Skip to main content

Thank you for visiting nature.com. 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.

Tissue clearing and its applications in neuroscience

A Publisher Correction to this article was published on 09 March 2020

This article has been updated

Abstract

State-of-the-art tissue-clearing methods provide subcellular-level optical access to intact tissues from individual organs and even to some entire mammals. When combined with light-sheet microscopy and automated approaches to image analysis, existing tissue-clearing methods can speed up and may reduce the cost of conventional histology by several orders of magnitude. In addition, tissue-clearing chemistry allows whole-organ antibody labelling, which can be applied even to thick human tissues. By combining the most powerful labelling, clearing, imaging and data-analysis tools, scientists are extracting structural and functional cellular and subcellular information on complex mammalian bodies and large human specimens at an accelerated pace. The rapid generation of terabyte-scale imaging data furthermore creates a high demand for efficient computational approaches that tackle challenges in large-scale data analysis and management. In this Review, we discuss how tissue-clearing methods could provide an unbiased, system-level view of mammalian bodies and human specimens and discuss future opportunities for the use of these methods in human neuroscience.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Fig. 1: Major tissue-clearing methods and their key features.
Fig. 2: Whole-brain single-cell-resolution imaging and analysis.
Fig. 3: The SHIELD–MAP and AAV-based labelling system.
Fig. 4: Towards a 3D developmental human cell atlas.
Fig. 5: Resolution and speed of custom and commercial light-sheet microscopes.

Change history

  • 09 March 2020

    An amendment to this paper has been published and can be accessed via a link at the top of the paper.

References

  1. 1.

    Spalteholz, W. Über das Durchsichtigmachen von Menschlichen und Tierischen Präparaten. (S. Hirzel, 1914).

  2. 2.

    Chung, K. et al. Structural and molecular interrogation of intact biological systems. Nature 497, 332–337 (2013). This article is the first to demonstrate in situ synthesis of a hydrogel and its fusion with tissue via covalent bonds to form a cleared tissue–hydrogel hybrid.

    CAS  PubMed  PubMed Central  Google Scholar 

  3. 3.

    Yang, B. et al. Single-cell phenotyping within transparent intact tissue through whole-body clearing. Cell 158, 945–958 (2014). This article first reports clearing of adult rodents via the vasculature; RNA detection in cleared tissues with single-molecule resolution by single-molecule fluorescence in situ hybridization and that specific formulations of tissue–hydrogel hybrids can significantly expand.

    CAS  PubMed  PubMed Central  Google Scholar 

  4. 4.

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

    CAS  PubMed  Google Scholar 

  5. 5.

    Susaki, E. A. et al. Whole-brain imaging with single-cell resolution using chemical cocktails and computational analysis. Cell 157, 726–739 (2014). This article first reports on the delipidation activity of amino alcohols and the high-performance hydrophilic tissue-clearing method CUBIC and reports tissue clearing of the marmoset brain.

    CAS  PubMed  Google Scholar 

  6. 6.

    Tainaka, K. et al. Whole-body imaging with single-cell resolution by tissue decolorization. Cell 159, 911–924 (2014). This article first demonstrates that decolourization of haem is possible in mild chemical conditions by amino alcohols, and reports whole-body imaging of the adult mouse.

    CAS  PubMed  Google Scholar 

  7. 7.

    Ertürk, A. et al. Three-dimensional imaging of the unsectioned adult spinal cord to assess axon regeneration and glial responses after injury. Nat. Med. 18, 166–171 (2012). This work demonstrates the application of an organic solvent-clearing method (3DISCO) on the intact adult mouse CNS to study neurodegeneration and regeneration.

    Google Scholar 

  8. 8.

    Belle, M. et al. A simple method for 3D analysis of immunolabeled axonal tracts in a transparent nervous system. Cell Rep. 9, 1191–1201 (2014). This work is the first to combine whole-mount immunostaining, 3DISCO clearing and light-sheet microscopy to analyse axon guidance defects in mutant mice.

    CAS  PubMed  Google Scholar 

  9. 9.

    Treweek, J. B. et al. Whole-body tissue stabilization and selective extractions via tissue-hydrogel hybrids for high-resolution intact circuit mapping and phenotyping. Nat. Protoc. 10, 1860–1896 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  10. 10.

    Costantini, I. et al. A versatile clearing agent for multi-modal brain imaging. Sci. Rep. 5, 9808 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  11. 11.

    Klingberg, A. et al. Fully automated evaluation of total glomerular number and capillary tuft size in nephritic kidneys using lightsheet microscopy. J. Am. Soc. Nephrol. 28, 452–459 (2017).

    CAS  PubMed  Google Scholar 

  12. 12.

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

    CAS  PubMed  Google Scholar 

  13. 13.

    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  PubMed  Google Scholar 

  14. 14.

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

    CAS  PubMed  Google Scholar 

  15. 15.

    Susaki, E. A. & Ueda, H. R. Whole-body and whole-organ clearing and imaging techniques with single-cell resolution: toward organism-level systems biology in mammals. Cell Chem. Biol. 23, 137–157 (2016).

    CAS  PubMed  Google Scholar 

  16. 16.

    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  PubMed  Google Scholar 

  17. 17.

    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). This article first demonstrates the polymer-gel property of a fixed mouse brain in the absence of exogenous polymers, reports expansion microscopy using hydrophilic reagents and reports the generation of a 3D single-cell-resolution mouse brain atlas, the CUBIC-Atlas.

    CAS  PubMed  Google Scholar 

  18. 18.

    Amiya, T. & Tanaka, T. Phase transitions in crosslinked gels of natural polymers. Macromolecules 20, 1162–1164 (1987).

    CAS  Google Scholar 

  19. 19.

    Shibayama, M. & Tanaka, T. in Responsive Gels: Volume Transitions I 1–62 (Springer, 1993).

  20. 20.

    Lorentz, H. A. Ueber die Beziehung zwischen der Fortpflanzungsgeschwindigkeit des Lichtes und der Körperdichte. Ann. Phys. 9, 641–665 (1880).

    Google Scholar 

  21. 21.

    Lorenz, L. Ueber die Refractionsconstante. Ann. Phys. 11, 70–103 (1880).

    Google Scholar 

  22. 22.

    Tainaka, K. et al. Chemical landscape for tissue clearing based on hydrophilic reagents. Cell Rep. 24, 2196–2210 (2018). This article first reports the chemical profiling of hydrophilic tissue-clearing reagents and proposes chemical principles of hydrophilic tissue-clearing methods.

    CAS  PubMed  Google Scholar 

  23. 23.

    Belle, M. et al. Tridimensional visualization and analysis of early human development. Cell 169, 161–173 e112 (2017). This study uses 3D imaging of cleared human embryos and fetuses to provide the first comprehensive description of the development of the human peripheral nervous system and the innervation pattern of many organs in intact specimens.

    CAS  PubMed  Google Scholar 

  24. 24.

    Kim, S. Y. et al. Stochastic electrotransport selectively enhances the transport of highly electromobile molecules. Proc. Natl Acad. Sci. USA 112, E6274–E6283 (2015).

    CAS  PubMed  Google Scholar 

  25. 25.

    Murray, E. et al. Simple, scalable proteomic imaging for high-dimensional profiling of intact systems. Cell 163, 1500–1514 (2015). This article is the first to demonstrate that controlling the chemical interaction time and kinetics achieves more uniform and scalable processing of large-scale tissues.

    CAS  PubMed  PubMed Central  Google Scholar 

  26. 26.

    Renier, N. et al. Mapping of brain activity by automated volume analysis of immediate early genes. Cell 165, 1789–1802 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  27. 27.

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

    CAS  PubMed  Google Scholar 

  28. 28.

    Cai, R. et al. Panoptic imaging of transparent mice reveals whole-body neuronal projections and skull–meninges connections. Nat. Neurosci. 22, 317–327 (2019). This study shows that vDISCO boosted fluorescent protein signal in intact transparent mice, thereby allowing detection of widespread CNS trauma effects, and reveals short vascular connections between the skull marrow and brain meninges.

    CAS  PubMed  Google Scholar 

  29. 29.

    Deverman, B. E. et al. Cre-dependent selection yields AAV variants for widespread gene transfer to the adult brain. Nat. Biotechnol. 34, 204–209 (2016). This is the first article to report efficient crossing of the blood–brain barrier in adult rodents by an engineered adeno-associated virus vector able to package the cargo of choice. A Cre-enzyme-based viral-vector screening method is introduced and it is demonstrated how whole-body tissue clearing can facilitate transduction maps of systemically delivered genes.

    CAS  PubMed  PubMed Central  Google Scholar 

  30. 30.

    Bedbrook, C. N., Deverman, B. E. & Gradinaru, V. Viral strategies for targeting the central and peripheral nervous systems. Annu. Rev. Neurosci. 41, 323–348 (2018).

    CAS  PubMed  Google Scholar 

  31. 31.

    Keller, P. J. & Ahrens, M. B. Visualizing whole-brain activity and development at the single-cell level using light-sheet microscopy. Neuron 85, 462–483 (2015).

    CAS  PubMed  Google Scholar 

  32. 32.

    Vigouroux, R. J., Belle, M. & Chédotal, A. Neuroscience in the third dimension: shedding new light on the brain with tissue clearing. Mol. Brain 10, 33 (2017).

    PubMed  PubMed Central  Google Scholar 

  33. 33.

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

    PubMed  Google Scholar 

  34. 34.

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

    CAS  PubMed  PubMed Central  Google Scholar 

  35. 35.

    Acar, M. et al. Deep imaging of bone marrow shows non-dividing stem cells are mainly perisinusoidal. Nature 526, 126–130 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  36. 36.

    Espinosa-Medina, I. et al. Parasympathetic ganglia derive from Schwann cell precursors. Science 345, 87–90 (2014).

    CAS  PubMed  Google Scholar 

  37. 37.

    Oshimori, N., Oristian, D. & Fuchs, E. TGF-β promotes heterogeneity and drug resistance in squamous cell carcinoma. Cell 160, 963–976 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  38. 38.

    Garofalo, S. et al. Enriched environment reduces glioma growth through immune and non-immune mechanisms in mice. Nat. Commun. 6, 6623 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  39. 39.

    von Neubeck, B. et al. An inhibitory antibody targeting carbonic anhydrase XII abrogates chemoresistance and significantly reduces lung metastases in an orthotopic breast cancer model in vivo. Int. J. Cancer 143, 2065–2075 (2018).

    Google Scholar 

  40. 40.

    Tanaka, N. et al. Whole-tissue biopsy phenotyping of three-dimensional tumours reveals patterns of cancer heterogeneity. Nat. Biomed. Eng. 1, 796–806 (2017).

    CAS  PubMed  Google Scholar 

  41. 41.

    Garvalov, B. K. & Ertürk, A. Seeing whole-tumour heterogeneity. Nat. Biomed. Eng. 1, 772–774 (2017).

    PubMed  Google Scholar 

  42. 42.

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

    CAS  PubMed  Google Scholar 

  43. 43.

    Herisson, F. et al. Direct vascular channels connect skull bone marrow and the brain surface enabling myeloid cell migration. Nat. Neurosci. 21, 1209–1217 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  44. 44.

    Pan, C. et al. Deep learning reveals cancer metastasis and therapeutic antibody targeting in whole body. Cell 179, 1661–1676.e19 (2019). This works describes a novel method to detect and quantify cancer metastasis and antibody drug targeting at cellular resolution in the entire mouse using whole-body clearing and deep learning.

    PubMed  Google Scholar 

  45. 45.

    Chiang, A. S. et al. Three-dimensional mapping of brain neuropils in the cockroach, Diploptera punctata. J. Comp. Neurol. 440, 1–11 (2001).

    CAS  PubMed  Google Scholar 

  46. 46.

    Liu, Y.-C. & Chiang, A.-S. High-resolution confocal imaging and three-dimensional rendering. Methods 30, 86–93 (2003).

    CAS  PubMed  Google Scholar 

  47. 47.

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

    CAS  PubMed  PubMed Central  Google Scholar 

  48. 48.

    Hirshburg, J., Choi, B., Nelson, J. S. & Yeh, A. T. Correlation between collagen solubility and skin optical clearing using sugars. Lasers Surg. Med. 39, 140–144 (2007).

    PubMed  Google Scholar 

  49. 49.

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

    CAS  PubMed  Google Scholar 

  50. 50.

    Chance, B., Liu, H., Kitai, T. & Zhang, Y. Effects of solutes on optical properties of biological materials: models, cells, and tissues. Anal. Biochem. 227, 351–362 (1995).

    CAS  PubMed  Google Scholar 

  51. 51.

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

    CAS  PubMed  Google Scholar 

  52. 52.

    Susaki, E. A. et al. Advanced CUBIC protocols for whole-brain and whole-body clearing and imaging. Nat. Protoc. 10, 1709–1727 (2015).

    CAS  PubMed  Google Scholar 

  53. 53.

    Tatsuki, F. et al. Involvement of Ca2+-dependent hyperpolarization in sleep duration in mammals. Neuron 90, 70–85 (2016).

    CAS  PubMed  Google Scholar 

  54. 54.

    Economo, M. N. et al. A platform for brain-wide imaging and reconstruction of individual neurons. eLife 5, e10566 (2016).

    PubMed  PubMed Central  Google Scholar 

  55. 55.

    Wang, L. et al. The coding of valence and identity in the mammalian taste system. Nature 558, 127–131 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  56. 56.

    Justus, D. et al. Glutamatergic synaptic integration of locomotion speed via septoentorhinal projections. Nat. Neurosci. 20, 16–19 (2017).

    CAS  PubMed  Google Scholar 

  57. 57.

    Romanov, R. A. et al. Molecular interrogation of hypothalamic organization reveals distinct dopamine neuronal subtypes. Nat. Neurosci. 20, 176–188 (2017).

    CAS  Google Scholar 

  58. 58.

    Lanjakornsiripan, D. et al. Layer-specific morphological and molecular differences in neocortical astrocytes and their dependence on neuronal layers. Nat. Commun. 9, 1623 (2018).

    PubMed  PubMed Central  Google Scholar 

  59. 59.

    Rousso, D. L. et al. Two pairs of on and off retinal ganglion cells are defined by intersectional patterns of transcription factor expression. Cell Rep. 15, 1930–1944 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  60. 60.

    Chen, J. Y. et al. Hoxb5 marks long-term haematopoietic stem cells and reveals a homogenous perivascular niche. Nature 530, 223–227 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  61. 61.

    Cuccarese, M. F. et al. Heterogeneity of macrophage infiltration and therapeutic response in lung carcinoma revealed by 3D organ imaging. Nat. Commun. 8, 14293 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  62. 62.

    Davis, F. M. et al. Single-cell lineage tracing in the mammary gland reveals stochastic clonal dispersion of stem/progenitor cell progeny. Nat. Commun. 7, 13053 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  63. 63.

    Li, J. et al. Single-cell lineage tracing reveals that oriented cell division contributes to trabecular morphogenesis and regional specification. Cell Rep. 15, 158–170 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  64. 64.

    Yamamoto, J. et al. Neuronal signals regulate obesity induced beta-cell proliferation by FoxM1 dependent mechanism. Nat. Commun. 8, 1930 (2017).

    PubMed  PubMed Central  Google Scholar 

  65. 65.

    Chen, F., Tillberg, P. W. & Boyden, E. S. Expansion microscopy. Science 347, 543–548 (2015). This article first reports the concept of expansion microscopy based on an exogenous hydrogel polymer.

    CAS  PubMed  PubMed Central  Google Scholar 

  66. 66.

    Matsumoto, K. et al. Advanced CUBIC tissue clearing for whole-organ cell profiling. Nat. Protoc. 14, 3506–3537 (2019).

    CAS  PubMed  Google Scholar 

  67. 67.

    Tomer, R., Ye, L., Hsueh, B. & Deisseroth, K. Advanced CLARITY for rapid and high-resolution imaging of intact tissues. Nat. Protoc. 9, 1682–1697 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  68. 68.

    Gradinaru, V., Treweek, J., Overton, K. & Deisseroth, K. Hydrogel-tissue chemistry: principles and applications. Annu. Rev. Biophys. 47, 355–376 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  69. 69.

    Ku, T. et al. Multiplexed and scalable super-resolution imaging of three-dimensional protein localization in size-adjustable tissues. Nat. Biotechnol. 34, 973–981 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  70. 70.

    Sylwestrak, E. L., Rajasethupathy, P., Wright, M. A., Jaffe, A. & Deisseroth, K. Multiplexed intact-tissue transcriptional analysis at cellular resolution. Cell 164, 792–804 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  71. 71.

    Park, Y.-G. et al. Protection of tissue physicochemical properties using polyfunctional crosslinkers. Nat. Biotechnol. 37, 73–83 (2019). This article is the first to demonstrate protection of tissue and biomolecular properties against harsh stress using polyfunctional crosslinkers.

    CAS  Google Scholar 

  72. 72.

    Renner, M. et al. Self-organized developmental patterning and differentiation in cerebral organoids. EMBO J. 36, 1316–1329 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  73. 73.

    Canter, R. G. et al. 3D mapping reveals network-specific amyloid progression and subcortical susceptibility in mice. Commun. Biol. 2, 360 (2019).

    Google Scholar 

  74. 74.

    Greenbaum, A. et al. Bone CLARITY: clearing, imaging, and computational analysis of osteoprogenitors within intact bone marrow. Sci. Transl Med. 9, eaah6518 (2017). This article reports clearing of whole bone with preserved marrow and imaging endogenous fluorescence with single-cell resolution throughout the marrow by light-sheet microscopy.

    PubMed  Google Scholar 

  75. 75.

    Greenbaum, A., Jang, M. J., Challis, C. & Gradinaru, V. Q&A: how can advances in tissue clearing and optogenetics contribute to our understanding of normal and diseased biology? BMC Biol. 15, 87 (2017).

    PubMed  PubMed Central  Google Scholar 

  76. 76.

    Shah, S. et al. Single-molecule RNA detection at depth via hybridization chain reaction and tissue hydrogel embedding and clearing. Development 143, 2862–2867 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  77. 77.

    DePas, W. H. et al. Exposing the three-dimensional biogeography and metabolic states of pathogens in cystic fibrosis sputum via hydrogel embedding, clearing, and rRNA labeling. mBio 7, e00796–e00816 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  78. 78.

    Treweek, J. B. & Gradinaru, V. Extracting structural and functional features of widely distributed biological circuits with single cell resolution via tissue clearing and delivery vectors. Curr. Opin. Biotechnol. 40, 193–207 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  79. 79.

    Menegas, W. et al. Dopamine neurons projecting to the posterior striatum form an anatomically distinct subclass. eLife 4, e10032 (2015).

    PubMed  PubMed Central  Google Scholar 

  80. 80.

    Chan, K. Y. et al. Engineered AAVs for efficient noninvasive gene delivery to the central and peripheral nervous systems. Nat. Neurosci. 20, 1172–1179 (2017). This article reports novel viral vectors to deliver cargo to neurons throughout the brain and body via the bloodstream, and a complementary vector toolbox for sparse stochastic labelling for morphological assessment. These delivery methods for Golgi-like genetic labelling can complement tissue clearing and microscopy methods to yield refined maps of the nervous system across the brain and body.

    CAS  PubMed  PubMed Central  Google Scholar 

  81. 81.

    Robinson, J. E. & Gradinaru, V. Dopaminergic dysfunction in neurodevelopmental disorders: recent advances and synergistic technologies to aid basic research. Curr. Opin. Neurobiol. 48, 17–29 (2018).

    CAS  PubMed  Google Scholar 

  82. 82.

    Liebmann, T. et al. Three-dimensional study of Alzheimer’s disease hallmarks using the iDISCO clearing method. Cell Rep. 16, 1138–1152 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  83. 83.

    Welniarz, Q. et al. Non cell-autonomous role of DCC in the guidance of the corticospinal tract at the midline. Sci. Rep. 7, 410 (2017).

    PubMed  PubMed Central  Google Scholar 

  84. 84.

    Hruska, M., Henderson, N., Le Marchand, S. J., Jafri, H. & Dalva, M. B. Synaptic nanomodules underlie the organization and plasticity of spine synapses. Nat. Neurosci. 21, 671–682 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  85. 85.

    Ando, K. et al. Inside Alzheimer brain with CLARITY: senile plaques, neurofibrillary tangles and axons in 3-D. Acta Neuropathol. 128, 457–459 (2014).

    PubMed  PubMed Central  Google Scholar 

  86. 86.

    Morawski, M. et al. Developing 3D microscopy with CLARITY on human brain tissue: towards a tool for informing and validating MRI-based histology. Neuroimage 182, 417–428 (2018).

    PubMed  PubMed Central  Google Scholar 

  87. 87.

    Phillips, J. et al. Development of passive CLARITY and immunofluorescent labelling of multiple proteins in human cerebellum: understanding mechanisms of neurodegeneration in mitochondrial disease. Sci. Rep. 6, 26013 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  88. 88.

    Liu, A. K. L. et al. Bringing CLARITY to the human brain: visualization of Lewy pathology in three dimensions. Neuropathol. Appl. Neurobiol. 42, 573–587 (2016).

    CAS  PubMed  Google Scholar 

  89. 89.

    Lee, E. et al. ACT-PRESTO: rapid and consistent tissue clearing and labeling method for 3-dimensional (3D) imaging. Sci. Rep. 6, 18631 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  90. 90.

    Lai, H. M. et al. Next generation histology methods for three-dimensional imaging of fresh and archival human brain tissues. Nat. Commun. 9, 1066 (2018).

    PubMed  PubMed Central  Google Scholar 

  91. 91.

    Allen, J. S., Damasio, H. & Grabowski, T. J. Normal neuroanatomical variation in the human brain: an MRI-volumetric study. Am. J. Phys. Anthropol. 118, 341–358 (2002).

    PubMed  Google Scholar 

  92. 92.

    Birey, F. et al. Assembly of functionally integrated human forebrain spheroids. Nature 545, 54–59 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  93. 93.

    Casoni, F. et al. Development of the neurons controlling fertility in humans: new insights from 3D imaging and transparent fetal brains. Development 143, 3969–3981 (2016).

    CAS  PubMed  Google Scholar 

  94. 94.

    Hsueh, B. et al. Pathways to clinical CLARITY: volumetric analysis of irregular, soft, and heterogeneous tissues in development and disease. Sci. Rep. 7, 5899 (2017).

    PubMed  PubMed Central  Google Scholar 

  95. 95.

    Behjati, S., Lindsay, S., Teichmann, S. A. & Haniffa, M. Mapping human development at single-cell resolution. Development 145, dev152561 (2018).

    PubMed  Google Scholar 

  96. 96.

    Kieffer, C., Ladinsky, M. S., Ninh, A., Galimidi, R. P. & Bjorkman, P. J. Longitudinal imaging of HIV-1 spread in humanized mice with parallel 3D immunofluorescence and electron tomography. eLife 6, e23282 (2017).

    PubMed  PubMed Central  Google Scholar 

  97. 97.

    Dantzer, R., O’Connor, J. C., Freund, G. G., Johnson, R. W. & Kelley, K. W. From inflammation to sickness and depression: when the immune system subjugates the brain. Nat. Rev. Neurosci. 9, 46–56 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  98. 98.

    Glaser, A. K. et al. Light-sheet microscopy for slide-free non-destructive pathology of large clinical specimens. Nat. Biomed. Eng. 1, 0084 (2017).

    PubMed  PubMed Central  Google Scholar 

  99. 99.

    Nojima, S. et al. CUBIC pathology: three-dimensional imaging for pathological diagnosis. Sci. Rep. 7, 9269 (2017).

    PubMed  PubMed Central  Google Scholar 

  100. 100.

    Royen, M. E. et al. Three-dimensional microscopic analysis of clinical prostate specimens. Histopathology 69, 985–992 (2016).

    PubMed  Google Scholar 

  101. 101.

    Huisken, J., Swoger, J., Del Bene, F., Wittbrodt, J. & Stelzer, E. H. Optical sectioning deep inside live embryos by selective plane illumination microscopy. Science 305, 1007–1009 (2004).

    CAS  PubMed  Google Scholar 

  102. 102.

    Keller, P. J., Schmidt, A. D., Wittbrodt, J. & Stelzer, E. H. K. Reconstruction of zebrafish early embryonic development by scanned light sheet microscopy. Science 322, 1065–1069 (2008).

    CAS  PubMed  Google Scholar 

  103. 103.

    Voie, A. H., Burns, D. H. & Spelman, F. A. Orthogonal-plane fluorescence optical sectioning: three-dimensional imaging of macroscopic biological specimens. J. Microsc. 170, 229–236 (1993).

    CAS  PubMed  Google Scholar 

  104. 104.

    Ryan, D. P. et al. Automatic and adaptive heterogeneous refractive index compensation for light-sheet microscopy. Nat. Commun. 8, 612 (2017).

    PubMed  PubMed Central  Google Scholar 

  105. 105.

    Tomer, R. et al. SPED light sheet microscopy: fast mapping of biological system structure and function. Cell 163, 1796–1806 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  106. 106.

    Gómez-Gaviro, M. V. et al. Optimized CUBIC protocol for 3D imaging of chicken embryos at single-cell resolution. Development 44, 2092–2097 (2017).

    Google Scholar 

  107. 107.

    Stefaniuk, M. et al. Light-sheet microscopy imaging of a whole cleared rat brain with Thy1-GFP transgene. Sci. Rep. 6, 28209 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  108. 108.

    Niedworok, C. J. et al. Charting monosynaptic connectivity maps by two-color light-sheet fluorescence microscopy. Cell Rep. 2, 1375–1386 (2012).

    CAS  PubMed  Google Scholar 

  109. 109.

    Planchon, T. A. et al. Rapid three-dimensional isotropic imaging of living cells using Bessel beam plane illumination. Nat. Methods 8, 417–423 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  110. 110.

    Chen, B. C. et al. Lattice light-sheet microscopy: imaging molecules to embryos at high spatiotemporal resolution. Science 346, 1257998 (2014). This article describes lattice light-sheet microscopy, which uses very thin laser light sheets for fluorescence generation and introduces a light-efficient concept for high-resolution imaging of a field of view of approximately 100 µm.

    PubMed  PubMed Central  Google Scholar 

  111. 111.

    Wu, Y. C. et al. Spatially isotropic four-dimensional imaging with dual-view plane illumination microscopy. Nat. Biotechnol. 31, 1032–1038 (2013). This article describes diSPIM light-sheet microscopy, which rapidly acquires two orthogonal views of a specimen with a field of view of several hundred micrometres and hence combines high imaging speeds with a high, spatially isotropic resolution of 330 nm.

    CAS  PubMed  PubMed Central  Google Scholar 

  112. 112.

    Chhetri, R. K. et al. Whole-animal functional and developmental imaging with isotropic spatial resolution. Nat. Methods 12, 1171–1178 (2015). By allowing simultaneous orthogonal four-view imaging with a field of view approaching a 1 mm, IsoView light-sheet microscopy achieves a volume throughput of more than 10 8 µm 3 per second and a high, spatially isotropic resolution of 400 nm.

    CAS  PubMed  Google Scholar 

  113. 113.

    Swoger, J., Verveer, P., Greger, K., Huisken, J. & Stelzer, E. H. Multi-view image fusion improves resolution in three-dimensional microscopy. Opt. Express 15, 8029–8042 (2007).

    PubMed  Google Scholar 

  114. 114.

    Royer, L. A. et al. Adaptive light-sheet microscopy for long-term, high-resolution imaging in living organisms. Nat. Biotechnol. 34, 1267–1278 (2016).

    CAS  PubMed  Google Scholar 

  115. 115.

    Royer, L. A., Lemon, W. C., Chhetri, R. K. & Keller, P. J. A practical guide to adaptive light-sheet microscopy. Nat. Protoc. 13, 2462–2500 (2018).

    CAS  PubMed  Google Scholar 

  116. 116.

    Silvestri, L. et al. RAPID: real-time image-based autofocus for all wide-field optical microscopy systems. Preprint at bioRxiv https://doi.org/10.1101/170555 (2017).

    Article  Google Scholar 

  117. 117.

    Hörl, D. et al. BigStitcher: reconstructing high-resolution image datasets of cleared and expanded samples. Nat. Methods 16, 870–874 (2019). This artcle describes BigStitcher, which offers highly customizable stitching of arbitrarily large image mosaics and multiview selective plane illumination microscopy data building on the BigDataViewer infrastructure in Fiji.

    PubMed  Google Scholar 

  118. 118.

    Gao, R. et al. Cortical column and whole-brain imaging with molecular contrast and nanoscale resolution. Science 363, eaau8302 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  119. 119.

    Dean, K. M., Roudot, P., Welf, E. S., Danuser, G. & Fiolka, R. Deconvolution-free subcellular imaging with axially swept light sheet microscopy. Biophys. J. 108, 2807–2815 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  120. 120.

    Pende, M. et al. High-resolution ultramicroscopy of the developing and adult nervous system in optically cleared Drosophila melanogaster. Nat. Commun. 9, 4731 (2018).

    PubMed  PubMed Central  Google Scholar 

  121. 121.

    Amat, F. et al. Efficient processing and analysis of large-scale light-sheet microscopy data. Nat. Protoc. 10, 1679–1696 (2015).

    CAS  PubMed  Google Scholar 

  122. 122.

    Pietzsch, T., Saalfeld, S., Preibisch, S. & Tomancak, P. BigDataViewer: visualization and processing for large image data sets. Nat. Methods 12, 481–483 (2015). This article describes BigDataViewer, which provides a well-engineered software framework to navigate and compute on arbitrarily large image data sets that is integrated into the popular Fiji ecosystem.

    CAS  PubMed  Google Scholar 

  123. 123.

    Schindelin, J., Rueden, C. T., Hiner, M. C. & Eliceiri, K. W. The ImageJ ecosystem: an open platform for biomedical image analysis. Mol. Reprod. Dev. 82, 518–529 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  124. 124.

    Pietzsch, T., Preibisch, S., Tomančák, P. & Saalfeld, S. ImgLib2—generic image processing in Java. Bioinformatics 28, 3009–3011 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  125. 125.

    Preibisch, S., Saalfeld, S., Schindelin, J. & Tomancak, P. Software for bead-based registration of selective plane illumination microscopy data. Nat. Methods 7, 418–419 (2010).

    CAS  PubMed  Google Scholar 

  126. 126.

    Preibisch, S. et al. Efficient Bayesian-based multiview deconvolution. Nat. Methods 11, 645–648 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  127. 127.

    Balazs, B., Deschamps, J., Albert, M., Ries, J. & Hufnagel, L. A real-time compression library for microscopy images. Preprint at bioRxiv https://doi.org/10.1101/164624 (2017).

    Article  Google Scholar 

  128. 128.

    Cheeseman, B. L., Günther, U., Susik, M., Gonciarz, K. & Sbalzarini, I. F. Forget pixels: adaptive particle representation of fluorescence microscopy images. Nat. Commun. 9, 5160 (2018).

    PubMed  PubMed Central  Google Scholar 

  129. 129.

    Schindelin, J. et al. Fiji: an open-source platform for biological-image analysis. Nat. Methods 9, 676–682 (2012).

    CAS  Google Scholar 

  130. 130.

    Tomer, R., Denes, A. S., Tessmar-Raible, K. & Arendt, D. Profiling by image registration reveals common origin of annelid mushroom bodies and vertebrate pallium. Cell 142, 800–809 (2010).

    CAS  PubMed  Google Scholar 

  131. 131.

    Heckscher, E. S. et al. Atlas-builder software and the eNeuro atlas: resources for developmental biology and neuroscience. Development 141, 2524–2532 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  132. 132.

    Ronneberger, O. et al. ViBE-Z: a framework for 3D virtual colocalization analysis in zebrafish larval brains. Nat. Methods 9, 735–742 (2012).

    CAS  PubMed  Google Scholar 

  133. 133.

    Bogovic, J. A., Hanslovsky, P., Wong, A. & Saalfeld, S. in 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI) 1123–1126 (IEEE, 2016).

  134. 134.

    Zheng, Z. et al. A complete electron microscopy volume of the brain of adult Drosophila melanogaster. Cell 174, 730–743.e22 (2017).

    Google Scholar 

  135. 135.

    Sommer, C. S., Kothe C., Hamprecht U. & Ilastik F. A. in 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro 230–233 (IEEE, 2011).

  136. 136.

    Fürth, D. et al. An interactive framework for whole-brain maps at cellular resolution. Nat. Neurosci. 21, 139–149 (2018).

    PubMed  Google Scholar 

  137. 137.

    Oh, S. W. et al. A mesoscale connectome of the mouse brain. Nature 508, 207–214 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  138. 138.

    Lein, E. S. et al. Genome-wide atlas of gene expression in the adult mouse brain. Nature 445, 168–176 (2007).

    CAS  PubMed  PubMed Central  Google Scholar 

  139. 139.

    Saalfeld, S., Cardona, A., Hartenstein, V. & Tomancak, P. CATMAID: collaborative annotation toolkit for massive amounts of image data. Bioinformatics 25, 1984–1986 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  140. 140.

    Schneider-Mizell, C. M. et al. Quantitative neuroanatomy for connectomics in Drosophila. eLife 5, e12059 (2016). This article describes the first applications of crowdsourcing of connectome tracing through the Web-based CATMAID framework.

    PubMed  PubMed Central  Google Scholar 

  141. 141.

    Amat, F. et al. Fast, accurate reconstruction of cell lineages from large-scale fluorescence microscopy data. Nat. Methods 11, 951–958 (2014).

    CAS  PubMed  Google Scholar 

  142. 142.

    Bria, A. & Iannello, G. TeraStitcher - a tool for fast automatic 3D-stitching of teravoxel-sized microscopy images. BMC Bioinforma. 13, 316 (2012).

    Google Scholar 

  143. 143.

    Wolff, C. et al. Multi-view light-sheet imaging and tracking with the MaMuT software reveals the cell lineage of a direct developing arthropod limb. eLife 7, e34410 (2018).

    PubMed  PubMed Central  Google Scholar 

  144. 144.

    Moffitt, J. R. et al. Molecular, spatial, and functional single-cell profiling of the hypothalamic preoptic region. Science 362, eaau5324 (2018).

    PubMed  PubMed Central  Google Scholar 

  145. 145.

    Bakutkin, V. V., Maksimova, I. L., Semyonova, T. N., Tuchin, V. V. & Kon, I. L. in Ophthalmic Technologies V 137–142 (SPIE, 1995).

  146. 146.

    Zimnyakov, D. A., Tuchin, V. V., Michin, A. A., Kon, I. L. & Serov, A. N. in Ophthalmic Technologies VI 233–243 (SPIE, 1996).

  147. 147.

    Tuchin, V. V. et al. in Photon Propagation in Tissues II 118–143 (SPIE, 1996).

  148. 148.

    Tuchin, V. V. et al. Light propagation in tissues with controlled optical properties. J. Biomed. Opt. 2, 401–417 (1997).

    CAS  PubMed  Google Scholar 

  149. 149.

    Bashkatov, A. N. et al. in Ophthalmic Technologies IX 311–320 (SPIE, 1999).

  150. 150.

    Tuchin, V. V. et al. Optics of living tissues with controlled scattering properties. Proc. SPIE 3863, 10–21 (1999).

    Google Scholar 

  151. 151.

    Tuchin, V. V., Xu, X. & Wang, R. K. Dynamic optical coherence tomography in studies of optical clearing, sedimentation, and aggregation of immersed blood. Appl. Opt. 41, 258–271 (2002).

    CAS  PubMed  Google Scholar 

  152. 152.

    Xu, X., Wang, R. K., Elder, J. B. & Tuchin, V. V. Effect of dextran-induced changes in refractive index and aggregation on optical properties of whole blood. Phys. Med. Biol. 48, 1205–1221 (2003).

    PubMed  Google Scholar 

  153. 153.

    Liu, H., Beauvoit, B., Kimura, M. & Chance, B. Dependence of tissue optical properties on solute-induced changes in refractive index and osmolarity. J. Biomed. Opt. 1, 200–211 (1996).

    CAS  PubMed  Google Scholar 

  154. 154.

    Vargas, O., Chan, E. K., Barton, J. K., Rylander, H. G. & Welch, A. J. Use of an agent to reduce scattering in skin. Lasers Surg. Med. 24, 133–141 (1999).

    CAS  PubMed  Google Scholar 

  155. 155.

    Vargas, G., Chan, K. F., Thomsen, S. L. & Welch, A. J. Use of osmotically active agents to alter optical properties of tissue: effects on the detected fluorescence signal measured through skin. Lasers Surg. Med. 29, 213–220 (2001).

    CAS  PubMed  Google Scholar 

  156. 156.

    Wang, R. K., Xu, X., Tuchin, V. V. & Elder, J. B. Concurrent enhancement of imaging depth and contrast for optical coherence tomography by hyperosmotic agents. JOSA B 18, 948–953 (2001).

    CAS  Google Scholar 

  157. 157.

    Xu, X. & Wang, R. K. The role of water desorption on optical clearing of biotissue: studied with near infrared reflectance spectroscopy. Med. Phys. 30, 1246–1253 (2003).

    PubMed  Google Scholar 

  158. 158.

    Jiang, J. & Wang, R. K. Comparing the synergistic effects of oleic acid and dimethyl sulfoxide as vehicles for optical clearing of skin tissue in vitro. Phys. Med. Biol. 49, 5283–5294 (2004).

    CAS  PubMed  Google Scholar 

  159. 159.

    Choi, B. et al. Determination of chemical agent optical clearing potential using in vitro human skin. Lasers Surg. Med. 36, 72–75 (2005).

    PubMed  Google Scholar 

  160. 160.

    Staudt, T., Lang, M. C., Medda, R., Engelhardt, J. & Hell, S. W. 2,2′-Thiodiethanol: a new water soluble mounting medium for high resolution optical microscopy. Microsc. Res. Tech. 70, 1–9 (2007).

    CAS  PubMed  Google Scholar 

  161. 161.

    Aoyagi, Y., Kawakami, R., Osanai, H., Hibi, T. & Nemoto, T. A rapid optical clearing protocol using 2,2′-thiodiethanol for microscopic observation of fixed mouse brain. PLOS ONE 10, e0116280 (2015).

    PubMed  PubMed Central  Google Scholar 

  162. 162.

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

    CAS  PubMed  PubMed Central  Google Scholar 

  163. 163.

    Tsai, P. S. et al. Correlations of neuronal and microvascular densities in murine cortex revealed by direct counting and colocalization of nuclei and vessels. J. Neurosci. 29, 14553–14570 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  164. 164.

    Hou, B. et al. Scalable and DiI-compatible optical clearance of the mammalian brain. Front Neuroanat. 9, 19 (2015).

    PubMed  PubMed Central  Google Scholar 

  165. 165.

    Diogo, R., Siomava, N. & Gitton, Y. Development of human limb muscles based on whole-mount immunostaining and the links between ontogeny and evolution. Development 146, dev180349 (2019).

    CAS  PubMed  Google Scholar 

  166. 166.

    LaVision BioTec. The UltraMicroscope setup. LaVision BioTec https://www.lavisionbiotec.com/products/UltraMicroscope/specification.html (2019).

  167. 167.

    Zeiss. Lightsheet Z1. Zeiss https://www.zeiss.com/microscopy/us/products/imaging-systems/lightsheet-z-1.html#downloads (2019).

  168. 168.

    Engelbrecht, C. J. & Stelzer, E. H. Resolution enhancement in a light-sheet-based microscope (SPIM). Opt. Lett. 31, 1477–1479 (2006).

    PubMed  Google Scholar 

  169. 169.

    Schwarz, M. K. et al. Fluorescent-protein stabilization and high-resolution imaging of cleared, intact mouse brains. PLOS ONE 10, e0124650 (2015).

    PubMed  PubMed Central  Google Scholar 

  170. 170.

    Jing, D. et al. Tissue clearing of both hard and soft tissue organs with the PEGASOS method. Cell Res. 28, 803–818 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  171. 171.

    Becker, K., Jährling, N., Saghafi, S., Weiler, R. & Dodt, H. U. Chemical clearing and dehydration of GFP expressing mouse brains. PLOS ONE 7, e33916 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  172. 172.

    Scott, G. D., Blum, E. D., Fryer, A. D. & Jacoby, D. B. Tissue optical clearing, three-dimensional imaging, and computer morphometry in whole mouse lungs and human airways. Am. J. Respir. Cell. Mol. Biol. 51, 43–55 (2014).

    PubMed  PubMed Central  Google Scholar 

  173. 173.

    Ertürk, A., Lafkas, D. & Chalouni, C. Imaging cleared intact biological systems at a cellular level by 3DISCO. J. Vis. Exp. https://doi.org/10.3791/5138 (2014).

  174. 174.

    Epp, J. R. et al. Optimization of CLARITY for clearing whole-brain and other intact organs. eNeuro 2, ENEURO.0022-15.2015 (2015).

    PubMed  PubMed Central  Google Scholar 

  175. 175.

    Abe, T. et al. Visualization of cell cycle in mouse embryos with Fucci2 reporter directed by Rosa26 promoter. Development 140, 237–246 (2013).

    CAS  PubMed  Google Scholar 

  176. 176.

    Breuss, M. et al. The expression of tubb2b undergoes a developmental transition in murine cortical neurons. J. Comp. Neurol. 523, 2161–2186 (2015).

    CAS  PubMed  Google Scholar 

  177. 177.

    Sekitani, T. et al. Ultraflexible organic amplifier with biocompatible gel electrodes. Nat. Commun. 7, 11425 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  178. 178.

    Mizutani, H. et al. Transparency-enhancing technology allows three-dimensional assessment of gastrointestinal mucosa: a porcine model. Pathol. Int. 68, 102–108 (2018).

    CAS  PubMed  Google Scholar 

  179. 179.

    Warner, C. A. et al. An optical clearing technique for plant tissues allowing deep imaging and compatible with fluorescence microscopy. Plant. Physiol. 166, 1684–1687 (2014).

    PubMed  PubMed Central  Google Scholar 

  180. 180.

    Hasegawa, J. et al. Three-dimensional imaging of plant organs using a simple and rapid transparency technique. Plant Cell Physiol. 57, 462–472 (2016).

    CAS  PubMed  Google Scholar 

  181. 181.

    Chen, L. et al. UbasM: an effective balanced optical clearing method for intact biomedical imaging. Sci. Rep. 7, 12218 (2017).

    PubMed  PubMed Central  Google Scholar 

  182. 182.

    Kurihara, D., Mizuta, Y., Sato, Y. & Higashiyama, T. ClearSee: a rapid optical clearing reagent for whole-plant fluorescence imaging. Development 142, 4168–4179 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  183. 183.

    Wang, Z. et al. Imaging transparent intact cardiac tissue with single-cell resolution. Biomed. Opt. Express 9, 423–436 (2018).

    PubMed  PubMed Central  Google Scholar 

  184. 184.

    Yu, T. et al. RTF: a rapid and versatile tissue optical clearing method. Sci. Rep. 8, 1964 (2018).

    PubMed  PubMed Central  Google Scholar 

  185. 185.

    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  PubMed  Google Scholar 

  186. 186.

    Lai, H. M. et al. Rationalisation and validation of an acrylamide-free procedure in three-dimensional histological imaging. PLOS ONE 11, e0158628 (2016).

    PubMed  PubMed Central  Google Scholar 

  187. 187.

    Xu, N. et al. Fast free-of-acrylamide clearing tissue (FACT)—an optimized new protocol for rapid, high-resolution imaging of three-dimensional brain tissue. Sci. Rep. 7, 9895 (2017).

    PubMed  PubMed Central  Google Scholar 

  188. 188.

    Perbellini, F. et al. Free-of-Acrylamide SDS-based tissue clearing (FASTClear) for three dimensional visualization of myocardial tissue. Sci. Rep. 7, 5188 (2017).

    PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

The authors thank E. A. Susaki for help in compiling Table 1 and Supplementary Table 1 for current tissue-clearing protocols and reagents, K. Matsumoto and Y. Shinohara for drawing the chemical structures in the supplementary information, T. Mano for contributing to the CUBIC figure, R. Cai and C. Pan for contributing to the uDISCO figure, S. R. Kumar, G. M. Coughlin, R. Challis and C. Challis for contributing to the viral-assisted spectral tracing figure and Y.-G. Park, C. H. Sohn, T. Ku, V. Lilascharoen and B. K. Lim for contributing to the SHIELD figure. The authors also gratefully acknowledge grant support from Brain/MINDS, the Basic Science and Platform Technology Program for Innovative Biological Medicine (AMED/MEXT), the Japan Society for the Promotion of Science (Grant-in-Aid for Scientific Research (S)) and the Human Frontier Science Program Research Grant Program (HFSP RGP0019/2018) (H.R.U.), the Munich Cluster for Systems Neurology (SyNergy), the Fritz Thyssen Stiftung and the Deutsche Forschungsgemeinschaft (A.E.), the David and Lucile Packard Foundation (Packard Fellowship), the McKnight Foundation, the US National Institutes of Health (NIH) (1-DP2-ES027992; U01MH117072), the NCSOFT Cultural Foundation and the Koreaan Institute for Basic Science (IBS-R026-D1) (K.C.), the NIH BRAIN Initiative, the NIH Office of the Director and the US National Science Foundation (NeuroNex) (V.G.), LABEX LIFESENSES (reference ANR-10-LABX-65) managed by the French Agence National de la Recherche within the Investissements d’Avenir programme under reference ANR-11-IDEX-0004-02 (A.C.), the European Regional Development Fund in the framework of the Czech IT4Innovations National Supercomputing Center path to exascale project, project number CZ.02.1.01/0.0/0.0/16_013/0001791, within the Czech Research, Development and Education Operational Programme (P.T.) and the Howard Hughes Medical Institute (P.J.K.).

Author information

Affiliations

Authors

Contributions

H.R.U., A.E., K.C., V.G., A.C. and P.J.K. researched data for the article. All the authors contributed to substantial discussion of its content, wrote the article and reviewed and edited the manuscript before submission.

Corresponding author

Correspondence to Hiroki R. Ueda.

Ethics declarations

Competing interests

H.R.U. is a co-inventor on a patent applications covering the CUBIC reagents (PCT/JP2014/070618 (pending), patent applicant is RIKEN, other co-inventors are E. A. Susaki and K. Tainaka; PCT/JP2017/016410 (pending), patent applicant is RIKEN, other co-inventors are K. Tainaka and T. Murakami) and a co-founder of CUBICStars Inc. A.E. is the applicant and the inventor on a patent application for technologies relating to vDISCO clearing (PCT/EP2018/063098 (pending)). K.C. is the inventor or a co-inventor on patents and patent applications for CLARITY (PCT/US2013/031066 (active), patent applicant is Stanford University, co-inventor is K. A. Deisseroth), stochastic electrotransport (PCT/US2015/024297 (active), patent applicant is MIT), SHIELD (PCT/US2016/064538 (pending), applicant is Massachusetts Institute of Technology (MIT), other co-inventors are E. Murray and J. H. Cho), SWITCH (PCT/US2016/064538 (pending), applicant is MIT, other co-inventors are E. Murray and J. H. Cho) and MAP (PCT/US2017/030285 (pending), applicant is MIT, other co-inventors are T. Ku, J. M. Swaney and J. Y. Park) and a co-founder of LifeCanvas Technologies. V.G. is a co-inventor on patent applications covering PACT and PARS (PCT/US2014/048985 (active), applicant is California Institute of Technology, other co-inventors are V. Gradinaru and B. Yang) and adeno-associated virus (US14/485,024 (active), applicant is California Institute of Technology, other co-inventors are B. E. Deverman, P. H. Patterson and V. Gradinaru) technologies. P.J.K. is an inventor or co-inventor on patents and patent applications covering multiview imaging (US14/049,470 (active), applicant is Howard Hughes Medical Institute) and adaptive light-sheet microscopy (PCT/US2017/038970 (pending), applicant is Howard Hughes Medical Institute, other co-inventors are R. K. Chhetri and L. A. Royer). P.T. and A.C. declare no competing interests.

Additional information

Peer review information

Nature Reviews Neuroscience thanks S. Gentleman and the other, anonymous, reviewer(s) 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.

Supplementary Information

Glossary

Tissue clearing

A method to make a biological specimen transparent by minimization of light scattering and light absorption by the biological specimen.

Hydrophobic tissue clearing

One of three major tissue-clearing methods; it uses hydrophobic (water-immiscible) reagents. It is also referred to as ‘solvent tissue clearing’.

Hydrophilic tissue clearing

One of three major tissue-clearing methods; it uses hydrophilic (water-miscible) reagents. It is also referred to as ‘aqueous tissue clearing’ but does not always involve the use of water.

Refractive index

(RI). The ratio of the speed of light in a vacuum to its speed in a specified medium. The RI of a vacuum is 1 by definition, whereas the RI of water is ~1.33.

Light-sheet microscopy

A technique that allows fast, high-resolution imaging of large biological specimens with low light exposure by rapidly acquiring images of thin optical sections illuminated by laser light sheets.

Passive CLARITY technique

(PACT). A technique that allows flexible hydrogel formulation and clearing without the need to use electrophoresis.

Refractive index-matching solution

A solution that is compatible with the passive CLARITY technique, perfusion-assisted agent release in situ and CLARITY. It provides high-resolution imaging at depth by further reducing light scattering in both cleared and uncleared samples.

Perfusion-assisted agent release in situ

(PARS). A method that allows whole-rodent clearing and labelling. It uses the intrinsic circulatory system (the vasculature) to deliver clearing agents and labels instead of relying on passive diffusion, which can be prohibitively slow for large organs or whole organisms.

Hydrogel-based tissue clearing

One of three major tissue-clearing methods; it crosslinks biological specimens to make a synthetic hydrogel.

sCMOS detectors

Scientific-grade CMOS-based cameras that offer a large sensor area, high pixel count, low noise, high frame rate, high dynamic range and high quantum yield, all of which are highly desirable properties for detectors used in widefield fluorescence light microscopy.

Hierarchical data format version 5

(HDF5). A hierarchical data format and versatile data model to manage and represent extremely large and complex data objects.

Compute unified device architecture

(CUDA). A parallel computing platform and programming model developed by Nvidia for general computing on its own graphics processing units.

Adaptive particle representation

A content-adaptive representation of fluorescence microscopy images that overcomes storage and processing bottlenecks in big microscopy image data.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Ueda, H.R., Ertürk, A., Chung, K. et al. Tissue clearing and its applications in neuroscience. Nat Rev Neurosci 21, 61–79 (2020). https://doi.org/10.1038/s41583-019-0250-1

Download citation

Further reading

Search

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