eprintid: 22920
rev_number: 15
eprint_status: archive
userid: 3099
dir: disk0/00/02/29/20
datestamp: 2017-05-29 09:06:08
lastmod: 2018-05-07 09:36:04
status_changed: 2017-05-29 09:06:08
type: doctoralThesis
metadata_visibility: show
creators_name: Pfalz, Birgit
title: Comparing bacterial gene networks based on high-throughput phenomics
subjects: 500
divisions: 140001
adv_faculty: af-14
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.
date: 2017
id_scheme: DOI
id_number: 10.11588/heidok.00022920
ppn_swb: 1655343297
own_urn: urn:nbn:de:bsz:16-heidok-229203
date_accepted: 2016-06-07
advisor: HASH(0x564e1c4b9fb8)
language: eng
bibsort: PFALZBIRGICOMPARINGB2017
full_text_status: public
citation:   Pfalz, Birgit  (2017) Comparing bacterial gene networks based on high-throughput phenomics.  [Dissertation]     
document_url: https://archiv.ub.uni-heidelberg.de/volltextserver/22920/1/Dissertation_BirgitPfalz.pdf