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Tregs self-organize into a computing ecosystem and implement a sophisticated optimization algorithm for mediating immune response.

Robert MarslandOwen HowellAndreas MayerPankaj Mehta
Published in: Proceedings of the National Academy of Sciences of the United States of America (2021)
Regulatory T cells (Tregs) play a crucial role in mediating immune response. Yet an algorithmic understanding of the role of Tregs in adaptive immunity remains lacking. Here, we present a biophysically realistic model of Treg-mediated self-tolerance in which Tregs bind to self-antigens and locally inhibit the proliferation of nearby activated T cells. By exploiting a duality between ecological dynamics and constrained optimization, we show that Tregs tile the potential antigen space while simultaneously minimizing the overlap between Treg activation profiles. We find that for sufficiently high Treg diversity, Treg-mediated self-tolerance is robust to fluctuations in self-antigen concentrations but lowering the Treg diversity results in a sharp transition-related to the Gardner transition in perceptrons-to a regime where changes in self-antigen concentrations can result in an autoimmune response. We propose an experimental test of this transition in immune-deficient mice and discuss potential implications for autoimmune diseases.
Keyphrases
  • immune response
  • regulatory t cells
  • dendritic cells
  • human health
  • climate change
  • toll like receptor
  • machine learning
  • signaling pathway
  • risk assessment