(317f) ­­­­­Syntrophic Co-Culture Amplification of Production Phenotype for High-Throughput Screening of Microbial Strain Libraries | AIChE

(317f) ­­­­­Syntrophic Co-Culture Amplification of Production Phenotype for High-Throughput Screening of Microbial Strain Libraries

Authors 

Saleski, T. - Presenter, University of Michigan
Kerner, A., University of Michigan
Chung, M. T., University of Michigan
Jackman, C., University of Michigan
Khasbaatar, A., University of Michigan
Kurabayashi, K., University of Michigan
Lin, X., University of Michigan
For most target molecules, the test phase of the design-build-test cycle remains a bottleneck for optimizing microbial production strains by metabolic engineering. Here, we present a screening framework based on cross-feeding auxotrophs. Through a metabolic cross-feeding circuit, the production level of a target molecule is translated into co-culture growth characteristics, which amplifies differences in production performance into highly screenable growth phenotypes. This strategy can be applied to target molecules for which auxotrophic biosensors exist or can be created. We demonstrate this screening framework for two target molecules: 2-ketoisovalerate (a precursor of the drop-in biofuel isobutanol), and L-tryptophan. We show that the dynamic range of the screening may be tuned by employing an inhibitory analog of the target molecule. We also demonstrate that it can be expanded to screening of secondary metabolite production using a pus­­­­h-pull strategy. 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, spatial separation on agar plates, and encapsulation in microdroplets. We employ the screening in the agar plate format to identify an efficient isobutanol production strain from a random mutagenesis library, reaching a final titer that is 4.7-fold higher than that of the parent strain. Finally, by fluorescence-activated droplet sorting, we show that super-producers in model libraries can be efficiently enriched from low frequencies.