Description
Project 1: Modeling antibiotic resistance evolution.
- Trainers:
Fernanda Pinheiro, Group Leader in the Computational Biology Research Centre, Human Technopole, Milan;
Leon Seeger, PhD student enrolled in the lab of Fernanda Pinheiro and Michael Lässig - University of Cologne. - Description:
Bacterial growth under antibiotic challenge results from a complex interplay between antibiotic chemistry, nutrient conditions, bacterial physiology, and evolution. While antibiotics disrupt essential cellular processes of the wild-type susceptible background, they are less harmful to resistant bacteria. Resistant bacteria have multiple ways to counteract antibiotic action, including upregulation of its targets, alteration of membrane permeability, overexpression of efflux pumps, and enzymatic modification of antibiotics. How do different resistance mechanisms shape dosage-dependent bacterial growth? And what determines prevalent mechanisms of resistance evolution as a function of environmental conditions? In this course, we will build fitness models to characterize the dosage-dependent growth of antibiotic-resistant mutants. We will integrate the biophysics of drug action and antibiotic resistance mechanisms into coarse-grained models of cell metabolism to establish a mechanistic description of bacterial growth under challenge. We will then fit these models to existing data of dosage-response curves and map the conditions for the onset of different resistance mechanisms from the inferred biophysical parameters. Can we predict mechanisms of resistance evolution as a function of conditions? The lectures will expose the participants to theoretical developments (systems biology models of bacterial growth, metabolic fitness landscapes, evolutionary models), and numerical work will be done in MatLab or Python.