Whole-protein screening and multi-modal profiling of antigen-specific CD4+ T cells at single-cell resolution
Abstract
Systematic whole-protein screening and comprehensive profiling of antigen-specific CD4+ T cells are crucial for advancing vaccine design and cancer immunotherapies, yet remain technically challenging. Here, we present a high-throughput platform that utilizes large-scale class II single-chain trimer libraries to detect antigen-specific CD4+ T cells, while simultaneously profiling their antigen specificity, TCRα/β sequences, MHC restriction, whole transcriptomes, and patient/timepoint origins at single-cell resolution. Upon rigorous platform validation, we screened the full SARS-CoV-2 spike receptor binding domain in a longitudinal cohort of 22 participants, identifying 2,188 antigen-specific CD4+ T cells and showing key metrics defining the immunogenicity of class II-restricted viral antigens. We further extended the platform to whole-protein screening of HPV-16 E6/E7 in a cohort of precancerous patients, indicating HPV-specific CD4 TCRs that, upon extensive characterization, demonstrate strong therapeutic potential. By integrating high-throughput antigen screening with high-dimensional, multi-modal cellular characterization, our approach provides detailed insight into CD4+ T cell immunity, potentially guiding vaccine design and next-generation TCR-based cancer immunotherapies. Rapid methods to identify antigen-specific T cells are essential for developing targeted immunotherapies. Here the authors present a high-throughput MHC class II single-chain trimer platform for the comprehensive profiling of CD4+ T cells, enabling the rapid identification and characterization of virus- and tumour-specific T cell receptors (TCR) at single-cell resolution.
Fields of Study & Subjects
vaccines and immunoinformatics approaches
Cancer Immunotherapy and Biomarkers
Immunotherapy and Immune Responses
Publication details
- Journal / source
- Nature Communications
- Publisher
- Springer Science and Business Media LLC
- Volume
- 17
- Issue
- 1
- Publication date
- 12 May 2026
- Language
- EN