Milan Avila Clasen, Max Ruwolt, Cong Wang, Julia Ruta, Boris Bogdanow, Louise U. Kurt, Zehong Zhang, Shuai Wang, Fabio C. Gozzo, Tao Chen, Paulo C. Carvalho, Diogo Borges Lima, Fan Liu
{"title":"蛋白质组规模的重组标准和强大的高速搜索引擎,推进基于交联质谱的相互作用组学。","authors":"Milan Avila Clasen, Max Ruwolt, Cong Wang, Julia Ruta, Boris Bogdanow, Louise U. Kurt, Zehong Zhang, Shuai Wang, Fabio C. Gozzo, Tao Chen, Paulo C. Carvalho, Diogo Borges Lima, Fan Liu","doi":"10.1038/s41592-024-02478-1","DOIUrl":null,"url":null,"abstract":"Advancing data analysis tools for proteome-wide cross-linking mass spectrometry (XL-MS) requires ground-truth standards that mimic biological complexity. Here we develop well-controlled XL-MS standards comprising hundreds of recombinant proteins that are systematically mixed for cross-linking. We use one standard dataset to guide the development of Scout, a search engine for XL-MS with MS-cleavable cross-linkers. Using other, independent standard datasets and published datasets, we benchmark the performance of Scout and existing XL-MS software. We find that Scout offers an excellent combination of speed, sensitivity and false discovery rate control. The results illustrate how our large recombinant standard can support the development of XL-MS analysis tools and evaluation of XL-MS results. This Article reports cross-linking mass spectrometry (XL-MS) standard datasets with fully controlled protein interactions that are an order of magnitude more complex than existing ones. These datasets are used to benchmark XL-MS software and establish a fast, error-controlled search tool for XL-MS with cleavable reagents.","PeriodicalId":18981,"journal":{"name":"Nature Methods","volume":"21 12","pages":"2327-2335"},"PeriodicalIF":36.1000,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41592-024-02478-1.pdf","citationCount":"0","resultStr":"{\"title\":\"Proteome-scale recombinant standards and a robust high-speed search engine to advance cross-linking MS-based interactomics\",\"authors\":\"Milan Avila Clasen, Max Ruwolt, Cong Wang, Julia Ruta, Boris Bogdanow, Louise U. Kurt, Zehong Zhang, Shuai Wang, Fabio C. Gozzo, Tao Chen, Paulo C. Carvalho, Diogo Borges Lima, Fan Liu\",\"doi\":\"10.1038/s41592-024-02478-1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Advancing data analysis tools for proteome-wide cross-linking mass spectrometry (XL-MS) requires ground-truth standards that mimic biological complexity. Here we develop well-controlled XL-MS standards comprising hundreds of recombinant proteins that are systematically mixed for cross-linking. We use one standard dataset to guide the development of Scout, a search engine for XL-MS with MS-cleavable cross-linkers. Using other, independent standard datasets and published datasets, we benchmark the performance of Scout and existing XL-MS software. We find that Scout offers an excellent combination of speed, sensitivity and false discovery rate control. The results illustrate how our large recombinant standard can support the development of XL-MS analysis tools and evaluation of XL-MS results. This Article reports cross-linking mass spectrometry (XL-MS) standard datasets with fully controlled protein interactions that are an order of magnitude more complex than existing ones. These datasets are used to benchmark XL-MS software and establish a fast, error-controlled search tool for XL-MS with cleavable reagents.\",\"PeriodicalId\":18981,\"journal\":{\"name\":\"Nature Methods\",\"volume\":\"21 12\",\"pages\":\"2327-2335\"},\"PeriodicalIF\":36.1000,\"publicationDate\":\"2024-10-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.nature.com/articles/s41592-024-02478-1.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Nature Methods\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://www.nature.com/articles/s41592-024-02478-1\",\"RegionNum\":1,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BIOCHEMICAL RESEARCH METHODS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nature Methods","FirstCategoryId":"99","ListUrlMain":"https://www.nature.com/articles/s41592-024-02478-1","RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
Proteome-scale recombinant standards and a robust high-speed search engine to advance cross-linking MS-based interactomics
Advancing data analysis tools for proteome-wide cross-linking mass spectrometry (XL-MS) requires ground-truth standards that mimic biological complexity. Here we develop well-controlled XL-MS standards comprising hundreds of recombinant proteins that are systematically mixed for cross-linking. We use one standard dataset to guide the development of Scout, a search engine for XL-MS with MS-cleavable cross-linkers. Using other, independent standard datasets and published datasets, we benchmark the performance of Scout and existing XL-MS software. We find that Scout offers an excellent combination of speed, sensitivity and false discovery rate control. The results illustrate how our large recombinant standard can support the development of XL-MS analysis tools and evaluation of XL-MS results. This Article reports cross-linking mass spectrometry (XL-MS) standard datasets with fully controlled protein interactions that are an order of magnitude more complex than existing ones. These datasets are used to benchmark XL-MS software and establish a fast, error-controlled search tool for XL-MS with cleavable reagents.
期刊介绍:
Nature Methods is a monthly journal that focuses on publishing innovative methods and substantial enhancements to fundamental life sciences research techniques. Geared towards a diverse, interdisciplinary readership of researchers in academia and industry engaged in laboratory work, the journal offers new tools for research and emphasizes the immediate practical significance of the featured work. It publishes primary research papers and reviews recent technical and methodological advancements, with a particular interest in primary methods papers relevant to the biological and biomedical sciences. This includes methods rooted in chemistry with practical applications for studying biological problems.