Sauer Group, Microbial metabolomics and modeling

Background

The response of bacteria to antibiotics has been extensively studied in the past decades, but only recently an important and yet unexplored role of metabolism has been discovered. Systems-level approaches have revealed that metabolic adaptation can play a key role in how successfully bacteria can cope with antibiotics. Even though, the underlying mechanisms are largely unknown and poor attention has been given to the experimental measurements of metabolic changes induced by an antibacterial agent.

Your Project

The goal of this project is to quantitatively analyze the metabolome patterns of evolved E.coli strains under the selective pressure of 3 different antibiotics (i.e. Norfloxacin, Ampicillin and Chloramphenicol) in two different media composition (i.e. glucose and acetate minimal media). To this end, the candidate will analyze data which were acquired from a novel high-throughput mass spectrometry method for about 200 evolved mutants, working on the development of computational approaches. The aim is to infer potential dependencies between general vs specific antimicrobial resistance mechanisms and levels of intracellular metabolites. Such predictions might reveal new ways of interfering with metabolic adaptation of evolved strains either increasing the fitness cost of beneficial mutations or reducing their resistance to the drug.

The candidate will familiarize with mass spectrometry methods, performing 2-3 weeks of lab work, and mostly learn concepts in the statistical analysis of high-throughput datasets. Programming experience in Matlab is required.

Contact person: Mattia Zampieri