Brain virtual histology with X-ray phase-contrast tomography Part II: 3D morphologies of amyloid-β plaques in Alzheimer's disease models
Matthieu ChourroutiD, Margaux Roux, Carlie Boisvert, Coralie Gislard, David LeglandiD, Ignacio Arganda‐CarrerasiD, Cécile OlivieriD, Françoise PeyriniD, Hervé BoutiniD, Nicolas RamaiD, Thierry BaroniD, David MeyronetiD, Emmanuel BruniD, Hugo RositiiD, Marlène WiartiD, Fabien ChauveauiD
Abstract
While numerous transgenic mouse strains have been produced to model the formation of amyloid-{beta} (A{beta}) plaques in the brain, efficient methods for whole-brain 3D analysis of A{beta} deposits are lacking. Moreover, standard immunohistochemistry performed on brain slices precludes any shape analysis of A{beta} plaques. The present study shows how in-line (propagation-based) X-ray phase-contrast tomography (XPCT) combined with ethanol-induced brain sample dehydration enables hippocampus-wide detection and morphometric analysis of A{beta} plaques. Performed in three distinct Alzheimer mouse strains, the proposed workflow identified differences in signal intensity and 3D shape parameters: 3xTg displayed a different type of A{beta} plaques, with a larger volume and area, greater elongation, flatness and mean breadth, and more intense average signal than J20 and APP/PS1. As a label-free non-destructive technique, XPCT can be combined with standard immunohistochemistry. XPCT virtual histology could thus become instrumental in quantifying the 3D spreading and the morphological impact of seeding when studying prion-like properties of A{beta} aggregates in animal models of Alzheimers disease. This is Part II of a series of two articles reporting the value of in-line XPCT for virtual histology of the brain; Part I shows how in-line XPCT enables 3D myelin mapping in the whole rodent brain and in human autopsy brain tissue. HighlightsO_LIX-ray phase-contrast tomography (XPCT) enables whole brain detection of A{beta} plaques C_LIO_LIMorphometric parameters of A{beta} plaques may be readily retrieved from XPCT data C_LIO_LINew shape parameters were successfully extracted from three Alzheimers disease models C_LIO_LIA Fiji-based "biologist-friendly" analysis workflow is proposed and shared C_LIO_LIXPCT is a powerful virtual histology tool that requires minimal sample preparation C_LI O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=120 SRC="FIGDIR/small/436908v2_ufig1.gif" ALT="Figure 1"> View larger version (39K): org.highwire.dtl.DTLVardef@7c3167org.highwire.dtl.DTLVardef@18f689eorg.highwire.dtl.DTLVardef@1d9c72org.highwire.dtl.DTLVardef@a027a_HPS_FORMAT_FIGEXP M_FIG Graphical abstract C_FIG
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