Understanding the complex multiscale regulatory feedbacks between genes, proteins, cell behaviours, and tissue-scale mechanics is a major challenge, which my team addresses with computational models. Depending on the specific question and the prior biological knowledge, we craft our models using approaches such as ordinary differential equations or multiscale cell-based models with cellular Potts or center-based formalisms.

Benjamin Planterose Jiménez [post-doc] is modeling cellular fate decision making in the postembryonic M lineage of C. elegans by fitting dynamical system models with experimental omics data. With a wide international academic experience (Spain, UK, Switzerland and Netherlands) and originally trained as an experimental biochemist, he specialized in computational biology, bioinformatics and biostatistics during his PhD (Erasmus MC, Rotterdam), with a focus on human epigenomics. Outside the lab, he enjoys playing a variety of musical instruments and jamming with other musicians. Benjamin is co-supervised by the Tsingos and Ten Tusscher groups.

Saber Shakibi [post-doc] is modelling cellular migration via a hybrid model of cell and extracellular matrix. He uses a combination of cellular Potts and bead-spring models to study cell migration in the presence of the extracellular matrix. Originally trained as a structural engineer, he specializes in multiscale modelling and computational material science in mechanobiology with a specific focus on cancer.

Nienke Tan [PhD candidate] is investigating how membrane-actin linkers shape cell and tissue morphology in the C. elegans intestine using computational models. She has a background in mathematics and bioinformatics & systems biology. In her free time, she enjoys playing video/boardgames and cooking.

Cell migration is a fundamental process in developmental biology. It is also critical in early cancer metastasis. If we understand what causes some cells to move and others not to, we could put an early stop to cancer cell migration.

Even in genetically identical cancer cells, migration is highly heterogeneous. Some cells do not migrate at all, while others migrate individually or as a collective [1]. Structural and mechanical properties of the extracellular matrix are known to affect this migratory phenotype [2].



This project will build on previous work combining a cellular Potts simulation with a coarse-grained model of collagen fibers [3] to simulate a tumour spheroid embedded in a collagen matrix. The major aims are:

• Develop a model of cell migration in fibrous matrix.
• Calibrate the model to confocal microscopy data from experimental collaborators working with tumour spheroids.
• Characterize how cell and matrix parameters affect the migratory phenotype.

This project is funded by the NWO grant VI.Veni.222.323.

C. elegans is a small nematode worm and a fascinating model organism. One of its salient characteristics is eutely - the fact that each individual worm has a specified and fixed number of somatic cells - devoid of any randomness. Every single somatic cell division occurs at a predefined time, with a predefined division axis, and resulting in a predefined pattern of daughter cell fates. How does the worm achieve this clockwork precision?



In this project we take a closer look at the C. elegans postembryonic M cell lineage. The offspring of the M cell undergo a different number of cell division rounds, and give rise to multiple cell fates. A few key mutations completely throw off the balance between proliferation and differentiation in this lineage, leading to massive overproliferation [1]. Several other mutants maintain the correct number of cell divisions, but show fate transformations [2]. Furthermore, many mutants lose their incredible precision. We will unravel the underlying control mechanisms using ordinary differential equation-based models informed by RNA sequencing data provided by collaborators.
In a first step, we developed a quantitative model of the Wnt/β-catenin Asymmetry (WβA) pathway determining cell fate specification in larval stage L1 [3]. Our work demonstrates that the current "textbook knowledge" is insufficient to explain anterior-posterior fate specification in the early M lineage. Currently, we are developing a model of the transitions between quiescence, proliferation and differentiation in the lineage.

This project is a collaboration with the Ten Tusscher group and the Van den Heuvel group.

The vertebrate thymus is the organ where immature T-cells of the immune system differentiate into either αβ or γδ cells, and then undergo thymic selection to prevent auto-immunity. In addition, the thymus also consists of supportive scaffold cells, the thymic epithelial cells. Fish model organisms allow to study the coming and going of T-cells in the living organism, giving unique insights into the turnover of thymocyte populations, while also enabling genetic manipulations [1].



Based on quantitative fluorescence microscopy data of the Medaka (Oryzias latipes) larval thymus, we previously developed and calibrated a spatial center-based model [2]. We used this model to understand how cell-intrinsic signals and extrinsic signals emanating from thymic epithelial cells (TECs) affect the balance of T-cell fates. We later extended the model to explore predictions when introducing a single mutated cell into the system [3]. Mutations in both the interleukin-7 and the Notch signalling pathways promote thymocyte proliferation, consistent with findings in patients of T-cell acute lymphoblastic leukemia (T-ALL). Interestingly, the model was able to pinpoint that the 3D architecture of thymic epithelial cells differentially affects wildtype and mutated cell lineages. Hence, the model predicts that these cells are an underappreciated therapeutic target. The model and source code are available on Zenodo [4].