Speaker: Keisha Cook (Clemson University)
Live cell imaging and single particle tracking techniques have become increasingly popular amongst the mathematical biology community. Lysosomes, known for endocytosis, phagocytic destruction, and autophagy, move about the cell along microtubules. Intracellular transport of lysosomes is carried out in membrane-bound vesicles by motor proteins. Single particle tracking methods utilize stochastic models to simulate intracellular transport and give rise to rigorous analysis of the resulting properties, specifically related to transitioning between inactive to active states. We find confidence in our methodology and develop a framework to understand how these properties play a role in determining an optimal frame rate for capturing live cells.
Biological systems are traditionally studied as isolated processes (e.g. regulatory pathways, motor protein dynamics, transport of organelles, etc.). Although more recent approaches have been developed to study whole cell dynamics, integrating knowledge across biological levels remains largely unexplored. In experimental processes, we assume that the state of the system is unknown until we sample it. Many scales are necessary to quantify the dynamics of different processes. These may include a magnitude of measurements, multiple detection intensities, or variation in the magnitude of observations. The interconnection between scales, where events happening at one scale are directly influencing events occurring at other scales, can be accomplished using mathematical tools for integration to connect and predict complex biological outcomes. In this work we focus on building statistical inference methods to study the complexity of the cytoskeleton from one scale to another by relying on two main components facilitating intracellular transport; that is microtubule network organization and cargo transport.
Time: April 14, 2023 2:30pm-3:30pm
Location: LeConte 118
Host: Paula Vasquez