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  • Research Engineer
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  • Technician
  • Undergraduate Student
  • Veterinary
  • Visiting Scientist
  • Deputy Director of Center
  • Deputy Director of Department
  • Deputy Director of National Reference Center
  • Deputy Head of Facility
  • Director of Center
  • Director of Department
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© Research
Publication : PloS one

Identification of French Guiana anopheline mosquitoes by MALDI-TOF MS profiling using protein signatures from two body parts.

Scientific Fields
Diseases
Organisms
Applications
Technique

Published in PloS one - 01 Jan 2020

Briolant S, Costa MM, Nguyen C, Dusfour I, Pommier de Santi V, Girod R, Almeras L

Link to Pubmed [PMID] – 32817616

Link to DOI – 10.1371/journal.pone.0234098

PLoS One 2020 ; 15(8): e0234098

In French Guiana, the malaria, a parasitic infection transmitted by Anopheline mosquitoes, remains a disease of public health importance. To prevent malaria transmission, the main effective way remains Anopheles control. For an effective control, accurate Anopheles species identification is indispensable to distinguish malaria vectors from non-vectors. Although, morphological and molecular methods are largely used, an innovative tool, based on protein pattern comparisons, the Matrix Assisted Laser Desorption / Ionization Time-of-Flight Mass Spectrometry (MALDI-TOF MS) profiling, emerged this last decade for arthropod identification. However, the limited mosquito fauna diversity of reference MS spectra remains one of the main drawback for its large usage. The aim of the present study was then to create and to share reference MS spectra for the identification of French Guiana Anopheline species. A total of eight distinct Anopheles species, among which four are malaria vectors, were collected in 6 areas. To improve Anopheles identification, two body parts, legs and thoraxes, were independently submitted to MS for the creation of respective reference MS spectra database (DB). This study underlined that double checking by MS enhanced the Anopheles identification confidence and rate of reliable classification. The sharing of this reference MS spectra DB should make easier Anopheles species monitoring in endemic malaria area to help malaria vector control or elimination programs.