Automated mass spectrometry imaging of over 2000 proteins from tissue sections at 100-μm spatial resolution.
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IF: 17.694
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Cited by: 129
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Abstract

Biological 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.

Keywords

Omics
LCM-seq
Gene Expression

MeSH terms

Animals
Automation
Female
Laser Capture Microdissection
Mass Spectrometry
Mice
Mice, Inbred C57BL
Microtomy
Proteins
Proteome
Proteomics
Uterus

Authors

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

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