Results of the above-mentioned analysis were parsed to extract meaningful biological information and loaded into a relational database developed to integrate them. positives + number of false positives); cNPVnegative predictive value; NPV = number of true negatives/(number of true negatives + number of false negatives).(DOCX) pone.0182299.s005.docx (14K) GUID:?F780D0F0-37D7-4BDA-AA0C-36FB32F52A60 S3 Table: Performance of each peptide used as an antigen in ELISA using sera from non-infected individuals living in endemic area as negative control. aCIconfidence interval; bPPV = positive predictive value; PPV = number of true positives/(number of true positives + number of false positives); cNPVnegative predictive value; NPV = number of true negatives/(number of true negatives + number of false negatives).(DOCX) pone.0182299.s006.docx (14K) GUID:?71BEAB2E-F710-43A1-9C00-CAB9945C664C S4 Table: Description of parasitological, molecular and serological results from each serum sample analyzed in the study. Ndnot determined.O.D.optical density at 560nm. *serum from patient evalueted before treatament in the infected group (INF). ndnot Lactitol determined. rantigen-reactive sera. (DOCX) pone.0182299.s007.docx (37K) GUID:?2B512868-33BD-4D4F-B2AE-AA5D0EC1A611 Data Availability StatementAll relevant data are within the paper and its Supporting Information files. Abstract In order to effectively control and monitor schistosomiasis, new diagnostic methods are essential. Taking advantage of computational approaches provided by immunoinformatics and considering the availability of predicted proteome information, candidate antigens of schistosomiasis were selected and used in immunodiagnosis tests based on Enzime-linked Immunosorbent Assay (ELISA). The computational selection strategy was based on signal peptide prediction; low similarity to human proteins; B- and T-cell epitope prediction; location and expression in different parasite life stages within definitive host. Results of the above-mentioned analysis were parsed to extract meaningful biological information and loaded into a relational database developed to integrate them. In the end, seven proteins were selected and one B-cell linear epitope from each one of them was selected using B-cell epitope score and the presence of intrinsically disordered regions (IDRs). These predicted epitopes generated synthetic peptides that were used in ELISA assays to validate the rational strategy of selection. ELISA was performed using sera from residents of areas of low endemicity for infection and also from healthy Hes2 donors (HD), not living in an endemic area for schistosomiasis. Discrimination of negative (NEG) and positive (INF) individuals from endemic areas was performed using parasitological and molecular methods. All infected individuals were treated with praziquantel, and serum samples were obtained from them 30 and 180 days post-treatment (30DPT and 180DPT). Results revealed higher IgG levels in INF group than in HD and NEG groups when peptides 1, 3, 4, 5 and 7 were used. Moreover, using peptide 5, ELISA achieved the best performance, since it could discriminate between individuals living in an endemic area that were actively infected from those that were not (NEG, 30DPT, 180DPT groups). Our experimental results also indicate that the computational prediction approach developed is feasible for identifying promising candidates for the diagnosis of Lactitol schistosomiasis and other diseases. Introduction Schistosomiasis remains one of the most prevalent parasitic diseases in the world with more than 240 million people infected in 78 countries [1]. Control strategies have been based on chemotherapy, but these attempts have failed to interrupt transmission. Part of this failure could be attributed to the absence of an accurate method of diagnosis that is able to determine the real prevalence of the disease in populations, and that could monitor the success of interventions and assess healing after therapeutic intervention [2C4]. Parasitological tests are still the most widely used diagnostic methods of schistosomiasis control programs [5,6], and of these, the Kato-Katz technique is the most used due to its low cost, abillity to detect different helminths infection and greater sensibility in reas high intensity infections [7C9]. However, low parasite burdens require examination of more slides or association of the parasitological tests with serological and molecular techniques to have an accurate diagnosis of the disease. In fact, molecular and immunological techniques have proven to be more sensitive and promising in identifying infection in individuals with negative coproscopic results [10C15]. An example of an immunological technique that has provided satisfactory results in the diagnosis of schistosomiasis is the urine-based point-of-care (POC-CCA) assay for detecting circulating cathodic antigen in urine samples (Rapid Medical Diagnostics, Pretoria, South Africa). This test Lactitol has demonstrated promise for use in epidemiological studies, in clinical laboratories and in endemic areas, with higher sensitivity than the Kato-Katz technique [16C19]. However, more studies are necessary to assess the efficacy of this technique in the field, especially in areas of low endemicity [20,21]. Immunodiagnostic methods based on serology have been widely used and have greater.