Ruth Baker – Mathematical Institute, University of Oxford (email@example.com)
In tissue growth and morphogenesis, cells make fate decisions in response to chemical gradients, many of which incorporate spatial information that instruct the future development of tissues and structures. However, these gradients are noisy at any level, raising the question of how cells read and respond faithfully to these spatial-information-incorporated chemical stimuli. Recently, new experimental data on early embryo development indicates that noise may play an important role in the regulation of cell fate decisions. We have developed hybrid spatial models to study how noise helps cells make fate decisions that, in return, maintain further system development. In particular, two systems are studied: zebrafish hindbrain rhombomere formation; and early mammalian embryo development. Our approaches allow us to recognize and validate mechanisms and principles underlining spatial cell fate decision dynamics during development and growth.
Angiogenesis, the growth of new blood vessels from existing ones through sprouting or splitting, is crucial for a range of physiological or pathological phenomena, ranging from wound healing to tumor development. In order to achieve fine-level control of angiogenesis in these mechanisms, we are developing multiscale, computational models of collective endothelial cell behavior during angiogenesis based on the cellular Potts model. In the first part of the talk, we will discuss cell behavior at the front of advancing angiogenic sprouts. The traditional view is that a specialized endothelial cell, the tip cell, leads the sprout. It is followed by a second type of endothelial cell, called the stalk cell. However, two experimental groups have shown independently that tip and stalk cell fates are reversible, and that cells compete for the tip cell position, a phenomenon coined ‘tip cell overtaking’. The groups could not agree on whether tip cell overtaking is actively regulated genetically, through the Notch1-Dlll4 pathway, or whether it is due to non-functional ‘cell mixing’. In support of the ‘cell mixing’ idea, tip cell overtaking emerges naturally in our models of angiogenesis. After introducing a dynamic Notch1-Dll4 model into each cell, we found that our ‘cell mixing’ model of tip cell overtaking can reproduce the evidence in favor of the ‘genetic control’ model. The two initial cell-based models of angiogenesis that we have used in these studies of tip-cell overtaking did not include the extracellular matrix (ECM), the jelly materials (e.g, fibrin or collagen) that the endothelial cells live in. In vitro studies have shown that the chemical composition and the mechanical properties of the ECM are key to the ability of endothelial cells to form blood vessel like structures. The second part of the talk will, therefore, discuss our attempts to model the mechanical and chemical cell-ECM interactions, and explain how the extracellular matrix could control and coordinate endothelial cell behavior during angiogenesis.
During somitogenesis the vertebrate embryo segments at regular time intervals. Underlying this periodicity is a molecular oscillator known as the somitogenesis clock. Using real-time reporters for clock gene expression, the dynamics of the clock can be experimentally interrogated, thus imposing constraints on theoretical models. In this talk I will present results from a collaborative project in which the effect of different drug treatments on the somitogenesis clock are recorded using a real-time reporter. I will then describe how mathematical models are used help to interpret the experimental data and explore underlying mechanisms.
Bone Morphogenetic Proteins (BMPs) act in developmental pattern formation as a paradigm of extracellular information that is passed from an extracellular morphogen to cells that process the information and differentiate into distinct cell types based on the morphogen level. Numerous extracellular modulators and feedback regulators establish and control the BMP signaling distribution along the dorsal-ventral (DV) embryonic axis in both Drosophila and zebrafish to induce space and time-dependent patterns of gene expression. To identify how the BMP patterning mechanism evolved in Drosophila vs. zebrafish, we have developed a new multi-objective optimization strategy. Since patterning in both systems relies on a common set of inhibitors and regulators, we developed a core-model and identified whether there is a single set of biophysical parameters that, when fit to both Drosophila and zebrafish data, is able to explain both patterning mechanisms. Intriguingly, there is a significant trade-off between the model fitness and different parameters are required to be independently tuned for a single mechanism to fit both types of data. We extended the framework and identified the minimal set of parametric differences that must be present for one core model to fit both patterning contexts.