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Predictive interactome modeling for precision microbiome engineering
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DOI：10.1016/j.coche.2020.08.003.png)
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Microbiome engineering aims to manipulate, control, and design community-level properties through targeted interventions of existing microbial communities or the construction of new synthetic consortia. These efforts often lead to unexpected or undesirable outcomes because of highly complex input-output relationships that are primarily ascribable to adaptive responses of interspecies interactions to perturbation. Therefore, accurate prediction of microbial interaction networks and context-specific organization will aid success in future microbiome engineering efforts. Here, we review state-of-the-art modeling approaches to evaluate their scope of prediction as in silico tools for microbiome design. We highlight the utility of advanced models for predicting context dependent interactions, multi-omics data integration, and combined use of complementary modeling and computational tools for enhanced prediction and eventual facilitation of in silico microbiome design.
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