Publications
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 |
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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 |