Superóxido dismutases (SODs) são metaloenzimas que convertem o ânion superóxido em oxigênio molecular (O2) e peróxido de hidrogênio (H2O2). A presença de metal nessas enzimas está diretamente relacionada com seus mecanismos de catálise e com suas estruturas tridimensionais. Evolucionariamente, FeSOD e MnSOD podem ter evoluído de um gene ancestral comum, porque possuem sequências homólogas e estruturas cristalográficas sobreponíveis. Entretanto, a nível catalítico, ambas as proteínas divergiram o suficiente para que seus metais não possam ser intercambiáveis, produzindo uma enzima funcional, indicando que essas proteínas possuem alta especificidade por metal. O objetivo deste projeto de pesquisa é Identificar os determinantes estruturais do ajuste fino da especificidade por metal de MnSOD e FeSOD. Inicialmente, pretendese selecionar resíduos para mutagênese sítio-dirigida em TrMnSOD e TbFeSODB2, a partir de análise de acoplamento estatístico (SCA). Em seguida, mutantes serão construídos, expressos, purificados e cristalizados. A estrutura tridimensional dos mutantes será resolvida por cristalografia e sua atividade enzimática determinada, bem como a acomodação estrutural dos metais por Resonância Paramagnética Eletrônica. Nossa hipótese de trabalho é que através de SCA é possível elencar resíduos de aminoácidos candidatos para mutagênese sítio-dirigida para desenhar novas SODs, com características intermediárias de ligação por Fe/Mn, como possibilidade de interconversão de especificidade, caminhando na história evolutiva dessas moléculas. / Superoxide dismutases (SODs) are metalloenzymes that convert the superoxide anion in molecular oxygen (O2) and hydrogen peroxide (H2O2). The metal in the catalytic center of such enzymes is directly related to their catalysis mechanisms and tridimensional structures. Evolutionarily, FeSOD and MnSOD may have evolved from a common ancestor, because both proteins have homologous primary sequences and superposable crystallographic structures. However, at the catalytic level, both proteins diverged sufficiently to prevent interchange of their metallic centers, which would generate non-functional enzymes, indicating that these proteins have high metal specificity. The objective of this research project is to identify structural determinants of Fe/MnSODs necessary to metal specificity. We intend to use statistical coupling analysis (SCA) to select amino acid residues for site-directed mutagenesis in TrMnSOD e TbFeSODB2. Mutant genes will be constructed and their proteins expressed, purified and crystallized. The tridimensional structure of such mutants will be solved by X-ray crystallography and their enzymatic activities determined, as well as their electron paramagnetic resonance spectra. We hypothesize that SCA is useful to identify amino acid candidates for site-directed mutagenesis to design new SODs with intermediated Fe/Mn specificity, and even metal specificity interconversion, by studying the evolutionary history of these proteins.

Yes / This paper investigates the interaction phenomena of the coupled axons while the mutual coupling factor is presented as a pairwise description. Based on the Hodgkin-Huxley model and the coupling factor matrix, the membrane potentials of the coupled myelinated/unmyelinated axons are quantified which implies that the neural coupling can be characterised by the presented coupling factor. Meanwhile the equivalent electric circuit is supplied to illustrate the physical meaning of this extended model. In order to estimate the coupling factor, a data-based iterative learning identification algorithm is presented where the Rényi entropy of the estimation error has been minimised. The convergence of the presented algorithm is analysed and the learning rate is designed. To verified the presented model and the algorithm, the numerical simulation results indicate the correctness and the effectiveness. Furthermore, the statistical description of the neural coupling, the approximation using ordinary differential equation, the measurement and the conduction of the nerve signals are discussed respectively as advanced topics. The novelties can be summarised as follows: 1) the Hodgkin-Huxley model has been extended considering the mutual interaction between the neural axon membranes, 2) the iterative learning approach has been developed for factor identification using entropy criterion, and 3) the theoretical framework has been established for this class of system identification problems with convergence analysis. / This work was supported in part by the National Natural Science Foundation of China (NSFC) under Grant 51807010, and in part by the Natural Science Foundation of Hunan under Grant 1541 and Grant 1734. / Research Development Fund Publication Prize Award winner, Nov 2020.

Nutrient sensing kinases lie at the heart of cellular health and homeostasis, allowing cells to quickly adapt to changing environments. Target of Rapamycin (TOR) and PAS kinase (PASK, or PASKIN) are two such nutrient kinases, conserved from yeast to man. In yeast, these kinases each have paralogs. The two TOR paralogs in yeast mimic the mammalian TORC1 and TORC2 complexes, except both Tor1 and Tor2 may contribute to TORC1 or TORC2 function. The two PAS kinase paralogs are paired with the TOR paralogs, meaning that both Psk1 and Psk2 regulate TORC1, while Psk2 suppresses a temperature-sensitive allele of Tor2. Herein we review the evolutionary models for these paralogs, their function in yeast and mammalian cells, as well as the overlapping function of PAS kinase and TOR. We also use Rice University’s Direct Coupling Analysis algorithms to analyze co-evolutionary relationships and identify potential interaction sites between PAS kinase and several of its substrates.

Esta tesis se centra en la construcción y usos de los modelos metabólicos a escala genómica para obtener biocombustibles de manera eficiente, como etanol e hidrógeno. Como organismo objetivo, se ha elegido a la cianobacteria Synechocystis sp. PCC6803. Este organismo ha sido estudiado como una potencial plataforma de producción alimentada por fotones, dada su capacidad de crecer solamente a partir de dióxido de carbono y fotones. Esta tesis versa acerca de los métodos para modelar, analizar, estimar y predecir el comportamiento del metabolismo de las células. La principal meta es extraer conocimiento de los diferentes aspectos biológicos de un organismo con el fin de utilizarlo para un objetivo industrial pertinente. Esta tesis ha sido estructurada en capítulos organizados de acuerdo con las sucesivas tareas que terminan con la construcción de una célula in silico que se comporta, idealmente, como la que está basada en el carbono. Este proceso suele comenzar con los archivos de anotación del genoma y termina con un modelo metabólico a escala genómica capaz de integrar datos -ómicos. El primer objetivo de la presente tesis es la reconstrucción de un modelo del metabolismo de esta cianobacteria que tenga en cuenta todas las reacciones presentes en la misma. Esta reconstrucción tenía que ser lo suficientemente flexible como para permitir el crecimiento en las distintas condiciones ambientales bajo las cuales este organismo crece en la naturaleza, así como permitir la integración de diferentes niveles de información biológica. Una vez que se cumplió este requisito, se pudieron simular variaciones ambientales y estudiar sus efectos desde una perspectiva de sistema. Se han estudiado hasta cinco diferentes condiciones de crecimiento en este modelo metabólico y sus diferencias han sido evaluadas. La siguiente tarea fue definir estrategias de producción para sopesar la viabilidad de este organismo como una plataforma de producción. Se simularon perturbaciones genéticas para e / This thesis is focused on the construction and uses of genome-scale metabolic models to efficiently obtain biofuels, such as ethanol and hydrogen. As a target organism, cyanobacterium Synechocystis sp. PCC6803 was chosen. This organism has been studied as a potential photon-fuelled production platform, for its ability to grow only from carbon dioxide, water and photons. This dissertation verses about methods to model, analyse, estimate and predict the metabolic behaviour of cells. Principal goal is to extract knowledge from the different biological aspects of an organism in order to use it for an industrial relevant objective. This dissertation has been structured in chapters accordingly organized as the successive tasks that end up building an in silico cell that behaves as the carbon-based one. This process usually starts with the genome annotation files and ends up with a genome-scale metabolic model able to integrate ¿omics data. First objective of present thesis is to reconstruct a model of this cyanobacteria¿s metabolism that accounts for all the reactions present in it. This reconstruction had to be flexible enough as to allow growth under the different environmental conditions under which this organism grows in nature as well as to allow the integration of different levels of biological information. Once this requisite was met, environmental variations could be simulated and their effect studied under a system-wide perspective. Up to five different growth conditions were simulated on this metabolic model and differences were evaluated. Following assignment was to define production strategies to weigh this organism¿s viability as a production platform. Genetic perturbations were simulated to design strains with an enhanced production of three industrially-relevant metabolites: succinate, ethanol and hydrogen. Resulting sets of genetic modifications for the overproduction of those metabolites are, thus, proposed. Moreover, functional reactions couplings were studied and weighted to their metabolite production importance. Finally, genome-scale metabolic models allow establishing integrative approaches to include different types of data that help to find regulatory hotspots that can be targets of genetic modification. Such regulatory hubs were identified upon light/dark shifts and general metabolism operational principles inferred. All along this process, blind spots in Synechocystis sp. PCC6803 metabolism, and more importantly, blind spots in our understanding of it, are revealed. Overall, the work presented in this thesis unveils the industrial capabilities of cyanobacterium Synechocystis sp. PCC6803 to evolve interesting metabolites as a clean production platform. / Esta tesis es centra en la construcció i els usos del models metabòlics a escala genòmica per a obtenir eficientment biocombustibles, com etanol i hidrogen. Com a organisme diana, s¿elegí el cianobacteri Synechocystis sp. PCC6803. Aquest organisme ha segut estudiat com una plataforma de producció nodrida per fotons, per la seva habilitat per créixer a partir únicament de diòxid de carboni, aigua i fotons. Aquesta tesi versa sobre mètodes per a modelitzar, analitzar, estimar i predir el comportament metabòlic de cèl¿lules. La principal meta és extreure coneixement del diferents aspectes biològics d¿un organisme de manera que s¿usen per a un objectiu industrial rellevant. La tesi ha segut estructurada en capítols organitzats d¿acord a les successives tasques que acaben construint una cèl¿lula in silico que es comporta, idealment, com la que està basada en carboni. Aquest procés generalment comença amb els arxius de l¿anotació del genoma i acaba amb un model metabòlic a escala genòmica capaç d¿integrar dades ¿òmiques. El primer objectiu de la present tesi és la reconstrucció d¿un model del metabolisme d¿aquest cianobacteri que tinga en compte totes les reaccions que hi estan presents. Esta reconstrucció havia de ser prou flexible com per permetre la simulació del creixement en les diferents condicions ambientals en les quals aquest cianobacteri creix en la natura, així com permetre la integració de diferents nivells d¿informació biològica. Una vegada que aquest requisit fou assolit, es pogueren simular variacions ambientals i estudiar els seus efectes amb una perspectiva de sistema. S¿han simulat fins a cinc condicions de creixement en este model metabòlic i les seves diferències han segut avaluades. La següent tasca fou definir estratègies de producció per a valorar la viabilitat d¿aquest organisme com a plataforma de producció. Es simularen pertorbacions genètiques per al disseny de soques amb producció millorada de metabòlits de rellevància industrial: succinat, etanol i hidrogen. Així, es proposen conjunts de modificacions genètiques per a la sobreproducció d¿aquests metabòlits. També s'han estudiat reaccions acoblades funcionalment i s¿ha ponderat la seva importància en la producció de metabòlits. Finalment, els models metabòlics a escala genòmica permeten establir criteris per integrar diferents tipus de dades que ens ajuden a trobar punts importants de regulació. Eixos centres reguladors, que poden ser objecte de modificacions genètiques, han segut investigats baix canvis dràstics d¿il¿luminació i s¿han inferit principis operacionals del metabolisme. Al llarg d'aquest procés, s¿han revelat punts cecs al metabolisme de Synechocystis sp. PCC6803 i, el més important, punts cecs en la nostra comprensió d'aquest metabolisme. En general, el treball presentat en aquesta tesi dona a conèixer les capacitats industrials del cianobacteri Synechocystis sp. PCC6803 per a produir metabòlits d'interès, tot sent una plataforma de producció neta i sostenible. / Montagud Aquino, A. (2012). Modelling and analysis of biological systems to obtain biofuels [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/17319 / Palancia

Does the active membrane transporter, Na+,K+-ATPase dimerize? If it does, whatis the functional benefit? Does it increase or decrease the turnover rate? Theseare still unanswered questions and current research topics. Previous studies havedemonstrated dimerizations in closely related proteins of the P-type ATPase family.For the Na+, K+-ATPase a first indication of dimerization has been shown viaFluorescence lifetime imaging microscopy (FLIM) or Fluorescence resonance energytransfer - Fluorescence correlation spectroscopy (FRET-FCS) experiments. Theprecise dimer structure, dimerization process, and its ultimate functional effecthowever, remain to be found. This master thesis approaches those questions froma co-evolutionary standpoint. It predicts a possible dimer structure by starting with amultiple sequence alignment, direct coupling analysis, and structural contact filteringalgorithm. This model would strengthen the dimerization model of a decreasedturnover rate due to a competitive behavior of two Na+, K+-ATPases for its energysource ATP. / Dimeriserar den aktiva membrantransporten Na+,K+-ATPas? Om den gör det,vad är den funktionella nyttan? Ökar eller minskar det omsättningshastigheten?Dessa är obesvarade frågor och rådande forskningsämnen. Tidigare studier hardemonstrerat dimeriseringar i nära relaterade proteiner av P-typ ATPas-familjen.För Na+, K+-ATPas har en första indikation av dimerisering visats via ”Flourescencelifetime imaging microscopy (FLIM)” eller ”Flourescence resonance energy transfer- Flourescence correlation spectroscopy (FRET-FCS)”. Den precisa dimerstrukturen,dimeriseringsprocessen och dess slutgiltiga funktionella effekt emellertid, återståratt ses. Detta examensarbete på masternivå närmar sig dessa frågor från ettsamevolutionärt perspektiv. Det förutser en möjlig dimerstruktur genom att utgåfrån en flersekvenslinjering, direkt kopplingsanalys och en strukturell kontaktfiltreringsalgoritm. Denna modell skulle stärka dimeriseringsmodellen av minskadomsättningshastighet till följd av tävlingsbeteende mellan två Na+,K+-ATPaser fördess energikälla ATP.