University of Southern California Dissertations and Theses

Epigenomic analyses of Kaposi's sarcoma-associated herpesvirus

(USC Thesis Other)

Epigenomic analyses of Kaposi's sarcoma-associated herpesvirus

PDF

Download

Open document

Flip pages

Download a page range

Download transcript

Copy asset link

Request this asset

Transcript (if available)

Content Copyright 2020

EPIGENOMIC ANALYSES OF
KAPOSI’S SARCOMA-ASSOCIATED HERPESVIRUS

by

Yun Kyung Park

A Dissertation Presented to the
FACULTY OF THE USC GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
MEDICAL BIOLOGY

August 2020

ii

Acknowledgements
I would like to express the deepest gratitude to my advisor, Dr. Jae U. Jung. He gave me
the opportunity to volunteer in his lab during my undergraduate years and mentored me ever
since. He continuously taught me the importance of thinking out of the box and being adventurous
in science. It was a privilege to be a part of Dr. Jung’s lab and train under him. I thank him for his
enthusiasm, motivation, encouragement, knowledge and warm heart.
I would like to thank my committee members, Drs. Keigo Machida and Peggy Farnham,
for their insightful comments and challenging questions. My thanks also go to Drs. Young-ki Choi
(Chungbuk University, South Korea), Un Yung Choi and Soohwan Oh, and Kyle Jung for the
extensive and productive collaboration. My appreciation also extends to all of the current and past
members of Dr. Jung’s lab (“Team JJ”) for the stimulating discussions and deep friendships.
Last but not least, I am extremely grateful to my family, who are the champions of my
world, for their endless support and love. My accomplishments would not have been possible
without them. This degree, and all the good things that will come from it, are because of them.

iii

TABLE OF CONTENTS
Acknowledgements ………………………………………………………………………...………….... ii
List of Tables …….………………………………………………………………………….....….……... v
List of Figures ….….…………………...………………………………………………….....…………. vi
Abstract ………………………………………………..……………………………...………..….....… vii
Chapter 1. KSHV overview ……………………………………………………………………...……… 1
1.1 Human herpesviruses ………………………………………………………………………….. 1
1.2 KSHV-associated disease and therapy ……………………………………………….……… 1
1.3 Genome organization ………………………………………………………………………….. 2
1.4 KSHV lifecycle ………………………………………………………………………………….. 4
1.4.1 KSHV latency …………………………………………………………………………... 6
1.4.2 KSHV lytic replication ………………………………………………………………….. 6
Chapter 2. KSHV epigenetics ……………………………………………………………………..…... 8
2.1 Epigenetics and epigenomics …………………………………………………………….…... 8
2.1.1 Tools used for epigenomic studies ………………………………………………..…. 8
2.1.2 Viral epigenetics ……………………………………………………………………..… 9
2.2 Dynamic chromatin landscape of KSHV genome …………………………………………... 9
2.2.1 de-novo Infection and Establishment of Latency ………………………………….. 10
2.2.2 Reactivation into Lytic Replication ………………………………………….………. 11
2.3 KSHV-mediated host epigenome reprogramming …………………………………………. 12
Chapter 3. Global analysis of KSHV-mediated host reprogramming …………………………….. 14
3.1 Introduction ……………………………………………………………………….....………… 14
3.1.1 Gene regulation by enhancers …………………………………………………….… 14
3.1.2 Super-enhancer and enhancer RNA …………………………………………….…. 14
3.1.3 Enhancer identification methods ……………………………………………………. 16
3.2 Results …………………………………………………………………………………...…….. 18
3.2.1 Global reduction of host enhancer activity upon KSHV reactivation ………….…. 18
3.2.2 Identification of nascent viral and host gene transcription …………………….….. 21
3.2.3 Reduction of global eRNA expression upon KSHV reactivation ……………….… 26
Chapter 4. KSHV-mediated MYC enhancer regulation ………………………………………….… 27
4.1 Introduction …………………………………………………………………………...……….. 27
4.1.1 Enhancer regulation of MYC ………………………………………………………… 27
4.1.2 MYC and KSHV lifecycle …………………………………………………………….. 27
4.1.3 MYC regulation by EBV ……………………………………………………………... 28
4.2 Results …………………………………………………………………………………………. 28
4.2.1 Identification of MYC super-enhancers and eRNAs in PELs ……………………. 28
4.2.2 MYC eRNA regulation upon KSHV lytic induction ………………………………... 32
4.2.3 Functional role of MYC super-enhancers in PELs ..……….………………………. 33
4.2.4 Potential roles of cellular IRF4 and viral IRF4 in MYC eRNA expression …….… 37
iv

Chapter 5. Discussion and future direction …………………………………………………………. 40
Chapter 6. Materials and methods …………………………………………………………………… 44
References ………………………………………………………………….………………………….. 53
Addendum. KSHV epigenome in oral Kaposi’s Sarcoma ………………………………………..… 61
Abstract …………………………………………………………………………………………….. 62
Introduction ………………………………………………………………………………………… 63
Aim 1. Differential regulation of KSHV 3D genomic structure and gene expression ………. 68
Aim 2. Host and viral gene regulation in 3D organotypic raft culture model ………………… 80
Conclusion ………………………………………………………………………………………..... 94
References ……………………………………………………………………………………….... 96

v

List of Tables
Table 1. Human herpesviruses ……………………………………………………………………….... 1
Table 2. Primers used for qPCR assays ………………………...…………………………………... 52
Table 3. Primers used for 4C-seq assays ……………………...……………………….…………... 52
Table 4. shRNA and sgRNA sequence ………………………...…………………….……………... 52

vi

List of Figures
Figure 1.1 KSHV episome ……………………………………………………………………………... 3
Figure 1.2 KSHV life cycle …………………………………………………………………………...… 5
Figure 2-1 Epigenetic regulation of latent and lytic states in KSHV ……………………...……..… 10
Figure 2-2 Epigenetic regulation is essential for transformation by oncoviruses ……………….. 13
Figure 3-1 eRNA-driven gene regulation in cis …………………………………………………..… 16
Figure 3-2 Identification of active enhancers using H3K27ac and H3K4me1 ChIP-seq ………. 19
Figure 3-3 Host genes controlled by super-enhancers ………………………………………….… 20
Figure 3-4. Identification of nascent viral RNA from GRO-seq …………………………………… 21
Figure 3-5. Identification of nascent host RNA from GRO-seq …………………………………… 24
Figure 3-6. Gene set enrichment analysis (GSEA) of GRO-seq data upon KSHV reactivation.. 25
Figure 3-7. Reduction of global enhancer RNAs upon KSHV reactivation ……………………… 26
Figure 4-1. KSHV+ PEL cell lines show potential MYC super-enhancers ………………………. 30
Figure 4-2. Various sequencing results confirm MYC super-enhancer activity …………………. 31
Figure 4-3. KSHV reactivation leads to reduction in MYC enhancer activity ……………………. 32
Figure 4-4. Disruption of MYC super-enhancers leads to KSHV reactivation …………………… 34
Figure 4-5. BRD4 inhibition leads to disruption of MYC enhancer ………………………………... 36
Figure 4-6. Role of IRF4 in PEL enhancer activity ………………………………………………….. 38
Figure 5-1. Global level of histone modifications upon KSHV reactivation …………………….… 40
vii

Abstract
Enhancers play indispensable roles in cell proliferation and survival through
spatiotemporally regulating gene transcription. Active enhancers and super-enhancers often
produce noncoding enhancer RNAs (eRNAs) that precisely control RNA polymerase II activity.
Kaposi’s sarcoma-associated herpesvirus (KSHV) is a human oncogenic gamma-2
herpesvirus that causes Kaposi’s sarcoma and primary effusion lymphoma (PEL). It is well
characterized that KSHV utilizes host epigenetic machineries to control the switch between
two lifecycles, latency and lytic replication. However, how KSHV impacts host epigenome at
different stages of viral lifecycle is not well understood. Using global run-on sequencing (GRO-
seq) and chromatin-immunoprecipitation sequencing (ChIP-seq), I profiled the dynamics of
host transcriptional regulatory elements during latency and lytic replication of KSHV-infected
PEL cells. This revealed that a number of critical host genes for KSHV latency, including MYC
proto-oncogene, were under the control of super-enhancers whose activities were globally
repressed upon viral reactivation. The eRNA-expressing MYC super-enhancers were located at
downstream of the MYC gene in KSHV-infected PELs and played a key role in MYC expression.
RNAi-mediated depletion or dCas9-KRAB CRISPR inhibition of eRNA expression significantly
reduced MYC mRNA level in PELs, as did the treatment of an epigenomic drug that globally
blocks super-enhancer function. Finally, while cellular IRF4 acted upon eRNA expression and
super-enhancer function for MYC expression during latency, KSHV viral IRF4 repressed cellular
IRF4 expression, decreasing MYC expression and thereby, facilitating lytic replication. These
results indicate that KSHV acts as an epigenomic driver that modifies host epigenomic status
upon reactivation by effectively regulating host enhancer function.
1

Chapter 1. KSHV overview
1.1 Human herpesviruses
Herpesviridae is a large family of DNA viruses in animals and humans. Herpesvirus virions
range from approximately 100-200 nm in diameter and contain large double-stranded DNA
genomes with 70-200 predicted open reading frames, giving the highest gene diversity among all
human viruses (Davison et al., 2009). Among 67 Herpesviridae, eight are known to infect humans:
Human Herpesvirus (HHV) 1-8. Based on their tropism and properties, they are grouped into three
subfamilies: α, β, and γ (Table 1) (Davison, 2010). It should be noted that γ-herpesviruses (EBV
and KSHV) are the only cancer-inducing herpesviruses.

Table 1: Human Herpesviruses
Name Subfamily Synonym Associated diseases
HHV-1 α Herpes simplex virus 1 (HSV-1) Cold sore
HHV-2 α Herpes simplex virus 2 (HSV-2) Genital sore
HHV-3 α Varicella zoster virus (VZV) Chicken pox, shingles
HHV-4 γ Epstein-Barr virus (EBV) Mononucleosis, Burkitt’s lymphoma
HHV-5 β Cytomegalovirus (CMV) Birth defects, childhood fever, others
HHV-6 β Human herpesvirus 6 Roseola, childhood rash
HHV-7 β Human herpesvirus 7 Fever, rash, diarrhea
HHV-8 γ Kaposi’s sarcoma-associated
herpesvirus (KSHV)
Kaposi’s sarcoma (KS), primary
effusion lymphoma (PEL), multicentric
Castleman’s disease (MCD)

1.2 KSHV-associated diseases and therapy
KSHV is a γ-herpesvirus that induces malignancies that often occur in immunosuppressed
individuals such as patients with HIV or transplant, making KSHV infection a global health concern
(Y. Chang et al., 1994). Kaposi’s sarcoma (KS) is an endothelial cancer characterized by KSHV-
infected spindle cells, infiltration of inflammatory cells, and high angiogenesis. While KS is
primarily recognized as an AIDS-defining malignancy, it also occurs in older Mediterranean men
2

(classic KS), transplant recipients (iatrogenic KS) and sub-Sharan Africans (endemic KS) (Schulz,
1999).
KSHV is also linked with two rare lymphoproliferative disorders that are also common in
HIV-infected patients: primary effusion lymphoma (PEL) and multicentric Castleman's disease
(MCD) (Cesarman, Chang, Moore, Said, & Knowles, 1995; Oksenhendler et al., 2002). PEL is
rare, but aggressive and has poor prognosis. Also known as body cavity lymphoma, PEL is a B-
cell non-Hodgkin lymphoma that is characterized by effusions of proliferating plasmablast-like
cells in pleural, pericardial and abdominal spaces (Okada, Goto, & Yotsumoto, 2014). 90% of PEL
cases are associated with EBV coinfection (Gloghini et al., 2017). Lastly, KSHV causes MCD
which is a non-neoplastic B-cell lymphoproliferative disorder that involves multiple regions of
lymphadenopathy and often severe complications (Katano & Sata, 2000).
Since the discovery of KSHV in 1994, there is still no clear standard of treatment for KSHV-
associated malignancies. While the treatment of HIV with highly active antiretroviral therapy
(HAART) has effectively decreased the prevalence of KSHV-associated malignancies, about a
third of HIV-associated KS cases still occur in such a group of successfully treated HIV patients
(Schneider & Dittmer, 2017). Radiotherapy, immunotherapy and chemotherapy are also used to
treat KSHV-associated diseases, but the prognoses of PEL and MCD remain poor (6 months and
2 years, respectively) (Gonçalves, Uldrick, & Yarchoan, 2017). There are still no therapies
available that specifically target KSHV itself.

1.3 Genome organization
The KSHV genome is a linear double-stranded DNA that consists of ~140 kb of unique
coding sequence with 25-30 kb of repetitive terminal repeats (TR) composed of 35-45 copies of
GC rich, 801 bp sequence (Renne, Lagunoff, Zhong, & Ganem, 1996; Russo et al., 1996) (Figure
1-1). The TR plays a critical role in tethering viral genome to the host chromosome during cell
division for efficient segregation. The KSHV open reading frames (ORFs) are labeled in the order
3

from left to right, and the ORFs that are unique to KSHV and not to other herpesviruses are
designated “K” labeling, starting from K1 to K15. KSHV encodes at least 86 proteins that promote
oncogenesis, modulate host immunity, hijack host mechanisms, package virions and many more,
allowing efficient survival within the host (Moore & Chang, 2003; Russo et al., 1996). KSHV also
produces non-coding RNAs (ncRNAs) and micro-RNAs (miRNAs) that contribute to viral
pathogenesis (Gottwein, 2012).

Figure 1-1. KSHV episome

White blocks labeled “ORF-” are genes conserved in other herpesviruses, and dark grey blocks
labeled “K-” are genes that are specific to KSHV. The arrowhead indicates direction of the genes.
Terminal repeats are flanked by the beginning and end of the KSHV genome, K1 and K15,
respectively. Figure adapted from reference (Brulois et al., 2012; Uppal, Jha, Verma, & Robertson,
2015)

0
10K
20K
30K
40K
50K
60K
70K
80K
90K
100K
110K
120K
130K
140K
150K
160K
ORFs 16-48
Z8
Terminal Repeats
ORFs 58-69
Z2
ORFs 4-11
74-75
52-56
LANA
K10 K9ORF57
K10.5
miRNAs
K3
K1
K14
vcyclin
K5
K8
K2
vFLIP
K11
K7
K6
K4
K8.1
kaposins
K15
RTA
nt 83527
KSHV episome
KSHV episome
(140kb)
4

1.4 KSHV lifecycle
Like other herpesviruses, KSHV life cycle consists of two phases, latent and lytic,
differentiated by complex but characteristic gene expression patterns (Figure 1-2). Upon cell entry,
KSHV genome is transported into the nucleus and its fate is determined: persistent latent
replication or transient lytic replication. If the virus establishes latency, it avoids host immune
response for efficient survival. However, if latency is disrupted or the virus fails to establish latency,
the virus enters lytic replication, leading to cell destruction and viral particle release to infect new
cells. Several environmental factors such as hypoxia, oxidative stress and epigenetic modifiers
have been shown to reactivate the virus in vitro, and immunosuppression and other co-infections
can trigger reactivation in vivo (Purushothaman, Dabral, Gupta, Sarkar, & Verma, 2016; Thakker
& Verma, 2016). The balance between the two phases of viral lifecycle is crucial for both the virus
and the host. Lytic replication is necessary to sustain enough number of latently infected cells that
would otherwise lose viral particles during cell division. In fact, while the majority of the KSHV-
infected cells in KSHV-associated malignancies are in latent phase, it has been established that
the presence of cells that undergo lytic replication, which make up about 1-3% of total infected
cells, is necessary for tumorigenesis (Staskus et al., 1997).

5

Figure 1-2. KSHV life cycle

Upon viral entry into the nucleus, the virus’s fate is divided into two: latent (in red) or lytic (blue)
infection. During latency, KSHV genome persists as non-integrated, circular episome in the
nucleus. Only the genes located in the major latent locus are expressed, with LANA (ORF73) as
the major regulator of latency. LANA protein also acts as a bridge that connects the terminal
repeat (TR) of the viral genome and the host chromatin to prevent the viruses from being lost
during cell division. Under specific conditions such as hypoxia, cell stress, co-infection and
chemical stimulation, the virus reactivates from latency into lytic replication. RTA encoded by
ORF50 is the key switch regulator that controls reactivation. With orchestrated expression of lytic
genes, from immediate early to early to late, the linear viral genomes are packaged into virion
particles that lyse the cells upon exit. Sometimes lytic replicating virus fails to complete the lytic
cycle and enters abortive state.

cytoplasm
nucleus
Immediate early
(IE)
Early
(E)
Late
(L)
Viral DNA replication
• DNA replication factors
• Immune system modulators
• Structural proteins
• Virus assembly
180kb genome
90 proteins
12 miRNAs
ncRNAs
Major latency
locus
Lytic
Latent
abortive
reactivation
•LANA
• Circular viral DNA associated with chromatin
• Expression of a subset of viral genes, which are
required for the maintenance of the episome
Host
chromatin
Lana
Major lytic
locus
TR
•RTA
•transcription factors
• Epigenetic factors
• Co-infections
• Cellular stress
• Hypoxia
6

1.4.1 KSHV latency
Latency is a defining feature of herpesviruses in which the linear viral genome circularizes
in the nucleus to form an episome and recruits histones from the host for chromatinization (Speck
& Ganem, 2010). In order to remain persistent with a limited genome copy number, latent viral
DNA utilizes cellular DNA polymerase and replicates from the multiple origins of replication (ori-
P) located in the TR (Lin et al., 2003). The majority of the viral genes are repressed during latency
to prevent the virus from going into lytic replication. Only a small number of genes in the latent
locus that play a role in host immune evasion and cell proliferation are expressed: ORF73
(latency-associated nuclear antigen, LANA), ORF72 (v-Cyclin), ORF71/K13 (FLICE-inhibitory
protein, v-FLIP), K12/Kaposin (Kaposin A/B/C) and about 12 microRNAs (miRNAs) (Kedes,
Lagunoff, Renne, & Ganem, 1997; Rainbow et al., 1997). LANA is the most crucial regulator of
latency, and is required for both replication and segregation of the viral genome during cell cycle
as it physically tethers the viral DNA to the host chromosome. In addition, LANA directly inhibits
lytic program by binding onto lytic gene promoters to prevent them from turning on (Uppal,
Banerjee, Sun, Verma, & Robertson, 2014).
As mentioned, KSHV latent genes manipulate host immune surveillance to promote
tumorigenesis. For instance, LANA inhibits p53 and pRb and activates c-Myc to promote growth
and survival of the infected cells, vCyclin interacts with CDK6 to induce cell cycle progression,
and vFLIP inhibits Fas ligands-induced apoptosis and activates NF-κB pathways to promote cell
survival. Lastly, KSHV miRNAs control IFN signaling to suppress antiviral immunity, or promote
endothelial cell migration and angiogenesis (Cousins & Nicholas, 2014; Guasparri, Keller, &
Cesarman, 2004; Lu et al., 2012; Moore & Chang, 1998; Qin, Li, Gao, & Lu, 2017)

1.4.2. KSHV lytic replication
Once latency is disrupted, KSHV reactivates and begins to express a cascade of lytic gene
products in three consecutive stages: immediate-early (IE), early (E), and late (L)—leading to
7

production of virion particles. Immediate-early genes are the first sets of genes that express and
are independent of other viral proteins. They usually encode proteins that alter the expression of
viral and host genes for cell cycle regulation and immune modulation. Early gene products are
involved in viral genome replication and viral DNA synthesis. Lastly, late genes produce viral
structural proteins that are needed for virion assembly (J. Chang, Renne, Dittmer, & Ganem, 2000;
J. Chen, Ueda, Sakakibara, Okuno, & Yamanishi, 2000; Lukac, Renne, Kirshner, & Ganem, 1998;
Sun et al., 1998; Zhu, Chong, Wu, & Yuan, 2005).
The IE gene ORF50 encodes Replication and Transcription Activator (RTA) that is
necessary and sufficient to initiate lytic replication. The multifunctional RTA transactivates by
directly binding to target viral promoters and turning on transcription, or by interacting with several
cellular and viral factors to indirectly induce transcription (Hair, Lyons, Smith, & Efstathiou, 2007).
Following RTA expression, extensive viral gene expression and viral DNA replication occurs,
resulting in successful viral particle production and propagation. Yet, KSHV reactivation is an
extremely complicated and heavily regulated process that requires many host and viral factors.
While the change in KSHV gene expression upon reactivation is well understood, only few
evidences show reactivation-induced global host reprogramming. Previously, Glaunsinger et al.
revealed that KSHV ORF37 encodes SOX (host shutoff and alkaline exonuclease) protein which
interacts with host translation machinery and shuts off the majority of host gene expression in the
early stage of infection in order to support viral replication (Glaunsinger, Chavez, & Ganem, 2005).
On the other hand, it was recently found that RTA rapidly induces several host genes that are
crucial for driving KSHV lytic cycle (Papp et al., 2019). Nevertheless, it is clearly suggested that
KSHV drives host and viral reprogramming by utilizing several host machineries.

8

Chapter 2. KSHV epigenetics
2.1 Epigenetics and epigenomics
Eukaryotic cells organize their genetic material into chromatin, which is a DNA-protein
complex that limit the accessibility of genomic sequences in order to control gene expression.
Chromatin dynamics in response to external stimuli and developmental cues play a crucial role
in fine-tuning gene transcription. Epigenetics is defined as sequence-independent heritable
changes of the chromatin that regulates gene network, such as DNA methylation, nucleosome
positioning, histone modification non-coding RNAs, and 3D chromatin remodeling. Disruption of
such epigenetic regulations lead to profound changes on chromatin accessibility and
occupancy, leading to changes in gene expression and ultimately changing cell fate.
While ‘epigenetics’ refers to these modifications that happen in a gene or sets of genes,
‘epigenomics’ refers to the study of genome-wide profiling of these epigenetic modifications.
Therefore, epigenome determines cell identity and overall expression profile. Together with
transcriptomics (study of the RNA molecules), genomics (study of the DNA sequences),
proteomics (study of the proteins) and metabolomics (study of the metabolites), they make up
functional genomics that integrates information from various components of the biological
system to gain a holistic understanding of a particular phenotype.

2.1.1 Tools used for epigenomic studies
The novel DNA sequencing method, also known as next-generation sequencing (NGS) or
high-throughput sequencing, has revolutionized every scientific fields, including virology. It
enabled us to identify epigenetic marks at a genome-wide level at high-resolution and high-
throughput. A more precise mapping of epigenome has been achieved by using a variety of novel
sequencing-based assays such as DNA methylation profiling (MeDIP-seq), DNA-binding protein
profiling (ChIP-seq), accessible chromatin sequencing (formaldehyde-assisted isolation or
9

regulatory elements; FAIRE-seq), and DNA-DNA interaction profiling (chromosome conformation
capture methods; 3C). Combined with the development of high-computational techniques and
bioinformatics, these genome-wide epigenomic tools have enabled comprehensive
understanding of the role of the epigenome in human diseases.

2.1.2 Viral epigenetics
Herpesviruses have developed ways to hijack cell processing machinery to provide ideal
environment for their viral state. And like other herpesvirus members, KSHV lifecycle is heavily
regulated by epigenetic modifications. Not only does a virus recruit host epigenetic factors onto
its own genome to modulate viral gene expression at different stages of lifecycle, it also
reprograms the host gene expression by producing viral proteins that act upon the host
epigenome. Therefore, understanding the complex interplay between host and viral epigenome
remains as a crucial research area to control viral infections in vivo.

2.2 Dynamic chromatin Landscape of KSHV genome
Since treating latently infected cells with chromatin-modulating chemicals such as DNA
demethylase and histone deacetylase inhibitors (HDACi) reactivates KSHV, it is clear that
epigenetic regulation is crucial in regulating KSHV lifecycle (J. Chen et al., 2001; Lu et al., 2003).
The dynamic epigenetic modifications of the KSHV genome during latency and lytic replication
are characterized below (Figure 2-1).
10

Figure 2-1. Epigenetic regulation of latent and lytic states in KSHV

Upon primary infection, promoters at both latent and lytic genes acquire activating histone marks
such as H3K4me3 and H3ac, resulting in expression (top panel). Upon establishment of latency,
lytic gene promoters acquire H3K27me3 and H2AK119ub repressive marks, often leaving them
at bivalent state where both activating and repressive marks are co-existing (bottom panel). Upon
reactivation, repressive histone modifications are removed, resulting in gene expression. Figure
adapted from reference (Uppal et al., 2015).

2.2.1 de-novo Infection and Establishment of Latency
Upon primary infection, linear histone-free KSHV genome circularizes and becomes
organized into nucleosome structure, or episome. The KSHV episome initially organizes into an
open euchromatin state, characterized by H3K4me3 and H3K27ac histone marks, allowing
expression of a few IE genes, including ORF50 (RTA). Then, the viral genome tries to establish
latency by adding on polycomb repressive complex (PRC)-mediated H3K27me3 and H2AK119ub
repressive histone marks (Figure 2-1). During latency, latent genes like ORF73 (LANA) maintain
H3K4me3 and acH3 activation marks while immediate early and early genes like ORF50 (RTA)
display bivalent chromatin, defined by the coexistence of both the active H3K4me3 and the
11

repressive H3K27me3. In contract, late genes only have repressive H3K9me3 and H3K27me3,
indicating tight repression (Toth et al., 2013). During latency, approximately 8% of the KSHV
genome is associated with the open chromatin regions, while the rest of the genes show closed
chromatin conformation (Hilton et al., 2013). Also, bisulfite sequencing of latently infected BCBL-
1 PEL cells show IE gene promoter DNA sequences to be highly methylated, suggesting DNA
methylation as one of the mechanisms of maintaining latency (J. Chen et al., 2001). More recently,
it was found that like other herpesviruses, the latent KSHV episome is compartmentalized into
different chromatin domains which involves DNA-DNA looping mechanism mediated by cellular
factors such as CTCF and cohesin complex. Specifically in KSHV, there is a genomic looping that
connects the latency locus to the RTA promoter, which physically prevents RTA expression (H.
S. Chen, Wikramasinghe, Showe, & Lieberman, 2012; Kang, Wiedmer, Yuan, Robertson, &
Lieberman, 2011).

2.2.2 Reactivation into Lytic Replication
Upon reactivation, several epigenetic changes occur on the KSHV genome that allow
expression of lytic genes. Because RTA promoter is heavily repressed by HDAC, treatment with
HDAC inhibitor effectively removes the repressive histone marks, rapidly activating it (Shin,
DeCotiis, Giron, Palmeri, & Lukac, 2014). RTA-mediated reactivation leads to dissociation of the
PRC from IE and E genes to decrease H3K27me3 level, increasing H3Ac and H3K4me3 levels
(Günther & Grundhoff, 2010; Toth et al., 2010). This shift allows RTA to recruit cellular cofactors
and histone activation enzymes such as histone acetyltransferases (HATs) to turn on the rest of
the viral lytic program. Also, the viral ncRNA, PAN RNA, serves as a guide RNA that brings
chromatin remodeling enzymes such as H3K4me3 methyltransferase and H3K27 histone
demethylase to the promoters of RTA and other lytic genes to release repressive marks (Rossetto
& Pari, 2012; Rossetto & Pari, 2014). Lastly, it was recently found that lytic-specific genomic
looping between PAN RNA gene locus and K12 locus via RTA-response element allows for
12

efficient usage of replication complex and activation of promoters, indicating that 3D genomic
structure of the viral genome changes upon reactivation (Campbell et al., 2018).

2.3 KSHV-mediated host epigenome reprogramming
Oncogenic viruses function at the epigenetic level to convert normal host cells into cancer
cells. The viral oncoproteins utilize host cellular machinery to reprogram the epigenetic landscape
of the host genome (Figure 2-2). The changes in host gene expression profile lead to cellular
transformation and higher viral replication. Thus, a better understanding of the relationship
between viral proteins and host epigenetic factors may be crucial in characterizing the initial virus-
induced tumorigenesis and identifying molecular targets for cancer therapy.
KSHV infection of endothelial cells results in transcriptional reprogramming that allows the
switch between lymphatic and blood vessel endothelial cells, or even the transition to
mesenchymal cells (H. H. Chang & Ganem, 2013; Cheng et al., 2011). KSHV infection of B cells
lead to the development of the primary effusion lymphoma (PEL), which show disruption of the B-
cell specific transcriptional program. Protein expression of several transcription factors that are
essential for B-cell development is significantly altered in PEL cells compared to uninfected B-
cells (Arguello et al., 2003). These observations imply that viral factors target cell type-specific
transcription factors to alter host gene expression profile. Some studies have suggested the
involvement of epigenetic reprogramming by latent and lytic viral factors. For example, during
latency, LANA recruits DNA methyltransferases to cellular promoters such as that of TGF-β type
II receptor to repress gene expression (Di Bartolo et al., 2008). Also, lytic PAN RNA
downregulates the expression of many immunomodulatory genes by binding to gene promoters
and recruiting different histone modifying enzymes (Rossetto & Pari, 2014).
13

Figure 2-2. Epigenetic regulation is essential for transformation by oncoviruses

Upon cell entry, oncovirus expresses proteins that interact with host epigenetic factors to activate
or silence host genes. This change in gene expression profile leads to leading to cellular
transformation. Both viral and host epigenetic factors have been suggested as therapeutic targets.
Figure adapted from (El-Araby et al., 2016)

Oncovirus
Viral epigenetic
factors
Inducers Repressors
Host epigenetic
factors
Host genome
Transcription
activation
Transcription
silencing
Transformation
Therapeutic
target
Therapeutic
target
14

Chapter 3. Global analysis of KSHV-mediated host reprogramming
(The work described in this chapter has been published in Park et al. (2020). Global epigenomic
analysis of KSHV-infected primary effusion lymphoma identifies functional MYC super-
enhancers and enhancer RNAs. Proceedings of the National Academy of Sciences of the
United States of America)

3.1 Introduction
3.1.1 Gene regulation by enhancers
Cell type-specific biology is epigenetically controlled by gene regulatory elements that are
comprised of promoters and enhancers, and by the transcription factors (TFs) that bind to these
DNA elements. With the help of TFs, distal enhancers physically interact with promoters, and this
looping and the networking among TFs and recruited cofactors leads to transcriptional activation
of target genes (Schoenfelder & Fraser, 2019; Shlyueva, Stampfel, & Stark, 2014). While
promoter includes transcription start site (TSS) and provide basic expression of a gene, enhancer,
sometimes up to 1 Mb way from its interacting promoter, can increase gene expression regardless
of their distance or orientation from the promoter (Lettice et al., 2003). While housekeeping genes
are regulated by simple promoters, many developmental and tissue-specific genes are regulated
by one or more enhancer elements (Zabidi et al., 2015). Recently, NGS technologies have
enabled the identification of differences between enhancer elements of tumor and normal cells,
revealing the role of enhancer malfunction in tumorigenesis.

3.1.2 Super-enhancer and enhancer RNA
Super-enhancers are clusters of enhancers that span large regions of DNA and drive very
high or stable level of expression of the target genes. They are often found close to genes that
define cell fate (Whyte et al., 2013), and are enriched for Mediator (Med) which mediates the
interaction between TFs and RNA polymerase II (RNAPII). There are considerable evidences
indicating that in cancer, super-enhancers are present near oncogenes essential for cell survival
15

and tumorigenesis in order to contribute to the oncogenic process by activating neighboring
genes (Hnisz et al., 2013; Vaharautio & Taipale, 2014).
These super-enhancers often produce bidirectional and unstable non-coding transcripts
called enhancer RNAs (eRNAs) that have been shown recently to play functional roles in
enhancer activity. They are hallmarks of active enhancers as they have been suggested to play
a role in transcriptional regulation in cis and trans. While functional roles of the majority of eRNAs
in the human genome are not identified, studies have shown that several of these ncRNAs
play critical roles in controlling gene expression. In these studies, targeted degradation of eRNA
using either RNA interference or RNase-H-mediated RNA cleavage showed reduction of nearby
protein-coding genes (Lam et al., 2013; W. Li et al., 2013). While the molecular mechanism
underlying how eRNA regulates gene expression isn’t completely understood, studies show that
eRNAs could modulate chromatin accessibility of promoters, stabilize enhancer-promoter
interactions, trap TFs on genomic sites, and regulate RNAPII pause release at promoters (W.
Li, Notani, & Rosenfeld, 2016) (Figure 3-1). An in-depth study of eRNAs is beneficial for a
deeper understanding of enhancer function and gene regulation. Therefore, eRNAs shows
great therapeutic potential.
16

Figure 3-1. eRNA-driven gene regulation in cis

eRNAs regulate gene expression via interaction with a variety of transcription-associated proteins,
such as transcription factors, cohesin, mediators, RNA polymerase II (RNAPII), and CREB-
binding protein (CBP). eRNA can (1) further recruit TFs onto enhancers, (2) directly interact with
looping factors to bring the enhancer closer to the target promoter, (3) make the gene body region
more accessible, (4) competes against negative elongation factor complex (NELF) to promote
RNAPII elongation, and (5) increase the histone acetylation activity of CBP. Figure adapted from
(Wu & Shen, 2019)

3.1.3 Enhancer identification methods
While earlier enhancer studies were based on reporter gene assays, where an enhancer
sequence was placed near a minimal core promoter and a reporter gene, NGS techniques have
greatly improved our understanding of enhancer biology. Enhancers have various histone marks
and chromatin features that distinguish them from other regulatory elements. Histone H3 lysine 4
mono-methylation (H3K4me1) is associated with enhancers while histone H3 lysine 4 tri-
17

methylation (H3K4me3) with promoters (Bernstein et al., 2005), and histone H3 lysine 27
acetylation (H3K27Ac) is associated with active regulatory elements (Bernstein et al., 2005;
Heintzman et al., 2007). Therefore, active enhancers can be identified by the high enrichments of
both H3K4me1 and H3K27ac relative to trimethylated H3K4 (H3K4me3) (Calo & Wysocka, 2013).
Using Chromatin Immunoprecipitation combined with sequencing (ChIP-seq), active enhancers
at a global level can be identified.
Since eRNAs indicate active enhancers, measuring eRNA level infers enhancer activity.
Due to their unstable nature, eRNA transcripts are often not captured by a traditional RNA-seq.
Global run-on sequencing (GRO-seq) is sensitive for detecting these transient RNAs because it
can measure these unstable transcripts before they are targeted by exosomes. GRO-Seq is a
derivative of RNA-Seq that aims to measure rates of transcription instead of steady state RNA
levels by directly measuring nascent RNA production (Core, Waterfall, & Lis, 2008). Specifically,
GRO-seq maps the binding sites of actively transcribing RNA polymerase II (RNAPII) at both
promoters and enhancers, allowing to capture unstable and lowly-expressed transcripts, such as
enhancer RNAs (Lam, Li, Rosenfeld, & Glass, 2014).
Lastly, since enhancers physically interact with promoters, deciphering three-dimensional
(3D) spatial organization has been crucial in predicting enhancer-promoter pairs accurately.
Chromosome conformation capture (3C)-based techniques are used to map chromatin contacts
by crosslinking and ligating the interacting genomic regions, then fragmenting using restriction
enzyme digestion. Then the ligated products, interpreted as chromatin contacts, are quantified
(Dekker, Rippe, Dekker, & Kleckner, 2002; Pombo & Dillon, 2015). 4C-seq combines 3C
principles with high-throughput sequencing to search for genomic contacts made by a given
genomic site of interest in an unbiased manner. Since several enhancers could interact and
control one single promoter, 4C-seq is an ideal method to identify which genomic loci physically
interact with a known promoter.
18

In the following section, I identify that how KSHV acts as an epigenomic driver that
modulates host epigenome at different stages of its viral lifecycle in order to maximize successful
replication and latency. By applying a combination of GRO-seq, ChIP-seq and 4C-seq, I present
a comprehensive transcriptomic and epigenomic landscape of KSHV-infected PEL cells during
latency and lytic replication.

3.2 Results
3.2.1 Global reduction of host enhancer activity upon KSHV reactivation
TRExBCBL1-RTA PEL cells, expressing a doxycycline (Doxy)-inducible RTA to allow
efficient lytic reactivation, were treated with Doxy for 0 h (latency) or 24 h (lytic replication), and
then used to generate ChIP-seq libraries (Nakamura et al., 2003). ChIP-seq analysis of the
H3K27ac enrichment in the intergenic and intronic regions detected over 19,579 distal active
enhancer elements in latent TRExBCBL1-RTA cells, whereas a majority of those active enhancer
elements were rapidly depleted upon RTA-induced reactivation (Figure 3-2A). ChIP-seq analysis
of the H3K4me1 enrichment exhibited a similar pattern (Figure 3-2B).
HOMER motif sequence analysis of those enhancer elements whose activities were
drastically depleted upon KSHV reactivation predicted involvement of several key B-cell
transcription factors (Figure 3-3A), including interferon regulatory factor 2/4 (IRF2/4), and YY1
and CTCF chromatin looping factors. Based on the dense occupancy of H3K27ac modification,
HOMER analysis also predicted 836 potential super-enhancer elements from latent TRExBCBL1-
RTA cells. Interestingly, high-ranked super-enhancer elements were primarily linked to genes that
are essential for B-cell development or oncogenesis including MYC, IRF1/4, XBP1, and CD70
(Figure 3-3B,C). These results collectively indicate that KSHV reactivation leads to the global
reduction of host enhancer elements as well as the specific reduction of super-enhancer elements
of B-cell transcription factors and oncogenes.
19

Figure 3-2. Identification of active enhancers using H3K27ac and H3K4me1 ChIP-seq

(A) Left: Heatmap of H3K27ac ChIP-seq signals at 19,579 putative active enhancers in
TRExBCBL1-RTA cells during latency and lytic replication induced by doxycycline for 24 h; each
row represents one enhancer region. Right: Density plot of average ChIP-seq signals in 10 kb
windows around the center of enhancer for latent (green) and lytic (orange) cells. ChIP was
replicated and the qualities were shown to be similar. (B) H3K4me1 ChIP-seq signals at 19,579
putative active enhancers as identified in A.

A
Colorkey
0.0 0.5 0.9 1.4 1.9
Latency
−5000 −2500 5'End 3'End 2500 5000
Colorkey
0.0 0.5 0.9 1.4 1.9
Lytic
−5000 −2500 5'End 3'End 2500 5000
0 1.5
Latent Lytic
Putative active enhancers
-5kb +5kb
Center
of Peak
Colorkey
0.0 0.4 0.7 1.1 1.5
Latency
−5000 −2500 5'End 3'End 2500 5000
Colorkey
0.0 0.4 0.7 1.1 1.5
Lytic
−5000 −2500 5'End 3'End 2500 5000
Colorkey
0.0 0.4 0.7 1.1 1.5
BRD4_Latency
−5000 −2500 5'End 3'End 2500 5000
Colorkey
0.0 0.4 0.7 1.1 1.5
Latency
−5000 −2500 5'End 3'End 2500 5000
Colorkey
0.0 0.4 0.7 1.1 1.5
Lytic
−5000 −2500 5'End 3'End 2500 5000
Colorkey
0.0 0.4 0.7 1.1 1.5
BRD4_Latency
−5000 −2500 5'End 3'End 2500 5000
ChIP-seq: H3K27ac
Global Active Enhancers
H3K27Ac coverage
Enhancer
center
0.0 0.2 0.4 0.6 0.8 1.0 1.2
Genomic Region (5' −> 3')
Read count Per Million mapped reads
−5000 −2500 5'End 3'End 2500 5000
Latency
Lytic
0.0 0.2 0.4 0.6 0.8 1.0 1.2
Genomic Region (5' −> 3')
Read count Per Million mapped reads
−5000 −2500 5'End 3'End 2500 5000
Latency
Lytic
Latent
Lytic
Latent Lytic
Putative enhancers ChIP-seq: H3K4me1
Global Enhancers
H3K4Me1 coverage
0.0 0.2 0.4 0.6 0.8 1.0 1.2
Genomic Region (5' −> 3')
Read count Per Million mapped reads
−5000 −2500 5'End 3'End 2500 5000
Latency
Lytic
Enhancer
center
0 1.5
-5kb +5kb
Center
of Peak
0.1 0.2 0.3 0.4 0.5 0.6 0.7
Genomic Region (5' −> 3')
Read count Per Million mapped reads
−5000 −2500 5'End 3'End 2500 5000
Latency
Lytic
Latent
Lytic
B
20

Figure 3-3. Host genes controlled by super-enhancers
(A) DNA binding motifs enriched at super-enhancers that were significantly downregulated upon
reactivation. (B) Rank order of H3K27ac ChIP-seq signals. Super-enhancers are the population
on the right side of the dotted line (with slope of more than 1). 836 super-enhancers are
identified and annotated to their nearest genes. Proto-oncogenes and B-cell transcription factors
important for PEL cells are indicated. (C) Three of the strongest super-enhancers detected in
TRExBCBL1-RTA cells during latency as indicated by high level of H3K27ac and H3K4me1 ChIP-
seq signal relative to H3K4me3 signal.

A
B
Low High
836 super-enhancers
Predicted enhancers ranked
by H3K27ac signals
H3K27ac signal
CD70
XBP1
BAX
MYC
IRF1
IRF4
MALAT1
MDM4
H3K27ac
H3K4me1
H3K4me3
CD70 MALAT1 MDM4
Consensus sequence P-value Motif
1e-767 IRF2
1e-631 ISRE
1e-527 IRF4
1e-468 Jun-AP1
1e-303 FLI1
1e-147 YY1
1e-116 CTCF
C
21

3.2.2 Identification of nascent viral and host gene transcription
To identify nascent mRNAs produced during latency or lytic replication, mock- or Doxy-
treated TRExBCBL1-RTA cells were subjected to GRO-seq analysis. To investigate the
correlation between nascent transcripts and steady-state transcripts, I re-analyzed and compared
the previously published mRNA-seq data of TRExBCBL1-RTA cells with our GRO-seq results
(Papp et al., 2019). When aligned to the KSHV genome, distinct patterns of viral transcripts
between GRO-seq and RNA-seq were observed: GRO-seq detected considerably more viral
transcripts during latency than RNA-seq (Figure 3-4), and those transcript peaks were highly
correlated to the RNAPII binding sites. This confirms that GRO-seq measures active transcription
from the loci where RNAPII is already bound (Figure 3-4, marked in black asterisks). GRO-seq
showed similar KSHV transcription patterns between latency and lytic replication, but the only
differences were primarily higher transcription profiles during lytic replication than during latency
(Figure 3-4). On the other hand, RNA-seq showed considerable difference of KSHV transcription
patterns between latency and lytic replication: low expressions of a few latent genes except PAN
RNA (marked in red asterisk) during latency and high expressions of most viral genes during lytic
replication (Figure 3-4).

Figure 3-4. Identification of nascent viral RNA from GRO-seq

GRO-seq and RNA-seq signals aligned to KSHV genome during latency and upon reactivation.
RNAPII ChIP-seq enrichments are from latency. Black asterisks indicate the regions where the
0
h
24
h
0
h
24
h
0
h
GRO-seq
f(transcription)
RNA-seq
f(transcription
+ stability)
Pol-II
ChIP-seq
+dox
* * * *
50
0
50
0
10,00
0
10,00
0
1,00
0
* *
10 kb
22

GRO-seq signals are significantly different from RNA-seq signals, and red asterisk is PAN RNA
locus that shows high upregulation in both RNA-seq and GRO-seq during latency. Two replicates
of GRO-seq were performed.

When host gene expressions were examined, the correlation coefficients between GRO-
seq and RNA-seq were 0.61 and 0.66 in KSHV latent conditions and lytic replication conditions,
respectively, suggesting that there are significant differences between newly synthesized
transcripts versus steady state transcripts (Figure 3-5A). Then, I surveyed the fold change in
between RNA abundance (RNA-seq) and transcription (GRO-seq) upon reactivation (Figure 3-
5B). I first identified host coding genes that were significantly upregulated or downregulated in
RNA-seq, and then checked whether the trend was similar in GRO-seq. RNA-seq analysis
showed that similar numbers of host genes were upregulated (fold change greater or equal to 2)
or downregulated (fold change less or equal to -2) for their expressions. In contrast, GRO-seq
showed that expressions of a few host genes were upregulated upon reactivation, whereas
expression of most host genes were highly downregulated. Interestingly, the gene expression
profile of GRO-seq upon reactivation was very similar to that of H3K27ac ChIP-seq (Figure 3-
5C,D), indicating the strong relationship between transcription rate and histone acetylation. For
instance, GGT6 and IL6 were highly upregulated upon reactivation from RNA-seq analysis, but
GRO-seq analysis showed little or no increase of their transcription rate (Figure 3-5E). As IL6
gene has been shown to escape KSHV ORF37 RNase-mediated host mRNA shutoff (Hutin, Lee,
& Glaunsinger, 2013), the increase of IL6 mRNA from RNA-seq analysis might be not due to
increased transcription, but due to increased mRNA stability. On the other hand, RNA-seq and
GRO-seq analyses showed that RTA-induced reactivation led to the drastic reduction of MYC
expression at both transcription and mRNA stability level. These results show that RNA-seq
results are more due to changes in RNA stability than to changes in transcription, indicating that
transcription and transcript turnover are two distinct mechanisms that govern host gene
expression changes upon KSHV reactivation.
23

Furthermore, I utilized gene set enrichment analysis (GSEA) of the GRO-seq results to
evaluate the biological relevance of the host gene alteration at the transcriptional level. I first
ranked all host genes according to the extent of their fold changes and p-value, followed by
computing the normalized enrichment scores of each biological pathway. This analysis revealed
that upon KSHV reactivation, inflammation pathways, including TNF-a and TFB-b signaling
pathways, were significantly upregulated, while EIF2 and MYC target pathways were markedly
downregulated (Figure 3-6). These data suggest that GRO-seq analysis is able to identify gene
networks whose transcriptional rates are specifically regulated upon KSHV reactivation.

24

A
r= 0.61
RPKM (GRO-seq)
RPKM (RNA-seq)
Latency
r= 0.66
RPKM (GRO-seq)
RPKM (RNA-seq)
Lytic
B
0.05 0.10 0.15 0.20 0.25
Genomic Region (5' −> 3')
Read count Per Million mapped reads
−5000 −2500 5'End 3'End 2500 5000
Latent
Lytic
Promoter
center
0.0 0.2 0.4 0.6 0.8 1.0 1.2
Genomic Region (5' −> 3')
Read count Per Million mapped reads
−5000 −2500 5'End 3'End 2500 5000
Latency
Lytic
GRO-seq mRNAs
GRO-seq coverage
Latent
Lytic
0.0 0.2 0.4 0.6 0.8 1.0
Genomic Region (5' −> 3')
Read count Per Million mapped reads
−5000 −2500 5'End 3'End 2500 5000
Latency
Lytic
Promoter
center
0.0 0.2 0.4 0.6 0.8 1.0 1.2
Genomic Region (5' −> 3')
Read count Per Million mapped reads
−5000 −2500 5'End 3'End 2500 5000
Latency
Lytic
Global Active Promoters
H3K27Ac coverage
Latent
Lytic
C
D
0 1.5
Latent Lytic
GRO-seq:
Putative mRNA
-1kb +1kb
Center of Peak
Colorkey
0.0 0.5 0.9 1.4 1.9
Latency
−5000 −2500 5'End 3'End 2500 5000
Colorkey
0.0 0.5 0.9 1.4 1.9
Lytic
−5000 −2500 5'End 3'End 2500 5000
0 1.5
Latent Lytic
Putative promoter
-1kb +1kb
Center of Peak
H3K27Ac ChIP-seq:
5
-5
5
-5
18
18
IL-6
140
-15
140
-15
500
500
MYC
0 h
24 h
0 h
24 h
GRO-seq
f(transcription)
RNA-seq
f(transcription
+ stability)
+dox
2
-1
2
-1
10
100
GGT6
E
Lytic vs Latent fold change (RNA-seq)
Lytic vs Latent fold change (GRO-seq)
I II
III IV
25

Figure 3-5. Identification of nascent host RNA from GRO-seq
(A) Correlation between GRO-seq and RNA-seq during latency (top) and lytic replication (bottom)
using Pearson’s correlation. Two replicates of GRO-seq and two replicates of RNA-seq were
averaged. (B) Differential gene expression fold change from latency to lytic replication. Correlation
plot of RNA-seq vs. GRO-seq. Genes with p-value < 0.05 and fold change threshold of -/+2 from
RNA-seq are displayed. Genes with fold change between -2 and 2 are considered no change. x-
axis is differential fold change from latency to lytic replication in RNA-seq, y-axis is differential fold
change in GRO-seq. Quadrant I are the genes whose mRNA and transcription level both
increased upon reactivation; quadrant II are those with increased transcription but decreased
mRNA level; quadrant III are those whose mRNA and transcription both decreased; quadrant VI
are genes with increased mRNA but decreased transcription. (C) Left: Heatmap of H3K27ac
ChIP-seq signals at putative active promoters in TRExBCBL1-RTA cells during latency and lytic
replication induced by doxycycline for 24 h; each row represents one promoter region. Right:
Density plot of average ChIP-seq signals in 10 kb windows around the center of promoter of KSHV
latent-infected (green) or lytic-infected (orange) cells. (D) Left: Heatmap of GRO-seq signals at
putative active promoters identified in A. Right: Density plot of average GRO-seq signals in 10kb
windows around the center of promoter of KSHV latent-infected (green) or lytic-infected (orange)
cells. (E) GRO-seq and RNA-seq results for three representative host genes: GGT6, IL6 and
MYC.

Figure 3-6. Gene set enrichment analysis (GSEA) of GRO-seq data upon KSHV reactivation

Enrichment scores are indicated in each plot along with p-value and FDR q-value. Positive (top
two) and negative (bottom two) ES values represent gene sets over-represented in the topmost
up- or down-regulated genes, respectively.
TNFA SIGNALING VIA NFKB
NES: 2.096
p-value<0.001
FDR q: 0.009
TGF BETA SIGNALING
NES: 1.945
p-value: 0.004
FDR q: 0.017
EF2 TARGETS
NES: -4.872
p-value<0.001
FDR q<0.001
MYC TARGETS V1
NES: -3.053
p-value<0.001
FDR q<0.001
26

3.2.3 Reduction of global eRNA expression upon KSHV reactivation
I plotted the GRO-seq densities for human active enhancers that were previously identified
from H3K27ac ChIP-seq (Figure 3-7). Statistical analysis showed that ~50% of active enhancers
produced eRNA above background noise. The global level of eRNAs was also significantly
reduced upon RTA-induced reactivation, which was correlated with the reduction of H3K27ac and
H3K4me1 at active enhancer elements (Figure 3-2A,B). This further indicates that KSHV
reactivation results in the global repression of host enhancer activity.

Figure 3-7. Reduction of global enhancer RNAs upon KSHV reactivation

Left: Heatmap of GRO-seq signals at putative active enhancers previously identified. Right:
Density plot of average GRO-seq signals in 10kb windows around the center of enhancer.

Latent Lytic
Putative eRNA
GRO-seq:
Global eRNAs
GRO-seq coverage
0.0 0.2 0.4 0.6 0.8 1.0 1.2
Genomic Region (5' −> 3')
Read count Per Million mapped reads
−5000 −2500 5'End 3'End 2500 5000
Latency
Lytic
Enhancer
center
0
1.5
-5kb +5kb
Center
of Peak
0.05 0.10 0.15 0.20 0.25
Genomic Region (5' −> 3')
Read count Per Million mapped reads
−5000 −2500 5'End 3'End 2500 5000
Latent
Lytic
Latent
Lytic
27

Chapter 4. KSHV-mediated MYC enhancer regulation
(The work described in this chapter has been published in Park et al. (2020). Global epigenomic
analysis of KSHV-infected primary effusion lymphoma identifies functional MYC super-
enhancers and enhancer RNAs. Proceedings of the National Academy of Sciences of the
United States of America)

4.1 Introduction
4.1.1 Enhancer regulation of MYC
MYC is one of the major oncogenes in cancer, as it is upregulated in 50-60% of all tumors
as it regulates a plethora of genes related to cell cycle, differentiation, survival, proliferation and
cell fate (Gabay, Li, & Felsher, 2014; Morton & Sansom, 2013). MYC is deregulated by several
mechanisms, such as chromosomal translocation, genetic mutations or single-nucleotide
polymorphisms (SNPs), and gene duplications. Recently, several studies have identified tissue-
specific super-enhancers of MYC that produce 3D long-range transcriptional regulation of MYC
(Lancho & Herranz, 2018). Depending on the cancer type, MYC utilizes enhancer elements at
different genomic location, recruiting different transcription factors and cofactors to aid in MYC
expression at different level. However, a recent study suggests that regardless of location, most
MYC enhancers interact with the CTCF-binding common docking site 2kb upstream of the MYC
promoter to control MYC expression (Schuijers et al., 2018). Overall, these studies highlight the
importance of enhancer-specific chromatin modification of MYC in cancer and suggest enhancer-
targeting as a potential therapeutic strategy.

4.1.2 MYC and KSHV lifecycle
Unlike other B-cell lymphomas, KSHV-infected PEL cells lack major genetic
translocations of proto-oncogenes such as MYC (Katano, Sato, & Sata, 2001). On the other
hand, KSHV still maintains elevated MYC expression during latency, which is crucial in
maintaining latent status and cell survival (X. Li, Chen, Feng, Deng, & Sun, 2010). Several viral
28

latent proteins such as LANA and vIRF3 (viral interferon regulatory factor-3) have been shown
to stabilize MYC at the post-translational level in PELs (Baresova, Pitha, & Lubyova, 2012;
Bubman, Guasparri, & Cesarman, 2007; Liu, Martin, Liao, & Hayward, 2007). The upregulation
of MYC expression has been shown to be necessary to repress KSHV lytic gene expression in
PELs, resulting in the maintenance of viral latency (X. Li et al., 2010). Also, RNAi-mediated MYC
knockdown induced KSHV reactivation and also reactivation-independent apoptosis (X. Li et al.,
2010). Given that MYC expression is highly associated with oncogenic activation, KSHV-
mediated deregulation of MYC is now viewed as one of the mechanisms of how KSHV induces
lymphomagenesis.

4.1.3 MYC regulation by EBV
EBV is another member of the γ-herpesvirus family that causes lymphoma. Recently, it
has been shown that in EBV-transformed lymphoblastoid cell lines (LCL), EBV oncoproteins
such as EBNA2 and EBNA3C modify host genome by binding to cellular enhancer sites and
upregulating oncogene expressions such as MYC and BCL2, ultimately inducing LCL
proliferation (H. Zhou et al., 2015). Further study revealed that the eRNA transcripts produced
from the MYC super-enhancer regions -500 kb upstream region of MYC transcription start site
(TSS) are critical for maintaining MYC mRNA expression and cell proliferation, suggesting the
significant role of eRNAs for EBV pathogenesis (Liang et al., 2016).

4.2 Results
4.2.1 Identification of MYC super-enhancers and eRNAs in PELs
Surprisingly, our GRO-seq analysis showed that unlike EBV+ GM12878 LCLs,
EBV+/KSHV+ JSC-1 and KSHV+ TRExBCBL1-RTA PELs both produced strong eRNA-like
transcripts in +500 kb downstream of the MYC TSS, even downstream of the PVT-1 IncRNA
(Figure 4-1A). I identified three highest peaks within the span of 50 kb of the newly identified MYC
29

eRNAs: +486 kb, +507 kb and +530 kb downstream of MYC TSS, which were labeled as e486,
e507, and e530, respectively. To measure the copy number of eRNAs, I performed drop digital
PCR (ddPCR) assay targeting each eRNA and the abundant viral PAN RNA during latency. This
showed that the level of GRO-seq peaks appeared to be similar to the copy numbers of three
eRNAs: e486 (6.1 copy/ng), e507 (14.8 copy/ng), and e530 (8.4 copy/ng) along with PAN RNA
(172,375 copy/ng) (Figure 4-2). This indicates that eRNAs are expressed downstream of the MYC
in KSHV-infected PELs, whereas they are expressed upstream of the MYC in EBV+ LCLs.
To further test whether these eRNA-expressing enhancer regions function specifically as
MYC enhancers, I performed chromosome conformation capture combined with high-throughput
sequencing (4C-seq) on TRExBCBL1-RTA cells to detect the genomic interaction of these two
regions. I used either MYC promoter (forward) or enhancer (backward) as the bait sequence and
identified the genomic loci that physically interacted with the bait (see Materials and Methods).
Both forward and backward 4C-seqs showed that TRExBCBL1-RTA PELs carried specific
interactions between the MYC promoter and the downstream enhancers corresponding the eRNA
transcription sites (Figure 4-1B). 3C-PCR reaction and DNA sequence analysis further validated
the specific interaction between the MYC promoter and its enhancer cluster identified by 4C-seq
analysis (Figure 4-1CD).

30

Figure 4-1. KSHV+ PEL cell lines show potential MYC super-enhancers

(A) GRO-seq peaks near MYC locus. EBNA2-mediated EBV super-enhancer is indicated by high
peaks -500 kb upstream of MYC transcription start site (TSS; red highlight) and potential KSHV
super-enhancer is indicated +500 kb downstream (blue highlight). (B) 4C-seq signals in latent
TRExBCBL-1.RTA cells near MYC locus. Top: MYC promoter set as the 4C viewpoint/anchor
sequence (red highlight); Bottom: enhancer set as the 4C viewpoint/anchor sequence (blue
highlight). (C) 3C-PCR showing intensities of a specific Promoter:Enhancer (P:E) looping in the
MYC locus. Control 3C samples without T4 ligase are shown as “-”. (D) Sanger sequencing of
the 3C-PCR products shows that the ligated fragment comprises the regions from MYC promoter
and enhancer.

MW
- + - + - +
Ligase
e486 e507 e530
3C-PCR
MYC P:E interaction (NlaIII)
100
200
300
bp
C
D
MYC promoter MYC enhancer (e486) NlaIII
MYC promoter MYC enhancer (e507)
NlaIII
MYC promoter
MYC enhancer (e530)
NlaIII
A
B
KSHV
SuperEnhancer
(+500 kb)
MYC Promoter
EBV SuperEnhancer
(-500 kb)
GM12878
JSC-1
TRExBCBL-1.RTA
PVT1 CASC8 CASC21 CASC19 MYC
50 kb
chr8:128,190,901-129,300,899 (1.1 Mb)
*
*
Promoter
Enhancer
TRExBCBL-1.RTA
Low High
31

An in-depth examination of GRO-seq, H3K27ac ChIP-seq and H3K4me1 ChIP-seq
showed extensive overlap at each enhancer cluster (Figure 4-2). By re-analyzing publicly
available ChIP-seq data, I observed the colocalizations of RNAPII, CTCF, SMC1, and BRD4
clusters with these enhancer elements, and the FAIRE-seq also showed chromatin accessibility
at these regions (H. S. Chen et al., 2012; Hilton et al., 2013; Hu et al., 2014; F. Zhou et al., 2017).
Active enhancers are marked by bi-directional GRO-seq signal, high H3K27ac and H3K4me1
relative to H3K4me3. These regions need to be accessible as indicated by FAIRE-seq so that
RNAPII and other chromatin modulating factors (CTCF, SMC1 and BRD4) can be recruited to the
sites. These results strongly indicate that the eRNA-expressing regions downstream of MYC gene
function as its super-enhancers. This also suggests that unlike EBV-infected LCL cells, KSHV-
infected PEL cells utilize super-enhancers downstream of MYC.

Figure 4-2. Various sequencing results confirm MYC super-enhancer activity

Each enhancer cluster (black dotted box) is labeled as the distance away from MYC TSS (+486
kb, +507 kb, +537 kb). GRO-seq peaks are for both latency (blue) and lytic replication (red), but
all others show peaks during latency only.
mRNA-seq
H3K27Ac
H3K4Me1
H3K4Me3
RNAPII
FAIRE-seq
CTCF
SMC1
BRD4
GRO-seq
Latent Lytic
25
-25
15
3
7
3
1
1
1
1
2
25
-25
140
-140
140
-140
500
1
2
3
2
1
15
5
1
Promoter Downstream enhancer clusters (+500 kb)
10 kb
MYC
e486 e507 e537
32

4.2.2 MYC eRNA regulation upon KSHV lytic induction
As seen with many host genes, MYC expression was also repressed upon KSHV
reactivation at both the mRNA and protein levels in TRExBCBL1-RTA PELs (Figure 4-3A). qRT-
PCR showed that RTA-mediated reactivation led to the pronounced reduction of e486 and e507
eRNA transcripts and the modest reduction of e530 eRNA transcript (Figure 4-3B). GRO-seq also
showed the visible reductions of all three eRNA peaks (Figure 4-2). ChIP-qPCR also showed that
RTA-mediated reactivation led to the marked reduction of H3K27ac and H3K4me1 enhancer mark
occupancy at the MYC super-enhancer regions (Figure 4-3C). These results collectively
demonstrate that KSHV reactivation represses MYC expression to facilitate lytic gene activation,
and its expression may partially be controlled by the reduced super-enhancer activity.

Figure 4-3. KSHV reactivation leads to reduction in MYC enhancer activity

(A) qRT-PCR and immunoblot showing reduction of MYC mRNA and protein level upon
doxycycline-induced KSHV reactivation. (B) qRT-PCR measuring reduction of enhancer
A
e486
e507
e530
0
10
20
30
H3K4me1 % enrichment
0 hpi
24 hpi
e486
e507
e530
0
5
10
15
H3K27Ac % enrichment
0 hpi
24 hpi
****
****
****
****
****
****
e486
e507
e530
0
10
20
30
H3K4me1 % enrichment
0 hpi
24 hpi
MYC
RTA
Actin
Doxy: 0 24 hpi
TREx BCBL1-RTA
0hpi
24hpi
MYC
0.0
0.5
1.0
1.5
mRNA (fold change)
*
e486
e507
e530
0.0
0.5
1.0
1.5
MYC eRNA
MYC eRNA (fold change)
0hpi
24hpi
****
****
*
B
C
33

transcripts at each MYC enhancer. (C) H3K27ac and H3K4me1 ChIP-qPCR showing reduction
of enhancer activity at MYC super-enhancers.

4.2.3 Functional role of MYC super-enhancers in PELs
To assess the functionality of the MYC enhancers, I used dCas9-KRAB CRISPR inhibition
(CRISPRi) approach. TRExBCBL1-RTA cells were transduced with lentivirus expressing the
nuclease-inactive dCas9-KRAB fusion repressor together with sgRNAs targeting each MYC
enhancer (Thakore et al., 2015). I also used sgRNAs targeting MYC mRNA or PVT-1 ncRNA as
controls to ensure the efficacy of this approach (Figure 4-4A). e486- or e530-specific CRISPRi
reduced e486 or e530 level, respectively, while e507-specific CRISPRi showed minimal effect on
e507 level (Figure 4-4B). qRT-PCR showed that the CRISPRi-mediated inhibition of the enhancer
expressions significantly reduced MYC mRNA expression compared to control CRISPRi
treatment (Figure 4-4C).
In order to further test the functional role of MYC eRNAs, TRExBCBL1-RTA PELs were
transduced with lentiviruses expressing scrambled control shRNA or eRNA-specific shRNA,
selected for puromycin resistance to remove untransduced cells, and then harvested to extract
total RNAs. e486- or e530-specific shRNA efficiently knocked down corresponding eRNA,
whereas e507-specific shRNA showed minimal knockdown of e507 (Figure 4-4D). qRT-PCR
showed that depletion of either e486 or e530 eRNA expression significantly reduced MYC mRNA
expression at different magnitudes (Figure 4-4E). Similar to the e507-specific CRISPRi, the e507-
specific shRNA weakly reduced e507 level but both treatments led to the strong reduction of MYC
mRNA (Figure 4-4E). Subsequently, the e486- or e530-specific shRNA-mediated reduction of
MYC expression led to lowering LANA latent gene expression but inducing RTA and K2 lytic gene
expression (Figure 4-4F), indicating that knockdown of these eRNAs prompts KSHV lytic gene
expression. Immunoblotting also showed the reduction of MYC and LANA levels (Figure 4-4G).
34

These studies collectively indicate that depletion of the enhancer function and eRNA expression
lead to repression of the MYC expression that ultimately affects KSHV gene regulation.

PVT-1
control
0.0
0.5
1.0
1.5
sgRNA
PVT-1 ncRNA (fold change)
MYC1/2/3
control
0.0
0.5
1.0
1.5
sgRNA
MYC mRNA (fold change)
PVT-1
control
0.0
0.5
1.0
1.5
sgRNA
PVT-1 ncRNA (fold change)
C
E
B
G
e486
e507
e530
control
0.0
0.5
1.0
1.5
MYC mRNA (fold change)
shRNA
**
**
e486
e507
e530
control
0.0
0.5
1.0
1.5
LANA mRNA (fold change)
shRNA
e486
e507
e530
control
0
1
2
3
4
5
RTA mRNA (fold change)
shRNA
e486
e507
e530
control
0
2
4
6
8
10
K2 mRNA (fold change)
shRNA
*
**
*
****
***
****
**
D
e486
control
0.0
0.5
1.0
1.5
MYC e486 eRNA (fold change)
shRNA
e507
control
0.0
0.5
1.0
1.5
2.0
MYC e507 eRNA (fold change)
shRNA
e530
control
0.0
0.5
1.0
1.5
MYC e530 eRNA (fold change)
shRNA
*
*
F
e486
control
0.0
0.5
1.0
1.5
sgRNA
MYC e486 eRNA (fold change)
e507
control
0.0
0.5
1.0
1.5
sgRNA
MYC e507 eRNA (fold change)
e530
control
0.0
0.5
1.0
1.5
sgRNA
MYC e530 eRNA (fold change)
*
**
e486
e507
e530
control
0.0
0.5
1.0
1.5
sgRNA
MYC mRNA (fold change)
*
***
****
MYC
LANA
e486 e507 e530 control
Actin
shRNA
A
35

Figure 4-4. Disruption of MYC super-enhancers leads to KSHV reactivation

(A) CRISPRi using dCas9-KRAB-MYC-sgRNA or dCas9-KRAB-PVT1-sgRNA to test system efficacy in
TRExBCBL1-RTA. 3 different sgRNAs were mixed to repress MYC mRNA. (B) dCas9-KRAB-sgRNA-
mediated CRISPR inhibition (CRISPRi) targeting each MYC eRNA, and dCas9-KRAB alone
used as control. (C) qRT-PCR of host MYC mRNA upon CRISPR inhibition of the three MYC
eRNAs. (D) shRNA-mediated RNA interference (RNAi) targeting each MYC eRNA, and
scrambled sequence used as control. (E) qRT-PCR of MYC gene mRNA level upon eRNA
shRNA treatment. (F) Latent (LANA) and lytic (RTA, K2) viral gene mRNA levels upon shRNA
treatment. (G) Immunoblot for MYC and LANA upon shRNA transduction validating the qRT-
PCR results (E).

BRD4 (bromodomain-containing protein 4) is a member of the BET (bromodomain and
extra terminal domain) family and an important coactivator that binds to H3K27ac specifically on
the super-enhancers but not on typical enhancers, and recruits RNAPII to trigger transcription
(Figure 4-5A) (Delmore et al., 2011; Tolani, Gopalakrishnan, Punj, Matta, & Chaudhary, 2014).
JQ1 is a well-known small molecule inhibitor that prevents BRD4 from associating with H3K27ac
at super-enhancers to suppress transcription (Filippakopoulos et al., 2010). To test the effects of
JQ1 on the MYC eRNA transcription, TRExBCBL1-RTA PELs were treated with 0.5 µM JQ1 or
DMSO control for 24 h and expressions of the MYC eRNAs were assessed by qRT-PCR.
Consequently, JQ1 treatment markedly repressed all three MYC eRNA expressions, resulting in
the reduction of MYC expression and the induction of KSHV lytic gene expression (Figure 4-5B,C).
These results indicate that JQ1-mediated BRD4 perturbation disrupts the MYC super-enhancer
function, reducing both MYC eRNA and mRNA levels while inducing KSHV lytic gene expressions.

36

Figure 4-5. BRD4 inhibition leads to disruption of MYC enhancer

(A) BRD4 ChIP-seq signals from the host genome during latency are aligned next to H3K27ac
signals. BRD4 preferentially binds to super-enhancers but not typical enhancers. (B) qRT-PCR
results for MYC eRNA upon treatment with 0.5µM of JQ1 for 24 h. (C) qRT-PCR results for MYC
mRNA and viral mRNAs (LANA, RTA and K2)

Super
enhancer
Typical
enhancer
Colorkey
0.0 0.5 0.9 1.4 1.9
Latency
−5000 −2500 5'End 3'End 2500 5000
Colorkey
0.0 0.5 0.9 1.4 1.9
Lytic
−5000 −2500 5'End 3'End 2500 5000
0 1.5
H3K27A
c
BRD4
Putative active enhancers
-5kb +5kb
Center
of Peak
Colorkey
0.0 0.4 0.7 1.1 1.5
Latency
−5000 −2500 5'End 3'End 2500 5000
Colorkey
0.0 0.4 0.7 1.1 1.5
Lytic
−5000 −2500 5'End 3'End 2500 5000
Colorkey
0.0 0.4 0.7 1.1 1.5
BRD4_Latency
−5000 −2500 5'End 3'End 2500 5000
A B
C
e486
e507
e530
0.0
0.5
1.0
1.5
fold change relative to DMSO
DMSO
JQ1 0.5uM
****
****
****
LANA
RTA
K2
0
1
2
3
4
MYC
0.0
0.5
1.0
1.5
fold change relative to DMSO
DMSO
JQ1 0.5uM
*
*
****
**
37

4.2.4 Potential roles of cellular IRF4 and viral IRF4 in MYC eRNA expression
H3K27ac ChIP-seq identified that host IFN regulatory factor (IRF4) was another essential
gene that was regulated by super-enhancers (Figure 3-3B). Its enhancer clusters were found in
the intragenic region of DUSP22 gene upstream (Figure 4-6A). I further investigated the role of
IRF4 in the enhancer regulation of PEL cells because not only is IRF4 essential for PEL growth
and survival (Forero, McCormick, Jenkins, & Sarkar, 2014; Manzano et al., 2018), but IRF4 also
directly binds to enhancers (Iwata et al., 2017). Because IRF4 was one of the top enriched factors
in our HOMER motif sequence analysis (Figure 3-3A), I examined the potential role of IRF4 in
MYC eRNA expression. BCBL-1 PELs carrying Doxy-inducible expression of IRF4-specific
shRNA were treated with a low concentration of Doxy (100 ng/ml) for 72 h and then tested for
cellular IRF4 expression and MYC eRNA expression by RT-PCR (Forero et al., 2014). This
showed that Doxy-induced IRF4-specific shRNA treatment detectably reduced IRF4 expression
(Figure 4-6B) as well as MYC e486 and e507 eRNA expressions (Figure 4-6C), suggesting the
role of IRF4 in MYC eRNA expression.
Our lab has previously shown that the KSHV viral IRF4 (vIRF4) lytic protein robustly
suppresses expression of cellular IRF4 at the transcriptional level to reshape host gene
expression profiles and facilitate viral lytic replication (Lee et al., 2014). TRExBCBL1-vIRF4 PELs
carrying Doxy-inducible vIRF4 expression were treated with Doxy for 24 h and subjected to RT-
PCR analysis. This showed that vIRF4 expression robustly reduced cellular IRF4 expression,
which led to the reduction of MYC e486 and e530 eRNA expression and thereby, MYC expression
(Figure 4-6D,E,F). These data suggest that while cellular IRF4 acts upon the MYC super-
enhancers for MYC expression during KSHV latency, vIRF4 lytic protein represses cellular IRF4
expression upon KSHV lytic reactivation, thereby suppressing MYC expression.

38

A
C B
D
E
vIRF4
cIRF4
actin
Doxy: 0 24 hpi
TREx BCBL1-vIRF4
MYC
cIRF4
vIRF4
0.0
0.5
1.0
1.5
13
14
15
mRNA (fold change)
*
***
**
e486
e507
e530
0.0
0.5
1.0
1.5
MYC eRNA (fold change)
-dox
+dox
***
*
***
*
e486
e507
e530
0.0
0.5
1.0
1.5
MYC eRNA (fold change)
-dox
+dox
e486
e507
e530
0.0
0.5
1.0
1.5
MYC eRNA
MYC eRNA (fold change)
-dox
+dox
*
IRF4
0.0
0.5
1.0
1.5
mRNA (fold change)
e486
e507
e530
0.0
0.5
1.0
1.5
MYC eRNA
MYC eRNA (fold change)
-dox
+dox
e486
e507
e530
0.0
0.5
1.0
1.5
MYC eRNA
MYC eRNA (fold change)
-dox
+dox
****
**
e486
e507
e530
0.0
0.5
1.0
1.5
MYC eRNA
MYC eRNA (fold change)
-dox
+dox
Promoter
mRNA-seq
H3K27Ac
H3K4Me1
H3K4Me3
RNAPII
FAIRE-seq
CTCF
SMC1
BRD4
Upstream enhancer
clusters (-50 kb)
GRO-seq
DUSP22 IRF4
140
-140
1200
0
4
0
12
0
3
0
3
0
1
0
3
0
2
0
2
0
0
10 kb
F
39

Figure 4-6. Role of IRF4 in PEL enhancer activity

(A) Identification of IRF4 super-enhancer -50 kb upstream of IRF4 TSS by aligning multiple
different sequencing results. The two enhancer clusters (black dotted boxes) are embedded within
the intronic region of DUSP22. (B) qRT-PCR of IRF4 in BCBL-1 cells with doxycycline-inducible
shRNA targeting IRF4. (C) qRT-PCR of MYC eRNA. Reduction of IRF4 expression leads to
downregulation of e486 and e507 but not e530. (D) qRT-PCR of MYC, cellular IRF4 and viral
IRF4 mRNA in TRExBCBL1-vIRF4 treated with doxycycline for 24 h to induce viral IRF4
expression. (E) Immunoblot showing induction of vIRF4 and reduction of cellular IRF4. (F) qRT-
PCR results showing the reduction of eRNAs upon vIRF4 overexpression.

40

Chapter 5. Discussion and future direction

This study introduces a new layer of epigenomic regulation in KSHV-infected PEL cells
and suggests a potential mechanism of how KSHV reactivation changes host epigenome. I
combined ChIP-seq, GRO-seq and 4C-seq datasets with publicly available Next Generation
Sequencing datasets to generate an in-depth genome-wide analysis of host enhancers and
super-enhancers during latent infection and lytic replication of KSHV. Firstly, I identified that a
number of active enhancer elements were detected during KSHV latency and those enhancer
elements were predicted to be targeted by IRF2 and IRF4 B-cell transcription factors, and YY1
and CTCF chromatin looping factors. Upon RTA-mediated KSHV lytic replication, however, host
enhancer activity was globally reduced as indicated by the decreased level of H3K27ac and
H3K4me1 modification. Surprisingly, when the actual modified histone level was measured
using immunoblot analysis, global levels of histone 3 (H3) expression as well as H3K4me1 and
H3K4me3 modification levels were not affected upon RTA-induced reactivation, whereas
H3K27ac modification level was detectably reduced (Figure 5-1).

Figure 5-1. Global level of histone modifications upon KSHV reactivation

Immunoblot analysis of total H3 and H3 modification levels in TRExBCBL1-RTA cells during
latency and lytic replication (induced by doxycycline for 24 h).

H3
H3K27ac
H3K4me1
H3K4me3
hpi: 0 24
41

p300 transcriptional cofactor contains histone acetyltransferase (HAT) activity that is
responsible for H3K27ac modification (Jin et al., 2011). Our lab has previously shown that KSHV
encodes viral IRF1 lytic protein that directly binds to p300 and displaces p300/CBP-associated
factor from p300 complexes (Jacobs & Damania, 2011; M. Li et al., 2000). This interaction inhibits
p300 HAT activity, resulting in the drastic reduction of global H3K27ac and the alteration of host
chromatin status. This may result in the dramatic decrease of active enhancers and promoters
marked by H3K27ac upon KSHV reactivation. On the other hand, it has not been studied how
KSHV directly or indirectly controls H3K4me1 modification. Nevertheless, this suggests that
KSHV has evolved to carry a number of viral proteins to target host epigenetic factors, resulting
in the alteration of host enhancer activity for its lifecycle.
Intriguingly, GRO-seq patterns of viral transcription were highly similar between KSHV
latency and lytic replication, and the only difference was primarily higher viral transcription profiles
during lytic replication than during latency. This indicates that the RNAPII occupancy is not
significantly changed on the viral genome upon reactivation. In fact, our lab has previously shown
that the KSHV genome is bivalent as both active and repressive histone marks are associated
with viral genome (Toth et al., 2010). Furthermore, RNAPII is already recruited to the viral loci but
its transcription is basically paused by the host's negative elongation factor, which is necessary
to efficiently respond to environmental stimuli and promptly activate viral lytic gene expression
(Toth et al., 2012).
GRO-seq measures nascent RNA levels, whereas RNA-seq measure steady state RNA
levels. Both GRO-seq and RNA-seq analyses showed similar viral transcription profiles during
lytic replication except a few genes such as ORF6 and ORF59 which were more highly expressed
from RNA-seq than from GRO-seq. Similarly, expression of several host genes such as GGT6
and IL6 were highly upregulated upon KSHV reactivation from RNA-seq analysis, but they
showed little or no increase from GRO-seq analysis. Previous studies have shown that lytic
protein ORF37 is primarily responsible for host mRNA shutoff upon reactivation but host IL6 gene
42

can escape ORF37-mediated host mRNA shutoff (Clyde & Glaunsinger, 2011). Thus, the
difference between RNA-seq results and GRO-seq results suggest that transcription and
transcript turnover are two potential mechanisms that govern host and viral gene expressions
upon KSHV reactivation.
I identified KSHV-specific downstream super-enhancer elements and corresponding
eRNAs of MYC where active enhancer marks and chromatin modulators were co-bound. While
the MYC super-enhancer elements were found at the upstream of its TSS in EBV+ LCLs, they
were at the downstream in KSHV+ infected or EBV+/KSHV+ co-infected PELs. This may be due
to the lack of certain EBV EBNAs that derive EBV-specific super-enhancer (H. Zhou et al., 2015),
which suggests that in PELs, MYC enhancer regulation is determined by KSHV factors.
KSHV reactivation led to downregulation of the MYC eRNA expression and enhancer
activity, which ultimately lowered MYC expression. Similarly, JQ1-mediated BRD4 perturbation
disrupted the MYC super-enhancer function, reducing both MYC eRNA and mRNA levels. It
should be noted that while RNAi- or CRISPRi-mediated repression of eRNA expression reduced
MYC expression and altered KSHV gene expression, the effects were highly variable potentially
due to the transduction efficiency.
Cellular IRF4 has been shown to turn on expression of critical target genes that play
important roles in PEL cell growth and survival (Manzano et al., 2018). My results show that not
only is cIRF4 an essential oncogene that is regulated by super-enhancers, its protein also binds
to many other super-enhancers that are most significantly dysregulated by reactivation, thus
confirming its crucial role in PEL. Both shRNA-mediated and vIRF4-mediated cIRF4 suppression
resulted in the reduction of MYC eRNAs, although at different levels. This suggests that each
eRNA expression may depend on the level of involvement and binding affinity of several
transcription factors.
Since host reprogramming is intricately regulated by viruses, it is possible that several
different viral factors and pathways are involved in host enhancer modulation. Another
43

mechanism could be a contribution from the highly abundant viral PAN RNA which interacts with
several chromatin modification complexes to regulate gene expression. As several nuclear
lncRNAs have been found to act as eRNA and target enhancers in trans (Alvarez-Dominguez,
Knoll, Gromatzky, & Lodish, 2017; Hsieh et al., 2014), it is possible that the multifunctional viral
ncRNA may directly or indirectly modulate eRNA expression. Furthermore, a recent study has
shown that some eRNAs are not limited to the nucleus and may function in the cytoplasm (Heward,
Roux, & Lindsay, 2015). In this case, these eRNAs may be also targeted by KSHV ORF37 RNase.
Taken together, there are multiple ways that virus may control eRNA expression to regulate
super-enhancer activity. Nevertheless, our analyses identify eRNAs and related transcription
factors that are highly correlated with KSHV gene expression, thus highlighting the importance of
transcriptional and epigenomic dynamics for KSHV lifecycle. Furthermore, our study suggests a
mechanism of how KSHV modulates host enhancer repertoire at different stages of the lifecycle
to benefit its own replication and immune modulation.

44

Chapter 6. Materials and methods

Cell culture
TRExBCBL1 cell lines contain a doxycycline-inducible gene that can be induced with 1 µg/ml
doxycycline (Doxy) to overexpress RTA or vIRF4. All Doxy treatments lasted for 24 h. They were
cultured in RPMI1640 media supplemented with 10% Tet system approved fetal bovine serum
(Clontech), 100 U/ml penicillin, 100µg/ml streptomycin and 20µg/ml hygromycin B. JSC-1 was
grown in RPMI1640 media supplemented with 10% FBS (Clontech), 100 U/ml penicillin and
100µg/ml streptomycin. BCBL-1 with Doxy-inducible shIRF4 or sh-scrambled control (gift from Dr.
Saumendra Sarkar) were grown in RPMI1640 media supplemented with 10% FBS (Clontech),
100 U/ml penicillin and 100µg/ml streptomycin, and selected with 1µg/ml puromycin.

Reagents and antibodies
The following antibodies were used for immunoblot or for ChIP: rabbit anti-histone H3 (Abcam
1791), rabbit anti-H3K27ac (Active Motif 39133), rabbit anti-H3K4me1 (Abcam 8895), rabbit anti-
H3K4me3 (Millipore 04-745), rabbit anti-MYC (Abcam 32072), mouse anti-β-actin (Santa Cruz
47778), rat anti-LANA (Advanced Biotech 13-210-100), rabbit vIRF4 serum (Covance). Rabbit
anti-RTA was a gift from Dr. Yoshihiro Izumiya (UC Davis, USA).

Quantitative real-time PCR (qRT-PCR)
Total RNA was extracted using Tri reagent (Sigma). 1µg of RNA was used for DNase I (Sigma),
reverse-transcribed with iScript cDNA synthesis kit (Bio-Rad), and the resulting cDNA was used
for qPCR. SsoAdvanced Universal SYBR Green Supermix (Bio-Rad) was used for qPCR
according to the manufacturer’s instructions. Each sample was normalized to 18S, and the ddCt
45

fold change method was used to calculate relative quantification. Primer sequences used for qRT-
PCR are found in Table S1.

ChIP-qPCR
Roughly 10µg of chromatin was used for each ChIP. TRExBCBL1-RTA cells were treated with
1µg/ml Doxy for 0 or 24 h, and cross-linked with 1% formaldehyde for 10 min at room temperature
(RT) then quenched using 0.125M glycine. Cells were washed with ice-cold 1XPBS then
resuspended in ice-cold swelling buffer (5mM PIPES pH 8.0, 85mM KCl, 1% Igepal). Cells were
then homogenized using a glass douncer then incubated in nuclei lysis buffer (50mM Tris-Cl pH
8.1, 10mM EDTA, 1% SDS) plus protease inhibitor on ice for 30 min then subjected for sonication
using Bioruptor Pico (Diagenode). The nuclei lysates were then diluted at least 5-folds with ice-
cold IP buffer (50mM Tris pH 7.4, 150mM NaCl, 1% Igepal, 0.25% deoxycholic acid, 1mM EDTA)
with protease inhibitor, then incubated with antibody of interest overnight in 4°C. Magnetic protein
A/G beads (Pierce) were used to pull down each ChIP for 2 h at 4°C, then the immunoprecipitant
was washed twice with IP wash buffer 1 (same as IP dilution buffer, without the protease inhibitor)
then twice with IP wash buffer 2 (100mM Tris-Cl pH 9.0, 500mM LiCl, 1% Igepal, 1% deoxycholic
acid), both in RT. The final antibody/chromatin complexes were eluted using IP elution buffer.
After elution, DNA was purified using MinElute PCR clean up kit (Qiagen) and was subjected for
qPCR or further processed as ChIP-seq library. Primer sequences used for ChIP-qPCR are found
in Table S1.

ChIP-seq
All ChIP-seq libraries were prepared using KAPA Hyper Prep Kit (KAPA KK8503) according to
the manufacturer’s instructions. Samples were sequenced on Illumina NextSeq550 machine
46

using 75-bp single-ended reads. Both H3K27ac and H3K4me1 ChIP-seq experiments were
repeated twice.

GRO-seq
GRO-Seq experiments were performed as previously reported(W. Li et al., 2015). Briefly, 40
million TRExBCBL1-RTA cells during latency and upon reactivation were washed with ice cold
PBS 3 times, incubated with swelling buffer (10mM Tris-Cl pH7.5, 2mM MgCl2, 3mM CaCl2) for
5 min on ice, harvested, and lysed in lysis buffer (swelling buffer plus 0.5% NP-40 and 10%
glycerol). The resultant nuclei were washed one more time with 10mL lysis buffer and finally re-
suspended in 100µL of freezing buffer (50mM Tris-Cl pH8.3, 40% glycerol, 5mM MgCl2, 0.1mM
EDTA). For the run-on assay, re-suspended nuclei were mixed with an equal volume of reaction
buffer (10mM Tris-Cl pH 8.0, 5mM MgCl2, 1mM DTT, 300mM KCl, 20 units of SUPERase-IN,
1% sarkosyl, 500µM ATP, GTP, and Br-UTP, 2µM CTP) and incubated for 5 min at 30°C. The
resultant nuclear-run-on RNA (NRO-RNA) was then extracted with TRIzol LS reagent (Life
Technologies) following manufacturer’s instructions. NRO-RNA was fragmented to ~300-500nt
by alkaline base hydrolysis on ice and followed by treatment with DNase I and Antarctic
phosphatase. These fragmented Br-UTP labeled nascent RNA was then immune-precipitated
with an anti-BrdU agarose beads (SC32323ac, Santa Cruz Biotechnology) in binding buffer
(0.5XSSPE, 1mM EDTA, 0.05% tween) for 3 hrs at 4°C with rotation. Subsequently, T4 PNK
was used to repair the end of the immune-precipitated BrU-NRO-RNA, at 37°C for 1hr. The
RNA was extracted and precipitated using acidic phenol-chloroform. cDNA synthesis was
performed as per a published method (Ingolia, Ghaemmaghami, Newman, & Weissman, 2009)
with few modifications. The RNA fragments were subjected to poly-A tailing reaction by poly-A
polymerase (NEB) for 30 min at 37°C. Subsequently, reverse transcription was performed using
oNTI223 primer (5′-/5Phos/GA TCG TCG GAC TGT AGA ACT CT/idSp/CAA GCA GAA GAC
47

GGC ATA CGA TTT TTT TTT TTT TTT TTT TTV N-3′) and superscript III RT kit (Life
Technologies). The cDNA products were separated on a 10% polyacrylamide TBE-Urea gel and
only those migrated between ~100-500bp were excised and recovered by gel extraction. After
that, the first-strand cDNA was circularized by CircLigase (Epicentre) and re-linearized by APE1
(NEB). Re-linearized single strand cDNA (sscDNA) was separated by a 10% polyacrylamide
TBE gel as described above and the product of needed size was excised (~170-400bp) for gel
extraction. Finally, sscDNA template was amplified by PCR (usually between 10-14 PCR cycles)
using the Phusion High-Fidelity enzyme (NEB) according to the manufacturer’s instructions.
Final libraries were sequenced on the Illumina Hi-Seq 2500 using single-read 100-cycle runs.

Drop digital PCR (ddPCR)
ddPCR was carried out using Bio-Rad system. First, total RNAs were reverse-transcribed using
DNase I (Sigma), reverse-transcribed with iScript cDNA synthesis kit (Bio-Rad) (Bio-Rad).
Droplet formation was carried out using
ddPCR™ Supermix for Probes (Bio-Rad; #1863023) and and QX200 droplet generator (Bio-
Rad) according to the manufacturer’s instructions. The generated oil droplets were transferred
onto a 96- well plate, and subsequently PCR was carried out using BioRad QX200 reader (Bio-
Rad). Data from the droplet reader were given as copies per ng of RNA for accurate
quantification. 40ng and 40pg were used for one ddPCR reaction for eRNA and PAN RNA,
respectively. All primers and probes were synthesized by Integrated DNA technologies (IDT).
Hydrolysis probes contained a 5′-FAM fluorophore and a 3′-Iowa black quencher. Primer
sequences are the same as qRT-PCR primers and probes for the genes studied are indicated
below (5’ to 3’).
e486_Probe: AGCCACAGTGTTCTGGATGTCCTT
e507_Probe: ACGTGACTCCAATTCATCCCACAGT
e530_Probe: AGAAGTCACAGTTACACAAGAGGTACA
48

PANRNA_Probe: CATTGGACTAAAGTGGTGTGCGGC

4C-seq
4C-seq experiments largely followed a published protocol (Stadhouders et al., 2013) with
modification. Briefly, 10 million cells were cross-linked with 1% formaldehyde for 10 min and nuclei
were extracted. Nuclei were resuspended in restriction enzyme buffer and incubated with 0.3 %
SDS for 1h at 37 °C and further incubated with 2% Triton X-100 for 1h. 400U of NlaIII restriction
enzyme was added and incubated overnight. Restriction enzyme was heat inactivated at 65°C for
20 min. Ligation of DNA regions in close physical proximity was performed using 1000U of T4
DNA ligase (NEB) for overnight. After de-crosslinking, the second digestion and ligation were
performed using restriction enzyme DpnII and T4 DNA ligase. 4C-seq libraries were amplified
using first round of PCR with the primers indicated in Table S2. Primers contained illumina
sequencing adaptors, and second round of PCR primers contained Index sequences
(NEBNext
®
Multiplex Oligos for Illumina; New England Biolabs Inc). Samples were sequenced on
Illumina NextSeq550 machine using 75-bp single-ended reads.

3C-PCR
3C-PCR followed previous methods (W. Li et al., 2013). In short, it was performed using NlaIII
restriction enzyme, using primers tested for their efficiency and linearity (primers listed in Table
S2). For results presented, 35 cycles of PCR were performed.

RNA-seq analysis
TRExBCBL1-RTA RNA-seq data (0 h and 24 h) were downloaded from NCBI (GSE123898) and
were aligned to either human hg19 or KSHV JSC-1 BAC16 (GQ994935.1) reference genomes.
49

Aligned .bam files were visualized using Integrative Genomics Viewer (IGV). Correlation
scatterplots comparing RNA-seq and GRO-seq was done using R and the ggplots2 package.

ChIP-seq analysis
H3K27ac and H3K4me1 ChIP-seq were produced in-house, while the rest were downloaded from
NCBI (H3K4me3, GSM1265857; BRD4, GSM2769881; RNAPII, GSM1265864; CTCF,
GSM941710; SMC1, GSM941711). The raw files were initially trimmed and aligned to the hg19
genome using Partek Flow and bowtie2. Reads were trimmed based on quality score from both
the 5’ and 3’ ends. FAIRE-seq data was analyzed similarly (GSM1223899). The resulting
aligned .bam files were either visualized with IGV or used for further analysis using HOMER
(Hypergeometric Optimization of Motif EnRichment). Tag directories were created from the .bam
files using the standard settings. Peak calling for transcription factors, histone markers, and super-
enhancers utilized the “factor,” “histone,” and “super” style options, respectively, with cumulative
Poisson p-value requirement of 0.0001 p-value for removing tag counts that are not statistically
significant. For H3K27ac and H3K4me1 modification, the peak size setting was set to “-size 1000”.
The peaks were annotated using the hg19 genome for HOMER and the resulting .txt file was
imported into excel. For H3K27ac ChIP-seq, potential active enhancers were found by removing
any peaks annotated to the transcription start site. The resulting differential peak files were then
used for motif analysis in HOMER or to generate heatmaps and profiles using NGSPlot.

GRO-seq analysis
Initial trimming and aligning were done same as ChIP-seq data. Tag Directories were created
from the .bam files with standard settings and peaks were identified using the “-style groseq”
option. Peaks were annotated to remove the transcription start site associated peaks and used
for NGSPlot to generate heatmaps and profiles.

50

4C-seq analysis
For all 4C-Seq data, the raw files were directly used for analysis with 4cseqpipe. The hg19
genome was used with the linear mean stat type and trend resolution of 1000.

CRISPR interference
Two small guide RNAs (sgRNAs) were designed for each targeted locus using the Alt-R Custom
Cas9 crRNA Design Tool (IDT) and cloned into the lentiviral vector pLKO.1-U6-2sgRNA-ccdB-
EF1a-Puromycin (A gift for Prof. Xingxu Huang) with the strategy developed by Xingxu Huang
(unpublished). Lentiviral gRNAs or Lenti-dCas9-KRAB-blast plasmids (89567; Addgene) were co-
transfected with packaging plasmids into HEK293T cells using PEI. Culture medium containing
lentivirus particles for gRNA and dCas9–KRAB was harvested after 2 days, and TRExBCBL1-
RTA cells were spin-infected with lentiviruses containing 10 µg/ml polybrene (sigma) and no
antibiotics at 450g for 90 min at 32°C. Fresh media was added to the cells and were incubated in
37°C for 2 days before being selected with 1µg/ml puromycin to select sgRNA expressing cells.
Cells were then harvested 2 days after selection. sgRNA sequences are included in Table S3.

shRNA lentivirus transduction
Lentiviruses were produced in HEK293T using pLKO shRNA system with packaging plasmids
using polyethylenimine (PEI). TRExBCBL1-RTA cells were spin-infected with lentiviruses
containing 10 µg/ml polybrene (sigma) and no antibiotics at 450g for 90 min at 32°C. Fresh media
was added to the cells and were incubated in 37°C for 2 days before being selected with 1µg/ml
puromycin. Cells were then harvested 2 days after selection. shRNA sequences are included in
Table S3.

Statistical analyses
51

The statistical tests were calculated using GraphPad Prism v.6.0 (GraphPad Software, La Jolla,
CA). All data represent at least two independent experiments. Analyses include one-way ANOVA
with Dunnett’s comparison and two-way ANOVA with Bonferroni’s comparison for multi-
component comparisons. And two-tailed unpaired Student’s t-test was used for two component
comparisons. Data are presented as the mean ± SD. Asterisks indicate statistically significant
differences between groups and across time points as determined by t-test. * indicates p < 0.05,
** indicates p < 0.01, and *** indicates p < 0.001.

Data availability
The GRO-seq, 4C-seq, and H3K27ac ChIP-seq were deposited in NCBI GEO database under
accession number GSE147063.

52

Table 2: Primers used for qPCR assays
Primer name Fwd Rev Assay
18S TTCGAACGTCTGCCCTATCAA GATGTGGTAGCCGTTTCTCAGG RT-qPCR
MYC AGAGTTTCATCTGCGACCCG AAGCCGCTCCACATACAGTC RT-qPCR
MYC_e486 GCCCTGTGAAACCTAATGACA AAGAGGGCATGGAGAGTGATT RT-qPCR, ChIP-qPCR
MYC_e507 GCTTTTCCAGATTTCCTGACC AACTATGCACGGTGTCCTGTC RT-qPCR, ChIP-qPCR
MYC_e530 GAATCCATTCAGCCTTTGCT TCTGTCCTCCTTGGGCTCT RT-qPCR, ChIP-qPCR
LANA GAGTCTGGTGACGACTTGGAG AGGAAGGCCAGACTCTTCAAC RT-qPCR
RTA TTGCCAAGTTTGTACAACTGCT ACCTTGCAAAGACCATTCAGAT RT-qPCR
K2 TCACTGCGGGTTAATAGGATTT CATGACGTCCACGTTTATCACT RT-qPCR
ORF 25 ACAGTTTATGGCACGCATAGTG GGTTCTCTGAATCTCGTCGTGT RT-qPCR
cellular IRF4 GGCCAGAGGAAAAACATTGA ATCCTGCTCTGGCACAGTCT RT-qPCR
viral IRF4 GAGCTCCTCAACCAGACAGG GCTGACTATCAGGGGGATCA RT-qPCR

Table 3: Primers used for 4C-seq assays
Primer name Fwd Rev
MYC-promoter
GTTCAGAGTTCTACAGTCCGACGATC
CAGCCGAGCACTCTAGCTCT
AGACGTGTGCTCTTCCGATCT
CTGAGTCTCCTCCCCACCTT
MYC-enhancer
GTTCAGAGTTCTACAGTCCGACGATC
CTCATCTGCCGAAGCCTTT
AGACGTGTGCTCTTCCGATCT
CTGCTGCTCATTTGCATAATG

Table 4: shRNA and sgRNA sequence
Primer name Fwd Rev
shRNA-e486 GGAGGACATGACAGCAGAAGT ACTTCTGCTGTCATGTCCTCC
shRNA-e507 GCCTGCCACATAACATCAATC GATTGATGTTATGTGGCAGGC
shRNA-e530 GCTCTGCTTTGCTAGTTATCT AGATAACTAGCAAAGCAGAGC
sgRNA-e486 GCTTACAAGCCACAGTGTTC ACCCCCGCAAGTTTCATAGA
sgRNA-e507 GGAGTCACAATACATTGGAG CAGCCTATGGATGCAAGCTA
sgRNA-e530 CACCACGTAACCTTCCACCT ATCCACTGGCAACCATTCAC
sgRNA-MYC1 GCGAAGCCCCCTATTCGCTC CGAAAACCGGCTTTTATACT
sgRNA-MYC2 AGGACGCGACTCTCCCGACG TCGCATTATAAAGGGCCGGT
sgRNA-MYC3 AGCTATCCCCTAAAGCGGCT GCTATCTCGGAGACGCACTT
sgRNA-PVT1 TCCTCCGGGCAGAGCGCGTG CCACACGCGCTCTGCCCGGA

53

References

Alvarez-Dominguez, J. R., Knoll, M., Gromatzky, A. A., & Lodish, H. F. (2017). The Super-
Enhancer-Derived alncRNA-EC7/Bloodlinc Potentiates Red Blood Cell Development
in trans. Cell Rep, 19(12), 2503-2514. doi:10.1016/j.celrep.2017.05.082
Arguello, M., Sgarbanti, M., Hernandez, E., Mamane, Y., Sharma, S., Servant, M., . . . Hiscott,
J. (2003). Disruption of the B-cell specific transcriptional program in HHV-8 associated
primary effusion lymphoma cell lines. Oncogene, 22(7), 964-973.
doi:10.1038/sj.onc.1206270
Baresova, P., Pitha, P. M., & Lubyova, B. (2012). Kaposi sarcoma-associated herpesvirus vIRF-
3 protein binds to F-box of Skp2 protein and acts as a regulator of c-Myc protein function
and stability. J Biol Chem, 287(20), 16199-16208. doi:10.1074/jbc.M111.335216
Brulois, K. F., Chang, H., Lee, A. S., Ensser, A., Wong, L. Y., Toth, Z., . . . Jung, J. U. (2012).
Construction and manipulation of a new Kaposi's sarcoma-associated herpesvirus
bacterial artificial chromosome clone. J Virol, 86(18), 9708-9720. doi:10.1128/JVI.01019-
12
Bubman, D., Guasparri, I., & Cesarman, E. (2007). Deregulation of c-Myc in primary effusion
lymphoma by Kaposi's sarcoma herpesvirus latency-associated nuclear antigen.
Oncogene, 26(34), 4979-4986. doi:10.1038/sj.onc.1210299
Calo, E., & Wysocka, J. (2013). Modification of enhancer chromatin: what, how, and why? Mol
Cell, 49(5), 825-837. doi:10.1016/j.molcel.2013.01.038
Campbell, M., Watanabe, T., Nakano, K., Davis, R. R., Lyu, Y., Tepper, C. G., . . . Izumiya, Y.
(2018). KSHV episomes reveal dynamic chromatin loop formation with domain-specific
gene regulation. Nat Commun, 9(1), 49. doi:10.1038/s41467-017-02089-9
Cesarman, E., Chang, Y., Moore, P. S., Said, J. W., & Knowles, D. M. (1995). Kaposi's
sarcoma-associated herpesvirus-like DNA sequences in AIDS-related body-cavity-based
lymphomas. N Engl J Med, 332(18), 1186-1191. doi:10.1056/NEJM199505043321802
Chang, H. H., & Ganem, D. (2013). A unique herpesviral transcriptional program in KSHV-
infected lymphatic endothelial cells leads to mTORC1 activation and rapamycin
sensitivity. Cell Host Microbe, 13(4), 429-440. doi:10.1016/j.chom.2013.03.009
Chang, J., Renne, R., Dittmer, D., & Ganem, D. (2000). Inflammatory cytokines and the
reactivation of Kaposi's sarcoma-associated herpesvirus lytic replication. Virology,
266(1), 17-25. doi:10.1006/viro.1999.0077
Chang, Y., Cesarman, E., Pessin, M. S., Lee, F., Culpepper, J., Knowles, D. M., & Moore, P. S.
(1994). Identification of herpesvirus-like DNA sequences in AIDS-associated Kaposi's
sarcoma. Science, 266(5192), 1865-1869. doi:10.1126/science.7997879
Chen, H. S., Wikramasinghe, P., Showe, L., & Lieberman, P. M. (2012). Cohesins repress
Kaposi's sarcoma-associated herpesvirus immediate early gene transcription during
latency. J Virol, 86(17), 9454-9464. doi:10.1128/JVI.00787-12
54

Chen, J., Ueda, K., Sakakibara, S., Okuno, T., Parravicini, C., Corbellino, M., & Yamanishi, K.
(2001). Activation of latent Kaposi's sarcoma-associated herpesvirus by demethylation of
the promoter of the lytic transactivator. Proc Natl Acad Sci U S A, 98(7), 4119-4124.
doi:10.1073/pnas.051004198
Chen, J., Ueda, K., Sakakibara, S., Okuno, T., & Yamanishi, K. (2000). Transcriptional
regulation of the Kaposi's sarcoma-associated herpesvirus viral interferon regulatory
factor gene. J Virol, 74(18), 8623-8634. doi:10.1128/jvi.74.18.8623-8634.2000
Cheng, F., Pekkonen, P., Laurinavicius, S., Sugiyama, N., Henderson, S., Günther, T., . . .
Ojala, P. M. (2011). KSHV-initiated notch activation leads to membrane-type-1 matrix
metalloproteinase-dependent lymphatic endothelial-to-mesenchymal transition. Cell Host
Microbe, 10(6), 577-590. doi:10.1016/j.chom.2011.10.011
Clyde, K., & Glaunsinger, B. A. (2011). Deep sequencing reveals direct targets of
gammaherpesvirus-induced mRNA decay and suggests that multiple mechanisms
govern cellular transcript escape. PLoS One, 6(5), e19655.
doi:10.1371/journal.pone.0019655
Core, L. J., Waterfall, J. J., & Lis, J. T. (2008). Nascent RNA sequencing reveals widespread
pausing and divergent initiation at human promoters. Science, 322(5909), 1845-1848.
doi:10.1126/science.1162228
Cousins, E., & Nicholas, J. (2014). Molecular biology of human herpesvirus 8: novel functions
and virus-host interactions implicated in viral pathogenesis and replication. Recent
Results Cancer Res, 193, 227-268. doi:10.1007/978-3-642-38965-8_13
Davison, A. J. (2010). Herpesvirus systematics. Vet Microbiol, 143(1), 52-69.
doi:10.1016/j.vetmic.2010.02.014
Davison, A. J., Eberle, R., Ehlers, B., Hayward, G. S., McGeoch, D. J., Minson, A. C., . . . Thiry,
E. (2009). The order Herpesvirales. Arch Virol, 154(1), 171-177. doi:10.1007/s00705-
008-0278-4
Dekker, J., Rippe, K., Dekker, M., & Kleckner, N. (2002). Capturing chromosome conformation.
Science, 295(5558), 1306-1311. doi:10.1126/science.1067799
Delmore, J. E., Issa, G. C., Lemieux, M. E., Rahl, P. B., Shi, J., Jacobs, H. M., . . . Mitsiades, C.
S. (2011). BET bromodomain inhibition as a therapeutic strategy to target c-Myc. Cell,
146(6), 904-917. doi:10.1016/j.cell.2011.08.017
Di Bartolo, D. L., Cannon, M., Liu, Y. F., Renne, R., Chadburn, A., Boshoff, C., & Cesarman, E.
(2008). KSHV LANA inhibits TGF-beta signaling through epigenetic silencing of the
TGF-beta type II receptor. Blood, 111(9), 4731-4740. doi:10.1182/blood-2007-09-
110544
El-Araby, A. M., Fouad, A. A., Hanbal, A. M., Abdelwahab, S. M., Qassem, O. M., & El-Araby,
M. E. (2016). Epigenetic Pathways of Oncogenic Viruses: Therapeutic Promises. Arch
Pharm (Weinheim), 349(2), 73-90. doi:10.1002/ardp.201500375
Filippakopoulos, P., Qi, J., Picaud, S., Shen, Y., Smith, W. B., Fedorov, O., . . . Bradner, J. E.
(2010). Selective inhibition of BET bromodomains. Nature, 468(7327), 1067-1073.
doi:10.1038/nature09504
55

Forero, A., McCormick, K. D., Jenkins, F. J., & Sarkar, S. N. (2014). Downregulation of IRF4
induces lytic reactivation of KSHV in primary effusion lymphoma cells. Virology, 458-459,
4-10. doi:10.1016/j.virol.2014.04.020
Gabay, M., Li, Y., & Felsher, D. W. (2014). MYC activation is a hallmark of cancer initiation and
maintenance. Cold Spring Harb Perspect Med, 4(6). doi:10.1101/cshperspect.a014241
Glaunsinger, B., Chavez, L., & Ganem, D. (2005). The exonuclease and host shutoff functions
of the SOX protein of Kaposi's sarcoma-associated herpesvirus are genetically
separable. J Virol, 79(12), 7396-7401. doi:10.1128/JVI.79.12.7396-7401.2005
Gloghini, A., Volpi, C. C., Gualeni, A. V., Dolcetti, R., Bongarzone, I., De Paoli, P., & Carbone,
A. (2017). Multiple viral infections in primary effusion lymphoma: a model of viral
cooperation in lymphomagenesis. Expert Rev Hematol, 10(6), 505-514.
doi:10.1080/17474086.2017.1326815
Gonçalves, P. H., Uldrick, T. S., & Yarchoan, R. (2017). HIV-associated Kaposi sarcoma and
related diseases. AIDS, 31(14), 1903-1916. doi:10.1097/QAD.0000000000001567
Gottwein, E. (2012). Kaposi's Sarcoma-Associated Herpesvirus microRNAs. Front Microbiol, 3,
165. doi:10.3389/fmicb.2012.00165
Guasparri, I., Keller, S. A., & Cesarman, E. (2004). KSHV vFLIP is essential for the survival of
infected lymphoma cells. J Exp Med, 199(7), 993-1003. doi:10.1084/jem.20031467
Günther, T., & Grundhoff, A. (2010). The epigenetic landscape of latent Kaposi sarcoma-
associated herpesvirus genomes. PLoS Pathog, 6(6), e1000935.
doi:10.1371/journal.ppat.1000935
Hair, J. R., Lyons, P. A., Smith, K. G., & Efstathiou, S. (2007). Control of Rta expression
critically determines transcription of viral and cellular genes following gammaherpesvirus
infection. J Gen Virol, 88(Pt 6), 1689-1697. doi:10.1099/vir.0.82548-0
Heward, J. A., Roux, B. T., & Lindsay, M. A. (2015). Divergent signalling pathways regulate
lipopolysaccharide-induced eRNA expression in human monocytic THP1 cells. FEBS
Lett, 589(3), 396-406. doi:10.1016/j.febslet.2014.12.026
Hilton, I. B., Simon, J. M., Lieb, J. D., Davis, I. J., Damania, B., & Dittmer, D. P. (2013). The
open chromatin landscape of Kaposi's sarcoma-associated herpesvirus. J Virol, 87(21),
11831-11842. doi:10.1128/JVI.01685-13
Hnisz, D., Abraham, B. J., Lee, T. I., Lau, A., Saint-Andre, V., Sigova, A. A., . . . Young, R. A.
(2013). Super-enhancers in the control of cell identity and disease. Cell, 155(4), 934-
947. doi:10.1016/j.cell.2013.09.053
Hsieh, C. L., Fei, T., Chen, Y., Li, T., Gao, Y., Wang, X., . . . Kantoff, P. W. (2014). Enhancer
RNAs participate in androgen receptor-driven looping that selectively enhances gene
activation. Proc Natl Acad Sci U S A, 111(20), 7319-7324.
doi:10.1073/pnas.1324151111
Hu, J., Yang, Y., Turner, P. C., Jain, V., McIntyre, L. M., & Renne, R. (2014). LANA binds to
multiple active viral and cellular promoters and associates with the
H3K4methyltransferase hSET1 complex. PLoS Pathog, 10(7), e1004240.
doi:10.1371/journal.ppat.1004240
56

Hutin, S., Lee, Y., & Glaunsinger, B. A. (2013). An RNA element in human interleukin 6 confers
escape from degradation by the gammaherpesvirus SOX protein. J Virol, 87(8), 4672-
4682. doi:10.1128/JVI.00159-13
Ingolia, N. T., Ghaemmaghami, S., Newman, J. R., & Weissman, J. S. (2009). Genome-wide
analysis in vivo of translation with nucleotide resolution using ribosome profiling.
Science, 324(5924), 218-223. doi:10.1126/science.1168978
Iwata, A., Durai, V., Tussiwand, R., Briseno, C. G., Wu, X., Grajales-Reyes, G. E., . . . Murphy,
K. M. (2017). Quality of TCR signaling determined by differential affinities of enhancers
for the composite BATF-IRF4 transcription factor complex. Nat Immunol, 18(5), 563-572.
doi:10.1038/ni.3714
Jacobs, S. R., & Damania, B. (2011). The viral interferon regulatory factors of KSHV:
immunosuppressors or oncogenes? Front Immunol, 2, 19.
doi:10.3389/fimmu.2011.00019
Jin, Q., Yu, L. R., Wang, L., Zhang, Z., Kasper, L. H., Lee, J. E., . . . Ge, K. (2011). Distinct roles
of GCN5/PCAF-mediated H3K9ac and CBP/p300-mediated H3K18/27ac in nuclear
receptor transactivation. EMBO J, 30(2), 249-262. doi:10.1038/emboj.2010.318
Kang, H., Wiedmer, A., Yuan, Y., Robertson, E., & Lieberman, P. M. (2011). Coordination of
KSHV latent and lytic gene control by CTCF-cohesin mediated chromosome
conformation. PLoS Pathog, 7(8), e1002140. doi:10.1371/journal.ppat.1002140
Katano, H., & Sata, T. (2000). Human herpesvirus 8 virology, epidemiology and related
diseases. Jpn J Infect Dis, 53(4), 137-155.
Katano, H., Sato, Y., & Sata, T. (2001). Expression of p53 and human herpesvirus-8 (HHV-8)-
encoded latency-associated nuclear antigen with inhibition of apoptosis in HHV-8-
associated malignancies. Cancer, 92(12), 3076-3084. doi:10.1002/1097-
0142(20011215)92:12<3076::aid-cncr10117>3.0.co;2-d
Kedes, D. H., Lagunoff, M., Renne, R., & Ganem, D. (1997). Identification of the gene encoding
the major latency-associated nuclear antigen of the Kaposi's sarcoma-associated
herpesvirus. J Clin Invest, 100(10), 2606-2610. doi:10.1172/JCI119804
Lam, M. T., Cho, H., Lesch, H. P., Gosselin, D., Heinz, S., Tanaka-Oishi, Y., . . . Glass, C. K.
(2013). Rev-Erbs repress macrophage gene expression by inhibiting enhancer-directed
transcription. Nature, 498(7455), 511-515. doi:10.1038/nature12209
Lam, M. T., Li, W., Rosenfeld, M. G., & Glass, C. K. (2014). Enhancer RNAs and regulated
transcriptional programs. Trends Biochem Sci, 39(4), 170-182.
doi:10.1016/j.tibs.2014.02.007
Lancho, O., & Herranz, D. (2018). The MYC Enhancer-ome: Long-Range Transcriptional
Regulation of MYC in Cancer. Trends Cancer, 4(12), 810-822.
doi:10.1016/j.trecan.2018.10.003
Lee, H. R., Doganay, S., Chung, B., Toth, Z., Brulois, K., Lee, S., . . . Jung, J. U. (2014).
Kaposi's sarcoma-associated herpesvirus viral interferon regulatory factor 4 (vIRF4)
targets expression of cellular IRF4 and the Myc gene to facilitate lytic replication. J Virol,
88(4), 2183-2194. doi:10.1128/JVI.02106-13
57

Lettice, L. A., Heaney, S. J., Purdie, L. A., Li, L., de Beer, P., Oostra, B. A., . . . de Graaff, E.
(2003). A long-range Shh enhancer regulates expression in the developing limb and fin
and is associated with preaxial polydactyly. Hum Mol Genet, 12(14), 1725-1735.
doi:10.1093/hmg/ddg180
Li, M., Damania, B., Alvarez, X., Ogryzko, V., Ozato, K., & Jung, J. U. (2000). Inhibition of p300
histone acetyltransferase by viral interferon regulatory factor. Mol Cell Biol, 20(21), 8254-
8263. doi:10.1128/mcb.20.21.8254-8263.2000
Li, W., Hu, Y., Oh, S., Ma, Q., Merkurjev, D., Song, X., . . . Rosenfeld, M. G. (2015). Condensin I
and II Complexes License Full Estrogen Receptor alpha-Dependent Enhancer
Activation. Mol Cell, 59(2), 188-202. doi:10.1016/j.molcel.2015.06.002
Li, W., Notani, D., Ma, Q., Tanasa, B., Nunez, E., Chen, A. Y., . . . Rosenfeld, M. G. (2013).
Functional roles of enhancer RNAs for oestrogen-dependent transcriptional activation.
Nature, 498(7455), 516-520. doi:10.1038/nature12210
Li, W., Notani, D., & Rosenfeld, M. G. (2016). Enhancers as non-coding RNA transcription units:
recent insights and future perspectives. Nat Rev Genet, 17(4), 207-223.
doi:10.1038/nrg.2016.4
Li, X., Chen, S., Feng, J., Deng, H., & Sun, R. (2010). Myc is required for the maintenance of
Kaposi's sarcoma-associated herpesvirus latency. J Virol, 84(17), 8945-8948.
doi:10.1128/JVI.00244-10
Liang, J., Zhou, H., Gerdt, C., Tan, M., Colson, T., Kaye, K. M., . . . Zhao, B. (2016). Epstein-
Barr virus super-enhancer eRNAs are essential for MYC oncogene expression and
lymphoblast proliferation. Proc Natl Acad Sci U S A, 113(49), 14121-14126.
doi:10.1073/pnas.1616697113
Lin, C. L., Li, H., Wang, Y., Zhu, F. X., Kudchodkar, S., & Yuan, Y. (2003). Kaposi's sarcoma-
associated herpesvirus lytic origin (ori-Lyt)-dependent DNA replication: identification of
the ori-Lyt and association of K8 bZip protein with the origin. J Virol, 77(10), 5578-5588.
doi:10.1128/jvi.77.10.5578-5588.2003
Liu, J., Martin, H. J., Liao, G., & Hayward, S. D. (2007). The Kaposi's sarcoma-associated
herpesvirus LANA protein stabilizes and activates c-Myc. J Virol, 81(19), 10451-10459.
doi:10.1128/JVI.00804-07
Lu, F., Tsai, K., Chen, H. S., Wikramasinghe, P., Davuluri, R. V., Showe, L., . . . Lieberman, P.
M. (2012). Identification of host-chromosome binding sites and candidate gene targets
for Kaposi's sarcoma-associated herpesvirus LANA. J Virol, 86(10), 5752-5762.
doi:10.1128/JVI.07216-11
Lu, F., Zhou, J., Wiedmer, A., Madden, K., Yuan, Y., & Lieberman, P. M. (2003). Chromatin
remodeling of the Kaposi's sarcoma-associated herpesvirus ORF50 promoter correlates
with reactivation from latency. J Virol, 77(21), 11425-11435.
doi:10.1128/jvi.77.21.11425-11435.2003
Lukac, D. M., Renne, R., Kirshner, J. R., & Ganem, D. (1998). Reactivation of Kaposi's
sarcoma-associated herpesvirus infection from latency by expression of the ORF 50
transactivator, a homolog of the EBV R protein. Virology, 252(2), 304-312.
doi:10.1006/viro.1998.9486
58

Manzano, M., Patil, A., Waldrop, A., Dave, S. S., Behdad, A., & Gottwein, E. (2018). Gene
essentiality landscape and druggable oncogenic dependencies in herpesviral primary
effusion lymphoma. Nat Commun, 9(1), 3263. doi:10.1038/s41467-018-05506-9
Moore, P. S., & Chang, Y. (1998). Antiviral activity of tumor-suppressor pathways: clues from
molecular piracy by KSHV. Trends Genet, 14(4), 144-150. doi:10.1016/s0168-
9525(98)01408-5
Moore, P. S., & Chang, Y. (2003). Kaposi's sarcoma-associated herpesvirus immunoevasion
and tumorigenesis: two sides of the same coin? Annu Rev Microbiol, 57, 609-639.
doi:10.1146/annurev.micro.57.030502.090824
Morton, J. P., & Sansom, O. J. (2013). MYC-y mice: from tumour initiation to therapeutic
targeting of endogenous MYC. Mol Oncol, 7(2), 248-258.
doi:10.1016/j.molonc.2013.02.015
Nakamura, H., Lu, M., Gwack, Y., Souvlis, J., Zeichner, S. L., & Jung, J. U. (2003). Global
changes in Kaposi's sarcoma-associated virus gene expression patterns following
expression of a tetracycline-inducible Rta transactivator. J Virol, 77(7), 4205-4220.
doi:10.1128/jvi.77.7.4205-4220.2003
Okada, S., Goto, H., & Yotsumoto, M. (2014). Current status of treatment for primary effusion
lymphoma. Intractable Rare Dis Res, 3(3), 65-74. doi:10.5582/irdr.2014.01010
Oksenhendler, E., Boulanger, E., Galicier, L., Du, M. Q., Dupin, N., Diss, T. C., . . . Meignin, V.
(2002). High incidence of Kaposi sarcoma-associated herpesvirus-related non-Hodgkin
lymphoma in patients with HIV infection and multicentric Castleman disease. Blood,
99(7), 2331-2336. doi:10.1182/blood.v99.7.2331
Papp, B., Motlagh, N., Smindak, R. J., Jin Jang, S., Sharma, A., Alonso, J. D., & Toth, Z. (2019).
Genome-Wide Identification of Direct RTA Targets Reveals Key Host Factors for
Kaposi's Sarcoma-Associated Herpesvirus Lytic Reactivation. J Virol, 93(5).
doi:10.1128/JVI.01978-18
Pombo, A., & Dillon, N. (2015). Three-dimensional genome architecture: players and
mechanisms. Nat Rev Mol Cell Biol, 16(4), 245-257. doi:10.1038/nrm3965
Purushothaman, P., Dabral, P., Gupta, N., Sarkar, R., & Verma, S. C. (2016). KSHV Genome
Replication and Maintenance. Front Microbiol, 7, 54. doi:10.3389/fmicb.2016.00054
Qin, J., Li, W., Gao, S. J., & Lu, C. (2017). KSHV microRNAs: Tricks of the Devil. Trends
Microbiol, 25(8), 648-661. doi:10.1016/j.tim.2017.02.002
Rainbow, L., Platt, G. M., Simpson, G. R., Sarid, R., Gao, S. J., Stoiber, H., . . . Schulz, T. F.
(1997). The 222- to 234-kilodalton latent nuclear protein (LNA) of Kaposi's sarcoma-
associated herpesvirus (human herpesvirus 8) is encoded by orf73 and is a component
of the latency-associated nuclear antigen. J Virol, 71(8), 5915-5921.
Renne, R., Lagunoff, M., Zhong, W., & Ganem, D. (1996). The size and conformation of
Kaposi's sarcoma-associated herpesvirus (human herpesvirus 8) DNA in infected cells
and virions. J Virol, 70(11), 8151-8154.
59

Rossetto, C. C., & Pari, G. (2012). KSHV PAN RNA associates with demethylases UTX and
JMJD3 to activate lytic replication through a physical interaction with the virus genome.
PLoS Pathog, 8(5), e1002680. doi:10.1371/journal.ppat.1002680
Rossetto, C. C., & Pari, G. S. (2014). PAN's Labyrinth: Molecular biology of Kaposi's sarcoma-
associated herpesvirus (KSHV) PAN RNA, a multifunctional long noncoding RNA.
Viruses, 6(11), 4212-4226. doi:10.3390/v6114212
Russo, J. J., Bohenzky, R. A., Chien, M. C., Chen, J., Yan, M., Maddalena, D., . . . Moore, P. S.
(1996). Nucleotide sequence of the Kaposi sarcoma-associated herpesvirus (HHV8).
Proc Natl Acad Sci U S A, 93(25), 14862-14867. doi:10.1073/pnas.93.25.14862
Schneider, J. W., & Dittmer, D. P. (2017). Diagnosis and Treatment of Kaposi Sarcoma. Am J
Clin Dermatol, 18(4), 529-539. doi:10.1007/s40257-017-0270-4
Schoenfelder, S., & Fraser, P. (2019). Long-range enhancer-promoter contacts in gene
expression control. Nat Rev Genet, 20(8), 437-455. doi:10.1038/s41576-019-0128-0
Schuijers, J., Manteiga, J. C., Weintraub, A. S., Day, D. S., Zamudio, A. V., Hnisz, D., . . .
Young, R. A. (2018). Transcriptional Dysregulation of MYC Reveals Common Enhancer-
Docking Mechanism. Cell Rep, 23(2), 349-360. doi:10.1016/j.celrep.2018.03.056
Schulz, T. F. (1999). Epidemiology of Kaposi's sarcoma-associated herpesvirus/human
herpesvirus 8. Adv Cancer Res, 76, 121-160. doi:10.1016/s0065-230x(08)60775-7
Shin, H. J., DeCotiis, J., Giron, M., Palmeri, D., & Lukac, D. M. (2014). Histone deacetylase
classes I and II regulate Kaposi's sarcoma-associated herpesvirus reactivation. J Virol,
88(2), 1281-1292. doi:10.1128/JVI.02665-13
Shlyueva, D., Stampfel, G., & Stark, A. (2014). Transcriptional enhancers: from properties to
genome-wide predictions. Nat Rev Genet, 15(4), 272-286. doi:10.1038/nrg3682
Speck, S. H., & Ganem, D. (2010). Viral latency and its regulation: lessons from the gamma-
herpesviruses. Cell Host Microbe, 8(1), 100-115. doi:10.1016/j.chom.2010.06.014
Stadhouders, R., Kolovos, P., Brouwer, R., Zuin, J., van den Heuvel, A., Kockx, C., . . . Soler, E.
(2013). Multiplexed chromosome conformation capture sequencing for rapid genome-
scale high-resolution detection of long-range chromatin interactions. Nat Protoc, 8(3),
509-524. doi:10.1038/nprot.2013.018
Staskus, K. A., Zhong, W., Gebhard, K., Herndier, B., Wang, H., Renne, R., . . . Haase, A. T.
(1997). Kaposi's sarcoma-associated herpesvirus gene expression in endothelial
(spindle) tumor cells. J Virol, 71(1), 715-719.
Sun, R., Lin, S. F., Gradoville, L., Yuan, Y., Zhu, F., & Miller, G. (1998). A viral gene that
activates lytic cycle expression of Kaposi's sarcoma-associated herpesvirus. Proc Natl
Acad Sci U S A, 95(18), 10866-10871. doi:10.1073/pnas.95.18.10866
Thakker, S., & Verma, S. C. (2016). Co-infections and Pathogenesis of KSHV-Associated
Malignancies. Front Microbiol, 7, 151. doi:10.3389/fmicb.2016.00151
Thakore, P. I., D'Ippolito, A. M., Song, L., Safi, A., Shivakumar, N. K., Kabadi, A. M., . . .
Gersbach, C. A. (2015). Highly specific epigenome editing by CRISPR-Cas9 repressors
60

for silencing of distal regulatory elements. Nat Methods, 12(12), 1143-1149.
doi:10.1038/nmeth.3630
Tolani, B., Gopalakrishnan, R., Punj, V., Matta, H., & Chaudhary, P. M. (2014). Targeting Myc in
KSHV-associated primary effusion lymphoma with BET bromodomain inhibitors.
Oncogene, 33(22), 2928-2937. doi:10.1038/onc.2013.242
Toth, Z., Brulois, K., Lee, H. R., Izumiya, Y., Tepper, C., Kung, H. J., & Jung, J. U. (2013).
Biphasic euchromatin-to-heterochromatin transition on the KSHV genome following de
novo infection. PLoS Pathog, 9(12), e1003813. doi:10.1371/journal.ppat.1003813
Toth, Z., Brulois, K. F., Wong, L. Y., Lee, H. R., Chung, B., & Jung, J. U. (2012). Negative
elongation factor-mediated suppression of RNA polymerase II elongation of Kaposi's
sarcoma-associated herpesvirus lytic gene expression. J Virol, 86(18), 9696-9707.
doi:10.1128/JVI.01012-12
Toth, Z., Maglinte, D. T., Lee, S. H., Lee, H. R., Wong, L. Y., Brulois, K. F., . . . Jung, J. U.
(2010). Epigenetic analysis of KSHV latent and lytic genomes. PLoS Pathog, 6(7),
e1001013. doi:10.1371/journal.ppat.1001013
Uppal, T., Banerjee, S., Sun, Z., Verma, S. C., & Robertson, E. S. (2014). KSHV LANA--the
master regulator of KSHV latency. Viruses, 6(12), 4961-4998. doi:10.3390/v6124961
Uppal, T., Jha, H. C., Verma, S. C., & Robertson, E. S. (2015). Chromatinization of the KSHV
Genome During the KSHV Life Cycle. Cancers (Basel), 7(1), 112-142.
doi:10.3390/cancers7010112
Vaharautio, A., & Taipale, J. (2014). Cancer. Cancer by super-enhancer. Science, 346(6215),
1291-1292. doi:10.1126/science.aaa3247
Whyte, W. A., Orlando, D. A., Hnisz, D., Abraham, B. J., Lin, C. Y., Kagey, M. H., . . . Young, R.
A. (2013). Master transcription factors and mediator establish super-enhancers at key
cell identity genes. Cell, 153(2), 307-319. doi:10.1016/j.cell.2013.03.035
Wu, M., & Shen, J. (2019). From Super-Enhancer Non-coding RNA to Immune Checkpoint:
Frameworks to Functions. Front Oncol, 9, 1307. doi:10.3389/fonc.2019.01307
Zabidi, M. A., Arnold, C. D., Schernhuber, K., Pagani, M., Rath, M., Frank, O., & Stark, A.
(2015). Enhancer-core-promoter specificity separates developmental and housekeeping
gene regulation. Nature, 518(7540), 556-559. doi:10.1038/nature13994
Zhou, F., Shimoda, M., Olney, L., Lyu, Y., Tran, K., Jiang, G., . . . Izumiya, Y. (2017). Oncolytic
Reactivation of KSHV as a Therapeutic Approach for Primary Effusion Lymphoma. Mol
Cancer Ther, 16(11), 2627-2638. doi:10.1158/1535-7163.MCT-17-0041
Zhou, H., Schmidt, S. C., Jiang, S., Willox, B., Bernhardt, K., Liang, J., . . . Zhao, B. (2015).
Epstein-Barr virus oncoprotein super-enhancers control B cell growth. Cell Host Microbe,
17(2), 205-216. doi:10.1016/j.chom.2014.12.013
Zhu, F. X., Chong, J. M., Wu, L., & Yuan, Y. (2005). Virion proteins of Kaposi's sarcoma-
associated herpesvirus. J Virol, 79(2), 800-811. doi:10.1128/JVI.79.2.800-811.2005

61

Addendum. KSHV epigenome in oral Kaposi’s Sarcoma
This section is adapted from a grant proposal that was accepted
by the National Institute of Dental and Craniofacial Research (NIDCR).

62

Abstract
Kaposi’s sarcoma-associated herpesvirus (KSHV) is the etiological agent of Kaposi’s
sarcoma (KS) and several lymphoid malignancies (Cesarman, Chang, Moore, Said, & Knowles,
1995; Chang et al., 1994; Soulier et al., 1995). Oral lesion is the initial site of involvement in many
KS cases, and often the first indication of HIV infection(Goncalves, Uldrick, & Yarchoan, 2017).
Nearly 25 years after the identification of KSHV, however, the initial steps in KSHV oral infection
and the expressions of host and KSHV genes are still poorly understood. While KSHV establishes
latency in most cells and in KSHV-associated complications by default, it leads to spontaneous
lytic replication in oral epithelial cells and oral lesions—which is why oral KS sheds much more
viral particles than other KS (Duus, Lentchitsky, Wagenaar, Grose, & Webster-Cyriaque, 2004).
Our previous works suggest that epigenetic regulation is one of the major drivers for this
discrepancy. While KSHV latency is characterized by restricted viral gene expression profile, its
reactivation induces lytic replication program with viral gene expression profile in a defined
sequential and temporal order. Based on our preliminary studies on epigenetic modification of the
viral genome, we hypothesize that sophisticated epigenomic regulations—from histone
modifications to high-order genomic structure—are crucial in determining KSHV latent infection
and lytic reactivation in oral KS. To test our hypothesis, we first investigated the alteration of KSHV
3D genomic structure during latency and lytic reactivation in various cell types including oral
epithelial cells, and the identification of host factors responsible for the viral high-order genomic
structure and gene expression (Aim 1). Next, we developed a 3D organotypic oral tissue infection
model that mimics in vivo oral transmission and identify the alteration of host and viral gene
expressions and epigenetic regulations at the single cell level (Aim 2). We used various high-
throughput sequencing technologies such as 4C-seq, GRO-seq and single-cell RNA-seq (scRNA-
seq), and bioinformatics, Bacmid genetics and 3D organotypic culture. A successful development
of KSHV intragenomic physical interaction and 3D organotypic oral tissue infection model will
provide insights into KSHV oral transmission and complication.
63

Introduction

Transcriptionally permissive chromatin assembly on the KSHV genome in oral epithelial
cells
When three different oral epithelial cells (OEPI human gingiva-derived primary epithelial
cells, SCC15 human tongue squamous carcinoma cells and NOK primary normal oral
keratinocytes cells) were used for KSHV infection, KSHV replication was only detected in OEPI
cells (Figure 1) (Toth et al., 2013). KSHV was initially chromatinized in infected OEPI cells at 8-
24 hpi, but the viral DNA became chromatin-depleted during replication. Euchromatinization
(H3K4me3 and H3K27ac) increased on the representative latent (LANA), IE (RTA), E (K2) and L
(ORF25) promoter regions, but the efficient deposition of heterochromatin histone marks
(H3K27me3 and H2AK119ub) was not observed on these regions (Figure 1B). Polycomb protein
levels were lower in OEPI cells than in NOK and SCC15 cells (Figure 1C), suggesting that the
low level of PcG protein correlates with the high level of KSHV replication in OEPI cells. Thus, the
differential epigenetic modification of the KSHV genome in distinct cell types is a potential
determining factor for latent infection vs. lytic replication of KSHV.

64

Figure 1. Euchromatinization of the KSHV genome in gingival oral epithelial cells.
(A) Measurement of viral DNA replication in SLK, OEPI, SCC15 and NOK cells infected by KSHV.
The viral DNA polymerase inhibitor, PAA, was applied to block the replication of KSHV. (B) ChIP
analysis of the indicated histone modifications on selected KSHV promoters in OEPI cells at 8,
24 and 72 hpi. ACT and MYT1 promoters were controls. (C) Immunoblot analysis of the indicated
host proteins in SLK and oral epithelial cells. Figure adapted from (Toth et al., 2013).

KSHV genomic structure
The chromatin-organizing factors, CCCTC-binding factor (CTCF) and cohesin protein
complex, function in DNA loop formation that is important for herpesvirus episomal structure
and gene expression (Phillips & Corces, 2009; Rubio et al., 2008). Dr. Lieberman’s group has
pioneered that the CTCF/cohesion complex establishes physical looping of the KSHV genome
(Chen, Wikramasinghe, Showe, & Lieberman, 2012; Kang, Wiedmer, Yuan, Robertson, &
Lieberman, 2011; Stedman et al., 2008). Specifically, their 3C studies revealed that the CTCF–
cohesin site in the latency control region forms two loops: a short loop between the CTCF
clusters of LANA and K12, encompassing the major latency transcripts; and a large loop
65

between the CTCF–cohesin sites and the control region for lytic transcripts of RTA, ORF45,
ORF46 and ORF47 (Figure 2A). Depletion of cohesin subunits or CTCF binding sites on KSHV
genome leads to a loss of DNA loop structures and a robust stimulation of lytic transcription,
suggesting that the CTCF-cohesin complex at the latency control region functions as a
repressor of lytic transcription. Thus, CTCF-cohesin-mediated loops can function in both
activation and repression of viral transcription. In addition, Dr. Izumiya’s group has,
demonstrated the high-resolution 3D KSHV genomic maps that show a physical, long-range, and
dynamic genomic interactions at the global level (Campbell et al., 2018). Mutant KSHV
chromosomes harboring point mutations in the RTA-responsive elements (RE) significantly
attenuate not only the directly proximal downstream gene, but also distal gene expression in a
domain-specific manner. This study suggests that multiple RE-containing genomic regions (ex:
RTA promoter, K12 and PAN loci) are positioned in close proximity to each other via 3D KSHV
genomic structure, which facilitates RTA to activate promoters efficiently (Figure 2B). RTA
expression further increases this “viral active chromatin hub” to induce efficient lytic gene
expression. These indicate the importance of genomic architectural dynamics for herpesvirus
gene expression.
Figure 2. High-order genomic structure of KSHV genome.
(A) CTCF and cohesion complex mediates looping at the 5’ and 3’ ends of the major latent locus,
and also from the latent locus to the lytic locus. Figure adapted from (Kang et al., 2011) (B) K12
and PAN loci are in close proximity to create KSHV active chromatin hub (Campbell et al., 2018).

66

KSHV infection in 3D oral epithelial organotypic raft culture
Cells are often statically cultured as monolayers on flat surfaces, and these conditions do
not faithfully reflect the biological situation in vivo given that proper tissue architecture and cell–
cell contacts are lost in such 2D cell culture. 3D cell culture are well documented to regain intrinsic
properties and to better mimic the in vivo situation than 2D cell culture (Langhans, 2018). Indeed,
the gene expression profiles as well as the responses to stress and infection in 3D culture
resemble more closely the in vivo situation than those in 2D culture. Similar to human tissues,
proliferating, quiescent and dying cells coexist in normoxic, hypoxic or necrotic zones within 3D
spheroids (Hirschhaeuser et al., 2010). The 3D oral tissue system that we utilized consists of
normal, human-derived primary oral epithelial cells that have been cultured to form multilayered,
highly differentiated models of the human buccal phenotypes. The tissues, which are cultured on
specially prepared cell culture inserts, attain levels of differentiation on the cutting edge of in vitro
air-liquid interface technology (Figure 3A). 3D oral organotypic raft culture exhibits in vivo-like
morphology and growth characteristics which are highly reproducible. It has a multilayered tissue
consisting of an organized basal layer and multiple non-cornified layers analogous to native
human oral tissue and each layer has specific differential markers (Figure 3B).

67

Figure 3. Development and differentiation markers of human 3D oral epithelial raft
culture.
(A) Preparation of organotypic epithelial raft cultures from human primary oral epithelial cells.
Figure adapted from (Andrei, Duraffour, Van den Oord, & Snoeck, 2010). (B) Example of an
organotypic raft culture showing epidermal organization. The stratified epidermis consists of
basal, spinous, granular and the cornified layer, assembled upon the basement membrane.
Each layer has morphological hallmarks and expresses distinct keratin markers.

A
68

Aim 1. Differential regulation of KSHV 3D genomic structure and gene expression
Previously, our lab has extensively profiled KSHV genome-wide epigenetic regulation for
viral gene expression. This section aims to add another level of epigenetic regulation—high-
ordered genomic organization and chromatin availability—to define how KSHV hijacks the host
epigenetic system to fine-tune its own gene expression. We hypothesize that the KSHV
undertakes distinct 3D genomic structures upon de novo infection of oral epithelial cells or other
cell types, leading to reactivation or latency, respectively. As expression of KSHV RTA
transcription factor is a major determinant for two different lifecycles, we will primarily focus on
comparing the intragenomic interactions of RTA promoter regions in oral epithelial cells or other
cell types upon de novo infection. We perform 4C-seq, ATAC-seq, ChIP-seq, and GRO-seq, and
re-analyze available ChIP-seq data to detail the KSHV 3D genomic structure and gene expression
profile. We will also utilize the Bacmid-mediated mutation of KSHV RTA promoter regions to alter
KSHV intragenomic interactions and test their gene expressions. This study will show that the
high-ordered genomic regulation of KSHV is important to determine viral lifecycle. Furthermore,
this aim along with the previous epigenetic study will be the underpinning of the epigenomic study
of KSHV in 3D organotypic raft culture (Aim 2).

KSHV 3D genomic structures during latency and reactivation
4C-seq technology combines Chromosome Conformation Capture (3C) principles with
high-throughput sequencing to enable unbiased genome-wide screens for DNA contacts made
by single genomic site of interest called “viewpoint” (Dekker, Rippe, Dekker, & Kleckner, 2002;
Zhao et al., 2006). While Hi-C technology can capture every interactions occurring, due to the
small size of the viral genome, we proceeded with 4C technology which could minimize
background and has better sensitivity. 4C uses cross-linking to capture genomic interactions, then
inverse PCR to amplify the viewpoint and its ligated partners. This way, instead of testing one
69

DNA site to another (standard 3C), we can look for all genomic loci that interact with a specific
locus of interest. We performed 4C-seq on two different KSHV-infected cells: iSLK epithelial cells
infected with recombinant KSHV-BAC16 (iSLK-BAC16) and JSC-1 (EBV/KSHV co-infected)
primary effusion lymphoma (PEL) cells. Because we were interested in the change of
intragenomic loopings upon reactivation, we chose the RTA lytic locus (ORF50) as our viewpoint.
Since RTA gene is located inside the major lytic locus, and RTA protein expression is necessary
and sufficient to reactivate the virus, we asked whether physical interactions with this locus is also
important for efficient viral gene expression.
For doxycycline-inducible iSLK-BAC16 cells, time points were chosen based on the RT-
qPCR data that showed dramatic gene expression changes from latency to reactivation (data not
shown). We aimed to search for the de novo gain or loss of intragenomic interactions over the
course of KSHV reactivation. We identified that the KSHV intragenomic structure was not cell-
line-dependent as both JSC-1 and iSLK-BAC16 cells displayed almost identical intragenomic
interactions during latency. Upon reactivation, KSHV episome showed numerous distinct short-
range and long-range loops (Figure 4), further indicating that rather than the simple circular viral
genome with nucleosomes, KSHV genome forms high-ordered structure. Upon reactivation, the
intragenomic loopings that interact with the lytic locus increased, in terms of both interaction
strength and the number of loci (Figure 4). We normalized the total number of interactions, and
then quantified the number of viral genomic loops to identify specific interactions (Figure 5).
70

Figure 4. Computed circo plot of KSHV episome structure using RTA upstream promoter
as a viewpoint.
Lines represent potential interactions with the RTA lytic locus, from 0 h to 72 h upon virus
reactivation. Darker-colored lines represent higher chance of interaction. There are several
interactions of RTA upstream promoter with the nearby region, but also with regions that are
further away.

Figure 5. Semi-quantified 4C reads from the major lytic locus viewpoint.
Top 8 interacting loci from the major lytic locus. RTA is within the major lytic locus, and based on
the 4C technology, the nearest locus gets the highest number of reads. The loci are named based
on their closest ORF/gene promoters. Data represented from two biological replicates.

0h 6h 12h
24h 48h 72h
ORF50
ORF9
ORF75
ORF68
ORF4
ORF2
ORF17.5
K8
ORF6
0
20
40
60
80
200
220
KSHV gene locus
fold change (4C reads)
interaction with the major lytic locus
upon KSHV reactivation
Interaction with the major lytic locus
upon KSHV reactivation (72 hpi)
71

As 4C is a semi-quantitative method, we plan to select few interaction sites from our
preliminary data and perform 3C-qPCR to measure the accurate interaction strength. The loci
with the strongest or the highest number of interactions with the major lytic locus will be the more
likely relevant interactions. We will also identify the loci interacting with the lytic RTA locus during
latency that disappear during the lytic replication. While there were nearly identical KSHV
intragenomic structures between iSLK-BAC16 and JSC-1 cells, which are cells that support
latency upon de novo infection, we expect that oral epithelial cells fail to establish tight latency
upon de novo infection and thus show different intragenomic structure from those of iSLK-BAC16
and PEL cells. To test these differences of viral intragenomic structure, we will perform 4C-seq
on OEPI gingiva-derived epithelial cells at various time points upon KSHV de novo infection. This
study will demonstrate that the differences of the intragenomic linkages to the lytic locus between
iSLK and OEPI cells ultimately correlate with default latency state or lytic replication state. Lastly,
we plan to perform ATAC-seq (Assay for Transposase-Accessible Chromatin using sequencing)
to assess genome-wide chromatin accessibility of KSHV during latency and reactivation in iSLK
and OEPI cells. ATAC-seq identifies accessible DNA regions by probing open chromatin with
hyperactive Tn5 transposase that inserts sequencing adapters into open regions of the genome
(Buenrostro, Giresi, Zaba, Chang, & Greenleaf, 2013). The tagged DNA fragments are then
purified, PCR-amplified and sequenced. ATAC-seq results of 2D culture and 3D culture will be
compared in Aim 2 to test the similarity or difference of the KSHV chromatin accessibility between
these two culture conditions.

Host factors for KSHV intragenomic 3D interactions
Architectural proteins CTCF and cohesin are two host factors that bridge separated
chromatin regions as well as create chromatin loops of topologically associated domains.
Previous studies using Chromatin Immunoprecipitation combined with high-throughput
sequencing (ChIP-seq) and 3C methods have revealed that CTCF and cohesin are responsible
72

for connecting nuclear organization and gene expression in KSHV genome. The CTCF is also
crucial in regulating KSHV gene expression by acting as an insulator and chromatin conformation
modifier. During latent infection, the major latency locus (near LANA/ORF73 locus) to control
KSHV latency physically represses the promoter region of a major lytic transcriptional factor RTA,
preventing lytic gene activation. This intragenomic interaction is mediated by host factors CTCF
and cohesin. siRNA-mediated depletion of these two host factors showed the deregulation of
KSHV gene expression and copy number. As a previous study was limited only to the LANA and
RTA loci, our goal is to test roles of CTCF and cohesin during in lytic reactivation throughout the
KSHV genome.
Our initial approach to identify CTCF and cohesin-mediated genomic linkage was to
combine public ChIP-seq data of CTCF (GSM941710) and SMC1 (GSM941711) (Chen et al.,
2012), a subunit of cohesin complex, with our own KSHV 4C-seq data (Figure 6). When major
lytic locus (blue box) was used as a viewpoint of interest from 4C-seq data, many of the strong
DNA linkages were co-populated with the CTCF and SMC1 (red boxes). This suggests that CTCF
and cohesin are the main mediators of the physical linkage between the major lytic locus and
other parts of the KSHV genome.
Figure 6. Major lytic locus intragenomic interaction sites overlap with CTCF and cohesin
binding sites.
Peaks on 4C-seq data indicate KSHV genomic loci that interact with the major lytic locus. Peaks
on ChIP-seq indicate genomic binding sites of SMC1 or CTCF. Blue box indicates viewpoint
(major lytic locus), red boxes indicate sites where CTCF and cohesion are co-populated with 4C-
seq peaks. Blue loops indicate potential interactions that are mediated by CTCF and cohesin.
RTA
intron
4C-seq
SMC1
CTCF
LANA TR RTA
ChIP-seq
73

As CTCF and cohesin have already been well established as KSHV chromatin
conformation modifiers, we will focus on these two factors to demonstrate how they mediate
changes in KSHV 3D organization. We will use shRNA-lentivirus specific for the CTCF or the
subunits of cohesin (RAD21, SMC1, SMC3), and explore their general roles in KSHV 3D genomic
structure. iSLK-BAC16 cells will be treated with shRNA-lentiviruses to knockdown CTCF or
cohesin subunit, followed by viral reactivation and then 4C-seq analysis. We anticipate that
depletion of either CTCF or cohesin potentially leads to entirely new KSHV intragenomic
structures. As CTCF and cohesin also aid in host chromatin looping in different manners, we
expect that depletion of CTCF or cohesin broadly affects KSHV intragenomic loopings.

Mutations at the KSHV lytic control region for CTCF-mediated viral 3D genomic loop
Drastically altering the total pools of host CTCF and cohesin may have global effects on
host genomic structures and gene expressions, which could also affect KSHV gene expression
and virion production in an indirect manner. Thus, we will mutate the specific CTCF-binding sites
of the KSHV major lytic locus without affecting the CTCF expression but instead prevent it from
binding to the KSHV major lytic locus. Our lab has developed a KSHV bacterial artificial
chromosome (BAC16) model that allows us to make mutations on the viral genome by two-step
“scarless” homologous recombination within bacteria (K. F. Brulois et al., 2012). We constructed
a novel reporter virus, called red-green-blue-BAC16 (RGB) wherein three fluorescent proteins
(mRFP1, eGFP, tagBFP) expressions are under the control of the constitutively active host EF1a,
the viral immediate early PAN, and the viral late K8.1 promoter, respectively (Figure 7) (K. Brulois
et al., 2014). Depending on the stage of viral lifecycle, KSHV produces different fluorescent
proteins. This system accurately and efficiently identifies live cells at different stages of lifecycle
by using flow cytometry without fixing cells and staining with antibody.

74

Figure 7. BAC16-RGB.
EF1a-RFP-pH8.1-BFP-pPAN-GFP cassette was inserted into the BAC16. The genomic integrity
was verified by pulsed-field electrophoresis and direct sequencing. Then, the BAC construct was
transfected into iSLK cells for stable infection. Figure adapted from (K. Brulois et al., 2014).

We will investigate the CTCF’s role in KSHV 3D intragenomic structure with a specific
focus on the lytic locus. We will mutate the CTCF binding sites (CBS) of KSHV lytic locus and re-
examine the 3D structure of the KSHV genome. As CTCF ChIP-seq data and motif analysis
indicate multiple CBSs on the KSHV lytic locus (Figure 8), we will first identify which of the CBSs
are important for creating the genomic linkages with other lytic gene loci. After mapping the
specific CBS with CTCF gel shift assay, we will proceed BAC mutagenesis to introduce specific
point mutations to this CBS of KSHV-RGB DNA that prevent CTCF binding. We will also make
revertant BAC16 clones—this ensures that there are no other mutations introduced into viral
genome during BAC mutation. After generating WT-, point mutant-, and revertant KSHV-RGB
reconstituted iSLK cells, we will then check for (1) the loss of DNA-DNA linkages by 4C, (2) the
percentage population in viral lifecycle by gating R/G/B fluorescence by flow cytometry (3) the
alteration of total viral copy number by qPCR. We expect that preventing the CTCF from binding
to specific lytic loci CBSs will potentially disrupt the authentic KSHV 3D structure, inaccurately
turning on sequential gene expressions and thereby affecting viral lifecycle.
KSHV episome
(BAC16-RGB)
EF1- K9
Latent Late Immediate early
IRES RFP pK8.1 pPAN GFP pA BFP
75

Figure 8. Combining CTCF motif analysis and ChIP-seq peaks to identify CTCF binding
sequence for mutagenesis.
Motif enrichment analysis was performed using FIMO algorithm (Grant, Bailey, & Noble, 2011),
and then the KSHV major lytic locus was zoomed in on Integrative Genomics Viewer. Red colored
nucleotides are the conserved CTCF-binding motifs.

Similar to viral active chromatin hub (Figure 1B), we hypothesize the CTCF-mediated
“chromatin hub” model where the promoter regions of multiple lytic genes are physically linked by
CTCF and brought together into a specific “multi-gene expression locus”. Various genes with
similar functions maximize their gene expressions by sharing transcriptional machineries and
initiating transcriptions in a synchronous and efficient manner. Dr. Izumiya’s group firstly showed
that mutant KSHV genome harboring mutations in the RTA-responsive elements significantly
attenuate the directly proximal downstream gene as well as distal gene expression in a domain-
specific manner. We also found that WT KSHV showed increased genomic interactions at the
lytic loci upon reactivation, while interactions decreased at the latent locus (Figure 6). To test this
“chromatin hub” model, KSHV mutant carrying the loss of the major lytic loci CBS will be tested
for viral gene expression upon de novo infection and reactivation conditions in comparison with
WT virus. We have developed NanoString’s nCounter technology of KSHV to measure whole viral
transcriptions. This method utilizes a digital color-coded barcode technology and single molecule
imaging to detect and count hundreds of mRNAs in a single reaction. It has high reproducibility,
sensitivity and low background signal, and does not require the amplification of target mRNAs.
CTCF
ChIP-seq
Motif
analysis
GAGCCCAGCAGGGGAAAATC CAGTCCCTCTGCCGGCCAGC
KSHV major lytic locus (67kb - 76kb)
CCAGCGTCCACTAGTGGCAG
76

We expect that disruption of the CBS alter expressions of the proximal or distal genes that interact
with this major CBS at the lytic locus by either short-range or long-range looping, respectively.
This would further validate that the genomic linkage is important for correct sequential gene
expression.

Role of KSHV DNA 3D looping for its lytic gene expression
Global Run-On sequencing (GRO-seq) captures nascent transcripts that are
actively being transcribed by RNA polymerase II, therefore giving a direct read-out for bona fide
newly synthesized transcripts (Figure 9A) (Core, Waterfall, & Lis, 2008). While RNA-seq captures
total levels of steady state RNAs, GRO-seq looks only for newly synthesized RNA transcripts at
each time point. Transcription is stopped, nuclei are isolated, transcription restarts briefly in vitro
with labeled nucleotides, and labeled transcripts are pulled down. Therefore, GRO-seq captures
nascent and unstable transcripts more efficiently than RNA-seq. We performed GRO-seq in
parallel with 4C-seq as time-course experiments to observe transcriptional changes. GRO-seq
data showed that there was an overall increase of viral transcription from latency to lytic replication
(Figure 9B). At latent state, only latent genes were produced. As time went by, all lytic genes
turned on in a temporal manner.

77

Figure 9. GRO-seq
(A) GRO-seq assay. Nuclear run-on assay identifies genes that are being transcribed at a certain
point. This assay involves labeling of newly synthesized transcripts with bromouridine in presence
of Sarkosyl to prevent new RNA polymerase (RNAPII) from binding to DNA. Then the labeled
transcripts are captured with anti-BrU antibody-labeled beads, then converted into cDNA, which
are used for sequencing. (B) KSHV nascent transcript in iSLK-BAC16 cells. Hours post RTA
induction are indicated on the left, and the transcripts are aligned to the KSHV genome. This
shows all nascent transcripts produced at different time points from latency to full reactivation.

0 h
6 h
12 h
24 h
48 h
72 h
7
2
h
RNAP
II
+ sarcosyl
A
B
78

There have been successful studies to bioinformatically link different sets of high
throughput data: the combination of Hi-C and ChIP-seq examines specific protein-mediated
genomic interactions (Lan et al., 2012); integrative analysis of ATAC-seq and RNA-seq identifies
cell type-selective gene regulatory regions (Ackermann, Wang, Schug, Naji, & Kaestner, 2016);
and RNA polymerase II ChIP-seq with RNA-seq together validates transcription start site (TSS)
(Yamashita et al., 2011). Integrating different –omics data allows us to investigate multi-level
regulatory mechanisms which is not possible when analyzing single dataset. As our goal is to
understand how KSHV genomic structure functionally contributes to viral gene expression, we
plan to combine the 4C-seq data with GRO-seq data. Integration of these results will lead to
understanding how genomic linkages directly affect transcription of those viral genes or loci. We
will bioinformatically align two data sets to the KSHV genome and examine whether interaction
data matches the transcription data. For example, if DNA looping between genes A and B
decreases and expression of gene A increases at the same time, this suggests that loss of the
repressive interaction between genes A and B allows gene A expression. We will also compare
GRO-seq of iSLK-KSHV BAC16-RGB WT vs. CBS mutant to globally test our hypothesis that
genomic linkages directly affect viral gene transcription. We expect that upon reactivation, lytic
gene loci go through a structural change where different lytic gene sets come together in close
proximity and each set turns on transcription accordingly (Figure 10).
79

Figure 10. Expected correlation plot for metadata analysis of 4C-seq and GRO-seq.
Integrating epigenome and transcriptome data helps us better understand gene regulatory
mechanisms. X axis is 4C-seq interaction signal level and Y axis is corresponding gene
expression. Each point represents one locus.

Overall, different types of high-throughput technologies give us information at global and
molecular level. For more comprehensive understanding and better biological meaning, datasets
need to be integrated together for analysis. The combination of 4C-seq and GRO-seq will provide
new insight at the genomic level that the intragenomic physical interaction considerably affects
KSHV gene expression during its lifecycle.

80

Aim 2. Host and viral gene regulation in 3D organotypic raft culture model
This aim is to develop a 3D organotypic oral tissue infection model that mimics in vivo oral
transmission, and to identify the chromatin structure and gene expression of host and KSHV at
the single cell level. Since our scRNA-seq results showed that KSHV lytic genes were expressed
primarily on the fully differentiated outer layers of epithelium, we hypothesize that KSHV
epigenome varies depending on the differentiation status of oral epithelium. Upon infection of
KSHV WT or mutant, the chromatin availability and gene expression of host and KSHV in 3D
organotypic oral tissue model will be examined using scRNA-seq, scATAC-seq and
bioinformatics. This will help us understand how the differentiation status of oral epithelium
epigenetically regulates KSHV gene expression and how the KSHV lifecycle affects the gene
expression and differentiation of oral epithelium.

KSHV infection of 3D oral epithelial organotypic raft culture
Since the oral cavity is the major site for the shedding of KSHV and KSHV lytic gene
expression is detected during keratinocyte differentiation into a mature epithelium (Johnson,
Maronian, & Vieira, 2005). This aim is directed to utilize an organotypic raft culture model using
keratinocytes from normal buccal tissue which is a common intraoral KS site. Initially, we used
commercial 3D cultures of primary oral epithelial cells to establish the conditions for efficient
KSHV infection and replication: commercial MatTek’s EpiOral 3D tissues consist of normal human
primary oral keratinocytes in an air-liquid interface format (Dongari-Bagtzoglou & Kashleva, 2006).
These cells have been cultured to form multilayered, highly-differentiated tissues with a non-
cornified, buccal phenotype. The tissues were cultured on specially prepared inserts in serum-
free medium, attaining levels of differentiation that exhibits in vivo-like morphological and growth
characteristics that are uniform and highly reproducible. After having experience of commercial
EpiOral tissue model, we then generated our own 3D human oral primary keratinocyte-derived
81

organotypic raft culture that was also highly reproducible for KSHV infectivity. First, we examined
whether KSHV infection led to a complete cycle of lytic replication in 3D oral epithelia raft culture,
an environment closely representative of normal oral epithelium in the host. rKSHV.219, carrying
the EF-1α promoter-driven eGFP for latent cycle marker and PAN promoter-driven mRFP for lytic
cycle marker (Vieira & O'Hearn, 2004), was applied to the apical surface of a raft culture 4 days
after keratinocytes were lifted to the air-liquid interface. We found that unlike herpes simplex virus-
1 (HSV-1) and human cytomegalovirus (HCMV) that effectively infiltrated to basal layers without
surface scratch, KSHV could not penetrate through the outer apical layer of 3D epithelial raft
culture. Opening up the outer apical cell-to-cell junctions by removing divalent ions was not
successful for KSHV infection, either. To achieve infection, we needed to score the top of the oral
tissue using 31G blunted syringe needles to expose the basal cell layer. This suggests that similar
to human papilloma virus (HPV), KSHV cannot infect the intact apical surface of oral keratinocytes,
and only when the basal layers are exposed due to a cut or a wound, KSHV can infect.
We performed immunohistochemistry (IHC), immunofluorescence (IF), flow cytometry
and scRNA-seq with 3D oral epithelial raft culture harvested at 3, 6, and 13 days post infection
(Figure 11A). rKSHV.219-infected 3D oral epithelial raft culture showed thinner epithelium than
mock infection with heat-inactivated rKSHV.219 (Figure 11B). When the keratinocytes were
allowed to differentiate into a multilayered epithelium in 3D, reactivation (RFP+) occurred and
increased with time (Figure 11C). Quantitative-PCR (q-PCR) showed the increased RTA and K8
lytic gene expression and viral DNA copy number, and IHC showed latent LANA expression at
basal layers (Figure 11DE).
As 3D oral infection system supports full KSHV lifecycle, this will be used to compare
KSHV-RGB WT, CBS mutant or CBS revertant (from Aim 1) for their latency and reactivation.
R/G/B flow cytometry, IF, IHC, q-PCR and DNA copy number will be measured. The disruption of
the authentic 3D structure of KSHV genome by either mutating the specific CTCF-binding sites at
the KSHV lytic locus or by depleting host CTCF, may inaccurately turn on sequential gene
82

expressions. In conclusion, this multilayer oral raft culture could provide novel information of
KSHV transmission, which closely mimics in vivo setting.

Figure 11. (A) Diagram of 3D oral raft cultures setup for the differentiation, infection and harvest
stages. (B) Scoring the apical surface of the tissue allowed successful infection. At each time
point, the KSHV-infected tissue morphology was thinner than the mock control. (C) Time course
of rKSHV.219 infection of organotypic raft cultures. Last column shows the ratio of latent-infected
cells vs. lytic-infected cells. (D) KSHV gene expression and genome copy numbers were
quantified by qPCR. (E) LANA IHC.
Mock KSHV
3dpi
Mock KSHV
6dpi
Virus infection by
needle-scoring the
3D tissue to expose
basal layer
IHC IF scRNA-seq Flow cytometry
D0 D3 D6 D13 -D4
Keratinocyte lifted
to air-liquid
interface
3dpi 6dpi 13dpi
KSHV latency KSHV lytic replication Merged
Flow
Cytometry
Latent (GFP): 5
Lytic (RFP): 1
Latent (GFP): 2
Lytic (RFP): 1
Latent (GFP): 1
Lytic (RFP): 1
Mock
3dpi
6dpi
13dpi
0
5
10
15
20
60
80
100
infection
fold change relative to mock
LANA
Mock
3dpi
6dpi
13dpi
0
5
10
15
K1
infection
fold change relative to mock
Mock
3dpi
6dpi
13dpi
0
10
20
30
40
50
RTA
infection
fold change relative to mock
Mock
3dpi
6dpi
13dpi
0
100
200
300
400
K8
infection
fold change relative to mock
Mock
3dpi
6dpi
13dpi
0
5
10
15
20
60
80
100
infection
fold change relative to mock
LANA
Mock
3dpi
6dpi
13dpi
0
5
10
15
K1
infection
fold change relative to mock
Mock
3dpi
6dpi
13dpi
0
10
20
30
40
50
RTA
infection
fold change relative to mock
Mock
3dpi
6dpi
13dpi
0
100
200
300
400
K8
infection
fold change relative to mock
Viral gene expression
Mock
3dpi
6dpi
13dpi
0
50
100
150
Viral copy
infection
copy number / cell
Viral DNA
copy number
Mock
3dpi
6dpi
13dpi
0
5
10
15
20
60
80
100
infection
fold change relative to mock
LANA
Mock
3dpi
6dpi
13dpi
0
5
10
15
K1
infection
fold change relative to mock
Mock
3dpi
6dpi
13dpi
0
10
20
30
40
50
RTA
infection
fold change relative to mock
Mock
3dpi
6dpi
13dpi
0
100
200
300
400
K8
infection
fold change relative to mock
LANA RTA K8
Mock 3dpi 6dpi
Anti-LANA
IHC
A
B
C
D
E
83

Single cell transcriptomics of 3D oral epithelial organotypic raft culture
To define the transcriptional landscape during KSHV infection of our 3D oral epithelial
tissue, we used the 10X Genomics Chromium scRNA-seq system to profile both host and viral
gene transcriptome at a single cell level. To isolate single cells, the tissues were enzymatically
digested and dispersed with a mixture of collagenase and trypsin. 3,000 cells were then used as
input into the 10X Chromium platform where microfluidics was used to isolate individual cell into
its own micelle with a gel bead (GEM). Within each GEM, cells were lysed and reverse-transcribed
to generate cDNA with identification barcodes to create standard NGS libraries. The libraries were
sequenced using an Illumina sequencing platform and then analyzed using a combination of
bioinformatic tools such as 10X Genomics Cell Ranger and Seurat (Satija, Farrell, Gennert, Schier,
& Regev, 2015) analysis pipelines (Figure 12).

Figure 12. An overview of the workflow to generate scRNA-seq from KSHV-infected 3D oral
epithelial tissue.
EpiOral cultures were infected with KSHV.219 for 3,6, or 13 days, harvested, digested into a
single cell suspension, and then used for scRNA-seq. With the 10X Chromium platform, we used
~5,000 cells per sample to generate a complete single-cell sequencing library which was used to
analyze different transcriptome at a single cell level.
Enzymatically
digest tissues to
isolate single cells
Use 2,000-7,000
cells for scRNA-
seq
Compare gene expression
profiles of single cells 10x Chromium technology
KSHV-infected
3D oral epithelial
organoid culture
84

Using our single-cell transcriptomics data, we validated the capacity of our 3D oral
epithelial raft culture model to accurately allow KSHV infection and replication. Using specific
differentiation markers such as CDH3 (Basal Layer), KRT6A (Spinous Layer), KRT10 (Granular
Layer), and SPRR2A (Cornified Layer), we annotated each cell into specific layers of the oral
epithelium (Figure 13). We observed that the spatial clustering of mock and 3 dpi tissue was very
similar, indicating that there are not many changes in the transcriptome to cause spatial shift in
clustering. However, we detected distinguishable clustering in 6 dpi. We will investigate what
drives the dramatic shifts shown in the 6 dpi tSNE plots compared to both mock and 3 dpi tSNE
plots. Is this clustering shift due to the natural course of keratinocyte differentiation at different
timepoints, or is this due to the KSHV infection and replication? To answer this, we will repeat
85

scRNA-seq with heat-inactivated KSHV.219 infection to complement each timepoint (3 dpi, 6 dpi,
and 9 dpi) to accurately distinguish the effects between viral infection vs. differentiation.

Figure 13. tSNE (t-distributed stochastic neighbor embedding) plots of scRNA-seq.
(A) 2D spatial clustering of the mock (pink), 3dpi (blue) and 6dpi (green) samples projected into
distinctly isolated clusters. (B) Differentiation status identified using keratin marker.

As confirmed by eGFP and mRFP expression by fluorescent microscopy, we not only
designated cells that were infected with rKSHV.219, but also searched for cells expressing eGFP
mRNA and/or mRFP mRNA from the scRNA-seq data. Cells that expressed eGFP mRNA only
were labeled as latent KSHV-infected cells and cells that expressed both eGFP and mRFP
mRNAs were labeled as lytic KSHV-infected cells. We bioinformatically collected all infected cells
and characterized the differentiation status of each cells to identify which layer of keratinocytes
supported the specific state of KSHV infection (Figure 14). Strikingly, while latent infected cells
Basal
Granular
Cornified
Basal
Granular
Cornified
Cornified
Spinous
Granular
Granular
Basal
3dpi mock 6dpi
A
B
86

were present in every layer of the tissue, lytic infected cells appeared to be localized primarily in
the apical/cornified layers. We hypothesize that upon initial infection of basal keratinocytes, KSHV
first establishes latency and subsequently undergoes lytic replication with the natural course of
tissue differentiation, ultimately releasing viral particles to the apical surface. As this finding is a
crux of this aim, we repeated scRNA-seq twice, will repeat once again and also perform IF and
IHC for viral latent and lytic proteins. We will compare scRNA-seq upon infection of KSHV-RGB
WT, CBS mutant or CBS revertant for their latency and reactivation. This study will provide clues
why KSHV undergoes reactivation at the apical layer of tissue.

Figure 14. KSHV infected cells in each tissue sample.
(A) Identification of eGFP+/mRFP- (latent) and eGFP+/mRFP+ (lytic) cells in each infected tissue.
Each dot represents one cell. (B) Heatmap of latent and lytic infected cells (collected from 3dpi
and 6dpi) expressing differentiation markers. Row represents genes and columns represent each
cell. (C) Proposed location of latent and lytic KSHV-infected cells in 3D tissue.

Basal
Layer
Spinous
Layer
Granular
Layer
Cornified
Layer
Epidermal differentiation
mock 3dpi 6dpi 13dpi
Latent (GFP mRNA)
mock 3dpi 6dpi 13dpi
Lytic (RFP mRNA)
Latent Lytic
Expression
B
A
C
87

Profiling viral and host gene expressions within infected tissue
While most cells in KS lesions are latently infected, it appears that both latency and lytic
replication are necessary for KS pathogenesis. Recently, Dr. Rose’s group performed extensive
RNA-seq on 23 KS tumor biopsies to show that KSHV latent and lytic gene expression profiles
are very different in each tumor and that discrete subgroups of lytic genes are regulated differently
in each KS(Rose et al., 2018). This suggests that even within the same tissue, KSHV gene
expression is highly intertwined with host gene expression. With the help of scRNA-seq
technology, we profiled viral transcripts produced from each infected cell, bioinformatically
gathered all virus-infected cells from scRNA-seq data, and then aligned each cell’s transcriptome
to the KSHV genome (GQ994935.1) (Figure 15). As expected, only small subset of viral genes
was expressed in latent-infected cells (eGFP+ cells), while most viral genes were detected in lytic
cells (eGFP+/mRFP+ cells). While LANA and RTA are the markers of latent and lytic infection,
respectively, we were unable to detect these mRNAs, which was likely too low levels of transcripts
to be detected by scRNA-seq technology. We will continue to (1) characterize the kinetics of viral
gene expression, (2) distinguish host gene expression profile among different viral gene-
expressing cells, and (3) include KSHV-RGB WT, CBS mutant or CBS revertant for infection study.

88

Figure 15. Differential expression of viral transcripts.
(A) Latent and lytic-infected cells aligned to the KSHV genome. Rows represent KSHV ORFs and
columns represent cells. (B) Heatmaps for KSHV latent and lytic infection.

After comparing the viral gene expression profile among infected cells, we will also profile
the host transcriptome. As previously shown, many host genes were significantly downregulated
in lytic replicating cells (Glaunsinger, Chavez, & Ganem, 2005), while a very few genes were
upregulated (Figure 16). Pathway analysis showed that top enriched pathways included EIF2
signaling, oxidative phosphorylation, and mitochondrial dysfunction. We will further characterize
Latent cells (GFP+/RFP-)
3dpi 6dpi 13dpi
Lytic cells (GFP+/RFP+)
3dpi 6dpi 13dpi
Latent locus Lytic locus
3dpi 6dpi 13dpi
All KSHV+ cells (Latent & Lytic)
A B
89

how the two states of KSHV lifecycle induce differential host transcriptional reprogramming.
Finally, the comparison gene expression changes between the infected cells and the uninfected
cells within the same tissue will help us identify which pathways and genes are affected by two
different stages of KSHV lifecycle. This section ultimately examines differential gene expression
profiles of infected cells within the infected tissue and the effect of virus lifecycle on host gene
expression changes.

Figure 16. Heatmap representing expression profile of the 25 most differentially expressing
host genes.
The top 20 rows, host genes that are downregulated in lytic compared to latency; the middle 2
rows, mRFP and eGFP; and the bottom 3 rows, host genes that are upregulated in lytic compared
to latency.

Differential gene expression between infected vs. uninfected tissue
Despite a low infectivity of the 3D tissues, we apparently observed the global changes of
whole tissues upon KSHV infection as shown by the visible thinning of the tissue upon infection
(Figure 11B). We hypothesize that KSHV infection provides a profound effect on infected cells as
well as on neighboring uninfected cells, ultimately affecting 3D microenvironment. We compared
2 1 0-1-2
Latent Lytic
EEF1A1
MALAT1
SAT1
CD9
RPS27L
SPINK5
EIF4A2
PSCA
TACSTD2
F3
ADIRF
MUC1
LYPD3
CD24
RHCG
CDZK1IP1
S100A6
S100A4
SAA2
SAA1
mRFP
eGFP
GOSR2
SPINK1
AVPI1
Top 20
downregulated
genes in cells in
lytic replication
compared to
latency
Top 3 upregulated
host genes
90

the transcriptome profiles of 3 dpi and 6 dpi KSHV-infected tissues with those of heat-inactivated
KSHV-infected mock tissues. Canonical signaling pathways and upstream analysis were
generated using Ingenuity Pathway Analysis (IPA) (Figure 17A). Interestingly, while there was no
significant change in signaling pathways between mock and 3dpi, there was considerable
changes in upstream transcriptional regulators. This might be due to the fact that the infection
was still spreading and that there was not enough expression of viral genes to make changes of
the host signaling pathways. In contrast, there were significant changes in the signaling pathways
and upstream regulators when comparing 6 dpi to mock. To further demonstrate that these
changes of host gene expressions are certainly due to KSHV infection, not because of epithelial
differentiation, mock tissues harvested at the same time as each infection timepoint will be used
to match the differential status of each tissue with or without infection, followed by scRNA-seq.
We also identified host genes whose expressions were drastically changed in KSHV-
infected 3D epithelial raft culture: e.g., CXCL-8 and Rac1 were highly upregulated and
downregulated, respectively (Figure 17B). CXCL8 and Rac1 are the inflammatory signal
mediators that are highly induced in latently-infected AIDS-KS or 2D-cultured endothelial cells
and involved in angiogenesis and lymphocyte recruitment (Lane et al., 2002; Ma et al., 2009). In
contrast, de novo KSHV infection of 3D epithelial tissues showed significant downregulation of
Rac1 expression. This suggests that Rac1 may play a different role in KSHV-infected 3D oral
tissues from latently-infected KS biopsies or 2D endothelial cells. The fact that low KSHV infection
was sufficient to induce global transcriptional and morphological changes of entire 3D tissues
suggests potential paracrine/autocrine signaling events that induce various responses to proximal
cells as well as distal cells within 3D tissue. We hope to study these upregulated or downregulated
host genes for their roles in global transcriptional and morphological changes of entire 3D tissues.
However, it should be noted that since this application is focused on the epigenomic analysis of
KSHV in 3D culture, this functional study will be limited with a few host genes, e.g., CXCL8 and
91

Rac1. Nevertheless, our computational analysis of host gene expression upon KSHV infection at
single cell level may reveal a crucial role for cell-to-cell communication in 3D infection model.

Figure 17. Pathway analysis.
(A) IPA analysis revealing top canonical pathway and upstream regulator. Heatmap shows
differentially expressed genes in the infected tissues (3dpi and 6dpi) compared to the mock. (B)
Violin plot showing the distribution of gene counts, split by sample. Each dot represents a cell. Y-
axis is log TPM (normalized transcripts per million).

Single cell-chromatin structure analysis of host and KSHV genome
In a cell, specific gene expression profile is controlled by intricate gene regulatory networks
such as chromatin availability. As the openness of chromatin can define important biological
processes such as differentiation status and cell fate, profiling chromatin availability at single cell
resolution can identify critical cell-to-cell variation in regulatory elements. Dr. Dittmer’s group has
performed formaldehyde-assisted isolation of regulatory elements (FAIRE) combined with
Canonical
pathways
3dpi vs mock
6dpi vs mock
Upstream
analysis
mock 3dpi 6dpi
RAC1
Expression level
mock 3dpi 6dpi
CXCL8 (IL-8)
Expression level
A B
92

sequencing on primary effusion lymphoma cells and KSHV-infected endothelial cells to identify
viral chromatin availability and regulatory elements in the latent KSHV genome (Hilton et al., 2013).
Also, our lab has previously done extensive studies to determine histone deposition across the
viral genome. Since we have well-established the 10x Chromium system in our lab, we will perform
ATAC-seq at a single-cell level (scATAC-seq) on KSHV-infected 3D organotypic raft cultures to
characterize regulatory elements on both virus and host genomes (Figure 18). scATAC-seq
technology from 10x Genomics uses the same 10X technology as described above (Figure 12)
with a few modifications: nuclei are isolated and undergo barcoding, after their DNAs are probed
with Tn5 transposase. We expect that each differentiation layer of keratinocytes will have different
chromatin state that allows diverse transcription factors to bind and differentiate accordingly. We
wim to find how the host chromatin state is changed in infected cells, as we know that KSHV is a
strong epi-driver that modifies host epigenome. By aligning the same set of data to the KSHV
genome, we will determine open chromatin maps of the KSHV genome and observe how the KSHV
epigenome is changed from latency to reactivation during epithelial differentiation. Specifically,
KSHV primarily stays in latency at the basal, spinous and granular layers and subsequently
undergoes reactivation at the cornified layer, releasing viral particles to the apical surface (Figure
14). This will also show whether the change of KSHV epigenome is similar or different between
2D (Aim 1) vs. 3D (Aim 2) conditions. This will show how host and KSHV genomes are altered
during epithelial differentiation and latency-to-reactivation transition, respectively, in 3D culture.
93

Figure 18. ATAC-seq.
(A) Schematic of ATAC-seq. Hyperactive mutant Tn5 transposase probes open chromatin regions
and inserts sequencing adapters (figure adapted from 10X Genomics website). (B) Expected
genome coverage profile of scATAC-seq on KSHV-infected 3D oral epithelial tissue, viewed at a
specific gene locus. Each row represents a single cell at different infection status: latently-infected,
lytic-infected, and uninfected. Peaks represent host genomic regions that are open (such as
promoter, enhancer or CTCF-binding site), therefore available for transcription factors to bind.

Lastly, the scRNA-seq data from the previous sections will be bioinformatically combined
with the scATAC-seq data to give us a clear picture of how chromatin regulation directly controls
to gene expression. For example, this multi-omics approach can reveal complex transcription
factor (TF) activity by identifying TF binding motifs and correlating its target gene expressions. With
this combination, we will, for the first time, distinguish the chromatin availability of infected vs. non-
infected cells and latent infected vs. lytic replicating cells. Thus, we will gain deeper insights into
how the cell type-specific gene regulatory networks control gene expression and how the
epigenomic variability of both host and KSHV can affect the outcome of two different viral lifecycles.
latency
lytic
uninfected
KSHV
A
B
94

Conclusion
Both the previous epigenetic study our lab published and the KSHV genomic study in 2D
culture (Aim 1) will be underpinning of the KSHV epigenomic study in 3D culture (Aim 2). We
anticipate that our extensive experience with NGS technology, bioinformatics skill as well as 10x
Chromium instrument will greatly facilitates the completion of this aim. Since we have already
demonstrated that we can detect transcriptional changes in infected oral epithelial raft culture at
the single cell level, the bioinformatic analysis and scATAC-seq will be straightforward. While
single cell sequencing technology and 3D tissue are still too new to predict the outcome, our initial
analysis of the scRNA-seq data is quite promising. It has been well studied that keratinocyte
layers have dynamic chromatin accessibility that negatively correlates with the level of
differentiation (Figure 19). Our preliminary study has shown that KSHV undergoes
heterochromatin-to-euchromatin transition and increasing chromatin accessibility upon
reactivation, and also prefers euchromatin state in oral epithelial cells (Figure 19). We expect that
as KSHV epigenomic profile is heavily dependent on the host epigenomic profile, the combination
of transcriptomics with chromatin availability will give us a clear understanding of complex gene
regulation. The study of scRNA-seq and scATAC-seq in 3D oral epithelial raft culture should
provide highly mechanistic insight of host and viral gene regulation. Thus, this proposal is highly
innovative, and a successful outcome should prove to be a major discovery to understand the in
vivo oral transmission of KSHV and ultimately, the prevention of KSHV-induced oral complication.

95

Figure 19. Schematic model depicting initial KSHV transmission of oral tissue.
KSHV initially infects basal cell layer and establish latency. With the course of the tissue’s natural
differentiation, KSHV undergoes latency-to-reactivation, therefore releasing viral particles to the
apical surface.

Normal epithelium Infected epithelium
KSHV Reactivation
VIRUS SIDE
Differentiation
HOST SIDE
Chromatin accessibility
Heterochromatin
Chromatin accessibility
Heterochromatin
Euchromatin
Uninfected cell
Latent infection
Lytic infection
Virion particle
96

References
Ackermann, A. M., Wang, Z., Schug, J., Naji, A., & Kaestner, K. H. (2016). Integration of ATAC-
seq and RNA-seq identifies human alpha cell and beta cell signature genes. Mol Metab,
5(3), 233-244. doi:10.1016/j.molmet.2016.01.002
Andrei, G., Duraffour, S., Van den Oord, J., & Snoeck, R. (2010). Epithelial raft cultures for
investigations of virus growth, pathogenesis and efficacy of antiviral agents. Antiviral
Res, 85(3), 431-449. doi:10.1016/j.antiviral.2009.10.019
Brulois, K., Toth, Z., Wong, L. Y., Feng, P., Gao, S. J., Ensser, A., & Jung, J. U. (2014).
Kaposi's sarcoma-associated herpesvirus K3 and K5 ubiquitin E3 ligases have stage-
specific immune evasion roles during lytic replication. J Virol, 88(16), 9335-9349.
doi:10.1128/JVI.00873-14
Brulois, K. F., Chang, H., Lee, A. S., Ensser, A., Wong, L. Y., Toth, Z., . . . Jung, J. U. (2012).
Construction and manipulation of a new Kaposi's sarcoma-associated herpesvirus
bacterial artificial chromosome clone. J Virol, 86(18), 9708-9720. doi:10.1128/JVI.01019-
12
Buenrostro, J. D., Giresi, P. G., Zaba, L. C., Chang, H. Y., & Greenleaf, W. J. (2013).
Transposition of native chromatin for fast and sensitive epigenomic profiling of open
chromatin, DNA-binding proteins and nucleosome position. Nat Methods, 10(12), 1213-
1218. doi:10.1038/nmeth.2688
Campbell, M., Watanabe, T., Nakano, K., Davis, R. R., Lyu, Y., Tepper, C. G., . . . Izumiya, Y.
(2018). KSHV episomes reveal dynamic chromatin loop formation with domain-specific
gene regulation. Nat Commun, 9(1), 49. doi:10.1038/s41467-017-02089-9
Cesarman, E., Chang, Y., Moore, P. S., Said, J. W., & Knowles, D. M. (1995). Kaposi's
sarcoma-associated herpesvirus-like DNA sequences in AIDS-related body-cavity-based
lymphomas. N Engl J Med, 332(18), 1186-1191. doi:10.1056/NEJM199505043321802
Chang, Y., Cesarman, E., Pessin, M. S., Lee, F., Culpepper, J., Knowles, D. M., & Moore, P. S.
(1994). Identification of herpesvirus-like DNA sequences in AIDS-associated Kaposi's
sarcoma. Science, 266(5192), 1865-1869.
Chen, H. S., Wikramasinghe, P., Showe, L., & Lieberman, P. M. (2012). Cohesins repress
Kaposi's sarcoma-associated herpesvirus immediate early gene transcription during
latency. J Virol, 86(17), 9454-9464. doi:10.1128/JVI.00787-12
Core, L. J., Waterfall, J. J., & Lis, J. T. (2008). Nascent RNA sequencing reveals widespread
pausing and divergent initiation at human promoters. Science, 322(5909), 1845-1848.
doi:10.1126/science.1162228
Dekker, J., Rippe, K., Dekker, M., & Kleckner, N. (2002). Capturing chromosome conformation.
Science, 295(5558), 1306-1311. doi:10.1126/science.1067799
Dongari-Bagtzoglou, A., & Kashleva, H. (2006). Development of a highly reproducible three-
dimensional organotypic model of the oral mucosa. Nat Protoc, 1(4), 2012-2018.
doi:10.1038/nprot.2006.323
97

Duus, K. M., Lentchitsky, V., Wagenaar, T., Grose, C., & Webster-Cyriaque, J. (2004). Wild-type
Kaposi's sarcoma-associated herpesvirus isolated from the oropharynx of immune-
competent individuals has tropism for cultured oral epithelial cells. J Virol, 78(8), 4074-
4084. doi:10.1128/jvi.78.8.4074-4084.2004
Glaunsinger, B., Chavez, L., & Ganem, D. (2005). The exonuclease and host shutoff functions
of the SOX protein of Kaposi's sarcoma-associated herpesvirus are genetically
separable. J Virol, 79(12), 7396-7401. doi:10.1128/JVI.79.12.7396-7401.2005
Goncalves, P. H., Uldrick, T. S., & Yarchoan, R. (2017). HIV-associated Kaposi sarcoma and
related diseases. AIDS, 31(14), 1903-1916. doi:10.1097/QAD.0000000000001567
Grant, C. E., Bailey, T. L., & Noble, W. S. (2011). FIMO: scanning for occurrences of a given
motif. Bioinformatics, 27(7), 1017-1018. doi:10.1093/bioinformatics/btr064
Hilton, I. B., Simon, J. M., Lieb, J. D., Davis, I. J., Damania, B., & Dittmer, D. P. (2013). The
open chromatin landscape of Kaposi's sarcoma-associated herpesvirus. J Virol, 87(21),
11831-11842. doi:10.1128/JVI.01685-13
Hirschhaeuser, F., Menne, H., Dittfeld, C., West, J., Mueller-Klieser, W., & Kunz-Schughart, L.
A. (2010). Multicellular tumor spheroids: an underestimated tool is catching up again. J
Biotechnol, 148(1), 3-15. doi:10.1016/j.jbiotec.2010.01.012
Johnson, A. S., Maronian, N., & Vieira, J. (2005). Activation of Kaposi's sarcoma-associated
herpesvirus lytic gene expression during epithelial differentiation. J Virol, 79(21), 13769-
13777. doi:10.1128/JVI.79.21.13769-13777.2005
Kang, H., Wiedmer, A., Yuan, Y., Robertson, E., & Lieberman, P. M. (2011). Coordination of
KSHV latent and lytic gene control by CTCF-cohesin mediated chromosome
conformation. PLoS Pathog, 7(8), e1002140. doi:10.1371/journal.ppat.1002140
Lan, X., Witt, H., Katsumura, K., Ye, Z., Wang, Q., Bresnick, E. H., . . . Jin, V. X. (2012).
Integration of Hi-C and ChIP-seq data reveals distinct types of chromatin linkages.
Nucleic Acids Res, 40(16), 7690-7704. doi:10.1093/nar/gks501
Lane, B. R., Liu, J., Bock, P. J., Schols, D., Coffey, M. J., Strieter, R. M., . . . Markovitz, D. M.
(2002). Interleukin-8 and growth-regulated oncogene alpha mediate angiogenesis in
Kaposi's sarcoma. J Virol, 76(22), 11570-11583. doi:10.1128/jvi.76.22.11570-
11583.2002
Langhans, S. A. (2018). Three-Dimensional in Vitro Cell Culture Models in Drug Discovery and
Drug Repositioning. Front Pharmacol, 9, 6. doi:10.3389/fphar.2018.00006
Ma, Q., Cavallin, L. E., Yan, B., Zhu, S., Duran, E. M., Wang, H., . . . Goldschmidt-Clermont, P.
J. (2009). Antitumorigenesis of antioxidants in a transgenic Rac1 model of Kaposi's
sarcoma. Proc Natl Acad Sci U S A, 106(21), 8683-8688. doi:10.1073/pnas.0812688106
Phillips, J. E., & Corces, V. G. (2009). CTCF: master weaver of the genome. Cell, 137(7), 1194-
1211. doi:10.1016/j.cell.2009.06.001
Rose, T. M., Bruce, A. G., Barcy, S., Fitzgibbon, M., Matsumoto, L. R., Ikoma, M., . . . Phipps,
W. (2018). Quantitative RNAseq analysis of Ugandan KS tumors reveals KSHV gene
expression dominated by transcription from the LTd downstream latency promoter. PLoS
Pathog, 14(12), e1007441. doi:10.1371/journal.ppat.1007441
98

Rubio, E. D., Reiss, D. J., Welcsh, P. L., Disteche, C. M., Filippova, G. N., Baliga, N. S., . . .
Krumm, A. (2008). CTCF physically links cohesin to chromatin. Proc Natl Acad Sci U S
A, 105(24), 8309-8314. doi:10.1073/pnas.0801273105
Satija, R., Farrell, J. A., Gennert, D., Schier, A. F., & Regev, A. (2015). Spatial reconstruction of
single-cell gene expression data. Nat Biotechnol, 33(5), 495-502. doi:10.1038/nbt.3192
Soulier, J., Grollet, L., Oksenhendler, E., Cacoub, P., Cazals-Hatem, D., Babinet, P., . . . et al.
(1995). Kaposi's sarcoma-associated herpesvirus-like DNA sequences in multicentric
Castleman's disease. Blood, 86(4), 1276-1280.
Stedman, W., Kang, H., Lin, S., Kissil, J. L., Bartolomei, M. S., & Lieberman, P. M. (2008).
Cohesins localize with CTCF at the KSHV latency control region and at cellular c-myc
and H19/Igf2 insulators. EMBO J, 27(4), 654-666. doi:10.1038/emboj.2008.1
Toth, Z., Brulois, K., Lee, H. R., Izumiya, Y., Tepper, C., Kung, H. J., & Jung, J. U. (2013).
Biphasic euchromatin-to-heterochromatin transition on the KSHV genome following de
novo infection. PLoS Pathog, 9(12), e1003813. doi:10.1371/journal.ppat.1003813
Vieira, J., & O'Hearn, P. M. (2004). Use of the red fluorescent protein as a marker of Kaposi's
sarcoma-associated herpesvirus lytic gene expression. Virology, 325(2), 225-240.
doi:10.1016/j.virol.2004.03.049
Yamashita, R., Sathira, N. P., Kanai, A., Tanimoto, K., Arauchi, T., Tanaka, Y., . . . Suzuki, Y.
(2011). Genome-wide characterization of transcriptional start sites in humans by
integrative transcriptome analysis. Genome Res, 21(5), 775-789.
doi:10.1101/gr.110254.110
Zhao, Z., Tavoosidana, G., Sjolinder, M., Gondor, A., Mariano, P., Wang, S., . . . Ohlsson, R.
(2006). Circular chromosome conformation capture (4C) uncovers extensive networks of
epigenetically regulated intra- and interchromosomal interactions. Nat Genet, 38(11),
1341-1347. doi:10.1038/ng1891

Abstract (if available)

Abstract Enhancers play indispensable roles in cell proliferation and survival through spatiotemporally regulating gene transcription. Active enhancers and super-enhancers often produce noncoding enhancer RNAs (eRNAs) that precisely control RNA polymerase II activity. Kaposi’s sarcoma-associated herpesvirus (KSHV) is a human oncogenic gamma-2 herpesvirus that causes Kaposi’s sarcoma and primary effusion lymphoma (PEL). It is well characterized that KSHV utilizes host epigenetic machineries to control the switch between two lifecycles, latency and lytic replication. However, how KSHV impacts host epigenome at different stages of viral lifecycle is not well understood. Using global run-on sequencing (GRO-seq) and chromatin-immunoprecipitation sequencing (ChIP-seq), I profiled the dynamics of host transcriptional regulatory elements during latency and lytic replication of KSHV-infected PEL cells. This revealed that a number of critical host genes for KSHV latency, including MYC proto-oncogene, were under the control of super-enhancers whose activities were globally repressed upon viral reactivation. The eRNA-expressing MYC super-enhancers were located at downstream of the MYC gene in KSHV-infected PELs and played a key role in MYC expression. RNAi-mediated depletion or dCas9-KRAB CRISPR inhibition of eRNA expression significantly reduced MYC mRNA level in PELs, as did the treatment of an epigenomic drug that globally blocks super-enhancer function. Finally, while cellular IRF4 acted upon eRNA expression and super-enhancer function for MYC expression during latency, KSHV viral IRF4 repressed cellular IRF4 expression, decreasing MYC expression and thereby, facilitating lytic replication. These results indicate that KSHV acts as an epigenomic driver that modifies host epigenomic status upon reactivation by effectively regulating host enhancer function.

Linked assets

University of Southern California Dissertations and Theses

Conceptually similar

PDF

FoxO1 suppresses Kaposi's sarcoma-associated herpesvirus lytic replication and controls viral latency

PDF

Viral and cellular N⁶-methyladenosine and N⁶,2'-O-dimethyladenosine epitranscriptomes in the Kaposi’s sarcoma‐associated herpesvirus life cycle

PDF

Kaposi's sarcoma‐associated herpesvirus‐Bcl-2 mediated regulation of NM23-H2 is required for KSHV lytic replication

PDF

Single cell gene expression analysis of KSHV infection in three-dimensional oral epithelial tissue cultures

PDF

Kaposi's sarcoma associated herpes-virus induces cellular proxi expression to modulate host gene expression that benefits viral infection and oncogenesis

PDF

An essential role of argininosuccinate synthase 1 in Kaposi’s sarcoma-associated herpesvirus-induced cellular transformation

PDF

Regulation of inflammation and angiogenesis by Kaposi’s sarcoma-associated herpesvirus

PDF

A functional genomic approach based on shRNA-mediated gene silencing to delineate the role of NF-κB and cell death proteins in the survival and proliferation of KSHV associated primary effusion l...

PDF

Molecular strategies towards inhibition of KSHV-associated malignancies

PDF

KSHV-mediated modulation of immunoreceptor surface expression

PDF

Virus customization of host protein machinery for efficient propagation

PDF

Functional characterization of colon cancer risk-associated enhancers: connecting risk loci to risk genes

PDF

Antibody discovery and structural studies of the viral oncogene ORF74

PDF

The role of amphisomes and Rab11 protein in release of mature hepatitis B viral particles and analysis of the arginine-rich C-terminal domain of HBV precore protein

PDF

Characterization of three novel variants of the MAVS adaptor

Asset Metadata

Creator Park, Yun Kyung (author)

Core Title Epigenomic analyses of Kaposi's sarcoma-associated herpesvirus

School Keck School of Medicine

Degree Doctor of Philosophy

Degree Program Medical Biology

Publication Date 07/29/2020

Defense Date 05/29/2020

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag epigenetics,epigenomics,herpesvirus,Kaposi's sarcoma-associated herpesvirus,KSHV,OAI-PMH Harvest,PEL,primary effusion lymphoma

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Machida, Keigo (committee chair), Farnham, Peggy (committee member), Jung, Jae (committee member)

Creator Email angelaykpark@gmail.com,yunkyunp@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c89-350641

Unique identifier UC11664165

Identifier etd-ParkYunKyu-8811.pdf (filename),usctheses-c89-350641 (legacy record id)

Legacy Identifier etd-ParkYunKyu-8811.pdf

Dmrecord 350641

Document Type Dissertation

Rights Park, Yun Kyung

Type texts

Source University of Southern California (contributing entity), University of Southern California Dissertations and Theses (collection)

Access Conditions The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the a...

Repository Name University of Southern California Digital Library

Repository Location USC Digital Library, University of Southern California, University Park Campus MC 2810, 3434 South Grand Avenue, 2nd Floor, Los Angeles, California 90089-2810, USA