Whole-mouse clearing and imaging at the cellular level with vDISCO.
Journal
Nature protocols
ISSN: 1750-2799
Titre abrégé: Nat Protoc
Pays: England
ID NLM: 101284307
Informations de publication
Date de publication:
04 2023
04 2023
Historique:
received:
29
09
2021
accepted:
20
10
2022
medline:
13
4
2023
pubmed:
26
1
2023
entrez:
25
1
2023
Statut:
ppublish
Résumé
Homeostatic and pathological phenomena often affect multiple organs across the whole organism. Tissue clearing methods, together with recent advances in microscopy, have made holistic examinations of biological samples feasible. Here, we report the detailed protocol for nanobody(V
Identifiants
pubmed: 36697871
doi: 10.1038/s41596-022-00788-2
pii: 10.1038/s41596-022-00788-2
doi:
Substances chimiques
Solvents
0
Coloring Agents
0
Types de publication
Journal Article
Review
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
1197-1242Informations de copyright
© 2023. Springer Nature Limited.
Références
Pan, C. et al. Deep learning reveals cancer metastasis and therapeutic antibody targeting in the entire body. Cell 179, 1661–1676.e19 (2019).
pubmed: 31835038
pmcid: 7591821
doi: 10.1016/j.cell.2019.11.013
Ntziachristos, V. Going deeper than microscopy: the optical imaging frontier in biology. Nat. Methods 7, 603–614 (2010).
pubmed: 20676081
doi: 10.1038/nmeth.1483
James, M. L. & Gambhir, S. S. A molecular imaging primer: modalities, imaging agents, and applications. Physiol. Rev. 92, 897–965 (2012).
pubmed: 22535898
doi: 10.1152/physrev.00049.2010
Timpson, P., McGhee, E. J. & Anderson, K. I. Imaging molecular dynamics in vivo—from cell biology to animal models. J. Cell Sci. 124, 2877–2890 (2011).
pubmed: 21878495
doi: 10.1242/jcs.085191
Erturk, 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).
doi: 10.1038/nm.2600
Hama, H. et al. Scale: a chemical approach for fluorescence imaging and reconstruction of transparent mouse brain. Nat. Neurosci. 14, 1481–1488 (2011).
pubmed: 21878933
doi: 10.1038/nn.2928
Chung, K. et al. Structural and molecular interrogation of intact biological systems. Nature 497, 332–337 (2013).
pubmed: 23575631
pmcid: 4092167
doi: 10.1038/nature12107
Susaki, E. A. et al. Whole-brain imaging with single-cell resolution using chemical cocktails and computational analysis. Cell 157, 726–739 (2014).
pubmed: 24746791
doi: 10.1016/j.cell.2014.03.042
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).
pubmed: 23792946
doi: 10.1038/nn.3447
Hama, H. et al. ScaleS: an optical clearing palette for biological imaging. Nat. Neurosci. 18, 1518–1529 (2015).
pubmed: 26368944
doi: 10.1038/nn.4107
Renier, N. et al. iDISCO: a simple, rapid method to immunolabel large tissue samples for volume imaging. Cell 159, 896–910 (2014).
pubmed: 25417164
doi: 10.1016/j.cell.2014.10.010
Belle, M. et al. Tridimensional visualization and analysis of early human development. Cell 169, 161–173.e12 (2017).
pubmed: 28340341
doi: 10.1016/j.cell.2017.03.008
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).
pubmed: 25456121
doi: 10.1016/j.celrep.2014.10.037
Murray, E. et al. Simple, scalable proteomic imaging for high-dimensional profiling of intact systems. Cell 163, 1500–1514 (2015).
pubmed: 26638076
pmcid: 5275966
doi: 10.1016/j.cell.2015.11.025
Dodt, H.-U. et al. Ultramicroscopy: three-dimensional visualization of neuronal networks in the whole mouse brain. Nat. Methods 4, 331–336 (2007).
pubmed: 17384643
doi: 10.1038/nmeth1036
Pan, C. et al. Shrinkage-mediated imaging of entire organs and organisms using uDISCO. Nat. Methods 13, 859–867 (2016).
pubmed: 27548807
doi: 10.1038/nmeth.3964
Susaki, E. A. et al. Advanced CUBIC protocols for whole-brain and whole-body clearing and imaging. Nat. Protoc. 10, 1709–1727 (2015).
pubmed: 26448360
doi: 10.1038/nprot.2015.085
Tainaka, K. et al. Whole-body imaging with single-cell resolution by tissue decolorization. Cell 159, 911–924 (2014).
pubmed: 25417165
doi: 10.1016/j.cell.2014.10.034
Kubota, S. I. et al. Whole-body profiling of cancer metastasis with single-cell resolution. Cell Rep. 20, 236–250 (2017).
pubmed: 28683317
doi: 10.1016/j.celrep.2017.06.010
Yang, B. et al. Single-cell phenotyping within transparent intact tissue through whole-body clearing. Cell 158, 945–958 (2014).
pubmed: 25088144
pmcid: 4153367
doi: 10.1016/j.cell.2014.07.017
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).
pubmed: 26492141
pmcid: 4917295
doi: 10.1038/nprot.2015.122
Jing, D. et al. Tissue clearing of both hard and soft tissue organs with the PEGASOS method. Cell Res. 28, 803–818 (2018).
pubmed: 29844583
pmcid: 6082844
doi: 10.1038/s41422-018-0049-z
Cai, R. et al. Panoptic imaging of transparent mice reveals whole-body neuronal projections and skull–meninges connections. Nat. Neurosci. 22, 317–327 (2019).
pubmed: 30598527
doi: 10.1038/s41593-018-0301-3
Muyldermans, S. Single domain camel antibodies: current status. Rev. Mol. Biotechnol. 74, 277–302 (2001).
doi: 10.1016/S1389-0352(01)00021-6
Muyldermans, S. Nanobodies: natural single-domain antibodies. Annu. Rev. Biochem. 82, 775–797 (2013).
pubmed: 23495938
doi: 10.1146/annurev-biochem-063011-092449
Schumacher, D., Helma, J., Schneider, A. F. L., Leonhardt, H. & Hackenberger, C. P. R. Nanobodies: chemical functionalization strategies and intracellular applications. Angew. Chem. Int. Ed. 57, 2314–2333 (2018).
doi: 10.1002/anie.201708459
Niess, J. H. et al. CX3CR1-mediated dendritic cell access to the intestinal lumen and bacterial clearance. Science 307, 254–258 (2005).
pubmed: 15653504
doi: 10.1126/science.1102901
Gage, G. J., Kipke, D. R. & Shain, W. Whole animal perfusion fixation for rodents. J. Vis. Exp. https://doi.org/10.3791/3564 (2012).
Wang, X. et al. An ocular glymphatic clearance system removes β-amyloid from the rodent eye. Sci. Transl. Med. 12, eaaw3210 (2020).
Louveau, A. et al. Structural and functional features of central nervous system lymphatic vessels. Nature 523, 337–341 (2015).
pubmed: 26030524
pmcid: 4506234
doi: 10.1038/nature14432
Hong, G., Antaris, A. L. & Dai, H. Near-infrared fluorophores for biomedical imaging. Nat. Biomed. Eng. 1, 0010 (2017).
doi: 10.1038/s41551-016-0010
Quan, T. et al. NeuroGPS-Tree: automatic reconstruction of large-scale neuronal populations with dense neurites. Nat. Methods 13, 51–54 (2016).
pubmed: 26595210
doi: 10.1038/nmeth.3662
Li, A. et al. Micro-optical sectioning tomography to obtain a high-resolution atlas of the mouse brain. Science 330, 1404–1408 (2010).
pubmed: 21051596
doi: 10.1126/science.1191776
Qi, X. et al. Fluorescence micro-optical sectioning tomography using acousto-optical deflector-based confocal scheme. Neurophotonics 2, 041406–041406 (2015).
pubmed: 26793740
pmcid: 4717231
doi: 10.1117/1.NPh.2.4.041406
Ragan, T. et al. Serial two-photon tomography for automated ex vivo mouse brain imaging. Nat. Methods 9, 255–258 (2012).
pubmed: 22245809
pmcid: 3297424
doi: 10.1038/nmeth.1854
Feng, G. et al. Imaging neuronal subsets in transgenic mice expressing multiple spectral variants of GFP. Neuron 28, 41–51 (2000).
pubmed: 11086982
doi: 10.1016/S0896-6273(00)00084-2
Zhao, S. et al. Cellular and molecular probing of intact human organs. Cell 180, 796–812.e19 (2020).
pubmed: 32059778
pmcid: 7557154
doi: 10.1016/j.cell.2020.01.030
Richardson, D. S. et al. Tissue clearing. Nat. Rev. Methods Primer 1, 1–24 (2021).
doi: 10.1038/s43586-021-00080-9
Erturk, A. et al. Three-dimensional imaging of solvent-cleared organs using 3DISCO. Nat. Protoc. 7, 1983–1995 (2012).
pubmed: 23060243
doi: 10.1038/nprot.2012.119
Rothbauer, U. et al. Targeting and tracing antigens in live cells with fluorescent nanobodies. Nat. Methods 3, 887–889 (2006).
pubmed: 17060912
doi: 10.1038/nmeth953
Horecker, B. L. The absorption spectra of hemoglobin and its derivatives in the visible and near infra-red regions. J. Biol. Chem. 148, 173–183 (1943).
doi: 10.1016/S0021-9258(18)72329-6
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).
pubmed: 27298088
doi: 10.1146/annurev-cellbio-111315-125001
Tuchin, V. V. Tissue optics and photonics: light–tissue interaction. J. Biomed. Photonics Eng. 1, 98–134 (2015).
doi: 10.18287/JBPE-2015-1-2-98
Tainaka, K. et al. Chemical landscape for tissue clearing based on hydrophilic reagents. Cell Rep. 24, 2196–2210.e9 (2018).
pubmed: 30134179
doi: 10.1016/j.celrep.2018.07.056
Kristinsson, H. G. & Hultin, H. O. Changes in trout hemoglobin conformations and solubility after exposure to acid and alkali pH. J. Agric. Food Chem. 52, 3633–3643 (2004).
pubmed: 15161242
doi: 10.1021/jf034563g
Alnuami, A. A., Zeedi, B., Qadri, S. M. & Ashraf, S. S. Oxyradical-induced GFP damage and loss of fluorescence. Int. J. Biol. Macromol. 43, 182–186 (2008).
pubmed: 18561996
doi: 10.1016/j.ijbiomac.2008.05.002
Fagan, J. M., Sleczka, B. G. & Sohar, I. Quantitation of oxidative damage to tissue proteins. Int. J. Biochem. Cell Biol. 31, 751–757 (1999).
pubmed: 10467731
doi: 10.1016/S1357-2725(99)00034-5
Acar, M. et al. Deep imaging of bone marrow shows non-dividing stem cells are mainly perisinusoidal. Nature 526, 126–130 (2015).
pubmed: 26416744
pmcid: 4850557
doi: 10.1038/nature15250
Greenbaum, A. et al. Bone CLARITY: clearing, imaging, and computational analysis of osteoprogenitors within intact bone marrow. Sci. Transl. Med. 9, eaah6518 (2017).
pubmed: 28446689
doi: 10.1126/scitranslmed.aah6518
Gonzalez-Chavez, S. A., Pacheco-Tena, C., Macias-Vazquez, C. E. & Luevano-Flores, E. Assessment of different decalcifying protocols on osteopontin and osteocalcin immunostaining in whole bone specimens of arthritis rat model by confocal immunofluorescence. Int. J. Clin. Exp. Pathol. 6, 1972–1983 (2013).
pubmed: 24133575
pmcid: 3796219
Xiao, X. et al. Antibody incubation at 37°C improves fluorescent immunolabeling in free-floating thick tissue sections. Biotechniques 62, 115–122 (2017).
pubmed: 28298178
doi: 10.2144/000114524
Weiss, K. R., Voigt, F. F., Shepherd, D. P. & Huisken, J. Tutorial: practical considerations for tissue clearing and imaging. Nat. Protoc. 16, 2732–2748 (2021).
pubmed: 34021294
doi: 10.1038/s41596-021-00502-8
Renier, N. et al. Mapping of brain activity by automated volume analysis of immediate early genes. Cell 165, 1789–1802 (2016).
pubmed: 27238021
pmcid: 4912438
doi: 10.1016/j.cell.2016.05.007
Voigt, F. F. et al. The mesoSPIM initiative: open-source light-sheet microscopes for imaging cleared tissue. Nat. Methods 16, 1105–1108 (2019).
pubmed: 31527839
pmcid: 6824906
doi: 10.1038/s41592-019-0554-0
Welch, A. Technique for high-performance data compression. Computer 17, 8–19 (1984).
doi: 10.1109/MC.1984.1659158
Ma, B. et al. A fast algorithm for material image sequential stitching. Comput. Mater. Sci. 158, 1–13 (2019).
doi: 10.1016/j.commatsci.2018.10.044
Dellatorre, G. & Gadens, G. A. Wide area digital dermoscopy applied to basal cell carcinoma. An. Bras. Dermatol. 95, 379–382 (2020).
pubmed: 32276794
pmcid: 7253909
doi: 10.1016/j.abd.2019.08.030
Boatright, J. H. et al. Methodologies for analysis of patterning in the mouse RPE sheet. Mol. Vis. 21, 40–60 (2015).
pubmed: 25593512
pmcid: 4301600
Hörl, D. et al. BigStitcher: reconstructing high-resolution image datasets of cleared and expanded samples. Nat. Methods 16, 870–874 (2019).
pubmed: 31384047
doi: 10.1038/s41592-019-0501-0
Schindelin, J. et al. Fiji: an open-source platform for biological-image analysis. Nat. Methods 9, 676–682 (2012).
pubmed: 22743772
doi: 10.1038/nmeth.2019
Pietzsch, T., Preibisch, S., Tomancak, P. & Saalfeld, S. ImgLib2-generic image processing in Java. Bioinformatics 28, 3009–3011 (2012).
pubmed: 22962343
pmcid: 3496339
doi: 10.1093/bioinformatics/bts543
Bria, A. & Iannello, G. TeraStitcher—a tool for fast automatic 3D-stitching of teravoxel-sized microscopy images. BMC Bioinformatics 13, 316 (2012).
pubmed: 23181553
pmcid: 3582611
doi: 10.1186/1471-2105-13-316
Glaser, J. R. & Glaser, E. M. Neuron imaging with neurolucida—a PC-based system for image combining microscopy. Comput. Med. Imaging Graph. 14, 307–317 (1990).
pubmed: 2224829
doi: 10.1016/0895-6111(90)90105-K
Belthangady, C. & Royer, L. A. Applications, promises, and pitfalls of deep learning for fluorescence image reconstruction. Nat. Methods https://doi.org/10.1038/s41592-019-0458-z (2019).
Moen, E. et al. Deep learning for cellular image analysis. Nat. Methods https://doi.org/10.1038/s41592-019-0403-1 (2019).
Zhou, H. et al. 3D high resolution generative deep-learning network for fluorescence microscopy imaging. Opt. Lett. 45, 1695–1698 (2020).
pubmed: 32235976
doi: 10.1364/OL.387486
Mano, T. et al. CUBIC-Cloud provides an integrative computational framework toward community-driven whole-mouse-brain mapping. Cell Rep. Methods 1, 100038 (2021).
pubmed: 35475238
pmcid: 9017177
doi: 10.1016/j.crmeth.2021.100038
Iwasato, T. et al. Cortex-restricted disruption of NMDAR1 impairs neuronal patterns in the barrel cortex. Nature 406, 726–731 (2000).
pubmed: 10963597
pmcid: 3558691
doi: 10.1038/35021059
Takatoh, J. et al. New modules are added to vibrissal premotor circuitry with the emergence of exploratory whisking. Neuron 77, 346–360 (2013).
pubmed: 23352170
pmcid: 3559006
doi: 10.1016/j.neuron.2012.11.010
Wickersham, I. R. et al. Monosynaptic restriction of transsynaptic tracing from single, genetically targeted neurons. Neuron 53, 639–647 (2007).
pubmed: 17329205
pmcid: 2629495
doi: 10.1016/j.neuron.2007.01.033
Reed, H. O. et al. Lymphatic impairment leads to pulmonary tertiary lymphoid organ formation and alveolar damage. J. Clin. Invest. 129, 2514–2526 (2019).
pubmed: 30946031
pmcid: 6546450
doi: 10.1172/JCI125044
Wigle, J. T. et al. An essential role for Prox1 in the induction of the lymphatic endothelial cell phenotype. EMBO J. 21, 1505–1513 (2002).
pubmed: 11927535
pmcid: 125938
doi: 10.1093/emboj/21.7.1505
Kivelä, R. et al. The transcription factor Prox1 is essential for satellite cell differentiation and muscle fibre-type regulation. Nat. Commun. 7, 13124 (2016).
pubmed: 27731315
pmcid: 5064023
doi: 10.1038/ncomms13124
Iwano, T., Masuda, A., Kiyonari, H., Enomoto, H. & Matsuzaki, F. Prox1 postmitotically defines dentate gyrus cells by specifying granule cell identity over CA3 pyramidal cell fate in the hippocampus. Dev. Camb. Engl. 139, 3051–3062 (2012).