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Vector soup: high‐throughput identification of Neotropical phlebotomine sand flies using metabarcoding
Author(s) -
Kocher Arthur,
Gantier JeanCharles,
Gaborit Pascal,
Zinger Lucie,
Holota Helene,
Valiere Sophie,
Dusfour Isabelle,
Girod Romain,
Bañuls AnneLaure,
Murienne Jerome
Publication year - 2017
Publication title -
molecular ecology resources
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.96
H-Index - 136
eISSN - 1755-0998
pISSN - 1755-098X
DOI - 10.1111/1755-0998.12556
Subject(s) - biology , vector (molecular biology) , psychodidae , identification (biology) , 16s ribosomal rna , leishmaniasis , dna barcoding , mitochondrial dna , ecology , entomology , lutzomyia , zoology , genetics , bacteria , gene , recombinant dna
Phlebotomine sand flies are haematophagous dipterans of primary medical importance. They represent the only proven vectors of leishmaniasis worldwide and are involved in the transmission of various other pathogens. Studying the ecology of sand flies is crucial to understand the epidemiology of leishmaniasis and further control this disease. A major limitation in this regard is that traditional morphological‐based methods for sand fly species identifications are time‐consuming and require taxonomic expertise. DNA metabarcoding holds great promise in overcoming this issue by allowing the identification of multiple species from a single bulk sample. Here, we assessed the reliability of a short insect metabarcode located in the mitochondrial 16S rRNA for the identification of Neotropical sand flies, and constructed a reference database for 40 species found in French Guiana. Then, we conducted a metabarcoding experiment on sand flies mixtures of known content and showed that the method allows an accurate identification of specimens in pools. Finally, we applied metabarcoding to field samples caught in a 1‐ha forest plot in French Guiana. Besides providing reliable molecular data for species‐level assignations of phlebotomine sand flies, our study proves the efficiency of metabarcoding based on the mitochondrial 16S rRNA for studying sand fly diversity from bulk samples. The application of this high‐throughput identification procedure to field samples can provide great opportunities for vector monitoring and eco‐epidemiological studies.