Resource diversity and supply drive colonization resistance.

Area of Science:

• Microbiology
• Ecology
• Computational Biology

Background:

• The human microbiota is crucial for preventing pathogenic microbe colonization, a process termed colonization resistance.
• Understanding the precise mechanisms underlying this resistance, particularly the influence of environmental factors, remains an active area of research.
• Environmental resource availability and diversity are known to shape microbial community structure and function.

Purpose of the Study:

• To investigate how environmental resource diversity and supply impact the relationship between species richness and colonization resistance.
• To explore the effects of environmental factors on overall colonization resistance and cross-feeding dynamics within microbial communities.
• To elucidate the mechanisms by which microbial communities resist pathogen invasion under varying environmental conditions.

Main Methods:

• Utilized a computational consumer-resource model to simulate microbial community dynamics.
• Performed computational invasion simulations to assess colonization resistance.
• Analyzed the influence of varying resource supply and diversity on community structure and resistance.

Main Results:

• A non-monotonic relationship was observed between species richness and colonization resistance, modulated by environmental conditions.
• Colonization resistance generally decreased with increased resource supply and diversity, except under conditions of limited resource supply.
• Cross-feeding interactions were found to reduce colonization resistance by enhancing resource diversity, though this effect diminished with limited resource supply.

Conclusions:

• Environmental resource characteristics significantly shape the effectiveness of microbial communities in resisting pathogen invasion.
• The interplay between species richness, resource availability, and cross-feeding dynamics is critical for understanding colonization resistance.
• This study provides a mechanistic framework for predicting microbial community responses to environmental changes in the context of pathogen resistance.