Performing Department
(N/A)
Non Technical Summary
This project supports the mission of theAgricultural Experiment Station by addressing the Hatch Act area(s) of: soil and water conservation and use, andplant and animal production, protection, and health. Currently, the plant disease known as bacterial wilt is a global issue with a high financial impact on farmers, and there are limited means of controlling the causal agent of this disease, the Ralstonia solanacearum species complex. These pathogens can survive in their environment for years in favorable conditions, and they are able to spread from farm-to-farm by contaminating and disseminating through irrigation water. We have a limited understanding of how Ralstonia wilt pathogens survive in their environment at a molecular level, and understanding how these pathogens survive will help use develop new management strategies for them. This research project is investigating the molecular basis for how Ralstonia wilt pathogens survive in water using a high-throughput genetic tool that allows us to screen thousands of genes at once. Specifically, with a single experiment, we have generated data that associates a score for nearly three-quarters of the genes within the genome of a Ralstonia wilt pathogen, and the score indicates the gene's contribution to the pathogen's ability to survive in water. This project aims to summarize the large data set in a meaningful way, communicating to translational scientists what genes are important for all Ralstonia wilt pathogens to survive in water. This ensures that management strategies can be developed in a manner that targets the full, global diversity of Ralstonia wilt pathogens, as opposed to the development of a management strategy that has a narrow range of effectiveness with respect to all Ralstonia wilt pathogens. The ultimate goal of this work is to further our understanding of how Ralstonia wilt pathogens of spread across the globe, persisted in the environments they have spread to, and how we can manage these wilt pathogens using management strategies that target the pathogens, but not the native microbiota that pathogens exist within.
Animal Health Component
0%
Research Effort Categories
Basic
100%
Applied
(N/A)
Developmental
(N/A)
Goals / Objectives
Project Plan Goals:Goal 1.1: Determine the core metabolism necessary for the Ralstonia solanacearum species complex to survive in pure water to broaden our understanding of how these pathogens can transmit via contaminated irrigation water.Objective 1: Categorize all water survival factors (genes that support or hinder water survival as determined by our forward genetic screen) based on gene function using the Gene Ontology Resource.Objective 2: Determine which of these water survival factors are part of the core genome of the RSSC using OrthoMCL pangenomic analysis & BLASTP.Objective 3: Associate the water survival factors with their metabolic pathways using MetaCyc to create a core water survival metabolic network.Goal 1.2: Determine the up- and down-regulated genes controlled by core water survival transcription factors in the RSSC during survival in pure water to refine our model of these pathogens can persist in contaminated water systems.Objective 1: Create targeted knockout mutants in the Ralstonia pseudosolanacearum GMI1000 strain, targeting the genes RS_RS10425 and phoU.Objective 2: Set up water microcosms with wild-type and targeted knockout strains & sample them out to 30 days for outgrowth and RNA sequencing.Objective 3: Identify differentially expressed genes within the RNA sequencing data across strains and timepoints.Goal 2.1: Determine the presence or absence of water survival factors in the Burkholderiaceae to understand how new and emerging Burkholderiaceae pathogens may survive and spread in their environment.Objective 1: Create a gene list from our genetic screen (RB-TnSeq) data that will include all genes that supported water survival in one or more of the three species evaluated.Objective 2: Use BlastP to determine the presence or absence of the genes in the gene list across the Burkholderiaceae.Goal 2.2: Infer the evolutionary history of water survival factors using synteny analysis to determine if water survival factors have been vertically inherited or have potential to be horizontally transferred within a community.Objective 1: Compile all of the GenBank files that contain the sequence and gene annotation data that will be imported into our synteny analysis tool, clinker, and filter out all genes with incomplete/broken sequences due to insufficient assemblage of the genome.Objective 2: Run the synteny analysis for all genes that passed our quality control metrics and analyze the results.Goal 2.3: Characterize the selection pressure on water survival factors in the Burkholderiaceae to determine what genes are under stabilizing selection and determine what genes would be ideal targets for the development of novel control strategies of pathogens. Objective 1: Create gene alignment files for all of the identified and conserved water survival factors.Objective 2: Run the Tajima's D test in the R statistical computing software and determine the synonymous & non-synonymous mutation ratios for each gene.Career/professional development goals:Goal 1: Develop an inclusive pedagogy and teaching philosophy to help me serve a diverse community of students.Objective 1: Complete the Future Undergraduate Science Educators program at UC Davis.Objective 2: Continually participate in workshops provided by the Center for Educational Effectiveness at UC Davis.Goal 2: Broaden my mentorship toolset to train future scientists.Objective 1: Continue to mentor students through institutions such as the Society for the Advancement of Chicanos/Hispanics and Native Americans in Science (SACNAS).Objective 2: Co-mentor students in collaboration with Professor Lowe-Power and train them to be independent scientists in our lab.Goal 3: Refine my technical and scientific skillset to ensure my trainees will provided with knowledge on cutting-edge techniques, as well as ensure they are using the best-practices with already established techniques.Objective 1: Attend the Joint Genome Institute Microbial Genomics & Metagenomics workshop to develop my computational skills.Objective 2: Present my work at least annually to my department and at least annually at research conferences to seek feedback on how I can improve my methods and techniques.Objective 3: Meet regularly with my mentors and discuss any technical problems I have been having in my research.Goal 4: Establish a network that consists of professors from Primarily Undergraduate Institutions (PUIs)to ensure that I can maximize my preparation for a professorship at a PUI.Objective 1: Meet regularly with my undergraduate research advisor, Professor Elinne Becket, and seek her advice on how to plan my professional development as a graduate student and post-doctoral scholar to ensure I am preparing for a professorship at a PUI.Objective 2: Obtain institutional support from the California State University (CSU) system (ideally in the form of becoming a CSU Chancellor's Doctoral Incentive Program Fellow) to further prepare myself for a professorship at a PUI.
Project Methods
Randomly barcoded transposon insert sequencing (RB-TnSeq) data analysis will occur by building on the already established methods developed by the scientists who developed the technique in the Lawrence Berkeley National Laboratory. Further development of statistical tests to determine what scores in our genetic screen are statistically significant will be done in collaboration with Nathalie Aoun, a post-doctoral researcher in the Lowe-Power lab. Prof. Danial Runcie, a professor in the Plant Sciences Department at UC Davis who develops statistical tools for large datasets, will also provide guidance on how to analyze our RB-TnSeq data. We expect that this analysis will provide a reliable list of genes that support or hinder water survival of Ralstonia pathogens in a statistically significant manner.Functional categorization of the genes in the gene list created from our genetic screen experiment will be done by hand using the Gene Ontology Resource. Genes will be searched and categorized, and these functional categories will be associated with the genes in an excel spreadsheet.All work to determine the presence and absence of genes will be done using the BlastP app within the KBase research platform provided by the Department of Energy. Spreadsheets can be created based on the BlastP results. The presence and absence of the genes searched using BlastP will be visualized in an already developed tool known as iTol. The spreadsheet generated from the BlastP searches can be imported into iTol and cross-referenced with a phylogenetic tree that was created for the genomes being used in the BlastP search.Visualization of metabolic pathways will be done by hand using MetaCyc. Genes will be looked up based on gene lists created in the analysis of the RB-TnSeq data. Metabolic pathways associated with genes that support water survival will be listed in an excel spreadsheet, and a visual network highlighting the metabolism that is necessary for water survival will be created using Affinity Designer.Targeted mutagenesis of regulator mutants will be done using Gibson Assembly to create a vector for gene deletion, electroporation to get the vector into Ralstonia cells, and homologous recombination for the vector to be integrated into the genome and excise out of the genome in a manner that creates a markerless deletion of our genes of interest. Selective media will be used throughout the cloning process to help ensure efficient selection of potential mutants that were successfully created. Putative mutants will be screened using polymerase-chain-reactions and gel electrophoresis. Putative mutants with positive screen results will then be sequenced using next-generation-sequencing to confirm we have successfully deleted our gene of interest from the genome.Creating water microcosms for transcriptome sequencing experiments will be set up using standard microbiology culturing practices. RNA extraction will be done using the standard methods for a Qiagen RNA extraction kit. Sequencing will be performed by a paid third partly, likely SeqCoast. Transcriptome analysis will be done in KBase using the already tested and established methods for transcriptome analysis available within the KBase system. Differentially expressed genes that are deemed to be important for water survival (differentially expressed genes between our wild-type and regulator mutants) will be listed in excel, and the gene regulation network will visualized using Affinity Designer.Synteny analysis will be done using the published tool known as Clinker. Sequence and gene annotation data will be downloaded from publicly available genomes from the National Center for Biotechnology Information (NCBI) and imported into Clinker.Analysis of synonymous and non-synonymous mutations will be done in R Studio using the tajimasD package, and the sequence data will be downloaded from NCBI.All this work will be done as part of the dissertation research for the PD, Matthew Cope-Arguello. Evaluation of the progress for each of these methods will be assessed by Matthew's dissertation committee on at least an annual basis by the dissertation committee, in addition to regular meetings that will occur between Matthew and his research advisor, Prof. Lowe-Power. Milestones to be evaluated will include: the creation of the gene lists for water survival factors based on the RB-TnSeq data, categorization of the genes based on function, visualization of the BlastP results for each water survival factor in iTol, the creation of a metabolic network based on the MetaCyc analysis results, the creation of transcriptional regulator mutants, the completion of the transcriptome sequencing for each regulator mutant in the water microcosm experiments, the analysis and visualization of the sequenced transcriptomes, the creation of a list (in excel) of conserved water survival factors across the Burkholderiaceae based on synteny analysis and selective pressure analysis (Tajima's D test).