MALDI-TOF MS for identification of Afro-tropical secondary malaria vectors.

Background: Characterizing malaria epidemiology at the local level requires understanding the diverse malaria vector species driving transmission, including both primary and secondary vectors. Effective mosquito surveillance and accurate species identification are critical; however, due to the associated cost and complexity, most surveillance strategies mainly focus on the primary malaria vectors. There is a need for cost-effective methods that can reliably identify both primary and secondary vectors as their role in transmission becomes increasingly important while reaching towards elimination. This study aimed to evaluate the use of MALDI-TOF MS as a sustainable tool for identifying secondary malaria vector.

Methods: Adult mosquitoes were collected in Kenya and Mozambique and morphologically identified. Secondary malaria vectors were considered as any Anopheline that did not pertain to Anopheles gambiae sensu lato (s.l.). or Anopheles funestus sensu lato (s.l.). At KEMRI Wellcome Trust Research Programme, MALDI TOF MS spectra were obtained from individual cephalothoraxes. Library creation and querying were guided by confirmatory species identification using Sanger sequencing of a subset of mosquitoes, targeting the Internal Transcribed Spacer 2 (ITS2) region of nuclear ribosomal DNA and the mitochondrial Cytochrome c Oxidase Subunit I (COI) gene. The libraries were then applied for the identification of other secondary malaria vectors.

Results: Species identification of secondary malaria vectors using MALDI-TOF MS showed high concordance with Sanger sequencing with an overall accuracy of 91% and a kappa value of 0.87. The technique demonstrated a sensitivity and specificity of 100% for most species, except for distinguishing between Anopheles cf. coustani 2 NFL-2015 and Anopheles ziemanni. In Kenya, the Anopheles species identified were Anopheles cf. coustani 2 NFL-2015 (19), Anopheles pretoriensis (6), Anopheles rufipes (8), Anopheles ziemanni (8), Anopheles coustani (2), and Anopheles pharoensis (1). In Mozambique, the identified species comprised: An. cf. coustani 2 NFL-2015 (10), An. pretoriensis (2), An. ziemanni (7), An. coustani (28), and An. pharoensis (4).

Conclusion: The results provide evidence that MALDI-TOF can identify secondary malaria vectors from Eastern and Southeastern African regions. This technique was as efficient as DNA sequencing in identifying mosquito species. Indeed, except for An. cf coustani 2NFL-2015 and An. ziemanni, an exact species identification was obtained for all individual mosquitoes. These findings highlight the potential of MALDI-TOF MS for monitoring malaria vectors.