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Rapid identification of mosquito species and age by mass spectrometric analysis
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,...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9872345/ https://www.ncbi.nlm.nih.gov/pubmed/36690979 http://dx.doi.org/10.1186/s12915-022-01508-8 |
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author | Wagner, Iris Grigoraki, Linda Enevoldson, Peter Clarkson, Michael Jones, Sam Hurst, Jane L. Beynon, Robert J. Ranson, Hilary |
author_facet | Wagner, Iris Grigoraki, Linda Enevoldson, Peter Clarkson, Michael Jones, Sam Hurst, Jane L. Beynon, Robert J. Ranson, Hilary |
author_sort | Wagner, Iris |
collection | PubMed |
description | 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12915-022-01508-8. |
format | Online Article Text |
id | pubmed-9872345 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-98723452023-01-25 Rapid identification of mosquito species and age by mass spectrometric analysis Wagner, Iris Grigoraki, Linda Enevoldson, Peter Clarkson, Michael Jones, Sam Hurst, Jane L. Beynon, Robert J. Ranson, Hilary BMC Biol Methodology Article 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12915-022-01508-8. BioMed Central 2023-01-24 /pmc/articles/PMC9872345/ /pubmed/36690979 http://dx.doi.org/10.1186/s12915-022-01508-8 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Methodology Article Wagner, Iris Grigoraki, Linda Enevoldson, Peter Clarkson, Michael Jones, Sam Hurst, Jane L. Beynon, Robert J. Ranson, Hilary Rapid identification of mosquito species and age by mass spectrometric analysis |
title | Rapid identification of mosquito species and age by mass spectrometric analysis |
title_full | Rapid identification of mosquito species and age by mass spectrometric analysis |
title_fullStr | Rapid identification of mosquito species and age by mass spectrometric analysis |
title_full_unstemmed | Rapid identification of mosquito species and age by mass spectrometric analysis |
title_short | Rapid identification of mosquito species and age by mass spectrometric analysis |
title_sort | rapid identification of mosquito species and age by mass spectrometric analysis |
topic | Methodology Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9872345/ https://www.ncbi.nlm.nih.gov/pubmed/36690979 http://dx.doi.org/10.1186/s12915-022-01508-8 |
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