Experimental and Molecular Pathology 97 (2014) 120–127
Contents lists available at ScienceDirect
Experimental and Molecular Pathology
journal homepage: www.elsevier.com/locate/yexmp
A rational study for identification of highly effective siRNAs against
hepatitis B virus
Nuttkawee Thongthae a, Sunchai Payungporn b, Yong Poovorawan c, Nattanan Panjaworayan T-Thienprasert a,⁎
a
b
c
Department of Biochemistry, Faculty of Science, Kasetsart University, Bangkok, Thailand
Department of Biochemistry, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
Center of Excellence in Clinical Virology, Department of Pediatrics, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
a r t i c l e
i n f o
Article history:
Received 10 February 2014
and in revised form 7 June 2014
Available online 19 June 2014
Keywords:
RNA interference
siRNA predicting program
Effective siRNAs
Hepatitis B virus
HBV PRE
a b s t r a c t
RNA interference (RNAi) is a powerful gene knockdown technique used for study gene function. It also potentially provides effective agents for inhibiting infectious and genetic diseases. Most of RNAi studies employ a single
siRNA designing program and then require large-scale screening experiments to identify functional siRNAs. In
this study, we demonstrate that an assembly of results generated from different siRNA designing programs
could provide clusters of predicting sites that aided selection of potent siRNAs. Based on the clusters, three
siRNA target sites were selected on a conserved RNA region of hepatitis B virus (HBV), known as HBV posttranscriptional regulatory element (HBV PRE) at nucleotide positions 1317–1337, 1357–1377 and 1644–1664.
All three chosen siRNAs driven by H1 promoter were highly effective and could drastically decrease expression
of HBV transcripts (core, surface and X) and surface protein without induction of interferon response and cell cytotoxicity in liver cancer cell line (HepG2). Based on prediction of secondary structures, the silencing effects of
siRNAs were less effective against a loop sequence of the mRNA target with hairpin structure. In summary, we
demonstrate an effectual approach for identification of functional siRNAs. Moreover, highly potent siRNAs identified here may serve as novel agents for development of nucleic acid-based HBV therapy.
© 2014 Elsevier Inc. All rights reserved.
Introduction
RNA interference (RNAi) is a post-transcriptional gene-silencing
mechanism conserved in most eukaryotes, including mammals
(Elbashir et al., 2001). In brief, RNase III family riboendonuclease,
Dicer, initially cleaves double-stranded RNA molecules into small
interfering RNAs (siRNAs), which are about 21 nucleotides (nt)
long duplex with a 2 nt overhang at the 3′ end of each strand and
a monophosphate at the 5′ end (Bernstein et al., 2001). After that
the sense strand (SS) of siRNA is removed and the antisense strand
(AS) is loaded on the RNA-induced silencing complex (RISC),
which then perfectly hybridizes to a complementary region of a target mRNA. This process results in a degradation of the target mRNA
by Argonaute 2 (Miyoshi et al., 2010). If complementarity is not
achieved, it can induce translational suppression (Schwarz et al.,
2003). RNAi technology provides potential therapeutic applications
for abnormal metabolisms, cancers and viral replication (Ely et al.,
2008; Guo et al., 2011; Kariko et al., 2004; Sun et al., 2007).
Pioneering studies have identified several critical features that
are desired when designing effective siRNAs. These include optimal
⁎ Corresponding author at: Department of Biochemistry, Faculty of Science, Kasetsart
University, 50 Ngamwonwan Rd. Ladyao, Chatujak, Bangkok 10900, Thailand.
E-mail address: fscinnp@ku.ac.th (N.P. T-Thienprasert).
http://dx.doi.org/10.1016/j.yexmp.2014.06.006
0014-4800/© 2014 Elsevier Inc. All rights reserved.
thermodynamic stability (Nicholson and Nicholson, 2002; Ui-Tei et al.,
2004), GC content of 30–52% (Elbashir et al., 2002; Reynolds et al.,
2004), presence of base preferences (Hsieh et al., 2004; Katoh and
Suzuki, 2007; Reynolds et al., 2004; Takasaki et al., 2004) and absence
of secondary structures of siRNAs or mRNA targets (Schubert et al.,
2005; Yoshinari et al., 2004). These key characteristics are important
data for developing siRNA-predicting program such as siExplorer
(Katoh and Suzuki, 2007), siDirect (Naito et al., 2009) and AsiDesigner
(Park et al., 2008). However, each program may predict different
siRNA target sites because it considers different criteria of siRNA
features. Up to now, no agreement has been made on which siRNApredicting program is the best of choice. All reported RNAi studies solely
rely on one program or manually handle sequences for identifying effective siRNA target sites.
Despite a successfulness of using one single program, researchers
have to examine a number of siRNAs (at least 4–5 sites) for identifying
1–2 functional siRNAs (Bandara et al., 2013; Chen et al., 2007; Li and
Shen, 2009; Li et al., 2013; Qin et al., 2008; Wuchter et al., 2012;
Zhang et al., 2006, 2010). These experimental works are timeconsuming and costly, thus effective bioinformatic methods that could
pin down potential siRNAs are required.
The objective of this study was to identify potent siRNA target sites
against hepatitis B virus (HBV). HBV is a small-enveloped DNA virus
that causes major liver diseases including chronic hepatitis, liver
N. Thongthae et al. / Experimental and Molecular Pathology 97 (2014) 120–127
cirrhosis and liver cancer. HBV genome is partially double stranded DNA
of about 3200 base pairs and contains 4 main overlapping open reading
frames (ORFs) namely C, P, S and X. These ORFs encode for core (C) protein, the polymerase (P) protein, the surface (S) protein and the X protein, respectively (Seeger and Mason, 2000). Notably, the HBV genome
also contains important cis-elements such as HBV DNA enhancer I,
HBV DNA enhancer II and HBV post-transcriptional regulatory element
(HBV PRE) (Huan and Siddiqui, 1993; Huang and Liang, 1993; Su and
Yee, 1992). HBV PRE is considered as a good target for potentially therapeutic hybridizing nucleic acid such as siRNA because it is a highly conserved RNA element (Panjaworayan et al., 2010) presented in all HBV
transcripts. Moreover, it has been reported to have important roles in
regulation of HBV mRNAs including nuclear export (Donello et al.,
1996; Huang and Liang, 1993; Huang and Yen, 1994), RNA splicing
(Heise et al., 2006) and RNA stability (Ehlers et al., 2004). Furthermore,
various stages in the HBV replication can be targeted by siRNAs. In brief,
the HBV virion attaches to the unknown liver receptor and gains entry.
The envelope is then removed, the viral core particle is subsequently released and it migrates to the hepatocyte nucleus. Within the nucleus,
the HBV genome is repaired to form a covalently closed circular DNA
(cccDNA). This cccDNA is the template for viral mRNA transcription
and may persist in the nucleus of liver cells for the lifetimes of patients
that are chronically infected (Ganem and Prince, 2004). From the
cccDNA, several genomic and subgenomic RNAs are transcribed by the
RNA polymerase II. The viral mRNAs are then exported in the cytoplasm
to generate viral proteins. These proteins together with viral RNA are
assembled into new progeny viral capsid. Subsequently, the RNA is
reverse-transcribed into viral DNA. Finally, the new progeny virion is
made and exported from the cell or it can recycle its genome into the
nucleus for conversion to cccDNA (Wand, 2004). The steps of HBV life
cycle that can be targeted by siRNAs include inhibition of cccDNA information, inhibition of transcription and post-transcriptional regulation
of HBV mRNA (in the nucleus) and inhibition of translation and nucleocapsid assembly (in the cytoplasm) (Grimm et al., 2011).
In this project, the identification of potent siRNA target site HBV PRE
was based on the cluster results of different siRNA predicting programs.
Luciferase assay and quantitative real-time PCR were performed to
study silencing effects against the luciferase and HBV transcripts in
HepG2 cells, respectively. Cytotoxicity and interferon response were
also analyzed to evaluate effects of the selected siRNAs. Together, the results from this study demonstrate an alternative approach for identifying effective siRNA target sites and also indicate highly functional
siRNAs against HBV transcripts.
121
Plasmid construction
Prior to plasmid constructions, 1 μg/μL of two complementary
shRNA oligonucleotides was annealed together in 1 × DNA annealing
solution (Ambion):
ShPRE1357_T, 5′-gatccatatacatcgtttccatggttcaagagaccatggaaacgatg
tatatttttttggaaa-3′;
ShPRE1357_B, 5′-agcttttccaaaaaaatatacatcgtttccatggtctcttgaaccatg
gaaacgatgtatat-3′;
ShPRE1644_T, 5′-gatccggtcttacataagaggactttcaagagaagtcctcttatgtaa
gaccttttttggaaa-3′;
ShPRE1644_B, 5′-agcttttccaaaaaaggtcttacataagaggacttctcttgaaagt
cctcttatgtaagacc-3′.
The annealing was carried out at 95 °C for 5 min and then cooled
down to room temperature for 1 h. Finally, all consequent mixtures
were ligated with cut pSilencer 3.0-H1 and cut pSilencer 4.1-CMV neo at
BamHI and HindIII sites. For construction of plasmid expressing siRNA
1317–1337 under CMV promoter, complementary nucleotide of HBV
PRE1317–1337 was cut from the pShPRE1317–1337 (Panjaworayan
et al., 2010) and ligated with cut pSilencer 4.1-CMV neo at BamHI and
HindIII.
Cell culture and transfection
HepG2 cells were cultured in 75 cm3 sterile tissue culture flasks
(Greiner Bio-One) at 37 °C with 5% CO2 in DMEM (Invitrogen) supplemented with 10% (v/v) heat inactivated FBS (Invitrogen) and 1%
antimycotic antibiotic (Invitrogen). Prior to transfection, the cells
were seeded into 24-well plates (Greiner Bio-One) with 105 cells/
well and incubated for 24 h. All transfections were performed using Lipofectamine™ 2000 (Invitrogen). The ratio between DNA (μg) and Lipofectamine™ 2000 (μL) was 1:2.5. For luciferase assay, 300 ng of the series of
siRNA expression plasmids was transiently co-transfected in triplicate
with 600 ng of pBasic/fPRE (Panjaworayan et al., 2010) and 100 ng of
the internal control plasmid, pCMV-RLuc. For studies of HBV gene expression and cccDNA, 600 ng of the series of siRNA expression plasmids was
transiently co-transfected in triplicate with 300 ng of a plasmid expressing a complete HBV genome subtype adw, genotype A (Panjaworayan
et al., 2007) (a gift from M-H Lin, National Taiwan University) and
100 ng of pCMV-RLuc. In addition, cells were treated with 100 ng of
Peginterferon alfa-2a as a positive control in IFN response assay.
Luciferase assay
Materials and methods
Identification and characterization of siRNA target sites
HBV PRE sequence (genotype A, GenBank accession No: AM282986)
was input into eleven siRNA predicting programs, which were
AsiDesigner (Park et al., 2008), BLOCK-iT™ RNAi Designer (Invitrogen),
siRNA Design (Kim et al., 2005), DSIR (Vert et al., 2006), siDESIGN Center (Thermo Fisher Scientific), siDirect 2.0 (Naito et al., 2009), siExplorer
(Katoh and Suzuki, 2007), siRNA Target Designer 1.6 (Promega), siRNA
Target Finder (Ambion), siRNA Target Finder (GenScript) and T7 RNAi
Oligo Designer (Dudek and Picard, 2004). The prediction results were
then clustered using Sequencher 4.10.1 program (Gene Codes Corporation). The selected siRNA target sites were then chosen from the three
highest potential groups based on consensus sequence (AAN19) and a
percentage of GC content around 30–52%. They were then characterized
by crucial features such as base preferences and thermodynamic stability. Subsequently, sequence of Luc+ (Firefly luciferase) conjugating with
HBV PRE and four HBV mRNAs (pgRNA, preS1, preS2/S and X; GenBank
accession No: AM282986) was input into the mfold program (Zuker,
2003) for prediction of secondary structures.
Forty-eight hours post-transfection, cells were lysed with 100 μL of
1× passive lysis buffer (Promega). The supernatant was collected and
cell debris was removed. The luciferase assay was performed using
Dual-Luciferase® Reporter Assay System (Promega) with Multi-Mode
Microplate Reader (Synergy™ HT, BioTek®).
Quantitative real-time PCR analysis
After 48 h of transfection, total RNA was extracted by TRIzol®
(Invitrogen). After treatment with DNaseI (New England BioLabs), first
strand cDNA was synthesized by RevertAid Reverse Transcriptase (Thermo Scientific) and then subjected to real-time PCR. On the other hand,
total DNA was extracted using Genomic DNA Extraction Kit (RBC Bioscience). In brief, real-time PCR was performed in 10 μL reaction volumes
containing RBC ThermoOne™ Real-time PCR premix (RBC Bioscience).
Specific primers used for detection of cccDNA, core, surface, X, STAT1,
and OAS1 were: cccDNA-F, 5′-actcttggactcccagcaatg-3′ and cccDNA-R,
5′-ctttataagggtcaatgtcca-3′ (Panjaworayan et al., 2010); Core-F 5′
cattgacccttataaagaatttggagc-3′ and Core-R, 5′-ccagcagagaattgcttgcctgag3′ (Fujiyama et al., 1983); Surface-F 5′-gtgtctgcggcgttttatca-3′ and
122
N. Thongthae et al. / Experimental and Molecular Pathology 97 (2014) 120–127
Surface-R, 5′-gacaaacgggcaacatacctt-3′ (Garson et al., 2005); X-F, 5′ctccccgtctgtgccttct-3′ and X-R, 5′-gatctggtgggcgttcac-3′ (Yalamanchili
et al., 2011); STAT-F, 5′-atgtctcagtggtacgaacttca-3′ and STAT-R, 5′tgtgccaggtactgtctgatt-3′ (Sun et al., 2010); and OAS1-F, 5′gatctcagaaataccccagcca-3′ and OAS1-R, 5′-agctacctcggaagcacctt-3′
(Sun et al., 2010). Fluorescence was measured after each cycle
with StepOne software version 2.3 (StepOnePlus Real-Time PCR System, Applied Biosystems). To confirm specific amplification, melting
curve analysis of each amplicon was performed using a default program
of the machine. Beta-globin (beta-globin-F: 5′-gtgcacctgactcctgaggaga3′ and beta globin-R: 5′-ccttgataccaacctgcccag-3′) (Panjaworayan et al.,
2010) and beta-actin (beta-actin-F: 5′-ctgggcatggagtcctgtggcatcc-3′ and
beta-actin-R: 5′-cgcaactaagtcatagtccgcctag-3′) (Sun et al., 2010)
were used as internal controls. The result was indicated in terms
of relative quantification by comparative threshold (delta–delta
Ct) method (2− ΔΔCt). Statistical analysis was performed using independent Student's t-test. Differences were determined to be statistically significant for p values b 0.05.
Cell viability (MTT) assay
After transfection for 48 h, the old media in each well was replaced
with 200 μL of new media and 10 μg of MTT (Invitrogen). Next, the
cells were incubated for 3 h at 37 °C. After that, media were removed
and DMSO (Amresco) was then added to dissolve the pure formazan.
After incubation for 5 min at room temperature, the absorbance was
then measured by a microplate reader (TECAN) at a wavelength of
570 nm.
Western blot analysis
After 48 h of transfection, the protein lysates was collected using 1×
Passive Lysis Buffer (Promega). The cell lysates were separated by using
NuPAGE® Bis-Tris mini gels (Invitrogen) and electrically transferred
into Hybond-P PVDF Membrane (GE-Healthcare) using 1 × NuPAGE®
transfer buffer (Invitrogen). After that, the membrane was blocked
and washed in TBS-T buffer for 1 h 30 min, respectively. Next, the
membrane was incubated with primary antibody (1:1000) of antiGAPDH (Santa Cruz) and anti-NF-κB (Santa Cruz) at room temperature
for 1 h. Blots were then incubated with secondary antibody linked
horseradish peroxidase (1:10,000) (Abcam) at room temperature
for 1 h. For chemiluminescent detection, the immune-blots were incubated with Amersham ECL Prime Western Blotting Detection Reagent
(GE-Healthcare) at room temperature for 5 min and visualized using
Image analyzer (Peqlab, Fusion FX7).
ELISA assay
The levels of HBsAg in the media were determined using the
ARCHITECT i1000SR kit (Abbott) based on enzyme-linked immunosorbent assay (ELISA) (Rukhsana et al., 2010). All samples were
performed in triplicate.
Results
Identification of effective siRNA target sites within HBV PRE by using a combined programming method
To minimize viral escape occurring from a selection pressure, a wellconserved element, HBV PRE, was chosen as a target site. Five hundreds
base pairs of full length HBV PRE was input into eleven predicting programs. As a result, each program predicted siRNA target sites (Supplementary data: Table 1S) with a range from 1 to 50 sites and there
were 130 target sites all together. A combined programing method
was then performed by grouping all predicting sites using a sequence
assembly program, Sequencher 4.10.1. Nine clusters (I–IX) were clearly
observed with clusters IX, V and IV as the top three clusters with the
most predicted siRNA target sites, respectively (Fig. 1). We then selected
a representative target site from each of clusters IX, V and IV based on
consensus sequence (AAN19) (Elbashir et al., 2002) and the percentage
of GC content (30–52%) (Amarzguioui and Prydz, 2004; Elbashir et al.,
2002; Reynolds et al., 2004). Consequently, three selected siRNA target
sites were named accordingly to their nucleotide positions: 1317–1337
(5′-aaagcucaucggaacugacaa-3′); 1357–1377 (5′-aaauauacaucguuucc
augg-3′); and 1644–1664 (5′-aaggucuuacauaagaggacu-3′) (Fig. 1).
Notably, the siRNA target site 1317–1337 was previously identified by
our laboratory and it was demonstrated to significantly decrease the
HBV DNA template (covalently closed circular DNA, cccDNA) in HuH-7
cells (Panjaworayan et al., 2010). All three selected siRNA target sites
were highly specific to the HBV genes (blastn analysis mode megablast
against human transcript database, Supplementary data: Table 2S).
Selected siRNAs were highly effective against expression of luciferase
and HBV genes without induction of interferon response and cell
cytotoxicity
All selected siRNA target sites were converted into shRNA template
oligonucleotides and ligated with the cut siRNA expression vectors,
pSilencer 3.0-H1 (Ambion) and pSilencer 4.1-CMV neo (Ambion). To
test whether selected siRNAs could silence a well-expressed transcript,
the luciferase assay was performed. 300 ng of the generated siRNA expression plasmids was transiently co-transfected in triplicate with
Fig. 1. A schematic diagram demonstrating clusters of identified siRNAs based on a combined programming method. One hundred and thirty predicted siRNAs from eleven programs were
clustered into nine groups (I–IX) using the assembly program Sequencher. The scale bar with numbers indicates nucleotide position of HBV genome when nucleotide 1151–1684 is defined as region of HBV PRE. The colored blocks above the scale bar represent the predicted siRNA sites. The coloring corresponds to different prediction programs (color online):
AsiDesigner (gray), BLOCK-iT™ RNAi Designer (orange), siRNA Design (red), DSIR (purple), siDESIGN Center (black), siDirect 2.0 (yellow), siExplorer (brown), siRNA Target Designer
1.6 (pale green), siRNA Target Finder (Ambion: blue), siRNA Target Finder (GenScript: pink) and T7 RNAi Oligo Designer (dark green). Three selected siRNAs are labeled in blue with nucleotide position.
N. Thongthae et al. / Experimental and Molecular Pathology 97 (2014) 120–127
600 ng of plasmid expressing Firefly luciferase conjugated with HBV PRE
(pBasic/fPRE) (Panjaworayan et al., 2010) and 100 ng of Renilla expression plasmid (pCMV-RLuc) using Lipofectamine™ 2000. The experiment also included the analytical control plasmid (pSilencer-GAPDH,
Ambion), which targets the human GAPDH mRNA and the negative
control plasmid (pSilencer-Negative, Ambion), a scrambled sequence
that is not found in the human genome. HepG2 cells were harvested
48 h post-infection. The result indicated that the siRNAs driven by H1
promoters significantly inhibited luciferase activity whereas all siRNAs
driven by the CMV promoter showed no effects on the luciferase activity
in the HepG2 cell line (Fig. 2(A)). The most potent siRNA effect against
luciferase activity was observed with siRNA 1317–1337 (90.47% reduction, p b 0.001) while the siRNA 1644–1664 and siRNA 1357–1377
showed 70.64% (p b 0.001), and 13.48% (p b 0.05) reductions, respectively (Fig. 2(A)).
In addition, siRNA expression plasmids driven by the H1 promoter
were carried on to test their abilities to abolish the expression of HBV
transcripts. HepG2 cells were transiently co-transfected with 300 ng of
plasmid expressing HBV genome (a gift from M-H Lin, National
Taiwan University), 600 ng of the siRNA expression plasmids and 100
ng of pCMV-RLuc. After 48 h post-transfection, the cells were harvested
to analyze the gene expression using quantitative real-time PCR. Overall, siRNA 1317–1337 demonstrated the greatest silencing effects by
suppressing the expression of HBV core, surface and X with about 94–
98% of reduction (Fig. 2(B)). The second best siRNA was 1644–1664. It
drastically inhibited the expression of core, surface and X by about
76% (p b 0.05), 81% (p b 0.01) and 98% (p b 0.01), respectively. Despite
siRNA 1357–1377 having the weakest effects, it could still significantly
decrease the expression of core, surface and X by 70% (p b 0.05), 74%
(p b 0.05) and 89% (p b 0.05), respectively (Fig. 2(B)). Therefore, all
selected siRNAs were highly effective against HBV transcripts. By
performing ELISA assay, the results confirmed that all identified siRNAs
could significantly decrease expression of surface protein (HBsAg).
Among the three siRNAs, siRNA 1317–1337 had the most potent activity
whereas siRNA 1357–1377 had the weakest silencing effects (Fig. 2(C)).
In addition, siRNA 1357–1377 could significantly decrease the level of
cccDNA (Fig. 2(D)).
123
Further experiments were then conducted to evaluate whether
these selected siRNAs had the ability to induce cell cytotoxicity and interferon response or not. HepG2 cells were co-transfected with the
same condition used to perform the quantitative real-time PCR above.
Cell viability was determined using MTT assay whereas the quantitative
real-time PCR was used to examine expression levels of STAT1 and
OAS1 (the down-stream genes of IFN). The result showed that none of
the siRNA expression plasmids caused cell cytotoxicity in the given condition (Fig. 3(A)). Moreover, the expression levels of STAT1, OAS1 and a
housekeeping gene (beta-globin) were not affected by the presence of
siRNAs (Fig. 3(B)). To confirm that these siRNAs did not generate offtarget effects, expression level of cellular proteins, GAPDH and nuclear
factor kappa-light-chain-enhancer of activated B cells (NF-κB)
were investigated. GAPDH was chosen because it is an abundant
housekeeping gene whereas NF-κB is a downstream signaling pathway of RNA-activated protein kinase that is elevated by off-target effect of
siRNAs (Hornung et al., 2005). Subsequently, cell lysates extracted from
the same transfection condition described above were subjected for
Western blot analysis. The result demonstrated that all identified siRNAs
had no effect on the expression of GAPDH and NF-κB, thus these siRNAs
did not cause off-target effects (Fig. 3(C)).
Base preferences, thermodynamic stabilities and secondary structure are
key characteristics of functional siRNAs
By analyzing the presence of base preferences, we found that siRNA
1317–1337 contains the highest numbers of base preferences while
siRNA 1357–1377 had the most unwanted position-specific bases
among the selected siRNAs (Supplementary data: Table 3S).
Furthermore, the mfold program (Zuker, 2003) was used to predict
secondary structures of luciferase conjugated with HBV PRE, pgRNA,
preS1, preS2/S and X transcripts. From each transcript, we noticed that
all of the selected siRNAs targeted part of the hairpin structures. However, only siRNA 1317–1337 did not target at the loops of any structures
(Fig. 4). According to the effects of siRNAs on luciferase and HBV transcripts (Fig. 2(A) and (B)), the results from the mfold program therefore
implied that siRNAs could function against mRNA targets with
Fig. 2. Effects of selected siRNAs on luciferase transcript, HBV transcripts and cccDNA in HepG2 cells. (A) The relative Luc+ activity (%). White box indicates siRNA expression plasmids driven by
H1 promoter and gray box for CMV promoter. (B) The relative HBV gene expression (%). White box, gray box and blue box indicate expressions of core, surface and X transcripts, respectively.
(C) The relative HBsAg expression (%). (D) The relative cccDNA level (%). “*”, “**” and “***” indicate significant inhibitory effects when compared with the control at p b 0.05, p b 0.01
and p b 0.001 (by t-test), respectively.
124
N. Thongthae et al. / Experimental and Molecular Pathology 97 (2014) 120–127
Fig. 3. The selected siRNAs did not induce cell cytotoxicity and interferon response.
(A) MTT assay indicates the cell viability (%). (B) Interferon response assay shows
human gene expression. White box, gray box and blue box mark the STAT1, OAS1 and
beta-globin mRNAs, respectively. (C) Western blot analysis showed expression of NF-κB
and GAPDH proteins. “***” indicates statistical difference of gene expression when
compared with the cell only at p b 0.001 (by t-test).
secondary structures. Nevertheless, their silencing effects became less
effective when targeting at the loops of the hairpin structures.
Discussion
Currently, there are several siRNA designing programs available for
RNAi studies (Dudek and Picard, 2004; Katoh and Suzuki, 2007; Kim
et al., 2005; Naito et al., 2009; Park et al., 2008; Vert et al., 2006).
Some of the programs are popular and often employed to identify
siRNA target sites such as siRNA Target Finder (Ambion) and BLOCKiT™ RNAi Designer (Invitrogen). In this study, we input 534 bp of HBV
PRE into eleven siRNA predicting programs. The results demonstrated
that one program predicted a range numbers of siRNA target sites
from 1 to 50 (Fig. 1 and Table 1S). However, some predicted siRNA
target sites identified more than one program (Fig. 1). By using cluster
results of different programs, potential target sites were easily distinguished because different programs detected them (Fig. 1). In this
study, only three potential siRNA target sites were selected and they
were all demonstrated to be highly effective siRNAs against HBV transcripts (Fig. 2(B)). Therefore, a combined method was found to be an effective approach. However, a high number of programs and program
selection are factors affecting prediction of siRNA target sites. The prediction may be less informative if predicting programs used have similar algorithms.
In this study, three highly effective siRNA target sites (siRNA
1317–1337, siRNA 1357–1377 and siRNA 1644–1664) were identified.
RNA polymerase III promoters are naturally ubiquitous and constitutively express high levels of shRNAs that may cause cytotoxicity of tissue culture cells and induce off-target effects due to the accumulation
of excessive AS (McBride et al., 2008). Our results, however, indicate
that siRNAs expressing from RNA polymerase III (H1 promoter) could
significantly inhibit luciferase (Fig. 2(A)), HBV transcripts (Fig. 2(B))
and surface protein (Fig. 2(C)) without causing off-target effects on cellular proteins (Fig. 3(C)) and did not induce cell cytotoxicity including
IFN response (Fig. 3(A) and (B)). In addition, our result suggested that
siRNA 1644–1664 might have a different mode of action from siRNA
1317–1337 and siRNA 1357–1377 because siRNA 1644–1664 could
not be able to decrease level of cccDNA expression (Fig. 2(D)). However,
it significantly abolished gene expression of HBV core, surface and X
transcripts (Fig. 2(B)) including surface protein (Fig. 2(C)), thus its
silencing effects must directly act on the HBV transcripts. On the other
hand, siRNA 1317–1337 and siRNA 1357–1377 could significantly decrease the level of cccDNA expression (Fig. 2(D) (Panjaworayan et al.,
2010)); implying that they could inhibit the cccDNA formation. However, the mechanism of RNAi on the cccDNA formation is unknown. Up to
date, the known role of RNAi at a DNA level has been reported on a heterochromatin assembly in yeast (Schizosaccharomyces pombe) (Verdel
et al., 2004) and Arabidopsis thaliana by the RNA-induced transcriptional silencing complex (RITS) (Verdel et al., 2009). Notably, the strong deduction of HBV transcripts and surface protein by siRNA 1317–1337
(Fig. 2(B) and (C)) may be due to mutually inclusive events from the
silencing effects on the cccDNA formation (Panjaworayan et al., 2010)
as well as the HBV transcripts. Despite the fact that siRNA 1357–1377
could inhibit the cccDNA, its silencing effect on HBV transcripts was
insignificantly different from siRNA 1644–1664 (Fig. 2(B)). Moreover,
it had the weakest inhibition on the expression of surface protein
(Fig. 2(C)). Therefore, we speculated that siRNA 1357–1377 might
mainly act on the inhibition of cccDNA formation leading to deduction
of HBV transcripts and HBV proteins. The inhibition by siRNAs at the
DNA level may have a lesser effect than at the RNA level. However,
more experiments will be required to prove this speculation.
Furthermore, Yoshinari et al. (2004) and Schubert et al. (2005) previously reported that the secondary structure is a very important feature
that affects the activity of siRNAs. Our results additionally demonstrate
that siRNAs could effectively target mRNAs with secondary structures,
but their silencing characteristics become less efficient when targeting
at the loop of the hairpin structure (Fig. 4).
Several pioneer studies previously demonstrated the effectiveness of
using one siRNA/short hairpin RNA (shRNA) to inhibit multiple HBV
RNAs either in mice or in HepG2 cells (Chen et al., 2003; McCaffrey
et al., 2003; Ren et al., 2005; Uprichard et al., 2005; Wu et al., 2005;
Zhao et al., 2006). Likewise, our results also provided novel siRNAs
that showed to silence multiple HBV gene expressions (core, X and S)
in HepG2 cells. Moreover, our results also demonstrated that siRNA
1317–1337 (Panjaworayan et al., 2010) and siRNA 1357–1377 could
significantly decrease the level of cccDNA (Fig. 2(D)). As cccDNA is a
template for HBV RNA synthesis and it is vital for the persistence of
HBV infection (Grimm et al., 2011), antiviral therapies therefore aim
to eliminate it. However, current available drugs cannot reduce viral
cccDNA from the nucleus of the infected (Anonymous, 2009). Until
today, only a few reports have indicated the effects of siRNA on the formation of cccDNA. The previous reports included results from Starkey
et al. (2009), which showed that specific shRNAs could reduce cccDNA
N. Thongthae et al. / Experimental and Molecular Pathology 97 (2014) 120–127
125
Fig. 4. All selected siRNA target sites were predicted to form secondary structures. The secondary structures of luciferase conjugated with HBV PRE, pgRNA, preS1, preS2/S and X mRNAs
were calculated using mfold program. The position of selected siRNA target sites and their free energy are indicated.
in a HBV baculovirus subculture system (Starkey et al., 2009) and results
from Li et al. (2007), which indicated that siRNAs against HBV nuclear
localization signal could markedly inhibit cccDNA in HepG2.2.15 cells
(Li et al., 2007). Furthermore, some studies have showed that single
siRNA/shRNA could inhibit different HBV genotypes (Sun et al., 2010;
Zhang et al., 2010). As HBV PRE is a highly conserved region, our identified siRNAs may possibly inhibit HBV gene expression for more than one
genotype. However, more experiments are required to prove this
hypothesis. Taken all together, the results from our study offered a
new approach to identify effective siRNAs. Furthermore, the identified
siRNAs here are promising to be further developed as a gene-based
therapy.
Since the discovery of the RNAi pathway in 1998 (Fire et al., 1998),
much knowledge about rational design for effective RNAi effectors,
RNAi approaches, and mechanism of delivery has been accumulated.
Current efforts have been tried to translate this knowledge into therapeutic intervention for disease treatment. Clinical trials with RNAi have begun
for several disorders (Deng et al., 2014), but challenges such as instability
and low bioavailability, off-target effects, immunostimulation and
efficient delivery methods have to be further investigated to overcome
the challenges.
In conclusion, a combined programing method is a potential
approach for effective identification of siRNA target sites. In this study,
three potential siRNA target sites (1317–1337, 1357–1377 and 1644–
1664) were identified and demonstrated to be potent and could significantly inhibited HBV transcripts (core, surface and X) and surface
protein without interferon induction or cytotoxicity or off-target effects
in HepG2 cells. In addition, siRNA 1357–1377 was also able to inhibit
cccDNA. Our results also suggested that a loop on the hairpin structure
is a less effective siRNA target site.
Supplementary data to this article can be found online at http://dx.
doi.org/10.1016/j.yexmp.2014.06.006.
Acknowledgment
We would like to express our deep appreciation to Dr. Christopher M
Brown for plasmids (pShPRE1317–1337 and pSilencer 3.0-H1 system)
and Dr. Amonida Zadissa for proofreading the manuscript. NT was
126
N. Thongthae et al. / Experimental and Molecular Pathology 97 (2014) 120–127
funded by Graduate School Kasetsart University Grant. NPT is funded by
Research Grant for New Scholar (co-funded by TRF and CHE:
MRG5380104) and Faculty of Science Grant, Kasetsart University
(ScRF-S20/2555). This study was also funded by the Kasetsart University Research and Development Institute Grant (Vor Tor Dor 45.53).
References
Amarzguioui, M., Prydz, H., 2004. An algorithm for selection of functional siRNA
sequences. Biochem. Biophys. Res. Commun. 316, 1050–1058.
Anonymous, 2009. EASL Clinical Practice Guidelines: management of chronic hepatitis B. J.
Hepatol. 50, 227–242.
Bandara, S., Malmersjo, S., Meyer, T., 2013. Regulators of calcium homeostasis identified
by inference of kinetic model parameters from live single cells perturbed by siRNA.
Sci. Signal. 6, ra56.
Bernstein, E., Caudy, A.A., Hammond, S.M., Hannon, G.J., 2001. Role for a bidentate ribonuclease in the initiation step of RNA interference. Nature 409, 363–366.
Chen, Y., Du, D., Wu, J., Chan, C.P., Tan, Y., Kung, H.F., He, M.L., 2003. Inhibition of hepatitis
B virus replication by stably expressed shRNA. Biochem. Biophys. Res. Commun. 311,
398–404.
Chen, C.C., Ko, T.M., Ma, H.I., Wu, H.L., Xiao, X., Li, J., Chang, C.M., Wu, P.Y., Chen, C.H., Han,
J.M., Yu, C.P., Jeng, K.S., Hu, C.P., Tao, M.H., 2007. Long-term inhibition of hepatitis B
virus in transgenic mice by double-stranded adeno-associated virus 8-delivered
short hairpin RNA. Gene Ther. 14, 11–19.
Deng, Y., Wang, C.C., Choy, K.W., Du, Q., Chen, J., Wang, Q., Li, L., Chung, T.K., Tang, T., 2014.
Therapeutic potentials of gene silencing by RNA interference: principles, challenges,
and new strategies. Gene 538, 217–227.
Donello, J.E., Beeche, A.A., Smith III, G.J., Lucero, G.R., Hope, T.J., 1996. The hepatitis B virus
posttranscriptional regulatory element is composed of two subelements. J. Virol. 70,
4345–4351.
Dudek, P., Picard, D., 2004. TROD: T7 RNAi Oligo Designer. Nucleic Acids Res. 32,
W121–W123.
Ehlers, I., Horke, S., Reumann, K., Rang, A., Grosse, F., Will, H., Heise, T., 2004. Functional
characterization of the interaction between human La and hepatitis B virus RNA. J.
Biol. Chem. 279, 43437–43447.
Elbashir, S.M., Harborth, J., Lendeckel, W., Yalcin, A., Weber, K., Tuschl, T., 2001. Duplexes
of 21-nucleotide RNAs mediate RNA interference in cultured mammalian cells. Nature 411, 494–498.
Elbashir, S.M., Harborth, J., Weber, K., Tuschl, T., 2002. Analysis of gene function in somatic
mammalian cells using small interfering RNAs. Methods 26, 199–213.
Ely, A., Naidoo, T., Mufamadi, S., Crowther, C., Arbuthnot, P., 2008. Expressed anti-HBV primary microRNA shuttles inhibit viral replication efficiently in vitro and in vivo. Mol.
Ther. 16, 1105–1112.
Fire, A., Xu, S., Montgomery, M.K., Kostas, S.A., Driver, S.E., Mello, C.C., 1998. Potent and
specific genetic interference by double-stranded RNA in Caenorhabditis elegans. Nature 391, 806–811.
Fujiyama, A., Miyanohara, A., Nozaki, C., Yoneyama, T., Ohtomo, N., Matsubara, K., 1983.
Cloning and structural analyses of hepatitis B virus DNAs, subtype adr. Nucleic
Acids Res. 11, 4601–4610.
Ganem, D., Prince, A.M., 2004. Hepatitis B virus infection—natural history and clinical consequences. N. Engl. J. Med. 350, 1118–1129.
Garson, J.A., Grant, P.R., Ayliffe, U., Ferns, R.B., Tedder, R.S., 2005. Real-time PCR quantitation
of hepatitis B virus DNA using automated sample preparation and murine cytomegalovirus internal control. J. Virol. Methods 126, 207–213.
Grimm, D., Thimme, R., Blum, H.E., 2011. HBV life cycle and novel drug targets. Hepatol.
Int. 5, 644–653.
Guo, W., Zhang, Y., Chen, T., Wang, Y., Xue, J., Xiao, W., Mo, X., Lu, Y., 2011. Efficacy of
RNAi targeting of pyruvate kinase M2 combined with cisplatin in a lung cancer
model. J. Cancer Res. Clin. Oncol. 137, 65–72.
Heise, T., Sommer, G., Reumann, K., Meyer, I., Will, H., Schaal, H., 2006. The hepatitis B
virus PRE contains a splicing regulatory element. Nucleic Acids Res. 34, 353–363.
Hornung, V., Guenthner-Biller, M., Bourquin, C., Ablasser, A., Schlee, M., Uematsu, S.,
Noronha, A., Manoharan, M., Akira, S., de Fougerolles, A., Endres, S., Hartmann, G.,
2005. Sequence-specific potent induction of IFN-alpha by short interfering RNA in
plasmacytoid dendritic cells through TLR7. Nat. Med. 11, 263–270.
Hsieh, A.C., Bo, R., Manola, J., Vazquez, F., Bare, O., Khvorova, A., Scaringe, S., Sellers, W.R.,
2004. A library of siRNA duplexes targeting the phosphoinositide 3-kinase pathway:
determinants of gene silencing for use in cell-based screens. Nucleic Acids Res. 32,
893–901.
Huan, B., Siddiqui, A., 1993. Regulation of hepatitis B virus gene expression. J. Hepatol. 17
(Suppl. 3), S20–S23.
Huang, J., Liang, T.J., 1993. A novel hepatitis B virus (HBV) genetic element with Rev response element-like properties that is essential for expression of HBV gene products.
Mol. Cell. Biol. 13, 7476–7486.
Huang, Z.M., Yen, T.S., 1994. Hepatitis B virus RNA element that facilitates accumulation of
surface gene transcripts in the cytoplasm. J. Virol. 68, 3193–3199.
Kariko, K., Bhuyan, P., Capodici, J., Ni, H., Lubinski, J., Friedman, H., Weissman, D., 2004.
Exogenous siRNA mediates sequence-independent gene suppression by signaling
through toll-like receptor 3. Cells Tissues Organs 177, 132–138.
Katoh, T., Suzuki, T., 2007. Specific residues at every third position of siRNA shape its
efficient RNAi activity. Nucleic Acids Res. 35, e27.
Kim, D.H., Behlke, M.A., Rose, S.D., Chang, M.S., Choi, S., Rossi, J.J., 2005. Synthetic dsRNA
Dicer substrates enhance RNAi potency and efficacy. Nat. Biotechnol. 23, 222–226.
Li, L., Shen, Y., 2009. Overcoming obstacles to develop effective and safe siRNA therapeutics.
Expert. Opin. Biol. Ther. 9, 609–619.
Li, G.Q., Gu, H.X., Li, D., Xu, W.Z., 2007. Inhibition of hepatitis B virus cccDNA replication by
siRNA. Biochem. Biophys. Res. Commun. 355, 404–408.
Li, P., Jing, J., Hu, J., Li, T., Sun, Y., Guan, H., 2013. RNA interference targeting snail inhibits
the transforming growth factor beta 2-induced epithelial–mesenchymal transition in
human lens epithelial cells. J. Ophthalmol. 2013, 869101.
McBride, J.L., Boudreau, R.L., Harper, S.Q., Staber, P.D., Monteys, A.M., Martins, I., Gilmore,
B.L., Burstein, H., Peluso, R.W., Polisky, B., Carter, B.J., Davidson, B.L., 2008. Artificial
miRNAs mitigate shRNA-mediated toxicity in the brain: implications for the therapeutic development of RNAi. Proc. Natl. Acad. Sci. U. S. A. 105, 5868–5873.
McCaffrey, A.P., Nakai, H., Pandey, K., Huang, Z., Salazar, F.H., Xu, H., Wieland, S.F., Marion,
P.L., Kay, M.A., 2003. Inhibition of hepatitis B virus in mice by RNA interference. Nat.
Biotechnol. 21, 639–644.
Miyoshi, K., Miyoshi, T., Hartig, J.V., Siomi, H., Siomi, M.C., 2010. Molecular mechanisms
that funnel RNA precursors into endogenous small-interfering RNA and microRNA
biogenesis pathways in Drosophila. RNA 16, 506–515.
Naito, Y., Yoshimura, J., Morishita, S., Ui-Tei, K., 2009. siDirect 2.0: updated software for
designing functional siRNA with reduced seed-dependent off-target effect. BMC
Bioinforma. 10, 392.
Nicholson, R.H., Nicholson, A.W., 2002. Molecular characterization of a mouse cDNA
encoding Dicer, a ribonuclease III ortholog involved in RNA interference. Mamm.
Genome 13, 67–73.
Panjaworayan, N., Roessner, S.K., Firth, A.E., Brown, C.M., 2007. HBVRegDB: annotation,
comparison, detection and visualization of regulatory elements in hepatitis B virus
sequences. Virol. J. 4, 136.
Panjaworayan, N., Payungporn, S., Poovorawan, Y., Brown, C.M., 2010. Identification of an
effective siRNA target site and functional regulatory elements, within the hepatitis B
virus posttranscriptional regulatory element. Virol. J. 7, 216.
Park, Y.K., Park, S.M., Choi, Y.C., Lee, D., Won, M., Kim, Y.J., 2008. AsiDesigner: exon-based
siRNA design server considering alternative splicing. Nucleic Acids Res. 36, W97–W103.
Qin, Q.M., Pei, J., Ancona, V., Shaw, B.D., Ficht, T.A., de Figueiredo, P., 2008. RNAi screen of
endoplasmic reticulum-associated host factors reveals a role for IRE1alpha in
supporting Brucella replication. PLoS Pathog. 4, e1000110.
Ren, G.L., Bai, X.F., Zhang, Y., Chen, H.M., Huang, C.X., Wang, P.Z., Li, G.Y., Lian, J.Q., 2005.
Stable inhibition of hepatitis B virus expression and replication by expressed siRNA.
Biochem. Biophys. Res. Commun. 335, 1051–1059.
Reynolds, A., Leake, D., Boese, Q., Scaringe, S., Marshall, W.S., Khvorova, A., 2004. Rational
siRNA design for RNA interference. Nat. Biotechnol. 22, 326–330.
Rukhsana, J., Perrotta, P.L., Okorodudu, A.O., Petersen, J.R., Mohammad, A.A., 2010. Fit-forpurpose evaluation of architect i1000SR immunoassay analyzer. Clin. Chim. Acta 411,
798–801.
Schubert, S., Grunweller, A., Erdmann, V.A., Kurreck, J., 2005. Local RNA target structure
influences siRNA efficacy: systematic analysis of intentionally designed binding
regions. J. Mol. Biol. 348, 883–893.
Schwarz, D.S., Hutvagner, G., Du, T., Xu, Z., Aronin, N., Zamore, P.D., 2003. Asymmetry in
the assembly of the RNAi enzyme complex. Cell 115, 199–208.
Seeger, C., Mason, W.S., 2000. Hepatitis B virus biology. Microbiol. Mol. Biol. Rev. 64,
51–68.
Starkey, J.L., Chiari, E.F., Isom, H.C., 2009. Hepatitis B virus (HBV)-specific short hairpin RNA is capable of reducing the formation of HBV covalently closed circular
(CCC) DNA but has no effect on established CCC DNA in vitro. J. Gen. Virol. 90,
115–126.
Su, H., Yee, J.K., 1992. Regulation of hepatitis B virus gene expression by its two enhancers.
Proc. Natl. Acad. Sci. U. S. A. 89, 2708–2712.
Sun, Y., Li, Z., Li, L., Li, J., Liu, X., Li, W., 2007. Effective inhibition of hepatitis B virus
replication by small interfering RNAs expressed from human foamy virus vectors.
Int. J. Mol. Med. 19, 705–711.
Sun, D., Rosler, C., Kidd-Ljunggren, K., Nassal, M., 2010. Quantitative assessment of the
antiviral potencies of 21 shRNA vectors targeting conserved, including structured,
hepatitis B virus sites. J. Hepatol. 52, 817–826.
Takasaki, S., Kotani, S., Konagaya, A., 2004. An effective method for selecting siRNA target
sequences in mammalian cells. Cell Cycle 3, 790–795.
Ui-Tei, K., Naito, Y., Takahashi, F., Haraguchi, T., Ohki-Hamazaki, H., Juni, A., Ueda, R., Saigo,
K., 2004. Guidelines for the selection of highly effective siRNA sequences for mammalian
and chick RNA interference. Nucleic Acids Res. 32, 936–948.
Uprichard, S.L., Boyd, B., Althage, A., Chisari, F.V., 2005. Clearance of hepatitis B virus from
the liver of transgenic mice by short hairpin RNAs. Proc. Natl. Acad. Sci. U. S. A. 102,
773–778.
Verdel, A., Jia, S., Gerber, S., Sugiyama, T., Gygi, S., Grewal, S.I., Moazed, D., 2004. RNAimediated targeting of heterochromatin by the RITS complex. Science 303, 672–676.
Verdel, A., Vavasseur, A., Le Gorrec, M., Touat-Todeschini, L., 2009. Common themes in
siRNA-mediated epigenetic silencing pathways. Int. J. Dev. Biol. 53, 245–257.
Vert, J.P., Foveau, N., Lajaunie, C., Vandenbrouck, Y., 2006. An accurate and interpretable
model for siRNA efficacy prediction. BMC Bioinforma. 7, 520.
Wand, Jack, 2004. Prevention of (HBV) hepatocellular carcinoma. N. Engl. J. Med. 351,
1567–1570.
Wu, H.L., Huang, L.R., Huang, C.C., Lai, H.L., Liu, C.J., Huang, Y.T., Hsu, Y.W., Lu, C.Y., Chen, D.S.,
Chen, P.J., 2005. RNA interference-mediated control of hepatitis B virus and emergence
of resistant mutant. Gastroenterology 128, 708–716.
Wuchter, J., Beuter, S., Treindl, F., Herrmann, T., Zeck, G., Templin, M.F., Volkmer, H., 2012.
A comprehensive small interfering RNA screen identifies signaling pathways required
for gephyrin clustering. J. Neurosci. 32, 14821–14834.
Yalamanchili, N., Syed, R., Chandra, M., Satti, V., Rao, R., Mohammed, A.H., Nanne, K.M.,
2011. A latest and promising approach for prediction of viral load in hepatitis B
virus infected patients. Indian J. Hum Genet. 17, 17–21.
N. Thongthae et al. / Experimental and Molecular Pathology 97 (2014) 120–127
Yoshinari, K., Miyagishi, M., Taira, K., 2004. Effects on RNAi of the tight structure, sequence
and position of the targeted region. Nucleic Acids Res. 32, 691–699.
Zhang, M.S., Zhou, Y.F., Zhang, W.J., Zhang, X.L., Pan, Q., Ji, X.M., Luo, Z.G., Wu, J.P., 2006.
Apoptosis induced by short hairpin RNA-mediated STAT6 gene silencing in human
colon cancer cells. Chin. Med. J. (Engl.) 119, 801–808.
Zhang, Y.L., Cheng, T., Cai, Y.J., Yuan, Q., Liu, C., Zhang, T., Xia, D.Z., Li, R.Y., Yang, L.W.,
Wang, Y.B., Yeo, A.E., Shih, J.W., Zhang, J., Xia, N.S., 2010. RNA interference in-
127
hibits hepatitis B virus of different genotypes in vitro and in vivo. BMC
Microbiol. 10, 214.
Zhao, Z.F., Yang, H., Han, D.W., Zhao, L.F., Zhang, G.Y., Zhang, Y., Liu, M.S., 2006. Inhibition
of hepatitis B virus expression and replication by RNA interference in HepG2.2.15.
World J. Gastroenterol. 12, 6046–6049.
Zuker, M., 2003. Mfold web server for nucleic acid folding and hybridization prediction.
Nucleic Acids Res. 31, 3406–3415.