Identification of Southeast Asian Anopheles mosquito species with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry using a cross-correlation approach
Issued Date
2025-01-16
Resource Type
eISSN
17563305
Scopus ID
2-s2.0-85216043403
Pubmed ID
39819789
Journal Title
Parasites & vectors
Volume
18
Issue
1
Rights Holder(s)
SCOPUS
Bibliographic Citation
Parasites & vectors Vol.18 No.1 (2025) , 8
Suggested Citation
Chaumeau V., Sawasdichai S., Min T.Z.M.M.M., Kularbkeeree T., Jaruwan N., Gloria N., Lee N.Y., Trackoolchengkaew M., Phanaphadungtham M., Rongthong P., Inta A., Watthanaworawit W., Nosten F. Identification of Southeast Asian Anopheles mosquito species with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry using a cross-correlation approach. Parasites & vectors Vol.18 No.1 (2025) , 8. doi:10.1186/s13071-024-06655-1 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/103124
Title
Identification of Southeast Asian Anopheles mosquito species with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry using a cross-correlation approach
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Abstract
BACKGROUND: Matrix-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. METHODS: Anopheles 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. RESULTS: With 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. CONCLUSIONS: The 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.