Rapid Evaporative Ionization Mass Spectrometry (REIMS): a Potential and Rapid Tool for the Identification of Insecticide Resistance in Mosquito Larvae. Issue 5 (9th September 2022)

• Record Type: Journal Article
• Authors: Morgan, Jasmine; Salcedo-Sora, J Enrique; Wagner, Iris; Beynon, Robert J; Triana-Chavez, Omar; Strode, Clare
• Editors: Swale, Daniel
• Is Part Of: Journal of insect science. Volume 22:Issue 5(2022)
• Publication Date: 2022-09-09
• Subjects: insecticide resistance -- rapid evaporative ionization mass spectrometry -- Aedes aegypti -- larvae -- Colombia; Insects -- Periodicals; Entomology -- Periodicals; Arthropoda -- Periodicals; Insects; Arthropods; Biology; Ecology; Entomologie -- Périodiques; Entomology; Insects; Electronic journals; Periodicals; 595.05
• DOI: 10.1093/jisesa/ieac052
• Languages: English
• ISSNs: 1536-2442

Abstract

Abstract: Insecticide resistance is a significant challenge facing the successful control of mosquito vectors globally. Bioassays are currently the only method for phenotyping resistance. They require large numbers of mosquitoes for testing, the availability of a susceptible comparator strain, and often insectary facilities. This study aimed to trial the novel use of rapid evaporative ionization mass spectrometry (REIMS) for the identification of insecticide resistance in mosquitoes. No sample preparation is required for REIMS and analysis can be rapidly conducted within hours. Temephos resistant Aedes aegypti (Linnaeus) larvae from Cúcuta, Colombia and temephos susceptible larvae from two origins (Bello, Colombia, and the lab reference strain New Orleans) were analyzed using REIMS. We tested the ability of REIMS to differentiate three relevant variants: population source, lab versus field origin, and response to insecticide. The classification of these data was undertaken using linear discriminant analysis (LDA) and random forest. Classification models built using REIMS data were able to differentiate between Ae. aegypti larvae from different populations with 82% (±0.01) accuracy, between mosquitoes of field and lab origin with 89% (±0.01) accuracy and between susceptible and resistant larvae with 85% (±0.01) accuracy. LDA classifiers had higher efficiency than random forest with this data set. The high accuracy observed here identifies REIMS as a potential new tool for rapid identification of resistance in mosquitoes. We argue that REIMS and similar modern phenotyping alternatives should complement existing insecticide resistance management tools. Graphical Abstract: