Population genomics of antibiotic resistance evolution

JA 2342/2-1

Owing to large population sizes, haploid genomes and short generation times, bacterial evolution can be extremely fast. This is particularly clear from the incredibly rapid emergence and spread of antibiotic resistance, which can render seemingly standard clinical interventions ineffective within as little as two years. A renewed interest in antibiotic resistance has recently led to a number of in vitro evolution experiments aimed at investigating how different antibiotics, dosages and ways of deployment affect the rates and outcome of resistance evolution. My own work surprisingly showed that antibiotic resistance can evolve within 36 hours. However, resistance evolution in environmental and clinical bacterial populations involves not only adaptation of clonal populations during antibiotic exposure, but is also influenced by biological factors such as genetic diversity, migration and bottleneck population sizes, e.g. during between-patient transmission events, in environmental reservoirs or for vector-borne infections. Nevertheless, the role of these factors in fast resistance evolution has not been systematically studied in detail under controlled conditions. The proposed project will therefore perform controlled serial passage experiments to investigate how migration, genetic diversity and bottleneck sizes influence the rates and trajectories of resistance evolution. Because adaptive evolution is a dynamic process playing within bacterial populations, I will particularly focus on the population genomics of evolving populations, i.e., genotypes in evolving bacterial populations will be monitored at different time points during the experiment. The latter aspect is not commonly addressed during previous in vitro experiments, which focused on resistance mechanisms that are fixed in the population at the end of experiments. The full-factorial experimental design will provide systematic data that can be generalized using mathematical models. The results will provide important insights into realistic dynamics of resistance evolution than is known from application-oriented experiments done until now, and carries high potential to identify novel mechanisms that play during adaptive evolution of rapid bacterial evolution.

Publications
  • Ferro K, Peuß R, Yang W, Rosenstiel P, Schulenburg H, Kurtz J. (2019) Experimental evolution of immunological specificity. Proceedings of the National Academy of Sciences 116. DOI: 10.1073/pnas.1904828116

  • Gunther Jansen, Niels Mahrt, Leif Tueffers, Camilo Barbosa, Malte Harjes, Gernot Adolph, Anette Friedrichs, Annegret Krenz-Weinreich, Philip Rosenstiel, Hinrich Schulenburg (2016) Association between clinical antibiotic resistance and susceptibility of Pseudomonas in the cystic fibrosis lung. Evolution, Medicine, and Public Health Volume 2016, Issue 1, January 2016, Pages 182–194. DOI: 10.1093/emph/eow016