988 resultados para Functional Annotation


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Sandy shores are known to be extreme ecosystems where the vegetation has evolved many morphological and physiological adaptations for its survival. With the aim of identify possible relationships between the vegetation´s functional diversity with abiotic factors and its corresponding quantification, we collected data on the abundance and richness of the sandy coast vegetation complex in Grande, Anclitas and Caguamas keys. Its flora is largely characterized by the dominance of hemicryptophytes and chamaephytes plants with nanophyllous leaves and displaying dispersal syndromes such as zoochory and anemochory. However, the functional groups´ richness, in the present study, varies from one key to another. Functional diversity is similar between the wet and dry seasons, and its spatial variation is influenced by the interplay of the set of abiotic factors herein studied.

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Deriving maps of phytoplankton taxa based on remote sensing data using bio-optical properties of phytoplankton alone is challenging. A more holistic approach was developed using artificial neural networks, incorporating ecological and geographical knowledge together with ocean color, bio-optical characteristics, and remotely sensed physical parameters. Results show that the combined remote sensing approach could discriminate four major phytoplankton functional types (diatoms, dinoflagellates, coccolithophores, and silicoflagellates) with an accuracy of more than 70%. Models indicate that the most important information for phytoplankton functional type discrimination is spatio-temporal information and sea surface temperature. This approach can supply data for large-scale maps of predicted phytoplankton functional types, and an example is shown.

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The factors regulating phytoplankton community composition play a crucial role in structuring aquatic food webs. However, consensus is still lacking about the mechanisms underlying the observed biogeographical differences in cell size composition of phytoplankton communities. Here we use a trait-based model to disentangle these mechanisms in two contrasting regions of the Atlantic Ocean. In our model, the phytoplankton community can self-assemble based on a trade-off emerging from relationships between cell size and (1) nutrient uptake, (2) zooplankton grazing, and (3) phytoplankton sinking. Grazing 'pushes' the community towards larger cell sizes, whereas nutrient uptake and sinking 'pull' the community towards smaller cell sizes. We find that the stable environmental conditions of the tropics strongly balance these forces leading to persistently small cell sizes and reduced size diversity. In contrast, the seasonality of the temperate region causes the community to regularly reorganize via shifts in species composition and to exhibit, on average, bigger cell sizes and higher size diversity than in the tropics. Our results raise the importance of environmental variability as a key structuring mechanism of plankton communities in the ocean and call for a reassessment of the current understanding of phytoplankton diversity patterns across latitudinal gradients.

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We introduce a trait-based description of diatom functional diversity to an existing plankton functional type (PFT) model, implemented for the eutrophied coastal ecosystem in the Southern Bight of the North Sea. The trait-based description represents a continuum of diatom species, each characterized by a distinct cell volume, and includes size dependence of four diatom traits: the maximum growth rate, the half-saturation constants for nutrient uptake, the photosynthetic efficiency, and the relative affinity of copepods for diatoms. Through competition under seasonally varying forcing, the fitness of each diatom varies throughout time, and the outcome of competition results in a changing community structure. The predicted seasonal change in mean cell volume of the community is supported by field observations: smaller diatoms, which are more competitive in terms of resource acquisition, prevail during the first spring bloom, whereas the summer bloom is dominated by larger species which better resist grazing. The size-based model is used to determine the ecological niche of diatoms in the area and identifies a range of viable sizes that matches observations. The general trade-off between small, competitive diatoms and large, grazing-resistant species is a convenient framework to study patterns in diatom functional diversity. PFT models and trait-based approaches constitute promising complementary tools to study community structure in marine ecosystems.

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1.There are tens of thousands of species of phytoplankton found throughout the tree of life. Despite this diversity, phytoplankton are often aggregated into a few functional groups according to metabolic traits or biogeochemical role. We investigate the extent to which phytoplankton species dynamics are neutral within functional groups. 2.Seasonal dynamics in many regions of the ocean are known to affect phytoplankton at the functional group level leading to largely predictable patterns of seasonal succession. It is much more difficult to make general statements about the dynamics of individual species. 3.We use a 7 year time-series at station L4 in the Western English Channel with 57 diatom and 17 dinoflagellate species enumerated weekly to test if the abundance of diatom and dinoflagellate species vary randomly within their functional group envelope or if each species is driven uniquely by external factors. 4.We show that the total biomass of the diatom and dinoflagellate functional groups is well predicted by irradiance and temperature and quantify trait values governing the growth rate of both functional groups. The biomass dynamics of the functional groups are not neutral and each has their own distinct responses to environmental forcing. Compared to dinoflagellates, diatoms have faster growth rates, and grow faster under lower irradiance, cooler temperatures, and higher nutrient conditions. 5.The biomass of most species vary randomly within their functional group biomass envelope, most of the time. As a consequence, modelers will find it difficult to predict the biomass of most individual species. Our analysis supports the approach of using a single set of traits for a functional group and suggests that it should be possible to determine these traits from natural communities.

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Ecosystems consist of complex dynamic interactions among species and the environment, the understanding of which has implications for predicting the environmental response to changes in climate and biodiversity. However, with the recent adoption of more explorative tools, like Bayesian networks, in predictive ecology, few assumptions can be made about the data and complex, spatially varying interactions can be recovered from collected field data. In this study, we compare Bayesian network modelling approaches accounting for latent effects to reveal species dynamics for 7 geographically and temporally varied areas within the North Sea. We also apply structure learning techniques to identify functional relationships such as prey–predator between trophic groups of species that vary across space and time. We examine if the use of a general hidden variable can reflect overall changes in the trophic dynamics of each spatial system and whether the inclusion of a specific hidden variable can model unmeasured group of species. The general hidden variable appears to capture changes in the variance of different groups of species biomass. Models that include both general and specific hidden variables resulted in identifying similarity with the underlying food web dynamics and modelling spatial unmeasured effect. We predict the biomass of the trophic groups and find that predictive accuracy varies with the models' features and across the different spatial areas thus proposing a model that allows for spatial autocorrelation and two hidden variables. Our proposed model was able to produce novel insights on this ecosystem's dynamics and ecological interactions mainly because we account for the heterogeneous nature of the driving factors within each area and their changes over time. Our findings demonstrate that accounting for additional sources of variation, by combining structure learning from data and experts' knowledge in the model architecture, has the potential for gaining deeper insights into the structure and stability of ecosystems. Finally, we were able to discover meaningful functional networks that were spatially and temporally differentiated with the particular mechanisms varying from trophic associations through interactions with climate and commercial fisheries.

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While protein tyrosine kinases (PTKs) have been extensively characterized in eukaryotes, far less is known about their emerging counterparts in prokaryotes. Studies of close to 20 homologs of bacterial protein tyrosine (BY) kinases have inaugurated a blooming new field of research, all since just the end of the last decade. These kinases are key regulators in the polymerization and exportation of the virulence-determining polysaccharides which shield the bacterial from the non-specific defenses of the host. This research is aimed at furthering our understanding of the BY kinases through the use of X-ray crystallography and various in vitro and in vivo experiments. We reported the first crystal structure of a bacterial PTK, the C-terminal kinase domain of E. coli tyrosine kinase (Etk) at 2.5Å resolution. The fold of the Etk kinase domain differs markedly from that of eukaryotic PTKs. Based on the observed structure and supporting evidences, we proposed a unique activation mechanism for BY kinases in Gram-negative bacteria. The phosphorylation of tyrosine residue Y574 at the active site and the specific interaction of P-Y574 with a previously unidentified key arginine residue, R614, unblock the Etk active site and activate the kinase. Both in vitro kinase activity and in vivo antibiotics resistance studies utilizing structure-guided mutants further support the novel activation mechanism. In addition, the level of phosphorylation of their C-terminal Tyr cluster is known to regulate the translocation of extracellular polysaccharides. Our studies have significantly clarified our understanding of how the phosphorylation status on the C-terminal tyrosine cluster of BY kinases affects the oligomerization state of the protein, which is likely the machinery of polysaccharide export regulation. In summary, this research makes a substantial contribution to the rapidly progressing research of bacterial tyrosine kinases.

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Thrombin-activatable fibrinolysis inhibitor (TAFI) is a human plasma zymogen that acts as a molecular link between the coagulation and fibrinolytic cascades. TAFI can be activated by thrombin and plasmin but the reaction is enhanced significantly when thrombin is in a complex with the endothelial cofactor thrombomodulin (TM). The in vitro properties of TAFI have been extensively characterized. Activated TAFI (TAFIa) is a thermally unstable enzyme that attenuates fibrinolysis by catalyzing the removal of basic residues from partially degraded fibrin. The in vivo role of the TAFI pathway, however, is poorly defined and very little is known about the role of different activators in regulating the TAFI pathway. In the present study, we have constructed and characterized various TAFI mutants that are resistant to activation by specific activators. Based on peptide sequence studies, these mutants were constructed by altering key amino acid residues surrounding the scissile R92-A93 bond. We measured the thermal stabilities of all our mutants and found them to be similar to wild type TAFI. We have identified that the TAFI mutants P91S, R92K, and S90P are impaired in activation by thrombin or thrombin-TM, thrombin alone, and thrombin alone or plasmin, respectively. The TAFI mutants A93V and S94V were predicted to be resistant to activation by plasmin but this was not observed. The triple mutant, DVV was not activated by any of the aforementioned activators. Finally, we have used in vitro fibrin clot lysis assays to evaluate the antifibrinolytic potential of our variants and were able to correlate their effectiveness with their respective activation kinetics. In summary, we have developed activation resistant TAFI variants that can potentially be used to explore the role of the TAFI pathway in vivo.

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Kinesins are molecular motors that transport intracellular cargos along microtubules (MTs) and influence the organization and dynamics of the MT cytoskeleton. Their force-generating functions arise from conformational changes in their motor domain as ATP is bound and hydrolyzed, and products are released. In the budding yeast Saccharomyces cerevisiae, the Kar3 kinesin forms heterodimers with one of two non-catalytic kinesin-like proteins, Cik1 and Vik1, which lack the ability to bind ATP, and yet they retain the capacity to bind MTs. Cik1 and Vik1 also influence and respond to the MT-binding and nucleotide states of Kar3, and differentially regulate the functions of Kar3 during yeast mating and mitosis. The mechanism by which Kar3/Cik1 and Kar3/Vik1 dimers operate remains unknown, but has important implications for understanding mechanical coordination between subunits of motor complexes that traverse cytoskeletal tracks. In this study, we show that the opportunistic human fungal pathogen Candida albicans (Ca) harbors a single version of this unique form of heterodimeric kinesin and we present the first in vitro characterization of this motor. Like its budding yeast counterpart, the Vik1-like subunit binds directly to MTs and strengthens the MT-binding affinity of the heterodimer. However, in contrast to ScKar3/Cik1 and ScKar3/Vik1, CaKar3/Vik1 exhibits weaker overall MT-binding affinity and lower ATPase activity. Preliminary investigations using a multiple motor motility assay indicate CaKar3/Vik1 may not be motile. Using a maltose binding protein tagging system, we determined the X-ray crystal structure of the CaKar3 motor domain and observed notable differences in its nucleotide-binding pocket relative to ScKar3 that appear to represent a previously unobserved state of the active site. Together, these studies broaden our knowledge of novel kinesin motor assemblies and shed new light on structurally dynamic regions of Kar3/Vik1-like motor complexes that help mediate mechanical coordination of its subunits.

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To predict where a catalytic reaction should occur is a fundamental issue scientifically. Technologically, it is also important because it can facilitate the catalyst's design. However, to date, the understanding of this issue is rather limited. In this work, two types of reactions, CH4 CH3 + H and CO C + 0 on two transition metal surfaces, were chosen as model systems aiming to address in general where a catalytic reaction should occur. The dissociations of CH4 - CH3 + H and CO --> C + O and their reverse reactions on flat, stepped, and kinked Rh and Pd surfaces were studied in detail. We find the following: First, for the CH4 Ch(3) + H reaction, the dissociation barrier is reduced by similar to0.3 eV on steps and kinks as compared to that on flat surfaces. On the other hand, there is essentially no difference in barrier for the association reaction of CH3 + H on the flat surfaces and the defects. Second, for the CO C + 0 reaction, the dissociation barrier decreases dramatically (more than 0.8 eV on Rh and Pd) on steps and kinks as compared to that on flat surfaces. In contrast to the CH3 + H reaction, the C + 0 association reaction also preferentially occurs on steps and kinks. We also present a detailed analysis of the reaction barriers in which each barrier is decomposed quantitatively into a local electronic effect and a geometrical effect. Our DFT calculations show that surface defects such as steps and kinks can largely facilitate bond breaking, while whether the surface defects could promote bond formation depends on the individual reaction as well as the particular metal. The physical origin of these trends is identified and discussed. On the basis of our results, we arrive at some simple rules with respect to where a reaction should occur: (i) defects such as steps are always favored for dissociation reactions as compared to flat surfaces; and (ii) the reaction site of the association reactions is largely related to the magnitude of the bonding competition effect, which is determined by the reactant and metal valency. Reactions with high valency reactants are more likely to occur on defects (more structure-sensitive), as compared to reactions with low valency reactants. Moreover, the reactions on late transition metals are more likely to proceed on defects than those on the early transition metals.

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We have carried out extensive density functional theory (DFT) calculations for possible redox states of the active center in Fe-only hydrogenases. The active center is modeled by [(H(CH(3))S)(CO)(CN(-))Fe(p)(mu-DTN)(mu-CO)Fe(d)(CO)(CN(-))(L)](z) (z is the net charge in the complex; Fe(p)= the proximal Fe, Fe(d) = the distal Fe, DTN = (-SCH(2)NHCH(2)S-), L is the ligand that bonds with the Fed at the trans position to the bridging CO). Structures of possible redox states are optimized, and CO stretching frequencies are calculated. By a detailed comparison of all the calculated structures and the vibrational frequencies with the available experimental data, we find that (i) the fully oxidized, inactive state is an Fe(II)-Fe(II) state with a hydroxyl (OH(-)) group bonded at the Fe(d), (ii) the oxidized, active state is an Fe(II)-Fe(l) complex which is consistent with the assignment of Cao and Hall (J. Am. Chem. Soc. 2001, 123, 3734), and (iii) the fully reduced state is a mixture with the major component being a protonated Fe(l)-Fe(l) complex and the other component being its self-arranged form, Fe(II)-Fe(II) hydride, Our calculations also show that the exogenous CO can strongly bond with the Fe(II)-Fe(l) species, but cannot bond with the Fe(l)-Fe(l) complex. This result is consistent with experiments that CO tends to inhibit the oxidized, active state, but not the fully reduced state. The electronic structures of all the redox states have been analyzed. It is found that a frontier orbital which is a mixing state between the e(g) of Fe and the 2pi of the bridging CO plays a key role concerning the reactivity of Fe-only hydrogenases: (1) it is unoccupied in the fully oxidized, inactive state, half-occupied in the oxidized, active state, and fully occupied in the fully reduced state; (ii) the e(g)-2pi orbital is a bonding state, and this is the key reason for stability of the low oxidation states, such as Fe(l)-Fe(l) complexes; and (iii) in the e(g)-2pi orbital more charge accumulates between the bridging CO and the Fe(d) than between the bridging CO and the Fe(p), and the occupation increase in this orbital will enhance the bonding between the bridging CO and the Fe(d), leading to the bridging-CO shift toward the Fe(d).

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The important role of alkali additives in heterogeneous catalysis is, to a large extent, related to the high promotion effect they have on many fundamental reactions. The wide application of alkali additives in industry does not, however, reflect a thorough understanding of the mechanism of their promotional abilities. To investigate the physical origin of the alkali promotion effect, we have studied CO dissociation on clean Rh(111) and K-covered Rh(111) surfaces using density functional theory. By varying the position of potassium atoms relative to a dissociating CO, we have mapped out the importance of different K effects on the CO dissociation reactions. The K-induced changes in the reaction pathways and reaction barriers have been determined; in particular, a large reduction of the CO dissociation barrier has been identified. A thorough analysis of this promotion effect allows us to rationalize both the electronic and the geometrical factors that govern alkali promotion effect: (i) The extent of barrier reductions depends strongly on how close K is to the dissociating CO. (ii) Direct K-O bonding that is in a very short range plays a crucial role in reducing the barrier. (iii) K can have a rather long-range effect on the TS structure, which could reduce slightly the barriers.