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Piarroux, M.

Publications and source records attributed to Piarroux, M..

2 recordsLinked to original sources

Identification of Southeast Asian Anopheles mosquito species using MALDI-TOF mass spectrometry

Malaria control in South-East Asia remains a challenge, underscoring the importance of accurately identifying malaria mosquitoes to understand transmission dynamics and improve vector control. Traditional methods such as morphological identification require extensive training and cannot distinguish between sibling species, while molecular approaches are costly for extensive screening. Matrix-assisted laser desorption and ionization time-of-flight mass spectrometry (MALDI-TOF MS) has emerged as a rapid and cost-effective tool for Anopheles species identification, yet its current use is limited to few specialized laboratories. This study aimed to develop and validate an online reference database for MALDI-TOF MS identification of Southeast Asian Anopheles species. The database, constructed using the in-house data analysis pipeline MSI2 (Sorbonne University), comprised 2046 head mass spectra from 209 specimens collected at the Thailand-Myanmar border. Molecular identification via COI and ITS2 DNA barcodes enabled the identification of 20 sensu stricto species and 5 sibling species complexes. The high quality of the mass spectra was demonstrated by a MSI2 median score (min-max) of 61.62 (15.94-77.55) for correct answers, using the best result of four technical replicates of a test panel. Applying an identification threshold of 45, 93.9% (201/214) of the specimens were identified, with 98.5% (198/201) consistency with the molecular taxonomic assignment. In conclusion, MALDI-TOF MS holds promise for malaria mosquito identification and can be scaled up for entomological surveillance in Southeast Asia. The free online sharing of our database on the MSI2 platform represents an important step towards the broader use of MALDI-TOF MS in malaria vector surveillance. Author summaryMosquito-borne diseases like malaria are on the rise globally, and climate change may exacerbate this global threat. Accurate identification of Anopheles mosquitoes, the malaria vectors, is crucial for understanding and controlling the disease. Unfortunately, morphological identification methods require extensive training and molecular methods can be time-consuming, especially when analyzing large samples. In this study, we established a reference database for identifying 25 species of Southeast Asian Anopheles using mass spectrometry, a rapid method based on protein fingerprinting. Using a test panel, we demonstrated the effectiveness of this innovative approach in identifying Southeast Asian Anopheles vectors. Importantly, the online sharing of our database marks an important step towards wider application of the tool, thereby contributing to the global effort to combat malaria.

microbiology↗

Targeting hotspots to reduce transmission of malaria in Senegal: modeling of the effects of human mobility

BackgroundIn central Senegal malaria incidences have declined in recent years in response to scaling-up of control measures, but now remains stable, making elimination improbable. Additional control measures are needed to reduce transmission.\n\nMethodsBy using a meta-population mathematical model, we evaluated chemotherapy interventions targeting stable malaria hotspots, using a differential equation framework and incorporating human mobility, and fitted to weekly malaria incidences from 45 villages, over 5 years. Three simulated approaches for selecting intervention targets were compared: a) villages with at least one malaria case during the low transmission season of the previous year; b) villages ranked highest in terms of incidence during the high transmission season of the previous year; c) villages ranked based on the degree of connectivity with adjacent populations.\n\nResultsOur mathematical modeling, taking into account human mobility, showed that the intervention strategies targeting hotspots should be effective in reducing malaria incidence in both treated and untreated areas.\n\nConclusionsMathematical simulations showed that targeted interventions allow increasing malaria elimination potential.

epidemiology↗