The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Modeling T Cell Antigen Discrimination Based on Feedback Control of Digital ERK Responses
Open accessAbstract
T-lymphocyte activation displays a remarkable combination of speed, sensitivity, and discrimination in response to peptide-major histocompatibility complex (pMHC) ligand engagement of clonally distributed antigen receptors (T cell receptors or TCRs). Even a few foreign pMHCs on the surface of an antigen-presenting cell trigger effective signaling within seconds, whereas 1 x 10(5)-1 x 10(6) self-pMHC ligands that may differ from the foreign stimulus by only a single amino acid fail to elicit this response. No existing model accounts for this nearly absolute distinction between closely related TCR ligands while also preserving the other canonical features of T-cell responses. Here we document the unexpected highly amplified and digital nature of extracellular signal-regulated kinase (ERK) activation in T cells. Based on this observation and evidence that competing positive- and negative-feedback loops contribute to TCR ligand discrimination, we constructed a new mathematical model of proximal TCR-dependent signaling. The model made clear that competition between a digital positive feedback based on ERK activity and an analog negative feedback involving SH2 domain-containing tyrosine phosphatase (SHP-1) was critical for defining a sharp ligand-discrimination threshold while preserving a rapid and sensitive response. Several nontrivial predictions of this model, including the notion that this threshold is highly sensitive to small changes in SHP-1 expression levels during cellular differentiation, were confirmed by experiment. These results combining computation and experiment reveal that ligand discrimination by T cells is controlled by the dynamics of competing feedback loops that regulate a high-gain digital amplifier, which is itself modulated during differentiation by alterations in the intracellular concentrations of key enzymes. The organization of the signaling network that we model here may be a prototypic solution to the problem of achieving ligand selectivity, low noise, and high sensitivity in biological responses.
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Cites
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Metadata
- Authors
- Altan-Bonnet, G., & Germain, R. N.
- Venue
- PLoS Biology
- Publisher
- Public Library of Science (PLoS)
- Published
- 2005-10-25
- Volume
- 3
- Issue
- 11
- Pages
- e356
- ISSN
- 1544-9173 (ISSN-L)
- 1545-7885
- OpenAlex
- W2063116057
- Cited by
- 468
- References
- 5
- FWCI
- 6.44
- Type
- journal article
- Language
- en
- Open access
- gold
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