Lipidomics based analysis in magnaporthe oryzae

LIPIDOMICS-BASED ANALYSIS IN MAGNAPORTHE ORYZAE   Table of Contents Title Page……………………………………………………………… … I Declaration….……………………….………………………………… … II Acknowledgement………………………….………………………… … III Publication List ……………………………………………………… … IV SUMMARY    4   List of Tables    5   List of Figures    6   List of Symbols    8   CHAPTER 1: INTRODUCTION    11   1.1 Challenges in Food Supply    11   1.2 Life Cycle of M oryzae and Rice Blast Disease    12   1.3 Important Signaling Pathways of M oryzae    15   1.4 Lipids and Their Metabolism    17   1.4.1  Phospholipids    17   1.4.2  Neutral  Lipids    24   1.4.3  Sphingolipids    28   1.5 Recent Advances of M oryzae Research    29   1.6 Proposed Model for Turgor Pressure Production    31   1.7  In  silico  Inhibitor  Design    34   1.8 Aims of the Project    36       CHAPTER 2: MATERIALS AND METHODS    38   2.1 Growth Medium    39   2.2 The Fungal Strain, Growth Condition and Appressorium Formation    39   2.3 Lipid Body/Droplet Staining by BODIPY    39   2.4 Live Cell Fluorescence Microscopy    40   2.5 Lipid Extraction    40   2.6 Lipid Profiling and Quantification by HPLC/MS    41   2.7 Analysis of Phosphatidylinositol Phosphates    43   2.8 Inhibitor Design by Bioinformatic Approaches    44   2.8.1 Homologous Modeling of Tps1’s Structure    44   2.8.2 Screening of MLSMR and Docking Results Analysis    44   2.8.3 Lead Optimization    45   2.8.4 Molecular Dynamics Simulation by Gromacs    45   CHAPTER 3: GENERAL LIPIDOMIC ANALYSIS    48   3.1 Lipid Body Staining    48   3.2  Profiling  of  the  Lipidome    54   3.3 Semi-quantitative Analysis of the Lipidome    60   3.3.1  Quantification  of  Phospholipids    61   3.3.2  Quantification  of  Ceramidehexosides    64   3.3.3  Quantification  of  TAGs  and  DAGs    68   3.3.4  Quantification  of  Phosphoinositides    71   3.4  Conclusion    73   CHAPTER 4: BETA OXIDATION AND PATHOGENICITY    74   4.1 Phospholipids and TAGs in Mutants and WT    75       4.2 Conclusion    79   CHAPTER 5: IN SILICO INHIBITOR DESIGN    80   5.1 Structure Modeling by Modeller    83   5.2 Screening of MLSMR for Inhibitors    86   5.3 Lead Optimization    90   5.4 Molecular Dynamics by Gromacs    92   5.5 Conclusion    94   CHAPTER 6: DISCUSSION    95   6.1 Lipid Body Staining    95   6.2 Profiling and Quantification of the Lipidome    96   6.3 Validation of the Mechanism for Turgor Pressure Production    99   6.4 Beta-oxidation: Mitochondria vs Peroxisomes    100   6.5 Lead 25 for Blast Disease Control    102   CONCLUSION    103   REFERENCES    105   APPENDICES    123       SUMMARY Magnaporthe oryzae (M oryzae) is the causal agent of the rice blast disease Triacylglycerides (TAGs) were one of the major sources used to generate turgor pressure as a means for M oryzae to penetrate into host’s leaf Lipids therefore play a very important role in the pathogenesis However, there is up to date no lipidomics study of M oryzae available As Part I of project, our research for the first time analyzed the lipidome of M oryzae and quantified the lipid species across different time points along the pathological cycle The lipidomics study as a platform was further used to analyze two beta oxidation pathway mutants and proposed possible explanation for their nonpathogenicity Our data had also shown interesting information and was suggestive of a possible mechanism for turgor production Previous studies already discovered that trehalose synthase (Tps1) was not only responsible for the production of trehalose and utilization of nitrogen source, but also the regulation of several NADPH-dependent transcriptional corepressors, namely Nmr1, Nmr2, and Nmr3, which can each bind NADP Therefore, as for Part II of the project, the structure of Tps1 was modeled for screening of possible inhibitors in silico against a database of 400k compounds, and molecular dynamics studies were also done for some of the best hits Advice was then given for future inhibitor design in the context of rice blast control To summarize, this project had: 1) profiled the lipidome of M oryzae; 2) identified key lipid species for turgor generation of M oryzae; 3) employed the lipidomics approach as the platform to study some nonpathogenic mutants; 4) proposed a possible mechanism for turgor production; 5) screened chemical databases for possible inhibitors of a key enzyme (Tps1) involved in pathogenesis     List of Tables Page Supplementary Table Lipid species identified and their (accurate) masses Supplementary Top 45 compounds with the lowest-energy Table binding confirmations     124-128 136 List of Figures Page Figure The pathogenesis cycle of M oryzae 13 Figure A proposed model for turgor generation in 33 appressoria Figure A brief illustration of the experimental 38 procedures Figure The staining the lipid droplets of M oryzae 50-53 Figure The elution profiles of different lipid classes 56-59 & tabulation of lipid species identified Figure Quantification of phospholipids 62-64 Figure Analysis on CMHs 66-67 Figure Quantification of TAGs and DAGs 70 Figure Quantification of PI-3,4-P2 and PI-4,5-P2 72 Figure 10 TAG analysis on WT, ΔEch1 and ΔFox2 77 Figure 11 Proposed function of trehalose metabolism 82 Figure 12 The modeled structure of Tps1 84 Figure 13 Structures of Tps1, 1gz5 and 2wtx aligned 85 Figure 14 The validation of Vina’s performance 88 Figure 15 The binding confirmation of the best 89 compounds when docked to Tps1     Figure 16 The structure, binding confirmation and 91 computed LogP of Lead 25 Figure 17 MD study of Lead 25 93 Supplementary TAG:DAG:PLs ratios over different time 129-132 figure points of the pathogenesis of M oryzae Supplementary Total PLs in WT, ΔEch1 and ΔFox2 in figure conidia and appressoria Supplementary Multiple sequence alignment of Tps1 and figure 2wtx Supplementary Multiple sequence alignment of truncated Figure Tps1,2wtx, 1gz5 and 1uqt Supplementary The binding confirmation of the best 45 Figure compounds when docked into Tps1 Supplementary The 2D structures of the best 45 compounds 149-152 Supplementary The 2D structures of the 26 modified 153-154 Figure compounds based on Compound 24789937 133 134 135 137-148 Figure         List of Symbols AA arachidonic acid cAMP cyclic 3', 5' adenosine monophosphate CM complete medium DAG diacylglycerol DHAP dihydroxyactone phosphate DMSO dimethyl sulfoxide ︒C degree Celcius C albicans Candida albicans DNA deoxyribonucleic acid g grams g relative centrifugal force g/L grams per litre GFP green fluorescent protein h hour HPLC high performance liquid chromatography IP(1,4,5)P3 inositol-1,4,5-trisphosphate kb kilobase LB lysogeny broth µg microgram     µL microlitre mg milligram minute mL millilitre mm millimetre mM millimolar M molar MRM multiple reaction monitoring MS mass spectrometry MAPK mitogen-activated protein kinase MM minimal medium NADPH nicotinamide adenine dinucleotide phosphate ng nanogram PCR polymerase chain reaction PI-3-P phosphatidylinositol 3-phosphate PI-3,4-P2 phosphatidylinositol 3,4-bisphosphate PI-3,4,5-P3 phosphatidylinositol 3,4,5-trisphosphate PI-4,5-P2 phosphatidylinositol 4,5-bisphosphate PKA protein kinase A rpm resolutions per minute     S ferax Saprolegniaferax U maydis Ustilago maydis TAG triacylglyeride % percentage % w/v percentage weight by volume % v/v percentage volume by volume 10     140     141     142     143     144     145     146     147     148     149     150     151     152     153     154     ... Heit et al 2009) through the interaction between the C2 domains and PS PS could also interact with proteins containing PH domains, such as 3-phosphoinositide- dependent kinase-1 (Lucas and Cho 2011)... virtual screening, scoring functions still could not identify the crystallographically correct binding mode from other suggested poses during a docking study or accurately predict binding affinities... (0 min-5 min), 0% - 50% (5 – 24 min), 50 % - 50% (24 – 31 min), 50% - 90% (31 – 34 min), 90% - 90% (34 – 51 min), 90%-0% (51 - 54 min), and 0% - 0% (54 – 60 min) The flow rate was 0.15 ml/min