Wagner, Iris, Grigoraki, Linta ORCID: https://orcid.org/0000-0001-8997-0406, Enevoldson, Peter, Clarkson, Michael, Jones, Sam, Hurst, Jane, Beynon, Robert and Ranson, Hilary ORCID: https://orcid.org/0000-0003-2332-8247 (2023) 'Rapid identification of mosquito species and age by mass spectrometric analysis.'. BMC Biology, Vol 21, e10.
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Abstract
Background
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.
Results
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.
Conclusions
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.
Item Type: | Article |
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Subjects: | QX Parasitology > QX 20 Research (General) QX Parasitology > Insects. Other Parasites > QX 510 Mosquitoes QX Parasitology > Insects. Other Parasites > QX 650 Insect vectors |
Faculty: Department: | Biological Sciences > Vector Biology Department |
Digital Object Identifer (DOI): | https://doi.org/10.1186/s12915-022-01508-8 |
Depositing User: | Maria Grimes |
Date Deposited: | 24 Jan 2023 15:09 |
Last Modified: | 24 Jan 2023 15:09 |
URI: | https://archive.lstmed.ac.uk/id/eprint/21732 |
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