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Comparing bacterial gene networks based on high-throughput phenomics

Pfalz, Birgit

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Abstract

Novel genes are being discovered at constantly increasing rates by sequencing bacterial genomes and bacterial communities. Gene function discovery has been lagging behind, but recent technological advances allow us to apply reverse genetics approaches on a genome wide scale. In this study I profile the growth of more than 3800 gene deletion mutants of the pathogen Salmonella Typhimurium in more than 550 perturbations including physical stresses, nutrient limitation, antibiotics and host defense molecules. Analysis of gene-drug interaction scores reveal significant phenotypes for 75% of the tested mutants. The data set provides a number of novel biological inferences, linking genes of unknown function to known pathways and providing insights into drug mode-of-action, uptake and efflux. Using similar high-throughput data available for E. coli., I provide the first comprehensive cross-species comparison of genetic networks in bacteria. Correlation analysis and detection of functional modules reveals broad conservation of cellular pathways and drug responses between Salmonella and E. coli. However, I also find intriguing cases of network rewiring and investigate how species-specific genes connect to conserved modules. Lastly, I investigate the highly different resistance levels of Salmonella and E. coli to the type 2 diabetes drug metformin and determine the Salmonella-specific efflux pump SmvA as the major component conferring drug resistance. Furthermore, I identify more transporters capable of exporting metformin and examine their wiring into the cellular networks of E. coli and Salmonella. This analysis reveals that many enterobacteria may have the potential to develop resistance against metformin leading to important implications for diabetic patients.

Document type: Dissertation
Supervisor: Steinmetz, Prof. Dr. Lars
Date of thesis defense: 7 June 2016
Date Deposited: 29 May 2017 09:06
Date: 2017
Faculties / Institutes: The Faculty of Bio Sciences > Dean's Office of the Faculty of Bio Sciences
DDC-classification: 500 Natural sciences and mathematics
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