Nanostructure-specific X-ray tomography reveals myelin levels, integrity and axon orientations in mouse and human nervous tissue
Journal article, 2021
Myelin insulates neuronal axons and enables fast signal transmission, constituting a key component of brain development, aging and disease. Yet, myelin-specific imaging of macroscopic samples remains a challenge. Here, we exploit myelin’s nanostructural periodicity, and use small-angle X-ray scattering tensor tomography (SAXS-TT) to simultaneously quantify myelin levels, nanostructural integrity and axon orientations in nervous tissue. Proof-of-principle is demonstrated in whole mouse brain, mouse spinal cord and human white and gray matter samples. Outcomes are validated by 2D/3D histology and compared to MRI measurements sensitive to myelin and axon orientations. Specificity to nanostructure is exemplified by concomitantly imaging different myelin types with distinct periodicities. Finally, we illustrate the method’s sensitivity towards myelin-related diseases by quantifying myelin alterations in dysmyelinated mouse brain. This non-destructive, stain-free molecular imaging approach enables quantitative studies of myelination within and across samples during development, aging, disease and treatment, and is applicable to other ordered biomolecules or nanostructures.
Author
Marios Georgiadis
Swiss Federal Institute of Technology in Zürich (ETH)
New York University
Stanford University
Aileen Schroeter
Swiss Federal Institute of Technology in Zürich (ETH)
Zirui Gao
Swiss Federal Institute of Technology in Zürich (ETH)
Paul Scherrer Institut
Manuel Guizar-Sicairos
Paul Scherrer Institut
Marianne Liebi
Chalmers, Physics, Materials Physics
Christoph Leuze
Stanford University
Jennifer A. McNab
Stanford University
Aleezah Balolia
University of Colorado at Denver
Jelle Veraart
New York University
Benjamin Ades-Aron
New York University
Sunglyoung Kim
New York University
Timothy Shepherd
New York University
Choong H. Lee
New York University
Piotr Walczak
Johns Hopkins Medicine
University of Maryland
Shirish Chodankar
Brookhaven National Laboratory
Phillip DiGiacomo
Stanford University
Gergely David
University of Zürich
Mark Augath
Swiss Federal Institute of Technology in Zürich (ETH)
Valerio Zerbi
Swiss Federal Institute of Technology in Zürich (ETH)
Stefan Sommer
Swiss Federal Institute of Technology in Zürich (ETH)
Ivan Rajkovic
Stanford Synchrotron Radiation Laboratory
Thomas Weiss
Stanford Synchrotron Radiation Laboratory
Oliver Bunk
Paul Scherrer Institut
Lin Yang
Brookhaven National Laboratory
Jiangyang Zhang
New York University
Dmitry S. Novikov
New York University
Michael Zeineh
Stanford University
Els Fieremans
New York University
Markus Rudin
University of Zürich
Swiss Federal Institute of Technology in Zürich (ETH)
Nature Communications
2041-1723 (ISSN) 20411723 (eISSN)
Vol. 12 1 2941Subject Categories
Biomedical Laboratory Science/Technology
Radiology, Nuclear Medicine and Medical Imaging
Medical Image Processing
DOI
10.1038/s41467-021-22719-7
PubMed
34011929