Open Access

Identification of novel genes associated with HIV-1 latency by analysis of histone modifications

Human Genomics201711:9

DOI: 10.1186/s40246-017-0105-7

Received: 6 February 2017

Accepted: 4 May 2017

Published: 12 May 2017

Abstract

Background

A reservoir of HIV-1 is a major obstacle in eliminating HIV-1 in patients because it can reactivate in stopping antiretroviral therapy (ART). Histone modifications, such as acetylation and methylation, play a critical role in the organization of chromatin domains and the up- or downregulation of gene expression. Although many studies have reported that an epigenetic mechanism is strongly involved in the maintenance of HIV-1 transcriptional latency, neither the epigenetic control of viral replication nor how HIV-1 latency is maintained is not fully understood.

Results

We re-analyzed a high throughput parallel DNA sequencing (ChIP-seq) data from previous work to investigate the effect of histone modifications, H3K4me3 and H3K9ac, on HIV-1 latency in terms of chromosome distribution. The outputs of ChIP-seq from uninfected CD4+ T cell lines and HIV-1 latently infected cells were aligned to hg18 using bowtie and then analyzed using various software packages. Certain chromosomes (16, 17, 19, and 22) were significantly enriched for histone modifications in both decreased and increased islands. In the same chromosomes in HIV-1 latently infected cells, 38 decreased and 41 increased islands from common islands of H3K4me3 and H3K9ac were selected for functional annotation. In Gene Ontology analysis, the 38 genes associated with decreased islands were involved in the regulation of biological process, regulation of cellular process, biological regulation, and purinergic receptor signaling pathway, while the 41 genes associated with increased islands were involved in nucleic acid binding, calcium-activated cation channel activity, DNA binding, and zinc ion binding. In Pathway Commons analysis, the 38 genes were strongly involved in the p63 transcription factor network, while the 41 genes were involved in the RNA polymerase III transcription termination pathway. Several genes such as Nuclear factor I X (NFIX) and TNF receptor association factor 4 (TRAF4) were selected as candidate genes for HIV latency. Especially, NFIX was highly expressed in HIV-1 latently infected cell lines and showed a dramatic reduction in expression after phorbol-13-myristate-12-acetate (PMA) treatment.

Conclusions

These results show that the unique enrichment of histone modifications and its linked genes in specific chromosomes might play a critical role in the establishment and maintenance of HIV-1 latency.

Keywords

HIV latency Histone modification Chromosome H3K4me3 H3K9ac

Background

HIV-1 can establish a state of latency in the early stages of infection. The integration of viral cDNA into host chromosomes is a fundamental step, after which, viral genomes can persist for the lifespan of infected cell [1]. Despite combination antiretroviral therapy (cART), which can repress HIV-1 replication and delay the progression of AIDS, HIV-1 reemerges rapidly after an interruption in treatment [2, 3]. Due to the long half-life of viral reservoirs, it has been reported that the eradication of HIV-1 with current drugs would require over 60 years [4]. The transcription of HIV-1 genome depends on both viral and cellular factors [5]. The activity of HIV promoter is closely connected to the activation of host cells [6]. Additionally, gene expression of HIV-1 latency can be dynamically regulated through epigenetic changes in chromatin structure surrounding and within integrated HIV-1 provirus [7, 8]. In particular, acetylation and methylation have considered as critical elements of chromatin activity and play a critical role in gene regulation [9]. Recently, Park et al. [10] generated the genome-wide maps of histone modifications for histone 3 lysine 4 trimethylated (H3K4me3) and histone 3 lysine 9 acetylated (H3K9ac) using HIV-1 latently infected cells and uninfected cells. They found that histone modification near HIV-1 integrated regions did not show significantly different patterns compared with control and that the enrichment of histone modification was generally no difference before and after HIV-1 integration. In addition, HIV-1 is able to establish interchromosomal interactions to control viral transcription [11]. Although many studies have reported that an epigenetic mechanism is strongly involved in the maintenance of HIV-1 transcriptional latency [1216], neither the epigenetic control of viral replication nor how HIV-1 latency is maintained is not fully understood.

Here, we re-analyzed chromatin immunoprecipitation-high throughput parallel DNA sequencing (ChIP-seq) data from Park et al. in AIDS [10] to examine the effect of histone modifications on HIV-1 latency in terms of chromosomal distribution and to find novel genes related to HIV-1 latency.

Results

Chromosomal distribution of enriched histone binding sites in HIV-1 latently infected cells

To identify binding sites of histone modifications such as H3K4me3 and H3K9ac, ChIP-seq data was obtained from the Gene Expression Omnibus (GEO) data repositories (GSE58246). Spatial clustering for identification of ChIP-enriched regions (SICER) 1.1 [17] was used to find differentially enriched histone islands. The number of decreased islands at H3K4me3 and H3K9ac histone modifications ranged from 1587 to 13,173 in HIV-1 latently infected cells (ACH2, NCHA1, and J1.1 cells). Increased islands ranged from 2078 to 9875 (Table 1). These results suggest that the binding sites of histone modifications may differ according to cell lines. Next, to determine the binding distribution pattern of H3K4me3 and H3K9ac across individual chromosomes, the cis-regulatory element annotation system (CEAS) software [18] was used with the decreased and increased island data (Fig. 1). Significant chromosomes were determined as those with a p value <104, those with a ratio of histone modification binding percentage to genome background binding percentage on each chromosome >1.3 and those showing both decreased and increased islands together in all HIV-1 latently infected cells. Chromosomes 16, 17, 19, and 22 were selected by these criteria for comparison of decreased and increased islands on the same chromosome (Additional files 1, 2, 3, and 4). The results suggested that histone modifications binding to host genomes are non-random and preferentially bind to specific chromosomes.
Table 1

Numbers of islands identified by SICER 1.1 in HIV-1 latently infected cells according to histone modifications

Cell line

Dec or Inc

Histone modifications

H3K4me3

H3K9ac

ACH2

Dec

1587

3344

Inc

2078

5563

J1.1

Dec

8634

13,173

Inc

6941

9875

NCHA1

Dec

5275

7124

Inc

6622

8084

Dec decreased islands identified by SICER 1.1, Inc increased islands identified by SICER 1.1, ACH2 and J1.1 HIV-1 latently infected cells, NCHA1 novel chronic HIV-1 infected cells derived from A3.01

Fig. 1

Chromosomal distribution of H3K4me3 binding sites in HIV-1 latently infected cells. Enrichment pattern of decreased H3K4me3 islands in individual chromosomes is shown as a bar chart. Percentage of total H3K4me3 islands (red bar) and expected results by random chance (blue bars) for each chromosome is shown. The p value is shown in parentheses

Identification of common decreased and increased islands in chromosomes 16, 17, 19, and 22

We investigated common decreased and increased islands in selected chromosomes of HIV-1 latently infected cells. As a result, we identified 126 and 302 decreased islands in H3K4me3 and H3K9ac, respectively (Fig. 2a). In particular, 38 islands were identified as common decreased islands in both H3K4me3 and H3K9ac (Fig. 2b). Meanwhile, 130 and 164 increased islands were identified in H3K4me3 and H3K9ac, respectively, and 41 islands were identified as common increased islands in both H3K4me3 and H3K9ac. To find out where islands were distributed on each chromosome, the location of 38 decreased and 41 increased islands were visualized on chromosomes 16, 17, 19, and 22 using the idiographica webtool (Fig. 2c). The results suggested that HIV-1 latency may be dominated by common factors.
Fig. 2

Identification of H3K4me3 and H3K9ac islands in chromosomes 16, 17, 19, and 22 of HIV-1 latently infected cells. a Venn diagram of differentially enriched histone modification islands in chromosomes 16, 17, 19, and 22 of HIV-1 latently infected cells. b The differential histone H3K4me3 and H3K9ac islands were compared and the co-occurrence of two histone modification islands was examined. c Human chromosome map showing the localization of 38 decreased and 41 increased genes of islands in chromosomes 16, 17, 19, and 22 of HIV-1 latently infected cells. Genes associated with decreased islands are highlighted in blue, and genes associated with increased islands are highlighted in red

Functional annotation of 38 decreased and 41 increased islands in both H3K4me3 and H3K9ac

First, 38 decreased and 41 increased islands were transformed to genes corresponding to each island (Additional file 5). To investigate the functional annotation of the genes associated with the 38 decreased and 41 increased islands, gene ontology enrichment analysis was performed using the WEB-based GEne SeT AnaLysis Toolkit (WebGestalt) [19]. The 38 genes associated with decreased islands were involved in the regulation of biological process, regulation of cellular process, biological regulation, and purinergic receptor signaling pathway. The 41 genes associated with increased islands were involved in nucleic acid binding, calcium-activated cation channel activity, DNA binding, and zinc ion binding (Additional file 6). Subsequently, Pathway Commons analysis was performed to further investigate the biological pathways of genes associated with decreased and increased islands. The p63 transcription factor network was strongly linked to the 38 genes with decreased islands (Fig. 3a), and the RNA polymerase transcription termination pathway was linked to the 41 genes with increased islands (Fig. 3b). Especially, DNA topoisomerase 2 alpha (TOP2A), integrin beta 4 subunit (ITGB2), TNF receptor association factor 4 (TRAF4), and SEC14-like lipid binding 2 (SEC14L2) genes associated with decreased islands were related to the p63 transcription factor network. While, nuclear factor IC (NFIC) and nuclear factor IX (NFIX) with increased islands were linked to the RNA polymerase transcription termination pathway. To examine interactions between TOP2A, ITGB2, TRAF4, SEC14L2, NFIC, and NFIX, the Pathway Commons Network Visualizer was used (Fig. 4a). NFIX was found to interact with TRAF4, which suggests that genes related to decreased and increased islands can mutually interact in the maintenance of HIV-1 latency.
Fig. 3

Functional annotation of 38 genes associated with decreased (a) and 41 genes associated with increased (b) islands on chromosomes 16, 17, 19, and 22 of HIV-1 latently infected cells using Pathway Commons analysis. TOP2, ITGB2, TRAF4, and SEC14L2 in the 38 genes associated with decreased islands were strongly linked to the p63 transcription factor network. Meanwhile, NFIC and NFIX in the 41 genes associated with increased islands were related to RNA polymerase III transcription termination. The x-axis values are –log10 of raw p values

Fig. 4

Identification of the interaction of NFIX with TRAF4 in HIV-1 latently infected cells. a A visualization of the interactions of TOP2A, ITGB2, TRAF4, and SEC14L2 with NFIC and NFIX by PCViz (Pathway Commons Network Visualizer). The query type can control the size of the network or interactions by filtering genes. The neighborhood in query type shows the overall frequency of alteration for each gene in the network and the paths between in query type shows the direct interaction of each gene in the network. b The result of real-time PCR in treatment with/without PMA in HIV-1 latently infected cells. Cells were treated with PMA at a final concentration of 10 ng/ml for 24 h. All experiments were performed in triplicate. Error bars indicate the standard deviation

Investigation of the interaction between NFIX and TRAF4 for HIV-1 latency

Lastly, the expression of NFIX and TRAF4 was examined using real-time PCR between HIV-1 latently infected cell lines, ACH2 and NCHA1, and an uninfected cell line, A3.01 (Fig. 4b). NFIX was highly expressed in HIV-1 latently infected cell lines compared with the uninfected cell line. The expression of TRAF4 was similar in all cell lines. After treatment by phorbol-13-myristate-12-acetate (PMA), NFIX showed a dramatic reduction in expression (nearly fourfold) in HIV-1 latently infected cell lines compared with untreated cells. TRAF4 was increased threefold in only A3.01 cells but was decreased in NCHA1 cells. These results suggest that NFIX might affect the reactivation and maintenance of HIV-1 latency.

Discussion

In this study, we re-analyzed ChIP-seq data obtained from GEO data repositories to investigate whether specific chromosomal distribution of histone modifications effects on HIV-1 latency and to find novel latency-related genes. As whole distribution of histone modification was unchanged before and after HIV-1 integration [10], chromatin domains which show enriched epigenetic features partially might be potential factors for the establishment or maintenance of HIV-1 latency. To elucidate the connection between chromosomal distribution of histone modification and HIV-1 latency, H3K4me3 and H3K9ac binding distribution patterns were determined using CEAS software. Chromosomes 16, 17, 19, and 22 were significantly enriched in both histone modifications of decreased and increased binding sites.

Accordingly, the alternation of chromatin conditions in host cells induced by HIV-1 infection might play an important role in viral latency. These results indicate that there may be common factors governing HIV-1 latency. Thought genome-wide analysis of histone modifications in HIV-1 latently infected cell lines, cyclin-dependent kinase inhibitor 1A (CDKN1A) and cyclin D2 were given into latency-related genes [10].

Based on Pathway Commons analysis, NFIX from RNA polymerase transcription termination pathway and TRAF4 from p63 transcription factor network were strongly linked to each other.

Nuclear factor one (NFI) is a family of transcription factors which consist of four related members, NFIA, NFIB, NFIC, and NFIX [20]. NFIX is known to bind to the palindromic sequence in viral and cellular promoters [21]. These binding sites may act as activators or repressors of transcription [22].

HIV-1 long terminal repeat (LTR) is comprised of U5, R, and U3 regions. The U3 region can be divided into the core promoter, enhancer, and modulatory regions [23]. The modulatory region includes the negative regulatory element (NRE) [22]. Schwartz et al. [24] has shown that core sequence in the NRE, TGATTGGC, was the binding site for NFI family, and the NFI binding on this site has negative effect on the control of HIV-1 transcription in Jurkat cells. In this study, NFIX showed the increased acetylation (H3K9ac) and methylation (H3K4me3) in HIV-1 latently infected cell lines. These will allow transcription factors to easily access to the promoter of NFIX and increase the mRNA expression level of NFIX in HIV-1 latently infected cells. Consequently, increased NFIX may bind to core sequence in the NRE and then repress the transcription of HIV-1. In addition, CCAAT/enhancer binding protein (C/EBP) was known to be necessary for HIV-1 replication [25] and HIV-1 LTR contains three C/EBP binding sites. NFIX was previously named as CCAAT-binding transcription factor. This will provide a possibility that C/EBP and NFIX may compete for binding sites of HIV-1 LTR each other. Therefore, C/EBP or NFIX binding on HIV-1 LTR will induce or repress HIV-1 transcription, respectively. Lastly, Biressi et al. [26] reported that NFIX is strongly expressed in the fetus and makes a complex with PKC theta and then activates MEF2A. These results suggest that NFIX may negatively control HIV-1 transcription via PKC pathway.

TRAF4 is known to encode a member of the TNF receptor association factor (TRAF) family and interact with neurotrophin receptor p75 (NTR). Also, it negatively controls NTR-induced cell death and NF-kappa B activation [27, 28]. Meanwhile, Xu et al. [29] showed that co-expression of p47 (phox) and TRAF4 increase oxidant production and c-Jun N-terminal kinase (JNK) activation and that HIV-1 Tat activates JNK via signaling pathway at the level of TRAF4. In contrast to NFIX, TRAF4 showed the decreased (H3K9ac) and methylation (H3K4me3) on HIV-1 latency. As a result, the decreased expression of TRAF4 may reduce activity of JNK to maintain HIV-1 latency. However, TRAF was not seen to directly control the expression of NFIX in our study.

Conclusions

In conclusion, these results suggest that the unique enrichment of histone modifications and its linked genes in specific chromosomes might play a critical role in the establishment and maintenance of HIV-1 latency.

Methods

Cell culture

A3.01, ACH2, and NCHA1 cells were maintained in RPMI 1640 medium supplemented with 10% FBS, 5% penicillin-streptomycin, and 2 mM glutamine. For comparison of NFIX expression between the normal and reactivation state, PMA was used at a final concentration of 10 ng/ml for 24 h.

ChIP-seq data analysis

To analysis of histone modifications for H3K4me3 and H3K9ac in HIV-1 latently infected cells, ChIP-seq data was obtained from GEO data repositories (GSE58246). Enriched histone islands of the genome were identified by comparing the chromatin immunoprecipitated (ChIPed) samples to the input samples using the SICER 1.1 program with the following parameters: window size = 200, gap size = 400, E value = 0.01, and FDR = 0.05. The overlapped histone islands were identified by hypergeometric optimization of motif enrichment (HOMER) programs [30] with maximum distance to merge (“given”). For genomic distribution of differential binding sites, CEAS program was used. Genomic position was plotted onto the chromosome map using the idiographica webtool (http://www.ncrna.org/idiographica). Gene ontology enrichment analysis was performed using WebGestalt, and interaction of genes was visualized using the Pathway Commons Network Visualizer (PCViz, http://www.pathwaycommons.org/pcviz).

Quantitative real-time PCR

Total RNA was extracted from cells using TRIzol reagent, and 1 μg of RNA was reverse-transcribed using Superscript III cDNA synthesis kit (Invitrogen). NFIX and TRAF4 quantitative reverse transcription PCR was performed on a 7500 real-time PCR system (Applied Biosystems) using SYBR Green PCR Master Mix (Applied Biosystems). The relative expression was calculated as follows using the ΔΔCt method: fold change of enrichment = 2 delta ((Ct-ChIPed)-(Ct-Input)). ΔCt values were determined using a the 7500 real-time PCR system software (Applied Biosystems) with GAPDH as an endogenous control. The following primers were used for real-time PCR:
  • NFIX forward primer (5′-AGGAGATGCGGACATCAAA-3′), NFIX reverse primer (5′-TACTCTCACCAGCTCCGTCA-3′), TRAF4 forward primer (5′-AGGAGTTCGTCTTTGACACCATC-3′), TRAF4 reverse primer (5′-CTTTGAATGGGCAGAGCACC-3′), GAPDH forward primer (5′-GAAGGTGAAGGTCGGAGTC-3′), and GAPDH reverse primer (5′-GAAGATGGTGATGGGATTTC-3′).

Abbreviations

ART: 

Antiretroviral therapy

cART: 

Combination antiretroviral therapy

CDKN1A

Cyclin-dependent kinase inhibitor 1A

CEAS: 

Cis-regulatory element annotation system

ChIPed: 

Chromatin immunoprecipitated

ChIP-seq: 

Chromatin immunoprecipitation-high throughput parallel DNA sequencing

H3K4me3: 

Histone 3 lysine 4 trimethylated

H3K9ac: 

Histone 3 lysine 9 acetylated

HOMER: 

Hypergeometric optimization of motif enrichment

ITGB2

Integrin beta 4 subunit

NFIX

Nuclear factor IX

PMA: 

Phorbol-13-myristate-12-acetate

SEC14L2

SEC14-like lipid binding 2

SICER: 

Spatial clustering for identification of ChIP-enriched regions

TOP2A

DNA topoisomerase 2 alpha

TRAF4

TNF receptor association factor 4

WebGestalt: 

WEB-based GEne SeT AnaLysis Toolkit

Declarations

Acknowledgements

We thank Tae-Young Roh (Pohang University of Science and Technology) and Jihwan Park (Pohang University of Science and Technology) for access to epigenetics data.

Funding

This research was supported by a grant from Research of Korea Centers for Disease Control and Prevention (Grant No. 2016-NG51003-00).

Availability of data and materials

The datasets supporting the results of this article are available in the Gene Expression Omnibus (GEO) repository (http://www.ncbi.nlm.nih.gov/geo/) under accession number GSE58246.

Authors’ contributions

KCK and BSC conceived and designed the experiments. JSS, YHS, and CHY performed the experiments. SYL and CK analyzed the data. KCK and BSC wrote the manuscript. All authors read and approved the final manuscript.

Competing interests

The authors declare that they have no competing interests.

Consent for publication

Not applicable

Ethics approval and consent to participate

Not applicable

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Authors’ Affiliations

(1)
Division of AIDS, Center for Immunology and Pathology, Korea National Institute of Health

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Copyright

© The Author(s). 2017

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