Literature DB >> 27821774

Ultrahigh-throughput-directed enzyme evolution by absorbance-activated droplet sorting (AADS).

Fabrice Gielen1, Raphaelle Hours1, Stephane Emond1, Martin Fischlechner1,2, Ursula Schell3, Florian Hollfelder4.   

Abstract

Ultrahigh-throughput screening, in which members of enzyme libraries compartmentalized in water-in-oil emulsion droplets are assayed, has emerged as a powerful format for directed evolution and functional metagenomics but is currently limited to fluorescence readouts. Here we describe a highly efficient microfluidic absorbance-activated droplet sorter (AADS) that extends the range of assays amenable to this approach. Using this module, microdroplets can be sorted based on absorbance readout at rates of up to 300 droplets per second (i.e., >1 million droplets per hour). To validate this device, we implemented a miniaturized coupled assay for NAD+-dependent amino acid dehydrogenases. The detection limit (10 μM in a coupled assay producing a formazan dye) enables accurate kinetic readouts sensitive enough to detect a minimum of 1,300 turnovers per enzyme molecule, expressed in a single cell, and released by lysis within a droplet. Sorting experiments showed that the AADS successfully enriched active variants up to 2,800-fold from an overwhelming majority of inactive ones at ∼100 Hz. To demonstrate the utility of this module for protein engineering, two rounds of directed evolution were performed to improve the activity of phenylalanine dehydrogenase toward its native substrate. Fourteen hits showed increased activity (improved >4.5-fold in lysate; kcat increased >2.7-fold), soluble protein expression levels (up 60%), and thermostability (Tm, 12 °C higher). The AADS module makes the most widely used optical detection format amenable to screens of unprecedented size, paving the way for the implementation of chromogenic assays in droplet microfluidics workflows.

Entities:  

Keywords:  directed evolution; emulsion droplets; microfluidics; protein engineering; ultrahigh-throughput

Mesh:

Substances:

Year:  2016        PMID: 27821774      PMCID: PMC5127370          DOI: 10.1073/pnas.1606927113

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


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