bioRxivBiophysics
Catch bond models may explain how force amplifies TCR signaling and antigen discrimination
H.-K. Choi, P. Cong, C. Ge, A. Natarajan, B. Liu, Y. Zhang, K. Li, M. N. Rushdi, W. Chen, J. Lou, M. Krogsgaard, C. Zhu
Abstract
Central to T cell biology, the T cell receptor (TCR) integrates forces in its triggering process upon interaction with peptide-major histocompatibility complex (pMHC)1-3. Phenotypically, forces elicit TCR catch-slip bonds with strong pMHCs but slip-only bonds with weak pMHCs4-10. While such correlation is commonly observed, the quantitative bond pattern and degree of "catchiness" vary. We developed two models based on the structure, elastic properties, and force-induced conformational changes of the TCR-pMHC-I/II complexes to derive from their bond characteristics more intrinsic parameters that underlie structural mechanisms, predict T cell signaling, and discriminate antigens. Applying the models to 55 datasets of 12 {beta}TCRs and their mutants interacting with corresponding pMHCs without coreceptor engagement demonstrated the ability for structural and physical parameters to quantitatively integrate and classify a broad range of bond behaviors and biological activities. Comparing to the generic two-state model for catch-slip bond that also fits the data, our models can distinguish class I from class II MHC systems and their best-fit parameters correlate with the TCR/pMHC potency to trigger T cell activation, which the generic model cannot. The models were tested by mutagenesis using structural analysis, bond profile measurement, and functional assay of a MHC and a TCR mutated to alter conformation changes. The extensive comparisons between theory and experiment provided strong validation of the models and testable hypothesis regarding specific conformational changes that control bond profiles, thereby suggesting structural mechanisms for the inner workings of the TCR mechanosensing machinery and plausible explanation of why and how force may amplify TCR signaling and antigen discrimination.
- organism: human
- assay: proteomics
- research focus: cell signaling & trafficking
- approach: statistical model
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