Dense neuronal reconstruction through X-ray holographic nano-tomography.
Aaron T KuanJasper S PhelpsLogan A ThomasTri M NguyenJulie HanChiao-Lin ChenAnthony W AzevedoJohn C TuthillJan FunkePeter CloetensAlexandra PacureanuWei-Chung Allen LeePublished in: Nature neuroscience (2020)
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.
Keyphrases
- electron microscopy
- high resolution
- induced apoptosis
- convolutional neural network
- drosophila melanogaster
- single molecule
- deep learning
- cell cycle arrest
- spinal cord
- small molecule
- computed tomography
- dual energy
- cerebral ischemia
- magnetic resonance imaging
- cell death
- oxidative stress
- risk assessment
- mass spectrometry
- signaling pathway
- heavy metals
- endoplasmic reticulum stress
- single cell
- optical coherence tomography
- cerebrospinal fluid
- contrast enhanced
- blood brain barrier