Murine leukemia virus particles activate Rac1 in HeLa cells

Krishna, Delfi; Doux, Joseph M. Le

doi:10.1016/j.bbrc.2006.05.027

Cited by 4 publications

(2 citation statements)

References 54 publications

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“…The genes within this subnetwork are very substantially supported by literature with respect to their role in leukaemia. For instance, the gene RAC (which regulates a diverse array of cellular events) is referenced in [30,31] as having an effect on leukaemia. Other genes within the network are Rhoa (regulates the actin cytoskeleton in formation of stress fibers) in [32,33], Vav1 (plays a major role in development and activation of T-cell and B-cell blood cells) in [34] and IQGAP (regulates cell adhesion, morphology and motility) in [35].…”

Section: Resultsmentioning

confidence: 99%

Finding consistent disease subnetworks across microarray datasets

et al. 2011

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BackgroundWhile contemporary methods of microarray analysis are excellent tools for studying individual microarray datasets, they have a tendency to produce different results from different datasets of the same disease. We aim to solve this reproducibility problem by introducing a technique (SNet). SNet provides both quantitative and descriptive analysis of microarray datasets by identifying specific connected portions of pathways that are significant. We term such portions within pathways as “subnetworks”.ResultsWe tested SNet on independent datasets of several diseases, including childhood ALL, DMD and lung cancer. For each of these diseases, we obtained two independent microarray datasets produced by distinct labs on distinct platforms. In each case, our technique consistently produced almost the same list of significant nontrivial subnetworks from two independent sets of microarray data. The gene-level agreement of these significant subnetworks was between 51.18% to 93.01%. In contrast, when the same pairs of microarray datasets were analysed using GSEA, t-test and SAM, this percentage fell between 2.38% to 28.90% for GSEA, 49.60% tp 73.01% for t-test, and 49.96% to 81.25% for SAM. Furthermore, the genes selected using these existing methods did not form subnetworks of substantial size. Thus it is more probable that the subnetworks selected by our technique can provide the researcher with more descriptive information on the portions of the pathway actually affected by the disease.ConclusionsThese results clearly demonstrate that our technique generates significant subnetworks and genes that are more consistent and reproducible across datasets compared to the other popular methods available (GSEA, t-test and SAM). The large size of subnetworks which we generate indicates that they are generally more biologically significant (less likely to be spurious). In addition, we have chosen two sample subnetworks and validated them with references from biological literature. This shows that our algorithm is capable of generating descriptive biologically conclusions.

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Section: Resultsmentioning

confidence: 99%

Finding consistent disease subnetworks across microarray datasets

et al. 2011

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“…Hepatitis B virus (HBV) infection may alter the activity of Rac1, which consequently facilitates HBV replication (Tan et al, 2008). Murine leukemia virus can activate Rac1 in HeLa cells (Krishna and Le Doux, 2006). However, the role of Rac1 activity in the regulation of VEC infection with DENV remains poorly understood.…”

Section: Introductionmentioning

confidence: 99%

Small G Rac1 is involved in replication cycle of dengue serotype 2 virus in EAhy926 cells via the regulation of actin cytoskeleton

Zhang

Gao

et al. 2016

Sci. China Life Sci.

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Bleeding is a clinical characteristic of severe dengue and may be due to increased vascular permeability. However, the pathogenesis of severe dengue remains unclear. In this study, we showed that the Rac1-microfilament signal pathway was involved in the process of DENV serotype 2 (DENV2) infection in EAhy926 cells. DENV2 infection induced dynamic changes in actin organization, and treatment with Cytochalasin D or Jasplakinolide disrupted microfilament dynamics, reduced DENV2 entry, and inhibited DENV2 assembly and maturation. Rac1 activities decreased during the early phase and gradually increased by the late phase of infection. Expression of the dominant-negative form of Rac1 promoted DENV2 entry but inhibited viral assembly, maturation and release. Our findings demonstrated that Rac1 plays an important role in the DENV2 life cycle by regulating actin reorganization in EAhy926 cells. This finding provides further insight into the pathogenesis of severe dengue. dengue virus, small Rho GTPase Rac1, actin, vascular endothelial cells

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