Abstract
Genetically encoded biosensors are powerful tools used to screen metabolite-producing microbial strains. Traditionally, biosensor-based screening approaches also use fluorescence-activated cell sorting (FACS). However, these approaches are limited by the measurement of intracellular fluorescence signals in single cells, rather than the signals associated with populations comprising multiple cells. This characteristic reduces the accuracy of screening because of the variability in signal levels among individual cells. To overcome this limitation, we introduced an approach that combined biosensors with droplet microfluidics (i.e., fluorescence-activated droplet sorting, FADS) to detect labeled cells at a multi-copy level and in an independent droplet microenvironment. We used our previously reported genetically encoded biosensor, 3-dehydroshikimic acid (3-DHS), as a model with which to establish the biosensor-based FADS screening method. We then characterized and compared the effects of the sorting method on the biosensor-based screening system by subjecting the same mutant library to FACS and FADS. Notably, our developed biosensor-enabled, droplet microfluidics-based FADS screening system yielded an improved positive mutant enrichment rate and increased productivity by the best mutant, compared with the single-cell FACS system. In conclusion, the combination of a biosensor and droplet microfluidics yielded a more efficient screening method that could be applied to the biosensor-based high-throughput screening of other metabolites.
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More From: Journal of Industrial Microbiology and Biotechnology
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