Biology subjects

Van Haver, D.

Publications and source records attributed to Van Haver, D..

11 recordsLinked to original sources

bioRxiv2026

Role of the gut microbiota in the remodelling of the jejunal, colonic, hepatic and blood proteomes in a mouse model of Anorexia Nervosa

Background: Anorexia nervosa (AN) is a typical form of eating disorder characterized by a severe body weight loss, a fear of gaining weight and dysmorphophobia. This disorder is associated with both psychiatric comorbidities and multi-organ dysfunctions. Increasing evidence suggests a role of the gut microbiota in the onset or maintenance of AN. Although a dysbiosis has been reported in patients with AN, the physiological consequences of this dysbiosis remain poorly documented. To gain further insight into the role of the gut microbiota in the pathophysiology of AN, we used the murine Activity-based Anorexia (ABA) model and compared the remodelling of the jejunal, colonic, hepatic and blood proteomes occurring in male mice with intact gut microbiota, as well as in gut microbiota-depleted animals. Results: We observed a significant proteome remodelling in several organs in response to the ABA model. More than 250 proteins involved in energy metabolism, catabolic processes, lipid metabolism, ghrelin regulation, and immune functions were found to show altered abundance in ABA mice compared to control mice. We observed in addition in the blood of ABA mice a significant increase in the level of circulating proteasome. By comparing mice treated or not with antibiotics, we identified 75 proteins whose regulation in ABA mice is gut-microbiota dependent. The other identified proteins were similarly affected in ABA mice with intact or depleted gut microbiota, suggesting that these factors are mainly regulated by food starvation and physical activity, and not directly by the gut microbiota. We finally confirmed that ORM2, a protein identified as significantly decreased in the plasma of ABA mice, is also decreased in the blood of patients suffering from AN. Conclusion: Our results demonstrate that the Activity-Based Anorexia model is associated with an extensive proteome remodelling in several organs and tissues. We highlight in addition that some of these targets are regulated in a gut microbiota-dependent manner, thereby reinforcing the hypothesis of a role of the gut microbiota in Anorexia Nervosa. Together, our study provides a valuable resource to better delineate the impact of undernutrition and maladaptive physical activity on the proteome of various organs and the role of the gut bacteria in the pathophysiology of Anorexia Nervosa.

pathology↗

bioRxiv2026

A novel nanobody-based approach for targeting heterogeneous Acinetobacter baumannii isolates and closely related pathogenic Acinetobacter spp.

Acinetobacter baumannii is a top-priority, ESKAPE pathogen that poses a major challenge to human health. The pathogen is difficult to combat due to its extensive arsenal of antibiotic resistance and its protective polysaccharide capsule. In addition, A. baumannii isolates are highly heterogeneous, which complicates the development of rapid detection methods or novel targeted therapeutic approaches. Here, we discovered and characterized a new biotechnological tool, the nanobody H7 (NbH7), along with its conserved target, the surface-exposed Omp25 protein of A. baumannii, and elucidated their interaction at the molecular level. Moreover, we demonstrate that NbH7-functionalized magnetic beads enable selective and efficient capture of A. baumannii from bacterial mixtures, including non-pathogenic intestinal bacteria. This provides proof of concept for a new targeting system that remains effective across diverse A. baumannii clinical isolates and capsule types and holds potential for use in diagnostic cell enrichment and targeted therapies.

molecular biology↗

bioRxiv2026

Proteomic profiling of whole tissue sections in cardiac ATTR amyloidosis reveals increased extracellular matrix remodeling

Cardiac transthyretin amyloidosis (ATTR-CA) is caused by myocardial deposition of misfolded transthyretin, leading to progressive heart failure. Disease pathology, however, extends beyond passive amyloid deposition and also involves active processes such as extracellular matrix (ECM) remodeling and immune activation. Mass spectrometry (MS) is the gold standard for amyloid typing in diagnostics. Here, we applied quantitative MS-driven proteomics on formalin-fixed paraffin-embedded whole cardiac tissue sections from six ATTR-CA cases, ten unaffected controls and four AL-CA controls to investigate protein expression changes. In addition to transthyretin, over 500 proteins were upregulated in ATTR-CA biopsies, including complement and coagulation factors as well as extracellular matrix (ECM) remodeling proteins. Among these, members of the A Disintegrin and Metalloproteinase with Thrombospondin Motifs (ADAMTS) family, metalloproteinases (MMPs), and Tissue Inhibitor of Metalloproteinases (TIMP3) showed significant upregulation. These proteins are key regulators of ECM turnover and structural integrity. Immunohistochemistry confirmed ADAMTS4 enrichment in amyloid deposits, while TIMP3 showed strong expression in cardiomyocytes and weaker staining within amyloid deposits. Together, these findings indicate that ECM remodeling, alongside complement and coagulation activation, represents a reproducible feature of cardiac ATTR amyloidosis. Whole-tissue proteomics provides biological insights that extend beyond amyloid typing, with potential implications for biomarker discovery and therapeutic targeting in ATTR-CA.

pathology↗

bioRxiv2025

Identification of DksA as a novel pro-inflammatory mediator of Pseudomonas aeruginosa under conditions mimicking chronic cystic fibrosis lung infection

Chronic infection with Pseudomonas aeruginosa is a major driver of airway inflammation, which plays a central role in the progression of cystic fibrosis (CF) lung disease. During long-term colonization, P. aeruginosa adapts to the CF lung by downregulating virulence factors and adopting a biofilm-associated, mucoid lifestyle. Despite the expected reduction in immune activation due to these adaptations, excessive inflammation persists, a paradox that remains poorly understood. Our objective was to identify novel bacterial mediators sustaining persistent inflammation by P. aeruginosa in the CF lung. To this end, we analyzed clinical P. aeruginosa CF isolates, cultured them in synthetic CF sputum medium, and exposed 3D lung epithelial cell cultures to the resulting cell-free supernatants. There was considerable variability in pro-inflammatory activity among the isolates, with a subset of the isolates inducing strong IL-8 secretion by the 3D cells despite low production of known virulence factors. Comparative proteomics analysis of the cell-free supernatants of pro- and anti-inflammatory isolates revealed several mediators not previously linked to inflammation. Thirteen of these candidate pro-inflammatory mediators were selected for further analysis. Using P. aeruginosa transposon mutants lacking the respective mediators, DksA (a transcription factor) was confirmed as an immunomodulatory mediator in the 3D lung model. Finally, analysis of existing transcriptomes of P. aeruginosa in CF sputum, revealed that dksA was found to be one of the most strongly expressed genes in this patient population, highlighting the relevance of our findings. In conclusion, we identified a novel P. aeruginosa mediator that may contribute to CF airway inflammation.

microbiology↗

bioRxiv2025

Deconvoluting fiber type proportions from human skeletal muscle transcriptomics and proteomics data using FibeRtypeR

Muscle fibers are the dominant, multinucleated cell type in skeletal muscle. In humans, they can be classified as slow (type 1) and fast (type 2) fibers, traditionally based on distinct properties of their contractile machinery. Slow and fast fibers are characterized by shared and specific cellular complexities that are pivotal for their adaptive capacity to exercise or role in metabolic disease progression. In this era of omics research, there is a critical need to accurately infer muscle fiber type proportions from bulk tissue omics datasets, as single-fiber approaches are not feasible in large-scale or retrospective studies. Here we present FibeRtypeR, an easy-to-use web application to accurately estimate fiber type proportions from bulk transcriptomics and proteomics datasets: https://muscleapps.ugent.be. FibeRtypeR exploits transcriptomics and proteomics profiles of 1000 fiber-typed individual human skeletal muscle fibers as a reference dataset and is validated against paired immunohistochemical fiber type determinations in 160 muscle biopsies. We show that FibeRtypeR can be applied to public datasets, illustrating the application potential across a wide range of biological contexts such as aging, disease and exercise training. This new freely accessible computational tool will prove valuable to the skeletal muscle research community. Key pointsO_LIBulk muscle omics datasets lack fiber type specific information C_LIO_LIOur new tool, FibeRtypeR, leverages in-house collected single-fiber profiles allowing for accurate fiber type inference C_LIO_LIFibeRtypeR is methodologically robust across omics technologies and workflows C_LIO_LIWe host FibeRtypeR as an intuitive open-access Shiny app, applicable to new and publicly available transcriptomics and proteomics datasets C_LI

physiology↗

bioRxiv2025

TurboID proximity interactome mapping reveals NR2E3 association with AP-1 and retinal developmental complexes

The photoreceptor-specific nuclear receptor NR2E3 is a key transcription factor in the retinal transcriptional network, essential in photoreceptor cell fate and maintenance. Various biallelic loss-of-function variants lead to autosomal recessive inherited retinal disease (IRD), while a single missense variant G56R has been identified to cause autosomal dominant retinitis pigmentosa (adRP). However, a comprehensive understanding of the interactome of NR2E3 remains elusive. Here, we aimed to map the interactome of this nuclear receptor and the G56R pathogenic variant through proximity labelling followed by mass spectrometry. We used the TurboID "T2A split/link design" to identify the proximity interactome of wild-type NR2E3 and mutant G56R-NR2E3 in ARPE-19 cells. Several protein complexes involved in retinal development, including the AP-1 complex, were enriched. The results suggest similar interactomes for NR2E3 and G56R-NR2E3 in ARPE-19. However, BCOR was exclusively enriched in the G56R-NR2E3 network, strengthening the connection with the IRD phenotype. In conclusion, our approach has mapped the proximity interactome of NR2E3 and G56R-NR2E3, revealing interaction with protein complexes involved in (retinal) development.

systems biology↗

bioRxiv2025

Decoding Phenotypic Variability in Osteogenesis Imperfecta: Zebrafish as a Model for Molecular and Ultrastructural Insights.

Phenotypic variability is common in human diseases, even when the same genes are affected. In this study, three zebrafish models of Osteogenesis Imperfecta (OI) with dominant glycine substitutions in type I collagen genes (col1a1amh13/+, col1a1adc124/+, and col1a2mh15/+) were characterized for phenotypic severity and variability, using a newly developed standardized scoring system. Comprehensive analyses of the vertebral columns in these models revealed histological and ultrastructural differences that corresponded with phenotypic severity. Increasing skeletal severity correlated with a higher incidence of skeletal deformities and abnormalities. This, in turn, was associated with thinner bones and increased disorganization of collagen fibrils, fiber accumulation and mineralization, elastin deposits, and increased cell proliferation in the notochord and intervertebral ligament (IVL). Additionally, osteoblast function and bone regenerative capacity were increasingly compromised. These characteristics, combined with genetic information, have the potential to predict the severity of phenotypic outcomes in dominant forms of OI, caused by mutations in type I collagen. A remarkable intra-familial phenotypic variability in the col1a2mh15/+mutant holds potential for future approaches that could help in understanding the underlying mechanisms of this variability and the identification of modifier genes. Finally, through proteomics analysis three potential protein biomarkers (HSP47, Col8a1, and Bcan) were identified, that could serve as indicators of disease severity. These biomarkers not only have diagnostic value, but will allow stratification by OI type, have predictive value towards progression of the clinical presentation and will play a role in treatment guidance. Validation in human tissue samples will further reveal their clinical relevance. Significance StatementPhenotypic variability in human diseases, such as Osteogenesis Imperfecta (OI), remains poorly understood. Using zebrafish models with dominant glycine substitutions in type I collagen, this study links genetic mutations to phenotypic severity through standardized scoring and detailed ultrastructural and molecular analyses. Key findings include skeletal abnormalities, compromised osteoblast function, and intra-familial phenotypic variability, suggesting the role of modifier genes. Proteomics identified three potential biomarkers (HSP47, Col8a1, and Bcan) with diagnostic and prognostic value. These results provide critical insights into genotype-phenotype correlations, offering a foundation for personalized approaches to diagnosis, stratification, and treatment of OI and related disorders.

molecular biology↗

bioRxiv2024

High-throughput nano-flow proteomics using a dual-column electrospray source

With current trends in proteomics, especially regarding clinical and low input (to single cell) samples, it is increasingly important to both maximize the throughput of the analysis and maintain as much sensitivity as possible. The new generation of mass spectrometers (MS) are taking a huge leap in sensitivity, allowing to analyze samples with shorter liquid chromatography (LC) methods while digging as deep in the proteome. However, the throughput can be doubled by implementing a dual column nano-LC-MS configuration. For this purpose, we used a dual-column setup with a two-outlet electrospray source, and compared it to a classic dual-column setup with a single-outlet source.

biochemistry↗

bioRxiv2023

Integrating multiple omics levels using the human protein complexome as a framework, a multi-omics study of inborn errors of metabolism

Proteins organize into functional assemblies that drive diverse biological activities. Leveraging a comprehensive dataset of manually curated annotations for the human protein complexome, we investigated biological perturbations at the protein complex level. Using proteomics and transcriptomics data from fibroblasts of patients with inborn errors of metabolism (IEM) and control samples, we globally mapped information onto complex subunits to discern affected processes. Across the patient cohort (consisting of organic acidaemias, fatty acid oxidation defects and mitochondrial respiratory chain defect IEMs), mitochondrial oxidative phosphorylation emerged as the most perturbed pathway, identified through proteomics datasets. Simultaneously, metabolomics highlighted significant regulation of phospholipids in patients with Fatty Acid and Mitochondrial IEM. Moreover, proteomics analysis also revealed the dysregulation of protein complexes involved in histone (de)acetylation, a finding validated through Western Blot analysis measuring histone acetylation levels. This introduces a novel epigenetic dimension to IEM and metabolic research, suggesting avenues for further exploration. Our study demonstrates a multiomics data integration concept that maps proteomics and transcriptomics data onto model organism complexomes. This integrative approach can be extended to metabolomics and lipidomics, associating information with complexes having metabolic functions, such as enzymatic complexes. This global strategy for identifying disease-relevant perturbations offers a systems-wide perspective on molecular-level physiological and pathological changes. Such insights are crucial for devising clinical intervention strategies and prioritizing druggable pathways and complexes. The presented methodology provides a foundation for future investigations, emphasizing the importance of integrating multiomics data to comprehensively understand cellular machinery alterations and facilitate targeted therapeutic approaches.

biochemistry↗

bioRxiv2023

Aberrant phase separation is a common killing strategy of positively charged peptides in biology and human disease

Positively charged repeat peptides are emerging as key players in neurodegenerative diseases. These peptides can perturb diverse cellular pathways but a unifying framework for how such promiscuous toxicity arises has remained elusive. We used mass-spectrometry-based proteomics to define the protein targets of these neurotoxic peptides and found that they all share similar sequence features that drive their aberrant condensation with these positively charged peptides. We trained a machine learning algorithm to detect such sequence features and unexpectedly discovered that this mode of toxicity is not limited to human repeat expansion disorders but has evolved countless times across the tree of life in the form of cationic antimicrobial and venom peptides. We demonstrate that an excess in positive charge is necessary and sufficient for this killer activity, which we name polycation poisoning. These findings reveal an ancient and conserved mechanism and inform ways to leverage its design rules for new generations of bioactive peptides.

cell biology↗

bioRxiv2018

Digging deeper into the human proteome: A novel nanoflow LCMS setup using micro pillar array columns (μPAC™)

In bottom-up proteomics, capillaries up to 75 cm long with internal diameters of 50 to 100 {micro}m packed with sub-2-{micro}m C18-functionalized particles are routinely used in combination with high-resolution mass spectrometry. Unlike such conventional liquid chromatography (LC) columns, micro pillar array columns ({micro}PAC) are fabricated using micromachining technology, resulting in perfectly ordered chromatographic separation beds, leading to a minimized analyte dispersion while column permeability is increased by one order of magnitude. This allows using very long columns (up to 200 cm) at only a fraction of the pressure needed to operate packed bed columns. To validate {micro}PAC column performances, different amounts of tryptic digests of HEK293T cell lysates were prepared and separated using a 200 cm {micro}PAC column or a 40 cm long conventional column. Using an Orbitrap Elite instrument, on average 25% more proteins were identified with the {micro}PAC column. Moreover, the rate at which the peak width increases with gradient time is much lower on the {micro}PAC column. For a 10-hour long gradient, average peak widths below 0.5 min were observed, resulting in consistent identification of over 5,000 proteins. Combining long solvent gradients and this new type of LC column, substantial improvements in proteome coverage could be obtained. Finally, we demonstrated high reproducibility and durability of the {micro}PAC column. Data are available via ProteomeXchange with identifiers PXD011547 and PXD013235.

biochemistry↗