Understanding the mechanism of maintenance and differentiation of stem cell populations is a central scientific issue on the path to realizing thefull therapeutic potential of stem cells in the treatment of human disease. Characterizing the cellular signals that maintain and regulate stem cell populations will lead to a new appreciation of the principles by which living organisms control growth and development and to the development of new technologies to utilize stem cells in health applications including tissue and organ regeneration. The proposed study, by characterizing the factors that regulate stem cell proliferation, differentiation, and specification in a model system, will reveal new principles of stem cell niche organization. The research proposed is designed to answer the central unanswered question in stem cell biology: what is the mechanism by which cell-cell communication instructs cellular behavior in stem cell populations? Because of its amenability to the full spectrum of methods from modern systems and genomic biology, as well as the remarkable regenerative abilities of plants, the shoot apical meristem (SAM) of the flowering plant Arabidopsis thaliana will be used as a model system. Two key signaling pathways, and their interactions, will be studied: the CLAVATA-WUSCHEL peptide signaling pathway and the hormonal cytokinin signaling pathway. The result of accomplishing the aims of the proposal will be a new level of understanding of stem cell niches, and the principles of feedback, signaling, and local cell type response that allow them to serve as permanent and regulated reservoirs of cells for creation of tissues. The experiments will lead to a new level of sophistication in our understanding of development, and of stem cell regulation in plants; and therefore to a more complete understanding of, and comparative view of, the principles of stem cell regulation in both plants and animals.
Each aim will use non-invasive live imaging techniques that are particularly effective in plants, because their stem cells are near the surface, and transgenic reporter transgenes, as well as an extensive array of mutations that change the regulation of stem cell behavior. The goal of the first aim is a full characterization of the mechanisms by which alterations in the levels of the hormone cytokinin affect the different domains of the SAM stem cell niche, both directly, via regulation of the peptide signaling pathway, and by the multiple feedbacks of the hormone signaling system on itself.
The second aim i s a systems approach to characterize the cytokinin signaling pathway from receptor to response regulator transcription. Using the novel TRAP-seq and INTACT methods, cytokinin target genes will be characterized at cellular and molecular resolution.
The third aim i s an unbiased yeast-one hybrid screen to identify transcriptional regulators of cytokinin signaling, and cytokinin biosynthetic genes. The fourth and final aim is to use the data generated through these approaches to parameterize computational models that encapsulate the complex feedbacks in the system, to test new hypotheses of the mechanism by which cell-cell communication regulates the SAM stem cell niche.
Understanding how stem cell populations are maintained in tissues is a central question that needs to be answered if we are to realize the full therapeutic potential of stem cells in the treatment of human disease. Characterizing the cellular signals that maintain and regulate stem cell populations will lead to the development of new technologies to utilize stem cells in health applications such as tissue and organ regeneration for the treatment of disease. The proposed study of stem cell niches in a model organism, by characterizing the factors that regulate stem cell proliferation, differentiation, and specification, will reveal new principles of stem cell niche organization, and will allow for the development of predictive computational models that can be applied to human stem cell niches, thereby aiding in the development of new therapeutic technologies.