Integrative Genomics Approach to Identify Genes Important for H2 Production By
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Integrative Genomics Approach to Identify Genes Important for H2 Production by Rhodopseudomonas Somsak Phattarasukol A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy University of Washington 2014 Reading Committee: Caroline S. Harwood, Chair Roger E. Bumgarner John E. Mittler Program Authorized to Offer Degree: Microbiology © Copyright 2014 Somsak Phattarasukol University of Washington Abstract Integrative Genomics Approach to Identify Genes Important for H2 Production by Rhodopseudomonas Somsak Phattarasukol Chair of the Supervisory Committee: Professor Caroline S. Harwood Microbiology Hydrogen gas (H2) is a clean-burning fuel and energy source that can be produced biologically by bacteria. Photosynthetic bacteria are especially promising as biocatalysts for H2 production because energy from light can be used to drive this thermodynamically difficult process. The photosynthetic bacterium Rhodopseudomonas draws on the functioning of three major metabolic modules to produce H2. These are photophosphorylation to generate ATP from light, carbon compound catabolism to generate electrons, and nitrogenase, an enzyme that combines electrons from carbon compounds with protons from water to generate H2 by an ATP-intensive process. Each of metabolic modules is complicated and when considered together it is clear that H2 production requires the integration of dozens of metabolic reactions. For example, acquisition of metals needed for synthesis of a functional nitrogenase is not easily identified as being associated with H2 production. To identify a full set of genes from Rhodopseudomonas involved in H2 production, I compared the genomes and transcriptomes of 16 closely related strains of Rhodopseudomonas. In addition, I constructed co-expression networks of a set of 7 other less closely related Rhodopseudomonas strains and correlated gene expression modules with nitrogenase activities and H2 production yields of the strains. I identified a set of 54 genes that were highly expressed in all 16 closely related strains grown under the H2-producing condition in high light. These are candidates for genes that contribute to H2 production. The co- expression analysis suggested that expression of nitrogenase genes is an essential but not a limiting factor for H2 production. In contrast, the expression of light-harvesting genes appeared to be important for H2 production under high and low light. In the process of generating data for this thesis, I developed an easy-to-use integrated tool for processing RNA-seq data, called Xpression. This tool is well suited to analyze gene expression data generated from bacteria and Achaea and should be useful to research laboratories that do not routinely carry out gene expression studies. TABLE OF CONTENTS CHAPTER 1. Introduction ________________________________________ 1! Hydrogen Gas - a Clean Fuel for the Future _______________________________ 2! Biological Production of H2 __________________________________________ 2! Rhodopseudomonas as a Platform for H2 Production ________________________ 3! Molecular Mechanism of H2 Production _________________________________ 3! Nitrogenase Synthesis and Regulation __________________________________ 4! Other Factors that Influence H2 Production _______________________________ 5! Challenges _____________________________________________________ 7! REFERENCES ____________________________________________________ 11! CHAPTER 2. Xpression – an Integrated Tool for Prokaryotic RNA-seq Data Processing __________________________________________________ 14! INTRODUCTION __________________________________________________15! MATERIALS AND METHODS _________________________________________16! Bacterial Strains and Growth Conditions _________________________________16! Electrophoretic Mobility Gel Shift Assays ________________________________17! Strand-specific cDNA Library Construction for RNA-seq ______________________17! Xpression Installation _____________________________________________17! RNA-seq Data Processing ___________________________________________18! Identifying Differentially Expressed Genes _______________________________19! RESULTS _______________________________________________________19! Sequence Read Extraction, Filtering, and Trimming ________________________ 20! Sequence Read Alignment and Classification _____________________________ 20! Sequence Read Quantification, Normalization and Visualization _________________21! The CouR Regulon_______________________________________________ 22! DISCUSSION ____________________________________________________ 23! REFERENCES ___________________________________________________ 26! CHAPTER 3. Comparative Genomic and Transcriptomic Analysis of Rhodopseudomonas Strains Provides Insights into Determinants of Microbial Hydrogen Gas Production_______________________________________ 36! INTRODUCTION __________________________________________________37! MATERIAL AND METHODS _________________________________________ 39! Bacterial Strains, Growth Conditions and Phenotypes _______________________ 39! Preparation of DNA and RNA for Sequencing_____________________________ 40! De novo Genome Assembly _________________________________________ 40! Genome Annotation______________________________________________ 42! Orthologous Gene and Gene Expression Analysis __________________________ 43! RESULTS ______________________________________________________ 44! General Genome Features of 14 Rhodopseudomonas Strains __________________ 44! Genetic and Transcriptomic Variations among Rhodopseudomonas Strains ________ 44! Genes Similarly Regulated in All Rhodopseudomonas Strains__________________ 47! DISCUSSION ____________________________________________________ 48! REFERENCES ____________________________________________________51! CHAPTER 4. Construction of Co-expression Networks of Diverse Strains of Rhodopseudomonas to Identify Genes Associated with Hydrogen Production__ 97! INTRODUCTION _________________________________________________ 98! MATERIALS AND METHODS ________________________________________100! Bacterial Strains, Growth Conditions and Phenotypes _______________________100! i Orthologous Gene and Gene Expression Analysis __________________________ 101! RNA-seq Data __________________________________________________102! Adapting WGCNA for Constructing Networks from Bacterial RNA-seq Data ________103! RESULTS ______________________________________________________ 107! Co-expression Networks ___________________________________________ 107! Modules Associated with Phenotypic Changes ____________________________108! DISCUSSION ____________________________________________________ 111! REFERENCES ___________________________________________________ 115! APPENDIX ________________________________________________ 202! ii TABLE OF FIGURES Figure 2.1. A depiction of the Xpression graphical interface. ______________________ 28! Figure 2.2. Tasks carried out the internal workflow of Xpression. ___________________ 29! Figure 2.3. A depiction of the types of DNA sequence reads that are quantified by Xpression. 30! Figure 2.4 Visualization of RNA-seq data using output from Xpression. _______________31! Figure 2.5. Map of genes in the CouR regulon and gel-shift assay. __________________ 32! Figure 3.1. H2 production by Rhodopseudomonas requires the integration of dozens of metabolic reactions. ______________________________________________ 53! Figure 3.2. Graph depicted numbers of orthologous groups shared by different combination of Rhodopseudomonas strains. ________________________________________ 54! Figure 3.3. Graph depicted numbers of orthologous groups not shared by all but found in different combination of Rhodopseudomonas strains. _______________________ 55! Figure 3.4. Expression ratios of the nifHK genes vary among closely related strains of Rhodopseudomonas. _____________________________________________ 56! Figure 3.5. Expression ratios of the nifH gene does not reflect H2 yield.________________57! Figure 3.6. Number of genes that were up-regulated or down-regulated in all Rhodopseudomonas strains. ________________________________________ 58! Figure 4.1. A co-expression network is an undirected graph, where nodes correspond to genes and edges represent the strength of co-expression relationships between genes. _____ 118! Figure 4.2. H2 production by Rhodopseudomonas requires the integration of dozens of metabolic reactions. ______________________________________________ 119! Figure 4.3. Phylogenetic relationships of seven Rhodopseudomonas strains based on 16S-rRNA sequences. ____________________________________________________120! Figure 4.4. Dendrogram of 750 orthologous genes that were up-regulated in the H2-producing, high-light (NF-high) condition compared to the non-H2-producing, high light (PM-high) condition._____________________________________________________ 121! Figure 4.5. Dendrogram of 732 orthologous genes that were down-regulated in the H2- producing, high-light (NF-high) condition compared to the non-H2-producing (PM-high) condition._____________________________________________________ 122! Figure 4.6. Dendrogram of 794 orthologous genes that were up-regulated in the H2-producing, low-light (NF-low) condition compared to the H2-producing, high-light (NF-high) condition._____________________________________________________ 123! Figure 4.7. Dendrogram of 700 orthologous genes that were down-regulated in the H2- producing, low-light (NF-low) condition compared to the