title: Pseudo-chaotic oscillations in CRISPR-virus coevolution predicted by bifurcation analysis.
abstract: BACKGROUND
  The CRISPR-Cas systems of adaptive antivirus immunity are present in most archaea and many bacteria, and provide resistance to specific viruses or plasmids by inserting fragments of foreign DNA into the host genome and then utilizing transcripts of these spacers to inactivate the cognate foreign genome. The recent development of powerful genome engineering tools on the basis of CRISPR-Cas has sharply increased the interest in the diversity and evolution of these systems. Comparative genomic data indicate that during evolution of prokaryotes CRISPR-Cas loci are lost and acquired via horizontal gene transfer at high rates. Mathematical modeling and initial experimental studies of CRISPR-carrying microbes and viruses reveal complex coevolutionary dynamics.
  
  
  RESULTS
  We performed a bifurcation analysis of models of coevolution of viruses and microbial host that possess CRISPR-Cas hereditary adaptive immunity systems. The analyzed Malthusian and logistic models display complex, and in particular, quasi-chaotic oscillation regimes that have not been previously observed experimentally or in agent-based models of the CRISPR-mediated immunity. The key factors for the appearance of the quasi-chaotic oscillations are the non-linear dependence of the host immunity on the virus load and the partitioning of the hosts into the immune and susceptible populations, so that the system consists of three components.
  
  
  CONCLUSIONS
  Bifurcation analysis of CRISPR-host coevolution model predicts complex regimes including quasi-chaotic oscillations. The quasi-chaotic regimes of virus-host coevolution are likely to be biologically relevant given the evolutionary instability of the CRISPR-Cas loci revealed by comparative genomics. The results of this analysis might have implications beyond the CRISPR-Cas systems, i.e. could describe the behavior of any adaptive immunity system with a heritable component, be it genetic or epigenetic. These predictions are experimentally testable.
  This manuscript was reviewed by Sandor Pongor, Sergei Maslov and Marek Kimmel. For the complete reports, go to the Reviewers' Reports section.
authors.forename: Faina S
authors.initials: FS
authors.lastname: Berezovskaya
authors.forename: Yuri I
authors.initials: YI
authors.lastname: Wolf
authors.affiliation: National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA. koonin@ncbi.nlm.nih.gov.
authors.forename: Eugene V
authors.initials: EV
authors.lastname: Koonin
authors.forename: Georgy P
authors.initials: GP
authors.lastname: Karev
mesh_terms: D001105:Archaea / Q000235:genetics / Q000821:virology; D001419:Bacteria / Q000235:genetics / Q000821:virology; D064112:Clustered Regularly Interspaced Short Palindromic Repeats / Q000235:genetics*; D019143:Evolution, Molecular; D016015:Logistic Models; D008957:Models, Genetic; D017711:Nonlinear Dynamics; D014780:Viruses / Q000235:genetics