Skip to main content

Thank you for visiting You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

High-dimensional cell-level analysis of tissues with Ce3D multiplex volume imaging


Understanding the structure–function relationships between diverse cell types in a complex organ environment requires detailed in situ reconstruction of cell-associated molecular properties in the context of 3D, macro-scale tissue architecture. We recently developed clearing-enhanced 3D (Ce3D), a simple and effective method for tissue clearing that achieves excellent transparency; preserves cell morphology, tissue architecture, and reporter molecule fluorescence; and is robustly compatible with direct immunolabeling. These characteristics permit high-quality multiplex fluorescence microscopy of large tissue volumes, as well as image analysis using advanced platforms such as volumetric histocytometry, collectively allowing quantitative characterization of cells with respect to their spatial positioning within tissues on the basis of phenotypic and functional markers. Ce3D clearing is fast, achieving robust transparency of most tissues within 24 h, albeit still necessitating additional time for staining, imaging, and analysis (1–2 weeks). Here, we provide detailed procedures for tissue clearing using Ce3D, including optimized workflows for tissue processing and staining, as well as treatment of difficult-to-clear organs such as the brain. We also describe a new procedure for RNA detection in Ce3D-treated tissues, as well as provide additional details for the volumetric histocytometry data processing steps. Finally, we discuss limitations and work-around strategies for improving antibody-based tissue immunolabeling, fluorophore multiplexing, large-volume microscopy, and computational analysis of large image datasets. Together, these detailed procedures and solutions for high-resolution volumetric microscopy with Ce3D enable quantitative visualization of cells and tissues at a high level of detail, allowing exploration of cellular spatial relationships in a variety of tissue settings.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Fig. 1: Flowchart of Ce3D clearing, imaging, and analysis protocol.
Fig. 2: Clearing, mounting, and microscope setup.
Fig. 3: Volumetric Ce3D microscopy of diverse organs.
Fig. 4: 3D in situ hybridization with immunostaining.
Fig. 5: Volumetric histocytometry example workflow.

Data availability

The image datasets generated and/or analyzed during the current study are available from the corresponding authors upon reasonable request.


  1. 1.

    Spitzer, M. H. & Nolan, G. P. Mass cytometry: single cells, many features. Cell 165, 780–791 (2016).

    CAS  Article  Google Scholar 

  2. 2.

    Alcantara-Hernandez, M. et al. High-dimensional phenotypic mapping of human dendritic cells reveals interindividual variation and tissue specialization. Immunity 47, 1037–1050 (2017).

    CAS  Article  Google Scholar 

  3. 3.

    Papalexi, E. & Satija, R. Single-cell RNA sequencing to explore immune cell heterogeneity. Nat. Rev. Immunol. 18, 35–45 (2018).

    CAS  Article  Google Scholar 

  4. 4.

    Altschuler, S. J. & Wu, L. F. Cellular heterogeneity: do differences make a difference? Cell 141, 559–563 (2010).

    CAS  Article  Google Scholar 

  5. 5.

    Junttila, M. R. & de Sauvage, F. J. Influence of tumour micro-environment heterogeneity on therapeutic response. Nature 501, 346–354 (2013).

    CAS  Article  Google Scholar 

  6. 6.

    Cutrale, F. et al. Hyperspectral phasor analysis enables multiplexed 5D in vivo imaging. Nat. Methods 14, 149–152 (2017).

    CAS  Article  Google Scholar 

  7. 7.

    Gerner, M. Y., Kastenmuller, W., Ifrim, I., Kabat, J. & Germain, R. N. Histo-cytometry: a method for highly multiplex quantitative tissue imaging analysis applied to dendritic cell subset microanatomy in lymph nodes. Immunity 37, 364–376 (2012).

    CAS  Article  Google Scholar 

  8. 8.

    Lin, J. R., Fallahi-Sichani, M. & Sorger, P. K. Highly multiplexed imaging of single cells using a high-throughput cyclic immunofluorescence method. Nat. Commun. 6, 8390 (2015).

    CAS  Article  Google Scholar 

  9. 9.

    Goltsev, Y. et al. Deep profiling of mouse splenic architecture with CODEX multiplexed imaging. Cell 174, 968–981 (2018).

    CAS  Article  Google Scholar 

  10. 10.

    Keren, L. et al. A structured tumor-immune microenvironment in triple negative breast cancer revealed by multiplexed ion beam imaging. Cell 174, 1373–1387 (2018).

    CAS  Article  Google Scholar 

  11. 11.

    Gerner, M. Y., Torabi-Parizi, P. & Germain, R. N. Strategically localized dendritic cells promote rapid T cell responses to lymph-borne particulate antigens. Immunity 42, 172–185 (2015).

    CAS  Article  Google Scholar 

  12. 12.

    Vu Manh, T. P., Bertho, N., Hosmalin, A., Schwartz-Cornil, I. & Dalod, M. Investigating evolutionary conservation of dendritic cell subset identity and functions. Front. Immunol. 6, 260 (2015).

    Google Scholar 

  13. 13.

    Gerner, M. Y., Casey, K. A., Kastenmuller, W. & Germain, R. N. Dendritic cell and antigen dispersal landscapes regulate T cell immunity. J. Exp. Med. 214, 3105–3122 (2017).

    CAS  Article  Google Scholar 

  14. 14.

    Im, S. J. et al. Defining CD8+ T cells that provide the proliferative burst after PD-1 therapy. Nature 537, 417–421 (2016).

    CAS  Article  Google Scholar 

  15. 15.

    Liu, Z. et al. Immune homeostasis enforced by co-localized effector and regulatory T cells. Nature 528, 225–230 (2015).

    CAS  Article  Google Scholar 

  16. 16.

    Petrovas, C. et al. Follicular CD8 T cells accumulate in HIV infection and can kill infected cells in vitro via bispecific antibodies. Sci. Transl. Med. 9, aag2285 (2017).

    Article  Google Scholar 

  17. 17.

    Petrovas, C. et al. CD4 T follicular helper cell dynamics during SIV infection. J. Clin. Invest. 122, 3281–3294 (2012).

    CAS  Article  Google Scholar 

  18. 18.

    Preite, S. et al. Hyperactivated PI3Kdelta promotes self and commensal reactivity at the expense of optimal humoral immunity. Nat. Immunol. 19, 986–1000 (2018).

    CAS  Article  Google Scholar 

  19. 19.

    Sayin, I. et al. Spatial distribution and function of T follicular regulatory cells in human lymph nodes. J. Exp. Med. 215, 1531–1542 (2018).

    CAS  Article  Google Scholar 

  20. 20.

    Mao, K. et al. Innate and adaptive lymphocytes sequentially shape the gut microbiota and lipid metabolism. Nature 554, 255–259 (2018).

    CAS  Article  Google Scholar 

  21. 21.

    Fonseca, D. M. et al. Microbiota-dependent sequelae of acute infection compromise tissue-specific immunity. Cell 163, 354–366 (2015).

    Article  Google Scholar 

  22. 22.

    Radtke, A. J. et al. Lymph-node resident CD8α+ dendritic cells capture antigens from migratory malaria sporozoites and induce CD8+ T cell responses. PLoS Pathog. 11, e1004637 (2015).

    Article  Google Scholar 

  23. 23.

    Steinert, E. M. et al. Quantifying memory CD8 T cells reveals regionalization of immunosurveillance. Cell 161, 737–749 (2015).

    CAS  Article  Google Scholar 

  24. 24.

    Masuda, A. et al. An improved method for isolation of epithelial and stromal cells from the human endometrium. J. Reprod. Dev. 62, 213–218 (2016).

    CAS  Article  Google Scholar 

  25. 25.

    Jabbari, A., Legge, K. L. & Harty, J. T. T cell conditioning explains early disappearance of the memory CD8 T cell response to infection. J. Immunol. 177, 3012–3018 (2006).

    CAS  Article  Google Scholar 

  26. 26.

    Richardson, D. S. & Lichtman, J. W. Clarifying tissue clearing. Cell 162, 246–257 (2015).

    CAS  Article  Google Scholar 

  27. 27.

    Tainaka, K., Kuno, A., Kubota, S. I., Murakami, T. & Ueda, H. R. Chemical principles in tissue clearing and staining protocols for whole-body cell profiling. Annu. Rev. Cell Dev. Biol. 32, 713–741 (2016).

    CAS  Article  Google Scholar 

  28. 28.

    Erturk, A. et al. Three-dimensional imaging of solvent-cleared organs using 3DISCO. Nat. Protoc. 7, 1983–1995 (2012).

    CAS  Article  Google Scholar 

  29. 29.

    Renier, N. et al. iDISCO: a simple, rapid method to immunolabel large tissue samples for volume imaging. Cell 159, 896–910 (2014).

    CAS  Article  Google Scholar 

  30. 30.

    Hama, H. et al. ScaleS: an optical clearing palette for biological imaging. Nat. Neurosci. 18, 1518–1529 (2015).

    CAS  Article  Google Scholar 

  31. 31.

    Hama, H. et al. Scale: a chemical approach for fluorescence imaging and reconstruction of transparent mouse brain. Nat. Neurosci. 14, 1481–1488 (2011).

    CAS  Article  Google Scholar 

  32. 32.

    Tainaka, K. et al. Whole-body imaging with single-cell resolution by tissue decolorization. Cell 159, 911–924 (2014).

    CAS  Article  Google Scholar 

  33. 33.

    Chung, K. et al. Structural and molecular interrogation of intact biological systems. Nature 497, 332–337 (2013).

    CAS  Article  Google Scholar 

  34. 34.

    Yang, B. et al. Single-cell phenotyping within transparent intact tissue through whole-body clearing. Cell 158, 945–958 (2014).

    CAS  Article  Google Scholar 

  35. 35.

    Murray, E. et al. Simple, scalable proteomic imaging for high-dimensional profiling of intact systems. Cell 163, 1500–1514 (2015).

    CAS  Article  Google Scholar 

  36. 36.

    Dodt, H. U. et al. Ultramicroscopy: three-dimensional visualization of neuronal networks in the whole mouse brain. Nat. Methods 4, 331–336 (2007).

    CAS  Article  Google Scholar 

  37. 37.

    Kuwajima, T. et al. ClearT: a detergent- and solvent-free clearing method for neuronal and non-neuronal tissue. Development 140, 1364–1368 (2013).

    CAS  Article  Google Scholar 

  38. 38.

    Ke, M. T., Fujimoto, S. & Imai, T. SeeDB: a simple and morphology-preserving optical clearing agent for neuronal circuit reconstruction. Nat. Neurosci. 16, 1154–1161 (2013).

    CAS  Article  Google Scholar 

  39. 39.

    Ke, M. T. et al. Super-resolution mapping of neuronal circuitry with an index-optimized clearing agent. Cell Rep. 14, 2718–2732 (2016).

    CAS  Article  Google Scholar 

  40. 40.

    Pan, C. et al. Shrinkage-mediated imaging of entire organs and organisms using uDISCO. Nat. Methods 13, 859–867 (2016).

    CAS  Article  Google Scholar 

  41. 41.

    Murakami, T. C. et al. A three-dimensional single-cell-resolution whole-brain atlas using CUBIC-X expansion microscopy and tissue clearing. Nat. Neurosci. 21, 625–637 (2018).

    CAS  Article  Google Scholar 

  42. 42.

    Tainaka, K. et al. Chemical landscape for tissue clearing based on hydrophilic reagents. Cell Rep. 24, 2196–2210 (2018).

    CAS  Article  Google Scholar 

  43. 43.

    Kubota, S. I. et al. Whole-body profiling of cancer metastasis with single-cell resolution. Cell Rep. 20, 236–250 (2017).

    CAS  Article  Google Scholar 

  44. 44.

    Li, W., Germain, R. N. & Gerner, M. Y. Multiplex, quantitative cellular analysis in large tissue volumes with clearing-enhanced 3D microscopy (Ce3D). Proc. Natl. Acad. Sci. USA 114, E7321–E7330 (2017).

    CAS  Article  Google Scholar 

  45. 45.

    Wang, F. et al. RNAscope: a novel in situ RNA analysis platform for formalin-fixed, paraffin-embedded tissues. J. Mol. Diagn. 14, 22–29 (2012).

    CAS  Article  Google Scholar 

  46. 46.

    Katoh, K. Microwave-assisted tissue preparation for rapid fixation, decalcification, antigen retrieval, cryosectioning, and immunostaining. Int. J. Cell Biol. 2016, 7076910 (2016).

    Article  Google Scholar 

  47. 47.

    Beghein, E. & Gettemans, J. Nanobody technology: a versatile toolkit for microscopic imaging, protein-protein interaction analysis, and protein function exploration. Front. Immunol. 8, 771 (2017).

    Article  Google Scholar 

  48. 48.

    Liu, T. L. et al. Observing the cell in its native state: imaging subcellular dynamics in multicellular organisms. Science 360, eaaq1392 (2018).

    Article  Google Scholar 

Download references


We thank K. Mao for helping with gut and mammary gland tissue preparation. In addition, we thank all members of the Laboratory of Immune System Biology, National Institute of Allergy and Infectious Diseases (NIAID) at the NIH for many helpful comments during the course of these experiments. This research was supported by the Intramural Research Program, NIAID, NIH, and NIH grant no. R01AI134713 MYG.

Author information




W.L., M.Y.G., and R.N.G. designed the experiments. W.L. and M.Y.G. performed the experiments and analysis. M.Y.G., W.L., and R.N.G. wrote the paper.

Corresponding authors

Correspondence to Ronald N. Germain or Michael Y. Gerner.

Ethics declarations

Competing interests

A patent for the methodology described in this paper was filed with the US Patent Office (PCT Patent Application PCT/US2017/049133, HHS reference no. E–168–2016, ‘Enhanced Tissue Clearing Solution, Clearing-Enhanced 3D (Ce3D), Compatible With Advanced Fluorescence Microscopy Imaging’).

Additional information

Journal peer review information: Nature Protocols thanks Michael Donovan and Constantinos Petrovas for their contribution to the peer review of this work.

Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Related links

Key references using this protocol

Li, W., Germain, R.N. and Gerner, M.Y. PNAS 114, E7321–E7330 (2017):

Gerner, M.Y., Kastenmuller, W., Ifrim, I., Kabat, J. & Germain, R.N. Immunity 37, 364–376 (2012):

Liu, Z. et al. Nature 528, 225–230 (2015):

Supplementary information

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Li, W., Germain, R.N. & Gerner, M.Y. High-dimensional cell-level analysis of tissues with Ce3D multiplex volume imaging. Nat Protoc 14, 1708–1733 (2019).

Download citation

Further reading


By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.


Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing