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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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Architecture of a standardized genetic device for termination efficiency measurements. (A) Anatomy of an intrinsic terminator (purple) and generic architecture of processed mRNA originating from a terminator measurement device. RNase recognition sites (orange diamonds) are intended to standardize the 3′- or 5′-ends of processed mRNA encoding upstream (UP, red) and downstream (DW, green) reporter genes. The four features selected in our best quantitative model of termination efficiencies (main text), numbered by decreasing importance (grey regions: 1 = TTHP_utail_score; 2 = hp_norm_dg; 3 = closing_stackGC; 4 = dna_dna_pattern). (B) Six terminator measurement device variants tested here. Green (G, green box) and red (R, red box) fluorescent reporter coding sequences bracket a terminator (purple T) test site flanked by RNase E sites (E, blue diamonds), RNase III sites (3, orange diamonds) or non-functional RNase III sites (*, orange diamonds).
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gkt163-F1: Architecture of a standardized genetic device for termination efficiency measurements. (A) Anatomy of an intrinsic terminator (purple) and generic architecture of processed mRNA originating from a terminator measurement device. RNase recognition sites (orange diamonds) are intended to standardize the 3′- or 5′-ends of processed mRNA encoding upstream (UP, red) and downstream (DW, green) reporter genes. The four features selected in our best quantitative model of termination efficiencies (main text), numbered by decreasing importance (grey regions: 1 = TTHP_utail_score; 2 = hp_norm_dg; 3 = closing_stackGC; 4 = dna_dna_pattern). (B) Six terminator measurement device variants tested here. Green (G, green box) and red (R, red box) fluorescent reporter coding sequences bracket a terminator (purple T) test site flanked by RNase E sites (E, blue diamonds), RNase III sites (3, orange diamonds) or non-functional RNase III sites (*, orange diamonds).

Mentions: Sequence features within intrinsic terminators have been well studied in E. coli and include a core GC-rich stem of 5–9 nt that is closed by a short 3–5 nt loop and followed by a 7–9 nt U-rich tail (Figure 1A) (10,16). A few intrinsic terminators have been extensively studied in vitro, resulting in mechanistic models for how individual sequence motifs contribute to overall termination efficiency (15,17). From these foundational studies, computational methods have been developed to identify putative terminator elements within natural DNA sequences. Such tools have improved the automated annotation of genome sequences and reshaped consideration of operon structure and chromosome organization (16,18–22). However, sequences that match putative terminator motifs are pervasive within natural genomes, and most computational predictions are not validated experimentally, thereby hindering the iterative development of improved terminator identification tools.Figure 1.


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)

Architecture of a standardized genetic device for termination efficiency measurements. (A) Anatomy of an intrinsic terminator (purple) and generic architecture of processed mRNA originating from a terminator measurement device. RNase recognition sites (orange diamonds) are intended to standardize the 3′- or 5′-ends of processed mRNA encoding upstream (UP, red) and downstream (DW, green) reporter genes. The four features selected in our best quantitative model of termination efficiencies (main text), numbered by decreasing importance (grey regions: 1 = TTHP_utail_score; 2 = hp_norm_dg; 3 = closing_stackGC; 4 = dna_dna_pattern). (B) Six terminator measurement device variants tested here. Green (G, green box) and red (R, red box) fluorescent reporter coding sequences bracket a terminator (purple T) test site flanked by RNase E sites (E, blue diamonds), RNase III sites (3, orange diamonds) or non-functional RNase III sites (*, orange diamonds).
© Copyright Policy - creative-commons
Related In: Results  -  Collection

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gkt163-F1: Architecture of a standardized genetic device for termination efficiency measurements. (A) Anatomy of an intrinsic terminator (purple) and generic architecture of processed mRNA originating from a terminator measurement device. RNase recognition sites (orange diamonds) are intended to standardize the 3′- or 5′-ends of processed mRNA encoding upstream (UP, red) and downstream (DW, green) reporter genes. The four features selected in our best quantitative model of termination efficiencies (main text), numbered by decreasing importance (grey regions: 1 = TTHP_utail_score; 2 = hp_norm_dg; 3 = closing_stackGC; 4 = dna_dna_pattern). (B) Six terminator measurement device variants tested here. Green (G, green box) and red (R, red box) fluorescent reporter coding sequences bracket a terminator (purple T) test site flanked by RNase E sites (E, blue diamonds), RNase III sites (3, orange diamonds) or non-functional RNase III sites (*, orange diamonds).
Mentions: Sequence features within intrinsic terminators have been well studied in E. coli and include a core GC-rich stem of 5–9 nt that is closed by a short 3–5 nt loop and followed by a 7–9 nt U-rich tail (Figure 1A) (10,16). A few intrinsic terminators have been extensively studied in vitro, resulting in mechanistic models for how individual sequence motifs contribute to overall termination efficiency (15,17). From these foundational studies, computational methods have been developed to identify putative terminator elements within natural DNA sequences. Such tools have improved the automated annotation of genome sequences and reshaped consideration of operon structure and chromosome organization (16,18–22). However, sequences that match putative terminator motifs are pervasive within natural genomes, and most computational predictions are not validated experimentally, thereby hindering the iterative development of improved terminator identification tools.Figure 1.

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