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TIMS<sup>2</sup>Rescore: A Data Dependent Acquisition-Parallel Accumulation and Serial Fragmentation-Optimized Data-Driven Rescoring Pipeline Based on MS<sup>2</sup>Rescore

Arthur Declercq, Robbe Devreese, Jonas Scheid, Caroline Jachmann, Tim Van Den Bossche, Annica Preikschat, David Gomez‐Zepeda, Jeewan Babu Rijal, Aurélie Hirschler, Jonathan R. Krieger, Tharan Srikumar, George Rosenberger, Claudia Martelli, Dennis Trede, Christine Carapito, Stefan Tenzer, Juliane S. Walz, Sven Degroeve, Robbin Bouwmeester, Lennart Martens, Ralf Gabriels

2025Journal of Proteome Research20 citationsDOIOpen Access PDF

Abstract

High Resolution Image Download MS PowerPoint Slide The high throughput analysis of proteins with mass spectrometry (MS) is highly valuable for understanding human biology, discovering disease biomarkers, identifying therapeutic targets, and exploring pathogen interactions. To achieve these goals, specialized proteomics subfields, including plasma proteomics, immunopeptidomics, and metaproteomics, must tackle specific analytical challenges, such as an increased identification ambiguity compared to routine proteomics experiments. Technical advancements in MS instrumentation can mitigate these issues by acquiring more discerning information at higher sensitivity levels. This is exemplified by the incorporation of ion mobility and parallel accumulation and serial fragmentation (PASEF) technologies in timsTOF instruments. In addition, AI-based bioinformatics solutions can help overcome ambiguity issues by integrating more data into the identification workflow. Here, we introduce TIMS 2 Rescore, a data-driven rescoring workflow optimized for DDA-PASEF data from timsTOF instruments. This platform includes new timsTOF MS 2 PIP spectrum prediction models and IM2Deep, a new deep learning-based peptide ion mobility predictor. Furthermore, to fully streamline data throughput, TIMS 2 Rescore directly accepts Bruker raw mass spectrometry data and search results from ProteoScape and many other search engines, including Sage and PEAKS. We showcase TIMS 2 Rescore performance on plasma proteomics, immunopeptidomics (HLA class I and II), and metaproteomics data sets. TIMS 2 Rescore is open-source and freely available at https://github.com/compomics/tims2rescore .

Topics & Concepts

Computer scienceProteomicsWorkflowPipeline (software)MetaproteomicsIdentification (biology)Fragmentation (computing)Computational biologyData miningBioinformaticsData scienceChemistryBiologyDatabaseOperating systemBiochemistryProgramming languageGeneBotanyAdvanced Proteomics Techniques and ApplicationsMass Spectrometry Techniques and ApplicationsMachine Learning in Bioinformatics
TIMS<sup>2</sup>Rescore: A Data Dependent Acquisition-Parallel Accumulation and Serial Fragmentation-Optimized Data-Driven Rescoring Pipeline Based on MS<sup>2</sup>Rescore | Litcius