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

Author:

Ma Xin,Shedlock Cameron J.,Medina Terrymar,Ribas Roberto A.,Clarke Harrison A.,Hawkinson Tara R.,Dande Praveen K.,Wu Lei,Burke Sara N.,Merritt Matthew E.,Vander Kooi Craig W.,Gentry Matthew S.,Yadav Nirbhay N.,Chen LiORCID,Sun Ramon C.ORCID

Abstract

AbstractHigh-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 athttps://metavision3d.rc.ufl.edu/) as an interactive online database and web server to further advance brain metabolism and related research.

Publisher

Cold Spring Harbor Laboratory

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1. Stem cells, cell therapies, and bioengineering in lung biology and diseases 2023;American Journal of Physiology-Lung Cellular and Molecular Physiology;2024-09-01

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