Cargando…

Dense neuronal reconstruction through X-ray holographic nano-tomography

Imaging neuronal networks provides a foundation for understanding the nervous system, but resolving dense nanometer-scale structures over large volumes remains challenging for light (LM) and electron microscopy (EM). Here, we show that X-ray holographic nano-tomography (XNH) can image millimeter-sca...

Descripción completa

Detalles Bibliográficos
Autores principales: 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, Allen Lee, Wei-Chung
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8354006/
https://www.ncbi.nlm.nih.gov/pubmed/32929244
http://dx.doi.org/10.1038/s41593-020-0704-9
Descripción
Sumario:Imaging neuronal networks provides a foundation for understanding the nervous system, but resolving dense nanometer-scale structures over large volumes remains challenging for light (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.