Modularity detection in protein-protein interaction networks

BACKGROUND: Many recent studies have investigated modularity in biological networks, and its role in functional and structural characterization of constituent biomolecules. A technique that has shown considerable promise in the domain of modularity detection is the Newman and Girvan (NG) algorithm, which relies on the number of shortest-paths across pairs of vertices in the network traversing a given edge, referred to as the betweenness of that edge. The edge with the highest betweenness is iteratively eliminated from the network, with the betweenness of the remaining edges recalculated in every iteration. This generates a complete dendrogram, from which modules are extracted by applying a quality metric called modularity denoted by Q. This exhaustive computation can be prohibitively expensive for large networks such as Protein-Protein Interaction Networks. In this paper, we present a novel optimization to the modularity detection algorithm, in terms of an efficient termination criterion based on a target edge betweenness value, using which the process of iterative edge removal may be terminated. RESULTS: We validate the robustness of our approach by applying our algorithm on real-world protein-protein interaction networks of Yeast, C.Elegans and Drosophila, and demonstrate that our algorithm consistently has significant computational gains in terms of reduced runtime, when compared to the NG algorithm. Furthermore, our algorithm produces modules comparable to those from the NG algorithm, qualitatively and quantitatively. We illustrate this using comparison metrics such as module distribution, module membership cardinality, modularity Q, and Jaccard Similarity Coefficient. CONCLUSIONS: We have presented an optimized approach for efficient modularity detection in networks. The intuition driving our approach is the extraction of holistic measures of centrality from graphs, which are representative of inherent modular structure of the underlying network, and the application of those measures to efficiently guide the modularity detection process. We have empirically evaluated our approach in the specific context of real-world large scale biological networks, and have demonstrated significant savings in computational time while maintaining comparable quality of detected modules

A human MAP kinase interactome.

Mitogen-activated protein kinase (MAPK) pathways form the backbone of signal transduction in the mammalian cell. Here we applied a systematic experimental and computational approach to map 2,269 interactions between human MAPK-related proteins and other cellular machinery and to assemble these data into functional modules. Multiple lines of evidence including conservation with yeast supported a core network of 641 interactions. Using small interfering RNA knockdowns, we observed that approximately one-third of MAPK-interacting proteins modulated MAPK-mediated signaling. We uncovered the Na-H exchanger NHE1 as a potential MAPK scaffold, found links between HSP90 chaperones and MAPK pathways and identified MUC12 as the human analog to the yeast signaling mucin Msb2. This study makes available a large resource of MAPK interactions and clone libraries, and it illustrates a methodology for probing signaling networks based on functional refinement of experimentally derived protein-interaction maps

Systems analysis of model organisms in the study of human disease phenotypes

Complex phenotypes are distinguished by the interplay of multiple interacting molecules and pathways. Effective study of these phenotypes requires a comprehensive approach utilizing unbiased, genome-scale datasets, including transcriptomics, proteomics and genome sequencing. These datasets can be computationally analyzed to identify known pathways and processes likely to contribute to the phenotype and can be integrated to produce models and make testable predictions. The latter analyses are aided by incorporation of proteome-wide protein-protein interaction data, which can be represented as a network and which may permit the identification of novel functional modules that contribute to the pathogenesis or physiology of the complex phenotype. I used a systems approach to study two complex phenotypes in animal models of the human conditions. In Chapter 2, I looked at rhesus macaques suffering from SIV encephalopathy (SIVE), a model for human HIV-Associated Dementia (HAD). Previous work using a human microarray had identified significant upregulation of inflammatory molecules in monkeys suffering from SIVE but little significant gene downregulation. I integrated gene expression data obtained using a newly available rhesus- specific microarray with a large human protein-protein interaction network I constructed from multiple sources, and then applied a module-finding algorithm to identify modules that discriminated between control and SIVE monkeys. I identified EGR1, which plays a role in memory and learning, as a candidate gene and further work led to a model linking infection-associated downregulation of EGR1 to the cognition deficits seen in HAD. In Chapters 3, 4, and 5, I investigated hypoxia tolerance in Drosophila melanogaster that had been adapted to 4% O2 over generations of selection at progressively lower oxygen tension. Hypoxia contributes to the morbidity and mortality of several important human diseases, including myocardial infarction and stroke, and plays a role in the chemo- and radio-resistance of solid tumors. Understanding mechanisms of hypoxia tolerance may help design new therapeutic approaches to these diseases. In Chapter 3, I analyzed the genome sequences of control and hypoxia- tolerant flies, and in Chapter 4, I analyzed gene expression data. Polymorphisms and gene expression changes identified in the hypoxia-tolerant flies both pointed to involvement of the Wnt signaling pathways in acquisition of hypoxia tolerance. In Chapter 5, I confirmed Wnt signaling involvement through experimental studies of Wnt pathway gene overexpression and knockdow

Reduction in T Cell Apoptosis in Patients with HIV Disease Following Antiretroviral Therapy

Patients with HIV infection manifest increased T lymphocyte apoptosis. This study investigated the influence of antiretroviral therapy (ART) upon lymphocyte apoptosis in 23 HIV-infected adults naive to protease inhibitors. Patients were enrolled in a treatment trial consisting of Nelfinavir (NFV), d4T, or NFV + d4T for 24 weeks, followed by triple therapy (NFV + reverse transcriptase inhibitors) for an additional 24 weeks. Spontaneous T cell apoptosis in cultured PBMC decreased by 23.67 ± 18.2% (P < 0.006) at 48 weeks and plasma HIV RNA decreased by 1.79 ± 0.59 log10 RNA copies/ml (P < 0.001). The absolute decrease and slope of T cell apoptosis correlated with plasma virus load and with activated CD8 T cells and was inversely correlated with CD4 T cells. We conclude that reduction in chronic antigenic stimulation and the absence of cellular signals elicited by viral products contribute to the rescue of T lymphocytes from apoptosis, which facilitates immunologic recovery in ART-treated patients

Wnt Pathway Activation Increases Hypoxia Tolerance during Development

<div><p>Adaptation to hypoxia, defined as a condition of inadequate oxygen supply, has enabled humans to successfully colonize high altitude regions. The mechanisms attempted by organisms to cope with short-term hypoxia include increased ATP production via anaerobic respiration and stabilization of Hypoxia Inducible Factor 1α (HIF-1α). However, less is known about the means through which populations adapt to chronic hypoxia during the process of development within a life time or over generations. Here we show that signaling via the highly conserved Wnt pathway impacts the ability of <i>Drosophila melanogaster</i> to complete its life cycle under hypoxia. We identify this pathway through analyses of genome sequencing and gene expression of a <i>Drosophila melanogaster</i> population adapted over >180 generations to tolerate a concentration of 3.5–4% O₂ in air. We then show that genetic activation of the Wnt canonical pathway leads to increased rates of adult eclosion in low O₂. Our results indicate that a previously unsuspected major developmental pathway, Wnt, plays a significant role in hypoxia tolerance.</p></div