Markov clustering versus affinity propagation for the partitioning of protein interaction graphs

<p>Abstract</p> <p>Background</p> <p>Genome scale data on protein interactions are generally represented as large networks, or graphs, where hundreds or thousands of proteins are linked to one another. Since proteins tend to function in groups, or complexes, an important goal has been to reliably identify protein complexes from these graphs. This task is commonly executed using clustering procedures, which aim at detecting densely connected regions within the interaction graphs. There exists a wealth of clustering algorithms, some of which have been applied to this problem. One of the most successful clustering procedures in this context has been the Markov Cluster algorithm (MCL), which was recently shown to outperform a number of other procedures, some of which were specifically designed for partitioning protein interactions graphs. A novel promising clustering procedure termed Affinity Propagation (AP) was recently shown to be particularly effective, and much faster than other methods for a variety of problems, but has not yet been applied to partition protein interaction graphs.</p> <p>Results</p> <p>In this work we compare the performance of the Affinity Propagation (AP) and Markov Clustering (MCL) procedures. To this end we derive an unweighted network of protein-protein interactions from a set of 408 protein complexes from <it>S. cervisiae </it>hand curated in-house, and evaluate the performance of the two clustering algorithms in recalling the annotated complexes. In doing so the parameter space of each algorithm is sampled in order to select optimal values for these parameters, and the robustness of the algorithms is assessed by quantifying the level of complex recall as interactions are randomly added or removed to the network to simulate noise. To evaluate the performance on a weighted protein interaction graph, we also apply the two algorithms to the consolidated protein interaction network of <it>S. cerevisiae</it>, derived from genome scale purification experiments and to versions of this network in which varying proportions of the links have been randomly shuffled.</p> <p>Conclusion</p> <p>Our analysis shows that the MCL procedure is significantly more tolerant to noise and behaves more robustly than the AP algorithm. The advantage of MCL over AP is dramatic for unweighted protein interaction graphs, as AP displays severe convergence problems on the majority of the unweighted graph versions that we tested, whereas MCL continues to identify meaningful clusters, albeit fewer of them, as the level of noise in the graph increases. MCL thus remains the method of choice for identifying protein complexes from binary interaction networks.</p

Post-Transcriptional Regulation of Cadherin-11 Expression by GSK-3 and β-Catenin in Prostate and Breast Cancer Cells

The cell-cell adhesion molecule cadherin-11 is important in embryogenesis and bone morphogenesis, invasion of cancer cells, lymphangiogenesis, homing of cancer cells to bone, and rheumatoid arthritis. However, very little is known about the regulation of cadherin-11 expression.Here we show that cell density and GSK-3beta regulate cadherin-11 levels in cancer cells. Inactivation of GSK3beta with lithium chloride or the GSK3 inhibitor BIO and GSK3beta knockdown with siRNA repressed cadherin-11 mRNA and protein levels. RNA Polymerase II chromatin immunoprecipitation experiments showed that inhibition of GSK3 does not affect cadherin-11 gene transcription. Although the cadherin-11 3'UTR contains putative microRNA target sites and is regulated by Dicer, its stability is not regulated by GSK3 inhibition or density. Our data show that GSK3beta regulates cadherin-11 expression in two ways: first a beta-catenin-independent regulation of cadherin-11 steady state mRNA levels, and second a beta-catenin-dependent effect on cadherin-11 3'UTR stability and protein translation.Cadherin-11 mRNA and protein levels are regulated by the activity of GSK3beta and a significant degree of this regulation is exerted by the GSK3 target, beta-catenin, at the level of the cadherin-11 3'UTR

Expression analysis of E-cadherin, Slug and GSK3β in invasive ductal carcinoma of breast

<p>Abstract</p> <p>Background</p> <p>Cancer progression is linked to a partially dedifferentiated epithelial cell phenotype. The signaling pathways Wnt, Hedgehog, TGF-β and Notch have been implicated in experimental and developmental epithelial mesenchymal transition (EMT). Recent findings from our laboratory confirm that active Wnt/β-catenin signaling is critically involved in invasive ductal carcinomas (IDCs) of breast.</p> <p>Methods</p> <p>In the current study, we analyzed the expression patterns and relationships between the key Wnt/β-catenin signaling components- E-cadherin, Slug and GSK3β in IDCs of breast.</p> <p>Results</p> <p>Of the 98 IDCs analyzed, 53 (54%) showed loss/or reduced membranous staining of E-cadherin in tumor cells. Nuclear accumulation of Slug was observed in 33 (34%) IDCs examined. Loss or reduced level of cytoplasmic GSK3β expression was observed in 52/98 (53%) cases; while 34/98 (35%) tumors showed nuclear accumulation of GSK3β. Statistical analysis revealed associations of nuclear Slug expression with loss of membranous E-cadherin (p = 0.001); nuclear β-catenin (p = 0.001), and cytoplasmic β-catenin (p = 0.005), suggesting Slug mediated E-cadherin suppression via the activation of Wnt/β-catenin signaling pathway in IDCs. Our study also demonstrated significant correlation between GSK3β nuclear localization and tumor grade (p = 0.02), suggesting its association with tumor progression.</p> <p>Conclusion</p> <p>The present study for the first time provided the clinical evidence in support of Wnt/β-catenin signaling upregulation in IDCs and key components of this pathway - E-cadherin, Slug and GSK3β with β-catenin in implementing EMT in these cells.</p

Twist expression promotes migration and invasion in hepatocellular carcinoma

Background: Twist, a transcription factor of the basic helix-loop-helix class, is reported to regulate cancer metastasis. It is known to induce epithelial-mesenchymal transition (EMT). In this study, we evaluated the expression of twist and its effect on cell migration in hepatocellular carcinoma (HCC). Methods: We examined twist expression using immunohistochemistry in 20 tissue samples of hepatocellular carcinoma, and assessed twist expression in HCC cell lines by RT-PCR and Western blot analysis. Ectopic twist expression was created by introducing a twist construct in the twist-negative HCC cell lines. Endogenous twist expression was blocked by twist siRNA in the twist-positive HCC cell lines. We studied EMT related markers, E-cadherin, Vimentin, and N-cadherin by Western blot analysis. Cell proliferation was measured by MTT assay, and cell migration was measured by in vitro wound healing assay. We used immunofluorescent vinculin staining to visualize focal adhesion. Results: We detected strong and intermediate twist expression in 7 of 20 tumor samples, and no significant twist expression was found in the tumor-free resection margins. In addition, we detected twist expression in HLE, HLF, and SK-Hep1 cells, but not in PLC/RPF/5, HepG2, and Huh7 cells. Ectopic twist-expressing cells demonstrated enhanced cell motility, but twist expression did not affect cell proliferation. Twist expression induced epithelial-mesenchymal transition together with related morphologic changes. Focal adhesion contact was reduced significantly in ectopic twist-expressing cells. Twist-siRNA-treated HLE, HLF, and SK-Hep1 cells demonstrated a reduction in cell migration by 50, 40 and 18%, respectively. Conclusion: Twist induces migratory effect on hepatocellular carcinoma by causing epithelial-mesenchymal transition

Nicotine exposure and transgenerational impact: a prospective study on small regulatory microRNAs

Early developmental stages are highly sensitive to stress and it has been reported that pre-conditioning with tobacco smoking during adolescence predisposes those youngsters to become smokers as adults. However, the molecular mechanisms of nicotine-induced transgenerational consequences are unknown. In this study, we genome-widely investigated the impact of nicotine exposure on small regulatory microRNAs (miRNAs) and its implication on health disorders at a transgenerational aspect. Our results demonstrate that nicotine exposure, even at the low dose, affected the global expression profiles of miRNAs not only in the treated worms (F0 parent generation) but also in two subsequent generations (F1 and F2, children and grandchildren). Some miRNAs were commonly affected by nicotine across two or more generations while others were specific to one. The general miRNA patterns followed a “two-hit� model as a function of nicotine exposure and abstinence. Target prediction and pathway enrichment analyses showed daf-4, daf-1, fos-1, cmk-1, and unc-30 to be potential effectors of nicotine addiction. These genes are involved in physiological states and phenotypes that paralleled previously published nicotine induced behavior. Our study offered new insights and further awareness on the transgenerational effects of nicotine exposed during the vulnerable post-embryonic stages, and identified new biomarkers for nicotine addiction.ECU Open Access Publishing Support Fun

Behavioral and Immune Responses to Infection Require Gαq- RhoA Signaling in C. elegans

Following pathogen infection the hosts' nervous and immune systems react with coordinated responses to the danger. A key question is how the neuronal and immune responses to pathogens are coordinated, are there common signaling pathways used by both responses? Using C. elegans we show that infection by pathogenic strains of M. nematophilum, but not exposure to avirulent strains, triggers behavioral and immune responses both of which require a conserved Gαq-RhoGEF Trio-Rho signaling pathway. Upon infection signaling by the Gαq pathway within cholinergic motorneurons is necessary and sufficient to increase release of the neurotransmitter acetylcholine and increase locomotion rates and these behavioral changes result in C. elegans leaving lawns of M. nematophilum. In the immune response to infection signaling by the Gαq pathway within rectal epithelial cells is necessary and sufficient to cause changes in cell morphology resulting in tail swelling that limits the infection. These Gαq mediated behavioral and immune responses to infection are separate, act in a cell autonomous fashion and activation of this pathway in the appropriate cells can trigger these responses in the absence of infection. Within the rectal epithelium the Gαq signaling pathway cooperates with a Ras signaling pathway to activate a Raf-ERK-MAPK pathway to trigger the cell morphology changes, whereas in motorneurons Gαq signaling triggers behavioral responses independent of Ras signaling. Thus, a conserved Gαq pathway cooperates with cell specific factors in the nervous and immune systems to produce appropriate responses to pathogen. Thus, our data suggests that ligands for Gq coupled receptors are likely to be part of the signals generated in response to M. nematophilum infection

Caenorhabditis elegans BAH-1 Is a DUF23 Protein Expressed in Seam Cells and Required for Microbial Biofilm Binding to the Cuticle

The cuticle of Caenorhabditis elegans, a complex, multi-layered extracellular matrix, is a major interface between the animal and its environment. Biofilms produced by the bacterial genus Yersinia attach to the cuticle of the worm, providing an assay for surface characteristics. A C. elegans gene required for biofilm attachment, bah-1, encodes a protein containing the domain of unknown function DUF23. The DUF23 domain is found in 61 predicted proteins in C. elegans, which can be divided into three distinct phylogenetic clades. bah-1 is expressed in seam cells, which are among the hypodermal cells that synthesize the cuticle, and is regulated by a TGF-β signaling pathway

A Role for SKN-1/Nrf in Pathogen Resistance and Immunosenescence in Caenorhabditis elegans

A proper immune response ensures survival in a hostile environment and promotes longevity. Recent evidence indicates that innate immunity, beyond antimicrobial effectors, also relies on host-defensive mechanisms. The Caenorhabditis elegans transcription factor SKN-1 regulates xenobiotic and oxidative stress responses and contributes to longevity, however, its role in immune defense is unknown. Here we show that SKN-1 is required for C. elegans pathogen resistance against both Gram-negative Pseudomonas aeruginosa and Gram-positive Enterococcus faecalis bacteria. Exposure to P. aeruginosa leads to SKN-1 accumulation in intestinal nuclei and transcriptional activation of two SKN-1 target genes, gcs-1 and gst-4. Both the Toll/IL-1 Receptor domain protein TIR-1 and the p38 MAPK PMK-1 are required for SKN-1 activation by PA14 exposure. We demonstrate an early onset of immunosenescence with a concomitant age-dependent decline in SKN-1-dependent target gene activation, and a requirement of SKN-1 to enhance pathogen resistance in response to longevity-promoting interventions, such as reduced insulin/IGF-like signaling and preconditioning H2O2 treatment. Finally, we find that wdr-23(RNAi)-mediated constitutive SKN-1 activation results in excessive transcription of target genes, confers oxidative stress tolerance, but impairs pathogen resistance. Our findings identify SKN-1 as a novel regulator of innate immunity, suggests its involvement in immunosenescence and provide an important crosstalk between pathogenic stress signaling and the xenobiotic/oxidative stress response

Topology analysis and visualization of Potyvirus protein-protein interaction network

Background: One of the central interests of Virology is the identification of host factors that contribute to virus infection. Despite tremendous efforts, the list of factors identified remains limited. With omics techniques, the focus has changed from identifying and thoroughly characterizing individual host factors to the simultaneous analysis of thousands of interactions, framing them on the context of protein-protein interaction networks and of transcriptional regulatory networks. This new perspective is allowing the identification of direct and indirect viral targets. Such information is available for several members of the Potyviridae family, one of the largest and more important families of plant viruses. Results: After collecting information on virus protein-protein interactions from different potyviruses, we have processed it and used it for inferring a protein-protein interaction network. All proteins are connected into a single network component. Some proteins show a high degree and are highly connected while others are much less connected, with the network showing a significant degree of dissortativeness. We have attempted to integrate this virus protein-protein interaction network into the largest protein-protein interaction network of Arabidopsis thaliana, a susceptible laboratory host. To make the interpretation of data and results easier, we have developed a new approach for visualizing and analyzing the dynamic spread on the host network of the local perturbations induced by viral proteins. We found that local perturbations can reach the entire host protein-protein interaction network, although the efficiency of this spread depends on the particular viral proteins. By comparing the spread dynamics among viral proteins, we found that some proteins spread their effects fast and efficiently by attacking hubs in the host network while other proteins exert more local effects. Conclusions: Our findings confirm that potyvirus protein-protein interaction networks are highly connected, with some proteins playing the role of hubs. Several topological parameters depend linearly on the protein degree. Some viral proteins focus their effect in only host hubs while others diversify its effect among several proteins at the first step. Future new data will help to refine our model and to improve our predictions.This work was supported by the Spanish Ministerio de Economia y Competitividad grants BFU2012-30805 (to SFE), DPI2011-28112-C04-02 (to AF) and DPI2011-28112-C04-01 (to JP). The first two authors are recipients of fellowships from the Spanish Ministerio de Economia y Competitividad: BES-2012-053772 (to GB) and BES-2012-057812 (to AF-F).Bosque, G.; Folch Fortuny, A.; Picó Marco, JA.; Ferrer, A.; Elena Fito, SF. (2014). Topology analysis and visualization of Potyvirus protein-protein interaction network. 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Characterization of the SNAG and SLUG Domains of Snail2 in the Repression of E-Cadherin and EMT Induction: Modulation by Serine 4 Phosphorylation

Snail1 and Snail2, two highly related members of the Snail superfamily, are direct transcriptional repressors of E-cadherin and EMT inducers. Previous comparative gene profiling analyses have revealed important differences in the gene expression pattern regulated by Snail1 and Snail2, indicating functional differences between both factors. The molecular mechanism of Snail1-mediated repression has been elucidated to some extent, but very little is presently known on the repression mediated by Snail2. In the present work, we report on the characterization of Snail2 repression of E-cadherin and its regulation by phosphorylation. Both the N-terminal SNAG and the central SLUG domains of Snail2 are required for efficient repression of the E-cadherin promoter. The co-repressor NCoR interacts with Snail2 through the SNAG domain, while CtBP1 is recruited through the SLUG domain. Interestingly, the SNAG domain is absolutely required for EMT induction while the SLUG domain plays a negative modulation of Snail2 mediated EMT. Additionally, we identify here novel in vivo phosphorylation sites at serine 4 and serine 88 of Snail2 and demonstrate the functional implication of serine 4 in the regulation of Snail2-mediated repressor activity of E-cadherin and in Snail2 induction of EMT