Authors
Pu Xue, University of Illinois At Urbana Champaign
Fatty acid biosynthesis in Saccharomyces cerevisiae is regulated by numerous transcription factors whose interactions remain inadequately understood, limiting metabolic engineering efforts for bioproduct enhancement. To elucidate these regulatory dynamics and optimize metabolic output, we established an automated yeast engineering platform to systematically evaluate transcription factor influences on free fatty acid (FFA) production. Leveraging a genome-scale engineering strategy, CRISPR-Cas9 and homology-directed repair (HDR)-assisted genome engineering (CHAnGE), we systematically targeted ten key transcription factors through combinatorial and sequential knockouts. This process was streamlined within the Illinois Biological Foundry for Advanced Biomanufacturing (iBioFAB), enabling high-throughput and precise mutant library generation. Screening efficiency was enhanced via Liquid Extraction Surface Analysis coupled with Mass Spectrometry (LESA-MS), facilitating direct quantitative analysis of FFAs from yeast liquid cultures. Through iterative cycles of automated library construction and evaluation, we developed a combinatorial knockout library featuring single, double, and triple gene deletions, achieving an 8.29-fold improvement in short-chain FFA production. This research significantly advances S. cerevisiae as a microbial platform by introducing a systematic, scalable, and automated framework for transcription factor modulation. The integration of advanced automation with rapid, accurate analytical methods accelerates strain development, offering a transformative framework for next-generation biomanufacturing and sustainable biochemical production.
