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

Ma, X.; Shedlock, C. J.; Medina, T.; Ribas, R.; Clarke, H.; Hawkinson, T.; Dande, P.; Wu, L.; Burke, S. N.; Merritt, M.; Vander Kooi, C.; Gentry, M.; Yadav, N.; Chen, L.; Sun, R. C.

2023-11-28 neuroscience
10.1101/2023.11.27.568931 bioRxiv
Show 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.

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