Dr Athanasius Maree

Publication

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Research

The general objective of his unique approach to Multi-level Modelling of Morphogenesis is to generate direct predictions of development, using models with experimentally determined parameters integrated within multi-scale frameworks, which can be verified experimentally through genetic, molecular and biophysical perturbations. To do so, the Marée Lab has developed an extensive computational environment for cell-based modelling, Excalib, which has central importance to unravel how (sub) cellular processes drive cell shape and topology, in its turn steering development. To validate and challenge the models, he is continuously developing novel image analysis tools, as well as directly linking them to the modelling environment. Moreover, the Marée Lab has developed high-throughput imaging strategies for multi-cellular tissues that are currently for application in biomedical research.

Crossing scales, information processing through excitable media asks questions how even a point mutation in an ion channel can not only change the bursting of a single neuron, but fundamentally modify the collective behaviour of neuronal tissue; it questions how the patterning changes the structure of the organism and the structure of the organism changes its patterning. Combining Extracellular Multi-Electrode Array (MEA) measurements, big data analysis and mechanistic modelling, we aim to to unravel how single point mutations can affect brain functioning. 

Teaching

Biology is undergoing a major transition into Big Data, AI-driven Research, Mathematical and Computational Approaches, Systems Thinking and Multidisciplinary. 

This transition concurrently requires a fundamental transition in teaching. I have therefore developed a unique approach to teaching Systems and Predictive Biology to both undergraduate and postgraduate students. 

The key concept is that students from the first moment onwards should be immersed in actively modelling and exploring biological systems. All my teaching is therefore "flipped learning", in which all material is provided beforehand through pre-recorded lectures, slides and reading material, while all interactions with students are in the form of active workshops, in which students themselves discover underlying mechanisms and principles (and often even more than we imagined!). Key elements are:

• In-depth teaching and demonstrations of leading edge computational and mathematical foundations for multi-level modelling of processes in biology.
• Transfer of knowledge on dealing with the complexity of biological processes; how to design and optimise models; how scientifically sound conclusions can be drawn, and the pitfalls involved.
• Compare and contrast the diverse model formalisms currently used for modelling, emphasising their relationship to the biological questions asked.
• Dissect biophysical processes at different levels of abstraction: from molecular, subcellular and cellular to multicellular, organism and ecosystem level, including how the different levels impact one another.
• Discover (through lectures, computational exercises and lab experiments) the diverse constraints involved in biological processes, such as biomechanics and information processing up to evolutionary mechanisms driving biological innovations.
• Explore how multiple mechanisms can act together to generate unexpected, biologically relevant behaviour.
• Challenge students to consider the nature of the research they are specifically interested in and the relationship between models and experiments within a well-formulated epistemological debate. Encourage students to leave their comfort zones.
• Stimulate students from diverse scientific backgrounds to interact and communicate across multifaceted barriers.
• Reveal how studying either animals or plants may require very different modelling strategies, but still can uncover common guiding principles.

Biography

Stan Marée pioneered the transition from classical pattern formation theories to multi-level modelling of morphogenesis. He has been acknowledged to be the first one ever to model an organism's full life cycle using integrated modelling approaches, specifically the life cycle of Dictyostelium discoideum. Throughout the years, he has continued to use his unique approach to multi-cellular systems to successfully show that principles of self-organisation, ingrained in well-established subcellular and cellular processes, can generate novel and useful insights on how organisms, across the kingdoms, are able to function. A good example of this approach is the multi-level experimental-modelling cycle that he led, together with Prof. Scheres from Wageningen University, to unravel how stem cells in the Arabidopsis root regulate asymmetric cell divisions that give rise to two new cell identities at the correct position. Through dissecting the underlying molecular circuit which operates in each cell, he found that it presents a highly robust bistable behaviour, due to two positive feedback loops involving the proteins SHR, SCR and the cell-cycle related players RBR and CYCD6;1. The physical location of the asymmetric stem cell division turned out to rely on the interaction of the plant hormone auxin and the protein SHR, its precise dynamics determined by the crossroads of two perpendicular morphogen gradients, which could all be tested and experimentally verified. In another experiment-model interaction he showed how strain rates and phytohormone signalling can explain plant responses to environmental signals, such as in hypernasty. Again, such insights could only be derived by integrating different levels of interaction within a spatial modelling framework. 

Through his ample experience in coordinating cross-disciplinary collaborations on diverse biological systems, ranging from Arabidopsis development to lymph node dynamics, Stann was successful in translating specific biological and biomedical problems into well-designed comprehensive mathematical forms, obtaining quantitative answers related to e.g. the estimation of the fitness of viral strains, HIV dynamics, diabetes disease progression and cellular contact times in immunology. 

Throughout his work he became used to bridging multiple scales of organisation. In high-resolution single cell models, Stan was able to show how cells can be induced to acquire and maintain polarity and complex shapes. An important conceptual shift of this work was that not only the intracellular biochemistry determined the shape of the cell, but that the shape in turn could cause internal spatiotemporal reorganisation, rendering traditional reductionist approaches futile. On the next level of organisation, Stan integrated the biophysical properties of single cells, their motility and interactions through intercellular adhesion, to study emerging phenomena on the level of multiple cells and tissues. Important findings were that cell shapes and cell shape changes, for example induced by chemotaxis and cell sorting,  can have a dramatic effect on tissue dynamics, to the point of inverting the direction of motion of individual cells. In a close collaboration with physicists and experimental biologists Stan then showed that cell adhesion and cortex contractility determine the cell patterning in the Drosophila retina. On yet another scale, organs arise through highly complex interactions between many cells of different types, involving gene regulatory networks, cell motion and tissue level properties. For example, by modelling the realistic 3D dynamics of a lymph node and making fine-detail comparisons with multi-photon microscopy data, we debunked the dogma that T cells are driven by an intrinsic stop-and-go motion. The modelling guided specific experiments that revealed that instead the T cell behaviour is dictated by the lymph node topology. Finally, he found that individual genes can even affect the ecological scale, by causing an eco-evo inevitability of spatio-temporal patterning in vector distribution.

Engagement

Together with the Grieneisen Lab (also at Cardiff University), we have extensive experience in brining more complex research questions to the broader public. This includes seminars at schools, open days and science-technology cross-overs.