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M.S. Defense: Jordan Force
May 9, 2022 @ 10:00 am - 11:00 am EDT
Title: Combining LC-MS/MS Peptide Sequencing with MHC-I Presentation Predictions
Student: Jordan Force
Major Advisor: Ion Mandoiu
Associate Advisors: Mukul Bansal, Derek Aguiar
Date/Time: Monday, May 9th, 2022, 10:00 AM
Location: HBL 1102
Meeting link: https://uconn-cmr.webex.com/uconn-cmr/j.php?MTID=mff2ba0267073bc8f143a7fd6fa916b86 (password is PMhbMYqm294)
Abstract: A critical part of cell-mediated immunity is the surveillance of MHC-I presented peptides by CD8+ T-cells. Understanding the specificity of MHC-I alleles will be important for designing vaccines and personalized cancer immunotherapy. Broadly, there are two types of experiments that can be done to understand this specificity. The first are experiments in which the strength of binding between an allele and peptide is measured in a test tube, and this is done for many, many peptides. Then, machine learning models are trained to predict this binding strength. The second are experiments in which MHC-I presented peptides are removed from the surface of cells, and sequenced using Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS). This yields a collection of mass spectra that must be matched to a database of peptides. In this thesis, I use the first class of methods to improve the database search step of LC-MS/MS sequencing.
