Measurement and modeling of intrinsic transcription terminators

The reliable forward engineering of genetic systems remains limited by the ad hoc reuse of many types of basic genetic elements. Although a few intrinsic prokaryotic transcription terminators are used rou-tinely, termination efficiencies have not been studied systematically. Here, we developed and validated a genetic architecture that enables reliable measurement of termination efficiencies. We then assembled a collection of 61 natural and synthetic terminators that collectively encode ter-mination efficiencies across an 800-fold dynamic range within Escherichia coli. We simulated co-transcriptional RNA folding dynamics to identify competing secondary structures that might interfere with terminator folding kinetics or impact termin-ation activity. We found that structures extending beyond the core terminator stem are likely to in-crease terminator activity. By excluding terminators encoding such context-confounding elements, we were able to develop a linear sequence-function model that can be used to estimate termination efficiencies (r=0.9, n=31) better than models trained on all terminators (r=0.67, n=54). The result-ing systematically measured collection of termin-ators should improve the engineering of synthetic genetic systems and also advance quantitative modeling of transcription termination