Evaluation of diffuse reflectance spectroscopy for predicting age, species, and cuticular resistance of Anopheles gambiae s.l under laboratory conditions

Pazmiño Betancourth, M. , Ochoa-Gutiérrez, V. , Ferguson, H. M. , González-Jiménez, M. , Wynne, K. , Baldini, F. and Childs, D. (2023) Evaluation of diffuse reflectance spectroscopy for predicting age, species, and cuticular resistance of Anopheles gambiae s.l under laboratory conditions. Scientific Reports, 13, 18499. (doi: 10.1038/s41598-023-45696-x) (PMID:37898634) (PMCID:PMC10613238)

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Abstract

Mid-infrared spectroscopy (MIRS) combined with machine learning analysis has shown potential for quick and efficient identification of mosquito species and age groups. However, current technology to collect spectra is destructive to the sample and does not allow targeting specific tissues of the mosquito, limiting the identification of other important biological traits such as insecticide resistance. Here, we assessed the use of a non-destructive approach of MIRS for vector surveillance, micro diffuse reflectance spectroscopy (µDRIFT) using mosquito legs to identify species, age and cuticular insecticide resistance within the Anopheles gambiae s.l. complex. These mosquitoes are the major vectors of malaria in Africa and the focus on surveillance in malaria control programs. Legs required significantly less scanning time and showed more spectral consistence compared to other mosquito tissues. Machine learning models were able to identify An. gambiae and An. coluzzii with an accuracy of 0.73, two ages groups (3 and 10 days old) with 0.77 accuracy and we obtained accuracy of 0.75 when identifying cuticular insecticide resistance. Our results highlight the potential of different mosquito tissues and µDRIFT as tools for biological trait identification on mosquitoes that transmit malaria. These results can guide new ways of identifying mosquito traits which can help the creation of innovative surveillance programs by adapting new technology into mosquito surveillance and control tools.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Ochoa Gutierrez, Dr Victor and Childs, Dr David and Gonzalez Jimenez, Dr Mario and Pazmino Betancourth, Mr Mauro and Baldini, Dr Francesco and Wynne, Professor Klaas and Ferguson, Professor Heather
Authors: Pazmiño Betancourth, M., Ochoa-Gutiérrez, V., Ferguson, H. M., González-Jiménez, M., Wynne, K., Baldini, F., and Childs, D.
College/School:College of Medical Veterinary and Life Sciences > School of Biodiversity, One Health & Veterinary Medicine
College of Science and Engineering > School of Chemistry
College of Science and Engineering > School of Engineering
Journal Name:Scientific Reports
Publisher:Nature Research
ISSN:2045-2322
ISSN (Online):2045-2322
Copyright Holders:Copyright © 2023 The Authors
First Published:First published in Scientific Reports 13:18499
Publisher Policy:Reproduced under a Creative Commons licence

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
174132Development of a new tool for malaria mosquito surveillance to improve vector controlHeather FergusonMedical Research Council (MRC)MR/P025501/1Institute of Biodiversity, Animal Health and Comparative Medicine
307465AI and InfraRed Spectroscopy to Accelerate Malaria ControlFrancesco BaldiniBill and Melinda Gates Foundation (GATES)OPP 1217647Computing Science
304469CONTROLKlaas WynneEuropean Commission (EC)832703Chemistry