Biology subjects

Jansen, F.

Publications and source records attributed to Jansen, F..

9 recordsLinked to original sources

bioRxiv2025

Loss of characteristic species across German federal states detected by repeated mapping of protected habitats

Identifying the winners and losers of biodiversity change within different habitat types requires systematic monitoring. While such data are still lacking in Germany, species trends could be derived from previously untapped sources. Here, we derive temporal trends in plant species from data of repeated habitat mapping programs of three German states from 1977-2021, both across all habitat types per state and within habitat types. Consistently negative trends were found across all states for species preferring heaths and semi-natural grasslands, moist to wet grasslands, and coastal and marine habitats, including many endangered species. Consistently positive trends were found for species preferring scrubs, copses and field hedges, and for non-native species. Trends within habitat types showed negative trends for species characteristic of those habitat types. While trends varied among states, the overall patterns were very similar. This points to ongoing habitat degradation and common drivers of biodiversity change in Germany.

ecology↗

bioRxiv2022

Porcine and human aortic valve endothelial and interstitial cell isolation and characterization

BackgroundCalcific aortic valve stenosis is defined by pathological changes in the aortic valve and their predominant cell types: valvular interstitial (VICs) and endothelial cells (VECs). Understanding the cellular and molecular mechanisms of this disease is a prerequisite to identify potential pharmacological treatment strategies. In this study, we present a unique aortic valve cell isolation technique to acquire specific human and porcine cell populations and compared VICs and VECs of these species with each other for the first time. Methods and ResultsAortic valve cells were isolated from human explants from patients undergoing surgical aortic valve replacement or porcine valvular tissue. Pure VEC and VIC populations could be verified by gene expression analysis and immunofluorescence staining showing a highly significant upregulation of endothelial markers in VECs and mesenchymal markers in VICs, respectively. Further analysis and comparison of cells in in vitro experiments revealed that endothelial-to-mesenchymal transition could be induced in hVECs, leading to significant increase of mesenchymal markers. In vitro calcification experiments of VICs induced by osteogenic medium or pro-calcifying medium demonstrated a pronounced calcification marker expression and visible calcific deposition in Alizarin red staining in both species. ConclusionThis study aims to initiate a first step towards standardization of a reproducible isolation technique for pure human and porcine VEC and VIC populations. Comparison of human and porcine aortic valve cells demonstrated that porcine cells might serve as an alternative cellular model system, in settings, where human tissues are difficult to obtain. Statements and DeclarationsThe authors declare no relevant financial or non-financial interests to disclose.

cell biology↗

bioRxiv2022

Aortic valve disease augments vesicular microRNA-145-5p to regulate the calcification of valvular interstitial cells via cellular crosstalk

RationaleAortic valve stenosis (AVS) is a major contributor to cardiovascular death in the elderly population worldwide. MicroRNAs (miRNAs) are highly dysregulated in patients with AVS undergoing surgical aortic valve replacement (SAVR). However, miRNA-dependent mechanisms regulating inflammation and calcification or miRNA-mediated cell-cell crossstalk during the pathogenesis of AVS are still poorly understood. Here, we explored the role of extracellular vesicles (EV)-associated miR-145-5p, which we showed to be highly upregulated upon valvular calcification in AVS in mice and humans. MethodsHuman TaqMan miRNA arrays identified dysregulated miRNAs in aortic valve tissue explants from AVS patients compared to non-calcified valvular tissue explants of patients undergoing SAVR. Echocardiographic parameters were measured in association with the quantification of dysregulated miRNAs in a murine AVS model. In vitro calcification experiments were performed to explore the effects of EV-miR-145-5p on calcification and crosstalk in valvular cells. To dissect molecular miRNA signatures and their effect on signaling pathways, integrated OMICS analyses were performed. RNA sequencing (RNA-seq), high-throughput transcription factor (TF) and proteome arrays showed that a number of genes, miRNAs, TFs, and proteins are crucial for calcification and apoptosis, which are involved in the pathogenesis of AVS. ResultsAmong several miRNAs dysregulated in valve explants of AVS patients, miR-145-5p was the most highly gender-independently dysregulated miRNA (AUC, 0.780, p-value, 0.01). MiRNA arrays utilizing patient-derived- and murine aortic-stenosis samples demonstrated that the expression of miR-145-5p is significantly upregulated and correlates positively with cardiac function based on echocardiography. In vitro experiments confirmed that miR-145-5p is encapsulated into EVs and shuttled into valvular interstitial cells. Based on the integrated OMICs results, miR-145-5p interrelates with markers of inflammation, calcification, and apoptosis. In vitro calcification experiments demonstrated that miR-145-5p regulates the ALPL gene, a hallmark of calcification in vascular and valvular cells. EV-mediated shuttling of miR-145-5p suppressed the expression of ZEB2, a negative regulator of the ALPL gene, by binding to its 3 untranslated region to inhibit its translation, thereby diminishing the calcification of target valvular interstitial cells. ConclusionElevated levels of pro-calcific and pro-apoptotic EV-associated miR-145-5p contribute to the progression of AVS via the ZEB2-ALPL axis, which could potentially be therapeutically targeted to minimize the burden of AVS. Clinical SignificanceO_ST_ABSWhat is known?C_ST_ABSO_LIAortic valve stenosis (AVS) is the most prevalent structural heart valve disease requiring surgical or interventional valve replacement. Currently, no medical treatment option is available to slow, halt, or reverse the progression of the disease. C_LIO_LIAVS induces pressure overload on the left ventricle (LV), resulting in concentric hypertrophy and LV dysfunction. C_LIO_LIAVS is not an exclusively degenerative disease that leads to fibrosis and calcification of the valve cusps but rather a chronic inflammatory disease, in which mechanical strain and shear stress lead to endothelial dysfunction and immune cell infiltration, which induces chronic inflammation, apoptosis and differentiation of valvular interstitial cells into osteoblast-like cells. C_LIO_LIIncreasing osteoblastic differentiation and the formation of macrocalcifications are hallmarks of the later stages of AVS. C_LI What is the new information we provide?O_LIDuring aortic valve stenosis, expression pattern of vesicle-associated regulatory miRNAs is altered. C_LIO_LIPatient-derived aortic valve tissue demonstrated an increased expression of miR-145-5p in humans, as well as in aortic valve explants from an experimental murine AVS model. C_LIO_LIMiR145-5p contributes to calcification of the aortic valve through ZEB2, a transcriptional repressor of ALPL, in valvular interstitial cells. C_LIO_LIExtracellular vesicular shuttling of miR-145-5p contributes to valvular cell-cell crosstalk and plays a role in the pathogenesis of AVS. C_LI

cell biology↗

bioRxiv2022

Interactive analysis of single-cell data using flexible workflows with SCTK2.0

Analysis of single-cell RNA-seq (scRNA-seq) data can reveal novel insights into heterogeneity of complex biological systems. Many tools and workflows have been developed to perform different types of analysis. However, these tools are spread across different packages or programming environments, rely on different underlying data structures, and can only be utilized by people with knowledge of programming languages. In the Single Cell Toolkit 2.0 (SCTK2.0), we have integrated a variety of popular tools and workflows to perform various aspects of scRNA-seq analysis. All tools and workflows can be run in the R console or using an intuitive graphical user interface built with R/Shiny. HTML reports generated with Rmarkdown can be used to document and recapitulate individual steps or entire analysis workflows. We show that the toolkit offers more features when compared with existing tools and allows for a seamless analysis of scRNA-seq data for non-computational users. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=112 SRC="FIGDIR/small/499900v1_ufig1.gif" ALT="Figure 1"> View larger version (49K): org.highwire.dtl.DTLVardef@2a3964org.highwire.dtl.DTLVardef@1debe9org.highwire.dtl.DTLVardef@6b3a2aorg.highwire.dtl.DTLVardef@1b7bf84_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIIntuitive graphical user interface for interactive analysis of scRNA-seq data C_LIO_LIAllows non-computational users to analyze scRNA-seq data with end-to-end workflows C_LIO_LIProvides interoperability between tools across different programming environments C_LIO_LIProduces HTML reports for reproducibility and easy sharing of results C_LI

bioinformatics↗

bioRxiv2022

ReSurveyGermany: Vegetation-plot time-series over the past hundred years in Germany

Vegetation-plot resurvey data are a main source of information on terrestrial biodiversity change, with records reaching back more than one century. Although more and more data from re-sampled plots have been published, there is not yet a comprehensive open-access dataset available for analysis. Here, we compiled and harmonised vegetation-plot resurvey data from Germany covering almost 100 years. We show the distribution of the plot data in space, time and across habitat types of the European Nature Information System (EUNIS). In addition, we include metadata on geographic location, plot size and vegetation structure. The data allow calculating temporal biodiversity change at the community scale and reach back further into the past than most comparable data yet available. They also enable tracking changes in the incidence and distribution of individual species across Germany. In summary, the data come at a level of detail that holds promise for broadening our understanding of the mechanisms and drivers behind plant diversity change over the last century.

ecology↗

bioRxiv2020

Comprehensive generation, visualization, and reporting of quality control metrics for single-cell RNA sequencing data

Single-cell RNA sequencing (scRNA-seq) can be used to gain insights into cellular heterogeneity within complex tissues. However, a variety of technical artifacts can be present in scRNA-seq data and need to be assessed before downstream analyses can be performed. While several algorithms and tools have been developed to perform individual quality control (QC) tasks, they are scattered in different packages across several programming environments. Comprehensive pipelines to streamline the process of generating and visualizing QC metrics are lacking. To address this need, we built the SCTK-QC pipeline within the singleCellTK R package (https://github.com/compbiomed/singleCellTK). Features in this pipeline include the ability to import data from 11 different preprocessing tools or file formats, perform empty droplet detection with 2 different algorithms, generate standard quality control metrics such as number of UMIs per cell or the percentage of mitochondrial counts, predict doublets using 6 different algorithms, and estimate ambient RNA. QC data can be exported to R and/or Python objects used in popular down-stream workflows. Results are visualized in an easy-to-read HTML report. This pipeline can also be used by non-computational users with an interactive graphical user interface developed with R/Shiny. Overall, the SCTK-QC pipeline will streamline and standardize QC analysis for scRNA-seq data across a variety of different single-cell transcriptomic platforms and preprocessing tools.

bioinformatics↗

bioRxiv2020

Widespread decline in plant diversity across six decades

Based on plant occurrence data covering all parts of Germany, we investigated changes in the distribution of 2146 plant species between 1960 and 2017. We analyzed 29 million occurrence records over an area of [~]350.000 km2 on a 5 x 5 km grid using temporal and spatio-temporal models and accounting for sampling bias. Since the 1960s, more than 70% of investigated plant species showed significant declines in nation-wide occurrence. Archaeophytes (species introduced before 1492) most strongly declined but also native plant species experienced severe declines. In contrast, neophytes (species introduced after 1492) increased in their nation-wide occurrence but not homogeneously throughout the country. Our analysis suggests that the strongest declines in native species already happened in the 1960s-80s, a time frame in which usually few data exist. Increases in neophytic species were strongest in the 1990s and 2010s. Overall, the increase in neophytes did not compensate for the loss of other species, resulting in a decrease in mean grid-cell species-richness of -1.9% per decade. The decline in plant biodiversity is a widespread phenomenon occurring in different habitats and geographic regions. It is likely that this decline has major repercussions on ecosystem functioning and overall biodiversity, potentially with cascading effects across trophic levels. The approach used in this study is transferable to large-scale trend analyses using heterogeneous occurrence data.

ecology↗

bioRxiv2020

Winners and losers over 35 years of dragonfly and damselfly distributional change in Germany

Recent studies suggest insect declines in parts of Europe; however, the generality of these trends across different taxa and regions remains unclear. Standardized data are not available to assess large-scale, long-term changes for most insect groups but opportunistic citizen science data is widespread for some taxa. We compiled over 1 million occurrence records of Odonata (dragonflies and damselflies) from different regional databases across Germany. We used occupancy-detection models to estimate annual distributional changes between 1980 and 2016 for each species. We related species attributes to changes in the species distributions and inferred possible drivers of change. Species showing increases were generally warm-adapted species and/or running water species while species showing decreases were cold-adapted species using standing water habitats such as bogs. We developed a novel approach using time-series clustering to identify groups of species with similar patterns of temporal change. Using this method, we defined five typical patterns of change for Odonata - each associated with a specific combination of species attributes. Overall, trends in Odonata provide mixed news - improved water quality, coupled with positive impacts of climate change, could explain the positive trend status of many species. At the same time, declining species point to conservation challenges associated with habitat loss and degradation. Our study demonstrates the great value of citizen science data for assessing large-scale distributional change and conservation decision-making.

ecology↗

bioRxiv2019

Genetic correlation between background EEG oscillations and genetic generalized epilepsy

ObjectiveParoxysmal epileptiform abnormalities on electroencephalography (EEG) are the hallmark of epilepsies, but it is uncertain to what extent epilepsy and background EEG oscillations share neurobiological underpinnings. Here, we aimed to assess the genetic correlation between epilepsy and background EEG oscillations. MethodsConfounding factors, including the heterogeneous etiology of epilepsies and medication effects hamper studies on background brain activity in people with epilepsy. To overcome this limitation, we compared genetic data from a GWAS on epilepsy (n=12,803 people with epilepsy and 24,218 controls) with that from a GWAS on background EEG (n=8,425 subjects without epilepsy), in which background EEG oscillation power was quantified in four different frequency bands: alpha, beta, delta and theta. We replicated our findings in an independent epilepsy replication dataset (n=4851 people with epilepsy and 20,428 controls). To assess the genetic overlap between these phenotypes, we performed genetic correlation analyses using linkage disequilibrium score regression, polygenic risk scores and Mendelian randomization analyses. ResultsOur analyses show strong genetic correlations between genetic generalized epilepsy (GGE) with background EEG oscillations, primarily with the beta frequency band. Furthermore, we show that subjects with higher beta and theta polygenic risk scores have a significantly higher risk of having generalized epilepsy. Mendelian randomization analyses suggest a causal effect of GGE genetic liability on beta oscillations. SignificanceOur results point to shared biological mechanisms underlying background EEG oscillations and the susceptibility for GGE, opening avenues to investigate the clinical utility of background EEG oscillations in the diagnostic work-up of epilepsy.

genetics↗