A proteomic road to acquire an accurate serological diagnosis for human tegumentary leishmaniasis.

Diagnostic tools are important for clinical management and epidemiological evaluation of Tegumentary (TL) and Visceral (VL) Leishmaniasis. Serology is not frequently used for the diagnosis of the TL form because low antibody titers and cross-reaction with VL. Therefore, it is crucial to identify specific and immunogenic antigens from species associated with the TL form. Here we employed a proteomic approach coupled to an in silico analysis and identified the most abundant and immunogenic proteins from Leishmania amazonensis, Leishmania braziliensis and Leishmania infantum. Of 16 species specific proteins, nine were from the species causative of the TL form (L. amazonensis and L. braziliensis). In silico analysis revealed 18 B-cell epitopes with 0% similarity to Trypanosoma cruzi orthologs and, therefore, less likely to crossreact with sera of patients with Chagas disease. Two proteins reacted exclusively with serum from TL patients and presented several B-cell epitopes without similarity to T. cruzi orthologs: the hypothetical protein GI 134063939 and the metallo-peptidase Clan MA(E)-Family M3. The immunoassay revealed nine peptides with strong reactivity to sera from TL patients. These proteins and peptides may be good candidates to improve the specificity and sensibility of serological tests aiming to diagnose the TL of this neglected human disease. BIOLOGICAL SIGNIFICANCE: As no gold-standard test for tegumentary leishmaniasis (TL) exists, a combination of different diagnostic techniques is often necessary to obtain precise results. Thus, the identification of species-specific, highly immunogenic and abundant proteins that stimulate the humoral immune response in the host should help in the development of serological tests for human TL. Herein we searched for these potential antigens in Leishmania species related to American Leishmaniasis (L. amazonensis, L. braziliensis and L. infantum). To this end, we employed an immunoproteomic approach using proteins from these Leishmania species and sera from TL and Visceral Leishmaniasis (VL) patients. Our study unveils specific proteins and peptides that may represent antigens that will help the efforts to improve the accuracy of serological tests to diagnose the TL form.

Immunoproteomic and bioinformatic approaches to identify secreted Leishmania amazonensis, L. braziliensis, and L. infantum proteins with specific reactivity using canine serum.

Leishmania spp have a wide range of hosts, and each host can harbor several Leishmania species. Dogs, for example, are frequently infected by Leishmania infantum, where they constitute its main reservoir, but they also serve as hosts for L. braziliensis and L. amazonensis. Serological tests for antibody detection are valuable tools for diagnosis of L. infantum infection due to the high levels of antibodies induced, unlike what is observed in L. amazonensis and L. braziliensis infections. Likewise, serology-based antigen-detection can be useful as an approach to diagnose any Leishmania species infection using different corporal fluid samples. Immunogenic and secreted proteins constitute powerful targets for diagnostic methods in antigen detection. As such, we performed immunoproteomic (2-DE, western blot and mass spectrometry) and bioinformatic screening to search for reactive and secreted proteins from L. amazonensis, L. braziliensis, and L. infantum. Twenty-eight non-redundant proteins were identified, among which, six were reactive only in L. amazonensis extracts, 10 in L. braziliensis extracts, and seven in L. infantum extracts. After bioinformatic analysis, seven proteins were predicted to be secreted, two of which were reactive only in L. amazonensis extracts (52kDa PDI and the glucose-regulated protein 78), one in L. braziliensis extracts (pyruvate dehydrogenase E1 beta subunit) and three in L. infantum extracts (two conserved hypothetical proteins and elongation factor 1-beta). We propose that proteins can be suitable targets for diagnostic methods based on antigen detection.