Frontiers in ImmunologyImmunologyPeer-reviewed journal article
Evaluating the effects of CD8/CD4 on T cell function in terms of TCR-pMHC-coreceptor catch and slip bonds
Stefano TravaglinoiD, Amir Hossein Kazemipour AshkezariiD, Menglan LiiD, Valencia E. Watson, Peiwen CongiD, Larissa DoudyiD, Hyun‐Kyu ChoiiD, Cheng ZhuiD
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Abstract
BackgroundT cells interact with peptide-major histocompatibility complex (pMHC) via the T cell receptor (TCR) and coreceptor CD4 or CD8 depending on the MHC class. These interactions form catch and slip bonds depending on the pMHC activity. Coreceptors and bond profiles impact TCR triggering and antigen discrimination. MethodsBuilt upon our recent correlative analysis of TCR-pMHC catch bond with T cell function, we analyzed 26 pairs of T-cell-pMHC interactions to compare the correlations of their biophysical metrics with antigen-induced T cell responses in two situations: when the coreceptor is prevented vs permitted to bind pMHC. ResultsWe found that the force-based metrics of TCR bond with pMHC perform better than parameters measured in the absence of force either in situ at the T cell membrane or in fluid phase using purified ectodomain proteins as predictors of T cell activation and thymocyte selection in both cases when the contributions of coreceptors are absent and present. Moreover, CD8 or CD4 co-engagement with pMHC systematically increases these metrics and increases TCR sensitivity and specificity, indicating coreceptor-mediated amplification of, or conversion to, catch-bonds that enhances mechanical tuning of TCR responses. ConclusionOur findings highlight the importance of force in antigen recognition by the TCR and reveal that parameters derived from the bond profile, especially in the presence of coreceptor, are more informative predictors of T cell activation compared to conventional affinity-based measurements. These results offer mechanistic insights into the roles of catch bonds and coreceptors in TCR antigen recognition.
- organism: human
- assay: proteomics
- research focus: cell signaling & trafficking
- approach: statistical model
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