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

Authors :
Ma X
Shedlock CJ
Medina T
Ribas RA
Clarke HA
Hawkinson TR
Dande PK
Wu L
Burke SN
Merritt ME
Vander Kooi CW
Gentry MS
Yadav NN
Chen L
Sun RC
Source :
BioRxiv : the preprint server for biology [bioRxiv] 2023 Nov 28. Date of Electronic Publication: 2023 Nov 28.
Publication Year :
2023

Abstract

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.

Details

Language :
English
Database :
MEDLINE
Journal :
BioRxiv : the preprint server for biology
Accession number :
38077043
Full Text :
https://doi.org/10.1101/2023.11.27.568931