4.7 Article

Displaced by Deceivers: Prevention of Biosensor Cross-Talk Is Pivotal for Successful Biosensor-Based High-Throughput Screening Campaigns

Journal

ACS SYNTHETIC BIOLOGY
Volume 8, Issue 8, Pages 1847-1857

Publisher

AMER CHEMICAL SOC
DOI: 10.1021/acssynbio.9b00149

Keywords

transcriptional biosensor; library screening; product sensing; fluorescence-activated cell sorting; protein engineering; directed evolution

Funding

  1. European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme [638718]
  2. European Research Council (ERC) [638718] Funding Source: European Research Council (ERC)

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Transcriptional biosensors emerged as powerful tools for protein and strain engineering as they link inconspicuous production phenotypes to easily measurable output signals such as fluorescence. When combined with fluorescence-activated cell sorting, transcriptional biosensors enable high throughput screening of vast mutant libraries. Interestingly, even though many published manuscripts describe the construction and characterization of transcriptional biosensors, only very few studies report the successful application of transcriptional biosensors in such high-throughput screening campaigns. Here, we describe construction and characterization of the trans-cinnamic acid responsive transcriptional biosensor pSenCA for Escherichia coli and its application in a FACS based screen. In this context, we focus on essential methodological challenges during the development of such biosensor-guided high-throughput screens such as biosensor cross-talk between producing and nonproducing cells, which could be minimized by optimization of expression and cultivation conditions. The optimized conditions were applied in a five-step FACS campaign and proved suitable to isolate phenylalanine ammonia lyase variants with improved activity in E. coli and in vitro. Findings from this study will help researchers who want to profit from the unmatched throughput of fluorescence-activated cell sorting by using transcriptional biosensors for their enzyme and strain engineering campaigns.

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