Centre for Proteome Research, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, L69 7ZB, UK.
Department of Vector Biology, Liverpool School of Tropical Medicine, Pembroke Place, Liverpool, L3 5QA, UK.
BMC Biol. 2023 Jan 24;21(1):10. doi: 10.1186/s12915-022-01508-8.
A rapid, accurate method to identify and to age-grade mosquito populations would be a major advance in predicting the risk of pathogen transmission and evaluating the public health impact of vector control interventions. Whilst other spectrometric or transcriptomic methods show promise, current approaches rely on challenging morphological techniques or simple binary classifications that cannot identify the subset of the population old enough to be infectious. In this study, the ability of rapid evaporative ionisation mass spectrometry (REIMS) to identify the species and age of mosquitoes reared in the laboratory and derived from the wild was investigated.
The accuracy of REIMS in identifying morphologically identical species of the Anopheles gambiae complex exceeded 97% using principal component/linear discriminant analysis (PC-LDA) and 84% based on random forest analysis. Age separation into 3 different age categories (1 day, 5-6 days, 14-15 days) was achieved with 99% (PC-LDA) and 91% (random forest) accuracy. When tested on wild mosquitoes from the UK, REIMS data could determine the species and age of the specimens with accuracies of 91 and 90% respectively.
The accuracy of REIMS to resolve the species and age of Anopheles mosquitoes is comparable to that achieved by infrared spectroscopy approaches. The processing time and ease of use represent significant advantages over current, dissection-based methods. Importantly, the accuracy was maintained when using wild mosquitoes reared under differing environmental conditions, and when mosquitoes were stored frozen or desiccated. This high throughput approach thus has potential to conduct rapid, real-time monitoring of vector populations, providing entomological evidence of the impact of alternative interventions.
一种快速、准确的识别和年龄分级蚊虫种群的方法将是预测病原体传播风险和评估媒介控制干预措施公共卫生影响的重大进展。虽然其他光谱或转录组学方法显示出前景，但目前的方法依赖于具有挑战性的形态学技术或简单的二元分类，无法识别出足以具有传染性的人群子集。在这项研究中，研究了快速蒸发离子化质谱（REIMS）识别在实验室中饲养和从野外采集的蚊子的物种和年龄的能力。
使用主成分/线性判别分析（PC-LDA），REIMS 识别形态相同的冈比亚按蚊复合体物种的准确率超过 97%，基于随机森林分析的准确率为 84%。通过将年龄分为 3 个不同的年龄组（1 天、5-6 天、14-15 天），REIMS 实现了 99%（PC-LDA）和 91%（随机森林）的准确率。当在来自英国的野生蚊子上进行测试时，REIMS 数据可以确定标本的物种和年龄，准确率分别为 91%和 90%。
REIMS 确定按蚊物种和年龄的准确率与红外光谱方法相当。与基于解剖的当前方法相比，处理时间和易用性是显著优势。重要的是，当使用在不同环境条件下饲养的野生蚊子以及冷冻或干燥的蚊子时，准确性得以保持。这种高通量方法因此具有实时监测媒介种群的潜力，为替代干预措施的影响提供昆虫学证据。
