Metabolic EngineeringSynthetic BiologyPeer-reviewed journal article
Syntrophic co-culture amplification of production phenotype for high-throughput screening of microbial strain libraries
Tatyana E. SaleskiiD, Alissa Kerner, Meng Ting ChungiD, Corine M. JackmaniD, Azzaya KhasbaatariD, Katsuo KurabayashiiD, Xiaoxia Nina LiniD
Abstract
Microbes can be engineered to synthesize a wide array of bioproducts, yet production phenotype evaluation remains a frequent bottleneck in the design-build-test cycle where strain development requires iterative rounds of library construction and testing. Here, we present Syntrophic Co-culture Amplification of Production phenotype (SnoCAP). Through a metabolic cross-feeding circuit, the production level of a target molecule is translated into highly distinguishable co-culture growth characteristics, which amplifies differences in production into highly distinguishable growth phenotypes. We demonstrate SnoCAP with the screening of Escherichia coli strains for production of two target molecules: 2-ketoisovalerate, a precursor of the drop-in biofuel isobutanol, and L-tryptophan. The dynamic range of the screening can be tuned by employing an inhibitory analog of the target molecule. Screening based on this framework requires compartmentalization of individual producers with the sensor strain. We explore three formats of implementation with increasing throughput capability: confinement in microtiter plates (102-104 assays/experiment), spatial separation on agar plates (104-105 assays/experiment), and encapsulation in microdroplets (105-107 assays/experiment). Using SnoCAP, we identified an efficient isobutanol production strain from a random mutagenesis library, reaching a final titer that is 5-fold higher than that of the parent strain. The framework can also be extended to screening for secondary metabolite production using a push-pull strategy. We expect that SnoCAP can be readily adapted to the screening of various microbial species, to improve production of a wide range of target molecules.
- organism: E. coli
- assay: metagenomics
- research focus: drug response / drug discovery
- approach: experimental assay
- Citations
- 52
- FWCI
- 2.65
- Field percentile
- top 9%
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