Biology subjects

David, R.

Publications and source records attributed to David, R..

15 recordsLinked to original sources

bioRxiv2026

An integrative cardio-informatics approach identifies positionally conserved ancestors of human lncRNA genes transcribed across vertebrate hearts

The poor conservation of lncRNA genes limits their comprehensive functional studies, as genetic engineering of relevant animal models presupposes the presence of corresponding defined orthologs. This limitation is prominently evident in cardiovascular research, where heart-related lncRNAs are rarely conserved between humans and other vertebrates, despite the highly conserved nature of cardiac function. Because lncRNAs frequently regulate neighboring protein-coding genes essential for cardomyocyte function (herein termed cardiomyocyte indispensable, CMIs), we hypothesized that they are under evolutionary pressure to retain their genomic position and transcriptional activity, irrespective of sequence similarities to prototypical human lncRNA genes. By integrating mouse cardiac knockout phenotypes with human single-cell transcriptomics data, we systematically identified heart-expressed CMIs and their neighboring. lncRNA genes. Cross-species synteny analyses revealed regions flanking 109 CMIs with conserved relative positions and transcriptional orientations across vertebrate genomes. As most of these loci reside within poorly annotated non-coding regions, we developed VertLncRNAchecker, a neural network-based web interface, that predicts lncRNA-like genes within these regions, which we termed positional ancestors. Finally, we validated in situ that these positional ancestors express mature lncRNA transcripts in the hearts of mice, pigs, and frogs, mirroring the expression of their human lncRNA counterparts. We present an accurate and retrainable computational platform for cross-species lncRNA discovery that prioritizes conserved genomic position over sequence conservation or existing genome annotations. This pipeline revealed putative ancestors of human heart-related lncRNAs hidden within the vertebrate non-coding dark genome, providing novel insights into lncRNA biology and evolution.

evolutionary biology↗

bioRxiv2026

Multi-Modal Toxicological Evaluation of NiO nanoparticles and ionic nickel in a Human Lung-Cardiac Co-Culture System

Nickel is a widespread environmental and occupational contaminant associated with respiratory and cardiovascular toxicity, yet the mechanisms linking pulmonary exposure to adverse cardiac effects remain poorly understood. This study aimed to establish and evaluate a human in vitro lung-heart co-culture model for investigating cardiovascular responses following pulmonary exposure. Human alveolar epithelial A549 cells were exposed at the air-liquid interface to different concentrations of NiO nanoparticles or NiCl2 for 4- and 24-hours. Following cloud exposure, A549 cells were co-cultured with human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs). Cytotoxicity, metabolic activity, cytokine release, DNA damage, epigenetic alterations, and cardiac electrophysiological function were assessed. Nickel translocation across the epithelial barrier was quantified to facilitate interpretation of downstream cardiomyocyte effects. Exposure to both nickel forms induced cytotoxicity and resulted in measurable nickel translocation into the basolateral compartment. NiCl2 exhibited a time-dependent increase in basolateral nickel concentrations, whereas NiO translocation remained relatively stable over time. Cytokine profiling revealed selective induction of IL-8 and IL-18, with no significant changes in IL-1{beta}, IL-6, IL-10, or TNF-. Genotoxicity analyses demonstrated cell type-specific responses, characterized by delayed DNA strand breaks in A549 cells and early but transient DNA damage in hiPSC-CMs. Oxidative DNA damage was particularly pronounced in hiPSC-CMs following NiCl2 exposure. Global DNA methylation was reduced in hiPSC-CMs without corresponding changes in DNA methyltransferase activity. Electrophysiological assessment showed transient increases in conduction velocity, while beating frequency and field potential duration remained largely unaffected. Overall, the lung-heart co-culture model successfully captured both pulmonary and cardiac responses to nickel exposure and provided evidence for direct and indirect mechanisms of cardiotoxicity. Nickel translocation across the epithelial barrier, together with inflammatory and oxidative stress-related signalling, may contribute to downstream cardiac effects. These findings highlight the utility of this human-relevant platform for investigating systemic cardiovascular consequences of inhaled toxicants.

pharmacology and toxicology↗

bioRxiv2026

Programmatic access to ICTV virus taxonomy through a public ontology API

The International Committee on Taxonomy of Viruses (ICTV) is responsible for developing and maintaining a universal virus taxonomy. As the reference framework for organising the viral world, it is essential for virology and related fields. Despite its widespread use in research and public health, programmatic access to ICTV taxonomy has remained limited, posing challenges for integration, versioning, and interoperability across databases and bioinformatics resources requiring up-to-date virus taxonomy. To address this, we developed a public and sustainable solution leveraging ontology-based APIs. Successive ICTV Master Species List (MSL) releases were transformed into a structured ontology and deployed as a unified representation through the Ontology Lookup Service (OLS). The framework also provides ICTV-NCBI mappings and helper libraries for integration into downstream systems. This enables, for the first time, public programmatic retrieval of current and historical virological taxon names, taxonomic relationships, metadata, and persistent identifiers through stable endpoints. More broadly, this work illustrates a general strategy for transforming structured biological datasets into semantically enriched graph resources exposed through scalable public APIs. These developments enhance interoperability, reduce manual curation, and support FAIR-aligned taxonomic data management in virology and pandemic preparedness. Key pointsO_LIICTV provides the official taxonomy for classifying viruses and naming virus taxa, but lacks standardised programmatic access. C_LIO_LITransforming ICTV data into an ontology enables semantic, machine-actionable access across releases via ontology-based APIs. C_LIO_LIICTV-NCBI mappings support interoperability across bioinformatics resources. C_LIO_LIThe framework enables programmatic resolution of current and historical viral taxa. C_LIO_LIThis approach provides a reusable model for exposing biological datasets through public APIs. C_LI

bioinformatics↗

bioRxiv2024

Automated Analysis of Bird Head Motion from Videos in Unconstrained Settings

This study introduces a framework applicable to videos of habitual behaviors of multiple bird species to automatically assess head angular velocities and frequencies during various behaviors in natural habitats. The process involves detecting birds, identifying key points on their heads, and tracking changes in their positions over time. Bird detection and key point extraction were trained on publicly available datasets, including Animal Kingdom, NABirds, Birdsnap, CUB-200-2011, and eBird, featuring videos and images of diverse bird species in uncontrolled settings. Initial challenges arose due to the complexity of video backgrounds, leading to misidentifications and inaccurate key point estimates. These issues were addressed through validation, refinement, filtering, and smoothing steps. Head angular velocities and rotation frequencies were computed from the refined key points. The algorithm performed well at moderate speeds but was limited by the 30 Hz frame rate of most eBird videos, which constrained measurable angular velocities and frequencies and caused motion blur, affecting key point detection. Our findings suggest that the framework may provide plausible estimates of head motion but also emphasize the importance of high frame rate videos in future research, including extensive comparisons against ground truth data, to fully characterize bird head movements.

evolutionary biology↗

bioRxiv2024

Maggot: An ecosystem for sharing metadata within the web of FAIR Data

BackgroundDescriptive metadata are crucial for the discovery, reporting and mobilisation of research datasets. Addressing all metadata issues within the Data Management Plan often poses challenges for data producers. Organising and documenting data within data storage entails creating various descriptive metadata. Subsequently, data sharing involves ensuring metadata interoperability in alignment with FAIR principles. Given the tangible nature of these challenges, a real need for management tools has to be addressed to assist data managers to the fullest extent. Moreover, these tools have to meet data producers requirements and be user-friendly as well with minimal training as prerequisites. ResultsWe developed Maggot which stands for Metadata Aggregation on Data Storage, specifically designed to annotate datasets by generating metadata files to be linked into storage spaces. Maggot enables users to seamlessly generate and attach comprehensible metadata to datasets within a collaborative environment. This approach seamlessly integrates into a data management plan, effectively tackling challenges related to data organisation, documentation, storage, and frictionless FAIR metadata sharing within the collaborative group and beyond. Furthermore, for enabling metadata crosswalk, metadata generated with Maggot can be converted for a specific data repository or configured to be exported into a suitable format for data harvesting by third-party applications. ConclusionThe primary feature of Maggot is to ease metadata capture based on a carefully selected schema and standards. Then, it greatly eases access to data through metadata as requested nowadays in projects funded by public institutions and entities such as Europe Commission. Thus, Maggot can be used on one hand to promote good local versus global data management with open data sharing in mind while respecting FAIR principles, and on the other hand to prepare the future EOSC FAIR Web of Data within the framework of the European Open Science Cloud.

bioinformatics↗

bioRxiv2021

AMES: Automated evaluation of sarcomere structures in cardiomyocytes

BackgroundArrhythmias are severe cardiac diseases and lethal if untreated. To serve as an in vitro drug testing option for anti-arrhythmic agents, cardiomyocytes are being generated in vitro from induced pluripotent stem cells (iPSCs). Unfortunately, these generated cardiomyocytes resemble fetal cardiac tissue rather than adult cardiomyocytes. An automated tool for an unbiased evaluation of cardiomyocytes would highly facilitate the establishment of new differentiation protocols to increase cellular maturity. ResultsIn this work, a novel deep learning-based approach for this task is presented and evaluated. Different convolutional neural networks (CNNs) including 2D and 3D models were trained on fluorescence images of human iPSC-derived cardiomyocytes, which were rated based on their sarcomere content (sarcomerisation) and the orientation of sarcomere filaments (directionality) beforehand by a domain expert. The CNNs were trained to perform classifications on sarcomerisation, directionality ratings, and cell source, including primary adult and differentiated cardiomyocytes. The best accuracies are reached by a 3D model with a classification accuracy of about 90 % for sarcomerisation classification, 63 % for directionality classification, and 80 % for cell source classification. The trained models were additionally evaluated using two explanatory algorithms, IGrad and Grad-CAM. The heatmaps computed by those explainability algorithms show that the important regions in the image occur inside the cell and at the cellular borders for the classifier, and, therefore, validate the calculated regions. ConclusionIn summary, we showed that cellular fluorescence images can be analyzed with CNNs and subsequently used to predict different states of sarcomere maturation. Our developed prediction tool AMES (https://github.com/maxhillemanns/AMES) can be used to make trustworthy predictions on the quality of a cardiomyocyte, which ultimately facilitates the optimized generation of cardiomyocytes from iPSCs and improves the quality control in an automated, unbiased manner. The applied workflow of testing different CNN models, adjusting parameters, and using a variety of explanatory algorithms can be easily transferred to further image based quality control, stratification, or analysis setups.

bioinformatics↗

bioRxiv2021

First isolation of virulent Tenacibaculum maritimum strains from diseased orbicular batfish (Platax orbicularis) farmed in Tahiti Island

The orbicular batfish (Platax orbicularis), also called Paraha peue in Tahitian, is the most important marine fish species reared in French Polynesia. Sudden and widespread outbreaks of severe white-patch disease have occurred since 2011 in batfish farms one to three weeks after the transfer of juveniles from bio-secured hatcheries to lagoon cages. With cumulative mortality ranging from 20 to 90%, the sustainability of aquaculture of this species is severely threatened. In this study, we describe for the first time the isolation from diseased batfish of several strains belonging to the species Tenacibaculum maritimum, a major pathogen of many marine fish species. Histopathological analysis, an experimental bath challenge and a field monitoring study showed that T. maritimum is associated with white-patch disease. Moreover, molecular and serological analyses performed on representative strains revealed some degree of genetic diversity among the isolates, a finding of primary importance for epidemiological studies and for the development of management and control strategies such as vaccination.

pathology↗

bioRxiv2021

Automated annotation of rare-cell types from single-cell RNA-sequencing data through synthetic oversampling

The research landscape of single-cell and single-nuclei RNA sequencing is evolving rapidly, and one area that is enabled by this technology, is the detection of rare cells. An automated, unbiased and accurate annotation of rare subpopulations is challenging. Once rare cells are identified in one dataset, it will usually be necessary to generate other datasets to enrich the analysis (e.g., with samples from other tissues). From a machine learning perspective, the challenge arises from the fact that rare cell subpopulations constitute an imbalanced classification problem. We here introduce a Machine Learning (ML)-based oversampling method that uses gene expression counts of already identified rare cells as an input to generate synthetic cells to then identify similar (rare) cells in other publicly available experiments. We utilize single-cell synthetic oversampling (sc-SynO), which is based on the Localized Random Affine Shadowsampling (LoRAS) algorithm. The algorithm corrects for the overall imbalance ratio of the minority and majority class. We demonstrate the effectiveness of the method for two independent use cases, each consisting of two published datasets. The first use case identifies cardiac glial cells in snRNA-Seq data (17 nuclei out of 8,635). This use case was designed to take a larger imbalance ratio ([~]1 to 500) into account and only uses single-nuclei data. The second use case was designed to jointly use snRNA-Seq data and scRNA-Seq on a lower imbalance ratio ([~]1 to 26) for the training step to likewise investigate the potential of the algorithm to consider both single cell capture procedures and the impact of "less" rare-cell types. For validation purposes, all datasets have also been analyzed in a traditional manner using common data analysis approaches, such as the Seurat3 workflow. Our algorithm identifies rare-cell populations with a high accuracy and low false positive detection rate. A striking benefit of our algorithm is that it can be readily implemented in other and existing workflows. The code basis is publicly available at FairdomHub (https://fairdomhub.org/assays/1368) and can easily be transferred to train other customized approaches.

bioinformatics↗

bioRxiv2020

On-chip perivascular niche with patient-derived glioma cells

Glioblastoma multiforme (GBM), is the most common and the most aggressive type of primary brain malignancy. Glioblastoma stem-like cells (GSCs) are able to migrate in vascular niches within or away from the tumour mass, increasing tumour resistance to patient treatments and contributing to relapses. To study individual GSCs migration and their interactions with the microenvironment in the vasculature, there is a need to develop a model of human blood vessels in vitro. Herein, we report a systematic study on the interaction between patient-derived glioma stem-like cell lines with different organotypic perivascular niche models. A microfluidic chip integrated with an extracellular matrix was fabricated to support the culture of rounded microvessels, formed with endothelial cells from three different organs, (1) human brain microvascular endothelial cells (hCMEC/D3), (2) human umbilical vein endothelial cells (HUVECs) and, (3) human lung microvascular endothelial cells (HMVEC-L). Three-dimensional (3D) cell culture retains selected adherent and tight junction markers of the endothelial cells, and the stemness-related genes of GSCs. We optimized the experimental protocol to perform qPCR, and western blot on the co-cultured GSCs with endothelial cells forming microvessels. Endpoint biological assays showed upregulation of neovascularization-related genes in endothelial cells (e.g., angiopoietins, vascular endothelial growth factor receptors) resulted after their co-culture with GBM cells. Moreover, we measured cancer cell speed and polarization during migration towards the endothelial cell formed vessel by live-cell imaging showing that organotypic (brain cancer cells - brain endothelial microvessel) interactions differ from those within non-tissue specific vascular niches. The development and optimization of this 3D microfluidic device could provide the next level of complexity of an in vitro system to study the influence of glioma cells on normal brain endothelium. More importantly, it enables the possibility to conduct comparative studies to dissect the influence of 3D culture, microvessel architecture and organotypic vessel types on glioma cells stemness and migration.

bioengineering↗

bioRxiv2020

Identifying protein subcellular localisation in scientific literature using bidirectional deep recurrent neural network

With the advent of increased diversity and scale of molecular data, there has been a growing appreciation for the applications of machine learning and statistical methodologies to gain new biological insights. An important step in achieving this aim is the Relation Extraction process which specifies if an interaction exists between two or more biological entities in a published study. Here, we employed natural-language processing (CBOW) and deep Recurrent Neural Network (bi-directional LSTM) to predict relations between biological entities that describe protein subcellular localisation in plants. We applied our system to 1700 published Arabidopsis protein subcellular studies from the SUBA manually curated dataset. The system was able to extract relevant text and the classifier predicted interactions between protein name, subcellular localisation and experimental methodology. It obtained a final precision, recall rate, accuracy and F1 scores of 0.951, 0.828, 0.893 and 0.884 respectively. The classifier was subsequently tested on a similar problem in crop species (CropPAL) and demonstrated a comparable accuracy measure (0.897). Consequently, our approach can be used to extract protein functional features from unstructured text in the literature with high accuracy. The developed system will improve dissemination or protein functional data to the scientific community and unlock the potential of big data text analytics for generating new hypotheses from diverse datasets.

bioinformatics↗

bioRxiv2020

Entraining corticocortical plasticity changes oscillatory activity in action control and inhibition

Oscillatory activity may reflect interactions between brain areas[1]. Here we tested whether inducing corticocortical plasticity in a specific set of connections changes oscillatory activity and cortico-cortical interactions and, if this is the case, whether the changes manifest in a manner that is behaviour state-dependent. We either increased or decreased the influence of activity in human ventral premotor cortex (PMv) over activity in primary motor cortex (M1) using cortico-cortical paired associative stimulation (ccPAS)[2, 3]. Before and after stimulation participants performed a Go/No-Go task. While M1 TMS pulses revealed the excitatory state of the motor system at specific time points, the electroencephalogram (EEG) revealed the evolution of oscillatory activity dynamics in the motor system over several hundreds of milliseconds before, during, and after each movement. Augmenting cortical connectivity between PMv and M1, by evoking synchronous pre- and postsynaptic activity in the PMv-M1 pathways, led to a state-dependent modulation of the causal influence of PMv over M1, and at the same time, enhanced oscillatory beta and theta rhythms in Go and No-Go trials, respectively. No changes were observed in the alpha rhythm. The plasticity induction effect was dependent on PMv-M1 stimulation order; the opposite patterns of results were observed after an equal amount of stimulation of PMv and M1 but applied in a temporal pattern that did not augment PMvs influence over M1. These results are consistent with Hebbian principles of synaptic plasticity[4] and show that artificial manipulation of cortico-cortical connectivity produces state-dependent functional changes in the spectral fingerprints of the motor circuit.

neuroscience↗

bioRxiv2020

Dicistronic tRNA-mRNA transcripts in grapevine (Vitis vinifera) display distinct, regional expression patterns that correlate with tRNA expression

Transfer RNAs (tRNA) are crucial adaptor molecules between messenger RNA (mRNA) and amino acids. Recent evidence in plants suggests that dicistronic tRNA-like structures also act as mobile signals for mRNA transcripts to move between distant tissues. Co-transcription is not a common feature in the plant nuclear genome and, in the few cases where polycistronic transcripts have been found, they include non-coding RNA species such as small nucleolar RNAs and microRNAs. It is not known, however, the extent to which dicistronic transcripts of tRNA and mRNAs are expressed in field-grown plants, or the factors contributing to their expression. We analysed tRNA-mRNA dicistronic transcripts in the major horticultural crop grapevine (Vitis vinifera) using a novel pipeline developed to identify dicistronic transcripts from high-throughput RNA sequencing data. We identified dicistronic tRNA-mRNA in leaf and berry samples from 22 commercial vineyards. Of the 124 tRNA genes that were expressed in both tissues, 18 tRNA were expressed forming part of 19 dicistronic tRNA-mRNAs. The presence and abundance of dicistronic molecules was tissue and geographic sub-region specific. In leaves, the expression patterns of dicistronic tRNA-mRNAs significantly correlated with tRNA expression, suggesting that their transcriptional regulation might be linked. We also found evidence of syntenic genomic arrangements of tRNAs and protein coding genes between grapevine and Arabidopsis thaliana, and widespread prevalence of dicistronic tRNA-mRNA transcripts among vascular land plants but no evidence of these transcripts in nonvascular lineages. This suggests that the appearance of plant vasculature and tRNA-mRNA occurred concurrently during the evolution of land plants.

plant biology↗

bioRxiv2018

Arabidopsis TRM5 encodes a nuclear-localised bifunctional tRNA guanine and inosine-N1-methyltransferase that is important for growth.

Modified nucleosides in tRNAs are critical for protein translation. N1-methylguanosine-37 and N1-methylinosine-37 in tRNAs, both located at the 3-adjacent to the anticodon, are formed by Trm5 and here we describe Arabidopsis thaliana AtTrm5 (At3g56120) as a Trm5 ortholog. We show that AtTrm5 complements the yeast trm5 mutant, and in vitro methylates tRNA guanosine-37 to produce N1-methylguanosine (m1G). We also show in vitro that AtTRM5 methylates tRNA inosine-37 to produce N1-methylinosine (m1I) and in Attrm5 mutant plants, we show a reduction of both N1-methylguanosine and N1-methylinosine. We also show that AtTRM5 is localized to the nucleus in plant cells. Attrm5 mutant plants have overall slower growth as observed by slower leaf initiation rate, delayed flowering and reduced primary root length. In Attrm5 mutants, mRNAs of flowering time genes are less abundant and correlated with delayed flowering. Finally, proteomics data show that photosynthetic protein abundance is affected in mutant plants. Our findings highlight the bifunctionality of AtTRM5 and the importance of the post-transcriptional tRNA modifications m1G and m1I at tRNA position 37 in general plant growth and development.

molecular biology↗

bioRxiv2018

Bone marrow-on-a-chip: Emulating the human bone marrow

Multipotent hematopoietic stem and progenitor cells HSPC reside in specialized stem cell niches within the bone marrow, that provide a suitable microenvironment for lifelong maintenance of the stem cells. Meaningful in vitro models recapitulating the in vivo stem cell niche biology can be employed for both basic research as well as for applied sciences and represent a powerful tool to reduce animal tests in preclinical studies. Recently we published the generation of an in vitro bone marrow niche model, capable of long-term cultivation of HSC based on an organ-on-a-chip platform. This study provides a detailed analysis of the 3D culture system including matrix environment analysis by SEM, transcriptome analysis and system intrinsic differentiation induction. Furthermore, the bone marrow on a chip model can serve to multiply and harvest HSPC, since repeated cell removal not compromised the functionality of the culture system. The prolongation of the culture time to 8 weeks demonstrate the capacity to apply the model in repeated drug testing experiments. The quality of the presented system is emphasized by the differentiation capacity of long-term cultivated HSPC in vitro and in vivo. Transplanted human HSPC migrated actively into the bone marrow of irradiated mice and contributed to the long-term reconstitution of the hematopoietic system after four and eight weeks of in vitro cultivation.\n\nThe introduced system offers a multitude of possible applications to address a broad spectrum of questions regarding HSPC, the corresponding bone marrow niche biology, and pathological aberrations.

bioengineering↗

bioRxiv2018

Human bone marrow disorders recapitulated in vitro using organ chip technology

Understanding human bone marrow (BM) pathophysiology in the context of myelotoxic stress induced by drugs, radiation, or genetic mutations is of critical importance in clinical medicine. However, study of these dynamic cellular responses is hampered by the inaccessibility of living BM in vivo. Here, we describe a vascularized human Bone Marrow-on-a-Chip (BM Chip) microfluidic culture device for modeling bone marrow function and disease states. The BM Chip is comprised of a fluidic channel filled with a fibrin gel in which patient-derived CD34+ cells and bone marrow-derived stromal cells (BMSCs) are co-cultured, which is separated by a porous membrane from a parallel fluidic channel lined by human vascular endothelium. When perfused with culture medium through the vascular channel, the BM Chip maintains human CD34+ cells and supports differentiation and maturation of multiple blood cell lineages over 1 month in culture. Moreover, it recapitulates human myeloerythroid injury responses to drugs and gamma radiation exposure, as well as key hematopoietic abnormalities found in patients with the genetic disorder, Shwachman-Diamond Syndrome (SDS). These data establish the BM Chip as a new human in vitro model with broad potential utility for studies of BM dysfunction.

bioengineering↗