Biology subjects

Mechtler, K.

Publications and source records attributed to Mechtler, K..

At least 19 recordsLinked to original sources

bioRxiv2026

Making the Impossible Possible: Uniting TMT and DIA for Scalable Low-Input-Proteomics

Isobaric multiplexing using tandem mass tags (TMT) and data-independent acquisition (DIA) are two powerful techniques in quantitative proteomics, each offering distinct advantages. Combining these strategies provides synergistic benefits for low-input applications such as single-cell proteomics (SCP). However, integrating these strategies has remained challenging due to co-isolation interference and increased data complexity. Here, we present a systematic, identification-linked evaluation of a hybrid DIA-TMTpro 18-plex workflow on the Orbitrap Astral mass spectrometer (MS). Using a two-proteome interference model of human and yeast digests, we benchmarked quantitative accuracy and precision of TMT based DDA and DIA acquisition strategies across a range of isolation windows, injection times and input amounts. We provide READ (Reporter Ion Extractor and Annotation Director), an in-house developed Python-based tool which enables streamlined reporter ion (RI) quantification and co-isolation purity assessment. Using READ, TMT-based quantification becomes possible from DIA-focused search engines like Spectronaut or DIA-NN, which do not natively support TMT. We show that co-isolation interference drives both ratio compression and ratio inflation in TMT RI-based quantification regardless of acquisition mode. As an interference-resistant alternative, we further evaluated quantification via TMT complementary ions, which achieved near-label free quantitative accuracy at the cost of reduced plexing capacity and proteome depth. Together, these results establish practical guidelines for combining DIA and TMTpro on the Orbitrap Astral mass spectrometer and provide a foundation for extending DIA-TMT workflows to low-input applications such as SCP, where sensitivity, accuracy and throughput are critical.

biochemistry↗

bioRxiv2026

Defining Quality Control Standards for Single-Cell Proteomics by Inter-Laboratory Benchmarking

Single-cell proteomics can quantify thousands of proteins from individual mammalian cells, yet the absence of community-wide quality control limits biological interpretability. Here, the HUPO Single Cell Initiative presents the first inter-laboratory single-cell proteomics benchmarking study across seven laboratories using standardized 384-well plates acquired on Orbitrap Astral and timsTOF Ultra2 instruments. Centralized analysis across six DIA software tools revealed that software choice impacts identification depth and quantitative accuracy more than instrument vendor. Multi-layered quality control enabled the detection of cell-leakage during sorting, LC misconfiguration, column degradation and site-specific pipetting failures. Inter-lab quantitative correlations were strongest between instruments of the same vendor relative to cross-platform comparisons. Sequential correction for plate identity and well position recovered clean cell-type separation for confident downstream differential expression analysis. This study provides a data-driven quality control framework spanning plate design to batch correction for reproducible single-cell proteomics across laboratories and platforms.

biochemistry↗

bioRxiv2026

Dbf4-dependent kinase promotes meiotic DNA end resection through cyclin-dependent kinase 12 and DNA-2 in Caenorhabditis elegans

Meiotic crossovers depend on the accurate processing of programmed DNA double-strand breaks by homologous recombination, which involves generating by resection the single-stranded DNA ends required for the subsequent strand invasion step. How regulatory kinases control DNA end resection in animal meiosis remains poorly understood. Here, we identify the Caenorhabditis elegans Dbf4-dependent kinase (DDK) complex, composed of CDC-7 and DBF-4, and identify CDK-12 as a candidate substrate. DDK promotes efficient meiotic DNA end resection, while crossover formation remains largely preserved in its absence. Loss of DDK function leads to SPO-11-dependent chromosome bridges at diakinesis that arise from recombination intermediates formed early in recombination. In addition to chromosome bridges, we observed elevated heterologous recombination that occurs independently of the canonical or alternative end-joining pathways. Interestingly, CDC-7 and DBF-4 localize dynamically during prophase I and load onto DNA in a hierarchical manner that depends on the BRC-1-BRD-1 complex. Epistasis analysis placed CDC-7 and CDK-12 within the DNA-2-dependent branch of long-range DNA resection. Together, our findings reveal an unidentified DDK/CDK-12/DNA-2 signaling axis that promotes efficient meiotic DNA resection to avoid the generation of aberrant recombination outcomes.

cell biology↗

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↗

bioRxiv2026

The Single Cell Proteomic blueprint, navigating instrumentation platforms, software tools and high-load libraries in neutrophils, RKO and A549 cells

Mass spectrometry-based single cell proteomics (SCP) is rapidly emerging as a powerful approach for biological research, with applications extending beyond in-vitro cancer cell lines. Recent advances make it possible to apply SCP to ex-vivo human cells from tissues such as the brain and pancreas, as well as to technically challenging immune populations such as neutrophils. However, these analyses remain more challenging and typically result in reduced proteomic coverage. To support the development of robust workflows for SCP data acquisition and analysis, we systematically evaluated multiple DIA search engines, search engine settings, the inclusion of high-load library samples in single-cell search spaces, the impact of contaminants, and the quantitative properties of identified proteins. These comparisons were performed across two major instrumentation platforms, Orbitrap Astral and timsTOF SCP, and across A549, RKO cells and neutrophils, three cell types differing in size and protein content. Our work here provides guidelines on the software parameters to use for SCP, instrument specific results and cell dependent optimizations of high-load libraries, as well as novel evaluation of the quantitative properties of proteins for single cell and low input proteomics.

biochemistry↗

bioRxiv2026

Digging deeper into the immunopeptidome with TripleToolWF

While the field of immunopeptidomics has matured substantially over the last years, high input amounts of cellular or tissue material are still required to obtain a somewhat complete profile of the immunopeptidome. Here we present a simple platform termed TripleToolWF (derived from Triple Tool workflow) to increase the number of identified and quantified immunopeptides combining the outputs of three search engines such as PEAKS Online 12, Sequest HT with INFERYS rescoring and MSFragger. For assessing the false discovery rate (FDR) an entrapment approach is used. The platform improved peptide identifications by 6-14% and peptide quantitations by 11-25% compared to the best individual search engine for two independent, previously published, bacterial infection datasets. Peptides were mostly 9-12mers as expected and >90% of the obtained 9mers were predicted binders by the stringent majority voting approach of Immunolyser 2.0 which indicates high confidence of the identified immunopeptides. The FDR was monitored using dedicated entrapment searches against shuffled databases. The resulting entrapment FDR was assessed before and after result pooling and showed only a minor increase upon pooling compared to the worst individual search engine. It remained even below the target of 1% peptide FDR in 40% of the experiments. Compared to the original publications, the number of high confidence bacterial immunopeptides was drastically elevated by 53% and 2800% for the Listeria monocytogenes and Mycobacterium bovis BCG projects, respectively, when applying strict filters. Of these additional bacterial sequences, >92% of the 9mer sequences were predicted as binders by at least one of the prediction algorithms of Immunolyser 2.0 illustrating their actual HLA binding nature. TripleToolWF hence provides a simple tool to further increase the number of obtained sequences from MS-based immunopeptidomics experiments to facilitate a deeper view of the immunopeptidome for refined vaccine candidate prioritization.

biochemistry↗

bioRxiv2026

Pushing the limits of SCP: bacSCP, a proof-of-concept study to investigate heterogeneity of bacteria by single cell proteomics.

Single-cell proteomics (SCP) has emerged as a powerful approach to quantify protein expression variability at cellular resolution, yet most state-of-the-art workflows are tailored to eukaryotic cells with only one study exploring how single bacteria can be analyzed by mass spectrometry. Here, we established bacSCP, a protocol extending SCP to bacterial cells, facing analytical challenges such as the thick bacterial cell wall hampering lysis, the extremely small cell size and resultant low protein content, and the consequently relatively high level of contaminating proteins from external sources. Using this bacSCP pipeline, we quantified more than 50 bacterial proteins from single Bacillus subtilis and Escherichia coli cells. Upon heat stress, we reproducibly observed up to 8-fold upregulation of chaperones including GroEL, GroES, and ClpC for a B. subtilis {Delta}mcsB strain. Importantly, single-cell measurements revealed potential heterogeneity within the heat-stressed subpopulation, enabling interrogation of stress-response variability at the proteome level. These results demonstrate the feasibility of bacSCP and provide a foundation for studying bacterial stress adaptation and phenotypic diversity with single-cell proteomic resolution.

systems biology↗

bioRxiv2026

CAN1-mediated autophagosome size regulation fine-tunes phosphate starvation tolerance in Arabidopsis thaliana

Inorganic phosphate (Pi) availability determines root development and plant performance. In Arabidopsis thaliana, external Pi is sensed by root tips and Pi limitation triggers ER stress-induced autophagy, yet the physiological impact and mechanisms controlling autophagosome biogenesis remain unclear. Here, we identify CANE1 (COMPONENT OF AUTOPHAGIC NETWORK) as a novel plant-specific regulator of autophagosome size in local Pi sensing. CANE1 associates with the plasma membrane-ER tethering protein VAP27-1 and binds to Pi-responsive ATG8 isoforms through conserved interaction motifs. Loss of CANE1 augments ER stress resistance by reducing autophagosome size in Pi-deprived root tips. Our findings establish CANE1 as a determinant of autophagosome size at the ER membrane. Thus, CANE1 functions as a molecular link between Pi-dependent ER stress signaling and fine-tuning of autophagic capacity.

plant biology↗

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↗

bioRxiv2025

Low-resolution FAIMS for increased peptide coverage in low-load and single-cell proteomics

Field Asymmetric Ion Mobility Spectrometry (FAIMS) enhances signal to noise ratio filtering ions based on their differential mobility, making it an indispensable tool for single-cell and low-input proteomics. Here, we investigate the impact of FAIMS resolution tuning via electrode temperature modulation to improve peptide identification sensitivity. We demonstrate that lowering FAIMS resolution broadens the compensation voltage window, thereby increasing ion transmission. This "low-resolution" mode significantly improves peptide identifications from a concentration range of HeLa digests by up to 18%. A weaker but still beneficial effect in peptide identifications and enhanced sensitivity could also be reproduced for single-cell samples. This leads to proteomic fingerprint shifts, resulting in distinct populations in principal component analysis from the very same cell-type in dependence on FAIMS resolution. Moreover, the increased ion counts of runs employing "low-resolution" FAIMS improve the quantitative precision of low-load measurements. These findings offer a practical optimization strategy for FAIMS-based low-input proteomics workflows, that allow for improved results by changing a single setting within the MS method without the need of any change in hardware adoption or data analysis pipelines.

biochemistry↗

bioRxiv2025

Single cell proteomic analysis defines discrete neutrophil functional states in human glioblastoma

Neutrophils are vital innate immune cells shown to infiltrate glioblastomas, however we currently lack the molecular understanding of their functional states within the tumour niche. Given that neutrophils are known to display a prominent discordance between mRNA and protein abundance, we developed ultra-sensitive mini-bulk and single cell proteomic (SCP) workflows to study the heterogeneity of peripheral blood and tumour associated neutrophils (TAN) from patients with glioblastoma. Mini-bulk analysis enabled a deeper protein coverage of circulating immature, mature and TAN populations, defining signatures of maturity and demonstrating that TANs resemble mature circulating neutrophils. Analysis of the SCP data resulted in the detection of >1,100 proteins from a single TAN providing a detailed characterization of neutrophil subsets in glioblastoma. Our approach shows evidence of pathogenic and anti-tumorigenic clusters and discovers cell states invisible to scRNAseq, opening new opportunities to selectively target pro-tumoural neutrophil states.

immunology↗

bioRxiv2025

A complex of MAST1 and 14-3-3 regulates Tau phosphorylation in the developing cortex

The MAST family of serine/threonine kinases has been implicated in a spectrum of human neurodevelopmental disorders. However, little is known about their biological function or regulation. Seeking to fill these gaps in our knowledge, we have identified upstream and downstream partners of MAST1. 14-3-3, a neuronal 14-3-3 paralog, specifically interacts with MAST1 at two regulatory serines, S90 and S161. PAK, a neuronal regulator of the actin cytoskeleton, phosphorylates MAST1 to regulate its interaction with 14-3-3. Exploiting mouse models of human Mega Corpus Callosum Syndrome (MCC) and whole brain phosphoproteomics, we identify the microtubule-associated protein Tau as a substrate of MAST1. We show that pathogenic MAST1 mutations perturb protein function either through misfolding or attenuation of kinase activity. Our data is consistent with a model in which the MAST kinases couple PAK, a neuronal regulator of the actin cytoskeleton, to microtubule remodeling during the differentiation and specification of cortical neurons.

molecular biology↗

bioRxiv2025

In vivo crosslinking and effective 2D enrichment for interactome studies of the nucleosome.

Cross-linking mass spectrometry has evolved as a powerful technique to study protein-protein interactions and to provide structural information over the past decades. Low reaction efficiencies, and complex matrices lead to challenging system wide crosslink analysis. In this study, we improved and streamlined an Azide-A-DSBSO based in vivo crosslinking workflow employing two orthogonal effective enrichment steps: Affinity enrichment and size exclusion chromatography (SEC). Combined, they allow an effective pulling of DSBSO containing peptides and remove the background of linear as well as mono-linked peptides. We found that the analysis of a single SEC fraction is effective to yield [~]90% of all crosslinks, which is important whenever measurement time is limited, and sample throughput is crucial. Our workflow resulted in more than 5000 crosslinks from K562 cells and generated a comprehensive PPI network from whole cells as well as nuclear extracts. From 393 PPI found within the nucleus, 56 have not yet been reported in the STING database and are representing a valuable resource for investigating new molecular mechanisms and provide complementary data for future studies. We further show, that by applying DSBSO to nuclear extracts we yield more crosslinks on lower abundant proteins and showcase this on the DEAD-box RNA helicase DDX39B which is predominantly expressed in the nucleus. Our data indicates that DDX39B is present in monomeric and dimeric form together with DDX39A within the nuclear extracts analyzed.

biochemistry↗

bioRxiv2024

Breaking Barriers in Crosslinking Mass Spectrometry: Enhanced Throughput and Sensitivity with the Orbitrap Astral Mass Analyzer

The advancement of crosslinking mass spectrometry (CLMS) has significantly enhanced the ability to study protein-protein interactions and complex biological systems. This study evaluates the performance of the Orbitrap Astral and Eclipse mass spectrometers in CLMS workflows, focusing on the identification of low-abundance crosslinked peptides. The comparison employed consistent liquid chromatography setups and experimental conditions, using Cas9 crosslinked with PhoX and DSSO as quality control samples. Results demonstrated that the Astral analyzer outperformed the Eclipse, achieving over 40% more unique residue pairs (URP) due to its superior sensitivity and dynamic range, attributed to its multi-reflection time-of-flight analyzer and nearly lossless ion transmission. Additionally, the study revealed that single higher-energy collisional dissociation (HCD) fragmentation methods significantly outperformed stepped HCD methods on the Astral, while the Eclipse maintained similar performance across both approaches. Gradient optimization experiments further highlighted the impact of separation times on crosslink identifications, with longer gradients yielding higher identification rates. Collectively, this work underscores the importance of instrumentation choice, fragmentation strategies, and method optimization in maximizing CLMS performance for protein interaction studies.

biochemistry↗

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↗

bioRxiv2024

A multi-year longitudinal harmonization of quality controls in mass spectrometry proteomics core facilities

Quality control procedures play a pivotal role in ensuring the reliability and consistency of data generated in mass spectrometry-based proteomics laboratories. However, the lack of standardized quality control practices across laboratories poses challenges for data comparability and reproducibility. In response, we conducted a harmonization study within proteomics laboratories of the Core for Life alliance with the aim to establish a common quality control framework, which facilitates comprehensive quality assessment and identification of potential sources of performance drift. Through collaborative efforts, we developed a consensus quality control standard for longitudinal assessment and we adopted a common processing software. We generated a 4-year longitudinal dataset from multiple instruments and laboratories, which enabled us to assess intra- and inter-laboratory variability, to identify causes of performance drift, and to establish community reference values for several quality control parameters. Our study enhances data comparability and reliability and fosters a culture of collaboration and continuous improvement within the proteomics community to ensure the integrity of proteomics data.

biochemistry↗

bioRxiv2024

Challenging the Astral mass analyzer - going beyond 5200 proteins per single-cell at unseen quantitative accuracy to study cellular heterogeneity.

A detailed proteome map is crucial for understanding molecular pathways and protein functions. Despite significant advancements in sample preparation, instrumentation, and data analysis, single-cell proteomics is currently limited by proteomic depth and quantitative performance. We combine a zero dead-end volume chromatographic column running at high throughput with the Thermo Scientific Orbitrap Astral mass spectrometer running in DIA mode. We demonstrate unprecedented depth of proteome coverage as well as accuracy and precision for quantification of ultra-low input amounts. Using a tailored library, we identify up to 7400 protein groups from as little as 250 pg HeLa at a throughput of 50 samples per day (SPD). We benchmark multiple data analysis strategies, estimate their influence on FDR and show that FDR on protein level can easily be maintained at 1 %. Using a two-proteome mix, we check for optimal parameters of quantification and show that fold change differences of 2 can still be successfully determined at single-cell level inputs. Eventually, we apply our workflow to A549 cells yielding a proteome coverage of up to 5300 protein groups from a single cell, which allows the observation of heterogeneity in a cellular population and studying dependencies between cell size and cell-cycle phase. Additionally, our work-flow enables us to distinguish between in vitro analogs of two human blastocyst lineages: naive human pluripotent stem cells (epiblast) and trophectoderm (TE)-like cells. Gene Ontology analysis of enriched proteins in TE-like cells harmoniously aligns with transcriptomic data, indicating that single-cell proteomics possesses the capability to identify biologically relevant differences between these two lineages within the blastocyst.

biochemistry↗