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The XV Collection: The Exquisite Precision of T Cell Receptors


by Avinash Bhandoola and Christelle Harly 


The vertebrate adaptive immune system can distinguish invaders from self with exquisite precision. The T cells, their immune receptors, and the antigenic ligands involved in this process are well characterized, but how a T cell receptor (TCR) can distinguish between closely related ligands, detect minute amounts of foreign antigens, and in turn trigger distinct downstream signals, remains poorly understood. Through its TCR, a T cell can distinguish between self and non-self ligands that differ by just a single amino acid and T cells can be activated by a single non-self peptide that might appear to be otherwise lost among millions of self molecules. Understanding this remarkable discrimination is a major challenge in immunology.


In the foundational paper that we have chosen to highlight for the PLOS Biology XV Collection, Grégoire Altan-Bonnet and Ron Germain addressed this problem. Using quantitative measurements and mathematical models, they showed that the previously well-established kinetic-proofreading model could not adequately explain the exquisite discrimination that T cells are capable of. To improve upon it, they incorporated into this model a negative feedback pathway previously suggested to sharpen the discrimination threshold between closely related TCR ligands. The new model accurately predicted the behavior of T cell activation in response to different TCR ligands, and accounted for the speed, sensitivity, and specificity of TCR-dependent activation.

The model used by Altan-Bonnet and Germain of the core module of early events of TCR signaling.

This model depicts the TCR signaling pathway as a tunable switch. The switch is provided by two discrete states of ERK phosphorylation that the authors document for the first time, and propose to be an early correlate for T cell activation. The sensitivity and specificity of this switch is tuned via the negative feedback loop by molecular players whose activity could be set during development, and further modulated by additional signaling pathways downstream of other receptors on T cells.


The work also provides an explanation for the seemingly counter-intuitive behavior of antagonistic TCR ligands. An agonist ligand activates a T cell response, but an antagonist ligand is one that blocks activation by an agonist ligand. Such ligands are proposed to trigger the negative feedback loop of a given TCR without reaching the threshold of activation, thus antagonizing activation by the agonist ligand. The closer a non-agonist ligand is to reaching the activation threshold, the more antagonistic it will appear. The function of antagonist ligands is still unclear, but more recent work by Paul François & coworkers (Physical Biology, 2016) derived a theorem demonstrating how antagonism is in fact a phenotypic “spandrel” (Stephen Jay Gould’s term) of sharp ligand discrimination. In other terms, the evolution of the negative feedback that receptors need to achieve the necessary sensitivity and specificity also led to the appearance of antagonism.


The model developed by Altan-Bonnet and Germain, which is an “adaptive kinetic proofreading” model, has endured the test of time. The negative feedback could apply to any receptor and in fact could be a general scheme for any complex system performing a classification task such as self/non-self discrimination in the adaptive or innate immune systems. Hence, this study focused on TCR signaling has general applications in immunology as well as in theoretical biological physics.


Altan-Bonnet G, Germain RN (2005) Modeling T Cell Antigen Discrimination Based on Feedback Control of Digital ERK Responses. PLoS Biol 3(11): e356.


Avinash Bhandoola works at the National Cancer Institute, USA, and is a member of the PLOS Biology Editorial Board. Christelle Harly is a research fellow at the same institution.


This blog post is the second in a series of twelve, forming PLOS Biology’s XV Collection, celebrating 15 years of outstanding open science; read Lauren Richardson’s blog for more information.


Featured image credit: Flickr user NIAID


Avinash Bhandoola and Christelle Harly image credit: Devin Kenney


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