Biology subjects

Huynen, M.

Publications and source records attributed to Huynen, M..

11 recordsLinked to original sources

bioRxiv2026

Imaging guided single-cell multiomics unveils shared autoreactive CD4+ T-cell responses in blood, locoregional lymph node and affected tissues of patients with systemic autoimmunity

Systemic autoimmune connective tissue diseases (CTDs) are characterized by anti-nuclear antibodies, shared HLA-associated genetic risk, and frequent disease overlap, suggesting a central role for CD4+ T cells in pathogenesis. However, defining disease-driving CD4+ T-cell responses remains challenging due to their localization within lymphoid and affected tissues and the lack of approaches linking these responses to circulating counterparts. We combined [18F]-labeled thymidine PET/CT-guided tissue sampling, ex vivo antigen stimulation, and single-cell multiomics to characterize CD4+ T-cell responses in blood, PET-avid locoregional lymph nodes (LNs), and disease-affected tissues from patients with the immunologically distinct CTDs systemic sclerosis and Sjogren's disease. PET-avid LNs from both diseases exhibited enhanced adaptive immune activity and contained an expanded population of interferon-stimulated gene (ISG)-expressing TRAIL+ CD4+ T cells. In Sjogren's disease, active LNs and affected tissues harbored diverse effector CD4+ T-cell populations, including follicular and peripheral helper T cells and Th2/Th17 cells. In contrast, systemic sclerosis tissues lacked effector CD4+ T cells, while active LNs were enriched for naive, regulatory, and TRAIL+ ISG CD4+ T cells. Antigen stimulation of peripheral blood mononuclear cells enriched for expanded effector CD4+ T-cell populations that shared activation profiles and clonal relationships with cells in LNs and affected tissues, many representing autoreactive antigen-specific T cells. TRAIL+ CD4+ T cells suppressed effector T-cell differentiation, autoreactive plasma cell generation, and autoantibody production in vitro, identifying a previously unrecognized immunoregulatory population. Together, this workflow enables comprehensive characterization of pathogenic and regulatory CD4+ T-cell responses across CTDs.

immunology↗

bioRxiv2025

KG-Bench: Benchmarking Graph Neural Network Algorithms for Drug Repurposing

MotivationDrug repurposing leverages existing drugs for new indications, accelerating drug development. Computational methods integrating diverse biological and chemical data can systematically prioritize repurposing candidates, but standardized benchmarks for deep learning evaluation are lacking. We present KG-Bench, a benchmarking framework for drug-disease association prediction using the Open Targets dataset. We constructed a knowledge graph (KG) of drugs, diseases, and targets, including annotations such as therapeutic area and molecular pathway, and ensured retrospective validation by leveraging regular dataset updates. To avoid data leakage, we removed redundant entities across splits. ResultsBenchmarking several graph neural network (GNN) architectures, TransformerConv achieved the highest performance (APR: 0.87). KG-Bench also assesses bias, node/feature importance, and uses GNNExplainer for interpretability. Our open-source framework enables fair, reproducible evaluation of graph-based drug repurposing algorithms. Availability and ImplementationData and codes are available at https://github.com/cmbi/Benchmark_GNN_OpenTargets.

bioinformatics↗

bioRxiv2024

In vitro-generated inflammatory fibroblasts secrete extracellular matrix with biochemical and biophysical properties similar to tissue-remodelling fibroblasts

In solid cancers, inflammation and viral infections, two main fibroblast subtypes have been identified: myofibroblast-like fibroblasts and inflammatory fibroblasts. In the tumour microenvironment (TME), these cancer-associated fibroblast (CAF) subtypes are known as myCAFs, which generate a stiffened fibrotic extracellular matrix (ECM), and iCAFs, which secrete inflammatory cytokines to locally modulate the immune response. Yet, whether iCAFs contribute to shaping the ECM biochemical and biophysical properties remains unknown, mainly because robust in vitro models to generate fibroblast subtypes are lacking. Here, we established an in vitro cell culture system based on murine NIH3T3 fibroblasts and stimulation by TGF{beta} and IL1, alone or in combination, to induce fibroblast subtypes. Gene expression analysis of well-documented myCAF (Acta2/Tagln) and iCAF (Ccl2/Il6/Lif) markers revealed that TGF{beta} induced a myCAF-like phenotype, while a combination of TGF{beta} and IL1 induced an iCAF-like phenotype. We compared these in vitro subtypes to myCAFs and iCAFs from publicly available scRNAseq data of tumour tissues from cancer patients. We found that, similar to myCAFs, both tumour-associated and in vitro iCAFs express Acta2/Tagln as well as genes encoding for typical ECM proteins, which correlated in vitro with the ability to contract collagen. Furthermore, fluorescence microscopy and atomic force microscopy revealed that in vitro both subtypes generate thick, layered and stiff matrices with highly aligned ECM, demonstrating for the first time that iCAFs may also contribute to a pathological ECM. Finally, matrices generated from these in vitro fibroblast subtypes, but not from uninduced or IL1-only stimulated fibroblasts, enhanced the expression of the immune suppression marker Arg1 in co-cultured macrophages. Our study provides new insights in the contribution of inflammatory fibroblasts to ECM deposition and remodelling and puts forward a well-defined in vitro model to generate different fibroblast subtypes for future in-depth mechanistic studies of their roles in cancer and other pathologies.

cell biology↗

bioRxiv2024

Chromosome-scale genome assembly and gene annotation of the hydrothermal vent annelid Alvinella pompejana yield insight into animal evolution in extreme environments

The types of genomic change needed for environmental adaptation are of great interest. Annelid worms are a large phylum found in a rich diversity of habitats, giving opportunities to explore this issue. We report the chromosome level genome sequence of the Pompeii worm, the annelid Alvinella pompejana, an inhabitant of an extreme deep-sea hydrothermal vent environment. We find strong but heterogeneously distributed genetic divergence between populations taken from either side of the equator. Using transcript data, we produced a set of gene models and analysed the predicted protein set in the light of past hypotheses about the thermotolerance of Alvinella, and compared it to other recently sequenced annelid vent worms. We do not find evidence of a more extreme genome wide amino acid composition than other species, neither do we find evidence for rapid genome evolution in the form of disrupted synteny. We discount the hypothesis of loss of amino acid biosynthesis genes associated with obligate symbioses reported in siboglinid annelids. We do find evidence of a parallel increase in the number of globin encoding genes and loss of light sensitive opsins and cryptochromes. Alvinella encodes several respiratory enzymes unusual for bilaterian animals, suggesting an ability to better tolerate hypoxic environments.

genomics↗

bioRxiv2023

Parallel evolution and enhanced virulence upon in vivo passage of an RNA virus in Drosophila melanogaster

Virus evolution is strongly affected by antagonistic co-evolution of virus and host. Host immunity positively selects for viruses that evade the immune response, which in turn may drive counter-adaptations in host immune genes. We investigated how host immune pressure shapes virus populations, using the fruit fly Drosophila melanogaster and its natural pathogen Drosophila C virus (DCV), as a model. We performed an experimental evolution study in which DCV was serially passaged for ten generations in three fly genotypes differing in their antiviral RNAi response: wild-type flies and flies in which the endonuclease gene Dicer-2 was either overexpressed or inactivated. All evolved virus populations replicated more efficiently in vivo and were more virulent than the parental stock. The number of polymorphisms increased in all three host genotypes with passage number, which was most pronounced in Dicer-2 knockout flies. Mutational analysis showed strong parallel evolution, as mutations accumulated in a specific region of the VP3 capsid protein in every lineage in a host genotype-independent manner. The parental tyrosine at position 95 of VP3 was substituted with either one of five different amino acids in 14 out of 15 lineages. However, no consistent amino acid changes were observed in the viral RNAi suppressor gene 1A, nor elsewhere in the genome in any of the host backgrounds. Our study indicates that the RNAi response restricts the sequence space that can be explored by viral populations. Moreover, our study illustrates how evolution towards higher virulence can be a highly reproducible, yet unpredictable process.

microbiology↗

bioRxiv2022

Activation mechanism of mitochondrial translation by LRPPRC-SLIRP

In mammalian mitochondria, mRNAs are co-transcriptionally stabilized by the protein factor LRPPRC. Here, we characterize LRPPRC as an mRNA delivery factor and report its cryo-EM structure in complex with SLIRP, mRNA and the mitoribosome. The structure shows that LRPPRC associates with the mitoribosomal proteins mS39 and the N-terminus of mS31 through recognition of the LRPPRC helical repeats. Together, the proteins form a corridor for hand-off the mRNA. The mRNA is directly bound to SLIRP, which also has a stabilizing function for LRPPRC. To delineate the effect of LRPPRC on individual mitochondrial transcripts, we used an RNAseq approach, metabolic labeling and mitoribosome profiling that showed a major influence on ND1, ND2, ATP6, COX1, COX2, and COX3 mRNA translation efficiency. Our data suggest that LRPPRC-SLIRP acts in recruitment of mitochondrial mRNAs to modulate their translation. Collectively, the data define LRPPRC-SLIRP as a regulator of the mitochondrial gene expression system.

biochemistry↗

bioRxiv2020

Nutrition or nature: disentangling the complex forces shaping prokaryote pan-genomes

Microbial pan-genomes are shaped by a complex combination of stochastic and deterministic forces. Even closely related genomes often exhibit extensive variation in their gene content. Understanding what drives this variation requires exploring the interactions of genes with each other and with their external environments. However, to date, conceptual models of pan-genome dynamics often represent genes as independent units and provide limited information about their mechanistic interactions. Here, we use pan-reactomes as proxies for pan-genomes since they can explicitly represent the interactions between the genes that code for metabolic reactions and simulate complex phenotypes that interact with the metabolic environment. We interpreted pan-reactomes as dynamic pools of metabolic reactions that are potentially gained or lost and simulated the routes along which different lineages lose reactions in alternative environments. We performed these simulations on the pan-reactomes of 46 bacterial and archaeal families covering a broad taxonomic range. These simulations allowed us to disentangle metabolic reactions whose presence does, and does not depend on the metabolite composition of the external environment, allowing us to identify reactions constrained "by nutrition" and "by nature", respectively. By comparing the frequency of reactions from the first group with their observed frequencies in bacterial and archaeal families, we predicted the metabolic niches that shaped the genomic composition of these lineages in their evolutionary past. Moreover, we found that the lineages that were shaped by a more diverse metabolic niche also occur in more diverse biomes as assessed by global environmental sequencing datasets. Together, we introduce a computational framework for analyzing and interpreting pan-reactomes that provides new insights into the ecological and evolutionary drivers of pan-genome composition.

evolutionary biology↗

bioRxiv2020

CEDAR, an online resource for the reporting and exploration of complexome profiling data

Complexome profiling is an emerging omics approach that systematically interrogates the composition of protein complexes (the complexome) of a sample, by combining biochemical separation of native protein complexes with mass-spectrometry based quantitation proteomics. The resulting fractionation profiles hold comprehensive information on the abundance and composition of the complexome, and have a high potential for reuse by experimental and computational researchers. However, the lack of a central resource that provides access to these data, reported with adequate descriptions and an analysis tool, has limited their reuse. Therefore, we established the ComplexomE profiling DAta Resource (CEDAR, www3.cmbi.umcn.nl/cedar/), an openly accessible database for depositing and exploring mass spectrometry data from complexome profiling studies. Compatibility and reusability of the data is ensured by a standardized data and reporting format containing the "minimum information required for a complexome profiling experiment" (MIACE). The data can be accessed through a user-friendly web interface, as well as programmatically using the REST API portal. Additionally, all complexome profiles available on CEDAR can be inspected directly on the website with the profile viewer tool that allows the detection of correlated profiles and inference of potential complexes. In conclusion, CEDAR is a unique, growing and invaluable resource for the study of protein complex composition and dynamics across biological systems.

bioinformatics↗

bioRxiv2020

Composition and stage dynamics of mitochondrial complexes in Plasmodium falciparum

Our current understanding of mitochondrial functioning is largely restricted to traditional model organisms, which only represent a fraction of eukaryotic diversity. The unusual mitochondrion of malaria parasites is a validated drug target but remains poorly understood. Here, we apply complexome profiling to map the inventory of protein complexes across the pathogenic asexual blood stages and the transmissible gametocyte stages of Plasmodium falciparum. We identify remarkably divergent composition and clade-specific additions of all respiratory chain complexes. Furthermore, we show that respiratory chain complex components and linked metabolic pathways are up to 40-fold more prevalent in gametocytes, while glycolytic enzymes are substantially reduced. Underlining this functional switch, we find that cristae are exclusively present in gametocytes. Leveraging these divergent properties and stage dynamics for drug development presents an attractive opportunity to discover novel classes of antimalarials and increase our repertoire of gametocytocidal drugs.

microbiology↗

bioRxiv2019

Surveillance-embedded genomic outbreak resolution of methicillin-susceptible Staphylococcus aureus in a neonatal intensive care unit

BackgroundWe observed an increase in methicillin-susceptible Staphylococcus aureus (MSSA) infections among neonates at a Dutch third level neonatal intensive care unit. Weekly surveillance data of MSSA carriage among neonates and cross-sectional screenings of health care workers (HCWs) were available for outbreak tracing. While traditional typing of MSSA isolates by staphylococcal protein A gene (spa typing) and Multiple-Locus Variable number tandem repeat Analysis (MLVA) suggested that nosocomial transmission had contributed to the infections, here they lacked the resolution to draw solid conclusions.\n\nMethodsMSSA isolates from neonatal infections, carriage surveillance, and HCWs were subjected to whole-genome sequencing and compared by a series of automated tools including de novo assembly, identification and localization of high-quality single nucleotide polymorphisms, and in-depth analysis of subsets of isolates. Outbreaks were defined as isolates that were more closely related than was to be expected from the genetic diversity in background surveillance.\n\nResultsGenomic analysis identified isolates that had been unjustly assigned to clusters based on MLVA typing, while spa typing was concordant but of insufficient resolution. Detailing particular subsets of isolates further improved resolution and although it provided evidence that HCWs were involved in multiple outbreaks, it alleviated heavy concerns about one particular HCW. Genomic clustering of isolates based on deviations from background surveillance matched epidemiological patient linkage. Compared to MLVA typing, the genomic analysis demonstrated more, shorter, and re-assorted nosocomial transmission chains during this outbreak.\n\nConclusionsIn this study the improved resolution and accuracy of genomic outbreak analyses compared to spa typing and MLVA substantially altered the view on outbreaks, along with apposite outbreak measures. Inclusion of the circulating background population has the potential to overcome current issues in genomic outbreak inference.

microbiology↗

bioRxiv2018

COmplexome Profiling ALignment (COPAL) reveals remodeling of mitochondrial protein complexes in Barth syndrome

MotivationComplexome profiling combines native gel electrophoresis with mass spectrometry to obtain the inventory, composition and abundance of multiprotein assemblies in an organelle. Applying complexome profiling to determine the effect of a mutation on protein complexes requires separating technical and biological variations from the variations caused by that mutation.\n\nResultsWe have developed the COmplexome Profiling ALignment (COPAL) tool that aligns multiple complexome profiles with each other. It includes the abundance profiles of all proteins on two gels, using a multidimensional implementation of the dynamic time warping algorithm to align the gels. Subsequent progressive alignment allows us to align multiple profiles with each other. We tested COPAL on complexome profiles from control mitochondria and from Barth syndrome (BTHS) mitochondria, which have a mutation in tafazzin gene that is involved in remodelling the inner mitochondrial membrane phospholipid cardiolipin. By comparing the variation between BTHS mitochondria and controls with the variation among either, we assessed the effects of BTHS on the abundance profiles of individual proteins. Combining those profiles with gene set enrichment analysis allows detecting significantly affected protein complexes. Most of the significantly affected protein complexes are located in the inner mitochondrial membrane (MICOS, prohibitins), or are attached to it (the large ribosomal subunit).\n\nAvailability and implementationCOPAL is written in Python and is available from gttp://github.com/cmbi/copal.\n\nContacthuynen@cmbi.ru.nl

bioinformatics↗