Topological and functional properties of the small GTPases protein interaction network

The ras-related protein RAB22A interacts with hypoxia-inducible factor 1-alpha (HIF-1α) in MDA-MB-231 breast cancer cells in hypoxia

BACKGROUND

Recent studies suggest that hypoxia-inducible factor 1-alpha (HIF-1α) and the small GTPase protein Ras-related protein Rab-22 A (RAB22A) may be colocalized in the cytoplasm and that as a conequence they may enhance the formation of microvesicles in breast cancer cells under hypoxia. Therefore, we sought to determine whether these two proteins are present in intracellular complexes in breast carcinoma cells.

METHODS AND RESULTS

Evaluation using molecular docking indicated that HIF-1α and RAB22A interact with each other. Co-immunoprecipitation of endogenous or ectopically expressed HIF-1α and RAB22A proteins in MDA-MB-231 breast cancer cells or HEK-293T cells demonstrated that endogenous HIF-1α and RAB22A can form an intracellular complex; however, transiently expressed HIF-1α and RAB22A failed to interact. Investigating RAB22A and HIF-1α interactions in various cancer cell lines under hypoxia may shed light on their roles in cancer cell survival and progression through regulation of intracellular trafficking by HIF-1α under hypoxic conditions.

CONCLUSIONS

Our study is the first to reveal the potential involvement of HIF-1α in intracellular trafficking through physical interactions with the small GTPase protein RAB22A. We discuss the implications of our work on the role of exosomes and microvesicles in tumor invasiveness.

System-level protein interaction network analysis and molecular dynamics study reveal interaction of ferulic acid with PTGS2 as a natural radioprotector

Ferulic acid is a crucial bioactive component of broccoli, wheat, and rice bran and is also an essential natural product that has undergone significant research. Ferulic acid's precise mode of action and effect on system-level protein networks have not been thoroughly investigated. An interactome was built using the STRING database and Cytoscape tools, utilizing 788 key proteins collected from PubMed literature to identify the ferulic acid-governed regulatory action on protein interaction network (PIN). The scale-free biological network of ferulic acid-rewired PIN is highly interconnected. We discovered 15 sub-modules using the MCODE tool for sub-modulization analysis and 153 enriched signaling pathways. Further, functional enrichment of top bottleneck proteins revealed the FoxO signaling pathway involved in enhancing cellular defense against oxidative stress. The selection of the critical regulatory proteins of the ferulic acid-rewired PIN was completed by performing analyses of topological characteristics such as GO term/pathways analysis, degree, bottleneck, molecular docking, and dynamics investigations. The current research derives a precise molecular mechanism for ferulic acid's action on the body. This in-depth in silico model would aid in understanding how ferulic acid origins its antioxidant and scavenging properties in the human body.Communicated by Ramaswamy H. Sarma.

Topological and system-level protein interaction network (PIN) analyses to deduce molecular mechanism of curcumin

Curcumin is an important bioactive component of turmeric and also one of the important natural products, which has been investigated extensively. The precise mode of action of curcumin and its impact on system level protein networks are still not well studied. To identify the curcumin governed regulatory action on protein interaction network (PIN), an interectome was created based on 788 key proteins, extracted from PubMed literatures, and constructed by using STRING and Cytoscape programs. The PIN rewired by curcumin was a scale-free, extremely linked biological system. MCODE plug-in was used for sub-modulization analysis, wherein we identified 25 modules; ClueGo plug-in was used for the pathway’s enrichment analysis, wherein 37 enriched signalling pathways were obtained. Most of them were associated with human diseases groups, particularly carcinogenesis, inflammation, and infectious diseases. Finally, the analysis of topological characteristic like bottleneck, degree, GO term/pathways analysis, bio-kinetics simulation, molecular docking, and dynamics studies were performed for the selection of key regulatory proteins of curcumin-rewired PIN. The current findings deduce a precise molecular mechanism that curcumin might exert in the system. This comprehensive in-silico study will help to understand how curcumin induces its anti-cancerous, anti-inflammatory, and anti-microbial effects in the human body.

Targeted Quantitative Proteomics Revealed Arsenite-induced Proteasomal Degradation of RhoB in Fibroblast Cells

Arsenic is a toxicant widely present in the environment. Previous epidemiological and animal studies support that arsenic exposure is associated with elevated incidences of lung and skin cancers. Therefore, it is important to understand the molecular mechanisms through which arsenite initiates malignant transformation of lung and skin tissues. Ras superfamily of small GTPases assumes a crucial role in many cellular processes including transcription, protein synthesis, and trafficking. In addition, small GTPase signaling is known to be altered in many types of cancer. By employing a multiple-reaction monitoring (MRM)-based targeted proteomic method, we found that the protein level of RhoB was substantially decreased in IMR90 human lung fibroblast cells upon a 12-h exposure to 5 μM NaAsO2. In addition, the protein level of ectopically expressed RhoB was found to decline in a dose-dependent manner upon arsenite exposure in HEK293T, HeLa, and GM00637 cells as well as that of endogenous RhoB protein in IMR90 cells. Moreover, the arsenite-elicited down-regulation of RhoB was found to arise from enhanced proteasomal degradation. Taken together, we demonstrated, for the first time, that exposure to arsenite could attenuate the protein expression of RhoB through proteasomal degradation.

Novel Prognostic Markers in Triple-Negative Breast Cancer Discovered by MALDI-Mass Spectrometry Imaging

There are no widely-accepted prognostic markers currently available to predict outcomes in patients with triple-negative breast cancer (TNBC), and no targeted therapies with confirmed benefit. We have used MALDI mass spectrometry imaging (MSI) of tryptic peptides to compare regions of cancer and benign tissue in 10 formalin-fixed, paraffin-embedded sections of TNBC tumors. Proteins were identified by reference to a peptide library constructed by LC-MALDI-MS/MS analyses of the same tissues. The prognostic significance of proteins that distinguished between cancer and benign regions was estimated by Kaplan-Meier analysis of their gene expression from public databases. Among peptides that distinguished between cancer and benign tissue in at least 3 tissues with a ROC area under the curve >0.7, 14 represented proteins identified from the reference library, including proteins not previously associated with breast cancer. Initial network analysis using the STRING database showed no obvious functional relationships except among collagen subunits COL1A1, COL1A2, and COL63A, but manual curation, including the addition of EGFR to the analysis, revealed a unique network connecting 10 of the 14 proteins. Kaplan-Meier survival analysis to examine the relationship between tumor expression of genes encoding the 14 proteins, and recurrence-free survival (RFS) in patients with basal-like TNBC showed that, compared to low expression, high expression of nine of the genes was associated with significantly worse RFS, most with hazard ratios >2. In contrast, in estrogen receptor-positive tumors, high expression of these genes showed only low, or no, association with worse RFS. These proteins are proposed as putative markers of RFS in TNBC, and some may also be considered as possible targets for future therapies.

Identification of human circadian genes based on time course gene expression profiles by using a deep learning method

Circadian genes express periodically in an approximate 24-h period and the identification and study of these genes can provide deep understanding of the circadian control which plays significant roles in human health. Although many circadian gene identification algorithms have been developed, large numbers of false positives and low coverage are still major problems in this field. In this study we constructed a novel computational framework for circadian gene identification using deep neural networks (DNN) - a deep learning algorithm which can represent the raw form of data patterns without imposing assumptions on the expression distribution. Firstly, we transformed time-course gene expression data into categorical-state data to denote the changing trend of gene expression. Two distinct expression patterns emerged after clustering of the state data for circadian genes from our manually created learning dataset. DNN was then applied to discriminate the aperiodic genes and the two subtypes of periodic genes. In order to assess the performance of DNN, four commonly used machine learning methods including k-nearest neighbors, logistic regression, naïve Bayes, and support vector machines were used for comparison. The results show that the DNN model achieves the best balanced precision and recall. Next, we conducted large scale circadian gene detection using the trained DNN model for the remaining transcription profiles. Comparing with JTK_CYCLE and a study performed by Möller-Levet et al. (doi: https://doi.org/10.1073/pnas.1217154110), we identified 1132 novel periodic genes. Through the functional analysis of these novel circadian genes, we found that the GTPase superfamily exhibits distinct circadian expression patterns and may provide a molecular switch of circadian control of the functioning of the immune system in human blood. Our study provides novel insights into both the circadian gene identification field and the study of complex circadian-driven biological control. This article is part of a Special Issue entitled: Accelerating Precision Medicine through Genetic and Genomic Big Data Analysis edited by Yudong Cai & Tao Huang.

Network analysis and cross species comparison of protein-protein interaction networks of human, mouse and rat cytochrome P450 proteins that degrade xenobiotics

Cytochrome P450 (CYP) enzymes that degrade xenobiotics play a critical role in the metabolism and biotransformation of drugs and xenobiotics in humans as well as experimental animal models such as mouse and rat. These proteins function as a network collectively as well as independently. Though there are several reports on the organization, regulation and functionality of various CYP enzymes at the molecular level, the understanding of organization and functionality of these proteins at the holistic level remain unclear. The objective of this study is to understand the organization and functionality of xenobiotic degrading CYP enzymes of human, mouse and rat using network theory approaches and to study species differences that exist among them at the holistic level. For our analysis, a protein-protein interaction (PPI) network for CYP enzymes of human, mouse and rat was constructed using the STRING database. Topology, centrality, modularity and robustness analyses were performed for our predicted CYP PPI networks that were then validated by comparison with randomly generated network models. Network centrality analyses of CYP PPI networks reveal the central/hub proteins in the network. Modular analysis of the CYP PPI networks of human, mouse and rat resulted in functional clusters. These clusters were subjected to ontology and pathway enrichment analysis. The analyses show that the cluster of the human CYP PPI network is enriched with pathways principally related to xenobiotic/drug metabolism. Endo-xenobiotic crosstalk dominated in mouse and rat CYP PPI networks, and they were highly enriched with endogenous metabolic and signaling pathways. Thus, cross-species comparisons and analyses of human, mouse and rat CYP PPI networks gave insights about species differences that existed at the holistic level. More investigations from both reductionist and holistic perspectives can help understand CYP metabolism and species extrapolation in a much better way.

SGK1 affects RAN/RANBP1/RANGAP1 via SP1 to play a critical role in pre-miRNA nuclear export: a new route of epigenomic regulation

The serum- and glucocorticoid-regulated kinase (SGK1) controls cell transformation and tumor progression. SGK1 affects mitotic stability by regulating the expression of RANBP1/RAN. Here, we demonstrate that SGK1 fluctuations indirectly modify the maturation of pre-miRNAs, by modulating the equilibrium of the RAN/RANBP1/RANGAP1 axis, the main regulator of nucleo-cytoplasmic transport. The levels of pre-miRNAs and mature miRNAs were assessed by qRT-PCR, in total extracts and after differential nuclear/cytoplasmic extraction. RANBP1 expression is the limiting step in the regulation of SGK1-SP1 dependent nuclear export. These results were validated in unrelated tumor models and primary human fibroblasts and corroborated in tumor-engrafted nude mice. The levels of pri-miRNAs, DROSHA, DICER and the compartmental distribution of XPO5 were documented. Experiments using RANGTP conformational antibodies confirmed that SGK1, through RANBP1, decreases the level of the GTP-bound state of RAN. This novel mechanism may play a role in the epigenomic regulation of cell physiology and fate.

In silico identification of essential proteins in Corynebacterium pseudotuberculosis based on protein-protein interaction networks

Background

Corynebacterium pseudotuberculosis (Cp) is a gram-positive bacterium that is classified into equi and ovis serovars. The serovar ovis is the etiological agent of caseous lymphadenitis, a chronic infection affecting sheep and goats, causing economic losses due to carcass condemnation and decreased production of meat, wool, and milk. Current diagnosis or treatment protocols are not fully effective and, thus, require further research of Cp pathogenesis.

Results

Here, we mapped known protein-protein interactions (PPI) from various species to nine Cp strains to reconstruct parts of the potential Cp interactome and to identify potentially essential proteins serving as putative drug targets. On average, we predict 16,669 interactions for each of the nine strains (with 15,495 interactions shared among all strains). An in silico sanity check suggests that the potential networks were not formed by spurious interactions but have a strong biological bias. With the inferred Cp networks we identify 181 essential proteins, among which 41 are non-host homologous.

Conclusions

The list of candidate interactions of the Cp strains lay the basis for developing novel hypotheses and designing according wet-lab studies. The non-host homologous essential proteins are attractive targets for therapeutic and diagnostic proposes. They allow for searching of small molecule inhibitors of binding interactions enabling modern drug discovery. Overall, the predicted Cp PPI networks form a valuable and versatile tool for researchers interested in Corynebacterium pseudotuberculosis.

Electronic supplementary material

The online version of this article (doi:10.1186/s12918-016-0346-4) contains supplementary material, which is available to authorized users.

Preclinical model in HCC: the SGK1 kinase inhibitor SI113 blocks tumor progression in vitro and in vivo and synergizes with radiotherapy

The SGK1 kinase is pivotal in signal transduction pathways operating in cell transformation and tumor progression. Here, we characterize in depth a novel potent and selective pyrazolo[3,4-d]pyrimidine-based SGK1 inhibitor. This compound, named SI113, active in vitro in the sub-micromolar range, inhibits SGK1-dependent signaling in cell lines in a dose- and time-dependent manner. We recently showed that SI113 slows down tumor growth and induces cell death in colon carcinoma cells, when used in monotherapy or in combination with paclitaxel. We now demonstrate for the first time that SI113 inhibits tumour growth in hepatocarcinoma models in vitro and in vivo. SI113-dependent tumor inhibition is dose- and time-dependent. In vitro and in vivo SI113-dependent SGK1 inhibition determined a dramatic increase in apoptosis/necrosis, inhibited cell proliferation and altered the cell cycle profile of treated cells. Proteome-wide biochemical studies confirmed that SI113 down-regulates the abundance of proteins downstream of SGK1 with established roles in neoplastic transformation, e.g. MDM2, NDRG1 and RAN network members. Consistent with knock-down and over-expressing cellular models for SGK1, SI113 potentiated and synergized with radiotherapy in tumor killing. No short-term toxicity was observed in treated animals during in vivo SI113 administration. These data show that direct SGK1 inhibition can be effective in hepatic cancer therapy, either alone or in combination with radiotherapy.

Systematic network assessment of the carcinogenic activities of cadmium

Cadmium has been defined as type I carcinogen for humans, but the underlying mechanisms of its carcinogenic activity and its influence on protein-protein interactions in cells are not fully elucidated. The aim of the current study was to evaluate, systematically, the carcinogenic activity of cadmium with systems biology approaches. From a literature search of 209 studies that performed with cellular models, 208 proteins influenced by cadmium exposure were identified. All of these were assessed by Western blotting and were recognized as key nodes in network analyses. The protein-protein functional interaction networks were constructed with NetBox software and visualized with Cytoscape software. These cadmium-rewired genes were used to construct a scale-free, highly connected biological protein interaction network with 850 nodes and 8770 edges. Of the network, nine key modules were identified and 60 key signaling pathways, including the estrogen, RAS, PI3K-Akt, NF-κB, HIF-1α, Jak-STAT, and TGF-β signaling pathways, were significantly enriched. With breast cancer, colorectal and prostate cancer cellular models, we validated the key node genes in the network that had been previously reported or inferred form the network by Western blotting methods, including STAT3, JNK, p38, SMAD2/3, P65, AKT1, and HIF-1α. These results suggested the established network was robust and provided a systematic view of the carcinogenic activities of cadmium in human.

A Systematic Analysis of Candidate Genes Associated with Nicotine Addiction

Nicotine, as the major psychoactive component of tobacco, has broad physiological effects within the central nervous system, but our understanding of the molecular mechanism underlying its neuronal effects remains incomplete. In this study, we performed a systematic analysis on a set of nicotine addiction-related genes to explore their characteristics at network levels. We found that NAGenes tended to have a more moderate degree and weaker clustering coefficient and to be less central in the network compared to alcohol addiction-related genes or cancer genes. Further, clustering of these genes resulted in six clusters with themes in synaptic transmission, signal transduction, metabolic process, and apoptosis, which provided an intuitional view on the major molecular functions of the genes. Moreover, functional enrichment analysis revealed that neurodevelopment, neurotransmission activity, and metabolism related biological processes were involved in nicotine addiction. In summary, by analyzing the overall characteristics of the nicotine addiction related genes, this study provided valuable information for understanding the molecular mechanisms underlying nicotine addiction.

Topological, functional, and dynamic properties of the protein interaction networks rewired by benzo(a)pyrene

Benzo(a)pyrene is a common environmental and foodborne pollutant that has been identified as a human carcinogen. Although the carcinogenicity of benzo(a)pyrene has been extensively reported, its precise molecular mechanisms and the influence on system-level protein networks are not well understood. To investigate the system-level influence of benzo(a)pyrene on protein interactions and regulatory networks, a benzo(a)pyrene-rewired protein interaction network was constructed based on 769 key proteins derived from more than 500 literature reports. The protein interaction network rewired by benzo(a)pyrene was a scale-free, highly-connected biological system. Ten modules were identified, and 25 signaling pathways were enriched, most of which belong to the human diseases category, especially cancer and infectious disease. In addition, two lung-specific and two liver-specific pathways were identified. Three pathways were specific in short and medium-term networks (<48h), and five pathways were enriched only in the medium-term network (6h-48h). Finally, the expression of linker genes in the network was validated by Western blotting. These findings establish the overall, tissue- and time-specific benzo(a)pyrene-rewired protein interaction networks and provide insights into the biological effects and molecular mechanisms of action of benzo(a)pyrene.

E-cadherin interactome complexity and robustness resolved by quantitative proteomics

E-cadherin-mediated cell-cell adhesion and signaling plays an essential role in development and maintenance of healthy epithelial tissues. Adhesiveness mediated by E-cadherin is conferred by its extracellular cadherin domains and is regulated by an assembly of intracellular adaptors and enzymes associated with its cytoplasmic tail. We used proximity biotinylation and quantitative proteomics to identify 561 proteins in the vicinity of the cytoplasmic tail of E-cadherin. In addition, we used proteomics to identify proteins associated with E-cadherin-containing adhesion plaques from a cell-glass interface, which enabled the assignment of cellular localization to putative E-cadherin-interacting proteins. Moreover, by tagging identified proteins with GFP (green fluorescent protein), we determined the subcellular localization of 83 putative E-cadherin-proximal proteins and identified 24 proteins that were previously uncharacterized as part of adherens junctions. We constructed and characterized a comprehensive E-cadherin interaction network of 79 published and 394 previously uncharacterized proteins using a structure-informed database of protein-protein interactions. Finally, we found that calcium chelation, which disrupts the interaction of the extracellular E-cadherin domains, did not disrupt most intracellular protein interactions with E-cadherin, suggesting that the E-cadherin intracellular interactome is predominantly independent of cell-cell adhesion.

RhoA/ROCK downregulates FPR2-mediated NADPH oxidase activation in mouse bone marrow granulocytes

Polymorphonuclear neutrophils (PMNs) express the high and low affinity receptors to formylated peptides (mFPR1 and mFPR2 in mice, accordingly). RhoA/ROCK (Rho activated kinase) pathway is crucial for cell motility and oxidase activity regulated via FPRs. There are contradictory data on RhoA-mediated regulation of NADPH oxidase activity in phagocytes. We have shown divergent Rho GTPases signaling via mFPR1 and mFPR2 to NADPH oxidase in PMNs from inflammatory site. The present study was aimed to find out the role of RhoA/ROCK in the respiratory burst activated via mFPR1 and mFPR2 in the bone marrow PMNs. Different kinetics of RhoA activation were detected with 0.1μM fMLF and 1μM WKYMVM operating via mFPR1 and mFPR2, accordingly. RhoA was translocated in fMLF-activated cells towards the cell center and juxtamembrane space versus uniform allocation in the resting cells. Specific inhibition of RhoA by CT04, Rho inhibitor I, weakly depressed the respiratory burst induced via mFPR1, but significantly increased the one induced via mFPR2. Inhibition of ROCK, the main effector of RhoA, by Y27632 led to the same effect on the respiratory burst. Regulation of mFPR2-induced respiratory response by ROCK was impossible under the cytoskeleton disruption by cytochalasin D, whereas it persisted in the case of mFPR1 activation. Thus we suggest RhoA to be one of the regulatory and signal transduction components in the respiratory burst through FPRs in the mouse bone marrow PMNs. Both mFPR1 and mFPR2 binding with a ligand trigger the activation of RhoA. FPR1 signaling through RhoA/ROCK increases NADPH-oxidase activity. But in FPR2 action RhoA/ROCK together with cytoskeleton-linked systems down-regulates NADPH-oxidase. This mechanism could restrain the reactive oxygen species dependent damage of own tissues during the chemotaxis of PMNs and in the resting cells.

The G protein-coupled receptor heterodimer network (GPCR-HetNet) and its hub components

G protein-coupled receptors (GPCRs) oligomerization has emerged as a vital characteristic of receptor structure. Substantial experimental evidence supports the existence of GPCR-GPCR interactions in a coordinated and cooperative manner. However, despite the current development of experimental techniques for large-scale detection of GPCR heteromers, in order to understand their connectivity it is necessary to develop novel tools to study the global heteroreceptor networks. To provide insight into the overall topology of the GPCR heteromers and identify key players, a collective interaction network was constructed. Experimental interaction data for each of the individual human GPCR protomers was obtained manually from the STRING and SCOPUS databases. The interaction data were used to build and analyze the network using Cytoscape software. The network was treated as undirected throughout the study. It is comprised of 156 nodes, 260 edges and has a scale-free topology. Connectivity analysis reveals a significant dominance of intrafamily versus interfamily connections. Most of the receptors within the network are linked to each other by a small number of edges. DRD2, OPRM, ADRB2, AA2AR, AA1R, OPRK, OPRD and GHSR are identified as hubs. In a network representation 10 modules/clusters also appear as a highly interconnected group of nodes. Information on this GPCR network can improve our understanding of molecular integration. GPCR-HetNet has been implemented in Java and is freely available at http://www.iiia.csic.es/~ismel/GPCR-Nets/index.html.

Identification of candidate miRNA biomarkers from miRNA regulatory network with application to prostate cancer

Background

MicroRNAs (miRNAs) are a class of non-coding regulatory RNAs approximately 22 nucleotides in length that play a role in a wide range of biological processes. Abnormal miRNA function has been implicated in various human cancers including prostate cancer (PCa). Altered miRNA expression may serve as a biomarker for cancer diagnosis and treatment. However, limited data are available on the role of cancer-specific miRNAs. Integrative computational bioinformatics approaches are effective for the detection of potential outlier miRNAs in cancer.

Methods

The human miRNA-mRNA target network was reconstructed by integrating multiple miRNA-mRNA interaction datasets. Paired miRNA and mRNA expression profiling data in PCa versus benign prostate tissue samples were used as another source of information. These datasets were analyzed with an integrated bioinformatics framework to identify potential PCa miRNA signatures. In vitro q-PCR experiments and further systematic analysis were used to validate these prediction results.

Results

Using this bioinformatics framework, we identified 39 miRNAs as potential PCa miRNA signatures. Among these miRNAs, 20 had previously been identified as PCa aberrant miRNAs by low-throughput methods, and 16 were shown to be deregulated in other cancers. In vitro q-PCR experiments verified the accuracy of these predictions. miR-648 was identified as a novel candidate PCa miRNA biomarker. Further functional and pathway enrichment analysis confirmed the association of the identified miRNAs with PCa progression.

Conclusions

Our analysis revealed the scale-free features of the human miRNA-mRNA interaction network and showed the distinctive topological features of existing cancer miRNA biomarkers from previously published studies. A novel cancer miRNA biomarker prediction framework was designed based on these observations and applied to prostate cancer study. This method could be applied for miRNA biomarker prediction in other cancers.

IQGAP1 is a key node within the small GTPase network

Coordination of the activity of multiple small GTPases is required for the regulation of many physiological processes, including cell migration. There are now several examples of functional interplay between small GTPase pairs, but the mechanisms that control GTPase activity in time and space are only partially understood. Here, we build on the hypothesis that small GTPases are part of a large, integrated network and propose that key proteins within this network integrate multiple signaling events and coordinate multiple small GTPase activities. Specifically, we identify the scaffolding protein IQGAP1 as a master regulator of multiple small GTPases, including Cdc42, Rac1, Rap1, and RhoA. In addition, we demonstrate that IQGAP1 promotes Arf6 activation downstream of β1 integrin engagement. Furthermore, following literature-curated searches and recent mass spectrometric analysis of IQGAP1-binding partners, we report that IQGAP1 recruits other small GTPases, including RhoC, Rac2, M-Ras, RhoQ, Rab10, and Rab5, small GTPase regulators, including Tiam1, RacGAP1, srGAP2 and HERC1, and small GTPase effectors, including PAK6, N-WASP, several sub-units of the Arp2/3 complex and the formin mDia1. Therefore, we propose that IQGAP1 acts as a small GTPase scaffolding platform within the small GTPase network, and recruits and/or regulates small GTPases, small GTPase regulators and effectors to orchestrate cell behavior. Finally, to identify other putative key regulators of small GTPase crosstalk, we have assembled a small GTPase network using protein-protein interaction databases.

Sharp bounds and normalization of Wiener-type indices

Complex networks abound in physical, biological and social sciences. Quantifying a network's topological structure facilitates network exploration and analysis, and network comparison, clustering and classification. A number of Wiener type indices have recently been incorporated as distance-based descriptors of complex networks, such as the R package QuACN. Wiener type indices are known to depend both on the network's number of nodes and topology. To apply these indices to measure similarity of networks of different numbers of nodes, normalization of these indices is needed to correct the effect of the number of nodes in a network. This paper aims to fill this gap. Moreover, we introduce an f-Wiener index of network G, denoted by Wf(G). This notion generalizes the Wiener index to a very wide class of Wiener type indices including all known Wiener type indices. We identify the maximum and minimum of Wf(G) over a set of networks with n nodes. We then introduce our normalized-version of f-Wiener index. The normalized f-Wiener indices were demonstrated, in a number of experiments, to improve significantly the hierarchical clustering over the non-normalized counterparts.

Small GTPases of the Ras superfamily regulate intestinal epithelial homeostasis and barrier function via common and unique mechanisms

The intestinal epithelium forms a stable barrier protecting underlying tissues from pathogens in the gut lumen. This is achieved by specialized integral membrane structures such as tight and adherens junctions that connect neighboring cells and provide stabilizing links to the cytoskeleton. Junctions are constantly remodeled to respond to extracellular stimuli. Assembly and disassembly of junctions is regulated by interplay of actin remodeling, endocytotic recycling of junctional proteins, and various signaling pathways. Accumulating evidence implicate small G proteins of the Ras superfamily as important signaling molecules for the regulation of epithelial junctions. They function as molecular switches circling between an inactive GDP-bound and an active GTP-bound state. Once activated, they bind different effector molecules to control cellular processes required for correct junction assembly, maintenance and remodelling. Here, we review recent advances in understanding how GTPases of the Rho, Ras, Rab and Arf families contribute to intestinal epithelial homeostasis.

Bioinformatic Analysis of Differential Protein Expression in Calu-3 Cells Exposed to Carbon Nanotubes

Carbon nanomaterials are widely produced and used in industry, medicine and scientific research. To examine the impact of exposure to nanoparticles on human health, the human airway epithelial cell line, Calu-3, was used to evaluate changes in the cellular proteome that could account for alterations in cellular function of airway epithelia after 24 hexposure to 10 μg/mL and 100 ng/mLof two common carbon nanoparticles, single- and multi-wall carbon nanotubes (SWCNT, MWCNT). After exposure to the nanoparticles, label-free quantitative mass spectrometry (LFQMS) was used to study the differential protein expression. Ingenuity Pathway Analysis (IPA) was used to conduct a bioinformaticanalysis of proteins identified in LFQMS. Interestingly, after exposure to ahigh concentration (10 μg/mL; 0.4 μg/cm²) of MWCNT or SWCNT, only 8 and 13 proteins, respectively, exhibited changes in abundance. In contrast, the abundance of hundreds of proteins was altered in response to a low concentration (100 ng/mL; 4 ng/cm²) of either CNT. Of the 281 and 282 proteins that were significantly altered in response to MWCNT or SWCNT respectively, 231 proteins were the same. Bioinformatic analyses found that the proteins in common to both nanotubes occurred within the cellular functions of cell death and survival, cell-to-cell signaling and interaction, cellular assembly and organization, cellular growth and proliferation, infectious disease, molecular transport and protein synthesis. The majority of the protein changes represent a decrease in amount suggesting a general stress response to protect cells. The STRING database was used to analyze the various functional protein networks. Interestingly, some proteins like cadherin 1 (CDH1), signal transducer and activator of transcription 1 (STAT1), junction plakoglobin (JUP), and apoptosis-associated speck-like protein containing a CARD (PYCARD), appear in several functional categories and tend to be in the center of the networks. This central positioning suggests they may play important roles in multiple cellular functions and activities that are altered in response to carbon nanotube exposure.

Roles of rho GTPases in intracellular transport and cellular transformation

Rho family GTPases belong to the Ras GTPase superfamily and transduce intracellular signals known to regulate a variety of cellular processes, including cell polarity, morphogenesis, migration, apoptosis, vesicle trafficking, viral transport and cellular transformation. The three best-characterized Rho family members are Cdc42, RhoA and Rac1. Cdc42 regulates endocytosis, the transport between the endoplasmic reticulum and Golgi apparatus, post-Golgi transport and exocytosis. Cdc42 influences trafficking through interaction with Wiskott-Aldrich syndrome protein (N-WASP) and the Arp2/3 complex, leading to changes in actin dynamics. Rac1 mediates endocytic and exocytic vesicle trafficking by interaction with its effectors, PI3kinase, synaptojanin 2, IQGAP1 and phospholipase D1. RhoA participates in the regulation of endocytosis through controlling its downstream target, Rho kinase. Interestingly, these GTPases play important roles at different stages of viral protein and genome transport in infected host cells. Importantly, dysregulation of Cdc42, Rac1 and RhoA leads to numerous disorders, including malignant transformation. In some cases, hyperactivation of Rho GTPases is required for cellular transformation. In this article, we review a number of findings related to Rho GTPase function in intracellular transport and cellular transformation.