Automated mass spectrometry imaging of over 2000 proteins from tissue sections at 100-μm spatial resolution

Author:

Piehowski Paul D.ORCID,Zhu YingORCID,Bramer Lisa M.,Stratton Kelly G.,Zhao Rui,Orton Daniel J.ORCID,Moore Ronald J.,Yuan JiaORCID,Mitchell Hugh D.,Gao YuqianORCID,Webb-Robertson Bobbie-Jo M.,Dey Sudhansu K.ORCID,Kelly Ryan T.,Burnum-Johnson Kristin E.ORCID

Abstract

AbstractBiological tissues exhibit complex spatial heterogeneity that directs the functions of multicellular organisms. Quantifying protein expression is essential for elucidating processes within complex biological assemblies. Imaging mass spectrometry (IMS) is a powerful emerging tool for mapping the spatial distribution of metabolites and lipids across tissue surfaces, but technical challenges have limited the application of IMS to the analysis of proteomes. Methods for probing the spatial distribution of the proteome have generally relied on the use of labels and/or antibodies, which limits multiplexing and requires a priori knowledge of protein targets. Past efforts to make spatially resolved proteome measurements across tissues have had limited spatial resolution and proteome coverage and have relied on manual workflows. Here, we demonstrate an automated approach to imaging that utilizes label-free nanoproteomics to analyze tissue voxels, generating quantitative cell-type-specific images for >2000 proteins with 100-µm spatial resolution across mouse uterine tissue sections preparing for blastocyst implantation.

Funder

U.S. Department of Health & Human Services | NIH | Eunice Kennedy Shriver National Institute of Child Health and Human Development

U.S. Department of Health & Human Services | NIH | Office of Strategic Coordination

U.S. Department of Health & Human Services | NIH | National Cancer Institute

Publisher

Springer Science and Business Media LLC

Subject

General Physics and Astronomy,General Biochemistry, Genetics and Molecular Biology,General Chemistry

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