Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2021 Sep 27;95(20):e0069821.
doi: 10.1128/JVI.00698-21. Epub 2021 Aug 4.

Human Cytomegalovirus RNA2.7 Is Required for Upregulating Multiple Cellular Genes To Promote Cell Motility and Viral Spread Late in Lytic Infection

Betty Lau  1 , Karen Kerr  1 , Salvatore Camiolo  1 , Katie Nightingale  2 , Quan Gu  1 , Robin Antrobus  2 , Nicolás M Suárez  1 , Colin Loney  1 , Richard J Stanton  3 , Michael P Weekes  2 , Andrew J Davison  1
Affiliations

Human Cytomegalovirus RNA2.7 Is Required for Upregulating Multiple Cellular Genes To Promote Cell Motility and Viral Spread Late in Lytic Infection

Betty Lau et al. J Virol. .

Abstract

Long noncoding RNAs (lncRNAs) are frequently associated with broad modulation of gene expression and thus provide the cell with the ability to synchronize entire metabolic processes. We used transcriptomic approaches to investigate whether the most abundant human cytomegalovirus-encoded lncRNA, RNA2.7, has this characteristic. By comparing cells infected with wild-type virus (WT) to cells infected with RNA2.7 deletion mutants, RNA2.7 was implicated in regulating a large number of cellular genes late in lytic infection. Pathway analysis indicated that >100 of these genes are associated with promoting cell movement, and the 10 most highly regulated of these were validated in further experiments. Morphological analysis and live cell tracking of WT- and RNA2.7 mutant-infected cells indicated that RNA2.7 is involved in promoting the movement and detachment of infected cells late in infection, and plaque assays using sparse cell monolayers indicated that RNA2.7 is also involved in promoting cell-to-cell spread of virus. Consistent with the observation that upregulated mRNAs are relatively A+U-rich, which is a trait associated with transcript instability, and that they are also enriched in motifs associated with mRNA instability, transcriptional inhibition experiments on WT- and RNA2.7 mutant-infected cells showed that four upregulated transcripts lived longer in the presence of RNA2.7. These findings demonstrate that RNA2.7 is required for promoting cell movement and viral spread late in infection and suggest that this may be due to general stabilization of A+U-rich transcripts. IMPORTANCE In addition to messenger RNAs (mRNAs), the human genome encodes a large number of long noncoding RNAs (lncRNAs). Many lncRNAs that have been studied in detail are associated with broad modulation of gene expression and have important biological roles. Human cytomegalovirus, which is a large, clinically important DNA virus, specifies four lncRNAs, one of which (RNA2.7) is expressed at remarkably high levels during lytic infection. Our studies show that RNA2.7 is required for upregulating a large number of human genes, about 100 of which are associated with cell movement, and for promoting the movement of infected cells and the spread of virus from one cell to another. Further bioinformatic and experimental analyses indicated that RNA2.7 may exert these effects by stabilizing mRNAs that are relatively rich in A and U nucleotides. These findings increase our knowledge of how human cytomegalovirus regulates the infected cell to promote its own success.

Keywords: cell motility; human cytomegalovirus; lncRNA; regulation of gene expression.

PubMed Disclaimer

Figures

FIG 1
FIG 1
Effects of RNA2.7 on viral growth kinetics. (A) Diagram depicting the regions deleted in the RNA2.7 mutants (ΔRNA2.7 and ΔTATA) in comparison with WT. The RNA2.7-coding region is indicated by a blue arrow, the TATA box by a red line, the polyadenylation [poly(A)] signal by a yellow line and deleted regions by gray-shaded rectangles. Numbers indicate the distance (nt) from the transcription initiation site (at 1 nt). In the HCMV genome, the RNA2.7 gene is oriented leftward near the left end (22). For analysis under standard culture conditions, HFFF2 cells were infected at an MOI of  1 (B) or an MOI of  0.001 (C) with WT, ΔRNA2.7, or ΔTATA, and cell-released viral titers were determined. For analysis under conditions of glucose deprivation (D) or cell synchronization (E), HFFF2 cells were infected with WT, ΔRNA2.7, or ΔTATA at an MOI of  5. Each result represents one of three independent experiments, with each error bar indicating the standard deviation of technical replicates. PFU, plaque-forming units.
FIG 2
FIG 2
Effects of RNA2.7 on viral transcription. HFFF2 cells were infected at an MOI of  5 with WT, ΔRNA2.7, or ΔTATA. Sequence reads generated from polyadenylated RNA isolated at 4, 24, or 72 h p.i. were aligned to the WT and ΔRNA2.7 genome sequences and counted. Each error bar indicates the standard deviation of three independent experiments. The data are shown for reads from RNA2.7 (A) and all other viral transcripts (B) and are expressed as percentages of all viral and host reads (% total reads). N.S., not significant. (C) Alignment of sense reads from WT- and ΔTATA-infected cells at 72 h p.i. to the region containing the RNA2.7 gene, visualized in Tablet. Greater height and intensity and indicate higher coverage. The two plots are shown on different scales: ΔTATA expressed approximately 10% of the level of RNA2.7 expressed by WT (see panel A).
FIG 3
FIG 3
Effects of RNA2.7 on viral sense and antisense transcription. HFFF2 cells were infected at an MOI of  5 with WT, ΔRNA2.7, or ΔTATA. Sequence reads generated from polyadenylated RNA isolated at 4, 24, or 72 h p.i. were aligned to the WT and ΔRNA2.7 genome sequences, sorted into those originating from sense and antisense transcripts from each CDS, and counted. Sense (A) and antisense (B) expressions of viral transcripts by the mutants were compared to those of WT and are shown as log2fold change (log2FC) values. Significantly dysregulated transcripts (q < 0.05) are marked by orange dots. (C) Lack of correlation between sense and antisense log2FC values in the RNA2.7 mutants. The data were generated from three independent experiments.
FIG 4
FIG 4
Effects of RNA2.7 on expression of regulated CMA genes. (A) Synchronized HFFF2 cells were infected at an MOI of  5 with WT, ΔRNA2.7 (denoted Δ2.7), or ΔTATA. At 72 h p.i., the transcript levels of 10 cell movement-associated (CMA) genes that were highly expressed in WT-infected cells and downregulated in mutant-infected cells in the transcriptomic analysis were confirmed by RT-PCR, with GAPDH and G6PD serving as loading controls. One representative result of three independent experiments is shown. (B) Protein levels for two of these genes examined by immunoblotting analysis. Band density was normalized to the actin loading control, and expression levels relative to WT-infected cells for three independent experiments are shown. (C) Differential expression data for the 73 regulated CMA genes that were registered in both the transcriptomic and proteomic analyses. These were calculated as log2fold change (log2FC) values relative to WT. R and p define the strength and significance of the correlation, respectively. M, mock infected. Error bars denote standard deviation values.
FIG 5
FIG 5
Effects of HCMV infection on transcription of CMA genes. HFFF2 cells were infected at an MOI of  5 with WT, ΔRNA2.7, or ΔTATA. (A) Data for 10 highly expressed CMA genes that were upregulated in the presence of RNA2.7 were extracted from Table S1 of a published report (36). Immortalized fibroblasts (HFFF-TERT cells) were infected at an MOI of 5 or 10 with HCMV strain Merlin in three biological replicates, and transcript abundance was determined by sequencing RNA samples harvested at 0 (mock infected), 24, or 72 h p.i. RPKM values were normalized for each gene to the highest level observed during the time course. (B) Data for RNA2.7, TPM3, and STX3 transcripts determined by RT-qPCR and normalized to that of the GAPDH transcript. Each result represents one of three independent experiments, with error bars indicating the standard deviation of technical replicates.
FIG 6
FIG 6
Effects of RNA2.7 on movement and rounding of cells. Synchronized HF-Tet cells were infected at an MOI of 5 with UL36-GFP-WT, UL36-GFP-ΔRNA2.7 (denoted ΔRNA2.7), or UL36-GFP-ΔTATA (denoted ΔTATA). (A) Fluorescent live cell microscopy and cell tracking performed at 72 to 120 h p.i., with images taken every 10 min. The data represent three independent experiments, each involving duplicate wells and five independent fields of view per well. An average of 756 good quality tracks per sample was analyzed. (B) Infected cell roundness, as defined by an aspect (breath versus width) ratio of ≥0.7 measured at 96 h p.i. before and after removing detached cells by changing the culture medium. The data were generated from three independent experiments. Px, pixels.
FIG 7
FIG 7
Effects of RNA2.7 on viral spread. Synchronized HF-Tet cells were infected at an MOI of 5 with UL36-GFP-WT, UL36-GFP-ΔRNA2.7 (denoted ΔRNA2.7), or UL36-GFP-ΔTATA (denoted ΔTATA). At 72 to 96 h p.i., infected cells were used to seed plaques on sparse or confluent monolayers in the presence of anti-HCMV blocking antibodies. GFP-expressing cells at 48 h p.i. were enumerated. A summary of results with Tukey box-and-whisker plots representing three independent experiments in which all plaques were assessed is shown.
FIG 8
FIG 8
Effects of GRIM-19 on expression of regulated CMA genes. HFT cells were transduced with lentivirus constructs expressing either a nontargeting shRNA as negative control (−) or one of three separate GRIM-19-targeting shRNAs (KD1-KD3). Stable cell lines established by puromycin selection were synchronized and mock-infected (mock) or infected at an MOI of 5 with WT, ΔRNA2.7, or ΔTATA. (A) RT-PCR of CMA transcripts in RNA harvested at 72 h p.i., using GAPDH as a loading control. (B) Immunoblot of GRIM-19 levels in mock-infected cells. In each panel, the data represent one of three independent experiments.
FIG 9
FIG 9
Effects of inhibiting viral DNA synthesis on cell movement. Synchronized HF-Tet cells were infected at an MOI of 5 with UL36-GFP-WT, UL36-GFP-ΔRNA2.7 (denoted ΔRNA2.7), or UL36-GFP-ΔTATA (denoted ΔTATA), after which the UL36-GFP-WT-infected cells were treated immediately with PFA or left untreated. (A) Cell movement speed measured by fluorescent live cell confocal microscopy and cell tracking at 48 to 96 h p.i., taking images at 10-min intervals. The data represent three independent experiments, each with duplicate wells and five independent fields of view per well. Significantly different results were grouped using Tukey’s test (columns A, B, and C), and error bars denote standard deviation values. (B) RNA2.7 levels measured by RT-qPCR at 72 h p.i., with GAPDH serving as a loading control. Error bars indicate standard deviation values between two independent experiments.
FIG 10
FIG 10
Effects of partially deleting RNA2.7 on expression of CMA genes and cell movement. (A) Diagram depicting the regions deleted in the RNA2.7 mutants (Δ5′ and Δ3′) in comparison to WT. The RNA2.7-coding region is indicated by a blue arrow, the TATA box by a red line, and the polyadenylation [poly(A)] signal by a yellow line. The deleted regions are marked by gray-shaded rectangles. Numbers indicate the distance (nt) from the transcription initiation site (at 1 nt). (B) HFFF2 cells were infected at an MOI of 5 with WT, Δ5′, Δ3′, ΔRNA2.7, or ΔTATA and CMA transcript levels in RNA harvested at 72 h p.i. were measured by RT-PCR, using GAPDH as a loading control. The data represent one of three independent experiments. RT, reverse transcriptase. (C) HF-Tet cells were infected at an MOI of 5 with UL36-GFP-WT, UL36-GFP-Δ5′ (denoted Δ5′), UL36-GFP-Δ3′ (denoted Δ3′), UL36-GFP-ΔRNA2.7 (denoted ΔRNA2.7), or UL36-GFP-ΔTATA (denoted ΔTATA). Cell movement at 72 to 120 h p.i. was measured by live cell confocal microscopy and tracking analysis. For each experiment, 10 random views of the field were analyzed per sample, resulting in the analysis of >1,700 tracks after excluding low quality tracks. Error bars denote standard deviation values. Significantly different results were grouped using Tukey’s test (columns A, B, and C). (D and E) Expression of the 5′ region (D) and the 3′ region (E) of RNA2.7 determined by RT-qPCR, normalizing levels to GAPDH. In each panel, the data represent three independent experiments, with error bars indicating standard deviation values.
FIG 11
FIG 11
A+U content of mRNAs regulated in association with RNA2.7. (A) The 99 upregulated CMA mRNAs. (B) All 785 upregulated mRNAs and all 146 downregulated mRNAs.
FIG 12
FIG 12
Effects of inhibiting RNA synthesis on persistence of regulated CMA transcripts. HFFF2 cells were infected at an MOI of 5 with WT, Δ5′, Δ3′, ΔRNA2.7 or ΔTATA, and then 12.5 μg/ml actinomycin D (+) or solvent only (−) was added at 72 h p.i. At 120 h p.i., CMA transcript levels were measured by RT-qPCR, normalizing levels to GAPDH: STX3 (A), TPM3 (B), HEBP1 (C), and DAG1 (D). The NT level for each virus was then normalized to 1, and the level in actinomycin D-treated samples was calculated relative to the relevant NT sample. Error bars indicate standard deviation values in four independent experiments.
FIG 13
FIG 13
Effects of nucleotide composition on viral transcripts regulated in association with RNA2.7. HFFF2 cells were infected at an MOI of 5 with WT, ΔRNA2.7, or ΔTATA. Sequence reads generated from polyadenylated RNA isolated at 72 h p.i. were aligned to individual viral CDSs or lncRNA sequences and counted. Transcript expression in mutants compared to WT was determined as log2-fold change (log2FC) values. Differential expression was plotted for all sense transcripts (except RNA2.7) (A), all antisense transcripts (B), regulated sense transcripts only (q < 0.05) (C), and regulated antisense transcripts only (q < 0.05) (D). R and P define the strength and significance of the correlation, respectively.
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

References

    1. Chen G, Wang Z, Wang D, Qiu C, Liu M, Chen X, Zhang Q, Yan G, Cui Q. 2013. LncRNADisease: a database for long-noncoding RNA-associated diseases. Nucleic Acids Res 41:D983–D986. 10.1093/nar/gks1099. - DOI - PMC - PubMed
    1. Fatica A, Bozzoni I. 2014. Long noncoding RNAs: new players in cell differentiation and development. Nat Rev Genet 15:7–21. 10.1038/nrg3606. - DOI - PubMed
    1. DiStefano JK. 2018. The emerging role of long noncoding RNAs in human disease. Methods Mol Biol 1706:91–110. 10.1007/978-1-4939-7471-9_6. - DOI - PubMed
    1. Hu G, Niu F, Humburg BA, Liao K, Bendi S, Callen S, Fox HS, Buch S. 2018. Molecular mechanisms of long noncoding RNAs and their role in disease pathogenesis. Oncotarget 9:18648–18663. 10.18632/oncotarget.24307. - DOI - PMC - PubMed
    1. Font-Cunill B, Arnes L, Ferrer J, Sussel L, Beucher A. 2018. Long noncoding RNAs as local regulators of pancreatic islet transcription factor genes. Front Genet 9:524. 10.3389/fgene.2018.00524. - DOI - PMC - PubMed

Publication types

LinkOut - more resources