Literature DB >> 29170967

High-Throughput Microfluidics for the Screening of Yeast Libraries.

Mingtao Huang1,2, Haakan N Joensson3,4, Jens Nielsen5,6.   

Abstract

Cell factory development is critically important for efficient biological production of chemicals, biofuels, and pharmaceuticals. Many rounds of the Design-Build-Test-Learn cycles may be required before an engineered strain meeting specific metrics required for industrial application. The bioindustry prefer products in secreted form (secreted products or extracellular metabolites) as it can lower the cost of downstream processing, reduce metabolic burden to cell hosts, and allow necessary modification on the final products , such as biopharmaceuticals. Yet, products in secreted form result in the disconnection of phenotype from genotype, which may have limited throughput in the Test step for identification of desired variants from large libraries of mutant strains. In droplet microfluidic screening, single cells are encapsulated in individual droplet and enable high-throughput processing and sorting of single cells or clones. Encapsulation in droplets allows this technology to overcome the throughput limitations present in traditional methods for screening by extracellular phenotypes. In this chapter, we describe a protocol/guideline for high-throughput droplet microfluidics screening of yeast libraries for higher protein secretion . This protocol can be adapted to screening by a range of other extracellular products from yeast or other hosts.

Entities:  

Keywords:  Droplet microfluidics; High-throughput screening; Protein secretion; Random mutagenesis; Systems biology; Yeast cell factories

Mesh:

Year:  2018        PMID: 29170967     DOI: 10.1007/978-1-4939-7295-1_19

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  1 in total

1.  Retinitis Pigmentosa Due to Rp1 Biallelic Variants.

Authors:  Rita Sousa Silva; Mariana Vallim Salles; Fabiana Louise Motta; Juliana Maria Ferraz Sallum
Journal:  Sci Rep       Date:  2020-01-31       Impact factor: 4.379

  1 in total

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