Evidence map›Paper›PMID 39819789›Full record

ArticleParasites & vectors2025

Identification of Southeast Asian Anopheles mosquito species with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry using a cross-correlation approach.

Victor Chaumeau, Sunisa Sawasdichai, Thu Zar Ma Ma Moe Min, Thithiwarada Kularbkeeree, Naw Jaruwan, Naw Gloria, Naw Yu Lee, Muesuwa Trackoolchengkaew, Monticha Phanaphadungtham, Patcharamai Rongthong and 3 more

Abstract read
In one paragraph

Article in Parasites & vectors, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Taxonomic signal in the wing cells ofJournal of advanced veterinary and animal research · 2025
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Victor ChaumeauShoklo Malaria Research Unit, Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Mae Ramat, Thailand. victor@tropmedres.ac.
Sunisa SawasdichaiShoklo Malaria Research Unit, Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Mae Ramat, Thailand.
Thu Zar Ma Ma Moe MinShoklo Malaria Research Unit, Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Mae Ramat, Thailand.
Thithiwarada KularbkeereeShoklo Malaria Research Unit, Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Mae Ramat, Thailand.
Naw JaruwanShoklo Malaria Research Unit, Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Mae Ramat, Thailand.
Naw GloriaShoklo Malaria Research Unit, Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Mae Ramat, Thailand.
Naw Yu LeeShoklo Malaria Research Unit, Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Mae Ramat, Thailand.
Muesuwa TrackoolchengkaewShoklo Malaria Research Unit, Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Mae Ramat, Thailand.
Monticha PhanaphadungthamShoklo Malaria Research Unit, Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Mae Ramat, Thailand.
Patcharamai RongthongShoklo Malaria Research Unit, Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Mae Ramat, Thailand.
Aritsara IntaShoklo Malaria Research Unit, Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Mae Ramat, Thailand.
Wanitda WatthanaworawitShoklo Malaria Research Unit, Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Mae Ramat, Thailand.
François NostenShoklo Malaria Research Unit, Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Mae Ramat, Thailand.

Funding

Bill and Melinda Gates Foundation OPP1177406Wellcome TrustWellcome Trust 220211
6 · The paper itself

Abstract

backgroundMatrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) is proposed for mosquito species identification. The absence of public repositories sharing mass spectra and open-source data analysis pipelines for fingerprint matching to mosquito species limits the widespread use of this technology. The objective of this study was to develop a free open-source data analysis pipeline for Anopheles species identification with MALDI-TOF MS.

methodsAnopheles mosquitoes were captured in 33 villages in Karen (Kayin) state in Myanmar. A subset of 403 specimens was selected for inclusion in either the reference or the test panel (270 and 133 specimens, respectively). Three hundred fifty-nine specimens could be identified with DNA barcodes and were assigned to 21 sensu stricto species and five sibling species pairs or complexes. A total of 3584 mass spectra of the head of these specimens identified with DNA barcoding were acquired and the similarity between mass spectra was quantified using a cross-correlation approach adapted from the published literature. A reference mass spectra database was created using all spectra of the PCR-identified specimens assigned to the reference panel. A simulation experiment was carried out by querying the reference database with the spectra of the test panel to evaluate the performance of species identification with MALDI-TOF MS at varying thresholds of the cross-correlation index for the algorithm to output an identification result and with varying numbers of technical replicates for the tested specimens, considering PCR identification results as the reference.

resultsWith one spot and a threshold value of -14 for the cross-correlation index on the log scale, the sensitivity was 0.99 [95% credible interval (CrI): 0.98-1.00], the predictive positive value was 0.99 (95% CrI: 0.98-0.99), and the accuracy was 0.98 (95% CrI: 0.97-0.99). It was not possible to directly estimate the sensitivity and negative predictive value because there was no true negative (i.e., queries of species not referenced in the database) in the assessment.

conclusionsThe cross-correlation approach can be used to match mass spectral fingerprints to predefined taxa. MALDI-TOF MS is a valuable tool for rapid, accurate, and affordable identification of Anopheles species.

Indexed as

AnophelesSpectrometry, Mass, Matrix-Assisted Laser Desorption-IonizationAnimalsDNA Barcoding, TaxonomicMyanmarAnophelesCross-correlationIdentificationMalariaMatrix-assisted laser desorption/ionization time-of-flight mass spectrometrySibling speciesSimilaritySoutheast Asia

Identifiers

PMID39819789
PMCPMC11737280

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.