Biology subjects

Klingmüller, U.

Publications and source records attributed to Klingmüller, U..

5 recordsLinked to original sources

bioRxiv2026

Integration of proteomic data from cell lines and tumors

Cancer cell lines are widely used in preclinical research, yet the clinical translation of findings from cell lines remains limited. Identifying cell lines that best resemble patient tumors requires integration of molecular profiles across biologically distinct sample types. Advances in transcriptomic integration have demonstrated the potential of deep learning for aligning data across different sample types. However, comparable approaches for proteomic data integration remain lacking, potentially because of the prevalence of missing values in proteomic datasets. Here, we introduce ProtInt, a deep learning-based framework that integrates proteomic data by combining principles from proteomic imputation and transcriptomic integration methods. We applied ProtInt to integrate label-free proteomic profiles from 771 cancer cell lines and 550 treatment-naive tumors, and showed that ProtInt outperformed batch correction and transcriptomic integration methods. Comparison of the cell line proteomes before and after integration revealed recurrent increase of proteins associated with immune reaction and reduction of proteins involved in mitochondrial gene expression as proteomes of cell lines were adapted to resemble tumors. These results establish ProtInt as a framework for joint analysis of proteomic datasets across distinct sample types and may facilitate the identification of cell lines best suited for clinically relevant studies.

bioinformatics↗

bioRxiv2024

TMPRSS6 cleaves KCNE1 and causes arrhythmias in iron overload disease

Iron storage disease is associated with cardiovascular manifestations, including various forms of cardiac arrhythmias of unknown origin. In this study, cardiac arrhythmias associated with iron overload were investigated in human iPSC-derived cardiomyocytes (hiPSC-CM) and hiPSC-derived sinus node-like pacemaker cells. Among other effects, iron overload leads to an increase in the plasma membrane-anchored protease TMPRSS6. TMPRSS6 cleaves the auxiliary subunit KCNE1 N-terminally and thus modulates the function of both the IKs (KCNQ1/KCNE1 current) and the If (HCN4/KCNE1) ion channels. Furthermore, TMPRSS6 induces a reduction of electric field potential (EFP) count and increased duration in hiPSC-derived ventricular-like cells and in hiPSC-derived pacemaker-like cells. In accordance with these in vitro generated results, TMPRSS6-mediated interactions show pro-arrhythmic effects in silico. Therefore, the TMPRSS6 - KCNE1-KCNQ1 and TMPRSS6 - KCNE1-HCN4 cascades may represent new clinically relevant pro-arrhythmic mechanisms in iron overload diseases.

physiology↗

bioRxiv2023

A General Method to Accurately Count Molecular Complexes and Determine the Degree of Labelling in Cells Using Protein Tags

Determining the label to target ratio, also known as degree of labelling (DOL), is crucial for quantitative fluorescence microscopy and a high DOL with minimal unspecific labelling is beneficial for fluorescence microscopy in general. Yet, robust, versatile, and easy-to-use tools for measuring cell-specific labelling efficiencies are not available. This study presents a novel DOL determination technique named Protein-tag DOL (ProDOL), which enables fast DOL measurements and optimisation of protein-tag labelling. With ProDOL various factors affecting labelling efficiency, including substrate type, incubation time, and concentration, as well as sample fixation and cell type can be easily assessed. We applied ProDOL to investigate how HIV-1 pathogenesis factor Nef modulates CD4 T cell activation measuring total and activated copy numbers of the adaptor protein SLP-76 in signalling microclusters. ProDOL proved to be a versatile and robust tool for labelling calibration, enabling determination of labelling efficiencies, optimisation of strategies, and quantification of protein stoichiometry.

cell biology↗

bioRxiv2023

Cancer-associated fibroblasts promote drug resistance in ALK-driven lung adenocarcinoma cells by upregulating lipid biosynthesis

Targeted therapy interventions using tyrosine kinase inhibitors (TKIs) provide encouraging treatment responses in ALK-rearranged lung adenocarcinomas, yet resistances occur almost inevitably. Apart from tumor cell-intrinsic resistance mechanisms, accumulating evidence supports a role of cancer-associated fibroblasts (CAFs) in affecting the therapeutic vulnerability of lung cancer cells. Here, we aimed to investigate underlying molecular networks shaping the therapeutic susceptibility of ALK-driven lung adenocarcinoma cells via tumor microenvironmental cues using three-dimensional (3D) spheroid co-culture settings. We show that CAFs promote therapy resistance of lung tumor cells against ALK inhibition by reducing apoptotic cell death and increasing cell proliferation. Using single-cell RNA-sequencing analysis, we show that genes involved in lipogenesis constitute the major transcriptional difference between TKI-treated homo- and heterotypic lung tumor spheroids. CAF-conditioned medium and CAF-secreted factors HGF and NRG1 were both able to promote resistance of 3D-cultured ALK-rearranged lung tumor cells via AKT signaling, which was accompanied by enhanced de novo lipogenesis and supression of lipid peroxidation. Notably, simultaneous targeting of ALK and SREBP-1 was able to overcome the established CAF-driven lipid metabolic-supportive niche of TKI-resistant lung tumor spheroids. Our findings highlight a crucial role of CAFs in mediating ALK-TKI resistance via lipid metabolic reprogramming and suggest new ways to overcome resistance towards molecular directed drugs by targeting vulnerabilities downstream of oncogenic signaling.

cancer biology↗

bioRxiv2020

Identification of Interleukin1β as an Amplifier of Interferon alpha-induced Antiviral Responses

The induction of an interferon-mediated response is the first line of defense against pathogens such as viruses. Yet, the dynamics and extent of interferon alpha (IFN)-induced antiviral genes vary remarkably and comprise three expression clusters: early, intermediate and late. By mathematical modeling based on time-resolved quantitative data, we identified mRNA stability as well as a negative regulatory loop as key mechanisms endogenously controlling the expression dynamics of IFN-induced antiviral genes in hepatocytes. Guided by the mathematical model, we uncovered that this regulatory loop is mediated by the transcription factor IRF2 and showed that knock-down of IRF2 results in enhanced expression of early, intermediate and late IFN-induced antiviral genes. Co-stimulation experiments with different pro-inflammatory cytokines revealed that this amplified expression dynamics of the early, intermediate and late IFN-induced antiviral genes can be mimicked by co-application of IFN and interleukin1 beta (IL1{beta}). Consistently, we found that IL1{beta} enhances IFN-mediated repression of viral replication. Conversely, we observed that in IL1{beta} receptor knock-out mice replication of viruses sensitive to IFN is increased. Thus, IL1{beta} is capable to potentiate IFN-induced antiviral responses and could be exploited to improve antiviral therapies. Author SummaryInnate immune responses contribute to the control of viral infections and the induction of interferon alpha (IFN)-mediated antiviral responses is an important component. However, IFN induces a multitude of antiviral response genes and the expression dynamics of these genes can be classified as early, intermediate and late. Here we show, based on a mathematical modeling approach, that mRNA stability as well as the negative regulator IRF2 control the expression dynamics of IFN-induced antiviral genes. Knock-down of IRF2 resulted in the amplified IFN-mediated induction of the antiviral genes and this amplified expression of antiviral genes could be mimicked by co-stimulation with IFN and IL1{beta}. We observed that co-stimulation with IFN and IL1{beta} enhanced the repression of virus replication and that knock-out of the IL1 receptor in mice resulted in increased replication of a virus sensitive to IFN. In sum, our studies identified IL1{beta} as an important amplifier of IFN-induced antiviral responses.

systems biology↗