Matrix regulation: a plug-and-tune method for combinatorial regulation in Saccharomyces cerevisiae

Xiaolong Teng, Zibai Wang, Yueping Zhang, Binhao Wang, Guiping Gong, Jinmiao Hu, Yifan Zhu, Baoyi Peng, Junyang Wang, James Chen, Shuobo Shi, Jens Nielsen and Zihe Liu ()
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Xiaolong Teng: Beijing University of Chemical Technology
Zibai Wang: Beijing University of Chemical Technology
Yueping Zhang: China Agricultural University
Binhao Wang: Beijing University of Chemical Technology
Guiping Gong: Beijing University of Chemical Technology
Jinmiao Hu: Beijing University of Chemical Technology
Yifan Zhu: Beijing University of Chemical Technology
Baoyi Peng: Beijing University of Chemical Technology
Junyang Wang: Beijing University of Chemical Technology
James Chen: Beijing University of Chemical Technology
Shuobo Shi: Beijing University of Chemical Technology
Jens Nielsen: Beijing University of Chemical Technology
Zihe Liu: Beijing University of Chemical Technology

Nature Communications, 2025, vol. 16, issue 1, 1-12

Abstract: Abstract Transcriptional fine-tuning of long pathways is complex, even in the extensively applied cell factory Saccharomyces cerevisiae. Here, we present Matrix Regulation (MR), a CRISPR-mediated pathway fine-tuning method enabling the construction of 68 gRNA combinations and screening for the optimal expression levels across up to eight genes. We first identify multiple tRNAs with efficient gRNA processing capacities to assemble a gRNA regulatory matrix combinatorially. Then, we expand the target recognition of CRISPR regulation from NGG PAM to NG PAM by characterizing dCas9 variants. To increase the dynamic range of modulation, we test 101 candidate activation domains followed by mutagenesis and screening the best one to further enhance its activation capability in S. cerevisiae by 3-fold. The regulations generate combinatorial strain libraries for both the mevalonate pathway and the heme biosynthesis pathway and increase squalene production by 37-fold and heme by 17-fold, respectively, demonstrating the versatility of our method and its applicability in fundamental research.

Date: 2025
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DOI: 10.1038/s41467-025-62886-5

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