BackgroundSeveral cases of food-borne acute Chagas disease (ACD) have been reported in the Brazilian Amazon so far. Up to 2004, the occurrence of ACD by oral transmission, associated with food consumption, was rare. Recent cases of ACD in Brazil have been attributed to the consumption of juice from the açai palm containing reservoir animals or insect vectors waste, infected with Trypanosoma cruzi. This study aimed to determine the T. cruzi contamination rate and to genotype the parasite in food samples prepared from açai, which are commercialized in Rio de Janeiro and the Pará States in Brazil.MethodsThe amplificability of DNA extracted from açai samples, and T. cruzi and Triatominae detection were performed by conventional PCR. Molecular characterization was done by multilocus PCR analysis, to determine the parasite discrete type units (DTUs) based on the size of PCR products in agarose gels, using the intergenic region of the spliced leader (SL), 24 Sα rDNA and nuclear fragment A10 as targets.ResultsFrom the 140 samples of açai-based products analyzed, T. cruzi DNA was detected in 14 samples (10%); triatomine DNA was detected in one of these 14 samples. The parasite genotyping demonstrated that food samples containing açai showed a mixture of T. cruzi DTUs with TcIII, TcV and TcI prevailing.ConclusionsIn this study, the molecular detection and identification of T. cruzi from açai-based manufactured food samples, was performed for the first time. Although parasite DNA is a marker of possible contamination during food manufacturing, our findings do not indicate that açai is a source of Chagas disease via oral transmission per se, as live parasites were not investigated. Nevertheless, a molecular approach could be a powerful tool in the epidemiological investigation of outbreaks, supporting previous evidence that açai-based food can be contaminated with T. cruzi. Furthermore, both food quality control and assessment of good manufacturing practices involving açai-based products can be improved, assuring the safety of açai products.

Background: Chemogenomic techniques use mathematical calculations to predict new drug-target interactions (DTIs) based on drugs' chemical and biological information and pharmacological targets. Compared to other structure-based computational methods, they are faster and less expensive. Network analysis and matrix factorization are two practical chemogenomic approaches for predicting DTIs from many drugs and targets. However, despite the extensive literature introducing various chemogenomic techniques and methodologies, there is no consensus for predicting interactions using a drug or a target, a set of drugs, and a dataset of known interactions. Methods: This study predicted novel DTIs from a limited collection of drugs using a heterogeneous ensemble based on network and matrix factorization techniques. We examined three network-based approaches and two matrix factorization-based methods on benchmark datasets. Then, we used one network approach and one matrix factorization technique on a small collection of Brazilian plant-derived pharmaceuticals. Results: We have discovered two novel DTIs and compared them to the Therapeutic Target Database to detect linked disorders, such as breast cancer, prostate cancer, and Cushing syndrome, with two drugs (Quercetin and Luteolin) originating from Brazilian plants. Conclusions: The suggested approach allows assessing the performance of approaches only based on their sensitivity, independent of their unfavorable interactions. Findings imply that integrating network and matrix factorization results might be a helpful technique in bioinformatics investigations involving the development of novel medicines from a limited range of drugs.

No abstract