Literature DB >> 32943147

Directed evolution of custom polymerases using droplet microfluidics.

Derek Vallejo1, Ali Nikoomanzar1, John C Chaput2.   

Abstract

DNA polymerases are critical tools for a large number of emerging applications in biotechnology, but oftentimes polymerases with desired functions are not readily available. Directed evolution provides a possible solution to this problem by enabling the creation of engineered polymerases that are better equipped to recognize a given unnatural substrate. Here we report a microfluidic-based method for evolving new polymerase functions that involves ultrahigh throughput sorting of fluorescent water-in-oil (w/o) microdroplets. The workflow entails the expression of a diverse population of polymerase variants in E. coli, production of microfluidic droplets containing one or less E. coli, bacteria lysis to release the polymerase and encoding plasmid into the surrounding droplet, a fluorescence-based activity assay to identify variants with a desired activity, isolation of fluorescent droplets using a fluorescence activated droplet sorting (FADS) device, and plasmid recovery with DNA sequencing to determine the identity of the functional variants. This technique is amenable to any type of unnatural nucleic acid and/or polymerase function, including DNA-templated synthesis, reverse transcription, and replication.
© 2020 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Droplet sorting; Microfluidics; Polymerase

Mesh:

Substances:

Year:  2020        PMID: 32943147     DOI: 10.1016/bs.mie.2020.04.056

Source DB:  PubMed          Journal:  Methods Enzymol        ISSN: 0076-6879            Impact factor:   1.600


  2 in total

1.  A Lab-in-a-Fiber optofluidic device using droplet microfluidics and laser-induced fluorescence for virus detection.

Authors:  Helen E Parker; Sanghamitra Sengupta; Achar V Harish; Ruben R G Soares; Haakan N Joensson; Walter Margulis; Aman Russom; Fredrik Laurell
Journal:  Sci Rep       Date:  2022-03-03       Impact factor: 4.379

2.  Programmable Droplet Microfluidics Based on Machine Learning and Acoustic Manipulation.

Authors:  Kyriacos Yiannacou; Vipul Sharma; Veikko Sariola
Journal:  Langmuir       Date:  2022-09-13       Impact factor: 4.331

  2 in total

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