Application of matrix-assisted laser desorption/ionization mass spectrometry to identify species of Neotropical Anopheles vectors of malaria

• Published in: Malaria Journal
• Main Authors: Jose R. Loaiza, Alejandro Almanza, Juan C. Rojas, Luis Mejía, Norma D. Cervantes, Javier E. Sanchez-Galan, Fernando Merchán, Arnaud Grillet, Matthew J. Miller, Luis F. De León, Rolando A. Gittens
• Format: Article in Journal/Newspaper
• Language: English
• Published: BMC 2019
• Subjects: Anopheles mosquito; Taxonomic identification; MALDI; Mass spectrometry; Malaria vector; Panama; Arctic medicine. Tropical medicine; RC955-962; Infectious and parasitic diseases; RC109-216; Arctic
• Online Access: https://doi.org/10.1186/s12936-019-2723-0; https://doaj.org/article/5bea6d960a2f46969bf02f131d820883

Abstract Background Malaria control in Panama is problematic due to the high diversity of morphologically similar Anopheles mosquito species, which makes identification of vectors of human Plasmodium challenging. Strategies by Panamanian health authorities to bring malaria under control targeting Anopheles vectors could be ineffective if they tackle a misidentified species. Methods A rapid mass spectrometry identification procedure was developed to accurately and timely sort out field-collected Neotropical Anopheles mosquitoes into vector and non-vector species. Matrix-assisted laser desorption/ionization (MALDI) mass spectra of highly-abundant proteins were generated from laboratory-reared mosquitoes using different extraction protocols, body parts, and sexes to minimize the amount of material from specimen vouchers needed and optimize the protocol for taxonomic identification. Subsequently, the mass spectra of field-collected Neotropical Anopheles mosquito species were classified using a combination of custom-made unsupervised (i.e., Principal component analysis—PCA) and supervised (i.e., Linear discriminant analysis—LDA) classification algorithms. Results Regardless of the protocol used or the mosquito species and sex, the legs contained the least intra-specific variability with enough well-preserved proteins to differentiate among distinct biological species, consistent with previous literature. After minimizing the amount of material needed from the voucher, one leg was enough to produce reliable spectra between specimens. Further, both PCA and LDA were able to classify up to 12 mosquito species, from different subgenera and seven geographically spread localities across Panama using mass spectra from one leg pair. LDA demonstrated high discriminatory power and consistency, with validation and cross-validation positive identification rates above 93% at the species level. Conclusion The selected sample processing procedure can be used to identify field-collected Anopheles species, including vectors of ...