Immune signaling networks: Sources of robustness and constrained evolvability during coevolution

Edward C. Schrom, Joaquın M. Prada, Andrea Linn Graham

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

Defense against infection incurs costs as well as benefits that are expected to shape the evolution of optimal defense strategies. In particular, many theoretical studies have investigated contexts favoring constitutive versus inducible defenses. However, even when one immune strategy is theoretically optimal, it may be evolutionarily unachievable. This is because evolution proceeds via mutational changes to the protein interaction networks underlying immune responses, not by changes to an immune strategy directly. Here, we use a theoretical simulation model to examine how underlying network architectures constrain the evolution of immune strategies, and how these network architectures account for desirable immune properties such as inducibility and robustness. We focus on immune signaling because signaling molecules are common targets of parasitic interference but are rarely studied in this context. We find that in the presence of a coevolving parasite that disrupts immune signaling, hosts evolve constitutive defenses even when inducible defenses are theoretically optimal. This occurs for two reasons. First, there are relatively few network architectures that produce immunity that is both inducible and also robust against targeted disruption. Second, evolution toward these few robust inducible network architectures often requires intermediate steps that are vulnerable to targeted disruption. The few networks that are both robust and inducible consist of many parallel pathways of immune signaling with few connections among them. In the context of relevant empirical literature, we discuss whether this is indeed the most evolutionarily accessible robust inducible network architecture in nature, and when it can evolve.

Original languageEnglish (US)
Pages (from-to)676-687
Number of pages12
JournalMolecular biology and evolution
Volume35
Issue number3
DOIs
StatePublished - Mar 1 2018

All Science Journal Classification (ASJC) codes

  • Genetics
  • Ecology, Evolution, Behavior and Systematics
  • Molecular Biology

Keywords

  • Coevolution
  • Evolutionary simulation
  • Evolvability
  • Optimal immunity
  • Robustness
  • Signaling networks.

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