Spatial Proteomics: A New LCMS/MS Tissue Imaging Workflow Providing Protein Identities and Their Distribution in Tissue

空间蛋白质组学:一种新型LCMS/MS组织成像工作流程,可提供蛋白质鉴定及其在组织中的分布信息

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Abstract

MALDI-Imaging of proteins in tissue sections has established itself as a powerful new approach to biomarker discovery and histopathological research in recent years. However, the lack of direct identification strategies continues to be an obstacle preventing its broader use in Proteomics studies. Initial studies that utilized in situ digestion followed by MALDI-MS/MS analysis typically provided 5–50 peptide IDs of only 1–5 high abundant proteins. Here we introduce a novel proteomics technology that combines the spatial information with the routine identification of proteins from tissue sections. Highly resolved protein digests are generated by applying trypsin onto two subsequent tissue sections by supersonic nebulization. One of the sections is then analyzed by MALDI imaging mass spectrometry at up to 50 μm spatial resolution yielding a list of 200-2000 peptide signals per image. Peptides are extracted from the other sections entire surface and submitted to routine LC-MS/MS analysis, in our case using MALDI-TOF/TOF. The identified peptide list is then filtered by the peaklist from the image. All matching peaks in the image can then be assigned to a protein and the co-localization of 2 or more tryptic peptides confirm their protein association. We analyzed rat brain and testis/epididymis using the new Spatial Proteomics approach typically yielding peptide distributions at the 50-100 μm level. In brain, more than 100 peptides were identified and more than 20 proteins localized without the need for MS/MS analysis directly from the tissue. The intensity, co-localization of 2 or more peptides and the degeneracy of molecular weight of peptideto-protein mapping were used as primary validation tools beyond significant mascot scores from peptide identification. As an extension of the established top-down imaging strategy, this bottom-up Spatial Proteomics approach may facilitate the identification and simultaneous localization of a much greater number proteins than it was previously possible.

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