Periodic selection and hitchhiking in a bacterial population

Area of Science:

• Microbial population genetics
• Evolutionary dynamics
• Mathematical biology

Background:

• Bacterial populations in chemostats exhibit complex dynamics due to continuous adaptation.
• Previous models often simplified the stochastic nature of variant appearance and selection.
• Understanding these dynamics is crucial for predicting evolutionary trajectories.

Purpose of the Study:

• To simulate periodic selection curves in bacterial populations with enhanced stochasticity.
• To model the impact of adaptive sweeps on neutral and weakly selected markers.
• To calculate substitution rates and probabilities of mutation presence/absence.

Main Methods:

• Developed deterministic equations incorporating stochastic initial conditions for new variants.
• Simulated the accumulation of neutral markers under balanced growth in a chemostat.
• Accounted for uncertainties in variant appearance time, survival, and early growth.

Main Results:

• The model accurately simulates jagged accumulation curves driven by periodic selection.
• Calculated substitution rates via hitchhiking, where neutral mutations are linked to adaptive ones.
• Determined the expected ratio of presence/absence probabilities for weakly selected or counterselected mutations.

Conclusions:

• Stochasticity significantly influences bacterial population dynamics and evolutionary outcomes.
• The model provides a framework for understanding hitchhiking and its effect on genetic drift.
• Interpreting the average time between adaptive shifts as effective population size offers new insights.