Unknown

Dataset Information

0

Resource uptake and the evolution of moderately efficient enzymes.


ABSTRACT: Enzymes speed up reactions that would otherwise be too slow to sustain the metabolism of self-replicators. Yet, most enzymes seem only moderately efficient, exhibiting kinetic parameters orders of magnitude lower than their expected physically achievable maxima and spanning over surprisingly large ranges of values. Here, we question how these parameters evolve using a mechanistic model where enzyme efficiency is a key component of individual competition for resources. We show that kinetic parameters are under strong directional selection only up to a point, above which enzymes appear to evolve under near-neutrality, thereby confirming the qualitative observation of other modelling approaches. While the existence of a large fitness plateau could potentially explain the extensive variation in enzyme features reported, we show using a population genetics model that such a widespread distribution is an unlikely outcome of evolution on a common landscape, as mutation-selection-drift balance occupy a narrow area even when very moderate biases towards lower efficiency are considered. Instead, differences in the evolutionary context encountered by each enzyme should be involved, such that each evolves on an individual, unique landscape. Our results point to drift and effective population size playing an important role, along with the kinetics of nutrient transporters, the tolerance to high concentrations of intermediate metabolites, and the reversibility of reactions. Enzyme concentration also shapes selection on kinetic parameters, but we show that the joint evolution of concentration and efficiency does not yield extensive variance in evolutionary outcomes when documented costs to protein expression are applied.

SUBMITTER: Labourel F 

PROVIDER: S-EPMC8382906 | biostudies-literature |

REPOSITORIES: biostudies-literature

Similar Datasets

| S-EPMC8745736 | biostudies-literature
2018-11-08 | PXD010847 | Pride
2020-03-04 | E-MTAB-6169 | biostudies-arrayexpress
| S-EPMC3943892 | biostudies-literature
2022-12-31 | GSE198560 | GEO
| S-EPMC4453541 | biostudies-literature