Immunogenic mapping of rDyn-1 and rKDDR-plus proteins and selection of oligopeptides by immunoblotting for the diagnosis of Leishmania infantum-infected dogs.


Journal

PLoS neglected tropical diseases
ISSN: 1935-2735
Titre abrégé: PLoS Negl Trop Dis
Pays: United States
ID NLM: 101291488

Informations de publication

Date de publication:
08 2023
Historique:
received: 17 01 2023
accepted: 15 07 2023
revised: 21 08 2023
medline: 23 8 2023
pubmed: 4 8 2023
entrez: 4 8 2023
Statut: epublish

Résumé

Endemic in Brazil, visceral leishmaniasis (VL) is a zoonotic infection that is among the most important parasitic diseases transmitted by vectors. Dogs are the main reservoirs of canine leishmaniasis (CanL) and their identification is used in some countries as part of disease prevention and control measures in the canine and human population. In this context, serological tests are necessary, composed of antigens capable of correctly identifying infected dogs, minimizing the number of false-negative cases. This study aimed to identify more immunoreactive peptides derived from two previously described whole proteins (rDyn-1 and rKDDR-plus) and compare their performance to the control antigens rK39 and the crude extract for the detection of dogs infected with L. infantum, especially the asymptomatic ones. The three selected peptides and a mixture of them, along with the rDyn-1, rKDDR-plus, rK39, and crude extract antigens were evaluated using indirect ELISA with sera samples from 186 dogs with CanL, being asymptomatic (n = 50), symptomatic (n = 50), co-infected (n = 19), infected with Babesia sp. (n = 7), Ehrlichia sp. (n = 6), T. cruzi (n = 20) and uninfected (n = 34). The results showed that the rDyn-1 protein and the peptide mixture had the highest sensitivity (100% and 98.32%, respectively) and specificity (97.01 and 98.51, respectively). A high degree of kappa agreement was found for rDyn-1 protein (0.977), mixed peptides (0.965), rKDDR-plus protein (0.953), K-plus peptide 1 (0.930) and Dyn-1 peptide (0.893). The mixture of peptides showed the highest likelihood (65.87). The ELISA using the mixture of peptides and the rDyn-1 protein showed high performance for CanL serodiagnosis. More mix combinations of the peptides and additional extended field tests with a larger sample size are recommended.

Identifiants

pubmed: 37540724
doi: 10.1371/journal.pntd.0011535
pii: PNTD-D-23-00083
pmc: PMC10442149
doi:

Substances chimiques

Antigens, Protozoan 0
Peptides 0
Oligopeptides 0
Antibodies, Protozoan 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

e0011535

Informations de copyright

Copyright: © 2023 Siqueira et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Déclaration de conflit d'intérêts

The authors have declared that no competing interests exist.

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Auteurs

Williane Fernanda Siqueira (WF)

Department of Parasitology, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.
Faculty of Science and Engineering of Maastricht University, Maastricht, Limburg, Netherlands.

Mariana Santos Cardoso (MS)

Department of Parasitology, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.

Vanessa Gomes Fraga (VG)

Department of Parasitology, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.

Jennifer Ottino (J)

Department of Parasitology, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.

Vitor Márcio Ribeiro (VM)

Veterinary School, Pontificial Catholic University of Minas Gerais, Betim, Brazil.

Carolina Novato Gondim (CN)

Department of Health Sciences, Universidade Federal de Lavras, Lavras (MG), Brazil.

Joziana Muniz de Paiva Barçante (JM)

Department of Health Sciences, Universidade Federal de Lavras, Lavras (MG), Brazil.

Ana Carolina Amado Gomes (AC)

Department of Parasitology, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.

Alexsandro Sobreira Galdino (AS)

Laboratory of Microbial Biotechnology, Universidade Federal de São João Del-Rei, Divinópolis, Minas Gerais, Brazil.

Kasper Eersels (K)

Faculty of Science and Engineering of Maastricht University, Maastricht, Limburg, Netherlands.

Bart van Grinsven (B)

Faculty of Science and Engineering of Maastricht University, Maastricht, Limburg, Netherlands.

Daniella Castanheira Bartholomeu (DC)

Department of Parasitology, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.

Lilian Lacerda Bueno (LL)

Department of Parasitology, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.

Thomas Cleij (T)

Faculty of Science and Engineering of Maastricht University, Maastricht, Limburg, Netherlands.

Ricardo Toshio Fujiwara (RT)

Department of Parasitology, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.

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Classifications MeSH