Transcriptome-wide characterization of human cytomegalovirus in natural infection and experimental latency

Shu Cheng, Katie Caviness, Jason Buehler, Megan Smithey, Janko Nikolich-Žugich, Felicia Goodrum

Research output: Contribution to journalArticle

55 Scopus citations

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 nonreactivating, latent-like or a replicative infection in CD34+ hematopoietic progenitor cells, 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 insight into the HCMV transcriptome associated with latency in the host and a resource for investigating virus–host interactions underlying persistence.

Original languageEnglish (US)
Pages (from-to)E10586-E10595
JournalProceedings of the National Academy of Sciences of the United States of America
Volume114
Issue number49
DOIs
StatePublished - Dec 5 2017

Keywords

  • Cytomegalovirus
  • Herpesvirus
  • Kernel density estimation
  • Latency
  • Transcriptome

ASJC Scopus subject areas

  • General

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