Epstein-Barr virus latency switch in human B-cells: a physico-chemical model

Werner, Maria Fernanda de Paula; Ernberg, Ingemar; Zou, Jie-Zhi; Almqvist, Jenny; Aurell, Erik

doi:10.1186/1752-0509-1-40

Cited by 14 publications

(21 citation statements)

References 46 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…4H). This transition from type I to type III EBV expression pattern is inefficient, presumably because of the robustness of this molecular switch (23).…”

Section: Subpopulations Representing Different Levels Of Marker Exprementioning

confidence: 99%

Dynamics inside the cancer cell attractor reveal cell heterogeneity, limits of stability, and escape

Wennborg

Aurell

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

Self Cite

107

100

View full text Add to dashboard Cite

The observed intercellular heterogeneity within a clonal cell population can be mapped as dynamical states clustered around an attractor point in gene expression space, owing to a balance between homeostatic forces and stochastic fluctuations. These dynamics have led to the cancer cell attractor conceptual model, with implications for both carcinogenesis and new therapeutic concepts. Immortalized and malignant EBV-carrying B-cell lines were used to explore this model and characterize the detailed structure of cell attractors. Any subpopulation selected from a population of cells repopulated the whole original basin of attraction within days to weeks. Cells at the basin edges were unstable and prone to apoptosis. Cells continuously changed states within their own attractor, thus driving the repopulation, as shown by fluorescent dye tracing. Perturbations of key regulatory genes induced a jump to a nearby attractor. Using the Fokker-Planck equation, this cell population behavior could be described as two virtual, opposing influences on the cells: one attracting toward the center and the other promoting diffusion in state space (noise). Transcriptome analysis suggests that these forces result from high-dimensional dynamics of the gene regulatory network. We propose that they can be generalized to all cancer cell populations and represent intrinsic behaviors of tumors, offering a previously unidentified characteristic for studying cancer.cancer cell attractor | cell heterogeneity | edge cells | gene regulatory network | cell population dynamics

show abstract

“…4H). This transition from type I to type III EBV expression pattern is inefficient, presumably because of the robustness of this molecular switch (23).…”

Section: Subpopulations Representing Different Levels Of Marker Exprementioning

confidence: 99%

Dynamics inside the cancer cell attractor reveal cell heterogeneity, limits of stability, and escape

Wennborg

Aurell

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

Self Cite

107

100

View full text Add to dashboard Cite

show abstract

“…Interestingly, Oct-1 also interacts directly with herpes simplex virus (HSV)-and varicella-zoster virus (VZV)-encoded tegument proteins (VP16 and ORF10, respectively), and this interaction is required for the efficient activation of the HSV and VZV immediate-early promoters (34,45,46,58,93). While Oct-1 and the related POU domain transcription factor, Oct-2, have been previously suggested to play a role in regulating the type of EBV latency (3,55,90), neither protein has been shown to play a role in EBV lytic reactivation.…”

Section: Epstein-barr Virus (Ebv) or Human Herpesvirus 4 (Hhv4)mentioning

confidence: 99%

Cellular Transcription Factor Oct-1 Interacts with the Epstein-Barr Virus BRLF1 Protein To Promote Disruption of Viral Latency

Robinson

Kwek

Hagemeier

et al. 2011

J Virol

View full text Add to dashboard Cite

The Epstein-Barr virus (EBV) latent-to-lytic switch is an essential part of the viral life cycle, but the cellular factors that promote viral reactivation are not well defined. In this report, we demonstrate that the cellular transcription factor Oct-1 cooperates with the EBV immediate-early protein BRLF1 (R, Rta) to induce lytic viral reactivation. We show that cotransfected Oct-1 enhances the ability of BRLF1 to activate lytic gene expression in 293 cells stably infected with a BRLF1-defective EBV mutant (BRLF1-stop) and that Oct-1 increases BRLF1-mediated activation of lytic EBV promoters in reporter gene assays. We find that Oct-1 interacts directly with BRLF1 in vitro and that a mutant BRLF1 protein (the M140A mutant) attenuated for the ability to interact with Oct-1 in vitro is also resistant to Oct-1-mediated transcriptional enhancement in 293 BRLF1-stop cells. Furthermore, we show that cotransfected Oct-1 augments BRLF1 binding to a variety of lytic EBV promoters in chromatin immunoprecipitation (ChIP) assays (including the BZLF1, BMRF1, and SM promoters) and that BRLF1 tethers Oct-1 to lytic EBV promoters. In addition, we demonstrate that an Oct-1 mutant defective in DNA binding (the S335D mutant) still retains the ability to enhance BRLF1 transcriptional effects. Finally, we show that knockdown of endogenous Oct-1 expression reduces the level of constitutive lytic EBV gene expression in both EBV-positive B-cell and EBV-positive epithelial cell lines. These results suggest that Oct-1 acts as a positive regulator of EBV lytic gene expression and that this effect is at least partially mediated through its interaction with the viral protein BRLF1. Epstein-Barr virus (EBV), or human herpesvirus 4 (HHV4), is a double-stranded DNA gammaherpesvirus which infects approximately 90% of the world's population (66). It causes a relatively mild primary disease if acquired early in life and infectious mononucleosis if acquired after adolescence. EBV is also associated with several B-cell and epithelial cell cancers, including Burkitt lymphoma, Hodgkin lymphoma, nasopharyngeal carcinoma (NPC), and gastric carcinoma (66, 101).EBV infection persists for the life of the host as a chronic asymptomatic infection by establishing latency in memory B cells (77). However, to be transmitted from host to host, and from cell to cell, the virus periodically reactivates from latency and converts to the lytic form of replication (66). Reactivation of lytic EBV infection in host cells is controlled at the level of the BZLF1 (Z, Zta, ZEBRA, EB1) and BRLF1 (R, Rta) viral promoters, as well as the activity of the BZLF1 and BRLF1 gene products (24,42,95). The BZLF1 and BRLF1 genes encode transcription factors that cooperatively turn on the expression of the early lytic viral genes involved in lytic viral replication (2,9,16,17,23,24,26,29,31,41,50,62,68), and the overexpression of either BZLF1 or BRLF1 is sufficient to induce lytic gene expression in many latently infected cell lines (13-15, 63, 83, 96). Since the combination of both BZL...

show abstract

“…A very simplified scheme of the regulatory network controlling the Cp and Qp promoter activity is depicted in Figure 1. We refer to Robertson (2010), Werner et al (2007b), and Young and Rickinson (2004) for the precise details about the complex gene regulation in the Epstein-Barr virus.…”

Section: A Case Study: the Epstein-barr Virus Genetic Switchmentioning

confidence: 99%

“…Moreover, with the advent of novel synthetic DNA binding domains, it is also possible to design a more complex gene circuit with information processing capabilities (Gaber et al, 2014). Modeling approaches for such systems have already been proposed (Vucko et al, 2013;Werner et al, 2007b). However, these approaches lack the inherent accuracy of the SSA approach and are unable to provide the detailed insights in the modeled systems on a molecular level.…”

Section: Introductionmentioning

confidence: 98%

“…Several examples of GRNs driven by transcription factors that can bind competitively on multiple binding sites can be found in nature, for example, in the switching mechanism of the Epstein-Barr virus (EBV) (Werner et al, 2007b). On the other hand there has been an increasing number of synthetic GRNs comprised of a particularly high number of designed transcriptional control binding sites in recent years (Boch et al, 2009;Bogdanove and Voytas, 2011).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Stochastic Simulation Algorithm for Gene Regulatory Networks with Multiple Binding Sites

Petroni

Zimic²,

Mraz³

et al. 2015

Journal of Computational Biology

View full text Add to dashboard Cite

Promoters with multiple binding sites present a regulatory mechanism of several natural biological systems. It has been shown that such systems reflect a higher stability in comparison to the systems with small numbers of binding sites. Regulatory mechanisms with multiple binding sites are therefore used more frequently in artificially designed biological systems in recent years. While the number of possible promoter states increases exponentially with the number of binding sites, it is extremely hard to model such systems accurately. Here we present an adaptation of stochastic simulation algorithm for accurate modeling of gene regulatory networks with multiple binding sites. Small computational complexity of adapted algorithm allows us to model any feasible number of binding sites per promoter. The approach introduced in this work is demonstrated on the model of switching mechanism in Epstein-Barr virus, where 20 binding sites are observed on one of the promoters. We show that the presented approach is easy to adapt to any biological systems based on the regulatory mechanisms with multiple binding sites in order to obtain and analyze their behavior.

show abstract

Epstein-Barr virus latency switch in human B-cells: a physico-chemical model

Cited by 14 publications

References 46 publications

Dynamics inside the cancer cell attractor reveal cell heterogeneity, limits of stability, and escape

Dynamics inside the cancer cell attractor reveal cell heterogeneity, limits of stability, and escape

Cellular Transcription Factor Oct-1 Interacts with the Epstein-Barr Virus BRLF1 Protein To Promote Disruption of Viral Latency

Stochastic Simulation Algorithm for Gene Regulatory Networks with Multiple Binding Sites

Contact Info

Product

Resources

About