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Cell Syst. 2019 Aug 16. pii: S2405-4712(19)30231-5. doi: 10.1016/j.cels.2019.06.008. [Epub ahead of print]

Microbial Interaction Network Inference in Microfluidic Droplets.

Author information

1
Department of Biochemistry, University of Wisconsin-Madison, Madison, WI 53706, USA.
2
Department of Biochemistry, University of Wisconsin-Madison, Madison, WI 53706, USA; Department of Chemical & Biological Engineering, University of Wisconsin-Madison, Madison, WI 53706, USA.
3
Department of Biochemistry, University of Wisconsin-Madison, Madison, WI 53706, USA; Department of Bacteriology, University of Wisconsin-Madison, Madison, WI 53706, USA; Department of Chemical & Biological Engineering, University of Wisconsin-Madison, Madison, WI 53706, USA. Electronic address: venturelli@wisc.edu.

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 elucidated the complex web of interactions linking antibiotics and different species in a synthetic consortium. In sum, we demonstrated a robust and generalizable method to infer microbial interaction networks by random encapsulation of sub-communities into microfluidic droplets.

KEYWORDS:

antibiotics; droplet microfluidics; microbial ecology; microbial interaction network; stochastic modeling

PMID:
31494089
DOI:
10.1016/j.cels.2019.06.008

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