Epidemiological and ecological consequences of virus manipulation of host and vector in plant virus transmission.
File(s)journal.pcbi.1009759 (1).pdf (5.39 MB)
Published version
Author(s)
Cunniffe, Nik J
Taylor, Nick P
Hamelin, Frédéric M
Jeger, Michael J
Type
Journal Article
Abstract
Many plant viruses are transmitted by insect vectors. Transmission can be described as persistent or non-persistent depending on rates of acquisition, retention, and inoculation of virus. Much experimental evidence has accumulated indicating vectors can prefer to settle and/or feed on infected versus noninfected host plants. For persistent transmission, vector preference can also be conditional, depending on the vector's own infection status. Since viruses can alter host plant quality as a resource for feeding, infection potentially also affects vector population dynamics. Here we use mathematical modelling to develop a theoretical framework addressing the effects of vector preferences for landing, settling and feeding-as well as potential effects of infection on vector population density-on plant virus epidemics. We explore the consequences of preferences that depend on the host (infected or healthy) and vector (viruliferous or nonviruliferous) phenotypes, and how this is affected by the form of transmission, persistent or non-persistent. We show how different components of vector preference have characteristic effects on both the basic reproduction number and the final incidence of disease. We also show how vector preference can induce bistability, in which the virus is able to persist even when it cannot invade from very low densities. Feedbacks between plant infection status, vector population dynamics and virus transmission potentially lead to very complex dynamics, including sustained oscillations. Our work is supported by an interactive interface https://plantdiseasevectorpreference.herokuapp.com/. Our model reiterates the importance of coupling virus infection to vector behaviour, life history and population dynamics to fully understand plant virus epidemics.
Date Issued
2021-12-30
Date Acceptance
2021-12-15
Citation
PLoS Computational Biology, 2021, 17 (12), pp.1-41
ISSN
1553-734X
Publisher
Public Library of Science (PLoS)
Start Page
1
End Page
41
Journal / Book Title
PLoS Computational Biology
Volume
17
Issue
12
Copyright Statement
© 2021 Cunniffe et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
License URL
Identifier
https://www.ncbi.nlm.nih.gov/pubmed/34968387
PII: PCOMPBIOL-D-21-01643
Subjects
01 Mathematical Sciences
06 Biological Sciences
08 Information and Computing Sciences
Bioinformatics
Publication Status
Published
Coverage Spatial
United States
Date Publish Online
2021-12-30