Immunodiagnosis of cystic echinococcosis in livestock: Development and validation dataset of an ELISA test using a recombinant B8/2 subunit of Echinococcus granulosus sensu lato.

The accuracy of screening tests for detecting cystic echinococcosis (CE) in livestock depends on characteristics of the host-parasite interaction and the extent of serological cross-reactivity with other taeniid species. The AgB8 kDa protein is considered to be the most specific native or recombinant antigen for immunodiagnosis of ovine CE. A particular DNA fragment coding for rAgB8/2 was identified, that provides evidence of specific reaction in the serodiagnosis of metacestode infection. We developed and validated an IgG Enzyme Linked Immunosorbent Assay (ELISA) test using a recombinant antigen B sub-unit EgAgB8/2 (rAgB8/2) of Echinoccocus granulosus sensu lato (s.l.) to estimate CE prevalence in sheep. A 273 bp DNA fragment coding for rAgB8/2 was expressed as a fusion protein (∼30 kDa) and purified by affinity chromatography. Evaluation of the analytical and diagnostic performance of the ELISA followed the World Organisation for Animal Health (OIE) manual, including implementation of serum panels from: uninfected lambs (n = 79); experimentally infected (with 2,000 E. granulosus s.l. eggs each) sheep with subsequent evidence of E. granulosus cysts by necropsy (n = 36), and animals carrying other metacestode/trematode infections (n = 20). The latter were used to assess the cross-reactivity of rAgB8/2, with these animals being naturally infected with Taenia hydatigena, Thysanosoma actinioides and/or Fasciola hepatica. EgAgB8/2 showed cross-reaction with only one serum sample from a sheep infected with Ta. hydatigena out of the 20 animals tested. Furthermore, the kinetics of the humoral response over time in five 6-month old sheep, each experimentally infected with 2,000 E. granulosus s.l. eggs, was evaluated up to 49 weeks (approximately one year) post infection (n = 5). The earliest detectable IgG response against rAgB8/2 was observed in sera from two and four sheep, 7 and 14 days after experimental infection, respectively. The highest immune response across all five animals was found 16 to 24 weeks post infection.

Modelling diagnostics for Echinococcus granulosus surveillance in sheep using Latent Class Analysis: Argentina as a case study.

Echinococcus granulosus sensu lato is a globally prevalent zoonotic parasitic cestode leading to cystic echinococcosis (CE) in both humans and sheep with both medical and financial impacts, whose reduction requires the application of a One Health approach to its control. Regarding the animal health component of this approach, lack of accurate and practical diagnostics in livestock impedes the assessment of disease burden and the implementation and evaluation of control strategies. We use of a Bayesian Latent Class Analysis (LCA) model to estimate ovine CE prevalence in sheep samples from the Río Negro province of Argentina accounting for uncertainty in the diagnostics. We use model outputs to evaluate the performance of a novel recombinant B8/2 antigen B subunit (rEgAgB8/2) indirect enzyme-linked immunosorbent assay (ELISA) for detecting E. granulosus in sheep. Necropsy (as a partial gold standard), western blot (WB) and ELISA diagnostic data were collected from 79 sheep within two Río Negro slaughterhouses, and used to estimate individual infection status (assigned as a latent variable within the model). Using the model outputs, the performance of the novel ELISA at both individual and flock levels was evaluated, respectively, using a receiver operating characteristic (ROC) curve, and simulating a range of sample sizes and prevalence levels within hypothetical flocks. The estimated (mean) prevalence of ovine CE was 27.5% (95%Bayesian credible interval (95%BCI): 13.8%-58.9%) within the sample population. At the individual level, the ELISA had a mean sensitivity and specificity of 55% (95%BCI: 46%-68%) and 68% (95%BCI: 63%-92%), respectively, at an optimal optical density (OD) threshold of 0.378. At the flock level, the ELISA had an 80% probability of correctly classifying infection at an optimal cut-off threshold of 0.496. These results suggest that the novel ELISA could play a useful role as a flock-level diagnostic for CE surveillance in the region, supplementing surveillance activities in the human population and thus strengthening a One Health approach. Importantly, selection of ELISA cut-off threshold values must be tailored according to the epidemiological situation.