MOLECULAR AND FUNCTIONAL CHARACTERISATION OF AN OSMOTIN GENE FROM THE RESURRECTION PLANT TRIPOGON LOLIIFORMIS
By Thi Thuy Trang LE BSc of Agronomy (Hons.) MSc of Plant Science
Submitted in fulfilment of the requirements for the degree of Doctor of Philosophy
at the
Centre for Tropical Crops and Biocommodities
Science and Engineering Faculty Queensland University of Technology
2018
Molecular and Functional Characterisation of an Osmotin Gene from the Resurrection Plant Tripogon loliiformis 1 Intentionally blank
2 Molecular and Functional Characterisation of an Osmotin Gene from the Resurrection Plant Tripogon loliiformis Keywords
Abiotic stress, Agrobacterium-mediated transformation, Agro-infiltration, BiFC, cell membrane integrity, co-localisation, cold stress, cold tolerance, confocal microscopic analysis, Coomassie stain, drought stress, drought tolerance, dry biomass, electrolyte leakage, embryogenic callus, EYFP, genetic engineering, GO term enrichment, Gus-reporter gene, Gus stain, His tag, hygromycin resistant marker, infiltration, KDEL, leaf damage, morphology, membrane protein tracker, Myc, NaCl, Nicotiana benthamiana, Nicotiana tabacum, Oryza sativa, osmotin, panicle length, plasmid cloning, photosynthesis, protein extraction, protein microarray, protein- protein interaction, protein purification, protein structure, qRT-PCR, recombinant proteins, resurrection plant, rice, ROS, RWC, salinity stress, salinity stress tolerance, transcriptional expression, transgenic plant, transient expression, Tripogon loliiformis, Ubi promoter, yield component.
Molecular and Functional Characterisation of an Osmotin Gene from the Resurrection Plant Tripogon loliiformis i
ii Molecular and Functional Characterisation of an Osmotin Gene from the Resurrection Plant Tripogon loliiformis Abstract
Abiotic stresses such as drought, salinity, and extreme temperature are key factors that limit crop productivity and are major constraints to meeting global food demands. The development of stress-tolerant crops that mitigate the effects of abiotic stresses on crop productivity is crucially needed to sustain agricultural production. The narrow genetic variation of stress-tolerant traits among crops and sexual barrier between species have restricted the success of developing stress-tolerant crops by conventional breeding. Genetic engineering of crops with stress-tolerant traits is a promising approach for improving stress tolerance in crops. Prior to the development of stress tolerant crops by genetic engineering, it is essential that key genes regulating stress-tolerant traits are characterised.
Stress-tolerant traits in plants are genetically coded. Naturally tolerant species, such as the resurrection plant Tripogon loliiformis, represent an ideal starting point for the identification of genes encoding stress-tolerant traits. T. loliiformis has evolved mechanisms to tolerate extreme dehydration down to 4% relative water content (RWC), facilitate cellular protection and survival during desiccation, and to rapidly recover within 48-72 h of rehydration to full metabolic activity. These mechanisms hold great potential for the introduction into crop species. It is important to identify the key regulators of these stress-tolerance mechanisms for effective transfer of stress- tolerant traits into crop species.
This PhD study describes the molecular characterisation of an osmotin gene (TlOsm) from the desiccation tolerant plant T. loliiformis. The conserved and novel characteristics of TlOsm were identified in comparison with two osmotins, OsOlp1_A from a drought-tolerant cultivar and OsOlp1_I from a drought-sensitive cultivar, of the stress sensitive species Oryza sativa (rice). Protein structural-to-functional predictions, the response of transgenic rice plants constitutively expressing each of the osmotins to cold, drought, and salinity stress, and the profiles of plant proteins interacting with three osmotins on the Arabidopsis protein microarrays (chip) and in living Nicotiana benthamiana plants were analysed. The results revealed the common and unique characteristics of TlOsm, the profiles of TlOsm protein interactors, possible
Molecular and Functional Characterisation of an Osmotin Gene from the Resurrection Plant Tripogon loliiformis iii pathways involving TlOsm, and functional roles of TlOsm in enhanced rice tolerance to cold, drought, and salinity stresses. The results highlight the higher functional efficacy of TlOsm, compared to rice osmotins, in regulating plant response to stress, indicate the potential use of TlOsm for developing crops tolerant to multiple abiotic stresses, and provide useful information for elucidating molecular mechanisms underlying osmotin functions in regulating plant response to stress.
Transcriptional profiling of TlOsm during T. loliiformis plant development and on exposure to cold, heat, drought, and salinity stresses indicated that TlOsm was induced up to a thousand fold upon cold, drought, and salinity stresses. The plasma membrane localisation of TlOsm was observed by confocal microscopy of transgenic Nicotiana tabacum expressing Enhanced Yellow Fluorescent Protein (EYFP)-tagged TlOsm. Sequence analysis of TlOsm revealed its conserved characteristics of an osmotin, the close genetic relationship with monocotyledonous osmotins, and a sequence of 50 AA at its C-terminus that is not homologous to other osmotins. Analyses based on structural-to-functional predictions, compared to two rice osmotins, revealed that TlOsm had more glucan-binding and phosphorylation sites than rice osmotins and four binding sites with enzymatic functions in sugar metabolism, which did not exist in either of rice osmotins.
The effects of TlOsm, OsOlp1_A, and OsOlp1_I on enhancing plant tolerance to cold, drought, and salinity stress were compared in transgenic rice expressing each of the osmotin gene. Agrobacterium-mediated transformation was used to generate 42 transgenic rice lines expressing TlOsm, OsOlp1_A, OsOlp1_I, or the Gus reporter gene. Transgenic plants of two successive generations were assessed for enhanced tolerance to cold, drought, and salinity stresses. The results demonstrate the capacity of TlOsm and OsOlp1_A to enhance rice tolerance to cold, drought, and salinity stresses and emphasise the additional efficacy of TlOsm. The tolerant traits passed on to the next generation. The results suggest a positive correlation between functional binding sites of the osmotins and the levels of enhanced stress tolerance in transgenic rice.
Interactive protein partners and possible pathways involving the osmotins were revealed by Arabidopsis protein chip assays. The results were validated in N. benthamiana. On the protein chips, 267, 239, and 237 proteins interacted with TlOsm, OsOlp1_A, and OsOlp1_I respectively. Osmotin interactors were found involved iv Molecular and Functional Characterisation of an Osmotin Gene from the Resurrection Plant Tripogon loliiformis in the diverse biological processes and pathways fundamental in plant development and adaptation. The three dominant pathways were fructose and mannose metabolism, glycolysis, and pentose phosphate pathways. Interestingly, 21 proteins interacted only with TlOsm and were involved in plant responses to stress, chemical, and endogenous stimuli. Nine of these 21 proteins are involved in nine pathways that do not contain any interactors of the rice osmotins. Fifteen interactions were validated in planta by Bimolecular Fluorescence Complementation (BiFC) analysis and 14 of those confirmed the results on the chip assays. Protein-protein interaction assays revealed that TlOsm is capable of interacting with more stress-responsive proteins than osmotins from sensitive species, O. sativa.
The study contributes significantly to understanding the proteomic evolution of osmotins from tolerant and sensitive species as well as from tolerant and sensitive cultivars within species. The results provide evidence highlighting the potential of T. loliiformis genetic resource for identification of stress-tolerant traits to introduce into crop species. The study also deepens our understanding of the molecular mechanisms underlying osmotin functions in regulating plant stress response.
Molecular and Functional Characterisation of an Osmotin Gene from the Resurrection Plant Tripogon loliiformis v List of Publications and Conferences
Thi Thuy Trang LE, Brett Williams, and Sagadevan Mundree (2017). An osmotin from the resurrection plant Tripogon loliiformis (TlOsm) confers tolerance to multiple abiotic stresses in transgenic rice. Physiologia Plantarum, doi: 10.1111/ppl.12585.
Thi Thuy Trang LE, Brett Williams, and Sagadevan Mundree (2016). Comparative analysis of osmotins from Tripogon loliiformis and Oryza sativa revealed role in abiotic stress tolerance through signalling pathways. Poster in the Combio2016 Workshop, 03-07 Oct 2016, Brisbane, Australia.
Thi Thuy Trang LE, Brett Williams, and Sagadevan Mundree (2016). Characterization of an osmotin gene from resurrection plant Tripogon loliiformis. Oral presentation in the 7th International Workshop on Desiccation Sensitivity and Tolerance across Life Forms, 11-15 Jan 2016, Cape Town, South Africa.
vi Molecular and Functional Characterisation of an Osmotin Gene from the Resurrection Plant Tripogon loliiformis Table of Contents
Keywords ...... i Abstract ...... iii List of Publications and Conferences ...... vi Table of Contents ...... vii List of Figures ...... xiii List of Tables ...... xvi List of Abbreviations ...... xvii Statement of Original Authorship ...... xxi Acknowledgements ...... xxiii Chapter 1: Introduction and Literature Review ...... 1 1.1 INTRODUCTION ...... 1 1.2 PLANTS AND ENVIRONMENTAL STRESSES ...... 3 1.2.1 Plants affected by environmental factors ...... 3 1.2.2 Plant responses to abiotic stresses ...... 4 1.2.3 Abiotic stress, world food security, and molecular breeding ...... 11 1.3 OSMOTIN AND OLP: THE STRESS-RESPONSIVE MULTIFUNCTIONAL PROTEINS ...... 13 1.3.1 Osmotins and OLPs, the members of pathogenesis-related proteins ...... 13 1.3.2 Osmotins and OLPs play roles in multi-stress responses ...... 15 1.3.3 Expression of osmotins and OLPs enhanced plant tolerance to multiple stress factors ...... 17 1.3.4 Possible roles of osmotins and OLPs in response to abiotic and biotic stress ...... 19 1.3.5 Osmotins and OLPs as potential candidate genes for enhancing multi- stress tolerance and for other uses in food industry...... 22 1.4 RESURRECTION PLANTS: A NOVEL SOURCE FOR STRESS-RESPONSIVE GENES ...... 23 1.5 RICE AS A TARGET FOR ENHANCING ABIOTIC STRESS TOLERANCE VIA TRANSGENIC APPROACH ...... 25 1.5.1 Rice is an important staple food crop ...... 25 1.5.2 Rice is the model plant for monocots ...... 26 1.5.3 Rice is susceptible to abiotic stresses ...... 26 1.6 RECENT ADVANCES IN STUDYING FUNCTIONAL PROTEINS ...... 28 1.6.1 Bioinformatics tools ...... 29 1.6.2 Advances in genetic manipulation ...... 30 1.6.3 Functional protein microarrays ...... 31 1.6.4 Detection tools for protein-protein interactions in living cells ...... 32 1.7 PROBLEM STATEMENT, GAPS, AIMS, AND OBJECTIVES ...... 35
Molecular and Functional Characterisation of an Osmotin Gene from the Resurrection Plant Tripogon loliiformis vii
Chapter 2: General Materials and Methods ...... 39 2.1 MATERIALS ...... 39 2.1.1 Source of general chemicals and specialized reagents ...... 39 2.1.2 Plant materials...... 39 2.1.3 Bacterial strains...... 40 2.1.4 Oligodeoxyribonucleotide (Primers) ...... 40 2.1.5 Backbone vectors ...... 43 2.1.6 General media, solutions: abbreviation and composition ...... 47 2.1.7 Plant tissue culture medium ...... 48 2.2 METHODS ...... 49 2.2.1 Cloning and bacterial transformation...... 49 2.2.2 General methods in nucleic acid extraction, amplification and analysis ...... 54 2.2.3 Agrobacterium-mediated transient transformation of plants ...... 57 2.2.4 Confocal imaging ...... 57 2.2.5 Relative water content ...... 58 2.2.6 Electrolyte leakage measurement ...... 58 2.2.7 Agrobacterium-mediated plant transformation and regeneration ...... 58 2.2.8 Bioinformatics analysis ...... 58 2.2.9 Abiotic stress treatment of T. loliiformis ...... 58 2.2.10 Transgenic rice acclimatisation and abiotic stress treatments ...... 58 2.2.11 Protein extraction, purification and analysis ...... 59 2.2.12 Protein microarray hybridisation and detection of protein-protein interaction ...... 59 2.2.13 Data analysis ...... 59 Chapter 3: Molecular Characterisation of TlOsm, an Osmotin from Tripogon loliiformis ...... 61 3.1 INTRODUCTION ...... 61 3.2 MATERIALS AND METHODS ...... 63 3.2.1 Plant materials...... 63 3.2.2 Sequence analysis of TlOsm ...... 63 3.2.3 Phylogenic tree construction ...... 64 3.2.4 Comparison of TlOsm with Os-OlP1_A and OsOlp1_I by bioinformatic tools ...... 64 3.2.5 Growth conditions, abiotic stress treatments and sampling for T. loliiformis plants ...... 64 3.2.6 RNA extraction and RT_qPCR analysis ...... 65 3.2.7 Generation of transgenic tobacco expressing EYFP-tagged TlOsm and VC ...... 66 3.2.8 Agro-infiltration of transgenic tobacco ...... 68 3.2.9 Salinity stress treatment of tobacco plants ...... 68 3.2.10 Confocal imaging ...... 69 3.3 RESULTS ...... 69 3.3.1 Sequence analysis of TlOsm ...... 69 3.3.2 TlOsm is induced by cold, drought and salinity stresses ...... 74 3.3.3 TlOsm localises to the plasma membrane ...... 77 3.3.4 TlOsm, OsOlp1_A and OsOlp1_I differ in active binding residues ..... 81 3.4 DISCUSSION ...... 83 3.4.1 TlOsm is a member of osmotins and OLPs ...... 83 3.4.2 TlOsm is involved in osmotic stress response of T. loliiformis plants ...... 84 3.4.3 TlOsm localises to the plasma membrane regardless of stress condition ...... 85 viii Molecular and Functional Characterisation of an Osmotin Gene from the Resurrection Plant Tripogon loliiformis 3.4.4 TlOsm has more binding sites typical for osmotins than OsOlp1_A and OsOlp1_I ...... 86 Chapter 4: Generation of Transgenic Rice Constitutively Expressing Oryza sativa and Tripogon loliiformis Osmotins ...... 89 4.1 INTRODUCTION ...... 89 4.2 MATERIALS AND METHODS ...... 91 4.2.1 Plasmid constructs and Agrobacterium strains ...... 91 4.2.2 Plant materials and culture media ...... 92 4.2.3 Rice callus induction, transformation, selection and regeneration ...... 92 4.2.4 Characterisation of transgenic rice plants ...... 94 4.3 RESULTS ...... 97 4.3.1 Callus induction, transformation, selection and regeneration of putative transgenic rice plants ...... 97 4.3.2 Confirmation of transgenes in putative transgenic rice lines ...... 99 4.3.3 Expression of transgenes in transgenic rice plants confirmed by RT-PCR ...... 101 4.3.4 Expression of GUS protein confirmed in GUS-expressing rice lines...... 103 4.4 DISCUSSION ...... 105 Chapter 5: Comparative Analysis of Transgenic Rice Constitutively Expressing Osmotins from Tolerant and Sensitive Species ...... 109 5.1 INTRODUCTION ...... 109 5.2 MATERIALS AND METHODS ...... 111 5.2.1 Plant materials ...... 111 5.2.2 Acclimatisation of tissue-cultured rice plants ...... 112 5.2.3 Growth conditions and stress treatments at seedling stage ...... 112 5.2.4 Germination of T1 transgenic rice plants ...... 113 5.2.5 Screening of T1 transgenic rice plants ...... 113 5.2.6 Growth conditions and reproductive-stage stress treatments ...... 114 5.2.7 Electrolyte leakage ...... 114 5.2.8 Relative water content determination ...... 115 5.2.9 Plant dry weight determination ...... 115 5.2.10 Measurement of photosynthetic parameters ...... 115 5.2.11 Statistical analysis ...... 116 5.3 RESULTS ...... 117 5.3.1 Rice plants constitutively expressing TlOsm or OsOlp1_A maintained growth under cold, drought, and salinity stresses ...... 117 5.3.2 Rice plants constitutively expressing TlOsm or OsOlp1_A produce more tillers than WT, NT, and VC plants under cold, drought, and salinity stresses ...... 119 5.3.3 Rice plants constitutively expressing OsOlp1_A or TlOsm retained water better than OsOlp1_I, VC and NT or WT plants under cold, drought, and salinity stresses ...... 121 5.3.4 Rice plants constitutively expressing osmotins maintain membrane integrity better than VC and WT or NT plants under cold, drought, and salinity stresses ...... 123 5.3.5 Rice plants constitutively expressing TlOsm or OsOlp1_A maintained photosynthesis efficiency under drought and salinity stresses ...... 125 5.3.6 Stressed rice plantlets constitutively expressing TlOsm or OsOlp1_A showed heathier morphological appearance than VC and WT ...... 130 5.3.7 Rice plants constitutively expressing TlOsm or OsOlp1_A resulted in higher dry biomass under cold, drought, and salinity stresses ...... 133
Molecular and Functional Characterisation of an Osmotin Gene from the Resurrection Plant Tripogon loliiformis ix 5.3.8 Constitutive expression of TlOsm or OsOlp1_A improves survival rate under salinity, drought and cold stress in transgenic rice...... 135 5.3.9 Constitutive expression of TlOsm or OsOlp1_A improved yield under drought and salinity in transgenic rice ...... 137 5.4 DISCUSSION ...... 141 5.4.1 TlOsm and OsOlp1_A confers tolerance to cold, drought and salinity stresses in rice ...... 142 5.4.2 Retaining water, maintaining membrane integrity, and maintaining photosynthesis activities are some strategies TlOsm and OsOlp1_A plants used to cope with cold, drought, and salinity stresses...... 145 5.4.3 TlOsm plants showed advantages over OsOlp1_A plants in drought and cold stresses, not in salinity stresses ...... 148 5.4.4 OsOlp1_I did not sufficiently enhance rice plants tolerance to cold, drought, and salinity stresses ...... 149 5.4.5 Low stomata conductance is possibly a cause of growth penalty of TlOsm plants under unstressed conditions...... 150 Chapter 6: Analysis of Protein-Protein Interactions of Osmotins from Stress Tolerant and Sensitive Species ...... 155 6.1 INTRODUCTION ...... 155 6.2 MATERIALS AND METHODS ...... 157 6.2.1 Plant materials...... 157 6.2.2 Plasmid vectors ...... 157 6.2.3 Protein expression in Nicotiana benthamiana ...... 159 6.2.4 Recombinant protein extraction, purification, and enrichment ...... 160 6.2.5 SDS-PAGE ...... 161 6.2.6 Coomassie blue staining ...... 161 6.2.7 Western blotting ...... 161 6.2.8 Protein chip hybridisation and scanning ...... 162 6.2.9 Identification of significant interactions ...... 163 6.2.10 Determination of significant protein interactors of target osmotins ...... 163 6.2.11 Identification of pathways containing interactive protein partners of TlOsm, OsOlp1_A, and OsOlp1_I ...... 164 6.2.12 BiFC performance and analysis ...... 164 6.3 RESULTS ...... 167 6.3.1 Expression and purification of recombinant osmotin proteins ...... 167 6.3.2 Arabidopsis proteins interacting with TlOsm, OsOlp1_A, and OsOlp1_I revealed ...... 169 6.3.3 Gene ontology (GO) enrichment for interactors of the three osmotins ...... 172 6.3.4 Pathways of TlOsm, OsOlp1_A, and OsOlp1_I interactive protein partners revealed ...... 174 6.3.5 Physical interactions of selected Arabidopsis proteins with TlOsm, OsOlp1_A, and OsOlp1_I confirmed in planta ...... 176 6.4 DISCUSSION ...... 183 6.4.1 Production of pure and functional recombinant osmotins ...... 187 6.4.2 Analysing potential protein interactors of TlOsm, OsOlp1_A and OsOlp1_I affirms their multiple functions ...... 189 6.4.3 Common and specific potential interactors of TlOsm, OsOlp1_A, and OsOlp1_I provide testable target proteins for unravelling osmotin functions ...... 191 6.4.4 Possible mechanisms underlying TlOsm, OsOlp1_A, and OsOlp1_I functions ...... 193
x Molecular and Functional Characterisation of an Osmotin Gene from the Resurrection Plant Tripogon loliiformis Chapter 7: General Discussion ...... 197 7.1 TlOsm has more functional efficacy in regulation of plant stress response than rice osmotins ...... 198 7.2 TlOsm is a multi-functional protein playing a role in plant response to stresses ....201 7.3 TlOsm (and OsOlp1_A) likely contribute to plant stress response through signal transduction ...... 203 7.4 TlOsm has potential for use in improving crop tolerance to multiple abiotic stresses 206 7.5 Concluding remarks ...... 207 Appendices ...... 209 Bibliography ...... 243
Molecular and Functional Characterisation of an Osmotin Gene from the Resurrection Plant Tripogon loliiformis xi
xii Molecular and Functional Characterisation of an Osmotin Gene from the Resurrection Plant Tripogon loliiformis List of Figures
Figure 1.1 Plant gene regulation in response to salt and drought stress ...... 6 Figure 1.2 Structure homology of osmotin, thaumatin and antifungal PR-5 ...... 15 Figure 1.3 Principle of BiFC and multicolour BiFC analysis...... 34 Figure 1.4 General research outline and thesis presentation ...... 38 Figure 2.1 Plasmid maps for primary cloning...... 43 Figure 2.2 Map of backbone vector used for cloning genes stably expressing in rice...... 44 Figure 2.3 Maps of destination vectors for cloning EYFP-tag TlOsm and VC...... 45 Figure 2.4 Map of destination vector used for recombinant osmotin production...... 46 Figure 2.5 Maps of destination vectors used for detecting protein-protein interaction in planta...... 47 Figure 3.1 Schematic diagram of gene constructs for expressing EYFP-tagged TlOsm and EYFP control in N. tabacum ...... 66 Figure 3.2 Alignment of TlOsm with selected plant osmotins...... 70 Figure 3.3 Property analysis of TlOsm...... 71 Figure 3.4 The phylogenic tree showing the relationship of TlOsm and osmotins from different monocotyledonous and dicotyledonous species...... 73 Figure 3.5 Developmental stages of T. loliiformis for sampling...... 74 Figure 3.6 Expression of TlOsm under developmental stages and various abiotic stresses...... 76 Figure 3.7 Fluorescence-based selection of transgenic tobacco expressing EYFP-tagged TlOsm and VC...... 77 Figure 3.8 Confirmation of stable transgene integration in transgenic tobacco by PCR...... 78 Figure 3.9 Cellular localisation of TlOsm...... 79 Figure 3.10 Subcellular co_localisation analysis of EYFP-tagged TlOsm and EYFP in N. tabacum...... 80 Figure 3.11 Localisation of EYFP-tagged TlOsm and EYFP in transgenic N. tabacum cells under unstressed and 150 mM NaCl stress...... 81 Figure 4.1 Schematic diagram of gene expression cassettes for expressing osmotins and GUS-reporter gene (control-VC) in O. sativa...... 92 Figure 4.2 Procedure of rice callus induction, transformation, selection, and plant regeneration...... 98 Figure 4.3 Characterisation of putative transgenic rice lines by PCR...... 100
Molecular and Functional Characterisation of an Osmotin Gene from the Resurrection Plant Tripogon loliiformis xiii Figure 4.4 Transcriptional expression of transgenes in transgenic rice by RT- PCR...... 102 Figure 4.5 GUS expression in transgenic rice calli and plants...... 104 Figure 5.1 Relative shoot growth of WT or NT, VC and transgenic plants expressing OsOlp1_A, OsOlp1_I, and TlOsm...... 119 Figure 5.2 Tiller number of WT or NT, VC and transgenic plants expressing OsOlp1_A, OsOlp1_I, and TlOsm...... 120 Figure 5.3 Leaf relative water content (RWC) of WT or NT, VC and transgenic plants expressing OsOlp1_A, OsOlp1_I, and TlOsm...... 122 Figure 5.4 Leaf electrolyte leakage of WT or NT, VC and transgenic plants expressing OsOlp1_A, OsOlp1_I, and TlOsm ...... 124 Figure 5.5 Net photosynthesis of NT, VC and transgenic plants expressing OsOlp1_A, OsOlp1_I, and TlOsm...... 127 Figure 5.6 Transpiration rate of NT, VC and transgenic plants expressing OsOlp1_A, OsOlp1_I, and TlOsm...... 128 Figure 5.7 Stomatal conductance of NT, VC and transgenic plants expressing OsOlp1_A, OsOlp1_I, and TlOsm...... 129
Figure 5.8 Morphology of T0 rice plants under cold, drought and salinity stresses at seedling stage...... 131
Figure 5.9 Morphology of T1 rice plants and panicles under unstressed, drought and salinity stresses when plants exposed to stresses at reproductive stage...... 133 Figure 5.10 Survival rate and morphology of rice plants recovered from stress treatments at seeding stage...... 136 Figure 6.1 Schematic diagram of gene expression cassettes for transiently expressing tagged osmotins in N. benthamiana...... 158 Figure 6.2 Schematic diagram of gene expression cassettes for detecting target osmotins and Arabidopsis protein interaction in N. benthamiana...... 159 Figure 6.3 Recombinant osmotin production...... 168 Figure 6.4 Procedure of recombinant osmotins hybridising with protein chips and data generation ...... 170 Figure 6.5 Biological processes involving protein interactors of TlOsm, OsOlp1_A and OsOlp1_I ...... 173 Figure 6.6 Analysis of in planta interactions between AtCPK4 and TlOsm, OsOlp1_A, or OsOlp1_I...... 178 Figure 6.7 Analysis of in planta interactions between AtCPK5 and TlOsm, OsOlp1_A, or OsOlp1_I...... 179 Figure 6.8 Analysis of in planta interactions between AtMS1 and TlOsm, OsOlp1_A, or OsOlp1_I...... 180 Figure 6.9 Analysis of in planta interactions between AtALDH7B4 and TlOsm, OsOlp1_A, or OsOlp1_I...... 181
xiv Molecular and Functional Characterisation of an Osmotin Gene from the Resurrection Plant Tripogon loliiformis Figure 6.10 Analysis of in planta interactions between AtPER42 and TlOsm, OsOlp1_A, or OsOlp1_I...... 182 Figure 6.11 Protein interaction networks of Arabidopsis genes selected for BiFC analysis...... 186
Molecular and Functional Characterisation of an Osmotin Gene from the Resurrection Plant Tripogon loliiformis xv List of Tables
Table 1.1 Representatives of transgenic plants expressing plant osmotins and their phenotypes ...... 18 Table 2.1 List of primers for plasmid cloning ...... 41 Table 2.2 List of plant expression vectors constructed and used in the research ...... 51 Table 3.1 List of primers for PCR characterisation of transgenic tobacco plants ...... 68 Table 3.2 Characteristics of TlOsm, OsOlp1_A, and OsOlp1_I by functional predictions ...... 82 Table 4.1 List of primers used for characterisation of transgenic plants ...... 95 Table 4.2 Summary of generating and characterising transgenic rice lines expressing target osmotins and control gene in the research ...... 105 Table 5.1 A summary of experiments in the study ...... 116 Table 5.2 Dry biomass of plants in seedling-stage stress treatment experiments .... 134 Table 5.3 Dry biomass of plants in reproductive-stage stress treatment experiments ...... 135 Table 5. 4 Yield components of TlOsm, OsOlp1_A, OsOlp1_I, VC and NT (control) plants under unstressed, drought, and salinity stress conditions ...... 139 Table 6.1 Select Arabidopsis genes for BiFC analysis ...... 165 Table 6.2 Combinations of osmotins and Arabidopsis genes used for co- expression and BiFC analysis ...... 166 Table 6.3 Comparison of significant interactions between Arabidopsis proteins on the chip with the three osmotins ...... 171 Table 6.4 Significant pathways of Arabidopsis proteins interacting with TlOsm, OsOlp1_A, and OsOlp1_I ...... 174 Table 6.5 Pathways of Arabidopsis proteins interacting with TlOsm and OsOlp1_A, or TlOsm only ...... 175 Table 6.6 Pathways of Arabidopsis proteins commonly interacting with TlOsm, OsOlp1_A, and OsOlp1_I in relation to published and predicted functions of osmotin ...... 176
xvi Molecular and Functional Characterisation of an Osmotin Gene from the Resurrection Plant Tripogon loliiformis List of Abbreviations
Abbreviations AA = amino acids ABA = abscisic acid AMP = adenosine monophosphate AMPK = Adenosine monophosphate-activated protein kinase APX = ascorbate peroxidase ATP = adenosine triphosphate BAP = 6-benzylaminopurine BiFC = Bimolecular Fluorescence Complementation BLAST = Basic Logical Alignment Tool bp = base pairs BSA = bovine serum albumin CaM = calmodulin CaMV = Cauliflower mosaic virus cDNA = complementary DNA CDPK = Calcium-dependent protein kinase CML = Calmodulin-like CTAB = cety trimethyl ammonium bromide CTCB = Centre for Tropical Crops and Biocommodities C-terminal = carboxyl- terminal DEPC = diethylpyrocarbonate DHAR = dehydro ascorbate reductase
dH2O = distilled water DIG = digoxygenin DMSO = dimethyl sulphoxide DNA = deoxyribonucleic acid dNTPs = deoxyribonucleotide triphosphates DTT = 1, 4-dithiothreitol DW = dry weight 2, 4,-D = 2, 4-dichlorophenoxyacetic acid EDTA = ethylenediaminetetraacetic acid EL = electrolyte leakage
Molecular and Functional Characterisation of an Osmotin Gene from the Resurrection Plant Tripogon loliiformis xvii ER = endoplasmic reticulum E. coli = Escherichia coli EYFP = Enhanced Yellow Fluorescence Protein FRET = Fluorescence Resonance Energy Transfer GMO = Genetically modified organism GUS = β-glucoronidase His = Histidine HK = Histidine kinase HSP = Heat shock protein IAA = indole-3-acetic acid IBA = indole-3-butyric acid IPTG = iso-propyl-β-D-thiogalatopyranoside kbp = kilo base pair(s) KDEL = Lys-Asp-Glu-Leu, an ER retention signal peptide LB = Luria-Bertani LEA = Late Embryogenic Abundant MAB = Marker-assisted breeding MAP = Mitogen-activated protein MAPK = Mitogen-activated protein kinase MDHAR = Monodehydroascorbate reductase mRNA = messenger RNA MS = Murashige and Skoog media NAA = α-naphthalene acetic acid NCBI = National Centre for Biotechnology Information Nos = Nopaline synthase nt = nucleotide N-terminal = amino terminal OD = optical density OD600 = optical density at 600 nm OLP = Osmotin-Like Protein PBS = phosphate buffered saline PCD = programmed cell death PCR = polymerase chain reaction pDNA = plasmid DNA PEG = Polyethylene glycose
xviii Molecular and Functional Characterisation of an Osmotin Gene from the Resurrection Plant Tripogon loliiformis pH = -log (proton concentration) PPAR = Peroxisome proliferator activated receptor PR5 = pathogenesis-related proteins group 5 QUT = Queensland University of Technology RKN = root-knot nematode RLK = receptor-like kinase RNA = ribonucleic acid RNase = ribonuclease ROS = reactive oxygen species RT-PCR = reverse transcription polymerase chain reaction RT_qPCR = reverse-transcription quantitative real-time polymerase chain reaction RWC = relative water content SDS = sodium dodecyl sulphate SDS-PAGE = sodium dodecyl sulphate polyacrylamide gel electrophoresis SE = standard error SOD = superoxide dismutase ssp = subspecies TAE = Tris acetate EDTA TAP = Tandem Affinity Purification TBS = Tris buffer saline TBS-T = Tween Tris buffer saline TEMED = N,N,N’,N’-tetramethylethylenediamine TLP = Thaumatin-like protein Tris = Tris (hydroxymethyl) aminomethane TW = turgor weight Tween20 = polyoxyethylene (20) sorbitan monolaurate Ubi = ubiquitin uidA = reporter gene encoding β-glucuronidase UTR = untranslated region UV = ultraviolet VC = vector control X-gal = 5-bromo-4-chloro-3-indolyl-β-D-galactopyranoside X-gluc = 5-bromo-4-chloro-3-indolyl-β-D-glucuronide- cyclohexylamine salt
Molecular and Functional Characterisation of an Osmotin Gene from the Resurrection Plant Tripogon loliiformis xix
Units °C = Degree Celsius d = days Da = Daltons(s) dSm-1 = deciSiemens per metre g = Gram(s) g = relative centrifugal force in units of gravity h = Hour(s) L = Litre(s) M = Molar m = Metre(s) MW = Molecular weight min = Minute(s) mol = Mole(s) rpm = Revolutions per minute s = Second(s) V = Volt(s) vol = Volume(s) v/v = Volume per volume w/v = Weight per volume
Prefixes K = kilo m = milli µ = micro
xx Molecular and Functional Characterisation of an Osmotin Gene from the Resurrection Plant Tripogon loliiformis Statement of Original Authorship
The work contained in this thesis has not been previously submitted to meet requirements for an award at this or any other higher education institution. To the best of my knowledge and belief, the thesis contains no material previously published or written by another person except where due reference is made.
QUT Verified Signature Signature:
Date: 16/01/2018
Molecular and Functional Characterisation of an Osmotin Gene from the Resurrection Plant Tripogon loliiformis xxi
xxii Molecular and Functional Characterisation of an Osmotin Gene from the Resurrection Plant Tripogon loliiformis Acknowledgements
The successful completion of my thesis would not have been possible without a supportive and encouraging supervisory committee, a diverse technical support team, my wonderful family and friends, and funding from Australian Government. With deep sense of gratitude, I wish to thank Professor Sagadevan Mundree my principal supervisor for giving me the opportunity to undertake my PhD study at QUT; for his guidance, support, and encouragement throughout my PhD research; for his helpful criticisms and stimulating discussions during thesis preparation; and for setting a high standard of academic conscientiousness and achievement for his students. I would like to express my sincere thanks to my associate supervisor Dr Brett Williams for his rigorous scientific guidance, excellent mentorship, incessant encouragement, and his availability in times of needs during the course of my PhD research; and for his critical guidance, comments and suggestions in the preparation of this thesis. I acknowledge my special thanks to Dr S. Robin (deceased) and Dr M. Raveendran my external supervisors at the Tamil Nadu Agriculture University (Coimbatore, India) for the conceptualisation of plant osmotin evolution and for sharing experimental information of two rice osmotins. I wish to pray for the departed soul to rest in peace. I would like to extend my thanks to CTCB fellow HDR students, Postdocs, and technical staff and Abiotic stress group members: Linh Hoang (rice transformation and stress treatments), Isaac Njaci (protein modelling and confocal imaging), Peraj Karbaschi (protein chip); Hao Long (cloning and RT-qPCR), Grace Tan (photography), Sudipta, Alam, Jacqui, Michael, Laleh, Anthony Brinin, Tom, Pauline, and Abagail for contributions to my project update presentations, for their friendship and supports; Dr Benjamin Dugdale for providing the pEAQ-HT construct. The entire CTCB family for their friendship, support, and encouragement. The assistance of all of these fellow students and research fellows is deeply appreciated. Special thanks go to Central Analytical Research Facility (CARF) staff: Sanjleena Singh and Jamie Riches for their assistant with the confocal microscope. Thanks go to the QIMT, Lea Lekieffre and Penny Groves for facility and support in protein chip scan and analysis using the Genepix 4300A slide scanner. I wish to acknowledge Professor Acram Taji for introducing me to such wonderful supervisors and research team and for her ceaseless encouragement. My dream for PhD program at QUT would not have been reached without the financial support from Australian Government through the Endeavour Prime Minister PhD Award scholarship. I acknowledge the support with gratitude. I am very grateful to my family: to my husband Dai Huong Nguyen and children Le Huong Giang Nguyen and Le Thuy Ninh Nguyen for their love, support, patience, and encouragement; for giving me the faith and strength to complete my PhD program; to my parents, parents-in-law, brothers, and sisters for their understanding, caring, and encouragement.
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Chapter 1: Introduction and Literature Review
1.1 INTRODUCTION
The global population is estimated to reach 9.8 billion by 2050. To provide sufficient food for this population globally, agricultural production must double (Ray et al., 2013). However, increasing agricultural productivity is a massive challenge and is limited by decreased yields and arable land as well as increased disease incidence and abiotic stress; both of which are significantly affected by changing climate conditions. Of the limitations, abiotic factors such as drought, extreme temperature, and salinity have been identified as the major factors hindering agricultural production worldwide (Cominelli et al., 2013). There is an urgent need to develop technologies for the generation of enhanced crops that can survive long spells of stresses, and upon return of favourable conditions, continue to grow and yield. Genetic engineering of crops with foreign gene(s) is an approach that offers a great potential for crop improvement particularly to abiotic stress tolerant traits. However, the complex nature of abiotic stress responses, the availability of the stress tolerant genes and the lack of knowledge regarding stress pathways in plants have affected the implementation of this approach in solving problems associated with abiotic stresses (Gosal et al., 2009).
The success of genetic engineering approaches to improve plant tolerance to abiotic stresses relies on the ability of transgene products to play a key role in tolerance. Studies have shown that stress tolerance in plants is a multigenic trait (Sairam and Tyagi, 2004). To develop strategies for the improvement of crops adapted to future extreme environment, it is important to identify the key upstream regulators of stress acclimation from the stress-adapted species and to engineer them into crop plants (Mittler and Blumwald, 2010). It is believed that such genes might provide the crop plants the necessary arsenal to tolerate extreme stress conditions compared to the non-modified parental plants (Cominelli et al., 2013). A small group of angiosperms known as resurrection plants can tolerate extreme levels of dehydration down to 4% relative water content and resume full metabolic activity upon watering. Studies on the Australian native
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resurrection grass, Tripogon loliiformis, have shown that this plant implements a number of molecular, biochemical, physiological and structural mechanisms for rapid response to water deficit and quick recovery upon rehydration as well as for facilitating survival mechanism during desiccation state (Williams et al., 2015; Karbaschi et al., 2016). Therefore, resurrection plants such as T. loliiformis represent both ideal model plants and a unique source for the identification of novel, functionally relevant, stress-associated genes and pathways for utilisation in enhancement of stress tolerance in crops.
Among genes involved in stress response networks, gene encoding osmotin has shown as a potential candidate gene. Osmotins and osmotin-like proteins (OLPs) are members of the pathogenesis-related proteins that have been proven to play key roles in both abiotic and biotic stress responses. Osmotin and OLP genes are induced in response to various abiotic and biotic stresses in different plant species (Singh et al., 1985; Zhu et al., 1995; Hong et al., 2004; Zhang and Shih, 2007). Genes encoding osmotins and OLPs have been characterised from many plant species and shown to have multiple functions in enhancing plant stress tolerance (Singh et al., 1987; Yen et al., 1994a; Kim et al., 2002; Onishi et al., 2006; Jami et al., 2007). Additionally, the constitutive expression of osmotin genes in transgenic crops has improved tolerance to drought, high-salinity, and cold stresses and some combinations of these stresses (D'Angei and Altamura, 2007; Goel et al., 2010; Subramanyam et al., 2011; Subramannyan et al., 2012; Patade et al., 2013). Although intensive studies have been conducted to dissect the roles of osmotins in plant stress responses, the mechanisms by which osmotins mediate these responses have not been well established. Primarily, it was suggested that osmotin improves salt tolerance by reducing the accumulation of Na+ ion in the cytoplasm, the uptake of Na+ into the cells, or acting as Na+/H+ antiporter (Singh et al., 1987; Yen et al., 1994a). Later, number of studies have shown osmotin enhanced abiotic tolerance in plants by modulating transcript abundance and functional expression of stress responsive genes and upregulating the levels of several compatible osmolytes and reactive oxygen species (ROS) scavengers (Barthaker et al., 2001; Husaini and Abdin, 2008a; Parkhi et al., 2009; Das et al., 2011; Subramanyam et al., 2011; Subramannyan et al., 2012; Patade et al., 2013). These studies hypothesised that osmotin might be a transcription factor of the key genes of plant response to abiotic and biotic stresses. However, this hypothesis was later ruled out by the evidence that osmotin structures did not contain any DNA-binding motif (Abdin et al., 2011). Osmotins were also shown to activate MAPK proteins (Yun et al., 1998), which are the key enzymes catalysing
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the phosphotransfer reactions. These reactions are fundamental to most signalling and regulatory processes associated to enzyme activation, macro-molecules assembly, protein localisation and degradation in plant stress responses. Osmotins role as a regulator of plant stress tolerance through cell signalling was recently gained recognition (Viktorova et al., 2012). Although the mode of action of osmotins remained unclear, their multifunctional nature suggests that osmotins represent a key modulator regulating plant response to biotic and abiotic stresses.
In field conditions, crop plants are often exposed to multiple stresses simultaneously. Therefore, genes encoding osmotins are likely to be suitable candidates for the genetic enhancement of crops, with respect to multiple-stress tolerance. In addition, stress- responsive genes from highly resilient species such as T. loliiformis hold great potential for introducing stress-tolerant traits into crop plants to cope with abiotic stresses. Characterisation of such a gene could provide great promise for the uses in genetic engineering approach. Moreover, understanding the pathways and the mechanisms by which osmotin mediates multiple stress responses of plants holds huge potentials for the gene utilization in developing broad-spectrum stress tolerant crops.
1.2 PLANTS AND ENVIRONMENTAL STRESSES
1.2.1 Plants affected by environmental factors
Plants require water, CO2, light, appropriate temperature and mineral nutrients to support growth, development and reproduction. The requirement of these factors for optimal growth varies depending on plant species and developmental stages. Environmental factors that reduce plant growth and production below optimal levels are considered as abiotic stresses. Many abiotic factors such as drought, salinity, temperature, high light intensity, soil chemical toxicity, and UV radiation have established stress agents in plants. Any stage of plant development such as seed germination, seedling and vegetative growth, flowering and fruit set as well as any plant tissue i.e. root, shoot, leaf, flower and fruit can be severely affected by abiotic stresses. For crop plants, these effects ultimately result in yield loss. The following instances are some effects that have been commonly reported. High salt concentrations in soils inhibit seed germination by creating an osmotic stress in plant cells. If prolonged osmotic stress leads to a number of modifications of plant cell plasma membranes, lipid and protein composition that result in nutrient imbalances; causes ion toxicity that damages to root
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systems, generates leaf mottling and leaf necrosis, and ultimately impairs growth and development. The consequence of all these can ultimately cause plant death as a result of growth arrest and molecular damage (Sairam and Tyagi, 2004). High temperature generates high respiration and evaporation in plants. These together can push plants to permanent wilting and temperatures exceeding 46 oC can lead to complete yield loss (Nagarajan and Nagarajan, 2010). In self-fertilising cereals such as rice and wheat, a short period of cold or drought stress at the young microspore stage of pollen development results in pollen sterility that can destroy all harvested products (Dolferus et al., 2011). In fruit crops, water logging inhibits flower bud initiation, anthesis, fruit set, size and quality. During fruit development, if flooding occurs, the high osmotic absorption of water through the root results in high internal pressure that causes the fruit to burst or crack thus reducing quality (Nagarajan and Nagarajan, 2010). The severity of the effects caused by abiotic stress is dependent on plant species, plant developmental stages, severity of condition and harvested parts of plants.
In addition to environmental factors, crop plants are often exposed to various pathogens that are also influenced by adverse environmental conditions. Recent evidence suggests that climate change has altered disease complexes, triggered plant pathogen adaptation, and changed pathogen vectors. The implications of climate change for crop pathogens have contributed to significant yield losses and the deterioration of crop quality (Newton et al., 2011). Pressure of weeds, pests and diseases on crops associated with current and future changing climate has also been evaluated and estimated with a projected increase of soil-borne pathogens linked to their multiplication rates promoted by warmer weather (Jaggard et al., 2010). For example, evaluation of root-knot nematode (RKN) mediated aerobic rice yield loss combined with normal or abiotic stress conditions showed that abiotic stresses contributed to more severe yield failure caused by RKN (Kreye et al., 2009). Furthermore, Masutomi et al. (2009) used 18 general circulation models to estimate the yield loss of rice in agro-ecological zones of Asia based on climatic projections and concluded that rice yield would decrease by 8% in 2050, most of this yield reduction to warmer winters would be the effects of weeds, pests and diseases.
1.2.2 Plant responses to abiotic stresses Being sessile, plants have evolved numerous mechanisms in response to abiotic stresses. Many strategies that plants implement in response to abiotic stresses have been
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documented. These strategies include avoidance, adaptation, and tolerance (Shinozaki and Yamaguchi-Shinozaki, 2007; Agarwal et al., 2013). In avoidance, some plant species escape stress by completing their life cycles before the onset of stresses (Hasanuzzamman et al., 2013; Pierik and Testerink, 2014). In adaptation, plants exhibit protective mechanisms such as stomatal closure, cuticular wax formation, sink/source allocation adjustment, and changed root architecture to prevent the effects of stress. Some plant species retain functions during stress together with employ a number of mechanisms including osmotic adjustment, osmoprotection, antioxidance and scavenger for tolerance to stress (Chaves et al., 2003). Stress tolerance permits plants, such as xerophytic vegetation, to withstand stress as well as employ a number of protective mechanisms for promoting survival and rapid recovery with full metabolic functions upon return of favourable conditions. However, tolerance strategy is limited to crop species (Bodner et al., 2015). These responses are the consequences of complex gene regulation, biochemical, and physiological changes.
1.2.2.1 Gene regulation in abiotic stress responses Plant gene regulation during plant responses to abiotic stresses is extremely complex. Many stress-inducible genes have been identified and their functions have been found to vary during different stages of development. Plant genes induced by abiotic stresses have been categorised into two groups: regulatory genes and single- function genes. It has been shown that there is a high degree of similarity, at the cellular level, during plant responses to salinity and drought stress and to some extent cold stress (Sairam and Tyagi, 2004). Agarwal et al. (2013) described gene regulation networks involved in establishing salinity and drought stress tolerance as shown in Figure 1.1.
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Figure 1.1 Plant gene regulation in response to salt and drought stress (Agarwal et al., 2013)
According to Agarwal et al. (2013), salinity and/or drought stress are perceived by signalling sensor molecules and sent to the cells, where the stress signal is amplified by signal transduction pathways. Histidine kinases (HKs) and receptor-like kinases (RLKs) are two important protein families involved in stress perception. Calcium sensing (Ca++) is one of the most well described and most complex signal sensing cascades; and the mitogen-activated protein (MAP) kinase cascade is one mechanism plants use to translate the external stimuli into cellular responses. Upon detection of the signal, transcription factors such as AREB/ABF, bZIP, CBF/DREB, MYC/MYB, NAC, and WRKY are triggered. These transcription factors play a pivotal role in developing abiotic stress tolerance in plants. They interact with promoters of downstream genes and regulate the expression of these genes. Genes activated by these transcription factors will
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subsequently produce many classes of molecules, which may help mitigate damage by these stresses. These stress-involved functional proteins include ROS scavengers, osmoprotectants, ion transporters, chaperones, photosynthesis and fatty acid metabolism enzymes, proteinase inhibitors, late embryogenic-abundant (LEA) proteins, and heat shock proteins (HSPs) that protect plant cells and macromolecules from damage and ultimately lead to tolerance. In addition, many other genes encoding transcription factors, protein kinases and phosphatases involved in signal transduction pathways are induced in plant cells under stress conditions (Bhatnagar-Mathur et al., 2008). As a consequence, genes induced by a specific stress are considered to function in that stress response (Swindell, 2006; Shinozaki and Yamaguchi-Shinozaki, 2007; Ni et al., 2009). Genes involved in stress perception, signal transduction, and immediate protection are activated early in the initial stages of stresses. While those induced later are likely responsible for stress adaptive establishment such as homeostasis and recovery (Swindell, 2006; Mishra et al., 2016; Zhu, 2016).
Stress perception has been found to be specific for certain stress factors and to be unique for some stress combinations (Mittler, 2006). However, drought, salt, and cold stresses (termed osmotic stresses) have been shown to share several common signal transduction pathways that further regulate the expression of similar gene sets (Xiong and Zhu, 2002; Fujita et al., 2006; Barnabas et al., 2008; Fujii and Zhu, 2012; Mishra et al., 2016). In fact, the genes induced by drought stress were found to be identical to those induced by salinity stress and some of those induced by cold stress (Qureshi et al., 2007). Studies have suggested that osmotic stresses are transmitted through at least two pathways: ABA-dependent and ABA-independent pathways. The existence of cross-talk or convergence between these signalling pathways has also been demonstrated (Fujita et al., 2006; Baena-Gonzalez and Sheen, 2008; Huang et al., 2012). As a result, there is an overlap in the expression pattern of stress-responsive genes after cold, drought, high salt, and ABA application. For example, analysis of cDNA harvested from rice exposed to cold, drought, high-salinity stresses and ABA application by cDNA microarray followed by RNA gel blot indicated that (1) 40% of drought-or high salinity-inducible genes were also inducible by cold and (2) more than 98% of the high salinity- and 100% of ABA inducible genes were induced by drought stress (Rabbani and Maruyama, 2003). The convergent point among abiotic stress signalling pathways was thought to be a MAP kinase cascade because it connects
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diverse sensors to a broad range of cellular responses to abiotic stress (Fujita et al., 2006; Huang et al., 2012). For instance, an Arabidopsis gene, AtMPK3, was found to be induced at the mRNA level by drought, cold, high salinity and mechanical stresses that regulate the expression of many stress-responsive genes including pathogen defense genes (Mizuguchi et al., 1996). Perhaps, it is this convergent point among abiotic stress signalling pathways that enables plants to efficiently respond and adapt to multiple stresses during their life cycles in their changing living environments. Regarding to functions of stress-inducible gene products in initial stress response and in establishing plant stress tolerance together with the existence of convergent points among various stresses, targeting genes in stress signalling pathways for engineering plants with enhanced abiotic stress tolerance appears to be the most promising approach (Mittler and Blumwald, 2010). These reports suggest that it is feasible to generate crop varieties that are tolerant to multiple abiotic stresses.
1.2.2.2 Biochemical changes in abiotic stress responses affect crop quality Upon detection of abiotic stress, numerous biochemical changes occur in plant tissues. Initial abiotic stresses generate ROS that in turn cause oxidation of membrane lipids, proteins, and nucleic acids in plant cells and subsequently cause biochemical changes. In the development of stress tolerance, numerous biochemical reactions occur that alter the chemical composition of plant cells. With regard to crop plants, these chemical alterations affect the quality of harvested products. Observed biochemical changes affecting food quality are available in the literature (Nagarajan and Nagarajan, 2010; Wang and Frei, 2011; Halford et al., 2015); and several major changes related to the above-mentioned gene expression network are summarised herein as examples. Under stress conditions, a higher protein concentration in harvested parts of crops has been observed as a result of increased expression of various genes. Similarly, antioxidants such as phenol, ascorbate, carotenoids and tocopherol have been recorded to be produced at higher levels for detoxifying ROS during stress responses. In the case of carbohydrates, changes in chemical composition vary depending on the plant tissues. Grain crops experiencing abiotic stress, especially during drought and heat stress, reduced grain starch concentrations and most possibly due to reduced activity of the enzyme starch synthase. In tuber crops such as potato, cassava, and sweet potato, decreases in starch concentration due to inhibition of starch synthase activity and increases in concentration of maltose due to higher activity of β-amylase, which
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decomposes starch to maltose, have been observed. Sugar concentration in fruit and vegetable crops was not consistent across crops. Sugars and sugar alcohol such as mannitol and sorbitol play an important role in abiotic stress tolerance and are accumulated during stress responses by conversion from other sugars such as fructose- 6-phosphate and glucose by stress induced enzymes Therefore, changing concentration of certain forms of sugars under stress may be the result of the conversion from one form to another. Leaf senescence as a result of programmed cell death induced by ROS, together with a reduction of chlorophyll content and leaf water content negatively affects physical and sensory traits of vegetables. Alterations in fatty acid composition of oil crops under stress have also been recorded with the general trend of increased and decreased proportions of saturated fatty acids and (poly) unsaturated fatty acids, respectively. These are believed to be due to changing activities of enzymes involved in lipid synthesis and conversion (Nagarajan and Nagarajan, 2010). Changes in membrane lipid composition by increased unsaturated fatty acids were found in chilling temperature adapted cells and transgenic tobacco plants with increased levels of unsaturated fatty acids have shown improved in chilling tolerance (Bhatnagar-Mathur et al., 2008).
In general, from initial responses to adaptation establishment in crop plants undergoing abiotic stresses, various sets of stress-responsive genes are activated and resulted in the changes to biochemical profiles of harvested parts. Many biochemical substances such as phytochemicals, vitamins, antioxidants, proteins, sugars, free amino acids, oils, and aroma volatiles are important determinants for food quality and safety. As analysed in the above-mentioned studies, some of the changes including increased antioxidants, proteins, and monounsaturated fatty acids were found to be beneficial for food quality. However, most of the changes were identified to have negative impacts on food quality and food safety.
1.2.2.3 Physiological adaptation Stresses including drought, salinity, and cold inhibit plant growth by primarily osmotic stress and decreasing cell turgor leading to the arrestment of shoot growth, cell division and expansion. To counteract the effects of osmotic stress and maintain cell turgor, adaptive plants use efficient osmotic adjustment strategies. Numerous physiological mechanisms, as a result of osmotic adjustments, are significantly advantageous for drought and salinity stress adaptation of plants include maintaining cell
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stability, accumulating antioxidants and compatible solutes, effectively using water, increasing soil water extraction by changing root architecture, maintaining higher leaf relative water contents, controlling stomatal closure to reduce water loss (Manavalan and Nguyen, 2012; Shabala and Munns, 2012). Additional beneficial physiological mechanisms that reduce sodium ion toxicity caused by salinity stress include exclusion of Na+ uptake by the root, sequestration of Na+ at intracellular and extracellular levels, retention of K+ in the cytosol and uptake of Na+ to the vacuole (Shabala and Munns, 2012). As a consequence of adjustments to stresses, various physiological, anatomical, and morphological changes have been observed and considered as essential features in plant adaptation to these stresses. Cell wall and leaf folding to avoid desiccation have been found to be important and novel features in resurrection plants (Mundree et al., 2002; Ingle et al., 2007; Karbaschi et al., 2016). Similarly, some heat-tolerant wheat cultivars implement leaf rolling to prevent structural and functional damage of the pigment antenna complexes, the reaction centre of photosynthetic system (PS) II, and the electron transport between PSII and PSI (Sarieva et al., 2010). Changes of root architecture by increasing branch root growth that enhance total root surface area for better access to water and nutrients have been identified as desirable traits of adaptive plants to both salinity and drought stresses (Manavalan and Nguyen, 2012; Shabala and Munns, 2012; Pierik and Testerink, 2014). For example, studies on how maize roots adjusted to optimize water and nitrogen uptake in different soil environments revealed a number of root architecture alterations contributing to effective water and nutrients uptake or avoidance of toxicity in their living environments (Lynch, 2013). The modulations upon stresses on the primary root diameter, the growth angles of seminal roots, the numbers of lateral roots, the length of root hairs, the branching ability of crown roots, the abundance of cortical aerenchym, the size of cortical cells resulted in a deeper or shallower root system to match the water and nutrient conditions in the soil. Leaf modifications have been found to facilitate protection of photosynthetic machinery, preventing toxicity of ionic and oxidative radicals, and reducing leaf transpiration, light and UV irradiation damage. Salinity and drought adapted genotypes can be identified by several morphological features of leaves such as smaller and thicker leaves, leaf surface covered by epicuticular wax, anthocyanin pigmentation, glaucous layer, or pubescent layer. Salt glands and bladders were found in leaves of many halophytes, the salt tolerant plants (Manavalan and Nguyen, 2012; Shabala and Munns, 2012; Karbaschi et al., 2016).
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The above-mentioned plant responses to abiotic stresses showed that the response is complex and depends on the species and genotype, the type of stresses, the length and severity of stresses, the age and stage of plant development, the organ and cell type, the subcellular compartment, gene and its mode of action. Understanding the full picture of how plants respond to abiotic stress will enable the determination of key processes that contribute to crop yield under stress. This knowledge will be valuable for plant breeding towards improving crop yield stability under changing climatic conditions.
1.2.3 Abiotic stress, world food security, and molecular breeding Abiotic stresses negatively affect plant growth, reduce crop productivity, food quality, and impact global food security. It has been shown that over 85% of crop loss is due to environmental stresses (USDA, 2017). For cereal crops, the most important staple food of most human societies, even a mild abiotic stress without affecting survival of the vegetative parts at a short period before anthesis could irreversibly affect grain yield (Dolferus et al., 2011). Wang and Frei (2011) extensively analysed the impact of the five most common environmental stresses on seven parameters used for evaluating food quality. Their results showed that only two parameters, levels of protein and antioxidants, were positively affected while five parameters including lipids, non-structural carbohydrates, minerals, feed value and sensory traits were negatively affected; the net effects were also negative. Moreover, in most of the future climate-change projections, an increase in aridity of many areas in the globe is the major concern for sustainability of global agriculture. It is predicted that about 7% of total land area and 20% of the irrigated agriculture land is affected by soil salinity (Agarwal et al., 2013). The impacts of abiotic stresses undoubtedly impose threats for global agricultural sustainability and food security. Future increases in the human population and living standards combined with soil water deficits and salinisation as a result of climate changes continuously threaten global agricultural sustainability and food security. These remain constraints for plant breeders towards ensuring food security for future populations. Enhancing plant resilience to the effects of abiotic stresses shows great potential as the most effective target for improved agricultural sustainability (Newton et al., 2011).
Many attempts have been made by plant breeders worldwide to improve abiotic stress tolerance. Conventional breeding has been extensively used with limited success (Bhatnagar-Mathur et al., 2008; Gosal et al., 2009; Ashraf, 2010; Agarwal et al., 2013; Shahbaz and Ashraf, 2013). In fact, although a number of cereal crop cultivars tolerant to
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drought developed through conventional breeding have been commercialised, the effectiveness is very low (Ashraf, 2010). A number of reasons accounting for the limited success of this breeding method include (1) reliance on the existence of naturally tolerant cultivars among species because of the sexual barrier between species, (2) the procedure is time-consuming, cost-and labour-intensive, and (3) the transference of unwanted linked traits along with desirable traits. Marker-assisted breeding (MAB), a procedure combining conventional breeding with DNA markers, has also been applied for improving abiotic stress tolerance in crops with better results. This process is still reliant upon conventional breeding for producing new cultivars, however the efficiency has been significantly enhanced as using DNA markers for selection reduces the length of breeding cycles (Cominelli et al., 2013). The combination of DNA markers in this breeding method have allowed high-throughput screening of germplasm for beneficial traits and the identification of quantitative trait loci (QTLs) of abiotic tolerant traits. A number of QTLs for abiotic stress tolerance have been identified in important crops including QTLs for salinity stress tolerance in rice (Shahbaz and Ashraf, 2013), QTLs for drought tolerance in maize, barley, cotton, sorghum, and rice (Ashraf, 2010). However, due to a lack of understanding of the key genes underlying the QTLs, the undesirable agronomic traits involved in QTLs from donor parents are also brought along with stress tolerance (Bhatnagar-Mathur et al., 2008). While MAB has still been widely used, the development of enhanced abiotic stress tolerant crops by genetic engineering approaches has recently gained attention. These approaches overcome the limitations of the two previously mentioned methods because it uses genes from tolerant species, across the genetic barrier, and only transfers the desirable traits into pre-selected elite cultivars. During the last several decades, many genes from different sources have been transferred to a variety of crop species to develop abiotic stress tolerant lines. These genes can be categorized into two groups: structural and regulatory genes (Gosal et al., 2009; Agarwal et al., 2013). Currently, transgenic crop lines are being evaluated under laboratory, greenhouse and field conditions. For example, maize plants transformed with a nuclear factor ZmNF-YB2 improved yields under drought stress at both greenhouse and field conditions (Nelson et al., 2007). Similarly, Shi et al. (2015) used ZmARGOS8, a regulator of ethylene signal transduction, to overexpress in maize plant and demonstrated that ZmARGOS8- overexpressing maize plants increased grain yield under drought stress conditions without reduction of grain yield under unstressed conditions. Furthermore, Shi et al. (2017) generated the maize ARGOS8 variants using genome editing technology, the CRISPR-
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Cas9. The maize lines carrying ARGOS8 genome-edited variants were tested in the field of eight locations across the United State with different environmental conditions. The results showed that maize lines carrying ARGOS8 genome-edited variants improved grain yield under field drought stress conditions and had no yield loss under well-water conditions. There are still some considerations on the types of genes that should be used for this method. Genetic engineering is currently thought to hold the greatest potential in developing enhanced abiotic stress tolerance crops. It is believed that the gaps between future required food and what conventional breeding can provide will be filled by achievements of genetic engineering technology in a sustainable and responsible manner (Oliver, 2014). To fulfil the task of sustainable future food demand, the future crops need to maintain high yield under stressful environmental conditions and unpredictable changing climates. It is likely that crops of the future need to be stacked with multiple desired traits for higher yielding while mitigate the effects of abiotic stresses and complex pathogenesis incidences triggered by changing climates. Therefore, combining multiple desired traits into existing nutritive value and high yielding varieties through genetic engineering appears to be the most appropriate approach to generate such crops. While multigene manipulation remains the technical hurdles impeding the combination of numerous genes into single selective genotype (Halpin, 2005), using single gene of upstream regulators to activate the balanced adaptive response that will enhance plant tolerance to different stresses has been considered the most effective strategy to achieve multiple desired traits combined in future crop generation (Mittler and Blumwald, 2010; Cominelli et al., 2013).
1.3 OSMOTIN AND OLP: THE STRESS-RESPONSIVE MULTIFUNCTIONAL PROTEINS
1.3.1 Osmotins and OLPs, the members of pathogenesis-related proteins Osmotin protein was first isolated and characterised in tobacco cells cv. Wisconsin 38 adapted to grow in vitro in a medium containing high concentrations of NaCl or polyethylene glycol (PEG) (Singh et al., 1985). This 26 kDa protein was suggested to be involved in the adaptation to NaCl and water stress of tobacco cells. When cultured for long durations in a medium containing high levels of NaCl, tobacco cells synthesized and accumulated osmotin up to 12% of total cellular protein (Singh et al., 1987). Since these initial experiments, genes encoding osmotin and OLPs have been identified in many other plants such as petunia, Petunia hybrida (Kim et al.,
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2002), pepper, Capsicum annuum (Hong et al., 2004), soybean, Glycine max (Onishi et al., 2006) black nightshade, Solanum nigrum (Jami et al., 2007), strawberry, Fragaria x ananassa (Zhang and Shih, 2007), ginger, Zingiber officinale (Prasath et al., 2011), and black pepper, Piper colubrinum (Mani and Manjula, 2010), to name a few. Although the accumulation of osmotin in plant cells has been found to be related to osmotic stress, its antifungal activity and its sequence homology with thaumatin, a pathogenesis-related protein, have reclassified osmotin as a pathogenesis-related protein group 5 (PR-5) (Singh et al., 1987; Yen et al., 1994b; Zhu et al., 1995; Husani and Rafiqi, 2012). Based on their isoelectric point (pI), PR-5 proteins are divided into three subclasses, osmotin proteins were in the basic subclass and OLPs in the neutral subclass (Koiwa et al., 1994).
Tobacco osmotin can exist in two forms; an aqueous soluble form (osmotin-I) and a detergent soluble form (osmotin-II). Characterisation of tobacco osmotin showed slight differences in their pI (7.8, and 8.2) and molecular weight of the two forms, the N-terminal sequences however were identical (Singh et al., 1987). Tobacco osmotin is synthesized as a pre-protein with a molecular weight of 26 kDa, the mature form has a 24 kDa (Singh et al., 1989). The N-terminal sequence and an alanine in the cleavage site of N-terminus are conserved among PR5 proteins (Min et al., 2004). This N-terminal signal peptide is responsible for protein transport across endoplasmic reticulum (ER) membrane. Like other PR5 proteins, osmotin was thought to be synthesized as precursor with an N-terminus, after sorting in ER the signal peptide is cleaved off and the mature form has slightly smaller weight (Singh et al., 1989).
Crystal structure analysis of tobacco osmotin revealed a noncrystallographic dimer in the asymmetric unit; its two monomers were slightly different in tertiary structure; and its folding was similar to that of thaumatin and other PR proteins (Min et al., 2004) (Figure 1.2). The comparison of the three-dimensional structure of tobacco osmotin with other osmotin and OLPs showed that the osmotins comprise three conserved domains and one large acidic cleft. Domain I consists of an 11-strand flattened β-sandwich that forms the compact core of the molecule. Domain II consists of several loops extending from domain I that is stabilized by four disulfide bonds. Domain III consisted of a small loop with two disulfide bonds. The tertiary structures of osmotin, thaumatin, zeamatin, and antifungal PR-5 showed high homology (Fig 1.2). Small differences however were observed in domain II and the distribution of surface charge
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(Anzlovar and Dermastia, 2003). It is widely accepted that this acidic cleft possesses amino acid residues acting as catalytic pair capable of glucan hydrolysis and this structural feature is required for antifungal activity of osmotins and other PR5 proteins (Mani et al., 2012).
Figure 1.2 Structure homology of osmotin, thaumatin and antifungal PR-5 (Min et al., 2004). Surface representation of the clefts of osmotin (A), PR-5d (B), zeamatin (C) and thaumatin (D) depicting the electrostatic potential with a colour scale that varies from blue to red, representing positive and negative potential, respectively.
The presence of alanine at the cleavage site of N-terminal sequence and 16 cysteine residues distributed throughout the protein sequence and linked by disulfide bridge formation was considered the conserved features of PR5 protein (Min et al., 2004). The 8 disulfide bridges formed by these conserved cysteines were found to be responsible for stability and correct folding of the molecule, supporting its resistance to protease degradation and its stability under extreme thermal and pH conditions (Liu et al., 2010). In addition, the presence of acidic clefts, as a common feature, in the PR5 protein structures was found to be essential for their antifungal activities against diverse fungal pathogens (Liu et al., 2010). 1.3.2 Osmotins and OLPs play roles in multi-stress responses Osmotin and OLP genes are reported to be induced by at least ten hormonal, pathogenesis and environmental stimuli (Kononowicz et al., 1992; LaRosa et al., 1992; Raghothama et al., 1993; Zhu et al., 1995). These stimuli included ABA, auxin, ethylene, drought, salinity, cold, UV light, tobacco mosaic virus infection, fungal infection, and wounding. Expression profiling studies have demonstrated the involvement of osmotin in both osmotic and pathogenic defence functions. However, the abundance of mRNA did not always reflect the levels of protein accumulation. In tobacco cells, the osmotin mRNA in cells adapted to salt are approximately 15 fold higher than the non-adapted cells and present at a constant level. The mRNA was
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decreased in exponential phase of growth and increased in stationary phase in non- adapted cells. The osmotin protein was synthesized and accumulated in NaCl-adapted cells; in non-adapted cells the protein was synthesized but not accumulated (LaRosa et al., 1992). In tobacco plants, the protein accumulated to substantial amounts only treated with ethylene, fungal infection or long-term exposed to salinity or water deficits. The levels of osmotin accumulation could go up to 12% total cellular protein when cultured for long duration in high-NaCl containing medium (Singh et al., 1987).
Studies on osmotin promoters have also shown activity in response to a number of stress factors. The promoter region of a tobacco OLP contains two AGCCGCC sequences responsible for ethylene-induced expression that are common in PR5 proteins (Sato et al., 1996). Additionally, the tobacco osmotin promoter has three elements specifically interacting with nuclear factors (Liu et al., 1995) and contains several sequences that are highly similar to ABRE, as-1 and E-8 cis element sequences (Raghothama et al., 1993) or OLP from Curcuma amada had the GT-1 box and TGTCA element (Prasath et al., 2011), which are typical for response to osmotic stresses. Subsequent analysis of the promoter sequences of Arabidopsis and rice in thaumatin-like protein (TLP) and OLP genes showed that most OLP genes of Arabidopsis contain the binding elements associated with fungal response while these binding elements are absent in all OLP genes of rice (Dehimi et al., 2012). These results have suggested the involvement of osmotins and OLPs in both abiotic and biotic responses of plants and that investigation on the promoter together with the coding sequence may provide more information supporting the functions of certain osmotin and OLP genes.
Subcellular localisation of a protein is typically related to its functions (O'Rourke et al., 2005). Tobacco osmotin was found to target to vacuole inclusion bodies and this localisation was dictated by the presence of a C-terminal 20 amino acid peptide sequence (Singh et al., 1987). CaOsm1 from pepper, Capsicum annuum, was validated to localise to the plasma membrane (Choi et al., 2013). Other osmotins have been shown be secreted proteins and localise to other sub-cellular organelles. The presence of an N- terminal signal peptide was found to be essential for transport to endoplasmic reticulum, the first location within the secretion pathway (Sato et al., 1995). Depending on their either N- or C- signal peptides, osmotin or OLPs are predicted to localise in either extracellular matrix, plasma membrane, chloroplast, vacuole, or endoplasmic reticulum.
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The diverse subcellular localisations of plant osmotins and OLPs have demonstrated their multiple functions in response to various stress factors.
1.3.3 Expression of osmotins and OLPs enhanced plant tolerance to multiple stress factors Osmotin and OLP genes have been expressed in various crops. Some of these plants are presented in the Table 1.1. In these transgenic plants, osmotin and OLPs have consistently shown stress-responsive multifunctional roles that enhanced tolerance to salt, drought, and cold stress as well as improved bacterial and fungal resistance. These results have validated the functional involvements of osmotins and OLPs in plant response to abiotic and biotic stresses. The ability of osmotins to exhibit dual functions in a broad-range of abiotic and biotic stresses has indicated osmotins as potential candidate genes for resolving global problems in agriculture such as increasing severity of drought, salinity, low temperature and rising disease incidence.
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Table 1.1 Representatives of transgenic plants expressing plant osmotins and their phenotypes
Transgenic Source of Phenotype of transgenic plants References plant osmotin gene
Potato Tobacco Resistance to Phytophthora infestans (Liu et al., 1994)
Rice Rice Resistance to Rhizoctonia solani (Datta et al., 1999)
(D'Angei and Olive tree Tobacco Tolerance to cold stress Altamura, 2007)
(Husaini and Abdin, 2008a) Strawberry Tobacco Tolerance to salinity stress (Husaini and Abdin, 2008b)
Enhanced ability to produce roots in (Noori and Sokhansanj, Wheat Tobacco high 250 mM NaCl 2008)
Tobacco Cotton Tolerance to drought (Goel et al., 2010) (truncated)
Chilli (Subramanyam et al., Tobacco Tolerance to salinity stress pepper 2011)
Tolerance to drought and salinity, resistant to Fusarium pallidoroserum, Mulberry Tobacco (Das et al., 2011) Collectotrichum gloeosporioide and C. dematium
Tolerance to salinity stress and (Subramannyan et al., Soybean Tobacco resistance to fungal infection 2012)
Tomato Tobacco Tolerance to cold stress (4 oC) (Patade et al., 2013)
Resistance to Pseudomonas syringe Arabidopsis Pepper (Choi et al., 2013) and Hyaloferronosspra arabidopsidis
Improved drought tolerance and (Bhattacharya et al., Tea Tobacco quality 2014)
Carrot Tobacco Tolerance to drought (Annon et al., 2014)
Solanum Soybean Tolerance to drought (Weber et al., 2014) nignum
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1.3.4 Possible roles of osmotins and OLPs in response to abiotic and biotic stress The mechanisms by which osmotins mediate plant defence have not been fully understood. Similar to other PR-5 proteins, osmotin and OLP have antifungal properties against a broad range of plant pathogens. Tobacco osmotin is involved in antifungal responses by permeabilizing the plasma membrane and killing fungal cells (Abad et al., 1996). Inducing fungal membrane permeabilization was also shown as antifungal properties of CpOsm from Calotropis procera (Freitas et al., 2011). In addition, osmotins have been associated with the MAPK pathway in yeast to weaken yeast cells and resulted in rapid cell death (Ibeas et al., 1998) or to suppress the Ras2/cAMP stress response pathway causing apotosis in yeast (Narasimhan et al., 2001). The role of pepper osmotin (CaOsm1) in anti-microbial responses was demonstrated to be associated with the hypersensitive cell death response and oxidative signalling (Choi et al., 2013). The common constituents of fungal cell walls are glucan molecules, a type of polysaccharide. Typical structural features of osmotins are glucan binding and hydrolysation into simpler carbohydrates. Binding β-1,3-glucan was thought to be required for antifungal activities of osmotin (Prasath et al., 2011; Mani et al., 2012). A study on two osmotins with differential antifungal activity from Piper colubrium revealed that an internal deletion of 50 amino acid residues of the smaller one (PcOsm1), as compared to the PcOsm2, resulted in its structure distortion in domain III and reduced the number of active binding sites to β-1,3-glucan, 17 in PcOsm1 vs 21 in PcOsm2. Corresponding in vitro antifungal assay of these two osmotins revealed a significant difference in antifungal activity. While PcOsm1 showed undetectable antifungal activity, PcOsm2 exhibited strong antifungal activity (Mani et al., 2012). It has been proposed that osmotin requires cell wall components of fungal target for its functions (Abad et al., 1996). Phosphomanno proteins, the mannoproteins on the outer layer of yeast cell wall were determined to be a surface determinant for osmotin binding to the yeast cell wall (Yun et al., 1997). In addition, Narasimhan et al. (2005) provided evidence that PHO36, a seven transmembrane domain receptor-like polypeptide, which regulates lipid and phosphate metabolism, was an osmotin binding plasma membrane protein that is required for full sensitivity to osmotin in yeast. Although the antifungal activities of osmotin have been demonstrated, its receptors and factors facilitating osmotin binding on fungal cells have been determined and the mechanisms of its actions have been proposed, a full understanding of its mode of action is still unclear and needs to be further elucidated.
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There is evidence of osmotin binding cytokinin, a hormonal signalling molecule. The biological implementations of osmotins in hormonal signalling is yet to be elucidated but its binding to protein receptors has shown to affect ion flux, phosphorylation of regulatory proteins, transcription, translation, and secretion (Kobayashi et al., 2000). It has been proposed that binding to cytokinin may be a mechanism by which osmotin mediates plants resistance to bacteria. Many bacteria, such as Agrobacterium tumefaciens, modulate host plant activities to produce specific cytokinins. By binding to cytokinins, osmotin deactivates of cytokinins, which prevents the spreading of bacterial infection (Viktorova et al., 2012). Thus, binding hormonal signalling molecules may be involved in host defence mechanism of osmotin. Diverse functions of osmotin have been exhibited in response to abiotic stresses. Tobacco osmotin found to be associated with salt adaptation and localised in the vacuole together with an OLP identified from the intercellular space of halophyte led to the suggestion that osmotin is involved in salt tolerance mechanisms of plants by reducing the build-up of Na+ ion in the cytoplasm and the uptake of that ion into the cell or acting as Na+/H+ antiporter (Singh et al., 1987; Yen et al., 1994b). Binding and hydrolysing glucan, particularly β-1,3- and β-1,4-glucan may be one of the mechanisms of osmotin contributing to abiotic stress tolerance in plants. It has been known that small sugar molecules can act as osmolytes and contribute to maintaining cell turgor under osmotic stress and/or play roles in organelle membrane formation, chloroplast protection under drought (Dway and Smille, 1971; Satoh et al., 1976; Lee et al., 2003). β-1,3-glucan is a component of plant cell wall and β-1,4-glucan is available in cytoplasm. Thus, osmotin may generate osmolytes through β-1,3- and β-1,4-glucanase hydrolysing activities for enhancing abiotic stress tolerance in plants. However, a direct evidence of plant cell wall β-1,3-glucan binding to osmotin is still lacking and need to be further exploited. The performance of plants expressing osmotin suggested its roles in signalling pathway. Programmed cell death (PCD) induction is one of the features related to cold adaptation of olive trees. In transgenic olive trees, osmotin was proven to induce PCD by blocking cold-induced calcium signalling and modifying cytoskeleton in response to cold stimuli (D'Angei and Altamura, 2007), suggested its relationship to calcium signalling cascade. Osmotin has shown enhanced cold tolerance in transgenic tomato by modulating transcript abundance and functional expression of stress-responsive genes (Patade et al., 2013); enhanced salt and drought stresses in other above-mentioned transgenic plants by upregulating the levels of several compatible osmolytes and ROS scavengers (Barthaker
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et al., 2001; Husaini and Abdin, 2008a; Parkhi et al., 2009; Das et al., 2011; Subramanyam et al., 2011; Subramannyan et al., 2012; Annon et al., 2014). These observations together with the similarity in molecular weight to transcription factors suggest that osmotin might regulate plant responses to abiotic stress by acting as either a transcription factor or cell signal modulator, or both (Abdin et al., 2011). However, osmotin does not have any DNA- binding motif to function as a transcription factor, the role in signalling pathways as a cell signal modulator has been strongly supported (Abdin et al., 2011; Viktorova et al., 2012; Kumar et al., 2015). Moreover, tobacco osmotin was proven to interact with AMP- activated protein kinase, a member of MAP kinase (Narasimhan et al., 2005). MAP kinase represents the key molecules catalysing the phosphotransfer reaction fundamental to most signalling and regulatory processes associated with enzyme activation, macro-molecule assembly, protein localisation and degradation in plant stress responses. In plants, MAPKs and calcium-dependent protein kinases (CDPKs) are in two major signal transduction pathways involved in plant response to various abiotic and biotic stresses. Some members of the two protein family were found working together to mediate crosstalk that triggers common stress responses such as ROS and hormonal signalling, accumulation of osmoprotectants and ROS scavengers, stomatal closure, osmotic adjustment leading to cross-tolerance to different stress conditions (Fujita et al., 2006; Wurzinger et al., 2011; Mohanta and Sinha, 2016). The roles of osmotins in plant response have shown to be associated with these two signalling pathways that helps osmotin-expressing plants tolerance to different abiotic and biotic stress factors. The intensive studies on osmotins discussed above have linked functions of osmotins and OLPs to a number of signalling crosstalk between abiotic and biotic stress responses. Although the mode of action of osmotins remains unclear, their multifunctional nature suggested that osmotins represent the key regulators mediating plant response to biotic and abiotic stresses. Even though osmotin was discovered early and identified as the most abundant protein in cultured tobacco cells adapted to osmotic stress (Singh et al., 1985), the difficulties in recombinant osmotin productions have prevented functional studies on the protein level and resulted in its poor elucidated mode of action (Viktorova et al., 2012). To date, only two published studies described the expression and purification of recombinant osmotins in microbial systems (Campos et al., 2008; Tzou et al., 2011). The poor availability of purified recombinant osmotin was demonstrated to be due to its toxicity and physical properties. Failure to produce recombinant tobacco osmotin in microbial systems in earlier studies was believed to be caused by osmotin antimicrobial
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activity that resulted in toxicity to osmotin expressing microbes (Tzou et al., 2011). In addition, osmotin protein structure has eight disulfide bonds and proper folding of these disulfide bonds is required for maintaining its functions. To minimize toxicity to bacterial cell, Campos et al (2008) and Tzou et al. (2011) targeted recombinant osmotin (Solanum nigrum OLP and truncated tobacco osmotin, respectively) accumulation in inclusion bodies and the system resulted in high accumulation of recombinant osmotin up to 30% of total protein extracts. However, targeting osmotins to inclusion bodies resulted in a majority of insoluble and aggregated form with misfolded protein present and the correct eight disulfide bonds in osmotin structure were not achieved. Further steps designed for denaturing and refolding these recombinant osmotins led to the highly pure osmotin with antifungal activities against a broad range of plant and human fungal pathogens. The protocols for expression and purification of recombinant osmotins in bacteria are now available but including the denaturation and refolding steps that have made it difficult for application in large scale. For proper folding of recombinant osmotins, the use of plant expression systems seem to be more feasible. However, the high hydrophobic nature of osmotins and the fact that many osmotins contain a membrane binding domain need to be taken into consideration when manipulating gene constructs for expressing in plants.
1.3.5 Osmotins and OLPs as potential candidate genes for enhancing multi- stress tolerance and for other uses in food industry Intensive studies and experimental data on biological systems have provided various practical evidences for the roles of osmotin and OLPs as master regulators in plant stress signalling that activates the acclimation response leading to enhancing plant tolerance to multiple abiotic and biotic stress factors. Hence, osmotin appears to be one of the potential candidate genes for developing multi-stress tolerant crops to suit the requirements for future crop generations, as discussed above. The expression of osmotin or OLP genes improved plant resistance to various fungal and bacterial pathogens. Recombinant osmotin maintained antifungal activities against a broad spectrum of fungi. These functions have made osmotin to be recommended for uses as a food preservative in food industry and as plant-derived fungicide in feed stock for organic meat industry (Liu et al., 2010; Viktorova et al., 2012; Kumar et al., 2015).
Besides, recent studies in mammalian system have shown that osmotin shares similar functions of human adiponectin, the hormone playing critical role in obesity, insulin resistance and atherosclerosis in human. Thus, osmotin was suggested to be
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used as a therapeutic component in replace of adiponectin for treatment of diseases related to adiponectin deficiency. Tobacco osmotin shares similarity in both structure and function with human adiponectin. Adiponectin functions by binding to its plasma membrane receptors called AdipoRs that further activates either 5’ adenosine monophosphate-activated protein kinase (AMPK) pathways in skeletal muscles or peroxisome proliferator activated receptor (PPARs) pathway in the liver to increase insulin sensitivity and decrease inflammation. Osmotin competes with adiponectin for binding to its receptors (Miele et al., 2011). Further experiment revealed that tobacco osmotin acted as an adiponectin agonist in type II diabetes and obesity and could be used as a therapeutic agent in replacement of adiponectin for type II diabetes and obesity treatment in human (Trivedi et al., 2012). Similarly, a study on a rat model system showed that both adiponectin and osmotin involved in neuroprotection against glutamate-induced synaptic dysfunction, excitotoxicity and neurodegeneration in developing brain, in which the role of osmotin as adiponectin agonist was confirmed. The study indicated the beneficial use of osmotin in the treatment of human neurodegenerative diseases (Shah et al., 2014). Adiponectin deficiency relates to some diseases such as insulin resistance found in obesity and diabetic type II patients, coronary artery disease, inflammation, and liver fibrosis. With the prevalence of diseases related to adiponectin deficits, the use of osmotin as pharmaceutical products appears to be feasible.
In summary, multifunctional properties of osmotin have made it a potential candidate for future applications in engineering crop plants for enhanced stress tolerance, in food and feed stock industries and as therapeutic agent in treatment various mammalian disorders related to adiponectin deficiency.
1.4 RESURRECTION PLANTS: A NOVEL SOURCE FOR STRESS- RESPONSIVE GENES
Resurrection plants belong to a small group of angiosperms that can tolerate extreme levels of dehydration down to 4% relative water content and are thought to possess unique mechanisms to cope with desiccation. Unlike their desiccation sensitive counterparts, resurrection plants have developed a distinctive strategy to withstand drought. Examples of their physiological responses to desiccation include (1) the loss of all free water in vegetative tissues then rehydration when water becomes available; (2) shading or dismantling photosynthetic machinery to reduce net
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photosynthetic rate during severe cellular water deficit by either leaf folding and anthocyanin accumulation or disassembling chloroplasts and chlorophyll on drying; (3) regulating protection mechanisms to minimize cell damage such as forming multiple vacuoles to maintain cell volume, cell wall folding to prevent mechanical damage, or replacing water by compatible solutes (Mundree et al., 2002). With respect to biochemical responses, resurrection plants have evolved a number of mechanisms against subcellular stresses as listed by Ingle et al. (2007). These include changes in cell wall composition, cytoplasmic packaging, and membrane lipid composition for preventing mechanical damage; increasing enzymatic activities in degradation of chlorophyll and elevating antioxidant production for reducing photosynthetic damages. The synthesis of compatible solutes such as sucrose, trehalose, LEA, and chaperone proteins for protecting the integrity of macromolecular is another strategy used by resurrection plants. Proteomic analysis of the resurrection plant Xerophyta viscosa during dehydration by Ingle et al. (2007) identified a number of dehydration- responsive proteins including antioxidants, RNA-binding proteins and photosynthesis- related proteins. These identified proteins provide evidence of the biochemical changes that occur during desiccation tolerance of this plant species. Therefore, resurrection plants represent both ideal model plants and a unique source for the identification of novel, functionally relevant, stress-associated genes and pathways (Mundree et al. 2002).
Primary studies on the Australian native resurrection grass that is a close relative of the economically important cereals such as rice, sorghum and maize, the T. loliiformis, have highlighted important strategies this plants used to withstand dehydration (Williams et al., 2015; Karbaschi et al., 2016). The study by Karbaschi et al. (2016) showed that this plant utilizes a number of physiological and structural mechanisms for rapid response to water deficit and quick recovery upon rehydration. These mechanisms include (1) leaf folding, cell wall folding and vacuole fragmenting quickly at the onset of dehydration that mitigate the mechanical damages to tissues; (2) shutting off the photosynthesis at early stage of dehydration for protecting the photosynthetic machinery and avoiding the subcellular damages caused by ROS laid down upon stress; and (3) accumulating of anthocyanin pigments and maintaining membrane integrity during drying resulted in the protection of tissues during drying and minimizing repairs needed upon rehydration. Williams et al. (2015) demonstrated that T. loliiformis modulates the trehalose metabolism
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to induce and maintain autophagy pathways that prevent senescence and program cell death, contributing to desiccation tolerance. These mechanisms suggested the potential of T. loliiformis for exploiting genes for utilisation in enhancement of stress-tolerance in crops, with special consideration in its close genetic relationship to important cereal crops.
With their unique ability to tolerate severe water deficit in drying vegetative tissues, resurrection plants represent a potentially rich source of genes conferring tolerance to abiotic stresses. A number of genes conferring dehydration tolerance have been isolated from resurrection plants including XvINO1encoding a myo-inositol 1- phosphate synthase (Lehner et al., 2008), XvSAP1 encoding a stress responsive protein (Garwe et al., 2003), and XvGolS encoding galatinol synthase enzyme responsible for the first catalytic step in raffinose family oligosaccharides (Peters et al., 2007). While the gene product of XvSAP1 was thought to play roles in stabilizing plasma membrane to prevent membrane damage, products of XvGolS and XvINO1 were proven to enhance carbohydrate accumulation during response to water deficit. The expression of XvSAP1 in Arabidopsis thaliana enhanced tolerance to salinity, osmotic, and high temperature stresses (Garwe et al., 2006). For effective utilisation of this potential genetic source for the generation of genetic engineered crops with enhanced abiotic stress tolerance, other genes involved in important abiotic stress responsive pathways need more investigation. If considering the combined tolerance to multiple abiotic and biotic stress factors, osmotin from resurrection plants is one of the most potential candidates for utilisation through genetic engineering due to increasing evidence supporting the role of osmotin as key regulators in response to abiotic and biotic stresses (as discussed in section 1.3.4).
1.5 RICE AS A TARGET FOR ENHANCING ABIOTIC STRESS TOLERANCE VIA TRANSGENIC APPROACH
1.5.1 Rice is an important staple food crop Rice is among the most important cereal crops and is the staple food for more than a half of the world’s population. More than 90% of world rice production has been produced and consumed in developing Asian countries that are experiencing a population boom. Prediction of future climate change has led to an estimation that affected rice culture areas will double at the end of this century (Jagadish et al., 2011), thus impacting the food security of many Asian regions (Lobell et al., 2008). Manavalan and Nguyen (2012) indicated that temperature increase, rising seas and changes in patterns of rainfall and its distribution under global climate changes are the main causes
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of substantial modifications in land and water resources for rice production and the productivity of rice crops grown in different parts of the world, resulting in a threat of global food security. Increasing rice production and productivity under such predicted climate conditions is a challenging task but imperative to feed the increasing population and to maintain world food security.
1.5.2 Rice is the model plant for monocots Rice has been considered to be the model plant for monocots for many reasons. Rice has the smallest genome size among cereal crops, estimated as 430 Mb. though small the rice genome is 3.7 times larger than the model plant, Arabidopsis thaliana. Its genome has high degrees of synteny among cereal genomes (Goff, 1999). In fact, rice has been a favourite crop for genetic studies due to a well-defined protocol for genetic transformation as well as widely distributed high density and physical maps (Shahbaz and Ashraf, 2013). The complete genome sequences of the two major sub-species of rice, indica and japonica, are now available (Londo et al., 2006) that have enabled the discovery of genes and molecular pathways associated with diverse agronomic traits, thus providing great opportunities for genetic improvements of this crop (Edwards and Batley, 2010; Bolger et al., 2014). Rice is familiar with most populations around the world because it is among the earliest domesticated crops, which is now cultivated globally (Londo et al., 2006). In addition, its short life cycle and the ease to be handled in laboratory conditions have made it a desirable crop for genetic studies. Many screening and phenotyping techniques as well as modern tools developed on rice (Singh et al., 2010; Zhang et al., 2014) have facilitated researches on rice. These advantages have made rice to be a model crop for monocots.
1.5.3 Rice is susceptible to abiotic stresses Among cereal crops, rice has been classified as a susceptible crop to major abiotic stresses such as drought, high salinity, heat, and cold. Based on the salinity threshold used to compare the salinity tolerance between species, rice is rated as a salt-sensitive crop with a threshold of 3 dSm-1 and a slope of 12% per dSm-1. This means that rice yield starts reducing when cultured in 30 mM NaCl and from that point, rice yield reduce 12% per 10 mM NaCl increasing of saturated soil extract (Sankar et al., 2011; Shabala and Munns, 2012). Differential effects by salinity were found at different developmental stages of rice plants, duration and severity of stress (Negrao et al., 2011). Rice germination stage is more tolerant to salt than seedling stage, and reproductive stage is
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the most susceptible phase. The mild stress at growth stage usually results in reducing photosynthesis and growth that lead to decreased yields. A long duration of exposure to even low salt concentration at 30 mM NaCl leads to reduced number of tillers per plant, number of spikelets per panicle, spikelet fertility, and grain weight and reduced grain production (Gay et al., 2009). Higher salt concentration leads to mature leaf death, and if the rate of leaf death overtakes the rate of new leaf initiation and expansion then the plant death occurs due to the lack of photosynthetic supply for further growth and development (Munns and Tester, 2008). During growth stage, exposure of rice plants to > 100 mM NaCl causes plant death before mature; but to < 50 mM NaCl delays panicle initiation and flowering, reduces pollen viability and results in poor seed setting. Reproductive stage is most susceptible to salt stress since ion toxicity affects pollen viability and high level of toxic ions can lead to sterility (Negrao et al., 2011).
Drought is the leading factor affecting global rice production and severe effects have been found in rainfed rice accounting for 45% of rice cultivation area (Babu, 2010). Rice has been found to be susceptible to drought stress throughout its life cycle but if stress occurs during flowering results in huge failure or complete yield loss (Swamy and Kumar, 2013). The effects of drought on rice production is much more serious when drought occurs in combination with heat stress (Barnabas et al., 2008; Dolferus et al., 2011; Rang et al., 2011; Powell et al., 2012). According to these authors, rice is sensitive to drought stress at the critical stage of flower development such as anthesis, pollination, and pollen germination. Drought stress during flowering together with heat stress (above 37 oC) at a short period can lead to complete yield loss because these combined stresses results in spikelet sterility. Drought brought about by recent changed climate conditions has affected rice production in almost all rice culture areas and caused tremendous loss, even in well-irrigated lands, and resulted in enormous social impacts (Breviariao and Genga, 2013). These severe impacts were evidenced by the 2002 drought in India and the 2004 drought in Thailand that affected 300 million Indian and 8 million Thai people, respectively (Mohanty et al., 2013).
Likewise, the “cold spell” or low temperature threshold (typically night temperature) for rice is 16 oC, considerably higher than other cereal crops. Under cold conditions, rice exhibits poor seedling establishment at the start of the season, resulting in delayed growth and massive grain losses at the end of the season when temperatures drop below 16 oC at night (Dolferus et al., 2013). If temperatures drop below 12 oC at
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the young microspore stage of rice pollen development, pollen sterility occurs resulting in maximum yield losses (Oliver et al., 2005; Powell et al., 2012). Cold stress is problematic for rice cultured in temperate or elevated regions and temperatures below cold spell can lead to yield reductions of over 40% (Dolferus et al., 2013).
The young microspore stage of pollen development of rice has been shown to be the most sensitive stage to a number of major abiotic stresses that account for a major grain losses. The growth stage of rice is not sensitive to abiotic stresses as that of the reproductive stage to most abiotic stresses, however, sensitivity to abiotic stress is evaluated based on yield reduction. Therefore, rice has been classified as an abiotic stress susceptible crop.
Being an important crop that provides staple food for a large part of world population, rice production must be maintained in a sustainable way to ensure the food supply for an increasing population. Its importance and abiotic stress susceptible features have attracted numerous research programs for improving productivity while mitigating stress effects. Intensive studies on rice genetic improvement have brought about various tools, protocols, techniques for rice transformation, phenotyping, and genome sequence readily for uses. Much information and knowledge of rice response to abiotic stresses have also been revealed. These make rice the best target for expressing foreign stress- responsive genes.
1.6 RECENT ADVANCES IN STUDYING FUNCTIONAL PROTEINS
Traditional methods for characterising a plant gene have relied mainly on primary DNA sequence and transcriptional expression profile. It is well known that biological functions are carried out mostly by proteins but RNA expression levels do not always correlate with protein expression levels. In addition, biological properties of a protein encoded by a given gene cannot be predicted based on its RNA expression profiles. It has been widely recognised that studying protein structures, functionalities, and protein- protein interactions will provide a direct way to characterise biological functions of a given gene (Hu et al., 2011). However, the laborious and time-consuming nature of traditional methods such as X-ray crystal analysis for protein structures and yeast two- hybrid systems for protein interactions, together with the shortage of detection systems have limited the functional studies of genes. In addition, the difficulties in solubilising, separating, and identifying membrane proteins have limited functional studies on
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membrane proteins (Tan et al., 2008). The recent innovation of bioinformatics and the development of modern technologies for studying biological functions have enabled researchers to mine data for protein functions, target binding predictions and structure- to-function relationships. Many newly-developed high-throughput tools provide opportunities to effectively unravel crucial questions related to protein functions and structures that were previously laborious, time-consuming or impossible. Likewise, recent advances in genetic manipulation have facilitated recombinant protein productions in various biological expression systems, which further make it possible to study gene functions at protein levels.
1.6.1 Bioinformatics tools The creation of bioinformatics tools such as 3-D protein modelling and sequence- or structure-based functional prediction has sped up gene characterisation and enabled precise predictions of biological functions of target genes in an evolutionary relationship manner, without the need of prior knowledge of gene identity. For example, to predict the function of a protein, researchers need to retrieve similar structures from huge protein databases and classify them into the same protein fold, which was a time-consuming process, but this process is now more efficient and more precise (Mirceva and Davcev, 2009). Computational tools can be used to discover new roles of genes according to their promoter architecture and co-expressed gene analyses. Dehimi et al. (2012) used this approach to demonstrate the multiple roles of TLP and OLP in biotic and abiotic stresses and recommended it as an effective means to discover unknown functions of genes. Various methods developed for protein structure prediction are now available and have made it possible for biologists without background in bioinformatics to access and investigate their genes of interest (Kelley and Sternberg, 2009; Roy et al., 2010; Jaroszewski et al., 2011). The quality and precision of these methods have been progressively assessed and improved for the best accuracy possible (Kryshtafovych and Fidelis, 2009; Schmidt et al., 2009; Zhang, 2009). In addition, many methods for determining protein properties such as subcellular localisation, ligand binding, protein- protein interactions and predicting active binding sites of protein are now accessible (Chen et al., 2007; Emanuelsson et al., 2007; Hernandez et al., 2009; Wass et al., 2010; Plasnas-Iglesias et al., 2013). Undoubtedly, these promising tools play a critical role in gene characterisation studies today.
Chapter 1: Introduction and Literature Review 29
1.6.2 Advances in genetic manipulation Unlike nucleic acids, proteins are prone to denature or degrade in standard buffer conditions and at ambient temperature; protein conformations change depending on the expressing systems; and so far proteins cannot be routinely amplified in artificial conditions using protein templates, reaction reagents, and amino acids like PCR- amplification-based for nucleic acid. These features have made it more challenging to study protein functions. The studies on functional proteins would not have been possible without the achievements of genetic manipulation and the availabilities of different expression vector systems. Besides binary vector systems that have been widely used for stably expressing foreign proteins in plants, many overexpression vector systems have been developed to facilitate the ability to easily express proteins of cloned genes and to enhance the protein expression levels of target genes required for functional analysis. For example, Gateway-compatible vectors have been developed to facilitate high-throughput cloning of target genes and have been demonstrated to be useful in studying protein localisation, protein-protein interactions, specificity of promoters, gene knockdown mutants, and protein production for affinity purification (Earley et al., 2006). Due to its features of efficient cloning and high sensitivity of fluorescent detection, Gateway vectors are increasingly used for studying subcellular localisation of proteins and testing the interactions of target protein with other fluorescently tagged proteins within living cells. Similarly, the pEAQ vectors have been designed to allow easy and quick production of recombinant proteins in plants (Peyret and Lomonossoff, 2013). Using pEAQ vectors allows cloning and expressing proteins of interest within several weeks that has made it the most suitable for agrobacterium infiltration and transient expression studies. The most advantages of pEAQ vector are the use of the Cowpea Mosaic Virus hypertranslational “CPMV-HT” that produces extremely high yield of recombinant proteins through enhancing high translational efficiency and the incorporation of P19 suppressor of gene silencing in the expression cassette that reduces the complicacy in sample preparation and maximizes expression efficiency. These distinct features have accelerated the utilisation of pEAQ in transient expression of recombinant proteins in plants. Another achievement that can be used to enhance protein production in plants is the incorporation of Lys-Asp-Glu-Leu (KDEL) peptide in the C- terminus of target protein. The KDEL retention peptide was discovered as a C-terminal signal peptide that makes proteins permanently reside in the lumen of the endoplasmic reticulum (ER) (Munro and Pelham, 1987). This signal peptide has been shown to be
30 Chapter 1: Introduction and Literature Review
essential for retention of transmembrane proteins in the ER by preventing them from secretion (Jackson et al., 1990). The KDEL peptide has been incorporated in a number of recombinant proteins expressed in plants and shown to significantly enhance the accumulation levels of recombinant proteins that primarily were cytoplasmic, secretion, or transmembrane proteins (Wandelt et al., 1992; Schouten et al., 1996). The accumulation level was reported up to 100 fold higher than control in leaf tissues of transgenic tobacco plants (Wandelt et al., 1992). It has been evidenced from these studies that the high accumulation levels of KDEL-tag proteins were the results of increasing protein stability, reducing exposure of proteins to proteases during translocation pathways, and increasing yield of protein extraction from ER as in the case of membrane proteins. In addition, the achievements in genetic manipulation have allowed to design a number of vector series for validating and visualizing the protein- protein interactions in living plant cells (Lee et al., 2008; Nishimura et al., 2015; Kamigaki et al., 2016). The progresses in genetic manipulation have facilitated studies on protein functions that have allowed to gain knowledge on protein mechanism and mode of action and have made it more convincible in explaining functions of a gene.
1.6.3 Functional protein microarrays Alternative to the high-throughput methodologies established for identifying protein-protein interactions, such as protein complex purification coupled with mass spectrometry analysis and the yeast two-hybrid system, functional protein microarray technology has recently emerged as a powerful approach for simultaneously studying thousands of proteins. A protein microarray (protein chip) is a solid surface on which thousands of different proteins are immobilized in discrete spatial locations, forming a high density protein dot matrix (Hu et al., 2011). To identify which proteins interact with a target plant protein, the gene is first fused with affinity and detecting tags and cloned; the recombinant protein will then be expressed in a suitable plant, extracted and purified; the purified recombinant protein will then be labeled and hybridised with a plant protein chip; an appropriate detection system will be applied to analyse interactions between target protein and known proteins in the chip. The applications of protein microarrays have enhanced efficiency for characterisation of protein-protein interactions, identification of relevant binding substrates for proteins under investigation and exploration of novel functions of known proteins (Popescu et al., 2007b; Fukao, 2011). Calcium sensor and MAP kinase are two major cascades in stress signalling and
Chapter 1: Introduction and Literature Review 31
transduction of plants. Using Arabidopsis protein microarrays has allowed researchers to screen binding targets and identify uncharacterised targets of Calmodulin (CaM) and Calmodulin-like (CML) proteins that unravel the unknown roles of CaMs/CMLs in calcium sensor network contributing to plant growth, development, and stress and defense responses (Popescu et al., 2007a). Similarly, a total of 570 MAPK phosphorylation substrates involved in MAP kinase network were revealed by one study using an Arabidopsis protein array (Popescu et al., 2009). Functional protein microarrays are now available and considered a valid tool for high-throughput characterisation of protein-protein interactions (Sutandy et al., 2013). Hu et al. (2011) stated that functional protein microarrays will soon become an indispensable tool in proteomics research and systems biology. In plant system, the commercial availability of Arabidopsis microarrays together with public-accessible progresses in functional and pathway analysis of Arabidopsis proteins allow the rapid identification of pathway and interactive protein partners of an under-studied plant protein. This system provides a mean to speed up functional protein studies.
1.6.4 Detection tools for protein-protein interactions in living cells Detection of protein interactions in living cells is of significant importance for studying protein-protein interactions because it allows the capture of the interactions that occur in a particular cell with a full complement of proteins present in the cell and the external stimuli that influence the cell. The visualisation and detection of protein-protein interaction in plant living cells is now eased by Bimolecular Fluorescence Complementation (BiFC) technique, in which the interaction of two non-fluorescence proteins, separately fused with N-terminus or C-terminus of a fluorescence molecule, is indicated by fluorescence emission (Kerppola, 2008) (Fig. 1.3 A). Even two protein complexes can be simultaneously detected in a single plant cell by BiFC using two coloured fluorescent complementary pairs (Kodama and Wada, 2009) (Figure. 1.3 B). Tsutsumi et al. (2009) used BiFC to study Ras proteins and successfully determined their spatio-temporal regulation in signalling. Ras proteins are monomeric GTPases that have a complex effectors and regulate a number of signal transduction cascades involved in cell growth, differentiation, survival and mortality. Application of BiFC in this study revealed the mechanism that Ras exploits different effectors via Ras-PI3K interaction, Ras subsequently regulates downstream signalling in the endosome. Likewise, a multicolour BiFC technique has been used to analyse the efficiencies of complex
32 Chapter 1: Introduction and Literature Review
formation between small subunits of the large family of cytoplasmic G protein (Dupre et al., 2006; Mervine et al., 2006). As compared with alternative methods for the visualisation of protein-protein interaction, including fluorescence resonance energy transfer (FRET), Kerppola (2008) indicated six advantages of using BiFC instead of FRET. BiFC method has become a standard approach for visualising protein interactions in living cells and has been applied in a variety of research applications during the last five years. There are still considerations in choosing fluorescent fragments for avoiding spontaneous association and for enhancing fluorescence intensity; in preparing an adequate control system for avoiding false positive; and in the quantitative evaluation of the efficiency of complex formation, many protocols and guidance for using BiFC are available (Hu et al., 2005; Kerppola, 2009, 2013). In addition, Identification of different fluorescence proteins and improvement of fluorescence intensity for BiFC use have been progressively carried out. Consequence, at least 15 fluorescence proteins have been developed for BiFC and some mutant versions of fluorescent proteins have improved intensity up to 8 fold as compared to their native versions (Komada and Hu, 2012). Its advantages and recent progress have made BiFC become a key technique that should be incorporated into studies on protein-protein interaction. These above-mentioned advances provide significant means to promote research on the identification, characterisation and validation of protein functions.
Chapter 1: Introduction and Literature Review 33
A
B
Figure 1.3 Principle of BiFC and multicolour BiFC analysis (Kerppola, 2009). A. Principle of BiFC: The red and blue rectangles represent putative interaction partners (A and B). They are fused to fragments of a fluorescent protein, represented by silver half- cylinders (YN and YC). If the proteins interact with each other, they can facilitate association of the fluorescent protein fragments to produce a fluorescent complex (green cylinder YN- YC). The image shows an example of a complex formed by nuclear proteins. B. Principle of Multicolar BiFC: Two alternative interaction partners (A and B) are fused to fragments of different fluorescent protein fragments (tinted grey half-cylinders). These fusions are co-expressed in cell with a shared interaction partner, Z, fused to a complementary fragment (grey half-cylinder). Complexes formed by A and Z can be distinguished from complexes formed by B and Z based on the difference in their fluorescence spectra. The image shows an example of the visualization of two protein complexes in the same cell, one nucleolar (cyan) and the other nucleoplasmic (yellow).
34 Chapter 1: Introduction and Literature Review
1.7 PROBLEM STATEMENT, GAPS, AIMS, AND OBJECTIVES
The current and the predicted changing climate scenarios could result in more prevalent of environmental stress factors such as drought, salinity, extreme temperature and excess UV radiation. These environmental factors have been identified as the key limiting factors in agricultural productivity and food quality (Lobell et al., 2008; Wang and Frei, 2011). With the projected future increasing human population, the global food production was estimated to be double by 2050 with a significant annual grain yield increase of 44 million metric tons will be need (Tester and Langridge, 2010). However, the massive increase agricultural production have been challenged by such environmental stress conditions together with the reduced agricultural land (due to urbanisation, industrialisation, and desertification brought about by climate change) and the declined available resources (Oliver, 2014). It is obvious that food security for future population is threatened. To meet the food demand (both quantity and quality) of future rising population, the challenges of improving crops production in unfavourable environmental conditions and limited agricultural resources need to be addressed. The current rate of crop improvement, mostly contributed by conventional breeding, was found to be far below the future rising food demand (Ray et al., 2013). Oliver (2014) indicated that the agricultural production gaps between future food demand and crop improvement brought by conventional breeding can be filled by the applications of genetically-modified organism (GMO) technologies, which offer more rapid crop improvement, novel genetic strategies for crop improvement and the ability to use genes from all sources regardless of origin. Besides, identifying the key factors for crop adaptation to adverse climate conditions could shape the severity of climate change impacts on food production (Lobell et al., 2008).
Plant adaptive response to environmental stress is a multigenic trait that involved a complex gene network. For more efficient use of GMO technologies in improving crop adaptation to environmental stresses, it is important to identify the master regulators of stress adaptation from the stress-tolerant species and engineer them into crop plants (Mittler and Blumwald, 2010; Cominelli et al., 2013). The Australian native resurrection plant T. loliiformis represents the ideal starting point for searching potential candidate genes for developing stress-tolerant crops, regarding the adaptive strategies this plant implements to cope with the environmental stresses (Section 1.4).
Chapter 1: Introduction and Literature Review 35
Among the functional and regulatory genes identified to be involved in plant stress response, plant osmotin holds great potential for enhancing stress tolerance in crops through genetic engineering approach, due to increasing evidence supporting the role of osmotin as key regulators in plant stress response (Husani and Rafiqi, 2012; Viktorova et al., 2012; Kumar et al., 2015).
Intensive studies conducted on osmotin have shown its potential for enhancing both abiotic and biotic stress tolerance in plants but the mechanisms by which osmotin mediates plants response to stress remains for further elucidation. Osmotin and OLP genes have been shown to be induced by a number of abiotic and biotic stresses and hormonal stimuli indicating their involvement in plant response to these factors (Section 1.3.2). Transgenic plants expressing osmotin and OLP genes have shown consistently enhanced tolerance to various abiotic stresses, bacterial and fungal pathogens (as discussed in Section 1.3), which indicate critical roles of osmotins and OLPs in promoting plant tolerance to abiotic and biotic stresses and the multifunction nature of the proteins. However, the direct evidence explaining stress response mechanisms of osmotins and OLPs such as stress-responsive pathways, their interactive protein partners, and their mode of action are still shortage in the literature. Regardless the early discovery of osmotins and a large number of studies designed to dissect the role of osmotins and OLPs in plant stress response, the difficulties in obtaining recombinant osmotins remain the obstacle for functional studies directly at protein levels. Recent advances in studying functional proteins (discussed in Section 1.6) would provide useful means for facilitating the discovery of osmotin functions and pathways. Likewise, comparative studies of osmotins from natural drought- tolerant species with those of drought-sensitive species would provide novel insights into molecular mechanisms required for adaptive response to stresses and shed the light for identifying unknown functions of osmotins.
In this study, an osmotin from the native Australian resurrection plant T. loliiformis (TlOsm), previously isolated from a drought-induced cDNA library of T. loliiformis, was molecularly characterised and functionally validated on transgenic plants in comparison with the two osmotin genes (OsOlp1_A and OsOlp1_I) from drought- tolerant (Apo) and -sensitive (IR64) cultivars of the stress sensitive crop, Oryza sativa (rice). Despites large numbers of osmotins and OLPs have been characterised from many plant species and numerous transgenic crops expressing osmotins and OLPs
36 Chapter 1: Introduction and Literature Review
have shown enhanced tolerance to abiotic and biotic stresses (Section 1.3), none of osmotins from a desiccation tolerant species such as the resurrection plant T. loliiformis has been characterised. Resurrection plants possess a unique ability to tolerate severe water deficit in vegetative tissues and represent a potentially rich source of genes conferring tolerance to abiotic stresses (Ingle et al. 2007; Karbaschi et al. 2016; Mundree et al. 2002; Williams et al. 2015). Even though a number of genes conferring dehydration tolerance have been isolated from other resurrection plants (Garwe et al. 2003; Garwe et al. 2006; Lehner et al. 2008; Peters et al. 2007), very little has been reported about the expression of these stress-responsive genes in crop species. A comparative drought responsive transcriptome analysis of the tolerant and susceptible rice genotypes (Apo vs IR64) identified two osmotin genes (OsOlp1-A and OsOlp1-I, respectively) that are only different in 10 amino acid of their encoded protein sequences but are differentially expressed in response to drought stress. Further analysis of these two proteins suggested that changes in amino acid residues on the functional sites of the proteins may account for their differential responses to drought of these two rice genotypes (unpublished, personal communication with S. Robin, TNAU-India). Therefore, the incorporation of two rice osmotin genes OsOlp1-A and OsOlp1-I into the study is necessary for comparison with TlOsm and to understand the mechanisms that these osmotins regulate abiotic stress responses in plants. In the field, crop plants are often exposed to multiple stresses either simultaneously or successively. Therefore, genes encoding osmotins are likely to be suitable candidates for the genetic enhancement of plants, with respect to multiple-stress tolerance. Understanding the molecular characteristics and functions of TlOsm in plant defense holds a great promise for the gene utilisation in improving crop tolerance to abiotic stresses through genetic engineering.
The overall aim of this research was to address a number of key questions that will improve our understanding of the roles of plant osmotin in general and TlOsm specifically:
1. Whether TlOsm plays a role in abiotic stress response? 2. How does TlOsm act during abiotic stress response? 3. Which stress responsive pathway is TlOsm involved in? 4. What is the role of TlOsm in abiotic stress responses in a crop species?
Chapter 1: Introduction and Literature Review 37
This overall aim was addressed through the following specific objectives:
Objective 1: Determining the molecular characteristics of TlOsm Objective 2: Generating transgenic plants constitutively expressing target osmotins and appropriate reporter gene. Objective 3: Investigating the roles of TlOsm, in comparision with OsOlp1_A and OsOlp1_I, in abiotic stress responses of transgenic rice plants. Objective 4: Identifying interactive protein partners of the TlOsm, OsOlp1_A, and OsOlp1_I and exploring stress responsive pathways involving these osmotins.
The general research outline and thesis presentation are shown in the Figure 1.4
Figure 1.4 General research outline and thesis presentation
38 Chapter 1: Introduction and Literature Review
Chapter 2: General Materials and Methods
This chapter describes the general materials and methods used throughout the entire research project. The materials include general chemicals and specialized reagents, Tripogon loliiformis, Oryza sativa, Nicotiana tabacum and Nicotiana benthamiana plants, bacteria, primers, backbone vectors, and common solutions and media in Section 2.1. Section 2.2 presents the general methods for gene construct cloning, E. coli transformation, Agrobacterium tumefaciens transformation, DNA and RNA extraction, purification and amplification. Specific methods relevant to particular objectives will be referred to Chapter 3, 4, 5 and 6.
2.1 MATERIALS
2.1.1 Source of general chemicals and specialized reagents All general laboratory reagents of analytical grade were obtained from Sigma- Alrich (USA), Merck Millipore (USA), Chem-supply (Australia), unless otherwise stated. Agarose used for gel electrophoresis was supplied by Roche (Australia). Restriction enzymes were supplied by Roche (Astralia) or New England Biolabs (Australia). DNA markers and PCR reaction mix were supplied by Promega (USA) and Invitrogen (USA). Miniprep plasmid extraction kits was supplied by Promega. Plant tissue culture media and phyto hormone were supplied by PhytoTech (USA). Plant DNA extraction kits and Plant RNA extraction kits were supplied by QiAgen (Netherlands). His Spintrap columns and protein G Mag sepherose Xtra were supplied by GE Healthcare Life Sciences. Ligation enzymes, LR recombination reaction, cDNA reverse transcription reaction and antibodies was purchased from Invitrogen. Protein chip ArabidopsisChip1 and plasmid pYL436 were purchased from Arabidopsis Resource center (ABRC-USA).
2.1.2 Plant materials 2.1.2.1 Plant materials for T. loliiformis mixed elicitor cDNA libraries Tripogon loliiformis plants were germinated from seeds originally colected from Charliville (GPS: 26o42’ S 146o15’ E) Queensland, Australia and propagated for generations in glasshouse. The plants were grown in a glasshouse under a 12 h
Chapter 2: General Materials and Methods 39
photoperiod (light intensity of 900 ±100 µmol m-2 s-1) with day/night temperature of 27 oC.
2.1.2.2 Plant materials for stable transformation Rice seeds (Oryza sativa L. spp Japonica cv. Nipponbare) previously provided by Yanco Agricultural Institude (NSW, Australia) and propagated in a glasshouse under a 12 h photoperiod with day/night temperature of 27 oC were used to generate calli for stable transformation.
Nicotiana tabacum plants were maintained in sterile closed tissue culture vessels with monthly sub-cultured and placed in growth chamber at 16 h photoperiod, 25 oC and moderate light. In vitro microcutting plants after 2-3 weeks sub-cultured in fresh medium were used to provide leaves for stable transformation.
2.1.2.3 Plant materials for transiently expression assays Nicotiana benthamiana plants were used for both producing recombinant osmotins and detecting protein-protein interactions in planta. The plants were germinated in 1.6-L pots with 3 plants/pot. They were grown under controlled conditions of 25 oC, light intensity of 900 ±100 µmol m-2 s-1, 65% relative humidity and 16 h photoperiod. Plants were ready for Agro-infiltration after 4-5 weeks.
2.1.3 Bacterial strains Escherichia coli (E. coli) strain XL-1-Blue was used for all general plasmid cloning, except for plasmid carrying the lethal ccdB gene. Agrobacterium tumefaciences strain LBA4404 was used for tobacco transformation and strain Agl1 was used for both rice stable transformation and transient expression assays in N. benthamiana. Except for the One Shot® ccdB Survival™ 2 T1R Competent Cells were supplied by Invitrogen (used for cloning plasmid carrying the lethal ccdB gene), other bacterial competent cells were readily available within the CTCB.
2.1.4 Oligodeoxyribonucleotide (Primers) All primers used for plasmid consruction and confirm the presence of the target genes in the plasmids in this chapter are shown in Table 2.1. Details of primers for characterisation of transgenic rice and tobacco and TlOsm expression in T. loliiformis refer to Chapter 4. All primers were synthesised by GeneWorks (Hindmarsh, South Australia). Primers were diluted to a concentration of 100 µM and working stocks of 10 µM were prepared for PCRs and 3.2 µM stocks were for sequencing.
40 Chapter 2: General Materials and Methods
Table 2.1 List of primers for plasmid cloning
Primer Product size set Primer name Sequence (5'-3') (bp) Aims
TlOsmBamHI F GGATCCATGGCGAGATTACGAGGGGCTG Amplify TlOsm and Nos terminator in the A1 1232 pCambia2300-TlOsm NosTerHindIII R AAGCTTCCCGATCTAGTAACATAGATGACA
UidA BamHI F GGATCCATGGTCCGTCCTGTAGA Amplify UidA gene and Nos terminator A2 2083 in the pCambia1300 NosTerHindIII R AAGCTTCCCGATCTAGTAACATAGATGACA
OsOsmApoBamHI F GGATCCATGGGATTAGACCAAGCTGC Amplify OsOlp1_A from 13ABRIKP- A3 836 OsOsmApo_pMK_RQ M13 R AACAGCTATGACCATG
OsOsmIR64BamHI F GGATCCATGGCTTCTGCCAAGCTG Amplify OsOlp1_I from 13ABRIKP- A4 836 OsOsmIR64_pMK_RQ M13 R AACAGCTATGACCATG
EYFPTopo F CACCATGGTGCCTAGCGTGACCAAGG Amplify EYFP gene with the Topo B1 838 overhang from pEarleyGate 101 EYFPTopo R TTAAGCGTAATCTGGAACATCG Amplify TlOsm with Topo overhang and TlOsmTopo F CACCATGGCGAGATTACGAGGGGCTG B2 943 no stop codon from pCambia 2300- TlOsmTopo R GTGCAGGGCACCAGCGAGCACGAG TlOsm Amplify TlOsm with Topo overhang and TlOsmTopo F CACCATGGCGAGATTACGAGGGGCTG B3 952 with the stop codon from pCambia 2300- TlOsmBstEII R GGTCACCTCAGTGCAGGCCACGAG TlOsm C1 2798 AttR1_AGEF ACCGGTACAAGTTTGTACAAAAAAGCTGAACG
Chapter 2: General Materials and Methods 41
Primer Product size set Primer name Sequence (5'-3') (bp) Aims Amplify fragment from AttR1 to IgG of pYL436 with KDEL signal sequence and AgeI and StuI sites for modifying IgG_KDEL_StuIR AGGCCTTCAGAGTTCATCCTTTACCGAGCTCGAATTCGCGTC pEAQ_HT Amplify OsOlp1_A without the stop OsOsmApoTopoF CACCATGGGATTAGACCAAGCTGC C2 745 codon from 13ABRIKP- OsOsmApoTopoR GTGGCAGAAGATGACCTTGAGCTC OsOsmApo_pMK_RQ Amplify OsOlp1_I without the stop OsOsmIR64TopoF CACCATGGCTTCTGCCAAGCTG C3 745 codon from 13ABRIKP- OsOsmApoTopoR GTGGCAGAAGATGACCTTGAGCTC OsOsmIR64_pMK_RQ AtCPK4_Topo F CACCATGGAGAAACCAAACCCTAGAAGAC Amplify AtCPK4 with Topo overhang D1 1507 and no stop codon from Arabidopsis AtCPK4_Topo R CTTTGGTGAATCATCAGATTTAGCAG thaliana cDNA
AtCPK5_Topo F CACCATGGGCAATTCTTGCCGTG Amplify AtCPK5 with Topo overhang D2 1672 and no stop codon from Arabidopsis AtCPK5_Topo R CGCGTCTCTCATGCTAATGTTTA thaliana cDNA
AtALDH7_TOPO F CACCATGGGTTCGGCGAACAACG Amplify AtALDH7B4 with Topo D3 1528 overhang and no stop codon from AtALDH7_TOPO R ACCGAAGTTAATTCCTTGCGCTAGAG Arabidopsis thaliana cDNA
AtMS1_TOPO F CACCATGGCTTCACACATTGTTGGATACC Amplify AtMS1 with Topo overhang and D4 2299 no stop codon from Arabidopsis thaliana AtMS1_TOPO R CTTGGCACTGGCGAGCTGGG cDNA
AtPER42_TOPO F CACCATGGGAGGCAAAGGTGTG Amplify AtPER42 with Topo overhang D5 994 and no stop codon from Arabidopsis AtPER42_TOPO R ATGGTTCTTGTTTGCGAGATTACATTG thaliana cDNA
42 Chapter 2: General Materials and Methods
2.1.5 Backbone vectors 2.1.5.1 Vector for primary cloning The pGEM®T Easy vector (Figure 2.1A) was used for primary amplification of the genes used for common cloning by restriction enzyme digestion and then ligation. The pENTR/D-TOPO® was used for primary cloning of genes for GatewayTM recombination cloning technology.
A B
Figure 2.1 Plasmid maps for primary cloning. A) pGEM®T Easy vector used for amplification of genes for common cloning and B) pENTR/D-TOPO® used as entry vector for GatewayTM recombination cloning technology.
2.1.5.2 Vector for cloning genes stably expressing in rice The pYC27 UidA vector (Figure 2.2) was used as a backbone plasmid for cloning the OsOlp1_A, OsOlp1_I, TlOsm, and UidA genes that were stably transformed into rice.
Chapter 2: General Materials and Methods 43
35S
SmaI (11955)
XmaI (11953) EcoRI (1)
ApaLI (11655) PstI (23) hptII Ubi promoter
ApaLI (11353) ApaLI (1319)
PstI (2014)
BamHI (2016) UidA pYC27 UidA ApaLI (2955) 12999 bp ApaLI (3280) NosT
ApaLI (8958) HindIII (4093)
ApaLI (8460)
Figure 2.2 Map of backbone vector used for cloning genes stably expressing in rice.
2.1.5.3 Destination vectors for cloning genes stably expressing in tobacco The vector pCE100, pCE101, and pCE104 (Figure 2.3) were previously modified from vector series pEaleyGate 100, 101, and 104, respectively. These vectors were used as destination vectors in GatewayTM recombination cloning to generate the vector control and EYFP-tagged TlOsm used for stable transformation of tobacco.
44 Chapter 2: General Materials and Methods
A lacZ promoter M13R CaMV35S promoter CaMV 35S promoter, duplicated aTTR1 Cm(R) Hyg(R)
CaMV 3'UTR CCDB left border aTTR2 pCE100 Octopine Synthase Terminator 12221 bp Kan(R) nos 3'UTR right border pBR322 origin of replication bom site from pBR322 pVS1-REP STA from pVS1
B M13R CaMV 35S promoter, duplicated lacZ promoter Hyg(R) CaMV35S promoter attR1 CaMV 3'UTR Cm(R) left border CCDB attR2 Kan(R) E-YFP pCE101 HindIII (3359) 13026 bp Octopine synthase terminator pBR322 origin of replication HindIII (4196) bom site from pBR322 nos 3'UTR right border
pVS1-REP STA from pVS1
M13R C CaMV 35S promoter, duplicated lacZ promoter Hyg(R) CaMV35S promoter EYFP CaMV 3'UTR attR1 left border Cm(R)
Kan(R) pCE104 ccdB 13077 bp aTTR2 pBR322 origin of replication Octopine Synthase Terminator
bom site from pBR322 nos 3'UTR right border
pVS1-REP STA from pVS1
Figure 2.3 Maps of destination vectors for cloning EYFP-tag TlOsm and VC. A) pCE100 used for the expression of EYFP control, B) pCE101 used for tagging EYFP at C- terminus of TlOsm, C) used for tagging EYFP at N-terminus of TlOsm
Chapter 2: General Materials and Methods 45
2.1.5.4 Destination vector for recombinant osmotin production The vector pEAQ-436 (Figure 2.4) was used as destination vector in gerarating plasmids for producing recombinant osmotins in N. benthamiana. This vector was modified from pYL436 and pEAQ-HT (Appendix A-Figure 2) by incoparating the AgeI and StuI restriction sites and KDEL sequence into the GatewayTM recombination site and the Tandem affinity purification (TAP) of pYL436, then inserting whole sequence within AgeI and StuI sites into backbone pEAQ-HT at AgeI and StuI sites.
ColE1 RB CaMV 35S promoter NPTIII C1 CPMV RNA-2 5'UTR
AgeI (1296) TrfA attR1 Cm(R) pE A Q -4 3 6 attR1-CmR-ccdB-attR2 GATEW AY cassette 12737 bp ccdB OriV attR2 9x myc tag LB 6x HIS tag protease 3C cleavage site NPTII 2x IgG binding domain KDEL
Stu I (4090) CPMV RNA-2 3'UTR C3 Nos Terminator 35S promoter P19 35S terminator
Figure 2.4 Map of destination vector used for recombinant osmotin production.
2.1.5.5 Destination vectors used for detecting protein-protein interaction in planta The pE3132 (Figure 2.5A) and pE3134 (Figure 2.5B) were used as destination vectors for cloning plasmids used in Bimolecular fluorescence complementation (BiFC) assays which was used for detecting protein-protein interactions in planta. The
46 Chapter 2: General Materials and Methods
pE3132 was used for the fusion of the half C-EYFP (from AA 175 to the end of the molecuole) with Arabidopsis genes. The pE 3134 was used to for the fusion of half N- EYFP (from AA 1 to 174 of the molecuole) with OsOlp1_A, OsOlp1_I, and TlOsm.
A B
35S promoter Amp R 35S Amp R 35S 35S promoter
TEV enhancer TEV enhancer attR1 pSAT5 DEST cEYFP N1 (pE3132) att R1 pSAT4 DEST nEYFP N1 (pE3134) 5743 bp 6054 bp
Cm R Cm R
35S terminator 35S terminator c(175 end)EYFP ccdB (n174)EYFP ccdB att R2 attR2
Figure 2.5 Maps of destination vectors used for detecting protein-protein interaction in planta.
2.1.6 General media, solutions: abbreviation and composition Acetosyringone: 100 mM acetosyringone; dissolved in DMSO Agarose gel loading dye (6X) 0.25% (w/v) bromophenol blue, 50% TE (w/v), 50% (v/v) glycerol Alkaline lysis solution I 50 mM Glucose, 25 mM Tris-HCl pH 8.0, 10 mM EDTA pH 8.0 Alkaline lysis solution II: 0.2 M NaOH, 1% (w/v) Sodium Dodecyl Sulphate (SDS) Alkaline lysis solution III: 2 M Glacial acetic acid, 3 M potassium acetate Ampicillin (100 mg mL-1): Dissolved in ampicillin in deionised water, filter sterilised BAP (1 mg mL-1): Dissolve 6-Benzylaminopurine in 1 M NaOH
CHCl3: IAA: Chloroform isoamyl alcohoh in a ratio of 24:1 (v/v) Coomassie Blue solution: 50% ethanol, 10% acetic acid, 0.1% Coomassie Blue G-250 (Biorad) CTAB buffer: 2% CTAB (cetyltrimethylammonium bromide), 2 M NaCl, 25 mM EDTA pH 8, 100 mM Tris-HCl, 2% polyvinylpyrrolidone (PVP 40 000) EDTA: 0.5 M Ethylene diamine tetra-acetic acid, pH 8.0
Chapter 2: General Materials and Methods 47
Fixation solution: 4% paraformaldehyde, 0.1% PBS buffer, pH 7.2 Gus stain solution: 100 mM phosphate buffer pH 7.0, 10 mM EDTA, 1 mM potassium ferriccyanide, 0.1% Triton X-100, 2 mM 5-bromo-4-chloro- 3-indolyl-β-D- glucuronide. IAA (2 mg mL-1): Dissolved indole-3-acetic acid in 1 N NaOH
Infiltration medium: 10 mM MES, 10 mM MgCl2, 100 mM acetosyringone IPTG: 0.1 M Isopropyl-β-B-thiogalactopyranoside in sterile water Kanamycin (100 mg mL-1): Dissolved kanamycin in deionised water, filter sterilised Kinetin (2 mg mL-1): Dissolved kinetin in 1 N KOH Luria Bertani (LB) solid medium: 10 g L-1 tryptone; 5 g L-1 yeast extract; 10 g L-1 NaCl; 1 5 g L-1 agar (pH to 7.5, autoclaved) Luria Bertani (LB) liquid medium 10 g L-1 tryptone; 5 g L-1 yeast extract; 10 g L-1 NaCl (pH to 7.5, autoclaved) NAA (1 mg mL-1): Dissolved 1-Naphthaleneacetic acid in ethanol
PBS buffer: 137 mM NaCl, 10 mM phosphate (10 mM Na2HPO4 and 1.8 mM
KH2PO4), 2.7 mM KCl, pH 7.4
Phosphate buffer (50 mM pH 7.4): 9.5 mM NaH2PO4, 40.5 mM Na2HPO4 Rifampicin (25 mg mL-1): Dissolved rifampicin in DMF (dimethylformanmide) SDS-PAGE destaining solution: 15% ethanol, 10% acetic acid SDS-PAGE loading buffer: 50 mM Tris pH 6.8, 1% SDS, 10% glycerol, 10 mM DTT, 0.025% bromophenol blue SDS-PAGE running buffer (1X): 25 mM Tris, 192 mM glycin, 0.1% (w/v) SDS TAE buffer: 10 mM Tris-HCl, 0.5 mM EDTA pH 7.8 TBS buffer: 100 mM Tris pH 7.5, 150 mM NaCl TBS-T buffer: TBS buffer, 0.1% Tween 20 TE buffer: 10 mM Tris-HCL pH 8.0, 1 mM EDTA Timentin (200 mg mL-1): Dissolved timentin in deionzed water, filter sterilized
TPS buffer: 100 mM Tris, 1 M KCl, 10 mM Na2EDTA Western blotting buffer: 25 mM Tris, 192 mM glycin, 20% methanol X-gal: 5-bromo-4-chloro-3-indolyl-β-D-galactopyranoside, 2% (w/v) prepared DMF
2.1.7 Plant tissue culture medium Refer to tobacco and rice transformation in Chapter 3 and 4
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2.2 METHODS
2.2.1 Cloning and bacterial transformation 2.2.1.1 Primary cloning The primers in the primer set A1, A2, A3, A4 and C1 and the respective templates in the Table 2.1 (refer to Appendix A-Figure 1 & 2 for the maps of plasmids) were used in PCR reactions to amplify the target genes by Taq polymerase for PCR product with A-tail. The A-tailed PCR products were cloned into pGEM-T Easy® vector system (Promega) in a 10 µL reaction mixture containing 3 µL of purified DNA fragments, 1 µL vector DNA, 5 µL 2X ligation buffer, 1U of T4 DNA Ligase and o topped to volume with dH2O. The mixture was incubated overnight at 14 C to maximize the number of ligations. The mixture was transformed into E. coli. The transformants were analysed by restriction enzyme analysis to identify transformants containing the target genes. The positive transformants were further grown to isolate plasmids (using Promega wizard miniprep plasmid isolation kit, Promega, USA) and to sequence plasmids for confirming the genes of interest. The pGEMT-easy vectors carrying the confirmed sequences were used to sub-clone into appropriate backbone vectors. The resulted vectors and their use in different purposes in the project is shown in Table 2.2. The primers in the primer set B1-B3, C2-C3, and D1-D5 and their respective templates in the Table 2.1 were used in PCR reactions to amplify the target genes by Taq polymerase for PCR products containing target genes with Topo-overhang. The PCR products containing target genes with Topo-overhang were purified from agarose gel after electrophoresis using a Freeze ‘N Squeeze DNA gel extraction spin column (Bio-Rad) follow the manufacturer’s protocol. The purified fragments were cloned into the pENTRTM Directional TOPO® vector (Invitrogen) in a 10 µL reaction mixture containing 1 µL vector DNA, 1 µL of salt solution, 8 µL of purified DNA fragments diluted in dH2O to get the insert/vector molar ratio of 3:1 in the reaction. The mixture were incubated overnight at room temperature for 5 min. The mixture was transformed into E. coli. The transformants were analysed by restriction enzyme analysis to identify transformants containing the target genes. The positive transformants were further grown to isolate plasmids and to sequence plasmids for confirming the genes of interest. The pENTR vectors carrying the confirmed sequences were used to sub-clone into appropriate destination vectors. The resulted vectors and their use as entry vectors in different purposes in the project is shown in Table 2.2.
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2.2.1.2 Sub-cloning by restriction enzyme digestion and ligation by T4 ligase This method was used for generating 4 plasmid constructs used in rice transformation and the pEAQ-436 destination vector for enhancing recombinant osmotin production. The pGEMT vectors containing the target genes and their corresponding backbone vectors (Table 2.2) were separately digested with appropriate restriction enzymes. To avoid re-circulation of plasmid backbone without the cloned insert, the phosphate group of linearized plasmid DNA 5’ ends were removed using alkaline phosphatase enzyme (AP). One unit of AP and 1 X AP buffer was added to the 20 µL digest reaction mixture and incubated for 40 min; after which the AP was inactivated by incubation at 65 oC for 10 min. The digested products of pGEMT vectors containing the target insert sequences and the backbone vectors were separated by agarose gel electrophoresis and the target insert fragments and backbone were separately purified using the High Pure PCR product purification kits (Roche) as per manufacturer’s instruction. The purified DNA was quantified by a NanoDropTM 2000 spectrophotometer (Thermo scientific, USA). In the ligation reaction, using the insert: backbone molar ratio of 3:1 with 50 ng of backbone for 10 µL reaction together with
1 X ligation buffer, 1U of T4 DNA Ligase (Promega) and topped to volume with dH2O. The mixture was incubated overnight at 14 oC to maximize the number of ligations.
2.2.1.3 Sub-cloning by GatewayTM recombination technology This method was used to sub-clone the target genes in the pENTR vectors into their corresponding destination vectors (Table 2.2). In this project, the resulted expression vectors were used in detecting of TlOsm localisation, producing recombinant osmotins for protein chip hybridisation, and detecting protein-protein interaction in planta. The pENTR vectors containing the target genes were digested with appropriate restriction enzyme and fragments containing the target genes together with the attL1 and attL2 recombination sites were purified from agarose gel after electrophoresis using the Freeze ‘N Squeeze DNA gel extraction spin column (Bio- Rad). The purified fragments with their corresponding destination vectors were used in a 10 µL LR recombination reaction using Gateway LR Clonase II enzyme mix (Invitrogen) according to the manufacturer’s protocol. After termination of the LR reaction, each 2 µL of reaction mixture was used for E. coli transformation. All resulted expression vectors were verified by restriction enzyme digestion and PCR
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with gene specific primers. The confirmed expression vectors were then transformed into Agrobacterium tumefaciens for expressing in plants.
Table 2.2 List of plant expression vectors constructed and used in the research
Destination Primer Name of entry and backbone Name of expression set vectors vectors vectors Purposes of uses
A1 pGEMT-TlOsm pYC27 UidA pYC-TlOsm Stably expressing TlOsm in rice
Stably expressing the GUS-reporter A2 pGEMT-Gus pYC27 UidA pYC-Ubi-Gus gene in rice (control)
A3 pGEMT-OsOlp1_A pYC_TlOsm pYC-OsOlp1_A Stably expressing OsOlp1_A in rice
A4 pGEMT-Oslp1_I pYC_TlOsm pYC-OsOlp1_I Stably expressing OsOlp1_I in rice
Stably expressing EYFP in tobacco for B1 pENTR-EYFP pCE100 pCE100-EYFP detecting protein localisation (control)
Stably expressing EYFP-C-terminus- B2 pENTR-TlOsm pCE101 pCE101-TlOsm tagged TlOsm in tobacco for detecting TlOsm localisation Producing recombinant TlOsm for pEAQ-436 pEAQ-TlOsm protein chip hybridisation BiFC assay for detecting protein- pE3134 pE3134-TlOsm protein interaction in planta Stably expressing EYFP-N-terminus- pENTR-TlOsm w B3 pCE104 pCE104-TlOsm tagged TlOsm in tobacco for detecting TGA TlOsm localisation Modifying backbone vector for C1 pGEMT-436 pEAQ-HT pEAQ-436 enhancing recombinant osmotin production
Producing recombinant OsOlp1_A for C2 pENTR-OsOlp1_A pEAQ-436 pEAQ-OsOlp1_A protein chip hybridisation
BiFC assay for detecting protein- pE3134 pE3134-OsOlp1_A protein interaction in planta
Producing recombinant OsOlp1_I for C3 pENTR-OsOlp1_I pEAQ-436 pEAQ-OsOlp1_I protein chip hybridisation
BiFC assay for detecting protein- pE3134 pE3134-OsOlp1_I protein interaction in planta
BiFC assay for detecting protein- D1 pENTR-AtCPK4 pE3132 pE3132-AtCPK4 protein interaction in planta
BiFC assay for detecting protein- D2 pENTR-AtCPK5 pE3132 pE3132-AtCPK5 protein interaction in planta
BiFC assay for detecting protein- D3 pENTR-AtALDH7 pE3132 pE3132-AtALDH7 protein interaction in planta
BiFC assay for detecting protein- D4 pENTR-AtMS1 pE3132 pE3132-AtMS1 protein interaction in planta
BiFC assay for detecting protein- D5 pENTR-AtPER42 pE3132 pE3132-AtPER42 protein interaction in planta
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2.2.1.4 E. coli transformation, growth in liquid culture and storage Chemically-competent E. coli XL1 Blue cells were transformed using the heat shock method as described by Inoue et al. (1990). A 2 µL aliquot of either T4 ligation reaction mixture, Topo reaction mixture, or LR recombination reaction mixture in a 2- mL tube was mixed with 50 µL of thawed competent E. coli cells and incubated on ice for 20 min. Cells were heat shocked at 42 oC for 90 sec, immediately transferred to ice for 2 min, resuspended in 500 µL LB media and incubated at 37 oC for 60 min on a rotary shaker at 200 rpm for aeration. The transformant was spread onto LB agar plates containing appropriate antibiotic and selecting agents and incubated at 37 oC overnight. The single and well growth colonies were selected to inoculate in overnight liquid cultures for subsequent plasmid DNA extraction.
The commercial E. coli strain ccdB minus competent cells (Invitrogen) were used for transformation of plasmid constructs pCE100, pCE101, pCE104, and pEAQ- 436 by the same heat shock method. E. coli liquid cultures were initiated from either single colony or from glycerol stock and inoculated in liquid LB supplemented with appropriate antibiotics. E. coli liquid cultures were incubated at 37 oC for up to 16 h or overnight on a rotary shaker at 200 rpm. For storage, an aliquot of 500 µL overnight-incubated E. coli liquid culture was mixed with 500 µL of autoclaved 80% glycerol in an autoclaved 2-mL cryovial. The cryovials were snap-frozen in liquid nitrogen and stored in -80 oC freezer.
2.2.1.5 Agrobacterium tumefaciens transformation, growth in liquid culture and storage Electro-competent cells of Agrobacterium either strain Agl1 or LBA4404 (used for tobacco transformation) were transformed using electroporation. An aliquot of 100 µL Agrobacterium electro-competent cells was thawed on ice and 1 µL of mini- prepped plasmid DNA was added and gently mixed by aspiration with a pipette. The mixture was transferred into a sterile pre-chilled electro cuvette before electroporation at 1.8 KV for 5 ms using an EC100 electroporator (Thermo EC). Cells were allowed to recuperate in 600 µL of LB for 2 h at 28 oC on a rotary shaker at 200 rpm. A 100 µL aliquot of cells was spread on each Petri plate containing LB agar supplemented with 25 mg L-1 rifampicin and appropriate antibiotic. The remaining cells were centrifuged at 12,000 rpm for 1 min, discarded the supernatant, re-suspended the pellet,
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and plate on another Petri plate containing the same medium and selecting agents. The plates were incubated at 28 oC for 48 h to allow the transformed colonies to grow. The transformed single colonies were selected for liquid cultures for verification of transformants containing the desired plasmid.
Agrobacterium liquid cultures were initiated from either single colonies or from glycerol stock and inoculated in liquid LB supplemented with appropriate antibiotics. Agrobacterium liquid cultures were incubated at 28 oC for 48 h on a rotary shaker at 200 rpm. Agrobacterium liquid cultures were used for preparation of plasmid verification, plant tissue transformation, infiltration, and storage. Similar protocol for storage of E. coli in glycerol stock was applied to storage of Agrobacterium.
2.2.1.6 Plasmid DNA extraction and purification A standard alkaline lysis protocol (Sambrook et al., 2001) was used to isolate plasmid DNA from E. coli cultures in primary cloning and from Agrobacterium cultures for verification of bacterial clones carrying the desired plasmid constructs. A 2 mL of E. coli or 4 mL of Agrobacterium culture aliquot was centrifuged at 14,000 rpm for 1 min and the resulting pellet was resuspended in 100 µL of Solution I. Bacteria was lysed in 200 µL of Solution II and mixed by inversion. Bacterial proteins and chromosomal DNA were then precipitated by the addition of 150 µL Solution III and cellular components were separated by centrifugation at 14,000 rpm for 5 min at room temperature. Plasmid DNA was then precipitated by transferring 400 µL of the supernatant to 1 mL of ice-cold 100% ethanol and centrifuged at 14,000 rpm for 5 min. The pellet was washed with 70% ethanol, re-centrifuged at 14,000 rpm for 5 min, -1 allowed to air dry and finally resuspended in 50 µL dH2O with 10 ng mL of RNaseA (Roche).
Alternatively, the pure plasmid DNA from E. coli cultures used for sequencing and confirming the desired expression vectors was isolated using the Wizard® Plus SV Minipreps DNA Purification Kits (Promega) as per the manufacturer protocol. The concentration and purity of the plasmid DNA were determined using a NanoDropTM 2000 spectrophotometer (Thermo scientific, USA).
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2.2.1.7 Plasmid DNA sequencing All sequencing reactions were performed using the Big Dye Terminator Cycle Sequencing KitTM version 3.1 (Applied Biosystems). Each reaction contained 200 ng of purified plasmid DNA template, 20 pmol primer, 4 µL of 5X reaction buffer and 1
µL BDTv3.1 ready mix in a final volume of 20 µL topped up with dH2O. All sequencing PCRs used an initial denaturation at 96 oC for 1 min prior to 35 cycles of 96 oC for 10 s, 50 oC for 5 s and 60 oC for 4 min. After cycling, PCR products were precipitated by the additional two volumes of 100% ethanol, 2 µL of 3 M sodium acetate (pH 5.2), 2 µL of 125 mM EDTA (pH 8.0), incubation at room temperature for 30 min, and centrifugation at 14,000 rpm for 20 min. DNA pellets were washed with 500 µL of 80% ethanol and centrifuged for further 10 min at 14,000 rpm. DNA pellets were air dried and capillary sequenced at the Molecular Genetics Research Facility (QUT).
2.2.1.8 Restriction enzyme digestion of plasmid DNA A reaction contained 1 µg of plasmid DNA, 5-10 U of appropriate restriction endonuclease, specific buffer, topped up to 20 µL with dH2O. The reaction was incubated at corresponding temperature for specific enzyme for 1 h. For double digestion with non-compatible buffers, sequential digests were performed.
2.2.2 General methods in nucleic acid extraction, amplification and analysis 2.2.2.1 Extraction of plant total DNA Genomic DNA from putative transgenic rice lines and WT was extracted using the DNeasy® plant mini kits (Qiagen). Approximately 100 mg of frozen rice leaves in a 2 mL Eppendorf containing a metal bead was frozen by immersing in liquid nitrogen and homogenised using TissueLyser (Qiagen) at maximum frequency for 30 sec and the tube was immersed back in liquid nitrogen. Genomic DNA was subsequently extracted from the ground leaf samples following the manufacturer’s instruction.
Genomic DNA from transgenic tobacco leaves and T1 transgenic rice leaves was isolated following the rapid release DNA protocol (Thomson and Henry, 1995). An aliquot of 50 mg of frozen leaves in a 2 mL Eppendorf containing a metal bead sample was homogenised as described above. 100 µL of ice-cold TPS buffer was added to the tube and the tube was incubated at 95 oC for 10 min following by a quench on ice. Proteins, pigments, and other organic compounds were extracted by adding 100 µL of
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chloroform: isoamyl alcohol (24:1) to the slurry. The resulting mixture was mixed by gently flicking and was centrifuged at 14,000 rpm for 5 min at room temperature. The resulting aqueous supernatant (40 µL) was carefully transferred to a fresh 1.5 mL microtube.
The dilution of the supernatant in dH2O (1:5 ratio) was used in the PCR reaction (1 µL in 20 µL PCR reaction).The stock extract and dilution were stored at -20 oC.
2.2.2.2 Extraction of plant total RNA Total RNA from roots and shoots of T. loliiformis and transgenic rice leaves was extracted using RNeasy® plant mini kits (Qiagen). An aliquot of approximately 100 mg of frozen plant tissues was ground in liquid nitrogen using a mortar and a pestle. The total RNA was subsequently extracted from the ground leaf samples as per manufacturer’s instruction.
2.2.2.3 Quality and quantitative assessment of nucleic acids The concentration and purity of isolated DNA and RNA were determined using the NanodropTM 2000 spectrophotometer. Sample absorbance was measured at wavelengths of 230, 260 and 280 nm. The purity of the RNA was assessed using the ratio of absorbance at 260/280 and 260/230 nm and the samples with absorbance ratios approximate to 2 were acceptable. For the DNA, a 260/280 of ~ 1.8 was desirable. The total RNA was further assessed for integrity by agarose gel electrophoresis analysis with the presence of two ribosomal RNA bands at approximately 1.6 and 2 Kbp and the intensity of the 2 Kbp band as twice as the 1.6 Kbp band. The presence of genomic DNA in the rapid-released extract was analysed by PCR reaction with the primer forward (5’- CATCACAGGATTTCGGTCCT-3’) and reverse (5’AGACAAATCGCTCCACCAAC- 3’) followed by agarose gel electrophoresis with the presence of a unique band of 507 bp.
2.2.2.4 Elimination of genomic DNA from total RNA Total RNA was treated with DNase I to eliminate any traces of genomic DNA using an RQ1 RNase-free DNase Kit (Promega) as per manufacturer’s instructions. The treated RNA was used as template in a PCR reaction with the primer forward (5’- CATCACAGGATTTCGGTCCT-3’) and reverse (5’AGACAAATCGCTCCACCAAC- 3’) followed by agarose gel electrophoresis to confirm the absence of genomic DNA in RNA samples. The presence of a 507 bp band on the gel indicated the contamination of genomic DNA in RNA samples, whereas no amplified products indicated the absence of genomic DNA in RNA samples.
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2.2.2.5 First-strand complementary DNA synthesis
Total DNA-free RNA was reverse transcribed using an anchored-oligo (dT)20 primer to generate cDNA using the SuperScript® III First-Strand Synthesis kit (Invitrogen) following the manufacturer’s protocol. Briefly, a two-step procedure was followed. In the first step, 1 µg of total RNA was mixed with 1 µL of 50 mM anchored- oligo (dT)20 primer, 1 µL 10 mM dNTP mix and topped up to 10 µl reaction volume with nuclease-free water. The reaction mixture was incubated for 5 min at 65 oC and placed on ice for 2 min. In step 2, a 10 µL reaction master mix containing 2 µL 10X
Reverse Transcriptase Reaction Buffer, 4 µL 25 mM MgCl2, 2 µL 0.1 M DTT, 1 µL RNaseOUT (40 U/ µL) and 1 µL of SuperScript® III Reverse Transcriptase (200 U/µL) was added to bring the total reaction volume to 20 µL. The final reaction mixture was incubated at 50 oC for 50 min followed by inactivation of the Reverse Transcriptase at 85 oC for 5 min. The reaction products were chilled on ice for 5 min, then 1 µL of RNase H was added and incubated at 37 oC for 20 min. The final reaction products were stored at -80 oC for further gene expression analysis.
2.2.2.6 PCR amplification PCRs were carried out using a Peltier Thermo Cycler-200 (MJ Research) using the GoTaq® master mix (Promega) or Phusion® High-Fidelity DNA Polymerase. All PCRs were performed in a final volume of 20 µL containing 5 pmol of each primers. Unless otherwise stated, all PCRs were initially denatured at 94 oC for 2 min prior to 35 cycles of 94 oC for 30 s, appropriate annealing temperature for 30 s and 72 oC for 1 min per 1 Kb of expected product. A final extension step of 72 oC for 7 min was also included.
2.2.2.7 Agarose gel electrophoresis Unless otherwise stated, separation of nucleic acids was carried out in 1% (for DNA) and 1.5% (for RNA or DNA fragments less than 500 bp) agarose gel in 1 X Tris-Acetate-EDTA (TAE buffer) premixed with 0.25X SYBR SafeTM DNA gel stain solution (Invitrogen). With the exception of PCR reaction performed with Gotaq® master mix, 6X gel loading buffer was added to all samples before being loaded onto agarose gel. A DNA ladder 2-Log DNA was load alongside samples for band size comparison. Gels were run in either mini or midi-multi sub electrophoresis system (Bio-Rad). Electrophoresis was performed at 100 V for 40-60 min and the gels were viewed on Safe ImagerTM (Invitrogen) with a blue-light transilluminator installed in a
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G:Box gel documentation system (Syngene) and documented using a computer installed with GeneSnapTM version 6.07 image acquisition software (Syngene).
2.2.2.8 Purification of DNA from agarose gels Restriction digested DNA or PCR products were separated by electrophoresis on agarose gel. DNA fragments were visualised under UV light, and the fragments corresponding to the expected size were excised from the stained gels using sterile scalpel blades and purified using either the Freeze ‘N Squeeze DNA gel extraction spin column (Bio-Rad) or the High Pure PCR product purification kits (Roche) as per manufacturer’s instructions.
2.2.2.9 RT-qPCR analysis Refer to Chapter 3
2.2.3 Agrobacterium-mediated transient transformation of plants Agro infiltration was performed in wild type N. benthamiana for recombinant osmotin production and for protein-protein interaction in planta analysis as well as in transgenic tobacco plants for co-localisation analysis. A. tumefaciens strain Agl1 carrying the target plasmid was grown in a 5 mL LB medium supplemented with rifampicin (25 µg mL-1) and appropriate antibiotic in a 50-mL Falcon tube and incubated at 28 oC for 48 h with shaking at 200 rpm. The culture volume was increased with LB containing the same set of antibiotic and incubated overnight at 28 oC with shaking at 200 rpm. The bacterial cell culture was collected by centrifugation at 4000 rpm for 10 min, washed three times with infiltration medium (10 mM 2-(N- morpholino) ethaesulfonic acid (MES), pH 5.5, 10 mM MgCl2), and resuspended with an infiltration medium containing 200 µM acetosyringone to a concentration of OD600 = 0.8. The bacterial suspension was incubated for further 3 h with gentle shaking at room temperature prior to infiltration. The bacteria were delivered into the underside of leaves of 5-week-old WT N. benthamiana plants or 3-week-acclimatised transgenic tobacco plants using a blunt tipped plastic syringe and applying gentle pressure.
2.2.4 Confocal imaging Leaves and roots of wild-type and transgenic tissue cultured tobacco plants expressing EYFP, TlOsm-EYFP, or EYFP-TlOsm were cut into 0.5 x 0.5 cm squares or 0.5 cm long, washed in PBS buffer (137 mM NaCl, 2.7 mM KCl, 10 mM Na2HPO4, o 1.8 mM KH2PO4, pH 7.4), fixed in 4% paraformaldehyde at 4 C for 1 h and stored in
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PBS buffer at 4 oC until being viewed. Organelle protein tracker-infiltrated transgenic tobacco leaves collected at 4-day post infiltration and leaves of infiltrated N. benthamiana collected at 2-day post infiltration were cut into 0.5 x 0.5 cm squares and fixed in 4% paraformaldehyde in a similar way as with tissue cultured samples. The fixed samples were examined under A1 Confocal Microscope (Nikon, Japan). For tissue cultured tobacco samples and infiltrated N. benthamiana samples, the green images representing EYFP fluorescence (autofluorescence as well) were captured under 488 nm laser channel with emission of 500-550 nm as contrast to red images resulted from emission of chloroplast at excitation of 638 nm in a 663-738 nm emission. For organelle protein tracker-infiltrated tobacco samples, the fluorescence images were captured under the combination of excitation 488 nm, 561 nm (emission of 552-617 nm) and 638 nm.
2.2.5 Relative water content (RWC) The percentage of RWC was calculated according to Bars and Weatherley (1962). T. loliiformis shoots and O. sativa leaves were weighed upon sampling to get the fresh weight, FW. The shoot or leaf samples were placed 15-mL Falcon tubes containing water overnight, botted dried with paper towel and weighed to get their turgid weight, TW. After that, samples were dried overnight in a vacuum oven at 80 oC and weighed to get final dry weight, DW. The percentage of the RWC of samples was calculated using the formula: RWC (%) = (FW-DW)*100/ (TW-DW).
2.2.6 Electrolyte leakage measurement Refer to Chapter 5 2.2.7 Agrobacterium-mediated plant transformation and regeneration Refer to Chapter 3 for tobacco transformation, Refer to Chapter 4 for rice transformation
2.2.8 Bioinformatics analysis Refer to Chapter 3 2.2.9 Abiotic stress treatment of T. loliiformis Refer to Chapter 3 2.2.10 Transgenic rice acclimatisation and abiotic stress treatments Refer to Chapter 5
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2.2.11 Protein extraction, purification and analysis Refer to Chapter 6
2.2.12 Protein microarray hybridisation and detection of protein-protein interaction Refer to Chapter 6
2.2.13 Data analysis All graphs and standard errors were prepared using Microsoft Excel. Statistical analysis of TlOsm transcriptional expression upon abiotic stresses and developmental stages was done using BioRad CFX ManagerTM software. Genetic relationship of TlOsm with other osmotins was analysed by default program in MEGA 7 software (refer to Chapter 3). Growth and physiological parameters of transgenic rice were analysed using ANOVA and significant differences among experimental treatments were analysed by Tukey’s HSD tests (Arend, 2010; refer to Chapter 5). Statistical analyses used for significant protein interactors of the three osmotins, gene ontology (GO) term enrichment of the protein sets, and significant pathways involving the osmotins were the default programs of indicated software and web servers (refer to Chapter 6).
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60 Chapter 2: General Materials and Methods
Chapter 3: Molecular Characterisation of TlOsm, an Osmotin from Tripogon loliiformis
Chapter 3 starts with an introduction to the first objective of this research project which includes the identification of novel and conserved characteristics of TlOsm, examination of expression profile of TlOsm upon major abiotic stresses and during developmental stages, and determination of TlOsm sub-cellular localisation. Section 3.2 briefly describes the materials and methods used to achieve the goals of this objective. Section 3.3 presents the identified novel and conserved characteristics of TlOsm, the expression profile of TlOsm upon abiotic stress and developmental stages, the sub-cellular localisation of TlOsm. The discussion of the results and findings in this objective is presented in Section 3.4.
3.1 INTRODUCTION
Abiotic stresses have been identified as the key limiting factor on agricultural production (Mittler and Blumwald, 2010). Rising food demand due to increasing global population is another challenge for future agriculture. Couple together, changing climate and increasing population undoubtedly pose a significant threat to agricultural production in meeting the global food demand. It has been estimated that agricultural production must be increased by at least 60% globally and doubled in some particular regions to fulfil the global food demand by 2050 (FAO, 2016). Progresses made by genetic improvement and agricultural resource management during the last century have significantly contributed to sustaining current food needs. To meet the needs for future food, agricultural productivity need to be constantly increased and that can only be achieved by both genetic improvement and sufficient management of agricultural production system. However, the current trends in yield improvement of major crops were not sufficient for future food demand (Ray et al., 2013). While crop yield progress made by conventional breeding reaches plateau and is unable to keep pace with the target crop production, the production of biotechnology together with genetically-engineered crops would be potentially filling the gap (Oliver, 2014). The abilities of more rapid and precise genetic improvement and transfer genes
Chapter 3: Molecular Characterisation of TlOsm, an Osmotin from Tripogon loliiformis 61
across species barriers have made genetic engineering an attractive tool to achieve the desired traits in crops to gain necessary yield sustainable in the near future.
There is a great need to identify the key factors contributing to genetic engineering applications for steadily increasing crop production under predicted adverse climate conditions. Characterisation of stress-responsive genes is necessary for utilisation in genetic engineering to generate enhanced crops that can cope with stresses and in return of favourable conditions they continue to grow and gain maximum yield. It has been suggested that the introduction of stress-responsive genes from stress-adapted species to crops might enable them to withstand more extreme abiotic stresses (Mittler and Blumwald, 2010). Resurrection plants, such as T. loliiformis, possess unique tolerant mechanisms in their vegetative tissues enable them to survive dehydration to air-dried state and restore full physiological activity and growth upon several days of rehydration (Dinakar and Bartels, 2013; Gaff and Oliver, 2013; Karbaschi et al., 2016). Therefore, resurrection plants represent an ideal genetic resource for seeking genes encoding for unique stress-adaptive mechanisms allow plants to survive extreme stress conditions. Identification of key upstream regulators of stress adaptation and use of these for enhancing abiotic stress tolerance are believed to be more effective in genetic engineering approach (Mittler and Blumwald, 2010; Cominelli et al., 2013). Among the genes isolated from a drought-induced cDNA library of T. loliiformis at the Centre for Tropical Crop and Biocommodities (CTCB), Queensland University of Technology (QUT), TlOsm was one of the candidate genes for use in developing enhanced abiotic stress tolerant crops. Plant osmotins have been found to be the key proteins associated with plant response to abiotic and biotic stresses. As discussed in Section 1.3, osmotin genes have been identified and characterised from many plant species and demonstrated to have multi-functions in plant response to abiotic and biotic stresses. Expression of osmotins has been used to generate a number of transgenic plants tolerant to drought, high salinity, cold, fungal pathogens and some combinations of these (see Table 1.1 for phenotype of transgenic osmotin plants and references). There have been progressive evidence showing osmotin roles as key regulators in plant defense response. However, no such osmotin from the resurrection plants, particularly in T. loliiformis, has been characterised.
62 Chapter 3: Molecular Characterisation of TlOsm, an Osmotin from Tripogon loliiformis
The aim of this research was to identify the novel and conserved characteristics of TlOsm, an osmotin from the resurrection plant T. loliiformis. The specific objectives of this chapter were to:
1. Identify the novel and conserved characteristics of TlOsm 2. Examine the transcriptional expression profile of TlOsm upon major abiotic stresses and during developmental stages. 3. Determine the sub-cellular localisation of TlOsm.
3.2 MATERIALS AND METHODS
3.2.1 Plant materials Seeds of T. loliiformis were propagated though multiple generations in glasshouse conditions, air dried at room temperature, and stored at 4 oC. These seeds were used to germinate plants for examining the transcriptional expression of TlOsm under major abiotic stresses and developmental stages.
Tobacco plants as described in Section 1.1.1 were used for generation of transgenic tobacco plants expressing EYFP-tagged TlOsm and EYFP control.
3.2.2 Sequence analysis of TlOsm The nucleotide sequence of TlOsm was translated at the ExPASY translation tool (Gasteiger et al., 2005). Hydropathy profile of TlOsm based on Kyle & Doolittle scale was performed using the ExPASY Proscale. Molecular weight of TlOsm was calculated using the ExPASY Compute pI/Mw tool. Physicochemical properties of the protein were obtained from the ExPASY ProtParam. Disulfide bridges were predicted on the ExPASY ProSite. The BLAST program of the National Centre for Biotechnological Information (NCBI) was used to search the sequences with similarity to TlOsm. Multiple sequence alignment of TlOsm with other selected osmotins was done using the T-coffee program (Tommaso et al., 2011) using the ClustalW method. To predict the signal peptide and cleavage site, SignalP server and TargetP 1.1 server were used (Emanuelsson et al., 2007). Subcellular localisation of TlOsm was predicted in the WoLF PSORT server (Horton et al., 2007), the SMART program (Schultz et al., 1998), and the MEMSAT server (Buchan et al., 2010). SUMOylation sites of TlOsm was predicted using SUMOsp server (Xue et al., 2006).
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3.2.3 Phylogenic tree construction Amino acid sequences of 39 osmotins and OLPs were obtained from the NCBI Protein Bank. Among these, 20 sequences originated from dicots that had been well– characterised and functionally validated and 19 sequences originated from monocot that had evidences of expression upon stress. The entire phylogenetic analysis was performed in MEGA 7 software. The amino acid sequence of TlOsm and 39 above- mentioned proteins were aligned using the ClustalW with all default settings for protein weight matrix. This alignment was used as input data for phylogenetic tree construction. The tree was constructed by the Maximum Likelihood method with all default settings and the JTT model method (Jones et al., 1992). The gaps/missing data were treated by partial deletion with site coverage cutoff 95%. The phylogeny was treated by Bootrapping with 1000 replications.
3.2.4 Comparison of TlOsm with Os-OlP1_A and OsOlp1_I by bioinformatic tools The sequence similarities of the three osmotins were compared and aligned using the ClustalW method of the T-coffee program (Tommaso et al., 2011). All the methods for signal peptide identification, protein localisation, SUMOylation site predictions applied for TlOsm (Section 3.2.2) were also applied for OsOlp1_A and OsOlp1_I. The active binding residues of the three osmotins were determined by submitting the three corresponding sequences to the I-TASSER for protein 3-D structure modelling and function predictions (Zhang, 2008; Roy et al., 2010). After receiving the packages from the server, the number one model suggested by the server of each osmotin was used for determine the active binding residues (also indicated for each model by the server) (Yang et al., 2015) and for comparison. Similarly, the sequences of the three osmotins were submitted to the GPS web server (Xue at el., 2005) and SUMOsp for prediction of potential phosphorylation sites and SUMOylation sites respectively. Then, the functional site comparison were made based on the results provided by these servers.
3.2.5 Growth conditions, abiotic stress treatments and sampling for T. loliiformis plants Seeds of T. loliiformis were germinated and grown in 50-mL pots in glasshouse at 27 oC and 16 h photoperiod until stress treatments were applied and samples were taken. For cold stress, 6-week old plants were placed in a cold room at 4 oC for 24 h
64 Chapter 3: Molecular Characterisation of TlOsm, an Osmotin from Tripogon loliiformis
with 16 h light and 8 h dark conditions; then the cold-stressed plants were recovered in the glasshouse. Samples were taken at 0, 1, 3, 6, 9, 12 and 24 h during stress and 48 h after recovery (72 h post initial stress). For heat stress, plants were grown at 45 oC in a growth chamber in a similar way as cold stress and samples were taken at the same time-points as cold stress. For salinity stress treatment, 6-week old plants in plastic pots were first treated with 200 mM NaCl solution when the leaf relative water content (RWC) was about 85% and the second treatment was 48 h later in a manner that the potting mix was saturated by NaCl solution and the exceeded NaCl solution was absorbed by paper towel placed underneath the pots. After 96 h and two 200 mM NaCl solution applications, salt solution was washed off from potting mix by submerging the pots in water and draining off for 5 times (change water every time). Plants were led to recover and were watered with a 2-day interval until the data collection for recovered plants completed. Salinity stress samples were taken at 0, 1, 3, 6, 12, 24, 48 and 96 h after salt treatment and 1 and 5 days after recovery. Previous to drought stress treatment, the morphological changes in shoots of T.loliiformis plants corresponding to specific leaf RWC (80, 70, 60, 40 and < 10%) were determined. In drought stress, 40-day old plants were fully watered in the late afternoon and the fully-hydrated samples were taken in the morning of the next day. Plants were then challenged by withholding water for a period of time until the leaf RWC reached the pre-determined points. Then the plants with <10% RWC were re-watered with a 2-day interval for recovery. Samples were taken at full hydration, 80, 70, 60, 40, <10% RWC and 24 and 72 h after re-hydration. In sampling for different developmental stages, plants were sampled at 2, 4, 6, 8 and 10 weeks post germination. For the drought stress, 8 pots of multiple plants were collected for each RWC point and RWC was determined for plants in each pot based on randomly-selected 15 leaves. For the remaining experiments, four pots of multiple plants were collected for each stress or developmental time-points. Each pot was considered as one biological replicate. Leaves and roots of the above stress-treated plants and the corresponding controls sampled at different stress time-points and developmental stages were snap frozen in liquid nitrogen and stored at -80 oC for RNA extraction.
3.2.6 RNA extraction and RT_qPCR analysis Total RNA was extracted from 100 mg of shoot or root samples using the methods described in Section 2.2.2.2. Genomic DNA in the total RNA samples was
Chapter 3: Molecular Characterisation of TlOsm, an Osmotin from Tripogon loliiformis 65
eliminated as in Section 2.2.2.4. cDNA was synthesized from 1 µg of total RNA in a 25 µl reaction using the methods described in Section 2.2.2.5. The synthesized cDNA was used as templates in PCR assay using a specific pair of primers that yields distinguish amplicons from T. loliiformis cDNA and genomic DNA to confirm the complete elimination of genomic DNA in each of cDNA samples. Real-time RT-PCR was performed on an optical 384-well plate with a BioRad CFX 384TM Real-time PCR system using SYBR premix (BioRad) according to the manufacturer’s protocol and TlOsm specific primers forward (5’- CTGCAAGCCGTCGCAGTACT-3’) and reverse (5’-AGGTGATGGCGTAGGTGGTGT-3’). The T. loliiformis Actin1 and Ubi10 genes were used as internal references. The PCR thermal cycling protocol was as follows: 95 oC for 10 s, followed by 40 cycles at 95 oC for 5 s and 60 oC for 30 s. BioRad CFX ManagerTM software was used for data analysis. The RT-qPCR products with highest, medium and lowest levels of TlOsm expression were ligated into pGEMT-easy vector (Invitrogen) and transformed into E. coli. Five individual E. coli colonies were randomly selected from each RT-qPCR product for sequencing to confirm the same amplicons of TlOsm.
3.2.7 Generation of transgenic tobacco expressing EYFP-tagged TlOsm and VC 3.2.7.1 Plasmids for tobacco transformation Three plasmids pCE101-TlOsm, pCE104-TlOsm, and pCE100-EYFP constructed by the methods described in Section 2.2.1 were used for tobacco transformation. The gene expression cassette between left and right borders of these plasmids are shown in Figure 3.1.
Figure 3.1 Schematic diagram of gene constructs for expressing EYFP-tagged TlOsm and EYFP control in N. tabacum
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3.2.7.2 Agrobacterium-mediated transformation of tobacco N. tabacum transformation, selection and regeneration were performed by leaf disc transformation as described by Clemente (2006). Leaves from 4-6 week-old N. tabacum plants germinated in vitro and cultured at 16 h photoperiod, 25 oC, and moderate light were used as target tissues for transformation. The day before transformation, Agrobacterium carrying the pCE-100-EYFP, pCE-101-TlOsm and pCE-104-TlOsm plasmids stored in glycerol were cultured overnight in LB medium (100 µl of bacterial stock in 10 ml of liquid LB). On the day of transformation, agrobacterial overnight cultures were diluted in inoculation medium containing full strength MS salts and 3% sucrose to get the OD600 of 0.1. Leaf discs about 1 cm in diameter were punched from fresh leaves, immersed in diluted bacterial suspension for 10 min with well agitation 3 times, blotted on filter paper and placed upside down on co-cultivation medium in Petri plates. These plates were incubated for 1 day at 25 oC in darkness. The infected leaf discs were washed 3 times with autoclaved water containing 200 mg L-1 timentin and cultured on Petri plates containing 30 mL of selection medium (full-strength MS salts and vitamins, 30 g L-1 of sucrose, 1 mg L-1 of NAA, 3 mg L-1 of BA, 8 g L-1 of agar, 200 mg L-1 of timentin and 25 mg L-1 of hygromycin, pH 5.7). These plates were placed in the growth room with 16 h photoperiod, 25 oC, and moderate light and frequently subcultured at 2 week intervals until shoot formation. For each plasmid construct, 10 plates of 10 leaf discs per plate were used in transformation.
3.2.7.3 Selection and regeneration of transgenic tobacco plants Shoots just emerged from calli induced by leaf disc after 3 subsequent selections in Petri plates were scanned under fluorescent microscope (Zeiss SteREO Lumar V.12). The well-defined stem shoots expressing EYFP, which was not observed in WT, were transferred into selection rooting medium containing 1/2 strength MS salts, 200 mg L-1 of timentin and 25 mg L-1 of hygromycin. For each plate, 5 strongest shoots were selected from 5 different leaf discs to ensure independent lines. Rooted plantlets were scanned under fluorescent microscope to ensure the EYFP expression in both root and shoot of plants. Well-rooted plantlets constitutively expressing EYFP were subjected for molecular characterisation of the transgenes. When the transgenic status were confirmed, plants were in vitro multiplied, subjected for analysis and acclimatised in the controlled growth room.
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3.2.7.4 PCR confirmation of transgenes in regenerated transgenic tobacco PCR analysis was used to confirm the presence of TlOsm and EYFP genes in EYFP expressing tobacco plants. Two WT and 12 normal-looking plants transformed with each plasmid construct were chosen. Genomic DNA from 38 tobacco leaf samples was isolated by following rapid protocol (Thomson and Henry, 1995) with a minor modification as described in Section 2.2.2.1. The presence of DNA in 38 rapid- released extracts were confirmed by PCR using Musa 18Sr primers (Table 3.1). For PCR and agarose gel electrophoresis, refer to methods as described in Section 2.2.2.6 and 2.2.2.7.
Table 3.1 List of primers for PCR characterisation of transgenic tobacco plants Annealing Amplicon Gene Primer sequence (5’-3’) temperature (oC) size (bp) TGGCCGAGTTCACCATGGAC TlOsm 60 405 AGGTGATGGCGTAGGTGGTGT CACCATGGTGCCTAGCGTGACCAAGG EYFP 50 838 TTAAGCGTAATCTGGAACATCG CATCACAGGATTTCGGTCCT Musa 18Sr 56 507 AGACAAATCGCTCCACCAAC
3.2.8 Agro-infiltration of transgenic tobacco The binary plasmid Pm-rk CD3-1007 (Nelson et al., 2007) carrying the mCherry-tagged protein targeting plasma membrane was used for co-localisation analysis. A. tumefaciens strain Agl1 carrying the plasmid were grown, prepared, and infiltrated into acclimatised transgenic tobacco plants expressing either EYFP, EYFP:TlOsm, or TlOsm: EYFP by the methods described in Section 2.2.3.
3.2.9 Salinity stress treatment of tobacco plants Tissue cultured transgenic tobacco plants were placed in autoclaved pots containing autoclaved half-strength MS medium with vitamins supplemented with 150 mM NaCl solution until the solution surface reached 1 cm above the root collar. Pots were placed in growth chamber with conditions as for tissue culture tobacco plants for 24 h. Roots of treated plants were used for preparing fixed samples in confocal analysis of TlOsm localisation under salinity stress as described in Section 2.2.4.
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3.2.10 Confocal imaging Refer to Section 2.2.4
3.3 RESULTS
3.3.1 Sequence analysis of TlOsm 3.3.1.1 TlOsm belongs to Thaumatin-like protein (TLP) superfamily but has a non-homologous C-terminal sequence Osmotin, OLP, and TLP are relatively low-molecular-weight proteins that plants produce in response to abiotic and biotic stresses (Liu et al., 2010). TlOsm was previously isolated from a T. loliiformis drought-induced cDNA library (unpublished, Williams). The full-length TlOsm cDNA encoded a protein consisting of 313 amino acids (AA). Its molecular weight was estimated to be 31 kDa. The BLAST search on the NCBI database revealed it to be homologous to those of a GH64-TLP_SF superfamily (osmotin, OLP, and TLP proteins) with a high similarity at its 26-252 AA sequence. The protein has 8 predicted disulfide bridges, which are conserved across osmotins, formed by 16 cysteine residues. Its theoretical pI is 4.75. To compare the TlOsm AA sequence with other osmotins, the five selected osmotin AA sequences, which were well characterised and validated to have roles in plant stress tolerance, were aligned with TlOsm. The alignment showed high identity only between N- terminus to AA 252 of TlOsm AA sequence (Figure 3.2). TlOsm sequence of AA 253-313 was not found homologous to other proteins in the database.
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Figure 3.2 Alignment of TlOsm with selected plant osmotins. Arabidopsis thaliana (accession number NM117234.2), Capsicum annuum (AY262059), Glycine max (NM001249476.1); Nicotiana tabacum (X65701.1); and Solanum nigrum (AF450276.1), as in order from the top. The identical amino acid are indicated as *. The 16 conserved Cysteines among osmotins are boxed. Multiple alignment was done in the T-coffee program (http://www.ebi.ac.uk/Tools/msa/tcoffee/) using the ClustalW). Arrow indicates the signal peptide of TlOsm.
The hydropathy profile showed that TlOsm is highly hydrophobic at the N- and C-terminus and is neutral in the middle of its sequence (Figure 3.3 A). It was predicted that TlOsm has a 24 AA N-terminal signal peptide with a cleavage site between Ser and Lys. Following cleavage of the signal peptide, TlOsm molecular weight was
70 Chapter 3: Molecular Characterisation of TlOsm, an Osmotin from Tripogon loliiformis
estimated to be 28.76 kDa with a pI of 4.60. A transmembrane α-helix at its AA sequence 294-309 determines TlOsm to be an integral transmembrane protein type I (Figure 3.3 B).
Figure 3.3 Property analysis of TlOsm. A: Hydropathy profile of TlOsm based on Kyte & Doolittle scale was performed at http://web.expasy.org/protscale/. B: Sub-cellular localisation prediction of TlOsm using MEMSAT server (http://bioinf.cs.ucl.ac.uk/psipred/?memsatsvm=1)
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3.3.1.2 TlOsm is closely related to osmotins of monocotyledonous plants To gain an understanding of the genetic relationship of TlOsm and other plant osmotins, a phylogenetic tree was generated for TlOsm with other osmotin sequences, 19 from monocotyledonous plants and 20 from dicotyledonous plants (Figure 3.4). The respective sequences were grouped in two distinct clades. All sequences from dicotyledonous plants formed one clade and the other clade grouped by those of monocotyledonous plants. The clade of monocotyledonous osmotins had two sub- groups, with TlOsm grouped to a sub-group containing the majority of sequences (15 sequences). TlOsm AA sequence was found to be closest to the osmotins of Setaria italica (foxtail millet).
72 Chapter 3: Molecular Characterisation of TlOsm, an Osmotin from Tripogon loliiformis
Figure 3.4 The phylogenic tree showing the relationship of TlOsm and osmotins from different monocotyledonous and dicotyledonous species. Only the complete published sequences of osmotin and osmotin-like proteins were selected including 20 sequences from dicotyledonous species and 19 sequences from monocotyledonous species. The amino acid sequences were obtained from the NCBI Protein bank with accession number indicated. Entire phylogenetic analysis was performed in MEGA 7 software. Alignment of 40 sequences was done using the ClustalW. The tree was constructed by the Maximum Likelihood method with all default settings. The gap/missing data were treated by partial deletion with site coverage cutoff 95%. The phylogeny was tested by Bootstrapping with one thousand replications. Arrow indicates the position of TlOsm. Two rice osmotins used to compare with TlOsm in this study were boxed: the sequence in red box from the drought-tolerant cultivar Apo and the sequence in blue box from the drought-sensitive cultivar IR 64.
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3.3.2 TlOsm is induced by cold, drought and salinity stresses Determination of critical sampling time-points is necessary for examining the expression pattern of TlOsm during developmental stages. To determine the time- points for sampling, the life cycle of T. loliiformis plants in controlled glasshouse conditions was first observed. T. loliiformis plants started tillering at about 4 weeks after germination and reached maximum density at 6 weeks. The plants started flowering at week 7 and in week 8, all of them were bearing flowers. Their seeds were all filled at week 10 and could be harvested at week 12. The plants completed their life cycle at about 12-14 weeks after germination. Therefore, five time-points including 2- , 4-, 6-, 8- and 10-week post germination were determined for examining TlOsm expression during developmental stages (Figure 3.5). Then, transcriptional expression of TlOsm during developmental stages was determined on these five time-point samples. The expression of TlOsm remained unchanged in shoots during development (Figure. 3.6 A) but was found at higher level in roots only at 6-week post germination (Figure 3.6 B).
Figure 3.5 Developmental stages of T. loliiformis for sampling. Time-points indicated as weeks after germination. Plants at 6 weeks were used for all stress treatments
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To determine the expression profile of TlOsm in response to abiotic stresses, the 6-week old plants were separately exposed to four major abiotic stresses including cold (4 oC), heat (45 oC), salinity (200 mM NaCl) and drought. Samples were collected at different time-points during the course of stress as indicated in the graphs in Figure 3.6 and analysed by RT-qPCR. TlOsm was down-regulated in shoot within first 12 h exposure to heat stress, then went up to the level before stress at 24 h and during recovery (Figure 3.6 C); while its expression levels in root remained unchanged during the course of heat stress and recovery (Figure 3.6 D). In response to cold stress, TlOsm was rapidly and transiently activated in both roots and shoots after only 1 - 3 h of treatment, then went down to normal levels after 6 h in shoots (Figure 3.6 E) and down- regulated during 6 - 24 h of stress in roots (Figure 3.6 F). Under drought stress, TlOsm expression was similar in shoots and roots that was sharply induced at 80% RWC, reached a peak at 70% RWC, and remained high levels at 60% RWC (Figure 3.6 G & H). The different response of roots and shoots in drought stress was found at 40-10% RWC where TlOsm transcripts went down to level of before stress in shoots (Figure 3.6 G) but remained significantly higher than unstressed levels in roots (Figure 3.6 H). TlOsm was rapidly and sharply activated upon exposure to salt stress in roots, reached thousand fold after only 1 h of stress treatment and remained significantly high levels within 12 h of salt stress (Figure 3.6 G). The activation in shoots was slower (started at 3 h), at lower levels, but lasted longer (until 96 h of stress) as compared to that in root (Figure 3.6 I).
Together, this investigation showed that TlOsm gene expression is sharply activated at early stages of osmotic stress (cold, drought, and salinity) in both roots and shoots of T. loliiformis. In plant recovery from all four types of abiotic stresses, the expression of TlOsm remained unchanged as compared to pre-stress levels for both roots and shoots.
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Figure 3.6 Expression of TlOsm under developmental stages and various abiotic stresses. Type of tissues and stresses are indicated. Sampling time-points during developmental stages expressed as weeks post-germination. Six week old T. loliiformis plants were subjected to cold (4 oC), heat (45 oC), salt (200 mM NaCl) and drought (withholding the water supply from the plants) stresses. The transcript expression levels were determined by RT-qPCR and normalized to the Actin and Ubi endogenous controls. Values represent means + SE of three biological replicates x 3 technical replicates (* indicates significant differences at P ≤ 0.05). Sequencing data from RT-qPCR products of the highest, medium, and lowest expression levels confirmed single product of TlOsm.
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3.3.3 TlOsm localises to the plasma membrane To gain insights into the function of TlOsm, its subcellular localisation was analysed. Predictions by bioinformatics tools suggested membrane localisation for TlOsm (Figure 3.3 B). To validate the subcellular localisation of TlOsm in planta, transgenic tobacco plants stably expressing EYFP-tagged TlOsm were generated and transgenic plants were subjected to confocal laser scanning analysis.
3.3.3.1 Generation of transgenic tobacco stably expressing EYFP-tagged TlOsm TlOsm was tagged with EYFP at its either C- or N-terminus together with EYFP control (vector control, VC), these three gene constructs (Figure 3.1) were stably transformed in N. tabacum by Agrobacterium-mediated transformation using leaf disc method (Clemente, 2006). After 3 cycles of culture in fresh selective media, newly emerging shoots expressing EYFP (Figure 3.7 A) were selected for further regeneration. When plants were fully regenerated, their roots were scanned for the expression of EYFP, which was not seen in WT, to confirm plants expressing EYFP (Figure 3.7 B).
Figure 3.7 Fluorescence-based selection of transgenic tobacco expressing EYFP-tagged TlOsm and VC. A: representatives of newly emerging shoots expressing EYFP selected for regeneration. B: representative of regenerated plant roots expressing EYFP. Type of under- expressing genes are indicated.
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When the EYFP-expressing status of tobacco plants was confirmed, 12 lines with normal-looking morphology transformed with each gene construct and 2 WT plants were selected for PCR analysis of transgene presence. The presence of DNA in rapid-released DNA samples were confirmed by using the Musa 18Sr primers in PCR reactions. All 38 samples showed the presence of genomic DNA, including 12 TlOsm:EYFP plants (Figure 3.8 A), 12 EYFP:TlOsm plants (Figure 3.8 B), 12 EYFP plants (Figure 3.8 G) and 2 WT plants (Figure 3.8 A & B). The presence of TlOsm gene in the plants transformed with EYFP-tagged TlOsm was shown in Figure 3.8 C & E. Similarly, the presence of EYFP gene in EYFP expressing plants but not in WT plants was confirmed (Figure 3.8 D, F & H).
Figure 3.8 Confirmation of stable transgene integration in transgenic tobacco by PCR. The presence of DNA in rapid-released DNA solutions of WT1 and 12 TlOsm:EYFP plants (A) WT2 and 12 EYFP:TlOsm plants (B) and EYFP plants (G). The presence of TlOsm gene in TlOsm:EYFP plants (C) and EYFP:TlOsm plants (E). The presence of EYFP gene in TlOsm:EYFP plants (D), EYFP:TlOsm (F), and EYFP plants (H). ML: molecular ladder, P: positive control-plasmid DNA, N: negative control, Kb: kilo base pair.
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3.3.3.2 TlOsm localised to the plasma membrane in unstressed conditions To examine the subcellular localisation of TlOsm, confocal laser scanning microscopy was used for leaf samples of tissue-cultured transgenic N. tabacum plants. As shown in Figure 3.9, in the EYFP-tagged TlOsm plants, the fluorescence was surrounding the cell borders of leaf cells. However, in N. tabacum cells expressing EYFP alone, the fluorescence was distributed throughout the cell.
Figure 3.9 Cellular localisation of TlOsm. A: leaf tissues expressing EYFP, B: leaf tissues expressing TlOsm:EYFP, C: leaf tissues expressing EYFP:TlOsm. The wavelengths captured the images are indicated. Fitc light channel captures the EYFP fluorescence, Cy5 light captures red fluorescence of chlorophyll (where green autofluorescence emitted), bars 10 µm.
To confirm the localisation of TlOsm, a positive control for a plasma membrane-localised protein, a fusion construct of AtPIP2 with red fluorescent protein mCherry (Nelson et al. 2007), was agro-infiltrated into leaves of acclimatised transgenic N. tabacum expressing EYFP tagged TlOsm and EYFP control. As shown in Figure 3.10, the EYFP-tagged TlOsm in both C- and N terminus co-localised with
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the plasma membrane protein marker as shown by the overlap of red and yellow fluorescence (Figure 3.10 B & C). The distribution of yellow fluorescence in cells expressing EYFP alone was throughout the cells and the overlap with red fluorescence pattern was not observed (Figure 3.10 A). These results confirmed the localisation of TlOsm to the plasma membrane.
Figure 3.10 Subcellular co_localisation analysis of EYFP-tagged TlOsm and EYFP in N. tabacum. Confocal microscopy images of leaf tissues co-expressing plasma membrane protein tracker AtPIP2A-mCherry with (A) EYFP, (B) EYFP:TlOsm, and (C) TlOsm:EYFP are shown. Images taken under Fitc light channel (488nm) captured green and EYFP fluorescence, Tritc (561 nm) captured plasma membrane tracker AtPIP2A-mCherry (and some photosynthesis pigments as well), Cy5 (668 nm) captured red fluorescence of chlorophyll (where auto-fluorescence and photosynthesis pigment emitted). Bars 10µm. 3.3.3.3 Localisation of TlOsm remains unchanged under salinity stress It has been evidenced that some stress-responsive proteins containing SUMOylation motifs translocate during stress conditions in order to perform their functions (Johnson, 2004). Two SUMOylation motifs were predicted to be present in TlOsm AA sequence, suggesting that TlOsm protein might translocate under stress conditions. To determine if TlOsm localises differently under unstressed and stressed
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conditions, tissue cultured plants expressing EYFP, EYFP:TlOsm, and TlOsm:EYFP were stressed by culture in liquid medium supplemented with 150 mM NaCl for 24 h. Then, roots of these plants were subjected to confocal laser scanning analysis. As shown in Figure 3.11, fluorescence distributions in the cells were the same for plants that had undergone unstressed and 150 mM NaCl stress treatments for all EYFP, EYFP:TlOsm, and TlOsm:EYFP samples. The results indicated that localisation of TlOsm was unchanged under salinity stress.
Figure 3.11 Localisation of EYFP-tagged TlOsm and EYFP in transgenic N. tabacum cells under unstressed and 150 mM NaCl stress. Confocal microscopy images of root tissues expressing (A) EYFP, (B) EYFP:TlOsm, and (C) TlOsm:EYFP under unstressed (first column) and 150 mM NaCl stress treatment (the second and third columns). Images taken under Fitc light channel (488nm) captured green and EYFP fluorescence. Bars 10µm
3.3.4 TlOsm, OsOlp1_A and OsOlp1_I differ in active binding residues OsOlp1_A and OsOlp1_I were isolated from drought-tolerant cultivar (Apo) and drought-sensitive cultivar (IR 64) of the stress sensitive species O. sativa. The two genes share 96% similarity in their encoded AA sequences but found differentially expressed upon drought. Thus, their only 10 AA difference must make the differences of their response to drought. To gain insights the functions and mechanisms of TlOsm and possible differences between osmotins from tolerant vs. sensitive species as well
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as from tolerant vs. sensitive cultivars within species in plant abiotic stress response, these two genes were incorporated in all the experiments for validating the role of TlOsm in biological system. Functional predictions for the three proteins were carried out using bioinformatic tools, as described in Section 3.2.4. Some of the characteristics in relevant to stress response of plant genes, which were different among the three proteins, are presented in Table 3.2.
Table 3.2 Characteristics of TlOsm, OsOlp1_A, and OsOlp1_I by functional predictions (numbers indicate the number of binding sites) Characteristics TlOsm OsOlp1_A OsOlp1_I
Plasma ER or Localisation Apoplast membrane chloroplast SUMOylation motifs 2 3 3 Glucan-endo 1,3-beta-D 8 5 2 glucosidase Isoamylase activity 1 0 0 Cellulase activity 1 0 0 Chondroitin AC lyase activity 1 0 0 Beta-fructofuranosidase activity 1 0 0 Serine/threonine type 55 14* 14* phosphorylation residue Tyrosine type phosphorylation 9 1 1 residue (*) the same number of residues but different in one site: Ser142 in OsOlp1_A and Thr144 in OsOlp1_I
The predictions showed the difference in the localisation, SUMOylation motifs, and active binding residues of the three proteins. Glucan hydrolysis and phosphorylation have been proposed to be functions of osmotins in response abiotic and biotic stresses. TlOsm was predicted to have more glucan binding residues and potential phosphorylation sites than 2 rice osmotins. OsOlp1_A has more glucan- binding residues than OsOlp1_I. Even OsOlp1_A and OsOlp1_I has the same number of potential phosphorylation residues, one site was found different in their protein sequences (Appendix B-Figure 1; Appendix B-Table 1). Four binding residues of the four enzymes (Isoamylase, Chondroitin AC lyase, Cellulase, and Beta- fructofuranosidase) responsible for break down carbohydrate into small sugar molecules such as monosaccharide or disaccharide only present in TlOsm (Appendix
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B-Figure 2). These differences may provide the key mechanism in the functions of these osmotins.
3.4 DISCUSSION
Osmotins and OLPs belong to the pathogenesis-related PR-5 family and have been shown to be a key protein associated with osmotic adjustment in plants. Large numbers of osmotins and OLPs have been characterised from diverse plant species. In addition, numbers of transgenic crops expressing osmotins and OLPs have demonstrated enhanced tolerance to abiotic and biotic stresses (D'Angei and Altamura, 2007; Goel et al., 2010; Subramanyam et al., 2011; Subramannyan et al., 2012; Patade et al., 2013). However, no osmotin from a desiccation tolerant species such as the resurrection plant T. loliiformis has been characterised. Resurrection plants possess a unique ability to tolerate severe water deficit in vegetative tissues and represent a potentially rich source of genes conferring tolerance to abiotic stresses (Mundree et al., 2002; Ingle et al., 2007; Williams et al., 2015; Karbaschi et al., 2016). In this study, we characterised an osmotin gene from T. loliiformis. The common and novel characteristics, transcriptional expression profile under various developmental stages and abiotic stresses, and the subcellular localisation of TlOsm were revealed. In addition, the predictions on proposed functional characteristics of TlOsm were made and compared with two rice osmotin genes, which were further incorporated in functional validation of TlOsm. Results from this study suggest the involvement of TlOsm in plant response to multiple stresses including cold, drought and salinity.
3.4.1 TlOsm is a member of osmotins and OLPs Osmotins and OLPs have been characterised in many monocotyledonous and dicotyledonous plant species. Thus, a large number of partial and complete sequences of osmotin are available in the NCBI database. A BLAST search of the database revealed that the AA sequence of TlOsm has high similarity to osmotins and OLPs at its 26-252 AA sequence only. TlOsm has the conserved characteristics of an osmotin or OLP such as 16 cysteine residues that form 8 disulfide bonds, N-terminus signal peptide, and a protease cleavage site. However, the alignment of TlOsm AA sequence with other five osmotins that were well characterised and validated to have roles in plant stress tolerance revealed the identities up to 54% (Figure 3.2). Hydrophobic nature, which has shown in common of an osmotin and made it difficult for
Chapter 3: Molecular Characterisation of TlOsm, an Osmotin from Tripogon loliiformis 83
recombinant osmotin production, was also shown in TlOsm (Figure 3.3). Phylogenetic analysis describing the relationship between TlOsm with 39 other osmotins from monocots and dicots showed that TlOsm has close genetic relationship to major group of osmotins from monocots and closest to the osmotins of Setaria italica (Figure 3.4). These results demonstrated that TlOsm is a member of osmotins and OLPs, has close genetic relationship to monocotyledonous osmotins, but has a non-homologous C-terminal sequence of about 50 AA.
3.4.2 TlOsm is involved in osmotic stress response of T. loliiformis plants Plant osmotin genes have been shown to be induced by at least ten abiotic and biotic stimuli (Raghothama et al., 1993). Osmotin was primarily named on the basis of its activation upon osmotic stress response (Singh et al., 1985). Results from this study showed that TlOsm was induced by cold, drought and salinity stresses. Transcriptional profiling of TlOsm under major abiotic stress and during developmental stages suggested the involvement of TlOsm in osmotic stress tolerance. TlOsm was up- regulated sharply in both roots and shoots at early stages of cold, drought, and salinity stress exposure. The gene was activated at highest levels within 1 - 3 h upon cold stress, at 80%-60% of leaf RWC in drought stress, and at 1 – 3 h in roots to 3 - 6 h in shoots upon salinity stress exposure (Fig. 2 E - J). High salt levels cause plant stress in two phases, osmotic stress at early phase and ion stress at later phase (Munns and Tester, 2008). TlOsm expression levels were reduced sharply in shoots and to the levels of unstressed in roots only after 12 h from the onset of NaCl stress, suggested that TlOsm is not directly involved in ion stress mechanism. In heat stress, TlOsm expression remained unchanged in roots but was down-regulated in shoots during the first 12 h of stress. While the direct evidence in regulating stomata has not been reported for osmotin, the main different responses of plants to osmotic stress and heat stress are the regulation of stomata. One of the responses of plants to osmotic stress is stomatal closure to reduce water loss, while in heat stress stomata are open to reduce heat (Mittler, 2006). It could be the reason that the expression of TlOsm connected to stomatal closure generating no advantage for leaf response to heat stress, resulted in the reduced TlOsm expression in shoots during heat stress. During the recovery from each of the four stresses, TlOsm expression levels were not different with those of before stress. This indicated that the gene does not play a role in plant recovery. During the course of development, the TlOsm expression remained unchanged except a slight
84 Chapter 3: Molecular Characterisation of TlOsm, an Osmotin from Tripogon loliiformis
increase at 6 weeks in roots. Although osmotin was found to express at basal levels in the cells that were not exposed to osmotic stress (Singh et al. 1985), the involvement of osmotin in plant development has not been reported so far. T. loliiformis plants had maximum density at this stage might consume more water that could generate the temporary water deficits in root environment at the time of sampling and might be the reason for this increase of TlOsm transcripts.
The expression levels of TlOsm upon stresses were found much higher than other characterised osmotins. It is difficult to make a comparison among studies because different methods were used to monitor the gene expression in the reports. However, if the comparison made by measuring mRNA using RT-qPCR, the expression levels of TlOsm by stress stimuli were by far higher. For example, strawberry FaOLP was induced up to 40 fold upon salicylic acid (Zhang and Shih, 2007). Similarly, PhOsm from Petunia were induced 40-80 fold by salt, wounding, jasmonic acid and salicylic acid (Kim et al., 2002). In this study, TlOsm was up-regulated a thousand fold in shoot after 1 h exposure to cold (Figure 3.6 E), in roots exposed to 200 mM NaCl (Figure 3.6 J) for 1 h or drought at 70% leaf RWC (Figure 3.6 H). It is not known if very high expression level of a gene upon stress would provide additive advantages for stress resilience in plants, the noticeably high expression levels of stress- responsive genes under drought were also found in other resurrection plants such as Haberlea rhodopensis (Gechev et al., 2013) and Craterostigma plantagineum (Rodriguez et al., 2010) by transcriptome analysis. It has been suggested that genes activated rapidly upon stress stimuli are involved in stress signalling while those activated later during the course of stresses are involved in adaptation (Zhu, 2016). In addition, there are some existing convergences among signal transduction pathways of different stress stimuli that help plants induce similar responses to a wide range of stresses and develop cross-tolerance to various stresses (Qin et al., 2011). TlOsm was sharply induced by a broad range of abiotic stress and at early stage of stress duration implies that the gene plays a positive role in plants stress response and might be involved in stress signalling pathway.
3.4.3 TlOsm localises to the plasma membrane regardless of stress condition In subcellular localisation analysis of TlOsm, the stable expression of EYFP- tagged TlOsm and EYFP control in tobacco was chosen for more convenience and facilitating analysis of plants undergone stress. The fluorescent signal in transgenic samples was critical for the detection of TlOsm localisation. Thus, the selection of tobacco plants for regeneration was based on the EYFP expression. When the stable
Chapter 3: Molecular Characterisation of TlOsm, an Osmotin from Tripogon loliiformis 85
integrations of the transgenes were confirmed, all the obtained transgenic plants showed EYFP expression. This selection basis had more advantages for localisation analysis of transgenes in transgenic plants because it eliminates the case of transgene silencing. All the transgenic tobacco lines regenerated from this experiment had strong EYFP fluorescence signal that made it easier for TlOsm localisation analysis.
Plant osmotins have been shown to localise to different cellular compartments including chloroplast, endoplasmic reticulum, plasma membrane, and vacuole. The in situ localisation analysis showed that TlOsm is in the secretory pathway (SMART program), and with a transmembrane binding domain, plasma membrane was predicted to be its destination. The evidence here revealed by confocal analysis either on roots or leaves, tissue-cultured or acclimatised plants, plants undergone unstressed or stress conditions constantly indicated that TlOsm localises to the plasma membrane. Memsat server predicted a transmembrane fragment in TlOsm sequence (Figure 3.3 B), which is homologous to those of major facilitator superfamily (MFS) membrane transporters, suggesting this sequence responsible for the plasma membrane localisation of the TlOsm protein. Despite the presence of two SUMOylation motifs in TlOsm sequence, the cellular localisation of TlOsm remained unchanged when plants undergone unstressed or stress conditions, suggesting that these motifs do not function in translocation of TlOsm.
It is generally accepted that plasma membrane contains proteins that are fundamental for stress-signal perception and transduction of stress signals into downstream cellular responses. Previous studies have shown that plant osmotin and OLPs are likely within signal transduction pathway of stress response (Abdin et al., 2011; Husani and Rafiqi, 2012; Viktorova et al., 2012). Our results on the plasma membrane localisation and early activation of mRNA in stress response of TlOsm strongly support the functions of TlOsm in stress signalling pathway.
3.4.4 TlOsm has more binding sites typical for osmotins than OsOlp1_A and OsOlp1_I As discussed in Section 1.3, osmotins and OLPs have been considered as crucial mediators of plant response to diverse stresses; and various functions and mechanisms have been suggested for osmotins. The resurrection plants, such as T. loliiformis, implement unique environmental stress response mechanism that enables them to rapidly response to stresses and immediately recover upon the return of favourable
86 Chapter 3: Molecular Characterisation of TlOsm, an Osmotin from Tripogon loliiformis
conditions (refer to Section 1.4). To investigate whether proteins from T. loliiformis have evolved unique characteristics contributing to additional level of stress tolerance, as compared to their desiccation sensitive counterparts, the comparison among TlOsm OsOlp1_A and OsOlp1_I were made based on functional predictions.
It is generally accepted that the presence of glucan-binding residues around acidic cleft is essential for antifungal activity of PR5 proteins. Osmotins have been thought to use endoglucanase catalytic activity to hydrolyse the fungal cell wall for killing fungi (Mani et al., 2012). The products of glucan hydrolysis were believed to act as osmolytes plants use for osmotic adjustment and organelle membrane formation (Dway and Smille, 1971; Satoh et al., 1976; Lee et al., 2003) but the direct evidence that links endoglucanase catalytic property of osmotins to plant abiotic stress response is still lacking. Functional predictions indicated that TlOsm contains more glucan- binding residues than the two rice osmotins; and the osmotin from rice drought tolerant cultivar also contains more glucan-binding residues than the osmotin from rice drought sensitive cultivar (Table 3.2). Hence, this predicted feature may represent the important clues insight the mechanism of these osmotins in plant stress response. Calcium-signalling and MAPK cascades represent the core plant stress-signalling pathways mainly regulated by CDPKs and MAPKs (Mohanta and Sinha, 2016; Zhu, 2016). The common features of CDPKs and MAPKs are the phosphorylation activities. Some pathways involving CDPKs and MAPKs were found to regulate crosstalk between abiotic and biotic stress and function in multiple stress responses of plants (Mohanta and Sinha, 2016). Osmotin has been shown to interfere calcium signalling for enhancing cold stress tolerance in olive tree (D'Angei and Altamura, 2007). It has been demonstrated that tobacco osmotin triggered an AMP kinase pathway in yeast and mammalian cells (Narasimhan et al., 2005). These observations suggested that the function of osmotin involving kinase activities. Predictions on phosphorylation activities showed that both serine/threonine type and tyrosine type are present in TlOsm and rice osmotins, OsOlp1_A and OsOlp1_I, but the number of potential phosphorylation sites of both types in TlOsm is significantly higher (Table 3.2). Accumulation of small sugar molecules such as sucrose, trehalose, and raffinose at remarkably high levels in vegetative tissues has been proven to be unique in desiccation tolerant plants for effective cellular protection during dehydration (Alpert and Oliver, 2002; Dinakar and Bartels, 2013; Gaff and Oliver, 2013). Such small sugar
Chapter 3: Molecular Characterisation of TlOsm, an Osmotin from Tripogon loliiformis 87
molecules was thought to protect the cells by maintaining hydrophilic interactions in the membrane and proteins during dehydration and by vitrification of cytoplasm of dry cells (Alpert and Oliver, 2002). Structural-functional prediction by ITASSER showed that four binding sites of four different enzymes catalysing the reactions for breaking down the high molecular weight sugar into smaller molecules are present only in TlOsm, not in the two rice osmotins (Table 3.2). It has been known that predicted information only can be used as reference for supporting biological experiments, but these predictions revealed the common and unique functional characteristics of TlOsm in comparison to the two rice osmotins. These functional predictions might provide some clues for investigation and validation the role of TlOsm in plant stress response. The correlation between predicted and actual functions of TlOsm can only be proven by experimental evidence.
In summary, research in this chapter revealed the conserved and novel characteristics of TlOsm. In addition, the predicted functional features of TlOsm were compared to those of two rice osmotins, which were found differentially expressing upon drought stress. Sequence analysis affirmed TlOsm as an osmotin with all conserved characteristics and a close genetic relationship to monocotyledonous osmotins and pointed out the presence of a non-homologous sequence at its C-terminus. Transcriptional expression profile of TlOsm upon major abiotic stresses and developmental stages indicated its involvements in cold, drought and salinity stress response of T. loliiformis. Subcellular localisation analysis confirmed the plasma membrane localisation of TlOsm and supported its possible function in stress signalling. Functional predictions with respect to plant stress response suggested it functions in both abiotic and biotic response with more functional active elements than the rice osmotins. However, the involvement of TlOsm in mediating plant stress response and the characteristics revealed in the research need to be further investigated and validated. Studies in the next objectives will focus on elucidating the roles of TlOsm in abiotic stress response. The two rice osmotin genes, OsOlp1_A and OsOlp1_I, were incorporated throughout the experiments for comparison with TlOsm. This elucidation was done by investigating the role of TlOsm in abiotic stress response of transgenic rice, identifying interactive protein partners of the three osmotins and pathways involving them, and validating physical interactions of the osmotins with other stress-responsive proteins in planta.
88 Chapter 3: Molecular Characterisation of TlOsm, an Osmotin from Tripogon loliiformis
Chapter 4: Generation of Transgenic Rice Constitutively Expressing Oryza sativa and Tripogon loliiformis Osmotins
In the previous chapter, the conserved and novel characteristics of TlOsm were described. Transcriptional expression analyses indicated the role of TlOsm in T. loliiformis response to cold, drought, and salinity stresses. The subcellular localisation analysis revealed that TlOsm is a plasma membrane protein. Functional prediction of TlOsm compared with two rice osmotins provided some insights into their differential active binding residues, which could be useful for understanding the functions and stress response mechanisms of these osmotins. The suggested information and predicted functions of these osmotins need to be elucidated in biological experiments. Generation of transgenic plants is a critical step to study the functions of transgenes in plant system. This chapter outlines the methods used to develop and characterise transgenic rice plants expressing osmotin genes and a control gene. The outcome transgenic plants from this chapter were used for experiments in Chapter 5.
4.1 INTRODUCTION
Rice is among the most important cereals with more than a half of the world population reliant upon it as a staple crop. During the last few decades, abiotic stresses such as drought, salinity, and extreme temperature have represented the most important factors limiting rice production (Das et al., 2015; Mohanty et al., 2013; Tripathi et al., 2012; Wani and Sah, 2014). Among cereals, rice is the most sensitive crop to drought, salinity, and extreme temperature. For instance, rainfed rice cultivation which accounts for 45% of global production has been substantially affected by drought (Wani and Sah, 2014). The 2002 drought in India affected 55% of country area and 300 million people, reduced rice production by 20% inter-annual baseline trend (Pandey and Bhandari, 2007). Salinity is the second most prevalent abiotic stress limiting rice production with approximately 30% of rice cultivation regions containing salt levels higher than threshold for normal rice yield (Das et al., 2015; Singh et al., 2010; Wani and Sah, 2014). The reduction of rice yield under salt-affected soil was estimated to be 68% (Naheed et
Chapter 4: Generation of Transgenic Rice Constitutively Expressing Oryza sativa and Tripogon loliiformis Osmotins 89
al., 2007). Similarly, in temperate areas, rice production is severely declined by cold stress (Zhang et al., 2014). Rice plants expose to cold stress during seedling stage display poor establishment, delayed growth and ununiformed maturation (Kim et al., 2012); if cold occurs during the reproductive stage, complete yield loss may occur (Powell et al., 2012). Therefore, rice is an ideal plant for study toward understanding the effects of abiotic stress tolerant traits.
Given its importance in global agriculture, countless attempts have been made to improve abiotic stress tolerance in rice. Conventional rice breeders have screened existing stress tolerant cultivars and made genetic alterations that have resulted in commercial cultivars adapting to a wide range of environments of rice ecosystems (Das et al., 2015; Sankar et al., 2011; Swamy and Kumar, 2013). The utilisation of molecular marker-assisted breeding techniques has contributed to significant progress in breeding programs, resulting in the generation of a number of current commercial stress tolerance cultivars. For example, combination of major-effect QTL for grain yield under drought into conventional breeding lines have generated drought tolerant rice cultivars that gained an increase of 150-500 kg ha-1, account for 10-30% yield advantage over parental genotypes (Swamy and Kumar, 2013). Similarly, the mutagenesis-induced VTL5 cultivar was developed and recommended for commercial cultivation in the coastal ecosystem of Kerala (Shylaraj and Sasidharan, 2005). The low success of rice breeding for abiotic stress tolerance through crossing was mainly due to (1) incompatibility between subspecies (Guo et al., 2016); (2) the low levels of stress tolerant traits present in existing compatible species (Singh et al., 2008); (3) the yield drag associated with conventional breeding (Peng et al., 2009; Sankar et al., 2011); and (4) a lack of understanding of the complex genetics underlying stress tolerance (Singh et al., 2008). Genetic engineering addresses many of the challenges associated with the development of tolerant rice varieties by breeding and is now considered an attractive option for developing abiotic stress tolerant rice. Genetic engineering has been used to develop abiotic stress tolerant rice with promising results at the glasshouse scale (Babu 2010; Das et al. 2015; Sankar et al. 2011; Singh et al. 2008; Swamy and Kumar 2013; Wani and Sah 2014). Hence, rice represents a suitable crop plant for engineering stress-responsive traits. Besides improvement of agronomic traits, transgenic plants have offered informative means for studying the functions and regulations of biochemical, physiological, and developmental processes (Hansen and
90 Chapter 4: Generation of Transgenic Rice Constitutively Expressing Oryza sativa and Tripogon loliiformis Osmotins
Wright, 1999; Ziemienovicz, 2014). Therefore, generation of transgenic rice expressing stress-responsive genes is critical for gaining knowledge in the functions and regulations of the transgenes affecting rice stress tolerance.
Several strategies have been suggested for the effective improvement rice with enhanced abiotic stress tolerance via genetic engineering. These strategies include the use of genes from stress tolerant species as well as the use of key regulators of multiple stress tolerant trait (Das et al., 2015; Singh et al., 2008). It is believed that genes from tolerant species would introduce additional tolerant effects that enable rice plants withstand more extreme stress conditions. In addition, the key regulator would provide rice more effective response to multiple stresses. In previous study, an osmotin gene (TlOsm) from desiccation tolerant plant T. loliiformis was characterised and demonstrated to have role in T. loliiformis response to multiple stresses including cold, drought, and salinity stresses. A comparison on functional sites of TlOsm with those of two rice osmotins suggested some potential differential functions in regulating stress response among three osmotins. To understand the functions these osmotins and to determine if more functional sites of TlOsm would bring advantage effects to enhanced plant stress tolerance compared with osmotins from sensitive species, we need to develop transgenic plants expressing the three osmotin genes.
The aim of this study was to develop transgenic rice plants constitutively expressing the three osmotins and control gene for further experimental investigations. With the availability of transformation protocols for rice, the specific objectives of this study were set as follow:
1. Transform Nipponbare rice embryogenic calli with OsOlp1_A, OsOlp1_I, TlOsm and UidA genes. 2. Generate for each gene about 10 independent transgenic rice lines. 3. Confirm the stable integration of transgenes in the rice genome and the constitutive expression of the transgenes.
4.2 MATERIALS AND METHODS
4.2.1 Plasmid constructs and Agrobacterium strains Plasmids pYC-OsOlp1_A, pYC-OsOlp1_A, pYC-TlOsm, and pYC-Ubi-Gus (VC) constructed by the methods described in Section 2.2.1 were used for rice transformation. Agrobacterium strain Agl1 was used for carrying these plasmids.
Chapter 4: Generation of Transgenic Rice Constitutively Expressing Oryza sativa and Tripogon loliiformis Osmotins 91
Figure 4.1 presents the T-DNA of these plasmids. Briefly, the target osmotin genes and GUS-reporter gene (UidA) are under driven of the Ubi promoter and the Nos terminator, the selection marker is hygromycin resistant gene (hpt) regulated by the CaMV 35S promoter and the Nos terminator.
Figure 4.1 Schematic diagram of gene expression cassettes for expressing osmotins and GUS-reporter gene (control-VC) in O. sativa. LB: left border, RB: right border
4.2.2 Plant materials and culture media Rice seeds of O. sativa L. spp Japonica cv. Nipponbare propagated and maintained as described in Section 2.1.2.2 were used to induce embryogenic calli as explants for Agrobacterium infection. Media for rice callus induction, transformation, selection, and plant regeneration were the basic N6 medium (Appendix C) added with growth hormones and other supplements depending on the stages of culture (described when appropriate).
4.2.3 Rice callus induction, transformation, selection and regeneration Rice embryogenic callus initiation, transformation and regeneration process followed the protocol established by Khanna and Raina (1999) with some minor modifications in regeneration step as in Sahoo et al. (2011).
4.2.3.1 Rice callus induction Rice seeds were de-husked, washed 3 times in deionised water, sterilised in 70% ethanol for 1 min followed by 4% sodium hypochlorite for 30 mins in a shaker. Sterilised de-husked seeds were washed 3 times with autoclaved deionised water and 10 seeds were placed on each Petri plate containing callus induction medium (N6 basal
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salts and vitamins supplemented with 60 g L-1 sucrose, 0.3 mg L-1 casein hydrolysate, 0.5 mg L-1 proline, 2 mg L-1 2,4-D, 3 mg L-1 BAP, 0.5 mg L-1 NAA, pH 5.8 and 2.5 g L-1 phytogel). The plates were placed in the dark at 27 oC for 2 weeks. Embryogenic calli induced from scutellum of seeds were isolated and place on Petri plates containing the same callus induction medium and culture conditions for 2 weeks. Then calli were multiplied by frequently subcultured with 2-week intervals.
4.2.3.2 Transformation of rice Four days before transformation, embryogenic calli were selected and transferred onto the same callus induction medium except pH 5.5 with the same culture conditions. These calli were used as target tissues for transformation. Agrobacterium tumefaciens strain Agl1 separately carrying pYC-OsOlp1_A, pYC-OsOlp1_I, pYC- TlOsm, and pYC-Ubi-GUS stored in glycerol was used for transformation. Four days prior to transformation, Agrobacterium from glycerol stocks was grown in LB liquid medium containing 50 mg L-1 of kanamycin and 25 mg L-1 of rifampicin in a shaking incubator at 28 oC, 200 rpm for 40 h to get maximum density. Cultures were then transferred to a large volume of growth medium and grown for a further 16 h. On the day of transformation, Agrobacterium cultures were grown in medium containing 200 mM glucose and 200 µM acetosyringone to activate virulence of Agrobacterium. Rice calli were heat shocked by placing in a water bath at 45 oC for 5 min then placing in a fridge at 4 oC for 30 min. Heat-shocked calli were immersed in activated Agrobacterium suspension, centrifuged for 10 min at 1000 rpm, then inoculated for 30 min in the hood, and decanted. The decanted calli were inoculated for 3 days at 25 oC in Petri plates containing 30 mL of MS medium. Infected calli were washed 4 times with liquid medium (N6 basal salts and vitamins containing 200mg L-1 timentin) by submersing in liquid medium for 1h per each wash with shaking at 100 rpm, then blotting on sterile towel paper. Ten clumps of washed calli were cultured on solid first selection medium (callus induction medium containing 200 mg L-1 of timentin and 25 mg L-1 of hygromycin). Plates were placed in the dark at 27 oC for 2 weeks. A total of 4 batches of transformation was done in this study (2 batches in 4 week calli, 1 batch in 6 week calli, and 1 batch in 8-week calli).
4.2.3.3 Selection and regeneration of putative transgenic rice plants Transformed calli from the first selection medium were sequentially sub- cultured for 3 times with 2-week intervals on second selection medium (the first
Chapter 4: Generation of Transgenic Rice Constitutively Expressing Oryza sativa and Tripogon loliiformis Osmotins 93
induction medium but hygromycin increased to 50 mg L-1). Only calli strongly proliferating on selection medium were selected for regeneration. Single clump of selected calli was cultured on each plate containing 30 mL of first regeneration medium (N6 basal salts and vitamins supplemented with 30 g L-1 sucrose, 0.1 mg L-1 casein hydrolysate, 0.5 mg L-1 proline, 2 mg L-1 kinetin, 3 mg L-1 BAP, 0.2 mg L-1 NAA, pH 5.8, 10 g L-1 agarose, 200 mg L-1 of timentin and 25 mg L-1 of hygromycin) and cultured under the light at 25 oC for 3 weeks. Then, somatic embryos were transfer onto plates containing 30 mL of second regeneration medium (N6 basal salts and vitamins supplemented with 30 g L-1 sucrose, 0.1 mg L-1 casein hydrolysate, 0.5 mg L-1 proline, 2 mg L-1 kinetin, 3 mg L-1 BAP, 0.1 mg L-1 NAA, pH 5.8, 10 g L-1 agar, 200 mg L-1 of timentin and 25 mg L-1 of hygromycin) and cultured under the light at 25 oC until shoot formation. Shoots were selected and rooted in 250-mL pots containing 80 mL of rooting medium (half strength N6 basal salts and N6 vitamins supplemented with 10 g L-1 sucrose, 0.1 mg L-1 casein hydrolysate, 0.5 mg L-1 proline, 2 mg L-1 kinetin, 1 mg L-1 BAP, 0.2 mg L-1 IAA, pH 5.8, 9 g L-1 agar, 200 mg L-1 timentin and 25 mg L-1 hygromycin). Plantlets from each plate were cultured in two pots, one pot with the best plantlet for confirming the transgenic status, the other containing the rest of regenerated plantlets as a back-up. Until the transgenic status was confirmed by PCR, the confirmed transgenic plantlets were sub-cultured in 500- mL pot containing 150 mL of rooting medium and samples were taken from these plants for RT-PCR to confirm transcriptional expression of the transgenes. Then the transgenic plants were in vitro multiplied in 500-mL pots containing 150 mL rooting medium without growth hormone and hygromycin. A similar process was concurrently used to generate wild-type (WT) plants. However, Agrobacterium was not included in the inoculation medium for WT callus and hygromycin was excluded in selection, regeneration, and rooting medium for WT.
4.2.4 Characterisation of transgenic rice plants 4.2.4.1 PCR analysis To confirm the presence of transgenes in putative transgenic lines, PCR analyses were performed using gene specific primers of the target genes, hygromycin resistant gene specific primers, and virC gene primers (Table 4.1). Genomic DNA from independent putative transgenic lines and wild-type control was extracted from 100 mg fresh rice leaf tissue using the DNeasy Plant Mini Kit. The plasmids used to
94 Chapter 4: Generation of Transgenic Rice Constitutively Expressing Oryza sativa and Tripogon loliiformis Osmotins
transform rice were used as positive control. PCR analyses were carried out in a 20-µl reaction mixture containing 10 µl of 2 x Gotaq green (Promega), 0.5 µl of each forward and reverse primers, 100 ng of genomic DNA, and nuclease-free water up to 20 µl. PCR was conducted in a Peltier Thermal Cycler following the previously-optimised temperature procedure for each pair of primers (Table 4.1). The PCR products were separated on 1% agarose gel by electrophoresis. Details of reagents and methods for DNA extraction, qualification, and quantification, PCR and agarose gel electrophoresis are described in Section 2.2.2.
Table 4.1 List of primers used for characterisation of transgenic plants
Gene Primer sequence (5’-3’) Annealing Amplicon Temperature (oC) size (bp) (i) For presence of transgenes in transgenic plants by PCR OsOlp1_A GTTGGGCGGTCGTTCATTCG 54 445 CGACCAGAGAAGCAGCTTGGTCTAATC OsOlp1_I GTTGGGCGGTCGTTCATTCG 54 443 ACCAGGAGAAGCAGCTTGGCAG TlOsm GGATCCATGGCGAGATTACGAGGGGCTG 58 754 AGGTGATGGCGTAGGTGGTGT UidA GTTGGGCGGTCGTTCATTCG 52 731 GTAACGCGCTTTCCCACCAACGC HygR ATGCTTTGGGCCGAGGACTG 54 487 TACTCTATTTCTTTGCCCTCGGACG VirC GCCTTAAAATCATTTGTAGCGACTTCG 57 738 TCATCGCTAGCTCAAACCTGCTTTCTG (ii) For transcriptional expression of transgenes in transgenic plants by RT-PCR OsOlp1_A GGATCCATGGGATTAGACCAAGCTGC 54 747 GTGGCAGAAGATGAC OsOlp1_I GGATCCATGGCTTCTGCCAAGCTG 54 747 GTGGCAGAAGATGAC TlOsm GGATCCATGGCGAGATTACGAGGGGCTG 58 754 AGGTGATGGCGTAGGTGGTGT UidA TGAACATGGCATCGTGGTGA 50 500 GCTAACGTATCCACGCCGTA Musa 18Sr CATCACAGGATTTCGGTCCT 56 507 AGACAAATCGCTCCACCAAC
Chapter 4: Generation of Transgenic Rice Constitutively Expressing Oryza sativa and Tripogon loliiformis Osmotins 95
4.2.4.2 RT-PCR analysis RT-PCR analysis was performed to confirm the transcriptional expression of transgenes in transgenic rice lines. Total RNA was isolated from 100 mg leaves of each transgenic rice line or WT using the RNeasy Plant Mini Kit following manufacturer’s protocol. Genomic DNA in the total RNA samples was eliminated by using the RQ1-RNase_Free DNase as per manufacturer’s protocol. The complete elimination of genomic DNA in the RNA samples was confirmed by PCR reactions with Musa 18Sr housekeeping gene primers (Table 4.1) and RNA samples as templates. cDNA was synthesized from total RNA using the SuperScriptTM III First- strand synthesis system for RT-PCR according to the manufacturer’s instruction. The cDNA samples of transgenic and 2 WT plants were confirmed by PCR reactions with the Musa 18Sr primers. The partial sequences of the transgenes were amplified from corresponding cDNA samples using gene specific primers, Platinum® Taq DNA Polymerase high fidelity kits (Invitrogen) and previously-optimised temperature procedure. The RT-PCR products were separated on 1% agarose gel by electrophoresis. Details of reagents and methods for RNA extraction, qualification, and quantification, RT-PCR reactions and agarose gel electrophoresis are described in Section 2.2.2.
4.2.4.3 Histochemical GUS assay Histochemical GUS assays were performed on rice calli and plants transformed with plasmid control, the pYC-Ubi-GUS. Transformed calli after 9-week selection were immersed in a GUS staining solution containing 100 mM phosphate buffer (pH 7.0), 10 mM EDTA, 1mM potassium ferriccyanide, 0.1% Triton X-100, and 2 mM 5- bromo-4chloro-3-indolyl-β-D-glucuronide. The calli in the GUS staining solution were then vacuum infiltrated for 10 min and incubated overnight at 37 oC. The staining solution was removed and calli were washed and reimmersed in 75% ethanol. Calli were viewed with a Zeiss Steri-2000-C stereomicroscope and images were acquired with a Digital microscope camera Progress®C5 (Jenoptic, Germany). The same GUS stain protocol was applied for transgenic T0 plants and images were captured by a Canon camera.
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4.3 RESULTS
4.3.1 Callus induction, transformation, selection and regeneration of putative transgenic rice plants Genetic engineering has become a great avenue to modify crops with desired traits and to provide solutions to gain an understanding of the functions and regulations of foreign genes in plants. The combination of genetic engineering and conventional breeding has made it possible to incorporate the important traits encoded by exogenous genes into commercial crop cultivars, which has overcome the existing species barrier faced by conventional breeding. Moreover, transgenic plants have provided informative means for understanding the functions and regulations of biochemical, physiological, and developmental processes modulated by a foreign gene (Hansen and Wright, 1999; Ziemienovicz, 2014). Therefore, generation of transgenic rice plants expressing the target osmotins is critical for gaining knowledge in the functions and mechanisms of the three osmotins in regulating abiotic stress response of rice.
Among the methods developed for genetic engineering, Agrobacterium- mediated transformation has been considered as a method of choice thanks to its ability to transfer a defined DNA fragment (T-DNA) into plant genome; and low copy number of T-DNA integrated in plant chromosomes (Gelvin, 2003; Tzfira and Citovsky, 2006). The plant transformation would not have achieved such progress without the success in plant tissue culture, in which plants can regenerate from various types of initial explants. Somatic embryogenesis has been shown to be a preferred method for developing transgenic plants because plants regenerated from single cell origin that can eliminate problems associated with chimeras (Deo et al., 2010). Embryogenic calli induced from scutellum of mature seeds were reported to be the best explants of rice transformation due to the high transformation efficiency and the availability of initial explants (Hiei and Komari, 2008).
In this study, the transgenic rice expressing three osmotins and a GUS-reporter gene were generated by transformation of calli produced from mature seeds of the rice Nipponbare cultivar using Agrobacterium carrying each of the plasmid described in Section 4.2.3. Generally, explants underwent the process as described in Figure 4.2.
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Figure 4.2 Procedure of rice callus induction, transformation, selection, and plant regeneration. A: calli induced from scutellum of mature seeds after 2 weeks in callus induction medium, B: calli at the stage used as explants for transformation, C: representative one plate of transformed calli entered first step of selection, D: transformed callus proliferation after 4 steps of selection, E: transformed somatic embryos germination in selection medium; F: putative transgenic plants regenerated after 7 steps of selection; arrows indicate selected calli and plants.
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Primarily, the transformation experiment was designed to transform calli at 4, 6, and 8 weeks in order to determine if any effect of callus age on transformation efficiency and plant regeneration capacity. Three batches of transformation on calli induced from 3,000 seeds and 1000 callus clumps per each batch underwent 4-5 cycles of selection. However, temperature fluctuation in the tissue culture lab due to the laboratory refurbishment led to heating the culture room that damaged all the embryos and the plantlets from 1-5 weeks in regeneration medium (the same stage in Figure 4.2 D & F). Therefore the forth batches of transformation was carried out on 4-week-old calli. A total of 43 independent lines were regenerated from calli transformed with 4 plasmid constructs.
4.3.2 Confirmation of transgenes in putative transgenic rice lines To confirm the transgenes stably integrated into genome of regenerated plants, genomic DNA was extracted from leaves of each independent line transformed with different constructs and WT plants. These DNA samples were used as templates for PCR. Both selectable marker hygromycin resistant, hpt, and gene-specific primers were used for PCR. In addition, the VirC primers (Table 4.1) were also used for PCR to detect the Agrobacterium residual in order to eliminate the possibility of false positive PCR. The PCR products followed by agarose electrophoresis are presented in Figure 4.3.
All 43 independent lines had the presence of hpt gene because of the presence of the expected 487 bp amplicon when using hpt gene primers in PCR mixtures (Figure 4.3 A, C, E & G). However, one of the 12 lines transformed with pYC-OsOlp1-A did not have the band in agarose gel running PCR product of OsOlp1-A specific primers (Figure 4.3 B). In this particular line, three leaf samples were taken at different times for DNA extractions and PCR reactions, the same results appeared that confirmed the absence of OsOlp1-A gene in this line. All 10 lines transformed with pYC-OsOlp1-I (Figure 4.2 D), 9 lines with pYC-TlOsm (Figure 4.2 F), and 12 lines with pYC-Ubi-Gus (Figure 4.2 H) construct had the presence of expected bands in PCR products using gene specific primes. Each of 43 lines was checked for the presence of Agrobacterium residual by using VirC gene primers. The results showed that none of the lines had the presence of Agrobacterium, suggesting that these bands were the hpt gene and other target genes stably integrated in the genome of these rice lines. The results also showed that 42 of 43 regenerated lines had both hpt gene and target gene insertions.
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Figure 4.3 Characterisation of putative transgenic rice lines by PCR. A: PCR products of putative OsOlp1_A plants with hpt primers and B: with gene specific primers, C: PCR products of putative OsOlp1_I plants with hpt primers and D: with gene specific primers, E: PCR products of putative TlOsm plants with hpt primers and F: with gene specific primers, G: PCR products of putative GUS plants with hpt primers and H: with gene specific primers, I-L: PCR products of putative OsOlp1_A, OsOlp1_I, TlOsm, and GUS plants with VirC gene primers. M: molecular DNA ladder, P: positive control, N: negative control, WT: wild type, Kb: kilo base pair, numbers above each gel indicate the line ID.
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4.3.3 Expression of transgenes in transgenic rice plants confirmed by RT-PCR To confirm the transcriptional expression of the target transgenes in transgenic rice, RT-PCR was used. Forty-four RNA samples were extracted from leaves of 42 transgenic rice lines and 2 WT plants. RQ1-DNase was used to eliminate the DNA contaminated in these RNA samples. Then, PCR with house-keeping gene Musa 18Sr primers was performed to confirm if the genomic DNA was completely removed from RNA samples. Results showed that none of the PCR products from these 44 RNA samples had the presence of 507 bp amplicon, suggesting that these RNA samples were DNA free (Figure 4.4 I-L).
cDNAs were then reverse transcribed from these RNA samples. PCR with house-keeping gene Musa 18Sr primers was again used to confirm if the cDNAs were successfully transcribed from each of RNA samples. The presence of a bright 507 bp band in all cDNA samples from 42 transgenic rice lines and 2 WT plants indicated the presence of cDNA in all the samples (Figure. 4.4 B, D, F & H).
PCR with gene specific primers and cDNA samples of 42 transgenic rice lines and the control were performed by pre-determined annealing temperature for specific pair of primers. Results showed that 11 OsOlp1_A lines (Figure 4.4 A), 10 OsOlp1_I lines (Figure 4.4C ), 9 TlOsm lines (Figure 4.4 E), and 12 UidA (GUS) lines (Figure 4.4 G) had the expected bands, which were the same sizes with corresponding control but absence in the WT and negative control samples. The intensity of RT-PCR products found varying among lines transformed with the same gene suggested that there may be some different levels of transgene expression among the lines. These results indicated that the target transgenes expressed at transcriptional level in all 42 transgenic rice lines.
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Figure 4.4 Transcriptional expression of transgenes in transgenic rice by RT-PCR. A: RT-PCR products of OsOlp1_A plants with gene specific primers and B: with Musa 18Sr primers, C: RT-PCR products of OsOlp1_I plants with gene specific primers and D: with Musa 18Sr primers, E: RT-PCR products of TlOsm plants with gene specific primers and F: with Musa 18Sr primers, G: RT-PCR products of GUS plants with gene specific primers and H: with Musa 18Sr primers, I-L: PCR products of the RQ1-DNase treated RNA samples from OsOlp1_A, OsOlp1_I, TlOsm, and GUS plants with Musa 18Sr primers. M: molecular DNA ladder, P: positive control, N: negative control, WT: wild type, Kb: kilo base pair, numbers above each gel indicate the line ID.
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4.3.4 Expression of GUS protein confirmed in GUS-expressing rice lines. In order to investigate if GUS-reporter gene expresses at protein level in these transgenic rice plants and how the transgene expresses under the regulation of the Ubi promoter, a histochemical GUS assay was conducted on all lines of selective calli after 9 weeks of selection in hygromycin-containing media and regenerated plants. Results showed that GUS expression and activity indicated as blue colour was observed in the entire callus clumps of all lines proliferated after 9 weeks in selective media, while no blue colour observed in the control (Figure 4.5 A). In the plants, a strong GUS activity was detected in all parts of tissues throughout 12 independent transgenic lines at 2 different stages of regeneration but not in the WT control (Figure 4.5 B). Since the GUS gene in pYC-Ubi-Gus had an intron, this expression should not be interfered by Agrobacterium residues that may be attached in rice tissues. GUS-staining results confirmed that GUS gene was constitutively regulated by the Ubi promoter that led to GUS expression at different stages and in all the cell types. Thus, OsOlp1_A, OsOlp1_I, and TlOsm should be regulated in the same manner.
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Figure 4.5 GUS expression in transgenic rice calli and plants. A: GUS expression of representative transgenic rice calli after 9 weeks of transformation and selection in 50 mg L-1 hygromycin – containing media, B: GUS expression of transgenic rice plants; upper row shows plants at 4 weeks regenerated from somatic embryos and lower row shows plants at 8 weeks regenerated from somatic embryos, WT: wild type, numbers indicate the ID of independent transgenic lines.
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Table 4.2 summarises all transgenic rice lines generated from this research and the confirmation of transgene intergration and expression in regenerated rice plants. Generally, among 43 rice lines regenerated from transformation and intensive selection, 42 lines showed the stable integration and expression of the target transgenes. There was a little variation in the number of transgenic lines for each gene with the smallest number of lines expressing TlOsm (9 lines) and the largest number of lines expressing GUS reporter gene (12 lines). The objectives of obtaining about 10 transgenic lines for each gene and the constitutive expression of transgenes in transgenic rice lines were achieved.
Table 4.2 Summary of generating and characterising transgenic rice lines expressing target osmotins and control gene in the research
Plasmid construct N0 of lines PCR (+) result RT-PCR (+) GUS (+) hpt primers Gene specific primers pYC-OsOlp1_A 12 12 11 11 pYC-OsOlp1_I 10 10 10 10 pYC-TlOsm 9 9 9 9 pYC-Ubi-Gus 12 12 12 12 12 Total 43 43 42 42 12
4.4 DISCUSSION
Rice is one of the most important cereal crops and is used as stable food for a large human population worldwide. Besides, rice is a susceptible crop to major abiotic stresses. Thus, rice has been recognised as an attractive crop for intensive studies on genetic improvement of abiotic stress tolerance. Progresses in rice research have brought about numerous methods, protocols for conducting experiments, phenotyping, and genetic engineering; and have updated our understanding on how rice response to environmental stresses (Wani and Sah, 2014; Zhang et al., 2014; Das et al., 2015). Rice research also indicated genetic engineering as a potential approach for improving rice production and enhancing rice tolerance to abiotic stresses (Grover and Minhas, 2000; Wani and Sah, 2014; Ansari et al., 2015). With the estimation of increasing rice cultivation areas affected by future changing climate condition (Jagadish et al., 2011)
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and the needs to increase 60% rice production to fulfil the demand of increasing world’s population by 2020 (Grover and Minhas, 2000), the key factors for sustainably increasing rice grain yield production while minimising effects by environmental stresses needed to be addressed. Hence, rice appears to be an appropriate target crops for expressing and validating the functions of stress-responsive genes in crop plants. In addition, an effective transformation and plant regeneration process plays a key role in the success of functional studies of foreign genes in rice plants.
Agrobacterium-mediated transformation is now a dominant method for plant genetic engineering. However, the efficiency of a transformation protocol depends on many factors such as virulence of Agrobacterium strain, types of initial plant tissues, regeneration capability of target plants, and strength of selectable marker (Tzfira and Citovsky, 2006). Rice has been a favourite cereal crop for genetic studies and protocol for Agrobacterium-mediated transformation has been established and routinely used in many laboratories worldwide. Somatic embryogenic callus is a preferred starting tissues for rice transformation. However, regeneration of transformed calli has been identified as a major obstacle for rice transformation (Sahoo et al., 2011). Moreover, initiation of rice embryogenic calli for transformation is a time-consuming and tedious process. In this study, beside the purpose of obtaining transgenic rice plants for evaluating abiotic stress tolerance, we attempted to investigate the effects of callus stages for transformation on plant regeneration efficiency in order to recommend the best callus stage as target tissues for transformation. However, this objective failed to achieve due to heating in culture room during embryo germination, which is the most sensitive stage to heat, led to most of 300 putative transgenic lines damaged. Nevertheless, 43 independent lines were regenerated (Table 4.2). Hygromycin selection was reported to be very efficient for the selection of transformed rice with the concentration ranged from 20-50 mg L-1 (Zuraida et al., 2013). In this study, transformed calli were first selected in the medium containing 25 mg L-1 of hygromycin, followed by three cycles of selection in 50 mg L-1 of hygromycin; then embryo germination, shooting, and rooting were selected in the medium containing 25 mg L-1 of hygromycin. This selection process resulted in 100% regenerated plants had the hpt gene integration (Figure 4.1) and expression and evidenced by the survival of transgenic plants in the selection media. The results confirm the effectiveness of hygromycin selection marker in rice transformation. Among 43 regenerated lines, one
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line transformed with pYC-OsOlp1_A did not show the presence of the target OsOlp1_A, despite the hygromycin selection marker was detected. Agrobacterium has been used as a method of choice for genetic transformation due to its ability to transfer a well-defined T-DNA fragment (Tzfira and Citovsky, 2006); but in this case it was not known why the T-DNA fragment was truncated. The purpose of this study was to obtain enough transgenic rice lines expressing the target transgenes for further experiments on gene functions. Thus the mechanism by which T-DNA truncated was beyond the objectives of this study and did not get attention.
The choice of an appropriate promoter for driving the target transgenes is another factor needed to be considered in generating transgenic plants. The purpose of this study was to generate transgenic rice plants constitutively expressing the genes of interest and the Zea maize Ubi (ZmUbi or Ubi) promoter was chosen for directing the TlOsm, OsOlp1_A, OsOlp1_I, and UidA. The Ubi promoter was reported to regulate the high levels of constitutive gene expression in rice and other cereal crops (Cornejo et al., 1993; Rooke et al., 2000). This promoter was shown to be active in many cell types and direct the strongest expression in dividing tissues such as young roots and leaves of transgenic rice (Cornejo et al., 1993). Hence, this promoter has been widely used in genetic transformation of monocots. In our study, all 42 transgenic rice lines expressing target genes under the control of Ubi promoter showed the expression of transgenes at transcriptional level (Figure 4.4). Furthermore, the results from the histochemical GUS assay conducted on all lines of selective calli and regenerated plants demonstrated the constitutive expression of GUS-reporter gene in the selected rice lines. The presence of GUS protein and its activity indicated as blue colour were observed in entire callus clumps, while no blue colour observed in the control (Figure 4.5 A) proved the uniform expression of GUS in the callus clumps. In the plants, a strong GUS activity was detected all parts of tissues throughout 12 independent transgenic lines at either 4 or 8 weeks after regeneration but not in the WT control plants, indicating the presence and activity of GUS in all the plant parts at both stages of regenerated plants (Figure 4.5 B). Since an intron was included in the GUS-reporter gene in the pYC-Ubi-Gus plasmid, the presence of GUS should only be the results of GUS expression in rice plants, not of Agrobacterium residues that may be attached in rice tissues. GUS-staining results confirmed that the Ubi promoter used for regulating
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the genes in this study is a constitutive promoter that expresses at different stages and all the cell types. Conclusion: using the established agrobacterium-mediated rice transformation system, total of 42 transgenic rice lines constitutively expressing either OsOlp1_A, OsOlp1_I, TlOsm, or GUS-reporter gene were generated. These transgenic rice lines together with WT will be tested for cold, drought, and salinity stress tolerance in Chapter 5.
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Chapter 5: Comparative Analysis of Transgenic Rice Constitutively Expressing Osmotins from Tolerant and Sensitive Species
Results from Chapter 3 suggested the involvement of TlOsm in Tripogon loliiformis responses to cold, drought and salinity stresses and identified possible functional differences among TlOsm, OsOlp1_A, and OsOlp1_I. Analysis of these differences might provide useful information for understanding the functions of osmotins in plant stress response. In Chapter 4, 42 transgenic rice lines constitutively expressing TlOsm, OsOlp1_A, OsOlp1_I, and the Gus-reporter gene as vector control (VC) were generated together with wild type (WT) control plants. This chapter details the assessment of the transgenic plants expressing TlOsm, OsOlp1_A, and OsOlp1_I for enhanced tolerance to cold, drought and salinity stresses.
5.1 INTRODUCTION
Previous studies have proposed additional advantages of using genes from stress tolerant species for engineering crops with enhanced abiotic stress tolerance (Mittler and Blumwald, 2010; Cominelli et al., 2013). It is believed that such genes would bring to engineered crops additional resilience not observed in parental crops. Thus, naturally tolerant species have great potential for seeking stress-responsive genes for use in improving abiotic stress tolerance in crops. Among stress tolerant species, the Australian-native resurrection grass, T. loliiformis, has great potential as a genetic resource for the identification of stress tolerant genes. T. loliiformis is capable of withstanding desiccation of its vegetative tissues which regain for metabolic function within 24 - 72 h of watering (Karbaschi et al., 2016; Williams et al., 2015). In Chapter 3, an osmotin from T. loliiformis (TlOsm) was identified and demonstrated to play role in T. loliiformis response to salinity, drought, and cold stresses. Comparision of TlOsm amino acid (AA) sequence and predicted structure with those of two osmotins from stress sensitive species, O. sativa, revealed some possible differences in their functions
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(Table 3.2). Two rice osmotins, OsOlp1_A and OsOlp1_I were identified from rice drought tolerant and drought sensitive cultivar, respectively. However, only OsOlp1_A was induced by drought. Comparative analysis of the three protein sequences and structures indicated differences in number of the potential glucan-binding and phosphorylation sites. TlOsm encoded the highest number of both potential glucan- binding sites (8) and phosphorylation sites (64). OsOlp1_A contained five glucan- binding sites while OsOlp1_I encoded two. OsOlp1_A and OsOlp1_I encode the same number of phosphorylation sites (15) but one Ser site in OsOlp1_A is replaced by the Thr site in OsOlp1_I. In addition, TlOsm has four binding sites of four enzymes including isoamylase, cellulase, chondroitin AC lyase and beta-fructofuranosidase that function in breaking high molecular-weight into lower molecular-weight sugars (Table 3.2). The differences in the predicted protein structures of the three osmotins suggest differences in their functions. Here, we hypothesized that proteins with more functional sites would have more functional activities.
Typically osmotins and other PR5 protein structures contain three domains with glucan-binding sites and an acidic cleft (Min et al., 2004). Previous studies have suggested that glucan-binding sites surrounding the acid cleft are essential for the antifungal activities of osmotins (Liu et al., 2010; Mani et al., 2012; Min et al., 2004; Viktorova et al., 2012). How glucan-binding sites contribute to the capacity of osmotins to regulate plant tolerance to abiotic stress however remains to be elucidated. Tobacco osmotin has been demonstrated to activate an AMPK cascade in yeast and mammalian cells (Narasimhan et al., 2001; Narasimhan et al., 2005). In transgenic plants, osmotin functions are linked to MAP kinase activities (Viktorova et al., 2012). The main function of most protein kinases is phosphorylation. These suggest that phosphorylation activities might contribute to osmotin functions. Rohrig et al. (2006) investigated the involvement of phosphorylation during acquisition of desiccation tolerance in resurrection plant C. plantagineum. They showed that at least two LEA proteins CDeT11-24 and CDeT6-19 were transiently phosphorylated during dehydration. Dinakar and Bartels (2013) proposed that the increased phosphorylation activities of these stress-responsive proteins might increase the hydrophilic residues necessary for interaction with macromolecules, which is required for cellular protection during desiccation tolerance. In addition, soluble sugar metabolism and accumulation during desiccation tolerance have been found distinct features of
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resurrection plants for protection of their vegetative tissues from damage. Four functional sites for sugar metabolism were found in the predicted structure of TlOsm, but none of them was found in two rice osmotins. To understand the effects of the three osmotins on enhancing plant abiotic stress tolerance, in relation to their predicted functional binding sites, we developed transgenic plants independently expressing the three osmotins and assessed them for enhanced abiotic stress tolerance.
To gain an understanding insights into the functions of these osmotins in improved rice tolerance to abiotic stress, the physiological and morphological responses of transgenic rice expressing TlOsm, OsOlp1_A, and OsOlp1_I need to be investigated. Moreover, comparative analysis of transgenic rice expressing TlOsm, OsOlp1_A, and OsOlp1_I might reveal any superior role of osmotin from highly tolerance species over those from rice. In this chapter, the response of transgenic rice constitutively expressing TlOsm, OsOlp1_A, OsOlp1_I, and the Gus-reporter gene were comparatively analysed under unstressed, cold, drought, and salinity stresses.
The comparisons were made on T0 generation with stress treatments at seedling stage and on T1 generation with stress treatments at reproductive stage.
The objectives of this study were set as follows:
1. Investigation of physiological response of the T0 and T1 transgenic rice plants exposure to cold, drought and salinity stresses at seedling and reproductive stages.
2. Investigation of morphological response of the T0 and T1 transgenic rice plants exposure to cold, drought and salinity stresses at seedling and reproductive stages. 3. Comparison of the effects of TlOsm, OsOlp1_A, and OsOlp1_I on enhancing rice tolerance to cold, drought, and salinity stresses.
5.2 MATERIALS AND METHODS
5.2.1 Plant materials Nine transgenic lines for each gene construct and the WT were included for evaluation of cold, drought, and salinity stress tolerance at the seedling stage. T0 plants were multiplied and maintained in tissue culture for assessment at seedling stage.
Seeds from T0 plants were harvested from plants grown in controlled glasshouse conditions. T1 plants germinated from seed pools of all available lines were used for
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reproductive stage evaluation and the segregated non-transgenic (NT) plants were used as control.
5.2.2 Acclimatisation of tissue-cultured rice plants Tissue cultured rice plants were acclimatised using 50-mL plastic pots and premium potting mix (Searles, Sunshine coast, Qld, Australia) following the protocol described by Hoang et al. (2014). Plants containing one tiller were transplanted into pots containing potting mix moistened with tap water. Pots were placed in a container filled with tap water to one-third the height of the pots and the container was covered with clear plastic foil and placed in a growth room at 24 oC, day/night cycle of 12 h/12 h, light intensity of 800 ± 100 µmol m-2 s-1, and relative humidity at 65%. Plants were sprayed with water twice a day for seven days and then the plastic foil was removed. Plants were grown for another seven days with water added into the container to cover the height of the pots. After that, Aquasol fertiliser (Yates, Pastow, NSW, Australia) containing nitrogen, phosphorus, potassium and trace elements (N: P: K: 23: 3.95: 14) was added to the water in the container to the concentration of 0.5 g L-1 and plants were grown for another seven days.
5.2.3 Growth conditions and stress treatments at seedling stage Cold, drought and salinity stresses were applied to 3-week post acclimatised plants when three fully expanded leaves had developed and the forth leaf had just emerged. For salinity stress, water in the container was drained out and 100 mM NaCl solution was poured in until the surface of salt solution was 1 cm above the potting mix level. The water level was maintained at this level by adding tap water daily into the container. After three weeks in 100 mM NaCl solution, plants were recovered by removing the salt solution from the container, washing off salt in the potting mix by submerging in water and draining five times. Tap water was added to the containers containing washed pots to the level of 1 cm above the potting mix level. For drought stress, the pots containing plants in water containers were drained off (potting mix saturated with water) and transferred to empty containers. Water was not added to these plants for three weeks. After stress, plants were recovered by adding tap water to the containers at a height of 1 cm above the potting mix. The survival rate was calculated three weeks after recovery for both experiments. In the unstressed experiment, water was maintained daily in the same level of 1 cm above the potting mix level during the course of experiment. Plants were grown in growth chambers
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(Thermoline, Japan) at 27 oC, day/night cycle of 12 h/12 h, light intensity of 800 ± 100 µmol m-2 s-1 and humidity at 65%. For cold stress, 4-leaf-stage plants were divided into two parts and concurrently placed in unstressed (27 oC) and cold stress (10 oC) conditions for 4 weeks. Cold water (10 oC) was added to plants in cold treatment at the same time with tap water added to unstressed plants to replace the evaporated water. After that, temperature in the cold treatment was changed to (27 oC) for plants to recover. The survival rate was calculated three weeks after recovery.
5.2.4 Germination of T1 transgenic rice plants
Seeds harvested from glasshouse grown T0 transgenic rice were dried in an oven at 37 oC for a week and maintained at room temperature for 4-5 months. Seeds from plants transformed with each gene construct were separately placed on paper towels moistened with tap water in a plastic box and the boxes were placed in the dark at room temperature for a week. The germinated seeds were transferred into 50-mL pots containing potting mix moistened with tap water. Pots were placed in a container filled with tap water to one-third the height of the pots and the container was covered with clear plastic foil and placed in growth room at 24 oC, day/night cycle of 12 h/12 h, light intensity of 800 ± 100 µmol m-2 s-1, and relative humidity at 65%. Plants were sprayed daily with water for seven days and then the plastic foil was removed. Plants were grown for another seven days with water added into the container to cover the height of the pots. After that, the Aquasol fertiliser was added weekly to the water in the container to the concentration of 0.5 g L-1 and plants were grown for another 14 days for screening of transgenic T1 plants.
5.2.5 Screening of T1 transgenic rice plants
The T1 transgenic rice plants were screened by PCR for the presence of the transgenes. One leaf from each 2- to 3-leaf stage plants was sampled and subjected for quick-released DNA following the rapid release DNA protocol by Thomson and Henry (1995) as described in Chapter 2 (Section 2.2.2.1). One microliter of each quick- released DNA sample was used as template in a 20 µl PCR mixture with either hygromycin resistant gene primers or gene-specific primers. The PCR products were separated in 1% agarose gels by electrophoresis. Plants that were PCR positive using both hygromycin resistant gene primers and gene-specific primers were considered transgenic. The plants generated a faint band with either primer pairs or both were
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eliminated. The plants negative to both pairs of primers were considered as segregated non-transgenic and used as non-transgenic (NT) control.
5.2.6 Growth conditions and reproductive-stage stress treatments Four weeks post germination and following the confirmation of the transgene, plants of a similar size and stage were selected and transferred into 1.2-L pots containing full volume of potting mix moistened with tap water. At this stage, the selected plants had one tiller and four fully expanded leaves with an immature fifth leaf and plant height varied from 13 to 17 cm. The plants in 1.2-L pots were placed in containers filled with tap water to 1 cm above the potting mix. Containers with plants were placed in a controlled glasshouse at 27 ± 3 oC, day/night cycle of 12 h/12 h, light intensity of 900 ± 100 µmol m-2 s-1, and relative humidity at 65%. Plants were grown for further 14 days with water added daily to maintain the same water levels and Aquasol fertiliser was added weekly to the water in the containers to a concentration of 0.5 g L-1.
Drought and salinity stresses were separately applied to 6-week post germinated plants and concurrently compared with unstressed plants. For salinity stress, water in the container was drained out and replaced with a 100 mM NaCl solution until the solution was 1 cm above the potting mix level. The water level was maintained at 1 cm above the potting mix level by adding tap water daily into the container. After four weeks in 100 mM NaCl, plants were recovered using the method applied for treatment plants at seedling stage. For drought stress, similar method applied for drought treatment and recovery at seedling-stage was used, except for the period of water withholding was 18 days. In the unstressed experiment, water was maintained daily in the same level of 1 cm above the potting mix surface during the course of experiment. For each experiment, 30 plants expressing each gene or NT control were randomly arranged in three replicates. After 28 days, a half of plants per each replicate from all three experiments were randomly selected for dry biomass determination and another half were left for recovery and calculating yield components.
5.2.7 Electrolyte leakage Electrolyte leakage was measured from leaves using a CM 100-2 conductivity meter (Reid and Associates CC, Durban, South Africa) following the manufacturer’s instruction. Briefly, the second youngest fully-expanded leaf was placed in a plastic bag and immediately put on ice. Leaves were washed twice in deionised water and
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blotted dry with paper towel. A 5-cm middle part of each leaf was cut into 0.5 cm pieces, rinsed in deionised water and loaded into wells of the CM 100-2 conductivity meter containing 1.25 ml of deionised water. Each well contained 2 pieces of leaf and 5 wells were used for each leaf as technical replicates. Measurement was carried out every 2 min over a 60 min period. Samples were removed and dried in an oven at 80 oC overnight (until the weight remained unchanged) for measurement of dry weight (DW). Electrolyte leakage was calculated as the slope of electrolyte leakage over time and normalised by DW.
5.2.8 Relative water content determination Leaf relative water content (RWC) was determined using the method described by Lafitte (2002). Approximately 10 cm of leaf was cut off from the middle part of the youngest fully expanded leaf, weighed (fresh weight - FW), and placed in a 15 ml Falcon tube. The tube was kept on ice until it was filled with deionised water and kept in dark at 4 oC overnight. The next morning, the leaf was blotted dry with tissue towel for 30 s and weighed (turgid weight – TW). The samples were then dried in a vacuum oven at 70 oC for 3 days and weighed (dry weight- DW). The relative water content was calculated as RWC (%) = (FW-DW)*100/ (TW-DW).
5.2.9 Plant dry weight determination Plants were sampled in unstressed and stress treatments at the end of treatment periods from transgenic, WT or NT plants for dry weight determination. Six pots per line per plasmid construct were sampled for each type of stress treatment in seedling- stage tested experiments and fifteen plants per plasmid construct were sampled for each type of stress treatment in reproductive-stage tested experiments. The plants in a pot were carefully pulled out along with root and potting mix adhering to the root was removed. Roots and shoots were dried in a vacuum oven at 80 oC for 72 h until the weight remained unchanged. Then the dry weights were determined.
5.2.10 Measurement of photosynthetic parameters Photosynthetic parameters such as net photosynthesis, stomatal conductance, and transpiration rate were measured using a LI-COR Infra-Red Gas Analyser Li-6400 XT (John Morris Scientific, Chatswood, NSW, Australia). Measurements were performed on the second fully expanded leaf at early stage or flag leaf (if available) at day 0, 3, 6, 12, and 18 for drought stressed plants and additional day 21 for salinity
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stressed and unstressed plants. For each data record, nine representative plants for each gene constructs in each experiment were randomly chosen for measurement.
5.2.11 Statistical analysis All experiments were conducted using a randomized complete block design and data were analysed using one-way ANOVA. When ANOVA results showed a significant difference at P ≤ 0.05, the Tukey’s HSD tests were used to analyse the significant differences among each experimental treatment (using Minitab 17 Statistical Software). All graphs and standard errors were prepared using Microsoft Excel. The number of randomly selected samples used to calculate each mean is indicated in each graph.
Table 5.1 details all the experiments conducted in this study to assess the transgenic rice expressing TlOsm, OsOlp1_A, OsOlp1_I, and the Gus-reporter gene together with WT or NT control for enhanced plant tolerance to cold, drought, and salinity stresses.
Table 5.1 A summary of experiments in the study
Seedling stage Reproductive stage
Materials T0 generation, tissue cultured propagation T1 generation, seed propagation
Day 0 plants 1 tiller, 4 leaves, 3-week post acclimatisation 3 tillers, 6-week post germination
Control WT and VC NT and VC Scale Growth chambers Glasshouse
Set 1 Set 2 Experiments Unstressed, drought, Unstressed and cold Unstressed, drought, salinity (100 mM NaCl) salinity (100 mM NaCl)
Stress period 3-week treatment 4-week treatment 18 days for drought 28 days for salinity
Size 9 lines x 15 plants per line 8 lines x 15 plants per line 30 plant per gene construct per gene construct for per gene construct for for each experiment (150 each experiment (675 each experiment (600 plants per experiment) plants per experiment) plants per experiment)
Parameters Shoot growth, tiller Shoot growth, tiller Shoot growth, tiller number, electrolyte number, electrolyte number, electrolyte leakage, RWC, dry leakage, RWC, dry leakage, RWC, dry biomass, survival rate biomass, survival rate biomass, photosynthesis- related parameters, yield components
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5.3 RESULTS
5.3.1 Rice plants constitutively expressing TlOsm or OsOlp1_A maintained growth under cold, drought, and salinity stresses TlOsm was isolated from a drought-induced cDNA library of desiccation tolerant species, T. loliiformis, made at the Centre for Tropical Crops and Biocommodities (CTCB) (Williams, unpublished). OsOlp1_A and OsOlp1_I were identified from drought-tolerant cultivar Apo and –sensitive cultivar IR64, respectively, of the stress sensitive species, O. sativa. The two rice osmotins were differentially expressed upon drought but different from each other in only 10 AA of their protein sequences. Structural-to-functional prediction for the three proteins suggested their functions associated with glucan-binding and phosphorylation sites. As shown in Table 3.2, TlOsm has the highest potential glucan-binding and phosphorylation sites. OsOlp1_A has more glucan-binding sites than OsOlp1_I, five vs. two sites. The two rice osmotins have the same number of phosphorylation sites but one Ser residue in OsOlp1_A is replaced by the Thr residue in OsOlp1_I (Appendix B-Figure 1 and Table 1). Besides, TlOsm has four unique binding sites of the enzymes function in sugar metabolism (Appendix B-Figure 2). To determine whether these glucan- binding sites correlate with improved stress tolerance and if the additional phosphorylation sites and the unique binding sites of TlOsm contribute to stress tolerance, transgenic rice expressing TlOsm, OsOlp1_A and OsOlp1_I were generated and subjected to cold, drought, and salinity stresses. Three type of control plants: vector control (VC), wild type (WT), and non-transgenic (NT) were included in the assessments. The VC plants expressing the Gus-reporter gene (UidA). Similar to T0 transgenic plants, WT plants went through process of callus induction, transformation, selection, plant regeneration, and tissue-culture multiplication, except the presence of Agrobacterium in inoculation media and of Hygromycin in selection media (Chapter 4). The NT plants were the non-transgenic segregation in the same generation with transgenic plants and produced by the same parental plants as transgenic plants. The performance of these plants were assessed based on growth, physiological, and photosynthesis-related parameters, recovery ability, and yield components.
Shoot growth rate is one of the indicators for rice stress tolerance, with higher growth rate under stress associated with higher level of tolerance (Zhang et al., 2014). To evaluate growth rate, plant height were measured at the day before stress
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application (day 0) and 18 days after the onset of salinity and drought stress in both seedling-stage and reproductive-stage experiments. For cold stress, growth was measured at 25 days post stress treatment. For all stress experiments, corresponding unstressed controls were also included. The differences in plant growth, expressed as shoot increment, among osmotin-, Gus-expressing plants and WT or NT control were observed in all cold, drought, and salinity stresses at both stages of plant development that stress treatments applied (Figure 5.1). At the seedling-stage, both drought and salinity stress significantly reduced plant growth (Figure 5.1 A). However, the growth reduction was greater in VC and WT plants, followed by OsOlp1_I plants in comparison to TlOsm and OsOlp1_A plants. A similar trend was observed following cold stress with TlOsm and OsOlp1_A plants was displaying significantly higher growth rate than the OsOlp1_I, VC, and WT plants (Figure 5.1 B). Notably, TlOsm plants showed superior growth to OsOlp1_A plants. When stress was applied before the transition between growth and reproductive stage on the T1 generation, the growth reduction was also observed in 100 mM NaCl and drought exposed plants, as compared to unstressed plants (Figure 5.1 C). At this stage, all three osmotin expressing plants exhibited significantly greater shoot growth than the NT and VC plants. TlOsm plants exhibited leading shoot growth in both 100 mM NaCl and drought exposure while shoot increment of OsOlp1_A plants was only comparable to that of TlOsm plants in 100 mM NaCl treatment (Figure 5.1). Shoot growth of OsOlp1_I plants was significantly smaller than that of OsOlp1_A and TlOsm plants in both 100 mM NaCl and drought stress treatments. The results here demonstrated that TlOsm and OsOlp1_A plants maintained growth better than OsOlp1_I, NT and VC plants.
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Figure 5.1 Relative shoot growth of WT or NT, VC and transgenic plants expressing OsOlp1_A, OsOlp1_I, and TlOsm grown in unstressed, 100 mM NaCl, and drought stress at seedling stage (A); in unstressed and cold stress (B); and in unstressed, 100 mM NaCl, and drought stress at reproductive stage (C). Data present the mean + SE of three replicates. Number of plants (n) used to calculate each mean is indicated in the corresponding charts. Data in the same treatment category followed by different letters are significantly different at P ≤ 0.05.
5.3.2 Rice plants constitutively expressing TlOsm or OsOlp1_A produce more tillers than WT, NT, and VC plants under cold, drought, and salinity stresses Tiller number is another indicative parameter for rice growth under stress with more tillers related to higher tolerance and potentially contribute to higher yield (Tripathi et al., 2012). Tiller number in all experiments was recorded at the same day
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as plant height, i.e. day 18 for 100 mM NaCl and drought stress with corresponding unstressed experiments and day 25 of cold stress with its unstressed control. Figure 5.2 presents number of tillers of WT, NT, transgenic plants expressing Gus-reporter gene, OsOlp1_A, OsOlp1_I, and TlOsm in all unstressed and cold, drought, and salinity stress treatments.
Figure 5.2 Tiller number of WT or NT, VC and transgenic plants expressing OsOlp1_A, OsOlp1_I, and TlOsm grown in unstressed, 100 mM NaCl, and drought stress (A); in unstressed and cold stress (B) at seedling stage; and in unstressed, 100 mM NaCl, and drought stress at reproductive stage (C). Data present the mean + SE of three replicates. Number of plants (n) used to calculate each mean is indicated in the corresponding charts. Data in the same treatment category followed by different letters are significantly different at P ≤ 0.05.
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No significant difference was observed in tiller numbers among the plants under unstressed conditions in all three experiments. However, in all three stress conditions and regardless of plant generations and developmental stages at which stresses applied, OsOlp1_A and TlOsm plants produced significantly more tillers than OsOlp1_I, VC and WT or NT plants. Only T1 generation and in drought stressed at reproductive stage, tiller numbers of TlOsm plants were significantly higher than that of OsOlp1_A plants (Figure 5.2 C). A significant difference in tiller numbers of OsOlp1_I plants compared to VC, WT or NT plants was observed in 100 mM NaCl stress at seedling stage (Figure 5.2 A) and both 100 NaCl and drought stresses at reproductive stage (Figure 5.2 C). Data presented in Figure 5.2 indicate that TlOsm and OsOlp1_A plants produce more tillers than WT, NT, and VC plants under cold, drought, and salinity stresses. Moreover, in exposure to drought stress at reproductive stage, TlOsm plants produced significantly more tillers than OsOlp11_A plants.
5.3.3 Rice plants constitutively expressing OsOlp1_A or TlOsm retained water better than OsOlp1_I, VC and NT or WT plants under cold, drought, and salinity stresses Relative water content (RWC) is considered an appropriate measurement of plant water status that reflects the physiological consequence of cellular water deficits (Gonzalez and Gonzalez-Vilar, 2001). Studies on rice have shown that tolerant plants maintain higher leaf RWC during stress (Lafitte et al., 2006; Cha-um et al., 2009; Kim et al., 2012; Zhang et al., 2014). To understand the physiological difference among plants expressing OsOlp1_A, OsOlp1_I and TlOsm with VC, and WT or NT plants, leaf RWC was measured in all unstressed and stressed plants. As presented in Figure 5.3, in all three sets of unstressed plants, leaf RWC of OsOlp1_A, OsOlp1_I, TlOsm, VC, and WT or NT plants was similar. After subjection to 100 mM NaCl, drought or cold stresses, leaf RWC of all plants was dramatically reduced, with a noticeable RWC reduction of plants exposed to drought stress. Leaf RWC of OsOlp1_A and TlOsm was always significantly higher than that of OsOlp1_I, VC, and WT or NT plants regardless of stress types, transgenic generations, and developmental stages that stresses applied. In seedling-stage stress treatments, RWC of TlOsm was significantly higher than that of OsOlp1_A only in drought stress (Figure 5.3 A). When stresses applied at reproductive stage on T1 transgenic plants, leaf RWC of TlOsm plants was significantly higher than that of OsOlp1_A in both drought and salinity stresses (Figure 5.3 C). The significant difference in leaf RWC of OsOlp1_I over VC and NT plants
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was observed in both drought and salinity stresses when stresses applied at reproductive stage (Figure 5.3 C). Among stress treatments at seedling stage, leaf RWC of OsOlp1_I plants was significantly greater than that of WT plants only in drought stress condition (Figure 5.3 A). Previous studies have indicated the ability to maintain higher leaf RWC during stress as advantage trait of rice stress-tolerant cultivars. Data from these experiments proved that OsOlp1_A and TlOsm plants exhibited better water retention under cold, drought and salinity stresses; thus contributing to their higher stress tolerance.
Figure 5.3 Leaf relative water content (RWC) of WT or NT, VC and transgenic plants expressing OsOlp1_A, OsOlp1_I, and TlOsm grown in unstressed, 100 mM NaCl, and drought stress (A); in unstressed and cold stress (B) at seedling stage; and in unstressed, 100 mM NaCl, and drought stress at reproductive stage (C). Day of measurement was indicated. Data present the mean + SE of three replicates. Number of samples (n) used to calculate each mean is indicated in the corresponding charts. Data in the same treatment category followed by different letters are significantly different at P ≤ 0.05.
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5.3.4 Rice plants constitutively expressing osmotins maintain membrane integrity better than VC and WT or NT plants under cold, drought, and salinity stresses Electrolyte leakage reflects the ability of cells to maintain membrane integrity and has been used as an indicator of membrane damage. Lower electrolyte leakage has been found in rice stress-tolerant cultivars (Cha-um et al., 2009; Kim et al., 2012; Zhang et al., 2014; Das et al., 2015). Leaf electrolyte leakage was another parameter being measured to understand the physiological difference among plants expressing OsOlp1_A, OsOlp1_I and TlOsm with VC, and WT or NT plants. Leaf electrolyte leakage was measured at the same day of RWC measurement in all unstressed and stress-treated experiments and data are presented in Figure 5.4.
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Figure 5.4 Leaf electrolyte leakage of WT or NT, VC and transgenic plants expressing OsOlp1_A, OsOlp1_I, and TlOsm grown in unstressed, 100 mM NaCl, and drought stress (A); in unstressed and cold stress (B) at seedling stage; and in unstressed, 100 mM NaCl, and drought stress at reproductive stage (C). Day of measurement was indicated. Data present the mean + SE of three replicates. Number of samples (n) used to calculate each mean is indicated in the corresponding charts. Data in the same treatment category followed by different letters are significantly different at P ≤ 0.05.
In these experiments, relative electrolyte leakage of leaf cells was calculated as a slope of electrolytes leaked out of cells against time in 1 h increment. The greater electrolyte leakage is associated with higher cellular damage. In three sets of plants in unstressed conditions, electrolyte leakage values were very small (range from 0.02 to < 0.1, dependent on stages) and similar across the transgenic OsOlp1_A, OsOlp1_I,
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TlOsm, and VC, and WT or NT plants. Under stress, these values sharply increased. There was a noticeable increase in electrolyte leakage of drought stressed plants. The values of OsOlp1_A and TlOsm plants were always smaller than those of OsOlp1_I, VC, and WT or NT plants. Electrolyte leakage from TlOsm tissues was significant less than from OsOlp1_A tissues during cold stress at the seedling stage and at both drought and salinity stress at the reproductive stage. Except for cold stress, OsOlp1_I cells had significantly less electrolyte leakage than that of the WT or NT plants in drought and salinity stress at both seedling-stage and reproductive stage stress treatments. The results on electrolyte leakage measurement demonstrated that TlOsm and OsOlp1_A plants maintained the membrane integrity better than OsOlp1_I, VC, and WT or NT plants. This ability of TlOsm plants was found to be superior to that of OsOlp1_A plants when exposed to cold stress at the seedling stage and drought and salinity stresses at the reproductive stage.
5.3.5 Rice plants constitutively expressing TlOsm or OsOlp1_A maintained photosynthesis efficiency under drought and salinity stresses Photosynthesis is a basic physiological process plants use to produce energy for their development and coping with environmental challenges. Abiotic stresses leading to photosynthesis reduction and ultimately inhibition have been well documented in rice (Babu, 2010; Zhang et al., 2014; Das et al., 2015). Stress tolerant rice cultivars maintain higher photosynthetic activity during stress (Moradi et al., 2007). To investigate the physiological differences among transgenic plants expressing Gus- reporter gene, OsOlp1_A, OsOlp1_I, and TlOsm and NT plants, photosynthetic parameters were measured in the plants exposed to drought and salinity stresses at reproductive stage together with corresponding unstressed control. Photosynthetic measurements were carried out from day 0 to day 21 of stress exposure for salinity stressed plants and unstressed control; and to day 18 for drought stressed plants. Photosynthesis data of these plants are presented in Figure 5.5. As shown in Figure 5.5.A, in unstressed conditions, net photosynthesis of TlOsm plants was significantly lower that of OsOlp1_I, NT and VC plants during the course of measurement. The significantly higher photosynthesis rates of OsOlp1_A plants over TlOsm plants were also detected at day 0, 3, 18, and 21. Net photosynthesis of OsOlp1_A plants was found lower than NT plants at day 0 and day 12. There were some variations in photosynthesis rate among different times of measurement, probably due to the
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changes in developmental stages. Under unstressed condition, panicle initiation started at around day 6 with the appearance of flag leaf and at day 18, 36% of OsOlp1_I, NT and VC plants flowered. Thus, from day 12 to day 21 photosynthesis was measured on flat leaves of unstressed plants. When exposed to 100 mM NaCl (Figure 5.5 B), photosynthesis of OsOlp1_I, NT and VC plants was significantly reduced since day 6 with a sharp reduction from day 12. Photosynthesis reduction was also observed in OsOlp1_A and TlOsm plants but with smaller reduction and at the later stage (day 12). Photosynthesis rate of OsOlp1_A and TlOsm plants was similar from day 12 to day 21, which was significantly higher than NT and VC plants. Significant lower photosynthesis rate of OsOlp1_I in comparison to OsOlp1_A and TlOsm plants was found from day 18 to day 21. A similar trend of photosynthesis rate was observed when plants exposed to drought stress (Figure 5.5 C). At day 6 of withholding water, photosynthesis of OsOlp1_I, NT and VC plants was significantly reduced and continued to reduce to very low rate (about 10% of normal levels) at day 18. OsOlp1_A maintained normal photosynthesis efficiency until day 6 of withholding water, then declined but kept significantly greater than those of OsOlp1_I, NT and VC plants. Photosynthesis rates of TlOsm plants were only significantly decreased after day 12 of withholding water. At the end of drought stress period (day 18), net photosynthesis of TlOsm plants was highest, followed by OsOlp1_A plants and significantly distinguished with those of OsOlp1_I, NT and VC plants. During the course of drought stress, OsOlp1_I plants did not show any difference in photosynthesis rate in compared to NT and VC plants. TlOsm and OsOlp1_A`plants maintain better photosynthesis efficiency than OsOlp1_I, NT and VC plants under drought and salinity stresses suggesting that this is one of the strategies TlOsm and OsOlp1_A plants used to cope with drought and salinity stresses.
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Figure 5.5 Net photosynthesis of NT, VC and transgenic plants expressing OsOlp1_A, OsOlp1_I, and TlOsm grown in unstressed (A) and exposure to 100 mM NaCl (B) and drought stress (C) at reproductive stage. Data present the mean ± SE of nine observations. * indicates significant difference at P ≤ 0.05.
Transpiration is the process of water loss through stomata. The trends of transpiration of OsOlp1_A, OsOlp1_I, TlOsm, VC and NT plants under unstressed, salinity and drought conditions (Figure 5.6) were similar as those of photosynthetic activity. Under unstressed condition (Figure 5.6 A), TlOsm plants exhibited lower transpiration rate than OsOlp1_I, VC and NT plants. Transpiration rate of OsOlp1_A was lower than those of OsOlp1_I, VC and NT plants but higher than TlOsm plants. As shown in Figure 5.6 B, at the first 6 days of exposure to 100 mM NaCl, transpiration rate of OsOlp1_I, VC and NT plants remained the levels similar to unstressed and
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significantly higher than that of TlOsm plants. Since day 12, transpiration rate of these plants dramatically decreased. TlOsm and OsOlp1_A plants had smaller values of transpiration rate at the first 6 day of NaCl exposure, their significant transpiration decrease compared with before stress was found at day 18. The reduction in transpiration rate of TlOsm and OsOlp1_A plants was slower than that of OsOlp1_I, VC and NT plants, resulting in their significant higher transpiration rate from day 12 to day 21. Similarly, transpiration rate of all plants sharply decreased after 6 days of withholding water (Figure 5.6 C), but the reduction rate was faster for the OsOlp1_I, VC and NT plants, resulting in their significant lower transpiration rate in compared with that TlOsm and OsOlp1_A plants since day 12.
Figure 5.6 Transpiration rate of NT, VC and transgenic plants expressing OsOlp1_A, OsOlp1_I, and TlOsm grown in unstressed (A), exposure to 100 mM NaCl (B) and drought stress (C) at reproductive stage. Data present the mean ± SE of nine observations. * indicates significant difference at P ≤ 0.05.
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Transpiration partially reflects the plant photosynthesis activity and water balance. TlOsm and OsOlp1_A plants have lower levels of transpiration rate in unstressed and at beginning of stress period would help in retaining water. At the later stages of drought and salinity stresses, transpiration remained higher than OsOlp1_I, VC and NT plants, suggesting their photosynthesis machinery was still active. In plant, stomata control gas exchange between plant and atmosphere, thus drive
CO2 influx into leaves for photosynthesis and water vapour as transpiration. Regulation of stomatal movement is a central mechanism to maintain photosynthesis efficiency and water balance in plants exposure to osmotic stress (Belin and Thomine, 2010). To understand the cause of variations in photosynthesis and transpiration among plants, stomatal conductance of OsOlp1_A, OsOlp1_I, TlOsm, VC and NT plants under unstressed, salinity and drought conditions was calculated and presented in the Figure 5.7.
Figure 5.7 Stomatal conductance of NT, VC and transgenic plants expressing OsOlp1_A, OsOlp1_I, and TlOsm grown in unstressed (A), exposure to 100 mM NaCl (B) and drought stress (C) at reproductive stage. Data present the mean ± SE of nine observations. * indicates significant difference at P ≤ 0.05.
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In unstressed conditions, stomatal conductance of TlOsm plants was significantly lower than that of OsOlp1_I, VC and NT plants during the course of measurement, and also of OsOlp1_A plants at day 0, day 18 and day 21. When exposed to 100 mM NaCl, stomatal conductance of OsOlp1_I, VC and NT plants was reduced with a noticeable reduction after day 6, while that of TlOsm plants found significant difference with before stress only from day 18, and of OsOlp1_A from day 12. Since day 12, conductance of OsOlp1_A and TlOsm plants was similar and significantly higher than that of NT and VC plants. The conductance of OsOlp1_I plants was found higher than that of the NT and VC plants only at day 12 and 18, but declined to the same level at day 21. Similarly, six days after water was withheld, stomatal conductance of all plants was declined. However, TlOsm plants maintained the highest values of stomatal conductance, followed by OsOlp1_A, OsOlp1_I; the NT and VC had the same lowest values. Regulation of stomatal closure is one of the mechanisms plants use to tolerate osmotic stresses by reducing water loss and balancing photosynthesis process. Constitutive expression of TlOsm or OsOlp1_A in rice resulted in transgenic plants with lower stomatal conductance, suggesting that functions of TlOsm and OsOlp1_A I are linked to stomatal regulation. At the later stages of drought and salinity stress exposure, TlOsm and OsOlp1_A plants maintained significant higher stomatal conductance than OsOlp1_I, NT and VC plants. The results here once support that the photosynthesis machinery was still active in TlOsm and OsOlp1_A plants in these stress treatments.
5.3.6 Stressed rice plantlets constitutively expressing TlOsm or OsOlp1_A showed heathier morphological appearance than VC and WT The phenotypic differences among TlOsm, OsOlp1_A, OsOlp1_I, WT and VC plants were apparent in all cold, drought and salinity stress conditions applied at seedling stage. Figure 5.8 shows the images capturing morphology of representative plants before and after a given period of stress exposure. Before entering stress treatments, plants were selected at the same stage and their morphologies were similar across all OsOlp1_A, OsOlp1_I, TlOsm, VC, and WT plants (Figure 5.8 A and B). Eighteen days later, in unstressed conditions all plants looked equally healthy except for shorter shoots of TlOsm plant (Figure 5.8 C). However, upon drought (Figure 5.8 E) and salinity (Figure 5.8 F) stresses, VC and WT plants completely stopped tillering, leaves yellowing or discoloured while the TlOsm and OsOlp1_A plants had more
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tillers, plants were greener, only the leaf tips damaged but entire leaves. OsOlp1_I plants were healthier than VC and WT plants but were not comparable to TlOsm and OsOlp1_A plants. Similarly, after 25 days undergone cold stress (Figure 5.8. D), OsOlp1_I, WT and VC plants had severely damaged appearance and the death of youngest leaves while TlOsm and OsOlp1_A had less leaf and stem damages and had more tillers.
Figure 5.8 Morphology of T0 rice plants under cold, drought and salinity stresses at seedling stage. Images A and B were taken right before plants undergone unstressed, 100 mM NaCl, and drought stress for three weeks (A) or unstressed and cold stress for 4 weeks (B). C, E, and F: representatives of plants in (A) after 18 days undergone unstressed, drought, and salinity stress respectively. D: Representative of plants in (B) after 25 days undergone cold stress.
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Four weeks after germination when transgenic status was confirmed, T1 rice plants grown in 50-ml pots were selected at similar size and at 5-leaf stage and were transplanted into 1.2-L pots. Plants were grown for further 2 weeks in glasshouse condition before the stresses applied. The day before stress exposure (day 0), appearance of all plants was similar but the shorter shoots of TlOsm plants could be observed (Figure 5.9 A). At this time, all plants typically had 3 tillers. After 18 days of withholding water (Figure 5.9 B), leaves of NT, VC and OsOlp1_I plants were completely rolled and discoloured, their newly-developed tillers were dried despite their stems of main culm survived. Most leaves of TlOsm plants and some of OsOlp1_A plants stayed expended and relatively greener, some of their newly- developed tillers stayed alive, their stems were greener and looked healthier than those of NT, VC and OsOlp1_I plants. After exposure to 100 mM NaCl for 28 days (Figure 5.9 B), severe senescence was observed in NT, VC and OsOlp1_I plants but not in TlOsm and OsOlp1_A plants. TlOsm and OsOlp1_A plants looked similar in term of green appearance and tillering.
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Figure 5.9 Morphology of T1 rice plants and panicles under unstressed, drought and salinity stresses when plants exposed to stresses at reproductive stage. A: plants before stress treatment; B-C: representatives of plants in (A) after 18 days under drought (B) and 28 days exposed to salinity stress (C) respectively. D-F Representative of panicles in plants undergone unstressed (D), drought (E) and salinity stress (F).
5.3.7 Rice plants constitutively expressing TlOsm or OsOlp1_A resulted in higher dry biomass under cold, drought, and salinity stresses Dry biomass of TlOsm, OsOlp1_A, OsOlp1_I, VC, and WT or NT plants was determined at the end of stress periods, i.e. day 21 for plants in set 1 exposed to drought and salinity stress at seeding stage, day 28 for plants in set 2 exposed to cold stress at seeding stage, and day 28 for T1 plants with stresses applied at reproductive stages, together with corresponding unstressed controls. As a result of growth arrest under
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stresses, dry biomass was dramatically reduced in all TlOsm, OsOlp1_A, OsOlp1_I, VC, WT, and NT plants in all stress conditions (Table 5.2 and 5.3). However, the reduction in dry biomass was smaller for TlOsm plants, followed by OsOlp1_A, OsOlp1_I plants and equally higher for VC and WT or NT plants. As shown in Table 5.2, when stresses were applied at seeding stage, dry biomass of TlOsm plants reduced by 1.21, 1.22, and 1.66 fold for drought, salinity, and cold stress, respectively, in comparison with corresponding unstressed control. But reduction was 2.58, 2.21, 3.50 fold for WT and 2.50, 2.18, and 2.47 for VC plants, in the same order. Dry biomass of TlOsm plants was significantly greater than that of OsOlp1_A plants in drought and cold stresses, but not in salinity stress. OsOlp1_I plants only produced significantly higher dry biomass than WT plants in salinity stress.
Table 5.2 Dry biomass of plants in seedling-stage stress treatment experiments Experiment Plants Dry biomass1 per plant (mg) Unstressed Drought Salinity
OsOlp1_A 525a ± 18.9 343b ± 18.9 353a ± 20.5 Seedling OsOlp1_I 535a ± 23.1 281c ± 25.8 271b ± 18.2 stage plant set 1, day 21 TlOsm 472b ± 19.1 390a ± 28.8 386a ± 17.3 VC 562a ± 22.4 257c ± 19.6 245bc ± 15.6 WT 559a ± 15.3 253c ± 44.7 216c ± 15.7 Unstressed Cold OsOlp1_A 585a ± 13.1 218b ± 12.9 Seedling a c stage OsOlp1_I 575 ± 10.0 175 ± 10.8 plant set 2, TlOsm 488b ± 13.7 294a ± 12.6 day 28 VC 567a ± 11.7 166c ± 9.1 WT 584a ± 27.1 167c ± 19.2 1 data represent mean ± SE of 54 plants. Data in the same treatment category followed by different letter are significantly different at P ≤ 0.05.
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Table 5.3 Dry biomass of plants in reproductive-stage stress treatment experiments Plants Dry biomass1 per plant (mg) Unstressed Drought Salinity a cd c NT 1652 ± 48 802 ± 36 875 ± 38 ab b a OsOlp1_A 1598 ± 53 1034 ± 35 1118 ± 47 a c b OsOlp1_I 1676 ± 51 876 ± 39 998 ± 56 b a a TlOsm 1537 ± 46 1157 ± 35 1093 ± 38 a d bc VC 1692 ± 55 795 ± 32 895 ± 55 1 data represent mean ± SE of 15 plants. Data in the same treatment category followed by different letters are significantly different at P ≤ 0.05.
Consistent with results in seedling-stage stress treatment, drought and salinity stresses applied at the reproductive stage also sharply decreased dry biomass of all plant types (Table 5.3). Under drought stress TlOsm plants still produced highest dry biomass, followed by OsOlp1_A plants, and both had significantly higher dry biomass than NT, VC and OsOlp1_I plants. Under salt stress, dry biomass of TlOsm and OsOlp1_A was not different but significantly higher than that of NT, VC and OsOlp1_I plants. Dry biomass of OsOlp1_I plants was found greater than VC plants in drought stress, and NT plants in salinity stress.
5.3.8 Constitutive expression of TlOsm or OsOlp1_A improves survival rate under salinity, drought and cold stress in transgenic rice. After stress treatment, the plants were recovered and the survival rates were assessed after 3 weeks of recovery (Figure 5.10). For salinity stress, the rates of survival plants were 42.22%, 45.56%, 50%, 70% and 74.44% for WT, VC, OsOlp1_I, OsOlp1_A, and TlOsm plants respectively (Figure 5. 10 A); while that rates were 24.07%, 28. 40%, 48.15%, 76.54% and 86.42% for drought stress (Figure 5.10 C). In cold stress, a symptom commonly observed in WT and VC plants was that in the same plant the newly emerging (youngest) leaves died while the mature leaves and stems remained alive. The tillers with the youngest leaf mortality stopped growth and panicle initiation that ultimately became infertile. Despite the severe effects under cold stress, in recovery, plants with infertile tillers continued tillering and new tillers developed normally in recovery conditions and that resulted in relatively high survival rates of cold stressed plants, compared to drought and salinity stresses (Figure 5. 10 E). The plants with infertile tillers had less grain yield. In this respect, 75.71% TlOsm plants and 63% of OsOlp1_A plants recovered without infertile tillers, while that rates were only 25.4%, 22.95% and 21.32% for OsOlp1_I, VC, and WT plants.
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Figure 5.10 Survival rate and morphology of rice plants recovered from stress treatments at seeding stage. A & B: salinity, C&D: drought, E & F: cold. Data present the mean + SE of 81 plants in three replicates. Data in A, C, and E followed by different letters are significantly different at P ≤ 0.05.
In recovery, TlOsm and OsOlp1_A plants showed greener and healthier appearance and had more tillers than the OsOlp1_I, VC, and WT plants (Figure 5.10 B, D & F). The significant higher survival rate and healthier recovery of TlOsm and OsOlp1_A plant under these three stress conditions demonstrated that TlOsm and OsOlp1_A enhanced tolerance to cold, drought, and salinity stresses in transgenic rice.
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5.3.9 Constitutive expression of TlOsm or OsOlp1_A improved yield under drought and salinity in transgenic rice Morphologically, panicles and seeds of TlOsm, OsOlp1_A, OsOlp1_I, VC and NT plants developed normally under unstressed condition with shorter panicle length and condensed distribution of seeds found in TlOsm plants (Figure 5.9 D). In both drought and salinity stress, panicles were shorter and seeds were smaller for all TlOsm, OsOlp1_A, OsOlp1_I, VC and NT plants (Figure 5.9 E & F). Additionally, many brown spots were observed on filled seeds of salt stressed plants (Figure 5.9 F), probably due to the consequence of oxidative stress.
The parameters used in this study for evaluating yield are indicative components contributing to rice grain yield (Tripathi et al., 2012). Yield components were calculated for all plants in drought, salinity, and unstressed experiments when stressed applied at reproductive stage and data are presented in Table 5.4. In drought-stressed plants, TlOsm plants had leading values in all observed parameters, including number of panicles per plant, panicle length, and number of spikelets per panicle, percentage of filled seeds, total filled seeds per plant and seed weight (expressed as weight of 100 seeds). Both TlOsm and OsOlp1_A plants produced significantly higher values of yield components than OsOlp1_I, VC, and NT plants. Panicle length and number of spikelets per panicle of OsOlp1_A were comparable to those of TlOsm plants. However, OsOlp1_A plants produced significantly less panicles than TlOsm plants and the percentage of filled seeds was also significantly smaller in OsOlp1_A than in TlOsm plants. These resulted in significant less seeds per plant of OsOlp1_A plants as compared to TlOsm plants. In addition, OsOlp1_A seed weight was significantly smaller than that of TlOsm. This would further contribute to less grain yield of OsOlp1_A plants.
Similarly, in salinity stress all the yield components of TlOsm and OsOlp1_A were significant higher than those of OsOlp1_I, VC, and NT plants. Across all yield parameters, values of TlOsm and OsOlp1_A plants were comparable under salinity stress conditions. As compared with applied drought stress conditions, values of all yield parameters of each type of plants were higher in applied salinity stress conditions. This indicates that the drought treatment has severer effects on rice yield than the salinity treatment.
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In unstressed conditions, there was no difference in number of panicles per plant, number of spikelets per panicle, percentage of filled seeds, and total seeds per plant among TlOsm, OsOlp1_A, OsOlp1_I, NT, and VC plants, despite significantly shorter panicle length was observed for both TlOsm and OsOlp1_A. However, seed weight of TlOsm and OsOlp1_A plants was significantly smaller, with the lowest value for TlOsm seeds.
Results on yield components here demonstrate that constitutive expression of either TlOsm or OsOlp1_A improved rice yield under drought and salinity stress. Significant higher yield of TlOsm plants over OsOlp1_A was observed in drought stress.
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Table 5. 4 Yield components of TlOsm, OsOlp1_A, OsOlp1_I, VC and NT (control) plants under unstressed, drought, and salinity stress conditions A) Drought stress Plants # of panicles/plant Panicle length (cm) # of spikelets/panicle Filled seeds (%) # of seeds/plant 100-seed weight (mg) NT 1.93d ± 0.27 13.07b ± 0.31 38.76b ± 2.19 35.12c ± 4.01 28c ± 4 1669c ± 14 OsOlp1_A 3.40b ± 0.16 13.85a ± 0.26 45.84a ± 1.57 57.69b ± 3.22 92b ± 7 1752b ± 16 OsOlp1_I 2.87c ± 0.20 13.19b ± 0.17 38.72b ± 1.41 26.72c ± 3.42 30c ± 5 1651c ± 15 TlOsm 4.73a ± 0.19 13.82a ± 0.11 44.10a ± 1.02 74.25a ± 2.96 155a ± 6 1790a ± 9 VC 2.40d ± 0.22 13.21b ± 0.18 37.04b ± 1.45 30.78c ± 3.16 29c ± 4 1654c ± 12 B) Salinity stress Plants # of panicles/plant Panicle length (cm) # of spikelets/panicle Filled seeds (%) # of seeds/plant 100-seed weight (mg) NT 2.87c ± 0.20 13.02b ± 0.19 40.62b ± 1.27 47.02b ± 3.14 53b ± 4 1763b ± 11 OsOlp1_A 5.87a ± 0.17 13.64a ± 0.15 43.97a ± 0.99 73.58a ± 2.35 191a ± 7 1825a ± 8 OsOlp1_I 3.67b ± 0.19 12.87b ± 0.15 39.15b ± 2.16 40.55b ± 3.77 58b ± 3 1782b ± 10 TlOsm 5.93a ± 0.16 13.77a ± 0.11 45.15a ± 0.79 74.06a ± 2.45 197a ± 7 1816a ± 7 VC 2.93c ± 0.24 13.16b ± 0.14 41.65b ± 0.94 45.32b ± 2.90 55b ± 6 1772b ± 9 C) Unstressed Plants # of panicles/plant Panicle length (cm) # of spikelets/panicle Filled seeds (%) # of seeds/plant 100-seed weight (mg) NT 9.20ns ± 0.46 16.61a ± 0.23 66.68ns ± 2.75 84.13ns ± 1.98 515ns ± 19 2190a ± 31 OsOlp1_A 8.93ns ± 0.51 16.04b ± 0.28 66.15ns ± 2.51 84.47ns ± 1.83 497ns ± 18 2109b ± 24 OsOlp1_I 8.33ns ± 0.45 16.45ab ± 0.25 70.08ns ± 3.57 86.26ns ± 1.74 503ns ± 16 2214a ± 22 TlOsm 8.73ns ± 0.30 15.07c ± 0.27 65.48ns ± 3.40 87.62ns ± 1.66 489ns ± 21 2042c ± 25 VC 8.60ns ± 0.31 16.53a ± 0.19 66.88ns ± 2.78 83.79ns ± 2.21 495ns ± 20 2170a ± 23 Data represent mean ± SE. Data in the same treatment category followed by different letter are significantly different at P ≤ 0.05; ns: none significance
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5.4 DISCUSSION
Rice is one of the most sensitive crops to abiotic stress. Countless efforts have been made to improve abiotic stress tolerance in rice through conventional breeding and the supports of advanced molecular assisted breeding techniques. Attempts in rice abiotic-stress-tolerant improvement have resulted in various commercial cultivars adapted to a wide range of rice cultivation areas but the success has reached the limitations (Das et al., 2015; Sankar et al., 2011; Swamy and Kim 2013). Genetic engineering allows researchers to breach species boundaries and incorporate genes from other species for enhancing abiotic stress tolerance. Incorporation of stress- responsive genes from naturally tolerant species for engineering rice with enhanced abiotic stress tolerance is essential to add adaptive traits into this species. In Chapter 3, an osmotin (TlOsm) from desiccation tolerant plant, T. loliiformis, was characterised and proven to respond to cold, drought, and salinity stresses. In Chapter 4, transgenic rice plants constitutively expressing TlOsm, OsOlp1-A, OsOlp1_I and Gus-reporter gene as control were generated. This chapter investigated the response of these rice plants under different stress and unstressed conditions.
The first aim was to validate if constitutive expression of TlOsm in rice confers tolerance to drought, salinity and cold stresses. Secondly, OsOlp1-A and OsOlp1_I were isolated from drought-tolerant and -sensitive cultivars Apo and IR64, respectively. The two genes encode two proteins containing high (96%) homology at the AA sequence level but are differentially expressed upon drought; only OsOlp1-A is induced by drought. Functional predictions based on sequences and structures of these three osmotins revealed different number of glucan-binding and phosphorylation sites among them. Thus, comparatively analysing rice plants expressing these three osmotins might reveal the key insights into osmotin functions and effects of functional binding sites on enhancing plant stress tolerance. To date, only one study by Mani et al. (2012) compared two Piper colubrinum osmotins, which are different in five glucan-binding sites, on their differential antifungal activities. According to the study, the two osmotin isoforms differ in 50 AA that results in disorder in domains I and III and less glucan-binding sites in the smaller isoform (22 sites in the larger isoform vs. 17 sites in the smaller one). Both isoforms were transcriptionally expressed by pathogen, wounding, jasmonic acid, and ethylene. However, recombinant protein of smaller isoform displayed much less activity against Phytophthora capsici and
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Fusarium oxysporum as compared to the larger isoform in in vitro conditions. The loss of antifungal activity of the smaller isoform was presumably due to the disorder in domain I and III. Thus, this study extended the possible effects of glucan-binding sites of osmotins on their functions in regulating plant response to abiotic stresses including cold, drought, and salinity. Thirdly, it has been proposed that genes from highly stress tolerance species would provide more level of tolerance over those of stress sensitive species. Additional glucan-binding and phosphorylation sites together with unique functional sites in sugar metabolism were found in TlOsm compared to rice osmotins. Some stress-responsive proteins of resurrection plant have been demonstrated to maintain phosphorylation reaction during desiccation and this reaction has been believed to be required for cellular protection during desiccation tolerance (Rohrig et al., 2006; Dinakar and Bartels, 2013). Thus, high number of phosphorylation sites of TlOsm might contribute to its function in regulating plant adaptive response. Furthermore, accumulation of soluble sugars at remarkably high levels during desiccation tolerance is a distinct characteristic of resurrection plants (Alpert and Oliver, 2002; Dinakar and Bartels, 2013; Gaff and Oliver, 2013). The unique binding sites with potential functions in sugar metabolism of TlOsm might be beneficial for its modulation of plant stress response. Hence, analysing the advantage in abiotic stress response of TlOsm expressing plants over OsOlp1-A or OsOlp1_I expressing plants was also included in this study.
5.4.1 TlOsm and OsOlp1_A confers tolerance to cold, drought and salinity stresses in rice Previous studies have indicated that the effects of cold, drought, and salinity stresses are more severe to rice when they occur at seedling stage, before tillering, and at the transition between growth stage and reproductive stage (Lafittle et al., 2004; Das et al., 2015). Therefore, these two stages were chosen for the assessments in this study. Throughout the stress experiments, the control plants, NT or WT of rice Nipponbare cultivar exhibited severe growth reduction, less tillering, leaf senescence and dry, reduced leaf water retention, severe membrane damage, photosynthesis inhibition, decreased survival rate, reduced panicle number and length, less spikelets, inadequate grain filling, and reduced seed weight. The severe effects of salinity, drought, and cold stresses on rice growth and reproductivity were sharply improved by expressing either TlOsm or OsOlp1_A in the same rice cultivar. The only difference among the transgenic
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plants were the genes they express; while WT and NT differed from transgenic plants by the absence of transgenes. Thus, the enhanced tolerance to cold, drought, and salinity stresses of TlOsm and OsOlp1_A plants must be a consequence of TlOsm or OsOlp1_A functions. Moreover, the enhanced stress tolerance of TlOsm and OsOlp1_A plants was constant through two successive generations of transgenic rice, the T0 and T1, suggesting that the tolerant traits were passed on next generations.
Shoot growth, tillering, dry biomass, number of panicle per plants, number of spikelets, and percentage of filled seeds per panicle were all found to directly contribute to final grain yield of rice. These parameters together with survival rate and plant overall health were recommended as effective parameters to evaluate abiotic stress tolerance in rice (Singh et al., 2013). Regardless of transgenic generation and developmental stages on which stresses applied, as compared to VC and WT or NT, TlOsm and OsOlp1-A plants constantly maintained significantly higher shoot growth (Figure 5.1) and produced greater number of tillers (Figure 5.2) under cold, drought, and salinity conditions. As a result of higher growth and tillering, dry biomass of TlOsm and OsOlp1-A plants was significantly higher than that of VC and WT or NT (Table 5.2 & 5.3). The purpose of investigating stress response at seedling stage was to observe the survival ability of plants after certain period of stresses and their recovery capability. Under all cold, drought, and salinity stresses, the survival rate of TlOsm and OsOlp1_A plants was by far higher than of the VC and WT plants. The recovered TlOsm and OsOlp1_A plants were taller, greener and had more tillers than the VC and WT plants (Figure 5.10). In the case of cold stress, the percentage of plants recovered without the infertile tillers was improved in TlOsm and OsOlp1_A plants, which would further reduce yield loss in cold stressed plants. Rice was found more tolerant to abiotic stress at the tillering stage (Singh et al., 2010). Thus, the same concentration of NaCl stress and mild drought applied at the tillering stage on T1 generation of transgenic rice did not cause plant death but ultimately caused severe reduction on grain yield. Once again, this severe grain yield reduction was significantly improved when expressing either TlOsm or OsOlp1-A in the same rice cultivar (Table 5.4). Taken all together, the results from these experiments proved that TlOsm and OsOlp1_A confer tolerance to cold, drought, and salinity stresses. In the same genetic background of Nipponbare cultivar for all tested plants, the tolerance to cold, drought, and salinity stresses was enhanced in only TlOsm and OsOlp1_A plants. Thus, the
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tolerance of TlOsm and OsOlp1_A plants must be a consequence of TlOsm or OsOlp1_A expression. Results here demonstrated that both TlOsm and OsOlp1_A played key roles in the tolerance to cold, drought, and salinity stresses in rice.
Intensive studies on transgenic plants expressing osmotins have proven the physiological functions of osmotins in plant tolerance, but little is known about how osmotins regulate plants tolerant to abiotic stresses. For example, tolerance to cold stress of transgenic tomato expressing tobacco osmotin was accompanied by increasing transcript abundance of some stress responsive genes such as transcription factor (CBF1), osmotic adjustment (P5CS), and ROS scarvenger (APX) and the accumulation of osmoprotectants proline and antioxidant ascorbate (Patade et al., 2013). Drought tolerance of soybean expressing osmotin from Solanum nigrum was associated with increased leaf water retention and maintained photosynthesis activities (Weber et al., 2014). Similarly, enhanced salinity tolerance of transgenic chili pepper expressing tobacco osmotin was linked to increased chlorophyll content, osmolyte accumulation, antioxidant enzyme activities, and water retention, and decreased membrane damage (Subramanyan et al., 2011). Generally, cold, drought, and salinity tolerance of other transgenic osmotin plants were associated with molecular, biochemical, and physiological changes. Molecular changes are linked to the transcriptional activation of stress responsive genes, which function as transcription factor, ROS scarvenger, and osmoprotectants (Patade et al., 2013). Biochemical changes are associated with accumulation of osmolytes and non-enzymatic antioxidants, increased activities of antioxidative enzymes, and higher chlorophyll content (Husaini and Abdin, 2008; Goel et al., 2010; Subramanyam et al., 2011; Das et al., 2011; Subramanyam et al., 2012; Patade et al., 2013; Bhattacharya et al., 2014; Annon et al., 2014; Weber et al., 2014). Regardless the source of osmotins and plant species expressing osmotins, in these studies the common physiological alterations in osmotin expressing plants include increased water retention, maintain membrane integrity, and maintain photosynthesis activities. Based on these changes of osmotin- expressing plants, it has been proposed that osmotins function as a regulator in stress- signalling pathway that modulates the expression of downstream stress-responsive genes leading to accumulation of adaptive compounds and resulting in stress-adaptive physiological traits (Husani and Rafiqi, 2012; Viktorova et al., 2012; Kumar et al., 2015). Although molecular and biochemical changes were not measured in TlOsm and
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OsOlp1_A plants, the physiological changes in rice plants expressing TlOsm and OsOlp1_A were in agreement with those reported for other osmotin-expressing plants. Therefore, we would expect TlOsm and OsOlp1_A to have similar functions in regulating plant stress response, as other osmotins.
To the extent of this study, the levels of enhanced rice stress tolerance positively correlated with the number of glucan-binding sites of osmotins they expressing. TlOsm has the highest number of potential glucan-binding, 8 sites (Table 3.2) and TlOsm plants showed the highest level of stress tolerance. As compared with OsOlp1_I, OsOlp1_A has three more glucan-binding sites (five for OsOlp1_A vs. two for OsOlp1_I). As shown throughout the study, OsOlp1_A plants significantly improved tolerance to cold, drought, and salinity stresses over OsOlp1_I plants. It is accepted that glucan-binding residues around acidic cleft of osmotin structure are required for osmotin antifungal activities (Prasath et al., 2011; Mani et al., 2012). However, in plant abiotic stress response, osmotin functions linked with the glucan-binding and hydrolysing activities remain to be elucidated. The responses of transgenic rice expressing each of the three osmotins to cold, drought, and salinity stress revealed from this study highlight a correlation of the number of glucan-binding sites of osmotins and their efficacy in enhanced rice tolerance to cold, drought, and salinity stress.
5.4.2 Retaining water, maintaining membrane integrity, and maintaining photosynthesis activities are some strategies TlOsm and OsOlp1_A plants used to cope with cold, drought, and salinity stresses. Unlike drought condition where water is unavailable in root zone for plants to uptake, in cold and salinity stress, water is available in root zone but the physiological changes and the ion toxicity lead to the restriction of water-uptake ability of plants and resulted in reduced cellular water potential. The common consequences of plants exposed to cold, drought and salinity are cellular osmotic stress (Huang et al., 2012). However, the stress-adaptive plants are able to cope with stresses by regulating osmotic adjustment (Xiong and Zhu, 2002). RWC has been identified as a useful measurement of plant water status in terms of the physiological consequence of cellular water deficit, due to both leaf water potential and osmotic adjustment ability are considered in the measurement (Gonzalez and Gonzalez-Vilar, 2001). In these experiments, rice plants exposed to all cold, drought and salinity stresses either at
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seedling or reproductive stage resulted in sharp decrease of leaf RWC. TlOsm- or OsOlp1_A- expressing tissues had significantly higher RWC than those of WT and VC under these stresses (Figure 5.3), indicating that they have better strategy for retaining water in their tissues under osmotic stress. Ability to maintain water under stress has been considered as an advantage trait for selection of rice cultivars tolerant to osmotic stress (Cha-um et al., 2009; Dionisio-Sese and Tobita, 1998; Kim et al., 2012; Zhang et al., 2014). Osmotic adjustment for retaining cell water under osmotic stress seems to be one of the physiological mechanisms TlOsm and OsOlp1_A plants used to cope with osmotic stress. Thus, functions of TlOsm and OsOlp1_A are likely linked with the regulation of osmotic adjustment. In coping with osmotic stress, adaptive plants use osmolytes in water replacement, glass formation, and chemical stability for protection of biomolecules and osmotic adjustment (Agarwal et al., 2013). Proline is one of the osmolytes repeatedly found to accumulate in osmotin-expressing plants. The gene encoding a proline synthetic enzyme, the ∆1-Pyrroline 5 - Carboxylate Synthase (P5CS), was found to be sharply activated in cold tolerant tomato expressing tobacco osmotin (Patade et al., 2013). Hence, it is in agreement with reported functions of osmotins that TlOsm and OsOlp1_A mediate osmotic adjustment in osmotic- stress-exposed rice leading to higher water retention.
The cell membrane is the primary site for perception of environmental stress signals. Under osmotic stress, plant cells generate excessive ROS production that facilitates lipid peroxidation, resulting in membrane damage and further loss of cell membrane integrity. One of the mechanisms plants adapted to stresses is developing a number of changes to maintain the membrane intact (Mansour, 2013). The ability of maintaining membrane integrity has been considered a key to conferring tolerance to cold, drought and salinity stresses in plants (Manavalan and Nguyen, 2012; Shabala and Munns, 2012; Zhang et al., 2014). Monitoring electrolyte leakage has been commonly used to reflect the level of membrane damage (Bajji et al., 2002). In rice, measurement of leaf electrolyte leakage has been used as characteristic to screen the stress tolerant cultivars with lower electrolyte leakage indicating higher stress tolerance (Cha-um et al., 2009; Dionisio-Sese and Tobita, 1998; Kim et al., 2012; Zhang et al., 2014). In this study, electrolyte leakage was measured from leaves of TlOsm, OsOlp1_A, OsOlp1_I, VC, and WT or NT plants exposed to cold, drought and salinity stresses at seedling stage and to drought and salinity stresses at reproductive
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stage. Regardless of stress types, TlOsm and OsOslp1_A plants had significantly lower electrolyte leakage values as compared with the control plants (Figure 5.4). These results indicated that leaf cells of TlOsm and OsOslp1_A plants maintain higher membrane integrity than their control counterparts under all these stress conditions. Thus, ability to maintain membrane integrity is likely to be another physiological mechanism implemented in TlOsm and OsOlp1_A rice plants, contributing to their tolerance to cold, drought and salinity stresses. Importantly, plasma membrane damage by osmotic stress is mostly contributed by lipid peroxidation caused by excessive ROS (Gill and Tuteja, 2010). To inhibit lipid peroxidation and maintain membrane intact, plants have developed a complex antioxidative defense that scavenges stress-induced ROS. The antioxidative defense is governed by non-enzymatic and enzymatic antioxidants. Ascorbate is the most abundant non-enzymatic antioxidant. Ascorbate was reported to highly accumulate in osmotin-expressing plants, and enzyme involved in ascorbate biosynthesis (APX) was found activated in osmotin-expressing plants (Subramanyam et al., 2012; Patade et al., 2013). Similarly, membrane integrity of osmotin-expressing plants exposed to stresses has been demonstrated as consequence of lipid peroxidation inhibition resulted from increased activities of antioxidative enzymes such as APX, CAT, DHAR, MDHAR, and SOD (Parkhi et al., 2009; Bhattacharya et al., 2014; Annon et al., 2014). Therefore, maintenance of membrane integrity in TlOsm and OsOlp1_A plants is probably resulted from an effective ROS scavenge mediated by TlOsm and OsOlp1_A.
Photosynthesis is a basic biological process plants use to produce all sources of energy for their living activities. Abiotic stress factors such as drought and salinity cause damage to photosynthetic machinery and result in photosynthesis inhibition (Kreslavski et al., 2013). Maintenance of photosynthetic activities under stresses is a desired trait of stress adaptive plants to produce energies necessary to maintain growth and reproduction (Manavalan and Nguyen, 2012). Under the same period of exposing to 100 mM NaCl or withholding water, photosynthesis activities of TlOsm and OsOlp1_A plants lasted longer than of VC and NT plants (Figure 5.5), suggesting that maintenance of photosynthetic activities is one of the strategies TlOsm and OsOlp1_A plants used to overcome adverse growth reduction affected by drought and salinity stresses and ultimately contribute to their higher dry biomass. The disturbance of photosynthesis activities in plant response to stresses is mainly due to the disturbance
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of stomatal regulation (Shabala and Munns, 2012). In plants, stomata are specialized cells performing gas exchange that regulates the diffusion of CO2 for photosynthetic activities and water loss through transpiration. When leaf water potential decreases, stomata close (Brodribb and Holbrook, 2003). Changes in stomatal aperture when exposed to osmotic stresses have been a reliable measurement for evaluating whole plants response to stresses. (Shabala and Munns, 2012). Data in these experiments showed that, stomatal conductance of VC and NT plants dramatically decreased after 6 days exposure to 100 mM NaCl or withholding water (Figure 5.6). The rapid decrease of stomata conductance in VC and NT plants was positively correlated with the reduction of net photosynthesis and transpiration rate (Figure 5.5 & 5.7). Constitutively expressing TlOsm or OsOlp1_A caused rice plants reduced stomatal conductance in unstressed conditions but prevented its rapid reduction in drought and salinity stresses, suggesting that functions of TlOsm and OsOlp1_A in stress response are related to stomatal regulation. Lower transpiration rate of TlOsm and OsOlp1_A plants in unstressed conditions and early stage of stress exposure seems to be contributed to their higher leaf water retention. Maintenance of photosynthesis has been highlighted as an advanced physiological trait of TbOsm mulberry tolerant to drought salinity (Das et al., 2011), SnOsm soybean tolerant to salinity, and TbOsm soybean tolerant to drought (Weber et al., 2014). In these studies, the maintained photosynthesis was believed to be the result of higher chlorophyll content in osmotin- expressing plants. The results from our study indicated that the maintained photosynthesis activities and water balance in TlOsm and OsOlp1_A plants were associated with stomatal regulation. Thus, the role in stomatal regulation was highlighted for TlOsm and OsOlp1_A.
5.4.3 TlOsm plants showed advantages over OsOlp1_A plants in drought and cold stresses, not in salinity stresses TlOsm was isolated from desiccation tolerant species T. loliiformis and was shown to be rapidly induced to very high levels by cold, drought and salinity (Chapter 3). OsOlp1_A was isolated from drought tolerant cultivar of drought sensitive species O. sativa and shown to be activated by drought but information on its response to cold and salinity stresses was not available. Evaluation of transgenic TlOsm and OsOlp1_A rice plants together with their control counterparts under cold, drought and salinity stresses at seedling stage on T0 generation and under drought and salinity stresses at
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reproductive stage on T1 generation constantly showed the significant improved stress tolerance of TlOsm and OsOlp1_A plants. These data demonstrated that both TlOsm and OsOlp1_A are positively involved in enhancing plant stress tolerance. These data also showed that the stress tolerance of TlOsm and OsOlp1_A plants was passed on the next generation. In comparison between TlOsm and OsOlp1_A plants in all the measured parameters, the performance of TlOsm and OsOlp1_A plants in salinity stress was undistinguishable except for the RWC at day 18 of reproductive stage stress treatment. In drought conditions, TlOsm plants showed superior to OsOlp1_A plants in most of the measured parameters. Cold stress at seedling stage caused more severe damage to OsOlp1_A leaf cells, as measured by electrolyte leakage (Figure 5.4), more reduction in dry biomass (Table 5.1), and produced more infertile tiller than to TlOsm plants. Thus, TlOsm plants exhibited more advantages than OsOlp1_A plants in cold stress response. The overlap in plant response to cold, drought and salinity stresses is osmotic adjustment. As discussed in Chapter 3, TlOsm seems not directly involved in ion stress at later phase of salt stress but likely to be in regulation of osmotic response because the gene was not up-regulated at later stage of salt stress. Effective osmotic adjustment allow plants to maintain cellular turgor when tissue water potential declines, maintain stomatal conductance and photosynthesis at lower water potentials, delay leaf senescence and death, reduce flower abortion, and improve plant growth (Manavalan and Nguyen, 2012). TlOsm and OsOlp1_A are likely to have similar functions in osmotic adjustment of plants. However, data resulting from the experiments on TlOsm and OsOlp1_A plants suggested that osmotic adjustment in TlOsm plants is more efficient than in OsOlp1_A plants. Based on the functional prediction (Table 3.2), TlOsm has more than OsOlp1_A three glucan-binding and 48 phosphorylation sites, and distinct four active residues of enzymes involved in carbohydrate metabolism. The more effective osmotic adjustment of TlOsm plants over OsOlp1_A plants is probably a functional consequence of these additional active residues of TlOsm. The remained question is whether these three types of residues all contribute to the more effective functions of TlOsm.
5.4.4 OsOlp1_I did not sufficiently enhance rice plants tolerance to cold, drought, and salinity stresses OsOlp1_I was found different with OsOlp1_A in only 10 AA in its protein sequence but the OsOlp1_I was isolated from drought sensitive cultivar IR64.
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Additionally, transcripts of OsOlp1_I was not induced by drought stress. As compared with VC and WT or NT plants, transgenic plants expressing OsOlp1_I did show some slight enhancements in some parameters such as shoot growth, RWC, electrolyte leakage, survival rate, and dry biomass but the patterns were not consistent throughout the generations, types of stresses, and the stages that stresses applied. Importantly, grain yield components, the target for rice improvement under stresses and the ultimate outcome necessary in rice stress tolerance, were not found improved in OsOlp1_I plants (Table 5.4). It has been demonstrated in rice that genes involved in stress tolerance at seedling stage are not necessarily involved in tolerance at reproductive stage (Sankar et al., 2011). OsOlp1_I might contribute to rice response to cold, drought, and salinity stresses at growth phase but its contribution was not very sufficient to be detectable in some measurements. In addition, during the adaptation process to a given environment, plants that are insufficient to reproduce will not be able to thrive and will not considered adaptive (Rosa et al., 2009). High proportion of OsOlp1_I spikelets was infertile when plants exposed to drought and salinity stresses and that resulted in low percentage of filled seeds. Even though OsOlp1_I plants produced more panicles than NT and VC under drought and salinity stresses, the total productive seeds per plant were not improved due to very high proportion of sterile spikelets. Seed weight of OsOlp1_I plants was similar as those of NT and VC plants. These results pointed out that OsOlp1_I did not confer tolerance in transgenic rice. Disregard its high sequence identity to OsOlp1_A, OsOlp1_I did not confer tolerance to cold, drought, and salinity stresses. Thus, activation by certain stress of a gene provides better indication for the involvement of the gene to that stress. Moreover, three lesser glucan-binding sites and one changed phosphorylation site as compared to OsOlp1_A would account for the lower functions of OsOlp1_I in plant stress response.
5.4.5 Low stomata conductance is possibly a cause of growth penalty of TlOsm plants under unstressed conditions. Rice plants constitutively expressing TlOsm had similar morphology and tillering capacity to control plants under unstressed conditions (Figure 5.2 & 5.8). The ripened seeds were harvested from all nine independent lines grown in glasshouse conditions and germinated normally, indicating that rice plants expressing TlOsm were fertile. However, relative to control plants, in all three sets of plants under unstressed conditions, growth rate of TlOsm plants was significantly slower (Figure 5.1), which
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further resulted in less dry biomass (Table 5.2 & 5.3), reduced panicle length, and seed weight (Table 5.4) that affected grain yield. Analysis of photosynthesis efficiency under unstressed conditions clearly indicated that net photosynthesis, stomatal conductance, and transpiration rate were all significantly lower in TlOsm plants.
Therefore, low stomatal conductance leading to low CO2 diffusion and resulting in low net photosynthesis seems to be one of the possible causes for growth penalty of TlOsm plants under unstressed conditions. There may be other causes related to energy uses for osmotic adjustment contributing to this growth penalty in TlOsm plants and need to be further explored. Despite the shorter panicle length, number of seeds per panicle was not reduced in TlOsm plants, as compared with the controls suggesting that constitutive expressing TlOsm did not alter the seed number determination. However, the yield penalty of TlOsm plants was from the smaller seeds and lower seed weight. It was not validated in this study but TlOsm contains potential four binding sites, which function in breaking down high molecular-weight sugars into smaller molecules (Table 3.2). Using soluble sugars for stress adaptation was found to be an effective strategy in plants (Rosa et al., 2009). Resurrection plants have been found to accumulate noticeably high level of soluble sugar for desiccation tolerance (Alpert and Oliver, 2002; Dinakar and Bartels, 2013; Gaff and Oliver, 2013). Thus, TlOsm might be involved in sugar metabolism to produce soluble sugars for stress adaptation that resulted in less starch accumulation and led to smaller seed weight. However, this assumption needs to be validated by an appropriate measurement. Similar trend was observed in T1 OsOlp1_A plants but the lower stomatal conductance was not always detected, which makes it difficult for an obvious explanation. A similar growth penalty was reported in transgenic mulberry constitutively expressing tobacco osmotin (Das et al., 2011). However, plants expressing the same gene under stress-inducible promoter did not exhibit growth reduction in unstressed conditions. While other causes of growth penalty in TlOsm plants need to be further exploited, the growth reduction of transgenic TlOsm (or OsOlp1_A) plants in unstressed conditions may be improved with the use of stress inducible promoter.
It has been known that stress tolerance in plants is a multi-genetic trait regulated by various molecular, biological and physiological processes (Sairam and Tyagi, 2004). However, recent studies have revealed a large overlap of genes function in plant stress signalling pathways enable some genotypes tolerate to multiple stress
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factors (Manavalan and Nguyen, 2012; Shabala and Munns, 2012). Two strategies have been suggested for genetic engineering rice with improved multi-abiotic stress tolerance: (1) incorporating a key regulator in common stress signalling pathways or (2) combining a whole QTL of important tolerant traits into elite rice cultivar (Babu, 2010; Swamy and Kumar, 2013). The limited number of genes that can be engineered into single genotype has made it difficult to combine whole QTL into one elite genotype (Atkinson and Urwin, 2012; Halpin, 2005; Mittler, 2006). Thus, seeking genes confer tolerance to multiple abiotic stresses holds a great promise for improving rice multi-abiotic stress tolerance that further ensures sustainable rice productivity under projected adverse climate conditions (Babu, 2010). Investigations in this study showed that tolerance of rice plants to cold, drought, and salinity stresses was significantly enhanced by expressing either TlOsm or OsOlp1_A, with a higher level of tolerance achieved in TlOsm expression. These results indicated the key functions of TlOsm and OsOlp1_A in enhancing plant tolerance to multi abiotic stress factors and highlight the potential of these genes for future uses in improvement of crops tolerance to cold, drought and salinity.
In conclusion, this chapter details the investigations in abiotic stress response of transgenic rice plants expressing osmotin genes (TlOsm, OsOlp1_A and OsOlp1_I) from stress tolerant and sensitive species (T. loliiformis vs. O. sativa). In contrast to VC and WT plants, TlOsm and OsOlp1_A plants displayed enhanced tolerance to cold, drought, and salinity stresses. This enhanced tolerance was demonstrated by maintained shoot growth and tillering capacity that resulted in higher dry biomass, survival rate, and grain yield than the control plants in exposure to the stresses. The highest level of tolerance was found in TlOsm plants. The enhanced stress tolerance of OsOlp1_I (identified from drought sensitive cultivar) was not sufficient due to few differences in compared with VC and WT plants and no yield improvement of OsOlp1_I plants. Tolerance of TlOsm and OsOlp1_A plants to cold, drought and salinity was found related to abilities to retain water, to maintain cell membrane integrity, and to maintain photosynthesis activities. The functions of TlOsm and OsOlp1_A were found associated with the regulation of osmotic adjustment, membrane protection, and stomatal movement. Importantly, the results pointed out a positive correlation between levels of stress tolerance and the number of active glucan- binding sites in the osmotin protein structures that rice plants expressing. The results
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also highlighted the additional effects of osmotin from tolerant species (TlOsm) in enhanced rice tolerance to cold and drought stresses, as compared with osmotin from sensitive species (OsOlp1_A). The molecular characteristics associated with the functions of these three osmotins will be investigated in the next chapter. The results in this study demonstrated the roles of TlOsm and OsOlp1_A in osmotic stress tolerance and highlighted the potential for their uses in developing crops tolerance to multiple abiotic stresses including cold, drought, and salinity. However, what needed in sustaining crop productivity for future food demand is a generation of crops that has high yield potential and adapted to adverse climate conditions. Hence, osmotic stress tolerance by lower stomatal conductance is not a desired trait due to its effects on productivity under unstressed conditions. The growth and yield penalty of TlOsm and OsOlp1_A plants in this study is probably a consequence of constitutively expressing the transgenes. For a practical use of TlOsm and OsOlp1_A, an inducible expression should be considered to minimize the effects on plant growth and productivity under unstressed conditions.
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Chapter 6: Analysis of Protein-Protein Interactions of Osmotins from Stress Tolerant and Sensitive Species
In Chapter 3, the comparison of potential functional binding sites of TlOsm from stress tolerant species (T. loliiformis) with two osmotins, OsOlp1_A and OsOlp1_I, from sensitive species (O. sativa) indicated TlOsm contained more potential glucan-binding and phosphorylation sites, followed by OsOlp1_A and lowest in OsOlp1_I. In Chapter 5, assessment of transgenic rice plants expressing TlOsm, OsOlp1_A or OsOlp1-I under cold, drought, and salinity stresses confirmed functional roles of TlOsm and OsOlp1_A in enhancing rice tolerance to cold, drought, and salinity stresses. Notably, plants expressing TlOsm were more stress tolerant. Osmotic stress tolerance levels in transgenic rice were found to be correlated with numbers of predicted functional sites of osmotins that rice plants expressing. Functions of TlOsm and OsOlp1_A in enhanced rice stress tolerance were demonstrated to be associated with the abilities to retain water, maintain membrane integrity and photosynthesis efficiency. These data suggest that the functional sites in osmotins contribute to the regulation of plant stress tolerance and that osmotin from stress tolerant species (TlOsm) have increased efficacy. Thus, an understanding of the protein binding complexes formed by these osmotins will provide the key information for the elucidation of the molecular mechanisms underlying their functions. This chapter aimed to identify potential plant proteins interacting with three target osmotins and possible stress responsive pathways involving them.
6.1 INTRODUCTION
Biological processes are driven by protein-protein interactions and the functional properties of many proteins are determined by their respective protein-protein interactions (Hu et al., 2005). Therefore, the study of protein-protein interaction can provide insight into the biological functions and complex cellular networks of protein with unknown functions (Fukao, 2012). The laborious and time-consuming procedures associated with protein studies in the past have limited the discovery of gene functions
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at protein levels (Hu et al., 2011). The recent availability of advanced technologies enables unprecedented options for high-throughput identification of protein-protein interactions and visualisation of protein-protein interactions in living cellular environment. Various studies using protein microarrays have indicated the Arabidopsis protein microarray as an excellent platform for high throughput screening the plant proteins interacting with a given protein (Popescu et al., 2007a; Popescu et al., 2007b; Popescu et al., 2009). The protein-protein interactions in living cells can be directly visualised by bimolecular fluorescence complementation (BiFC) analysis (Kerppola, 2013). These advances offer a valuable complement to unravel biological functions for the proteins of interest.
Osmotins are a class of pathogenesis-related proteins that play key roles in both abiotic and biotic stress responses of plants. However, the mechanisms underlying their functions in plant stress responses remain to be elucidated due to the lack of information in their protein interactive partners and pathways. Numerous studies have been carried out on osmotins, but to date only few interactive partners of osmotin have been revealed. One of the major limitations for direct study osmotin protein is the difficulties associated with producing recombinant osmotins. Osmotin has been known for its hydrophobicity, anti-microbial property and the presence of 8 disulfide bonds in its structure that have made it difficult for expressing in microbial system with proper folding of resulted proteins. The current protocols for recombinant osmotin production in microbial system require targeting osmotin in the inclusion bodies, denaturing osmotin during protein extraction and refolding the protein (Campos et al., 2008; Tzou et al., 2011). However, with 8 disulfide bonds in the structure, the refolding osmotin is a difficult step accompanied with limited protein yield upon water-insoluble of the hydrophobic protein. These limitations would be overcome by the progresses of genetic manipulation and protein expression system (discussed in Section 1.6.2). For the ultimate purpose of functionally characterising TlOsm, we compared the predicted functional sites of TlOsm with two rice osmotins and demonstrated the roles of TlOsm and OsOlp1_A in enhanced rice tolerance to cold, drought, and salinity stresses (in Chapter 3 and 5). This study aimed to gain insights into functions and pathways of these osmotins via their interactive partners and biological networks involving their interactive protein partners.
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The objectives of this study were set as follows:
1. Produce and purify functional recombinant osmotins (TlOsm, OsOlp1_A, and OsOlp1_I). 2. Identify potential protein partners by Arabidopsis protein chip assays. 3. Identify biological pathways that play role in osmotin functionalities. 4. Validate interactions of the three osmotins with Arabidopsis stress-responsive proteins in planta.
6.2 MATERIALS AND METHODS
6.2.1 Plant materials Nicotiana benthamiana plants were used for both transient expression of recombinant osmotins and co-expression of osmotins with their putative Arabidopsis interactive protein partners in the BiFC analysis. Plants were germinated, grown, and prepared for Agro-infiltration as described in Section 2.1.2.3.
6.2.2 Plasmid vectors 6.2.2.1 Plasmid vectors for expressing recombinant osmotins The plasmid pEAQ-TlOsm, pEAQ-OsOlp1-A, and pEAQ-OsOlp1-I were used for producing recombinant osmotins. In these plasmids, osmotins were tagged with different elements necessary for high protein production, purification, and detection of protein-protein interaction on protein microarrays. The gene expression cassettes of these plasmids are shown in Figure 6.1. Generally, the tagged osmotins are driven by the CaMV 35S promoter and the Nos terminator and placed within the Cowpea Mosaic Virus 5’ upstream translational enhancer. The P19 gene under control of the CaMV 35S promoter and terminator used for suppressing of gene silencing, which is usually faced in plant transiently expressing of foreign genes. The NptII gene under regulation of the Nos promoter and terminator was plant selectable marker against kanamycin antibiotic. The methods used for constructing these plasmid are described in Section 2.2.1.
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Figure 6.1 Schematic diagram of gene expression cassettes for transiently expressing tagged osmotins in N. benthamiana. LB: left border, RB: right border
6.2.2.2 Plasmid vectors for detection of protein-protein interactions Plasmids with the gene expression cassettes shown in Figure 6.2 were used in the BiFC assay for detecting protein-protein interaction in planta. The TlOsm, OsOlp1_A and OsOlp1_I genes were fused at their protein C-terminus with a DNA fragment encoding half molecule of EYFP from N-terminus to AA 174. Five Arabidopsis genes AtCPK4, AtCPK5, AtMS1, AtALDH7B4, and AtPER42 were fused at their protein C-terminus with a DNA fragment encoding half molecule of EYFP from AA 175 to the end of protein molecule. The Tobacco Etch Virus translational enhancer was incorporated upstream of all the three osmotins and five Arabidopsis genes. The fused genes together with the enhancer were driven by the tandem CaMV 35S promoter and terminator. Details of methods used for constructing these plasmids were presented in the Section 2.2.1.
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Figure 6.2 Schematic diagram of gene expression cassettes for detecting target osmotins and Arabidopsis protein interaction in N. benthamiana. A) TlOsm, OsOlp1_A, or OsOlp1_I cloned in the pE3134 destination vector; B) 5 Arabidopsis genes separately cloned in the pE3132 destination vector. LB: left border, RB: right border
6.2.3 Protein expression in Nicotiana benthamiana Wild type N. benthamiana plants were grown in pots in a growth chamber under the conditions described in Section 2.1.2.3 for at least five weeks then were used for agro-infiltration. The plant overexpression vectors pEAQ-TlOsm, pEAQ-OsOlp1-A, and pEAQ-OsOlp1-I were separately transformed into Agrobacterium strain Alg1 using the methods described in Section 2.2.1.5. Agrobacterium Alg1 containing
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pEAQ-TlOsm, pEAQ-OsOlp1-A, or pEAQ-OsOlp1-I vectors were grown and prepared for infiltration, and infiltrated into N. benthamiana leaves of 5-week-old plants by the methods described in Section 2.2.3. Fifteen plants with 3 leaves (number 3-5 from the top) per plant were used for each plasmid construct and the WT control was infiltrated with the infiltration medium. Four days after infiltration, N. benthamiana leaves were harvested. Aliquots of approximately two grams of infiltrated leaves were wrapped in aluminium foil, immediately frozen in liquid nitrogen, and stored at -80 oC for protein extraction.
6.2.4 Recombinant protein extraction, purification, and enrichment Extraction of total proteins from the frozen leaf tissues was done in 50 mM phosphate buffer. Frozen infiltrated leaf samples were ground to a fine powder in liquid nitrogen prior to homogenisation in 6 mL of 50 mM phosphate extraction buffer (50 mM phosphate buffer pH 7.4, 300 mM NaCl, 10% glycerol, 0.1% Triton X-100, 1 mM PMSF and 1x complete protease inhibitor cocktail (Sigma, St. Louise, MO, USA). Samples were homogenised by gentle rotation at 4 oC for two hours. Cell debris was removed by centrifugation at 4000 g at 2 oC for 5 min. Further removal of solids was performed by centrifugation of the supernatant at 14 000 g at 4 oC for 20 min. The recombinant proteins were enriched and purified using a three-step purification protocol described below. Each total protein extract was pre-purified using 3 His-spin columns of His-Spin Trap Kits (GE healthcare Life Sciences) following the manufacturer’ protocol, then eluted into 1200 mL of elution buffer. The solution containing pre-purified proteins was incubated at 4 oC with Protein G Mag SepharoseTM Xtra beads (GE healthcare Life Sciences) overnight with gentle rotation. Beads with bound proteins were then washed two times with Wash buffer
(137 mM NaCl, 2.7 mM KCL, 100 mM Na2HPO4, 2 mM KH2PO4, pH 7.4). The recombinant proteins were eluted from the beads through incubation with 12 µL (50 units) of 3C protease (Precision protease; Amersham Biosciences) in 500 µL of cleavage buffer (50 mM Tris HCl pH 7.0, 150 mM NaCl, 1 mM EDTA, 1 mM DTT, 0.1% Triton) overnight in a cold room with gentle rotation. The following day, the recombinant proteins in the cleavage were first separated from the beads, and went through the His-Spin columns to eliminate the excess protease and other track elements. The proteins trapped in the His-Spin columns were eluted, mixed with glycerol to a final concentration of 30%, and stored at -80 oC. Protein concentration was determined using the Bradford assay (Bradford, 1976).
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6.2.5 SDS-PAGE SDS-PAGE (sodium dodecyl sulphate polyacrylamide gel electrophoresis) was used to separate proteins. The protein extracts were run on a 12% resolving gel (dH2O 4.170 mL, 1.5 M tris pH 8.8 2.5 mL, 10% SDS 100 µL, 40% acryl/bis (29:1) 3.125 mL,
10% ammonium persulphate 100 µL and TEMED 5 µL) and 5% stacking gel (dH2O 2.916 mL, 1 M tris pH 6.8 0.5 mL, 10% SDS 40 µL, 40% acryl/bis (29:1) 0.5 mL, 10% ammonium persulphate 40 µL and TEMED 4 µL). Gel was prepared using a Mini SDS- PAGE gel apparatus (Bio-Rad, Hercules, CA, USA) according to the manufacturers’ protocol. Protein extracts and loading buffer were mixed in a ratio of 4:1 (v/v), followed by a short spin and then heated for 10 min at 95 oC. A 15 µL aliquot was loaded to each well and the gel was run for 3 h at 120 V. Coomassie blue dye was used for verification of proteins on the SDS-PAGE gel.
6.2.6 Coomassie blue staining The separated proteins in the SDS-PAGE gel were stained in Coomassie blue solution (0.1% Coomassie Brilliant blue R-250, 50% methanol and 10% glacial acetic acid) for at least 1 h with gentle agitation until the gel was in a uniform blue colour. Gels were de-stained overnight in a 25% methanol and 10% glacial acetic acid solution with gentle agitation until the background cleared. Images were captured using a Cannon camera with a white light background.
6.2.7 Western blotting After electrophoresis, proteins in the SDS-PAGE gel were transferred onto a nitrocellulose membrane (immobilonTM; Millipore) using a mini SDS-PAGE apparatus tank (Bio-Rad, Hercules, CA, USA). The sandwich was prepared according to the manufacturers’ protocol, placed in the tank filled with blotting buffer (25 mM Tris, 192 mM glycine, 10% methanol) and proteins were transferred overnight at 15 V in the cold room. The following day, the apparatus was disassembled. The membrane was blocked using blocking buffer (TBST, 5% (v/w) skim milk powder) for 1 h with gentle shaking on a rotate shaker. The blocking solution was discarded and 12 mL of a dilute (1:5000) of primary antibody (mouse monoclonal anti-human c-myc unconjugated antibody) (Invitrogen, Carlsbad, CA, USA) in 5%-skim milk TBS buffer solution was added. The membrane was incubated overnight in the cold room with gentle agitation. Following incubation, the membrane was washed four times with TBST buffer with gentle
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agitation, 10 min per each wash. The membrane was incubated with secondary antibody (Goat-Anti-Mouse IgG (H+L)-HRP) (Life Technologies) diluted at a 1:20000 ratio in 5%-skim milk containing TBS solution for 1 h at room temperature with gentle agitation. Following the incubation, the membrane was washed four times with TBST buffer with gentle agitation, 10 min per each wash. The chemiluminescent detection assay was performed according to the DIG (Roche) protocol.
6.2.8 Protein chip hybridisation and scanning The high-density Arabidopsis protein microarrays (chip or slide; 5000- AtPROTEINCHIP1) were provided by Dinesh-Kumar Laboratory (Department of Plant Biology & Genome Centre, University of California, Davis, USA) and purchased from the Arabidopsis Research Centre (Ohio, USA). These chips were used to identify Arabidopsis proteins interacting with TlOsm, OsOlp1_A, and OsOlp1_I. The protein slides stored at -80 oC were equilibrated at 4 oC by putting each slide into a 50- ml Falcon tube with closed cap and placed in the cold room for 15 min. The slides were blocked in PBS-T (137 mM NaCl, 2.7 mM KCl, 10 mM Na2HPO4, 1.8 mM
KH2PO4, 0.1% (v/v) Tween-20, and 1% (w/v) BSA) for 1 h. Eight micrograms of purified recombinant osmotin in 50 mM phosphate buffer were diluted in a probing solution (1X PBS, 5 mM MgCl2, 0.05% (v/v) Triton X-100, 5% (v/v) glycerol and 1% (w/v) BSA) to the final volume of 250 µL. The probing solution containing each osmotin was separately applied to each slide surface and the slide was covered by a glass slide, incubated for 1.5 h at 4 oC. Slides were then washed 3 times with probing solution with a gentle agitation for 10 min per each wash. The slides were incubated with 12 mL of a dilute (1:5000) primary antibody (mouse monoclonal anti-human c- myc unconjugated antibody) (Invitrogen) in probing solution for 2 h in the cold room. The unbound antibody was removed from the slides by washing the slides 4 times in probing solution with 10 min per wash on an orbital shaker. The slides were incubated with Cy5 conjugated-Goat-anti-mouse IgG antibody (Jackson ImmunoResearch Laboratory, Inc.) diluted in probing buffer (1:700) for 1 h at room temperature with a gentle agitation. The slides were washed for 3 times with probing solution with a gentle agitation for 10 min per each wash to remove the unbound secondary antibody. The slides were then dried by draining off the washing solution and putting into a 50-mL Falcon tube with a piece of Kimwipe tissues at the bottom of the tube. The tube containing slide was spined for 1 min at 1000 g. Slides were stored inside the Falcon
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tube at room temperature until being scanned in the day after. Slides were scanned using a Genepix 4300A slide scanner (Axon Instruments).
6.2.9 Identification of significant interactions The scanned microarray images were subsequently processed following the instruction described by Zhou-Da et al. (2008). The GenePix Pro software (Molecular Devices, Union City, CA) was used to determine the spot intensity. A grid of circles was placed over the protein spots on the chip. The position and size of the spots were adjusted to be insight the circles for an accurate intensity data. For each slide, an output file containing mean, median, and standard deviation of array spots and background intensity was created by the program. These output files with background intensity of each spot were subjected for analysis of significant interactions (Diez et al., 2012). The mean, standard deviation, and standard error of the mean values were calculated for 5210 entry names on the slides including all Arabidopsis proteins on the chip and multiple positive and negative controls. The significant probe-binding candidates were determined using one-sided Student’s t-test, pooled variance and 5% significance level. All the mean values that were not significant lower than the mean values of positive control, the RIN4-cMyc (12 spots) were considered as significant candidates for further analysis.
6.2.10 Determination of significant protein interactors of target osmotins The description of the Arabidopsis proteins on the chip significantly interacted with the target osmotins was looked up through the DAVID database (Huang et al., 2009; Sherman et al., 2007) using TAIR_ID identifier. The entire list of interactors of each target osmotin was submitted to the Gene Name Batch Viewer tool for revealing the name of the osmotin interactors. Gene ontology (GO) term enrichment was performed separately for the protein sets considered to significant interacted with all three osmotins (271 proteins) with TlOsm and OsOlp1_A (11 proteins), or with only TlOsm (21 proteins) using agriGO web server (Du et al., 2010). The entire list of each set of interactors was submitted to the analysis tool using Singular Enrichment Analysis (SEA). Each gene set was enriched using a Fisher’s exact test with the Arabidopsis genomodel 9 as a reference and biological process as a category. For statistical significance, P-values were corrected according to Benjamini and Hochberg (1995) and a critical false discovery rate (FDR) q- value of 0.05 was applied. The significant GO term for each protein set was summarised and visualised by REVIGO server (Supek et al., 2011) and viewed as Treemap.
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6.2.11 Identification of pathways containing interactive protein partners of TlOsm, OsOlp1_A, and OsOlp1_I The entire list of three osmotin interactive protein partners was submitted to the DAVID Database for Annotation, Visualisation and Integrated Discovery (version 6.8) for gene ID conversion, using TAIR ID as gene identifier, to convert the list into Genomic GI Accessions (GIs). The output GIs list was retrieved and used as input for automated annotation and identification of enriched pathways (KEGGS, Panther and BioCyc) using KOBAS 2.0 web server (Wu et al., 2006; Xie et al., 2011). Statistical significance P-values were corrected according to Benjamini and Hochberg and applied a False Discovery rate q-value of 0.05.
6.2.12 BiFC performance and analysis 6.2.12.1 Determination of Arabidopsis candidate genes for BiFC analysis All potential protein partners of TlOsm, OsOlp1_A, and OsOlp1_I that were identified as significant on the protein chip were classified into 7 categories: (1) the common interactors of all three osmotins, (2) the interactors of TlOsm and OsOlp1_A, (3) the interactors of TlOsm and OsOlp1_I, (4) the interactors of OsOlp1_A and OsOlp1_I, the interactors of only (5) TlOsm, (6) OsOlp1_A, or (7) OsOlp1_I. The selection of candidate genes for BiFC analysis focused on the common interactors, the TlOsm and OsOlp1_A, and the TlOsm only interactors. The AtPER42 was used as negative control due to non-detected interaction with all three osmotins on the chip. The candidates were selected based on their well- characterised roles in plant stress response. The selective candidate genes for BiFC analysis are presented in Table 6.1. The full length cDNA sequences of the selective genes were retrieved from the NCBI database and used for primer design in plasmid vector cloning. The genes were amplified from Arabidopsis cDNA and cloned in the pE3132 vector as described in Section 2.2.1 and the gene expression cassettes of the vectors are in Figure 6.2.
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Table 6.1 Select Arabidopsis genes for BiFC analysis TAIR ID Gene name Description Category AT4G09570 AtCPK4 Calcium-dependent protein kinase 4 Common interactor of all three osmotins AT4G35310 AtCPK5 Calcium-dependent protein kinase 5 Common interactor of all three osmotins AT5G17920 AtMS1 5-methyltetrahydropteroyltriglutamate- Interactor of TlOsm -homocysteine methyltransferase and OsOlp1_A AT1G54100 AtALDH7B4 Aldehyde dehydrogenase family 7 Interactor of TlOsm member B4 only AT4G21960 AtPER42 Peroxidase 42 Negative control
6.2.12.2 Co-expression of target osmotins and Arabidopsis genes in N. benthamiana Five-week-old wild type N. benthamiana plants were grown in pots in a growth chamber under the conditions described in Section 2.1.2.3. The Agrobacterium strain Alg1 separately carrying each vector in Figure 6.2 and the pCE100_EYFP (positive control) were grown and prepared for infiltration as method described in Section 2.2.3. Before infiltration, equal amount of each Agrobacterium sample containing each osmotin and each Arabidopsis gene were combined (the combinations are shown in Table 6.2) and infiltrated into N. benthamiana leaves of 5-week-old plants by the methods described in Section 2.2.3.
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Table 6.2 Combinations of osmotins and Arabidopsis genes used for co-expression and BiFC analysis
N0 Combinations Interaction on the chips
1 pE3134-TlOsm and pE3132-AtCPK4 + 2 pE3134-OsOlp1_A and pE3132-AtCPK4 + 3 pE3134-OsOlp1_I and pE3132-AtCPK4 + 4 pE3134-TlOsm and pE3132-AtCPK5 + 5 pE3134-OsOlp1_A and pE3132-AtCPK5 + 6 pE3134-OsOlp1_I and pE3132-AtCPK5 + 7 pE3134-TlOsm and pE3132-AtMS1 + 8 pE3134-OsOlp1_A and pE3132-AtMS1 + 9 pE3134-OsOlp1_I and pE3132-AtMS1 - 10 pE3134-TlOsm and pE3132-AtALDH7B4 + 11 pE3134-OsOlp1_A and pE3132-AtALDH7B4 - 12 pE3134-OsOlp1_I and pE3132-AtALDH7B4 - 13 pE3134-TlOsm and pE3132-AtPER42 - 14 pE3134-OsOlp1_A and pE3132-AtPER42 - 15 pE3134-OsOlp1_I and pE3132-AtPER42 - 16 pCE100_EYFP Positive control 17 Infiltration medium Negative_WT control
6.2.12.3 Sample preparation and imaging Two days post-infiltration, leaves from each combination were harvested and fixed using the methods described in Section 2.2.4. The fixed samples were examined under the A1 Confocal Microscope (Nikon, Tokyo, Japan). The images were captured under 488 nm laser channel with emission of 500-550 nm for green fluorescence and 638 nm laser channel with emission of 663-738 nm for autofluorescence. The captured images were used for analysis of target osmotins and Arabidopsis protein interactions in planta.
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6.3 RESULTS
6.3.1 Expression and purification of recombinant osmotin proteins To perform hybridisation of protein probes and the protein chips, the protein probes need to be pure, functional, and containing the tags necessary for detection. Gene constructs containing osmotins with all tags necessary for recombinant osmotin purification and detection on the chip and elements for enhancing protein production were prepared. The gene constructs were transiently expressed in N. benthamiana. Recombinant osmotins were extracted in 50 mM phosphate buffer and purified through 3 steps based on His and IgG tags fused with the osmotins. First, recombinant osmotins were enriched by passing the protein extract through a His SpinTrap column that only binds the protein with His tag. The elution from His SpinTrap columns was inoculated with Protein G Mag Sepharose Xtra beads that bind to the IgG tag of recombinant osmotins. The proteins were cleaved from the beads by incubating with Precision Proteases. Then the cleaved protein solutions once went through the His SpinTrap columns to eliminate all the tag elements and the excessive protease in the buffer so that only proteins with His tag bound to the columns. Following elution from the final His SpinTrap columns, the protease-cleaved and purified osmotins were confirmed by Coomassie staining of SDS-PAGE gel and western blot analysis. Figure 6.3 presents the schematic of recombinant osmotins with estimated sizes before and after cleavage and the images of Coomassie stained SDS-PAGE gel and western blot film of the purified recombinant osmotins.
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Figure 6.3 Recombinant osmotin production. A-B) schematic diagram of recombinant osmotins and estimated sizes before (A) and after protease cleavage (B); C-D) visualisation of cleaved and purified osmotins by Coomassie staining of PAGE gel (C) and western blot (D); film was exposed for 5 min; ML, molecular ladder; WT-Ctrl, wild type control
Results from SDS-PAGE gel Coomassie stain and western blot analysis indicated that all three recombinant osmotins were obtained at high purity and identity. Coomassie stained SDS-PAGE gel (Figure 6.3 C) showed the bands of OsOlp1_A, OsOlp1_I and TlOsm with 9xMyc and His-6 downstream tags similar to their estimated sizes (Figure 6.3 B). The bands were intense with little smearing, thus suggesting the intact and purity of resulted osmotins. Western blotting using antibody against Myc tag verified the identity of the purified proteins as demonstrated by intensive bands after only 5 min of film exposure. The results here demonstrated that the purpose of obtaining pure recombinant OsOlp1_A, OsOlp1_I and TlOsm with all necessary tags was achieved by using advanced gene manipulation and multi-step protein purification.
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6.3.2 Arabidopsis proteins interacting with TlOsm, OsOlp1_A, and OsOlp1_I revealed The functions of unknown proteins can be discovered through the study of their respective protein partners with known functions (Rao et al., 2014). TlOsm from desiccation tolerant species, T. loliiformis, and its counterparts, the OsOlp1_A and OsOlp1_I, from drought-tolerant and –sensitive cultivars of stress sensitive species, O. sativa, were previously compared in their predicted functional residues and in their contribution in enhanced stress tolerance of transgenic rice. To provide new insights into the mechanisms and pathways of TlOsm and its counterparts in plant stress response, Arabidopsis proteins on the 5000-AtPROTEINCHIP1 interacting with the three osmotins were screened. Each of purified recombinant TlOsm, OsOlp1_A, and OsOlp1_I downstream by Myc epitope and His tags was probed with separate protein chip. The primary antibody, the anti-Myc IgG, detected the Myc epitope was incubated for detecting the interaction. Then, the anti-IgG antibody with Cy5 conjugated was incubated to bind the anti-Myc IgG. The protein-protein interaction was detected by scanning with the Cy5 fluorescence for the indication of interaction. The GenePix Pro software was used to determine the fluorescence intensity of the spots. Fluorescent intensity of the interaction was analysed according to the instruction of the software. For each slide, an output file containing mean, median, and standard deviation of array spots and background intensity was created by the program. These output files with background intensity of each spot were subjected for analysis of interactions. This procedure is illustrated in Figure 6.4.
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Figure 6.4 Procedure of recombinant osmotins hybridising with protein chips and data generation
6.3.2.1 Identification of Arabidopsis proteins on the chip interacting with TlOsm, OsOlp1_A, and OsOlp1_I The mean, standard deviation, and standard error of the mean values were calculated for each spot (5210 entry names) on each slide including all Arabidopsis proteins (expressed as TAIR_ID) on the chip and multiple positive and negative controls. One-sided Student’s t-test was used and the false discovery rate by FDR method (Storey, 2002) was applied to determine the significant interactions. Total of 271 Arabidopsis proteins on the chips were found significantly interacted with TlOsm, OsOlp1_A, and OsOlp1_I. The list of total 271 Arabidopsis proteins either common or specific interacted with OsOlp1_A, OsOlp1_I, and TlOsm was analysed against the DAVID database for functional analysis using TAIR_ID identifier (Jiao et al., 2012). The profile for all Arabidopsis proteins on the chip interacting with each respective osmotins is provided in Appendix E-Table 1. These proteins were in various families and appeared to be involved in a diverse biological process of plant stress responses and development.
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6.3.2.2 More Arabidopsis proteins on the chip interacted with TlOsm than with OsOlp1_A, and OsOlp1_I Structural-to-functional predictions suggested more functional sites for TlOsm than two rice osmotins. For rice osmotins, OsOlp1_A has three more glucan-binding sites than OsOlp1_I; and the two differ in one phosphorylation site. Functional validation in transgenic rice indicated the positive correlation between the levels of stress tolerance and functional sites of the transgenes they expressed. In order to prove the hypothesis that protein with more functional sites binds to more proteins in the same condition, chips containing 5000 Arabidopsis proteins were separately hybridised with each target osmotin. As indicated in Table 6.3, TlOsm had 267 significant interactors while OsOlp1_A had 239 interactors, and OsOlp1_I interacted with 237 proteins. In the same hybridisation conditions and the same quantity of proteins applied, there were more proteins interacting with osmotin from T. loliiformis than with those from O. sativa. The results are in agreement with the hypothesis.
Table 6.3 Comparison of significant interactions between Arabidopsis proteins on the chip with the three osmotins Parameters Number of Arabidopsis proteins All proteins interacting with 3 osmotins 271 Proteins interacting with TlOsm 267 Proteins interacting with OsOlp1_A 239 Proteins interacting with OsOlp1_I 237 Proteins commonly interacting with the 3 osmotins 225 (83.03%) Proteins interacting with OsOlp1_A and TlOsm 11 (4.05%) (not OsOlp1_I) Proteins interacting with OsOlp1_A and 1 (0.37%) OsOlp1_I (not TlOsm) Proteins interacting with OsOlp1_I and TlOsm 10 (3.69%) (not OsOlp1_A) Proteins specifically interacting with TlOsm 21 (7.75%) Proteins specifically interacting with OsOlp1_A 2 (0.74%) Proteins specifically interacting with OsOlp1_1 1 (0.37%)
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The interactors of these three osmotins were categorised into 7 groups: those commonly interacted with all three osmotin (83.03%), those interacted with OsOlp1_A and TlOsm (not OsOlp1_I) (4.05%); those interacted with OsOlp1_A and OsOlp1_I (not TlOsm) (0.37%), those interacted with OsOlp1_I and TlOsm (not OsOlp1_A) (3.69%), those specifically interacted with only TlOsm (7.75%), OsOlp1_A (0.74%) and OsOlp1_I (0.37%). In Chapter 5, TlOsm and OsOlp1_A genes were proven to confer tolerance to cold, drought, and salinity stresses with the higher level of stress tolerance found for TlOsm plants. Thus, the interactors of OsOlp1_A and TlOsm and with only TlOsm were highlighted for further analysis on their functions in cold, drought, and salinity response (Table 6.3). The common interactors of these osmotins hold potential for understand the common functions of these osmotins in biotic stress response and plant development.
6.3.3 Gene ontology (GO) enrichment for interactors of the three osmotins To help understand the molecular function and biological process of the Arabidopsis proteins interacting with TlOsm, OsOlp1_A, and OsOlp1_I, the GO enrichment was performed for all the 271 proteins interacted with the three osmotins. The GO terms were enriched in agriGO web server against the Arabidopsis genomodel 9 background (Du et al., 2010). A total of 37767 GO terms was suggested and 127 GO terms were found significantly enriched in the protein-binding gene set (adjusted P- value ≤ 0.05) (Appendix E-Table 2). All the significant GO terms displayed by biological process were summarised and visualised by REVIGO web server (Supek et al., 2011) using Treemap. Figure 6.5 presents the biological processes that the 271 interactors of TlOsm, OsOlp1_A, and OsOlp1_I significantly participate in.
The data showed that TlOsm, OsOlp1_A, and OsOlp1_I bound proteins are involved in the diverse biological process of plant stress responses and development such as response to abiotic stress, disease, endogenous stimuli, signal transduction, carboxylic acid biosynthesis, cellular process and metabolism. Thus, the data suggest that the functions of these osmotins in multiple stress responses and development of plants.
A total 83.03% of the 271 three osmotins interactors are in common for TlOsm, OsOlp1_A, and OsOlp1_I. However, TlOsm, OsOlp1_A, and OsOlp1_I differentially responded to cold, drought and salinity stresses as evidenced by the results in the Chapter 5. The key functional mechanisms underlying the different regulations of TlOsm, OsOlp1_A, and OsOlp1_I in plant stress response could
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rely on the 16.97% of their different interactive partners. Only TlOsm and OsOlp1_A conferred tolerance to cold, drought and salinity stresses in transgenic rice with the higher levels of tolerance to cold and drought for TlOsm. Hence, interactors of TlOsm and OsOlp1_A should be the focus for understanding the underlying mechanisms for abiotic stress tolerance of TlOsm and OsOlp1_A. Thus, GO term enrichment and biological process involving the interactors of TlOsm and OsOlp1_A and those of TlOsm only were analysed and highlighted as the black and red ovals in Figure 6.5.
Figure 6.5 Biological processes involving protein interactors of TlOsm, OsOlp1_A and OsOlp1_I based on Gene Ontology analysis. Area of rectangles reflects the proportion of GO terms; back ovals indicate the GO distribution of 11 interactors of TlOsm and OsOlp1_A (not OsOlp1_I); red ovals indicate the GO distribution of 21 interactors of TlOsm.
Interestingly, proteins interacting with TlOsm and OsOlp1_A participate in a number of biological processes (Figure 6.5, back ovals); while those only interacting with TlOsm participated in response to stress and stimuli only (Figure 6.5, red ovals). Interacting with more proteins in the process of plant response to stresses and stimuli would explain for higher effects on enhancing rice tolerance to abiotic stresses of TlOsm (Chapter 5).
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6.3.4 Pathways of TlOsm, OsOlp1_A, and OsOlp1_I interactive protein partners revealed Understanding the pathways involved in a set of genes or proteins provides valuable biological insights into their functions (Wu et al. 2006). To investigate the biological pathways involving the target osmotins, the pathways of their interactors were analysed. The entire list of TlOsm, OsOlp1_A, and OsOlp1_I interactors with TAIR_ID identity was converted into gene identity (GI) in DAVID knowledgebase server. The list with GIs was used as input for pathway analysis in KOBAS 2.0 server (Xie et al., 2011). In this analysis, GIs were subjected for automated annotation and a Fisher’s exact test for differential GO term distribution. The pathway enrichment analysis based on automated annotation generated by KOBAS was further used to look up the number of interactors for each osmotin interactor category. The details of entire putative pathways involving all interactors of the osmotins are presented in the Appendix E-Table 3.
Table 6.4 Significant pathways of Arabidopsis proteins interacting with TlOsm, OsOlp1_A, and OsOlp1_I (background indicates the number of proteins in the pathways available in the database)
Biological pathway Background TlOsm OsOlp1_A OsOlp1_I number interactors interactors interactors Fructose and mannose 62 8 7 6 metabolism Glycolysis 113 11 10 9 Pentose phosphate pathway 54 7 6 5 Benzoate biosynthesis II 6 3 2 2 Alkane oxidation 6 3 2 2 Riboflavin metabolism 9 3 1 1 Super pathway of lysine, threonine and methionine 24 5 4 4 biosynthesis Fatty acid alpha oxidation I 7 3 2 2 Flavonoid biosynthesis 21 4 3 2 Ethanol degradation II 16 4 3 3
Interactive protein partners of the three osmotins are involved in diverse putative biological pathways, suggesting the involvements of the osmotins in various pathways. No pathway specific to rice osmotin interactors was identified but nine pathways were found specific for TlOsm interactors. Notably, even in conserved pathways, the numbers of TlOsm, OsOlp1_A, OsOlp1_I interactors were different with TlOsm binding to
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more proteins in the pathways. Table 6.4 presents the ten most significant pathways involving interactors of TlOsm, OsOlp1_A, and OsOlp1_I. These pathways provide more informative indicator for testing hypothesized functions of these osmotins. Moreover, the interactors involved in nine pathways specific for TlOsm would offer great targets for exploiting any additional functions of osmotin from stress tolerant species.
Since the focuses of this study were to understand the mechanisms and pathways associated with the osmotins conferred tolerance to abiotic stresses, the pathways only containing TlOsm and OsOlp1_A were used for further analysis. Table 6.5 lists all the pathways containing interactors of TlOsm and OsOlp1_A, or TlOsm only. Among these 18 pathways, 9 pathways contain proteins interacting with TlOsm and OsOlp1_A and 9 pathways contain proteins only interacting with TlOsm. These pathways are within biosynthesis, oxidative phosphorylation, and amino acid degradation.
Table 6.5 Pathways of Arabidopsis proteins interacting with TlOsm and OsOlp1_A, or TlOsm only (background indicates the number of proteins in the pathways available in the database; input indicates the numbers of osmotin interactors)
Background TlOsm& TlOsm Pathway name Database number Input OsOlp1_A only Scopoletin biosynthesis BioCyc 9 2 1 1 Suberin monomers biosynthesis BioCyc 17 2 1 1 Chlorogenic acid biosynthesis I BioCyc 17 2 1 1 Phenylalanine metabolism KEGG PATHWAY 42 2 1 1 Phenylpropanoid biosynthesis BioCyc 37 2 1 1 Stilbenoid, diarylheptanoid and gingerol biosynthesis KEGG PATHWAY 61 2 1 1 UDP-sugars interconversion BioCyc 19 1 1 Carotenoid biosynthesis KEGG PATHWAY 29 1 1 Oxidative phosphorylation KEGG PATHWAY 162 1 1 Valine biosynthesis BioCyc 6 1 1 Superpathway of isoleucine and valine biosynthesis BioCyc 7 1 1 Quercetin sulfate biosynthesis BioCyc 8 1 1 Leucine biosynthesis BioCyc 8 1 1 Superpathway of flavones and derivatives biosynthesis BioCyc 8 1 1 UDP-D-xylose biosynthesis BioCyc 11 1 1 Leucine degradation I BioCyc 12 1 1 Valine degradation I BioCyc 14 1 1 Superpathway of leucine, valine, and isoleucine biosynthesis BioCyc 15 1 1
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Beside the roles in abiotic stress tolerance, osmotin has been suggested to participate in plant signalling and pathogen defense and to be used as a therapeutic component for human disease treatment (discussed in Section 1.3). Thus, the pathways related to these aspects and containing three osmotin interactors were also analysed and presented in Table 6.6. Even though these 10 pathways were common for interactors of all three osmotins, the number of TlOsm interactors was higher in five pathways.
Table 6.6 Pathways of Arabidopsis proteins commonly interacting with TlOsm, OsOlp1_A, and OsOlp1_I in relation to published and predicted functions of osmotin
Background Common TlOsm& TlOsm& TlOsm Pathway name Database Input number interactors OsOlp1_A OsOlp1_I only Plant-pathogen KEGG 167 10 7 1 1 1 interaction PATHWAY
Cadherin signalling PANTHER 8 2 1 1 pathway
Nicotinic acetylcholine receptor signalling PANTHER 15 2 1 1 pathway Apoptosis signalling PANTHER 21 1 1 pathway
Phosphatidylinositol KEGG 68 2 2 signalling system PATHWAY
Plant hormone signal KEGG 271 8 7 1 transduction PATHWAY Inflammation mediated by chemokine and PANTHER 19 2 1 1 cytokine signalling pathway KEGG Insulin resistance 37 1 1 PATHWAY Huntington disease PANTHER 36 3 2 1
Parkinson disease PANTHER 42 1 1
6.3.5 Physical interactions of selected Arabidopsis proteins with TlOsm, OsOlp1_A, and OsOlp1_I confirmed in planta Analyses of proteins interacted with the three osmotins revealed their involvement in intricate biological processes and pathways. However, the evaluation of protein interactions on the chip was an artificial procedure and might not reflect what happens in a living system. Thus, the validation of the protein-protein interaction in planta was necessary before any conclusion was drawn. BiFC is a proven method for visualisation of protein-protein interactions in planta (Hu et al., 2005) (refer to
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Figure 1.3 for the principle of BiFC analysis). The BiFC assays were used for validating the interactions of the three osmotins with selected Arabidopsis proteins.
Among the 7 categories of Arabidopsis proteins interacting with three target osmotins, only three categories were selected for validation in planta due to the interests in the osmotic stress tolerant mechanisms. These categories included those commonly interacted with all three osmotins, those interacted with TlOsm and OsOlp1_A, and those interacted with TlOsm only. In addition, a protein did not interact with all three osmotins on the chip was selected as negative interaction control, the AtPER42. To select the candidates in the three chosen categories, the sub-cellular localisation of the osmotins and their putative interactors were considered. TlOsm was proven to localise to the plasma membrane in both normal and salt stressed conditions (Chapter 3). The localisation of OsOlp1_A and OsOlp1_I were unknown but bioinformatics predictions suggested the apoplast localisation for OsOlp1_I and either ER or chloroplast localisation for OsOlp1_A. Thus, in order for Arabidopsis proteins contact with the three osmotins, the candidate proteins should not localise to the nucleus. Hence, all the nuclear localised proteins were eliminated from the list. Moreover, the proteins had been well characterised and shown to play roles in stress tolerance were selected as priority. Taken all selection criteria together, the AtCPK4, AtCPK5 were selected as representatives of proteins commonly interacted with all three osmotins; the AtMS1 for representing those interacted with TlOsm and OsOlp1_A but not OsOlp1_I; and AtALDH7B4 for representing those interacted with TlOsm only.
The TlOsm, OsOlp1_A, and OsOlp1_I were separately fused with the half N- terminus of EYFP gene in the pE3134 plasmid vector (Figure 6.2 A). The five selected Arabidopsis genes were separately fused with the half C-terminus of EYFP gene in the pE3132 plasmid vector. Co-expression of target osmotin genes and selected Arabidopsis genes together with positive and negative control (Table 6.2) was performed transiently in N. benthamiana by agro-infiltration method. Two days after infiltration, agro-infiltrated leaves from all combinations and controls were harvested and fixed. These samples were subjected to confocal laser scanning microscopic analysis. Representative images captured the fluorescence of experimental leaf samples are presented in the Figure 6.6, 6.7, 6.8, 6.9 and 6.10.
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Figure 6.6 Analysis of in planta interactions between AtCPK4 and TlOsm, OsOlp1_A, or OsOlp1_I. The protein combinations are indicated underneath the images. Images were taken under Fitc light channel (488nm) captured green and EYFP fluorescence and Cy5 light channel (668 nm) captured red fluorescence of chlorophyll. Bar 10 µm.
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Results shown in Figure 6.6 indicated the interactions of AtCPK4 with TlOsm and OsOlp1_A but not with OsOlp1_I. Few green fluorescent spots in Figure 6.6 C reflect the autofluorescence from chlorophyll not from EYFP fluorescence as the results of the two protein interactions, indicating no interaction of OsOlp1_I with AtCPK4 taken place. Hence, only the interactions between AtCPK4 with TlOsm and with OsOlp1_A were demonstrated to happen in planta. AtCPK4 and OsOlp1_I were showed strong interaction on the chip but that interaction did not take play in living N. benthamiana plants.
Figure 6.7 Analysis of in planta interactions between AtCPK5 and TlOsm, OsOlp1_A, or OsOlp1_I. The protein combinations are indicated underneath the images. Light channels for capturing images and corresponding controls refer to Figure 6.8. Bar 10 µm.
Figure 6.7 confirmed the interactions of all TlOsm, OsOlp1_A, and OsOlp1_I with AtCPK5 in planta.
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Figure 6.8 Analysis of in planta interactions between AtMS1 and TlOsm, OsOlp1_A, or OsOlp1_I. The protein combinations are indicated underneath the images. Light channels for capturing images and corresponding controls refer to Figure 6.5. Bar 10 µm.
Fluorescent images in the Figure 6.8 proved the interactions between AtMS1 with TlOsm and with OsOlp1_A, not with OsOlp1_I. The interactions of these protein combinations in living N. benthamiana plants were in agreement with the results generated from screening interactions on the chip.
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Figure 6.9 Analysis of in planta interactions between AtALDH7B4 and TlOsm, OsOlp1_A, or OsOlp1_I. The protein combinations are indicated underneath the images. Light channels for capturing images and corresponding controls refer to Figure 6.6. Bar 10 µm.
Fluorescent images from the Figure 6.9 demonstrated the interactions between AtALDH7B4 only with TlOsm, not with OsOlp1_A and OsOlp1_I. The results of these interactions in planta completely reflected what had been observed on the chip.
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Figure 6.10 Analysis of in planta interactions between AtPER42 and TlOsm, OsOlp1_A, or OsOlp1_I. The protein combinations are indicated underneath the images. Light channels for capturing images refers to Figure 6.6. Bar 10 µm.
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In comparison with the fluorescence signals from the positive and the negative_WT controls, the results shown in Figure 6.10 indicated that no interaction between AtPER42 and TlOsm, OsOlp1_A, or OsOlp1_A takes play in planta. These results affirmed the observations acquired from in vitro hybridisations of the three target osmotins with the protein chips.
BiFC analysis indicated a total of eight interactions between the three target osmotins and the selected Arabidopsis genes as indicated by the fluorescent emission from leaf cells of eight combinations (Figure 6.6-6.9). Among nine combinations showed significant interactions on the chip, one combination (OsOlp1_I and AtCPK4) did not show interaction in planta. Seven combinations not significantly interacting on the chip were confirmed in planta. Fourteen out of 15 combinations of three osmotins with 5 Arabidopsis proteins in planta affirmed the results generated from protein chip hybridisation. These results showed the reliability of the interactions screened from hybridising the three osmotins and Arabidopsis proteins on the chip. The results of BiFC analysis provided a firm evidence for the interactions of the osmotins with plant proteins in living plants. These results also offered the basis for elucidating the functions of TlOsm and OsOlp1_A in plant response to osmotic stresses.
6.4 DISCUSSION
Plant osmotins have been proven as key regulators in both abiotic and biotic stress responses of plants (Liu et al., 2010). However, the mechanisms underlying their functions in plant stress response are not well established due to the lack of information in their interaction partners and pathways. The difficulties in producing recombinant osmotins with functionality and purity have additionally slowed the progress of studying osmotins at protein levels. Intensive studies have been carried on osmotin but to date only few evidences on osmotin binding to other proteins have been demonstrated. In addition, none of the physical interactions between osmotin and plant proteins have been reported in the literature. Interactions of osmotin to the Pir proteins were validated in the Saccharomyces cerevisiae strain resistant to osmotin (Yun et al., 1997). Similarly, binding of osmotin to phosphomannans on the cell-wall was proven in S. cerevisiae strain sensitive to osmotin (Ibeas et al., 2000). The binding of osmotin to PHO36 leading to the suppression of fungal apoptosis signalling pathway was also evidenced in S. cerevisiae (Narasimhan et al., 2001; Narasimhan et al., 2005).
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Evidence of osmotin functions as agonist of adiponectin for binding to adiponectin receptor was demonstrated in mammalian C2C12 cell line (Narasimhan et al., 2005). Nevertheless, the validation of these few interactions has contributed to the dissection of osmotin functions and mechanisms of its in vitro toxicity to fungi and its adiponectin-mimic functions. In the previous chapter, the roles in enhancing plant tolerance to cold, drought and salinity stresses of TlOsm, OsOlp1_A, and OsOlp1_I were compared in transgenic rice. The results demonstrated the capacity in enhancing cold, drought, and salinity stress tolerance in transgenic rice of TlOsm and OsOlp1_A, with the superior tolerant levels to cold and drought stresses of TlOsm expressing plants. In this study, to understand the functions and stress-responsive pathways by which these osmotins mediate plant response to stresses, the potential interactive protein partners of each TlOsm, OsOlp1_A, and OsOlp1_I were assessed by the Arabidopsis protein microarray. Recombinant osmotin proteins were obtained with purity and identity needed for probing with the proteins on the microarray. Arabidopsis proteins interacting with each osmotin on the chip were identified. More proteins on the chip interacted with TlOsm than with rice osmotins. In comparison within rice osmotins, the OsOlp1_A from drought tolerant cultivar interacted with two more proteins than OsOlp1_I from drought sensitive cultivar; they have 225 common interactors, 14 interactors specific to OsOlp1_A and 12 interactors specific to OsOlp1_I. The interactors of osmotins were found to participate in a diverse biological process. Interestingly, all proteins only interacting with TlOsm were found involved in plant responses to stress and stimuli. Pathway analysis of osmotins interactors revealed the conserved pathways among three osmotins and specific pathways for osmotins conferred tolerance to abiotic stress and nine unique pathways for osmotin from T. loliiformis. Putative interactors of osmotins were selected for validating the interactions in planta upon their well-characterised functions in plant stress response. CPK4 and CPK5 belong to calcium-dependent protein kinase family that play the crucial regulatory roles in plant signalling to diverse stress conditions including both abiotic and biotic stresses (Mohanta and Sinha, 2016; Steinhorst and Kudla, 2013). Both CPK4 and CPK5 were found to directly regulate ROS signalling through modulation of RBOH by NADPH oxidases. Kobayashi et al. (2007) demonstrated in potato (Solanum tuberosum) that StCPK4 and StCPK5 phosphorylated NADPH oxidase
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and regulated the production of ROS. Arabidopsis CPK4 together with CPK1/CPK2/CPK11 was shown to phosphorylate NADPH oxidases in vitro and was considered as important components for the production of ROS during immune signalling (Gao et al., 2013). Similarly, AtCPK5 was proposed to be a key component of self-propagating activation circuit regulating cell-to-cell communication. AtCPK5-dependent phosphorylation activated RBOHD that generated an apoplastic ROS wave that further enabled signal propagation upon pathogen-associated molecular pattern stimulation to distal parts of the plants. Thus, AtCPK5 represents a positive regulator of the NADPH oxidising RBOHD during pathogen immune defense in Arabidopsis (Dubiella et al., 2013). Moreover, AtCPK4 was proven to regulate ABA signal transduction in Arabidopsis (Zhu et al., 2007). Accordingly, AtCPK4 was evidenced to be induced by ABA stimulus and to regulate ABA signal transduction pleiotropically in seed germination, seedling growth, stomatal movement, and in plant response to salt stress. Another stress-responsive gene, the AtMS1, was demonstrated to interact with TlOsm and OsOlp1_A but not with OsOlp1_I on the chip. AtMS1 is involved in various biological processes including methionine biosynthesis, methylation, and homocysteine metabolic process and in response to salt stress, to zinc ion, and to cadmium ion. In the significant pathways of osmotin interactors described in Table 6.4, AtMS1 is within the super pathway of lysine, threonine, and methionine biosynthesis. Among the four proteins selected for elucidating interactions with osmotins in N. benthamiana plants, AtMS1 has the most complex protein interaction network (Figure 6.11 C). This protein is involved in biosynthesis of compounds beneficial for plant adaptation. Abiotic stresses generate ROS that consequently cause excessive accumulation of aldehydes in plant cells. Aldehyde dehydrogenases (ALDHs) work as aldehyde scavengers to eliminate aldehyde toxicity caused by oxidative stress (Hou and Bartels, 2014). As a member of the ALDH family, AtALDH7B4 was demonstrated to enhanced A. thaliana plants tolerant to abiotic stress by protecting plants against lipid peroxidation and oxidative stress (Kotchoni et al., 2006). According to the authors, plants overexpressing AtALDH7B4 showed higher level of AtALDH7B4 protein accumulation and conferred tolerance to osmotic and oxidative stresses. The stress tolerance of
AtALDH7B4-overexpresing plants was accompanied by a decreasing level of H2O2 and MDA generated from cellular lipid peroxidation. The AtALDH7B4-knockout mutant plants exhibited higher sensitivity to drought and salinity stresses than WT plants. The
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currently available protein-protein interaction networks of the selected Arabidopsis stress-responsive proteins are presented in Figure 6.11.
Figure 6.11 Protein interaction networks of Arabidopsis genes selected for BiFC analysis. AtCPK4 (A); AtCPK5 (B); AtMS1 (C); AtALDH7B4 (D). Images were retrieved from String server.
Validation of the protein-protein interactions in planta showed very high correlation with results obtained from the chip. The differential interactors of these osmotins provide the key mechanisms underlying the functions of osmotins in plant stress response. In addition, the study provides the evidence, for the first time, on the physical interactions between target osmotins and other plant stress-responsive proteins in planta.
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6.4.1 Production of pure and functional recombinant osmotins Critical criteria for recombinant proteins used to hybridise with the protein chip require purity, functional activity, and appropriate tags for detection of interactions. Therefore, the gene manipulation and expression system for recombinant target osmotin production needed to consider all the elements necessary for enhancing protein production, facilitating proper protein folding, supporting purification process, remaining protein activity after purification, and promoting detection of interactions. The hydrophobicity, anti-microbial property and the presence of 8 disulfide bonds in the structure of osmotins have made it difficult for expressing in microbial system with proper folding of resulted proteins. Due to its toxicity to expressing microbes, osmotin was targeted to inclusion bodies that resulted in water insoluble and aggregated form and with misfolded proteins (Campos et al., 2008; Viktorova et al., 2012). Two current existing protocols for recombinant osmotins in E. coli by Compos et al. (2008) and Tzou et al. (2011) did not suit our purposes. The protocol by Compos et al. (2008) requires targeting osmotin in the inclusion bodies, denaturing osmotin during protein extraction and refolding the protein. However, with 8 disulfide bonds in the structure, refolding osmotin is a difficult step accompanied with limited protein yield upon water-insoluble of hydrophobic protein. The protocol by Tzou et al. (2011) developed for C-terminus truncated tobacco osmotin that resulted in extra cellular secretion of recombinant osmotin with reasonable yield and antifungal activities of recombinant osmotin remained. However, TlOsm is a plasma membrane protein with a membrane binding domain at its C-terminus. Truncated TlOsm at its C-terminus might affect its native activities. Hence, another strategy was needed for gene manipulation and expression of the three target osmotins.
Popescu et al. (2007b) compared two eukaryotic systems for protein expression, S. cerevisiae and N. benthamiana, in order to identify the biological system that allowed native protein folding and post-translational modification to occurs, providing necessary cofactors for protein activity to be used on the protein chips. Their results indicated that even though the proteins expressed at comparable levels in the two systems, proteins produced by plants retained their enzymatic functions after purification better than the yeast expression system. Therefore, expression of osmotins in plant system would produce protein with more proper folding and functionally active on the chip similarly to their cellular counterparts. However, TlOsm was
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validated to be a plasma membrane protein. If protein localises naturally, the extraction of recombinant TlOsm must require the disruption of the plasma membrane to release the protein. The chemicals used to disrupt cell membrane could cause protein denatured, change protein conformation that may further effect protein activity. Numerous studies have proven that addition of a KDEL sequence to the C-terminus of a protein allowed it retained in the ER (discussed in Section 1.6.2). Incorporation of the KDEL sequence in cytoplasmic, transmembrane, and other secreted proteins has been proven to result in ER retention, higher level of expression, stabilisation, and accumulation of recombinant proteins as compared to their native derivatives (Jackson et al., 1990; Wandelt et al., 1992; Schouten et al., 1996). Thus, a KDEL sequence were attached to the C-terminus of the target recombinant osmotins for their ER retention and improvement in protein expression, stabilisation, and accumulation. Moreover, progresses in cloning studies have identified number of elements necessary for stabilising and maintaining native protein activities. Thus, various gene constructs have been developed for enhancing protein production in transient expression systems and for facilitating protein purification. The CPMV-HT sequence and P19 suppressor of gene silencing in the gene expression cassette have been found to be advantages of pEAQ vector for enhancing recombinant protein expression and for maximizing expression efficiency in a transient expression system (Preyret and Lomonossoff, 2013). The Tandem affinity purification (TAP) tagged to the C-terminus of a protein was found to be an efficient approach for isolation of recombinant protein in a plant protein complex (Rubio et al., 2005). Taking all the considerations required for recombinant osmotins and the advances of gene cloning into gene manipulation strategy, we generated the plasmid constructs for expressing target osmotins with the schematic T-DNA shown in Figure 6.1. In these gene expression cassettes, the CPMV- HT sequence and P19 gene silencing suppressor were incorporated; and the recombinant osmotins included either TlOsm, OsOlp1_A, or OsOlp1_I downstreamed by 9xMyc epitope, His-6, a rhinovirus 3C protease cleavage site, the 2xIgG binding domain of protein A, and the KDEL sequence. These gene constructs were used for transient expression in N. benthamiana by agro-infiltration method.
The recombinant osmotin proteins were purified through three-step purification protocol. The osmotin proteins were obtained with purity and identity as evidenced by the Coomassie staining of SDS-PAGE and western blot analysis (Figure 6.3).
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Functional activities of recombinant target osmotins were further demonstrated by higher levels of interaction signals detected from some spots on the chip, as compared to positive control spots (Figure 6.4). Thus, the protocols for cloning, transient expression in plant system, and protein purification used in this study provide an alternative method for producing pure and functional recombinant osmotin.
6.4.2 Analysing potential protein interactors of TlOsm, OsOlp1_A and OsOlp1_I affirms their multiple functions Protein-protein interaction is one of the fundamental networks reflecting the complex biological processes in living organisms. Identification of protein interactors for a protein under study is a crucial desire to unravel the mechanisms underlying the protein functions. Revealing and cataloguing these protein interactors would provide a comprehensive understanding of cellular functions and regulatory network of the under-studied gene in living organism (Popescu et al., 2007a). Numerous studies on osmotin by various methods have identified only few proteins interacting with osmotin. These proteins include Pir proteins (Yun et al., 1997), phosphomanno proteins (Ibeas et al., 2000), the PHO36 regulating the Ras/cAMP pathway in yeast (Narasimhan et al., 2001), and a mammalian adiponectin receptor (Narasimhan et al., 2005). Using the Arabidopsis protein microarrays containing 5000 proteins for separately hybridising with TlOsm, OsOlp1_A, and OsOlp1_I, total of 271 interactive protein partners were identified. Further analysis of the osmotin interactors revealed their involvement in diverse protein families, biological processes and pathways. The results demonstrated the effectiveness of using protein microarray to identify osmotin interactive protein partners that further facilitates the progress for functional characterisation of these osmotins. The results also confirm the assumption that TlOsm has more functional sites would interact with more proteins than the rice osmotins, OsOlp1_A and OsOlp1_I.
Analysis of significant pathways involving three osmotin interactors indicated the three most dominant pathways to be fructose and mannose metabolism, glycolysis and pentose phosphate pathways (Table 6.4), with corrected P-value < 0.05. In plants, soluble sugars not only serve as cell metabolic resources and structural constituents but also signalling regulators in various processes of plant growth, development, and response to stress stimuli. Members of the soluble sugar metabolism have been evidenced to play important roles in plant signalling and adaptive response to abiotic
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stress (Rosa et al., 2009). Glycolysis is a central metabolic pathway present in all organisms. Different to non-plant systems, plant glycolysis occurs both in the cytosol and the plastid. The cytosolic glycolysis has been known to provide essential components for promoting plant development and adaptation to environmental stress (Plaxton, 1996). Parallel to glycolysis, the pentose phosphate pathway is a metabolic pathway generating NADPH and pentoses including ribose-5-phosphate that is fundamental for the synthesis of nucleotides and for building other molecules. In plants, the pentose phosphate pathway has been shown to be linked with other pathways including proline biosynthesis, antioxidant response pathway, and phenolic biosynthesis (Shetty, 2004; Kishor et al., 2005). In the study by Shetty (2004), the author argued that products of all these pathways are beneficial for plant and also animal response to stresses. Thus, they suggested the key components that link the pentose phosphate pathway to these three pathways to be exploited for producing functional food for use in manage human diseases such as diabetes, cardiovascular, inflammatory, and cognition diseases, and cancer; and for enhancing plant environmental stress tolerance. Beside these three dominant pathways, less significant numbers of osmotin interactors are involved in other 7 pathways (Table 6.4; corrected P-value < 0.1) that somewhat relate to plant response to environmental and pathogenic stress factors (Dong and Beer, 2000; Ferreyra et al., 2012; Kishor et al., 2005; Gerdes et al., 2012). The involvement of osmotin interactors in numbers of fundamental pathways in plant development and stress response demonstrated the functional roles of osmotins in above-discussed pathways.
Screening Arabidopsis proteins interacting with TlOsm, OsOlp1_A, and OsOlp1_I using protein microarray identified a large group of proteins with recognised roles in biological processes associated with plants response to abiotic and biotic stresses and development. The involvements of the osmotin interactors in multiple biological processes and pathways demonstrate the multiple functions of the osmotins in plant development and adaptation. However, the interactions of these osmotins with the proteins on the chips were generally artificial environment, where the sub-cellular localisation of interactive protein partners were not considered. Therefore, the actual interactors of these osmotins in plants can only be drawn by the validation of interactions in an appropriate living system.
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6.4.3 Common and specific potential interactors of TlOsm, OsOlp1_A, and OsOlp1_I provide testable target proteins for unravelling osmotin functions Osmotin has been demonstrated to be a multi-functional protein and a key modulator in plant defense against pathogens and environmental stresses (Husaini & Rafiqui, 2012; Viktorova et al., 2012; Kumar et al., 2015). As discussed in Section 1.3, its roles in both abiotic and biotic stress response of plants have been proven by analysing gene expression upon stress stimuli, promoters, and various transgenic plants expressing osmotins from different species. In addition, osmotins have shown antifungal activities in vitro against a broad range of fungi. Although the mechanisms underlying osmotin functions in plant defense have not been elucidated, some mechanisms of osmotin antifungal properties in vitro have been determined via proteins it interacted with. For examples, mechanisms underlying osmotin functions that cause fungal cell permeability and susceptible to osmotin were discovered by its interaction with cell wall phosphomanno proteins (Ibeas et al., 2000). Similarly, resistance to osmotin toxicity of some S. cerevisiae strains was determined by the interaction of osmotin with the Pir proteins, the cell-wall-localised stress proteins (Yun et al., 1997). The mechanism of osmotin causing apoptosis in yeast was found by its interaction with PHO36, which regulates lipid and phosphate metabolism. In interacting with PHO36, osmotin suppresses the downstream RAS2/cAMP cell death signalling pathway and causes apoptosis to yeast cells. The function of tobacco osmotin as an agonist of mammalian adiponectin was demonstrated based on its interaction with adiponectin receptors, which resulted in activation of AMP kinase signalling in C2C12 myocyte cells (Narasimhan et al., 2005). Therefore, the list of 11 interactors of both TlOsm and OsOlp1_A and 21 interactors of TlOsm only (highlighted in Table 6.3) holds a great target for understand the mechanisms by which TlOsm and OsOlp1_A regulate plants response to cold, drought, and salinity stresses. The comparision among TlOsm, OsOlp1_A and OsOlp1_I in transgenic rice only focussed on plant response to abiotic stresses, particularly to cold, drought and salinity. TlOsm and OsOlp1_A conferred tolerance to cold, drought, and salinity in transgenic rice with a higher tolerant levels to cold and drought of TlOsm. Thus, the mechanisms that TlOsm and OsOlp1_A use to regulate cold, drought, and salinity stress response could be related to 11 proteins involved in various biological processes (Table 6.3 and Figure 6.5). The physiological changes in transgenic rice associated with additional effects of TlOsm over OsOlp1_A were higher osmotic
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adjustment, better membrane protection, and better regulation of stomatal closure. The 21 proteins, which interacted with only TlOsm and are involved in biological process of plant response to stress, to toxic chemical, and to endogenous stimuli, would be the ideal target for determination the mechanism of TlOsm leading to such physiological changes.
Osmotin has been suggested to function in pathogen defence pathway and a number of signalling pathways. Pathway analysis of osmotin interactors indicated the involvements of various interactors in plant-pathogen interaction pathway and numerous stress-signalling pathway such as cadherin signalling, plant hormone signal transduction, apoptosis signalling pathways (Table 6.6). Interestingly, tobacco osmotin has shown to share structural and functional similarities with adiponectin, an insulin sensitising hormone in mammals (Miele et al., 2011), to mimic adiponectin in activating AMP kinase phosphorylation in mammalian cells (Narasimhan et al., 2005), and to function as human adiponectin in type II diabetes and obesity (Trivedi et al., 2012). Since adiponectin has anti-diabetic, anti-atherogenic, and anti-inflammatory activities, osmotin has been suggested to be used as a therapeutic compound in replacement of adiponectin for treatment of human diseases related to insulin resistance (refer to Section 1.3.5). Few proteins interacted with three osmotins on the chip are also involved in insulin resistant pathway and inflammation mediated by chemokine and cytokine signalling pathway. Likewise, in mammalian model systems, osmotin has been demonstrated to function in preventing neurodegeneration and been suggested to be used as a neuroprotective agent (Shah et al., 2014; Naseer et al., 2014). Several proteins either commonly or specifically interacted with the three osmotins on the chip were found to function in the Huntington’s disease and Parkinson disease, the two neurodegenerative diseases in Human (Table 6.6). These demonstrate the relations of the results generated from screening protein-protein interactions on the chip to the previously reported roles of osmotin. Therefore, the osmotin interactors identified from this study offer a direct targets for testing hypothesis on the mechanisms underlying these osmotin functions.
Similar to other osmotins, all TlOsm, OsOlp1_A and OsOlp1_I potentially play roles in defense response to pathogens. Many proteins in the group of common interactors of the three osmotins are involved in recognised biological processes for plant disease resistance and innate immunisation response. Hence, this group of
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proteins can serve as testable targets for further studies on mechanism of osmotins in plant response to biotic stress. Thus, the resulted protein interactors of the three osmotin provide an informative information for testing binding targets of the osmotins for elucidation of mechanisms underlying osmotin functions in regulating plant responses to abiotic and biotic stresses and for exploiting the use of the osmotins as therapeutic reagents.
6.4.4 Possible mechanisms underlying TlOsm, OsOlp1_A, and OsOlp1_I functions The functions and mechanisms by which osmotin regulates plant stress response have not been well-elucidated partially due to the lack of information in interaction of osmotin with plant protein. Interactions of the three osmotins with the Arabidopsis proteins by BiFC analysis reported here present, for the first time, the physical interactions of the osmotins with plant proteins in plants. Arabidopsis proteins selected for validating in planta interaction with TlOsm, OsOlp1_A, and OsOlp1_I were on the basis of their well-characterised roles in plant stress adaptation and within different stress-responsive pathways (Figure 6.11). The validated interactions in planta between TlOsm, OsOlp1_A, and OsOlp1_I with Arabidopsis stress-responsive genes serve as firm evidence for elucidating the mechanisms by which TlOsm and OsOlp_A regulate plant tolerance to cold, drought and salinity stresses.
In this study, TlOsm and OsOlp1_A were evidenced to interact with AtCPK4 and AtCPK5 both on the chip and in planta, while OsOlp1_I significantly interact with AtCPK4 and AtCPK5 on the chip but only interacted with AtCPK5 in plants (Figure 6.8 & 6.9). The interactions of TlOsm with AtCPK4 and AtCPK5, which have been known for functions in plant stress signalling pathway, demonstrate the functions of target osmotins in stress signalling pathways. In addition, TlOsm and OsOlp1_A both conferred tolerance to cold, drought, and salinity stresses in transgenic rice and interacted with AtCPK4 in living plants. AtCPK4 was demonstrated to regulate ABA signal transduction in plant response to drought and salinity stresses (Zhu et al., 2007). This suggests that interacting with AtCPK4 is essential to transmit abiotic stress signals to acquire sufficient stress adaptation. AtCPK5 has been demonstrated a positive regulator of plant signal transduction upon pathogenic infection (Dubiella et al., 2013). All TlOsm, OsOlp1_A, OsOlp1_I interacted with AtCPK5 in planta, suggesting their involvement in plant signalling
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defense to pathogens. Lack of interaction with AtCPK4 of OsOlp1_I probably results in the failure to transduce abiotic stress signals that further leads to its insufficient regulation of plant stress response, as compare to its allele OsOlp1_A. Similarly, AtMS1 is involved in biosynthesis of compounds beneficial for plant adaptation (its protein interaction network in Figure 6.11 C). Interactions of TlOsm and OsOlp1_A with AtMS1 would contribute additional effects on their ability to facilitate plant tolerance to abiotic stress. Hence, without interacting with AtMS1 of OsOlp1_I would further limit OsOlp1_I functions in enhancing plant tolerance to cold, drought, and salinity stresses. Moreover, in agreement with the results derived from interaction of osmotins and Arabidopsis proteins on the chip, in N. benthamiana plants, only TlOsm was found to interact with AtALDH7B4 (Figure 6.9). TlOsm but not OsOlp1_A interacting with ALDH7B4 at least partially demonstrating to the higher level of enhanced tolerance to drought and cold stress as demonstrated in TlOsm rice plants over the OsOlp1_A plants. Failure to interact with key proteins in stress responsive pathways explains for the failure to promote transgenic rice tolerance to cold, drought and salinity stresses of OsOlp1_I.
Patade et al. (2013) showed that some stress-responsive genes including CBF1 (transcription factor), P5CS (osmotic adjustment), APX (antioxidant defense) were activated in cold tolerant tomato expressing tobacco osmotin. This indicated that osmotin should be an upstream modulator of transcription factor in the stress signal transduction process. Choi et al. (2013) demonstrated that pepper osmotin (CaOSM1) regulated hypersensitive cell death response and oxidative burst signalling during infection of Xanthomonas campestris. Both CPK4 and CPK5 were proven to regulate ROS signalling but CPK5 was likely specific for response to pathogen stimuli (Gao et al., 2013; Dubiella et al., 2013). Interactions of TlOsm and OsOlp1_A with both AtCPK4 and AtCPK5 suggested that these two osmotins function in ROS signalling. OsOlp1_I interacted with AtCPK5 but not AtCPK4 suggested its function in signalling upon pathogenic stimuli. Zhu et al. (2007) demonstrated that AtCPK4 regulated drought and salinity stress response through ABA signal transduction and worked upstream of several ABA transcription factors. The gene showed functions in regulating stomatal movement, osmotic adjustment and lipid peroxidation inhibition that further lead to enhanced Arabidopsis plant tolerance to drought and salt stresses. Considering the physiological changes in rice plants
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expressing TlOsm and OsOlp1_A, functions for TlOsm and OsOlp1_A were also associated with stomatal closure, osmotic adjustment and lipid peroxidation inhibition. Besides, TlOsm and OsOlp1_A showed interacting with AtMS1, which is involved in plant response to chemical and within a biosynthesis pathways. Only TlOsm (not OsOlp1_A) interacted with AtALDH7B4, a protein functions in detoxification of aldehydes generated upon plant stress, which protects plants against lipid peroxidation and oxidative stress (Kotchoni et al., 2006). Regarding localisation of the proteins, TlOsm localises to the plasma membrane while AtCPK4 and AtALDH7B4 are cytoplasmic proteins (Kotchoni et al., 2006; Zhu et al., 2007), and AtMS1 is annotated as cytoplasmic or chloroplast protein. Thus, TlOsm is likely an upstream regulator of these three proteins. Regarding the physiological differences of rice plants expressing TlOsm or OsOlp1_A in comparison with OsOlp1_I, WT or NT, and VC (Chapter 5), the mechanisms underlying TlOsm and OsOlp1_A functions cold, drought, and salinity stress responses could be suggested. TlOsm would transmit the stress signal by interacting with CPK4 homolog that further activates ABA signal transduction leading to downstream adaptive response such as stomatal closure, osmotic adjustment, and antioxidative defense response. Besides, it would interact with rice MS1 homolog to regulate biosynthesis of compounds beneficial for protecting rice plants from chemical toxicity. On the other hand, it would interact with ALDH7B4 homolog that further mediates detoxification of aldehydes generated by osmotic stress to prevent oxidation and lipid peroxidation. OsOlp1_A would function in a similar way when interacting with CPK4 and MS1 homologs. However, lack of interaction with ALDH7B4 homolog would be the reasons for less efficiency in protect membrane damage leading to higher electrolyte leakage in OsOlp1_A plant as compared to TlOsm plants (Figure 5.4). Without interactions with CPK4, MS1, and ALDH7B4 homologs of OsOlp1_I would lead to failure to transmit the stress signals and regulate other detoxification processes that result in failure in improving rice plants to cold, drought, and salinity stress of OsOlp1_I.
In conclusion, research in this chapter has indicated that osmotin from T. loliiformis, TlOsm, has more potential binding partners than osmotins from O. sativa. In addition, OsOlp1_A from drought tolerant cultivar has two more binding partners than OsOlp1_I from drought sensitive cultivar. The results are in agreement with the hypothesis that protein with more functional binding sites interact with more proteins.
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The Arabidopsis protein interactors of TlOsm, OsOlp1_A and OsOlp1_I are involved in the diverse biological processes and pathways of development and adaptation. These interactors and pathways provide the testable targets for further studies in exploiting osmotins for biotechnological applications in GMO crops, the food industry and pharmaceuticals. The in planta experiments validated interactions between the three osmotins and stress-responsive Arabidopsis proteins demonstrated the functions of TlOsm and OsOlp1_A in stress signal transduction, adaptation, and additional oxidative-stress detoxification for TlOsm. Shortage of in planta interaction with the key stress-responsive components of OsOlp1_I provides evidence for its limited functions in abiotic stress response, as compared with its allele, the OsOlp1_A. These results provide evidence on the physical interactions of osmotins with numbers of stress-responsive proteins in plants and contribute to present knowledge and understanding insights into mechanisms of osmotin in regulation of plant stress response. Moreover, the gene manipulation method and the N. benthamiana transient expression system used in this study can be applied as an alternative method for recombinant osmotin production.
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Chapter 7: General Discussion
Abiotic stresses such as drought, salinity, and extreme temperature are massive challenges hindering the capacity of agriculture to meet the food demands of an increasing global population. To feed the growing population we will need to produce approximately 60% more food to meet the demands in 2050; this is the equivalent to a 2.4% yield growth rate per annum for all crops. Currently, crop yield has an estimated growth rate of 1.6%, 1.0%, 0.9%, and 1.3% for maize, rice, wheat, and soybean, respectively (Ray et al., 2013). By looking at what causes the great levels of crop loss we may be able to increase production. Approximately 50% yield loss of major food crops are caused by abiotic stresses (Huang et al., 2012). Hence, besides high yielding, future crops must be equipped with stress-adaptive traits to cope with adverse conditions. To ensure global food security, the development of stress-adaptive crops represents a key goal in constant supplying improved crop cultivars for commercial cultivation. Genetic engineering high yielding crop cultivars with stress-adaptive traits is considered a promising approach for developing such crops (Cominelli et al., 2013; Oliver, 2014). Thus, characterisation of the key components controlling stress- adaptive traits to be used in genetic engineering is in crucial need for the development of resilient crops. Moreover, seeking genes from stress-tolerant species for engineering into crops displays great promise as an effective strategy for introducing new stress- adaptive traits into yield-improved crop cultivars (Mittler and Blumwald, 2010).
In this project, an osmotin gene from resurrection plant T. loliiformis (TlOsm) was characterised and functionally analysed for abiotic stress response in various systems, in comparison with two osmotin genes (OsOlp1_A and OsOlp1_I) identified from drought-tolerant and –sensitive cultivars of stress-sensitive species O. sativa. The common and specific characteristics of TlOsm were identified. Its involvement in plant abiotic stress responses was analysed in T. loliiformis as well as in transgenic N. tabacum and O. sativa. Its roles in enhancing plant tolerance to stress were validated by comparative assessment transgenic rice expressing TlOsm, OsOlp1_A, OsOlp1_I, and corresponding controls under cold, drought, and salinity stresses. The interactive protein partners of the three osmotins were identified and pathways involving osmotin interactors were also determined. Interactions between TlOsm, OsOlp1_A, or
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OsOlp1_I, with some stress-responsive proteins were validated in living N. benthamiana plants. The study indicates the role of TlOsm in plant response to multiple abiotic stresses and its additional effects over osmotins from sensitive species, O. sativa. The study highlights potential applications of TlOsm for engineering crops with improved tolerance to multiple stresses such as cold, drought, and salinity. The study also deepens our understanding the functions and molecular mechanisms of osmotins in regulating plant stress response and provides evidence, for the first time, the physical interactions of osmotins with plant proteins in planta.
7.1 TlOsm has more functional efficacy in regulation of plant stress response than rice osmotins
Resurrection plants have evolved unique stress-tolerant mechanisms that enable them rapidly respond to stress, effectively protecting cellular components during stress, whilst allowing rapid recovery to full metabolic functions within 48 – 72 h of watering (Peters et al., 2007). Proteomic analyses on these plants during dehydration have shown the increased abundance of many proteins functioning in antioxidance, energy metabolism, and macromolecule protection (Dinakar and Bartels, 2013; Ingle et al., 2007; Jiang et al., 2007). In addition, enzymatic activities of many proteins related to antioxidant synthesis, sugar metabolism, and chaperones were found increased during dehydration in various resurrection plants (Petersen et al., 2012; Rohrig et al., 2006; Whithaker et al., 2001). In these studies, the increased abundance and enzymatic activities and maintained phosphorylation activities of stress- responsive proteins positively correlated with the accumulation of sugar metabolites, antioxidants and other cellular protective compounds. Perhaps, proteins of resurrection plants have evolved additional functions that enable them to more effectively mitigate stress. Similar molecular, biochemical, physiological, and structural changes for early response to water deficit, for promoting survival mechanisms during desiccation, and for rapid recovering upon rehydration with minimal damage have been reported in T. loliiformis (Karbaschi et al., 2016; Williams et al., 2015). Thus, we hypothesised that stress-responsive proteins from T. loliiformis evolve additional functions than their respective counterparts of sensitive species.
Comparative bioinformatics analysis of functional binding residues of TlOsm and rice osmotins from drought-tolerant vs. -sensitive cultivars (OsOlp1_A vs. OsOlp1_I) indicated that TlOsm contains additional glucan-binding and
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phosphorylation sites as well as unique sites with enzymatic functions in sugar metabolism. The tolerant cultivar OsOlp1_A contains three more glucan-binding sites than its sensitive counterpart OsOlp1_I. Binding and hydrolysing glucan molecules are essential for the antifungal activities of an osmotin (Liu et al., 2010; Mani et al., 2012). The glucan-hydrolytic functions of osmotin in plant abiotic stress response are not clear though glucan-hydrolytic products have been suggested to be used for development of organelle and cell membrane and for osmotic adjustment (Dway and Smille, 1971; Satoh et al., 1976). Eight, five, and two glucan-binding residues were predicted for TlOsm, OsOlp1_A, and OlOlp1_I, respectively (Table 3.2). Moreover, osmotin has been proven to activate MAP kinase signalling pathway (Narasimhan et al., 2005; Narasimhan et al., 2001). In plants, phosphorylation reactions play the central signalling role that translates environmental stimuli into cellular response. These reactions are common in stress signal transducers such as the MAP kinases and calcium-dependent protein kinases and are performed by phosphorylation sites (Mohanta and Sinha, 2016; Sinha et al., 2011; Wurzinger et al., 2011). Phosphorylation reactions are maintained in resurrection plants during dehydration and are believed to be essential for protecting their cells from damaged by stress (Dinakar and Bartels, 2013; Rohrig et al., 2006). TlOsm, OsOlp1_A, and OlOlp1_I all contain the potential phosphorylation residues but the number of residues is higher in TlOsm (64 residues) than in either rice osmotin (15 residues for both). In addition to these sites, TlOsm possesses 4 functional sites for sugar metabolism, neither rice osmotin contains a similar site. Soluble sugar metabolism is a key pathway in plant sensing and response to abiotic stress (Rosa et al. 2009). The accumulation of remarkably high soluble sugars during desiccation is a unique feature of desiccation tolerant plants (Dinakar and Bartels, 2013; Gaff and Oliver, 2013). Therefore, we speculated that TlOsm is more effective in regulating plant response to stresses. This assumption was validated in rice plants expressing these osmotins.
Investigating the response of transgenic rice expressing TlOsm, OsOlp1_A, or OsOlp1_I upon exposure to cold, drought, and salinity stresses proved that levels of rice stress tolerance positively correlate with the number of functional sites of the osmotin that plants expressing. The highest levels of enhanced stress tolerance were found in TlOsm plants, following by OsOlp1_A plants and lowest in OsOlp1_I plants. Since OsOlp1_I did not confer stress tolerance in transgenic rice (Chapter 5), here the
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higher functional efficacy in regulating plant response to stresses of the osmotins from tolerant and sensitive species is compared between TlOsm and OsOlp1_A.
OsOlp1_A was isolated from a drought tolerant rice cultivar. Similar to TlOsm, OsOlp1_A was induced by drought (personal communication with Raveendran, TNAU). When exposure to cold and drought stresses, transgenic OsOlp1_A plants showed lower levels of tolerance than TlOsm plants in both physiological and agronomic traits. The lower tolerance levels of OsOlp1_A plant were demonstrated by lower growth rate, tillering capacity, dry biomass, survival rate, and grain yield; which were associated with less ability to retain water, maintain membrane integrity and photosynthesis efficiency. When exposure to salinity stress, TlOsm plants displayed better water retention than OsOlp1_A plants (Figure 5.3). Thus, there might be common functional features between TlOsm and OsOlp1_A that made both TlOsm and OsOlp1_A conferred tolerance to these stresses. There might be unique features for TlOsm that made TlOsm plants performed better than OsOlp1_A plants under cold, drought, and salinity stresses.
Protein interactions regulate various cellular functions and provide basis for understanding molecular mechanisms of protein functions (Hu et al. 2005). Several interactions of tobacco osmotin with fungal and mammalian proteins have been demonstrated (Ibeas et al. 2000; Narasimhan et al. 2005; Narasimhan et al. 2001; Yun et al. 1997). These interactions have provided useful information for elucidation of mechanisms underlying osmotin toxicity to fungi and its function in activating AMP cascade in mammalian cells. To date, information on plant proteins interacting with osmotins and evidence of osmotin interacting with other proteins in living plant cells is still missing in the literature. For understanding insights into osmotin functions in regulating plant response to stress, plant proteins interacting with TlOsm, OsOlp1_A, and OlOlp1_I were identified and some interacting complexes in living plants were also determined. To understand the functions underlying the enhanced effects of TlOsm to improve rice stress tolerance, the potential interactive protein partners of TlOsm and OsOlp1_A were compared. TlOsm had 28 more interactive protein partners than OsOlp1_A (267 vs. 239) and the two osmotins share 236 common interactors. Thus, understanding the different interactors of the two osmotins would provide the key insight into functional efficacy of TlOsm over OsOlp1_A. Among the different interactors, 21 proteins were found unique
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interactors of TlOsm, not interacted with either of rice osmotins. All the 21 proteins were found involved in three biological processes of plant response to abiotic stresses, to chemicals, and to endogenous stimuli (Figure 6.5). This suggests that TlOsm potentially interact with more stress-responsive proteins than OsOlp1_A. Among these 21 TlOsm interactors, AtALDH7B4 had been demonstrated to enhanced Arabidopsis plants tolerant to drought and salinity by protecting plants from damages of lipid peroxidation and oxidation and effective aldehyde detoxification (Kotchoni et al. 2006). AtALDH7B4 interacted with only TlOsm in living N. benthamiana, not with OsOlp1_A. Thus, TlOsm interacting with AtALDH7B4 homologs probably activates the system that mitigates damages caused by lipid peroxidation and oxidation. This interaction ultimately contributes to its additional effects on enhanced plants tolerant to cold, drought and salinity stresses.
It is possible that osmotin protein from tolerant species T. loliiformis has evolved with more functional binding sites than osmotin proteins from sensitive species O. sativa. These extra functional binding sites, including the extra number of glucan- binding and phosphorylation residues and unique enzymatic residues functioning in sugar metabolism, would enable TlOsm interact with more stress-responsive proteins when plants exposed to stresses. As consequence of the interactions, more stress- responsive processes and pathways would be activated. These activations would result in more effective mitigation of cellular damages and enhanced physiological and morphological responses for adaptation. Thus, proteomic evolution of TlOsm would provide it additional functions that enhance TlOsm efficacy of regulating plant response to stresses.
7.2 TlOsm is a multi-functional protein playing a role in plant response to stresses
Previous studies on osmotins have indicated their multi-functional roles in plant response to both abiotic and biotic stresses (Husani and Rafiqi 2012; Kumar et al. 2015; Viktorova et al. 2012). Analyses of transgenic plants expressing various osmotin genes from diverse plant species (Table 1.1) have emphasised their potential for use in genetic engineering of crops with enhanced tolerance to multiple stress factors. This is the first time an osmotin from a resurrection plant has been characterised. In agreement with the functional roles of other osmotins from previous studies, results in this study
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demonstrated that TlOsm play multi-functional role in plants response to stresses. In addition, novel characteristics of TlOsm was identified. TlOsm was previously isolated from T. loliiformis drought-induced cDNA library, suggesting its involvement in plant response to drought. Sequence analysis of TlOsm indicated it an osmotin with all conserved characteristics, with closest relationship to osmotins of monocots, but including a non-homologous sequence of 50 AA at its C-terminus. Structural-to-functional predictions of TlOsm, in comparison with two rice osmotins, proposed the multi-functional nature of TlOsm and its novel characteristics. Functional predictions indicate two types of TlOsm binding sites (glucan-binding and phosphorylation sites) in common with other osmotins and one type of binding sites (sites with enzymatic functions in sugar metabolism) unique to TlOsm. TlOsm contains three types of potential functional activities in different biological processes of plant response to abiotic and biotic stresses, suggesting the multiple functions of TlOsm in both abiotic and biotic defense response of plants. Gene activated by stress stimuli are likely involved in the response to those stresses. Profiling the transcriptional expression of TlOsm in native T. loliiformis plants during development and during cold, drought, heat, and salinity stresses indicated the involvement of TlOsm in plant response to cold, drought, and salinity stresses (Figure 3.6). TlOsm was activated in both root and shoot of T. loliiformis plants at noticeably high levels at very early stage of cold, drought, and salinity stresses. The remarkable activation of TlOsm upon various stresses suggested its role in multi-stress response of T. loliiformis. The multi-functional roles in plant stress response of osmotins has been demonstrated and transgenic plants expressing osmotin have exhibited enhanced tolerance to cold, drought, salinity stresses and resistant to bacterial and fungal infections (summarized with reference in Table 1.1). In transgenic osmotin plants, osmotins have shown function in activating various molecular, chemical, and physiological changes that ultimately resulted in morphological changes for adaptation. The roles of TlOsm in plant response to multiple abiotic stress were also validated in transgenic rice in comparision with the rice osmotins (Chapter 5). Analyses of physiological and agronomic traits of transgenic rice expressing TlOsm, OsOlp1_A, OlOlp1_I and controls subjected to cold, drought, and salinity stresses proved the roles of TlOsm and OsOlp1_A in enhancing rice plants tolerance to these stresses. Across two generations (T0 and T1) of transgenic rice plants and
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regardless the developmental stages (seedling and reproductive stages) when stresses applied, TlOsm and OsOlp1_A plants showed enhanced shoot growth rate (Figure 5.1), tiller number (Figure 5.2), dried biomass (Table 5.2 & 5.3), survival rate (Figure 5.10), and grain yield (Table 5.4). The enhanced stress tolerance of TlOsm and OsOlp1_A rice plants was accompanied with the abilities to greater retain leaf water content (Figure 5.3), to better maintain cell integrity (Figure 5.4), and to more effective regulate photosynthesis-related activities (Figure 5.5-5.7). These physiological changes were similar to those of other transgenic osmotin plants (refer to Section 5.4.1). All the tested plants were generated from the same genetic background of rice cultivar Nipponbare. The physiological and agronomic traits associated with rice stress tolerance were exhibited in TlOsm and OsOlp1_A plants. Thus, the tolerance to cold, drought, and salinity stresses of TlOsm and OsOlp1_A rice plants must be the consequence of TlOsm and OsOlp1_A expression. These results demonstrate the functions of TlOsm (and OsOlp1_A) in rice response to multiple stresses including cold, drought, and salinity. TlOsm was demonstrated to interact with various Arabidopsis proteins, which are involved in diverse biological processes and pathways for plant signalling, abiotic stress response, plant-pathogen interaction, biosynthesis, and metabolism (Figure 6.5, Table 6.4, Table 6.5, Table 6.6, Appendix E-Table 2&3). Interacting with significant numbers of proteins in the conserved and fundamental pathways in plant development and adaptation such as fructose and mannose metabolism, glycolysis, and pentose phosphate pathways displays different functions of TlOsm. In planta, TlOsm was proven to interact with four stress-responsive proteins in signalling, biosynthesis, and detoxification pathways. The involvements of TlOsm interactors in diverse biological processes and pathways reflect the multiple functions of TlOsm.
7.3 TlOsm (and OsOlp1_A) likely contribute to plant stress response through signal transduction
In plants, efficacy of stress responses depend on early signal perception and rapid signal transduction that activate the appropriate cellular responses such as gene transcriptional reprogram, hormonal alteration, and production of protective compounds that subsequently result in adaptation (Huang et al., 2012; Mishra et al., 2016; Zhu 2016). The characteristics of TlOsm revealed from this research suggest its contribution to plant stress response through signal transduction.
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Studies have shown that genes activated early are involved in stress signal sensing and transduction while those with delayed activation are involved in later adaptive responses (Agarwal et al., 2013; Zhu, 2016). Transcriptional expression of TlOsm upon major abiotic stresses indicated its early activation in cold, drought, and salinity stresses (Figure 3.6 E-J). TlOsm was activated at highest levels in both root and shoot within 1-3 h upon cold stress, at 80-60% of leaf RWC in in drought stress, and at 1-6 h upon salinity stress exposure. In addition, the plasma membrane is a sensory site and a location for many proteins functioning in environmental signal interpretation and triggering cellular responses (Tan et al., 2008). TlOsm was localised to the plasma membrane (Figure 3.10) regardless of stress condition (Figure 3.11). Early activation of TlOsm and its plasma membrane localisation suggest its functions in stress signalling pathways.
Previous studies on plant stress response have indicated some common signal transduction pathways shared by cold, drought and salinity stress responses that subsequently regulate the expression of similar gene sets and result in similar adaptive response of plants to more than one stress (Fujii and Zhu, 2012; Huang et al., 2012; Mishra et al., 2016; Xiong and Zhu, 2002). These shared signalling pathways facilitate plant adaptive responses and protect them from multiple environmental stresses. Hence, single gene functioning in multiple stress response is likely involved in the shared signalling pathways. TlOsm was activated by cold, drought, and salinity stresses in T. loliiformis and thus involved in these stress responses of T. loliiformis. The enhanced cold, drought, and salinity stress tolerance of transgenic rice plants was achieved by expressing either TlOsm or OsOlp1_A. Therefore, it is likely that TlOsm (and OsOlp1_A) facilitate plant stress response via signalling pathways.
The functions in stress signalling pathways of TlOsm and OsOlp1_A were strongly confirmed by their interactions with AtCPK4 and AtCPK5 in N. benthamiana plants (Figure 6.6 & 6.7). CPK4 and CPK5 are the members of well- known plant stress signal transducers, the calcium-dependent protein kinase family. CPK4 and CPK5 have been demonstrated to regulate plant defense through generation of ROS signalling by phosphorylating NADPH oxidase/ RBOH (Gao et al., 2013; Kobayashi et al., 2007). AtCPK4 was proven to function in plant abiotic stress response by up-stream modulating abscisic acid signal transduction via phosphorylating ABF1 and ABF4 transcription factors (Zhu et al., 2007). Similarly, AtCPK5 was proven to
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regulate immune signalling by functioning in rapid cell-to-cell propagation and mediating phyto-hormone defense response to plant pathogens (Dubiella et al., 2013). The two interactive partners of TlOsm and OsOlp1_A are within the identified signal transduction pathways indicating the function of TlOsm and OsOlp1_A in stress signal transducing. It is not know the mode of action for AtCPK4 or AtCPK5 with TlOsm or OsOlp1_A, possibly via phosphorylation, because both TlOsm and OsOlp1_A contain potential phosphorylation sites and phosphorylation is typical reaction of calcium-dependent protein kinase for decoding stress signals (Mohanta and Sinha, 2016). It is clear that interacting with CPK4 is required for TlOsm and OsOlp1_A to activate plant adaptive response to cold, drought, and salinity stresses. Lacking of interaction with CPK4, at least, partially contributed to the failure to enhance rice tolerance to cold, drought, and salinity stress of OsOlp1_I.
Besides, AtCPK4 and AtCPK5, TlOsm was shown to interact with AtMS1 and AtALDH7B4 in planta. It is not known from the experiments that TlOsm is upstream or downstream of the CPK4 and CPK5 in the signalling network, as well as of the AtMS1 and AtALDH7B4. Here, the subcellular localisation of the interactive proteins should be considered in the interpretation. AtCPK4 was demonstrated a cytoplasmic protein (Dammann et al., 2003); while AtCPK5 is a plasma membrane protein (Lu and Hrabak, 2013). AtALDH7B4 was proven a cytoplasmic enzyme by Kotchoni et al (2006) and AtMS1 was annotated a cytoplasmic protein. TlOsm is a plasma membrane protein. Among four proteins validated to interact with TlOsm in living plants, three of them are cytoplasmic proteins. This evidence together with early activation of TlOsm upon cold, drought, and salinity stress, it is likely that TlOsm is an upstream regulator of AtCPK4, AtMS1, and AtALDH7B4.
The mechanics by which TlOsm mediates plant response to cold, drought, and salinity stresses remain to be further detailed, due to the protein-protein interaction network of TlOsm was not fully validated in planta. However, based on the existing evidences, we can speculate a plausible mechanism underlying TlOsm functions. (1) Interaction with AtCPK4 homolog is required for TlOsm and OsOlp1_A to transduce stress signals that further activate down-stream ABA signalling and abiotic stress responses such as osmotic adjustment, stomatal regulation, and membrane protection. (2) Interaction with AtMS1 homolog is probably necessary for TlOsm and OsOlp1_A to
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regulate biosynthesis of compounds beneficial for salinity stress tolerance. (3) Interaction with AtALDH7B4 homolog promotes TlOsm functions in enhanced aldehyde detoxification, reduced lipid peroxidation, and increased ROS scavenge. This interaction at least partially contributed to additional effects of TlOsm over OsOlp1_A in enhanced rice tolerance to cold, drought, and salinity stresses. (4) AtCPK5 is required for signal transduction upon pathogen infection (Dubiella et al., 2013), interaction of the osmotins with AtCPK5 (or its homologs) might facilitate pathogenic signal transduction but might not be necessary for abiotic stress response. This point is evidenced by the interaction of OsOlp1_I and AtCPK5 occurred in planta but OsOlp1_I did not confer tolerant to cold, drought, and salinity stresses in transgenic rice.
7.4 TlOsm has potential for use in improving crop tolerance to multiple abiotic stresses
In field conditions, plants are exposed to multiple abiotic and biotic stresses, either simultaneously or successively. The survival and reproduction of plants exposed to stresses depend on the rapid perception of stress and signal transduction to switch on adaptive responses (Mishra et al., 2016). Various studies have indicated significant overlaps in signalling pathways involved in abiotic and biotic stress responses (AbuQamar et al., 2009; Atkinson and Urwin, 2012; Huang et al., 2012; Mishra et al., 2016). Thus, key components conserved in these overlapping pathways may play a crucial role in eliciting plant adaptive responses to different stresses. Engineering crops with the master regulator in stress signalling pathways has been considered as an effective strategy for developing crops with broad spectrum of tolerance (Bhatnagar- Mathur et al., 2008; Cominelli et al., 2013; Mittler and Blumwald, 2010). TlOsm has exhibited the characteristics of a key modulator in regulating plant tolerant to multiple stresses throughout this research. These characteristics are described as its early transcriptional activation under different stresses and its plasma membrane localisation (Chapter 3), the diversity of biological processes and pathways that TlOsm interactive protein partners are involved in (Chapter 6), and especially the sufficient enhanced tolerance to cold, drought, and salinity stress of transgenic rice constitutively expressing TlOsm (Chapter 5). The results demonstrate the potential of TlOsm for uses in genetic engineering plants with enhanced tolerance to multi-stress factors. It should be noticed that osmotin gene from drought-tolerant rice cultivar (OsOlp1_A) can also be used for develop multi-stress tolerant crop with less efficacy than TlOsm.
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7.5 Concluding remarks
To meet the food demands of an increasing population and to mitigate the effects of changing climate on agricultural production, the development of stress-adaptive crops is in crucial need. The combination of stress-adaptive traits from naturally tolerant species into elite crop cultivars is desired and represents a key goal for genetic engineering. Thus, identification of key components regulating stress-adaptive traits in tolerant species is required for introduce new stress-adaptive traits into crop species. In this project, molecular and functional characteristics of an osmotin from desiccation tolerant plant T. loliiformis were analysed and shown potential for use in crop improvement with multiple stress tolerant traits.
For effective utilisation of T. loliiformis genetic resource in improving crop tolerance to stresses, a deep understanding of molecular basis and functional efficacy of genes controlling stress tolerant traits in this species is needed. This research presents the identification of conserved and novel characteristics of TlOsm through the comparative analyses of TlOsm with osmotin genes from stress sensitive species, O. saliva. The analyses were made through investigation of potential functional sites of the osmotin proteins based on structural-to-functional predictions, identification of their interactive protein partners and pathways, and assessment of transgenic rice expressing each osmotin gene for enhanced abiotic stress tolerance. The results suggest the evolved characteristics of TlOsm for more functional efficacy in regulating plant tolerant to stresses. These characteristics were demonstrated by extra functional binding sites in TlOsm protein structure that enable the protein interact with more stress-responsive genes. These characteristics were validated by additional effects of TlOsm over rice osmotins, the OsOlp1_A and OsOlp1_I, in enhanced transgenic rice tolerance to cold, drought, and salinity stresses. Results from evaluation of transgenic rice expressing the osmotins under cold, drought and salinity stress indicate the functional role of TlOsm and OsOlp1_A in enhanced rice tolerant to stresses and that the tolerant traits pass on the next generation. Importantly, the results provide molecular basis for speculating the mechanisms by which TlOsm and OsOlp1_A mediate plant response to osmotic stresses. The results highlight the values of T. loliiformis genetic resource for searching stress-responsive genes for combining into crops.
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In conclusion, the results highlight the additional effects on enhanced plant stress tolerance of osmotin from tolerant species over those from sensitive species. The results indicate the potential of TlOsm for use in genetic engineering of crops with improved tolerance to multiple abiotic stresses including cold, drought, and salinity. Through the analyses of TlOsm protein structure and its interactive protein partners, TlOsm also showed potential functions in regulating plant response to biotic stress. Further research should investigate if TlOsm plays role in biotic stress response of plants. The contributions of glucan-binding sites to osmotin functions in plant response to abiotic stress need to be further detailed, probably by point mutation of binding sites. To dissect the functions of TlOsm in regulating sugar metabolism, analysis of sugar metabolites in transgenic TlOsm plants should be carried out. In addition, some TlOsm protein interactors involved in the pathways related to human diseases should be interesting targets for further testing to exploit this protein as a therapeutic agent.
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Appendices
Appendix A
Chapter 2 supplementary figures
A B
PstI (2717)
KanR AvaI (524)
NcoI (2330) 13ABRILP OsOSM Apo pMK-RQ OsOSM Apo 3022 bp
PstI (879)
ApaLI (1043)
Col E1 origin ApaLI (1592)
D C
Promoter P 3 CDS 4 NcoI (360) PstI (2717) Misc Feature 7 Tl Osm Promoter P 2 NcoI (822) Promoter P 1 BstEII (947) KanR AvaI (524) Misc Feature 1 NcoI (8648) Misc Feature 2 CDS 3 NcoI (2330) 13ABRIKP OsOSM IR64 pMK-RQ OsOSM IR64 pCambia 2301- TlOsm 3022 bp 10518 bp Misc Feature 6 Misc Feature 3 PstI (879) Misc Feature 5
CDS 2 ApaLI (5880) Rep Origin 2 Rep Origin 1 Col E1 origin Misc Feature 4 ApaLI (1592) ApaLI (5382)
Appendix A-Figure 1. Maps of vectors used as templates for amplification of Gus-reporter gene (A), OsOlp1_A (B), OsOlp1_I (C) and TlOsm (D).
Appendices 209
A duplicated CaMV 35S promoter NcoI (11619) TMV U1 omega sequence attR1 Cm(R) NcoI (1761)
SpecR attR1-CmR-ccdB-attR2 GATEWAY cassette
ApaLI (9952) ApaLI (2360) pYL436 (AY737283) ccdB 12607 bp attR2 ApaLI (8860) 9x myc tag
6x HIS tag ApaLI (8362) protease 3C cleav age site 2x IgG binding domain ClaI (7415) Nos terminator
B RB CaMV 35S promoter ColE1 C1
CPMV RNA-2 5'UTR enhancer region NPTIII AgeI (1296) HISx6 HISx6
StuI (1356) pEAQ-HT CPMV RNA-2 3'UTR 10003 bp TrfA C3 Nos Terminator 35S promoter P19 OriV 35S terminator NPTII LB
Appendix A-Figure 2. Maps of vectors used to generate the pEAQ-436 destination vector. The pL436 (A) was used as template to amplify the fragment from AttR1 to the end of 2x IgG binding domain with the addition of AgeI restriction site before AttR1 and the KDEL and StuI restriction site after the 2x IgG binding domain; the pEAQ-HT was served as the backbone for the insertion of the amplicon from (A) within the AgeI and StuI sites.
210 Appendices
Appendix B
Chapter 3 supplementary data
Appendix B-Figure 1. Differences in glucan binding residues for TlOsm, OsOlp1_A, and OsOlp1_I by structural to functional prediction. A. Structure of OsOlp1_A with five binding residues D135, G136, S183, A225, and T132; B. Structure of OlOlp1_I with two binding residues D135 and T232; C. Structure of TlOsm with eight binding residues E117, F128, D130, D135, A221, Y226, A229, and T236.
Appendices 211
Appendix B-Figure 2. Sugar binding residues unique for TlOsm by structural to functional prediction.
Table 1. Difference in potential phosphorylation sites for TlOsm, OsOlp1_A, and OsOlp1_I
Type of residues Serine site Threonine site Tyrosine site TlOsm 18, 24, 26, 30, 43, 44, 47, 28, 36, 53, 64, 79, 35, 137, 197, (33 Ser, 22 Thr, 9 52, 62, 66, 69, 72, 82, 91, 83, 87, 94, 114, 119, 214, 226, Tyr) 99, 123, 132, 175, 187, 157, 208, 234, 236, 228, 230, 194, 200, 212, 215, 227, 238, 244, 245, 249, 246, 276 235, 253, 256, 259, 262, 254, 255, 273, 286 263, 264, 297, 235 OsOlp1_A 47, 63, 128, 132, 142, 127, 204 210 (12 Ser, 2 Thr, 1 177, 183, 201, 207, 208, Tyr) 211, 228 OsOlp1_I 47, 63, 128, 132, 177, 127, 144, 204 210 (11 Ser, 3 Thr, 1 183, 201, 207, 208, 211, Tyr) 228
212 Appendices
Appendix C
Chapter 4 supplementary information
Media and solutions for rice callus induction and transformation
N6 Stock Solution 1: Macronutrients (20x concentrated)
Quantity (g) per 1 L Quantity (mg) per 1 L Ingredients stock N6
KNO3 56.6 2,830
(NH4)2SO4 9.26 463
MgSO4.7H2O 3.7 185
KH2PO4 8 400
CaCl2.2H2O 3.32 166
N6 Stock Solution 2: Micronutrients (100x concentrated)
Quantity (mg) per 1 L Quantity (mg) per 1 L N6 Ingredients stock KI 80 0.8
H3PO3 160 1.6
MnSO4.4H2O 440 4.4
ZnSO4.7H2O 150 1.5
Na2MoO4.2H2O 25 0.25
N6 Stock Solution 3: Vitamins (1000 x concentrated)
Quantity (mg) per 100ml Quantity (mg) per 1L Ingredients stock N6 Nicotinic Acid 50 0.5 Pyrodoxin-HCl 50 0.5 Myo-Inositol 1,000 10 Thiamine-HCl 50 0.5 Glycine 100 1
Appendices 213
N6 Stock Solution 4: Fe-EDTA (100 x concentrated)
Quantity (mg) per 1 L Quantity (mg) per 1L Ingredients stock N6
Na2EDTA.2H2O 3,725 37.25
FeSO4.7H2O 2,785 27.85
N6 basal medium and vitamins from stock solutions
Ingredients Quantity per 1 L N6 N6 stock solution 1 50 ml N6 stock solution 2 10 ml N6 stock solution 3 1 ml N6 stock solution 4 10 ml
214 Appendices
Appendix D
Chapter 5 supplementary information
Appendix D – Table 1. Plant height before and after stress treatments at seedling stage
Treatment Plants Plant height (cm) at Plant height (cm) at day 0 day 18 Unstressed set 1 OsOlp1_A 12.59 ± 0.92 27.92 ± 1.69 Unstressed set 1 OsOlp1_I 12.58 ± 1.02 28.14 ± 1.75 Unstressed set 1 TlOsm 12.17 ± 0.70 24.56 ± 1.57 Unstressed set 1 VC 12.81 ± 0.93 28.30 ± 1.65 Unstressed set 1 WT 12.95 ± 0.73 28.79 ± 1.52 Drought OsOlp1_A 12.84 ± 0.46 22.34 ± 0.76 Drought OsOlp1_I 12.73 ± 0.46 20.79 ± 0.84 Drought TlOsm 12.56 ± 0.41 22.76 ± 0.84 Drought VC 12.72 ± 0.53 20.20 ± 0.78 Drought WT 12.86 ± 0.44 20.28 ± 0.71 Salinity OsOlp1_A 13.15 ± 0.48 23.10 ± 0.68 Salinity OsOlp1_I 12.85 ± 0.50 20.58 ± 0.65 Salinity TlOsm 12.29 ± 0.39 22.11 ± 0.65 Salinity VC 12.82 ± 0.46 19.22 ± 0.58 Salinity WT 12.88 ± 0.49 18.66 ± 0.60 Treatment Plants Plant height (cm) at Plant height (cm) at day 0 day 25 Unstressed set 2 OsOlp1_A 13.00 ± 0.29 29.46 ± 0.98 Unstressed set 2 OsOlp1_I 13.02 ± 0.30 29.57 ± 0.76 Unstressed set 2 TlOsm 12.60 ± 0.24 26.56 ± 0.78 Unstressed set 2 VC 13.01 ± 0.33 29.45 ± 1.35 Unstressed set 2 WT 13.44 ± 0.34 29.25 ± 1.31 Cold OsOlp1_A 13.07 ± 0.56 16.96 ± 0.35 Cold OsOlp1_I 13.08 ± 0.47 15.47 ± 0.27 Cold TlOsm 12.53 ± 0.40 16.97 ± 0.29 Cold VC 13.12 ± 0.52 15.47 ± 0.33 Cold WT 12.95 ± 0.49 15.18 ± 0.28 Data are expressed as mean ± SE of 135 plants in set 1 and 120 plants in set 2
Appendices 215
Appendix D – Table 2. Plant height before and after stress treatments at reproductive stage
Treatment Plants Plant height (cm) Plant height (cm) at day 0 at day 18
Unstressed NT 22.50 ± 0.42 33.75 ± 0.65 Unstressed OsOlp1_A 21.74 ± 0.33 31.74 ± 0.32 Unstressed OsOlp1_I 22.52 ± 0.36 34.34 ± 0.59 Unstressed TlOsm 21.29 ± 0.39 30.75 ± 0.37 Unstressed VC 22.12 ± 0.36 33.99 ± 0.68 Drought NT 22.86 ± 0.36 28.17 ± 0.34 Drought OsOlp1_A 21.92 ± 0.31 28.59 ± 0.32 Drought OsOlp1_I 22.43 ± 0.40 28.25 ± 0.36 Drought TlOsm 20.90 ± 0.33 28.95 ± 0.31 Drought VC 22.42 ± 0.41 27.91 ± 0.39 Salinity NT 22.60 ± 0.38 28.82 ± 0.40 Salinity OsOlp1_A 20.06 ± 0.34 30.17 ± 0.29 Salinity OsOlp1_I 22.45 ± 0.34 29.63 ± 0.32 Salinity TlOsm 21.67 ± 0.35 29.76 ± 0.34 Salinity VC 22.88 ± 0.42 28.37 ± 0.32 Data are expressed as mean ± SE of 30 plants
216 Appendices
Appendix E
Chapter 6 supplementary information
Appendix E-Table 1. Description of Arabidopsis proteins interacting with TlOsm, OsOlp1_A, and OsOlp1_I on the chip
# of TAIR-ID Description Interacting with hits OsOlp1_A OsOlp1_I TlOsm RNA-binding (RRM/RBD/RNP AT1G01080 motifs) family protein X X X 3 HR-like lesion-inducing protein-like AT1G04340 protein X 1 NAD(P)-linked oxidoreductase AT1G04420 superfamily protein X X X 3
AT1G04550 AUX/IAA transcriptional regulator family protein (IAA12) X X X 3
AT1G05010 Ethylene-forming enzyme (EFE) X X X 3
AT1G05410 CDPK adapter, putative (DUF1423) X X X 3
AT1G07140 Pleckstrin homology (PH) domain superfamily protein (SIRANBP) X X X 3 AT1G07750 RmlC-like cupins superfamily protein X X X 3 AT1G07890 Ascorbate peroxidase 1(APX1) X X X 3 AT1G09630 Ras-related protein RABA2a X X X 3 E3 ubiquitin ligase SCF complex AT1G10230 subunit SKP1/ASK1 family protein(SK18) X X X 3
AT1G10700 Phosphoribosyl pyrophosphate (PRPP) synthase 3(PRS3) X X X 3 AT1G11860 Glycine cleavage T-protein family X X X 3 Probable calcium-binding protein AT1G12310 CML13 X X X 3
AT1G13280 Allene oxide cyclase 4 (AOC4) X X X 3 Rubisco methyltransferase family AT1G14030 protein (LSMT-L) X X X 3 Polyketide cyclase/dehydrase and lipid AT1G14950 transport superfamily protein X 1 Transducin family protein / WD-40 AT1G15750 repeat family protein (TPL) X X X 3 Ribosomal protein AT1G15930 L7Ae/L30e/S12e/Gadd45 family protein X X X 3
AT1G16030 Heat shock protein 70B (Hsp70b) X X X 3
AT1G18080 Transducin/WD40 repeat-like superfamily protein (ATARCA) X X X 3 AT1G19570 Dehydroascorbate reductase (DHAR1) X X X 3
AT1G20510 4-coumarate--CoA ligase-like 5 X X X 3
AT1G20950 Phosphofructokinase family protein X X X 3
Appendices 217
# of TAIR-ID Description Interacting with hits OsOlp1_A OsOlp1_I TlOsm Aldehyde dehydrogenase 2B7 AT1G23800 (ALDH2B7) X X X 3 AT1G26640 Isopentenyl phosphate kinase (IPK) X X X 3
AT1G27500 Tetratricopeptide repeat (TPR)-like superfamily protein (KLCR3) X X X 3 AT1G30070 SGS domain-containing protein X 1
AT1G35160 GF14 protein phi chain (GF14 PHI) X X X 3
AT1G35460 Basic helix-loop-helix (bHLH) DNA- binding superfamily protein (FBH1) X X X 3
AT1G36390 Co-chaperone GrpE family protein X X X 3 Inositol monophosphatase family AT1G43670 protein (FBP) X X X 3 Ubiquitin interaction motif-containing AT1G43690 protein X 1 AT1G47420 succinate dehydrogenase 5 (SDH5) X X X 3 Receptor for activated C kinase 1B AT1G48630 (RACK1B_AT) X X X 3 AT1G49570 Peroxidase 10 X X X 3
AT1G49820 S-methyl-5-thioribose kinase (MTK) X X X 3 Sirohydrochlorin ferrochelatase B AT1G50170 (SIRB) X X X 3 Transducin/WD40 repeat-like AT1G52730 superfamily protein X X X 3
AT1G54100 Aldehyde dehydrogenase family 7 member B4 (ALDH7B4) X 1 FAD/NAD(P)-binding oxidoreductase AT1G57770 family protein X X X 3 B-box zinc finger family protein AT1G60250 (BBX26) X 1 Probable calcium-binding protein AT1G62820 CML14 X X X 3
AT1G65870 Disease resistance-responsive (dirigent- like protein) family protein X X X 3 Histone-lysine N-methyltransferase AT1G66240 ATX1 X 1 AT1G66270 Beta-glucosidase BGLU21 X X X 3 AT1G68760 Nudix hydrolase 1 (NUDX1) X X X 3 AT1G70570 Anthranilate phosphoribosyltransferase X 1 AT1G70830 MLP-like protein 28 (MLP28) X 1 AT1G70890 MLP-like protein 43 (MLP43) X X X 3 Tubulin folding cofactor E / Pfifferling AT1G71440 (Wurzinger et al.) X X X 3 AT1G71697 Choline kinase 1 (CK1) X X X 3 Transducin family protein / WD-40 AT1G71840 repeat family protein X X X 3
AT1G73720 Transducin family protein / WD-40 repeat family protein (SMU1) X X X 3
AT1G74040 2-isopropylmalate synthase 1 (IMS1) X X 2
218 Appendices
# of TAIR-ID Description Interacting with hits OsOlp1_A OsOlp1_I TlOsm Glycine-rich RNA-binding protein AT1G74230 5(GR-RBP5) X X X 3 Dehydroascorbate reductase 2 AT1G75270 (DHAR2) X X X 3 Calcium-dependent protein kinase 29 AT1G76040 (CPK29) X X 2 Indole glucosinolate O- AT1G76790 methyltransferrase 5 (IGMT5) X X X 3 AT1G77120 Alcohol dehydrogenase 1 (ADH1) X X X 3 AT1G77520 O-methyltransferase family protein X X X 3 AT1G78300 General regulatory factor 2 (GRF2) X X X 3 AT1G78680 Gamma-glutamyl hydrolase 2 (GGH2) X X 2 AT1G79070 SNARE-associated protein-like protein X X X 3 AT1G79250 AGC kinase 1.7 (AGC1.7) X X X 3 AT1G79550 Phosphoglycerate kinase (PGK) X X 2 Rad23 UV excision repair protein AT1G79650 family (RAD23B) X X X 3 AT2G02990 Ribonuclease 1 (RNS1) X X X 3 AT2G03310 Transmembrane protein X X X 3 Zinc-dependent activator protein-1 AT2G04880 (ZAP1) X X X 3 AT2G05710 Aconitase 3(ACO3) X X 2 AT2G17190 Ubiquitin receptor protein (DSK2A) X 1 AT2g17290 Calcium-dependent protein kinase family protein (CPK6) X X X 3
AT2G17560 High mobility group B4 (HMGB4) X 1
AT2G17700 ACT-like protein tyrosine kinase family protein (STY8) X X 2
AT2G17870 Cold shock domain protein 3 (CSP3) X X X 3 Leucine-rich repeat (LRR) family AT2G19780 protein X X X 3
AT2G20630 PP2C induced by AVRRPM1 (PIA1) X X X 3
AT2G20690 Lumazine-binding family protein X X X 3 AT2G21100 Disease resistance-responsive (dirigent- like protein) family protein X X X 3 AT2G22480 Phosphofructokinase 5 (PFK5) X X X 3 N-acetyl-l-glutamate synthase 1 AT2G22910 (NAGS1) X X X 3 LOB domain-containing protein 10 AT2G23660 (LBD10) X X X 3 Cytosol aminopeptidase family protein AT2G24200 (LAP1) X X X 3 AT2G25080 Glutathione peroxidase 1 (GPX1) X X X 3 AT2G26840 MutS2 X X X 3 UDP-D-apiose/UDP-D-xylose synthase AT2G27860 1 (AXS1) X X 2
AT2G30050 Transducin family protein / WD-40 repeat family protein X X X 3
Appendices 219
# of TAIR-ID Description Interacting with hits OsOlp1_A OsOlp1_I TlOsm Tubulin folding cofactor A (KIESEL) AT2G30410 (KIS) X X X 3 PfkB-like carbohydrate kinase family AT2G31390 protein X X X 3
AT2G35320 Eyes absent-like protein (EYA) X X X 3
AT2G35380 Peroxidase 20 X X 2
AT2G35500 Shikimate kinase like 2 (SKL2) X X X 3
AT2G38270 CAX-interacting protein 2 (CXIP2) X X X 3
AT2G38380 Peroxidase 22 X X X 3
AT2G38860 Class I glutamine amidotransferase-like superfamily protein (YLS5) X X X 3
AT2G42120 DNA polymerase delta small subunit X X X 3
AT2G42540 Cold-regulated 15a (COR15A) X X X 3
AT2G43750 O-acetylserine (thiol) lyase B (OASB) X X X 3
AT2G43790 MAP kinase 6 (MPK6) X X 2 Inositol 1,3,4-trisphosphate 5/6-kinase AT2G43980 4 (ITPK4) X X X 3 6,7-dimethyl-8-ribityllumazine AT2G44050 synthase / DMRL synthase / lumazine synthase / riboflavin synthase (COS1) X X X 3
AT2G44530 Ribose-phosphate pyrophosphokinase 5 X X X 3 Methionine aminopeptidase 1A AT2G45240 (MAP1A) X X X 3
AT2G45770 Signal recognition particle receptor protein, chloroplast (FTSY) (CPFTSY) X X X 3
AT2G46170 Reticulon-like protein B5 X 1 Auxin-responsive GH3 family protein AT2G46370 (JAR1) X X X 3 Transducin/WD40 repeat-like AT3G01340 superfamily protein X X X 3
AT3G01680 Sieve element occlusion amino- terminus protein (SEOR1) X X X 3
AT3G02520 General regulatory factor 7 (GRF7) X X X 3 Rad23 UV excision repair protein AT3G02540 family (RAD23C) X X X 3
AT3G02900 Low-density receptor-like protein X X X 3
AT3G03780 Methionine synthase 2 (MS2) X X X 3
AT3G04650 FAD/NAD(P)-binding oxidoreductase X X X 3 AT3G05020 Acyl carrier protein 1 (ACP1) X X X 3 D-aminoacid aminotransferase-like AT3G05190 PLP-dependent enzymes superfamily protein X 1
220 Appendices
# of TAIR-ID Description Interacting with hits OsOlp1_A OsOlp1_I TlOsm AT3G06050 peroxiredoxin IIF (PRXIIF) X X X 3 AT3G06110 MAPK phosphatase 2 (MKP2) X X X 3 AT3G06650 ATP-citrate lyase B-1 (ACLB-1) X X X 3 AT3G07800 Thymidine kinase (TK1a) X X X 3 AT3G09390 Metallothionein 2A (MT2A) X 1 AT3G10230 Lycopene cyclase (LYC) X X 2 3-phosphoinositide-dependent protein AT3G10540 kinase X X X 3 AT3G10700 Galacturonic acid kinase (GalAK) X X X 3 AT3G11200 Alfin-like 2 (AL2) X X X 3
AT3G11930 Adenine nucleotide alpha hydrolases- like superfamily protein X X X 3 AT3G12110 Actin-11 (ACT11) X X X 3 Amino acid dehydrogenase family AT3G12290 protein X X X 3 Phosphoenolpyruvate carboxylase 3 AT3G14940 (PPC3) X X X 3 RNA-binding (RRM/RBD/RNP AT3G15010 motifs) family protein X X X 3
AT3G15890 PTI1-like tyrosine-protein kinase X 1 Pollen Ole e 1 allergen and extensin AT3G16670 family protein X X X 3
AT3G16910 Acyl-activating enzyme 7 (AAE7) X X X 3
AT3G18680 Amino acid kinase family protein X X X 3
AT3G18780 Actin 2 (ACT2) X 1
AT3G19100 Protein kinase superfamily protein X X X 3
AT3G20530 Protein kinase superfamily protein X X X 3 Histidine-containing AT3G21510 phosphotransmitter 1 (AHP1) X X X 3 Homocysteine S-methyltransferase 3 AT3G22740 (HMT3) X X X 3
AT3G24020 Disease resistance-responsive (dirigent- like protein) family protein X X X 3 AT3G24530 AAA-type ATPase family protein / ankyrin repeat family protein X X X 3 Nuclear transport factor 2 (NTF2) family protein with RNA binding AT3g25150 (RRM-RBD-RNP motifs) domain- containing protein X X X 3 AT3G25770 Allene oxide cyclase 2 (AOC2) X X X 3
AT3G26744 Basic helix-loop-helix (bHLH) DNA- binding superfamily protein (ICE1) X X X 3
AT3G27850 Ribosomal protein L12-C (RPL12-C) X X X 3
Appendices 221
# of TAIR-ID Description Interacting with hits OsOlp1_A OsOlp1_I TlOsm
AT3G28500 60S acidic ribosomal protein P2-3 X X X 3 Histidine-containing AT3G29350 phosphotransmitter 2 (AHP2) X X X 3 Alfin1-like family of nuclear-localized AT3G42790 PHD (plant homeodomain) domain containing proteins, AL3 X X X 3
AT3G44860 Farnesoic acid carboxyl-O- methyltransferase (FAMT) X X X 3 Serine carboxypeptidase-like 48 AT3G45010 (Scpl48) X X X 3 AT3G46010 Actin depolymerizing factor 1 (ADF1) X X X 3 Aldehyde dehydrogenase 2B4 AT3G48000 (ALDH2B4) X X X 3 AT3G51130 Transmembrane protein (UPF0183) X X X 3 BCL-2-associated athanogene 4 AT3G51780 (BAG4) X X X 3 Phosphoglycerate mutase family AT3G52155 protein X X X 3
AT3G53990 Adenine nucleotide alpha hydrolases- like superfamily protein X X X 3
AT3G54050 High cyclic electron flow 1 (HCEF1) X X 2
AT3G54600 Class I glutamine amidotransferase-like superfamily protein (DJ1F) X X X 3
AT3G54900 CAX interacting protein 1 (CXIP1) X X X 3 Chalcone-flavanone isomerase family AT3G55120 protein (TT5) X X X 3 Nucleic acid binding / AT3G58470 methyltransferase X X X 3
AT3G61080 Protein kinase superfamily protein X X X 3 Alpha/beta-Hydrolases superfamily AT3G61540 protein X X X 3
AT3G61830 Auxin response factor 18 (ARF18) X X X 3 Protein kinase superfamily protein AT3G63260 (ATMRK1) X X X 3 ATP binding microtubule motor family AT3G63480 protein X X X 3
AT4G00220 Lateral organ boundaries (LOB) domain family protein (JLO) X X X 3 bZIP transcription factor family protein AT4G02640 (BZO2H1) X X X 3 Methionine sulfoxide reductase B5 AT4G04830 (MSRB5) X X X 3
AT4G08390 Stromal ascorbate peroxidase (SAPX) X X X 3
AT4G09180 Basic helix-loop-helix (bHLH) DNA- binding superfamily protein (FBH2) X X X 3 Calcium-dependent protein kinase 4 AT4G09570 (CPK4) X X X 3
222 Appendices
# of TAIR-ID Description Interacting with hits OsOlp1_A OsOlp1_I TlOsm
AT4G09620 Mitochondrial transcription termination factor family protein X X X 3 B-box zinc finger family protein AT4G10240 (Bbx23) X X X 3
AT4G10250 HSP20-like chaperones superfamily protein (ATHSP22.0) X X X 3
AT4G11180 Disease resistance-responsive (dirigent- like protein) family protein X X X 3
AT4G11210 Disease resistance-responsive (dirigent- like protein) family protein X X X 3
AT4G11320 Papain family cysteine protease X X X 3
AT4G13200 Hypothetical protein X X X 3
AT4G13580 Disease resistance-responsive (dirigent- like protein) family protein X X X 3 Serine hydroxymethyltransferase 4 AT4G13930 (SHM4) X X X 3 Ubiquitin C-terminal hydrolase 3 AT4G17510 (UCH3) X X X 3
AT4G20780 Calcium-binding protein CML42 X X 2 Riboflavin kinase/FMN hydrolase AT4G21470 (FMN/FHY) X X X 3
AT4G23170 Receptor-like protein kinase-related family protein (EP1) X X 2 Calcium-dependent protein kinase 6 AT4G23650 (CDPK6) X X X 3
AT4G23670 Polyketide cyclase/dehydrase and lipid transport superfamily protein X X X 3 Ubiquitin-associated (UBA)/TS-N domain-containing protein / AT4G24690 octicosapeptide/Phox/Bemp1 (PB1) domain-containing protein (NBR1) X X 2
AT4G25050 Acyl carrier protein 4 (ACP4) X X X 3
AT4G26070 MAP kinase/ ERK kinase 1 (MEK1) X X X 3
AT4G26220 S-adenosyl-L-methionine-dependent methyltransferases superfamily protein X 1
AT4G26270 Phosphofructokinase 3 (PFK3) X X 2 Adenine nucleotide alpha hydrolases- AT4G27320 like superfamily protein (PHOS34) X X X 3 Rhodanese/Cell cycle control AT4G27700 phosphatase superfamily protein X X X 3 AT4G28660 Photosystem II reaction center PSB28 protein (PSB28) X X X 3 PfkB-like carbohydrate kinase family AT4G28706 protein X X X 3 Pyridoxal phosphate phosphatase- AT4G29530 related protein X X X 3
Appendices 223
# of TAIR-ID Description Interacting with hits OsOlp1_A OsOlp1_I TlOsm
AT4G29720 Polyamine oxidase 5 (PAO5) X 1
AT4G29830 Transducin/WD40 repeat-like superfamily protein (VIP3) X X X 3
AT4G30910 Cytosol aminopeptidase family protein X X X 3
AT4G31720 TBP-associated factor II 15 (TAFII15) X X X 3 2Fe-2S ferredoxin-like superfamily AT4G32590 protein; X X X 3
AT4G32840 Phosphofructokinase 6 (PFK6) X X X 3
AT4G33090 Aminopeptidase M1 (APM1) X X X 3 Pyridoxal phosphate (PLP)-dependent AT4G33680 transferases superfamily protein (AGD2) X X X 3 S-adenosyl-L-methionine-dependent AT4G34050 methyltransferases superfamily protein (CCoAOMT1) X X 2
AT4G35220 Cyclase family protein (CYCLASE2) X X X 3 Calmodulin-domain protein kinase 5 AT4G35310 (CPK5) X X X 3
AT4G36910 Cystathionine beta-synthase (CBS) family protein (LEJ2) X X X 3
AT4G37000 Accelerated cell death 2 (ACD2) X X X 3 B-box type zinc finger family protein AT4G38960 (BBX19) X 1 Alanine:glyoxylate aminotransferase 2 AT4G39660 (AGT2) X X X 3 SNF1-related protein kinase 2.7 AT4G40010 (SNRK2.7) X X X 3 Heat shock cognate protein 70-1 AT5G02500 (HSC70-1) X X X 3 Chalcone-flavanone isomerase family AT5G05270 protein (CHIL) X X X 3
AT5G05610 Alfin-like 1 (AL1) X X X 3
AT5G06110 DNAJ and myb-like DNA-binding domain-containing protein X X X 3
AT5G06730 Peroxidase superfamily protein X 1 Structural maintenance of AT5G08400 chromosomes-like protein, putative (DUF3531) X X X 3
AT5G09810 Actin 7 (ACT7) X X X 3
AT5G10300 Methyl esterase 5 (MES5) X X X 3
AT5G10450 G-box regulating factor 6 (GRF6) X X X 3 Zincin-like metalloproteases family AT5G10540 protein X X X 3
224 Appendices
# of TAIR-ID Description Interacting with hits OsOlp1_A OsOlp1_I TlOsm AT5G10830 S-adenosyl-L-methionine-dependent methyltransferases superfamily protein X X X 3
AT5G11170 DEAD/DEAH box RNA helicase family protein (UAP56a) X 1
AT5G11680 Classical AGP protein X X X 3
AT5G13120 Peptidyl-prolyl cis-trans isomerase CYP20-2, cyclophilin 20-2 (Pnsl5) X X X 3
AT5G13280 Aspartate kinase 1 (AK-LYS1) X X X 3
AT5G13520 Peptidase M1 family protein X X X 3 Chalcone and stilbene synthase family AT5G13930 protein (TT4) X 1 Peroxidase superfamily protein, AT5G14130 peroxidase 55 X X X 3
AT5G16050 General regulatory factor 5 (GRF5) X X X 3 Ribonuclease E inhibitor AT5G16450 RraA/Dimethylmenaquinone methyltransferase X X X 3
AT5G17920 Cobalamin-independent synthase family protein (ATMS1) X X 2 Nudix hydrolase homolog 19 AT5G20070 (NUDX19) X X X 3 SAUR-like auxin-responsive protein AT5G20810 family X X 2 Nuclear-encoded CLP protease P7 AT5G23140 (NCLPP7) X X X 3 Calmodulin-like domain protein kinase AT5G23580 9 (CDPK9) X 1
AT5G24490 30S ribosomal protein X X X 3 DUF1995 domain protein, putative AT5G27560 (DUF1995) X X X 3 PfkB-like carbohydrate kinase family AT5G37850 protein (SOS4) X X X 3 Rad23 UV excision repair protein AT5G38470 family (RAD23D) X X X 3
AT5G38480 General regulatory factor 3 (GRF3) X X X 3 Histidine-containing AT5G39340 phosphotransmitter 3 (AHP3) X X X 3
AT5G39790 Protein targeting to starch (PTST) X X X 3
AT5G40850 Urophorphyrin methylase 1 (UPM1) X X 2
AT5G41600 VIRB2-interacting protein 3 (BTI3) X 1 Heat shock protein 70 (Hsp 70) family AT5G42020 protein (BIP2) X X 2
AT5G42070 Hypothetical protein X X 2 Inositol-pentakisphosphate 2-kinase 1 AT5G42810 (IPK1) X X X 3
Appendices 225
# of TAIR-ID Description Interacting with hits OsOlp1_A OsOlp1_I TlOsm Ureidoglycolate amidohydrolase AT5G43600 (UAH) X X X 3 AT5G45070 Phloem protein 2-A8 (PP2-A8) X X X 3 AT5G45080 Phloem protein 2-A6 (PP2-A6) X X X 3 ATPase, F1 complex, delta/epsilon AT5G47030 subunit X X 2
AT5G47810 Phosphofructokinase 2 (PFK2) X X X 3 Adenosine monophosphate kinase AT5G47840 (AMK2) X X X 3 Bifunctional inhibitor/lipid-transfer AT5G48485 protein/seed storage 2S albumin superfamily protein (DIR1) X X X 3 AT5G49650 Xylulose kinase-2 (XK-2) X X X 3 AT5G58110 Chaperone binding / ATPase activator X X X 3 PfkB-like carbohydrate kinase family AT5G58730 protein (Mik) X X X 3
AT5G59500 Protein C-terminal S-isoprenylcysteine carboxyl O-methyltransferase X X X 3 Zn-dependent exopeptidases AT5G60160 superfamily protein X X X 3 ABC transporter family protein AT5G60790 (ABCF1) X X X 3 Inositol polyphosphate kinase 2 beta AT5G61760 (IPK2BETA) X X X 3 SGNH hydrolase-type esterase AT5G62930 superfamily protein X X X 3 Nucleoside diphosphate kinase 2 AT5G63310 (NDPK2) X X X 3 SNF1-related protein kinase 2.5 AT5G63650 (SNRK2.5) X X X 3 Inositol monophosphatase family AT5G64380 protein X X X 3 AT5G65020 Annexin 2 (ANNAT2) X X X 3 AT5G65430 General regulatory factor 8 (GRF8) X X X 3 Zincin-like metalloproteases family AT5G65620 protein X X X 3
Total 239 237 267
226 Appendices
Appendix E-Table 2. Significant GO terms for Arabidopsis proteins interacting with TlOsm, OsOlp1_A, and OsOlp1_I on the chip
GO term Description Input Background p-value FDR GO:0050896 response to stimulus 87 4057 1.1e-21 1e-18 GO:0006950 response to stress 59 2320 1.2e-17 5.6e-15 GO:0042221 response to chemical stimulus 48 2085 7.8e-13 2.4e-10 GO:0009987 cellular process 137 11684 4.3e-12 9.9e-10 cellular amino acid and derivative GO:0006519 26 682 8.5e-12 1.6e-09 metabolic process cellular nitrogen compound metabolic GO:0034641 21 506 2.2e-10 3.3e-08 process GO:0008152 metabolic process 122 10614 8.6e-10 1.1e-07 cellular nitrogen compound GO:0044271 18 394 1e-09 1.2e-07 biosynthetic process GO:0044237 cellular metabolic process 106 8722 1.2e-09 1.2e-07 GO:0016053 organic acid biosynthetic process 18 417 2.4e-09 2e-07 GO:0046394 carboxylic acid biosynthetic process 18 417 2.4e-09 2e-07 GO:0009628 response to abiotic stimulus 33 1471 8.2e-09 5.3e-07 cellular aromatic compound metabolic GO:0006725 17 399 8.2e-09 5.3e-07 process GO:0042180 cellular ketone metabolic process 25 882 7.9e-09 5.3e-07 GO:0051716 cellular response to stimulus 24 840 1.4e-08 8.3e-07 GO:0043436 oxoacid metabolic process 24 859 2.1e-08 1.1e-06 GO:0006082 organic acid metabolic process 24 860 2.1e-08 1.1e-06 GO:0019752 carboxylic acid metabolic process 24 859 2.1e-08 1.1e-06 aromatic compound biosynthetic GO:0019438 13 237 3e-08 1.4e-06 process GO:0010033 response to organic substance 30 1342 4.4e-08 1.9e-06 cellular amino acid biosynthetic GO:0008652 12 202 4.5e-08 1.9e-06 process GO:0070887 cellular response to chemical stimulus 17 452 4.7e-08 1.9e-06 GO:0005996 monosaccharide metabolic process 11 168 6.5e-08 2.6e-06 GO:0007242 intracellular signalling cascade 20 659 9.1e-08 3.5e-06 GO:0009698 Phenylpropanoid metabolic process 11 175 9.6e-08 3.5e-06 cellular amino acid derivative GO:0006575 14 315 1.1e-07 3.7e-06 metabolic process GO:0009699 Phenylpropanoid biosynthetic process 10 141 1.3e-07 4.1e-06 GO:0044238 primary metabolic process 102 8995 1.3e-07 4.1e-06 GO:0006066 alcohol metabolic process 13 270 1.3e-07 4.1e-06 GO:0009309 amine biosynthetic process 12 229 1.6e-07 5e-06 GO:0010035 response to inorganic substance 13 279 1.8e-07 5.3e-06 cellular amino acid derivative GO:0042398 12 233 2e-07 5.6e-06 biosynthetic process
Appendices 227
GO term Description Input Background p-value FDR GO:0009719 response to endogenous stimulus 24 1068 9.8e-07 2.7e-05 GO:0006979 response to oxidative stress 13 332 1.2e-06 3.2e-05 cellular carbohydrate metabolic GO:0044262 14 417 2.6e-06 6.9e-05 process GO:0009266 response to temperature stimulus 15 485 3.1e-06 7.8e-05 GO:0006520 cellular amino acid metabolic process 14 430 3.7e-06 9.2e-05 GO:0044106 cellular amine metabolic process 14 438 4.6e-06 0.00011 GO:0019318 hexose metabolic process 8 126 5.2e-06 0.00012 GO:0046686 response to cadmium ion 9 178 7.7e-06 0.00018 GO:0006970 response to osmotic stress 13 408 1e-05 0.00023 GO:0009755 hormone-mediated signalling pathway 11 321 2.6e-05 0.00056 GO:0032870 cellular response to hormone stimulus 11 321 2.6e-05 0.00056 GO:0009308 amine metabolic process 14 521 3e-05 0.00062 GO:0009409 response to cold 11 328 3.2e-05 0.00063 GO:0009725 response to hormone stimulus 20 982 3.2e-05 0.00063 GO:0044249 cellular biosynthetic process 59 4925 3.4e-05 0.00066 GO:0019748 secondary metabolic process 13 489 6.4e-05 0.0012 GO:0010038 response to metal ion 9 238 6.9e-05 0.0013 GO:0006096 glycolysis 5 57 7.7e-05 0.0014 GO:0009651 response to salt stress 11 366 8.2e-05 0.0015 GO:0009058 biosynthetic process 59 5118 0.0001 0.0018 GO:0009611 response to wounding 8 197 0.00011 0.0019 GO:0046483 heterocycle metabolic process 12 460 0.00014 0.0024 GO:0006952 defense response 16 766 0.00015 0.0025 GO:0007165 signal transduction 21 1228 0.00022 0.0036 GO:0009607 response to biotic stimulus 14 638 0.00024 0.0038 GO:0006007 glucose catabolic process 5 83 0.0004 0.0063 GO:0000096 sulfur amino acid metabolic process 5 84 0.00042 0.0063 GO:0019320 hexose catabolic process 5 84 0.00042 0.0063 GO:0046365 monosaccharide catabolic process 5 84 0.00042 0.0063 GO:0006006 glucose metabolic process 5 86 0.00047 0.0069 GO:0042440 pigment metabolic process 6 134 0.00048 0.007 GO:0046164 alcohol catabolic process 5 89 0.00054 0.0077 aspartate family amino acid metabolic GO:0009066 5 90 0.00057 0.008 process GO:0006633 fatty acid biosynthetic process 6 140 0.0006 0.0083 monocarboxylic acid metabolic GO:0032787 10 408 0.00081 0.011 process GO:0009605 response to external stimulus 10 429 0.0012 0.016 generation of precursor metabolites GO:0006091 8 285 0.0012 0.016 and energy
228 Appendices
GO term Description Input Background p-value FDR GO:0009408 response to heat 6 161 0.0012 0.016 GO:0006631 fatty acid metabolic process 7 225 0.0013 0.017 GO:0051707 response to other organism 12 599 0.0014 0.018 GO:0046148 pigment biosynthetic process 5 112 0.0015 0.018 GO:0005975 carbohydrate metabolic process 15 866 0.0016 0.019 GO:0044272 sulfur compound biosynthetic process 5 115 0.0016 0.02 GO:0051186 cofactor metabolic process 8 308 0.0019 0.023 cellular carbohydrate catabolic GO:0044275 5 125 0.0023 0.027 process GO:0016052 carbohydrate catabolic process 5 128 0.0025 0.03 GO:0051704 multi-organism process 13 776 0.0041 0.048 GO:0003824 catalytic activity 138 9638 9e-20 2.4e-17 GO:0016740 transferase activity 69 3321 3.3e-16 4.5e-14 GO:0016301 kinase activity 44 1641 5.5e-14 4.9e-12 transferase activity, transferring GO:0016772 47 1887 9.2e-14 6.2e-12 phosphorus-containing groups GO:0019200 carbohydrate kinase activity 9 53 5.3e-10 2.9e-08 protein phosphorylated amino acid GO:0045309 7 23 1.4e-09 5.3e-08 binding GO:0051219 phosphoprotein binding 7 23 1.4e-09 5.3e-08 phosphotransferase activity, alcohol GO:0016773 29 1154 6.4e-09 2.2e-07 group as acceptor GO:0016209 antioxidant activity 11 150 2.2e-08 5.4e-07 GO:0008168 methyltransferase activity 14 273 2e-08 5.4e-07 transferase activity, transferring one- GO:0016741 14 275 2.1e-08 5.4e-07 carbon groups GO:0008443 phosphofructokinase activity 5 12 9.5e-08 2.1e-06 GO:0004177 aminopeptidase activity 5 14 1.8e-07 3.7e-06 oxidoreductase activity, acting on GO:0016684 9 127 5.6e-07 1e-05 peroxide as acceptor GO:0004601 peroxidase activity 9 127 5.6e-07 1e-05 calmodulin-dependent protein kinase GO:0004683 6 42 1.1e-06 1.8e-05 activity GO:0008238 exopeptidase activity 7 104 1.4e-05 0.00022 GO:0008171 O-methyltransferase activity 5 45 2.7e-05 0.0004 GO:0008237 metallopeptidase activity 6 90 6.2e-05 0.00088 GO:0020037 heme binding 5 97 0.00079 0.011 GO:0016491 oxidoreductase activity 22 1463 0.00087 0.011 peptidase activity, acting on L-amino GO:0070011 12 579 0.0011 0.013 acid peptides S-adenosylmethionine-dependent GO:0008757 5 109 0.0013 0.015 methyltransferase activity GO:0008233 peptidase activity 12 646 0.0026 0.029
Appendices 229
GO term Description Input Background p-value FDR GO:0046906 tetrapyrrole binding 5 136 0.0033 0.034 GO:0016853 isomerase activity 7 265 0.0033 0.034 GO:0005622 intracellular 149 9671 2e-25 4.7e-23 GO:0005737 cytoplasm 121 6822 2.2e-24 2.6e-22 GO:0044424 intracellular part 143 9302 7.1e-24 5.6e-22 GO:0044444 cytoplasmic part 105 6289 1.4e-18 8.5e-17 GO:0044464 cell part 176 15217 3.5e-17 1.4e-15 GO:0005623 cell 176 15217 3.5e-17 1.4e-15 GO:0005829 cytosol 32 912 2.5e-13 8.3e-12 intracellular membrane-bounded GO:0043231 102 7615 1.1e-11 3.1e-10 organelle GO:0043227 membrane-bounded organelle 102 7622 1.2e-11 3.1e-10 GO:0043229 intracellular organelle 106 8149 2.1e-11 4.6e-10 GO:0043226 organelle 106 8155 2.2e-11 4.6e-10 GO:0009536 plastid 53 2965 4.6e-10 9e-09 GO:0009507 chloroplast 50 2740 8e-10 1.5e-08 GO:0009570 chloroplast stroma 12 249 3.9e-07 6.5e-06 GO:0009532 plastid stroma 13 322 8.6e-07 1.4e-05 GO:0044435 plastid part 20 867 5.6e-06 8.2e-05 GO:0044434 chloroplast part 18 746 9.2e-06 0.00013 GO:0005886 plasma membrane 25 1456 5.3e-05 0.00069 GO:0019898 extrinsic to membrane 5 104 0.0011 0.012 GO:0005634 nucleus 33 2621 0.001 0.012 GO:0044422 organelle part 32 2562 0.0014 0.015 GO:0044446 intracellular organelle part 32 2561 0.0014 0.015
230 Appendices
Appendix E-Table 3. Biological pathways involving Arabidopsis proteins interacting with TlOsm, OsOlp1_A, and OsOlp1_I on the chip
Corrected Total Common TlOsm& TlOsm& TlOsm Pathway name Database Background # P-value P-value input interactors OsOlp1_A OsOlp1_I only KEGG Fructose and mannose metabolism PATHWAY 62 0.001807659 0.030085886 8 6 1 1 KEGG Glycolysis / Gluconeogenesis PATHWAY 113 0.002229822 0.034706772 11 9 1 1 KEGG Pentose phosphate pathway PATHWAY 54 0.003376058 0.044337143 7 5 1 1 benzoate biosynthesis II (CoA-independent, non-beta-oxidative) BioCyc 6 0.005177588 0.057639239 3 2 1 alkane oxidation BioCyc 6 0.005177588 0.057639239 3 2 1 KEGG Riboflavin metabolism PATHWAY 9 0.00592447 0.064514323 3 1 2 Superpathway of lysine, threonine and methionine biosynthesis II BioCyc 24 0.00665369 0.068200322 5 4 1 fatty acid alpha-oxidation I BioCyc 7 0.007168357 0.069884258 3 2 1 KEGG Flavonoid biosynthesis PATHWAY 21 0.007924232 0.07136007 4 2 1 1 ethanol degradation II BioCyc 16 0.008811526 0.075114605 4 3 1 glycolysis I (from glucose 6-phosphate) BioCyc 35 0.006901122 0.076117908 6 5 1 glycolysis II (from fructose 6-phosphate) BioCyc 36 0.007775099 0.082289863 6 5 1 Flavin biosynthesis I (bacteria and plants) BioCyc 9 0.012346065 0.105886406 3 3 methionine biosynthesis II BioCyc 9 0.012346065 0.105886406 3 2 1 ascorbate glutathione cycle BioCyc 10 0.015557855 0.127946865 3 3 flavonoid biosynthesis (in equisetum) BioCyc 11 0.019195197 0.145347416 3 2 1 glycolysis IV (plant cytosol) BioCyc 33 0.020709096 0.15286884 5 4 1 KEGG Lysine biosynthesis PATHWAY 16 0.022081898 0.160394176 3 2 1
Appendices 231
Corrected Total Common TlOsm& TlOsm& TlOsm Pathway name Database Background # P-value P-value input interactors OsOlp1_A OsOlp1_I only KEGG Pyruvate metabolism PATHWAY 84 0.027680366 0.182756418 7 5 1 1 KEGG Histidine metabolism PATHWAY 18 0.028907404 0.187833448 3 3 KEGG Biosynthesis of amino acids PATHWAY 255 0.029160885 0.187833448 15 9 2 3 1 benzoate biosynthesis III (CoA-dependent, non-beta-oxidative) BioCyc 14 0.032681584 0.201976993 3 3 1 Cadherin signalling pathway PANTHER 8 0.034603115 0.209236822 2 1 1 KEGG alpha-Linolenic acid metabolism PATHWAY 36 0.039294669 0.22935534 4 4 Superpathway of scopoline and esculin biosynthesis BioCyc 6 0.04211016 0.239956538 2 2 KEGG beta-Alanine metabolism PATHWAY 40 0.05286024 0.276816399 2 1 1 KEGG Fatty acid degradation PATHWAY 41 0.056602026 0.28832729 4 3 1 KEGG Ascorbate and aldarate metabolism PATHWAY 41 0.056602026 0.28832729 4 3 1 KEGG Plant-pathogen interaction PATHWAY 167 0.061264381 0.302898309 10 7 1 1 1 Flavonoid biosynthesis BioCyc 19 0.063499324 0.30869623 3 2 1 lipid-dependent phytate biosynthesis II (via Ins(1,3,4)P3) BioCyc 8 0.064035815 0.30869623 2 2 1D-myo-inositol hexakisphosphate biosynthesis V (from Ins(1,3,4)P3) BioCyc 8 0.064035815 0.30869623 2 2 S-adenosyl-L-methionine cycle II BioCyc 8 0.064035815 0.30869623 2 1 1 Superpathway of lipid-dependent phytate biosynthesis BioCyc 8 0.064035815 0.30869623 2 2
232 Appendices
Corrected Total Common TlOsm& TlOsm& TlOsm Pathway name Database Background # P-value P-value input interactors OsOlp1_A OsOlp1_I only KEGG Lysine degradation PATHWAY 26 0.065834464 0.314396972 3 2 1 Scopoletin biosynthesis BioCyc 9 0.076143099 0.342777218 2 1 1 Superpathway of cytosolic glycolysis (plants), pyruvate dehydrogenase and TCA cycle BioCyc 65 0.078189891 0.342777218 6 5 1 1D-myo-inositol hexakisphosphate biosynthesis III (Spirodela polyrrhiza) BioCyc 10 0.088902506 0.36456647 2 2 KEGG Cysteine and methionine metabolism PATHWAY 112 0.090683373 0.36456647 7 6 1 Nicotinic acetylcholine receptor signalling pathway PANTHER 15 0.092032736 0.36456647 2 1 1 KEGG Vitamin B6 metabolism PATHWAY 14 0.09279216 0.36456647 2 2 KEGG Biosynthesis of secondary metabolites PATHWAY 1078 0.100706063 0.382137455 44 32 4 4 4 isoleucine biosynthesis I BioCyc 11 0.102237897 0.383882929 2 1 1 Cytoskeletal regulation by Rho GTPase PANTHER 17 0.111594485 0.397437137 2 1 1 KEGG Arginine and proline metabolism PATHWAY 53 0.111874251 0.397591154 4 2 2 KEGG Galactose metabolism PATHWAY 55 0.122804217 0.414525879 4 3 1 KEGG Arachidonic acid metabolism PATHWAY 17 0.124246464 0.416833101 2 2 Superpathway of carotenoid biosynthesis BioCyc 13 0.130357842 0.416833101 2 1 1 Inflammation mediated by chemokine and cytokine signalling pathway PANTHER 19 0.132177023 0.418436113 2 1 1 KEGG Selenocompound metabolism PATHWAY 18 0.135232671 0.42650304 2 1 1 jasmonic acid biosynthesis BioCyc 14 0.145014999 0.439225609 2 2
Appendices 233
Corrected Total Common TlOsm& TlOsm& TlOsm Pathway name Database Background # P-value P-value input interactors OsOlp1_A OsOlp1_I only UTP and CTP de novo biosynthesis BioCyc 14 0.145014999 0.439225609 2 2 lysine biosynthesis VI BioCyc 14 0.145014999 0.439225609 2 2 KEGG Phenylpropanoid biosynthesis PATHWAY 157 0.165525664 0.46863376 8 4 1 1 2 Ascorbate degradation PANTHER 5 0.170984761 0.475083277 1 1 Threonine biosynthesis PANTHER 5 0.170984761 0.475083277 1 1 Suberin monomers biosynthesis BioCyc 17 0.190702417 0.499880597 2 1 1 Chlorogenic acid biosynthesis I BioCyc 17 0.190702417 0.499880597 2 1 1 KEGG Valine, leucine and isoleucine degradation PATHWAY 45 0.201916898 0.507357707 3 2 1 tetrahydrofolate biosynthesis II BioCyc 18 0.206339756 0.514624822 2 2 pyridine nucleotide cycling (plants) BioCyc 18 0.206339756 0.514624822 2 2 KEGG Carbon fixation in photosynthetic organisms PATHWAY 69 0.210092915 0.520074133 4 3 1 KEGG Tryptophan metabolism PATHWAY 46 0.210328205 0.520074133 3 2 1 pyrimidine ribonucleotides interconversion BioCyc 19 0.222108279 0.534507078 2 2 Superpathway of pyrimidine ribonucleotides de novo biosynthesis BioCyc 19 0.222108279 0.534507078 2 2 tetrahydrofolate salvage from 5,10- methenyltetrahydrofolate BioCyc 5 0.228521799 0.541812616 1 1 chlorophyll a degradation II BioCyc 5 0.228521799 0.541812616 1 1 KEGG Glycine, serine and threonine metabolism PATHWAY 72 0.23071846 0.54525558 4 3 1 Superpathway of pyrimidine deoxyribonucleoside salvage BioCyc 20 0.237969174 0.551000251 2 2 Superpathway of pyrimidine nucleobases salvage BioCyc 20 0.237969174 0.551000251 2 2
234 Appendices
Corrected Total Common TlOsm& TlOsm& TlOsm Pathway name Database Background # P-value P-value input interactors OsOlp1_A OsOlp1_I only KEGG 2-Oxocarboxylic acid metabolism PATHWAY 74 0.244737889 0.55222066 4 2 2 Lysine biosynthesis PANTHER 8 0.245706526 0.553663097 1 1 lipid-dependent phytate biosynthesis I (via Ins(1,4,5)P3) BioCyc 6 0.261196586 0.574062471 1 1 L-ascorbate degradation V BioCyc 6 0.261196586 0.574062471 1 1 6-hydroxymethyl-dihydropterin diphosphate biosynthesis I BioCyc 6 0.261196586 0.574062471 1 1 fatty acid beta-oxidation II (peroxisome) BioCyc 6 0.261196586 0.574062471 1 1 phosphatidylethanolamine biosynthesis II BioCyc 6 0.261196586 0.574062471 1 1 ornithine biosynthesis BioCyc 6 0.261196586 0.574062471 1 1 glycine biosynthesis BioCyc 6 0.261196586 0.574062471 1 1 glycine biosynthesis I BioCyc 6 0.261196586 0.574062471 1 1 valine biosynthesis BioCyc 6 0.261196586 0.574062471 1 1 KEGG Glycerolipid metabolism PATHWAY 52 0.262157573 0.574559167 3 2 1 KEGG Carbon metabolism PATHWAY 262 0.269106152 0.578339595 11 8 1 2 folate transformations II BioCyc 22 0.269827732 0.578339595 2 2 gluconeogenesis III BioCyc 22 0.269827732 0.578339595 2 2 Calvin-Benson-Bassham cycle BioCyc 23 0.285762125 0.592274165 2 2 Threonine biosynthesis BioCyc 7 0.292494646 0.599614025 1 1 De novo pyrimidine deoxyribonucleotide biosynthesis PANTHER 10 0.291926253 0.599614025 1 1 chlorophyll a degradation I BioCyc 7 0.292494646 0.599614025 1 1 Superpathway of isoleucine and valine biosynthesis BioCyc 7 0.292494646 0.599614025 1 1
Appendices 235
Corrected Total Common TlOsm& TlOsm& TlOsm Pathway name Database Background # P-value P-value input interactors OsOlp1_A OsOlp1_I only adenosine deoxyribonucleotides de novo biosynthesis BioCyc 7 0.292494646 0.599614025 1 1 KEGG RNA degradation PATHWAY 111 0.321089203 0.625956429 5 4 1 KEGG Protein processing in endoplasmic reticulum PATHWAY 220 0.32212958 0.625956429 9 8 1 arginine biosynthesis II (acetyl cycle) BioCyc 8 0.322473687 0.625956429 1 1 arginine biosynthesis I (via L-ornithine) BioCyc 8 0.322473687 0.625956429 1 1 quercetin sulfate biosynthesis BioCyc 8 0.322473687 0.625956429 1 1 purine deoxyribonucleosides salvage BioCyc 8 0.322473687 0.625956429 1 1 leucine biosynthesis BioCyc 8 0.322473687 0.625956429 1 1 Superpathway of flavones and derivatives biosynthesis BioCyc 8 0.322473687 0.625956429 1 1 pyrimidine deoxyribonucleotide phosphorylation BioCyc 8 0.322473687 0.625956429 1 1 guanosine deoxyribonucleotides de novo biosynthesis I BioCyc 8 0.322473687 0.625956429 1 1 Huntington disease PANTHER 36 0.326912931 0.630930697 3 2 1 Superpathway of adenosine nucleotides de novo biosynthesis I BioCyc 27 0.348910807 0.656061596 2 2 sucrose biosynthesis I (from photosynthesis) BioCyc 27 0.348910807 0.656061596 2 2 CMP phosphorylation BioCyc 9 0.351189006 0.656668495 1 1 glutathione redox reactions I BioCyc 9 0.351189006 0.656668495 1 1 choline biosynthesis I BioCyc 9 0.351189006 0.656668495 1 1 sporopollenin precursor biosynthesis BioCyc 9 0.351189006 0.656668495 1 1 Serine glycine biosynthesis PANTHER 13 0.356255455 0.660270583 1 1 De novo pyrimidine ribonucleotides biosythesis PANTHER 13 0.356255455 0.660270583 1 1
236 Appendices
Corrected Total Common TlOsm& TlOsm& TlOsm Pathway name Database Background # P-value P-value input interactors OsOlp1_A OsOlp1_I only folate polyglutamylation BioCyc 10 0.378693597 0.681962529 1 1 pyrimidine deoxyribonucleotides de novo biosynthesis II BioCyc 10 0.378693597 0.681962529 1 1 guanosine ribonucleotides de novo biosynthesis BioCyc 10 0.378693597 0.681962529 1 1 gluconeogenesis I BioCyc 29 0.379826415 0.681962529 2 2 oxygenic photosynthesis BioCyc 29 0.379826415 0.681962529 2 2 KEGG Glutathione metabolism PATHWAY 93 0.383508512 0.687289775 4 4 KEGG Monobactam biosynthesis PATHWAY 14 0.389258012 0.689507606 1 1 Superpathway of pyrimidine ribonucleosides salvage BioCyc 30 0.395056515 0.697573532 2 2 Superpathway of pyrimidine deoxyribonucleotides de novo biosynthesis BioCyc 30 0.395056515 0.697573532 2 2 KEGG Inositol phosphate metabolism PATHWAY 68 0.404005833 0.705564025 3 3 UDP-D-xylose biosynthesis BioCyc 11 0.405038241 0.705564025 1 1 linoleate biosynthesis I (plants) BioCyc 11 0.405038241 0.705564025 1 1 KEGG Phenylalanine metabolism PATHWAY 42 0.418365094 0.724275719 2 1 1 KEGG Nicotinate and nicotinamide metabolism PATHWAY 16 0.42814894 0.728385262 1 1 fatty acid activation BioCyc 12 0.430271603 0.728385262 1 1 pyrimidine deoxyribonucleosides salvage BioCyc 12 0.430271603 0.728385262 1 1 leucine degradation I BioCyc 12 0.430271603 0.728385262 1 1 photorespiration BioCyc 13 0.454440316 0.750406847 1 1
Appendices 237
Corrected Total Common TlOsm& TlOsm& TlOsm Pathway name Database Background # P-value P-value input interactors OsOlp1_A OsOlp1_I only pyrimidine deoxyribonucleotides de novo biosynthesis III BioCyc 13 0.454440316 0.750406847 1 1 Superpathway of guanosine nucleotides de novo biosynthesis I BioCyc 13 0.454440316 0.750406847 1 1 valine degradation I BioCyc 14 0.477589064 0.769728874 1 1 methionine salvage cycle II (plants) BioCyc 14 0.477589064 0.769728874 1 1 De novo purine biosynthesis PANTHER 20 0.485504949 0.776530752 1 1 Phenylpropanoid biosynthesis BioCyc 37 0.496246916 0.785570762 2 1 1 KEGG One carbon pool by folate PATHWAY 20 0.498677386 0.785872482 1 1 D-sorbitol degradation I BioCyc 15 0.499760668 0.785872482 1 1 indole glucosinolate breakdown (active in intact plant cell) BioCyc 15 0.499760668 0.785872482 1 1 Superpathway of leucine, valine, and isoleucine biosynthesis BioCyc 15 0.499760668 0.785872482 1 1 Apoptosis signalling pathway PANTHER 21 0.501824492 0.787751755 1 1 KEGG Pentose and glucuronate interconversions PATHWAY 81 0.513468972 0.796991081 3 3 Superpathway of pyrimidine deoxyribonucleotides de novo biosynthesis (E. coli) BioCyc 16 0.52099616 0.799812371 1 1 pyrimidine deoxyribonucleotides de novo biosynthesis I BioCyc 16 0.52099616 0.799812371 1 1 TCA cycle II (plants and fungi) BioCyc 16 0.52099616 0.799812371 1 1 methionine salvage cycle I (bacteria and plants) BioCyc 16 0.52099616 0.799812371 1 1 TCA cycle variation V (plant) BioCyc 17 0.541334859 0.818386623 1 1 KEGG Valine, leucine and isoleucine biosynthesis PATHWAY 23 0.545818841 0.818386623 1 1
238 Appendices
Corrected Total Common TlOsm& TlOsm& TlOsm Pathway name Database Background # P-value P-value input interactors OsOlp1_A OsOlp1_I only KEGG Pyrimidine metabolism PATHWAY 116 0.546203826 0.818386623 1 1 glutamine biosynthesis III BioCyc 18 0.560814439 0.823762097 1 1 Superpathway of purine nucleotides de novo biosynthesis I BioCyc 43 0.574017616 0.834709007 2 2 UDP-sugars interconversion BioCyc 19 0.579471002 0.841079402 1 1 KEGG Limonene and pinene degradation PATHWAY 59 0.591292242 0.850063642 2 2 adenosine ribonucleotides de novo biosynthesis BioCyc 20 0.597339138 0.853834243 1 1 sucrose degradation II (sucrose synthase) BioCyc 20 0.597339138 0.853834243 1 1 KEGG Cyanoamino acid metabolism PATHWAY 60 0.600192619 0.853936801 2 2 Stilbenoid, diarylheptanoid and gingerol KEGG biosynthesis PATHWAY 61 0.608946552 0.859056852 2 1 1 KEGG Purine metabolism PATHWAY 158 0.610161155 0.859056852 5 5 KEGG Metabolic pathways PATHWAY 1912 0.621610348 0.862567677 62 48 5 4 5 KEGG Citrate cycle (TCA cycle) PATHWAY 63 0.626015804 0.862567677 2 1 1 KEGG Carotenoid biosynthesis PATHWAY 29 0.627250698 0.863561362 1 1 salvage pathways of pyrimidine ribonucleotides BioCyc 22 0.630841327 0.864688012 1 1 Superpathway of choline biosynthesis BioCyc 22 0.630841327 0.864688012 1 1 sucrose degradation III (sucrose invertase) BioCyc 23 0.64653757 0.876475529 1 1 glutathione-mediated detoxification II BioCyc 50 0.653306645 0.878995801 2 2 glucosinolate biosynthesis from tryptophan BioCyc 24 0.661569881 0.885429116 1 1
Appendices 239
Corrected Total Common TlOsm& TlOsm& TlOsm Pathway name Database Background # P-value P-value input interactors OsOlp1_A OsOlp1_I only KEGG Phosphatidylinositol signalling system PATHWAY 68 0.666152615 0.887323729 2 2 KEGG Nucleotide excision repair PATHWAY 69 0.673751073 0.892526017 2 2 simple coumarins biosynthesis BioCyc 25 0.675966195 0.892659739 1 1 KEGG Plant hormone signal transduction PATHWAY 271 0.684924673 0.901611883 8 7 1 KEGG Arginine biosynthesis PATHWAY 35 0.694116089 0.907793402 1 1 KEGG Endocytosis PATHWAY 142 0.699385888 0.909959503 4 4 phospholipid biosynthesis II BioCyc 27 0.702956789 0.911782686 1 1 Superpathway of sucrose and starch metabolism I (non-photosynthetic tissue) BioCyc 27 0.702956789 0.911782686 1 1 KEGG Circadian rhythm - plant PATHWAY 36 0.704033922 0.912369326 1 1 KEGG Glyoxylate and dicarboxylate metabolism PATHWAY 74 0.709656175 0.913424219 2 1 1 KEGG Insulin resistance PATHWAY 37 0.713631063 0.91708271 1 1 KEGG Mismatch repair PATHWAY 39 0.731904302 0.93136346 1 1 KEGG Tyrosine metabolism PATHWAY 40 0.740600094 0.938875383 1 1 Parkinson disease PANTHER 42 0.750090206 0.944988093 1 1 KEGG Base excision repair PATHWAY 43 0.76503579 0.951202043 1 1 KEGG Porphyrin and chlorophyll metabolism PATHWAY 48 0.800766889 0.979829731 1 1 KEGG Alanine, aspartate and glutamate metabolism PATHWAY 48 0.800766889 0.979829731 1 1
240 Appendices
Corrected Total Common TlOsm& TlOsm& TlOsm Pathway name Database Background # P-value P-value input interactors OsOlp1_A OsOlp1_I only KEGG DNA replication PATHWAY 50 0.813492592 0.986465136 1 1 phosphatidylcholine acyl editing BioCyc 39 0.82387468 0.992072591 1 1 Amino sugar and nucleotide sugar KEGG metabolism PATHWAY 135 0.828235371 0.993366595 3 2 1 KEGG Protein export PATHWAY 53 0.831077338 0.994335235 1 1 KEGG Basal transcription factors PATHWAY 55 0.841871876 0.997312632 1 1 KEGG Homologous recombination PATHWAY 56 0.847008356 0.998471982 1 1 KEGG Spliceosome PATHWAY 192 0.882517299 1 4 4 aerobic respiration III (alternative oxidase pathway) BioCyc 52 0.900188299 1 1 1 KEGG RNA transport PATHWAY 169 0.920243315 1 3 3 KEGG Glycerophospholipid metabolism PATHWAY 86 0.943271383 1 1 1 KEGG Peroxisome PATHWAY 87 0.945119356 1 1 1 aerobic respiration I (cytochrome c) BioCyc 68 0.950502772 1 1 1 KEGG Starch and sucrose metabolism PATHWAY 196 0.989094977 1 2 2 KEGG Ubiquitin mediated proteolysis PATHWAY 149 0.993001023 1 1 1 KEGG Oxidative phosphorylation PATHWAY 162 0.99546225 1 1 1 KEGG Ribosome PATHWAY 355 0.999427687 1 3 3
Appendices 241
242 Appendices
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