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Automated annotation and visualisation of high-resolution spatial proteomic mass spectrometry imaging data using HIT-MAP

Abstract

Spatial proteomics has the potential to significantly advance our understanding of biology, physiology and medicine. Matrix-assisted laser desorption/ionisation mass spectrometry imaging (MALDI-MSI) is a powerful tool in the spatial proteomics field, enabling direct detection and registration of protein abundance and distribution across tissues. MALDI-MSI preserves spatial distribution and histology allowing unbiased analysis of complex, heterogeneous tissues. However, MALDI-MSI faces the challenge of simultaneous peptide quantification and identification. To overcome this, we develop and validate HIT-MAP (High-resolution Informatics Toolbox in MALDI-MSI Proteomics), an open-source bioinformatics workflow using peptide mass fingerprint analysis and a dual scoring system to computationally assign peptide and protein annotations to high mass resolution MSI datasets and generate customisable spatial distribution maps. HIT-MAP will be a valuable resource for the spatial proteomics community for analysing newly generated and retrospective datasets, enabling robust peptide and protein annotation and visualisation in a wide array of normal and disease contexts.

Type Journal
ISBN 2041-1723 (Electronic) 2041-1723 (Linking)
Authors Guo, G.; Papanicolaou, M.; Demarais, N. J.; Wang, Z.; Schey, K. L.; Timpson, P.; Cox, T. R.; Grey, A. C.
Publisher Name Nature Communications
Published Date 2021-05-31
Published Volume 12
Published Issue 1
Published Pages 3241
Status Published in-print
DOI 10.1038/s41467-021-23461-w
URL link to publisher's version https://www.ncbi.nlm.nih.gov/pubmed/34050164