Microbial Interaction Network Inference in Microfluidic Droplets.

ABSTRACT: Microbial interactions are major drivers of microbial community dynamics and functions but remain challenging to identify because of limitations in parallel culturing and absolute abundance quantification of community members across environments and replicates. To this end, we developed Microbial Interaction Network Inference in microdroplets (MINI-Drop). Fluorescence microscopy coupled to computer vision techniques were used to rapidly determine the absolute abundance of each strain in hundreds to thousands of droplets per condition. We showed that MINI-Drop could accurately infer pairwise and higher-order interactions in synthetic consortia. We developed a stochastic model of community assembly to provide insight into the heterogeneity in community states across droplets. Finally, we elu

SUBMITTER: Hsu RH 

PROVIDER: S-EPMC6763379 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature