Research in veterinary science · 2026
Smartphone-assisted ELISA for the detection of Ehrlichia canis antibodies in dogs.
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Peretti Leandro Ezequiel, Schaumburg Federico, Peverengo Luz Maria, Berli Claudio Luis Alberto, Pujato Nazarena
Аннотация
Canine monocytic ehrlichiosis (CME), caused by Ehrlichia canis, has emerged as a significant infectious disease in Latin America, including Argentina, where underdiagnosis remains a challenge due to limited access to laboratory infrastructure. In this context, developing accessible diagnostic tools deployable outside conventional laboratory settings is essential. In this study, we developed a smartphone-assisted, point-of-care (POC) ELISA platform for decentralized CME diagnosis, designed to operate without specialized laboratory equipment. Two peptide-based ELISAs using the E. canis peptides TRP19 and P30 were comparatively evaluated to identify the antigen with the best diagnostic performance for the local serological detection of canine ehrlichiosis. The selected ELISA was subsequently adapted to a smartphone-assisted a point-of-care (POC)-ELISA format by integrating the appuente platform for image acquisition and analysis together with a compact heating plate, replacing the conventional microplate reader and laboratory incubator, respectively. The P30-based ELISA demonstrated superior diagnostic performance, achieving 98.51% sensitivity and specificity, compared with the TRP19-ELISA (Se = 83.58%, Sp = 80.60%). Additionally, likelihood ratio analysis indicated excellent clinical utility for P30-ELISA (LR + = 66.0 and LR - = 0.02), whereas the TRP19-ELISA showed only moderate utility (LR + = 4.31, LR - = 0.20). Agreement between conventional ELISA and the smartphone-assisted POC-ELISA was almost perfect (Cohen's κ = 0.93), confirming the reliability of the smartphone-based approach. These results show that translating the assay to a portable POC format did not compromise diagnosis performance while reducing equipment requirements. The proposed platform represents a promising approach for decentralized CME serodiagnosis and may facilitate access to accurate diagnostic testing in resource-limited settings.