Anna A Bakhtina, Helisa H Wippel, Juan D Chavez, James E Bruce
{"title":"Combining Quantitative Proteomics and Interactomics for a Deeper Insight into Molecular Differences between Human Cell Lines.","authors":"Anna A Bakhtina, Helisa H Wippel, Juan D Chavez, James E Bruce","doi":"10.1021/acs.jproteome.4c00503","DOIUrl":null,"url":null,"abstract":"<p><p>In modern biomedical research, cultivable cell lines are an indispensable tool, and the selection of cell lines that exhibit specific functional profiles is often critical to success. Cellular functional pathways have evolved through the selection of protein intra- and intermolecular interactions collectively referred to as the interactome. In the present work, quantitative in vivo protein cross-linking and mass spectrometry were used to probe large-scale protein interactome differences among three commonly employed human cell lines, namely, HEK293, MCF-7, and HeLa cells. These data illustrated highly reproducible quantitative interactome levels with <i>R</i><sup>2</sup> values larger than 0.8 for all biological replicates. Proteome abundance levels were also measured using data-independent acquisition quantitative proteomics methods. Combining quantitative interactome and proteome information allowed the visualization of cell type-specific interactome changes mediated by proteome level adaptations and independently regulated interactome changes to gain deeper insight into possible drivers of these changes. Among the largest detected alterations in protein interactions and conformations are changes in cytoskeletal proteins, RNA-binding proteins, chromatin remodeling complexes, mitochondrial proteins, and others. Overall, these data demonstrate the utility and reproducibility of quantitative cross-linking to study system-level interactome variations. Moreover, these results illustrate how combined quantitative interactomics and proteomics can provide unique insight into cellular functional landscapes.</p>","PeriodicalId":3,"journal":{"name":"ACS Applied Electronic Materials","volume":null,"pages":null},"PeriodicalIF":4.3000,"publicationDate":"2024-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Electronic Materials","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1021/acs.jproteome.4c00503","RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
In modern biomedical research, cultivable cell lines are an indispensable tool, and the selection of cell lines that exhibit specific functional profiles is often critical to success. Cellular functional pathways have evolved through the selection of protein intra- and intermolecular interactions collectively referred to as the interactome. In the present work, quantitative in vivo protein cross-linking and mass spectrometry were used to probe large-scale protein interactome differences among three commonly employed human cell lines, namely, HEK293, MCF-7, and HeLa cells. These data illustrated highly reproducible quantitative interactome levels with R2 values larger than 0.8 for all biological replicates. Proteome abundance levels were also measured using data-independent acquisition quantitative proteomics methods. Combining quantitative interactome and proteome information allowed the visualization of cell type-specific interactome changes mediated by proteome level adaptations and independently regulated interactome changes to gain deeper insight into possible drivers of these changes. Among the largest detected alterations in protein interactions and conformations are changes in cytoskeletal proteins, RNA-binding proteins, chromatin remodeling complexes, mitochondrial proteins, and others. Overall, these data demonstrate the utility and reproducibility of quantitative cross-linking to study system-level interactome variations. Moreover, these results illustrate how combined quantitative interactomics and proteomics can provide unique insight into cellular functional landscapes.