Print Email Facebook Twitter Rapid Multivariate Analysis Approach to Explore Differential Spatial Protein Profiles in Tissue Title Rapid Multivariate Analysis Approach to Explore Differential Spatial Protein Profiles in Tissue Author Sharman, Kavya (VanderBilt University; Vanderbilt University Medical Center) Patterson, Nathan Heath (VanderBilt University) Weiss, Andy (Vanderbilt University Medical Center) Neumann, Elizabeth K. (VanderBilt University) Guiberson, Emma R. (VanderBilt University) Ryan, Daniel J. (Pfizer Inc.) Gutierrez, Danielle B. (VanderBilt University) Spraggins, Jeffrey M. (VanderBilt University) Van de Plas, Raf (TU Delft Team Raf Van de Plas; VanderBilt University) Skaar, Eric P. (Vanderbilt University Medical Center) Caprioli, Richard M. (VanderBilt University) Date 2023 Abstract Spatially targeted proteomics analyzes the proteome of specific cell types and functional regions within tissue. While spatial context is often essential to understanding biological processes, interpreting sub-region-specific protein profiles can pose a challenge due to the high-dimensional nature of the data. Here, we develop a multivariate approach for rapid exploration of differential protein profiles acquired from distinct tissue regions and apply it to analyze a published spatially targeted proteomics data set collected from Staphylococcus aureus-infected murine kidney, 4 and 10 days postinfection. The data analysis process rapidly filters high-dimensional proteomic data to reveal relevant differentiating species among hundreds to thousands of measured molecules. We employ principal component analysis (PCA) for dimensionality reduction of protein profiles measured by microliquid extraction surface analysis mass spectrometry. Subsequently, k-means clustering of the PCA-processed data groups samples by chemical similarity. Cluster center interpretation revealed a subset of proteins that differentiate between spatial regions of infection over two time points. These proteins appear involved in tricarboxylic acid metabolomic pathways, calcium-dependent processes, and cytoskeletal organization. Gene ontology analysis further uncovered relationships to tissue damage/repair and calcium-related defense mechanisms. Applying our analysis in infectious disease highlighted differential proteomic changes across abscess regions over time, reflecting the dynamic nature of host-pathogen interactions. Subject abscess formationbioinformaticscomputational proteomicshost-pathogen interfacemachine learningmass spectrometrymicroLESAproteomicsspatially targeted proteomicsStaphylococcus aureus To reference this document use: http://resolver.tudelft.nl/uuid:4a3dfc36-ace3-475b-b01d-56f8b2114d48 DOI https://doi.org/10.1021/acs.jproteome.2c00206 Embargo date 2023-01-18 ISSN 1535-3893 Source Journal of Proteome Research, 22 (5), 1394-1405 Bibliographical note Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public. Part of collection Institutional Repository Document type journal article Rights © 2023 Kavya Sharman, Nathan Heath Patterson, Andy Weiss, Elizabeth K. Neumann, Emma R. Guiberson, Daniel J. Ryan, Danielle B. Gutierrez, Jeffrey M. Spraggins, Raf Van de Plas, Eric P. Skaar, Richard M. Caprioli Files PDF acs.jproteome.2c00206.pdf 3.31 MB Close viewer /islandora/object/uuid:4a3dfc36-ace3-475b-b01d-56f8b2114d48/datastream/OBJ/view