Species matter for predicting the functioning of evolving microbial communities - An eco-evolutionary model

Area of Science:

• Microbial Ecology
• Evolutionary Biology
• Systems Biology

Background:

• Microbial communities provide essential ecosystem services, but their dynamics and functioning are difficult to predict.
• Current approaches often simplify functioning prediction based solely on the enzyme repertoire.
• The role of ecological and evolutionary dynamics, particularly enzyme packaging among species, remains underexplored.

Purpose of the Study:

• To investigate whether community functioning is predictable from enzyme sets alone or if species' ecological and evolutionary dynamics are crucial.
• To extend classical chemostat models to explore multi-species evolution in resource utilization.
• To understand how enzyme packaging constrains and influences community functioning and evolution.

Main Methods:

• Extended classical chemostat models to simulate multi-species bacterial growth and evolution.
• Modeled ecological interactions emerging from evolving patterns of resource use and enzyme allocation.
• Quantified community functioning based on metabolite concentrations and bacterial density.

Main Results:

• Community functioning exhibits significant redundancy but is constrained by enzyme packaging among species.
• Evolutionary dynamics can either enhance or diminish community functioning compared to purely ecological models.
• The shape of trade-offs in resource use critically influences the impact of evolution on functioning.

Conclusions:

• Species packaging of enzymes is a vital factor, not just enzyme presence, for predicting microbial community functioning.
• Evolutionary processes can lead to unpredictable outcomes for ecosystem services, highlighting the need for integrated ecological-evolutionary models.
• This theoretical framework aids in interpreting empirical data on microbial evolution and ecosystem functioning.