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SZABADOS TAMÁS, BAKÁCS TIBOR. SUFFICIENT TO RECOGNIZE SELF TO ATTACK NON-SELF: BLUEPRINT FOR A ONE-SIGNAL T CELL MODEL. J BIOL SYST 2011. [DOI: 10.1142/s0218339011003919] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Current consensus postulates that the class I-antigen processing system is evolved to present microbial antigens to specific T cells. Since such cells are rare and short-lived, they require three to five days to attain fighting strength. During this critical period he innate immune system holds back the briskly multiplying pathogens. Nevertheless, a T cell response is measurable in the lymph nodes draining the infection site within 12 to 18 h. In order to explain this paradox here we suggest a new T cell model. This is based on the observation that T cells require continuous contact of the T cell receptor (TCR) with selecting self-peptide–major histocompatibility complex (MHC) molecules in the periphery for their survival. We postulate that a dynamic steady state, a so-called coupled system is formed through low affinity complementary TCR–MHC interactions between T cells and host cells. Under such condition it is sufficient to recognize what is self in order to attack what is not self. A coupled system is regulated via soluble forms of peptide–MHC and TCR molecules by the law of mass action. In a coupled system one signal is sufficient for T cell activation. The new model implies that a significant fraction of the naive polyclonal T cells are recruited into the first line of defense from the very outset of an infection, so the number of activated T cells is increased by several orders of magnitude compared to conventional models. The one-signal model also predicts that therapeutic administration of soluble agonist or antagonist T cell receptor ligands may be able to fine tune the homeostatic physiological regulatory mechanism and thus improve the treatment of some chronic diseases such as metastatic cancer, HIV/AIDS, and transplantation.
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Affiliation(s)
- TAMÁS SZABADOS
- Department of Mathematics, Budapest University of Technology and Economics, Műegyetem rkp 3, Budapest, 1521, Hungary
| | - TIBOR BAKÁCS
- Alfréd Rényi Institute of Mathematics, Hungarian Academy of Sciences, Reáltanoda u 13-15, Budapest, 1053, Hungary
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