Fatty acid-derived compounds have a range of industrial applications, from chemical building blocks to biofuels. Due to the highly dynamic nature of fatty acid metabolism, it is difficult to identify genes modulating fatty acyl-CoA levels using a rational approach. Metabolite biosensors can be used to screen genes from large-scale libraries in vivo in a high throughput manner. Here, a fatty acyl-CoA sensor based on the transcription factor FadR from Escherichia coli was established in Saccharomyces cerevisiae and combined with a gene overexpression library to screen for genes increasing the fatty acyl-CoA pool. Fluorescence-activated cell sorting, followed by data analysis, identified genes enhancing acyl-CoA levels. From these, overexpression of RTC3, GGA2, and LPP1 resulted in about 80% increased fatty alcohol levels. Changes in fatty acid saturation and chain length distribution could also be observed. These results indicate that the use of this acyl-CoA biosensor combined with a gene overexpression library allows for identification of gene targets improving production of fatty acids and derived products.

• PMID: 31314504
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Journal Article | Research Support, Non-U.S. Gov't

Authors

Dabirian Y, Gonçalves Teixeira P, Nielsen J, Siewers V, David F

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