Quartet: Disentangling positive and negative components of microbial interactions

Area of Science:

• Community ecology
• Microbial interactions
• Metabolic interactions

Background:

• Interspecies interactions are conventionally measured by net influence, obscuring underlying positive and negative components.
• Current community ecology theories rely on net interactions, limiting understanding of complex community dynamics.
• Disentangling positive (e.g., cross-feeding) and negative (e.g., competition) interaction components is crucial but challenging.

Purpose of the Study:

• To develop a method for estimating the distinct positive and negative components of interspecies metabolic interactions.
• To introduce the 'quartet' framework for a more fundamental characterization of pairwise species interactions.
• To improve the predictive power of community ecology theories by accounting for interaction components.

Main Methods:

• Devised a theoretical resource partitioning strategy to analyze species growth rate data.
• Applied the method to in silico oral microbiome data and in vitro auxotroph data.
• Decomposed net species influence into constituent positive and negative interaction components.

Main Results:

• Positive and negative interaction components were found to have comparable average strengths.
• Identified species pairs with similar net interactions but distinct underlying component quartets.
• Demonstrated that weak net interactions can result from the cancellation of strong positive and negative components.

Conclusions:

• The 'quartet' of interaction components provides a more fundamental characterization than net interactions alone.
• Understanding these components is essential for accurately predicting microbial community behavior.
• This approach can enhance the reliability of community ecology theories and inform microbial community design.