Exploring chemical conversions in metabolic networks by tracing atoms transitions

Dissertação de mestrado em Bioinformática

Quantitative image analysis as a tool for Yarrowia lipolytica dimorphic growth evaluation in different culture media

Yarrowia lipolytica, a yeast strain with a huge biotechnological potential, capable to produce metabolites such as γ-decalactone, citric acid, intracellular lipids and enzymes, possesses the ability to change its morphology in response to environmental conditions. In the present study, a quantitative image analysis (QIA) procedure was developed for the identification and quantification of Y. lipolytica W29 and MTLY40-2P strains dimorphic growth, cultivated in batch cultures on hydrophilic (glucose and N-acetylglucosamine (GlcNAc) and hydrophobic (olive oil and castor oil) media. The morphological characterization of yeast cells by QIA techniques revealed that hydrophobic carbon sources, namely castor oil, should be preferred for both strains growth in the yeast single cell morphotype. On the other hand, hydrophilic sugars, namely glucose and GlcNAc caused a dimorphic transition growth towards the hyphae morphotype. Experiments for γ-decalactone production with MTLY40-2P strain in two distinct morphotypes (yeast single cells and hyphae cells) were also performed. The obtained results showed the adequacy of the proposed morphology monitoring tool in relation to each morphotype on the aroma production ability. The present work allowed establishing that QIA techniques can be a valuable tool for the identification of the best culture conditions for industrial processes implementation.

Modelling integral viscoelastic flows in OpenFOAM

[Excerpt] A large number of constitutive equations were developed for viscoelastic fluids, some empirical and other with strong physical foundations. The currently available macroscopic constitutive equations can be divided in two main types: differential and integral. Some of the constitutive equations, e.g. Maxwell are available both in differential and integral types. However, relevant in tegral models, like K - BKZ, just possesses the integral form. (...)

Assessment of the properties to characterize the interface between clay brick substrate and strengthening mortar

The behaviour of masonry elements under in-plane and out-of-plane loads can be improved through the application of strengthening systems based on reinforcing overlays. After strengthening, the transition region between the original substrate and the strengthening layer is especially stressed, and premature failure of the strengthened masonry is reached if insufficient interfacial capacity is assured. Therefore, the assessment of the mechanical behaviour of the interface is critical to the development of the masonry strengthening system based on the application of strengthening overlays. In this research a method for the characterization of the interface behaviour between two different materials, a polypropylene fibre reinforced mortar (PFRM) and a ceramic brick used for masonry construction is presented. Direct shear tests were carried out in couplet specimens. Due to the orthotropic nature of the bricks surface, the shear load was applied along three different directions in order to perform an overall estimation of the interface behaviour. The peak and residual shear stresses, as well as the failure modes, were obtained at different levels of the normal stress. Based on these experimental results constitutive laws were assessed for the simulation of the interface mechanical behaviour based on the Mohr and Mohr-Coulomb failure criteria.

Discrimination of Brazilian propolis according to the seasoning using chemometrics and machine learning based on UV-Vis scanning data

Propolis is a chemically complex biomass produced by honeybees (Apis mellifera) from plant resins added of salivary enzymes, beeswax, and pollen. The biological activities described for propolis were also identified for donor plants resin, but a big challenge for the standardization of the chemical composition and biological effects of propolis remains on a better understanding of the influence of seasonality on the chemical constituents of that raw material. Since propolis quality depends, among other variables, on the local flora which is strongly influenced by (a)biotic factors over the seasons, to unravel the harvest season effect on the propolis chemical profile is an issue of recognized importance. For that, fast, cheap, and robust analytical techniques seem to be the best choice for large scale quality control processes in the most demanding markets, e.g., human health applications. For that, UV-Visible (UV-Vis) scanning spectrophotometry of hydroalcoholic extracts (HE) of seventy-three propolis samples, collected over the seasons in 2014 (summer, spring, autumn, and winter) and 2015 (summer and autumn) in Southern Brazil was adopted. Further machine learning and chemometrics techniques were applied to the UV-Vis dataset aiming to gain insights as to the seasonality effect on the claimed chemical heterogeneity of propolis samples determined by changes in the flora of the geographic region under study. Descriptive and classification models were built following a chemometric approach, i.e. principal component analysis (PCA) and hierarchical clustering analysis (HCA) supported by scripts written in the R language. The UV-Vis profiles associated with chemometric analysis allowed identifying a typical pattern in propolis samples collected in the summer. Importantly, the discrimination based on PCA could be improved by using the dataset of the fingerprint region of phenolic compounds ( = 280-400m), suggesting that besides the biological activities of those secondary metabolites, they also play a relevant role for the discrimination and classification of that complex matrix through bioinformatics tools. Finally, a series of machine learning approaches, e.g., partial least square-discriminant analysis (PLS-DA), k-Nearest Neighbors (kNN), and Decision Trees showed to be complementary to PCA and HCA, allowing to obtain relevant information as to the sample discrimination.

Extracting kinetic information from literature with KineticRE

To better understand the dynamic behavior of metabolic networks in a wide variety of conditions, the field of Systems Biology has increased its interest in the use of kinetic models. The different databases, available these days, do not contain enough data regarding this topic. Given that a significant part of the relevant information for the development of such models is still wide spread in the literature, it becomes essential to develop specific and powerful text mining tools to collect these data. In this context, this work has as main objective the development of a text mining tool to extract, from scientific literature, kinetic parameters, their respective values and their relations with enzymes and metabolites. The approach proposed integrates the development of a novel plug-in over the text mining framework @Note2. In the end, the pipeline developed was validated with a case study on Kluyveromyces lactis, spanning the analysis and results of 20 full text documents.

A review of mycotoxins in food and feed products in Portugal and estimation of probable daily intakes

Mycotoxins are toxic secondary metabolites produced by filamentous fungi that occur naturally in agricultural commodities worldwide. Aflatoxins, ochratoxin A, patulin, fumonisins, zearalenone, trichothecenes and ergot alkaloids are presently the most important for food and feed safety. These compounds are produced by several species that belong to the Aspergillus, Penicillium, Fusarium and Claviceps genera and can be carcinogenic, mutagenic, teratogenic, cytotoxic, neurotoxic, nephrotoxic, estrogenic and immunosuppressant. Human and animal exposure to mycotoxins is generally assessed by taking into account data on the occurrence of mycotoxins in food and feed as well as data on the consumption patterns of the concerned population. This evaluation is crucial to support measures to reduce consumer exposure to mycotoxins. This work reviews the occurrence and levels of mycotoxins in Portuguese food and feed to provide a global overview of this issue in Portugal. With the information collected, the exposure of the Portuguese population to those mycotoxins is assessed, and the estimated dietary intakes are presented.

Daldinia eschscholtzii (Ascomycota, Xylariaceae) isolated from the Brazilian Amazon: taxonomic features and mycelial growth conditions

The Amazon has a high diversity of fungi, including species of the genus Daldinia (Ascomycota, Xylariaceae), which produce secondary metabolites with recognized nematicidal and antimicrobial activity. The ecological role of Daldinia is important, as stromata serve as refuges to many insects and arthropodes, and the fungi contribute to the degradation of vegetable organic matter. The aim of this study was to analyze the taxonomic features and mycelial growth conditions in vitro of a Daldinia specimen collected in the Brazilian Amazon. Morphological and molecular studies of the fungus identified it as D. eschscholtzii. To evaluate mycelial growth, we cultivated the fungus at 20, 25, 30, 35, and 40 °C in malt extract-peptone agar (MEPA), malt extract-peptone (MEP), potato dextrose (PD), and minimum medium (MM). The best mycelial growth occurred at 35 °C, although the greatest amount of biomass was obtained at 25 °C and 30 °C. PD proved to be the best medium for biomass production.

Dynamic interface model for masonry walls subjected to high strain rate out-of-plane loads

The present study proposes a dynamic constitutive material interface model that includes non-associated flow rule and high strain rate effects, implemented in the finite element code ABAQUS as a user subroutine. First, the model capability is validated with numerical simulations of unreinforced block work masonry walls subjected to low velocity impact. The results obtained are compared with field test data and good agreement is found. Subsequently, a comprehensive parametric analysis is accomplished with different joint tensile strengths and cohesion, and wall thickness to evaluate the effect of the parameter variations on the impact response of masonry walls.

Metabolic profiling and classification of propolis samples from Southern Brazil: an NMR-based platform coupled with machine learning

The chemical composition of propolis is affected by environmental factors and harvest season, making it difficult to standardize its extracts for medicinal usage. By detecting a typical chemical profile associated with propolis from a specific production region or season, certain types of propolis may be used to obtain a specific pharmacological activity. In this study, propolis from three agroecological regions (plain, plateau, and highlands) from southern Brazil, collected over the four seasons of 2010, were investigated through a novel NMR-based metabolomics data analysis workflow. Chemometrics and machine learning algorithms (PLS-DA and RF), including methods to estimate variable importance in classification, were used in this study. The machine learning and feature selection methods permitted construction of models for propolis sample classification with high accuracy (>75%, reaching 90% in the best case), better discriminating samples regarding their collection seasons comparatively to the harvest regions. PLS-DA and RF allowed the identification of biomarkers for sample discrimination, expanding the set of discriminating features and adding relevant information for the identification of the class-determining metabolites. The NMR-based metabolomics analytical platform, coupled to bioinformatic tools, allowed characterization and classification of Brazilian propolis samples regarding the metabolite signature of important compounds, i.e., chemical fingerprint, harvest seasons, and production regions.

Seasonal effects and antifungal activity from bark chemical constituents of Sterculia apetala (Malvaceae) at Pantanal of Miranda, Mato Grosso do Sul, Brazil

In the Southern Pantanal, the hyacinth macaw (Anodorhynchus hyacinthinus), an endangered species, often chooses the manduvi tree (Sterculia apetala) as a nesting site, because of its physical properties. In addition, the chemical composition of the wood may also contribute to a nesting selection by the hyacinth macaws. The objective of this study was to determine the main chemical components of S. apetala bark for two seasons, and evaluate its fungicidal potential. Bark samples from S. apetala trees with and without nests of A. hyacinthinus were collected in January (wet season) and August (dry season) of 2012. The inhibition of mycelium growth (MGI) from tree samples with and without nests were assessed using a phytochemical analysis to evaluate their antifungal activity against Trichoderma sp. Phytochemical analysis confirmed the presence of phenolic compounds and flavonoids. In both seasons, samples obtained from nested trees had higher content of total phenols than those collected from non-nested trees. The average content of total flavonoids was higher in January for samples with nest and in August for samples without nest. All selected samples showed antifungal activity, and those with nest collected in August (peak of hyacinth macaw breeding) resulted in an MGI of 51.3%. Therefore, this percentage, related to the content of flavonoids and the presence of coumarins, may influence the reproductive success of hyacinth macaws and other species of birds, in this region. This is the first chemical study report with the stem bark of S. apetala.

Influence of casting condition on the anisotropy of the fracture properties of Steel Fibre Reinforced Self-Compacting Concrete (SFRSCC)

Identification of the tensile constitutive behaviour of Fibre Reinforced Concrete (FRC) represents an important aspect of the design of structural elements using this material. Although an important step has been made with the introduction of guidance for the design with regular FRC in the recently published fib Model Code 2010, a better understanding of the behaviour of this material is still necessary, mainly for that with self-compacting properties. This work presents an experimental investigation employing Steel Fibre Self-Compacting Concrete (SFRSCC) to cast thin structural elements. A new test method is proposed for assessing the post-cracking behaviour and the results obtained with the proposed test method are compared with the ones resulted from the standard three-point bending tests (3PBT). Specimens extracted from a sandwich panel consisting of SFRSCC layers are also tested. The mechanical properties of SFRSCC are correlated to the fibre distribution by analysing the results obtained with the different tests. Finally, the stress-crack width constitutive law proposed by the fib Model Code 2010 is analysed in light of the experimental results.

Atividade fotossintética do bago de uva (Vitis vinifera, cv. Alvarinho) ao longo do desenvolvimento dos cachos em diferentes microambientes de luz

Dissertação de mestrado em Biologia Molecular, Biotecnologia e Bioempreendedorismo em Plantas

Biotechnological approaches for yield improvement of anticancer alkaloids in the plant Catharanthus roseus

Dissertação de mestrado em Biologia Molecular, Biotecnologia e Bioempreendedorismo em Plantas

Phytosterols isolated from endophytic fungus Colletotrichum gloeosporioides(Melanconiaceae)

ABSTRACTEndophytic fungi are fungi that colonize internal tissues of plants. There are few studies of compounds isolated from endophytic fungi of Amazon plants. Thus, the aim this study was the isolation and structural identification of sitosterol (1), stigmasterol (2), sitostenone (3), squalene (4), ergosterol (5) and ergosterol peroxide (6) from fungus Colletotrichum gloeosporioidesisolated as endophytic from Virola michelli, a typical Amazon plant, used in folk medicine against skin infection. Compounds were isolated by chromatography column on silica and identified by 1H and 13C NMR and MS. The presence of phytosterols in fungi is rare and this is the first report of the isolation of the phytosterols sitosterol, stigmasterol and sitostenone from the genus Colletotrichum.