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Sorting for secreted molecule production using a biosensor-in-microdroplet approach
Author(s) -
Emily K. Bowman,
James M. Wagner,
ShuoFu Yuan,
Matthew Deaner,
Claire M. Palmer,
Simon d’Oelsnitz,
Lauren T. Cordova,
Xin Li,
Frank F. Craig,
Hal S. Alper
Publication year - 2021
Publication title -
proceedings of the national academy of sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.011
H-Index - 771
eISSN - 1091-6490
pISSN - 0027-8424
DOI - 10.1073/pnas.2106818118
Subject(s) - biosensor , sorting , cell sorting , extracellular , high throughput screening , throughput , intracellular , computer science , small molecule , biochemical engineering , synthetic biology , computational biology , metabolic engineering , production (economics) , chemistry , nanotechnology , biochemistry , cell , biology , enzyme , materials science , engineering , programming language , telecommunications , macroeconomics , economics , wireless
Sorting large libraries of cells for improved small molecule secretion is throughput limited. Here, we combine producer/secretor cell libraries with whole-cell biosensors using a microfluidic-based screening workflow. This approach enables a mix-and-match capability using off-the-shelf biosensors through either coencapsulation or pico-injection. We demonstrate the cell type and library agnostic nature of this workflow by utilizing single-guide RNA, transposon, and ethyl-methyl sulfonate mutagenesis libraries across three distinct microbes ( Escherichia coli , Saccharomyces cerevisiae , and Yarrowia lipolytica ), biosensors from two organisms ( E. coli and S. cerevisiae ), and three products (triacetic acid lactone, naringenin, and L-DOPA) to identify targets improving production/secretion.

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