Frugivores at higher risk of extinction are the key elements of a mutualistic network

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

MicroRNoma do carcinoma de pâncreas

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Natural intracellular peptides can modulate the interactions of mouse brain proteins and thimet oligopeptidase with 14-3-3e and calmodulin

Protein interactions are crucial for most cellular process. Thus, rationally designed peptides that act as competitive assembly inhibitors of protein interactions by mimicking specific, determined structural elements have been extensively used in clinical and basic research. Recently, mammalian cells have been shown to contain a large number of intracellular peptides of unknown function. Here, we investigate the role of several of these natural intracellular peptides as putative modulators of protein interactions that are related to Ca2+-calmodulin (CaM) and 14-3-3 epsilon, which are proteins that are related to the spatial organization of signal transduction within cells. At concentrations of 1-50 mu M, most of the peptides that are investigated in this study modulate the interactions of CaM and 14-3-3 epsilon with proteins from the mouse brain cytoplasm or recombinant thimet oligopeptidase (EP24.15) in vitro, as measured by surface plasmon resonance. One of these peptides (VFDVELL; VFD-7) increases the cytosolic Ca2+ concentration in a dose-dependent manner but only if introduced into HEK293 cells, which suggests a wide biological function of this peptide. Therefore, it is exciting to suggest that natural intracellular peptides are novel modulators of protein interactions and have biological functions within cells.

Protein Disulfide Isomerase Is Required for Platelet-derived Growth Factor-induced Vascular Smooth Muscle Cell Migration, Nox1 NADPH Oxidase Expression, and RhoGTPase Activation

Vascular Smooth Muscle Cell (VSMC) migration into vessel neointima is a therapeutic target for atherosclerosis and postinjury restenosis. Nox1 NADPH oxidase-derived oxidants synergize with growth factors to support VSMC migration. We previously described the interaction between NADPH oxidases and the endoplasmic reticulum redox chaperone protein disulfide isomerase (PDI) in many cell types. However, physiological implications, as well as mechanisms of such association, are yet unclear. We show here that platelet-derived growth factor (PDGF) promoted subcellular redistribution of PDI concomitant to Nox1-dependent reactive oxygen species production and that siRNA-mediated PDI silencing inhibited such reactive oxygen species production, while nearly totally suppressing the increase in Nox1 expression, with no change in Nox4. Furthermore, PDI silencing inhibited PDGF-induced VSMC migration assessed by distinct methods, whereas PDI overexpression increased spontaneous basal VSMC migration. To address possible mechanisms of PDI effects, we searched for PDI interactome by systems biology analysis of physical protein-protein interaction networks, which indicated convergence with small GTPases and their regulator RhoGDI. PDI silencing decreased PDGF-induced Rac1 and RhoA activities, without changing their expression. PDI co-immunoprecipitated with RhoGDI at base line, whereas such association was decreased after PDGF. Also, PDI co-immunoprecipitated with Rac1 and RhoA in a PDGF-independent way and displayed detectable spots of perinuclear co-localization with Rac1 and RhoGDI. Moreover, PDI silencing promoted strong cytoskeletal changes: disorganization of stress fibers, decreased number of focal adhesions, and reduced number of RhoGDI-containing vesicular recycling adhesion structures. Overall, these data suggest that PDI is required to support Nox1/redox and GTPase-dependent VSMC migration.

Using gene-network landscape to dissect genotype effects of TCF7L2 genetic variant on diabetes and cardiovascular risk

Vaquero AR, Ferreira NE, Omae SV, Rodrigues MV, Teixeira SK, Krieger JE, Pereira AC. Using gene-network landscape to dissect genotype effects of TCF7L2 genetic variant on diabetes and cardiovascular risk. Physiol Genomics 44: 903-914, 2012. First published August 7, 2012; doi:10.1152/physiolgenomics.00030.2012.-The single nucleotide polymorphism (SNP) within the TCF7L2 gene, rs7903146, is, to date, the most significant genetic marker associated with Type 2 diabetes mellitus (T2DM) risk. Nonetheless, its functional role in disease pathology is poorly understood. The aim of the present study was to investigate, in vascular smooth muscle cells from 92 patients undergoing aortocoronary bypass surgery, the contribution of this SNP in T2DM using expression levels and expression correlation comparison approaches, which were visually represented as gene interaction networks. Initially, the expression levels of 41 genes (seven TCF7L2 splice forms and 40 other T2DM relevant genes) were compared between rs7903146 wild-type (CC) and T2DM-risk (CT + TT) genotype groups. Next, we compared the expression correlation patterns of these 41 genes between groups to observe if the relationships between genes were different. Five TCF7L2 splice forms and nine genes showed significant expression differences between groups. RXR alpha gene was pinpointed as showing the most different expression correlation pattern with other genes. Therefore, T2DM risk alleles appear to be influencing TCF7L2 splice form's expression in vascular smooth muscle cells, and RXR alpha gene is pointed out as a treatment target candidate for risk reduction in individuals with high risk of developing T2DM, especially individuals harboring TCF7L2 risk genotypes.

Bottom-up effects of plant diversity on multitrophic interactions in a biodiversity experiment

Biodiversity is rapidly declining, and this may negatively affect ecosystem processes, including economically important ecosystem services. Previous studies have shown that biodiversity has positive effects on organisms and processes across trophic levels. However, only a few studies have so far incorporated an explicit food-web perspective. In an eight-year biodiversity experiment, we studied an unprecedented range of above- and below-ground organisms and multitrophic interactions. A multitrophic data set originating from a single long-term experiment allows mechanistic insights that would not be gained from meta-analysis of different experiments. Here we show that plant diversity effects dampen with increasing trophic level and degree of omnivory. This was true both for abundance and species richness of organisms. Furthermore, we present comprehensive above-ground/below-ground biodiversity food webs. Both above ground and below ground, herbivores responded more strongly to changes in plant diversity than did carnivores or omnivores. Density and richness of carnivorous taxa was independent of vegetation structure. Below-ground responses to plant diversity were consistently weaker than above-ground responses. Responses to increasing plant diversity were generally positive, but were negative for biological invasion, pathogen infestation and hyperparasitism. Our results suggest that plant diversity has strong bottom-up effects on multitrophic interaction networks, with particularly strong effects on lower trophic levels. Effects on higher trophic levels are indirectly mediated through bottom-up trophic cascades.

Generation and analysis of a mouse intestinal metatranscriptome through Illumina based RNA-sequencing

With the advent of high through-put sequencing (HTS), the emerging science of metagenomics is transforming our understanding of the relationships of microbial communities with their environments. While metagenomics aims to catalogue the genes present in a sample through assessing which genes are actively expressed, metatranscriptomics can provide a mechanistic understanding of community inter-relationships. To achieve these goals, several challenges need to be addressed from sample preparation to sequence processing, statistical analysis and functional annotation. Here we use an inbred non-obese diabetic (NOD) mouse model in which germ-free animals were colonized with a defined mixture of eight commensal bacteria, to explore methods of RNA extraction and to develop a pipeline for the generation and analysis of metatranscriptomic data. Applying the Illumina HTS platform, we sequenced 12 NOD cecal samples prepared using multiple RNA-extraction protocols. The absence of a complete set of reference genomes necessitated a peptide-based search strategy. Up to 16% of sequence reads could be matched to a known bacterial gene. Phylogenetic analysis of the mapped ORFs revealed a distribution consistent with ribosomal RNA, the majority from Bacteroides or Clostridium species. To place these HTS data within a systems context, we mapped the relative abundance of corresponding Escherichia coli homologs onto metabolic and protein-protein interaction networks. These maps identified bacterial processes with components that were well-represented in the datasets. In summary this study highlights the potential of exploiting the economy of HTS platforms for metatranscriptomics.

SNARE-fusion mediated insertion of membrane proteins into native and artificial membranes

Membrane proteins carry out functions such as nutrient uptake, ATP synthesis or transmembrane signal transduction. An increasing number of reports indicate that cellular processes are underpinned by regulated interactions between these proteins. Consequently, functional studies of these networks at a molecular level require co-reconstitution of the interacting components. Here, we report a SNARE protein-based method for incorporation of multiple membrane proteins into artificial membrane vesicles of well-defined composition, and for delivery of large water-soluble substrates into these vesicles. The approach is used for in vitro reconstruction of a fully functional bacterial respiratory chain from purified components. Furthermore, the method is used for functional incorporation of the entire F1F0 ATP synthase complex into native bacterial membranes from which this component had been genetically removed. The novel methodology offers a tool to investigate complex interaction networks between membrane-bound proteins at a molecular level, which is expected to generate functional insights into key cellular functions.

SNARE-fusion mediated inserton of membrane proteins into native and artificial membranes

Membrane proteins carry out functions such as nutrient uptake, ATP synthesis or transmembrane signal transduction. An increasing number of reports indicate that cellular processes are underpinned by regulated interactions between these proteins. Consequently, functional studies of these networks at a molecular level require co-reconstitution of the interacting components. Here, we report a SNARE-protein based method for incorporation of multiple membrane proteins into membranes, and for delivery of large water-soluble substrates into closed membrane vesicles. The approach is used for in vitro reconstruction of a fully functional bacterial respiratory chain from purified components. Furthermore, the method is used for functional incorporation of the entire F1F0-ATP synthase complex into native bacterial membranes from which this component had been genetically removed. The novel methodology offers a tool to investigate complex interaction networks between membrane-bound proteins at a molecular level, which is expected to generate functional insights into key cellular functions.

Effects of forest management on bryophyte communities on deadwood

Epixylic bryophytes are important components of forest vegetation but are currently endangered by increment of wood harvest and intensive forest management. In this paper we present a study about the relationship between forest management, deadwood abundance, deadwood attributes and species richness of epixylic bryophytes on 30 plots comprising three forest types (managed coniferous, managed deciduous and unmanaged deciduous forests) in three regions in Germany. Additionally we analyzed the relations between deadwood attributes (wood species, decay, deadwood type, size) and bryophytes on deadwood items (n = 799) and calculated species interaction networks of wood species and bryophytes. Overall, species richness of epixylic bryophytes was positively related to deadwood abundance and diversity. The mean deadwood abundance was lowest in unmanaged forests (9.7 m³ ha^-1) compared with 15.0 m³ ha^-1 in managed deciduous and 25.1 m³ ha^-1 in managed coniferous forests. Accordingly, epixylic bryophyte species richness per plot increased from 7 species per 400 m 2 in unmanaged, 10 in managed deciduous and 16 in managed coniferous forests. The interaction network provided evidence of importance of tree-species diversity for bryophyte diversity and the relevance of particular wood species for rare bryophytes.

Generally, the results demonstrate a considerable lack of deadwood in all forest types, even in unmanaged forests. Species richness of epixylic bryophytes was strongly limited by available substrates within the observed deadwood abundance ranging up to only 60 m³ ha^-1. Altogether, this suggests a high demand to increase both abundance and diversity of deadwood in forests.

Differential Micro RNA Expression in PBMC from Multiple Sclerosis Patients

Differences in gene expression patterns have been documented not only in Multiple Sclerosis patients versus healthy controls but also in the relapse of the disease. Recently a new gene expression modulator has been identified: the microRNA or miRNA. The aim of this work is to analyze the possible role of miRNAs in multiple sclerosis, focusing on the relapse stage. We have analyzed the expression patterns of 364 miRNAs in PBMC obtained from multiple sclerosis patients in relapse status, in remission status and healthy controls. The expression patterns of the miRNAs with significantly different expression were validated in an independent set of samples. In order to determine the effect of the miRNAs, the expression of some predicted target genes of these were studied by qPCR. Gene interaction networks were constructed in order to obtain a co-expression and multivariate view of the experimental data. The data analysis and later validation reveal that two miRNAs (hsa-miR-18b and hsa-miR-599) may be relevant at the time of relapse and that another miRNA (hsa-miR-96) may be involved in remission. The genes targeted by hsa-miR-96 are involved in immunological pathways as Interleukin signaling and in other pathways as wnt signaling. This work highlights the importance of miRNA expression in the molecular mechanisms implicated in the disease. Moreover, the proposed involvement of these small molecules in multiple sclerosis opens up a new therapeutic approach to explore and highlight some candidate biomarker targets in MS

Quantitative modeling of stochastic systems in molecular biology by using stochastic Petri nets

An integrated understanding of molecular and developmental biology must consider the large number of molecular species involved and the low concentrations of many species in vivo. Quantitative stochastic models of molecular interaction networks can be expressed as stochastic Petri nets (SPNs), a mathematical formalism developed in computer science. Existing software can be used to define molecular interaction networks as SPNs and solve such models for the probability distributions of molecular species. This approach allows biologists to focus on the content of models and their interpretation, rather than their implementation. The standardized format of SPNs also facilitates the replication, extension, and transfer of models between researchers. A simple chemical system is presented to demonstrate the link between stochastic models of molecular interactions and SPNs. The approach is illustrated with examples of models of genetic and biochemical phenomena where the UltraSAN package is used to present results from numerical analysis and the outcome of simulations.

Computational Analysis of Intelligent Agents: Social and Strategic Settings

The central motif of this work is prediction and optimization in presence of multiple interacting intelligent agents. We use the phrase `intelligent agents' to imply in some sense, a `bounded rationality', the exact meaning of which varies depending on the setting. Our agents may not be `rational' in the classical game theoretic sense, in that they don't always optimize a global objective. Rather, they rely on heuristics, as is natural for human agents or even software agents operating in the real-world. Within this broad framework we study the problem of influence maximization in social networks where behavior of agents is myopic, but complication stems from the structure of interaction networks. In this setting, we generalize two well-known models and give new algorithms and hardness results for our models. Then we move on to models where the agents reason strategically but are faced with considerable uncertainty. For such games, we give a new solution concept and analyze a real-world game using out techniques. Finally, the richest model we consider is that of Network Cournot Competition which deals with strategic resource allocation in hypergraphs, where agents reason strategically and their interaction is specified indirectly via player's utility functions. For this model, we give the first equilibrium computability results. In all of the above problems, we assume that payoffs for the agents are known. However, for real-world games, getting the payoffs can be quite challenging. To this end, we also study the inverse problem of inferring payoffs, given game history. We propose and evaluate a data analytic framework and we show that it is fast and performant.

Identity formation in social networks websites: facebook and the interaction between young individuals in the cases of Slovenia and Catalonia

This paper lays down some theoretical framework for further research to be made on the subject of how identity of young Slovenian and Catalan users is forming within the social networking website Facebook. The author pursues his interest based on observation of how communicationand thus interaction between users is changing and how this is reflected in everyday practices. In so doing he tries to identify the connections between the individual, society and technology, asthese are more and more interwoven, and we cannot think one without the other in thecontemporary globalised world.

Transition to parenthood: The role of social interaction and endogenous networks

Empirical studies indicate that the transition to parenthood is influenced by an individual's peer group. To study the mechanisms creating interdepen- dencies across individuals' transition to parenthood and its timing we apply an agent-based simulation model. We build a one-sex model and provide agents with three different characteristics regarding age, intended education and parity. Agents endogenously form their network based on social closeness. Network members then may influence the agents' transition to higher parity levels. Our numerical simulations indicate that accounting for social inter- actions can explain the shift of first-birth probabilities in Austria over the period 1984 to 2004. Moreover, we apply our model to forecast age-specific fertility rates up to 2016.