A platform for efficient identification of molecular phenotypes of brain-wide neural circuits

A neural circuit is a structural-functional unit of achieving particular information transmission and processing, and have various inputs, outputs and molecular phenotypes. Systematic acquisition and comparative analysis of the molecular features of neural circuits are crucial to elucidating the operating mechanisms of brain function. However, no efficient, systematic approach is available for describing the molecular phenotypes of specific neural circuits at the whole brain scale. In this study, we developed a rapid whole-brain optical tomography method and devised an efficient approach to map brain-wide structural and molecular information in the same brain: rapidly imaging and sectioning the whole brain as well as automatically collecting all slices; conveniently selecting slices of interest through quick data browsing and then performing post hoc immunostaining of selected slices. Using this platform, we mapped the brain-wide distribution of inputs to motor, sensory and visual cortices and determined their molecular phenotypes in several subcortical regions. Our platform significantly enhances the efficiency of molecular phenotyping of neural circuits and provides access to automation and industrialization of cell type analyses for specific circuits.

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

[2]  L. Looger,et al.  A Designer AAV Variant Permits Efficient Retrograde Access to Projection Neurons , 2016, Neuron.

[3]  M. Ananth,et al.  Basal Forebrain Cholinergic Circuits and Signaling in Cognition and Cognitive Decline , 2016, Neuron.

[4]  Cheuk Y. Tang,et al.  Mapping of Brain Activity by Automated Volume Analysis of Immediate Early Genes , 2016, Cell.

[5]  Sung June Kim,et al.  Selectivity of Neuromodulatory Projections from the Basal Forebrain and Locus Ceruleus to Primary Sensory Cortices , 2016, The Journal of Neuroscience.

[6]  L. Luo,et al.  Organization of the Locus Coeruleus-Norepinephrine System , 2015, Current Biology.

[7]  Charles Watson,et al.  The Somatosensory System , 2012 .

[8]  Charles Watson,et al.  The Mouse Nervous System. , 2012 .

[9]  Shaoqun Zeng,et al.  Continuously tracing brain-wide long-distance axonal projections in mice at a one-micron voxel resolution , 2013, NeuroImage.

[10]  J. Price :Allen Reference Atlas: A Digital Color Brain Atlas of the C57BL/6J Male Mouse , 2008 .

[11]  Atsushi Miyawaki,et al.  ScaleS: an optical clearing palette for biological imaging , 2015, Nature Neuroscience.

[12]  Allan R. Jones,et al.  A robust and high-throughput Cre reporting and characterization system for the whole mouse brain , 2009, Nature Neuroscience.

[13]  Shaoqun Zeng,et al.  Fast optical sectioning obtained by structured illumination microscopy using a digital mirror device , 2013, Journal of biomedical optics.

[14]  George Paxinos,et al.  The Mouse Brain in Stereotaxic Coordinates , 2001 .

[15]  G. Iannello,et al.  Confocal light sheet microscopy: micron-scale neuroanatomy of the entire mouse brain. , 2012, Optics express.

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

[17]  S. Sara,et al.  Orienting and Reorienting: The Locus Coeruleus Mediates Cognition through Arousal , 2012, Neuron.

[18]  Misha B. Ahrens,et al.  Visualizing Whole-Brain Activity and Development at the Single-Cell Level Using Light-Sheet Microscopy , 2015, Neuron.

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

[20]  Allan R. Jones,et al.  A mesoscale connectome of the mouse brain , 2014, Nature.

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

[22]  Liqun Luo,et al.  Viral-genetic tracing of the input–output organization of a central norepinephrine circuit , 2015, Nature.

[23]  Shaoqun Zeng,et al.  High-throughput dual-colour precision imaging for brain-wide connectome with cytoarchitectonic landmarks at the cellular level , 2016, Nature Communications.

[24]  Francesco Saverio Pavone,et al.  Clearing of fixed tissue: a review from a microscopist’s perspective , 2016, Journal of biomedical optics.

[25]  Hans-Ulrich Dodt,et al.  Image contrast enhancement in confocal ultramicroscopy. , 2010, Optics letters.

[26]  Saad Jbabdi,et al.  Long-range connectomics , 2013, Annals of the New York Academy of Sciences.

[27]  Kwanghun Chung,et al.  Simple, Scalable Proteomic Imaging for High-Dimensional Profiling of Intact Systems , 2015, Cell.

[28]  L. Luo Principles of Neurobiology , 2015 .

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

[30]  D. F. Russell,et al.  Embedding of neural tissue in agarose or glyoxyl agarose for vibratome sectioning. , 1993, Biotechnic & histochemistry : official publication of the Biological Stain Commission.

[31]  K. Kissa,et al.  Preferential transduction of neurons by canine adenovirus vectors and their efficient retrograde transport in vivo , 2001, FASEB journal : official publication of the Federation of American Societies for Experimental Biology.

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

[33]  N. Plesnila,et al.  Shrinkage-mediated imaging of entire organs and organisms using uDISCO , 2016, Nature Methods.

[34]  Wei-Cheng Chang,et al.  Organization of long-range inputs and outputs of frontal cortex for top-down control , 2016, Nature Neuroscience.

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

[36]  Wei-Cheng Chang,et al.  Cell type-specific long-range connections of basal forebrain circuit , 2016, eLife.

[37]  M. Alexander,et al.  Principles of Neural Science , 1981 .

[38]  Tianyi Mao,et al.  A comprehensive thalamocortical projection map at the mesoscopic level , 2014, Nature Neuroscience.

[39]  E. Callaway,et al.  Three Types of Cortical Layer 5 Neurons That Differ in Brain-wide Connectivity and Function , 2015, Neuron.

[40]  Ian R. Wickersham,et al.  Cortical representations of olfactory input by trans-synaptic tracing , 2011, Nature.

[41]  Arthur W. Toga,et al.  Neural Networks of the Mouse Neocortex , 2014, Cell.

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

[43]  Karel Svoboda,et al.  A platform for brain-wide imaging and reconstruction of individual neurons , 2016, eLife.