High-throughput screening of microbial communities using nanodroplets

Microbial communities play key roles in medicine, agriculture, and biotechnology. A predictive understanding of the structure and function of these communities is crucial for managing natural communities and designing novel ones. Despite their importance, predictive models of microbial communities remain elusive. Modeling microbial communities is challenging as it requires considering the properties of individual species, interspecies interactions, and their dependence on the environment. These properties typically cannot be accurately inferred from first principles, nor measured experimentally using traditional techniques. To overcome these limitations, we have developed the kChip, a droplet-based platform that performs rapid, massively parallel construction and screening of ~100,000 synthetic microbial communities per day. The kChip allows screening for any optically assayable property, including growth of specific microbes, total community biomass, and activation of specific cellular functions. Using the kChip, we have measured the interactions between a diverse set of soil bacteria growing on a panel of carbon sources. This screen has revealed that facilitation is prevalent among microbes - poor growers almost always exploited strong ones, even when growing on simple monomeric carbon sources. Broadly, kChip screening can uncover the rules underlying species` growth and interactions, provide high-throughput measurements to parameterize models, and identify specific microbial consortia that perform desired functions including suppression of pathogens and degradation of recalcitrant substrates.