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Optimizing Cell-Free Biosensors to Monitor Enzymatic Production
Amir Pandi1, Ioana Grigoras2, Olivier Borkowski2
1Micalis Institute, INRA, AgroParisTech, Université Paris-Saclay , Jouy-en-Josas 78352 , France.
Abstract:
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.
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