MetaVision3D: Automated Framework for the Generation of Spatial Metabolome Atlas in 3D.


Journal

bioRxiv : the preprint server for biology
Titre abrégé: bioRxiv
Pays: United States
ID NLM: 101680187

Informations de publication

Date de publication:
28 Nov 2023
Historique:
medline: 11 12 2023
pubmed: 11 12 2023
entrez: 11 12 2023
Statut: epublish

Résumé

High-resolution spatial imaging is transforming our understanding of foundational biology. Spatial metabolomics is an emerging field that enables the dissection of the complex metabolic landscape and heterogeneity from a thin tissue section. Currently, spatial metabolism highlights the remarkable complexity in two-dimensional space and is poised to be extended into the three-dimensional world of biology. Here, we introduce MetaVision3D, a novel pipeline driven by computer vision techniques for the transformation of serial 2D MALDI mass spectrometry imaging sections into a high-resolution 3D spatial metabolome. Our framework employs advanced algorithms for image registration, normalization, and interpolation to enable the integration of serial 2D tissue sections, thereby generating a comprehensive 3D model of unique diverse metabolites across host tissues at mesoscale. As a proof of principle, MetaVision3D was utilized to generate the mouse brain 3D metabolome atlas (available at https://metavision3d.rc.ufl.edu/ ) as an interactive online database and web server to further advance brain metabolism and related research.

Identifiants

pubmed: 38077043
doi: 10.1101/2023.11.27.568931
pmc: PMC10705265
pii:
doi:

Types de publication

Preprint

Langues

eng

Auteurs

Classifications MeSH