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Single-molecule imaging of non-equilibrium molecular ensembles on the millisecond timescale

Abstract

Single-molecule fluorescence microscopy is uniquely suited for detecting transient molecular recognition events, yet achieving the time resolution and statistics needed to realize this potential has proven challenging. Here we present a single-molecule imaging and analysis platform using scientific complementary metal-oxide semiconductor (sCMOS) detectors that enables imaging of 15,000 individual molecules simultaneously at millisecond rates. This system enabled the detection of previously obscured processes relevant to the fidelity mechanism in protein synthesis.

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Figure 1: Imaging platform for enhanced-throughput smFRET.
Figure 2: Robust detection of millisecond-scale transient events by smFRET.

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Acknowledgements

We thank J. Munro and P. Geggier for contributing to the design and implementation of analysis software; F. Sachs and C. Nicholi for help using QuB; P. Schultz (Scripps) for the Escherichia coli S12 knockout strain; Q. Zheng for preparing labeled DNA duplexes; and J. Sims, D. Butts, M. Feldman, F. Huang and the members of the Blanchard lab for helpful discussions. This work was supported by the US National Institutes of Health (grants 1R01GM079238 and 1R01GM098859 to S.C.B.). M.F.J. was supported by a postdoctoral fellowship from the German Academic Exchange Service (DAAD).

Author information

Authors and Affiliations

Authors

Contributions

M.F.J. and D.S.T. designed and implemented the sCMOS TIRF (total internal reflection fluorescence) microscope and analyzed the data. M.F.J. and M.R.W. performed smFRET experiments. D.S.T. designed and implemented the analysis software, with help from S.C.B., M.F.J. and M.R.W. M.F.J. designed and implemented data-acquisition software. M.R.W. developed the S12 ribosome-labeling strategy. M.R.W., R.B.A. and M.F.J. prepared ribosome and smFRET reagents. Z.Z. and H.Z. synthesized fluorophores. All authors contributed to experimental design and writing of the manuscript.

Corresponding author

Correspondence to Scott C Blanchard.

Ethics declarations

Competing interests

S.C.B. and R.B.A. have an equity interest in Lumidyne Technologies.

Integrated supplementary information

Supplementary Figure 1 Improved throughput enables full ensemble characterization from a single pre–steady-state measurement of tRNA selection.

(a-d) Data from a single movie acquired at 10 ms time resolution with EMCCD (a-b) and sCMOS (c-d) cameras, respectively. (a,c) Post-synchronized ensemble plots of FRET efficiency reveal the transit through intermediate states on path to accommodation. (b,d) The reversible nature of conformational sampling during the selection process is highlighted by transition density plots1, which juxtapose the initial and final FRET efficiency for each HMM-identified transition. (e-h) Experiments identical to a-d in the presence of 20 μM concentrations of the translation inhibitors hygromycin A (e-f) and A201A (g-h), two closely related peptidyl transferase inhibitors with different affinities for the ribosome that stall the selection process during the proofreading phase2. (i-k) Example sCMOS FRET traces (blue lines) and HMM idealizations (red lines): (i) in the absence of drug, (j) in the presence of hygromycin A, and (k) in the presence of A201A. (l-n) FRET histograms, summed from the data in panels a-d, provide a direct comparison of the capability to resolve the distinct effects of hygromycin A (black) and A201A (red) at the population level with (l) EMCCD and (m) sCMOS cameras. Error bars are the standard error from 100 bootstrap samples. (n) The ratio of transitions from the mid-FRET/GTPase activation (GA) state to the high-FRET/accommodated (AC) state vs. lower FRET states is shown for hygromycin A (gray bars) and A201A (red bars) as calculated from data from EMCCD and sCMOS cameras. Error bars are the 95% confidence intervals from 100 bootstrap samples and show that the effects of the two drugs are statistically indistinguishable with EMCCD cameras, but clear with sCMOS from a single movie.

1 McKinney, S.A., Joo, C. & Ha, T. Biophys J 91, 1941-1951 (2006).

2 Polikanov, Y.S. et al. Mol Cell 58, 832-844 (2015).

Source data

Supplementary Figure 2 Reproducibility of software-timed reagent delivery for pre–steady-state experiments.

The syringe pump was loaded with a 100 nM solution of Cy3 in buffer, which was then injected into the imaging channel containing only buffer while monitoring the total fluorescence signal registered by the camera. Multiple repeats (solid lines) demonstrate the precise reproducibility of the timing (50 % point: τ0.5; 10-90 % rise time: Δτ0.1-0.9) of the injections. For ribosome experiments, an adjustable delay was used to align the beginning of the movie with the 50 % point of the injection. Rise time and 50 % point specified as mean and s.d. of three technical replicates.

Source data

Supplementary Figure 3 Control experiments to validate the FRET states observed in S12-tRNA FRET experiments.

The correspondence of the high-FRET intermediate states in S12-tRNA FRET experiments to low/mid-FRET states in the previously described1 tRNA-tRNA FRET system was confirmed by control experiments with well-described translation inhibitors. (a) Without drug, the system accommodates into a ~0.73 FRET state after transiting intermediates at ~0.87 FRET. (b) Tetracycline (40 μM) and (c) tigecycline (2 μM) both promote rejection during the early (CR) stages of tRNA selection2, but the lifetime of events is shorter for the more efficient inhibitor tigecycline. (d) Kirromycin (20 μM) stalls the ribosome in an A/T hybrid state after GTP hydrolysis3. In combination, these results confirm that both the low- and mid-FRET states in the tRNA-tRNA system1 correspond to the high- (~0.87) FRET signal in the S12-tRNA system, while the high-FRET accommodated state in the tRNA-tRNA FRET system corresponds to the lower- (~0.73) FRET configuration in the S12-tRNA system.

1 Geggier, P. et al. J Mol Biol 399, 576-595 (2010).

2 Jenner, L. et al. Proc Natl Acad Sci USA 110, 3812-3816 (2013).

3 Schuette, J.C. et al. EMBO J (2009).

Source data

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–3 and Supplementary Table 1 (PDF 1639 kb)

Supplementary Software 1

Compiled MATLAB software for smFRET data analysis, including detailed documentation. Requires 64-bit Windows. (ZIP 18893 kb)

Supplementary Software 2

Compiled DLL (written in C) for conversion of Hamamatsu raw image format to BigTIFF with example client code for LabVIEW 8.2 or higher. Requires 64-bit Windows. (ZIP 387 kb)

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Juette, M., Terry, D., Wasserman, M. et al. Single-molecule imaging of non-equilibrium molecular ensembles on the millisecond timescale. Nat Methods 13, 341–344 (2016). https://doi.org/10.1038/nmeth.3769

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