Thermal Adaptation in Viruses and Bacteria

TL;DR

This paper develops a multiscale population genetics model linking protein stability to microbial fitness, explaining diverse thermal adaptation phenomena in bacteria and viruses through a combination of analytical and numerical methods.

Contribution

It extends existing models by directly relating replication rate to protein copy number and stability, providing a quantitative framework for thermal adaptation in microbes.

Findings

Broad protein stability distribution influences thermal response.

Model explains asymmetry in thermal response curves.

High accuracy in predicting bacterial thermal responses with minimal parameters.

Abstract

A previously established multiscale population genetics model states that fitness can be inferred from the physical properties of proteins under the physiological assumption that a loss of stability by any protein confers the lethal phenotype to an organism. Here we develop this model further by positing that replication rate (fitness) of a bacterial or viral strain directly depends on the copy number of folded proteins which determine its replication rate. Using this model, and both numerical and analytical approaches, we studied the adaptation process of bacteria and viruses at varied environmental temperatures. We found that a broad distribution of protein stabilities observed in the model and in experiment is the key determinant of thermal response for viruses and bacteria. Our results explain most of the earlier experimental observations: striking asymmetry of thermal response curves, the absence of evolutionary trade-off which was expected but not found in experiments, correlation between denaturation temperature for several protein families and the Optimal Growth Temperature (OGT) of their host organisms, and proximity of bacterial or viral OGTs to their evolutionary temperatures. Our theory quantitatively and with high accuracy described thermal response curves for 35 bacterial species using, for each species, only two adjustable parameters, the number of replication rate determining genes and energy barrier for metabolic reactions.