Computational modeling of adhesion-based cell sorting in label-free microfluidic platform
ORAL
Abstract
Identifying and isolating cells that express desired molecular surface markers is required in a variety of applications in the biological sciences, cell therapy, and medical diagnostics. We develop a biophysical approach for high-throughput and label-free sorting of cells by their affinity for target ligands by molecular surface markers. Our approach consists of a microchannel decorated with periodic skewed ridges and coated with adhesive molecules. We use computer simulations to examine the effects of specific and non-specific adhesion on cell trajectories. Our specific adhesion model captures the adhesion kinetics and accounts for the molecular binding/unbinding events due to specific interactions of adhesive molecules and corresponding ligands. We find that specific and non-specific adhesion lead to distinct parameters of cells trajectories such as cell interaction time with the ridge, which can be used to identify different types of cell interaction. Furthermore, cell trajectories are sensitive to adhesion level and therefore can be used to sort cells with different ligand expression.
–
Presenters
-
Fatima Ezahra Chrit
Georgia Institute of Technology
Authors
-
Fatima Ezahra Chrit
Georgia Institute of Technology
-
Alan Liu
Georgia Institute of Technology
-
Avi Gupta
Georgia Institute of Technology
-
Todd Sulchek
Georgia Institute of Technology
-
Alexander Alexeev
Georgia Institute of Technology