Graduate Student Seminar with Simon Wang on Data-Driven Analysis Reveals Cellular Tuning of Size and Growth Rate on Organelle Level

A fundamental question in cellular biophysics is how the multiple components of the cell are coordinately built to optimize physiological function. To tackle this problem, we construct a “rainbow” yeast strain by tagging multiple organelles with fluorescent proteins, which enables the measurements of sizes and numbers of multiple organelles in a large population of cells. The principal component analysis (PCA) reveals several organelle response modes that are consistent across various nutritional conditions. This data-driven analysis indicates that cellular compartmentalization enables independent tuning of cell size and growth rate to better adapt to the environment. In order to capture the organelle dynamics on the single-cell level, we are developing a deep-learning-based method to spectrally resolve various fluorescent proteins from bright-field fluorescent microscopy.