67 resultados para Unicellular organisms
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Dissertation presented to obtain the Ph.D degree in Biochemistry.
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Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous priority pollutants that tend to be trapped in aquatic sediments due to their high hydrophobicity. Nonetheless, the differential toxicological effects and mechanisms between the various classes of PAHs and their mixtures, as they invariably occur in the environment, are scarcely known, especially under ecologically-relevant scenarios. This thesis aimed at establishing a bridge between the study of mechanistic pathways and environmental monitoring of carcinogenic and non-carcinogenic PAHs, by introducing ecological-relevance in the research with model PAHs. A first bioassay conducted in situ with the mussel Mytilus edulis demonstrated that, dredging operations in harbours increase PAH bioavailability, eliciting genotoxicity, and showed that established environmental guidelines underestimate risk. Subsequent ex situ bioassays were performed with the carcinogenic benzo[b]fluoranthene (B[b]F) and non-carcinogenic phenantrene (Phe), selected following preceding results, and revealed that low-moderate concentrations of these PAHs in spiked sediments induce genotoxic effects to the clam Ruditapes decussatus, therefore contradicting the general notion that bivalves are less sensitive to PAHs than vertebrates due to inefficient bioactivation. Also, it was demonstrated that passive samplers permit inferring on PAH bioavailability but not on bioaccumulation or toxic effects. On the other hand, sea basses (Dicentrarchus labrax), yielded a complex pattern of effects and responses, relatively to genotoxicity, oxidative stress and production of specific metabolites, especially when exposed to mixtures of the PAHs which led to additive, if not synergistic, effects. It was shown that Phe may elicit significant genotoxicity especially in presence of B[b]F, even though the low, albeit realistic, exposure concentrations diluted dose- and time-independent relationships. The present work demonstrated that environmental quality guidelines underestimate the effects of PAHs in realistic scenarios and showed that the significant genotoxic and histopathological effects caused by mixed PAHs may not be reflected by oxidative stress- or CYP-related biomarkers. Besides important findings on the metabolism of PAH mixtures, the work calls for the need to re-evaluate the criteria for assessing risk and for the disclosure of more efficient indicators of toxicological hazard.
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In Portugal, Carixian is generally represented by alternative layers of marly limestones characterized by nodule and lumpy levels. These layers are particularly developped [show preferential development] on passage areas to a sedimentary basin, particularly along the slope of tilted blocks between the Meseta and Berlenga's horst. This facies is included in the range of the «nodular limestone» and of the «ammonitico-rosso». Limestones are radiolaria micrites with fragments of pelagic organisms (ammonoids, thin shelled gastropods). These layers can be affected by intensive bioturbation (Brenha) which is responsible for dismantlement, specially where the initial thickness does not exceed a few centimetres. This process can lead to the isolation of residual nodules (Brenha, São Pedro de Muel, Peniche) which can be mobilised by massive sliding (Peniche). The isolated elements, shell fragments or residual nodules, can also be incrustated, thus developing oncolitic cryptalgal structures. At Brenha the lump structure developed progressively into a sequence overlapping the normal sedimentary one (thick limestone beds alternating with bituminous shales). Cryptalgal structures correspond to rather unstable environment conditions on mobile margins. These structures are known in deep pelagic sediments corresponding to well defined events of the geodynamic evolution (end of the initial rifting). Cryptalgal accretions disappear towards the sedimentary basin, and the nodular levels are less important. In the articulation areas with the Tomar platform, small mounds and cupules (Alcabideque) developed within the alternating marly-limestone levels. They represent the so called «mud mounds» of metric dimensions. The upper part of these «mud mounds» is hardened, showing track remains and supporting some brachiopods and pectinids. Hence the lumpy facies of Portugal is included among the range of sedimentaty environments and can be used as «geodynamic tracer».
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This Thesis describes the application of automatic learning methods for a) the classification of organic and metabolic reactions, and b) the mapping of Potential Energy Surfaces(PES). The classification of reactions was approached with two distinct methodologies: a representation of chemical reactions based on NMR data, and a representation of chemical reactions from the reaction equation based on the physico-chemical and topological features of chemical bonds. NMR-based classification of photochemical and enzymatic reactions. Photochemical and metabolic reactions were classified by Kohonen Self-Organizing Maps (Kohonen SOMs) and Random Forests (RFs) taking as input the difference between the 1H NMR spectra of the products and the reactants. The development of such a representation can be applied in automatic analysis of changes in the 1H NMR spectrum of a mixture and their interpretation in terms of the chemical reactions taking place. Examples of possible applications are the monitoring of reaction processes, evaluation of the stability of chemicals, or even the interpretation of metabonomic data. A Kohonen SOM trained with a data set of metabolic reactions catalysed by transferases was able to correctly classify 75% of an independent test set in terms of the EC number subclass. Random Forests improved the correct predictions to 79%. With photochemical reactions classified into 7 groups, an independent test set was classified with 86-93% accuracy. The data set of photochemical reactions was also used to simulate mixtures with two reactions occurring simultaneously. Kohonen SOMs and Feed-Forward Neural Networks (FFNNs) were trained to classify the reactions occurring in a mixture based on the 1H NMR spectra of the products and reactants. Kohonen SOMs allowed the correct assignment of 53-63% of the mixtures (in a test set). Counter-Propagation Neural Networks (CPNNs) gave origin to similar results. The use of supervised learning techniques allowed an improvement in the results. They were improved to 77% of correct assignments when an ensemble of ten FFNNs were used and to 80% when Random Forests were used. This study was performed with NMR data simulated from the molecular structure by the SPINUS program. In the design of one test set, simulated data was combined with experimental data. The results support the proposal of linking databases of chemical reactions to experimental or simulated NMR data for automatic classification of reactions and mixtures of reactions. Genome-scale classification of enzymatic reactions from their reaction equation. The MOLMAP descriptor relies on a Kohonen SOM that defines types of bonds on the basis of their physico-chemical and topological properties. The MOLMAP descriptor of a molecule represents the types of bonds available in that molecule. The MOLMAP descriptor of a reaction is defined as the difference between the MOLMAPs of the products and the reactants, and numerically encodes the pattern of bonds that are broken, changed, and made during a chemical reaction. The automatic perception of chemical similarities between metabolic reactions is required for a variety of applications ranging from the computer validation of classification systems, genome-scale reconstruction (or comparison) of metabolic pathways, to the classification of enzymatic mechanisms. Catalytic functions of proteins are generally described by the EC numbers that are simultaneously employed as identifiers of reactions, enzymes, and enzyme genes, thus linking metabolic and genomic information. Different methods should be available to automatically compare metabolic reactions and for the automatic assignment of EC numbers to reactions still not officially classified. In this study, the genome-scale data set of enzymatic reactions available in the KEGG database was encoded by the MOLMAP descriptors, and was submitted to Kohonen SOMs to compare the resulting map with the official EC number classification, to explore the possibility of predicting EC numbers from the reaction equation, and to assess the internal consistency of the EC classification at the class level. A general agreement with the EC classification was observed, i.e. a relationship between the similarity of MOLMAPs and the similarity of EC numbers. At the same time, MOLMAPs were able to discriminate between EC sub-subclasses. EC numbers could be assigned at the class, subclass, and sub-subclass levels with accuracies up to 92%, 80%, and 70% for independent test sets. The correspondence between chemical similarity of metabolic reactions and their MOLMAP descriptors was applied to the identification of a number of reactions mapped into the same neuron but belonging to different EC classes, which demonstrated the ability of the MOLMAP/SOM approach to verify the internal consistency of classifications in databases of metabolic reactions. RFs were also used to assign the four levels of the EC hierarchy from the reaction equation. EC numbers were correctly assigned in 95%, 90%, 85% and 86% of the cases (for independent test sets) at the class, subclass, sub-subclass and full EC number level,respectively. Experiments for the classification of reactions from the main reactants and products were performed with RFs - EC numbers were assigned at the class, subclass and sub-subclass level with accuracies of 78%, 74% and 63%, respectively. In the course of the experiments with metabolic reactions we suggested that the MOLMAP / SOM concept could be extended to the representation of other levels of metabolic information such as metabolic pathways. Following the MOLMAP idea, the pattern of neurons activated by the reactions of a metabolic pathway is a representation of the reactions involved in that pathway - a descriptor of the metabolic pathway. This reasoning enabled the comparison of different pathways, the automatic classification of pathways, and a classification of organisms based on their biochemical machinery. The three levels of classification (from bonds to metabolic pathways) allowed to map and perceive chemical similarities between metabolic pathways even for pathways of different types of metabolism and pathways that do not share similarities in terms of EC numbers. Mapping of PES by neural networks (NNs). In a first series of experiments, ensembles of Feed-Forward NNs (EnsFFNNs) and Associative Neural Networks (ASNNs) were trained to reproduce PES represented by the Lennard-Jones (LJ) analytical potential function. The accuracy of the method was assessed by comparing the results of molecular dynamics simulations (thermal, structural, and dynamic properties) obtained from the NNs-PES and from the LJ function. The results indicated that for LJ-type potentials, NNs can be trained to generate accurate PES to be used in molecular simulations. EnsFFNNs and ASNNs gave better results than single FFNNs. A remarkable ability of the NNs models to interpolate between distant curves and accurately reproduce potentials to be used in molecular simulations is shown. The purpose of the first study was to systematically analyse the accuracy of different NNs. Our main motivation, however, is reflected in the next study: the mapping of multidimensional PES by NNs to simulate, by Molecular Dynamics or Monte Carlo, the adsorption and self-assembly of solvated organic molecules on noble-metal electrodes. Indeed, for such complex and heterogeneous systems the development of suitable analytical functions that fit quantum mechanical interaction energies is a non-trivial or even impossible task. The data consisted of energy values, from Density Functional Theory (DFT) calculations, at different distances, for several molecular orientations and three electrode adsorption sites. The results indicate that NNs require a data set large enough to cover well the diversity of possible interaction sites, distances, and orientations. NNs trained with such data sets can perform equally well or even better than analytical functions. Therefore, they can be used in molecular simulations, particularly for the ethanol/Au (111) interface which is the case studied in the present Thesis. Once properly trained, the networks are able to produce, as output, any required number of energy points for accurate interpolations.
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Dissertação apresentada para a obtenção do Grau de Doutor em Bioquímica, especialidade de Bioquímica-Física pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia
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Dissertation presented to obtain a Ph.D. degree in Biology, speciality Microbiology, by Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia
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Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia do Ambiente, perfil Engenharia Sanitária
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Aging is a long-standing biological question of tremendous social and cultural importance. Despite this, only in the last 15 years has biology started to make significant progress in understanding the underlying mechanisms that regulate aging. This progress stemmed mainly from the use of model organisms, which allowed the discovery of several genes directly modulating longevity. Interestingly, several of these longevity genes are necessary for normal mitochondrial function, and disruption of their activity delays the aging process. This is somewhat paradoxical, considering the importance of cellular respiration for energy production and viability of eukaryotic organisms. One possible rationalization for this is that by decreasing cellular respiration, reactive oxygen species (ROS) generation is also reduced, and in that way, cellular decay and aging are delayed.(...)
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Microbiology (2009), 155, 3476–3490
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International Biodeterioration & Biodegradation 64(2010)388 e 396
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Dinoflagellates are planktonic unicellular microorganisms, that under certain conditions may produce cysts prone to fossilization. These cysts are abundant in the sedimentary record since the Palaeozoic, supplying important biostratigraphical and palaeoecological information. In Portugal, the study of dinoflagellates is still in its beginnings. Considering the late developments in this domain, an updated nomenclature in Portuguese language is presented, pertaining to it's biology, taxonomy, ecology, palaeoecology and biostratigraphy.
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Similarly to other organisms, Vertebrates changed during the Cenozoic Era. Mammals are the only ones to change quickly; their well mineralised bones and teeth are often fossilised. They are highly diverse and even isolated teeth can be identified. They are thus a good tool for establishing a biochronological framewoork. Among Mammals, Rodents with a short lifetime evolve more quickly than the large Mammals. In Europe, the first elaborated zonation was investigated by the Regional Committee on Neogene Stratigraphy and issued as the MN Zonation (Mammals Neogene) by Mein, 1976. During the following years, progress in knowledge lead to new charts. The latest one resulted from collective work (de Bruijn et al., 1992). Bîochronology gives relative data; if we desire to have numerical age estimates, we must correlate these results with radiometrie data, marine biostratigraphîcal units or the Geomagnetic Polarity Time Scale. For Europe, these results are summarised by Steininger et al. (1989-1996) and Steininger (1999). After some recents developments on MN Zonation, here is discussed the succession of Neogene small mammals Portuguese localities. Fortunately these localities are in majority inbedded in marine context. Their assigment to MN Zones is proposed and correlations with the spanish Aragonian Scale (Daams el al., 1999) are also suggested. In fact, some differences appear between Portugal and Aragonian assemblages, probably for ecological reasons. Therefore, the MN zonation is always useful for short and long distance biochronological correlations.
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Dissertação apresentada para obtenção do grau de Doutor em Bioquímica,especialidade Bioquímica-Física, pela Universidade Nova de Lisboa, Faculdade de Cincias e Tecnologia
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Abstract The emergence of multi and extensively drug resistant tuberculosis (MDRTB and XDRTB) has increased the concern of public health authorities around the world. The World Health Organization has defined MDRTB as tuberculosis (TB) caused by organisms resistant to at least isoniazid and rifampicin, the main first-line drugs used in TB therapy, whereas XDRTB refers to TB resistant not only to isoniazid and rifampicin, but also to a fluoroquinolone and to at least one of the three injectable second-line drugs, kanamycin, amikacin and capreomycin. Resistance in Mycobacterium tuberculosis is mainly due to the occurrence of spontaneous mutations and followed by selection of mutants by subsequent treatment. However, some resistant clinical isolates do not present mutations in any genes associated with resistance to a given antibiotic, which suggests that other mechanism(s) are involved in the development of drug resistance, namely the presence of efflux pump systems that extrude the drug to the exterior of the cell, preventing access to its target. Increased efflux activity can occur in response to prolonged exposure to subinhibitory concentrations of anti-TB drugs, a situation that may result from inadequate TB therapy. The inhibition of efflux activity with a non-antibiotic inhibitor may restore activity of an antibiotic subject to efflux and thus provide a way to enhance the activity of current anti-TB drugs. The work described in this thesis foccus on the study of efflux mechanisms in the development of multidrug resistance in M. tuberculosis and how phenotypic resistance, mediated by efflux pumps, correlates with genetic resistance. In order to accomplish this goal, several experimental protocols were developed using biological models such as Escherichia coli, the fast growing mycobacteria Mycobacterium smegmatis, and Mycobacterium avium, before their application to M. tuberculosis. This approach allowed the study of the mechanisms that result in the physiological adaptation of E. coli to subinhibitory concentrations of tetracycline (Chapter II), the development of a fluorometric method that allows the detection and quantification of efflux of ethidium bromide (Chapter III), the characterization of the ethidium bromide transport in M. smegmatis (Chapter IV) and the contribution of efflux activity to macrolide resistance in Mycobacterium avium complex (Chapter V). Finally, the methods developed allowed the study of the role of efflux pumps in M. tuberculosis strains induced to isoniazid resistance (Chapter VI). By this manner, in Chapter II it was possible to observe that the physiological adaptation of E. coli to tetracycline results from an interplay between events at the genetic level and protein folding that decrease permeability of the cell envelope and increase efflux pump activity. Furthermore, Chapter III describes the development of a semi-automated fluorometric method that allowed the correlation of this efflux activity with the transport kinetics of ethidium bromide (a known efflux pump substrate) in E. coli and the identification of efflux inhibitors. Concerning M. smegmatis, we have compared the wild-type M. smegmatis mc2155 with knockout mutants for LfrA and MspA for their ability to transport ethidium bromide. The results presented in Chapter IV showed that MspA, the major porin in M. smegmatis, plays an important role in the entrance of ethidium bromide and antibiotics into the cell and that efflux via the LfrA pump is involved in low-level resistance to these compounds in M. smegmatis. Chapter V describes the study of the contribution of efflux pumps to macrolide resistance in clinical M. avium complex isolates. It was demonstrated that resistance to clarithromycin was significantly reduced in the presence of efflux inhibitors such as thioridazine, chlorpromazine and verapamil. These same inhibitors decreased efflux of ethidium bromide and increased the retention of [14C]-erythromycin in these isolates. Finaly, the methods developed with the experimental models mentioned above allowed the study of the role of efflux pumps on M. tuberculosis strains induced to isoniazid resistance. This is described in Chapter VI of this Thesis, where it is demonstrated that induced resistance to isoniazid does not involve mutations in any of the genes known to be associated with isoniazid resistance, but an efflux system that is sensitive to efflux inhibitors. These inhibitors decreased the efflux of ethidium bromide and also reduced the minimum inhibitory concentration of isoniazid in these strains. Moreover, expression analysis showed overexpression of genes that code for efflux pumps in the induced strains relatively to the non-induced parental strains. In conclusion, the work described in this thesis demonstrates that efflux pumps play an important role in the development of drug resistance, namely in mycobacteria. A strategy to overcome efflux-mediated resistance may consist on the use of compounds that inhibit efflux activity, restoring the activity of antimicrobials that are efflux pump substrates, a useful approach particularly in TB where the most effective treatment regimens are becoming uneffective due to the increase of MDRTB/XDRTB.
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Dissertação apresentada para obtenção do Grau de Doutor em Bioquímica pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia