Finding effective T-cell receptors for infectious diseases based on receptor sequences
Funded at Dartmouth College · NIH-11449453 · Data updated 2026-11-12
A patient-friendly platform will help researchers find T-cell receptors that can recognize harmful microbes using data from TCRs, microbiome, and genetics.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Dartmouth College NIH-funded |
| Lab location | 1 site (Hanover, United States) |
| Project start | September 1, 2026 |
| Project end | August 31, 2031 |
| Funding year | 2026 |
| Award (this year) | $717,139 |
| NIH project number | 1R01AI195878-01A1 |
| Project ID | NIH-11449453 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates are individuals with infectious diseases or immune system conditions whose data could help refine TCR-target mappings and therapies.
✕Less likely to help
Patients without infectious diseases or immune-related conditions may not directly benefit from this specific tool.
What this research studies
This project aims to build a user-driven database and search tool that links T-cell receptors to their potential microbial targets using publicly available data. It will extract TCR sequences from single-cell RNA data with TRUST4, even when explicit TCR assays aren’t done, and categorize T cells by subtype and state. Users can search for TCRs that recognize the same antigen, using sequence similarity, motifs, or advanced embeddings, to identify candidates that may activate protective immune responses. The effort will connect TCRs to their microbial targets by reconstructing repertoires and incorporating HLA and microbiome context. The resulting platform could guide future research and development of targeted immunotherapies for infectious diseases.
Why it matters
Potential benefit: If successful, patients could benefit from faster identification of protective TCRs and better-informed strategies for vaccines and therapies against infections.
How similar studies have gone: Similar approaches using TCR data and single-cell RNA sequencing have shown promise in identifying repertoire-wide patterns, but this project aims to integrate multiple data types in a new searchable platform.
Where this research is happening
-
Dartmouth College
Hanover, United States Active
Researchers
- Principal investigator: Song, Li — Dartmouth College
- Study coordinator: Song, Li
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About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page.