Quantitative single-molecule localization microscopy combined with rule-based modeling reveals ligand-induced TNF-R1 reorganization toward higher-order oligomers

We report on the assembly of tumor necrosis factor receptor 1 (TNF-R1) prior to ligand activation and its ligand-induced reorganization at the cell membrane. We apply single-molecule localization microscopy to obtain quantitative information on receptor cluster sizes and copy numbers. Our data suggest a dimeric pre-assembly of TNF-R1, as well as receptor reorganization toward higher oligomeric states with stable populations comprising three to six TNF-R1. Our experimental results directly serve as input parameters for computational modeling of the ligand-receptor interaction. Simulations corroborate the experimental finding of higher-order oligomeric states. This work is a first demonstration how quantitative, super-resolution and advanced microscopy can be used for systems biology approaches at the single-molecule and single-cell level.

A high-density immunoblotting methodology for quantification of total protein levels and phosphorylation modifications

The components of many signaling pathways have been identified and there is now a need to conduct quantitative data-rich temporal experiments for systems biology and modeling approaches to better understand pathway dynamics and regulation. Here we present a modified Western blotting method that allows the rapid and reproducible quantification and analysis of hundreds of data points per day on proteins and their phosphorylation state at individual sites. The approach is of particular use where samples show a high degree of sample-to-sample variability such as primary cells from multiple donors. We present a case study on the analysis of >800 phosphorylation data points from three phosphorylation sites in three signaling proteins over multiple time points from platelets isolated from ten donors, demonstrating the technique's potential to determine kinetic and regulatory information from limited cell numbers and to investigate signaling variation within a population. We envisage the approach being of use in the analysis of many cellular processes such as signaling pathway dynamics to identify regulatory feedback loops and the investigation of potential drug/inhibitor responses, using primary cells and tissues, to generate information about how a cell's physiological state changes over time.

Maintenance and differentiation of neural stem cells

The adult mammalian brain contains self-renewable, multipotent neural stem cells (NSCs) that are responsible for neurogenesis and plasticity in specific regions of the adult brain. Extracellular matrix, vasculature, glial cells, and other neurons are components of the niche where NSCs are located. This surrounding environment is the source of extrinsic signals that instruct NSCs to either self-renew or differentiate. Additionally, factors such as the intracellular epigenetics state and retrotransposition events can influence the decision of NSC`s fate into neurons or glia. Extrinsic and intrinsic factors form an intricate signaling network, which is not completely understood. These factors altogether reflect a few of the key players characterized so far in the new field of NSC research and are covered in this review. (C) 2010 John Wiley & Sons, Inc. WIREs Syst Biol Med 2011 3 107-114 DOI:10.1002/wsbm:100

Molecular Characterization of Propolis-Induced Cell Death in Saccharomyces cerevisiae

Propolis, a natural product of plant resins, is used by the bees to seal holes in their honeycombs and protect the hive entrance. However, propolis has also been used in folk medicine for centuries. Here, we apply the power of Saccharomyces cerevisiae as a model organism for studies of genetics, cell biology, and genomics to determine how propolis affects fungi at the cellular level. Propolis is able to induce an apoptosis cell death response. However, increased exposure to propolis provides a corresponding increase in the necrosis response. We showed that cytochrome c but not endonuclease G (Nuc1p) is involved in propolis-mediated cell death in S. cerevisiae. We also observed that the metacaspase YCA1 gene is important for propolis-mediated cell death. To elucidate the gene functions that may be required for propolis sensitivity in eukaryotes, the full collection of about 4,800 haploid S. cerevisiae deletion strains was screened for propolis sensitivity. We were able to identify 138 deletion strains that have different degrees of propolis sensitivity compared to the corresponding wild-type strains. Systems biology revealed enrichment for genes involved in the mitochondrial electron transport chain, vacuolar acidification, negative regulation of transcription from RNA polymerase II promoter, regulation of macroautophagy associated with protein targeting to vacuoles, and cellular response to starvation. Validation studies indicated that propolis sensitivity is dependent on the mitochondrial function and that vacuolar acidification and autophagy are important for yeast cell death caused by propolis.

Comparison of the interactomic networks of different species in terms of accessibility

Protein-protein interaction networks were investigated in terms of outward accessibility, which quantifies the effectiveness of each protein in accessing other proteins and is related to the internality of nodes. By comparing the accessibility between 144 ortholog proteins in yeast and the fruit fly, we found that the accessibility tends to be higher among proteins in the fly than in yeast. In addition, z-scores of the accessibility calculated for different species revealed that the protein networks of less evolved species tend to be more random than those of more evolved species. The accessibility was also used to identify the border of the yeast protein interaction network, which was found to be mainly composed of viable proteins.

Protein lethality investigated in terms of long range dynamical interactions

The relationship between network structure/dynamics and biological function constitutes a fundamental issue in systems biology. However, despite many related investigations, the correspondence between structure and biological functions is not yet fully understood. A related subject that has deserved particular attention recently concerns how essentiality is related to the structure and dynamics of protein interactions. In the current work, protein essentiality is investigated in terms of long range influences in protein-protein interaction networks by considering simulated dynamical aspects. This analysis is performed with respect to outward activations, an approach which models the propagation of interactions between proteins by considering self-avoiding random walks. The obtained results are compared to protein local connectivity. Both the connectivity and the outward activations were found to be strongly related to protein essentiality.

Resilience of protein-protein interaction networks as determined by their large-scale topological features

The relationship between the structure and function of biological networks constitutes a fundamental issue in systems biology. Particularly, the structure of protein-protein interaction networks is related to important biological functions. In this work, we investigated how such a resilience is determined by the large scale features of the respective networks. Four species are taken into account, namely yeast Saccharomyces cerevisiae, worm Caenorhabditis elegans, fly Drosophila melanogaster and Homo sapiens. We adopted two entropy-related measurements (degree entropy and dynamic entropy) in order to quantify the overall degree of robustness of these networks. We verified that while they exhibit similar structural variations under random node removal, they differ significantly when subjected to intentional attacks (hub removal). As a matter of fact, more complex species tended to exhibit more robust networks. More specifically, we quantified how six important measurements of the networks topology (namely clustering coefficient, average degree of neighbors, average shortest path length, diameter, assortativity coefficient, and slope of the power law degree distribution) correlated with the two entropy measurements. Our results revealed that the fraction of hubs and the average neighbor degree contribute significantly for the resilience of networks. In addition, the topological analysis of the removed hubs indicated that the presence of alternative paths between the proteins connected to hubs tend to reinforce resilience. The performed analysis helps to understand how resilience is underlain in networks and can be applied to the development of protein network models.

Potassium Current in Mature Bovine Spermatozoa

Ion channels have been assigned a pivotal importance in various sperm functions and are therefore promising targets for contraceptive development. The lack of data on channel functionality and pharmacology has hampered this goal. This is a consequence of technical problems of applying electrophysiological techniques to spermatozoa due to their small size and form. By using a laminin coating to increase adherence of spermatozoa and nystatin in the patch pipette for pore formation, we have adapted the whole-cell recording technique to study currents in mature uncapacitated bovine spermatozoa. Employing these conditions, in the head region, patched spermatozoa could be transferred into the whole-cell configuration. For the first time we document an outward rectifying current in mature bovine spermatozoa was blocked by tetraethyl ammonium (TEA) chloride. The observation of a shift in the reversal potential as a response to changes in the extracellular concentration of K+ ions allowed us to identify this current as K+ selective. This result shows that K+ channels in the head region of mature uncapacitated bovine spermatozoa can be suitably investigated using the whole-cell recording patch-clamp technique.

The Economic Effects of Ski Resorts on Communities in the State of Maine

Skiing and snowboarding is a fairly expensive activity for participant and one in which the industry as a whole makes handsome profits. In the 2005/06 season, resorts in the Northeast reported an average gross revenue of $18.5 million. (NSAA) With the current weather phenomenon of El Nino, however, resorts in New England especially, have been suffering economically. The gross revenue in New England in the ’05/’06 season was down 4% from the previous year, likely due to the fact the total snowfall declined by 16%. (NSAA) Much of this loss in revenue came during the Christmas to New Years vacation period. In the 2007 season, most mountains were less than half-opened during this peak week and the number of skiers and riders was especially low. With such a large decrease in profits, it is likely that many people will soon be affected (if they have not already been), including local employees. This project, therefore, seeks to analyze the impact that the resorts have on the local economies in order to determine the potential problems the changing snowfall patterns could have on locals’ well-being. It is hypothesized that there will be a strong correlation between the proximity of a community to a resort and the relative economic prosperity of that community; meaning that the ski industry is a pivotal part of their income and livelihood.

Resposta de Chromobacterium Violaceum cultivada em alta concentração de ferro

The Chromobacterium violaceum is a β-proteobacterium Gram-negative widely found in tropical and subtropical regions, whose genome was sequenced in 2003 showing great metabolic versatility and biotechnological and pharmaceutical potential. Given the large number of ORFs related to iron metabolism described in the genome of C. violaceum, the importance of this metal for various biological processes and due to lack of data about the consequences of excess of iron in free-living organisms, it is important to study the response mechanism of this bacterium in a culture filled with iron. Previous work showed that C. violaceum is resistant to high concentrations of this metal, but has not yet been described the mechanism which is used to this survival. Thus, to elucidate the response of C. violaceum cultured in high concentrations of iron and expecting to obtain candidate genes for use in bioremediation processes, this study used a shotgun proteomics approach and systems biology to assess the response of C. violaceum grown in the presence and absence of 9 mM of iron. The analysis identified 531 proteins, being 71 exclusively expressed by the bacteria grown in the presence of the metal and 100 just in the control condition. The increase in expression of proteins related to the TCA cycle possibly represents a metabolic reprogramming of the bacteria caused by high concentration of iron in the medium. Moreover, we observed an increase in the activity assay of superoxide dismutase and catalase as well as in Total Antioxidant Activity assay, suggesting that the metal is inducing oxidative stress in C. violaceum that increases the levels of violacein and antioxidant enzymes to better adapt to the emerging conditions. Are also part of the adaptive response changes in expression of proteins related to transport, including iron, as well as an increased expression of proteins related to chemotaxis response, which would lead the bacteria to change the direction of its movement away from the metal. Systems Biology results, also suggest a metabolic reprogramming with mechanisms coordinated by bottleneck proteins involved in transcription (GreA), energy metabolism (Rpe and TpiA) and methylation (AhcY)

Bioinformatical and in vitro approaches to essential oil-induced matrix metalloproteinase inhibition

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Construção, caracterização global e local de redes biológicas

A Biologia Sistêmica visa a compreensão da vida através de modelos integrativos que enfatizem as interações entre os diferentes agentes biológicos. O objetivo é buscar por leis universais, não nas partes componentes dos sistemas mas sim nos padrões de interação dos elementos constituintes. As redes complexas biológicas são uma poderosa abstração matemática que permite a representação de grandes volumes de dados e a posterior formulação de hipóteses biológicas. Nesta tese apresentamos as redes biológicas integradas que incluem interações oriundas do metabolismo, interação física de proteínas e regulação. Discutimos sua construção e ferramentas para sua análise global e local. Apresentamos também resultados do uso de ferramentas de aprendizado de máquina que nos permitem compreender a relação entre propriedades topológicas e a essencialidade gênica e a previsão de genes mórbidos e alvos para drogas em humanos

Prediction of Oncogenic Interactions and Cancer-Related Signaling Networks Based on Network Topology

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

Análise de propriedades topológicas das redes biológicas integradas da Escherichia coli e da Saccharomyces cerevisiae

Biological processes are complex and possess emergent properties that can not be explained or predict by reductionism methods. To overcome the limitations of reductionism, researchers have been used a group of methods known as systems biology, a new interdisciplinary eld of study aiming to understand the non-linear interactions among components embedded in biological processes. These interactions can be represented by a mathematical object called graph or network, where the elements are represented by nodes and the interactions by edges that link pair of nodes. The networks can be classi- ed according to their topologies: if node degrees follow a Poisson distribution in a given network, i.e. most nodes have approximately the same number of links, this is a random network; if node degrees follow a power-law distribution in a given network, i.e. small number of high-degree nodes and high number of low-degree nodes, this is a scale-free network. Moreover, networks can be classi ed as hierarchical or non-hierarchical. In this study, we analised Escherichia coli and Saccharomyces cerevisiae integrated molecular networks, which have protein-protein interaction, metabolic and transcriptional regulation interactions. By using computational methods, such as MathematicaR , and data collected from public databases, we calculated four topological parameters: the degree distribution P(k), the clustering coe cient C(k), the closeness centrality CC(k) and the betweenness centrality CB(k). P(k) is a function that calculates the total number of nodes with k degree connection and is used to classify the network as random or scale-free. C(k) shows if a network is hierarchical, i.e. if the clusterization coe cient depends on node degree. CC(k) is an indicator of how much a node it is in the lesse way among others some nodes of the network and the CB(k) is a pointer of how a particular node is among several ...(Complete abstract click electronic access below)

Caracterização topológica dos motivos das redes biológicas integradas da Escherichia coli e da Saccharomyces cerevisiae

The reducionism method has helped in the clari cation of functioning of many biological process. However, such process are extremely complex and have emergent properties that can not be explained or even predicted by reducionism methods. To overcome these limits, researchers have been used a set of methods known as systems biology, a new area of biology aiming to understand the interactions between the multiple components of biological processes. These interactions can be represented by a mathematical object called graph or network, where the interacting elements are represented by a vertex and the interactions by edges that connect a pair of vertexes. Into graphs it is possible to nd subgraphs, occurring in complex networks at numbers that are signi cantly higher than those in randomized networks, they are de ned as motifs. As motifs in biological networks may represent the structural units of biological processess, their detection is important. Therefore, the aim of this present work was detect, count and classify motifs present in biological integrated networks of bacteria Escherichia coli and yeast Saccharomyces cere- visiae. For this purpose, we implemented codes in MathematicaR and Python environments for detecting, counting and classifying motifs in these networks. The composition and types of motifs detected in these integrated networks indicate that such networks are organized in three main bridged modules composed by motifs in which edges are all the same type. The connecting bridges are composed by motifs in which the types of edges are diferent