Principles of Mechanochemical Signal Integration Underlying Developmental Robustness

发育稳健性背后的机械化学信号整合原理

• 批准号: 10715011
• 负责人: Tony Yu-Chen Tsai
• 金额: $ 36.93万
• 依托单位: WASHINGTON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-22 至 2028-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10715011
• 关键词: Address; Adhesions; Artificial tissue; Biochemical; Cadherins; Cell Adhesion; Cells; Computer Models; Congenital Abnormality; Development; Developmental Biology; Disease; Disease model; Embryonic Development; Engineering; Environment; Event; Genetic; Image; In Vitro; Individual; Malignant Neoplasms; Mechanics; Morphogenesis; Pathology; Pattern; Positioning Attribute; Research; Shapes; Signal Pathway; Signal Transduction; Testing; Therapeutic; Tissue Engineering; Tissues; Work; Zebrafish; cell type; embryo tissue; empowerment; experimental study; improved; in vivo; innovation; mechanical force; mechanical signal; morphogens; multidisciplinary; novel; novel strategies; programs; public health relevance; response; tool

Project Summary / Abstract My research program aims to understand cellular mechanisms underlying robust embryonic tissue patterning. Despite environmental fluctuations, tissues develop nearly identical patterns, shapes, and sizes among different stage-matched individuals. In contrast, artificial tissues grown in vitro are highly variable, limiting their value for disease modeling. How single cells can reliably sense and control tissue parameters remains an important open question in both developmental biology and tissue engineering. Departing from the traditional focus of patterning control by biochemical signaling, my research aims to understand how cells integrate biochemical and mechanical signals to detect and respond to changes in tissue pattern and shape. We are empowered by our expertise in in vivo live imaging, zebrafish genetics, computational modeling, and innovative approaches to manipulating tissues’ biochemical and mechanical environments. Using these multidisciplinary tools, we will test how cells incorporate mechanical information to detect tissue-scale changes that are challenging to detect by morphogen signaling alone. First, we will determine whether cells can sense the cell type identity of their neighbors through cadherin-based adhesion, and use this information to modify cell fate decisions and correct errors in tissue patterning. Second, we will identify mechano-responsive morphogen signaling pathways and investigate whether mechanochemical crosstalk allows the cells to infer their relative positions more accurately in tissues undergoing morphogenesis. By revealing how tissue parameters are encoded by biochemical and mechanical signals, and how cells decode mechanochemical signals to sense and control changes in tissue parameters, our research will elucidate the information flow from tissue-scale changes to cellular responses. Our work will establish cell adhesion and mechanical force as key channels of tissue information directing accurate cellular decisions in early tissue patterning events, a novel paradigm that will impact our understanding of development, mechanical consequences in diseases, and engineering strategies for artificial tissues.

项目摘要/摘要