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Dense neuronal reconstruction through X-ray holographic nano-tomography.
Kuan, Aaron T; Phelps, Jasper S; Thomas, Logan A; Nguyen, Tri M; Han, Julie; Chen, Chiao-Lin; Azevedo, Anthony W; Tuthill, John C; Funke, Jan; Cloetens, Peter; Pacureanu, Alexandra; Lee, Wei-Chung Allen.
Afiliação
  • Kuan AT; Department of Neurobiology, Harvard Medical School, Boston, MA, USA.
  • Phelps JS; Department of Neurobiology, Harvard Medical School, Boston, MA, USA.
  • Thomas LA; Program in Neuroscience, Harvard University, Boston, MA, USA.
  • Nguyen TM; Department of Neurobiology, Harvard Medical School, Boston, MA, USA.
  • Han J; Department of Neurobiology, Harvard Medical School, Boston, MA, USA.
  • Chen CL; Department of Neurobiology, Harvard Medical School, Boston, MA, USA.
  • Azevedo AW; Department of Genetics, Harvard Medical School, Boston, MA, USA.
  • Tuthill JC; Department of Physiology and Biophysics, University of Washington, Seattle, WA, USA.
  • Funke J; Department of Physiology and Biophysics, University of Washington, Seattle, WA, USA.
  • Cloetens P; HHMI Janelia Research Campus, Ashburn, VA, USA.
  • Pacureanu A; ESRF, The European Synchrotron, Grenoble, France.
  • Lee WA; Department of Neurobiology, Harvard Medical School, Boston, MA, USA. joitapac@esrf.eu.
Nat Neurosci ; 23(12): 1637-1643, 2020 12.
Article em En | MEDLINE | ID: mdl-32929244
ABSTRACT
Imaging neuronal networks provides a foundation for understanding the nervous system, but resolving dense nanometer-scale structures over large volumes remains challenging for light microscopy (LM) and electron microscopy (EM). Here we show that X-ray holographic nano-tomography (XNH) can image millimeter-scale volumes with sub-100-nm resolution, enabling reconstruction of dense wiring in Drosophila melanogaster and mouse nervous tissue. We performed correlative XNH and EM to reconstruct hundreds of cortical pyramidal cells and show that more superficial cells receive stronger synaptic inhibition on their apical dendrites. By combining multiple XNH scans, we imaged an adult Drosophila leg with sufficient resolution to comprehensively catalog mechanosensory neurons and trace individual motor axons from muscles to the central nervous system. To accelerate neuronal reconstructions, we trained a convolutional neural network to automatically segment neurons from XNH volumes. Thus, XNH bridges a key gap between LM and EM, providing a new avenue for neural circuit discovery.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Processamento de Imagem Assistida por Computador / Neurônios Limite: Animals Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Processamento de Imagem Assistida por Computador / Neurônios Limite: Animals Idioma: En Ano de publicação: 2020 Tipo de documento: Article