Dataset Information

Viral transcriptional regulators extensively rewire host pathways through diverse mechanisms

ABSTRACT: Viral transcriptional regulators (vTRs) reprogram host gene regulatory networks to promote replication, persistence, and immune evasion. Despite the identification of hundreds of vTRs in human viruses, how they rewire host pathways remains unclear. Here, we systematically profiled 95 vTRs from diverse human viruses across multiple functional assays. vTRs perturb immune, cell proliferation/death, and signaling pathways through various mechanisms; some bind DNA directly, others cooperate or antagonize human transcription factors (hTFs), and some remodel chromatin. vTRs can act as activators or repressors and recruit similar but not identical repertoires of proteins as hTFs. These findings reveal vTRs as versatile transcriptional modulators that converge on conserved host “pressure points” while diversifying across pathways to promote viral replication and persistence. Notably, many vTR dysregulate genes within autoimmune, neurological, and cardiovascular risk loci, revealing mechanistic links to disease. Together, we provide a comprehensive resource for understanding and targeting viral control of human transcription.

ORGANISM(S): Homo sapiens

PROVIDER: GSE312349 | GEO | 2026/03/01

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:Genotypic differences greatly influence susceptibility and resistance to disease. Understanding genotype-phenotype relationships requires that phenotypes be viewed as manifestations of network properties, rather than simply as the result of individual genomic variations. Genome sequencing efforts have identified numerous germline mutations associated with cancer predisposition and large numbers of somatic genomic alterations. However, it remains challenging to distinguish between background, or “passenger” and causal, or “driver” cancer mutations in these datasets. Human viruses intrinsically depend on their host cell during the course of infection and can elicit pathological phenotypes similar to those arising from mutations. To test the hypothesis that genomic variations and tumour viruses may cause cancer via related mechanisms, we systematically examined host interactome and transcriptome network perturbations caused by DNA tumour virus proteins. The resulting integrated viral perturbation data reflects rewiring of the host cell networks, and highlights pathways that go awry in cancer, such as Notch signalling and apoptosis. We show that systematic analyses of host targets of viral proteins can identify cancer genes with a success rate on par with their identification through functional genomics and large-scale cataloguing of tumour mutations. These complementary approaches together result in increased specificity for cancer gene identification. Combining systems-level studies of pathogen-encoded gene products with genomic approaches will facilitate prioritization of cancer-causing driver genes so as to advance understanding of the genetic basis of human cancer. We profiled the transcriptome of human cells expressing tumor virus proteins, in order to trace pathways through which viral proteins could alter cellular states. To examine transcriptome network perturbations directly in human cells, we generated expression constructs fusing each viral ORF (open reading frame) to a tandem epitope tag and introduced each construct into IMR-90 normal human diploid fibroblasts. Total RNA was isolated from IMR-90 cells expressing viORFs and gene expression was assayed on Human Gene 1.0 ST arrays.

Project description:Abstract: The transcriptional program associated with herpesvirus latency and the viral genes regulating entry into and exit from latency are poorly understood and controversial. Here, we developed and validated a targeted enrichment platform and conducted large-scale transcriptome analyses of human cytomegalovirus (HCMV) infection. We used both an experimental hematopoietic cell model of latency, and cells from naturally infected, healthy human subjects (clinical) to define the breadth of viral genes expressed. The viral transcriptome derived from experimental infection was highly correlated with that from clinical infection, validating our experimental latency model. These transcriptomes revealed a broader profile of gene expression during infection in hematopoietic cells than previously appreciated. Further, using recombinant viruses that establish a non-reactivating, latent-like or replicative infection in CD34+ hematopoietic progenitors (HPCs), we defined classes of low to moderately expressed genes that are differentially regulated in latent vs. replicative states of infection. Most of these genes have yet to be studied in depth. By contrast, genes that were highly expressed, were expressed similarly in both latent and replicative infection. From these findings, a model emerges whereby low or moderately expressed genes may have the greatest impact on regulating the switch between viral latency and replication. The core set of viral genes expressed in natural infection and differentially regulated depending on the pattern of infection provides novel insight into the HCMV transcriptome associated with latency in the host and a resource for investigating new virus-host interactions underlying persistence. Significance: Herpesviruses have an extraordinarily complex relationship with their host, persisting for the lifetime of the host by way of a latent infection. Reactivation of replication is associated with significant disease risk, particularly in immunocompromised individuals. We characterize in depth transcriptional profiles of HCMV latency. We show that a broad and concordant viral transcriptome is found in both an experimental model of latency and in asymptomatically infected individuals. We further define genes that are differentially regulated during latent and replicative states- candidates for key regulators controlling the switch between latency and reactivation. This work will help understand the persistence of complex DNA viruses and provides a path towards developing antiviral strategies to control herpesvirus entry into and exit from latency.

Dataset Information

Viral transcriptional regulators extensively rewire host pathways through diverse mechanisms

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets