FGF-2 Low Molecular Weight Selectively Promotes Neuritogenesis of Motor Neurons In Vitro

In this study, we screened in vitro the different capabilities of trophic factors with promising effect for enhancing selective regeneration and thus promoting specific reinnervation of target organs after peripheral nerve regeneration. We found that FGF-2 (18 kDa) was the trophic factor that exerted the most selective effect in promoting neurite outgrowth of spinal motoneurons both in terms of elongation and arborization. The mechanism underlying this effect on neuritogenesis seems related to FGF-2 enhancing the interaction between FGFR-1 and PSA-NCAM. The interaction of these two receptors is important during the early stages of neuritogenesis and pathfinding, while integrin alpha7B subunit seems to play a role during neurite stabilization.     

Superhelical DNA as a preferential binding target of 14-3-3γ protein

The 14-3-3 protein family is a highly conserved and widely distributed group of proteins consisting of multiple isoforms in eukaryotes. Ubiquitously expressed, 14-3-3 proteins play key roles in DNA replication, cell cycle regulation, and apoptosis. The function of 14-3-3 proteins is mediated by interaction with a large number of other proteins and with DNA. It has been demonstrated that 14-3-3γ protein binds strongly to cruciform structures and is crucial for initiating replication. In this study, we analyzed DNA binding properties of the 14-3-3γ isoform to linear and supercoiled DNA. We demonstrate that 14-3-3γ protein binds strongly to long DNA targets, as evidenced by electrophoretic mobility shift assay on agarose gels. Binding of 14-3-3γ to DNA target results in the appearance of blurry, retarded DNA bands. Competition experiments with linear and supercoiled DNA on magnetic beads show very strong preference for supercoiled DNA. We also show by confocal microscopy that 14-3-3 protein in the HCT-116 cell line is co-localized with DNA cruciforms. This implies a role for the 14-3-3γ protein in its binding to local DNA structures which are stabilized by DNA supercoiling.     

Molecular Dynamics Simulations of Rhodopsin Point Mutants at the Cytoplasmic Side of Helices 3 and 6

Abstract

The present work reports on a structural analysis carried out through different computer simulations of a set of rhodopsin mutants with differential functional features in regard to the wild type. Most of these mutants, whose experimental features had previously been reported [Ramon et al. J Biol Chem 282, 14272–14282 (2007)], were designed to perturb a network of electrostatic interactions located at the cytoplasmic sides of transmembrane helices 3 and 6. Geometric and energetic features derived from the detailed analysis of a series of molecular dynamics simulations of the different rhodopsin mutants, involving positions 134(3.49), 247(6.30), and 251(6.34), suggest that the protein structure is sensitive to these mutations through the local changes induced that extend further to the secondary structure of neighboring helices and, ultimately, to the packing of the helical bundle. Overall, the results obtained highlight the complexity of the analyzed network of electrostatic interactions where the effect of each mutation on protein structure can produce rather specific features.     

Differences in Conformational Behavior of ATA and TAT Sequences in Single Strand DNA Trimer

Abstract

The conformational behavior of single strand (ss) TAT and ATA trimers of DNA have been studied by computational chemistry tools including CICADA software interfaced with AMBER molecular mechanics and dynamics. The Single-Coordinate-Driving (SCD) method has been used in conjunction with molecular dynamics simulated annealing. It has been revealed that the conformational flexibility of each sequence differs substantially from the other one. Four common conformational families have been found for both trimers. These are: helical, reverse-stacked (base 3), half-stacked (base 3), reverse-stacked (base 1). However, the energies of conformers representing the families are different for both the studied systems. An additional conformational family, bulged, has been found for ss(ATA), while ss(TAT) has been found also in half-stacked (base 1) conformation. In general, ss(TAT) exhibits a higher number of low energy conformations while ss(ATA) shows one interesting low energy conformational interconversion between reverse-stacked (A3) family and half-stacked (A3) family. The high conformational variability of the trimers has been confirmed by flexibility analysis and by molecular dynamics simulations, which have also shown the conformational stability of single conformational families. It has been concluded that the methodology used is able to provide a very detailed picture of the conformational space of these molecules.     

The nitrite-oxidizing community in activated sludge from a municipal wastewater treatment plant determined by fatty acid methyl ester-stable isotope probing

Metabolically-active autotrophic nitrite oxidizers from activated sludge were labeled with ¹³C-bicarbonate under exposure to different temperatures and nitrite concentrations. The labeled samples were characterized by FAME-SIP (fatty acid methyl ester-stable isotope probing). The compound cis-11-palmitoleic acid, which is the major lipid of the most abundant nitrite oxidizer in activated sludge, Candidatus Nitrospira defluvii, showed ¹³C-incorporation in all samples exposed to 3 mM nitrite. Subsequently, the lipid cis-7-palmitoleic acid was labeled, and it indicated the activity of a nitrite oxidizer that was different from the known Nitrospira taxa in activated sludge. The highest incorporation of cis-7-palmitoleic acid label was found after incubation with a nitrite concentration of 0.3 mM at 17 and 22 °C. While activity of Nitrobacter populations could not be detected by the FAME-SIP approach, an unknown nitrite oxidizer with the major lipid cis-9 isomer of palmitoleic acid exhibited ¹³C-incorporation at 28 °C with 30 mM nitrite. These results indicated flexibility of nitrite-oxidizing guilds in a complex community responding to different conditions. Labeled lipids so far not described for activated sludge-associated nitrifiers indicated the presence of unknown nitrite oxidizers in this habitat. The FAME-SIP-based information can be used to define appropriate conditions for the enrichment of nitrite-oxidizing guilds from complex samples.     

Multiscale Metabolic Modeling: Dynamic Flux Balance Analysis on a Whole-Plant Scale

Plant metabolism is characterized by a unique complexity on the cellular, tissue, and organ levels. On a whole-plant scale, changing source and sink relations accompanying plant development add another level of complexity to metabolism. With the aim of achieving a spatiotemporal resolution of source-sink interactions in crop plant metabolism, a multiscale metabolic modeling (MMM) approach was applied that integrates static organ-specific models with a whole-plant dynamic model. Allowing for a dynamic flux balance analysis on a whole-plant scale, the MMM approach was used to decipher the metabolic behavior of source and sink organs during the generative phase of the barley (Hordeum vulgare) plant. It reveals a sink-to-source shift of the barley stem caused by the senescence-related decrease in leaf source capacity, which is not sufficient to meet the nutrient requirements of sink organs such as the growing seed. The MMM platform represents a novel approach for the in silico analysis of metabolism on a whole-plant level, allowing for a systemic, spatiotemporally resolved understanding of metabolic processes involved in carbon partitioning, thus providing a novel tool for studying yield stability and crop improvement.Plants are of vital significance as a source of food (Grusak and DellaPenna, 1999; Rogalski and Carrer, 2011), feed (Lu et al., 2011), energy (Tilman et al., 2006; Parmar et al., 2011), and feedstocks for the chemical industry (Metzger and Bornscheuer, 2006; Kinghorn et al., 2011). Given the close connection between plant metabolism and the usability of plant products, there is a growing interest in understanding and predicting the behavior and regulation of plant metabolic processes. In order to increase crop quality and yield, there is a need for methods guiding the rational redesign of the plant metabolic network (Schwender, 2009).Mathematical modeling of plant metabolism offers new approaches to understand, predict, and modify complex plant metabolic processes. In plant research, the issue of metabolic modeling is constantly gaining attention, and different modeling approaches applied to plant metabolism exist, ranging from highly detailed quantitative to less complex qualitative approaches (for review, see Giersch, 2000; Morgan and Rhodes, 2002; Poolman et al., 2004; Rios-Estepa and Lange, 2007).A widely used modeling approach is flux balance analysis (FBA), which allows the prediction of metabolic capabilities and steady-state fluxes under different environmental and genetic backgrounds using (non)linear optimization (Orth et al., 2010). Assuming steady-state conditions, FBA has the advantage of not requiring the knowledge of kinetic parameters and, therefore, can be applied to model detailed, large-scale systems. In recent years, the FBA approach has been applied to several different plant species, such as maize (Zea mays; Dal’Molin et al., 2010; Saha et al., 2011), barley (Hordeum vulgare; Grafahrend-Belau et al., 2009b; Melkus et al., 2011; Rolletschek et al., 2011), rice (Oryza sativa; Lakshmanan et al., 2013), Arabidopsis (Arabidopsis thaliana; Poolman et al., 2009; de Oliveira Dal’Molin et al., 2010; Radrich et al., 2010; Williams et al., 2010; Mintz-Oron et al., 2012; Cheung et al., 2013), and rapeseed (Brassica napus; Hay and Schwender, 2011a, 2011b; Pilalis et al., 2011), as well as algae (Boyle and Morgan, 2009; Cogne et al., 2011; Dal’Molin et al., 2011) and photoautotrophic bacteria (Knoop et al., 2010; Montagud et al., 2010; Boyle and Morgan, 2011). These models have been used to study different aspects of metabolism, including the prediction of optimal metabolic yields and energy efficiencies (Dal’Molin et al., 2010; Boyle and Morgan, 2011), changes in flux under different environmental and genetic backgrounds (Grafahrend-Belau et al., 2009b; Dal’Molin et al., 2010; Melkus et al., 2011), and nonintuitive metabolic pathways that merit subsequent experimental investigations (Poolman et al., 2009; Knoop et al., 2010; Rolletschek et al., 2011). Although FBA of plant metabolic models was shown to be capable of reproducing experimentally determined flux distributions (Williams et al., 2010; Hay and Schwender, 2011b) and generating new insights into metabolic behavior, capacities, and efficiencies (Sweetlove and Ratcliffe, 2011), challenges remain to advance the utility and predictive power of the models.Given that many plant metabolic functions are based on interactions between different subcellular compartments, cell types, tissues, and organs, the reconstruction of organ-specific models and the integration of these models into interacting multiorgan and/or whole-plant models is a prerequisite to get insight into complex plant metabolic processes organized on a whole-plant scale (e.g. source-sink interactions). Almost all FBA models of plant metabolism are restricted to one cell type (Boyle and Morgan, 2009; Knoop et al., 2010; Montagud et al., 2010; Cogne et al., 2011; Dal’Molin et al., 2011), one tissue or one organ (Grafahrend-Belau et al., 2009b; Hay and Schwender, 2011a, 2011b; Pilalis et al., 2011; Mintz-Oron et al., 2012), and only one model exists taking into account the interaction between two cell types by specifying the interaction between mesophyll and bundle sheath cells in C4 photosynthesis (Dal’Molin et al., 2010). So far, no model representing metabolism at the whole-plant scale exists.Considering whole-plant metabolism raises the problem of taking into account temporal and environmental changes in metabolism during plant development and growth. Although classical static FBA is unable to predict the dynamics of metabolic processes, as the network analysis is based on steady-state solutions, time-dependent processes can be taken into account by extending the classical static FBA to a dynamic flux balance analysis (dFBA), as proposed by Mahadevan et al. (2002). The static (SOA) and dynamic optimization approaches introduced in this work provide a framework for analyzing the transience of metabolism by integrating kinetic expressions to dynamically constrain exchange fluxes. Due to the requirement of knowing or estimating a large number of kinetic parameters, so far dFBA has only been applied to a plant metabolic model once, to study the photosynthetic metabolism in the chloroplasts of C3 plants by a simplified model of five biochemical reactions (Luo et al., 2009). Integrating a dynamic model into a static FBA model is an alternative approach to perform dFBA.In this study, a multiscale metabolic modeling (MMM) approach was applied with the aim of achieving a spatiotemporal resolution of cereal crop plant metabolism. To provide a framework for the in silico analysis of the metabolic dynamics of barley on a whole-plant scale, the MMM approach integrates a static multiorgan FBA model and a dynamic whole-plant multiscale functional plant model (FPM) to perform dFBA. The performance of the novel whole-plant MMM approach was tested by studying source-sink interactions during the seed developmental phase of barley plants.     

The plant Selaginella moellendorffii possesses enzymes for synthesis and hydrolysis of the compatible solutes mannosylglycerate and glucosylglycerate

A mannosylglycerate synthase (MgS) gene detected in the genome of Selaginella moellendorffii was expressed in E. coli and the recombinant enzyme was purified and characterized. A remarkable and unprecedented feature of this enzyme was the ability to efficiently synthesize mannosylglycerate (MG) and glucosylglycerate (GG) alike, with maximal activity at 50 °C, pH 8.0 and with Mg²⁺ as reaction enhancer. We have also identified a novel glycoside hydrolase gene in this plant’s genome, which was functionally confirmed to be highly specific for the hydrolysis of MG and GG and named MG hydrolase (MgH), due to its homology with bacterial MgHs. The recombinant enzyme was maximally active at 40 °C and at pH 6.0–6.5. The activity was independent of cations, but Mn²⁺ was a strong stimulator. Regardless of these efficient enzymatic resources we could not detect MG or GG in S. moellendorffii or in the extracts of five additional Selaginella species. Herein, we describe the properties of the first eukaryotic enzymes for the synthesis and hydrolysis of the compatible solutes, MG and GG.     

Attenuated and Replication-Competent Vaccinia Virus Strains M65 and M101 with Distinct Biology and Immunogenicity as Potential Vaccine Candidates against Pathogens

Replication-competent poxvirus vectors with an attenuation phenotype and with a high immunogenic capacity of the foreign expressed antigen are being pursued as novel vaccine vectors against different pathogens. In this investigation, we have examined the replication and immunogenic characteristics of two vaccinia virus (VACV) mutants, M65 and M101. These mutants were generated after 65 and 101 serial passages of persistently infected Friend erythroleukemia (FEL) cells. In cultured cells of different origins, the mutants are replication competent and have growth kinetics similar to or slightly reduced in comparison with those of the parental Western Reserve (WR) virus strain. In normal and immune-suppressed infected mice, the mutants showed different levels of attenuation and pathogenicity in comparison with WR and modified vaccinia Ankara (MVA) strains. Wide genome analysis after deep sequencing revealed selected genomic deletions and mutations in a number of viral open reading frames (ORFs). Mice immunized in a DNA prime/mutant boost regimen with viral vectors expressing the LACK (Leishmania homologue for receptors of activated C kinase) antigen of Leishmania infantum showed protection or a delay in the onset of cutaneous leishmaniasis. Protection was similar to that triggered by MVA-LACK. In immunized mice, both polyfunctional CD4⁺ and CD8⁺ T cells with an effector memory phenotype were activated by the two mutants, but the DNA-LACK/M65-LACK protocol preferentially induced CD4⁺ whereas DNA-LACK/M101-LACK preferentially induced CD8⁺ T cell responses. Altogether, our findings showed the adaptive changes of the WR genome during long-term virus-host cell interaction and how the replication competency of M65 and M101 mutants confers distinct biological properties and immunogenicity in mice compared to those of the MVA strain. These mutants could have applicability for understanding VACV biology and as potential vaccine vectors against pathogens and tumors.     

Fossilization of Acidophilic Microorganisms

This study examines fossil microorganisms found in iron-rich deposits in an extreme acidic environment, the Tinto River in SW Spain. Both electron microscopy (SEM and TEM) and non-destructive in situ microanalytical techniques (EDS, EMP and XPS) were used to determine the role of permineralization and encrustation in preserving microorganisms forming biofilms in the sediments. Unicellular algae were preserved by silica permineralization of their cell walls. Bacterial biofilms were preserved as molds by epicellular deposition of schwertmannite around them. In the case of fungi and filamentous algae, we observed permineralization of cell structures by schwertmannite in the sediments. The extracellular polymeric matrix around the cells was also preserved through permineralization of the fibrillar component. The process of permineralization and deposition of iron-rich precipitates present in the acidic waters of Rio Tinto served to preserve many microfossils in an oxidizing environment, in which organic compounds would not normally be expected to persist. Studies of microbial fossil formation mechanisms in modern extreme environments should focus on defining criteria to identify inorganic traces of microbial life in past environments on Earth or other planets.     

Lactate administration reproduces specific brain and liver exercise‐related changes

The effects of exercise are not limited to muscle, and its ability to mitigate some chronic diseases is under study. A more complete understanding of how exercise impacts non‐muscle tissues might facilitate design of clinical trials and exercise mimetics. Here, we focused on lactate's ability to mediate changes in liver and brain bioenergetic‐associated parameters. In one group of experiments, C57BL/6 mice underwent 7 weeks of treadmill exercise sessions at intensities intended to exceed the lactate threshold. Over time, the mice dramatically increased their lactate threshold. To ensure that plasma lactate accumulated during the final week, the mice were run to exhaustion. In the liver, mRNA levels of gluconeogenesis‐promoting genes increased. While peroxisome proliferator‐activated receptor‐gamma co‐activator 1 alpha (PGC‐1α) expression increased, there was a decrease in PGC‐1β expression, and overall gene expression changes favored respiratory chain down‐regulation. In the brain, PGC‐1α and PGC‐1β were unchanged, but PGC‐1‐related co‐activator expression and mitochondrial DNA copy number increased. Brain tumor necrosis factor alpha expression fell, whereas vascular endothelial growth factor A expression rose. In another group of experiments, exogenously administered lactate was found to reproduce some but not all of these observed liver and brain changes. Our data suggest that lactate, an exercise byproduct, could mediate some of the effects exercise has on the liver and the brain, and that lactate itself can act as a partial exercise mimetic.