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Single-cell systems biology by super-resolution imaging and combinatorial labeling

Nature Methods volume 9, pages 743–748 (2012)Cite this article

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Abstract

Fluorescence microscopy is a powerful quantitative tool for exploring regulatory networks in single cells. However, the number of molecular species that can be measured simultaneously is limited by the spectral overlap between fluorophores. Here we demonstrate a simple but general strategy to drastically increase the capacity for multiplex detection of molecules in single cells by using optical super-resolution microscopy (SRM) and combinatorial labeling. As a proof of principle, we labeled mRNAs with unique combinations of fluorophores using fluorescence in situ hybridization (FISH), and resolved the sequences and combinations of fluorophores with SRM. We measured mRNA levels of 32 genes simultaneously in single Saccharomyces cerevisiae cells. These experiments demonstrate that combinatorial labeling and super-resolution imaging of single cells is a natural approach to bring systems biology into single cells.

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Figure 1: Spatial ordering of fluorophores on mRNAs can be resolved by Gaussian centroid localization.
Figure 2: Super-resolution imaging enables combinatorial labeling of individual transcripts.
Figure 3: Validation of mRNA quantitation by super-resolution barcoding.
Figure 4: Single-cell expression profiles of 32 mRNAs.
Figure 5: Msn2 and Crz1 combinatorially affect target regulons.

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References

  1. Johnson, D.S., Mortazavi, A., Myers, R.M. & Wold, B. Genome-wide mapping of in vivo protein-DNA interactions. Science 316, 1497–1502 (2007).

    Article  CAS  Google Scholar 

  2. Mortazavi, A., Williams, B.A., McCue, K., Schaeffer, L. & Wold, B. Mapping and quantifying mammalian transcriptomes by RNA-seq. Nat. Methods 5, 621–628 (2008).

    Article  CAS  Google Scholar 

  3. Nagalakshmi, U. et al. The transcriptional landscape of the yeast genome defined by RNA sequencing. Science 320, 1344–1349 (2008).

    Article  CAS  Google Scholar 

  4. Schena, M., Shalon, D., Davis, R.W. & Brown, P.O. Quantitative monitoring of gene expression patterns with a complementary DNA microarray. Science 270, 467–470 (1995).

    Article  CAS  Google Scholar 

  5. Elowitz, M.B. & Leibler, S. A synthetic oscillatory network of transcriptional regulators. Nature 403, 335–338 (2000).

    Article  CAS  Google Scholar 

  6. Chalfie, M., Tu, Y., Euskirchen, G., Ward, W. & Prasher, D. Green fluorescent protein as a marker for gene expression. Science 263, 802–805 (1994).

    Article  CAS  Google Scholar 

  7. Golding, I., Paulsson, J., Zawilski, S.M. & Cox, E.C. Real-time kinetics of gene activity in individual bacteria. Cell 123, 1025–1036 (2005).

    Article  CAS  Google Scholar 

  8. Cai, L., Friedman, N. & Xie, X.S. Stochastic protein expression in individual cells at the single molecule level. Nature 440, 358–362 (2006).

    Article  CAS  Google Scholar 

  9. Yu, J., Xiao, J., Ren, X., Lao, K. & Xie, X.S. Probing gene expression in live cells, one protein molecule at a time. Science 311, 1600–1603 (2006).

    Article  CAS  Google Scholar 

  10. Raj, A., Peskin, C.S., Tranchina, D., Vargas, D.Y. & Tyagi, S. Stochastic mRNA synthesis in mammalian cells. PLoS Biol. 4, e309 (2006).

    Article  Google Scholar 

  11. Hell, S.W. Far-field optical nanoscopy. Science 316, 1153–1158 (2007).

    CAS  Google Scholar 

  12. Betzig, E. et al. Imaging intracellular fluorescent proteins at nanometer resolution. Science 313, 1642–1645 (2006).

    Article  CAS  Google Scholar 

  13. Rust, M.J., Bates, M. & Zhuang, X. Sub-diffraction-limit imaging by stochastic optical reconstruction microscopy (STORM). Nat. Methods 3, 793–795 (2006).

    Article  CAS  Google Scholar 

  14. Hess, S.T., Girirajan, T.P.K. & Mason, M.D. Ultra-high resolution imaging by fluorescence photoactivation localization microscopy. Biophys. J. 91, 4258–4272 (2006).

    Article  CAS  Google Scholar 

  15. Femino, A.M. Visualization of single RNA transcripts in situ. Science 280, 585–590 (1998).

    Article  CAS  Google Scholar 

  16. Raj, A., van den Bogaard, P., Rifkin, S.A., van Oudenaarden, A. & Tyagi, S. Imaging individual mRNA molecules using multiple singly labeled probes. Nat. Methods 5, 877–879 (2008).

    Article  CAS  Google Scholar 

  17. Lowenstein, M.G. Long-range interphase chromosome organization in Drosophila: a study using color barcoded fluorescence in situ hybridization and structural clustering analysis. Mol. Biol. Cell 15, 5678–5692 (2004).

    Article  CAS  Google Scholar 

  18. Levsky, J.M., Shenoy, S.M., Pezo, R.C. & Singer, R.H. Single-cell gene expression profiling. Science 297, 836–840 (2002).

    Article  CAS  Google Scholar 

  19. Thompson, R.E., Larson, D.R. & Webb, W.W. Precise nanometer localization analysis for individual fluorescent probes. Biophys. J. 82, 2775–2783 (2002).

    Article  CAS  Google Scholar 

  20. Yildiz, A. et al. Myosin V walks hand-over-hand: single fluorophore imaging with 1.5-nm localization. Science 300, 2061–2065 (2003).

    Article  CAS  Google Scholar 

  21. Bates, M., Dempsey, G.T., Chen, K.H. & Zhuang, X. Multicolor super-resolution fluorescence imaging via multi parameter detection. ChemPhysChem 13, 99–107 (2012).

    Article  CAS  Google Scholar 

  22. Barish, R.D., Schulman, R., Rothemund, P.W.K. & Winfree, E. An information-bearing seed for nucleating algorithmic self-assembly. Proc. Natl. Acad. Sci. USA 106, 6054–6059 (2009).

    Article  CAS  Google Scholar 

  23. Cai, L., Dalal, C.K. & Elowitz, M.B. Frequency-modulated nuclear localization bursts coordinate gene regulation. Nature 455, 485–490 (2008).

    Article  CAS  Google Scholar 

  24. Gasch, A.P. et al. Genomic expression programs in the response of yeast cells to environmental changes. Mol. Biol. Cell 11, 4241–4257 (2000).

    Article  CAS  Google Scholar 

  25. Zenklusen, D., Larson, D.R. & Singer, R.H. Single-RNA counting reveals alternative modes of gene expression in yeast. Nat. Struct. Mol. Biol. 15, 1263–1271 (2008).

    Article  CAS  Google Scholar 

  26. Gandhi, S.J., Zenklusen, D., Lionnet, T. & Singer, R.H. Transcription of functionally related constitutive genes is not coordinated. Nat. Struct. Mol. Biol. 18, 27–34 (2011).

    Article  CAS  Google Scholar 

  27. Dempsey, G.T., Vaughan, J.C., Chen, K.H., Bates, M. & Zhuang, X. Evaluation of fluorophores for optimal performance in localization-based super-resolution imaging. Nat. Methods 8, 1027–1036 (2011).

    Article  CAS  Google Scholar 

  28. Huang, B., Wang, W., Bates, M. & Zhuang, X. Three-dimensional super-resolution imaging by stochastic optical reconstruction microscopy. Science 319, 810–813 (2008).

    Article  CAS  Google Scholar 

  29. Cella Zanacchi, F. et al. Live-cell 3D super-resolution imaging in thick biological samples. Nat. Methods 8, 1047–1049 (2011).

    Article  Google Scholar 

  30. Agnew, H.D. et al. Iterative in situ click chemistry creates antibody-like protein-capture agents. Angew. Chem. Int. Ed. Engl. 48, 4944–4948 (2009).

    Article  CAS  Google Scholar 

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Acknowledgements

We credit B. Wold with discussions that led to this work. We thank M. Elowitz for lending space and equipment in his laboratory, T. Zhiyentayev, H.Q. Li and X. Wang for assistance with experiments, A. Raj for technical assistance with FISH, X.W. Zhuang and her group for STORM, and A. Eldar, S. Fraser, G.W. Li, J. Levine and J. Locke for discussion and reading of the manuscript. This work was supported by a Beckman Institute seed grant and a US National Institutes of Health New Innovator Award 1DP2OD008530.

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Authors and Affiliations

  1. Program in Biochemistry and Molecular Biophysics, California Institute of Technology, Pasadena, California, USA

    Eric Lubeck & Long Cai

  2. Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, California, USA

    Long Cai

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  1. Eric Lubeck
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  2. Long Cai
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E.L. and L.C. performed the experiments, carried out the analysis and wrote the manuscript. L.C. conceived the idea and designed the experiments.

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Correspondence to Long Cai.

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The authors declare no competing financial interests.

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Supplementary Figures 1–21, Supplementary Tables 1–4, Supplementary Note (PDF 4012 kb)

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Lubeck, E., Cai, L. Single-cell systems biology by super-resolution imaging and combinatorial labeling. Nat Methods 9, 743–748 (2012). https://doi.org/10.1038/nmeth.2069

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