isocitrate dehydrogenase 30 NS AT1G60550 264920_at naphthoate synthase 31 ECI AT1G65520 264627_at enoyl -CoA hydratase/isomerase family protein 32 PAO4 AT1G65840 262933_at polyamine oxidase 4 33 BZO1 AT1G65880 261915_at benzoate -CoA ligase 34 AAE12 AT1G65890 261922_at acyl -activating enzyme 12 35 HPR1 AT1G68010 260014_at hydroxypyruvate reductase 1 36 GGT2 AT1G70580 260309_at glutamate:glyoxylate aminotransferase 2 37 ECH2 AT1G76150 261771_at monofunctional enoyl -CoA hydratase 2 38 ATF2 AT1G77540 259706_at histone acetyltransferase 39 PEX2 AT1G79810 261348_at peroxin2 40 SMP2 AT2G02510 267239_at NADH dehydrogenase 41 OPR3 AT2G06050 265530_at OPDA -reductase 3 42 AGT1 AT2G13360 263350_at alanine:glyoxylate aminotransferase 43 DRP3B AT2G14120 263278_at dynamin -related protein 3 B 44 MDH1 AT2G22780 266457_at peroxisomal NAD -malate dehydrogenase 1 45 SOX AT2G24580 263788_at sarcosine oxidase family protein 46 Uri AT2G26230 267374_at uricase/urate oxidase putative 47 PEX10 AT2G26350 267433_at peroxin 10 48 CoAE AT2G27490 265637_at dephospho -CoA kinase 49 st5 AT2G29590 266298_at thioesterase family protein Table 2.2. (cont™d) 50 NDA2 AT2G29990 266835_at alternative NAD(P)H dehydrogenase 2 51 CHYH1 AT2G30650 267571_at 3- hydroxyisobutyryl -coenzyme a hydrolase 52 CHYH2 AT2G30660 267572_at 3-hydroxyisobutyryl -coenzyme a hydrolase 53 UP3 AT2G31670 263449_at unknown protein 3 54 KAT2 AT2G33150 245168_at 3-keto -acyl -CoA thiolase 2 55 ACX5 AT2G35690 265843_at acyl -CoA oxidase 5 56 GLH AT2G38180 267096_at gdsl -motif lipase/hydrolase family protein 57 PXN/PMP38/PMP36 AT2G39970 267363_at peroxisomal membrane protein 36 58 PM16 AT2G41790 260554_at peptidase m16 family protein 59 CuAO AT2G42490 265882_at copper amine oxidase 60 CSY3 AT2G42790 263986_at citrate synthase 3 61 PAO2 AT2G43020 265244_at polyamine oxidase 2 62 PEN2 AT2G44490 267392_at o-glycosyl compounds hydrolase 63 PEX16 AT2G45690 267512_at peroxin 6 64 PEX11d AT2G45740 266925_at PEX11d, peroxisome elongation 65 SO AT3G01910 258948_at sulfite oxidase 66 SDRc AT3G01980 258976_at short -chain dehydrogenase/reductase (sdr) family protein 67 6PGDH AT3G02360 256328_at 6-phosphogluconate dehydrogenase family protein 68 PEX19A AT3G03490 259052_at peroxin 19 -1 69 PEX12 AT3G04460 258627_at peroxin 22 70 PNC1 AT3G05290 259306_at peroxisomal adenine nucleotide carrier 1 71 LACS6 AT3G05970 258563_at long -chain acyl -CoA synthetase 6 72 IBR3 AT3G06810 258525_at acyl -CoA dehydrogenase 73 MFP2 AT3G06860 258555_at multifunctional protein 2 74 CML3 AT3G07490 259064_at calcium ion binding Table 2.2. (cont™d) 75 PEX13 AT3G07560 259068_at peroxin 13 76 SDRb AT3G12800 257687_at short -chain dehydrogenase 77 HAOX1/2 AT3G14130, AT3G14150 257004_s_at putative glycolate oxidase 78 GOX1/2 AT3G14415, AT3G14420 258359_s_at glycolate oxidase 79 HBCDH AT3G15290 257052_at 3-hydroxybutyryl -CoA dehydrogenase, putative 80 AAE7 AT3G16910 257880_at acyl -activating enzyme 7 81 GPK1 AT3G17420 257295_at glyoxysomal protein kinase 1 82 PEX3A AT3G18160 258150_at peroxin 3a 83 SCO3 AT3G19570 257047_at snowy cotyledon3 84 DRP5B AT3G19720 257045_at dynamin -related protein 5 B 85 ICL AT3G21720 257947_at isocitrate lyase 86 PEX22 AT3G21865 257953_at peroxin 22 87 GR1 AT3G24170 257252_at glutathione -disulfide reductase 1 88 MDAR4 AT3G27820 257227_at monodehydroascorbate reductase 4 89 PEX11b AT3G47430 252411_at PEX11b, peroxisome elongation 90 B12D1 AT3G48140 252348_at senescence -associated protein 91 BADH AT3G48170 252354_at betaine aldehyde dehydrogenase 92 MIF AT3G51660 252076_at macrophage migration inhibitory factor family protein 93 ACX4 AT3G51840 246304_at acyl -CoA oxidase 4 94 MDAR1 AT3G52880 252024_at monodehydroascorbate reductase 95 SDRd AT3G55290 251780_s_at short -chain dehydrogenase/reductase (sdr) family protein] 96 CDC AT3G55640 251757_at mitochondrial substrate carrier family protein 97 ZnDH AT3G56460 251687_at zinc -binding dehydrogenase 98 HIT3 AT3G56490 251707_at histidine triad family protein Table 2.2. (cont™d) 99 FIS1A AT3G57090 251659_at fission protein 1 A 100 CP AT3G57810 251558_at OTU -like cysteine protease 101 CSY1 AT3G58740 251540_at citrate synthase 1 102 CSY2 AT3G58750 251541_at citrate synthase 2 103 PMD1 AT3G58840 251556_at peroxisome and mitochodria division protein 104 PAO3 AT3G59050 251505_at polyamine oxidase 3 105 PEX11e AT3G61070 251352_at PEX11e, peroxisome elongation 106 st3 AT3G61200 251307_at thioesterase family protein 107 ACH AT4G00520 255679_at acyl -CoA thioesterase family protein 108 EH3 AT4G02340 255525_at putative epoxide hydrolase 109 MCD AT4G04320 255327_at malonyl -CoA decarboxylase family protein 110 PMP22 AT4G04470 255338_at peroxisomal membrane protein 22 111 4CL1 AT4G05160 255263_at putative 4 -coumaroyl -CoA synthase 112 IBR1 AT4G05530 255240_at short -chain dehydrogenase 113 NDPK1 AT4G09320 255089_at nucleoside diphosphate kinase 1 114 SCPL20 AT4G12910 254791_at serine carboxypeptidase -like 20 115 IBR10 AT4G14430 245359_at enoyl -CoA hydratase/isomerase family protein 116 ECHIA AT4G16210 245484_at enoyl -CoA hydratase/isomerase family protein 117 HIT1 AT4G16566 245337_at histidine triad family protein 118 ACX1 AT4G16760 245249_at acyl -CoA oxidase 1 119 GOX3 AT4G18360 254630_at putative glycolate oxidase 120 4Cl5 AT4G19010 254600_at 4-coumaroyl -coa synthase family protein 121 NDB1 AT4G28220 253810_at NAD(P)H dehydrogenase b 122 AIM1 AT4G29010 253759_at abnormal inflorescence meristem1 , enoyl -CoA hydratase 123 DRP3A AT4G33650 253306_at dynamin -related protein 3 A 124 APX3 AT4G35000 253223_at ascorbate peroxidase 3 Table 2.2. (cont™d) 125 CAT2 AT4G35090 253174_at catalase 2 126 RDL1 AT4G36880 246250_at cysteine -type peptidase 127 AGT2 AT4G39660 252855_at alanine:glyoxylate aminotransferase 2 128 PXA1/CTS AT4G39850 252830_at peroxisomal ABC transporter 1 129 MLS AT5G03860 250868_at malate synthase 130 BIOTIN_F AT5G04620 250837_at 7- keto -8- aminopelargonic acid synthase 131 CPK1 AT5G04870 246955_at calcium -dependent protein kinase isoform 132 PEX1 AT5G08470 250520_at peroxin 1, ATPase 133 MDH2 AT5G09660 250498_at peroxisomal NAD -malate dehydrogenase 2 134 ASP3 AT5G11520 250385_at aspartate aminotransferase 3 135 ELT1 AT5G11910 250299_at esterase/lipase/thioesterase family protein 136 FIS1B AT5G12390 245178_at mitochodria and peroxisome fission protein 137 AAE5 AT5G16370 250114_s_at acyl -activating enzyme 5 138 ATMS1 AT5G17920 259343_s_at methionine synthesis 1 139 CSD3 AT5G18100 250016_at copper superoxide dismutase 3 140 NUDT19 AT5G20070 246126_at nudix hydrolase homolog 19 141 AAE17 AT5G23050 249869_at acyl -activating enzyme 17 142 6PGL AT5G24400 249733_at 6-phosphoglucunolactonase 143 PEX4 AT5G25760 246862_at peroxin4, ubiquitin -protein ligase 144 PNC2 AT5G27520 246779_at peroxisomal adenine nucleotide carrier 2 145 LACS7 AT5G27600 246789_at long -chain acyl -CoA synthetase 7 146 AtHsp15.7 AT5G37670 249575_at 15.7 kda class i -related small heat shock protein -like 147 GSTT1 AT5G41210 249291_at glutathione s -transferase (class theta) 1 148 SCP2 AT5G42890 249178_at sterol carrier protein 2 149 AtDCI AT5G43280 249145_at delta(3,5),delta(2,4) -dienoyl -CoA isomerase 1 150 UP5 AT5G44250 249064_at unknown protein 5 Table 2.2. (cont™d) 151 LON2 AT5G47040 248818_at lon protease homolog 2 152 ACAT1.3 AT5G47720 248779_at putative acetyl -CoA c -acyltransferase 153 ACAT2 AT5G48230 248690_at acetoacetyl -CoA thiolase 2 154 KAT5 AT5G48880 248625_at 3-keto -acyl -CoA thiolase 5 155 PEX5 AT5G56290 248010_at peroxin 5, peroxisome matrix targeting signal -1 binding protein 156 TLP AT5G58220 247858_at transthyretin -like protein 157 PEX14 AT5G62810 247422_at peroxin 14 158 4CL2 AT5G63380 247380_at 4-coumarate -CoA ligase family protein 159 ACX2 AT5G65110 247176_at acyl -CoA oxidase 2 160 CHY1 AT5G65940 247117_at beta -hydroxyisobutyryl -CoA hydrolase 1 161 AAE18 AT1G48635 no probe acyl -activating enzyme 18 162 PEX3B AT1G50510 no probe peroxin 3 B 163 IndA AT1G55320 no probe indigoidine synthase a family protein 164 NADK3 AT1G78590 no probe NADH kinase 165 APEM9 AT3G10572 no probe required for both pts1 - and pts2 -dependent protein transport 166 PEX19B AT5G17550 no probe peroxin 19 B 167 MIA40 AT5G23395 no probe mitochondrial intermembrane space assembly machinery 40 168 HIT2 AT5G48545 no probe histidine triad nucleotide -binding 3 Table 2.3. Mutants used in the primary screen for drought tolerance KO, knock -out; KD, knock -down F¹ Mutant SALK_ID Gene expression Transcriptional regulation by drought, log 2 Reference (FC) aba1 SALK_059469 KO Control ( Riboni et al., 2013 ) hpr1 -1 SALK_067724 KO limited up-regulation , 0.44 ( Timm et al., 2008 ) hpr1 -2 SALK_143584 KO cat2 SALK_076998 KO up-regulated by drought , 1.70 ( Shibata et al., 2013 ) gox1 SAIL_177_G11 KO limited up-regulation by drought, 0.42 ( Rojas et al., 2012 ) gox3 SALK_020909 KO up-regulated by drought , 1.10 ( Quan et al., 2013 ) hsp15.7 -1 SALK_038951 KD up-regulated by drought , 2.05 ( Ma, 2005 ) hsp15.7 -2 SALK_107711 KO pao2-1 SALK_046281 KO down -regulated by drought , -1.37 ( Kim et al., 2014 ) pao2-2 SALK_062035 pxn -1 SALK_038951 KO limited up-regulation by drought, 0.03 ( Bernhardt et al., 2012) pxn -2 SALK_107711 KD csy3 SALK_076319 KO up-regulated by drought , 2.23 Mif SALK_037373 up-regulated by drought , 1.79 lon2 -2 SALK_043857 KO up-regulated by ABA /drought , 1.98/0.51 (Lingard and Bartel, 2009) kat5 -1 SALK_132871 down -regulated by drought , -1.93 kat5 -2 SALK_144464 KD ( Wiszniewski, 2011 ) acx3 -1 SALK_128947 limited up-regulation by drought, 0.05 acx3 -2 SALK_044956 KO ( Adham et al., 2005 ) acx4 -1 SALK_000879 KO up-regulated by drought , 1.21 ( Adham et al., 2005 ) acx4 -2 SALK_065013 KO Table 2.3. 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Transcriptional regulatory networks in cellular responses and tolerance to dehydration and cold stresses. Annu Rev Plant Biol 57, 781-803. Zhu, J.K. (2002). Salt and drought stress signal transduction in plants. Annu Revi Plant Biol 53, 247-273. CHAPTER 3 Dissecting the role of peroxisom es in modulating photosynthesis under dynamic light conditions 3.1. Abstract In plant cells, peroxisomes cooperate with other subcellular compartments such as chloroplasts, mitochondria, lipid bodies and cytoplasm to support cellular functions . Emerging evidence also suggested physical connections between peroxisomes and chloroplasts, leading to the question of how general peroxisomal metabolism affects photosynthesis. To comprehensively investigate t he impact of peroxisomes on photosynthesis, a systematic mutant screen was conducted. One hundred and forty -seven mutants of 104 Arabidopsis genes encoding peroxisomal proteins were subjected to an automated screen system , Dynamic Environment Phenotype Ima ger (DEPI), which measures a suite of photosynthetic parameters continuously and non -invasively. Photosynthetic defects were revealed under dynamically changing light conditions for a subset of peroxisomal mutants. A peroxisomal NAD + transporter PXN was identified to play a role in modulating photosynthesis via photorespiration , which suggests that peroxisomal NAD + homeostasis is critical for photorespiration under dynamic light condition. In addition , although photorespiration is known to be linked t o photosynthesis, detailed molecular mechanisms regarding how the block ing of photorespiration alter s photosynthetic efficiency were poorly understood. We have found that the block of photorespiration alter s various photosynthe tic processes including inhibit ion of the activity of triose phosphate isomerase (TPI) by the accumulated phosphoglycolate , diminished ATP synthase conductivity , increased proton motive force ( pmf ) and energy -dependent quenching (qE) , compromised photosystem integrity, reduced photosystem subunit abundance, induced CEF and less induction of anthocyanin . In summary, our systematic mutant screen identified multiple peroxisomal proteins required for robust photosynthetic efficiency under dynamically changing light and discovered an addition al player , the NAD + transporter PXN , in photorespiration. Further characterization of photorespiratory mutants provided a deeper understanding of the connection between photorespiration and photosynthesis. Knowledge gained from this study will enhance our understanding of peroxisome function, photosynthesis and interorganellar communication. 3.2. Introduction Peroxisomes are small and single -membrane delimited organelles that exist in almost all eukaryo tic cells (Fagarasanu et al., 2010 ; Hu et al., 2012 ; Pieuchot and Jedd, 2012; Smith and Aitchison, 2013 ). The peroxisome houses conserved metabolic functions across di fferent kingdoms, such as fatty acid -oxidation and hydrogen peroxide (H 2O2Islinger et al., 2012 ) detoxification (; Schrader and Fahimi, 2008 ; Waterham and Wanders, 2012). Plant specific metabolism, such as photorespiration, conversion of i ndole-3- butyric acid (IBA) to indole-3- acetic acid (IAA) and j asmonic acid (JA) biosynthesis , take place in peroxisomes as well (Hu et al., 2012 ). Besides the metabolism that exclusively occurs in peroxisomes, peroxisomes also coordinate with other subcellular compartments to support important cellular functions. Numerous studies have shown that subcellular organelles often coordinate in response to and integrating various signals and exchanging metabolites, thereby sustaining optimal plant growth and development (Fu and Dong, 2013 ; Sulpice and McKeown, 2015 ; Wang and Wu, 2013 ). For example, chloroplasts and mitochondria interact with the nucleus through retrograde signaling, in which signals from organelles to nucl eus play critical roles in coordinating nuclear gene expression ( Chi et al., 2013 ; Hartl and Finkemeier, 2012). C hloroplast retrograde signal s, which are derived from chloroplastic m etabolites, redox status and ROS, are critical for chloroplast development and the maint enance of optimal chloroplast function under a series of stress conditions ( Chi et al., 2013 ; Fernandez and Strand, 2008 ). Mitochondria, another important energy organelle, also use retrograde signaling to coordinate with the nucleus under a variety of environmental perturbations , such as cold, drought and high light ( Ng et al., 2013a ; Ng et al., 2013b ). Organelles also act in concert in metabolism. In plant cells, photorespiration is a well -known carbon recycling metabolic pathway that requires the collaboration of the chloroplast, peroxisome, mitochondrion and cytosol (Bauwe et al., 2010 ). A lipase Sugar -Dependent 1 (SDP1), which is critical for efficient lipid mobilization in seed germination, can migrate from peroxiso mes to oil bodies through peroxisomal extension, indicating that protein transport complexes may exi st between peroxisomes and lipid bodies (Thazar -Poulot et al., 2015 ). It was also shown that mitochondria -derived vesicles (MDVs) can f use with peroxisomes for transporting metabolites, proteins and membranes in mammalian cells (McBride and Sedwick, 2014 ; Neuspiel et al., 2008 ; Schumann and Subramani, 2008 ). Peroxisomes can dynamically interact with other organelles. Microscopic studies revealed that tightly associated membrane s exist between peroxisomes and chloroplasts (Oikawa et al., 2015 ), lipid bodies (Thazar -Poulot et al., 2015 ) and the e ndoplasmic reticulum ( Mullen and Trelease, 2 006), which suggested that interorganellar channels may facilitate protein and metabolite exchange. A recent study reported the light -induced physical interaction between peroxisomes and chloroplasts, which plays a critical role in ensuring efficient in terorganellar metabolite flow (Oikawa et al., 2015 ). Finally, s nowy cotyledon 3 (SCO3) is a microtubule -associated peroxisomal protein, which is important for chloroplast biogenesi s in the cotyledon and robust photosynthetic efficiency under changed CO 2Albrecht et al., 2010 conditions in mature plants with an unknown mechanism (). Since emerging evidence suggested the physical and functional connections between p eroxisomes and chloroplasts, one of our interests was to study how peroxisomal metabolism modulates photosynthesis in the chloroplast. Photosynthesis is a principal and complex pathway, which converts sunlight energy to ATP and NADPH for CO2Kaur and Hu, 2011 fixation and other dark reaction related metabolism s. To explore the interaction between peroxisomal metabolism and photosynthesis at a systems level, a large collection of mutants of genes encoding peroxisomal proteins, as well as a high -throughput photo synthesis phenotyping platform were needed to enable efficient phenotype discovery. Thanks to the recent peroxisomal proteomic analyses followed by in vivo subcellular protein targeting verifications, the total number of known peroxisome proteins has been increased to ~170 (; Quan et al., 2010 ; Quan et al., 2013). The collection of mutants of genes encoding these peroxisomal proteins laid a foundation for various phenotypic assays. For example, our lab has successfully uncov ered the involvement of novel peroxisomal proteins in fatty acid -oxidation, conversion of IBA to IAA and stress response by screening peroxisomal mutants using a series of physiological assays (Cassin -Ross and Hu, 2014 ; Quan et al., 2013 ). Given the complexity and dynamics of photosynthetic processes, a robust assay is needed for the screen. Approaches used to study photosynthesis include chlorophyll fluorescence, absorption spectroscopy, gas exchange and biochemical analyses of photosynthetic complexes (Hunt, 20 03; Kügler et al., 1997 ; Long and Bernacchi, 2003 ; Tanaka and Makino, 2009 ). Chlorophyll fluorescence measurement has become a commonly used method because it is non -destructive , quantitative and applicable to high throughput phenotyping ( Baker, 2008 ). Photosynthetic parameters that reflect basic prope rties of photosynthesis , such as maximum quantum yield (F v/Fm) of photosynthesis, photosystem II (PSII) operating efficiency ( ), non -photochemical quenching (NPQ), energy -dependent quenching (qE) and photoinhibition quenching (qI), can be measured through this method. One system that suits our purpose is the recently developed Dynamic Environment Phenotype Imager (DEPI), which allows continuous, highly sensitive, non -invasive and simultaneous measurement of photosynthetic parameters ( Attaran et al., 2014; Dutta et al., 2015 ; Kramer et al., 2013 ). DEPI can reveal phenotypes that emerge under dynamic light conditions and otherwise may not show under constant light conditions, thus these new phenotypes are called emerging phenotypes (Attaran et al., 2014; Dutta et al., 2015 ). To acclimate to constantly changing light in the natural environment, plants have evolved sophisticated biophysical, biochemical and physiological strategies to fine tune the balance between photosynthesis and photodamage. For example, plants tend to redistribute chloroplasts to the periphery of cells to minimiz e light absorption under high light exposure (Kasahara et al., 2002 ). Activation of NPQ, phosphorylation of light -harvesting complex II (LHCII), and accelerated repair cycle of core subunits in photosystem (PS) I and PSII can together efficiently dissipate and partition excessively absorbed energy under dynamic light conditions ( Bellafiore et al., 2005 ; Eberhard et al., 2008 ; Fristedt et al., 2009 ; Niyogi and Truong, 2013 ). Interruption of the Calvin -Benson- Bassham (CBB) cycle and other dark metabolism can largely affect photosynthetic efficiency (Eberhard et al., 2008 ). Mutants that are defective in the primary light reaction, the CBB cycle and their regulation can potentially be discovered through the DEPI screen. 3.3. Result 3.3.1. Collecting mutants for genes encoding peroxisomal proteins Recent advances in Arabidopsis peroxisome studies using proteomics, in silico prediction and in vivo targeting confirmation identified more than three dozen novel peroxisomal pro teins (Quan et al., 2013 ; Reumann et al., 2009 ). The number of known peroxisomal proteins in Arabidopsis has been expanded to ~170, which enabled us to start a comprehensive peroxisome -centered analysis and genetic screens for target phenotypes ( Cassin -Ross and Hu, 2014 ). By collecting T -DNA insertion mutants from Arabidopsis Biological Research Center (ABRC, https://abrc.osu.edu/ ) and other research groups, followed by PCR -based genotyping, our lab has collected 147 homozygous mutants for 104 peroxisomal genes (Table 3.1 ). 3.3.2. Mutant screen and photosynthetic data analysis In DEPI system, dynamically changing light conditions are imposed over a 5 -day experiment (Figure 3.1A). Simultaneously, , NPQ, qE and qI are measured at multiple time points across five days. On Day 1, plants were exposed to constant illumination typical of that used in a growth chamber (100 -2 s -1 ). On Day 2, the light was programmed fisinusoidalfl to mimic solar radiation with maxima l intensity of 500 m-2 s -1 Kulheim et al., 2002. On Day 3, plants were exposed to a regime of fluctuating light to simulate changing light conditions that occur in natural environment, under which strong phenotypes were revealed in mutants defective in photoprotective process (; Tikkanen et al., 2012 ). Light intensity was changed every 30 minutes following the sinusoidal curve as on Day 2, but with superimposed fluctuations. Each light interval consisted of an 18 -min period at an fiambientfl light peaking at 500 -2 s -1 Photosynthetic parameters from 16, 32, 64, 16 and 64 time point s were collected from Day 1 to Day 5, summing up to a total of 192 time points. Using software OLIVER (Tessmer et al. , submitted), I generated heatmaps that were linked to each other by mutant name -based linking curves. Each heatmap represents the values o , NPQ, qE or qI for 147 peroxisomal mutants, as log -fold changes in each mutant relative to the wild -type Col -0 control (Figure 3.1B). The x axis represents the time points across five days, and the y axis represents the screened mutants. In each heatmap, mutants were positioned from top to bottom based on the sum of all values across 5 days ( low to high ). A subset of mutants that exhi Figure 3.1B). The corresponding locations of this subset of mutants in each heatmap were indicated by the linking curves. Consistent with the lower igher NPQ, as indicated by their position at the bottom of the NPQ heatmap (data for generating heatmaps is in Supplemental Table 1). , followed by an 8 -min period of twice the ambient intensity (fifluctuatingfl intensity). Day 4 was a repeat of Day 1 and Day 5 was a repeat of Day 3. peroxisome biogenesis and division mutants pex14 , drp5B, drp3A drp3B double, and drp3A drp3B drp5B triple ; ii) photorespiratory mutants hpr1-1 , hpr1-2 , gox1 -3 and cat2 -1, and iii) mutants of the NAD + transporter PXN, pxn -1 and pxn -2 ( Figure 3.1C ). Only the peroxisomal protein import mutant pex14 , which is often used as a control for exhibited distinguished phenotypes mainly under dynamic illumination on Day 2, Day 3 and Day 5. 3.3.3. Peroxisomal b iogenesis and division mutants exhibit ed reduced photosynthe tic efficiency under various light conditions To examine the overall impact of peroxisomes on photosynthesis, we first assessed the peroxisome protein import mutant pex14 and peroxisome division mutants drp5B , drp3 A drp3B and drp3 A drp3 B drp5B , as these mutants should display general defects in peroxisomal functions. PEX14 is a peroxisomal membrane protein required for efficient peroxisome protein targeting and import (Hayashi et al., 2000 ), and DRP3 and DRP5B are shared factors in the division of mitochondri a and peroxisomes (DRP3) (Aung and Hu, 2012 ; Zhang and Hu, 2009 ) and peroxisomes and chloroplasts (DRP5B) (Aung and Hu, 2012 ; Zhang and Hu, 2010 ). Not surprisingly, pex14 on Day 1 (Figure 3.2). Under sinusoidal light on Day 2 and fluctuating light on Day 3, the dissipated as heat, as indicated by higher NPQ (Figure 3.2). Interestingly, qI, rather than qE, was the major quenching in pex14 . After a recovery period on Day 4, pex14 exhibited similar phenotype s as exhibited on Day 3 under the second round of fluctuating light conditions on Day 5 (Figure 3.2 ). In the peroxisomal division mutants, photosynthetic performance was similar to that of WT under constant light on Day 1 ( Figur e 3.3). However, mutants began to show m-2 s -1 and became more severely affected under higher intensities. On Day 2 under sinusoidal light, drp5B had higher qE, while drp3 A drp3B and drp3 A drp3 B drp5B had higher qI, which were consistent with an conditions , which consisted of lower bound fiambient lightfl and upper bound fifluctuating lightfl, these mutant s behaved similarly mutant showing the great est reduction. NPQ under lower bound ambient light was higher in all mutants than in WT, but NPQ under upper bound fluctuating light was lower in double and triple mutants. A similar pattern was found in qE. Meanwhile, qI was strongly activated under both ambient and fluctuating light in the double and triple mutants. After two days of dynamic light treatme nt, all three mutants (especially the triple mutant) the second round of fluctuating light treatment on Day 5, all mutants showed similar defects as those shown under the first round of fluctuating light condition s (Day 3) , but the difference from the WT became less obvious (Figure 3.3). Overall, both peroxi some biogenesis mutant pex14 and the organelle division mutants showed impaired photosynthetic performance, indicating that peroxisomes play a crucial role in robust photosynthesis under dynamic light. 3.3.4. Photorespiratory mutant s displayed various lev els of deficiencies in photosynthetic performance under high light and fluctuating light condition s Glycolate oxidases (GOX1 and GOX2 ) and hydroxypyruvate reductase 1 (HPR1) respectively ca talyze the first and last step of the peroxisomal portion of the photorespiration pathway. Catalase 2 (CAT2) is the major catalase enzyme in the peroxisome that breaks down H 2O2Cousins et al., 2008b produced by photorespiration. Two p eroxisomal malate dehydrogenase s (PMDH1 and PMDH2) produce NADH to facilitate the reduction reaction by HPR1 ( ). As previously rep orted ( Timm et al., 2008 ; Vanderauwera et al., 2005 ), null mutant s hpr1-1 , hpr1-2 and cat2 -1 showed typical photorespiratory phenotypes, i.e. retarded growth and smaller rosette leaves when grown in ambient air. Semi -quan titative RT -PCR analysis was performed on the mutant alleles of GOX1 . The gox1-1 and gox1-2 mutants sustained similar amount of transcript as WT (Figure 3.4A), and gox1 -3 appeared to be a knockout mutant (Rojas et al., 2012 ). Two mutant alleles of GOX2 , which is highly similar to GOX1 , were examined as well, and the result suggested that they are knockout mutants (Figure 3.4A). A knockout mutant of PMDH1 , which grew normal ly under ambient air (Figure 3.4B ), was also included in the screen . Null mutants gox1-3 , gox2-1 and gox2-2 grew as well as the WT in ambient air, which is possibly due to the functional redundancy between GOX1 and GOX2 under ambient conditions (Figure 3.4B). Likewise, null mutant pmdh1 did not show typical photorespiratory phenotype, which is possibly due to the functional redundancy between PMDH1 and PMDH2 despite the fact that the expression of PMDH2 is much higher tha n that of PMDH1 in leaves (Li and Hu, 2015 ). However, hpr1-1 , hpr1-2 , cat2 -1, and interestingly, gox1-3 as well, exhibited strong phenotypes under dynamic light conditions , which will be described below. Day 1 and Day 2: Under constant light on Day 1, there were limited differences between photorespiratory mutants and WT in photosynthetic performance (Figure 3.5 ). However, under sinusoidal light on Day 2, was reduced in all four mutants, with hpr1-1 and hpr1-2 showing the fastest and strongest decrease and gox1-3 and cat2 -1 displaying weaker but significant decreases. The fast decay of began at 170 m-2 s-1 in hpr1-1 and hpr1-2 , and at ~30 0 m-2 s -1 in gox1-3 and ~330 m-2 s -1 For NPQ, hpr1-1 , hpr1 -2, gox1-3 and cat2 -1 started to show an exponential increase at around 170, 170, 300 and 330 photons m in cat2 -1 (Figure 3.5 A) in hpr1-1 and hpr1- 2 kept decreasing to around 0.2 at the highest light intensity. The lowest in gox1 -3 and cat2 -1 were both around 0.4 , with a faster decrease in gox1-3 . recovered as light intensity decreased and b y the end of the day, WT recovered to around 95% of its starting level, while in hpr1-1 , hpr1-2 , gox1-3 and cat2 -1, it was 57%, 60%, 83% and 77%, respectively ( Fig ure 3.5 A). Pseudo fluorescence images of in hpr1-1 and gox1-3 also reflected the change of during the course of sinusoidal light on Day 2 (Figure 3.6). -2 s -1 Rochaix, 2014 , respectively, corresponding to the light intensities that triggered the drastic decay (Figure 3.5 B). hpr1-1 and hpr1-2 exhibited the highest NPQ, followed by gox1 -3 and cat2 -1 . qE is the fast relaxing component of NPQ, and qI is the slowly relaxing component of NPQ ( ). All four mutants had much higher qE than WT. hpr1-1 and hpr1-2 had a large peak of qE photons m -2 s -1 , and the response gradually relaxed even when the light was increasing ( Figure 3.5C). On the other hand, gox1-3 and cat2 -1 had a fast increase of qE at around 250 and 290 photons m -2 s -1 respectively, and kept increasing as light intensity increased (Figure 3.5C). At the end of the day, there was residual qE in hpr1-1 , hpr1-2 and cat2 -1 , but not gox1-3 . hpr1-1 and hpr1- 2 exhibited the highest qI, followed by gox1-3 and cat2 -1 . hpr1-1 , hpr1-2 and cat2 -1 showed gradually increased qI , which reached the highest value after the highest light intensity , while the kinetics of qI in gox1-3 and WT correlated with light intensity changes (Figure 3.5 D). There were residual qI in hpr1-1 , hpr1- 2 and cat2 -1 , which is in line with their enhanced reduction of . Day 3: Under fluctuating light conditions on Day 3, , NPQ, qE and qI were clearly distinct between mutants and WT. hpr1-1 , hpr1-2 and cat2 -1 started with lower 2, and continued to decrease faster than the WT under both lower bound ambient light and upper bound fluctuating light (Figure 3.5 A). gox1-3 under both ambient light and fluctuating light, but to a lesser extent tha n that of hpr1-1 , hpr1-2 and cat2 -1 (Figure 3.5 A). A ll the mutants have overall higher NPQ than WT, especially under ambient light. hpr1-1 , hpr1-2 and cat2 -1 had much smaller range s of qE, indicating impaired qE adaptation to fluctuating light ( Figure 3.5C). However, qE in gox1-3 was overall higher than WT under both ambient and fluctuating light, indicating that gox1 -3 sustained robust adaptive qE response under fluctuating light condition s ( Figure 3.5 C). Compared with the wild type, hpr1-1 , hpr1-2 and cat2 -1 had significantly higher qI under both ambient light and fluctuating light, while gox1 -3 had significantly higher qI under fluctuating light ( Figure 3.5 D). Day 4: After light stress on Day 2 and Day dropped from the starting value on Day 2, to 47% in hpr1-1 , 48% in hpr1-2 , 57% in cat2 -1, 77% in gox1-3 in and 62% in WT, suggesting strongly enhanced photoinhibition in most mutants ( Figure 3.5A). Since NPQ, qE and qI are activated under high light conditions, NPQ, qE and qI showed no change under constant low light on Day 4 (Figure 3. 5B- D) Day 5: Under the repeated fluctuating light condition s hpr1-1 and hpr1-2 not only decreased faster than WT, similar to the trend in Day 3, but also exhibited a quick decay similar to that of Day 2. So were cat2 -1 and gox1 -3 , but to a lesser extent ( Figure 3.5A). Compared with Day 3, qE in hpr1-1 , hpr1-2 and cat2 -1 were responding more robustly to light fluctuation, and gox1-3 was responding as strongly as on Day 3 (Figure 3.5 C). qI in both hpr1-1 and hpr1-2 had two peaks, one was before and one was after the highest light intensity. qI in cat2 -1 and gox1-3 was a s responsive to the fluctuating light conditions as on Day 3 (Figure 3.5 between Day 3 and Day 5 might be due to the light conditions prior to that day, which was sinusoidal for Day 3 and constant moderate light for Day 5. 3.3.5. The peroxisomal NAD +PXN is a peroxisomal NAD carrier PXN modulates photosynthesis un der fluctuating light condition s + carrier delivering cytosolic NAD +Cousins et al., 2008a into peroxisome s for the production of NADH , a reducing equivalent that presumably facilitate s photorespiration ( ), -oxidation, conversion of IBA to IAA and others (Bernhardt et al., 2012 ). Two T -DNA insertion mutants , the knockout pxn -1 and the strong knock -down pxn -2 ( Bernhardt et al., 2012 ) were analyzed in this study. Limited phenotypic difference was observed on Day 1 and Day 2 . However, under fluctuating light conditions on Day 3 , both pxn alleles exhibited emerging phenotypes. pxn-1 and pxn -2 show ed lower than WT as light intensity increased to high level s under both lower bound ambient light and upper bound fluctuating light (Figure 3.7A). Pseudo fluorescence images pxn-1 and pxn -2 also reflected the stMeanwhile, pxn-1 and pxn -2 exhibited higher NPQ than WT, especially under ambient light ( Figure 3 .7B). Correspondingly, the kinetics of qE largely res emble d that of NPQ (Figure 3.7C) , and qI in both pxn alleles we re higher than WT under fluctuating light (Figure 3.7D). After recovering on Day 4, pxn-1 and pxn -2 did not show altered response to repeated NPQ ( Figure 3 .7), suggesting that pxn-1 and pxn -2 may have fimemorizedfl the fluctuating light condition s via certain adaptive mechanisms, or that the emerging phenotype on Day 3 was dependent on the light stress on Day 2, i.e. was an accumulative effect from light stress on both Day 2 and Day 3. half period of Day 3 (Figure 3.8). 3.3.6. Supply of CO2Typical phenotype s exhibited on photorespiratory mutants, including reduced photosynthetic rate, altered primary metabolism and compromised stress tolerance, can be complemented by supply of high concentration CO rescued the phenotypes of the photorespiratory mutants and the pxn mutants 2Foyer et al., 2009 , which suppres ses the oxygenase activity of Rubisco (). To test whether the emerging phenotype s in the mutants were dependent on photorespiration, we tested the mutants in the same five -day experiment in DEPI under saturated concentration of CO 2 (3000 ppm) . The measurement of , NPQ, qE and qI were acquired as in the previous five -day DEPI screen. The photorespiratory mutants and pxn mutants were all completely rescued by elevated CO 2 and no phenotypic differences were observed between mutants and WT (Figure 3.9 ). This result suggested that PXN modulates photosynthesis under fluctuating light through photorespiration, and confirmed that it was the impairment of photorespiration in the photorespiratory mutants that caused the emerging phenotypes. 3.3.7. Fast increase in proton motive force contributes to fast qE response in photorespiratory mutants Through the five -day chlorophyll fluorescence -based screen by DEPI, we identified photorespiratory mutants that had strongly reduced photosynthetic capacities under high light (HL) and fluctuating light conditions. Enhanced photoinhibition by HL The highly elevated NPQ and qE in the mutants prompted us to investigate whether the proton motive force ( pmf ) is increased as well, because pmf is the indicat or of the buildup of pH across thylakoid membranes, which in turn leads to the generation of qE ( Takizawa et al., 2007 ). To this end, we measured pmf using a spectrophotometer and simultaneously measured other relevant parameters such as the thylakoid membrane proton efflux (vH +), conductivity of ATP synthase (gH +Pick et al., 2013 photorespiratory mutant plgg1 , which lacks a plastidic glycolate /glycerate transporter (), was added into the photorespiratory mutant group. Since hpr1-1 and hpr1-2 are both knockout mutants and exhibited the same phenotype, we only use d hpr1- 1 hereafter. For the rest of this chapter, hpr1, cat2 and gox1 represented hpr1-1 , cat2 -1 and gox1-3 respectively. Indeed, pmf was higher in photorespiratory mutants at high light intensities. hpr1 and plgg1 exhibited rapid increase s of pmf at moderate light intensities (100 and 250 -2 s-1 ), but the increases were quickly relax ed in spite of increasing light intensit ies -2 s -1 Takizawa et al., 2007 ), which suggested a rapid increase and a fast buildup of (Figure 3.10A). The buildup of could result from increased proton influx and/ or decrease of proton efflux. Since LEF, which is coupled with proton influx (), was largely decreased in hpr1 and plgg1 , a decrease of prot on efflux seemed more likely to be the case. Indeed, we found that hpr1 and plgg1 exhibited strong decrease in proton efflux, indicated by lower vH + at high light intensities (250, 500 and -2 s -1 ) (Figure 3.10A). Consistently , hpr1 and plgg1 also showed reduced ATP synthase conductivity, as indicated by lower gH+ at high light intensities (250, 500 -2 s -1 ). vH + and gH + in cat2 and gox1 was similar to those of WT under all light intensities, suggesting that proton efflux rate and ATP synthase conductivity were not affected in cat2 and gox1 . Furthermore, all mutants had lower LEF as light -2 s -1 and higher (Figure 3.10A), which was in line with a strongly reduced PSII quantum yield C onsistent with results from the chlorophyll fluorescence - -2 s-1 ) (Figure 3.10B). 3.3.8. Activation of CEF in hpr1 under high li ght conditions CEF around PSI is considered an important mechanism to balance the ATP/NADPH energy budget in photosynthesis (Shikanai, 2007 ). Under stress conditions, CEF is activated to meet higher demand of ATP/NADPH, which cannot be sufficiently provided by LEF (Joliot and Johnson, 2011 ). The photorespiratory mutant s showed reduced LEF and lower proton efflux through ATP synthase (vH +To test CEF in the mutants, we first plotted vH ) (Figure 3.11A), which indicated an altered ATP/NADPH ratio and activated CEF. + as a function of LEF to qualitatively analyze CEF related contribution of vH +. Under low light intensities (50 and 100 photons m -2 s -1 ), all photorespiratory mutants showed similar vH +-to-LEF ratio as the WT (Figure 3.11A). However, as light intensity increased to over 250 photons m -2 s -1 , all four mutants shifted to a higher vH +/LEF ratio, and hpr1 exhibited the largest shift (30% increase to WT, p -value < 0.01). This result indicated that CEF was enhanced to compensate for reduced LEF to sustain adequate vH +Since hpr1 showed the strongest phenotypes in the first assay, we used post -illumination chlorophyll fluorescence rise signal as an independent assessment of CEF in hpr1 ( and ATP/N ADPH in the photorespiratory mutants, especially hpr1 . Gotoh et al., 2010 ). In principle, the fluorescence rise signal following imposition of darkness is mainly attributed to CEF -related reduction of the PQ pool through the NAD(P)H dehydrogenase (NDH) complex, thus the kinetics of fluorescence rise can be used to reflect CEF induction (Gotoh et al., 2010 ; Shikanai et al., 1998 ). As shown in Figure 3.11B, hpr1 and WT exhibited similar kinetics of fluorescence ri se under growth light (GL) Œ i.e. 100 photons m -2 s -1 . However, after 6 hours of HL (1000 photons m -2 s-1 ) treatment, hpr1 showed a much more rapid and stronger fluorescence rise than WT. The signal in hpr1 kept increasing and even surpassed the signal under actinic light. These two independent approaches together demonstrated the higher activation of CEF in photorespiratory mutants, especially hpr1 , under HL. 3.3.9. Interaction between photorespiration and excessive energy dissipation It is known that robust induction of qE requ ires the thylakoid membrane protein PsbS as a pH sensor and zeaxanthin (Niyogi and Truong, 2013 ). Rapid increase of qE and elevated proton gradient across the thylakoid membrane (as indicated by high level of pmf ) exhibited on the photorespiratory mutants suggested that these mutants provide ideal systems to study the relationship between and qE. To this end, double mutants were constructed between photorespiratory mutants ( hpr1 , gox1 and plgg1 ) and mutants defective in the biosynthesis of the photoprotective zeaxanthin ( npq1, which has a lower level of zeaxanthin ), the conversion of zeaxanthin to violaxanthin ( npq2, which has a higher level of zeaxanthin ), and the pH sensor PsbS ( npq4, a knockout of PsbS that has no qE under high light). All the mutants were subjected to the five -day experiment in DEPI. Under sinusoidal light on Day 2, hpr1 exhibited highly e levated qE compared to WT ( Figure 3.12A). Similar to previous report (Havaux et al., 2000 ), npq1 had very limited qE due to reduced level of zeaxanthin. However, hpr1 npq1 had significantly decreased qE than hpr1 , but higher qE than that of WT and npq1 (Figure 3.12A). The initial phase of qE increase in hpr1 and hpr1 npq1 were well synchronized, suggesting that the gain of qE in hpr1 npq1 was due to activation of qE by the mutation in hpr1 . This data suggested that higher qE in hpr1 is partially dependent on zeaxanthin level. The increased might bypass zeaxanthin and directly activate qE via protonation of the pH sensor PsbS protein. Consistent with previous studies, npq2 showed faster buildup and a higher level of qE compared to WT as a result of sustaining higher levels of zeaxanthin (Niyogi et al., 1998 ). hpr1 npq2 showe d lower qE than hpr1 , and higher qE than npq2 (Figure 3.12B ), suggesting that a higher level of zeaxanthin might not always enhance qE, or that the equilibrium between zeaxanthin and violaxanthin might be more important for robust qE production. As previously reported, npr4 showed no qE due the absence of the pH se nsor PsbS (Li et al., 2000 ). Adding npq4 to the hpr1 background completely abolished high qE in hpr1 , which suggested that qE in hpr1 is completely dependent on PsbS (Figure 3.12C). Similar patterns have been found in double mutants gox1 npq1 , gox1 npq 2, gox1 npq 4, plgg 1 npq1, plgg 1 npq2, and plgg 1 npq4 ( Figure 3.13 ). Since gox1 and plgg1 had lower qE than hpr1 , they exhibited less effect in qE production in npq1 and npq2 background. Consistently, gox1 npq4 and plgg1 npq4 showed no qE (Figure 3.13). Measurement of , NPQ, and qI was also made under sinusoidal light on Day 2. s in hpr1 , hpr1 npq1, hpr1 npq2 and hpr1 npq4 were similarly decreased, but qIs in hpr1 and hpr1 npq2 were much higher than those of hpr1 npq1 and hpr1 npq4 (Figure 3.14-3.16), indicating that PsbS and zeaxanthin were also required for qI generation in hpr1 . Photosynthetic measurements of double mutants, including gox1 npq1 , gox1 npq 2 and gox1 npq 4, were also measured under dynamically changing light conditions (Figure 3.17-3.19). s in gox1 , gox1 npq1 and gox1 npq4 were similarly decreased, but in gox1 npq2 was partially rescued, suggesting that zeaxanthin can protect photosystem from photoinhibi tion in gox1 . qIs in gox1 npq1, gox1 npq2 and gox1 npq4 were all decreased than that in gox1 , suggesting that PsbS and zeaxanthin were also required for qI generation in gox1 , consistent with the result of hpr1 npq double mutants. Photosynthetic parameters of double mutants, including plgg 1 npq1, plgg 1 npq2, and plgg 1 npq4, were measured under dynamically changing light conditions (Figure 3.20 -3.22). s in plgg1 , plgg 1 npq1, plgg1 npq2 and plgg1 npq4 were similarly decreased, but qIs in plgg1 npq1 and plgg1 npq4, suggesting that that PsbS and zeaxanthin were also required for qI generation in plgg1. Overall, we conclude that the activation of qE in the photorespiratory mutants is completely dependent on PsbS, and partially dependent on zeaxanthin, and that qI is also partially dependent on PsbS and zeaxanthin. 3.3.10. Elevated ROS burst, faster chlorophyll degradation and anthocyanin deficiency in the photorespiratory mutants under high light We have shown that the photorespiratory mutants displayed enhanced photoinhibition under sinusoidal and fluctuating light conditions. Since these are short- term HL treatments, we were interested in investigating how these mutants adapt to long term HL stress. Three -week -old plants were treated with 3 days of HL stress (6 hours of 1000 -2 s -1 daily) or kept under 100 -2 s -1 . Measurements of F v/Fm, chlorophyll and anthocyanin were conducted for each genotype. hpr1, plgg1 and cat2 showed pale green leaves after long term HL stress, with faster chlorophyll degradation as well as pronounced reduction of F v/Fm ( Figure 3.23A and 3.23B). Stronger photoinhibition and accelerated chlorophyll degradation were previously shown to be resulte d from elevated levels of ROS in photorespiratory mutants (Nishiyama et al., 2006). To follow up on this possibility, we took leaf samples of plants after one day of HL treatment or grown under GL, and stained for a major stable ROS, H 2O2, using 3, 3 -diaminobenzidine (DAB). Under GL all the plants exhibited similarly low levels of ROS. Under HL however, hpr1 , plgg1 and cat2 displayed significantly increased levels of H2O2Another aspect of acclimation to long term HL is the induction of anthocyanin, a pigment that protects plants by absorbing excessive UV light (, which were observed as dark brown stains on discolored leaves ( Figu re 3.23C ). Higher level s of ROS burst was further confirmed by quantitative RT -PCR analysis of two oxidative -stress responsive gene markers, a heat shock protein gene 17.6B- CI ( HSP 17.6B- CI) and a transcription factor gene ( WRKY30 ), which were shown to be strongly induced in expression by HL in hpr1 , plgg1 and cat2 (Figure 3.23C ). Page et al., 2012 ; Zeng et al., 2010 ). While leaves of WT and gox1 turned dark purple due to anthocyanin accumulation, this adaptive response was largely missing in hpr1 , plgg1 and cat2 ( Figure 3.23A and 3.23B ). To gain insight into the anthocyanin deficiency, we used quantitative RT-PCR to quantify the transcripts of six representative genes involve d in anthocyanin biosynthesis or regulation . Two known regulatory MYB transcription factor genes that control the accumulation of anthocyanin , Production of Anthocyanin P igment 1 (PAP1 ) and PAP2 ( Borevitz et al., 2000 ; Winkel- Shirley, 2002 ), and four genes that are involved in anthocyanin biosynthesis, including phenylalanine ammonia -lyase 2 (PAL2 ), chalcone synthase ( CHS ), dihydroflavonol 4 -reductase ( DFR ) and flavonol-7-o- rhamnosyltransferase (UGT89C1 ) ( Gou et al., 2011 ; Winkel- Shirley, 2002 ), were tested (Figure 3.23D ). PAP1 , PAL2 , and CHS were less up -regulated by HL in hpr1 , plgg1 and cat2 , indicating that they were still HL -responsive but not as strong as in WT ( Figure 3.23D). PAP2 , DFR and UGT89C1 were even suppressed by HL in hpr1 , plgg1 and cat2 (Figure 3.23D). Overall, expression patterns of the six anthocyanin -related genes correlated with the amount of anthocyanin in the mutants, and the transcriptional regulation in hpr1 , cat2 and plgg1 seeme d insufficient to stimulate accumulation of anthocyanin. Earlier studies reported the inhibitory effect of H 2O2Fahnenstich et al., 2008 on anthocyanin biosynthesis ( ; Hou et al., 2015 ; Vanderauwera et al., 2005 ). Here our data support the view that under HL in the photorespiratory mutants, elevated ROS inhibits anthocyanin biosynthesis through transcriptional regulation. 3.3.11. Compromised integrity of photosynthetic complexes and decreased abundance of photosynthetic subu nits in photorespiratory mutants under high light Optimal performance of photosynthesis requires structural and functional integrity of photosynthetic complexes embedded in thylakoid membranes ( Liu and Last, 2015 ; Rochaix, 2014 ). The enhanced photoinhibition, induced CEF, and deficienc ies in photosynthe tic capacities in the photorespiratory mutants le d to the hypothesis that the integrity of the photosyst hetic complexes may be compromised in the mutants . To test th is hypothesis , we first used blue native polyacrylamide gel electrophoresis (BN -PAGE) to examine the integrity of the native form s of photosyst hetic complexes . Thylakoid membranes were isolated from wild type and mut ants treated with 3 days of HL or grown under GL, and subsequently used for BN -PAGE analysis. The overall distribution and abundance of most complexes were similar between mutants and WT under either GL or HL. However, under HL the abundance of the protein corresponding to the PSI/PSII dimer was reduced in hpr1, plgg1 and cat2 compared to WT (Figure 3.24A). This data was in line with the severe photoinhibition observed in hpr1 , plgg1 and cat2 , since photoinhibition can directly result in decrease of PSII co mplex abundance. We also performed immunoblot analysis to analyze the abundance of representative subunits of each complex. Equal amounts of isolated thylakoid membranes were loaded for standard SDS -PAGE, followed by western blotting with specific antibodi es (Figure 3.24B). After HL treatment, the levels of the PSII core reaction center subunits D1 and D2 were dramatically decreased in hpr1 (10% for D1 and 30% for D2), plgg1 (20% for D1 and 45% for D2) and cat2 (35% for D1 and 50% for D2) relative to that of WT. Levels of the PSI reaction center protein PsaA and antenna protein LHCA2 were also reduced in hpr1 (40% and 50%, respectively) and plgg1 (40% and 80%, respectively) after HL treatment. Interestingly, the Cyt. b6f subunit Cyt. f was much less abundant in hpr1 compared to WT (15% of WT) after HL treatment. However , the ATP synthase subunit CF1 - remained largely unchanged in all the mutants relative to WT (Figure 3.24B). The decrease d levels of PSII reaction center D1 and D2 protei ns, as well as the reduction of the PSI/PSII dimer collectively indicate accelerated damage of photosystems and/ or inhibited repair process es in hpr1 , plgg1 and cat2 . Both data were also consistent with reduced F v/Fm and LEF in these mutants. The decrease of PSI reaction center protein PsaA and antenna protein Lhca2 in hpr1 after HL suggested that PSI complex is also vulnerable to strong photo oxidative stress upon disruption of photorespiration. I n addition to defects in PSII and PSI, t he decrease of the Cyt. b6f subunit Cyt. f in hpr1 could also account for the severely reduced LEF in hpr1 under HL, since Cyt. b6Rochaix, 2011 f significantly limits photosynthetic electron transport (; Yamori et al., 2011 ). Although the conductivity of ATP synthase is significantly decreased in hpr1 under HL, the abundance of ATP synthase was not reduced , which suggests that other mechanisms could account for the reduced ATP synthase conductivity in hpr1 . Taken together, the compromised integrity of photosynthe tic complex es and decreased levels of photosynthetic proteins are consistent with the impairment of photosynthesis in the photorespiratory mutants. 3.3.12. Evidence for the inhibition of triose phosphate isomerase activity and activation of the oxidative pentose phosphate pathway in hpr1 under high light Previous studies have shown that multiple photorespiration intermediates are accumulated in photorespiratory mutants under ambient conditions (Foyer et al., 2009 ; Pick et al., 2013 ; Timm et al., 2013 ; Timm et al., 2012b ). Among these intermediates, phosphoglycolate (P -glyc) was speculated to be toxic in directl y affecting the activity of enzymes participating in the CBB cycle in the chloroplast (Eisenhut et al., 2008 ; Schwarte and Bauwe, 2007 ). A previous study showed that Rubisco activity was inhibited in a glycolate oxidase -deficient rice mutant glo , possibly by high levels of P -glyc (Xu et al., 2009 ). An early report showed that triose phosphate isomerase (TPI) is strongly inhibited by P -glyc in vitro ( Anderson, 1971 ). Triose phosphate isomerase converts g lyceraldehyde 3 -phosphate (GAP) to d ihydroxyacetone phosphate (DHAP). Both of these triose phosphates are required to regenerate ribulose 1,5 -bisphosphate (RuBP) to make starch; they can also be exported to the cytosol for sucrose synthesis. A block in stromal TPI could be overcome by export of GAP to the cytosol, where it is converted to DHAP, followed by the import of DHAP back to the chloroplast (Athanasiou et al., 2010 ; Dyson et al., 2015 ). An alternative to the import of DHAP is to process the carbon to glucose 6 -phosphate (G6P), which can be imported to the chloroplast by the glucose -6- phosphate transporter GPT2 (Athanasiou et al., 2010 ; Dys on et al., 2015 ). Induced expression of GPT2 would increase the protein amount of GPT2, which provides a higher capacity for reimport of carbon into the stroma. To test whether GPT2 is up -regulated, we first extracted RNA from leaf samples of each genotype after one day of HL treatment or grown under GL, and examined the expression level of GPT2 by quantitative RT -PCR. Under GL, as the WT, all tested photorespiratory mutants showed similarly low expression levels of GPT2 (Figure 3.25A). HL treatment induced the expression of GPT2 in all mutants and WT, but to a much larger extent in hpr1 and plgg1 , which was consistent with the other profound phenotypes displayed in these two mutants. The stronger up -regulation of GPT2 by high light suggested that there could be a significant flux of G6P from the cytosol to the chloroplast in these two mutants. We also measured the levels of GAP and DHAP in HL -treated hpr1 . The average level of DHAP was higher in hpr1 than WT, but the difference was not statistically significant (Figure 3.25B). However, the level of GAP in hpr1 was over two -fold higher than WT (p -value < 0.01). The ratio of DHAP to GAP w as lower in hpr1 than WT (Figure 3.25B) and well below isomerase equilibrium (Sharkey an d Weise, 2012 ). Since TPI converts GAP to DHAP, the lower DHAP/GAP indicates that TPI activity was inhibited. It was previously shown that hpr1 accumulates higher levels of P -glyc in ambient air, and HL can stimulate photorespiration and probably enhance P -glyc accumulation (Timm et al., 2008 ). Our results support the model that high level s of P -glyc in hpr1 under high light inhibits TPI activity and consequently disrupts the equilibrium of DHAP/GAP. As a bypass to inhibited TPI activity and disrupted equilibrium of DHAP/GAP, the export of GAP to the cytosol allows the conversion of GAP to G6P, whic h can then be re -imported back to the chloroplast to allow photosynthesis to proceed. Re -import of G6P also stimulates the oxidative branch of the pentose phosphate pathway, in which NADP +Schnarrenberger et al., 1995 is reduced to NADPH using energy from the conversion of glucose -6-p hosphate to ribulose 5 -phosphate ( ) . Activation of the oxidative branch of the pentose phosphate pathway results in a futile cycle (Sharkey and Weise, 2012 ) that in turn leads to a higher demand of ATP. The increased CEF in hpr1 under HL condition may be a mechanism to supply the extra ATP. 3.4. Discussion In recent years considerable progress has been made in identifying novel peroxisomal proteins, charactering their biochemical functions, and discovering their involvements in metabolic pathways and stress response. Towards understanding the function of peroxisomes at a systems level, the methodology that utilizes rich g enetic materials combined with powerful high -throughput phenotyping platforms has proven to be an efficient way for discovering a wide range of phenotype s. Increasing evidence suggested the physical and functional connections between peroxisome s and chloro plast s. Here we report the first comprehensive peroxisome -centered reverse genetics screen, which was aimed at discovering peroxisomal proteins that contribute to robust photosynthetic capacity under dynamic light conditions, followed by detailed character ization of a group of photorespiratory mutants identified from the screen. 3.4.1. Photorespiration is the major peroxisomal function that connects to photosynthesis The mutant screen reported here is the first comprehensive peroxisomal mutant screen in te rms of the large coverage of peroxisomal proteins and the number of tested mutants. Mutant s of genes involved in major peroxisomal functions, i.e. fatty acid -oxidation , glyoxylate cycle, biosynthesis of JA, conversion of IBA to IAA, photorespiration, H 2O2Novel emerging phenotype s displayed by the NAD detoxification and others were included, yet only mutants deficient in photorespiration -related proteins were identified, suggesting that photorespiration is the primary and dominant peroxisomal pathway that significantly impact s photosynthesis. + transporter mutant pxn under fluctuating light suggested that peroxisomal NADH homeostasis is important for robust photosynthesis. CO 2 can rescue the phenotype of pxn , suggesting that peroxisomal NADH homeostasis mo dulates photosynthesis through photorespiration . Previous studies showed that NADH produced by PMDHs facilitates the reducing reaction catalyzed by HPR1 (Cousins et al., 2008a ), and that the double mutant pmdh1 pmdh2 exhibited relatively subtle but statistically significant changes in photosynthesis (Cousins et al., 2008a). NAD +Bernhardt et al., 2012 delivered by PXN could be used by PMDH to generate NADH, thus contributing to photorespiration. Both PMDH and PXN may also be involved in fat ty acid degradation during seed germination, as the knockout mutants exhibited germination defect (; Pracharoenwattana et al., 2007 ). Thus, PMDH and PXN seem to play dual roles in fatty acid -oxidation during seed germination and photorespiration in adult plants. We have shown in this study that previously reported peroxisomal photorespiratory mutants, such as hpr1 and cat2 , exhibited profound phenotypes under dynamic light, which makes sense because hpr1 and cat2 already grew slowly in ambient air. For gox1 , which grew as well as WT in ambient air, the emerging phenotype could not be revealed without subjecting the mutant to stress condition s and monitoring real -time photosynthetic capacity, which proved the high sensitivity of phenotype discovery by DEPI. The general growth abnormality exhibited in the peroxisome biogenesis mutant pex14 , such as extremely small rosette and pale green leaves, correlated with its strongly affected photosynthetic capacity. In this study, peroxisomal division mutants also displayed significant phenotype s. DRP3 proteins are involved in both mitochondrial and peroxisomal division, and double mutan t drp3A drp3B showed growth retardation ( Zhang and Hu, 2009 ). DRP5B participates in both chloroplast and peroxisome division, with a stronger role in the chloroplast (Zhang and Hu, 2010 ). The affected growth in drp5B mutant could be recovered by CO 2 , suggesting that the emerging phenotype exhibited in drp5B is mostly due to insufficient photorespiration. The strongest emerging phenotype exhibited in the triple mutant drp3A drp3B drp5B should be an additive effect of the photorespiratory defect s caused by impaired division of all three organelles (chloroplasts , peroxisomes and mitochondria) involved in photorespiration. 3.4.2. Various enzymes in photorespiration play quantitatively and kinetically different roles in photorespiration under dynamic light condition s Extensive real -time monitoring of in vivo physiological parameters, in our case photosynthetic capacities, provides valuable information on the specific importance of each enzyme in the same pathway. GOX1 and HPR1 are metabolic enzymes directly involved in the photorespiratory metabolic flux. CAT2, on the other hand, is responsible for degrading H 2O2Mhamdi et al., 2012 produced in photorespiration and other oxidative reactions, thus it is indirectly involved in photorespiratory metabolism (). Our results showed that HPR1 has the most significant impact on photosynthesis, as the hpr1 mutant showed the strongest phenotype under dynamic light conditions. Although a cytosolic HPR2 was identified as a bypa ss to the peroxisomal HPR1, the metabolic conversion from hydroxypyruvate to glycerate is still predominately catalyzed by HPR1 (Timm et al., 2008). Due to functional redundancy between the highly identical genes GOX1 and GOX2 , gox1 knockout only exhibited emerging phenotype, which can also explain why gox1 under sinusoidal light happened later than in hpr1 . Mutant cat2 hpr1 , which is possibly due to the redundant role between CAT2, CAT1 and CAT3, although CAT2 is the mostly highly expressed in leaves. Both hpr1 and cat2 conditions, indicating that photorespiration is critical in protecting photosystem from photoinhibition. Under fluctuating light condition s, the degree of responsive adaptation in gox1 is more robust than in hpr1 and cat2 , as indicated by the range of qE fluctuation. This suggested that GOX2 still largely, although not fully, functionally substituted GOX1, and that the photodamage in hpr1 and cat2 may also inhibit components responsible for qE build up. 3.4.3. Highly elevated qE in photorespiratory mutants i s due to rapid buildup of proton gradient across thylakoid membrane and largely dependent on PsbS and zeaxanthin Stimulated energy -depend ent quenching under high light results from the buildup of proton gradient across the thylakoid membrane (Niyogi and Truong, 2013 ). Photorespiration mutants analyzed in this study, especially hpr1 and plgg1 , exhibited a nice correlation between qE and pmf . pmf is an i ndicator of the proton gradient across the thylakoid membrane (Takizawa et al., 2007 ), thus higher pmf in hpr1 and plgg1 indica ted elevated proton gradient. Inhibited activity of ATP synthase, which pumps out proton from lumen to stroma, was probably the major reason for the buildup of the proton gradient in these mutants. The exact inhibitory effect on ATP synthase activity in th e photorespiratory mutants remains to be investigated. One speculation is that the depletion of glycerate to CBB cycle, as a result from blocking of photorespiration, slows down the CBB cycle, which in turn leads to accumulation of ATP in the stroma. It is possible that accumulated stromal ATP has a negative feedback regulation on ATP synthase conductivity. The highly activated qE and pmf in hpr1 provide a useful in vivo system to study the relationship between strong pH and NPQ components in generating NPQ. Adding hpr1 into the npq4 background, which lack s the key pH sensor PsbS, did not change the qE phenotype in npq4 (Figure 3.12C), suggesting that PsbS is downst ream from HPR1 in generating qE, i.e. HPR1 acts through PsbS in qE generation. However, the addition of hpr1 to npq1, which has diminished level of zeaxanthin and qE, led to a significant stimulation of qE (Figure 3.12A), suggesting that the qE in hpr1 is only partially dependent on zeaxanthin. Besides, qE in double mutant hpr1 npq2 was between that of hpr1 and npq2, suggesting that higher zeaxanthin cannot always enhance qE or the equilibrium between zeaxanthin and violaxanthin is more important for enhancement of qE (Figure 3.12B). Evidence from the double mutant analysis indicated that activated qE by increased pH in hpr1 was completely dependent on the PsbS protein, and partially dependent on zeaxanthin. Other double mutants, including gox1 npq1 , gox1 npq 2, gox1 npq4, plgg 1 npq1, plgg 1 npq2, and plgg 1 npq4, showed similar patterns of the relationship between photorespiration and NPQ components regarding qE generation, based on which we can make the same conclusions as from results of the hpr1 npq double mutant analysis. Previous reports showed that unusually high was able to bypass PsbS and stimulate qE through direct protonation of LHC in vitro (Sylak -Glassman et al., 2014), whereas our evidence indicated that the high in vivo is unable to stimulate qE. 3.4.4. Activation of CEF and inhibition of TPI occurs in photorespiratory mutants under high light We have shown that photorespiratory mutants had lower LEF under high light, and hpr1 and plgg1 , in particular, had the lowest LEF. Meanwhile, hpr1 and plgg1 showed strongly reduced proton efflux vH +. The disrupted ratio between LEF and vH + may result from the activation of CEF. Indeed, hpr1 showed higher CEF under HL, as shown in two independent assays (Figure 3.11). Our evidence suggested the reasons for activated CEF in hpr1 . ROS and H 2O2Casano et al., 2001 have been shown as direct and indirect players in activating CEF (; Strand et al., 2015 ), and we showed that the amount of H 2O2Takahashi et al., 2007 and transcripts of oxidative stress responsi ve gene s were increased after short term HL treatment (Figure 3.23C). In addition, we have shown that under HL , the enzymatic activity of TPI was inhibited, possibly by the toxic levels of P -glyco in hpr1 , as shown by the disequilibrium of GAP and DHAP (Fi gure 3.25B). As a bypass of this inhibition, re -import of G6P from cytosol to the chloroplast stroma may allow photosynthesis to proceed, but with a trade -off that the oxidative branch of pentose phosphate may be simulated and higher ATP demand is created. Previous studies suggested that the disruption of photorespiration interrupts the CBB cycle, which results in accumulated ATP and NADPH to generate ROS (). Here we provided the evidence supporting that the oxidative branch of the pentose phosphate pathway is another pathway for a source of ROS production in hpr1 . 3.4.5. Photorespiratory mutants exhibited compromised PS complex integrity, diminished PS subuni t abundance and reduced stress resistance after HL treatment Multiple lines of evidence suggested the molecular basis of the strong photoinhibition in photorespiratory mutants. The level of the PSII -PSI dimer was reduced in hpr1 after HL treatment. Subunit s in PS systems, such as D1 and D2 in PSII reaction center, PsaA in the PSI core , LHCAII in PSI antenna and Cyt. f in Cyt. b6Takahashi et al., 2007 f, were significantly reduced in level. Decrease of D1 in other photorespiratory mutants, such as glyk , was demonstrated in previous studies (). D2, as shown here, the mutants. Although PSI is more stable than PSII under photo damage, we showed decreased levels of the PSI core protein and PSI antenna protein in hpr1 after HL treatment. Decreased level of Cyt. b6f, together with reduced abundance of the PSII core protein, correlated with decreased LEF in the mutants, since Cyt. b6Rochaix, 2011 f is the rate -limiting step in photosynthetic electron transport ( ; Yamori et al., 2011 ). In addition to short term HL stress, photorespiratory mutants also demonstrated strong phenotype s after 3 days of HL treatm ent. Fast degradation of chlorophyll, which was possibly caused by over accumulation of ROS over time, resulted in pale green leave s. Deficiency in the induction of photoprotective pigment anthocyanin due to transcriptional repression of enzymes in the anthocyanin biosynthetic pathway was also shown in the photorespiratory mutants after long term HL. H 2O2Vanderauwera et al., 2005 was shown as a signal in repressing anthocyanin biosynthesis in cat2 ( ). Our data confirmed this result in cat2 , and in addition found similar phenotype and mechanism in hpr1 and plgg1 . In addition to the inhibitory effect of ROS on anthocyanin b iosynthesis through transcriptional regulation, disrupted amino acid metabolism resulted from the blocking of photorespiration may also negatively affect anthocyanin biosynthesis by depriving the anthocyanin biosynthetic precursors. It was previously repor ted that supplementing phenyalanine can increase anthocyanin content in plants (Voll et al., 2004), and expressing P henylalanine Ammonia -L yase (PAL), which conver ts phenylalanine to ammonia in anthocyanin biosynthesis pathway, in Daucus carota induced accumulation of anthocyanin (Heinzmann and Seitz, 1977 ). Drastic changes in amino acid metabolis m were identified in photorespiratory mutants (Pick et al., 2013 ; Timm et al., 2012b ; Timm et al., 2008 ), and the herbicide glyphosate inhibits amino a cid biosynthesis pathway, including phenylalanine , as well as enzymatic activity of proteins involved in photorespiration (Vivancos et al., 2011 ). It is also possible that the disrupted level of phenyalanine is the cause of anthocyanin deficiency in the photorespiration mutants. 3.4.6. Conclusion. To conclude, our study has helped us to come up with a n integrated model for the events that occur in the photorespiration mutants (Figure 3.26). First , increased photorespiration under high light increases the accumulation of phosphoglycolate in photorespiratory mutants. Phosphoglycolate inhibits TPI activity, which leads to the activation of the oxidative branch of pentose pathway that requires more ATP and increases oxidative stress. Second , depletion of the CBB cycle intermediates slows dow n the CBB cycle , which causes accumulation of unused ATP and NADPH. The unused ATP in stroma inhibits the ATP synthase conductivity and leads to increased pmf and subsequent higher NPQ to dissipate excessive energy. Less consumed NADPH can be used to gener ate more ROS and creates enhance oxidative stress as well. Third In summary, our comprehensive peroxisomal mutant screen has identified peroxisomal proteins involved in modulating photosynthesis and photorespiration under dynamic light conditions. Further characterization of the mutants also helped to dissect the qualitative and quantitative contribution of different proteins in the photorespiratory pathway to photosynthesis, providing new insight into the connection between photorespir ation and photosynthesis. Knowledge gained from this study opens an avenue for future research on photosynthesis, photorespiration and interorganelle communication. , the increased oxidative stress, resulted from the two effects mentioned above, activates CEF to supply higher ATP/NADPH. Besides, elevated ROS impacts various photosynthetic processes, such as photoinhibition, compromised photosystem integrity, damaged photosystem subunit. 3.5. Materials and m ethods 3.5.1. Plant materials and growth conditions Arabidopsis thaliana ecotype Col -0 and Ws-4 were used as wild type (WT). T -DNA insertion mutant lines were obtained from the Arabidopsis Biological Resource Center (ABRC; http://www.arabidopsis.org/ ) and confirmed by PCR -based genotyping. Information on gene locus and annotation of all the tested mutants is in Table 3.1. For constructing the double mutants, npq1 and npq2 are the same as npq1-2 and npq2-1 in a previous study ( Niyogi et al., 1998 ), and npq4 is npq4-1 in Li et al (2000) ( Li et al., 2000 ). Seeds were sown in the soil, stratified in the dark at 4 °C for 3 days, and plants were grown under 16/8 -h light/dark cycle of 100 -2 s -1 of white light at 22 °C and 60% humidity. P lants that were screened in the Dynamic Environment Photosynthesis Imager (DEPI) were grown with black foam masks covering the soil for better background separation from the rosette leaves for fluorescence imaging. To allow for acclimation, plants were transferred to the imaging chamber 1 -2 days before the 5 -day experiment. Growth conditions in the imaging chambers were similar to those described above. 3.5.2. Fluorescence measurement s, image processing and data analysis Fluorescence measurements were performed in the Dynamic Environment Photosynthesis Imager (DEPI), as described in Kramer et al. , 2013, US patent WO 2013181433 A2 . The initial fluorescence, F 0, was determined by turning on the weak measuring light. F m was obtained by exposing the plants to a 0.3 s saturation flash of approximately 10,000 -2 s -1 Dutta et al., 2015 . Detailed methods were described in a previous study ( ). Chlorophyll fluorescence images were processed using Visual Phenomics software ( Tessmer et al., 2013 ). The maximum quantum effic iency of PSII photochemistry (F v/Fm) was calculated as (F m Œ F 0)/Fm Krause an d Jahns, 2003 (; Krause and Weis, 1991 ), where F0 is the fluorescence of the dark -adapted plant and F m is the maximum fluorescence. T he quantum yield of m™Œ F s)/F m™, where Fs is the steady -state fluorescence and F mBaker, 2008 ™ is the fluorescence maximum at steady state ( ). NPQ was calculated as (F mŒF m™)/ F mBaker, 2008 ™ (), qE as F m/F m™Œ Fm/F mfl, and qI as (F m-F mfl)/F mfl, where F mBaker, 2008 fl is the post -illumination fluorescence maximum (; Krause and Jahns, 2003 ). At least three replicates for each genotype were tested. All imaging data were put in Origin (OriginLab, Northampton, MA) for data analysis. Heatmaps were generated with OLIVER software ( Tessmer et al. , submitted ). 3.5.3. In vivo spectroscopic assays All spectroscopic measurements were made using inta ct and fully expanded leaves in 25 -30-d ay-old plants just before bolting. Plants were dark adapted for 10 min before analysis. Actinic light intensities ranged between 50 and 750 -2 s -1 Hall et al., 2013 . Chlorophyll a fluorescence yield changes and light -induced absorbency changes were measured using a laboratory -built spectrophoto meter/fluorimeter ( ) using the techniques described in Livingston et al., (2010 ). Saturation pulse chlorophyll a fluorescence yield parameters (F0, Fm, Fs, F m', F mAvenson et al., 2004 '') were recorded as described (; Baker, 2008 ; Baker et al., 2007 ; Kanazawa and Kramer, 2002 ), using 1 -s saturation pulses of 10,000 -2 s -1 Edwards and Baker, 1993 . These measurements were used to estimate , LEF, NPQ, qE and qI ( ; Genty et al., 1989) qE and qI were calculated using the same equations mentioned above. Leaf absorptivity of all the mutants did not differ from WT (p -value > 0.15, n=4). The ECS measurements , which were used to c alculate pmf , vH + and gH +Avenson et al., 2004 , were normalized for variations in leaf thickness and pigmentation by the extent of the rapid -rise single -turnover flash -induced ECS (; Livingston et al., 2010 ). The ECSt ECS Baker et al., 2007 parameters were taken from a first order exponential decay fit to ECS dark interval relaxatio n kinetics as described in ( ). pmf was calculated as amplit ude of the ECS first order exponential decay, vH + was calculated as the slope during the initial linear phase of ECS first order exponential decay, and gH + was calculated as 1/ ECS . 3.5.4. Measurements of CEF LEF, with no contributions from CEF, should produce a constant ratio of proton flux to electron transfer through PSII (Sacksteder et al., 2000 ), which in our measurements should result in a constant, linear slope of vH + plotted against LEF. The relative rates of CEF can then be estimated by the increase in the slope of vH +Livingston et al., 2010 versus LEF above the baseline slope for LEF alone ( ). Post- illumination transient chlorophyll fluorescence was measured as described (Gotoh et al., 2010 ). Leaves were illuminated for 40 s with 150 -2 s -1 , followed by a 10 -s dark interval. The plastoquinone pool was then oxidized by two 200 -ms flashes of 730- nm light at 10 s apart. 3.5.5. Statistical analysis Descriptive statistics and figures were generated using Origin 9.0 software (Microcal Software), and statistical analyses were performed using MATLAB R2012a (The MathWorks, Inc.) or Microsoft Excel. Except for calculating the difference of slope of vH + against LEF, which I used ANCOVA (a nalysis of covariance ), Student™s t - test were used for evaluating the differences of other parameters. 3.5.6. Thylakoid membrane preparation Thylakoid membranes were prepared as previously described (Zhang et al., 199 9). The leaves were homogenized in an ice -cold isolation buffer containing 400 mM sucrose, 50 mM HEPES -KOH, pH 7.8, 10 mM NaCl, and 2 mM MgCl 2 with a chilled mortar and pestle and filtrated through two layers of cheesecloth. The filtrate was centrifuged at 5000g for 10 min. The thylakoid pellets were washed with isolation buffer, re -centrifuged, and suspended in isolation buffer. The resulting t hylakoid membrane pellets were either used freshly or frozen in liquid N 2 and stored at Œ70 °C before use. The chlorophyll content was determined by spectrophotometer measurement according to ( Wellburn, 1994). 3.5.7. BN-PAGE and immunoblot analyses BN-PAGE was performed by modification of a previously described protocol (Liu et al., 2012 ), and thylakoid membranes were solubilized using 2% dodecyl --D- maltopyranoside . Electrophoresis was performed using a Native PAGE TM Novex @Immunoblotting was performed according to standard techniques by probing with specific antibodies after electroblotting of thylakoid membranes on SDS ŒPAGE gels onto nitrocellulose membranes (GE Healthcare, http://www3.gehealthcare.com) ( 4Œ16% Bis/Tris mini gel and an XCellSureLock mini -cell (Life Technologies, https://www.lifetechnologies.com) at 4°C according to the manufacturer™s instructions. Liu et al., 2012). Rabbit primary antibodies were purchased from Agrisera (http://www.agrisera.com ). Primary antibodies were diluted 20,000 -fold for antibodies against D1 and D2 , 5000-fold for LHCAII, cytochrome f , and 2500-fold for -PsaA ( all antibodies we re generously shared from Dr. Rob Last Lab) . S ignals from horseradish peroxidase -conjugated goat anti -rabbit IgG (H+L) were visualized using Clarity Western ECL substrate ( Bio -rad, http://www.bio -rad.com/en -us/product/clarity- ecl-western -blotting -substrate ) and analyzed using software Image LabTM (ver sion 5.0) (Bio ŒRad, http://www.bio -rad.com ). Protein accumulation was normalized to the amount of Coomassie Brilliant Blue -stained LHCII of PSII as an internal standard and was quantified from ChemiDoc TM XRS+ scans of the membrane using Image Lab TM software (http://www.bio -rad.com/en -mx/sku/170-8265-chemidoc- xrssystem -with -image -lab -software). 3.5.8. Quantitative RT -PCR Arabidopsis total RNA was isolated using a Plant RNeasy kit according to the manufacturer™s instructions (Qiagen, https://www.qiag en.com), and treated with DNase I. 500 ng of each RNA sample was used for cDNA synthesis with random primers and iScript TM cDNA Synthesis Kit (Bio -rad, http://www.bio -rad.com/). Quantitative real -time PCR was performed using a 7500 Fast Real -Time PCR Syst em with Fast SYBR Green Master Mix (Applied Biosystems, http://www.appliedbiosystems.com). Relative gene expression was normalized to ACTIN2 (At3g18780). Expression was determined in triplicate biological measurements. 3.5.9. Measurement of chlorophyll and anthocyanin For chlorophyll measurement, rosette leaves were weighed and placed into 2 ml 80% acetone in the dark for 3 days. Absorbance at 645 nm and 663 nm was measured using a spectrophotometer. Total chlorophyll content = (22.22 x A 645 + 9.05 x A 66 3Wellburn, 1994 ) µg/ml x 2 ml /leaf fresh weight in mg ( ). For anthocyanin measurement, rosette leaves were weighed, frozen by liquid nitrogen, and ground to powder. After adding 2 ml extraction buffer ( 1% HCl in methanol), the samples were placed at 4 °C overnight. Later, an equal amount of chloroform was added, and the mixture was centrifuged for 5 min. After the top supernat ant was transferred to a new tube, equal volume of 60 % extraction buffer was added. Absorbance of each tube at 530 nm and 657 nm were measured with a spectrophotometer. Anthocyanin content = (A 530 -A 657 Zeng et al., 2010 ) /weight (). 3.5.10. In situ detection of H 2OIn situ detection of H 2 2O2Thordal- Christensen et al., 2002 was performed by treating plants with DA B- HCl as previously described (). Detached rosette leaves were vacuum- infiltrated with 5mM DAB -HCl, pH 3.8, for 5 min, and incubated in the same solution under growth light or HL for 6 h. Stained leaves were boiled in an acetic acid: glycerol: ethanol (1:1:3 [v/v/v]) solution for 5 min and photographed. 3.5.11. Measurement of GAP and DHAP ~500 mg F.W. of l eaves were immediately frozen in liquid N 2, weighed and fully pulverized using Retsch Mill M300 (Retsch, http://www.retsch.com/ ). Cold 3.5% perchloric acid (2 l per mg tissue ), was added with tissues in eppendorf tubes, and tubes were placed on ice for 5 min incubation. Extracts were centrifuged at maximum speed at 4 °C for 10 min. Approx. 500 l supernatant was recovered. Neutralizing buffer (2M KOH, 150 mM HEPES and 10mM KCl), in the ratio of 0.25 l per l of recovered supernatant, was added to the supernatant to bring the pH to ~7. pH sticks were used to check pH , volume of neutralizing buffer was adjusted accordingly, and volume of neutralizing buffer was recorded. Samples were frozen and thawed to precipitate salts, and centrifuged at maximum speed for 2 min. Supernatant was pipette off for immediate GAP and DHAP assays, or frozen at -80 °C for future assay s. (Adapted protocol from Dr. Thomas Sharkey Lab at MSU) The amount of GAP and DHAP was 50 l supernatant was added to 800 l reaction buffer (100 mM HEPES buffer pH 7.6, 1 M DTT, 1M KH 2AsO 4OH and JV, 1972, 50 mM NAD and 50 Mm ADP) in a cuvette , which was inserted to the cuvette holder in the spectrophotometer. 5 l of glyceraldehydes -phosphate dehydrogenase GAPDH (Sigma G -5537) was added into cuvette and immediately mixed using a clean plastic stick. Absorbency of NADH at 340nm was recorded throughout the reaction, which reflected the reaction kinetics. The difference of abs (340) between the baseline and the maximum level was measured to estimate the level of GAP. Next, 5 l of triose phosphate isomerase TPI (Sigma T -6285) was added into cuvette and immediately mixed by a clean plastic stick. Absorbance of NADH at 340nm was recorded throughout the reaction, and the difference of abs at 340 nm between the baseline and the maximum level was measured to estimate the level of DHAP. This protocol was adapted from Dr. Thomas Sharkey La b and modified from (; Shirokane et al., 2000 ). 3.6. Acknowledgement I thank Dr. David Kramer for constant support, share of devices and insightful discussions. I also want to give appreciations to the great helps from Kramer Lab members: Dr. Jeffery Cruz for teaching me chlorophyll fluorescence measurement techniques and data analysis, Linda Savage for scheduling my experiments, Dr. Deserah Strand for technical support on in vivo spectroscopic assays and CEF measurements , Geoffry Davis for sharing npq1, npq2 and npq4 mutants and help with data analysis, David Hall for image processing, Dr. Mio Sato -Cruz and Ruby Carrillo for sharing devices. I want to especially thank Dr. Jun Liu for teaching me BN -PAGE techniques, doing western bl ot of all the photosynthetic subunits and constant encouragements. I want to express my gratitude to other collaborators: Dr. Jin Chen for teaching me using R programming and data analysis, Dr. Thomas Sharkey and Dr. Sean Weise for providing ideas and help ing with GAP and DHAP measurements. Finally, I would like to thank Center for Advanced Algal and Plant Phenotyping (CAAPP) at MSU -PRL for strong technical support. APPENDIX Figure 3.1. Revealing photosynthetic phenotypes of peroxisomal mutants under dynamic light conditions using DEPI. (A) 5-day dynamically changing light conditions. The x axis represents time. The y axis ased on log fold- change in mutant relative to the WT. In each heatmap, the x axis represents time points, and the y Figure 3.1. (c ont™d) axis represents the 147 screened peroxisomal mutants. Mutants are positioned from top to bottom based on the sum of all values (low to high ) across 5 days. Corresponding color significant difference from WT. It is a zoom-in picture of the area in the black rectangle in Figure 3.1B . The x axis represents time points, and t he y axis represents mutants. Color code is under the heatmap. Figure 3.2. Photosynthetic performance of the pex14 mutant under dynamically changing light conditions . Figure 3.2. (cont™d) The positive control pex14 was tested in DEPI under dynamically changing light conditions. Each horizontal panel shows the measurement of a photosynthetic parameter across 5 days. The x axis represents time points, and y axis represents the value o f the corresponding parameter. Three biological replicates were used for each genotype. Figure 3.3. Photosynthe tic capabilities of peroxisomal division mutants under dynamically changing light conditions . Figure 3. 3. (cont™d) Peroxisomal division mutants drp5B , drp3A drp3B , and drp3A drp3B drp5B , were tested in DEPI under high light and fluctuating light condition s. Each horizontal panel shows the measurement of a photosynthetic parameter across 5 days. The x axis represents time points, and y axis represents the value of corresponding parameter. Three biological replicates were used for each genotype. Figure 3.4. Gene expression analysis and growth appearance of photorespiratory mutants. (A) Semi quantitative RT -PCR a nalysis of gene expression of the photorespiratory mutants that had not been reported before, including gox1-1 , gox1-2 , gox2 -1 , gox2-2 and pmdh1 . (B) Growth phenotype of photorespiratory mutants that had been growing under ambient air for 3 -3.5 weeks. Figure 3.5. Photosynthetic performance of p hotorespiratory mutants under high light and fluctuating light condition s. Figure 3.5. (cont™d) Photorespiratory mutants, including hpr1-1 , hpr1-2 , gox1-3 and cat2 -1 , and WT were tested in DEPI under high light and fluctuating light condition s. Each horizontal panel shows the measurement of a photosynthetic parameter across 5 days. The x axis represents the time points, and y axis represents the value of the corresponding parameter. Three biological replicates were used for each genotype. Figure 3.6. Chlorophyll fluorescence images of representative photorespiratory mutants under sinusoidal light on Day 2 Figure 3.6. (cont™d) Pseudo fluorescence images of hpr1-1 , gox1-3 and WT are shown. Each horizontal panel shows the measurement of a photosynthetic parameter. Images for individual plants are arranged from left to right according to the chronological order of each measurement under sinusoidal light on Day 2, which inclu de measurements at 32 time points . Figure 3.7. Mutants of the peroxisomal NAD + transporter PXN, pxn-1 and pxn-2 , exhibit emerg ing phenotype under fluctuating light conditions. Figure 3.7 . (c ont™d) Each horizontal panel shows the measurement of a photosynthetic parameter across 5 days. The x axis represents the time points, and y axis represents the value of the corresponding parameter. Three biological replicates were used for each genotype. Figure 3.8. Chlorophyll fluorescence image of pxn under the first half period of fluctuating light on Day 3. Figure 3.8. (cont™d) Pseudo fluorescence images of pxn -1 , pxn -2 and WT are shown. Each horizontal panel shows the measurement of a photosynthetic parameter. Images for individual plant are arranged from left to right according to the chronological order of each measurement under the first half period of fluctuating light on Day 3, which includes measurements at 32 time points. Figure 3.9. Supply of CO 2 rescued the emerging phenotype exhibited in the photorespiratory mutants and pxn mutants. Figure 3.9. (cont™d) Photorespiratory mutants and pxn mutants were tested under dynamically changing lights in the 5- day experiment setting in DEPI with elevated CO2 (3000ppm). Three biological replicates were used for each genotype. Figure 3.10. Quantitative spectroscopic analysis of photorespiratory mutants. (A ). In vivo spectroscopic assays of m -2 s-1 of light . Three biological replicates were used for each genotype. (B). I n vivo spectroscopic in the mutants. Figure 3.11. Activation of CEF in hpr1 under high light condition s. Figure 3.11. (cont™d) (A). Light driven proton efflux vH + as a function against LEF in the mutants and WT -2 s-1 of light. Three biological replicates were used for each genotype. B. Chlorophyll fluorescence rise post illumination in hpr1 and -2 s-1 m-2 s-1 ). Figure 3.12. qE measurement in hpr1 npq double mutants. Figure 3.12. (cont™d) (A) qE kinetics under sinusoidal light on Day 2. (B) qE kinetics under sinusoidal light on Day 2. (C) qE kinetics under sinusoidal light on Day 2. Three biological replicates were used for each genotype. Figure 3.13. qE measurement of the gox1 npq and plgg1 npq double mutants Figure 3.13. (cont™d) (A-C) qE kinetics of the gox1 npq double mutants under sinusoidal light on Day 2. (D-F) qE kinetics of the plgg1 npq mutants under sinusoidal light on Day 2. Three biological replicates were used for each genotype. Figure 3.14. Photosynthetic measurements of hpr1 , npq1 and hpr1 npq1 under dynamically changing light conditions . Three biological replicates were used for each genotype. Figure 3. 15. Photosynthetic measurements of hpr1 , npq2 and hpr1 npq2 mutants under dynamically changing light conditions . Three biological replicates were used for each genotype. Figure 3. 16. Photosynthetic measurements of hpr1 , npq4 and hpr1 npq4 under dynamically changing light conditions. Three biological replicates were used for each genotype. Figure 3. 17. Photosynthetic measurements of gox1, npq1 and gox1 npq1 under dynamically changing light conditions. Three biological replicates were used for each genotype. Figure 3. 18. Photosynthetic measurements of gox1, npq2 and gox1 npq2 under dynamically changing light conditions . Three biological replicates were used for each genotype. Figure 3. 19. Photosynthetic measurements of gox1, npq4 and gox1 npq4 under dynamically changing light conditions. Three biological replicates were used for each genotype. Figure 3. 20. Photosynthetic measurements of plgg1 , npq1 and plgg1 npq1 under dynamically changing light conditions . Three biological replicates were used for each genotype. Figure 3. 21. Photosynthetic measurements of plgg1 , npq2 and plgg1 npq2 under dynamically changing light conditions. Three biological replicates were used for each genotype. Figure 3. 22. Photosynthetic measurements of plgg1 , npq4 and plgg1 npq4 under dynamically changing light conditions. Three biological replicates were used for each genotype. Figure 3.23. Adaptation of the photorespiratory mutants to long term HL stress . Figure 3.23. (cont™d) (A). 3- week -old plants grown under GL and treated with 3 days of HL. (B). Quantification of F v/Fm, chlorophyll content and anthocyanin content. Three biological replicates were used for each genotype. (C). DAB staining of H 2O2 in leaves of plants under GL and after 6 hours of HL treatment (top), and quantitative RT -PCR analysis of two oxidative stress -responsive genes (bottom) . Three biological replicates were used for each genotype. (D). Quantitative RT -PCR analysis of six anthocyanin biosynthetic or regulatory genes. Three biological replicates were used for each genotype. Figure 3.24. Analysis of the integrity of photosynthetic complexes and levels of photosynthetic subunits in photorespiratory mutants under high light. (A) . BN -PAGE analysis of thylakoid membrane protein complexes. Thylakoid samples were loaded on the basis of equivalent chloroph yll . (B). Immunoblot analysis of photosynthetic proteins. CB B, coomassie brilliant blue staining . Thylakoid samples were loaded on the basis of equ al lane. Figure 3.25. High light induc tion of GPT2 expression in photorespiratory mutants and change of the amount of GAP and DHAP in hpr1 . (A). Quantitative RT -PCR analysis of GPT2 transcripts in photorespiratory mutants under GL and after 6 hours of HL. Three biological replicates were used for each genotype. (B). M easurement of glyceraldehyde 3 -phosphate (GAP) and dihydroxyacetone phosphate (DHAP) in hpr1 and WT treated with 6 hours of HL. D/G, DHAP/GAP. Five biological replicates were used for each genotype. Asterisk indicates p-value < 0.01 in Student™s t test. Figure 3.26. An integrated model for the role of photorespiration in modulating photosynthesis. The p hotorespiration pathway initiates with the production of phosphoglycolate by Rubisco in the chloroplast, and ends with the re- feeding of glycerate to the CBB cycle, with the cooperation of chloroplasts, peroxisomes and mitochondria. The photorespiratory metabolic flow is indicated by the red dotted line. As a consequence of blocking of the photorespiration pathway, the level of phosphoglycolate is increased , which inhibits TPI activity. Meanwhile, depletion of the CBB cycle intermediates, such as glycerate, slows down the CBB cycle and caus es accumulation of stromal ATP and NADPH. The accumulated ATP in stroma inhibits ATP synthase conductivity, which leads to increased pmf and subsequently stimulates an increase of NPQ to dissipate excessive energy. Accumulated stromal ATP and NADPH are als o subsequently used to generate Figure 3. 26. (c ont™d) ROS and creates enhanced oxidative stress as well. The increased oxidative stress impacts on various photosynthetic processes, such as photoinhibition, compromised photosystem integrity , damaged photosystem subunit and activation of CEF. This integrated model provides novel mechanistic insights into the connection between photorespiration and photosynthesis. Table 3.1. List of screened peroxisomal mutants ATG ID gene name Annotation mutant name mutant ID background AT4G35090 CAT2 catalase 2 cat2 -1 SALK_076998 Col -0 AT1G68010 HPR1 hydroxypyruvate reductase 1 hpr1 -1 SALK_067724 Col -0 hpr1 -2 SALK_143584 Col -0 AT5G62810 PEX14 peroxin 14 pex14 SALK_007441 Col -0 AT4G33650 AT2G14120 AT3G19720 DRP3A DRP3B DRP 5B dynamin -related protein drp3A -2 drp3B -2 drp5B -2 SALK_147485 SALK_112233 SAIL 71D_11 Col -0 AT4G33650 AT2G14120 DRP3A DRP 3B dynamin -related protein drp3A -2 drp3B -2 SALK_147485 SALK_112233 Col -0 AT3G19720 DRP5B dynamin -related protein drp5B -2 SAIL 71D_11 Col -0 AT1G78590 NADK3 arabidopsis Thaliana NADH Kinase 3 nadk3 -1 SALK_079342 Col -0 AT2G39970 PXN peroxisomal membrane protein of 36kDa pxn -1 GK_046D01 Col -0 pxn -2 GK_830A06 Col -0 AT3G14415 GOX2 glycolate oxidase 2 gox2 -1 SALK_082542 Col -0 gox2 -2 SALK_025574 Col -0 AT5G56290 PEX5 PTS1 peroxisomal protein receptor pex5 CS3949 Col -0 AT5G43280 DCI1 delta(3,5),Delta(2,4) -dienoyl -CoA isomerase 1 dci1 -1 SALK_002674 Col -0 AT3G58840 PMD1 peroxisome mito division factor pmd1 -1 CS854214 Col -0 AT4G35000 APX3 ascorbate Peroxidase 3 apx3 -1 SALK_059352 Col -0 AT2G24580 SOX sarcosine oxidase sox -1 SALK_017108 Col -0 AT3G06810 IBR3 IBA -response 3/ acyl -CoA dehydrogenase ibr3 -1 SALK_033467 Col -0 AT1G11840 GLX1 glyoxylase I homolog glx1 -1 SALK_110070 Col -0 Table 3.1. (cont™d) AT2G42490 CuAO copper amine oxidase cuao-1 SALK_095214 Col -0 cuao-2 SALK_096065 Col -0 AT1G06460 Acd31.2 small heat shock protein acd31.2 -1 SALK_114949 Col -0 AT3G58740 CSY1 citrate synthase 1 csy1 SALK_007026 Col -0 AT1G55320 AAE18 similarity to acyl activating enzymes aae18 -1 SALK_071698 Col -0 aae18 -2 SALK_075217 Col -0 AT2G38180 GLH hydrolase -type esterase glh1 SALK_052637 Col -0 AT3G16910 AAE 7 acyl CoA activating enzyme aae7 -1 SALK_009373 Col -0 aae7 -2 SALK_055243 Col -0 AT5G04870 CPK1 calcium dependent protein kinase 1 cpk1 -1 SALK_007698 Col -0 cpk1 -2 SALK_080155 Col -0 AT5G41210 GSTT1 glutathione transferase gstt1 SALK_075383 Col -0 AT1G48320 sT1 small thioesterase 1 dhnat1 -1 SAIL_1253_B02 Col -0 AT5G16370 AAE5 acyl -activating enzyme 5 aae5 -1 SALK_009731 Col -0 AT5G48880 KAt5 3 keto -acyl -CoA thiolase 5 kat5 -1 SALK_132871 Col -0 kat5 -2 SALK_144464 Col -0 AT2G35690 ACX5 acyl CoA oxidase in JA biosynthesis acx5 SALK_009998 Col -0 AT1G77540 ATF2 Acetyltransferase atf2 -1 FLAG_206E09 Ws -4 AT4G12910 SCPL20 serine Carboxypeptidase -like 20 scpl20 -1 CS818066 Col -3 scpl20 -2 SALK_147839 Col -0 AT3G17420 GPK1 glyoxysomal protein kinase 1 gpk1 -1 SALK_047519 Col -0 gpk1 -2 SALK_047485 Col -0 AT1G11840 GLX glyoxylase I homolog glx1 SALK_059170 Col -0 AT4G39850 PXA1 ATP binding cassette transporter pxa1 SALK_002100 Col -0 Table 3.1. (cont™d) AT3G15950 UP2 unknown protein 2 up2-1 GK_381F11 Col -0 AT3G14420 GOX1 glycolate oxidase 1 gox1 -1 SALK_051930 Col -0 gox1 -2 SALK_133946 Col -0 gox1 -3 SAIL_177_G11 Col -0 AT5G11910 ELT1 esterase/ lipase/ thioesterase family isoform 1 elt1 -1 FLAG_632F03 Ws -4 AT5G44250 UP5 unknown protein up5-1 SALK_107281 Col -0 AT2G42790 CSY3 citrate synthase 3 csy3 -1 SALK_076319 Col -0 AT1G07180 NDA1 NAD(P)H dehydrogenase nda1 SALK_054530 Col -0 AT1G49670 NQR undefined, involved in oxidative stress tolerance nqr-1 SALK_014601 Col -0 nqr-2 SALK_123841 Col -0 AT3G05970 LACS6 long -chain acyl -CoA synthetase 6 lacs6 -1 SALK_069510 Col -0 AT1G28320 DEG15 degredation of periplasmic proteins 15 deg15 -1 SALK_022777 Col -0 AT1G49350 PLCK pfkB -like carbohydrate kinase plck SALK_006361 Col -0 AT1G16730 UP6 unknown protein 6 up6-1 SALK_122395 Col -0 AT4G16760 AT2G35690 ACX1/ACX5 acyl CoA oxidase in JA biosynthesis acx1 acx5 SALK_041464 SALK_009998 Col -0 AT5G12390 FIS1B peroxisome fission fis1b -RNAi RNAi line Col -0 AT2G38400 AGT3 glyoxylate aminotransferase 3 agt3 -1 SALK_100364 Col -0 AT1G01710 ACH2 acyl -CoA thioesterase ach2-1 SALK_134567 Col -0 ach2-2 GK_705E01 Col -0 ach2-3 SALK_126817 Col -0 AT1G20510 OPCL1 4- coumarate -CoA ligase opcl1 -1 SALK_140659 Col -0 AT3G08860 PYD4 pyriminine 4 pyd4 SALK_141570 Col -0 AT2G29590 sT5 small thioesterase 5 st5-1 SALK_089257 Col -0 st5-2 SALK_092512 Col -0 Table 3.1. (cont™d) AT4G28220 NDB1 NAD(P)H dehydrogenase B1 ndb1 SALK_087720 Col -0 AT3G48140 B12D1 senescence -associated protein/ B12D -related protein b12d1 -1 FLAG_548C12 Ws -4 AT1G70580 GGT2 glutamate:glyoxylate aminotransferase2 ggt2 -1 SALK_011617 Col -0 ggt2 -2 SALK_042954 Col -0 AT4G00520 ACH acyl -CoA thioesterase ach-1 SALK_045174 Col -0 ach-2 SALK_150023 Col -0 AT5G20070 NUDX19 nudix hydrolase homolog 19 nudx19 -1 SALK_114456 Col -0 nudx19 -2 SALK_115339 Col -0 AT5G27600 LACS7 long -chain Acyl -CoA synthetase 7 lacs7 -1 SALK_146444 Col -0 AT3G51840 ACX4 acyl -CoA oxidase4 acx4 -1 SALK_000879 Col -0 acx4 -2 SALK_065013 Col -0 AT1G06290 ACX3 acyl -CoA oxidase3 acx3 -1 SALK_128947 Col -0 acx3 -2 SALK_044956 Col -0 AT1G54340 ICDH/ IDHP1 NADP -dependent isocitrate deshydrogenase icdh -1 SALK_034151 Col -0 AT1G20480 4CL3 4- coumarate -CoA ligase 4cl3 -1 SALK_027694 Col -0 4cl3 -2 SALK_010491 Col -0 AT4G09320 NDPK1 nucleoside diphosphate kinase type 1 ndpk1 -1 SALK_089749 Col -0 AT2G41790 PM16 peptidase family M16 pm16 -1 SALK_056340 Col -0 pm16 -2 SALK_019128 Col -0 AT3G14150 HAOX2 hydroxy -acid oxidase isoform 2 haox2 -1 SALK_102409 Col -0 AT2G42450 Lcp3 lipase class 3 family protein lcp3 -1 SALK_035053 Col -0 AT2G30660 CHYH2 ATP - dependent caseinolytic protease chyh2 -1 SALK_082635 Col -0 chyh2 -2 SALK_143061 Col -0 AT1G50510 IndA indigoidine synthase A inda -1 GK_681B01 Col -0 Table 3.1. (cont™d) AT3G56460 ZnDH zinc -binding dehydrogenase zndh -1 SALK_056640 Col -0 zndh -2 SALK_082243 Col -0 AT1G04290 sT4 acyl -CoA thioesterase st4-1 SALK_087372 Col -0 st4-2 SALK_061841 Col -0 AT5G42890 SCP2 sterol carrier protein 2 scp2 CS829325 Col -0 AT5G58220 TLP transthyretin -like protein tlp -1 SALK_137289 Col -0 AT5G18100 CSD3 copper/zinc superoxide dismutase 3 csd3 SALK_126981 Col -0 AT5G11520 ASP3 aspartate aminotransferase3 asp3 -1 SALK_008526 Col -0 asp3 -2 SALK_063210 Col -0 asp3 -3 SALK_083372 Col -0 AT4G16760 ACX1 acyl CoA oxidase in JA biosynthesis acx1 SALK_041464 Col -0 AT4G29010 AIM1 abnormal inflorescence meristem 1 aim1 SALK_038805 Col -0 AT1G06310 ACX6 acyl -CoA oxidase6 acx6 SALK_023093 Col -0 AT3G24170 GR1 glutathione reductase 1 gr1 -1 SALK_060425 Col -0 gr1 -2 SALK_105794 Col -0 AT3G57090 FIS1A peroxisome fission fis1a SALK_086794 Col -0 AT5G47040 Lon2 long Protease 2 lon2 -2 SALK_043857 Col -0 AT4G05160 4CLP1 4- coumarate:CoA ligase 1 4clp1 -1 SALK_050214 Col -0 AT3G55640 CDC Ca2+ -dependent carrier cadc-1 CS832927 Col -0 cadc-2 GK_237H07 Col -0 AT3G51660 MIF MIF superfamily protein mif SALK_037373 Col -0 AT2G22780 PMDH1 peroxisomal NAD -malate dehydrogenase 1 pmdh1 SALK_047994 Col -0 Table 3.1. (cont™d) AT5G65400 UP7 Unknown protein 7 up7-1 SALK_062218 Col -0 up7-2 SALK_067081 Col -0 AT1G04710 KAT1 3 keto -acyl -CoA thiolase 1 kat1 -1 SALK_013834 Col -0 AT5G37670 Hsp15.7 heat shock protein similar to 17.7KDa class I hsp15.7 -1 SALK_038951 Col -0 hsp15.7 -2 SALK_107711 Col -0 AT3G27820 MDAR4 peroxisomal monodehydroascorbate reductase 4 mdar4 SALK_015596 Col -0 AT5G65940 CHY1 beta -hydroxyisobutyryl -CoA hydrolase 1 chy1 -1 SALK_025417 Col -0 chy1 -2 SALK_102725 Col -0 AT1G23310 GGT1 glutamate:glyoxylate aminotransferase1 ggt1 SALK_064982 Col -0 AT3G19570 SCO3 snowy cotyledon sco3 SALK_021491 Col -0 AT3G06860 MFP2 multifunction protein 2 mfp2 SALK_098016 Col -0 AT2G43020 PAO2 polyamine oxidase 2 pao2 -1 SALK_046281 Col -0 pao2 -2 SALK_062035 Col -0 AT1G65840 PAO4 Polyamine oxidase 4 pao4 -1 SALK_062544 Col -0 pao4 -2 SALK_118752 Col -0 AT5G47720 ACAT1.3 acetoacetyl -CoA thiolase 1.3 acat1.3 -1 SALK_008505 Col -0 AT3G48170 BADH aldehyde deshydrogenase badh-1 CS822971 Col -0 AT1G30520 AAE14 acyl -activating enzyme 14 aae14 SALK_038308 Col -0 AT4G04320 MCD malonyl -CoA decarboxylase mcd -1 SALK_069574 Col -0 mcd -2 GK_859E12 Col -0 AT4G16210 ECHIa enoyl -CoA hydratase/isomerase A echia -1 SALK_004620 Col -0 echia -2 SALK_024138 Col -0 AT1G20560 AAE1 acyl -activating enzyme isoform 1 aae1 -1 SALK_041152 Col -0 Table 3.1. (cont™d) AT2G14120 DRP3B dynamin -related protein drp3b -1 SALK_045316 Col -0 drp3b -2 SALK_112233 Col -0 AT4G02340 EH3 epoxide hydrolase isoform 3 eh3 -1 SALK_106529 Col -0 eh3 -2 SALK_149885 Col -0 AT3G05290 PNC1 peroxisomal adenine nucleotide carrier 1 pnc1-1 SALK_152091 Col -0 pnc1-2 SALK_044502 Col -0 AT4G33650 DRP3A dynamin -related protein drp3a -2 SALK_147485 Col -0 AT1G19570 DHAR1 dehydroascorbate reductase dhar-1 SALK_005382 Col -0 dhar-2 SALK_029966 Col -0 AT5G03860 MLS malate synthase mls -1 SALK_060987 Col -0 mls -2 SALK_109976 Col -0 Table 3.2 . Primers used in this study Hu Lab ID Primer name Sequence Direction Usage Gene name Gene ID HU6151 Anth15 -RTF ATACCTTTTACAATTTGTTTAT fw qPCR PAP1 AT1G56650 HU6152 Anth15 -RTR CTAATCAAATTTCACAGTC rv qPCR PAP1 AT1G56650 HU6153 Anth16 -RTF TGGGAAGCCACAATAACCCC fw qPCR PAP2 AT1G66390 HU6154 Anth16 -RTR CTAATCAAGTTCAACAGTCTC rv qPCR PAP2 AT1G66390 HU6125 Anth2 -RTF ATGGATCAAATCGAAGCAATGTTG fw qPCR PAL2 AT3G53260 HU6126 Anth2 -RTR TCGTGAACCTTTTGAGCTAATT rv qPCR PAL2 AT3G53260 HU6129 Anth4 -RTF ATGGTGATGGCTGGTGCTTC fw qPCR CHS AT5G13930 HU6130 Anth4 -RTR TTAGAGAGGAACGCTGTGCA rv qPCR CHS AT5G13930 HU6141 Anth10 -RTF ATGGTTAGTCAGAAAGAGACCG fw qPCR DFR AT5G42800 HU6142 Anth10 -RTR CTAGGCACACATCTGTTGTGC rv qPCR DFR AT5G42800 HU6149 Anth14 -RTF AACTCCGTTGAGGAAGATGTGAT fw qPCR UGT89C1 AT1G06000 HU6150 Anth14 -RTR TTACAAACACATCTCTGCAACG rv qPCR UGT89C1 AT1G06000 HU6166 SHSP-RTF GCGATCGTGAACGCACGTGTGGA fw qPCR SHSP AT2G 29500 HU6167 SHSP-RTR TCCATCTTCACATTCTCCGGCAACC rv qPCR SHSP AT2G 29500 HU6168 WRKY30 -RTF CGCTGGACGATGGATTCAGTTGGAGA fw qPCR WRKY30 AT5G 24110 HU6169 WRKY30 -RTR TCGGTTCGAGGTTTTGTATCGGCATTG rv qPCR WRKY30 AT5G 24110 REFERENCES REFERENCES Albrecht, V., Simkova, K., Carrie, C., Delannoy, E., Giraud, E., Whelan, J., Small, I.D., Apel, K., Badger, M.R., and Pogson, B.J. 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Zhang, L., Paakkarinen, V., Wijk, K.J.v., and Aro, E.-M. (1999). Co-translational assembly of the D1 protein into photosystem II. J Biol Chem. Zhang, X., and Hu, J. (2009). Two small protein families, DYNAMIN- RELATED PROTEIN3 and FISSION1, are required for peroxisome fission in Arabidopsis. The Plant journal : for cell and molecular biology 57, 146-159. Zhang, X., and Hu, J. (2010). The Arabidopsis chloroplast division protein DYNAMIN- RELATED PROTEIN5B also mediates peroxisome division. The Plant cell 22, 431-442. CHAPTER 4 CONCLUSION S AND FUTURE PERSPECTIVE S Peroxisomes house a wide array of metabolic reactions essential for plant growth and development . These organelles also dynamically interact with other organelles to support cellular functions. However, o ur knowledge regarding the role of peroxisomal proteins in various biological processes, including plant stress response and photosynthesis , is still incomplete. The objectives of my dissertation studies were to determine the role of peroxisomes in modul ating environmental stress response and photosynthesis at a systems level, using in silico analysis , mutant screens followed by in-depth physiological and biochemical characterizations . Knowledge gained from my dissertation studies provides new insights into the connection between peroxisomal function and drought stress response and between photorespiration and photosynthesis, and opens new potential directions for future research on environmental stress response, photosynthesis, photorespiration and interorganellar communication. 4.1. Co mprehensive analysis of transcriptional regulation on genes encoding peroxisomal proteins across developmental stages and und er various environmental str esses In Chapter 2, I presented the studies on transcriptional regulation of genes encoding peroxisomal proteins across developmental stages and under various environmental stresses . We found that many genes that function in the same pathway, such as glyoxylate cycle and photorespiration, tend to be co -expressed. For example, genes that encode glyoxylate cycle enzymes isocitrate lyase (ICL), malate synthase (MLS), and citrate synthase 1 (CSY1) were co-up- regulated during seed maturation , presumably in preparation of their role in seed germination. Genes encoding the peroxisomal proliferation factors PEX11b, PEX11c and PEX11d were co-up- regulated under hypoxia conditions , consistent with a previous finding that hypoxia stress stimulate s peroxisomal exten sion over the endoplasmic reticulum ( Sinclair et al., 2009 ). Individual genes that showed dramatic up -regulations under certain conditions, such as >150- fold transcript increase of a heat shock protein gene AtHsp15.7 under high light (HL), may shed light on the possible roles of these proteins in pertinent stress responses. Besides drought stress, other environmental stresses, such as high light, bacterial pathogen Pseudomonas syringae pv. Tomato DC3000 and bac terial e longation factor elf18, also significantly regulated the transcript levels of a large number of genes encoding peroxisomal proteins. This peroxisome -centered gene expression analysis provides a comprehensive view of transcript level changes of Arabidopsis peroxisomal genes, and is a starting point for selecting potential key players in stress response for further investigations. Future directions: Based on our peroxisome -centered gene expression analysis, we can narrow down our focus to promising candidate genes. Uncharacterized genes that cluster with genes functioning in well known pathways are likely to play a role in that pathway. Mutant analysis of the heat shock protein gene AtHsp15.7 under HL treatment is a worthy experiment to pursue, as this gene is dramatically up -regulated by HL. In addition to drought response screens, mutant screens can also be performed using other stress assays, such as pathogen infections and cold treatment, under which a signific ant number of genes show altered transcript level s. We also need to keep in mind that many genes play a significant role in stress response but are not transcriptionally regulated under stress conditions. 4.2. LON2 protease and the photorespiratory enzyme hydroxypyruvate reductase 1 (HPR1) play important roles in drought response In Chapter 2, I discovered that mutants of LON2 protease and hydroxypyruvate dehydrogenase HPR1 exhibited enhanced drought susceptibility, with faster chlorophyll degradation and water loss, and inhibited photosynthetic efficiency and anthocyanin induction under drought conditions. Unlike LON2 , gene expression of HPR1 was not highly induced by drought or the drought- related phytohormone abscisic acid. It is known that photorespiration is activated by environmental stresses, such as drought and high light (Foyer et al., 2009 ). The drought sus ceptibility exhibited by the two null mutants of HPR 1 may be mainly attributed to the block of photorespiration, which generates toxic levels of phosphoglycolate and strong accumulation of H 2O2Future directions: Whether LON2 affects drought response via photorespiration needs further investigation. Since high CO that impair the photosynthetic apparatus, membrane integrity, and other cellular components. Since LON2 was up- regulated by ABA, this protease may play a role in drought response through ABA signaling. I t is also possible that the insufficient number of peroxisomes in lon2 cannot carry out robust photorespiration, which is critical for plant survival under drought conditions. 2 can suppress photorespiration, carrying out drought tolerance experiments under high CO 2 condition may help to answer this question. If the drought phenotype of lon2 is rescued, we may conclude that the role of LON2 in drought is dependent on photorespiration. If not, it is more likely that LON2 itself has a direct role in drought tolerance. We may measure the abundance and morphology of peroxisomes during drought in both WT and lon2 , which could possibly reveal the dynamics of peroxisome abundance during drought stress, and identify connections between organelle behavior and stress response. Another possibility is that the substrates for LON2 protease have a role in conferring drought tolerance, thus the identification of LON2 substrate through genetic, biochemical and/or cell biological approaches may shed light on the mechanism underlying the drought stress phenotype of lon2 . 4.3. PXN is an additional factor in photorespiration In Chapter 3, I presented that both pxn mutant alleles showed photosynthetic phenotypes under fluctuating light conditions, which can be rescued by providing high CO2. One explanation for PXN™s role is that NAD +Future directions: The photosynthetic phenotype exhibited by the pxn mutants, and previously shown by the pmdh1 pmdh 2 double mutants ( delivered into peroxisome by PXN can be used as a substrate for p eroxisomal malate dehydrogenase s (PMDHs) to generate NADH that is needed for the reduction reaction catalyzed by the photorespiratory protein HPR1. Cousins et al., 2008 ), was significant but relatively subtle, indicating that there are additional sources of NAD + and NADH in peroxisomes. The role of PXN in photorespiration could be further studied by analyzing higher order mutants. Since PXN and PMDH function in NADH generation in subsequent orders, creating triple mutant pxn pmdh1 pmdh 2, followed by photorespiratory and photosynthetic characterization could facilitate our understanding of the additive effect by PXN and PMDH. 4.4. gox1 exhibited drastic photosynthetic phenotype under dynamic light conditions despite its normal growth in ambient air In Chapter 3, I showed that gox1 displayed significant photosynthetic phenotypes, including lower and higher NPQ under high light and fluctuating light conditions. The fact that GOX1 and GOX2 are highly similar proteins and gox1 null mutant does grow as well as WT led to an as sumption that GOX1 and GOX2 are completely functionally redundant. However, we were able to reveal the phenotype of gox1 by DEPI. This result testifies the high sensitivity and robustness of DEPI and indicates that GOX2 cannot fully substitute GOX1 under conditions in which photorespiration is strongly induced. Future directions: GOX1 and GOX2 are closely linked to each other on Chromosome 3 in Arabidopsis, thus it is difficult to generate double mutants via crosses between the single mutants. To study the role of GOX in photorespiration through genetic approaches, we may generate CRISPR -CAS mediated (Feng et al., 2014 ; Hsu et al., 2013 ; Li et al., 2013 ) knockout lines for both GOX1 and GOX2, which will be an important genetic material for characterizing GOX functions. 4.5. Metabolites and molecules resulting from blocking photorespiration have a large impact on photosynthetic complexes and processes In Chapter 3, I demonstrated that several photorespiratory mutants exhibited strong defects in various aspects of photosynthesis. I showed that the increased NPQs occurred in the photorespiratory mutants were attributed to elevated proton motive force (pmf ) resulted from inhibited proton efflux across the thylakoid membrane . Meanwhile, I showed that the increase d NPQ s in photorespiratory mutants were completely dependent on the lumenal pH sensor protein PsbS and partially dependent on zeaxanthin. In addition, I found that cyclic electron flow (CEF) was activated in photorespiratory mutants to compensate for the ATP -to-NADPH ratio deficiency resulted from the decreased ATP synthase conductivity in photorespiratory mutants under high light (HL) . Furthermore, subjecting t he photorespirat ory mutants to long term HL stresses led to strong photoinhibtion, enhanced reactive oxygen species (ROS), deficiency in anthocyanin accumulation, compromised photosynthetic complex integrity and reduced abundance of key photosystem subunits. Last but not least, w e provided biochemical evidence that the activity of the CBB cycle enzyme triose phosphate isomerase (TPI) was inhibited in the photorespiratory mutants in vivo under HL. Expression of the G6P transport er gene GPT2 was concomitantly increased , suggesting enhanced re-import of glucose 6 -phosphate (G6P), which would activate the oxidative branch of the pentose phosphate pathway that subsequently creates a higher demand of ATP and enhanced oxidative stress in photoresp iratory mutants . Future directions: The diverse photosynthetic phenotypes exhibited on photorespiratory mutants may lead us to a few future directions to pursue. First, the quantitatively and kinetically different phenotypes exhibited on mutants of genes i n photorespiration, such as hpr1 , plgg1 and cat2 , pro mpted us to speculate the relative importance and rate -limiting effect of each step in photorespiration. Photorespiratory metabolite flow data might be integrated with our genetics data to generate a quantitative model of photorespiration. Decreased ATP s ynthase conductivity in hpr1 and plgg1 is the cause for higher pmf and NPQ, but the molecular mechanisms underlying the inhibitory effect on ATP synthase are still elusive. I speculate that the depletion of glycerate in hpr1 and plgg1 results in a slow -dow n of the CBB cycle, which increases the amount of ATP in stroma. Elevated levels of stromal ATP can possibly have a negative feedback effect on ATP conductivity. hpr1 and plgg1 provide suitable systems to study the regulation of ATP conductivity in vivo . Additional enzymes and regulators involved in photorespiration need to be further discovered. Conducting a suppressor screen on hpr1 could facilitate the discovery of these proteins. The obvious HL phenotype in hpr1 , including small and pale green rosette compared to larger and purple rosette in WT, can help us to design an easy assay to look for hpr1 suppressors under HL. Possible suppressors may include mutants of genes that negatively regulate photorespiration, positively regulate light absorption in pho tosystems, or positively regulate the production of H 2O2 . In summary, results from my thesis work make a significant step towards deepening our understanding of the role of peroxisomes in modulating environmental stress response and photosynthesis at the molecular level. These findings will not only contribute to the knowledge of organelle biology and plant biology, but also provide valuable information to biotechnological endeavors to improve crop plants for higher yields and better quality. REFE RENCES REFERENCES Cousins, A.B., Pracharoenwattana, I., Zhou, W., Smith, S.M., and Badger, M.R. (2008). Peroxisomal Malate Dehydrogenase Is Not Essential for Photorespiration in Arabidopsis But Its Absence Causes an Increase in the Stoichiometry of Photorespiratory CO2 Release. Plant Physiology Vol. 148 , 786-795. 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