Pipeline and insulated dual-reporter system to predict and quantify strong terminators from RNA-seq datasets for metabolic engineering.

The limited availability of genetic regulatory parts, especially terminators from non-model microorganisms, hampers precise gene regulation and the construction of efficient microbial cell factories. To address this problem, we developed a novel strategy for predicting and quantifying strong terminators genome-widely by integrating RNA-seq datasets with an insulated dual-reporter system. We validated 48, and 41 strong terminators in Zymomonas mobilis and Escherichia coli, respectively. Our results demonstrated notable cross-species compatibility of these terminators between the two bacteria and revealed that the length of the upstream sequence affects termination efficiency in Z. mobilis. We further applied selected strong terminators to enhance 2,3-butanediol production in Z. mobilis. This work thus establishes a pipeline for genome-wide prediction, quantitative assessment, and cross-species evaluation of bacterial terminators. It provides a valuable resource for expanding prokaryotic terminator libraries and engineering efficient microbial cell factories with refined transcriptional control.