Biology subjects

Jachmann, C.

Publications and source records attributed to Jachmann, C..

4 recordsLinked to original sources

bioRxiv2025

ProteoBench: the community-curated platform for comparing proteomics data analysis workflows

Mass spectrometry (MS)-based proteomics is a well-established strategy for analyzing complex biological mixtures. Many MS instruments and data acquisition strategies are available, and the data they acquire differ substantially, thus requiring tailored analysis algorithms. Hence, many dedicated bioinformatics workflows are developed. These are in constant evolution, and the community lacks a centralized platform for comparing their performance. Here, we propose ProteoBench, a single platform that brings together software developers and software users to provide an ever-evolving comparison of state-of-the-art proteomics data processing tools. ProteoBench is an open-source resource that enables the community to evaluate data analysis workflows, develop benchmarking modules dedicated to specific comparisons, and discuss the best methods to compare software tools. The platform ensures that the benchmark evolves alongside advances in proteomics data analysis workflows. ProteoBench guides researchers towards the best-suited tool and parameters for their specific project and data according to their needs, and developers can test their newly developed tools or workflows privately, before adding them as public references. This community-driven effort will increase transparency and reproducibility between MS data analysis workflows, as well as facilitate the development and publication of software workflows in the field.

bioinformatics↗

bioRxiv2025

The E. coli PeptideAtlas Build: Characterizing the observed Escherichia coli pan-proteome and its post-translational modifications

Escherichia coli is a widely used model organism in molecular biology. Despite its pivotal role, a comprehensive proteome resource covering the E. coli pan-proteome and its post-translational modifications (PTMs) has been lacking. Here we present the E. coli PeptideAtlas build, the first comprehensive pan-proteome analysis of E. coli, generated from 40 high-quality public and in-house datasets spanning a broad diversity of strains, sample types, and experimental conditions, and comprising over 73 million MS/MS spectra. All datasets were reprocessed using both a closed search (Trans-Proteomic Pipeline using MSFragger) and an open search (ionbot). The E. coli PeptideAtlas build provides evidence for 4,755 proteins, including 1,410 previously lacking protein-level support in UniProt. The resource offers protein coverage, modification sites, raw spectra with matched peptides, and manually annotated metadata for the E. coli pan proteome. PTM profiling identified over 10,000 modification sites, including phosphorylation (3,806), acetylation (754), methylation (730), glutathionylation (352) and phosphoribosylation (226). Analysis of the glutathionylation sites revealed potential links to metal binding regulation. We also detected proteins likely associated with phages, underscoring the value of pan-proteomic approaches for studying host-phage interactions. All identifications are publicly accessible and traceable through the PeptideAtlas interface. We expect that the E. coli PeptideAtlas build will provide a useful resource for the community, which supports, for example, targeted MS experiment design, PTM enrichment method development, and strain typing. It allows straightforward lookups of protein and peptide identifications and facilitates comparative proteomic analyses by enabling the assessment of protein presence and variability across different E. coli strains. The build is available at https://db.systemsbiology.net/sbeams/cgi/PeptideAtlas/buildDetails?atlas_build_id=585.

bioinformatics↗

bioRxiv2024

PathwayPilot: A User-Friendly Tool for Visualizing and Navigating Metabolic Pathways

BackgroundMetaproteomics, the study of collective proteomes in environmental communities, plays a crucial role in understanding microbial functionalities affecting ecosystems and human health. Pathway analysis offers structured insights into the biochemical processes within these communities. However, no existing tool effectively combines pathway analysis with peptide- or protein-level data. ResultsThis manuscript introduces PathwayPilot, a user-friendly web application for exploring and visualizing metabolic pathways. PathwayPilot can compare functional annotations across different samples or organisms within a sample. A case study on the impact of caloric restriction on gut microbiota demonstrated the tools efficacy in deciphering complex metaproteomic data. The re-analysis revealed significant shifts in enzyme expressions related to short-chain fatty acid biosynthesis, aligning with existing research findings and showcasing PathwayPilots capability for accurate functional annotation and comparison across different microbial communities. ConclusionsPathwayPilot represents a significant advancement in metaproteomic data analysis, offering a user-friendly interface for exploring and visualizing metabolic pathways. This study not only validates the tools applicability in real-world scenarios but also highlights its potential for broader research implications in microbial ecology and health sciences.

bioinformatics↗

bioRxiv2024

TIMS2Rescore: A DDA-PASEF optimized data-driven rescoring pipeline based on MS2Rescore

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 - such as 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 counter these issues by acquiring more discerning information at higher sensitivity levels, as is exemplified by the incorporation of ion mobility and parallel accumulation - 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 TIMS2Rescore, a data-driven rescoring workflow optimized for DDA-PASEF data from timsTOF instruments. This platform includes new timsTOF MS2PIP spectrum prediction models and IM2Deep, a new deep learning-based peptide ion mobility predictor. Furthermore, to fully streamline data throughput, TIMS2Rescore directly accepts Bruker raw mass spectrometry data, and search results from ProteoScape and many other search engines, including MS Amanda and PEAKS. We showcase TIMS2Rescore performance on plasma proteomics, immunopeptidomics (HLA class I and II), and metaproteomics data sets. TIMS2Rescore is open-source and freely available at https://github.com/compomics/tims2rescore.

bioinformatics↗