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Updated: Jun 28, 2025

Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays
Published on: November 12, 2012
A generic approach to infer community-level fitness of microbial genes
Teng Wang1, Andrea Weiss1, Lingchong You1,2,3
1Department of Biomedical Engineering, Duke University, Durham, NC 27705.
Abstract:
The gene content in a metagenomic pool defines the function potential of a microbial community. Natural selection, operating on the level of genomes or genes, shapes the evolution of community functions by enriching some genes while depriving the others. Despite the importance of microbiomes in the environment and health, a general metric to evaluate the community-wide fitness of microbial genes remains lacking. In this work, we adapt the classic neutral model of species and use it to predict how the abundances of different genes will be shaped by selection, regardless of at which level the selection acts. We establish a simple metric that quantitatively infers the average survival capability of each gene in a microbiome. We then experimentally validate the predictions using synthetic communities of barcoded Escherichia coli strains undergoing neutral assembly and competition. We further show that this approach can be applied to publicly available metagenomic datasets to gain insights into the environment-function interplay of natural microbiomes.
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