BMP Signaling and the Robustness of In Vivo Stem Cell Decisions

Texas A&M Engineering Experiment Station, College Station TX

Investigators

Abstract

Gaining the ability to reproducibly control stem cell differentiation would advance fundamental knowledge of cell and tissue biology. This would have broad impacts on society and human health. It is well-known that stem cells make decisions based on signals they receive from neighboring cells. A quantitative understanding of this process is required for reliable human control of stem cell differentiation. However, this crucial piece of the puzzle, in the form of a predictive mathematical model, is currently missing. To address this conceptual gap, researchers from Texas A&M University will employ light microscopy, genetics, and mathematical approaches to quantitatively probe the relationship between signaling and stem cell differentiation. The goal is to create a mathematical model of this relationship that can be used to design efficient and reliable protocols for controlling differentiation. The research will focus on the Bone Morphogenetic Protein (BMP) signaling pathway and its role in germline stem cell (GSC) decisions in the Drosophila ovary. The highly-conserved BMP pathway is one of many major regulators of stem cell decisions across the animal kingdom, and in Drosophila female GSCs, it is the central hub in dictating differentiation vs self-renewal decisions. In GSCs and in differentiating cells, known as cystoblasts (CBs), positive and negative feedback loops regulate the BMP pathway. The hypothesis is that these feedback loops enhance the robustness of stem cell decisions, and as such, must be accounted for when designing protocols to control differentiation. Therefore, the project will investigate these feedback loops in both GSCs and CBs to incorporate them into the model. Advanced confocal microscopy techniques, such as raster image correlation spectroscopy (RICS) and fluorescence recovery after photobleaching (FRAP), will be used to measure biophysical parameters of the BMP pathway and to obtain time courses of concentrations of fluorescently-tagged BMP pathway components. These measurements will be used as model constraints or to test model predictions. Experiments will be done under wildtype and genetically perturbed conditions, such as loss of feedback loop components. Precise perturbations to the pathway will be achieved through optogenetics. The outcome of the project is expected to be a predictive, mechanistic model of BMP pathway regulation of stem cell decisions, which will have several positive impacts. First, due to the high conservation of the pathway, a detailed mechanistic model impacts the understanding of BMP signaling in other organisms. Second, the quantitative, mechanistic description of the system will form the foundation for external manipulation of stem cell decisions, such as designed de-differentiation. Finally, the results will provide an in vivo complement to stem cell cultures, and as such, will be a model system to advance knowledge of stem cell biology within native context. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.