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Publication | Open Access

Identification of Leishmania by Matrix-Assisted Laser Desorption Ionization–Time of Flight (MALDI-TOF) Mass Spectrometry Using a Free Web-Based Application and a Dedicated Mass-Spectral Library

48

Citations

27

References

2017

Year

Abstract

Human leishmaniases are widespread diseases with different clinical forms caused by about 20 species within the <i>Leishmania</i> genus. <i>Leishmania</i> species identification is relevant for therapeutic management and prognosis, especially for cutaneous and mucocutaneous forms. Several methods are available to identify <i>Leishmania</i> species from culture, but they have not been standardized for the majority of the currently described species, with the exception of multilocus enzyme electrophoresis. Moreover, these techniques are expensive, time-consuming, and not available in all laboratories. Within the last decade, mass spectrometry (MS) has been adapted for the identification of microorganisms, including <i>Leishmania</i> However, no commercial reference mass-spectral database is available. In this study, a reference mass-spectral library (MSL) for <i>Leishmania</i> isolates, accessible through a free Web-based application (mass-spectral identification [MSI]), was constructed and tested. It includes mass-spectral data for 33 different <i>Leishmania</i> species, including species that infect humans, animals, and phlebotomine vectors. Four laboratories on two continents evaluated the performance of MSI using 268 samples, 231 of which were <i>Leishmania</i> strains. All <i>Leishmania</i> strains, but one, were correctly identified at least to the complex level. A risk of species misidentification within the <i>Leishmania donovani</i>, <i>L. guyanensis</i>, and <i>L. braziliensis</i> complexes was observed, as previously reported for other techniques. The tested application was reliable, with identification results being comparable to those obtained with reference methods but with a more favorable cost-efficiency ratio. This free online identification system relies on a scalable database and can be implemented directly in users' computers.

References

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