Biology subjects

Kuster, B.

Publications and source records attributed to Kuster, B..

At least 19 recordsLinked to original sources

bioRxiv2026

TOPAS: phosphoproteome data analysis and decision support platform for molecular tumor boards

The molecular tumor board (MTB) is central to precision oncology, providing personalized treatment recommendations based on molecular profiles of patient tumors. Genomics is instrumental for MTBs but often fails to identify clinically actionable targets, a gap that phosphoproteomics can fill. We present the tumor proteome activity status (TOPAS) platform, an end-to-end analysis pipeline that converts terabytes of phosphoproteomic data into patient-specific reports for MTB discussions, focusing on clinically relevant signaling linked to oncogenic mechanisms and therapeutic targets. Designed to scale with growing cohorts, the platform integrates data from 1,998 tumor samples to support patient- and cohort-level hypothesis generation. A web portal handles quality control, calculates TOPAS scores, identifies tumor antigens and immune checkpoints, and offers interactive analyses of differential protein abundance and outlier detection. The TOPAS platform is open source, addresses a critical unmet need and facilitates broader adoption of phosphoproteomics in precision oncology in the future.

bioinformatics↗

bioRxiv2026

High-Speed Mass Spectrometers diminish the difference between Data-Dependent and Data-Independent Acquisition Proteomics

Data-dependent acquisition mass spectrometry (DDA-MS) and data-independent acquisition mass spectrometry (DIA-MS) have historically offered complementary strengths in bottom-up proteomics, with DDA providing high-selectivity spectra for post-translational modification (PTM) analysis and DIA enabling more systematic peptide sampling. Here, we asked if this is still the case for the Orbitrap Astral platform that offers high-speed DDA and (ultra-) narrow-window DIA (nDIA) capabilities across proteome and phosphoproteome applications. When DDA and DIA measurements were parameter-matched (to the extent possible), the differences in analytical performance diminished markedly. Across extensive replicate analyses, both methods continued to identify new peptides and proteins without reaching saturation, indicating that the molecular complexity of biological samples still overwhelms even the fastest liquid chromatography-MS (LC-MS) methods. Incomplete sampling also contributed to substantial peptide-level non-overlap between DDA and nDIA and data completeness was only modestly better for nDIA than DDA across many replicates. Quantitatively, DDA and nDIA showed broadly similar precision and accuracy, with nDIA offering slightly higher precision and DDA slightly better accuracy in controlled mixture experiments. MS1-based quantification outperformed MS2-based quantification, particularly for short gradients, supporting MS1 quantification as a robust and general strategy for high-throughput proteomics. In phosphoproteomic samples, DDA and nDIA identified similar numbers of phosphopeptides, but DDA retained a small edge for phosphorylation site localisation. Together, the results show that advances in acquisition speed and sensitivity are narrowing the historical gap between DDA and DIA, while also revealing that current LC-MS workflows remain far from providing comprehensive proteome coverage. Going forward, further gains in dynamic range, scan speed, sensitivity, and transparent software tools will be required to reach systematic, comprehensive and reliable measurements of complex proteomes in a single shot.

biochemistry↗

bioRxiv2026

Brassinosteroid-regulated transcription factors confer epigenetic changes that repress plant immunity

When organisms encounter pathogens, they rapidly activate complex defense programs to ensure survival. While these immune responses are vital, they often also incur trade-offs, such as reduced growth and development and must therefore be tightly controlled 1,2. In this study, we reveal that the steroid hormones brassinosteroids (BRs) contribute to this control in Arabidopsis thaliana by repressing immunity-related genes. We provide evidence that the BR-regulated basic helix-loop-helix (bHLH) transcription factor CESTA (CES), along with its homologs BR ENHANCED EXPRESSION (BEE)1-3, mediate DNA methylation changes at transposable element (TE)-rich loci containing nucleotide-binding leucine-rich-repeat (NLR)-type receptor genes, including SUPPRESSOR OF NPR1-1 CONSTITUTIVE 1 (SNC1). These CES-induced methylation changes correlate with altered splicing of SNC1 pre-mRNA, a process that requires the BR receptor BRASSINOSTEROID INSENSITIVE 1 (BRI1). In support, we show that CES associates with components of the chromatin remodeling and splicing machinery. Together, our findings reveal a previously unrecognized BR-induced mechanism that modulates the epigenetic and post transcriptional regulation of immune genes, enabling plants to prioritize growth over defense. Significance statementSteroid hormones are powerful regulators of growth but also act as potent suppressors of immunity, with well-established clinical applications, for example in treating autoimmune diseases in humans. In plants, the steroid hormones brassinosteroids (BRs) exert similar effects. Here, we uncover that BR-mediated immune suppression involves DNA methylation changes and alternative splicing of a subset of immune receptor genes, that govern resistance responses mediated by the plant hormone salicylic acid. We provide evidence for a function of specific bHLH transcription factors in this process that link BR signaling to chromatin remodelling and RNA processing. Thereby our study reveals a novel mode of steroid hormone activity in immune repression, which involves epigenetic and posttranscriptional adjustment of immune receptor function.

plant biology↗

bioRxiv2026

GAP-MS: Automated validation of gene predictions using integrated mass ‎spectrometry evidence

1.Accurate genome annotation is fundamental to modern biology, yet distinguishing authentic protein-coding sequences from prediction artifacts remains challenging, particularly in complex plant genomes where automated methods are error-prone and manual curation is rarely feasible due to prohibitive time and costs. Here, we present GAP-MS (Gene model Assessment using Peptides from Mass Spectrometry), an automated proteogenomic pipeline that leverages mass spectrometry evidence to validate the protein-level accuracy of predicted gene models. Applied across 9 major crop species, GAP-MS consistently improved the prediction precision for four widely used gene prediction tools. In addition to filtering likely erroneous models, the pipeline identified hundreds of candidate protein-coding loci absent from current standard reference annotations. These peptide-supported loci were further verified by transcriptional evidence, well-supported functional annotations, and high coding-potential scores. Together, these results demonstrate that direct proteomic evidence can help resolve annotation ambiguities, define high-confidence peptide-supported reference proteomes, and uncover overlooked protein-coding genes, while facilitating the identification of sequences that may require further investigation.

bioinformatics↗

bioRxiv2025

Chemical proteomics decrypts the kinases that shape the dynamic human phosphoproteome

Mass-spectrometry-based phosphoproteomics enables the analysis of thousands of protein phosphorylation events across the human proteome. However, there is a lack of scalable, hypothesis-free, and statistically sound approaches for discovering, evaluating, and falsifying kinase::substrate relationships (KSRs). Here, we developed a new concept termed potency-coherence analysis. By measuring and integrating 17 million peptidoform-specific dose-response curves for 133 kinase inhibitors with known targets and affinities, we could critically re-evaluate published KSRs and discover thousands of potency-coherent and motif-plausible new KSRs for 96 human kinases. Application of these high-confidence KSRs enabled the estimation of kinase and signaling pathway activities in cancer patient biopsies. This unified and extendable framework has been implemented in ProteomicsDB to aid researchers in understanding the human phosphoproteome in health and disease.

systems biology↗

bioRxiv2025

Learning the Unseen: Data-Augmented Deep Learning for PTM Discovery with Prosit-PTM

Post-translational modifications (PTMs) are critical regulators of protein function, yet confidently identifying and localizing PTM sites across proteomes remains a challenging task. Integrating peptide property predictions into spectrum interpretation improves identification performance, but training data enabling zero-shot prediction across diverse PTMs are scarce. Here, we present a major expansion of the ProteomeTools dataset, comprising over 977,000 synthetic peptides, covering 22 PTM-residue combinations. Furthermore we developed Prosit-PTM, a model with chemically-informed encoding and amino acid substitution-based augmentation trained with our novel ground-truth dataset, that achieves accurate zero-shot predictions. Applied to modified peptides, Prosit-PTM enhances PTM-site localization in phosphoproteomics, increases identification of multiply modified peptides in histones, and enables data-driven rescoring for unseen modifications such as HLA peptides. Furthermore, the learned embeddings of amino acids and modifications capture physicochemical relationships underlying PTM-driven HLA presentation. Prosit-PTM is integrated into multiple open-source tools enabling PTM-aware rescoring, site localization, spectral library generation, and beyond.

bioinformatics↗

bioRxiv2025

Loss of PIMREG impairs double-strand break signaling and repair

Glioblastoma (GBM) is the most common primary brain tumor in adults. It is an aggressive type of tumor with an average overall survival of 12-15 months post-diagnosis. Standard treatment involves surgical resection, followed by radiotherapy and chemotherapy with temozolomide (TMZ). However, resistance to treatment is frequently observed. PIMREG is a marker of proliferation highly expressed across different tumor types, with particularly elevated levels in GBM. Our previous study revealed that PIMREG silencing sensitizes GBM cells to TMZ treatment and affects ATM activation, a key apical kinase involved in DNA damage signaling. Given the emerging significance of PIMREG in the DNA damage response, we sought to explore PIMREGs role in DNA damage repair and signaling in GBM cells exposed to genotoxic agents. Here we assessed the functionally enriched pathways associated with high PIMREG expression in GBM patient samples, analyzed the interactome of PIMREG upon treatment of GBM cells with TMZ and evaluated the impact of PIMREG loss on DNA damage signaling, DNA break formation and the repair of double-strand breaks. Our findings reveal that PIMREG functions as a direct substrate for ATM/ATR kinases, interacts with key DNA repair proteins upon TMZ treatment and actively facilitates the cellular response to chemotherapy- and radiotherapy-induced DNA damage. Taken together, PIMREG may function in the DNA damage response, particularly in the signaling and repair of double strand breaks via homologous recombination in GBM cells. In all, our data suggested high PIMREG expression may affect resistance of GBM cells to treatment.

cancer biology↗

bioRxiv2025

Multi-omics of barley Fusarium Head Blight converge on pathogen-triggered biosynthesis of aromatic amino acid derived chemical defense compounds

Fusarium Head Blight (FHB) is a devastating fungal disease of small grain cereals like wheat and barley, causing substantial yield and quality losses each year worldwide. FHB is caused by Fusarium species that produce mycotoxins such as deoxynivalenol (DON) that impairs protein biosynthesis. Although defense responses in barley to Fusarium infection have been described at the transcriptional level, it remains unclear to what extent these responses are translated into functional changes at the protein and metabolite levels. In this study, we employed comprehensive transcriptomics, proteomics, and metabolomics to dissect the defense responses of barley heads during infection with Fusarium culmorum. Our integrated analyses revealed a set of significantly regulated gene-protein pairs linked to biosynthetic pathways that consistently correspond to upregulated defense-related metabolites. These include tryptophan-derived stress metabolites such as tryptamine and serotonin, as well as barley-specific hydroxycinnamylamides, including conjugates from the trypthophan metabolism, hordatines, and their biosynthetic precursors. Integrating data across multiple omics layers identifies the upregulation of aromatic amino acid derived secondary metabolism as the most consistent barley response to FHB infection across diverse barley varieties that share barley-typical type II resistance to fungal spreading in the head rachis.

plant biology↗

bioRxiv2025

Peptide-RNA photo-crosslinks with tunable RNA chain map protein-RNA interfaces

Photocrosslinking mass spectrometry (MS) can map protein-RNA interfaces in living cells, but current isolation procedures for peptide-RNA crosslinks eliminate most RNA and therefore cannot identify the crosslinked RNA sequence. We introduce pepR-MS, a method that enriches peptide-RNA crosslinks with RNA chains of tunable length. To maximize proteomic depth, we applied pepR-MS to generate highly truncated RNA adducts, identifying over 34,000 unique crosslinks in 589 proteins of breast cancer cells and pinpointing RNA contacts in hundreds of structured domains and intrinsically disordered regions. By modulating nuclease digestion, longer RNA chains of up to five nucleotides were retained and sequenced alongside the crosslinked peptide using a specialized MS strategy. For RNA sequence assignment, we further introduce the computational tool SALT, which identified peptide-RNA sequence pairs for over 1,600 crosslinks in a single LC-MS run. Together, pepR-SALT provides a framework for mapping protein-RNA interfaces across the proteome and transcriptome at single-amino acid and nucleotide resolution.

molecular biology↗

bioRxiv2025

Enhanced photo-crosslinking in living cells with high-intensity longwave ultraviolet light

The activation of chemical reactions in living cells using ultraviolet (UV) light enables the interrogation of biomolecules in their native environment with photoreactive probes or crosslinking reagents. Although numerous photo-crosslinking approaches have been successfully employed, they often suffer from common limitations, including low reaction yields, the need for long exposure times, and irradiation-induced cellular damage from heat, desiccation, or side reactions. We recently showed that 365 nm light-emitting diodes (LEDs) enable rapid, bioorthogonal protein-DNA crosslinking in living cells, incurring minimal photodamage. Here we generalize this approach and demonstrate that high-intensity, longwave UV light reduces the irradiation time for in-cell photo-crosslinking reactions by up to 1000-fold, allowing protein-drug, protein-protein, protein-DNA and protein-RNA interactions to be fixed within seconds. Benchmarking this rapid photo-activation for the analysis of RNA-interacting proteomes responding to RNA-binding drugs, we demonstrate both qualitative and quantitative advantages of controlled, high-intensity UV irradiation, uncovering emergent experimental opportunities that were previously inaccessible to light-activated chemistry in intact cells and tissues.

molecular biology↗

bioRxiv2025

High-throughput chemical proteomics workflow for profiling protein citrullination dynamics

Citrullination is a post-translational modification implicated in autoimmune and inflammatory diseases, yet its low abundance and lack of effective enrichment tools have limited proteome-wide analysis. Here, we developed a robust chemical proteomics workflow with improved specificity and throughput. This method builds upon glyoxal-based derivatization and incorporates a cleavable biotin linker for efficient peptide enrichment, release, and identification via mass spectrometry. Benchmarking across biological systems demonstrated a >10-fold increase in the detection of citrullinated peptides (> 150-fold increase in intensity) at sub-0.1% abundance. Applying the workflow to mouse brain tissue and human primary neutrophils revealed dynamics and condition-specific changes in the citrullinome, including previously uncharacterized sites and regulatory processes. Notably, extensive citrullination of linker histone H1 and structural proteins such as lamin B1 in ionomycin-activated neutrophils suggests broad remodeling of cell architecture via citrullination. This workflow enables proteome-wide mapping of citrullination sites and facilitates its study across diverse biological contexts.

biochemistry↗

bioRxiv2025

High-performance proteomics at any chromatographic flow rate

Current applications of mass spectrometry-based proteomics range from single cell to body fluid analysis that come with very different demands regarding sensitivity or sample throughput. Additionally, the vast molecular complexity of proteomes and the massive dynamic range of protein concentrations in these biological systems require very high-performance chromatographic separations in tandem with the high speed and sensitivity afforded by mass spectrometer. In this study, we focussed on the chromatographic angle and, more specifically, systematically evaluated proteome analysis performance across a wide range of chromatographic flow rates (0.3 - 50 L/min) and associated column diameters using a Vanquish Neo UHPLC coupled online to a Q Exactive HF-X mass spectrometer. Serial dilutions of HeLa cell line digests were used for benchmarking and total analysis time from injection-to-injection was intentionally fixed at 60 minutes (24 samples per day). The three key messages of the study are that i) all chromatographic flow rates are suitable for high-quality proteome analysis, ii) capLC (1.5 L/min) is a very robust, sensitive and quantitative alternative to nanoLC for many applications and iii) showcased proteome, phosphoproteome and drug proteome data provide sound empirical guidance for laboratories in selecting appropriate chromatographic flow rates and column diameters for their specific application.

systems biology↗

bioRxiv2025

Illuminating oncogenic KRAS signaling by multi-dimensional chemical proteomics

Mutated KRAS is among the most frequent activating genetic alterations in cancer and drug discovery efforts have led to inhibitors that block its activity. To better understand oncogenic KRAS signaling and the cytostatic effects of drugs, we performed comprehensive dose-dependent proteome-wide target deconvolution, pathway engagement and protein expression characterization of KRAS, MEK, ERK, SHP2 and SOS1 inhibitors in pancreatic (KRAS G12C, G12D) and lung cancer (KRAS G12C) cells. Analysis of the resulting 687,954 dose-response curves available online revealed both common and cell line-specific signaling networks dominated by oncogenic KRAS activity. Time-dose experiments separated early KRAS-MEK-ERK from CDK-mediated signaling that cause cells to exit from the cell cycle. This transition to a quiescent state occurred without substantial proteome re-modelling but extensive changes of protein phosphorylation and ubiquitylation. The collective data highlights the complexity of KRAS signaling in cancer and places a large number of new proteins into this functional context.

cell biology↗

bioRxiv2024

Spermidine alleviates depression via control of the stress response

Depression is a stress-associated disorder, and it represents a major global health issue. Its pathophysiology is complex and remains insufficiently understood, with current medications often showing limited efficacy and undesirable side effects. Here, we identify imbalanced polyamine levels and dysregulated autophagy as key components of the acute stress response in humans, and as hallmarks of chronic stress and depressive disorders. Moreover, conventional antidepressant pharmacotherapy increases endogenous plasma concentrations of the polyamine spermidine exclusively in patients who respond to the treatment, suggesting a link between spermidine and successful outcomes. In a clinical trial, involving drug-naive depressed individuals, three weeks of spermidine supplementation increased autophagy and alleviated symptoms of depression. Behavioral and mechanistic findings of spermidine supplementation were validated in various mouse stress and depression models. In summary, spermidine supplementation mitigates polyamine dysregulation and stimulates autophagy under pathological stress conditions, offering a novel and well-tolerated treatment approach for stress-related depressive disorders.

neuroscience↗

bioRxiv2024

Barley resistance and susceptibility to fungal cell entry involve the interplay of ROP signaling with phosphatidylinositol-monophosphates

Rho-of-plant small GTPases (ROPs) are regulators of plant polar growth and of plant-pathogen interactions. The barley ROP, RACB, is involved in susceptibility towards infection by the barley powdery mildew fungus Blumeria hordei (Bh) but little is known about the cellular pathways that connect RACB-signaling to disease susceptibility. Here we identify novel RACB interaction partners of plant or fungal origin by untargeted co-immunoprecipitation of constitutively active (CA) RACB tagged by green-fluorescent protein from Bh-infected barley epidermal layers and subsequent analysis by liquid chromatography-coupled mass spectrometry. Three of immunoprecipitated proteins, a plant phosphoinositide phosphatase, a plant phosphoinositide phospholipase and a putative Bh-effector protein are involved in the barley-Bh-pathosystem and support disease resistance or susceptibility, respectively. RACB and its plant interactors bind to overlapping anionic phospholipid species in vitro, and in case of RACB, this lipid-interaction is mediated by its carboxy-terminal polybasic region (PBR). Fluorescent markers for anionic phospholipids show altered subcellular distribution in barley cells during Bh-attack and under expression of a RACB-binding fungal effector. Phosphatidylinositol 4-phosphate, phosphatidylinositol 3,5-bisphosphate and phosphatidylserine show a distinct enrichment at the haustorial neck region, suggesting a connection to subcellular targeting of RACB at this site. The interplay of ROPs with anionic phospholipids and phospholipid-metabolizing enzymes may thus enable the subcellular enrichment of components pivotal for success or failure of fungal penetration.

plant biology↗

bioRxiv2024

Pharmacoproteomic profiling identifies secreted markers for aberrant drug action

Adverse drug reactions (ADRs) contribute significantly to late-stage attrition in drug discovery due to their unpredictability and enigmatic underlying mechanisms. Here we applied mass spectrometry-based proteomics to assess the effects of 46 approved or retracted drugs with various levels of concerns for drug-induced liver injury and annotated for mitochondrial mechanisms, along with 8 tool compounds, on the secretome of a hepatocyte liver model. We observed distinct clusters of non-canonical secretion, and intracellular thermal proteome profiling linked dysregulated mechanisms to extracellular markers. Functional follow-up confirmed lysosomal alterations by cationic-amphiphilic drugs, connected damage of the respiratory chain to Rab7-dependent secretion of mitochondrial proteins, and linked drug-induced endoplasmic reticulum stress to reduced basal secretion. Perturbation of sphingolipid biosynthesis pathways specifically induced secretion of the cargo sorting protein SDF4 whilst suppressing secretion of its cargo proteins. Thermal stability changes of clusters of membrane proteins in distinct subcellular compartments suggest local accumulation as important driver for unexpected drug effects through direct and indirect interactions.

pharmacology and toxicology↗

bioRxiv2024

KIPK and KIPK-LIKE1 suppress overbending during negative hypocotyl gravitropic growth

Plants use environmental cues, such as the direction of gravity or the direction, quantity and quality of light, to orientate organ and plant growth. During germination of angiosperm seeds in the soil, hypocotyl elongation is directed by negative gravitropism responses such that the seedling can reach the light for photosynthesis and autotrophic growth. Hypocotyl elongation in the soil, however, also requires mechanisms to efficiently grow around obstacles such as soil particles. Here, we identify KIPK (KINESIN-LIKE CALMODULIN-BINDING PROTEIN INTERACTING PROTEIN KINASE) and the paralogous KIPKL1 (KIPK-LIKE1) as genetically redundant regulators of hypocotyl bending, in that KIPK and KIPKL1 are required to efficiently align hypocotyl growth with the gravity vector after obstacle avoidance. At the same time, we find that the highly homologous KIPKL2 (KIPK-LIKE2) must be functionally distinct. We further find that KIPK, and likely also KIPKL1, phosphorylate BRXL2 (BREVIS RADIX LIKE2) and ARKs (ARMADILLO REPEAT KINESINs), that mutants of both KIPK phosphorylation substrates share the overbending phenotype with kipk kipkl1 mutants, and that KIPK and KIPKL1 act synergistically with the ARK-regulatory NEK6 (NIMA-RELATED PROTEIN KINASE6). We propose that KIPK and KIPKL1 regulate ARK kinesins and thereby cortical microtubules for efficient gravitropic hypocotyl bending.

plant biology↗

bioRxiv2024

Unifying the analysis of bottom-up proteomics data with CHIMERYS

Proteomic workflows generate vastly complex peptide mixtures that are analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS), creating thousands of spectra, most of which are chimeric and contain fragment ions from more than one peptide. Because of differences in data acquisition strategies such as data-dependent (DDA), data-independent (DIA) or parallel reaction monitoring (PRM), separate software packages employing different analysis concepts are used for peptide identification and quantification, even though the underlying information is principally the same. Here, we introduce CHIMERYS, a novel, spectrum-centric search algorithm designed for the deconvolution of chimeric spectra that unifies proteomic data analysis. Using accurate predictions of peptide retention time, fragment ion intensities and applying regularized linear regression, it explains as much fragment ion intensity as possible with as few peptides as possible. Together with rigorous false discovery rate control, CHIMERYS accurately identifies and quantifies multiple peptides per tandem mass spectrum in DDA, DIA and PRM experiments.

biochemistry↗