Unpacking fitness differences between two invaders in a multispecies context.

Area of Science:

• Ecology
• Microbiology
• Evolutionary Biology

Background:

• Ecosystems face constant invasion by new species or strains.
• Assessing newcomer success relies on understanding relative fitness.
• Classical methods often use exponential models for fitness differences.

Purpose of the Study:

• To develop an explicit framework for quantifying fitness differences between co-invading strains.
• To apply this framework to the invasion of gut microbiota by antibiotic-resistant Escherichia coli.
• To demonstrate the context-dependent nature of fitness and selection coefficients.

Main Methods:

• Utilizing the replicator equation to model co-invasion dynamics.
• Assuming constant resident species frequencies during initial invasion phases.
• Applying the framework to previously published data on Escherichia coli gut microbiota invasion.

Main Results:

• Developed a novel method to determine invasion fitness differentials between co-invading strains.
• Showcased how host environment species frequencies explicitly modulate selection coefficients.
• Highlighted the context-dependent nature of microbial fitness.

Conclusions:

• The developed mechanistic framework provides a more explicit quantification of fitness differences.
• This approach is critical for understanding and managing invasions, such as antibiotic-resistant pathogens in microbiomes.
• Future applications include machine learning integration for predicting fitness and designing resistance-lowering strategies.