 |
HAL-CNRSCNRS scientific publications |
 |
Journal articles
Nano-imaging trace elements at organelle levels in substantia nigra overexpressing α-synuclein to model Parkinson’s disease.
Abstract : Sub-cellular trace element quantifications of nano-heterogeneities in brain tissues offer unprecedented ways to explore at elemental level the interplay between cellular compartments in neurodegenerative pathologies. We designed a quasi-correlative method for analytical nanoimaging of the substantia nigra, based on transmission electron microscopy and synchrotron X-ray fluorescence. It combines ultrastructural identifications of cellular compartments and trace element nanoimaging near detection limits, for increased signal-to-noise ratios. Elemental composition of different organelles is compared to cytoplasmic and nuclear compartments in dopaminergic neurons of rat substantia nigra. They exhibit 150-460 ppm of Fe, with P/Zn/Fe-rich nucleoli in a P/S-depleted nuclear matrix and Ca-rich rough endo-plasmic reticula. Cytoplasm analysis displays sub-micron Fe/S-rich granules, including lipo-fuscin. Following AAV-mediated overexpression of α-synuclein protein associated with Parkinson's disease, these granules shift towards higher Fe concentrations. This effect advocates for metal (Fe) dyshomeostasis in discrete cytoplasmic regions, illustrating the use of this method to explore neuronal dysfunction in brain diseases.
Cited literature [65 references]
https://hal-cnrs.archives-ouvertes.fr/hal-02879375
Contributor : Laurence Lemelle <>
Submitted on : Friday, September 25, 2020 - 3:55:47 PM
Last modification on : Friday, June 25, 2021 - 2:42:02 PM
Long-term archiving on: : Thursday, December 3, 2020 - 6:07:01 PM
Contributor : Laurence Lemelle <>
Submitted on : Friday, September 25, 2020 - 3:55:47 PM
Last modification on : Friday, June 25, 2021 - 2:42:02 PM
Long-term archiving on: : Thursday, December 3, 2020 - 6:07:01 PM
File
s42003-020-1084-0.pdf
Publisher files allowed on an open archive
Licence
Distributed under a Creative Commons Attribution - NoDerivatives 4.0 International License