Science, Faculty of
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UBCV
Munz, Jacob Alexander
Doctor of Philosophy - PhD
University of British Columbia
Nitrogen (N) is a fundamental macronutrient that constitutes nucleic/amino acids. Therefore, organisms require signaling mechanisms to sense external and internal N and regulate essential processes like cell growth, development, and energy metabolism. The responses to changes in cellular N status in bacteria/fungi are mediated by monitoring metabolites of the N assimilation pathway ending with glutamine synthetase (GS) and glutamate synthase (GOGAT) enzymes, forming the GS/GOGAT cycle. In photosynthetic eukaryotes, N assimilation relies on the GS/GOGAT cycle, however, whether similar signaling mechanisms are operant remains unknown. Breakthroughs in the N status signaling of bacteria/fungi were made by utilizing N sources that activated N starvation responses during growth, defined as 'derepressive'. While it is known that NH₄⁺ and NO₃- repress N starvation responses in photosynthetic eukaryotes, no derepressive N sources have been established. The unicellular green alga, Chlamydomonas reinhardtii, can survive on a wider array of N sources than land plants, of which arginine-feeding was known to derepress gametogenesis, a N starvation-specific response. This work investigated the use of arginine as a derepressive N source in photosynthetic eukaryotes and documented that N starvation responses were activated (Chapter 3 and 4). Using this derepressive condition, screens for defective N starvation responses collected mutants displaying nitrogen insensitivity (nsi) or constitutive nitrogen starvation responses (cns). Five nsi mutants disrupted the same region, NSI1, encoding a divergent glutamine synthetase (GLN4) (Chapter 5). NSI1 homologs were found in chlorophytes, and sequence features common to this family suggested it is unlikely to catalyze the reduction of NH₄⁺ but may detect N status via its potential binding to glutamate (Chapter 5). The cns mutants suggested a negative regulation of N starvation responses, whose further study may elucidate how NH₄⁺ rapidly represses N starvation responses (Chapter 6). Collectively, the work done in this thesis has led to the discovery of a hypothetical signaling network that responds to cellular N status in photosynthetic eukaryotes involving a detection mechanism of N flux through the GS/GOGAT cycle, comparable to the N status signaling counterparts in bacteria/fungi. Whether an analogous system for N status signaling exists in land plants remains to be investigated.
DISCOVERY OF NITROGEN STARVATION DETECTING AND SIGNALING MUTANTS IN CHLAMYDOMONAS REINHARDTII by Jacob Alexander Munz B.Sc., Colorado State University, 2011 M.Sc., Illinois State University, 2014 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (BOTANY) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) April 2020 © Jacob Alexander Munz, 2020 ii The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, the dissertation entitled: Discovery of nitrogen starvation detecting and signaling mutants in Chlamydomonas reinhardtii submitted by Jacob Munz in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Botany Examining Committee: Jae-Hyeok Lee, Professor, Botany, UBC Supervisor George Haughn, Professor, Botany, UBC Supervisory Committee Member Robert Guy, Professor, Forestry, UBC University Examiner Yuelin Zhang, Professor, Botany, UBC University Examiner iii Abstract Nitrogen (N) is a fundamental macronutrient that constitutes nucleic/amino acids. Therefore, organisms require signaling mechanisms to sense external and internal N and regulate essential processes like cell growth, development, and energy metabolism. The responses to changes in cellular N status in bacteria/fungi are mediated by monitoring metabolites of the N assimilation pathway ending with glutamine synthetase (GS) and glutamate synthase (GOGAT) enzymes, forming the GS/GOGAT cycle. In photosynthetic eukaryotes, N assimilation relies on the GS/GOGAT cycle, however, whether similar signaling mechanisms are operant remains unknown. Breakthroughs in the N status signaling of bacteria/fungi were made by utilizing N sources that activated N starvation responses during growth, defined as 'derepressive'. While it is known that NH4+ and NO3- repress N starvation responses in photosynthetic eukaryotes, no derepressive N sources have been established. The unicellular green alga, Chlamydomonas reinhardtii, can survive on a wider array of N sources than land plants, of which arginine-feeding was known to derepress gametogenesis, a N starvation-specific response. This work investigated the use of arginine as a derepressive N source in photosynthetic eukaryotes and documented that N starvation responses were activated (Chapter 3 and 4). Using this derepressive condition, screens for defective N starvation responses collected mutants displaying nitrogen insensitivity (nsi) or constitutive nitrogen starvation responses (cns). Five nsi mutants disrupted the same region, NSI1, encoding a divergent glutamine synthetase (GLN4) (Chapter 5). NSI1 homologs were found in chlorophytes, and sequence features common to this family suggested it is unlikely to catalyze the reduction of NH4+ but may detect N status via its potential binding to glutamate (Chapter 5). The cns mutants suggested a negative regulation of N starvation responses, whose further study may elucidate how NH4+ rapidly represses N starvation responses (Chapter 6). Collectively, the work done in this thesis has led to the discovery of a hypothetical signaling network that responds to cellular N status in photosynthetic eukaryotes involving a detection mechanism of N flux through the GS/GOGAT cycle, comparable to the N status signaling counterparts in bacteria/fungi. Whether an analogous system for N status signaling exists in land plants remains to be investigated. iv Lay Summary Nitrogen (N) is a fundamental macronutrient for plants that is essential for nucleotides and amino acids and therefore growth and development. Environmental N availability varies greatly, and high crop yields in agricultural systems rely on N fertilizer application, the large part of which cannot be absorbed by plants. Engineering plants with improved N utilization could be possible if the cellular detection of N status and the subsequent signaling pathways were known. Plant organs have differing N demands and availability which imposes a challenge towards understanding cellular N status regulation. This technical problem can be overcome by using a unicellular photosynthetic eukaryote that is closely related to plants. My research investigates the control of N status responses in a unicellular photosynthetic eukaryote, the genes and enzymes that may be used to detect and signal N status, and what metabolites may be used as proxies for N abundance or limitation. v Preface A version of Chapter 1 will be submitted as a mini-review article written by Jacob Munz and reviewed and revised by Jae-Hyeok Lee. A version of Chapter 3 has been published as: Munz, J., Xiong, Y., Kim, J.Y.H., Sung, Y.J., Seo, S., Hong, R.H., Kariyawasam, T., Shelley, N., Lee, J., Sim, S.J., Jin, E., Lee, J. (2020) Arginine-fed cultures generate triacylglycerol by triggering nitrogen starvation responses during robust growth in Chlamydomonas. Algal research 46: 101782. Micrographs of starch sheaths were carried out by Thamali Kariyawasam. Measurements of chlorophyll fluorescence, chlorophyll quantity, and oxygen evolution were performed by Yuan Xiong. The photobioreactor experiments were carried out by Nolan Shelley. The real time quantitative PCR measurements were carried out by Jacob Munz, Sunjoo Joo, and Ran Ha Hong. Lipid profiling experiments were carried out by Young Hwan Kim and Young Joon Sung with the supervision of Sang Jun Sim. Phaeodactylum tricornutum experiments were carried out by Seungbeom Seo supervised by EonSeon Jin. Measurements of gametogenesis and lipid micrographs in C. reinhardtii were carried out by Jacob Munz. A version of Chapter 4 will be submitted as a research article for peer-review written by Jacob Munz and reviewed and revised by Jae-Hyeok Lee. Jacob Munz and Sunjoo Joo carried out the experiments. The analysis of RNA-seq data was carried out by Jae-Hyeok Lee and Jacob Munz. The preparation of RNA for the analysis was carried out by Sunjoo Joo. The preparation of the cell samples was carried out by Jacob Munz A version of Chapter 5 will be submitted as a research article for peer-review written by Jacob Munz and reviewed and revised by Jae-Hyeok Lee. Jacob Munz, Moyan Jia, Jenny Lee, and Sunjoo Joo carried out the experiments. vi The screen conditions and protocol were designed by Jacob Munz. The mutant library screen was carried out by Jacob Munz. Mapping of the mutants was carried out by Jenny Lee and Sunjoo Joo. The real time quantitative PCR measurements were carried out by Jacob Munz, Moyan Jia, and Sunjoo Joo. The photosynthetic measurements were carried out by Jacob Munz. The micrographs of lipid droplets were carried out by Jacob Munz. The measurement of cell viability was carried out by Jacob Munz. A version of Chapter 6 will be submitted as a research article for peer-review by written by Moyan Jia and reviewed and revised by Jae-Hyeok Lee. Jacob Munz, Moyan Jia, Yuan Xiong, Sunjoo Joo, and Jenny Lee carried out the experiments. The screen conditions and protocol were designed by Jacob Munz. The mutant library screen was carried out by Jacob Munz and Yuan Xiong. Mapping of the mutants was carried out by Jenny Lee and Sunjoo Joo. The real time quantitative PCR measurements were carried out by Jacob Munz, Moyan Jia, and Sunjoo Joo. The photosynthetic measurements were carried out by Jacob Munz. vii Table of Contents Abstract ................................................................................................................................... iii Lay Summary ........................................................................................................................... iv Preface ...................................................................................................................................... v Table of Contents ................................................................................................................... vii List of Tables ........................................................................................................................... xi List of Figures ....................................................................................................................... xiii List of Abbreviations ............................................................................................................ xvi Acknowledgements ............................................................................................................ xviii Chapter 1: Introduction ............................................................................................................ 1 1.1. Nitrogen assimilation in photosynthetic eukaryotes ........................................................ 1 1.2. Signaling of internal N status vs external N availability ................................................... 1 1.3. External N availability signaling in photosynthetic eukaryotes......................................... 3 1.3.1. NO3--specific transcriptional regulation ................................................................. 3 1.3.2. NH4+-repression of alternative N assimilation ....................................................... 6 1.3.3. Nitric oxide-mediated repression of NO3- assimilation ........................................... 7 1.4. Putative N status signaling pathways in photosynthetic eukaryotes ................................ 8 1.4.1. PII proteins ............................................................................................................ 9 1.4.2. TOR complex ..................................................................................................... 13 1.4.3. The general amino acid control (GAAC) pathway ............................................... 16 1.4.4. Glutamate receptor-like proteins ......................................................................... 17 1.4.5. Glutamine synthetase-dependent regulation ...................................................... 18 1.5. Chlamydomonas arginine-fed cultures as a putative N starvation model system .......... 19 1.6. Research questions, objectives, and biological significance ......................................... 21 Chapter 2: Materials and methods ......................................................................................... 22 2.1. Strains and culture conditions....................................................................................... 22 2.2. Selection of N limitation marker genes ......................................................................... 22 2.3. Photosynthetic parameter measurements of cell stress and cytochrome b6f degradation .................................................................................................................. 22 2.4. Reverse transcription quantitative PCR (RT-qPCR) ..................................................... 24 2.5. Measurement of gametogenesis and gamete dedifferentiation ..................................... 24 2.6. Random insertional mutagenesis ................................................................................. 25 2.7. Screening for mutants with aberrant regulation of N starvation marker genes .............. 26 viii 2.8. Phylogenetic analysis ................................................................................................... 26 2.9. Construction of the GLN4 protein model ....................................................................... 27 2.10. RNA-seq sample preparation and analysis................................................................ 27 2.11. Selection of light sensitive mutants ........................................................................... 28 Chapter 3: Arginine-fed cultures derepress nitrogen starvation responses during robust growth in C. reinhardtii ........................................................................................................... 32 3.1. Introduction .................................................................................................................. 32 3.2. Results and Discussion ................................................................................................ 33 3.2.1. Arginine-fed mixotrophic cultures undergo gametogenesis and show reduced chlorophyll content during normal growth. ............................................................. 33 3.2.2. N starvation-induced genes are upregulated in arginine-fed mixotrophic cultures.................................................................................................................. 34 3.2.3. Mixotrophic arginine-grown cells increase the flux of organic C towards storage .................................................................................................................. 41 3.2.4. N starvation responses are induced in arginine-fed phototrophic cultures .......... 44 3.2.5. Arginine-induced lipid accumulation occurs in the diatom Phaeodactylum.......... 45 3.3. Conclusions.................................................................................................................. 47 Chapter 4: The transcriptome of arginine-fed cultures showed derepression of N starvation responses and identified putative routes of arginine assimilation ................... 48 4.1. Introduction ................................................................................................................. 48 4.2. Results and Discussion ............................................................................................... 49 4.2.1. Differentially expressed genes strongly overlap between arginine-fed and nitrogen starved cultures ....................................................................................... 49 4.2.2. Arginine-fed cultures upregulate N assimilation pathways in a manner consistent with N starvation .................................................................................................... 51 4.2.3. Amino acid biosynthetic pathways are significantly downregulated except for arginine biosynthesis ............................................................................................. 56 4.2.4. Cells grown with arginine significantly downregulate nuclear encoded photosynthetic apparatus genes ............................................................................ 63 4.2.5. The mitochondrial electron transport chain complex II is downregulated and alternative oxidation via AOX1 is upregulated in arginine-fed cultures ................... 71 4.2.6. C assimilation is downregulated in arginine-fed cultures as in long-term N starvation suggesting that arginine may serve as a C source ................................ 76 ix 4.2.7. Upregulation of specific amino acid transporters, polyamine degradation and arginine deiminase in arginine infer catabolic route ............................................... 84 4.2.8. Identification of putative regulators or arginine metabolism and N starvation responses .............................................................................................................. 95 4.3. Conclusions................................................................................................................ 100 Chapter 5: GLN4 encodes a glutamine synthetase required for transcriptional regulation of N starvation responses in C. reinhardtii ......................................................................... 103 5.1. Introduction ................................................................................................................ 103 5.2. Results and Discussion .............................................................................................. 104 5.2.1. NIT1 promoter-reporter activity is N starvation-dependent in a nit2-null background ......................................................................................................... 104 5.2.2. N starvation marker genes are not upregulated in ns mutants resistant to methylammonium ................................................................................................ 106 5.2.3. Complementation of gln4 restored upregulation of N starvation markers .......... 109 5.2.4. NSI1/GLN4 belongs to a chlorophyte-specific family including non-canonical glutamine synthetases ......................................................................................... 112 5.2.5. Disruption of GLN4 prevents N starvation-induced gene regulation and gametogenesis ................................................................................................... 117 5.2.6. GLN4 is not involved in NIT2-dependent NO3--responsive gene regulation ..... 122 5.2.7. Transcription analysis reveals that GLN4 regulates a majority of N starvation-induced genes ..................................................................................................... 124 5.3. Conclusions................................................................................................................ 128 Chapter 6: Identification of novel NH4+-repression candidate genes and genes encoding proteins that link photoprotection to N assimilation in C. reinhardtii ............................... 131 6.1. Introduction ................................................................................................................ 131 6.2. Results and Discussion .............................................................................................. 132 6.2.1. Random insertional mutagenesis disrupted NH4+-repression regulation of the NIT1 promoter driven reporter ............................................................................. 132 6.2.2. Mutants disrupted in NIT1 promoter driven reporter activity display defective regulation of N starvation-induced gene regulation .............................................. 132 6.2.3. Mutants disrupted in NIT1 promoter driven reporter activity display increased levels of cell stress that increases with light intensity ........................................... 138 6.3. Discussion .................................................................................................................. 142 x Chapter 7: Conclusions ........................................................................................................ 144 7.1. Major findings of this work .......................................................................................... 144 7.1.1. Arginine is a derepressive nitrogen source ....................................................... 144 7.1.2. GLN4 is central to N status signal transduction and N starvation responses .... 145 7.1.3. NIT1 regulation is extremely dynamic ............................................................... 146 7.2. Future work ................................................................................................................ 146 7.2.1. How is arginine assimilated and is there an arginine-specific transcription factor ................................................................................................................... 146 7.2.2. How does GLN4 detect N status and trigger the appropriate signal responses 147 7.2.3. Are NH4+ - repression and N status mutually exclusive signals ......................... 147 References ............................................................................................................................ 149 xi List of Tables Table 2.1 – Details of selected N starvation marker genes analyzed in this study ..................... 23 Table 3.1 – C. reinhardtii cells acclimated to arginine media exhibit N-starvation-induced responses without stress symptoms. ......................................................................................... 35 Table 3.2 – C. reinhardtii arginine-fed cultures grow slower than NH4+-fed cultures but show higher final cell densities ........................................................................................................... 37 Table 3.3 – FA profiles suggest de novo synthesis as a primary route for the increased FAs in arginine-fed cultures.................................................................................................................. 42 Table 4.1 – N assimilation genes were upregulated in arginine-fed cultures as in N starvation 53 Table 4.2 – Most amino acid biosynthesis genes were downregulated in arginine-fed cultures as in N starvation .......................................................................................................................... 58 Table 4.3 – Photosynthetic electron transport genes were downregulated in arginine-fed cultures ..................................................................................................................................... 64 Table 4.4 – Genes encoding proteins for PSII and cytochrome b6f assembly were downregulated in ARG but upregulated in NF48 transcriptomes ............................................... 67 Table 4.5 – Genes encoding for light harvesting complex-like proteins were upregulated in all transcriptomes .......................................................................................................................... 69 Table 4.6 – Mitochondrial electron transport chain complex II was downregulated in arginine-fed cultures whereas alternative oxidase 1 was upregulated ........................................................... 72 Table 4.7 – Genes encoding proteins involved in the Calvin cycle, glycolysis, and TCA cycle were downregulated in arginine-fed cultures as in long-term N starvation ................................. 77 Table 4.8 – Genes encoding the putative arginine metabolism enzymes were upregulated in arginine-fed cultures.................................................................................................................. 87 Table 4.9 – Putative transcription factors significantly upregulated in arginine-fed cultures may control arginine assimilation or N starvation responses ............................................................. 97 Table 5.1 – Mutants resistant to methylammonium in arginine-fed cultured ns mutants were putatively disrupted in the regulation of N starvation marker gene, AMT4 ............................... 107 Table 5.2 - Progeny of complement 2 backcrossed to wild-type showed 1:1 segregation of methylammonium resistance ................................................................................................... 113 Table 5.3 – Decreases in chlorophyll content of arginine-fed gln4;nit2 and gln4;GLN4C;nit2 strains was comparable to wild-type ........................................................................................ 121 Table 5.4 – Arginine-fed growth of the double mutant gln4;nit2 was impaired relative to wild-type.................................................................................................................................. 126 xii Table 5.5 – Arginine-fed growth of the gln4 single mutant was impaired relative to gln4;GLN4C ............................................................................................................................................... 126 Table 6.1 – Mutants sensitive to chlorate when cultured with NH4+ were putatively disrupted in NH4+ repression of NO3--assimilation genes ............................................................................ 135 xiii List of Figures Figure 1.1 – Key regulatory proteins in NO3- assimilation repression pathways are still unknown in C. reinhardtii ............................................................................................................................4 Figure 1.2 – N status regulation in enteric bacteria and cyanobacteria via P II proteins .............. 11 Figure 1.3 – N status regulation in yeast via the TOR and GAAC pathways .............................. 15 Figure 2.1 – The within-group variability (dispersion) for RNA-seq replicates is low and fits tightly with the trendline ....................................................................................................................... 29 Figure 2.2 – Shrinkage of the log2 fold changes found between ARG and NF2 samples relative to AMM-I reduces the impact of low read counts per gene ........................................................ 30 Figure 2.3 – Volcano plots show that significantly differentially expressed genes are distributed evenly between up- and downregulated genes for ARG and NF2 samples relative to AMM-I ... 31 Figure 3.1 – Arginine-fed cultures show comparable growth rates in mixotrophic conditions but reduced rates in phototrophic conditions relative to NH4+-fed cultures ....................................... 36 Figure 3.2 – Arginine-grown cells constitutively upregulate N starvation marker genes. ............38 Figure 3.3 – Arginine-grown cells exhibit N starvation phenotypes. ...........................................40 Figure 3.4 – Arginine-fed cultures of P. tricornutum increase neutral lipid content during robust growth. ...................................................................................................................................... 46 Figure 4.1 – Variance between transcriptomes is associated with culture conditions ................ 50 Figure 4.2 – The arginine transcriptome shows strong overlap with the two-hour N starvation transcriptome in addition to greater total amount of DEGs ........................................................ 52 Figure 4.3 – N assimilation genes were upregulated in arginine comparable to two-hour N starvation expression profiles .................................................................................................... 55 Figure 4.4 – N assimilation genes were upregulated in arginine comparable to 48-hour N starvation expression profiles. ................................................................................................... 57 Figure 4.5 – Amino acid biosynthesis genes were significantly downregulated in all pathways except arginine biosynthesis relative to two-hour NF profiles .................................................... 61 Figure 4.6 – Amino acid biosynthesis genes were significantly downregulated in all pathways except arginine biosynthesis relative to 48-hour NF profiles. ..................................................... 62 Figure 4.7 – Photosynthesis genes were downregulated in arginine-fed cultures ...................... 66 Figure 4.8 – Arginine-fed cultures downregulate tetrapyrrole biosynthesis as in N-starved cultures ..................................................................................................................................... 70 Figure 4.9 – Calvin cycle and exogenous C assimilation genes were downregulated more in arginine-fed cultures than two-hour N starvation ....................................................................... 81 xiv Figure 4.10 – Calvin cycle and exogenous C assimilation genes were downregulated in arginine-fed cultures comparable to 48-hour N starvation ......................................................... 82 Figure 4.11 – Arginine cannot support heterotrophic growth in cultures without supplementation of exogenous C ......................................................................................................................... 85 Figure 4.12 – Arginine metabolism through arginine deiminase (ADI1) and polyamine degradation was upregulated in arginine-fed cultures relative to two-hour N starvation ............. 90 Figure 4.13 – Arginine metabolism through arginine deiminase (ADI1) was upregulated in arginine-fed cultures relative to 48-hour N starvation ................................................................ 91 Figure 5.1 – Utilization of a NIT1 promoter-driven conditional swimming reporter allowed for the identification of mutants putatively disrupted in N starvation regulation ................................... 105 Figure 5.2 – Five nsi1 mutants with defective N starvation marker gene regulation were disrupted in the same region ................................................................................................... 108 Figure 5.3 – Mutations in gln4 ordered from a public collection have defective N starvation marker gene expression .......................................................................................................... 110 Figure 5.4 – Stronger gln4 complementation of N starvation marker gene expression was observed in the progeny of B66 complement #2 backcrossed with a wild-type strain .............. 111 Figure 5.5 – GLN4 homologs form a clade of type II glutamine synthetases found in the core Chlorophytes ........................................................................................................................... 114 Figure 5.6 – GLN4 lacks key conserved residues and has a large deletion within the catalytic domain. ................................................................................................................................... 116 Figure 5.7 – gln4 mutants showed impaired regulation of N starvation marker genes ............. 118 Figure 5.8 – gln4;nit2 mutants cannot activate gametogenesis and showed decreased cell viability during N starvation whereas other N starvation responses are not interrupted ........... 119 Figure 5.9 – Arginine-fed gln4;nit2 mutants showed impaired regulation of N starvation marker genes ...................................................................................................................................... 120 Figure 5.10 – Arginine-fed gln4;nit2 mutants showed wild-type chlorophyll decreases and lipid accumulation ........................................................................................................................... 121 Figure 5.11 – gln4 single mutants showed wild-type regulation of NIT2-dependent genes in NO3- ........................................................................................................................................ 123 Figure 5.12 – Arginine growth of gln4 mutants is reduced compared to wild-type strains ........ 125 Figure 5.13 – gln4;nit2 double mutants showed impaired regulation of hundreds of N starvation inducible genes ....................................................................................................................... 127 Figure 6.1 – Utilization of a NIT1 promoter-driven conditional swimming reporter allowed for the identification of mutants putatively disrupted in NH4+-repression regulation ............................. 134 xv Figure 6.2 – Chlorate sensitive mutants cannot repress the N starvation marker gene AMT4 when cultured with NH4+ .......................................................................................................... 136 Figure 6.3 – Complementation of cs152 restored wild-type chlorate resistance ...................... 137 Figure 6.4 – The optimal cluster number for k-means clustering was calculated using the elbow method .................................................................................................................................... 139 Figure 6.5 – Principal components analysis identified mutants with very strong decreases in Fv / Fm ................................................................................................................................. 140 Figure 6.6 – Screening for light stress in autotrophic conditions reveals mutants putatively involved in photoprotection...................................................................................................... 141 xvi List of Abbreviations 2-OG 2-oxoglutarate AAAP Amino Acid/Auxin Permease ACCase acetyl-CoA carboxylase ADP adenosine diphosphate AP 3-acetylpyridine APC Amino acid Polyamine organoCation Arg arginine ARG arginine two-hour transcriptome ARS arylsulphatase ATP adenosine triphosphate BAC bacterial artificial chromosome C carbon Chl chlorophyll CLiP Chlamydomonas library project cs constitutive swimmer DAO diamine oxidases DEG differentially expressed gene DL dim light (5 μmol m−2 s−1) FA fatty acid GAAC general amino acid control GABA γ-aminobutyric acid Gln glutamine GLR glutamate-like receptor Glu glutamate GOGAT glutamine-2-oxoglutarate aminotransferase GS glutamine synthetase HL high light (150 μmol m−2 s−1) HygR hygromycin resistance iGluR ionotropic glutamate receptor LHCSR light-harvesting complex stress response LL low light (30 μmol m−2 s−1) MA methylammonium xvii N nitrogen NAGK N-acetyl-L-glutamate kinase NCR nitrogen catabolite repression NF nitrogen-free NF2 two-hour n starvation transcriptome NF48 forty-eight-hour n starvation transcriptome NH4+ ammonium NIN nodule inception protein NIT1 Chlamydomonas reinhardtii nitrate reductase NLP NIN-like protein NO nitric oxide ns non-swimmer PAO polyamine oxidases PCA principal components analysis PCR polymerase chain reaction PEG polyethylene glycol PUFA polyunsaturated fatty acid qPCR quantitative polymerase chain reaction ROS reactive oxygen species TAG triacylglycerol TAP Tris-acetate-phosphate TCA tricarboxylic acid TOR target of rapamycin TP Tris-phosphate UTase/UR uridyltransferase/uridyl-removing enzyme VHL very high light (250 μmol m−2 s−1) xviii Acknowledgements This scientific endeavor could not have been accomplished alone, and I am eternally grateful for the contributions towards this research and my personal growth throughout the process of my education and doctoral degree. Dr. Jae-Hyeok Lee, your patience, tireless efforts, and ingenuity were the driving force behind these pursuits. I cannot thank you enough. I would not be able to reach my goals without your mentorship and guidance. To my committee members, the deepest of thanks for the time that you have freely devoted towards my objectives. The quality of my work has been tremendously improved by your candid critiques and thoughtful insights. I am a better scientist and writer as a direct result of your inputs. Your willingness to sacrifice your energy into my education is truly appreciated. To my fellow lab members, you are a joy to work with and have been nothing but supportive and generous. A special thank you to Dr. Sunjoo Joo for your technical expertise and regular encouragement and support. A thank you to Yuan Xiong for sharing his skills studying photosynthesis which was essential to this thesis. Thank you Thamali Kariyawasam for showing me the ropes and teaching me the fundamentals of working with microalgae, I could not have even begun this research without your help. Lastly, a thank you to everyone in the lab who has provided their efforts to this project: Ran Ha Hong, Jenny Lee, Nolan Shelley, and Moyan Jia. The fruits of your labor are evident within this thesis. Funding for this project was provided in the form of a Discovery Grant to Dr. Jae-Hyeok Lee from the Natural Sciences and Engineering Research Council (NSERC) and by the Korea CCS R&D Center (KCRC), Korean Ministry of Science. Additional funding for my education was provided in the form of the Frances Chave Memorial Scholarship. It has been a long journey that would not have been possible without my close friends and family. Thank you to my parents and my brother for being there no matter what. No good thing is pleasant without friends to share it, you know who you are. And without Amanda Moreira I would not have the resolve to always continue, you are the reason to keep trying. Elaine, Gerry, JR, and Cameron; you will forever be missed, and this journey would not have been the same without you. 1 Chapter 1: Introduction 1.1 Nitrogen assimilation in photosynthetic eukaryotes Nitrogen (N) is a fundamental macronutrient for life as it is an essential component of nucleic acids and amino acids. Photosynthetic eukaryote productivity, in both the soil and the ocean, is limited by the availability of the major assimilated forms of N, NO3- and NH4+ (Xu et al., 2012). Agricultural production of plant crops, such as cereals, depends on the application of N fertilizer whose uptake is as low as 33% of that applied which leads to N overuse. Such overuse results in both higher costs and changes to the local (i.e. eutrophication) and global environment (i.e., greenhouse gas emission during the production of N fertilizers) (Raun and Johnson, 1999; Rothstein, 2007). One way to reduce these problems is to engineer crops with a higher N utilization efficiency. Unfortunately, the mechanisms regulating N assimilation in phototrophic eukaryotes is poorly understood, limiting the possibility of engineering crops for improved efficiency of N use (Kant et al., 2011; Gent and Forde, 2017). The major environmental N sources assimilated by photosynthetic eukaryotes as well as fungi are inorganic and potentially toxic, which necessitates a finely tuned coordination of their uptake and assimilation. The primary route of N assimilation in photosynthetic eukaryotes is via the glutamine synthetase (GS)/glutamine-2-oxoglutarate aminotransferase (GOGAT) cycle that assimilates inorganic NH4+ into glutamate at the expense of 2-oxoglutarate (2-OG) (Roon et al., 1974; Miflin and Lea, 1975; Hemmila and Mantsala, 1978; Cullimore and Sims, 1981). Thus, N assimilation requires monitoring both the availability of intracellular carbon (C) and external inorganic N sources. Survival during N limitation requires mechanisms that activate the uptake machinery of alternative N sources in response to low N availability (i.e., N scavenging), concomitant with the activation of protein and nucleic acid catabolism to use internal N reserves (i.e., N salvage) (Müntz, 2007; Werner and Witte, 2011; Avila-Ospina et al., 2014; Forde, 2014; Li et al., 2014; Krapp et al., 2014; Kiba and Krapp, 2016). 1.2 Signaling of internal N status vs external N availability Macronutrient detection and subsequent responses occur via two distinct mechanisms: the detection of intracellular concentrations of the macronutrient referred to here as the macronutrient status and the detection of extracellular concentrations of a unique macronutrient species referred to here as macronutrient scavenging. Both types of detection mechanisms can be found in species throughout all biological kingdoms (Reitzer, 2003; Conrad et al., 2014; Efeyan et al., 2015; Ham et al., 2018). 2 To more clearly define the distinction between the two mechanisms for macronutrient detection, particularly regarding N, it is helpful to review examples from yeast. In budding yeasts, the SPS (SSY1-PTR3-SSY5) pathway scavenges for amino acid N sources and the Target of Rapamycin (TOR)-regulated GLN3 transcription factor responds to the intracellular N status (Conrad et al., 2014; Zhang et al., 2018). The SPS system utilizes a transporter-like plasma membrane protein (SSY1) as a sensor for extracellular amino acids. When SSY1 binds external amino acids, a signal is transmitted through two other transmembrane proteins, PTR3 and SSY5, for which SSY5 is an endoprotease that is activated via the degradation of its prodomain by the interaction of PTR3 with SSY1 under certain amino acid conditions (Klasson et al., 1999; Souciet et al., 2000; Forsberg and Ljungdahl, 2001). The activated SSY5 protein cleaves the N-terminal inhibitor domains of two transcriptional activators (STP1/2) localized in the cytosol which induces their nuclear localization, activating genes involved in amino acid assimilation (Andréasson and Ljungdahl, 2002; Abdel-Sater et al., 2004; Ljungdahl, 2009; Tanaka and Mukai, 2015). In summary, the SPS system represents a 'transceptor'-type detection mechanism of external N sources for the transcriptional activation of relevant genes. In contrast, the TOR pathway in yeast responds to particular intracellular amino acid levels to monitor cellular N status via the TOR complex at the vacuolar membrane (Sturgill et al., 2008). The TOR complex, conserved throughout eukaryotes, consists of TOR kinase and scaffolding proteins that can differ between TOR complexes and endow them with unique characteristics (Loewith and Hall, 2011). The TOR complex is activated when the intracellular N status is high by a vacuolar membrane-associated complex known as the EGO complex which is comprised of the EGO1-3 subunits and the regulatory subunits, GTR1/2. Detection of the intracellular N status by the EGO complex is mediated by three pathways that alter the activation state of GTR1/2: 1) the guanine nucleotide exchange factor, 2) the GTPase-activating protein, and 3) the SEH1-associated complex (Sancak et al., 2008; Binda et al., 2009; Neklesa and Davis, 2009; Bonfils et al., 2012; Han et al., 2012; Powis and De Virgilio, 2016). When the TOR complex is active, the TAP42-PP2A (Type 2A phosphatase-associate protein 42/Protein phosphatase 2) complex is sequestered at the vacuolar membrane via a direct interaction of the TOR complex with TAP42 (Kunz et al., 2000; Yan et al., 2006; Aronova et al., 2007). Conversely, amino acid (N) depletion inactivates TOR and the TAP42-PP2A complex is released from the vacuolar membrane into the cytosol (Yan et al., 2006). The cytosolic TAP42-PP2A complex dephosphorylates transcriptional activators like GLN3, causing them to translocate to the nucleus and activate N catabolism and stress response genes (Shamji et al., 2000; Düvel et al., 2003). Under N starvation conditions, the extracellular N scavenging (SPS 3 system) is suppressed by dephosphorylation of SSY5 via TAP42-PP2A complexes released when the TOR complex is inactivated (Omnus and Ljungdahl, 2013). However, if the external concentration of amino acids is high enough then the phosphorylation of SSY5 by the SPS system can overcome the dephosphorylation by the TAP42-PP2A complex. By this mechanism, the intracellular N status monitoring can prevent superfluous protein production and N expenditure towards amino acid catabolism if amino acids are not present in high enough abundance. In summary, the key difference between the two detection mechanisms (scavenging vs. status) is that macronutrient scavenging regulatory pathways respond directly to a molecular species of an available macronutrient whereas the macronutrient status regulatory pathways respond to key metabolites that indicate the overall intracellular macronutrient availability. 1.3 External N availability signaling in photosynthetic eukaryotes 1.3.1 NO3--specific transcriptional regulation Inorganic N sources, particularly NO3-, are the most abundant forms of N utilized by photosynthetic eukaryotes in the soil and ocean (Xu et al., 2012). One of the earliest discoveries of N scavenging regulatory components in photosynthetic eukaryotes was made in Chlamydomonas reinhardtii (C. reinhardtii) by using a selection system for resistance to the toxic NO3- analog, chlorate, which suggested defects in the NO3- assimilation system (Nichols and Syrett, 1978). Of the chlorate resistant mutants, many had mutations in genes encoding transporters and enzymes in the NO3- assimilation pathway, whereas one mutation, NIT2 (originally NITB), displayed both undetectable NO3- reductase activity and substantially lower NO3- uptake. These data suggested that NIT2 was a regulator of the NO3- assimilation pathway (summarized in Figure 1.1) (Nichols et al., 1978). Further studies found that NIT2 is a positive regulator for most known genes involved in NO3- uptake and assimilation (NII1, NRT2.1, NRT2.2, NRT2.3, NAR2, NIT1, NAR1.1, NAR1.6; AMT1.1) (Quesada et al., 1993; Quesada and Fernández, 1994; Quesada et al., 1998; González-Ballester et al., 2004; Mariscal et al., 2006; Camargo et al., 2007). Of these genes, the NIT1 gene encoding NO3- reductase has been used as the primary marker of NIT2-dependent gene activation (Fernandez and Galvan, 2007). 4 Figure 1.1 – Key regulatory proteins in NO3- assimilation repression pathways are still unknown in C. reinhardtii. The assimilation of inorganic N sources are displayed with grey arrows. Positive regulation is displayed with green arrows and negative regulation is displayed with red lines. Proteins/genes outlined in purple indicate targets of NIT2-dependent regulation. Proteins with a question mark indicate unknown regulatory enzyme(s). The molecular structures of ammonium, nitrate, nitrite, and nitric oxide are illustrated with oxygen atoms in red, hydrogen atoms in grey, and nitrogen atoms in blue. 5 While NIT2 is the primary regulator of NO3--inducible genes, the residual uptake of NO3-/nitrite (NO2-) and activity of NO3-/ NO2- reductases has been documented in stains with well-studied nit2 mutant alleles (from strains 203 and 137c) (Nichols and Syrett, 1978; Galván et al., 1992). The residual expression of the NO3- assimilation pathway was hypothesized to be the consequence of leaky expression activated by these nit2 mutant alleles. However, it remains to be investigated whether the upregulation of NO3--inducible genes occurred via a NIT2-independent pathway. The cumulative conclusion reached over three decades of research was that NO3- assimilation is controlled solely by NIT2 in response to the presence of NO3- with NIT1 regulation serving as a reliable marker of NIT2 induction (Camargo et al., 2007; Fernandez and Galvan, 2007). Homologues to the C. reinhardtii NIT2 transcription factor were subsequently discovered in Arabidopsis thaliana (A. thaliana) (Castaings et al., 2009; Marchive et al., 2013), implicating a degree of conservation regarding N scavenging regulation between green algae and land plants. In A. thaliana, a number of transcription factors controlling NO3--inducible regulation have been identified, including TGA1, TGA4, ANR1, bZIP1, LBD37, LBD38, TCP20, NAC4, SLP9, and NLPs homologous to NIT2 (Chardin et al., 2014; Vidal et al., 2015; O’Brien et al., 2016). Of importance to the early NO3- transcriptional responses in A. thaliana is the nodule inception-like protein 7 (NLP7) which is shuttled between the cytosol and nucleus in response to NO3- availability (Castaings et al., 2009; Marchive et al., 2013). NLP7 and its homologs share a GAF domain associated with cyclic GMP binding and signal transduction (Ho, 2000) and a RWP-RK domain that is conserved among the plant nodule inception (NIN) proteins, C. reinhardtii NIT2, and the C. reinhardtii MID protein that controls mating-type specific gene expression during N starvation (Galloway and Goodenough, 1985; Camargo et al., 2007; Castaings et al., 2009; Konishi and Yanagisawa, 2013; Marchive et al., 2013). In addition to transcription factors, research on NO3- responses in A. thaliana have identified a dual function NO3- transporter and detecting protein (transceptor) , AtNRT1.1 (CHL1) that controls the transcription of high and low affinity NO3- transporters (Ho et al., 2009). AtNRT1.1 detects whether external NO3- concentrations are high or low and transmits the signals for low or high external NO3- concentrations through CBL-interacting protein kinase 23 and 8 (CIPK23/8), respectively (Hu et al., 2009). The downstream effectors of AtCIPK23/8 are not known with much clarity, however, AtNLP7 is thought to be involved in modulating this transcriptional response (Zhao et al., 2018). AtNRT1.1 belongs to the Nitrate Peptide Family (NPF) which, in A. thaliana, includes 53 proteins with varying substrate specificity including NO3-, NO2-, amino acids, peptides, glucosinolates, auxin, and abscisic acid (Léran et al., 2014; O’Brien et al., 2016). C. reinhardtii 6 has only one NPF family protein (CrNRT1), however, whether CrNRT1 is involved in NO3- transport or detection has not been characterized. 1.3.2 NH4+-repression of alternative N assimilation While NO3- is often the most abundant form of bioavailable nitrogen, NH4+ is preferred due to the low energetic cost of assimilation relative to its oxidized forms, NO3- and NO2-. NH4+ from extracellular and intracellular (photorespiration or amino/nucleic acid catabolism) sources is incorporated into the cell primarily via the GS/GOGAT cycle in the chloroplast, contributing a net production of glutamate, the major N donor for several biosynthetic pathways (i.e. tetrapyrrole biosynthesis) (Cullimore and Sims, 1980, 1981; Hipkin et al., 1982; Crawford and Arst, 1993; Crawford, 1995; Daniel-Vedele et al., 1998). The preference for NH4+ in C. reinhardtii is suggested by the fact that many essential NO3-/NO2- genes are repressed in the presence of NH4+ known as NH4+ repression (Fernández and Cárdenas, 1982; Florencio and Vega, 1983; Fernández and Cardenas, 1989; Galván et al., 1992; Fernández et al., 1998). The negative regulation of NO3-/NO2- assimilation by NH4+ in C. reinhardtii occurs through currently unknown molecular mechanisms that repress the transcription of genes encoding NO3- uptake machinery within two hours (Florencio and Vega, 1983; Quesada and Fernández, 1994; Fernandez and Galvan, 2007). Early attempts to elucidate these molecular regulators identified mutants with alleviation of NH4+ repression when NH4+ concentrations were lower than NO3- concentrations (nrg1-4, far1) but the identities of those mutants were not determined (Prieto et al., 1996; Zhang and Lefebvre, 1997; Perez-Alegre et al., 2005). Plants, such as Nicotiana plumaginifolia and barley, likewise show repression of NO3- uptake machinery when grown in reduced N sources such as NH4+ or glutamine indicating that the preferential use of NH4+ is conserved among photosynthetic eukaryotes (Quesada et al., 1997; Vidmar et al., 2000). Additionally, NH4+ and NO3- ions have been shown to directly repress N starvation-induced gametogenesis in C. reinhardtii via either chemical inhibition of NH4+ assimilation or by preventing NO3- assimilation using nit1 mutants (Matsuda et al., 1992; Pozuelo et al., 2000). However, whether NH4+ repression of NO3--inducible genes and the repression of the N starvation-induced gametogenesis are regulated by the same pathway is unknown. In 2005, González-Ballester et al., reported a large-scale insertional mutagenesis screen for the regulators of NH4+ repression using a NIT1 promoter-driven reporter. Screens for mutants that were unable to repress NIT1-promoter reporter activity in the presence of 7.5 mM NH4+ and 4 mM NO3- revealed a set of mutants (named NH4+ insensitive), whose characterization suggested 7 a mechanism involving nitric oxide (NO) for the negative regulation of NO3--inducible gene expression (De Montaigu et al., 2011; Calatrava et al., 2017; Chamizo-Ampudia et al., 2017). A caveat of the Gonzalez-Ballester study is the lack of NH4+ insensitive mutants that show full activation of NIT1 in the presence of NH4+ and NO3-. Additionally, the requirement of NO3- in the media for characterizing the NH4+ insensitive phenotype may cause a complication due to the potential uptake of NO3- via a NIT2-independent pathway. In 2011, De Montaigu et al., found low expression of the NO3- assimilation pathway in the conditions used by Gonzalez-Ballester et al., (2005) to screen for the NH4+ insensitive mutants (7.5 mM NH4+ and 4 mM NO3-). This low expression of the NO3- assimilation pathway would result in the reduction of NO3- to NO2- in the cytosol, whose potential toxicity is normally reverted by its reduction into NH4+ in the chloroplast. However, the reduction of NO2- to NH4+ is catalyzed by NO2- reductase (NII1) that uses ferredoxins as a reductant, which are possibly limiting under high NH4+ condition (7.5 mM) where the chloroplast GOGAT competitively consumes ferredoxin reductant (García-Sánchez et al., 1997). Therefore, the 7.5 mM NH4+ and 4 mM NO3- culture condition may generate a toxic accumulation of NO2-, which would complicate the cellular responses that are presumably also regulated by the external NH4+. Consequently, it remains unknown whether NH4+ detection and/or assimilation affects N responses independent from NO3- metabolism, which serves as a primary source of the NO (detailed below) which was proposed as a critical mediator of NH4+-repression. Thus, considering that NH4+ represses gametogenesis and other N starvation responses, additional studies are required to dissect the NH4+ repression mechanisms in NO3--dependent and N starvation responses, which may represent separate signaling pathways (shown in Figure 1.1) (Sanz-Luque et al., 2013, 2015a; Chamizo-Ampudia et al., 2016; Sanz-Luque et al., 2016). 1.3.3 Nitric oxide-mediated repression of NO3- assimilation NO has recently emerged as a critical signaling molecule in C. reinhardtii for its roles in N-related signaling (Wei et al., 2014; Calatrava et al., 2017). A mutation in a guanylate cyclase (CYG56) with homology to the mammalian NO-dependent guanylate cyclases caused a failure to repress NIT1 promoter-reporter activity driven by NO3- in the presence of NH4+ (de Montaigu et al., 2010). Characterization of the cyg56 mutants reported an increased expression of NIT1 in the presence of 2 mM NH4+ and 4 mM NO3- relative to the wild-type. NO donors, DEA NONOate and SNAP, resulted in the full repression and partial repression of NIT1 expression, respectively, which supported NO as a repressor molecule. However, de Montaigu et al., (2010) suggested that the negative regulation of NIT2-responsive genes may not be a response to NH4+ at all but 8 directly regulated by NO produced from NIT1 or the mitochondrial electron transport chain using NO2- as the substrate (Yamasaki and Sakihama, 2000; Bethke et al., 2004; Tischner et al., 2004; Planchet et al., 2005). The hypothesis that NO2--derived NO represses the NIT2-responsive genes is further supported by the discovery that NIT1 mediates the release of NO from NO2- via its coordinated activity with the Amidoxime Reducing Component (ARC) (Chamizo-Ampudia et al., 2016). The generated NO can then be converted back into NO3- through the combined action of NIT1 and truncated hemoglobin 1 (THB1) which fulfills a cycle for which NIT1 is the central component (Sanz-Luque et al., 2015a). The cycle of NO3- -> NO2- -> NO -> NO3- (illustrated in Figure 1.1) could serve to alleviate toxicity if too much NO3- or NO2- accumulate intracellularly by preventing the overaccumulation of any one molecule. NO-mediated repression of NO3-/NO2- assimilation from the NO produced in the cycle would therefore prevent further toxicity since the NO content is expected to increase in excess NO3- conditions. Furthermore, NO controls NIT1 activity and NO3-/NO2-/NH4+ transporters at the post-translational level via an unknown mechanism (Sanz-Luque et al., 2013). Another role for this cycle could be to scavenge NO produced by other signaling pathways so that this diffusible gas messenger and its valuable N is not lost to the environment. This role is supported by the fact that NO positively regulates THB1 expression for converting NO back into NO3- (Sanz-Luque et al., 2015a, 2015b). 1.4 Putative N status signaling pathways in photosynthetic eukaryotes In A. thaliana, N starvation responses appear to be substantially regulated at the transcriptional level, as outlined in the references below, but few molecular components have been described. The NLP family of transcription factors have been suggested to regulate some N starvation-inducible gene expression in addition to their role as key regulators of NO3- assimilation (Castaings et al., 2009; Marchive et al., 2013; Liu et al., 2017). Conversely, the repression of N starvation-inducible genes is alleviated by disruption of Lateral Organ Boundary Domain (LBD37-39) transcription factors, the NIGT1/HRS1 subfamily of GARP-type transcription factors, and miR169 (Rubin et al., 2009; Zhao et al., 2011; Kiba et al., 2018), suggesting that multiple pathways are involved in repressing N starvation responses. Other than transcription factors, the calcium sensor, CBL7, has been shown to participate via an unknown mechanism in the upregulation of the N starvation-induced genes, NRT2.4 and NRT2.5 (Ma et al., 2015). The known mechanisms for the regulation of N assimilation pathways have hinted at glutamine and glutamate as the most likely candidates for detecting intracellular N status (Vidmar et al., 2000; Krapp, 2015; Gent and Forde, 2017). However, it remains largely unknown in 9 photosynthetic eukaryotes how N status is detect or the major molecular mechanisms/key player(s) that coordinate the appropriate transcriptional responses. One major difficulty in N starvation studies using plants as a model is the complexity predicted in multicellular organisms. For example, in A. thaliana, there are >40 known cell types and cells of the same type are subject to the constant flow of N between source and sink tissues, creating a network of N-replete and N-limited cells. Therefore, the transcriptional consequences of experimental manipulation of cellular N status is highly unpredictable. The utilization of a unicellular photosynthetic eukaryote allows for the study of N starvation on a clonal population of cells that are all exposed to the same N availability. N starvation transcriptomics studies in C. reinhardtii have revealed rapid and robust upregulation of N scavenging and N salvage genes within two hours of N starvation (Lee et al., 2012; Schmollinger et al., 2014; Wase et al., 2014; Park et al., 2015). The upregulation of these genes within 15 minutes suggests that detectors of N availability and downstream regulators are present prior to N starvation. Potential N starvation signal transduction pathways in photosynthetic eukaryotes could be regulated as in the two best studied mechanisms: the PII/NTRC pathway in E. coli and the TOR/GLN3 pathway in S. cerevisiae (Huergo et al., 2013 and Baena-González and Hanson, 2017). It is known that homologues of the PII and TOR proteins are present in photosynthetic eukaryotes with the PII protein localized in the chloroplast and the TOR complex in the cytosol, reviewed recently (Dobrenel et al., 2016 and Forchhammer and Lüddecke, 2016). However, whether the PII or TOR complexes play significant roles in N assimilation regulation or if another signaling pathway exists in photosynthetic eukaryotes remains to be experimentally determined. Five potential routes for photosynthetic eukaryotes to detect their intracellular N status are: 1) PII proteins, 2) TOR complexes, 3) the general amino acid control pathway (GAAC), 4) glutamate-like receptors (GLRs), and 5) GS-dependent regulation (Gent and Forde, 2017). Below I summarize these putative routes of N status detection including the context of their discovery in bacteria and fungi if applicable and how a similar approach could be applied in photosynthetic eukaryotes. 1.4.1 PII proteins In prokaryotes, the transcriptional control of N-regulated genes (NTR regulon) allows for the assimilation of alternative N sources in response to N limitation or the lack of a preferred N source (Neidhardt and Magasanik, 1957; Prival and Magasanik, 1971; Kustu et al., 1979). The NTR regulon includes direct assimilation targets like glutamine synthetase (GLNA) and the 10 arginine utilization (AUT) gene but also includes transcription factors like NAC which controls proline, histidine, and urea assimilation. The NTR regulon is derepressed during growth on histidine, arginine, or proline, which are defined as poor or derepressive N sources, whereas preferred N sources are defined for their ability to fully repress the NTR regulon (Ninfa et al., 1995). The derepressive N sources show a varying degree of NTR regulon derepression. The N sources with the most derepression of the NTR regulon provided the necessary conditions for the isolation and characterization of the molecular components that govern NTR regulation in bacteria, such as Klebsiella aerogenes and Escherichia coli (Magasanik, 1982). Studies utilizing such poor (derepressive) N sources identified regulatory mutants that fall into two predominant categories; 1) those unable to induce NTR genes (glutamine synthetase/histidase) when grown with poor (derepressive) N sources and 2) those unable to suppress NTR genes when preferred (repressive) N sources were present (Magasanik, 1982). Mutants insensitive to poor N sources that were unable to induce NTR genes identified the master positive regulator of the NTR regulon as the two-component system NTRB/NTRC (NRI/NRII) (illustrated in Figure 1.2). Under N starvation, NTRC phosphorylation is required for the full activation of the NTR regulon (Reitzer and Magasanik, 1985; Ninfa and Magasanik, 1986). The phosphorylation state of NTRC is primarily controlled via its dephosphorylation by the complex of NTRB and an unmodified PII protein (Ninfa and Magasanik, 1986). In enteric bacteria, the homotrimeric PII proteins coordinate a variety of cellular processes around N metabolism particularly as a regulator of NTRB/NTRC (Huergo et al., 2013). PII proteins play a dual role in both inducing and suppressing NTR regulon expression (Prival et al., 1973; Foor et al., 1975). During N limitation, the PII protein is uridylated by the uridyltransferase/uridyl-removing enzyme (UTase/UR) in response to decreased glutamine levels. The uridylation of PII inhibits its binding with NTRB, resulting in the activation of NTRB and the phosphorylation of NTRC, leading to the upregulation of the NTR regulon (Brown et al., 1971; Kamberov et al., 1994, 1995; Jiang et al., 1998). Conversely, high glutamine levels produced during excess N availability enhances the uridyl-removing activity of UTase/UR resulting in the formation of PII - NTRB complexes that dephosphorylate NTRC and prevent the expression of the NTR regulon (Atkinson et al., 1994; Kamberov et al., 1994). The PII protein is considered essential towards the regulation of N starvation-dependent transcription in bacteria, however, the regulation of PII proteins in response to nutrient conditions varies among different bacteria. In cyanobacteria where photosynthesis alters the C availability 11 Figure 1.2 – N status regulation in enteric bacteria and cyanobacteria via P II proteins. Scissors indicate the removal of covalent modifications from PII proteins. Sigma 54 (𝛔54) is the sigma factor controlling nitrogen regulated promoters. U = uridyl, P = phosphate, Gln = glutamine, 2-OG = 2-oxoglutarate, UTase/UR = uridyltransferase/uridyl-removing enzyme, RNAP = RNA polymerase, PPHA = PII-P phosphatase, PIPX = PII interacting protein X, NAGK = N-acetyl glutamate kinase. 12 for N assimilation, the global nitrogen regulator NTCA, instead of the NTRB/NTRC two-component system, controls N starvation-dependent transcription in response to 2-OG levels (Vega‐Palas et al., 1992). During N starvation, less 2-OG is consumed by the GS/GOGAT cycle which results in high 2-OG levels and leads to the formation of 2-OG bound NTCA dimers. The 2-OG bound NTCA dimers are then stabilized by the transcriptional co-activator, PII interacting protein X (PIPX), thereby activating its target genes (Espinosa et al., 2006; Llácer et al., 2010; Zhao et al., 2010; Espinosa et al., 2014). Conversely, during N abundance when 2-OG levels are low, NTCA dimers no longer bind 2-OG and PIPX is bound by PII proteins, decreasing active NTCA-PIPX complexes and N starvation-dependent transcription. In addition, cyanobacterial PII proteins possess a regulatory function independent from the NTCA-driven transcription. The PII protein binds 2-OG, therefore, low 2-OG levels allow for the PII phosphatase (PPHA) to access and remove PII phosphorylation, resulting in the interaction of the PII protein with the rate-limiting enzyme of arginine biosynthesis, N-acetyl-L-glutamate kinase (NAGK). The PII-complexed NAGK becomes insensitive to feedback inhibition by arginine, leading to an increased N flux into polyamine synthesis and arginine synthesis for N storage (Forchhammer, 1999; Irmler and Forchhammer, 2001; Ruppert et al., 2002; Heinrich et al., 2004). Therefore, the cyanobacterial PII plays a role in both N-replete and N-deplete conditions, as in enteric bacteria, but with distinct interacting partners and mechanisms. In summary, the bacterial PII protein is a central regulator of N status-dependent responses, which primarily depends on the levels of GS/GOGAT cycle metabolites, 2-OG and/or glutamine, as key metrics of N availability. A PII protein (GLNB) descended from a cyanobacterial PII is conserved throughout photosynthetic eukaryotes and is localized to the chloroplast (Hsieh et al., 1998; Uhrig et al., 2009; Chellamuthu et al., 2013, 2014). Post-translational modification has not been reported for the eukaryotic version PII and no PIPX homologue has been identified so far in eukaryotic genomes (Smith et al., 2004; Ermilova et al., 2013). However, the interaction of PII with NAGK has been reported in major photosynthetic eukaryotic lineages, including green algae, mosses, and angiosperms (Burillo et al., 2004; Sugiyama et al., 2004; Chellamuthu et al., 2014; Minaeva et al., 2015). In addition to NAGK, PII-affinity chromatography in A. thaliana chloroplast soluble extracts identified subunits of plastidial acetyl-CoA carboxylase (ACCase) as interacting partners (Bourrellier et al., 2010). ACCase is a rate-limiting step in fatty acid biosynthesis whose activity was shown to be inhibited by ATP-bound PII proteins (Bourrellier et al., 2010). Eukaryotic PII proteins from the rice Oryza, the moss Physcomitrella, and the green algae Chlamydomonas show direct binding to glutamine, an important diversion from their bacterial ancestors, which may eliminate the need for covalent modification by its interacting partners. 13 Increased interaction of PII and NAGK upon N-replete conditions (e.g. increased glutamine) was shown to result in a measurable increase of N flux into arginine and polyamine synthesis (Chellamuthu et al., 2014; Minaeva et al., 2015), suggesting the conservation of PII roles under excess N conditions. Mutations in the A. thaliana PII protein resulted in reduced arginine biosynthesis, increased accumulation of C metabolites, and an increased chloroplast uptake of NO2- (Ferrario-Méry et al., 2005, 2006, 2008), indicating an C:N imbalance. Future studies will be required to test whether PII with or without its interacting partners is also involved in N starvation-dependent transcriptional responses as found in bacteria. 1.4.2 TOR complex Following the identification of the critical players for N-dependent responses in bacteria, a similar approach using repressive and derepressive conditions has been powerful for unraveling N starvation signal transduction networks in fungi. As with E. coli, N starvation responses in the budding yeast S. cerevisiae are repressed by the GS/GOGAT metabolite glutamine. S. cerevisiae selectively assimilates more useful external N sources first in a process coined nitrogen catabolite repression (NCR) (Cooper, 1982). The expression of genes encoding N scavenging pathways for glutamine, glutamate, proline, urea, arginine, γ-aminobutyrate (GABA), and allantoin are all upregulated when the preferred N sources (glutamine, asparagine, and NH4+) are not sufficiently available (Hofman-Bang, 1999). Likewise, NCR regulates the expression of genes encoding N salvage proteases, CPS1, PRB1, LAP1, and PEP4, involved in the degradation of proteins into amino acids. Mutants that failed to upregulate the N starvation genes when grown on derepressive N sources such as glutamate, histidine, lysine, and methionine identified the GLN3 GATA-type zinc finger transcription factor as the primary positive regulator (Mitchell and Magasanik, 1984), much like the identification of the NTR regulon mutants in E. coli (Ninfa et al., 1995). Further studies have collected three other GATA-type zinc finger transcription factors, GAT1, DAL80, and GZF3, as regulators of NCR gene expression (Hofman-Bang, 1999). Of these, GLN3 and GAT1 serve as positive regulators of N scavenging and salvage in S. cerevisiae (Coffman and Cooper, 1997). However, the mechanisms of N starvation-dependent regulation described for yeast are not conserved in other fungal lineages. The activation of NCR genes in S. cerevisae is triggered by the nuclear translocation of GLN3 and GAT1 positive regulators, which is orchestrated by a TOR-dependent pathway that responds to low glutamine and the general amino acid control (GAAC; discussed below) pathway that is activated by uncharged tRNAs (illustrated in Figure 1.3) (Bertram et al., 2000; Crespo et al., 2002; Hinnebusch, 2005; Tate et al., 2017). The core of the TOR complex is formed by the 14 serine/threonine kinase TOR protein which links to other proteins that differ between organisms and, in yeast, between the two possible TOR complexes that give each a unique set of characteristics. The TOR complexes regulate a wide range of responses including cell growth, cell proliferation, cell motility, cell survival, protein synthesis, autophagy, and transcription in response to various metabolites, hormones, or amino acids (Lipton and Sahin, 2014; Xiong and Sheen, 2014; Weisman, 2016). In response to low glutamine levels, the TOR complex releases the TAP42-PP2A phosphatase complex into the cytosol where it dephosphorylates GLN3 and GAT1 (described earlier) (Heitman et al., 1991; Bertram et al., 2000). The dephosphorylated GLN3 and GAT1 transcription factors can localize to the nucleus and activate the NCR genes. The N starvation-dependent control of GLN3/GAT1 nuclear localization can occur independent from the phosphorylation states of GLN3, GAT1, or the URE2 repressor protein controlled by TOR likely by GAAC pathway regulation (Beck and Hall, 1999; Feller et al., 2013). With few exceptions, all eukaryotes have a TOR-based signaling pathway linking nutrient signaling and energy supply to the regulation of cell growth (Serfontein et al., 2010; Van Dam et al., 2011; Chantranupong et al., 2015). In mammals, active TOR under high N availability promotes energy-consuming processes such as cell division, mRNA translation, and anabolism while repressing autophagic nutrient remobilization (Dobrenel et al., 2016). Inactivation of TOR during nutrient stress or by rapamycin treatment promotes autophagy and the use of non-preferred nutrient sources (Crespo et al., 2002; Loewith and Hall, 2011; Broach, 2012). The advances in the understanding of TOR-mediated regulation in fungi and animals have been greatly facilitated using TOR-specific inhibitors such as rapamycin. On the other hand, studies of TOR functions in photosynthetic eukaryotes have suffered from an insensitivity of rapamycin and lethality of TOR mutations in model plants. Therefore, a primary approach has been to study plant proteins homologous to those involved in TOR functions conserved in yeasts and animals. One conserved target of the TORC1 complex involved in N status signaling is A. thaliana TAP46, an ortholog to TAP42 (Harris et al., 1999). Disruption of TAP46 or inducible downregulation of TOR in A. thaliana resulted in the downregulation of NO3- assimilation and upregulation of amino acid recycling genes, suggesting that TOR may control N status responses in plants (Ahn et al., 2011; Caldana et al., 2013). The downstream effectors of A. thaliana TOR and TAP46 that mediate the transcriptional regulation of N metabolism remain to be determined. The most well-known function of TOR in plants is to convey C signals, namely sucrose and glucose, indicative of energy state. A combination of chemical, genetic, genomic, bio-computational and cell-based analyses showed that exogenous supply 15 Figure 1.3 – N status regulation in yeast via the TOR and GAAC pathways. The TOR and GAAC regulation pathways have overlapping control of N catabolite repression (NCR) gene expression. Phosphate groups are indicated by yellow circles with the letter P. 16 of glucose or sucrose induced TOR-dependent increases in the phosphorylation state of S6 kinase (S6K1/2) and E2 promoter-binding factor (E2Fa/b) proteins, which resulted in increased growth and cell division in both roots and shoots (Xiong et al., 2013; Caldana et al., 2019; Ryabova et al., 2019; Wu et al., 2019). More recently new techniques have been developed to study TOR regulation in plants using new chemical inhibitors or the exogenous expression of yeast TOR and advances in TOR signaling in plants are forthcoming. The role of TOR in photosynthetic eukaryotes has recently been studied in C. reinhardtii where rapamycin can inactivate TOR in a FKBP12-dependent manner as shown in yeast and animals (Crespo et al., 2005; Caldana et al., 2019). Inactivation of TOR in C. reinhardtii by rapamycin showed multiple phenotypes related to N starvation, including the prevention of protein synthesis and the induction of autophagy and triacylglycerol synthesis (Pérez-Pérez et al., 2010; Díaz-Troya et al., 2011; Imamura et al., 2015). Furthermore, hundreds of proteins involved in translation, carotenoid biosynthesis, and autophagy were found with altered phosphorylation states in TOR-inhibited cells (Roustan and Weckwerth, 2018; Werth et al., 2019). Additionally, the transcriptomes and metabolomes of rapamycin-treated cells suggested the involvement of TOR in the regulation of de novo amino acid synthesis (Jüppner et al., 2018; Mubeen et al., 2018). Taken together, it has been hypothesized that TOR plays a large role in the responses to N limitation, given the similarities between TOR-inhibited cells and N-starved cells (Pérez-Pérez et al., 2010; Imamura et al., 2015; Pérez-Pérez et al., 2017). However, this hypothesis remains to be experimentally tested. It was recently shown that phosphorus starvation induces a sharp decrease in the expression of LST8, a conserved component of the TOR complex, in a PSR1 (Phosphorus Starvation Response 1) transcription factor-dependent manner (Couso et al., 2020) which resulted in decreased TOR complex activity responsible for some phosphorus starvation-induced responses. Therefore, it will be critical to investigate whether TOR complex activity is controlled by cellular N status and is necessary for the known N starvation responses. 1.4.3 The general amino acid control (GAAC) pathway Advances in the understanding of TOR-dependent control of GLN3-regulated NCR genes have determined that TOR alone cannot explain NCR in yeast (Cox et al., 2004; Tate et al., 2006; Georis et al., 2008; Tate et al., 2010; Georis et al., 2011b, 2011a; Fayyad-Kazan et al., 2016; Tate et al., 2017). The GAAC pathway is well positioned to fulfill the missing component of NCR regulation via the detection of uncharged tRNAs (Mitchell and Magasanik, 1984; Natarajan et al., 2001; Valenzuela et al., 2001; Riego et al., 2002; Sosa et al., 2003; Staschke et al., 2010; Hernández et al., 2011). During amino acid starvation, the level of uncharged tRNA increases, 17 which activates the GCN2 kinase that phosphorylates the eIF2a translation elongation factor and results in the increased translation of the GCN4 transcription factor responsible for upregulating >500 genes, including those of amino acid biosynthesis (Cherkasova and Hinnebusch, 2003; Hinnebusch, 2005; Staschke et al., 2010; Castilho et al., 2014; Lageix et al., 2015; Dever et al., 2016). Additionally, the GAAC pathway is necessary for the nuclear localization of GLN3 during cultivation on nonpreferred N sources (Tate et al., 2017). In summary, the NCR genes are regulated by reciprocal manners, activation by the GAAC pathway that is induced by nutrient starvation and repression by the TOR pathway that is activated by nutrient-replete conditions. The opposing control of GAAC and TOR provides the mechanisms necessary for tight control over N homeostasis in yeast. Photosynthetic eukaryotes possess a homologous GCN2 kinase and two types of eIF2a kinases, however, no GCN4 homolog has been found (Gent and Forde, 2017). In vitro studies of the plant GCN2 shows it is likewise activated by uncharged tRNAs and can phosphorylate the plant eIF2α kinases (Li et al., 2013). The plant GCN2 kinase has been implicated in plant immune responses, suggesting that the GAAC pathway may operate in vivo in plants (Luna et al., 2014). It remains to be studied whether a transcriptional regulator analogous to the yeast GCN4 exists and is regulated by eIF2a in photosynthetic eukaryotes. 1.4.4 Glutamate receptor-like proteins Ionotropic glutamate receptors (iGluRs) were first found in mammals where they primarily act as neurotransmitters in the nervous system. Homologs of iGluRs known as glutamate receptor-like (GLR) proteins have since been identified across all domains of life including photosynthetic eukaryotes (Gasic and Hollmann, 1992; Price et al., 2012; De Bortoli et al., 2016). Given the function of iGluRs as highly specialized transporters in the nervous system, the finding of homologs in photosynthetic eukaryotes was unexpected. The GLRs were originally predicted to be localized to the plasma membrane, however, some GLR homologs have also been found to localize to the chloroplast or mitochondria (Lam et al., 1998; Teardo et al., 2011, 2015). GLRs may function as amino acid-detecting transporters. Genetic and pharmacological studies have shown signaling roles of GLRs in a wide array of cellular processes including: abiotic stress responses (Kang et al., 2004; Meyerhoff et al., 2005), photosynthesis (Teardo et al., 2010, 2011), pollen tube growth (Michard et al., 2011; Wudick et al., 2018b), root architecture (Li et al., 2006; Miller et al., 2010a; Vincill et al., 2013), plant immunity (Kang et al., 2006), Ca2+ kinetics (Vincill et al., 2012; Ortiz-Ramírez et al., 2017), and of particular relevance, C:N homeostasis 18 (Kang and Turano, 2003). Therefore, it is feasible that GLRs may also participate in conveying N status and triggering the appropriate responses. The membrane localization of these potential amino acid detectors could be best suited to long-distance intercellular signaling. While A. thaliana possesses 20 GLR homologues, C. reinhardtii possesses three which all have very low homology to the A. thaliana GLRs (phytozome.net; Chiu et al., 2002; Davenport, 2002; Wudick et al., 2018a). Of those, CrGLR1, predicted to localize to the secretory pathway by PredAlgo (Tardif et al., 2012), is highly induced in long-term N starvation transcriptomes (Schmollinger et al., 2014). Therefore, CrGLR1 may serve a regulatory role, however, this hypothesis remains to be investigated. 1.4.5 Glutamine synthetase-dependent regulation Glutamine synthetase (GS) holds a central position in the primary metabolism of N in photosynthetic eukaryotes, converting inorganic N sources into the inert organic N source, glutamine. The activity of GS requires the substrates NH4+, glutamate, 2-oxoglutarate, and ATP/ADP that fluctuate upon the intracellular availability of N, C, and energy, therefore, GS could have a role in N status detection. In Bacillus subtilis, GS was shown to directly interact with transcription factors that regulate the expression of N-regulated genes in response to N status (Gunka and Commichau, 2012). When the B. subtilis GS is feedback-inhibited by high glutamine levels, the transcriptional activator of N starvation responses, TNRA, binds to the GS side cavity and changes the conformation of the catalytic cleft. The interaction with TNRA and GS alters the quaternary structure of GS which inhibits GS catalytic activity in addition to preventing TNRA nuclear localization and DNA-binding (Wray et al., 1996, 2001; Wray and Fisher, 2008; Schumacher et al., 2015). TNRA-regulated genes include alternative N source assimilation enzymes (i.e. aspartate, urea, and NO3-) and those involved in NH4+ uptake (Nakano et al., 1998; Wray et al., 2000; Brandenburg et al., 2002). Glutamine feedback-inhibited GS also serves as a chaperone for the transcriptional repressor, GLNR, resulting in the repression of N starvation responses (Schreier et al., 1989; Nakano and Kimura, 1991; Commichau and Stülke, 2008; Wray and Fisher, 2008). Thus, the B. subtilis GS serves as not only the primary assimilating enzyme but also as a detector of intracellular N status for modulating both the repressor- and activator-type transcription factors for tight regulation of N starvation responses. Recently, eukaryotic GSs have also been implicated in controlling transcriptional responses from studies in the fungi Fusarium and the plant Medicago trunculata (Wagner et al., 2013; Silva et al., 2015; Brauer et al., 2020). The GS superfamily has three subclasses (type I, II, and III) which vary in distribution across the domains of life where type I and type II are the 19 predominant forms in prokaryotes and eukaryotes, respectively (Kumada et al., 1993; Reyes and Florencio, 1994; Silva et al., 2015). The type II GS enzymes in photosynthetic eukaryotes are further subdivided into GS1 (cytosol) and GS2 (plastid). Studies in Fusarium type II GSs were able to separate GS catalytic function from the transcriptional regulation of NCR genes with site-directed mutagenesis, showing for the first time that eukaryotic GS enzymes can catalyze the formation of glutamine while serving a dual role as a regulatory enzyme (Wagner et al., 2013). In addition to the predominant type II GS, photosynthetic eukaryotes commonly possess a type I GS gene that is homologous to the prokaryotic GSs for which enzymatic activity assays to date have found no catalytic properties. The type I GSs of Medicago trunculata show expression patterns that are associated with lateral root growth and root nodule emergence in response to N status and were therefore suggested to have a role in N detection/signaling (Silva et al., 2015). Beyond the prokaryotic type I GSs in plants, there is often redundancy in the type II GS cytosolic isoforms (GS1). Thus the diverse GS1s could hypothetically have a secondary role as N detecting/signaling enzymes similar to the type II GS found in Fusarium (Swarbreck et al., 2011; Thomsen et al., 2014). Plant GS1 isoforms differ in their spatial/temporal expression such that the different isoforms might serve as N status detection systems unique to the N demands of different organs during development such as seed filling or the remobilization of N during senescence and diurnal cycles (Lothier et al., 2011; Guan et al., 2015; Konishi et al., 2018; Ji et al., 2019). 1.5 Chlamydomonas arginine-fed cultures as a putative N starvation model system My thesis considers a critical strategy towards exposing the central N status signal transduction in photosynthetic eukaryotes, which is the establishment of repressive and derepressive N sources comparable to those facilitating the discovery and characterization of PII and TOR, in prokaryotes and fungi, respectively. A common scheme of N status detection in prokaryotes and fungi is the utilization of the GS/GOGAT cycle intermediates as proxies for N status. Prokaryotes and fungi rapidly upregulate N scavenging/salvage genes following the onset of N starvation, a response shared in photosynthetic eukaryotes suggesting a comparable signaling mechanism that responds to changes in N status. The major N sources used by photosynthetic eukaryotes, NH4+ and NO3-, are known repressors of N starvation-inducible genes. However, establishing derepressive conditions is particularly challenging, because photosynthetic eukaryotes typically cannot subsist on a wide array of organic N sources as can prokaryotes and fungi. Additionally, the remobilization of N through a multicellular organism makes it difficult to assess the N status of an individual cell and therefore cellular responses to N starvation. 20 C. reinhardtii, has been used as a model organism to study N assimilation in photosynthetic eukaryotes in part owing to the ability to study the regulation of gene expression and protein activities in a clonal population of cells that are readily subject to a new nutrient condition (Galván et al., 2006; Salomé and Merchant, 2019). In addition, C. reinhardtii and plants share a high degree of sequence similarity in the genes encoding major N assimilation machinery and therefore discoveries in C. reinhardtii are potentially applicable to plants (Galván et al., 2006; Schmollinger et al., 2014; Park et al., 2015). Physiological responses to N starvation have been studied in C. reinhardtii for decades and can be used as reliable proxies for identifying derepressive N sources. These physiological responses include the transition to sexually competent gametes (gametogenesis), decreases in photosynthetic proteins, ribosome turnover, and the accumulation of C storage molecules (starch and triacylglycerols) (Sager, 1954; Siersma and Chiang, 1971; Martin and Goodenough, 1975; Bulté and Wollman, 1992; Weers and Gulati, 1997). C. reinhardtii has already served as an invaluable model organism for the regulation of macronutrient metabolism in photosynthetic eukaryotes (N, phosphorus, potassium, calcium, sulfur, magnesium, C, oxygen, and hydrogen). The discovery of the central regulator of phosphorus assimilation in C. reinhardtii was used to find homologs in A. thaliana (Wykoff et al., 1999; Rubio et al., 2001). Photosynthetic C fixation has been extensively studied in C. reinhardtii owing to its ability to survive using exogenous organic C sources allowing for the study of otherwise lethal photosynthetic mutants (Rochaix, 2002; Salomé and Merchant, 2019). C. reinhardtii has also been used to investigate the tolerance mechanisms to anoxia (Terashima et al., 2010; Catalanotti et al., 2012, 2013; Noth et al., 2013; Subramanian et al., 2014). More crucial to the study of N responses, it is known that C. reinhardtii can sustain growth on a wider variety of inorganic and organic N sources than most plants, including simple NH4+ and amino acids to complex nucleic acids and their derivatives (Sager and Granick, 1953; Cain, 1965). Of particular interest, arginine is known to have its own specific transporter(s) for uptake and can be directly incorporated into multiple possible metabolic pathways (Sussenbach and Strijkert, 1969, 1970; Kirk and Kirk, 1978). Studies of arginine-fed C. reinhardtii cultures showed that the N starvation response gametogenesis was induced, a response rapidly suppressed by NH4+ and NO3- (Honeycutt and Margulies, 1972; Matsuda et al., 1992; Pozuelo et al., 2000). The failure to repress a N starvation response like gametogenesis is the hallmark of a derepressive N source. Thus, arginine-feeding provides an ideal condition in C. reinhardtii for making breakthroughs in photosynthetic eukaryote N status signaling. 21 1.6 Research questions, objectives, and biological significance My thesis research has four objectives: to identify a derepressive N source in C. reinhardtii whereby growth does not suffer and N starvation responses are not fully repressed (Chapter 3), to elucidate the regulatory networks unique to N status through comparison of the derepressive N source with N starvation (Chapter 4), and to identify and characterize N status regulatory mutants that are unable to respond to N starvation (Chapters 5 and 6), . My thesis work found that utilizing arginine as the sole N source derepressed N starvation responses without a significant negative impact to growth. The derepressive arginine-fed growth allowed for the identification of mutants with defective regulation of N scavenging/salvage. This led to the discovery of Glutamine synthetase 4 (GLN4) as an essential regulator of N status that if disrupted results in a complete loss of N starvation gene regulation and gametogenesis. The establishment and successful implementation of a derepressive N source in a photosynthetic eukaryote will facilitate future inquiries into N status regulation and enabled a breakthrough necessary for unraveling the regulatory networks that respond to cellular N status. Additionally, novel mutants unique to NH4+-mediated repression of N starvation gene regulation were discovered. Future research delineating whether N starvation induction and NH4+-mediated repression operate within the same or separate pathways will be made possible by the availability of a suite of mutants discovered by my thesis work. 22 Chapter 2: Materials and methods 2.1 Strains and culture conditions Chlamydomonas reinhardtii wild-type strain, 137c (CC-125: nit1; nit2; mt+) and the mutant strains CC-3352 (far1; rsp3; NIT1pro::RSP3) and CC-350 (nic7; mt-) were obtained from the Chlamydomonas Center (https://www.chlamycollection.org/). All strains were maintained in Tris-acetate-phosphate (TAP) medium (Gorman & Levine, 1965) containing 8 mM NH4+ chloride (NH4Cl). Acetate was omitted for all autotrophic and heterotrophic growth experiments. All strains were cultured under low light (30 μmol m−2 s−1) at 23°C unless otherwise stated. 2.2 Selection of N limitation marker genes N starvation marker genes were collected representing N scavenging (ex. DUR3A, NRT2.1, and LAO1) and N salvage (ex. AIH2, AMT4, and GLN3), which were previously shown to be upregulated between 100 and 1000-fold within two hours of N starvation with stably low basal expression (Schmollinger et al., 2014; Table 2.1). Three expression patterns distinguish N starvation marker genes: 1) Continue expression once induced early in N starvation, 2) Transient expression going back to basal expression within two hours of N starvation, and 3) Also induced by NO3- in a NIT2-dependent manner. I selected two or three genes from each category that displayed the most robust upregulation under N starvation in the available transcriptome sets (Table 2.1). 2.3 Photosynthetic parameter measurements of cell stress and cytochrome b6f degradation Cells were grown on 8 mM NH4+-TAP plates for three days under low light (30 μmol m−2 s−1) and 1 - 2 x 107 cells were resuspended in 1 mL of NF-TAP. The cells were washed twice with 1 mL of NF-TAP and centrifuge spins at 3,000 RPM for 3 min. The cells were then resuspended in 150 µL of NF-TAP, moved to a 96-well plate, and replica plated onto selection medium agar plates. Thirty mutant strains were replica plated alongside six control strains in a randomly generated order. The replica plates were incubated under low light (30 μmol m−2 s−1) or high light (150 μmol m−2 s−1) for 48 hours. In vivo chlorophyll fluorescence of replica plated strains was measured with a JTS-10 spectrophotometer (Bio-Logic Science Instruments, France) and recorded with a CCD camera (C9300-221, Hamamatsu, Japan) with the lid removed from the agar plate (Johnson et al., 2009). Samples were incubated in dark for 10 min prior to fluorescence measurements. Maximum quantum efficiency of PSII photochemistry (Fv / Fm) and PSII operating 23 Table 2.1 – Details of selected N starvation marker genes analyzed in this study. Transcriptome data of mixotrophic cultures is from Schmollinger et al., (2014), which is also available on www.phytozome.net. 24 Efficiency (Fq’ / Fm’; ΦPSII) were calculated as Fm - Fo / Fm and Fm–‘ - F / Fm’, respectively (Baker, 2008). 2.4 Reverse transcription quantitative PCR (RT-qPCR) Liquid precultures (100 mL) of NH4+ or arginine TAP were inoculated to a concentration of 2 x 105 cells mL−1 and grown to mid-log phase (2 - 8 x 106 cells mL−1). Fresh cultures (100 mL) of the same media type were inoculated again to a concentration of 2 x 105 cells mL−1 using the mid-log phase precultured cells acclimated to either NH4+ or arginine. At mid-log phase the cultures were harvested at 3,000 rpm for 3 min and washed twice with 50 mL N-free TAP. Washed cells were added to 25 mL of arginine, NH4+, or N-free TAP in a petri dish to a final concentration of 2 x 106 cells mL−1 and incubated for 2 hours or 24 hours. RNA extraction and RT-qPCR were performed as previously described (Joo et al., 2017). All qPCR experiments were normalized to the endogenous reference gene CBLP (aka RCK1) which has been commonly used for normalization in C. reinhardtii, including long-term N starvation (Allen et al., 2007; Tsai et al., 2014). Samples were run in duplicate for three biological replicates and one tech replicate was run on a gel to confirm one single band of the correct length. Primer sequences and amplicon lengths are presented in Table 2.1. 2.5 Measurement of gametogenesis and gamete dedifferentiation To determine whether mutant strains were capable of inducing gametogenesis, cells were grown on 8 mM NH4+-TAP plates for ten days under low light (30 μmol m−2 s−1) and 1 - 2 x 107 cells were resuspended in 1 mL of NF-TAP alongside the high mating efficiency plus strain, CC-125. Mating activity was observed by mixing 1 x 107 cells of the tester strain with an equal cell number of each mutant after six hours in NF-TAP in a 24-well plate. The 24-well plate with the cell mixtures were incubated under low light and the presence or absence of pellicles was determined after 24 h. To determine whether mutant strains were capable of dedifferentiating from gametes to vegetative cells, cells were grown on 8 mM NH4+-TAP plates for ten days under low light (30 μmol m−2 s−1). Next, 1 x 107 cells were resuspended in 1 mL of NF-TAP alongside the high mating efficiency plus strain, CC-125, and a mutant library parent control strain. Mating activity was observed after six hours in NF-TAP by mixing the tester strain with an equal cell number of each mutant. Each mutant strain alongside a mutant library parent control strain was then harvested by centrifugation at 3,000 RPM for 3 min and resuspended in 1 mL of 8 mM NH4+-TAP. After three 25 hours, the mating activity was assessed again by mixing the tester strain with an equal cell number of each mutant. 2.6 Random insertional mutagenesis The glass bead method (Kindle, 1990) was used to randomly insert a linearized NIC7 plasmid driven by a constitutive promoter (proRR::NIC7) followed by selection of successful transformants growing in the presence of acetyl pyrimidine (AP), a toxic nicotinamide analog lethal to nic7-null mutants. The N-starvation reporter line in a nit2-null; nic7-null background was grown to mid-log phase in 100 mL of TAP liquid media supplemented with 0.75 µg / mL of nicotinamide. The cells were then harvested at 3,000 RPM for 3 minutes and resuspended in 10 mL of gametolysin and incubated under low light (30 μmol m−2 s−1) for 30 – 60 minutes until the cell wall was lysed. Ten µL were fixed with 4% glutaraldehyde and counted using a hemocytometer. An additional ten µL were treated with 1% NP40 to assess whether the cell wall was effectively lysed by gamteolysin. The 1% NP40 treated cells were counted with a hemocytometer and compared to the 4% glutaraldehyde treated cell count with the expectation that effective gametolysin cell wall lysis will result in >90% of the cells bursting when treated with 1% NP40. If the gametolysin treatment effectively removed the cell wall, then the cells were harvested at 3,000 RPM for 3 minutes and resuspended in 300 µL of TAP media for every additional 108 cells present after the first 108 cells. A 300 µL aliquot of cells were then added to 100 µL polyethylene glycol (PEG) with 1 µg of linearized proRR::NIC7 plasmid added. The PEG, plasmid, cells mixture was then added to 0.25 g of 0.5 mm washed, glass beads in a 13 x 100 mm culture tube with a cap and vortexed for 25 seconds. Four mL of TAP media was then immediately added, pulsed twice with the vortex, and poured into a 15 mL centrifuge tube leaving all glass beads in the 13 x 100 mm culture tube. The cells remaining in the 13 x 100 mm culture tube were washed with six more mL of TAP and combined with the first four mL of transformed cells. The process was repeated with 300 µL aliquots at a time until the last 300 µL which was repeated the same as above but omitting the linearized proRR::NIC7 plasmid to serve as a negative control for spontaneous nic7-null revertants. All sets were completed within 30 minutes and then harvested at 3,000 RPM for 3 minutes and resuspended in 10 mL of TAP media to remove the PEG. The cultures were then again harvested at 3,000 RPM for 3 minutes followed by resuspension in 300 µL of TAP medium. Three mL of melted 0.5% TAP agar cooled to <60 °C was added and the culture was spread evenly onto TAP agar plates supplemented with 10 µL / L of AP. Successful transformants growing on the TAP + AP plates were picked after 10 – 14 days 26 and moved to fresh TAP plates for 7 – 10 days before being screened for aberrant NIT1pro::PF14 reporter activity. 2.7 Screening for mutants with aberrant regulation of N starvation marker genes Successful transformants were grown on TAP plates for 3 days and then a small toothpick scrape of cells was resuspended in 150 µL of normal NH4+-TAP and 150 µL of NF-TAP in a 96-well plate and incubated under low light overnight. The following day, cultures were examined under a dissecting scope for swimming. Wild-type regulation of the NIT1 promoter conferred swimming in NF-TAP cultures but not NH4+-TAP cultures. Transformants displaying no swimming in either culture were collected and renamed non-swimmers (ns) whereas transformants that were swimming in both cultures were collected and renamed constitutive swimmers (cs). The ns mutants may not swim because of mutations in flagellum synthesis rather than mutations in the regulation of the NIT1 promoter therefore all ns mutants were examined under the stereo microscope for the presence of fully formed flagellum. The collected ns and cs mutants were screened for the uptake/assimilation of toxic analogs to common N sources as a proxy for upregulation of N starvation marker genes in NH4+ or arginine-fed cultures. Assessment of uptake/assimilation of toxic N analogs was measured using the photosynthetic parameter measurements of cell stress described above. The two toxic analog conditions tested were L-Arginine 2.5 mM + 0.1 mM Methylammonium TAP and 1 mM NH4+ + 10 mM Chlorate TAP. All ns and cs mutants were screened and those without significant alterations in the uptake/assimilation of toxic N analogs were removed. Three biological replicates were tested for mutants with significantly altered uptake/assimilation of toxic N analogs. The mutants collected were single colony isolated and two colonies were retested to confirm defective regulation of uptake/assimilation of toxic N analogs. Expression profiling of N starvation marker genes with qPCR was subsequently analyzed in the selected mutants. 2.8 Phylogenetic analysis 220 sequences for 116 organisms were obtained from accession numbers provided in Ghoshroy et al., 2010 or from NCBI BLASTp searches using C. reinhardtii sequences for GLN1 (canonical eukaryotic GSIIE), GLN2 (canonical eukaryotic bacterial GSIIB), or GLN4. Additionally, newly sequenced algal genomes not available from NCBI were searched using BLASTp. All the sequences used in the phylogenetic analysis were aligned with ClustalO (Sievers et al., 2011). A phylogenetic reconstruction was performed using Bayesian (MrBayes; Ronquist et al., 2012) and Maximum-likelihood (PhyML, RaxML, and IQ-TREE; Guindon et al., 2010; Rokas, 2011; Minh et 27 al., 2013) methods. IQ-TREE yielded a strongly supported consensus with Ultrafast bootstrap test score using the ‘-bb 1000’ option and rooting the tree with the Eubacterial GSIIB sequence from Cytophaga hutchinsonii. The LG+R5 model was chosen according to Bayesian Information Criteria (Luo et al., 2010). Shimodaira-Hasegawa-like and Bayesian approximate likelihood-ratio tests were performed by IQ-TREE with ‘-alrt 1000’ and ‘abayes’ options (Anisimova et al., 2011). A score of 95% in Ultrafast bootstrap and 80% in Shalrt was considered highly significant recommended by the software authors. 2.9 Construction of the GLN4 protein model Homology-based protein models were created for cytosolic A. thaliana GLN1.1 and C. reinhardtii GLN4 based on homology to the Zea mays crystal structure with bound ligands (SMLT ID: 2d3a.1) on the SWISS-MODEL site (https://swissmodel.expasy.org/interactive) (Unno et al., 2006; Waterhouse et al., 2018). The protein models were then matched with a Clustal Omega alignment of full-length sequences of GLN4 homologs and GLN1 homologs using ESPRIPT3.0 (Sievers et al., 2011; Robert and Gouet, 2014). 2.10 RNA-seq sample preparation and analysis Chlamydomonas reinhardtii gln4-null strains (B55_5-3 and B66_11-2) and gln4 complemented strains (B66_19-3 and B66_20-3) from Chapter 5 were maintained in TAP medium (Gorman & Levine, 1965) containing 8 mM NH4+ chloride (NH4Cl). All strains were cultured under low light (30 μmol m−2 s−1) at 23°C unless otherwise stated. Liquid precultures (100 mL) of NH4+ TAP were inoculated to a concentration of 2 x 105 cells mL−1 and grown to mid-log phase (5 x 106 cells mL−1). Fresh cultures (100 mL) of the same media type were inoculated again to a concentration of 2 x 105 cells mL−1 using the mid-log phase precultured cells acclimated to either NH4+ or arginine. At mid-log phase the cultures were harvested at 3,000 rpm for 3 minutes and washed twice with 50 mL N-free TAP. Washed cells were added to 25 mL of Arg (2 mM), NH4+, or N-free TAP in a petri dish to a final concentration of 2 x 106 cells mL−1 and incubated for 2 hours (NH4+ or N-free) or 24 hours (Arg). RNA extraction was performed as previously described (Joo et al., 2017). RNA quality and concentrations were assessed using an Agilent 2100 Bioanalyzer (Agilent Technologies, USA) and cDNA libraries were assembled and sequenced on an Illumina Hiseq 4000 platform. The raw sequences were quality-filtered by and mapped to the reference genome Chlamydomonas reinhardtii v5.5 using TopHat2. I used DESeq2 for differential expression analysis of the RNA-seq reads using a p-adjust < 0.05 as the threshold (Love et al., 2014). 28 The variability between replicates is modeled by the dispersion parameter whose accurate estimation is critical to the accuracy of differential expression analysis. Smaller sample sizes such as those used here (n = 2) result in highly variable dispersion estimates for each gene. This is resolved within DESeq2 through individual gene-wise dispersion estimates that are shrunken towards the average dispersion estimate for genes of a similar length. The dispersion plots from the DESeq2 analysis of each pairwise condition (ARG or NF2 compared to NH4+) show that the majority of shrunken estimates (blue dots) closely associate with the mean curve (red line) suggesting that the variance between samples is acceptably low and downstream analysis of differential expression is reliable (Figure 2.1). Lastly, short genes can result in false positives for differential expression because a few extra reads mapping to these genes by chance in one condition versus another will appear as strong fold changes in expression between conditions. In the DESeq2 package, I performed shrinkage of the log fold changes whereby genes with large fold changes and high read counts were used to establish a prior distribution and shrink the fold changes of genes with low read counts (Figure 2.2). It is expected that differentially expressed genes (DEGs) are equally likely to be up- or downregulated. To confirm there was no bias towards up- or downregulated DEGs, volcano plots for each condition (ARG or NF2 compared to NH4+) were visualized and demonstrated a roughly even distribution of significantly up- and downregulated genes (Figure 2.3). 2.11 Selection of light sensitive mutants Cells were grown for three days on TAP plates under low light (30 μmol m−2 s−1) and then a large scoop (~1e7 cells) was resuspended in TP (without acetate added) and washed twice. The cells were resuspended in 100 uL of TP and replica plated onto four fresh TP plates in a random order alongside two controls; the mutant lib parent and CC-1690. One plate was placed in each of four light intensities; DL = dim light (5 μmol m−2 s−1), LL = low light (30 μmol m−2 s−1), HL = high light (150 μmol m−2 s−1), and VHL = very high light (250 μmol m−2 s−1). After 48 hours, the plates were assessed for Fv / Fm and strains that deviated from the control strains were selected and retested for three repetitions. The selected mutants were sorted into groups based on observed patterns of light sensitivity by unsupervised k-means clustering with the averaged Fv / Fm values normalized to the mutant library parent. Strong outliers with either substantially less or more cell stress than the mutant library parent were removed and placed into two groups prior to the clustering analysis. 29 Figure 4.2 – The within-group variability (dispersion) for RNA-seq replicates is low and fits tightly with the trendline. The dispersion estimates (black dots) for each gene is obtained by considering each gene separately. The red trend line shows the gene dispersions’ dependence on the mean. The gene dispersion estimates are shrunken towards the red line (blue points) and used for the downstream analysis. The blue points above the main set of points indicate genes with high-gene dispersion estimates and are not shrunk toward the trend line (Love et al., 2014). The low abundance of outliers suggests the within-condition variability is low. Dispersion plots of NF (A) and Arg (B) DESeq2 analysis compared with NH4+ are presented. A B 30 Figure 4.3 – Shrinkage of the log2 fold changes found between ARG and NF2 samples relative to AMM-I reduces the impact of low read counts per gene. Plots of NF (A) and Arg (B) log2 fold changes relative to the mean normalized counts for each gene prior to log fold change shrinkage relative to plots following shrinkage NF (C) and Arg (D). A B C D 31 Figure 4.4 – Volcano plots show that significantly differentially expressed genes are distributed evenly between up- and downregulated genes for ARG and NF2 samples relative to AMM-I. All genes within the DESeq2 analysis of NF (A) and Arg (B) transcriptomes relative to NH4+ were plotted with the -log10 adjusted p-value relative to the log2 fold change. Genes with expression levels significantly different (adjusted p-value < 0.05) when grown of NF or Arg relative to NH4+ are colored teal while those not significantly different are colored in red. A B 32 Chapter 3: Arginine-fed cultures derepress nitrogen starvation responses during robust growth in C. reinhardtii 3.1 Introduction Recent interest in the N starvation responses of microalgae stem from their position as a promising feedstock for biofuels and other valuable bio-compounds compared to traditional crop systems (Antizar-Ladislao and Turrion-Gomez, 2008). The usual protocol to stimulate lipid accumulation in microalgae is by way of nutrient limitation, most commonly nitrogen (N) (Hu et al., 2008; Wang et al., 2009). However, N starvation-induced lipid production is accompanied by a strong decrease in overall biomass since N is essential for growth, impeding the goal of economical microalgal lipid cultivation. Therefore, establishment of derepressive conditions that are unable to repress N starvation responses like TAG production during N-replete growth is demanded for microalgae to become an economically viable biofuel crop. N limitation responses are presumably triggered by signaling mechanisms that detect external and internal N availability. Transcriptional/proteomic changes stimulated by N starvation in C. reinhardtii have been intensively studied and have shown the rapid induction of genes including those for N scavenging and salvage, suggesting that N from purines and amino acids is actively remobilized while searching for alternative external N sources (Schmollinger et al., 2014; Wase et al., 2014; Park et al., 2015). N limitation also downregulates genes encoding proteins needed for photosynthesis including the majority that encode antenna and photosystem proteins (39 out of 42 genes in Miller et al., 2010) while upregulating key genes encoding proteins involved in fatty acid and lipid biosynthesis (Boyle et al., 2012). The differentiation of vegetative cells into sexually active gamete cells is known as gametogenesis and is a response unique to N starvation. The removal of any single component other than N from the growth medium does not elicit gametogenesis, and cultures produce <1% sexually competent gametes when the preferred N sources, NH4+ or NO3-, are present (Sager and Granick, 1953; Matsuda et al., 1992; Pozuelo et al., 2000). Interestingly, arginine is the only N source reported to allow gamete production while retaining a growth rate comparable to NH4+ or NO3- (Honeycutt and Margulies, 1972; Matsuda et al., 1992). These studies suggest that the occurrence of gametogenesis in arginine-grown populations is not due to a lack of N but rather to the lack of a repressive gametogenesis signal such as NH4+. C. reinhardtii can grow on various N sources ranging from simple NH4+ and amino acids to complex nucleic acids and their derivatives (Sager and Granick, 1953). Muñoz-Blanco et al., 33 (1990) reported that twelve amino acids can serve as the sole N source for C. reinhardtii growth but in all but one case these amino acids undergo extracellular deamination via a L-amino acid oxidase encoded by LAO1, releasing NH4+ which then enters the cell. Arginine, the exception, is reported to enter the cells by a specific active transporter system (Kirk and Kirk, 1978) whose molecular identity has been proposed but not determined experimentally (Vallon and Spalding, 2009). With the goal of discovering a derepressive N source growth condition that can improve the lipid yields in photosynthetic microorganisms, I report in this chapter the comparison of arginine-fed cultures to NH4+-fed and N-starved cultures. I examined the physiological and molecular responses of two lab strains of C. reinhardtii, differing in their NO3--assimilation capability, and a diatom, Phaeodactylum tricornutum, to test the applicability of arginine-fed cultures outside of chlorophytes. To test whether arginine-fed cultures affect N starvation responses in any trophic conditions, I made the comparison of arginine-fed cultures to other cultures in mixotrophic conditions (Sections 3.2.1 - 3.2.3) or in phototrophic conditions (Section 3.2.4). My examination across trophic conditions, however, does not intend to make a direct comparison between the trophic conditions. I document that arginine-fed cultures exhibit multiple N starvation-induced responses, including the accumulation of lipid droplets, without compromising growth and photosynthesis. My results indicate that derepressive conditions inducing significant lipid production in N-replete conditions is possible and could lead to economically feasible microalgal lipid production when combined with other methods such as genetically engineered high lipid yield strains. Additionally, the establishment of arginine as a derepressive N source in C. reinhardtii allows for the dissection of N starvation regulation in growing cultures that may be extended to other photosynthetic eukaryotes. 3.2 Results and Discussion 3.2.1 Arginine-fed mixotrophic cultures undergo gametogenesis and show reduced chlorophyll content during normal growth. Previous reports documenting gametogenesis in arginine-fed mixotrophic cultures characterized the 137c strain which is defective in NO3- assimilation (Honeycutt and Margulies, 1972; Matsuda et al., 1992). To test whether the gametogenesis induced in arginine-fed mixotrophic cultures depends on the 137c genetic background, I characterized two strains, 21gr (CC-1690: NIT1; NIT2) and 137c (CC-125: nit1; nit2), where NIT1 encodes NO3- reductase (Fernández and Matagne, 1984) and NIT2 encodes the transcription factor regulating 34 NO3- assimilation genes (Fernández and Matagne, 1986). In both 21gr and 137c about ~10% of the population were gametes in arginine-fed cultures in contrast to little or no gametes in NH4+-fed cultures (Table 3.1a). I extended the query to four natural isolates of C. reinhardtii whose genomes contain ~2 - 3% difference at the nucleotide level with the laboratory strains such as 21gr and 137c (Flowers et al., 2015). Arginine-fed mixotrophic cultures of the natural strains exhibited 5 - 35% of gametes (Table 3.1a), indicating that arginine-fed culture induces gametogenesis in diverse genetic backgrounds of C. reinhardtii. To test whether inefficient utilization of arginine causes weak growth and consequently induces gametogenesis, I examined growth curves measured as optical density at 720 nm of arginine-fed and NH4+-fed mixotrophic cultures using a photobioreactor (Figure 3.1a). The doubling time calculated from the growth curves was increased by 7 – 10%, not significantly, in the arginine-fed cultures compared to the NH4+-fed cultures during the logarithmic phase (Table 3.2a). At stationary phase, manual cell counts showed that arginine-fed mixotrophic cultures had a significantly higher maximal cell density at 1.97 ± 0.19 x 107 cells per mL for 21gr and a comparable maximal cell density at 1.35 ± 0.13 x 107 cells per mL for 137c relative to NH4+-fed mixotrophic cultures, indicating no growth impairment of the arginine-fed mixotrophic cultures (Table 3.2a; Figure 3.1a). These results suggest that constitutive gametogenesis in arginine-fed mixotrophic cultures is unlikely to be caused by actual N limitation in the cells. 3.2.2 N starvation-induced genes are upregulated in arginine-fed mixotrophic cultures. One of the early responses to N starvation is the rapid upregulation of N catabolism genes within 0.5 – 2 hours (Schmollinger et al., 2014). To ask whether this response occurs in growing arginine-fed mixotrophic cultures, I analyzed the expression levels of eight N starvation marker genes involved in N scavenging and N salvaging (Table 2.1). All were upregulated between 10- to >1,000-fold after NH4+-fed cultures were transferred to N-free medium for two hours (Figure 3.2a, N-free of NH4+-fed cultures), and a comparable upregulation was observed when transferred to arginine-fed medium (Figure 3.2a, Arg of NH4+-fed culture). The upregulated expression remained high for all marker genes in 21gr after 24 hours in arginine-fed medium, whereas in 137c, AIH2, DUR3A, LAO1 showed some reduction but were still 8- to 125-fold higher than the levels in NH4+-fed mixotrophic cultures, while FDX2 and NRT2.1 expression fell to the levels in NH4+-fed mixotrophic cultures (Figure 3.2a, Arg-24hr of NH4+-fed culture). The reduced 24-hour expression of AIH2 and DUR3A in arginine-fed medium is concordant with their previously reported transient upregulation within two hours of N starvation and reduced expression in the subsequent hours (Schmollinger et al., 2014; Table 2.1). 35 Table 3.1. C. reinhardtii cells acclimated to arginine media exhibit N starvation-induced responses without stress symptoms. (a) Gametogenesis frequency(%) Strains NH4+ Arginine N-free 21gr 0.2 ± 0.5 16.5 ± 5.6 87.5 ± 7.1 137c 0.2 ± 0.4 11.1 ± 2.5 81.7 ± 7.0 CC-2344 0.0 ± 0.0 5.9 ± 1.0 58.6 ± 2.5 CC-2290 0.9 ± 0.1 37.5 ± 0.8 88.3 ± 1.1 CC-2932 0.0 ± 0.0 12.4 ± 1.3 64.1 ± 5.8 CC-2931 0.0 ± 0.0 20.8 ± 4.6 78.1 ± 2.9 (b-c) Photosynthesis-related characteristics 21gr 137c NH4+ Arginine NH4+ Arginine (b) Mixotrophic culture Fv / Fm 0.75 ± 0.02 0.76 ± 0.01 0.74 ± 0.02 0.73 ± 0.01 ΦPSII 0.51 ± 0.10 0.57 ± 0.06 0.57 ± 0.01 0.55 ± 0.04 Chl a/b 2.35 ± 0.18 2.78 ± 0.22 2.65 ± 0.06 2.83 ± 0.05* Total Chl 3.47 ± 0.50 1.18 ± 0.46* 2.64 ± 0.40 1.78 ± 0.06 (nmol/106 cells) (c) Phototrophic cultures Fv / Fm 0.50 ± 0.06 0.58 ± 0.01 0.56 ± 0.05 0.64 ± 0.03 ΦPSII 0.32 ± 0.05 0.39 ± 0.01 0.37 ± 0.06 0.45 ± 0.04 Chl a/b 2.61 ± 0.12 2.71 ± 0.10 2.94 ± 0.13 2.81 ± 0.07 Total Chl 2.28 ± 0.07 2.56 ± 0.37 2.50 ± 0.33 2.11 ± 0.57 Mating efficiency was used to measure gametogenesis frequency, determined by the percentage of cells fused with tester gametes. Data represents the mean ± the standard deviation from three biological replicates, except for field-isolated strains examined by single experiment with two replicates. (b-c) Properties of C. reinhardtii cells acclimated to different N sources. Cells from mid-logarithmic mixotrophic (b) or phototrophic (c) cultures used to determine the Fv / Fm, ΦPSII at 210 mole photons m-2 s-1, chlorophyll a/b ratio, and total chlorophyll. Values shown are means ± standard deviation (n = 2). Significance is indicated with an asterisk and was calculated by a Student’s t-test (p < 0.05). Chl, chlorophyll. 36 Figure 3.1 – Arginine-fed cultures show comparable growth rates in mixotrophic conditions but reduced rates in phototrophic conditions relative to NH4+-fed cultures. Growth curves of 21gr and 137c cultures in mixotrophic conditions (a) or in phototrophic conditions (b), measured as optical density at 720 nm on a log2 scale. Solid and dashed lines indicate NH4+ and arginine-fed cultures, respectively. Error bars indicate the standard deviation from two or more independent experiments. 37 Table 3.2. C. reinhardtii arginine-fed cultures grow slower than NH4+-fed cultures but show higher final cell densities. 21gr 137c NH4+ Arginine NH4+ Arginine (a) Mixotrophic cultures Growth rate (µ) 0.084 ± 0.005 0.079 ± 0.009 0.118 ± 0.012 0.108 ± 0.020 Doubling time (h) 8.24 ± 0.55 8.82 ± 0.99 5.93 ± 0.64 6.54 ± 1.12 Stationary density (107 cells/mL) 1.24 ± 0.12 1.97 ± 0.19* 1.48 ± 0.21 1.35 ± 0.13 (b) Phototrophic cultures Growth rate (µ) 0.115 ± 0.008 0.049 ± 0.010* 0.112 ± 0.004 0.059 ± 0.005* Doubling time (h) 6.03 ± 0.39 14.36 ± 2.50* 6.31 ± 1.06 11.86 ± 1.01* Stationary density (107 cells/mL) 1.88 ± 0.19 6.00 ± 0.23* 0.51 ± 0.03 3.53 ± 0.35* The growth rate (µ) and doubling times were calculated during ten hours of linear growth of the logarithmic phase in mixotrophic (a) and phototrophic (b) cultures (initial concentration of 8 mM for each N source). Values are means ± standard deviation (n = 3). A significant difference of cells grown on arginine compared to NH4+ is indicated with an asterisk and was calculated by a Student’s t-test (p < 0.05). 38 Figure 3.2 – Arginine-grown cells constitutively upregulate N starvation marker genes. Expression of target transcripts relative to NH4+ condition. NH4+-fed (closed bars; 8 mM initial conc.) or arginine-fed (open bars; 8 mM initial conc.) cultures of 21gr and 137c strains grown in mixotrophic condition (a) or in phototrophic condition (b) were harvested at mid-logarithmic phase and incubated in NH4+, N-free (NF), arginine (Arg) medium for two hours or arginine medium for twenty-four hours (Arg-24h, only for mixotrophic cultures). Data represent the mean ± the standard deviation from three biological replicates. Letters above error bars indicate a significant difference within each strain relative to NH4+ (a), NF (b), or Arg 2hr (c) data points using a pairwise hierarchical ANOVA with p < 0.05 (n = 3). 39 To minimize the effects of putative acclimation responses to the change in N source, I examined arginine-fed mixotrophic cultures pre-acclimated to the arginine medium for at least two growth cycles from logarithmic to stationary phase. The logarithmic arginine-fed mixotrophic cultures of arginine-acclimated cells showed a significant 27- to >1,200-fold upregulation of AMT4, GLN3, LAO1, NIT1, and NRT2.1 and 3.5- to >500-fold upregulation of DUR3A, FDX2, AIH2, compared to NH4+-fed cultures (Figure 3.2a, Arg of arginine-fed culture). When these arginine-acclimated cells were transferred to N-free medium, they exhibited only a modest 1.33- to 11-fold upregulation in all marker genes but DUR3A, whose expression was reduced close to the level in NH4+-fed culture (Figure 3.2a, N-free of arginine-fed culture). I also examined whether the observed N starvation responses of the arginine-fed mixotrophic cultures are due to excess arginine in the media above the minimally required concentration (2 mM) and observed comparable upregulation of N starvation target genes between the cultures with 2 mM and 8 mM arginine (data not shown). Together, these results suggest that the same gene regulatory mechanism triggered by N starvation becomes activated during arginine-fed mixotrophic growth regardless of the genetic difference between 21gr and 137c. N starvation responses are generally considered to be a stress response. I therefore asked whether an arginine-fed mixotrophic growth invokes additional cellular stress that may in turn activate N starvation responses. To assess the physiological stress of arginine-fed cultures, chlorophyll a fluorescence parameters that are known to fluctuate upon cellular stress were analyzed (Baker, 2008). The maximum quantum yield of PSII (Fv / Fm) and the photosynthetic efficiency (ΦPSII at 210 μmol photons m− 2 s− 1) in arginine-fed mixotrophic cultures were not significantly different from those in NH4+-fed mixotrophic cultures (Table 3.1b). The chlorophyll a/b ratio as an indicator of antenna size was found to be marginally higher in arginine-fed mixotrophic cultures, significantly so for 137c but not for 21gr. On the contrary, arginine-fed mixotrophic cultures showed a substantial reduction in the cellular chlorophyll content, down 34% - 66% of the levels found in NH4+-fed mixotrophic cultures and visibly evident as pale green cultures at the logarithmic phase (Table 3.1b; Figure 3.3a). Taken together, I consider that the decreases in chlorophyll are unlikely a consequence of severe stress which would have been observed as a drop in the Fv / Fm below 0.7 (Baker, 2008). It awaits further study whether the low chlorophyll content results from a downregulation of chlorophyll biosynthesis genes triggered by a N starvation signal or a redirection of N metabolic flow away from chlorophyll biosynthesis in arginine-fed mixotrophic cultures. 40 Figure 3.3 – Arginine-grown cells exhibit N starvation phenotypes. (a) Pale green logarithmic culture indicates reduced cellular chlorophyll content. Photographs of NH4+- or arginine-fed 21gr and 137c mixotrophic cultures (initial conc. of 8 mM for each) were taken at their early logarithmic phase after being adjusted to 2 x 106 cells per mL. (b-c) Nile red staining reveals increased neutral lipid biosynthesis in cells grown with arginine. Micrographs of Nile red stained mid-logarithmic phase cells from NH4+ or arginine-fed cultures (initial conc. of 8 mM for each) of 21gr, 137c, and sta6 grown either mixotrophically (b) or phototrophically (c) alongside cells starved of N for 3 days captured using a 100x objective. The starchless mutant, sta6 was used as a high lipid accumulating control line. Scale bar represents 5 µm. 41 3.2.3 Mixotrophic arginine-grown cells increase the flux of organic C towards storage. Lipid accumulation in response to N starvation is well documented (Hu et al., 2008; Wang et al., 2009); however, it is not known whether N starvation stimulates lipid body biogenesis directly or indirectly due to cell cycle arrest and/or generic stress responses. Lipid droplets were present in logarithmic arginine-fed mixotrophic cultures with more pronounced accumulation in 137c (Figure 3.3b). The relative size and number of lipid droplets found in the arginine-fed cultures were less than those observed in cells starved of N for three days. Strain specific differences in lipid droplet formation could be due to differences in C flux towards starch biosynthesis that also increases during N starvation (Siaut et al., 2011). To quantitatively assess the C flux into storage molecules without diversion into starch biosynthesis, Dr. Sang Jun Sim’s lab in Korea examined the starchless mutant, sta6, that shunts all storage C to lipids without apparent changes in TAG biosynthesis pathways (Ball et al., 1991; Fan et al., 2011; Li et al., 2010). The large number and size of lipid droplets in arginine-fed mixotrophically grown sta6 cells attests to an increased C flux toward lipid storage molecules (Figure 3.3b, sta6). In arginine-fed mixotrophic cultures, the total fatty acid (FA) content per cell was 18% and 60% higher than the level in the NH4+-fed mixotrophically grown cells for 21gr and sta6, respectively (Table 3.3a). The TAG content per cell also increased 27% and 317% from the level in NH4+-fed culture (Table 3.3b). For sta6, TAGs accounted for 28% of the cellular FA content in the arginine-fed mixotrophically grown cells, more than 2-fold greater than the NH4+-fed mixotrophically grown cells (13%). The arginine-fed mixotrophically grown 21gr cells, however, showed no significant enrichment of TAG, suggesting a diversified C flux in wild-type cells. This result suggests that increased FA biosynthesis occurs in arginine-fed mixotrophic cultures, as reported for N-starved cells (Moellering and Benning, 2010). Increased incorporation of FAs into TAG during N starvation can have two explanations: de novo synthesis and the recycling of membrane lipids (Boyle et al., 2012; Fan et al., 2011; Liu et al., 2013; Moellering and Benning, 2010; Siaut et al., 2011). To investigate the sources of the increased FAs in arginine-fed cultures, Dr. Sang Jun Sim’s lab in Korea analyzed the relative quantity of FA profiles distinguishing saturated and monounsaturated FAs, representing newly synthesized fatty acids, and polyunsaturated FAs (PUFAs) such as C16:4, C18:3, and C18:4, representing typical forms of membrane lipids (Ohlrogge and Browse, 1995). The FA profiles of total lipids within arginine-fed mixotrophic cultures of 21gr and sta6 were significantly different from those of NH4+-fed mixotrophic cultures, showing an increase in C16:0 and C18:111 ( indicating the position of the double bond counting from the carboxyl end) and a decrease in C16:4, which was comparable to the FA profiles of N-starved cultures except an increase of 42 Table 3.3. FA profiles suggest de novo synthesis as a primary route for the increased FAs in arginine-fed cultures. 21gr sta6 NH4+ Arginine N-free NH4+ Arginine N-free a. Total lipids Total amount (g per 106 cells) 3.92 ± 0.07 4.62 ± 0.04* 11.32 ± 0.34* 3.26 ± 0.04 5.21 ± 0.04** 17.74 ± 0.01** C16:0 22.3 ± 0.6 22.0 ± 0.3 25.0 ± 0.7* 23.6 ± 0.4 27.2 ± 0.1* 30.4 ± 0.2* C16:1 2.8 ± 0.1 2.9 ± 0.0 0.2 ± 0.0* 2.6 ± 0.0 3.1 ± 0.0* 2.0 ± 0.0* C16:2 2.2 ± 0.0 1.8 ± 0.0** 1.1 ± 0.0** 2.7 ± 0.0 0.7 ± 0.0** 1.9 ± 0.0** C16:3 1.8 ± 0.1 3.3 ± 0.0* 2.9 ± 0.1 1.7 ± 0.0 4.0 ± 0.0* 1.6 ± 0.0 C16:4 14.8 ± 0.7 13.3 ± 0.3 11.4 ± 0.7* 14.4 ± 0.5 4.5 ± 0.1* 9.0 ± 0.3* C18:0 5.9 ± 0.1 4.4 ± 0.0* 3.6 ± 0.1** 5.9 ± 0.0 3.6 ± 0.0* 4.4 ± 0.0** C18:1Δ9 9.6 ± 0.2 7.8 ± 0.1* 9.3 ± 0.1 7.3 ± 0.0 18.6 ± 0.1** 5.4 ± 0.1** C18:1Δ11 2.6 ± 0.1 3.1 ± 0.0* 4.9 ± 0.0** 2.5 ± 0.0 5.2 ± 0.0** 8.1 ± 0.1** C18:2 5.4 ± 0.0 7.6 ± 0.1** 9.3 ± 0.0** 6.7 ± 0.0 15.4 ± 0.0** 8.9 ± 0.1* C18:3n6 4.7 ± 0.0 5.4 ± 0.0* 5.9 ± 0.0** 4.3 ± 0.1 4.2 ± 0.0 5.9 ± 0.0* C18:3n3 26.2 ± 0.0 25.8 ± 0.0* 24.4 ± 0.1* 26.0 ± 0.0 12.2 ± 0.0** 20.6 ± 0.0** C18:4 1.7 ± 0.1 2.6 ± 0.1* 1.9 ± 0.0 2.3 ± 0.0 1.2 ± 0.0* 1.8 ± 0.2 b. TAG fraction Total amount (g per 106 cells) 0.22 ± 0.01 0.28 ± 0.03 2.48 ± 0.03** 0.22 ± 0.01 0.91 ± 0.01** 7.13 ± 0.21** C16:0 51.0 ± 0.6 43.0 ± 1.8 33.2 ± 0.1* 46.1 ± 1.6 63.8 ± 0.6* 42.1 ± 1.0 C16:1 n.d. n.d. 3.4 ± 0.1 n.d. 0.9 ± 0.8 4.5 ± 0.1 C16:2 n.d. n.d. 2.1 ± 0.0 n.d. n.d. 0.9 ± 0.0 C16:3 n.d. n.d. 1.1 ± 0.1 n.d. n.d. 0.6 ± 0.0 C16:4 21.5 ± 0.0 16.6 ± 1.3 5.0 ± 0.6* 21.3 ± 0.8 5.7 ± 0.0* 3.1 ± 3.6 C18:0 11.2 ± 0.1 17.9 ± 1.4 5.3 ± 0.2* 13.8 ± 0.5 10.2 ± 0.1 6.3 ± 0.6 C18:1Δ9 16.2 ± 0.5 22.6 ± 0.9 8.9 ± 0.5** 18.8 ± 1.3 14.3 ± 0.1 27.5 ± 2.3* C18:1Δ11 n.d. n.d. 8.9 ± 0.9 n.d. n.d. 6.7 ± 0.2 C18:2 n.d. n.d. 7.9 ± 0.4 n.d. 3.7 ± 0.1 5.4 ± 0.5 C18:3n6 n.d. n.d. 4.8 ± 0.2 n.d. n.d. 1.0 ± 0.1 C18:3n3 n.d. n.d. 17.0 ± 0.5 n.d. 1.5 ± 0.1 1.6 ± 0.1 C18:4 n.d. n.d. 2.6 ± 0.5 n.d. n.d. 0.2 ± 0.0 PUFA (excluding C16:4) 21.5 ± 0.0 (0.0 ± 0.0) 16.6 ± 1.3 (0.0 ± 0.0) 40.5 ± 0.5* (35.4 ± 0.1) 21.3 ± 0.8 (0.0 ± 0.0) 10.9 ± 0.1* (5.2 ± 0.1***) 12.9 ± 2.9* (9.7 ± 0.7) Relative quantity (%) of FA profile in total lipid extracts (a) or in TAG fractions (b) was analyzed using gas chromatography of mixotrophic cultures of 21gr and sta6 grown to mid-logarithmic 43 phase using either NH4+ or arginine (initial conc. of 8 mM for each), alongside NH4+-grown cells starved of N for three days (N-free). FAME quantification of total lipids and TAG fractions is provided in the row (Total amount), expressed in g per 106 cells, above the FA profile data. Values are means ± standard deviation (%, n ≥ 2). Significant difference from NH4+ data is indicated with an asterisk (p < 0.05) or double asterisks (p < 0.01) and was calculated by a Student’s t-test.  indicating the position of the double bond counting from the carboxyl end and n indicating the position from the terminal methyl C. n.d., not detected; PUFA, polyunsaturated fatty acids; ***, significant difference from N-free data (p < 0.01). 44 C18:111 instead of C18:19 (Table 3.3a). The FA profiles of the TAG fraction showed that the increased cellular TAG content of the sta6 arginine-fed mixotrophic cultures was contributed primarily by a 574% increase in C16:0 and a >300% increase in C18:0 and C18:19, respectively as calculated by the proportion of each FA normalized to the total amount of TAGs. PUFA content of the TAG fraction showed a significant reduction in the sta6 arginine-fed mixotrophic culture from that of N-starved sta6 cells, and the reduction was 46% when excluding C16:4, the major FA of photosynthetic membranes (Giroud et al., 1988) (Table 3.3b). The low quantity of PUFAs indicates a minor flux of membrane lipid recycling into TAG biosynthesis in arginine-fed mixotrophic cultures. These results suggest that the increased TAG in arginine-fed mixotrophic culture depends on de novo FA synthesis. 3.2.4 N starvation responses are induced in arginine-fed phototrophic cultures. N starvation signaling presumably operates in all trophic states, whereas some N starvation responses may depend on the trophic state. To test whether the N starvation responses of arginine-fed cultures depend on the mixotrophic state, I also examined phototrophic cultures. AMT4, GLN3, and NIT1 were upregulated by 53- to >500-fold in arginine-fed phototrophic cultures compared to NH4+-fed phototrophic cultures in both 21gr and 137c (Figure 3.2b), which is comparable to the upregulation observed in the mixotrophic cultures. LAO1 was 33-fold upregulated in 137c but not in 21gr. Lipid droplets were present in arginine-fed phototrophic cultures of the 21gr strain, whereas they were few or absent in those of the 137c strain (Figure 3.3c). The absence or relatively low number of lipid droplets visible in the arginine-fed phototrophic cultures may by attributable to the positive effect that exogenous acetate has on C storage (Goodson et al., 2011). The growth rates of the arginine-fed phototrophic cultures were reduced by 47.5 – 55.5% compared to the NH4+-fed phototrophic cultures (Fig. 3.1b, Table 3.2b). However, the stationary phase culture density in arginine-fed phototrophic cultures was 3.2 to 6.9-fold higher as measured by manual cell counts and 1.5 to 2.4-fold higher as measured by OD (Table 3.3b). There was no significant difference between NH4+ and arginine phototrophic cultures in their chlorophyll a fluorescence parameters (Table 3.1c). The chlorophyll content of arginine-fed phototrophic cultures was comparable to that of NH4+-fed phototrophic cultures, in contrast to the ~50% decreased chlorophyll content in arginine-fed mixotrophic cultures. This difference may be due to the trophic state affecting chlorophyll metabolism as in N-starved cells (Terauchi et al., 2010; Msanne et al., 2012). Collectively, arginine-fed phototrophic cultures also showed N starvation 45 responses without any apparent defect in photosynthesis but accompanied by slow growth, the cause of which requires further study. Constitutive N starvation responses in phototrophic cultures is important for biofuel development because mixotrophic cultures are more prone to bacterial/fungal contamination than phototrophic cultures. The three to seven-fold increase in the final cell density recorded in the arginine-fed phototrophic cultures is of great interest towards the aim of improved biomass yield (Cheirsilp and Torpee, 2012). Whether higher cell density is associated to constitutive N starvation responses of cells or to any other arginine-specific effects warrants a further investigation. 3.2.5 Arginine-induced lipid accumulation occurs in the diatom Phaeodactylum. Arginase is a major enzyme for arginine catabolism in plants and algae; however, the C. reinhardtii genome lacks genes encoding this enzyme (Vallon and Spalding, 2009; Winter et al., 2015). To test whether arginine-fed cultures can elicit N starvation responses in photosynthetic organisms with arginase, Dr. Eonseon Jin’s lab in Korea examined a marine diatom, P. tricornutum, that can grow with arginine as the sole N source and expresses arginase (Allen et al., 2011; Fig. 3.4a). As in C. reinhardtii, pronounced lipid droplets were found in P. tricornutum when grown solely with arginine for seven days (Fig. 3.4b). A fluorescence-based semi-quantitative assay demonstrated a two- to seven-fold higher neutral lipid content during a seven-day growth period (Fig. 3.4c). Similar lipid accumulation suggests that the putative mechanism triggered by arginine-fed cultures may be conserved across diverse photosynthetic organisms. 46 Figure 3.4 – Arginine-fed cultures of P. tricornutum increase neutral lipid content during robust growth. (a) Culture proliferation measured by cell counting with a hemocytometer for cultures grown with arginine (closed circles) or NO3- as the sole N source (open circles) (initial conc. of 0.22 mM for arginine and 0.88 mM for NO3-. Data represent the mean and standard deviation from triplicate sampling in two independent experiments (n = 6). (b) Micrographs of Nile red stained cells from cultures grown for seven days with NO3- or arginine as the sole N source grown. Bar = 20 µm. (c) Semi-quantitative determination of total neutral lipid accumulation per 106 cells using a fluorescence-based assay comparing overall Nile red fluorescence between NO3- and arginine-fed cultures. Error bars are standard deviation from triplicate sampling in two independent experiments (n = 6). Significant differences between arginine and NO3- cultures were found in all the time points when calculated by a Student’s t-test (p < 0.05). A.U., arbitrary unit. 47 3.3 Conclusions Arginine-fed cultures of C. reinhardtii in mixotrophic and phototrophic conditions activate a suite of N catabolism genes together with N starvation-induced responses such as gametogenesis and TAG accumulation while supporting growth to a comparable or higher maximum density than NH4+-fed cultures. This finding firmly supports arginine as a derepressive N source in C. reinhardtii. Dr. Eonseon Jin’s lab in Korea documented a similar induction of TAG accumulation in arginine-fed cultures of a diatom, P. tricornutum (Fig. 3.4c). Hence, arginine feeding serves to derepress canonical N catabolism repression by NH4+ or NO3- and provides a fruitful approach to manipulate N starvation responses without growth arrest in microalgae concomitant with the goal of developing practical solutions to improve biodiesel productivity and quality. The study of N starvation responses in growing arginine-fed derepressive cultures is analogous to how major breakthroughs in N starvation signaling were accomplished with derepressive N sources in fungi and bacteria, respectively (Ninfa et al., 1995; Mitchell and Magasanik, 1984). Furthermore, the finding that NIT1 is regulated in a N starvation-dependent manner independent of the NO3--specific transcription factor NIT2 indicates that the established NIT1 promoter-reporter lines (Zhang and Lefebvre, 1997; González-Ballester et al., 2005) can be used to screen for regulatory mutants defective in N starvation-specific induction (Chapters 5 & 6). 48 Chapter 4: The transcriptome of arginine-fed cultures showed derepression of N starvation responses and identified putative routes of arginine assimilation 4.1 Introduction Microalgae have been sought after for their potential value as biofuel factories, particularly considering their high fatty acid, isoprenoid, and triacylglycerol (TAG) content on a per cell dry weight basis (Sheehan et al., 1998; Jones and Mayfield, 2012). While other algae are more suitable for the economical production of biofuel precursors, C. reinhardtii has become the most reliable model system due to the deep genetic toolbox available and, most importantly, the reputable annotated genome (Merchant et al., 2007; Salomé and Merchant, 2019). Using C. reinhardtii as a model system, a number of recent publications using -omics based approaches have explored genetic and physiological variables to learn about the connections between TAG production and central metabolism, exploring known mutants (i.e. starchless and acetate non-utilizing mutants), trophic statuses (hetero-, auto-, and mixotrophic), diurnal cycles, and stress-causing conditions including nutrient limitations (N, sulfur, phosphorus, oxygen, and iron) (Nguyen et al., 2008; Miller et al., 2010b; Boyle et al., 2012; Fang et al., 2012; Blaby et al., 2013; Hemschemeier et al., 2013; Goodenough et al., 2014; Schmollinger et al., 2014; Wase et al., 2014; Gargouri et al., 2015; Ngan et al., 2015; Park et al., 2015; Zones et al., 2015; Bajhaiya et al., 2016; Tsai et al., 2018; Hidayati et al., 2019; Strenkert et al., 2019) These -omics based approaches have revealed insights into the mechanisms that increase lipid biosynthesis during N starvation, leading to the identification of potential transcription regulators affecting lipid yield: P i starvation response 1 (PSR1) in the Myb family, N response regulator (NRR1) in the SQUAMOSA promoter-binding family, the TAR1 protein kinase, and Cre01.g011150 in the bHLH family (Boyle et al., 2012; Schmollinger et al., 2014; Kajikawa et al., 2015; Bajhaiya et al., 2016). While they likely play critical roles in coping with given stress conditions, none of these factors explain the whole-scale remodeling of the transcriptome triggered by N starvation, where approximately one third of genes were found to be differentially regulated. The work described in Chapter 3 demonstrated that arginine-fed cultures derepress N starvation-specific genes, which provides an excellent opportunity for the investigation into N starvation-specific regulation without the complications of the generic stress imposed in N-starved cultures. This chapter analyzed the transcriptomes of arginine-fed cultures in comparison to those 49 in N-replete and N-deplete cultures using the GLN4C strain (described in Chapter 5) for the following three aims. The first aim was to collect genes directly regulated by N starvation-triggered signaling. The genes that were commonly regulated in N-deplete and arginine-fed cultures compared to N-replete cultures were considered as putative N starvation-dependent genes. The second aim was to examine whether the genes for 1) N assimilation pathways and 2) the rerouting of C into starch and TAG accumulation are regulated by N starvation-specific signaling or generic stress signaling. In the third aim, genes that were uniquely upregulated in arginine-fed cultures were collected to predict the likely routes of arginine assimilation/catabolism in C. reinhardtii that are currently unknown. Lastly, I put forward a hypothesis for which N assimilation routes may be bypassed in arginine-fed cultures resulting in the failure to repress N starvation responses. 4.2 Results and Discussion 4.2.1 Differentially expressed genes strongly overlap between arginine-fed and nitrogen starved cultures. To characterize the similarities and differences in the transcriptional regulation between arginine-fed and N-starved cultures, RNA-seq reads were collected from three conditions in biological duplicates: AMM-I (NH4+-fed control), logarithmic NH4+-fed culture; NF2 (N-free for 2 hours), two hours after the transfer of logarithmic NH4+-fed culture to N-deplete medium; and ARG (arginine-fed), logarithmic arginine-fed culture. Following the mapping of reads (according to the v5.6 C. reinhardtii annotation; www.phytozome), the read counts per gene were used to analyze differential expression with DESeq2 (Love et al., 2014). The overall similarity among the six samples were compared using the Pearson’s correlation coefficient, which helped to assess whether the differences between samples were dictated by the N regime or by any confounding extraneous factors. The clustering of the two biological replicates was evident in the dendrogram generated from the Pearson’s correlation matrix (visualized in the heat maps of Figure 4.1a & b). 50 Figure 4.1 – Variance between transcriptomes is associated with culture conditions. The hierarchical clustering of sample distances provides an overview of similarities and dissimilarities between the arginine (A) and two-hour N starvation (B) samples used for DESeq2 differential expression analysis relative the NH4+ controls. A B 51 An overall comparison of the differentially expressed genes (DEGs, false discovery rate-adjusted p-values < 0.05) that were shared between the two conditions and those that were unique to each was made by filtering the DEGs from each DESeq2 analysis (ARG or NF2 compared to AMM-I) against one another. This comparison showed a strong overlap of DEGs between ARG and NF2 as well as >1000 DEGs unique to each condition (Figure 4.2). The DEGs unique to NF2 samples are hypothetically associated with stress responses caused by N source limitation, whereas DEGs unique to ARG samples are hypothetically enriched with genes involved in arginine metabolism. On the other hand, the DEGs shared between the conditions are hypothetically the direct targets of N starvation as generic stress responses caused by the lack of N resources in NF2 samples are not expected in the ARG samples. 4.2.2 Arginine-fed cultures upregulate N assimilation pathways in a manner consistent with N starvation. In Chapter 3, the upregulation of N starvation-specific responses in arginine-fed cultures were examined based on eight marker genes encoding proteins responsible for N assimilation. Therefore, it was prudent to assess whether the transcriptome data also indicated that arginine-fed cultures regulate N assimilation in the same manner as N-starved cells. Most N assimilation genes were significantly upregulated (34 out of 49) in the ARG sample relative to the AMM sample, which was comparable to the upregulation of the same genes in the NF2 sample relative to the AMM sample (28 out of 49) (Figure 4.3; Table 4.1). Notable differences between ARG and NF2 include the ARG-specific upregulation of plasma membrane transporters (DUR3A, DUR3C, NRT1.1, NAR1.3, and NRT2.4-5), a glutamate dehydrogenase (GDH1), a truncated hemoglobin (THB1), and arginine deiminase (ADI1). Lastly, the gene encoding the chloroplast NO2- transporter, NAR1.2, was not significantly upregulated in the ARG samples but was in the NF2 samples. NF2 samples were prepared after two hours of N starvation, whereas the ARG samples were maintained in arginine-fed conditions for more than two growth cycles. This difference may explain the increased expression in arginine-fed cultures of some plasma membrane transporters that were previously shown to have robust upregulation during long-term N starvation (Schmollinger et al., 2014). To compare the ARG transcriptome with long-term N starvation conditions, previously published transcriptome data collected from a 48-hour N starvation time course experiment, including an NH4+-fed control (AMM-II) sample and a 48-hour N-starved (NF48) sample, 52 Figure 4.2 – The arginine transcriptome shows strong overlap with the two-hour N starvation transcriptome in addition to greater total amount of DEGs. The DEGs identified in NF and Arg transcriptomes relative to NH4+ transcriptomes were filtered against one another to assess the extent of transcriptome level similarity. DEGs were identified using a p-adjusted threshold of < 0.05 in DESeq2. 1468 53 Table 4.1. N assimilation genes were upregulated in arginine-fed cultures as in N starvation. Bold face indicates ≥ 2 Log2 FC and underlines indicates ≤ -1 Log2 FC each with < 0.05 adj. p-value (n = 2). ARG NF2 NF48 Gene Phytozome v5.5 Log2 FC Adj. p-value Log2 FC Adj. p-value Log2 FC Adj. p-value (a) Ammonium assimilation AMT1 Cre03.g159254 6.37 4.73E-18 2.98 7.11E-06 9.84 5.53E-24 AMT3 Cre06.g293051 0.51 2.30E-01 0.56 2.00E-01 -1.6 1.18E-18 AMT4 Cre13.g569850 8.13 7.11E-53 7.25 2.51E-42 5.53 1.00E-42 AMT5 Cre09.g400750 3.09 1.40E-14 1.93 2.32E-08 4.28 3.25E-29 AMT6 Cre07.g355650 0.58 3.20E-01 0.45 5.20E-01 -3.5 1.34E-14 AMT7 Cre02.g111050 0.2 6.30E-01 -0.17 8.30E-01 -0.56 3.81E-03 AMT8 Cre12.g531000 3.97 1.24E-14 2.54 2.36E-09 3.16 1.08E-34 GDH1 Cre09.g388800 1.1 2.93E-02 0.62 3.94E-01 0.86 1.14E-04 GDH2 Cre05.g232150 -1.9 1.35E-09 -2.02 3.25E-07 -3.32 6.12E-153 GLN1 Cre02.g113200 0.75 1.10E-02 1.33 2.64E+00 1.26 5.34E-29 GLN2 Cre12.g530650 -0.17 7.50E-01 -0.22 6.13E-01 -0.19 1.32E-01 GLN3 Cre12.g530600 7.41 6.86E-73 5.6 8.05E-30 6.44 4.14E-72 GLN4 Cre03.g207250 1.17 1.34E-03 0.96 2.29E-02 -1.19 1.06E-23 GSF1 Cre12.g514050 0 9.73E-01 0.53 2.79E-01 0.77 1.86E-11 GSN1 Cre13.g592200 1.11 1.36E-03 1.04 7.83E-03 1.09 2.53E-17 (b) Nitrate/nitrite assimilation ARC1 Cre09.g389089 0.1 9.35E-01 0.27 6.97E-01 1.06 6.21E-05 NAR1.2 Cre06.g309000 2.96 3.54E+00 2.73 1.33E-04 2.9 6.19E-08 NAR1.3 Cre04.g217915 1.54 1.18E-04 0.27 5.39E-01 -2.83 8.10E-85 NAR1.4 Cre07.g335600 1.12 3.67E-03 1.74 2.52E-06 2.29 3.22E-25 NAR1.5 Cre12.g541250 -1.71 2.96E-06 -0.37 6.63E-01 -0.53 1.22E-02 NAR1.6 Cre01.g012050 0 2.22E-01 0 0.00E+00 2.16 1.51E-08 NAR2 Cre09.g410900 2.82 7.06E-06 3.08 9.43E-07 5.21 5.14E-26 NII1 Cre09.g410750 1.64 3.12E-06 4.51 1.22E-47 5.79 2.50E-107 NIT1 Cre09.g410950 0.15 1.53E-03 0.85 2.10E-03 4.04 4.55E-17 NRT1.1 Cre04.g224700 1.4 1.33E-03 0.4 5.62E-01 1.6 1.01E-12 NRT2.1 Cre09.g410850 2.14 3.28E-08 2.42 1.34E-08 4.62 2.20E-16 NRT2.2 Cre09.g410800 1.11 8.08E-05 0.96 3.25E-04 0 8.54E-01 NRT2.3 Cre09.g396000 0 1.00E+00 0 1.00E+00 0 7.41E-01 NRT2.4 Cre03.g150101 1.45 4.45E-05 0 9.53E-01 -3.27 8.00E-51 NRT2.5 Cre03.g150151 1.12 1.18E-03 0 7.99E-01 -4.39 1.71E-74 NRT2.6 Cre02.g110800 1.94 2.00E-07 2.12 3.41E-08 1.39 3.32E-13 THB1 Cre14.g615400 -3.07 6.56E-02 -3.07 2.84E-03 0 8.54E-01 Table 4.1 continued next page 54 Table 4.1. continued ARG NF2 NF48 Gene Phytozome v5.5 Log2 FC Adj. p-value Log2 FC Adj. p-value Log2 FC Adj. p-value (c) Organic N assimilation ADI1 Cre08.g360350 1.53 8.10E-04 -0.62 4.67E-01 -0.36 1.40E-01 DAL1 Cre13.g592050 -0.06 9.16E-01 0.12 8.86E-01 0.11 7.24E-01 DUR1 Cre08.g360050 2.21 5.04E-12 2.19 4.12E-10 4.51 9.10E-20 DUR2 Cre08.g360100 0.56 4.35E-02 1.97 1.47E-05 3.92 2.53E-20 DUR3A Cre08.g360200 2.42 1.25E-08 0 NA 5.53 1.22E-08 DUR3B Cre08.g360250 1.49 2.91E-05 0.97 2.81E-02 0.97 1.16E-06 DUR3C Cre17.g703800 1.13 5.62E-05 0 NA 2.54 7.36E-07 LAO1 Cre12.g551353 4.18 1.51E-09 3.33 2.66E-06 10.29 4.80E-12 LAO2 Cre12.g551350 2.36 7.16E-14 2.62 5.52E-15 5.1 9.68E-215 LAO3 Cre05.g246550 0.82 1.39E-01 -0.53 5.56E-01 2.35 4.92E-12 UAPA1 Cre10.g442800 4.14 1.32E-14 3.56 6.78E-12 7.36 1.00E-41 UAPA2 Cre10.g442600 2.66 1.55E-16 1.47 1.19E-05 4.13 1.13E-32 UAPA3 Cre10.g433200 0 NA 0 NA 1.57 4.20E-07 UAPA5 Cre10.g448450 0 NA 0 NA 8.97 4.66E-63 UAPA6 Cre06.g260700 6.03 2.61E-04 4.48 9.53E-03 7.05 1.00E-41 UOX1 Cre12.g504950 3.56 1.58854E-23 4.81 3.66E-46 2.66 7.25E-51 XDH1 Cre08.g360350 1.53 8.10E-04 -0.62 4.67E-01 -0.36 1.40E-01 (d) N assimilation regulators NRR1 Cre16.g673250 0.73 3.00E-01 1.32 2.48E-02 0.28 5.82E-01 NIT2 Cre03.g177700 0.93 1.42E-08 0.02 7.95E-05 3.51 5.71E-32 55 Figure 4.3 – N assimilation genes were upregulated in arginine comparable to two-hour N starvation expression profiles. Schematic representation of differential expression of mRNAs involved in N metabolism adapted from Schmollinger et al., 2014. The log2 fold change is represented by blue for increases and red for decreases in mRNA abundance when cells were either N starved or grown with arginine relative to NH4+. Only genes with changes in transcript that were significant adjusted p-values (p < 0.05) were colored (n = 2). Changes in mRNA abundance for arginine are outlined in purple (in front) and two-hour N starvation in black (in back). The localizations are based on either PredAlgo predictions (Tardif et al., 2012) or previous experimental evidence (Fernandez and Galvan, 2007; Harris, 2009). Boxes with dashed outlines are for unidentified proteins/genes in the Phytozome V5 annotation. 56 was re-analyzed using my DESeq2 pipeline (Schmollinger et al., 2014). In the NF48 transcriptome, the urea transporters (DUR3A-C), UAPA6, NRT1.1, and AMT1 were upregulated comparable to the ARG samples, whereas the other transporters, AMT3, AMT6, AMT7, NAR1.3, and NRT2.4-5 were significantly downregulated unique to the NF48 samples (Figure 4.4; Table 4.1). The AMT3, 6, and 7 genes are expressed during NH4+-replete conditions and their downregulation during N starvation was previously hypothesized to be related to their higher proportion of N containing amino acids relative to the other AMTs (Schmollinger et al., 2014). In contrast, the NAR1.3, and NRT2.4-5 genes were previously found to be differentially regulated across two different strains during N starvation (Schmollinger et al., 2014). Therefore, changes in NAR1.3, and NRT2.4-5 between my ARG and NF2 samples relative to the NF48 sample may represent a strain-specific difference (Schmollinger et al., 2014). Of the ARG-specific DEGs, ADI1 and GDH1 are of special interest due to their potential link to arginine metabolism (discussed further in Section 4.2.7). 4.2.3 Amino acid biosynthetic pathways are significantly downregulated except for arginine biosynthesis. To examine how the metabolism of amino acids is altered in ARG relative to NF, the regulation of genes encoding proteins for amino acid biosynthesis regarding the overall flow of N and C throughout the amino acid pool were analyzed. All amino acid biosynthesis pathways except for arginine/ornithine biosynthesis were significantly downregulated at one or more steps within a biosynthetic pathway in the ARG sample (Figure 4.5 and Figure 4.6; Table 4.2). The upregulation of genes encoding the arginine biosynthetic pathway during N starvation has previously been suggested as a mechanism for rapid N assimilation upon N resupply whereby N is temporarily stored as arginine (Schmollinger et al., 2014; Park et al., 2015). Further metabolite studies will be needed to address whether the free amino acid content is lower in arginine cells. The concerted downregulation of genes encoding amino acid biosynthetic enzymes in the ARG sample was likewise observed in the NF2 sample except for glycine biosynthesis via the glycolate pathway (genes 1-10; Figure 4.5; Table 4.2). The photorespiratory glycolate pathway in plants is found in the photosynthetic organs and is upregulated in response to active photosynthesis occurring during the daytime (Benstein et al., 2013; Toujani et al., 2013). Therefore, in the early N starvation NF2 samples that do not yet show decreases in chlorophyll content and photosynthesis, the lack of downregulation in the genes encoding enzymes of the glycolate pathway suggests that it is likewise regulated in response to photosynthesis in C. reinhardtii. 57 Figure 4.4 – N assimilation genes were upregulated in arginine comparable to 48-hour N starvation expression profiles. Schematic representation of differential expression of mRNAs involved in N metabolism adapted from Schmollinger et al., 2014. The log2 fold change is represented by blue for increases and red for decreases in mRNA abundance when cells were grown in NF or Arg relative to NH4+. Only genes with changes in transcript that were significant adjusted p-values (p < 0.05) were colored (n = 2). Changes in mRNA abundance for arginine are outlined in purple (in front) and two-hour N starvation in black (in back). The localizations are based on either PredAlgo predictions (Tardif et al., 2012) or previous experimental evidence (Fernandez and Galvan, 2007; Harris, 2009). Boxes with dashed outlines are for unidentified proteins/genes in the Phytozome V5 annotation. 58 Table 4.2. Most amino acid biosynthesis genes were downregulated in arginine-fed cultures as in N starvation. Bold face indicates ≥ 2 Log2 FC, underline indicates ≤ -1 Log2 FC. ARG NF2 NF48 Gene Phytozome v5.5 Log2 FC Adj. p-value Log2 FC Adj. p-value Log2 FC Adj. p-value (a) Glycine/Serine biosynthesis via glyoxylate 1 SHMT1 Cre16.g664550 -1.02 7.27E-04 -1.02 5.23E-03 -1.52 2.11E-30 2 SHMT2 Cre06.g293950 -2.07 2.08E-13 -2.42 1.15E-03 0.73 1.65E-09 3 SHMT3 Cre09.g411900 0.28 5.86E-01 0.03 9.67E-01 1.78 3.71E-30 4 AGT1 Cre06.g294650 -3.51 1.74E-29 -0.42 5.58E-01 -3.70 2.42E-119 5 AGT2 Cre03.g182800 -0.49 3.20E-01 2.56 2.49E-13 -1.74 2.40E-29 6 AGT3 Cre16.g650650 -0.87 1.59E-01 0.74 2.59E-01 1.41 2.17E-04 7 GYX1 Cre03.g171300 -0.23 7.99E-01 0.74 3.12E-01 1.18 5.44E-02 8 PGP1 Cre03.g168700 -1.08 5.52E-03 -0.38 5.86E-01 -0.88 9.58E-08 9 PGP2 Cre10.g438100 -0.20 6.81E-01 -0.13 8.43E-01 0.11 7.16E-01 10 PGP3 Cre06.g271400 0.09 9.43E-01 -0.01 9.84E-01 1.05 4.48E-02 (b) Serine biosynthesis via nonphotorespiratory pathways 11 SGA1 Cre01.g005150 -0.52 2.74E-01 0.84 1.47E-01 0.14 3.79E-01 12 HPR1 Cre06.g295450 -2.28 1.06E-06 -0.63 5.37E-01 -1.71 1.24E-15 13 GYK1 Cre12.g542300 -0.97 1.43E-02 -0.13 8.68E-01 1.27 3.47E-07 14 PGD1 Cre07.g344600 -1.85 1.04E-06 -1.59 1.43E-04 -0.01 9.88E-01 15 PGD3 Cre07.g344550 -1.44 1.87E-05 -1.14 1.52E-02 0.01 9.72E-01 16 PGD2 Cre07.g344400 -1.00 3.00E-03 -1.82 3.01E-04 0.88 9.51E-12 17 PST1 Cre07.g331550 0.11 7.53E-01 -0.23 6.56E-01 -0.12 4.07E-01 18 PSP1 Cre04.g217955 0.00 NA 0.00 NA 0.00 NA (c) Cysteine biosynthesis 19 SAT1 Cre10.g466750 -0.03 9.44E-01 -0.20 8.09E-01 -0.40 4.29E-02 20 SAT2 Cre17.g713850 -0.51 3.34E-01 -0.18 8.28E-01 -0.20 4.51E-01 21 SAT3 Cre10.g454150 0.31 5.68E-01 -1.11 5.35E-02 -0.28 2.25E-01 22 OASTL1 Cre08.g367600 0.30 5.37E-01 0.40 4.65E-01 0.40 2.91E-02 23 OASTL2 Cre16.g664250 -0.89 9.16E-02 -0.13 9.11E-01 -1.03 4.21E-02 24 OASTL3 Cre03.g172850 -0.13 8.19E-01 -0.57 3.23E-01 -0.21 3.14E-01 25 OASTL4 Cre16.g685550 0.06 9.32E-01 -1.13 2.59E-02 0.14 3.90E-01 (d) Methionine biosynthesis 26 CGS1 Cre03.g144627 -0.51 1.25E-01 -1.88 4.52E-08 -0.04 8.02E-01 27 MET1 Cre16.g669550 -0.06 9.18E-01 -0.49 4.30E-01 -0.45 1.64E-02 28 METE Cre03.g180750 -2.26 9.36E-18 -2.10 2.28E-01 -0.09 6.16E-01 29 METH2 Cre06.g250902 -1.13 1.01E-04 -1.23 5.42E-02 -0.01 9.44E-01 (e) Tryptophan biosynthesis 30 MAA7 Cre03.g161400 -0.57 1.22E-01 -0.94 1.18E-01 0.02 8.82E-01 31 TSA1 Cre12.g528700 -1.13 3.29E-03 -1.70 4.41E-03 -0.41 5.75E-02 32 IGS1 Cre13.g575800 -1.01 1.65E-01 -0.56 5.12E-01 0.50 3.15E-01 33 ASB2 Cre12.g519000 -2.37 1.15E-05 -2.89 7.28E-06 2.18 1.03E-03 34 PRT1 Cre10.g429150 -1.51 1.85E-04 -2.92 8.04E-09 -0.53 4.47E-02 35 ANS1 Cre06.g306601 -1.03 3.77E-03 -1.77 5.01E-03 0.28 9.76E-02 36 ASB1 Cre14.g620300 -0.64 1.30E-01 -1.82 1.05E-03 0.63 1.91E-03 Table 4.2 continued next page 59 Table 4.2. continued ARG NF2 NF48 Gene Phytozome v5.5 Log2 FC Adj. p-value Log2 FC Adj. p-value Log2 FC Adj. p-value (f) Chorismate biosynthesis 37 SHKA1 Cre17.g726750 -0.39 3.87E-01 0.19 7.71E-01 -0.11 4.50E-01 38 DHQS Cre08.g368950 0.14 7.46E-01 -0.93 2.01E-02 -0.35 2.85E-02 39 SHKD1 Cre08.g380201 -1.64 1.53E-04 -2.32 7.94E-04 0.04 9.37E-01 40 SHKF1 Cre10.g436350 -1.91 1.30E-06 -3.56 2.42E-11 -0.81 6.78E-03 41 SHKG1 Cre03.g181300 -0.61 8.47E-02 -0.29 6.46E-01 -0.69 2.64E-07 42 SHK7 Cre03.g145747 -1.23 1.13E-04 -3.34 7.85E+00 -0.82 5.79E-05 (g) Tyrosine, phenylalanine, and aspartate biosynthesis 43 CHM1 Cre03.g155200 -0.79 7.89E-02 -1.03 2.26E-02 1.19 8.27E-04 44 PRD1 Cre06.g261800 -2.02 2.21E-07 -2.24 3.22E-04 -1.21 3.09E-07 45 AST1 Cre09.g387726 -2.70 2.90E-17 -0.88 1.10E-01 -2.61 3.10E-72 46 AST2 Cre01.g051800 -0.09 9.43E-01 0.04 9.72E-01 1.29 6.30E-06 47 AST3 Cre02.g097900 -0.81 2.15E-02 0.80 2.39E-02 -1.31 3.59E-13 48 AST4 Cre06.g257950 -1.15 2.13E-04 -1.45 7.01E-03 1.25 1.02E-13 49 AST5 Cre06.g278249 -0.37 6.63E-01 -1.29 1.39E-01 2.51 3.90E-08 50 AGD1 Cre06.g278350 -1.20 7.09E-04 -1.38 8.46E-03 0.23 5.20E-01 (h) Alanine biosynthesis from pyruvate 51 AAT1 Cre10.g451950 -1.65 7.19E-09 -0.88 9.41E-02 -1.26 2.19E-17 52 AAT2 Cre06.g284700 -0.41 3.52E-01 -2.07 3.89E-04 -0.35 8.73E-02 (i) Threonine biosynthesis 53 THS1 Cre10.g451900 -1.05 2.74E-04 -3.34 6.80E-19 0.01 9.68E-01 (j) Isoleucine and valine biosynthesis 54 THD1 Cre02.g073200 -0.34 4.61E-01 -1.10 4.15E-03 -0.53 6.63E-03 55 ALSL1 Cre09.g386758 -0.30 5.35E-01 -0.39 5.93E-01 -0.81 2.31E-10 56 ALSS1 Cre01.g055453 -1.05 1.46E-03 -1.58 4.27E-04 -0.42 1.18E-02 57 AAI1 Cre10.g434750 -0.48 1.49E-01 -0.52 1.70E-01 -1.47 4.21E-34 58 AAD1 Cre03.g206600 -2.99 1.12E-03 -1.77 3.48E-01 -1.35 6.42E-26 59 BCA1 Cre02.g081400 -1.00 4.34E-02 -0.23 8.38E-01 0.92 2.91E-03 60 BCA2 Cre05.g245900 -1.54 1.72E-06 -2.48 3.28E-08 -0.42 4.17E-03 61 BCA3 Cre10.g458050 0.57 3.03E-01 2.39 8.24E-12 1.56 2.16E-06 (k) Methionine and threonine biosynthesis 62 HSK1 Cre02.g082200 0.24 8.49E-01 0.52 6.20E-01 -0.22 7.73E-01 63 HSD1 Cre02.g109550 -0.75 8.26E-02 -0.44 4.75E-01 0.66 4.05E-03 64 AHD1 Cre18.g749447 -0.34 4.48E-01 -0.96 7.96E-02 -0.79 4.34E-09 (l) Methionine, threonine, and lysine biosynthesis 65 ASD1 Cre09.g389689 -1.95 1.59E-11 -0.51 2.77E-01 -3.00 1.12E-131 66 ASK1 Cre10.g458500 -0.02 1.00E+00 -0.19 7.17E-01 -0.67 5.22E-07 (m) Lysine biosynthesis 67 DPS1 Cre02.g107300 -0.84 1.60E-02 -1.55 6.08E-07 -0.27 1.12E-01 68 DPR1 Cre16.g656300 -0.65 8.52E-02 0.38 4.01E-01 2.40 4.93E-28 69 DPA1 Cre17.g734200 -1.09 9.76E-03 -0.36 6.24E-01 -1.44 1.13E-27 70 DAE1 Cre05.g237400 -0.85 3.68E-02 -2.89 2.38E-16 1.56 1.18E-09 Table 4.2 continued next page 60 Table 4.2. continued ARG NF2 NF48 Gene Phytozome v5.5 Log2 FC Adj. p-value Log2 FC Adj. p-value Log2 FC Adj. p-value (n) Lysine biosynthesis (continued) 71 DPD1 Cre01.g050100 0.38 3.51E-01 0.13 8.42E-01 0.38 5.58E-03 (o) Valine biosynthesis 72 ALSL1 Cre09.g386758 -0.30 5.35E-01 -0.39 5.93E-01 -0.81 2.31E-10 73 ALSS1 Cre01.g055453 -1.05 1.46E-03 -1.58 4.27E-04 -0.42 1.18E-02 74 AAI1 Cre10.g434750 -0.48 1.49E-01 -0.52 1.70E-01 -1.47 4.21E-34 75 AAD1 Cre03.g206600 -2.99 1.12E-03 -1.77 3.48E-01 -1.35 6.42E-26 (p) Leucine biosynthesis from 2-ketoisovalarate 76 LEU2 Cre06.g258733 -1.71 4.73E-07 -1.03 1.22E-01 -0.83 7.07E-08 77 LEU1L Cre01.g004500 -0.94 5.89E-03 -0.40 4.84E-01 -0.52 5.04E-05 78 LEU1S Cre06.g252650 -1.47 1.15E-05 -2.02 3.52E-04 -1.25 9.76E-04 79 LEU3a Cre07.g325400 -1.13 1.94E-04 -0.37 4.56E-01 -1.71 2.67E-35 (q) Asparagine biosynthesis 80 ASNS Cre01.g004300 -1.24 1.35E-04 -1.03 8.78E-02 -1.33 2.53E-21 (r) Ammonium assimilation 81 GSN1 Cre13.g592200 1.11 1.36E-03 1.04 7.83E-03 1.09 2.53E-17 82 GSF1 Cre12.g514050 -0.01 9.73E-01 0.53 2.79E-01 0.77 1.86E-11 83 GLN1 Cre02.g113200 0.75 1.09E-02 1.33 2.64E-06 1.26 5.34E-29 84 GLN2 Cre12.g530650 -0.17 7.52E-01 -0.22 6.14E-01 -0.19 1.33E-01 85 GLN3 Cre12.g530600 7.41 6.86E-73 5.60 8.05E-30 6.44 4.14E-72 (s) Arginine biosynthesis 86 CMPL1 Cre08.g358580 1.03 2.47E-04 1.9 1.21E-10 1.27 5.60E-28 87 CMPS1 Cre06.g308500 1.47 8.01E-08 1.74 4.28E-09 1.57 9.91E-37 88 NAGS1 Cre16.g694850 0.02 9.64E-01 1.30 4.08E-04 -0.18 4.51E-01 89 LCI8 Cre02.g144800 0.83 1.31E-02 1.80 6.24E-09 0.36 3.17E-02 90 AGK1 Cre01.g015000 0.55 9.64E-02 1.45 3.91E-05 1.14 1.60E-14 91 ARG1 Cre03.g146187 0.77 2.02E-02 1.98 6.62E-11 1.59 2.49E-27 92 ARG9 Cre06.g278163 -0.21 6.79E-01 0.34 5.51E-01 0.95 3.21E-12 93 AOD1 Cre02.g105500 0.26 5.51E-01 0.98 1.20E-02 -0.62 1.46E-03 94 OTC1 Cre12.g489700 0.43 2.48E-01 1.29 2.15E-05 1.79 7.37E-26 95 AGS1 Cre09.g416050 1.27 6.24E-06 2.11 9.39E-14 1.04 7.31E-13 96 ARG7 Cre01.g021251 0.07 9.26E-01 1.43 6.12E-06 1.34 1.39E-13 (t) Proline biosynthesis 97 PROB1 Cre17.g705700 1.9 1.85E-06 0.00 6.73E-01 -2.00 9.69E-11 98 PROB2 Cre17.g705850 -1.37 2.48E-03 -1.67 1.35E-03 0.76 7.63E-03 99 GSD1 Cre03.g146527 -0.95 1.86E-02 -1.81 2.23E-04 -0.86 3.61E-07 100 PCR1 Cre03.g154550 -1.31 1.66E-04 -1.25 1.56E-03 1.94 8.21E-15 101 ALD1 Cre12.g520350 -0.73 1.31E-01 -1.23 5.52E-02 -0.03 9.64E-01 102 PDY1 Cre01.g036850 -0.12 8.10E-01 0.45 3.62E-01 -1.16 6.46E-11 103 PDY2 Cre16.g648350 -0.86 3.40E-02 -1.45 8.54E-04 -1.64 1.52E-29 104 OTA1 Cre11.g474800 2.11 2.22E-07 1.10 6.21E-02 1.22 4.24E-06 61 Figure 4.5 – Amino acid biosynthesis genes were significantly downregulated in all pathways except arginine biosynthesis relative to two-hour NF profiles. Adapted from Lea and Ireland, 1999. Representation of differential expression of mRNAs involved in amino acid metabolism. The log2 fold change is represented by blue for increases and red for decreases in mRNA abundance when cells were N starved or grown in arginine relative to NH4+. Only genes with changes in transcript that were significant adjusted p-values (p < 0.05) were colored (n = 2). Changes in mRNA abundance for arginine are outlined in purple (on the right) and two-hour N starvation in black (on the left). 62 Figure 4.6 – Amino acid biosynthesis genes were significantly downregulated in all pathways except arginine biosynthesis relative to 48-hour profiles. Adapted from Lea and Ireland, 1999. Representation of differential expression of mRNAs involved in amino acid metabolism. The log2 fold change is represented by blue for increases and red for decreases in mRNA abundance when cells were N starved or grown in arginine relative to NH4+. Only genes with changes in transcript that were significant adjusted p-values (p < 0.05) were colored (n = 2). Changes in mRNA abundance for arginine are outlined in purple (on the right) and 48-hour N starvation in black (on the left). 63 4.2.4 Cells grown with arginine significantly downregulate nuclear encoded photosynthetic apparatus genes. Arginine-fed cultures have significantly less chlorophyll content than NH4+-fed cultures without affecting the efficiency of PSII (ΦPSII) or the maximum efficiency of PSII (Fv / Fm) (Table 3.1 in Chapter 3). To investigate the impact of arginine-feeding on photosynthesis at the transcriptomic level, the expression of 134 genes related to photosynthesis in five categories were analyzed. Chlorophyll loss is minimal in the NF2 sample whereas the chlorophyll content per cell has reached its N starvation low point in the NF48 transcriptome, therefore, the ARG transcriptome can be compared to two contrasting levels of photosynthetic regulation. First, in the photosynthetic electron transport chain category, 47 of the 52 genes were significantly downregulated in the ARG sample in comparison to the AMM-I sample (Figure 4.7; Table 4.3). This compares to 46 genes significantly downregulated in the NF48 transcriptome, 43 of which were the same as in the ARG transcriptome. On the other hand, only 18 of the 52 photosynthetic electron transport chain genes were significantly downregulated in the NF2 transcriptome all of whom were also downregulated in the ARG sample. The level of downregulation was less severe on average (4-fold reduced) in the ARG over AMM-I comparison relative to the NF48 over AMM-II comparison (20-fold reduced). This suggests that these genes were significantly downregulated in the arginine-fed culture while maintaining the necessary expression for active photosynthesis. Taken together, it appears that the decrease in photosynthetic complexes of arginine-fed cultures results from transcriptional downregulation. Many of the genes that encode proteins necessary for the assembly of PSII, cytochrome b6f, and PSI were previously found to be upregulated during long-term N starvation conditions (Schmollinger et al., 2014). As such, I compared the genes encoding photosystem assembly-related proteins in the ARG samples relative to the NF samples as the second category of photosynthetic regulation. The ARG sample relative to the AMM-I sample was downregulated for the assembly genes for PSII (six out of seven genes) and cytochrome b6f (four out of ten genes) whereas those for PSI were relatively unchanged (one out of six genes is upregulated) (Table 4.4). Comparatively, the NF48 to AMM-II differential expression showed that half of the genes encoding proteins for the assembly of each complex were upregulated and only one or two genes were downregulated. These data led to the speculation that the long-term N starvation samples may be primed to re-assemble the photosynthetic electron transfer chain if the genes encoding the proteins for each complex are upregulated upon the resupply of N. 64 Table 4.3. Photosynthetic electron transport genes were downregulated in arginine-fed cultures. Bold face indicates ≥ 2 Log2 FC, underline indicates ≤ -1 Log2 FC each with < 0.05 adj. p-value (n = 2). ARG NF2 NF48 Gene Phytozome v5.5 Log2 FC Adj. p-value Log2 FC Adj. p-value Log2 FC Adj. p-value (a) Light harvesting complex II LHCB4 Cre17.g720250 -1.82 8.49E-12 -1.32 1.29E-03 -5.91 0.00E+00 LHCB5 Cre16.g673650 -1.96 1.67E-13 -1 1.97E-02 -8.46 0.00E+00 LHCB7 Cre02.g110750 -1.31 1.31E-03 0.17 8.17E-01 0.45 3.25E-01 LHCBM1 Cre01.g066917 -1.99 1.19E-11 -0.75 8.97E-02 -12.96 3.03E-301 LHCBM2 Cre12.g548400 -2.49 4.42E-18 -0.61 1.48E-01 -7.36 0.00E+00 LHCBM3 Cre04.g232104 -2.21 6.67E-14 -0.7 8.00E-02 -10.84 1.24E-86 LHCBM4 Cre06.g283950 -4.56 1.46E-45 -1.33 3.71E-04 -9.52 2.96E-32 LHCBM5 Cre03.g156900 -2.41 6.71E-20 -0.83 1.20E-02 -8.18 0.00E+00 LHCBM6 Cre06.g285250 -1.22 6.56E-06 -0.79 3.84E-02 -6.35 0.00E+00 LHCBM7 Cre12.g548950 -1.94 3.40E-10 -0.75 1.15E-01 -12.33 3.82E-65 LHCBM8 Cre06.g284250 -7.7 6.95E-61 -0.6 5.13E-01 -5.21 9.61E-19 LHCBM9 Cre06.g284200 0.41 7.29E-01 -0.47 2.19E-01 -1.89 9.22E-07 (b) Photosystem II PSBP1 Cre12.g550850 -2.06 3.81E-15 -1.33 1.40E-03 -5.27 0.00E+00 PSBPQ Cre08.g372450 -1.88 7.98E-11 -1.35 6.90E-04 -4 1.07E-220 PSBPO Cre09.g396213 -1.66 2.42E-09 -1.13 3.49E-03 -4.56 1.59E-300 PSBS Cre01.g016750 0 1.18E-01 0 NA 0 NA PSBX Cre02.g082750 -2.17 9.61E-14 -0.92 2.54E-02 -5.91 8.16E-195 PSBR Cre06.g261000 -1.05 6.95E-04 -0.89 2.72E-02 -2.65 5.26E-110 PSBY Cre10.g452100 -1.65 4.88E-08 -1.42 5.30E-05 -3.73 1.90E-170 PSB27 Cre05.g243800 -2.43 5.12E-18 -1.39 5.36E-04 -4.39 7.70E-169 PSB28 Cre10.g440450 -1.91 2.53E-10 -1.45 1.33E-05 -2.15 3.51E-32 PSBP1 Cre12.g550850 -2.06 3.81E-15 -1.33 1.40E-03 -5.27 0.00E+00 (c) Cytochrome b6f complex PETC Cre11.g467689 -1.81 1.33E-11 -0.14 7.85E-01 -2.63 1.62E-115 PETM Cre12.g546150 -2.29 1.14E-18 -0.18 7.49E-01 -2.58 4.00E-64 PETN Cre16.g650100 -2.14 5.41E-16 -0.49 2.04E-01 -3.4 2.20E-166 PETO Cre12.g558900 -1.96 1.03E-12 -1.21 3.43E-03 -2.57 8.70E-78 (d) Lumen photosynthetic components PCY1 Cre03.g182551 -1.94 5.38E-10 -0.81 5.08E-02 -6.07 0.00E+00 CYC6 Cre16.g651050 -4.71 3.42E-06 -2.87 4.17E-01 0 3.56E-01 Table 4.3 continued next page 65 Table 4.3. continued ARG NF2 NF48 Gene Phytozome v5.5 Log2 FC Adj. p-value Log2 FC Adj. p-value Log2 FC Adj. p-value (e) Photosystem I PSAD Cre05.g238332 -1.1 6.50E-04 -0.53 2.53E-01 -3.89 1.21E-235 PSAE Cre10.g420350 -1.71 2.37E-08 -0.45 3.80E-01 -5.74 0.00E+00 PSAF Cre09.g412100 -1.58 2.48E-08 -0.44 2.86E-01 -5.17 0.00E+00 PSAG Cre12.g560950 -1.85 1.81E-08 -0.76 1.09E-01 -7.84 0.00E+00 PSAH Cre07.g330250 -1.7 2.19E-07 -0.41 4.51E-01 -5.51 0.00E+00 PSAI Cre03.g165100 -1.44 8.51E-06 -0.57 2.93E-01 -4.5 1.56E-284 PSAK Cre17.g724300 -1.57 2.71E-06 -0.48 3.64E-01 -5.16 0.00E+00 PSAL Cre12.g486300 -1.53 7.37E-08 -0.54 1.92E-01 -4.94 0.00E+00 PSAN Cre02.g082500 -2.26 7.32E-14 -0.96 2.27E-02 -7.06 0.00E+00 PSAO Cre07.g334550 -2.19 1.30E-12 -0.67 1.17E-01 -7.5 0.00E+00 (f) Light harvesting complex I LHCA1 Cre06.g283050 -2.12 1.64E-12 -0.68 1.22E-01 -7.76 0.00E+00 LHCA2 Cre12.g508750 -1.21 1.35E-03 -0.19 8.52E-01 -7.22 0.00E+00 LHCA3 Cre11.g467573 -2.19 4.17E-16 -0.45 2.70E-01 -7.09 0.00E+00 LHCA4 Cre10.g452050 -2.16 1.17E-13 -0.93 3.64E-02 -7.88 0.00E+00 LHCA5 Cre10.g425900 -2.13 8.58E-16 -0.88 3.41E-02 -9.74 2.47E-258 LHCA6 Cre06.g278213 -2.07 3.08E-14 -0.7 9.60E-02 -9.65 6.93E-203 LHCA7 Cre16.g687900 -1.8 2.68E-10 -0.41 4.17E-01 -7.79 0.00E+00 LHCA8 Cre06.g272650 -1.86 8.03E-12 -0.48 2.69E-01 -7.03 0.00E+00 LHCA9 Cre07.g344950 -1.27 3.24E-05 -0.36 4.65E-01 -7.48 0.00E+00 (g) Chloroplast ATPase ATPC Cre06.g259900 -2.40 9.66E-18 -0.32 0.513 -2.40 3.77E-102 ATPD Cre11.g467569 -2.16 5.62E-16 -0.22 0.663 -2.36 1.61E-76 ATPG Cre11.g481450 -2.09 1.45E-15 -0.17 0.774 -2.25 5.50E-73 (h) Stromal photosynthetic components PETF Cre14.g626700 -0.40 3.08E-01 -2.54 3.79E-20 -3.59 1.61E-213 FDX2 Cre16.g658400 1.57 1.48E-01 0.39 7.25E-01 4.94 1.04E-22 FDX3 Cre06.g306350 -1.74 3.74E-04 -1.21 1.42E-03 0.72 8.66E-04 FDX4 Cre07.g334800 -4.16 1.90E-11 -1.49 4.11E-06 -0.50 2.99E-02 FDX5 Cre17.g700950 -0.40 6.06E-01 -4.29 2.54E-21 0.86 1.40E-01 FDX6 Cre03.g183850 -2.00 3.99E-04 -1.94 4.70E-07 -0.56 7.58E-02 66 Figure 4.7 – Photosynthesis genes were downregulated in arginine-fed cultures. Adapted from Schmollinger et al., 2014 in which the diagram is assembled schematically according to Eberhard et al., 2008 and Allen et al., 2011b. Chloroplast encoded genes are outlined in purple. Representation of differential expression of mRNAs involved in photosynthetic electron transport. The log2 fold change is represented by blue for increases and red for decreases in mRNA abundance when cells were N starved or grown in arginine relative to NH4+. Only genes with changes in transcript that were significant adjusted p-values (p < 0.05) were colored (n = 2). 67 Table 4.4. Genes encoding proteins for PSII and cytochrome b6f assembly were downregulated in ARG but upregulated in NF48 transcriptomes. Bold face indicates ≥ 2 Log2 FC, underline indicates ≤ -1 Log2 FC. ARG NF2 NF48 Gene Phytozome v5.5 Log2 FC Adj. p-value Log2 FC Adj. p-value Log2 FC Adj. p-value (a) PS-II assembly ALB3.1 Cre06.g251900 -3.05 8.22E-10 -2.75 3.98E-15 -1.06 2.53E-02 ALB3.2 Cre17.g729800 -0.43 3.89E-01 -1.2 7.84E-05 -1.06 1.24E-11 VIPP1 Cre13.g583550 -1.07 1.34E-02 -1.72 2.48E-08 0.36 2.06E-02 VIPP2 Cre11.g468050 -3.29 1.16E-07 -2.18 9.67E-11 0.97 4.13E-03 MBD1 Cre10.g456300 -0.83 7.46E-02 -0.64 1.83E-01 1.11 2.33E-05 MBB1 Cre09.g416200 -1.87 9.90E-05 -1.36 9.32E-04 1.73 3.09E-07 (b) Cytochrome b6f assembly MCA1 Cre08.g358250 -1.28 4.09E-04 -0.55 7.51E-02 1.49 2.96E-15 MCD1 Cre11.g476100 -0.84 2.28E-01 -0.56 5.15E-01 1.64 2.67E-07 TCA1 Cre09.g415500 0.21 7.58E-01 0.05 9.68E-01 1.53 7.06E-05 CCS1 Cre13.g575000 -3.64 1.43E-09 -1.67 1.56E-03 0.7 4.60E-02 CCA1 Cre07.g357800 -0.07 9.39E-01 -0.73 9.91E-02 1.46 5.87E-03 TRX20 Cre17.g702150 -0.89 3.68E-02 -0.69 7.70E-02 -0.31 2.12E-01 CCB1 Cre16.g662150 -2.3 5.82E-05 -1.37 1.15E-03 0.45 3.38E-01 CCB2 Cre12.g537850 -0.97 6.36E-02 -1.5 4.47E-04 -0.28 5.57E-01 CCB3 Cre01.g052400 -1.66 1.23E-03 -1.14 1.30E-02 -1.01 3.08E-03 CCB4 Cre08.g382300 -1.42 1.53E-02 -0.67 2.31E-01 0.38 3.85E-01 (c) PS-I assembly RAA1 Cre09.g394150 -1.08 7.04E-02 -0.14 7.43E-01 0.74 1.55E-02 RAA2 Cre16.g665750 1.56 2.36E-02 0.89 2.62E-01 3.24 1.40E-15 RAA3 Cre12.g531050 0 7.18E-01 0 9.44E-01 0.26 1.62E-03 RAA4 Cre09.g390060 -0.27 8.03E-01 -0.89 1.30E-01 0.97 6.40E-02 RAT1 Cre09.g388400 -1.33 1.04E-03 -0.63 1.67E-01 -0.58 4.24E-02 RAT2 Cre09.g388350 0 9.01E-01 1.35 6.24E-03 0.00 1.11E-01 68 Photosynthetic organisms can mitigate harm from the overreduction of the photosynthetic electron transport chain by several mechanisms that enable the non-photochemical quenching of incident light energy. One mechanism of non-photochemical quenching is to dissipate excess energy as heat by employing antenna proteins that display a shorter lifespan of excited energy state than those of typical light harvesting proteins (Niyogi, 1999). In C. reinhardtii, it has been proposed that the light harvesting complex stress response proteins, LHCSR1 and LHCSR3.1/2, mediate heat-releasing non-photochemical quenching (Peers et al., 2009). Therefore, as the third category, whether similar non-photochemical quenching mechanisms operate in arginine-fed samples was asked by examining the regulation of LHCSR1 and LHCSR3.1/2 and other genes encoding similar light harvesting complex-like (LHC-like) proteins. Five out of ten LHC-like genes were upregulated in the ARG and NF2 samples relative to the AMM-I sample, including LHCSR1 and LHCSR3.1/2 whereas two, LHL3 and ELI2, were downregulated (Table 4.5). This contrasts with the NF48 sample relative to the AMM-II sample where seven out of ten LHC-like genes were upregulated, including LHCSR3.1/2, and three were downregulated, including LHCSR1. These data suggest that energy-dependent quenching is important for arginine-fed cultures as during N starvation. In the case of arginine-feeding, this may help to prevent the overreduction of the photosynthetic transport chain and the accumulation of reactive species considering that arginine-fed cultures do not show signs of cell stress (Table 3.1; Chapter 3). Tetrapyrroles make up the active core of chlorophyll, therefore, I investigated the regulation of tetrapyrrole biosynthesis genes as the fourth category. The tetrapyrrole biosynthesis genes in the ARG sample were significantly downregulated ≥ 60% in 24 out of the 27 genes comparable to both NF samples, which is consistent with previous studies (Figure 4.8) (Schmollinger et al., 2014). Regarding chlorophyll degradation as the fifth photosynthetic category, three of thirteen orthologs to A. thaliana genes encoding proteins for chlorophyll degradation were significantly upregulated in ARG sample compared to nine out of thirteen upregulated in the NF48 sample (Hörtensteiner and Kräutler, 2011; Schmollinger et al., 2014). These data suggest that the reduced chlorophyll content in arginine-fed cultures is regulated by the reduction of tetrapyrrole synthesis at the level of gene expression, rather than increased protein degradation. 69 Table 4.5. Genes encoding for light harvesting complex-like proteins were upregulated in all transcriptomes. Bold face indicates ≥ 2 Log2 FC, underline indicates ≤ -1 Log2 FC each with < 0.05 adj. p-value. ARG NF2 NF48 Gene Phytozome v5.5 Log2 FC Adj. p-value Log2 FC Adj. p-value Log2 FC Adj. p-value (a) LHC-like OHP1 Cre06.g251150 0.08 8.97E-01 -0.55 1.77E-01 -1.05 8.09E-02 LHCSR1 Cre08.g365900 1.77 2.63E-02 1.79 2.86E-04 -0.96 1.64E-02 LHCSR3.1 Cre08.g367500 2.28 1.31E-02 3.59 4.15E-23 2.24 4.25E-06 LHCSR3.2 Cre08.g367400 2.14 2.80E-02 3.18 1.30E-15 2.53 2.00E-02 LHL3 Cre03.g199535 -3.02 2.37E-05 -1.97 2.64E-12 -0.98 3.02E-12 LHL4 Cre17.g740950 0.18 8.25E-01 0.20 7.14E-01 2.34 3.82E-20 ELI1 Cre16.g679250 -0.23 8.14E-01 -0.76 1.25E-01 1.60 2.54E-06 ELI2 Cre09.g393173 -2.05 5.20E-07 -1.95 1.62E-09 -2.01 9.24E-22 ELI3 Cre09.g394325 0.93 6.18E-02 2.85 3.29E-17 1.08 1.13E-11 ELI4 Cre02.g143550 1.43 2.89E-04 1.19 3.57E-04 1.73 3.75E-26 ELI5 Cre04.g211850 0.55 6.28E-01 0.21 8.88E-01 2.64 7.66E-08 70 Figure 4.8 – Arginine-fed cultures downregulate tetrapyrrole biosynthesis as in N-starved cultures. Adapted from Schmollinger et al., 2014. Representation of differential expression of mRNAs involved in tetrapyrrole biosynthesis. The log2 fold change is represented by blue for increases and red for decreases in mRNA abundance when cells were grown in NF or Arg relative to NH4+. Only genes with changes in transcript that were significant adjusted p-values (p < 0.05) were colored (n = 2). 71 4.2.5 The mitochondrial electron transport chain complex II is downregulated and alternative oxidation via AOX1 is upregulated in arginine-fed cultures During long-term N starvation, the cellular energy demand is reduced as N assimilation is no longer an energy sink and cellular growth/proliferation is ceased. Therefore, most of the genes encoding proteins for the mitochondrial electron transport chain (ETC) complexes were downregulated as observed in NF48; 18 out of 30 for Complex I, 3 out of 4 for Complex II, 8 out of 11 for Complex III, nine out of nineteen for Complex IV, and 18 out of 21 for ATPase (Table 4.6) (Schmollinger et al., 2014). In contrast, most of the genes encoding proteins of the electron carriers, ubiquinone and cytochrome c, are upregulated in the NF48 sample; six of eleven for ubiquinone and three of four for cytochrome c. Contrary to these findings, the ARG transcriptome only showed a downregulation in the genes encoding proteins for ETC-Complex II (three out of four genes), whereas genes encoding proteins for the other ETC-complexes and ETC-ATPase were, for the most part, not significantly downregulated. ETC-Complex II provides a parallel electron transport pathway to ETC-Complex I carried out by electrons delivered from the conversion of succinate to fumarate. In arginine-fed cultures, the levels are fumarate are likely increased during arginine catabolism (discussed in more detail in Section 4.2.7) which may result in feedback inhibition of the ETC-Complex II pathway. In addition to ETC-Complex II regulation, genes encoding proteins required for the cytochrome c electron carrier were downregulated in arginine rather than upregulated. This data would suggest that the transfer of electrons between ETC-Complex III and ETC-Complex IV is decreased in arginine-fed cultures. If the overall the electron flow between ETC-Complex III and ETC-Complex IV is decreased, it predicts that the proton gradient driving ATP production would also be decreased in arginine-fed cultures. In support of this hypothesis is the upregulation of the gene encoding alternative oxidase 1, AOX1, in the ARG sample whereas it is downregulated in the NF48 transcriptome and unchanged in the NF2 transcriptome. However, Schmollinger et al., 2014 found that AOX1 was upregulated in two of the three different strains tested suggesting that the upregulation of AOX1 may be a common feature of N starvation. The AOX proteins, of which C. reinhardtii has two (AOX1/2), bypass ETC-complexes III and IV in the mitochondria and reduce oxygen with less ATP production. Collectively, these results suggest that mitochondrial respiration through ETC-Complexes III and IV is decreased and that electron flow through AOX1 increases resulting in less mitochondrial ATP production in arginine-fed cultures. This regulation may be triggered in response to the reduction state of the photosynthetic electron transport chain. As with the LHCSR proteins (Table 4.5), AOX1 is known to be involved in high light survival by providing an outlet for dissipating excess energy (Kaye et al., 2019). The upregulation of AOX1 72 Table 4.6. Mitochondrial electron transport chain complex II was downregulated in arginine-fed cultures whereas alternative oxidase 1 was upregulated. Bold face indicates ≥ 2 Log2 FC, underline indicates ≤ -1 Log2 FC each with < 0.05 adj. p-value. ARG NF2 NF48 Gene Phytozome v5.5 Log2 FC Adj. p-value Log2 FC Adj. p-value Log2 FC Adj. p-value (a) Complex I ACP1 Cre16.g673109 -1.09 2.41E-03 -0.43 4.31E-01 -0.6 6.33E-05 CAG2 Cre06.g293850 -0.35 3.11E-01 0.19 6.72E-01 -0.32 5.98E-02 CAG3 Cre09.g415850 -0.5 1.97E-01 0.22 6.44E-01 -0.34 5.62E-02 CGL66 Cre09.g390467 0.32 5.78E-01 -0.48 4.68E-01 1.09 1.67E-11 NUO3 Cre08.g378900 -0.18 6.42E-01 0.28 5.07E-01 -0.25 1.64E-01 NUO5 Cre10.g450400 -0.04 9.19E-01 0.33 4.48E-01 -0.35 3.13E-02 NUO6 Cre10.g422600 -0.08 8.92E-01 0.26 5.52E-01 -0.35 2.34E-02 NUO7 Cre09.g405850 0.07 9.66E-01 0.17 7.17E-01 -0.48 5.96E-04 NUO8 Cre12.g496750 -0.23 6.57E-01 0.06 8.76E-01 -0.55 2.96E-04 NUO9 Cre07.g327400 -0.2 6.56E-01 0.15 7.86E-01 -0.14 4.25E-01 NUO10 Cre12.g492300 -0.44 2.83E-01 -0.08 9.21E-01 -0.28 1.43E-01 NUO11 Cre09.g402552 -0.4 3.20E-01 0.23 6.38E-01 -0.69 3.74E-05 NUO13 Cre11.g467767 -0.26 6.29E-01 -0.1 9.30E-01 -0.39 2.21E-02 NUO17 Cre05.g240800 -0.41 4.03E-01 0.16 7.26E-01 -0.02 9.85E-01 NUO21 Cre06.g267200 -0.3 5.88E-01 0.3 5.34E-01 -0.61 1.39E-03 NUOA1 Cre10.g459750 -0.12 8.47E-01 -0.07 9.66E-01 -0.53 3.31E-03 NUOA8 Cre07.g333900 -0.72 1.21E-01 0.01 9.50E-01 -0.68 3.55E-04 NUOA9 Cre10.g434450 0.01 9.93E-01 0.23 6.24E-01 -0.49 2.00E-03 NUOAF1 Cre02.g076750 -0.7 2.11E-01 0.35 5.91E-01 0.27 5.85E-01 NUOB8 Cre16.g679500 0.1 7.99E-01 0.55 2.25E-01 -0.19 1.99E-01 NUOB10 Cre12.g555150 -0.32 4.85E-01 0 9.53E-01 -0.4 3.65E-02 NUOB12 Cre05.g24485 NA NA NA NA NA NA NUOB13 Cre13.g568800 -0.35 3.89E-01 0.12 8.25E-01 0.14 4.55E-01 NUOB14 Cre12.g555250 -0.42 4.54E-01 0.07 8.66E-01 -0.42 1.32E-02 NUOB16 Cre16.g664600 -0.13 9.06E-01 0.17 7.00E-01 -0.5 1.86E-03 NUOB18 Cre06.g278188 -0.38 3.69E-01 0.15 8.03E-01 -0.49 1.18E-02 NUOB22 Cre11.g467668 -0.37 4.22E-01 0.3 5.21E-01 -0.35 9.68E-02 NUOP1 Cre13.g571150 -0.59 1.79E-01 -0.09 9.23E-01 -0.26 1.81E-01 NUOP3 Cre02.g100200 -0.46 2.91E-01 -0.11 8.83E-01 -0.54 3.90E-03 NUOP4 Cre08.g378550 -0.3 4.70E-01 0.19 6.93E-01 -0.03 8.36E-01 NUOP5 Cre08.g378050 -0.36 4.25E-01 0.18 7.28E-01 -0.13 5.04E-01 NUOS1 Cre12.g535950 -0.21 5.63E-01 0.24 5.60E-01 -0.09 6.31E-01 NUOS4 Cre03.g146247 0.28 4.57E-01 -0.11 8.87E-01 -0.35 4.22E-02 NUOS4b Cre16.g681700 -0.2 6.98E-01 0.32 6.48E-01 1.64 5.23E-03 Table 4.6 continued next page 73 Table 4.6. continued ARG NF2 NF48 Gene Phytozome v5.5 Log2 FC Adj. p-value Log2 FC Adj. p-value Log2 FC Adj. p-value (b) Complex I (continued) NUOS5 Cre12.g511200 -0.37 5.67E-01 0.01 9.42E-01 -0.1 6.85E-01 NUOS6 Cre03.g178250 -0.23 6.63E-01 -0.02 9.98E-01 0 9.39E-01 (b) Complex II SDH1 Cre14.g619133 -1.42 1.20E-05 -0.26 6.84E-01 -1.95 2.57E-48 SDH2 Cre06.g264200 -1.41 8.80E-06 -0.37 5.34E-01 -0.72 1.13E-07 SDH3 Cre01.g020350 -1.56 4.81E-08 -0.26 6.83E-01 -0.74 5.04E-06 SDH4 Cre01.g020300 NA NA NA NA NA NA (c) Complex III BCS1 Cre05.g234661 -1.7 4.41E-07 -2.81 2.34E-05 -0.63 8.78E-05 CBP3 Cre01.g052050 -0.61 1.92E-01 0.54 2.80E-01 1.91 3.21E-10 CYC1 Cre15.g638500 -0.24 4.48E-01 0.08 8.22E-01 -0.35 9.02E-03 MPPA1 Cre17.g722800 -0.54 2.74E-01 -0.28 6.94E-01 0.8 1.38E-02 MPPA2 Cre12.g509750 -0.6 5.03E-02 0.18 6.88E-01 -0.78 1.44E-08 QCR1 Cre12.g523850 -0.35 3.32E-01 0.1 8.42E-01 -0.59 1.89E-05 QCR7 Cre06.g262700 -0.41 3.20E-01 -0.12 9.33E-01 -0.39 1.37E-02 QCR8 Cre03.g156950 -0.25 5.13E-01 0.06 7.95E-01 -0.2 2.70E-01 QCR9 Cre11.g468950 -0.32 7.22E-01 0.02 9.29E-01 -0.72 6.23E-07 QCR10 Cre09.g409150 -0.59 1.78E-01 -0.11 9.18E-01 -0.75 2.11E-05 RIP1 Cre01.g051900 -0.53 1.67E-01 0 9.77E-01 -0.65 1.74E-06 (d) Cytochrome c CCS1 Cre13.g575000 -1.67 1.56E-03 -3.64 1.43E-09 0.7 4.60E-02 HCS1 Cre12.g525700 -0.37 5.12E-01 -0.13 8.97E-01 1.73 1.67E-12 HCS2 Cre16.g690050 -1.8 4.87E-05 0.4 4.48E-01 1.04 3.20E-03 CYC2 Cre12.g522600 -1.57 1.27E-06 -0.56 2.98E-01 -1.39 4.97E-24 (d) Complex IV COX2A Cre03.g154350 -0.31 6.52E-01 0.16 7.10E-01 -0.57 4.37E-05 COX2B Cre01.g049500 -0.29 7.08E-01 0.08 8.37E-01 -0.55 7.89E-05 COX3 Cre04.g221700 0.07 9.12E-01 0.18 6.58E-01 -0.46 4.87E-04 COX4 Cre13.g567600 -0.55 2.08E-01 0.1 8.12E-01 -0.62 3.16E-07 COX5C Cre03.g157700 -0.39 5.06E-01 0.03 9.26E-01 -0.69 1.14E-06 COX10 Cre12.g516350 -0.59 1.21E-01 0.02 9.56E-01 -0.1 6.99E-01 COX11 Cre01.g055550 -1.49 3.12E-04 0.27 6.56E-01 -1.24 1.45E-03 COX12 Cre06.g304350 -0.25 6.05E-01 0.26 6.06E-01 -0.74 2.83E-08 COX13 Cre12.g537450 -0.13 7.14E-01 0.19 7.09E-01 -0.66 5.76E-07 COX15 Cre02.g082700 -0.76 1.60E-01 0.02 9.53E-01 0.35 3.34E-01 COX16 Cre03.g165400 -1.14 9.90E-02 0.07 8.88E-01 2.68 2.01E-07 Table 4.6 continued next page 74 Table 4.6. continued ARG NF2 NF48 Gene Phytozome v5.5 Log2 FC Adj. p-value Log2 FC Adj. p-value Log2 FC Adj. p-value (d) Complex IV (continued) COX17 Cre05.g232850 -1.25 1.60E-04 -0.02 9.91E-01 -0.36 1.85E-01 COX18 Cre16.g690200 -1.62 1.00E-04 0.27 6.82E-01 0.42 4.25E-01 COX19 Cre10.g454500 -0.53 6.43E-01 0.79 4.90E-01 0 3.97E-01 COX23 Cre03.g213425 -0.62 1.87E-01 0.17 7.98E-01 0.18 6.63E-01 COX90 Cre16.g691850 -0.27 5.11E-01 0.21 6.32E-01 -0.91 1.27E-11 PET191 Cre01.g069107 -0.45 4.35E-01 -1.06 4.90E-02 -0.29 3.37E-01 SCO1 Cre17.g732850 -1.22 1.59E-03 -0.06 9.71E-01 0.25 4.45E-01 SHY1 Cre16.g664700 -0.58 2.34E-01 0.42 5.16E-01 0.67 4.58E-02 (e) ATPase ASA1 Cre07.g340350 -0.3 4.30E-01 0.49 1.96E-01 -0.87 2.57E-12 ASA2 Cre09.g415550 -0.44 5.64E-02 0.45 2.63E-01 -0.94 1.44E-10 ASA3 Cre07.g338050 -0.13 7.65E-01 0.41 3.41E-01 -0.88 8.48E-12 ASA4 Cre13.g581600 -0.45 2.18E-01 0.44 2.89E-01 -0.91 7.92E-11 ASA5 Cre17.g721300 -0.18 7.13E-01 0.26 6.66E-01 -0.75 9.55E-08 ASA6 Cre02.g079800 -0.49 3.61E-01 0.13 7.45E-01 -0.78 7.72E-09 ASA7 Cre09.g416150 -0.57 1.05E-01 0.14 7.58E-01 -1.22 7.21E-16 ASA8 Cre09.g402300 -0.53 2.01E-01 0.12 8.25E-01 -0.9 4.24E-10 ASA9 Cre09.g395350 -0.3 6.39E-01 0.31 5.59E-01 -0.9 3.52E-11 ATP1A Cre02.g116750 -0.48 1.36E-01 0.32 4.21E-01 -1.08 7.22E-21 ATP1B Cre10.g419050 -0.43 4.54E-01 -1.02 8.43E-02 1.15 6.42E-07 ATP2 Cre17.g698000 -0.73 3.49E-02 0.28 4.81E-01 -0.99 2.88E-17 ATP3 Cre15.g635850 -0.59 9.91E-02 0.31 4.84E-01 -1.19 5.57E-21 ATP4 Cre11.g467707 -0.71 3.97E-02 0.11 8.32E-01 -0.75 1.75E-08 ATP5 Cre16.g680000 -0.56 2.41E-01 0.2 6.53E-01 -0.86 1.16E-10 ATP6 Cre01.g018800 -0.37 2.43E-01 0.36 4.52E-01 -1.18 3.97E-21 ATP9A Cre17.g732000 -0.57 1.18E-01 0.01 9.53E-01 -1.3 1.65E-29 ATP9B Cre17.g731950 -0.11 8.68E-01 0.52 2.68E-01 -0.51 8.93E-05 ATP11 Cre10.g437050 -1.11 2.31E-02 -0.01 9.69E-01 1.6 9.28E-04 ATP12A Cre17.g726250 -1.26 1.39E-01 -0.16 9.07E-01 0.88 2.88E-01 ATP15 Cre10.g420700 -0.77 5.32E-02 0.12 7.75E-01 -1.05 2.56E-13 (f) Ubiquinone COQ1 Cre12.g511700 -0.93 1.33E-02 0.55 2.02E-01 2.11 5.16E-10 COQ2 Cre06.g291800 -0.28 5.80E-01 0.07 9.23E-01 0.52 1.34E-01 COQ3 Cre10.g423750 -0.21 7.79E-01 0.99 7.18E-02 1.7 2.52E-03 COQ4 Cre03.g154850 -0.76 2.10E-01 0.12 8.80E-01 0.7 9.42E-02 COQ5A Cre05.g245450 -0.91 6.22E-02 0.78 1.01E-01 0.23 6.08E-01 Table 4.6 continued next page 75 Table 4.6. continued ARG NF2 NF48 Gene Phytozome v5.5 Log2 FC Adj. p-value Log2 FC Adj. p-value Log2 FC Adj. p-value (f) Ubiquinone (continued) COQ5B Cre06.g286300 0.02 9.85E-01 -0.13 8.89E-01 2.49 2.89E-12 COQ5E Cre11.g467612 -0.38 3.82E-01 -0.23 6.50E-01 -0.74 4.14E-05 COQ6 Cre02.g112850 -0.07 9.53E-01 0.51 5.27E-01 0.17 6.57E-01 COQ8 Cre10.g429800 -0.57 5.27E-01 0.64 4.43E-01 1.79 6.94E-08 COQ9 Cre06.g269550 -0.42 6.36E-01 0.32 7.41E-01 2 9.35E-05 COQ10 Cre07.g345700 0.28 5.54E-01 -0.65 3.04E-01 0.54 3.98E-02 (g) Alternative oxidases AOX1 Cre09.g395950 1.21 4.35E-03 0.52 2.10E-01 -2.07 2.42E-55 AOX2 Cre03.g169550 -0.32 5.24E-01 -0.32 6.81E-01 0 3.25E-01 (h) Uncoupling proteins UCP1 Cre06.g278750 -1.65 2.15E-06 -0.76 1.15E-01 -1.07 6.11E-09 UCP2 Cre06.g257550 0.47 4.16E-01 0.78 1.47E-01 1.67 5.35E-04 UCP3 Cre04.g218650 -0.82 4.37E-01 0.18 8.64E-01 1.91 1.15E-06 76 in arginine-fed cultures could help to explain the lack of light stress compared with N starvation. 4.2.6 C assimilation is downregulated in arginine-fed cultures as in long-term N starvation suggesting that arginine may serve as a C source. An obvious source of organic C in the mixotrophic media used is acetate. Alternatively, arginine may serve as a C source as well as an N source, which has not been investigated previously (Sussenbach and Strijkert, 1969; Kirk and Kirk, 1978). The deamination of the four N molecules of arginine would be expected to release six molecules of C in CO2 or other forms that may be used as organic C skeletons. Therefore, the critical questions are how many Cs are released as organic C skeletons and whether the amount of C skeletons are enough to support the use of arginine as a sole organic C source for growth. Examination of the expression profiles of genes involved in C flux through the energetic processes of the Calvin cycle, glycolysis, and the tricarboxylic acid (TCA) cycle showed that most genes were significantly downregulated (≥ 2-fold) throughout NF2, ARG, and NF48 samples in comparison to AMM-I or AMM-II (Table 4.7). These data suggest that arginine-fed and N-starved cultures rely less on the Calvin cycle, glycolysis, and TCA cycle for energy. During N starvation, energy consumption is reduced as N assimilation no longer serves as an energy sink and cellular growth and proliferation are ceased, therefore, excess energy is redirected towards C storage (Johnson and Alric, 2013). A notable exception to the overall downregulation in energetic processes among the NF2, ARG, and NF48 samples in comparison to AMM-I or AMM-II was the lack of downregulation for genes encoding proteins involved in cytosolic glycolysis (Figures 4.9 and 4.10; Table 4.7). Specifically, the enzymatic reactions from glyceraldehyde 3-phosphate to the conversion of pyruvate into either acetyl-CoA or oxaloacetate are not downregulated (encoded by genes 34, 37, 39, and 48 in Table 4.7). In addition, the chloroplast glyceraldehyde 3-phosphate dehydrogenase (GAP1) is significantly upregulated in the ARG and NF48 samples. In plants, the chloroplast glyceraldehyde 3-phosphate dehydrogenase is not relevant in phototrophic cells but is crucial to heterotrophic cells (Anoman et al., 2016; Flores-Tornero et al., 2017), such as long-term N-starved C. reinhardtii cells. 77 Table 4.7. Genes encoding proteins involved in the Calvin cycle, glycolysis, and TCA cycle were downregulated in arginine-fed cultures as in long-term N starvation. Bold face indicates ≥ 2 Log2 FC, underline indicates ≤ -1 Log2 FC each with < 0.05 adj. p-value. ARG NF2 NF48 Gene Phytozome v5.5 Log2 FC Adj. p-value Log2 FC Adj. p-value Log2 FC Adj. p-value (a) Starch metabolism 1 SBE1 Cre06.g289850 0.484 3.75E-01 0.31 6.39E-01 1.18 1.37E-09 2 SBE2 Cre06.g270100 -0.54 1.98E-01 0.77 9.65E-02 -0.49 2.01E-02 3 SBE3 Cre10.g444700 0.44 2.09E-01 1.35 3.97E-05 0.42 4.98E-04 4 PHOA Cre07.g336950 1.04 7.40E-04 0.98 4.70E-03 1.96 1.26E-50 5 PHOB Cre12.g552200 0.35 3.40E-01 0.56 1.58E-01 0.3 1.14E-02 6 ISA2 Cre17.g698850 -0.42 4.43E-01 -0.13 8.64E-01 -0.54 3.78E-02 7 ISA3 Cre03.g207713 0.2 7.42E-01 0.74 6.15E-02 0.29 6.72E-02 8 INV1 Cre12.g488000 0.73 7.67E-02 -0.39 6.26E-01 0 9.83E-01 9 INV2 Cre12.g488050 -0.57 2.95E-01 -3.3 5.91E-09 0.75 1.54E-03 10 GWD1 Cre07.g319300 0.97 9.71E-02 -0.5 6.25E-01 -0.41 3.07E-02 11 GWD2 Cre07.g332300 1.07 1.03E-03 1.51 3.69E-06 0.83 2.10E-09 12 HXK1 Cre02.g117500 -0.69 9.13E-02 0.09 8.93E-01 1.49 3.77E-14 13 GPM1b Cre06.g278210 -0.88 5.74E-03 -0.06 9.40E-01 -0.93 1.12E-12 14 GPM2 Cre01.g012600 -0.64 4.32E-01 1.6 6.39E-03 1.27 7.86E-03 15 STA1 Cre03.g181500 -0.73 4.90E-02 -0.42 3.45E-01 -0.9 3.22E-07 16 STA6 Cre03.g188250 -1.29 3.85E+00 -0.02 9.86E-01 -1.31 2.42E-27 17 SSS1 Cre04.g215150 0.47 1.59E-01 0.77 3.20E-02 1.36 2.96E-25 18 SSS2 Cre03.g185250 -1.79 8.71E-10 -1.52 2.63E-04 -2.35 5.07E-74 19 SSS3 Cre06.g282000 -0.06 9.15E-01 1.54 1.93E-07 -1.25 5.43E-19 20 SSS4 Cre16.g665800 0.15 8.22E-01 0.64 2.22E-01 0.09 6.95E-01 21 SSS5 Cre16.g663850 0.05 9.64E-01 1.2 4.21E-02 1.2 2.53E-07 22 SSI1 Cre12.g521700 -1.27 1.42E-02 -1.97 7.50E-03 1.51 6.45E-05 23 SSI2 Cre17.g721500 -1.75 1.16E-07 0.83 2.34E-02 -3.42 6.40E-136 (b) Glycolysis/gluconeogenesis 24 PGI1 Cre03.g175400 -0.94 9.35E-04 0.75 1.95E-02 -0.91 3.09E-14 25 FBP1 Cre07.g338451 -4.13 3.76E-38 -0.87 4.54E-02 -4.07 1.45E-174 26 FBP2 Cre12.g510650 -1.06 3.62E-04 -0.54 2.24E-01 -1.35 8.24E-28 27 PFK1 Cre06.g262900 -0.11 8.36E-01 0.51 2.19E-01 0.23 1.97E-01 28 PFK2 Cre12.g553250 0.12 7.41E-01 0.67 4.82E-02 -0.41 7.30E-03 29 FBA2 Cre02.g093450 -1.85 5.25E-08 -1.35 2.79E-04 -1.24 3.33E-05 30 FBA1 Cre01.g006950 -2.19 7.96E-14 -0.07 9.29E-01 -2.81 9.95E-68 31 FBA3 Cre05.g234550 -2.45 7.19E-18 0.14 7.62E-01 -1.37 1.16E-33 32 FBA4 Cre02.g115650 -1.77 7.56E-02 -1.02 3.84E-01 -2.28 4.17E-04 33 TPI1 Cre01.g029300 -1.26 5.11E-04 -1.14 2.51E-03 -0.75 4.81E-07 34 GAP2 Cre07.g354200 -0.7 2.58E-01 -0.48 4.99E-01 -0.14 7.41E-01 35 GAP4 Cre12.g556600 -1.08 6.80E-03 -0.85 8.80E-02 0.82 1.60E-03 36 GAP1 Cre12.g485150 1.43 4.90E-05 0.43 3.41E-01 0.79 3.64E-11 37 PGK2 Cre07.g354250 0.17 9.09E-01 -0.18 9.30E-01 -0.19 7.49E-01 Table 4.7 continued next page 78 Table 4.7. continued ARG NF2 NF48 Gene Phytozome v5.5 Log2 FC Adj. p-value Log2 FC Adj. p-value Log2 FC Adj. p-value (b) Glycolysis/gluconeogenesis (continued) 38 PGK1 Cre11.g467770 -2.82 1.61E-27 -2.01 3.60E-04 -3.45 2.12E-175 39 PGM4 Cre05.g232550 -0.49 3.76E-01 0.38 5.10E-01 0.1 8.02E-01 40 PGM9 Cre12.g527400 -1.24 2.47E-02 0.03 9.66E-01 -0.73 1.92E-01 41 PGM2 Cre10.g460300 0.08 9.78E-01 0.52 6.74E-01 0.06 9.20E-01 42 PGH1 Cre12.g513200 -0.67 1.01E-01 0.07 9.01E-01 -1 3.36E-17 43 PYK1 Cre12.g533550 -0.89 9.21E-03 -0.6 2.10E-01 0.67 1.35E-06 44 PYK2 Cre06.g280950 -1.05 3.13E-03 0.33 5.80E-01 0.78 3.78E-07 45 PYK3 Cre05.g234700 0.27 4.56E-01 0.89 6.70E-03 -1.57 9.76E-24 46 PYK4 Cre03.g144847 -0.33 4.55E-01 0.29 5.15E-01 -1.65 3.09E-28 47 PYK5 Cre02.g147900 -1.16 3.16E-04 -3.26 6.41E-09 -0.35 2.43E-02 48 PYK6 Cre10.g426292 0 1.97E-01 0 5.26E-01 0 5.33E-01 49 PDH1 Cre16.g677026 -0.3 4.79E-01 0.59 8.85E-02 -0.69 1.61E-06 50 PCK1 Cre02.g141400 -3.74 1.17E-35 -0.75 1.10E-01 -3.4 4.34E-170 51 PYC1 Cre06.g258700 -0.61 6.30E-02 -0.74 7.47E-02 -0.05 8.38E-01 (c) Oxidative pentose phosphate pathway 52 G6PDH1 Cre17.g725550 0.84 2.79E-02 1.04 9.51E-03 1.76 1.17E-18 53 G6PDH2 Cre08.g378150 0.12 7.38E-01 0.8 1.77E-02 1.1 3.26E-13 54 PGL1 Cre01.g034400 -0.39 2.58E-01 -0.25 7.51E-01 -0.35 1.62E-02 55 PGL2 Cre08.g370650 -2.52 2.22E-05 -1.55 2.59E-02 -2.53 1.14E-16 56 6PGD Cre12.g526800 1.13 2.89E-04 0.82 9.83E-03 1.48 8.65E-30 57 RPI1 Cre03.g187450 -2.03 1.24E-13 -1.31 7.22E-03 -1.8 1.59E-34 58 RPE1 Cre12.g511900 -0.01 1.00E+00 -0.77 9.17E-02 -0.28 2.08E-02 59 TRK1 Cre02.g080200 -2.09 2.70E-14 -0.21 6.69E-01 -1.53 6.10E-44 60 TAL1 Cre01.g032650 -4.01 8.47E-49 -0.8 5.02E-02 -2.19 3.88E-51 61 TAL2 Cre14.g630847 -0.57 2.03E-01 -1.66 2.60E-04 -3.12 9.76E-66 62 TAL3 Cre17.g728900 0.62 2.38E-01 0.64 2.96E-01 1.41 1.69E-06 (d) Acetate assimilation 63 ACS1 Cre01.g071662 -0.45 2.91E-01 0.54 2.16E-01 -0.74 3.95E-04 64 ACS2 Cre01.g055408 -1.9 1.53E-09 -0.78 1.43E-01 -1.44 2.89E-29 65 ACS3 Cre07.g353450 -3.16 2.23E-27 -0.91 6.02E-02 -2.24 8.53E-84 66 PAT1 Cre17.g699000 -0.46 3.07E-01 -0.01 9.96E-01 -1.21 1.99E-11 67 PAT2 Cre09.g396650 0.31 5.88E-01 -0.13 8.54E-01 -1.73 4.02E-32 68 ACK1 Cre09.g396700 0.45 3.37E-01 0.15 7.91E-01 -1.63 4.35E-14 69 ACK2 Cre17.g709850 -0.11 8.75E-01 0.16 8.37E-01 -0.12 7.20E-01 (e) TCA cycle 70 CIS1 Cre12.g514750 -0.69 8.42E-02 0.04 9.59E-01 0.32 3.41E-02 71 ACH1 Cre01.g042750 -1.88 2.91E-09 -0.37 5.29E-01 -0.89 5.47E-13 72 IDH1 Cre17.g728800 -0.03 9.78E-01 0.8 3.25E-02 0.72 1.19E-04 73 IDH2 Cre02.g143250 -0.93 2.87E-03 0.04 9.04E-01 -0.23 1.34E-01 74 IDH3 Cre04.g214500 -1.49 1.17E-05 -1.02 5.15E-03 -1.73 1.75E-41 75 OGD1 Cre12.g537200 -1.43 5.22E-06 -0.51 3.77E-01 -1.43 2.33E-33 Table 4.7 continued next page 79 Table 4.7. continued ARG NF2 NF48 Gene Phytozome v5.5 Log2 FC Adj. p-value Log2 FC Adj. p-value Log2 FC Adj. p-value (e) TCA cycle (continued) 76 SCLA1 Cre03.g193850 -1.15 2.18E-04 -0.1 9.10E-01 -0.38 2.07E-02 77 SCLB1 Cre17.g703700 -1.38 5.80E-05 -0.02 9.92E-01 -0.89 1.94E-08 78 SDH1 Cre14.g619133 -1.42 1.20E-05 -0.26 6.84E-01 -1.95 2.57E-48 79 SDH2 Cre06.g264200 -1.41 8.80E-06 -0.37 5.34E-01 -0.72 1.13E-07 80 SDH3 Cre01.g020350 -1.56 4.81E-08 -0.26 6.83E-01 -0.74 5.04E-06 81 FUM1 Cre06.g254400 -1.73 1.78E-09 0.26 5.41E-01 -0.14 6.04E-01 82 MDH1 Cre03.g194850 -1.67 2.46E-09 -0.33 4.99E-01 -2.25 2.36E-71 83 MDH4 Cre12.g483950 -0.5 1.99E-01 0.14 7.69E-01 -0.91 3.70E-12 (f) Glyoxylate cycle 84 CIS2 Cre03.g149100 -1.85 2.70E-07 -0.98 7.61E-02 -2.05 8.25E-68 85 ICL1 Cre06.g282800 -4.52 1.22E-36 -1.13 4.56E-03 -4.52 2.53E-242 86 MAS1 Cre03.g144807 -4.06 7.66E-28 -1.27 9.76E-03 -4.52 2.96E-205 87 MDH2 Cre10.g423250 -1.55 6.41E-07 -2.03 7.32E-06 -1.66 6.93E-21 88 MDH3 Cre02.g145800 -1.04 8.46E-04 -0.15 7.91E-01 -0.72 1.68E-05 (g) Calvin Benson cycle 89 RBCS1 Cre02.g120100 -1.4 5.37E-07 -3.13 1.11E+00 -0.91 2.34E-14 90 RBCS2 Cre02.g120150 -2.23 7.33E-17 -0.25 5.31E-01 -2.71 2.00E-92 91 PGK1 Cre11.g467770 -2.82 1.61E-27 -2.01 3.60E-04 -3.45 2.12E-175 92 GAP3 Cre01.g010900 -3 2.16E-30 -0.14 8.02E-01 -2.49 2.29E-108 33 TPI1 Cre01.g029300 -1.26 5.11E-04 -1.14 2.51E-03 -0.75 4.81E-07 30 FBA1 Cre01.g006950 -2.19 7.96E-14 -0.07 9.29E-01 -2.81 9.95E-68 31 FBA3 Cre05.g234550 -2.45 7.19E-18 0.14 7.62E-01 -1.37 1.16E-33 32 FBA4 Cre02.g115650 -1.77 7.56E-02 -1.02 3.84E-01 -2.28 4.17E-04 26 FBP2 Cre12.g510650 -1.06 3.62E-04 -0.54 2.24E-01 -1.35 8.24E-28 59 TRK1 Cre02.g080200 -2.09 2.70E-14 -0.21 6.69E-01 -1.53 6.10E-44 58 RPE1 Cre12.g511900 -0.01 1.00E+00 -0.77 9.17E-02 -0.28 2.08E-02 57 RPI1 Cre03.g187450 -2.03 1.24E-13 -1.31 7.22E-03 -1.8 1.59E-34 93 RPI2 Cre07.g314600 -0.6 2.60E-01 -0.58 3.86E-01 -0.21 6.30E-01 94 PRK1 Cre12.g554800 -1.61 2.19E-07 -0.49 3.15E-01 -1.76 1.57E-54 95 SBP1 Cre03.g185550 -2.34 1.18E-17 -0.24 6.71E-01 -1.92 1.69E-60 96 SBP2 Cre17.g699600 -0.15 7.52E-01 0.41 3.80E-01 0.74 2.16E-03 (h) Putative C4 photosynthetic cycle NADP-ME type 97 PPD2 Cre17.g734548 -0.22 7.13E-01 -1.11 8.26E-03 -0.58 1.65E-04 98 PEPC1 Cre16.g673852 1.08 1.22E-01 1.43 6.24E-02 0.99 3.01E-08 99 PEPC3 Cre11.g476325 0 NA 0 NA 0 NA 100 MDH5 Cre09.g410700 0.58 6.14E-02 -0.9 1.04E-01 0.28 3.60E-02 101 MME3 Cre14.g629700 -1.63 8.53E-04 0.34 4.91E-01 -1.29 5.19E-12 102 MME5 Cre01.g022500 -2.81 1.35E-08 -1.75 1.82E-03 -2.43 8.95E-14 Table 4.7 continued next page 80 Table 4.7. continued ARG NF2 NF48 Gene Phytozome v5.5 Log2 FC Adj. p-value Log2 FC Adj. p-value Log2 FC Adj. p-value (i) Fatty acid and triacylglycerol synthesis 103 PDH2 Cre03.g194200 -1.36 1.26E-05 -1.99 3.88E-05 -0.53 9.61E-05 104 GPD1 Cre12.g511150 -0.95 3.15E-02 -1.39 3.83E-03 1.03 1.00E-03 105 GPD2 Cre01.g053000 3.72 2.39E-27 -0.93 2.21E-01 6.15 1.00E-52 106 GPD4 Cre10.g421700 1.51 4.70E-04 1.57 4.48E-04 3.26 2.43E-101 107 ACX1 Cre12.g519100 -1.27 1.22E-05 -1.88 5.63E-10 1.4 1.27E-19 108 BCX1 Cre12.g484000 -1.35 6.30E-06 -1.41 1.48E-04 0.04 7.41E-01 109 BCR1 Cre08.g359350 -1.6 4.60E-07 -1.62 5.66E-06 -0.51 3.34E-05 110 BXP1 Cre17.g715250 -1.87 5.01E-09 -1.58 1.34E-04 -0.38 1.00E-02 111 BXP2 Cre01.g037850 -1.93 1.07E-08 -1.93 5.98E-07 -1.09 5.53E-15 112 ACP1 Cre16.g673109 -1.09 2.41E-03 -0.43 4.31E-01 -0.6 6.33E-05 113 ACP2 Cre13.g577100 -2.2 3.09E-15 -0.58 1.24E-01 -0.77 6.30E-12 114 MCT1 Cre14.g621650 -3.23 8.13E-23 -0.59 2.03E-01 -1.99 1.19E-43 115 KAS3 Cre04.g216950 -2.59 2.98E-16 -3.97 1.57E-25 -1.2 7.06E-10 116 KAR1 Cre03.g172000 -2.12 1.83E-11 -0.85 4.29E-02 -1.39 3.75E-21 117 HAD1 Cre03.g208050 -1.8 4.95E-07 -1.34 9.40E-05 -0.98 3.01E-09 118 ENR1 Cre06.g294950 -1.51 4.70E-07 -0.58 1.31E-01 -1.2 1.70E-22 119 KAS1 Cre11.g467723 -1.32 1.80E-05 -2.68 9.60E-06 -0.34 9.81E-03 120 KAS2 Cre07.g335300 -2.23 8.25E-12 -3.42 4.29E-17 0.15 5.04E-01 121 FAB2 Cre17.g701700 -1.9 5.89E-09 -0.76 1.79E-01 0.01 9.67E-01 122 DESA1 Cre14.g630883 0.1 8.28E-01 0.91 7.07E-03 1.97 5.63E-49 123 FAT1 Cre06.g256750 0.05 9.26E-01 1.07 1.78E-03 1.32 8.19E-17 124 ACS1 Cre13.g566650 0.21 5.85E-01 0.17 7.45E-01 1.02 6.46E-15 125 ACS2 Cre03.g182050 -0.32 5.05E-01 -0.19 7.82E-01 -0.15 3.54E-01 126 ACS3 Cre12.g507400 -2.23 2.68E-10 -1.37 4.91E-03 -1.46 4.51E-19 127 GPA1 Cre02.g143000 -1.51 1.43E-06 -2.1 6.09E-08 0.18 3.41E-01 128 GPA2 Cre06.g273250 -0.26 6.32E-01 0.13 8.31E-01 0.25 3.55E-01 129 PGA5 Cre17.g738350 -0.15 8.48E-01 -0.46 4.99E-01 0.64 2.60E-02 130 PAP1 Cre05.g230900 0.56 3.36E-01 0.29 6.43E-01 -1.16 2.26E-07 131 PAP2 Cre05.g240000 1.08 1.15E-02 0.39 5.14E-01 -1.71 1.02E-15 132 DGTT1 Cre12.g557750 2.58 4.18E-07 1.78 9.54E-03 5.05 1.37E-16 133 MGAT2 Cre09.g386912 -0.28 6.28E-01 -0.4 4.68E-01 0.29 2.20E-01 134 DGTT3 Cre06.g299050 -0.55 2.10E-01 -0.08 8.99E-01 0.82 2.32E-04 135 DGTT4 Cre03.g205050 -0.84 1.84E-01 -0.68 4.03E-01 1.87 6.95E-04 136 DGTT5 Cre02.g079050 0.63 4.94E-01 -0.36 8.05E-01 0 NA 137 PDAT1 Cre02.g106400 0.04 9.64E-01 0.67 2.23E-01 0.42 1.13E-01 138 DGAT1 Cre01.g045903 0.42 5.57E-01 1.4 1.31E-03 2.27 1.26E-11 139 MLDP1 Cre09.g405500 1.94 1.61E-05 -0.18 8.58E-01 3.47 2.18E-66 81 Figure 4.9 – Calvin cycle and exogenous C assimilation genes were downregulated more in arginine-fed cultures than two-hour N starvation. Representation of differential expression of mRNAs involved in C assimilation and metabolism. The log2 fold change is represented by blue for increases and red for decreases in mRNA abundance when cells were N starved or grown in arginine relative to NH4+. Only genes with changes in transcript that were significant adjusted p-values (p < 0.05) were colored (n = 2). Changes in mRNA abundance for arginine are outlined in purple (on the right) and two-hour N starvation in black (on the left). Localizations were based on PredAlgo predictions (Tardif et al., 2012). 82 Figure 4.10 – Calvin cycle and exogenous C assimilation genes were downregulated in arginine-fed cultures comparable to 48-hour N starvation. Representation of differential expression of mRNAs involved in C assimilation and metabolism. The log2 fold change is represented by blue for increases and red for decreases in mRNA abundance when cells were N starved or grown in arginine relative to NH4+. Only genes with changes in transcript that were significant adjusted p-values (p < 0.05) were colored (n = 2). Changes in mRNA abundance for arginine are outlined in purple (on the right) and 48-hour N starvation in black (on the left). Localizations were based on PredAlgo predictions (Tardif et al., 2012). 83 An increase in C storage molecules, starch and TAGs, is a well-known hallmark of N starvation in C. reinhardtii (Weers and Gulati, 1997; Wang et al., 2009). During N starvation, membrane lipids are recycled and stored in TAG-rich lipid bodies (Li et al., 2012). This finding was reinforced in transcriptome studies showing that de novo FA biosynthesis was downregulated in N-starved cultures, and the major contribution of FAs for TAG synthesis was shown to come from membrane recycling (Miller et al., 2010b; Boyle et al., 2012). TAG accumulation occurs in the later stages of N starvation beginning at six hours and reaching a maximum around five days whereas starch synthesis occurs in the early stages prior to TAG biosynthesis (Siaut et al., 2011; Lee et al., 2012). The shift from starch synthesis to TAG synthesis is correlated with a downregulation of genes encoding starch synthesis enzymes and an upregulation of genes encoding starch breakdown and TAG biosynthesis enzymes (Park et al., 2015). The ARG and NF48 transcriptomes showed the same regulation whereby the committal step to starch synthesis (AGPase; STA6 and STA1; genes 15 and 16 in Figure 4.10; Table 4.7i) was significantly downregulated and TAG synthesis genes were either significantly upregulated (DGTT2; gene 132 in Figure 4.10; Table 4.7i) or remain unchanged. Likewise, the synthesis of TAG glycerol-3-phosphate backbones was upregulated in ARG comparable to NF48 (GPD1, 2, and 4; genes 104-106 in Figure 4.10; Table 4.7i). Additionally, the major lipid droplet protein (MLDP1; gene 139 in Figure 4.10; Table 4.7i) known to affect the size of lipid droplets (Moellering and Benning, 2010) was upregulated in the ARG transcriptome comparable to the NF48 transcriptome. The TAGs produced in arginine-fed cultures were rich in saturated FAs compared to N-starved TAGs (Table 3.3; Chapter 3), suggesting that de novo FA biosynthesis was the source of TAGs in arginine cultures. However, the genes encoding proteins involved in de novo FA biosynthesis were downregulated in arginine (Figure 4.10; Table 4.7 genes 103-123). Therefore, the increased contribution of FAs to TAG biosynthesis during arginine-fed growth might be explained by an overflow of C into TAG. The excess C may come from the >50% reduction in the chlorophyll content (and therefore photosystem antennas). The assimilation of exogenous C in the form of acetate proceeds in specialized peroxisomes known as glyoxysomes through the glyoxylate cycle which resembles the TCA cycle except that the decarboxylation steps are bypassed by isocitrate lyase (ICL1) and malate synthase (MAS1) (Kornberg and Krebs, 1957; Kornberg and Madsen, 1957; Kornberg and Beevers, 1957). All enzymes of the glyoxylate cycle in C. reinhardtii have been localized to peroxisomes apart from ICL1 which is in the cytosol (Lauersen et al., 2016). Examination of the genes encoding enzymes of the glyoxylate cycle found that they were all significantly 84 downregulated in the ARG transcriptome consistent with NF48 (Figure 4.10; Table 4.7f). To test if arginine can serve as a heterotrophic organic C source, I characterized whether heterotrophic growth was possible with arginine-feeding without acetate supplementation in two strains, 21gr (CC-1690: NIT1; NIT2) and 137c (CC-125: nit1; nit2). No growth was observed in the arginine-fed cultures without acetate supplementation under dim light (10 μmol m−2 s−1) which is the same as for NH4+-fed cultures (Figure 4.11). Additionally, mutants with a defective icl1 gene encoding isocitrate lyase which is necessary for acetate assimilation were unable to grow in the dark on arginine-fed agar plates with acetate supplementation (data not shown). Together, these data indicate that exogenous acetate is likely the major source of organic C in arginine-fed cultures and that arginine catabolism cannot provide organic C for heterotrophic growth. Therefore, the six molecules of C in each arginine molecule are likely released as CO2 or directed away from the glyoxylate or TCA cycles. 4.2.7 Upregulation of specific amino acid transporters, polyamine degradation and arginine deiminase in arginine infer catabolic route. It is known that arginine assimilation in C. reinhardtii is unique from the assimilation of other amino acids in that it possesses its own transporters for uptake (Kirk and Kirk, 1978). However, the arginine-specific transporters have not been identified, and the possible routes of intracellular arginine assimilation are not fully understood in C. reinhardtii. Therefore, the ARG transcriptome was examined to see whether sets of putative amino acid transporters and the potential metabolic routes serving arginine catabolism were specifically upregulated in arginine-fed culture. The two main classes of putative amino acid transporters are the Amino Acid/Auxin Permease (AAAP) family and the Amino acid Polyamine organoCation (APC) family, which belong to the greater APC superfamily. The AAAP family are distant constituents of the APC superfamily that are solute:cation symporters which transport auxin, single amino acids, or multiple amino acids (Fischer et al., 2002). In A. thaliana, six of the nine AAAPs have been characterized and transport neutral amino acids, while only some can transport acidic amino acids, both with one proton. Additionally, AtAAP3 and AtAAP5 are the only ones shown to transport basic amino acids whereas AtAAP6 transports aspartate (Fischer et al., 2002; Dinkeloo et al., 2018). Likewise, the APC proteins can function as solute:cation symporters, however, they can also function as solute:solute antiporters. Some members of the APC family can also transport polyamines which are not structurally related to amino acids, but contain 85 Figure 4.11 – Arginine cannot support heterotrophic growth in cultures without supplementation of exogenous C. Growth curves of (A) 21gr and (B) 137c cultures maintained in Tris-phosphate (TP) medium without the addition of exogenous C in the form of acetate (Gorman & Levine, 1965). Comparisons of growth were made between media containing 8 mM NH4+ chloride (NH4Cl) or 8 mM arginine as measured by optical density at 720 nm on a log2 scale. Error bars indicate the standard deviation from two independent experiments. A B 86 terminal amine groups (Dinkeloo et al., 2018). In addition to AAAP and APC transporters, plants have recently been shown to have a third class of amino acid transporters known as the Usually Multiple Amino acids Move In and out Transporters (UMAMIT) (Dinkeloo et al., 2018), however, homologs are not found in C. reinhardtii. C. reinhardtii possesses seven AAAPs (AOT1-7) and seven APCs (AOC1, 3-8) (Vallon and Spalding, 2009; Park et al., 2015). Among the APC family, AOC5 and AOC6 bear the greatest homology to the mammalian arginine, lysine, and ornithine y+ transport system (SLC7A1-3) and have been put forth as the putative plasma membrane arginine transporters (Vallon and Spalding, 2009). Additionally, AOC5 and AOC6 are homologous to the recently described Solanum lycopersicum vacuolar ATP-regulated arginine transporter SlCAT2 (Regina et al., 2017; Cosco et al., 2019). AOC5 was significantly upregulated in the ARG, NF2, and NF48 transcriptomes (Figure 4.12 and 4.13; Table 4.8), whereas AOC6 was only significantly upregulated in the NF48 transcriptome suggesting AOC5 as a candidate arginine transporter. Additionally, AOC1 was the only gene encoding a putative amino acid transporter that was uniquely upregulated in arginine and is therefore another strong candidate. Once arginine enters the cell, it may be metabolized in either the chloroplast or mitochondria (described below). The AOC7 and AOT3 transporters were the only transporters with predicted chloroplast localization by PredAlgo (Tardif et al., 2012) of which the gene encoding AOC7 was significantly upregulated in the ARG, NF2, and NF48 transcriptomes. In contrast, the genes encoding the only putative amino acid transporters with a predicted mitochondrial localization, AOT1 and AOT2, did not show significantly altered expression in ARG or NF2 samples compared to the AMM-I sample whereas AOT1 was significantly downregulated in NF48 compared to AMM-II (Figures 4.12 and 4.13; Table 4.8). All in all, these data suggest that AOC5 is a prime candidate for the plasma membrane-localized arginine transporter and that AOC1 or 7 may be involved in shunting arginine or arginine-derived metabolic intermediates between organelles during arginine-dependent growth. Future studies of arginine-fed cultures using strains defective in these transporters will help determine their role in arginine assimilation. There are three classical pathways known for arginine catabolism in photosynthetic eukaryotes: 1) arginase (Arg -> NH4+ + Urea), 2) the agmatine pathway (Arg -> polyamines -> NH4+), and 3) arginine deiminase (Arg -> NH4+ + citrulline) (Winter et al., 2015). In eukaryotes and some prokaryotes outside of the green lineage, NO synthase is an important pathway converting arginine to citrulline and NO, however, NO synthase has not been found in the green lineage apart from Ostreococcus taurii (Foresi et al., 2010). There is no arginase homolog present in the C. reinhardtii genome, leaving only the agmatine pathway and arginine deiminase pathways as 87 Table 4.8. Genes encoding putative arginine metabolism enzymes are upregulated in arginine-fed cultures. Bold face indicates ≥ 2 Log2 FC, underline indicates ≤ -1 Log2 FC. ARG NF2 NF48 Gene Phytozome v5.5 Log2 FC Adj. p-value Log2 FC Adj. p-value Log2 FC Adj. p-value (a) Ammonium assimilation AMT1 Cre03.g159254 6.37 4.73E-18 2.98 7.11E-06 9.84 5.53E-24 AMT3 Cre06.g293051 0.51 2.30E-01 0.56 2.00E-01 -1.6 1.18E-18 AMT4 Cre13.g569850 8.13 7.11E-53 7.25 2.51E-42 5.53 1.00E-42 AMT5 Cre09.g400750 3.09 1.40E-14 1.93 2.32E-08 4.28 3.25E-29 AMT6 Cre07.g355650 0.58 3.20E-01 0.45 5.20E-01 -3.5 1.34E-14 AMT7 Cre02.g111050 0.2 6.30E-01 -0.17 8.30E-01 -0.56 3.81E-03 AMT8 Cre12.g531000 3.97 1.24E-14 2.54 2.36E-09 3.16 1.08E-34 GDH1 Cre09.g388800 1.1 2.93E-02 0.62 3.94E-01 0.86 1.14E-04 GDH2 Cre05.g232150 -1.9 1.35E-09 -2.02 3.25E-07 -3.32 6.12E-153 GLN1 Cre02.g113200 0.75 1.09E-02 1.33 2.64E-06 1.26 5.34E-29 GLN2 Cre12.g530650 -0.17 7.52E-01 -0.22 6.14E-01 -0.19 1.33E-01 GLN3 Cre12.g530600 7.41 6.86E-73 5.6 8.05E-30 6.44 4.14E-72 GLN4 Cre03.g207250 1.17 1.34E-03 0.96 2.30E-02 -1.19 1.06E-23 GSF1 Cre12.g514050 -0.01 9.73E-01 0.53 2.79E-01 0.77 1.86E-11 GSN1 Cre13.g592200 1.11 1.36E-03 1.04 7.83E-03 1.09 2.53E-17 (b) Arginine biosynthesis AGK1 Cre01.g015000 0.55 9.64E-02 1.45 3.91E-05 1.14 1.60E-14 AGS1 Cre09.g416050 1.27 6.24E-06 2.11 9.39E-14 1.04 7.31E-13 AOD1 Cre02.g105500 0.26 5.51E-01 0.98 1.20E-02 -0.62 1.46E-03 ARG1 Cre03.g146187 0.77 2.02E-02 1.98 6.62E-11 1.59 2.49E-27 ARG7 Cre01.g021251 0.07 9.26E-01 1.43 6.12E-06 1.34 1.39E-13 ARG9 Cre06.g278163 -0.21 6.79E-01 0.34 5.51E-01 0.95 3.21E-12 CMPL1 Cre08.g358580 1.03 2.47E-04 1.9 1.21E-10 1.27 5.60E-28 CMPS1 Cre06.g308500 1.47 8.01E-08 1.74 4.28E-09 1.57 9.91E-37 GLB1 Cre07.g357350 0.03 9.38E-01 1.24 1.24E-03 0.25 1.66E-01 LCI8 Cre02.g144800 0.83 1.31E-02 1.8 6.24E-09 0.36 3.17E-02 NGS1 Cre16.g694850 0.02 9.64E-01 1.3 4.08E-04 -0.18 4.51E-01 OTC1 Cre12.g489700 0.43 2.48E-01 1.29 2.15E-05 1.79 7.37E-26 (c) Putative arginine catabolic enzymes ADC1 Cre02.g105150 -0.95 1.93E-01 -1.03 2.16E-01 -0.35 5.71E-01 ADI1 Cre08.g360350 1.53 8.10E-04 -0.62 4.67E-01 -0.36 1.40E-01 ALD1 Cre12.g520350 -0.73 1.31E-01 -1.23 5.52E-02 -0.03 9.64E-01 FUM2 Cre01.g020223 1.11 7.32E-03 0.77 1.06E-01 1.96 3.56E-13 OAD1 Cre16.g675900 0 8.77E-01 0 9.21E-01 0.83 5.92E-04 ODC1 Cre03.g159500 0.19 8.63E-01 -2.5 4.06E-21 0.44 6.33E-03 Table 4.8 continued next page 88 Table 4.8. continued ARG NF2 NF48 Gene Phytozome v5.5 Log2 FC Adj. p-value Log2 FC Adj. p-value Log2 FC Adj. p-value (c) Putative arginine catabolic enzymes (continued) ODC2 Cre16.g683371 0.64 1.02E-01 -0.02 1.00E+00 -0.23 1.51E-01 OTA1 Cre11.g474800 2.11 2.22E-07 1.1 6.21E-02 1.22 4.24E-06 (d) Polyamine metabolism AIH1 Cre01.g053300 -0.86 1.76E-01 -0.23 8.63E-01 2.05 4.49E-07 AIH2 Cre01.g009350 3.1 2.24E-07 1.32 1.77E-01 3.74 5.41E-109 AMX1 Cre09.g402515 4.27 8.82E-23 3.22 6.43E-16 6.47 6.69E-102 AMX2 Cre01.g000650 2.8 4.11E-14 4.89 5.11E-37 3.31 1.49E-100 AMX3 Cre13.g572750 1.48 1.84E-05 0 5.67E-01 4.17 7.58E-15 CPA1 Cre12.g535750 -0.87 3.83E-01 -0.87 1.21E-01 1.27 1.02E-01 CPA2 Cre01.g035300 0 NA 0 NA 0 NA SPD1 Cre12.g558450 -0.86 5.59E-02 -0.46 3.95E-01 -0.04 8.50E-01 SPS1 Cre06.g251500 -1.4 1.06E-04 -4.99 4.18E-23 -1.01 1.74E-03 (e) Putative amino acid transporters AOC1 Cre04.g226150 1.46 7.33E-04 0.79 2.13E-01 -1.44 1.20E-16 AOC3 Cre02.g108550 0.98 1.82E-04 0 2.33E-02 4.6 3.00E-40 AOC4 Cre06.g292350 0.46 3.06E-01 -0.11 9.05E-01 0.77 6.59E-07 AOC5 Cre07.g329050 2.1 3.33E-05 2.23 1.87E-05 1.61 6.35E-23 AOC6 Cre01.g041050 0.17 8.33E-01 0.48 4.59E-01 1.6 5.09E-06 AOC7 Cre01.g023650 1 5.01E-10 1.45 1.55E-12 1.91 1.15E-17 AOC8 Cre07.g348040 0.14 8.19E-01 0.03 9.60E-01 0.38 1.47E-01 AOT1 Cre02.g145700 0.14 8.50E-01 -0.65 2.17E-01 -1.35 3.75E-05 AOT2 Cre02.g145750 0.65 2.68E-01 0 8.76E-01 0.37 6.34E-01 AOT3 Cre03.g168550 0.19 8.16E-01 0.01 9.76E-01 -0.71 3.29E-04 AOT4 Cre06.g298750 0.75 6.03E-02 0.06 9.29E-01 0.92 4.03E-05 AOT5 Cre06.g264450 0.71 1.55E-01 1.41 3.57E-04 -0.19 5.41E-01 AOT6 Cre02.g115300 0.48 3.52E-01 0.56 2.35E-01 1.23 2.32E-08 AOT7 Cre02.g112000 1.92 4.89E-06 1.96 7.52E-05 3.05 1.65E-27 (f) NO-associated enzymes ARC1 Cre09.g389089 0.1 9.35E-01 0.27 6.97E-01 1.06 6.21E-05 CYG56 Cre16.g688901 1.94 5.77E-07 0.02 9.75E-01 0.49 3.67E-02 NIT1 Cre09.g410950 0.15 1.53E-03 0.85 2.10E-03 4.04 4.55E-17 NOA1 Cre09.g400550 -0.07 9.13E-01 -1.75 2.09E-06 1.07 1.52E-04 NOA2 Cre07.g315400 0.17 8.85E-01 -2.37 6.33E-05 0.98 1.69E-03 THB1 Cre14.g615400 -3.07 6.56E-02 -3.07 2.84E-03 0 8.54E-01 (g) Fumarate metabolism ACL1 Cre05.g241850 -0.47 3.21E-01 0.65 1.37E-01 0.44 2.30E-02 Table 4.8 continued next page 89 Table 4.8. continued ARG NF2 NF48 Gene Phytozome v5.5 Log2 FC Adj. p-value Log2 FC Adj. p-value Log2 FC Adj. p-value (c) Putative arginine catabolic enzymes (continued) ACL1 Cre05.g241850 -0.47 3.21E-01 0.65 1.37E-01 0.44 2.30E-02 ACL2 Cre02.g088600 -0.54 1.81E-01 0.19 7.07E-01 0.56 1.96E-03 AST1 Cre09.g387726 -2.7 2.90E-17 -0.88 1.10E-01 -2.61 3.10E-72 AST2 Cre01.g051800 -0.09 9.43E-01 0.04 9.72E-01 1.29 6.30E-06 AST3 Cre02.g097900 -0.81 2.15E-02 0.8 2.39E-02 -1.31 3.59E-13 AST4 Cre06.g257950 -1.15 2.13E-04 -1.45 7.01E-03 1.25 1.02E-13 AST5 Cre06.g278249 -0.37 6.63E-01 -1.29 1.39E-01 2.51 3.90E-08 CIS1 Cre12.g514750 -0.69 8.42E-02 0.04 9.55E-01 0.32 3.41E-02 CIS2 Cre03.g149100 -1.85 2.70E-07 -0.98 7.61E-02 -2.05 8.25E-68 FUM1 Cre06.g254400 -1.73 1.78E-09 0.26 5.41E-01 -0.14 6.04E-01 FUM2 Cre01.g020223 1.11 7.32E-03 0.77 1.06E-01 1.96 3.56E-13 MDH1 Cre03.g194850 -1.67 2.46E-09 -0.33 4.99E-01 -2.25 2.36E-71 MDH2 Cre10.g423250 -1.55 6.41E-07 -2.03 7.32E-06 -1.66 6.93E-21 MDH3 Cre02.g145800 -1.04 8.46E-04 -0.15 7.91E-01 -0.72 1.68E-05 MDH4 Cre12.g483950 -0.5 1.99E-01 0.14 7.69E-01 -0.91 3.70E-12 MDH5 Cre09.g410700 0.58 6.14E-02 -0.9 1.04E-01 0.28 3.60E-02 MME1 Cre06.g268750 -0.82 2.21E-02 -0.45 3.52E-01 -0.81 1.22E-05 MME2 Cre14.g629750 -1 1.64E-02 -1.03 1.41E-02 -0.59 2.83E-02 MME3 Cre14.g629700 -1.63 8.53E-04 0.34 4.91E-01 -1.29 5.19E-12 MME4 Cre14.g628650 0 NA 0 NA 0 NA MME5 Cre01.g022500 -2.81 1.35E-08 -1.75 1.82E-03 -2.43 8.95E-14 MME6 Cre06.g251400 -0.68 4.35E-02 -1.03 3.99E-03 -1.43 2.28E-09 PCK1 Cre02.g141400 -3.74 1.17E-35 -0.75 1.10E-01 -3.4 4.34E-170 90 Figure 4.12 – Arginine metabolism through arginine deiminase (ADI1) and polyamine degradation was upregulated in arginine-fed cultures relative to two-hour N starvation. Schematic representation of differential expression of mRNAs involved in arginine metabolism. The log2 fold change is represented by blue for increases and red for decreases in mRNA abundance relative to NH4+. Changes in mRNA abundance when cells are grown in arginine versus NH4+ are outlined in purple (in front) and two-hour N starvation versus NH4+ in black (in back). The green arrows indicate the putative metabolic route of arginine catabolism through arginine deiminase and the orange arrows indicate arginine metabolism through polyamine synthesis. The localizations are based on either PredAlgo predictions (Tardif et al., 2012) or previous experimental evidence (Fernandez and Galvan, 2007; Harris, 2009). Boxes with dashed outlines are for unidentified proteins/genes in the Phytozome V5 annotation. 2-OG = 2-oxoglutarate, Agm = agmatine, Arg = arginine, ASA = Argininosuccinic Acid, Asp = Aspartate, Cit = Citrulline, CP = carbamoyl phosphate, Fum = Fumarate, Gln = Glutamine, Glu = Glutamate, NAG = N-acetyl glutamate, NAGP = N-acetylglutamyl-phosphate, NAGS = N-acetylglutamate-5-semialdehyde, NAO = N-acetylornithine, NCP = N-carbamoylputrescine, Orn = Ornithine, Put = Putrescine, Spd = Spermidine, Spm = Spermine, Suc = Succinate. 91 Figure 4.13 – Arginine metabolism through arginine deiminase (ADI1) was upregulated in arginine-fed cultures relative to 48-hour N starvation. Schematic representation of differential expression of mRNAs involved in arginine metabolism. The log2 fold change is represented by blue for increases and red for decreases in mRNA abundance relative to NH4+. Changes in mRNA abundance when cells are grown in arginine versus NH4+ are outlined in purple (in front) and 48-hour N starvation versus NH4+ in black (in back). The green arrows indicate the putative metabolic route of arginine catabolism through arginine deiminase and the orange arrows indicate arginine metabolism through polyamine synthesis. The localizations are based on either PredAlgo predictions (Tardif et al., 2012) or previous experimental evidence (Fernandez and Galvan, 2007; Harris, 2009). Boxes with dashed outlines are for unidentified proteins/genes in the Phytozome V5 annotation. 2-OG = 2-oxoglutarate, Agm = agmatine, Arg = arginine, ASA = Argininosuccinic Acid, Asp = Aspartate, Cit = Citrulline, CP = carbamoyl phosphate, Fum = Fumarate, Gln = Glutamine, Glu = Glutamate, NAG = N-acetyl glutamate, NAGP = N-acetylglutamyl-phosphate, NAGS = N-acetylglutamate-5-semialdehyde, NAO = N-acetylornithine, NCP = N-carbamoylputrescine, Orn = Ornithine, Put = Putrescine, Spd = Spermidine, Spm = Spermine, Suc = Succinate. 92 potential arginine catabolism pathways in C. reinhardtii. Of the two pathways for arginine catabolism in C. reinhardtii, only the bacterial-type arginine deiminase has been documented biochemically in C. reinhardtii (green arrows in Figure 4.12 and 4.13) (Sussenbach and Strijkert, 1969). Arginine deiminase (ADI1) was significantly upregulated in the ARG transcriptome and not in either NF2 or NF48 (2.9-fold; Table 4.8). Catabolism of arginine by ADI1 in the chloroplast releases one molecule of NH4+ and one molecule of citrulline (Sussenbach and Strijkert, 1969; Ludwig, 1993). The metabolic fate of citrulline in photosynthetic eukaryotes is its reintegration into the arginine biosynthetic pathway whereby it is either used by arginosuccinate synthase (AGS1) towards the re-synthesis of arginine, consuming an aspartate and producing a fumarate, or it is used by ornithine transcarbamylase (OTC1) to produce ornithine and carbamoyl phosphate (Joshi and Fernie, 2017). If the citrulline is used for the re-synthesis of arginine, then the aspartate molecule used is produced by the consumption of one oxaloacetate and one glutamate via aspartate transaminase (AST). Overall, one glutamate is consumed and one NH4+ is generated, balancing out the N quota, which appears to be a futile cycle (Glu -> Asp -> Arg -> Glu). However, the fumarate is likely shuttled out of the chloroplast (described below) whereas aspartate, oxaloacetate, and/or their precursors are moved in, therefore, this cycle may be necessary for the localization of metabolites. The fumarate is converted into malate either by the mitochondrial fumarase (FUM1) as part of the TCA cycle or by the cytosolic fumarase (FUM2). In A. thaliana, fumarate serves as a C storage molecule that is massively accumulated by the cytosolic fumarase (FUM2) when intracellular glutamine levels are high during the day (Pracharoenwattana et al., 2010; Zell et al., 2010; Zubimendi et al., 2018). In contrast, at night when the intracellular glutamine levels are decreased, the activity of FUM2 favors malate production and C flux through glycolysis and the TCA cycle to support the heterotrophic phase (Zubimendi et al., 2018). In both the ARG and NF48 transcriptomes, the expression of FUM2 is significantly upregulated whereas FUM1 is significantly downregulated only in ARG (Table 4.8). This finding suggests that fumarate produced by the ADI1 cycle is mobilized to the cytosol and produces malate. The malate is either converted to oxaloacetate, producing one NAD(P)H, by malate dehydrogenase (MDH) or to pyruvate by a malic enzyme (MME). All of six of the genes encoding MMEs are significantly downregulated in ARG and NF48 compared to AMM-I or AMM-II, respectively (Table 4.8). In contrast, three of the five MDHs are downregulated in ARG compared to AMM-I whereas all five are downregulated in NF48 compared to AMM-II. The two MDHs that are not altered in the ARG transcriptome relative to AMM-I are MDH4 and MDH5 which are 93 localized to the mitochondria (Atteia et al., 2009) and the chloroplast (Terashima et al., 2011), respectively. Therefore, in arginine-fed cultures, the malate produced from fumarate by FUM2 in the cytosol could be mobilized to the mitochondria or chloroplast and converted into oxaloacetate and NAD(P)H by either MDH4 or MDH5, respectively. Subsequently, the oxaloacetate could be used to synthesize aspartate by ASTs, citrate by CIS1 or CIS2, or phosphoenolpyruvate by PCK1. Whereas CIS2, PCK1, AST1, AST3, and AST4, are significantly downregulated in ARG relative to AMM-I, the AST2, AST5, and CIS1 genes are unaltered in ARG relative to AMM-I. These data suggest that oxaloacetate metabolism in arginine-fed cultures moves through the mitochondrial CIS1 protein in the TCA cycle producing citrate or through AST2 or AST5 to produce aspartate. A previous study by Wase et al., (2014) found that citrate levels increase during N starvation and that the supplementation of citrate during NH4+-fed growth of C. reinhardtii increased the final cell density and increased the cellular lipid content, both of which are observed in arginine-fed cultures (Table 3.1 and Table 3.3). Considering that eleven of fourteen genes encoding enzymes of the TCA cycle are downregulated in ARG relative to AMM-I (Figure 4.9 and Figure 4.10; Table 4.7), citrate likely does not proceed through the TCA cycle. Therefore, the citrate produced by CIS1 could serve as a carrier of acetyl units that are mobilized to the cytosol and metabolized back into oxaloacetate and acetyl-CoA by ATP citrate lyase. The subunits of ATP citrate lyase are encoded by ACL1 and ACL2 whose expression is not significantly altered in ARG relative to AMM-I but are significantly upregulated in NF48 relative to AMM-II (Table 4.8). Again, this cycle may seem futile, however, the shuttling of intermediates into the mitochondria releases reductant in the form of NADH by MDH4 activity in the mitochondria and acetyl units back to the cytosol for the biosynthesis of C compounds such as lipids. Another metabolic fate of the malate produced from fumarate derived from the ADI1 pathway in arginine-fed cultures is the regeneration of aspartate via AST. As mentioned above, the ASTs not downregulated in ARG relative to AMM-I are AST2 and AST5, whose products are predicted to localize to the chloroplast and cytosol, respectively (Tardif et al., 2012). The production of aspartate by AST utilizes one molecule of oxaloacetate and one molecule of glutamate producing one molecule of 2-OG in the process. Oxaloacetate production in arginine-fed cultures is likely through MDH4 or MDH5 in the mitochondria and chloroplast, as mentioned above. Therefore, oxaloacetate production by MDH5 and subsequent production of aspartate by AST2 in the chloroplast seems the most likely route during arginine metabolism. On the other hand, cytosolic aspartate production by AST5 may play a role if oxaloacetate is shuttled out of the chloroplast or mitochondria. Taken together, the re-synthesis of arginine from citrulline produced by the ADI1 enzyme produces fumarate that can shuttle C from the chloroplast which 94 results in the production of NAD(P)H in either the chloroplast or the mitochondria, ATP consumption in the chloroplast, and the shuttling of acetyl units from the mitochondria to the cytosol in the form of citrate. There is an alternate route for the metabolism of citrulline generated by ADI1 that produces ornithine rather than re-synthesizing arginine. If AGS1 activity is limited by low aspartate levels, then the accumulated citrulline could produce ornithine and carbamoyl phosphate through the OTC1 enzyme. As photosynthetic eukaryotes have no homolog for carbamate kinase, the carbamoyl phosphate is likely directed towards pyrimidine synthesis. The ornithine could either be directed to polyamine biosynthesis (described below), or alternatively, the δ-amino group could be transaminated with 2-OG by ornithine transaminase (OTA1) in the mitochondria to glutamate and glutamate 5-semialdehyde (GSA). Interestingly, OTA1 is significantly upregulated in the ARG and NF48 transcriptomes, more so in ARG (Figure 4.13; Table 4.8). The glutamate produced in the mitochondria could then be deaminated to NH4+ and 2-OG by either of the two glutamate dehydrogenases (GDH1/2) in C. reinhardtii. Whereas GDH1 is significantly upregulated in the ARG and NF48 transcriptomes, GDH2 is significantly downregulated in all transcriptomes. The GSA can be reduced to glutamate in the mitochondria by L-glutamate gamma-semialdehyde dehydrogenase encoded by ALD1 in C. reinhardtii. The ALD1 gene does not show significant alteration in any of the transcriptomes examined here. These data suggest that ornithine transamination and glutamate reduction play an important role in the metabolism of citrulline from arginine catabolism via ADI1 activity. The second classical pathway of arginine catabolism present in C. reinhardtii is that of the plant-type agmatin degradation pathway (Orange arrows in Figure 4.12 and Figure 4.13). The first step is decarboxylation of arginine or ornithine by either arginine or ornithine decarboxylase (ADC and ODC, respectively) towards the production of the polyamine putrescine (Put). Most plants primarily synthesize Put from ornithine by ODC apart from A. thaliana where no ODC ortholog exists (Hanfrey et al., 2001). Previous biochemical studies in plants have suggested that the ODC route is more important for normal cellular division, differentiation, and development whereas the ADC route is necessary for cell expansion and environmental stress responses (Malmberg et al., 1998). To determine whether the synthesis of polyamines plays a major role in arginine catabolism, transcript abundance of the arginine/ornithine decarboxylases were assessed. In C. reinhardtii, two ODC homologs (ODC1/2) have been identified and functionally characterized whereas genes putatively encoding ADC (OAD1, ADC1) have been put forth but not validated experimentally (Illingworth et al., 2003; Merchant et al., 2007; Park et al., 2015). Additionally, it is 95 possible that ODC1/2 catalyze the decarboxylation of arginine (Baumann et al., 2007). The putative C. reinhardtii ADCs were almost undetectable in all transcriptomes. Furthermore, the ODCs were not significantly altered in any transcriptome studied here. Additionally, genes encoding proteins for the synthesis of the two other common polyamines, Spd by spermidine synthase (SPD1) from Put and Spm via spermine synthase (SPS1), were downregulated in all transcriptomes, significantly so for SPS1 (Figure 4.12 & 4.13; Table 4.8). Lastly, the degradation of polyamines in photosynthetic eukaryotes occurs via diamine oxidases (DAOs) or polyamine oxidases (PAOs). C. reinhardtii possesses three DAOs (AMX1-3), which are copper-containing enzymes that oxidize the diamine Put, all of which are significantly upregulated in the ARG transcriptome and in NF2 and NF48 except for AMX3 in NF2 (Figure 4.12 & 4.13; Table 4.8). The upregulation of AMX1-3 and the downregulation of SPD1 and SPS1 suggests that any overflow of arginine catabolic products into polyamine synthesis is curtailed by the degradation of Put. This may be related to the regulatory role that polyamines play in growth/development and environmental responses signaled by the ratio of each polyamine such that the flow of arginine catabolism through polyamines would disrupt growth and development. Taken together, the contribution of polyamine synthesis to arginine metabolism appears to be minimal. Based on the data outlined here, a hypothetical arginine catabolism route can be proposed as the sequential actions of 1) uptake of arginine by AOC5 or AOC1, 2) mobilization to the chloroplast by AOC7, and 3) degradation by ADI1 into NH4+ and citrulline. The citrulline may be used to generate the C storage molecule, fumarate, by FUM2 or be converted to ornithine which could be remobilized to the mitochondria and deaminated to two molecules of glutamate by OTA1 and GDH1. 4.2.8 Identification of putative regulators of arginine metabolism and N starvation responses. To find candidate transcription factors involved in the activation of putative arginine assimilation genes or the coordination of N starvation responses in arginine-fed cultures, I searched within the genes significantly upregulated in the ARG set of DEGs for those with DNA binding domains. I found 32 putative transcription factors that fall into seven categories based on whether they are also significantly regulated in NF2 or NF48 (Table 4.9). To find a putative arginine-specific transcription factor that upregulates arginine assimilation genes, I focused on transcription factors upregulated in ARG and NF2 transcriptomes that return to basal levels in NF48. The rationale is that, early in N starvation, cells will upregulate all alternative N source assimilation genes, including those for arginine assimilation, to scavenge 96 any available N. If no alternative N is found, such as arginine, then the majority of these N assimilation proteins will be degraded and the genes encoding them will no longer be upregulated. There were two putative transcription factors, RWP9 (Cre06.g297150) and RWP11 (Cre03.g149400) with the expected expression profile (Table 4.9). Next, it was examined how the genes for these transcription factors are regulated during previously published N starvation time-course transcriptomes (Schmollinger et al., 2014). RWP9 expression peaks very early (0.5 h) following N starvation and returns to basal levels by 2 h of N starvation (Table 4.9). In contrast, RWP11 was expressed at similar levels throughout N starvation and its expression peaked slightly later in N starvation (12 h). Additionally, RWP11 was previously associated with the putative regulation of core carbohydrate metabolic processes, FA biosynthesis, and general N assimilation which are represented by genes for the pentose phosphate pathway, TAG lipases, and NO3-/NH4+ assimilation, respectively (Romero-Campero et al., 2016). Therefore, RWP11 is more likely to be associated with N starvation responses that occur in arginine-fed cultures and RWP9 is the strongest candidate for arginine-specific regulation to be examined in future studies. The category of transcription factors that are significantly upregulated in all three comparisons (ARG, NF2, NF48) include six genes, two of which (NRR1 and PSR1) were previously identified as regulators of N starvation responses, specifically TAG accumulation (Boyle et al., 2012; Schmollinger et al., 2014; Ngan et al., 2015). Of note is Cre01.g011150, encoding a helix-loop-helix transcription factor that was recently identified among the candidate regulators that are co-regulated with core metabolism of carbohydrates and N together with RWP11 described above (Schmollinger et al., 2014; Romero-Campero et al., 2016). Another gene encoding a putative transcription factor in this category, Cre01.g034350, was found by Ngan et al., 2015 to be associated with lipid metabolism alongside PSR1. The other two genes (Cre07.g332250 and Cre16.g671200) in this category were not found in the previous studies. Arginine-fed cultures exhibit N starvation-like phenotypes but not responses such as cell cycle arrest. A search for transcription factors that are upregulated in the ARG transcriptome but are downregulated in NF48 revealed transcription factors that are putatively involved in the suppression of some N starvation responses. This category is enriched in AP2 binding domain proteins (Cre13.g602750, Cre08.g385350, Cre14.g620500), MYB-like binding domain proteins (Cre16.g677382, Cre02.g103450, Cre12.g507500, Cre03.g144747), and basic leucine zipper domain proteins (Cre07.g318050, Cre09.g413050). Additionally, there is one helix-loop-helix type (Cre14.g620850) and one SQUAMOSA binding domain type 97 Table 4.9. Putative transcription factors significantly upregulated in arginine-fed cultures may control arginine assimilation or N starvation responses. All putative transcription factors were significantly upregulated in ARG. For NF2 and NF48, up = significantly upregulated and down = significantly downregulated FC vs. AMM-I FC vs. AMM-II Gene Phytozome v5.5 ARG NF2 NF0.5 NF2 NF4 NF8 NF12 NF24 NF48 PF (a) Putative arginine assimilation regulators (NF2up) RWP11 Cre03.g149400 2.38 8.82 0.64 0.88 0.89 1.28 1.28 1.17 1.17 1.5 RWP9 Cre06.g297150 4.16 2.43 1.77 1.03 0.61 0.93 0.9 0.97 1 1.4 (b) Putative arginine assimilation regulators (NF2up NF48down) RWP6 Cre06.g291500 2.12 3.01 0.97 1.08 0.92 0.59 0.61 0.41 0.3 2.84 (c) Putative N starvation regulators (NF2up NF48up) NRR1 Cre16.g673250 11.64 21.88 97.25 252.56 112.47 138.23 154.88 348.85 230.35 2.13 putative bHLH Cre01.g011150 77.9 146.08 1323.53 3371.61 2406.71 2399.95 2541.25 2646.62 3369.09 6.22 PSR1 Cre12.g495100 9.12 6.27 33.35 41.05 27.38 25.92 24.22 20.06 19.8 19.7 _MYB1 Cre01.g034350 5.22 8.35 12.4 24.42 9.22 19.26 22.73 30.41 34.34 4.47 bHLH Cre07.g332250 6.09 5.44 3.61 1.82 0.84 2.25 2.48 2.83 3.14 1.45 _BLZ20 Cre16.g671200 5.43 2.65 3.41 14.12 6.74 8.47 12.32 10.29 15.26 116.8 (d) Putative N starvation regulators (NF48down) Putative AP2 domain TF Cre13.g602750 0.98 2.33 0.08 0.12 0.15 0.22 0.19 0.22 0.21 0.85 SQUAMOSA binding domain Cre02.g110150 1.34 1.91 0.27 0.26 0.22 0.29 0.28 0.24 0.23 1.1 _BLZ4 Cre07.g318050 0.87 3.34 0.1 0.1 0.13 0.28 0.39 0.4 0.39 0.88 _MYB3 Cre16.g677382 1.56 6.57 0.56 0.39 0.4 0.4 0.52 0.65 0.82 1.62 _MYB6 Cre02.g103450 1.43 2.44 0.23 0.22 0.26 0.3 0.24 0.26 0.27 0.95 _NSG17 bHLH Cre14.g620850 0.98 2.3 0.31 0.27 0.24 0.4 0.47 0.53 0.47 1.03 _MYB23 Cre12.g507500 1.93 6.49 0.13 0.35 0.26 0.35 0.22 0.19 0.09 0.81 _BLZ7 Cre09.g413050 1.6 2.52 0.45 0.49 0.27 0.44 0.43 0.4 0.43 0.6 _MYB2 Cre03.g144747 0.6 3.83 0.57 0.44 0.52 0.61 0.51 0.49 0.42 1.08 Putative AP2 domain TF Cre08.g385350 0.88 2.48 0.51 0.4 0.44 0.5 0.48 0.66 0.59 1.5 Putative AP2 domain TF Cre14.g620500 0.66 2.35 0.24 0.29 0.5 0.74 0.64 0.81 0.72 2.85 (e) Putative N starvation regulators (NF48up) RWP12 Cre01.g004600 1.07 1.74 1.05 1.1 0.81 1.59 1.98 2.27 2.56 1.25 Table 4.9 continued next page 98 Table 4.9. continued FC vs. NH4+-I FC vs. NH4+-II Gene Phytozome v5.5 ARG NF2 NF0.5 NF2 NF4 NF8 NF12 NF24 NF24 PF (e) Putative N starvation regulators (NF48up) RWP4 (AT5G66990.1) Cre03.g149350 2.2 9.72 1.33 4.5 15.15 28.05 25.59 17.04 10.61 3.13 _MYB12 Cre03.g197100 0.74 5.11 0.08 0.37 0.86 1.38 1.72 2.02 2.34 1.3 GSP1 Cre02.g109650 0.56 2 22.73 11.88 5.02 2.08 2.59 5.14 6.95 1.95 putative DNA transposase binding domain Cre04.g228250 2.67 4.58 1.01 1.14 1.79 2.87 4.43 4.55 4.26 16.71 BUG25 (basal body protein AP2 domain) Cre01.g009650 0.79 2.44 1.36 0.74 0.58 1.24 1.59 1.71 2.2 0.89 RWP8 Cre04.g218050 0.76 2.59 0.91 1.07 0.96 1.18 1.18 1.27 1.22 1.39 (f) Putative N starvation regulators (NF2down NF48up) bZIP1 Cre05.g238250 0.45 1.62 0.61 0.52 0.62 0.79 0.73 0.94 0.99 1.38 (g) Putative arginine-specific regulators (no NF DE) _BLZ9 Cre12.g510200 1.41 2.71 0.51 0.68 0.72 0.78 0.79 0.82 0.85 0.72 Putative AP2 domain TF Cre08.g364400 1.32 2.07 0.82 0.85 0.64 0.84 0.8 0.88 0.94 0.99 TF with PHD zinc finger/SAND domains Cre01.g018650 1.02 1.75 0.72 0.64 0.55 0.9 1.2 1.07 1.05 1.48 HSF2 Cre07.g354500 1.21 1.88 0.99 0.79 0.63 0.9 0.83 0.89 0.95 1.32 99 (Cre02.g110150) transcription factor. Only Cre14.g620850 has been described elsewhere as a N starvation induced gene (NSG17) (Abe et al., 2004). All of these putative transcription factors were downregulated throughout the previous N starvation time-course study (Schmollinger et al., 2014). The role of these putative transcription factors remains to be determined. Many phenotypes occur after six hours of N starvation (i.e. decreases in chlorophyll, robust gametogenic mating activity, and triacylglycerol accumulation), therefore, transcription factors upregulated in the ARG and NF48 transcriptomes, but not NF2 may include regulators of these phenotypes. As expected, within this category I found GSP1 which encodes a well-known regulator of plus gamete sexual development that is upregulated following the activation of gametogenesis (Goodenough et al., 2007). Interestingly, this category is enriched in the RWP-RK family of transcription factors, RWP4, 8, and 12 (Cre03.g149350, Cre04.g218050, Cre01.g004600, respectively). The RWP-RK family also includes known master regulators of N metabolism (NIT2) and gametogenesis (MID1) in C. reinhardtii (Fernández and Matagne, 1986; Camargo et al., 2007; Goodenough et al., 2007). RWP12 and RWP8 were previously suggested to be targets of chloroplast retrograde signaling in response to singlet oxygen production (Wakao et al., 2014). RWP4 was previously identified as an early N starvation upregulated transcription factor with an expression profile correlating with N starvation marker genes encoding glutamine synthetases and L-amino acid peroxidase (LAO1/2) (Gargouri et al., 2015). In addition, this category holds a MYB-like transcription factor (Cre03.g197100), a putative DNA transposase binding protein (Cre04.g228250), and a basal body protein with a putative AP2 binding domain (Cre01.g009650). The MYB-like transcription factor was identified previously by searching for transcription factors that were co-expressed with the TAG synthesis gene DGTT1 and subsequently was demonstrated to be a regulator of lipid remodeling in P starvation (Hidayati et al., 2019). Further characterization of these putative transcription factors will determine whether they regulate late stage N starvation responses that are also found in arginine-fed cultures. Lastly, transcription factors upregulated in the ARG transcriptome but not in either NF2 or NF48 identified four transcription factors: 1) a basic leucine zipper protein (Cre12.g510200), 2) a putative AP2 domain protein (Cre08.g364400), 3) a PHD zinc finger / SAND domain protein (Cre01.g018650), and 4) heat shock transcription factor 2 (HSF2) (Cre07.g354500). Each of these transcription factors has high basal expression in NH4+ and is upregulated ~twofold in arginine. The basic leucine zipper (CrHY5) has been previously associated with light responses, carbohydrate metabolism, and cold stress responses (Romero-Campero et al., 2016; Li et al., 2019). The gene encoding the PHD zinc finger / SAND domain protein may respond to singlet 100 oxygen via chloroplast retrograde signaling as with RWP8 and RWP12 (Wakao et al., 2014). Considering these putative transcription factors are upregulated in the ARG transcriptome and not NF2 or NF48, one of these DNA-binding proteins may play a role in arginine-specific upregulation, however, this requires further studies. 4.3 Conclusions Previous transcriptomic studies have found many N starvation upregulated genes, but they also include many genes indirectly regulated by cellular stress. The utilization of arginine as a derepressive N source arginine allowed for the first transcriptomic inquiry into the direct consequences of N status signaling. The arginine transcriptome showed that genes encoding N assimilation enzymes were constitutively upregulated in arginine-fed cultures (34 out of 49 genes), comparably to N-starved cells (28 out of 49 genes) (Figure 4.3; Table 4.1). This finding fortifies the evidence that arginine is a derepressive N source that triggers the activation of N status signaling and the upregulation of genes encoding N assimilation enzymes. Furthermore, the only genes encoding N assimilation enzymes the were uniquely upregulated in arginine are likely involved in arginine metabolism such as ADI1. Additionally, the upregulation of some plasma membrane N transporters (i.e. DUR3A-C or AMT1) in arginine was comparable to that of long-term N starvation. On the other hand, the unique downregulation only found in long-term N starvation of other plasma membrane N transporters (i.e. AMT3, 6, and 7) that have higher N content suggests that N-sparing mechanisms active in late stage N starvation (Schmollinger et al., 2014) may not be active in arginine-fed cultures. However, the downregulation of overall amino acid biosynthesis, except arginine biosynthesis, was comparable between arginine-fed cultures and N starvation suggesting that N-sparing mechanisms may operate at different levels. The arginine-fed cells downregulated genes encoding the photosynthetic apparatus as in N starvation, suggesting that these genes are responsive to the same N status signaling that regulates N assimilation. The arginine-fed cells shared a common expression profile with long-term N starvation regarding genes encoding the photosynthetic linear electron transport chain, non-photochemical quenching, and tetrapyrrole biosynthesis. In contrast, the genes encoding protein necessary for PSII, PSI, and cytochrome b6f showed an opposite expression profile to that of long-term N starvation whose upregulation may prime cells for re-assembly of the photosynthetic electron transfer chain upon N resupply. Lastly, whereas genes encoding orthologs of A. thaliana chlorophyll degradation proteins were upregulated in in long-term N starvation, they remain mostly unchanged in arginine-fed cultures. Together, these data suggest 101 that the decreases in chlorophyll content in arginine-fed cultures results from downregulation of genes necessary for biosynthesis rather than active degradation. During N starvation the cellular energy demands are decreased which is reflected in the downregulation of genes encoding the mitochondrial electron transport chain. In contrast, arginine cultured cells show only a downregulation of genes encoding Complex II which is likely related arginine metabolism potentially altering cellular fumarate levels considering it would normally use electrons from the conversion of succinate to fumarate. Additionally, the genes encoding the electron carrier cytochrome C are downregulated in arginine-fed cells suggesting that electron flow between Complex III and IV is decreased. These data together with the upregulation of the gene encoding alternative oxidase 1 (AOX1) suggested that oxygen is reduced with less production of ATP indicating that arginine-fed cells are not limited for energy which could be related to the potential production of NAD(P)H during arginine metabolism. The genes encoding many of the proteins involved in the major C assimilation pathways are comparably downregulated in arginine cultures as with N starvation. This suggests that economical TAG production in cells growing in N-replete medium may be achievable through understanding how TAG production becomes increased in arginine-fed cultured cells relative to NH4+. While genes encoding de novo FA synthesis enzymes are downregulated there could still overflow of C through this pathway which could be incorporated in TAGs as the genes encoding the synthesis of the glycerol backbone were significantly upregulated in arginine-fed and N starved cultures. Lastly, the ARG transcriptome suggests that the acetyl groups for FA synthesis may be supplied from citrate produced from fumarate released during arginine catabolism. Interestingly, the genes encoding enzymes for the assimilation of exogenous C in the form acetate were significantly downregulated in arginine-fed cultures comparable with long-term N starvation which suggests that acetate may not be a major contributor to C assimilation in arginine. However, arginine metabolism could not serve as an organic C source when grown heterotrophically indicating that C released from arginine metabolism is redirected elsewhere. The utilization of arginine as the sole N source has received little attention and much is left to be discovered regarding how arginine is taken up into the cell and its subsequent metabolic fate particularly regarding how arginine metabolism bypasses the detection of internal N status and triggers N starvation responses. This chapter reported that the most likely routes for the primary assimilation of N from arginine are through arginine deiminase (ADI1). Future studies of mutants in AOC5, ADI1, and OTA1 within these pathways will help reveal the primary contributors to the utilization of arginine. Lastly, the question of why arginine cannot be used as an organic C source remains open. If citrate metabolism from fumarate feeds into ATP citrate lyase production 102 of acetyl-CoA that can be used for structural C-based intermediates such as lipid biosynthesis, it might be expected that the acetyl-CoA could also serve as an organic C source. However, the significant decrease in the expression of glyoxylate cycle and TCA cycles suggest that arginine-fed cultured cells do rely heavily on available organic C for energy production. Future studies regarding the flow of C through arginine-fed cells will determine the metabolic fate of C derived from arginine catabolism. Removal of the background noise introduced via generic cell stress during N starvation allowed for the curation of a set of transcription factors specific to N starvation that overlap with arginine transcriptomes. Transcription factors unique to N starvation that are linked to the generic stress responses like TAG production were also able to be separated some of which have been described elsewhere. These targets provide a wealth of interesting candidates for future studies, most of which are available in the recently produced C. reinhardtii mutant library (Li et al., 2016). The transcription factors uniquely upregulated within the arginine transcriptome likely contain a positive regulator specific to arginine uptake and metabolism, the disruption of which would be expected to decrease the upregulation of genes identified here as encoding the likely route of arginine metabolism. The utilization of arginine-fed cultures was essential to the discovery of mutants unable to activate N starvation responses (Chapter 5) and studying the arginine transcriptome identified many transcription factors that putatively regulate various facets of N status control. 103 Chapter 5: Forward genetics mutant screens identified NSI1 encoding a glutamine synthetase that is required for activating N starvation responses in C. reinhardtii 5.1 Introduction Breakthrough discoveries of the molecular components regulating N status responses in prokaryotes and fungi were made possible by first establishing derepressive conditions (Mitchell and Magasanik, 1984; Kamberov et al., 1995). In C. reinhardtii, arginine-fed cultures induced canonical N starvation responses including the upregulation of genes encoding proteins involved in N scavenging/salvage and was established as a derepressive N source (Chapter 3 and 4). Therefore, C. reinhardtii becomes an ideal model for studying N status regulation in a photosynthetic eukaryote as there is a high degree of conservation with higher plant N assimilation proteins (Galván et al., 2006). The successful mutant screen described in this chapter utilized two strategies. The first one is the novel use of NIT1 as a N starvation-specific marker that is expressed independently of NIT2, the master transcriptional activator for NO3--responsive genes. The second is the use of a toxic N source analog to probe whether the relevant N starvation-inducible N assimilation pathways are upregulated, resulting in its uptake and adverse effects. Previously, methylammonium (MA), a toxic analog of NH4+, has been used in C. reinhardtii to identify mutations disrupting genes encoding NH4+ transporters. Four out of eight genes encoding NH4+ transporters are upregulated in arginine-fed conditions (Chapter 4). Therefore, MA supplementation to arginine-fed cultures results in arrested cell growth due to the uptake and assimilation of MA (Arst and Cove, 1969; Kim et al., 2005). AMT4 is the predominant NH4+ transporter gene expressed in arginine-fed cultures, therefore, it is not surprising that Kim et al., (2005) only found mutations in this gene when screens were performed using arginine-feeding supplemented with MA. Thus, in an arginine-fed culture where N starvation responses are derepressed, MA-resistance indicates either mutations in AMT4 or in genes that encode the necessary factors regulating N starvation transcriptional responses in C. reinhardtii. My forward genetic screen identified several mutants, displaying near complete insensitivity to N starvation. Five of the six mutants identified were found to disrupt the same gene, Nitrogen Starvation Insensitive 1 (NSI1), encoding a novel type II glutamine synthetase (GS) (E.C. 6.3.1.2), annotated as GLN4. This led to my working hypothesis that glutamine or glutamate may serve as a key metabolite whose cytosolic concentration indicates the intracellular N status 104 in photosynthetic eukaryotes. Both metabolites directly interact with most GS proteins, supporting NSI1/GLN4 as a putative detector of N status in C. reinhardtii. Some GS proteins are known for regulatory functions. The best example is the type I GS in B. subtilis that affects the transcriptional regulation of N assimilation/starvation genes in response to the intracellular N status (Gunka and Commichau, 2012; described in Chapter 1). Recently, a regulatory role was discovered for the type II GS of Fusarium (Wagner et al., 2013; Brauer et al., 2020) and putatively for a GSI-like enzyme found in plants (Silva et al., 2015). This chapter describes the identification and characterization of a novel type II GS in C. reinhardtii that serves an essential role in N starvation responses including transcriptional regulation of N starvation marker genes and gametogenesis. 5.2 Results and Discussion 5.2.1 NIT1 promoter-reporter activity is N starvation-dependent in a nit2-null background. In order to screen for defects in N starvation transcriptional regulation in a high-throughput manner, an easily observable reporter gene activated by N starvation-specific regulation must be developed. My previous studies in Chapter 3 and 4 determined that the NIT1 gene is upregulated in response to N starvation in the absence of NIT2, despite its well-known regulation by the NIT2 transcription factor in response to NO3- availability (Quesada et al., 1993; Camargo et al., 2007). Previously, NIT1 promoter-reporter constructs have been used in screens to identify regulatory elements controlling NH4+ repression of NIT1 expression in a wild-type NIT2 background (González-Ballester et al., 2005; Zhang and Lefebvre, 1997) but have never been used in nit2 background. This led me to the reutilization of a NIT1 promoter-reporter system for the forward genetics mutant screen described in this chapter. The NIT1 promoter-reporter system employed here is the one used by Zhang and Lefebvre (1997) where the NIT1 promoter was conjugated to the RSP3 coding sequence and the resultant construct (NIT1pro::RSP3) was introduced into a rsp3 mutant. The RSP3 gene encodes the flagellum protein, Radial Spoke Protein 3, which is essential for flagellum movement and therefore swimming (Luck et al., 1977). Using this system, the activation of the NIT1 promoter can be easily monitored with a dissecting microscope by the restoration of flagellar motility (Figure 5.1). To generate a host strain with the NIT1 reporter in a nit2-null, the far1 mutant (CC-3352; far1; NIT1pro::RSP3; rsp3; NIT2) was mated with a derivative of the 137c background (nit1; nit2; nic7), where the nic7 mutation is necessary for the use of NIC7 as a selectable marker for random 105 Figure 5.1 – Utilization of a NIT1 promoter-driven conditional swimming reporter allowed for the identification of mutants putatively disrupted in N starvation regulation. The NIT1 promoter-reporter lines conferring conditional swimming were transformed with a NIC7 plasmid complementing the nic7 mutation which conferred resistance to the nicotinamide analog 3-acetylpyridine (AP). The AP resistant colonies were grown for three days on NH4+-TAP agar plates and then resuspended in 150 µL of NH4+-TAP or NF-TAP in a 96-well plate. Following overnight incubation under low light (30 μmol m−2 s−1), cells were observed under a dissecting microscope for swimming behavior in NF-TAP. 106 insertional mutagenesis (Figure 5.1). From the resultant progeny, the single best nic7; nit2 strain was chosen as the library host (1b7), which reproducibly displayed little to no reporter activity in fresh NH4+-TAP and robust reporter activity (swimming) when left overnight in NF-TAP medium (nic7; NIT1pro::RSP3; nit2; rsp3). To hit most of the genes encoded in the C. reinhardtii genome at least once, 10,134 AP resistant mutants were generated. The entire collection was examined for N starvation-dependent swimming after overnight incubation in N-free media (NF-TAP) (Figure 5.1). The swimming-based screen collected 390 mutants (3.85% screen rate) that did not swim in NF-TAP (named as ns, non-swimmers). This primary screen may also collect flagellum mutants because the flagellum consists of at least 360 proteins and its correct assembly requires orchestrated delivery of cargo running through the flagellar axis (Pazour et al., 2005; Jeanneret et al., 2016). Therefore, any mutants with obvious defects in the number of flagellum or flagellum length were removed as a false positive, leaving a collection of 74 ns mutants (0.73% screen rate). 5.2.2 N starvation marker genes are not upregulated in ns mutants resistant to methylammonium. The primary ns mutant collection may still include false positives due to the use of an indirect reporter system whose malfunction can cause a positive phenotype. To select true mutants with defective N starvation responses, a secondary screen was done focusing on phenotypes unique to N starvation conditions, gametogenesis and the upregulation of genes involved in N scavenging/salvage (Sager and Granick, 1953; Schmollinger et al., 2014; Chapter 3). Gametogenesis can be readily examined by flagellar agglutination; however, the ns mutants were defective in swimming and were therefore expected to show variable levels of flagellar agglutination irrespective of cells ability to turn on gametogenesis. Therefore, due to this expected variability, my secondary screen instead centered on MA-resistance as an indicator of the failure to upregulate N scavenging/salvage genes, described in Section 5.1. Considering that mutations may result in the partial upregulation of N scavenging/salvage genes, the screen needed to provide a quantitative measure of cell stress in order to increase its sensitivity. Therefore, the secondary screen for the MA-resistance phenotype of cellular stress level was examined using the maximum photosynthetic efficiency measure, indicated by Fv / Fm (Baker, 2008). To provide a robust photosynthetic signal for the detection of cellular stress, cultures were concentrated and grown on arginine TAP agar plates with and without supplementation of MA and assessed directly from the plates after 48 hours. This secondary screen identified eight of the 74 ns lines as resistant to MA (Table 5.1). Analysis of two N Table 107 5.1. Mutants resistant to methylammonium in arginine-fed cultured ns mutants were putatively disrupted in the regulation of N starvation marker gene, AMT4. Arg (Fv / Fm) Arg + MA (Fv / Fm) (a) Control lines (n = 5) 137c 0.760 ± 0.004 0.475 ± 0.040 Library parent 0.767 ± 0.022 0.440 ± 0.060 amt4-null (CC-4047) 0.737 ± 0.008 0.707 ± 0.015 (b) ns MAR mutants (n = 5) ns102 (nsi1.1) 0.752 ± 0.027 0.689 ± 0.025* ns103 0.744 ± 0.017 0.660 ± 0.033* ns106 0.765 ± 0.023 0.733 ± 0.018* ns119 (nsi1.2) 0.767 ± 0.028 0.727 ± 0.012* ns133 0.761 ± 0.032 0.643 ± 0.040* ns141 (nsi1.3) 0.751 ± 0.052 0.735 ± 0.010* ns152 (nsi1.4) 0.769 ± 0.022 0.736 ± 0.018* ns172 (nsi1.5) 0.746 ± 0.033 0.702 ± 0.017* (c) Other mutants (n = 20) Pool 1 0.764 ± 0.017 0.551 ± 0.099 Pool 2 0.758 ± 0.014 0.547 ± 0.121 Pool 3 0.758 ± 0.019 0.511 ± 0.119 Pool 4 0.749 ± 0.020 0.539 ± 0.106 Pool 5 0.759 ± 0.016 0.533 ± 0.138 Cell stress was measured via in vivo chlorophyll fluorescence of Fv / Fm in cells replica plated on agar plates and incubated under low light (30 μmol m−2 s−1) for 48 hours with 2.5 mM Arg as the sole N-source and supplementation with 0.1 mM MA. The control lines (a) shown are from the same plate as the ns MAR mutant measurements. The other mutants (c) are five pools of 20 randomly selected mutants that do not display the MAR phenotype to demonstrate the variance among replicates. Significant differences (marked with an asterisk) between ns mutants and the library parent were found when calculated by a Student’s t-test (p < 0.05). 108 Figure 5.2 – Five nsi1 mutants with defective N starvation marker gene regulation were disrupted in the same region. (A) N starvation marker gene qPCR screening of MA resistant ns mutants from samples grown to mid-log phase in NH4+-TAP that were resuspended in N-free TAP for two hours and compared to wild-type expression. (B) Mapping of the nsi1 mutants arranged from smallest deletion to largest (phytozome.net). A B 109 starvation marker genes, AMT4 and GLN3, in cells starved of N for two hours showed that six of the eight MA-resistant ns strains did not upregulate these genes (Figure 5.2a). All six of these ns mutants showed no flagellar agglutination after six hours in N-free media, indicating defects in gametogenesis (data not shown). Taken together, these six ns mutants were considered true N starvation signal transduction mutants and were renamed N starvation insensitive (nsi; Table 5.1). To identify the disrupted genes of the six nsi mutants, either flanking sequence tag analysis or whole genome resequencing were performed revealing that the lesions in five of the nsi mutants all resided in the same region on chromosome 3 (Figure 5.2b). The only gene that was disrupted in all five mutations was glutamine synthetase 4 (GLN4; nsi1; Cre03.g207250) (Figure 5.2b). To test whether GLN4 is required for N starvation responses, two independent insertional mutants of GLN4, available from the Chlamydomonas Library Project (CLiP; Li et al., 2016), were examined with each showing no upregulation of AMT4 or GLN3 (Figure 5.3). In summary, my genetic screen suggests that GLN4 likely encodes an essential factor for inducing N starvation responses in C. reinhardtii. 5.2.3 Complementation of gln4 restored upregulation of N starvation markers. To further characterize the nsi1 phenotypes caused by the disruption of GLN4, genetic complementation of nsi1 with a wild type copy of GLN4 was necessary. A complementation construct was prepared by cloning the GLN4 cDNA into a vector harboring a constitutive promoter, HSP70A/RBCS2 (AR; Schroda et al., 2000). The resultant construct was co-transformed with a Hygromycin resistance (HYGR) cassette and more than 160 transformants were collected, however, none of them showed recovery of swimming in any culture conditions. Therefore, these 160 transformants were screened by PCR for the presence of the GLN4 transgene which identified 14 co-transformants. Two of them showed a recovery of MA sensitivity, and qRT-PCR analysis confirmed that they expressed the GLN4 transgene and upregulated the N starvation marker gene, AMT4, in response to N starvation (Comp1 and Comp2 in Figure 5.4). However, these two complemented strains only showed partial recovery of AMT4 upregulation, which was suspected to be caused by the relatively low expression of the GLN4 transgene relative to endogenous GLN4 expression in a wild-type strain (137c; Figure 5.4b). 110 Figure 5.3 – Mutations in gln4 ordered from a public collection have defective N starvation marker gene expression. N starvation marker gene qPCR screening of strains with mutations in GLN4 ordered from a public collection (Chlamydomonas Library Project (CLiP); chlamycollection.org; Li et al., 2016). Samples were grown to mid-log phase in NH4+-TAP and were resuspended in N-free TAP for two hours. The relative expression was compared with the wild-type expression of the mutant library parent (n = 1). The CLiP 126748 mutant disrupts in the 5’ end of GLN4 whereas CLiP 197957 effects the 3’ end. 111 Figure 5.4 – Stronger gln4 complementation of N starvation marker gene expression was observed in the progeny of B66 complement #2 backcrossed with a wild-type strain. Cells grown to mid-log phase in TAP were harvested and resuspended in N-free TAP for two hours. A) The log fold change in expression of AMT4 was compared among the original nsi1.1 complemented lines (C1 and C2) and backcrossed progeny of the complemented lines that have the nsi1.1 deletion (gln4) and complementation (gln4;GLN4C). B) Expression of GLN4 in 2 h N-free cultures was compared relative to that of the wild-type strain CC-125. Progeny from the C2 backcross were selected for further study (C2-gln4-p1 and C2-GLN4C-p3). The sample size was n = 1 for all progeny and n = 3 for 137c, gln4, Comp1, and Comp2. A B 112 The Comp1 and Comp2 strains also showed very weak mating activity, however, they were able to produce viable progeny from a backcross to the mutant library parental strain (nit1; nit2; nic7). From the backcross, the progeny carrying the nsi1.1 deletion (NIC7) showed a perfect co-segregation of the wild-type MA sensitivity with the GLN4 transgene (Table 5.2). Additionally, AMT4 was upregulated between 25- and 58-fold or 1150- and 1800-fold in response to N starvation among the complemented nsi1.1 progeny of Comp1 and Comp2, respectively (Figure 5.4). In contrast, the non-complemented nsi1.1 progeny showed no significant upregulation of AMT4 (between 0.8 and 2-fold; Figure 5.4). The N starvation-induced upregulation of AMT4 in the Comp2 progeny was higher than in the Comp1 progeny and was comparable to the wild-type upregulation of AMT4. The Comp2 progeny were chosen for all future studies based on stronger complementation phenotypes. Of the Comp2 progeny, C2-GLN4C-p3 and C2-gln4-p1 strains (Figure 5.4) were selected for further analysis, referred to as gln4;GLN4C;nit2 and gln4;nit2, respectively. Additionally, these strains do not possess the reporter genes used for the primary screen alleviating any unnecessary complications in analysis (i.e., wild-type RSP3 and no NIT1pro::RSP3 reporter transgene). In summary, the complementation of nsi1 was initially difficult, but full complementation was successfully observed in the backcrossed progeny, confirming that GLN4 is essential to the regulation of the N starvation responses. 5.2.4 NSI1/GLN4 belongs to a chlorophyte-specific family including non-canonical glutamine synthetase In the C. reinhardtii genome, five GS genes are found, including two chloroplast localized type II GS2 homologs (GLN2 and GLN3) and a single cytosol localized type II GS1 homolog (GLN1). In contrast to these well characterized type II GS homologs, the other two GS homologs, including a type I homolog (GLN5) and a divergent type II homolog (GLN4), remain uncharacterized. I reconstructed the phylogeny of the type II GS subfamily with the inclusion of GLN4 to determine the conservation and lineage of GLN4. The phylogeny revealed a separate clade containing GLN4 and its homologs from chlorophyte species which shared a common ancestry with the type II cytosolic GS1 subfamily of chlorophytes (Figure 5.5). Strong statistical support of the sister relationship between the GLN4-clade and the type II GS1 clade suggests that the GLN4 clade is derived from the type II cytosolic GS1. 113 Table 5.2 - Progeny of complement 2 backcrossed to wild-type showed 1:1 segregation of methylammonium resistance Arg (Fv / Fm) Arg + MA (Fv / Fm) (a) Control lines (n = 5) 137c 0.741 ± 0.048 0.520 ± 0.087 Library parent 0.766 ± 0.020 0.447 ± 0.062 amt4-null (CC-4047) 0.745 ± 0.052 0.689 ± 0.034* nsi1.1 (ns102) 0.777 ± 0.015 0.736 ± 0.018* nsi1.1 Complement 2 0.785 ± 0.086 0.525 ± 0.052 (b) no nsi1.1 deletion (n = 16) 0.760 ± 0.012 0.519 ± 0.059 (c) with nsi1.1 deletion Δgln4 (n = 6) 0.738 ± 0.035 0.677 ± 0.044* Δgln4-T(GLN4) (n = 8) 0.759 ± 0.011 0.514 ± 0.046 **Cell stress was measured via in vivo chlorophyll fluorescence of Fv / Fm in cells replica plated on agar plates and incubated under low light (30 μmol m−2 s−1) for 48 hours with 2.5 mM Arg as the sole N-source and supplementation with 0.1 mM MA. The MAR results from the first thirty progeny from the backcross of nsi1.1 Complement 2 with wild-type were pooled by genotype (b) and (c). The MAR resistance phenotype segregated 1:1 with the nsi1.1 deletion of gln4 in the absence of complementation by T(GLN4). The control lines (a) shown are from the same plate as the measurements of the progeny to account for plate to plate variation. Significant differences (marked with an asterisk) between ns mutants and the library parent were found when calculated by a Student’s t-test (p < 0.05). 114 Figure 5.5 – GLN4 homologs form a clade of type II glutamine synthetases found in the core Chlorophytes. Maximum likelihood phylogeny of the GS superfamily across domains supports the distinct lineage of GLN4 homologs (red bracket) within chlorophytes. Maximum likelihood trees were generated from full-length amino acid alignment of 220 sequences from 116 organisms with major clades collapsed. The consensus tree out of 1000 bootstrap trees is shown. The numbers at critical nodes show %bootstrap in support of clades. 115 Type II GSs are known to form decameric structures composed of two pentameric rings placed on top of one another to form an inverted donut (Unno et al., 2006; Krajewski et al., 2008; He et al., 2009). Each monomeric subunit is composed of a smaller N-terminal domain (~100 amino acids) and a larger C-terminal domain (~250 amino acids). The catalytic cleft of the type II GSs is formed between two neighboring subunits within the same pentameric ring whereby the active site is comprised of the N-terminal (beta-grasp) domain from one subunit and the C-terminal (catalytic) domain of the other (Eisenberg et al., 2000). The two pentameric rings are held together by the C-terminal helices of each subunit, known as the ‘helical thong’ (α9 in Figure 5.6), which is inserted into the hydrophobic hole of the corresponding subunit on the opposite pentameric ring (Yamashita et al., 1989). The GS monomers are held together predominantly by hydrophobic interactions and hydrogen bonding (Almassy et al., 1986). According to the published type II GS structure from maize (PDB: 2d3a), a large insertion of ~50 residues is found within the catalytic domain of GLN4, which tentatively would render the protein incapable of catalyzing the conversion of NH4+ and glutamate to glutamine (Figure 5.6). In support of an absence of GLN4 catalytic activity, conserved residues contributing to the substrate binding pockets conserved between the type I and II GSs were not conserved in GLN4 (5 out of 15 residues; Figure 5.6). Perhaps the most important of which is the lack of residues Asp-56 and Gln-297, conserved among plant GSs, which bind NH4+ and prevent glutamate from entering the active site in addition to the absence of two other conserved NH4+ binding residues (green highlights in Figure 5.6) (Unno et al., 2006). Taken together, the GLN4 amino acid sequence suggests that it may not bind NH4+. Diversification of the GLN4 sequence extends beyond the lack of NH4+ binding sites. There are three Mn2+ ions (Mn-n1, Mn-n2, Mn-3) that facilitate the catalytic activity of GSs, however, GLN4 lacks at least one key binding residue for each of the three conserved Mn2+ binding sites (orange highlights in Figure 5.6), suggesting that the catalytic activity of GLN4 is likely lower than that of typical type II GSs, if there is any. Also necessary within the catalytic cleft are binding sites for ATP and glutamate for which GLN4 possesses 2 of the 6 conserved ATP binding residues and 3 of the 5 conserved glutamate binding residues (pink and cyan highlights, respectively in Figure 5.6). All in all, these data suggest that the catalytic function of GLN4 is compromised and NH4+ is not bound whereas the other substrates of GS may be able to bind. 116 Figure 5.6 – GLN4 lacks key conserved residues and has a large insertion within the catalytic domain. Conserved residues as indicated in Eisenberg et al., 2000 and Unno et al., 2006 are highlight in green (NH4+ binding), orange (Mn2+ binding), pink (ATP binding), cyan (Glu binding), and blue (intersubunit stability). The red highlights indicate conserved residues and the red text indicates similar residues within a group whereas the blue boxes indicate similarity across groups. The The tracks above and below the alignment show the predicted secondary structure using homology-based protein models for cytosolic A. thaliana GLN1.1 and C. reinhardtii GLN4 based on homology to the Zea mays crystal structure with bound ligands (SMLT ID: 2d3a.1) on the SWISS-MODEL site (https://swissmodel.expasy.org/interactive) (Waterhouse et al., 2018; Unno et al., 2006). 117 The GLN4 peptide sequence also suggests that it may not form a traditional decameric structure. A C-terminal extension of 136 residues in GLN4 (not shown in the alignment Figure 5.6) could alter the helical thong and interfere with the expected interaction between the two pentameric rings. Furthermore, GLN4 possesses only one of the three conserved residues involved in intersubunit stability (blue highlighted residues in Figure 5.6). Taken together, the bioinformatic data suggest that the GLN4 class of type II GS1s represents a highly divergent GS, conserved in chlorophytes, that may not form the predicted decameric structure or bind the substrate NH4+. The partial retention of glutamate and ATP binding residues suggests that GLN4 could still interact with these molecules or other molecules with similar structures. 5.2.5 Disruption of GLN4 prevents N starvation-induced gene regulation and gametogenesis N starvation in C. reinhardtii elicits various physiological responses, including gametogenesis, cell cycle arrest following a final division, decrease in chlorophyll content, and increased storage C biosynthesis in the form of triacylglycerols and starch (Sager, 1954; Siersma and Chiang, 1971; Martin and Goodenough, 1975; Bulté and Wollman, 1992; Weers and Gulati, 1997). To assess the biological role of NSI1/GLN4, the gln4;nit2 and gln4;GLN4C;nit2 strains were examined for the known N starvation responses. The gln4;nit2 double mutants were unable to upregulate the selected set of seven N starvation-induced genes or undergo gametogenesis (Figures 5.7 and 5.8a). In contrast, gln4;nit2 and gln4;GLN4C;nit2 were indistinguishable in the other N starvation phenotypes, including the reduction in chlorophyll content within 48 hours, the doubling in cell number within 24 hours, and lipid accumulation within 72 hours (Figure 5.8b-e). However, later in N starvation, the gln4;nit2 strain showed accelerated chlorophyll loss, which coincided with notable bleaching of the cultures and a loss of cell viability when compared to the gln4;GLN4C;nit2 strain (Figure 5.8e,f). Likewise, in arginine-fed cultures, the gln4;nit2 double mutants did not show gametogenesis or wild-type upregulation of N starvation marker genes whereas decreases in chlorophyll content and increases in lipid accumulation appeared unaltered, compared to gln4;GLN4C;nit2 (Figures 5.9 and 5.10; Table 5.3). These data support the critical role of GLN4 for the activation of canonical N starvation responses and suggest that a subset of N starvation phenotypes such as chlorophyll degradation and lipid accumulation may be controlled by generic stress signals or redundantly controlled by both N starvation signal and generic stress signals. 118 Figure 5.7 – gln4 mutants showed impaired regulation of N starvation marker genes. Mean values are represented by solid circles with a line indicating the 95% confidence interval. Three biological replicates were performed for each strain and are presented as open circles. The dashed line represents the NH4+ expression level from each biological replicate that was used for normalization. The 137c (nit1;nit2) and 21gr (NIT1;NIT2) strains were used for controls. Significance was assessed using a Tukey-HSD test to compare all possible combinations of means and is represented by letters corresponding to groups of not significantly different pairs (n = 3). 119 Figure 5.8 – gln4;nit2 mutants cannot activate gametogenesis and showed decreased cell viability during N starvation whereas other N starvation responses are not interrupted. N starvation responses in gln4;nit2 and gln4;GLN4C;nit2 were assessed: A) gametogenesis, B) cell doubling, C) lipid accumulation, D and E) decreased chlorophyll content. The survival of cells during N starvation was tested by assessing cell viability (E) by measuring the proportion of live cells remaining via staining with Evan’s blue. Student’s t-tests were used to assess significant changes relative to wild-type for mating efficiency, chlorophyll quantity, and cell viability (p < 0.05) (n = 3). WT gln4 GLN4C NH4+ NF A B C F E D 120 Figure 5.9 – Arginine-fed gln4;nit2 mutants showed impaired regulation of N starvation marker genes. Mean values are represented by solid circles with a line indicating the 95% confidence interval. gln4;GLN4C and gln4 were grown to mid-log phase in NH4+ (8 mM) and transferred to Arg (2 mM) and incubated for two hours. 137c controls grown to mid-log in NH4+ (8 mM) and incubated in NF or Arg (8 mM) for 2 hours for are presented for comparison. Three biological replicates were performed for each strain and are presented as open circles. The dashed line represents the NH4+ expression level from each biological replicate that was used for normalization. Significance was assessed using a Tukey-HSD test to compare all possible combinations of means and is represented by letters corresponding to groups of not significantly different pairs (n = 3). 121 WT Δgln4 GLN4C Figure 5.10 – Arginine-fed gln4;nit2 mutants showed wild-type chlorophyll decreases and lipid accumulation. N starvation responses previously found to occur in arginine-fed cultures were assessed in gln4;nit2 and gln4;GLN4C;nit2: A) decreased chlorophyll content, B) gametogenesis, and C) lipid accumulation. Student’s t-tests were used to assess significant changes relative to wild-type for mating efficiency and chlorophyll quantity (p < 0.05) (n = 3). Table 5.3 – Decreases in chlorophyll content of arginine-fed gln4;nit2 and gln4;GLN4C;nit2 strains was comparable to wild-type. NH4+ Arginine Growth rate (µ) 137c 33.41 ± 1.93 27.45 ± 0.89* gln4 31.84 ± 3.64 23.32 ± 3.37* gln4;GLN4C 31.36 ± 1.46 22.92 ± 5.09* ** Samples were harvested at mid-log phase of growth on either 8 mM NH4+-TAP or 2 mM Arginine-TAP. Student’s t-tests were used to assess significant changes (p < 0.05) the (a) is used for significance relative to NH4+ and the (b) is for significance relative to wild-type (n = 3). A B C 122 5.2.6 GLN4 is not involved in NIT2-dependent NO3--responsive gene regulation To test whether the master regulator of NO3- assimilation, NIT2, requires GLN4 for its regulation of NO3--specific responses, the nsi1.1 mutation was introduced into a NIT2 wild-type background by mating the gln4;GLN4C;nit2 with strain CC-1691 (NIT1;NIT2). Three nsi1.1 (gln4;NIT2) and three nsi1.1;GLN4C (gln4;GLN4C;NIT2) progeny were then tested for the induction of N starvation marker genes following a two hour incubation in NF-TAP. The two NIT2 targets (NIT1 and NRT2.1) were upregulated in the gln4 single mutant, indicating that NIT2 activates its targets independent from GLN4 (Figure 5.7). The upregulation of NO3- assimilation genes by NIT2 in N-free conditions is expected as sub-micromolar levels of NO3- were reported to be present in most media and were shown to trigger NIT2-dependent NO3--inducible transcriptional regulation (Llamas et al., 2002; Camargo et al., 2007). Nonetheless, the expression of NIT1 and NRT2.1 during N starvation in gln4 was less than that of gln4;GLN4C, but not significantly so, (44 vs. 538-fold for NIT1 and 54 vs. 186-fold for NRT2.1), suggesting that NIT2 and GLN4-dependent pathways control these genes in parallel. Previous studies have shown that nit2 mutants are still capable of slow growth in NO3- which is observed as a pale green phenotype rather than complete bleaching found in nit1 mutants (Nichols and Syrett, 1978; Galván et al., 1992). To directly assess whether GLN4 participates in the upregulation of NO3- assimilation genes in response to NO3-, their gene expression was examined in gln4 single mutants and their gln4;GLN4C counterpart following incubation in NO3--TAP medium for two hours. NIT1 and NRT2.1, were significantly upregulated in the gln4 single mutant as in the gln4;GLN4C and 21gr strains (Figure 5.11). In contrast, DUR3A and LAO1 showed little to no upregulation in any strain tested which is consistent with their role in urea and amino acid assimilation and not NO3- assimilation. However, the AIH2, AMT4, and GLN3 genes did show significant upregulation in 21gr and gln4;GLN4C but not gln4. This upregulation may reflect the transition period from NH4+ to NO3- metabolism during which time the cells briefly experience low N status as the NO3- assimilation machinery is being upregulated and synthesized. In this scenario, AIH2, AMT4, and GLN3 would be expected to return to NH4+-TAP basal levels following a longer NO3- incubation which will be tested in future studies. In toto, the contribution of GLN4 to the upregulation of NO3- assimilation genes during growth with NO3- appears to be minimal if at all. 123 Figure 5.11 – gln4 single mutants showed wild-type regulation of NIT2-dependent genes in NO3-. Cells were grown to mid-log phase in 8 mM NH4+-TAP and transferred to 4 mM NO3- for two hours prior to harvesting RNA. Mean values are represented by solid circles with a line indicating the 95% confidence interval. 21gr was used as a NIT2 wild-type control. Three biological replicates the NH4+ expression level from each biological replicate that was used for normalization. Significance was assessed using a Tukey-HSD test to compare all possible combinations of means and is represented by letters corresponding to groups of not significantly different pairs (n = 3). 124 The lack of upregulation in N starvation marker genes encoding N scavenging/salvage genes predicts that gln4 mutants will show defective growth on alternative N sources. Analysis of growth with arginine as the sole N source found that the doubling time of the gln4;nit2 double mutant was longer by >2-fold relative to gln4;GLN4C;nit2 and the 137c control (Figure 5.12a, b; Table 5.4). Likewise, the doubling time of the gln4 single mutant grown with arginine was >2-fold longer when compared to gln4;GLN4C (Figure 5.12c; Table 5.5). These data suggest that the N starvation-induced genes upregulated in arginine-fed cultures are necessary for full-scale arginine-dependent growth. 5.2.7 Transcription analysis reveals that GLN4 regulates a majority of N starvation-induced genes. Previously, N starvation was shown to affect the expression of one third of all genes, however, how many of those genes are directly regulated by the absence of a preferred N source, the detection of low N status, or the generic stress imposed by the lack of N is not known. In Chapter 4, the absence of a preferred N source and the lack of N were compared using transcriptome analysis of arginine-fed or N-starved cells. Here, the transcriptomes of gln4;nit2 and gln4;GLN4C;nit2 were analyzed to distinguish the direct targets of GLN4-dependent regulation from the generic stress-induced genes that would be upregulated in the absence of GLN4. To determine the extent of the impact that GLN4 has on the transcriptome during N starvation the top 200 upregulated and top 200 downregulated DEGs (adj. p-value < 0.05) in gln4;GLN4C;nit2 after two hours of N starvation were collected and compared with the gln4;nit2 samples. Of the 200 genes examined, the expression remained unaltered in the gln4;nit2 samples for of all but three upregulated genes suggesting a lack of N-starvation induced regulation (Figure 5.13). This preliminary analysis indicates that both up- and downregulated genes responding to N starvation require a functional GLN4 protein, suggesting a critical role of GLN4 upstream to the expected network of N starvation-specific transcriptional regulators. 125 Figure 5.12 – Arginine growth of gln4 mutants is reduced compared to wild-type strains. Growth curves of gln4;nit2 and gln4;GLN4C;nit2 mixotrophic cultures in a) NH4+ (8 mM) and b) Arg (2 mM) measured as optical density at 720 nm on a log2 scale. c) gln4 and gln4;GLN4C growth curves in NH4+ (8 mM) and Arg (2 mM). Error bars are standard deviation from two or more independent experiments. A B C 126 Table 5.4 – Arginine-fed growth of the double mutant gln4;nit2 was impaired relative to wild-type. NH4+ Arginine (a) Growth rate (µ) 137c 0.086 ± 0.03 0.05 ± 0.01a gln4;nit2 0.081 ± 0.009 0.024 ± 0.011ab gln4;GLN4C;nit2 0.078 ± 0.007 0.052 ± 0.006a (b) Doubling time (h) 137c 8.05 ± 0.09 13.33 ± 1.59a gln4;nit2 8.61 ± 0.08 29.60 ± 5.80ab gln4;GLN4C;nit2 8.86 ± 0.08 13.21 ± 2.81a ** Student’s t-tests were used to assess significant changes (p < 0.05) (n = 2) the (a) is used for significance relative to NH4+ and the (b) is for significance relative to wild-type. Table 5.5 – Arginine-fed growth of the gln4 single mutant was impaired relative to gln4;GLN4C. NH4+ Arginine (a) Growth rate (µ) gln4 0.049 ± 0.006 0.023 ± 0.001ab gln4;GLN4C 0.050 ± 0.005 0.037 ± 0.001a (b) Doubling time (h) gln4 14.39 ± 1.55 30.01 ± 1.76ab gln4;GLN4C 13.96 ± 1.34 18.97 ± 0.42a ** Student’s t-tests were used to assess significant changes (p < 0.05) (n = 2) the (a) is used for significance relative to NH4+ and the (b) is for significance relative to gln4;GLN4C. 127 Figure 5.13 – gln4;nit2 double mutants showed impaired regulation of hundreds of N starvation inducible genes. Transcriptomes for mid-log phase NH4+ grown cells harvested and cultured in either NH4+ - TAP or N-free - TAP for two hours were compared between gln4;nit2 and gln4;GLN4C;nit2 strains. The top 200 up- or downregulated genes with an adjusted p value < 1E-5 from the gln4;GLN4C;nit2 strain were directly compared to gln4;nit2 (A and B), respectively. The shaded areas of the graph represent genes that were not up- or downregulated in gln4;nit2 but were in gln4;GLN4C;nit2. Points that fall on the line are regulated the same in gln4;nit2 as in gln4;GLN4C;nit2. Top 200 upregulated genes Top 200 downregulated genes 128 5.3. Conclusions The screen of C. reinhardtii using derepressive conditions to find regulators of N starvation transcription identified novel mutants of which many were disrupted in a previously uncharacterized GS (GLN4). The disruption of GLN4 in nsi1 mutants resulted in a drastic loss of N starvation marker gene regulation for both up- and downregulated genes, suggesting a central role in N starvation signal transduction. As described earlier, the use of arginine as a derepressive N source provides a critical tool to analyze N starvation responses without growth arrest. The identification of NSI1/GLN4 opens the door towards future studies into the molecular mechanisms of N status detection and the biological roles of N status regulation. While the disruption of GLN4 abolished gametogenesis and the regulation of N starvation marker genes in both N-free and arginine conditions, it did not affect some physiological responses such as the decrease in chlorophyll and increase in TAGs. The N starvation phenotypes unaffected in gln4 mutants are putatively generic stress responses to nutrient deprivation rather than N starvation-specific responses. In support of this, the physiological responses of chlorophyll decreases and TAG biosynthesis are found during other macronutrient starvation regimes, namely sulfur and phosphorus deprivations (Wykoff et al., 1998; Çakmak et al., 2014). However, decreases in chlorophyll and increases in TAG were also found in arginine-fed cultures, suggesting that these responses can be uncoupled from cell stress and growth arrest. Therefore, arginine-fed cultures also provide a platform for dissecting the regulation of these responses in addition to the derepression of N starvation-specific responses. GS, one of the oldest enzymes, catalyzes the first step in the primary route of inorganic N assimilation, the ATP-dependent condensation of NH4+ with glutamate which yields the glutamine necessary for the synthesis of all other essential nitrogenous compounds (Elliott, 1951; Webster, 1953; Pesole et al., 1991; Kumada et al., 1993). GS activity plays another critical role, converting cytosolic NH4+ produced from photorespiration and nucleic/amino acid degradation to non-toxic, organic N (Lea and Miflin, 2018). Therefore, GS performs essential roles in cellular N metabolism. The GS superfamily includes three classes, type I, II, and III, that were previously thought to be uniquely distributed in prokaryotes, eukaryotes, and cyanobacteria, respectively. More recently, the three GS classes have been found across the three domains of life, suggesting that the GS superfamily diverged prior to the emergence of eukaryotes (Kumada et al., 1993; Reyes and Florencio, 1994; Brown and Doolittle, 1997; Mathis et al., 2000; Robertson and Tartar, 2006; Silva et al., 2015). In photosynthetic eukaryotes, the major catalytic GS proteins are type II enzymes which are further subdivided into GS1 (cytosol) and GS2 (plastid) which share a high 129 degree of amino acid conservation but differ by molecular mass whereby the plastid isoenzyme is larger (Forde and Cullimore, 1989). Angiosperms only have one gene encoding the chloroplast isoenzyme of GS whereas a small gene family encodes multiple cytosolic GS isoenzymes (Sechley et al., 1992; Lam et al., 1996; Woodall et al., 1996). Phylogenetic analysis supports the hypothesis that the cytosolic and chloroplast isoenzymes are the result of a gene duplication prior to the diveregence of monocots and dicots (Coruzzi et al., 1989; Robertson et al., 1999). Unlike the gene duplication event in angiosperms, the GS2 of chlorophytes and early diverging streptophytes is hypothesized to have been obtained from eubacteria in a horizontal gene transfer event that occurred after the divergence of primary photosynthetic groups (Chen and Silflow, 1996; Ghoshroy et al., 2010). The comparison of GLN4 homologs to the GS superfamily revealed many important differences that led to the hypothesis that GLN4 cannot catalyze the reduction of NH4+ and glutamate to glutamine. GLN4 only possesses 7 of the 22 conserved amino acid residues necessary for GS catalytic activity which will be tested in future studies. The predicted lack of catalytic activity mirrors that of A. thaliana NodGS and the GSI-like enzymes of Medicago trunculata (Doskočilová et al., 2011; Silva et al., 2015). It is noteworthy that some of the few conserved residues present within GLN4 are required for glutamate and ATP binding which could allow for GLN4 to detect intracellular N and energy levels. GLN4 lacks any DNA binding domain, thus its regulatory role on transcription must be relayed via a yet unknown signaling cascade. Previous studies in B. subtilis have shown the capability of a GS to bind a global N transcriptional activator, TNRA, during conditions of excess glutamine to prevent the upregulation of N starvation responses (Hauf et al., 2016). Conversely, the B. subtilis GS serves as a chaperone for the repressor of N starvation responses, GLNR, when N availability is high. Whether an analogous mechanism exists for GLN4 in C. reinhardtii remains to be determined. The mutant library did not identify any putative transcription factors that may mediate signals from GLN4. This may be a consequence of redundancy within the pathway whereby GLN4 controls multiple transcription factors and disruption of one does not eliminate AMT4 expression. Partial expression of AMT4 in the arginine-fed culture used here would still result in cell stress, therefore, the mutant would not have been selected. In such a case, the remaining ns mutants are worth a second look. Alternatively, the transcription factors responding to global N status may play an essential function in the basal level expression of fundamental N assimilation proteins such as the catalytic GSs in C. reinhardtii (GLN1-3). Such a scenario would predict lethality for the disruption of the global N status transcription factors 130 Another putative model of GLN4 signaling involves the interaction of 14-3-3 proteins. Studies in yeast have found 14-3-3 proteins are required for the full upregulation of NCR genes during N starvation via the general amino acid control (GAAC) pathway (Tate et al., 2017). Previous studies of 14-3-3 proteins in C. reinhardtii demonstrated that they interact with the other cytosolic GS encoded by GLN1 (Pozuelo et al., 2001). One of the ns mutants (ns103) from this study was found to be disrupted in one of the two 14-3-3 proteins in C. reinhardtii, however, whereas it did show MA resistance it did not show significant reduction of N starvation marker gene expression (Figure 5.2A; Table 5.1). Whether GLN4 directly interacts with 14-3-3 proteins will require future experiments such as pull-down assays. Exploratory purification of the GLN4-interactome may provide useful information about how GLN4 works. While land plants do not have a divergent member of type II GS, it is possible that plant cytosolic GS1s may function in both catalyzing NH4+ reduction and regulating the N assimilation genes. The dual role of a GS as a regulator and catalytic protein has been reported in the type II GS of the rice fungal pathogen Fusarium fujikuroi (Wagner et al., 2013; Brauer et al., 2020). The redundancy and organ specific localization of plant cytosolic GSs could be relevant towards uniquely responding to N availability throughout various organs at different stages of development (Bernard and Habash, 2009; Thomsen et al., 2014). There are five GS1 genes in maize (Sakakibara et al., 1996; Martin et al., 2006), three in rice (Tabuchi et al., 2005) and five in Arabidopsis (Ishiyama et al., 2004) that have been shown to have differential expression patterns suggesting non-redundant roles (Peterman and Goodman, 1991; Sakakibara et al., 1996; Ishiyama et al., 2004). Four of the five A. thaliana GS1s have been shown to be functional enzymes that work individually or cooperatively towards N assimilation, pollen development, vegetative growth, seed filling and seed germination (Lothier et al., 2011; Guan et al., 2015; Konishi et al., 2018; Ji et al., 2019). Therefore, the GS1s of C. reinhardtii, GLN1 and GLN4, may have diverged such that one is catalytic, and one is regulatory in function whereas plant GS1s may have retained both functions but have diverged in their temporal/spatial distribution. 131 Chapter 6: Identification of novel NH4+-repression candidate genes and genes encoding proteins that link photoprotection to N assimilation in C. reinhardtii 6.1 Introduction It has previously been shown that intracellular NH4+ ions can repress the expression of NO3- assimilation genes like NIT1. In 1983, Florencio and Vega showed that treating NO3- grown cells with L-Methionine-D,L-sulfoximine (MSX), an inhibitor of GS and therefore NH4+ assimilation, resulted in the rapid inhibition of NO3- transporters and NIT1 activity and synthesis attributed to the accumulation of intracellular NH4+. Later studies by Matsuda et al., (1992) showed that sexually competent gametes rapidly lost their gametic activity when treated with the GS inhibitor, MSX, followed by NH4+ suggesting that NH4+ ions and not the products of its metabolism can repress gametogenesis. However, these studies did not rule out the possibility that NH4+ may be assimilated by other enzymes than GS such as the mitochondrial glutamate dehydrogenases. Taken together, these data suggest that NH4+ repression plays roles in both the regulation of NO3- assimilation genes and of N starvation responses such as gametogenesis. Subsequently, two mutant libraries each using a NIT1 promoter-reporter were constructed, each with the aim of identifying the molecular components involved in the NH4+ repression of NO3- assimilation genes (Zhang and Lefebvre, 1997; González-Ballester et al., 2005). Zhang and Lefebvre (1997) used the RSP3 system to identify multiple mutant alleles of far1 (Free from Ammonia Repression). However, the causative gene disruption in far1 mutants was not reported. González-Ballester et al., (2005) used an arylsulphatase gene as the reporter whose activity was sensitively assayed by colorimetry to identify a collection of putative mutants with defective NH4+ repression. Characterization of these mutants suggested NO as a critical secondary messenger for NH4+ repression of NIT2-dependent NO3- assimilation genes, but could not reveal any mechanism for detecting NH4+ or additional transcriptional regulators other than NIT2 (reviewed in Chamizo-Ampudia et al., 2017; Calatrava et al., 2017). I have a tentative hypothesis for why these screens biasedly collected the NO-signaling mutants. First, these studies used NO3- feeding to induce NIT1 expression via NIT2 activation and screened for mutants with NIT1 reporter activity when supplemented with NH4+, which would not screen for NH4+ repression of N starvation phenotypes like gametogenesis. Considering the finding that NIT1 expression is also induced by N starvation independent of NIT2 (Chapters 3 – 5), whether the NO-signaling mutants express NIT1 in a nit2 mutant cultured in NH4+-replete 132 media without NO3- needs to be tested. Second, in the given experimental condition where both NH4+ (7.5 mM) and NO3- (4 mM) were present, cells will preferentially use the NH4+ while the NO3- assimilation pathway was active at low levels resulting in the accumulation of toxic NO2- (De Montaigu et al., 2011). The toxic NO2- can produce NO by the NIT1-ARC complex (Chamizo-Ampudia et al., 2016) which serves as a signal to directly repress NO3- / NO2- assimilation genes as a detoxification mechanism (Chamizo-Ampudia et al., 2017; Calatrava et al., 2017). The collection of mutations involved in NO-mediated repression may therefore be explained by defects in NO-signaling that resulted in the upregulation of NIT1 by the activation of NIT2 in the presence of NO3- rather than defects in NH4+ repression of NO3- assimilation genes. According to my hypothesis, it would therefore be of merit to try and recover NH4+ repression mutants in NO3--free conditions with a nit2 mutant background, which will address how NH4+ rapidly represses N starvation responses such as gametogenesis. Therefore, the mutant library developed in Chapter 5 was screened for the defective regulation of an N starvation marker gene when grown in NH4+-replete conditions to identify putative molecular components of NH4+ repression of N starvation responses. 6.2 Results 6.2.1 Random insertional mutagenesis disrupted NH4+-repression regulation of the NIT1 driven reporter I have previously established that the NIT1 gene is upregulated in response to N starvation independent from the NO3- transcription factor NIT2 (Chapters 3 - 5). The same techniques and promoter-reporter system used in Chapter 5 were used to collect putative mutants that are insensitive to NH4+ repression. The 10,134 transformants described in Chapter 5 were screened for constitutive reporter activity under NH4+-replete conditions, suggesting that NH4+-repression of NIT1 expression was disrupted (outlined in Figure 6.1). A total of 112 mutants (1.11%) displaying constitutive swimming (cs) were collected initially, and careful re-examination using a diluted cell concentration to prevent the local depletion of NH4+ led to the identification of 54 cs (0.53%) that were further analyzed for NH4+-repression. 6.2.2 Mutants disrupted in NIT1 promoter driven reporter activity display defective regulation of N starvation-induced N salvage/scavenging responses To test whether NH4+ repression was truly disrupted in the 54 cs mutants, NH4+ repression of the NO3- assimilation genes was examined by the chlorate (ClO3-) toxicity assay. In this assay, 133 NO3- is replaced by its analog ClO3- and whether the NO3- assimilation pathway is derepressed is probed by the toxicity of chlorite (ClO2-) produced by the uptake and conversion of ClO3- (Zhang and Lefebvre, 1997; Sanz-Luque et al., 2016). Measurements of cells stress (Fv / Fm) were performed with cultures incubated for two days on TAP agar plates containing 3 mM of NH4+ supplemented with 10 mM ClO3- as described previously (Zhang and Lefebvre, 1997). This secondary screen was utilized under two light intensities, low light (LL; 30 μmol m−2 s−1) and under high light (HL; 150 μmol m−2 s−1), which may assess the induction of NIT1 by the over-reduction of the plastoquinone pool expected under the HL condition (Giordano et al., 2005). Under both the LL and HL conditions, wild-type cells did not show any cell stress, whereas nine out of 54 cs mutants displayed significantly more cell stress with 10 mM ClO3- than without ClO3- under HL (Table 6.1). To directly assess whether NH4+ repression of N starvation genes is disrupted, the expression of AMT4, which is typically suppressed in 8 mM NH4+ media, was examined in 9 cs mutants, showing significantly upregulated AMT4 in eight mutants (Figure 6.2). Therefore, these 8 cs mutants were insensitive to NH4+ and were renamed as cns1 - cns8 (constitutive N starvation responses). All cns mutants except cns1 also displayed higher stress levels (Fv / Fm) than wild-type in NH4+ without ClO3- supplementation when incubated under HL (Table 6.1), suggesting defects in stress responses that help to cope with excess light. The cns1-cns3 mutants showed an upregulation of AMT4 in 8 mM NH4+-fed cultures comparable to that of wild-type cells in N-free culture (Figure 3.2 in Chapter 3). Genome sequencing of the cns1 mutant identified a single insertion within an annotated gene encoding a basic helix-loop-helix (bHLH) transcription factor. A BAC clone having the wild-type copy of the gene disrupted by the insertion in cns1 was co-transformed with a HygR plasmid into the cns1 strain. The restoration of ClO3- resistance was noted in three of four co-transformants (Comp1, Comp2, and Comp3 in Figure 6.3), documenting that the identified mutation causes the observed NH4+-insensitive phenotypes. The expression of CNS1 was significantly upregulated in the arginine sample (> 2-fold) in the arginine transcriptome study (Chapter 4). 134 Figure 6.1 – Utilization of a NIT1 promoter-driven conditional swimming reporter allowed for the identification of mutants putatively disrupted in NH4+-repression regulation. NIT1 promoter conditional swimming lines were transformed with complementation of NIC7 conferring resistance to AP. The AP resistant colonies were grown for three days on NH4+-TAP agar plates and then resuspended in 150 µL of NH4+-TAP or NF-TAP in a 96-well plate. Following overnight incubation under low light (30 μmol m−2 s−1), cells were observed under a dissecting microscope for swimming in NH4+-TAP. 135 Table 6.1. Mutants sensitive to chlorate when cultured with NH4+ were putatively disrupted in NH4+ repression of NO3--assimilation genes. Low light (30 μmol m−2 s−1) High light (150 μmol m−2 s−1) NH4+ NH4++ ClO3- NH4+ NH4++ ClO3- (a) Control lines (n = 5) 137c 0.741 ± 0.009 0.749 ± 0.011 0.627 ± 0.010 0.666 ± 0.025 Library parent 0.776 ± 0.005 0.750 ± 0.019 0.693 ± 0.025 0.594 ± 0.060 (b) cs ClO3- sensitive mutants (n = 5) cns1 (cs152) 0.764 ± 0.013 0.566 ± 0.074 0.670 ± 0.021 0.374 ± 0.027 cns2 (cs29) 0.629 ± 0.084 0.696 ± 0.022 0.576 ± 0.045 0.421 ± 0.044 cns3 (cs113) 0.636 ± 0.093 0.708 ± 0.014 0.549 ± 0.038 0.514 ± 0.013 cns4 (cs126) 0.682 ± 0.079 0.701 ± 0.020 0.573 ± 0.030 0.455 ± 0.041 cns5 (cs143) 0.753 ± 0.001 0.647 ± 0.051 0.609 ± 0.057 0.510 ± 0.032 cs147 0.741 ± 0.029 0.697 ± 0.043 0.294 ± 0.109 0.199 ± 0.146 cns6 (cs148) 0.755 ± 0.009 0.568 ± 0.025 0.573 ± 0.050 0.273 ± 0.032 cns7 (cs153) 0.762 ± 0.008 0.668 ± 0.053 0.612 ± 0.059 0.448 ± 0.042 cns8 (cs156) 0.651 ± 0.036 0.660 ± 0.014 0.491 ± 0.061 0.519 ± 0.004 (c) Other mutants (n = 20) Pool 1 0.747 ± 0.020 0.756 ± 0.007 0.678 ± 0.038 0.622 ± 0.017 Pool 2 0.748 ± 0.007 0.746 ± 0.010 0.666 ± 0.053 0.649 ± 0.013 Pool 3 0.743 ± 0.011 0.727 ± 0.010 0.713 ± 0.010 0.631 ± 0.016 Pool 4 0.745 ± 0.010 0.718 ± 0.018 0.717 ± 0.017 0.610 ± 0.036 Pool 5 0.776 ± 0.025 0.749 ± 0.012 0.722 ± 0.013 0.675 ± 0.050 Cell stress was measured via in vivo chlorophyll fluorescence of Fv / Fm in cells replica plated on agar plates and incubated under high light (150 μmol m−2 s−1) for 48 hours with 3 mM NH4+ with and without 10 mM ClO3-. The control lines (a) shown are from the same plate as the cs ClO3- mutant measurements. The other mutants (c) are five pools of 20 randomly selected mutants that do not display the ClO3- sensitivity phenotype to demonstrate the variance among replicates. 136 Figure 6.2 – Chlorate sensitive mutants cannot repress the N starvation marker gene AMT4 cultured with NH4+. Strains were grown in NH4+ (8 mM) TAP liquid cultures until mid-log phase and RNA was harvested. Expression profiling of the N starvation-inducible gene, AMT4, was used as a preliminary screen for defects in NH4+-mediated repression (n=1). 137 Figure 6.3 – Complementation of cs152 restored wild-type chlorate resistance. Cell stress was measured via in vivo chlorophyll fluorescence of Fv / Fm in cells replica plated on agar plates and incubated under low light (30 μmol m−2 s−1) for 48 hours with 3 mM NH4+ with and without 10 mM ClO3-. Four strains with successful transformation of the BAC as confirmed by PCR were tested (cs152; BAC) (n = 1). With the number indicating the HygR colony identification number. 138 6.2.3 Mutants disrupted in NIT1 promoter driven reporter activity display increased levels of cell stress that increases with light intensity Most of the cns mutants also displayed higher stress levels (lower Fv / Fm) than wild-type under HL, suggesting a mechanistic link between NIT1 regulation and excess light responses. To identify additional mutants with defects in excess light responses, all cs/ns mutants collected so far were subject to Fv / Fm measurement during phototrophic growth under four light intensities (dim light, DL (5 μmol m−2 s−1); low light, LL (30 μmol m−2 s−1); high light, HL (150 μmol m−2 s−1); very high light, VHL (250 μmol m−2 s−1)). A total of 27 (out of 128 ns/cs strains) strains were selected for increased cell stress relative to the wild-type parent in at least one of the four light intensities tested. Of the seven cns mutants that showed higher stress levels than wild-type in mixotrophic NH4+-fed cultures under HL (Table 6.1), four were found (cns4, cns6, cns7, and cns8) to have higher cell stress in more than one light intensity during the phototrophic screen. Additionally, the cs147 mutant, originally screened for ClO3- sensitivity (Table 6.1), was also recovered during the screen for higher stress levels during phototrophic growth. The higher stress levels of cns2, cns3, and cns5 in HL mixotrophic NH4+-fed cultures may therefore be specific to mixotrophic conditions. The resulting 27 mutants were further clustered into similar groups by unsupervised k-means clustering using the Fv / Fm values for each light intensity. A suitable number of groups (n = 4) for the clustering was determined by the elbow method (Figure 6.4). Principal components analysis (PCA) was then used to assess the overall similarity of the four groups assigned by k-means clustering (Figure 6.5). A Tukey’s HSD test was then used to test whether the means of the average Fv / Fm for each group were significantly different from one another (Figure 6.6). This showed that the four groups were distinguished by the severity of the cell stress (decrease in Fv / Fm) with group one representing the least severe and group four representing the most severe cell stress. The four cns mutants were each in separate light-sensitivity groups. Mutations of the four light-sensitive cns mutants were identified with genome sequencing. Within the mutations, candidate genes were collected as the following: A SQUAMOSA promoter binding protein was identified in group 1, a GATA transcription factor was found in group 2, an E3 ubiquitin ligase complex component, known to play a role in photoprotection was found in group 3, and a triose phosphate transporter was found in group 4. These candidates include two transcription factors and one ubiquitin-dependent proteasome factor, warranting further studies of these mutants for investigating the signal transduction connecting excess light and/or redox- 139 Figure 6.4 – The optimal cluster number for k-means clustering was calculated using the elbow method. Simulation of cluster numbers up to ten were used to find the lowest number of clusters able to explain ~80% or more of the sample variation. The dashed line indicates the shoulder of the elbow plot and the number of clusters used for the subsequent principal components analysis. 140 Figure 6.5 – Principal components analysis identified mutants with very strong decreases in Fv / Fm. Light sensitive mutants with cell stress Fv / Fm measurements deviating from the wild-type were grouped with unsupervised k-means clustering. The average from three biological replicates was plot with principal components analysis and colored according to k-means clusters. Outliers to the right of PC1 were removed and k-means clustering and PCA were re-tested. 141 Figure 6.6 – Screens for light stress in autotrophic conditions revealed mutants putatively involved in photoprotection. Three-day-old TAP plate grown cells were incubated on TP plates for 48 hours in four light intensities and measured for cell stress (Fv / Fm). DL = dim light (5 μmol m−2 s−1), LL = low light (30 μmol m−2 s−1), HL = high light (150 μmol m−2 s−1), and VHL = very high light (250 μmol m−2 s−1). Groupings were selected using k-means clustering and principle components analysis. Open circles represent one biological replicate, three biological replicates are presented for each strain. Closed circles represent the mean of the group and the line indicates the 95% confidence interval for each group. The letters indicate significant differences between groups as determined by Tukey-HSD tests comparing the group mean values across all possible pairwise combinations (n = 3). 142 responsive regulation of NIT1 and N metabolism. The future characterization of these mutants may reveal novel components regarding the connection between light and N assimilation. 6.3 Discussion Previous studies using NIT2-dependent expression of NIT1 as the marker of the NH4+ repression identified mutants that showed only a partial alleviation of NH4+ repression when the NH4+ concentration was relatively low (1 or 2 mM). The authors of these studies suggested that the genes required for the NH4+ repression pathway were highly redundant (de Montaigu et al., 2010; De Montaigu et al., 2011). This study, using a N starvation gene as a marker of the NH4+ repression in a nit2 background identified eight cns mutants with upregulated expression of AMT4 during growth in 8 mM of NH4+, where AMT4 expression is repressed. Of those, three cns mutants showed high AMT4 expression at the level observed in N-starved wild-type cells, representing full alleviation of NH4+ repression. This study also documents the genetic complementation of the cns1/cs152 mutant, providing the first candidate transcription factor of NH4+ repression studies in C. reinhardtii. Excess light stress observed in seven of the eight cns mutants may suggest a potential link between the NH4+ repression and photoprotection mechanisms. Previous studies in the closely related chlorophyte algae, Dunaliella tertiolecta, have shown that the genes encoding the chlorophyll a/b binding proteins controlling antenna size and therefore photon absorption are up- or downregulated in response to the redox status of the plastoquinone pool (Escoubas et al., 1995). Likewise, in C. reinhardtii, Giordano et al., (2005) showed that the plastoquinone pool redox status controlled the expression of NIT1 in response to light. If the reduction of the plastoquinone pool is blocked by 3-(3’4’-dichlorophenyl)-1,1’-dimethyl urea (DCMU), then NIT1 gene expression was inhibited >80% (Giordano et al., 2005). Similarly, mutants in the PSII core protein, D1, unable to bind tightly with plastoquinone result in less plastoquinone reduction were found to have reduced NIT1 gene expression (Giordano et al., 2005). These data suggest that the signal transduction in response to the redox state of plastoquinone may control NIT1 expression in addition to genes encoding light harvesting proteins. Therefore, the cns mutants sensitive to excess light may be explained by aberrant regulation of N assimilation genes due to defects in redox-dependent signal transduction. The absorption of light exceeding that of the cell’s redox capacity can result in photosystem damage and cell death. Protective mechanisms referred to as non-photochemical quenching exist to prevent damage from overreduction (Niyogi and Truong, 2013). One type of 143 non-photochemical quenching is energy-dependent quenching that safely dissipates excess energy as heat via the upregulation of genes coding the PSBS protein and the light-harvesting complex stress response (LHCSR) proteins (Li et al., 2000; Peers et al., 2009). One pathway regulating LHCSR1 and LHCSR3 expression is the plasma membrane photoreceptor phototropin (PHOT) (Petroutsos et al., 2016). The PHOT pathway functions through the control of the CONSTANS (CO) and NFYB transcription factors via the regulation of a CUL4-dependent E3 ubiquitin ligase complex containing the DE-ETIOLATED 1 (DET1) and DAMAGED DNA-BINDING 1 (DDB1) proteins that, if active, targets the CO/NFYB complex for degradation (Aihara et al., 2019). The mutations identified in the four light-sensitive cns mutants includes candidate transcription factors and an E3 ubiquitin ligase, suggesting a signal transduction pathway like the PHOT pathway. The putative signal transduction pathway disrupted in this screen is well suited for coordinating the photosynthesis-dependent production of reductant with N assimilation consumption of reductant. This rationale motivated further analysis of the cs/ns mutants collecting the additional 22 mutants sensitive to excess light, whose characterization may reveal additional components of photoprotective/energy status regulation. Whether the PHOT pathway is involved in the transcriptional regulation of N assimilation genes is of interest to the crosstalk between light detection and N status. For instance, the CO transcription factor involved in the diurnal regulation of gene expression may also regulate the diurnal cycle of N assimilation gene expression noted in C. reinhardtii (Strenkert et al., 2019). 144 Chapter 7: Conclusions 7.1 Major findings of this work 7.1.1 Arginine is a derepressive source of N Our understanding of the perception and regulatory mechanisms for cellular N status in photosynthetic eukaryotes lags many decades behind that of bacteria and heterotrophic eukaryotes. Crucial to the previous breakthroughs towards the understanding of N status transcriptional regulation was the establishment of derepressive N source study systems within which the responses to changes in N regime could be monitored and dissected without limiting cellular growth. No such derepressive system had been established in photosynthetic eukaryotes due to 1) N source choices are limited because most photosynthetic eukaryotes typically assimilate inorganic N sources such as NO3- and NH4+ and not much has been known for utilization of organic N sources, and 2) plants uptake N from the roots and systemically redistribute it throughout creating a mosaic of N-replete and N-starved cells. C. reinhardtii offers well-defined N starvation responses, a convenient single cell type experimental system, and numerous N sources that support normal growth. In my thesis work, I first asked whether a derepressive condition could be identified in C. reinhardtii (Chapters 3 and 4), and secondly whether a forward genetics screen could reveal one of the critical missing pieces in our understanding of N homeostasis in photosynthetic eukaryotes, the detection and signal transduction of intracellular N status (Chapters 5 and 6). Early work in C. reinhardtii hinted at arginine being capable of derepressing N starvation responses, specifically gametogenesis. Chapters 3 and 4 described that arginine was capable of not only activating gametogenesis but also a full suite of N starvation-specific marker genes all while maintaining robust growth. Combining the NIT1 reporter system with the arginine MA resistance assay for probing N starvation responses enabled the first truly targeted screen for N status regulators in a photosynthetic eukaryote. This screen identified a putative sensor of N status, NSI1/GLN4, encoding a novel type II GS, whose disruption resulted in the complete loss of gametogenesis and N starvation-specific transcriptional regulation (Chapters 5 and 6). An important finding along the way to this discovery was that the NIT2 transcription factor is not essential for the upregulation of NO3- assimilation genes (Chapter 3). While the NIT2 transcription factor is necessary for the full activation of NIT1, many other factors contribute to its expression, particularly N starvation. 145 The transcriptome analysis of arginine-fed C. reinhardtii cultures helped to distinguish the N starvation induced genes into two pools, the genes directly regulated by N status signaling and the genes related to generic stress imposed during N starvation. Genes with regulation specific to arginine conditions suggested the arginine deiminase (ADI1)-dependent route as a primary route of arginine catabolism. The chloroplast localization of ADI1 arginine catabolism and local NH4+ assimilation into other amino acids suggests that N status is detected elsewhere answering why arginine-fed cultures evade the detection of a N-replete status. My studies provided specific candidate proteins for arginine catabolism whose further study will shed light on how arginine-fed cultures cannot suppress N starvation responses in C. reinhardtii. 7.1.2 GLN4 is central to N status signal transduction and N starvation responses Characterization of N starvation insensitive mutant 1 (nsi1) suggest that GLN4 is a critical regulator of N starvation responses and documented that N starvation responses were necessary for long-term survival under N limitation conditions. Long-term survival of cells in N-deplete conditions would require remobilization of N reserves in the cell, however, unicellular organisms such as C. reinhardtii have limited N reserves. A critical survival strategy was inferred from the long-term starvation phenotypes of the nsi1 mutants, displaying accelerated bleaching, suggesting the importance of redox management for survival during long-term N starvation. Whether redox stress is involved in the early bleaching of nsi1 cells and how redox stress responses of nsi1 differ from wild-type cells are critical questions to be addressed. Another option for the long-term survival of unicellular organisms is to enter a dormant stage, typically as sexual zygotes. The requirement of GLN4 for triggering gametogenesis supports the idea that mating is a survival strategy in N starvation conditions. The screen of N starvation regulatory mutants yielded six mutants unable to upregulate N starvation marker genes, five of which disrupted the same region including GLN4. The lack of other mutations (except for ns106; Figure 5.2A) disrupting N starvation-induced gene activation could suggest redundancy within the pathway or lethality of the disruption of the N starvation response pathway. Bioinformatics assessment of the GLN4 sequence suggested that it cannot catalyze the incorporation of NH4+ into glutamine, by the lack of conserved NH4+ binding residues including the glutamate flap necessary to prevent glutamate from interfering with the active site. Considering NSI1/GLN4 as a putative sensor of cellular N status, it is important to study which metabolites that GLN4 can bind as an indicator of cellular N status. Given that NH4+ is generally toxic to the cell and that the cellular content of NH4+ may fluctuate depending on the environmental conditions rather than internal conditions, NH4+ may not be suitable to represent 146 cellular N status. Likewise, bacteria and heterotrophic organisms avoid NH4+ in N status detection. Glutamate or glutamine are more likely to signal N status as observed in many fungi and bacteria. GLN4 retains three of five conserved glutamate binding residues and two of six ATP binding residues. Therefore, it is possible that GLN4 can detect glutamate or ATP levels as triggers for N and energy status, respectively. Whether the GLN4 protein binds to the typical substrates of GSs should be investigated to learn more about the detection as well as catalytic functions of GLN4. The discovery of a GS regulating N status responses in photosynthetic eukaryotes fits a model of regulation comparable to that found in B. subtilis. While no homologs for GLN4 exist in land plants, they do possess prokaryotic type I GSs associated with N metabolism regulation (Doskočilová et al., 2011; Silva et al., 2015). The C. reinhardtii genome also encodes one type I GS (GLN5), however, it has not been characterized. Additionally, it is possible that the redundant cytosolic catalytic GSs in plants could serve a dual role as regulators of N status. 7.1.3 NIT1 regulation in the absence of NIT2 probes for N starvation and ammonium repression signaling mechanisms The identification of novel mutants with defective NIT1 expression in response to excess light as well as N limitation has demonstrated its complex regulation. A general sensitivity to excess light observed in the NH4+ repression mutants suggests that redox-dependent regulation of NIT1 in a nit2-null background may help to identify a signaling network connecting N metabolism and photosynthesis. The collection of cns mutants provides invaluable resources to tease apart the N-responsive signaling and how it is interconnected with redox poise, C availability, and photoreceptors. The NIT1 gene and the genetic tools developed to study its regulation will continue to be a source of new knowledge. Further dissection of the mutants collected from this thesis will add new mechanisms for NIT1 regulation to what are already known, listed in the following: 1) NO3- -specific induction via NIT2, 2) NO-mediated repression in response to NO2- toxicity, 3) NH4+ repression (Chapter 6), 4) N starvation responses dependent on NSI1/GLN4 (Chapter 5), and 5) light-regulated responses (Chapter 6). 7.2 Future work 7.2.1 How is arginine assimilated and is there an arginine-specific transcription factor The transcriptome analysis of arginine-fed C. reinhardtii cultures revealed many facets of the metabolism of arginine-fed cells, provided clues for the metabolic route, and collected 147 potential transcription factor(s) involved in arginine uptake and metabolism. Studies of mutants deficient in these regulatory elements or metabolic proteins, available in the collection of C. reinhardtii CLiP mutants (chlamycollection.org; Li et al., 2016), will test the predictions made from the transcriptome analysis. The catabolism of arginine as the primary N source and the absence of metabolites for N status detection can be monitored by analyzing metabolite profiles upon changes in N sources and with isotope-labeled arginine. Defective N starvation responses in nsi1 also showed defects in growth with arginine as a sole N source. Assessing the growth of nsi1 and cns mutants in other N sources will answer the question as to whether other N sources requires similar signaling networks for their uptake and utilization. 7.2.2 How does GLN4 detect N status and trigger the appropriate signal transduction Characterization of the biochemical features of GLN4 and its interacting partners will provide critical information for predicting how it detects the cellular N status and triggers the N starvation signaling pathway. The bioinformatic analysis described in Chapter 5 predicted: 1) GLN4 may bind glutamate but not NH4+, and 2) GLN4 may not form the traditional decameric structure of eukaryotic GSs. To test whether it can catalyze the conversion of NH4+ to glutamine, two approaches may be suitable: 1) biochemical assays using E. coli expressed GLN4 proteins, and 2) genetic complementation of the NH4+ auxotrophic E. coli GS mutant (glnA). Quantitative metabolite binding kinetics may be obtained by isothermal calorimetry, which can determine binding constants of GLN4 for NH4+, glutamate, glutamine, or ATP. Whether GLN4 can form a multimeric structure on its own or with other GS proteins such as GLN1 is also a critical question regarding how GLN4 functions. If a multimeric structure is formed, the metabolite binding assay will need to be performed in various conditions where the multimeric structure is allowed or prohibited. The GLN1 protein has previously been shown to interact with the two 14-3-3 proteins in C. reinhardtii. The 14-3-3 proteins in yeast have been shown to play a role in regulating N-responsive genes via the GAAC pathway (Tate et al., 2017). Therefore, testing whether GLN4 interacts with the 14-3-3 proteins may offer a clue on how GLN4 may transduce the N status signal. 7.2.3 Are NH4+-repression and N status in the same pathway or in mutually exclusive pathways? The novel mutants in N status detection and NH4+ repression described here offer an opportunity to test whether the two mechanisms operate within the same pathway. Testing for epistasis in double mutants of nsi1 and cns mutants may address this. If N starvation marker gene 148 expression cannot be activated in the double mutant, it would indicate that GLN4 is epistatic and represents a necessary factor for conveying the NH4+ repression signal. Alternatively, if N starvation marker genes are expressed under NH4+ and N starvation conditions in the double mutant, it would suggest that the cns mutation(s) is epistatic and likely regulated by the GLN4-independent pathway. Whether NH4+ repression is mediated through GLN4 should be investigated to test whether it is linked to N status detection in C. reinhardtii. 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Thesis/Dissertation
eng
Botany
Vancouver : University of British Columbia Library
Attribution-NonCommercial-NoDerivatives 4.0 International
Graduate
Discovery of nitrogen starvation detecting and signaling mutants in Chlamydomonas reinhardtii
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