REGULATION OF PLANT IMMUNITY: LESSONS FROM SNIPER4 AND CDK8 by Jianhua Huang B.Sc., Hunan University, 2010 M.Sc., Sun Yat-sen 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 2019 © Jianhua Huang, 2019 ii The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, the dissertation entitled: REGULATION OF PLANT IMMUNITY: LESSONS FROM SNIPER4 AND CDK8 submitted by Jianhua Huang in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Botany Examining Committee: Dr. Xin Li, Botany Supervisor Dr. Jae-Hyeok Lee, Botany Supervisory Committee Member Dr. George Haughn, Botany University Examiner Dr. Simone Diego Castellarin, Wine Research Centre University Examiner Additional Supervisory Committee Members: Supervisory Committee Member Supervisory Committee Member iii Abstract Plants employ sophisticated innate immune systems to ward off the invasion of pathogens. Upon perception of pathogens, plants transduce signals to downstream components and activate defense responses. To investigate the regulation of immune responses and the mechanisms of immune signaling, my Ph.D. projects focus on the characterization of immune regulators isolated from two genetic screens conducted in autoimmune mutants snc1 and camta1/2/3. SNIPER4, identified from the snc1-influencing plant E3 ligase reverse genetic screen (SNIPER), encodes an F-box protein being part of an SCF E3 complex. Two redundant tumor necrosis factor receptor associated factors (TRAF) proteins MUSE13 and MUSE14 serve as adaptors in the SCFCPR1 E3 complex to facilitate the degradation of NLRs including SNC1 and RPS2. Accumulation of MUSE13 and MUSE14 is decreased by overexpression of SNIPER4, but is increased when dominant-negative (DN)-SNIPER4 is overexpressed. In addition, SNIPER4 interacts with MUSE13 and MUSE14. Collectively, my data suggest that SNIPER4 fine-tunes the output of NLR proteins by modulating the turnover of MUSE13 and MUSE14 of the SCFCPR1 E3 complex. Three calmodulin binding transcription activators (CAMTAs), including CAMTA1, CAMTA2 and CAMTA3, play redundant roles in plant immunity. However, their major function in immune responses remains ambiguous. By conducting the Suppressor of camta1/2/3 (SUCA) screen, I found that loss-of function ICS1, a gene indispensable for SA biosynthesis, almost fully suppresses the drastic autoimmunity of camta1/2/3 triple mutant, suggesting that the major role of CAMTAs is to inhibit SA biosynthesis. In support of this, SA levels are decreased in the gain-of-function camta3-3D mutant. Transcriptional analysis revealed that expression of SA-related genes, including ICS1, EDS5 and PBS3, is iv compromised in camta3-3D plants. On the other hand, mutations in Cyclin-Dependent Kinase 8 (CDK8), isolated from the SUCA screen, compromise SA accumulation and systemic required resistance (SAR). cdk8 mutants exhibit reduced transcript levels of ICS and EDS5. Taken together, my results indicate that CAMTAs and CDK8 function oppositely in transcriptional regulation of SA biosynthesis. Overall, my thesis work adds to the current literature on the regulation of plant immunity. Such knowledge will assist the future development of sustainable methods for controlling diseases of our crop plants. v Lay Summary Microbial pathogens can cause diseases in crop plants and lead to massive yield loss. In nature, plants utilize their immune system to defend against pathogens. In depth investigation of the plant immune system would enable us to develop efficient and environmentally-friendly approaches to prevent crop yield loss caused by pathogens. My thesis focuses on the regulation of the immune system. My first project shows that a protein called SNIPER4 regulates immunity by assisting the degradation of two proteins involved in plant immunity. My second project finds that three redundant proteins, namely CAMTA1, CAMTA2 and CAMTA3, and a protein called CDK8 play opposite roles in regulating the synthesis of salicylic acid, a plant defense molecule that can activate plant immunity. Overall, my thesis expands our knowledge of the regulation of plant immunity. vi Preface The results presented in this Ph.D. thesis are derived from research performed between Sep 2014 to Dec 2018. A manuscript based on Chapter 2 has been published in the Plant Journal. A manuscript modified from chapter 3 has been submitted to the same journal and is under minor revision. Details of the two manuscripts and the contribution of the candidate are listed as follows: Chapter 2 - SCFSNIPER4 controls the turnover of two redundant TRAF proteins in plant immunity was based on the manuscript: Huang, J., Zhu, C., & Li, X. (2018). SCFSNIPER 4 controls the turnover of two redundant TRAF proteins in plant immunity. The Plant Journal.  J.H and X.L designed the experiments. J.H. carried out most of the experiments. C.Z. observed enhanced dwarfism in snc1 by overexpression of SNIPER4 and generated pHAN-SNIPER4, pHAN-At4g11580 and pHAN-DN-SNIPER4-HA constructs. J.H and X.L wrote the manuscript. Chapter 3 - CAMTA transcription factors and CDK8 play opposite roles in the transcriptional regulation of salicylic acid levels and systemic acquired resistance is based mostly on the manuscript: Huang, J., Sun, Y., Ruiz Orduna, A., Jetter, R & Li, X. (2019). The Mediator kinase module acts as a positive regulator of salicylic acid accumulation and systemic acquired resistance. The Plant Journal (Accepted).  J.H and X.L designed the experiments. J.H. carried out most of the experiments. Y. X. mapped SUCA2 and conducted the allelism test between suca2 camta1/2/3 and suca6 camta1/2/3. X.H. carried out Sanger sequencing of ICS1 in suca4 camta1/2/3 and suca5 vii camta1/2/3 and of EDS5 in suca6 camta1/2/3. Y.L. and A.R.O. assisted with SA measurement. J.R. provided necessary instruments for SA measurement. J.H and X.L wrote the manuscript. viii Table of Contents Abstract .................................................................................................................................... iii Lay Summary............................................................................................................................ v Preface ..................................................................................................................................... vi Table of Contents ................................................................................................................... viii List of Tables .......................................................................................................................... xii List of Figures ........................................................................................................................ xiii List of Abbreviations .............................................................................................................. xv Acknowledgements.............................................................................................................. xviii Dedication .............................................................................................................................. xix 1 Introduction........................................................................................................................ 1 1.1 Plant immune responses .......................................................................................... 1 1.1.1 PAMP-triggered immunity ........................................................................... 1 1.1.2 Effector-triggered immunity (ETI) ............................................................... 3 1.1.3 SAR .............................................................................................................. 7 1.2 The ubiquitin-26S proteasome system (UPS) ......................................................... 9 1.2.1 Ubiquitination in plant immunity ............................................................... 10 1.2.2 Regulation of immune receptors by E3 ligases .......................................... 10 1.2.3 E3 ligases play positive and negative roles in immune signaling. ............. 11 1.3 Calmodulin-binding transcription activators (CAMTAs) ..................................... 13 1.3.1 Diverse roles of CAMTAs in Arabidopsis ................................................. 13 1.3.2 The controversial mechanisms of CAMTAs in plant immunity ................ 15 2 SCFSNIPER4 controls the turnover of two redundant TRAF proteins in plant immunity .. 18 ix 2.1 Summary ............................................................................................................... 18 2.2 Introduction ........................................................................................................... 18 2.3 Material and method ............................................................................................. 20 2.3.1 Plant growth ................................................................................................ 20 2.3.2 Transcriptional analysis .............................................................................. 20 2.3.3 Pathogen infection ...................................................................................... 21 2.3.4 Genotyping and Construction of Plasmids ................................................. 21 2.3.5 Split luciferase complementation assay ...................................................... 22 2.3.6 Total Protein Extraction, Western Blot and Immunoprecipitation ............. 22 2.4 Results ................................................................................................................... 23 2.4.1 SNIPER4 overexpression enhances snc1-mediated autoimmunity ............ 23 2.4.2 SNIPER4 is part of an SCF E3 complex .................................................... 25 2.4.3 SNIPER4 knockout reduces SNC1 protein levels and attenuates snc1-mediated autoimmunity .......................................................................................... 27 2.4.4 Overexpression of SNIPER4 enhances disease resistance in muse13 or muse14 single mutant ............................................................................................. 29 2.4.5 SNIPER4 regulates the turnover of MUSE13 and MUSE14 ..................... 33 2.4.6 SNIPER4 associates with MUSE13 and MUSE14 in vivo ........................ 37 2.5 Discussion ............................................................................................................. 38 2.5.1 The SNIPER screen is an efficient approach to identify E3s involved in plant immunity ........................................................................................................ 38 2.5.2 Hierarchical organization of ubiquitination and substrate protein degradation ............................................................................................................. 39 x 2.5.3 SCFSNIPER4 regulates the protein levels of TRAF proteins MUSE13 and MUSE14 ................................................................................................................. 40 2.5.4 SCFSNIPER4 regulates immune output by controlling TRAF protein MUSE13/14 homeostasis ....................................................................................... 41 3 CAMTA transcription factors and CDK8 play opposite roles in the transcriptional regulation of salicylic acid levels and systemic acquired resistance ...................................... 44 3.1 Summary ............................................................................................................... 44 3.2 Introduction ........................................................................................................... 44 3.3 Material and method ............................................................................................. 46 3.3.1 Plant growth condition and SA measurement ............................................ 46 3.3.2 Mutagenesis and mutant screen .................................................................. 47 3.3.3 Next generation sequencing and mapping .................................................. 47 3.3.4 Pathogen infection assays ........................................................................... 47 3.3.5 Quantitative RT-PCR.................................................................................. 47 3.3.6 Ion leakage assay ........................................................................................ 48 3.3.7 Construction of plasmids ............................................................................ 48 3.3.8 Split luciferase complementation assay ...................................................... 48 3.4 Results ................................................................................................................... 49 3.4.1 The suca mutations suppress the autoimmune phenotypes of a camta1/2/3 triple mutant ............................................................................................................ 49 3.4.2 Positional cloning of suca1, suca2 and suca3 ............................................ 52 3.4.3 The autoimmunity of camta1/2/3 is attributed largely to higher SA accumulation ........................................................................................................... 60 xi 3.4.4 CAMTAs negatively regulate SA accumulation ........................................ 64 3.4.5 Characterization of the cdk8 single mutants ............................................... 67 3.4.6 Transcriptional regulation of ICS1 and EDS5 by CDK8 ............................ 69 3.4.7 Contribution of the other Mediator subunits of the CDK8 kinase module to SA accumulation and SAR ..................................................................................... 71 3.5 Discussion ............................................................................................................. 71 3.5.1 The major role of CAMTA3 in plant immunity ......................................... 72 3.5.2 The kinase module of the Mediator serves as a positive regulator of SA biosynthesis ............................................................................................................ 73 4 Summary and future perspectives .................................................................................... 76 4.1 Regulation of E3 ligase activity to fine-tune NLR protein levels. ........................ 76 4.2 Opposite transcriptional regulation of SA biosynthesis by CAMTAs and CDK8 79 Bibliography ........................................................................................................................... 81 xii List of Tables Table 3-1 Mutations with PSNP = 1 in the causal region of SUCA1. ................................... 53 Table 3-2 Mutations with PSNP = 1 in the causal region of SUCA3. ................................... 54 xiii List of Figures Figure 2.1 Overexpression of SNIPER4 enhances the autoimmunity of snc1 but has no effect in wild type Col-0. ..................................................................................................... 24 Figure 2.2 Sequence analysis of SNIPER4. ........................................................................ 26 Figure 2.3 SNIPER4 associates with ASK1. ....................................................................... 27 Figure 2.4 sniper4 partially suppresses the autoimmunity of snc1. .................................... 28 Figure 2.5 sniper4 knockout plants do not exhibit enhanced disease susceptibility. .......... 30 Figure 2.6 Overexpression of SNIIPER4 activates immune responses in muse13 or muse14 background. ......................................................................................................................... 32 Figure 2.7 Overexpression of SNIPER4 reduces MUSE13 and MUSE14 protein levels. . 35 Figure 2.8 A dominant-negative (DN) version of SNIPER4 leads to MUSE13-FLAG and MUSE14-FLAG protein accumulations. ............................................................................. 36 Figure 2.9 SNIPER4 interacts with MUSE13 or MUSE14. ............................................... 37 Figure 2.10 A working Model for SNIPER4-mediated degradation of MUSE13/14 to fine-tune SNC1 protein levels. .................................................................................................... 43 Figure 3.1 Suppression of camta1/2/3-mediated autoimmunity mediated by suca1, suca2 and suca3 ............................................................................................................................. 51 Figure 3.2 SUCA1 encodes ICS1. ....................................................................................... 56 Figure 3.3 Identification of SUCA2 using mapping-by-sequencing. .................................. 57 Figure 3.4 Cloning of SUCA3. ............................................................................................ 58 Figure 3.5 Knockout of CDK8 suppresses the autoimmune resposnes in camta1/2/3. ...... 59 Figure 3.6 Autoimmunity in camta1/2/3 is suppressed by eds1-2. ..................................... 61 Figure 3.7 SARD1 and CBP60G are requried for the camta1/2/3-mediated autoimmunity. ............................................................................................................................................. 64 xiv Figure 3.8 SA-related genes are up-regulated in camta1/2/3 triple mtant plants. ............... 65 Figure 3.9 camta3-3D mutant is compromised in SA accumulation .................................. 66 Figure 3.10 CAMTA3-binding motifs in promoter regions of ICS1 and PBS3. ................. 67 Figure 3.11 Characterization of the cdk8 single mutants. ................................................... 68 Figure 3.12 Expression of ICS1 and EDS5 is down-regulated in cdk8 mutants. ................ 69 Figure 3.13 med12 mutants are compromised in SA synthesis. .......................................... 70 Figure 3.14 CDK8 does not interact with SARD1 or CBP60g proteins. ............................ 75 xv List of Abbreviations 35S A strong promoter from Cauliflower mosaic virus (CaMV) ALD1 Agd2-like defense response protein1 ANF Atrial natriuretic factor APC Anaphase-promoting complex ASK1 Arabidopsis-SKP1-like 1 ATR1 Arabidopsis thaliana recognized 1 AvrB Avirulence protein from Pseudomonas syringae pv. Glycinea AvrL567 Avirulence protein from Melampsora lini AvrPphB Avirulence protein from Pseudomonas syringae pv. tomato DC3000 AvrRpm1 Avirulence protein from Pseudomonas syringae pv. maculicola AvrRps4 Avirulence protein from Pseudomonas syringae pv. pisi AvrRpt2 An avirulence gene from Pseudomonas syringae pv. tomato DC3000 AvrXa7 A transcription activator-like (TAL) effector from Xanthomonas oryzae BAK1 BRI1- associated receptor kinase 1 BIK1 Botrytis–induced kinase 1 BTB Broad-Complex, Tramtrack and Bric a brac CaM Calmodulin CAMTA Calmodulin-binding transcription activators CAMTA3 Calmodulin-binding transcription activator3 CBF2 C-repeat/dehydration responsive element-binding factor 2 CC Coiled-coil domain CCT Center city CDK8 Cyclin-Dependent Kinase 8 CEBiP Chitin elicitor-binding protein ChIP Chromosome immunoprecipitation CKM CDK8 kinase module C-Luc C-terminal luciferase CM2 The second conserved DNA motif CNL Coiled-coil NLR COP1 Constitutive photomorphogenic 1 CRL Cullin-RING Ligases DDB1 UV- damaged DNA-binding protein DIAP1 Drosophila inhibitor of apoptosis 1 DN Dominant-negative DSC Dominant Suppressor of CAMTA3 EBF1 EIN3-BINDING F BOX PROTEIN 1 EDS1 Enhanced disease susceptibility EDS5 Enhanced disease susceptibility 5 EFR Elongation factor Tu receptor EGF Epidermal growth factor EIRP1 Erysiphe necator-induced RING finger protein 1 EMS Ethyl methanesulfonate EMSA Electrophoretic mobility shift assay ETI Effector-triggered immunity xvi FLS2 Flagellin-sensitive 2 FMO1 Flavin-dependent monooxygenase1 HECT Homologous to E6-associated protein C-Terminus HEN3 Hua enhancer3 HopF2 Avirulence protein from Pseudomonas syringae pv. tomato DC3000 Hpa Hyaloperonospera arabidopsidis HR Hypersensitive response ICS1 Isochorismate Synthase 1 JA Jasmonic acid LRR Leucine-rich repeat LYK5 LysM-containing receptor-like kinase 5 LysM Lysine motif MAB2 Macchi-bou 2 MAPK Mitogen-activated protein kinase MEKK MAP kinase kinase kinase MIEL1 MYB30-Interacting E3 Ligase1 MKK MAP kinase kinase MKS1 MAP kinase 4 substrate 1 MOS Modifier of snc1 MPK MAP kinase MUSE Mutant, snc1-enhancing N. benthamiana Nicotiana benthamiana NDR1 Non-race-resistance 1 NF-κB Nuclear factor-κB NLR Nucleotide-binding domain leucine-rich repeat containing protein N-Luc N-terminal luciferase NOD Nucleotide binding and oligomerization domain NPR1 Non-expresser of PR genes 1 NRB4 Non-recognition of BTH4 PAD3 Phytoalexin deficient 3 PAD4 Phytoalexin deficient 4 PAMP Pathogen-associated molecular patterns PBS3 avrPphB susceptible 3 Pep1 Protein essential during penetration-1 PFT1 Phytochrome and flowering time 1 POX12 Maize peroxidase-12 PR gene Pathogenesis-related gene PRR Pattern recognition receptor Psm Pseudomonas syringae pv. maculicola 4326 Pst DC3000 Pseudomonas syringae pv. tomato DC3000 PthXo1 A transcription activator-like (TAL) effector from Xanthomonas oryzae xvii PTI PAMP-triggered immunity R protein Resistance protein RBOHD Respiratory burst oxidase homologue D RIN4 RPM1 interacting protein 4 RING Really Interesting New Gene RIPK Receptor interacting protein kinase RLCK Receptor-like cytoplasmic kinase RLK Receptor-like kinase RLP Receptor-like protein ROS Reactive oxygen species RPP1 Recognition of Peronospora parasitica 1 RPS2 Pseudomonas syringae 2 SA Salicylic acid SAG101 Senescence-associated gene 101 SAR Systemic acquired resistance SARD SAR-Deficient SCF SKP1-CULLIN1-F-box SFR6 Sensitive to freezing 6 SID2 Salicylic acid induction-deficient2 snc1 suppressor of npr1-1, constitutive 1 SNIPER snc1‐influencing plant E3 ligase reverse genetic screen SPIN6 SPL11-interacting Protein 6 SPL11 Spotted Leaf11 SPL6 Squamosa promoter binding protein-like 6 STAND Signal-transduction ATPases with numerous domains SUCA Suppressor of camta1/2/3 SWP Struwwelpeter TIR Toll/interleukin-1 receptor TLR Toll-like receptor TMV tobacco mosaic virus TNF Tumor necrosis factor TNL Toll/Interleukin-1-receptor-like NLR TNV tobacco necrosis virus TRAF Tumor necrosis factor receptor-associated factor UPS Ubiquitin-26S proteasome system WT Wild type xviii Acknowledgements I would like to express my tremendous gratitude to my supervisor Dr. Xin Li for her mentorship. Her dedication to science sets her as a role model for me during my pursuit of the Ph.D. degree. She is always available for discussion whenever I have problems with my projects. Many insightful discussions with her help my projects progress smoothly and deepen my understanding of plant immunity. One of the most important things I learn from her is how to read critically, which enables me to evaluate the reliability of published literatures. Such skill is a treasure for my academic career. I would also offer my gratitude to my committee members Dr. Jae-Hyeok Lee, Dr. James Kronstad and Dr. Yuelin Zhang for their valuable advices on my research. I would like to thank all the former and present members from the Li and the Zhang labs. A big thank you to Dr. Shuai Huang who coached me during the early stage of my Ph.D. Thanks to Dr. Kaeli Johnson, Dr. Fang Xu, Dr. Charles Copeland, Dr. Oliver Dong, Paul Kapos and Kevin Ao for the fruitful discussions. Thanks to Chipan Zhu and Dr. Meixuezi Tong who were always nice and sweet and who made the lab a happy place to work. Thanks to Dr. Tongjun Sun, Yanan Liu and Di Wu for the help they offered me and experimental materials they shared with me. I am grateful for the financial supports from UBC Dewar Endowment Fund, Natural Sciences and Engineering Research Council of Canada (NSERC) and Chinese Scholarship Council (CSC). I also really appreciate the teaching assistantship opportunity the UBC Botany Department provided me. Finally, I would like to thank my dear friends Sishuo Wang and Erik Groenenberg for their companionship and encouragements when I was down, and to my loving family for their unconditional and enduring support. xix Dedication To curiosity.1 1 Introduction 1.1 Plant immune responses Living in an environment surrounded by various pathogenic microbes, plants are under constant threat of diseases. Nevertheless, few pathogens are able to colonize plants. In most of cases, plants are resistant to potential pathogens. The frontline of resistance to pathogens is a preformed physical barrier including waxy cuticles and cell walls (Serrano et al., 2014; Underwood, 2012). To counteract the pathogens that overcome the frontline resistance, plants employ a two-tiered local defense to ward off invading pathogens (Dangl and Jones, 2001b; Jones and Dangl, 2006a) and systemic acquired resistance (SAR) to defend against subsequent infection in distal tissues (Durrant and Dong, 2004; Fu and Dong, 2013). 1.1.1 PAMP-triggered immunity The first layer of local defense is activated through the recognition of conserved microbial molecules, termed pathogen-associated molecular patterns (PAMPs) by transmembrane pattern recognition receptors (PRRs) (Macho and Zipfel, 2014; Zhou et al., 2017; Zipfel, 2014). PRR proteins include superfamilies of receptor-like kinases (RLKs) and receptor-like proteins (RLPs) (Zipfel, 2014), with ~410 RLK genes and ~170 RLP genes in the Arabidopsis genome (Shiu and Bleecker, 2003; Shiu et al., 2004). The best studied examples of PRR-PAMP pairs include Arabidopsis flagellin-sensitive 2 (FLS2) for bacterial flagellin (Zipfel et al., 2004), Arabidopsis EF-TU receptor (EFR) for elongation factor (EF) Tu (Zipfel et al., 2006), as well as Arabidopsis LysM-containing receptor-like kinase 5 (LYK5) (Cao et al., 2014) and rice LysM-RPP chitin elicitor-binding protein (CEBiP) (Kaku et al., 2006) for fungal chitin. A typical RLK comprises three domains: an extracellular ectodomain which perceives PAMP, a transmembrane domain, and an intracellular kinase domain that transduces external signals into cells. RLP proteins share a structure similar to RLKs, except for the lack of a cytoplasmic kinase domain (Zipfel, 2014). PRRs are categorized into distinct subfamilies based on their different N terminal ectodomains, including leucine-rich repeat (LRR) domain, epidermal growth factor (EGF)-like domain, lysine motifs (LysM), and lectin domain (Couto and Zipfel, 2016; Zhou et al., 2017). Recognition of PAMPs by PRRs triggers the first layer of local defense termed PAMP-triggered immunity (PTI), which culminates in the burst of reactive oxygen species 2 (ROS), activation of mitogen-activated protein kinase (MAPK) cascades, callose deposition, induction of salicylic acid (SA) synthesis, and transcriptional reprograming to ward off pathogens (Boller and Felix, 2009). Mechanistic studies suggest that PRRs usually require co-receptors, receptor-like cytoplasmic kinases (RLCKs) and MAPK cascades to transduce downstream signals (Macho and Zipfel, 2014). One of the most intensive studied PRRs is LRR-RLK FLS2 in Arabidopsis. FLS2 recognizes flg22, a conserved 22-amino acid peptide within the N terminal end of bacterial flagellin (Gómez-Gómez and Boller, 2000). In the absence of flg22, FLS2 and co-receptor LRR-RLK BRI1- associated receptor kinase 1 (BAK1) form individual heterodimers with Botrytis–induced kinase 1 (BIK1), which belongs to the RLCK subfamily VII. Upon flg22 perception, BAK1 is recruited to FLS2, resulting in the phosphorylation of BIK1 by BAK1 (Lu et al., 2010; Roux et al., 2011). Phosphorylated BIK1 dissociates from the FLS2-BAK1 complex and binds to respiratory burst oxidase homologue D (RBOHD) on the plasma membrane. BIK1 then phosphorylates RBOHD at multiple residues triggering the production of ROS (Kadota et al., 2014; Li et al., 2014). The MAPK cascades are evolutionarily conserved modules that can convert signals from PRR complexes to downstream responses. A MAPK cascade is composed of three components in a hierarchical order: a MAP kinase kinase kinase (MEKK), a MAP kinase kinase (MKK) and a MAP kinase (MPK). Studies have shown that activated PRR complexes trigger transcriptional reprogramming through MAPK cascades. For example, MPK4 associates with MAP kinase 4 substrate 1 (MKS1)-WRKY33 complex and sequesters the binding of MKS1-WRKY33 to the promoter of PHYTOALEXIN DEFICIENT3 (PAD3). PAD3 encodes a cytochrome P450 enzyme required for the synthesis of antimicrobial camalexin. Upon flg22 elicitation, FLS2 activates and triggers the phosphorylation of the MEKK1-MKK1/MKK2-MPK4 cascade. MSK1 is then phosphorylated by MPK4, which leads to the dissociation of MSK1-WRKY33 complex from MPK4. The released MKS1-WRKY33 complex is recruited to the promoter of PAD3 and induces its expression (Qiu et al., 2008). 3 1.1.2 Effector-triggered immunity (ETI) 1.1.2.1 Effector-triggered susceptibility Adaptive pathogens have evolved effectors with diverse enzymatic activities to subvert PTI and manipulate host metabolism in order to promote their invasion and growth (Kamoun, 2007; Xin and He, 2013). For example, effector AvrPphB, a cysteine protease secreted by Pseudomonas syringae, cleaves BIK1 in Arabidopsis (Zhang et al., 2010a). HopF2, an ADP-ribosyltransferase, interacts with Arabidopsis MKK5 and inactivates it by introducing an ADP-ribose moiety at its C terminus (Wang et al., 2010). The corn smut Ustilago maydis protein essential during penetration-1 (Pep1) binds to maize peroxidase-12 (POX12) and inhibits the burst of ROS produced by POX12 (Hemetsberger et al., 2012). Xanthomonas oryzae transcription activator-like (TAL) effectors PthXo1 and AvrXa7 act as transcriptional activators to induce the expression of rice Os8N3 and Os11N3, respectively (Antony et al., 2010; Yang et al., 2006). Os8N3 and Os11N3 encode sugar transporters in rice. The manipulation of Os8N3 and Os11N3 by PthXo1 and AvrXa7 is suggested to create a nutrient rich environment in favor of bacterial growth (Feng and Zhou, 2012). 1.1.2.2 NLR receptors The development of effectors by pathogens poses a strong selection on host plants. In the arms race between plants and pathogens, to counter invasion by pathogens, plants have evolved resistance (R) proteins to recognize effectors directly or indirectly and induce the second layer of local defense, termed effector-triggered immunity (ETI) (Jones and Dangl, 2006b). ETI is faster and more robust than PTI. Activation of ETI usually culminates in rapid programmed cell death known as the hypersensitive response (HR), production of SA and transcriptional reprogramming. The majority of plant R genes encode nucleotide-binding domain leucine-rich repeat containing (NLR) proteins, which also exist in animals. They belong to the STAND (signal-transduction ATPases with numerous domains) ATPase family (Leipe et al., 2004; Li et al., 2015a). Canonical NLRs are composed of three domains: an N terminal domain, which mediates signaling; a central nucleotide binding and oligomerization domain (NOD) domain that is required for activation, nucleotide-binding and oligomerization of NLRs; and a C-terminal LRR domain (Zhang et al., 2017). Based on their N terminal domains, typical NLRs 4 can be divided into two groups: NLRs containing an N terminal Toll/interleukin-1 receptor (TIR) domain or a coiled-coil (CC) motifs are designated as TNLs and CNLs, respectively (Li et al., 2015a; Maekawa et al., 2012). Genomic analysis reveals that higher plant species experience drastic expansion of NLR coding genes, usually leading to hundreds of NLR genes in the plant genome (Meyers et al., 2003; Yu et al., 2002). Compared with the small number of NLR genes in mammalian species, the highly expanded NLR repertoire in plants suggests that NLRs may compensate for the lack of adaptive immunity in plants (Li et al., 2015a). 1.1.2.3 Recognition of effectors by NLRs NLRs serve as immune receptors to recognize the presence of effectors either directly by binding to effectors, or indirectly by monitoring the activity of effectors on host proteins. Reports on direct recognition remain limited. For example, direct interaction between three flax TNLs (L5, L6, and L7) and flax rust fungus AvrL567 effector was detected by yeast two hybrid assay (Catanzariti et al., 2010; Dodds et al., 2006). Arabidopsis thaliana Recognition of Peronospora parasitica 1 (RPP1) specifically interacts with downy mildew effector Arabidopsis thaliana recognized 1 (ATR1) through its LRR domain (Krasileva et al., 2010; Steinbrenner et al., 2015). In contrast, many cases of indirect recognition of effectors have been documented, suggesting that indirect recognition may be a dominant mechanism for effector perception. Host proteins monitored by plant NLRs are either referred to as guardees which serve as regulators in immune responses, or decoys which are mimics of immune regulators (van der Hoorn and Kamoun, 2008). The best characterized examples of indirect recognition are the detection of RPM1 interacting protein 4 (RIN4) by two CNLs, RPM1 and RPS2 (Day, 2005; Mackey et al., 2002). Two P. syringae effectors, AvrRpm1 and AvrB, promote the phosphorylation of RIN4 through receptor interacting protein kinase (RIPK). Phosphorylation of RIN4 is sensed by RPM1, the recognition of which activates immune responses (Chung et al., 2011; Liu et al., 2011). P. syringae effectors AvrRpt2 is a cysteine protease that cleaves RIN4. The cleavage of RIN4 by AvrRpt2 is detected by RPS2 and results in RPS2-triggered ETI (Axtell and Staskawicz, 2003; Mackey et al., 2003). 5 1.1.2.4 Regulation of ETI: a paradigm from the studies using snc1 The autoimmune snc1 (suppressor of npr1-1, constitutive 1) mutant was identified from a suppressor screen of npr1 (nonexpresser of PR gene 1), which is defective in the expression of pathogenesis-related (PR) genes in response to SA (Li et al., 1999). The snc1 mutant carries a gain-of function mutation in the TNL encoding gene SNC1, leading to a Glu552Lys amino acid change between the NB and the LRR domain of SNC1 protein (Zhang et al., 2003a). The Glu552Lys mutation stabilizes the snc1 protein and causes constitutive activation of immune responses in the absence of pathogens (Cheng et al., 2011a; Gou et al., 2012). The autoimmune phenotypes of snc1 plants include enhanced resistance against pathogens, increased PR gene expression, elevated SA levels and dwarfed size, a hallmark of autoimmune mutants (Zhang et al., 2003a). Since plant size is usually reversely correlated with defense output in autoimmune mutants, autoimmune mutants are useful tools for straight forward genetic screens for isolation of immune regulators. 1.1.2.5 The MOS suppressor screens To identify positive regulators of TNL-mediated immunity, genetic screens have been conducted in snc1-related backgrounds, including snc1 and snc1 npr1-1. These screens lead to the isolation of modifier of snc1 (MOS) genes. Studies on the MOS genes reveal that regulation of TNL-mediated immunity occurs at diverse levels: transcriptional regulation by MOS1 and MOS9 (Li et al., 2010; Xia et al., 2013); post-transcriptional regulation by MOS2, MOS4, and MOS12 (Palma et al., 2007; Xu et al., 2012; Zhang et al., 2005); regulation of mRNA export by MOS3 and MOS11 (Germain et al., 2010; Zhang, 2005); regulation of nucleocytoplasmic protein trafficking by MOS6, MOS7, and MOS14 (Cheng et al., 2009; Palma et al., 2005; Xu et al., 2011); post-translational regulation by MOS5 and MOS8 (Goritschnig et al., 2007, 2008). 1.1.2.6 The MUSE enhancer screens The mutant, snc1-enhancing (MUSE) enhancer screens were conducted in snc1 mos4 and snc1 mos2 npr1-1 backgrounds in order to isolate negative regulators of TNL-mediated immunity. The majority of MUSE genes encode proteins that are involved in post-translational regulation of NLRs, highlighting the importance of post-translational regulation 6 in preventing over activation of immunity (Huang et al., 2013a). For example, a cpr1 allele was identified from the MUSE screen (Huang et al., 2013a). Previous report shows that mutations in CPR1 cause an over accumulation of the NLR proteins SNC1 and RPS2, which leads to autoimmunity. CPR1 encodes an F-box protein and is predicted to be part of a SKP1-CULLIN1-F-box (SCF) E3 ligase complex. CPR1 associates with SNC1 and RPS2, and promotes their degradation (Cheng et al., 2011a). MUSE10 and MUSE12 are two isoforms of HSP90 genes, HSP90.2 and HSP90.3. HSP90 likely assists the formation of the SCFCPR1 E3 complex for SNC1 and RPS2 degradation (Huang et al., 2014a). MUSE13 and MUSE14 encode two redundant tumor necrosis factor receptor-associated factor (TRAF) proteins. MUSE13 and MUSE14 serve as adaptors to bridge NLR proteins, SNC1 and RPS2, to the SCFCPR1 complex for ubiquitination (Huang et al., 2016). MUSE3, an E4 ubiquitin ligase, works together with SCFCPR1 complex to further promote polyubiquitination of SNC1 and RPS2 (Huang et al., 2014b). Poly-ubiquitinated NLR substrates are targeted to the proteasome, facilitated by MUSE3-interacting protein AtCDC48A, for degradation (Copeland et al., 2016). 1.1.2.7 Signaling pathway of ETI Despite the intensive efforts, signaling events leading to ETI activation remain mostly unknown. The best characterized components downstream of NLR activation are enhanced disease susceptibility (EDS1) and NON-RACE-RESISTANCE 1 (NDR1), which are required for ETI triggered by TNLs and CNLs, respectively (Aarts et al., 1998). EDS1 is a lipase-like protein, which forms distinct complexes with another two lipase-like proteins, PHYTOALEXIN DEFICIENT 4 (PAD4) and SAG101 (SENESCENCE-ASSOCIATED GENE 101), the ligase activity of which is dispensable for their function (Wagner et al., 2013). EDS1-PAD4 complexes are distributed in both the cytosol and the nucleus, whereas EDS1-SAG101 complexes are limited to the nuclear compartment (Feys, 2005; Wagner et al., 2013). Addition of NES sequence to EDS1 decreases the nuclear accumulation of EDS1 and compromises resistance against P. syringae pv. tomato (Pst) DC3000 AvrRps4 conferred by RPS4 as well as resistance against H. arabidopsidis (Hpa) isolate Emwa1 conferred by RPP4. This indicates that nuclear localization of EDS1 is required for its function (García et al., 2010). Several TNLs, 7 including RPS4, SNC1, and RPS6, are found to interact with EDS1 (Bhattacharjee et al., 2011; Heidrich et al., 2011). NDR1 encodes an integrin-like protein localizing to the plasma membrane, which likely plays a role in defense signaling. The N terminal region of NDR1 interacts with RIN4, which is indispensable for RPM1 and RPS2 triggered immunity (Day et al., 2006). How EDS1 and NDR1 transduce signals downstream remains elusive. In addition, several studies show that transcription factors are able to associate with NLRs and induce transcriptional reprograming. bHLH84 interacts with SNC1 and RPS4 to positively regulate plant immunity (Xu et al., 2014). Tobacco immune receptor N associates with SPL6 (squamosa promoter binding protein-like 6) to activate expression of defense related genes (Padmanabhan et al., 2013). Barley CNL MLA10 interacts with HvMYB6 to release the repression of HvMYB6 by HvWRKY1 and HvWRKY2, therefore activating gene expression mediated by HvMYB60 (Shen et al., 2007). This raises the question whether direct interaction of NLRs and transcription factors is a general mechanism for NLR signaling. While all the cases discussed above involve different transcription factors, no common components for signaling downstream of EDS1/NDR1 have been identified. This may indicate divergence of the pathways downstream of these common signaling components (Zhang et al., 2017). 1.1.3 SAR Pathogen infection triggers local defense, such as PTI and/or ETI, in infected tissue, which in turn primes resistance against secondary pathogen invasion in uninoculated distal parts of the plant. Such a phenomenon is termed SAR, which was first discovered by Frank Ross in 1961 during the study of tobacco mosaic virus (TMV) infection in tobacco (Ross, 1961). Studies in the 1970s connect SAR with the induction of expression of PR genes as PR proteins accumulate locally and systemically in tobacco in response to TMV (Gianinazzi and Kassanis, 1974; Van Loon and Van Kammen, 1970). Therefore, PR genes are used as molecular markers for both local defense and SAR. In 1979, White found that SA treatment induces the accumulation of PR proteins and resistance against TMV in tobacco (White, 1979). The role of SA as a signal molecule for SAR is supported by two studies published in 1990: 1) Malamy et al., 1990 reported that local and systemic SA levels in tobacco were elevated after TMV infection, which correlated with the induction of PR genes. 2) Métraux et 8 al., 1990 showed that inoculation of tobacco necrosis virus (TNV) or Colletotrichum lagenarium in cucumber plants induced SA levels in the phloem sap. SAR has two main features. First, SAR confers resistance against a broad spectrum of pathogen, such as bacteria, fungi and viruses. Next, SAR is a long-lasting process, which can maintain itself from weeks to months (Durrant and Dong, 2004; Fu and Dong, 2013). 1.1.3.1 Signaling components of SAR Different genetic screens aimed at isolating components of SAR downstream of SA found mutations in the same gene, namely NON-EXPRESSER OF PR GENES1 (NPR1) (Durrant and Dong, 2004). NPR1 regulates SA signaling and is required for both local defense and SAR. Mediator subunit-encoding gene MED15, which was isolated from a forward genetic screen searching for genes involved in SA signaling, is epistatic downstream of NPR1 and contributes to SAR (Canet et al., 2012). 50 SAR-Deficient (sard) mutants that are compromised in SAR were isolated from the SARD screen. Characterization of some of the sard mutants revealed mutations in PAD4, SALICYLIC ACID INDUCTION-DEFICIENT2 (SID2), avrPphB susceptible 3 (PBS3), CALMODULIN-BINDING TRANSCRIPTION ACTIVATOR3 (CAMTA3), AGD2-LIKE DEFENSE RESPONSE PROTEIN1 (ALD1), FLAVIN-DEPENDENT MONOOXYGENASE1 (FMO1) and SARD4, mutations in all of which leads to compromised local defense and SAR (Jing et al., 2011). These components act either upstream of SA biosynthesis or independent of SA. Taken together, it suggests that components involved in local defense and SAR overlap. 1.1.3.2 Mobile signals of SAR Early grafting experiments indicated that a mobile signal was generated in the infected tissues and then transferred to the distal tissues to induce SAR (Dean and Kuć, 1986; White, 1979). The nature of the mobile signal has been under debate for many years. Candidates for the mobile signal include SA (Dempsey et al., 1999), methyl SA (Park et al., 2007), jasmonic acid (Truman et al., 2007), azelaic acid (Jung et al., 2009), N-hydroxy-pipecolic acid (Chen et al., 2018; Hartmann et al., 2018), the lipid transfer protein DIR1 (Maldonado et al., 2002), glycerol-3-phosphate (Chanda et al., 2011) and abietane diterpenoid dehydroabietinal (Chaturvedi et al., 2012). The function of these molecules in SAR has been extensively 9 reviewed (Dempsey and Klessig, 2012; Durrant and Dong, 2004; Fu and Dong, 2013). The identity of the mobile signal remains to be clarified. 1.2 The ubiquitin-26S proteasome system (UPS) Ubiquitination is a post-translational modification conserved throughout eukaryotes. It involves the covalent attachment of a 76 amino acid ubiquitin protein or a ubiquitin chain to a lysine residue of a substrate protein. Ubiquitination regulates various biological processes in eukaryotic cells, including signal transduction, protein trafficking and gene transcription (Duplan and Rivas, 2014). The multifaceted function of ubiquitination is reflected by the huge number of E3 ligase encoding genes in eukaryotic genomes, ranging from around 600 in human to at least 1,500 in Arabidopsis (Deshaies and Joazeiro, 2009; Hua and Vierstra, 2011). Ubiquitination is a three-step enzymatic process involving an E1 (Ub-activating enzyme), an E2 (ubiquitin-conjugating enzyme) and an E3 (ubiquitin ligase) protein (Vierstra, 2009). To begin with, a ubiquitin is activated by being covalently attached to an E1 through a thioester bond. The activated ubiquitin moiety is transferred from E1 to E2. Subsequently, an E3 ligase associates with a substrate protein and catalyzes the transfer of the ubiquitin moiety thioesterified with the E2 to the substrate protein, rendering the ubiquitination of the substrate protein. Therefore, E3 ligases are determinants of the specificity of substrate proteins. After multiple rounds of ubiquitin addition, a poly-ubiquitin chain is formed on the substrate. The fate of a ubiquitinated substrate depends on the length of ubiquitin chain and the position of lysine covalently connecting ubiquitins into a chain (Swatek and Komander, 2016). Monoubiquitination usually marks the substrate protein for intracellular trafficking or protein activation (Deshaies and Joazeiro, 2009). A ubiquitin contains seven lysine residues. Degradation by the 26S proteasome, the most prevalent consequence of ubiquitination, is determined by chains composed of Lys48-linked ubiquitins. In contrast, K63-linked chains are often involved in processes such as activation of proteins (Deshaies and Joazeiro, 2009; Kravtsova-Ivantsiv and Ciechanover, 2012; Kulathu and Komander, 2012). The functions of chains linked by other Lys residues are not always clear. 10 Based on their domain features and modes of action, E3s can be classified into four families: HECT (Homologous to E6-associated protein C-Terminus), RING (Really Interesting New Gene), U-Box and CRL (Cullin-RING Ligases) proteins (Vierstra, 2009). The first three families are simple E3s wherein the interaction sites for an E2 and a substrate protein locate in the same polypeptide. For ubiquitination regulated by RING and U-Box E3s, a substrate protein receives a ubiquitin directly from a E2-ubiquitin (Deshaies and Joazeiro, 2009). Whereas, a ubiquitin is transferred to the HECT E3 substrate indirectly from a E2-ubiquitin, via a HECT- ubiquitin intermediate (Rotin and Kumar, 2009). The CRL E3s consist of multiple subunits in forming E3 complexes, with different Cullin proteins serving as backbones. The CRL E3s can further be divided into four groups according to the composition of subunits, including S-phase kinase-associated protein (Skp1)-Cullin 1-F-box (SCF), CUL3-BTB (Broad-Complex, Tramtrack and Bric a brac), CUL4-DDB1 (UV- damaged DNA-binding protein), and APC (Anaphase-promoting complex) E3s (Cheng and Li, 2012; Trujillo and Shirasu, 2010). 1.2.1 Ubiquitination in plant immunity Ubiquitination provides an efficient approach to control protein stability, which is ideal for responses to external stimuli, such as abiotic and biotic stresses. Clues of E3s involved in plants immunity come from the fact that expression of E3s is altered after PAMPs or pathogen treatment (Duplan and Rivas, 2014). Manipulation of E3 expression by ectopic overexpression or RNAi silencing modulates resistance against pathogens (Marino et al., 2012), supporting the roles of E3s in immune responses. Accumulating studies show that E3s ubiquitinate immune receptors or immune signaling components to regulate plant immunity (Cheng and Li, 2012). 1.2.2 Regulation of immune receptors by E3 ligases Immune receptors, including RLKs and NLRs, are constantly expressed in the plant surveillance system to detect the presence of pathogens. Homeostasis of immune receptors must be tightly regulated in order to avoid over accumulation, which can lead to constitutive activation of immunity. In Arabidopsis, PUB12 and PUB13, two close U-Box type E3 ligase homologs, target RLK FLS2 for degradation upon flagellin recognition. In response to 11 flagellin, BAK1 mediates the phosphorylation of PUB12 and PUB13, which is indispensable for FLS2-PUB12/13 complex formation. Recruitment of PUB12 and PUB13 to FLS2 results in polyubiquitination and degradation of FLS2. When either PUB12 or PUB13 is knocked out, plants exhibit enhanced flagellin-mediated resistance, consistent with their role in FLS2 turnover (Lu et al., 2011a). Liao et al., 2017 showed that pub13 mutants but not pub12 mutants were hypersensitive in chitin-triggered rapid responses, such as burst of ROS and phosphorylation of MAPKs. This suggests that PUB12 and PUB13 undergo sub-functionalization. PUB13 interacts with LYSIN MOTIF RECEPTOR KINASE5 (LYK5), the chitin RLK receptor, and promotes polyubiquitination on the kinase domain of LYK5 in vitro. In addition to RLKs, regulation of NLR turnover by E3s has been reported. For examples, F-box protein CPR1 associates with two NLRs, SNC1 and RPS2, and target them for degradation. Protein levels of SNC1 and RPS2 are decreased when CPR1 is overexpressed. Whereas, knocking out CPR1 results in autoimmunity and higher accumulation of SNC1 and RPS2 proteins. The autoimmunity in cpr1 mutants is mostly restored by loss-of-function of SNC1, suggesting that the autoimmunity caused by CPR1 knockout is largely due to the misregulation of SNC1 (Cheng et al., 2011b). 1.2.3 E3 ligases play positive and negative roles in immune signaling. Besides the regulation of immune receptors, E3 ligases are involved in the negative regulation of defense signaling components to prevent autoimmune responses. For example, Arabidopsis PUB22 functions together with its close homologs PUB23 and PUB24 to suppress immune responses. The pub22 pub23 pub24 triple mutant displays enhanced PTI responses, such as ROS production, MPK3 phosphorylation, and immune marker gene expression. Consistent with the elevated PTI responses, enhanced resistance against virulent bacterial pathogen Pst DC3000 is observed in the pub22 pub23 pub24 triple mutants (Trujillo et al., 2008). PUB22 is shown to target Exo70B2, a component of the exocyst complex required for vesicle trafficking, for ubiquitination and degradation through the UPS. Exo70B2 contributes to rapid and later PTI responses triggered by different elicitors and plays a positive role in resistance against several pathogens including Pst DC3000. Taken together, these results suggest that PUB22 controls PTI signaling through regulating the turnover of Exo70B2 (Stegmann et al., 2012). 12 The rice U-box E3 SPL11 (Spotted Leaf11) also serves as a negative regulator in immune responses. A mutation in SPL11 results in extensive cell death and enhanced resistance against rice pathogens (Zeng et al., 2004). Unlike its Arabidopsis homolog PUB13, SPL11 was found to interact with SPL11-interacting Protein 6 (SPIN6), a Rho GTPase-activating protein, through a yeast-two hybrid screen. In vitro assays showed that ubiquitination and degradation of SPIN6 is mediated by SPL11. Surprisingly, knockdown of SPIN6 through RNAi causes elevated responses to flg22 and chitin in ROS production and enhanced expression of defense marker genes. Furthermore, SPIN6 RNAi lines exhibit spontaneous cell death and increased resistance against fungal pathogen Magnaporthe oryzae, suggesting that SPIN6 plays a negative role in immune responses (Kawano et al., 2010; Liu et al., 2015). How both SPIN6 and its corresponding E3 ligase SPL11 function as negative regulators in immunity remains unknown. To prevent inadequate activation of immune signaling, transcription factors are targeted by E3 ligases. For example, transcription factor MYB30 play a positive role in immune responses. In non-inoculated plants, Arabidopsis RING-type E3 ligase MIEL1 (MYB30-Interacting E3 Ligase1) recruits and subjects MYB30 for degradation to prevent inadequate activation of immunity. Upon pathogen inoculation, MIEL1 expression is repressed and the suppression of MIEL1 on MYB30 is released, leading to induction of immune responses (Marino et al., 2013). In addition to their negative roles, E3 ligases can positively regulate immune responses. RING type E3 EIRP1 (Erysiphe necator-induced RING finger protein 1) in Vitis pseudoreticulata plays a positive role in plant immunity as overexpression of EIRP1 confers resistance against fungal and bacterial pathogens in Arabidopsis. Transcript levels of EIRP1and VpWRKY11 are rapidly induced by powdery mildew. EIRP1 interacts with VpWRKY11 and accelerates its degradation (Yu et al., 2013). A homolog of VpWRKY11 in Arabidopsis, WRKY11, controls the expression of JA synthesis l genes, LOX2 and AOS (Journot-Catalino et al., 2006). Since JA is a negative regulator of plant defense against biotrophic pathogens, it is hypothesized that EIRP1 plays a positive role in immunity by prohibiting JA synthesis which is likely dependent on VpWRKY11 (Yu et al., 2013). Silencing of the U-box E3 encoding gene NtCMPG1 in N. benthamiana compromises HR caused by Avr9 elicitation in Cf9 tobacco, while increased HR is observed upon Cf9/Av9 13 elicitation when Nt CMPG1 is overexpressed. Knocking down of CMPG1 by RNAi in tomato supports higher Cladosporium fulvum growth. Taken together, CMPG1 promotes immune responses in both tobacco and tomato (Gonzalez-Lamothe et al., 2006). However, the ubiquitination substrate of CMPG1 has not been determined. 1.3 Calmodulin-binding transcription activators (CAMTAs) Ca2+ is ubiquitously used as a secondary messenger for signal transduction. One of the various classes of proteins that relay the Ca2+ signal is the EF-hand Ca2+-binding protein calmodulin (CaM) (Ikura et al., 2002). CaMs bind and regulate the activity of a battery of transcription factors, such as WRKYs (Journot-Catalino et al., 2006), MYBs (Jae et al., 2005) and CAMTAs (Bouché et al., 2002). CAMTAs are widely distributed in eukaryotes and play diverse roles in biological processes, ranging from development to response to external stress (Shen et al., 2015). The CAMTAs are composed of multiple domains arranged in a consistent order (Finkler et al., 2007). The first functional domain GC-1, a DNA-binding domain, imparts specific DNA-binding ability to CAMTA. Following GC-1 is a TIG domain that mediates nonspecific DNA-binding and protein dimerization. Ankyrin repeats come after the TIG domain and are involved in protein-protein interactions. The C termini of CAMTA contains IQ motifs with a characteristic sequence of IQXXXRGXXX, which interacts with CaMs and CaM-like proteins (Bouché et al., 2002; Choi et al., 2005). Studies in rice and Drosophila reveal distinct effects of CaMs on CAMTAs. Co-expression of CaM and OsCBT (Oryza sativa CaM-binding transcription factor) compromises OsCBT-mediated transcriptional activation, suggesting that CaM negatively regulates the activity of OsCBT (Choi et al., 2005). On the other hand, association with CaM is indispensable for the transcriptional activity of Drosophila DmCAMTA (Han et al., 2006). 1.3.1 Diverse roles of CAMTAs in Arabidopsis The Arabidopsis thaliana genome encodes six CAMTAs, ranging from CAMTA1 to CAMTA6 (Bouché et al., 2002). The initial study on CAMTA3 identified (G/A/C)CGCG(C/G/T) as a CAMTA3-binding motif in Arabidopsis (Yang and Poovaiah, 2002). In Drosophila, the DmCAMTA is able to bind to sequences with the CGCG core 14 motif (Han et al., 2006), suggesting that the CAMTA-binding core motif is conserved among species. Further studies in rice revealed a second CAMTA-bind motif, namely (C/A)CGTGT (Choi et al., 2005). Interestingly, (C/A)CGTGT is an ABA-responsive cis-element, suggesting that CAMTA transcription factors may be involved in ABA signaling. The transcription activity of Arabidopsis CAMTAs is under debate (Galon et al., 2010a). The human HsCAMTA binds to the homeodomain Nkx2-5 transcription factor, and serves as a coactivator in inducing the expression of the atrial natriuretic factor (ANF) gene (Song et al., 2006). The role of CAMTAs as transcriptional activators is supported by yeast one-hybrid assay (Bouché et al., 2002; Mitsuda et al., 2003), by expression of reporter gene in Arabidopsis protoplasts (Mitsuda et al., 2003) and in Nicotiana benthamiana (Benn et al., 2014), and by cold-mediated gene induction in Arabidopsis (Doherty et al., 2009). However, in vivo studies in A. thaliana propose that CAMTAs function as transcription repressors (Du et al., 2009; Nie et al., 2012). CAMTAs are likely involved in different signaling pathways. Differential transcriptional responses of CAMTAs can be observed as early as 15 mins after exposure to abiotic stresses such as heat, cold, UV, NaCl and wounding, and to plant hormones, including ethylene, ABA, SA, and methyl JA (Yang and Poovaiah, 2002). Galon et al., 2010b reported that CAMTA1 participates in auxin signaling. camta1 mutants are hyper-sensitive to auxin treatment in hypocotyl elongation. In support of the role of CAMTA1 in auxin signaling, expression of AtCAMTA::GUS resembles that of auxin reporter gene DR5. Furthermore, 17 out of 63 genes up regulated in camta1 are related to auxin signaling. In addition to its role in auxin signaling, CAMTA1 plays a positive role in drought response. Increased sensitivity to drought is observed in camta1 mutants compared with wild type, leading to reduced viability of camta1 plants under drought condition. Transcriptome analysis suggests that CAMTA1 may control drought recovery through affecting the expression of genes involved in the ABA signaling pathway (Pandey et al., 2013). CAMTA3 contributes to cold tolerance by directly binding to the promoter of cold acclimation gene CBF2 (C-repeat/dehydration responsive element-binding factor 2) and promoting its expression. camta1 camta3 mutants are compromised in freezing tolerance. Expression of CBF2 is down-regulated in camta3 mutants compared with that in wild type under cold temperature. The second conserved DNA motif (CM2) within the CBF2 promoter 15 region contains a vCGCGb CAMTA binding site. Electrophoretic mobility shift assay (EMSA) revealed that CAMTA3 binds to CM2 and the CGCG core motif is necessary for the binding (Doherty et al., 2009). CAMTAs also are involved in plant immune responses. CAMTA3 functions redundantly with CAMTA1 and CAMTA2 to suppress immunity. Modest autoimmune phenotypes are observed in plants carrying loss-of-function CAMTA3 at low temperature, which disappear at room temperature. In contrast, knockout of CAMTA1, CAMTA2 and CAMTA3 simultaneously results in severe autoimmunity at room temperature, with drastic dwarfed size, extensive cell death and high levels of SA (Kim et al., 2013). On the other hand, gain-of-function camta3-3D mutants display compromised SAR (Jing et al., 2011) and enhanced susceptibility against virulent bacteria pathogen Pst DC3000 (Jing et al., 2011; Nie et al., 2012) and avirulent pathogen Pst DC3000 carrying AvrRps4 or AvrRpt2 (Nie et al., 2012). This suggests that CAMTA3 negatively regulates SAR, basal resistance and ETI mediated by TNL RPS4 and CNL RPS2. 1.3.2 The controversial mechanisms of CAMTAs in plant immunity Despite the efforts on the study of CAMTA3, the major function of CAMTA3 in regulating immune responses is still uncertain. Four hypotheses have been proposed regarding the mechanisms of CAMTAs in immune responses. The initial hypothesis indicates CAMTA3 to be a negative regulator of SA biosynthesis given that high levels of SA accumulate in the autoimmune camta3 plants (Du et al., 2009; Kidokoro et al., 2017; Kim et al., 2013, 2017). However, high SA accumulation is a typical feature in autoimmune mutants, which are either caused by loss-of-function mutations in negative regulators of immunity, or gain-of-function mutations in immune receptors or positive regulators of immunity (Yuan et al., 2018). Du et al., 2009 and Nie et al., 2012 reported that CAMTA3 acts as a negative regulator of immunity by directly inhibiting the expression of EDS1 and NDR1, respectively. This is supported by the promoters of EDS1 and NDR1 carrying a CAMTA3-binding motif (ACGCGT), which is directly bound by CAMTA3 as revealed by chromosome immunoprecipitation (ChIP)-qPCR and EMSA. In addition, the activity of EDS1 promoter-driven luciferase is increased in camta3 protoplasts, but is reduced in protoplasts expressing CAMTA3. Similarly, expression of NDR1 is up-regulated in camta3 plants but down-16 regulated in camta3-3D mutants. The negative regulation of EDS1 by CAMTA3 can neither explain the compromised RPS2-mediated immunity in camta3-3D, which is independent of EDS1, nor address the autoimmunity in camta3 since overexpression of EDS1 alone is insufficient to trigger autoimmune responses (García et al., 2010). Nie et al., 2012 proposed that CAMTA3 negatively regulates immunity by repressing NDR1 expression. Under this hypothesis, the compromised resistance against Pst DC3000 carrying AvrRps4 is puzzling, because resistance to AvrRps4 is independent of NDR1. Transcriptome analysis does not show differential expression of NDR1 in autoimmune camta1/3, camta2/3 and even camta1/2/3 compared with wild type (Kim et al., 2013), raising questions about the negative regulation of NDR1 expression by CAMTA3. The fourth hypothesis disagrees with the role of CAMTA3 as an immune negative regulator and suggests CAMTA3 is a guardee monitored by two TNLs, Dominant Suppressor of CAMTA3 (DSC) 1 and 2. It is suggested that autoimmunity in camta3 is due to activation of DSC1 and DSC2 in the absence of CAMTA3. Programmed cell death triggered by transient expression of DSC1 and DSC2 in Nicotiana benthamiana is inhibited by co-expression with CAMTA3. Overexpression of dominant-negative (DN) forms of DSC1 and DSC2 completely abolishes the autoimmune responses of camta3. Furthermore, CAMTA3 physically associates with DSC1 and DSC2 (Lolle et al., 2017). However, the guardee model of CAMTA3 fails to explain the compromised SAR, basal resistance and ETI mediated by RPS4 and RPS2. In addition, while overexpression of the DN form of DSC1 and DSC2 abolishes the autoimmunity in camta3, it has no effects on the autoimmune responses of camta2/3 double mutants (Lolle et al., 2017). CAMTA2 and CAMTA3 play a redundant role in immunity and CAMTA3 is a major contributor to the autoimmunity in camta2/3 plants as immune responses in camta2 single mutants are comparable to wild type plants (Kim et al., 2013). If DN forms of DSC1 and DSC2 are able to suppress the autoimmunity of camta3, they should also be able to inhibit the autoimmune phenotypes of camta2/3 (Yuan et al., 2018). Future genetic and biochemical studies are required to elucidate the major role of CAMTAs in immune responses. Thesis objective The objective of my Ph.D. projects involves three aspects: 17 a) to elucidate the molecular mechanism of SNIPER4, identified from the snc1‐influencing plant E3 ligase reverse genetic (SNIPER) screen, in plant immunity; b) to unravel the major role of CAMTAs in immune response through isolation and characterization of suppressors from the Suppressor of camta1/2/3 (SUCA) screen; c) to characterize CDK8 isolated from the SUCA screen and study how it regulates SAR. Taken together, my projects deepen our understanding of the regulation of ETI and SAR. 18 2 SCFSNIPER4 controls the turnover of two redundant TRAF proteins in plant immunity 2.1 Summary In mammals, tumor necrosis factor receptor associated factors (TRAFs) are signaling adaptors that regulate diverse physiological processes, including immunity and stress responses. In Arabidopsis, MUSE13 and MUSE14 are redundant TRAF proteins serving as adaptors in the SCFCRP1 complex to facilitate the turnover of nucleotide-binding domain and leucine-rich repeats (NLR) immune receptors. Degradation of MUSE13 is inhibited by proteasome inhibitor, suggesting that the MUSE13 stability is controlled by the 26S proteasome. However, the E3 ligase that regulates MUSE13 level is unknown. Here we report the identification of an F-box protein, SNIPER4 that regulates the turnover of MUSE13 and MUSE14. Protein levels of MUSE13 and MUSE14 are reduced by SNIPER4 overexpression, while higher accumulation of MUSE13 and MUSE14 is observed when dominant-negative SNIPER4 is expressed. Furthermore, SNIPER4 associates with MUSE13 or MUSE14. Taken together, these data suggest that the SCFSNIPER4 complex controls the turnover of TRAF proteins for an optimum immune output. 2.2 Introduction Plants and animals utilize sophisticated innate immune systems to defend against pathogen invasions. Upon infection, plant Pattern-recognition receptors (PRRs) residing on plasma membrane perceive pathogen-associated molecular patterns (PAMPs) and induce PAMP-triggered-immunity (PTI) (Boller and Felix, 2009). Successful pathogens can deliver effectors in host cells to suppress PTI and promote invasion (Jones and Dangl, 2006b). To antagonize the effect of effectors, intracellular nucleotide binding leucine-rich repeat domain receptors (NLRs) recognize effectors directly or indirectly, the recognition of which induces a strong defense response termed effector triggered immunity (ETI). ETI is often more robust than PTI and normally leads to localized programmed cell death known as the hypersensitive response (HR). Plant NLRs are classified into Toll/Interleukin-1-receptor-like NLRs (TNLs) and coiled-coil NLRs (CNLs) based on their different N terminal domains (Dangl and Jones, 2001a; Li et al., 2015b). 19 Inadequate activation of immune responses can lead to disease, while over-activation of ETI may cause growth and development retardation. Thus, plant immunity has to be tightly regulated at multiple levels, especially through controlling the homeostasis of immune receptors. Post-translational regulation via ubiquitination is a major mechanism for regulating the turnover of substrate proteins. Ubiquitination requires an enzymatic cascade mediated by three enzymes: E1 (Ub-activating enzyme), E2 (Ub-conjugating enzyme) and E3 (Ub ligase) which determines substrate specificity. The reactions result in the covalent attachment of a single ubiquitin moiety or an ubiquitin chain to a substrate protein (Deshaies and Joazeiro, 2009). In most studied cases, ubiquitinated substrate proteins are directed for degradation via the 26S proteasome (Smalle and Vierstra, 2004). More recent studies have shown that ubiquitination plays a significant role in controlling the protein levels of plant immune receptors. For example, in ETI, a SKP1-CULLIN1-F-box (SCF) E3 complex SCFCPR1 ubiquitinates the NLRs Suppressor of npr1-1, Constitutive 1 (SNC1) and Resistant to Pseudomonas syringae 2 (RPS2), and subjects them to degradation (Cheng et al., 2011b). Along with the SCFCPR1 E3 complex, two redundant Tumor necrosis factor receptor (TNFR)-associated factors (TRAF) proteins MUSE13 and MUSE14 serve as adaptors to bridge the F-box protein CPR1 and its substrate SNC1 or RPS2 (Huang et al., 2016). During PTI, upon flagellin recognition, BAK1 phosphorylates a pair of U-Box type E3 ligases PUB12 and PUB13. Phosphorylated PUB12 and PUB13 associate PRR receptor FLS2 and promote its degradation (Lu et al., 2011b). The snc1 mutant contains a gain-of-function mutation in a TNL-encoding gene SNC1 (Li et al., 2001; Zhang et al., 2003b). The mutation stabilizes SNC1 and leads to constitutive immune responses without the presence of pathogens (Cheng et al., 2011b). snc1 plants display stunted growth as a result of autoimmunity. As the defense response of snc1 plants is negatively correlated with its size, the snc1 mutant has become an ideal tool for straightforward genetic screens for gene discovery. Indeed, we have conducted two series of forward genetic screens-MODIFIER OF SNC1 (MOS) and MUTANT, SNC1-ENHANCING (MUSE) (Huang et al., 2013a; Johnson et al., 2012), as well as two reverse genetic screens (Xu et al., 2014), using snc1 mutants. These screens resulted in the identification of over twenty new genes regulating plant immunity at various levels. 20 There are over 1,500 E3 ligase-encoding genes in the genome of A. thaliana (Hua and Vierstra, 2011), most of which without known functions (Cheng and Li, 2012). We hypothesized that many E3s are immune regulators. Hence we conducted a reverse genetic screen to identify novel E3s that regulate plant immunity (Tong et al., 2017). In our snc1-influencing plant E3 ligase reverse genetic screen (SNIPER), 104 E3s which can be induced by PAMP treatment (TAIR Microarray Expression databases), or whose promoter is targeted by master immune regulator SAR Deficient 1 (SARD1) (Sun et al., 2015), were overexpressed in the snc1 background to screen for E3s that alter snc1-mediated autoimmunity. Here we report that an F-box protein, SNIPER4, functions in an SCF E3 complex to regulate the turnover of two redundant TRAF proteins, MUSE13 and MUSE14, for an optimum immune output. 2.3 Material and method 2.3.1 Plant growth All plants, unless specified, were grown in growth rooms with climate control at 22oC under long-day regime (16 hr day/8 hr night). 2.3.2 Transcriptional analysis Leaf tissue was harvested from plants grown on ½ MS plates or soil, ground to powder with liquid nitrogen, and then used for total RNA extraction following manufacturer’s protocol (Ambion). Total RNA was reversed transcribed into cDNA using EasyScriptTM cDNA Synthesis Kit (Abm). RT-PCR was carried out as described previously (Zhang et al., 2003). Expression of SNIPER4 was quantified using primers F: 5’- GTT GCG ATC CGA TTC TTT GG-3’ and R: 5’- CTG GAC ACC TTT CTG CGG TG-3’. To measure the transcript levels of MUSE13, primers F: 5’- ATT CCT GTT GGG AGG GAA CG -3’ and R: 5’- CGT CTG CGG TTG AAA TGC TC -3’ were used. Primers F: 5’- CCT GTT AGC AAG GAT CCC AA -3’ and R: 5’- TAC AGG TGC AGC TTG CGT TG -3’ were used for determination of MUSE14 transcriptional levels. The primers for determination of PR1, PR2 and ACT1 transcript levels were described previously (Zhang et al., 2003b). 21 2.3.3 Pathogen infection For Hpa Noco2 infection assays, 10-day-old or 2-week-old soil-grown seedlings were sprayed with conidia spore solution. Plants were kept at 18oC under short day condition (12 hr light/12 hr dark) for 7 days before the quantification of spores on plant leaves. For P. syringae infection, specified P. syringae strains were infiltrated into 4-week-old leaves of soil-grown plants. Infected leaves were harvested at 0 h (Day 0) or 72 h (Day 3) after infiltration. Bacterial titer was quantified as previously described (Zhang et al., 2003b). 2.3.4 Genotyping and Construction of Plasmids T-DNA knockout line Salk_031643 (sniper4) was obtained from ABRC. Homozygous sniper4 mutants were identified using primers F: 5’- GTC CTA CCG GCT TGG AAC AG -3’ and R: 5’- GAT CAC TAC AGA CAT TCA TTG GC -3’. To generate 35S::SNIPER4, genomic sequence of AT3G48880 with 774 bp upstream of the start codon was PCR-amplified using primers F: 5’-CGC GGA TCC GGC CGT CAA GGC CGT TCG ACT GAT TTG GGA ATG-3’ and R: 5’-CGC GAA TTC GGC CCA TGA GGC CTC AAA GAT GAA GAG AAC TCA C-3’. The fragment was digested with SfiI and cloned into pHAN-35S. To create 35S:: At4g11580, At4g11580 genomic sequence was amplified by primers F: 5’- CGC GGA TCC GGC CGT CAA GGC CCT CTT CTT GAA TTG ACT TGT CG-3’ and R: 5’- CGC GAA TTC GGC CCA TGA GGC CCA GCC AAC AAA TCT TTT CAG-3’, digested with SfiI and cloned into pHAN-35S. For the construction of dominant-negative SNIPER4-HA, a deletion between amino acids Arg12 and Asn61 was introduced through site-directed mutagenesis using primers F: 5’-GAT GGG AAG AGT TGT TAG AGC CTT ATG T-3’ and R: 5’-GAC ATA AGG CTC TAA CAA CTC TTC CCA TC-3’. The genomic fragment of SNIPER4 containing 911 bp upstream of start codon was amplified using primers F: 5’-CGC GGA TCC GGC CGT CAA GGC CCT TCA TTT CTC TCA GTG CCC CTT TG-3’ and R: 5’-CGC GAA TTC GGC CCA TGA GGC CAA GAT GAA GAG AAC TCA CTT CAT CAA CC-3’. The cloned sequence was digested with SfiI and ligated into pHAN-35S-HA. 22 2.3.5 Split luciferase complementation assay With genomic WT DNA and pHAN-35S-DN-SNIPER4-HA construct as templates respectively, the SNIPER4 and DN-SNIPER4 were amplified using primers F: 5’-CGC GGA TCC GGC CGT CAA GGC CAT GAT GGA AGA AGA GTA TGA GAG TC-3’ and R: 5’-CGC GAA TTC GGC CCA TGA GGC CCA AGA TGA AGA GAA CTC ACT T-3’. Genomic sequence of MUSE13 was amplified using primers F: 5’-CGC GGA TCC GGC CGT CAA GGC CAT GGC AGA GGC TGT TGA TGA AG-3’ and R: 5’-CGC GAA TTC GGC CCA TGA GGC CCA TGA CCA TTC GAT GGC CTG AAC TC-3’. To amplify genomic sequence of ASK1, primers F: 5’-CGC GGA TCC GGC CGT CAA GGC CAT GTC TGC GAA GAA GAT TGT G-3’ and R: 5’-CGC GAA TTC GGC CCA TGA GGC CCT TCA AAA GCC CAT TGG TTC TC-3’ were used. The above amplicons were digested with SfiI. MUSE14 genomic sequence was amplified with primers F: 5’-CGG GGT ACC ATG TCA GAG AGT ACT AAT GAA G-3’ and R:5’-ACG CAC GCG TCG ACG TGT CCG TTC GAT GGC CTG A-3’, and digested with KpnI and SalI. Digestion products were ligated to the corresponding pCambia1300-35S-HA-Cluc or pCambia1300-35S-HA-Nluc vectors. A. tumefaciens with resulting constructs were infiltrated in N. benthamiana. Infiltrated leaves were treated with 1 mM luciferin 24 h later prior recording luminescence. 2.3.6 Total Protein Extraction, Western Blot and Immunoprecipitation 80 mg A. thaliana tissue was homogenized with liquid nitrogen and resuspended in 0.08 ml extraction buffer (100 mM Tris-HCl pH 8.0, 1 mM PMSF, 0.2% SDS and 2% β-mercaptoethanol) to obtain plant total protein. The extract was mixed with 1/3 volume of 4× SDS loading buffer and boiled for 7 min before western blot analyses. The immunoprecipitation experiment was performed following a previously described procedure with some modifications (Huang et al., 2016). Briefly, proteins from about 2.5 g leaves of 3-week-old soil grown Arabidopsis expressing the indicated proteins were extracted using 2.5 ml extraction buffer (25 mM Tris-HCl pH 7.5, 150 mM NaCl, 1 mM EDTA, 1 mM EGTA, 0.15% Nonidet P-40, 10% glycerol, 1 mM PMSF, 1× protease inhibitor cocktail (Sigma), and 1% w/v polyvinylpolypyrrolidone). Tissue lysate was centrifuged at 1,5000 rpm for 10 min at 4 °C to pellet tissue debris. 25 μL anti-FLAG M2 beads (Sigma; Cat.#A2220) was added to the supernatant and incubated for 30 min at 4 °C 23 with gentle rotation for immunoprecipitation. Beads were centrifuged down at 1,000 rpm for 1 min and washed eight times with extraction buffer. The beads were treated with 1 volume of 2 × SDS loading buffer and boiled for 7 min to release the bounded proteins. 2.4 Results 2.4.1 SNIPER4 overexpression enhances snc1-mediated autoimmunity To search for novel E3 ligases that regulate immune responses, we conducted snc1-influencing plant E3 ligase reverse genetic screen (SNIPER) by overexpressing E3 ligases in the autoimmune snc1 background (Tong et al., 2017). 104 E3s, which are > 1.7-fold up-regulated upon PAMP treatment (TAIR Microarray Expression databases) or potentially regulated by master immune transcriptional regulator SARD1 (Sun et al., 2015), were selected. From the SNIPER screen, overexpression of At3g48880 drastically enhanced the dwarfism of snc1 (Figure 2.1A). At3g48880 encodes an F-box protein and henceforth is designated as SNIPER4. To confirm the role of SNIPER4 in immune responses, expression of the defense marker gene PR1 and PR2 was examined. Consistent with the reduced size, transgenic plants overexpressing SNIPER4 accumulated significantly higher PR1 and PR2 levels compared with snc1 (Figure 2.1B), suggesting that SNIPER4 overexpression enhances snc1-mediated autoimmunity. Interestingly, when SNIPER4 was overexpressed in the Col-0 background, all transgenic plants, even the ones with high transcript levels, were completely wild type (WT) like in regards to morphology (Figure 2.1C and 2.1D). When they were tested for resistance against virulent oomycete pathogen Hyaloperonospora arabidopsidis (Hpa) Noco2 (Figure 2.1E) or bacterial pathogen P. syringae pv. maculicola (Psm) 4326 (Figure 2.1F), they again did not exhibit differences from WT. These data indicate that SNIPER4 is a positive regulator of immunity; its effect seems only obvious in the sensitized snc1 background. Analysis of SNIPER4 homologs showed that SNIPER4 is conserved in higher plants (Figure 2.2A). Phylogenetic analysis of Arabidopsis F-box proteins showed that At4g11580 is the closest homolog of SNIPER4 (Figure 2.2B), although AT4G11580 and SNIPER4 only share 26% identity and 46% similarity in amino acid sequence. To examine the potential redundancy of AT4G11580, AT4G11580 was overexpressed in snc1. In contrast to dramatic 24 effect of SNIPER4 overexpression in snc1, overexpression of AT4G11580 did not lead to observable alteration of morphology and weight in snc1 (Figure 2.2C and 2.2D), suggesting AT4G11580 and SNIPER4 are unlikely to be functionally redundant. Figure 2.1 Overexpression of SNIPER4 enhances the autoimmunity of snc1 but has no effect in wild type Col-0. (A) Morphology of 4-week-old soil-grown plants of wild type (WT), snc1 and two independent transgenic lines overexpressing SNIPER4 in the snc1 background. (B) RT-PCR analysis of PR1, PR2 and SNIPER4 expression in plants shown in (A). ACT1 is used as loading control. (C) Morphology of 4-week-old soil-grown WT and two independent SNIPER4 transgenic plants in WT background. 25 (D) qPCR analysis of SNIPER4 gene expression in plants shown in (C). Letters represent statistical significance (p < 0.01, one-way ANOVA) among specified genotypes. Error bars indicate mean values of 3 replicates ± SD. ACT1 is used as internal control. (E) Quantification of Hpa Noco2 conidia spore growth on the indicated genotypes. eds1-2 serves as a postive control. 10-day-old seedlings were spray-inoculated with 5 × 104 spores/ml inoculum. Spores were quantified at 7 days post inoculation (dpi). Letters represent statistical significance (p < 0.01, one-way ANOVA) among specified genotypes. Error bars indicate mean values of 5 replicates ± SD. (F) Bacterial growth of Psm ES4326 on 4-week-old soil-grown plants of the indicated genotypes. eds1-2 serves as a postive control. Bacterial suspension was diluted to OD600=0.002 and infiltrated into leaves with a needleless syringe. Statistical test was only conducted in day 3 samples. Letters represent statistical significance (p < 0.01, one-way ANOVA) among specified genotypes. Error bars indicate mean values of 5 replicates ± SD. 2.4.2 SNIPER4 is part of an SCF E3 complex Sequence analysis of SNIPER4 identified an F-box domain at its N-terminus and a C-terminal leucine-rich repeat (LRR) domain (Figure 2.2E). F-box proteins normally function in SCF E3 complexes, acting as adaptors to connect substrate proteins to SKP1 for ubiquitination (Kuroda et al., 2002; Xu et al., 2009). The F-box domain of SNIPER4 is predicted to associate with SKPs in SCF E3 complex, while the LRR domain mediates protein-protein interaction with its substrates (Hua and Vierstra, 2011). From the publicly available yeast-two-hybrid dataset (Arabidopsis Interactome Mapping Consortium, 2011), SNIPER4 was found to interact directly with not only AT1G75950 (Arabidopsis-SKP1-like 1, ASK1), but also the other redundant ASK proteins AT5G42190 (ASK2), AT2G25700 (ASK3) and AT1G20140 (ASK4) (Dreze et al., 2011). To further test the interaction between SNIPER4 and ASK1, SNIPER4 and ASK1 were fused with C-terminal luciferase (C-Luc) and N-terminal luciferase (N-Luc) respectively for split-luciferase complementation assay. The assay confirmed that SNIPER4 interacts with ASK1 (Figure 2.3), indicating that SNIPRE4 is indeed part of an SCFSNIPER4 E3 complex. 26 Figure 2.2 Sequence analysis of SNIPER4. (A) A phylogenetic tree of SNIPER4 and its orthologs in higher plants. Sequences of SNIPER4 orthologs were retrieved from NCBI (https://blast.ncbi.nlm.nih.gov/Blast.cgi) using SNIPER4 full-length amino acid sequence as input. Sequences were first aligned by MUSCLE, then subjected to construct a Neighbor-joining tree using MEGA 7.0 with JTT model. The bootstrap value is 1000. Ortholog sequences are: Citrus sinensis (XP_006490368), Populus trichocarpa (XP_002318828), Glycine max (XP_006606101), Brassica rapa (XP_009151585), Vitis vinifera (XP_002262912), Solanum tuberosum (XP_006353318), Zea mays (XP_008667948), Oryza sativa (XP_015612728), and Selaginella moellendorffii (XP_002974092). 27 (B) Part of the phylogenetic tree of Arabidopsis F-box protein superfamily (Gagne et al., 2002). (C) Morphology of 3.5-week-old soil-grown plants of WT, snc1, 10 independent snc1 lines overexpressing At4g11580. (D) Fresh weight of 3.5-week-old soil-grown plants of the indicated genotypes. Letters represent statistical significance analyzed by one-way ANOVA among indicated genotypes (p < 0.05). Error bars indicate mean values of 6 replicates ± SD. (E) Protein structure of SNIPER4. Gray and blue boxes represent the F-box domain and the LRR domain, respectively. An arrow indicates the sniper4 mutation site. Figure 2.3 SNIPER4 associates with ASK1. SNIPER4 associates with AKS1 in split luciferase complementation assay. Indicated constructs were co-infiltrated in N. benthamiana. Cluc-MKK6 and MPK4-Nluc constructs served as positive control. 2.4.3 SNIPER4 knockout reduces SNC1 protein levels and attenuates snc1-mediated autoimmunity As overexpression of SNIPER4 enhances snc1 autoimmunity, we tested whether SNIPER4 knockout affects snc1 phenotypes. An exonic T-DNA insertional mutant of SNIPER4 (Salk_031643) was obtained from the Arabidopsis Biological Resource Centre (ABRC) and was named sniper4 (Figure 2.4A). RT-PCR showed that sniper4 mutants accumulated significantly less SNIPER4 transcripts compared with wild type (Figure 2.4B). We crossed sniper4 with snc1 to generate the sniper4 snc1 double mutant. While sniper4 plants are WT-like in morphology, sniper4 snc1 mutant shows larger size and increased plant biomass compared with snc1 plants (Figure 2.4C and 2.4D). In addition, enhanced disease resistance against Hpa Noco2 (Figure 2.4E) and elevated PR gene expression (Figure 2.4F) in snc1 are partially suppressed by sniper4. In summary, sniper4 knockout partially suppresses the autoimmune phenotypes of snc1. 28 Figure 2.4 sniper4 partially suppresses the autoimmunity of snc1. (A) Gene structure of SNIPER4. Black and gray boxes represent exons and untranslated regions, respectively. Introns are indicated by lines. The arrow head indicates the T-DNA insertion site in sniper4. Primers used for RT-PCR (B) are represented by arrows. (B) RT-PCR analysis of SNIPER4 expression in indicated plants. RNA was extracted from 10-day-old seedlings grown on ½ MS plates, and reversely transribed into cDNA. ACT1 is used as loading control. (C) Morphology of 4-week-old soil grown WT, snc1, sniper4 and sniper4 snc1 double mutant plants. (D) Fresh weight of 4-week-old soil-grown plants of the indicated genotypes. Letters represent statistical significance analyzed by one-way ANOVA among indicated genotypes (p < 0.01). Error bars indicate mean values of 6 replicates ± SD. (E) Quantification of Hpa Noco2 conidia spore growth on the indicated genotypes. 10-day-old seedlings were spray-inoculated with 105 spores/ml inoculum. Spores were quantified at 7 dpi. Letters represent statistical significance (p < 0.01, one-way ANOVA) among specified genotypes. Error bars indicate mean values of 5 replicates ± SD. (F) qPCR analysis of PR1 and PR2 gene expression in plants shown in (A). Letters represent statistical significance (p < 0.05, one-way ANOVA) among specified genotypes. Error bars indicate mean values of 3 replicates ± SD. ACT1 is used as internal control. 29 (G) Western blot analysis of SNC1 protein levels in the indicated genotypes. Total protein was extracted from 10-day-old seedlings grown on ½ MS plates. SNC1 protein levels were examined using an anti-SNC1 antibody (Li et al., 2010). Ponceau staining serves as loading control. Relative band intensity quantified by Image J is indicated below the image. (H) qPCR analysis of SNC1 gene expression of plants from (E). Error bars indicate mean values of 3 replicates ± SD. ACT1 is used as internal control. SNC1 expression in sniper4 snc1 was normalized to that in snc1. SNC1 expression in sniper4 was normalized to that in WT. To examine whether SNIPER4 is a general positive regulator of plant immunity, we challenged sniper4 single mutant plants with both virulent and avirulent pathogens. Resistance to virulent pathogens Psm ES4324 and Hpa Noco2, and avirulent Pst DC3000 AvrRps4, Pst DC3000 AvrRpt2 and Pst DC3000 AvrRpm1 in sniper4 plants is comparable to that in WT (Figure 2.5A to 2.5E). The lack of observable susceptibility of sniper4 plants either is due to that SNIPER4 does not regulate basal resistance or defense response mediated by RPS4, RPS2 and RPM1, or that the effect of sniper4 knockout on immunity is too weak to be observed. As the dramatic phenotypes of plants overexpressing SNIPER4 in snc1 background are reminiscent of muse mutants, most of which affect SNC1 homeostasis, we analyzed SNC1 protein levels in sniper4 and sniper4 snc1 plants. Western blot analysis revealed that SNC1 protein levels in sniper4 is slightly less than WT, while it is considerably less in sniper4 snc1 than in snc1 (Figure 2.4G). To test whether the reduced snc1 accumulation in sniper4 snc1 is due to lower snc1 transcripts, transcript levels of SNC1 is examined. sniper4 snc1 accumulates similar snc1 transcripts as snc1 plants (Figure 2.4H), indicating that SNIPER4 positively regulates the autoimmunity of snc1 by affecting the stability of snc1 proteins. When SNIPER4 is knocked out, less SNC1 protein accumulates. 2.4.4 Overexpression of SNIPER4 enhances disease resistance in muse13 or muse14 single mutant Since SNIPER4 is an F-box protein in an SCF E3 complex, and its overexpression enhances snc1-mediated autoimmunity, we hypothesized that SNIPER4 likely targets a negative regulator of SNC1 for ubiquitination and degradation. The phenotype of SNIPER4 overexpression line should therefore resemble that of the knockout of its substrate, while the phenotype of sniper4 mutant should be similar to that of the substrate overexpression plants. 30 As the previous snc1 enhancer screens (Mutant, snc1 enhancing; MUSE screens) conducted in mos2 snc1 npr1 or mos4 snc1 background identified a number of negative regulators of SNC1, many of which also affect SNC1 homeostasis, they became candidates of SCFSNIPER4 substrate. Figure 2.5 sniper4 knockout plants do not exhibit enhanced disease susceptibility. (A) Bacterial growth of Psm ES4326 in 4-week-old soil-grown plants of WT, sniper4 and eds1-2. Bacterial suspension was diluted to OD600=0.0002 and infiltrated into leaves with syringe. Statistical test was only conducted in day 3 samples. Letters represent statistical significance (p < 0.01, one-way ANOVA) among specified genotypes. Error bars indicate mean values of 5 replicates ± SD. (B) Quantification of Hpa Noco2 conidia growth on plants of the indicated genotypes at 7 dpi with 5 × 104 spores/ml inoculum. Letters represent statistical significance (p < 0.01, one-way ANOVA) among specified genotypes. Error bars indicate mean values of 5 replicates ± SD. (C-E) Quantification of growth of Pst DC3000 with AvrRps4 (C), AvrRpt2 (D) or AvrRpm1 (E) in 4-week-old soil-grown plants of the specified genotypes. Leaves were infiltrated with bacterial suspension at an OD600=0.001. Statistical test was only conducted in day 3 samples. Letters represent statistical significance analyzed by (p < 0.01, one-way ANOVA) among specified genotypes. Error bars indicate mean values of 5 replicates ± SD. 31 When the knockout and overexpression phenotypes of the muse mutants were compared with that of SNIPER4 overexpression and loss-of-function lines, respectively, muse13 or muse14 stood out as they resembled OX-SNIPER4 the most (Huang et al., 2016). Knockout mutations of MUSE13 or MUSE14 in snc1 lead to severe dwarfism (Huang et al., 2016), reminiscent of SNIPER4 overexpression in snc1 (Figure 2.1A). In addition, single mutants of muse13 are wild type like (Huang et al., 2016), similar to the phenotype of SNIPER4 overexpression in Col-0. Furthermore, overexpression of MUSE13 partially suppresses snc1, similar to sniper4 snc1 double mutant (Figure 2.4C). Therefore, we hypothesized that the turnover of MUSE13 or MUSE14 might be regulated by SNIPER4. In support of this hypothesis, previous data suggested that the stability of MUSE13 is indeed regulated by an unknown E3 ligase since the degradation of MUSE13 is inhibited by proteasome inhibitor MG132 treatment (Huang et al., 2016). 32 Figure 2.6 Overexpression of SNIIPER4 activates immune responses in muse13 or muse14 background. (A) Morphology of 4.5-week-old soil grown plants of WT, muse13-2 muse14-1 (m.m.), muse13-2, SNIPER4 transgenic line in the muse13-2 background, muse14-1 and SNIPER4 transgenic line in the muse14-1 background. (B) Fresh weight of 4-week-old soil-grown plants of the indicated genotypes under short day condition. Letters represent statistical significance analyzed by one-way ANOVA among indicated genotypes (p < 0.05). Error bars indicate mean values of 6 replicates ± SD. (C) Quantification of Hpa Noco2 conidia growth on the indicated genotypes. Two-week-old seedlings were spray-inoculated with 7.5 × 104 spores/ml inoculum. Spores are quantified at 7 dpi. Letters represent statistical significance (p < 0.01, one-way ANOVA) among specified genotypes. Error bars indicate mean values of 5 replicates ± SD. (D) Western blot analysis of SNC1 protein levels in the indicated genotypes. Total protein was extracted from 4.5-week-old soil grown plants. Ponceau staining serves as loading control. Relative band intensity indicated below the image is measured by Image J. Vertical line: bands from the same blot with relevant treatments are put together. MUSE13 is functionally redundant with its closest homolog MUSE14. Due to genetic redundancy, muse13-2 and muse14-1 single mutants are WT-like in morphology, PR gene 33 expression and resistance to Hpa Noco2. However, muse13-2 muse14-1 double mutants exhibit extreme autoimmunity, culminating in severe dwarfism, constitutive PR gene expression and resistance to Hpa Noco2 (Huang et al., 2016). To test whether SNIPER4 regulates the turnover of MUSE13 and/or MUSE14, we transformed 35S::SNIPER4 into muse13-2 and muse14-1 single mutants. The prediction was that if SNIPRE4 controls the degradation of MUSE13 and/or MUSE14, SNIPER4 overexpression in muse13 or muse14 single mutant backgrounds should be able to overcome the genetic redundancy of MUSE13 and MUSE14, leading to autoimmunity. As shown in Figure 2.6A and 2.6B, SNIPER4 overexpression reduces the plant size and plant biomass of muse13-2 almost to muse13-2 muse14-1 level. In addition, overexpressing SNIPER4 in muse14-1 also displays apparent dwarfed morphology and reduced plant biomass compared with that of muse14-1 plants (Figure 2.6A and 2.6B). Consistent with the reduced size, these transgenic plants exhibit enhanced disease resistance to Hpa Noco2 (Figure 2.6C) compared with muse13-2 and muse14-1 single mutants. SNC1 protein levels are higher in transgenic plants compared with that in muse13-2 and muse14-1 single mutants (Figure 2.6D). Taken together, SNIPER4 does seem to affect both MUSE13 and MUSE14, with MUSE14 likely being a preferred substrate. It therefore became the most likely E3 candidate for the regulation of MUSE13 and MUSE14 turnover. 2.4.5 SNIPER4 regulates the turnover of MUSE13 and MUSE14 To test whether SCFSNIPER4 controls MUSE13/14 levels, we first examined whether SNIPER4 affects the protein stability of MUSE14. When MUSE14::MUSE14-FLAG was transiently co-expressed with 35S::SNIPER4 in Nicotiana (N.) benthamiana, less MUSE14-FLAG protein accumulated compared with empty vector control (Figure 2.7A), suggesting that SNIPER4 negatively regulates MUSE14 levels . To confirm the effect of SNIPER4 on MUSE14 observed in tobacco, and to test whether SNIPER4 also regulates the stability of MUSE13, we transformed 35S::SNIPER4 into Arabidopsis transgenic lines expressing either MUSE13::MUSE13-FLAG or MUSE14::MUSE14-FLAG. As shown in Figure 2.7B, overexpression of SNIPER4 significantly reduced the levels of MUSE13-FLAG in multiple transgenic lines. RT-PCR analysis revealed that overexpression of SNIPER4 did not alter MUSE13 transcript levels 34 (Figure 2.7C), excluding the possibility that SNIPER4 negatively regulates the transcription of MUSE13. Similarly, when SNIPER4 was overexpressed in a MUSE14::MUSE14-FLAG line, MUSE14-FLAG levels were reduced (Figure 2.7D) while their transcripts were not affected (Figure 2.7E). Together, SNIPER4 indeed negatively regulates both MUSE13 and MUSE14 levels. Deletion of the F-box domain in an F-box protein can disrupt ubiquitination of the substrate but maintains the interaction between the F-box proteins and their substrates, leading to a dominant-negative (DN) form of the F-box protein (Yaron et al., 1998). We therefore generated a DN form of SNIPER4 by introducing a deletion in its F-box domain through PCR. Among nine independent transgenic plants, three exhibited snc1-suppressing morphology. This is expected as knocking out SNIPER4 partially suppresses snc1 (Figure 2.4). Using one representative line, it was shown that expression of 35S::DN-SNIPER4-HA partially suppressed the dwarfism (Figure 2.8A), constitutive PR gene expression (Figure 2.8B) and enhanced resistance against Hpa Noco2 (Figure 2.8C) of snc1, suggesting that DN-SNIPER4-HA is functional. As shown in Figure 2.8D and 2.8E, much higher accumulation of MUSE13-FLAG and MUSE14-FLAG was observed when 35S::DN-SNIPER4-HA was transformed into MUSE13::MUSE13-FLAG or MUSE14::MUSE14-FLAG transgenic line. Taken together, SNIPER4 controls the turnover of MUSE13 and MUSE14. Overexpression of SNIPER4 leads to reduced MUSE13 and MUSE14 levels, whereas reducing SNIPER4 by overexpression of DN-SNIPER4 results in higher accumulation of the two MUSE proteins. 35 Figure 2.7 Overexpression of SNIPER4 reduces MUSE13 and MUSE14 protein levels. (A) Western blot analysis of MUSE14-FLAG levels in N. Benthamiana. MUSE14-FLAG was transiently co-expressed with SNIPER4 or empty vector (EV). Total protein extract was subjected to immunoblot analysis with anti-FLAG. The right bar chart shows relative intensity of MUSE14-FLAG bands to Ponseau staining control from three biological repeats. Letters represent statistical significance (p < 0.01, one-way ANOVA). (B) Western blot analysis of MUSE13-FLAG levels in 5 independent MUSE13-FLAG transgenic lines overexpressing SNIPER4. Total protein was extracted from 10-day-old seedlings grown on ½ MS plates and subjected to immunoblot analysis. (C) qPCR analysis of MUSE13 expression in the indicated genotypes shown in (B). Total RNA was extracted from 10-day-old seedlings grown on ½ MS plates and reversely transcribed into cDNA for qPCR. Letters represent statistical significance (one-way ANOVA) among the specified genotypes. Error bars indicate mean values of 3 replicates ± SD. ACT1 is used as internal control. (D) Western blot analysis of MUSE14-FLAG levels in two independent MUSE14-FLAG transgenic lines overexpressing SNIPER4. Total protein was extracted from 10-day-old seedlings grown on ½ MS plates and subjected to immunoblot analysis. (E) qPCR analysis of MUSE14 expression in indicated genotypes shown in (D). Total RNA was extracted from 10-day-old seedlings grown on ½ MS plates. ACT1 is used as internal control. Letters represent statistical significance (one-way ANOVA) among the specified genotypes. Error bars indicate mean values of 3 replicates ± SD. 36 Figure 2.8 A dominant-negative (DN) version of SNIPER4 leads to MUSE13-FLAG and MUSE14-FLAG protein accumulations. (A) Morphology of 4-week-old soil grown plants of WT, snc1, and DN-SNIPER4-HA transgenic line in the snc1 background. (B) RT-PCR analysis of PR1 and PR2 gene expression in plants shown in (A). (C) Quantification of Hpa Noco2 conidia growth on indicated genotypes. Two-week-old seedlings were spray inoculated with 105 spores/ml inoculum. Spores are quantified at 7 dpi. Letters represent statistical significance (p < 0.01, one-way ANOVA) among specified genotypes. Error bars indicate mean values of 5 replicates ± SD. (D) Western blot analysis of MUSE13-FLAG in 3 independent transgenic lines overexpressing DN-SNIPER4-HA in Arabidopsis. Total protein was extracted from 10-day-old seedlings grown on ½ MS plates and subjected to immunoblot analysis. (E) Western blot analysis of MUSE14-FLAG in 5 independent transgenic lines overexpressing DN-SNIPER4-HA in Arabidopsis. Total protein was extracted from 10-day-old seedlings grown on ½ MS plates and subjected to immunoblot analysis. 37 2.4.6 SNIPER4 associates with MUSE13 and MUSE14 in vivo Due to the negative effects of SNIPER4 on MUSE13 and MUSE14 accumulation, we further tested whether SNIPER4 interacts with MUSE13 or MUSE14 using split-luciferase complementation assay. DN-SNIPER4 was fused to C-Luc, whereas MUSE13 or MUSE14 was cloned in-frame with N-Luc. Split luciferase complementation assay showed that indeed DN-SNIPER4 associates with MUSE13 or MUSE14 upon co-expression of MUSE13-N-Luc or MUSE14-N-Luc with DN-SNIPER4-C-Luc in N. benthamiana (Figure 2.9A and 2.9B). In addition, when 35S::DN-SNIPER4-HA was stably co-expressed with MUSE13::MUSE13-FLAG in Arabidopsis, DN-SNIPER4-HA co-immunoprecipitated with MUSE13-FLAG (Figure 2.9C). Taken together, SNIPER4 interacts with MUSE13 or MUSE14 in planta, supporting the hypothesis that SCFSNIPER4 targets MUSE13/14 for ubiquitination and further degradation. Figure 2.9 SNIPER4 interacts with MUSE13 or MUSE14. 38 (A) SNIPER4 interacts with MUSE13 in split luciferase complementation assay. Indicated constructs were co-infiltrated in N. benthamiana. Cluc-MKK6 and MPK4-Nluc constructs served as positive control. (B) SNIPER4 associates with MUSE14 in split luciferase complementation assay. Indicated constructs were co-infiltrated in N. benthamiana. Cluc-MKK6 and MPK4-Nluc constructs served as positive control. (C) Immunoprecipitation of DN-SNIPER4-HA by MUSE13-FLAG in Arabidopsis plants stably transformed with both MUSE13-FLAG and DN-SNIPER4-HA. Proteins extracted from MUSE13-FLAG plants and MUSE13-FLAG plants expressing DN-SNIPER4-HA were pulled down by anti-FLAG agarose beads. DN-SNIPER4-HA was visualized using anti-HA antibodies. 2.5 Discussion From our SNIPER reverse genetic screen, an F-box protein SNIPER4 was identified as a positive regulator of ETI. Direct interaction between SNIPER4 and ASK proteins suggests that SNIPER4 is part of an SCFSNIPER4 E3 ligase complex. SNIPER4 was found to negatively regulate MUSE13 and MUSE14 accumulation, resulting in fine-tuned protein levels of NLRs. 2.5.1 The SNIPER screen is an efficient approach to identify E3s involved in plant immunity Ubiquitination regulates almost every aspect of plant development and responses to stimuli (Duplan and Rivas, 2014). Accumulating reports show that ubiquitination plays vital roles in plant immunity. Modifier of snc1 5 (MOS5) encodes Ub-activating enzyme UBA1 in Arabidopsis. Mutation in MOS5 suppresses the autoimmunity of snc1 and impairs defense against virulent pathogen Psm ES4326 as well as avirulent pathogen Pst DC3000 AvrRpt2, indicating the importance of ubiquitination in plant immunity (Goritschnig et al., 2007). E3 ligases are key substrate determinants of ubiquitination reactions. A number of E3s have been shown to regulate plant immunity. For example, U-box E3 PUB12 and PUB13 regulate the turnover of PAMP receptor FLS2 (Lu et al., 2011b). Redundant U-box E3 PUB22, PUB23 and PUB24 negatively regulate PTI (Trujillo et al., 2008). Given the large number of E3s (>1,500) encoded in the Arabidopsis genome, E3s with assigned function remain scarce. SNIPER3/SAUL1 was the first E3 ligase identified in our SNIPER screen for immune-regulating E3s. U-box E3 SAUL1/PUB44 and its homolog PUB43 are positive regulators of 39 PTI, the former of which is guarded by TNL SOC3. Both knockout and overexpression of SAUL1 cause autoimmunity mediated through SOC3 (Tong et al., 2017). There are several advantages with the SNIPER screen. First, redundancy precludes discovery of redundant genes via forward genetic screens. Redundancy can be overcome by using an overexpression approach. Second, the sensitized snc1 genetic background enables the identification of E3 with modest phenotypes. For example, overexpression of SNIPER4 in a wild type background does not trigger observable changes in morphology (Figure 2.1C) or immune responses (Figure 2.5A to 2.5E). However, overexpression of SNIPER4 drastically enhances the dwarfism and PR gene expression in snc1 (Figure 2.1A). With snc1 in the background, altered immunity caused by E3s can be visualized through plant size, accelerating the screening process. Despite all these advantages, E3s that regulate immune pathways other than TNL-mediated immunity may still be overlooked as snc1 specifically activates TNL-mediated immunity. This problem can be potentially solved by conducting parallel screens using other autoimmune mutants activated in different pathways as screening backgrounds. 2.5.2 Hierarchical organization of ubiquitination and substrate protein degradation Degradation of E3 ligases can be mediated via in-cis (acting on itself) and or in-trans (acting on others) mechanisms by E3s. Examples of in-trans regulation of E3 ligases includes: 1) RING-type E3 Drosophila inhibitor of apoptosis 1 (DIAP1) is targeted for degradation by another RING E3 DIAP2 (Herman-Bachinsky et al., 2007); 2) CRL complex APC/CCDH1 E3 mediates the degradation of F-box proteins, SKP2 (Bashir et al., 2004; Wei et al., 2004), and TOME-1 (Ayad et al., 2003) during G1 phase; 3) Degradation of F-box protein EIN3-BINDING F BOX PROTEIN 1 (EBF1) and EBF2 is mediated by RING E3 Constitutive photomorphogenic 1 (COP1) (Shi et al., 2016). de Bie and Ciechanover (2011) proposed several modes of hierarchical organizations of E3 degradation, which can be mediated through either in-cis self-ubiquitination or in-trans by an external E3 in a circular manner. Alternatively, one E3 can regulate single or multiple other E3s in a linear manner, and is subjected for degradation via self-ubiquitination or another proteolytic approach. In our study, the ubiquitination of SCFCPR1 complex adaptor MUSE13/14 seems to be mediated in-trans by SCFSNIPER4, in which MUSE13 and MUSE14, not the F-box protein of 40 SCFCPR1, is directed for degradation by SCFSNIPER4. According to the modes of hierarchical organizations of E3 degradation, it would be an interesting question to address in the future what then controls the degradation of SCFSNIPER4. Is it regulated by self-ubiquitination, or by SCFCPR1 in a circular manner, or by another E3 in a linear manner? In-trans ubiquitination of E3 ligases often occurs in response to stimuli for quick responses (de Bie and Ciechanover, 2011). Currently, substrates of only limited number of over 1,500 E3s have been identified in Arabidopsis. Further investigation of E3 ligase substrates will help uncover the roles of in-tran regulation of E3 in plants, especially in response to stimuli, and provide a detailed picture of hierarchical organizations of E3 degradation. 2.5.3 SCFSNIPER4 regulates the protein levels of TRAF proteins MUSE13 and MUSE14 Mammalian TRAF proteins are intracellular master signal transducers that relay signal from membrane receptors, such as tumor necrosis factors (TNFs) or Toll-like receptors (TLRs), to downstream effectors including nuclear factor-κB (NF-κB) and the mitogen-activated protein kinases (MAPKs)(Häcker et al., 2011a). Germ-line and cell-specific TRAF-deficient mice studies show that TRAFs regulate diverse biological processes, including innate and adaptive immunity, stress response and embryonic development (Xie, 2013a). In humans, the TRAF family consists of seven members (TRAF1 to 7) with a characteristic TRAF domain at C-termini (except for TRAF7). As a protein-protein interaction domain, the TRAF domain mediates TRAF oligomerization and interactions with downstream effectors. TRAF2 to TRAF7 also contains an N-terminal really interesting new gene (RING) finger domain, a domain shared by RING-type E3 ligases, followed by a variable number of zinc finger domains (Pineda et al., 2007). Thus, most mammalian TRAFs serve as E3 ligases in addition to adaptors (Xie, 2013a). Post-translational modifications, including ubiquitination, regulate TRAF-mediated signaling. As most mammalian TRAFs are E3 ligases, both in-cis and in-trans ubiquitination events have been observed for these proteins (de Bie and Ciechanover, 2011). For example, U-box E3 Act1 catalyzes the polyubiquitination of TRAF6, and K-63 linked TRAF6 is then activated which in turn mediates the ubiquitination of downstream proteins for NF-κB activation (Liu et al., 2009). TRAF6 can also self-regulate through auto-ubiquitination. Unlike their mammalian counterparts, plant TRAF proteins are enriched in both number (>70 41 in Arabidopsis) and expanded diversity of domain combinations (Cosson et al., 2010). MUSE13 and MUSE14 are the best-studied plant TRAFs in immune regulation. They only contain a TRAF domain at their N-termini, lacking RING and zinc finger domains. MUSE13 and MUSE14 act as adaptors that associate NLR immune sensors (i.e. SNC1 and RPS2) with SCFCPR1, facilitating the degradation of SNC1 and RPS2 (Huang et al., 2016). Loss of both MUSE13 and MUSE14 causes extreme autoimmunity due to over-accumulation of SNC1, compromising plant growth and development. Previously MUSE13/14 were found to be extremely unstable; their protein levels are regulated by the ubiquitin-proteasome system (Huang et al., 2016). SCFSNIPER4 is now found to be the E3 complex that is likely responsible for ubiquitinating MUSE13 and MUSE14 and facilitating their degradation. Such novel mechanism adds additional layer of regulation to fine-tune NLR homeostasis, as regulating MUSE13/14 levels by SCFSNIPER4 is a fast and efficient way with high specificity to down-regulate MUSE13 and MUSE14 to guarantee adequate levels of NLR sensors for defense activation. 2.5.4 SCFSNIPER4 regulates immune output by controlling TRAF protein MUSE13/14 homeostasis Constant pathogen threats demand that plants are equipped with a robust surveillance system to detect pathogens and mount effective immune responses. NLRs are immune sensors that recognize effectors secreted by pathogens and trigger ETI. NLR homeostasis must be tightly regulated to guarantee sufficient NLRs for surveillance while preventing NLR over-accumulation, which can lead to autoimmunity and impairment of plant development. Microarray data show that induction of MUSE13/14 starts at 2 hrs post-pathogen treatment and is maintained to 24 hrs post-pathogen treatment (Figure 2.10A and 2.10B). In contrast, SNIPER4 is not induced until 6 hrs post-pathogen treatment (Figure 2.10C). While pathogen invasion activates immune responses that includes up-regulation of SNC1, induction of MUSE13/14 promotes the degradation of SNC1 to avoid its over-accumulation. However, at a later stage when SNC1 level is below the requirement for surveillance due to degradation, SNIPER4 is then up-regulated to target MUSE13/14 for degradation to recover SNC1 to 42 sufficient levels (Figure 2.10D). Such intricate regulation guarantees the proper defense output without causing autoimmunity. Mammalian TRAFs play central roles in immunity and ubiquitination of TRAFs are critical for their function. SCFSNIPER4 is the first E3 reported to target plant TRAF proteins for ubiquitination and degradation. Like TRAFs in mammals, ubiquitination is likely a key post-translational modification for other TRAFs in plants, which would require external E3s since most plant TRAFs do not carry RING finger domains. Future studies on the roles of ubiquitination of plant TRAFs may reveal how the function and/or turnover of these adaptor proteins are regulated. 43 Figure 2.10 A working Model for SNIPER4-mediated degradation of MUSE13/14 to fine-tune SNC1 protein levels. (A-C) Expression of MUSE13 (A), MUSE14 (B) and SNIPER4 (C) under mock treatment and Pst 3000 treatment conditions. Gene expression levels were extracted from microarray data AtGenEpxress (http://jsp.weigelworld.org/expviz/expviz.jsp). Plant were either infiltrated with 10 mM MgCl2 (mock) or 108 cfu/ml virulent pathogen Pst 3000. (D) A working model on fine-tuning SNC1 protein levels by SNIPER4. As immune sensors in the plant surveillance system, SNC1 proteins reach a homeostasis under normal conditions. Upon pathogen invasion, it increases to enhance immune responses, likely through the positive feedback transcriptional up-regulation. MUSE13/14 expression is then induced to promote the degradation of SNC1 by SCFCPR1, which prevents its over-accumulation. At a later stage, when SNC1 is below the level required for proper surveillance due to degradation, expression of SNIPER4 is induced to direct MUSE13/14 for degradation to recover SNC1 in the surveillance system. Eventually, homeostasis of SNC1, MUSE13/14 and SNIPER4 reaches a balance to ensure a robust and tightly regulated immune output. 44 3 CAMTA transcription factors and CDK8 play opposite roles in the transcriptional regulation of salicylic acid levels and systemic acquired resistance 3.1 Summary In plants, the calmodulin binding transcription activators (CAMTAs) are required for transcriptional regulation of abiotic and biotic stress responses. Among them, CAMTA3 has been intensively studied and shown to function redundantly with CAMTA1 and CAMTA2 to regulate plant immunity. However, the major role of CAMTAs in plant immunity is controversial. Here, through a suppressor screen using camta1/2/3 triple mutant, we found that mutations in ICS1, which is responsible for pathogen-induced defense hormone salicylic acid (SA) biosynthesis, mostly suppress the severe autoimmune responses of camta1/2/3, suggesting that the major role of the CAMTAs is to inhibit SA biosynthesis. The gain-of-function camta3-3D mutants exhibit compromised expression of SA-related genes, including ICS1, EDS5 and PBS3. On the other hand, Cyclin-Dependent Kinase 8 (CDK8), identified from the same screen, positively regulates steady-state SA levels and systemic required resistance (SAR). The expression of SA biosynthesis genes including ICS1 and EDS5 is down-regulated in the cdk8 mutants. These results demonstrate that CAMTAs and CDK8 play opposite roles in regulating SA biosynthesis at the transcription level. 3.2 Introduction Plant disease resistance (R) proteins are immune receptors that detect the effectors secreted into the host cells by pathogens, the recognition of which induces effector triggered immunity (ETI) (Jones and Dangl, 2006b). Besides direct recognition, effectors can be recognized indirectly through monitoring the modification of host proteins by effectors. Such host proteins are called guardees. Intracellular nucleotide binding leucine-rich repeat domain receptors (NLRs) are a major type of R protein (Zhang et al., 2017). Based on the difference in their N terminal domains, typical plant NLRs are divided into Toll/Interleukin-1-receptor-like NLRs (TNLs) and coiled-coil NLRs (CNLs), which depend on EDS1 (enhanced disease susceptibility 1) and NDR1 (non-race-specific disease resistance 1), respectively (Dangl and Jones, 2001a; Li et al., 2015b). 45 Systemic acquired resistance (SAR) is a systemic immune response that is induced in uninfected distal parts of plants upon local pathogen infection. Once established, SAR provides plants with long-lasting protection against a broad spectrum of pathogens, such as fungi, bacteria and viruses (Fu and Dong, 2013). Salicylic acid (SA) is a phytohormone contributing to diverse immune responses, including local defense, ETI and SAR (Vlot et al., 2009). SA accumulation is induced in both infected and distal tissues after pathogen infection. Exogenous application of SA or SA analogs triggers resistance against pathogens (Gorlach, 1996; Ward et al., 1991; White, 1979), whereas depletion of SA in plants by expressing salicylate hydroxylase gene NahG abolishes SAR (Gaffney et al., 1993). In Arabidopsis, pathogen-induced SA biosynthesis is mainly through the pathway controlled by Isochorismate Synthase 1 (ICS1/SID2) (Wildermuth et al., 2001). Induction of ICS1 is positively regulated by transcription factors SARD1(SAR deficient 1), CBP60g (calmodulin binding protein 60-like g), TGA1 and TGA4 (Sun et al., 2015; Zhang et al., 2010b). Besides ICS1 and the transcription factors, other components have been reported to be involved in regulating SA accumulation. EDS5 (enhanced disease susceptibility 5), PBS3 (for avrPphB susceptible3), EDS1 and PAD4 (phytoalexin deficient 4) are positive regulators of SA accumulation. EDS5, a multidrug and toxin extrusion transporter, is hypothesized to export SA from chloroplasts (Nawrath, 2002). PBS3 is a member of the GH3 acyl adenylase family, the mechanism of it affecting SA accumulation remains unclear (Okrent et al., 2009). EDS1 and PAD4 promote SA accumulation by participating in a SA feedback amplification loop (Jirage et al., 1999; Wiermer et al., 2005). Calmodulin-binding transcriptional activators (CAMTAs) are evolutionarily conserved in multicellular eukaryotes (Finkler et al., 2007). There have been controversial reports about the transcriptional activity of CAMTAs in plants (Galon et al., 2010a): CAMTAs were found to serve as transcriptional activators, as supported by yeast one-hybrid assay (Bouché et al., 2002; Mitsuda et al., 2003), transient expression assays in Arabidopsis cell culture (Mitsuda et al., 2003) and in Nicotiana benthamiana (Benn et al., 2014), and by cold-regulated activation in A. thaliana (Doherty et al., 2009). CAMTA3 were also reported to act as transcriptional repressors in planta (Du et al., 2009; Nie et al., 2012). Among the six CAMTAs in Arabidopsis, CAMTA1, CAMTA2 and CAMTA3 function redundantly in plant 46 immunity (Kim et al., 2013). A loss-of-function camta3 mutant exhibit constitutive immunity under cold conditions (Galon et al., 2008). However, gain-of-function camta3-3D mutant is compromised in disease resistance against Pst DC3000 (Jing et al., 2011; Nie et al., 2012), avirulent pathogen Pst DC3000 with AvrRps4 and Pst DC3000 with AvrRpt2 (Nie et al., 2012), as well as in SAR (Jing et al., 2011). This suggests that CAMTA3 is negatively involved in basal resistance, defense responses mediated by TNL RPS4, and CNL RPS2, as well as SAR. In support of this, CAMTA3 was found to act as a transcriptional repressor to directly suppress the expression of EDS1 (Du et al., 2009) and NDR1 (Nie et al., 2012). Lastly adding to the complexity is a recent report on CAMTA3 serving as a guardee monitored by two TNLs DSC1 and DSC2 (Lolle et al., 2017). In an attempt to detangle the role of the CAMTAs in plant immunity, a forward genetic screen was carried out with the camta1/2/3 triple mutant. We report here that the major role of the three CAMTAs in immunity is to inhibit SA synthesis. Severe autoimmunity in camta1/2/3 mutants is mostly suppressed by mutations in ICS1 and partially suppressed by eds5 mutants. Gain-of-function camta3-3D suppresses SA accumulation through down-regulating the expression of ICS1, EDS5 and PBS3. In addition, cdk8-3, identified from the same screen, partially rescues autoimmunity in camta1/2/3 mutants. cdk8 mutants are defective in SA biosynthesis and SAR. ICS1 and EDS5 expression was compromised in cdk8 mutants. Our data suggest that CAMTA3 and CDK8 function oppositely to control SA synthesis and SAR. 3.3 Material and method 3.3.1 Plant growth condition and SA measurement Unless specified, Arabidopsis plants were grown in growth rooms at 22ºC under a 16-h-day/8-h-night cycle. To measure SA levels, SA was extracted from Arabidopsis plants as described previously (Li et al., 1999), separated through a 4.6 ×150 mm Eclipse XDB-C18 column (Agilent) and quantified using high-performance liquid chromatography. 47 3.3.2 Mutagenesis and mutant screen EMS mutagenesis was carried out with a previously described protocol(Li and Zhang, 2016). In brief, the camta1/2/3 seeds were suspended in 20 mM ethyl methanesulfonate (EMS) for 16 hours with shaking to induce point mutants. The mutagenized seeds were sterilized and plated on ½ Murashige and Skoog (MS) medium. Approximately 3,000 10-d-old M1 seedlings were transplanted to soil, grown to flowering and selfed. From the resulting seeds which were pool harvested, approximately 48,000 M2 plants were grown and screened for plants with increased plant size compared with the camta1/2/3 mutants. 3.3.3 Next generation sequencing and mapping camta1/2/3 suca quadruple mutants were backcrossed with camta1/2/3 plant. Leaf tissues from 45 to 100 F2 segregants that show larger size (about a quarter) were pooled together and used for DNA extraction. The resulting genomic DNA was sequenced by Illumina whole-genome re-sequencing as mentioned previously (Huang et al., 2013a). SNPs mapped to genes encoding non-coding RNA or repetitive genes were removed as they often interfere with SNP analysis. The frequency of remaining SNPs was caculated using Excel and used to identify linkage and candicate mutations. 3.3.4 Pathogen infection assays For Hpa Noco2 and Hpa Emwa1 infection, soil-grown Arabidopsis plants were spray-inoculated with Hpa spores suspended in water at the indicated concentrations. Plants were grown in a chamber at 18°C under a 12-h-day/12-h-night cycle with 80% humidity for 7 d prior to quantification of Hpa spores. For SAR assays, 3.5-week-old soil-grown plants were infiltrated with virulent bacterial pathogen Psm ES4326 at a concentration of OD600=0.001. 3 days after infiltration, infected plants were spray-inoculated with Hpa Noco2 spores suspended in water at a concentration of 5 × 104 spores/ml. Hpa Noco2 spores on plants were quantified at 7 dpi. 3.3.5 Quantitative RT-PCR About 40 mg leaf tissue was collected for each sample and subjected for RNA extraction using a Total RNA kit (Ambion). 1 µg RNA was reverse transcribed into cDNA following 48 the manufacturer’s protocol (EasyScriptTM cDNA Synthesis Kit, Abm). RT-PCR was performed as decribed previously (Zhang et al., 2003a). Primers used for the quantificaiton of ICS1, EDS5 and PBS3 transcriptional levels were as described previously (Sun et al., 2015). Transcripts were normalized to Actin1 and then compared with that of WT. 3.3.6 Ion leakage assay 3.5-week-old soil-grown plants were place into 50 mL tubes with 20 mL deionized water, the conductivity of which was measured after overnight shaking. The samples were then autoclaved and incubated at room temperature for 3h with shaking. The condutivity of the samples were measured again. Percentage of ion leakage was caculated by dividing condutivity values before autoclaving with values afterwards. 3.3.7 Construction of plasmids To create 35S::CDK8, CDK8 genomic sequence with 1303 bp upstream of the start codon was amplified using primers F: 5’-CCC GGC CGT CAA GGC CCT GGT TTG TGA ATG ACT GCT-3’ and R: 5’- CCC GG CCC ATG AGG CCG TAA ATA GAT AAG ACT GGC AGG-3’, digested with Sfi I and ligated into pHAN-35S vector. For the generation of CDK8 CRISPR-Cas9 consruct, two sgRNA target sites (5’-TAG TTT CCA TTC TCA GCG T-3’ and 5’-CCT GCC AGT CTT ATC TAT TTA C-3’) upstream and downstream of CDK8 coding region were first selected. A fragment contraining sequence encoding two sgRNA was amplified using primers BsF: 5’-ATA TAT GGT CTC GAT TGT AGT TTC CAT TCT CAG CGT GTT-3’, F0: 5’-TG T AGT TTC CAT TCT CAG CGT GTT TTA GAG CTA GAA ATA GC-3’, R0: 5’-AAC CAT GCT GCA TTA CAA TCT ACA ATC TCT TAG TCG ACT CTA C-3’ and BsR: 5’-ATT ATT GGT CTC GAA ACC ATG CTG CAT TAC AAT CTA C-3’ using pCBC DT1T2 vector as template. The resulting fragment was digested with BbsI and ligated into pHEE401E vector, an egg cell-specific promoter-controlled CRISPR/Cas9 system (Wang et al., 2015).. 3.3.8 Split luciferase complementation assay For amplification of genomic CDK8 sequence, primers F: 5’-CCC GGC CGT CAA GGC CAA TGG GAG ATG GGA GTT CCA G-3’ and R: 5’-GCC GGC CCA TGA GGC CCG 49 AGG CGT CTG GAT TTG TTA G-3’ were used. Using genomic DNA as template, SARD1 was amplified with primers F: 5’-CCC GGC CGT CAA GGC CAA TGG CAG GGA AGA GGT TAT TTC-3’ and R: 5’-GCC GGC CCA TGA GGC CCA GTT CCA AAA ATA TGT CTG TCT AC-3’. Primers F: 5’-CCC GGC CGT CAA GGC CAA TGA AGA TTC GGA ACA GCC C-3’ and R: 5’- GCC GGC CCA TGA GGC CCC AAG CCT TCC CTC GGA TTT C-3’ were used for the amplification of genomic sequence of CBP60g. To amplify PCN genomic sequence, primers F: 5’-CCC GGC CGT CAA GGC CAA TGC TCG AGT ACC GTT GCA G-3’ and R: 5’-GCC GGC CCA TGA GGC CCA GTT CCA AAA ATA TGT CTG TCT AC-3’ were used. PCR products were digested with SfiI, and then ligated into either pCambia1300-35S-HA-Cluc or pCambia1300-35S-HA-Nluc vectors. Split luciferase complementation assay was conducted as described previously (Huang et al., 2018). 3.4 Results 3.4.1 The suca mutations suppress the autoimmune phenotypes of a camta1/2/3 triple mutant To dissect the immune signaling pathways regulated by three redundant transcription factor genes CAMTA1, CAMTA2 and CAMTA3, we conducted a forward genetic screen in the extremely dwarfed camta1/2/3 triple mutant background. camta1/2/3 seeds were mutagenized with ethyl methanesulfonate (EMS) and mutants with larger size were identified in the M2 population. Heritable mutants identified from the screen were named suca (suppressor of camta1/2/3) mutants. Here, we describe in detail the study of three of them, suca1, suca2 and suca3. camta1/2/3 plants develop severe dwarfism due to constitutive activation of immune responses. However, the dwarfed size in camta1/2/3 is almost fully suppressed by suca1, and partially suppressed by suca2 and suca3 (Figure 3.1A). When backcrossed to the camta1/2/3 parent, all three mutants (suca1 camta1/2/3, suca2 camta1/2/3 and suca3 camta1/2/3), F1 plants were camta1/2/3-like, suggesting that these suca mutants are recessive. Allelism test revealed that two additional suppressors, suca4 camta1/2/3 and suca5 camta1/2/3, failed to complement suca1 camta1/2/3 inmorphology in F1 (Figure 3.1B), indicating that suca4 and suca5 are allelic to suca1. Similarly, when we performed allelism test with suca2 camta1/2/3, suca6 camta1/2/3 failed to complement (Figure 3.1C), suggesting that suca6 is another allele 50 of suca2. Since suca4 and suca5 are allelic to suca1 while suca6 is allelic to suca2, we only focused on the characterization of the suca1 and suca2 alleles. camta1/2/3 mutants exhibit extensive spontaneous cell death. To examine the effects of the suca mutants on cell death of camta1/2/3, electrolyte leakage was monitored in the quadruple mutants. As shown in Figure 3.1D, camta1/2/3 exhibited high levels of electrolyte leakage compared with WT. suca1 almost restored electrolyte leakage in camta1/2/3 to WT level. In contrast, suca2 partially reduced the electrolyte leakage in camta1/2/3. Although not statistically significant, suca3 camta1/2/3 consistently showed lower electrolyte leakage compared with camta1/2/3. These results indicate that suca1, suca2 and suca3 suppress the spontaneous cell death in camta1/2/3. 51 Figure 3.1 Suppression of camta1/2/3-mediated autoimmunity mediated by suca1, suca2 and suca3 (A) Morphology of 3.5-week-old soil-grown plants of WT, camta1/2/3, suca1 camta1/2/3, suca2 camta1/2/3 and suca3 camta1/2/3. (B) Morphology of 3.5-week-old soil-grown plants of WT, camta1/2/3, suca1 camta1/2/3, F1 plant (F1-4) between suca4 camta1/2/3 and suca1 camta1/2/3, and F1 plant (F1-5) between suca1 camta1/2/3 and suca5 camta1/2/3. (C) Morphology of 3.5-week-old soil-grown plants of WT, camta1/2/3, suca2 camta1/2/3, suca6 camta1/2/3 and F1 plant between suca2 camta1/2/3 and suca6 camta1/2/3. 52 (D) Ion leakage of plants shown in (A). The values indicate averages of replicates ± Standard Deviation (SD) (n = 5). Statistical significance represented by different letters was caculated using one-way ANOVA followed by Tukey's post hoc test (P < 0.05). (E-F) Free SA (C) and total SA (D) levels of 3.5-week-old soil-grown plants of the indicated genotypes. The values indicate averages of biological replicates ± SD (n = 3). Statistical significance represented by different letters was caculated using one-way ANOVA followed by Tukey's post hoc test. P < 0.05 for (E) and P < 0.01 for (F). (G) Growth of Hpa Noco2 on the indicated genotypes. 105 spores/ml inoculum was spray-inoculated on 10-day-old soil-grown seedlings. Number of spores was measured at 7 dpi. The values indicate averages of biological replicates ± SD (n = 4). Statistical significance represented by different letters was caculated using one-way ANOVA followed by Tukey's post hoc test (P < 0.05). Kim et al. (2013) reported that camta1/2/3 accumulates high levels of SA relative to wild type. As shown in Figure 3.1E and 3.1F, high accumulation of free SA and total SA in camta1/2/3 are reduced to wild type (WT) levels by suca1. In contrast, both free SA and total SA in camta1/2/3 were greatly reduced by both suca2 and suca3, but not back to WT levels (Figure 3.1E and 3.1F). To test whether suca1, suca2 and suca3 alter disease resistance in camta1/2/3, we challenged plants with virulent oomycete pathogen Hyaloperonospora arabidopsidis (Hpa) Noco2. suca1 camta1/2/3 plants are as susceptible as WT. In comparison, suca2 camta1/2/3 and suca3 camta1/2/3 seedlings support more Hpa Noco2 growth compared to camta1/2/3, but less than WT (Figure 3.1G). Taken together, suca1, suca2 and suca3 all suppress camta1/2/3-mediated autoimmune responses. suca1 seems to be an almost complete suppressor while suca2 and suca3 are partial suppressors. 3.4.2 Positional cloning of suca1, suca2 and suca3 To map the three suca mutants, genomic DNA was extracted from about a quarter of bulk segregants (total between 45-100 plants) that showed camta triple supressing phenotype in the F2 population which is derived from a backcross between suca camta1/2/3 and camta1/2/3. After whole-genome sequencing, SNP frequency (PSNP) was calculated in order to identify the causal region and candidate mutations. Unlinked SNPs are expected to have a PSNP value of 0.5 due to random segregation. PSNP would increase towards 1 as the SNP is located closer to the casual mutation. 53 By analyzing the SNP frequency (PSNP) derived from suca1 camta1/2/3 F2 bulked backcross segregants, we identified a single causal region located at chromosome 1 (Figure 3.2A). Since the causal mutation should co-segregates perfectly with morphological suppression of camta1/2/3, only mutations with PSNP=1 are considered as initial candidate mutations. Ten such mutations with PSNP=1 were identified in this region (Figure 3.2A and Table 3.1). Only three of them result in amino acid changes in genes, including SID2, AT1G75020 and AT1G75340 (Table 3.1). Since SID2 encodes the SA biogenesis enzyme ICS1 and suca1 completely reduces the free SA and total SA level in camta1/2/3 to WT level (Figure 3.1E and 3.1F), we hypothesized that suppression of autoimmune responses in suca1 camta1/2/3 is due to the mutation in SID2. To test this, we generated sid2-1 camta1/2/3 quadruple mutants by crossing loss-of-function sid2-1 mutant with camta1/2/3. Similar to the effect of suca1 on camta1/2/3, sid2-1 suppressed the dwarfed size and resistance against Hpa Noco2 in camta1/2/3 (Figure 3.2B and 3.2C). In addition, sequencing of SID2 in the other two allelic suca mutants, suca4 and suca5, identified the nonsense mutations Trp183 and Gln262 to stop codons, respectively (Figure 3.2D). We therefore conclude that SUCA1 is SID2; knocking out the SA biosynthesis gene ICS1 almost fully suppresses the extreme autoimmunity of camta1/2/3. Table 3-1 Mutations with PSNP = 1 in the causal region of SUCA1. GENE Mutation site Consequence of mutation AT1G74450\AT1G74448 upstream\x3bdownstream no aa change AT1G74660 upstream no aa change AT1G74710 exon S448F AT1G74960 exon no aa change AT1G75020 exon L53F AT1G75340 exon G15D AT1G75430 intron no aa change AT1G75550 downstream no aa change 54 AT1G75820, AT1G75830 intergene no aa change AT1G76170 downstream no aa change To identify suca2, we analyzed PSNP derived from bulk co-segregants in the F2 of the suca2 camta1/2/3 backcross. A causative region was observed on chromosome 4, wherein there is only one mutation with PSNP=1 (Figure 3.3A). This mutation results in a Gly246 to Glu amino acid change in the putative SA transporter EDS5 (Figure 3.3B), and hence became the sole candidate mutation for suca2. When we sequenced EDS5 in the allelic suca6 camta1/2/3 mutant, a mutation causing Gly416 to Arg amino acid changes in EDS5 was identified (Figure 3.3B). Taken together, the evidence indicates that SUCA2 is EDS5. Table 3-2 Mutations with PSNP = 1 in the causal region of SUCA3. GENE Mutation site Consequence of mutation AT5G60010 exon no aa change AT5G60930 intron no aa change AT5G61440 intron no aa change AT5G61950 exon Q167 stop codon AT5G62550 exon E2K AT5G62865 exon P8S AT5G63090 intron change in splicing AT5G63610 exon W200 stop codon AT5G64855\AT5G64860 upstream\downstream no aa change AT5G65140, AT5G65158 intergene no aa change Through the analysis of PSNP derived from suca3 camta1/2/3 F2 bulked backcross segregants (Figure 3.4A), ten mutations with PSNP = 1 were identified as candidates for suca3 55 (Table 3.2). Further analysis of these mutations revealed that only five of them led to predicted premature stop codons, amino acid changes or defective splicing. Genes affected by these five mutations are: AT5G61950, AT5G62550, AT5G62865, AT5G63090 and AT5G63610 (CDK8) (Table 3.2). Among them, CDK8 was reported to be involved in positive regulation of plant immunity. In addition, cdk8 mutants exhibit sterility and altered leaf morphology, which are observed in suca3 camta1/2/3 plants. Thus, CDK8 became the most likely candidate for SUCA3. To test this, a transgene complementation experiment was carried out by expressing a genomic region of CDK8 with 1306 bp upstream sequence from the start codon in suca3 camta1/2/3. The suca3 camta1/2/3 lines harbouring the CDK8 transgene were reverted to smaller plant size (Figure 3.4B), lower susceptibility against Hpa Noco2 (Figure 3.4C), as well as higher free and total SA levels (Figure 3.4D and 3.4E) than the quadruple mutant parent, similar to camta1/2/3. Together, these data suggest that SUCA3 is CDK8. 56 Figure 3.2 SUCA1 encodes ICS1. (A) Dot plot of SNP frequency of mutations from chromosom (chr) 1 to chr 5 derived from suca1 camta1/2/3 bulked backcross segregants. Blue dots represent mutations with PSNP = 1. Mutations with PSNP < 1 are indicated by red dots. (B) Morphology of 3.5-week-old soil-grown plants of WT, camta1/2/3, sid2-1 and sid2-1 camta1/2/3. (C) Growth of Hpa Noco2 on the indicated genotypes. 104 spores/ml inoculum was spray-inoculated on 10-day-old soil-grown seedlings. Number of spores was measured at 7 dpi. The values indicate averages of biological replicates ± SD (n = 4). Statistical significance represented by different letters was caculated using one-way ANOVA followed by Tukey's post hoc test (P < 0.05). (D) Structure of ICS1 protein. Corresponding mutations are indicated by arrows. 57 Figure 3.3 Identification of SUCA2 using mapping-by-sequencing. (A) Dot plot of SNP frequency of mutations from chr 1 to chr 5 derived from suca2 camta1/2/3 bulked backcross segregants. Blue dots represent mutations with PSNP = 1. Mutations with PSNP < 1 are indicated by red dots. (B) Structure of EDS5 protein. Corresponding mutations are indicated by arrows. To further confirm the identity of SUCA3, we generated CDK8 knockout alleles in camta1/2/3 through deletion by a CRISPR/Cas9 gene editing method. A construct carrying two gRNA sites upstream or downstream of CDK8 (Figure 3.5A) was transformed in camta1/2/3. Two out of roughly 600 T2 lines resembled suca3 camta1/2/3 quadruple mutant in morphology (Figure 3.5C). Genotyping of CDK8 in these two lines showed that they indeed both carry homozygous deletions of CDK8 (Figure 3.5B). Further analyses revealed that these two CRISPR lines exhibited reduced levels of free and total SA (Figure 3.5D and 3.5E), and compromised resistance against Hpa Noco.2 (Figure 3.5F) compared to camta1/2/3. Taken together, SUCA3 is CDK8. We therefore renamed suca3 as cdk8-3. The cdk8-3 allele was found to carry a mutation changing Trp200 to a stop codon (W200X) (Table 3.2), leading to truncation of the CDK8 protein. 58 Figure 3.4 Cloning of SUCA3. (A) Dot plot of SNP frequency from chr 1 to chr 5 derived from suca3 camta1/2/3 bulked backcross segregants. Blue dots represent mutations with PSNP = 1. Mutations with PSNP < 1 are indicated by red dots. (B) Morphology of 3.5-week-old soil-grown plants of WT, camta1/2/3, suca3 camta1/2/3 and two transgenic lines expressing CDK8 in suca3 camta1/2/3 background. 59 (C) Growth of Hpa Noco2 on the indicated genotypes. 105 spores/ml inoculum was spray-inoculated on 10-day-old soil-grown seedlings. Number of spores was measured at 7 dpi. The values indicate averages of biological replicates ± SD (n = 4). Statistical significance represented by different letters was caculated using one-way ANOVA followed by Tukey's post hoc test (P < 0.01). (D and E) Free SA (D) and total SA (E) levels of 3.5-week-old soil-grown plants of the indicated genotypes. The values indicate averages of biological replicates ± SD (n = 3). Statistical significance represented by different letters was caculated using one-way ANOVA followed by Tukey's post hoc test (P < 0.05). Figure 3.5 Knockout of CDK8 suppresses the autoimmune resposnes in camta1/2/3. (A) Schematic drawing of indicating the gRNA target sites of CDK8 CRISPR/Cas9 construct indicated by triangles. Primers used for genotyping the presence of CDK8 in (B) are represented by arrows. CDK8 is colored in green. (B) DNA Gel of the genotyping of CDK8 in two independent CDK8 CRISPR/Cas9 T2 lines and WT plant. Presence of CDK8 leads to a ~ 3.1 kb band, while a ~ 0.8 kb band is expected to be amplified if CDK8 is knocked out through targeted deletion as described in (A). 60 (C) Morphology of 4-week-old soil-grown WT, camta1/2/3, suca3 camta1/2/3 and two independent CDK8 knockout lines created by CRISPR/Cas9 in camta1/2/3 background. (D-E) Free SA (D) and total SA (E) levels of 4-week-old soil-grown plants of the indicated genotypes. The values indicate averages of biological replicates ± SD (n = 3). Statistical significance represented by different letters was caculated using one-way ANOVA followed by Tukey's post hoc test. P < 0.01 for (D) and P < 0.05 for (E). . (F) Growth of Hpa Noco2 on the indicated genotypes. 105 spores/ml inoculum was spray-inoculated on 10-day-old soil-grown seedlings. Number of spores was measured at 7 dpi. The values indicate averages of biological replicates ± SD (n = 4). Statistical significance represented by different letters was caculated using one-way ANOVA followed by Tukey's post hoc test (P <0.01). 3.4.3 The autoimmunity of camta1/2/3 is attributed largely to higher SA accumulation The almost complete suppression of the autoimmune responses in camta1/2/3 by mutations in ICS1 indicates that high SA accumulation is the major factor contributing to the autoimmune phenotypes of the camta1/2/3 triple mutant. As TNL-mediated defense was suggested to be the major contributor of the autoimmunity of camta3, we further tested how much of the constitutive defense in camta1/2/3 triple mutant comes from activation of TNLs. When a knockout mutation of the TNL pathway regulator EDS1 was introduced in camta1/2/3 through a cross between eds1-2 and camta1/2/3, the dwarfed size (Figure 3.6A), intensive cell death (Figure 3.6B) and higher total SA levels (Figure 3.6C) in camta1/2/3 were only partially rescued. These data confirm that the autoimmunity of the camta1/2/3 triple mutant is mainly due to its higher SA levels. The partial suppression of camta1/2/3 by eds1 is probably due to EDS1’s known role in feedback regulation on SA accumulation. 61 Figure 3.6 Autoimmunity in camta1/2/3 is suppressed by eds1-2. (A) Morphology of 3.5-week-old soil-grown plants of WT, eds1-2, camta1/2/3 and eds1-2 camta1/2/3. (B) Ion leakage of plants shown in (A). The values indicate averages of replicates ± Standard Deviation (SD) (n = 5). Statistical significance represented by different letters was caculated using one-way ANOVA followed by Tukey's post hoc test (P < 0.05). (C) Total SA levels of 3.5-week-old soil-grown plants of the indicated genotypes. The values indicate averages of biological replicates ± SD (n = 3). Statistical significance represented by different letters was caculated using one-way ANOVA followed by Tukey's post hoc test (P < 0.01). To further validate this idea, we generated sard1-1 cbp60g-1 camta1/2/3 quintuple mutants by crossing sard1-1 cbp60g-1 double mutant with camta1/2/3. SARD1 and CBP60g are two redundant transcription factors that control SA biosynthesis. In agreement with our prediction, the dwarfed size (Figure 3.7A), cell death (Figure 3.7B), resistance against Hpa Noco2 (Figure 3.7C), free SA and total SA levels (Figure 3.7D and 3.7E) were all partially reduced in camta1/2/3 by sard1-1 cbp60g-1. Further detailed analysis showed that sard1 cpb60g camta1/2/3 still accumulated ~10 fold higher free SA and ~17 fold higher total SA 62 than WT (Figure 3.7D and 3.7E), which are higher than those in camta1/2/3 suca1 and camta1/2/3 suca2 mutants, suggesting that additional transcription factors, besides SARD1 and CBP60g, may be involved in transcriptional regulation of SA biosynthesis-related genes. 63 64 Figure 3.7 SARD1 and CBP60G are requried for the camta1/2/3-mediated autoimmunity. (A) Morphology of 3.5-week-old soil-grown plants of WT, sard1-1 cbp60g-1, camta1/2/3 and sard1-1 cbp60g-1 camta1/2/3. (B) Ion leakage of plants shown in (A). The values indicate averages of replicates ± Standard Deviation (SD) (n = 5). Statistical significance represented by different letters was caculated using one-way ANOVA followed by Tukey's post hoc test (P < 0.05). (C) Growth of Hpa Noco2 on the indicated genotypes. 104 spores/ml inoculum was spray-inoculated on 10-day-old soil-grown seedlings. Number of spores was measured at 7 dpi. The values indicate averages of biological replicates ± SD (n = 4). Statistical significance represented by different letters was caculated using one-way ANOVA followed by Tukey's post hoc test (P < 0.05). (D-E) Free SA (D) and total SA (E) levels of 3.5-week-old soil-grown plants of the indicated genotypes. The values indicate averages of biological replicates ± SD (n = 3). Statistical significance represented by different letters was caculated using one-way ANOVA followed by Tukey's post hoc test (P < 0.01). 3.4.4 CAMTAs negatively regulate SA accumulation Similar to what was described in Kim et al. (2013), we observed increased free and total SA levels in the camta1/2/3 triple mutant (Figure 3.1E and 3.1F). Previously reported microarray data on the triple mutant also revealed elevated expression of SA biosynthesis genes ICS1 and EDS5, genes encoding positive regulators of SA accumulation (SARD1, CBP60g, EDS1, PAD4, SAG101 and PBS3), and SA receptor genes NPR1, NPR3 and NPR4 (Figure 3.8) in camta1/2/3 plants, suggesting that CAMTA1, CAMTA2 and CAMTA3 negatively regulate genes required for SA synthesis and signaling. 65 Figure 3.8 SA-related genes are up-regulated in camta1/2/3 triple mtant plants. Expression of SID2, EDS5, SARD1, CBP60G, EDS1, PAD4, SAG101, PBS3, NPR1, NPR3 and NPR4 in WT and camta1/2/3. Transcript levels extracted from microarray data (Kim et al., 2013) were normalized to that in WT. To test this hypothesis, we further examined the SAR-defective mutant camta3-3D, which carries a gain-of-function mutation in CAMTA3 (Jing et al., 2011). To examine whether SA levels are altered in camta3-3D, we first measured free and total SA levels in camta3-3D plants. These plants accumulated lower free SA and total SA level than in WT (Figure 3.9A and 3.9B), suggesting that CAMTA3 indeed suppresses SA accumulation and it is a true negative regulator of SA accumulation. Since CAMTAs are transcription factors, we tested whether the expression of SA-related genes is affected in camta3-3D. RT-PCR analysis revealed that expression of ICS1, EDS5 and PBS3 was indeed significantly reduced in camta3-3D plants than in WT (Figure 3.9C to 3.9E). Taken together, CAMTAs inhibit SA biosynthesis, probably through regulating the expression of SA related genes. Since ICS1 and PBS3 contain two and one CAMTA-binding motifs (A/C/G)CGCG(C/G/T) in their respective promoters (Figure 3.10), we tested whether CAMTA3 directly regulates the expression of ICS1 and PBS3. In an electrophoretic mobility shift assay (EMSA), CAMTA3 exhibited weak association to the CAMTA-binding motifs from the ICS1 promoter but not to that from the PBS3 promoter (preliminary data not shown), suggesting that CAMTA3 may not directly affect the expression of ICS1 and PBS3. 66 Figure 3.9 camta3-3D mutant is compromised in SA accumulation (A-B) Free SA (A) and total SA (B) levels of 6-week-old soil-grown plants of the indicated genotypes. The values indicate averages of biological replicates ± SD (n = 4). Statistical significance represented by different letters was caculated using one-way ANOVA followed by Tukey's post hoc test (P < 0.01). (C-E) Expression of ICS1 (C), EDS5 (D) and PBS3 (E) in 6-week-old soil-grown plants WT and camta3-3D plants. The values indicate averages of replicates ± SD (n = 3). ACT1 serves as internal control. Transcript levels were normalized to that in WT. Statistical significance represented by different letters was caculated using one-way ANOVA followed by Tukey's post hoc test. P < 0.05 for (C), P < 0.01 for (D) and P < 0.05 for (E). 67 Figure 3.10 CAMTA3-binding motifs in promoter regions of ICS1 and PBS3. The triangles indicate the CAMTA3-binding motifs. The numbers above triangles represents the position of corresponding CAMTA3-binding motif. 3.4.5 Characterization of the cdk8 single mutants CDK8 encodes a highly conserved eukaryotic cyclin-dependent kinase that is part of the kinase module of the Mediator complex responsible for activating RNA polymerase (Pol) II-mediated transcription. To examine the role of CDK8 in plant immunity, two previously described T-DNA knockout alleles of CDK8, SALK_138675 (cdk8-1) and SALK_016169 (cdk8-2), were obtained from the Arabidopsis Biological Resource Centre (ABRC). cdk8 mutants displayed reduced plant size compared with WT plants (Figure 3.11A). As sid2 and eds5 alleles deficient in SA biosynthesis were also identified in the camta1/2/3 suppressor screen, we speculated that CDK8 may be involved in regulating SA accumulation. To test this, we examined the SA levels in the cdk8 mutants. Indeed, cdk8-1 and cdk8-2 plants accumulated less free SA and total SA compared with WT (Figure 3.11B and 3.11C). As SA is required for SAR and basal defense, we examined the SAR response and basal defense in the cdk8 mutants. As shown in Figure 3.11D, pre-treatment of WT plants with virulent bacterial pathogen P. syringae pv. maculicola (Psm) ES4326 induced SAR, resulting in enhanced disease resistance in distal leaves against Hpa Noco2. However, systemic resistance in distal leaves against Hpa Noco2 was compromised in cdk8-1 and cdk8-2 plants, suggesting that cdk8 mutants are defective in SAR. Similarly, when cdk8 plants were challenged with Hpa Noco2, enhanced disease susceptibility was observed (Figure 3.11E). We further examined whether CDK8 is required for TNL-mediated immunity by inoculating plants with avirulent pathogen Hpa Emwa1. cdk8-1 and cdk8-2 seedlings exhibit WT level disease resistance against Hpa Emwa1(Figure 3.11F), indicating that CDK8 is not required for immune responses mediated by TNL RECOGNITION OF PERONOSPORA PARASITICA 4 (RPP4). Taken together, defects in CDK8 cause enhanced susceptibility 68 against virulent pathogens and compromised SAR, which is likely due to the reduced steady-state SA levels in the cdk8 mutants. Figure 3.11 Characterization of the cdk8 single mutants. (A) Morphology of 3.5-week-old soil-grown plants of WT, cdk8-1 and cdk8-2 mutants. (B-C) Free SA (B) and total SA (C) levels of 6-week-old soil-grown plants of the indicated genotypes. The values indicate averages of replicates ± SD (n = 6). Statistical significance represented by different letters was caculated using one-way ANOVA followed by Tukey's post hoc test. P < 0.05 for (B) and P < 0.01 for (C). (D) SAR assay on the indicated genotypes. 3.5-week-old soil-grown plants were infiltrated with Psm ES4326 at a concentration of OD600=0.001 3 days prior to Hpa Noco2 inoculation at a 104 spores/ml inoculum. Levels of disease sypmtoms were graded at 7dpi according to Zhang et al., 2010. (E) Growth of Hpa Noco2 on WT, cdk8-1 and cdk8-2. 104 spores/ml inoculum was spray-inoculated on 4-week-old soil-grown plants. Levels of disease sypmtoms were graded at 7dpi according to Zhang et al., 2010. (F) Growth of Hpa Emwa1 on the indicated genotypes. 105 spores/ml inoculum was spray-inoculated on 10-day-old soil-grown seedlings. Number of spores was measured at 7 dpi. The values indicate averages of biological replicates ± SD (n = 4). Statistical significance represented by different letters was caculated using one-way ANOVA followed by Tukey's post hoc test (P < 0.01). 69 3.4.6 Transcriptional regulation of ICS1 and EDS5 by CDK8 The Mediator complex serves as a co-activator of Pol II to promote transcription. To determine whether compromised SA accumulation in cdk8 mutants is due to reduced transcripts of SA related genes, we examined the expression of ICS1, EDS5 and PBS3 in cdk8 mutants. Expression of ICS1 and EDS5 were indeed significantly lower in cdk8 mutants than in WT (Figure 3.12A and 3.12B). However, cdk8 mutants exhibit similar PBS3 transcript levels as WT (Figure 3.12C). This suggests that CDK8 is required for the expression of ICS1 and EDS5. Figure 3.12 Expression of ICS1 and EDS5 is down-regulated in cdk8 mutants. (A-C) Expression of ICS1 (A), EDS5 (B) and PBS3 (C) of 6-week-old soil-grown WT and two CDK8 knockout mutants. The values indicate averages of replicates ± SD (n = 3). ACT1 serves as internal control. Transcript levels were normalized to that in WT. Statistical significance represented by different letters was caculated using one-way ANOVA followed by Tukey's post hoc test. P < 0.01 for (A) and P < 0.05 for (B). 70 Figure 3.13 med12 mutants are compromised in SA synthesis. (A) Morphology of 3.5-week-old soil-grown plants of WT, cdk8-1, med12 and med13. (B) SAR assay on the indicated genotypes. 3.5-week-old soil-grown plants were infiltrated with Psm ES4326 at a concentration of OD600=0.001 3 days prior to Hpa Noco2 inoculation at a 104 spores/ml inoculum. Levels of disease symptoms were graded at 7 dpi according to Zhang et al., 2010. 71 (C) Growth of Hpa Noco2 on WT, cdk8-1 and med12. 104 spores/ml inoculum was spray-inoculated on 4-week-old soil-grown plants. Levels of disease symptoms were graded at 7dpi according to Zhang et al., 2010. (D-E) Free SA (D) and total SA (E) levels of 6-week-old soil-grown plants of the indicated genotypes. The values indicate averages of biological replicates ± SD (n = 6). Statistical significance represented by different letters was caculated using one-way ANOVA followed by Tukey's post hoc test (P < 0.01). 3.4.7 Contribution of the other Mediator subunits of the CDK8 kinase module to SA accumulation and SAR CDK8, MED12, MED13 and CycC constitute the CDK8 kinase module (CKM) of the Mediator complex. To test the roles of the other CKM subunits in plant immunity, we examined available exonic T-DNA mutants of genes encoding the CKM proteins. There are two tandem CycC genes including CycCa and CycCb in Arabidopsis. As they are likely redundant, we did not include the CycCs for further analysis. Similar to cdk8, med12 and med13 plants exhibit smaller size and altered plant morphology compared with WT (Figure 3.13A). As the med13 homozygous mutant is extremely sterile under our growth conditions, and segregation ratio of homozygous lines to heterozygous lines in progeny population derived from med13 heterozygous plants was far less than 1: 3, we failed to collect enough med13 homozygous plants for infection or SA analysis experiments. We therefore excluded med13 for further analysis. Similar to cdk8-1 mutants, med12 plants were compromised in SAR (Figure 3.13B). In addition, med12 plants supported more growth of Hpa Noco2 than WT (Figure 3.13C). Therefore, like CDK8, MED12 is also required for SAR and basal defense. When the SA levels were measured, we observed that free SA and total SA levels in med12 were comparable to that in cdk8, but significantly lower than those in WT (Figure 3.13D and 3.13E). Taken together, the CKM of the Mediator complex seems to be a positive regulator of SA accumulation, defects of CKM subunits lead to compromised SA accumulation, basal defense and SAR. 3.5 Discussion The roles of CAMTA transcription factors in plant immunity regulation are ambiguous. Here, through forward genetics, we demonstrate that negative regulation of SA biosynthesis is the 72 major role of CAMTA1/2/3. First, autoimmune responses in camta1/2/3 triple mutant can be mostly suppressed by mutations in SA biosynthesis gene ICS1. Second, free SA and total SA levels are lower in the gain-of-function camta3-3D mutant due to decreased expression of ICS1, EDS5 and PBS3. Thus, the multifaceted effects on immunity observed in camta3-3D are likely ascribed to the negative regulation of SA biosynthesis by CAMTAs as SA is indispensable for basal defense, SAR and ETI. On the contrary, the severe autoimmune responses in camta1/2/3 is likely caused by the enhanced expression of positive regulators of SA biosynthesis genes directly or indirectly targeted by CAMTAs. In addition to the negative regulation of SA biosynthesis by the CAMTAs, mediator subunit CDK8 is found to positively regulate SA biosynthesis and SAR by promoting the expression of SA biosynthesis genes such as ICS1 and EDS5. Taken together, our study indicates that CAMTAs and CDK8 function oppositely to regulate SA biosynthesis at transcriptional level. 3.5.1 The major role of CAMTA3 in plant immunity Despite the fact that it has been almost twenty years since the first characterization of CAMTAs in Arabidopsis (Reddy et al., 2000), the major roles of CAMTA3 in plants immunity remain controversial. CAMTA3 was suggested to negatively regulate SA biosynthesis based on the observation that autoimmune camta3 mutant accumulates higher SA levels (Du et al., 2009; Kidokoro et al., 2017; Kim et al., 2013, 2017). However, elevated SA is a common feature of autoimmunity, which is mostly caused by loss-of-function mutations in negative immune regulators, or gain-of-function mutations in positive immune regulators or immune receptors (Yuan et al., 2018). As a result, the major roles of CAMTA3 in immunity are still uncertain. Previous studies proposed two distinct roles of CAMTA3 in plant immunity. The first hypothesis suggests that CAMTA3 plays a negative role in plant immunity (Du et al., 2009; Nie et al., 2012). The autoimmune phenotypes of the loss-of-function camta3 mutant are due to de-repression of positive regulators, such as EDS1 and NDR1, which positively regulate SA biosynthesis, (Shapiro and Zhang, 2001). Such an hypothesis was proposed based on the observations that: 1) CAMTA3 associates with the promoter regions of EDS1 and NDR1; 2) EDS1 and NDR1 were up-regulated in camta3 mutants (Du et al., 2009; Nie et al., 2012). On the other hand, since dominant-negative form of two TNLs, Dominant Suppressor of 73 CAMTA3 (DSC) 1 and 2, can completely suppress the autoimmunity of camta3, and co-expression with CAMTA3 can inhibit cell death triggered by transient expression of DSC1/DCS2, Lolle et al., 2017 hypothesized CAMTA3 serves as a guardee rather than a negative regulator in plant immunity. Under this scenario, autoimmunity of camta3 was proposed to be due to the activation of the two TNLs that guard CAMTA3 rather than de-repression of immune responses. In our study, mutations in ICS1 almost fully suppresses autoimmunity in camta1/2/3 (Figure 3.1A to 3.1G), suggesting that CAMTAs mainly negatively regulate SA biosynthesis. This hypothesis is further supported by the multifaceted defects of immunity in camta3-3D since SA regulates basal resistance, SAR and ETI. The negative regulation in SA synthesis by CAMTAs is likely through inhibiting the expression of genes encoding positive regulators of SA biosynthesis. Autoimmunity of camta3 may be due the de-repression of such genes. Since the promoter regions of SARD1 and CBPG60g, the master regulators of SA biosynthesis, contain three and two CAMTA-binding motifs (A/C/G)CGCG(C/G/T), respectively (Kim et al., 2013), it would be interesting to test whether CAMTA3 directly binds to these promoters to affect the transcription of SA-related genes. Future studies using ChIP-seq to identify a full spectrum of genes directly regulated by CAMTAs is desired to illustrate how CAMTAs regulate SA biosynthesis. 3.5.2 The kinase module of the Mediator serves as a positive regulator of SA biosynthesis In eukaryotes, all protein-encoding genes are transcribed through Pol II. Mediator is a conserved multi-protein complex that bridges transcription factors and Pol II (Conaway and Conaway, 2011). Mediator contains more than 20 subunits, which can be divided into four modules: head, middle, tail and a separable kinase module. The kinase module is composed of CDK8 (cyclin-dependent kinase 8), MED12 (Mediator complex subunit 12), MED13 and CycC (C-type cyclin). Different Mediator subunits integrate distinct external stimuli and induce pathway-specific gene expression (Ansari and Morse, 2013; Balamotis et al., 2009; Kidd et al., 2011). Several Arabidopsis Mediator subunits have been reported to regulate specific signaling pathway during development and in response to external stimuli. For example, MED12/ CCT (CENTER CITY) and MED13/MAB2 (MACCHI-BOU 2) regulate 74 embryo patterning in Arabidopsis (Gillmor et al., 2010; Ito et al., 2011). MED14/SWP (STRUWWELPETER) contributes to cell proliferation (Autran et al., 2002). MED16/SFR6 (SENSITIVE TO FREEZING 6) serves as an key regulator in cold acclimation and coordinates cellular and environmental inputs to control the circadian clock (Knight et al., 1999, 2008, 2009). MED17, MED18 and MED20a are required for small and long noncoding RNA biogenesis (Kim et al., 2011). MED25 is involved in inhibiting abscisic acid (ABA), and activating jasmonic acid (JA) signaling (Cevik et al., 2012; Chen et al., 2012). Recent reports support the idea that Mediator serves as a hub in plant immunity. Effector HaRxL44 of oomycete pathogen Hyaloperonospora arabidopsidis (Hpa) interacts with and promotes the degradation of MED19a (Caillaud et al., 2013), which positively regulates plant immunity (Caillaud et al., 2013; Seo et al., 2017). In addition, six more Hpa effectors were shown to associate with Mediator subunits or regulator of Mediator in yeast 2-hybrid assays (Caillaud et al., 2013; Mukhtar et al., 2011). MED8, MED16, MED 21 and MED25/ PFT1 (phytochrome and flowering time 1) contribute to immunity against necrotrophic pathogen Botrytis cinereal (Dhawan et al., 2009; Kidd et al., 2009; Zhang et al., 2012), while MED14, MED15 and MED16 are required for SAR. A previous study suggested that CDK8/HEN3 (hua enhancer3) plays a role in the formation of floral organ identity (Wang, 2004). A genetic screen aiming at isolating regulators of alternative oxidase showed that CDK8 controls mitochondrial retrograde signaling under stress (Ng et al., 2013). Mutations in CDK8 result in impaired resistance against necrotrophic fungi B. cinereal. CDK8 was also shown to interact with MED25 and function in the JA signaling pathway (Zhu et al., 2014). Although three Mediator subunits have been shown to regulate SAR, the underlying mechanisms are different. MED14 directly affects the transcription of defense genes including ICS1 and EDS5 (Zhang et al., 2013). MED15/ NRB4 (non-recognition of BTH4) functions downstream of NPR1 (non-expresser of pathogenesis-related gene 1), one of the SA receptors (Canet et al., 2012). MED16 is required for the homeostasis of NPR1 (Zhang et al., 2012). Our current study shows that the kinase module of Mediator also contributes to SAR, which is likely to due to its positive role in SA accumulation through controlling the expression of SA related genes such as ICS1 and EDS5, as SA accumulation and expression of ICS1 and EDS5 are compromised in cdk8 mutants. 75 As the kinase module of Mediator is dissociable during transcription, CDK8 was initially suggested to be a negative regulator of transcription. However, further studies support that CDK8 can also promote transcription (Conaway and Conaway, 2011; Nemet et al., 2014). The positive roles of CDK8 in transcription is either through its phosphorylation of transcription factors, which leads to protein degradation in some cases, or through stimulation of Pol II elongation (Allen and Taatjes, 2015). The decreases in ICS1 and EDS5 transcript levels in cdk8 mutants may be caused by compromised phosphorylation of yet-to-be identified transcription factors that regulate expression of ICS1 and EDS5, or defects in Pol II elongation during transcription of ICS1 and EDS5. Since transcription factors SARD1 and CBP60g directly regulate the expression of ICS1 and EDS5 (Zhang et al., 2010b), CDK8 may phosphorylate SARD1 and CBP60g to fine-tune their activity in order to control the expression of ICS1 and EDS5. However, no interaction between CDK8 and SARD1 or CBP60g was detected using split-luciferase complementation assay (Figure 3.14), suggesting no direct connection between CDK8 and these master transcription factors, or the protein interaction during phosphorylation is too weak and transient to be detected in our experiments. Further analysis on how CDK8 affects expression of SA related genes such as ICS1 and EDS5 would provide more insight on how the Mediator kinase module regulation SA accumulation and SAR. Figure 3.14 CDK8 does not interact with SARD1 or CBP60g proteins. Split luciferase complementation assay between CDK8 and SARD1 or CBP60g. Indicated constructs were transiently expressed in N. benthamiana. MKK6 and MPK4 were used as positive control. Nulear localized protein POPCORN (PCN) served as negative control. 76 4 Summary and future perspectives Modern agriculture is facing a great challenge in feeding the rapidly growing human population. The lack of genetic diversity due to the prevalence of monocultures exposes agriculture to the vulnerability of outbreaks of plant diseases. Extensive use of chemicals to control plant diseases is not sustainable, and poses a threat to our ecosystem and human health (Lu et al., 2015). Demand in controlling pathogens using resistant cultivars has been increasing as it is the easiest and cleanest solution in the field. In depth study of plant immunity will enable us to develop more efficient and sustainable approaches to prevent crop yield loss caused by pathogens. Autoimmune mutants usually display reduced plant size, which typically reversely correlates with their defense output. As a result, complicated immune responses can be translated into simple morphological phenotypes in autoimmune mutants, rendering them ideal tools for straight forward genetic screens intended for investigating immune signaling and the regulation of immunity (Dong et al., 2018; Huang et al., 2014a). My Ph.D. projects derive from two genetic screens conducted in autoimmune mutants, snc1 and camta1/2/3 separately. Characterization of SNIPER4 from the SNIPER screen reveals the mechanism of regulation of an E3 ligase to fine-tune the protein levels of NLRs. Through the SUCA screen, I demonstrate that CAMTA3 and CDK8 function oppositely to control SA synthesis and SAR. 4.1 Regulation of E3 ligase activity to fine-tune NLR protein levels. The Arabidopsis genome encodes a substantial number of E3s (>1,500) (Hua and Vierstra, 2011), most of which have not been characterized (Cheng and Li, 2012). SNIPER4 was isolated from the SNIPER screen aimed at identifying E3s involved in immune responses. SNIPER4 encodes an F-box protein that interacts with ASK1, a common subunit in SCF E3 ligase complexes (Cardozo and Pagano, 2004), suggesting that SNIPER4 is part of an SCF E3. Pathogen assays showed that sniper4 mutants displayed WT level resistance against virulent pathogen Hpa Noco2 and Psm ES4324, indicating that SNIPER4 is not involved in basal resistance. In addition, resistance against avirulent Pst DC3000 with AvrRps4, AvrRpt2 or AvrRpm1, which is conferred by RPS4, RPS2 and RPM1 respectively, is similar 77 between sniper4 mutants and wild type plants. This suggests that SNIPER4 is less likely to act as a general regulator in immunity. Dwarfism and expression of PR genes in snc1 is dramatically enhanced by overexpression of SNIPER4, but is partially alleviated by loss-of-function of SNIPER4, suggesting that SNIPER4 plays a positive role in plant immunity. Knockout of SNIPER4 reduces the protein levels of SNC1, while transcription of SNC1 remains unchanged, indicating that SNIPER4 affects the turnover of SNC1 proteins. Taken together, the substrate protein of SNIPER4 is most likely a negative regulator in immunity that controls the homeostasis of SNC1 proteins. Intensive studies on the snc1 mutant have identified over a dozen negative regulators of snc1-mediated immunity (Huang et al., 2013b), some of which are involved in the regulation of SNC1 turnover (Copeland et al., 2016; Dong et al., 2018; Huang et al., 2014a, 2016, 2013b, 2013a, 2014b). Among them, MUSE13 and MUSE14 stand out as potential substrates of SNIPER4 as knockout of MUSE13/14 resembles the effects of overexpression of SNIPER4 on snc1-mediated immunity while overexpression of MUSE13 causes similar phenotypes as loss-of function of sniper4 in snc1 plants (Huang et al., 2016). TRAF proteins MUSE13 and MUSE14 function redundantly and serve as adaptors in the SCFCPR1 E3 complex that targets two NLRs, SNC1 and RPS2, for degradation. Their homeostasis was previously known to be regulated through the proteasome system (Huang et al., 2016). To test whether MUSE13 and MUSE14 are the substrate proteins of SNIPER4, SNIPER4 and DN-SNIPER4 were overexpressed in MUSE13-FLAG lines and MUSE14-FLAG lines. MUSE13-FLAG and MUSE14-FLAG protein levels are decreased by SNIPER4 overexpression but are increased when DN-SNIPER4 is overexpressed. In addition, MUSE13 and MUSE14 interact with DN-SNIPER4 in vivo. These results suggest that SNIPER4 regulates the turnover of MUSE13 and MUSE14. An E3 ligase can be subjected for degradation either by itself and/or an external E3. Three modes of hierarchical organizations of E3 degradation are proposed. An E3 is targeted for degradation either by itself or by another E3 in a circular manner. Alternatively, single or multiple E3s are regulated by an external E3 in a linear manner, which is directed for degradation by itself or by another proteolytic approach (de Bie and Ciechanover, 2011). 78 Regulation of an E3 ligase by another E3 ligase is hypothesized to be able to confer rapid response to environmental stimuli (de Bie and Ciechanover, 2011). By regulating the stability of adaptor proteins MUSE13/MUSE14, SNIPER4 fine-tunes the activity of the SCFCRP1 E3 complex so as to optimize the output of NLRs SNC1 and RPS2 according to the external environment. Such sophisticated regulation enables plants to rapidly establish immunity responses in the presence of pathogens but suppresses immunity post-infection. According to the modes of hierarchical organizations of E3 degradation, an interesting question to address is how the degradation of SNIPER4 is regulated. Is it by self-ubiquitination, or in a circular manner by SCFCPR1, or in a linear manner by an external E3? F-box proteins are integrated into SCF E3 complexes by binding the SCF protein Skp1 with their F-box domain (Cardozo and Pagano, 2004). Removal of the F-box domain detaches the F-box protein from the SCF E3 complexes, abolishing the self-ubiquitination of an F-box protein. When transiently expressed in N. benthamiana, DN-SNIPER4, which lacks the sequence encoding an F-box domain leads to a higher protein level compared with that caused by transient expression of intact SNIPER4 (data not shown), indicating that SNIPER4 undergoes self-ubiquitination. However, this does not exclude the possibility that the stability of SNIPER4 is regulated by an external E3. To confirm whether an external E3 is deployed to ubiquitinate SNIPER4, ubiquitination of DN-SNIPER4, which lacks the self-ubiquitination activity, can be examined using an antibody against ubiquitin following IP-western blot. The external E3, if there is any, may be identified through IP-MS using DN-SNIPER4 as bait. Most TRAF proteins in humans contain a RING domain and ubiquitination of TRAF proteins is required for their function (Häcker et al., 2011b; Xie, 2013a, 2013b). In contrast, the majority of TRAF proteins in plants lack a RING domain, which raises the question of whether ubiquitination plays a role in the function of plant TRAF proteins. Sequencing of the ubiquitome would test whether plant TRAF proteins are commonly regulated by ubiquitination. Subsequent in vitro ubiquitination assays would reveal the types of ubiquitination on plant TRAF proteins, which offers clues about the roles of ubiquitination on plant TRAF proteins. 79 4.2 Opposite transcriptional regulation of SA biosynthesis by CAMTAs and CDK8 CAMTA3 functions redundantly with CAMTA1 and CAMTA2 in the regulation of plant immunity (Kim et al., 2013). Despite several attempts to elucidate the function of CAMTAs, the major role of CAMTAs remain ambiguous. For my Ph.D. research, I conducted the SUCA screen in order to dissect the roles of CAMTAs in immunity. From the suppressor screen, mutations in ICS1 are found to almost fully suppress the autoimmunity of camta1/2/3, suggesting that the major role of CAMTAs is to suppress SA synthesis. In accordance with this hypothesis, free and total SA levels are up-regulated in camta1/2/3 plants but are compromised in gain-of-function camta3-3D mutants. Since CAMTAs are transcription factors, it is speculated that CAMTAs regulate SA synthesis at the transcriptional level. In support with this, expression of SA-related genes, including ICS1, EDS5 and PBS3, is increased in camta1/2/3, as revealed by microarray data, but is reduced in camta3-3D as shown by qPCR. The promoter regions of ICS1 and PBS3 contain two and one CAMTA-binding motifs (A/C/G)CGCG(C/G/T), respectively. CAMTAs may directly bind to the promoter regions of ICS1 and PBS3 to inhibit their expression. This scenario is less likely since CAMTA3 can only weakly bind to the two CAMTA-binding motifs from the ICS1 promoter in EMSA and displays no interaction with the CAMTA-binding motif from the PBS3 promoter (preliminary data not shown). Alternatively, CAMTAs may directly regulate the expression of transcription factors that control the expression of SA-related genes. Interestingly, two partially redundant transcription factors, SARD1 and CBP60g, positively control SA synthesis by regulating the expression of a repertoire of SA-related genes, such as ICS1, EDS5 and PBS3 (Sun et al., 2015; Zhang et al., 2010b). Analysis of the promoter regions of SARD1 and CBP60g identified three and two CAMTA-binding motifs, respectively (Kim et al., 2013). It is possible that CAMTAs suppress the expression of SA-related genes by directly manipulating the expression of SARD1 and CBP60g. Future experiments, such as ChIP-qPCR and EMSA, are desired to test the potential connection between CAMTAs and SARD1 as well as CBP60g. CDK8 was isolated from the SUCA screen. Loss-of-function CDK8 partially restores the enhanced disease resistance against Hpa Noco2 and elevated SA levels in camta1/2/3. cdk8 mutants are compromised in accumulation of free and total SA, suggesting that CDK8 80 plays a positive role in SA biosynthesis. CDK8 encodes a cyclin-dependent kinase in the kinase module of the mediator complex, which acts as a co-activator of Pol II during transcription (Malik and Roeder, 2010). qPCR analysis showed that expression of ICS1 and EDS5 was down-regulated in cdk8 mutants, suggesting that CDK8 may contribute to SA synthesis by regulating the expression of SA-related genes, such as ICS1 and EDS5. CDK8 positively regulates transcription either through manipulating the activity of transcription factors by phosphorylation or through promoting Pol II elongation (Allen and Taatjes, 2015). It is possible that CDK8 phosphorylates and activates SARD1 and CBP60g for the regulation of expression of SA-related genes. However, no interaction between CDK8 and the two transcription factors was observed in split luciferase complementation assay, disagreeing with a direct regulation of SARD1 and CBP60g by CDK8. Mutations in SARD1 and CBP60g only partially reduce the high levels of free and total SA in camta1/2/3, indicating that additional transcription factors, besides SARD1 and CBP60g, regulate expression of genes required for SA biosynthesis, such as ICS1. Alternatively, CDK8 may regulate such transcription factors for the expression SA-related genes. A yeast-one hybrid screen can be conducted with the promoter region of ICS1 to isolate the alternative transcription factors that regulate the transcription of SA-related genes. Subsequently, protein-protein interaction assays and in vitro kinase assays can be done to examine whether the isolated transcription factors can interact with and be targeted for phosphorylation by CDK8. Another possibility is that the positive effects of CDK8 on expression of ICS1 and EDS5 may be due to its promotion of Pol II elongation during ICS1 and EDS5 transcription. To examine this possibility, the transcription elongation rate of ICS1 and EDS5 can be measured in protoplasts from wild type and cdk8 plants by assessing the distance travelled by transcribing Pol II in a timed manner. 81 Bibliography Aarts, N., Metz, M., Holub, E., Staskawicz, B.J., Daniels, M.J., and Parker, J.E. (1998). 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