Measurement and modeling of intrinsic transcription terminators

Abstract

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 routinely, 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 termination 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 termination activity. We found that structures extending beyond the core terminator stem are likely to increase 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 resulting systematically measured collection of terminators should improve the engineering of synthetic genetic systems and also advance quantitative modeling of transcription termination.

Principles of genetic circuit design

“…Strong, tandem terminators can be placed on either side of each gene to ensure isolated expression of individual operons 177 . Large libraries of rho-independent terminators were recently built and characterized to enable the construction of large circuits that are robust to read-through and homologous recombination (described below) 50,177 .…”

Control of Gene Expression at a Bacterial Leader RNA, the agn43 Gene Encoding Outer Membrane Protein Ag43 of Escherichia coli

“…SA1 in the supplemental material for a predicted secondary structure of the entire leader RNA). Such structures have been found to effect termination of transcription by bacterial RNA polymerase (15,26,27). We first determined whether this structure (T1) ( Fig.…”

Promoter and Terminator Discovery and Engineering

“…In prokaryotes, multiple biophysical models have been developed to predict terminator strength based on elementary steps in termination, including U:A hybrid formation, hairpin formation, and mRNA transcript dissociation [122,133,134]. Training one of these models on a set of natural and synthetic terminators over a large dynamic range in termination efficiencies afforded a linear sequence-function model with a high coefficient of determination (R 2 ¼ 0.81) [134]. In S. cerevisiae, however, terminator function is much less predictable based simply on distinct sequence elements whose function is determined by biophysical models.…”