The Interaction of RNA Helicase DDX3 with HIV-1 Rev-CRM1-RanGTP Complex during the HIV Replication Cycle

Mahboobi, Seyed Hanif; Javanpour, Alex A.; Mofrad, Mohammad R. K.

doi:10.1371/journal.pone.0112969

Cited by 27 publications

(16 citation statements)

References 64 publications

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“…In addition, DDX3 is essential for the nuclear export of the human immunodeficiency virus 1 (HIV-1) protein Rev and is, therefore, also a potential therapeutic target in the treatment of HIV infections 35,36. Understanding the cellular mechanisms behind increased nuclear retention of DDX3 may facilitate the development of therapies specifically targeting the export function of DDX3 37. In addition, nuclear DDX3 could serve as a prognostic and potentially therapeutic biomarker for selecting cancer patients that may benefit from treatment with DDX3 inhibitors.…”

Section: Discussionmentioning

confidence: 99%

Nuclear DDX3 expression predicts poor outcome in colorectal and breast cancer

Voss¹,

Vesuna²,

Bol³

et al. 2017

OTT

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PurposeDEAD box protein 3 (DDX3) is an RNA helicase with oncogenic properties that shuttles between the cytoplasm and nucleus. The majority of DDX3 is found in the cytoplasm, but a subset of tumors has distinct nuclear DDX3 localization of yet unknown biological significance. This study aimed to evaluate the significance of and mechanisms behind nuclear DDX3 expression in colorectal and breast cancer.MethodsExpression of nuclear DDX3 and the nuclear exporter chromosome region maintenance 1 (CRM1) was evaluated by immunohistochemistry in 304 colorectal and 292 breast cancer patient samples. Correlations between the subcellular localization of DDX3 and CRM1 and the difference in overall survival between patients with and without nuclear DDX3 were studied. In addition, DDX3 mutants were created for in vitro evaluation of the mechanism behind nuclear retention of DDX3.ResultsDDX3 was present in the nucleus of 35% of colorectal and 48% of breast cancer patient samples and was particularly strong in the nucleolus. Nuclear DDX3 correlated with worse overall survival in both colorectal (hazard ratio [HR] 2.34, P<0.001) and breast cancer (HR 2.39, P=0.004) patients. Colorectal cancers with nuclear DDX3 expression more often had cytoplasmic expression of the nuclear exporter CRM1 (relative risk 1.67, P=0.04). In vitro analysis of DDX3 deletion mutants demonstrated that CRM1-mediated export was most dependent on the N-terminal nuclear export signal.ConclusionOverall, we conclude that nuclear DDX3 is partially CRM1-mediated and predicts worse survival in colorectal and breast cancer patients, putting it forward as a target for therapeutic intervention with DDX3 inhibitors under development in these cancer types.

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Section: Discussionmentioning

confidence: 99%

Nuclear DDX3 expression predicts poor outcome in colorectal and breast cancer

Voss¹,

Vesuna²,

Bol³

et al. 2017

OTT

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“…To our knowledge, both our proposed physical transport mechanism and our mathematical approach are novel. Most previous modeling work on the NPC has focused on atomistic (2,(43)(44)(45) and coarse-grained simulations (8,12,33,(46)(47)(48)(49)(50). This has illuminated many of the finer points of nuclear transport, but the detailed nature of this work makes it difficult to draw general conclusions about the driving force behind cargo translocation.…”

Section: Comparison To Previous Modelsmentioning

confidence: 99%

Enhanced Nucleocytoplasmic Transport due to Competition for Elastic Binding Sites

Fogelson

Keener

2018

Biophysical Journal

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Nuclear pore complexes (NPCs) control all traffic into and out of the cell nucleus. NPCs are molecular machines that simultaneously achieve high selectivity and high transport rates. The biophysical details of how cargoes rapidly traverse the pore remain unclear but are known to be mediated by interactions between cargo-binding chaperone proteins and natively unstructured nucleoporin proteins containing many phenylalanine-glycine repeats (FG nups) that line the pore's central channel. Here, we propose a specific and detailed physical mechanism for the high speed of nuclear import based on the elasticity of FG nups and on competition between individual chaperone proteins for FG nup binding. We develop a mathematical model to support our proposed mechanism. We suggest that the recycling of nuclear import factors back to the cytoplasm is important for driving high-speed import and predict the existence of an optimal cytoplasmic concentration of cargo for enhancing the rate of import over a purely diffusive rate.

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“…The expression of DDX3X was also activated at the intermediate HIV infection stage. Therefore, we suggested that DDX3X could regulate HIV replication through MIR139-5p regulations [ 98 , 99 ].…”

Section: Discussionmentioning

confidence: 99%

Constructing an integrated genetic and epigenetic cellular network for whole cellular mechanism using high-throughput next-generation sequencing data

Chen

2016

BMC Syst Biol

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BackgroundEpigenetics has been investigated in cancer initiation, and development, especially, since the appearance of epigenomics. Epigenetics may be defined as the mechanisms that lead to heritable changes in gene function and without affecting the sequence of genome. These mechanisms explain how individuals with the same genotype produce phenotypic differences in response to environmental stimuli. Recently, with the accumulation of high-throughput next-generation sequencing (NGS) data, a key goal of systems biology is to construct networks for different cellular levels to explore whole cellular mechanisms. At present, there is no satisfactory method to construct an integrated genetic and epigenetic cellular network (IGECN), which combines NGS omics data with gene regulatory networks (GRNs), microRNAs (miRNAs) regulatory networks, protein-protein interaction networks (PPINs), and epigenetic regulatory networks of methylation using high-throughput NGS data.ResultsWe investigated different kinds of NGS omics data to develop a systems biology method to construct an integrated cellular network based on three coupling models that describe genetic regulatory networks, protein–protein interaction networks, microRNA (miRNA) regulatory networks, and methylation regulation. The proposed method was applied to construct IGECNs of gastric cancer and the human immune response to human immunodeficiency virus (HIV) infection, to elucidate human defense response mechanisms. We successfully constructed an IGECN and validated it by using evidence from literature search. The integration of NGS omics data related to transcription regulation, protein-protein interactions, and miRNA and methylation regulation has more predictive power than independent datasets. We found that dysregulation of MIR7 contributes to the initiation and progression of inflammation-induced gastric cancer; dysregulation of MIR9 contributes to HIV-1 infection to hijack CD4+ T cells through dysfunction of the immune and hormone pathways; dysregulation of MIR139-5p, MIRLET7i, and MIR10a contributes to the HIV-1 integration/replication stage; dysregulation of MIR101, MIR141, and MIR152 contributes to the HIV-1 virus assembly and budding mechanisms; dysregulation of MIR302a contributes to not only microvesicle-mediated transfer of miRNAs but also dysfunction of NF-κB signaling pathway in hepatocarcinogenesis.ConclusionThe coupling dynamic systems of the whole IGECN can allow us to investigate genetic and epigenetic cellular mechanisms via omics data and big database mining, and are useful for further experiments in the field of systems and synthetic biology.

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The Interaction of RNA Helicase DDX3 with HIV-1 Rev-CRM1-RanGTP Complex during the HIV Replication Cycle

Cited by 27 publications

References 64 publications

Nuclear DDX3 expression predicts poor outcome in colorectal and breast cancer

Nuclear DDX3 expression predicts poor outcome in colorectal and breast cancer

Enhanced Nucleocytoplasmic Transport due to Competition for Elastic Binding Sites

Constructing an integrated genetic and epigenetic cellular network for whole cellular mechanism using high-throughput next-generation sequencing data

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