Bottlenecks, population dynamics, and antibiotic resistance evolution
Evolution, Anthropology
Microbial Ecology and Applied Microbiology
Statistical Physics, Nonlinear Dynamics, Complex Systems, Soft and Fluid Matter, Biological Physics
Final Report Abstract
Antibiotic resistance is a growing global health threat, driving experimental and theoretical studies to identify factors that prevent or slow its emergence. Studies often compare the efficacy of treatment strategies but rarely consider population bottlenecks—events that drastically reduce population size. In pathogen infections, bottlenecks occur due to pathogen transmission, immune responses, or antibiotic treatment. Despite their known impact on evolution, their role in resistance evolution, especially alongside other infection-related factors, remains largely unexplored. In our study, we used mathematical models informed by data to explore the effect of population bottlenecks on antibiotic resistance evolution. As a first step, we focused on the interplay between antibiotic pressure and bottleneck size. We built a mathematical model based upon experimental results from Mahrt et al. (2021), exploring trait adaptation and the effect of demographic fluctuations. Our results show that different bottleneck sizes can favour the selection of different resistance traits—for example, small bottlenecks promote the adaptation of the maximum growth rate, while large bottlenecks promote the adaptation of lag time and carrying capacity. These findings provide insight into how different treatment conditions can steer resistance evolution through distinct adaptive pathways, potentially informing the design of more effective antibiotic therapies. As a second step, we focused on the interplay between migration, bottlenecks, and competition on evolutionary dynamics. This study was motivated by recent experimental work showing that mixing of within-species strains and bacterial interactions can influence resistance evolution in polymicrobial infections (Batra et al., submitted to Nature Ecology and Evolution). Using a mathematical approach, we developed a meta-population model to explore how migration between demes (isolated subpopulations) affects adaptive outcomes. We compared two extreme regimes: full isolation, where demes evolve independently, and full migration, where demes are well-mixed. Our study identifies the key factors that amplify differences between these regimes, highlighting the relevance of spatial structure and stochastic effects in resistance evolution. These findings have broader implications, extending beyond antibiotic resistance to various ecological contexts.
Link to the final report
https://doi.org/10.34657/18613
Publications
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Resistance variation and bacterial interactions shape the adaptation of a genetically diverse bacterial population to antimicrobial treatment. openRxiv.
Batra, Aditi; Tueffers, Leif; Haas, Kira; Loeblein, Tabea; Botelho, João; Habig, Michael; Schuetz, Daniel; Sakalyte, Gabija; Buchholz, Florian; Berríos-Caro, Ernesto; Uecker, Hildegard; Unterweger, Daniel & Schulenburg, Hinrich
