Biology subjects

Birklbauer, M. J.

Publications and source records attributed to Birklbauer, M. J..

4 recordsLinked to original sources

bioRxiv2026

A DIA-based quantitative crosslinking mass spectrometryframework for dynamic structural proteomics

Proteins undergo dynamic conformational rearrangements and interactions that are central to their biological functions. Quantitative crosslinking mass spectrometry enables the analysis of those dynamics and molecular interactions, but rigorous confidence assessment and empirical validation strategies for quantitative measurements remain underdeveloped, and integrated analysis of complementary structural features, including monolinks and protein-RNA adducts, remains limited. Here we present a data-independent acquisition (DIA)-based framework for quantitative crosslinking mass spectrometry (DIA-QCLMS) that combines optimized acquisition strategies, crosslink-aware spectral libraries and empirical false-discovery-rate (FDR) validation. The workflow supports crosslinks, monolinks and protein-RNA adducts and integrates spectral-library generation from two crosslinking search engines (xiSEARCH and MS Annika). To enable robust confidence assessment in DIA data, we developed a four-state target-decoy spectral library strategy that explicitly models target-target, target-decoy, decoy-target and decoy-decoy crosslink spectra. Experimental entrapment datasets enabled empirical validation of confidence estimation, whereas benchmarking with PhoX-crosslinked Cas9 demonstrated improved quantitative completeness and reproducibility compared with data-dependent acquisition. Application of the workflow to the ATP-dependent RNA helicase UAP56 (DDX39B) resolved ligand-dependent changes in intramolecular restraints, residue accessibility and candidate RNA-contact sites associated with the transition from an open to a clamped conformation. These results establish DIA-QCLMS as a scalable framework for quantitative structural proteomics and provide practical strategies for confidence-controlled analysis of dynamic protein interactions and conformational states.

biochemistry↗

bioRxiv2025

Unified down-stream analysis of crosslinking mass spectrometry results with pyXLMS

Crosslinking mass spectrometry has become the method of choice for the identification of protein-protein interactions and for gaining insight into the structures of proteins in vivo. However, connecting crosslink search engine results with down-stream analysis tools, and therefore gaining biological insight from crosslink identifications, has remained a manual and cumbersome step in the analysis that often requires expert bioinformatics knowledge. Here we introduce pyXLMS, a python package and public web application which aims to simplify and streamline this intermediate step, enabling researchers even without bioinformatics knowledge to conduct in-depth crosslink analyses. In its current state pyXLMS supports input from seven different crosslink search engines, as well as the mzI-dentML format of the HUPO Proteomics Standards Initiative. Down-stream analysis is facilitated by functionality that is directly available within pyXLMS such as aggregation, validation, annotation, filtering, and visualization. In addition, the data can easily be exported to more than ten supported down-stream analysis tools and formats. We demonstrate the applicability and benefits of pyXLMS by re-analyzing a publicly available crosslink dataset with a variety of different search engines and show how the same data analysis workflow can be applied using pyXLMS. pyXLMs is available via https://github.com/hgb-bin-proteomics/pyXLMS.

bioinformatics↗

bioRxiv2024

A journey towards developing a new cleavable crosslinker reagent for in-cell crosslinking

Crosslinking mass spectrometry (XL-MS) is a powerful technology that recently emerged as an essential complementary tool for elucidating protein structures and mapping interactions within a protein network. Crosslinkers which are amenable to post-linking backbone cleavage simplify peptide identification, aid in 3D structure determination and enable system-wide studies of protein-protein interactions (PPIs) in cellular environments. However, state-of-the-art cleavable linkers are fraught with practical limitations, including extensive evaluation of fragmentation energies and fragmentation behaviour of the crosslinker backbone. We herein introduce DiSPASO as a lysine-selective, MS-cleavable cross-linker with an alkyne handle for affinity enrichment. DiSPASO was designed and developed for efficient cell membrane permeability and crosslinking while securing low cellular perturbation. We tested DiSPASO employing three different copper-based enrichment strategies using model systems with increasing complexity (Cas9-Halo, purified ribosomes, live cells). Fluorescence microscopy in-cell crosslinking experiments revealed a rapid uptake of DiSPASO into HEK 293 cells within 5 minutes. While DiSPASO represents progress in cellular PPI analysis, its limitations and low crosslinking yield in cellular environments require careful optimisation of the crosslinker design, highlighting the complexity of developing effective XL-MS tools and the importance of continuous innovation in accurately mapping PPI networks within dynamic cellular environments. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=60 SRC="FIGDIR/small/621843v2_ufig1.gif" ALT="Figure 1"> View larger version (13K): org.highwire.dtl.DTLVardef@1821ed4org.highwire.dtl.DTLVardef@1b6180dorg.highwire.dtl.DTLVardef@1e50aaborg.highwire.dtl.DTLVardef@1f6185_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2024

Proteome-wide non-cleavable crosslink identification with MS Annika 3.0 reveals the structure of the C. elegans Box C/D complex

AbstractThe field of crosslinking mass spectrometry has seen substantial advancements over the past decades, enabling the structural analysis of proteins and protein-complexes and serving as a powerful tool in protein-protein interaction studies. However, data analysis of large non-cleavable crosslink studies is still a mostly unsolved problem due to its n-squared complexity. We here introduce a novel algorithm for the identification of non-cleavable crosslinks implemented in our crosslinking search engine MS Annika that is based on sparse matrix multiplication and allows for proteome-wide searches on commodity hardware. Application of this new algorithm enabled us to employ a proteome-wide search of C. elegans nuclei samples, where we were able to uncover previously unknown protein interactions and conclude a comprehensive structural analysis that provides a detailed view of the Box C/D complex, enhancing our understanding of its assembly and functional dynamics. Our findings provide valuable insights into the intricate regulation of cellular homeostasis and immune responses, which are conserved across species, including humans. Moreover, our algorithm will enable researchers to conduct similar studies that were previously unfeasible.

bioinformatics↗