Biochemical and spectroscopic characterization of the membrane-bound nitrate reductase from Marinobacter hydrocarbonoclasticus 617

J Biol Inorg Chem (2008) 13:1321–1333 DOI 10.1007/s00775-008-0416-1

Photochemical control of rheology

The main objective of the research work developed in the framework of this PhD thesis was the preparation and development of novel photorheological fluids. This was pursued following two distinct strategies. The first one focused on the synthesis of tripodal compounds functionalized with photodimerizable moieties of cinnamic acid, coumarin and anthracene. Two sets of compounds were prepared, varying the central unit as well as spacers resulting in molecules with different solubilities and molecular weight. All compounds were characterized towards their photochemical properties and all exhibited photoreactivity upon irradiation with ultra-violet light. In particular, both coumarin derivatives exhibited the greatest photopolymerization reactivity, resulting in the formation of dendrimeric nanoparticles or in the increase of viscosity of organic solutions. The second strategy was focused on the careful design of photosensitive ionic liquids, based on the results of several quantitative structure-property relationship studies. Thus, photosensitive ionic liquids were synthesized bearing cinnamic acid or coumarin moieties in the organic cation. Upon irradiation, all compounds exhibited reactivity, which resulted in changes in their physical properties, such as melting point or viscosity. In addition, novel coumarin chromophores with different photophysical and photochemical properties were developed. It is expected that these compounds may find application in the preparation of new photosensitive ionic liquids.

Understanding the relationship between central metabolism and virulence in the human pathogen Streptococcus pneumoniae

Dissertation presented to obtain the Ph.D. degree in Biochemistry

Effects of team task structure on team climate for innovation and team outcomes

In this cross-sectional study we analyzed, whether team climate for innovation mediates the relationship between team task structure and innovative behavior, job satisfaction, affective organizational commitment, and work stress. 310 employees in 20 work teams of an automotive company participated in this study. 10 teams had been changed from a restrictive to a more self-regulating team model by providing task variety, autonomy, team-specific goals, and feedback in order to increase team effectiveness. Data support the supposed causal chain, although only with respect to team innovative behavior all required effects were statistically significant. Longitudinal designs and larger samples are needed to prove the assumed causal relationships, but results indicate that implementing self-regulating teams might be an effective strategy for improving innovative behavior and thus team and company effectiveness.

Management Structure and Work Team Processes; Responsibilities and Responsiveness

This paper explores the management structure of the team-based organization. First it provides a theoretical model of structures and processes of work teams. The structure determines the team’s responsibilities in terms of authority and expertise about specific regulation tasks. The responsiveness of teams to these responsibilities are the processes of teamwork, in terms of three dimensions, indicating to what extent teams indeed use the space provided to them. The research question that this paper addresses is to what extent the position of responsibilities in the team-based organization affect team responsiveness. This is done by two hypotheses. First, the effect of the so-called proximity of regulation tasks is tested. It is expected that the responsibility for tasks positioned higher in the organization (i.e. further from the team) generally has a negative effect on team responsiveness, whereas tasks positioned lower in the organization (i.e. closer to the team) will have a positive effect on the way in which teams respond. Second, the relationship between the number of tasks for which the team is responsible with team responsiveness is tested. Theory suggests that teams being responsible for a larger number of tasks perform better, i.e. show higher responsiveness. These hypotheses are tested by a study of 109 production teams in the automotive industry. The results show that, as the theory predicts, increasing numbers of responsibilities have positive effects on team responsiveness. However, the delegation of expertise to teams seems to be the most important predictor of responsiveness. Also, not all regulation tasks show to have effects on team responsiveness. Most tasks do not show to have any significant effect at all. A number of tasks affects team responsiveness positively, when their responsibility is positioned lower in the organization, but also a number of tasks affects team responsiveness positively when located higher in the organization, i.e. further from the teams in the production. The results indicate that more attention can be paid to the distribution of responsibilities, in particular expertise, to teams. Indeed delegating more expertise improve team responsiveness, however some tasks might be located better at higher organizational levels, indicating that there are limitations to what responsibilities teams can handle.

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.

Bridging environmental conflicts with social metabolism : forestry expansion and socioeconomic change

Dissertação apresentada para obtenção do Grau de Doutor em Ciências do Ambiente, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Metabolism of primary astrocytes studied by NMR: metabolic trafficking and neuroprotection

Dissertation presented to obtain a Ph. D. degree in Biochemistry by Universidade Nova de Lisboa, Instituto de Tecnologia Química e Biológica.

Análise da estrutura e da função da proteína morfogenética RodZ de Bacillus subtilis

Resumo: RodZ é um componente do sistema morfogenético das células bacterianas. É uma proteína transmembranar que localiza em bandas ao longo do eixo longitudinal da célula. Em Bacillus subtilis, RodZ consiste numa porção citoplasmática, RodZn, e em uma parte extra-citoplasmática, RodZc. RodZn contém um domínio em helixturn- helix (HTH), enquanto que RodZc pode ser dividido num domínio coiled-coil e num domínio terminal C, de função desconhecida. Um segmento transmembranar (TM) único separa RodZn de RodZc. A eliminação de rodZ causa alongamento do nucleóide e leva à produção de células polares nucleadas. Aqui, mostramos que RodZn é estruturado, estável e em hélice α. Descobrimos que as substituições Y32A e L33A na suposta hélice de reconhecimento (3) do motivo HTH, bem como as substituições Y49A e F53A, fora do motivo HTH (4), causam divisão assimétrica, mas apenas as últimas levam à deslocalização sub-celular de RodZ. Sugerimos que as hélices 3 e 4 são utilizadas para uma interacção proteína-proteína ou proteína- DNA essencial para divisão celular enquanto que 4 deve contactar um componente do citosqueleto, possivelmente MreB, uma vez que a correcta localização sub-celular de RodZ depende desta proteína. Em todos os mutantes as células polares são anucleadas, pelo que concluímos que o alongamento do nucleóide não é um prérequisito para divisão assimétrica. RodZc é largamente não estruturado mas com conteúdo de folha , sendo estabilizado pelo domínio coiled-coil. Mostramos uma relação homóloga entre RodZc e a bomba de transporte Na+/Ca2+ NCX1 e identificámos dois resíduos no domínio C, G265 e N275, essenciais para a manutenção da forma celular. Estes resíduos fazem parte de um motivo em gancho que pode actuar como um local de interacção com um ligando desconhecido. RodZn e RodZc são monoméricos em solução. Contudo, na membrana, RodZ interage consigo própria num sistema de dois híbridos (Split-Ubiquitin) em levedura, sugerindo que possa formar multímeros in vivo.-----------ABSTRACT: RodZ is a transmembrane component of the bacterial core morphogenic apparatus. RodZ localizes in bands long the longitudinal axis of the cell, and it is though to functionally link the cell wall to the actin cytoskeleton. In Bacillus subtilis, RodZ consists of a cytoplasmic moiety, RodZn, and an extracytoplasmic moiety, RodZc. RodZn contains a predicted helix-turn-helix domain, whereas RodZc is thought to contain a coiled-coil region and a terminal C domain of unknown function. A single transmembrane domain separates RodZn from RodZc. Deletion of rodZ causes elongation of the nucleoid and leads to the production of polar minicells containing DNA. Here, we have studied the structure and function of RodZn and RodZc. We show that RodZn is a stable, folded, -helical domain. We discovered that the Y32A and L33A substitutions within the presumptive recognition helix (3) of the HTH motif, as well as the Y49A and F53A substitutions outside of the HTH motif (in 4) cause asymmetric cell division. However, only the substitutions in 4 cause sub-celular delocalization of RodZ. We suggest that 3 and 4 are used for a protein-protein or protein-DNA interaction important for cell division, whereas 4 is likely to contact a cytoskeletal component, presumably MreB. The polar cells formed by all the mutants are anucleate. We conclude that nucleoid elongation is not a prerequisite for asymmetric division. RodZc appears to be a largely unstructured domain, with some -sheet content, and is stabilized by the coiled-coil region. We show a homology relationship between RodZc and the NCX1 Na+/Ca2+ transporter and we found two residues within the C domain, G265 and N275, that are important for cell shape determination. These residues are predicted to be essential determinants of a claw-like motif, which may act as a binding site for an unknown ligand. Both the isolated RodZn and RodZc proteins are monomeric in solution. However, because full-length RodZ interacts with itself in a split-ubiquitin yeast two-hybrid assay, we suggest that it may dimerize or form higher order multimers in vivo.

Business planning in nonprofit: laying the ground for customer relationship management in Instituto de Empreendedorismo Social

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics