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Measurement and modeling of intrinsic transcription terminators.

Cambray G, Guimaraes JC, Mutalik VK, Lam C, Mai QA, Thimmaiah T, Carothers JM, Arkin AP, Endy D - Nucleic Acids Res. (2013)

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: BIOFAB International Open Facility Advancing Biotechnology (BIOFAB), 5885 Hollis Street, Emeryville, CA 94608, USA.

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.

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Immediate local sequence impacts on termination efficiencies. (A) Comparison of normalized transcription read-through (TRNORM, 0.0–1.0) for terminators flanked by 30 nt of native upstream and downstream genomic sequence (blue) relative to minimal cognate terminators (red). Numbers above bars indicate the fold-increase in read-through for the minimal context. (B) Varying flanking contexts modify the predicted folding kinetics of some terminators. Each graph compares the folding frequency (0.0–1.0) for a core terminator stem over time (x-axes: 0, 0.5, 1, 10, 20 and 30 s) for expanded context (blue) and minimal terminators (red), as derived from co-transcriptional folding simulations (main text). (C) Outer terminators extending past core terminator motifs. Core terminator motifs (red bases) and native (blue, main panel) or minimal (black, insets) flanking sequences as indicated. For four terminators an extended terminator stem comprising part of the poly-U tail and closed by a GC pair could be identified in their expanded native context (main panel), but not within a minimal context (insets). Variable positions indicated at the base of the stems for paralogs rrnB and rrnD (stars).
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gkt163-F4: Immediate local sequence impacts on termination efficiencies. (A) Comparison of normalized transcription read-through (TRNORM, 0.0–1.0) for terminators flanked by 30 nt of native upstream and downstream genomic sequence (blue) relative to minimal cognate terminators (red). Numbers above bars indicate the fold-increase in read-through for the minimal context. (B) Varying flanking contexts modify the predicted folding kinetics of some terminators. Each graph compares the folding frequency (0.0–1.0) for a core terminator stem over time (x-axes: 0, 0.5, 1, 10, 20 and 30 s) for expanded context (blue) and minimal terminators (red), as derived from co-transcriptional folding simulations (main text). (C) Outer terminators extending past core terminator motifs. Core terminator motifs (red bases) and native (blue, main panel) or minimal (black, insets) flanking sequences as indicated. For four terminators an extended terminator stem comprising part of the poly-U tail and closed by a GC pair could be identified in their expanded native context (main panel), but not within a minimal context (insets). Variable positions indicated at the base of the stems for paralogs rrnB and rrnD (stars).

Mentions: Genetic elements whose functions are encoded via RNA structures can be highly sensitive to changes in neighboring sequence context (31). For example, efficient transcription termination relies on the formation of a terminator hairpin, as the elongation complex is transiently paused at the U tail (17); the presence of competing structures upstream of a terminator core can prevent timely formation of a hairpin, thereby attenuating termination (36). To evaluate the impact of changing genetic context on TE, we compared the performance of 11 terminators in their natural genetic context with cognate minimal terminator motifs (i.e. sequences encoding only the hairpin and U tail; Figure 1). For 10 of the 11 terminator pairs, the full terminators flanked by 30 nt of native genomic context were at least as active as their cognate minimal terminators (P = 0.04, one-way ANOVA). Conversely, the minimal his terminator was ∼20-fold more active than the full his terminator (Figure 4A).Figure 4.


Measurement and modeling of intrinsic transcription terminators.

Cambray G, Guimaraes JC, Mutalik VK, Lam C, Mai QA, Thimmaiah T, Carothers JM, Arkin AP, Endy D - Nucleic Acids Res. (2013)

Immediate local sequence impacts on termination efficiencies. (A) Comparison of normalized transcription read-through (TRNORM, 0.0–1.0) for terminators flanked by 30 nt of native upstream and downstream genomic sequence (blue) relative to minimal cognate terminators (red). Numbers above bars indicate the fold-increase in read-through for the minimal context. (B) Varying flanking contexts modify the predicted folding kinetics of some terminators. Each graph compares the folding frequency (0.0–1.0) for a core terminator stem over time (x-axes: 0, 0.5, 1, 10, 20 and 30 s) for expanded context (blue) and minimal terminators (red), as derived from co-transcriptional folding simulations (main text). (C) Outer terminators extending past core terminator motifs. Core terminator motifs (red bases) and native (blue, main panel) or minimal (black, insets) flanking sequences as indicated. For four terminators an extended terminator stem comprising part of the poly-U tail and closed by a GC pair could be identified in their expanded native context (main panel), but not within a minimal context (insets). Variable positions indicated at the base of the stems for paralogs rrnB and rrnD (stars).
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3643576&req=5

gkt163-F4: Immediate local sequence impacts on termination efficiencies. (A) Comparison of normalized transcription read-through (TRNORM, 0.0–1.0) for terminators flanked by 30 nt of native upstream and downstream genomic sequence (blue) relative to minimal cognate terminators (red). Numbers above bars indicate the fold-increase in read-through for the minimal context. (B) Varying flanking contexts modify the predicted folding kinetics of some terminators. Each graph compares the folding frequency (0.0–1.0) for a core terminator stem over time (x-axes: 0, 0.5, 1, 10, 20 and 30 s) for expanded context (blue) and minimal terminators (red), as derived from co-transcriptional folding simulations (main text). (C) Outer terminators extending past core terminator motifs. Core terminator motifs (red bases) and native (blue, main panel) or minimal (black, insets) flanking sequences as indicated. For four terminators an extended terminator stem comprising part of the poly-U tail and closed by a GC pair could be identified in their expanded native context (main panel), but not within a minimal context (insets). Variable positions indicated at the base of the stems for paralogs rrnB and rrnD (stars).
Mentions: Genetic elements whose functions are encoded via RNA structures can be highly sensitive to changes in neighboring sequence context (31). For example, efficient transcription termination relies on the formation of a terminator hairpin, as the elongation complex is transiently paused at the U tail (17); the presence of competing structures upstream of a terminator core can prevent timely formation of a hairpin, thereby attenuating termination (36). To evaluate the impact of changing genetic context on TE, we compared the performance of 11 terminators in their natural genetic context with cognate minimal terminator motifs (i.e. sequences encoding only the hairpin and U tail; Figure 1). For 10 of the 11 terminator pairs, the full terminators flanked by 30 nt of native genomic context were at least as active as their cognate minimal terminators (P = 0.04, one-way ANOVA). Conversely, the minimal his terminator was ∼20-fold more active than the full his terminator (Figure 4A).Figure 4.

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: BIOFAB International Open Facility Advancing Biotechnology (BIOFAB), 5885 Hollis Street, Emeryville, CA 94608, USA.

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.

Show MeSH
Related in: MedlinePlus