Big Data Institute, University of Oxford, Oxford, OX3 7LF, UK.
Department of Vector Biology, Liverpool School of Tropical Medicine, Liverpool, L35QA, UK.
BMC Biol. 2022 Feb 15;20(1):46. doi: 10.1186/s12915-022-01242-1.
Resistance in malaria vectors to pyrethroids, the most widely used class of insecticides for malaria vector control, threatens the continued efficacy of vector control tools. Target-site resistance is an important genetic resistance mechanism caused by mutations in the voltage-gated sodium channel (Vgsc) gene that encodes the pyrethroid target-site. Understanding the geographic distribution of target-site resistance, and temporal trends across different vector species, can inform strategic deployment of vector control tools.
We develop a Bayesian statistical spatiotemporal model to interpret species-specific trends in the frequency of the most common resistance mutations, Vgsc-995S and Vgsc-995F, in three major malaria vector species Anopheles gambiae, An. coluzzii, and An. arabiensis over the period 2005-2017. The models are informed by 2418 observations of the frequency of each mutation in field sampled mosquitoes collected from 27 countries spanning western and eastern regions of Africa. For nine selected countries, we develop annual predictive maps which reveal geographically structured patterns of spread of each mutation at regional and continental scales. The results show associations, as well as stark differences, in spread dynamics of the two mutations across the three vector species. The coverage of ITNs was an influential predictor of Vgsc allele frequencies, with modelled relationships between ITN coverage and allele frequencies varying across species and geographic regions. We found that our mapped Vgsc allele frequencies are a significant partial predictor of phenotypic resistance to the pyrethroid deltamethrin in An. gambiae complex populations.
Our predictive maps show how spatiotemporal trends in insecticide target-site resistance mechanisms in African An. gambiae vary across individual vector species and geographic regions. Molecular surveillance of resistance mechanisms will help to predict resistance phenotypes and track their spread.
对拟除虫菊酯的抗药性是疟疾传播媒介最广泛使用的控制工具，这威胁到媒介控制工具的持续有效性。靶标抗性是一种重要的遗传抗性机制，是由编码拟除虫菊酯靶标的电压门控钠离子通道（Vgsc）基因中的突变引起的。了解靶标抗性的地理分布和不同媒介物种的时间趋势，可以为媒介控制工具的战略部署提供信息。
我们开发了一个贝叶斯统计时空模型，以解释在 2005 年至 2017 年期间，三种主要疟疾传播媒介种系——冈比亚按蚊、库蚊和阿拉伯按蚊中最常见的抗性突变 Vgsc-995S 和 Vgsc-995F 的种特异性趋势。该模型由 2418 个观测结果组成，这些观测结果来自 27 个国家的现场采集的蚊子种群中每种突变的频率，这些国家横跨非洲的西部和东部地区。对于九个选定的国家，我们开发了年度预测图，这些预测图揭示了每个突变在区域和大陆尺度上的传播的地理结构模式。结果表明，两种突变在三种媒介种系中的传播动态既有关联，也有明显的差异。经杀虫剂处理的蚊帐（ITN）的覆盖率是 Vgsc 等位基因频率的一个有影响力的预测因子，模型中的 ITN 覆盖率与等位基因频率之间的关系因物种和地理区域而异。我们发现，我们绘制的 Vgsc 等位基因频率是冈比亚按蚊复合体种群对拟除虫菊酯溴氰菊酯表型抗性的一个重要部分预测因子。
我们的预测图显示了非洲冈比亚按蚊中昆虫杀虫剂靶标抗性机制的时空趋势如何因个别媒介种系和地理区域而异。对抗性机制的分子监测将有助于预测抗性表型并跟踪其传播。
