Antibody detection against Kunitz-type protein in Fasciola hepatica experimentally infected sheep using enzyme-linked immunosorbent assay (ELISA)

Description

Abstract Fasciolosis is a parasitic disease considered as emerging and neglected by the WHO. Sheep are highly susceptible to this disease, and affected flocks experience decreased productivity due to increased mortality and reduced quality of their products such as wool and meat. To effectively control this disease, reliable and early diagnosis is essential for making decisions regarding the application of antiparasitics and/or the removal of affected animals. The current diagnosis of F. hepatica in sheep relies on the detection of parasite eggs in feces, a method that becomes reliable from week 10 post-infection. Consequently, there is a need for earlier diagnostic tools based on immune response. However, the obtaining of antigens for antibody detection has proven to be difficult and expensive. In this study, we compared the performance of recombinant F. hepatica Kunitz-type inhibitors (FhKT1.1, FhKT1.3, and FhKT4) in sera from experimentally F. hepatica-infected sheep six weeks post-infection with a synthetic Kunitz-type peptide (sFhKT) used as antigens by ELISA. Among these, FhKT1.1 showed the most promising diagnostic indicators, exhibiting high precision and low cross-reactivity, thus holding potential for standardized production. The results of our study demonstrated that the application of FhKT1.1 is a valuable tool for early-stage diagnosis of F. hepatica in sheep. Such an early diagnosis can aid in implementing timely interventions and effectively managing the disease in sheep populations

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1-Nineteen 5-month to 1 year-old sheep (male n 11=; female n =8), creole biotype , were distributed into four groups: negative control, orally infected with 100 F. hepatica metacercariae for a vaccine challenge trial, and naturally Coccidiaor Nematodes infected sheep; 2-Synthetic FhKT peptide: A FhKT peptide (sFhKT) was synthesized according to the sequence described by Bozas et al, 1995 ONTORESBiotechnologies ; 3-Plasmid constructs:The expression plasmids used in this study were: pET26b-rFhKT 1.1, pET26b-rFhKT 1.3, and pET26b-rFhKT 4: pET26b vector carriers(Novagen; Merck KGaA; Darmstadt, Germany) with a synthetic DNA segment (GenScript) containing the corresponding FhKT(without the secretory signal peptide; 4-Expression and purification of recombinant F. hepatica Kunitz type (FhKT1.1, FhKT1.2, FhKT4) proteins,transformed E. coli cells were grown at 37 ◦C with shaking in 500 mL LB medium with added of kanamycin (25 μg/mL) to OD600 value 0.6 - 0.8. 5-Detection of anti-F. hepatica FhKT-specific antibodies in sheep sera by ELISA 6-Statistical analyses: A Microsoft Excel 2007 spreadsheet was utilized to create a data bank, which was then analyzed using GraphPad Prism software (version 9.0; San Diego, CA, USA) and Infostat software (version 2020; a mixed linear model was employed for the analyses using the R program for estimation purposes. Fisher's LSD test was used to compare the means of optical densities obtained for sFhKT and rFhKTs (p-value < 0.05) at each dilution value (1:500, 1:1000, 1:2000, 1:4000, 1:8000, and 1:16000). For the determination of sensitivity, specificity, positive predictive value, and negative predictive value, a contingency analysis with Fisher's exact test was conducted, with a significance value of p<0.05. The likelihood ratio was estimated based on the sensitivity and specificity values using the following formulas: +LR = sensitivity/1-specificity and -LR = 1-sensitivity/specificity . . The kappa index was calculated using the formula: k = (Po - Pe) / (1 - Pe), where k represents the kappa index, Po denotes the observed agreement between the two tests (copropasitological and ELISA), and Pe signifies the expected agreement between the two tests. Po is calculated as the sum of true positives (TP) and true negatives (TN) divided by the total number of cases (n). Pe is determined using the formula P + N/n, where P represents the true positive results (TP) plus false positive results (FP) divided by the total number of cases (n). N is calculated as the sum of false negatives (FN) and true negatives

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