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Amebiasis, a global intestinal parasitic disease, is due to Entamoeba histolytica. This parasite, which feeds on bacteria in the large intestine of its human host, can trigger a strong inflammatory response upon invasion of the colonic mucosa. Whereas information about the mechanisms which are used by the parasite to cope with oxidative and nitrosative stresses during infection is available, knowledge about the contribution of bacteria to these mechanisms is lacking. In a recent study, we demonstrated that enteropathogenic Escherichia coli O55 protects E. histolytica against oxidative stress. Resin-assisted capture (RAC) of oxidized (OX) proteins coupled to mass spectrometry (OX-RAC) was used to investigate the oxidation status of cysteine residues in proteins present in E. histolytica trophozoites incubated with live or heat-killed E. coli O55 and then exposed to H2O2-mediated oxidative stress. We found that the redox proteome of E. histolytica exposed to heat-killed E. coli O55 is enriched with proteins involved in redox homeostasis, lipid metabolism, small molecule metabolism, carbohydrate derivative metabolism, and organonitrogen compound biosynthesis. In contrast, we found that proteins associated with redox homeostasis were the only OX-proteins that were enriched in E. histolytica trophozoites which were incubated with live E. coli O55. These data indicate that E. coli has a profound impact on the redox proteome of E. histolytica. Unexpectedly, some E. coli proteins were also co-identified with E. histolytica proteins by OX-RAC. We demonstrated that one of these proteins, E. coli malate dehydrogenase (EcMDH) and its product, oxaloacetate, are key elements of E. coli-mediated resistance of E. histolytica to oxidative stress and that oxaloacetate helps the parasite survive in the large intestine. We also provide evidence that the protective effect of oxaloacetate against oxidative stress extends to Caenorhabditis elegans. [ABSTRACT FROM AUTHOR]

Copy number variation (CNV) plays a role in pathogenesis of many human diseases, especially cancer. Several whole genome CNV association studies have been performed for the purpose of identifying cancer associated CNVs. Here we undertook a novel approach to whole genome CNV analysis, with the goal being identification of associations between CNV of different genes (CNV-CNV) across 60 human cancer cell lines. We hypothesize that these associations point to the roles of the associated genes in cancer, and can be indicators of their position in gene networks of cancer-driving processes. Recent studies show that gene associations are often non-linear and non-monotone. In order to obtain a more complete picture of all CNV associations, we performed omnibus univariate analysis by utilizing dCov, MIC, and HHG association tests, which are capable of detecting any type of association, including non-monotone relationships. For comparison we used Spearman and Pearson association tests, which detect only linear or monotone relationships. Application of dCov, MIC and HHG tests resulted in identification of twice as many associations compared to those found by Spearman and Pearson alone. Interestingly, most of the new associations were detected by the HHG test. Next, we utilized dCov's and HHG's ability to perform multivariate analysis. We tested for association between genes of unknown function and known cancer-related pathways. Our results indicate that multivariate analysis is much more effective than univariate analysis for the purpose of ascribing biological roles to genes of unknown function. We conclude that a combination of multivariate and univariate omnibus association tests can reveal significant information about gene networks of disease-driving processes. These methods can be applied to any large gene or pathway dataset, allowing more comprehensive analysis of biological processes. [ABSTRACT FROM AUTHOR]