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Single Molecule Cluster Analysis dissects splicing pathway conformational dynamics

Nature Methods volume 12, pages 1077–1084 (2015)Cite this article

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Abstract

We report Single Molecule Cluster Analysis (SiMCAn), which utilizes hierarchical clustering of hidden Markov modeling–fitted single-molecule fluorescence resonance energy transfer (smFRET) trajectories to dissect the complex conformational dynamics of biomolecular machines. We used this method to study the conformational dynamics of a precursor mRNA during the splicing cycle as carried out by the spliceosome. By clustering common dynamic behaviors derived from selectively blocked splicing reactions, SiMCAn was able to identify the signature conformations and dynamic behaviors of multiple ATP-dependent intermediates. In addition, it identified an open conformation adopted late in splicing by a 3′ splice-site mutant, invoking a mechanism for substrate proofreading. SiMCAn enables rapid interpretation of complex single-molecule behaviors and should prove useful for the comprehensive analysis of a plethora of dynamic cellular machines.

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Figure 1: smFRET analysis of pre-mRNA splicing using the HMM.
Figure 2: SiMCAn workflow for sorting and clustering single-molecule-derived HMMs for common dynamic behaviors.
Figure 3: Validation of SiMCAn using a previously analyzed data set describing the transition from the purified Bact complex to the C complex5.
Figure 4: Clustering of clusters to identify 'clades' of similar behavior.
Figure 5: Cluster-occupancy histogram showing the raw fraction of molecules occupying each cluster for the late assembly stages of the splicing cycle.
Figure 6: Dynamic clusters of clade VII enriched in the Prp16DN-WCE conditions showed repeated excursions from the 0.85 state to lower FRET states.

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Acknowledgements

The authors thank A. Price (University of California, San Francisco) for providing native gel analysis of CC2 formation using Ubc4; D.R. Semlow and J.P. Staley (University of Chicago) for providing the dominant-negative Prp16 protein expression plasmid; N.N. Vo for compiling all Matlab scripts of SiMCAn into a GUI; and C. Guthrie, D.R. Semlow, J.P. Staley and A.A. Hoskins for providing valuable comments on the manuscript. The authors acknowledge funding from the US National Institutes of Health (grant R01GM098023 to N.G.W. and J.A.), the National Heart, Lung and Blood Institute (grant R01HL111527-01 to A.L.) and the National Science Foundation through the National Evolutionary Synthesis Center (NESCent) (grant NSF\#EF-0905606 to J.S.M.).

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Author notes

  1. Mario R Blanco & Joshua S Martin

    Present address: Present addresses: Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California, USA (M.R.B.); National Evolutionary Synthesis Center, Durham, North Carolina, USA (J.S.M.).,

  2. Mario R Blanco, Joshua S Martin and Matthew L Kahlscheuer: These authors contributed equally to this work.

Authors and Affiliations

  1. Department of Chemistry, Single Molecule Analysis Group, University of Michigan, Ann Arbor, Michigan, USA

    Mario R Blanco, Matthew L Kahlscheuer, Ramya Krishnan & Nils G Walter

  2. Cellular and Molecular Biology, University of Michigan, Ann Arbor, Michigan, USA

    Mario R Blanco

  3. Biology Department, University of North Carolina, Chapel Hill, North Carolina, USA

    Joshua S Martin & Alain Laederach

  4. Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, California, USA

    John Abelson

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Contributions

M.L.K. and R.K. performed in vitro splicing verification assays. M.L.K. and M.R.B. performed single-molecule experiments and performed data analysis. M.L.K. expressed and purified the Prp16DN protein. M.R.B. and J.S.M. wrote and developed the Matlab scripts for SiMCAn. M.L.K. prepared all fluorescent substrates and yeast whole-cell extracts. M.R.B., J.S.M., M.L.K., J.A., A.L. and N.G.W. jointly wrote the manuscript.

Corresponding author

Correspondence to Nils G Walter.

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The authors declare no competing financial interests.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–19, Supplementary Tables 1–3 and Supplementary Notes 1–5 (PDF 11322 kb)

Supplementary Software

SiMCAn MATLAB scripts (ZIP 1156 kb)

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Blanco, M., Martin, J., Kahlscheuer, M. et al. Single Molecule Cluster Analysis dissects splicing pathway conformational dynamics. Nat Methods 12, 1077–1084 (2015). https://doi.org/10.1038/nmeth.3602

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