Biology subjects

Uhlig, S.

Publications and source records attributed to Uhlig, S..

8 recordsLinked to original sources

bioRxiv2026

A chemogenetic CRISPR knockout screen identifies a ubiquitin-mediated calcineurin-BMP pathway relay in T cell activation

T cell activation is dependent on calcineurin signalling, yet how this pathway integrates with other regulatory systems remains incompletely understood. Here, we exploit the dual pharmacology of FK506, which inhibits calcineurin while also releasing FKBP12-mediated repression of BMP receptors, to dissect signalling crosstalk during T cell responses. A comparative genome-wide CRISPR knockout screen using FK506 and Cyclosporin A revealed that FK506 uniquely engages BMP pathway components and ubiquitin regulatory networks. Functional analyses in Jurkat and primary human T cells showed that FK506 induces BMP receptor-dependent activation of SMAD1/5/8 and triggers a rapid remodelling of K48- and K29-linked ubiquitin chains. Proteomics further demonstrated selective ubiquitination of immune signalling proteins and ubiquitin regulators, linking BMP pathway activation to proteasome-dependent turnover and non-proteolytic ubiquitin signalling. In primary T cells, BMP receptor signalling enhance calcineurin-driven activation, while changes in ubiquitin conjugation modulate this response, thereby establishing an integrated calcineurin-BMP-ubiquitin relay. Together, our results uncover a context-dependent signalling axis in which BMP activation and ubiquitin dynamics fine-tune calcineurin-mediated T cell signalling.

cell biology↗

bioRxiv2024

Towards Spectral Variation Analysis: A Data Quality Framework for Non-Targeted Methods

Non-targeted methods (NTM) require robust methods for comparing spectral data for reliable classification and identification. Traditional approaches using match factors reduce complex spectral relationships to single values, limiting their utility in quality assurance. This study presents an evaluation of spectral comparison methodologies, contrasting classical Mahalanobis distance (MD) with neural network approaches, namely, neural classification distance (NCD). Using matrix assisted laser desorption ionization-time of flight (MALDI-TOF) mass spectrometry data from bacterial isolates, we systematically assessed these methods across varying levels of spectral variability. The MD approach exhibited consistent performance under controlled conditions but showed limitations with increasing spectral complexity. In contrast, the NCD demonstrated adaptability across all scenarios, revealing its capability in handling complex spectral relationships. Through this exemplary example, we present the mathematical framework for quantifying spectral variations and establish criteria for method selection in different analytical scenarios. This work provides a foundation for proposing data quality metrics in NTMs and offers practical implementations for routine quality assurance. The methodology developed here extends beyond mass spectrometry applications and contributes to the broader field of analytical quality control in complex spectral analysis.

bioinformatics↗

bioRxiv2024

Non-targeted screening method for detecting temporal shifts in spectral patterns of Methicillin Resistance Staphylococcus aureus and post-hoc description of peak features

Non-targeted methods (NTMs) using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) show promise in bacterial resistance detection, yet temporal variations in spectral features pose significant challenges. These proteomic patterns, which characterize bacterial phenotypes and pathological functions, may vary over time due to bacterial adaptation, virulence, or resistance mechanisms, resulting in large prediction uncertainties and potentially degrading NTM performance. We present a comprehensive screening method to detect temporal changes in MALDI-TOF spectral patterns, demonstrated using methicillin-resistant and -susceptible Staphylococcus aureus (MRSA/MSSA) isolates collected over several years. Our approach combines convolutional neural networks (CNN) with statistical methods, including significance testing, kernel density estimation, and receiver operating characteristics for dataset shift detection. We employ Gradient-weighted Class Activation Mapping (Gradcam) for post-hoc feature description, enabling biochemical characterization of temporal changes. This analysis reveals crucial insights into the dynamic relationship between spectral data patterns over time, addressing key challenges in developing robust NTMs for routine applications.

microbiology↗

bioRxiv2024

Insights into the nature of the microalgal toxins from the Chrysochromulina leadbeateri blooms in Northern Norwegian fjords

In May-June 2019, the microalga Chrysochromulina leadbeateri caused a massive fish-killing event in several fjords in Northern Norway, resulting in the largest direct impact ever on aquaculture in northern Europe due to toxic algae. Motivated by the fact that no algal toxins have previously been described from C. leadbeateri, we set out to investigate the chemical nature and toxicity of secondary metabolites in extracts of two strains (UIO 393, UIO 394) isolated from the 2019 bloom, as well as one older strain (UIO 035) isolated during a bloom in Northern Norway in 1991. Initial LC-DAD-MS/MS-based molecular networking analysis of the crude MeOH extracts of the cultivated strains showed that their profiles of small organic molecules, including a large number of known lipids, were very similar, suggesting that the same class of toxin(s) were likely the causative agents of the two harmful algal bloom (HAB) events. Next, bioassay-guided fractionation using the RTgill-W1 cell line and metabolomics analysis pointed to a major compound affording [M+H]+ ions at m/z 1399.8333 as a possible toxin, corresponding to a compound with the formula C67H127ClO27. Moreover, our study unveiled a series of minor analogues exhibiting distinct patterns of chlorination and sulfation, together defining a new family of compounds, which we propose to name leadbeaterins. Remarkably, these suspected toxins were detected in situ in samples collected during the 2019 bloom close to Tromso, thereby substantiating their likely role in fish kills. The elemental compositions of the putative C. leadbeateri ichthyotoxins strongly indicate them to be long linear polyhydroxylated polyketides, structurally similar to sterolysins, reported from a number of dinoflagellates.

ecology↗

bioRxiv2022

Secreted long non-coding RNAs Gadlor1 and Gadlor2 affect multiple cardiac cell types and aggravate cardiac remodeling during pressure overload

BackgroundPathological overload triggers maladaptive myocardial remodeling that leads to heart failure. Recent studies have shown that long non-coding RNAs (lncRNAs) regulate cardiac remodeling. This study investigates two recently discovered, secreted lncRNAs, Gadlor1 and Gadlor2 (Gadlor 1/2). MethodsWe generated compound Gadlor1/2 knock-out (KO) mice and compared their response to pressure overload by transverse aortic constriction (TAC) to that of wild-type (WT) littermates. Endothelial cells, fibroblasts and cardiomyocytes were isolated from the hearts of both genotypes after TAC and their transcriptome was investigated by RNA sequencing. Gadlor target proteins were identified by RNA antisense purification coupled with mass spectrometry (RAP-MS) in cardiomyocytes. In addition, we investigated the effects of cardiac overexpression of Gadlor1/2. ResultsGadlor1/2 are jointly upregulated in failing mouse hearts as well as in the myocardium of heart failure patients. Cardiac overexpression of Gadlor1 and Gadlor2 aggravated myocardial dysfunction and enhanced hypertrophic and fibrotic remodeling in mice exposed to pressure overload. Compound Gadlor1/2 KO mice, in turn, exerted markedly reduced myocardial hypertrophy, fibrosis and dysfunction, but more angiogenesis during short and long-standing pressure overload. Paradoxically, Gadlor1/2 KO mice suffered from sudden death during prolonged overload, possibly due to cardiac arrhythmia. Gadlor1 and Gadlor2, which are mainly expressed in endothelial cells (ECs) in the heart, where they inhibit pro-angiogenic gene-expression, are strongly secreted within extracellular vesicles (EVs). These EVs transfer Gadlor lncRNAs to cardiomyocytes, where they bind and activate calmodulin-dependent kinase II, induce pro-hypertrophic gene-expression and enhance calcium re-uptake into the sarcoplasmic reticulum. ConclusionGadlor1 and Gadlor2 are lncRNAs that are mainly enriched in EC-derived EVs and are jointly upregulated in mouse and human hearts during pathological overload. We reveal a crucial endothelial cell-cardiomyocyte crosstalk, which aims at restoring calcium homeostasis in cardiomyocytes during overload at the cost of aggravated hypertrophy and fibrosis.

systems biology↗

bioRxiv2021

Effects of Hydroxychloroquine and Azithromycin on iPSC-derived Cardiomyocytes: Considerations for the Treatment of COVID-19 Patients

Despite known adverse effects of hydroxychloroquine (HCQ) and azithromycin (AZM) on cardiac function, HCQ and AZM have been used as combination therapy in the treatment of COVID-19 patients. Recent clinical data indicate higher complication rates with HCQ/AZM combination treatment in comparison to monotherapy. Here, we used human induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) to systematically investigate the effects of HCQ and AZM individually and in combination. The clinically observed QT prolongation caused by treatment with HCQ could be recapitulated in iPSC-CMs based on prolonged field potential duration (FPDc). Interestingly, HCQ-induced FPDc prolongation was strongly enhanced by combined treatment with AZM, although AZM alone slightly shortened FPDc in iPSC-CMs. Furthermore, combined treatment with AZM and HCQ leads to higher cardiotoxicity, more severe structural disarrangement, and more pronounced contractile and electrophysiological dysfunctions, compared to respective mono-treatments. First mechanistic insights underlying the synergistic effects of AZM and HCQ on iPSC-CM functionality are provided based on increased Cx43- and Nav1.5-protein levels. Taken together, our results highlight that combined treatment with HCQ and AZM strongly enhances the adverse effects on cardiomyocytes, providing mechanistic evidence for the high mortality in patients receiving HCQ/AZM combination treatment.

pharmacology and toxicology↗

bioRxiv2021

Validation of binary non-targeted approaches: mathematical framework and experimental designs

Non-targeted methods (NTMs) are being increasingly developed and adopted to detect food fraud and identify the authenticity of the food. Method validation is a critical step before bringing the NTMs to the routine to be assured of method performance and trust that its outcomes are reliable. However, the paucity of well structured and harmonized validation strategies has been one of the hurdles, withholding the exploitation of NTMs. This report aims to describe a validation framework for methods that involve binary classification, which are prevalent in non-targeted workflows. We foresee this work to contribute to filling the current gap in the provisions for NTM method validation; perhaps also push the dialogue further to collectively resolve existing challenges.

bioinformatics↗

bioRxiv2020

AI-based identification of grain cultivars via non-target mass spectrometry

Detection of food fraud and geographical traceability of ingredients is a continually sought goal for government institutions, producers, and consumers. Herein we explore the use of non-target high-resolution mass spectrometry approaches and demonstrate its utility through a particularly challenging case study - to distinguish wheat and spelt cultivars. By employing a data-independent acquisition (DIA) approach for sample measurement, the spectra are of considerable size and complexity. We utilize artificial intelligence (AI) algorithms (artificial neural networks) to evaluate the extensive proteomic footprint of several wheat and spelt cultivars. The AI model thus obtained is used to classify newer varieties of spelt, processed flour, and bread samples. Additionally, we discuss the validation of such a method coupling DIA and AI approaches. The novel framework for method validation enables calculation of precision parameters for facile comparison of the discriminatory power of the method and in the development of a reliable decision rule.

bioinformatics↗