Conference ID: 636-589-64450
The Ca2+ modulated pulsatile secretions of glucagon and insulin by pancreatic α and β cells play a key role in glucose metabolism and homeostasis. However, how different types of cells in the islet couple and coordinate to give rise to various Ca2+ oscillation patterns and how these patterns are being tuned by paracrine regulation are still elusive. Here we develop a microfluidic device to facilitate long-term recording of islet Ca2+ activity at single cell level and find that islets show heterogeneous but intrinsic oscillation patterns. The α and β cells in an islet oscillate in antiphase and are globally phase locked to display a variety of oscillation modes. A coarse-grained mathematical model is constructed and compares well with the experiments. The model generates two-dimensional Arnold tongues and maps out the dependence of the oscillation modes on the paracrine interactions between α and β cells. Our study reveals the origin of the islet oscillation patterns and highlights the role of paracrine regulation in tuning them.
Chao Tang is a Chair Professor of Physics and Systems Biology and the Executive Dean of the Academy for Advanced Interdisciplinary Studies at Peking University. He had his undergraduate training at the University of Science and Technology of China and received a Ph.D. degree in Physics from the University of Chicago. In his early career, he worked on problems in statistical physics, condensed matter physics, dynamical and complex systems. His current research interest is at the interface between physics and biology, in particular in quantitative systems biology and biological physics. He was a tenured full professor at the University of California San Francisco before returning to China full-time in 2011. He is a Fellow of the American Physical Society, an Academician in the Chinese Academy of Sciences, the founding director of the interdisciplinary Center for Quantitative Biology at Peking University and the founding Co-Editor-in-Chief of the journal Quantitative Biology.