Development and analytical validation of an enzyme-linked immunosorbent assay based on baculovirus recombinant LipL32 protein antigen for the accurate detection of canine leptospirosis

Autor: Nohemí Castro del Campo, Sergio Daniel Gómez-Gómez, Enrique Trasviña-Muñoz, K Moreno-Torres, C Torres-Guzmán, KO Espinoza-Blandón, C Orozco-Cabrera, Gilberto López-Valencia, JG Guerrero-Velázquez, Soila Gaxiola-Camacho, Sergio Arturo Cueto-González, Francisco Javier Monge-Navarro
Rok vydání: 2018
Předmět:
Popis: Leptospira infects a wide range of companion, domestic and wild animal species, shedding the spirochetes into the environment via urine. Dogs become infected by direct or indirect contact with wild or domestic infected animal reservoirs increasing the risk of zoonotic transmission of the disease. The microscopic agglutination test has been used as the gold standard for the diagnosis of leptospirosis but has low sensitivity and is technically complex. Several ELISA tests have been developed based on recombinant proteins of Leptospira for the diagnosis of leptospirosis with similar or higher specificity and sensitivity levels than the microscopic agglutination test. Here, we developed and analytically validated an ELISA test based on recombinant LipL32 protein of Leptospira expressed in baculovirus. The LipL32 protein was successfully adapted in an indirect ELISA using dog plasma samples. Optimization of the ELISA resulted in a P/N ratio of 7.18 using only 5 ng of rLipL32 per well. Inter-assay and intra-assay variation showed a CV of 3.96% and 6.98% respectively, suggesting that the ELISA-LipL32 is highly reproducible. When tested with field samples, concordance of the ELISA-LipL32 with a real-time PCR, positive concordance was 100%. Our results indicate that the ELISA-LipL32 has the potential to be used by veterinarians and public health investigators as a safe, rapid, inexpensive and reliable method for the early diagnosis of Leptospira infection in dogs. Additional studies are still required for clinical validation on field samples under different epidemiological scenarios.
Databáze: OpenAIRE