Biology subjects

Barth, E.

Publications and source records attributed to Barth, E..

13 recordsLinked to original sources

bioRxiv2026

Host-derived lipids license proliferation of sterol-auxotrophic tick cells and promote flavivirus output

Sterol molecules play indispensable roles in the biology of cells and organisms. Yet, arthropods, including ticks, lack the capacity for de novo sterol biosynthesis and must rely on exogenous sources. How these organisms sense and utilise exogenous lipids at the cellular level remains poorly understood. Here, we show that host cholesterol and linoleic acid act as essential external signals that license proliferation of Ixodes ricinus tick cells. In lipid-depleted conditions, cells fail to proliferate despite retaining intracellular cholesterol, indicating that exogenous lipids function as regulatory cues rather than merely structural components. We further demonstrate that tick cells exhibit a non-canonical intracellular distribution of cholesterol, with predominant accumulation in lysosome-associated compartments, and that lipid availability induces a coordinated transcriptional program involving lipid uptake and trafficking machinery. Importantly, we find that limiting host lipid availability significantly reduces extracellular RNA output of tick-borne encephalitis virus (TBEV) from infected tick cells, indicating that viral production is affected by the metabolic state of the host cell. Together, our findings establish host-derived lipids as key regulators of cellular state in a sterol-auxotrophic organism and identify lipid availability as a determinant of flavivirus output. This work provides a conceptual framework linking nutrient sensing, cell proliferation, and vector-pathogen interactions.

microbiology↗

bioRxiv2025

diffONT: predicting methylation-specific PCR biomarkers based on nanopore sequencing data for clinical application

DNA methylation is known to act as biomarker applicable for clinical diagnostics, especially in cancer detection. Methylation-specific PCR (MSP) is a widely used approach to screen patient samples fast and efficiently for differential methylation. During MSP, methylated regions are selectively amplified with specific primers. With nanopore sequencing, knowledge about DNA methylation is generated during direct DNA sequencing, without any need for pretreatment of the DNA. Multiple methods, mainly developed for whole-genome bisulfite sequencing (WGBS) data, exist to predict differentially methylated regions (DMRs) in the genome. However, the predicted DMRs are often very large, and not sufficiently discriminating to generate meaningful results in MSP creating a gap between theoretical cancer marker research and practical application, as no tool currently provides methylation difference predictions tailored for PCR-based diagnostics. Here we present diffONT, which predicts differentially methylated primer regions, directly suitable for MSP primer design and thus allowing a direct translation into practical approaches. diffONT takes into account (i) the specific length of primer and amplicon regions, (ii) the fact that one condition should be unmethylated, and (iii) a minimal required amount of differentially methylated cytosines within the primer regions. Based on two nanopore sequencing data sets we compared the results of diffONT to metilene, DSS and pycoMeth. We show that the regions predicted by diffONT are more specific towards hypermethylated regions and more usable for MSP. diffONT accelerates the design of methylation-specific diagnostic assays, bridging the gap between theoretical research and clinical application.

bioinformatics↗

bioRxiv2024

Pathogenesis of mtDNA point mutation m.10191T>C affecting complex I function is a multifactorial process leading to metabolic remodeling of mitochondria

Inherited mitochondrial disorders are of multiple genetic origins and may lead to a broad range of frequently severe disease phenotypes. Yet, the correlation between molecular causes and clinical presentations is poorly understood. To address this conundrum, we thoroughly investigated the consequences of the well-known pathogenic mitochondrial DNA mutation m.10191T>C. The mutation changes serine-45 in subunit ND3 of respiratory chain complex I to proline and causes Leigh syndrome, which is one of the most devastating mitochondrial diseases. Human mitochondria carrying the mutation ND3S45P retained 30-40% of complex I activity and oxidative phosphorylation capacity. In stark contrast, intact mutant cells exhibited only minimal oxygen consumption and a massively increased NADH/NAD+ ratio. Since the energy barrier for the Active/Deactive transition of complex I was reduced by [~]20 kJ{middle dot}mol-1 in mutant cells, we concluded that complex I was shut-off by malfunctioning of an as yet unknown regulatory pathway. Comprehensive analysis of the mitochondrial complexome of cybrids, patient fibroblasts and muscle biopsies rendered other causes for the accumulation of NADH unlikely. The complexome datasets provide a rich resource for further studies to discover possible additional factors involved in regulating complex I. We propose that the derailed regulation of complex I is the main culprit leading to NADH accumulation and eventually the severity of the disease phenotype caused by mutation ND3S45P.

biochemistry↗

bioRxiv2024

Algal growth and morphogenesis-promoting factors released by cold-adapted bacteria contribute to the resilience and morphogenesis of the seaweed Ulva (Chlorophyta) in Antarctica (Potter Cove)

Macroalgae are found in a variety of marine vegetation ecosystems around the world, contributing significantly to global net primary production. In particular, the sea lettuce species, i.e., members of the genus Ulva (Chlorophyta), are located in many ecological niches and are characterized by excellent adaptability to environmental changes but depend on essential associated bacteria, which release algal growth and morphogenesis-promoting-factors (AGMPFs). Our work investigated the hypothesis that bacteria need to be stress-adapted to provide sufficient amounts of AGMPFs for the growth and morphogenesis of Ulva throughout its life cycle, even under severe environmental conditions. Our study thus aimed to understand which bacteria contribute to overcoming a variety of stressors in polar regions. Green macroalgae were collected from Potter Cove, King George Island (Isla 25 de Mayo), Antarctica, to study the associated microbiome and, subsequently, to identify AGMPFs releasing bacteria. Therefore, microbiome analysis was combined with morphogenetic bioassays and chemical analysis, identifying bacteria essential for algal growth under Antarctic conditions. Hereby, axenic cultures of a Mediterranean Ulva compressa (cultivar Ulva mutabilis), previously developed as a model system for bacteria-induced algal growth and morphogenesis, were inoculated with freshly isolated and cultivable Antarctic bacteria to determine their morphogenetic activity. The exploratory microbiome investigation identified numerous cold-adapted AGMPF-producing bacteria. Unlike the reference bacterial strains isolated from the Mediterranean Sea, the cold-adapted isolates Maribacter sp. BPC-D8 and Sulfitobacter sp. BPC-C4, released sufficient amounts of AGMPFs, such as thallusin, necessary for algal morphogenesis even at 2{degrees}C. Our results illustrate the role of chemical mediators provided by bacteria in cross-kingdom interactions under cold conditions within aquatic systems. The newly isolated bacteria will enable further functional studies to understand the resilience of the holobiont Ulva and might applied in algal aquaculture even under adverse conditions. The study highlights the importance of ecophysiological assays in microbiome analysis.

plant biology↗

bioRxiv2023

Analysis of Metabolomics and Transcriptomics Data to Assess Interactions in Microalgal Co-culture of Skeletonema marinoi and Prymnesium parvum

In marine ecosystems, microbial communities often interact using specialised metabolites, which play a central role in shaping the dynamics of the ecological networks and maintaining the balance of the ecosystem. With metabolomics and transcriptomics analyses, this study explores the interactions between two marine microalgae, Skeletonema marinoi and Prymnesium parvum, grown in mono-cultures and non-contact co-cultures. As a growth indicator, the photosynthetic potential, measured via fluorescence, suggested chemical interaction between S. marinoi and P. parvum. Using Liquid Chromatography-Mass Spectrometry (LC-MS) data, we identified 346 and 521 differentially produced features in the endo- and exometabolome of S. marinoi and P. parvum, respectively. Despite limited tandem mass spectrometry data (MS2) for these features, we structurally annotated 14 compounds, most of which were previously under-studied specialised metabolites. Differential gene expression analysis was then performed on the transcriptomes of the microalgae, which uncovered differentially expressed genes involved in energy metabolism and cellular repair for both species. These metabolic and transcriptomics changes depict the adaptation of both species in the co-culture. However, further data acquisition and investigation will be necessary to confirm the type of interaction and the underlying mechanisms. ImportanceMarine microalgae have great ecological importance and biochemical potential. Among these microbes are the diatom Skeletonema marinoi, known for its marine biogeochemical cycling, and the haptophyte Prymnesium parvum, which poses adverse environmental consequences. Given these opposing roles for the two cosmopolitan microalgae, we designed a study using untargeted metabolomics and transcriptomics to acquire a comprehensive snapshot of their interactions, grown as mono-cultures and co-cultures. The statistical analysis of the chlorophyll a fluorescence levels, and the metabolomics and transcriptomics dataset revealed metabolic communication occurring among the two species via specialised metabolites and activated cellular repair mechanisms. These findings reveal the complexity of the interactions within marine microbial ecosystems, offering a foundation for future research to understand and harness marine ecological systems.

microbiology↗

bioRxiv2023

CLUH maintains functional mitochondria and translation in motoneuronal axons and prevents peripheral neuropathy

Transport and local translation of mRNAs in distal axonal compartments are essential for neuronal viability. Local synthesis of nuclear-encoded mitochondrial proteins protects mitochondria from damage during their long journey along the axon, however the regulatory factors involved are largely unknown. Here, we show that CLUH, a cytosolic protein that binds mRNAs encoding mitochondrial proteins, is essential for preventing axonal degeneration of spinal motoneurons and maintaining motor behavior in the mouse. We demonstrate that CLUH is enriched in the growth cone of developing spinal motoneurons and is required for their growth. The absence of CLUH affects the abundance of target mRNAs and the corresponding mitochondrial proteins more prominently in axons, leading to ATP deficits specifically in the growth cone. CLUH binds ribosomal subunits, translation initiation and ribosome recycling components, and preserves axonal translation. Overexpression of the ribosome recycling factor ABCE1 rescues the growth cone and translation defects in CLUH-deficient motoneurons. In conclusion, we demonstrate a role for CLUH in mitochondrial quality control and translational regulation in axons, which are essential for their development and long-term integrity and function.

cell biology↗

bioRxiv2021

CLUH controls astrin-1 expression to couple mitochondrial metabolism to cell cycle progression

Proliferating cells undergo metabolic changes in synchrony with cell cycle progression and cell division. Mitochondria provide fuel, metabolites, and ATP during different phases of the cell cycle, however it is not completely understood how mitochondrial function and the cell cycle are coordinated. CLUH is a post-transcriptional regulator of mRNAs encoding mitochondrial proteins involved in oxidative phosphorylation and several metabolic pathways. Here, we show a role of CLUH in regulating the expression of astrin, which is involved in metaphase to anaphase progression, centrosome integrity, and mTORC1 inhibition. We find that CLUH binds both the SPAG5 mRNA and its product astrin, and controls the synthesis and the stability of the full-length astrin-1 isoform. We show that CLUH interacts with astrin-1 specifically during interphase. Astrin-depleted cells show mTORC1 hyperactivation and enhanced anabolism. On the other hand, cells lacking CLUH show decreased astrin levels and increased mTORC1 signaling, but cannot sustain anaplerotic and anabolic pathways. In absence of CLUH, cells fail to grow during G1, and progress faster through the cell cycle, indicating dysregulated matching of growth, metabolism and cell cycling. Our data reveal a role of CLUH in coupling growth signaling pathways and mitochondrial metabolism with cell cycle progression.

cell biology↗

bioRxiv2020

EpiDope: A Deep neural network for linear B-cell epitope prediction

By binding to specific structures on antigenic proteins, the so-called epitopes, B-cell antibodies can neutralize pathogens. The identification of B-cell epitopes is of great value for the development of specific serodiagnostic assays and the optimization of medical therapy. However, identifying diagnostically or therapeutically relevant epitopes is a challenging task that usually involves extensive laboratory work. In this study, we show that the time, cost and labor-intensive process of epitope detection in the lab can be significantly shortened by using in silico prediction. Here we present EpiDope, a python tool which uses a deep neural network to detect B-cell epitope regions on individual protein sequences (github.com/mcollatz/EpiDope). With an area under the curve (AUC) between 0.67 {+/-} 0.07 in the ROC curve, EpiDope exceeds all other currently used B-cell prediction tools. Moreover, for AUC10% (AUC for a false-positive rate < 0.1), EpiDope improves the prediction accuracy in comparison to other state-of-the-art methods. Our software is shown to reliably predict linear B-cell epitopes of a given protein sequence, thus contributing to a significant reduction of laboratory experiments and costs required for the conventional approach.

bioinformatics↗

bioRxiv2019

Viral host prediction with Deep Learning

MotivationZoonosis, the natural transmission of infections from animals to humans, is a far-reaching global problem. The recent outbreaks of Zika virus, Ebola virus and Corona virus are examples of viral zoonosis, which occur more frequently due to globalization. In the case of a virus outbreak, it is helpful to know which host organism was the original carrier of the virus. Once the reservoir or intermediate host is known, it can be isolated to prevent further spreading of the viral infection. Recent approaches aim to predict a viral host based on the viral genome, often in combination with the potential host genome and arbitrarily selected features. These methods have a clear limitation in either the number of different hosts they can predict or the accuracy of their prediction. ResultsHere, we present a fast and accurate deep learning approach for viral host prediction, which is based on the viral genome sequence only. To ensure a high prediction accuracy, we developed an effective selection approach for the training data to avoid biases due to a highly unbalanced number of known sequences per virus-host combinations. We tested our deep neural network on three different virus species (influenza A, rabies lyssavirus, rotavirus A). We reached for each virus species an AUG between 0.93 and 0.98, outperforming previous approaches and allowing highly accurate predictions while only using fractions (100-400 bp) of the viral genome sequences. We show that deep neural networks are suitable to predict the host of a virus, even with a limited amount of sequences and highly unbalanced available data. The deep neural networks trained for this approach build the core of the virus-host predicting tool VIDHOP (Virus Deep learning HOst Prediction). AvailabilityThe trained models for the prediction of the host for the viruses influenza A, rabies lyssavirus, rotavirus A are implemented in the tool VIDHOP. This tool is freely available under https://github.com/flomock/vidhop. Supplementary informationSupplementary data are available at DOI 10.17605/OSF.IO/UXT7N

bioinformatics↗

bioRxiv2019

The landscape of the alternatively spliced transcriptome remains stable during aging across different species and tissues

Aging is characterized by a decline of cellular homeostasis over time, leading to various severe disorders and death. Alternative splicing is an important regulatory level of gene expression and thus takes on a key role in the maintenance of accurate cell and tissue function. Missplicing of certain genes has already been linked to several age-associated diseases, such as progeria, Alzheimers disease, Parkinsons disease and cancer. Nevertheless, many studies focus only on transcriptional variations of single genes or the expression changes of spliceosomal genes, coding for the proteins that aggregate to the spliceosomal machinery. Little is known on the general change of present and switching isoforms in different tissues over time. In this descriptive RNA-Seq study, we report differences and commonalities of isoform usage during aging among different tissues within one species and compare changes of alternative splicing among different, evolutionarily distinct species. Although we identified a multitude of differntially spliced genes among different time points, we observed little to no general changes in the transcriptomic landscape of the investigated samples. Although there is undoubtedly considerable influence of specifically spliced genes on certain age-associated processes, this work shows that alternative splicing remains stable for the majority of genes with aging.

bioinformatics↗

bioRxiv2018

Identification of potential microRNAs associated with Herpesvirus family based on bioinformatic analysis

MicroRNAs (miRNAs) are known key regulators of gene expression on posttranscriptional level in many organisms encoded in mammals, plants and also several viral families. To date, no homologous gene of a virus-originated miRNA is known in other organisms. To date, only a few homologous miRNA between two different viruses are known, however, no gene of a virus-originated miRNA is known in any organism of other kingdoms. This can be attributed to the fact that classical miRNA detection approaches such as homology-based predictions fail at viruses due to their highly diverse genomes and their high mutation rate.\n\nHere, we applied the virus-derived precursor miRNA (pre-miRNA) prediction pipeline ViMiFi, which combines information about sequence conservation and machine learning-based approaches, on Human Herpesvirus 7 (HHV7) and Epstein-Barr virus (EBV). ViMiFi was able to predict 61 candidates in EBV, which has 25 known pre-miRNAs. From these 25, ViMiFi identified 20. It was further able to predict 18 candidates in the HHV7 genome, in which no miRNA had been described yet. We also studied the undescribed candidates of both viruses for potential functions and found similarities with human snRNAs and miRNAs from mammals and plants.

bioinformatics↗

bioRxiv2018

Identification of miRNAs and associated pathways regulated by Leukemia Inhibitory Factor in trophoblastic cell lines

IntroductionLeukemia Inhibitory Factor (LIF) regulates behavior of trophoblast cells and their interaction with immune and endothelial cells. In vitro, trophoblast cell response to LIF may vary depending on the cell model. Reported differences in the miRNA profile of trophoblastic cells may be responsible for these observations. Therefore, miRNA expression was investigated in four trophoblastic cell lines under LIF stimulation followed by in silico analysis of altered miRNAs and their associated pathways.\n\nMethodsLow density TaqMan miRNA assays were used to quantify levels of 762 mature miRNAs under LIF stimulation in three choriocarcinoma-derived (JEG-3, ACH-3P and AC1-M59) and a trophoblast immortalized (HTR-8/SVneo) cell lines. Expression of selected miRNAs was confirmed in primary trophoblast cells and cell lines by qPCR. Targets and associated pathways of the differentially expressed miRNAs were inferred from the miRTarBase followed by a KEGG Pathway Enrichment Analysis. HTR-8/SVneo and JEG-3 cells were transfected with miR-21-mimics and expression of miR-21 targets was assessed by qPCR.\n\nResultsA similar number of miRNAs changed in each tested cell line upon LIF stimulation, however, low coincidence of individual miRNA species was observed and occurred more often among choriocarcinoma-derived cells (complete data set at http://www.ncbi.nlm.nih.gov/geo/ under GEO accession number GSE130489). Altered miRNAs were categorized into pathways involved in human diseases, cellular processes and signal transduction. Six cascades were identified as significantly enriched, including JAK/STAT and TGFB-SMAD. Upregulation of miR-21-3p was validated in all cell lines and primary cells and STAT3 was confirmed as its target.\n\nDiscussionDissimilar miRNA responses may be involved in differences of LIF effects on trophoblastic cell lines.

molecular biology↗

bioRxiv2017

A miRNA catalogue and ncRNA annotation of theshort-living fish Nothobranchius furzeri

Background: The short-lived fish Nothobranchius furzeri is the shortest-lived vertebrate that can be cultured in captivity and was recently established as a model organism for aging research. Small non-coding RNAs, especially miRNAs, are implicated in age-dependent control of gene expression.\n\nResults: Here, we present a comprehensive catalogue of miRNAs and several other non-coding RNA classes (ncRNAs) for Nothobranchius furzeri. Analyzing multiple small RNA-Seq libraries, we show most of these identified miRNAs are expressed in at least one of seven Nothobranchius species. Additionally, duplication and clustering of N. furzeri miRNAs was analyzed and compared to the four fish species Danio rerio, Oryzias latipes, Gasterosteus aculeatus and Takifugu rubripes. A peculiar characteristic of N. furzeri as compared to other teleosts was a duplication of the miR-29 cluster.\n\nConclusion: The completeness of the catalogue we provide is comparable to that of zebrafish. This catalogue represents a basis to investigate the role of miRNAs in aging and development in this species.\n\nAvailability: All supplementary material can be found online at http://www.rna.uni-jena.de/en/supplements/nothobranchius-furzeri-mirnome/.

genomics↗