{"title":"Proteoform Identification Using Multiplexed Top-Down Mass Spectra.","authors":"Zhige Wang, Xingzhao Xiong, Xiaowen Liu","doi":"10.1002/pmic.70020","DOIUrl":null,"url":null,"abstract":"<p><p>Top-down mass spectrometry (TDMS) is the method of choice for analyzing intact proteoforms, as well as their posttranslational modifications and sequence variations. In top-down tandem mass spectrometry (TD-MS/MS) experiments, multiple proteoforms are often co-fragmented, resulting in multiplexed TD-MS/MS spectra. Due to their increased complexity, compared to spectra from single proteoforms, multiplexed TD-MS/MS spectra present significant challenges for proteoform identification and quantification. Here we present TopMPI, a new computational tool specifically designed for the identification of multiplexed TD-MS/MS spectra. Experimental results demonstrate that TopMPI substantially increases the sensitivity and accuracy of proteoform identification in multiplexed TD-MS/MS spectral analysis compared to existing tools. SUMMARY: Top-down mass spectrometry (TDMS) is a powerful technique for analyzing intact proteoforms; however, identifying multiple co-fragmented proteoforms from multiplexed tandem mass spectrometry (MS/MS) spectra remains a significant challenge. In this paper, we introduce TopMPI, a new computational tool specifically designed to identify multiplexed TD-MS/MS spectra using a two-round database search strategy. Compared to existing tools, TopMPI significantly improves the sensitivity and accuracy of proteoform identification from multiplexed MS/MS spectra. The development of TopMPI enhances the identification of low abundance proteoforms in complex biological samples and increases the potential of TDMS for discovering proteoform biomarkers in disease studies.</p>","PeriodicalId":224,"journal":{"name":"Proteomics","volume":" ","pages":"e70020"},"PeriodicalIF":3.9000,"publicationDate":"2025-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proteomics","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1002/pmic.70020","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
引用次数: 0
Abstract
Top-down mass spectrometry (TDMS) is the method of choice for analyzing intact proteoforms, as well as their posttranslational modifications and sequence variations. In top-down tandem mass spectrometry (TD-MS/MS) experiments, multiple proteoforms are often co-fragmented, resulting in multiplexed TD-MS/MS spectra. Due to their increased complexity, compared to spectra from single proteoforms, multiplexed TD-MS/MS spectra present significant challenges for proteoform identification and quantification. Here we present TopMPI, a new computational tool specifically designed for the identification of multiplexed TD-MS/MS spectra. Experimental results demonstrate that TopMPI substantially increases the sensitivity and accuracy of proteoform identification in multiplexed TD-MS/MS spectral analysis compared to existing tools. SUMMARY: Top-down mass spectrometry (TDMS) is a powerful technique for analyzing intact proteoforms; however, identifying multiple co-fragmented proteoforms from multiplexed tandem mass spectrometry (MS/MS) spectra remains a significant challenge. In this paper, we introduce TopMPI, a new computational tool specifically designed to identify multiplexed TD-MS/MS spectra using a two-round database search strategy. Compared to existing tools, TopMPI significantly improves the sensitivity and accuracy of proteoform identification from multiplexed MS/MS spectra. The development of TopMPI enhances the identification of low abundance proteoforms in complex biological samples and increases the potential of TDMS for discovering proteoform biomarkers in disease studies.
期刊介绍:
PROTEOMICS is the premier international source for information on all aspects of applications and technologies, including software, in proteomics and other "omics". The journal includes but is not limited to proteomics, genomics, transcriptomics, metabolomics and lipidomics, and systems biology approaches. Papers describing novel applications of proteomics and integration of multi-omics data and approaches are especially welcome.