LAUSR

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.