STUDY of RETROVIRUS and HOST INTERPLAY: RNA HELICASE a and MICRORNA MODULATE VIRAL GENE EXPRESSION DISSERTATION Presented In
STUDY OF RETROVIRUS AND HOST INTERPLAY: RNA HELICASE A AND
MICRORNA MODULATE VIRAL GENE EXPRESSION
DISSERTATION
Presented in Partial Fulfillment of the Requirements for
the Degree Doctor of Philosophy in the Graduate School of
The Ohio State University
By
Shuiming Qian, B.S., M.S.
* * * * *
The Ohio State University
2009
Dissertation Committee: Approved by Dr. Kathleen Boris-Lawrie, Advisor
Dr. Patrick Green ______Advisor Dr. Michael Lairmore Graduate Program in Molecular, Cellular, Dr. Deborah Parris and Developmental Biology
ABSTRACT
Retroviruses are RNA viruses that replicate through a DNA intermediate, the provirus. Provirus gene expression is dependent on the host machinery. The interplay between the virus and host post-transcriptional armamentarium is complex and the interface with the small RNA pathway has not been characterized. Retroviruses including human immunodeficiency virus type 1 (HIV-1) have evolved multiple strategies to utilize host machinery to execute intricate control of viral gene expression. As introduced in
Chapter One of this dissertation, a prominent theme is that viral cis-acting RNA elements interact with cellular RNA binding proteins to modulate balanced viral post-transcriptional expression and sustain virus replication. The work in this dissertation characterized host protein interaction with a post-transcriptional control element (PCE) identified in the 5’ untranslated region (UTR) of at least eight retroviruses that facilitates efficient synthesis of retroviruses structural proteins. In addition, these studies also characterized virus-host interaction presented by the host small RNA pathway, which poses an innate cellular defense against infectious agents and retrotransposons. A growing literature shows that virus-encoded small RNAs and host encoded small RNAs play fundamental roles in animal virus replication. Another focus of the research herein was the characterization of the interaction of HIV-1 with the host small RNA pathway. The results revealed that
ii virus-encoded RNA silencing suppressor activity modulates the activity of host-encoded
microRNAs that can attenuate viral translation.
Results of Chapter Two demonstrated for the first-time that RNA helicase A
(RHA) is the cellular effector protein that operates the PCE/RNA switch. RNA mobility
shift assays and RNA co-immunoprecipitation assays revealed that RHA specifically
recognizes features of the redundant stem-loop structure of the PCE; the PCE/RHA interaction occurs in both the nucleus and the cytoplasm and is necessary for PCE activity.
Downregulation of RHA abolishes PCE activity independently of a change in PCE mRNA
stability or its cytoplasmic accumulation. Sucrose gradient analysis showed that RHA
facilitates polysome accumulation of PCE-containing retroviral RNA and the cellular junD
transcript. JunD is an AP-1 transcription factor and this transcript represents the first
example of a cellular PCE/RHA interaction that is necessary for efficient translation. In
summary, our results revealed a previously unidentified role for RHA in retrovirus and
host cell translation that implicates RHA as an integrative effector of gene expression
involved in the continuum of gene expression from transcription to translation.
Chapter Three characterizes interplay between the host small RNA pathway and
HIV-1. Experiments in plant and animal cell systems demonstrate that HIV-1 Tat
regulatory protein exerts RNA silencing suppressor (RSS) activity across the plant and
animal kingdoms. HIV-1 Tat and plant virus P19 RSS function similarly to suppress RNA
silencing downstream of small RNA maturation. The effect of the host small RNA
iii pathway was characterized by downregulation of the key enzyme of host microRNA biogenesis (Dicer), P19 expression, or by mutation in the conserved double-stranded
RNA-binding domain of the Tat RSS. The outcome of the small RNA pathway on HIV-1
replication is attenuation of viral translation. The reversal of HIV-1 translation repression
by plant RSS supports the recent finding in Arabidopsis that plant miRNAs operate by
inhibition of translation. An implication of our study is that the host small RNA pathway
plays a strategic role in the viral accumulation in a newly HIV-1-infected patient.
Chapter Four describes results from microRNA microarrays and functional assays
that assess the interface between the host small RNA pathway the HIV-1 accessory
proteins Vpr and Vif. Profiles of host microRNAs were compared between cells infected
with HIV-1 or a strain deficient in vpr/vif. The outcome of this work is a microRNA
microarray database that stands a resource to develop testable hypotheses about the role of
microRNAs in HIV-1 biology. Protein analysis demonstrated that Vpr/Vif modulates the
activity of two miRNAs that downregulate a cellular transcriptional cofactor of Tat. The
results of RNA and protein analysis provide an explanation for upregulation of HIV-1
transcription during HIV-1-induced cell cycle arrest. We conclude that modulation of
microRNA activity by Vpr and Vif contributes to the positive selection for conservation of
vpr in HIV-1 quasispecies in infected patients.
In Chapter Five, changes in microRNA profile were evaluated upon infection of
human lymphocytes with an HIV-1 strain deficient in Tat RSS activity. Comparative
iv analyses with HIV-1 infection demonstrated that a collection of host microRNAs are
modulated by HIV-1 Tat RSS activity and indicated a generalized rather than selective
effect of Tat RSS activity on host small RNA activity. Results of ribosomal profile
analysis of HIV-1 transfected 293 cells determined that HIV-1 gag RNA accumulates in
high molecular weight complexes that co-sediment with puromycin resistant
pseudo-polysomes. Pseudo-polysomes are known sites of translational repression by
microRNA. The gag transcripts redistribute to polyribosomes upon expression of viral
RSS. These results document that the interface between HIV-1 and the host small RNA
pathway modulates viral protein synthesis.
Perspectives on the experimental results and ideas for future directions are presented in Chapter Six. In conclusion, the work in this dissertation comprehensively characterized specific viral RNA interactions with host protein RNA helicase A and the interaction of HIV-1 regulatory and accessory genes with the host small RNA pathway.
Each of these interactions is important for balanced translational control of the retrovirus.
v
Dedicated to all members of my family, especially to my mom Yexian, my wife Xuehua, my daughter Grace and my son Aiden
vi
ACKNOWLEDGMENTS
No single word can express my sincere gratitude for my advisor, Dr. Kathleen
Boris-Lawrie, for her intellectual guidance and being supportive through this unforgettable journey. She has been the most amazing advisor and shares the knowledge she possesses and makes learning an enjoyable experience. The knowledge I gain from this experience is something that will stay with me for a lifetime and benefit me greatly. Her talent, endless encouragement and consistent support, enthusiasm about the science, unselfish training to be a good scientist, this is a wonderful opportunity to advance my career in science and have a greater understanding of a subject I am passionate about.
I am grateful to my advisory committee members, Dr. Patrick Green, Dr. Michael
Lairmore and Dr. Deborah Parris for their invaluable suggestions and discussions on my projects and my dissertation. I appreciate their time and continuous support. Thanks to Dr.
Lianbo Yu for statistical analysis for microarray analysis and Tim Vojt for professional figure preparation.
I would like to thank the past and present members of the Boris-Lawrie lab: Dr.
Tiffiney Roberts Hartman, Dr. Alper Yilmaz, Dr. Marcela Hernandez, Dr. Deepali Singh,
Dr. Cheryl Bolinger, Dr. Amy Hayes, Nicole Placek, Arnaz Ranji, Wei Jing, Amit Sharma
vii and Xueya Liang. My special appreciation goes to Dr. Tiffiney Roberts Hartman and Dr.
Alper Yilmaz for their friendship and numerous discussions on my research projects and advice on experimental designs. I also thank Dr. Cheryl Bolinger for her great discussion and sharing.
Finally and most importantly, I would like to thank my parents, my wife Xuehua
Zhong, my daughter Grace and my son Aiden for their love, support and encouragement.
Xuehua has been my spiritual support throughout my whole career. She has been the best listener of my complaints and always refreshes my ideas. She is not only my life-mate but also soul-mate. Grace and Aiden have always been my source of energy and motivation. I have to thank my Mom for her great support in the most difficult time in my life. There are no words to say how much I love and cherish you all.
viii
VITA
June 15, 1976 ...... Born - Haining, P.R.China
1995-1999 ...... B.S. - Microbiology, Wuhan University, Wuhan, P.R.China
1999-2002 ...... M.S. - Molecular Genetics, Wuhan University, Wuhan, P.R.China
2003-present ...... Graduate Research Associate, The Department of Veterinary Biosciences The Ohio State University Columbus, Ohio
PUBLICATIONS
1. Qian, S., Zhong, X., Yu, L., Ding, B. and Boris-Lawrie. K. HIV-1 Tat RNA silencing suppressor activity is conserved across kingdoms and counteracts translational repression of HIV-1. Proceedings of the National Academy of Sciences, USA. 2009 106(2): 605-10
2. Zhong, X., Leontis, N., Qian, S., Itaya, A., Qi, Y. and Boris-Lawrie, K., Ding, B. Tertiary Structural and Functional Analyses of Loop E/Sarcin-Ricin Motif in Viroid RNA Reveal Its Essential Role in RNA-Templated RNA Replication by the Nuclear Transcription Machinery. Jouranl of Virology. 2006 80(17):8566-81
3. Hartman, T. RФ., Qian, SФ., Bolinger, C., Fernandez, S., Schoenberg, D.R., and Boris-Lawrie, K. RNA helicase A stimulates translation of selected mRNAs. Nature Structure and Molecular Biology. 2006 13(6):509-16. Ф These authors contribute equally to this work Issue cover story
ix 4. Qian SM, Yu QX. Explore on the advanced method of G-banding of Rana plancyt. Yi Chuan 2002 Sep;24(5):555-58
FIELDS OF STUDY
Major Field: Molecular, Cellular and Developmental Biology
x
TABLE OF CONTENTS
Page Abstract...... ii
Dedication...... vi
Acknowledgments...... vii
Vita...... ix
List of Tables ...... xiii
List of Figures...... xiv
Abbreviations...... xvi
Chapters:
1. Insights into dynamic interplay between the retrovirus and host cell post-transcriptional machinary...... 1
Introduction ...... 1 1.1 Retrovirus genome and life cycle...... 2 1.1.1 Retrovirus genomic structure...... 3 1.1.2 Retrovirus life cycle...... 5 1.2 RNA helicase A is a cellular co-factor that modulates HIV-1 and other retroviruses ...... 7 1.2.1 Physiological function of RNA helicase A in cell biology...... 8 1.2.2 RNA helicase A has multiple functions in retrovirus life cycle .....11
1.3 Current study of miRNA and virus interaction ...... 13 1.3.1 miRNA biogenesis...... 14 1.3.2 Virus- encoded miRNA and function ...... 17 1.3.3 Host- encoded miRNA and function...... 18 1.3.4 Viruse- encode proteins and RNAs that suppress small RNA function...... 20 1.3.5 miRNA and HIV-1 interplay ...... 24
xi 2. RNA helicase A is necessary for translation of selected mRNAs ...... 27
Abstract...... 27 Introduction...... 28 Materials and Methods...... 30 Results...... 34 Discussion...... 52
3. HIV-1 Tat RNA silencing suppressor activity is conserved across kingdoms and counteracts translational repression of HIV-1...... 59
Abstract...... 59 Introduction...... 60 Materials and Methods...... 62 Results...... 66 Discussion...... 81
4. Interplay of HIV-1 accessory genes and host microRNAs activity upregulates viral RNA expression ...... 82
Abstract...... 82 Introduction...... 84 Materials and Methods...... 87 Results...... 91 Discussion...... 99
5. Different host microRNAs are expressed in lymphocytes infected with HIV-1 or HIV-1 deficient in Tat RNA silencing suppressor activity...... 135
Introduction...... 135 Materials and Methods...... 136 Results and discussion ...... 137
6. Perspectives...... 168
Bibliography ...... 177
xii
LIST OF TABLES
Table Page
2.1. RHA downregulation eliminates PCE activity ...... 58
4.1. Comparison of intensities of 906 miRNA probe signals in different infections...... 113
4.2. Three categories of miRNA expression pattern are observed in microarray data from CEMx174 cells infected with either HIV-1 or vpr/vif-deficient HIV-1 (∆VV) ...... 114
4.3. Realtime PCR of 6 precursor miRNAs in HIV-1 infected or mock treated CEMx174 cells identified similar trends expression level ...... 133
4.4. Comparison of miRNA cluster members’ expression levels in HIV-1 infection compared to ∆VV infection...... 134
5.1. Comparison of intensities of 906 miRNA probe signals in different infections...... 149
5.2. MiRNA expression pattern observed in microarray data from CEMx174 cells infected with either HIV-1 or HIV-1 Tat RSS mutant (RSS)...... 150
5.3. Comparison of miRNA cluster members’ expression levels in HIV-1 infection compared to RSS infection ...... 167
xiii
LIST OF FIGURES
Figure Page
1.1 Retroviruses genome structures ...... 4
1.2. Summary of retroviral life cycle...... 6
1.3. MiRNA biogenesis and function ...... 16
1.4 The interaction of viral RNA silencing suppressors (RSS) with the small RNA pathway...... 23
2.1 RNA helicase A is a PCE binding protein...... 35
2.2. RT-PCR detects selected RNAs that co-immunoprecipitate with RNA helicase A...... 38
2.3. RNA helicase A downregulation eliminates PCE activity ...... 41
2.4. Overexpression of RNA helicase A increases PCE activity...... 43
2.5. RNA helicase A is necessary for efficient translation of PCEgag RNA ...... 45
2.6. RHA is necessary for efficient translation of junD RNA ...... 47
2.7. RNA helicase A immunoprecipitates with junD mRNA and PCEgag in the nucleus and cytoplasm ...... 51
2.8. Model for RNA helicase A translation stimulation of PCE RNA ...... 55
3.1. Tat exhibits RSS activity in plant cells that is not attributable to inhibited processing of long dsRNA...... 67
3.2. Tat suppresses miR30 function but does not block miR30 processing in human cells ...... 70
xiv 3.3. Down-regulation of Dicer enhances the production of the HIV-1 structural protein in human cells...... 74
3.4. Expression of P19 enhanced virion production from HIV-1 and HIV-1/RSS ...... 77
3.5. Tat is the viral RSS and the plant viral RSS P19 can replace Tat RSS activity...... 79
4.1. HIV-1 accessory proteins Vpr and Vif are necessary for HIV-1-induced suppression of cellular translation ...... 102
4.2. Kinetics of gag RNA translation efficiency in wild-type HIV-1 and ∆VifVprX infected cells ...... 104
4.3. Kinetics of gag RNA translation efficiency in wild-type HIV-1 and VprX infected cells ...... 106
4.4. Procedures and main steps of miRNA expression profiling...... 107
4.5. Box plots of signal intensity range of 906 miRNA probes...... 108
4.6. Scatterplot analysis of the changes in miRNA probe expression in human CEMx174 lymphocytes infected with HIV-1, vif/vpr-deficient HIV-1 (∆VV), or mock infected ...... 109
4.7. PCAF protein expression is upregulated by HIV-1 but not vif/vpr-deficient HIV-1 ...... 111
5.1. HIV-1 proviruses used for infections...... 142
5.2. Loss function mutation of Tat RSS does not affect HIV-1 Gag stability ...... 143
5.3. HIV-1 gag mRNA was efficiently translated in heavy polysome and puromycin treatment disrupt gag mRNA polysome localization ...... 144
5.4. Plant virus RSS activity regulates HIV-1 gag mRNA profile in high molecular weight fraction ...... 145
5.5. Box plots of signal intensity range of 906 miRNA probes...... 146
5.6. Scatterplot analysis of the changes in miRNA probe expression after infection of human CEMx174 lymphocytes infected with HIV-1, HIV-1/RSS viruses, or mock infection ...... 147
xv
ABBREVIATIONS
A254 Absorbance at 254nm wavelength
Ago2 Argonaute2
ALV Avian leucosis virus
BSA Bovine serum albumin
CaCl2 Calcium chloride
CaPO4 Calcium phosphate
CBP CREB-binding protein
CD4 Cluster of differentiation 4 cDNA Complemantary deoxyribonucleic acid
CHX Cyclohexamide
CMV Cytomegalovirus
CMV-IE Cytomegalovirus immediate early co-IP Co-immunopreciptation
CP Coat protein cpm Counts per minute
CREB cAMP-responsive element binding protein
CRM-1 Chromosome region maintenance gene 1
CTD Carboxy-terminal domain
xvi CTE Constitutive transport element
CTV Citrus tristeza virus
DEAD Asp–Glu–Ala–Asp
DEPC Diethylpyrocarbonate
DMEM Dulbecco's Modified Eagle Medium dsRBD Double strand RNA binding domain
DTT Dithiothreitol
EBV Epstein Barr Virus
EDTA Ethylenediamine tetraacetic acid
EGTA Ethylene glycol tetraacetic acid
ELISA Enzyme-Linked Immunosorbent Assay
EMCV Encephalomyocarditis virus
Env Envelope protein
Exp5 Exportin 5
FACS Fluorescence-activated cell-sorting
FHV Flock house virus
FITC Fluorescein isothiocyanate gapdh Glyceraldehyde-3-phosphate dehydrogenase
GFP Green flourescent protein hCMV Human cytomegalovirus
HCV Hepatitis C virus
HDAC1 Histone deacetylase enzyme
xvii HeLa Henrietta Lacks
HEPES 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid
HIV-1 Human Immunodeficiency Virus type 1 hnRNP Heterogeneous nuclear ribonucleoprotein
HTLV Human T-cell lymphotropic virus
IP Immunoprecipitation
IRES Internal ribosome entry site
KSHV Kaposi's sarcoma-associated herpesvirus lacZ Beta galactosidase
LNA Antisense locked nucleic acid
LTR Long terminal repeat
Luc Luciferase miRNA MicroRNA
MLV Murine Leukemia Virus
MPMV Mason-Pfizer monkey virus mRNA Messenger RNA
MTAD Minimal transactivation domain
NoV Nodamura virus
NP-40 Nonidet P40
NTD Nuclear transport domain
ORF Open reading frame
P19 Tomato bushy stunt virus protein 19
xviii PAGE Polyacrylamide gel electrophoresis
PBMC Peripheral Blood Mononuclear Cell
PBS Phosphate buffered saline
PBS Primer binding site
PCAF Protein of CREBBP-associated factor
PCE Posttranscriptional control element
PCR Polymerase chain reaction
PFV Primate foamy virus
PI Propidium iodide
PI Phosphorimager units
PMSF Phenylmethanesulphonylfluoride
Pol Polymerase
PPT Polypurine tract
PRE Post-transciptional regulatory element pri-miRNA Primary miRNA
P-TEFb Positive transcription elongation factor b
Puro Puromycin
REV-A Reticuloendotheliosis virus A
RHA RNA helicase A
RIP Radioimmunoprecipitation
RISC RNA-induced silencing complex
RLU Relative light units
xix RNP Ribonucleoprotein
RPMI Roswell Park Memorial Institute medium
RRE Rev-responsive element
RSS RNA silencing suppressor
RSV Rous sarcoma virus
RT Reverse transciption /transcriptase
RT-PCR Reverse transcriptase-polymerase chain reaction
SDS Sodium dodecyl sulphate shRNA Short hairpin RNA
SIV Simian Immunodeficiency Virus siRNA Small interference RNA
SMN Survival motor neuron protein
SNV Spleen necrosis virus snRNP Small nuclear ribonucleoproteins ssRNA Single-strand RNA
SV40 Simian vacuolating virus 40
TAR Trans-activation response RNA
Tat Transactivator of transcription
TBSV Tomato bushy stunt virus
TCA Trichloroacetic acid
TRBP TAR RNA binding protein
VsRNA Viral encoded small RNA
xx
CHAPTER 1
INSIGHTS INTO THE DYNAMIC INTERPLAY BETWEEN THE RETROVIRUS AND HOST CELL POST-TRANSCRIPTIONAL MACHINERY
Introduction
A virus is an infectious agent that is unable to grow or reproduce outside of its host cell. The genome of the most complicated virus includes about 200 open reading frames
(1;2) while the most complicated retrovirus encodes fewer than 50 transcripts. Lacking
genes needed for their own metabolism, viruses utilize the host machinery to replicate.
The issue of how viruses co-opt cellular machinery to ensure viral gene expression is a
major focus in the field of virology.
Recently, an RNA element termed the post-transcriptional element (PCE) was found
to mediate the cross-talk between retroviruses and the host cell to facilitate viral protein
synthesis (3;4). The 5’ untranslated region (UTR) of retroviruses, including HIV-1, is the
most conserved region and contains highly structured RNA elements such as the
transactivation response element (TAR), the primer binding site (PBS), and the packaging
signal (ψ) (5). The packaging signal and other structural elements in the 5’UTR are
considered road blocks that inhibit efficient ribosome scanning and reduce the efficiency
of retroviral RNA translation (6;7). A recent study has identified one member of the
DExD/H box superfamily, RNA helicase A (also called RHA and Dhx9) that specifically
binds to the spleen necrosis virus (SNV) 5’ UTR to facilitate translation. The RNA element
1 is present in the RU5 region of 5’ UTR and is responsive to RHA is named the
post-transcriptional control element (PCE). The PCE has been identified in seven
additional retroviruses including avian reticuloendotheliosis virus A (REV-A) and human
T-cell lymphotropic virus type 1 (HTLV-1) (8). More recent data suggests that the HIV-1
5’ UTR also has PCE activity (Bolinger C and Boris-Lawrie K, unpublished observations).
In Chapter Two of this dissertation, our work identified a cellular mRNA, junD, as the first cellular gene described that contains a PCE (9). Hernandez et al. characterized the PCE in a group of cellular genes using genome wide microarray analysis and observed primary motifs sequence were highly conserved in cellular but not retroviral PCEs (Hernandez JM and Boris-Lawrie K, unpublished observations).
Another example of virus interaction with host cell post-transcriptional machinery was shown recently with small RNA pathway (including small interfering RNA and microRNA). A growing number of studies have reported that the small RNA pathway plays a role in retroviruses replication (10-15). Although this issue has been controversial, miRNA has drawn attention in many retroviral studies. Currently, miRNA is postulated to be a therapeutic target for anti-retroviral treatment.
1.1 Retrovirus genome and life cycle
Retroviruses comprise a large and diverse group of enveloped RNA virus. The hallmark of a retrovirus is replication via a DNA intermediate. Retroviruses encode their own reverse transcriptase to perform reverse transcription of their genome from RNA into
DNA, which then is integrated into the host genome by the viral integrase. The provirus
2 then replicates as a part of the cellular DNA (16). human T-cell lymphotropic virus type 1
(HTLV-1) was the first pathogenic human retrovirus that discovered in 1981 (17), and then the human immunodeficiency virus HIV-1 in 1983 (18). Although human retroviruses have acquired world-wide attention, neither a protective vaccine nor curative therapy is currently available against retrovirus infection (16) and this presents a great challenge for retrovirologists and society.
1.1.1 Retrovirus genomic structure
The retroviral virion RNA is a 7-to-12 kb, linear, single-stranded, diploid, non-segmented, and positive polarity molecule (16). Retroviruses can be divided into two categories, complex and simple, based on their genetic structure makeup. All retroviruses contain a gag gene that encodes the internal virion proteins that form the matrix, the capsid and the nucleoprotein structures; a pro gene for protease; a pol gene for reverse transcriptase and integrase; and an env gene for viral envelope protein. In addition, the complex retroviruses (Betaretrovirus, Deltaretrovirus, Spumaretrovirus, Lentivirus), encode additional regulatory and accessory proteins. The DNA provirus created through reverse transcription is flanked on each end by a long terminal repeat (LTR) that is divided into three sections, U3, R, and U5 (Figure 1.1). The 5’ U3 region contains the promoter and enhancer sequences used to generate viral transcripts. The R region is repeated at each end of the viral RNA. The U5 region is unique to the 5’ end of the RNA, and the U3 region is unique to the 3’ end of the RNA. The genome structure of a selected simple retrovirus, avian leucosis virus (ALV), and a complex retrovirus, human immunodeficiency virus 1
(HIV-1), are depicted in Figure 1.1.
3
A
ALV 5’ CAP AAA(n) 3’ R U5 U3 R gag pro env pol
B HIV 5’ CAP AAA(n) 3’ R U5 U3 R gag vif env pro pol vpr nef tat rev
vpu
Figure 1.1. A). Simple retrovirus genome. The genetic map of avian leukosis virus contains the coding regions gag, pro, pol and env (yellow boxes). Both UTRs are indicated, RU5 and U3R. R, repeated RNA sequences (black boxes); U3, unique to the 3’ end of the RNA; U5, unique to the 5’ end of the RNA (gray boxes). B) Complex retrovirus genome. Human immunodeficiency virus contains the structural and enzymatic genes gag, pol and env as well as accessory genes vpr, vif, vpu, tat, rev, and nef (white boxes) (adapted from(16)).
4 1.1.2 Retrovirus life cycle
The retrovirus replication cycle follows the general pattern of enveloped virus
infections with some highly unusual features (19-21). The hallmark characteristic of
retroviruses is the process of reverse transcription, during which the viral RNA genome is
copied into a double-stranded DNA (dsDNA) form, which integrates into the host cellular
DNA as the provirus. A summary of the retroviral replication cycle is shown in Figure 1.2.
In brief, after interaction with a specific host cell membrane protein or a group of proteins,
the retroviral envelope fuses directly with the plasma membrane (step 1). This
protein-protein interaction triggers the fusion of viral envelope with the cell membrane.
Following fusion, the nucleocapsid enters the cytoplasm of the cell. After penetration into the host cell, viral reverse transcriptase copies the single-stranded RNA (ssRNA) genome of the virus into a dsDNA copy (step 2). The viral DNA then is transported into the nucleus and integrated into the host-cell chromosomal DNA (step 3). The integrated viral DNA, referred to as a provirus, then is transcribed into mRNAs (pink) and virion precursor RNA molecules (dark red) by host cell RNA polymerase. The host cell machinery translates the viral mRNAs into glycoproteins, nucleocapsid proteins and enzymatic proteins (step 4).
The latter assembles with genomic RNA to form progeny nucleocapsids, which interact with membrane-bound viral glycoproteins. Finally the host cell membrane buds out and progeny virions are pinched off (step 5).
5
Fusion Host – cell Budding chromosomal DNA 5 1
2 Reverse Transcription 4 transcription
3
Integration Provirus
Figure 1.2. Summary of the retrovirus life cycle. Retroviruses enter the host cell through the attachment of the viral surface glycoproteins to specific cellular plasma membrane receptors (step 1). After fusion, the viral core enters the cytoplasm and reverse transcription takes place (step 2). The newly synthesized double-stranded DNA enters the nucleus and integrates into the cellular DNA (step 3). After integration, the viral RNA is transcribed by cellular RNA polymerase II (step 4); the virus utilizes cellular export and translation machinery. Both spliced and unspliced viral RNAs are exported to the cytoplasm and undergo translation. The viral proteins assemble into virions and the unspliced viral genomic RNA is packaged into immature virions. After budding from the cell, progeny virions undergo proteolytic maturation and are ready to infect a new target cell (step 5). (Adapted from(22))
6 1.2 RNA helicase A is a cellular co-factor that modulates expression of HIV-1 and other retroviruses
RNA helicases of the DEAD-box and related families appear to be key components of all living organisms (23). The DEAD-box proteins are associated with nearly all processes involving RNA, from transcription to RNA decay (24). DEAD-box proteins have been identified in most organisms where they work as RNA/DNA helicases or
RNPases to remodel the interactions of RNA and proteins. The name of the family is derived from the amino-acid sequence D-E-A-D (Asp–Glu–Ala–Asp) of its Walker helicase motif. The DEAD-box motif has been found in more than 500 proteins. The classification of these proteins into three superfamilies and two families (named SF1 to
SF5) is based on the occurrence and characteristics of conserved motifs in the sequence
(24). The DEAD-box and the related DEAH, DExH and DExD families, which are commonly referred to as the DExD/H helicase family, are members of SF2 (24).
RNA helicase A (RHA, also known as Dhx9 and nuclear DNA helicase II) is a highly studied DExH protein suggested to be involved in almost all aspects of the life cycle of cellular and viral RNAs. RHA initially was isolated from human cells (25) and the RHA gene is mapped to chromosome 1q25 and its pseudo gene is located on chromosome 13q22
(25;26). RHA contains three functionally distinct conserved domains: two N-terminal double-stranded RNA binding domains (dsRBD), a central Walker helicase motif common to DEAD/DExH box family proteins, and a C-terminal arginine-glycine-rich domain.
7 1.2.1 Physiological function of RNA helicase A in cell biology
Transcription and RNA processing The suggestion that RHA is involved in the
regulation of transcription comes from the physiological role of the Drosophila RNA
helicase maleless (MLE) protein in X-chromosome dosage compensation (27). MLE is a
Drosophila RHA orthologue and is essential for maintaining the hypertranscriptional activity of the single male X-chromosome. The male can produce the same transcriptional level from its single X-chromosome as the female can from two X-chromosomes (27), thus
X-linked gene expression in males (XY) is equivalent to that in females (XX). However, the MLE-X chromosome association is abolished when treated with RNase, suggesting
DNA binding of MLE-X is RNA-dependent (28).
Nakajima et al. (29) demonstrated that RHA plays an active role in transcription in human 293T cells. Biochemical evidence showed that RHA acts as a bridging factor between the CREB-binding protein (CBP) and RNA polymerase II (Pol II), thus cooperating with CBP to activate transcription (29). The N-terminal region of RHA, which contains the double strand RNA binding domain (dsRBD), was shown to be responsible for the interaction with CBP/p300. The region overlapping the N-terminal domain and the helicase domain also was shown to interact with Pol II (29). RHA contains a minimal transactivation domain (MTAD), which is enriched in aromatic amino acids and is sufficient to interact with RNA Pol II (30). Interestingly, RNA helicase-defective mutants showed a decreased ability to co-activate CBP-dependent transcription, raising the possibility that the function of RHA in transcription activation is more than just acting as a bridging factor. CPB/p300 binds to the cAMP-responsive element binding protein (CREB)
8 by recognizing its phosphorylated serine 133. RHA is considered to stimulate transcription
via the transmission of the CREB/CBP-specific binding signal to RNA polymerase II and
this cause further phosphorylating the PolII C-terminal domain by cyclin-dependent kinase
(30).
RHA has been found to fulfill a similar bridging role between the breast
cancer-specific tumor suppressor BRCA1 and the Pol II holoenzyme through interaction
with the transcriptionally active C-terminal domain of BRCA1 (31). Interestingly, the
interacting region for BRCA1 is separate from that for CBP binding, implying that RHA may interact specifically with other factors involved in transcription from specific
promoters in response to particular signals.
RHA also was found to interact with the p65 subunit of NF-κB to enhance
NF-κB-dependent transcription (32). In addition, RHA has been shown to preferentially bind the promoter sequence of the p16INK4a tumor suppressor gene in cells with
transcriptionally active p16INK4a; this interaction is sequence-specific (33).
Pellizzoni et al. reported that RHA is associated with the survival motor neuron protein
(SMN) and postulated a role in RNA processing (34). SMN is a component of small nuclear ribonucleoproteins (snRNP). The association of RHA with SMN suggests the
possible involvement of RHA in the assembly of spliceosomes (34). Bratt & Ohman
reported that RHA strongly associates with the RNA editing enzyme ADAR, suggesting
RHA might play a role in mRNA splicing and editing (35). Using inosine-containing RNA
(ADAR-edited RNA) chromatography, Wang et al. identified a vigilin nuclear complex that likely is involved in heterochromatin formation through an RNA-mediated pathway.
Since RHA is present in this complex (36), it suggests that RHA is involved in RNA
9 editing and heterochromatin formation. Taken together, RHA has been shown to function
in several different cellular processes, including transcription, RNA processing and
editing, through its interaction with different components of the machinery involved in
these processes.
Small RNA pathway The miRNA pathway is a conserved gene silencing pathway that
depends on the interaction between small guide RNAs (siRNA or miRNA) and target mRNAs through proteins assembled in the RNA-induced silencing complex (RISC). The
known human RISC components are Argonaute2 (Ago-2), Dicer and TAR RNA binding
protein (TRBP) (37). To identify other RISC components in human cells, Robb and Rana
(38) transfected human HeLa cells with biotinylated GFP siRNA and purified the cell
lysates with streptavidin. Using this affinity-purification strategy, siRNA programmed
RISC was isolated. Interestingly, RHA was reported as a human RISC-associated factor in
this assay by mass spectrometry (38). RHA interacts with siRNA, Ago-2, TRBP, and Dicer
in co-immunopreciptation (co-IP) assays and functions in the small RNA pathway (38). In
RHA-depleted cells, RNAi was reduced approximately three-fold as a consequence of
decreased intracellular concentration of active RISC assembled with the guide-strand RNA
and Ago-2. In spite of the lack of detailed mechanism about how RHA functions in RISC,
it is hypothesized that RHA helicase activity is used to unwind the duplex of small RNA
and its target that allows Ago-2 binding for further function. Taken together, these results
demonstrate that RHA is important for RISC assembly and RNAi activity.
10 1.2.2 RNA helicase A has multiple functions in retrovirus life cycle
Nuclear export RHA has been reported to bind specifically to a region of retroviral RNA named the constitutive transport element (CTE) (39;40). CTE is a cis-acting element first identified in Mason-Pfizer monkey virus (MPMV). MPMV uses the host Tap/p15 RNA transport receptor to promote RNA export of the CTE-containing viral unspliced and spliced RNAs. Tang et al. reported that RHA is associated with CTE and facilitates CTE function (40). However, these findings have not been reproduced by others and remain controversial (3).
RHA interacts with the Rev response element (RRE) of HIV-1, stimulating
Rev-dependent gene expression (41). Unspliced and partially spliced viral RNAs are transcribed in the nucleus and transported into the cytoplasm for appropriate function. Rev protein binds a highly structured element (Rev responsive element; RRE) present in all unspliced and partially spliced HIV-1 transcripts (42-46). Rev is an adaptor molecule to the
CRM-1 nuclear export receptor and the RRE-Rev-CRM-1 complex specifically exports viral mRNA out of the nucleus (47). RHA binds weakly to HIV-1 RRE independently of
Rev. Overexpression of RHA, but not an RHA mutant lacking helicase activity, increased
Rev-RRE-dependent LacZ reporter gene expression and the levels of unspliced HIV-1 mRNA (47). Microinjection of anti-RHA antibodies into nuclei of primary HS68 human fibroblasts dramatically inhibited Rev-dependent gene expression in human cells.
Exogenous RHA cDNA, but not mutant RHA, rescued this inhibition (47).
It has been shown that Sam68, RHA and Tap cooperate in the nucleus to export
RRE-containing RNA. RHA binds to Sam68 and Tap both in vivo and in vitro (48).
Overexpression of Sam68 activates RRE-regulated reporter gene expression in human
11 cells. This activation was competitively inhibited by the nuclear transport domain (NTD)
of RHA and a transdominant negative mutant of Tap (48). Although this study suggested that the association between RHA, Tap and Sam68 provides an alternative export pathway for RRE mRNA in a Rev-independent pathway, this export pathway is inefficient under physiological conditions, requiring synergism from Rev for optimal viral expression (48).
Reverse transcription A recent unexpected finding revealed the possibility that RHA
may contribute to HIV-1 particle assembly and reverse transcription (49). Using proteomic
analyses, Roy et al. reported that RHA was associated with HIV-1 Gag packaged into
HIV-1 virions in an RNA-dependent manner. When RHA was down-regulated by siRNA,
HIV-1 particles were significantly less infectious and reverse transcription was inhibited as
much as six-fold as measured using realtime PCR to detect the (-)cDNA (49).
Transcription TAR is a nascent viral leader RNA transcribed from the R region of the
HIV-1 LTR that forms a unique stem-loop structure and plays an important role in HIV-1
gene expression (50;51). The function of Tat is mediated by TAR RNA and requires the
recruitment of a complex consisting of Tat and the cyclin T1 component of positive
transcription elongation factor b (P-TEFb) (52). Fujii et al. (53) reported that TAR RNA is
a preferred target of RHA double-stranded RNA binding domains (dsRBDs) and
TAR-RHA binding is thought to partially enhance HIV-1 transcription in vivo. In addition,
these authors found that wild-type RHA preferably bound to TAR RNA in vitro and in
vivo. Over-expression of wild-type RHA strongly enhanced viral mRNA synthesis
(northern blot) and virion production (six-fold) as well as HIV-1 long terminal
12 repeat-directed reporter (luciferase) gene expression. Substitution of lysine with glutamate
at residue 236 in RHA dsRBD2 (RHA K236E) reduced its affinity for TAR RNA and
impaired HIV-1 transcriptional activity as measured by northern blot (53). However, it remains unclear whether RHA provides a direct role in transcription or indirectly influences the milieu of polymerase II initiation/elongation at the LTR (2).
Translation Recent reports also have indicated a role for RHA in translation of selected
mRNAs through interaction with their 5’UTR region (3;8;54). Bolinger et al. provided
evidence that RHA interacts with divergent retroviral 5’ UTRs (including HTLV-1, SNV,
REV-A) at a cis RNA element termed the post-transcriptional control element (PCE) and
facilitates PCE-containing mRNA translation. Down-regulation of RHA results in
approximately three-fold reduction of HTLV-1 Gag production while the gag mRNA level
remained unchanged, suggesting that RHA facilitates PCE function at the
post-transcriptional level (8). Recently, Hartman et al. showed that PCE mRNA localized
at the polysome fraction; down-regulation of RHA using RHA-specific siRNA abolished
PCE mRNA polysome localization (9). In addition, RHA was shown to facilitate the
translation of a cellular PCE mRNA, junD (9).
1.3 Current study of miRNA and virus interaction
The discovery that cells encode small RNAs to regulate gene expression at a
post-transcriptional level in a sequence specific manner is a major breakthrough in biology
(37;55-57). These small RNAs can be divided into two general categories, small
interfering RNAs (siRNAs) and microRNAs (miRNAs), which share the same cellular
13 machinery to achieve a similar function (37). Recent findings of small RNA activity have
brought our understanding of post-transcriptional gene regulation to an entirely new level.
1.3.1 MiRNA biogenesis
The cellular miRNAs characterized to-date are transcribed from intergenic
regions, introns, and exons by RNA polymerase II (pol II). As shown in Figure 1.3, the
initial RNA transcript is an RNA precursor called a primary miRNA (pri-miRNA)
(55;58-60). One copy of pri-miRNA may contain a cluster of distinct miRNAs (miRNA
cluster) or only a single miRNA. The pri-miRNA ranges from 200 nucleotides to several
thousand nucleotides in length and forms highly structured stem-loop secondary structures
(61;62). This stem-loop pri-miRNA is recognized and cleaved in the nucleus by a cellular
RNase III enzyme called Drosha with its cofactor DGCR8 in vertebrates (63-65).
Cleavage produces an RNA hairpin intermediate around 70 nt, bearing a characteristic two
nt 3’overhang that is called pre-miRNA (Figure 1.3) (63). The next step in miRNA
biogenesis is the nuclear export of the pre-miRNA hairpin by a heterodimer consisting of
Exportin 5 (Exp5) and the GTP-bound form of cofactor Ran, which together recognize and bind the two-nt 3′ overhang and the adjacent stem that are characteristic of pre-miRNAs
(66;67). When the short hairpin miRNA precursor reaches the cytoplasm, another cellular
RNase III enzyme called Dicer binds to this structured RNA with cofactor TAR RNA
binding protein (TRBP) to perform a second cleavage (68;69). The cleavage product is a
two-nt 3′ overhang double-stranded RNA that is approximiately 22 bp. One strand (guide
strand, red in Fig 1.3) of this dsRNA remains bound to Dicer and is known as mature
miRNA. The other RNA strand (passenger strand, miRNA*) (blue in Fig 1.3) generally is
14 degraded. Dicer facilitates assembly of the miRNA-induced silencing complex (RISC)
(68;70;71). TRBP, originally identified as a cellular co-factor that specifically binds to the
stem-loop of HIV-1 TAR and facilitates the Tat-TAR interaction (72;73), stabilizes Dicer
and promotes the interaction between Dicer and Argonaut2 (Ago-2) to form the RISC
(68;70;71). Ago-2 is a key component of RISC in human cells (74;75). The miRNA-guided
RISC associates with the target mRNA; this association has two possible outcomes:
mRNA degradation or translation inhibition. Perfect complementarity of miRNA and
target mRNA results in target mRNA cleavage mediated by Ago-2 (76) (70;74;77;78).
However, imperfect complementarity of miRNA and target mRNA (6-8 nt seed sequence)
induces translational repression, most often when the target sequences are located in the 3’
UTR of mRNA (37;79). Most recently, miR10a was found to bind to the 5’ UTR of the
target mRNA that encodes ribosomal proteins and result in translation enhancement of
these mRNAs (80). In addition, Vasudevan et al. reported that the AU-rich elements
(AREs) located at the 5’UTR of some cellular mRNAs associate with two microRNP related proteins, Ago-2 and fragile-X mental-retardation-related protein 1 (FXR1). This interaction resulted in translation activation upon serum starvation of human cells by an unidentfied mechanism (81). Since miRNA targeting to mRNA does not require a high level of sequence specificity, one single miRNA may target up to 1000 mRNA targets (37).
It’s predicted that miRNA may evolve in every step of cellular metabolism.
15
miRNA gene Nucleus
Pri-miRNA Pre-miRNA Drosha
Cytoplasm Exportin 5
Pre-miRNA
Dicer
miRNA:miRNA* duplex
Dicer TRBP
Mature miRNA RISC
Target mRNA
Translation repression mRNA cleavage
Figure 1.3. MiRNA biogenesis and function. The pri-miRNA transcripts are transcribed by RNA pol II and processed into 70-nucleotide pre-miRNAs by Drosha inside the nucleus. Pre-miRNAs are processed into miRNA:miRNA* dsRNA by Dicer after transport to the cytoplasm by Exportin 5. Mature miRNA is assembled preferentially into the RNA-induced silencing complex (RISC), which subsequently acts on its target by translational repression or mRNA cleavage (Adapted from (82)).
16 1.3.2 Virus-encoded miRNAs and their function
For viruses, miRNAs would offer another opportunity to modulate the host cellular
environment to benefit virus replication. Unlike viral proteins that may be recognized by
the host immune system, our present knowledge suggests that miRNA may escape this host
defense. Furthermore, since miRNA regulation occurs at the mRNA level and not the
protein level, the rapid accumulation of miRNAs in infected cells provides a rapid means to post-transcriptionally modulate viral and cellular gene expression. Recent studies showed that some viruses do exploit this pathway by generating their own miRNAs (83-85). To date, 14 viruses have been identified that encode more than 100 viral miRNAs
(http://microrna.sanger.ac.uk/cgi-bin/sequences/browse.pl).
Since miRNA acts at the mRNA level, the effects caused by miRNA can be delayed
due to the existing pools of proteins that turn over in hours or days (79). Thus, a virus
undergoing rapid replication is less likely to encode miRNA because viral miRNA can
only target mRNA after viral infection (79). However, those viruses that undergo a more
protracted later phase of infection are more likely to encode viral miRNA. To date, the
majority of these viral miRNAs are encoded by herpesviruses (83), a group of DNA viruses
that cause disease in animals and humans and undergo a latency stage. Epstein-Barr virus
(EBV) encodes 23 miRNAs (83;85); Kaposi sarcoma-associated herpesvirus (KSHV)
encodes 12 miRNAs (86-88); and human cytomegalovirus (hCMV) encodes 11 miRNAs
(84;89). In addition to herpesviruses, two other DNA viruses, SV40 and human adenovirus,
are reported to encode miRNAs (90-92). Five SV40-encoded microRNAs were identified
from a 57 nt pre-miRNA that is expressed in the later stage of viral infection (miRNAs
were detected after 30 hours SV-40 infection by northern blot). These miRNAs were
17 perfectly complementary to early viral mRNAs and resulted in target mRNA cleavage (90).
Sullivan et al. introduced a mutation in the predicted pre-miRNA that disrupted its hairpin structure and observed greater early viral mRNA expression compared to wild-type virus infection. The increase of early mRNA expression resulted in increased expression of viral large and small T-antigens. Thus, by down-regulating the accumulation of unnecessary T antigen, the viral miRNAs reduced susceptibility of infected cells to recognition by CTLs and enhanced the probability of successful infection. It is clear that more virus-encoded miRNAs will be identified and investigated.
1.3.3 Host encoded miRNAs and their function in virus biology
It has been predicted that all metazoans encode miRNAs and there might be at least 1,000 copies of miRNAs in each cell (37). Differentiated human cells express distinct patterns of miRNA in various human tissues (37). Evidence suggests that cellular mRNAs are under selection of miRNAs/siRNAs by sequences complementary to miRNAs present in cells (79). Subsequently, viruses also may be subject to evolutionary pressure to avoid encoding viral RNA regions complementary to host miRNAs that are present in normal target tissues (79). It would be surprising if viral transcripts are not subjected to regulation by at least some host encoded miRNAs. Recently, Lecellier et al. showed that human miRNAs inhibit primate foamy virus 1 (PFV-1, a retrovirus) replication in human embryonic kidney 293T cells (93). Over-expression of a plant viral RNA silencing suppressor (RSS) P19 strongly enhanced PFV expression, suggesting that siRNA or miRNA plays an important role in the PFV replication cycle. Using a reporter system in which the PFV-1 subgenome sequence was fused to the 3’UTR region of GFP, Lecellier et
18 al. failed to detect any viral-encoded siRNA or miRNA. However, using a computer
program (DIANA-microT algorithm(94)), Lecellier et al. successfully predicted a cellular
microRNA, miR-32 that could bind to PFV-1 RNA. The miR-32 target is in open reading
frame (ORF) 2, shared by the Bet and EnvBet proteins of the retrovirus. MiR-32 also targets the 3' UTR of all remaining PFV-1 mRNAs. In cells that were treated with antisense locked nucleic acid (LNA) oligonucleotides to specifically block miR-32
function, enhanced expression of PFV-1 was observed (93).
Further evidence supporting the emerging notion that miRNAs modulate viral
infection comes from the study of hepatitis C virus (HCV) (95). Sarnow and colleagues
(95) reported that the liver-specific miRNA miR-122 had a strong positive effect on HCV replication in Huh7 liver cells. HCV contains a miR-122 target in its 5’ UTR. Sequestration of miR-122 by miR-122-specific 2’-O-methyl antisense oligonucleotides reduced HCV
RNA and protein abundance in Huh7 cells (95). The mechanism underlying this effect is
not clear, however, the direct interaction between miR-122 and its 5′ UTR target is
required for this enhancing effect. Mutations of the target sequence abolished translation
enhancement. This unexpected result emphasizes the fact that our knowledge of miRNA
function is far from complete. Recently, RNA helicase A was reported to facilitate mRNA
translation (9) and to be a component of RISC (38), raising the possibility that RHA may
play a role in this unique miRNA-directed translation enhancement mechanism. One
possible mechanism is that RHA serves as a bridge protein and binds to poly A binding
protein (PABP), which in turn binds the 3’ tail of mRNA (Jing W, Boris-Lawrie K,
unpublished observations). Thus, the mRNA 5’ end and 3’ end are connected via this
protein-protein interaction thereby facilitating ribosome reinitiation.
19 1.3.4 Viruses encode proteins and RNAs that suppress the host small RNA pathway
As discussed above, virus or host encoded miRNAs can modulate virus infection.
Although HCV replication is up-regulated by miR122, miRNAs generally inhibit viral replication. To break through this host cell defense barrier, some viruses encode RNA binding proteins that can suppress the cellular antiviral defense mediated by miRNAs. In fact, a significant number of viruses have been identified that encode viral proteins to suppress RNA silencing pathway in plants (96). Well-known examples are P1/HC-Pro encoded by potyviruses, 2b protein encoded by cucumoviruses, P19 of tombusviruses, P25 of potato virus X, coat protein (CP) of carmoviruses and P20, P23 and CP of citrus tristeza virus. Animal viruses also are reported to encode viral RSS protein and RNA, such as B2 of flock house virus (FHV) and nodamura virus (NoV), vaccinia E3L, NS1 of human influenza A, B, and C viruses, NSs of La Crosse virus, σ3 of reovirus, Tat of HIV-1, Tas of
PFV-1 (97;98),VP35 of Ebola virus and VA1 RNA of adenovirus (99).
P19 protein encoded by tomato bushy stunt virus (TBSV) is one of the most well studied RSS (96) and recent progress on the structural and functional properties of P19
makes it one of the best characterized viral silencing suppressor proteins. Notably, P19
was the first protein demonstrated to bind miRNAs directly, functioning presumably to
prevent the miRNAs from entering the RISC (100). Two independent studies have
resolved the P19-miRNA complex crystal structure (101;102). This elegant data provided
a structural explanation for the dimerization of P19 that is essential for binding siRNA at
the double-stranded RNA binding domain. P19 protein acts as a molecular caliper to
specifically select siRNAs; this activity is based on the length of the duplex region of the
20 RNA but not the sequence (Figure 1.4). HC-pro is suggested to suppress RNA interference by affecting the assembly and/or targeting of the RISC (103).
Recently, Ebola virus protein VP35 has been reported to be an RSS and its dsRNA-binding domain is required for RSS activity (Figure 1.4) (99). In addition, VP35 can complement HIV-1 Tat RSS activity in a Tat-minus HIV-1 virus.
An alternative strategy to block the RNAi pathway is used by human adenovirus.
The 39-kb dsDNA genome of adenovirus expresses early and late transcripts. Among the late transcripts is the very abundant and highly structured virus-associated (VA) RNA.
VA1 RNA blocks the host small RNA pathway by competing for the usage of exportin 5.
In microRNA biogenesis pathway, Exportin 5 exports pre-miRNA from the nucleus to the cytoplasm. Thus, large amounts of VA1 expression hijack exportin 5 and result in less mature miRNAs (104). Andersson et al. reported that VA RNAs were the substrates of
Dicer and incorporated into RISC and thus saturate Dicer and RISC activity, thus inhibit the small RNA pathway (91) (Figure 1.4).
HIV-1 Tat is an essential viral protein that contains both a trans-activating domain and an RNA-binding domain; it also has been reported to possess RSS activity (105). Tat is a novel transcriptional transactivator that specifically recognizes nascent HIV-1 transcripts at the 59 nt double stranded transactivation responsive element (TAR). Recruitment of the cellular co-factors cyclin T1 and the serine kinase CDK9 induces phosphorylation of the carboxyl-terminal domain (CTD) of RNA polymerase II, which is necessary for transcriptional elongation and robustly activates productive transcription of the viral genome. There are several suggestions about how Tat performs its RSS function. One explanation is that Tat sequestrates the TAR RNA binding protein, TRBP, which is an
21 essential component in RISC (68;69;106;107). Christensen et al. suggested that TRBP
contributes mainly to the enhancement of virus production by acting as a
Dicer-Tat-TAR-TRBP complex (108). Replacement of HIV-1 lysine with alanine at
position 51 (K51A) in the Tat dsRNA-binding domain abolished the RNAi suppression
activity of Tat without any effect on its transcriptional activity (105). By contrast, the
K41A mutation that is located in the transactivating domain retained RSS function (105).
These data suggested that the dsRNA binding domain is required for Tat RSS function. To
date, it is known that both NS1 and B2 bind siRNAs in addition to long dsRNA (109).
Whether HIV-1 Tat also could bind to siRNA and/or dsRNA is unknown. Potential roles
for RSS activity in HIV-1 infection are: 1) Perturbation of the cellular miRNA profile to
affect beneficial changes in host gene expression. This activity would reduce restriction
factors and/or up-regulate receptor and other necessary cellular proteins. 2) Protection of
the virus against attack by cellular miRNA. The interplay between host miRNA biology and virus RSS activity is expected to have a significant effect on the outcome of acute viral infection. Understanding this interplay will provide important insights into cell biology and virus pathogenesis. Figure 1.4 summarizes the interaction between the viral RSSs that
are encoded by human pathogenic viruses.
22
Pri-miRNA
Tat? NS1? Drosha ADARs
Pre-miRNA
VA RNAs Exportin 5 VP35 NS1 Pre-miRNA
VA RNAs Dicer Tat TAR miRNA:miRNA* duplex Dicer TRBP
VP35 Tat Mature miRNA NS1
Target mRNA
Translation repression mRNA cleavage
Figure. 1.4. The interaction of viral RNA silencing suppressors (RSS) with the small RNA pathway. The mammalian small RNA pathway is shown in the blue boxes from pri- to pre- and mature. The viral RSS functions are shown in the red boxes. The HIV-1 Tat protein has been reported to suppress RNAi by inhibiting Dicer activity and is postulated to bind mature miRNA. The Ebola virus VP35 and influenza A virus NS1 proteins potentially block RNAi by binding pre-miRNA/long dsRNA or siRNA/miRNA duplexes. The RSS Tat and NS1 proteins can potentially affect RNAi by binding long dsRNA, pri- and pre-miRNAs in the nucleus. The HIV-1 TAR hairpin is capable of saturating TRBP, thereby suppressing RNAi. The RNA editing enzymes ADARs (orange) may alter the specificity of pri- and pre-miRNAs (Adapted from (109)).
23 1.3.5 MiRNA and HIV-1 interplay
Host cell-encoded miRNAs have been shown to play critical roles in HIV-1 latency in two major studies (12;110). Down-regulation of Dicer and/or Drosha enhanced HIV-1 replication in chronically infected human PBMC and Jurkat T-cells (12). Microarray and northern blotting analyses showed that expression of the miR17/92 cluster was reduced more than 50% at 21 days after HIV-1 infection in Jurkat cells. Interestingly, the cluster members miR-17-5p and miR-20a target PCAF and reduce HIV-1 replication. These results leave an open issue of whether the alterations in the host miRNA expression profile due to HIV-1 are attributable to RSS activity in Tat or virus-induced changes in host cell gene expression. Recently, Huang et al. (110) reported that over-expression of cellular miRNAs miR-28, -125b, -150, -223, and -382, which are targeted to the 3’ end of HIV-1
RNA, silenced almost all viral mRNAs in quiescent T4 lymphocytes. Neutralizing these cellular miRNAs by transfecting specific antagonists into T-cells from patients with HIV-1 under highly active antiretroviral therapy led to increased in vitro efficiency of virus production by 10-fold. These observations strongly suggest a role for cellular miRNAs in
HIV-1 latency. However, whether or not host-encoded miRNAs are important for HIV-1 infection at the acute stage still remains unknown. Answering this question is important to better understand disease onset, and may facilitate the discovery of therapeutic targets.
Although host miRNAs clearly play a role in HIV-1 replication, a controversial issue is whether or not HIV-1 encodes viral small RNAs. Studies by two groups failed to identify viral-encoded small RNAs (vsRNAs) in HIV-1-infected cells (14;84). Using a cDNA clone and sequencing method, Lin et al. failed to detect HIV-1-encoded small RNA in acutely infected ACH-2 cells (14). However, a virus-encoded small RNA targeted to the
24 LTR that is able to inhibit LTR-driven transcription was reported by another group
(111;112). Bennasser et al. showed that a stem loop HIV-1 RNA can be processed by
Dicer into a vsRNA that is able to target env mRNA (105). Transfection of the
corresponding short hairpin RNA (shRNA) inhibited over 80% of env mRNA production
(105). This result was challenged later by Lin et al. (14). Recently, Klase et al. (113) and
Ouellet et al. (114) have shown that TAR can be processed by Dicer to produce viral small
RNAs that down-regulate viral gene expression. Beside these experimental approaches,
computational analyses have been used to predict HIV-1-encoded small RNAs and their
cellular targets. Using a consensus scoring approach, Hariharan et al. revealed that human
miRNAs exhibited sufficient complementary to selected HIV-1 sequences to render their
targets for RNAi: miR-29a and 29b exhibit complementarity to nef sequences, miR-149
exhibits complementarity to vpr sequence, miR-378 exhibits complementarity to env
sequences and miR-324-5p exhibits complementarity to vif sequence (115). In silico
analysis by Bennasser et al. (116) predicted that HIV-1 encodes five candidate
pre-miRNAs to target the 3’ UTR of a population of cellular transcripts, suggesting Tat
RSS activity might be miRNA sequence-specific or miRNA biogenesis-specific.
HIV-1-encoded miRNA could be a potential mechanism to improve viral fitness or
replication efficiency (116).
The infectious virion of all retroviruses contains two copies of the highly structured
RNA genome; the structural features of the RNA pose the hypothesis that retroviruses
encode viral miRNA. Using nef-specific probes, Omoto et al. (111) detected viral miRNA expression in HIV-1-infected MT-4 T-cells. Omoto et al. cloned and sequenced these miRNAs and revealed that a virus-encoded miRNA (miR-N367) derived from HIV-1 nef
25 suppressed both Nef function and HIV-1 virulence in MT-4 T cells and in a mouse model.
Omoto et al. also suggested that miR-N367 reduced HIV-1 LTR promoter activity and down-regulated HIV-1 replication by both transcriptional and post-transcriptional mechanisms (111;112). Although Lin et al. failed clone HIV-1 microRNA from
HIV-1-infected ACH-2 cells and challenged that HIV-1 encodes small RNA (14), the collection of evidence from other groups indicates that further study of the HIV-1 interaction with the small RNA pathway is warranted.
26
CHAPTER 2
RNA HELICASE A IS NECESSARY FOR TRANSLATION
OF SELECTED MRNAS
ABSTRACT
RNA helicase A (RHA) is a highly conserved DEAD box protein that activates transcription, modulates RNA splicing, and binds the nuclear pore complex. The lifecycle of a typical cellular mRNA involves RNA processing and efficient translation initiation by ribosome scanning of a relatively short and unstructured 5’ untranslated region. The precursor RNA of retroviruses and selected cellular genes harbor a complex 5’ untranslated region and utilize yet-to-identified host post-transcriptional effector to stimulate efficient translation. Here RHA is identified to recognize a structured 5’ terminal post-transcriptional control element (PCE) of a retrovirus and the junD growth control gene. RHA interacts with PCE RNA in the nucleus and cytoplasm, facilitates polyribosome association and is necessary for its efficient translation. Our results reveal a previously unidentified role for RHA in translation and implicate RHA as an integrative effector of gene expression involved in the continuum of gene expression from transcription to translation.
27 INTRODUCTION
Translational control regulates expression of 30% of the eukaryotic proteome and plays a pivotal role in effecting rapid response to changes in cellular growth conditions
(117). Initiation is the rate-limiting step in translation and the prevailing model prescribes efficiently translated RNA to be monocistronic, contain a m7G(5’)ppp(5’)N cap structure at the 5’ terminus, and have a 5’ untranslated region (UTR) that is less than 100 nt in length and is relatively unstructured (118;119). Pre-mRNA splicing exerts a stimulatory effect on translation, and recent findings imply that the deposition of an exon junction complex
(EJC) in the nucleus satisfies an RNA surveillance checkpoint that is necessary for efficient translation in the cytoplasm (120-122). Naturally nonspliced mRNA templates that contain a long and highly structured 5’ UTR represent exceptions to this paradigm;
these mRNAs would require alternative post-transcriptional regulatory circuits for efficient protein synthesis. Two exceptions are the pre-mRNA of retroviruses and selected
naturally intronless cellular genes, which contain a complex 5’ UTR, a m7G(5’)ppp(5’)N
cap structure and are expected to lack an EJC (123;124)
In the case of HIV-1 and other complex retroviruses, the viral regulatory protein,
Rev in conjunction with the Rev-responsive element (RRE), trans-activates efficient
post-transcriptional expression of gag from the viral pre-mRNA (125). However, genetically simpler retroviruses lack a viral post-transcriptional regulatory protein and are
reliant on a host post-transcriptional regulatory protein. Bioinformatics searches identified approximately 200 human naturally intronless genes that share features with retrovirus gag
mRNA. One example is the junD growth control gene of the AP1 family of transcription
28 factors that contains a highly structured ~200 nt 5’ UTR and initiates translation by a
cap-dependent mechanism (123). It is possible that junD and selected retroviral genes
recruit a common host post-transcriptional regulatory protein to stimulate their efficient
translation.
Recently a unique 5’ terminal orientation-dependent post-transcriptional control
element (PCE) was identified in spleen necrosis virus (SNV) and Mason-Pfizer monkey
virus (MPMV) that facilitates translation of unspliced RNA containing a complex 5’ UTR
(3;54). PCE functions in concert with yet-to-be identified host cell effector protein to
stimulate Rev/RRE-independent expression of HIV-1 unspliced gag RNA by facilitating
polyribosome association (3;4). Paradoxically, the PCE and adjacent cis-acting replication
sequences present structural barriers to ribosome scanning (7;126). Combined results of
site-directed mutagenesis and enzymatic mapping experiments demonstrated that PCE is
composed of two redundant stem-loop structures that present unpaired nucleotides for
interaction with the host cell effector protein (4). Studies with bicistronic reporter RNAs
determined that PCE does not function as an internal ribosome entry site to stimulate
cap-independent internal initiation (4). Quantitative RNA and protein analyses on deletion and point mutants determined that the elimination of Gag protein production does not
correlate with change in steady-state level, splicing efficiency, or cytoplasmic
accumulation of PCEgag RNA. Instead, loss-of-function mutations eliminate utilization of
the cytoplasmic RNA as template for Gag protein production (54;127). Results of RNA
transfection and competition studies with Rev/RRE revealed that PCE interaction with a
cellular effector in the nucleus is necessary for translational stimulation (128).
29 We hypothesized that the PCE effector is a nucleocytoplasmic shuttle protein with
RNA helicase activity that neutralizes barriers to efficient ribosome scanning. A good candidate was RNA helicase A (RHA), a member of the DEAD box family of RNA helicases (129). DEAD box proteins catalyze rearrangements of RNA-RNA and
RNA-protein complexes in virtually all steps of RNA processing and metabolism, including transcription, splicing, association of RNA with the nuclear pore complex, and export (130). Here we set out to identify and characterize PCE effector protein. Our findings reveal a new and essential role for RHA in efficient translation of selected mRNAs by recognition of features of their complex 5’ UTR.
MATERIALS AND METHODS
RNA affinity chromatography.
DNA templates for in vitro transcription were PCR products that contain T7 promoter and either wildtype PCE (pYW100) (3), or the indicated mutants (127) or antisense PCE (pTR147) (4). After transcription with 15mM biotinylated UTP or CTP
(ENZO) and 135 mM UTP with Megashortscript kit (Ambion), RNA was precipitated, resuspended in DEPC water, and applied to G25 exclusion column. Biotinylated RNA (2
µg) was incubated with 50 µl streptavidin coated beads and 120 µl binding buffer (40mM
KCl, 10 mM HEPES pH 7.6, 5 mM EDTA pH 8.0, 3 mM MgCl2, 5% glycerol, 0.5% NP40,
2 mM DTT) for 1 h at 4°C, centrifuged at 1,200 × g, and incubated with 250 µl biotin blocking solution at room temperature for 5 min. Pelleted beads were washed 3 times with
250 µl binding buffer and added to HeLa nuclear extract (600 µg) in 100 µl binding buffer,
30 1,000 µg heparin, and 50 µg tRNA, incubated for 2 h at 4°C, centrifuged and washed 4
times. Proteins were eluted in 100 µl of progressive concentrations of KCl. The 2 M elution
products were dialyzed overnight at 4°. Samples were separated by 8% SDS-PAGE and stained with Coomassie blue. Proteins in gel slices were digested with trypsin and
microsequenced at the Ohio State University Proteomics Facility.
RNA electromobility shift assays.
Probes were prepared as above but with 32P-α-UTP and MAXIscript kit (Ambion)
and 200,000 CPM was incubated with HeLa nuclear lysates, or total cell extracts of COS
cells two days post-transfection with pFL-RHA, and 5 µg heparin on ice for 30 min.
Preincubation of lysate was with competitor RNA or RHA antiserum or FLAG M2
monoclonal antibody for 10 min, followed by 6.5% nondenaturing PAGE and
PhosphorImager analysis. HeLa nuclear extract was prepared from 10 L cell pellet
purchased from National Cell Culture Center. Sucrose gradient analysis was performed as
described previously (4). Puromycin treatment (200 µg/ml) was for 30 min prior to cell
harvest. Proteins were precipitated in 20% trichloroacetic acid for 30 min on ice,
centrifuged for 20 min at 12,000 RPM at 4°C, washed with acetone 5 times, and dried in
Speedvac for 2 h. Pellets were separated by 8% SDS-PAGE and subjected to western blot.
Plasmids, transfections and protein analysis.
PCEgag reporter plasmids were described previously (3;4;127). Co-transfections
with pGL3 luciferase expression plasmid and pcDNA-FLAG-RHA were performed in triplicate with Lipofectamine (Invitrogen) as described (54). Cocktails of RHA siRNAs
31 and scrambled RHA siRNAs were provided by Dharmacon (Smartpool) that target Homo
sapiens RHA (Genebank accession number: NM_001357) and transfected with
Oligofectamine at a final concentration of 100 nM per 1 × 105 cells. Bradford assay was
used to measure 50 µg of protein for immunoblots, which were performed as previously
described (3) with antiserum including: polyclonal rabbit RHA from C.G. Lee, histone H1
and β-tubulin mouse monoclonal antibody (Abcam), β-actin rabbit polyclonal antibody
(Novus Biologicals) and FLAG M2 monoclonal antibody (Sigma). Metabolic labeling,
TCA precipitation assays and IP were performed as described previously. Briefly, COS
cells were plated at 2x105 per 35 mm well and transfected with siRNA in two 24 h
intervals. After transfection with pYW100 and incubation for 24 h, the cells were
incubated with 10 µCi/ml 35S-cysteine/methionine or 3H-uridine for the indicate periods.
RNA analysis.
Nuclear and cytoplasmic fractions of COS cells were prepared as described
previously and RNAs were was isolated in TriReagent and treated at least twice with
DNase (54). RPA and probes are described in Roberts et al. (127), and northern blots were
performed by standard protocols with 32P-labeled DNA probes prepared by random
priming (Random Primers DNA Labeling System, Invitrogen). For RNA immunoprecipitation, 4 x 106 COS cells were transfected with pYW100 alone or together
with pcDNA-FLAG-RHA. Cells were harvested 48 h post-transfection and either total
cellular protein or nuclear and cytoplasmic fractions were prepared as described (131) and
subjected to either Western blot or RNA IP as described (132) using FLAG M2
monoclonal antibody. For RNA isolation, the sample was extracted in Trizol and treated
32 with DNase four times. We used either random hexamer or junD-specific antisense primer and Sensiscript reverse transcriptase (Qiagen) to generate cDNA; 10% of the reaction was used for PCR with the primers complementary to HIV-1 gag, junD, c-myc, or gapdh
(sequences available upon request). For real time PCR assays to quantify steady state
RNA, 50 ng aliquots of total RNA were reverse transcribed and 10% of the reaction was subjected to Quantitect SYBR Green PCR (Qiagen) using a Lightcycler (Roche).
33 RESULTS
RNA helicase A recognizes structural features of PCE
PCE RNA-protein complexes were isolated by RNA affinity chromatography using biotinylated RNA and concentrated HeLa nuclear extracts. In RNA electrophoretic mobility shift assays (EMSA), the complexes were selectively competed by excess PCE
RNA (Fig. 2.1a). They were not competed by antisense PCE RNA (As), which is similar in length but dissimilar in secondary structure and does not confer PCE activity (127). RNA affinity columns were prepared with PCE or As RNA and incubated with concentrated
HeLa nuclear extracts, washed repeatedly with binding buffer, and RNA binding proteins were eluted with 2 M KCl. SDS-PAGE results from several replicate experiments consistently detected a ~150 kDa protein bound exclusively to PCE RNA (Fig. 2.1b). The lack of detectable binding to As RNA indicated concordance between binding and PCE activity. Two other proteins of ~100 and 60 kDa consistently eluted from both PCE and As
RNA affinity columns indicating discordance between binding of these proteins and PCE activity. Eluants of four replicate PCE RNA affinity columns were pooled, subject to
SDS-PAGE, and the 150 kDa protein was excised, digested with trypsin and the peptides were evaluated by MALDI-TOF MS. Bioinformatics analysis identified the ~150 kDa protein as human DExH-box protein 9 (DDX9), also known as RNA helicase A (RHA).
Western blotting verified that RHA was present exclusively in the 2M eluant of PCE RNA affinity column but not the As RNA affinity column (Fig. 2.1c).
34
Figure 2.1. RNA helicase A is a PCE binding protein. RNA electrophoretic mobility shift assay (EMSA) of PCE RNA-protein complexes formed in Hela nuclear extracts. The PCE RNA-protein complexes are competed upon addition of 100-fold excess of PCE RNA, but not antisense (As) RNA, which is similar in length but dissimilar in structure. b) SDS-PAGE of 2 M KCl eluant of RNA affinity columns prepared using PCE or As RNA. The ~150 kDa protein eluted from PCE exclusively while proteins of ~100 and 60 kDa eluted from both PCE and As RNA. c) RHA immunoblot determined that RHA eluted from the PCE RNA affinity column but not the As RNA affinity column. d) Addition of RHA antiserum RNA EMSA reactions produced a subtle shift in the mobility of the high molecular weight PCE-protein complexes formed on PCE RNA, but not AC’Aall point mutant or As RNA. E) EMSA reactions between PCE, AC’Aall point mutant or As RNA and total cellular extracts of COS cells transfected with pFL-RHA expression plasmid. Addition of FLAG antibody to the reactions selectively shifted the PCE RNA-protein complexes (Data published in (9)) (Figure 2.1a,b,c provided by Hartman TR).
35 EMSAs were used to examine the specificity of interaction of RHA with PCE.
EMSA reactions were performed with PCE and the AC’Aall point mutant that contains
substitutions disrupting basepairing between the A and C stem loops and altering the unpaired A loop nucleotides that are necessary for PCE activity (127). Addition of RHA antiserum to PCE EMSA reaction produced a subtle shift in the mobility of the high molecular weight PCE-protein complexes (Fig. 2.1d). A shift was not observed upon addition of RHA antiserum to the AC’Aall and As EMSA reactions. Similar results were observed in EMSA reactions performed with cell extracts prepared from COS cells transfected with epitope-tagged RHA expression plasmid pFL-RHA. Addition of FLAG antibody to PCE EMSA produced the subtle shift in the mobility of the PCE-protein complexes. Addition of FLAG antibody to EMSA reactions performed with the AC’Aall point mutant and the As RNA did not produce a shift (Fig 2.1e). These results demonstrated that RHA is a component of the PCE RNA-protein complexes.
The specificity of PCE interaction with RHA was further investigated by co-immunoprecipitation assay (co-IP). COS cells were cotransfected with HIV-1 gag test
plasmids that contained PCE, As, or PCE point mutants (Fig. 2.2a) together with
pFL-RHA. Cell extracts were prepared two days later, assayed for PCE activity by Gag
ELISA and immunoprecipitated with FLAG antibody. Western blotting of the cell lysate
before the IP showed that similar levels of FLAG-RHA were present in the cells and that
FLAG-RHA was not detectable in control cells that were transfected with empty plasmid
(Fig. 2.2b, lanes labeled L). Western blotting of the supernatant after IP showed that
FLAG-RHA had been efficiently depleted (Fig. 2.2b, lanes labeled S). RT-PCR on total
36 cellular RNA with gag-specific primers demonstrated that gag RNA was expressed in the cells (Fig. 2.2c). The RT-PCR product was present in reactions that contained RT and absent in reactions that lacked RT. RNA was harvested from the immunoprecipitates and subjected to RT-PCR with gag-specific primers. An RT-PCR product was detectable in samples from cells that expressed PCEgag, but not Asgag or the PCE deletion mutant
(Delta). FL-RHA did not co-precipitate with gag RNA that contained the AC’Aall or AC’ structural mutation (127). The AA’CC’compensatory mutation rescued PCE activity and co-precipitated with FL-RHA. The AallCall mutant exhibited partial PCE activity and co-precipitated with FL-RHA. RT-PCR with gene-specific primers determined that RHA did not co-precipitate with endogenous gapdh nor c-myc RNA, which contains a long and highly structured 5’ UTR. These results indicated that RHA interaction correlated with
PCE activity and that RHA selectively recognized structural characteristics that are presented in the context of A and C stem loops.
37
Figure 2.2. RT-PCR detects selected RNAs that co-immunoprecipitate with RNA helicase A. a) Schematic diagram of the HIV-1 gag test plasmid showing the position of the post-transcriptional control element (PCE), RNA start site (arrow), 5’ and 3’ splice sites (ss), HIV-1 gag open reading frame that is positioned within the intron (black rectangle), and polyadenylation signal (p(A)). Mutated sequences within the PCE point mutants are indicated. PCE deletion is designated by a hatched line. b-d) COS cells were cotransfected with each HIV-1 gag test plasmid, pFL-RHA and pGL3 reference plasmid. Cell extracts were prepared two days later and proteins were subject to Gag ELISA or immunoprecipitation with FLAG antibody, followed by RNA isolation and RT-PCR. b) FLAG immunoblot of the cell lysate before the immunoprecipitation (lysate) or after immunoprecipitation (sup). c) RT-PCR products of total cellular RNA with gag-specific primers demonstrated similar expression of the gag test plasmid. Reactions that contained or lacked reverse transcriptase (RT) are designated (+ or -). d) RT-PCR products of the indicated gene-specific primers and RNA harvested that co-precipitated with FLAG-RHA, or were supplemented with DNA (input) (Data published in (9)).
38
Figure 2.2
39 RHA is necessary for PCE activity
To investigate the possibility that RHA is necessary for PCE translational enhancement, the effect of downregulating endogenous RHA was examined using small interfering RNAs (siRNAs). Immunoprecipitation (IP) assays with RHA antibody determined that the half-life of RHA protein in COS cells was approximately 30 h and established that RHA is a reasonable target for downregulation by RNA interference (data not shown). The cells were transfected with either RHA siRNAs (RHA) or scrambled siRNAs (Sc) and the downregulation of RHA was monitored by northern and western analyses. Transfection with RHA siRNAs reduced endogenous RHA mRNA to <15% of control, while no effect was observed on gapdh RNA levels (Fig. 2.3a) and cell viability remained similar during the 4 consecutive days post-transfection. RHA protein was reduced to <30% at day 3 and day 4 post-treatment (Fig. 2.3b). To evaluate PCE activity, two days after siRNA treatment the cells were transfected with the PCE HIV-1 gag test plasmid and the pGL3 reference plasmid that produces firefly luciferase. Cell extracts were harvested on day 4 and Gag and luciferase levels were measured by ELISA and enzymatic assay, respectively. Results of five independent transfection experiments indicated that
RHA downregulation significantly reduced Gag protein production without reducing luciferase production (p = 0.003) (Table 2.1). Gag activity was reduced within a 17% to
40% of control and was proportional to the downregulation of RHA by the siRNAs.
40
Figure 2.3. RNA helicase A downregulation eliminates PCE activity. COS cells were transfected with RHA siRNAs (RHA) or scrambled siRNAs (Sc) and cell extracts were harvest at consecutive days post-treatment. a) Total cellular RNA was subjected to Northern blot with complementary RHA or gapdh radiolabeled probes. b) Immunoblot with antiserum against RHA or β-actin. c) Gag and luciferase levels after transfection with siRNA and the PCE HIV-1 gag test plasmid and pGL3 reference plasmid. Real time PCR analyses on total cellular RNA with indicated primers. d) RNase protection assay on nuclear and cytoplasmic RNA. e) Western blot with indicated antiserum. f) Sucrose gradient analysis was performed on 293 cells and proteins analyzed by RHA immunoblot. Ribosomal profile of mock and puromycin-treated cells with labels to designate low molecular weight mRNPs; 40S, and 60S ribosomal subunits; 80S monosome fractions; LP, light polysomes (2-3 ribosomes); HP, heavy polyribosomes (4+ ribosomes). Indicated are the position of RHA, and reactions without EDTA (-EDTA) or supplemented with EDTA (+EDTA), or with puromycin (+puromycin) (Data published in (9)) (Figure 2.3 d,e,f provided by Hartman TR).
41 Results of real-time RT-PCR on total cellular RNA determined that the steady state of HIV-1 gag RNA was not changed by RHA downregulation. The copy numbers of
HIV-1 gag RNA remained similar (40 × 102 and 43 × 102 copies per µg) despite reduction of Gag protein production by a factor of 5 from 53,000 to 10,000 pg/ml. To further investigate that the reduction in Gag production is not attributable to lower steady state level of the gag RNA, RNase protection assays (RPA) were performed on nuclear and cytoplasmic RNA. RPAs demonstrated that RHA downregulation did not reduce the steady state of PCEgag RNA (Fig. 2.3d) despite reduction in Gag production by a factor of
5. Furthermore, RHA downregulation did not affect splicing efficiency nor reduce cytoplasmic accumulation. Immunoblotting with histone H1 and β-actin on proteins prepared from an aliquot of the nuclear and cytoplasmic proteins verified effective fractionation of the nucleus from the cytoplasm and that equivalent amounts of protein were analyzed (Fig. 2.3e). Immunoblotting with RHA determined that RHA downregulation was effective and that RHA is abundant in the nucleus (Fig. 2.3e). The determination that RHA activity is not attributable to increased PCEgag RNA in the cytoplasm is consistent with the hypothesis that RHA facilitates translation of this mRNA.
If RHA facilitates translation, RHA present in the cytoplasm may preferentially associate with polyribosomes. Sucrose gradients and RHA immunoblotting were used to assess the distribution of RHA in the cytoplasm. RHA present in the cytoplasm was associated with the high molecular weight fractions and is not observed in lower molecular weight messenger RNPs (mRNPs) (Fig. 2.3e). Disassociation of the ribosomal subunits by treatment with EDTA disrupted the polyribosome association of RHA. Furthermore, reduction of polyribosomes by treatment with puromycin to induce premature translation
42 termination redistributed RHA to lighter fractions. These data indicate that RHA in the cytoplasm was preferentially associated with actively translating polyribosomes. The polyribosomal distribution of RHA is consistent with the hypothesis that RHA is necessary for efficient translation of PCEgag RNA.
Another approach to examine the effect of RHA on PCE activity used supplementation of endogenous RHA with recombinant RHA. COS cells were co-transfected with the PCE-gag test plasmid, the pGL3 reference plasmid and increasing amounts of pFL-RHA expression plasmid. Equivalent amounts of transfected DNA were maintained by supplementation with empty plasmid. Flag immunoblot verified increasing
Figure 2.4. Overexpression of RNA helicase A increases PCE activity. a) Triplicate cultures of COS cells were cotransfected with PCE-gag or As-gag test plasmid, pGL3 reference plasmid, and indicated amounts of FLAG-RHA expression plasmid. Equivalent amounts of transfected DNA were maintained by supplementation with pcDNA empty plasmid. Gag production was measured by Gag ELISA and standardized to luciferase produced from cotransfected pGL3. FLAG immunoblot verified gradient of expression of FLAG-RHA. Data shown are representative of three independent triplicate experiments (Data published in (9)) (Figure 2.4 provided by Bolinger C).
43 expression of FLAG-RHA and Gag ELISA determined that recombinant RHA increased
PCE activity up to 3-fold (Fig. 2.4). In the absence of FLAG-RHA, Gag production from the As-gag test plasmid was less than the minimum detectable and was not stimulated by expression of FLAG-RHA. RPAs verified that FLAG-RHA overexpression did not alter the steady state level, splicing efficiency, nor nuclear export of PCEgag RNA (data not shown) consistent with RHA facilitating the translation of PCEgag RNA. These results indicated that overexpression of RHA increased PCE activity.
RHA is necessary for efficient translation of PCEgag RNA but not global cellular
RNA
Metabolic labeling experiments were used to assess the effect of RHA downregulation on translational efficiency of PCEgag RNA and cellular RNAs. COS cells were treated with siRNAs for two days, downregulation of RHA was verified by Western blot, and the cells were co-transfected with the same siRNAs and the PCEgag test plasmid, and the pGL3 reference plasmid. Two days later, Western blot on an aliquot of the cells verified downregulation of RHA to <30% and additional aliquots of the cells were labeled with 35S-cysteine/methionine for 15-min intervals. Cell extracts were prepared and used for
IP with Gag antibody and or trichloroacetic acid (TCA)-precipitation. The Gag IP demonstrated that RHA downregulation severely reduced the rate of Gag protein synthesis
(Fig. 2.5a). For cells treated with scrambled siRNAs, the incorporation of
35S-cysteine/methionine into Gag increased from 20 × 103 units at 15 min post-labeling to
44
Figure 2.5. RNA helicase A is necessary for efficient translation of PCEgag RNA. a) Metabolic labeling with 35S-methionine/cysteine and immunoprecipitation assay determined that RHA siRNA treatment severely reduced the rate of Gag protein synthesis. COS cells were transfected with PCE-gag and either scrambled siRNAs (Sc) or RHA siRNAs (RHA) as in legend of Figure 2.3 and labeled with 35S-cysteine/methionine for indicated intervals. These cell extracts and extract of cells overexpressing HIV-1 Gag (HIV-1 Gag) were subjected to Gag IP assay. b) Metabolic labeling with 35S-methionine/cysteine and measurement of TCA precipitable counts determined that RHA downregulation does not inhibit global cellular translation. Cell extracts from a) were subjected to trichloroacetic acid (TCA)-precipitation and scintillation. Average results of 2 replicate assays. c) Metabolic labeling with 3H-uridine and measurement of TCA precipitable counts determined that RHA downregulation does not inhibit global cellular transcription. Average results from 2 replicate assays (Data published in (9)) (Figure 2.5 b,c provided by Hartman TR). .
45 130 × 103 units at 60 min post-labeling. By contrast, for cells treated with RHA siRNAs,
the level of incorporation of 35S-cysteine/methionine into Gag remained approximately 10
× 103 units at each sequential time point. Evaluation in parallel of TCA-precipitable counts
determined that global cellular protein synthesis was not altered by RHA downregulation
(Fig. 2.5b). Metabolic labeling with 3H-uridine and TCA precipitation assay verified that global cellular mRNA synthesis was not altered by RHA RNAi (Fig. 2.5c). These results, taken together with the determination that RHA downregulation did not alter PCEgag
RNA metabolism, indicate that RHA is necessary for efficient translation of PCEgag
RNA.
RHA is necessary for efficient translation of junD mRNA
Because the 5’ UTR of the naturally intronless junD shares features with SNV PCE
(123;127), derivatives of the PCEgag test plasmid were created to test the hypothesis that junD contains a cellular PCE. The 5’ terminal 119 nt sequence of rat junD was substituted in place of SNV PCE in the sense and antisense orientations. Results of three replicate transient transfections in 293 cells determined that PCE activity is conferred by junD in the sense, but not antisense orientation (30±5 ng/ml versus undetectable Gag). The metabolic labeling experiment was used to assess the effect of RHA downregulation on translational efficiency of endogenous junD RNA. COS cells were treated with siRNAs for two days and aliquots of the cells were labeled with 35S-cysteine/methionine and cell extracts were
prepared and used for IP with JunD antibody. IP demonstrated that RNA downregulation
46
Figure 2.6. RHA is necessary for efficient translation of junD RNA. a) COS cells transfected with either scrambled siRNAs (Sc) or RHA siRNAs (RHA) were labeled with 35S-cysteine/methionine for indicated intervals and cell extracts were prepared and subjected to immunoprecipitation with either JunD or GAPDH antibody. b) Graphic representation of phosphorimager analysis of (a) showing that RHA downregulation severely reduced synthesis of JunD but not GADPH. c) Northern blot analysis determined that RHA siRNA treatment did not reduce the steady state of junD or gapdh RNA but severely reduced RHA RNA. d) RT-PCR analysis determined that RHA downregulation reduced polyribosome incorporation of junD but not gapdh mRNA. Replicate sucrose gradients were performed on cytoplasmic extracts and pooled fractions (cytoplasm) or the polyribosome fraction was harvested and subjected to RT and PCR with primers complementary to junD and gapdh (Data published in (9)) (Figure 2.6c provided by Hartman TR).
47
Figure 2.6
48 significantly reduced JunD protein synthesis (Fig. 2.6a). For cells treated with scrambled
siRNAs, the incorporation of 35S-cysteine/methionine into JunD increased from 15 × 103 units at 30 min post-labeling to 130 × 103 units at 360 min post-labeling (Fig. 2.6b). In
contrast, for cells treated with RHA siRNAs, the level of incorporation of
35S-cysteine/methionine into JunD was limited to 30 × 103 units at 360 mins. By comparison, IP with GAPDH antibody showed that the rate of GAPDH protein was unaffected by downregulation of RHA (Fig. 2.6b). Northern blot analysis of total cellular
RNA determined that RHA downregulation did not alter steady state junD mRNA or
gapdh mRNA, but reduced RHA mRNA to a barely detectable level (Fig. 2.6c). To further
evaluate the effect of RHA downregulation on translational efficiency of junD, sucrose
gradients were prepared and semiquantitative RT-PCR assessed junD RNA association
with polyribosomes. Downregulation of RHA did not reduce the cytoplasmic abundance of
junD mRNA or gapdh, but selectively reduced the polyribosome association of junD
mRNA (Fig. 2.6d, lanes 3 and 4). The co-IP assay demonstrated that FLAG-RHA interacts
with endogenous junD RNA in the cells cotransfected with FLAG-RHA expression
plasmid and PCE test plasmids (Fig. 2.2d). RNA that co-IP with FLAG antibody produced
an RT-PCR product with junD-specific primers. The RT-PCR products were not detected in reactions that lacked RT.
To further assess RHA interaction with junD and PCEgag, COS cells were transfected with FLAG-RHA, PCE gag test plasmid and the pGL3 reference plasmid.
Cells were harvested two days later and nuclear and cytoplasmic proteins were isolated and subject to IP with FLAG antibody. RNA isolated from the immunoprecipitates produced an RT-PCR product with junD primers and gag primers, but not with gapdh primers (Fig.
49 2.7a). The junD and PCEgag RNAs were detectable in both the nucleus and cytoplasm.
Control cells that lack FL-RHA or reactions that lack RT did not produce the RT-PCR product. Immunoblotting with histone H1 or β-tubulin antiserum verified effective fractionation of nucleus and cytoplasm (Fig. 2.7b). Immunoblotting of the samples before
IP verified levels of FLAG-RHA were similar and immunoblotting of the supernatants after IP verified that the FLAG-tagged RHA was effectively depleted. Immunoblotting with β-actin antiserum verified similar protein loading. The combined results of the IP and the metabolic labeling assays indicated that RHA interacted with junD mRNA and
PCEgag in the nucleus and cytoplasm and selectively stimulated their rate of protein synthesis.
50
Figure 2.7. RNA helicase A immunoprecipitates with junD mRNA and PCEgag in the nucleus and cytoplasm. a) RNA immunoprecipitation assay with FLAG antibody on nucleoplasm or cytoplasm of COS cells that were transfected with PCE-gag test plasmid, FLAG-RHA expression plasmid and pGL3 reference plasmid and subjected to subcellular fractionation. RNA preparations were treated with DNase and incubated in reverse transcription reactions with or without reverse transcriptase (RT), as labeled. PCR was performed with primers complementary to gag, junD, or gapdh. Control reactions contained water or DNA. b) Immunoblotting with histone H1 or β-tublin antibody verified effective fractionation. Immunoblotting with β-actin verified equivalent sample loading. Immunoblotting with FLAG antibody verified effective precipitation (lysate) and depletion (sup) of FL-RHA from the respective fractions (Data published in (9)).
51 DISCUSSION
Previous to this report, RHA had been shown to activate transcription (29-31;53),
modulate RNA splicing (27;41;133), and bind the nuclear pore complex (134). Our results
demonstrate that RHA is necessary for efficient translation of selected RNAs that contain a
long and highly structured 5’ UTR. RHA-PCE interaction stimulates polyribosome incorporation and the rate of protein synthesis. Analysis of PCE point mutants indicated that RHA selectively recognizes structural characteristics that are presented in the context of A and C stem loops. Previous RNA structure mapping studies identified point mutations that disrupt basepairing of functionally redundant stem loops (designated A and C) and eliminate PCE activity (127). The loss-of-function was not attributable to reduction in the steady state or cytoplasmic accumulation of the RNA (127). Instead the cytoplasmic RNA was translationally silent, which is reminiscent of translationally silent mRNAs that are sequestered in stress granules or processing bodies (135). Compensatory mutations that restore the basepairing of A and C stems rescued PCE activity. Results here show that
RHA-PCE co-precipitate from the nucleoplasm and previous results show that interaction with a nuclear protein is necessary for PCE activity (128). Taken together, the results posit
the hypothesis that RHA interaction early in the post-transcriptional expression of PCE
RNA satisfies an RNA surveillance checkpoint necessary for efficient translation in the
cytoplasm. Because the junD 5’ UTR forms a secondary structure that is remarkably
similar to PCE (123;127), we expect that similar structural mutations in junD PCE will likewise eliminate interaction with RHA and efficient translation. JunD is a member of the
Jun family of transcription factors (136), which dimerize with Fos or other Jun family
52 members to form the Activator Protein-1 (AP-1). AP-1 is a central signaling component in
cell growth regulation and provides a key pathway for early response to cellular stress
(137). The expression of AP-1 family members is tightly regulated and dysregulation of
AP-1 family members contributes to cancer and metabolic disease (138;139). It is possible
that future studies will identify junD PCE to be an important component to effective
regulation of junD and responsiveness to changes in cell growth conditions such as serum
starvation. Bioinformatic searches have identified additional naturally intronless genes that
likewise possess a long and highly structured 5’ UTR. It is possible that RHA interaction
with these pre-mRNAs represents a conserved post-transcriptional control axis to
overcome barriers posed by conserved structural motifs in the 5’ UTR.
A long-standing issue has been to understand the observation that nuclear
interactions profoundly effect the ultimate translational utilization of spliced RNAs
(140-144). Several recent studies have identified protein mediators that promote translation and RNA surveillance in coordination with intron removal. For example,
RNA-protein tethering experiments have determined that the EJC components RNPS1 or
Y14 can stimulate translation (120;122). Naturally nonspliced mRNA templates are expected to require alternative post-transcriptional regulatory circuits for efficient protein synthesis. Our results identify that RHA is necessary for translation of two nonspliced
mRNAs. It is possible that recruitment of RHA satisfies an RNA surveillance checkpoint
that would otherwise impede translation of these nonspliced mRNA.
53 Model for RNA helicase A translation stimulation of selected mRNAs
We propose a model in which RHA recognizes structural features of PCE and stimulates RNA-protein rearrangements that are necessary for efficient translation (Fig.
2.8). PCE-containing RNA that does not interact with RHA early in its post-transcriptional expression is incompetent for translation. RHA-PCE interaction may stimulate ribosome scanning directly by promoting RNA-protein rearrangements that are necessary for translation initiation. A non-mutually exclusive possibility is that RHA stimulates ribosome recycling by securing circularization of the mRNA template (145). A recent study of bovine diarrheal virus found RHA to bind to redundant 5’ and 3’ UTR structures and the authors speculated that circularization of viral RNA was secured by RHA and promoted productive viral replication (146). An important issue to be addressed is whether
RHA activity on PCE is constitutive or regulated. We speculate that regulation of RHA activity occurs by post-translational modification of RHA that provides a conformational change that is necessary for interaction with PCE or an essential cofactor.
Previous studies have shown that translation of mRNAs harboring a complex 5’
UTR can be increased by overexpression of eIF4E and this activity was attributed to improved recruitment of eIF4A to the 5’ RNA terminus (119). eIF4A is a DEAD box RNA helicase that has RNA chaperone activity as defined as RNA unwinding activity and
RNPase activity (117). The observed requirement for eIF4A in proportional to the degree of secondary structure indicates that increased RNA chaperone activity is engaged during efficient scanning of a complex 5’ UTR (147). It is possible that RHA supplements eIF4A
54
Figure 2.8. Model for RNA helicase A translation stimulation of PCE RNA. PCE and distal structural motifs in the 5’ UTR pose barriers to efficient ribosome scanning. Lack of RHA-PCE interaction correlates with lack of initiation, as represented by a stalled 43S ribosomal subunit (shaded oval on cap). Interaction between RHA and PCE occurs early in post-transcriptional gene expression and induces RNA-protein and RNA-RNA rearrangements that ultimately stimulate polyribosome incorporation and the rate of protein synthesis. RHA-PCE interaction may also stimulate ribosome recycling directly by securing a circularized polyribosome via interaction with poly(A) binding protein (rectangle labeled PABP) (Data published in (9)).
55 RNA chaperone to neutralize the complex 5’ UTR of PCE-containing RNA. We favor a role for RHA in stimulating PCE RNA-protein rearrangements because RHA has been shown to have limited ability to unwind stable duplexes and to require a 3’ overhang (148).
Recent studies on spliced mRNAs reinforce the point that RNA-protein rearrangements operate sequential RNA surveillance checkpoints that are necessary for efficient post-transcriptional gene expression (149).
DEAD-box helicases represent a common element in divergent post
-transcriptional regulatory circuits DEAD/DEXH-box proteins are a versatile superfamily of proteins that play a role in all processes involving RNA (130). Recent studies suggest that selected family members recognize specific subsets of RNA targets. For example,
Dbp5 provides RNA chaperone activity to spliced mRNAs exported by a
TAP/NXF1-mediated nuclear export pathway during release from the nuclear pore complex (150;151). The nuclear isoform of eIF4A, eIF4AIII, preferentially associates with spliced RNAs and functions in nonsense mediated decay (152;153). Another family member, DED1 was previously identified to modulate translation in yeast (154). Recent findings connect the human homolog of DED1, DDX3 with nuclear export of
Rev/RRE-dependent HIV-1 mRNA by CRM-1 nuclear export receptor (1). The possibility that Dbp5 and DDX3 can substitute for RHA to confer PCE activity was ruled out in overexpression experiments (Hartman and Boris-Lawrie, unpublished). Coller and Parker recently showed that yeast DEAD box helicase Dhh1p is a general translation repressor and facilitator of P body formation (155). Dhh1p modulates the conversion of an active mRNA template to a translationally silent form that is targeted to P bodies. The results with
56 Dhh1p identify a general mechanism of translation repression that is applicable to the majority of cytoplasmic mRNAs. By comparison, our results identify a selective mechanism of translation stimulation for a specific class of mRNAs that contain a complex
5’ UTR.
57
Table 2. 1. RHA downregulation eliminates PCE activitya.
a COS cells were transfected with indicated siRNAs, incubated 48 h, cotransfected with
PCE –gag test plasmid and pGL3 reference plasmid, incubated 24 h and total cellular protein was harvested. Gag production was measured by Gag ELISA and standardized
to luciferase produced from cotransfected pGL3. Detection limit of Gag was 10,000
pg/ml.
b RLU, relative light unit.
c [ ] indicates the level relative to –RHA siRNA control. The Fisher’ sign test was used to compare the fold differences of Gag and luciferase activity, p = 0.003.
Data published in (9).
Replicate Sc siRNA RHA siRNA
Experiment Gag (pg/ml) Luc (RLUb) Gag (pg/ml) Luc (RLU)
1 53,000 21,882 15,090 [0.27]c 40,224 [2]
2 49,000 35,016 17,890 [0.37] 57,239 [1.7]
3 61,990 11,998 20,715 [0.33] 23,169 [2]
4 104,375 16,436 45,016 [0.43] 35,548 [2]
5 225,155 10,094 37,096 [0.17] 55,607 [5]
58
CHAPTER 3
HIV-1 TAT RNA SILENCING SUPPRESSOR ACTIVITY IS CONSERVED ACROSS KINGDOMS AND COUNTERACTS TRANSLATIONAL REPRESSION OF HIV-1
ABSTRACT
The RNA silencing pathway is an intracellular innate response to plant and animal virus infections that is countered by many plant and animal viruses by expression of an
RNA silencing suppressor (RSS). HIV-1 Tat and tomato bushy stunt virus P19 are double-stranded RNA (dsRNA)-binding proteins with RSS activity. Here, we demonstrate
HIV-1 Tat and P19 function across the plant and animal kingdoms and suppress a common step in RNA silencing that is downstream of small RNA maturation. Our experiments reveal that RNA silencing in HIV-1 infected human cells severely attenuates the translational output of the unspliced HIV-1 gag mRNA, and possibly all HIV-1 transcripts.
The attenuation in gag mRNA translation is exacerbated by K51A substitution in the Tat double-stranded RNA-binding domain. Tat, plant virus RSS, or Dicer down-regulation rescues robust gag translation and bolsters HIV-1 virion production. The reversal of HIV-1 translation repression by plant RSS supports the recent finding in Arabidopsis that plant miRNAs operate by translational inhibition. Our results identify common features between
59 RNA silencing suppression of plant and animal viruses. We suggest that RNA silencing-mediated translation repression plays a strategic role in determining the viral set-point in a newly HIV-1-infected patient.
INTRODUCTION
RNA silencing is a eukaryotic post-transcriptional gene regulation mechanism and innate defense to quell virus infections and genetic damage by retro-transposons. Antiviral
RNA silencing is initiated when virus-specific double-stranded RNA appears in the cytoplasm and is processed by Dicer endonuclease into 21-25 nucleotide miRNA/miRNA*
(guide/passenger) duplexes (13;79;156;157). The guide strand and complementary target mRNA is incorporated into RNA-induced silencing complexes (RISC) (37;158), which coalesce as processing bodies (P bodies) that are sites of target mRNA degradation or translation inhibition (159). To counteract this restriction, most plant viruses encode an
RNA silencing suppressor (RSS) that prevents recovery from infection and drives pathogenesis (reviewed in (98;160)). For HIV-1, cell-encoded miRNAs dampen virus replication in activated T lymphocytes (12) and contribute to viral latency in resting T lymphocytes (110). In response, the viral Tat transcriptional trans-activator confers general suppression of RNA silencing (105). Tat RSS activity is genetically separable from Tat transcriptional activity, but segregates with the arginine-rich double-stranded
RNA-binding domain (105). A similar RNA binding domain is conserved in Tombusvirus
P19 RSS and confers interaction with miRNA duplexes in a sequence-non specific manner and blocks programming of RISC for RNA silencing. For TBSV, viral RNA remains intact resulting in virus propagation and disease pathogenesis (100;101;161). For Tat, tomato 60 bushy stunt virus (TBSV) P19 and other Tombusvirus RSS, mutation of this domain eliminates RNA silencing suppression (102;105). The necessary role of the RNA binding domain in plant and animal RSS suggests a common mechanism of activity. To investigate whether HIV-1 Tat RSS protects against viral RNA degradation, we compared the activity of Tat and P19 in plant protoplasts and animal cells.
Here, we present evidence that HIV-1 Tat and TBSV P19 function equivalently in plant protoplasts and animal cells to suppress RNA silencing at a step downstream of the dsRNA processing, most likely by sequestering mature si/miRNAs. HIV-1 Tat and TBSV
P19 overcome RNA silencing-mediated restriction of HIV-1 mRNA translation.
61 MATERIALS AND METHODS
Plasmids
HIV-1/RSS was constructed by PCR-based site-directed mutagenesis of pNL4-3 to
introduce K51A (105). P19 eukaryotic expression plasmid pCMVP19FL was constructed
by PCR amplification of the P19 open reading frame from template pRTL2P19 (103) with
primers containing terminal ClaI and BamHI restriction sites. Plant expression plasmid
pRTL2Tat was constructed by SacI and BamHI restriction of pRTL2 (162) and
pCMV-Tat-1 (163) (gift of Andrew Rice) followed by isolation from agarose and ligation.
All constructions were verified by sequencing. Previously described expression plasmids
are pRTL2:smGFP, HC-Pro, and CP (164), VA1 (104); NS1 and E3L (99;165).
pCMV-Luc-8(x)-miR30(p) and pCMV-miR30 were gifts of Bryan Cullen (104).
Cells culture, transfection and infection
Monolayer human HEK293 embryonic kidney cells and HeLaT4 (CD4+ HeLa) cells were cultured in DMEM media supplemented with 10% FBS at 37°C and 5% CO2.
Human CEMx174 lymphocytes were cultured as suspension cells in RPMI 1640 media with 10% FBS. Transient transfections were performed on 1 x 105 HelaT4 cells in triplicate
in 6-well plates. One µg of P19FL or empty pCAM vector and 0.2 µg of pGL3 firefly luciferase transfection efficiency control were cotransfected in Fugene6 as previously
described. After two days, the transfectants were subcultured and transfected with 1 µg of
HIV-1NL4-3 or HIV-1/RSS proviral plasmid. Culture media were harvested at 12h, 24h, 36h
and 48h from each triplicate well and HIV-1 Gag was quantified by a commercial Gag p24
62 enzyme-linked immunosorbent assay (ELISA) (Zeptrometriz). Cells lysates were
harvested in parallel in 100 µl NP40 lysis buffer (20 mM Tris HCl [pH 7.4], 150 mM NaCl,
2mM EDTA, and 1% NP-40). Ten µl of lysate was assayed in luciferase reagent (Promega)
and relative light units were used to standardize minor differences in transfection
efficiency.
Virus stocks for infections were generated by transfection of 1x106 HEK293 cells
with HIV-1NL4–3 or HIV-1/RSS and infection of stock culture of CEMx174 T cells. After
48 h, cells were harvested on Ficoll Hypaque and cultured with naïve CEMx174 cells at a
1:10 ratio. Fluorescence-activated cell sorting (FACS) analysis of intra-cellular Gag expression was performed with anti-p24 KC57-FITC antibody (Beckman-Coulter) and Fix and Perm (CALTAG).
Transient transfection and Tat RSS assay
Transient transfections were performed on 1 x 105 HelaT4 cells in triplicate in 6-wells
plates. One µg of p19, E3L, NS1, Tat expression plasmids or pCAM were transfected to
each well by fugene 6 (Roche) according to the manufacturer’s instruction. After 24 hours
transfection, cells are further transfected with 0.3 µg of pCMV-Luc-8x-miR30(P), 0.3 µg
of pCMV-miR30 and 0.1 µg pRL-CMV. After 2 days of second transfection, half cells
were lysated in 50 µl NP40 lysis buffer (20 mM TrisHcl [pH 7.4], 150 mM Nacl, 2mM
EDTA, and 1% NP-40). 10-20 µl of the lysate were used to dual luciferase assays by
utilizing luciferase reagent (Promega). 10 µg of total proteins were used for western blot
assay for p19 expression. The other half cells were harvest by Trizol reagent (Invitrogen) to
isolate total RNA.
63 Protein analysis
Cells were lysed in RIPA buffer (50mM Tris pH 8.0, 0.1% SDS, 1% Triton-X,
150mM NaCl, 1% deoxycholic acid, 2mM PMSF) and 50 µg protein was subjected to
SDS-PAGE and transferred to nitrocellulose membrane. Immunoblotting antibodies detected Flag and β-actin (Abcam, Cambridge, MA). Visualization was performed with
Luminol reagent (Santa Cruz Biotechnology, Santa Cruz, CA). The IP and TCA precipitation protocols are described previously (9).
Statistical analysis.
One-way analysis of variance model was applied to log base 2-transformed data.
Dunnett's method was used to test the mean difference among multiple groups.
Nicotiana benthamiana protoplast assays
Isolation of N. benthamiana cultured cell protoplasts and electroporation are described in detail by Qi et al. (164). One-million protoplasts were electroporated with 5
µg of pRTL2:smGFP, in the presence or absence of 5 µg of double stranded GFP effector
RNA by electroporation. The assays were performed in triplicate wells of six-well plates with 5 µg of suppressor plasmid. At three days post-electroporation, GFP fluorescence intensity was measured by CytofluorTM 2350 Fluorescence Measurement System with the plate reader software (Millipore, Billerica, MA). Excitation (EX) and emission (EM) parameters were set as EX 485 nm and EM 530 nm for GFP. For detection of plant GFP effector RNA, 5 µg of total RNA was separated on 5% PAGE with 8M urea and 0.5X TBE. 64 For detection of miR30 precursor miRNA and mature miRNA, 10 µg of enriched small
RNA were separated by 15% PAGE/8M urea/0.5X TBE. The small RNA preparations
were isolated from total cellular RNA with differential ethanol precipitation using
miRvana protocol (Ambion). The RNAs were transferred to Hybond-XL nylon membrane
(Amersham Biosciences) and subjected to UV crosslinking. The membranes were
hybridized in ULTRAhyb Ultrasensitive Hybridization Buffer (Ambion) overnight,
washed twice in 2X SSC/0.1% SDS for 15 min and twice in 0.2X SSC/0.1% SDS for 15
min. Hybridization and washing were performed at 65°C and at 37°C for detection of large
RNA species and small RNA species, respectively. The membranes were exposed to
Storage Phosphor Screen (Kodak) that were scanned by Molecular Imager FX using
Quantity One-4.1.1 software (Bio-Rad, Hercules, CA). To generate the antisense miR30
probe, the miR30 template was amplified by PCR with primers that contain the T7
promoter. One µg of PCR product was used for in vitro transcription by T7 RNA
polymerase with NTPs supplemented with 32P-UTP.
Real time RT PCR
Our previously described RT-PCR protocol (9) was used. Random hexamers and
Sensiscript reverse transcriptase (Qiagen) were used to generate cDNA from 100 ng RNA.
Ten percent of the cDNA preparation was used for real-time PCR with primers
complementary to luciferase mRNA or actin and Quantitect SYBR Green PCR (Qiagen) in
a Lightcycler (Roche).
65 RESULTS
HIV-1 Tat suppresses RNA silencing in plant cells downstream of the maturation step of dsRNA duplexes.
We used Nicotiana benthamiana protoplasts to investigate whether or not Tat RSS activity is maintained in the plant kingdom similar to the activity of influenza A virus NS1
RSS (165). Tat was expressed in plant cells downstream of the strong and constitutive 35S promoter derived from cauliflower mosaic virus. The RSS activity of Tat was compared to that of plant viral RSSs by co-electroporation with GFP reporter plasmid and 700 nt
GFP-specific dsRNAs that down-regulate GFP expression (164). Representative images from five independent triplicate transfection assays (Fig 3.1A) demonstrated that HIV-1
Tat (Tat), TBSV P19 (P19) and tobacco etch virus helper component-protease (HC-Pro) restored GFP fluorescence compared to the empty vector control. Quantification of GFP fluorescence in the bulk cultures revealed that the RSS activity was statistically significant
(p value < 0.0001) (Fig 3.1B). Northern blot analysis using a sense strand GFP-specific probe revealed low but detectable levels of the 700 nt GFP effector RNA in the cells electroporated with the empty vector (Ve), HC-Pro, P19, or Tat. By comparison, Turnip crinkle virus coat protein (CP) caused the accumulation of effector dsRNA, consistent with its role in preventing processing of dsRNAs (164;166). These results confirm the published observation that HC-Pro and P19 do not affect the processing of long dsRNAs into mature siRNAs (100-102;167;168). Thus, we show for the first-time that Tat RSS activity is conserved across kingdoms and functions downstream of dsRNA duplexes.
66
Figure 3.1. Tat exhibits RSS activity in plant cells that is not attributable to inhibited processing of long dsRNA. (A) N. benthamiana culture cells protoplasts were transfected with GFP reporter plasmid, long GFP-specific dsRNA and the empty vector (Ve) (1) or indicated RSS expression plasmid (2,3,4) and monitored for GFP activity three days post electroporation. P19, Tat and HC-Pro restored GFP expression. (B) Quantitative analysis of bulk cultures is summarized from five replicate experiments. Expression of indicated RSS increased the GFP fluorescence compared to empty vector control. (C) Northern blot analysis with probe complementary to the antisense strand of gfp effector RNA. HC, P19 and Tat do not induce accumulation of effector RNA. CP induced accumulation of effector RNA. Lower panel is stained with ethidium bromide to control for minor differences in RNA loading (Data published in (169) Figure provided by Zhong X and Ding B).
67
Figure 3.1
68 TBSV P19 suppresses RNA silencing in animal cells downstream of miRNA
maturation.
We next compared the RSS activity of Tat and plant virus RSS in animal cells. The miR30-based luciferase reporter system (104) contains eight copies of the mir30 target sequence (pCMV-Luc-8(x)-miR30) (Fig. 3.2A). Co-transfection of human embryonic kidney 293 cells with the primary precursor miR30 (pri-pre-miR30) expression plasmid pCMV-miR30 and the pCMV-Luc-8(x)-miR30 reporter robustly silenced luciferase activity (compare tan bars, reduction by factor of 5) (Fig 3.2B). Co-transfection with P19 suppressed miR30 activity by a factor of 7 (compare blue bar, Fig 3.2B). By comparison, down-regulation of Dicer by Dicer-specific siRNAs likewise eliminated miR30 activity
(dicer siRNA, blue bars, Fig 3.2C) as compared to treatment with scrambled siRNAs (sc, tan bars) (Fig 3.2C). Real time RT PCR to quantify steady state mRNA levels showed that the copy number of luciferase mRNA did not change in response to P19 expression (data not shown). We used the mirR30 assay to compare suppressor activity of P19 with HIV-1
Tat, vaccinia virus E3L, influenza A virus NS1, and adenovirus VA1. miR30 reduced luciferase activity from pCMV-Luc8(x)-miR30 by a factor of five (blue bars, treatment group 1 and 2, Fig 3.2D). Statistically significant partial restoration of luciferase activity was observed for E3L, NS1, P19 and Tat and VA1 completely restored luciferase activity
(blue bars, Fig 3.2D, p<0.05). Real time RT PCR showed that the steady state level of luciferase mRNA was similar among all samples (tan bars, Fig 3.2D) and indicated that the increased luciferase activity was attributable to reversal of translation repression.
69
Figure 3.2. Tat suppresses miR30 function but does not block miR30 processing in human cells. (A) The luciferase RNA expressed from reporter plasmid pCMV-Luc-8(x)-miR30 contains eight miR30 target sites. Co-transfection of pCMV-miR30 is used to over-express miR30 pri-precursor that is processed by Drosha and Dicer to produce precursor miR30 and mature miR30, respectively. (B) Luciferase activity from HelaT4 cells at 48 h posttransfection with indicated plasmids determined that miR30 activity is reduced by P19. (C) Luciferase activity from HelaT4 cells at 48 h posttransfection with indicated siRNA and plasmids determined that miR30 activity is reduced by Dicer down-regulation. Firefly luciferase (F-Luc) activity from equivalent protein preparations. (D) Luciferase activity and luciferase RNA levels in 293 cells transfected with indicated RSS and miR30 reporter plasmid and miR30 expression plasmid. Equivalent protein preparations were assays for Firefly luciferase (F-Luc) activity. (E) Northern blot analysis with antisense miR30-specific RNA probe that detected precursor miR30 (pre-miR30) and mature miR30. Small RNAs were enriched and separated by 15% urea-PAGE. Lower panel was stained with ethidium bromide to control for minor differences in RNA loading (Data published in (169)).
70
Figure 3.2
71 Northern blotting with the antisense miR30 RNA probe on size fractionated RNA
was used to investigate the amounts of the 71 nt pre-miR30 and 22 nt mature miR30 (Fig
3.2E). Low but detectable endogenous miR30 was detectable (treatment group 1 and 2) and
abundant pre-miR30 and mature miR30 was observed upon transfection of pCMV-miR30
(treatment group 3). Similar levels of pre-miR30 were detected in E3L, NS1, Tat and P19
(treatment groups 4-7) and a reduction was observed in response to VA1 (treatment group
8). The ratio of pre-miR30 to mature miR30 was similar between empty vector control
(-suppressor) and E3L (1.2 and 1.4, respectively). The ratio was reduced in response to
NS1, Tat, and P19 (range 0.75 to 0.9), indicating no significant block in the processing of pre-miR30 to mature miR30. VA1 treatment resulted in baseline levels of pre-miR30 and mature miR30 and the appearance of a smaller species of pre-miR30 (treatment group 8) and supports the observation that VA1 serves as a decoy substrate for exportin 5, Dicer and
RISC (91;104). The accumulation of pre-miR30 and miR30 in the Tat treatment group indicated that, similar to the plant viral RSS P19, Tat does not disrupt the maturation of dsRNA, but reduces the efficiency of a downstream step in the RNA silencing pathway.
RNA silencing restricts HIV-1 Gag protein synthesis in human cells.
To determine whether the RNA silencing pathway inhibits gag mRNA translation,
Dicer was down-regulated in Hela T4 cells by transfection with Dicer-specific siRNAs
(170). Northern and Western blotting detected significant Dicer mRNA down-regulation
by 24 h and 48 h post-transfection (Fig 3.3A), and Dicer protein was down-regulated in
comparison to treatment with non-silencing scrambled control (sc) (Fig 3.3B, 48 hr
sample). These cells were transfected with HIV-1NL4-3 and virion production was measured 72 at 24 h, 36 h and 48 h post transfection. Dicer down-regulation increased virion production
four to seven-fold (Fig. 3.3C). Pulse labeling and Gag IP showed that the rate of Gag
protein synthesis was increased significantly by Dicer down-regulation (Fig. 3.3D,
p<0.05). By comparison, gapdh translation was not affected, as determined by GAPDH IP.
Analysis of CEMx174 lymphocytes infected with HIV-1NL4-3 yielded a similar increase in
Gag protein synthesis upon Dicer knockdown (data not shown). Meanwhile,
TCA-precipitable counts measuring 35S-cysteine/methionine incorporation were similar
between the samples treated with the Dicer-specific siRNAs (3.3 x 106 ± 8 x 105 CPM) and
the sc siRNAs (3 x 106 ± 6 x 105 CPM). The results demonstrate that HIV-1 replication in human cells is attenuated by RNA silencing and that down-regulation of the RNA silencing pathway significantly increases de novo Gag protein synthesis independently of general
effects on cellular protein synthesis.
73
Figure 3.3. Down-regulation of Dicer enhances the production of the HIV-1 structural protein in human cells. (A) Northern blot of total cellular RNA from HelaT4 cells transfected with dicer siRNA (dicer) or scrambled siRNA (sc) determined down-regulation of dicer mRNA at both 24 and 48 h post-treatment. (B) Immunoblot with Dicer and Grp78 antiserum determined down-regulation of Dicer protein at 48 h. (C) Down-regulation of Dicer enhanced Gag production in HeLaT4 cells transfected with HIV-1NL4-3. Gag ELISA was performed on cell-free medium from three independent transfections. Gag levels were normalized to cotransfected luciferase. (D) Immunoprecipitation assay determined that Dicer down-regulation increases rate of synthesis of Gag p55 but not GAPDH (Data published in (169)).
74
Figure 3.3
75 RNA silencing-mediated restriction of the HIV-1 Gag protein synthesis is suppressed
equivalently by Tat and P19.
We next evaluated whether Tat and P19 RSS rescue gag mRNA translation.
Flag-tagged P19 was expressed in HelaT4 cells and P19 was consecutively verified by
Western blotting at 12, 24, 36 and 48 hrs (Fig. 3.4A). At the 24 hr time point, the cells were
transfected with HIV-1NL4-3and virion levels were measured by Gag p24 ELISA on supernatant medium. P19 produced a significant increase in virion level at each time point
(Fig. 3.4B) but did not alter the copy number of gag mRNA (Fig 3.4C). Real time RT PCR
results revealed no change in gapdh or c-myc mRNA in response to P19 or HIV-1
expression (Fig 3.4C). The rate of Gag protein synthesis was assessed by pulse labeling
and Gag radioimmunoprecipitation (IP) experiments. The increase in virion level by P19
expression was attributable to increased Gag protein synthesis (Fig 3.4D). We next
compared virion production between HIV-1NL4-3 and the derivative provirus HIV-1/RSS
that contains the K51A mutation in the tat gene, which eliminates RSS activity but retains
transcriptional trans-activation activity (105). Gag ELISA results showed a significant reduction in virion production by a factor of five in response to K51A (tan bars, Fig 3.4E).
Expression of P19 was sufficient to complement the defect in virion production from
HIV-1/RSS, and bolstered virion production from HIV-1 (blue bars, Fig 3.4E). Real-time
RT PCR data showed no difference in the copy number of HIV-1/RSS gag mRNA nor gapdh and c-myc RNA loading controls in response to P19 (Fig 3.4F). These levels were also were unchanged in relation to HIV-1 (Fig 3.4C). Pulse labeling and Gag IP demonstrated that HIV-1/RSS leads to a significant reduction in the rate of Gag protein
76
Figure 3.4. Expression of P19 enhanced production from HIV-1 and HIV-1/RSS. (A) Immunoblot of HelaT4 cells transfected with indicated plasmids with Flag or beta-actin antiserum determined expression of P19-Flag fusion protein at indicated times post-transfection. (B) Gag production from HeLaT4 cells transfected with HIV-1NL4-3 was reduced by P19 RSS. Gag ELISA was performed on cell-free medium from three independent co-transfections of HIV-1NL4-3 and pCMV-P19FL (P19) or empty vector (pCAM). Gag levels were normalized to cotransfected luciferase. (C) P19 expression did not change steady state levels of HIV-1 gag, c-myc or gapdh transcripts. Evaluation of total cellular RNA preparations from three replicate transfections by reverse transcription and real time PCR with HIV-1 gag, c-myc and gapdh specific primers. (D) IP assay demonstrated that P19 expression increases rate of synthesis of HIV-1 Gag p55 but not GAPDH. (E) Gag production from HeLaT4 cells transfected with HIV-1NL4-3 or HIV-1/RSS was increased by co-expression of P19 RSS. Gag ELISA was performed on cell-free medium from 3 independent co-transfections of indicated provirus and pCMV-P19FL (P19) or empty vector (pCAM). Gag levels were normalized to cotransfected luciferase. (F) P19 expression did not change steady state levels of HIV-1/RSS gag, c-myc or gapdh transcripts. Evaluation of total cellular RNA preparations from three replicate transfections by reverse transcription and real time PCR with HIV-1 gag, c-myc and gapdh specific primers. (g) IP assay determined that P19 expression increases rate of synthesis of HIV-1/RSS Gag p55 but not GAPDH (Data published in (169)).
77
Figure 3.4
78 Figure 3.5. Tat is the viral RSS and the plant viral RSS P19 can replace Tat RSS activity. Quantification of Gag immunoprecipitation assay results of Fig 3.4C and Fig 3.4F. Introduction of K51A mutation in HIV-1/RSS reduces Gag production and P19 expression increases rate of HIV-1 and HIV-1/RSS Gag protein synthesis to similar levels (Data published in (169)).
synthesis (Fig 3.4G right panel) and that P19 expression significantly increased the rate of
Gag protein synthesis (Fig 3.4G left panel). As summarized in Fig 3.5, these IP data indicated that the K51A mutation reduced Gag protein synthesis by a factor of three (tan squares, HIV-1 + pCAM; tan circles, HIV-1/RSS + pCAM). Similar to the Gag ELISA results, P19 expression bolstered Gag protein synthesis to above the level of HIV-1 + pCAM (compare to blue squares and circles). Measurement of TCA-precipitable counts revealed similar levels of 35S-cysteine/methionine incorporation in the P19 treated cells
(4.2 x 106 ± 1 x 106) and the pCAM control (3.2 x 106 ± 3.8 x 105 CPM). Statistical analysis
by Dunnett's method determined no significant difference in de novo cellular protein
production (p=0.2273). Likewise, metabolic labeling with 3H–uridine demonstrated no
significant difference in total cellular RNA synthesis during the 1 h labeling period (P19 79 treatment: 5.2 x 105 ± 1.8 x 104 and the pCAM control: 6 x 105 ± 1.3 x 104 CPM). The results demonstrated that Tat and P19 increase the translatability of HIV-1 gag mRNA.
80 DISCUSSION
Our data indicate that the production of HIV-1 Gag proteins and thereby, production of virus particles, is restricted by RNA silencing, which confirms the results of
De Vries et al., 2007 (109). Furthermore, our results suggest that HIV-1 Tat serves as the viral RSS and counters translation inhibition by RNA silencing that is attributable to cell-encoded miRNAs (12;110)). The observation that virion production from an HIV-1 strain lacking RSS activity is severely attenuated indicates that Tat RSS promotes acute
HIV-1 infection. Heterologous plant virus P19 RSS is sufficient to overcome translational
RNA silencing and provides a mechanistic explanation for the observation that Ebola V35 can replace Tat RSS activity (99). HIV-1 Tat and TBSV P19 also co-segregate in their loss of activity by point mutation of the dsRNA-binding domain. Our results showing reversal of translation repression by a plant RSS support the recent finding in Arabidopsis that plant miRNAs operate by translational inhibition (171). Our IP results taken together, with
Northern analyses in human cells and N. benthamiana cells suggest that the underlying mechanism of RNA silencing suppression by human virus Tat and plant virus P19 are related. The Northern analyses demonstrated that Tat and P19 did not reduce maturation of dsRNA duplexes and suggested that they use a common mechanism to prevent guide strand programming of RISC. We also showed that influenza A virus NS1 RSS also relies on si/miRNA-binding, whereas vaccinia virus E3L functions upstream and relies on binding to long dsRNAs, thereby preventing their processing into mature si/miRNAs.
81
CHAPTER 4
INTERPLAY OF HIV-1 ACCESSORY GENES AND HOST MIRNAS ACTIVITY UPREGULATES VIRAL RNA EXPRESSION
ABSTRACT
Human immunodeficiency virus type 1 (HIV-1) employs multiple strategies
including manipulation of the host microRNA pathway to interface with the host gene
expression machinery to produce progeny virions and to counter innate host responses that
guard against infectious agents. Herein, we asked whether HIV-1 accessory gene Vpr and
Vif interface with the host miRNA pathway to modulate virus replication. Quantitative
RNA analysis determined that cells infected with HIV-1 exhibit a higher steady state gag
RNA level in comparison to vpr- or vpr/vif-deficient HIV-1. Moreover, the increase in
steady state gag RNA in HIV-1 offsets a generalized decline in viral RNA translational
efficiency during progression of infection. Microarrays of host cellular miRNAs in
cultures acutely infected with HIV-1, vpr/vif deficient HIV-1, or uninfected CEMx174
lymphocytes were performed. A subset of miRNAs were differentially affected by HIV-1
and vpr/vif-deficient HIV-1, including a miRNA cluster affected in leukemia and two
miRNAs previously shown to downregulate PCAF, a cellular transcriptional cofactor of 82 Tat. Transfection experiments determined that expression of HIV-1 but not the vpr/vif
deficient mutant was sufficient to downregulate the activity of these miRNAs and
upregulate PCAF expression. Our results provide a mechanistic explanation for the
upregulation of HIV-1 transcription during virus-induced cell cycle arrest. We conclude
that host miRNA activity is modulated in response to the activity of HIV-1 Vpr/Vif
accessory proteins and correlates with upregulation of HIV-1 transcription that is attributable to PCAF activity. This translational upregulation offsets a generalized decline in protein synthesis in the infected cells. We speculate that Vpr/Vif modulation of host miRNA activity contributes to the positive selection for maintenance of Vpr/Vif in patient quasi-species.
83 INTRODUCTION
Eukaryotic cells use the small RNA pathway to execute RNA interference and
post-transcriptionally modulate a variety of biological processes including developmental
timing, signal transduction, apoptosis, cell proliferation, cell cycle progression,
tumorigenesis and virus replication (37;56;79;172-176). Studies in plant virus systems
have demonstrated that the small pathway is an effective innate defense strategy to limit
viral replication and pathogenesis. Plant virus strategies to overcome this innate response
include virus-encoded RNA silencing suppressor (RSS) (96;160;177;178) and/or
virus-encoded miRNAs that downregulate the components and activity of the small RNA
pathway machinery (179). Animal viruses also have been reported that exhibit interplay
with the small RNA pathway. For example, human hepatitis C virus (HCV) uses host
miRNA122 to promote virus infection (95), and Epstein-Barr virus (EBV) modulates host-
and virus-encoded miRNAs to promote virus growth and immortalization of the host cell
(83;85;180). Chronic HIV-1 infection has been shown to alter cellular miRNA expression
and assist viral persistence (12;110). Microarray and northern blot analyses of Jurkat cells
after 21 days of HIV-1 infection identified that the host miR-17-92 cluster was
downregulated by a factor of 2 (12). Biochemical analysis showed that cluster members
miR-17-5p and miR-20a target to p300/CREB-binding protein-associated factor (PCAF)
and were sufficient to reduce HIV-1 replication. Functionally, PCAF acetylates the Lys28 residue in the activation domain of Tat, which enhances Tat binding to the Tat-associated kinase, CDK9/P-TEFb. This stimulates Tat transactivation of HIV-1 transcription (181).
PCAF also acetylates the lys50 residue of Tat which increases the binding affinity to Tat.
84 This PCAF-Tat association reduces Tat binding to TAR, which is expected to allow release of TAR-containing mRNA.(182). Therefore PCAF activity is important for robust HIV-1 transcription, and modulation of the level of PCAF is expected to modulate expression of
HIV-1 RNA.
The HIV-1 Tat protein is an essential regulatory protein of viral transcription. In addition to transcriptional transactivation, Tat exhibits RSS activity that mechanistically resembles plant viral protein P19 (tomato bushy stunt virus, TBSV) (169). P19 overcomes
RNA interference of viral gene expression and is necessary for viral pathogenesis
(reviewed in (109)). We have shown that HIV-1 Tat and TBSV P19 function reciprocally across the plant and animal kingdoms to suppress the small RNA pathway by affecting the small function downstream of maturation (169). Furthermore, RNA silencing in HIV-1 infected human cells severely attenuates the translational output of the unspliced HIV-1 gag mRNA, and possibly additional HIV-1 transcripts (169). It remains to be determined whether other HIV-1 gene products also play redundant roles in the virus replication cycle by modulating virus interaction with the host small RNA pathway.
The viral accessory protein viral protein R (Vpr) was initially identified as a transcriptional activator (183;184). Vpr has been extensively investigated for its necessary role in HIV-1 induced cell cycle arrest, which is attributable to inhibition of the cellular
CDC34-CyclinB kinase complex (185-187). Recently the viral infectivity factor (Vif) accessory protein was shown to also contribute to cell cycle arrest by HIV-1 (188-190).
Because miRNA activity is known to modulate cell cycle progression (173-176;191), an
85 open issue is whether or not Vpr/Vif affect miRNA expressed during HIV-1 infection.
Herein we compared the profile of miRNA levels in cells acutely infected with HIV-1 or vpr/vif-deficient HIV-1. We characterized general trends in miRNA profiles and the activity of two miRNAs in the miR-17-92 cluster.
86 MATERIALS AND METHODS
Plasmids and cells
HIV-1 proviral clone NL4-3 was obtained from AIDS Reagent Reference Program.
Vpr-deficient HIV-1 provirus pNL4-3-VprX (192;193) and pNL101-∆Vif were obtained from V. Planelles (190). ∆VifVpr was constructed by replacing Vif open reading frame in pNL4-3-VprX with ∆Vif from pNL101-∆Vif by NheI-PflMI restriction digest. pHRvprIRESgfp (194) was obtained from V. Planelles and pHR-IRESgfp was constructed by removing vpr sequences from pHRvprIRESgfp by SalI-XhoI restriction digest. The miRNA luciferase reporters (Signosis, Inc Sunnyvale, CA) contain a unique miRNA target site that is a sequence perfectly complementary to miR-17-5p or miR-20a at the 3’UTR of firefly luciferase gene. Flag-P19 expression plasmid PCMVP19FL was constructed from pRTL2P19 and pCMVMS2FL as described in Chapter 3.
CEMx174 human lymphocytes were grown in RPMI with 10% fetal bovine serum and 1% antibiotic-antimycotic (Gibco). HEK293 cells were grown in DMEM with 10% fetal bovine serum and 1% antibiotic-antimycotic (Gibco).
Transfections, infections and flow cytometry
All plasmid transfections were conducted with Fugene 6 (Roche) based on manufacturer instruction. HIV-1 virions were propagated by transfection of HEK293 cells with 10 µg of wild-type or mutant HIV-1NL4-3. After 12 hours transfection, supernatant medium was harvested every 12 hours for 3 collections. Producer cells were generated by culturing cell-free supernatant medium containing HIV-1 virions (3x108 pg/ml of Gag) with CEMx174 cells (1x106). After 48 hours incubation, viable cells were isolated on 87 Ficoll and these HIV-1 producer cells were co-cultured with target cells at a ratio of 1:10
and progression of the infection was evaluated by FACS of intracellular Gag. The
intracellular staining of Gag utilized FITC conjugated anti-p24 antibody (KC57-FITC,
Beckman Coulter). Cells were fixed and permeabilized with Cytofix/ Cytoperm kit (BD
Biosciences) as described by manufacturer protocol.
Metabolic labeling and immunoprecipitation
Uninfected and infected cells were pre-incubated 30 minutes in RPMI with 10%
dialyzed FBS that lacked methionine and cysteine, and 5x105 cell aliquots were metabolically labeled with 50 µCi/ml [35S] Cysteine/Methionine (MP Biomedicals) for 1
hour. Cells were washed with PBS twice at room temperature and lysed in 100 µl RIPA buffer (50mM Tris pH 8.0, 0.1% SDS, 1% Triton-X, 150mM NaCl, 1% deoxycholic acid,
2mM PMSF). For radio-immunoprecipitation, 1 µl of Gag antibody (195) or 1 µl actin
antibody (ab6276, Abcam) was incubated with 50 µg lysate for equal mass or 50 µl lysate
for equal volume along with Protein A Sepharose beads (GE Healthcare). For TCA
precipitation, radioactively labeled 50 µl or 50 µg cellular lysate was mixed with 10%
TCA, 50 µg bovine serum albumin and 0.01% sodium azide on ice for 30 min.
Unincorporated radioactive amino acids were eliminated by filtering the precipitate
through glass fiber filter discs and washing with 10% TCA twice, followed by dehydration
with 100% ethanol twice. Radioactive protein in precipitates was determined by
scintillation counter. For pulse-chase, 293 cells were pre-incubated with DMEM media
and 10% dialyzed FBS which lacked methionine and cysteine (Invitrogen) and then
labeled for 30 minutes with 50 µCi/ml [35S] Cysteine/Methionine. Cells were washed with
88 fresh DMEM and harvested at 0, 2, 4, 6, 8 and 20 hours in RIPA buffer and subjected to
Gag and Actin immunoprecipitation. Images were captured by Typhoon imager (GE
Healthcare).
Reverse transcription and real-time PCR
Total RNA was isolated with Trizol reagent (Invitrogen). RNA was denatured at
65ºC for 5 min and converted into cDNA with Sensiscript RT kit (Qiagen) by manufacturer
protocol in the presence of random hexamer primers. Equivalent volumes of cDNA (10%
of total reaction volume) were used for standard PCR amplification or real-time PCR
quantification on Lightcycler (Roche). The sequences and PCR conditions of gag and actin
were described previously (9). The primer sequences for pcaf amplification were: Forward
5’CTTGGATTCCAGTTTAGTGC3’, Reverse 5’GCACTAAACTGGAAT CCCAAG3’.
HIV-1 Gag ELISA, luciferase assay and immunoblotting
Cell medium and cell lysate from HIV-1 transfected or infected samples were
harvested at the indicated time points. HIV-1 Gag production was determined by
commercial enzyme-linked immunosorbent assay (ELISA) kit (Zeptometrix) according to
manufacturer instruction. Twenty µL of cell lysate was used for luciferase assay with
luciferase reagent (Promega). Bradford assay was used to measure protein concentration
and 50 µg protein was subjected to SDS-PAGE and transferred to nitrocellulose membrane. Immunoblotting was performed with mouse monoclonal antibodies against
PCAF and β-actin (Abcam, Cambridge, MA).
89 Microarray probes, hybridization and analysis
Total RNA from CEMx174 lymphocytes was isolated with Trizol reagent
(Invitrogen) from cells evaluated for HIV-1 infection by intracellular Gag staining.
Biotin-labeled complementary DNA was generated by reverse transcription. Hybridization was performed at The Ohio State University Comprehensive Cancer Center genomics core facility on miRNA microarray chips (OSU_CCC version 4.0) that contain 906 human miRNA probes that are spotted in duplicate. The chip captures 522 mature miRNAs and
336 precursors(196). GenePix Pro 6 image analysis software was used to quantify the detected signals by the array scanner. Background subtracted signal intensity was obtained for each spot on the chip and averaged over duplicate probe sets before log base 2 transformation. Quantile normalization was performed to adjust experimental variation among chips (197). Normalized expression values of each miRNA probe set were
averaged over two samples of each virus infection. Fold ratios were then calculated
between virus infections. Blank spots on the chip were used to evaluate the signal
measurement uncertainty. Statistical software R (198) was employed for data manipulation
and generating expression scatter plots. The heat map of miRNA expressions was
generated by MeV software (199).
90 RESULTS
Global protein translational suppression is attributable to HIV-1 accessory proteins
Vpr and Vif, but Gag protein translation is not suppressed during cell cycle arrest
Recent analysis of HIV-1 molecular clones demonstrated that vif mutation in
combination with vpr mutation is necessary to completely abolish HIV-1-induced cell
cycle arrest, indicating that the viral protein Vpr and Vif both contributed to virus-induced cell cycle arrest (185;188;190). To evaluate whether or not translation suppression is attributable to HIV-1 induced cell cycle arrest, vpr-deficient (VprX) and vpr/vif-deficient
(∆VV) proviral clones were propagated and acutely infected cells were evaluated by the metabolic labeling assay. In a representative assay (Figure 4.1A), the percentage of infected cells was >77% for HIV-1, >81% for VprX, and >65% for ∆VV (Data not shown).
HIV-1 and VprX increased the proportion of G2M cells from 10% to 29% and 25%,
respectively, and significantly reduced TCA-precipitable counts by 60% and VprX by
25%, respectively ( p < 0.0001) (Figure 4.1A). By comparison ∆VV did not increase G2/M cells (14%), nor change TCA-precipitable counts (p =0.8062). For each culture,
Noc-treatment increased the proportion of G2M cells to 40-46% and significantly reduced
TCA-precipitable counts (p < 0.0001). The lack of concordance by ∆VV demonstrated that
the translation suppression is attributable to virus-induced cell cycle arrest. Our results recapitulate published results that both Vpr and Vif contribute to HIV-1-induced cell cycle arrest (188;189), and demonstrate for the first-time that cell cycle arrest induced by Vpr and Vif suppresses global cellular translation. Gag immunoprecipitation (IP) experiments were performed with equivalent numbers of cells infected with HIV-1, VprX or ∆VV
(>80% infection at 40 hr). By 40 hrs post-infection, Gag protein production was sustained
91 in among the infections, despite differences in host translation (Figure 4.1B). Noc treatment decreased TCA-precipitable counts and de novo Actin synthesis, but did not significantly reduce Gag production (Figure 4.1B). These metabolic labeling results suggest that translation of HIV-1 gag mRNA is sustained in the face of HIV-1-induced suppression of global cellular translation.
Upregulation of HIV-1 steady state gag RNA offsets generalized impairment of host translation machinery
The initial phase of viral infection is characterized by expression of HIV-1 regulatory genes, which subsequently trans-activate expression of accessory and structural genes. We sought to determine whether translational output of HIV-1 gag RNA is changed in concert with Vpr/Vif-induced suppression of the host translation. Time course experiments measured translational output of HIV-1 gag RNA before and during cell cycle arrest induced by Vpr and Vif accessory proteins. Four experiments were performed on
HIV-1, ∆VV or VprX infected cells at intervals beginning at 8 hr post-infection.
Intracellular Gag staining measured the progression of the HIV-1 infection, RT-real time
PCR measured steady state gag mRNA, and the 1 h metabolic labeling and IP measured de novo Gag protein synthesis. As shown in representative experiments, HIV-1 infection reached 60- 75% by 40-48 h (Figure 4.2A and Figure 4.3A). HIV-1 Gag synthesis was readily detectable by 12-16 h and increased as the infection progressed (Figure 4.2B, 4.2C and Figure 4.3B, 4.3C). Compared to HIV-1, de novo Gag protein synthesis in cells infected with ∆VV (Figure 4.2B, 4.2C) or VprX (Figure 4.3B, 4.3C) followed similar trends, but the abundance of Gag was typically lower at each time point. Quantitative
92 real-time PCR demonstrated increasing steady state gag RNA as the infections progressed
(Figure 4.2D, 4.3D). The gag RNA copy number was consistently greater for HIV-1 than
∆VV or VprX (Figure 4.2D and Figure 4.3D), consistent with published results that Vpr
increases HIV-1 RNA level (200;201). The results indicated that the delayed progression of the ∆VV and VprX infections is attributable to a lag in the gag mRNA expression, and
not a lag in translation of the mRNA. The infections displayed similar trends in the
efficiency of de novo Gag synthesis (Figure 4.2E and Figure 4.3E). These results
confirmed the result of Figure 4.1 that gag translational efficiency is sustained during progression of virus infection, despite cell cycle arrest.
Trends in host miRNA profile in lymphocytes infected with HIV-1 or vpr/vif-deficient
HIV-1
The results above indicated that Vpr/Vif activity upregulated the HIV-1 RNA steady state level. We further asked whether or not modulation of host microRNA contributed to
Vpr/Vif activity. Microarrays of human lymphocytes cultures infected with HIV-1, ∆VV or uninfected provided a sampling of the interface between HIV-1 and host miRNAs.
Human CEMx174 cells were infected with HIV-1 or ∆VV by co-culture for 40 to 48 hr
(Fig 4.4a). Intracellular staining of Gag and FACS determined that the majority of cells were infected (90% to 95%) (Fig 4.4b), which determined the majority of cells were infected with virus. Total RNA was isolated and the RNA quality was evaluated on an
Agilent Bioanalyzer. As shown in Fig 4.4c, the Mock sample showed three ribosomal
RNA bands that represent intact 5S, 18S and 28S ribosomal RNA species and lacked discernible RNA degradation. The ∆VV sample exhibited ribosomal RNA species and
93 heterogeneous RNA species, while the HIV-1 infected RNA sample displayed
heterogenous RNA species consistent with more robust RNA degradation but similar overall RNA signal intensity (Fig 4.4c). The microarray was performed by the Ohio State
University genomics core on chips that contain 906 human microRNA probes that represent 522 miRNAs. The chips were probed with total RNA processed as summarized
Figure 4.4d in two independent infection and array experiments. The biostatistical analysis determined similar magnitude of signal intensity across the microarray chips, which indicated similar efficiency of sample labeling and array hybridization (Fig 4.5) The trends in miRNA expression between HIV-1 infection and Mock treatment were illustrated by scatter plots that highlight the proportion of miRNA probes that exhibit a 1.5-fold difference (blue lines), and also a 2-fold or greater difference (red lines) (Figure 4.6). Axes are truncated at log2 = 5 to eliminate measurement uncertainty at lower signal intensities.
As illustrated in Figure 4.6a and 4.6b, infection with HIV-1 or ∆VV substantially changed
the miRNA expression profile of the cells, as shown by the miRNA probe dots allocated to
positions outside of the +2 and -2 fold red lines. However, comparison of the two virus
strains determined less robust change (Figure 4.6c). We only observed 5 mature miRNAs
were upregulated more than 2 fold in HIV-1 infection compared to ∆VV infection
(miR-496, miR-32, miR-199a, miR-194-2 and miR-324-3p) in a range from 2.02 to 6.15
and 3 miRNA precursors (miR-323, miR-340 and miR-564) that were upregulated moe
than 2 fold in HIV-1 infection compared to ∆VV infection. We also identified 1 mature
miRNA was downegulated more than a factor of 2 (miR-450-2) (Table 4.2 shown in gray).
The observation that majority of the miRNA probes were allocated to positions inside of
94 the +2 and -2 fold red lines when we compared these two viruses infection (Figure 4.6c).
Indicating other viral proteins may also involved in regulating host microRNA expression.
The absolute signal intensities of the miRNA probes in Mock, HIV-1 and ∆VV samples were compared using a 1.5-fold difference in signal intensity as a threshold and the miRNAs were divided into three categories. MiRNA probes expression intensities lower than 32 in HIV-1 and ∆VV infection were eliminated as measurement uncertainty.
The miRNA probes that exhibit a reduction by a factor of 1.5 or more were designated downregulated (Down). Probes that exhibit a 1.5-fold or more increase in signal intensity were designated upregulated (Up) (Table 4.1). The miRNA probes that exhibit differences in signal intensity between these parameters (1/1.499-1.499) were designated minimal change. These miRNA probes signal intensities below 32 were elimited as referred as not determined. As summarized in Table 4.1, comparison of HIV-1 infection to mock treatment detected downregulation of 161 miRNA probes and upregulation of 212 miRNA probes. When we compared ∆VV to mock treatment samples, we observed 162 miRNA probes were downregulated and 210 miRNA probes were upregulated. However, comparison of HIV-1 infection to ∆VV infection detected downregulation of only 28 miRNA probes upregulation of 38 miRNA probes (Table 4.1). These data indicate that
HIV-1 infection changed the host miRNA expression profile and vif/vpr contributed to the change in miRNA profile. Table 4.2 lists miRNA probes expression level comparison in
HIV-1 and ∆VV virus infection and mock infection.
Real time RT-PCR with previously established primers was used for independent assessment of 6 precursor miRNAs (202). Real time RT-PCR on RNA from HIV-1 infected cells or mock-infected cells determined the precursors of miR24, miR27a,
95 miR144 miR29a were down-regulated by a factor of 2.1 to 2.9, which was similar in magnitude to the microarray downregulation by a factor of 3.1 to 3.9 (Table 4.3). The upregulation of let-7d-V2 was 3.4-fold in the real time PCR and 4-fold in the microarray
(Table 4.3). The results indicate that the trends in representative miRNAs observed in the miRNA microarrays were similar to trends observed by real-time RT-PCR on independent
RNA samples.
Three miRNA clusters members are differentially affected in HIV-1 but not ∆VV
A miRNA cluster is a gene locus that encodes a polycistronic primary precursor miRNA that is processed to produce several mature miRNAs (203;204). An example of coordinate regulation of a miRNA cluster is miR-17-92 the primary precursor transcriptionally upregulated by c-Myc (205). Here, we asked whether or not HIV-1 and
∆VV infection modulate expression of 3 miRNA clusters. We observed that the absolute signal intensity of mature miRNA of the miR-17-92 cluster, miR-29a,b-1 cluster or miR-29b-2,c cluster were downregulated in HIV-1 infected cells compared to mock infected cells (Table 4.4). Precursors of miR-92-1 and miR-29a were not downregulated.
For the cluster 17-92, the range of downregulation in HIV-1 infected cells compared to mock infected cells of the mature miRNA was 0.28 to 0.71. These results agree with the report of modulation of the miR-17-92 cluster during chronic HIV-1 infection in Jurkat cells (12). We further asked whether or not Vpr/Vif contributed to modulate miRNA cluster expression. We observed that ∆VV regulated miRNA cluster members’ expression less robust (Table 4.4). Comparison the ratios of HIV-1 infection versus ∆VV infection, the three miRNA cluster expression (range from 0.76 to 1.40) were in the category of
96 minimal change (range from 0.66 to 1.50) (Table 4.4). These data indicated additional viral
gene products or virus-host interaction contribute to miRNA cluster modulation.
HIV-1 downregulation of miR-17-5p and miR-20a function correlates with
up-regulation of PCAF
Recently two members of the miR-17-92 cluster were identified to target PCAF
RNA: miR-17-5p and miR-20a (12). Our microRNA microarray data supported this observation and we observed that miR-17-5p was downregulated at a factor of 1.82 and
miR-20a was downregulated by a factor of 1.87 in HIV-1 infection compared to mock
infection (Table 4.2). Here we further addressed whether or not HIV-1 accessory gene
vpr/vif modulate miR-17-5p and miR-20a function. Luciferase reporter plasmids were
obtained that contain a single copy of the miR-17-5p or miR-20a target site introduced into the 3’UTR of the luciferase reporter gene, and used to test modulation of miR-17-5p or miR-20a activity by HIV-1 or ∆VV (Figure 4.7a). Cultures of 293 cells were transfected with HIV-1 or ∆VV proviral plasmid or mock transfection for 24 hours, and then
transfected with luciferase-miR target reporter plasmid and Renilla luciferase transfection
control and incubated for 48 hours. Total cell protein was harvested for dual luciferase
assay. F-luc numbers were normalized to R-Luc transfection efficiency control. HIV-1
expression resulted in a 2.25-fold increase in luciferase activity from the miR-17-5p
reporter and 3.6- fold increase from the miR-20a reporter in comparison to the mock
control (Figure 4.7b). ∆VV expression caused 1.5-fold increase in luciferase activity from the miR-17-5p reporter and 2-fold increase from miR-20a reporter in comparison to the mock control. In comparison to ∆VV infection, HIV-1 downregulated luciferase activity 97 from the miR-17-5p reporter by a factor of 1.5. Luciferase activity from the miR-20a reporter was downregulated by a factor of 1.8.
Triboulet et al. reported that chronically HIV-1 infected Jurkat cells upregulated
PCAF protein expression. Treatment of Jurkat cells with specific locked-nucleic
-acid-modified oligonucleotides to inhibit miR-17-5p and miR-20a activity correlated with
3-fold induction of HIV-1 Gag expression (12). To evaluate whether or not Vpr/Vif are
sufficient to upregulate PCAF, immunoblotting with PCAF antiserum was performed. The
immunoblots evaluated 5 µg aliquots of cell lysate from three independent replicate
experiments. Comparison of PCAF protein in the bulk cultures determined PCAF levels
were slightly increased in the ∆VV sample than mock treatment (Fig 4.7c). PCAF
increased 2-fold in the HIV-1 sample compared independently of a change in B-Actin. Gag
proteins p55, p41 and p24 were detected by anti-Gag immunoblotting during provirus
transfection but not the mock control, indicating HIV-1 and ∆VV were expressed (Fig
4.7c).
Taken together, we observed that HIV-1 vpr/vif accessory gene contribute to global
cellular translation suppression. However gag translation is not suppressed during
infection with vpr/vif-deficient HIV-1. Instead steady state gag mRNA is reduced
consistent with reduction in HIV-1 transcription. HIV-1 infection reduced miR-17-5-p and
miR-20a levels in CEMx174 cells and 293 cells. This reduction was attenuated in
vpr/vif-deficient HIV-1 infection. Expression of Vpr/Vif downregulated miR-17-5-p and
miR-20a activity on luciferase reporter RNA and upregulated PCAF protein expression in
human 293 cells. The upregulation of PCAF in HIV-1 infected cells is attributable, at least
in part, to Vpr/Vif modulation of miR-17-5p and miR-20a.
98 DISCUSSION
HIV-1 and ∆VV acute infection modulates cellular miRNA expression
Herein miRNA microarrays identified patterns of cellular miRNAs that are modulated during infection with HIV-1 and vpr/vif deficient HIV-1 in human CEMx174 lymphocytes. This microarray database is informative to develop specific hypotheses of the interplay between host small RNA pathway and HIV-1. A challenging issue is the ability of one particular miRNA to affect a population of target RNAs, which is governed
by a collection of 6 nt seed sequences (37). Previously, Triboulet et al. identified that the
miR-17-92 cluster members miR-17-5p and miR-20a target the PCAF transcript (12). We
extended the results of Triboulet et al. 2007 (12) and identified that expression of Vpr/Vif
is sufficient for downregulation of miR-17-5p and miR-20a activity in our luciferase
reporter system. Experimentation with cell cycle arrest mutants of Vpr or pharmaceutical
drug nocadazole (Noc, induce cell cycle G2 arrest) did not induce this change of
miR-17-5p and miR-20a expression (data not shown). These data indicated that modulation of miR-17-5p and miR-20a expression by viral protein is not attributable to generalized cell cycle arrest.
In conclusion, Vpr/Vif down-regulation of miR-17-5p and miR-20a function in
HIV-1 infected cells correlates with upregulation of PCAF protein. In turn, PCAF upregulation correlates with increased HIV-1 transcription during Vpr/Vif-induced cell cycle arrest (206). In the future, additional targeted analysis of cellular miRNAs identified in miRNA microarray experiments is needed. Our results indicate that HIV-1 interfaces
99 with the host small RNA pathway by affecting expression of host factor PCAF that is required for efficient virus replication.
Vpr/Vif modulation of PCAF facilitates viral gene transcription and sustains gag translation during cell cycle arrest
Recently, Legesse-Miller et al. reported that cellular miRNA let-7 overexpression caused cell arrest at G2/M by downregulation of Cdc34 (191). Our microarray analysis identified that let-7d was upregulated by HIV-1 by 4.2-fold. Here we observed that HIV-1 infected cells transcribe 3-fold more gag mRNA than ∆VV infected cells after 48 hours infection and support the model that the lower level of gag mRNA transcription with ∆VV infection is due to decreased PCAF expression. We demonstrate that HIV-1 infection suppresses host cell translation by approximately 60% and this translational suppression is attributable to cell cycle arrest induced by the Vpr and Vif accessory proteins. Because retroviruses are reliant on the host translational machinery to catalyze viral protein synthesis, the impairment of host translation secondary to viral infection (207-210) poises a potential deterrent to virus production. Kinetic analysis before and during HIV-1-induced cell cycle arrest and in vpr/vif-deficient molecular clones revealed that HIV-1 gag mRNA translation efficiency is not reduced and implicate a viral strategy to overcome this potential deterrent to virus protein production. The upregulation of HIV-1 transcription by
PCAF contributes to virus retains robust expression during this cellular suppression barrier during G2 arrest.
100 In conclusion, this report documents for the first-time that HIV-1 vpr/vif modulate cellular miRNA activity. The activity of miR-17-5p and miR-20a target a cellular viral co-factor PCAF and facilitate robust viral expression during cell cycle arrest induced by virus infection. Our informative microRNA microarray database is useful to investigate the interplay of host miRNAs and HIV-1. For example, our results connect HIV-1 induced cell cycle arrest to the recent report that cellular miRNA let-7 overexpression causes cell cycle arrest at G2/M by downregulation of Cdc34 (191). Our microarray analysis identified that let-7d was upregulated by HIV-1 by 4.2 fold, and suggests a fresh idea that HIV-1 modulates the host cell cycle progression by regulation of the host small RNA pathway.
101
Figure 4.1. HIV-1 accessory proteins Vpr and Vif are necessary for HIV-1-induced suppression of cellular translation.
(A) One-hour metabolic labeling with [35S]-cysteine/methionine of CEMx174 cells that were Mock-infected or infected with HIV-1, VprX or ∆VifVprX after incubation without or with nocodazole (Noc). The histogram represents average TCA precipitable counts of incorporated [35S] and standard deviation from three independent experiments. Asterisks indicate significant reductions (p < 0.05) as summarized in text for all of the infection except ∆VifVprX (p =0.8062). Noc treatment significantly reduced de novo protein synthesis in all infections. Propidium iodide staining intensity and ModFit analysis demonstrates the number of cells in G1 or G2/M and percentages are summarized below each plot. (B) Comparison of de novo HIV-1 Gag protein production without and with Noc-treatment. Results of two independent immunoprecipitation assays on acutely infected cells. Summarized below the phosphorimage are the results of TCA precipitation assay and the percent of infected cells demonstrated by intracellular staining of Gag. Positions are designated of Gag p55 precursor protein, p37 processing intermediate and p24 and cellular Actin protein (Figure provided by Alper Yilmaz).
102
Figure 4.1
103
Figure 4.2. Kinetics of gag RNA translation efficiency in wild-type HIV and ∆VifVprX infected cells. (a) Percent of cells infected at each time point by HIV (black bar) or ∆VifVprX (gray bar) determined by intracellular p24 Gag staining with FITC conjugated antibody and FACS. (b,c) Immunoprecipitation of equal volume of metabolically labeled whole-cell extracts with antibodies against p24 Gag and Actin were separated on SDS-PAGE. Phosphorimager quantification of Gag bands in each lane plotted, HIV (solid line) and ∆VifVprX (dashed line) Gag levels were normalized to immunoprecipitated and quantified Actin levels. (d) Real-time RT-PCR analysis gag mRNA at each time point from total cellular RNA isolated from HIV (solid line) or ∆VifVprX (dashed line) infected cells. Copy number of gag mRNA was normalized to actin mRNA copy number. (Figure provided by Alper Yilmaz)
104
Figure 4.2
105
Figure 4.3. Kinetics of gag RNA translation efficiency in wild-type HIV-1 and VprX infected cells. (a-e) as described in Fig. 4.1. (Figure provided by Alper Yilmaz.)
106
Uninfected CEMx174 b a Incubate with viron equivalent to 3x108 pg/ml of Gag per 1x106 cells Isolate viable cells by Ficoll after 48 hours 95% 90% 100 Co-culture 90 ratio 1:9 80 Infection producer: native cells 70 Culture 40-48 hours 60 50 Determine infection percentage by internal Gag staining 40 Isolate viable cell on Ficoll 30 20 Total RNA extraction by Trizol 10 ND 0
Percentagecells has signal Gag/FITC of Mock HIV-1 ∆VV c
Time Time Ladder Mock HIV ∆VV
d Total RNA cDNA labeling array hybridization washing scanning Data processing
Figure 4.4. Procedures and main steps of miRNA expression profiling. (a) Flow chart of virus infection and RNA preparation. Cultures of HIV-1- and ∆VV-infected CEMx174 cells were prepared by coculture, as described. (b) Percentage of each culture that exhibited intracellular staining of HIV-1 Gag indicated that the majority of cells were infected. (c) RNA samples were evaluated by bioanalyzer and displayed differences in quality attributable to RNA degradation. (d) Total RNA were labeled and hybridized to the microarray chip and the data were processed for statistical analysis.
107
a
Figure 4.5. Box plots of signal intensity range of 906 miRNA probes. Intensities of four replicates per chip of each miRNA probe were averaged before log2 transformation. Quantile normalization was performed to adjust experimental variation among chips. The median value is represented by a line within the rectangular box.
108
Figure 4.6. Scatterplot analysis of the changes in miRNA probe expression in human CEMx174 lymphocytes infected with HIV-1, vif/vpr-deficient HIV-1 (∆VV), or mock-infected. Signal intensity of individual miRNA probes was collected, averaged and converted into log2 values. Each datum point represents replicate analysis of one unique probe sequence. The black line at x = y denotes unchanged expression level. The blue lines illustrate 1.5-fold change and the red lines illustrate 2-fold change. Axes are truncated at log2 = 5 to eliminate measurement uncertainty at lower signal intensities. (a) Log2 expression values of human miRNA probes in mock treatment are shown on the x-axis and the corresponding values for HIV-1 infection are shown on the y-axis. (b) Comparison of mock infection and HIV-1 ∆VV infection. (c) Comparison of HIV-1 ∆VV infection and HIV-1 infection.
109
(a)
(b)
(c)
Figure 4.6
110
Figure 4.7. PCAF protein expression is upregulated by HIV-1 but not vif/vpr-deficient HIV-1. Cultures of 293 cells were transfected with HIV-1, or vif/vpr-deficient HIV-1 (ΔVV), or mock transfected. After 24 hours, these cultures were transfected with pLuc-miR-17-5p or pLuc-miR-20a reporter plasmid and Renilla luciferase transfection efficiency control. Forty-eight hours later, cell lysates were prepared in an NP-40 lysis buffer. (a) Drawing of Firefly luciferase reporter plasmids that contain one miRNA target site for miR-17-5p or miR-20a positioned in the 3’ untranslated region upstream of the polyadenylation signal (p[A]). (b) The values of Firefly luciferase activity (F-luc) relative to Renilla luciferase (R-luc) are presented from triplicate transfection experiments. Twentyμl of cell lysate was evaluated in dual luciferase assays and relative light units (RLUs) were standardization to equivalent total cell protein (5 μg). Students’s t test was used to generate P values at a significance level of 0.05. Brackets indicate comparisons. (c) Representative immunoblots are shown that analyzed 5 μg of protein from Luc-miR-20a transfection lysate with antiserum against PCAF, B-Actin and HIV-1 Gag. Box represents quantification of PCAF and B-actin immunoblots signals using Multi Gauge software (FujiFilm).
111
miRNA target a site Poly (A) signal CMV
F-luc
0.000007 Luc-miR-17-5p 0.009 16 Luc-miR-20a 0.045 12 0.003 b 0.017 8
F-luc/R-luc 0.000001 RLU per 5 µg lysate)
2 4 (10
0 HIV-1 Mock ∆ VV HIV-1 Mock ∆ VV c M ock ?∆ VV H IV-1
PCAF
B-actin
p55 p41
p37
17.0x105 18.5x105 51.9x105 PCAF
6 6 6 3.1x10 2.8x10 1.5x10 B-actin
Figure 4.7
112
Table 4.1. Comparison of intensity of 906 miRNA probe signals in different infectionsa.
a Human CEMx174 lymphocytes were infected with indicated virus as described in methods and materials. Total RNA samples were harvested and subjected to microarray analysis of 522 mature and 336 precursor miRNA. b Down, downregulated (<1/1.5); Up, upregulated (>1.5); Minimal change (1/1.5-1.5); Not determined: below detection limit in at least one of two replicate microarray experiments.
Infection Comparison
Expressionb HIV-1/Mock ∆VV/Mock HIV-1/ ∆VV
Down 161 162 28
Up 212 210 38
Minimal change 156 154 515
Not determined 377 380 325
113 Table 4.2. Three categories of miRNA expression pattern are observed in microarray data from CEMx174 cells infected with either HIV-1 or vpr/vif-deficient HIV-1 (∆VV). Panel A: upregulation (HIV-1 expression level minimum 1.5 fold increase over ∆VV); minimal change (HIV-1 expression level between 1/1.5 and 1.5 relative to ∆VV), and downregulation (HIV-1 expression level maximum 1/1.5 times ∆VV). Gray highlight denotes probes with >2-fold upregulation. Values shown are average signal intensity of four replicates of each probe on replicate chips after quantile normalization.
Category A: MiRNA expression levels upregulated in HIV-1 infection in comparison to ∆VV infection. (average signal intensity units) Ratio MiRNA Probe HIV-1 Infection ∆VV Infection HIV-1/∆VV hsa-mir-496-A 216 35 6.15 hsa-mir-32-A 113 42 2.66 hsa-mir-323-P 8537 3413 2.50 hsa-mir-340-P 210 89 2.36 hsa-mir-199a-A 154 67 2.30 hsa-mir-194-2-A 2551 1153 2.21 hsa-mir-564-P 862 426 2.02 hsa-mir-378-3p/422b-A 81 41 1.97 hsa-mir-103-1-A 2203 1145 1.92 hsa-mir-139-A 62 33 1.88 hsa-mir-423-A 67 37 1.82 hsa-mir-25-A 2735 1570 1.74 hsa-mir-423-P 1396 806 1.73 hsa-mir-9-A 175 101 1.72 hsa-mir-27a-A 137 80 1.71 hsa-mir-453-A 381 225 1.69 hsa-mir-296-P 103 62 1.67 hsa-mir-501-P 189 115 1.64 hsa-mir-658-A 198 121 1.64 hsa-mir-429-P 347 213 1.63 hsa-mir-551b-P 253 156 1.62 hsa-mir-502-P 107 66 1.61 hsa-mir-572-P 739 461 1.61 hsa-mir-26a-2-P 196 123 1.60 hsa-mir-448-P 52 33 1.59 hsa-let-7a-A 138 87 1.58
Continued 114 Table 4.2 continued
Category A: MiRNA expression levels upregulated in HIV-1 infection in comparison to ∆VV infection. (average signal intensity units) Ratio MiRNA Probe HIV-1 Infection ∆VV Infection HIV-1/∆VV hsa-miR-126-3p-A 70 45 1.55 hsa-mir-29b-1-P 131 84 1.55 hsa-mir-34c-P 413 266 1.55 hsa-let-7c-A 113 73 1.55 hsa-miR-454-3p-A 101 65 1.55 hsa-mir-515-2-3p-A 100 65 1.53 hsa-mir-659-P 97 64 1.52 hsa-mir-28-A 88 58 1.52 hsa-mir-19b2-A 153 101 1.52 hsa-mir-504-A 108 72 1.51 hsa-mir-654-A 1201 797 1.51
Category B: MiRNA expression levels with minimal change in HIV-1 infection in comparison to ∆VV infection. (average signal intensity units) Ratio MiRNA Probe HIV-1 Infection ∆VV Infection HIV-1/∆VV hsa-mir-449-A 290 196 1.48 hsa-mir-601-A 97 66 1.47 hsa-mir-600-P 88 60 1.47 hsa-mir-561-P 102 70 1.46 hsa-mir-30c-1-A 266 183 1.46 hsa-mir-132-A 76 53 1.45 hsa-mir-626-P 125 87 1.44 hsa-mir-100-1/2-A 238 165 1.44 hsa-mir-585-P 47 32 1.44 hsa-mir-494-A 21919 15270 1.44 hsa-mir-642-P 192 135 1.42 hsa-mir-383-A 343 242 1.42 hsa-mir-141-A 294 208 1.41 hsa-mir-222-A 1299 920 1.41
Continued 115 Table 4.2 continued
Category B: MiRNA expression levels with minimal change in HIV-1 infection in comparison to ∆VV infection. (average signal intensity units) Ratio MiRNA Probe HIV-1 Infection ∆VV Infection HIV-1/∆VV hsa-mir-9*-3p-A 118 84 1.41 hsa-mir-595-P 2349 1677 1.40 hsa-mir-578-P 94 67 1.40 hsa-mir-17-5p-A 4328 3103 1.40 hsa-mir-513-1-A 117 84 1.39 hsa-mir-93-A 720 520 1.38 hsa-let-7d-A 119 86 1.38 hsa-mir-99b-A 373 270 1.38 hsa-let-7b-A 1068 776 1.38 hsa-mir-130a-A 251 183 1.37 hsa-mir-107-A 2412 1761 1.37 hsa-mir-301-P 3213 2350 1.37 hsa-mir-378-5p-A 99 73 1.36 hsa-mir-15a-P 64 47 1.36 hsa-mir-16-1-P 189 139 1.36 hsa-mir-194-1-P 109 81 1.35 hsa-mir-375-A 113 84 1.35 hsa-mir-645-A 231 172 1.35 hsa-mir-412-A 339 252 1.34 hsa-mir-21-A 542 406 1.33 hsa-let-7d-v1-A 58 43 1.33 hsa-mir-516-1-P 58 44 1.33 hsa-mir-105-1-A 178 134 1.32 hsa-mir-143-A 50 37 1.32 hsa-mir-560-P 1941 1470 1.32 hsa-mir-638-A 2495 1892 1.32 hsa-mir-424-A 61 46 1.32 hsa-mir-16a-chr13-A 483 367 1.32 hsa-mir-489-P 428 328 1.31 hsa-mir-566-P 2496 1916 1.30 hsa-mir-219-1-A 161 124 1.30 hsa-mir-92b-P 1128 869 1.30
Continued 116 Table 4.2 continued
Category B: MiRNA expression levels with minimal change in HIV-1 infection in comparison to ∆VV infection. (average signal intensity units) Ratio MiRNA Probe HIV-1 Infection ∆VV Infection HIV-1/∆VV hsa-mir-218-2-A 447 345 1.29 hsa-mir-7-3-A 133 103 1.29 hsa-mir-195-A 592 461 1.28 hsa-mir-583-P 64 50 1.28 hsa-mir-135a2-A 813 633 1.28 hsa-mir-587-P 676 528 1.28 hsa-mir-495-P 104 82 1.28 hsa-mir-100-A 141 110 1.28 hsa-mir-589-A 475 372 1.28 hsa-mir-15b-A 116 91 1.28 hsa-mir-500-A 468 368 1.27 hsa-mir-125b2-P 531 419 1.27 hsa-mir-330-A 289 228 1.27 hsa-mir-382-A 294 233 1.26 hsa-mir-103-2-A 2845 2254 1.26 hsa-mir-221-A 545 433 1.26 hsa-mir-196a2-A 279 222 1.25 hsa-let-7d-v2-P 144 115 1.25 hsa-mir-18b-P 42 34 1.25 hsa-mir-142-5p-A 387 311 1.25 hsa-mir-188-A 134 108 1.24 hsa-mir-627-A 432 350 1.23 hsa-mir-215-A 165 134 1.23 hsa-mir-20a-A 5066 4118 1.23 hsa-mir-202-3p-A 141 115 1.23 hsa-mir-518a1-3p-A 197 161 1.22 hsa-mir-151-A 125 102 1.22 hsa-mir-758-P 72 59 1.22 hsa-mir-602-A 947 778 1.22 hsa-mir-219-2-P 616 507 1.22 hsa-mir-625-P 248 204 1.21 hsa-mir-212-P 1579 1304 1.21
Continued 117 Table 4.2 continued
Category B: MiRNA expression levels with minimal change in HIV-1 infection in comparison to ∆VV infection. (average signal intensity units) Ratio MiRNA Probe HIV-1 Infection ∆VV Infection HIV-1/∆VV hsa-mir-499-A 1139 941 1.21 hsa-mir-21No1 709 587 1.21 hsa-mir-196a1-P 108 90 1.21 hsa-mir-16-2-A 604 503 1.20 hsa-mir-636-A 3744 3122 1.20 hsa-mir-202*-5p-A 12794 10669 1.20 hsa-mir-362-P 91 76 1.20 hsa-mir-34b-P 225 189 1.19 hsa-mir-511-2-A 46 39 1.19 hsa-mir-136-A 318 267 1.19 hsa-mir-196a-1-A 3635 3053 1.19 hsa-mir-498-P 53 44 1.19 hsa-mir-20b-A 3528 2969 1.19 hsa-mir-611-A 66 56 1.18 hsa-mir-632-P 467 395 1.18 hsa-mir-192-A 432 365 1.18 hsa-mir-497-A 6035 5114 1.18 hsa-mir-550-2-A 194 164 1.18 hsa-mir-216-A 71 60 1.18 hsa-mir-663-P 5249 4457 1.18 hsa-mir-30c-2-A 755 643 1.17 hsa-mir-563-A 53 45 1.17 hsa-mir-33b-A 312 266 1.17 hsa-mir-651-A 168 143 1.17 hsa-mir-30c-A 838 714 1.17 hsa-mir-214-A 1275 1086 1.17 hsa-mir-7-2-P 119 102 1.17 hsa-mir-106b-A 1618 1391 1.16 hsa-mir-150-A 1419 1221 1.16 hsa-mir-646-P 780 672 1.16 hsa-mir-598-A 69 60 1.16 hsa-mir-30d-A 1573 1355 1.16
Continued 118 Table 4.2 continued
Category B: MiRNA expression levels with minimal change in HIV-1 infection in comparison to ∆VV infection. (average signal intensity units) Ratio MiRNA Probe HIV-1 Infection ∆VV Infection HIV-1/∆VV hsa-mir-594-P 519 447 1.16 hsa-mir-516-4-5p-A 488 422 1.16 hsa-mir-181b-1-A 4243 3665 1.16 hsa-mir-30b-A 731 636 1.15 hsa-mir-30e-5p-A 263 229 1.15 hsa-miR-769-5p-A 324 282 1.15 hsa-mir-517*b-5p-A 54 47 1.15 hsa-mir-550-1-P 421 368 1.14 hsa-mir-663-A 230 201 1.14 hsa-mir-124a1-A 64 56 1.14 hsa-miR-302b*-5p-A 60 53 1.14 hsa-mir-130b-A 677 593 1.14 hsa-mir-346-P 140 123 1.14 hsa-let-7e-A 212 187 1.13 hsa-mir-200b-A 63 56 1.13 hsa-mir-557-A 594 525 1.13 hsa-mir-548b-A 745 659 1.13 hsa-mir-324-3p-A duplicate 176 155 1.13 hsa-mir-521-2-P 178 157 1.13 hsa-mir-200a*-5p-A 46 40 1.13 hsa-mir-766-P 626 556 1.13 hsa-mir-92b-A 13441 11952 1.12 hsa-mir-593-A 3963 3531 1.12 hsa-mir-192-P 91 81 1.12 hsa-mir-106a-A 2829 2534 1.12 hsa-mir-513-2-A 88 79 1.12 hsa-mir-145-A 1076 965 1.11 hsa-mir-598-P 1289 1156 1.11 hsa-mir-551a-A 205 184 1.11 hsa-mir-595-A 906 816 1.11 hsa-mir-138-2-A 655 590 1.11 hsa-mir-30a-5p-A 995 903 1.10
Continued 119 Table 4.2 continued
Category B: MiRNA expression levels with minimal change in HIV-1 infection in comparison to ∆VV infection. (average signal intensity units) Ratio MiRNA Probe HIV-1 Infection ∆VV Infection HIV-1/∆VV hsa-mir-574-P 10151 9222 1.10 hsa-mir-196a-1-P 258 235 1.10 hsa-mir-16b-chr3-A 646 588 1.10 hsa-mir-361-A 460 418 1.10 hsa-mir-16-2-P 277 252 1.10 hsa-mir-433-A 278 254 1.09 hsa-mir-191-5p-A 1298 1188 1.09 hsa-mir-431-P 981 898 1.09 hsa-mir-668-A 527 483 1.09 hsa-mir-220-A 485 445 1.09 hsa-mir-558-A 163 150 1.09 hsa-mir-34-A 314 290 1.09 hsa-mir-639-P 1601 1482 1.08 hsa-mir-766-A 11389 10544 1.08 hsa-mir-194-1No2 132 123 1.08 hsa-mir-147-A 152 141 1.08 hsa-mir-196a1-A 379 352 1.08 hsa-mir-374-A 47 44 1.08 hsa-mir-196b-P 2114 1964 1.08 hsa-mir-16-1-A 538 500 1.08 hsa-mir-609-A 436 406 1.07 hsa-mir-634-A 2942 2749 1.07 hsa-mir-616-A 360 336 1.07 hsa-mir-92-1-A 21919 20525 1.07 hsa-mir-636-P 709 665 1.07 hsa-mir-518c*-5p-A 82 77 1.07 hsa-mir-155-A 60674 57016 1.06 hsa-mir-629-A 3599 3384 1.06 hsa-let-7a3-A 92 87 1.06 hsa-mir-623-P 68 64 1.06 hsa-mir-383-P 388 367 1.06 hsa-mir-339-P 1656 1569 1.06
Continued
120 Table 4.2 continued
Category B: MiRNA expression levels with minimal change in HIV-1 infection in comparison to ∆VV infection. (average signal intensity units) Ratio MiRNA Probe HIV-1 Infection ∆VV Infection HIV-1/∆VV hsa-mir-801-A 3020 2875 1.05 hsa-mir-128a-P 443 423 1.05 hsa-mir-146a-A 5281 5036 1.05 hsa-mir-135a1-A 643 613 1.05 hsa-mir-135a-2-A 569 543 1.05 hsa-mir-554-P 385 368 1.05 hsa-let-7g-A 97 93 1.05 hsa-mir-181c-A 1025 980 1.05 hsa-mir-668-P 138 132 1.04 hsa-mir-511-1-P 119 114 1.04 hsa-mir-187-A 248 237 1.04 hsa-let-7a2-P 152 146 1.04 hsa-mir-9*-A 72 69 1.04 hsa-mir-219-1-P 16086 15453 1.04 hsa-mir-604-P 180 174 1.04 hsa-mir-371-P 321 310 1.04 hsa_mir_147 left 324 312 1.04 hsa-mir-15a-A 259 249 1.04 hsa-mir-331-P 6503 6272 1.04 hsa-mir-194-2-P 68 65 1.04 hsa-mir-619-P 57016 55002 1.04 hsa-mir-370-P 151 146 1.04 hsa-mir-326-P 1666 1609 1.04 hsa-mir-429-A 792 767 1.03 hsa-mir-181a-A 1771 1716 1.03 hsa-mir-26a-P 116 112 1.03 hsa-mir-550-1-A 62 60 1.03 hsa-mir-609-P 222 216 1.03 hsa-mir-19a-A 286 279 1.02 hsa-mir-338-A 1342 1311 1.02 hsa-mir-488-A 59 58 1.02 hsa-mir-29a-P 291 285 1.02
Continued 121 Table 4.2 continued
Category B: MiRNA expression levels with minimal change in HIV-1 infection in comparison to ∆VV infection. (average signal intensity units) Ratio MiRNA Probe HIV-1 Infection ∆VV Infection HIV-1/∆VV hsa-mir-96-A 506 496 1.02 hsa-mir-146b-P 359 352 1.02 hsa_mir_95 right 257 252 1.02 hsa-mir-216-P 323 318 1.02 hsa-mir-502-A 123 121 1.02 hsa-mir-125b1-A 96 94 1.01 hsa-mir-566-A 2614 2576 1.01 hsa-mir-148a-P 195 193 1.01 hsa-mir-606-P 119 118 1.01 hsa-mir-337-A 244 241 1.01 hsa-mir-618-A 434 429 1.01 hsa-mir-615-P 118 117 1.01 hsa-mir-1-2-P 56 55 1.01 hsa-mir-550-2-P 643 637 1.01 hsa-mir-198-A 589 584 1.01 hsa-mir-219-A 102 101 1.01 hsa-mir-662-A 400 398 1.01 hsa-mir-19b1-A 138 137 1.01 hsa-mir-335-P 2191 2184 1.00 hsa-mir-30c-2-P 244 244 1.00 hsa-mir-326-A 384 383 1.00 hsa-mir-331-A 58 58 1.00 hsa-mir-558-P 13174 13169 1.00 hsa-mir-92-2-A 14466 14466 1.00 hsa-mir-325-P 67 67 1.00 hsa-mir-122a-A 674 674 1.00 hsa-mir-516-3-5p-A 169 169 1.00 hsa-mir-376a-3p-A 36 36 1.00 hsa-mir-449-P 38 38 1.00 hsa-mir-658-P 8097 8120 1.00 hsa-mir-519e*-5p-A 296 297 1.00 hsa-mir-342-P 256 257 1.00
Continued 122 Table 4.2 continued
Category B: MiRNA expression levels with minimal change in HIV-1 infection in comparison to ∆VV infection. (average signal intensity units) Ratio MiRNA Probe HIV-1 Infection ∆VV Infection HIV-1/∆VV hsa-mir-152-P 988 992 1.00 hsa-mir-129-2-P 197 199 0.99 hsa-mir-199b-P 455 458 0.99 hsa-mir-186-A 125 126 0.99 hsa-mir-92-1-P 397 401 0.99 hsa-mir-563-P 277 280 0.99 hsa-mir-26a-2-A 362 366 0.99 hsa-mir-570-A 2189 2219 0.99 hsa-mir-621-P 1124 1140 0.99 hsa-mir-128a-A 640 650 0.98 hsa-mir-544-P 36 36 0.98 hsa-mir-622-A 223 227 0.98 hsa-mir-125a-P 121 123 0.98 hsa-mir-485-3p-A 740 754 0.98 hsa-mir-324-5p-A duplicate 826 843 0.98 hsa-mir-659-A 36 37 0.98 hsa-miR-769-3p-A 246 251 0.98 hsa-mir-559-P 34 35 0.98 hsa-mir-485-5p-A 33 34 0.98 hsa-mir-487a-A 1014 1038 0.98 hsa-mir-146b-A 4282 4394 0.97 hsa-mir-574-A 15869 16307 0.97 hsa-mir-660-A 153 157 0.97 hsa-mir-181b-2-A 5889 6065 0.97 hsa-mir-31-A 207 214 0.97 hsa-mir-564-A 150 155 0.97 hsa-mir-1b2-A 84 87 0.97 hsa-mir-765-P 129 133 0.97 hsa-mir-135b-A 417 432 0.96 hsa-mir-602-P 204 212 0.96 hsa-mir-604-A 721 750 0.96 hsa-mir-197-A 1655 1723 0.96
Continued 123 Table 4.2 continued
Category B: MiRNA expression levels with minimal change in HIV-1 infection in comparison to ∆VV infection. (average signal intensity units) Ratio MiRNA Probe HIV-1 Infection ∆VV Infection HIV-1/∆VV hsa-miR-126*-5p-A 5198 5422 0.96 hsa-mir-7-2-A 587 616 0.95 hsa-mir-29a-A 87 92 0.95 hsa-mir-34a-A 609 639 0.95 hsa-mir-649-A 285 300 0.95 hsa-mir-102-A 170 179 0.95 hsa-mir-153-1-A 69 73 0.95 hsa-mir-539-P 4763 5029 0.95 hsa-mir-570-P 763 806 0.95 hsa-mir-657-A 758 800 0.95 hsa-mir-26b-A 3145 3326 0.95 hsa-mir-518a2-3p-A 326 345 0.95 hsa-mir-539-A 103 109 0.94 hsa-mir-210-A 1218 1289 0.94 hsa-mir-511-2-P 154 163 0.94 hsa-mir-27b-A 213 226 0.94 hsa-mir-148b-A 53 56 0.94 hsa-mir-801-P 5616 5983 0.94 hsa-mir-493-3p-A 481 514 0.94 hsa-mir-30b-P 299 320 0.93 hsa-mir-95-A 282 303 0.93 hsa-mir-504-P 500 537 0.93 hsa-mir-551a-P 39 41 0.93 hsa-mir-129-1-P 380 409 0.93 hsa-let-7i-A 1177 1266 0.93 hsa-mir-581-P 483 520 0.93 hsa-mir-589-P 4843 5216 0.93 hsa-mir-553-P 92 99 0.93 hsa-mir-206-A 503 544 0.93 hsa-mir-29c-A 52 57 0.92 hsa-mir-128b-A 192 208 0.92 hsa-mir-181d-A 1531 1658 0.92
Continued 124 Table 4.2 continued
Category B: MiRNA expression levels with minimal change in HIV-1 infection in comparison to ∆VV infection. (average signal intensity units) Ratio MiRNA Probe HIV-1 Infection ∆VV Infection HIV-1/∆VV hsa-mir-342-A 8339 9032 0.92 hsa-mir-363*-5p-A 602 652 0.92 hsa-mir-487a-P 162 176 0.92 hsa-mir-425-5p-A 100 109 0.92 hsa-mir-26a-A 997 1082 0.92 hsa-mir-449b-P 3705 4022 0.92 hsa-mir-193b-A 938 1019 0.92 hsa-mir-196a-2-A 224 243 0.92 hsa-mir-365-1-P 155 168 0.92 hsa-mir-650-A 190 207 0.92 hsa-mir-181b-2-P 312 339 0.92 hsa-mir-320-A 612 667 0.92 hsa-mir-580-P 1203 1313 0.92 hsa-mir-129-A 1140 1245 0.92 hsa-mir-575-A 58 64 0.92 hsa-mir-321-A 403 441 0.91 hsa-mir-206-P 669 733 0.91 hsa-mir-181c-P 418 458 0.91 hsa-mir-548b-P 2716 2977 0.91 hsa-mir-631-A 391 429 0.91 hsa-mir-585-A 134 147 0.91 hsa-mir-7-3-P 366 401 0.91 hsa-mir-615-A 893 982 0.91 hsa-mir-632-A 574 631 0.91 hsa-mir-491-P 222 244 0.91 hsa-mir-611-P 103 113 0.91 hsa-mir-205-A 334 368 0.91 hsa-mir-213-A 4498 4958 0.91 hsa-mir-553-A 57016 62895 0.91 hsa-mir-325-A 83 92 0.91 hsa-mir-525-5p-A 145 160 0.91 hsa-mir-613-A 385 426 0.91
Continued 125 Table 4.2 continued
Category B: MiRNA expression levels with minimal change in HIV-1 infection in comparison to ∆VV infection. (average signal intensity units) Ratio MiRNA Probe HIV-1 Infection ∆VV Infection HIV-1/∆VV hsa-mir-30e-3p-A 161 178 0.90 hsa-mir-635-A 157 174 0.90 hsa-mir-99b-P 38 42 0.90 hsa-mir-499-P 476 529 0.90 hsa-mir-105-2-A 62 69 0.90 hsa-mir-565-P 94 105 0.90 hsa-mir-518a2-5p/mir527-A 284 316 0.90 hsa-mir-660-P 705 785 0.90 hsa-mir-193a-A 84 94 0.90 hsa-miR-324-3p-A 440 492 0.90 hsa-miR-181a*-3p-A 140 156 0.90 hsa-mir-448-A 291 326 0.89 hsa-mir-129-2-A 1762 1974 0.89 hsa-mir-377-A 582 654 0.89 hsa_mir_320_Hcd306 right 509 573 0.89 hsa-mir-149-A 663 749 0.89 hsa-mir-671-P 110 125 0.88 hsa-miR-181a-5p-A 1821 2064 0.88 hsa-mir-634-P 239 272 0.88 hsa-mir-7-1-A 348 396 0.88 hsa-mir-640-A 121 138 0.88 hsa-mir-345-A 147 168 0.88 hsa-mir-612-P 212 242 0.87 hsa-mir-596-A 1578 1807 0.87 hsa-mir-329-2-P 1543 1770 0.87 hsa-mir-184-P 2550 2926 0.87 hsa-mir-212-A 9695 11132 0.87 hsa-mir-498-A 5252 6035 0.87 hsa-mir-320-P 2265 2605 0.87 hsa_mir_95 left 183 210 0.87 hsa-mir-487b-A 464 535 0.87 hsa-mir-650-P 5417 6249 0.87
Continued 126 Table 4.2 continued
Category B: MiRNA expression levels with minimal change in HIV-1 infection in comparison to ∆VV infection. (average signal intensity units) Ratio MiRNA Probe HIV-1 Infection ∆VV Infection HIV-1/∆VV hsa-mir-505-A 212 244 0.87 hsa-mir-379-A 64 75 0.86 hsa-mir-631-P 386 449 0.86 hsa-mir-30c-1-P 450 524 0.86 hsa-mir-24-3p-A 97 114 0.86 hsa-mir-588-P 71 83 0.85 hsa-mir-548a2-P 1343 1571 0.85 hsa-mir-548a3-P 2577 3016 0.85 hsa-miR-324-5p-A 554 649 0.85 hsa-mir-576-A 1276 1495 0.85 hsa-mir-484-A 796 934 0.85 hsa-mir-346-A 2335 2741 0.85 hsa-mir-18a*-3p-A 45 53 0.85 hsa-mir-556-P 4233 4989 0.85 hsa-mir-181a2-P 257 302 0.85 hsa-mir-181a1-5p-A 1677 1977 0.85 hsa-mir-455-P 38 45 0.85 hsa-mir-373*-5p-A duplicate 3665 4340 0.84 hsa-mir-199b-A 149 176 0.84 hsa-mir-520e-A 218 258 0.84 hsa-mir-487b-P 284 338 0.84 hsa-mir-635-P 220 262 0.84 hsa-mir-656-P 280 334 0.84 hsa-mir-135bNo2 124 149 0.84 hsa-mir-371-A 8829 10567 0.84 hsa-mir-125b2-A 163 195 0.83 hsa-mir-422a-P 625 749 0.83 hsa-mir-296-A 255 305 0.83 hsa-mir-591-P 1353 1630 0.83 hsa-mir-661-A 568 684 0.83 hsa-mir-23a-A 1799 2171 0.83 hsa-mir-661-P 305 369 0.83
Continued 127 Table 4.2 continued
Category B: MiRNA expression levels with minimal change in HIV-1 infection in comparison to ∆VV infection. (average signal intensity units) Ratio MiRNA Probe HIV-1 Infection ∆VV Infection HIV-1/∆VV hsa-mir-548c-P 3481 4222 0.82 hsa-mir-410-A 511 621 0.82 hsa-mir-329-1-P 1202 1461 0.82 hsa-mir-520d-3p-A 225 274 0.82 hsa-mir-185-A 179 218 0.82 hsa-mir-644-P 3419 4167 0.82 hsa-mir-637-P 400 488 0.82 hsa-mir-106b-P 101 123 0.82 hsa-mir-593-P 2106 2574 0.82 hsa-mir-483-A 10168 12442 0.82 hsa-mir-495-A 63 78 0.82 hsa-mir-185-P 1124 1378 0.82 hsa-mir-200b-P 251 309 0.81 hsa-mir-603-P 1373 1689 0.81 hsa-mir-130a-P 166 204 0.81 hsa-mir-520a-3p-A 236 292 0.81 hsa-mir-630-P 69 85 0.81 hsa-mir-10a-A 116 143 0.81 hsa-mir-148b-P 618 763 0.81 hsa-mir-372-A 158 197 0.81 hsa-mir-24-2-A 409 508 0.80 hsa-mir-571-P 110 137 0.80 hsa-mir-613-P 87 108 0.80 hsa-mir-579-P 1015 1267 0.80 hsa-mir-410-P 66 83 0.80 hsa-mir-548a3-A 2043 2564 0.80 hsa-mir-548d2-P 4967 6241 0.80 hsa-miR-302b-3p-A 60 75 0.80 hsa-mir-616-P 343 433 0.79 hsa-mir-562-A 798 1008 0.79 hsa-miR-768-3p-A 119 150 0.79 hsa-mir-527-P 45 57 0.79
Continued 128 Table 4.2 continued
Category B: MiRNA expression levels with minimal change in HIV-1 infection in comparison to ∆VV infection. (average signal intensity units) Ratio MiRNA Probe HIV-1 Infection ∆VV Infection HIV-1/∆VV hsa-mir-26a-1-A 828 1051 0.79 hsa-mir-9-5p-A 654 830 0.79 hsa-mir-511-1-A 44 56 0.79 hsa-mir-584-A 257 328 0.78 hsa-mir-136-P 41 53 0.78 hsa-mir-23b-A 8473 10836 0.78 hsa-mir-548a2-A 808 1034 0.78 hsa-mir-32-P 168 215 0.78 hsa-mir-649-P 45 58 0.78 hsa-mir-299-3p-A 62 80 0.78 hsa-mir-213-P 274 352 0.78 hsa-mir-126-5p-A 6449 8294 0.78 hsa-mir-183-A 474 610 0.78 hsa-mir-500-P 412 530 0.78 hsa-mir-519d-P 104 134 0.78 hsa-mir-548a1-P 2344 3021 0.78 hsa-mir-196b-A 43 56 0.78 hsa-mir-575-P 46 59 0.77 hsa_mir_320_Hcd306 left 1742 2251 0.77 hsa-mir-562-P 857 1109 0.77 hsa-mir-671-A 86 112 0.77 hsa-mir-381-A 87 113 0.77 hsa-mir-640-P 373 487 0.77 hsa-mir-181b-1-P 258 338 0.77 hsa-mir-770-A 393 515 0.76 hsa-mir-657-P 57 75 0.76 hsa-mir-552-P 345 454 0.76 hsa-mir-29b-1-A 51 67 0.76 hsa-mir-560-A 727 959 0.76 hsa-mir-548d1-A 630 835 0.75 hsa-miR-373-3p-A 125 165 0.75 hsa-mir-519d-A 48 64 0.75
Continued 129 Table 4.2 continued
Category B: MiRNA expression levels with minimal change in HIV-1 infection in comparison to ∆VV infection. (average signal intensity units) Ratio MiRNA Probe HIV-1 Infection ∆VV Infection HIV-1/∆VV hsa-mir-424-P 66 88 0.75 hsa-mir-135a-1-A 1845 2475 0.75 hsa-mir-328-A 2817 3781 0.74 hsa-mir-200c-P 185 249 0.74 hsa-miR-373*-5p-A 3504 4714 0.74 hsa-mir-133b-P 1199 1617 0.74 hsa-mir-130b-P 1435 1936 0.74 hsa-mir-299-5p-A 92 124 0.74 hsa-mir-544-A 189 255 0.74 hsa-mir-133a1-A 76 103 0.74 hsa-mir-605-A 191 258 0.74 hsa-mir-181d-P 63 85 0.74 hsa-mir-370-A 99 134 0.74 hsa-mir-33-A 33 44 0.73 hsa-mir-548d1-P 5849 7997 0.73 hsa-mir-603-A 624 853 0.73 hsa-mir-493-5p-A 197 270 0.73 hsa-mir-520e-P 218 299 0.73 hsa-mir-607-A 338 464 0.73 hsa-mir-515-1-3p-A 141 194 0.73 hsa-mir-770-P 104 144 0.72 hsa-mir-548c-A 1215 1690 0.72 hsa-mir-577-P 183 255 0.72 hsa-mir-633-P 396 551 0.72 hsa-mir-548d2-A 560 785 0.71 hsa-mir-516-2-A 103 145 0.71 hsa-mir-450-1-A 132 187 0.70 hsa-miR-768-5p-A 138 197 0.70 hsa-mir-329-1-A 60 86 0.70 hsa-mir-557-P 65 94 0.69 hsa-mir-369-3p-A 42 60 0.69 hsa-mir-138-1-A 69 100 0.69
Continued 130 Table 4.2 Continued
Category B: MiRNA expression levels with minimal change in HIV-1 infection in comparison to ∆VV infection. (average signal intensity units) Ratio MiRNA Probe HIV-1 Infection ∆VV Infection HIV-1/∆VV hsa-mir-1-A 38 56 0.69 hsa-mir-524-3p-A 89 131 0.68 hsa-mir-204-P 721 1057 0.68 hsa-mir-330-P 383 564 0.68 hsa-mir-211-P 186 277 0.67 hsa-mir-654-P 187 280 0.67 hsa-mir-628-P 86 130 0.66 hsa-mir-34b-A 41 62 0.66 hsa-mir-516-1-A 149 227 0.66
Category C: MiRNA expression levels downregulated in HIV-1 infection in comparison to ∆VV infection. (average signal intensity units) Ratio MiRNA Probe HIV-1 Infection ∆VV Infection HIV-1/∆VV hsa-mir-619-A 37 58 0.65 hsa-mir-565-A 1602 2478 0.65 hsa-let-7i-P 73 113 0.65 hsa-mir-518b-P 63 98 0.64 hsa-mir-191*-3p-A 151 234 0.64 hsa-mir-548a1-A 1259 1960 0.64 hsa-mir-125a-A 49 77 0.64 hsa-mir-329-2-A 71 110 0.64 hsa-mir-363-3p-A 52 81 0.64 hsa-mir-339-A 94 149 0.63 hsa-mir-494-P 86 137 0.63 hsa-mir-321-AP 260 419 0.62 hsa-mir-644-A 83 137 0.61 hsa-mir-377-P 50 82 0.60 hsa-mir-152-A 52 87 0.60 hsa-mir-594-A 3528 5945 0.59
Continued 131 Table 4.2 Continued
Category C: MiRNA expression levels downregulated in HIV-1 infection in comparison to ∆VV infection. (average signal intensity units) Ratio MiRNA Probe HIV-1 Infection ∆VV Infection HIV-1/∆VV hsa-mir-302a-3p-A 91 156 0.58 hsa-mir-30a-3p-A 100 183 0.55 hsa-mir-105-2-P 124 254 0.49 hsa-mir-365-2-P 33 68 0.49 hsa-mir-451-P 34 72 0.48 hsa-mir-302b*-5p-A duplicate 33 74 0.45 hsa-mir-450-2-A 84 196 0.43
132
Table 4.3. Trends in 6 precursor miRNAs identified in independent RNA preparations from HIV-1 infected or mock treated CEMx174 cells. a Fold change in microRNA precursor levels identified by microarray of RNA preparations from HIV-1 infected cells and mock treated cells. b Fold change in microRNA precursor levels identified by reverse transcription and quantitative realtime PCR of independent RNA preparations of HIV-1 infected cells and mock treated cells.
MicroRNA HIV-1/Mock HIV-1/Mock precursor miRNA microarraya realtime PCRb miR-024-2-pre 1/3.9 1/2.1
miR-027a-pre 1/3.5 1/2.9
miR-024-1-pre 1/3.5 1/2.1
miR-144a-pre 1/3.3 1/2.5
miR-029a-pre 1/3.1 1/2.2
let-7d-v2-pre 4.2 3.4
133
Table 4.4. Expression level of three miRNA clusters are compared between HIV-1 and ∆VV samples from two replicate experiments ( − ; below detection limit (40 units)). Highlight denotes downregulation trend of mir17-5 and mir-20a in HIV-1 infection.
Comparison of expression level of miRNA cluster members in infected CEMx174 lymphocytes (average signal intensity units) Ratio Ratio Mock HIV-1 ∆VV HIV-1 / HIV-1 / Cluster MiRNA Probe Infection Infection Infection Mock ∆VV hsa-mir-17-3p-A − − − − − hsa-mir-17-5p-A 8097 4328 3103 0.53 1.40 hsa-mir-18a-A − − − − − hsa-mir-19a-A 405 286 279 0.71 1.02 Cluster hsa-mir-19b1-A 490 138 137 0.28 1.01 17-92 hsa-mir-20a-A 9238 5066 4118 0.55 1.23 hsa-mir-20b-A 6211 3528 2969 0.57 1.19 hsa-mir-20b-P − − − − − hsa-mir-92-1-A 62895 21919 20525 0.35 1.07 hsa-mir-92-1-P 252 397 401 1.58 0.99 hsa-mir-29a-A 1133 87 92 0.08 0.95 Cluster hsa-mir-29a-P 275 291 285 1.06 1.02 29a,b-1 hsa-mir-29b-1-A 582 51 67 0.09 0.76 hsa-mir-29b-1-P 264 131 84 0.49 1.55 Cluster hsa-mir-29b2-A 567 − 44 − − 29b-2,c hsa-mir-29c-A 754 52 57 0.07 0.92
134
CHAPTER 5
DIFFERENT HOST MICRORNAS ARE EXPRESSED IN LYMPHOCYTES
INFECTED WITH HIV-1 OR HIV-1 DEFICIENT IN TAT RNA SILENCING
SUPPRESSOR ACTIVITY
INTRODUCTION
The host small RNA pathway downregulates HIV-1 translation and reduces HIV-1 replication (12;105;110;169). HIV-1 Tat exhibits RNA silencing suppressor (RSS) activity that attenuates the translation downregulation (105;169). The translational inhibition of
HIV-1 mRNA by the small RNA pathway is also attenuated by expression of TBSV P19
RSS (169). Tat RSS activity is abolished by Tat K51A mutation. The profile of host miRNAs modulated by HIV-1 infection has been evaluated (11;12), but an unanswered issue is host miRNAs that are modulated by Tat RSS activity. For instance, by using the
MicroInspector online program, Huang et al. identified a set of cellular miRNAs (miR-28,
-125b, -150, -223, and -382) that target the 3’ UTR of HIV-1 RNA and silence viral mRNA in quiescent T4 lymphocytes (110). Here, we report microarray analysis to profile miRNAs differentially upregulated or downregulated in response to Tat RSS activity during virus infection. RNA was harvested from human CEMx174 lymphocytes infected with
135 wild-type HIV-1 or HIV-1 harboring the Tat K51A RSS mutation. Our results provide a
sampling of the interface between HIV-1 and host miRNAs that have the potential to
modulate virus replication and execute the innate host response to HIV-1 infection.
MATERIALS AND METHODS
Plasmids, infections and transfections
HIV-1 provirus NL4-3 was obtained from AIDS Reagent Reference Program.
1GA mutant HIV-1 provirus was obtained from Eric Freed (211). HIV-1/RSS construction was described in Chapter 3. Chapter 4 describes all transfections and infections, intracellular staining of Gag, RNA isolation, reverse transcription and real-time PCR, microarray protocol and biostatistical analysis.
Ribosome profile analysis
Cultures of 293 cells (2x107 per 10 cm dish) were transfected with HIV-1 1GA.
After 48 hour incubation, the cells were treated with 200 µM puromycin for 3 hours at
37°C. After 20 minute incubation with 200 µM cycloheximide, the cells were washed and harvested in PBS that contained 200 µM cyclohexamide. After centrifugation at 1540 rpm for 4 minutes at RT, the cell pellet was resuspended in 450 µl sucrose gradient buffer (10 mM HEPES, 10 mM NaCl, 3 mM CaCl2, 7 mM MgCl2), and supplemented with DTT to
1mM, 80 units of RNAsin, cyclohexamide to 100 µg/ml, and NP40 to 0.5%. Lysates were
centrifuged at 13,200 rpm for 5 minutes at 4°C. The lysate was loaded onto 15% - 50%
sucrose gradients and centrifuged at 36,000 rpm for 2 hours and 15 minutes at 4°C in
136 SW41Ti rotor (Beckman) without brake. The sucrose gradients were fractionated after
needle puncture at the bottom of tube and monitored at A254 using an ISCO fractionation
system (Lincoln, NE). Each gradient fraction was mixed with warm 95% ethanol and RNA
was precipitated at -80˚C overnight, and then extracted with Trizol (Invitrogen) according
to manufacturer protocol.
One hundred ng RNA aliquots of total RNA were used for reverse transcription. RNA
was denatured at 65ºC for 5 min and converted into cDNA with Sensiscript RT kit
(Qiagen) according to manufacturer protocol in presence of random hexamer. Equivalent
volumes of cDNA (10% of total reaction volume) were used for standard PCR amplification or real-time PCR quantification on a Lightcycler (Roche). The sequences and
PCR conditions of gag and actin were described in (9).
RESULTS AND DISCUSSION
Tat RSS activity does not affect Gag protein stability
Previous analysis has demonstrated that the small RNA pathway suppresses the translation of HIV-1 mRNA (169) and attenuates virion production. Tat K51A mutation eliminatesTat RSS activity without impairment of Tat transcriptional transactivation activity (105). To determine whether or not Tat RSS activity affects Gag stability, a pulse-chase analysis measured the half life of Gag protein in cells infected with either
HIV-1 or HIV-1 RSS. Cultures of 293 cells were transfected with HIV-1NL4-3 or HIV-1
RSS (Figure 5.1). After 48 hour incubation, the culture medium was removed and
supplemented with cysteine/methionine minus RPMI medium for 30 min, followed by
137 supplementation with 35S-cysteine/ methionine for 30 min. Afterwards, the culture was washed and incubated in fresh medium and total cellular protein was collected at intervals.
As indicated in Figure 5.2, Gag production was significantly greater for HIV-1 than
HIV-1/RSS, consistent with our previous data that RSS activity is essential for HIV-1 Gag protein synthesis (169). By 6 hour, the Gag p55 levels reached steady state si in both
HIV-1 and RSS infections. The results indicate that RSS mutation does not significantly decrease Gag protein stability or accumulation.
RSS activity modulates host ribosomal profile and HIV-1 gag translation
The translational inhibition of HIV-1 mRNA by the small RNA pathway is attenuated by expression of HIV-1 Tat or TBSV P19 RSS (169). Here, we asked whether or not expression of the TBSV P19 RSS changes the polysome profile of HIV-1 infected cells. The analysis used an HIV-1 strain with 1GA mutation in Gag myristoylation signal, which eliminates virus particle assembly and release (212;213). This strain was used to eliminate the potential pitfall that cell-associated virus particles co-sediment with polysomes. Human 293 cells were co-transfected with the eukaryotic TBSV P19 RSS expression plasmid (169) or pCDNA3.1 control plasmid. At 48 hours post transfection, cultures were subjected to treatment with the translation elongation inhibitor puromycin.
Cytoplasmic lysates were isolated and applied to 15 to 50% sucrose gradients and centrifuged. Ribosomal profiles were generated at A254 and RNA was harvested from each fraction for reverse transcription and real-time PCR. As shown in Figure 5.3a, the ribosomal profile of cells transfected with pCDNA3.1 control plasmid exhibit polysomes
138 in fractions 17-25. As expected, treatment with puromycin eliminated the heavy polysomes
(Figure 5.3c). Quantitative RT-PCR determined that HIV-1 gag mRNA was abundant in the heavy polysomes (Figure 5.3b). Puromycin treatment shifted gag RNA to fractions 11 to 13 that correspond to the 80S monosomes (Figure 5.3d).
When the cells were transfected with P19 RSS, the ribosome profile was similar although the abundance of heavy polysomes in fractions 23-25 was reduced (Fig 5.4a). Quantitative
RT-PCR determined that the distribution of HIV-1 gag mRNA was different; instead of accumulation in fractions 23-25, more accumulated in fraction 20 (Figure 5.4b).
Treatment with puromycin eliminated the heavy polysomes but did not change the position of the gag RNA (Figure 5.4c, Figure 5.4d). Recently, Thermann and Hentze performed similar polysome analysis and identified puromycin-resistant complexes (designated pseudo-polysomes) that contain RISC/miR-2 complexes. They suggested pseudo-polysomes are complexes of miRNA-targeted mRNA in stalled translation initiation complexes (214). Based on the observation of gag RNA in similar puromycin-resistant complexes accumulating in fractions 19-22, we suggest that gag RNA is in pseudopolysomes.
HIV-1 miRNA profile is changed in response to RSS mutation
To investigate the contribution of Tat RSS to the miRNA profile in HIV-1 infected cells, microarrays profiled host miRNAs that are up- or down-regulated by Tat RSS activity early after infection. Briefly, human CEMx174 cells were infected by co-culture and total RNA was isolated by Trizol reagent at 48 hrous post-infectin (Chapter 4). The
139 infections were evaluated by intracellular staining of Gag and flow cytometry. The
infection efficiency was reached at least 87%, indicating the majority of cells were
infected. The high infection rate indicated that the miRNA profiles would be enriched for
virus-infected cells rather than unproductively low infected cells. The microarray process
is similar as described in Chapter 4. The biostatistical analysis determined similar signal
intensities among the microarray chips, indicating similar efficiency of sample labeling and array hybridization (Figure 5.5).
To identify the miRNAs that change in response to virus infections, we compared the absolute signal intensity of each microRNA probe, mature miRNA and precursor miRNA in Mock, HIV-1 and RSS samples. A 1.5 fold threshold was set to define the up- and down-regulation parameters. The miRNA probes as designated as upregulated were
1.5-fold or greater in the HIV-1 treatment than the RSS treatment. Probes designated as downregulated were lower by a factor of 1.5 or more. The miRNA probes that exhibited expression levels between 1/1.499 and 1.499 fold were considered as minimal change.
MiRNA probes expression intensity lower than 32 in HIV-1 and HIV-1/RSS infections
were eliminated to avoid measurement uncertainty. These microRNA probes were referred
as not determined. As summarized in Table 5.1, comparison of HIV-1 infection to mock
treatment detected downregulation of 161 miRNA probes and upregulation of 212 miRNA
probes. Comparison of HIV-1 infected cells and RSS infected cells detected 68 miRNAs
probes were downregulated and 80 miRNA probes were upregulated. We further observed
the majority of miRNA probes (426) were not changed in HIV-1 infected cells compared to
RSS infected cells. These data suggested that Tat RSS does not dramatically change the
overall host miRNA expression pattern. However, the miRNAs differentially regulated by
140 Tat RSS are of interest to uncover their possible targets and identify their function on
HIV-1 biology. All the miRNAs that are modulated in HIV-1 infected cells compared to
RSS infected cells are listed in Table 5.2. Twenty-five miRNA probes were upregulated more than 2 fold, which are highlighted in gray. Scatterplot analysis provides an overview of the distribution of signal intensity of all miRNA probes (Figure 5.7). The microarray
database generated here is useful for further study of the interplay between HIV-1 and host
small RNA pathway.
We further asked whether or not miRNA cluster expression was differentially
modulated between the virus infections. As described in Chapter 4, HIV-1 infection
downregulated miR-17-92 cluster members at a range of 0.28 to 0.71. Interestingly,
miR-17-92 cluster members were upregulated in HIV-1 infection compared to RSS
infection at a range of 1.37 to 2.44-fold. These results suggest that Tat RSS activity
modulates expression of these miRNA (Table 5.3). Possible explanations of how RSS
activity modulates miRNA function include that Tat RSS suppresses the activity of one or
more host miRNAs that downregulates expression of a cellular transcription factor
necessary for mir-17-92 transcription. For example, c-Myc has been reported to activate
transcription of miR-17-92 (205); a corrolary is that Tat RSS affects c-Myc activity.
In conclusion, the results demonstrated gag RNA cosediments with polysomes and
that puromycin treatment or expression of P19 RSS disrupts this complex. The results
suggest that gag RNA cosediments with pseudopolysomes. Our microRNA microarray
database revealed a set of miRNAs that are differentially expressed in cells infected with
HIV-1 or Tat RSS-deficient HIV-1. This database will be useful for future investigation of
the interplay of specific miRNAs with HIV-1. 141
(K51A) HIV-1/RSS
Figure 5.1. HIV-1 proviruses used for infection. Schematic representation of HIV-1 and HIV-1/RSS genomes indicate HIV-1 genes and LTRs. Separate open reading frames that encode Tat and the Tat K51A mutants are shown, introns are denoted by dashed lines.
142
Virus: HIV-1 HIV-1/RSS
Chase: 0 2 4 6 8 20 0 2 4 6 8 20 Hours
P55p55
p24
Figure 5.2. Loss function mutation of Tat RSS does not affect HIV-1 Gag stability. Human 293 cells transfected with HIV-1 and HIV-1/RSS provirus, cells were labelled with 35S-cysteine/methionine for an hour, and medium was replaced with fresh medium and at indicated time intervals, cell extracts were prepared and subjected to immunoprecipitation with HIV-1 Gag antibody.
143
- puromycin + puromycin
a c
9
) 10 d
b 8 ) 7 8 8 7 6 6 5 4 4 3 2 2 Gag mRNA (copies x10 (copies mRNA Gag 1 Gag mRNA(copies x10 0 0 1357911131517192123 1 3 5 7 9 1113151719212325
Figure 5.3. HIV-1 gag RNA was efficiently translated in heavy polysomes and puromycin treatment disrupts gag RNA polysome association. Human 293 cells transfected with 1GA mutant HIV-1 provirus and co-transfected with pCDNA control plasmid. After 48 hours incubation, cells were treated with puromycin (c, d) or no drug treatment (a, b) and harvest for polysome profile analysis (a, c). RNA from each fraction was harvested and 10% RNA was reverse transcribed and subjected to gag realtime PCR (b, d).
144
- puromycin + puromycin
a c mRNP
b d 25 4.5 ) ) 9 8 4.0 20 3.5 3.0 15 2.5 2.0 10 1.5 5 1.0 x10 (copies mRNA Gag x10 Gag mRNA (copies 0.5 0 0
135791113 17 19 21 23 25 135791115 17 19 21 23 25
Figure 5.4. Plant virus RSS activity regulate HIV-1 gag mRNA profile in high molecular weight fraction. Human 293 cells were transfected with 1GA mutant HIV-1 provirus and co-transfected with P19 expression plasmid. After 48 hours incubation cells were treated with puromycin (c, d) or no drug treatment (a, b) and harvest for polysome profile analysis (a, c). RNA from each fraction was harvested and 10% RNA were reverse transcribed and perform gag realtime PCR (b, d).
145
a
Figure 5.5. Box plot of signal intensity range of 906 miRNA probes. Average signal intensity of four miRNA probe across two chips were averaged and log2 transformed. Quantile normalization was performed to average experimental variation among chips. The median value is represented by a line within the rectangular box.
146
Figure 5.6. Scatterplot analysis of the changes in miRNA probe expression in human CEMx174 lymphocytes infected with HIV-1, HIV-1 K51A (RSS) or mock infection. Signal intensity of four replicate miRNA probes across two chips were collected, averaged, and converted into log2 values. Each datum point represents replicate analysis of one unique probe sequence. The black line at x = y denotes unchanged expression level. The blue lines illustrate 1.5-fold change and the red lines illustrate 2-fold change. Axes are truncated at log2 = 5 to eliminate measurement uncertainty at lower signal intensities. (a) Log2 expression values of human miRNA probes in mock treatment are shown on the x-axis and the corresponding values for HIV-1 infection are shown on the y-axis. (b) Comparison of mock infection and HIV-1 RSS infection. (c) Comparison of HIV-1 RSS infection and HIV-1 infection.
147
(a)
(b)
(c)
Figure 5.6
148
Table 5.1. Comparison of average intensity of 906 miRNA probe signals in different infectionsa.
a Human CEMx174 lymphocytes were infected with indicated viruses as described in methods and materials. Total RNA samples were harvested and microarrays of 522 mature and 336 precursor miRNA were performed. b Down, downregulated (<1/1.5); Up, upregulated (>1.5); Minimal change (1/1.5-1.5); Not determined: below detection limits on at least one of the two chips compared.
Comparison of infection treatments (Average signal intensity)
Expressionb HIV-1/Mock RSS/Mock HIV-1/RSS
Down 161 171 68
Up 212 208 80
Minimal change 156 145 426
Not determined 377 379 332
149 Table 5.2. MiRNA expression pattern observed in microarray data from CEMx174 cells infected with either HIV-1 or HIV-1 Tat RSS mutant (RSS). Values shown are average signal intensity of four replicates of each probe of replicate chips after quantile normalization as described in Materials and Methods. Ratio HIV-1/Mock was generated by dividing HIV-1 infection to Mock expression values. Shown in gray highlight are probes with >2-fold up regulation.
Comparison of miRNA level in CEMx174 cells infected with HIV-1 or HIV-1 K51A (RSS) or mock infected Ratio Ratio Mock HIV-1 RSS HIV-1 / HIV-1 / MiRNA Probe Infection Infection Infection Mock RSS hsa-mir-340-P 89 210 32 2.37 6.54 hsa-mir-323-P 1709 8537 1690 4.99 5.05 hsa-mir-194-2-A 979 2551 746 2.61 3.42 hsa-mir-560-P 788 1941 574 2.46 3.38 hsa-mir-30e-3p-A 290 161 50 0.56 3.24 hsa-mir-494-A 3374 21919 7192 6.50 3.05 hsa-mir-500-A 147 468 161 3.18 2.91 hsa-mir-453-A 241 381 138 1.58 2.76 hsa-mir-26b-A 8872 3145 1165 0.35 2.70 hsa-mir-215-A 573 165 63 0.29 2.60 hsa-mir-219-1-A 197 161 63 0.81 2.55 hsa-mir-20b-A 6211 3528 1445 0.57 2.44 hsa-mir-193a-P 638 2164 889 3.39 2.43 hsa-mir-125a-P 80 121 51 1.52 2.37 hsa-mir-20a-A 9238 5066 2207 0.55 2.30 hsa-mir-21No1 1785 709 313 0.40 2.27 hsa-mir-489-P 256 428 191 1.67 2.24 hsa-mir-106a-A 5648 2829 1280 0.50 2.21 hsa-mir-17-5p-A 8097 4328 1986 0.53 2.18 hsa-mir-658-A 414 198 92 0.48 2.16 hsa-mir-564-P 478 862 407 1.80 2.12 hsa-mir-128a-P 539 443 215 0.82 2.06 hsa-mir-499-A 935 1139 559 1.22 2.04 hsa-mir-125b2-P 1357 531 265 0.39 2.00 hsa-mir-196a2-A 364 279 140 0.77 2.00 hsa-mir-21-A 1630 542 274 0.33 1.97 hsa-mir-19a-A 405 286 148 0.71 1.94 hsa-mir-496-A 257 216 112 0.84 1.93 hsa-mir-668-A 232 527 273 2.27 1.93 hsa-mir-196a1-A 305 379 196 1.24 1.93 hsa-mir-93-A 1723 720 378 0.42 1.90
Continued 150 Table 5.2 continued
Comparison of miRNA level in CEMx174 cells infected with HIV-1 or HIV-1 K51A (RSS) or mock infected Ratio Ratio Mock HIV-1 RSS HIV-1 / HIV-1 / MiRNA Probe Infection Infection Infection Mock RSS hsa-mir-196a-1-A 1627 3635 1929 2.23 1.89 hsa-mir-26a-A 4473 997 529 0.22 1.88 hsa-mir-649-A 97 285 153 2.94 1.87 hsa-mir-429-P 901 347 187 0.38 1.86 hsa-miR-768-5p-A 560 138 74 0.25 1.85 hsa-mir-15a-P 49 64 35 1.32 1.84 hsa-mir-516-2-A 31 103 56 3.31 1.82 hsa-mir-487a-P 20 162 90 7.93 1.81 hsa-mir-558-A 98 163 90 1.66 1.81 hsa-mir-16-2-P 877 277 154 0.32 1.80 hsa-mir-106b-A 3323 1618 900 0.49 1.80 hsa-mir-378-3p/422b-A 250 81 45 0.32 1.78 hsa-mir-668-P 137 138 79 1.01 1.75 hsa-mir-126-3p-A duplicate 12 66 38 5.53 1.75 hsa-mir-9-A 838 175 100 0.21 1.75 hsa-mir-516-1-A 17 149 86 9.00 1.73 hsa-mir-216-P 204 323 187 1.58 1.73 hsa-mir-570-A 625 2189 1271 3.50 1.72 hsa-mir-575-A 27 58 34 2.12 1.72 hsa-mir-487a-A 420 1014 602 2.42 1.69 hsa-mir-578-P 102 94 56 0.92 1.68 hsa-mir-638-A 1382 2495 1491 1.81 1.67 hsa-mir-548a3-A 465 2043 1225 4.40 1.67 hsa-mir-572-P 542 739 448 1.37 1.65 hsa-mir-16-1-A 1991 538 329 0.27 1.63 hsa-mir-16a-chr13-A 1975 483 296 0.24 1.63 hsa-mir-194-1No2 5 132 81 25.91 1.63 hsa-mir-34c-P 286 413 254 1.44 1.63 hsa-mir-520e-A 123 218 134 1.76 1.63 hsa-mir-26a-2-A 2362 362 223 0.15 1.62 hsa-mir-7-3-A 53 133 82 2.50 1.61 hsa-mir-663-A 292 230 143 0.79 1.60 hsa-mir-493-3p-A 90 481 300 5.35 1.60 hsa-mir-519d-P 53 104 65 1.96 1.60
Continued 151 Table 5.2 continued
Comparison of miRNA level in CEMx174 cells infected with HIV-1 or HIV-1 K51A (RSS) or mock infected Ratio Ratio Mock HIV-1 RSS HIV-1 / HIV-1 / MiRNA Probe Infection Infection Infection Mock RSS hsa-mir-654-A 831 1201 756 1.44 1.59 hsa-mir-155-A 38328 60674 38328 1.58 1.58 hsa-mir-124a1-A 78 64 41 0.83 1.58 hsa-mir-502-P 18 107 68 5.90 1.56 hsa-mir-639-P 1736 1601 1024 0.92 1.56 hsa-mir-26a-2-P 131 196 126 1.50 1.56 hsa-mir-604-A 867 721 467 0.83 1.54 hsa-mir-26a-1-A 4390 828 538 0.19 1.54 hsa-mir-382-A 172 294 192 1.71 1.53 hsa-mir-626-P 21 125 82 5.96 1.53 hsa-mir-560-A 1019 727 481 0.71 1.51 hsa-mir-663-P 2574 5249 3477 2.04 1.51 hsa-mir-195-A 1700 592 393 0.35 1.51 hsa-mir-102-A 1335 170 113 0.13 1.50 hsa-mir-515-2-3p-A 134 100 67 0.74 1.49 hsa-mir-423-P 1563 1396 938 0.89 1.49 hsa-mir-19b2-A 554 153 103 0.28 1.49 hsa-mir-539-A 77 103 69 1.33 1.48 hsa-mir-16b-chr3-A 2194 646 438 0.29 1.48 hsa-mir-202-3p-A 241 141 96 0.59 1.47 hsa-mir-181b-1-A 9398 4243 2882 0.45 1.47 hsa-mir-516-3-5p-A 153 169 115 1.10 1.47 hsa-mir-424-A 69 61 42 0.88 1.47 hsa-mir-511-1-P 24 119 82 5.01 1.44 hsa-mir-21-P 76 55 39 0.73 1.43 hsa-mir-101-1/2-P 14 56 39 3.92 1.42 hsa-mir-192-P 53 91 65 1.74 1.41 hsa-miR-454-3p-A 428 101 72 0.24 1.41 hsa-mir-518a2-5p/mir527- A 179 284 202 1.58 1.41 hsa-mir-548a3-P 264 2577 1839 9.77 1.40 hsa-mir-345-A 95 147 105 1.54 1.40 hsa-mir-563-P 154 277 198 1.80 1.40 hsa-mir-511-2-A 35 46 33 1.31 1.40 hsa-mir-28-A 20 88 63 4.38 1.39
Continued 152
Table 5.2 continued
Comparison of miRNA level in CEMx174 cells infected with HIV-1 or HIV-1 K51A (RSS) or mock infected Ratio Ratio Mock HIV-1 RSS HIV-1 / HIV-1 / MiRNA Probe Infection Infection Infection Mock RSS hsa-mir-498-A 4068 5252 3795 1.29 1.38 hsa-mir-187-A 302 248 179 0.82 1.38 hsa-mir-548a2-A 279 808 588 2.90 1.37 hsa-mir-92-1-P 252 397 290 1.58 1.37 hsa-mir-19b1-A 490 138 101 0.28 1.37 hsa-mir-363-3p-A 65 52 38 0.80 1.37 hsa-mir-26a-P 233 116 85 0.50 1.36 hsa-mir-584-A 102 257 190 2.51 1.35 hsa-mir-29c-A 754 52 39 0.07 1.35 hsa-mir-372-A 119 158 117 1.33 1.35 hsa-mir-139-A 13 62 46 4.92 1.34 hsa-mir-135a1-A 207 643 481 3.11 1.34 hsa-mir-361-A 1504 460 345 0.31 1.33 hsa-mir-548a2-P 261 1343 1009 5.14 1.33 hsa-mir-92b-P 1267 1128 848 0.89 1.33 hsa-mir-370-P 18 151 114 8.25 1.33 hsa-mir-520d-3p-A 71 225 169 3.18 1.33 hsa-mir-325-A 23 83 63 3.70 1.32 hsa-mir-593-A 1163 3963 3006 3.41 1.32 hsa-mir-425-3p-A 268 548 416 2.04 1.32 hsa-mir-132-A 15 76 58 5.20 1.32 hsa-mir-579-P 155 1015 776 6.56 1.31 hsa-mir-548b-P 365 2716 2081 7.45 1.31 hsa-mir-202*-5p-A 7852 12794 9841 1.63 1.30 hsa-mir-9*-3p-A 625 118 91 0.19 1.30 hsa-mir-589-A 277 475 366 1.72 1.30 hsa-mir-16-1-P 109 189 146 1.73 1.29 hsa-mir-606-P 21 119 92 5.74 1.29 hsa-mir-450-2-A 48 84 65 1.73 1.29 hsa-mir-132-P 115 278 216 2.41 1.28 hsa-mir-409-3p-A 119 133 104 1.12 1.27 hsa-mir-570-P 126 763 600 6.05 1.27 hsa-mir-516-4-5p-A 286 488 385 1.71 1.27 hsa-mir-497-A 2333 6035 4763 2.59 1.27 hsa-mir-135bNo2 90 124 98 1.38 1.27
Continued 153 Table 5.2 continued
Comparison of miRNA level in CEMx174 cells infected with HIV-1 or HIV-1 K51A (RSS) or mock infected Ratio Ratio Mock HIV-1 RSS HIV-1 / HIV-1 / MiRNA Probe Infection Infection Infection Mock RSS hsa-mir-138-2-A 557 655 520 1.18 1.26 hsa_mir_147 left 230 324 257 1.40 1.26 hsa-mir-449-A 156 290 231 1.85 1.26 hsa-mir-329-1-P 317 1202 959 3.79 1.25 hsa-mir-518c*-5p-A 13 82 66 6.32 1.25 hsa-mir-146b-P 208 359 287 1.73 1.25 hsa-mir-548d2-P 622 4967 3980 7.98 1.25 hsa-mir-219-1-P 8577 16086 12901 1.88 1.25 hsa-mir-495-P 68 104 84 1.53 1.24 hsa-mir-331-A 52 58 47 1.13 1.24 hsa-mir-371-A 3963 8829 7128 2.23 1.24 hsa-mir-646-P 254 780 631 3.07 1.24 hsa-mir-16-2-A 2329 604 491 0.26 1.23 hsa-mir-603-P 307 1373 1115 4.47 1.23 hsa-mir-198-A 277 589 481 2.13 1.23 hsa-mir-146b-A 12901 4282 3495 0.33 1.23 hsa-mir-181b-2-P 114 312 256 2.74 1.22 hsa-mir-127-A 50 103 84 2.07 1.22 hsa-mir-548d2-A 153 560 460 3.66 1.22 hsa-mir-564-A 111 150 124 1.35 1.22 hsa-mir-551b-P 322 253 208 0.79 1.22 hsa-mir-29a-A 1133 87 72 0.08 1.22 hsa-mir-410-A 207 511 423 2.47 1.21 hsa-mir-651-A 248 168 139 0.68 1.21 hsa-mir-511-2-P 95 154 127 1.63 1.21 hsa-mir-219-2-P 328 616 512 1.88 1.20 hsa_mir_95 left 14 183 152 12.81 1.20 hsa-mir-495-A 70 63 53 0.90 1.20 hsa-mir-32-P 219 168 140 0.77 1.20 hsa-mir-329-2-P 482 1543 1284 3.20 1.20 hsa-mir-627-A 457 432 360 0.94 1.20 hsa-mir-629-P 206 135 113 0.66 1.20 hsa-mir-621-A 198 152 127 0.77 1.20 hsa-mir-548c-A 321 1215 1017 3.79 1.19 hsa-mir-616-P 131 343 288 2.62 1.19
Continued 154 Table 5.2 continued
Comparison of miRNA level in CEMx174 cells infected with HIV-1 or HIV-1 K51A (RSS) or mock infected Ratio Ratio Mock HIV-1 RSS HIV-1 / HIV-1 / MiRNA Probe Infection Infection Infection Mock RSS hsa-mir-662-A 220 400 338 1.82 1.18 hsa-mir-501-P 20 189 161 9.30 1.18 hsa-mir-146a-A 13842 5281 4482 0.38 1.18 hsa-mir-645-A 96 231 197 2.40 1.17 hsa-mir-7-1-A 139 348 298 2.49 1.17 hsa-mir-595-A 883 906 777 1.03 1.17 hsa-mir-199a-A 66 154 133 2.33 1.16 hsa-mir-448-P 12 52 45 4.32 1.16 hsa-mir-548d1-P 674 5849 5034 8.67 1.16 hsa-mir-1-1-P 88 48 42 0.55 1.16 hsa-let-7b-A 1195 1068 928 0.89 1.15 hsa-mir-122a-A 655 674 586 1.03 1.15 hsa-mir-635-A 57 157 137 2.77 1.15 hsa-mir-365-1-P 140 155 135 1.11 1.14 hsa-mir-513-1-A 49 117 102 2.36 1.14 hsa-mir-330-A 96 289 255 3.01 1.13 hsa-mir-575-P 21 46 40 2.20 1.13 hsa-mir-525-5p-A 50 145 128 2.87 1.13 hsa-mir-548a1-P 322 2344 2071 7.29 1.13 hsa-mir-212-A 2302 9695 8570 4.21 1.13 hsa-mir-134-P 70 246 218 3.54 1.13 hsa-mir-135a-2-A 300 569 508 1.90 1.12 hsa-mir-562-A 337 798 713 2.37 1.12 hsa-mir-152-A 48 52 47 1.10 1.12 hsa-mir-331-P 3210 6503 5808 2.03 1.12 hsa-mir-363*-5p-A 314 602 539 1.92 1.12 hsa-mir-649-P 12 45 40 3.72 1.11 hsa-mir-587-P 337 676 607 2.01 1.11 hsa-mir-548c-P 431 3481 3145 8.07 1.11 hsa-mir-183-A 123 474 429 3.86 1.11 hsa-mir-603-A 261 624 565 2.39 1.10 hsa-mir-143-A 83 50 45 0.60 1.10 hsa-mir-210-A 1900 1218 1106 0.64 1.10 hsa-mir-27b-A 544 213 194 0.39 1.10 hsa-mir-504-A 5 108 99 21.17 1.09
Continued 155 Table 5.2 continued
Comparison of miRNA level in CEMx174 cells infected with HIV-1 or HIV-1 K51A (RSS) or mock infected Ratio Ratio Mock HIV-1 RSS HIV-1 / HIV-1 / MiRNA Probe Infection Infection Infection Mock RSS hsa-mir-96-A 411 506 464 1.23 1.09 hsa-mir-656-P 113 280 257 2.48 1.09 hsa-mir-342-P 285 256 236 0.90 1.08 hsa-mir-218-2-A 330 447 412 1.36 1.08 hsa-mir-511-1-A 15 44 41 2.88 1.08 hsa-mir-325-P 5 67 63 13.17 1.08 hsa-miR-768-3p-A 252 119 110 0.47 1.08 hsa-mir-548b-A 133 745 692 5.58 1.08 hsa-mir-342-A 17611 8339 7759 0.47 1.07 hsa-mir-200b-P 137 251 235 1.84 1.07 hsa-mir-650-A 102 190 178 1.87 1.07 hsa-mir-34b-P 82 225 211 2.76 1.07 hsa-mir-520a-3p-A 86 236 221 2.76 1.07 hsa-mir-487b-A 180 464 437 2.58 1.06 hsa-miR-769-5p-A 215 324 305 1.50 1.06 hsa-mir-206-P 622 669 631 1.08 1.06 hsa-mir-200b-A 84 63 60 0.75 1.06 hsa-mir-607-A 85 338 321 3.99 1.06 hsa-mir-615-P 250 118 112 0.47 1.05 hsa-mir-375-A 306 113 108 0.37 1.05 hsa-mir-770-P 96 104 99 1.08 1.05 hsa-mir-196a-2-A 371 224 213 0.60 1.05 hsa-mir-29b-1-P 264 131 125 0.49 1.05 hsa-let-7a-A 926 138 132 0.15 1.04 hsa-mir-383-A 465 343 329 0.74 1.04 hsa-mir-185-A 145 179 172 1.24 1.04 hsa-mir-562-P 270 857 822 3.18 1.04 hsa-mir-373*-5p-A duplicate 2903 3665 3526 1.26 1.04 hsa-mir-630-P 21 69 67 3.31 1.03 hsa-mir-184-P 880 2550 2465 2.90 1.03 hsa-mir-103-1-A 5489 2203 2133 0.40 1.03 hsa-mir-429-A 536 792 767 1.48 1.03 hsa-mir-433-A 221 278 269 1.26 1.03 hsa-let-7a3-A 731 92 89 0.13 1.03
Continued 156 Table 5.2 continued
Comparison of miRNA level in CEMx174 cells infected with HIV-1 or HIV-1 K51A (RSS) or mock infected Ratio Ratio Mock HIV-1 RSS HIV-1 / HIV-1 / MiRNA Probe Infection Infection Infection Mock RSS hsa-mir-221-A 1388 545 529 0.39 1.03 hsa-mir-548a1-A 598 1259 1223 2.10 1.03 hsa-mir-339-P 886 1656 1610 1.87 1.03 hsa-mir-30b-A 5308 731 711 0.14 1.03 hsa-mir-135b-A 72 417 406 5.79 1.03 hsa-mir-496-P 17 106 103 6.31 1.03 hsa-mir-644-P 683 3419 3332 5.01 1.03 hsa-mir-608-A 256 499 487 1.95 1.02 hsa-mir-765-P 123 129 126 1.05 1.02 hsa-mir-151-A 78 125 122 1.61 1.02 hsa-mir-595-P 659 2349 2302 3.57 1.02 hsa-mir-329-1-A 18 60 59 3.38 1.02 hsa-mir-558-P 3272 13174 12939 4.03 1.02 hsa-mir-583-P 15 64 63 4.37 1.02 hsa-mir-152-P 710 988 976 1.39 1.01 hsa-mir-521-2-P 74 178 176 2.40 1.01 hsa-mir-220-A 391 485 481 1.24 1.01 hsa-mir-34a-A 432 609 606 1.41 1.00 hsa-mir-30e-5p-A 1633 263 263 0.16 1.00 hsa-mir-206-A 476 503 506 1.06 0.99 hsa-mir-381-A 15 87 87 5.73 0.99 hsa-let-7i-A 1016 1177 1188 1.16 0.99 hsa-mir-329-2-A 10 71 72 7.40 0.99 hsa-mir-576-A 495 1276 1291 2.58 0.99 hsa-mir-196b-A 33 43 44 1.33 0.99 hsa-mir-338-A 442 1342 1360 3.04 0.99 hsa-mir-374-A 333 47 48 0.14 0.99 hsa-mir-181a-A 4283 1771 1799 0.41 0.98 hsa-mir-556-P 2738 4233 4301 1.55 0.98 hsa-mir-632-A 496 574 584 1.16 0.98 hsa-mir-598-P 438 1289 1311 2.94 0.98 hsa-mir-766-A 3866 11389 11630 2.95 0.98 hsa-mir-214-A 628 1275 1303 2.03 0.98 hsa-mir-200c-P 90 185 190 2.05 0.98 hsa-mir-1b2-A 215 84 86 0.39 0.97
Continued 157 Table 5.2 continued
Comparison of miRNA level in CEMx174 cells infected with HIV-1 or HIV-1 K51A (RSS) or mock infected Ratio Ratio Mock HIV-1 RSS HIV-1 / HIV-1 / MiRNA Probe Infection Infection Infection Mock RSS hsa-mir-450-1-A 65 132 136 2.03 0.97 hsa-mir-9*-A 509 72 74 0.14 0.97 hsa-mir-509-P 5 34 35 6.66 0.97 hsa-mir-635-P 121 220 228 1.82 0.97 hsa-mir-455-P 83 38 39 0.45 0.96 hsa-mir-130a-A 1267 251 261 0.20 0.96 hsa-mir-181d-A 4243 1531 1593 0.36 0.96 hsa-mir-574-P 3675 10151 10567 2.76 0.96 hsa-mir-520e-P 113 218 227 1.93 0.96 hsa-mir-504-P 300 500 522 1.67 0.96 hsa-mir-346-P 99 140 147 1.41 0.96 hsa-mir-519e*-5p-A 223 296 310 1.33 0.95 hsa-mir-381-P 183 237 249 1.29 0.95 hsa-miR-373-3p-A 93 125 131 1.33 0.95 hsa-mir-659-A 5 36 38 7.00 0.95 hsa-mir-598-A 147 69 73 0.47 0.95 hsa-mir-658-P 2349 8097 8577 3.45 0.94 hsa-mir-181b-2-A 10844 5889 6241 0.54 0.94 hsa-mir-196b-P 782 2114 2246 2.70 0.94 hsa-mir-345-P 678 841 895 1.24 0.94 hsa-mir-622-A 108 223 238 2.07 0.94 hsa-mir-493-5p-A 21 197 210 9.45 0.94 hsa-mir-191-5p-A 4328 1298 1384 0.30 0.94 hsa-mir-498-P 14 53 56 3.78 0.94 hsa-mir-631-A 385 391 418 1.02 0.93 hsa-mir-561-P 57 102 109 1.78 0.93 hsa-mir-30b-P 194 299 321 1.54 0.93 hsa-mir-219-A 75 102 110 1.35 0.93 hsa-mir-7-2-A 207 587 630 2.84 0.93 hsa-mir-518a1-3p-A 112 197 211 1.75 0.93 hsa-mir-636-A 2443 3744 4022 1.53 0.93 hsa-mir-494-P 24 86 93 3.53 0.93 hsa-mir-623-P 17 68 73 4.01 0.93 hsa-let-7e-A 716 212 228 0.30 0.93 hsa-mir-30a-5p-A 2538 995 1075 0.39 0.93
Continued 158 Table 5.2 continued
Comparison of miRNA level in CEMx174 cells infected with HIV-1 or HIV-1 K51A (RSS) or mock infected Ratio Ratio Mock HIV-1 RSS HIV-1 / HIV-1 / MiRNA Probe Infection Infection Infection Mock RSS hsa-mir-660-P 690 705 764 1.02 0.92 hsa-miR-126*-5p-A 5845 5198 5653 0.89 0.92 hsa-mir-296-P 12 103 112 8.51 0.92 hsa-mir-383-P 129 388 424 3.00 0.92 hsa-mir-129-2-A 1213 1762 1926 1.45 0.91 hsa-mir-148b-P 768 618 675 0.80 0.91 hsa-mir-135a-1-A 903 1845 2018 2.04 0.91 hsa-mir-633-P 338 396 433 1.17 0.91 hsa-mir-553-P 89 92 100 1.02 0.91 hsa-mir-181c-P 265 418 459 1.58 0.91 hsa-mir-18a*-3p-A 59 45 50 0.77 0.91 hsa-mir-23b-A 9454 8473 9309 0.90 0.91 hsa-mir-181b-1-P 170 258 285 1.52 0.91 hsa-mir-619-P 15270 57016 62895 3.73 0.91 hsa-mir-553-A 55002 57016 62895 1.04 0.91 hsa-mir-550-2-P 416 643 709 1.55 0.91 hsa-mir-204-A 105 159 176 1.52 0.90 hsa-mir-30c-2-A 4837 755 838 0.16 0.90 hsa-mir-574-A 4512 15869 17611 3.52 0.90 hsa-mir-557-P 54 65 73 1.21 0.90 hsa-let-7d-A 541 119 133 0.22 0.90 hsa-mir-554-P 337 385 429 1.14 0.90 hsa-mir-631-P 170 386 430 2.27 0.90 hsa-mir-213-P 259 274 307 1.06 0.89 hsa-mir-30c-A 6236 838 938 0.13 0.89 hsa-mir-629-A 1271 3599 4034 2.83 0.89 hsa-mir-130a-P 107 166 186 1.55 0.89 hsa-mir-589-P 1426 4843 5447 3.40 0.89 hsa-mir-634-A 1421 2942 3313 2.07 0.89 hsa-mir-609-A 174 436 491 2.51 0.89 hsa-mir-552-P 129 345 389 2.68 0.89 hsa-mir-613-A 172 385 435 2.24 0.89 hsa-mir-640-P 158 373 421 2.36 0.89 hsa-mir-15b-A 842 116 131 0.14 0.89 hsa-mir-130b-A 1731 677 765 0.39 0.88
Continued 159 Table 5.2 continued
Comparison of miRNA level in CEMx174 cells infected with HIV-1 or HIV-1 K51A (RSS) or mock infected Ratio Ratio Mock HIV-1 RSS HIV-1 / HIV-1 / MiRNA Probe Infection Infection Infection Mock RSS hsa-mir-134-A 60 37 42 0.61 0.88 hsa-mir-515-1-3p-A 164 141 161 0.86 0.88 hsa-mir-92b-A 22021 13441 15270 0.61 0.88 hsa-mir-145-A 913 1076 1223 1.18 0.88 hsa-mir-103-2-A 6149 2845 3235 0.46 0.88 hsa-mir-30c-1-A 2599 266 303 0.10 0.88 hsa-mir-640-A 102 121 138 1.19 0.88 hsa-mir-100-1/2-A 681 238 272 0.35 0.88 hsa-mir-659-P 163 97 110 0.59 0.88 hsa-mir-138-1-A 288 69 79 0.24 0.88 hsa-mir-657-A 442 758 865 1.71 0.88 hsa-mir-133a1-A 36 76 87 2.10 0.87 hsa-mir-544-A 37 189 216 5.12 0.87 hsa-mir-449b-P 1163 3705 4257 3.18 0.87 hsa-mir-361-P 524 752 866 1.43 0.87 hsa-mir-213-A 8799 4498 5198 0.51 0.87 hsa-mir-105-1-A 21 178 206 8.63 0.86 hsa-mir-199b-P 228 455 527 2.00 0.86 hsa-mir-448-A 254 291 337 1.15 0.86 hsa-mir-99b-A 817 373 432 0.46 0.86 hsa-mir-551a-P 160 39 45 0.24 0.86 hsa-miR-769-3p-A 234 246 286 1.05 0.86 hsa-miR-302b*-5p-A 19 33 39 1.78 0.86 hsa-mir-34-A 388 314 366 0.81 0.86 hsa-mir-634-P 111 239 279 2.15 0.86 hsa-mir-618-A 332 434 506 1.31 0.86 hsa-mir-31-A 193 207 242 1.08 0.86 hsa-mir-193b-A 1402 938 1099 0.67 0.85 hsa-mir-200a*-5p-A 5 46 54 8.90 0.85 hsa-mir-431-P 661 981 1156 1.48 0.85 hsa-mir-636-P 827 709 836 0.86 0.85 hsa-mir-129-1-P 187 380 449 2.03 0.85 hsa-mir-136-A 391 318 376 0.81 0.85 hsa-mir-516-1-P 39 58 69 1.47 0.84 hsa-mir-621-P 1420 1124 1333 0.79 0.84
Continued 160 Table 5.2 continued
Comparison of miRNA level in CEMx174 cells infected with HIV-1 or HIV-1 K51A (RSS) or mock infected Ratio Ratio Mock HIV-1 RSS HIV-1 / HIV-1 / MiRNA Probe Infection Infection Infection Mock RSS hsa-mir-602-A 669 947 1128 1.41 0.84 hsa-mir-661-A 240 568 677 2.36 0.84 hsa-mir-377-A 689 582 695 0.84 0.84 hsa-mir-133b-P 544 1199 1432 2.20 0.84 hsa-mir-524*-5p-A 66 35 42 0.53 0.84 hsa-mir-107-A 5692 2412 2882 0.42 0.84 hsa-mir-191*-3p-A 42 151 180 3.57 0.84 hsa-mir-539-P 3163 4763 5694 1.51 0.84 hsa-mir-483-A 4086 10168 12184 2.49 0.83 hsa-mir-141-A 203 294 352 1.44 0.83 hsa-mir-581-P 408 483 579 1.19 0.83 hsa-miR-181a-5p-A 3654 1821 2184 0.50 0.83 hsa-mir-30c-2-P 205 244 294 1.19 0.83 hsa-let-7c-A 914 113 136 0.12 0.83 hsa-mir-611-P 318 103 124 0.32 0.83 hsa-mir-15a-A 931 259 312 0.28 0.83 hsa-mir-550-1-P 386 421 508 1.09 0.83 hsa-mir-766-P 671 626 757 0.93 0.83 hsa-mir-128a-A 1223 640 774 0.52 0.83 hsa-mir-487b-P 316 284 343 0.90 0.83 hsa-mir-596-A 683 1578 1909 2.31 0.83 hsa-mir-188-A 125 134 162 1.07 0.83 hsa-mir-637-A 44 56 68 1.28 0.82 hsa-mir-142-5p-A 1591 387 470 0.24 0.82 hsa-mir-371-P 209 321 391 1.54 0.82 hsa-mir-126-5p-A 6196 6449 7852 1.04 0.82 hsa-mir-378-5p-A 36 99 121 2.73 0.82 hsa-mir-758-P 61 72 88 1.18 0.82 hsa-mir-502-A 212 123 150 0.58 0.82 hsa-mir-601-A 315 97 119 0.31 0.81 hsa-let-7g-A 446 97 119 0.22 0.81 hsa-mir-616-A 182 360 443 1.98 0.81 hsa-mir-518a2-3p-A 164 326 402 1.99 0.81 hsa-mir-320-A 2493 612 762 0.25 0.80 hsa-mir-199b-A 88 149 185 1.69 0.80
Continued 161 Table 5.2 continued
Comparison of miRNA level in CEMx174 cells infected with HIV-1 or HIV-1 K51A (RSS) or mock infected Ratio Ratio Mock HIV-1 RSS HIV-1 / HIV-1 / MiRNA Probe Infection Infection Infection Mock RSS hsa-mir-519d-A 45 48 60 1.06 0.79 hsa-mir-324-3p-A duplicate 109 176 222 1.61 0.79 hsa-mir-612-P 116 212 268 1.83 0.79 hsa-mir-335-P 1014 2191 2774 2.16 0.79 hsa-mir-577-P 112 183 232 1.63 0.79 hsa-mir-181d-P 11 63 79 5.77 0.79 hsa-mir-147-A 18 152 194 8.51 0.79 hsa-mir-205-A 230 334 424 1.45 0.79 hsa-mir-192-A 800 432 550 0.54 0.79 hsa-mir-632-P 652 467 596 0.72 0.78 hsa-mir-30c-1-P 308 450 574 1.46 0.78 hsa-mir-196a-1-P 303 258 330 0.85 0.78 hsa-mir-625-P 592 248 317 0.42 0.78 hsa-mir-758-A 15 39 51 2.68 0.78 hsa-miR-324-3p-A 298 440 564 1.48 0.78 hsa-mir-550-2-A 75 194 248 2.59 0.78 hsa-mir-222-A 2589 1299 1667 0.50 0.78 hsa-mir-346-A 2192 2335 2998 1.06 0.78 hsa-mir-186-A 252 125 160 0.50 0.78 hsa-mir-551a-A 177 205 264 1.16 0.78 hsa-mir-499-P 207 476 613 2.30 0.78 hsa-mir-125a-A 479 49 64 0.10 0.77 hsa-mir-24-3p-A 985 97 126 0.10 0.77 hsa-mir-591-P 502 1353 1758 2.70 0.77 hsa-mir-150-A 686 1419 1849 2.07 0.77 hsa-mir-609-P 242 222 289 0.92 0.77 hsa-mir-671-A 241 86 112 0.36 0.77 hsa-mir-566-A 2212 2614 3412 1.18 0.77 hsa-mir-362-P 69 91 119 1.31 0.76 hsa-mir-661-P 460 305 400 0.66 0.76 hsa-mir-211-P 105 186 244 1.77 0.76 hsa-miR-181a*-3p-A 142 140 183 0.98 0.76 hsa-mir-326-P 1060 1666 2195 1.57 0.76 hsa-mir-330-P 104 383 505 3.66 0.76
Continued 162 Table 5.2 continued
Comparison of miRNA level in CEMx174 cells infected with HIV-1 or HIV-1 K51A (RSS) or mock infected Ratio Ratio Mock HIV-1 RSS HIV-1 / HIV-1 / MiRNA Probe Infection Infection Infection Mock RSS hsa-mir-95-A 729 282 373 0.39 0.76 hsa-mir-637-P 140 400 530 2.86 0.75 hsa-mir-129-2-P 127 197 262 1.55 0.75 hsa-mir-484-A 645 796 1057 1.23 0.75 hsa-mir-518b-P 12 63 84 5.22 0.75 hsa-mir-181a1-5p-A 4197 1677 2232 0.40 0.75 hsa-mir-517*b-5p-A 40 54 72 1.37 0.75 hsa-mir-148b-A 142 53 70 0.37 0.75 hsa-mir-29b-1-A 582 51 68 0.09 0.75 hsa-mir-485-3p-A 320 740 995 2.31 0.74 hsa-mir-628-P 50 86 116 1.73 0.74 hsa-mir-370-A 469 99 134 0.21 0.74 hsa-mir-376a-3p-A 85 36 50 0.43 0.73 hsa-miR-373*-5p-A 2933 3504 4793 1.19 0.73 hsa-mir-326-A 215 384 527 1.79 0.73 hsa-mir-580-P 555 1203 1661 2.17 0.72 hsa-mir-24-2-A 1812 409 568 0.23 0.72 hsa-miR-324-5p-A 373 554 771 1.49 0.72 hsa-mir-181a2-P 309 257 359 0.83 0.71 hsa-mir-455-A 140 61 85 0.43 0.71 hsa-mir-551b-A 145 71 100 0.49 0.71 hsa-mir-619-A 21 37 53 1.80 0.71 hsa-mir-337-A 19 244 345 12.86 0.71 hsa-mir-654-P 141 187 265 1.33 0.70 hsa-mir-801-P 1902 5616 7978 2.95 0.70 hsa-mir-324-5p-A duplicate 510 826 1180 1.62 0.70 hsa-mir-585-A 122 134 192 1.10 0.70 hsa-mir-194-1-P 25 109 156 4.39 0.70 hsa-mir-422a-P 290 625 895 2.16 0.70 hsa-mir-196a1-P 172 108 156 0.63 0.70 hsa-mir-7-2-P 136 119 171 0.87 0.69 hsa_mir_320_Hcd306 left 1138 1742 2511 1.53 0.69 hsa-mir-602-P 153 204 294 1.33 0.69 hsa-mir-650-P 2281 5417 7830 2.37 0.69
Continued 163 Table 5.2 continued
Comparison of miRNA level in CEMx174 cells infected with HIV-1 or HIV-1 K51A (RSS) or mock infected Ratio Ratio Mock HIV-1 RSS HIV-1 / HIV-1 / MiRNA Probe Infection Infection Infection Mock RSS hsa-mir-513-2-A 36 88 128 2.42 0.68 hsa-mir-320-P 1190 2265 3315 1.90 0.68 hsa-mir-100-A 584 141 207 0.24 0.68 hsa-mir-299-5p-A 53 92 134 1.73 0.68 hsa-mir-328-A 1165 2817 4133 2.42 0.68 hsa-mir-423-A 154 67 99 0.44 0.68 hsa-mir-424-P 62 66 98 1.05 0.67 hsa-mir-491-P 109 222 330 2.03 0.67 hsa-mir-588-P 61 71 105 1.17 0.67 hsa-mir-505-A 106 212 315 1.99 0.67 hsa-mir-642-P 127 192 287 1.51 0.67 hsa-mir-604-P 95 180 272 1.90 0.66 hsa-mir-369-3p-A 153 42 63 0.27 0.66 hsa_mir_320_Hcd306 right 2292 509 768 0.22 0.66 hsa-mir-135a2-A 3500 813 1229 0.23 0.66 hsa-mir-194-2-P 14 68 102 4.86 0.66 hsa-mir-379-A 159 64 98 0.40 0.66 hsa-mir-593-P 1308 2106 3204 1.61 0.66 hsa-mir-92-2-A 43828 14466 22021 0.33 0.66 hsa-mir-149-A 346 663 1014 1.92 0.65 hsa-mir-613-P 72 87 133 1.21 0.65 hsa-mir-451-P 105 34 53 0.33 0.65 hsa-mir-770-A 290 393 606 1.36 0.65 hsa-mir-615-A 469 893 1381 1.91 0.65 hsa-mir-657-P 269 57 89 0.21 0.64 hsa-let-7d-v2-P 118 144 226 1.22 0.64 hsa-mir-566-P 2309 2496 3963 1.08 0.63 hsa-mir-30d-A 4590 1573 2499 0.34 0.63 hsa-let-7a2-P 85 152 243 1.80 0.63 hsa-mir-216-A 29 71 113 2.45 0.63 hsa-mir-296-A 178 255 407 1.43 0.63 hsa-mir-18b-P 13 42 68 3.18 0.62 hsa-mir-379-P 202 58 93 0.29 0.62 hsa-mir-500-P 311 412 664 1.33 0.62
Continued 164 Table 5.2 continued
Comparison of miRNA level in CEMx174 cells infected with HIV-1 or HIV-1 K51A (RSS) or mock infected Ratio Ratio Mock HIV-1 RSS HIV-1 / HIV-1 / MiRNA Probe Infection Infection Infection Mock RSS hsa-mir-125b1-A 1340 96 155 0.07 0.62 hsa-mir-605-A 74 191 309 2.58 0.62 hsa-mir-25-A 10267 2735 4438 0.27 0.62 hsa-mir-594-A 11390 3528 5738 0.31 0.61 hsa-mir-10a-A 440 116 189 0.26 0.61 hsa-mir-660-A 378 153 250 0.40 0.61 hsa-mir-125b2-A 1036 163 270 0.16 0.60 hsa-mir-30a-3p-A 416 100 171 0.24 0.58 hsa-mir-611-A 16 66 114 4.23 0.58 hsa-mir-425-5p-A 874 100 173 0.11 0.58 hsa-mir-193a-A 212 84 145 0.40 0.58 hsa-mir-106b-P 15 101 176 6.70 0.57 hsa-mir-99a-A 564 53 93 0.09 0.57 hsa-mir-92-1-A 62895 21919 38328 0.35 0.57 hsa-mir-449-P 5 38 67 7.44 0.57 hsa-mir-128b-A 727 192 342 0.26 0.56 hsa-mir-23a-A 9669 1799 3242 0.19 0.56 hsa-mir-197-A 1014 1655 3003 1.63 0.55 hsa-mir-671-P 82 110 200 1.34 0.55 hsa-mir-130b-P 1005 1435 2612 1.43 0.55 hsa-mir-412-A 361 339 627 0.94 0.54 hsa-mir-339-A 151 94 175 0.62 0.54 hsa-mir-488-A 94 59 110 0.63 0.54 hsa-mir-365-1-A 227 40 77 0.18 0.53 hsa-mir-185-P 689 1124 2135 1.63 0.53 hsa-mir-644-A 64 83 160 1.30 0.52 hsa-mir-410-P 165 66 130 0.40 0.51 hsa-mir-105-2-P 281 124 246 0.44 0.50 hsa-mir-571-P 90 110 218 1.22 0.50 hsa-mir-550-1-A 20 62 131 3.16 0.47 hsa-mir-105-2-A 85 62 134 0.73 0.47 hsa-mir-32-A 1032 113 243 0.11 0.46 hsa-mir-565-P 634 94 207 0.15 0.46 hsa-mir-33b-A 529 312 694 0.59 0.45 hsa-mir-301-P 7427 3213 7203 0.43 0.45
Continued 165 Table 5.2 continued
Comparison of miRNA level in CEMx174 cells infected with HIV-1 or HIV-1 K51A (RSS) or mock infected Ratio Ratio Mock HIV-1 RSS HIV-1 / HIV-1 / MiRNA Probe Infection Infection Infection Mock RSS hsa-mir-594-P 3010 519 1274 0.17 0.41 hsa-mir-136-P 577 41 105 0.07 0.39 hsa-mir-565-A 3692 1602 4198 0.43 0.38 hsa-mir-365-2-P 55 33 89 0.60 0.37 hsa-mir-204-P 921 721 2394 0.78 0.30 hsa-mir-321-A 2423 403 1451 0.17 0.28 hsa-mir-321-AP 2784 260 1726 0.09 0.15 hsa-let-7i-P 30 73 502 2.42 0.14
166
Table 5.3. Comparison of miRNA cluster members’ expression levels. Three known miRNA clusters’ miRNA probes’ expression are compared between HIV-1 and RSS samples from two replicate experiments ( − : below detection limits).
Comparison of miRNA cluster members’ expression levels in HIV-1 infection compared to RSS infection. HIV-1 HIV-1 Mock HIV-1 RSS Infection/ Infection/ Infection Infection Infection Mock RSS MiRNA Probe Exp. Exp. Exp. Infection Infection hsa-mir-17-3p-A 135 − − − − hsa-mir-17-5p-A 8097 4328 1986 0.53 2.18 hsa-mir-18a-A − − − − − hsa-mir-19a-A 405 286 148 0.71 1.94 Cluster hsa-mir-19b1-A 490 138 101 0.28 1.37 17-92 hsa-mir-20a-A 9238 5066 2207 0.55 2.30 hsa-mir-20b-A 6211 3528 1445 0.57 2.44 hsa-mir-20b-P − − − − − hsa-mir-92-1-A 62895 21919 38328 0.35 0.57 hsa-mir-92-1-P 252 397 290 1.58 1.37 hsa-mir-29a-A 1133 87 72 0.08 1.22 Cluster hsa-mir-29a-P 275 291 299 1.06 0.97 29a,b-1 hsa-mir-29b-1-A 582 51 68 0.09 0.75 hsa-mir-29b-1-P 264 131 125 0.49 1.05 Cluster hsa-mir-29b2-A 567 − 54 − − 29b-2,c hsa-mir-29c-A 754 52 39 0.07 1.35
167
CHAPTER 6
PERSPECTIVES
Approaches implemented by a virus to evade host cell defenses against virus infection are topics of great interest and importance in infectious disease research. A key issue is to understand the molecular basis of specific protein or RNA molecules that modulate virus-host interactions. In this dissertation, a retroviral model system was used to investigate post-transcriptional virus-host interactions. These outcomes inform fundamental issues of gene expression and development of new and improved antiviral strategies.
RNA helicase A facilitates translation of selected retroviral and cellular mRNAs
Using proteomic, genetic and biochemical analysis of retroviral genomes, our laboratory has identified a specialized post-transcriptional control mechanism operated by
RNA helicase A that acts on selected retrovirus and cellular genes (3;4;8;9;54;127). RHA specifically recognizes structural features of the PCE to facilitate efficient cap-dependent translation (9;127). An important question is how RHA activity on the PCE is regulated.
Ongoing investigation of inter- and intra-molecular interactions between RHA domains is revealing that RHA may exist in alternative conformations that confer inactive and active
168 states, similar to the regulation of cellular antiviral protein kinase R (PKR) by
double-stranded RNA (Jing W and Boris-Lawrie K unpublished observations). Ongoing
study of RHA during conditions of cell stress is showing that RHA is a target for caspase
cleavage during serum starvation, which downregulates PCE activity (Sharma A and
Boris-Lawrie K, unpublished observations). It is possible that caspase-cleaved isoforms of
RHA serve additional unidentified functions in the cell as part of the stress response.
Another issue is possible modulation of the cytoplasmic localization of RHA during cell
cycle progression. Ongoing investigation indicates that RHA can co-localize with the RNA
granule marker TIA-1 (Bolinger C and Boris-Lawrie K, unpublished observations). Our
laboratory’s findings posit that during conditions of normal growth, the RHA/PCE RNA
switch is active to facilitate PCE-mRNA translation and contribute to growth. However,
under stress conditions, such as serum starvation, RHA is sequestered in cytoplasmic RNA storage granules of translationally silenced RNPs. Furthermore, accessory components of the RHA:PCE complex are being investigated to understand protein co-factors that confer the specific functions of the RHA/PCE switch (Ranji A and Boris-Lawrie K, unpublished observations). Using microarray approaches, our laboratory identified two databases of candidate cellular PCE genes that require RHA for polyribosome association or that co-immunoprecipitate with RHA in COS cells (Hernandez et al. unpublished observations). The intersection of these databases identified archetype cellular PCE genes that exhibit a generic signature in their 5’ UTR. The sequence motifs exhibit secondary structural features that are postulated to be essential for PCE activity. We previously identified two redundant stem-loop structures that are necessary for retrovirus PCE activity
(127).
169 What may be a functional role for RHA in the small RNA pathway?
Recent biochemical experiments determined RNA helicase A is a component of
RNA silencing induced complex (RISC) (38). This observation raised the possibility that
RHA plays a role in the small RNA pathway, possibly by providing helicase activity. RHA
unwinding of duplex of small RNA and its target could interface with Ago-2 binding (38).
RHA contains two double-stranded RNA (dsRNA) binding domains at the N-terminus.
HIV-1 Tat encodes a dsRNA binding domain that is required for Tat RSS function (169).
To date, several RSSs have been shown to inhibit the small RNA pathway by binding small
RNAs, such as NS1, B2 and P19 (109). Therefore, we speculate that RHA also might bind
small RNAs and inhibit the small RNA pathway. Comparison of the miRNA sequences
from a published miRNA database (miRbase) to SNV PCE revealed complementarity between several cellular miRNAs and SNV PCE (Boris-Lawrie K, unpublished observations). This posited that RHA interaction with miRNA may contribute to PCE activity. Several experiments are proposed to evaluate this hypothesis. First, RNA-IP experiment may identify the interaction between RHA and cellular miRNA. MicroRNA microarry analysis could be used to identify what miRNAs bind to RHA. Second, the miR30 luciferase reporter system described in Chapter 3 will be used to test RHA RSS activity. Investigation of possible RHA-PCE-miRNA interplay will expand our current knowledge of PCE activity and help to elucidate unifying principles governing gene expression.
170 What is the effect of HIV-1 Tat RSS on the small RNA pathway?
The small RNA pathway is emerging as a new paradigm for modulation of
virus-host interaction. We demonstrated that HIV-1 Tat protein can suppress the small
RNA pathway in mammalian and plant cells and that Tat RSS functions at a step
downstream of the maturation of precursor miRNA to mature miRNA (169). However, our
results diverge from an in vitro biochemical observation that Tat inhibits Dicer activity in a
dsRNA-binding dependent manner. Our results that Tat RSS functions across kingdoms in
plant and animal cells are not surprising given that Tat and P19 share conserved amino acid
residues in their dsRNA-binding domains. Tat K51 mutation of the dsRNA-binding domain caused the loss of Tat RSS function. A similar amino acid residue in P19 was reported to be critical for P19 RSS activity and facilitates direct P19 binding to small RNAs
(102). Our functional results indicated that Tat shares a mechanism similar to P19 in suppressing small RNA function by competing for binding to small RNAs and thus blocking RISC loading. An experimental approach to address this hypothesis is to perform
Electrophoretic Mobility Shift Assay (EMSA) with recombinant Tat protein and
radiolabeled miRNA; a protein-RNA shift by Tat but not the K51 mutant Tat would verify
the miRNA binding capability of Tat. RNA immunoprecipitation using anti-Tat antibody
in transfected human cells would confirm direct binding of Tat and small RNAs in vivo by
realtime RT-PCR (Invitrogen).
Is the small RNA pathway involved in antiviral immunity in mammalian cells?
Double-stranded RNA (dsRNA) has been considered a by-product of virus infection
(reviewed in (215)). During the replication cycle of typical RNA viruses, long dsRNA 171 molecules are produced. In plants and invertebrates, these dsRNA are processed by Dicer
to generate mature siRNA that can induce RNA silencing (216;217). Currently, RNA
silencing is considered a key component of the innate immune response to viral infection in
both plants and invertebrate animals (217). However, in mammalian cells, long dsRNA
sequences (more than 30 base pairs) are potential inducers of the cellular interferon
response and cellular effectors such as PKR (translation inhibition), RNase L (RNA degradation) and ADAR (RNA editing) (215). Because of these redundant mechanisms some argue that mammalian cells do not need siRNA-based antiviral responses (217).
Nevertheless, the recently identified microRNA pathway identified an approach to escape the host cell defense. The miRNA is processed from a stem-loop structured primary miRNA (pri-miRNA) and further processed to produce a ~70 nt precursor miRNA
(pre-miRNA) in the nucleus. Further cleavage by Dicer in the cytoplasm produces the mature miRNA duplex; the “guide strand” is loaded onto RISC, which inhibits mRNA cleavage or translation (reviewed in Chapter One). Notably, although pri-miRNA, pre-miRNA and mature miRNA duplex molecules certainly have secondary structure and form dsRNA during the small RNA biogenesis pathway, these short and imperfect stems are distinct from the long and perfect dsRNA molecules that induce the IFN pathway (217). dsRNA fragments shorter than 30 bp do not activate PKR activity to any significant degree
(218) and small RNAs ranging from 21-27 bp are very poor activators of
2’-5’-oligoadenylate synthetase (215).
172 If the small RNA pathway has antiviral function during virus infection in mammalian cells, two predictions logically follow. First, inhibition of the small RNA pathway should enhance virus replication. Take HIV-1 for example, we reported in
Chapter Three that inhibition of the small RNA pathway by down-regulation of Dicer or
P19 RSS expression upregulated HIV-1 Gag production at 3-fold (169). Second, virus may encode an RSS, similar to the protective proteins of plant and insect viruses. Recently, several mammalian viruses have been shown to encode viral factors that exhibit RSS activity in animal cells. These factors include the influenza A virus NS1 (NS1), vaccinia virus E3L (E3L), hepatitis C virus core, primate foamy virus type 1 (PFV-1) Tas, ebola virus Viral protein 35 (VP35) and the adenovirus virus-associated RNAs I and II (VAI and
VAII) (93;99;104;219). Recently, we and others reported that HIV-1 Tat is an RSS that suppresses the small RNA pathway in both plants and animals (105;169).
Does HIV-1 acute replication modulate host microRNA expression?
We have demonstrated that the miRNA pathway plays a role in acute replication of
HIV-1 (Chapters Three, Four, and Five). In Chapters Four and Five, we addressed the miRNAs affected by HIV-1 infection and the broad issue of possible targets of host-encoded miRNA that modulate HIV-1. Host-encoded miRNA could modulate HIV-1 either by direct targeting to HIV-1 genome or indirect targeting to cellular factors that are essential for HIV-1 replication. Presumably, all cellular and viral genes that contribute to the HIV-host interplay could be targets of miRNA to either facilitate viral replication or cellular defense. The miRNA microarray database that we built in Chapters Four and Five will help identify the role of at least some miRNAs. 173 Does HIV-1-encoded TAR RNA possess additional RSS activity?
Another important question is whether or not other HIV-1 encoded proteins or
RNAs have RSS activity. A prime candidate is TAR RNA. TAR is 57 nt stem-loop structured RNA and has been suggested to serve as a Dicer substrate to produce small
RNA. It is possible that a large amount of TAR RNA would hijack Dicer in HIV-1 infected cells. This notion is supported by our microarray data in Chapters Four and Five where we demonstrated that HIV-1 infection down-regulates global miRNA expression. TAR sequestration of Dicer would reduce the production of endogenous miRNA. Additionally,
TAR binds to TRBP to facilitate Tat transcriptional activation. TRBP was identified recently as a cofactor that stabilizes Dicer and promotes the Dicer and Argonaut 2 (Ago-2) interaction to form the RISC (68;108). Therefore, TAR could act as a potent RSS by usurping Dicer and TRBP to potently suppress both miRNA biogenesis and RISC formation.
Our microarray data suggest that Vpr/Vif could be novel RSS proteins. Cells infected with vpr/vif-deficient HIV-1 exhibit less global down-regulation of miRNA expression compared to wild-type HIV-1 (Chapter Four). The possible mechanisms of how
Vpr/Vif suppresses global miRNA biogenesis could be related to the Vpr-induced cell cycle arrest at G2/M stage. Our lab has shown that Vpr can suppress global protein translation inhibition (Yilmaz A, Boris-Lawrie K unpublished observations), which may downregulate RNA translation to Drosha and Dicer. Reduced Drosha or Dicer protein would reduce miRNA production. This hypothesis could be addressed by western blot to determine the steady-state level of Drosha and Dicer protein and radio-
174 immunoprecipitation to measure de novo synthesis rate changes in Dicer and Drosha
during Vpr-induced cell cycle arrest.
Whether HIV-1 encodes small RNAs is controversial
Many plant viruses produce viral small RNAs that control host defense systems and
in turn sustain virus replication. Whether HIV-1 also encodes its own small RNAs
(VsRNA) is controversial. Certainly, HIV-1-encoded miRNAs are not a necessary feature
of the virus armamentarium to disable the innate RNA response. Some studies have
successfully identified HIV-1 VsRNA; however, two other groups failed to replicate the
experiments (reviewed in Chapter One) (14;84;105;111-115). A discrepancy between the
studies was that the RNA samples for cloning were harvested at the different stages of
infection or transfection. As we discussed in Chapter One, a relatively long progression of
virus infection (hours instead of minutes) is important for virus to produce VsRNA since
RNAi functions at a late stage of gene expression (posttranscriptional level). This notion is supported by the functions of cellular miRNA on HIV-1 during the latency stage.
Alternatively, the tradition cloning method used in their studies might not have been sensitive enough to clone the low amounts of VsRNAs. RNA samples from later stage
AIDS patients together with a sensitive sequencing method that allows extremely low levels of detection, such as 454 sequencing, would provide a better opportunity to clone and study VsRNAs.
175 What are possible implications for use of small RNA in antiviral therapy?
The application of miRNA to development of new and improved antiviral treatments is of interest to the field. Our study in Chapter Three demonstrated that miRNA affect progression of the acute HIV-1 infection. Inhibition of the host small RNA pathway by down-regulation of Dicer or over-expression of P19 produced a three-fold increase in
HIV-1 virion production. These findings suggest that Dicer downregulation is an opportunity to slow the course of disease at the acute infection stage by blocking miRNA mediated translation inhibition. We speculate that down-regulation of specific host miRNAs will delay the onset of AIDS significantly. Chemically modified, cholesterol conjugated single strand RNA analogues complementary to miRNAs also could be used in future antiviral therapies. Alternatively, over-expression of the cellular miRNAs that target
HIV-1 transcripts may prolong HIV-1 latency. However, one could argue that high doses of “RNA-drug” will lead to cell toxicities via competition for the usage of the cellular miRNA machinery, thus resulting in inhibition of the normal endogenous miRNA function. To avoid this potential problem, tissue-specific or cell-specific miRNAs can be used and low doses of “RNA drug” would help to minimize the off-target effects.
Altogether, a full understanding of the interplay between HIV-1 and the host miRNA pathway will offer a great opportunity to develop strategic targets for antiviral therapies.
176
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