Using fungible biosensors to evolve improved alkaloid biosyntheses

A key bottleneck in the microbial production of therapeutic plant metabolites is identifying enzymes that can improve yield. The facile identification of genetically encoded biosensors can overcome this limitation and become part of a general method for engineering scaled production. We have develop...

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Veröffentlicht in:	Nature chemical biology 2022-09, Vol.18 (9), p.981-989
Hauptverfasser:	d’Oelsnitz, Simon, Kim, Wantae, Burkholder, Nathaniel T., Javanmardi, Kamyab, Thyer, Ross, Zhang, Yan, Alper, Hal S., Ellington, Andrew D.
Format:	Artikel
Sprache:	eng
Schlagworte:	631/45/535/1266 631/92/349 631/92/469 631/92/552 Alkaloids Alkaloids - chemistry Binding sites Biochemical Engineering Biochemistry Bioorganic Chemistry Biosensing Techniques Biosensors Biosynthesis Cell Biology Chemical sensors Chemistry Chemistry and Materials Science Chemistry/Food Science Evolution Genetic code Metabolites Methylation Microorganisms Plants - metabolism Screening Transcription factors
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Zusammenfassung:	A key bottleneck in the microbial production of therapeutic plant metabolites is identifying enzymes that can improve yield. The facile identification of genetically encoded biosensors can overcome this limitation and become part of a general method for engineering scaled production. We have developed a combined screening and selection approach that quickly refines the affinities and specificities of generalist transcription factors; using RamR as a starting point, we evolve highly specific (>100-fold preference) and sensitive (half-maximum effective concentration (EC 50 )
ISSN:	1552-4450 1552-4469 1552-4469
DOI:	10.1038/s41589-022-01072-w