(647a) Developing a Fully Automated Workflow to Speed up the Design-Build-Test-Learn Cycle for Engineering of Microbial Cell Factories | AIChE

(647a) Developing a Fully Automated Workflow to Speed up the Design-Build-Test-Learn Cycle for Engineering of Microbial Cell Factories

Authors 

Xue, P. - Presenter, University of Illinois At Urbana Champaign
Zhao, H., University of Illinois-Urbana
Microbial cell factories (MCFs) have been extensively engineered to produce chemicals, fuels, and materials. However, metabolic engineering of MCFs remains time-consuming and labor-intensive. One major reason is the lack of a general platform for large-scale mutagenesis and high-throughput screening. To address this limitation, we performed genetic engineering and phenotypic screening by integrating the Design-Build-Test-Learn cycle with a biofoundry. As proof-of-concept, we are building a fully automated gene deletion workflow for the construction of transcriptional factor (TF) knock-out variants combinatorially in Saccharomyces cerevisiae. 175 single, double, or triple gene deletion variants are being created by our biofoundry in a single day. In parallel, we developed a mass spectrometry (MS)-based high-throughput screening method for rapid profiling of these TF variants. Most triple gene deletion variants were identified with improving shorter-acyl chain free fatty acids production. Through the integration of automated acoustic liquid handling and MS-based screening, the throughput of phenotyping can achieve up to 2 colonies/liquid cultures per second. Additionally, we attempted to develop a fully automated DNA assembly method for quick plasmid construction, which could achieve ~100% fidelity for assembly of 2-12 fragments with a final plasmid size of 25 kb. Thousands of plasmids in 96-well plate format can be created by our biofoundry in a single day. These developed workflows should be generally applicable to metabolic engineering of MCFs for production of value-added products.