Challenges in quantifying functional redundancy and selection in microbial communities.

Area of Science:

• Microbiome research
• Ecology
• Systems biology

Background:

• Microbiomes show high functional redundancy despite species variability.
• Functional redundancy is often interpreted as evidence for selection on functional units.
• The relationship between functional redundancy and selection in microbiomes is not fully understood.

Purpose of the Study:

• To investigate whether reduced functional variability in microbiomes implies selection.
• To develop empirical null models to differentiate true selection from statistical artifacts.
• To re-evaluate functional selection in existing microbiome datasets.

Main Methods:

• Development of empirical null models to account for statistical averaging and bias.
• Application of these models to microbiome data from bromeliad foliage, soil bacteria, and human gut commensals.
• Analysis of Human Microbiome Project gut microbiome data using the developed framework.

Main Results:

• Bromeliad foliage microbiomes showed no evidence of functional selection.
• In vitro grown soil bacteria and human gut commensals exhibited selection for metabolic capabilities.
• Apparent functional selection in Human Microbiome Project gut data was identified as an artifact; no selection for KEGG orthology functions was found.

Conclusions:

• Reduced functional variability does not automatically indicate selection on functional profiles.
• Statistical averaging and bias can create the appearance of functional selection.
• A new framework is proposed for quantifying functional redundancy and selection in microbiomes.