New bio-strategies for ochratoxin A detoxification using lactic acid bacteria

The occurrence of mycotoxigenic moulds such as Aspergillus, Penicillium and Fusarium in food and feed has an important impact on public health, by the appearance of acute and chronic mycotoxicoses in humans and animals, which is more severe in the developing countries due to lack of food security, poverty and malnutrition. This mould contamination also constitutes a major economic problem due the lost of crop production. A great variety of filamentous fungi is able to produce highly toxic secondary metabolites known as mycotoxins. Most of the mycotoxins are carcinogenic, mutagenic, neurotoxic and immunosuppressive, being ochratoxin A (OTA) one of the most important. OTA is toxic to animals and humans, mainly due to its nephrotoxic properties. Several approaches have been developed for decontamination of mycotoxins in foods, such as, prevention of contamination, biodegradation of mycotoxins-containing food and feed with microorganisms or enzymes and inhibition or absorption of mycotoxin content of consumed food into the digestive tract. Some group of Gram-positive bacteria named lactic acid bacteria (LAB) are able to release some molecules that can influence the mould growth, improving the shelf life of many fermented products and reducing health risks due to exposure to mycotoxins. Some LAB are capable of mycotoxin detoxification. Recently our group was the first to describe the ability of LAB strains to biodegrade OTA, more specifically, Pediococcus parvulus strains isolated from Douro wines. The pathway of this biodegradation was identified previously in other microorganisms. OTA can be degraded through the hydrolysis of the amide bond that links the L-β-phenylalanine molecule to the ochratoxin alpha (OTα) a non toxic compound. It is known that some peptidases from different origins can mediate the hydrolysis reaction like, carboxypeptidase A an enzyme from the bovine pancreas, a commercial lipase and several commercial proteases. So, we wanted to have a better understanding of this OTA degradation process when LAB are involved and identify which molecules where present in this process. For achieving our aim we used some bioinformatics tools (BLAST, CLUSTALX2, CLC Sequence Viewer 7, Finch TV). We also designed specific primers and realized gene specific PCR. The template DNA used came from LAB strains samples of our previous work, and other DNA LAB strains isolated from elderberry fruit, silage, milk and sausages. Through the employment of bioinformatics tools it was possible to identify several proteins belonging to the carboxypeptidase family that participate in the process of OTA degradation, such as serine type D-Ala-D-Ala carboxypeptidase and membrane carboxypeptidase. In conclusions, this work has identified carboxypeptidase proteins being one of the molecules present in the OTA degradation process when LAB are involved.

A critical evaluation of methods for the reconstruction of tissue-specific models

Under the framework of constraint based modeling, genome-scale metabolic models (GSMMs) have been used for several tasks, such as metabolic engineering and phenotype prediction. More recently, their application in health related research has spanned drug discovery, biomarker identification and host-pathogen interactions, targeting diseases such as cancer, Alzheimer, obesity or diabetes. In the last years, the development of novel techniques for genome sequencing and other high-throughput methods, together with advances in Bioinformatics, allowed the reconstruction of GSMMs for human cells. Considering the diversity of cell types and tissues present in the human body, it is imperative to develop tissue-specific metabolic models. Methods to automatically generate these models, based on generic human metabolic models and a plethora of omics data, have been proposed. However, their results have not yet been adequately and critically evaluated and compared. This work presents a survey of the most important tissue or cell type specific metabolic model reconstruction methods, which use literature, transcriptomics, proteomics and metabolomics data, together with a global template model. As a case study, we analyzed the consistency between several omics data sources and reconstructed distinct metabolic models of hepatocytes using different methods and data sources as inputs. The results show that omics data sources have a poor overlapping and, in some cases, are even contradictory. Additionally, the hepatocyte metabolic models generated are in many cases not able to perform metabolic functions known to be present in the liver tissue. We conclude that reliable methods for a priori omics data integration are required to support the reconstruction of complex models of human cells.

Predicting triage waiting time in maternity emergency care by means of data mining

Healthcare organizations often benefit from information technologies as well as embedded decision support systems, which improve the quality of services and help preventing complications and adverse events. In Centro Materno Infantil do Norte (CMIN), the maternal and perinatal care unit of Centro Hospitalar of Oporto (CHP), an intelligent pre-triage system is implemented, aiming to prioritize patients in need of gynaecology and obstetrics care in two classes: urgent and consultation. The system is designed to evade emergency problems such as incorrect triage outcomes and extensive triage waiting times. The current study intends to improve the triage system, and therefore, optimize the patient workflow through the emergency room, by predicting the triage waiting time comprised between the patient triage and their medical admission. For this purpose, data mining (DM) techniques are induced in selected information provided by the information technologies implemented in CMIN. The DM models achieved accuracy values of approximately 94% with a five range target distribution, which not only allow obtaining confident prediction models, but also identify the variables that stand as direct inducers to the triage waiting times.

Localização de conteúdos: experiência de estágio na Bloomidea

Relatório de estágio de mestrado em Tradução e Comunicação Multilingue