Identifying Pathway Proteins in Networks using Convergence

One of the key goals of systems biology concerns the analysis of experimental biological data available to the scientific public. New technologies are rapidly developed to observe and report whole-scale biological phenomena; however, few methods exist with the ability to produce specific, testable hypotheses from this noisy ‘big’ data. In this work, we propose an approach that combines the power of data-driven network theory along with knowledge-based ontology to tackle this problem. Network models are especially powerful due to their ability to display elements of interest and their relationships as internetwork structures. Additionally, ontological data actually supplements the confidence of relationships within the model without clouding critical structure identification. As such, we postulate that given a (gene/protein) marker set of interest, we can systematically identify the core of their interactions (if they are indeed working together toward a biological function), via elimination of original markers and addition of additional necessary markers. This concept, which we refer to as “convergence,” harnesses the idea of “guilt-by-association” and recursion to identify whether a core of relationships exists between markers. In this study, we test graph theoretic concepts such as shortest-path, k-Nearest- Neighbor and clustering) to identify cores iteratively in data- and knowledge-based networks in the canonical yeast Pheromone Mating Response pathway. Additionally, we provide results for convergence application in virus infection, hearing loss, and Parkinson’s disease. Our results indicate that if a marker set has common discrete function, this approach is able to identify that function, its interacting markers, and any new elements necessary to complete the structural core of that function. The result below find that the shortest path function is the best approach of those used, finding small target sets that contain a majority or all of the markers in the gold standard pathway. The power of this approach lies in its ability to be used in investigative studies to inform decisions concerning target selection

Arousal frequency is associated with increased fatigue in obstructive sleep apnea

Fatigue is an important and often underemphasized symptom in patients with obstructive sleep apnea (OSA). Sleep fragmentation, i.e., arousals and disruptions in sleep architecture, is common in patients with OSA and may potentially contribute to their fatigue. We hypothesized that arousal frequency and changes in sleep architecture contribute to the fatigue experienced by patients with OSA. Seventy-three patients with diagnosed but untreated OSA (AHI ≥ 15) were enrolled in this study. A baseline polysomnogram was obtained, and fatigue was measured with the Multidimensional Fatigue Symptom Inventory-short form (MFSI-sf). We evaluated the association between fatigue and arousals and various polysomongraphic variables, including sleep stages and sleep efficiency. Significant correlations between MFSI-sf subscale scores and various arousal indices were noted. Emotional fatigue scores were associated with total arousal index (r = 0.416, p = .021), respiratory movement arousal index (r = 0.346, p = .025), and spontaneous movement arousal index (r = 0.378, p = .025). Physical fatigue scores were associated with total arousal index (r = 0.360, p = .033) and respiratory movement arousal index (r = 0.304, p = .040). Percent of stage 1 sleep and REM sleep were also associated with physical and emotional fatigue scores. Hierarchal linear regression analysis demonstrated that emotional fatigue scores were independently associated with spontaneous movement arousals after controlling for age, body mass index, depression, and sleep apnea severity. These findings suggest that arousals may contribute to the fatigue seen in patients with OSA

Poly(ADP-ribose) polymerase family member 14 (PARP14) is a novel effector of the JNK2-dependent pro-survival signal in multiple myeloma

Copyright @ 2013 Macmillan Publishers Limited. This is the author's accepted manuscript. The final published article is available from the link below.Regulation of cell survival is a key part of the pathogenesis of multiple myeloma (MM). Jun N-terminal kinase (JNK) signaling has been implicated in MM pathogenesis, but its function is unclear. To elucidate the role of JNK in MM, we evaluated the specific functions of the two major JNK proteins, JNK1 and JNK2. We show here that JNK2 is constitutively activated in a panel of MM cell lines and primary tumors. Using loss-of-function studies, we demonstrate that JNK2 is required for the survival of myeloma cells and constitutively suppresses JNK1-mediated apoptosis by affecting expression of poly(ADP-ribose) polymerase (PARP)14, a key regulator of B-cell survival. Strikingly, we found that PARP14 is highly expressed in myeloma plasma cells and associated with disease progression and poor survival. Overexpression of PARP14 completely rescued myeloma cells from apoptosis induced by JNK2 knockdown, indicating that PARP14 is critically involved in JNK2-dependent survival. Mechanistically, PARP14 was found to promote the survival of myeloma cells by binding and inhibiting JNK1. Moreover, inhibition of PARP14 enhances the sensitization of MM cells to anti-myeloma agents. Our findings reveal a novel regulatory pathway in myeloma cells through which JNK2 signals cell survival via PARP14, and identify PARP14 as a potential therapeutic target in myeloma.Kay Kendall Leukemia Fund, NIH, Cancer Research UK, Italian Association for Cancer Research and the Foundation for Liver Research

The mating-specific Gα interacts with a kinesin-14 and regulates pheromone-induced nuclear migration in budding yeast

As a budding yeast cell elongates toward its mating partner, cytoplasmic microtubules connect the nucleus to the cell cortex at the growth tip. The Kar3 kinesin-like motor protein is then thought to stimulate plus-end depolymerization of these microtubules, thus drawing the nucleus closer to the site where cell fusion and karyogamy will occur. Here, we show that pheromone stimulates a microtubule-independent interaction between Kar3 and the mating-specific Gα protein Gpa1 and that Gpa1 affects both microtubule orientation and cortical contact. The membrane localization of Gpa1 was found to polarize early in the mating response, at about the same time that the microtubules begin to attach to the incipient growth site. In the absence of Gpa1, microtubules lose contact with the cortex upon shrinking and Kar3 is improperly localized, suggesting that Gpa1 is a cortical anchor for Kar3. We infer that Gpa1 serves as a positional determinant for Kar3-bound microtubule plus ends during mating. © 2009 by The American Society for Cell Biology

High-throughput, quantitative analyses of genetic interactions in E. coli.

Large-scale genetic interaction studies provide the basis for defining gene function and pathway architecture. Recent advances in the ability to generate double mutants en masse in Saccharomyces cerevisiae have dramatically accelerated the acquisition of genetic interaction information and the biological inferences that follow. Here we describe a method based on F factor-driven conjugation, which allows for high-throughput generation of double mutants in Escherichia coli. This method, termed genetic interaction analysis technology for E. coli (GIANT-coli), permits us to systematically generate and array double-mutant cells on solid media in high-density arrays. We show that colony size provides a robust and quantitative output of cellular fitness and that GIANT-coli can recapitulate known synthetic interactions and identify previously unidentified negative (synthetic sickness or lethality) and positive (suppressive or epistatic) relationships. Finally, we describe a complementary strategy for genome-wide suppressor-mutant identification. Together, these methods permit rapid, large-scale genetic interaction studies in E. coli

Computational Prediction and Experimental Verification of New MAP Kinase Docking Sites and Substrates Including Gli Transcription Factors

In order to fully understand protein kinase networks, new methods are needed to identify regulators and substrates of kinases, especially for weakly expressed proteins. Here we have developed a hybrid computational search algorithm that combines machine learning and expert knowledge to identify kinase docking sites, and used this algorithm to search the human genome for novel MAP kinase substrates and regulators focused on the JNK family of MAP kinases. Predictions were tested by peptide array followed by rigorous biochemical verification with in vitro binding and kinase assays on wild-type and mutant proteins. Using this procedure, we found new ‘D-site’ class docking sites in previously known JNK substrates (hnRNP-K, PPM1J/PP2Czeta), as well as new JNK-interacting proteins (MLL4, NEIL1). Finally, we identified new D-site-dependent MAPK substrates, including the hedgehog-regulated transcription factors Gli1 and Gli3, suggesting that a direct connection between MAP kinase and hedgehog signaling may occur at the level of these key regulators. These results demonstrate that a genome-wide search for MAP kinase docking sites can be used to find new docking sites and substrates

Mutations in BCOR, a Co-Repressor of CRX/OTX2, Are Associated With Early-Onset Retinal Degeneration

Many transcription factors regulating the production, survival, and function of photoreceptor cells have been identified, but little is known about transcriptional co-regulators in retinal health and disease. Here, we show that BCL6 co-repressor (BCOR), a Polycomb repressive complex 1 factor mutated in various cancers, is involved in photoreceptor degenerative diseases. Using proteomics and transcription assays, we report that BCOR interacts with the transcription factors CRX and OTX2 and reduces their ability to activate the promoters of photoreceptor-specific genes. CUT&RUN sequencing further shows that BCOR shares genome-wide binding profiles with CRX/OTX2, consistent with a general co-repression activity. We also identify missense mutations in huma

EhMAPK, the Mitogen-Activated Protein Kinase from Entamoeba histolytica Is Associated with Cell Survival

Mitogen Activated Protein Kinases (MAPKs) are a class of serine/threonine kinases that regulate a number of different cellular activities including cell proliferation, differentiation, survival and even death. The pathogen Entamoeba histolytica possess a single homologue of a typical MAPK gene (EhMAPK) whose identification was previously reported by us but its functional implications remained unexplored. EhMAPK, the only mitogen-activated protein kinase from the parasitic protist Entamoeba histolytica with Threonine-X-Tyrosine (TXY) phosphorylation motif was cloned, expressed in E. coli and functionally characterized under different stress conditions. The expression profile of EhMAPK at the protein and mRNA level remained similar among untreated, heat shocked and hydrogen peroxide-treated samples in all cases of dose and time. But a significant difference was obtained in the phosphorylation status of the protein in response to different stresses. Heat shock at 43°C or 0.5 mM H2O2 treatment enhanced the phosphorylation status of EhMAPK and augmented the kinase activity of the protein whereas 2.0 mM H2O2 treatment induced dephosphorylation of EhMAPK and loss of kinase activity. 2.0 mM H2O2 treatment reduced parasite viability significantly but heat shock and 0.5 mM H2O2 treatment failed to adversely affect E. histolytica viability. Therefore, a distinct possibility that activation of EhMAPK is associated with stress survival in E. histolytica is seen. Our study also gives a glimpse of the regulatory mechanism of the protein under in vivo conditions. Since the parasite genome lacks any typical homologue of mammalian MEK, the dual specificity kinases which are the upstream activators of MAPK, indications of the existence of some alternate regulatory mechanisms of the EhMAPK activity is perceived. These may include the autophosphorylation activity of the protein itself in combination with some upstream phosphatases which are not yet identified