Modeling T cell antigen discrimination based on feedback control of digital ERK responses

PLoS Biol. 2005 Nov;3(11):e356. doi: 10.1371/journal.pbio.0030356. Epub 2005 Oct 25.

Abstract

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.

Publication types

  • Research Support, N.I.H., Intramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Antigen-Presenting Cells
  • Antigens / chemistry
  • Antigens, Differentiation, T-Lymphocyte / chemistry*
  • Calibration
  • Cell Differentiation
  • Cell Membrane / metabolism
  • Cluster Analysis
  • Computer Simulation
  • Cytoplasm / metabolism
  • Extracellular Signal-Regulated MAP Kinases / metabolism*
  • Feedback, Physiological
  • Flow Cytometry
  • Gene Expression Regulation
  • Intracellular Signaling Peptides and Proteins / metabolism
  • Kinetics
  • Ligands
  • Lymphocyte Activation
  • Major Histocompatibility Complex
  • Mice
  • Mice, Transgenic
  • Models, Theoretical
  • Peptides / chemistry
  • Protein Tyrosine Phosphatase, Non-Receptor Type 6
  • Protein Tyrosine Phosphatases / metabolism
  • Receptors, Antigen, T-Cell / metabolism
  • Reproducibility of Results
  • Retroviridae / metabolism
  • Sensitivity and Specificity
  • Signal Transduction
  • Software
  • T-Lymphocytes / metabolism
  • src Homology Domains

Substances

  • Antigens
  • Antigens, Differentiation, T-Lymphocyte
  • Intracellular Signaling Peptides and Proteins
  • Ligands
  • Peptides
  • Receptors, Antigen, T-Cell
  • Extracellular Signal-Regulated MAP Kinases
  • Protein Tyrosine Phosphatase, Non-Receptor Type 6
  • Protein Tyrosine Phosphatases
  • Ptpn6 protein, mouse