Stuart, T. & Satija, R. Integrative single-cell analysis. Nat. Rev. Genet. 20, 257–272 (2019).
McKinnon, K. M. Flow cytometry: an overview. Curr. Protoc. Immunol. 120, 5.1.1–5.1.11 (2018).
Longo, S. K., Guo, M. G., Ji, A. L. & Khavari, P. A. Integrating single-cell and spatial transcriptomics to elucidate intercellular tissue dynamics. Nat. Rev. Genet. 22, 627–644 (2021).
McGinnis, L. M., Ibarra-Lopez, V., Rost, S. & Ziai, J. Clinical and research applications of multiplexed immunohistochemistry and in situ hybridization. J. Pathol. 254, 405–417 (2021).
Byron, S. A., Van Keuren-Jensen, K. R., Engelthaler, D. M., Carpten, J. D. & Craig, D. W. Translating RNA sequencing into clinical diagnostics: opportunities and challenges. Nat. Rev. Genet. 17, 257–271 (2016).
Liu, H. et al. DNA methylation atlas of the mouse brain at single-cell resolution. Nature 598, 120–128 (2021).
Yao, Z. et al. A transcriptomic and epigenomic cell atlas of the mouse primary motor cortex. Nature 598, 103–110 (2021).
Schwanhüusser, B. et al. Global quantification of mammalian gene expression control. Nature 473, 337–342 (2011).
Prabakaran, S., Lippens, G., Steen, H. & Gunawardena, J. Post-translational modification: nature’s escape from genetic imprisonment and the basis for dynamic information encoding. Wiley Interdiscip. Rev. Syst. Biol. Med. 4, 565–583 (2012).
Moffitt, J. R., Lundberg, E. & Heyn, H. The emerging landscape of spatial profiling technologies. Nat. Rev. Genet. 23, 741–759 (2022).
Chung, K. et al. Structural and molecular interrogation of intact biological systems. Nature 497, 332–337 (2013).
Park, Y.-G. G. et al. Protection of tissue physicochemical properties using polyfunctional crosslinkers. Nat. Biotechnol. https://doi.org/10.1038/nbt.42813 (2018).
Susaki, E. A. et al. Whole-brain imaging with single-cell resolution using chemical cocktails and computational analysis. Cell 157, 726–739 (2014).
Renier, N. et al. IDISCO: a simple, rapid method to immunolabel large tissue samples for volume imaging. Cell 159, 896–910 (2014).
Arias, A., Manubens-Gil, L. & Dierssen, M. Fluorescent transgenic mouse models for whole-brain imaging in health and disease. Front. Mol. Neurosci. 15, 958222 (2022).
Renier, N. et al. Mapping of brain activity by automated volume analysis of immediate early genes. Cell 165, 1789–1802 (2016).
Susaki, E. A. et al. Versatile whole-organ/body staining and imaging based on electrolyte-gel properties of biological tissues. Nat. Commun. 11, 1982 (2020).
Zhao, S. et al. Cellular and molecular probing of intact human organs. Cell 180, 796–812 (2020).
Murray, E. et al. Simple, scalable proteomic imaging for high-dimensional profiling of intact systems. Cell 163, 1500–1514 (2015).
Cai, R. et al. Panoptic imaging of transparent mice reveals whole-body neuronal projections and skull–meninges connections. Nat. Neurosci. 22, 317–327 (2018).
Lai, H. M. et al. Antibody stabilization for thermally accelerated deep immunostaining. Nat. Methods 19, 1137–1146 (2022).
Ku, T. et al. Elasticizing tissues for reversible shape transformation and accelerated molecular labeling. Nat. Methods 17, 609–613 (2020).
Tainaka, K. et al. Whole-body imaging with single-cell resolution by tissue decolorization. Cell 159, 911–924 (2014).
Belle, M. et al. Tridimensional visualization and analysis of early human development. Cell 169, 161–173 (2017).
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).
Hama, H. et al. ScaleS: an optical clearing palette for biological imaging. Nat. Neurosci. 18, 1518–1529 (2015).
Gleave, J. A., Lerch, J. P., Henkelman, R. M. & Nieman, B. J. A method for 3D immunostaining and optical imaging of the mouse brain demonstrated in neural progenitor cells. PLoS ONE 8, e72039 (2013).
Sillitoe, R. V. & Hawkes, R. Whole-mount immunohistochemistry: a high-throughput screen for patterning defects in the mouse cerebellum. J. Histochem. Cytochem. 50, 235–244 (2002).
Dent, J. A., Polson, A. G. & Klymkowsky, M. W. A whole-mount immunocytochemical analysis of the expression of the intermediate filament protein vimentin in Xenopus. Development 105, 61–74 (1989).
Mai, H. et al. Whole-body cellular mapping in mouse using standard IgG antibodies. Nat. Biotechnol. 42, 617–627 (2023).
Kubota, S. I. et al. Whole-body profiling of cancer metastasis with single-cell resolution. Cell Rep. 20, 236–250 (2017).
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).
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).
Shi, L. et al. Highly-multiplexed volumetric mapping with Raman dye imaging and tissue clearing. Nat. Biotechnol. 40, 364–373 (2021).
Kim, S.-Y. et al. Stochastic electrotransport selectively enhances the transport of highly electromobile molecules. Proc. Natl Acad. Sci. USA 112, E6274–E6283 (2015).
Pavlova, I. P., Shipley, S. C., Lanio, M., Hen, R. & Denny, C. A. Optimization of immunolabeling and clearing techniques for indelibly-labeled memory traces. Hippocampus 28, 523–535 (2018).
Yau, C. N. et al. Principles of deep immunohistochemistry for 3D histology. Cell Rep. Methods 3, 100458 (2023).
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).
Roberts, D. et al. Specific ion and buffer effects on protein–protein interactions of a monoclonal antibody. Mol. Pharm. 12, 179–193 (2015).
Qualtiere, L. F., Anderson, A. G. & Meyers, P. Effects of ionic and nonionic detergents on antigen-antibody reactions. J. Immunol. 119, 1645–1651 (1977).
Cabral, D. J., Hamilton, J. A. & Small, D. M. The ionization behavior of bile acids in different aqueous environments. J. Lipid Res. 27, 334–343 (1987).
Esposito, G., Giglio, E., Pavel, N. V. & Zanobi, A. Size and shape of sodium deoxycholate micellar aggregates. J. Phys. Chem. 91, 356–362 (1987).
Makino, S., Reynolds, J. A. & Tanford, C. The binding of deoxycholate and Triton X 100 to proteins. J. Biol. Chem. 248, 4926–4932 (1973).
Proença, L. et al. Electrocatalytic oxidation of d-sorbitol on platinum in acid medium: analysis of the reaction products. J. Electroanal. Chem. 432, 237–242 (1997).
Albanese, A. et al. Multiscale 3D phenotyping of human cerebral organoids. Sci. Rep. 10, 21487 (2020).
Roy, D. S. et al. Brain-wide mapping reveals that engrams for a single memory are distributed across multiple brain regions. Nat. Commun. 13, 1799 (2022).
Muzumdar, M. D., Tasic, B., Miyamichi, K., Li, L. & Luo, L. A global double-fluorescent Cre reporter mouse. Genesis 45, 593–605 (2007).
Livet, J. et al. Transgenic strategies for combinatorial expression of fluorescent proteins in the nervous system. Nature 450, 56–62 (2007).
Gong, S. et al. A gene expression atlas of the central nervous system based on bacterial artificial chromosomes. Nature 425, 917–925 (2003).
Valjent, E., Bertran-Gonzalez, J., Hervé, D., Fisone, G. & Girault, J.-A. Looking BAC at striatal signaling: cell-specific analysis in new transgenic mice. Trends Neurosci. 32, 538–547 (2009).
Kim, Y. et al. Brain-wide maps reveal stereotyped cell-type-based cortical architecture and subcortical sexual dimorphism. Cell 171, 456–469 (2017).
Zhang, C. et al. A platform for stereological quantitative analysis of the brain-wide distribution of type-specific neurons. Sci. Rep. 7, 14334 (2017).
Tanahira, C. et al. Parvalbumin neurons in the forebrain as revealed by parvalbumin-Cre transgenic mice. Neurosci. Res. 63, 213–223 (2009).
Nigro, M. J., Kirikae, H., Kjelsberg, K., Nair, R. R. & Witter, M. P. Not all that is gold glitters: PV-IRES-Cre mouse line shows low efficiency of labeling of parvalbumin interneurons in the perirhinal cortex. Front. Neural Circuits 15, 781928 (2021).
Li, X. et al. Generation of a whole-brain atlas for the cholinergic system and mesoscopic projectome analysis of basal forebrain cholinergic neurons. Proc. Natl Acad. Sci. USA 115, 415–420 (2018).
Heffner, C. S. et al. Supporting conditional mouse mutagenesis with a comprehensive cre characterization resource. Nat. Commun. 3, 1218 (2012).
von Engelhardt, J., Eliava, M., Meyer, A. H., Rozov, A. & Monyer, H. Functional characterization of intrinsic cholinergic interneurons in the cortex. J. Neurosci. 27, 5633–5642 (2007).
Vogel, C. & Marcotte, E. M. Insights into the regulation of protein abundance from proteomic and transcriptomic analyses. Nat. Rev. Genet. 13, 227–232 (2012).
Madisen, L. et al. A robust and high-throughput Cre reporting and characterization system for the whole mouse brain. Nat. Neurosci. 13, 133–140 (2009).
Luo, L. et al. Optimizing nervous system-specific gene targeting with Cre driver lines: prevalenceof germline recombination and influencing factors. Neuron 106, 37–65 (2020).
Swaney, J. et al. Scalable image processing techniques for quantitative analysis of volumetric biological images from light-sheet microscopy. Preprint at bioRxiv https://doi.org/10.1101/576595 (2019).
Tallini, Y. N. et al. BAC transgenic mice express enhanced green fluorescent protein in central and peripheral cholinergic neurons. Physiol. Genomics 27, 391–397 (2006).
Schmidt-Supprian, M. & Rajewsky, K. Vagaries of conditional gene targeting. Nat. Immunol. 8, 665–668 (2007).
Matthaei, K. I. & Matthaei, K. I. Genetically manipulated mice: a powerful tool with unsuspected caveats. J. Physiol. 582, 481–488 (2007).
Huang, Z. J., Taniguchi, H., He, M. & Kuhlman, S. Genetic labeling of neurons in mouse brain. Cold Spring Harb. Protoc. 2014, 150–160 (2014).
Marín, O. Interneuron dysfunction in psychiatric disorders. Nat. Rev. Neurosci. 13, 107–120 (2012).
Zikopoulos, B. & Barbas, H. Altered neural connectivity in excitatory and inhibitory cortical circuits in autism. Front. Hum. Neurosci. 7, 609 (2013).
Niwa, M. et al. Knockdown of DISC1 by in utero gene transfer disturbs postnatal dopaminergic maturation in the frontal cortex and leads to adult behavioral deficits. Neuron 65, 480–489 (2010).
Canty, A. J. et al. Regionalized loss of parvalbumin interneurons in the cerebral cortex of mice with deficits in GFRα1 signaling. J. Neurosci. 29, 10695–10705 (2009).
Park, J. et al. Integrated platform for multiscale molecular imaging and phenotyping of the human brain. Science 384, eadh9979 (2024).
Caballero, A., Flores-Barrera, E., Cass, D. K. & Tseng, K. Y. Differential regulation of parvalbumin and calretinin interneurons in the prefrontal cortex during adolescence. Brain Struct. Funct. 219, 395–406 (2014).
Caballero, A., Flores-Barrera, E., Thomases, D. R. & Tseng, K. Y. Downregulation of parvalbumin expression in the prefrontal cortex during adolescence causes enduring prefrontal disinhibition in adulthood. Neuropsychopharmacology 45, 1527–1535 (2020).
Black, S. et al. CODEX multiplexed tissue imaging with DNA-conjugated antibodies. Nat. Protoc. 16, 3802–3835 (2021).
Hong, F. et al. Thermal-plex: fluidic-free, rapid sequential multiplexed imaging with DNA-encoded thermal channels. Nat. Methods 21, 331–341 (2023).
Lancaster, M. A. & Knoblich, J. A. Generation of cerebral organoids from human pluripotent stem cells. Nat. Protoc. 9, 2329–2340 (2014).
Mellios, N. et al. MeCP2-regulated miRNAs control early human neurogenesis through differential effects on ERK and AKT signaling. Mol. Psychiatry 23, 1051–1065 (2017).
Tehrani-Bagha, A. R. & Holmberg, K. Solubilization of hydrophobic dyes in surfactant solutions. Materials 6, 580–608 (2013).
Podgorski, K., Terpetschnig, E., Klochko, O. P., Obukhova, O. M. & Haas, K. Ultra-bright and -stable red and near-infrared squaraine fluorophores for in vivo two-photon imaging. PLoS ONE 7, e51980 (2012).
Dong, H. W. Allen Reference Atlas: A Digital Color Brain Atlas of the C57Bl/6J Male Mouse (Wiley, 2008).
Klein, S., Staring, M., Murphy, K., Viergever, M. A. & Pluim, J. elastix: a toolbox for intensity-based medical image registration. IEEE Trans. Med. Imaging 29, 196–205 (2010).
Yun, D. H. et al. Uniform volumetric single-cell processing for organ-scale molecular phenotyping. GitHub https://github.com/chunglabmit/eflash (2024).
