Cargando…

Vector control with driving Y chromosomes: modelling the evolution of resistance

BACKGROUND: The introduction of new malaria control interventions has often led to the evolution of resistance, both of the parasite to new drugs and of the mosquito vector to new insecticides, compromising the efficacy of the interventions. Recent progress in molecular and population biology raises...

Descripción completa

Detalles Bibliográficos
Autores principales: Beaghton, Andrea, Beaghton, Pantelis John, Burt, Austin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5513332/
https://www.ncbi.nlm.nih.gov/pubmed/28705249
http://dx.doi.org/10.1186/s12936-017-1932-7
_version_ 1783250637896548352
author Beaghton, Andrea
Beaghton, Pantelis John
Burt, Austin
author_facet Beaghton, Andrea
Beaghton, Pantelis John
Burt, Austin
author_sort Beaghton, Andrea
collection PubMed
description BACKGROUND: The introduction of new malaria control interventions has often led to the evolution of resistance, both of the parasite to new drugs and of the mosquito vector to new insecticides, compromising the efficacy of the interventions. Recent progress in molecular and population biology raises the possibility of new genetic-based interventions, and the potential for resistance to evolve against these should be considered. Here, population modelling is used to determine the main factors affecting the likelihood that resistance will evolve against a synthetic, nuclease-based driving Y chromosome that produces a male-biased sex ratio. METHODS: A combination of deterministic differential equation models and stochastic analyses involving branching processes and Gillespie simulations is utilized to assess the probability that resistance evolves against a driving Y that otherwise is strong enough to eliminate the target population. The model considers resistance due to changes at the target site such that they are no longer cleaved by the nuclease, and due to trans-acting autosomal suppressor alleles. RESULTS: The probability that resistance evolves increases with the mutation rate and the intrinsic rate of increase of the population, and decreases with the strength of drive and any pleiotropic fitness costs of the resistant allele. In seasonally varying environments, the time of release can also affect the probability of resistance evolving. Trans-acting suppressor alleles are more likely to suffer stochastic loss at low frequencies than target site resistant alleles. CONCLUSIONS: As with any other intervention, there is a risk that resistance will evolve to new genetic approaches to vector control, and steps should be taken to minimize this probability. Two design features that should help in this regard are to reduce the rate at which resistant mutations arise, and to target sequences such that if they do arise, they impose a significant fitness cost on the mosquito. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12936-017-1932-7) contains supplementary material, which is available to authorized users.
format Online
Article
Text
id pubmed-5513332
institution National Center for Biotechnology Information
language English
publishDate 2017
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-55133322017-07-19 Vector control with driving Y chromosomes: modelling the evolution of resistance Beaghton, Andrea Beaghton, Pantelis John Burt, Austin Malar J Research BACKGROUND: The introduction of new malaria control interventions has often led to the evolution of resistance, both of the parasite to new drugs and of the mosquito vector to new insecticides, compromising the efficacy of the interventions. Recent progress in molecular and population biology raises the possibility of new genetic-based interventions, and the potential for resistance to evolve against these should be considered. Here, population modelling is used to determine the main factors affecting the likelihood that resistance will evolve against a synthetic, nuclease-based driving Y chromosome that produces a male-biased sex ratio. METHODS: A combination of deterministic differential equation models and stochastic analyses involving branching processes and Gillespie simulations is utilized to assess the probability that resistance evolves against a driving Y that otherwise is strong enough to eliminate the target population. The model considers resistance due to changes at the target site such that they are no longer cleaved by the nuclease, and due to trans-acting autosomal suppressor alleles. RESULTS: The probability that resistance evolves increases with the mutation rate and the intrinsic rate of increase of the population, and decreases with the strength of drive and any pleiotropic fitness costs of the resistant allele. In seasonally varying environments, the time of release can also affect the probability of resistance evolving. Trans-acting suppressor alleles are more likely to suffer stochastic loss at low frequencies than target site resistant alleles. CONCLUSIONS: As with any other intervention, there is a risk that resistance will evolve to new genetic approaches to vector control, and steps should be taken to minimize this probability. Two design features that should help in this regard are to reduce the rate at which resistant mutations arise, and to target sequences such that if they do arise, they impose a significant fitness cost on the mosquito. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12936-017-1932-7) contains supplementary material, which is available to authorized users. BioMed Central 2017-07-14 /pmc/articles/PMC5513332/ /pubmed/28705249 http://dx.doi.org/10.1186/s12936-017-1932-7 Text en © The Author(s) 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Beaghton, Andrea
Beaghton, Pantelis John
Burt, Austin
Vector control with driving Y chromosomes: modelling the evolution of resistance
title Vector control with driving Y chromosomes: modelling the evolution of resistance
title_full Vector control with driving Y chromosomes: modelling the evolution of resistance
title_fullStr Vector control with driving Y chromosomes: modelling the evolution of resistance
title_full_unstemmed Vector control with driving Y chromosomes: modelling the evolution of resistance
title_short Vector control with driving Y chromosomes: modelling the evolution of resistance
title_sort vector control with driving y chromosomes: modelling the evolution of resistance
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5513332/
https://www.ncbi.nlm.nih.gov/pubmed/28705249
http://dx.doi.org/10.1186/s12936-017-1932-7
work_keys_str_mv AT beaghtonandrea vectorcontrolwithdrivingychromosomesmodellingtheevolutionofresistance
AT beaghtonpantelisjohn vectorcontrolwithdrivingychromosomesmodellingtheevolutionofresistance
AT burtaustin vectorcontrolwithdrivingychromosomesmodellingtheevolutionofresistance