Computational-guided discovery of UDP-glycosyltransferases for lauryl glucoside production using engineered E. coli

Abstract Defining suitable enzymes for reaction steps in novel synthetic pathways is crucial for developing microbial cell factories for non-natural products. Here, we developed a computational workflow to identify C12 alcohol-active UDP-glycosyltransferases. The workflow involved three steps: (1) assembling initial candidates of putative UDP-glycosyltransferases, (2) refining selection by examining conserved regions, and (3) 3D structure prediction and molecular docking. Genomic sequences from Candida, Pichia, Rhizopus, and Thermotoga, known for lauryl glucoside synthesis via whole-cell biocatalysis, were screened. Out of 240 predicted glycosyltransferases, 8 candidates annotated as glycosyltransferases were selected after filtering out those with signal peptides and identifying conserved UDP-glycosyltransferase regions. These proteins underwent 3D structure prediction and molecular docking with 1-dodecanol. RO3G, a candidate from Rhizopus delemar RA 99–880 with a relatively high ChemPLP fitness score, was selected and expressed in Escherichia coli BL21 (DE3). It was further characterized using a feeding experiment with 1-dodecanol. Results confirmed that the RO3G-expressing strain could convert 1-dodecanol to lauryl glucoside, as quantified by HPLC and identified by targeted LC-MS. Monitoring the growth and fermentation profiles of the engineered strain revealed that RO3G expression did not affect cell growth. Interestingly, acetate, a major fermentation product, was reduced in the RO3G-expressing strain compared to the GFP-expressing strain, suggesting a redirection of flux from acetate to other pathways. Overall, this work presents a successful workflow for discovering UDP-glycosyltransferase enzymes with confirmed activity toward 1-dodecanol for lauryl glucoside production. Graphical abstract