Characterization of 582 natural and synthetic terminators ...10.1038/nmeth.2515... · 1...

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Characterization of 582 natural and synthetic terminators and quantification of their design constraints Ying-Ja Chen1, Peng Liu1, Alec A.K. Nielsen1, Jennifer A.N. Brophy1, Kevin Clancy2, Todd Peterson2, and Christopher A. Voigt1 1 Synthetic Biology Center, Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA 2 Synthetic Biology Research & Development, Life Technologies, Carlsbad, CA 92008, USA Correspondence and requests for materials should be addressed to C.A.V. ([email protected]). Supplementary Item Title or Caption Page

Supplementary Figure 1 The terminator strengths measured for the natural and synthetic libraries. 3

Supplementary Figure 2 Potential mechanisms that complicate the measurement of terminator strength. 6

Supplementary Figure 3 GFP expression for the complete natural and synthetic terminator libraries. 7

Supplementary Figure 4 Measured fluorescence for terminators with abnormal GFP induction. 8

Supplementary Figure 5 Measured fluorescence for terminators with abnormal RFP induction is shown. 9

Supplementary Figure 6 RNase E sites were added to the plasmid construct as insulators for the terminator assay. 10

Supplementary Figure 7 The impact of including RNase E sites as spacers is shown. 11

Supplementary Figure 8 Terminator strength is not correlated with ΔGH or the length of the hairpin. 12

Supplementary Figure 9 Sequence trends for the region downstream of the U-tract are shown. 13

Supplementary Figure 10 Terminator strength is shown as a function of ∆GBubble.

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Supplementary Figure 11 Terminator strength is not correlated with loop volume. 15

Supplementary Figure 12 The von Hippel model shows moderate correlation with TS. 16

Supplementary Figure 13 Experimentally measured terminator strength is compared with d from the Thermes model. 17

Nature Methods: doi:10.1038/nmeth.2515

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Supplementary Figure 14 The strengths of terminators compared in the forward and reverse direction. 18

Supplementary Figure 15 Terminator strength is shown as a function of the activity of the upstream promoter. 19

Supplementary Figure 16 The strengths of terminators in Synthetic Library #1 are shown. 20

Supplementary Figure 17 The strengths of terminators in Synthetic Library #2 are shown. 21

Supplementary Figure 18 The secondary structure pheA-1 terminator can form a pseudoknot with the downstream sequence. 22

Supplementary Figure 19 A schematic is shown to illustrate the kinetic model of termination. 23

Supplementary Figure 20 The sensitivity of the fit to changes in the parameters is shown. 24

Supplementary Figure 21 The sequence homology of the new strong terminators is shown. 25

Supplementary Figure 22 Terminator diversification decreases the rate of homologous recombination in genetic circuits. 26

Supplementary Figure 23 The plasmid map of the pGR** plasmid used for measuring terminator strength is shown. 27

Supplementary Table 1 Composition of the Terminator Library 28 Supplementary Tables 2–4 Description of Columns in Supplementary tables 2–4 29

Supplementary Note 1 Library of Terminators 31

Supplementary Note 2 Complicating Effects in Measuring Terminator Strength 32

Supplementary Note 3 Additional Model Parameters Evaluated 34

Supplementary Note 4 The Strength of Terminators in the Forward and Reverse Direction 37

Supplementary Note 5 The Impact of Promoter Strength on Terminator Strength 38

Supplementary Note 6 Design and Characterization of Synthetic Terminators 39

Supplementary Note 7 Secondary Structure of the Strong PheA-1 Terminator (Scaffold #1) 40

Supplementary Note 8 Biophysical Model of Transcriptional Termination 41

Supplementary Note 9 Analysis for Homologous Recombination in Strong Terminators 45

Supplementary Note 10 Recombination Experiment 46 Supplementary Note 11 Plasmid Information 47 Supplementary Note 12 Supplementary References 49


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Supplementary Figure 1: The terminator strengths measured for the natural and synthetic libraries.


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Supplementary Figure 1 (previous pages): The terminator strengths measured for the natural (a) and synthetic (b) libraries. The data and sequences for each terminator are provided in Supplementary Tables 2–4. Commonly used terminators from the Registry of Standard Biological Parts are shown in blue. Terminators measured in the reverse orientation are indicated with a red “–R.” In (b), the white bars are the scaffolds used to construct synthetic terminators. For the first and second library, the naming convention for synthetic terminators is LxUyHz, where L is the library number, H is the hairpin number, and U is the U-tract number (corresponding to Supplementary Table 3). For the third library, it is LxSyPza, where S is the scaffold, P indicates variant a in region z that was changed (Supplementary Table 3). Synthetic terminators lacking a bar were inactive (TS < 1). Inactive natural terminators are not shown. Error bars are standard deviations calculated from at least three measurements performed on different days.


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Supplementary Figure 2: Potential mechanisms that complicate the measurement of terminator strength.

Supplementary Figure 2: Potential mechanisms that complicate the measurement of terminator strength. (a) Changes in the 3’-end of the mRNA of GFP can impact degradation. This will lead to a change in GFP, but not impact RFP. (b) A promoter can arise at the interface of the terminator and the downstream sequence of the reporter construct (or just arise in the putative terminator being measured). This will lead to an increase in RFP, whether or not the upstream promoter is being induced. (c) Changes in the secondary structure due to different terminator sequences impact the RFP RBS. (d) The terminator sequence leads to less translational coupling from the expression of GFP.


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Supplementary Figure 3: GFP expression for the complete natural (a) and synthetic (b) terminator libraries.

Supplementary Figure 3: GFP expression for the complete natural (a) and synthetic (b) terminator libraries. Dark turquoise bars indicate the expression of GFP through the addition of 10 mM arabinose; light turquoise bars are the basal expression in the absence of inducer. The solid, dash, and red dashed lines show the average and one or two standard deviations of the fluorescence across all terminators after removal of the two terminators. The data represents the average of 3-6 experiments performed on different days.


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Supplementary Figure 4: Measured fluorescence for terminators with abnormal GFP induction.

Supplementary Figure 4: Measured fluorescence for terminators with abnormal GFP induction. Fluorescence from GFP (turquoise bars) and RFP (red bars) are measured when PBAD is uninduced (light colors) and induced with 10 mM L-arabinose (dark colors). Data are shown for the cells without the reporter plasmid (DH5α, no plasmid), reporter plasmid lacking a terminator (Control plasmid) and containing the BBa_B0010 terminator as references. Error bars are standard deviations calculated 2–3 measurements performed on different days.


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Supplementary Figure 5: Measured fluorescence for terminators with abnormal RFP induction is shown.

Supplementary Figure 5: Measured fluorescence for terminators with abnormal RFP induction is shown. Typical measured fluorescence from the reporter construct with no terminator (Control) and BBa_B0010 are included. (a) The GFP is shown for each terminator when induced (dark turquoise) and uninduced (light turquoise). (b) The RFP is shown for each terminator when induced (dark red) and uninduced (light red). The error bars are the standard deviations calculated from three measurements performed on different days.


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Supplementary Figure 6: RNase E sites were added to the plasmid construct as insulators for the terminator assay.

Supplementary Figure 6: RNase E sites were added to the plasmid construct as insulators for the terminator assay (Fig. 1a). RNase E sites (TATTATTTGTATTGATCTCCT) are added in the junctions between the fluorescent proteins and the terminator. A hairpin (TACTATCTCTCGAGAGATTAGTACCTTTGGAGATC) is added between the second RNase E site and the RBS of the RFP. PBAD, promoter inducible by L-arabinose; RBS, ribosome binding site; GFP, green fluorescent protein; RFP, red fluorescent protein.


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Supplementary Figure 7: The impact of including RNase E sites as spacers is shown.

Supplementary Figure 7: The impact of including RNase E sites as spacers is shown. (a) Fluorescence from GFP and RFP for plasmids containing RNase E. Terminator names are shown on the bottom. (b) Fluorescence from GFP and RFP for plasmids without RNase E. Both GFP and RFP increase at least 2-fold upon induction. Data are shown for uninduced (light colors) and induced (dark colors) conditions. Error bars are standard deviations calculated from three measurements performed on different days.


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Supplementary Figure 8: Terminator strength is not correlated with ΔGH or the length of the hairpin.

Supplementary Figure 8: Terminator strength is not correlated with ΔGH or the length of the hairpin. (a) The free energy of hairpin folding ΔGH is plotted against TS for all natural hairpins. The line shows a fit to an exponential curve (R2 = 0.22). (b) The average ΔGH is plotted against the average TS for the library. (c) The average length of the hairpin (black diamonds) and the loop (gray squares) is plotted as a function of the average TS. (d) The average number of stem mismatches is plotted versus TS. (e) The terminator strength is plotted versus ΔGH/nH for the library of natural terminators. (R2=0.054) (f) The average ΔGH/nH is shown as a function of the average TS in the library as a stringency cut-off is applied. The left most point represents the complete library and the right most represents the strongest 15 terminators.


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Supplementary Figure 9: Sequence trends for the region downstream of the U-tract are shown.

Supplementary Figure 9: Sequence trends for the region downstream of the U-tract are shown. (a) The free energy of DNA denaturation in the positions downstream of the U-tract is plotted. (b) The %GC observed for strong, all, and weak terminators are shown for the positions downstream of the U-tract. The black line indicates the expected value of 50%. Legend: strong terminators (TS > 40, blue diamonds), all terminators (red squares) and weak terminators (TS < 3, green triangles).


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Supplementary Figure 10: Terminator strength is shown as a function of ∆GBubble.

Supplementary Figure 10: Terminator strength is shown as a function of ∆GBubble. The average ΔGBubble is plotted against the average TS for the library as the stringency of a cut-off is increased. The left most point represents the complete library and the right most point is the strongest 15 terminators.


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Supplementary Figure 11: Terminator strength is not correlated with loop volume.

Supplementary Figure 11: Terminator strength is not correlated with loop volume. The average terminator strength for hairpin loop sequence is plotted against its volume. Since one loop sequence can appear in multiple structures and therefore correspond to different volumes, both the average and the standard deviation of loop volume are plotted.


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Supplementary Figure 12: The von Hippel model shows moderate correlation with TS.

Supplementary Figure 12: The von Hippel model shows moderate correlation with TS. (a) The measured TS for all (natural: black; synthetic: red) terminators are plotted against (∆G0

f,complex)max derived by von Hippel and Yager1. The fit to the y=x line yields an R2 of 0.20. (b) As a comparison, the measured TS for all (natural: black; synthetic: red) terminators are plotted against ∆GU (equation (1)) in our model. The fit to the y=x line yields an R2 of 0.17.


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Supplementary Figure 13: Experimentally measured terminator strength is compared with d from the Thermes model.

Supplementary Figure 13: Experimentally measured terminator strength is compared with d from the Thermes model. The line shows a best fit of the natural terminators to an exponential curve (R2 = 0.11). Natural (black) and synthetic (red) terminators are shown.


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Supplementary Figure 14: The strengths of terminators compared in the forward and reverse direction.

Supplementary Figure 14: The strengths of terminators compared in the forward and reverse direction. (a) The ECK120010863 terminator sequence is shown to illustrate the similarities and differences between the forward and reverse direction of a terminator. The hairpin structure and the flanking U-tract and A-tract are shown. Note that there is a bulge in the hairpin in the reverse direction. (b) The terminator strength measured from the reverse direction vs. the forward direction. Error bars are standard deviations calculated from three measurements performed on different days.


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Supplementary Figure 15: Terminator strength is shown as a function of the activity of the upstream promoter.

Supplementary Figure 15: Terminator strength is shown as a function of the activity of the upstream promoter. (a) Induction curves for single terminators are shown. The terminators are ECK120033736 (orange triangles), BBa_B0010 (black diamonds), ECK120015444 (red squares), ECK120010840 (green circles), and ECK120029341 (blue diamonds). (b) Induction curves for double terminators are shown. The single BBa_B0010 terminator (black diamonds) is shown as a reference. Terminators are BBa_B0010+BBa_B1006 (brown squares), BBa_B0015 (BBa_B0010+BBa_B0012, cyan triangles), and BBa_B0014 (BBa_B0012+BBa_B0011, purple circles). Data without adding inducer is shown on the y-axis. Error bars are standard deviations calculated from three measurements performed on different days.


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Supplementary Figure 16: The strengths of terminators in Synthetic Library #1 are shown.

Supplementary Figure 16: The strengths of terminators in Synthetic Library #1 are shown. In this library, terminators were measured in a 96-well plate format combining a different hairpin sequence in each column and a U-tract sequence in each row. The sequences are listed and the brackets indicate where the loop of the hairpin begins and ends. The A-tract sequence for all terminators is “AAGAAUUC”, which is the sequence in the plasmid backbone immediately upstream of the terminator. Gray wells indicate missing data due to cloning errors. The data shown is the average strength calculated from three experiments on different days (with an average standard deviation of 19%).


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Supplementary Figure 17: The strengths of terminators in Synthetic Library #2 are shown.

Supplementary Figure 17: The strengths of terminators in Synthetic Library #2 are shown. In this library, terminators were measured in a 96-well plate format. For each well position, the terminator sequence combines the hairpin stem listed on the bottom of the corresponding column with the hairpin loop and U-tract sequence listed on the left of the corresponding row. The sequences are listed and the brackets indicate where the loop of the hairpin begins and ends. The A-tract sequence for all terminators is “AAGAAUUC”, which is the sequence in the plasmid backbone immediately upstream of the terminator. The hairpin stem sequences that derived from natural terminators are shown in red. The hairpin stem sequences in columns 4, 8, and 11 were modified from columns 5, 9, and 12, respectively (changes underlined). The hairpin stem in column 4 is the reverse sequence of column 5. In column 8, an A-U base-pair is modified to a G-C base-pair. In column 11, an AA-GC mismatch was modified to an AA-UU base-pair. The average ΔGH from left to right are -13.53, -17.63, -15.63, -14.34, -14.45, -14.03, -12.23, -19.70, -17.70, -19.63, -20.93, and -15.63 kcal/mol. The data shown is the average strength calculated from four experiments on different days (with an average standard deviation of 34%).


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Supplementary Figure 18: The secondary structure pheA-1 terminator can form a pseudoknot with the downstream sequence.

Supplementary Figure 18: The secondary structure pheA-1 terminator can form a pseudoknot with the downstream sequence. Secondary structure is shown for pheA-1 and blue lines show the base pairing between the hairpin loop and the sequence downstream of the U-tract that forms the pseudoknot. This is the fourth structure that is likely to form as predicted by KineFold2. The free energy is 18.5 kcal/mol.


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Supplementary Figure 19: A schematic is shown to illustrate the kinetic model of termination.

Supplementary Figure 19: A schematic is shown to illustrate the kinetic model of termination. The mechanism follows the kinetic steps of the hybrid-shearing model. When the RNAP elongation complex arrives at the terminator, the hairpin forms at kinetic rate constant k1. Then, the U-tract is pulled from the DNA at rate k4. This is taken to be the irreversible step where the complex commits to termination, after which the DNA duplex reforms and the RNAP dissociates. If the hairpin forms too slowly or the RNAP progresses before the U-tract dissociates, then the mRNA is elongated and termination does not occur. The rate of elongation competing with folding is k2 and U-tract dissociation is k3.


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Supplementary Figure 20: The sensitivity of the fit to changes in the parameters is shown.

Supplementary Figure 20: The sensitivity of the fit to changes in the parameters is shown. Here we plot the R2 versus B1 (a, left) β1 (a, right), B4 (b, left) and β4 (b, right) for the model while varying one fit parameter at a time. The points on each graph show the final parameter reported for the model.


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Supplementary Figure 21: The sequence homology of the new strong terminators is shown.

Supplementary Figure 21: The sequence homology of the new strong terminators is shown. Each entry in this matrix is the length of the maximal homologous sequence between the terminator pair in the corresponding row and column. Homologous sequences >25 bp are shown in red. The upper left triangle of the matrix shows the 39 new strong terminators with diverse sequences and can be used in the same construct.


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Supplementary Figure 22: Terminator diversification decreases the rate of homologous recombination in genetic circuits.

Supplementary Figure 22: Terminator diversification decreases the rate of homologous recombination in genetic circuits. (a) Restriction digests showing the size of the genetic circuit sequence after evolution in the absence of 3OC6HSL for seven days. The repeated-terminator construct exhibits a high rate of recombination, whereas the re-engineered version primarily retains the full-length circuit. (b) Flow cytometry histograms showing the fluorescent population profile over the course of the three days for the repeated-terminator and re-engineered NOT-gates grown in 3OC6HSL. The repeated terminator construct population rapidly increases it’s fluorescence as the ButR repressor is eliminated via recombination, while the re-engineered version shows repression over three days.


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Supplementary Figure 23: The plasmid map of the pGR** plasmid used for measuring terminator strength is shown.

Supplementary Figure 23: The plasmid map of the pGR** plasmid used for measuring terminator strength is shown. For naming purposes, the ** is replaced with the name of the terminator to be tested. The plasmid backbone was constructed by rearranging each component from pSB1A10. The terminators were annealed oligonucleotides inserted between the EcoRI and SpeI restriction sites. Other features are described in the text.


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Supplementary Table 1: Composition of the Terminator Library Number Source Forward Reverseb Total RegulonDB 199 89 288 Yager & von Hippel 17 0 17 Registry 11 1 12 Natural (Total)a 227 90 317 Synthetic (Total) 265 0 265 Total 582 aConsisting of the RegulonDB, Yager, and Registry terminators. bReverse complementary sequences of terminators


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Supplementary Tables 2–4 Supplementary Tables 2–4 provide the sequences, data, and calculated parameters for the natural, synthetic, and removed terminators in the library. The following is a description of the value in each column. 1. Name: These terminators come from three sources. The terminators in

RegulonDB and the Registry of Standard Biological Parts appear as they are named in those databases. Other terminators were extracted from the literature compiled by Yager and von Hippel and named according to the transcription unit that they regulate.

2. Recombination-resistant strong terminators: Those terminators marked with an “X” in this column are both strong (TS > 50) and share less than a 25 bp contiguous stretch of perfect sequence identity (Supplementary Note 9).

3. Recombination-resistant strong-medium terminator: Those terminators marked with an “X” in this column are strong-medium (TS > 10) and share less than 25 bp contiguous stretch of perfect sequence identity (Supplementary Note 9).

4. Scaffold 1: Synthetic terminators built based on the pheA-1 terminator are marked with an “X” in this column. The strengths of these terminators are higher than expected from the biophysical model and may be the result of translational effects, rather than termination efficiency (see main text and Supplementary Note 7).

5. Transcription unit: The terminator is found at the end of this gene or operon. 6. Sequence: The complete sequence inserted into the reporter plasmid for

measurement. 7. Average uninduced GFP: Fluorescence of GFP measured by flow cytometry

without induction by L-arabinose. Averages are taken from at least three measurements from different days.

8. Average uninduced RFP: Fluorescence of RFP measured by flow cytometry without induction by L-arabinose. Averages are taken from at least three measurements from different days.

9. Average induced GFP: Fluorescence of GFP measured by flow cytometry with induction by 10 mM L-arabinose. Averages are taken from at least three measurements from different days.

10. Average induced GFP: Fluorescence of RFP measured by flow cytometry with induction by 10 mM by L-arabinose. Averages are taken from at least three measurements from different days.

11. Average GFP/RFP: The average of the ratio of induced GFP to induced RFP. Averages are taken from at least three measurements from different days.

12. Average terminator strength: Average terminator strength calculated as induced GFP/induced RFP normalized by control (plasmid pGR with no terminator inserted) measured on the same day. In half the cases, the control was not run on the same day and the average GFP/RFP ratio of the control was used for normalization. Averages are taken from at least three measurements from different days.

13. Standard deviation uninduced GFP: Standard deviation of GFP fluorescence


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measured without induction taken from at least three measurements from different days.

14. Standard deviation uninduced RFP: Standard deviation of RFP fluorescence measured without induction taken from at least three measurements from different days.

15. Standard deviation uninduced GFP: Standard deviation of GFP fluorescence measured with induction taken from at least three measurements from different days.

16. Standard deviation uninduced RFP: Standard deviation of RFP fluorescence measured with induction taken from at least three measurements from different days.

17. Standard deviation uninduced GFP/RFP: Standard deviation of induced GFP/induced RFP taken from at least three measurements from different days.

18. Standard deviation of terminator strength: Standard deviation of induced GFP/induced RFP taken from at least three measurements from different days normalized by the average GFP/RFP ratio of the control.

19. A-tract: The 8-bp sequence immediately upstream of the predicted hairpin. 20. Hairpin: The predicted hairpin sequence within the terminator sequence. This

is left as blank if no hairpin structure can be predicted within the terminator sequence.

21. Structure: The predicted secondary structure of the hairpin in dot-brackets format.

22. Loop: The hairpin loop sequence. 23. U-tract: The 12-bp region immediately downstream of the hairpin is the U-tract.

While the 12 bp region is included here, only the first 8 bp are used to calculate GU.

24. ΔGU: ΔGU described in the main text (equation (1)). 25. ΔGL: ΔGL described in Supplementary Note 3. 26. ΔGH: ΔGH described in Supplementary Note 3. 27. ΔGA: ΔGA described in Supplementary Note 3 (equation (S8)). 28. ΔGB: ΔGB described in Supplementary Note 3 (equation (S7)). 29. Predicted TS: The terminator strength predicted by the model (equation (2)).


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Supplementary Note 1: Library of Terminators

Sources of terminators The first step of designing the library was to collate a set of putative terminator sequences. These were obtained primarily from RegulonDB 6.4, which includes 217 terminators identified by biochemical methods3. The sequences (labeled with an ECK prefix) were defined as in the database, including the hairpin and 10 bp of up and downstream sequence. A second source of terminators is a large set compiled by Yager and von Hippel4, of which 19 are different from RegulonDB. These are named based on their associated operon and their sequences include the start of the hairpin to the last U (7-15 bp downstream). Terminators can be bidirectional, meaning that they can reduce RNAP flux in both directions. To include measurements of both orientations, a subset of 92 terminators from RegulonDB is included in the reverse direction (labeled with a suffix -R). Finally, a small set of terminators is included that are commonly used in the field of synthetic biology, encompassing 14 from the Registry of Standard Biological Parts (BBa_B0010-11, BBa_B0021, BBa_B0051-54, BBa_B0057, BBa_B0060-62, BBa_J34813, BBa_J61053, BBa_K088008)5. A small subset of terminators was removed from analysis due to abnormal measured results (summarized in Supplementary Note 2 and Supplementary Table 4). The resulting terminators analyzed are summarized in Supplementary Table 1. A full list of all of the terminators and their sequences is available in Supplementary Tables 2–4. All terminators listed in the natural library are annotated as E. coli intrinsic terminators. All terminators listed as reverse terminators are the reverse complement sequences of terminators.

Measured terminator strength In our reporter construct, an arabinose-inducible PBAD promoter was placed upstream of the green fluorescent protein gene (gfp). Transcripts were produced that either contain just gfp or an operon containing both gfp and the gene encoding red fluorescent protein (rfp). Stronger terminators will reduce the fraction of transcripts that contain both reporters and their ratio can be used to calculate the terminator strength,

𝑇𝑆 = 11−𝑇𝐸

= �⟨𝐺𝐹𝑃⟩𝑇𝑒𝑟𝑚⟨𝑅𝐹𝑃⟩𝑇𝑒𝑟𝑚� �⟨𝐺𝐹𝑃⟩0⟨𝑅𝐹𝑃⟩0

�−1

, (S1)

where the averages are of populations measured by flow cytometry and the subscript Term refers to the measurements when the terminator is present and 0 refers to the measurements of the control. The control is defined as a reporter construct lacking a terminator sequence. Following this definition, no termination is observed when TS = 1. Note that TS is simply related to the “terminator efficiency” (TE) that is commonly reported as a %4. Here, we use the inverse of this function to emphasize differences in between very strong terminators. In essence, it reflects the fold to which a terminator will reduce the transcription of a downstream gene. The terminator strength of 317 natural, 265 synthetic and 22 removed terminators are shown in Supplementary Fig. 1 and listed in Supplementary Tables 2–4.


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Supplementary Note 2: Complicating Effects in Measuring Terminator Strength

Potential mechanisms for interference A challenge in assaying a large library of terminators is that the genetic context of the reporter plasmid potentially impacts the measurement of terminator strength. This interference can cause the miscalculation of the strength due to effects not related to transcriptional termination. Some modes of interference can be detected and used to eliminate terminators from the library.

There are several potential mechanisms by which the terminator strength can be miscalculated (Supplementary Fig. 2). First, different terminators will lead to the fusion of varying hairpins to the 3’-end of the mRNA that is released after termination. This can impact the stability of this transcript, which only includes gfp6. This leads to a different level of GFP expression, whereas it would otherwise be expected to be the same across all terminators. Second, the terminator can encode a cryptic promoter or cause a promoter to emerge at its upstream or downstream junction of the reporter plasmid7. This could be especially problematic due to the presence of U-tracts, which have the potential to be similar to the AT-rich box of a constitutive promoter. This would lead to the overexpression of RFP in both the induced and the uninduced data. Third, the terminator sequences can impact the secondary structure of the mRNA. This could have a number of effects, including the exposure or occlusion of the RFP RBS, which could change the expression level of the RFP8. In our construct, this is mitigated by the presence of strong and clearly defined hairpins in the terminators and a 38 bp spacer between the end of the terminator and the start of RFP. Fourth, there may be translational coupling between the GFP and the RFP9. This coupling may be impacted by the terminator sequence. A change in the coupling would be indiscernible from transcriptional termination using the fluorescence assay data alone.

Terminators that exhibit unusual expression patterns Upon induction, the GFP expression of all of the terminators should be approximately equal, which was observed in most cases (Supplementary Fig. 3). When the GFP fluorescence in the induced state is lower than two times the standard deviation (Induced GFP < 5000), the terminator is removed from analysis. Only two terminators were removed for this reason, both of which are reverse complement of terminators (ECK120035133-R, ECK120010871-R) (Supplementary Fig. 4).

The level of RFP expression should depend on the strength of the terminator. When the terminator is weak, RFP is highly expressed and shows similar fold-induction as GFP (Supplementary Fig. 5 second column, Control). When the terminator is strong, the RFP expression is much lower than control, but still shows significant induction (Supplementary Fig. 5 third column, BBa_B0010). For some terminators, we noticed that the RFP expression is almost the same in both the induced and the uninduced states. In these cases, GFP remains inducible. We eliminated those terminators that have a ratio of uninduced RFP/induced RFP > 0.50 (Supplementary Fig. 5). This could be due to a constitutive promoter that is either internal to the terminator or emergent at the junctions (Supplementary Fig. 2b). Twenty one natural terminators and one reverse terminator were removed for this reason (Supplementary Table 4).

In summary, we measured 606 terminators, including 248 natural, 265 synthetic, and 93 reverse terminators. Two reverse terminators were removed due to the uninducibility of GFP. 21 natural and 1 reverse terminators were removed due to high


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ratio of uninduced-to-induced RFP. Together, the library was reduced to 227 natural, 265 synthetic, and 90 reverse terminators (582 total).

RNase E sites as insulators Kelly and co-workers previously proposed to add RNase E sites up- and downstream of the terminator6. The intent is to cleave the mRNA before and after the terminator hairpin, thus eliminating its impact on the mRNA stability of the fluorescent protein reporters. At the beginning of this project, we first used a reporter plasmid that contained RNase E sites that had been previously designed to characterize terminator sequences (Supplementary Fig. 6)6. These sites had been included to eliminate potential interference due to changes in mRNA degradation rates (Supplementary Fig. 2a). In our hands, we found that the inclusion of these sites makes the second gene in the operon uninducible (Supplementary Fig. 7a). It does not respond to the induction of the upstream promoter (PBAD). This is in contrast for the first gene, which responds normally. We found that this effect occurred irrespective of which reporter gene appears first (not shown). It may be that the introduction of the AT-rich RNaseE sites is prone to generating a constitutive promoter (Supplementary Fig. 2b), but this is not an effect that we separately confirmed.


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Supplementary Note 3: Additional Model Parameters Evaluated

Parameters related to the hairpin Hairpin is a distinct feature for terminators. We first evaluate if the free energy of hairpin folding ΔGH is correlated with TS (Supplementary Fig. 8a). Surprisingly, TS shows no correlation with ΔGH. However, there is a general trend for strong terminators to have stronger hairpins with lower ΔGH (Supplementary Fig. 8b). When we evaluate the trend for the length of the hairpin or the hairpin loop, we found no trend relating to TS (Supplementary Fig. 8c). However, mismatches in the stem of the hairpin are unfavorable and occur very rarely in strong terminators (Supplementary Fig. 8d).

The free energy of hairpin formation ΔGH normalized by hairpin length nH. Thermes and co-workers also found that ΔGH does not correlate with strength, but they found improvement when they normalize the free energy by the length of the hairpin nH. This penalizes long hairpins, which are less observed in natural terminators. We evaluated the correlation with terminator strength and did not find an improvement over ΔGH (Supplementary Fig. 8e and 8f). Moreover, several strong terminators in our library have hairpins with long stems (ECK120029600, 21 bp; BBa_B0010, 14 bp).

Sequences downstream of the U-tract The sequence downstream of the U-tract has been observed to be important for efficient termination, especially for terminators with weak U-tracts10. This sequence dependency may be related to the closing of the DNA bubble. Here, we calculate the free energy of DNA denaturation ΔGDNA:DNA in positions 9-20 (Supplementary Fig. 9a) to examine if the closing of the DNA bubble is a contributing term. ΔGDNA:DNA is calculated by the nearest-neighbor thermodynamic parameters11 at the respective position. We found no correlation between ΔGDNA:DNA in positions 9-15 and TS. The high %GC in weak terminators is likely the result of our measurement construct, which has a high %GC in the plasmid sequence immediately following the terminator insert position (Supplementary Fig. 9b).

Landick and co-workers suggest that besides the hybrid-shearing mechanism, there may be forward-translocation in terminators with imperfect U-tracts, supported by the high %AT in the +10-12 positions12. These observations explain why natural terminators with imperfect U-tracts can still terminate transcription efficiently. In our library, many terminators were designed to be extremely strong. In these strong terminators, it is possible that the perfect U-tract and the high %AT in the downstream positions allow both hybrid-shearing and forward-translocation mechanisms to exist for the same terminator, which makes the terminator extremely strong.

The free energy of DNA bubble formation Transcription elongation requires that a transcription bubble be opened. This may contribute to the overall stability of the transcription elongation complex and its tendency to terminate transcription or continue to elongation. We calculated the free energy of bubble formation ΔGBubble by considering the 17 bp region encompassing the U-tract from -5 to +12, where +1 is the first position in the U-tract. ΔGBubble is calculated according to the following:


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∆𝐺𝐵𝑢𝑏𝑏𝑙𝑒 = �∆𝐺𝐷𝑁𝐴:𝐷𝑁𝐴(𝑛𝑖,𝑛𝑖+1) + 0.5∆𝐺𝐷𝑁𝐴:𝐷𝑁𝐴(𝑛−6,𝑛−5) + 0.5∆𝐺𝐷𝑁𝐴:𝐷𝑁𝐴(𝑛12,𝑛13)11

𝑖=1

(S2) where the disruption of the terminal base-stacking are weighted by 0.54. There is no correlation between ∆GBubble and terminator strength (Supplementary Fig. 10).

The volume of the hairpin loop The volume of the hairpin loop could impact the terminator strength because the hairpin must form within the RNA exit channel of RNAP and there may be spatial constraints that prevent hairpins with larger loops to form13,14. While related, the volume is not entirely dictated by the length of the loop. The crystal structures of many RNA hairpins have been solved and compiled in the RLooM database15. For each hairpin loop, the corresponding sequence is identified in RLooM to obtain the atomic coordinates for the three-dimensional structure. Based on this, the atomic volume of the loop is calculated using the StrucTools webserver with the “Voronoi Volume (Gerstein)” option16. Because not all hairpin loop structures have been identified, only the data for the 89 terminators whose loop sequence corresponds to solved structures were analyzed (Supplementary Fig. 11). A few hairpin loops with very large volumes do have low TS. However, there are only a few data points above 1200 Å3. Four hairpins have large loops and large volumes (BBa_J61053, ECK120010843, ECK120033127, and ECK120051408, 5-bp loops).

The von Hippel Model Yager and von Hippel proposed a terminator model based on the assumption that the dissociation of the transcriptional elongation complex (the RNAP bound to DNA and the mRNA transcript) is at thermal equilibrium with respect to the time scale of transcription1,4. According to equation (8) in von Hippel and Yager1, termination efficiency TE is calculated as 𝑇𝐸 = 1

1+𝑒−∆(∆𝐺‡)𝑅𝑇

(S3)

where ∆(∆G‡) is the difference in activation free energy barrier for elongation and termination. When TE = 0.5, ∆(∆G‡) = 0, which also coincides with the maximal free energy of formation for the elongation complex (∆G0

f,complex)max when it is -2 kcal/mol. ∆G0

f,complex is calculated as equation (4) in the same article1.

∆𝐺𝑓,𝑐𝑜𝑚𝑝𝑙𝑒𝑥0 = ∆𝐺𝐵𝑢𝑏𝑏𝑙𝑒0 + ∆𝐺𝑈0 + ∆𝐺𝑃𝑜𝑙0 (S4)

Here, ∆G0

U, ∆G0bubble, and ∆G0

pol are the standard free energies of formation for the RNA-DNA hybrid, DNA transcription bubble opening, and polymerase binding to DNA, respectively. At a terminator site, ∆G0

U and ∆G0bubble can be calculated using equations

(1) and (S2), which were calculation methods adapted from von Hippel and Yager1,4. ∆G0

pol is adapted from the estimation by von Hippel and Yager1 to be -32 kcal/mol. We calculate the (∆G0

f,complex)max for all 582 terminators measured using equation (S4) and plot TS against it (Supplementary Fig. 12). The correlation with the measured strengths is R2 = 0.20, which is comparable to our model when only ∆GU is considered (R2 = 0.17).


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The Thermes Model Thermes and co-workers developed an empirical model of transcriptional termination17. It is based on the derivation of a “rule” to distinguish terminators from non-terminator controls for E. coli. The model is based on two parameters: Uscore and ∆GH/nH. The term Uscore accounts for the contribution from the U-tract. This was determined to be a sum over the first 15 base pairs after the hairpin and is set up such that the contributions of neighboring nucleotides are multiplied, 𝑈𝑠𝑐𝑜𝑟𝑒 = ∑ 𝑥𝑖15

𝑖=1 , where (S5)

𝑥𝑖 = �0.9𝑥𝑖−1, if i-th nucleotide is U0.6𝑥𝑖−1, if i-th nucleotide is not U

and

𝑥1 = �0.9, if first nucleotide is U

0.6, if first nucleotide is not U . This produces a range of Uscore from 1.5 to 7.15. The Thermes model also includes a term for the free energy for the formation of the hairpin. This was calculated by FOLD18, which is an earlier version of Mfold. The parameters used in this model were from Freier et al.19, except that the authors manually assigned a free energy contribution of -1 kcal/mol for the two special loops, GAAA and UUCG. They found that there was no correlation between the terminator efficiency and the free energy of hairpin formation so they divided by hairpin length (∆GH/nH). From this, they developed an empirical equation 𝑑 = 96.59 −∆𝐺𝐻

𝑛𝐻+ 18.16𝑈𝑠𝑐𝑜𝑟𝑒 − 116.87 , (S6)

where terminators are defined as having d > 0 and terminator strength should be predictable by d. The correlation with our terminator measurements is shown in Supplementary Fig. 13.


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Supplementary Note 4: The Strength of Terminators in the Forward and Reverse Direction

Many terminators can terminate transcription from both directions4,20,21. Bi-directional terminators often have an “A-tract” when the sequence is viewed in the forward direction. The A-tract functions as a U-tract when terminating transcription from the reverse direction. This creates a U-tract that is often imperfect. The hairpin is similar in both orientations, and will sometimes yield a similar ∆GH, but the sequence of the loop region and the folding kinetics will be different2. Also, if there are any G-U base pairs or mismatches in the stem region, these will become C-A mismatches in the reverse terminator.

To investigate the impact of directionality on terminator strength, 80 natural terminators were measured in both the forward and the reverse orientations (Supplementary Table 2, Supplementary Fig. 14). As expected, the terminator strength is systematically higher in the forward direction. There is only a weak correlation between the strengths in either direction, adding evidence to the observation that ∆GH does not significantly contribute to terminator strength. Only three terminators were strong (TS > 10) in both directions (ECK120010858, ECK120011170 and ECK120026481).


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Supplementary Note 5: The Impact of Promoter Strength on Terminator Strength

It is unclear how the strength of the upstream promoter affects the terminator strength. There is some evidence in the literature that the identity and strength of promoters could impact the efficiency of a terminator22-24. In theory, higher RNAP fluxes could impact terminator strength by increasing the effective force that is being generated by the RNAP closest to the terminator25. For a subset of terminators, the strength was measured as a function of the induction of the PBAD promoter (Supplementary Fig. 15). For single terminators, the measured TS of strong terminators goes up ~3-fold as a function of promoter activity. This effect is more pronounced for double terminators, which vary ~7-fold as a function of promoter activity. The commonly-used BBa_B0015 double terminator shows an interesting step change in activity where it is weak for low promoter activities, but medium-strong at high promoter activities.


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Supplementary Note 6: Design and Characterization of Synthetic Terminators

We designed three synthetic terminator libraries. The first library was built by combining eight U-tracts and twelve hairpins, where the intent of selecting the sequences was to aid the parameterization of the model (Supplementary Fig. 16). The majority of these terminators were weak (TS < 10) and only two have TS > 20. A second library was designed to further dissect the effects of base composition and position of imperfect U-tracts, as well as properties of the hairpin. A combination of different U-tracts with at least four uridines was combined with different hairpins, with a focus on diversifying the loop (Supplementary Fig. 17). The library yielded only modestly stronger terminators than the first library and again the U-tract had to be near perfect. The third library was designed to find strong terminators based on three known strong terminators as scaffolds and varying different sequence features (Fig. 3). Detailed description and analysis for each library is provided below or in the Main Text.

Synthetic Library #1 We designed a library of synthetic terminators by combining different hairpin and U-tracts with the intent of determining the effects of each parameter on terminator strength. In the first library, 12 hairpin sequences were designed with varying free energies and stem lengths within a range observed for natural terminators. The sequence of the loop was fixed. Eight U-tract sequences were designed to span a wide distribution of uridine residues and ΔGU. The sequences and data for the library are listed in Supplementary Table 3. The naming convention for synthetic terminators is LxUyHz, where L is the library number, H is the hairpin number, and U is the U-tract number.

The measured terminator strengths from Synthetic Library #1 are shown in Supplementary Fig. 16. U-tracts containing 3 or less uridines all yield TS ~ 1. The hairpins were designed to systematically vary the free energy of folding ∆GH. The data is too sparse with respect to good terminators to draw conclusions regarding the impact of the hairpins. One U-tract seemed to slightly increase TS across multiple hairpins, but this is likely due to a unique ability for this sequence to form a hairpin and interfere with the RBS controlling RFP. Out of this data set, only two medium-strength terminators were identified based on a perfect U-tract. It is surprising that even when a perfect U-tract is placed next to a set of good designed hairpins, most of the resulting sequences do not have significant terminator function.

Synthetic Library #2 A second library was designed to explore more detailed parameters that affect strength. Different hairpin stem sequences were selected or modified from the natural terminator library. These stems were combined with different loop regions and U-tract sequences to determine how these features impact TS when the stem sequence is fixed. The measured terminator strength from Synthetic Library #2 is shown in Supplementary Fig. 17. As expected, the strongest terminators correspond to having a perfect U-tract but, as in the first library, this is insufficient for producing a strong terminator, even when coupled with a strong hairpin. When point mutations were introduced to include stronger base pairs (column 8 vs. column 9; column 11 vs. column 12), terminator strength did not change significantly.


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Supplementary Note 7: Secondary Structure of the Strong PheA-1 Terminator (Scaffold #1)

The pheA-1 terminator is one of the strongest natural terminators in our library and also used as a scaffold for designing strong synthetic terminators. From Synthetic Library #3, we found this terminator to be the most sensitive to changes in its sequence. All changes in the loop, stem, and U-tract reduced its TS. Intriguingly, we find that this disruption in TS may be related to a pseudoknot structure that can form between the hairpin loop and the three nucleotides immediately following the U-tract.

We performed secondary structure prediction for this terminator using the KineFold webserver with default settings, except for transcription rate for co-transcriptional folding, which was set to 20 ms/nt for E. coli RNA polymerase. The prediction shows that a pseudoknot can form between the loop of the hairpin and the three nucleotides immediately following the U-tract (Supplementary Fig. 18). This structure appears in the fourth most probable folding structure as predicted by KineFold.

We speculate that the sensitivity to changes in sequence feature in this terminator may be due to disruption of this pseudoknot structure. Indeed, changes in the hairpin loop sequence disrupt the pseudoknot. Similarly, changes in the U-tract (+4bp) also remove the pseudoknot. In fact, this is the only scaffold that decreases in TS when replacing with a perfect U-tract. Changes in the hairpin stem length also reduce TS. These changes may alter the spatial orientation of the hairpin and prevent the pseudoknot from being formed quickly. Since the A-tract does not participate or interfere with the structure of the pseudoknot, it is reasonable that it is the only sequence feature that does not reduce TS significantly. In this case, the A-tract may not have a significant impact on TS.


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Supplementary Note 8: Biophysical Model of Transcriptional Termination

Identification of Terminator Sequence Features The first step towards predicting the strength of a terminator is to identify and parse those sequence features that contribute to termination (the hairpin, U-tract, etc). The steps to identify these sequences are outlined below. After these sequences are identified, the contribution of each feature can be determined using the thermodynamic expressions outlined in the main text and below. Prediction of secondary structure by KineFold RNA secondary structures were predicted using KineFold (http://kinefold.curie.fr/)2. For every terminator sequence, we performed twenty independent runs by using different random seeds and the most frequent secondary structure was chosen. If multiple secondary structures appeared at the same frequency, the one with the lowest energy was selected. The rate of transcription was selected to be 1 nt per 20 milliseconds (consistent with prokaryotic RNAP). Simulated molecular time was estimated by the server and no pseudoknots or entanglements were allowed. In the folding simulations, we added five nucleotides from the plasmid sequence to the 5’ (AAUUC) and 3’ (ACUAG) ends of terminator sequence. Identification of the U-tract, hairpin, and A-tract regions The secondary structure predicted for terminators are often hairpins that extend beyond the terminator hairpin because the upstream poly(A) sequence and the U-tract can also form base pairs. In parsing the terminator sequence, it is important that the poly(U) region is part of the U-tract and not the hairpin. In order to do so, several steps were taken to identify the U-tract once KineFold predicts a secondary structure.

Given a stemloop structure, we screen for potential U-tracts in the sequence region starting from the sixth nucleotide in the 3’-arm of the stemloop until eight nucleotides downstream of the stemloop structure. In this region, we evaluate every 8-bp sequence that begins with a U. The 8-bp sequence with the highest ∆GU (equation (2)) is selected as the U-tract. If multiple U-tracts have the same ∆GU, the one on the 5'-end is selected. If there are no 8-bp sequences that begin with a U, the 8-bp sequence immediately downstream of the stemloop is selected as the U-tract.

In some cases, multiple stemloops are predicted in a given sequence. In these cases, the U-tract is selected by the highest ∆GU in all of the possible regions. Once the U-tract is defined, the hairpin is simply the stemloop immediately 5’ to the U-tract, and the A-tract is the 8-bp sequence immediately 5’ to the hairpin. However, if no 8-bp sequence in any of the possible regions begins with a U, the most 3’ stemloop is selected as the hairpin, with the exception when that stemloop is within eight nucleotides to the 3’ end of the sequence for terminator prediction. In that case, the next most 3’ stemloop is selected as the hairpin and the U-tract and A-tract are defined as the 8-bp sequence immediately downstream and upstream of the hairpin. Energy calculation for the hairpin and A-tract Free energies for the hairpin ∆GH, base-pair stacking for each stack ni ∆GRNA:RNA(ni), and loop folding ∆GL were calculated by the Vienna RNA package version 1.8.526 using the program RNAeval (options “-v –d0”). The free energy for the stacking of the last three base stacks is calculated as: 𝛥𝐺𝐵 = ∑ ∆G𝑅𝑁𝐴:𝑅𝑁𝐴(𝑛𝑖)3

𝑖=1 . (S7)


http://kinefold.curie.fr/

42

The free energy for the A-tract ∆GA was calculated by first calculating ∆GH and

∆GHA. ∆GHA is the free energy of the structure that consists of the terminator hairpin folded as predicted by KineFold, and the eight nucleotides up- and downstream of the hairpin folded into the minimal free energy structure under the constraint that the terminator hairpin is folded into the predefined structure (predicted by KineFold). This is calculated using Vienna RNA’s RNAFold command with constraints not allowing dangling ends (options “-C –d0”). In this calculation, the structure of the hairpin region is constrained to the structure predicted by KineFold, but the up and downstream regions can fold freely. The minimal free energy calculated under this constraint is ∆GHA. The free energy for the A-tract ∆GA was calculated by the following equation. ∆GA = ∆GHA - ∆GH. (S8) Note that this is different from the difference in free energy without constraints because in the latter case, RNAFold may predict the hairpin to be part of another stemloop structure involving the upstream regions, preventing the terminator hairpin to form. However, here we are calculating the additional free energy gained from the base pairing between the A-tract and the U-tract given that the terminator hairpin has already formed.


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Calculation of terminator strengths The goal is to develop a simple model that captures how the sequence of a terminator impacts its strength. Three mechanisms have been proposed for transcriptional termination. In the “forward-translocation model,” the hairpin causes RNAP to forward translocate and this prevents the next nucleotide from polymerizing, thus causing RNAP to dissociate27,28. In the “hybrid-shearing model,” the formation of the hairpin disrupts the first few base pairs in the RNA-DNA hybrid and pulls out the U-tract from the RNAP4,25,27. Structural studies also support an “allosteric model,” where the RNA hairpin causes the polymerase to undergo a conformation change that induces the dissociation of the complex13,29,30. These models are not mutually exclusive and may all contribute to termination efficiency to differing degrees depending on the terminator and its context12,31. We describe below a kinetic model based on the hybrid-shearing mechanism.

Initially, the RNAP moves along the DNA in the form of the elongation complex (Supplementary Fig. 19). When the sequence containing the hairpin is transcribed, it has the potential to fold in the exit channel of the RNAP. If it does not fold until it is outside of the exit channel, then the RNAP will progress to elongation and termination will not occur4. When considering the rate of hairpin folding k1 for simple hairpins, the slow step has been shown to be the nucleation of the closure of the loop, after which the stem rapidly forms following a highly cooperative zipper mechanism32-36. As such, the rate can be calculated as 𝑘1 = 𝐴1𝑒−𝛽∆𝐺𝐿, (S9) where β is the inverse of the Boltzmann’s constant multiplied by temperature and A1 is a scaling constant. The mechanism is treated as a Markov chain,34 where the probability of the transition between states is calculated from the rates37. Following this approach, the probability of forming the hairpin sufficiently quickly 𝑃1 = 𝑘1

𝑘1+𝑘2 (S10)

is a function of k1 and the rate of the progression of RNAP k2. The latter rate includes the pausing that occurs due to the U-tract sequence12. In our model, this is treated as a constant and is not sequence-dependent.

Once the hairpin folds, the RNAP can continue to progress at a rate k3. The model leaves open the possibility that the hairpin affects the rate, although this is believed not to occur12 (in which case k3 = k2). Instead of progressing, the U-tract can pull off of the DNA template, thus leading to termination and the dissociation of the elongation complex. The rate k4 at which this occurs will be dependent on the sequence of the U-tract. This can be imagined as a Brownian ratchet, where the base of the hairpin and the A-tract displace the RNA U-tract from the DNA template38. The rate of displacement can be estimated by 𝑘4 = 𝐴4𝑒−𝛽(∆𝐺𝐵+∆𝐺𝐴−∆𝐺𝑈)

(S11) where A4 is a constant. It should be noted that this equation is not technically correct; rather, it captures that tighter binding to the template (more negative ∆GU) will progress more slowly and a larger binding energy to the hairpin (∆GB and ∆GA) will yield a less


44

reversible process, thus increasing the rate at which the U-tract is ratcheted from the template. The changes in free energy ∆GB (equation (S7)), ∆GA (equation (S8)), and ∆GU (equation (1)) are as described above and the main text. Once the mRNA is disrupted, the final dissociation of the RNAP and the collapse of the DNA bubble are assumed to be an irreversible event4.

Based on these rates, the probability of termination can be calculated as 𝑃𝑡𝑒𝑟𝑚 = 𝑘4

𝑘3+𝑘4𝑃1 . (S12)

The probability of termination is equivalent to the terminator efficiency, so considering equation (S1), 𝑇𝑆 = 1 + 𝑘1𝑘4

𝑘1𝑘3+𝑘2𝑘3+𝑘2𝑘4 . (S13)

Equation (S8) is valid based on the reaction scheme depicted above and is independent of any assumptions that go into the calculation of each rate. Equations (S4) and (S6) encompass the sequence-dependent terms and all other terms are assumed to be constant and are grouped and treated as fit parameters, 𝑇𝑆 = 1 + 1

𝐵1𝑒𝛽1∆𝐺𝐿+𝐵4𝑒−𝛽4(∆𝐺𝐵+∆𝐺𝐴−∆𝐺𝑈) (1+𝐵1𝑒𝛽1∆𝐺𝐿 ) (S14)

where B1 = 0.005, B4 = 6.0, β1 = 0.6, and β4 = 0.45 are fit parameters. The predicted TS is calculated by equation (S14) using the free energies provided by equations (1), (S7), and (S8). Equation (S14) is used to fit the experimentally derived terminator strengths for all 582 terminators yielding a fit to the x = y line of R2 = 0.40 (r = 0.63) (Fig. 4a). A sensitivity analysis was performed to evaluate the robustness of the fit to changes in the parameters (Supplementary Fig. 20).


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Supplementary Note 9: Analysis for Homologous Recombination in Strong Terminators Of the total library of 582 natural and synthetic terminators, 84 are deemed strong (TS > 50). We analyzed the propensity for recombination by comparing the sequence identities shared between this subset. We performed pairwise sequence alignment for each terminator pair and recorded the length of the longest contiguous stretch of identical nucleotide sequences using the Needleman-Wunsch global alignment algorithm with the MATLAB’s nwalign command39. Terminator pairs with a contiguous stretch of nucleotides shorter than a cutoff of 25 bp are assumed to be resistant to homologous recombination40-42. A matrix of all 84 strong terminators where each element shows the length of the longest identical sequence is shown (Supplementary Fig. 21). Each entry colored in red indicates that that pair has a contiguous stretch greater than 25bp. A subset of 39 strong terminators are identified where none share >25bp of contiguous sequence identity. The number of terminators increases to 115 when moderate-strong terminators are considered (TS > 10). Both the strong and medium-strong subsets are marked in Supplementary Tables 2 and 3.


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Supplementary Note 10: Recombination Experiment

Repeated terminator sequences can undergo homologous recombination to eliminate intervening DNA sequence. To ascertain how diversification of terminator sequences affects the rate of homologous recombination, we designed a NOT-gate circuit comprising two cistrons. In the first cistron, a ButR-repressible promoter (PButR) drives expression of YFP; in the second cistron, a 3OC6HSL-inducible promoter (PLux) drives expression of a slightly toxic repressor ButR (Fig. 4d). We designed a repeated terminator NOT-gate where both cistrons are terminated by the BBa_B0015 double terminator, and also two re-engineered versions—one where the ButR terminator was replaced with the synthetic L3S2P21 terminator, and one where the YFP terminator was replaced with the synthetic L3S2P56 terminator (Fig. 4d). We propagated cells containing the NOT-gates for ~70 generations (seven days, see Online Methods) to evaluate the stability of the NOT-gate. Plasmid DNA was restriction digested at AvrII and BamHI sites, which cuts 43 bp upstream from the YFP start codon and 2106 bp downstream from the ButR stop codon, respectively. For the full length circuit, the digested fragment length is 3927 bp. Elimination of ButR via homologous recombination at the terminators results in loss of 1058 bp that includes the ButR coding sequence. In this case, the digested fragment length is 2869 bp. The passaged cells exhibited high amounts of recombination when the BBa_B0015 terminator is used repeatedly in the NOT-gate (Supplementary Fig. 22a, lower band, ButR not present), and low amounts of recombination when one of the terminators is replaced with L3S2P21 in the NOT-gate (full-length band). The backbone restriction digest fragment is not shown.

Furthermore, over the course of three days we induced production of ButR in the both NOT-gate constructs using the same passaging protocol described above, with the addition of 20 µM 3OC6HSL. The NOT-gate with BBa_B0015 used repeatedly loses ButR through recombination, causing YFP to become de-repressed, observable by the emergence of a highly fluorescent sub-population (Supplementary Fig. 22b left). On the other hand, the NOT-gate re-engineered to use L3S2P21 as one of the terminators maintains its population with a majority of cells still repressing YFP, indicative of maintained ButR function and low amounts of transformation (Supplementary Fig. 22b, right).


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Supplementary Note 11: Plasmid Information

The plasmid map (Supplementary Fig. 23) and sequence of the reporter plasmid are shown. In the sequence, each feature is highlighted. The PBAD promoter is shown in white text, which contains the AraC gene (highlighted black) being transcribed in the reverse direction followed by a promoter that drives the genes being assayed in the forward direction. The promoter part is italicized and highlighted in dark red. The BBa_B0010 terminator is in bold face, underlined, and highlighted red as an example to indicate the position where the terminators of interest are inserted. It is inserted between the EcoRI and SpeI sites, which are in bold face. The RBSs of GFP and RFP are underlined and italicized. The sequence of GFP and RFP are highlighted green and magenta, respectively. Other terminators in the plasmid are underlined. The ColE1 origin of replication is highlighted in gray. The ampicillin resistance gene is the next region highlighted in gray. pGR-BBa_B0010 ttatgacaacttgacggctacatcattcactttttcttcacaaccggcacggaactcgctcgggctggccccggtgcattttttaaatacccgcgagaaatagagttgatcgtcaaaaccaacattgcgaccgacggtggcgataggcatccgggtggtgctcaaaagcagcttcgcctggctgatacgttggtcctcgcgccagcttaagacgctaatccctaactgctggcggaaaagatgtgacagacgcgacggcgacaagcaaacatgctgtgcgacgctggcgatatcaaaattgctgtctgccaggtgatcgctgatgtactgacaagcctcgcgtacccgattatccatcggtggatggagcgactcgttaatcgcttccatgcgccgcagtaacaattgctcaagcagatttatcgccagcagctccgaatagcgcccttccccttgcccggcgttaatgatttgcccaaacaggtcgctgaaatgcggctggtgcgcttcatccgggcgaaagaaccccgtattggcaaatattgacggccagttaagccattcatgccagtaggcgcgcggacgaaagtaaacccactggtgataccattcgcgagcctccggatgacgaccgtagtgatgaatctctcctggcgggaacagcaaaatatcacccggtcggcaaacaaattctcgtccctgatttttcaccaccccctgaccgcgaatggtgagattgagaatataacctttcattcccagcggtcggtcgataaaaaaatcgagataaccgttggcctcaatcggcgttaaacccgccaccagatgggcattaaacgagtatcccggcagcaggggatcattttgcgcttcagccatacttttcatactcccgccattcagagaagaaaccaattgtccatattgcatcagacattgccgtcactgcgtcttttactggctcttctcgctaaccaaaccggtaaccccgcttattaaaagcattctgtaacaaagcgggaccaaagccatgacaaaaacgcgtaacaaaagtgtctataatcacggcagaaaagtccacattgattatttgcacggcgtcacactttgctatgccatagcatttttatccataagattagcggatcctacctgacgctttttatcgcaactctctactgtttctccatacccgtttttttgggctagctactagagaaagaggagaaatactagatgcgtaaaggagaagaacttttcactggagttgtcccaattcttgttgaattagatggtgatgttaatgggcacaaattttctgtcagtggagagggtgaaggtgatgcaacatacggaaaacttacccttaaatttatttgcactactggaaaactacctgttccatggccaacacttgtcactactttcggttatggtgttcaatgctttgcgagatacccagatcatatgaaacagcatgactttttcaagagtgccatgcccgaaggttatgtacaggaaagaactatatttttcaaagatgacgggaactacaagacacgtgctgaagtcaagtttgaaggtgatacccttgttaatagaatcgagttaaaaggtattgattttaaagaagatggaaacattcttggacacaaattggaatacaactataactcacacaatgtatacatcatggcagacaaacaaaagaatggaatcaaagttaacttcaaaattagacacaacattgaagatggaagcgttcaactagcagaccattatcaacaaaatactccaattggcgatggccctgtccttttaccagacaaccattacctgtccacacaatctgccctttcgaaagatcccaacgaaaagagagaccacatggtccttcttgagtttgtaacagctgctgggattacacatggcatggatgaactatacaaataataagaattcccaggcatcaaataaaacgaaaggctcagtcgaaagactgggcctttcgttttatctgttgtttgtcggtgaacgctctcactagtagcggccgctgcagaaagaggagaaatactagatggcttcctccgaagacgttatcaaagagttcatgcgtttcaaagttcgtatggaaggttccgttaacggtcacgagttcgaaatcgaaggtgaaggtgaaggtcgtccgtacgaaggtacccagaccgctaaactgaaagttaccaaaggtggtccgctgccgttcgcttgggacatcctgtccccgcagttccagtacggttccaaagcttacgttaaacacccggctgacatcccggactacctgaaactgtccttcccggaaggtttcaaatgggaacgtgttatgaacttcgaagacggtggtgttgttaccgttacccaggactcctccctgcaagacggtgagttcatctacaaagttaaactgcgtggtaccaacttcccgtccgacggtccggttatgcagaaaaaaaccatgggttgggaagcttccaccgaacgtatgtacccggaagacggtgctctgaaaggtgaaatcaaaatgcgtctgaaactgaaagacggtggtcactacgacgctgaagttaaaaccacctacatggctaaaaaaccggttcagctgccgggtgcttacaaaaccgacatcaaactggacatcacctcccacaacgaa


48

gactacaccatcgttgaacagtacgaacgtgctgaaggtcgtcactccaccggtgcttaataacgctgatagtgctagtgtagatcgctactagagccaggcatcaaataaaacgaaaggctcagtcgaaagactgggcctttcgttttatctgttgtttgtcggtgaacgctctctactagagtcacactggctcaccttcgggtgggcctttctgcgtttatatactagagtcaattgaggtagaggtacacacgcgaactccgatagccaattcagagtaataaactgtgataatcaatgcagtgcttcctcgctcactgactcgctgcgctcggtcgttcggctgcggcgagcggtatcagctcactcaaaggcggtaatacggttatccacagaatcaggggataacgcaggaaagaacatgtgagcaaaaggccagcaaaaggccaggaaccgtaaaaaggccgcgttgctggcgtttttccataggctccgcccccctgacgagcatcacaaaaatcgacgctcaagtcagaggtggcgaaacccgacaggactataaagataccaggcgtttccccctggaagctccctcgtgcgctctcctgttccgaccctgccgcttaccggatacctgtccgcctttctcccttcgggaagcgtggcgctttctcatagctcacgctgtaggtatctcagttcggtgtaggtcgttcgctccaagctgggctgtgtgcacgaaccccccgttcagcccgaccgctgcgccttatccggtaactatcgtcttgagtccaacccggtaagacacgacttatcgccactggcagcagccactggtaacaggattagcagagcgaggtatgtaggcggtgctacagagttcttgaagtggtggcctaactacggctacactagaaggacagtatttggtatctgcgctctgctgaagccagttaccttcggaaaaagagttggtagctcttgatccggcaaacaaaccaccgctggtagcggtggtttttttgtttgcaagcagcagattacgcgcagaaaaaaaggatctcaagaagatcctttgatcttttctacggggtctgacgctcagtggaacgaaaactcacgttaagggattttggtcatgagattatcaaaaaggatcttcacctagatccttttaaattaaaaatgaagttttaaatcaatctaaagtatatatgagtaaacttggtctgacagttaccaatgcttaatcagtgaggcacctatctcagcgatctgtctatttcgttcatccatagttgcctgactccccgtcgtgtagataactacgatacgggagggcttaccatctggccccagtgctgcaatgataccgcgagacccacgctcaccggctccagatttatcagcaataaaccagccagccggaagggccgagcgcagaagtggtcctgcaactttatccgcctccatccagtctattaattgttgccgggaagctagagtaagtagttcgccagttaatagtttgcgcaacgttgttgccattgctacaggcatcgtggtgtcacgctcgtcgtttggtatggcttcattcagctccggttcccaacgatcaaggcgagttacatgatcccccatgttgtgcaaaaaagcggttagctccttcggtcctccgatcgttgtcagaagtaagttggccgcagtgttatcactcatggttatggcagcactgcataattctcttactgtcatgccatccgtaagatgcttttctgtgactggtgagtactcaaccaagtcattctgagaatagtgtatgcggcgaccgagttgctcttgcccggcgtcaatacgggataataccgcgccacatagcagaactttaaaagtgctcatcattggaaaacgttcttcggggcgaaaactctcaaggatcttaccgctgttgagatccagttcgatgtaacccactcgtgcacccaactgatcttcagcatcttttactttcaccagcgtttctgggtgagcaaaaacaggaaggcaaaatgccgcaaaaaagggaataagggcgacacggaaatgttgaatactcatactcttcctttttcaatattattgaagcatttatcagggttattgtctcatgagcggatacatatttgaatgtatttagaaaaataaacaaataggggttccgcgcacatttccccgaaaagtgccacctgacgtctaagaaaccattattatcatgacattaacctataaaaataggcgtatcacgaggcagaatttcagataaaaaaaatccttagctttcgctaaggatgatttctggaattgaattgaggtagaggtacacacgcgaactccgatagccaattcagagtaataaactgtgataatcaatgcatgtactagag


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Supplementary Note 12: Supplemental References

1. von Hippel, P.H. and Yager, T.D., Transcript elongation and termination are competitive kinetic processes. Proc. Natl. Acad. Sci. 88, 2307-2311 (1991).

2. Xayaphoummine, A., Bucher, T., and Isambert, H., Kinefold web server for rna/DNA folding path and structure prediction including pseudoknots and knots. Nucleic Acids Res. 33, W605-610 (2005).

3. Gama-Castro, S. et al., Regulondb (version 6.0): Gene regulation model of escherichia coli k-12 beyond transcription, active (experimental) annotated promoters and textpresso navigation. Nucleic Acids Res. 36, D120-124 (2008).

4. Yager, T.D. and Hippel, P.H.V., A thermodynamic analysis of rna transcript elongation and termination in escherichia coli. Biochem. 30, 1097-1118 (1991).

5. Registry of standard biological parts, Available at http://partsregistry.org/. 6. Kelly, J.R., Tools and reference standards supporting the engineering and evolution

of synthetic biological systems, Ph.D. Dissertation, Massachusetts Institute of Technology, 2008.

7. Team, U.D.i., Available at http://2010.igem.org/Team:UC_Davis/notebook/c0051debug.html, (2010).

8. Carrier, T.A. and Keasling, J.D., Engineering mrna stability in e. Coli by the addition of synthetic hairpins using a 5' cassette system. Biotechnol. Bioeng. 55, 577-580 (1997).

9. Mendez-Perez, D., Gunasekaran, S., Orler, V.J., and Pfleger, B.F., A translation-coupling DNA cassette for monitoring protein translation in escherichia coli. Metab. Eng. 14, 298-305 (2012).

10. Reynolds, R. and Chamberlin, M.J., Parameters affecting transcription termination by escherichia coli rna ii . Construction and analysis of hybrid terminators. J. Mol. Biol. 224, 53-63 (1992).

11. Sugimoto, N. et al., Thermodynamic parameters to predict stability. Biochem. 34, 11211-11216 (1995).

12. Peters, J.M., Vangeloff, A.D., and Landick, R., Bacterial transcription terminators: The rna 3'-end chronicles. J. Mol. Biol. 412, 793-813 (2011).

13. Epshtein, V., Cardinale, C.J., Ruckenstein, A.E., Borukhov, S., and Nudler, E., An allosteric path to transcription termination. Mol. Cell 28, 991-1001 (2007).

14. Lubkowska, L., Maharjan, A.S., and Komissarova, N., Rna folding in transcription elongation complex: Implication for transcription termination. J. Biol. Chem. 286, 31576-31585 (2011).

15. Schudoma, C., May, P., Nikiforova, V., and Walther, D., Sequence-structure relationships in rna loops: Establishing the basis for loop homology modeling. Nucleic Acids Res. 38, 970-980 (2010).

16. The high-performance computational capabilities of the helix systems at the national institutes of health, bethesda, md, Available at http://helixweb.nih.gov/structbio/basic.html.

17. d'Aubenton Carafa, Y., Brody, E., and Thermes, C., Prediction of rho-independent escherichia coli transcription terminators. A statistical analysis of their rna stem-loop structures. J. Mol. Biol. 216, 835-858 (1990).

18. Zuker, M. and Stiegler, P., Optimal computer folding of large rna sequences using thermodynamics and auxiliary information Nucleic Acids Res. 9 (1), 133-148 (1981).

19. Freier, S.M. et al., Improved free-energy parameters for predictions of rna duplex stability. Proc. Natl. Acad. Sci. USA 83, 9373-9377 (1986).

20. Registry of standard biological parts. Help:Terminators/design.


http://partsregistry.org/

http://2010.igem.org/Team:UC_Davis/notebook/c0051debug.html

http://helixweb.nih.gov/structbio/basic.html

50

21. Gama-Castro, S. et al., Regulondb version 7.0: Transcriptional regulation of escherichia coli k-12 integrated within genetic sensory response units (gensor units). Nucleic Acids Res. 39, D98-105 (2011).

22. Goliger, J.A., Yang, X.J., Guo, H.C., and Roberts, J.W., Early transcribed sequences affect termination efficiency of escherichia coli rna polymerase. J. Mol. Biol. 205, 331-341 (1989).

23. Telesnitsky, A. and Chamberlin, M.J., Terminator-distal sequences determine the in vitro efficiency of the early terminators of bacteriophages t3 and t7. Biochem. 28, 5210-5218 (1989).

24. Telesnitsky, A.P. and Chamberlin, M.J., Sequences linked to prokaryotic promoters can affect the efficiency of downstream termination sites. J. Mol. Biol. 205, 315-330 (1989).

25. Macdonald, L.E., Zhou, Y., and Mcallister, W.T., Termination and slippage by bacteriophage t7 rna polymearse. J. Mol. Biol. 232, 1030-1047 (1993).

26. Hofacker, I.L., Vienna rna secondary structure server. Nucleic Acids Res. 31, 3429-3431 (2003).

27. Yarnell, W.S. and Roberts, J.W., Mechanism of intrinsic transcription termination and antitermination. Science 284, 611-615 (1999).

28. Santangelo, T.J. and Roberts, J.W., Forward translocation is the natural pathway of rna release at an intrinsic terminator. Mol. Cell 14 (1), 117-126 (2004).

29. Epshtein, V., Dutta, D., Wade, J., and Nudler, E., An allosteric mechanism of rho-dependent transcription termination. Nature 463, 245-249 (2010).

30. Toulokhonov, I., Artsimovitch, I., and Landick, R., Allosteric control of rna polymerase by a site that contacts nascent rna hairpins. Science 292, 730-733 (2001).

31. Larson, M.H., Greenleaf, W.J., Landick, R., and Block, S.M., Applied force reveals mechanistic and energetic details of transcription termination. Cell 132, 971-982 (2008).

32. Kuznetsov, S.V., Ren, C.-C., Woodson, S.a., and Ansari, A., Loop dependence of the stability and dynamics of nucleic acid hairpins. Nucleic Acids Res. 36, 1098-1112 (2008).

33. Zimm, B.H. and Bragg, J.K., Theory of the phase transition between helix and random coil in polypeptide chains. J. Chem. Phys 31, 526-535 (1959).

34. Zhang, W. and Chen, S.-J., Exploring the complex folding kinetics of rna hairpins: Ii. Effect of sequence, length, and misfolded states. Biophys. J. 90, 778-787 (2006).

35. Zhang, W. and Chen, S.-J., Exploring the complex folding kinetics of rna hairpins: I. General folding kinetics analysis. Biophys. J. 90, 765-777 (2006).

36. Zhang, W. and Chen, S.-J., Rna hairpin-folding kinetics. Proc. Natl. Acad. Sci. 99, 1931-1936 (2002).

37. Gillesple, D.T., Exact stochastic simulation of coupled chemical reactions. Journal of Physical Chemistry 81, 2340-2361 (1977).

38. Peskin, C.S., Odell, G.M., and Oster, G.F., Cellular motions and thermal fluctuations: The brownian ratchet. Biophys. J. 65, 316-324 (1993).

39. Durbin, R., Eddy, S., Krogh, A., and Mitchison, G., Biological sequence analysis. (Canbridge University Press, 1998).

40. Shen, P. and Huang, H.V., Homologous recombination in escherichia coli: Dependence on substrate length and homology. Genetics 112, 441-457 (1986).

41. Lovett, S.T., Luisi-deluca, C., and Kolodner, R.D., The genetic dependence of recombination in recd mutants of eschericia coli. Genetics 120, 37-45 (1988).

42. Fujitani, Y., Yamamoto, K., and Kobayashi, I., Dependence of frequency of homologous recombination on the homology length. Genetics 140, 797-809 (1995).


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