All-in-one Detection of T cells - Specificity, Phenotype, and Function
T cells are important as a type of immune cell for fighting infections and cancers, thus monitoring their behavior is a critical step in understanding and engineering T cell responses. T cells detect pathogens by recognizing their short peptide sequences (epitopes) with exquisite specificity. It is estimated that there are ~107 T cell specificities in a human body to ensure a good epitope coverage for pathogen recognition. Upon activation, T cells secrete an array of proteins that orchestrate the action of other white blood cells for infection clearance, or directly induce apoptosis of infected cells. Depending on the antigen experience, T cells with a range of differentiation stages are circulating in the body. As a result, there is a high degree of heterogeneity within the T cell population, making them challenging to study at a systematic level, especially when the availability of patient samples is very limited. The goal of this project is to address the limitations of current flow-cytometry-based technology and enable highly multiplexed phenotypic and functional profiling of T cells with many specificities. Towards this goal, we will pool expertise from various disciplines including protein/celllular engineering, molecular dynamics modeling, and statistics.
Efficient Estimation of Binding Free Energies between Peptides and an MHC Class II Molecule Using Coarse-Grained Molecular Dynamics Simulations with a Weighted Histogram Analysis Method
Published in Journal of Computational Chemistry, 2017