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An ultrahigh‐throughput screening platform based on flow cytometric droplet sorting for mining novel enzymes from metagenomic libraries
Author(s) -
Ma Fuqiang,
Guo Tianjie,
Zhang Yifan,
Bai Xue,
Li Changlong,
Lu Zelin,
Deng Xi,
Li Daixi,
Kurabayashi Katsuo,
Yang Guangyu
Publication year - 2021
Publication title -
environmental microbiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.954
H-Index - 188
eISSN - 1462-2920
pISSN - 1462-2912
DOI - 10.1111/1462-2920.15257
Subject(s) - metagenomics , biology , sorting , computational biology , high throughput screening , identification (biology) , throughput , biochemical engineering , gene , computer science , bioinformatics , genetics , ecology , engineering , telecommunications , wireless , programming language
Summary Uncultivable microbial communities provide enormous reservoirs of enzymes, but their experimental identification by functional metagenomics is challenging, mainly due to the difficulty of screening enormous metagenomic libraries. Here, we propose a reliable and convenient ultrahigh‐throughput screening platform based on flow cytometric droplet sorting (FCDS). The FCDS platform employs water‐in‐oil‐in‐water double emulsion droplets serving as single‐cell enzymatic micro‐reactors and a commercially available flow cytometer, and it can efficiently isolate novel biocatalysts from metagenomic libraries by processing single cells as many as 10 8 per day. We demonstrated the power of this platform by screening a metagenomic library constructed from domestic running water samples. The FCDS assay screened 30 million micro‐reactors in only 1 h, yielding a collection of esterase genes. Among these positive hits, Est WY was identified as a novel esterase with high catalytic efficiency and distinct evolutionary origin from other lipolytic enzymes. Our study manifests that the FCDS platform is a robust tool for functional metagenomics, with the potential to significantly improve the efficiency of exploring novel enzymes from nature.