Metabolic EngineeringSynthetic BiologyPeer-reviewed journal article
Regulatory control circuits for stabilizing long-term anabolic product formation in yeast
Vasil D’AmbrosioiD, Eleonora DoreiD, Roberto Di BlasiiD, Marcel A. van den BroekiD, Suresh SudarsaniD, Jolanda ter HorstiD, Francesca AmbriiD, Morten Otto Alexander SommeriD, Peter RugbjergiD, Jay D. KeaslingiD, Robert MansiD, Michael Krogh JenseniD
Abstract
Engineering living cells for production of chemicals, enzymes and therapeutics can burden cells due to use of limited native co-factor availability and/or expression burdens, totalling a fitness deficit compared to parental cells encoded through long evolutionary trajectories to maximise fitness. Ultimately, this discrepancy puts a selective pressure against fitness-burdened engineered cells under prolonged bioprocesses, and potentially leads to complete eradication of high-performing engineered cells at the population level. Here we present the mutation landscapes of fitness-burdened yeast cells engineered for vanillin-{beta}-glucoside production. Next, we design synthetic control circuits based on transcriptome analysis and biosensors responsive to vanillin-{beta}-glucoside pathway intermediates in order to stabilize vanillin-{beta}-glucoside production over [~]55 generations in sequential passage experiments. Furthermore, using biosensors with two different modes of action we identify control circuits linking vanillin-{beta}-glucoside pathway flux to various essential cellular functions, and demonstrate control circuits robustness and 92% higher vanillin-{beta}-glucoside production, including 5-fold increase in total vanillin-{beta}-glucoside pathway metabolite accumulation, in a fed-batch fermentation compared to vanillin-{beta}-glucoside producing cells without control circuits.
- organism: yeast
- assay: DNA methylation
- assay: proteomics
- research focus: gene regulatory network inference
- research focus: drug response / drug discovery
- approach: statistical model
- approach: experimental assay
- Citations
- 30
- FWCI
- 1.30
- Field percentile
- top 21%
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