Biology subjects

Rykaer, M.

Publications and source records attributed to Rykaer, M..

3 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

From HeLa to human blood: extending single-cell proteomics to the smallest immune cells

Single-cell proteomics (SCP) holds the promise of decoding cellular heterogeneity at the functional level, yet achieving deep and reproducible proteome coverage from individual cells has remained a formidable challenge. Here, we established a high-sensitivity, label-free SCP platform that surpasses previous limits in depth and reproducibility. By integrating optimized low-input sample processing, refined liquid chromatography, and the Orbitrap Astral Zoom mass spectrometer, our approach routinely quantified over 7,000 proteins per individual HeLa cell, capturing thousands of low-abundance proteins that eluded prior SCP studies. Applied to very small human peripheral blood mononuclear cells (PBMCs), we identified up to 4,000 proteins per cell, including key markers distinguishing monocytes, T cells, and activated lymphocytes within heterogeneous populations, underscoring that single-cell proteomics can now directly elucidate clinically relevant primary samples with both depth and precision.

cell biology↗

bioRxiv2020

Mapping physiological ADP-ribosylation using Activated Ion Electron Transfer Dissociation (AI-ETD)

ADP-ribosylation (ADPr) is a post-translational modification that plays pivotal roles in a wide range of cellular processes. Mass spectrometry (MS)-based analysis of ADPr under physiological conditions, without relying on genetic or chemical perturbation, has been hindered by technical limitations. Here, we describe the applicability of Activated Ion Electron Transfer Dissociation (AI-ETD) for MS-based proteomics analysis of physiological ADPr using our unbiased Af1521 enrichment strategy. To benchmark AI-ETD, we profiled 9,000 ADPr peptides mapping to >5,000 unique ADPr sites from a limited number of cells exposed to oxidative stress, corresponding to 120% and 28% more ADPr peptides compared to contemporary strategies using ETD and EThcD, respectively. Under physiological conditions AI-ETD identified 450 ADPr sites on low-abundant proteins, including in vivo cysteine auto-modifications on PARP8 and tyrosine auto-modifications on PARP14, hinting at specialist enzymatic functions for these enzymes. Collectively, our data provides new insights into the physiological regulation of ADP-ribosylation.

molecular biology↗