Loop analysis for pathogens: niche partitioning in the transmission graph for pathogens of the North American tick Ixodes scapularis

J Theor Biol. 2011 Jan 21;269(1):96-103. doi: 10.1016/j.jtbi.2010.10.011. Epub 2010 Oct 13.

Abstract

In population biology, loop analysis is a method of decomposing a life cycle graph into life history pathways so as to compare the relative contributions of pathways to the population growth rate across species and populations. We apply loop analysis to the transmission graph of five pathogens known to infect the black-legged tick, Ixodes scapularis. In this context loops represent repeating chains of transmission that could maintain the pathogen. They hence represent completions of the life cycle, in much the same way as loops in a life cycle graph do for plants and animals. The loop analysis suggests the five pathogens fall into two distinct groups. Borellia burgdorferi, Babesia microti and Anaplasma phagocytophilum rely almost exclusively on a single loop representing transmission to susceptible larvae feeding on vertebrate hosts that were infected by nymphs. Borellia miyamotoi, in contrast, circulates among a separate set of host types and utilizes loops that are a mix of vertical transmission and horizontal transmission. For B. miyamotoi the main loop is from vertebrate hosts to susceptible nymphs, where the vertebrate hosts were infected by larvae that were infected from birth. The results for Powassan virus are similar to B. miyamotoi. The predicted impacts of the known variation in tick phenology between populations of I. scapularis in the Midwest and Northeast of the United States are hence markedly different for the two groups. All of these pathogens benefit, though, from synchronous activity of larvae and nymphs.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Animals
  • Host-Pathogen Interactions*
  • Ixodes / growth & development*
  • Ixodes / microbiology*
  • Life Cycle Stages*
  • North America
  • Seasons
  • Species Specificity