4.4 Article

Analysing Megasynthetase Mutants at High Throughput Using Droplet Microfluidics

Journal

CHEMBIOCHEM
Volume -, Issue -, Pages -

Publisher

WILEY-V C H VERLAG GMBH
DOI: 10.1002/cbic.202300680

Keywords

A-domain engineering; droplet microfluidics; high-throughput screening; liposome; NRPS engineering

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This study establishes a microfluidic platform for reliable detection of nonribosomal peptide gramicidin S production and identification of NRPS mutants, providing a high-throughput method for studying large libraries of NRPS variants. The platform enables more sophisticated structure-activity studies and new engineering applications in the future.
Nonribosomal peptide synthetases (NRPSs) are giant enzymatic assembly lines that deliver many pharmaceutically valuable natural products, including antibiotics. As the search for new antibiotics motivates attempts to redesign nonribosomal metabolic pathways, more robust and rapid sorting and screening platforms are needed. Here, we establish a microfluidic platform that reliably detects production of the model nonribosomal peptide gramicidin S. The detection is based on calcein-filled sensor liposomes yielding increased fluorescence upon permeabilization. From a library of NRPS mutants, the sorting platform enriches the gramicidin S producer 14.5-fold, decreases internal stop codons 250-fold, and generates enrichment factors correlating with enzyme activity. Screening for NRPS activity with a reliable non-binary sensor will enable more sophisticated structure-activity studies and new engineering applications in the future. NRPSs are an important source of pharmaceutically valuable natural products. The large sequence space of NRPS variant libraries requires a robust, high-throughput sorting and screening platform. Here we present a novel high-throughput microfluidic screening platform for the investigation of mutants of NRP producing bacteria in a highly parallel manner. Our results demonstrate the power of this platform for studying large libraries of NRPS variants.**+image

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