Role of Signal Transduction in the Pathogenicity of Stagonospora Nodorum on Wheat
Role of signal transduction in the pathogenicity of Stagonospora nodorum on wheat
TAN, Kar-Chun
B.Sc. Molecular Biology (1st Class Hons.)
This thesis is presented for the degree of Doctor of Philosophy of Murdoch University 2007
“We make our luck” Words from a teacher
I. Declaration
I declare that this thesis is my own account of my research and contains as its main content work which has not previously been submitted for a degree at any tertiary education institution.
……….……...... TAN, Kar-Chun B.Sc. Murdoch (1st Class Hons.) Submission: 1st June 2007 Revised: 1st November 2007
II. Acknowledgements
First and foremost, I would like to extend my heartfelt thanks to both of my immediate supervisors in the ACNFP, Prof. Richard Oliver and Dr. Peter Solomon for taking me under their wings. You both have been excellent mentors to me since I stepped into your lab in 2001. I am grateful to both of you for giving me a chance to do some outstanding research in you lab. Also, I would like to express my sincere thanks to our collaborators for lending their time and unique expertise to assist in giving this thesis a colourful life. Prof. Harvey Millar and Dr. Joshua Heazlewood, I thank you both for helping us with the mass spec work. The valuable data that you have helped to obtain early in my PhD candidature have opened some new doors. Assoc. Prof. Robert Trengove, I thank you for your help on metabolomics and the work on the RT4557 compound. Your skills are invaluable and highly appreciated. Dr. Gordon Thompson, thank you for your advice and help on the tissue cross sectioning work. It has been a great learning experience. I can consider myself lucky to be able to stand on the shoulders of giants. Special acknowledgements to Rohan Lowe for establishing the metabolomic SOP, Dr. Judith Lichtenzveig for advice on stats, Dr. Mary Oliver for her help in proof reading this thesis, Super James for the help on the fungal genome, Kazza for you advice on plant infection assays and Lazza+Zippy+Kazza+Supa James for the gladiatorial squash games. How can I forget the luvly Amanda… Finally, I would like to extend a big thank to my family and fiancé. Big thanks to my young sister Yew Foon for constructive discussions. Dearest May, sorry for being away so long. Really appreciate that radio song dedication. Was it really for me or the free movie ticket? I guess a large part of this work is dedicated to for keeping me going. Be with you soon…
III. Gene nomenclature
Genes are shown in italics with the first letter in uppercase (eg. Abc1 ). Proteins are written in non italics with the first letter in uppercase (eg. Abc1). Deleted genes are written in full lowercase italics (eg. abc1 ).
IV. Front cover description
Top. 2D IEF/SDS PAGE overlay of Stagonospora nodorum wild type (magenta) and a
Gα subunit gene Gna1 deficient mutant (green). The red arrow indicates the location of a putative short chain dehydrogenase protein, Sch1. Bottom. False colour light microscope images of S. nodorum wild type (bottom left) and the sch1 mutant cross sectioned pycnidia (bottom right).
V. Table of contents
I. DECLARATION ...... I
II. ACKNOWLEDGEMENTS ...... II
III. GENE NOMENCLATURE ...... III
IV. FRONT COVER DESCRIPTION ...... III
V. TABLE OF CONTENTS ...... IV
VI. LIST OF FIGURES AND TABLES ...... IX
VII. ABSTRACT ...... XI
VIII. ABBREVIATIONS ...... XIII
CHAPTER 1 - GENERAL INTRODUCTION ...... 1 1.1 Signal transduction in plant pathogenic fungi ...... 2 1.1.1 Heterotrimeric G protein and cAMP signalling...... 2 1.1.2 Mitogen-activated protein kinase signalling...... 15 1.1.3 Phosphotidylinositol and calcium signalling...... 25 1.1.4 Two-component signalling...... 26 1.1.5 Genetic evidence of signal transduction effectors ...... 27 1.1.6 Biochemical evidence of signal transduction effectors ...... 33 1.2 Wheat - the cultivated cereal crop...... 34 1.3 Stagonospora nodorum , the cereal pathogen...... 37 1.3.1 Epidemiology and economical importance ...... 37 1.3.2 The infection life cycle ...... 40 1.3.3 Genetic manipulation...... 42 1.3.4 Signal transduction genes ...... 43 1.4 Fungal genome sequences and proteomics ...... 46 1.5 Project aims...... 49
CHAPTER 2 - GENERAL MATERIALS AND METHODS ...... 51 2.1 General solutions and buffers ...... 52 2.2 Media...... 54 2.3 General computational methods ...... 56 2.3.1 Image analysis ...... 56 2.3.2 In silico DNA and protein sequence analysis ...... 56 2.3.3 Statistical analysis...... 56 2.3.4 Gene content in the Stagonospora nodorum genome...... 57
2.4 Bacterial manipulation...... 57 2.4.1 Preparation of competent Escherichia coli cells ...... 57 2.4.2 Bacterial transformation ...... 58 2.5 DNA manipulation...... 58 2.5.1 Genomic DNA extraction...... 58 2.5.2 Plasmid DNA isolation...... 59 2.5.3 DNA purification and elution from agarose gel ...... 59 2.5.4 DNA cloning ...... 59 2.5.5 Restriction enzyme digestion of DNA ...... 60 2.5.6 Polymerase chain reaction (PCR) ...... 60 2.5.7 DNA electrophoresis on agarose gel...... 61 2.5.8 Southern blotting ...... 61 2.5.9 DNA probe labelling ...... 62 2.5.10 DNA probe hybridisation ...... 62 2.6 RNA manipulation...... 63 2.6.1 RNA isolation...... 63 2.6.2 First strand cDNA synthesis ...... 63 2.6.3 Quantitative real-time polymerase chain reaction (qRT-PCR)...... 64 2.7 Determination of nucleic acid concentration ...... 64 2.8 Manipulation of Stagonospora nodorum ...... 65 2.8.1 Growth and maintenance of Stagonospora nodorum ...... 65 2.8.2 Pycnidiospore isolation...... 65 2.8.3 Preparation of fungal glycerol stock ...... 65 2.8.4 Preparation of fungal protoplasts...... 65 2.8.5 Fungal transformation ...... 66 2.8.6 Fungal growth assay ...... 67 2.9 Wheat manipulation...... 68 2.9.1 Growth and maintenance of Triticum aestivum (cv. Amery) ...... 68 2.9.2 Detached leaf assay...... 68 2.9.3 Whole plant spray...... 68 2.9.4 In planta sporulation assay...... 69
CHAPTER 3 - IDENTIFICATION OF Gααα PROTEIN -REGULATED EFFECTOR PROTEINS IN STAGONOSPORA NODORUM BY PROTEOMICS ...... 70 3.1 Introduction ...... 71 3.2 Methods ...... 72 3.2.1 Fungal growth conditions and harvesting method ...... 72 3.2.2 Protein extraction and solubilisation...... 72 3.2.2.1 Soluble intracellular fraction...... 72 3.2.2.2 Soluble extracellular fraction...... 73 3.2.3 Determination of protein concentration...... 74 3.2.4 SDS polyacrylamide gel electrophoresis ...... 75 3.2.5 First dimension protein separation via IEF ...... 75 3.2.6 Second dimension protein separation via SDS-PAGE ...... 76 3.2.7 Protein visualisation ...... 76
3.2.8 Gel image acquisition and analysis ...... 76 3.2.9 LC-MS/MS analysis and database searching...... 77 3.2.10 Enzymatic assay for mannitol dehydrogenase activity ...... 78 3.2.11 Signal peptide analysis...... 79 3.2.12 Statistical analysis of transcript abundance...... 79 3.3 Results...... 80 3.3.1 The determination of extracellular pH...... 80 3.3.2 Assaying for cytoplasmic contamination in the extracellular protein fraction ...... 80 3.3.3 Comparative extracellular proteome analysis...... 80 3.3.4 Comparative intracellular proteome analysis...... 81 3.3.5 Functional classification of differentially abundant proteins...... 81 3.3.6 qRT-PCR analysis of gene expression...... 89 3.3.7 Variants of Snp3 and serine protease precursor ...... 98 3.3.8 Qa-2 is located in a putative quinate gene cluster...... 98 3.3.9 Genomic organisation of other Gna1 protein effector genes ...... 100 3.4 Discussion...... 101 3.4.1 Comparative analysis of the intracellular proteome...... 101 3.4.2 Comparative analysis of the extracellular proteome...... 101 3.4.3 Transcript analysis of putative Gna1 -regulated genes ...... 106 3.4.4 Signal peptides and sub-cellular protein localisation...... 107 3.4.5 Identification of an extracellular malate dehydrogenase...... 108 3.4.6 Nucleotide degradation ...... 108 3.4.7 Protein folding and stabilisation...... 109 3.4.8 Protein/peptide degradation ...... 110 3.4.9 Cell wall degradation ...... 112 3.4.10 Quinate metabolism ...... 113 3.4.11 Association of putative Gna1 -regulated genes in probable gene clusters? ...... 114 3.4 Conclusion ...... 115
CHAPTER 4 - IDENTIFICATION OF MITOGEN -ACTIVATED PROTEIN KINASE -REGULATED EFFECTOR PROTEINS IN STAGONOSPORA NODORUM BY PROTEOMICS ...... 117 4.1 Introduction ...... 118 4.2 Methods ...... 118 4.3 Results...... 119 4.3.1 Comparative intracellular proteome analysis...... 119 4.3.2 Functional classification of differentially abundant proteins...... 119 4.3.3 qRT-PCR analysis of gene expression...... 122 4.3.4 Genomic organisation of putative Mak2 effector genes...... 126 4.4 Discussion...... 126 4.4.1 Difficulties in isolating extracellular proteins for proteomics ...... 126 4.4.2 Gna1 and Mak2 effector co-regulation ...... 128 4.4.3 Identification of a glucose repressible protein ...... 131 4.4.4 Identification of S. nodorum mannitol dehydrogenase...... 131
4.4.5 Association of SNOG_08282.1 with a probable gene cluster?...... 132 4.5 Conclusion ...... 132
CHAPTER 5 - ANALYSIS OF A PUTATIVE SHORT -CHAIN DEHYDROGENASE GENE (SCH 1) FOR ITS ROLE IN THE PATHOGENICITY OF STAGONOSPORA NODORUM ON WHEAT ....134 5.1 Introduction ...... 135 5.2 Materials and methods ...... 136 5.2.1 Sch1 gene knockout vector construction and gene deletion ...... 136 5.2.2 2D SDS-PAGE analysis ...... 138 5.2.3 Spore germination assay...... 138 5.2.4 Osmotolerance assays...... 138 5.2.5 Protoplasting of the sch1-42 mutant...... 139 5.2.6 Microscopy analysis and basic photography ...... 139 5.2.7 Histological staining of cross-sectioned tissues ...... 139 5.2.8 Leaf clearing and viability staining...... 141 5.2.9 Preparations of biological materials for polar metabolite analysis ...... 141 5.2.10 Metabolite extraction ...... 142 5.2.11 Derivatisation of metabolites ...... 143 5.2.12 GC-MS metabolite separation and detection...... 143 5.2.12.1 Electron ionisation...... 143 5.2.12.2 Positive chemical ionisation (PCI)...... 144 5.2.13 Metabolite identification...... 145 5.2.14 Metabolite normalisation ...... 145 5.2.15 Statistical analysis for metabolomic analysis...... 146 5.2.16 Determination of the RT4557 retention index...... 147 5.3 Results...... 148 5.3.1 Identification of Sch1 from Gna1 and Mak2 -deleted strains ...... 148 5.3.2 Polypeptide sequence analysis of Sch1 ...... 148 5.3.3 Sch1 expression...... 153 5.3.4 Deletion of Sch1 ...... 153 5.3.5 Proteomic confirmation of Sch1 deletion ...... 156 5.3.6 Comparative proteomic analysis of SN15 and sch1-42 ...... 156 5.3.7 Colony morphology of the sch1 mutants ...... 160 5.3.8 Osmotolerance assays...... 164 5.3.9 Pathogenicity assays...... 167 5.3.10 Spore phenotyping assays ...... 167 5.3.11 Sporulation of the sch1 mutants ...... 171 5.3.12 Pycnidial development of the sch1 mutants ...... 171 5.3.13 Protoplasting of sch1-42 ...... 182 5.3.14 In vitro metabolomic analysis ...... 182 5.3.15 Quantification of RT4557...... 184 5.3.16 Attempts to elucidate the molecular identify of RT4557 ...... 188 5.3.17 In planta metabolomic analysis ...... 191 5.3.18 Extracellular metabolome analysis of the sch1 mutants...... 193 5.4 Discussion...... 193 5.4.1 Sch1 encodes for a putative short-chain dehydrogenase...... 193
5.4.2 sch1 mutants are affected in vegetative development in vitro ...... 194 5.4.2 sch1 mutants are affected in vegetative development in vitro ...... 195 5.4.3 Sch1 is not required for vegetative proliferation within wheat...... 196 5.4.4 Disruption in pycnidial ontogeny...... 196 5.4.5 Sch1 is required for asexual sporulation ...... 197 5.4.6 Deletion of Sch1 resulted in the accumulation of the novel intracellular metabolite RT4557...... 198 5.4.7 Alterations in the extracellular metabolome of the sch1 mutants...... 200 5.4.8 Association between secondary metabolism and sporulation? ...... 200 5.4.9 Proteomic analysis ...... 201 5.4.10 On the accumulation and possible function of RT4557 ...... 201 5.5 Conclusion ...... 203
CHAPTER 6 - GENERAL DISCUSSION ...... 204 6.1 Confirmation of gene annotation via proteomics ...... 205 6.2 Relationship between protein and transcript abundance ...... 205 6.3 Putative gene clusters in S. nodorum ...... 207 6.4 Targeted deletion of other signalling effector genes...... 208 6.5 Potential antifungal targets...... 209 6.6 Fungal signal transduction and proteomics...... 210 6.6.1 Y2H and tandem affinity purification (TAP) ...... 211 6.6.2 Phosphoproteomics...... 212 6.6.3 Sub-cellular proteomics...... 212 6.7 Overall summary...... 213
REFERENCES ...... 214
APPENDICES ...... 251
VI. List of Figures and Tables
The heterotrimeric G protein pathway (Figure 1.1) ...... 4 The amino acid sequence relationship between fungal Galpha subunits (Figure 1.2) ...... 6 Heterotrimeric G protein pathway genes in plant pathogenic fungi (Table 1.1) ...... 7 Mitogen-activated protein kinase pathways in yeast (Figure 1.3)...... 16 The amino acid sequence relationship between fungal MAPKs (Figure 1.4)...... 17 MAPK signalling genes in plant pathogenic fungi (Table 1.2) ...... 19 Wheat (Figure 1.5) ...... 35 Leading wheat producing countries (Table 1.3) ...... 36 Rainfall figure and disease prominence in Australia (Figure 1.6) ...... 38 Disease symptoms of wheat infected with Stagonospora nodorum (Figure 1.7) ...... 39 Host penetration and pycnidiation (Figure 1.8)...... 41 Rate of homologous gene recombination in S. nodorum (Table 1.4)...... 44 2D electrophoresis workflow (Figure 1.9) ...... 48 Enzymatic assay for mannitol dehydrogenase (Table 3.1)...... 82 Extracellular 2D proteome gels of SN15 and gna1-35 (Figure 3.1)...... 83 Differentially abundant extracellular protein spots of SN15 and gna1-35 (Table 3.2)...... 84 Intracellular 2D proteome gels of SN15 and gna1-35 (Figure 3.2)...... 86 Differentially abundant intracellular protein spots of SN15 and gna1-35 (Table 3.3) ...... 87 Functional classification of putative Gna1 -effector genes (Table 3.4) ...... 88 qRT-PCR analysis of genes that encode extracellular proteins (Figure 3.3)...... 91 qRT-PCR analysis of genes that encode intracellular proteins (Figure 3.4)...... 95 Gene expression profiles in planta (Figure 3.5)...... 97 MS peptide coverage of Snp3 (Figure 3.6) ...... 99 MS peptide coverage of a putative serine protease (Figure 3.7)...... 99 CipC and NmrA putative gene cluster (Table 3.5) ...... 102 SNOG_10217.1 putative gene cluster (Table 3.6) ...... 103 SNOG_13042.1 putative gene cluster (Table 3.7) ...... 104 SNOG_14370.1 putative gene cluster (Table 3.8) ...... 105 Intracellular 2D proteome gels of SN15 and mak2-65 (Figure 4.1)...... 120 Differentially abundant intracellular protein spots of SN15 and mak2-65 (Table 4.1 ...... 121 qRT-PCR analysis of genes that encode intracellular proteins (Figure 4.2)...... 123 Gene expression profiles in planta (Figure 4.3)...... 125 SNOG_08282.1 putative gene cluster (Table 4.2) ...... 127 Gna1 and Mak2 effector co-regulation (Figure 4.4) ...... 129 Sch1 knockout vector construction (Figure 5.1)...... 137 Mass spectrometry peptide coverage of Sch1 (Figure 5.2) ...... 149 Predicted motifs in Sch1 (Table 5.1)...... 150 Predicted secondary structure of Sch1 (Figure 5.3) ...... 151 BlastP analysis of Sch1 (Table 5.2) ...... 152 PCR and Southern analysis for Sch1 deletion (Figure 5.4) ...... 154 Proteomic confirmation of Sch1 deletion (Figure 5.5) ...... 155 Intracellular 2D proteome gels of SN15 and sch1-42 (Figure 5.6) ...... 157 Differentially abundant intracellular protein spots of SN15 and sch1-42 (Table 5.3)...... 158 3D imaging of spot C1 (Figure 5.7) ...... 159 Colony morphology of the sch1 mutants on agar media (Figure 5.8)...... 161 Colony diameter of the sch1 mutants on agar media (Figure 5.9) ...... 162 Morphology of the sch1 mutants in liquid culture (Figure 5.10) ...... 163 Trypan blue staining of infected wheat leaves (Figure 5.11) ...... 165 Infection assays (Figure 5.12)...... 166 Spore pellet and germination rate of the sch1 mutants (Figure 5.13)...... 168 The length of sch1-42 pycnidiospores (Table 5.4)...... 169 DIC images of pycnidiospores (Figure 5.14) ...... 169 Pycnidiospore count (Figure 5.15) ...... 170 Pycnidia size measurements in vitro (Figure 5.16)...... 172
Pycnidia size measurements in planta (Figure 5.17)...... 173 Pycnidiation pattern of the sch1 strains on wheat meal agar (Figure 5.18) ...... 174 Cross-section light microscopy analysis of sch1-42 pycnidia (Figure 5.19)...... 176 Cross-section TEM analysis of sch1-42 pycnidia (Figure 5.20)...... 178 Nuclei distribution (Figure 5.21)...... 180 Proprotoplasting of sch1-42 (Figure 5.22)...... 181 GC-MS ion chromatograms of Sch1 and sch1 strains (Figure 5.23)...... 183 Metabolite classification (Figure 5.24)...... 185 Principal component analysis (Figure 5.25)...... 186 Quantification of RT4557 (Figure 5.26) ...... 187 Fragmentation pattern of RT4557 via electron ionisation (Figure 5.27)...... 189 Positive chemical ionisation of RT4557 (Figure 5.28) ...... 190 Structural matches to RT4557 based on fragmentation profiles (Figure 5.29)...... 192 Alterations in the extracellular metabolome of the sch1 mutants (Figure 5.30)...... 194 Confirmation of gene prediction via MS-derived data (Table 6.1) ...... 206 The plasmid vector pBSK-phleo (Appendix A) ...... 252 qRT-PCR primer sequences (Appendix B)...... 253 Densitometry data of extracellular protein spots in Chapter 3 (Appendix C)...... 254 Supplementary BlastP data (Appendix D)...... 257 Densitometry analysis of intracellular protein spots in Chapters 3 and 4 (Appendix E)...... 259 Densitometry analysis of intracellular protein spots in Chapter 5 (Appendix F)...... 261 In vitro metabolomics data (Appendix G) ...... 262 The AMDIS mass spectrum format of RT4557 (Appendix H)...... 265 Peptide coverage of CipC (Appendix I)...... 266 Construction of the CipC knockout vector (Appendix J)...... 267 Peptide coverage of Sch2 (Appendix K) ...... 268 Construction of the Sch2 knockout vector (Appendix L) ...... 269 Peptide coverage of Sch3 (Appendix M) ...... 270 Construction of the Sch3 knockout vector (Appendix N) ...... 271 Peptide coverage of Nrd1 (Appendix O) ...... 272 Construction of the Nrd1 knockout construct (Appendix P)...... 274
VII. Abstract
The fungus Stagonospora nodorum is the causal agent of leaf and glume blotch disease on wheat and is an emerging model for the study of the interaction between plants and necrotrophic fungal pathogens. Signal transduction plays a critical role during infection by allowing the pathogen to sense and appropriately respond to environmental changes. The role of signal transduction in the pathogenicity of S. nodorum was analysed by the targeted inactivation of genes encoding a G α subunit
(Gna1 ) and a mitogen activated protein kinase ( Mak2 ). Strains carrying the inactivated genes were impaired in virulence and demonstrated a host of phenotypic impairments such as abolished sporulation. Therefore, it was hypothesised that Gna1 and Mak2 regulate downstream effector molecules that are critical for pathogenic development. A
2D gel based proteomic approach was used to compare the extracellular and intracellular proteomes of the wild type fungus and signalling mutants for differences in protein abundance. Tandem mass spectrometry (LC MS/MS) analysis and pattern matching against the S. nodorum genome sequence led to the identification of 26 genes from 34 differentially abundant protein spots. These genes possess probable roles in protein cycling, plant cell wall degradation, stress response, nucleotide metabolism, proteolysis, quinate and secondary metabolism. A putative short chain dehydrogenase gene ( Sch1 ) was identified and its expression was shown to be reduced in both signalling mutants. The transcript level of Sch1 increased during the latter period of infection coinciding with pycnidiation. Sch1 was inactivated by targeted gene deletion.
Mutants were able to effectively colonise the host but asexual sporulation was dramatically reduced and pycnidial ontogeny was severely disrupted. Furthermore, the sch1 mutants showed alterations in the metabolome. GC MS analysis identified a
metabolite which accumulated in the sch1 mutants. Computational and database analyses indicated that the compound possesses a cyclic carbon backbone. Based on these findings, Sch1 may be a suitable target for fungicides that inhibit asexual sporulation and the accumulated compound may be used to design novel antifungal compounds. 2D SDS PAGE analysis identified increased abundance of another putative short chain dehydrogenase ( Sch2 ) and a nitroreductase in the sch1 deleted background. It was also shown that Sch2 was regulated by Gna1 .
VIII. Abbreviations
ABC ATP binding cassette AC Adenylyl (syn. adenylate) cyclase ACNFP Australian Centre for Necrotrophic Fungal Pathogens AMDIS Automated Mass Spectral Deconvolution and Identification System ANOVA Analysis of variance BCA Bicinchoninic acid BSA Bovine serum albumin cAMP Cyclic AMP CID Collision induced dissociation DAPI 4’,6 diamido 2 phenylindole CAS Chemical abstracts service CHAPS 3 [(3 cholamidopropyl)dimethylammonio] 1 propane sulfonate Cpka Catalytic subunit of protein kinase A CS Complete supplement CzV8CS Czapek Dox V8 juice with CS (k)Da (Kilo)Dalton(s) DAG Diacylglycerol DEPC Diethyl pyrocarbonate DHN Dihydroxynapththalene DIC Differential interference contrast DLA Detached leaf assay DNase Deoxyribonuclease DOPA Dihydroxphenylalanine DTT Dithiothreitol EDTA Ethylenediaminetetraacetic acid ER Endoplasmic reticulum ESI Electrospray ionisation EST Expressed sequence tag F Faraday FPP Farnesyldiphosphate g Centrifugal force g Gram GABA γ aminobutyrate (syn. γ aminobutyric acid) GC-MS Gas chromatograph mass spectrometry GPCR G protein coupled receptor GST Glutathione S transferase h Hour(s) HCA Hierarchical component analysis HK Histidine kinase HMM Hidden Markov model ICAT Isotope coded affinity tags IP 3 Inositol 1,4,5 trisphosphate IPG Immobilised pH gradient IPTG β D 1 thiogalactopyranoside J Joule(s)
LC-MS/MS High performance liquid chromatography tandem mass spectrometry MALDI-ToF Matrix assisted laser desorption/ionisation time of flight MAPK Mitogen activated protein kinase MAPKK Mitogen activated protein kinase kinase MAPKKK Mitogen activated protein kinase kinase kinase MM Minimal medium MS Mass spectrometer MSS Multiple surfactant solution MST Mass spectral tag MW Molecular weight m/z Mass to charge NIST National Institute of Standards and Technology NN Neural network NRPS Non ribosomal peptide synthetase Ohm OD Optical density ORF Open reading frame PCA Principal component analysis PCI Positive chemical ionisation PCR Polymerase chain reaction PKA Protein kinase A PKC Protein kinase C PKS Polyketide synthase PMSF Phenylmethylsulfonyl fluoride PPI Peptidylprolyl isomerase RGS Regulator of G protein signalling RNase Ribonuclease RT Retention time s Second(s) SAGE Serial analysis of gene expression SDS Sodium dodecyl sulphate SDS-PAGE SDS polyacrylamide gel electrophoresis SE Standard error SSH Suppression subtractive hybridisation TAE Tris, acetic acid, EDTA TAP Tandem affinity purification TCA Trichloroacetic acid TMS Trimethylsilyl or transmethylsilylation UTR Untranslated region V Volt(s) X-Gal 5 bromo 4 chloro 3 indoyl β D galactoside Y2H Yeast two hybrid
Chapter 1 - General introduction
Chapter 1
1.1 Signal transduction in plant pathogenic fungi
Signal transduction in plant pathogenic fungi has received considerable attention for its possible roles in the perception of host and environmental signals (Bahn et al. ,
2007; Kronstad, 2000). These signals can influence fungal spore germination (Bagga &
Straney, 2000; Blakeman, 1975; Chaky et al. , 2001) penetration/proliferation
(Beckerman & Ebbole, 1996; Emmett & Parberry, 1975; Grambow, 1977; Nierman et al. , 2005) and sporulation (Kihara et al. , 2007; Lee et al. , 2006). Perceived signals are transduced within the fungus via an intricate intracellular signalling network to elicit a metabolic, developmental or a pathogenic response (Bagga & Straney, 2000; DeZwaan et al. , 1999; Klose et al. , 2004).
Intense research during the past decade has uncovered a number of signalling pathways critical for development and pathogenicity. The heterotrimeric G protein pathway utilises cyclic AMP (cAMP) as a secondary intracellular messenger to regulate effector function. The mitogen activated protein kinase cascade undergoes a series of protein phosphorylation events for signal amplification and transduction. Evidence of phosphotidylinositol/Ca 2+ and two component signalling involvement in fungal phytopathogenicity has surfaced just recently (Section 1.1.3). This Chapter will attempt to provide a summary linking some previous and recent findings on the regulation of development and virulence in fungi.
1.1.1 Heterotrimeric G protein and cAMP signalling
The heterotrimeric G protein family is a universal eukaryotic signalling component. The heterotrimer consists of the α, β, and γ subunits. Heterotrimeric G
2 Chapter 1
proteins are coupled to the cytoplasmic side of a membrane bound G protein coupled receptor (GPCR) (Figure 1.1). The heterotrimer is activated by the interaction of an extracellular ligand with the GPCR, triggering a conformational change within the βγ subunits. This causes the displacement of GDP by GTP on the G α subunit resulting in its release from the parental trimer. As a result, the G α and G βγ subunits can interact with intracellular effectors such as phosphodiesterase, phospholipases, adenylyl cyclase
(AC) and ion channels (Simon et al. , 1991). Once the ligand is no longer present, an intrinsic GTPase located within the G α subunit catalyses GTP hydrolysis. GTPase activity is promoted by a family of GTPase activating protein known as regulator of G protein signalling (RGS) (Ross & Wilkie, 2000). This permits the reassociation of the
α subunit with the βγ heterodimer (Pennington, 1994). Two of the most commonly studied Gα families are the stimulatory (G αs) and inhibitory (G αi) families. The G αs family is known to activate AC thus resulting in the production of a secondary messenger molecule cAMP from ATP. The G αi family prevents the activation of adenylyl cyclase. cAMP interacts with downstream components such as protein kinase
A (PKA). PKA is composed of two catalytic and two regulatory subunits. The catalytic subunits are active when cAMP interacts with the regulatory subunits causing molecular dissociation. Traditionally, G α proteins have been viewed as the “business end” of a heterotrimeric G protein because it binds to GTP and interacts with effectors whereas the G βγ function as regulatory subunits (Helper & Gilman, 1992). However, a growing body of evidence suggests that free G βγ subunits possess independent effector regulating functions (Helper & Gilman, 1992; Nishimura et al. , 2003; Schwindinger &
Robishaw, 2001).
3 Chapter 1
Figure 1.1. An illustration of the heterotrimeric G protein signalling pathway in
eukaryotes. Diagram adapted from Borkovich (1996).
1The heterotrimeric G protein pathway (Figure 1.1)
Figure 1.1. An illustration of the heterotrimeric G protein signalling pathway in eukaryotes. Diagram adapted from Borkovich (1996).
4 Chapter 1
The first report a G α subunit gene cloned in a filamentous fungus was in N. crassa (Turner & Borkovich, 1993). To date, three G α subunit genes ( Gna1 to 3) have been reported and characterised in N. crassa . Mutation in Gna1 caused a reduction in vegetative growth, increased sensitivity to osmotic stress, abberent conidiation and defective mating (Ivey et al. , 1996). The deletion of the second G α subunit gene Gna2 did not produce any obvious defects in N. crassa . However, when introduced into a gna1 background, the double mutation accentuated the gna1 mutant phenotype and thus suggests overlapping functions (Baasiri et al. , 1997). Mutation of a third G α subunit gene Gna3 led to excess conidiation which was reversed by the addition of cAMP
(Kays et al. , 2000). It is evident that G α protein signalling plays a major role in developmental regulation in N. crassa . From here, questions arise on the role of G α protein signalling in plant pathogenic fungi.
Bolker (1998) devised a classification scheme that places fungal G α proteins into three major classes based on amino acid sequence similarities (Figure 1.2). Other components of the heterotrimeric G protein pathway were also subjected to pathogenicity studies. This includes the G β subunit, AC, PKA, Ras and RGS. A summary of published studies describing components of the heterotrimeric G protein pathway in plant pathogenic fungi is listed in Table 1.1. Depending on the fungus, the deletion of genes encoding components of the pathway often result in reduced fitness in conidiation, spore germination, asexual reproduction, formation of penetration structure, vegetative growth, pigmentation and virulence. A brief discussion on the role
5 Chapter 1
Figure 1.2. Phylogram showing the amino acid sequence relationship of GUmGpa4 α subunits
UmGpa2 reported from Neurospora crassa and plant pathogenic fungi using TREEVIEW. Prefix BcBcg2 abbreviation of species; Nc, Neurospora crassaNcGna2; Um, Ustilago maydis ; Bc, Botrytis II RnRga3 cinerea ; Rn, Rosellinia necatrix ; Cp, Cryphonectria parasitica ; Mg, Magnaporthe CpCpg3 grisea ; Fo, Fusarium oxysporum ; Uh, UstilagoMgMagC hordei ; Ch, Cochliobolus
Bcg3 heterostrophus , Aa, Alternaria alternata ; Ct, Colletotrichum trifolii . Gpa4 is an unusual RnRga1
Gα protein and has been used as an outgroup. The barNcGna3 indicates the relative measure of FoFga2 III the distance in the phylogenetic tree as given by CLUSTALW. CpCpg2
MgMagA
UhFil1 UmGpa3
2The amino acid sequence relationship between fungaUmGpa1l Galpha subunits (Figure 1.2)
ChCga1
AaAga1
SnGna1
BcBcg1 I NcGna1
CpCpg1
MgMagB
RnRga2
FoFga1
CtCtg1 0.1
Figure 1.2. Phylogram showing the amino acid sequence relationship of G α subunits reported from Neurospora crassa and plant pathogenic fungi using TREEVIEW. Prefix abbreviation of species; Nc, Neurospora crassa ; Um, Ustilago maydis ; Bc, Botrytis cinerea ; Rn, Rosellinia necatrix ; Cp, Cryphonectria parasitica ; Mg, Magnaporthe grisea ; Fo, Fusarium oxysporum ; Uh, Ustilago hordei ; Ch, Cochliobolus heterostrophus , Aa, Alternaria alternata; Ct, Colletotrichum trifolii . Gpa4 is an unusual G α protein and has been used as an outgroup. The bar indicates the relative measure of the distance in the phylogenetic tree as given by CLUSTALW.
6 Chapter 1 Table 1.1. Heterotrimeric G protein pathway genes reported in plant pathogenic fungi. Continued on the next page.
3Heterotrimeric G protein pathway genes in plant pathogenic fungi (Table 1.1) S. nodorum Gna1 (Solomon et al. , 2004b) TableA. alternate 1.1. Heterotrimeric G protein pathway genes reported i Aga1 (Yamagishi et al. , 2006) n plant pathogenic fungi. Continued on the next page.
Organism Gene Genbank acc Gene family Function Reference Stagonospora nodorum Gna1 AY327542 Gα protein (Class I) Pycnidiation, extracellular protease secretion, DOPA Solomon et al. (2004b) metabolism and virulence Alternaria alternata Aga1 BAE71312 Gα protein (Class I) Conidial germ tube formation and virulence Yamagishi et al. (2006) Aspergillus niger PkaC CAA64172 Cat PKA subunit Overexpression caused hypersporulation and Bencina et al. (1997) alteration in vegetative growth Blumeria graminis f. sp. Bka1 CAB61490 Cat PKA subunit Complementation of M. grisea cpka mutant defects Bindslev et al. (2001) hordei Botrytis cinerea Bcg1 CAC19871 Gα protein (Class I) Vegetative growth, conidiation, extracellular Gronover et al. (2001) protease secretion and virulence Bcg2 CAC19872 Gα protein (Class II) Virulence Gronover et al. (2001) Bcg3 BAD93277 Gα protein (Class Conidiation, conidia germination and virulence Doehlemann et al. III) (2006) Bcgb1 BAD93278 Gβ protein Unknown Osada et al. (2005) Bac CAB77164 Adenylyl cyclase Vegetative growth, conidiation and virulence Klimpel et al. (2002) Cochliobolus Cga1 AAC23576 Gα protein (Class I) Appressorium formation and female fertility Horwitz et al. (1999) heterostrophus Cgb1 AAO25585 Gβ protein Vegetative growth, appressorium formation, female Ganem et al. (2004) fertility, pigmentation and virulence Colletotrichum lagenarium Rpk1 AAK31209 Reg PKA subunit Vegetative growth, conidiation, appressorial Takano et al. (2001) penetration hyphae and virulence Cpk1 Q9C1C2 Cat PKA subunit Appressorial penetration, conidia germination, lipid Yamauchi et al. metabolism and virulence (2004) Cac1 BAD04045 Adenylyl cyclase Appressorial penetration, conidia germination, lipid Yamauchi et al. metabolism and virulence (2004) Colletotrichum trifolii Ctg1 AAC03782 Gα protein (Class I) Vegetative growth, conidia germination and Truesdell et al. (1999) virulence CtpkaC AAC04355 Cat PKA subunit Host penetration and virulence Yang & Dickman (1999a) CtPkaR AAC04356 Reg PKA subunit Unknown Yang & Dickman (1999b)
7 Chapter 1 B. gra minis Bka1 (Bindslev et al. , 2001) B. cinerea Bcg1 (Gronover et al. , 2001) Table 1.1. Continued from the previous page. Bcg2 (Gronover et al. , 2001) Organism Gene Genbank acc Gene family Function Reference Cryphonectria parasitica Cpg1 AAA67706 Gα protein (Class I) Colony morphology, female fertility, pigmentation, Gao & Nuss (1996); hydrophobin synthesis and virulence Segers & Nuss (2003) Cpg2 AAA67707 Gα protein (Class III) Vegetative growth and conidiation Gao & Nuss (1996) Cpg3 AAM14395 Gα protein (Class II) Unknown Parsley et al. (2003) Cpgb1 AAC49838 Gβ protein Vegetative growth, female fertility, pigmentation and Kasahara & Nuss virulence (1997) Bdm1 AAF26212 Phosducin Vegetative growth, female fertility, pigmentation and Kasahara et al. (2000) virulence Cprgs1 AAT92283 RGS Vegetative growth, pigmentation, hydrophobin Segers et al. (2004) synthesis and virulence Fusarium oxysporum Fga1 BAB69488 Gα protein (Class I) Conidiation, heat resistance and virulence Jain et al. (2002) Fga2 BAD44729 Gα protein (Class III) Heat resistance and virulence Jain et al. (2005) Fgb1 BAB69489 Gβ protein Vegetative growth, conidiation, conidia germination, Jain et al. (2003); extracellular protease secretion, heat resistance and Prados Rosales et al. virulence. (2006) Magnaporthe grisea Pth11 AAD30438 Membrane protein Appressorium formation and virulence DeZwaan et al. (1999) MagA AAB65425 Gα protein (Class III) Asci formation Liu & Dean (1997) MagB AAB65426 Gα protein (Class I) Vegetative growth, conidiation, appressorium Liu & Dean (1997) formation, female fertility and virulence MagC AAB65427 Gα protein (Class II) Conidiation and asci formation Liu & Dean (1997) Mgb1 BAC01165 Gβ protein Vegetative growth, conidiation, appressorium Nishimura et al. formation and virulence (2003) Mac1 AAB66482 Adenylyl cyclase Vegetative growth, conidiation, appressorium Choi & Dean (1997) formation, female fertility and virulence Sum1 AAC34140 Reg PKA sununit Restore growth, appressorium formation sexual and Adachi & Hamer (1998) asexual morphopgenesis in mac1 mutants Cpka AAA93199 Cat PKA subunit Appressorium formation, penetration, lipid Mitchell & Dean mobilisation and virulence (1995); Xu et al. (1997); Thines et al. (2000) Rgs1 ABC60049 RGS Appressorium formation, negatively regulates Liu et al. (2007) MagA, MagB and MagC, hyperconidiation in rga1 mutants.
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Table 1.1. Continued from the previous page.
Organism Gene Genbank acc Gene family Function Reference Mycosphaerella MgTpk2 ABD92791 Cat PKA subunit Deletion increased melanisation. Vegetative growth, Mehrabi & Kema graminicola pycnidiation in planta and virulence (2006) MgBcy1 ABD92792 Reg PKA subunit Deletion reduced melanisation. Vegetative growth, Mehrabi & Kema osmotolerance, pycnidiation in planta and virulence (2006) Rosellinia necatrix Rga1 BAB20821 Gα protein (Class III) Unknown Aimi et al. (2001) Rga2 BAB20820 Gα protein (Class I) Unknown Aimi et al. (2001) Rga3 BAB20819 Gα protein (Class II) Unknown Aimi et al. (2001) Sclerotinia sclerotiorum Pka1 AY545583 Cat PKA subunit No detectable phenotype Jurick et al. (2004) Ustilago hordei Fil1 AAC49880 Gα protein (Class III) Filamentous growth, dimorphic switching of haploid Lichter & Mills (1997) cells and pigmentation Lichter & Mills (1998) Ustilago maydis Gpa1 UM05123 Gα protein (Class I) No detectable phenotype Regenfelder et al. (1997) Gpa2 UM02517 Gα protein (Class II) No detectable phenotype Regenfelder et al. (1997) Gpa3 UM04474 Gα protein (Class III) Constitutive filamentation of mutants, pheromone Regenfelder et al. response, sexual dimorphism and virulence (1997) Gpa4 UM05385 Gα protein (Class IV) No detectable phenotype Regenfelder et al. (1997) Bpp1 AAN33051 Gβ protein Constitutive filamentation of mutants, pheromone Muller et al. (2004) response and sexual dimorphism Uac1 P49605 Adenylyl cyclase Constitutive filamentation of mutants and virulence Gold et al. (1994); Kruger et al. (1998) Ubc1 AAA57470 Reg PKA subunit Mutants showed multiple budding phenotype, Gold et al. (1994); fungicide resistance and non tumor inducing Ramesh et al. (2001) phenotype Uka1 AAC24243 Cat PKA subunit No detectable phenotype Durrenberger et al. (1998) Adr1 AAC24242 Cat PKA subunit Constitutive filamentation of mutants and virulence Durrenberger et al. (1998) Ras2 AAO19639 Ras G protein Suppressor of adr1 mutation, regulator of Kpp2 Lee & Kronstad (2002); signalling, cell morphology and virulence Muller et al. (2003a) Sql1 AF268097 Transcriptional Antagonise cAMP signalling Loubradou et al. (2001) repressor Hgl1 AF274314 Substrate for PKA Suppressor of the adr1 phenotype. Pigmentation and Durrenberger et al. teliospore formation. (2001)
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of heterotrimeric G protein signalling in virulence and development of plant pathogenic fungi is provided below.
In the corn smut fungus Ustilago maydis , the process of mating requires the fusion of haploid cells to form an infective dikaryotic hyphae that is regulated by heterotrimeric G protein and mitogen activated protein kinase signalling (Feldbrugge et al. , 2004). Genetic evidence suggests that these two pathways regulate the expression of genes in the a and b mating loci. The a locus contains the pheromone ( Mfa1/2 ) and receptor ( Pra1/2 ) genes required for mating recognition whereas the b locus encodes two proteins which form an active heterodimeric transcription factor (bE/ bW) after hyphal fusion (Feldbrugge et al. , 2004). Both pathways converged downstream to regulate 1. Crk1 , a novel MAPK gene required for filamentation, mating and virulence
(Garrido et al. , 2004) and 2. Prf1 , the transcription factor gene require to promote the expression of a and b genes (Kaffarnik et al. , 2003). The heterotrimeric G protein pathway plays an important role in morphogenesis (Feldbrugge et al. , 2004). The deletion of the Uac1 adenylyl cyclase gene resulted in a constitutive filamentous phenotype (Gold et al. , 1994), abolished response to pheromone and hence resulted in mating deficiencies and abolished pathogenicity (Gold et al. , 1994; Kruger et al. , 1998).
The addition of cAMP restored the budding phenotype (Gold et al. , 1994). Suppressor mutation of the Ubc1 PKA regulatory subunit gene restored budding growth to the uac1 mutant (Gold et al. , 1994). Deletion of Ubc1 alone resulted in a multiple budding phenotype and resistance to certain fungicides (Gold et al. , 1994; Ramesh et al. , 2001).
Two PKA catalytic subunit genes, Adr1 and Uka1 were identified and characterised by
Durrenberger et al. (1998). The deletion of Uka1 did not produce a noticeable
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phenotype but adr1 mutants showed a similar phenotype to the uac1 mutant.
Furthermore, PKA assays suggests that Adr1 is the likely partner for Ubc1
(Durrenberger et al. , 1998). Regenfelder et al. (1997) identified and disrupted four G α subunit genes ( Gpa1 to 4). Normally, G α subunits will range from 350 to 380 amino acids in length (Birnbaumer, 1992). The predicted size of Gpa1 to 3 is consistent to the proposed figure. However, Gpa4 encodes a predicted 580 amino acid polypeptide.
Deletion of Gpa1 , 2 and 4 did not produce a noticeable phenotype. However, gpa3 mutants were non pathogenic, unable to mate and showed constitutive filamentation in a haploid strain (Regenfelder et al. , 1997). The G β subunit Bpp1 was identified as a epistatic partner for Gpa3 but interestingly is dispensible for pathogenicity (Muller et al. , 2004). Kruger et al. (1998) proposed that Gpa3 acts upstream to Uac1 based on evidence derived from two experiments: 1. the gpa3 mutant responded to cAMP and 2.
Uac1 deletion in a constitutively active Gpa3 background resulted in phenotypes indistinguishable from uac1 mutants (Kruger et al. , 1998).
The heterotrimeric G protein/cAMP pathway of the rice blast fungus
Magnaporthe grisea is well characterised for its role in appressorium morphogenesis and sexual development. Pth11 encodes a predicted membrane protein originally identified through a screen for defective mutants generated via restriction enzyme mediated integration (DeZwaan et al. , 1999). pth11 mutants can form appressoria but at a reduced frequency compared to the wild type. Mutants were also less pathogenic.
These defects can be overcome by exogenous cAMP and this suggests that Pth11 may function upstream of the intracellular cAMP pathway (DeZwaan et al. , 1999). Three
Gα subunit genes were identified and characterised via gene deletion by Liu & Dean
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(1997). The deletion of MagC and MagA that code for Class II and III G α subunits, respectively, resulted in defects in conidiation and asci maturation but were fully virulent. However, mutation in MagB (a Class I Gα subunit gene) caused a reduction in conidial attachment to hydrophobic surfaces, defective germ tube and a reduction in the ability to infect rice (Liu & Dean, 1997). Similar to pth11 mutants, magB mutants showed reduced ability to form appressoria. The addition of cAMP was able to restore appressorium formation similar to the wild type (Liu & Dean, 1997). This indicates the involvement of MagB in cAMP signalling. All three G α subunits were subjected to negative regulation by Rgs1, a RGS protein (Liu et al. , 2007). The G β subunit gene
Mgb1 was identified and cloned by Nishimura et al. (2003). Mutants carrying the Mgb1 deletion were unable to form appressoria without exogenous cAMP. In addtion, two critical pieces of evidence that further implicate Mgb1 functioning as a positive regulator of cAMP production are 1. mgb1 mutants were reduced in cAMP level and 2. strains carrying multiple copies of Mgb1 possessed higher cAMP level than the wild type (Nishimura et al. , 2003). The adenylyl cyclase Mac1 required for cAMP production downstream of the heterotrimeric G protein complex were also critical for appressorium morphogenesis (Choi & Dean, 1997). Sum1 is a regulatory PKA subunit gene identified though a screening for repressor mutation of the mac1 phenotype
(Adachi & Hamer, 1998). In the absence of cAMP, the proposed function of Sum1 was to negatively regulate the catalytic PKA subunit Cpka via physical association. The role of Cpka includes lipid mobilisation during appressorium morphogenesis, appressorium formation and virulence (Mitchell & Dean, 1995; Thines et al. , 2000).
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Three G α subunit genes have been inactivated in the gray mold fungus Botrytis cinerea . Gronover et al. (2001) inactivated Bcg1 and Bcg2 which codes for a Class I and II G α protein, respectively. The deletion of the Bcg2 has little bearing on the phenotype of the fungus but resulted in a slight reduction in virulence. In contrast, bcg1 mutants were reduced in vegetative growth, extracellular protease secretion (discussed below), loss of asexual sporulation and attenuated virulence. The addition of cAMP restored wild type morphology indicating that Bcg1 is involved in cAMP signalling
(Gronover et al. , 2001). This is further supported from evidence derived from the deletion of the AC gene Bac . Mutants showed similar phenotype to bcg1 deletants but were still capable of causing a delayed infection. In addition mutants were also reduced in intracellular cAMP level which thus far beckons an explanation as to an alternate mechanism for cAMP production (Klimpel et al. , 2002). The sequence of Bcg3
(encoding a Class III G α protein) was initially reported by Osada et al. (2005). The role of Bcg3 during infection was investigated via targeted gene deletion by Doehlemann et al. (2006). Conidia of the bcg3 mutant germinated normally on hydrophobic surfaces but germination rate was reduced in the presence of carbon sources when compared to the wild type (Doehlemann et al. , 2006). A similar defect was observed for bac mutants. The ability of the bcg3 mutant to cause infection was delayed due to reduced number of penetrations. Like bcg1 deletants, bcg3 mutants were responsive to cAMP which restored the germination and penetration defect. Therefore, it was proposed that
Bcg3 is responsible for cAMP mediated penetration and sporulation whereas Bcg1 is responsible for cAMP signalling during pathogenic growth (Doehlemann et al. , 2006).
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In the southern corn leaf blight fungus Cochliobolus heterostrophus , the Class I
Gα subunit gene Cga1 is required for female fertility. The frequency of appressorium formation was greatly reduced in cga1 mutants but retained full ability to infect corn
(Horwitz et al. , 1999). Hence, it is possible that the appressorium of C. heterostrophus is dispensible for infection (Ganem et al. , 2004). Cgb1 is the sole G β subunit gene in C. heterostrophus (Ganem et al. , 2004). The cgb1 mutants showed overlapping phenotype with cga1 mutants with the exception of reduced conidiation and inability to infect corn
(Ganem et al. , 2004). This suggests that Cgb1 can function independently of Cga1 .
Growth of young vegetative hyphae was also affected in cgb1 mutants. Mutants also showed symptoms of hyphal cell death as indicated by an increase in DNA degradation
(Ganem et al. , 2004).
Thus far, discussions on heterotrimeric G protein signalling have been focused on necrotrophic and non obligate fungi. The obligate biotroph Blumeria graminis f. sp. hordei is the causal agent of barley powdery mildew. B. graminis f. sp. hordei is able to form appressoria shortly after conidial germination. Gene expression analysis and pharmacological studies linked the cAMP pathway to conidial germination and appressorial morphogenesis in B. graminis f. sp. hordei (Hall et al. , 1999; Kinane et al. ,
2000). A consistent genetic manipulation procedure for B. graminis f. sp. hordei remains elusive. To functionally characterise signalling components in the obligate fungus, Bindslev et al. (2001) were able to introduce the powdery mildew protein kinase A catalytic subunit gene Bka1 , into a Cpka deficient mutant of M. grisea . Bka1 is an ortholog of Cpka and was able to restore defects in pathogenicity and appressoria maturation in Cpka deficient M. grisea (Bindslev et al. , 2001; Hall et al. , 1999). This
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illustrates the strong conservation of signalling components in regulating development across different classes of phytopathogenic fungi.
1.1.2 Mitogen-activated protein kinase signalling
Mitogen activated protein kinases (MAPK) are a conserved family of protein kinases found in eukaryotes. MAPKs are activated by mitogen activated protein kinase kinases (MAPKK) via phosphorylation, which in turn are activated by mitogen activated protein kinase kinase kinases (MAPKKK). MAPK cascades are implicated in the regulation of diverse cellular processes such as the cell cycle (Dangi et al. , 2006;
Torii et al. , 2006), transformation (Kennedy & Davis, 2003), cell/tissue differentiation
(Puri et al. , 2000), stress response (Jonak et al. , 1996) and immune activation (Ashwell,
2006). In baker’s yeast Saccharomyces cerevisiae , five functional MAPK cascades have been identified (Figure 1.3). Fus3 and Kss1 MAPK pathways play an overlapping role in pheromone response and mating (Elion et al. , 1990; Elion et al. , 1991). The
Kss1 pathway also regulates filamentous growth (Madhani et al. , 1997). Cellular integrity is maintained by the Slt2 pathway (Mazzoni et al. , 1993) and the Hog1 pathway is required for osmotolerance (Brewster et al. , 1993). Finally, the Smk1
MAPK pathway regulates the assembly of ascospore cell wall (Brewster et al. , 1993).
MAPKs in plant pathogenic fungi can be divided into three major groups based on amino acid sequence resemblances to yeast Fus3, Kss1, Slt2 and Hog1 MAPKs (Xu,
2000) (Figure 1.4). Furthermore, components upstream to these MAPKs also showed strong similaritites to their yeast counterparts (Table 1.2). Almost all reports indicate that the perturbation of MAPK signalling in plant pathogenic fungi resulted in
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4 Mitogen-activated protein kinase pathways in yeast (Figure 1.3)
Figure 1.3 . Simplified MAPK pathways in S. cerevisiae showing components of the five cascades regulating mating response, filamentous growth, cell integrity, osmotolerance and asexual sporulation. Modified from Xu (2000).
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ScSmk1 ScSlt2 ClCpmk2 AoMpkA ChMps1 MgSlt2 Slt2 5The amino acid sequence relationship betweenBgMpk2 fungal MAPKs (Figure 1.4) BcBmp3 MrMps1 CoMaf1 FgMgv1 ScHog1 BcSak1 MgHog1 BoSrm1 Hog1 ChHog1 CpCpmk1 CoOcs1 MrOsm1 ScFus3 ScKss1 UmKpp6 UmKpp2 MgFus3 SnMak2 AbAmk1 BoBmk1 ChChk1 BgMpk1 Fus3/Kss1 BcBmp1 SsSmk1 GgGmk1 MrPmk1 CpCpmk2 CoCmk1 VdVmk1 FgGpmk1 FoFmk1 FsMapk ClCpmk1 0.1 Figure 1.4. Phylogram showing the amino acid sequence relationship of MAPKs of Saccharomyces cerevisiae and plant pathogenic fungi using TREEVIEW. Prefix abbreviation of species; Sc, Saccharomyces cerevisiae ; Sn, Stagonospora nodorum ; Ab, Alternaria brassicicola ; Ao, Aspergillus oryzae ; Bo, Bipolaris oryzae ; Bg, Blumeria graminis ; Bc, Botrytis cinerea ; Cl, Claviceps purpurea ; Ch, Cochliobolus heterostrophus ; Co, Colletotrichum lagenarium ; Cp, Cryphonectria parasitica ; Fg, Fusarium graminearum ; Fo, Fusarium oxysporum ; Fs, Fusarium solani ; Gg, Gaeumannomyces graminis ; Mr, Magnaporthe grisea ; Mg, Mycosphaerella graminicola ; SS, Sclerotinia sclerotiorum ; Um, Ustilago maydis ; Vd, Verticillium dahliae . The Smk1 MAPK of S. cerevisiae was used as an outgroup. The bar indicates the relative measure of the distance in the phylogenetic tree as given by CLUSTALW. 17 Chapter 1
phenotypes that were compromised in development and virulence. A limited discussion on the role of MAPK signalling in development and virulence of several plant pathogenic fungi is provided below.
After the mating response in U. maydis , the MAPK pathway takes over the role of plant penetration (Feldbrugge et al. , 2004). The Fus3 like MAPK gene, Kpp6 was identified via RNA fingerprinting. The kpp6 mutants were able to mate and form appressoria but lost the ability to penetrate the host (Brachmann et al. , 2003). It was proposed that the Fuz7 MAPKK activates Kpp6 (Brachmann et al. , 2003). However fuz7 mutants were attenuated in mating, incapable of forming appressoria and conjugation tube and were non pathogenic (Banuett & Herskowitz, 1994). In fact,
Fuz7 is a component of a MAPK pathway that regulates the expression of a/b genes, appressorium and conjugation tube formation (Feldbrugge et al. , 2004). The MAPK pathway is activated by Ras2 (Lee & Kronstad, 2002) which in turn, is activated by a
CDC25 like guanyl nucleotide exchange factor Sql2 (Muller et al. , 2003a).
Components of the MAPK cascade consists of the Ubc2 (Ste50) adaptor protein,
Kpp4/Ubc4 MAPKKK, Fuz7/Ubc5 MAPKK and Kpp2/Ubc3 MAPK. The presence of
Ras interacting domains in Kpp4 and Ubc2 indicates the probable site of Ras2 activation (Mayorga & Gold, 2001). Not surprisingly, ubc2 , kpp4 and kpp2 mutants showed a similar phenotype to fuz7 except that kpp2 mutants were only reduced in virulence (Muller et al. , 1999; Muller et al. , 2003b). Double deletions of Kpp2 and
Kpp6 abolished pathogenic development whereas single gene deletion caused a reduction in virulence. This indicates that both MAPKs share partial redundant functions (Brachmann et al. , 2003).
18 Chapter 1 6MAPK signalling genes in plant pathogenic fungi (Table 1.2)
Table 1.2. MAPK signalling genes reported in plant pathogenic fungi. Continued on the next page.
Organism Gene Genbank acc Gene fa mily Function Reference Stagonospora nodorum Mak2 AAX63387 MAPK ( Fus3/Kss1 ) Vegetative growth, pycnidiation and virulence Solomon et al. (2005b) Alternaria brassicicola Amk1 AAS20192 MAPK ( Fus3/Kss1 ) Anastamosis Craven et al. (2006) Aspergillus oryzae MpkA BAD12561 MAPK ( Slt2 ) Unknown Mitzutani et al. (2004) Bipolaris oryzae Bmk1 BAD42855 MAPK ( Fus3/Kss1 ) Vegetative growth, conidiation and virulence Moriwaki et al. (2007) Srm1 BAE48722 MAPK ( Hog1 ) Tolerance to hyperosmotic, UV and oxidative Moriwaki et al. (2006) stresses Blumeria graminis f. sp. Mpk1 AAG53654 MAPK ( Fus3/Kss1 ) Transcript accumulation during the formation of Zhang & Gurr (2001) hordei the conidial primary and appressorial germ tubes Mpk2 AAG53655 MAPK ( Slt2 ) Transcript accumulation during the formation of Zhang & Gurr (2001) the conidial primary and appressorial germ tubes Botrytis cinerea Bmp1 AAG23132 MAPK ( Fus3/Kss1 ) Conidial germ tube morphogenesis, unable to Zheng et al. (2000); germinate on hydrophobic surfaces and virulence Doehlemann et al. (2006) Bmp3 ABJ51957 MAPK ( Slt2 ) Vegetative growth, conidiation, sclerotia Rui & Hahn (2007) formation, reduced fungicide tolerance and virulence BcSak1 CAJ85638 MAPK ( Hog1 ) Vegetative growth, sclerotia formation, Segmuller et al. (2007) osmotolerance, tolerance to oxidative stress, conidiation and virulence AAP72037 MAPKKK ( Ssk22 ) Conidiation, cercosporin biosynthesis and Shim & Dunkle (2003) Cercospora zeae-maydis Czk3 virulence Claviceps purpurea Cpmk1 CAC47939 MAPK ( Fus3/Kss1 ) Virulence Mey et al. (2002b) Cpmk2 CAC87145 MAPK ( Slt2 ) Conidiation, cell wall structure and virulence Mey et al. (2002a) Cochliobolus Chk1 AAF05913 MAPK ( Fus3/Kss1 ) Vegetative growth, cellular integrity, conidiation, Lev et al. (1999); Lev & heterostrophus pseudothecia formation, melanin biosynthesis, Horwitz (2003); Eliahu et appressorium formation, cellulase gene expression al. (2007) and virulence Mps1 ABM54149 MAPK ( Slt2 ) Cellular integrity and melanin biosynthesis Eliahu et al. (2007) Hog1 BAD99295 MAPK ( Hog1 ) Activated during osmotic stress Kojima et al. (2004) Colletotrichum CgMek1 AF169644 MAPKK ( Ste7 ) Cell division after spore germination, Kim et al. (2000) gloeosporioides appressorium formation and virulence
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Table 1.2. Continued from the previous page.
Organism Gene Genbank acc Gene family Function Reference Colletotrichum lagenarium Maf1 AAL50116 MAPK ( Slt2 ) Appressorium formation, conidiation and virulence Kojima et al. (2002) Cst1 BAC11803 Transcrp. factor Formation of lipid bodies in appressoria, infectious Tsuji et al. (2003) (Ste12 ) hyphae formation and virulence Ocs1 BAD11137 MAPK ( Hog1 ) Osmotolerance and ocs1 mutants showed increase Kojima et al. (2004) resistance to fungicide Cmk1 AAD50496 MAPK ( Fus3/Kss1 ) Conidiation, germination, melanin metabolism and Takano et al. (2000) virulence Cryphonectria parasitica Cpmk1 AAO27796 MAPK ( Hog1 ) Conidiation, pigmentation, osmotolerance, Park et al. (2004b) hydrophobin biosynthesis and virulence Cpmk2 AAP86959 MAPK ( Fus3/Kss1 ) Vegetative growth, conidiation and virulence Choi et al. (2005) Cpkk1 AF069777 MAPKK (Mkk1/2 ) Hyperphosphorylation during active mycelial gorwth Turina et al. (2006) Cpkk2 AY623045 MAPKK ( Ste7 ) Unknown Turina et al. (2006) Fusarium graminearum Gpmk1 AF448230 MAPK ( Fus3/Kss1 ) Vegetative growth, conidiation, cell wall degrading Jenczmionka et al. enzymes, perithecia development and virulence (2003); Jenczmionka & Schafer (2005) Mgv1 AF492766 MAPK ( Slt2 ) Vegetative growth, female fertility, cell wall Hou et al. (2002) integrity and virulence Fusarium oxysporum Fmk1 AAG01162 MAPK ( Fus3/Kss1 ) Expression of genes encoding for pectinolytic Di Pietro et al. (2001) enzymes, hydrophobicity and virulence Fusarium solani FsMapk Q00859 MAPK ( Fus3/Kss1 ) Unknown Li et al. (1997) Gaeumannomyces graminis Gmk1 AAG44657 MAPK ( Fus3/Kss1 ) Complementation of M. grisea Pmk1 mutation Dufresne & Osbourn (2001) Magnaporthe grisea Pmk1 AAC49521 MAPK ( Fus3/Kss1 ) Appressorium formation, lipid mobilisation and Xu & Hamer (1996); virulence Thines et al. (2000) Mst7 EAA49142 MAPKK ( Ste7 ) Appressorium formation and virulence Zhao et al. (2005) Mst11 EAA56368 MAPKKK ( Ste11 ) Appressorium formation and virulence Zhao et al. (2005)
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Table 1.2. Continued from the previous page.
Organism Gene Genbank acc Gene family Function Reference Magnaporthe grisea Mps1 AAC63682 MAPK ( Slt2 ) Appressorium formation, cell wall integrity, Xu et al. (1998) conidiation, female fertility and virulence Mmk2 EAA56511 MAPKK (Mkk1/2 ) Phenotype similar to mps1 mutants Zhao et al. (2005) Bck1 EAA49225 MAPKKK ( Bck1 ) Phenotype similar to mps1 mutants Zhao et al. (2005) Mst50 EAA52507 Adaptor protein Interacts with Mst11, Mst7, Ras1, Ras2 and Mgb1, Park et al. (2006) (Ste50 ) host penetration and virulence Osm1 AAF09475 MAPK ( Hog1 ) Osmotolerance, arabitol accumulationand formation Dixon et al. (1999) of multiple appressoria from a single germ tube Pbs2 EAA48205 MAPKK ( Pbs2 ) Phenotype similar to osm1 mutants Zhao et al. (2005) Ssk2 EAA48525 MAPKKK ( Ssk2 ) Phenotype similar to osm1 mutants Zhao et al. (2005) Ras1 EAA53749 Ras G protein Interacts with Mst11 and Mst50 Park et al. (2006); Zhao et al. (2005) Ras2 EAA53026 Ras G protein Interacts with Mst11 and Mst50 Park et al. (2006); Zhao et al. (2005) Cdc42 AF250928 Small rho like Interacts with Mst50 Park et al. (2006) GTPase Mst12 AAL27626 Transcrip. Factor Appressorial penetration, invasive growth and Park et al. (2002) (Ste12) virulence Mycosphaerella MgFus3 AAX81518 MAPK ( Fus3/Kss1 ) Pycnidiation, vegetative growth, melanisation, Cousin et al. (2006) graminicola stomatal penetration and virulence MgSlt2 AAY98511 MAPK ( Slt2 ) Vegetative growth, pycnidiation, fungicide Mehrabi et al. (2006a) resistance, melanisation and virulence MgHog1 ABD92790 MAPK ( Hog1 ) Osmotolerance, yeastlike growth, fungicide Mehrabi et al. (2006b) resistance and virulence
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Table 1.2. Continued from the previous page.
Organism Gene Genbank acc Gene family Function Reference Sclerotinia sclerotiorum Smk1 AAQ54908 MAPK ( Fus3/Kss1 ) Regulate sclerotial formation. Pathway inhibited by Chen et al. (2004) cAMP. SsRas AY664402 Ras G protein Activaror of the Smk1 pathway. Required for Chen et al. (2004) sclerotia formation. Ustilago maydis Ras2 AAO19639 Ras G protein Suppressor of adr1 mutation, regulator of Kpp2 Lee & Kronstad (2002); signalling, cell morphology and virulence Muller et al. (2003a) Sql2 AAO19638 CDC25 like guanyl Activate Ras2 Muller et al. (2003a) nucleotide exchange factor Kpp6 CAD43731 MAPK ( Fus3/Kss1- Host penetration and virulence Brachmann et al. (2003) like ) Kpp2/Ubc3 AAF15528 MAPK ( Fus3/Kss1 ) Filamentous growth, attenuation in pheromone Mayorga & Gold response, formation of dikaryotic hyphae, induction (1999); Muller et al. of pheromone responsive genes, conjugation tube (1999) and reduced virulence Fuz7/Ubc5 EAK82569 MAPKK (Mkk1/2 ) Filament formation, attenuation in formation of Banuett & Herskowitz conjugation tube, tumor induction, teliospore, (1994) germination, appressorium formation and non virulent Kpp4/Ubc4 AAN63948 MAPKKK ( Ste11 ) Suppressor of the uac1 mutation Andrews et al. (2000); Muller et al. (2003b) Ubc2 AAK49432 Adaptor protein Suppressor of the uac1 mutation, pheromone Mayorga & Gold (2001) (Ste50 ) response and virulence Verticillium dahliae Vmk1 AAW71477 MAPK ( Fus3/Kss1 ) Conidiation, microsclerotia formation and virulence Rauyaree et al. (2005)
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The role of MAPK signalling in the virulence of M. grisea has been a topic of intense research during the past decade. The Fus3/Kss1 type MAPK gene Pmk1 was the first MAPK gene reported in M. grisea (Xu & Hamer, 1996). Pmk1 was strongly expressed in the appressorium relative to the conidia, germ tube, vegetative hyphae and conidiophore thus suggesting a possible role in appressorium morphogenesis (Bruno et al. , 2004). The inactivation of Pmk1 resulted in mutants that were unable to produce appressoria (Xu & Hamer, 1996). Other components of the Pmk1 cascade were later identified. Zhao et al. (2005) were able to identify genes encoding Mst7 MAPKK and
Mst11 MAPKKK based on sequence homology to yeast Ste7 MAPKK and Ste11
MAPKKK. Phosphorylation assays indicated that a dominant active Mst7 was able to phosphorylate Pmk1. Not surprisingly, mutants carrying a deletion in these genes showed similar phenotype to the pmk1 mutants (Zhao et al. , 2005). The Ste12 transcription factor Mst12 was proposed as an effector of Pmk1 signalling (Talbot,
2003). Mst1 may directly interact with Pmk1 based on yeast two hydrid analysis (Y2H)
(Park et al. , 2002). Unlike pmk1 , mst12 mutants were able to form appressoria but failed to penetrate and grow invasively in the host (Park et al. , 2002; Park et al. , 2004a).
Mst12 deletion also caused a disturbance in microtuble organisation which was postulated to be associated with appressorial development (Park et al. , 2004a). Cross signalling between the cAMP pathway and Pmk1 MAPK cascades was evident as the addition of cAMP restored the early stage of appressorium morphogenesis in the pmk1 mutants. Furthermore, mgb1 mutants shared similar defects in appressorium morphogenesis to which the addition of cAMP was only able to restore the early stage of appressorium morphogenesis (Nishimura et al. , 2003). It was postulated that Mgb1 acts upstream of the Pmk1 MAPK signalling to regulate appressorial penetration and
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infectious hyphal growth (Nishimura et al. , 2003). This hypothesis was later supported by a classical Y2H experiment showing a positive interaction between Mgb1 and the
MAPK cascade scaffolding protein Mst50 yeast Ste50 ortholog. Not surprisingly,
Mst50 interacted with Mst7 and Mst11 (Park et al. , 2006). The Slt2 and Hog1 type
MAPK cascades have been characterised by the Xu laboratory. Mutants of the Slt2 type
MAPK gene Mps1 showed an increase sensitivity to cell wall digesting enzymes and hence were compromised in cellular integrity (Xu et al. , 1998). Furthermore, mutants were able to form appressoria but unable to penetrate the host and were non pathogenic.
The deletion of Mmk2 and Bck1 which codes for Mmk1/Mmk2 type MAPKK and
Bck1 type MAPKKK produced mutants that were identical to the mps1 mutants (Zhao et al. , 2005). The deletion of the Hog1 ortholog Osm1 resulted in increased sensitivity to osmotic stress, a phenotype observed with hog1 mutants of yeast. In addition, osm1 mutants formed multiple appressoria from the germ tube and accumulated arabitol in the appressorium (Dixon et al. , 1999). The deletion of Pbs2 and Ssk2 which encode Pbs2 type MAPKK and Ssk2/Ssk22 type MAPKKK produced mutants that were phenotypically similar to the osm1 mutants (Zhao et al. , 2005). Thus, three MAPK cascades were proposed for M. grisea : 1. Mst11 Mst7 Pmk1, 2. MgBck1 MgMmk2
Mps1 and 3. MgSsk2 MgPbs2 Osm1 (Zhao et al. , 2005). The latter two cascades showed some functional conservation with their yeast counterparts.
The role of three MAPKs in B. cinerea was examined via gene deletion. Bmp1 is an ortholog of M. grisea Pmk1. A bmp1 mutant was defective in host penetration and infection (Zheng et al. , 2000). Upon further examination by Doehlemann et al. (2006), the bmp1 mutant was found to be defective in spore germination in the presence of a
24 Chapter 1
carbon source and hydrophobic surfaces. The addition of cAMP restored wild type germination rate on carbon source and hence indicated evidence of cross signalling between the MAPK and heterotrimeric G protein pathways (Doehlemann et al. , 2006).
The role of B. cinerea Bmp3 Slt2 type MAPK gene (sequence ortholog of M. grisea
Mps1) was recently reported by Rui & Hahn (2007) using a gene knockout approach.
The bmp3 mutant showed an increase in susceptibility to fungicide, oxidative stress and lacked the ability to spread within the host after penetration. Conidiation and sclerotia formation were also compromised. Growth of the bmp3 mutant was reduced, which was more pronounced under low osmolarity conditions. However, under high osmolarity the growth rate of the mutant was comparable to the wild type (Rui &
Hahn, 2007). In contrast, mutants defective in the Hog1 type MAPK gene BcSak1 were more sensitive to osmotic stress, showed increased sclerotia production and were more resistant to fungicide that the wild type (Segmuller et al. , 2007). This suggests that two
MAPK pathways may be involved in establishing an osmo equilibriation in B. cinerea .
1.1.3 Phosphotidylinositol and calcium signalling
In contrast to heterotrimeric G protein and MAPK signalling, phospholipase/Ca 2+ signal transduction in plant pathogenic fungi have received relatively little attention. The phosphotidylinositol/Ca 2+ signalling pathway is initiated upon phopholipase C activation which converts phosphotidylinositol biphosphate into diacylglycerol (DAG) and inositol 1,4,5 triphosphate (IP 3) (Rhee et al. , 1989).
Phosphotidylinositol signalling can be activated by the G βγ subunits or tyrosine kinase linked receptors (Berridge, 1993; Park et al. , 1993). DAG activates protein kinase C
2+ whereas IP 3 causes the release of intracellular Ca from storage bodies within the cell
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(Berridge, 1993; Irvine, 1990; Nishizuka, 1988). Ca 2+ functions as a secondary messenger for many proteins including Ca 2+ /calmodulin dependent protein kinases
(Cruzalegui & Bading, 2000). In the anthracnose fungus Colletotrichum gloeosporioides , hard surface contact induces germination and appressorium formation.
A calmodulin gene was up regulated during hard surface contact which suggests the possible involvement of the Ca 2+ pathway in the early stage of infection (Kim et al. ,
1998). To test this possibility, the fungus was supplemented with pharmacological antagonists of phospholipase C, calmodulin and Ca 2+ /calmodulin dependent protein kinase. Spore germination and appressorium formation were reduced. This strongly suggests that hard surface contact induces Ca 2+ signalling that regulate the early stage of infection (Kim et al. , 1998). It is interesting to note that a Ste7 MAPKK CgMek1 is also required for spore germination and appressorium formation in C. gloeosporoides
(Kim et al. , 2000). Further research is required to determine a possible link between the two pathways and its regulation of early infection. Recently, a phospholipase C gene
(Cplc1 ) was shown to be an important pathogenicity factor of the chestnut blight fungus
Cryphonectria parasitica (Chung et al. , 2006). Cplc1 is involved in the regulation of a laccase gene previously known to be regulated by heterotrimeric G protein signalling and hypovirus infection (Chen et al. , 1996; Dawe & Nuss, 2001). Three genes encoding Ca 2+ /calmodulin protein kinases were identified in Stagonospora nodorum
(Solomon et al. , 2006c). The role of these genes will be discussed in Section 1.3.4.
1.1.4 Two-component signalling
In many bacteria, two component signalling systems are used to sense a variety of environmental stimuli such as stresses (Bourret et al. , 1991; Mascher et al. , 2006).
26 Chapter 1
Two component systems consist of a sensor histidine kinase (HK) that autophosphorylate on a conserved histidine residue during activation. The phosphate moeity is then transferred to a conserved aspartate group of a response regulator protein and thus forming a two component signalling system (West & Stock, 2001; Wolanin et al. , 2002). The presence of two component signalling in plant pathogenic fungi is a relatively recent discovery. Whole genome analysis of C. heterostrophus , B. cinerea and Gibberella moniliformis reveals an extensive number of putative histidine kinases that are divided into 11 classes based on amino acid sequence relationship (Catlett et al. ,
2003). In C. heterostrophus , the Class III HK Dic1 act as a positive upstream regulator of Hog1 signalling which is required for osmotolerance and regulation of fungicide tolerance (Yoshimi et al. , 2005). Two conserved response regulators, Ssk1 and Skn7, were identified as immediate effectors of Dic1 based on sequence homology to conserved components in yeast (Izumitsu et al. , 2007). Both regulators play an additive role to osmotolerance and fungicide sensitivity. Phosphorylation assays indicate that
Ssk1 activates the Hog1 cascade whereas Skn7 participates in an unidentified pathway also require for osmotolerance and fungicide adaptation (Izumitsu et al. , 2007).
Reduction in osmotolerance and alterations in fungicide adaption of Class III HKs mutants in B. cinerea and M. grisea were observed (Motoyama et al. , 2005; Viaud et al. , 2006).
1.1.5 Genetic evidence of signal transduction effectors
Mutational analysis of fungal signal transduction components has provided an insight into phenotypic regulation and the contribution to fungal virulence. However, it cannot be fully concluded that reduced fitness in pathogenicity is due to inappropriate
27 Chapter 1
signalling or the pleiotrophic effect of the mutation. Hence, understanding the precise mechanism of signal regulation by identifying and functionally characterising effector molecules remains the next challenging step in pathogenicity studies.
Gronover et al. (2004) used a cDNA suppression subtractive hybridisation
(SSH) approach to identify effectors of Bcg1 signalling in B. cinerea during infection.
Genes encoding putative secondary metabolism proteins such as cytochrome P450 monooxygenases and a polyketide synthase (PKS) were identified as Bcg1 regulated.
Furthermore, genes for proteases and cell wall degrading enzymes were down regulated in the bcg1 mutant (Gronover et al. , 2004).
In U. maydis , the bE/ bW heterodimer binds to the promoter sequence of Lga2 and induces gene expression (Romeis et al. , 2000). Lga2 encodes a putative mitochondrial matrix protein that is required to maintain mitochondrial functions
(Bortfeld et al. , 2004; Urban et al. , 1996). Regulation of bE/ bW effectors were further examined by Brachmann et al. (2001) using RNA fingerprinting. Ten genes were identified as b regulated. These genes encode disulphide isomerase, exochitanase, cation antitransporter, ATPase, acyl transferase, capsule associate protein, DNA polymerase X and three unknown proteins. From this, a b induced DNA polymerase X and b repressed unknown protein were tested for their role in virulence via targeted gene deletion. No discernable phenotypes were observed in either of mutants when compared to the wild type (Brachmann et al. , 2001).
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Gene expression profiles of morphologically altered U. maydis strains were examined by Andrews et al. (2004) and Garcia Pedrajas & Gold (2004) by SSH analysis. To do this, mRNAs from U. maydis haploid budding wild type and a constitutively filamentous uac1 mutant were used to construct filament down regulated and up regulated cDNA libraries. Genes that code for a conidiophore surface protein, endo 1,4 β xylanase, γ aminobutyrate (GABA) permease, GABA aminotransferase, sterol desaturase, amino acid permease, UDP glucose dehydrogenase and phosphate transporters (phosphate acquisition) showed greater expression in the budding form
(Garcia Pedrajas & Gold, 2004). Genes that code for an oxidoreductase and several unknown proteins showed greater expression in the filamentous form (Andrews et al. ,
2004). Deletion of the oxidoreductase gene resulted in slightly reduced growth rate compared to the wild type (Andrews et al. , 2004). Larraya et al. (2005) came across similar findings using serial analysis of gene expression (SAGE) to compare the transcript profile of wild type, ubc1 and adr1 mutants. SAGE tags for genes involved in phosphate acquisition were elevated in the PKA active ubc1 mutant as compared to the wild type and PKA inactive adr1 mutant. The ubc1 mutant showed defects in phosphate accumulation presumably due to an increase in cell wall permeability
(Larraya et al. , 2005). Nevertheless, this indicates a role of cAMP in the regulation of phosphate metabolism in U. maydis .
The availability of fungal genome sequences permits large scale global gene expression analysis. Eichhorn et al. (2006) used a global microarray approach to analyse gene expression in U. maydis . The expression profile of an Adr1 overexpressing strain was compared to the wild type. Of the 847 differentially
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expressed genes observed, nine of these genes showed increased transcript abundance in the Adr1 overexpressing mutant and are located in three gene clusters in different chromosomes. Sequence analysis indicates that some of these genes may play a role in iron acquisition. Two of these genes that code for L ornithine N5 monooxygenase and non ribosomal peptide synthetase (NRPS) were previously characterised for their involvement in iron siderophore biosynthesis (Mei et al. , 1993; Yuan et al. , 2001).
Attenuation in siderophore biosynthesis did not affect the ability of U. maydis to infect
(Mei et al. , 1993). However, non siderophore iron acquiring genes that code for an iron permease and multicopper oxidase (located within a putative gene cluster in chromosome 4) were inactivated and resulting mutants were reduced in virulence
(Eichhorn et al. , 2006).
The heterotrimeric G protein pathway of C. parasitica is required for virulence, maintenance of colony mophology and sporulation (Gao & Nuss, 1996; Kasahara &
Nuss, 1997). Mutants of the heterotrimeric G protein pathway showed similar, but not identical, phenotypes to strains infected with the hypovirus CHV1 EP713 (Dawe &
Nuss, 2001). Microarrays consisting of 2,200 genes were probed with cDNAs from wild type, cga1 , cpgb1 mutants and a hypovirus infected strain to identify genes that are regulated by heterotrimeric G protein signalling and hypovirus infection (Dawe et al. , 2004). The expression profile of cga1 (216 genes) and cpgb1 (163 genes) mutants shared a considerable overlap (100 genes) with genes that are expressed in the same directions. Some of the genes that showed increased expression in all strains relative to the wild type code for glutathione S transferase, oxidoreductase, cytochrome P450,
TOXD and o methyltransferase (Dawe et al. , 2004). Genes that showed decreased
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expression encode a transcription factor Mst12, aspergillopepsin II, nucleases, acid proteinase and endothiapepsin (Dawe et al. , 2004). Furthermore, a 45 gene overlap was observed between the hypovirus infected strain and cga1 /cpgb1 strains which mostly occur in the same direction. This data support the hypothesis that modifications of the heterotrimeric G protein pathway contributed significantly to hypovirus mediated phenotype in C. parasitica (Dawe et al. , 2004). Furthermore, constitutive activation of
Cpg1 and Cprgs1 deletion resulted in an easily wettable mutant phenotype that was likely due to a reduction in the transcript accumulation of the hydrophobin encoding gene cryparin (Segers & Nuss, 2003; Segers et al. , 2004). Interestingly, the expression of the cyparin gene is also positively regulated by the Cpmk1 MAPK thus indicating evidence of cross signalling (Park et al. , 2004b).
The maize pathogen Cochliobolus carbonum is well studied for its role in the production of HC toxin (Walton, 2006) and cell wall degrading enzymes (Apel
Birkhold & Walton, 1996; Kim et al. , 2001; Scott Craig et al. , 1990; Scott Craig et al. ,
1998; Wegener et al. , 1999). A gene orthologous to yeast Snf1 was identified and characterised in C. carbonum (Tonukari et al. , 2000). In yeast, the Snf1 protein kinase is a central component of the signalling pathway that regulates the activation of glucose repressed genes during glucose starvation (Carlson, 1999). The deletion of Ccsnf1 caused a reduction in pathogenicity of C. carbonum on maize. Furthermore, genes coding for xylanases, a xyloxidase, polygalacturonases and glucanases were reduced in expression in the ccsnf1 mutant when compared to the wild type (Tonukari et al. , 2000).
Enzymatic activities of some cell wall degrading enzymes correlated gene expression.
Growth of the ccsnf1 mutant was reduced when grown on plant cell wall components
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(Tonukari et al. , 2000). It is interesting to note that a similar phenotype was observed with mutants deficient in a histone histone deacetylase gene Hdc1 (Baidyaroy et al. ,
2001).
The disruption of a Hog1 type MAPK Srm1 in Bipolaris oryzae , the causal agent of brown leaf spot disease on rice, rendered the pathogen more sensitive to hyperosmotic, UV and oxidative stresses (Moriwaki et al. , 2006). Susceptibility to oxidative stress may be explained by the lack of expression of a catalase gene in the srm1 mutant.
Melanin is required for appressorial morphogenesis in M. grisea and the anthracnose fungus Colletotrichum lagenarium (Howard & Valent, 1996; Kubo et al. ,
1999). Cmk1 encodes a putative Fus3/Kss1 class MAPK in C. lagenarium and is essential for conidial germination, formation of appressoria and for pathogenicity on cucumber (Takano et al. , 2000). The expression of major melanin biosynthetic genes coding for scytalone dehydratase, PKS and trihydroxynaphthalene reductase were greatly reduced in the cmk1 mutant (Takano et al. , 2000). In addition, melanin biosynthesis in C. lagenarium may be regulated by a second pathway. Cmr1 encodes a transcription factor that regulates the same set of melanin biosynthetic genes as Cmk1 but regulation occurs only in the hyphae (Tsuji et al. , 2000). The cmr1 mutants accumulated scytalone, an intermediate of dihydroxynapththalene melanin biosynthesis
(Tsuji et al. , 2000).
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Fusarium oxysporum is a soil borne vascular wilt fungus. The deletion of a
Fus3/Kss1 MAPK gene Fmk1 resulted in loss of virulence and a drastic reduction of the cell wall degrading enzyme pectate lyase (Di Pietro et al. , 2001). Orthologous to Fmk1 ,
Chk1 in C. heterostrophus is required for wild type expression of genes coding for a cellobiohydrolase and endoglucanase. The chk1 mutants were reduced in pathogenicity
(Lev et al. , 1999; Lev & Horwitz, 2003). In addition, Chk1 and another MAPK gene
Mps1 regulate the expression of melanin biosynthetic genes though a novel transcription factor Cmr1 (Eliahu et al. , 2007).
1.1.6 Biochemical evidence of signal transduction effectors
In the head blight fungus Fusarium graminearum , the Fus3 /Kss1 type MAPK gene Gpmk1 is required for pathogenicity, conidiation and asexual reproduction
(Jenczmionka et al. , 2003). Enzymatic analysis indicates that gpmk1 mutants were significantly reduced in extracellular xylanotic, proteolytic and lipolytic activities
(Jenczmionka & Schafer, 2005). Similar observations were made with bcg1 and fgb1 mutants of B. cinerea and F. oxysporum , respectively. A growth assay using casein agar indicates that bcg1 mutant of B. cinerea was reduced in extracellular protease activity (Gronover et al. , 2001). The fgb1 mutants of F. oxysporum defective in G β protein showed reduced secreted general protease activity (Prados Rosales et al. , 2006).
Evidence of secondary metabolite regulation by MAPK signalling has been shown by two studies. Cercosporin is a photo activated phytotoxin produced by many
Cercospora species. Genes involved in cercosporin biosynthesis and transport have been identified (Choquer et al. , 2005; Choquer et al. , 2007; Dekkers et al. , 2006;
33 Chapter 1
Upchurch et al. , 2001). Cercosporin biosynthesis appears to be regulated by MAPK
(Shim & Dunkle, 2003). In F. graminearum , the Mgv1 MAPK gene plays a significant signalling role. The deletion of Czk3 , a putative MAPKKK gene, resulted in abolished cercosporin production in the gray spot pathogen of maize Cercospora zeae-maydis
(Hou et al. , 2002). Trichothecene is synthesised by enzymes encoded in a gene cluster
(Brown et al. , 2004).
1.2 Wheat - the cultivated cereal crop
Wheat ( Triticum spp.) was first given a modern taxonomic description in the
“Species Plantarum” by a Swedish botanist, Carl Linnaeus in 1753 (Linnaeus, 1753)
(Figure 1.5A). Einkorn wheat ( T. monococcum ) and emmer wheat ( T. turgidum ) are considered as “founder crops” of the Fertile Crescent located in present day Iraq, Syria, southeast Turkey and the Palestine region (Zohary & Hopf, 2000) (Figure 1.5B). DNA fingerprinting suggests that cultivated T. monococcum may have originated from wild einkorns in the Karacadağ mountains in the Fertile Crescent (Heun et al. , 1997) (Figure
1.5B). Evidence of deliberate cultivation stemmed from the discovery of numerous quantities of T. monococcum grains collected in Tell Abu Hureyra, an ancient settlement located in the Fertile Crescent dating back to the 10 th and 9 th millennia BC (Hillman,
1975; Moore, 1982; Zohary & Hopf, 2000) (Figure 1.5B). It has been postulated that wheat domestication enabled early settlers to shift from a lifestyle of hunting and gathering to establishing ancient settlements and civilisations in the Fertile Crescent
(Harlan & Zohary, 1966) (Figure 1.5C).
34 Chapter 1
A B
7Wheat (Figure 1.5)
C
D
Figure 1.5. A. Photograph of the common bread wheat, Triticum aestivum L (http://calphotos.berkeley.edu ). B. The location of the Karacadağ region ( ) and Tell Abu Hureyra ( ) in the Fertile Crescent (green) are indicated (http://earthobservatory.nasa.gov/ ). C. (Top row) A carving impression excavated from Tell es Suleimeh ( ) showing evidence of ploughing (approx. 2,400 BC) (Postgate, 1992). D. Examples of wheat based products. The illustration includes wheat based beer, breakfast cereals, breads, pasta and biscuits. 35 Chapter 1
8Leading wheat producing countries (Table 1.3)
Table 1. 3. Top 20 wheat producers in 2005 (Food
and Agriculture Organisation of the United
Nations; http://faostat.fao.org ). Australia was
ranked as the seventh largest wheat producer in
the world. Country Million metric tonnes China 97 India 72 USA 57 Russia 48 France 37 Canada 27 Australia 25 Germany 24 Pakistan 22 Turkey 21 Ukraine 19 UK 15 Iran 14 Argentina 13 Kazakhstan 11 Poland 9 Egypt 8 Italy 8 Romania 7 Uzbekistan 6 World total 631
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In modern days, wheat is a major cereal crop cultivated globally for its grains which are used to make many food products (Figure 1.5D). It was estimated that 631 million tonnes of wheat were produced globally in 2005 (Food and Agriculture
Organisation of the United Nations; http://faostat.fao.org ). Australia is considered as one of the world’s leading producer of wheat with an estimate of 24 million tonnes harvested in 2005 (Table 1.3). Wheat is predominantly grown in the South Eastern and
South Western regions of Australia where the recorded annual rainfall figure ranges from 200 to 600 mm (Figure 1.6A) (Australian Bureau of Meteorology; www.bom.gov.au ). The estimated gross value of wheat produced in Australia between
2004 and 2005 is over AUD$4 billion. A significant portion of wheat is exported to major international markets such as Indonesia, Middle East, South Korea, China and
Japan (Australian Bureau of Statistics; www.abs.gov.au). Thus, wheat represents a major food source and export income for Australia.
1.3 Stagonospora nodorum , the cereal pathogen
1.3.1 Epidemiology and economical importance
The ascomycete Stagonospora (syn. Septoria ) nodorum (Berk.) Castell. &
Germano [family: Dothideomycetes; teleomorph: Phaeosphaeria (syn. Leptosphaeria ) nodorum (Müll.) Hedjar.] is a major fungal pathogen on wheat, causing leaf and glume blotch diseases (Weber, 1922) (Figure 1.7A and B). Stagonospora leaf and glume blotch is prevalent in the wheat growing region of Australia (Figure 1.6B). The disease can cause between five to 15% yield loss in South Western Australia alone (Brennan &
Murray, 1998). However, yield losses up to 31% have been reported under conditions favourable for infection (Bhathal et al. , 2003).
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(Brennan & Murray, 1998).
9Rainfall figure and disease prominence in Australia (Figure 1.6) A
B
(%)
Figure 1.6 . A. Major wheat growing regions in Australia (Statistics
Yearbook Australia 2006; www.abs.gov.au ). B. Estimated loss in
wheat yield due to S. nodorum (Brennan & Murray, 1998).
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A B (Douaiher et al. , 2004; Richardson & Noble, 1970)
10Disease symptoms of wheat infected with Stagonospora nodorum (Figure 1.7)
C D 10 m O 10 m
SL S
V
C C SL
E
10 m
Figure 1.7 . Disease symptoms of wheat infected with Stagonospora nodorum . A. Leaf blotch (http://pubs.caes.uga.edu/caespubs/pubcd/B1190.htm ). B. Glume blotch
(http://ohioline.osu.edu/ac fact/0002.html ) disease. Morphology of the C. pycnidial primodium (immature) and D. mature pycnidium (Douaiher et al. 2004). Key = O, ostiole; S, spore; C, conidiogeneous cell; V, pycnidial cavity and SL, subparietal layer.
E. Camera lucida drawings of asexual pycnidiospores (Richardson & Noble, 1970). 39 Chapter 1
1.3.2 The infection life cycle
The life cycle of the pathogen includes a sexual and an asexual stage. Asexual spores of S. nodorum , called pycnidiospores, are produced within solid black fruiting bodies called pycnidia. These fruiting bodies are 160 to 210 m in diameter (Cunfer &
Ueng, 1999; Douaiher et al. , 2004) (Figure 1.7C and D). The inner surface of the pycnidial wall consists of a subparietal layer that is made up of conidiogenous cells.
Sporogenesis occurs via enteroblastic phialidic conidiogenesis (Sunny & Zeyen, 1977;
Sutton & Waterston, 1966). Mitotic division occurs at the tip of the conidiogenous cell which results in an elongated cell. The formation of a septum within the elongated cell gives rise to a pycnidiospore which is oriented towards the ostiole (Douaiher et al. ,
2004). When mature, the pycnidium releases a pink cirrhus from the ostiole which contains a mixture of pycnidiospores and mucilaginous exudates (Langeron &
Vanbreuseghem, 1952) (Figure 1.8). Pycnidiospores spores are typically 14.2 to 32 m in length and septated (Cunfer & Ueng, 1999; Richardson & Noble, 1970) (Figure
1.7E). Pycnidiospores can be dispersed locally via rainfall splashes (Faulkner &
Colhoun, 1976) and are considered as a major source of secondary inoculum which can lead to the generation of a clonal phenotype in spatial areas of infection (Sommerhalder et al. , 2006).
The sexual cycle is initiated from the development of sexual fruting bodies called pseudothecia which produce ascospores and are considered to be a major source of primary inoculum in an epidemic (Sommerhalder et al. , 2006). Ascospores are
40 Chapter 1
11Host penetration and pycnidiation (Figure 1.8)
i ii
i ii
Figure 1. 8. Top . A necrotic lesion on a wheat leaf caused by S. nodorum . i.
Trypan blue staining of the lesion showing fungal penetration. Red arrows
indicate fungal entry via the stomata. Black arrows indicate epidermal penetration
attempts. ii. The release of pycnidiospores (pink chirri) from mature pycnidia.
41 Chapter 1
disseminated via long distance airborne dispersal under moist conditions (Arseniuk et al. , 1998; Bathgate & Loughman, 2001; Keller et al. , 1997; von Wechmar, 1966).
However, pseudothecia and ascospores are difficult to induce under laboratory conditions for detailed studies.
Spores of S. nodorum are a major source of inoculum for the onset of an epidemic (Eyal, 1999). The infection process is initiated once contact is made with the host surface. Germination occurs soon after, giving rise to vegetative hyphae which then proliferate along the surface of the host looking for weaknesses or openings to enter. The hyphae can attempt to penetrate the host epidermis (Karjalainen &
Lounatmaa, 1986; Solomon et al. , 2004b) or invade through the stomata (Solomon et al. , 2004b) (Figure 1.8). Once inside the leaf, the fungus will continue to proliferate and cause necrotic tissue damage. It is likely that S. nodorum uses an array of cell wall degrading enzymes to assist in the infection process (Lehtinen, 1993; Magro, 1984).
Asexual sporulation occurs seven days post infection (Solomon et al. , 2006e).
1.3.3 Genetic manipulation
The development of S. nodorum from a spore propagule to infectious hyphae during pathogenesis requires genetic and biochemical coordination. One way to study developmental processes in S. nodorum is at the molecular level. Genetic transformation of S. nodorum was first reported by Cooley et al. (1988). The fungus was successfully transformed with a hygromycin phosphotransferase gene which confers resistance to hygromycin B. Three g to eight g of DNA are routinely used per 5 x 10 7 protoplasts to facilitate homologous recombination. Construction of a gene
42 Chapter 1
knockout vector requires a flanking region of one kb or greater to achieve homologous gene recombination of at least 2% of transformants screened (Solomon et al. , 2006b)
(Table 1.4). This indicates that S. nodorum is a genetically tractable organism and is ideal for molecular genetic analysis using targeted gene disruption to identify pathogenicity genes.
1.3.4 Signal transduction genes
Signal transduction in S. nodorum was investigated for a potential role in virulence on wheat. Heterotrimeric G protein signalling was the first pathway investigated for its role in pathogenicity. A cDNA encoding the G α gene Gna1 was initially identified from a cDNA library derived from S. nodorum grown on wheat cell wall. The deletion of this gene resulted in mutants that produced extensive aerial hyphae, showed radial crevassing when grown on synthetic media and increased sensitivity to osmotic stress. Moreover, pycnidiation and asexual sporulation in the gna1 mutants were not observed under in vitro and in planta conditions. The gna1 mutants also secreted a large quantity of tyrosine, phenylalanine and dihydroxyphenylalanine (DOPA) into the extracellular enviroment. Hence, gna1 mutants may be defective in DOPA melanin biosynthesis. In addition, the gna1 mutants showed a reduction in extracellular protease and cell wall degrading enzyme activities
(Solomon et al. , 2004b). Cytological analysis indicated that the gna1
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(Solomon et al. , 2006b)
12Rate of homologous gene recombination in S. nodorum (Table 1.4) Nia1 Howard et al. (1999) Odc1 – Bailey et al. (2000) Snp1 Bindschedler et al. (2003) Gox1 Solomon & Oliver (2004) Mpd1 Solomon et al. (2005a) Gna1 – Solomon et al. (2004b) Ptr1 Solomon et al. (2003) Mls1 Solomon et al. (2004a) Mak2 Solomon et al. (2005b)
Table 1.4 . Rate of homologous gene recombination in S. nodorum from selected publications. Adapted from Solomon et al. (2006b).
Gene 5’ flank 3’ flank Total Gene Rate Reference (kb) (kb) transformants KOs (%) Nia1 1 4.8 26 6 23 Howard et al. (1999) Odc1 1 1 150 3 2 Bailey et al. (2000) Snp1 1+ 1+ 79 10 13 Bindschedler et al. (2003) Ptr2 0.5 1.2 37 24 65 Solomon et al. (2003) Gox1 0.3 0.8 45 4 9 Solomon & Oliver (2004) Mls1 0.9 0.8 48 2 4 Solomon et al. (2004a) Gna1 0.6 0.5 50 2 4 Solomon et al. (2004b) Mpd1 0.3 0.8 60 2 3 Solomon et al. (2005a) Mak2 0.2 0.2 101 14 4 Solomon et al. (2005b)
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mutants may be defective in penetration of wheat leaf epidermis. Consequently, these phenotypic defects may attribute to the reduced ability of the gna1 mutants to colonise the host tissue. A putative G β subunit gene was inactivated in a later experiment and the phenotype of the resulting mutants were similar to the gna1 mutants (Solomon, unpublished data ).
The role of MAPK signalling in S. nodorum virulence on wheat was elucidated by Solomon et al. (2005b). Mak2 was cloned using degenerate PCR. Sequence analysis indicates that Mak2 belongs to the Fus3/Kss1 MAPK class (Figure 1.4).
Mutants carrying the deleted gene were reduced in vegetative growth and showed radial crevassing. Similar to gna1 deletants, the mak2 mutation were abolished in pycnidiation. Mutants were unable to penetrate the epidermal surface but can still enter the stomata of wheat. However, mak2 mutants were unable to further colonise the host beyond penetration and hence was completely non pathogenic.
The role of phosphotidylinositol/Ca 2+ signalling in the virulence of S. nodorum was examined by Solomon et al. (2006c). Three putative Ca 2+ /calmodulin protein kinase genes, CpkA , CpkB and CpkC , were inactivated by targeted deletion. The disruption of CpkB did not result in a discernable phenotype. However, the deletion of
CpkA caused a reduction in asexual sporulation and altered pigmentation in response to growth in the dark. The deletion of CpkC resulted in delayed lesion formation and reduced asexual sporulation during infection.
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Perturbation of the heterotrimeric G protein, MAPK and Ca 2+ /calmodulin signalling pathways have resulted in developmental defects and reduced/abolished virulence in S. nodorum on wheat. Hence, the identification of molecules that were altered in these developmentally challanged mutants represent a critical step towards understanding the intricacy of the signalling network and pathogenicity in S. nodorum .
1.4 Fungal genome sequences and proteomics
Genome sequences of M. grisea and U. maydis were recently reported by Dean et al. (2005) and Kamper et al. (2006). In addition, complete genome sequences of other phytopathogenic fungi such as S. nodorum , F. graminearum , Fusarium verticillioides , Mycosphaerella graminicola , Nectria haematococca , B. cinerea ,
Sclerotinia sclerotiorum and Aspergillus flavus are publicly available. Genome sequencing undoubtedly opens new doors for designing genome arrays for gene expression studies in plant pathogenic fungi (Guldener et al. , 2006). The expression of a large number of genes can be simultaneously analysed with a microarray (Fraser &
Fleischmann, 1997) and could be used to elucidate gene regulation by signal transduction pathways. Transcriptomics can provide a useful overview of global gene expression, although it cannot discriminate the cellular localisation of a gene, end product and forms of post translational modifications that may be critical for its activity
(Patterson & Aebersold, 1995). Annotation of genome sequences will provide an opportunity for a large scale proteome analysis. In the post genomic era, proteomics are rapidly gaining status for expression analysis of functional end products of transcription
(Gygi et al. , 1999a). The state and abundance of a protein often dictate its activity within a cell.
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The term ‘proteomic’ is coined to encompass a field that attempts to understand the expression, function and regulation of the entire set of proteins encoded by an organism (Wasinger et al., 1995; Zhu et al., 2003). It also enables the identification of proteins that are regulated by post translational modifications prevalent during a signal transduction event such as phosphorylation/dephosphorylation or alterations in sub cellular localisation (Patterson & Aebersold, 1995). Dissection and identification of these targets that are modulated by signalling cascades would require a complex global analysis to look for changes in the abundance of downstream targets between two or more different tissues, cell type or treatments of identical tissue and cell types. One of the most commonly used proteomic techniques to monitor these changes at the proteome level is two dimensional (2D) gel electrophoresis (Herbert et al. , 2001).
Current 2D electrophoresis technology is largely based on the technique described by O'Farrell (1975) whereby a complex mixture of proteins is separated based on their isolectric properties and molecular weight (MW). 2D electrophoresis concerns the analysis of protein profiles between sample pairs (cells at different stages of growth and mutant versus wild type organism) or chemically treated cells. Protein samples are solubilised in a chaotrophic buffer. This is followed by protein separation via isoelectric focusing (IEF) and electrophoresis via sodium dodecyl sulphate polyacrylamide gel electrophoresis (SDS PAGE). Protein spots can be detected with a variety of staining methods such as Coomassie dye, silver precipitation or fluorescent dyes. Protein spots of interest are excised and subjected to proteolysis. The serine protease trypsin is often used to digest the protein spot. The protease hydrolyses
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132D electrophoresis workflow (Figure 1.9) (Graves & Haystead, 2003; Weistermeir & Naven, 2002)
A
Protein spot is excised for further analysis (B)
B
Figure 1.9 . Typical work flow of 2D electrophoresis. Adapted from A. Graves &
Haystead (2003) and B. Weistermeir & Naven (2002).
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peptide bonds at the carboxyl side of lysine and arginine residues. Trypsinated peptides are subjected to mass spectrometry analysis to provide peptide mass fingerprints, collision induced dissociation (CID) ion spectra or amino acid sequences depending on the equipment used. The availability of annotated fungal genome sequences and expressed sequence tag (EST) databases such as Cogeme
(http://cogeme.ex.ac.uk/ ) will greatly facilitate in the identification of the protein of interest from mass spectrometry derived data (Figure 1.9).
1.5 Project aims
One of the goals of the Australian Centre for Necrotrophic Fungal Pathogens
(ACNFP) is to identify pathogenicity genes in S. nodorum . Genes have been selected for analysis through a systematic process or based on published information. Functional analysis of these genes has been primarily conducted through targeted gene disruption and resulting mutants then tested for alterations in pathogenicity. The aim of this PhD candidature is to identify key metabolic weaknesses in S. nodorum to aid in facilitating the development of crop protection strategies.
Heterotrimeric G protein and MAPK signalling are critical pathogenicity factors in S. nodorum . The host of phenotypic defects and impaired virulence associated with gna1 and mak2 mutants present an attractive option to identify molecular effectors. It is hypothesised that alterations in the abundance or state of signalling effectors may be crucial in determining the outcome of development and virulence of S. nodorum .
Hence, the primary aim of this project is to use a proteomic approach to identify signalling effectors. Functional analysis of signalling effector genes via molecular
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genetics may provide a further understanding of the mechanism of signal transduction in the virulence of S. nodorum on wheat. Goals and experimental approaches are listed below.
1. Proteomic analysis of SN15 and signalling mutants. Identification of
Gna1 and Mak2 effector proteins at the sub cellular level.
2. Identification of differentially abundant protein spots via mass
spectrometry.
3. Transcript expression analysis of genes that corresponded to
differentially abundant proteins.
4. Targeted disruption of putative Gna1 and Mak2 regulated genes.
5. Analysis of mutants for alterations in pathogenicity.
6. Detailed phenotypic analysis of mutants using a variety of classical
plant pathology and molecular techniques.
7. Identification of potential antifungal targets.
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Chapter 2 - General materials and methods
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2.1 General solutions and buffers
50 x complete 20 g.L 1 bacto casamino acid (Difco) supplement (CS) 20 g.L 1 bacto peptone (Difco) 20 g.L 1 bacto yeast extract (Difco) 3 g.L 1 adenine 20 mg.L 1 biotin 20 mg.L 1 nicotinic acid 20 mg.L 1 p aminobenzoic acid 20 mg.L 1 pyridoxine 20 mg.L 1 thiamin Colloidal Commassie G250 17% (w/v) ammonium sulphate staining solution 0.1% (w/v) Coomassie G250 (Bio Rad) (Neuhoff et al. , 1988) 3% (v/v) phosphoric acid (Sigma) 34% (v/v) methanol Coomassie destaining solution 50% (v/v) acetonitrile 10 mM ammonium hydrogen carbonate Denaturation solution 0.5 M NaOH 1.5 mM NaCl DEPC treated water 1 mL diethyl pyrocarbonate (DEPC) (Sigma) To 1L with sterile deionised water Incubated at 37oC overnight prior to autoclaving Depurination solution 0.2 M HCl 4’,6 diamino 2 phenylindole, 10 mg DAPI (Invitrogen) dilactate (DAPI) stock (5 mg.mL 1) 2 mL sterile deionised water DIG Easy Hyb solution DIG Easy Hyb granules (Roche) Dissolve in 64 mL sterile deionised water Equilibration buffer I 6 M urea (Sigma) with dithiothreitol (DTT) 0.375 M Tris pH 8.8 (Invitrogen) 2% (w/v) SDS 20% (v/v) glycerol 2% (w/v) DTT (Sigma) Equilibration buffer II 6 M urea (Sigma) with iodoacetamide 0.375 M Tris pH 8.8 (Invitrogen) 2% (w/v) SDS 20% (v/v) glycerol 2.5% (w/v) iodoacetamide (Sigma) Formal acetic alcohol (Sass, 1958) 3.7% (v/v) formaldehyde
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5% (v/v) glacial acetic acid 47% (v/v) ethanol 10 x Ligation buffer 300 mM Tris Cl (pH 7.8) 100 mM MgCl 2 100 mM DTT 10 mM ATP Multiple surfactant solution (MSS) 40 mM Tris (Invitrogen) (Herbert, 1999) 2% (w/v) CHAPS (Sigma) (Herbert et al. , 1998) 2% (w/v) SB 3 10 (Sigma) (Rabilloud, 1998) 5 M Urea (Sigma) 2 M Thiourea (Sigma) 2 mM Tributylphosphine (Sigma) 0.2% (v/v) Bio Lyte 3 10 (Bio Rad) Neutralisation solution 1 M Tris pH 7.5 1.5 M NaCl 1 0.025 M phosphate buffer (pH 7.0) 3.55 g.L Na 2HPO 4 10 x Phosphate buffered saline 80 g.L 1 NaCl (PBS) 2 g.L 1 KCl 1 14.4 g.L Na 2HPO 4 1 2.4 g.L KH 2PO 4 Peptide extraction solution 50% (v/v) acetonitrile 5% (v/v) formic acid Peptide resuspension solution 5% (v/v) acetonitrile 0.1% (v/v) formic acid 2 x Rapid ligation buffer 60 mM Tris Cl (pH 7.8) 20 mM MgCl 2 20 mM DTT 2 mM ATP 10% polyethylene glycol Sorbitol, Tris, 1.2 M sorbitol and calcium chloride 10 mM CaCl 2 (STC) buffer 10 mM Tris HCl pH 7.5 20 x SSC 175 g.L 1 NaCl 88.2 g.L 1 tri sodium citrate SM buffer 0.1 M NaCl 8 mM MgSO 4.7H 2O 50 mM Tris Cl pH 7.5
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0.01% (w/v) gelatin Spurr’s resin 26 g Nonenyl succinic anhydride (ProSciTech) (Spurr, 1969) 10 g Vinyl cyclohexene dioxide (ProSciTech) 6 g Diglycidyl ether (ProSciTech) 0.4 g Dimethylaminoethanol (ProSciTech) Sterile salt homogenisation 0.4 M NaCl buffer (Aljanabi & Martinez, 1997) 10 mM Tris Cl pH 8.0 2 mM EDTA pH 8.0 Transformation solution 60% PEG 4000 (BDH, UK) 10 mM Tris pH 7.5 10 mM CaCl 2 10x Tris/glycine running buffer 30.3 g.L 1 Tris (Sambrook et al. , 1989) 144.0 g.L 1 glycine 10.0 g.L 1 SDS Trypan blue stain 50% (v/v) ethanol (Bruzzese & Hasan, 1983) 10 mL lactic acid (Shipton & Brown, 1962) 10 g phenol 16 mL 60% glycerol 10 mg trypan blue (Sigma) Trypsin solution 12.5 g.mL 1 trypsin (Roche) 10 mM ammonium hydrogen carbonate 2.2 Media
Benzimidazole agar 150 mg.L 1 benzimidazole (Benedikz et al. , 1981) (ICN Biomedicals) 5 g.L 1 agar (BBL) Czapek Dox V8 juice 45 g.L 1 Czapek Dox agar (Oxoid) complete supplement 200 mL.L 1 filtered V8 juice (Campbell's, (CzV8CS) medium Australia) 30 mM CaCO 3 1 x CS 200 g.mL 1 hygromycin B (Roche) if necessary 50 mg.L 1 phleomycin (InvivoGen) if necessary 10 g.L 1 agar (BBL) if necessary adjust to pH 6.0 with NaOH. CzV8 bottom protoplast agar 45.4 g.L 1 Czapek Dox agar (Oxoid) 1 M sorbitol 200 mL.L 1 V8 juice (Campbell’s, Australia)
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10 g.L 1 agar (BBL) adjust to pH 6.0 with NaOH. CzV8 top protoplast agar 45.4 g.L 1 Czapek Dox liquid (Oxoid) 1 M sorbitol 200 mL.L 1 V8 juice (Campbell’s, Australia) 7.5 g.L 1 agar (BBL) adjust to pH 6.0 with NaOH Luria Bertani (LB) medium 10 g.L 1 bacto peptone (Difco) 5 g.L 1 yeast extract (Difco) 10 g.L 1 sodium chloride 15 g.L 1 agar (BBL) if necessary 100 g.mL 1 ampicillin if necessary 25 g.mL 1 kanamycin if necessary 12 g.mL 1 tetracycline if necessary 0.5 mM IPTG if necessary 80 g.mL 1 X Gal if necessary Minimal medium (MM) 1 g.L 1 dipotassium hydrogen phosphate 2 g.L 1 sodium nitrate 1 x trace solution Carbon source (see text) 15 g.L 1 agar (BBL) if necessary adjust to pH 6.0 with HCl
SOC medium 20 g.L 1 bacto peptone (Difco) (Sambrook et al. , 1989) Top LB agar 10 g.L 1 bacto peptone (Difco) 5 g.L 1 sodium chloride 6 g.L 1 agarose Wheat meal agar 15 g.L 1 wheat meal 15 g.L 1 agar (BBL)
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2.3 General computational methods
2.3.1 Image analysis
Images were viewed and edited using Adobe Photoshop version 6.0 (Adobe,
USA) unless stated otherwise.
2.3.2 In silico DNA and protein sequence analysis
General DNA and protein sequence analyses were performed with Vector NTI suite (Invitrogen). Genome browsing was performed with ACNFPbrowse version 1.0.1
(Hane, Murdoch University). Phylogenetic trees were constructed using TREEVIEW
1.6.6 (Page, 1996) based on sequence alignments generated from CLUSTALW
(Thompson et al. , 1994). Analysis for N terminal signal peptide was performed with
SignalP 3.0 (Bendtsen et al. , 2004; Nielsen et al. , 1997; Nielsen & Krogh, 1998), cellular localisation prediction was performed with PSORT II (Horton & Nakai, 1997), identification of consensus motifs was performed with Motif Scan (Falquet et al. , 2002), secondary structure prediction was performed with 3D JIGSAW (Bates & Sternberg,
1999; Bates et al. , 2001), conserved domain prediction with CDD Blast (Marchler
Bauer et al. , 2007) and Blast analysis using the NCBI Genbank database (Altschul et al. , 1997).
2.3.3 Statistical analysis
Unless stated, all replicate numerical data were analysed with the JMP IN version 5.1 software (SAS Institute Inc. USA). Unpaired t test was used to test for significant differences between two groups of data. One way analysis of variance
(ANOVA) set for the Tukey Kramer test was used for multiple group comparisons that
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were greater than two. When stated, Dunnett’s test was used to analyse whether means are different from the mean of a control group. The sample was considered significantly different if p < 0.05.
2.3.4 Gene content in the Stagonospora nodorum genome
The S. nodorum genome was sequenced by the Broad Institute (Hane, manuscript in prep. ). Genewise, Fgenesh, Fgenesh+ and Geneid programs were used to predict for genes in the genome. This led to the identification of 16,597 putative genes.
These genes were designated with a “SNOG” prefix
(http://www.broad.mit.edu/annotation/genome/stagonospora_nodorum/Home.html).
2.4 Bacterial manipulation
2.4.1 Preparation of competent Escherichia coli cells
E. coli DH10b competent cells were prepared according to Inoue et al. (1990).
Briefly, cells from an original stock stored in 25% (w/v) glycerol in 80 oC were inoculated into 50 mL of LB broth. Cells were allowed to grow overnight at 37 oC in a
Certomat R shaker set at 225 rpm. Following this, 20 mL of the overnight culture was inoculated into 500 mL of SOC broth and shaken at 180 rpm in 37 oC until the cell density (OD 600nm ) reached 0.68. All competent cell preparation work from here on was performed at 4 oC. Cells were pelleted by centrifugation at 5,000 g for 10 min.
Following this, the cell pellet was resuspended and washed twice in sterile ice cold water and once with 10 mL of sterile ice cold 10% (w/v) glycerol. The pellet was then resuspended in three mL of 10% (w/v) ice cold glycerol and partitioned into 50 L aliquots. This was then immersed into liquid nitrogen and stored at 80 oC until use.
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2.4.2 Bacterial transformation
Bacterial transformation was performed as described by Inoue et al. (1990).
Competent cells were thawed on ice prior to transformation with plasmid DNA. The appropriate plasmid was mixed with the cell suspension and was left on ice for five min.
Transformation was performed via electroporation using a Bio Rad electroporation device set at 200 , 25 F, and 2.5 V. The competent cells were allowed to recover in one mL of LB broth shaking at 225 rpm in 37 oC for one h prior to selection on LB agar with the appropriate antibiotics in 37 oC overnight.
2.5 DNA manipulation
2.5.1 Genomic DNA extraction
Genomic DNA extraction was performed using two methods. For the use of quantitative real time PCR (qRT PCR) and Southern blotting, genomic DNA was auto extracted using a Retsch MM301 autolyser and Qiagen BioSprint 15. For PCR screening, genomic DNA was extracted according to the method described by Aljanabi
& Martinez (1997) with modifications. Briefly, mycelia were harvested in an 1.5 mL
Eppendorf tube and ground with a mortar and pestle in 400 L of sterile salt homogenisation buffer. Following this, 80 L of 10% (w/v) SDS and 160 g of proteinase K (Promega) was added to the homogenate. The mixture was incubated at
65 oC for one h followed by the addition of 300 L of saturated NaCl solution. Cellular debris was removed via centrifugation at 10,000 g for 30 min. The supernatant carrying genomic DNA was retained and precipitated with an equal volume of isopropanol in
20 oC for one h. The DNA was pelleted by centrifugation, washed in 70% ethanol and
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aspirated. Finally, the DNA pellet was resuspended in 300 to 500 L of sterile deionised water.
2.5.2 Plasmid DNA isolation
Plasmid DNA extractions from E. coli were carried out using the Wizard Plus
SV Minipreps kit according to the manufacturer’s instruction (Promega, Madison) to obtain pure plasmid for cloning and DNA sequencing.
2.5.3 DNA purification and elution from agarose gel
DNA was eluted and purified using an Ultraclean 15 DNA Purification Kit according to the manufacturer (MO BIO, California).
2.5.4 DNA cloning
The cloning of gel eluted PCR amplified fragments with an A overhang was performed with a pGEM T Easy Vector kit according to the manufacturer (Promega,
Madison). Sub cloning of restriction enzyme generated DNA fragments for gene recombination and the construction of gene knockout vectors was performed using pBSK phleo (supplied by Dr. Peter Solomon, see Appendix A). The ligation reaction consisted of one L of 10 x ligase buffer, 100 ng of pBSK phleo (or sub clones), one
Weiss unit of T4 DNA ligase and insert fragment to a molar ratio of 3:1 insert:vector.
The reaction volume was made up to 10 L with sterile deionised water. The ligation reaction was performed at room temperature for one h prior to transformation into E. coli DH10b vector described below. E. coli transformants were selected on LB agar
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with ampicillin. Restriction fragment length polymorphism and PCR were used to screen for colonies carrying the correct insert.
2.5.5 Restriction enzyme digestion of DNA
DNA was digested with restriction enzymes purchased from Promega
(Madison). Each reaction was performed in a 15 L volume unless stated otherwise.
The content of a restriction digest contained 1.5 L of reaction buffer, 1.5 L of 10 x bovine serum albumin (BSA), five units of restriction enzyme and DNA. Sterile deionised water was used to make up the reaction volume. Reactions were performed at
37 oC for one h unless stated otherwise.
2.5.6 Polymerase chain reaction (PCR)
PCR reactions were routinely performed in a 20 or 50 L volume containing a variable amount of DNA, one M of forward and reverse primers (Geneworks,
Australia), 0.2 L of Taq polymerase (Promega, Madison), and 0.2 mM dNTPs
(Promega, Madison) and 1 x Taq PCR polymerisation reaction buffer (Promega,
Madison) equivalent to 10 mM Tris HCl pH 9.0, 50 mM KCl, 0.1% Triton X 100.
Thermocycling reactions were performed as follows: at 95 oC (two min) followed by 35 to 40 cycles of 95 oC (one min) denaturation, 55 60 oC annealing (one min), 72 oC (two min) amplification followed by a final 72 oC (five min) extension, and a final 14 oC hold.
Perkin Elmer GeneAmp PCR System 2400 and Eppendorf Mastercycler ep thermocyclers were used for reaction amplification. The annealing temperature is primer dependent. PCR amplification of DNA fragments above one kb was performed with TaKaRa Ex Taq (Takara Bio. Inc., Japan).
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2.5.7 DNA electrophoresis on agarose gel
DNA was electrophoresed in a horizontal gel apparatus (Bio Rad). The DNA sample was mixed with 6 x DNA loading buffer (Promega, Madison) prior to loading onto the agarose gel (Progen, Queensland). The gel was run in 1 x TAE gel electrophoresis buffer at 70 to 100 V unless stated otherwise. The agarose gel was stained with 0.5 g.mL 1 ethidium bromide for 30 min prior to visualisation of DNA under UV light with a Bio Rad Gel Doc 1000. Gel images were captured with
Molecular Analyst (Bio Rad).
2.5.8 Southern blotting
Gene copy number and the verification of a successful gene knockout were determined by a Southern analysis. Genomic DNA (10 g) was digested with the appropriate restriction enzyme in a 300 L reaction overnight. This was concentrated down to a 40 L volume via isopropanol precipitation and loaded on a large format horizontal gel electrophoresis apparatus (Bio Rad). The digested DNA was allowed to run overnight at 20 mA in a 0.7% (w/v) TAE gel. The DNA was transferred to
Hybond N+ nylon membrane (Amersham Pharmacia Biotech, Sweden) using a
VacuGene XL vacuum blotting system (Amersham Pharmacia Biotech, Sweden).
Firstly, the agarose gel containing digested DNA was loaded onto the apparatus and set at 50 mbar vacuum. Fifty mL of 0.2 M HCl was immediately poured onto the gel to allow for depurination. The solution was discarded after 20 min and denaturation solution was applied to the gel and removed after a further 20 min. This process was repeated with 50 mL neutralisation solution. The DNA was transferred in 20 x SSC for
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one h. The membrane was washed in 5 x SSC, blotted dry and the DNA was fixed by
UV irradiation at 150 mJ with a Bio Rad GS Gene Linker.
2.5.9 DNA probe labelling
The labelling of DNA probe and Southern hybridisation was carried out with a
Digoxigenin (DIG) High Prime DNA Labelling and Detection Starter Kit 2 (Roche,
Mannheim). The DNA probe was created by random priming. This involved incubating one to two g DNA with one L of DIG High Prime solution (consists of
Klenow polymerase, DIG UTP, dNTP, and random primers) at 37 oC overnight in a 20
L reaction volume. The labelling reaction was terminated by adding two L 0.2 M
EDTA. Labelling efficiency was determined according to the manufacturer’s instruction (Roche). After this, the freshly labelled probe was denatured at 95 oC for five min and snap chilled in ice for a further five min. Prior to hybridisation, the freshly labelled probe was added to 10 mL prehybridisation solution and filtered through a 0.45
m filter (Millipore). Previously used probes were denatured at 70 oC prior to hybridisation.
2.5.10 DNA probe hybridisation
Prior to Southern hybridisation, the nylon membrane containing genomic DNA of interest was prehybridised in DIG Easy Hyb solution for one h at 42 oC. The prehybridisation solution was removed and the denatured DNA probe (25 ng.mL 1 DIG
Easy Hyb) was then added to the membrane and was allowed to hybridise at 42 oC overnight. Following this, excess probes were removed and hybridisation was carried out by stringency washes at 65 oC with 0.5 x SSC, 0.1% (w/v) SDS. The hybridised
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probe was immunologically labelled and detected via CDP Star chemiluminescent substrate (Roche, Mannheim) upon exposure to Lumi film (Boehringer Mannheim,
Indianopolis) overnight. This was then developed in a Fuji X ray film processor FPM
3000.
2.6 RNA manipulation
2.6.1 RNA isolation
RNA isolation was carried out with the TRIzol ® reagent (GibcoBRL) according to the manufacturer's instruction. Briefly, freeze dried mycelia in a 1.5 mL Eppendorf tube was homogenised in one mL of TRIzol with a mortar and pestle. The homogenate was allowed to stand for five min at room temperature prior to the addition of 200 L of chloroform and was vigorously mixed by brief shaking. The mixture was allowed to stand for three min at room temperature before centrifugation at 12,000 g for 15 min at
4oC. Following this, the white aqueous top phase was retained and re extracted twice in
TRIzol. RNA was precipitated with 500 L of isopropanol and the pellet was washed in 75% ethanol. The RNA pellet was aspirated and resuspended in 50 L of sterile
DEPC treated water. The resuspended RNA was DNase treated with DNA free ™ reagent (Ambion) to remove carry over DNA.
2.6.2 First strand cDNA synthesis
First strand cDNA was synthesised with an iScript ™ cDNA synthesis kit (Bio
Rad) according to the manufacturer's instructions. The first strand synthesis reaction was performed in a 20 L volume containing one g of total RNA, 1 x iScript reaction mix and one L of iScript reverse transcriptase. The reaction was carried out at 25 oC
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for five min, 42 oC for 30 min and 85 oC for five min in an Eppendorf Mastercycler ep thermocycler. The first strand DNA was kept at 20oC until required.
2.6.3 Quantitative real-time polymerase chain reaction (qRT-PCR)
Gene transcript abundance was analysed with qRT PCR. The reaction consisted of 10 L iO SYBR R Green Supermix (Bio Rad), 500 nM of forward and reverse primers and five L of a 1:10 to 1:70 dilution of the DNase treated RNA sample in a 20
L reaction volume. Primers used for the experiment are listed in Appendix B. Actin
(SNOG_01139.1) or elongation factor 1 α (EF1 α; SNOG_11663.1) were used as constitutively expressed gene controls for expression normalisation. SN15 genomic
DNA was used as a standard at 25, 7.5, 2.5 and 0.75 ng per reaction. The thermocycling reaction was performed in a Rotor Gene RG3000 (Corbett Research,
Australia) as follows: 95 oC (3 min) followed by 40 cycles of 94 oC (10 s) denaturation,
57 oC (20 s), 72 oC (30 s) extension. The sample spectrum was acquired using 470 nm excitation filter and detected at 510 nm with a gain of +5. Rotor Gene 6 (Corbett
Research, Australia) software was used to analyse the data. All reactions were performed in duplicate.
2.7 Determination of nucleic acid concentration
DNA and RNA concentrations were determined spectrophotometrically using a
NanoDrop DN 1000 or a Perkin Elmer Lambda 25 UV/VIS spectrophotometer measuring at a wavelength of 260 nm. An OD 260nm reading of 1.00 is equivalent to a concentration of 50 g.mL 1 DNA or 40 g.mL 1 RNA (Sambrook et al. , 1989).
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2.8 Manipulation of Stagonospora nodorum
2.8.1 Growth and maintenance of Stagonospora nodorum
Stagonospora nodorum SN15 (obtained from Department of Agriculture,
Western Australia) was routinely maintained on CzV8CS agar medium, and was used throughout the study as the wild type strain. The fungus was left to grow at 20 oC in a
12 h dark/12 h near UV light cycle to induce pycnidiation. All other S. nodorum strains were grown in a similar manner.
2.8.2 Pycnidiospore isolation
Pycnidiospores were harvested from agar plate cultures by flooding with five mL of sterile deionised water followed by gentle scrapings of the mycelial surface.
Flooded plates were left to stand for 10 min to allow spore resuspension prior to collection. This step was repeated with an additional seven mL of sterile deionised water. The spore suspension was filtered through a 20 mL syringe (Terumo) partially filled with sterile glass wool to remove mycelial debris. Spores were then pelleted by centrifugation at 5,000 g for 10 min. The spore pellet was washed and resuspended in sterile deionised water.
2.8.3 Preparation of fungal glycerol stock
All S. nodorum strains were stored in 80 oC as spores or scraped mycelia in 20%
(w/v) glycerol.
2.8.4 Preparation of fungal protoplasts
Protoplast preparation was performed according to Solomon et al. (2004b).
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Briefly, spores (5 x 10 8) were inoculated into a conical flask containing 100 mL of
CzV8CS broth and incubated in the dark overnight in a Certomat R shaker (Braun) at
170 rpm. The mycelial suspension was harvested by centrifugation at 7,500 g for 10 min at 4 oC. The resulting supernatant was discarded and the mycelia were resuspended and washed with 50 mL of 600 mM MgSO 4. Following this, the washed mycelia was resuspended in 25 mL of 1.2 M MgSO 4 buffered to pH 5.8 with 10 mM K 2HPO 4 containing 15 mg.mL 1 Glucanex (Novo Nordisk, Switzerland). The solution was transferred to a sterile glass petri dish and incubated at 28 oC for two h. The solution was transferred to a 50 mL centrifuge tube and overlaid with five mL of solution containing 600 mM sorbitol and 10 mM Tris pH 7.5. Following centrifugation at 4,000 g for 25 min at 4 oC, the resulting protoplast layer located within the interface was removed and resuspended in an equal volume of a solution consisting of one M sorbitol and 10 mM Tris pH 7.5. The mixture was centrifuged at 1,530 g for five min to obtain a protoplast pellet. This pellet was then washed and resuspended in STC buffer.
2.8.5 Fungal transformation
Fungal transformation was performed as described by Solomon et al. (2004b).
Briefly, the procedure was performed by mixing 2.5 x 10 7 to 1 x 10 8 protoplasts with
6.75 to 8.85 g knockout vector generated by PCR amplification. The reaction volume was made up to 125 L with STC buffer and was allowed to incubate at room temperature for 20 min. After incubation, 200 L of the transformation solution was added to the STC mixture. This was mixed by inversion and incubated for five min before a further 200 L transformation solution was added and mixed. Following incubation for five min, a final 800 L was added and mixed. The mixture was
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aliquoted out as 300 L portions into five mL top protoplast CzV8 agar, mixed, and poured onto CzV8 protoplast agar medium. The protoplasts were incubated in the dark at 22 oC for 24 h before being covered with five mL top protoplast CzV8 agar containing phleomycin. This was incubated in the dark for one week to allow the transformed protoplasts to develop.
Transformed colonies were randomly selected and plated out onto CzV8Cs agar containing phleomycin. These were then incubated under near UV light for a week or until mature pycnidia were present. Transformants were then further purified by single spore isolation. This was performed by harvesting pycnidiospores with a fine wire and resuspended in sterile deionised water. The suspension was diluted so that 100 L of this suspension carrying 100 spores were plated onto CzV8CS agar with phleomycin and incubated for four days under near UV light.
2.8.6 Fungal growth assay
Fungal growth assays in minimal medium (MM) broth were performed in a 96 well microtitre plate (Solomon et al. , 2006c). Briefly, each well composed of 200 L
MM broth containing 25 mM of the appropriate carbon source. The well was inoculated with 10,000 spores or sterile deionised water as a negative control and the absorbance was measured with a Beckman Coulter DTX 880 Multimode Detector at a wavelength of 595 nm. The microtitre plate was then wrapped and incubated in the dark at 20 oC. A second absorbance reading was taken after seven days. The net growth was calculated from the subtracting the absorbance value at day 0 with the second reading. The assay was performed in biological duplicate.
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2.9 Wheat manipulation
2.9.1 Growth and maintenance of Triticum aestivum (cv. Amery)
Wheat Triticum aestivum (cv. Amery) was routinely grown in 10 cm pots containing Perlite (P500) and grade two vermiculite (The Perlite and Vermiculite
Factory, Australia) for two weeks at 20 oC in a 12 h light/dark cycle prior to manipulation. For the detached leaf assay (DLA), 10 cm pots were seeded with 40 seeds whereas whole plant spray experiments required 10 seeds per pot.
2.9.2 Detached leaf assay
The ability of fungal mutants to proliferate within the host tissue from a single point inoculation was assayed on the first true leaf from two week old wheat seedlings
(cv. Amery) using a DLA method modified from those described by Benedikz et al.
(1981). Two cm of the detached wheat leaves distal end was removed. The next four to five cm portion was embedded onto benzimidazole agar adaxial side up. The detached leave was challenged with 5 x 10 3 spores in 0.02% (v/v) Tween 20 or small mycelial agar plugs (~one mm on all sides). This was allowed to incubate in a 12 h light/dark cycle at 25 oC to enable disease development. The size of the lesion was measured with a caliper.
2.9.3 Whole plant spray
Whole plant spray infection was performed as described by Solomon et al.
(2005a). Each treatment consisted of two week old wheat plants (cv. Amery), which were sprayed with 1.3 x 10 7 spores in 0.02% (v/v) Tween 20 using an airbrush (Paasche
Airbrush Co., USA). Each treatment was performed in eight replicate pots unless stated
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otherwise. After spraying, treated plants were covered in darkness for two days and incubated at 20 oC prior to growth under the normal growth condition for a further five days. Infection symptoms were given on a scale of 0 to 10 based on visual scoring. A score of 0 indicates no disease symptoms were observed whereas a score of 10 indicates that the plant is completely necrotic.
2.9.4 In planta sporulation assay
Sporulation assays were performed on infected plant material. For infected detached leaf assays, 14 day old infected leaves were harvested and submerged in one mL of sterile deionised water for one h with gentle inversions to collect spores. Wheat leaves were removed and spores were collected by centrifugation at 5,000 g. Spores were then resuspended in 50 to 300 L of sterile deionised water and counted with a haemocytometer. For whole plant sprays, five cm portions of the first true leaf were harvested seven days post infection and embedded onto benzimidazole agar. Pycnidia and spores were left to develop for five days in a 12 h light/dark cycle at 25 oC before spore harvesting and quantification.
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Chapter 3 - Identification of G ααα protein-regulated
effector proteins in Stagonospora nodorum by
proteomics
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3.1 Introduction
The heterotrimeric G protein is a signalling component common to eukaryotic organisms. In the mammalian system, heterotrimeric G protein signalling regulates metabolic enzyme activity, ion channels, secretory machineries, embryo development, steroid production and carbohydrate metabolism (Neves et al. , 2002). In other biological systems, hetetrotrimeric G protein signalling is responsible for cell division in arthropods (Afshar et al. , 2004; Fuse et al. , 2003), pheromone response in yeast
(Blumer & Thorner, 1991) and chemotaxis in the slime mould Dictyostelium discoideum (Kimmel & Parent, 2003). Recent genetic evidence on the model plant
Arabidopsis thaliana indicates that heterotrimeric G protein signalling plays important roles in plant development and defence against fungal pathogens (Lease et al. , 2001;
Trusov et al. , 2006). Heterotrimeric G protein signalling regulates development and virulence in many plant pathogenic fungi (Chapter 1). These examples illustrate the functional diversity of heterotrimeric G protein signalling in eukaryotic organisms.
Hence it is considered that heterotrimeric G protein regulates a plethora of signalling effectors that may participate to maintain cellular function (Komatsu et al. , 2005; Neves et al. , 2002).
A Gα subunit gene Gna1 (SNOG_10086.1) of S. nodorum was functionally disrupted by Solomon et al. (2004b) and mutants were reduced in pathogenicity and demonstrated developmental impairments (Chapter 1). It is hypothesised that these impairments are a result of changes in the state and/or abundance of signalling effectors of Gna1 . Recent studies have used global transcriptomic approaches to further dissect heterotrimeric G protein signalling in plant pathogenic fungi (Andrews et al. , 2004;
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Dawe et al. , 2004; Eichhorn et al. , 2006; Garcia Pedrajas & Gold, 2004; Gronover et al. , 2004; Larraya et al. , 2005). In this study, a comparative proteomic approach was used to analyse S. nodorum SN15 and a gna1 mutant (gna1-35 ) for alterations of protein abundance at the sub cellular level.
3.2 Methods
3.2.1 Fungal growth conditions and harvesting method
Fungal strains were grown on CzV8CS agar plates for two weeks prior to harvest by mycelial scraping. Approximately 100 to 150 mg of mycelia was inoculated into a conical flask containing 100 mL of MM broth supplemented with glucose to a final concentration of 3% (w/v). The fungus was allowed to grow in the dark at 22 oC in a Braun shaker set at 150 rpm for three days. The fungus was harvested using cheese cloth filtration, rinsed with sterile water, immersed in liquid nitrogen and freeze dried overnight (Heto MAXI dry lyo freeze dryer). For extracellular protein analysis, the fungus was grown in a similar manner except that 10 mM glutamate was used as a carbon and nitrogen source.
3.2.2 Protein extraction and solubilisation
3.2.2.1 Soluble intracellular fraction
Freeze dried mycelia were homogenised in liquid nitrogen cooled mortar and pestle with five mL of 10 mM Tris pH 7.6 with one mM phenylmethylsuphonylfluoride
(PMSF) (Sigma). Glass beads (106 micron) (Sigma) were used to assist tissue grinding.
The crude homogenate was collected and centrifuged at 20,000 g for 1 h at 4 oC. The
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resulting supernatant was retained and incubated with 20 units of DNase (Sigma) and 20 units of RNase (Sigma) for 1 h at room temperature to degrade nucleic acids.
Following this, proteins were precipitated with nine volumes of 100% analytical grade methanol at 80 oC overnight. Precipitated proteins were collected by centrifugation at
4,000 g for 15 min at 4oC followed by two washes in 50 mL of 90% ice cold methanol.
The protein pellet was air dried for one h. Protein solubilisation step involved the addition of 300 to 600 L MSS buffer to the protein pellet followed by sonication with a probe tip Misonix Sonicator XL2015 with an output of 95 W and a 25%.s 1 pulsar duty cycle. This step was performed with the sample tube placed on ice to avoid sample overheating. Following this, the protein sample was continuously mixed with an
Eppendorf Thermomixer comfort for one to two h to aid protein solubilisation.
Insoluble proteins were collected and removed by two rounds of centrifugation at
20,000 g for 15 min at room temperature. The resolubilised protein in MSS buffer was stored at 80 oC until required.
3.2.2.2 Soluble extracellular fraction
Cell free supernatant was obtained by filtering the fungal broth in cheese cloth to remove substantially grown mycelia. The crude supernatant was filtered through a
Millipore 0.22 m membrane to further remove cellular debris. Protein in the filtered supernatant was precipitated with the addition of trichloroacetic acid (TCA) to a final concentration of 5% (w/v). The TCA/supernatant mixture was left to precipitate for two h at 4 oC under constant agitation. The precipitated protein was pelleted by centrifugation at 4,000 g for 15 min and washed three times with ice cold 80% acetone.
The protein pellet was aspirated at room temperature for 30 min prior to solubilisation
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in MSS buffer without sonication. The resolubilised protein was stored at 80 oC until required.
3.2.3 Determination of protein concentration
Protein concentration was determined using the bicinchoninic acid (BCA)
(Smith et al. , 1985) or RC-DC Lowry kit (Bio Rad). Firstly, the BCA method was performed by combining one mL solution containing 2% CuSO 4 and 98% BCA (Sigma,
St Louis) with 50 L of diluted crude protein extract. This was incubated at 37 oC for one h to enable the reduction of Cu 2+ to Cu 1+ by the peptide bonds of proteins. BCA chelates Cu 1+ , thus forming a purple complex which was measured spectrophotometrically at OD 562 nm . A standard curve was constructed from a serial dilution of one mg.mL 1 BSA (Sigma, St Louis) with sterile deionised water.
Protein samples derived from the MSS solubilisation require concentration determination with a RC-DC Lowry kit. This was performed according to the manufacturer's instruction with recommended modifications. Briefly, 25 L of the crude protein extract (diluted in MSS if necessary) was mixed by vortexing with 125 L
RC reagent I reagent. This was left to stand for one min prior to the addition of 125 L of RC reagent II to precipitate the protein. The mixture was vortexed and centrifuged at
15,000 g for five min. The protein pellet was then washed with 500 L R C reagent I and 160 L R C reagent II. The pellet was resuspended in 127 L reagent consisting of
2.5 L of DC reagent S and 124.5 L of DC reagent A and incubated at room temperature for five min. Colourimetric analysis was performed by adding one mL of
DC reagent B and incubating at room temperature for 15 min prior to OD 750 nm reading.
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Protein concentration was determined from a standard curve constructed from determining the BSA absorbance at concentrations from 0.3 to 1.5 g. L 1.
3.2.4 SDS polyacrylamide gel electrophoresis
Crude protein extracts were routinely examined for quality with SDS PAGE prior to further manipulation. SDS PAGE was performed in a discontinuous system using a 4% (w/v) stacking/12% (w/v) resolving acrylamide/bisacrylamide gel
(Laemmli, 1970). Electrophoresis was performed with a mini Bio Rad Protean III apparatus set at 80 V for 10 min followed by 120 V until the bromophenol dye front reached the end of the gel.
3.2.5 First dimension protein separation via IEF
First dimension isoelectric focusing was used for separating proteins based on their isoelectric point. This was performed using seven cm linear immobilised pH gradient (IPG) acrylamide strips (Bio Rad). Typically, 100 g to 300 g of protein solubilised in MSS buffer was loaded into pH 5 8 linear IPG strips and rehydrated at 50
V in a Protean IEF Cell (Bio Rad) for 16 to 20 h. Intracellular protein samples were focused in the same apparatus programmed for rapid ramping, 250 V for 15 min, 14,000
V h and held at 500 V after focusing. Strips were covered with mineral oil during rehydration and IEF to prevent sample evaporation. Extracellular protein samples were focused as described above with the following exceptions: 1. The focusing condition was set at 12,000 V h and 2. pH 3 10 linear IPG strips were used.
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3.2.6 Second dimension protein separation via SDS-PAGE
Second dimension electrophoresis separates proteins by size. Excess mineral oil was removed from the focused IPG strip by draining. Proteins in the IPG strip were reduced and alkylated in equilibration buffer I and II containing DTT and iodoacetamide respectively, for 20 min each. The equilibrated strip was placed onto a
12% SDS polyacrylamide gel and sealed with 0.5% (w/v) agarose made from 1 x
Tris/glycine running buffer with a trace of bromophenol blue as a tracking dye.
Electrophoresis was performed with a mini Bio Rad Protean III apparatus set at 80 V for 30 min followed by 120 V until the bromophenol blue dye front has reached the end of the gel.
3.2.7 Protein visualisation
Protein gels were visualised via colloidal Coomassie G250 staining (Neuhoff et al. , 1988). After electrophoresis, the polyacrylamide gel was stained overnight in colloidal Coomassie G250 stain. Following this, the gel was destained in several washes of 0.5% (v/v) phosphoric acid to attain a sufficiently clear background for visualisation.
3.2.8 Gel image acquisition and analysis
Gel image was captured using ProXPRESS densitometry scanner (Perkin Elmer) and visualised with ProFinder (Perkin Elmer). Scanning parameters for the ProFinder software were set for a resolution of 100 microns, using bottom illumination and an emission wavelength spectrum of 530 nm. Image acquisition was carried out using an exposure time of three s after a flatfield has been established. Following this, spot
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detection and analysis was performed by eye in conjuction with the ProGENESIS
Workstation 2005 software (Perkin Elmer and Linear Dynamics). Replicate 2D gels were used to create average gels of SN15 and gna1-35 for comparisons. Software parameters as follows: background subtraction was set at the "ProGENESIS background" option, spots were manually matched and volume normalisation was performed using the "total spot volume" option. Matching protein spots from SN15 and gna1-35 were considered differentially abundant if the normalised densitometry values were significantly different according to an unpaired t test (p < 0.05) with an average of
> two fold difference. Experiments were performed in biological triplicate.
3.2.9 LC-MS/MS analysis and database searching
Tryptic peptides were analysed by liquid chromatography tandem MS (LC
MS/MS) as described by Taylor et al. (2005). Briefly, selected protein spots were subjected to in gel trypsin digestion. Tryptic digests were analysed on an Agilent 1100 series capillary LC system coupled to an Applied Biosystems QSTAR Pulsar i LC
MS/MS system equipped with the IonSpray source in positive ion mode. Data produced by this method were used for searching the Mascot search engine (Matrix
Sciences) for protein identifications. The CID data from each sample were exported from Analyst QS using a purpose built script obtained from Matrix Sciences (this script centroided the survey scan ions (TOF MS) at a height percentage of 50% and a merge distance of 0.1 amu (for charge state determination), centroided MS/MS data at a height percentage of 50% and a merge distance of two amu, reject a CID if less than 10 peaks, discarded ions with charge equal and greater than 5+). Search parameters at Mascot employed a peptide tolerance of ± two Da and MS/MS tolerance of ± 1.2 Da, no
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variable modifications, allow up to one miss cleavage for trypsin digest and the instrument type was set to ESI QUAD TOF. Searches were performed against a custom database built from an in house set of ESTs from S. nodorum (1,772 sequences derived from infected plant materials, growth on cell wall and oleate) and predicted genes in the genome of S. nodorum (Broad Inst., Massachusetts). Function was assigned to the matched protein by BlastP homology search of the NCBI non redundant protein database. An expected value cut off score of 10 8 was applied to all NCBI non redundant searches. The Blast2GO software (http://www.blast2go.de ) was used to obtain gene ontology information for all genes under default settings (Conesa et al. ,
2005). The FunCat database (http://mips.gsf.de/projects/funcat ) was used to assign functional categories based on significant gene ontology matches of each gene (Ruepp et al. , 2004).
3.2.10 Enzymatic assay for mannitol dehydrogenase activity
Protein fractions of SN15 and gna1 35 were assayed for mannitol dehydrogenase activity according to Noeldner et al. (1994). Briefly, freeze dried mycelia were ground to a fine powder under liquid nitrogen using a mortar and pestle.
The ground material was resuspended in 10 mM Tris Cl pH 7.6 supplemented with 10 mM PMSF. The crude protein extract was desalted on a PD10 Sephadex column according to the manufacturer’s instructions (Amersham). To measure the activity of mannitol dehydrogenase, a reaction mixture was made up to one mL with 50 mM Tris
Cl (pH 7.6) containing 0.25 mM NADPH, 50 L of desalted protein extract and 0.8 M fructose to start the reaction. Mannitol dehydrogenase activity was measured at
+ OD 340nm to observe the conversion of NADPH to NADP . The assay was performed at
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30 oC. Specific activity of the enzyme was determined as activity per mg of total protein.
3.2.11 Signal peptide analysis
Polypeptide sequences were analysed for N terminal signal peptides with the software prediction engine SignalP 3.0. Positive signal peptide prediction was scored on the basis of agreement between the neural network (NN) and hidden Markov model
(HMM) prediction algorithms trained on eukaryotic protein sequences.
3.2.12 Statistical analysis of transcript abundance
Quantitative RT PCR was performed as described in Chapter 2. Analysis of gene expression was performed from transcripts extracted under a similar in vitro growth condition used for protein extraction for proteomic analysis. The expression of each gene was normalised and correlated with protein abundance data to identify possible correlations. To keep statistical analysis consistent with the model set for protein abundance, gene expression between SN15 and gna1-35 was deemed differentially abundant if the normalised transcript abundance values were significantly different according to an unpaired t test (p < 0.05) with an average of > two fold difference. The expression of putative Gna1 regulated genes was also examined during
SN15 infection on wheat. One way ANOVA set for Tukey Kramer analysis was performed in conjunction with a Dunnett’s control group for statistical analysis. Gene expression was considered significantly different if p < 0.05 with an average of > two fold difference of the normalised transcript abundance of each time points relative to the
Dunnett’s control group.
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3.3 Results
3.3.1 The determination of extracellular pH
Prior to protein isolation, extracellular supernatants of SN15 and gna1-35 were checked for pH to ensure that the growing condition remains similar for both strains.
The average extracellular pH of SN15 and gna1-35 was 8.1 and 8.2 (n = 3), respectively. This was not statistically different.
3.3.2 Assaying for cytoplasmic contamination in the extracellular protein fraction
The extracellular and intracellular protein fractions of SN15 and gna1-35 were assayed for the cytoplasmic enzyme marker mannitol dehydrogenase. No mannitol dehydrogenase activity was detected in the extracellular proteome fraction (Table 3.1).
This indicates that intracellular protein contamination in the extracellular protein fraction is negligible.
3.3.3 Comparative extracellular proteome analysis
The extracellular proteomes of SN15 and gna1-35 were analysed for changes in protein abundance using 2D gel electrophoresis. A total of 189 unique protein spots were identified from SN15 and gna1-35 . Of these, 25 (13.2%) spots were considered differentially abundant by ProGENESIS (Figure 3.1; Appendix C). Of these changes,
17 protein spots were reduced in abundance in gna1-35 whereas eight showed increase in abundance. LC MS/MS was used to obtain peptide spectra and the resulting data were matched against the S. nodorum predicted protein set to find the matching genes
(Table 3.2; Appendix D).
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3.3.4 Comparative intracellular proteome analysis
The intracellular proteomes of SN15 and gna1-35 were methanol extracted from mycelia grown in MM broth supplemented with glucose and separated via 2D gel electrophoresis (Figure 3.2). A total of 475 unique protein spots were identified from
SN15 and gna1-35 . Of these, six (1.3%) spots were deemed differentially abundant by
ProGENESIS (Figure 3.2; Appendix E). Of these changes, five spots were significantly less abundant in gna1-35 whereas one spot showed increase in abundance. LC MS/MS was used to obtain peptide spectra and the resulting data were matched against the S. nodorum predicted protein set to find the matching gene (Table 3.3; Appendix D).
3.3.5 Functional classification of differentially abundant proteins
Thirty one spots were identified. Of these, 22 spots were decreased and nine spots were increased in abundance in gna1-35 . Twenty two genes were identified from these protein spots. These genes were divided into five functional categories based on the FunCat classification scheme of gene ontology predictions (Table 3.4). Fourteen genes did not receive a functional assignment and hence were classified as FunCat unassigned genes. These genes encode a putative Concanamycin C induced protein
(CipC ), a glutathione S transferase 2 ( Gst2), short chain dehydrogenases, tyrosinase, cell wall glucanase, vacuolar targeting protein, tyrosinase/oxidase and unknown
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Figure14 Enzymatic assay for mannitol dehydrogenase (Table 3.1)
Table 3.1. Enzymatic assay for the cytoplasmic enzyme mannitol dehydrogenase in protein fractions of SN15 and gna1-35 .
Specific activity of mannitol dehydrogenase (nmol NADPH -1.min -1.mg protein -1) Strain Extracellular fraction Intracellular fraction SN15 0 383.1 gna1-35 0 394.4
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A 3 pH 10 15Extracellular kDa 2D proteome gels of SN15 and gna1-35 (Figure 3.1) 250
75
50 E2 E3 E4 E1 37 E13 E14 E12 E8 E9 E7 E5 E15 25 E6 E11 E10 E16 E18 E17
E19 15 E21 E20 E23 E24 E22 E25
B
250
75
50 E2 E3 E4 E1 E13 E14 E8 E9 37 E12 E5 E7
E15 E6 E11 E10 25 E16 E18 E17
E19 15 E21 E20 E23 E24 E25 E22
Figure 3.1. Representative 2D gels of A. SN15 and B. gna1-35
extracellular proteomes. Differentially abundant spots are indicated.
83 Chapter 3 .
Figure16Differentially abundant extracellular protein spots of SN15 and gna1-35 (Table 3.2)
Table 3.2. Identification of differentially abundant extracellular proteins with LC MS/MS. Mascot was used to pattern matched the mass spectrometry data with the S. nodorum whole genome annotated protein set to give a gene match. Fold difference of matching protein spots was calculated from normalised spot value of SN15 relative to gna1-35 . Fold difference designated by ( ) indicates protein spots that were not observed in gna1-35 proteome gel whereas (++) designate spots that were not observed in the SN15 proteome gel. Molecular weight
(MW) is given in kDa. BlastP identity and E value are given in Appendix D. Continued on the next page.
Spot Fold Observed Broad acc Theoretical BlastP functional match (organism; Genbank acc ID) Mascot score diff (% coverage) pI MW ID pI MW E1 4.4 5.65 33.1 SNOG_00656.1 6.14 36.7 Putative vacuolar targeting protein ( Candida albicans ; 215 (25.6) XP_711465.1) E2 6.73 38.0 SNOG_11078.1 6.06 37.8 Hypothetical protein (NmrA like domain) ( Gibberella zeae ; 832 (54.1) XP_384929) E3 6.90 37.6 SNOG_11078.1 6.06 37.8 Hypothetical protein (NmrA like domain ) ( Gibberella zeae ; 778 (54.1) XP_384929) E4 7.09 37.4 SNOG_11078.1 6.06 37.8 Hypothetical protein (NmrA like domain) ( Gibberella zeae ; 911 (54.1) XP_384929) E5 2.7 5.80 29.3 SNOG_15451.1 5.48 33.2 Acetyl xylan esterase ( Aspergillus oryzae ; BAD12626.1) 121 (17.8) E6 +3.3 6.64 26.3 SNOG_14370.1 5.09 45.8 Tyrosinase, putative ( Aspergillus fumigatus ; EAL86390.1) 394 (26.5) E7 2.4 7.14 30.2 SNOG_06492.1 7.71 40.6 Subtilisin like protease ( Phaeosphaeria nodorum ; AAP30889.1) 226 (17.2) E7 2.4 7.14 30.2 SNOG_05974.1 9.33* 35.8* Malate dehydrogenase ( Paracoccidioides brasiliensis ; AAP37966.2) 189 (23.0) E8 6.7 7.68 29.8 SNOG_06492.1 7.71 40.6 Subtilisin like protease ( Phaeosphaeria nodorum ; AAP30889.1) 278 (25.9) E8 6.7 7.68 29.8 SNOG_05974.1 9.33* 35.8* Malate dehydrogenase ( Paracoccidioides brasiliensis ; AAP37966.2) 72 (10.3)
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Table 3.2. Continued from the previous page. Spot Fold Observed Broad acc Theoretical BlastP match (organism; Genbank acc ID) Mascot score diff (% coverage) pI MW ID pI MW E9 8.39 29.8 SNOG_06492.1 7.71 40.6 Subtilisin like protease ( Phaeosphaeria nodorum ; AAP30889.1) 365 (28.0) E10 8.5 8.25 26.7 SNOG_06492.1 7.71 40.6 Subtilisin like protease ( Phaeosphaeria nodorum ; AAP30889.1) 457 (38.5) E11 17.0 7.70 26.8 SNOG_06492.1 7.71 40.6 Subtilisin like protease ( Phaeosphaeria nodorum ; AAP30889.1) 311 (29.4) E12 4.81 28.5 SNOG_12730.1 4.64 41.2 Putative protein ( Neurospora crassa ; CAC28723.1) 59 (7.8) E13 4.98 28.6 SNOG_12730.1 4.64 41.2 Putative protein ( Neurospora crassa ; CAC28723.1) 264 (25.1) E14 5.15 28.0 SNOG_12730.1 4.64 41.2 Putative protein ( Neurospora crassa ; CAC28723.1) 262 (22.5) E14 5.15 28.0 SNOG_01569.1 4.79 49.4 Cell wall glucanase ( Aspergillus fumigatus ; XP_748349.1) 131 (16.9) E15 4.55 27.7 SNOG_06180.1 4.74 22.4 Hypothetical protein ( Chaetomium globosum ; EAQ89481.1) 60 (4.4) E16 ++ 4.73 23.6 SNOG_05918.1 5.01 24.4 Hypothetical protein ( Aspergillus niger ; CAJ18289.1) 187 (28.4) E16 ++ 4.73 23.6 SNOG_08052.1 4.69 26.5 Poor BlastP match 142 (15.8) E17 ++ 5.10 23.9 SNOG_05918.1 5.01 24.4 Hypothetical protein ( Aspergillus niger ; CAJ18289.1) 182 (28.4) E17 ++ 5.10 23.9 SNOG_08052.1 4.69 26.5 Poor BlastP match 86 (15.8) E18 ++ 5.28 24.0 SNOG_05918.1 5.01 24.4 Hypothetical protein ( Aspergillus niger ; CAJ18289.1) 223 (28.4) E19 +5.6 6.47 18.0 SNOG_13504.1 6.27 19.7 Predicted protein ( Chaetomium globosum ; EAQ87808.1) 261 (44.7) E20 ++ 7.73 <15.0 SNOG_16063.1 6.28 18.0 RNase T1 (Aspergillus oryzae ; CAA30560.1) 91 (21.3) E21 +3.2 4.97 <15.0 SNOG_00848.1 4.74* 14.4* Peptidylprolyl isomerase ( Neurospora crassa ; CAA06962.1) 305 (41.7) E22 ++ 5.21 <15.0 SNOG_10685.1 5.41 33.6 Poor BlastP match 98 (23.3) E23 6.83 <15.0 SNOG_06491.1 5.13 37.6 Serine protease precursor ( Fusarium oxysporum ; AAC27316.2) 315 (15.6) E24 7.52 <15.0 SNOG_06491.1 5.13 37.6 Serine protease precursor ( Fusarium oxysporum ; AAC27316.2) 312 (15.6) E25 7.78 <15.0 SNOG_06491.1 5.13 37.6 Serine protease precursor ( Fusarium oxysporum ; AAC27316.2) 288 (15.1) *Prediction based on re annotated values. Refer to Chapter 6.
85 Chapter 3 A 5 pH 8 17 Intracellular kDa 2D proteome gels of SN15 and gna1-35 (Figure 3.2)
250
75
50
37
C4
25 C1 C2
C6
15 C8 C7
B
250
75
50
37
C4
25 C2 C1
C6
15 C8 C7
Figure 3.2. Representative 2D gels of A. SN15 and B. gna1-35
intracellular proteomes. Differentially abundant spots are indicated.
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18Differentially abundant intracellular protein spots of SN15 and gna1-35 (Table 3.3)
Table 3.3. Identification of differentially abundan t intracellular proteins with LC MS/MS. Mascot was used to pattern matched the mass spectrometry data with the S. nodorum whole genome annotated protein set to give a gene match. Fold difference of matching protein spots is calculated from normalised spot value of SN15 relative to gna1-35. BlastP identity and E value are given in Appendix D. Molecular weight (MW) is given in kDa.
Spot Fold Observed Broad acc Theoretical BlastP functional match (organism; Genbank acc ID) Mascot score diff (% coverage) pI MW ID pI MW C1 2.7 5.81 27.1 SNOG_13042.1 5.41 28.9 Short chain dehydrogenase, putative ( Aspergillus fumigatus ; 683 (49.1) EAL86301) C2 17.5 5.94 28.5 SNOG_10217.1 5.46 31.8 Short chain dehydrogenase/reductase SDR ( Solibacter usitatus ; 480 (29.4) ZP_00520385.1) C4 7.2 6.06 29.2 SNOG_07541.1 6.20 27.9 Proteasome component Pre8 ( Aspergillus funigatus ; XP_748923.1) 294 (40.2) C6 3.5 7.43 23.3 SNOG_07604.1 6.53 24.4 Glutathione transferase 2 ( Aspergillus fumigatus ; AAX07319.1) 74 (14.2) C7 +4.7 7.43 <15.0 SNOG_11441.1 6.49 16.5 3 dehydroquinate dehydratase ( Aspergillus fumigatus ; XP_754140.1) 228 (42.1) C8 19.2 5.70 <15.0 SNOG_11081.1 5.21 15.1 CipC protein ( Emericella nidulans ; CAC87272.1) 414 (46.2)
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Figure19Functional classification of putative Gna1 -effector genes (Table 3.4)
Table 3. 4. Functional classification of putative Gna1 effector genes.
Functional classification Broad acc ID Spot identity Protein/peptide degradation Proteasome component Pre8 SNOG_07541.1 C4 Subtilisin like protease (Snp3) SNOG_06492.1 E7, E8, E9, E10 and E11 Serine protease precursor SNOG_06491.1 E23, E24 and E25 Protein folding and stabilisation Peptidylprolyl isomerase SNOG_00848.1 E21 C-compound and carbohydrate metabolism Acetyl xylan esterase SNOG_15451.1 E5 Malate dehydrogenase SNOG_05974.1 E7 and E8 3 dehydroquinate dehydratase SNOG_11441.1 C7 Nucleotide/nucleoside/nucleobase metabolism RNase T1 SNOG_16063.1 E20 FunCat unassigned CipC protein SNOG_11081.1 C8 Cell wall glucanase SNOG_01569.1 E14 Vacuolar targeting protein SNOG_00656.1 E1 Glutathione S transferase 2 SNOG_07604.1 C6 Short chain dehydrogenase SNOG_10217.1 C2 Short chain dehydrogenase SNOG_13042.1 C1 Tyrosinase/oxidase SNOG_14370.1 E6 Unknown protein SNOG_05918.1 E16, E17 and E18 Unknown protein SNOG_08052.1 E16 and E17 Unknown protein with an NmrA like domain SNOG_11078.1 E2, E3 and E4 Unknown protein SNOG_13504.1 E19 Unknown protein SNOG_10685.1 E22 Unknown protein SNOG_06180.1 E15 Unknown protein SNOG_12730.1 E12, E13 and E14
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proteins. Genes that code for a subtilisin like protease (Snp3 ), a putative serine protease and a proteasome subunit (Pre8 ) were placed into the category of protein/peptide degradation. Another gene involved in determining protein fate, encodes a putative peptidylprolyl isomerase (Ppi). RNase T1 is implicated in nucleotide degradation.
Genes encoding a putative cell wall degradation enzyme acetyl xylan esterase, the quinate pathway enzyme 3 dehydroquinate dehydratase ( Qa-2) and malate dehydrogenase were placed into the C compound and carbohydrate metabolism category.
3.3.6 qRT-PCR analysis of gene expression
The expression of genes that code for Gna1 effector proteins was examined with qRT PCR. Comparative gene expression of SN15 and gna1-35 were analysed from transcripts extracted under similar in vitro growth conditions used for proteomic analysis. The normalised expression of each gene was compared with protein abundance data to identify correlations of protein and transcript abundances (Figure 3.3;
Figure 3.4). Expression of these genes was normalised against actin transcript abundance. Of the 22 genes examined, 12 showed a positive correlation between protein and transcript abundance. Ten genes showed no correlation.
The expression of these putative Gna1 regulated genes was analysed during
SN15 infection on wheat. This was performed to elucidate whether genes are expressed or showed differential pattern of expression during host infection (Figure 3.3; Figure
3.4). Expression of these genes were normalised against EF1 α transcript abundance.
The in planta transcription pattern of the 22 putative Gna1 regulated genes was divided
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into six unique expression profiles (Figure 3.5). Ten of the 22 putative Gna1 regulated genes showed increased expression during late infection coinciding with pycnidiation.
These genes code for putative short chain dehydrogenases, Pre8 , glutathione S transferase 2, Qa-2, tyrosinase/oxidase, PPI and RNase T1 and two genes encoding proteins of unknown function (SNOG_06180.1 and SNOG_08052.1). Four genes showed greater transcription during day one post infection. These genes code for CipC,
Snp3, acetyl xylan esterase and an unknown function protein (SNOG_13504.1). Two genes showed a biphasic expression pattern during early and late infection. These genes encode a putative vacuolar targeting protein and a protein of unknown function
(SNOG_12730.1). In contrast, a gene encoding an unknown protein with an NmrA domain ( NmrA ) showed greater expression during the mid infection sampling time point. Interestingly, gene expression was not observed for four putative Gna1 regulated genes during infection. These genes encode a cell wall glucanase, serine protease precursor and two proteins of unknown function (SNOG_10685.1 and SNOG_05918.1).
Collectively, 17 of the 22 genes showed a differential gene expression pattern during infection.
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SNOG_00656.1: Vacuolar targeting protein SNOG_00656.1: Vacuolar targeting protein (Spot E1) (Spot E1) 1.5 0.05 A a B b a b a a 20 qRT-PCR1.2 analysis of genes that encode extracellular0.04 proteins (Figure 3.3) 0.9 0.03
0.6 0.02 expression abundance 0.3 0.01 Normalised relative Normalised transcript 0 0 SN15 gna1-35 1 3 5 8 Strain Days post infection
SNOG_11078.1: Unknown protein with NmrA SNOG_11078.1: Unknown protein with NmrA domain (Spot E2, E3 and E4) domain (Spot E2, E3 and E4) 1.4 0.07 1.2 A A A a B B B b 0.06 a b b b 1 0.05 0.8 0.04 0.6 0.03 expression
abundance 0.4 0.02 0.2
Normalised relative 0.01 Normalised transcript 0 0 SN15 gna1-35 1 3 5 8 Strain Days post infection
SNOG_15451.1: Acetyl xylan esterase (Spot E5) SNOG_15451.1: Acetyl xylan esterase (Spot E5) 1.4 0.07 1.2 A a B b 0.06 a b b b 1 0.05 0.8 0.04 0.6 0.03 abundance 0.4 expression 0.02
Normalised relative 0.2 0.01 Normalised transcript 0 0 SN15 gna1-35 1 3 5 8 Strain Days post infection
SNOG_14370.1: Tyrosinase (Spot E6) SNOG_14370.1: Tyrosinase (Spot E6) 4.5 0.26 4 A a B a 0.24 a a a b 0.22 3.5 0.2 3 0.18 0.16 2.5 0.14 2 0.12 1.5 0.1 abundance expression 0.08 1 0.06 Normalised relative 0.5 0.04 Normalised transcript 0.02 0 0 SN15 gna1-35 1 3 5 8 Strain Days post infection
SNOG_06492.1: Subtilisin-like protease SNOG_06492.1: Subtilisin-like protease (Spot E7, E8, E9, E10 and E11) (Spot E7, E8, E9, E10 and E11) 1.5 0.07 a b a b 1.2 A A A A A a B B B B B b 0.06 0.05 0.9 0.04 0.6 0.03 expression abundance 0.02 0.3 Normalised relative
Normalised transcript 0.01 0 0 SN15 gna1-35 1 3 5 8 Strain Days post infection
Figure 3.3. Continued on the next page.
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SNOG_00656.1: Vacuolar targeting protein SNOG_00656.1: Vacuolar targeting protein (Spot E1) (Spot E1) 1.5 0.05 A a B b a b a a 1.2 0.04
0.9 0.03
0.6 0.02 expression abundance 0.3 0.01 Normalised relative Normalised transcript 0 0 SN15 gna1-35 1 3 5 8 Strain Days post infection
SNOG_11078.1: Unknown protein with NmrA SNOG_11078.1: Unknown protein with NmrA domain (Spot E2, E3 and E4) domain (Spot E2, E3 and E4) 1.4 0.07 1.2 A A A a B B B b 0.06 a b b b 1 0.05 0.8 0.04 0.6 0.03 expression
abundance 0.4 0.02 0.2
Normalised relative 0.01 Normalised transcript 0 0 SN15 gna1-35 1 3 5 8 Strain Days post infection
SNOG_15451.1: Acetyl xylan esterase (Spot E5) SNOG_15451.1: Acetyl xylan esterase (Spot E5) 1.4 0.07 1.2 A a B b 0.06 a b b b 1 0.05 0.8 0.04 0.6 0.03 abundance 0.4 expression 0.02
Normalised relative 0.2 0.01 Normalised transcript 0 0 SN15 gna1-35 1 3 5 8 Strain Days post infection
SNOG_14370.1: Tyrosinase (Spot E6) SNOG_14370.1: Tyrosinase (Spot E6) 4.5 0.26 4 A a B a 0.24 a a a b 0.22 3.5 0.2 3 0.18 0.16 2.5 0.14 2 0.12 1.5 0.1 abundance expression 0.08 1 0.06 Normalised relative 0.5 0.04 Normalised transcript 0.02 0 0 SN15 gna1-35 1 3 5 8 Strain Days post infection
SNOG_06492.1: Subtilisin-like protease SNOG_06492.1: Subtilisin-like protease (Spot E7, E8, E9, E10 and E11) (Spot E7, E8, E9, E10 and E11) 1.5 0.07 a b a b 1.2 A A A A A a B B B B B b 0.06 0.05 0.9 0.04 0.6 0.03 expression abundance 0.02 0.3 Normalised relative
Normalised transcript 0.01 0 0 SN15 gna1-35 1 3 5 8 Strain Days post infection
Figure 3.3. Continued on the next page.
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SNOG_05974.1: Malate dehydrogenase SNOG_05974.1: Malate dehydrogenase (Spot E7 and E8) (Spot E7 and E8) 1.4 0.2 1.2 A A a B B a a a a a 1 0.15 0.8 0.1 0.6 expression
abundance 0.4 0.05 0.2 Normalised relative Normalised transcript 0 0 SN15 gna1-35 1 3 5 8 Strain Days post infection
SNOG_12730.1: Unknown protein SNOG_12730.1: Unknown protein (Spot E12, E13 and E14) (Spot E12, E13 and E14) 1.5 0.07 A A A a B B B b 0.06 a b b a 1.2 0.05 0.9 0.04 0.6 0.03 expression abundance 0.02 0.3 Normalised relative
Normalised transcript 0.01 0 0 SN15 gna1-35 1 3 5 8 Strain Days post infection
SNOG_01569.1: Cell wall glucanase (Spot E14) 1.4 1.2 A a B b 1 0.8 SNOG_01569.1 expression 0.6 not observed in planta
abundance 0.4
Normalised relative 0.2 0 SN15 gna1-35 Strain
SNOG_06180.1: Unknown protein (Spot E15) SNOG_06180.1: Unknown protein (Spot E15) 1.5 0.024 A a B b 0.022 a a b b 1.2 0.020 0.018 0.016 0.9 0.014 0.012 0.6 0.010
expression 0.008 abundance 0.3 0.006
Normalised relative 0.004 Normalised transcript 0.002 0 0.000 SN15 gna1-35 1 3 5 8 Strain Days post infection
SNOG_05918.1: Unknown protein (Spot E16, E17 and E18) 2 1.8 1.6 A A A a B B B a 1.4 SNOG_05918.1 expression 1.2 1 not observed in planta 0.8
abundance 0.6 0.4
Normalised relative 0.2 0 SN15 gna1-35 Strain Figure 3.3. Continued on the next page.
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SNOG_06491.1 (Spot E23, E24 and E25) 1.6 1.4 A A A a B B B b 1.2 1 SNOG_06491.1 expression 0.8 not observed in planta 0.6 abundance 0.4
Normalised relative 0.2 0 SN15 gna1-35 Strain
Constituitive transcript expression control Constituitive transcript expression control 0.3 0.4 a a 0.35 a a a a α α α α 0.25 α α α α 0.3 0.2 0.25 0.15 0.2 0.1 0.15
relative to EF1 0.1 Actin expression relative to EF1 0.05 Actin expression 0.05 0 0 SN15 gna1-35 1 3 5 8 Strain Days post infection Figure 3.3. Comparisons of extracellular protein ( ) and tra nscript ( )
abundance of putative Gna1 regulated genes from strains grown in MM broth
supplemented with glutamate as a carbon and nitrogen source (left column).
Expression of these genes was also examined during wheat infection (right
column). Uppercase alphabets located on top of bar graphs signify significant
differences in protein abundance whereas lowercase alphabets denote
significant differences in transcript abundance. The underlined alphabet
denotes a Dunnett’s control group used for one way ANOVA analysis.
Standard error bars are shown.
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SNOG_13042.1: Short chain dehydrogenase SNOG_13042.1: Short chain dehydrogenase (Spot C1) (Spot C1) 0.03 1.4 a a a b 21qRT-PCR1.2 analysisA of a genes that encodeB b intracellular proteins0.025 (Figure 3.4) 1 0.02 0.8 0.015 0.6 0.01 abundance 0.4 expression 0.2 0.005 Normalised relative 0 Normalised transcript 0 SN15 gna1-35 1 3 5 8 Strain Days post infection
SNOG_10217.1: Short chain dehydrogenase SNOG_10217.1: Short chain dehydrogenase (Spot C2) (Spot C2) 1.4 0.25 A a B b a a a b 1.2 0.2 1 0.8 0.15 0.6 0.1 expression
abundance 0.4 0.2 0.05 Normalised relative Normalised transcript 0 0 SN15 gna1-35 1 3 5 8 Strain Days post infection
SNOG_07541.1: Proteasome component Pre8 SNOG_07541.1: Proteasome component Pre8 (Spot C4) (Spot C4) 1.8 0.03 1.6 A a B a a a a b 1.4 1.2 0.02 1 0.8 0.6 0.01 expression abundance 0.4
Normalised relative 0.2 Normalised transcript 0 0 SN15 gna1-35 1 3 5 8 Strain Days post infection
SNOG_07604.1: Glutathione transferase 2 SNOG_07604.1: Glutathione transferase 2 (Spot C6) (Spot C6) 1.6 0.6 1.4 A a B a 0.5 a a a b 1.2 1 0.4 0.8 0.3 0.6 0.2 abundance 0.4 expression 0.2 0.1 Normalised relative Normalised transcript 0 0 SN15 gna1-35 1 3 5 8 Strain Days post infection
SNOG_11441.1: 3-dehydroquinate dehydratase SNOG_11441.1: 3-dehydroquinate dehydratase (Spot C7) (Spot C7) 7 0.04 A a B a a a a b 6 0.032 5 4 0.024 3 0.016 expression
abundance 2 1 0.008 Normalised relative Normalised transcript 0 0 SN15 gna1-35 1 3 5 8 Strain Days post infection
Figure 3.4. Continued on the next page.
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SNOG_11081.1: CipC protein (Spot C8) SNOG_11081.1: CipC protein (Spot C8) 1.4 2.8 a b b b 1.2 A a B b 2.4 1 2 0.8 1.6 0.6 1.2 expression abundance 0.4 0.8
Normalised relative 0.2 0.4 Normalised transcript 0 0 SN15 gna1-35 1 3 5 8 Strain Days post infection
Constituitive transcript expression control Constituitive transcript expression control 0.3 0.4 a a a a a a 0.35 α α α α 0.25 α α α α 0.3 0.2 0.25 0.15 0.2 0.1 0.15
relative to EF1 0.1 Actin expression relative to EF1 0.05 Actin expression 0.05 0 0 SN15 gna1-35 1 3 5 8 Strain Days post infection Figure 3.4. Comparisons of intracellular protein ( ) and transcript ( )
abundance of putative Gna1 regulated genes from strains grown in MM broth
(left column). Expression of these genes was also examined during wheat
infection (right column). Uppercase alphabets located on top of bar graphs
signify significant differences in protein abundance whereas lowercase
alphabets denote significant differences in transcript abundance. The
underlined alphabet denotes a Dunnett’s control group used for one way
ANOVA analysis. Standard error bars are shown.
96 Chapter 3 22Gene expression profiles in planta (Figure 3.5 )
i ii iii iv v vi
SNOG_11081.1 SNOG_11078.1 SNOG_00656.1 SNOG_13042.1 SNOG_05974.1 SNOG_01569.1 SNOG_06492.1 SNOG_12730.1 SNOG_10217.1 SNOG_05918.1 SNOG_13504.1 SNOG_07541.1 SNOG_10685.1 SNOG_15451.1 SNOG_07604.1 SNOG_06491.1 SNOG_11441.1 SNOG_14730.1 SNOG_06180.1 SNOG_08052.1 SNOG_00848.1 SNOG_16063.1 Figure 3.5 . Expression profiles of putative Gna1 regulated genes during infection on wheat. Gene expression profiles were sorted based on their relative transcript abundance during infection; i. maximal transcript level during host penetration, ii. maximal transcript level during tissue colonisation, iii. maximal transcript level during host penetration and sporulation, iv. maximal transcript level during sporulation, v. constant transcript level through the infection period and vi . gene expression not observed.
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3.3.7 Variants of Snp3 and serine protease precursor
LC MS/MS and Mascot analysis of spot E7, E8, E9, E10 and E11 have identified Snp3, a protease previously characterised by Bindschedler et al. (2003). The predicted polypeptide MW (40.6 kDa) was approximately 10 kDa greater than the observed value (26.7 to 30.2 kDa) in the 2D gel. Referring to the mass spectrometry peptide coverage of Snp3, the first 109 peptides from the N terminal were not covered by mass spectrometry derived data (Figure 3.6). A theoretical MW was recalculated based on the Snp3 sequence from amino acid 110 to 287. The re predicted MW is 28.7 kDa which was similar to the observed value. This suggests that a portion of the N terminal of Snp3 may be absent in spot E7, E8, E9, E10 and E11. This requires further studies.
A putative serine protease precursor gene (SNOG_06491.1) is located adjacent
(5.8 kb) to Snp3 in supercontig 9. The polypeptide of SNOG_06491.1 was identified in spot E23, E24 and E25. The predicted polypeptide is much larger than the experimental value (Table 3.2). CDD Blast analysis of the SNOG_06491.1 polypeptide indicates two predicted domains; a subtilisin N terminal region and a peptidase S8 subtilase family domain (Figure 3.7). The latter domain was not confirmed by peptide coverage.
3.3.8 Qa-2 is located in a putative quinate gene cluster
Qa-2 (SNOG_11441.1) is associated with quinate metabolism. Analysis of predicted genes proximal to Qa-2 led to the identification of a putative quinate gene cluster (Hane, manuscript in preparation ).
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23 MS peptide coverage of Snp3 (Figure 3.6)
24 MS peptide coverage of a putative serine protease (Figure 3.7)
1 MKLSVLLALL PLALA APAPV IVPRAGSPIP GRFIVKMKNE NLQQLVDTAL 51 KLLRKDPAHV YKFAGFGGFA ADMADDIVEL IRNLPGVEYV EQDAVVKANL 101 GEIDSIEKR A FTTQSSSTWG LSR VSHINRQ TSGTSYTYDS SAGQGTCVYV 151 VDTGIETSHP EFEGRATFLA NFAGDGQNSD GNGHGTHCAG TIGSKTYGVA 201 K KASLYAVKV LDASGSGSNS GVIAGINYVA NDAK TR SCPN GAVGSMSLGG 251 SKSTAVNSAV ANAVTAGVFF AVAAGNDGAD ASRYSPASEV SAFTVGATDS 301 SDR VASFSNY GTLVDMHAPG VSILSTWLNG GTNTISGTSM ATPHVAGVAA 351 YILALEGK IS PAALSTRLTT LATKDK ITGL KGSTKNYLAF NGNPSG Figure 3.6 . Peptide coverage of Snp3 ( SNO G_06492.1) from mass
spectrometry analysis of trypsin digests of spot E7 to E11 (red). The predicted
N terminal signal peptide is shown in bold.
Peptide coverage
Figure 3.7. CDD Blast analysis of the SNOG_06491.1 predicted polypeptide
detected two protease associated domains. Mass spectrometry analysis of trypsin
digests of spot E23 to E25 (arrow) only covered the predicted subtilisin domain.
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3.3.9 Genomic organisation of other Gna1 protein effector genes
The localisation of Qa-2 within a putative gene cluster has prompted further investigations into the genomic structure of other putative Gna1 regulated genes to identify contiguous arrays of genes that may participate in a metabolic process. Broad designated genes were considered for analysis based on significant BlastP hits, the presence of a conserved domain or in house prediction with the UNVEIL software trained on genes fully supported by EST data (Hane, unpublished data ).
CipC and NmrA are located 5.4 kb apart in supercontig 18. Genes proximal to
CipC and NmrA encode putative PKSs, transporters, oxidoreductases, fatty acid enzymes and methyltransferases (Table 3.5). Genes proximal to a putative short chain dehydrogenase gene (SNOG_10217.1) encode an acyl CoA oxidase, a lipase, a transcription factor, an oxidoreductase and methyltransferases (Table 3.6). Genes proximal to a second putative short chain dehydrogenase gene (SNOG_13042.1) encode a putative PKS, methyltransferases and oxidoreductases (Table 3.7).
Polypeptide sequence analysis of SNOG_14370.1 indicated that it is similar to a putative tyrosinase of A. fumigatus . One of the characteristics of tyrosinases is the presence of two copper binding sites distinguishable by two conserved motifs. Analysis of the SNOG_14370.1 polypeptide with Motif Scan indicated the presence of only one copper binding motif. The size of the SNOG_14370.1 polypeptide (45.7 kDa) is much less than the characterised 68.6 kDa tyrosinase of N. crassa (Genbank acc. YRNC).
YRNC contained two putative copper binding sites (Motif Scan). Hence,
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SNOG_14370.1 may encode a unique oxidase. Furthermore, SNOG_14370.1 is located within a putative iron metabolism gene cluster (Table 3.8).
3.4 Discussion
3.4.1 Comparative analysis of the intracellular proteome
Impairments in gna1-35 are likely to be due to a loss of signalling co ordination of effectors that are critical for maintaining normal fungal development. Comparative intracellular proteomic analysis of SN15 and gna1-35 was performed to identify changes in protein effectors in gna1-35 .
3.4.2 Comparative analysis of the extracellular proteome
The extracellular secretome of fungi is of considerable scientific and commercial interest. A large amount of research has been devoted to identifying secreted molecules that determine the outcome of plant microbe interactions (Rep, 2005), phytopathogenicity (Belien et al. , 2006), decomposition/carbon cycling (Leschine,
1995) and the exploitation of fungal proteins for biotechnological and commercial purposes (de Vries, 2003; Subramaniyan & Prema, 2002). This is the first report that provides a specific analysis of extracellular proteome regulation by a signalling pathway in a plant pathogenic fungus.
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Figure25 CipC and NmrA putative gene cluster (Table 3.5) Table 3.5. BlastP analysis of predicted genes proximal to CipC and NmrA in a 70.6 kb region of supercontig 18 Broad ID E-value % aa Organism Match (Genbank acc ID) similarity SNOG_11060.1 8E 46 31% Aspergillus fumigatus β lactamase (XP_747079) SNOG_11061.1 1E 149 47% Magnaporthe grisea MDR efflux pump ABC3 (AAZ81480) SNOG_11063.1 4E 55 66% Magnaporthe grisea Hypothetical protein (XP_360219) SNOG_11066.1* 0.0E 45% Botryotinia fuckeliana Polyketide synthase (AAR90244) SNOG_11067.1 Predicted protein SNOG_11068.1 0.0E 42% Neurospora crassa Hypothetical protein (XP_958827) SNOG_11070.1 4E 36 29% Aspergillus fumigatus Exopolyphosphatase (XP_748002) SNOG_11071.1 1E 42 48% Coccidioides immitis Hypothetical protein (EAS28904) SNOG_11072.1 9E 108 37% Aspergillus fumigatus MFS toxin efflux pump (XP_754099) SNOG_11073.1 7E 50 41% Aspergillus fumigatus Short chain dehydrogenase/reductase family (XP_749056) SNOG_11074.1 9E 77 37% Aspergillus fumigatus Aminotransferase (XP_754156) SNOG_11076.1^ 0.0E 73% Cochliobolus heterostrophus Polyketide synthase (AAR90268) SNOG_11078.1 1E-53 37% Gibberella zeae Hypothetical protein with NmrA domain (XP_384929) SNOG_11079.1 Predicted protein SNOG_11080.1 4E 54 47% Aspergillus nidulans Hypothetical protein with phospholipase/carboxyesterase domain ( XP_682091) SNOG_11081.1 3E-17 44% Emericella nidulans CipC protein (CAC87272) SNOG_11082.1 0.0E 49% Aspergillus fumigatus Signal transduction protein Syg1 (XP_753707) SNOG_11084.1 Predicted protein SNOG_11086.1 Predicted protein SNOG_11087.1 4E 46 37% Aspergillus fumigtus MFS transporter (XP_747222)
*Merger of SNOG_11065.1 and SNOG_11066.1 (Hane, unpublished data ). ^Merger of SNOG_11075.1 and SNOG_11076.1 (Hane, unpublished data ).
102 Chapter 3 Figure26SNOG_10217.1 putative gene cluster (Table 3.6)
Table 3.6. BlastP analysis of predicted genes proximal to SNOG_10217.1 in a 34.6 kb region of supercontig 16.
Broad ID E-value % aa Organism Match (Genbank acc ID) similarity SNOG_10209.1 3E 14 33% Herpetosiphon aurantiacus Methyltransferase type 11 (ZP_01426122) SNOG_10210.1 5E 127 55% Aspergillus terreus Methionine aminopeptidase 2 (XP_001209448) SNOG_10211.1 Predicted protein SNOG_10216.1 1E 41 45% Coccidioides immitis Hypothetical protein with phosphotransferase domain (EAS32640) SNOG_10217.1 9E-29 36% Solibacter usitatus Short-chain dehydrogenase (YP_827156) SNOG_10219.1 6E 26 34% Aspergillus fumigatus Acyl CoA oxidase (XP_747031) SNOG_10221.1 8E 36 31% Neurospora crassa Related to integral membrane protein PTH11 (CAC28570) SNOG_10222.1 7E 36 33% Aspergillus fumigatus Cytochrome P450 monooxygenase (XP_751878) SNOG_10223.1 9E 49 32% Aspergillus fumigatus Lipase (XP_748709) SNOG_10225.1 3E 49 43% Aspergillus fumigatus Methyltransferase (XP_755772) SNOG_10226.1 8E 38 35% Gibberella zeae Hypothetical protein (XP_389194) SNOG_10228.1* 4E 51 88% Aspergillus terreus Small nuclear ribonucleoprotein SM D3 (XP_001210791) SNOG_10229.1 4E 55 61% Magnaporthe grisea Hypothetical protein (XP_364641) SNOG_10230.1 4E 109 49% Aspergillus fumigatus Transcription factor RfeF (XP_751806) *Merger of SNOG_10227.1 and SNOG_10228.1 (Hane, unpublished data ).
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Figure27SNOG_13042.1 putative gene cluster (Table 3.7)
Ta ble 3.7. BlastP analysis of predicted genes proximal to the SNOG_13042.1 in a 35.4 kb region of supercontig 25. Broad ID E-value % aa Organism Match (Genbank acc ID) similarity SNOG_13032.1 0.0E 75% Aspergillus fumigatus Polyketide synthase, putative (EAL87813) SNOG_13033.1 2E 171 76% Aspergillus fumigatus Oxidoreductase (XP_749850) SNOG_13034.1 2E 124 85% Aspergillus fumigatus Short chain dehydrogenase (EAL87811) SNOG_13035.1 9e 121 68% Aspergillus fumigatus FAD dependent oxidase, putative (EAL87810) SNOG_13036.1 9E 119 82% Aspergillus fumigatus MFS monocarboxylate transporter, putative (EAL87809) SNOG_13037.1 3E 74 46% Neurospora crassa Hypothetical protein (XP_958575) SNOG_13039.1 1E 40 34% Aspergillus flavus o methyltransferase OmtB (AAS90034) SNOG_13040.1 1E 48 30% Leptosphaeria maculans Cytochrome P450 monooxygenase SirC (AAS92547) SNOG_13041.1 1E 24 25% Aspergillus flavus o methyltransferase OmtA (AAS90041) SNOG_13042.1 5E-26 32% Aspergillus fumigatus Short-chain dehydrogenase, putative (EAL86301) SNOG_13043.1 5E 108 51% Gibberella zeae Hypothetical protein/ FAD/FMN containing dehydrogenase domain (XP_390785) SNOG_13044.1 4E 35 33% Coccidioides immitis Predicted protein (EAS31229) SNOG_13045.1 9E 60 33% Gibberella fujikuroi Cytochrome P450 monooxygenase (CAA75566)
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28SNOG_14370.1 putative gene cluster (Table 3.8)
Table 3.8. BlastP analysis of predicted genes proximal SNOG_14370.1 in a 23.9 kb region of supercontig 31. Broad ID E-val ue % aa Organism Match (Genbank acc ID) similarity SNOG_14362.1 2E 109 45% Neosartorya fischeri Siderophore biosynthesis acetylase AceI, putative (XP_001259091) SNOG_14364.1 9E 38 38% Neosartorya fischeri L ornithine N5 oxygenase SidA (XP_001260287) SNOG_14365.1 0.0E 50% Aspergillus fumigatus ABC multidrug transporter (MTABC3 domain*) (XP_748663) SNOG_14368.1 0.0E 68% Cochliobolus miyabeanus Nonribosomal peptide synthetase (ABI51982) SNOG_14370.1 5E-35 31% Aspergillus fumigatus Tyrosinase, putative (XP_748428) SNOG_14372.1 1E 65 34% Cryptococcus neoformans Efflux protein (XP_569134) *MTABC3 – iron homeostasis domain.
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The extracellular pH of SN15 and gna1-35 grown in MM broth were alkaline, presumably due to glutamate depletion. The experiment was performed to ensure that changes observed in the extracellular proteome between SN15 and gna1-35 were directly due to Gna1 deletion and not pH alteration. According to Solomon et al.
(2004b), defects in general extracellular protease activity of the gna1 mutants were more pronounced at an alkaline pH. Changes in pH are known to affect the expression of secreted proteins and secondary metabolite biosynthesis in other fungi (Cotton et al. ,
2003; Espeso et al. , 1993; Hube et al. , 1994; Poussereau et al. , 2001; Rollins, 2003).
Hence, regulation of the extracellular proteome of S. nodorum by Gna1 under different pH conditions should be considered for future investigation.
3.4.3 Transcript analysis of putative Gna1 -regulated genes
It would be desirable to perform comparative and quantitative fungal proteomics on infected plant materials. However, this approach is complicated by several technical difficulties. For instance, gna1-35 poorly infects wheat, so obtaining sufficient fungal proteins from infected plant materials for experiments can be difficult. Contamination by plant proteins also represents a major technical difficulty for comparative proteomic studies. To gain an insight into the regulation of putative Gna1 regulated genes in planta , qRT PCR was used to monitor transcript abundance at different stages of infection. Time points sampled were 1, 3, 5 and 8 days post infection. These time points were chosen to reflect the developmental stages of S. nodorum during infection in DLAs (Solomon et al. , 2006e). Pycnidiospore germination and host penetration occur during the first day of infection. Once host penetration is successful, the pathogen is able to proliferate within the plant tissue. This stage is represented by three
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and five days post infection. The onset of pycnidiation occurs at five days post infection. The completion of the infection cycle can be represented by pycnidiation and sporulation at eight days post infection (Solomon et al. , 2004b). The in vitro growth condition used for proteomic analysis is reflective of a nutrient rich environment. This in part mimics the in planta condition where nutrient is abundant from the onset of host penetration until asexual sporulation in S. nodorum (Waters, personal communications ).
In a closely related fungal pathogen M. graminicola, the expression of carbon metabolism genes in a nutrient rich environment in vitro and during in planta sporulation was not significantly different (Keon et al. , 2005).
3.4.4 Signal peptides and sub-cellular protein localisation
Signal peptides are short peptide sequences that direct post translational protein localisation to sub cellular compartments such as membrane and extracellular localisation. A bioinformatics approach was used to validate the sub cellular localisation of all putative Gna1 effector proteins. All intracellular proteins returned a negative prediction for signal peptides. N terminal signal peptides were predicted for
12 of the 16 extracellular proteins. SignalP did not conclusively predict N terminal signal peptides for four predicted polypeptides; malate dehydrogenase
(SNOG_05974.1), unknown protein (SNOG_08052.1), RNase T1 (SNOG_16063.1) and NmrA (SNOG_11078.1). PPI (SNOG_00848) contains an N terminal signal peptide and also a C terminal “KDEL” sequence implicated in sub cellular trafficking through endoplasmic reticulum (ER) retention. Classical protein secretion to the extracellular environment initiates upon protein migration to the ER which requires an
N terminal signal peptide (Conesa et al. , 2001). Non classical protein secretion does
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not follow this route. Hence, it is likely that signal peptide deficient proteins identified in this study are secreted through an ER/Golgi independent protein secretory pathway
(Nickel, 2003).
3.4.5 Identification of an extracellular malate dehydrogenase
Malate dehydrogenase is a key citric acid cycle enzyme involved in the reversible conversion of malate to oxaloacetate intracellularly. The putative malate dehydrogenase co localised with Snp3 in spot E7 and E8. This observation was confirmed with LC MS/MS of biological replicates of spot E7 and E8. The appearance of putative malate dehydrogenase in the extracellular proteome is surprising as the enzyme is classically associated with the cytoplasm and mitochondria. SignalP analysis indicates that the putative malate dehydrogenase does not carry an N terminal signal peptide. Assays for the cytoplasmic enzyme mannitol dehydrogenase indicated that cytoplasmic contamination was negligible. Malate dehydrogenase orthologs were found in the secretome of A. flavus during growth on the flavanoid rutin (Medina et al. ,
2005), cell free filtrates of the protozoan Trichomonas vaginalis (Addis et al. , 1997) and cell wall preparations of the legume Medicago sativa (Bailey et al. , 2001). The biological role of extracellular malate dehydrogenases is unknown.
3.4.6 Nucleotide degradation
A putative extracellular RNase T1 represented in spot E20 suggests that extracellular nucleic acid metabolism may be regulated by Gna1 . The RNase T1 family possesses a two stage endonucleolytic activity. The enzyme cleaves nucleoside 3' phosphates and 3' phosphooligonucleotides ending in G P with 2',3' cyclic phosphate
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intermediates. Proteomic analysis of A. flavus secretome revealed a putative secreted
RNase (Medina et al. , 2005). Two possible roles for extracellular RNase are described.
Since S. nodorum is a necrotrophic organism, the degradation of host tissue can result in the release of nucleic acids. Extracellular RNases may participate in RNA degradation to produce basic phosphate, carbon and nitrogen compounds for nutritional assimilation
(Lindberg & Drucker, 1984). Increased expression of RNase T1 during infection implicates a probable role in nucleotide acquisition from the host plant (Figure 3.3).
RNase may also play a role in disabling the host during fungal colonisation. For example, a class of secreted toxin resembling the RNase T1 family known as ribotoxin, has been shown to be cytotoxic by interfering with protein synthesis through ribosomal inactivation (Madan et al. , 1997a; Madan et al. , 1997b; Wool et al. , 1992).
3.4.7 Protein folding and stabilisation
SNOG_00848.1 matched to NcFKP22 of N. crassa , a characterised PPI
(Solscheid & Tropschug, 2000). PPIs or cyclophilins interact with the immunosuppressive drug cyclosporin A (Siewers et al. , 2005). The enzyme catalyses the isomerisation of the cis and trans peptide bonds on the N terminal side of proline residues (Gothel & Marahiel, 1999; Schreiber, 1992). The presence of a KDEL sequence suggests that S. nodorum PPI may be ER localised. PPI showed greater abundance in the gna1-35 extracellular proteome. Transcript abundance did not correlate with protein abundance. This suggests that either non transcriptional regulation or the perturbation of the secretory pathway through Gna1 deletion which resulted in extracellular localisation. Heterotrimeric G protein signalling has been implicated to modulate secretion, vesicle trafficking and membrane trafficking events in
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other systems (Gasman et al. , 1998; Neves et al. , 2002; Schwiebert et al. , 1994; Vitale et al. , 1996). The role of cyclophilins in fungal phytopathogenicity has been determined in M. grisea and B. cinerea . The cyclophilin Cyp1 is required for the formation of infectious structure and virulence of M. grisea (Viaud et al. , 2002). The cyp1 mutant also showed a reduction in intracellular lipid bodies and extensive vacuolation (Viaud et al. , 2002). The deletion of the Bcp1 cyclophilin in B. cinerea resulted in the reduction in pathogenicity. Unlike the wild type, the bcp1 mutant was insensitive to vegetative growth inhibition by cyclosporin A (Viaud et al. , 2003).
3.4.8 Protein/peptide degradation
A protein orthologous to a putative 20S proteasome Pre8 component of A. fumigatus was identified as reduced in abundance in gna1-35 . The observed MW for the SNOG_07541.1 protein is 27.9 kDa which is consistent with the MW of 20S proteasome subunits described by Coux et al. (1996). The 20S proteasome component is a part of the 26S proteasome complex that participates in the degradation of ubiquinated proteins, an integral process of intracellular protein cycling.
Solomon et al. (2004b) observed that the activity of the subtilisin like protease
Snp3 was greatly reduced in gna1-35 . Transcript and protein abundance data from this study supported the observation. Snp3 is an alkaline trypsin like protease discovered in the deletion background of another alkaline protease, Snp1 (Bindschedler et al. , 2003).
However, Snp1 was shown to be dispensable for pathogenicity and the role of Snp3 during infection has yet to be determined. Bindschedler et al. (2003) suggested that
Snp1 and Snp3 may play a synergistic role in proteolysis during pathogenesis. The
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creation of a double mutant defective in both proteases is required to test the hypothesis.
The in planta transcription profile suggests that the expression of Snp3 is biphasic and may be involve in multiple stages of infection. The serine protease precursor identified in spot E23, E24 and 25 may have N terminal zymogenic fragments post translationally cleaved during protease activation (Jain et al. , 1998). Thus it is possible to infer that the serine protease precursor was originally transcribed as a zymogen that required structural alterations to become active and prevent inappropriate self proteolysis
(Stennicke & Salvesen, 2000).
Regulation of protease secretion by G α signalling in phytopathogenic fungi was first reported by Gronover et al. (2001) through the deletion of Bcg1 in B. cinerea . In a later experiment, Gronover et al. (2004) identified a number of protease encoding genes down regulated in the bcg1 mutant via SSH analysis. This includes a metalloproteinase, aorsin, polyporopepsin, acid protease, penicillolysin precursor and tripeptidyl peptidase I precursor. Similarly, the inactivation of a putative G β subunit gene Fgb1 in F. oxysporum resulted in a significant loss in general extracellular protease activity (Prados Rosales et al. , 2006). The expression of an acid protease gene
Acp1 in the soft rot fungus Sclerotinia sclerotiorum increased when given exogenous cAMP which indicates the involvement of the cAMP/protein kinase A signalling pathway (Girard et al. , 2004). The role of fungal extracellular proteases during infection is yet to be fully defined. Plant cell walls are composed of glycine , hydroxyproline and proline rich proteins that are capable of altering cell wall properties in order to restrict pathogen invasion (Garcia Muniz et al. , 1998; Otte &
Barz, 1996; Otte & Barz, 2000; Showalter, 1993). Fungal extracellular proteases may
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function to break down cell wall proteins to facilitate invasion. Proteolysis may also provide a nutritional support for fungal growth during colonisation of the host tissue.
Snp3 was expressed throughout the infection process which suggests that extracellular protein degradation may be important during infection. Taken collectively, results from this study and recent findings in B. cinerea , F. oxysporum and S. slerotiorum provide evidence for heterotrimeric G protein/cAMP regulated protease metabolism in pathogenic fungi.
3.4.9 Cell wall degradation
It is widely considered that necrotrophic fungi require a large array of cell wall degrading enzymes to break through the host cell wall barrier and possibly acquire nutrients during plant pathogenesis and saprotrophy (Walton, 1994). This study has identified a putative cell wall depolymerase acetyl xylan esterase implicated in carbon metabolism (SNOG_15451.1). Protein and transcript abundance were reduced in gna1-
35 which suggests that the gene is controlled at the transcriptional level. Gene expression analysis during infection indicates that expression is maximal during the early stage of infection coinciding with host penetration. As gna1-35 showed a reduction in its ability to colonise the host tissue, the putative acetyl xylan esterase may function in parallel to other cell wall degrading enzymes to degrade the host cell wall to facilitate penetration, tissue colonisation and liberating carbon sources for growth. To test this hypothesis, the deletion of SNOG_15451.1 must be performed and mutants characterised.
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This study has thus far identified three putative cell wall degrading enzymes regulated by Gna1 . It is long known that culture filtrates of S. nodorum showed polygalacturonase, xylanase and cellulase activities (Magro, 1984). Furthermore, xylanase, glucosidase, galactosidase and butyrate esterase enzyme activities were detected in SN15 but were significantly reduced in gna1-35 (Solomon et al. , 2004b).
These enzymes were not identified in this study through 2D electrophoresis which could be due to several reasons. The pH range for growth prior to protein extraction was limited. As described above, alterations in extracellular pH may influence protein secretion. Plant cell wall components were not used as a nutrient source for proteomic analysis due to the possibility of exogenous protein contamination. Finally, 2D electrophoresis is resolution limited. Proteins with extremes in MW and pI, hydrophobic or low abundance may not be well represented for detection (Celis &
Gromov, 1999). Thus the in vitro environment used in this study may not be optimal for the expression and secretion of some cell wall degrading enzymes.
3.4.10 Quinate metabolism
Quinate is a common plant metabolite. Most fungi are capable of assimilating quinate as a carbon source via the β ketoadipate pathway (Giles et al. , 1991; Harwood
& Parales, 1996). A putative Qa 2 showed increase protein abundance in gna1-35 .
Qa 2 catalyses the reversible conversion of 3 dehydroquinate to 3 dehydroshikimate.
Both compounds are intermediates of the aromatic amino acid biosynthesis and quinate catabolism pathways. In N. crassa , the deletion the the Gα subunit gene Gna3 resulted in the increase expression of Qa-2 (Kays et al. , 2000). The addition of cAMP overrides the expression of Qa-2 during carbon starvation thus indicating a signal transduction
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regulated carbon sensing system in N. crassa (Kays et al. , 2000). This suggests that heterotrimeric G protein/cAMP signalling plays a suppressive role in quinate metabolism, at least for S. nodorum and N. crassa .
3.4.11 Association of putative Gna1 -regulated genes in probable gene clusters?
In fungi, secondary metabolism genes are often arranged in a genetic cluster
(Keller et al. , 2005). Gene clustering has been demonstrated for the biosynthetic pathway of sterigmatocystin toxin in A. nidulans (Brown et al., 1996). In S. nodorum , genes that encode CipC, NmrA, tyrosinase like oxidase and short chain dehydrogenases are located in genomic regions which contain genes that are characteristic of a gene cluster (Keller et al. , 2005).
NmrA and CipC were transcriptionally down regulated in the gna1-35 . The
NmrA polypeptide contained a domain associated with a regulator of the transcription factor AreA (CDD Blast). The function of NmrA is unknown. CipC was first identified as a cocanamycin A induced protein that was accumulated in A. nidulans in response to concanamycin A (Melin et al. , 2002). Transcripts of a CipC ortholog in G. fujikuroi accumulated in response to nitrogen starvation (Teichert et al. , 2004). A CipC ortholog in U. maydis was induced during filamentous growth caused by the overexpression of the bE/ bW heterotrimer and a GTP binding protein Rac1 (Bohmer et al. , 2007). CipC orthologs were expressed in the ectomycorrhizal fungi Paxillus involutus and Lacarria bicolour during symbiosis (Le Quere et al. , 2004; Morel et al. , 2005; Peter et al. , 2003)
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and saprophytic growth of a Termitomyces fungus commonly associated with termites
(Johjima et al. , 2006). The function of CipC is unknown.
Genes proximal to SNOG_10217.1 code for putative lipid metabolism and redox proteins. Genes required for de novo secondary metabolite biosynthesis such as PKSs and NRPSs were not observed. The gibberellin biosynthesis gene cluster of G. fujikuroi consist of genes that synthesise gibberellins in a series of reactions from farnesyldiphosphate (FPP) (Tudzynski, 1999; Tudzynski et al. , 2003). The farnesylpyrophosphate synthase gene responsible for FPP biosynthesis located outside of the giberellin gene cluster (Homann et al. , 1996). The gibberellin gene cluster does not contain genes that encode PKSs and NRPSs. It is probable that SNOG_10217.1 and proximal genes may participate in the modification of a metabolite backbone. This hypothesis is purely speculative but it is noted that S. nodorum mutants defective in
SNOG_10217.1 were altered in the metabolome profile. This will be discussed in greater detail in Chapter 5.
Gene expression and metabolomic experiments are currently being conducted to determine a possible link between heterotrimeric G protein signalling and secondary metabolism in S. nodorum .
3.4 Conclusion
Results from this study have confirmed the initial finding by Solomon et al.
(2004b) on the reduction in extracellular alkaline protease activities in gna1-35.
Alterations in the abundance of proteins associated with nucleotide degradation,
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proteosomal function, protein folding, carbon metabolism and nucleotide degradation were also observed in the signalling mutant. A large number of putative Gna1 regulated genes showed similar a transcriptional profile to Gna1 whereby expression were maximal during the latter stage of infection [see Solomon et al. (2004b)]. In addition, bioinformatic analysis indicates that some putative Gna1 regulated genes may be associated within putative gene clusters. The transcription profile of putative cluster associated genes and the metabolome of gna1 mutants are under current investigation.
The research conducted in this chapter has fulfilled the first three project objectives listed in Chapter 1.
116
Chapter 4 - Identification of mitogen-activated
protein kinase-regulated effector proteins in
Stagonospora nodorum by proteomics
117 Chapter 4
4.1 Introduction
For most organisms, adaptation to environmental changes requires an initial perception to a stimulus. Once the stimulus is recognised, a signal is relayed within the cell which instigates changes in effector functions that allow the organism to adapt to the environment. A major area of fungal research in recent years is dedicated to understanding the role of signal transduction in phytopathogenicity in particular
MAPK signalling. This is mediated through a protein kinase cascade that involves series of signal amplification through phosphorylation. MAPK signalling is implicated in growth, differentiation, survival and pathogenesis in many plant pathogenic fungi
(Xu, 2000). Despite a wealth of studies on MAPK signalling and fungal virulence
(Chapter 1), little is known about downstream effectors that contribute to the infection process.
S. nodorum Mak2 (SNOG_03299.1) is a Fus3 /Kss1 type MAPK gene required for sporulation and virulence (Solomon et al. , 2005b) (Chapter 1). A comparative 2D
SDS PAGE approach will be used to analyse the intracellular proteome of SN15 and a mak2 mutant ( mak2-65 ) for proteins differing in abundance. These proteins will be analysed with LC MS/MS and mass spectra obtained will be matched to Broad predicted genes in the S. nodorum genome. The aim of this experiment is to identify
Mak2 signalling protein effectors that may contribute to the phenotype of the mak2 mutant.
4.2 Methods
As decribed in Chapters 2 and 3.
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4.3 Results
4.3.1 Comparative intracellular proteome analysis
The intracellular proteomes of SN15 and mak2-65 were methanol extracted from mycelia grown in MM broth supplemented with glucose and separated via 2D gel electrophoresis (Figure 4.1). A total of 475 unique protein spots were identified from
SN15 and mak2-65 . Of these, six spots (1.3%) were deemed differentially abundant by
ProGENESIS (Figure 4.1; Appendix E). Of these changes, five spots were significantly less abundant in mak2-65 whereas one spot showed increase in abundance. LC MS/MS was used to obtain peptide spectra and the resulting data were matched against the S. nodorum predicted protein set to identify the matching gene (Table 4.1; Appendix D).
4.3.2 Functional classification of differentially abundant proteins
Seven genes were identified from six differentially abundant spots. The FunCat classification scheme based on gene ontology predictions was used to place these genes into four functional categories. The unknown category consisted of genes that code for a putative short chain dehydrogenase (SNOG_10217.1), glutathione S transferase 2
(Gst2; SNOG_07604.1), hydrolase (SNOG_08775.1) and a glucose repressible protein like protein ( Grg1 ). S. nodorum Grg1 was not annotated by the Broad Institute and hence was identified through a match with a cDNA (FP 1_B06) derived from growth on cell wall. A second putative short chain dehydrogenase gene (SNOG_08282.1) was classified into the lipid and isoprenoid metabolism category. A 20S proteasome component Pre8 (Pre8 ; SNOG_07541.1), identified in spot C4, was placed in the
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A 5 pH 8 kDa 29Intracellular 2D proteome gels of SN15 and mak2-65 (Figure 4.1) 250 75
50
37
C4
25 C2 C3 C5 C6
15
C14 B 250
75
50
37
C4 25 C2 C3 C6 C5
15
C14
Figure 4.1. Representative 2D gels of A. SN15 and B. mak2 -65
intracellular proteomes. Differentially abundant spots are indicated. 120 Chapter 4
30Differentially abundant intracellular protein spots of SN15 and mak2-65 (Table 4.1 )
Table 4.1. Identification of differentially abundant intracellular proteins with LC MS/MS. Mascot was used to pattern matched the mass
spectrometry data with the S. nodorum whole genome annotated protein set to give a gene match. Fold difference of matching protein spots
was calculated from normalised spot value of SN15 relative to mak2-65 . Fold difference designated by ( ) indicates protein spots that were
not observed in mak2-65 proteome gel. Molecular weight (MW) is given in kDa. BlastP identity and E value are given in Appendix D.
Fold Observed Broad acc Theoretical Mascot score Spot diff pI MW ID pI MW BlastP functional match (organism; Genbank acc ID) (% coverage) C2 15.2 5.94 28.5 SNOG_10217.1 5.46 31.8 Short chain dehydrogenase/reductase SDR ( Solibacter usitatus ; 514 (38.5) ZP_00520385.1) C3 3.1 6.04 26.1 SNOG_08775.1 5.37 27.6 HAD superfamily hydrolase ( Aspergillus fumigatus ; XP_753809.1) 130 (28.1) C3 3.1 6.04 26.1 SNOG_15488.1 5.64 28.6 Mannitol dehydrogenase ( Phaeosphaeria nodorum ; AAX14688.1) 128 (13.9) C4 6.06 29.2 SNOG_07541.1 6.20 27.9 Proteasome component Pre8 ( Aspergillus fumigatus ; XP_748923.1) 294 (40.2) C5 17.6 7.59 24.8 SNOG_08282.1 5.64 27.2 Short chain dehydrogenase ( Aspergillus fumigatus ; XP_746365.1) 507 (34.1) C6 3.5 7.43 23.3 SNOG_07604.1 6.53 24.4 Glutathione transferase 2 ( Aspergillus fumigatus ; AAX07319.1) 74 (14.2) C9 +6.2 5.57 <15.0 *FP 1_B06 5.71 9.0 Glucose repressible gene protein like protein ( Magnaporthe grisea ; 55 (39.3) AAX07712.1) *The matching cDNA designation derived from S. nodorum growth on plant cell wall is given. Gene not annotated by the Broad.
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protein/peptide degradation category. Mannitol dehydrogenase (SNOG_15488.1) was co localised with the putative hydrolase in spot C3 and was classified in the C compound and carbohydrate metabolism category.
4.3.3 qRT-PCR analysis of gene expression
The expression of genes that code for Mak2 effector proteins was examined with qRT PCR. Comparative gene expression of SN15 and mak2-65 was analysed from transcripts extracted under a similar in vitro growth condition used for proteomic analysis. The normalised expression of each gene was compared with protein abundance data to identify possible correlations. These data are summarised in Figure
4.2. Expression of these genes were normalised against actin transcript abundance. Of six genes examined (excluding mannitol dehydrogenase), only three showed a correlation between protein and transcript abundance. These genes are SNOG_10217.1,
SNOG_08282.1 and Gst2 . The in vitro expression of the mannitol dehydrogenase gene in mak2-65 is currently being examined.
The expression of these putative Mak2 regulated genes was analysed during
SN15 infection on wheat. This was performed to elucidate whether genes are expressed or showed differential pattern of expression during host infection (Figure 4.2).
Expression of these genes were normalised against EF1 α transcript abundance. The in planta transcription pattern of the six putative Mak2 regulated genes was divided into two expression profiles (Figure 4.3). Five of the six putative Mak2 regulated genes showed increased expression during the late onset of infection coinciding pycnidiation and sporulation. These genes code for the putative short chain dehydrogenase
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SNOG_10217.1: Short chain dehydrogenase SNOG_10217.1: Short chain dehydrogenase (Spot C2) (Spot C2) 1.4 0.25 1.2 A a B b a a a b 0.2 31qRT-PCR 1analysis of genes that encode intracellular proteins (Figure 4.2) 0.8 0.15 0.6 0.1 expression
abundance 0.4 0.2 0.05 Normalised relative Normalised transcript 0 0 SN15 mak2-65 1 3 5 8 Strain Days post infection
SNOG_08775.1: HAD superfamily hydrolase SNOG_08775.1: HAD superfamily hydrolase (Spot C3) (Spot C3) 1.6 0.6 A a B a a a b b 1.4 0.5 1.2 1 0.4 0.8 0.3 0.6 0.2 expression abundance 0.4 0.2 0.1 Normalised relative Normalised transcript 0 0 SN15 mak2-65 1 3 5 8 Strain Days post infection
SNOG_07541.1: Proteasome component Pre8 SNOG_07541.1: Proteasome component Pre8 (Spot C4) (Spot C4) 1.8 0.03 1.6 A a B a a a a b 1.4 1.2 0.02 1 0.8 0.6 0.01 expression abundance 0.4
Normalised relative 0.2 Normalised transcript 0 0 SN15 mak2-65 1 3 5 8 Strain Days post infection
SNOG_08282.1: Short chain dehydrogenase SNOG_08282.1: Short chain dehydrogenase (Spot C5) (Spot C5) 1.4 0.08 1.2 A a B b 0.07 a b b b 1 0.06 0.8 0.05 0.04 0.6 0.03 expression
abundance 0.4 0.02 0.2 Normalised relative
Normalised transcript 0.01 0 0 SN15 mak2-65 1 3 5 8 Strain Days post infection
SNOG_07604.1: Glutathione transferase 2 SNOG_07604.1: Glutathione transferase 2 (Spot C6) (Spot C6) 1.6 0.6 A a B b a a a b 1.4 0.5 1.2 1 0.4 0.8 0.3 0.6 0.2 abundance 0.4 expression 0.2 0.1 Normalised relative Normalised transcript 0 0 SN15 mak2-65 1 3 5 8 Strain Days post infection Figure 4.2. Continued on the next page.
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FP-1_B06: Glucose-repressible gene protein-like FP-1_B06: Glucose-repressible gene protein-like protein (Spot C9) protein (Spot C9) 9 7.0 8 A a B a 6.0 a a a b 7 5.0 6 5 4.0 4 3.0 3 expression
abundance 2.0 2
Normalised relative 1.0 1 Normalised transcript 0 0.0 SN15 mak2-65 1 3 5 8 Strain Days post infection
Constituitive transcript expression control Constituitive transcript expression control 0.3 0.4 a a 0.35 a a a a α α α α 0.25 α α α α 0.3 0.2 0.25 0.15 0.2 0.1 0.15
relative to EF1 0.1 Actin expression relative to EF1 0.05 Actin expression 0.05 0 0 SN15 mak2-65 1 3 5 8 Strain Days post infection Figure 4. 2. Comparisons of intracellular protein ( ) and transcript ( )
abundance of putative Mak2 regulated genes from strains grown in MM broth
(left column). Gene expression was also examined during wheat infection
(right column). Uppercase alphabets located on top of bar graphs signify
significant differences in protein abundance whereas lowercase alphabets
denote significant differences in transcript abundance. The underlined
alphabet denotes a Dunnett’s control group used for one way ANOVA
analysis. Standard error bars are shown.
124 Chapter 4
32Gene expression profiles in planta (Figure 4.3)
i ii iii
SNOG_08282.1 SNOG_10217.1 SNOG_15488.1 SNOG_08775.1 SNOG_07541.1 SNOG_07604.1 Grg1
Figure 4.3. Expression profiles of putative Mak2 regulated genes during wheat
infection. Gene expression profiles were sorted based on their relative transcript
abundance during infection; i. maximal transcript level during host penetration, ii.
maximal transcript level during sporulation and iii. constant transcript level
through the infection period.
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(SNOG_10217.1), hydrolase, Gst2 , Pre8 and Grg1 . Only one gene, encoding a putative short chain dehydrogenase (SNOG_08282.1), showed maximal expression during the early stage of infection. Mannitol dehydrogenase showed constitutive expression throughout infection (Solomon et al. , 2006d).
4.3.4 Genomic organisation of putative Mak2 effector genes
Bioinformatic analyses of some putative Gna1 regulated genes have led to the identification of possible gene clusters (Chapter 3). This has prompted a similar investigation into genomic regions surrounding putative Mak2 regulated genes to identify contiguous arrays of genes that may participate in a metabolic process. From the analysis, genomic regions associated with putative short chain dehydrogenase genes, SNOG_10217.1 and SNOG_08282.1 contained genes that encode proteins with putative secondary metabolism function. The genome organisation of the proximal
SNOG_10217.1 region in supercontig 16 was previously discussed in Chapter 3. A large number of genes in proximal to SNOG_08282.1 encode proteins with putative redox functions (Table 4.2). A putative PKS, transporter, methyltransferases and two genes that code for lipid metabolism proteins were also observed.
4.4 Discussion
4.4.1 Difficulties in isolating extracellular proteins for proteomics
The Mak2 ortholog Gpmk1 in F. graminearum regulates the induction of extracellular lipases, proteases and cell wall depolymerases (Jenczmionka & Schafer,
2005). This prompted an initial investigation into the extracellular proteome of mak2-
65 to identify changes that may provide an explaination for the mutant phenotype.
126 Chapter 4 33SNOG_08282.1 putative gene cluster (Table 4.2)
Table 4.2. BlastP analysis of predicted genes proximal to the putative short chain dehydrogenase (SNOG_08282.1) in a
52.2 kb region of supercontig 12. Broad I D E-value % aa Organism Match similarity (Genbank acc ID) SNOG_08259.1 0.0E 49% Aspergillus terreus Hypothetical protein with a SAM:diacylglycerol 3 amino 3 carboxypropyl transferase domain (XP_001208848) SNOG_08260.1 Predicted protein SNOG_08261.1 Predicted protein SNOG_08262.1 2E 30 36% Deinococcus geothermalis Lipase, active site (YP_594288) SNOG_08263.1 Predicted protein SNOG_08265.1 1E 49 41% Leptosphaeria maculans Alcohol dehydrogenase IV (ABB55460) SNOG_08266.1 2E 29 26% Chaetomium globosum Hypothetical protein with methyltransferase domain (EAQ84242) SNOG_08267.1 8E 93 55% Debaryomyces hansenii Hypothetical protein with NmrA domain (XP_459312) SNOG_08268.1 2E 86 35% Aspergillus fumigatus Cytochrome P450 (XP_747131) SNOG_08269.1 Predicted protein SNOG_08270.1 1E 55 39% Aspergillus fumigatus Cytochrome P450 (XP_746900) SNOG_08274.1* 0.0E 52% Nectria haematococca Polyketide synthase (AAS48892) SNOG_08275.1 3E 16 35% Gibberella zeae Hypothetical protein (XP_382501) SNOG_08276.1 2E 159 65% Aspergillus terreus Predicted protein with a monooxygenase domain (XP_001216123) SNOG_08277.1 6E 65 70% Cochliobolus heterostrophus 1,3,6,8 tetrahydroxynaphthalene reductase (ABK63477) SNOG_08278.1 1E 49 45% Aspergillus nidulans Hypothetical protein (atrazine degradation family) (XP_681862) SNOG_08280.1 2E 78 53% Aspergillus fumigatus Short chain dehydrogenase (XP_748189) SNOG_08281.1 1E 54 29% Fusarium oxysporum Putative oxidoreductase (CAJ85791) SNOG_08282.1 2E-40 54% Aspergillus fumigatus Short chain dehydrogenase (XP_746365) SNOG_08285.1 4E 44 29% Cercospora nicotianae Cercosporin toxin biosynthesis protein (ABC79591) SNOG_08286.1 3E 55 36% Aspergillus oryzae Unnamed protein product with a Zn dependent hydrolase domain (BAE63022) SNOG_08287.1 7E 87 55% Aspergillus fumigatus Hypothetical protein (XP_748585) SNOG_08288.1 9E 59 38% Aspergillus fumigatus MFS monocarboxylate transporter (XP_748652) *merger of SNOG_08272.1, SNOG_08273.1 and SNOG_08274.1 (Hane, unpublished data ).
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General extracellular protease activities of mak2-65 are comparable to SN15 (Solomon et al. , 2005b). However, this does not account for other possible changes in the extracellular proteome of the mak2 mutant. Several attempts were made to isolate extracellular proteins from mak2-65 . This was hindered by technical difficulties that have resulted from the mutant phenotype. For instance, mak2-65 grew poorly in MM broth supplemented with glutamate as a carbon source. Consequently, extracellular proteins obtained were insufficient in quantity for 2D gel electrophoresis. Glucose was considered as an alternative carbon source but led to the production of polysaccharides that interfered with downstream 2D SDS PAGE methods (data not shown). Hence, the development of an alternative culturing technique is required to culture mak2-65 to produce a sufficient amount of extracellular proteins for proteomic analysis.
4.4.2 Gna1 and Mak2 effector co-regulation
Protein spots that were co regulated by both signalling pathways were identified by comparing the intracellular proteome profile of SN15, gna1-35 and mak2-65 (Figure
4.4). SNOG_10217.1 showed 17.5 and 15.2 fold reduction in protein abundance in gna1-35 and mak2-65 , respectively. The transcript abundance of SNOG_10217.1 was significantly reduced in both mutants, suggesting transcriptional regulation by Gna1 and
Mak2 signalling.
Gna1 and Mak2 signalling affects the protein abundance of Pre8 in spot C4.
Proteomic analysis of M. grisea led to the identification of two putative proteasome subunits that showed increased abundance during appressorium morphogenesis and
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34 Gna1 and Mak2 effector co-regulation (Figure 4.4) SNOG_10217.1: Short-chain dehydrogenase (Spot C2) 1.4 1.2 1 0.8 0.6
abundance 0.4 0.2 Normalisedrelative 0 SN15 gna1-35 mak2-65 Strain
SNOG_07541.1: Proteasome component Pre8 (Spot C4) 1.4 1.2 1 0.8 0.6
abundance 0.4 0.2 Normalisedrelative 0 SN15 gna1-35 mak2-65 Strain
SNOG_07604.1: Glutathione transferase 2 (Spot C6) 1.4 1.2 1 0.8 0.6
abundance 0.4 0.2 Normalisedrelative 0 SN15 gna1-35 mak2-65 Strain
Figure 4. 4. Gna1 and Mak2 co regulation of
effectors. Relative protein ( ) and transcript ( )
abundance are shown for each gene. Standard
error bars are shown.
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under nutrient starvation (Kim et al. , 2004). Incidently, appressorium morphogenesis in
M. grisea is regulated by heterotrimeric G protein and MAPK signalling (Talbot, 2003).
Gna1 and Mak2 signalling affects the protein abundance of Gst2
(SNOG_07604.1) in spot C6. Gst2 was placed in the unknown category by the FunCat classification scheme. However, CDD Blast analysis of Gst2 indicates conserved amino and carboxyl domains common to the GST family were present (Sheehan et al. , 2001).
GSTs are best characterised in mammals and plants where they catalyse the conjugation of reduced glutathione on non polar compounds that contain an electrophilic carbon, sulphur or nitrogen atom (Hayes et al. , 2005). Well known roles for GSTs include the detoxification of xenobiotics (Kelly et al. , 2000), oxidative stress protection (Hurst et al. , 1998; Yang et al. , 2002), steroid biosynthesis (Johansson & Mannervik, 2001) and amino acid degradation (Fernandez Canon & Penalva, 1998). A putative GST gene in the black spot disease fungus Alternaria brassicicola showed increase expression when the fungus was exposed to isothiocyanate, heavy metals and 1 chloro 2,4 dinitrobenzene (Sellam et al. , 2006). Three GST genes were identified in B. cinerea and were shown to be regulated by a putative G protein coupled receptor (Gronover et al. , 2005).
Heterotrimeric G protein and MAPK signalling are normally considered as distinct signalling pathways in eukaryotic organisms. However, cross signalling do occur. For example, the co ordination of pheromone response in S. cerevisiae during the mating process by the Gpa1 heterotrimeric G protein and Fus3 MAPK pathways has been described (Dohlman & Thorner, 2001). Regulation of appressorium formation by
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signal transduction pathways is well described in M. grisea (Chapter 1). The two major signalling pathways involved in this process are the MagB heterotrimeric G protein
(Choi & Dean, 1997; Liu & Dean, 1997; Mitchell & Dean, 1995) and Pmk1 MAPK pathways (Park et al. , 2006; Xu & Hamer, 1996; Zhao et al. , 2005; Zhao & Xu, 2007).
Despite a multitude of studies on the regulation of appressorium morphogenesis by heterotrimeric G protein and MAPK signalling, knowledge of downstream effectors of these pathways at this stage is lacking.
4.4.3 Identification of a glucose repressible protein
A protein that resembled the putative glucose repressible protein of M. grisea accumulated in mak2-65 . Grg1 was first identified in N. crassa and gene expression was inducible by carbon starvation (McNally & Free, 1988) . In addition, a Grg1 ortholog in Podospora anserina was down regulated in response to the deletion of the
GRISEA transcription factor associated with fungal lifespan (Kimpel & Osiewacz,
1999). Like NcGrg1 , PaGrg1 is up regulated under a carbon limiting environment.
The function of Grg1 in N. crassa and P. anserina is unknown.
4.4.4 Identification of S. nodorum mannitol dehydrogenase
Mannitol dehydrogenase co localised with a putative hydrolase in spot C3 which is less abundant in mak2-65 . Mannitol dehydrogenase is an enzyme of the postulated mannitol cycle that reduces fructose to mannitol. Mannitol accumulates to a great quantity within the mycelium of many fungi (Solomon et al. , 2007). However, the role of mannitol in fungi remains largely an enigma. Solomon et al. (2006d) recently showed that the metabolism of mannitol was required for asexual sporulation in S.
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nodorum . The MAPK MpkC in A. fumigatus is required for polyol utilisation (Reyes et al. , 2006). A narrow range IPG strip would be desirable to separate mannitol dehydrogenase and the putative hydrolase from spot C3. Metabolomic analysis may provide an insight into mannitol metabolism of mak2-65 .
4.4.5 Association of SNOG_08282.1 with a probable gene cluster?
The function of SNOG_08282.1 is unclear but gene ontology and the FunCat classification scheme have placed it as a lipid/isoprenoid metabolism gene.
SNOG_08282.1 is located within a probable gene cluster in S. nodorum . This hypothesis is speculative and requires further investigation. A recent study of Mak2
MAPK in N. crassa by Li et al. (2005) has shed new light into MAPK effector regulation. Subtractive transcript enrichment of N. crassa Mak2 deficient strains identified three genes designated Mkr2 , Mkr3 and Mkr6 that code for a short chain dehydrogenase, pyridoxal reductase and unknown protein, respectively. These genes were down regulated in the N. crassa mak2 mutant and are genetically clustered with a polyketide synthase. Genetic microsynteny was observed between the Mkr cluster in N. crassa and an uncharacterised genomic region in M. grisea (Li et al. , 2005).
4.5 Conclusion
The deletion of Mak2 in S. nodorum has led to major phenotypic impairments such as abolished pathogenicity and sporulation on wheat (Solomon et al. , 2005b).
Proteomics was used to gain a comparative insight into the intracellular proteome of
SN15 and mak2-65 in an effort to identify effector proteins associated with the phenotype of the mak2 mutant. Gna1 and Mak2 co regulation was observed. One of
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the co regulated genes is a putative short chain dehydrogenase (SNOG_10217.1). The role of this gene in S. nodorum pathogenicity will be discussed in Chapter 5.
Bioinformatic analysis of a second Mak2 regulated putative short chain dehydrogenase gene (SNOG_08282.1) suggests that it may be associated with a potential gene cluster.
This study has altogether fulfilled the second and third aims and partially fulfilled the first aim set in Chapter 1.
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Chapter 5 - Analysis of a putative short-chain
dehydrogenase gene (Sch1 ) for its role in the
pathogenicity of Stagonospora nodorum on
wheat
134 Chapter 5
5.1 Introduction
Asexual reproduction is regarded as a key to invasive spread and generation of an epidemic by many fungal pathogens (Kohn, 1995). Sporulation is a major mode of asexual reproduction. Dissection of the molecular mechanism that triggers and maintains the development of asexual sporulation is essential for developing strategies to interfere with the fungal life cycle. The role of signal transduction in pathogenesis has been extensively investigated in phytopathogenic fungi in particular, the involvement of the heterotrimeric G protein and MAPK signalling pathways [reviewed by Xu (2000); Lee et al. (2003); Bolker (1998) and Chapter 1]. Mutants carrying impairments in these signalling pathways are often perturbed in asexual sporulation
(Table 1.1 and 1.2). It is probable that signalling effectors critical for asexual sporulation are altered in these signalling mutants. However, knowledge on such components in plant pathogenic fungi is scarce and needs further investigation.
In S. nodorum , mutants defective in the Class I Gα subunit Gna1 and the
Fus3/Kss1 MAPK Mak2 failed to produce pycnidia and were unable to sporulate
(Solomon et al. , 2004b; Solomon et al. , 2005b). Proteomic analysis has led to the identification of SNOG_10217.1 as an effector gene of Gna1 and Mak2 signalling that encodes a novel short chain dehydrogenase (Chapters 3 and 4). Targeted gene deletion was used to inactivate the gene to determine its role during infection on wheat. From here on, SNOG_10217.1 is referred to as Sch1 (short ch ain dehydrogenase 1) whereas the derived polypeptide will be referred to as Sch1.
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5.2 Materials and methods
5.2.1 Sch1 gene knockout vector construction and gene deletion
Sch1 was deleted by gene replacement (Figure 5.1). The 5' and 3' untranslated region (UTR) of Sch1 was PCR amplified with the primer pairs 5'FwdXhoI
R567/5'RevHindIII R567 and 3'FwdPstI R567/3'RevNotI R567, respectively.
Restriction sites were introduced into the primer sequences to facilitate cloning with the phleomycin selectable marker plasmid vector pBSK phleo constructed by Solomon et al. (2006c). To achieve this, the 5' Sch1 UTR amplicon (562 bp) was introduced into
Xho I and Hin dIII sites of pBSK phleo to give pBSK phleo 5'Sch1. Following this, the
3' Sch1 UTR amplicon (850 bp) was cloned into Pst I and Not I sites of pBSK phleo
5'Sch1 to give the knockout vector pBSK Sch1KO. A 3.52 kb gene deletion KO construct was PCR amplified from pBSK Sch1KO using the primer pair R567FwdKO and R567RevKO. The PCR amplified product was then purified with a QIAquick PCR
Purification Kit (Qiagen) and used in the transformation of SN15 as described in
Chapter 2. Resulting phleomycin resistant transformants were selected by single spore isolation. PCR was used to screen transformants for gene knockout strains. The primer pair R5675'KOScr (5’ TTCGCGCTCGCTCGTATGCA 3’) and R5673'KOScr (5’
TCGCTGTGCCAGTAAAACGAGG 3’) designed to flank the homologous recombined gene knockout vector was used to screen for sch1 mutants. Transformants carrying an intact Sch1 gene produced a 4.2 kb amplicon whereas a substitution with the
KO construct produced a 5.5 kb PCR product.
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35 Sch1 knockout vector construction (Figure 5.1)
Probe i
ii
iii
Figure 5.1. i. The Sch1 knockout vector was constructed by ligating PCR
amplified 5' and 3' UTR region of Sch1 to the Xho I/ Hin dIII and Pst I/ Not I
restriction sites of pBSK phleo, respectively. ii. The knockout vector was PCR
amplified and transformed into SN15 to facilitate iii. homologous gene
replacement. Restriction sites are as follows, X. Xho I; H. Hin dIII; P. Pst I and N.
Not I. Primers are as follows:
Xho I 1. 5'FwdXhoI R567 (5’ CTCGAG ATCTACGCCTTGGTCCAGTG 3’ ) Hin dIII 2. 5'RevHindIII R567 (5’ AAGCTT TAGCTGCGGAGTCGTGATCT 3’) Pst I 3. 3'FwdPstI R567 (5’ CTGCAG GAAGGGCAGATGAGTGTAA 3’) Not I 4. 3'RevNotI R567 (5’ GCGGCCGC TACACATAAACTTAGACTTG 3’) 5. R567FwdKO (5’ CCTTGGTCCAGTGGAATCGGA 3’) 6. R567RevKO (5’ CGACCTCGTCATCGTATGGAAAACT 3’) Bold text refers to introduced restriction sites used for cloning.
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5.2.2 2D SDS-PAGE analysis
As described in Chapter 3.
5.2.3 Spore germination assay
To assess spore germination frequencies, germination assays were performed by inoculating 150 spores onto 0.5% agarose overlaid thinly on a microscope glass slide.
Spores were left to germinate for six h prior to scoring under a light microscope for the presence of out growing hyphae. One hundred spores were counted in biological triplicates. One way ANOVA using the Tukey Kramer test was used to statistically analyse the data for significant differences (p < 0.05).
5.2.4 Osmotolerance assays
Osmotolerance assays were performed using two methods. The first assay was performed on CzV8CS medium supplemented with 0, 0.25, 0.5, 0.75 and 1 M NaCl in a standard size Petri dish. The medium was inoculated at the centre with a mycelial plug
(~0.7 x ~0.7 cm). The fungus was left to grow on the medium for two weeks and the diameter was measured. The second method was performed in a similar fashion as the carbon test described in Chapter 2 with the addition of NaCl to final concentrations of 0,
0.25, 0.5, 0.75 and 1 M NaCl. Twenty five mM glucose was used as a carbon source.
Ten L of crushed mycelium from a stock OD 595nm absorbance of 0.05 was used as an inoculum. An OD 595nm reading was taken at day 0 and again at day four. Net growth was determined by subtracting the optical density of day 0 from day four. The experiment was performed with five biological replicates.
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5.2.5 Protoplasting of the sch1-42 mutant
The sch1-42 mutant was tested for the capability of producing protoplasts for genetic transformation. SN15 and Ect were used as control strains. This was carried out according to Chapter 2 with modifications. These modifications were 1. 3 x 10 6 spores of sch1-42 and 2. mycelia from a two week old CzV8CS plate cultures pulverised with mortar and pestle, were grown for 20 h in CzV8 broth prior to the protoplasting procedure. Protoplasts generated from SN15 and Ect were resuspended in two mL of STC buffer and diluted 500 fold whereas protoplasts derived from sch1-42 were resuspended in 40 L of STC prior to visualisation with a light microscope.
5.2.6 Microscopy analysis and basic photography
Light microscopy analysis was performed with an Olympus BH 2 compound microscopy fitted with Olympus DP12 image acquirement hardware. Stereomicroscopy was performed with an Olympus SZ ST stereo microscope unless stated. All photographs except for light microscopy images were taken with a Nikon Coolpix 995.
5.2.7 Histological staining of cross-sectioned tissues
Tissues for cross section histological examination were fixed and degassed overnight in formal acetic alcohol solution in a glass vial (Sass, 1958). For embedding in paraffin, the tissue was dehydrated in an ascending series of ethanol (70%, 90% and
100% ethanol, three h for each step). The tissue was then cleared in two rounds of chloroform prior to infiltration with molten paraffin wax (Paraplast). The paraffin block containing the tissue was sectioned at 10 m with a Leica RM225 microtome. The section was embedded onto a glass slide at 60 oC overnight. Prior to staining and
139 Chapter 5
microscopic analysis, the wax was removed from the section and washed by two rounds of xylene for five min each.
For embedding in Spurr’s resin (Spurr, 1969), the fixed tissue was washed in several changes of 0.025 M phosphate buffer and dehydrated in an ascending series of acetone (30%, 50%, 70%, 90% and 100% acetone, two changes of each solution and 15 min for each change). The tissue was then infiltrated with an ascending series of
Spurr’s resin (5%, 10%, 20%, 40% and 80% Spurr’s resin in acetone, two h for each step). The tissue was then transferred to 100% Spurr’s resin for two h and again for overnight incubation. The resin block was then cut into one m sections with a
Reichert Jung 2050 microtome. Each section was fixed onto a glass slide by incubation at 60 oC overnight. Prior to staining and microscopic analysis, the resin was removed from the tissue section with saturated potassium hydroxide in ethanol. The section was then washed in water and dried at 60 oC.
For non specific tissue staining, the paraffin section was stained with 1% toluidine blue stain. The resin section was stained with a mixture of 1% methylene blue and 1% azur II in 1% sodium tetraborate solution (Richardson et al. , 1960).
The paraffin section was stained with 4’,6 diamidino 2 phenylindole dilactate
(DAPI) (Kubista et al. , 1987) according to the manufacturer’s instruction (Invitrogen).
The stained sample was viewed under an Olympus BX51 compound microscope fitted with a U RFL T UV filter. Fluorescent excitation was set at 358 nm.
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Bright field or differential contrast interference (DIC) mode was used to view all other cross sectioned light microscope tissue images. All light microscope images were captured with the DPcontroller software (Olympus).
For transmission electron microscopy (TEM) analysis, tissues fixed in Spurr’s resin were cut into into 80 nm sections with a Reichart Ultracut E. The section was mounted onto a copper grid 200 mesh (ProSciTech) and stained for 20 min in a saturated solution of uranyl acetate. Following this, the section was washed twice in distilled water, stained in lead citrate for four min and washed again with several changes of distilled water (Venable & Coggshall, 1965). TEM was used to view the stained specimen. This was performed with a Phillips CM100 Biotransmission EM set at 80 kV high tension.
5.2.8 Leaf clearing and viability staining
Diseased leaf tissue was cleared and stained with trypan blue using a modified protocol described by Bruzzese & Hasan (1983) and Shipton & Brown (1962). This involved boiling the infected leaf in trypan blue stain for five min. Prior to light microscopy analysis, the stained leaf was washed in several rounds of 100% ethanol to remove excess stain.
5.2.9 Preparations of biological materials for polar metabolite analysis
Growth of fungal strains and metabolite analysis were performed as described by Solomon et al. (2004b) with modifications. Half a standard size Petri dish of two week old fungus approximated to 250 mg of mycelia was inoculated into a conical flask
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containing 25 mL of MM broth supplemented with 25 mM glutamate as the sole carbon source and a piece of polyethylene foam (~2 x ~2 x ~0.5 cm). The foam was used to mimic the physical in planta environment. The fungus was allowed to grow with shaking at 140 rpm for three days at 22 oC. The foam piece with the attached fungus was collected, washed with ice cold sterile deionised water and snap frozen prior to metabolite extraction. For the analysis of extracellular metabolites, one mL of culture supernatant was collected and lyophilised (Heto MAXI dry lyo). The supernatant was derived from a four day old fungal culture grown in a similar fashion as described but supplemented with 10 mM glucose as a carbon source. The lyophilised supernatant was processed in methanol as described below. Biological triplicates were used.
5.2.10 Metabolite extraction
The frozen sample was ground in liquid nitrogen with a mortar and pestle. Fifty to 100 mg of finely ground sample was collected and placed in a pre weighed two mL tube containing one mL methanol and 50 L of 0.2 g. L 1 ribitol. This was re weighted to obtain the fresh weight of the collected sample. The remainder ground sample was collected in a similar fashion but without methanol and ribitol. The tissue was DNA extracted using the DNA BioSprint according to Chapter 2. The DNA concentration was determined for the used of metabolite normalisation. The sample immersed in methanol was briefly vortexed and incubated at 70 oC for 15 min and shaken at 1,000 rpm (Eppendorf Thermomixer comfort). The sample was then centrifuged at 20,000 g for five min. The methanolic supernatant containing polar metabolites was retained. The centrifuged pellet was re extracted with 500 L of sterile deionised water and 375 L of chloroform by incubation at 37 oC for five min shaken at
142 Chapter 5
1,000 rpm. The polar phase was retained after centrifugation and combined with the methanol supernatant. The polar metabolite extract was lyophilised (Heto MAXI dry lyo). For metabolomic analysis of infected plant materials, detached leaf assays were used for infection. Diseased lesions were excised from nine days post infected
(coinciding with pycnidiation) detached wheat leaves. Metabolite extraction of excised lesions was carried as described above.
5.2.11 Derivatisation of metabolites
The metabolite sample was derivatised by methoxyamination of the carbonyl groups by the addition of 50 L methoxyamine hydrochloride (Sigma) in pyridine
(Solomon et al. , 2006a). This was left to incubate for 90 min at 30 oC with shaking at
1,200 rpm (Eppendorf Thermomixer comfort). Following this, 80 L of N methyl N
(trimethylsilyl) trifluoroacetamide (Sigma) was added to the sample to facilitate trimethylsilylation (TMS). The mixture was incubated at 37 oC for 30 min. After this, the sample was centrifuged at 20,000 g for one min and 100 L of the supernatant was transferred into a 12 x 32 mm glass vial (Alltech, UK) prior to gas chromatograph mass spectrometry (GC MS) analysis.
5.2.12 GC-MS metabolite separation and detection
5.2.12.1 Electron ionisation
GC MS analysis of derivatised and methylsilylated metabolites was performed according to Solomon et al. (2006a) using electron ionisation. Briefly, samples were injected into the GC MS equipment as one L derivatised metabolites in a 1:20
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(sample:methanol) split ratio. The GC MS equipment consisted of an Agilent 7680 autosampler, an Agilent 6890 gas chromatograph and an Agilent 5973N quadrupole mass spectrometer (Agilent, USA). Perflurotributylamine was used to autotune the GC
MS. A 30 m HP 50+ column with a 250 m internal diameter and 0.25 m film thickness was used for gas chromatography (J & W Scientific, USA). Injection temperature was 230 oC, interface temperature was 300 oC and the ion source temperature was 230 oC. Helium was used as a carrier gas. The helium flow rate was retention time locked to elute mannitol TMS at 24.3 min. The temperature gradient consisted of an initial temperature of 70 oC for five min before reaching the final temperature of 300 oC for three min. The temperature ramp rate was set at 5 oC per min.
Polar metabolites were separated in the GC in a 57 min retention run time.
5.2.12.2 Positive chemical ionisation (PCI)
PCI was performed using the GC MS equipments described above according to the HP 5973 MSD PCI/NCI manual (Hewlett Packard). Briefly, extra high purity methane (>99.97%) was fitted as a chemical ionisation source and used as a carrier gas.
The GC MS was set for positive ion polarity and autotuned with perfluror 5,8 dimethyl
3,6,9 trioxidodecane. A 30 m HP 50+ column with a 250 m internal diameter and
0.25 m film thickness was used for gas chromatography (J & W Scientific, USA). Ion source temperature was set at 250 oC, quadrupole temperature was set at 106 oC and interface temperature was set at 320 oC. Polar metabolites were separated in the GC in a
61 min retention run time.
144 Chapter 5
5.2.13 Metabolite identification
GC MS mass spectra were analysed with the Automated Mass Spectral
Deconvolution and Identification System (AMDIS) version 2.64 (National Institute of
Standards and Technology, USA, http://chemdata.nist.gov/mass spc/amdis/ ) using both auto and manual deconvolution to detect polar metabolites. Auto deconvolution parameters were set to a minimum match factor of 10, one adjacent peak subtraction, medium resolution, low sensitivity and a medium peak shape requirement. The metabolite was analysed with an in house metabolite standard library and a metabolite library obtained from the Max Planck Institute Golm Metabolome Database
(http://csbdb.mpimp golm.mpg.de/csbdb/gmd/gmd.html ). Identified metabolites were given the following nomenclature; for example, an AMDIS output of L Phenylalanine
(2TMS) with a chromatographic retention time (RT) of 21.8493 was given as “RT 21.85
L Phenylalanine (2 TMS)”. Unidentified metabolites were classified tentatively by the best matching spectrum from above libraries and given a nomenclature as “RT
[Metabolite (TMS)]”.
5.2.14 Metabolite normalisation
To quantify and analyse polar metabolites from fungal strains for differential abundance, the integrated signal calculated by AMDIS through manual and auto deconvolution, was collected for each metabolite and normalised accordingly. Detected metabolites were selected for analysis under two conditions. Firstly, a tentative match must have an AMDIS minimum abundance value greater than 0.005% and secondly, the metabolite must be present in more than one biological replicate. The normalisation process from here on is as described by Solomon et al. (2006a) with modifications. The
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integrated signal area of each metabolite was divided by the integrated signal area of ribitol (5 TMS) which elutes at a retention time of 20.57 min to give an area.ribitol 1 value. This value was then divided by the fresh weight of the tissue used for metabolite extraction and again by the DNA concentration per mg of fresh weight to give a value of area.ribitol 1.fresh weight 1.DNA concentration 1 for normalised metabolite abundance. An average was calculated from the normalised value of biological replicates to give avg( N1 ).
5.2.15 Statistical analysis for metabolomic analysis
Principal component analysis (PCA) was used to analyse the log 10 (R1 ) values of the all the metabolite derivatives. PCA is a multivariate analysis procedure that is used for the simplification of data for the identification of patterns of similarities and differences. PCA is able to separate variances into unique coordinates; the greatest variance of the data is plotted on the first coordinate known as principal component one and the second greatest variance into an alternate coordinate known as principal component two and so on. PCA was performed with the JMP IN version 5.1 software after log 10 transformation of avg( N1 ) giving rise to log 10 (R1 ) (Desbrosses et al. , 2005).
Often, metabolites that are not detected in some samples were classified as missing values. A zero was given to missing values to facilitate PCA hence, log 10 (R1 ) = 0
(Desbrosses et al. , 2005). One way ANOVA set for Tukey Kramer analysis was used to compare the normalised value of each metabolite for significant differences.
Metabolite abundance was considered significantly different if the normalised values from both sch1 mutants were different to both SN15 and Ect (p < 0.05).
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5.2.16 Determination of the RT4557 retention index
The retention index of RT4557 was estimated from a standard curve constructed with the retention time of n alkane standards. The retention index of the n alkanes was calculated according to van den Dool & Kratz (1963) using the following formula;
t − t I =100N +100n Ra RN a tR( N +n) − tRN
where; Ia represents the retention index of the component N is the number of carbon of the lower n alkane N is the difference in carbon number of the two n alkanes that bracket the compound tRa is the retention time of the component tRN is the retention time of the lower n alkane tR(N+n) is the retention time of the higher n alkane
From here, a linear formula was constructed to elucidate the retention index of
RT4557 based on the relationship between the retention index and RT of C15, C19,
C22, C28 and C38 n alkanes;
I a = 65.36tRa − .1 53
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5.3 Results
5.3.1 Identification of Sch1 from Gna1 and Mak2 -deleted strains
The protein spot C2 was reduced in abundance in gna1-35 and mak2-65
(Chapters 3 and 4). LC MS/MS data of spot C2 were matched against the Broad annotated S. nodorum genome with the Mascot software. This was able to produce a significant match to a polypeptide encoded by SNOG_10217.1 located in supercontig
16 (Figure 5.2). Two predicted introns within Sch1 were confirmed by peptide coverage. The predicted polypeptide length of Sch1 is 299 amino acids.
5.3.2 Polypeptide sequence analysis of Sch1
Examination of the polypeptide sequence revealed a number of motifs common to the short chain dehydrogenase family (Oppermann et al. , 2003) (Table 5.1). Amino acid sequence analysis using the 3D JIGSAW software indicates that the secondary structure of Sch1 consisted of a series of alternating α helices and β sheets (Figure 5.3).
PSORT II prediction indicates that Sch1 is likely to reside in the cytoplasm (65.2% likelihood). Top NCBI BlastP matches for Sch1 were fungal predicted proteins possessing a predicted short chain dehydrogenase domain (Table 5.2). No significant
BlastP matches to fungal genes documented for pathogenesis were observed. The genome sequence of the dothideomycete Pyrenophora tritici-repentis is available in
NCBI as unassembled traces. Cross species Megablast and tBlastN of Sch1 nucleotide and protein sequences did not result in a match to P. tritici-repentis traces. A putative
Goldberg Hogness box core promoter site is located 663 base pairs upstream of Sch1 .
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Spot C2 A 1. FGENESH 00290212213 Score: 480 Queries matched: 10 Query Observed Mr(expt) Mr(calc) Delta Miss Score Expect Rank Peptide (Brot & Weissbach, 1983). 2 429.86 428.86 429.30 -0.44 0 21 1.1 3 VLAK 8 409.68 817.35 817.42 -0.07 0 18 2.3 5 SLAPSDTK 16 466.22 930.43 930.50 -0.07 0 65 4.1e-05 1 ADVLESVAK 36Mass 20 spectrometry 530.26 peptide 1058.51 coverage 1058.60 of Sch1-0.08 (Figur 1 e 5.2) 51 0.00099 1 KADVLESVAK 27 601.33 1200.64 1200.71 -0.07 0 51 0.00086 1 TVLITGVSGGIGK 38 867.89 1733.77 1733.88 -0.11 0 96 1.7e-08 1 AADITDEASVAALFAAAK 39 900.42 1798.82 1798.94 -0.12 0 43 0.0034 1 DVYPLLEPTQPELSAK 40 915.93 1829.84 1829.96 -0.13 0 (81) 5.4e-07 1 AIAESWATAGASGIVITGR 41 610.96 1829.86 1829.96 -0.10 0 90 6.5e-08 1 AIAESWATAGASGIVITGR 45 652.65 1954.93 1955.04 -0.11 1 45 0.0016 1 RDVYPLLEPTQPELSAK B Spot C2 (repeat) 1. cDNA FP-1_F01. Score: 343 Queries matched: 14 Frame: 3 Query Observed Mr(expt) Mr(calc) Delta Miss Score Expect Rank Peptide 15 530.27 1058.52 1058.60 -0.08 1 29 0.068 1 KADVLESVAK 18 601.32 1200.63 1200.71 -0.08 0 42 0.0028 1 TVLITGVSGGIGK 27 527.56 1579.66 1579.78 -0.12 0 21 0.26 1 IMENLHAEQPNIR 28 790.85 1579.68 1579.78 -0.10 0 (16) 0.79 1 IMENLHAEQPNIR 33 867.89 1733.77 1733.88 -0.11 0 62 2e-05 1 AADITDEASVAALFAAAK 35 900.42 1798.83 1798.94 -0.11 0 22 0.17 1 DVYPLLEPTQPELSAK 37 915.93 1829.84 1829.96 -0.12 0 81 1.8e-07 1 AIAESWATAGASGIVITGR 38 610.96 1829.85 1829.96 -0.11 0 (72) 1.7e-06 1 AIAESWATAGASGIVITGR 42 652.65 1954.93 1955.04 -0.11 1 25 0.075 1 RDVYPLLEPTQPELSAK 46 715.65 2143.93 2144.08 -0.15 0 20 0.18 1 IDVLINNAGSLGGGMVGSTEPK 47 1072.97 2143.93 2144.08 -0.14 0 (19) 0.26 1 IDVLINNAGSLGGGMVGSTEPK 54 825.42 2473.24 2473.40 -0.16 0 11 0.96 1 VFQLIPGIVLTGMTVDALKPFAK 55 843.36 2527.05 2527.20 -0.15 1 33 0.0061 1 GGIVSVNWDVEEMEAHKDEIVR 56 632.80 2527.17 2527.20 -0.03 1 (28) 0.025 1 GGIVSVNWDVEEMEAHKDEIVR C SNOG _10217.1 1 ATGGATTACTCCGACCCCAACGCATTCACCCTACCCTACCAGTTGACCAAGCAAATCCGC M D Y S D P N A F T L P Y Q L T K Q I R 61 CGTGATGTCTATCCACTGCTGGAGCCAACGCAGCCAGAGCTTTCAGCAAAAGGAAAGACA R D V Y P L L E P T Q P E L S A K G K T 121 GTACTCATCACAGGCGTTTCCGGAGGCATAGGCAAGGTAAGCACGATTTTCGAGACTCGA V L I T G V S G G I G K 181 TTGTCCTTTTCCGTGACTAACGCATG CAGGCCATCGCCGAATCATGGGCCACCGCGGGAG A I A E S W A T A G 241 CTTCTGGAATCGTGATTACTGGACGGAAAGCCGATGTGCTTGAGAGCGTCGCCAAGTCAC A S G I V I T G R K A D V L E S V A K S 301 TCAAGAGTCTTGCCCCATCCGACACCAAAGTCCTCGCCAAGGCAGCCGACATCACTGACG L K S L A P S D T K V L A K A A D I T D 361 AAGCATCGGTCGCGGCGCTCTTCGCCGCTGCCAAAGAGGCGGTCGGCAAGATCGATGTGC E A S V A A L F A A A K E A V G K I D V 421 TGATCAACAACGCAGGCAGTCTAGGAGGGGGCATGGTGGGTAGCACCGAACCTAAGGACT L I N N A G S L G G G M V G S T E P K D 481 TCTTCGCGGACTTCCAGGTAAACGTTCTGGGCACGTACATAGTGACGCACCAATTCCTCG F F A D F Q V N V L G T Y I V T H Q F L 541 CCCAGGCAGACGGATCTGGTACTGTCATCAGCTTCACAACAGGCGCCATCGCCAATGTTT A Q A D G S G T V I S F T T G A I A N V 601 TCCCAGGTATGGGAGCCTACACGGCGTCCAAGACGGCCCTTACCCGCATCATGGAAAATC F P G M G A Y T A S K T A L T R I M E N 661 TGCACGCCGAGCAGCCAAACATTCGTGTTTTCCAGCTCATTCCGGGAATTGTTCTAACGG L H A E Q P N I R V F Q L I P G I V L T 721 GAATGACGGTCGATGCGTTGAAGCCGTTTGCGAAGGACACTCCCGAGCTCAGTGCCAGCT G M T V D A L K P F A K D T P E L S A S 781 GGACACTCTTCCTGTCTACCCCTCGCGCCGAATGGTTGCGTGGCGGCATAGTCAGCGTCA W T L F L S T P R A E W L R G G I V S V 841 ACTGTGAGTCTGCCCCCAATTGCTTAAAACTTCCTACAATTCTGACATGAGGTTCTATCA N 901 ACA GGGGATGTCGAGGAGATGGAGGCCCACAAGGATGAAATTGTTCGTGACAACTTGCTC W D V E E M E A H K D E I V R D N L L 961 AGCCGCGCTTTCTTGAACGCCAAGCTCGGAAAGGATGGCCATCCCTGGTCTTGA S R A F L N A K L G K D G H P W S * Figure 5.2. A. LC MS/MS analysis of spot C2. Mascot was used to match the mass spectrum generated by trypsinated peptides to the Broad predicted S. nodorum protein database for a matching gene (red font). B. A repeat analysis was performed on an SN15 oleate grown cDNA library taking in account of peptide modifications from common oxidation of methionine residues (Brot & Weissback, 1983) (blue font). C. Peptide coverage of Sch1. 149 Chapter 5
(Oppermann et al. , 2003)
37Predicted motifs in Sch1 (Table 5.1)
Table 5 .1. Consensus short chain dehydrogenase motifs in Sch1. Motifs were predicted from sequence alignments with other short chain dehydrogenases (data not shown). Adapted from Oppermann et al. (2003). Consensus motif Function Predicted Sch1 motif (position*) (position) TGxxxGxG (12 19) Coenzyme binding region, TGVSGGIG (44 51) maintenance of central β sheet D (60) Stabilisation of adenine ring D (96) pocket, weak binding to coenzyme NNAG (86 89) Stabilisation of central β sheet NNAG (125 128) N S Y K (111, 138, 151, 155) Active site N x Y K (150, x, 189, 193) N (179) Connection of substrate binding Not determined loop and active site PG (183 184) Reaction direction PG (217 218) T (188) H bonding to carboxamide of T (221) nicotinamide ring
*Positions refer to the amino acid order from the N terminus of a characterised short chain dehydrogenase (PDB code 1hxh).
150 Chapter 5
(Jornvall et al. , 1995)
38Predicted secondary structure of Sch1 (Figure 5.3)
βββA αααB HH EEEEE HHHHHHHHHHHH 1 MDYSDPNAFTLPYQLTKQIRRDVYPLLEPTQPELSAKGKTVLITGVSGGIGKAIAESWAT β B αααC βββC αααD EEEEEEE HHHHHHHHHHHHHH EEEEE HHHHHHHHHHHHHH 61 AGASGIVITGRKADVLESVAKSLKSLAPSDTKVLAKAADITDEASVAALFAAAKEAVGKI
βββD αααE βββE EEEE HH HHHHHHHHHHHHHHHHHHHHHHHHHH EEEEE HHH 121 DVLINNAGSLGGGMVGSTEPKDFFADFQVNVLGTYIVTHQFLAQADGSGTVISFTTGAIA α α α F βββF HHHHHHHHHHHHHHHHHHHH EEEEEEE E HHHH HHHH 181 NVFPGMGAYTASKTALTRIMENLHAEQPNIRVFQLIPGIVLTGMTVDALKPFAKDTPELS
α G βββG HHHHHHHH HH EEEE HHHHHHHHHHHHHHHHHHHH 241 ASWTLFLSTPRAEWLRGGIVSVNWDVEEMEAHKDEIVRDNLLSRAFLNAKLGKDGHPWS
Figure 5.3. Secondary structure prediction of Sch1 (blue). ‘H’ denotes α helices and ‘E’ denotes β sheets. Secondary structures were grouped according to Jornvall et al. (1995). There is no αA helix designation in the short chain dehydrogenases described in Jornvall et al. (1995).
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39BlastP analysis of Sch1 (Table 5.2)
Table 5.2. BlastP analysis of Sch1. Top matches to predicted fungal proteins and non fungal proteins are given.
BlastP match Organism Genbank % E-value Polypeptide Top conserved domain hit ( CDD - Function accession similarity length Blast NCBI) Fungal Hypothetical protein Chaetomium EAQ89426 37% 6e 45 300 pfam00106, short chain dehydrogenase Unknown CHGG_06045 globosum Hypothetical protein Gibberella XP_384775 40% 1e 41 359 COG1028, FabG, Dehydrogenases with Unknown FG04599.1 zeae different specificities Hypothetical protein Coccidioides EAS35803 36% 2e 36 324 pfam00106, short chain dehydrogenase Unknown CIMG_01157 immitis Hypothetical protein Aspergillus XP_664678 35% 3e 36 310 COG1028, FabG, Dehydrogenases with Unknown AN7074.2 nidulans different specificities Non-fungal Short chain dehydrogenase Solibacter YP_827156 36% 1e 28 260 pfam00106, short chain dehydrogenase Unknown usitatus Short chain dehydrogenase Polaromonas YP_551544 32% 4e 22 254 pfam00106, short chain dehydrogenase Unknown sp. JS666 3 oxoacyl [acyl carrier Bacillus BAD66294 38% 6e 22 238 pfam00106, short chain dehydrogenase Fatty acid protein] reductase clausii biosynthesis 7 alpha hydroxysteroid Escherichia YP_669471 32% 7e 22 255 pfam00106, short chain dehydrogenase Sterol dehydrogenase coli metabolism
152 Chapter 5
This is indicated by the presence the consensus 5’ TATAAA 3’ nucleotide sequence
(Lifton et al. , 1978; Smale & Kadonaga, 2003).
5.3.3 Sch1 expression
Sch1 expression was analysed using qRT PCR (Chapters 3 and 4). Sch1 transcript abundance was greatly reduced in gna1-35 and mak2-65 when compared to
SN15 in vitro . Therefore, it is highly probable that protein abundance of Sch1 is dictated by heterotrimeric G protein and MAPK signalling mediated transcriptional regulation. To understand the role of Sch1 play during plant infection, gene expression was further examined on S. nodorum infected wheat leaves. Sch1 transcripts accumulated greatly during the late stage of infection coinciding with the development of pycnidia.
5.3.4 Deletion of Sch1
A targeted gene deletion approach was used to investigate the role of Sch1 during pathogenesis on wheat. The identification of sch1 mutants was carried out by
PCR screening 19 phleomycin resistant transformants for gene deletion (Figure 5.4A).
Ten transformants produced a 5.5 kb PCR amplicon indicative of gene knockout. Eight transformants carried an ectopic insertion. This represents a homologous recombination efficiency of 56%. Gene deleted strains sch1-11 and sch1-42 were selected for further analysis. A strain carrying an ectopic integration of the gene knockout vector was selected for further analysis as a transformant control (Ect). Southern analysis was used to confirm the gene knockout and determine the insertion number of the gene knockout
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40PCR and Southern analysis for Sch1 deletion (Figure 5.4)
A 1 11 22 25 30 42 57 58 59 60 61 62 63 64
5.5 kb 4.2 kb
65 66 67 68 69 SN15
5.5 kb 4.2 kb
B i ii iii iv
5.5 kb
4.2 kb
Figure 5.4. A. PCR screening of phleomycin resistant transformants
for potential Sch1-deleted strains. B. Southern analysis of the Sch1
locus of i. SN15, ii. Ect, iii. sch1-11 and iv. sch1-42 . Genomic DNA
was digested with Xho I to generate a 4.2 kb fragment containing an
intact Sch1 in SN15 and Ect. Sch1 knockout strains sch1-11 and sch1-
42 produced a 5.5 kb fragment indicative of gene displacement by the
phleomycin selectable marker cassette.
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41Proteomic confirmation of Sch1 deletion (Figure 5.5)
i ii
iii iv
Figure 5.5. 2D electrophoresis detection of Sch1 in i. SN15, ii.
Ect, iii. sch1-11 and iv. sch1-42 . Sch1 was observed in SN15
and Ect (arrows) but not in the sch1 mutants. Significant
alterations in surrounding protein spots (blue arrows) were
observed. This was discussed in Section 5.3.6.
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construct in the selected strains (Figure 5.4B). A 562 bp probe generated from the 5'
UTR of Sch1 was used to detect size polymorphism at the Sch1 locus of SN15 and mutant strains. SN15 and Ect produced a 4.2 kb Xho I fragment carrying an intact gene whereas sch1-11 and sch1-42 produced a 5.5 kb Xho I fragment indicative of Sch1 displacement by the knockout construct.
5.3.5 Proteomic confirmation of Sch1 deletion
2D electrophoresis was used to verify that the deleted gene corresponded to the protein of interest (Figure 5.5). The experimental MW and pI of Sch1 is 28.5 kDa and
5.94, respectively. The Sch1 protein spot was observed in SN15 and Ect but not sch1-
11 and sch1-42 . This strongly indicates a correct protein to gene assignment via mass spectrometry identification and provides strong evidence of gene deletion.
5.3.6 Comparative proteomic analysis of SN15 and sch1-42
The intracellular proteomes of SN15 and sch1-42 were compared and analysed for changes in protein abundance by 2D electrophoresis. A total of 350 unique protein spots were identified from SN15 and sch1-42 . A comparison of spots with the
ProGENESIS Workstation 2005 software has identified four protein spots that were significantly altered in abundance between the two strains (Figure 5.6; Table 5.3).
These proteins spots were excised, trypsinated and analysed with LC MS/MS. Mass spectrometry derived data were matched to the S. nodorum genome for corresponding genes via Mascot. The experiment was performed in biological triplicates. Normalised protein abundance values are listed in Appendix F.
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A 5 pH 8 kDa
250 42Intracellular 2D proteome gels of SN15 and sch1-42 (Figure 5.6)
75
50
37
25 C1 C2
C11 C10 15
10
B 250
75
50
37
25 C2 C1
C11 C10 15
10
Figure 5.6. Representative 2D gels of A. SN15 and B.
sch1-42 intracellular proteomes. Differentially abundant
spots are indicated. The experiment was performed in
biological triplicate. Gel contrasts were relatively adjusted
to allow visualisation of highly abundant spots in sch1-42 .
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43Differentially abundant intracellular protein spots of SN15 and sch1-42 (Table 5.3)
Table 5.3. Identification of differentially abundant intracellular proteins with LC MS/MS. Mascot was used to pattern matched the mass
spectrometry data with the S. nodorum whole genome annotated protein set to give a gene match. Fold difference of matching protein spots was
calculated from normalised spot value of SN15 relative to sch1-42 . Fold difference designated by ( ) indicates protein spots that were not
observed in sch1-42 proteome gel whereas (++) designate spots that were not observed in the SN15 proteome gel. BlastP identity and E value are
given in Appendix D. Molecular weight (MW) is given in kDa. Spot Fold Observed Broad acc ID Theoretical CDD Blast BlastP match (Organism; Mascot score diff pI MW pI MW (Expected value) Genbank acc ID) (% coverage) C1 +2.2 5.95 25.6 SNOG_13042.1 5.41 28.9 COG1028: FabG, Short chain dehydrogenase 988 (61.0) dehydrogenases with different (Aspergillus fumigatus ; XP_748339.1) specificities (2E 12) C2 6.10 25.7 SNOG_10217.1 5.46 31.8 COG4221: Short chain alcohol Short chain dehydrogenase/reductase 514 (38.5) dehydrogenase of unknown SDR ( Solibacter usitatus ; specificity (3E 27) ZP_00520385.1) C10 +8.6 7.00 19.0 SNOG_09590.1 5.98* 23.3* CD02140: Nitroreductase like Nitroreductase family protein ( Bacillus 564 (60.5) family 4 (3E 70) cereus ; ZP_00240643) C11 ++ 6.79 19.6 SNOG_09590.1 5.98* 23.3* CD02140: Nitroreductase like Nitroreductase family protein ( Bacillus 393 (52.7) family 4 (3E 70) cereus ; ZP_00240643) *Prediction based on re annotated values. Refer to Chapter 6.
158 Chapter 5
443D imaging of spot C1 (Figure 5.7) i ii
pH MW pH MW
iii iv
pH MW pH MW
v vi
pH MW pH MW
Figure 5. 7. Three dimensional densitometry analysis of spot C1 (red
arrows) in SN15 ( i. iii . and v. ) and sch1 - 42 ( ii . iv. and vi .) triplicate 2D
intra cellular proteome gels. Black arrows indicate the gel orientation by
increasing pH and decreasing MW .
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Spot C1, previously identified as a putative short chain dehydrogenase
(SNOG_13042.1), accumulated greatly in sch1-42 . The average normalised densitometry value of spot C1 of sch1-42 is 2.2 fold greater than the corresponding spot in SN15. Three dimensional densitometry indicated pixel saturation of all C1 designated spots in sch1-42 (Figure 5.7). This indicates that the upper detection limit of colloidal Coomassie G250 has been reached. Therefore, it is highly probable that the actual abundance of spot C1 in sch1-42 is greater than the current values calculated from densitometry analysis by ProGENESIS.
Peptides generated from spot C10 and C11 matched to the predicted polypeptide of SNOG_09590.1. The predicted polypeptide showed a significant sequence similarity to a nitroreductase protein of Bacillus cereus (48% similarity and an expected value of
6E 51). Spot C10 is 8.6 fold more abundant in sch1-42 , whereas spot C11 was not detected in SN15. The observed pI differed from predicted values for spot C10 and C11 thus suggesting that post translational modifications may affect the location of the protein in the 2D gel.
5.3.7 Colony morphology of the sch1 mutants
The colony morphology of sch1-11 and sch1-42 was compared to SN15 and Ect
(Figure 5.8). When grown on solid CzV8CS and MM agar, Ect showed similar colony morphology to SN15. The sch1 strains produced a green pigment on the older part of the colony similar to gna1-35 (Solomon et al. , 2004b). All strains showed similar radial growth rate on CzV8CS agar (Figure 5.9A). When grown on MM agar supplemented with 25 mM glucose, the sch1 mutants were significantly reduced in radial growth when
160 Chapter 5
CzV8CS Minimal medium agar 45Colony morphology of theagar sch1 mutants on agar media(25 (Figure mM 5.8)glucose) i
ii
iii
iv
Figure 5 .8. The colony morphology of i. SN15, ii. Ect, iii.
sch1-11 and iv. sch1-42 growing on agar media.
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46Colony diameter of the sch1 mutants on agar media (Figure 5.9)
A 70 a a a a 60 50 40 30 20 10 Colony diameter (mm) Colonydiameter 0 SN15 Ect sch1-11 sch1-42 Strain B 70 a a b b 60 50 40 30 20 10 Colony diameter (mm) Colonydiameter 0 SN15 Ect sch1-11 sch1-42 Strain
Figure 5.9. The colony diameter of SN15, Ect, sch1-11 and
sch1-42 grown on A. CzV8CS and B. MM agar
supplemented with 25 mM glucose for 13 days were
measured and statistically analysed (n = 2). Standard error
bars are shown.
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47Morphology of the sch1 mutants in liquid culture (Figure 5.10)
i ii
iii iv
Figure 5.10. The morphology of i. SN15, ii. Ect, iii. sch1-11 and iv. sch1-42 after 24 h growth in MM broth supplemented with 25 mM glucose. All cultures were shaken at 140 rpm. Bar = 1 cm.
163 Chapter 5
compared to SN15 and Ect (Figure 5.9B). It was also observed that the sch1 mutants produced more aerial hyphae than the Sch1 strains on MM agar.
The morphology of SN15, Ect and sch1 mutants was examined as submerged
MM broth cultures (Figure 5.10). After 24 h of growth from crushed mycelial scrapings shaken at 140 rpm, mycelia of SN15 and Ect were dispersed throughout the broth.
However, mycelia of the sch1 mutants were clumped. Growth of the sch1 mutants on different carbon sources was examined with in a microtitre plate format as described in
Chapter 2. Growth of the sch1 mutants on glucose, fructose, mannitol, trehalose and oleate was similar to SN15.
5.3.8 Osmotolerance assays
The sch1-42 mutant was tested for osmotolerance using two methods. The first method tested the radial growth rate of sch1-42 on CzV8CS agar supplemented with 0,
0.25, 0.5, 0.75 and 1 M NaCl. After two weeks of growth, the diameter of the colony of sch1-42 was not significantly different to the Sch1 strains under all concentrations tested. The second method examined the growth of sch1-42 in grown in a stationary
MM broth supplemented with 0, 0.25, 0.5, 0.75 and 1 M NaCl. This was performed as per the 96 well microtitre plate carbon test format (Chapter 2). Net growth was measured after four days incubation. The growth of sch1-42 was not significantly different to Sch1 strains. This suggests that Sch1 does not play a significant role in osmotolerance.
164 Chapter 5
48Trypan blue staining of infected wheat leaves (Figure 5.11)
i ii
iii iv
Figure 5.11 . Light microscope analysis of trypan blue stained wheat leaves three
days post infected with i. SN15, ii. Ect, iii. sch1-11 and iv. sch1-42 . Red arrows
indicate fungal entry via the stomata. Black arrows indicate epidermal penetration
attempts. Bar = 30 m.
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49Infection assays (Figure 5.12)
A1 B1 i ii iii iv v i ii iii iv v
A2 B2 27 10 24 a a a a b 21 8 18 6 15 12 4 9 Lesion size (mm) size Lesion 6 Disease score 2 3 0 0 SN15 Ect sch1-11 sch1-42 Tween 3 4 5 6 7 8 9 10 11 12 13 14 Days post infection Strain Figure 5.12 . Pathogenicity was measured with the A. detached leaf assay and B. whole plant spray. i. SN15, ii. Ect, iii. sch1-11 , iv. sch1-42 and v. 0.02% (v/v)
Tween negative control. Bar = 5 mm. A2. Lesion sizes caused by SN15 ( ), Ect
(■), sch1-11 ( ▲) and sch1-42 ( x) on the detached wheat leaves were recorded over a 14 day infection period (n = 10). B1. Disease symptoms from whole plant spray and B2. disease score measurements. Standard error bars are shown.
166 Chapter 5
5.3.9 Pathogenicity assays
Trypan blue staining of three day old infected wheat leaves indicate that the sch1 mutants were capable of epidermal penetration attempts and stomatal entry (Figure
5.11). Pathogenicity of the sch1 mutants was assessed with DLA. No differences in symptoms and lesion sizes were observed between all strains. The result indicates that
Sch1 is not required for tissue proliferation on detached wheat leaves (Figure 5.12). The sch1 mutants were tested on their ability to infect whole plants using the whole plant spray assay. Disease symptoms were scored seven days post infection. Lesion symptoms and disease scores of all strains were similar (Figure 5.12). This indicates that Sch1 is not required for penetration and invasive growth on wheat.
5.3.10 Spore phenotyping assays
The sch1 mutants showed sporulation abnormalities (Figure 5.13). Centrifuged spore pellets collected from SN15 and Ect were pink whereas sch1-11 and sch1-42 were white in appearance (Figure 5.13A). Examination under light microscopy has revealed that the resuspended spore pellets of the sch1 mutants were composed of spores and mycelia debris in contrast to SN15 and Ect (Figure 5.13B). The germination frequency of SN15, Ect, sch1-11 and sch1-42 spores was assessed (Figure 5.13C). Spores were left to germinate on 0.5% (w/v) agarose for six h prior to scoring. The germination frequency of sch1-11 and sch1-42 was slightly reduced in comparison to SN15 although no difference was observed when compared to Ect. As the spore germination efficiency of the sch1 mutants was not statistically different to Ect, this suggests that Sch1 is not critical for spore germination.
167 Chapter 5
A i ii iii iv 50Spore pellet and germination rate of the sch1 mutants (Figure 5.13)
B i ii
iii iv
C 100
80
60 a a/b b b 40
20 Germinated spores Germinated 0 SN15 Ect sch1-11 sch1-42 Strain Figure 5.13. A. Centrifuged spores harvested from i. SN15, ii. Ect, iii. sch1 -
11 and iv. sch1-42 grown on CzV8CS agar. B. Light microscope images of
the resuspended spore pellets; i. SN15, ii. Ect, iii. sch1-11 and vi. sch1-42. C.
Spore germination frequencies (n = three counts of 100 spores). Standard error
bars are shown.
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51The length of sch1-42 pycnidiospores (Table 5.4)
52DIC images of pycnidiospores (Figure 5.14)
Table 5.4. The average length SN15, Ect and sch1 -42 pycnidiospores (n = 34).
Strain Length ( m) SE of the mean ANOVA grouping SN15 24.6 ± 0.727 A Ect 23.8 ± 0.526 A sch1-42 18.5 ± 0.472 B
i ii
* * * * * * * * * * * *
* * *
iii
* *
Figure 5.14. DIC images of i. SN15, ii. Ect and iii. sch1-42 pycnidiospores. *
denotes the septum. Bar = 5 m.
169 Chapter 5
53Pycnidiospore count (Figure 5.15) A 1.E+08 a b c c
1.E+07 Logspores
1.E+06 SN15 Ect sch1-11 sch1-42 Strain B 1.E+07 a b c c 1.E+06
1.E+05
1.E+04
Log spores from 5 leaves 5 Logsporesfrom 1.E+03 SN15 Ect sch1-11 sch1-42 Strain
Figure 5.1 5. A. Spores per plate from strains grown on
CzV8CS agar for two weeks. Mean values were
calculated from three technical spore counts from
biologically independent pooled SN15 (n = 3), Ect (n = 3),
sch1-11 (n = 11) and sch1-42 (n = 12) spores. B. In
planta sporulation assay. Mean values were calculated
from three to six technical spore counts of pooled spores
derived from fungal infected leaves. Replicate infected
leaf numbers; SN15 (n = 10), Ect (n = 10), sch1-11 (n = 5)
and sch1-42 (n = 5). Standard error bars are shown.
170 Chapter 5
The length of spores ranged from 14.8 to 32.6 m for SN15 and 19.0 to 33.6 m for Ect. In contrast, the length of spores ranged from 12.6 to 25.4 m for sch1-42 . On average, the length of pycnidiospores from sch1-42 was significantly shorter than those of SN15 and Ect (Table 5.4). Closer examination of pycnidiospores under light microscopy has revealed those of sch1-42 possessed 0 or one septum whereas those of
SN15 and Ect possessed up to three septa (Figure 5.14).
5.3.11 Sporulation of the sch1 mutants
Major reductions in sporulation were observed in the sch1 mutants. Spores were counted from two week old fungal cultures grown on CzV8CS agar. Sporulation efficiencies of sch1-11 and sch1-42 were 5.6% and 5.0% of SN15, respectively (Figure
5.15A). In planta sporulation assays were performed to compare sporulation efficiency of the sch1 mutants with SN15 and Ect. Sporulation of the sch1 mutants was also reduced during growth on wheat leaves (Figure 5.15B). This indicates that Sch1 has a significant role in asexual sporulation.
5.3.12 Pycnidial development of the sch1 mutants
Pycnidia of the sch1 mutants were examined and compared with Sch1 strains for phenotypic abnormalities. Pycnidia of SN15 and Ect exuded pink cirrhi. In contrast, the sch1 mutants rare white cirrhi (Figure 5.16A). The average diameter of SN15 pycnidia when grown on CzV8CS was 208.5 m. This is significantly greater than sch1-11 and sch1-42 where average pycnidia diameters were 142 and 146 m, respectively (Figure 5.16B). The sch1 mutants were able to produce pycnidia during
171 Chapter 5
A i ii
54Pycnidia size measurements in vitro (Figure 5.16)
iii iv
v
B 240 a a b b 220 m) 200 180 160 140 120
Pycnidia diameter ( diameter Pycnidia 100 SN15 Ect sch1-11 sch1-42 Strain
Figure 5.16. A. Photographs of i. SN15, ii. Ect , iii. sch1 -
11 and iv. sch1-42 pycnidia on CzV8CS agar. Bar = 1
cm. v. A close up image of two exuding sch1-42
pycnidia, each producing a white cirrhus. B. Pycnidial
diameter was measured and statistically analysed (SN15,
n = 191; Ect, n = 146; sch1-11 , n = 144 and sch1-42 , n =
286). Standard error bars are shown.
172 Chapter 5
55Pycnidia size measurements in planta (Figure 5.17) A i ii
iii iv
B 130 a b c c 120
m) 110 100 90 80 70 60 Pycnidia size ( size Pycnidia 50 40 SN15 Ect sch1-11 sch1-42 Strain
Fig ure 5.17. A. Photographs of i. SN15, ii. Ect, iii. sch1-11 and iv.
sch1-42 pycnidia taken from trypan blue stained nine day old infected
wheat leaves. Bars = 200 m. B. Pycnidial diameter was measured and
statistically analysed (SN15, n = 69; Ect, n = 69; sch1-11 , n = 151 and
sch1 -42 , n = 184). Standard error bars are shown.
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56Pycnidiation pattern of the sch1 strains on wheat meal agar (Figure 5.18)
i ii
iii iv
Figure 5. 18 . The pycnidiation pattern of i. SN15, ii. Ect, iii. sch1-11 and iv. sch1-
42 on wheat meal agar. Arrows indicate concentrated regions of pycnidial
development. Bars = 2 mm.
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growth on wheat leaves. However, these pycnidia were unable to exude cirrhi unlike
SN15 and Ect. Furthermore, the average diameter of pycnidia of the sch1 mutants was significantly smaller than SN15 and Ect (Figure 5.17).
The pycnidiation pattern of S. nodorum follows a biphasic rhythm likely to be a response to the exposure to the near UV light growth regime. The sch1 mutants were observed for possible defects in the pycnidiation pattern. When grown on wheat meal agar, pycnidia of SN15 and Ect showed a distinct biphasic developmental pattern. The biphasic developmental pattern was observed with the sch1 mutants but was less distinct (Figure 5.18).
The morphology of SN15 and sch1-42 pycnidia was examined with tissue cross sectioning and light microscopy. This was performed on pycnidia derived from growth on CzV8CS agar. Cells of the melanised pycnidial wall contained a brown pigment
(Figure 5.19 i and ii). These cells in SN15 were predominantly thin and elongated whereas corresponding cells in sch1-42 were irregularly shaped. Toluidine blue staining revealed greater details of the pycnidium. The most striking feature that differs between the pycnidia of SN15 and sch1-42 was the intensity of the stained cavity contents (Figure 5.19 iii and iv). The cavity content of SN15 stained intensely with toluidine blue whereas the cavity content of sch1-42 stained poorly. In addition, a distinct subparietal layer that lined the inner wall of the pycnidium was observed in
SN15. This layer was less defined in sch1-42 . The chirrus of SN15 was predominantly composed of pycnidiospores. In contrast, the chirrus of sch1-42 was composed of
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W i ii W
57Cross-section light microscopy analysis of sch1-42 pycnidia (Figure 5.19)
Cv Cv
iii iv Ch Ch S
W
OC OC Cv Cv
SL
100 m 100 m
v 20 m vi
S
20 m
vii W viii C
S Cv
Cv
SL PC PC 20 m 20 m Figure 5.19. Continued on the next page.
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Figure 5.19 . Cross section photographs of SN15 ( i, iii and v) and sch1-42 ( ii , iv and vi ) pycnidia from growth on CzV8CS agar and wheat leaves ( vii and viii). The morphology of cells from the pycnidial wall was examined under DIC microscopy using unstained specimens ( i and ii ). iii and iv shows the general morphology of erupting pycnidia stained with toluidine blue. Close up detailed images of chirri stained with toluidine blue ( vii and viii ). v and vi shows the morphology of pycnidia formed during growth on wheat leaves stained with methylene blue/azur II. Key = W, pycnidial wall; Cv, pycnidial cavity; Ch, chirrus; S, spore; OC, ostiolar cone; SL, subparietal layer; C, conidiogenous cell and PC, plant cell.
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i ii 20 m Cv
58Cross-section TEM analysis of sch1-42 pycnidia (Figure 5.20) C vi
iii v iv C
Cv 20 m
iii iv
S
2 m 2 m
v vi
Vc
CW Vc Cp Vc
Vc
CW
Vc
1 m 1 m Figure 5.20. Detail analysis of pycnidial tissues of SN15 ( i, iii and v) and sch1-42 ( ii , iv and vi ) from growth on CzV8CS agar. Cross sections were stained with methylene blue/azur II for light microscopy ( i and ii ) and lead citrate/uranyl acetate for TEM analysis ( iii , iv , v and vi ). Images of the pycnidial cavity ( iii and iv). Photographs of cells of the pycnidial wall ( v and vi). Key = S, spore; Cv, pycnidial cavity; C, conidiogenous cell; CW, cell wall; Cp, cytoplasm and Vc, vacuole. 178 Chapter 5
septated hyphae. No pycnidiospores were observed in the chirrus of sch1-42 (Figure
5.19 v and vi). Pycnidia of SN15 and sch1-42 on wheat leaves showed similar morphological defects to those derived from growth on CzV8CS agar (Figure 5.19 vii and viii). At a greater magnification, conidiogenous cells in SN15 showed a compact arrangement. In contrast, the conidiogenous cell layer was less defined in sch1-42
(Figure 5.20 i and ii). TEM was used to analyse the pycnidial cross sections. Electron dense structures were observed in the pycnidial cavity of SN15 and were presumed to be pycnidiospores. These structures were not observed in sch1-42 (Figure 5.20 iii and iv). SN15 cells from the pycnidial wall were rounder. Electron dense materials, presumed to be cytoplasmic constituents, were often located adjacent to the intracellular side of the cell wall. A significant portion of the cell volume was occupied by a large vacuole. In contrast, corresponding cells in sch1-42 were irregularly shaped and contained numerous small vacuoles. Electron dense materials were often scattered throughout the cell (Figure 5.20 v and vi).
Pycnidia of SN15 and sch1-42 were examined for nuclei distribution using the dsDNA specific DAPI fluorescent stain (Figure 5.21). The SN15 subparietal layer was distinguishable from the cell wall as the latter tissue lacked nuclei. Nuclei were also observed in spores located in the pycnidial cavity amidst the background fluorescence.
Interestingly, the pycnidial cell wall and subparietal layer of sch1-42 were indistinguishable as DAPI staining indicates that most cells surrounding the pycnidial cavity were nucleated.
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i * ii * OC 59 Nuclei distribution (Figure 5.21) *
S & V * V iii iv
W/SL
W SL
iii iv
N
N
v OC vi W W/SL
S & V
SL V
50 m
Figure 5.21. Cross section photographs of SN15 ( i, iii and v ) and sch1-42 ( ii , iv and vi ) pycnidia on CzV8CS agar. The nuclei content of pycnidia was examined in cross sectioned tissues (10 m thick) stained with DAPI ( i, ii, iii and iv ). Close up images of the DAPI stained cross sections of iii. SN15 and iv. sch1-42 . Toluidine blue was used to counter stain all tissues ( v and vi ). Key = W, pycnidial wall; V, pycnidial cavity; S, spore; OC, ostiolar cone; SL, subparietal layer; C, conidiogenous cell and N, nucleus.
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60Proprotoplasting of sch1-42 (Figure 5.22)
i ii
iii iv
v vi
Figure 5.22 . Light microsc ope images of protoplasts generated from overnight
growth of spore ( i, iii and v) and mycelial ( ii , iv and vi ) inocula of SN15 ( i and ii ),
Ect ( iii and iv ) and sch1-42 ( v and vi ).
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5.3.13 Protoplasting of sch1-42
Genetic complementation of sch1-42 with a functional sch1 gene construct was attempted. To perform this experiment, the generation of viable protoplasts is vital for genetic transformation. The sch1-42 mutant was subjected to protoplasting using
Glucanex as described in Chapter 2. It was observed that spore inoculum of sch1-42 was unable to produced protoplasts (Figure 5.22). Furthermore, protoplasts were rarely observed from mycelial inoculum of sch1-42 in comparison to SN15 and Ect (Figure
5.22). A substantial amount of cell debris was pelleted below the protoplast interface in the Glucanex solution during protoplast isolation. The amount of protoplasts produced from the sch1-42 mycelial inoculum was only sufficient for light microscopy analysis
(Figure 5.22). Subsequent experimental attempts using the same protoplasting protocol on mycelial inoculum of the sch1-42 mutant failed to produce any protoplasts. Hence, genetic transformation of sch1-42 is currently improbable using the protoplasting technique.
5.3.14 In vitro metabolomic analysis
The polar metabolome of the sch1 mutants was analysed for changes in metabolite abundance via electron ionisation with a GC MS. AMDIS was able to consistently detect an average of 223 components per GC MS trace (Figure 5.23). Of these components, an average of 174 components was designated as target based on m/z fragmentation match to the Max Planck Institute and in house metabolite standard libraries. Of these targets, 61 major metabolite derivatives (excluding the ribitol standard) were identified and retained for comparisons (Appendix G). A metabolite
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61GC-MS ion chromatograms of Sch1 and sch1 strains (Figure 5.23) i
ii
iii LOGabundance
iv
Metabolite retention time (min utes ) Figure 5.23. Representative GC MS polar intracellular metabolite profiles of i.
SN15, ii. Ect, iii. sch1-11 and iv. sch1-42 . Green arrows indicate the ribitol
standard used for normalisation of metabolite abundance. Orange arrows
indicate a metabolite peak detected at the retention time of 45.57 minutes,
showed a noticeable increase in abundance in the sch1 mutants.
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derivative was scored as a positive hit to compounds in the Max Planck and in house libraries under the following conditions; 1. matching chromatographic RT and 2. similar electron fragmentation pattern. As a result, 45 metabolite derivatives tentatively matched to metabolite standards from these libraries whereas 16 metabolite derivatives were classified as unknown compounds (Appendix G). Amino acids and amino acid derivatives composed of 35% and 8% of identified components, respectively.
Unidentified metabolites made up 26%. Metabolites from the citric acid cycle, fatty acid, polyol and polyamine metabolism were also identified (Figure 5.24).
PCA was used identify a possible clustering pattern between the Sch1 strains and the sch1 mutants based on the total metabolite variance. Sch1 and sch1 strains were distinctly separated by variances of principal component two (PC2) (Figure 5.25A).
Furthermore, loading component analysis indicates that the unidentified metabolite with a retention time (RT) of 45.57 min was a major contributor of variations in PC2 (data not shown). Vice versa, PCA was used to identify a possible clustering pattern in all metabolite derivatives based on strain dependent variances. Two clusters were observed. The major cluster consists of 60 metabolite derivatives, separated based on their general abundance in all strains. The minor cluster, separated by PC2 consisted of the unidentified metabolite (RT 45.57) (Figure 5.25B). The unknown metabolite from here on will carry the nomenclature of RT4557.
5.3.15 Quantification of RT4557
Quantification of RT4557 via normalisation of the integrated signal indicates that the metabolite was 86 and 202 fold more abundant in sch1-11 and sch1-42 ,
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62Metabolite classification (Figure 5.24)
Amino acid Purine Others derivatives derivatives 7% 8% 3% Unknown Fatty 26% acids/alcohols 7% Citric acid Polyols cycle 5% 5% Amino acids Disaccharide 35% sugar Polyamine 2% 2%
Figure 5.24 . The classification of metabolite derivatives based on metabolic groupings.
Individual metabolite derivatives are listed in Appendix G with colour coding to match the classification scheme.
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A 7.5
63Principal component analysis (Figure 5.25) 5 Ect Ect
SN15 Ect 2.5 SN15 SN15
0
sch1 -11 sch1-42 -2.5 sch1 -11 sch1 -42 sch1 -11 -5 sch1-42
Principal component 2 (21.8% of variance) of component(21.8% 2 Principal -7.5 -10 -5 0 5 10 15 Principal component 1 (32.0% of variance) B
1
-1.5
RT 45.57 Principal component 2 (9.3% of variance) of component(9.3% 2 Principal -4 -4 -2 0 2 4 6 8 Principal component 1 (88.2% of variance)
Figure 5.25 . PCA analyses of metabolite profiles. A. The clustering pattern of
all strains analysed based on the total metabolite variance. PC1 and PC2
accounted for over 50% of the total variance. Two distinct clusters were
observed. B. The clustering pattern of all metabolites based on the total
variance in all strains. PC1 and PC2 accounted for 97% of the total variance.
Two distinct clusters were observed.
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64Quantification of RT4557 (Figure 5.26)
1000 a a b c 100
10
scale) 1 10
(log 0.1
0.01
Normalised averageabundance Normalised 0.001 SN15 Ect sch1-11 sch1-42 Strain
Figure 5.26 . Quantification of RT4557 in the intracellular
metabolome of SN15, Ect, sch1-11 and sch1-42 grown in
MM broth. Standard error bars are shown.
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respectively to SN15 (Figure 5.26). Targeted metabolomics were performed on the
MM broth supernatant to determine if RT4557 was secreted into the extracellular environment. RT4557 was detected in all strains. To determine if the presence of
RT4557 in the extracellular supernatant was the result of cell lysis or diffusion, the normalised value of secreted RT4557 was re normalised against the integrated signal of secreted glutamate (3 TMS; RT 20.98 min). Glutamate was chosen for normalisation as the metabolite derivative showed no significant difference in abundance in all strains
(data not shown). No differences were observed in the abundance of RT4557 in all strains relative to glutamate. Hence, RT4557 is predominantly accumulated and retained in the sch1 mutants.
5.3.16 Attempts to elucidate the molecular identify of RT4557
One of the aims of AMDIS is to match the electron fragmentation pattern of a metabolite of interest to the fragmentation patterns of known metabolite standards. The electron fragmentation profile of RT4557 did not produce a match to compound standards in the Max Planck and in house ACNFP metabolite libraries. Excluding the peak at 73 m/z which correspond to a TMS conjugate, major components of the RT
4557 peak were located at 222, 387, 459 and 547 m/z (Figure 5.27).
GC MS PCI with methane derivatives as electron carriers to reduce fragmentation was used to determine the parental MW of the RT4557 TMS derivative
(Figure 5.28). In addition to the 459 m/z component, several components of higher m/z value were identified. The probable parental MW of RT4557 including TMS conjugates is 474 Da. The PCI profile also suggests that RT4557 contains at
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65Fragmentation pattern of RT4557 via electron ionisation (Figure 5.27)
A
Abundance B
m/z
Figure 5.27 . GC MS electron fragmentation pattern of RT4557 in A. SN15 and B. sch1-42 . The relative peak height of fragments
at 222, 387, 459 and 547 m/z between the two spectra differed slightly due to detection saturation in sch1-42 .
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66Positive chemical ionisation of RT4557 (Figure 5.28)
[MW+H +]
-2 TMS -1 TMS
+ [MW+C 2H5 ] + [MW+C 3H5 ]
Figure 5.28 . Positive chemical ionisation profile of RT4557. ‘M’ denotes the probable parental molecular weight of the derivatised RT4557.
+ + Methane derived adducts that act as electron carriers are indicated as [+H], [+C 2H5 ] and [C 3H5 ]. Neutral loss of these adducts result in the parental m/z and molecular weight of 474 Da. The probable molecular weight of RT4557 resulting from neutral loss of up to two TMS group
through partial fragmentation is indicated (arrows).
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least a hydroxy group with a possibility of a second for the conjugation of the TMS group.
Interrogations of the commercially available Wiley SpecInfo (http://www.wiley vch.de/stmdata/specinfo.php#mass ) and NIST98 (National Institute of Standards and
Technology, USA) metabolite databases have uncovered several metabolites with similar electron fragmentation profiles (Figure 5.29). The mass spectrum of the abietic acid compound 15 hydroxy 7 oxodehydroabietic acid consisted of a dominant 459 m/z component peak (PubChem ID 635228) (Berg et al. , 2000). In addition, the MW of the compound matched to the deduced PCI MW of RT4557. A 459 m/z component peak was also observed from the fragmentation profile of methyl 3α 7β dihydroxy 6 oxo
5β cholan 24 oate (2 TMS) (CAS # 100009 97 8). Although the MW of the latter metabolite is dissimilar to the deduced weight of RT4557, the striking structural similarity between both partially matching metabolites suggests the likelihood of a sterol or at least a cyclic carbon backbone in RT4557. The retention index of RT4557 was 2978.79. A mass spectral search (Appendix H) of the Golm metabolome database limited to the retention index with a default tolerance of ±25, was unable to provide a conclusive metabolite match.
5.3.17 In planta metabolomic analysis
GC MS was used to analyse infected wheat leaves to determine if RT4557 is accumulated during nine days post infection coinciding with pycnidiation. The fungal biomarker mannitol was detected in all samples infected with SN15, Ect and sch1-42 .
However, RT4557 was not observed in all samples.
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67 Structural matches to RT4557 based on fragmentation profiles (Figure 5.29)
A
B Abundance Abundance
m/z Figure 5.29 . Structural matches to RT4557 based on electron fragmentation
profiling. A. 15 hydroxy 7 oxodehydroabietic acid (2 TMS) and B. Methyl 3α 7β
dihydroxy 6 oxo 5 βcholan 24 oate (2 TMS).
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5.3.18 Extracellular metabolome analysis of the sch1 mutants
The sch1 mutants secrete a brown pigment during growth on solid and in liquid media (Figure 5.30A). This indicates that the extracellular metabolome of the sch1 mutants is altered. Seven day old extracellular MM broth culture filtrates of SN15, Ect, sch1-11 and sch1-42 were analysed spectrophotometrically (Figure 5.30B). OD spectra of the sch1 mutants differ remarkably from SN15 and Ect. For instance, the absorbance value for the the sch1 mutants was consistently higher than SN15 and Ect.
Furthermore, two distinct OD peaks at 340 and 370 nm were observed in the extracellular supernatant of the sch1 mutants. These peaks were not prevalent in SN15 and Ect (Figure 5.30B).
5.4 Discussion
5.4.1 Sch1 encodes for a putative short-chain dehydrogenase
The short chain dehydrogenase family consists of functionally diverse enzymes that are 250 to 350 residues in length (Oppermann et al. , 2003). The amino acid sequence identity between short chain dehydrogenases is typically around 15 to 30% via pairwise comparisons (Jornvall et al. , 1995). This is consistent with a majority of
BlastP putative short chain dehydrogenase matches to Sch1. The secondary structure of
Sch1 consists of a series of alternating α helices and β sheets which is characteristic of a coenzyme binding Rossmann fold (Rossmann et al. , 1975) (Figure 5.3). Motifs required for protein stabilisation and coenzyme binding (Filling et al. , 2002;
Oppermann et al. , 1997; Rossmann et al. , 1975; Wierenga et al. , 1985) are present in
Sch1 (Table 5.1). The serine residue of the “N S Y K” catalytic motif is not conserved in Sch1. This could be due to substrate specificity.
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68Alterations in the extracellular metabolome of the sch1 mutants (Figure 5.30)
i ii iii iv A
B
iii
i iv
ii
Wavelength (nm)
Figure 5.30 . i. SN15, ii. Ect, iii. sch1-11 and iv. sch1-42 were investigated
for alterations in the extracellular metabolome. A. A brown pigment
secreted by the sch1 mutants. B. OD readings of the cell free supernatant.
Arrows indicate two distinct OD peaks in the cell free supernatant of the
sch1 mutants.
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5.4.2 sch1 mutants are affected in vegetative development in vitro
Mutants carrying the deleted Sch1 were characterised for defects that may lead to a decrease in pathogen fitness. Phenotype alterations were first observed when the mutants were grown on agar and in liquid media. The radial growth of the sch1 mutants was significantly reduced on MM agar. Radial growth was similar to SN15 on CzV8CS agar. This strongly suggests that the sch1 mutants are auxotrophic for component(s) present in the CzV8CS medium. The deletion of Sch1 did not alter sensitivity of the fungus to osmotic stress. This is in contrast to the gna1 mutants reported by Solomon et al. (2004b) and hence suggesting that other Gna1 effector elements are involved in regulating osmotolerance.
Genetic complementation is performed by introducing a functional copy of the deleted gene to restore the wild type phenotype in the gene knockout mutant. The quantity of protoplasts from sch1-42 was insufficient for genetic transformation. It is possible that the deletion of Sch1 may have increased the sensitivity of sch1-42 to protoplasting agent and hence resulted in protoplast lysis. The congregation of crushed sch1-42 mycelia into a single mass during growth in MM broth under constant agitation suggests an increase in adhesive property. This could be due to increase in abundance or alterations in the property of hydrophobins, a family of small secreted proteins that is required for adhesion (Wosten, 2001). The S. nodorum genome contains two predicted hydrophobin genes (Hane, manuscript in prep. ). Mycelial congregation may also increase sch1-42 resilience to protoplasting agents. This hypothesis requires further investigation. We are currently investigating transformation methods using
Agrobacterium tumefaciens (de Groot et al. , 1998).
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5.4.3 Sch1 is not required for vegetative proliferation within wheat
Histological examination and infection assays have demonstrated that Sch1 is not required for proliferation and colonisation of the host tissue. Hence, an unknown plant component that is present in both CzV8CS and wheat may have chemically complemented the vegetative growth defect of the sch1 mutants.
5.4.4 Disruption in pycnidial ontogeny
The transcript abundance of Sch1 is maximal during the latter stage of infection that coincided with pycnidiation. It was observed that the average size of pycnidia of the sch1 mutants was smaller than in SN15. Detailed examination of the pycnidia was performed to further characterise for defects in the sch1 mutants. The morphology of melanised cells between SN15 and sch1-42 showed considerable differences; those of the mutant were irregular in shape. These cells were observed in the young pycnidial primordium by Douaiher et al. (2004). The morphologies of the pycnidial wall, subparietal and conidiogenous cell tissues of sch1-42 were remarkably different to
SN15. Cells from the cell wall of sch1-42 pycnidia also showed an abnormality in vacuolation and cytoplasm distribution. This indicates that Sch1 is required for pycnidial development. In U. maydis , the deletion of a kinesin gene altered microtubule organisation that led to the formation of small vacuoles (Steinberg et al. , 1998).
Using TEM, Philipson (1989) observed that pycnidiospores from a
Stagonospora sp . were electron dense. These structures were observed in the pycnidium of SN15 but not in sch1-42. This strongly suggests that Sch1 is critical for
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conidiogenesis. Genetic regulation of conidia development is well described in A. nidulans (Adams et al. , 1998). AbaA is a regulatory gene required for the differentiation of conidiogenous cells (Sewall et al. , 1990). AbaA expression is not prominent in mutants carrying double deletion chitin synthases. These double mutants showed aberrant conidiophore morphology and were severely reduced in sporulation
(Ichinomiya et al. , 2005). MedA is another regulator gene required for conidiophore development in A. nidulans (Busby et al. , 1996; Clutterbuck, 1969). MedA orthologs are also found in fungal pathogens. For example, Ren1 and Acr1 are developmental components critical for asexual spore differentiation from conidiophores of F. oxysporum and M. grisea , respectively (Lau & Hamer, 1998; Ohara et al. , 2004).
5.4.5 Sch1 is required for asexual sporulation
Pycnidia of the sch1 mutants rarely exude chirri which can be attributed to the lack of pycnidiospores formed within the pycnidium. In other pycnidial fungi such as
Septoria lycopersici and Guignardia bidwellii , tension exerted by pycnidiospores on the ostiolar cells causes an opening where spores may empty out to the external environment (Harris, 1935; Janex Favre et al. , 1993). The sch1 mutants may have lacked such tension due to low spore numbers.
Cellular debris associated with the pycnidiospores of the sch1 mutants could be pcynidial cavity cells that failed to differentiate into spores. Nuclei within the pycnidial cavity of sch1-42 were difficult to distinguish with DAPI staining due to high fluorescence. This could be due to the presence of fragmented DNA, a symptom of cell
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death (Eastman & Barry, 1992). To test this hypothesis, TUNEL staining should be used to detect for DNA degradation (Gavrieli et al. , 1992) in the sch1 mutants.
Asexual sporulation in S. nodorum is an intricate process and has been under intensive investigations (Solomon et al. , 2004b; Solomon et al. , 2005a; Solomon et al. ,
2005b; Solomon et al. , 2006c; Solomon et al. , 2006d). Proper functioning of signalling pathways are critical for sporulation (Solomon et al., 2004b; Solomon et al. , 2005b;
Solomon et al. , 2006c). Furthermore, the polyol mannitol seems to play a major role in asexual sporulation of S. nodorum (Solomon et al. , 2005a; Solomon et al. , 2006d).
However, the deletion of Sch1 did not have a significant impact on the mannitol level in the sch1 mutants (Appendix G).
Taken collectively, the deletion of Sch1 resulted in the perturbation of pycnidial ontogeny that may have compromised the ability of conidiogenous cells to properly differentiate into pycnidiospores. The location of a putative core promoter site for Sch1 was identified. Tissue specific expression analysis using a GFP construct driven by the
Sch1 promoter is currently being investigated. The purpose of this experiment is to gain a further understanding of Sch1 regulation during infection and pycnidial development.
5.4.6 Deletion of Sch1 resulted in the accumulation of the novel intracellular metabolite RT4557
Sch1 encode a putative redox enzyme therefore, it was hypothesised that gene deletion may result in a metabolic blockage. Hence, we set out to investigate SN15, Ect and the sch1 mutants for biochemical alterations via GC MS analysis which led to the
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identification of RT4557. The electron fragmentation profile of RT4557 consisted of a dominant 459 m/z ion peak. PCI analysis indicated that the parental MW of RT4557 is
474 Da. However, a 547 ion m/z peak was observed in the electron fragmentation profile of RT4557 which could be a co eluting metabolite.
The electron fragmentation pattern of two TMS derivatised compounds possessed the dominant 459 m/z ion peak. The methyl 3α 7β dihydroxy 6 oxo 5
βcholan 24 oate TMS (cholanoate) derivative is one of the two candidate compounds.
Cholanoate is an intermediate of bile metabolism. 7α hydroxysteroid dehydrogenase of
E. coli (Yoshimoto et al. , 1991) is a top functional BlastP match to Sch1. The enzyme is involved in the oxidation of the 7 α hydroxyl group of bile acids. Some fungi possess the ability to hydrolyse bile (Chong et al. , 1980; Johns et al. , 1982). 15 Hydroxy 7 oxodehydroabietic acid (2 TMS) is the second compound that possess the dominant 459 m/z ion peak. PCI indicates that the MW of RT4557 and abietic acid is similar. Abietic acid is a diterpernoid found in conifers and implicated in defence against herbivores and microorganisms. Some fungi are able to produce diterpernoid type coumpounds such as the mycotoxin paxilline from Penicillium paxilli (Young et al. , 2001). Both cholanoate and abietic acid differ in biological properties but possess a central core structure composed of conjoining cyclohexane rings. This suggests that differences in moiety groups may account for the differences in the minor electron fragmentation peaks. A diverse number of fungal secondary metabolites possess a cyclic carbon ring like backbone (Keller et al. , 2005).
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The retention index and component profile of RT4557 were established
(Appendix H). These are unique properties of a mass spectral tag (MST) used for universal identification (Desbrosses et al. , 2005). This data may be useful once more fungal MSTs become available for comparisons. High resolution GC/GC MS will be used to further fractionate RT4557 to identify the presence of co eluting metabolites.
Determining the purity of the RT4557 peak and subsequent purification of the compound are critical for structural analysis via nuclear magnetic resonance.
5.4.7 Alterations in the extracellular metabolome of the sch1 mutants
The extracellular metabolomes of the sch1 mutants were analysed for alterations. A distinct brown pigmentation of the extracellular supernatant associated with the sch1 mutants was observed. Spectrophotometric analysis of the supernatant produced an absorbance profile reminiscent of the gna1 mutants (Solomon et al. ,
2004b). Progress is currently underway to analyse the extracellular metabolome of
SN15 and the sch1 mutants via GC MS and liquid chromatography ultraviolet mass spectrometry. The latter approach was proposed as it can effectively fractionate a large number of fungal secondary metabolites (Nielsen & Smedsgaard, 2003).
5.4.8 Association between secondary metabolism and sporulation?
The relationship between secondary metabolism and fungal development has been long noted and appears to be regulated. The Gα protein FadA regulates sporulation and sterigmatocystin biosynthesis in A. nidulans (Hicks et al. , 1997; Tag et al. , 2000). Similarly, a novel gene designated as VeA in Aspergillus parasiticus is required for sporulation, aflatoxin biosynthesis and the formation of the sclerotial
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resistant structure (Calvo et al. , 2004). An investigation should be performed to elucidate a possible link between the accumulation of RT4557 and phenotypic alterations in the sch1 mutants.
5.4.9 Proteomic analysis
A comparative analysis of the intracellular proteome of sch1-42 with SN15 was used to identify proteins that are altered in abundance. A notable change in the proteome profile is the large increase of another putative short chain dehydrogenase
(SNOG_13042.1) in sch1-42 . The function of the gene encoding the protein is unknown. The identification of two proteins spots that matched to the same putative nitroreductase gene indicates evidence of post translational modifications that potentially altered the isoelectric property of the protein. Nitroreductases catalyse the reduction of nitroaromatic compounds using flavin mononucleotide as a cofactor (Hecht et al. , 1995). In E. coli , nitroreductases NfsA, B and C of E. coli reduces nitrofurazone, an antibacterial compound into a toxic mutagen (Bryant et al. , 1981). The biological role of fungal nitroreductases is unknown.
5.4.10 On the accumulation and possible function of RT4557
Several hypotheses are formulated to explain the accumulation of RT4557.
Firstly, Sch1 may participate in the synthesis of a metabolite to which RT4557 is an intermediate substrate. Hence, the deletion of Sch1 may have resulted in the blockage of a biochemical pathway resulting in the accumulation of RT4557. The deletion of
Sch1 also resulted in significant accumulation of proteins that are coded by the putative short chain dehydrogenase (SNOG_13042.1) and nitroreductase (SNOG_09590.1)
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genes. Both genes should be investigated for a possible role RT4557 accumulation.
This hypothesis requires further investigation. The SNOG_13042.1 putative short chain dehydrogenase is of particular interest as the gene is located within a probable gene cluster containing a PKS (Chapter 3). SNOG_13042.1 is also Gna1 regulated (Chapter
3).
RT4557 was not observed from infected plant materials. The analysis was performed on a single infection time point correlating with pycnidiation. More sampling time points representing different stages of infection are required to establish if RT4557 is accumulated during the course of the infection. Alternatively, RT4557 may be degraded or mobilised through an unknown metabolic shunt during infection.
This requires further investigation.
Secondary metabolites are known to influence fungal development (Beppu,
1992). For instance, the estrogenic mycotoxin zearalenone regulates sexual development in F. graminearum (Wolf & Mirocha, 1977), sclerosporin is a sporogenic compounds produced by the brown rot fungus Sclerotinia fruticola (Katayama &
Marumo, 1978) and cerebrosides isolated from Schizophyllum commune stimulate fruiting body development (Kawai & Ikeda, 1982). Recently, the deletion of a putative
NRPS gene in A. brassicicola resulted in defects in sporulation (Kim et al. , 2007).
From this study, it is speculated that RT4557 may be an intermediate of a pathway that play an important role in S. nodorum development. The isolation and identification of
RT4557 is critical to test these hypotheses and possibly identifying a novel fungal metabolic pathway. Furthermore, abnormal vacuolation observed in sch1-42 pycnidial
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cells may be related to the accumulation of RT4557 in vitro . Fungal vacuoles involving in the storage of metabolites have been documented elsewhere (Klionsky et al. , 1990).
5.5 Conclusion
This study has provided a unique insight into the regulation of pycnidial development and sporogenesis in S. nodorum by the G α and MAPK pathway target gene Sch1 . Furthermore, the RT4557 compound is currently being investigated for a possible role in modulating asexual development. Exploiting Sch1 as an antifungal target is a focal point of research in our laboratory. In addition, we hope that this study will stimulate research to further understand the biology of pycnidial development in other fungal pathogens and its requirement for the establishment of diseases. This
Chapter has fulfilled the fourth, fifth and sixth objectives listed in Chapter 1.
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Chapter 6 - General discussion
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6.1 Confirmation of gene annotation via proteomics
The estimated haploid assembled genome size of S. nodorum is 37.1 Mb which contains over 16,000 predicted genes. Automatic gene annotation may result in erroneous gene predictions that require manual curation and experimental evidence to correct. Mass spectrometry derived data can aid in identifying novel genes, confirm predicted open reading frames (ORFs) and to correct erroneous predictions (Mann &
Pandey, 2001). Twenty seven genes were identified in this study from LC MS/MS analysis of protein spots. Peptide and EST data (Hane, manuscript in prep. ) were used to refine the current gene prediction (Table 6.1). Eleven predicted ORFs were confirmed by peptide and EST coverage. Thirteen predicted ORFs were without supporting EST data but were partially confirmed by peptide coverage. Three predicted
ORFS were erroneous. Intron/exon boundaries of SNOG_00848.1 and SNOG_05974.1 were inaccurately predicted and the start of the SNOG_09590.1 ORF was incorrect. In addition, LC MS/MS data indicated that the FP 1_B06 cDNA should be annotated as a novel gene which was not initially predicted by the Broad Institute. BlastN against S. nodorum excluded genomic reads indicate that G707P894FD11.T1 and
G707P830FA10.T0 matched the Grg1 cDNA sequence (Broad Inst.). LC MS/MS analysis the proteome of the mosquito Anopheles gambiae was used to assist in genome annotation (Kalume et al. , 2005). A similar approach is currently being used to analyse the soluble proteome of S. nodorum to refine the current genome annotation.
6.2 Relationship between protein and transcript abundance
Non correlation between protein and transcript abundance of putative signalling regulated genes was observed in vitro . Non correlations between protein and mRNA
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69Confirmation of gene prediction via MS-derived data (Table 6.1)
Table 6.1 . Confirmation of Broad ORF prediction using LC MS/MS and EST coverage.
Gene/cDNA ID Putative function Comment FP 1_B06 Glucose repressible gene ORF encoding this cDNA was not predicted. Peptide coverage of the EST protein like protein indicates that a gene should be assigned. SNOG_00656.1 Vacuolar targeting protein Peptide coverage confirmed ORF presence. Two predicted introns not confirmed. SNOG_00848.1 Peptidylprolyl isomerase Peptide coverage and EST alignment confirmed ORF presence. Two predicted introns not confirmed by peptide coverage. EST sequences indicate that the first 15 bases of the predicted intron one are transcribed. SNOG_01569.1 Cell wall glucanase Peptide coverage confirmed ORF presence. Three predicted introns not confirmed. SNOG_05918.1 Unknown protein Single intron confirmed by peptide coverage. SNOG_05974.1 Malate dehydrogenase Peptide coverage and EST alignments confirmed ORF presence. First 13 bases of exon three should be part of intron two. SNOG_06180.1 Unknown protein Peptide coverage confirmed ORF presence. Weak coverage. SNOG_06491.1 Serine protease precursor Peptide coverage confirmed ORF presence. First of four predicted introns confirmed. SNOG_06492.1 Subtilisin like protease Peptide coverage and EST alignments confirmed ORF prediction. SNOG_07541.1 Proteasome component Pre8 Peptide coverage confirmed ORF presence. First three of four predicted introns confirmed. SNOG_07604.1 Glutathione transferase 2 Peptide coverage and EST alignments confirmed ORF prediction. SNOG_08052.1 Unknown protein Peptide coverage confirmed ORF presence. Single predicted intron not confirmed. SNOG_08282.1 Short chain dehydrogenase Peptide coverage and EST alignments confirmed ORF prediction. SNOG_08775.1 HAD superfamily hydrolase Peptide coverage and EST alignments confirmed ORF prediction. SNOG_09590.1 Nitroreductase family protein Peptide and EST coverage indicates that the first 105 predict amino acids should be excluded from the ORF. SNOG_10217.1 Short chain dehydrogenase Peptide coverage and EST alignments confirmed ORF prediction. SNOG_10685.1 Unknown protein Peptide coverage confirmed ORF presence. Two predicted introns not confirmed. SNOG_11078.1 Unknown protein with an Peptide coverage confirmed ORF presence. Single predicted intron NmrA like domain confirmed. SNOG_11081.1 CipC protein Peptide coverage and EST alignments confirmed ORF prediction. SNOG_11441.1 3 dehydroquinate Peptide coverage and EST alignments confirmed ORF prediction. dehydratase SNOG_12730.1 Unknown protein Peptide coverage confirmed ORF presence. Single predicted intron confirmed. SNOG_13042.1 Short chain dehydrogenase Peptide coverage and EST alignments confirmed ORF prediction. SNOG_13504.1 Unknown protein Peptide coverage and EST alignments confirmed ORF prediction. SNOG_14370.1 Tyrosinase/oxidase Peptide coverage and EST alignments confirmed ORF prediction. SNOG_15451.1 Acetyl xylan esterase Peptide coverage confirmed ORF presence. SNOG_15488.1 Mannitol dehydrogenase Peptide coverage and EST alignments confirmed ORF prediction. SNOG_16063.1 RNase T1 Single intron confirmed by peptide coverage.
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abundance have been previously observed from studies of gene expression in hepatocytes, neutrophils and yeasts (Anderson & Seilhamer, 1997; Fessler et al. , 2002;
Gygi et al. , 1999b). This may be attributed to post transcriptional regulation [reviewed by Kozak (2005) and Yaman et al. (2003)], post translational modifications [reviewed by Mann & Jensen (2003)], sub cellular localisation and mRNA stability [reviewed by
Newbury (2006)].
6.3 Putative gene clusters in S. nodorum
Chapters 3 and 4 have identified several signalling effector genes that may be associated in probable secondary metabolism gene clusters. In A. nidulans , the expression of secondary metabolism gene clusters are regulated through epigenetic control by the LaeA protein (Bok & Keller, 2004). S. nodorum possessed an apparent ortholog of LaeA (SNOG_11365.1). Regulation of secondary metabolite biosynthesis in filamentous fungi by signal transduction pathways has also been described. Using
SSH, Gronover et al. (2004) has identified putative secondary metabolism genes
(polyketide synthase, two cytochrome P450 monooxygenases and averantin oxidoreductase) as effectors of Bcg1 signalling. One of the cytochrome P450 monooxygenases plays a role in pathogenicity and botrydial toxin production in B. cinerea (Siewers et al. , 2005). In A. nidulans , the influence of G α protein mediated signalling on the production of toxic secondary metabolite includes FadA , a negative regulator of sterigmatocystin biosynthesis (Hicks et al. , 1997). For MAPK signalling in
C. zeae-maydis , the inactivation of a MAPKKK gene Czk3 resulted in mutants with abolished cercosporin production and reduced pathogenicity (Gafur et al. , 1998).
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Transcriptomics and metabolomics are currently being used to complement proteomics to further provide a physiological insight into heterotrimeric G protein and
MAPK signalling in the pathogenicity of S. nodorum . Gas and liquid chromatography separation based mass spectrometry are being used to identify changes in the metabolome of signalling mutants (Solomon, personal communications ). Custom gene arrays are being constructed from information generated by predicted genes from the S. nodorum genome sequence (Ip Cho, personal communications ). This will provide an insight into the regulation of gene expression by Gna1 and Mak2 .
6.4 Targeted deletion of other signalling effector genes
In addition to Sch1 , other genes from the proteomic study were analysed for ther potential role in pathogenicity by reverse genetics. CipC , putative short chain dehydrogenase genes Sch2 and Sch3 were chosen for gene knockout analysis based on two criteria listed below;
1. Correlation between protein and transcript abundances.
2. Single gene to protein spot match.
The deletion of CipC did not alter pycnidiation and virulence of the fungus
(Appendix I and J). PCR and Southern analysis are currently being used to screen for potential sch2 mutants (Appendix K and L). A third Mak2 regulated short chain dehydrogenase gene Sch3 (Appendix M and N) has also been shown to be dispensible for asexual sporulation and virulence on wheat. The putative Sch1 regulated nitroreductase gene ( Nrd1 ) was subjected to reverse genetic analysis due to an increase
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in protein abundance in sch1-42 (Appendix O and P). No changes in asexual sporulation and virulence were observed in nrd1 mutants. Sch2 and Nrd1 may play a role in the accumulation of RT4557. Double deletion of Sch1 /Sch2 and Sch1 /Nrd1 are required to test this hypothesis. This is the first record of a secondary metabolite produced by S. nodorum .
6.5 Potential antifungal targets
The economic importance of S. nodorum has instigated the need for the development of an effective pathogen control strategy. Hence, a solid understanding of the fungal infection process is key for the development of crop protection strategies such as fungicide discovery, biological control and the identification of resistance genes in wheat to target weaknesses in fungal metabolism (Dancer et al. , 1999; Murphy et al. ,
1999; Van Ginkel & Rajaram, 1999).
Among the known targets of existing fungicides are cell wall biosynthesis, membrane function, nuclear processes, tubulin biosynthesis, oxidative phosphorylation and protein synthesis (Hewitt, 1998). Recent evidence that suggests that fungal signal transduction pathways are involved in fungicide tolerance and can be exploited for fungicide development (Izumitsu et al. , 2007; Kojima et al. , 2004; Mehrabi et al. ,
2006b; Ramesh et al. , 2001). Proteomic analysis has led to the identification of putative signalling effectors in S. nodorum . Snp3 and a serine protease precursor are major
Gna1 regulated proteases, the former is expressed during infection. Numerous studies have indicated that protease inhibitors can inhibit fungal growth. For example, a serine protease/trypsin inhibitor zeamatin (Schimoler O'Rourke et al. , 2001) and a cysteine
209 Chapter 6
protease inhibitor isolated from pearl millet (Joshi et al. , 1998; Joshi et al. , 1999) are inhibitory to fungal growth and can be considered as an option for plant transgenics to confer fungal disease resistance.
Promoting the accumulation of a toxic biochemical intermediate within the fungus can be considered as another form of antifungal control. The use of fungal secondary metabolites as control agents that limit fungal growth has been proposed by
Thines et al. (2004). For example, azole based fungicides interfere with ergosterol biosynthesis. This causes the accumulation of ergosterol biosynthesis intermediates
(Vanden Bossche, 1985) which is toxic to the fungus (Debieu et al. , 1998). The unknown metabolite RT4557 may be investigated for antagonistic properties on S. nodorum . The identification and isolation of RT4557 is essential to test this hypothesis.
Sch1 encodes a putative short chain dehydrogenase. Members of this family are regarded as potential targets for biotechnological applications (Oppermann et al. , 2003).
For example, melanin biosynthetic enzymes tri and tetrahydroxynaphthalene reductases of M. grisea are known fungicide targets (Liao et al. , 2001; Thompson et al. , 1997;
Thompson et al. , 2000). The identification of the Sch1 natural substrate is critical for formulating analogue compounds with antagonistic properties. This has fulfilled the final project objective described in Chapter 1.
6.6 Fungal signal transduction and proteomics
The Broad annotation of S. nodorum genome resulted in a prediction of over
16,000 putative genes and has helped to facilitate identification of signalling effector
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proteins in this study via 2D electrophoresis. This has led to the identification of the
Sch1 gene that plays a major role in sporulation. This section will provide a brief discussion on experiments that could be used to further facilitate the identification of signalling effectors in S. nodorum .
6.6.1 Y2H and tandem affinity purification (TAP)
Interactomics is concerned with all physical protein protein interactions that can take place within a cell (Cusick et al. , 2005). The Y2H method was first reported by
Fields & Song (1989) as a novel method to study protein protein interactions. This approach was used by Kulkarni & Dean (2004) to identify proteins that interact with
Mac1 of M. grisea such as the Mmk2 MAPKK (Zhao et al. , 2005). Similarly, Park et al. (2006) used Y2H to identify components of the Pmk1 MAPK pathway in M. grisea
(Chapter 1). TAP is developed to identify protein complexes in vivo without prior knowledge of the complex composition (Rigaut et al. , 1999). The technique involves the introduction of a tagged protein into the organism of interest to allow native interactions. The protein complex can then be isolated and subjected to downstream identification of the individual components. TAP has yet to be implemented for signalling studies in plant pathogenic fungus but it has been used in yeast to study signalling interactions (Martin Yken et al. , 2003). Results from Chapters 3 and 4 suggest evidence of cross signalling between the Gna1 and Mak2 pathways. The point of cross signalling of both signal transduction pathways is not known. Y2H, TAP and reverse genetics could be used to identify the point cross signalling between the Gna1 and Mak2 pathways as well identifying other interacting components that may be critical for pathogenicity.
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6.6.2 Phosphoproteomics
It is estimated that protein phosphorylation affects up to 30% of the proteome
(Cohen, 2000). Since the heterotrimeric G protein and MAPK pathways require a series of signal amplification via phosphorylation to relay messages within the cell, a disturbance in these signalling cascades can alter the phosphoproteome in S. nodorum .
Phosphoproteomics is an emerging field of studies involving the comprehensive study of protein phosphorylation (Kersten et al. , 2006). Phosphorylated proteins can be enriched through the use of immobilised metal affinity chromatography (Ficarro et al. ,
2002) and manipulated thereafter (Nuhse et al. , 2003). 2D electrophoresis can be used to separate phosphoproteins which can be visualised via Pro Q Diamond staining
(Martin et al. , 2003). Alternatively, phosphoproteins can be detected immunologically or via 32 P ATP radiolabelling. The identification of Gna1 and Mak2 phosphoprotein effectors can enable pathogenicity studies via reverse genetics.
6.6.3 Sub-cellular proteomics
Methods to analyse the extracellular and intracellular proteome of S. nodorum strains have been established in this study. A protocol describing the extraction of proteins anchored to the fungal cell wall have been established on the cellulolytic filamentous fungus Trichoderma reesei (Lim et al. , 2001). In addition, the isolation of proteins from cellular organelles such as mitochondria for proteomic analysis has been demonstrated in the biocontrol fungus Trichoderma harzianum and N. crassa (Grinyer et al. , 2004; Schmitt et al. , 2006). These protocols can be adapted to elucidate Gna1 and Mak2 regulation in other sub cellular compartments.
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6.7 Overall summary
Proteomic analysis has led to the identification of Gna1 and Mak2 effector proteins with putative roles in nucleotide degradation, cell wall degradation, proteolysis, protein folding, and quinate metabolism. A number of putative Gna1 and Mak2 regulated genes may be associated in potential gene clusters. From this, Sch1 was identified as a gene co regulated by Gna1 and Mak2 . The deletion of Sch1 resulted in the reduction vegetative growth in vitro . Pycnidial ontogeny was perturbed which resulted in the reduction in asexual sporulation of the sch1 mutants. Alterations in the proteome and metabolome were observed in the sch1 mutants. RT4557 is an unknown compound that accumulated in the sch1 mutants and studies are underway to elucidate the structure of the metabolite and test for antifungal properties. Furthermore, Sch1 is currently being investigated as a potential target for the development of antifungal compounds. Finally, the availability of the S. nodorum genome sequence and recent advances in the development of molecular tools will enable a potential study of the interactome and phosphoproteome in S. nodorum for a role in pathogenicity. This PhD candidature has fulfilled all the project objectives described in Chapter 1.
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250
Appendices
251 Appendices
70The plasmid vector pBSK-phleo (Appendix A)
KpnI (658) XhoI (669) HindIII (690) EcoRV (698)
pBSK-phleo 5233 bp
Phleomycin resistance NotI (3011) BamHI (2992) PstI (2984)
Appendix A . Schematic plasmid map of pBSK phleo showing all restriction sites critical for cloning of gene flanking regions. pBSK phleo was developed by amplifying a 2,272 bp section of the pAN8 1 plasmid containing the phleomcycin resistance cassette using primers pBSK phleoF (5’ TTCGTTGACCTAGCTGATTCTGG 3’) and pBSK phleoR (5’ CTCTTCGCTATTACGCCAGCTG 3’). The amplicon was TA cloned into pGEMT Easy (Promega) and liberated via Eco RI digestion to facilitate cloning into pBluescript SK (Stratagene) digested with Eco RI to create pBSK phleo.
252 Appendices
71qRT-PCR primer sequences (Appendix B)
Appendix B . Primers used for qRT PCR.
Broad acc ID Primer code Sequence (5' - 3') Broad acc ID Primer code Sequence (5' - 3') SNOG_01139.1 ActinF CTGCTTTGAGATCCACAT SNOG_15451.1 SNU15451RTF ACATGATGGAGGCGGTGATTCA ActinR GTCACCACTTTCAACTCC SNU15451RTR AGCAGCAAACAGGTCCGGGTAG SNOG_01139.1 ActinqPCRf AGTCGAAGCGTGGTATCCT SNOG_14370.1 SNU14370RTF GCGTCCGACAGGAATGGGAT ActinqPCRr ACTTGGGGTTGATGGAG SNU14370RTR TTGGGTGTCAATGTCTGGTGGA SNOG_11663.1 EF 1alphaF TGTTGTCGCCGTTGAATC SNOG_06492.1 SNU06492RTF CTACCTTCCTTGCCAACTTTGCTG EF 1alphaR CTCATCGTCGCCATCAAC SNU06492RTR AGAACCTGAGGCGTCGAGCA SNOG_09590.1 R638RTF TACGAAGACCCGGAACCCGT SNOG_05974.1 SNU05974RTF TACAACCCCAAGCGCCTCTTC R638RTR GGGGTTGTAGTGCTGGAGGTTG SNU05974RTR TGTAGCCAGACTGCGACAGGAGA SNOG_13042.1 R1048RTF AGTGACGACGCCAATGTGGC SNOG_12730.1 SNU12730RTF AATGGCGCGAGCAGTTCAAC R1048RTR AACTGAGTTCGCGATGCGGG SNU12730RTR AATCCTGTCCGTTCTTCTGGATGA SNOG_10217.1 FP1F01Fwd CACTCAAGAGTCTTGCCCCATCC SNOG_01569.1 SNU01569RTF GAGTACGAATTCAATGCCGCG FP1F01Rev ATCAGCACATCGATCTTGCCG SNU01569RTR GGCAGAAGCCCATAATCCAAGTAGT SNOG_07541.1 R563RTF CAGCCTCATAACACCTAACATTGGC SNOG_06180.1 SNU06180RTF GGAAACATCCCCTCCTCTGCA R563RTR GCTTGTAGCCGGTATGTGAGACCT SNU06180RTR ACCAGCATATTTGGGCGGGT SNOG_07604.1 R646RTF GTCTGGTTCACGGGCTTCCA SNOG_05918.1 SNU05918RTF CTCGGTTACCGCTTTGGAATTG R646RTR GAGTACTTGCCGCCGACCAA SNU05918RTR AGTACATCAGACCTGCGTCGTACG SNOG_11441.1 R806RTF GATCACCTTTTCGCACATTCAGTCC SNOG_08052.1 SNU08052RTF TAGCCAACCCTGAAGCACAGAGA R806RTR TTAATGCTCCAGGGTTGATCACAA SNU08052RTR CAAGGGCGTTGGTGCTGTCT SNOG_11081.1 F6B03rtF1 GGTTTCTGGGATAAGAAC SNOG_13504.1 SNU13504RTF CGATCGACAGCAAGAACTATACGCT F6B03rtR1 TTTAGCCTCAGTCTGAGC SNU13504RTR CATTTTCACGCCTTCGCTGTAAT SNOG_08775.1 FP7G05Fwd GAAAAGCACAACTTCACCATGGC SNOG_16063.1 SNU16063RTF GCCATTGCCGAAGCAGTAGC FP7G05Rev TGTTAAGCTCCGCGGTGACAC SNU16063RTR CGAGGAACGCCACCTTGATCT SNOG_08282.1 FP7B06Fwd CGGAAAGCATCCAGAAGGCC SNOG_00848.1 SNU00848RTF GGCGACCAGATCAGCGTTCA FP7B06Rev TCTCTGAGCTGTTCGGGAGGGA SNU00848RTR GCCAGGGCACATGTCGAGAA FP 1_B06 FP1B06Fwd AAGAACGCCGCCAACTACGTC SNOG_10685.1 SNU10685RTF TTCGCTTACCCAGTGGGACAAC FP1B06Rev TCTGGTCGATCTTGTCGCCG SNU10685RTR ACAGCTTGCCGCTCAACCAG SNOG_00656.1 SNU00656RTF GCGGCTCGCATGCAAACTAC SNOG_06491.1 SNU06491RTF CAGAGCAGACGCTACTACTTCCGC SNU00656RTR GCATTCCTCCCCGCATCGTA SNU06491RTR AGAGTTCTTCAGACGCGTTGCC SNOG_11078.1 SNU11078RTF GGATGTCAGTCGAGGAATACGCA SNU11078RTR TGCTTGTACTTGCCACCGCTG
253 Appendices
72Densitometry data of extracellular protein spots in Chapter 3 (Appendix C)
Appendix C. Normalised densitometry value of triplicate of protein spots excised from SN15 and gna1-35 extracellular proteome analysis with 2D gel electrophoresis. Unpaired t test was used to
analyse protein spots for significant differences in the normalised volumes (p < 0.05). For the purpose
of graphing with transcript data, normalised values were re standardised to “1” in SN15 (Chapter 3).
Continued on the next page.
Spot Strain Normalised protein Mean SD SE p-value abundance value 2.034 1.395 0.983 1.471 0.530 0.306 E1 SN15 0.024 gna1-35 0.388 0.480 0.129 0.332 0.182 0.105 E2 SN15 0.730 0.607 0.567 0.635 0.085 0.049 NA gna1-35 0.000 0.000 0.000 0.000 0.000 0.000 E3 SN15 0.620 0.412 0.370 0.467 0.134 0.077 NA gna1-35 0.000 0.000 0.000 0.000 0.000 0.000 E4 SN15 0.290 0.186 0.309 0.262 0.066 0.038 NA gna1-35 0.000 0.000 0.000 0.000 0.000 0.000 E5 SN15 1.321 1.019 1.269 1.203 0.161 0.093 0.047 gna1-35 0.167 0.945 0.224 0.445 0.434 0.250
254 Appendices
Appendix C. Continued from the previous page. Spot Strain Normalised protein Mean SD SE p-value abundance value E6 SN15 0.374 0.411 0.114 0.300 0.162 0.093 0.013 gna1-35 1.084 0.732 1.172 0.996 0.233 0.134 E7 SN15 0.381 0.540 0.450 0.457 0.080 0.046 0.036 gna1-35 0.331 0.151 0.096 0.193 0.123 0.071 E8 SN15 0.760 0.784 0.641 0.728 0.077 0.044 0.000 gna1-35 0.119 0.131 0.074 0.108 0.030 0.017 E9 SN15 0.467 0.411 0.355 0.411 0.056 0.032 NA gna1-35 0.000 0.000 0.000 0.000 0.000 0.000 E10 SN15 2.939 2.407 1.560 2.302 0.695 0.402 0.008 gna1-35 0.168 0.391 0.253 0.271 0.113 0.065 E11 SN15 2.050 1.800 2.529 2.126 0.370 0.214 0.011 gna1-35 0.135 0.144 0.097 0.125 0.025 0.014 E12 SN15 1.767 4.876 4.392 3.678 1.673 0.966 NA gna1-35 0.000 0.000 0.000 0.000 0.000 0.000 E13 SN15 1.983 2.446 2.090 2.173 0.242 0.140 NA gna1-35 0.000 0.000 0.000 0.000 0.000 0.000 E14 SN15 4.195 3.726 3.631 3.851 0.302 0.174 NA gna1-35 0.000 0.000 0.000 0.000 0.000 0.000 E15 SN15 2.640 3.204 4.824 3.556 1.134 0.655 NA gna1-35 0.000 0.000 0.000 0.000 0.000 0.000
255 Appendices
Appendix C. Continued from the previous page.
Spot Strain Normalised protein Mean SD SE p-value abundance value E16 SN15 0.000 0.000 0.000 0.000 0.000 0.000 NA gna1-35 0.132 1.101 1.048 0.760 0.545 0.314 E17 SN15 0.000 0.000 0.000 0.000 0.000 0.000 NA gna1-35 0.076 0.943 1.542 0.854 0.737 0.426 0.000 0.000 0.000 0.000 0.000 0.000 E18 SN15 NA gna1-35 0.102 0.887 1.255 0.748 0.589 0.340 0.287 0.231 0.062 0.193 0.117 0.068 E19 SN15 0.002 gna1-35 1.264 0.989 0.968 1.074 0.165 0.095 0.000 0.000 0.000 0.000 0.000 0.000 E20 SN15 NA gna1-35 0.222 0.066 0.052 0.113 0.094 0.054 0.423 0.361 0.582 0.455 0.114 0.066 E21 SN15 0.014 gna1-35 1.853 1.064 1.418 1.445 0.395 0.228 E22 SN15 0.000 0.000 0.000 0.000 0.000 0.000 NA gna1-35 0.800 0.510 1.155 0.822 0.323 0.187 E23 SN15 0.642 1.190 1.863 1.232 0.612 0.353 NA gna1-35 0.000 0.000 0.000 0.000 0.000 0.000 E24 SN15 0.518 0.382 1.170 0.690 0.421 0.243 NA gna1-35 0.000 0.000 0.000 0.000 0.000 0.000 E25 SN15 0.521 0.421 1.303 0.748 0.483 0.279 NA gna1-35 0.000 0.000 0.000 0.000 0.000 0.000
256 Appendices
73Supplementary BlastP data (Appendix D) Appendix D. BlastP values of putative Gna1 , Mak2 and Sch1 regulated genes. Continued on the next page.
Broad acc ID % amino E-value BlastP functional ma tch (organism; Genbank acc ID) acid identity SNOG_00656.1 36% 1E 44 Vacuolar targeting protein (Candida albicans ; XP_711465.1) SNOG_11078.1 37% 2E 53 Hypothetical protein (NmrA like domain) (Gibberella zeae ; XP_384929) SNOG_15451.1 47% 1E 73 Acetyl xylan esterase ( Aspergillus oryzae ; BAD12626.1) SNOG_14370.1 31% 5E 35 Tyrosinase, putative ( Aspergillus fumigatus ; EAL86390.1) SNOG_06492.1 100% 0.0E Subtilisin like protease ( Phaeosphaeria nodorum ; AAP30889.1) SNOG_05974.1 79% 2E 148 Malate dehydrogenase ( Paracoccidioides brasiliensis ; AAP37966.2) SNOG_12730.1 29% 1E 19 Putative protein ( Neurospora crassa ; CAC28723.1) SNOG_01569.1 51% 1E 90 Cell wall glucanase ( Aspergillus fumigatus ; XP_748349.1) SNOG_06180.1 43% 2E 35 Hypothetical protein ( Chaetomium globosum ; EAQ89481.1) SNOG_05918.1 29% 2E 12 Hypothetical protein ( Aspergillus niger ; CAJ18289.1) SNOG_08052.1 Poor BlastP match SNOG_13504.1 40% 2E 26 Predicted protein ( Chaetomium globosum ; EAQ87808.1) SNOG_16063.1 33% 1E 08 RNase T1 ( Aspergillus oryzae ; CAA30560.1) SNOG_00848.1 63% 2E 38 Peptidylprolyl isomerase ( Neurospora crassa ; CAA06962.1) SNOG_10685.1 Poor BlastP match SNOG_06491.1 50% 6E 69 Serine protease precursor ( Fusarium oxysporum ; AAC27316.2)
257 Appendices
Appendix D. Continued from the previous page. Broad acc ID % amino E-value BlastP functional match (organism; Genbank acc ID) acid identity SNOG_13042.1 32% 5E 26 Short chain dehydrogenase ( Aspergillus fumigatus ; XP_748339.1) SNOG_10217.1 36% 9E 29 Short chain dehydrogenase/reductase SDR ( Solibacter usitatus ; ZP_00520385.1) SNOG_07541.1 84% 5E 129 Proteasome component Pre8 ( Aspergillus funigatus ; XP_748923.1) SNOG_07604.1 55% 7E 64 Glutathione transferase 2 ( Aspergillus fumigatus ; AAX07319.1) SNOG_11441.1 70% 2E 53 3 dehydroquinate dehydratase ( Aspergillus fumigatus ; XP_754140.1) SNOG_11081.1 44% 3E 17 CipC protein ( Emericella nidulans ; CAC87272.1) SNOG_08775.1 50% 5E 60 HAD superfamily hydrolase ( Aspergillus fumigatus ; XP_753809.1) SNOG_15488.1 100% 0.0E Mannitol dehydrogenase ( Phaeosphaeria nodorum ; AAX14688.1) SNOG_08282.1 54% 2E 40 Short chain dehydrogenase, putative ( Aspergillus fumigatus ; EAL86301) SNOG_09590.1 48% 2E 48 Nitroreductase family protein (Bacillus cereus ; ZP_00240643) FP 1_B06 50% 4E 10 Glucose repressible gene protein like protein ( Magnaporthe grisea ; cDNA AAX07712.1)
258 Appendices
Appendix E. Normalised densitometry value of triplicate of protein spots excised from SN15, gna1-
74Densitometry analysis35 , mak2-65 of intracellular and sch1-42 protein sp intracellular proteome analysis with 2D gel electrots in Chapters 3 and 4 (Appendix E) ophoresis. Unpaired t test was used to analyse protein spots for significant differences in the normalised volumes of SN15 and mutants (p < 0.05). For the purpose of graphing with transcript data, normalised values were re standardised to “1” in SN15 (Chapters 3 and 4). Continued on the next page. Spot Strain Normalised protein Mean SD SE p-va lue abundance value C1 SN15 6.014 2.709 5.199 4.641 1.722 0.994 gna1-35 1.567 1.421 2.082 1.690 0.347 0.200 0.044 mak2-65 2.281 1.420 2.683 2.128 0.645 0.373 0.077 C2 SN15 2.189 2.354 3.415 2.653 0.665 0.384 gna1-35 0.077 0.140 0.238 0.152 0.081 0.047 0.023 mak2-65 0.197 0.135 0.189 0.174 0.034 0.019 0.023 C3 SN15 2.389 3.650 2.943 2.994 0.632 0.365 gna1-35 0.966 1.243 2.363 1.524 0.740 0.427 0.059 mak2-65 0.567 0.371 1.955 0.964 0.864 0.499 0.030 C4 SN15 0.272 0.716 0.84 0.609 0.299 0.172 gna1-35 0.254 0.000 0.000 0.085 0.147 0.085 NA mak2-65 0.000 0.000 0.000 0.000 0.000 0.000 NA C5 SN15 1.184 1.477 1.78 1.480 0.298 0.172 gna1-35 1.126 0.949 2.312 1.462 0.741 0.428 0.971 mak2-65 0.05 0.203 0 0.084 0.106 0.061 0.010 C6 SN15 0.486 0.410 0.224 0.373 0.135 0.078 gna1-35 0.131 0.105 0.083 0.106 0.024 0.014 0.028 mak2-65 0.055 0.038 0.000 0.031 0.028 0.016 0.048
259 Appendices
Appendix E. Continued from the previous page. Spot Strain Normalised protein Mean SD SE p-value abundance value C7 SN15 0.238 0.000 0.000 0.079 0.137 0.079 gna1-35 0.297 0.322 0.445 0.355 0.079 0.046 NA mak2-65 0.068 0.138 0.099 0.102 0.035 0.020 NA C8 SN15 3.140 4.096 4.074 3.770 0.546 0.315 gna1-35 0.588 0.000 0.000 0.196 0.339 0.196 NA mak2-65 3.178 3.263 2.303 2.915 0.531 0.307 0.124 C9 SN15 0.825 0.184 0.511 0.507 0.321 0.185 gna1-35 0.219 1.459 0.235 0.638 0.711 0.411 0.787 mak2-65 2.988 2.997 3.440 3.142 0.258 0.149 0.000
260 Appendices
75Densitometry analysis of intracellular protein spots in Chapter 5 (Appendix F)
Appendix F. Normalised densitometry value of triplicate of protein spots excised from SN15 and
sch1-42 intracellular proteome analysis with 2D gel electrophoresis. Unpaired t test was used to
analyse protein spots for significant differences in the normalised volumes (p < 0.05). Spot Strain Normalised protein Mean SD SE p-value abundance value C1 SN15 4.844 2.945 4.091 3.960 0.956 0.552 0.015 sch1-42 7.314 10.617 8.058 8.663 1.733 1.000 C2 SN15 0.921 0.831 0.907 0.048 0.048 0.028 NA sch1-42 0.000 0.000 0.000 0.000 0.000 0.000 C10 SN15 0.152 0.241 0.196 0.045 0.045 0.026 0.036 sch1-42 1.278 1.537 2.245 0.501 0.501 0.289 C11 SN15 0.000 0.000 0.000 0.000 0.000 0.000 NA sch1-42 0.564 0.539 1.174 0.360 0.360 0.208
261 Appendices
Appendix76 In vitro metabolomics G. A comparative analysis for metabolite abundance i data (Appendix G) n SN15, Ect, sch1-11 and sch1-42 grown in MM broth with glutamate and foam. The average and standard error of the no rmalised integrated signal value of each metabolite is given. The number of TMS group attached to each metabolite derivative is indicated in brackets where possible. Colour coding in the first column are key references to compound classification in Figure 5.24. Continued on the next page.
RT SN15 Ect sch1-11 sch1-42 Metabolite match (minute) Average SE Average SE Average SE Average SE Identified L Alanine (2TMS) 5.86 2.410 0.187 0.958 0.445 1.219 0.297 4.078 1.187 L Valine (2TMS) 9.15 0.286 0.021 0.242 0.099 0.563 0.041 2.672 0.066 L Leucine (2TMS) 10.86 0.104 0.006 0.095 0.048 0.058 0.020 0.117 0.051 L Isoleucine (2TMS) 11.51 0.107 0.028 0.119 0.063 0.038 0.021 0.074 0.037 Glycine (3TMS) 11.72 0.773 0.054 0.575 0.117 0.621 0.227 1.007 0.310 L Serine (2TMS) 12.16 0.388 0.052 0.794 0.087 0.378 0.069 0.434 0.123 1,3 di tert butylbenzene 12.33 0.091 0.036 0.105 0.008 0.073 0.018 0.164 0.049 L Proline (2TMS) 12.54 0.442 0.027 0.434 0.217 0.000 0.000 0.000 0.000 Phosphoric acid (3TMS) 12.81 12.008 1.099 15.088 1.555 14.347 4.445 12.978 2.926 L Alanine (3TMS) 12.99 0.844 0.107 0.376 0.143 1.233 0.661 0.964 0.228 L Serine (3TMS) 13.65 1.013 0.128 0.943 0.261 0.682 0.231 1.016 0.339 Fumaric acid (2TMS) 13.79 0.189 0.025 0.257 0.025 0.077 0.024 0.111 0.082 L Threonine (3TMS) 14.10 0.954 0.102 1.107 0.234 0.421 0.126 0.729 0.235 Succinic acid (2TMS) 14.18 0.349 0.027 0.372 0.128 0.903 0.180 1.330 0.172 β Alanine (3TMS) 15.00 0.130 0.015 0.084 0.043 0.065 0.010 0.017 0.017 L Aspartic acid (3TMS) 17.55 0.133 0.031 0.141 0.057 0.166 0.026 0.803 0.380 4 Aminobutyric acid (3TMS) 17.73 0.796 0.064 1.101 0.508 4.916 1.124 12.463 2.187 Malic acid (3TMS) 17.81 2.595 0.218 3.492 0.038 1.786 0.328 3.137 0.747 4 Hydroxyproline (3TMS) 17.85 0.116 0.028 0.355 0.118 0.229 0.062 0.223 0.035 L Aspartic acid (3TMS) 18.48 1.471 0.020 1.176 0.078 1.390 0.414 1.195 0.372
262 Appendices
Appendix G . Continued from the p revious page.
RT SN15 Ect sch1-11 sch1-42 Metabolite match (minute) Average SE Average SE Average SE Average SE Identified Glutamine (4 TMS) 20.04 8.231 1.584 3.618 1.962 9.729 5.036 6.224 2.982 N Acetylglutamic acid (2 TMS) 20.28 0.935 0.073 1.645 0.692 1.405 0.322 0.664 0.077 Xylitol (5 TMS) 20.73 3.827 1.449 1.149 0.247 5.264 0.576 13.440 3.537 L Glutamic acid (3 TMS) 20.85 25.217 2.089 18.851 3.385 12.246 4.005 30.932 7.637 Pyroglutamic acid (2 TMS) 20.98 22.651 7.009 17.616 5.101 13.645 2.226 29.796 8.732 L Phenylalanine (2 TMS) 21.85 0.107 0.012 0.153 0.012 0.063 0.018 0.059 0.041 L Proline (2 TMS) 22.42 0.301 0.057 0.254 0.061 0.126 0.023 0.385 0.265 1H Indole 2,3 dione 22.56 1.069 0.143 0.800 0.028 0.796 0.166 0.933 0.240 L Asparagine (3 TMS) 22.86 1.193 0.062 1.760 0.256 0.604 0.082 0.842 0.336 Ornithine (4 TMS) 23.35 4.605 0.586 1.307 0.352 2.232 0.932 2.997 1.328 Mannitol (6 TMS) 24.43 142.389 48.297 131.752 19.619 113.422 11.988 204.479 31.027 L Glutamine (3 TMS) 25.14 35.560 4.761 25.948 4.826 26.499 2.367 43.326 10.082 L Lysine (4 TMS) 25.39 3.660 0.347 6.771 1.860 1.821 0.337 2.543 0.714 Allantoin (5 TMS) 26.29 1.884 0.078 1.719 0.185 1.523 0.318 1.517 0.347 myo Inositol (6 TMS) 26.86 0.103 0.006 0.129 0.018 0.138 0.028 0.086 0.051 Methylcitric acid (4 TMS) 27.16 0.000 0.000 0.000 0.000 0.081 0.031 0.065 0.034 Allantoin (4 TMS) 27.54 4.638 0.383 4.097 1.618 2.536 0.250 3.508 0.720 L Tyrosine (3 TMS) 27.75 0.165 0.004 0.368 0.072 0.067 0.016 0.049 0.036 Hexadecanoic acid (1 TMS) 28.88 0.825 0.138 0.979 0.105 1.007 0.136 1.781 0.506 Glutamine (4 TMS) 29.07 0.574 0.121 0.232 0.065 0.872 0.556 0.236 0.052 Octadecanol (1 TMS) 29.93 0.090 0.018 0.261 0.015 0.224 0.054 0.120 0.064 Octadecanoic acid (1 TMS) 32.31 1.266 0.205 2.068 0.301 2.083 0.247 2.708 0.582 L(+) Cystathonine (4 TMS) 32.39 0.384 0.017 0.412 0.128 0.441 0.105 0.195 0.109
263 Appendices
Appendix G . Continued from the previous page. RT SN15 Ect sch1-11 sch1-42 Metabolite match (minute) Average SE Average SE Average SE Average SE Identified 9,12 (Z,Z) Octadecadienoic acid 32.61 0.597 0.126 0.641 0.044 0.968 0.168 1.230 0.287 (1 TMS) Trehalose (8 TMS) 38.46 0.407 0.041 1.664 0.440 0.604 0.195 0.422 0.207 Unidentified [Glycine (3 TMS)] 9.46 2.235 0.401 1.696 0.340 1.364 0.296 3.210 1.041 [Indole 3 acetaldehyde {BP} 10.16 0.054 0.013 0.096 0.015 0.045 0.005 0.093 0.071 (TMS)] [β Alanine (3 TMS)] 13.19 0.219 0.021 0.117 0.042 0.778 0.154 2.501 1.372 [Calystegine B2 B4 (4 TMS)] 15.35 0.161 0.028 0.202 0.009 0.159 0.019 0.407 0.203 [L Proline (2 TMS)] 19.70 0.187 0.011 0.343 0.145 0.216 0.021 0.058 0.032 [L Alanine (3 TMS)] 20.37 0.369 0.024 0.283 0.039 0.140 0.057 0.038 0.024 [Phosphoric acid (3 TMS)] 24.68 0.115 0.012 0.054 0.032 0.171 0.043 0.171 0.114 [Trehalose (8 TMS)] 28.75 1.621 0.069 1.344 0.719 1.894 0.277 1.864 0.386 [Triethanolamine (3 TMS)] 31.02 0.049 0.026 0.115 0.010 0.084 0.012 0.100 0.018 [1 Aminocyclopropanecarboxylic 31.12 1.220 0.154 1.397 0.197 0.901 0.115 0.752 0.154 acid (3 TMS)] [Galactinol (9 TMS)] 33.46 0.122 0.007 0.114 0.018 0.175 0.003 0.279 0.045 [Urea (2 TMS)] 33.68 0.177 0.045 0.256 0.131 0.033 0.018 0.031 0.031 [trans Ferulic acid (2 TMS)] 38.81 0.102 0.078 0.225 0.139 0.203 0.050 0.152 0.088 [Glucopyranose (5 TMS)] 42.86 0.204 0.012 0.204 0.015 0.252 0.029 0.554 0.198 [Calystegine B2 methoxyamine (4 45.57 0.357 0.014 0.073 0.014 30.710 3.556 72.194 12.545 TMS)] [Galactonic acid (6 TMS)] 50.92 0.490 0.034 0.713 0.243 0.305 0.028 0.212 0.122
264 Appendices
77The AMDIS mass spectrum format of RT4557 (Appendix H)
( 45 41) ( 73 350) ( 74 32) ( 75 34) (133 14) (165 7) (207 6) (222 78) (251 3) (269 9) (272 1) (283 4) (285 8) (297 8) (315 20) (317 4) (325 2) (328 6) (329 4) (339 3) (340 3) (341 7) (342 5) (343 8) (345 2) (353 1) (355 5) (357 27) (358 13) (359 5) (367 2) (368 2) (369 11) (371 12) (372 5) (374 2) (384 6) (385 8) (386 16) (387 56) (388 16) (389 7) (415 2) (429 15) (430 5) (432 1) (441 1) (443 11) (444 4) (446 2) (457 21) (459 1000) (460 394) (461 181) (462 46) (464 3) (471 2) (473 7) (474 12) (475 7) (476 4) (517 6) (518 3) (531 3) (547 196) (548 97) (549 44) (550 13) (551 5) (562 11) (563 7) (564 4)
Appendix H. The AMDIS mass spectrum format of RT4557 from SN15. Seventy two peaks were detected (left of brackets) and their relative intensities (right of brackets).
265 Appendices
78Peptide coverage of CipC (Appendix I)
A Spot C8 1. 00290217925 Score: 414 Queries matched: 12 Query Observed Mr(expt) Mr(calc) Delta Miss Score Expect Rank Peptide 26 451.70 901.38 901.40 -0.03 0 30 0.14 1 AFEDHQR 31 462.67 923.33 923.38 -0.05 0 32 0.057 1 GEDWFDR 37 515.74 1029.46 1029.50 -0.04 1 14 4.6 2 AFEDHQRK 44 591.24 1180.46 1180.51 -0.05 1 43 0.0044 1 GEDWFDREK 48 614.31 1226.61 1226.64 -0.03 0 (19) 1.2 2 EGKPVSHQFAK 49 409.88 1226.61 1226.64 -0.03 0 20 0.86 3 EGKPVSHQFAK 50 660.32 1318.62 1318.68 -0.06 0 65 3e-05 1 ELLAGFAGAEVDK 57 589.61 1765.79 1765.88 -0.08 0 (36) 0.015 1 SSFGHELIAGGAAFAGFK 58 883.91 1765.82 1765.88 -0.06 0 75 2.2e-06 1 SSFGHELIAGGAAFAGFK 60 910.37 1818.73 1818.77 -0.04 0 63 3.3e-05 1 YQQVYENDNFEENK 63 621.30 1860.89 1860.98 -0.09 1 73 3e -06 1 ELLAGFAGAEVDKLAETK
B SNOG _11081 .1 1 ATGGGTTTCTGGGGTAGGTGACGCTCCGAACCAGCATCTCTCGAGTCGTGCTCAACAGTC M G F W 61 CGCAG ATAAGAACGAAGACAAGTACCAGCAGGTGTACGAGAACGACAACTTTGAGGAGAA D K N E D K Y Q Q V Y E N D N F E E N 121 CAAGTCGAGCTTCGGACATGAATTGATTGCCGGAGGAGCTGCCTTTGCTGGTTTCAAAGC K S S F G H E L I A G G A A F A G F K A 181 GTTCGAGGACCATCAGCGCAAGGAGGGTTCGTGCATCCCCCGCCCAACCTGGCACACTCT F E D H Q R K E 241 ATACTGACAATCATGACTAG GCAAGCCCGTTTCCCACCAGTTCGCCAAAGAGCTCCTTGC G K P V S H Q F A K E L L A 301 CGGCTTCGCAGGTGCCGAAGTCGACAAGCTCGTGAGTCCGATCGCACCCTCAGACACACA G F A G A E V D K L 361 GCACACTGACACCAAGGCAG GCCGAGACAAAGGGCGAGGACTGGTTCGACCGCGAGAAGG A E T K G E D W F D R E K 421 CTCAGCATGAGGCTAAAAAGCAAGCCGAGCACATGTACGACGAGCACTACGTGAACGGCC A Q H E A K K Q A E H M Y D E H Y V N G 481 AGGGTGCGAACCAGTATGATCCCAACCAGTACGGGCGCCCTGAGCACTTTGACAGGCGCG Q G A N Q Y D P N Q Y G R P E H F D R R 541 GCTGGTAA G W * Appendix I . A. LC MS/MS analysis of spot C8. Mascot was used to match the mass spectrum generated by trypsinated peptides to the Broad predicted S. nodorum protein database for a matching gene. B. Peptide coverage of CipC confirmed two of the three
Broad predicted introns.
266 Appendices
79Construction of the CipC knockout vector (Appendix J)
XK XK B 1 3 i CipC 2 4
K X B XK N 5 ii Phleomycin R 6
XK X B B
iii Phleomycin R XK 1 kb
Appendix J. i. The CipC knockout vector was constructed by ligating PCR amplified 5' and 3' UTR region of CipC to the Kpn I/ Xho I and Bam HI/ Not I restriction sites of pBSK phleo, respectively. ii. The knockout vector was PCR amplified and transformed into
SN15 to facilitate iii. homologous gene replacement. Restriction sites are as follows, X.
Xho I; B. BamHI; K. Kpn I and N. Not I. Primers are as follows:
Kpn I 1. F6B035’fwd (5’ GGTACC CCCGCAGCTAAGCTTTCT 3’) Xho I 2. F6B035’rev (5’ CTCGAG GCGGATCACTCCATTAAG 3’) Bam HI 3. F6B033’fwd (5’ GGATCC GCCCTGAGCACTTTGACA 3’) Not I 4. F6B033’rev (5’ GCGGCCGC TTGATGTACGTGTACTTG 3’) 5. 5’FP6B03KOcon (5’ CCCGCAGCTAAGCTTTCTCTAAA 3’) 6. 3’FP6B03KOcon (5’ TCTTCTTGCCTGTCTGCAGCG 3’) Bold text refers to introduced restriction sites used for cloning.
267 Appendices
80PeptideSpot coverage C1 of Sch2 (Appendix K) A 1. 00290256263 Score: 683 Queries matched: 21 Query Observed Mr(expt) Mr(calc) Delta Miss Score Expect Rank Peptide 10 424.19 846.36 846.41 -0.05 0 27 0.32 1 NTADLEGK 13 436.67 871.32 871.51 -0.20 0 53 0.00066 1 AGGNIVITK 17 495.75 989.49 989.55 -0.06 0 16 3.3 1 STTVVIGASR 22 521.74 1041.46 1041.53 -0.07 0 16 2.3 1 GPVTPEESVK 25 568.77 1135.52 1135.59 -0.07 0 46 0.0024 1 IANSVPYSASK 30 400.19 1197.56 1197.64 -0.08 1 (36) 0.023 1 GPVTPEESVKR 31 599.79 1197.56 1197.64 -0.07 1 43 0.0048 1 GPVTPEESVKR 43 903.92 1805.83 1805.92 -0.09 0 82 3.7e-07 1 VTYISSAVADGPETVAAR 44 603.29 1806.86 1805.92 0.94 0 (57) 0.00011 1 VTYISSAVADGPETVAAR 45 622.64 1864.89 1864.99 -0.10 0 (58) 7.8e-05 1 VANVHVVEADLVSADSLK 46 933.46 1864.90 1864.99 -0.09 0 103 2.5e-09 1 VANVHVVEADLVSADSLK 49 654.98 1961.93 1962.02 -0.09 1 66 1.4e-05 1 RVTYISSAVADGPETVAAR 51 727.35 2179.03 2179.15 -0.12 1 71 3.7e-06 1 ADKVANVHVVEADLVSADSLK 52 545.77 2179.07 2179.15 -0.08 1 (38) 0.0069 1 ADKVANVHVVEADLVSADSLK 53 1114.56 2227.11 2227.20 -0.09 0 51 0.00041 1 SDEANVAGPLFAINAFLPLLR 54 743.38 2227.12 2227.20 -0.08 0 (48) 0.00078 1 SDEANVAGPLFAINAFLPLLR 56 756.03 2265.08 2265.18 -0.10 0 (58) 7.9e-05 1 GIGYQFIQTLAAEGNTVVGTAR 57 1133.55 2265.08 2265.18 -0.09 0 74 1.8e-06 1 GIGYQFIQTLAAEGNTVVGTAR 58 756.36 2266.07 2265.18 0.90 0 (31) 0.034 1 GIGYQFIQTLAAEGNTVVGTAR 62 786.06 2355.16 2355.29 -0.14 1 39 0.0048 1 KSDEANVAGPLFAINAFLPLLR 63 786.73 2357.18 2355.29 1.88 1 (35) 0.015 1 KSDEANVAGPLFAINAFLPLLR
B SNOG _13042 .1 1 ATGTCTACCACCGTTGTCATCGGCGCCTCGCGCGGAATCGGGGTATGTATGCCGCATCTT M S T T V V I G A S R G I G 61 TTACATCACAATTTTTCTGGTTCAGCCTTAGAAGATAGGAAAGGGCTGAATATCTTAG TA Y 121 TCAATTCATTCAAACCCTCGCCGCTGAGGGAAATACCGTCGTTGGGACTGCACGCAATAC Q F I Q T L A A E G N T V V G T A R N T 181 CGCCGACCTCGAGGGCAAGCTGAAAGCCGACAAGGTTGCAAATGTGCATGTCGTCGAGGC A D L E G K L K A D K V A N V H V V E A 241 TGACTTGGTTTCTGCGGACTCCTTGAAAGCTGCAGCAAAGGCCACATCCTCCCTTGTCAA D L V S A D S L K A A A K A T S S L V N 301 CGGCCAGATCGATCACCTGATCATCAACGGCGCCTTTCTCTCTTCCACCACAGGTGGCAT G Q I D H L I I N G A F L S S T T G G M 361 GAACCCCACTGATTTCGCCGAAAAGCCCGAGCTCTTCCTTGAGGAGCTTAAGAAGAGTGA N P T D F A E K P E L F L E E L K K S D 421 CGAGGCCAATGTGGCTGGACCGCTGTTCGCGATCAACGCCTTCCTGCCGCTCCTCCGCAA E A N V A G P L F A I N A F L P L L R K 481 AGGCACGGAGAAGCGCGTTACGTACATATCCAGTGCCGTTGCTGATGGGCCTGAGACTGT G T E K R V T Y I S S A V A D G P E T V 541 GGCGGCCCGCATCGCGAACTCAGTTCCGTACAGCGCAAGCAAGGCGGGAGGTAACATTGT A A R I A N S V P Y S A S K A G G N I V 601 CATCACCAAGTTTGCGGCCGAGCTCCAGGACGAAGGCTTCACCTTCCTGAGCATTGCGCC I T K F A A E L Q D E G F T F L S I A P 661 TGGCGCAGTTGCGACGGACACGCTGATGAACGCGTCCGCCAATTGTAGGTTTTCCCTCCC G A V A T D T L M N A S A N 721 TTTGATTGCAATTTCTCTGACCAGACGTCTACAG TCAGCGAAGCGGATAAGGAGAAGATG F S E A D K E K M 781 CAGGGCATGTTCGCCAGGCTGATGCAAAAGTACCCCGAATGGAAGGGTCCGGTCACTCCT Q G M F A R L M Q K Y P E W K G P V T P 841 GAGGAGAGCGTGAAGAGGATCTTGGAAGTCGTAAAGAAGTCTAAGCCTGAGCAGAGTGGC E E S V K R I L E V V K K S K P E Q S G 901 CAGTTCTTGAGCTACTGGGGCAACACTACCGAGTGGTTGTAG Q F L S Y W G N T T E W L *
Appendix K . A. LC MS/MS analysis of spot C1. Mascot was used to match the mass spectrum generated by trypsinated peptides to the Broad predicted S. nodorum protein database for a matching gene (red font). B. Peptide coverage of Sch2 confirmed one of the two Broad predicted introns.
268 Appendices
81Construction of the Sch2 knockout vector (Appendix L)
P P P P 1 3 i Sch2 2 4
K P PH P B 5 ii Phleomycin R 6
P P P H P iii Phleomycin R
1 kb
Appendix L. i. The Sch2 knockout vector was constructed by ligating PCR amplified 5' and 3' UTR region of Sch2 to the Kpn I/ Hin dIII and Pst I/ Bam HI restriction sites of pBSK phleo, respectively. ii. The knockout vector was PCR amplified and transformed into SN15 to facilitate iii. homologous gene replacement. Restriction sites are as follows, P. Pst I; B. Bam HI; K. Kpn I and H. Hin dIII. Primers are as follows:
Kpn I 1. R1048_5’Fwd (5’ GGTACC CGCAAGCCACTCGAATCTAG 3’) Hin dIII 2. R1048_5’Rev (5’ AAGCTT CGATGACAACGGTGGTAGAC 3’) Pst I 3. R1048_3’Fwd (5’ CTGCAG AGAGTGGCCAGTTCTTGAGC 3’) Bam HI 4. R1048_3’Rev (5’ GGATCC GAGCAATACATAGCTACTGCA 3’) 5. R1048FwdKO (5’ GCCACTCGAATCTAGACTTCCCG 3’) 6. R1048RevKO (5’ GATGCCTAAGTGTTGAAGCTGAGCA 3’) Bold text refers to introduced restriction sites used for cloning.
269 Appendices
A Spot C5 1. 00290250611 Score: 507 Queries matched: 17 Query Observed Mr(expt) Mr(calc) Delta Miss Score Expect Rank Peptide 5 401.74 801.46 801.46 -0.00 0 32 0.097 1 AVVEVTGK 7 414.76 827.51 827.51 -0.01 0 29 0.16 1 GIGLELVK 82Peptide 14 coverage 452.76 of Sch3 903.50 (Appendix 903.48 M) 0.01 0 56 0.00037 1 LLGAYPDR 30 636.35 1270.69 1269.69 1.00 0 14 3.8 3 IILESTPAQNGK 41 476.60 1426.78 1425.79 0.98 1 10 7.1 2 RIILESTPAQNGK 42 714.40 1426.79 1425.79 0.99 1 (9) 9.1 3 RIILESTPAQNGK 44 829.42 1656.83 1656.83 -0.00 0 66 1.9e-05 1 TSHVVASVGDTESIQK 45 553.29 1656.85 1656.83 0.02 0 (32) 0.04 1 TSHVVASVGDTESIQK 51 641.71 1922.11 1922.12 -0.01 0 (27) 0.11 1 QLLELPVSQVGTVVALTR 52 962.07 1922.13 1922.12 0.01 0 46 0.0014 1 QLLELPVSQVGTVVALTR 53 642.05 1923.13 1922.12 1.01 0 (19) 0.66 1 QLLELPVSQVGTVVALTR 54 978.52 1955.02 1955.02 0.00 0 89 7.4e-08 1 GLDVLVNNAGVQAFAPGGTR 55 652.68 1955.03 1955.02 0.01 0 (45) 0.0016 1 GLDVLVNNAGVQAFAPGGTR 57 1056.03 2110.05 2110.06 -0.01 0 (62) 3e-05 1 TELGGEHAEFPVEVGVAELK 58 704.36 2110.06 2110.06 -0.00 0 73 2.1e-06 1 TELGGEHAEFPVEVGVAELK 61 756.40 2266.17 2266.16 0.01 1 52 0.00027 1 TELGGEHAEFPVEVGVAELKR 63 848.45 2542.34 2542.30 0.04 1 42 0.002 1 LLGAYPDRTSHVVASVGDTESIQK
B 1.FP-7_B06.SEQ Score: 504 Queries matched: 20 Query Observed Mr(expt) Mr(calc) Delta Miss Score Expect Rank Peptide 23 846.93 1691.85 1691.86 -0.00 0 50 0.00037 1 VINVSSSMGSLTWAPK 25 607.66 1819.96 1819.95 0.01 1 29 0.041 1 KVINVSSSMGSLTWAPK
C SNOG _08282 .1 1 ATGGCCTCATTCCTAATCACCGGTGCTTCTCGCGGTATTGGCCTTGAGCTGGTCAAGCAG M A S F L I T G A S R G I G L E L V K Q 61 TTGCTGGAGCTTCCCGTCTCGCAGGTTGGCACAGTTGTGGCCCTCACACGCAGCAGCGAA L L E L P V S Q V G T V V A L T R S S E 121 TGTCCCTCCTTAGCGAAGCTGCTCGGCGCCTACCCAGATCGCACTAGCCATGTTGTTGCT C P S L A K L L G A Y P D R T S H V V A 181 TCTGTGGGCGACACGGAAAGCATCCAGAAGGCCGTCGTGGAGGTCACCGGAAAGCTTGGC S V G D T E S I Q K A V V E V T G K L G 241 GGCCGTGGTCTGGACGTTCTTGTGAACAACGCCGGCGTCCAAGCGTTCGCTCCCGGCGGT G R G L D V L V N N A G V Q A F A P G G 301 ACTAGGACGGTCCCTCCCGAACAGCTCAGAGATATCTTCGATACCAATGTGGTAAGTCAC T R T V P P E Q L R D I F D T N V 361 AATCGAGGCCGTAGTATTCTTGAAGGCGCACACTTAACACTTCGCAGTATGTAAACTCCT
421 TTGAGCATTTCCCACATTGTCCACTCGCTATGTCTAGTCATGCAGAGCTGCAGTGCTGCC
481 TCTGGTTCTTACATAACGCCAAAACGCCACATGGCGCTCCTTCACACACGATGGTCGAGC
541 ATATACACTGACATTCTACCTTCCCTTTTAG TGTCGGAGTGCACCGAGTCACTTCCGCTT V G V H R V T S A 601 TCCTACCCTTGTTGGAGGCTGGCAAGTCGAAGAAAGTGATCAATGTGTATGTTACCCCAA F L P L L E A G K S K K V I N V 661 AAACGTAGACAGCCGCATCTAATCGTAGGGCAG CTCGTCCTCGATGGGCTCCCTTACATG S S S M G S L T W 721 GGCGCCAAAGTACAAGATGGCCCCCACGCAGGCCTACAAAGTTTCAAAGGCCGCACTCCA A P K Y K M A P T Q A Y K V S K A A L H 781 CATGCTCAATGCACAGTACGCCCTAGACCACGCAGACGCGGGGTTCACGTTCCTCTGCGT M L N A Q Y A L D H A D A G F T F L C V 841 ATCCCCTGGCGTAAGTATTTGCCCTCAGCAGATTTCACCAAAACAGAGAGGCTGACGCTG S P G 901 TACAG TGGCTGAAGACTGAATTGGGAGGCGAGCACGCCGAATTTCCTGTCGAGGTTGGTG W L K T E L G G E H A E F P V E V G 961 TTGCTGAGCTGAAGAGGATCATTCTCGAATCAACGCCAGCTCAAAACGGGAAATTGGTCA V A E L K R I I L E S T P A Q N G K L V 1021 ACATCCATGTTCCTGGCCAAGAGGACAGTTGGGGCCATTACGACGGTGGAGAGATCCCTT N I H V P G Q E D S W G H Y D G G E I P 1081 GGTAG W *
Appendix M . A. LC MS/MS analysis of spot C5. Mascot was used to match the mass spectrum generated by trypsinated peptides to the Broad predicted S. nodorum protein database for a matching gene (red font). B. A repeat analysis was performed on an SN15 oleate grown cDNA library taking in account of peptide modifications from common oxidation of methionine residues (blue font). Only modified peptides are shown. C. Peptide coverage of Sch3 confirmed two of the three Broad predicted introns. 270 Appendices
83Construction of the Sch3 knockout vector (Appendix N)
K KX 1 3 i Sch3 2 4
K X B N 5 ii Phleomycin R 6
K X B KX iii Phleomycin R
1 kb
Appendix N. i. The Sch3 knockout vector was constructed by ligating PCR amplified 5' and 3' UTR region of Sch3 to the Kpn I/ Xho I and Bam HI/ Not I restriction sites of pBSK phleo, respectively. ii. The knockout vector was PCR amplified and transformed into
SN15 to facilitate iii. homologous gene replacement. Restriction sites are as follows, X.
Xho I; B. Bam HI; K. Kpn I and N. Not I. Primers are as follows:
Kpn I 1. 5'FwdKpnI R637 (5’ GGTACC GAGCTATGGAACATGTACAGG 3’) Xho I 2. 5'RevXhoI R637 (5’ CTCGAG TGTTTGCGCTTCACTTGCTT 3’) Bam HI 3. 3'FwdBamHI R637 (5’ GGATCC GTACAGTGGCTGAAGACTGA 3’) Not I 4. 3'RevNotI R637 (5’ GCGGCCGC ATGTAGTAATCATTTAGGTC 3’) 5. R637FwdKO (5’ ATGGAACATGTACAGGGTGTCGC 3’) 6. R637RevKO (5’ GCCACAACACTGAACGTGCTCAA 3’) Bold text refers to introduced restriction sites used for cloning.
271 Appendices
84Peptide coverage of Nrd1 (Appendix O)
A Spot C10 1. 00290215281 Score: 428 Queries matched: 20 Query Observed Mr(expt) Mr(calc) Delta Miss Score Expect Rank Peptide 21 390.24 778.47 778.42 0.04 0 40 0.021 1 SFLDAVK 24 417.26 832.51 832.46 0.05 0 31 0.17 1 GQLVFGGR 7 300.83 899.47 899.49 -0.02 1 (22) 1.1 1 LFVHGAKE 31 450.77 899.53 899.49 0.04 1 47 0.0038 1 LFVHGAKE 42 514.81 1027.61 1027.55 0.06 1 (13) 8 2 RTYYALNK 43 514.83 1027.65 1027.55 0.10 1 14 6.6 1 RTYYALNK 48 532.81 1063.61 1063.57 0.04 1 (38) 0.026 1 SFLDAVKER 49 532.82 1063.63 1063.57 0.06 1 44 0.0071 1 SFLDAVKER 125 729.01 1456.01 1455.75 0.25 0 20 1.5 1 AAQQWSIPLEWK 47 525.33 1572.97 1572.75 0.22 1 41 0.015 1 AGGVGEKEFQETHGK 217 806.93 1611.85 1611.81 0.03 1 2 90 3 TYYALNKEAPISDK 88 643.14 1926.40 1926.93 -0.53 0 (49) 0.0016 1 GAYGTILFYEDPEPVEK 294 964.48 1926.95 1926.93 0.02 0 56 0.00039 1 GAYGTILFYEDPEPVEK 132 733.15 2196.43 2196.11 0.32 1 49 0.0016 1 GAYGTILFYEDPEPVEKLR 208 805.30 2412.88 2413.22 -0.35 0 (15) 4.5 1 ITEIAEQAVLHVPSSFNSQSTR 210 805.65 2413.93 2413.22 0.70 0 (3) 63 1 ITEIAEQAVLHVPSSFNSQSTR 211 805.71 2414.11 2413.22 0.88 0 54 0.00056 1 ITEIAEQAVLHVPSSFNSQSTR 212 805.79 2414.35 2413.22 1.12 0 (5) 39 1 ITEIAEQAVLHVPSSFNSQSTR 214 805.81 2414.41 2413.22 1.18 0 (16) 3.5 1 ITEIAEQAVLHVPSSFNSQSTR 235 829.80 2486.38 2486.24 0.14 1 29 0.17 1 INGFKGAYGTILFYEDPEPVEK
Spot C11 1. 00290215281 Score: 393 Queries matched: 14 Query Observed Mr(expt) Mr(calc) Delta Miss Score Expect Rank Peptide 25 417.28 832.55 832.46 0.09 0 31 0.17 1 GQLVFGGR 26 436.74 871.47 871.44 0.02 0 23 0.9 1 TYYALNK 30 450.77 899.53 899.49 0.04 1 42 0.013 1 LFVHGAKE 4 300.91 899.71 899.49 0.22 1 (24) 0.66 1 LFVHGAKE 34 514.74 1027.47 1027.55 -0.08 1 15 5.5 1 RTYYALNK 37 532.85 1063.69 1063.57 0.12 1 37 0.038 1 SFLDAVKER 103 728.60 1455.19 1455.75 -0.57 0 35 0.036 1 AAQQWSIPLEWK 35 525.30 1572.88 1572.75 0.13 1 27 0.4 1 AGGVGEKEFQETHGK 39 538.29 1611.85 1611.81 0.03 1 11 18 1 TYYALNKEAPISDK 269 964.37 1926.73 1926.93 -0.20 0 65 3.4e-05 1 GAYGTILFYEDPEPVEK 68 643.45 1927.33 1926.93 0.40 0 (55) 0.00044 1 GAYGTILFYEDPEPVEK 106 733.09 2196.25 2196.11 0.14 1 47 0.0029 1 GAYGTILFYEDPEPVEKLR 174 805.48 2413.42 2413.22 0.19 0 (11) 13 1 ITEIAEQAVLHVPSSFNSQSTR 176 805.78 2414.32 2413.22 1.09 0 59 0.00016 1 ITEIAEQAVLHVPSSFNSQSTR
Appendix O . Continued on the next page.
272 Appendices
B SNOG_09590.1 1 ATGGCGGTTGCTCCCAAATCACTCCTAGTTGGCTTGCTGGTCGGCGTTTTTCTGGCTTTT M A V A P K S L L V G L L V G V F L A F 61 CTGGCACCACAACTCGTTTCTCATTCGCAGTTGCCGATACAAGAAGAAGCTGGAGAGCTG L A P Q L V S H S Q L P I Q E E A G E L 121 GGATCTAGCTCACCGCTTTCCATTCAAGCAATGGCGCAAGTACTGAAGAATATTGCCAAA G S S S P L S I Q A M A Q V L K N I A K 181 CGGGGAGTCGCCGGTGGATACAAAAGCCTCTGGGTCCCACCCTCTACCTCAACTTCCTCA R G V A G G Y K S L W V P P S T S T S S 241 TTATTACGCTCTTCATCTACACCCACTGCTTCTTCCACACCTAAACAATCTTCCTTCTCC L L R S S S T P T A S S T P K Q S S F S 301 ACAACCACATCAACCATGTCTGCCCAGAAGTCCTTCTTGGATGCGGTCAAGGAGCGCCGC T T T S T M S A Q K S F L D A V K E R R 361 ACCTACTACGCGCTCAACAAGGAGGCTCCCATCTCCGACAAGCGAATCACCGAGATCGCT T Y Y A L N K E A P I S D K R I T E I A 421 GAGCAAGCTGTTCTCCACGTTCCCTCTTCATTCAACTCTCAGTCCACTCGCCTCGTTGTC E Q A V L H V P S S F N S Q S T R L V V 481 CTTCTGAACAAGGATCACGATACCTTCTGGGGGCATGTGCTCGACGTCTTGAAGCCTCTC L L N K D H D T F W G H V L D V L K P L 541 GTACCTGAGGATCAGTTTCCCTCAACCGCAGAGAGAATCAACGGCTTCAAGGGCGCTTAT V P E D Q F P S T A E R I N G F K G A Y 601 GGAACTGTGAGTACCTCGATTCATTTCTCTATATGGCCGTCGTGCCAGCGTGGGCAAGTC G T 661 TTCTGGTGGTGTCGTGGAGCTCGAAGCTTCGAGCTCGACGCAGCCCCACCAGGTGGACCG
721 CGAGCCCCGCCATTTACTCGCCTGCTCCCACTCCATCGCCCACAAAAGTGCCACGCACTA
781 ACACAGTTGGGTAG ATCCTCTTCTACGAAGACCCGGAACCCGTCGAGAAGCTCCGCAAGG I L F Y E D P E P V E K L R K 841 CATTCCCTGAATACGCCCACCACTTCGGCGACTGGTCTGAGCAGACCGACGCCATGCACC A F P E Y A H H F G D W S E Q T D A M H 901 AGTATGCCCTGTGGGTCGCGCTTGAGGCTGAGGGCTTCGGCGCCAACCTCCAGCACTACA Q Y A L W V A L E A E G F G A N L Q H Y 961 ACCCCATTATCGACCAGAAGGCTGCTCAGCAATGGAGCATTCCGCTCGAGTGGAAGCTCC N P I I D Q K A A Q Q W S I P L E W K L 1021 GTGGACAGCTGGTCTTCGGTGGCCGCGCTGGCGGTGTTGGCGAGAAAGAGTTTCAGGAAA R G Q L V F G G R A G G V G E K E F Q E 1081 CACACGGCAAGAGACTGTTTGTCCACGGTGCTAAGGAGTAA T H G K R L F V H G A K E * Appendix O . A. LC MS/MS analysis of spot C10 and C11. Mascot was used to match the mass spectrum generated by trypsinated peptides to a Broad predicted S. nodorum protein database for a matching gene (red font). B. Peptide coverage of Nrd1 confirmed the single Broad predicted intron. The ghosted Broad predicted coding region should be excluded as part of the Nrd1 open reading frame based on experimental evidence
(Table 6.1).
273 Appendices
85Construction of the Nrd1 knockout construct (Appendix P)
X 1 3 i Nrd1 2 4 K X P B 5 ii Phleomycin R 6
X P iii Phleomycin R
1 kb
Appendix P. i. The Nrd1 knockout vector was constructed by ligating PCR amplified 5' and 3' UTR region of Nrd1 to the Kpn I/ Xho I and Pst I/ Bam HI restriction sites of pBSK phleo, respectively. ii. The knockout vector was PCR amplified and transformed into
SN15 to facilitate iii. homologous gene replacement. Restriction sites are as follows, P.
Pst I; B. Bam HI; K. Kpn I and X. Xho I. Primers are as follows:
Kpn I 1. R638_5’Fwd (5’ GGTACC GCTTACACCAACGATTGTCA 3’) Xho I 2. R638_5’Rev (5’ CTCGAG TGGTTGATGTGGTTGTGGAG 3’) Pst I 3. R638_3’Fwd (5’ CTGCAG TTGTCCACGGTGCTAAGGAG 3’) Bam HI 4. R638_3’Rev (5’ GGATCC TAACGACTGAGCGCATCATC 3’) 5. R638FwdKO (5’ CAACAACGATTGTCAGCAAGGCG 3’) 6. R638RevKO (5’ CGCAATATGGCCAGGGACCA 3’) Bold text refers to introduced restriction sites used for cloning.
274