NMR Structural Profiling of Transcriptional Intermediates Reveals Riboswitch Regulation by Metastable RNA Conformations.

Transcription

1 Supporting Information for: NMR Structural Profiling of Transcriptional Intermediates Reveals Riboswitch Regulation by Metastable RNA Conformations. Christina Helmling, Anna Wacker, Michael T. Wolfinger,, Ivo L. Hofacker,, Martin Hengesbach, Boris Fürtig, Harald Schwalbe *, Institute for Organic Chemisty and Chemical Biology, Center for Biomolecular Magnetic Resonance (BMRZ), Johann Wolfgang Goethe-Universität, Frankfurt/M., 60438, Germany Department of Theoretical Chemistry and Faculty of Computer Science, Research Group Bioinformatics and Computational Biology, University of Vienna, 1090 Vienna, Austria Medical University of Vienna, Center for Anatomy and Cell Biology, Währingerstraße 13, 1090 Vienna, Austria *Address correspondence to: S1

2 SI1: NMR characterization of the terminator helix Figure S1: Secondary structure of dgsw FL highlighting the sequence of the terminator model hairpin dgsw in red (left). The secondary structure assignment of the terminator hairpin is shown in the NOESY spectral overlay of dgsw FL (black, 450 µm, 800 MHz, 283 K) with the terminator model hairpin (red, 700 µm, 600 MHz, 283 K) on the right. SI2-4: NMR characterization of the antiterminator conformation Figure S2: Strategy applied for NMR secondary structure characterization of the ON-state. The following constructs were prepared: dgsw , dgsw , dgsw Fragments colored in red and black are hybridized to assemble the ON-state without further ligation. Isotope labeling patterns of the individual fragments are indicated accordingly. S2

3 Figure S3: a) Overlay and assignment of NOESY spectrum of dgsw and dgsw 122 for verification of correct folding (left) and overlay of NOESY 15 N(black)/ 14 N(red)-X-filtered spectra of dgsw (right). The spectra were recorded at 800 MHz, 283 K with a mixing time of 100 ms on 500 µm of each RNA fragment. b) Overlay of NOESY 15 N(black)/ 14 N(red)-X-filtered spectra of dgsw The spectra were recorded at 900 MHz, 283 K with a mixing time of 150 ms on 400 µm of each RNA fragment. c) NOESY spectrum of dgsw N-X-filtered in the direct dimension. The spectrum was recorded at 700 MHz and 283 K with 100 ms mixing time and 400 µm of each RNA fragment. Pathways that could not be assigned unambiguously from dgsw 122 alone (red and orange) are highlighted in each NOESY spectrum. S3

4 Figure S4: Verification of the ON-state assignment. a) Assembling of the proposed elongated antiterminator conformation and corresponding NOESY spectrum for cross validation. The spectrum was recorded at 900 MHz, 283 K on 500 µm of each RNA fragment. b) Final assignment of dgsw 122 and proposed secondary structures in conformational exchange. The spectrum was recorded at 900 MHz and 283 K on a 700 µm RNA sample. Continuous pathways of segments of P0 (red, green, orange), P2 (cyan) and P3 (blue) are color coded accordingly in both NMR spectra and secondary structures. S4

5 SI5: Secondary structure screening of transcriptional intermediates Figure S5: Imino region of 1D NMR spectra of 18 transcriptional intermediates showing a) the transition from PA (orange) to PT (green) and b) from PT (green) to TH (red). Screening of the aptamer domain constructs (dgsw 75 -dgsw 80 and dgsw 85 ) has been reported previously. 1 Spectra for dgsw dgsw 117 were recorded at 800 MHz and spectra for dgsw 134 -dgsw 144 were recorded at 700 MHz. All spectra were recorded at 298 K. S5

6 SI 6: Effect of Mg 2+ -induced aptamer stabilization on conformational transitions. Figure S6: Titration of dgsw 114 with Mg 2+. dgsw 114 was chosen as a construct to fully adopt the antiterminator helix PT, while all smaller constructs adopt proportions of the aptamer domain. Addition of Mg 2+ predominantly leads to broadening of imino proton signals. Minor resonance shifts can be observed, particularly for imino proton signals assigned to helix P3. However, a decrease in antiterminator PT reporter signals cannot be observed. Therefore, the presence of Mg 2+ does not stabilize the aptamer domain sufficiently to induce a conformational rearrangement. S6

7 SI 7: Simulations of co-transcriptional folding Cotranscriptional folding simulations of the 2'dG riboswitch were performed at the level of RNA secondary structures with the barmap software. 2 Being built on the nearest neighbor model 3 for RNA folding, the main idea behind this approach is to construct the energy landscape of the growing RNA chain at each elongation step, thereby elucidating topological properties such as local minima and saddle points as well as computing transition rates among minima. 4 The basins of attraction associated with each local minimum can be regarded as macro-states, which provide a convenient coarse-graining of the landscape. Minima among consecutive landscapes are mapped onto each other, providing a so called 'BarMap'. 2 A coarse grained folding dynamics is then computed for each landscape of the growing chain by numerical integration of the underlying Markov process. 5 Macro state population densities are then mapped among landscapes guided by the BarMap. Simulations were performed at 298 K. A caveat of the nearest neighbor model is that tertiary interactions such as pseudoknots or the effect of ligand binding cannot be directly modeled. Also, dependence on buffer conditions are neglected which can be a source of deviation between simulation and experiment. To address the issue of ligand binding, we have added an experimentally derived bonus energy of -8.0 kcal/mol to all structures exhibiting an aptamer binding pocket. 6 We consider a structure binding competent if the enclosing terminal base pairs of helices P1, P2 and P3 are present and add the bonus energy to every structure exhibiting this structural feature accordingly. This implicitly assumes infinite ligand concentration and instantaneous ligand binding. Figure S7: Coarse grained simulations of cotranscriptional folding of the 2 dg riboswitch. Macro states separated by an energy barrier of less than 4.5 kcal/mol are clustered by additional post processed coarse graining for better visualization. Elongation steps were introduced every 4000 time units corresponding to a transcription rate of ~25 nt/s. Clustered macro states are schematically depicted and color coded according to probability evaluations in the graph. The detailed secondary structure of these states is shown on the right. S7

8 All suboptimal structures within an initial energy interval of 10 kcal/mol above the ground state were computed with RNAsubopt from the ViennaRNA package v Energy landscapes and transition rates were computed with the following options of barriers v : '-G RNA -M noshift max rates'. In case the resulting energy landscape was not connected by a saddle point, the energy range for RNAsubopt was gradually increased by 2 kcal/mol until the resulting landscape was connected. The dynamics simulations were performed with treekin v One difficulty is that rates used in the simulations are fixed only up to a pre-factor that has to be gauged by comparison with experiment. To achieve that, we analyzed experimental data from 8 with the same barriers and treekin versions mentioned above, measuring simulated refolding times. We found that 1 second corresponds to approximately internal time units and consequently introduced an elongation step every 4000 time units corresponding to a transcription rate of 25 nt/sec. We performed the kinetics simulations with a set of 999 macro states at each elongation step to achieve an optimal resolution of the lower portion of the energy landscapes. Consequently, many states are populated at low probabilities, which makes visualization difficult. To overcome this issue, we applied another coarse graining at the level of barrier heights among local minima to the fully simulated cotranscriptional dynamics to make interpretation of the results more accessible. A minimal barrier height of 4.5 kcal/mol turned out to provide a good clustering of representative macro states. SI 8: Transcription assays performed with E.coli polymerase. Figure S8: 10% polyacrylamide gel showing a multi-round transcription of the full-length I-A 2 dg sensing riboswitch using E.coli polymerase. The larger 235 nt fragment resembles the full-length runoff transcript, while the 144 nt fragment corresponds to terminated RNA. Percentages indicated correspond to the fraction of full-length and terminated RNA in the presence and absence of ligand by correcting band intensities with the amount of U residues present in the two fragments. S8

9 SI 9: ITC data of transcriptional intermediates Figure S9. ITC data of dgsw 85 (12 µm), dgsw 104 (15 µm), dgsw 109 (15 µm), dgsw 112 (15 µm), dgsw 114 (40 µm), dgsw 117 (80 µm), dgsw 122 (80 µm) and dgsw 144 (20 µm) titrated with 2 dg (20x excess in concentration compared to RNA). Integrated heat was fit with a standard single-site binding model. Table 1: Thermodynamic parameters obtained from ITC measurements of transcriptional intermediates. Errors were propagated from standard deviations obtained from the fit. Construct dgsw 85 dgsw 104 dgsw 109 dgsw 112 dgsw 114 dgsw 117 dgsw 122 dgsw 144 KD [µm] 0.25 ± ± ± ± ± 0.2 > 10 > ± 0.03 ΔG [kcal mol -1 ] -9.0 ± ± ± ± ± ± 0.3 S9

10 References (1) Helmling, C.; Keyhani, S.; Sochor, F.; Fürtig, B.; Hengesbach, M.; Schwalbe, H. J. Biomol. NMR 2015, 63, 67. (2) Hofacker, I. L.; Flamm, C.; Heine, C.; Wolfinger, M. T.; Scheuermann, G.; Stadler, P. F. RNA 2010, 16, (3) Turner, D. H.; Mathews, D. H. Nucleic Acids Res. 2010, 38, D280. (4) Flamm, C.; Hofacker, I. L.; Stadler, P. F.; Wolfinger, M. T. Zeitschrift für Phys. Chemie 2002, 216, 155. (5) Wolfinger, M. T.; Svrcek-Seiler, W. A.; Flamm, C.; Hofacker, I. L.; Stadler, P. F. J. Phys. A. Math. Gen. 2004, 37, (6) Badelt, S.; Hammer, S.; Flamm, C.; Hofacker, I. L. Methods Enzymol. 2015, 553, 193. (7) Lorenz, R.; Bernhart, S. H.; Höner Zu Siederdissen, C.; Tafer, H.; Flamm, C.; Stadler, P. F.; Hofacker, I. L. Algorithms Mol. Biol. 2011, 6, 26. (8) Fürtig, B.; Wenter, P.; Reymond, L.; Richter, C.; Pitsch, S.; Schwalbe, H. J. Am. Chem. Soc. 2007, 129, S10