Pairwise interactions and serial bottlenecks help explain species composition in a multispecies microbial community

Area of Science:

• Ecology
• Microbial Ecology
• Community Ecology

Background:

• Microbial community assembly is complex and challenging to characterize.
• Previous studies often used synthetic communities or artificial environments, limiting applicability to natural systems.
• Existing models of pairwise interactions may not account for nonequilibrium dynamics found in natural environments like gut microbiomes.

Purpose of the Study:

• To investigate if pairwise interactions can predict multispecies co-occurrence patterns in natural microbial communities.
• To assess the predictive power of pairwise interaction models for microbes from sourdough starters.
• To determine if incorporating nonequilibrium demography enhances predictive accuracy.

Main Methods:

• Inferred interaction parameters from pairwise growth trajectories of sourdough microbes.
• Developed and applied a model based on pairwise interactions to predict community structure.
• Incorporated nonequilibrium demographic factors into the interaction model for improved accuracy.

Main Results:

• Pairwise interaction parameters suggested widespread coexistence among microbes in the species pool.
• The model accurately predicted the presence and relative abundance of species in communities up to nine species.
• Inclusion of nonequilibrium demography significantly improved the predictive accuracy of the pairwise interaction model.

Conclusions:

• Pairwise interactions are predictive of microbial community structure, even in moderately complex systems.
• Sourdough starters serve as a relevant model system for studying microbial community assembly.
• Accounting for nonequilibrium demography is crucial for accurate ecological predictions in microbial communities.