Research
Advanced Optical Microscopy
Within the department of Genetics and Cell Biology an extensive range of microscopy and imaging modalities are employed. This includes, but is not limited to, confocal laser scanning microscopy (CLSM), multiphoton laser scanning microscopy (TPLSM), Multiphoton Endoscopy (ME), Raman SRS microscopy, super-resolution microscopy (STED), light-sheet microscopy (LSFM). Imaging is supported by advanced sample-preparation methods, including optical clearing, expansion, immuno-histochemistry, cell culture, as well as sophisticated image and data analysis pipelines.
Approaches are applied across diverse areas of biomedical research, such as cardiovascular disease, oncology, epilepsy, preeclampsia, and metabolism, but since a few years also in plant and crop biology. Studies, ranging from organ to sub-cellular level, are using material from cells in culture, via animal and plant tissues, to human samples. Innovative imaging approaches are developed and applied to deepen the understanding of disease processes and to advance clinically relevant diagnostics, in close collaboration with our clinical colleagues from the local hospital (MUMC+).
Individual & Forensic (Epi)genomics
Our research aims to uncover novel layers of biological individuality by advancing concepts of (epi)genomic uniqueness. We integrate biomarker discovery, technology development, and translational applications to explore human diversity and its implications for health and justice. Current work focuses on the human repetitive (epi)genome using long-read nanopore sequencing, but also extends to single-cell profiling, methylation-based age prediction, and forensic genomic diagnostics. The long-term vision of our group is to deepen understanding of human variability and individuality, improve precision medicine, support forensic and clinical diagnostics, and contribute to a safer and healthier society. Our approach combines experimental, computational, and integrative analyses to push the boundaries of what (epi)genomic data can reveal about (unknown) individuals.
Reproductive Genetics
To better understand early human development and improve reproductive care, we apply single-cell and liquid-biopsy technologies as well as AI to determine cause and consequence of genome instability in early life. A primary focus lies on developing diagnostic and predictive models that can prevent unnecessary embryo transfers and invasive testing, while deepening insight into maternal-fetal interactions and conditions such as endometriosis. Ultimately, the aim is to translate these innovations into clinical practice, enabling more accurate, personalized, and effective strategies in reproductive medicine.
Model System genomics
Investigating the genetic and molecular mechanisms underlying cardiogenetic and metabolic diseases can be done using zebrafish as an advanced model system. Zebrafish have several advantages, including optical transparency, rapid development, and amenability to CRISPR-based genome editing. This allows the application of imaging, image analysis, and functional genomics to characterize pathogenic variants and model disease processes. This research supports the identification of disease-causing mechanisms, the development of genetic heart-disease models, and the screening of potential therapeutic approaches.
Immunometabolism in Depression
Our research investigates the molecular and metabolic underpinnings of depression by focusing on the interplay between lipid biology and neuropsychiatric disease. Building on a background in lipid metabolism and its role in inflammatory disorders, including metabolic-associated steatohepatitis (MASH), atherosclerosis, and Niemann-Pick type C disease, we now direct this expertise toward understanding how lipid changes and metabolic dysregulation contribute to depression and modulate antidepressant response. Current work explores two interconnected questions: how do lipid deviations influence susceptibility to or severity of depressive illness, and how does lipid metabolism shape sensitivity or resistance to antidepressant therapy? To address these questions, we employ an integrated approach combining cell-based models, preclinical mouse models, and clinical patient samples. The long-term vision of our group is to establish metabolic pathways as both mechanistic drivers of depression and tractable therapeutic targets, whether as adjuncts to existing antidepressant strategies or as independent treatment avenues, ultimately contributing to more personalized and effective care for patients with depression.
Oncometabolism
To improve the treatment of liver cancer, several innovative therapeutic strategies are investigated, which are targeted at metabolic adaptations that are (partly) driving disease progression. In addition, biomarker discovery to predict response to treatment is an area of ongoing research. Both directions are facilitated by fundamental research into the tumor microenvironment and metabolic profiles of tumors and are performed using a range of experimental models.
This research is conducted within the OncoMetabolic group that collaborates with the department of Precision Medicine.