Direct electrochemistry of the Desulfovibrio gigas aldehyde oxidoreductase

Eur. J. Biochem. 271, 1329–1338 (2004)

Cytochrome c nitrite reductase from desulfovibrio desulfuricans ATCC 27774

The Journal of Biological Chemistry Vol. 278, No. 19, Issue of May 9, pp. 17455–17465, 2003

Automatic learning for the classification of chemical reactions and in statistical thermodynamics

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.

Selenium role in an human biomonitoring study applied to occupational health

Selenium functions as a co-factor for the reduction of antioxidant enzymes and is an important component of antioxidant enzymes. Dietary selenium significantly inhibits the induction of skin, liver, colon, and mammary tumours in experimental animals by a number of different carcinogens, as well as the induction of mammary tumours by viruses. Selenium shows a “U” shaped curve for functionality, whereby too little is as damaging as too much. At optimal levels, selenium may protect against the formation of DNA adducts, DNA or chromosome breakage, chromosome gain or loss, mitochondrial DNA, and telomere length and function. Aim of study: Investigate the relation between selenium and genotoxic effects in a human biomonitoring study applied to occupational health.

Molecular diversity of bla genes in Klebsiella pneumoniae and Escherichia coli isolates

Dissertation presented to obtain a Ph.D. degree in Biology, speciality Microbiology, by Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Analysis of glycosylation heterogeneity in antibody production by Pichia pastoris

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Biotecnologia

Micronutrients intake associated with DNA damage assessed by in a human biomonitoring study

Nutrition science has evolved into a multidisciplinary field that applies molecular biology and integrates individual health with the epidemiologic investigation of population health. Nutritional genomics studies the functional interaction of food and its components, macro and micronutrients, with the genome at the molecular, cellular, and systemic level. Diet can influence cancer development in several ways, namely direct action of carcinogens in food that can damage DNA, diet components (macro or micronutrients) that can block or induce enzymes involved in activation or deactivation of carcinogenic substances. Moreover, inadequate intake of some molecules involved in DNA synthesis, repair or methylation can influence mutation rate or changes in gene expression. Several studies support the idea that diet can influence the risk of cancer; however information concerning the precise dietary factor that determines human cancer is an ongoing debate. A lot of epidemiological studies, involving food frequency questionnaires, have been developed providing important information concerning diet and cancer, however, diet is a complex composite of various nutrients (macro and micronutrients) and non-nutritive food constituents that makes the search for specific factors almost limitless.

Electrochemical and analytical investigation of passive films formed on stainless steels in alkaline media

Passive films were grown in potentiodynamic mode, by cyclic voltammetry on AISI 316 and AISI 304 stainless steels. The composition of these films was investigated by X-ray photoelectron spectroscopy (XPS). The electrochemical behaviour and the chemical composition of the passive films formed by cyclic voltammetry were compared to those of films grown under natural conditions (by immersion at open circuit potential, OCP) in alkaline solutions simulating concrete. The study included the effect of pH of the electrolyte and the effect of the presence of chloride ions. The XPS results revealed important changes in the passive film composition, which becomes enriched in chromium and depleted in magnetite as the pH decreases. On the other hand, the presence of chlorides promotes a more oxidised passive layer. The XPS results also showed relevant differences on the composition of the oxide layers for the films formed under cyclic voltammetry and/or under OCP.

Investigation of structural effects and behaviour of pseudomonas aeruginosa amidase encapsulated in reserved micelles

The acetohydroxamic acid synthesis reaction was studied using whole cells, cell-free extract and purified amidase from the strains of Pseudomonas aeruginosa L10 and A13 entrapped in a reverse micelles system composed of cationic surfactant tetradecyltrimethyl ammonium bromide. The specific activity of amidase, yield of synthesis and storage stability were determined for the reversed micellar system as well as for free amidase in conventional buffer medium. The results have revealed that amidase solutions in the reverse micelles system exhibited a substantial increase in specific activity, yield of synthesis and storage stability. In fact, whole cells from P. aeruginosa L10 and AI3 in reverse micellar medium revealed an increase in specific activity of 9.3- and 13.9-fold, respectively, relatively to the buffer medium. Yields of approximately 92% and 66% of acetohydroxamic acid synthesis were obtained for encapsulated cell free extract from P. aeruginosa L10 and A13, respectively. On the other hand, the half-life values obtained for the amidase solutions encapsulated in reverse micelles were overall higher than that obtained for the free amidase solution in buffer medium. Half-life values obtained for encapsulated purified amidase from P. aeruginosa strain L10 and encapsulated cell-free extract from P. aeruginosa strain AI3 were of 17.0 and 26.0 days, respectively. As far as the different sources biocatalyst are concerned, the data presented in this work has revealed that the best results, in both storage stability and biocatalytic efficiency, were obtained when encapsulated cell-free extract from P. aeruginosa strain AI3 at 14/0 of 10 were used. Conformational changes occurring upon encapsulation of both strains enzymes in reverse micelles of TAB in heptane/octanol were additionally identified by FTIR spectroscopy which clarified the biocatalysts performances.

Production, purification and characterization of laccase from pleurottus ostreatus grown on tomato pomace

A strain of Pleurotus ostreatus was grown in tomato pomace as sole carbon source for production of laccase. The culture of P. ostreatus revealed a peak of laccase activity (147 U/L of fermentation broth) on the 4th day of culture with a specific activity of 2.8 U/mg protein. Differential chromatographic behaviour of laccase was investigated on affinity chromatographic matrices containing either urea, acetamide, ethanolamine or IDA as affinity ligands. Laccase exhibited retention on such affinity matrices and it was purified on a Sepharose 6B-BDGE-urea column with final enzyme recoveries of about 60%, specific activity of 6.0 and 18.0 U/mg protein and purification factors in the range of 14-46. It was also possible to demonstrate that metal-free laccase did not adsorb to Sepharose 6B-BDGE-urea column which suggests that adsorption of native laccase on this affinity matrix was apparently due to the specific interaction of carbonyl groups available on the matrix with the active site Cu (II) ions of laccase. The kinetic parameters (V (max), K (m) , K (cat), and K (cat)/K (m) ) of the purified enzyme for several substrates were determined as well as laccase stability and optimum pH and temperature of enzyme activity. This is the first report describing the production of laccase from P. ostreatus grown on tomato pomace and purification of this enzyme based on affinity matrix containing urea as affinity ligand.

Proteomic analysis of the influence of the adipocyte secretome on Glioma Gl261 cells

Glioma is the most frequent form of malignant brain tumor in the adults and childhood. There is a global tendency toward a higher incidence of gliomas in highly developed and industrialized countries. Simultaneously obesity is reaching epidemic proportions in such developed countries. It has been highly accepted that obesity may play an important role in the biology of several types of cancer. We have developed an in vitro method for the understanding of the influence of obesity on glioma mouse cells (Gl261). 3T3-L1 mouse pre-adipocytes were induced to the maturity. The conditioned medium was harvested and used into the Gl261 cultures. Using two-dimension electrophoresis it was analyzed the proteome content of Gl261 in the presence of conditioned medium (CGl) and in its absence (NCGl). The differently expressed spots were collected and analyzed by means of mass spectroscopy (MALDI-TOF-MS). Significantly expression pattern changes were observed in eleven proteins and enzymes. RFC1, KIF5C, ANXA2, N-RAP, RACK1 and citrate synthase were overexpressed or only present in the CGl. Contrariwise, STI1, hnRNPs and phosphoglycerate kinase 1 were significantly underexpressed in CGl. Aldose reductase and carbonic anhydrase were expressed only in NCGl. Our results show that obesity remodels the physiological and metabolic behavior of glioma cancer cells. Also, proteins found differently expressed are implicated in several signaling pathways that control matrix remodeling, proliferation, progression, migration and invasion. In general our results support the idea that obesity may increase glioma malignancy, however, some interesting paradox finding were also reported and discussed.

Two distinct arabinofuranosidases contribute to arabino-oligosaccharide degradation in Bacillus subtilis.

Microbiology 154 (2008) 2719-2729

trans-Acting factors and cis elements involved in glucose repression of arabinan degradation in Bacillus subtilis.

Journal of Bacteriology (Nov 2007) 8371-8376

Comparative studies of Yersinia pestis outer membrane isolation techniques and their potential use in plague epidemiology

In the present study three techniques for obtaining outer membrane enriched fractions from Yersinia pestis were evaluated. The techniques analysed were: differential solubilization of the cytoplasmic membrane with Sarkosyl or Triton X-100, and centrifugation in sucrose density gradients. The sodium dodecyl-sulfate polyacrylamide gel electrophoresis (SDS-PAGE) of outer membrane isolated by the different methods resulted in similar protein patterns. The measurement of NADH-dehydrogenase and succinate dehydrogenase (inner membrane enzymes) indicated that the outer membrane preparations obtained by the three methods were pure enough for analytical studies. In addition, preliminary evidences on the potential use of outer membrane proteins for the identification of geographic variants of Y. pestis wild isolates are presented.

Simultaneous identification of Trypanosoma cruzi surface and internal antigens reactive to different immunoglobulin classes (radio-immunoblotting)

A radioactive Western-blotting technique was developed by which the reactivity of Immunoglobulins (Igs) from different classes to both membrane radiolabelled and internal parasite antigens is simultaneously identified. The method includes radioiodination of parasites, polypeptide fractionation by SDS-PAGE, Western-blot transfer and autoradiography of the immunoblots developed with anti-Igs conjugates labelled with enzymes. The analysis is then performed by the comparison of common bands on the autoradiograms and the respective substrate stained nitrocellulose blots. This technique was used to analyse T. cruzi trypomastigote surface labelled antigens reactive to IgM, IgA and IgG specific antibodies. A different pattern of reactivity with acute Chagas' disease patients sera was thus obtained.