Biology subjects

Beck, K.

Publications and source records attributed to Beck, K..

11 recordsLinked to original sources

bioRxiv2026

Prospective pan-cancer phosphoproteomics at clinical scale extends therapeutic options in precision oncology

Genomics-guided precision oncology has improved survival in cancer entities with actionable mutations but cannot capture oncogenic signaling that manifests at the protein level. Here, we report a prospective, real-world pan-cancer study profiling proteomes and phosphoproteomes of 1,998 tumor samples from adults and children with rare or advanced cancers enrolled in the German precision oncology programs DKFZ/NCT/DKTK MASTER, CATCH and INFORM and their molecular tumor boards (MTBs). We developed tumor proteome activity status (TOPAS) scores for 46 clinically relevant kinases, an immune activity score capturing antigen presentation and T-cell activation and identified therapeutically targetable cell-surface proteins for 94% of patients. These readouts enhance MTB recommendations by exposing actionable non-genomic kinase activity, refining interpretation of oncogenic genome alterations, and highlighting cell-surface treatment options. Three proof-of-concept analyses indicate clinical utility including kinase activity-stratified pazopanib response in sarcoma, immune activity score-tracked checkpoint-inhibitor outcomes pan-cancer, and a phosphoproteomic biomarker distinguishing EGFR-inhibitor response in chordoma.

cancer biology↗

bioRxiv2026

Active microbial communities and their extrachromosomal elements link organic matter degradation to methane cycling in anoxic sediments

Anaerobic carbon transformation in freshwater sediments drives substantial methane emissions globally, yet the microbial taxa linking complex carbon degradation to methane production remain poorly characterized. Here, we combined metagenomics with the first metatranscriptomic dataset from the anoxic sediments of meromictic Lake Cadagno (Swiss Alps) to identify the active microbial clades, metabolic pathways, and extrachromosomal elements (ecDNA) across a depth gradient within the upper 56 cm of sediment. We recovered 802 species-level metagenome-assembled genomes (MAGs) spanning 66 phyla and identified a Bacteroidota clade (VadinHA17) as one of the most abundant and transcriptionally active populations in the sediment. This clade encodes and transcribes a broad range of diverse glycoside hydrolases (GH), indicating a central role in complex carbohydrate degradation. Transcriptional profiles suggest that this clade ferments organic substrates to acetate and hydrogen, which are key substrates for methanogenesis. In line with this, the acetoclastic methanogen Methanothrix and hydrogenotrophic Methanoregula were among the most abundant and transcriptionally active archaea in the same depth layers. Beyond microbial genomes, we detected 86,905 viral OTUs (vOTUs) and 2,136 plasmid OTUs (pOTUs), with free viruses and plasmids accounting for 5-10% and 0.2% of all sequencing reads, respectively. Notably, plasmids and viruses associated with Bacteroidota VadinHA17 encode and transcribe GHs that could augment host carbohydrate-degrading capacity. Together, these findings reveal new details on how methane production in anoxic lake sediments emerges from a network spanning primary fermentation, methanogenesis and ecDNA-mediated metabolisms.

ecology↗

bioRxiv2025

Ripples of Resistance: Unveiling Antimicrobial Resistance Dynamics Along Switzerland's Aare River

The global spread of antimicrobial resistance (AMR) is a serious public health concern, driven by widespread antibiotic use and the global environmental circulation of antibiotic-resistant bacteria and resistance genes (ARGs). Wastewater treatment plants (WWTPs) are important sources of anthropogenic AMR entering large rivers, which serve as vital water resources but facilitate downstream dissemination. The drivers and dynamics of AMR propagation along river systems remain poorly understood. As Switzerlands longest and one of its largest rivers, the Aare, situated in the upper Rhine watershed, plays a central role in the water castle of Europe. This study examines the impact of WWTP discharges, some receiving high loads of hospital effluent, on ARG distribution along the 288 km Aare river-continuum. Using quantitative PCR targeting 14 ARGs conferring resistance to eight antibiotic classes, combined with 16S rRNA gene amplicon sequencing, we conducted a high-resolution spatial survey to assess shifts in the riverine ARG content and microbiome. Concentrations of trace metals and nutrients were analyzed as tracers of anthropogenic inputs. Results revealed a progressive increase in ARG abundance downstream, driven by WWTP effluents enriched in ARGs. Effluents had 70-fold higher mean ARG concentrations than upstream waters, raising downstream levels up to 141-fold. Major tributaries such as the Reuss and Limmat sustained elevated ARG levels, while passage through lakes markedly reduced concentrations. This study provides the first detailed baseline for ARG prevalence along a large river system, from pristine headwaters to pollution-affected lower reaches and insights into aquatic AMR dynamics and guidance for future monitoring.

microbiology↗

bioRxiv2025

Comparative toxicity of menthol- and tobacco-flavored electronic cigarette constituents causing inflammation, epithelial barrier dysfunction, and nicotinic acetylcholine receptor modulation in the absence of nicotine.

BackgroundMenthol and tobacco-flavored nicotine delivery systems (ENDS) are widely used as safer alternatives to combustible cigarettes. These flavored products include constituents such as propylene glycol/vegetable glycerin (PG/VG), benzoic acid, acetoin, L-menthone, 98% menthone, 2-isopropyl-N,2,3-trimethylbutanamide (WS-23), vanillin, and carvone. However, little is known about the potential adverse effects of the constituents in these flavored products. Rationale and hypothesisWe hypothesized that exposure to common constituents in tobacco- and menthol-flavored ENDS constituents could elicit a lung-injurious response mediated by nicotinic acetylcholine receptor (-nAChR or CHRNA) modulation. MethodsHuman bronchial epithelial cells, BEAS-2B, cells were treated with commonly used menthol and tobacco constituents on trans well inserts. Transepithelial barrier resistance (TEER) and millivolts (mV) across epithelial cells were measured over a 24-hour time. To assess the elicited inflammatory response, cytokines IL8 and IL6 were quantified in the conditioned media. Cytotoxicity caused by these constituents was evaluated by acridine orange/propidium iodide (AO/PI) staining of the cells after 24 hrs. alpha nicotinic receptor protein abundance (1, 4, 5, and 7) was quantified by immunoblotting. ResultsEpithelial integrity was decreased over time with a significant decrease in TEER and voltage by ENDS constituents. A significant increase in IL6 in conditioned media was observed in PG/VG, carvone, and WS-23 treated cells. Carvone-treated cells also elicited significantly elevated IL8 in conditioned media. Further, increased 1, 4, 5, and 7 nAChR were seen in cells treated with PG/VG, Acetoin, Carvone, and WS-23. ConclusionThese findings suggested that common constituents in menthol- and tobacco-flavored ENDS induce lung inflammation, epithelial barrier dysfunction, and lung injury. Further, our data implicate potential lung disease pathogenesis via nAChR modulation-mediated inflammation by exposure to these ENDS constituents, even in the absence of nicotine.

pharmacology and toxicology↗

bioRxiv2024

Mapping the impact of age and APOE risk factors for late onset Alzheimer disease on long range brain connections through multiscale bundle analysis

Alzheimers disease currently has no cure and is usually detected too late for interventions to be effective. In this study we have focused on cognitively normal subjects to study the impact of risk factors on their long-range brain connections. To detect vulnerable connections, we devised a multiscale, hierarchical method for spatial clustering of the whole brain tractogram and examined the impact of age and APOE allelic variation on cognitive abilities and bundle properties including texture e.g., mean fractional anisotropy, variability, and geometric properties including streamline length, volume, and shape, as well as asymmetry. We found that the third level subdivision in the bundle hierarchy provided the most sensitive ability to detect age and genotype differences associated with risk factors. Our results indicate that frontal bundles were a major age predictor, while the occipital cortex and cerebellar connections were important risk predictors that were heavily genotype dependent, and showed accelerated decline in fractional anisotropy, shape similarity, and increased asymmetry. Cognitive metrics related to olfactory memory were mapped to bundles, providing possible early markers of neurodegeneration. In addition, physiological metrics such as diastolic blood pressure were associated with changes in white matter tracts. Our novel method for a data driven analysis of sensitive changes in tractography may differentiate populations at risk for AD and isolate specific vulnerable networks.

neuroscience↗

bioRxiv2023

Single-cell and spatial multi-omics identify innate and stromal modules targeted by anti-integrin therapy in ulcerative colitis.

Ulcerative colitis (UC) is driven by immune and stromal subsets, culminating in epithelial injury. Vedolizumab (VDZ) is an anti-integrin antibody that is effective for treating UC. VDZ is known to inhibit lymphocyte trafficking to the intestine, but its broader effects on other cell subsets are less defined. To identify the inflammatory cells that contribute to colitis and are affected by VDZ, we performed single-cell transcriptomic and proteomic analyses of peripheral blood and colonic biopsies in healthy controls and patients with UC on VDZ or other therapies. Here we show that VDZ treatment is associated with alterations in circulating and tissue mononuclear phagocyte (MNP) subsets, along with modest shifts in lymphocytes. Spatial multi-omics of formalin-fixed biopsies demonstrates trends towards increased abundance and proximity of MNP and fibroblast subsets in active colitis. Spatial transcriptomics of archived specimens pre-treatment identifies epithelial-, MNP-, and fibroblast-enriched genes related to VDZ responsiveness, highlighting important roles for these subsets in UC.

immunology↗

bioRxiv2023

Screening megasynthetase mutants at high throughput using droplet microfluidics

Nonribosomal peptide synthetases (NRPSs) are giant enzymatic assembly lines that deliver many pharmaceutically valuable natural products, including antibiotics. As the search for new antibiotics motivates attempts to redesign nonribosomal metabolic pathways, more robust and rapid sorting and screening platforms are needed. Here, we establish a microfluidic platform that reliably detects production of the model nonribosomal peptide gramicidin S. The detection is based on calcein-filled sensor liposomes yielding increased fluorescence upon permeabilization. From a library of NRPS mutants, the sorting platform enriches the gramicidin S producer 14.5-fold, decreases the number of stop codons 250-fold, and generates enrichment factors correlating with enzyme activity. Screening for NRPS activity with a reliable non-binary sensor will enable more sophisticated structure-activity studies and new engineering applications in the future.

bioengineering↗

bioRxiv2022

Vulnerable Brain Networks Associated with Risk for Alzheimer's Disease

Brain connectomes provide untapped potential for identifying individuals at risk for Alzheimers disease (AD), and can help provide novel targets based on selective circuit vulnerability. Age, APOE4 genotype, and female sex are thought to contribute to the selective vulnerability of brain networks in Alzheimers disease, in a manner that differentiates pathological versus normal aging. These brain networks may predict pathology otherwise hard to detect, decades before overt disease manifestation and cognitive decline. Uncovering network based biomarkers at prodromal, asymptomatic stages may offer new windows of opportunity for interventions, either therapeutic or preventive. We used a sample of 72 people across the age span to model the relationship between Alzheimers disease risk and vulnerable brain networks. Sparse Canonical Correlation analysis (SCCA) revealed relationships between brain subgraphs and AD risk, with bootstrap based confidence intervals. When constructing a composite AD risk factor based on sex, age, genotype, the highest weight was associated with genotype. Next, we mapped networks associated with auditory, visual, and olfactory memory, and identified networks extending beyond the main nodes known to be involved in these functions. The inclusion of cognitive metrics in a composite risk factor pointed to vulnerable networks, and associated with the specific memory tests. These regions with the highest cumulative degree of connectivity in our studies were the pericalcarine, insula, banks of the superior sulcus and cerebellum. To help scale up our approach, we extended Tensor Network Principal Component Analysis (TNPCA) to evaluate AD risk related subgraphs, introducing CCA components and sparsity. When constructing a composite AD risk factor based on sex, age, and genotype, and family risk factor the most significant risk was associated with age. Our sparse regression based predictive models revealed vulnerable networks associated with known risk factors. The prediction error was 17% for genotype, 24% for family risk factor, and 5 years for age. Age prediction in groups including MCI and AD subjects involved several regions that were not prominent for age prediction otherwise. These regions included the middle and transverse temporal, paracentral and superior banks of temporal sulcus, as well as the amygdala and parahippocampal gyrus. The joint estimation of AD risk and connectome based mappings involved the cuneus, temporal, and cingulate cortices known to be associated with AD, and add new candidates, such as the cerebellum, whose role in AD is to be understood. Our predictive modeling approaches for AD risk factors represent a stepping stone towards single subject prediction, based on distances from normative graphs.

neuroscience↗

bioRxiv2021

Integrated phospho-proteogenomic and single-cell transcriptomic analysis of meningiomas establishes robust subtyping and reveals subtype-specific immune invasion

Meningiomas are the most frequent primary intracranial tumors. They can follow a wide clinical spectrum from benign to highly aggressive clinical course. No specific therapy exists for refractory cases or cases not amenable to resection and radiotherapy. Identification of risk of recurrence and malignant transformation for the individual patients is challenging. However, promising molecular markers and prognostic subgrouping by DNA methylation are emerging. Still, the biological underpinnings of these diagnostic subgroups are elusive, and, consequently, no novel therapeutic options arise thereof. Here we establish robust subgroups across the full landscape of meningiomas, consistent through DNA methylation, mutations, the transcriptomic, proteomic and phospho-proteomic level. Pronounced proliferative stress and DNA damage repair signals in malignant cells and in clusters exclusive to recurrent tumors are in line with their higher mitotic activity, but also provide an explanation for the accumulation of genomic instability in anaplastic meningiomas. Although homozygous deletion of CDKN2A/B is a diagnostic marker of high-grade meningioma, the expression of its gene product increased from low to non-deleted high-grade cases. Differences between subgroups in lymphocyte and myeloid cell infiltration, representing a majority of tumor mass in low-grade NF2 tumors, could be assigned to cluster-specific interaction with tumor cells. Activation to a more proinflammatory phenotype and decreased infiltration of myeloid cells in high-grade cases correlated with lower expression of CSF1, located on chromosome arm 1p, whose deletion is known as prognostic marker, with no proposed mechanism before. Our results demonstrate a robust molecular subclassification of a tumor type across multiple layers, provide insight into heterogeneous growth dynamics despite shared pathognomonic mutations, and highlight immune infiltration modulation as a novel target for meningioma therapy.

genomics↗

bioRxiv2019

Transcriptomic profiling of plaque psoriasis and cutaneous T cell subsets during treatment with secukinumab

The IL17A inhibitor secukinumab is efficacious for the treatment of psoriasis. In order to define its mechanism of action, it is important to understand its impact on psoriatic whole skin tissue as well as specific skin-resident immune cell populations such as T lymphocytes. In this study, we treated 15 moderate-to-severe plaque psoriasis patients with secukinumab and characterized the longitudinal transcriptomic changes of whole lesional skin tissue and cutaneous CD4+ T effector cells (Teffs), CD4+ T regulatory cells (Tregs), and CD8+ T effector cells during 12 weeks of treatment. Secukinumab was clinically effective, with 100%, 47%, and 27% of patients in the study achieving PASI75, PASI90, and PASI100 by week 12, respectively. At baseline prior to treatment, we observed that IL17A overexpression predominates in psoriatic CD8+ T cells rather than Teffs, supporting the importance of IL-17-secreting CD8+ T cells (Tc17) compared to IL-17-secreting CD4+ T cells (Th17) cells in the pathogenesis of psoriasis. Although secukinumab targets only IL17A, we observed rapid reduction of IL17A, IL17F, IL23A, IL23R, and IFNG expression in lesional skin as soon as 2 weeks after initiation of treatment and normalization of expression by week 12. Secukinumab treatment resulted in resolution of 89-97% of psoriasis-associated expression differences in both bulk tissue and T cell subsets by week 12 of treatment. Overall, secukinumab appears to rapidly reverse many of the molecular hallmarks of psoriasis.

genomics↗

bioRxiv2017

Synthesizing Signaling Pathways from Temporal Phosphoproteomic Data

Advances in proteomics reveal that pathway databases fail to capture the majority of cellular signaling activity. Our mass spectrometry study of the dynamic epidermal growth factor (EGF) response demonstrates that over 89% of significantly (de)phosphorylated proteins are excluded from individual EGF signaling maps, and 63% are absent from all annotated pathways. We present a computational method, the Temporal Pathway Synthesizer (TPS), to discover missing pathway elements by modeling temporal phosphoproteomic data. TPS uses constraint solving to exhaustively explore all possible structures for a signaling pathway, eliminating structures that are inconsistent with protein-protein interactions or the observed phosphorylation event timing. Applied to our EGF response data, TPS connects 83% of the responding proteins to receptors and signaling proteins in EGF pathway maps. Inhibiting predicted active kinases supports the TPS pathway model. The TPS algorithm is broadly applicable and also recovers an accurate model of the yeast osmotic stress response.

bioinformatics↗