Dynamic, live-cell monitoring of T-cell states against presented peptides

The goal of this Phase I SBIR proposal is to demonstrate and advance a new technology, cell-MAPP (live Cell Monitoring Against Presented Peptides), that enables the unprecedented, dynamic monitoring of T cells to stimuli on a single cell basis. Cell-MAPP will be the first technology to produce continuous, flow-cytometry-like data on T cell states while monitoring live cells throughout stimulation by antigen exposure. Through antigen-multimer barcoding and post-cell-MAPP elution and T-cell receptor sequencing (TCRseq), this technique will connect millions of live T cell state trajectories and TCR sequences to their interactions with thousands of identifiable antigens. Cell-MAPP is expected to uncover insights such as the immunogenicity level of antigen candidates in vaccine design, validation of TCR binding by cancer neoantigens towards improved personalized vaccines, and determining the exhaustive potential of specific antigens. Upon the successful commercialization of this technology, cell-MAPP may be used to monitor T cell therapies such as CAR-Ts, T cell engagers, and checkpoint inhibitors. Phase I proof of concept work entails monitoring for 12 hours to observe state transitions of pre- activated cells. Phase II plans include extending analysis to >48 hours and longer for primary activation analysis. The utility of cell-MAPP has been confirmed with potential customers (see letters of support). The currently available tools for studying immune cells are generally divided between two groups: 1) technologies that offer extremely detailed snapshots in time such as flow cytometry, CyTOF, and scRNA seq, and 2) those that offer crude, but functional results such as ELISPOT and cell proliferation assays. While highly useful in their respective ways, these technologies do not allow for the functional monitoring of single T cells throughout stimulation. Cell-MAPP will enable the continuous monitoring of live, individual T cells over time enabling high throughput analysis of 1,000s+ antigens over millions of T cells and connect TCR sequence to bound antigens. Previous studies demonstrating proof of concept for cell-MAPP have been conducted by Prof. Jennifer Dionne’s lab at Stanford University. Prof. Dionne (consultant) and her team (including PI Dr. Jack Hu) have pioneered Raman spectroscopy, combined with ML, to detect and identify whole cell states including macrophage polarization (M0/M1/M2), T cell versus CAR-T designation, distinct melanoma cell lines, and over 40 bacterial species in a variety of complex sample types (blood, plasma, sputum, etc.). Macrophage and CAR-T studies have demonstrated cell classification accuracies generally over 90% (see Preliminary Data). This Phase I work entails developing algorithms to map cell Raman signatures to known T cell states (Aim 1); dynamic live T cell monitoring through state transitions enabled by an integrated incubator flow cell (Aim 2); and creating a library of 100+ Raman- and DNA-barcoded antigen probes capable of high throughput multiplexing (Aim 3). These Aims will result in the proof of concept for a technique capable of dynamically sensing T cell states of ~1M cells exposed to ~1,000s of antigens at the single cell level every 5 minutes for 12+ hours.