ScaleS: an optical clearing palette for biological imaging

Optical clearing methods facilitate deep biological imaging by mitigating light scattering in situ. Multi-scale high-resolution imaging requires preservation of tissue integrity for accurate signal reconstruction. However, existing clearing reagents contain chemical components that could compromise tissue structure, preventing reproducible anatomical and fluorescence signal stability. We developed ScaleS, a sorbitol-based optical clearing method that provides stable tissue preservation for immunochemical labeling and three-dimensional (3D) signal rendering. ScaleS permitted optical reconstructions of aged and diseased brain in Alzheimer's disease models, including mapping of 3D networks of amyloid plaques, neurons and microglia, and multi-scale tracking of single plaques by successive fluorescence and electron microscopy. Human clinical samples from Alzheimer's disease patients analyzed via reversible optical re-sectioning illuminated plaque pathogenesis in the z axis. Comparative benchmarking of contemporary clearing agents showed superior signal and structure preservation by ScaleS. These findings suggest that ScaleS is a simple and reproducible method for accurate visualization of biological tissue.

[1]  Y. Lu,et al.  Expression of Inducible Nitric Oxide Synthase after Focal Cerebral Ischemia Stimulates Neurogenesis in the Adult Rodent Dentate Gyrus , 2003, The Journal of Neuroscience.

[2]  W. Guido,et al.  ClearT: a detergent- and solvent-free clearing method for neuronal and non-neuronal tissue , 2013, Development.

[3]  Ann-Shyn Chiang,et al.  Insect NMDA receptors mediate juvenile hormone biosynthesis , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[4]  Aaron S. Andalman,et al.  Structural and molecular interrogation of intact biological systems , 2013, Nature.

[5]  Rajan P Kulkarni,et al.  Single-Cell Phenotyping within Transparent Intact Tissue through Whole-Body Clearing , 2014, Cell.

[6]  R. Mrak.  Microglia in Alzheimer Brain: A Neuropathological Perspective , 2012, International journal of Alzheimer's disease.

[7]  G. Cole,et al.  The microglial phagocytic role with specific plaque types in the Alzheimer disease brain , 2004, Neurobiology of Aging.

[8]  J. Grutzendler,et al.  Multicolor time-stamp reveals the dynamics and toxicity of amyloid deposition , 2011, Scientific reports.

[9]  Donald F. Smith,et al.  UNBIASED STEREOLOGICAL ESTIMATION OF DIFFERENT CELL TYPES IN RAT CEREBRAL CORTEX , 2011 .

[10]  K. Deisseroth,et al.  Advanced CLARITY for rapid and high-resolution imaging of intact tissues , 2014, Nature Protocols.

[11]  N. Renier,et al.  iDISCO: A Simple, Rapid Method to Immunolabel Large Tissue Samples for Volume Imaging , 2014, Cell.

[12]  D. Wahlsten,et al.  Prenatal formation of the normal mouse corpus callosum: A quantitative study with carbocyanine dyes , 1992, The Journal of comparative neurology.

[13]  John Hardy,et al.  Dense-core plaques in Tg2576 and PSAPP mouse models of Alzheimer's disease are centered on vessel walls. , 2005, The American journal of pathology.

[14]  B. Giros,et al.  Morphometric characterization of microglial phenotypes in human cerebral cortex , 2014, Journal of Neuroinflammation.

[15]  W. C. Hall,et al.  High-speed mapping of synaptic connectivity using photostimulation in Channelrhodopsin-2 transgenic mice , 2007, Proceedings of the National Academy of Sciences.

[16]  H. Braak,et al.  The Development of Amyloid β Protein Deposits in the Aged Brain , 2022 .

[17]  Hiroyuki Kimura,et al.  Push-pull benzothiazole derivatives as probes for detecting beta-amyloid plaques in Alzheimer's brains. , 2009, Bioorganic & medicinal chemistry.

[18]  Dave Morgan,et al.  Intracranially Administered Anti-Αβ Antibodies Reduce β-Amyloid Deposition by Mechanisms Both Independent of and Associated with Microglial Activation , 2003, The Journal of Neuroscience.

[19]  R. Galuske,et al.  Tracing of temporo-entorhinal connections in the human brain: cognitively impaired argyrophilic grain disease cases show dendritic alterations but no axonal disconnection of temporo-entorhinal association neurons , 2007, Acta Neuropathologica.

[20]  J. Fiala.  Mechanisms of amyloid plaque pathogenesis , 2007, Acta Neuropathologica.

[21]  E. Susaki,et al.  Whole-Brain Imaging with Single-Cell Resolution Using Chemical Cocktails and Computational Analysis , 2014, Cell.

[22]  Frank Bradke,et al.  Three-dimensional imaging of solvent-cleared organs using 3 DISCO , 2012 .

[23]  Atsushi Miyawaki,et al.  Scale: a chemical approach for fluorescence imaging and reconstruction of transparent mouse brain , 2011, Nature Neuroscience.

[24]  J. Growdon,et al.  Differential relationships of reactive astrocytes and microglia to fibrillar amyloid deposits in Alzheimer disease. , 2013, Journal of neuropathology and experimental neurology.

[25]  Frank Bradke,et al.  Three-dimensional imaging of solvent-cleared organs using 3DISCO , 2012, Nature Protocols.

[26]  Tianzi Jiang,et al.  Scalable and DiI-compatible optical clearance of the mammalian brain , 2015, Front. Neuroanat..

[27]  Jeff W. Lichtman,et al.  Clarifying Tissue Clearing , 2015, Cell.

[28]  D. Wilcock,et al.  Intracranially administered anti-Abeta antibodies reduce beta-amyloid deposition by mechanisms both independent of and associated with microglial activation. , 2003, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[29]  H. Braak,et al.  The development of amyloid beta protein deposits in the aged brain. , 2006, Science of aging knowledge environment : SAGE KE.

[30]  A. Schierloh,et al.  Ultramicroscopy: three-dimensional visualization of neuronal networks in the whole mouse brain , 2007, Nature Methods.

[31]  S. Itohara,et al.  Single APP knockin mouse models of Alzheimer’s disease , 2014 .

[32]  Dimitri Perrin,et al.  Whole-Body Imaging with Single-Cell Resolution by Tissue Decolorization , 2014, Cell.

[33]  Ville Leinonen,et al.  Immunohistochemical visualization of amyloid-beta protein precursor and amyloid-beta in extra- and intracellular compartments in the human brain. , 2010, Journal of Alzheimer's disease : JAD.

[34]  Herbert F. Jelinek,et al.  Quantitating the subtleties of microglial morphology with fractal analysis , 2013, Front. Cell. Neurosci..

[35]  N. Rothwell,et al.  The effect of intravenous interleukin-1 receptor antagonist on inflammatory mediators in cerebrospinal fluid after subarachnoid haemorrhage: a phase II randomised controlled trial , 2014, Journal of Neuroinflammation.

[36]  Takeshi Imai,et al.  SeeDB: a simple and morphology-preserving optical clearing agent for neuronal circuit reconstruction , 2013, Nature Neuroscience.

[37]  N. Otsu.  A threshold selection method from gray level histograms , 1979 .

[38]  Tomomi Nemoto,et al.  A Rapid Optical Clearing Protocol Using 2,2′-Thiodiethanol for Microscopic Observation of Fixed Mouse Brain , 2015, PloS one.

[39]  E. Mufson,et al.  Staging of Alzheimer's Pathology in Triple Transgenic Mice: A Light and Electron Microscopic Analysis , 2010, International journal of Alzheimer's disease.

[40]  S. Itohara,et al.  Single App knock-in mouse models of Alzheimer's disease , 2014, Nature Neuroscience.

[41]  B. Ghetti,et al.  The Psen1‐L166P‐knock‐in mutation leads to amyloid deposition in human wild‐type amyloid precursor protein YAC transgenic mice , 2012, FASEB journal : official publication of the Federation of American Societies for Experimental Biology.

[42]  Cleopatra Kozlowski,et al.  An Automated Method to Quantify Microglia Morphology and Application to Monitor Activation State Longitudinally In Vivo , 2012, PloS one.

[43]  Y. Shinoda,et al.  Phospholipase D Family Member 4, a Transmembrane Glycoprotein with No Phospholipase D Activity, Expression in Spleen and Early Postnatal Microglia , 2010, PloS one.

[44]  G. Feng,et al.  Imaging Neuronal Subsets in Transgenic Mice Expressing Multiple Spectral Variants of GFP , 2000, Neuron.