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ACS Synth Biol. 2019 Aug 16;8(8):1952-1957. doi: 10.1021/acssynbio.9b00160. Epub 2019 Aug 2.

Optimizing Cell-Free Biosensors to Monitor Enzymatic Production.

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Micalis Institute, INRA, AgroParisTech, Université Paris-Saclay , Jouy-en-Josas 78352 , France.
iSSB Laboratory, Génomique Métabolique, Genoscope, Institut François Jacob, CEA, CNRS , Université Evry, Université Paris-Saclay , 91057 Evry , France.
SYNBIOCHEM Center, School of Chemistry , University of Manchester , Manchester M13 9PL , U.K.


Cell-free systems are promising platforms for rapid and high-throughput prototyping of biological parts in metabolic engineering and synthetic biology. One main limitation of cell-free system applications is the low fold repression of transcriptional repressors. Hence, prokaryotic biosensor development, which mostly relies on repressors, is limited. In this study, we demonstrate how to improve these biosensors in cell-free systems by applying a transcription factor (TF)-doped extract, a preincubation strategy with the TF plasmid, or reinitiation of the cell-free reaction (two-step cell-free reaction). We use the optimized biosensor to sense the enzymatic production of a rare sugar, D-psicose. This work provides a methodology to optimize repressor-based systems in cell-free to further increase the potential of cell-free systems for bioproduction.


cell-free system; D-psicose; bioproduction; biosensor; cell-free optimization; transcriptional repressor


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