Development of a new tool for malaria mosquito surveillance to improve vector control

开发疟疾蚊子监测新工具以改善病媒控制

• 批准号: MR/P025501/1
• 负责人: Heather Ferguson
• 金额: $ 75.47万
• 依托单位: University of Glasgow
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2017
• 资助国家: 英国
• 起止时间: 2017 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=MR%2FP025501%2F1
• 关键词: Development; new; tool; malaria; mosquito

Since the year 2000, controlling mosquitoes with insecticide-based interventions has led to a 37% reduction in malaria mortality globally. Nevertheless, malaria still caused 438 000 deaths in 2015, and further progress is being threatened by increasing levels of insecticide resistance in mosquito vectors. The global malaria community urgently needs new tools to monitor mosquito vector populations. Several aspects of mosquito demography and physiology are particularly crucial for planning and assessing vector control strategies. Prime amongst these are determination of mosquito vector species and age structure. Accurate species identification is required to confirm what vectors are responsible for transmission. Mosquito age is a critical determinant of their transmission potential. This is because the malaria parasite undergo a period of development within the vector before they become transmissible. Additionally, measurement of insecticide resistance status is essential to assess how effectively vectors could be targeted by current frontline control methods such as Insecticide Treated Nets (ITNs) and spraying. Unfortunately, no methods are currently available for rapid, large-scale and simultaneous measurement of these crucial mosquito vector demographic and physiological traits. This proposal aims to fill that gap by developing and validating a novel technology for high throughput, high precision surveillance of malaria vector populations in LMICs. This project aims to develop such a tool for malaria vectors on the basis on strong existing partnerships with leading African malaria researchers, and world-class physical chemists and vector biologists in the UK. Specifically, the technology is based on the measurement of molecular signature of the mosquito cuticle, which is the outer part of the insects, to predict key traits (species, age and insecticide resistance). Indeed, the composition and structure of the mosquito cuticle, similar to the mammalian skin, changes when the organism ages, it is different in different species, and it is altered in mosquitoes that are resistant to insecticides. Here, we propose to characterize the cuticular changes associated with the traits mentioned above to then make predictions on individual mosquitoes of unknown conditions. The proposed technology is rapid and cost effective as it is based on the measurement of the light absorbed by mosquitoes, a procedure that do not require any sample preparation nor chemical reagents, and it is readily performed in few seconds by a spectrophotometer. The spectra - corresponding to the light absorbed by individual mosquitoes - will be analysed by powerful computational analysis which will enable to estimate the mosquito traits. We will follow a two-stage process starting with laboratory evaluation of mosquitoes at the University of Glasgow to build on our compelling pilot work on the use of Mid Infrared Spectroscopy (MIRS) coupled with artificial neural network (ANN). After further optimization and methods development, we will transfer this technology to two of Africa's leading malaria vector research and control institutes where it will undergo further evaluation and application within a diverse range of mosquito vector populations. We envision this will form the first steps of a pathway along which this technology can be transferred to LMICs for integration into a range of mosquito surveillance applications including programmes to eliminate malaria, and control of other mosquito-borne pathogens such as Zika and Dengue where effective solutions are desperately needed.

自 2000 年以来，通过以杀虫剂为基础的干预措施控制蚊子，全球疟疾死亡率下降了 37%。尽管如此，疟疾在 2015 年仍造成 438 000 人死亡，而蚊媒对杀虫剂的抗药性水平不断提高正威胁着进一步的进展。全球疟疾界迫切需要新工具来监测蚊媒种群。蚊子人口学和生理学的几个方面对于规划和评估病媒控制策略尤其重要。其中最主要的是确定蚊媒种类和年龄结构。需要准确的物种鉴定来确认哪些载体负责传播。蚊子年龄是其传播潜力的关键决定因素。这是因为疟疾寄生虫在传播之前要在媒介内经历一段发育期。此外，测量杀虫剂抗药性状态对于评估当前一线控制方法（如杀虫剂处理蚊帐 (ITN) 和喷洒）如何有效地瞄准病媒至关重要。不幸的是，目前还没有方法可以快速、大规模、同时测量这些重要的蚊媒人口统计和生理特征。该提案旨在通过开发和验证一种对中低收入国家疟疾病媒种群进行高通量、高精度监测的新技术来填补这一空白。该项目旨在与非洲领先的疟疾研究人员以及英国世界一流的物理化学家和媒介生物学家建立牢固的现有合作关系，为疟疾媒介开发这样一种工具。具体来说，该技术基于测量蚊子角质层（昆虫的外部部分）的分子特征，以预测关键特征（物种、年龄和杀虫剂抗性）。事实上，蚊子角质层的组成和结构与哺乳动物皮肤类似，会随着生物体的老化而发生变化，不同物种的情况有所不同，并且对杀虫剂有抗药性的蚊子也会发生变化。在这里，我们建议描述与上述特征相关的角质层变化，然后对未知条件下的个体蚊子进行预测。所提出的技术快速且具有成本效益，因为它基于蚊子吸收的光的测量，该过程不需要任何样品制备或化学试剂，并且可以通过分光光度计在几秒钟内轻松完成。光谱——对应于个体蚊子吸收的光——将通过强大的计算分析进行分析，这将能够估计蚊子的特征。我们将遵循两个阶段的过程，从格拉斯哥大学对蚊子的实验室评估开始，以我们使用中红外光谱 (MIRS) 与人工神经网络 (ANN) 相结合的引人注目的试点工作为基础。经过进一步优化和方法开发后，我们将把这项技术转移到非洲两个领先的疟疾病媒研究和控制机构，在那里它将在不同的蚊媒种群中进行进一步的评估和应用。我们预计，这将成为将该技术转移到中低收入国家的途径的第一步，以便整合到一系列蚊子监测应用中，包括消除疟疾的计划，以及在有效的情况下控制寨卡和登革热等其他蚊媒病原体的计划。迫切需要解决方案。

项目成果

Development of a mid-infrared spectroscopy based tool for mosquito surveillance

开发基于中红外光谱的蚊子监测工具

• 发表时间: 2018
• 作者: Gonzalez-Jimenez M

Detection of malaria parasites in dried human blood spots using mid-infrared spectroscopy and logistic regression analysis

使用中红外光谱和逻辑回归分析检测干人体血斑中的疟疾寄生虫

• DOI: 10.1101/19001206
• 发表时间: 2019
• 作者: Mwanga E

Prediction of malaria mosquito species and population age structure using mid-infrared spectroscopy and supervised machine learning

使用中红外光谱和监督机器学习预测疟疾蚊子种类和种群年龄结构

• DOI: 10.1101/414342
• 发表时间: 2018
• 作者: González-Jiménez M

Key considerations, target product profiles, and research gaps in the application of infrared spectroscopy and artificial intelligence for malaria surveillance and diagnosis.

• DOI: 10.1186/s12936-023-04780-3
• 发表时间: 2023-11-10
• 期刊: MALARIA JOURNAL
• 影响因子: 3
• 作者: Mshani, Issa H.;Siria, Doreen J.;Mwanga, Emmanuel P.;Sow, Bazoumana BD.;Sanou, Roger;Opiyo, Mercy;Sikulu-Lord, Maggy T.;Ferguson, Heather M.;Diabate, Abdoulaye;Wynne, Klaas;Gonzalez-Jimenez, Mario;Baldini, Francesco;Babayan, Simon A.;Okumu, Fredros
• 通讯作者: Okumu, Fredros