Computational modelling of morphogenesis and biomechanics
Our research uses mathematical and computer simulation techniques to investigate questions in plant development. Working in close collaboration with experimental biologists, we develop cellular-level simulation models of hormone signaling and patterning in plant tissue. These models involve a biochemical aspect, genes, proteins, hormones, combined with growing, changing geometry as cells divide and tissues grow. We are interested in the interaction between these two processes. How genes control physical properties of cells resulting in growth, and how the resulting change in geometry and physical forces feeds back on signaling and gene regulation. With this in mind, we are researching methods to quantify mechanical properties in plant tissues, to facilitate the construction of biophysically-based simulation models of plant growth. We are always looking for motivated students, interns and postdocs that are interested in applying their skills to questions in plant development and simulation modelling. Please contact Richard Smith for more information.
Much of our research involves the precise tracking of cell shape change, either from growth or elastic deformation. Since plants display symplastic growth, considerable information about morphogenesis can be obtained by looking at shape change in the surface layer of cells. However, in many systems, the surface layer of cells is not flat, and cell shape information is lost when doing max projections of confocal image data onto a plane. To address this problem, we have developed specialized software (www.MorphoGraphX.org) for the quantification of curved surface layers of cells. Working somewhere between 2 and 3D, MorphoGraphX is able to turn 3D confocal image stacks into curved surface images, which are then processed with standard algorithms we have adapted for this purpose. We are now extending our software for full 3D cell segmentation, fluorescence quantification, shape analysis, and other image processing problems as our research demands.
Cellular Force Microscopy
Cellular force microscopy (CFM) is a new micro-indentation technique (Routier-Kierzkowska et al. 2012) that we have developed in collaboration with the Nelson lab and Femtotools. Sample stiffness is measured by indenting a thin probe connected to a force sensor. The recorded force and displacement are then used to determine the stiffness. Similar to atomic force microscopy (AFM), CFM uses computer controlled actuators to move the probe and can be used to create high-resolution stiffness maps as well as height maps. Some advantages of CFM are the wide range of forces that can be measured, filling the gap between AFM and load cells. CFM also has greater geometrical freedom; it is able to make large movements (up to cm's) and its long slender probe can access areas that a cantilever cannot. The CFM system is also highly flexible and can be used in combination with various optical microscopes, including both upright and inverted confocal systems.
Morphogenesis during early Arabidopsis embryo development
Early embryo development provides an excellent system to study morphogenesis. In this system cell expansion, cell division, and genetic activity can be followed cell by cell in great detail. In collaboration with the Weijers lab, we use state of the art 3D imaging and molecular techniques to link gene and signaling networks to morphogenesis in plants. We test our hypothesis by using 3D spatial simulation models, developed in collaboration with the Prusinkiewicz lab, that are based on cell shape information extracted from sample tissue using MorphoGraphX. By developing a close integration between our simulation and imaging environments we will be able to use gene expression marker levels as direct input to our models, as well as to test model outputs. Our goal is to move one step closer to a true virtual plant tissue.
Cell expansion during seed germination
Another great systems for exploring the link between genetics and cell expansion is the mature Arabidopsis embryo. During germination a decision is made based largely on environmental cues to break dormancy and commence growth. Driven by the gibberellic acid (GA) signaling pathway, this binary growth switch represents an ideal system for examining the relationship between the induction of growth promoting gene expression and organ morphogenesis. In collaborating with the Bassel lab, Birmingham, we are developing methods to quantify cell shape change and gene expression in 3D. These data are being used to feed a physically-based finite-element (FEM) simulation model of the embryo that we are using to explore the regulation of cell expansion in a geometrically and mechanically realistic environment.