1. Wolbachia detection in Aedes aegypti using MALDI-TOF MS coupled to artificial intelligence
- Author
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Valentine Ballan, Antsa Rakotonirina, Nicolas Pocquet, Cédric Caruzzo, Julien Colot, Nazha Selmaoui-Folcher, Vincent Richard, Myrielle Dupont-Rouzeyrol, Marie Marin, Malia Kainiu, Entomologie médicale [Nouméa, Nouvelle-Calédonie] (URE-EM), Institut Pasteur de Nouvelle-Calédonie, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP), Institut de sciences exactes et appliquées (ISEA), Université de la Nouvelle-Calédonie (UNC), Groupe Bactériologie Expérimentale [Nouméa, Nouvelle-Calédonie], Direction Internationale de l'Institut Pasteur, Institut Pasteur [Paris] (IP)-Université Paris Cité (UPCité), Dengue et Arbovirose (URE-DA), The project leading to this publication received funding from the French Fund for Economic, Social, Cultural and Scientific cooperation in the Pacific ('Pacific Fund') and the Institut Pasteur of New Caledonia. AR obtained a scholarship from the Institut Pasteur International Network (Bourse Calmette & Yersin)., and Institut Pasteur [Paris]
- Subjects
Mosquito Control ,Desorption ionization ,Bioinformatics ,Science ,[SDV]Life Sciences [q-bio] ,030231 tropical medicine ,Loop-mediated isothermal amplification ,Mosquito Vectors ,Aedes aegypti ,Biology ,medicine.disease_cause ,Article ,Dengue fever ,03 medical and health sciences ,0302 clinical medicine ,Aedes ,Artificial Intelligence ,parasitic diseases ,medicine ,Animals ,Chikungunya ,030304 developmental biology ,0303 health sciences ,Multidisciplinary ,Mass spectrometry ,Biological techniques ,fungi ,virus diseases ,biochemical phenomena, metabolism, and nutrition ,medicine.disease ,biology.organism_classification ,Virology ,Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization ,Vector (epidemiology) ,Medicine ,Wolbachia ,Genetic techniques - Abstract
The mosquito Aedes aegypti is the major vector of arboviruses like dengue, Zika and chikungunya viruses. Attempts to reduce arboviruses emergence focusing on Ae. aegypti control has proven challenging due to the increase of insecticide resistances. An emerging strategy which consists of releasing Ae. aegypti artificially infected with Wolbachia in natural mosquito populations is currently being developed. The monitoring of Wolbachia-positive Ae. aegypti in the field is performed in order to ensure the program effectiveness. Here, the reliability of the Matrix‑Assisted Laser Desorption Ionization‑Time Of Flight (MALDI‑TOF) coupled with the machine learning methods like Convolutional Neural Network (CNN) to detect Wolbachia in field Ae. aegypti was assessed for the first time. For this purpose, laboratory reared and field Ae. aegypti were analyzed. The results showed that the CNN recognized Ae. aegypti spectral patterns associated with Wolbachia-infection. The MALDI-TOF coupled with the CNN (sensitivity = 93%, specificity = 99%, accuracy = 97%) was more efficient than the loop-mediated isothermal amplification (LAMP), and as efficient as qPCR for Wolbachia detection. It therefore represents an interesting method to evaluate the prevalence of Wolbachia in field Ae. aegypti mosquitoes.
- Published
- 2021
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