A Parallel Accumulation-Mobility Aligned Fragmentation Strategy Utilizing High-Resolution Ion Mobility for High-Performance Proteomics Analysis.

IF 6.3 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS
Molecular & Cellular Proteomics Pub Date : 2026-07-01 Epub Date: 2026-06-22 DOI:10.1016/j.mcpro.2026.101608
Leonard C Rorrer, Liulin Deng, Lauren Royer, Isabel Uribe, Benjamin C Orsburn, Oliver Bernhardt, Tejas Gandhi, Lukas Reiter, Daniel DeBord
{"title":"A Parallel Accumulation-Mobility Aligned Fragmentation Strategy Utilizing High-Resolution Ion Mobility for High-Performance Proteomics Analysis.","authors":"Leonard C Rorrer, Liulin Deng, Lauren Royer, Isabel Uribe, Benjamin C Orsburn, Oliver Bernhardt, Tejas Gandhi, Lukas Reiter, Daniel DeBord","doi":"10.1016/j.mcpro.2026.101608","DOIUrl":null,"url":null,"abstract":"<p><p>Here we present a novel data-independent acquisition (DIA) mass spectrometry (MS) operating mode termed parallel accumulation-mobility aligned fragmentation (PAMAF) that offers enhanced speed and sensitivity of ion fragmentation analysis for discovery workflows such as bottom-up proteomics. This mode of operation leverages high-resolution ion mobility (HRIM) separation capabilities of the structures for lossless ion manipulation technology to achieve HRIM-based precursor isolation in place of traditional quadrupole filtering approaches. PAMAF mode increases the number of features that can be identified per MS1/MS2 acquisition cycle by employing mobility-based time alignment to associate fragment ions with their corresponding precursor ions. By using a high-speed, lossless separation technique for precursor isolation instead of the comparatively slow and wasteful quadrupole filtering, ion losses are avoided while simultaneously increasing the rate at which precursor ions are sequentially fragmented and detected. In addition, by accumulating ions while the previous packet of ions is being analyzed, the PAMAF mode achieves ∼100% ion utilization efficiency. Benchmarking results of LC-PAMAF-MS analysis of a whole cell protein digest showed ∼6× more protein group identifications compared to a standard data-dependent acquisition analysis without HRIM on the same QTOF instrument, and >100 x improvement for low-load workflows. Quantitative evaluations demonstrated that PAMAF mode could quantify low abundance peptides, including those undetectable by data-dependent acquisition. In addition, since precursor isolation in PAMAF mode is size-based rather than m/z-based, coeluting isobars and isomers can be resolved prior to fragmentation, eliminating chimeric spectra that compromise identification accuracy. We also explored the benefits of combining HRIM and quadrupole isolation to achieve improved specificity termed DIA-PAMAF mode, which enabled the detection of over 8000 protein groups from a HeLa digest analysis. PAMAF mode brings a powerful new technique to the field of proteomics with the potential to improve the sensitivity and selectivity of mass spectrometry-based proteomics.</p>","PeriodicalId":18712,"journal":{"name":"Molecular & Cellular Proteomics","volume":" ","pages":"101608"},"PeriodicalIF":6.3000,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13396739/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Molecular & Cellular Proteomics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1016/j.mcpro.2026.101608","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2026/6/22 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
引用次数: 0

Abstract

Here we present a novel data-independent acquisition (DIA) mass spectrometry (MS) operating mode termed parallel accumulation-mobility aligned fragmentation (PAMAF) that offers enhanced speed and sensitivity of ion fragmentation analysis for discovery workflows such as bottom-up proteomics. This mode of operation leverages high-resolution ion mobility (HRIM) separation capabilities of the structures for lossless ion manipulation technology to achieve HRIM-based precursor isolation in place of traditional quadrupole filtering approaches. PAMAF mode increases the number of features that can be identified per MS1/MS2 acquisition cycle by employing mobility-based time alignment to associate fragment ions with their corresponding precursor ions. By using a high-speed, lossless separation technique for precursor isolation instead of the comparatively slow and wasteful quadrupole filtering, ion losses are avoided while simultaneously increasing the rate at which precursor ions are sequentially fragmented and detected. In addition, by accumulating ions while the previous packet of ions is being analyzed, the PAMAF mode achieves ∼100% ion utilization efficiency. Benchmarking results of LC-PAMAF-MS analysis of a whole cell protein digest showed ∼6× more protein group identifications compared to a standard data-dependent acquisition analysis without HRIM on the same QTOF instrument, and >100 x improvement for low-load workflows. Quantitative evaluations demonstrated that PAMAF mode could quantify low abundance peptides, including those undetectable by data-dependent acquisition. In addition, since precursor isolation in PAMAF mode is size-based rather than m/z-based, coeluting isobars and isomers can be resolved prior to fragmentation, eliminating chimeric spectra that compromise identification accuracy. We also explored the benefits of combining HRIM and quadrupole isolation to achieve improved specificity termed DIA-PAMAF mode, which enabled the detection of over 8000 protein groups from a HeLa digest analysis. PAMAF mode brings a powerful new technique to the field of proteomics with the potential to improve the sensitivity and selectivity of mass spectrometry-based proteomics.

利用高分辨率离子迁移率进行高性能蛋白质组学分析的平行积累-迁移率对齐碎片化策略。
在这里,我们提出了一种新的数据独立采集(DIA)质谱(MS)操作模式,称为平行积累-迁移率排列碎片(PAMAF),它为发现工作流程(如自下而上的蛋白质组学)提供了更快的速度和灵敏度。这种操作模式利用结构的高分辨率离子迁移率(hrm)分离能力,用于无损离子操作(SLIM)技术,以实现基于hrm的前体分离,取代传统的四极滤波方法。PAMAF模式通过利用基于迁移率的时间对齐将碎片离子与其相应的前体离子相关联,增加了每个MS1/MS2采集周期可以识别的特征数量。通过使用高速、无损的分离技术来分离前驱体,而不是相对缓慢和浪费的四极过滤,避免了离子损失,同时增加了前驱体离子依次破碎和检测的速度。此外,通过在分析前一包离子时积累离子,PAMAF模式实现了~ 100%的离子利用效率。全细胞蛋白质消化的LC-PAMAF-MS分析的基准结果显示,与在相同的QTOF仪器上没有hrm的标准数据依赖采集(DDA)分析相比,蛋白质组鉴定增加了约6倍,并且在低负载工作流程中提高了约100倍。定量评价表明PAMAF模式可以量化低丰度肽,包括DDA检测不到的肽。此外,由于PAMAF模式下的前体分离是基于尺寸的,而不是基于m/z的,因此可以在碎片化之前解决共溶等压线和异构体,从而消除了影响识别准确性的嵌合光谱。我们还探索了结合HRIM和四极分离的好处,以获得更高的特异性,称为DIA-PAMAF模式,该模式能够从HeLa消化分析中检测超过8,000个蛋白质组。PAMAF模式为蛋白质组学领域带来了一种强有力的新技术,具有提高基于质谱的蛋白质组学的灵敏度和选择性的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Molecular & Cellular Proteomics
Molecular & Cellular Proteomics 生物-生化研究方法
CiteScore
11.50
自引率
4.30%
发文量
131
审稿时长
84 days
期刊介绍: The mission of MCP is to foster the development and applications of proteomics in both basic and translational research. MCP will publish manuscripts that report significant new biological or clinical discoveries underpinned by proteomic observations across all kingdoms of life. Manuscripts must define the biological roles played by the proteins investigated or their mechanisms of action. The journal also emphasizes articles that describe innovative new computational methods and technological advancements that will enable future discoveries. Manuscripts describing such approaches do not have to include a solution to a biological problem, but must demonstrate that the technology works as described, is reproducible and is appropriate to uncover yet unknown protein/proteome function or properties using relevant model systems or publicly available data. Scope: -Fundamental studies in biology, including integrative "omics" studies, that provide mechanistic insights -Novel experimental and computational technologies -Proteogenomic data integration and analysis that enable greater understanding of physiology and disease processes -Pathway and network analyses of signaling that focus on the roles of post-translational modifications -Studies of proteome dynamics and quality controls, and their roles in disease -Studies of evolutionary processes effecting proteome dynamics, quality and regulation -Chemical proteomics, including mechanisms of drug action -Proteomics of the immune system and antigen presentation/recognition -Microbiome proteomics, host-microbe and host-pathogen interactions, and their roles in health and disease -Clinical and translational studies of human diseases -Metabolomics to understand functional connections between genes, proteins and phenotypes
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信
小红书