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Probing low-copy-number proteins in single living cells using single-cell plasmonic immunosandwich assays

Abstract

Cellular heterogeneity is pervasive and of paramount importance in biology. Single-cell analysis techniques are indispensable for understanding the heterogeneity and functions of cells. Low-copy-number proteins (fewer than 1,000 molecules per cell) perform multiple crucial functions such as gene expression, cellular metabolism and cell signaling. The expression level of low-copy-number proteins of individual cells provides key information for the in-depth understanding of biological processes and diseases. However, the quantitative analysis of low-copy-number proteins in a single cell still remains challenging. To overcome this, we developed an approach called single-cell plasmonic immunosandwich assay (scPISA) for the quantitative measurement of low-copy-number proteins in single living cells. scPISA combines in vivo microextraction for specific enrichment of target proteins from cells and a state-of-the-art technique called plasmon-enhanced Raman scattering for ultrasensitive detection of low-copy-number proteins. Plasmon-enhanced Raman scattering detection relies on the plasmonic coupling effect (hot-spot) between silver-based plasmonic nanotags and a gold-based extraction microprobe, which dramatically enhances the signal intensity of the surface-enhanced Raman scattering of the nanotags and thereby enables sensitivity at the single-molecule level. scPISA is a straightforward and minimally invasive technique, taking only ~6–15 min (from in vivo extraction to Raman spectrum readout). It is generally applicable to all freely floating intracellular proteins provided that appropriate antibodies or alternatives (for example, molecularly imprinted polymers or aptamers) are available. The entire protocol takes ~4–7 d to complete, including material fabrication, single-cell manipulation, protein labeling, signal acquisition and data analysis.

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Fig. 1: Overview of the scPISA procedure for the determination of low-copy-number proteins in single living cells.
Fig. 2: Fabrication of extraction microprobes.
Fig. 3: Fabrication of plasmonic nanotags.
Fig. 4: Single-cell manipulation via a three-dimensional manipulator.
Fig. 5: Raman spectrum acquisition and analysis.
Fig. 6: Examples of anticipated results of detection of survivin in single living cells by the scPISA.

Data availability

The detailed raw data for Fig. 6 and their interpretation for the low-copy-number protein detection in single living cells by scPISA are available in the original publication24. Source data are provided with this paper.

References

  1. Irish, J. M., Kotecha, N. & Nolan, G. P. Innovation-mapping normal and cancer cell signalling networks: towards single-cell proteomics. Nat. Rev. Cancer 6, 146–155 (2006).

    Article  CAS  PubMed  Google Scholar 

  2. Graf, T. & Stadtfeld, M. Heterogeneity of embryonic and adult stem cells. Cell Stem Cell 3, 480–483 (2008).

    Article  CAS  PubMed  Google Scholar 

  3. Easwaran, H., Tsai, H. C. & Baylin, S. B. Cancer epigenetics: tumor heterogeneity, plasticity of stem-like states, and drug resistance. Mol. Cell 54, 716–727 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Bonavia, R., Inda, M. D., Cavenee, W. K. & Furnari, F. B. Heterogeneity maintenance in glioblastoma: a social network. Cancer Res 71, 4055–4060 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Dagogo-Jack, I. & Shaw, A. T. Tumour heterogeneity and resistance to cancer therapies. Nat. Rev. Clin. Oncol. 15, 81–94 (2018).

    Article  CAS  PubMed  Google Scholar 

  6. Jacob, F. et al. A patient-derived glioblastoma organoid model and biobank recapitulates inter- and intra-tumoral heterogeneity. Cell 180, 188–204 (2020).

    Article  CAS  PubMed  Google Scholar 

  7. Almendro, V., Marusyk, A. & Polyak, K. Cellular heterogeneity and molecular evolution in cancer. Annu. Rev. Pathol. Mech. Dis. 8, 277–302 (2013).

    Article  CAS  Google Scholar 

  8. Toriello, N. M. et al. Integrated microfluidic bioprocessor for single-cell gene expression analysis. Proc. Natl Acad. Sci. USA 105, 20173–20178 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Labib, M. & Kelley, S. O. Single-cell analysis targeting the proteome. Nat. Rev. Chem. 4, 143–158 (2020).

    Article  Google Scholar 

  10. Wang, D. J. & Bodovitz, S. Single cell analysis: the new frontier in ‘omics’. Trends Biotechnol. 28, 281–290 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Pollen, A. A. et al. Low-coverage single-cell mRNA sequencing reveals cellular heterogeneity and activated signaling pathways in developing cerebral cortex. Nat. Biotechnol. 32, 1053–1058 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Zheng, X. T. & Li, C. M. Single cell analysis at the nanoscale. Chem. Soc. Rev. 41, 2061–2071 (2012).

    Article  CAS  PubMed  Google Scholar 

  13. Ahmed, Z. et al. Grb2 monomer-dimer equilibrium determines normal versus oncogenic function. Nat. Commun. 6, 7354 (2015).

    Article  CAS  PubMed  Google Scholar 

  14. Timsah, Z. et al. Competition between Grb2 and Plc gamma 1 for FGFR2 regulates basal phospholipase activity and invasion. Nat. Struct. Mol. Biol. 21, 180–188 (2014).

    Article  CAS  PubMed  Google Scholar 

  15. Timsah, Z. et al. Grb2 depletion under non-stimulated conditions inhibits PTEN, promotes Akt-induced tumor formation and contributes to poor prognosis in ovarian cancer. Oncogene 35, 2186–2196 (2016).

    Article  CAS  PubMed  Google Scholar 

  16. Revankar, C. M., Cimino, D. F., Sklar, L. A., Arterburn, J. B. & Prossnitz, E. R. A transmembrane intracellular estrogen receptor mediates rapid cell signaling. Science 307, 1625–1630 (2005).

    Article  CAS  PubMed  Google Scholar 

  17. Ghaemmaghami, S. et al. Global analysis of protein expression in yeast. Nature 425, 737–741 (2003).

    Article  CAS  PubMed  Google Scholar 

  18. Restrepo-Perez, L., Joo, C. & Dekker, C. Paving the way to single-molecule protein sequencing. Nat. Nanotechol. 13, 786–796 (2018).

    Article  CAS  Google Scholar 

  19. Howard, M. & Rutenberg, A. D. Pattern formation inside bacteria: fluctuations due to the low copy number of proteins. Phys. Rev. Lett. 90, 128102 (2003).

    Article  PubMed  CAS  Google Scholar 

  20. Patel, A. P. et al. Single-cell RNA-seq highlights intratumoral heterogeneity in primary glioblastoma. Science 344, 1396–1401 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Navin, N. et al. Tumour evolution inferred by single-cell sequencing. Nature 472, 90–U119 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Tang, F. C. et al. mRNA-Seq whole-transcriptome analysis of a single cell. Nat. Methods 6, 377–U86 (2009).

    Article  CAS  PubMed  Google Scholar 

  23. Klein, A. M. et al. Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells. Cell 161, 1187–1201 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Liu, J., Yin, D. Y., Wang, S. S., Chen, H. Y. & Liu, Z. Probing low-copy-number proteins in a single living cell. Angew. Chem. Int. Ed. 55, 13215–13218 (2016).

    Article  CAS  Google Scholar 

  25. Wen, Y. R., Liu, J., He, H., Li, S. S. C. & Liu, Z. Single cell analysis of signaling proteins provides insights into pro-apoptotic properties of anti-cancer drugs. Anal. Chem. 92, 12498–12508 (2020).

    Article  CAS  PubMed  Google Scholar 

  26. Valaskovic, G. A., Kelleher, N. L. & McLafferty, F. W. Attomole protein characterization by capillary electrophoresis mass spectrometry. Science 273, 1199–1202 (1996).

    Article  CAS  PubMed  Google Scholar 

  27. Zhang, L. W. & Vertes, A. Single-cell mass spectrometry approaches to explore cellular heterogeneity. Angew. Chem. Int. Ed. 57, 4466–4477 (2018).

    Article  CAS  Google Scholar 

  28. Rubakhin, S. S. & Sweedler, J. V. Characterizing peptides in individual mammalian cells using mass spectrometry. Nat. Protoc. 2, 1987–1997 (2007).

    Article  CAS  PubMed  Google Scholar 

  29. Irish, J. M. et al. Single cell profiling of potentiated phospho-protein networks in cancer cells. Cell 118, 217–228 (2004).

    Article  CAS  PubMed  Google Scholar 

  30. Newman, J. R. S. et al. Single-cell proteomic analysis of S. cerevisiae reveals the architecture of biological noise. Nature 441, 840–846 (2006).

    Article  CAS  PubMed  Google Scholar 

  31. Hughes, A. J. et al. Single-cell western blotting. Nat. Methods 11, 749–U94 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. 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  PubMed  Google Scholar 

  33. Huang, B. et al. Counting low-copy number proteins in a single cell. Science 315, 81–84 (2007).

    Article  CAS  PubMed  Google Scholar 

  34. Taniguchi, Y. et al. Quantifying E. coli proteome and transcriptome with single-molecule sensitivity in single cells. Science 329, 533–538 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  36. Tu, X. Y. et al. Molecularly imprinted polymer-based plasmonic immunosandwich assay for fast and ultrasensitive determination of trace glycoproteins in complex samples. Anal. Chem. 88, 12363–12370 (2016).

    Article  CAS  PubMed  Google Scholar 

  37. Muhammad, P., Tu, X. Y., Liu, J., Wang, Y. J. & Liu, Z. Molecularly imprinted plasmonic substrates for specific and ultrasensitive immunoassay of trace glycoproteins in biological samples. ACS Appl. Mater. Inter. 9, 12082–12091 (2017).

    Article  CAS  Google Scholar 

  38. Li, W. et al. Controllably prepared aptamer-molecularly imprinted polymer hybrid for high-specificity and high-affinity recognition of target proteins. Anal. Chem. 91, 4831–4837 (2019).

    Article  CAS  PubMed  Google Scholar 

  39. Xing, R. R. et al. Dual molecularly imprinted polymer-based plasmonic immunosandwich assay for specific and sensitive detection of protein biomarkers. Anal. Chem. 91, 9993–10000 (2019).

    Article  CAS  PubMed  Google Scholar 

  40. Zhou, L. L. et al. Orthogonal dual molecularly imprinted polymer-based plasmonic immunosandwich assay: a double characteristic recognition strategy for specific detection of glycoproteins. Biosens. Bioelectron. 145, 111729 (2019).

    Article  CAS  PubMed  Google Scholar 

  41. Muhammad, P. et al. Fast probing of glucose and fructose in plant tissues via plasmonic affinity sandwich assay with molecularly-imprinted extraction microprobes. Anal. Chim. Acta 995, 34–42 (2017).

    Article  CAS  PubMed  Google Scholar 

  42. Liu, J., Wen, Y. R., He, H., Chen, H. Y. & Liu, Z. Probing cytoplasmic and nuclear microRNAs in single living cells via plasmonic affinity sandwich assay. Chem. Sci. 9, 7241–7246 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Zhang, Q. et al. Gold nanoparticle-decorated Ag@SiO2 nanocomposite-based plasmonic affinity sandwich assay of circulating microRNAs in human serum. ACS Appl. Nano Mater. 2, 3960–3970 (2019).

    Article  CAS  Google Scholar 

  44. Wulff, G. & Sarhan, A. Use of polymers with enzyme-analogous structures for resolution of racemates. Angew. Chem. Int. Ed. 11, 341–342 (1972).

    CAS  Google Scholar 

  45. Vlatakis, G., Andersson, L. I., Muller, R. & Mosbach, K. Drug assay using antibody mimics made by molecular imprinting. Nature 361, 645–647 (1993).

    Article  CAS  PubMed  Google Scholar 

  46. Ye, L. & Mosbach, K. Molecular imprinting: synthetic materials as substitutes for biological antibodies and receptors. Chem. Mater. 20, 859–868 (2008).

    Article  CAS  Google Scholar 

  47. Nishino, H., Huang, C. S. & Shea, K. J. Selective protein capture by epitope imprinting. Angew. Chem. Int. Ed. 45, 2392–2396 (2006).

    Article  CAS  Google Scholar 

  48. Sibrian-Vazquez, M. & Spivak, D. A. Molecular imprinting made easy. J. Am. Soc. Chem. 126, 7827–7833 (2004).

    Article  CAS  Google Scholar 

  49. Li, L., Lu, Y., Bie, Z. J., Chen, H. Y. & Liu, Z. Photolithographic boronate affinity molecular imprinting: a general and facile approach for glycoprotein imprinting. Angew. Chem. Int. Ed. 52, 7451–7454 (2013).

    Article  CAS  Google Scholar 

  50. Wang, S. S., Ye, J., Bie, Z. J. & Liu, Z. Affinity-tunable specific recognition of glycoproteins via boronate affinity-based controllable oriented surface imprinting. Chem. Sci. 5, 1135–1140 (2014).

    Article  CAS  Google Scholar 

  51. Lee, P. C. & Meisel, D. Adsorption and surface-enhanced Raman of dyes on silver and gold sols. J. Phy. Chem. 86, 3391–3395 (1982).

    Article  CAS  Google Scholar 

  52. Ye, J., Chen, Y. & Liu, Z. A boronate affinity sandwich assay: an appealing alternative to immunoassays for the determination of glycoproteins. Angew. Chem. Int. Ed. 53, 10386–10389 (2014).

    Article  CAS  Google Scholar 

  53. Bie, Z. J., Chen, Y., Ye, J., Wang, S. S. & Liu, Z. Boronate-affinity glycan-oriented surface imprinting: a new strategy to mimic lectins for the recognition of an intact glycoprotein and its characteristic fragments. Angew. Chem. Int. Ed. 54, 10211–10215 (2015).

    Article  CAS  Google Scholar 

  54. Delean, A., Munson, P. J. & Rodbard, D. Simultaneous analysis of families of sigmoidal curves-application to bioassay, radioligand assay, and physiological dose-response curves. Am. J. Physiol. 235, E97–E102 (1978).

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

This work is supported by Key Scientific Instrumentation Grant (21627810) from the National Natural Science Foundation of China, and Excellent Research Program of Nanjing University (ZYJH004).

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J.L., R.Y.W. and Z.L. developed the protocol. J.L., H.H. and Z.L. wrote the paper. All authors have discussed the results and approved the final version of the manuscript.

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Correspondence to Zhen Liu.

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Peer review information Nature Protocols thanks Jakub Dostálek, Ugur Tamer and the other, anonymous reviewer(s) for their contribution to the peer review of this work.

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Key references using this protocol

Liu, J. et al. Angew. Chem. Int. Ed. 55, 13215–13218 (2016): https://onlinelibrary.wiley.com/doi/full/10.1002/anie.201608237

Liu, J. et al. Chem. Sci. 9, 7241–7246 (2018): https://pubs.rsc.org/en/content/articlepdf/2018/sc/c8sc02533a

Wen, Y. R. et al. Anal. Chem. 92, 12498–12508 (2020): https://pubs.acs.org/doi/10.1021/acs.analchem.0c02344

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Source Data Fig. 5

Raw data for Fig. 5e and 5f.

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Liu, J., He, H., Xie, D. et al. Probing low-copy-number proteins in single living cells using single-cell plasmonic immunosandwich assays. Nat Protoc 16, 3522–3546 (2021). https://doi.org/10.1038/s41596-021-00547-9

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