BACKGROUND: Rapid, accurate and high-throughput identification of vector arthropods is of paramount importance in surveillance programmes that are becoming more common due to the changing geographic occurrence and extent of many arthropod-borne diseases. Protein profiling by MALDI-TOF mass spectrometry fulfils these requirements for identification, and reference databases have recently been established for several vector taxa, mostly with specimens from laboratory colonies. METHODS: We established and validated a reference database containing 20 phlebotomine sand fly (Diptera: Psychodidae, Phlebotominae) species by using specimens from colonies or field-collections that had been stored for various periods of time. RESULTS: Identical biomarker mass patterns ('superspectra') were obtained with colony- or field-derived specimens of the same species. In the validation study, high quality spectra (i.e. more than 30 evaluable masses) were obtained with all fresh insects from colonies, and with 55/59 insects deep-frozen (liquid nitrogen/-80 °C) for up to 25 years. In contrast, only 36/52 specimens stored in ethanol could be identified. This resulted in an overall sensitivity of 87 % (140/161); specificity was 100 %. Duration of storage impaired data counts in the high mass range, and thus cluster analyses of closely related specimens might reflect their storage conditions rather than phenotypic distinctness. A major drawback of MALDI-TOF MS is the restricted availability of in-house databases and the fact that mass spectrometers from 2 companies (Bruker, Shimadzu) are widely being used. We have analysed fingerprints of phlebotomine sand flies obtained by automatic routine procedure on a Bruker instrument by using our database and the software established on a Shimadzu system. The sensitivity with 312 specimens from 8 sand fly species from laboratory colonies when evaluating only high quality spectra was 98.3 %; the specificity was 100 %. The corresponding diagnostic values with 55 field-collected specimens from 4 species were 94.7 % and 97.4 %, respectively. CONCLUSIONS: A centralized high-quality database (created by expert taxonomists and experienced users of mass spectrometers) that is easily amenable to customer-oriented identification services is a highly desirable resource. As shown in the present work, spectra obtained from different specimens with different instruments can be analysed using a centralized database, which should be available in the near future via an online platform in a cost-efficient manner.

Avia GIS Risschotlei 33 2980 Zoersel Belgium

Current address NSF Center for Integrated Pest Management 1730 Varsity Drive Suite 110 Venture 4 Building Raleigh North Carolina 27606 USA

Department of Parasitology Faculty of Sciences Charles University Prague Vinicna 7 128 44 Prague 2 Czech Republic

Instituto de Microbiología Universidad San Francisco de Quito Diego de Robles S N Quito Ecuador

Laboratory of Molecular Structure Characterization Institute of Microbiology The Czech Academy of Sciences Videnska 1083 142 20 Prague 4 Czech Republic

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Swiss National Centre for Vector Entomology Institute of Parasitology University of Zürich Winterthurerstrasse 266a 8057 Zürich Switzerland

Université de Reims Champagne Ardenne ANSES EA4688 USC transmission vectorielle et épidémiosurveillance de maladies parasitaires SFR Cap Santé 51 rue Cognacq Jay 51096 Reims France

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Species identification of phlebotomine sandflies using deep learning and wing interferential pattern (WIP)

An integrative approach to identify sand fly vectors of leishmaniasis in Ethiopia by morphological and molecular techniques

Sand flies (Diptera: Psychodidae) in eight Balkan countries: historical review and region-wide entomological survey

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