_Genomes_for_HGT_prediction__Predicting_horizontal_gene_transfer_in_E__coli_and_Salmonella_enterica-sc-5059
_Genomes_for_HGT_prediction__Predicting_horizontal_gene_transfer_in_E__coli_and_Salmonella_enterica
Our ultimate goal is to understand host factors needed for horizontal gene transfer, identify lead targets for conjugation inhibitors and predict horizontal transmission of antimicrobial resistance (AMR) factors. We propose to disclose candidate drug targets controlling the horizontal cell-cell transmission of anti-microbial resistance (AMR) and to predict AMR and its transmission dynamics from bacterial genome composition. We will integrate leading expertise from bacteriology, -omics and mathematical biology in the development of an integrated theoretical-empirical framework of plasmid borne transmission of AMR cassettes. We will employ massive-scale experimental evolution of Escherichia coli and Salmonella enterica gene deletion and overexpression collections, where adaptation requires transfer of AMR carrying conjugative plasmids. In addition, we will select for, identify and functionally dissect de novo mutations that promote horizontal transmission during long-term experimental evolution. Both approaches will disclose cellular functions controlling horizontal AMR transmission that are candidate targets for helper drugs delaying AMR development and spread. Second, we will sequence vast swaths of the genotype space inhabited by clinical bacterial isolates and disclose variants likely to alter transmission properties. DNA sequence data will be complemented by data on transcriptome, proteome and antibiotics resistance, allowing causally cohesive reconstruction of the history of antibiotics resistance. Third, we will integrate the omics data into a mathematical framework capable of predicting AMR transmission in clinical isolates, thereby laying the foundations for a future personalized medicine that tailors antibiotic choice to infection. As part of our larger effort described aboce, we aim to predict horizontal transmission of AMR from bacterial genomes and phenomes. Here, we propose to sequence thousands of clinical isolates to associate individual transmission events to sequence features, and to obtain the genomic data required for these predictions. We have selected 1152 clinically relevant strains of E. coli and S. enterica from Europe's largest collection of clinical isolates (Culture collection of University of Gothenburg, www.ccug.se) for high depth short read re-sequencing on the Illumina page 1 [A3] Please provide text (abstract) which will accompany data for this study in the ENA/EGA. [A4] Does this project use samples? [A5] Please choose which types of sample you will be using [A7] Please state the anticipated date (month/year) samples will be available in-house (if known). If samples are already in-house, type 'in-house' here. Please note that for sequencing, genotyping and microarrays this is essential for scheduling the work. [A8] Please state the anticipated project start date (month/year). [A9] Please state the project duration (months). [A10] Please read WTSI's Data Sharing Policy and Guidelines, then explain your data sharing plans for the project [A11] Are the data sharing plans of this project compliant with the Institute's Guidelines? [A15] Are there any conflicts of interest related to this proposal? [A17] Does the Programme approve this prelim in accordance with the Programme's delegated authority structure for prelims? platform. Our goal is to identify polymorphisms in mappable regions, and quantify gene content in the more fluid plasmid complement.
We propose to disclose candidate drug targets controlling the horizontal cell-cell transmission of anti-microbial resistance (AMR) and to predict AMR and its transmission dynamics from bacterial genome composition. We will integrate leading expertise from bacteriology, -omics and mathematical biology in the development of an integrated theoretical-empirical framework of plasmid borne transmission of AMR cassettes. We will employ massive-scale experimental evolution of Escherichia coli and Salmonella enterica gene deletion and overexpression collections, where adaptation requires transfer of AMR carrying conjugative plasmids. In addition, we will select for, identify and functionally dissect de novo mutations that promote horizontal transmission during long-term experimental evolution. Both approaches will disclose cellular functions controlling horizontal AMR transmission that are candidate targets for helper drugs delaying AMR development and spread. Second, we will sequence vast swaths of the genotype space inhabited by clinical bacterial isolates and disclose variants likely to alter transmission properties. DNA sequence data will be complemented by data on transcriptome, proteome and antibiotics resistance, allowing causally cohesive reconstruction of the history of antibiotics resistance. Third, we will integrate the omics data into a mathematical framework capable of predicting AMR transmission in clinical isolates, thereby laying the foundations for a future personalized medicine that tailors antibiotic choice to infection.