2020
DOI: 10.1128/jvi.01966-19
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Nascent Transcriptomics Reveal Cellular Prolytic Factors Upregulated Upstream of the Latent-to-Lytic Switch Protein of Epstein-Barr Virus

Abstract: Lytic activation from latency is a key transition point in the life cycle of herpesviruses. Epstein-Barr virus (EBV) is a human herpesvirus that can cause lymphomas, epithelial cancers, and other diseases, most of which require the lytic cycle. While the lytic cycle of EBV can be triggered by chemicals and immunologic ligands, the lytic cascade is activated only when expression of the EBV latent-to-lytic switch protein ZEBRA is turned on. ZEBRA then transcriptionally activates other EBV genes and, together wit… Show more

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Cited by 14 publications
(16 citation statements)
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“…Host genes upregulated within lytic cluster cells (e.g., NFATC1 , MIER2 , SFN , and SGK1 ) represent a limited subset of transcription factors associated with B (and T) lymphocyte activation ( Peng et al, 2001 ; Tsitsikov et al, 2001 ), several of which have been recently identified at various degrees of enrichment within lytic cells ( Frey et al, 2020 ). The presence of NFATC1 is particularly notable considering the recent report of this factor contributing to the spontaneous lytic phenotype of type 2 EBV by upregulating expression of BZLF1 to promote the lytic gene expression cascade ( Romero-Masters et al, 2020 ).…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…Host genes upregulated within lytic cluster cells (e.g., NFATC1 , MIER2 , SFN , and SGK1 ) represent a limited subset of transcription factors associated with B (and T) lymphocyte activation ( Peng et al, 2001 ; Tsitsikov et al, 2001 ), several of which have been recently identified at various degrees of enrichment within lytic cells ( Frey et al, 2020 ). The presence of NFATC1 is particularly notable considering the recent report of this factor contributing to the spontaneous lytic phenotype of type 2 EBV by upregulating expression of BZLF1 to promote the lytic gene expression cascade ( Romero-Masters et al, 2020 ).…”
Section: Discussionmentioning
confidence: 99%
“…Host genes upregulated within lytic cluster cells (e.g., NFATC1, MIER2, SFN, SGK1) represent a limited subset of transcription factors associated with B (and T) lymphocyte activation 72,73 , several of which have been recently identified at various degrees of enrichment within lytic cells. 74 The presence of NFATC1 is particularly notable considering the recent report of this factor contributing to the spontaneous lytic phenotype of type 2 EBV by upregulating expression of BZLF1 to promote the lytic gene expression cascade. 75 Although PC loadings reveal substantial upregulation of more than a dozen EBV lytic genes, cells within the lytic clusters curiously lack expression of BZLF1, which plays a role in the latentto-lytic transition.…”
Section: Viral Origins Of Lcl Phenotypic Variancementioning
confidence: 99%
“…Here, results can be browsed alongside genomic annotations (which have been loaded from NCBI for each genome) or any JBrowse compatible file ( Buels et al, 2016 ) a user has available. As an example, for EBV-1 we include additional tracks alongside results to help identify regions of interest; the McIntosh lab has generated RNA sequencing data for the EBV-1 genome as it transitions from a latent to a lytically active state ( Frey et al, 2020 ). The sequencing data from this study can now be seen as a coverage track and allows users to quickly assess whether regions highlighted by fall within actively transcribed regions.…”
Section: Discussionmentioning
confidence: 99%
“…Here, results can be browsed alongside genomic annotations (which have been loaded from NCBI for each genome) or any JBrowse compatible file (Buels et al 2016) a user has available. As an example, for EBV-1 we include additional tracks alongside ScanFold results to help identify regions of interest; the McIntosh lab has generated RNA sequencing data for the EBV-1 genome as it transitions from a latent to a lytically active state (Frey et al 2020). The sequencing data from this study can now be seen as a coverage tracks and allows users to quickly assess whether regions highlighted by ScanFold fall within actively transcribed regions.…”
Section: Discussionmentioning
confidence: 99%