Identification of Novel Compounds That Inhibit HIV-1 Gene … · 2016. 11. 20. · Expression by...

Identification of Novel Compounds That Inhibit HIV-1 Gene Expression by Targeting Viral RNA Processing

by

Ahalya Balachandran

A thesis submitted in conformity with the requirements for the degree of Master of Science

Department of Molecular Genetics University of Toronto

© Copyright by Ahalya Balachandran 2015

ii

Identification of Novel Compounds That Inhibit HIV-1 Gene

Expression by Targeting Viral RNA Processing

Ahalya Balachandran

Master of Science

Department of Molecular Genetics

University of Toronto

2015

Abstract

Novel strategies targeting different stages of the HIV lifecycle are vital for continued success in

combating viral infection. Since HIV gene expression is dependent upon controlled splicing of

the viral transcript, small molecule modulators of RNA processing hold tremendous promise as

novel drugs. To this end, we screened splicing modulators for their effect on HIV-1 gene

expression. We identified four compounds, 191, 791, 833 and 892, that strongly suppressed

accumulation of HIV-1 incompletely spliced RNA and expression of viral structural/regulatory

proteins. Furthermore, compound treatment had limited effects on alternative splicing of host

RNA splicing events. Subsequent studies confirmed anti-HIV activity of two compounds in the

context of peripheral blood mononuclear cells. The distinct effects of these compounds from

previously characterized HIV-1 RNA processing inhibitors validate targeting this stage of the

virus lifecycle. Elucidating the mechanism by which these compounds alter HIV-1 gene

expression holds key insights for novel therapeutic strategies.

iii

Acknowledgments

I would like to thank my supervisor, Dr. Alan Cochrane, for the opportunity to work on

this project in his laboratory over the past few years. I would also like to thank my committee

members, Dr. Lori Frappier, Dr. Craig Smibert, and Dr. Peter Roy, for their continued guidance

and support. It has been a pleasure working with all members of the Cochrane Lab over the past

few years. I’d like to thank all the students and post docs for their help and support along the

way. Special thanks go to Raymond Wong for taking me under his wing when I was an

undergraduate student and for sharing his knowledge and experience about the drug screening

projects in our lab. I’d also like to thank Dr. Alex Chen for training me in preparation for

working with replicative HIV in the BSL3 facility and the Scott Gray-Owen Lab for source of

PBMCs. Last but not least, I’d like to thank our collaborators Dr. Peter Stoilov at West Virginia

and Dr. Sandy Pan from the Blencowe Lab for examining the effect of the compounds on

cellular alternative splicing. The work presented here would not be possible without funding

provided by CIHR grants, as well as the Ontario Graduate Scholarship Award.

iv

Table of Contents

Acknowledgments.......................................................................................................................... iii

Table of Contents ........................................................................................................................... iv

List of Tables ............................................................................................................................... viii

List of Figures ................................................................................................................................ ix

List of Appendices ......................................................................................................................... xi

Abbreviations ................................................................................................................................ xii

1 Introduction .................................................................................................................................1

1.1 mRNA processing ................................................................................................................1

1.1.1 mRNA capping ........................................................................................................1

1.1.2 Constitutive splicing and the spliceosome ...............................................................2

1.1.3 Alternative splicing ..................................................................................................2

1.1.4 Polyadenylation........................................................................................................4

1.1.5 RNA export ..............................................................................................................4

1.1.6 Translational initiation .............................................................................................6

1.1.7 Interdependence of events in mRNA processing .....................................................6

1.2 Regulation of mRNA splicing .............................................................................................7

1.2.1 Role of cis elements in splicing ...............................................................................7

1.2.2 Role of trans factors in splicing .............................................................................10

1.2.2.1 SR-protein family of splicing factors ......................................................10

1.2.2.2 Heterogeneous nuclear ribonucleoproteins (hnRNPs) ............................10

1.2.3 Regulation of splicing factors ................................................................................11

1.2.4 Splicing factors and signaling pathways ................................................................12

1.3 Perturbation of alternative splicing in disease ...................................................................14

1.4 HIV-1 utilizes host alternative splicing machinery for viral gene expression ...................15

v

1.4.1 Overview of the HIV-1 lifecycle ...........................................................................15

1.4.2 Current treatment strategies for HIV-1 ..................................................................16

1.4.3 Limitations of current HIV-1 therapies ..................................................................18

1.4.4 HIV-1 RNA processing..........................................................................................19

1.4.5 Regulation of HIV-1 RNA splicing .......................................................................19

1.4.6 HIV-1 gene expression and Rev-dependent export ...............................................24

1.5 Modulation of RNA splicing as a therapeutic strategy ......................................................27

1.5.1 Modulation of AS using small molecules ..............................................................27

1.5.1.1 Spliceosome inhibitors ............................................................................29

1.5.1.2 Histone deacetylase (HDAC) inhibitors ..................................................29

1.5.1.3 Topoisomerase (Topo I) inhibitors ..........................................................30

1.5.1.4 Kinase and phosphatase inhibitors ..........................................................30

1.6 Effect of splicing modulators on HIV-1 gene expression ..................................................31

1.7 Research objective and rationale .......................................................................................33

2 Materials and Methods ..............................................................................................................34

2.1 HIV-1 provirus doxycycline-inducible cell lines ...............................................................34

2.2 Assess activity of compounds on HIV-1 gene expression .................................................34

2.2.1 Preparation of compounds .....................................................................................34

2.2.2 Compound treatment assay ....................................................................................34

2.3 HIV-1 p24 antigen ELISA .................................................................................................36

2.4 XTT cytotoxicity assay ......................................................................................................36

2.5 Analysis of HIV-1 protein expression ...............................................................................37

2.6 Analysis of HIV-1 RNA expression and localization ........................................................38

2.6.1 RNA extraction and reverse transcription ..............................................................38

2.6.2 Quantification of HIV-1 mRNA expression by qPCR ..........................................38

2.6.3 Analysis of splice site selection within the HIV-1 MS RNA ................................39

vi

2.6.4 Analysis of HIV-1 US RNA subcellular localization ............................................40

2.7 Monitoring protein synthesis by SUnSET .........................................................................42

2.8 Viral protein degradation assay .........................................................................................44

2.9 Proteasomal degradation protection assay .........................................................................44

2.10 Analysis of cellular alternative splicing events by RT-PCR .............................................45

2.11 Analysis of cellular alternative splicing by RNA sequencing ...........................................45

2.11.1 Sample preparation for RNA sequencing (RNAseq) .............................................45

2.11.2 RNAseq ..................................................................................................................46

2.11.3 Analysis of RNAseq data .......................................................................................46

2.11.3.1 Gene expression estimation .....................................................................46

2.11.3.2 Percent spliced in (PSI) estimation ..........................................................47

2.12 Compound treatment assay in primary cells ......................................................................48

2.12.1 Human primary cell donors and cell preparation ...................................................48

2.12.2 Generation of replication-competent HIV-1 virus .................................................48

2.12.3 HIV-1 BaL infection of primary cells ....................................................................49

2.12.4 Compound treatment of primary cells ...................................................................49

2.13 Statistical analysis ..............................................................................................................50

3 Results .......................................................................................................................................51

3.1 Identification of four compounds that suppress HIV-1 gene expression in HeLa cells ....51

3.1.1 Previously published literature for 191, 791, 833, and 892 activity ......................53

3.2 191, 791, 833, and 892 potently inhibited HIV-1 gene expression in a dose-dependent

manner................................................................................................................................54

3.3 191, 791, 833, and 892 decreased HIV-1 structural and regulatory protein expression ....54

3.4 191, 791, 833, and 892 reduced HIV-1 US and SS RNA but not MS RNA .....................56

3.5 191 and 791 did not alter splice site usage among HIV-1 MS RNA .................................60

3.6 Inhibition of cytoplasmic accumulation of HIV-1 US RNA and Gag with compound

treatment was consistent with perturbation of Rev function .............................................62

vii

3.7 191, 791, 833, and 892 did not affect total protein synthesis ............................................62

3.8 The compounds did not alter the stability of existing HIV-1 Tat protein. .........................67

3.9 791 did not significantly affect cellular alternative splicing while 191, 833, and 892

had limited effects ..............................................................................................................70

3.10 Preliminary analysis of the effect of the compounds on expression of cellular splicing

factors .................................................................................................................................75

3.11 191 and 791 inhibit HIV-1 BaL replication in primary cells .............................................77

4 Discussion .................................................................................................................................80

4.1 Future Directions ...............................................................................................................88

4.2 Conclusions ........................................................................................................................90

Appendices ...................................................................................................................................102

I. Analysis of cellular alternative splicing by RT-PCR .......................................................102

II. Global analysis of cellular alternative splicing and gene expression by RNA seq ..........110

viii

List of Tables

Table 1.1 List of small molecule inhibitors of alternative splicing and their molecular targets ... 41

Table I-1 Effect of 892 treatment on a subset of cellular alternative splicing (AS) ................... 112




Table II-1 Effect of 791 treatment on a cellular alternative splicing (AS) by RNAseq ............. 120

Table II-1 Effect of 191 treatment on a cellular alternative splicing (AS) by RNAseq ............. 126

Table II-3 Effect of 791 treatment on a gene expression by RNAseq. ....................................... 133

Table II-4 Effect of 191 treatment on a gene expression by RNAseq. ....................................... 136

ix

List of Figures

Figure 1.1 Mechanism of mRNA splicing .................................................................................... 16

Figure 1.2 Possible products of alternative splicing of a hypothetical gene ................................. 18

Figure 1.3 Regulation of alternative splicing by SR and hnRNP proteins ................................... 21

Figure 1.4 Cellular alternative splicing factors ............................................................................. 22

Figure 1.5 Regulation of alternative splicing by signaling pathways ........................................... 26

Figure 1.6 HIV-1 lifecycle and current treatment strategies ......................................................... 30

Figure 1.7 HIV-1 mRNA splicing and regulation ........................................................................ 33

Figure 1.8 HIV-1 gene expression in host cell ............................................................................. 38

Figure 2.1 Schematic of HIV-1 proviral system integrated in HeLa cell lines ............................. 48

Figure 2.2 Characterization of HeLa C7 cells for fluorescence studies ....................................... 54

Figure 2.3 Compound treatment in HeLa C7 cells inhibits HIV-1 gene expression in a dose-

dependent manner similar to effects observed in HeLa B2 cells .................................................. 56

Figure 3.1 Screen of RNA splicing modulators identifies four potent inhibitors of HIV-1 gene

expression. .................................................................................................................................... 65

Figure 3.2 Compound treatment inhibits HIV-1 gene expression in a dose-dependent manner .. 68

Figure 3.3 Compound treatment dramatically decreases the expression of HIV-1 structural

proteins .......................................................................................................................................... 70

Figure 3.4 191, 791, 833, and 892 dramatically decrease the expression of HIV-1 regulatory

proteins, in contrast to previously characterized HIV-1 inhibitors ............................................... 71

Figure 3.5 The compounds dramatically decrease the levels of HIV-1 US and SS RNAs .......... 72

Figure 3.6 191 and 791 do not alter splice site selection within HIV-1 MS RNAs...................... 74

x

Figure 3.7 Compounds inhibit cytoplasmic accumulation of HIV-1 US RNA ............................ 76

Figure 3.8 The compounds do not affect total protein synthesis .................................................. 78

Figure 3.9 191 and 791 had better long-term toxicity profiles than 833 and 892......................... 79

Figure 3.10 Compounds do not affect the half-life of HIV-1 Tat relative to DMSO ................... 81

Figure 3.11 HIV-1 Tat expression can be rescued with proteasome inhibition by MG132 ......... 82

Figure 3.12 Compounds have limited effects on cellular alternative splicing events .................. 85

Figure 3.13 191 and 791 do not appreciably alter cellular alternative splicing events ................. 86

Figure 3.14 Differential host gene expression with 191 and 791 treatment ................................. 87

Figure 3.15 Compounds have limited effects on expression of cellular splicing factors ............. 89

Figure 3.16 191 and 791 inhibit HIV-1 replication in PBMCs .................................................... 91

Figure 3.17 191 and 791 inhibit HIV-1 replication in PBMCs in a dose-dependent manner....... 92

Figure 4.1 Proposed model for how the compounds inhibit HIV-1 gene expression ................... 97

xi

List of Appendices

I. Analysis of cellular alternative splicing by RT-PCR .......................................................112

II. Global analysis of cellular alternative splicing and gene expression by RNA seq ..........120

xii

Abbreviations

AIDS acquired immunodeficiency syndrome

BSA bovine serum albumin

DMSO dimethyl sulfoxide

Dox doxycyline

ELISA enzyme-linked immunosorbent assay

ESE exon splicing enhancer

ESS exon splicing silencer

FBS fetal bovine serum

HAART highly active antiretroviral therapy

HIV-1 human immunodeficiency virus type 1

hnRNP heterogeneous nuclear ribonucleoprotein

IC inhibitory concentration

IMDM Iscove’s modified Delbecco’s medium

MS multiply spliced

Nef negative effector

NRTI nucleoside or nucleotide reverse transcriptase inhibitor

NNRTI non-nucleoside reverse transcriptase inhibitor

P/S penicillin/streptomycin

PBS phosphate buffered saline

xiii

PCR polymerase chain reaction

qRT-PCR quantitative reverse transcription PCR

Rev regulator of expression of virion proteins

RT-PCR reverse transcription PCR

rtTA reverse tetracycline transactivator

snRNP small nuclear ribonucleoprotein particle

SS singly spliced

TAR trans-acting response region

Tat transactivator of transcription

tetO tet operator

US unspliced

Vif viral infectivity factor

Vpu virion protein unique to HIV-1

1

1 Introduction

Transcription of messenger RNA (mRNA) is the first step of converting the information stored

within a genome into functional proteins. In eukaryotic cells, mRNA is further processed by

events that include capping, splicing, and 3’ end formation to produce a mature mRNA prior to

subsequent export to the cytoplasm and translation. Human immunodeficiency virus 1 (HIV-1) is

a retrovirus that relies on host cellular mRNA processing for viral gene expression and

replication. However, unlike most cellular mRNAs, HIV-1 encodes many of its structural and

enzymatic proteins on unspliced viral RNAs. To overcome the requirement of fully processed

mRNAs for export, HIV-1 encodes a viral regulatory protein, Rev, which specifically binds and

exports incompletely spliced viral RNAs. Studying the interplay between host factors and viral

proteins can provide insight into novel strategies for inhibiting HIV-1 replication.

1.1 mRNA processing

mRNA processing refers to the series of events that occur for mature mRNA to be generated

from the primary transcript. This process was often seen as a linear cascade of events that

included mRNA capping, splicing, polyadenylation, export to the cytoplasm and translation to

produce the encoded protein. However, an increasing body of evidence over the years suggests a

shift in this paradigm. In fact, there is extensive crosstalk between these events and cellular

factors involved in mRNA processing often have roles in more than one of these events (1).

1.1.1 mRNA capping

The earliest processing event is modification of the 5’ end of the nascent RNA polymerase II

(Pol II) transcript, when it is 20-25 nucleotides in length, to form the 7-methyl guanosine cap (2).

This evolutionarily conserved modification is necessary for efficient eukaryotic gene expression

and cell viability (2). Formation of the cap occurs via three reactions by three different enzymes.

The 7-methylguanosine cap is joined to the first transcribed nucleotide via the 5′ hydroxyl group,

through a triphosphate linkage which is hydrolysed by an RNA 5′ triphosphatase (2). Next,

guanosine monophosphate is added to the diphosphate–RNA by a guanylyltransferase to produce

the guanosine cap, via a two-step reversible reaction (2). Finally, an RNA (guanine-7-)

methyltransferase catalyses the methylation of the guanosine cap at the N-7 position to produce

the 7-methylguanosine cap, using S-adenosylmethionine as the methyl donor (2). The cap serves

2

to protect mRNA from the action of 5’-exonucleases and promotes transcription, splicing,

polyadenylation and mRNA export (2).

1.1.2 Constitutive splicing and the spliceosome

Splicing is the process of excising the sequences in pre-mRNA corresponding to introns

(typically thousands of nucleotides in length), so that exons (typically hundreds of nucleotides in

length) are connected into a continuous mRNA to form the coding sequence (3). When only one

mature mRNA is formed in this process, it is called constitutive splicing. Splicing is carried out

by a large ribonucleoprotein complex referred to as the spliceosome, which recognizes conserved

sequence elements in the pre-mRNA. These include 5’ splice sites (5’ SS) and 3’ splice sites (3’

SS), the polypyrimidine tract (PPT) and the branchpoint sequence (BPS) (3). Figure 1.1A depicts

these elements and the proteins that bind to them. The spliceosome machinery consists of five

core small nuclear ribonucleoproteins (snRNPs), U1, U2, U5 and U4/U6 and up to 300 other

proteins. The pre-mRNA is recognized and bound by the splicing factor 1 (SF1) at the BPS and

the U2-associated factor (U2AF; 65 and 35 kDa subunits) at the PPT upstream of the 3’ splice

site (3’ss) (3). Following the binding of SF1 and U2AF, U1snRNP binds the 5’ splice site (5’ss)

and U2AF recruits U2 snRNP to the branch point. This U1-pre-mRNA-U2 complex then

interacts with the U4-U5-U6 snRNP complex and conformational rearrangement leads to the

splicing reaction by two transesterification steps, outlined in Figure 1.1B (3). The first step

involves the attack by the 2’ hydroxyl of the branch point adenine on the phosphate at the 5’ss,

cleaving the RNA at the 5’ exon/intron boundary. The second step involves the attack by one of

the hydroxyl groups of the terminal phosphate on the phosphate at the 3’ss, liberating the intron

in the form of a lariat (3). During the second step of splicing reaction, a complex of proteins

called the exon junction complex (EJC) recognizes the splicing complex and binds to the RNA

(3). The EJC complex consists of over nine proteins, including a group of proteins called the

REF family (3).

1.1.3 Alternative splicing

To increase the diversity of mRNAs expressed from the genome, almost all transcripts in higher

eukaryotic cells undergo alternative splicing (AS) of the pre-mRNA (3). Both constitutive and

alternative splicing is mediated by the spliceosome, but alternative splicing differentially links

exon regions in a single precursor mRNA to produce two or more different mature mRNAs. The

3

Figure 1.1 Mechanism of mRNA splicing.

A) Consensus splicing sequences. The 5’ss, BPS, PPT and 3’ss are represented and are bound by

U1 snRNP, SF1, U2AF65 and U2AF35, respectively. B) Splicing reaction. The first step

involves the attack by the 2’ hydroxyl of the branch point adenine on the phosphate at the 5’ss,

releasing the 3’end of the mRNA. The second step involves the attack by the hydroxyl of the

terminal phosphate on the phosphate at the 3’ss, liberating the intron in the form of a lariat.

Brosseau, J-P and S. Abou-Elela. The Merit of Alternative Messenger RNA Splicing as a New Mine for the Next

Generation Ovarian Cancer Biomarkers, Ovarian Cancer - A Clinical and Translational Update, InTech. Edited by

Dr. I. Diaz-Padilla (2013). Copyright Brosseau and Abou-Elela. Reproduced with permission.

Available from URL: <http://www.intechopen.com/books/ovarian-cancer-a-clinical-and-translational-update/the-

merit-of-alternative-messenger-rna-splicing-as-a-new-mine-for-the-next-generation-ovarian-cancer>

4

choice of which splice sites are used is regulated by cis-acting sequences present in the mRNA

exonic and intronic regions and trans-acting factors that bind to these elements to promote or

repress splicing at that site (3, 4). In addition, AS can also affect 5’ and 3’ untranslated region

(UTR) regulatory sequences and polyadenylation site selection. There are a number of possible

mRNA isoforms that may be generated by exon skipping, intron retention, alternative splice site

selection, alternative promoter usage and alternative polyadenylation (5). Some of these isoforms

are described in Figure 1.2. Thus, AS can lead to changes in the proteins encoded by mRNAs

and results in more profound functional effects in the cell. In fact, AS has been shown to regulate

binding, localization, enzymatic properties, interactions with ligands and enable additional post-

transcriptional control of gene expression (5). Thus, it is not surprising that aberrations in

alternative splicing has been implicated in numerous diseases, cancers and viral infections.

1.1.4 Polyadenylation

Mature 3’ ends of mRNAs are generated by endonucleolytic cleavage of the pre-mRNA,

followed by polyadenylation of the upstream cleavage product (6, 7). 3'-cleavage and

polyadenylation are closely coupled to the termination of transcription since Pol II transcribes

the DNA template several hundreds of nucleotides downstream of the cleavage and

polyadenylation site (conserved AAUAAA sequence), while specific sequence signals in the pre-

mRNA direct the binding of protein factors (6, 7). Polyadenylation requires more than a dozen

proteins but the main conserved factors include cleavage stimulation factor (CstF), cleavage/

polyadenylation specificity factor (CPSF), poly(A) polymerase (PAP), and the poly(A) binding

protein, PABPN1 (6, 7). PAP is not strongly associated with the end of the pre-mRNA initially,

until approximately 20 adenosines have been added and PABPN binds to the short poly(A)-tail.

Then, PAP is more firmly bound until 150-200 adenosines are rapidly added, at which point PAP

dissociates (6, 7) and the mRNA can be transported to the cytoplasm for translation.

1.1.5 RNA export

Nuclear export of mRNAs, occurs through nuclear pore complexes (NPCs) embedded in the

nuclear envelope. Generally, translocation of proteins and RNAs through the NPC is carried out

by soluble transport receptors, which recognize specific signals on the transport substrate and

mediate the interaction between the transport receptor–cargo complex and NPC components

d

5

Figure 1.2 Possible products of alternative splicing of a hypothetical gene

Types of alternative splicing that can generate functionally distinct transcripts are depicted. Blue

boxes indicate alternative exons.

Blencowe, BJ. Alternative splicing: new insights from global analyses. Cell 126:1 (2006). Copyright Elsevier Inc.

Reproduced with permission.

6

called nucleoporins (8, 9). However, export of fully processed RNA is difficult since the

transport substrate recognized by the mRNA export machinery is the messenger

ribonucleoprotein particle (mRNP) consisting of the mRNA molecule in association with cap

binding complex (CBC; CBP20 and CBP80), RNA binding proteins, splicing factors, the EJC

proteins (Aly/REF), PABPN and other factors involved in pre-mRNA processing (8, 9). Thus,

export of bulk mRNA is thought to be mediated by members of the conserved family of

TAP/NXF proteins (8, 9). TAP interacts with components of the NPC and binds directly or

indirectly to its RNA cargoes (usually by interaction with Aly/REF) via two distinct functional

domains: an N-terminal cargo-binding domain and a C-terminal NPC-binding domain (8, 9).

1.1.6 Translational initiation

Following nuclear export, the newly processed mRNA (in association with CBC, PABPN and

the EJC), undergoes a “pioneer round of translation” (10). This step is thought to assess the

quality of RNA processing before commitment to significant protein synthesis (10). During this

step, EJC proteins are removed, PABPN1 is replaced by PABPC (cytoplasmic isoform) and the

CBC is replaced by eukaryotic initiation factor 4E (eIF4E) (10). eIF4E is part of the eIF4F

translation initiation complex, consisting of eIF4E, eIF4G, and eIF4A (11, 12). eIF4E binds to

the mRNA cap and recruits the 43S ribosomal subunit and pre-initiation complex (PIC) by

binding to eIF4G (11, 12). eIF4G is the large scaffolding protein onto which the initiation factors

assemble by interaction with their corresponding domains. eIF4A is the ATP-dependent helicase

that unwinds the mRNA. Two additional factors, eIF4B and eIF4H are RNA-binding proteins

that stimulate the activity of eIF4A and stabilize single strand RNA regions. eIF4G also binds

PABPC, causing the mRNA to circularize and stimulates the formation of the PIC (11, 12).

Finally, the 60S ribosomal subunit is recruited and protein translation begins.

1.1.7 Interdependence of events in mRNA processing

For many years, the paradigm for mRNA processing was that pre-mRNA splicing was a post-

transcriptional process, with the spliceosomal machinery devoted to the removal of introns from

the transcripts. However, over the years, splicing and splicing factors were shown to impact

additional processes during transcription and extending to mRNA export and translation,

indicating a link between splicing and all the other steps in gene expression (5, 13). Furthermore,

it has also been demonstrated over the past decade, that pre-mRNA can be spliced

7

cotranscriptionally. Co-transcriptional splicing allows functional integration of transcription and

RNA processing, and could allow them to modulate one another, whereas post-transcriptional

splicing could facilitate coupling RNA splicing with downstream events such as RNA export (5,

13). Often RNA binding proteins can act as multi-taskers with roles in alternative splicing,

polyadenylation, RNA export and RNA transport (5, 13). Thus, there appears to be many

opportunities for crosstalk between splicing and other RNA-processing steps in the cell. This

additional level of regulation means that alternative splicing has a profound impact on many

aspects of gene regulation.

1.2 Regulation of mRNA splicing

It is estimated that 80–95% of human multi-exon pre-mRNAs are alternatively spliced (3). Thus,

to regulate mRNA isoform generation, there must be additional RNA sequences present in both

exon and intron elements to either stimulate or inhibit splicing (14). These sequences are referred

to as cis-acting RNA sequences and are often bound by trans-acting factors which facilitate or

prevent the recruitment of the splicing machinery to these sites as depicted in Figure 1.3 (14).

1.2.1 Role of cis elements in splicing

The requirement of exonic sequences other than the splice sites for correct processing of certain

transcripts was demonstrated experimentally by Reed and Maniatis (1986) (15). It was shown

that some cis-acting RNA sequence elements located within the regulated exons, increase exon

inclusion by serving as binding sites for the assembly of multicomponent splicing enhancer

complexes (15). Thus, these sequence elements were termed exonic splicing enhancers (ESEs).

Other classes of splicing regulatory elements that recruit proteins to enhance and silence splicing

were subsequently identified and named intronic splicing enhancers (ISEs), exonic splicing

silencers (ESSs) and intronic splicing silencers (ISSs), respectively, depending on their location

and effect on neighbouring splice sites. These elements allow the splicing machinery to

discriminate between pseudoexons and real exons, and between competing splice sites (14).

These silencer and enhancer sequences are often present near exon/intron junctions, suggesting

that the interplay between the activation and repression of cis-acting elements, by trans-acting

factors, regulates the extent of exon inclusion.

8

Figure 1.3 Regulation of alternative splicing by SR and hnRNP proteins

(A) Model for RS domain proteins in mediating the ESE-dependent inclusion of the alternative

exon. Members of the SR family and SR-related proteins bind to exonic splicing enhancer (ESE)

motifs (green bands) within the alternative exon (blue box) and facilitate the stable assembly of

U1 and U2 snRNPs. SR-related splicing coactivator proteins (green ovals) serves to bridge

interactions involving snRNPs and ESE-bound SR proteins. (B) Model for exonic splicing

silencer (ESS) dependent skipping of the alternative exon promoted by the binding of an hnRNP

protein to ESS motif (purple band). Binding of the ESS motif by the hnRNP protein disrupts

binding of one or more adjacent SR proteins, resulting in exon skipping. Not shown are

interactions involving intronic splicing enhancers (ISE) and silencers (ISS), which can function

to promote or repress interactions required for the inclusion of adjacent alternative exons.

Blencowe, BJ. Alternative splicing: new insights from global analyses. Cell 126:1 (2006). Copyright Elsevier Inc.

Reproduced with permission.

9

Figure 1.4 Cellular alternative splicing factors

(A) Classification of the main human alternative splicing factors by RNA-binding domain

composition. Only the proteins containing RRM domains are shown. (B) Members of the SR

protein family of splicing factors and their evolutionary relationship.

Cléry, A. and F. H-T. Allain. A structural biology perspective of proteins involved in splicing regulation (Chapter 4,

page 34) from Alternative pre-mRNA Splicing: Theory and Protocols, First Edition. Edited by Stefan Stamm, Chris

Smith, and Reinhard Lührmann. (2012). Copyright Wiley-VCH Verlag GmbH & Co. KGaA. Adapted and

reproduced with permission.

Francisco Javier Blanco and Carmelo Bernabéu. The splicing factor SRSF1 as a marker for endothelial senescence.

Front. Physiol. (2012). Copyright Blanco and Bernabéu.

A

B

10

1.2.2 Role of trans factors in splicing

The trans-acting cellular factors that regulate splicing can be categorized into three main

families: SR proteins, hnRNPs, and tissue-specific splicing factors. All of these splicing factors

contain different types of RNA-binding domains, with the most common being the RNA-

recognition motifs (RRMs), KH domains and zinc fingers (see Figure 1.4) (14). These factors

recognize specific RNA sequences, which in turn dictates their effect on select RNAs. Splicing

enhancer sequences generally recruit SR proteins or spliceosomal components to enhance exon

recognition. In contrast, splicing silencers generally influence RNA splicing events by recruiting

heterogeneous nuclear ribonucleoproteins (hnRNPs) (14). This concept has been the general rule,

however, recent studies have shown that the activity of a splicing factor as an inhibitor or

enhancer is dependent on the location of protein binding relative to the regulated exon (16).

Thus, the location of the splicing regulatory sequence, in addition to the sequence specificity and

the balance of antagonistic splicing factors (SR proteins and hnRNPs, described in following

sections) dictate the splicing reaction.

1.2.2.1 SR-protein family of splicing factors

The majority of cellular splicing factors include serine/arginine-rich (SR) proteins and SR-

related proteins, which contain N-terminal RNA binding domains called RNA recognition motifs

(RRMs) and C-terminal domains rich in serine and arginine residues (RS domains). SR and SR-

related proteins containing a single RRM include SRSF3 (SRp20), SRSF7 (9G8), SRSF2

(SC35), SRSF8 (SRp46), SRSF11 (SRp54), Tra2α, and Tra2β (14). However, most splicing

factors contain multiple RRM copies. Five human SR proteins, SRSF1 (SF2/ASF), SRSF9

(SRp30c), SRSF5 (SRp40), SRSF6 (SRp55) and SRSF4 (SRp75), contain a canonical RRM and

a pseudo-RRM and have different RNA-binding specificities (14). SR proteins help define exons

and introns in pre-mRNA splicing by acting as bridges between snRNPs along the length of the

pre-mRNA. Generally, SR and SR-related proteins enhance splicing by binding to exonic or

intronic splicing enhancer (ESE or ISE) motifs and facilitating the stable assembly of U1 and U2

snRNPs to the pre-mRNA at adjacent splice sites (5) (Figure 1.3).

1.2.2.2 Heterogeneous nuclear ribonucleoproteins (hnRNPs)

Heterogeneous nuclear ribonucleoproteins (hnRNPs) also have RNA recognition motifs (RRMs)

by which they interact with the pre-mRNA to regulate splicing, but lack the RS domains found in

11

SR proteins (14). The hnRNP family consists of approximately 20 splicing factors including

hnRNP A1 – U (17). In contrast to SR proteins, hnRNPs generally bind exon splicing silencers

(ESSs) or intron splicing silencers (ISSs) to repress splicing. Thus, they generally compete with

SR proteins in an antagonistic manner to determine whether an exon is included or skipped.

hnRNP-bound splicing silencers have been shown to repress spliceosomal assembly through

steric hindrance, multimerization along exons, or by looping out exons (5, 17) (see Figure 1.3).

The steric hindrance mechanism involves binding of an hnRNP protein to an ESS leading to the

direct displacement of an adjacent SR protein. The multimerization of hnRNPs along the

alternative exon, is thought to be mediated by the arginine/glycine (RG) repeat region of the

protein, and is proposed block the recruitment of snRNPs and the spliceosome machinery,

resulting in exon skipping. In the “looping-out” mechanism, binding of hnRNP proteins to distal

sites within the introns flanking an alternative exon results in preferential splicing of the distal

splice sites and skipping of the alternative exon (5, 17). These models are not mutually exclusive

and may operate in different pre-mRNAs.

1.2.3 Regulation of splicing factors

Many splicing factors are post-translationally modified by phosphorylation, glycosylation or

methylation, to allow rapid alteration of splice site selection (4). The most common modification

is reversible phosphorylation, and the function of SR proteins and hnRNPs is primarily regulated

by the phosphorylation and dephosphorylation by kinases and phosphatases, respectively. The

primary protein kinase families that control SR protein phosphorylation include the SR protein

kinase (SRPK) family, the Cdc-2 like kinase (Clk) family, and topoisomerase I (4). A single SR

protein may be modified by members of more than one kinase family to regulate alternative

splicing (4). In contrast to the over 400 protein kinases encoded by the human genome, only 25

serine/threonine protein phosphatases are known (4). Two such proteins, protein phosphatase 1

and 2C (PP1 and PP2C) have been identified to dephosphorylate splicing factors by binding to a

degenerate RVXF motif present in their interacting proteins (4). In addition to alteration of their

activity, changes in the subcellular localization of these splicing factors affects their

concentration in areas where splicing occurs and results in altered splice site selection. Several

splicing factors shuttle between the nucleus and the cytosol, and their localization is sensitive to

reversible phosphorylation that mediates interactions with export and import systems (18).

12

Thus, by influencing protein-protein and protein-RNA interactions, reversible protein

phosphorylation modulates the assembly of regulatory proteins on pre-mRNA. It follows that

even a small change in the proportions of the spliceosomal components or their regulatory

kinases could trigger a change from the inclusion of an exon to its exclusion (14).

1.2.4 Splicing factors and signaling pathways

In addition to the various kinases and phosphatases that regulate modification of SR proteins and

hnRNPs, there are additional levels of control upstream of these processes. Signaling cascades in

the cell lead to the phosphorylation and dephosphorylation of the kinases and phosphatases,

rendering them active or inactive for their subsequent roles in phosphorylating splicing

regulatory proteins (4). Some of these signaling pathways are depicted in Figure 1.5. Numerous

studies have shown that targeting the proteins involved in these pathways can alter splicing

reactions via the modulation of SR protein or hnRNP activity.

A large number of splicing events are regulated by the phosphoinositide-3 kinase (PI3K) /Akt

pathway since spliceosomal proteins are the most abundant substrates for Akt (4). For example,

insulin activates Akt, which phosphorylates the SR proteins SRSF5, SRSF1, and SRSF7 (SRp40,

SF2/ASF, and 9G8, respectively), resulting in a shift in the splicing pattern of protein kinase C

beta (PKC) toward exon inclusion, creating a PKC isoform that facilitates glucose uptake (4,

19, 20). In addition, studies by the Schaal group have demonstrated that many viruses exploit

PI3K/Akt signaling pathway for efficient viral replication and that pharmacological inhibition of

this signaling cascade alters viral mRNA splicing (21, 22).

T cell receptor signaling has also been implicated in regulating alternative splicing. A study by

Heyd and Lynch (2011) showed that T cell activation leads to reduced glycogen synthase kinase

3 (GSK3) activity such that phosphorylation of PTB-associated splicing factor (PSF) by GSK3 is

reduced. The unphosphorylated form of PSF is released from a complex with TRAP150 and

allows PSF to mediate exon skipping within CD45 mRNA via the splicing regulatory sequence

ESS1 (23, 24). Similarly, a study by Matter et al (2002) demonstrated that activation of the Ras-

ERK signaling pathway leads to phosphorylation of Sam68, which mediates alternative splicing

of CD44 mRNA (25). Furthermore, stress-induced signaling via the p38-mitogen activated

protein kinase (MAPK) pathway has been shown to increase hnRNP A1 phosphorylation,

resulting in altered splicing of an adenovirus E1A mRNA reporter (26).

13

Figure 1.5 Regulation of alternative splicing by signaling pathways.

The p38 kinase transduces stress signals to hnRNP A1 by the MAPK pathway. The Wnt or T cell

receptor (TCR) signaling pathway, by regulating GSK3, phosphorylates and potentiates the

activity of PSF by releasing the splicing regulator from the inhibitory complex with TRAP150.

Growth factor signals (GFs) activate both the Raf-MEK-ERK pathway to modify Sam68 and the

PI3K-Akt pathway. Activated Akt binds to SRPKs and induces nuclear translocation of SRPKs.

In the nucleus, SRPKs act in synergy with Clks to phosphorylate SR proteins. Thus, these

signaling pathways ultimately affect the ability of splicing factors (hnRNP A1, Sam68, SR

proteins, and PSF) to bind to splicing regulatory sequences and alter splice site usage of mRNAs

transcribed by RNA polymerase II (Pol II).

Zhou, Z and X Fu. Regulation of splicing by SR proteins and SR protein-specific kinases. Chromosoma. 122:3

(2013). Copyright Springer-Verlag Berlin Heidelberg. Adapted and reproduced with permission.

14

Together, these studies demonstrate that changes in the activity or levels of kinases or

phosphatases by extracellular stimulus and subsequent signaling cascades have far reaching

consequences for gene expression. Thus, signal transduction pathways induce post-translational

modification of multiple splicing regulators, which in turn function to modulate splice site

selection in the nucleus. The spectrum of splicing regulators and the distinct activities of

individual signaling pathways, suggest roles for specific splicing programs in different cell types,

during development or in the context of disease, cancer or viral infection. (18).

1.3 Perturbation of alternative splicing in disease

It is becoming increasingly evident that a number of diseases are caused by aberrant splicing or

the selection of “wrong” splice sites during mRNA processing. The selection of these splice sites

can be caused by mutation in cis-acting sequences or by changes in trans-acting factors and their

regulation (27). Since mRNA processing is coupled to transcription and translation, it is likely

that these changes in alternative splicing affect transcription and translation, as well. Over the

past decades, several groups have identified links between changes in alternative splicing and

cancer, neuromuscular disorders, and viral infections (27). In fact, aberrant mRNA processing is

also seen in many neuromuscular disorders and cells infected with virus.

A considerable amount of research has been published on regulation of the Survival of Motor

Neuron (SMN) pre-mRNA splicing (14, 27) and can be seen as a model for aberrant alternative

splicing causing disease. Two almost identical genes code for functional protein SMN1 and

mostly nonfunctional protein SMN2, due to a single base transition in exon 7 that is

preferentially skipped in SMN2 (14, 27). The CT mutation (CU in mRNA transcript) in the

SMN2 gene at the 6th position of exon 7 is translationally silent but results in low, insufficient

levels of functional SMN protein due to truncation of the transcript (14, 27). Autosomal

recessive SMA is caused by the loss of SMN1 and the inability of SMN2 to compensate for the

less of SMN1 (14, 27). The disease is characterized by progressive paralysis caused by the loss

of alpha-motor neurons in the spinal cord and is the most frequent genetic cause of infantile

death (14, 27, 28). Since the genes encoding SMN1 and SMN2 are nearly identical, it was

generally believed that restoration of SMN2 exon 7 inclusion held the promise of a cure for

SMA.

15

Numerous studies have uncovered a number of splicing regulatory elements within exon 7 and

its flanking introns, including an enhancer element associated with splicing factor SRSF1

(SF2/ASF), and a silencer element associated with hnRNP A1 (14, 27). Many groups have

attempted to modulate splicing and influence inclusion of exon 7 in SMN2 as a therapeutic

approach to treat SMA. A recent study by Naryshkin et al (2014) validates this approach using

small molecules as a means to shift the balance of SMN2 splicing toward the production of full-

length SMN2 messenger RNA with a high degree of selectivity (28). In fact, administration of

these compounds to a mouse model of severe SMA, led to an increase in SMN protein levels in

the brain, improvement of motor function, and increased longevity, suggesting that selective

SMN2 splicing modifiers is a promising therapeutic strategy for patients with SMA (28).

The success of this approach in modulating mRNA processing to promote exon inclusion and

rescue protein expression suggests that perhaps a similar strategy can be used to inhibit the

balance of mRNA splicing during HIV infections as well. Indeed, a number of studies have

verified the use of small molecules as modulators of mRNA splicing in the context of numerous

diseases, cancer and viral infection, as outlined in further detail in section 1.5.

1.4 HIV-1 utilizes host alternative splicing machinery for viral gene expression

A common mechanism among many human and animal viruses is the use of alternative splicing

(AS) to maximize their viral protein expression from a limited genome size. HIV-1 is such a

virus that requires AS for efficient viral replication during the infectious life cycle.

1.4.1 Overview of the HIV-1 lifecycle

HIV-1 is a complex retrovirus consisting of two identical RNA strands of 9.3 kb contained in a

conical capsid, surrounded by a lipoprotein membrane (29). The glycoproteins on the surface of

the virion are comprised of trimers of an external glycoprotein, gp120, and a transmembrane

protein, gp41. The gp120-gp41 trimer structure mediates HIV tropism towards cells expressing

CD4 and chemokine co-receptors CCR5 or CXCR4. Viral entry into susceptible cells, such as

CD4+ T lymphocytes, is mediated by the binding of gp120 to CD4 on the cell surface (Figure

1.6, Step 1), resulting in a conformational change in gp120 and exposure of a region that is able

to bind the co-receptor, CCR5 or CXCR4 (29). Binding of the co-receptor causes another

conformational change in gp41, initiating fusion of viral and cellular membranes and release of

16

the viral capsid into the cytoplasm of the target cell. Once in the cytoplasm, the virus undergoes

partial disassembly of the capsid and initiates reverse transcription and delivery of the viral

double stranded DNA to the nucleus (Step 2). Once integrated into the host cell genome (Step 3),

the HIV-1 provirus uses the host transcription, mRNA processing, and translation pathways for

efficient viral gene expression (Steps 4-5). The HIV-1 RNA genome and associated viral

proteins are assembled at the plasma membrane where release of the viral particle occurs (Step

6). Finally, proteolytic cleavage and maturation must occur for the virus particle to infect new

host cells (Step 7).

1.4.2 Current treatment strategies for HIV-1

The drugs currently used to treat HIV-1 infection belong to four distinct classes targeting viral

entry and each of the viral enzymes, reverse transcriptase, integrase and protease. The stages at

which these classes of drugs target are illustrated in Figure 1.6. Entry inhibitors block the

penetration of HIV virions into their target cells by blocking fusion of the viral and cellular

membranes (eg. enfuvirtide/T20) or binding to the co-factor CCR5 (eg. maraviroc).

Nucleoside/nucleotide reverse transcriptase inhibitors (NRTIs) are nucleoside or nucleotide

analogues which act as DNA-chain terminators and inhibit reverse transcription of the viral RNA

genome into DNA (eg. zidovudine/AZT) while non-nucleoside reverse- transcriptase inhibitors

(NNRTIs) bind and inhibit reverse transcriptase activity (eg. nevirapine) (30). Protease inhibitors

target the viral protease to inhibit cleavage of precursor proteins (gag and gag-pol), (eg.

ritonavir) and integrase inhibitors prevent the provirus from integrating into the host genome (eg.

raltegravir) (30). A therapy to treat HIV-1 infection uses combinations of these anti-retroviral

drugs and is known as highly active antiretroviral therapy (HAART). Current HAART regimens

generally comprise three anti-retroviral drugs, usually two nucleoside analogues and either a

protease inhibitor or a nonnucleoside reverse-transcriptase inhibitor. Effective combination anti-

retroviral therapy can suppress HIV viral load in patients and has dramatically improved HIV-

associated morbidity and mortality. However, HAART requires strict adherence to long-term

therapy to prevent the emergence of drug resistant virus from latent reservoir pools.

17

Figure 1.6 HIV-1 lifecycle and current treatment strategies

Diagram depicts stages of the HIV-1 lifecycle in a host CD4+ T cell (Steps 1-7). Current drugs

used in HIV-1 treatments are indicated in red boxes next to their viral targets. NRTIs =

nucleoside/nucleotide reverse transcriptase inhibitors (zidovudine, didanosine, zalcitabine,

stavudine, lamivudine, abacavir, emtricitabine and tenofovir). NNRTIs = Non-nucleoside reverse

transcriptase inhibitors (nevirapine, delavirdine, efavirenz and etravirine).

18

1.4.3 Limitations of current HIV-1 therapies

HAART has greatly improved the quality of life in HIV-1-infected individuals however, success

of this therapeutic approach is limited by patient incompliance to therapy, development of drug

resistance, side effects with prolonged use, and virus persistence in latent reservoirs (30). Viral

drug resistance is particularly problematic because of HIV-1 genetic heterogeneity, high

replication rates and high mutation rates associated with reverse transcriptase (30). For example,

the proportion of multidrug-resistant virus transmitted in new HIV infections increased in North

America from 1.1% to 6.2% within a five year period between 1995 and 2000 while the

frequency of multidrug resistance detected by sequence analysis increased from 3.8% to 10.2%

(31). Furthermore, among subjects infected with drug-resistant virus, the time to viral

suppression after the initiation of antiretroviral therapy was longer, and the time to virologic

failure was shorter (31). The prevalence of transmitted drug-resistant virus, especially multidrug-

resistant HIV, has important implications for the continued use and management of current anti-

viral therapies. The existence of fewer options for initial treatment and suboptimal responses to

treatment among recently infected patients may seriously limit the expected reduction in the rate

of disease progression and increase secondary transmission of drug-resistant variants. An

additional caveat to treating HIV-1 infection, is the ability of the virus to establish a latent

cellular reservoir and avoid immune detection. HIV-infection is currently treated as a chronic

condition requiring life-long daily treatment because HAART does not eliminate resting long-

lived cells containing integrated proviruses. If treatment is stopped, HIV-1 rebounds to very high

levels as virus emerges from these cells. The mechanism of how HIV-1 persists latently in these

infected cells is not known, but presumably requires interaction with cellular factors involved in

chromatin modification pathways to keep the provirus in a latent state.

Thus, a better understanding of how HIV-1 interacts with the host cell would give insight

towards curbing viral drug resistance and combating persistent viral infection. New drugs that act

on stages of the HIV-1 lifecycle not currently targeted by HAART with less susceptibility to

developing resistant viral strains should be explored to continue combating HIV-1 infection.

Over the past several years, these has been a refocusing of HIV-1 research towards the

development of drugs targeting cellular factors that are essential for viral infection, rather than

targeting viral proteins. This approach would be advantageous because it would reduce the risk

of developing viral drug resistance. There are a number of cellular factors, including host

19

proteins essential for viral gene expression and RNA processing that are promising targets for

novel therapeutic strategies for HIV-1 infection.

1.4.4 HIV-1 RNA processing

The HIV-1 genome consists of long terminal repeat (LTR) regions flanking the open reading

frames that encode for fifteen distinct proteins (Figure 1.7A). The gag gene encodes the

nucleocapsid, capsid, and matrix proteins. The pol gene encodes the viral reverse transcriptase,

integrase and protease. The env gene encodes the glycoproteins gp120 and gp41. Other proteins

encoded by the viral genome include regulatory proteins Rev and Tat, and accessory proteins

Nef, Vif, Vpu, and Vpr (29).

Following integration into the host cell genome, the HIV-1 provirus is transcribed by the cellular

RNA polymerase II (Pol II) to generate a 9 kb pre-mRNA. To generate all the proteins required

for virion assembly from a single 9 kb transcript, HIV-1 relies on a controlled process of

alternative splicing to generate over 40 mRNAs (32), a subset of which are depicted in Figure

1.7B. The viral RNAs are divided into three classes depending on their degree of splicing:

unspliced (US) 9 kb RNAs, singly spliced (SS) 4 kb RNAs, and the multiply spliced (MS) 1.8 kb

RNAs. Unlike eukaryotic cellular transcripts, HIV-1 requires a significant portion of viral RNA

to remain unspliced as the viral RNA genome and to encode viral structural proteins (32). Thus,

there must be a controlled process of alternative splicing to get efficient viral gene expression.

HIV-1 uses suboptimal 5’ and 3’ splice sites (5’ and 3’ ss) to generate the different viral RNA

species (32). These splice sites are in turn regulated by exonic splicing enhancers (ESEs), exonic

splicing silencers (ESSs), and intronic splicing silencers (ISSs). Regulation of viral mRNA

processing is described in detail in the following section.

1.4.5 Regulation of HIV-1 RNA splicing

The efficiency of splice site use is determined by the interactions between the proteins and the

pre-mRNA and is influenced by the action of many cellular splicing factors. These factors bind

to splicing regulatory elements near the splice acceptor and splice donor sites, almost all of

which are conserved across all HIV-1 strains (32), in the pre-mRNA to mediate inclusion and

exclusion of nearby exons. Many of these elements as well as the splicing factors that bind them

are extensively reviewed in Stoltzfus (2009) with more recently identified viral cis-elements

described by Erkelenz et al (2015). Studies examining the intrinsic strength of the viral 5’ss and

20

s

Figure 1.7 HIV-1 mRNA splicing and regulation.

(A) Schematic diagram of HIV-1 genome indicating open reading frames (open rectangles) and

LTRs (gray rectangles). (B) Locations of 5’ and 3’ss and RRE in the HIV-1 genome. The exons

present in the SS (4 kb) and MS (1.8 kb) mRNA species corresponding to the HIV-1 genes are

shown as open rectangles. Noncoding exon 1 and is present in all spliced HIV-1 mRNA species,

while exons 2 and 3 (black rectangles) are included in a fraction of the mRNA species. The exon

compositions of the RNA species are shown with ‘‘I’’ designating incompletely spliced mRNA

species and brackets indicating mRNA isoforms containing neither, only one, or both exons 2

and 3. (C) Locations of known splicing regulatory elements in the HIV-1. Splicing enhancers and

splicing silencers are designated by green and red rectangles, respectively.

Stoltzfus, CM. Regulation of HIV-1 alternative RNA splicing and its role in virus replication. Advances in Virus

Research, Volume 74, Chapter 1 (2009). Copyright Elsevier Inc. Reproduced with permission.

Erkelenz, S et al. Balanced splicing at the Tat-specific HIV-1 3′ss A3 is critical for HIV-1 replication. Retrovirology,

12:29 (2015). Copyright Erkelenz et al. Reproduced with permission.

21

3’ss, revealed that the 5’ss D1 and D4 are relatively strong (closely match the consensus motif)

while the 5’ss D2 and D3 are relatively weak, consistent with reduced complementarity to U1

snRNA (32). Furthermore, in contrast to 3’ss A2 and A3, which splice with an efficiency of at

least 40% compared to an optimal control, A1, A4c, A4a, A4b, A5 and A7 have weak intrinsic

strength (32, 33).

However, addition of exonic sequences downstream of the 3’ ss, significantly change the

efficiency of splicing, demonstrating the importance of splicing regulatory elements to functional

splice site strength. The use of 3’ss A1, A4cab, A5 and A7 is considerably increased in presence

of their respective downstream exonic sequences, whereas the splicing efficiency at 3’ss A2 and

A3 is decreased (32). Viral mRNAs encoding Vif, Vpr and Tat proteins, are expressed at

relatively low levels in infected cells, suggesting that 3’ss A1, A2 and A3 are rarely spliced. In

contrast, viral mRNAs encoding Rev, Nef, Env, and Vpu are expressed at higher levels,

suggesting that splicing at the 3’ss A4cab and A5 occurs more efficiently (32). In addition,

approximately one half of all spliced viral mRNAs remove the downstream env-intron,

indicating that 3’ss A7 is also used with high efficiency (32). These observations demonstrate

that alternative splicing of HIV-1 mRNAs must be strictly controlled to allow efficient

expression of all viral proteins.

Splicing at each of the viral splice sites is tightly regulated by neighbouring splicing elements

such as exonic and intronic splicing silencers (ESSs/ISSs) and exonic splicing enhancers (ESEs)

(see Figure 1.7C). The viral 3’ss A2, A3 and A7 contain ESS elements (ESS2, ESS3, and ESSV)

within their downstream exonic sequences. Most of these elements contain motifs which match

the consensus binding sequence for hnRNP A/B proteins and were found to negatively act on

splice site activation (34). Studies have shown that depletion of hnRNP A1/A1B/A2/B1 resulted

in inhibition of ESS2, ESS3 and ESSV-mediated splicing and that splicing can be rescued by

addition of any of the depleted hnRNPs (34). In addition, a UGGGU sequence downstream of

3’ss A3 (ESS2p) was shown to be bound by hnRNP H for inhibition of the tat-mRNA specific

3’ss A3 (34). A mutation within ESS2p was shown to cause reduced hnRNP H binding and 2-

fold increase in splicing at A3 (34).

An ISS element was also identified to regulate splicing at 3’ss A7 and was found to be hnRNP

A/B-dependent. Disruption of this ISS by mutagenesis increases the splicing efficiency at 3’ss

22

A7 (34). Furthermore, hnRNP mediation of ESS and ISS repression was shown to occur at early

steps in splicing process with models proposing that the cooperative binding of hnRNPs to these

sequences prevent efficient binding of the cellular splicing factors to the 3’ ss (34). The binding

of hnRNPs to the silencer sequences act antagonistically on viral splice site usage with cellular

factors and cis elements that increase the efficiency of splicing of neighbouring splice sites.

Members of the SR protein family were identified to positively regulate viral splicing by

recognizing exonic splicing enhancer (ESE) elements (34). One of the earliest identification of

SR proteins necessary for HIV-1 splicing was the requirement of SRSF1 (SF2/ASF) for splicing

at the 3’ ss A7 (34). In fact, deletions downstream of A7 lead to the identification of

ESE3/(GAA)3 as an enhancer element (35). However, further mutational studies suggested that

the ESE3/(GAA)3 element could act either as an ESS or an ESE in the context of exon 7 (a so-

called Janus element) and that its activity may be determined by the relative amounts of hnRNP

proteins and SRSF1 (35). In addition, studies by the Schaal group revealed that a guanosine-

adenosine rich (GAR) enhancer within HIV-1 exon 5 is bound by the SR proteins SRSF1 and

SRSF5 and allows recruitment of the U1 snRNP to the flanking 5’ss D4 (36). This recruitment is

necessary for bridging interactions across the exon and splice site pairing, as exon 5 recognition

in the absence of the GAR element can be partially bypassed by coexpression of a mutated U1

snRNA perfectly matching 5’ss D4 (36). Subsequent overexpression studies have identified

ESE2 to be SRSF2 (SC35)-dependent and ESEVpr to be SRSF1-dependent (16). In addition,

Exline et al (2008) showed that ESEVif (within 5'-proximal region of exon 2) binds specifically to

SRSF4 and that mutations within ESEVif resulted in altered Vif expression (37). Similarly,

Kammler et al (2006) described a SRSF1-dependent ESE (ESEM) within exon 2 for which

single point mutation was shown to be detrimental for HIV-1 exon 2 recognition without

affecting Rev-dependent Vif expression (38). A recent study by Erkelenz et al (2015) identified

an additional splicing enhancer, ESEtat, located between ESS2p and ESE2/ESS2, which is critical

for regulation of 3′ss A3 usage and viral tat-mRNA splicing. Subsequent in vitro binding assays

suggest SRSF2 and SRSF6 as candidate splicing factors acting through ESEtat and ESE2 for 3′ss

A3 activation (39).

The strict requirement for balanced splicing of viral mRNAs for HIV-1 replication is most

strongly demonstrated by mutations in ESSV. Disruption of ESSV activity resulted in a selective

increase in the levels of incompletely spliced Vpr-mRNAs and a reduction in the levels of US

23

mRNAs and intracellular Gag protein levels (40). This oversplicing phenotype is consistent with

a dramatic perturbation of the balance between spliced and unspliced viral mRNAs and a 10 to

20 fold reduction in virus particle production, probably due to insufficient accumulation of

structural proteins required for capsid assembly (40). Consistent with its role as a key regulator

of viral splicing, it has been shown that viruses lacking ESSV escape from their replication

defect by second site mutations upon prolonged culturing, to switch off unbalanced exon 3 splice

site recognition (40). Therefore, ESSV appears to be important in regulating HIV-1 exon 3

splicing to levels permitting both accumulation of unspliced mRNA for structural protein

expression and vpr-mRNA formation. Furthermore, a recent study by Erkelenz et al (2015) has

revealed that mutational inactivation or masking of the ESEtat element resulted in dramatic

impairment of viral replication due to decreased accumulation of mRNAs encoding Tat (39).

These studies further demonstrate that regulation of HIV-1 splicing, particularly by altering the

splicing pattern of viral mRNAs encoding regulatory proteins, is critical for viral gene expression

and that perturbations in splicing cause severe defects in viral replication.

Several studies have examined the effect of over expression of SR proteins in splicing of HIV-1

mRNAs. As mentioned briefly, over expression of SRSF2 and SRSF5 resulted in selective

increase of tat mRNA isoforms spliced at 3’ ss A3, while over expression of SRSF1 resulted in

exon 3 inclusion by activation of 3’ ss A2 splice site use (34). In addition, over expression of

SRSF1, SRSF2 and SRSF7 resulted in significant reduction of unspliced HIV-1 mRNAs and

decreased Env expression. Likewise, previous studies in our lab have revealed that changes in

the expression of hnRNP D, Tra2α, and Tra2β also modulate HIV-1 mRNA alternative splicing

(41, 42). Studies by Lund et al (2012) demonstrated that siRNA mediated depletion of hnRNP

A1 and hnRNP A2 increased expression of viral structural proteins, while depletion of hnRNP H,

hnRNP I or hnRNP K had little effect (41). In contrast, depletion of hnRNP D expression

decreased synthesis of HIV-1 Gag and Env due to the reduction of accumulation of HIV-1

unspliced and singly spliced RNAs in the cytoplasm (41). Similarly, over expression of Tra2α or

Tra2β resulted in a marked reduction in HIV-1 Gag/Env expression by perturbation of HIV-1

RNA accumulation, altered viral splice site usage, and a block to export of HIV-1 genomic RNA

(42). In addition, depletion of Tra2β resulted in a selective reduction in HIV-1 Env expression

and an increase in multiply spliced viral RNA (42). The role of kinases that regulate

phosphorylation of splicing factors have also been shown to alter splicing of HIV-1, as the

24

overexpression of CLK1 and CLK2 resulted in the enhancement and inhibition of HIV-1 Gag

production, respectively (43). Together, these findings demonstrate that tight regulation of HIV-1

splicing is required for efficient virus replication and that this regulation can be abrogated by

changes in the levels or phosphorylation status of cellular splicing factors.

Given the numerous studies which demonstrate that HIV-1 replication is severely impaired by

mutations within splicing regulatory elements or changes in the expression levels of splicing

factors that bind to these elements, it seems likely that the perturbation of the expression of

cellular splicing factors may be a novel avenue by which to inhibit HIV-1 gene expression. Since

the action of these splicing factors can be modulated by specific kinases and phosphatases by

differential phosphorylation of the RS domains, the ratio of these regulatory enzymes can also

play an important role in determining which pairs of splice sites are selected. Therefore, a novel

therapeutic strategy can be outlined where targeting specific regulatory proteins involved in

alternative splicing pathways leads to inhibition of HIV-1 viral RNA processing and hence virus

replication.

1.4.6 HIV-1 gene expression and Rev-dependent export

Since HIV-1 relies on the host cellular machinery for splicing and export of viral US, SS and MS

RNAs, it must adopt ways to bypass the cellular restriction on export of incompletely spliced

mRNAs. For many years, the paradigm for the export of viral RNAs was as follows: During the

early phase of viral gene expression, only the completely spliced MS RNAs are exported

presumably via the TAP-dependent export pathway, like all spliced cellular mRNAs, while the

US and SS RNAs are degraded in the nucleus. The MS RNA encodes the virsl regulatory facter,

Rev, which contains both a nuclear localization signal (NLS) and a nuclear export signal (NES).

The NLS and NES allow Rev to interact with Importin and the CRM1, respectively, so that

Rev can shuttle between the nucleus and cytoplasm via the nuclear pore complex. When Rev has

accumulated in the nucleus during the late phase of viral gene expression, it recognizes and binds

the Rev response elements (RREs) present in both the US and SS RNAs. Binding of Rev to the

RRE, and interaction between Rev and CRM1, allows the export of US and SS viral RNAs by

the CRM1-dependent export pathway, and subsequent expression of viral proteins encoded by

these RNAs. Thus, HIV-1 was thought to bypass the nuclear retention mechanism, by expressing

25

s

Figure 1.8 HIV-1 gene expression in host cell.

Following integration of the HIV-1 provirus into the host genome, a single 9kb transcript is

produced. This transcript needs to be alternatively spliced to generate >40 mRNAs, which are

divided into 3 classes US, SS and MS RNA. There are two phases of HIV-1 gene expression. In

the early phase, only the MS RNA is exported from the nucleus while the US and SS RNA are

degraded. The MS RNA encodes for regulatory proteins, importantly Rev. Once Rev has

accumulated, during the late phase of gene expression, Rev can shuttle back to the nucleus and

bind to RRE present on US and SS RNA to allow their export and subsequent expression of viral

structural proteins.

26

the viral regulatory factor, Rev, to specifically transport the incompletely spliced viral RNAs via

the CRM1-mediated pathway.

A recent publication by Taniguchi et al (2014), shows that Rev-mediated export of viral RNAs is

more complicated than the paradigm initially suggested. The authors proposed a model for Rev-

mediated export of RRE-containing mRNAs, whereby Rev binds to the RRE and also interacts

with the cap-binding complex (CBC) at the 5’ end of the mRNA and competitively inhibits the

interaction between CBC and Aly/REF, a component of the TAP-mediated export pathway. In

this way, interaction of Aly/REF with viral mRNAs and subsequent recruitment of the TREX

complex is suppressed, such that RRE-containing RNAs are preferentially exported via the

CRM1-mediated pathway (44). It was further suggested, that HIV-1 likely suppresses TAP-

dependent RNA export as a means to prevent the association of TAP with the incompletely

spliced viral US and SS RNAs, and the specific nuclear retention and reduction of these RNAs

(44). Thus, HIV-1 presumably utilizes Rev to circumvent TAP-mediated reduction in viral gene

expression.

The molecular mechanism by which Rev binds to both the RRE and the distantly located CBC

remains to be elucidated, but they propose the most likely way this could occur as follows: RRE-

containing RNA may form a closed loop structure between the 5’ end and the RRE by the

interaction of Rev with the CBC, similar to the closed loop structure observed for the 5’ end and

the (poly A) tail in cellular mRNA translation (44). An alternative possible model where CRM1-

binding of Rev-RRE may enhance Rev multimerization along the entire length of the RRE-

containing RNA and association of Rev with the 5’ end is stabilized by CBC, was deemed

unlikely since the intervening sequence is cleavable by DNase and RNase H (44). Taken

together, this study demonstrates that Rev is crucial for efficient HIV-1 gene expression and is

the mediator required to bypass the cellular export block of incompletely spliced mRNAs.

Furthermore, since Rev interacts with many cellular proteins to carry out its function, it suggests

that perturbation of the specific Rev-cellular factor interaction could be a strategy to specifically

inhibit HIV-1 mRNA processing and subsequent viral gene expression. Thus, an approach that

targets both cellular regulators of alternative splicing and Rev function would be tremendously

detrimental to viral replication and offer a novel therapeutic strategy for HIV-1 infection.

27

1.5 Modulation of RNA splicing as a therapeutic strategy

Since alternative pre-mRNA splicing is an important regulator of gene expression, the selection

of ‘wrong’ alternative exons, leading to differential protein expression, is being increasingly

recognized as the cause of numerous human diseases, cancers and viral infections (reviewed in

(21, 27, 45)). Thus, strategies that target regulation of alternative splicing can be used to modify

aberrant splicing patterns to treat these diseases.

1.5.1 Modulation of AS using small molecules

A promising line of research that has attracted recent attention involves the use of small

molecules that act by interfering with cellular signaling pathways, thereby modifying the activity

of splicing regulatory proteins through an altered cellular distribution or a change in

phosphorylation state. For this, screening methods have been developed to identify small

molecules from chemical libraries that regulate a given splicing event. Stoilov et al (2008)

described a high-throughput screening assay to discover compounds that target the splicing

reaction using a two-color fluorescent reporter system. The authors tested known bioactive

compounds for their effect on inclusion of microtubule-associated protein tau (MAPT) exon 10.

From their compound library screen, they identified digoxin, a cardiotonic steroid used in the

treatment of heart failure, as a novel splicing modulator. Futhermore, another study by Anderson

et al (2012) demonstrated that digitoxin, another cardiotonic steroid, regulates alternative

splicing by depletion of SRSF3 and Tra2β. These observations identify previously characterized

drugs as novel modulators of alternative splicing and demonstrate the feasibility of screening for

compounds that alter exon inclusion.

Indeed, research during the last several years has identified a number of small molecules that can

change alternative exon usage, most often by targeting histone deacetylases or by interfering

with the phosphorylation of splicing factors (reviewed in (45-47). Table 1.1 lists some of the

small molecules that were identified to modulate splicing, with the compounds tested in the

context of HIV-1 highlighted orange. There still remains many compounds for which the

mechanistic basis for how they perturb splicing is not yet fully understood. Thus, further

examination of these small molecules gives insight into alternative pre-mRNA splicing, and

more importantly, paves the way for therapeutic application of these compounds to control

diseases and infections that are dependent upon alternative splicing.

28

Table 1.1 List of small molecule inhibitors of alternative splicing and their molecular

targets. Compounds tested in the context of HIV are indicated in orange. *unknown mechanism.

Compound Drug type Mechanism Reference(s)

Spliceostatin A FR901464-derivative SF3b Kaida et al, 2007

Sudemycin C1 FR901464-derivative SF3b Fan et al, 2011

Sodium butyrate Short chain fatty acid HDAC inhibition Chang et al, 2001

Valproic acid Carbon branched-chain fatty acid

HDAC inhibition Brichta et al, 2003

Phenylbutyrate Short chain fatty acid HDAC inhibition Andreassi et al, 2004

M344 Benzamide HDAC inhibition Riessland et al, 2006

SAHA Hydroxyl-phenyl-octanediamide

HDAC inhibition Hahnen et al, 2006

Aclarubicin Aclacinomycin A Topo 1 Andreassi et al, 2001

Camptothecin Alkaloid Topo 1 Gonzalez-Molleda et al, 2012

Isodiospyrin Diospyrin derivative Topo 1 Tazi et al, 2005 Ting et al, 2003

NB-506 Indolocarbazole derivative Topo 1 Pilch et al, 2001

IDC16 Indol derivative Topo 1, SRSF1 Bakkour et al, 2007

IDC13 Indol derivative SR proteins* Keriel et al, 2009

IDC78 Pyridocarbazole SR proteins* Keriel et al, 2009

Digitoxin Cardiac glycoside SRSF3, Tra2β Anderson et al, 2012

SRPIN340 Isonicotinamide derivative SRPK1, SRPK2 Karakama et al, 2010 Fukuhara et al, 2006

TG003 Benzothiazole CLK1, CLK4 Muraki et al, 2004 Wong et al, 2011

Leucettine L41 Leucettamine B derivative CLKs, DYRKs Debdab et al, 2011

KH-CB19 Dichloroindolyl enaminonitrile

CLK1, CLK4 Fedorov et al, 2011

Chlorhexidine Biguanide CLK2, CLK3, CLK4 Younis et al, 2010 Wong et al, 2011

Lithium chloride GSK3 Hernandez et al, 2004

AR-A014418 Thiazole GSK3 Yadav et al, 2014 Hernandez et al, 2004

SB216763 Indole maleimide GSK3 Heyd and Lynch, 2010

C6-ceramide Ceramide analog PP1 regulation Chalfant et al, 2002

Tautomycin Alkylmaleic anhydride PP1 inhibition Novoyatleva et al, 2008

Cantharidin Natural toxin PP1 inhibition Novoyatleva et al, 2008

Digoxin Cardiac glycoside * HIV-1 Rev Stoilov et al, 2008 Wong et al, 2013

8-azaguanine Purine analog * HIV-1 Rev Wong et al, 2013

5350150 Quinoline * HIV-1 Rev Wong et al, 2013

ABX464 IDC16-derivative * HIV-1 Rev Campos et al, 2015

29

1.5.1.1 Spliceosome inhibitors

Spliceostatin A is a stabilized derivative of FR901464, a Pseudomonas bacterial fermentation

product that has been shown to modulate pre-mRNA splicing (48). Spliceostatin A inhibits

alternative splicing by binding the U2 small nuclear ribonucleoprotein (snRNP) component

SF3b, which is essential for recognition of the pre-mRNA branch point (48). Studies by Kaida et

al (2007) revealed that spliceostatin A inhibited interaction of an SF3b subunit with the pre-

mRNA by preventing recruitment of U2 snRNP to sequences 5′ of the branch point (48).

Sudemycin C1 is an analog of FR901464 and its derivative spliceostatin A. This compound and

another analog sudemycin E similarly bind to SF3b, induce dissociation of the U2 snRNPs and

alter pre-messenger RNA splicing (49). These compounds illustrate a proof of principle, but the

development of small molecule inhibitors of splicing as therapeutics requires compounds that act

in a more selective manner. Compounds that were shown to inhibit various factors that regulate

the activity of splicing factors is described in the following sections.

1.5.1.2 Histone deacetylase (HDAC) inhibitors

HDAC inhibitors were identified in studies aimed at promoting exon 7 inclusion in SMN2

mRNA. The function of HDACs is to regulate chromatin structure and gene expression by

controlling the acetylation state of histones. The acetylation of histones determines histone

affinity for DNA, hence it follows that application of HDAC inhibitors would cause a

coordinated change in the expression of splicing regulatory factors, and thus splicing. In support

of this hypothesis, a change in SR protein expression was observed after sodium butyrate

application in mice (50). Similarly, valproic acid, phenylbutyrate, M344 and SAHA

(suberoylanilide hydroxamic acid) increased SMN2 RNA and protein levels in vitro (51-54). For

valproic acid and M344, this occurred via two mechanism: increase the overall SMN2 expression

through inhibition of targeted HDACs and increase the incorporation of exon 7 into the SMN2

transcripts through the activation of splicing factors (51, 53). Both valproic acid and

phenylbutyrate were tested in clinical trials, however the results of the trial were varied (47).

Given the therapeutic potential of HDAC inhibitors and their proposed mechanisms of action, a

search for further alternative splicing inhibitors is warranted in an effort to identify molecules

with more suitable properties that can be used as therapeutics agents.

30

1.5.1.3 Topoisomerase (Topo I) inhibitors

DNA topoisomerase I (Topo I) have a dual function in RNA metabolism. The enzyme nicks the

DNA strand upon transcription to regulate supercoiling of the DNA (55, 56). Furthermore,

studies have shown that Topo I phosphorylates SR proteins that associate with the nascent pre-

mRNA and may act as a potential protein kinase in vivo (55, 56). So, it comes as no surprise that

testing of numerous drugs that target Topo I found that several of them alter splice-site selection

(46). Diospyrin was found to inhibit spliceosomal assembly whereas its derivatives had specific

inhibitory effects on catalytic steps in splicing (57, 58). Another Topo I inhibitor, NB-506,

inhibited phosphorylation of SRSF1 (SF2/ASF) and perturbed the early formation of the

spliceosome (59). Furthermore, an indole derivative, IDC16, was shown to interfere with exonic

splicing enhancer activity of the SR protein splicing factor SRSF1 (60).

1.5.1.4 Kinase and phosphatase inhibitors

SR proteins are also phosphorylated by a family of nuclear cell division cycle 2-related kinases,

termed CDC-like kinases (Clks) 1–4. A specific inhibitor of these kinases, TG003, changes

alternative splicing in reporter genes and has been tested as an anti-viral agent (61) but it is not

active against HIV-1 (43). Similarly, chlorohexidine was found to selectively inhibit CLK2,

CLK3 and CLK4 without having a general effect on splicing, and also inhibited CLK3 in the

context of HIV-1 (43, 62). Yet another inhibitor of CLKs, KH-CB19, specifically inhibited

CLK1 and CLK4 and altered the phosphorylation patterns of SR proteins (63). Leucettine L41, a

CLK and dual-specificity tyrosine kinase (DYRK) inhibitor, inhibits phosphorylation of several

SR proteins, including SRSF4, SRSF6, and SRSF7 (64). In contrast, SRPIN340 selectively

inhibited SRPK1 and SRPK2 with no inhibition of CLK1, CLK4 or other kinases (65). When

tested in the context of viral infections, SRPIN340 was not able to reproducibly inhibit HIV

replication, but suppressed propagation of Sindbis virus and inhibited HCV replication in vitro

(65, 66), suggesting that SRPIN340 and other SRPK1/2 inhibitors may be useful for limiting

viral infections.

Furthermore, inhibition of glycogen synthase kinase 3 (GSK3) by AR-A014418 resulted in

significant downregulation of splicing factors (SRSF1, SRSF5, PTPB1, and hnRNP) in U87 cells

with downregulation of anti-apoptotic genes (67). Furthermore, Hernandez et al (2004) showed

that inhibition of GSK3 by lithium chloride and AR-A014418 changed alterative splicing of

31

exon 10 of the tau gene, mutations in which were found to cause aberrant usage of the exon

leading to frontotemporal dementia and Alzheimer’s disease (68). In fact, compound-induced

inhibition of GSK3 resulted in redistribution of SRSF2 to nuclear speckles. Studies by Heyd and

Lynch (2010) revealed that SB216763-mediated inhibition of GSK3 resulted in a decrease in

PTB-associated splicing factor (PSF) phosphorylation and subsequently induced PSF-mediated

CD45 exon skipping in an ESS1-dependent manner (23).

Since protein phosphatase-1 (PP1) binds directly to a conserved motif in the RNA-recognition

motif of at least nine different splicing-regulatory proteins, inhibition of PPI would have an

effect on alternative splicing. Indeed this is the case, as tautomycin, a specific inhibitor for PP1,

was found to induce changes in alternative splicing in cell culture and mouse models (69).

Similar effects were seen for cantharidin, which inhibits both PP1 and protein phosphatase-2A

(PP2A) (69). In addition, C6-ceramide has been shown to change splice-site selection in some

apoptotic genes (70).

Together, these observations demonstrate that targeting of alternative splicing by small

molecules can be achieved in a specific manner without detriments to the normal cellular

splicing process. Thus, these studies have tremendous implications for the treatment of diseases

associated with altered mRNA splicing events. HIV-1 infection, is one disease that requires new

therapeutic strategies to continue combating the development of drug resistant viral strains. Since

HIV-1 relies on cellular mRNA splicing to generate all viral proteins, small molecule modulators

of alternative splicing is a promising avenue for further research.

1.6 Effect of splicing modulators on HIV-1 gene expression

As outlined above, several studies have shown that it is indeed feasible to modulate mRNA

processing as a therapeutic approach for treating disease, cancer and viral infection. It is fair to

presume that this method would also work in the context of HIV-1 infection. Indeed, previous

work from our lab, as well as two recent studies, have verified that small molecules can be used

to inhibit HIV-1 infection by modulating viral RNA splicing. Previously, our lab has shown that

chlorohexidine, digoxin, 8-azaguanine, and 5350150 treatment potently inhibited HIV-1 gene

expression in vitro. These compounds inhibited HIV-1 RNA processing by inducing oversplicing

of viral RNA, and/or perturbation of HIV-1 Rev function (43, 71, 72). Although the compounds

inhibited HIV-1 through different mechanisms of action, all lead to the same outcome of

32

decreased expression of viral structural proteins and the incompletely spliced viral RNAs. Thus,

these findings demonstrate that perturbation of HIV-1 splicing by small molecules is an effective

strategy to inhibit viral gene expression.

In addition to the small molecules tested by our lab, a study published by Bakkour et al (2007),

demonstrated that the indole derivative, IDC16, suppresses the production of key HIV-1

proteins, thereby compromising subsequent synthesis of full-length HIV-1 pre-mRNA and

assembly of infectious particles. IDC16 was also shown to inhibit replication of macrophage-

and T cell–tropic laboratory strains, clinical isolates, and strains with high-level resistance to

inhibitors of viral protease and reverse transcriptase (60). Importantly, drug treatment of primary

blood cells did not alter splicing profiles of endogenous genes involved in cell cycle transition

and apoptosis (60).

Furthermore, a recent study by Campos et al (2015) showed that ABX464, a synthetic derivative

of IDC16 with decreased cytotoxic effects, inhibits HIV-1 replication of clinical isolates and

decreased viral proliferation in humanized mouse models (73). The inhibitory effect of ABX464

was shown to be dose-dependent in peripheral blood mononuclear cells and in macrophages

infected with different subtypes of HIV with no adverse effects on cell viability when treated at

concentrations in the micromolar range (73). Importantly, this compound did not select for drug

resistant mutations in vitro and controlled viral rebound in humanized mouse models for two

months following cessation of treatment while viral loads rebounded within a week in animals

following cessation of HAART treatment (73). Thus, this drug is promising as a novel

therapeutic agent for HIV-1 infection and is currently being tested in clinical trials. Together

these studies validate that small molecules targeted at modulating alternative splicing, can be

used as a novel therapeutic approach to treat HIV-1 infection. Since these compounds act on host

cellular processes required for viral replication rather than viral proteins, they might have less

risk in developing drug resistance, complement existing anti-viral therapies in combination with

HAART, or serve as a second line of a defense to combat drug-resistant viral strains. Thus,

further studies of compounds that specifically inhibit HIV-1 alternative splicing, without

perturbing cellular splicing is warranted for continued success in combating HIV-1 infection.

33

1.7 Research objective and rationale

Since HIV gene expression is critically dependent upon controlled splicing of the viral transcript,

perturbing mRNA splicing would have detrimental effects on HIV-1 gene expression. Thus,

small molecules that are able to modulate RNA processing are promising as novel anti-HIV

drugs. We and others have previously shown this to be true with small molecular compounds

digoxin, 8-azaguanine, 5350150 (71, 72), IDC16 (60), and ABX464 (73). The success of these

compounds in inhibiting HIV-1 gene expression, prompted us to expand the repertoire of HIV-1

inhibitors and look for compounds that have distinct modes of action from those previously

described. The potential to differentially affect HIV-1 gene expression would further validate the

use of small molecule modulators of alternative splicing as a viable new strategy against HIV-1

replication. Furthermore, since current anti-viral therapies for HIV, do not target viral RNA

processing, this approach can complement existing treatments or be used as salvage therapy to

combat drug-resistant virus.

34

2 Materials and Methods

2.1 HIV-1 provirus doxycycline-inducible cell lines

To determine the effects of small molecular compound treatment on HIV-1 gene expression,

HeLa cells stably transduced with an inducible Tet-On HIV-1 system (as described by (43, 71,

72)) were used. Briefly, an HIV-1 LAI-2 viral genome was modified with the following changes:

tet operator (tetO) DNA binding sites incorporated into the LTR promoter, inactivating mutation

in the Tat gene, five nucleotide substitutions in the TAR hairpin motif, and replacement of the

nef gene with reverse tetracycline transactivator (rtTA) (74, 75). The provirus was further

modified with a deletion in the reverse transcriptase and integrase region of the pol gene by an

MlsI restriction digest (B2 cell line) or gfp gene in the pol open reading frame, deleting the PR

and RT-coding regions (C7 cell line). In this system, rtTA undergoes a conformational change

when bound by doxycycline (dox) allowing dox-bound rtTA to bind to the tetO sites and activate

viral gene expression. Tat and its TAR binding site are inactivated so that HIV-1 gene expression

is only induced in the presence of doxycycline (dox). Thus, these cells allow the production of

virus particles from a single-round of replication upon dox induction. All cell lines were

maintained in Iscove’s modified Delbecco’s medium (IMDM; Wisent) supplemented with 10%

(vol/vol) fetal bovine serum (FBS, Wisent), 1% penicillin/streptomycin (P/S, Wisent) and 0.2%

Amphotericin B (Wisent).

2.2 Assess activity of compounds on HIV-1 gene expression

2.2.1 Preparation of compounds

The compounds used in the treatment assay were obtained from ChemBridge. All compounds

were solubilized 10 mM or 1mM stock concentrations in dimethyl sulfoxide (DMSO), aliquoted

into microtubes and stored at -20°C for subsequent experiments.

2.2.2 Compound treatment assay

The compound treatment assays were performed as described by Wong et al (43, 71, 72).

Briefly, B2 or C7 cells were seeded at 60-80% cell confluence in IMDM complete medium in 6-

well, 24-well, 6 cm or 10 cm tissue culture plates (Sarstedt) one day prior to compound treatment

and cultured overnight at 37°C in a 5% CO2 humidified incubator. The following day,

compounds were diluted in Opti-MEM (Invitrogen/GIBCO) with equivalent concentrations of

35

d

Figure 2.1. Schematic of HIV-1 proviral system integrated in HeLa cell lines

To assess the effect of small molecules on HIV-1 gene expression, we used HeLa cells that have

been stably integrated with an HIV-1 provirus. The provirus consists of an X4-tropic LAI

genome that has been modified with the Tet-On regulatory system as previously described (71,

72, 74, 75). Briefly, the HIV-1 Nef gene was replaced with rtTA (reverse tetracyclin

transactivator) and Tat and its TAR binding site were mutated and functionally replaced with a

TetOperator (TetO, double copy) within the LTR region. The genome was further modified by 1)

Mls deletion of the pol gene, deleting RT & IN (1000 bp deletion) or 2) replacement of a portion

of the pol gene with gfp (to produce a Gag-GFP fusion protein) and stably transfected into HeLa

cells (we call this the HeLa B2 and HeLa C7 cell lines, respectively. With the addition of the

activator molecule, doxycyclin, rtTA can bind doxycyclin causing a conformational change that

allows it to bind to the TetO and induce viral gene expression.

36

DMSO and added to each well or plate in a circular drop-wise manner to achieve the desired

final concentration. The plates were then incubated for 3-5 hours in the presence of the

compounds prior to induction with doxycycline (dox) at a final concentration of 2 μg/mL (equal

volume of IMDM complete was added to uninduced control samples) and incubated overnight at

37°C in a 5% CO2 humidified incubator. 24 hours post compound treatment, 900 μL of culture

medium was harvested and added to 100 μL of 10% Triton X-100 and incubated at 37°C for 1

hour prior to storage at -20°C for p24 antigen ELISA. The remaining culture medium was

discarded and the cells were washed with PBS twice, before the addition of 2 mM EDTA-PBS

for 15 minutes at 37°C in a 5% CO2 humidified incubator. Cells were lifted from the well or

plate, collected in separate microtubes for RNA and protein, and pelleted by centrifugation at

3,800 x g for 5 minutes at room temperature. The supernatant was discarded and the cells were

lysed in either 350 μL of total RNA lysis buffer (BioRad) for RNA or 100-200 μL of RIPA

buffer (1% NP-40, 0.1% SDS, 0.5% Sodium Deoxycholate, 150 mM NaCl, 50 mM Tris-HCl) for

protein in RNase free microtubes. The lysates were kept on ice prior to storage at -20°C for

further analysis.

2.3 HIV-1 p24 antigen ELISA

HIV-1 gene expression was measured by quantifying the levels of HIV-1 present in culture

supernatants by ELISA for p24 Gag antigen using kits purchased from Frederick National

Laboratory for Cancer Research (Leidos) and performed according to manufacturer’s

instructions. ELISA plates were read at 450 nm and 650 nm on Thermo Scientific Multiskan FC

Filter-based Photometer (Thermo Scientific) or the VersaMax microplate reader using Softmax

Pro version 5.0 software (Molecular Devices). HIV-1 p24 concentration in the samples was

calculated by inputting the absorbance of the sample into a four parameter sigmoid fit equation

based on the two-fold serial dilutions of the HIV-1 p24 standard lysate and expressed relative to

the concentration in DMSO-treated samples.

2.4 XTT cytotoxicity assay

Cellular metabolism following compound treatment was measured by an XTT-based in vitro

toxicology assay kit (Sigma-Aldrich) as proxy for degree of cytotoxicity relative to DMSO

control treatment. This assay provides a spectrophotometric method for estimating cell number

based on the mitochondrial dehydrogenase activity in viable cells since an increase or decrease in

37

viable cells relative to control cells would result in an accompanying change in the amount of the

coloured formazan derivative generated. Briefly, HeLa cells were seeded at a density of ~8,000

cells / 100 L in IMDM complete medium in 96-well tissue culture flat-bottom plates (Sarstedt)

and treated as described above for the compound treatment assay. After 24 hours, culture

supernatant was removed, replaced with 20% XTT solution (40% IMDM complete, 40% PBS,

20% XTT) and incubated at 37°C in a 5% CO2 humidifed incubator for 2-6 hours. Plates were

read at 450 nm and 650 nm on Thermo Scientific Multiskan FC Filter-based Photometer

(Thermo Scientific). Relative cell viability was measured as absorbance at 450 nm subtracted by

the absorbance at 650 nm and absorbance of blank wells containing only the XTT solution as

background signal, in compound treated cells relative to DMSO-treated cells. To examine the

long term effects of the compounds on cell proliferation, HeLa cells were seeded at 2,000 to

6,000 cells / 100 L in IMDM complete medium in 96-well tissue culture flat-bottom plates

(Sarstedt) and treated as described above for the compound treatment assay. After 24, 72, and 96

hours post treatment, culture supernatant was removed, replaced with 20% XTT solution and

incubated at 37°C in a 5% CO2 humidifed incubator for 2-6 hours, and relative cell viability was

measured in compound treated cells relative to DMSO-treated cells, as described above.

2.5 Analysis of HIV-1 protein expression

Protein concentration in cell lysates was quantified by Bradford assay and equal amounts of

protein run on 7, 10, 12, or 14% SDS-PAGE, depending on the protein of interest, under

reducing conditions. Proteins were transferred to 0.2-0.45 m PVDF (BioRad or Perkin-Elmer)

by electrophoretic transfer or by the Trans-Blot Turbo blotting system (BioRad). Blots were

blocked in either 5% Milk-PBS-T (5% Milk, 0.05% Tween-20, 1x PBS) or 3% BSA-PBS-T (3%

BSA, 0.05% Tween-20, 1x PBS) for ≥1 hour at room temperature, prior to incubating the blots in

primary antibody (all diluted in 3% BSA-PBS-T). Conditions used for the primary antibodies are

as follows: purified mouse anti-p24 supernatant from hybridoma 183 (anti-HIV-1 Gag, NIH) at

1/500 dilution probed 2 hours at room temperature, mouse anti-gp120 purified supernatant from

hybridoma 902 (anti-HIV-1 Env, NIH) at 1/10 dilution probed overnight at 4°C, mouse

monoclonal antibody to HIV-1 Rev (Abcam) 1/1000 dilution probed overnight at 4°C, rabbit

polyclonal antibody to HIV-1 Tat (Abcam) 1/7500 dilution probed for 2 hours at room

temperature, rabbit polyclonal antibody to GAPDH (Sigma-Aldrich) 1/5000 dilution probed for 2

hours at room temperature, and mouse monoclonal antibody to α-Tubulin (Sigma-Aldrich)

38

1/5,000 dilution probed for 1 hour at room temperature. After incubations, blots were washed

three times with PBS-T and incubated with a 1/5000 dilution of isotype-specific HRP-conjugated

secondary antibody (Jackson ImmunoResearch) in PBS-T. Following washes, blots were

visualized by ECL, ECL Plus (Perkin-Elmer), or Clarity Western ECL substrate (BioRad) and

exposed to autoradiography film or imaged using the ChemiDoc MP imager (BioRad) and

ImageLab (BioRad) software. Quantification of the relative intensity of the detected bands was

done using ImageLab software and normalized to corresponding bands of the loading control

(GAPDH or α-Tubulin).

2.6 Analysis of HIV-1 RNA expression and localization

2.6.1 RNA extraction and reverse transcription

Samples were processed and assayed as previously described (43, 71, 72). Briefly, total RNA

was extracted from compound-treated cell pellets and genomic DNA was eliminated using the

BioRad Aurum Total RNA Lysis Kit (BioRad) as per manufacturer’s instructions with the

addition of Turbo DNase (Ambion). Purified RNA (0.5-2 g) was reverse transcribed using M-

MLV (Invitrogen) to generate complementary DNA (cDNA). The cDNA product was then

diluted 1:7.5 in nuclease free water and the samples stored at -20°C for further anaylsis.

2.6.2 Quantification of HIV-1 mRNA expression by qPCR

HIV-1 mRNA levels in DMSO- and compound-treated samples were quantified by qPCR using

the Mastercycler ep realplex (Eppendorf ) as described by Wong et al (43, 71, 72). Briefly, 25 l

reactions were run in duplicate in 96-well skirted plates (Axygen) using the standard curve

method with a non-template control blank for each primer to control for contamination or

primer-dimers. Each reaction was set-up as follows: 0.4 μL of Taq DNA polymerase (5 U/μL,

NEB), 2.5 μL of ThermolPol buffer, 2.5 μL of 10X SYBR Green I (Sigma-Aldrich), 2.5 μL of

2.5 mM dNTPs, 1.0 μL of 5' primer (0.1 ug/uL), and 1.0 μL of 3' primer (0.1 μg/μL), 10.1 μL

H2O, and 5 μL of cDNA. The forward and reverse primers used in the quantitation of HIV-1

mRNA are outlined below: unspliced (US), 5' - GAC GCT CTC GCA CCC ATC TC - 3' and 5' -

CTG AAG CGC GCA CGG CAA - 3'; singly spliced (SS), 5' - GGC GGC GAC TGG AAG

AAG C - 3' and 5' - CTA TGA TTA CTA TGG ACC ACA C - 3'; and multiply spliced (MS), 5'

- GAC TCA TCA AGT TTC TCT ATC AAA - 3' and 5' - AGT CTC TCA AGC GGT GGT - 3'.

39

Results were normalized to the housekeeping gene, -actin, which served as an internal loading

control. The forward and reverse primers used to detect -actin were as follows: 5'-GAG CGG

TTC CGC TGC CCT GAG GCA CTC-3' and 5'-GGG CAG TGA TCT CCT TCT GCA TCC

TG-3'. cDNA amplification was detected under the following cycle conditions: 95°C, 2 min

followed by 40 cycles of 95°C, 15s; 60°C, 15s; and 72°C, 15s (for US, MS, and Actin) and 95°C,

2 min followed by 40 cycles of 95°C, 30s; 55°C, 30s; and 72°C, 30s (for SS). qPCR values

crossing threshold (Ct) were obtained during the exponential amplification phase and exported

into Microsoft Excel where gene quantification was evaluated using the absolute quantification

method, normalized to -actin expression, and expressed relative to DMSO-treatment.

2.6.3 Analysis of splice site selection within the HIV-1 MS RNA

The effect of compound treatment on splice site selection within the HIV-1 MS RNA class was

analyzed by radioactive RT-PCR as described previously (43, 71, 72). Total RNA from DMSO-

or compound-treated samples was extracted, reverse transcribed to cDNA and diluted as

described above. The forward and reverse primers used the amplify HIV-1 MS RNAs are as

follows: 5'-GGG CAG TGA TCT CCT TCT GCA TCC TG -3' and 5' -TCA TTG CCA CTG

TCT TCT GCT CT - 3'. Initial rounds of cold RT-PCR were set-up as follows: 1 μL cDNA, 1 μL

of Taq DNA polymerase, 5 μL of 10X ThermolPol buffer, 4 μL of 2.5 mM dNTPs, 10 μL of

forward primer (10 μM), 10 μL of reverse primer (10 μM), and 19 μL of H2O in a 50 μL final

reaction volume. Thermocycler conditions used were 95°C, 2 min followed by 34 cycles of

95°C, 1 min; 57°C, 1 min; and 68°C, 1 min; and ended with 68°C, 5 min; and 4°C, indefinitely.

A second round of radioactive PCR was run with the following changes/additions to the

conditions described above: 3 μL of diluted cDNA from the first PCR reaction (1/10th dilution),

0.5 μL of α-32P-dCTP (Perkin Elmer), and 16.5 μL of H2O. The same thermocycler conditions

were also used except only 5 cycles were run. An equal volume of loading buffer (90%

formamide, 10 mM EDTA, 0.025% xylene cyanol, and 0.025% bromophenol blue) was added to

the products and heated at 95°C for 5 minutes prior to resolving radioactive reaction products

using 6% denaturing polyacrylamide gels (8 M Urea, 1xTBE) and detection using a Typhoon

9400 PhosphorImager (Amersham). Gel densitometry was analyzed using ImageJ software

(NIH) to calculate mRNA levels of HIV-1 MS mRNA isoforms, measured as the density of an

individual isoform divided by the total density of all visible viral RNA species in a sample.

40

2.6.4 Analysis of HIV-1 US RNA subcellular localization

Changes in HIV-1 US RNA subcellular distribution in response to compound treatment was

analyzed by fluorescent in situ hybridization in HeLa C7 cells, as described by Wong et al.,

2013. I confirmed the induction of viral gene expression in HeLa C7 cells with doxycyclin by

fluorescent microscopy. Induced cells (+ Dox) showed strong GFP fluorescence in the cytoplasm

while cells incubated in the absence of doxycyclin only showed background fluorescence (Figure

2.2A). Briefly, HeLa C7 cells were treated with DMSO or compounds as described initially in

the compound treatment assay, except, after 24 hours, cells were fixed in 3.7% formaldehyde-1X

PBS for 10 minutes at room temperature. Cells were permeabilized by treatment with 70%

ethanol, then rehydrated in hybridization buffer (10% formamide, 2X SSPE). Hybridization was

performed using a mixture of 48 Quasar 570-labelled oligonucleotides spanning the matrix,

capsid, and nucleocapsid regions of HIV-1 as detailed by the supplier (Biosearch Technologies).

Following washing to remove unbound probe, nuclei were stained with DAPI and images were

acquired using a Leica DMR microscope at 630× magnification by Raymond Wong.

To ensure that the effect of the compounds in the context of HeLa C7 cells were similar to their

effects in HeLa B2 cells, I tested a wide range of concentrations of the compounds in HeLa C7

cells and measured GagGFP fluorescence intensity as a readout for HIV-1 gene expression using

the Typhoon 9400 imager and ImageJ software. First, I determined the range of cell density that

would provide a linear relationship between cell number and fluorescence intensity. Briefly,

HeLa C7 cells were seeded at a range of concentrations and incubated either in the presence or

absence of doxycyclin for a period of 24 hours, after which the cells were washed and stored in

PBS, covered at either room temperature (less than 10 minutes) or at 4°C (longer than 10

minutes). GagGFP fluorescence was detected using the Typhoon 9400 imager (laser emission

488nm) and the mean fluorescence intensities were used to calculate the HIV-1 GagGFP signal

in uninduced and induced cells using ImageJ software (blank wells were used as background

signal). Induced cells showed a linear relation between cell number and mean fluorescent

intensity between 2.0 x 104 and 8.0 x 104 cells (r2 = 0.9810) while uninduced cells had almost

undetectable fluorescence, as expected (Figure 2.2B). Next, I examined whether GagGFP

fluorescence reflected the levels of HIV-1 Gag levels as measured by p24 antigen ELISA

following compound treatment. To do this, HeLa C7 cells were seeded, treated and induced as

outlined previously (section 2.2.2), however, instead of harvesting cells by EDTA, cells were

41

d

Figure 2.2. Characterization of HeLa C7 cells for fluorescence studies.

(A) Representative images of HeLa C7 cells treated with DMSO in the absence (uninduced) or

presence (induced) of doxycyclin (N ≥ 3). Cells were viewed at 630X (oil immersion)

magnification. Images are cropped to show a representative field of view. (B) Measurement of

mean fluorescence intensity in uninduced and induced cells at various cell densities (N = 1).

Linear regression of mean fluorescent intensity in induced cells (between 2x104 and 8x104) is

indicated by the dotted line and labelled with the regression coefficient (N = 1).

A

B

42

washed and stored in PBS (covered) and GFP fluorescence was detected using the Typhoon 9400

imager as described above. The mean fluorescence intensities were used to calculate the HIV-1

GagGFP signal in the compound treated cells relative to the DMSO control treated cells.

Furthermore, XTT assays were performed in parallel as described previously (section 2.4) to

examine the effect of the compounds on HeLa C7 cell metabolism as a proxy for cell viability.

The IC80-90 concentrations for the compounds were approximately 15 uM, 35 uM, >3 uM and 3

uM for 892, 791, 833 and 191, respectively (Figure 2.3). These concentrations correlate well

with those used in HeLa B2 cells as measured by p24 antigen ELISA (Figure 3.2), suggesting

that the effect of the compounds on HIV-1 US RNA localization and GagGFP expression in

HeLa C7 cells reflect the effect of the compounds in HeLa B2 cells as well.

2.7 Monitoring protein synthesis by SUnSET

The effect of the compounds on nascent protein synthesis was measured by surface sensing of

translation (SUnSET) as described by Schmidt et al., 2009 (76). Cells were incubated with

puromycin, an aminoacyl tRNA analog, to allow puromycin incorporation into newly translated

peptides and prevention of further ribosomal elongation by chain termination. In this way, newly

synthesized polypeptides were “tagged” with puromycin and detected by SDS-PAGE using an

antibody against puromycin. To assess the effect of the compounds on protein translation, B2

cells were prepared and treated as described by the compound treatment assay, but were

incubated with 10 g/mL of puromycin for a period of 30 minutes at 37°C in a 5% CO2

humidified incubator prior to harvesting cell lysates for protein analysis (as described

previously). Protein concentration in cell lysates was quantified by Bradford assay and equal

amounts of protein (30-50 g) was run on either 10% or 4-15% (gradient) Tris-glycine gels.

Proteins were transferred to 0.2 m PVDF (BioRad) using the Trans-Blot Turbo blotting system

(BioRad) and blots were blocked in 5% Milk-PBS-T for ≥2 hours at room temperature. Blots

were probed overnight at 4°C with a 1/5000 dilution of mouse monoclonal antibody to

puromycin (anti-12D10, EMD Millipore) in 3% BSA-PBS-T. After incubations, blots were

washed three times with PBS-T for 10 minutes and incubated with a 1/5000 dilution of isotype-

specific HRP-conjugated anti-mouse antibody in PBS-T (Jackson ImmunoResearch). Following

washes, blots were developed using ECL Plus (Perkin-Elmer) or Clarity (BioRad) and imaged

using the ChemiDoc MP Imager (BioRad). To quantify the levels of protein synthesis, the

d

43

Figure 2.3. Compound treatment in HeLa C7 cells inhibits HIV-1 gene expression in a

dose-dependent manner similar to effects observed in HeLa B2 cells.

The dose range of the compounds which inhibit HIV-1 GagGFP expression in HeLa C7 cells

was measured by mean fluorescence intensity and expressed relative to fluorescence intensity in

DMSO-treated samples (N ≥ 3, * = p ≤ 0.05, ** = p ≤ 0.01, and *** = p ≤ 0.001). The effect of

the compounds on cellular metabolism at the indicated concentrations was measured using an

XTT assay as a readout of viable cells and expressed relative to absorbance reads of DMSO-

treated samples (N ≥ 3, * = p ≤ 0.05, ** = p ≤ 0.01, and *** = p ≤ 0.001). Error bars indicate

standard error of the mean (SEM).

44

volume intensity in each lane of compound-treated sample was calculated relative to the DMSO-

treated, dox-induced sample lane and normalized to GAPDH loading control using ImageLab

software (BioRad) from at least four independent experiments.

2.8 Viral protein degradation assay

To determine whether the compounds directly cause destabilization and/or degradation of HIV-1

regulatory proteins, the decay of HIV-1 Tat levels was compared between DMSO-treated and

compound-treated protein lysates in the presence of cycloheximide, an inhibitor of protein

translation. First, B2 cells were seeded in 6cm or 10cm plates (multiple plates per treatment for

different time points) in IMDM complete medium and HIV-1 gene expression was induced with

doxycylin (dox) for 24 hours at 37°C in a 5% CO2 humidified incubator to allow viral protein

expression. Next, 5 g/mL cycloheximide (Sigma-Aldrich) was added to block new protein

synthesis in combination with either DMSO or the compounds and cell lysates were harvested

for protein every 2 hours. Protein concentration in cell lysates was quantified by Bradford assay

and equal amounts of protein run on 13 or 14% gels by SDS-PAGE. Proteins were transferred,

blocked, probed with antibodies for Tat and Gapdh, and detected as described above.

Quantification of the relative intensity of the detected bands was performed using ImageLab

software (BioRad) and normalized to corresponding bands of the loading control (GAPDH) from

at least three independent experiments.

2.9 Proteasomal degradation protection assay

To determine whether the effect of the compounds on HIV-1 gene expression can be directly

reversed with protection from degradation of viral regulatory proteins, B2 cells were treated with

compounds in the presence of MG132, a proteasome inhibitor. Briefly, the compound treatment

assay was performed as previously described with the addition of 10 M MG132 (Sigma-

Aldrich) to compound-treated cells 8 hours prior to harvesting cell lysates for protein. Protein

concentration in cell lysates was quantified by Bradford assay and equal amounts of protein run

on 13 or 14% gels by SDS-PAGE. Proteins were transferred, blocked, probed with antibodies for

Tat and Gapdh, and detected as described above. Quantification of the relative intensity of the

detected bands was performed using ImageLab software (BioRad) and normalized to

corresponding bands of the loading control (GAPDH) from at least three independent

experiments.

45

2.10 Analysis of cellular alternative splicing events by RT-PCR

The effect of the compounds on alternative splicing of cellular RNA was analyzed by RT-PCR

by Peter Stoilov as previously described (Wong et al., 2013). Briefly, total RNA from three

independent biological replicates of each compound treatment was reverse transcribed using

random hexamers and RNaseH(-) reverse transcriptase. The samples were assayed by medium

throughput RT-PCR to determine the inclusion levels of alternatively spliced exons and splice

sites located in 73 events. For this purpose 73 primer sets (see Appendix I) containing a

fluorescently (5-FAM) labeled primer for each, were used. The fluorescently labeled PCR

products were denatured in formamide and quantified using ABI Prism capillary sequencer (Life

Technologies). The PCR reaction assembly and the subsequent liquid handling steps were

carried out using 384 well PCR plates (Axygen) and automated using Biomek 2000 and

Multimek 96 liquid handlers. The fragment analysis was performed on the PeakScanner software

(Life Technologies) in batch mode and automated using custom scripts written in Python. The

inclusion level of each exon was calculated as the amount of transcripts carrying the alternative

exon relative to the total amount of all transcripts detected in the PCR reaction and results are

summarized for compound-treatment in comparison to DMSO treatment.

2.11 Analysis of cellular alternative splicing by RNA sequencing

2.11.1 Sample preparation for RNA sequencing (RNAseq)

Total RNA from DMSO-, 791-, and 191- treated samples (RNA extraction described earlier) was

converted to mRNA into a library of template molecules suitable for subsequent cluster

generation and DNA sequencing using the Illumina TruSeq RNA Sample Preparation Kit

(Illumina) according to the manufacturer’s instructions. First, total RNA integrity was verified

using an Agilent Technologies 2100 Bioanalyzer (RNA Integrity Number (RIN) value ≥ 8).

Next, polyadenylated RNA was enriched twice from 1 g of total RNA using oligo-dT attached

magnetic beads and fragmented under elevated temperature. The RNA fragments were then

copied into first strand cDNA using reverse transcriptase and random primers, followed by

second strand cDNA synthesis using DNA Polymerase I and RNase H. Finally, end repair, A-

tailing, and paired end adaptor ligation of the cDNA fragments was performed prior to PCR

amplification to create the cDNA library.

46

2.11.2 RNAseq

The cDNA library was validated (passed quality control on a Bioanalyzer 1000 DNA chip

(Agilent)), normalized and pooled for cluster generation. cDNA libraries were sequenced on the

Illumina HiSeq2500 (paired-end, 125 bp) with version four chemistry following manufacturer’s

protocols.

2.11.3 Analysis of RNAseq data

The full human genome and transcriptomic sequences were downloaded from the UCSC

Genome Browser database and Ensembl, respectively, as described by Irimia et al., 2014 (77)

and was analyzed by Dr. Sandy Pan (Blencowe Lab, University of Toronto). For each gene, a

canonical transcript was selected for gene expression (GE) analysis based on the hierarchy

derived from the BioMart associated transcript names, or if this information was not available,

the longest protein-coding transcript was selected as the gene representative. Exon annotations

and genomic coordinates for alternative splicing (AS) analysis were derived from tables

downloaded from the UCSC Genome Browser database. To determine GE or AS changes in an

unbiased way, the effective number of unique mappable positions in each transcript (i.e. the

effective length) was determined by aligning sequences with unique transcriptomic alignment to

the human genome using Bowtie, by Dr. Sandy Pan (Blencowe Lab, University of Toronto).

Briefly, the reads obtained from the sequencing were first mapped to the human genome with

reads that map more than one place in the genome removed and the remaining reads aligned to

the transcriptome. Then, the effective mappable positions are counted by mapping a k-mer from

the transcriptome that is the same length as the reads to the genome, removing the k-mers that

map more than one place in the genome, and mapping the remaining k-mers back to the

transcriptome. This way, the "unmappable" positions are disregarded since if the k-mer extracted

from the transcriptome cannot be aligned, the reads cannot be aligned either.

2.11.3.1 Gene expression estimation

For each sample, the corresponding mRNA-Seq data were aligned against the human genome

using Bowtie, allowing for a maximum of two mismatches by Dr. Sandy Pan (Blencowe Lab,

University of Toronto).. Reads with one unique genomic alignment were then aligned against the

canonical transcriptome and, for each transcript, the number of reads with one unique

transcriptomic alignment were counted. The expression level of genes was quantified as

47

corrected ‘reads per kilobase of exon model per million mapped reads’ (cRPKM), a widely used

metric to estimate gene expression levels. The expression cutoff was 0.5 cRPKM, corresponding

to the transcript of the gene being present if there were ≥10 reads that mapped uniquely to a

single genomic locus. Approximately 19,847 Ensembl annotated protein-coding genes were

compared to create a gene list of differentially expressed genes. Genes were considered

differentially expressed if fold changes in cRPKM was ≥ 2 in compound-treated versus DMSO-

treated samples.

2.11.3.2 Percent spliced in (PSI) estimation

Every internal exon in each annotated transcript was considered a potential “cassette” exon as

described previously (77). Briefly, each “cassette” AS event was defined by three exons: C1, A

and C2, where A was the alternative exon, and C1 and C2 were the 5´ and 3´ constitutive exons,

respectively. For each event, spliced junctions were defined as follows: C1A (connecting exons

C1 and A), AC2 (connecting exons A and C2), and one alternative junction, C1C2 (connecting

exons C1 and C2). For each sample, the corresponding mRNA-Seq data were aligned against the

human genome using Bowtie, allowing for a maximum of two mismatches. Reads that did not

map to the genome were then aligned to the full non-redundant set of junction sequences and, for

each junction, the number of reads with one unique alignment mapping to it were counted. For

each junction, the corresponding read count was normalized for its mapping ability by

multiplying the read count by the ratio between the maximum number of mappable positions and

its effective number of unique mappable positions (as defined above). The percent inclusion, or

“percent spliced-in” (PSI) value, for each internal exon was defined as: PSI = 100 × average

(#C1A,#AC2) / (#C1C2 + average(#C1A,#AC2)), where #C1A, #AC2 and #C1C2 were the

normalized read counts for the associated junctions. Exons were considered alternative in a

sample if 5 ≤ PSI ≤ 95. In addition “high confidence” PSI levels were defined as those PSI

values that fulfilled the following specific coverage and balance criteria:

max(min(#C1A,#AC2),#C1C2) ≥ 5 AND min(#C1A,#AC2) + #C1C2 ≥ 10 and

|log2(#C1A/#AC2)| ≤ 1 OR max(#C1A,#AC2) < #C1C2. The goal of the first criterion was to

ensure enough read coverage for sufficient precision and resolution in the estimation of PSI

levels. The goal of the second criterion was to exclude AS events where there was a high

imbalance in read counts between the two junctions formed by exon inclusion since these

imbalances can confound PSI estimates for cassette AS events. For comparison of AS levels

48

between pairs of samples, Pearson correlation was applied to PSI levels. Events were considered

differentially spliced between DMSO- and compound-treated samples if changes in PSI levels

were ≥ 10.

2.12 Compound treatment assay in primary cells

2.12.1 Human primary cell donors and cell preparation

Peripheral blood mononuclear cells (PBMCs) were isolated from healthy (HIV-uninfected)

volunteer blood donors as described by Dobson-Belaire et al., 2010 (78). Informed consent was

obtained from participants in accordance with the guidelines for conduct of clinical research at

the University of Toronto and St. Michael’s Hospital, Toronto, Ontario, Canada. Briefly, PBMCs

were isolated from the volunteers by leukophoresis (Spectra apheresis system, Gambro BCT) or

whole blood collection (by Gordon McSheffrey). PBMCs were collected using Ficoll-Paque Plus

(Amersham Biosciences) following the manufacturer’s instructions (PBMCs obtained from

whole blood were further depleted of monocytes by Gordon McSheffrey) and stored at -80°C in

90% (vol/vol) heat-inactivated fetal calf serum (FCS, HyClone) and 10% (vol/vol) dimethyl

sulfoxide (DMSO, Sigma-Aldrich) for subsequent experimentation.

2.12.2 Generation of replication-competent HIV-1 virus

HIV-1 R5 BaL virus was generated in U87.CD4.CCR5 cells (NIH AIDS reagent program

#4035) by Dr. Alex Chen. Briefly, U87 cells were grown in Dulbecco’s Modified Eagle’s

Medium (DMEM, Wisent) supplemented with 10% [vol/vol] heat inactivated fetal bovine serum

(FBS, Wisent), 1 g/ml puromycin (Sigma-Aldrich), and 300 g/ml G418 (Sigma-Aldrich) in a

T75 tissue culture flask (Sarstedt). After 24 hours, (approximately 70% cell confluency), the

cells were infected with the HIV BaL stock (obtained from Dr. Donald Branch) at a multiplicity

of infection (MOI) of 0.01 for 1 hour at 37°C in 5% CO2 humidified incubator. After 1 hour, the

cells were washed twice with DMEM medium to remove the remaining HIV BaL viruses and

cultured in fresh DMEM medium at 37°C in 5% CO2 humidified incubator. Viral supernatants

were harvested by filtering through a 0.45 M filter at different days post-infection and the level

of infectious virus was measured by p24 antigen ELISA. Viral supernatants harvested on Day 10

post infection were found to correspond to peak levels of viral replication and these supernatants

were stored in aliquots at -80°C for subsequent experiments.

49

2.12.3 HIV-1 BaL infection of primary cells

PBMCs were thawed, washed with RPMI 1640 complete medium and cultured in RPMI 1640

complete medium containing 2 μg/mL of PHA-L (Sigma-Aldrich) and 20 U/mL of IL-2 (BD

Pharmingen) at 37°C in a 5% CO2 humidified incubator for 72 hours. Subsequently, cells were

counted and a portion of the cells was separated to another tube for uninfected control

treatments. The remaining PBMCs were resuspended in HIV-1 BaL at a multiplicity of infection

(MOI) of approximately 0.01 in a total volume of 1 mL and infected by spinoculation for 1 hour

at 900 x g at room temperature. Subsequently, cells were washed twice with room temperature

RPMI 1640 complete medium and resuspended to a concentration of 5 x 105 cells/mL in

complete RPMI 1640 containing 40 U/mL of IL-2. Cells were seeded in 6-well or 12-well tissue

culture plates (Sarstedt and Falcon, respectively) in a volume of 1 mL in preparation for

compound treatment.

2.12.4 Compound treatment of primary cells

Compounds were prepared at 2X of the desired concentrations in complete RPMI 1640 with

equivalent concentrations of dimethyl sulfoxide (DMSO) and added to infected PBMCs or

uninfected control PBMCs to a total volume of 2 mL/well. Azidothymidine (AZT, Sigma-

Aldrich) was used as control treatment at a final concentration of 3.74 M. Plates were incubated

at 37°C in a 5% CO2 humidified incubator for a period of eight days. On day 4 post infection,

culture medium was replenished with the compounds and IL-2 in fresh complete RPMI 1640. On

days 0, 2, 4, and 6 post infection, 450 L of culture supernatant was harvested, lysed with 50 L

of 10% TritonX-100 at room temperature for approximately 1 hour and stored at -20°C for p24

antigen ELISA. Subsequently, 20 L of culture medium was harvested to assess percent cell

viability by trypan blue exclusion using glasstic slides (Kova). On day 8 post infection, 1.0-1.2

mL of culture medium was harvested, centrifuged at 2,000 rpm for 5 minutes, and 450 L of

culture supernatant was harvested for p24 antigen ELISA as described for the previous days. The

remaining supernatant was discarded and the pellet was resuspended in 100-200 L of complete

RPMI 1640 for assessing cell viability by trypan blue exclusion as described for previous days. If

necessary, cells were further diluted in complete RPMI 1640 for more accurate counts. Relative

percent cell viability in compound treated samples versus DMSO-control treated samples was

calculated as follows: (total viable cells / total cells)compound / (total viable cells / total cells)DMSO.

50

2.13 Statistical analysis

In vitro experiments were all performed on at least three separate occasions and are represented

as the mean the standard error (SEM) of the experiment, unless otherwise stated. Statistical

significance comparisons between two samples were calculated using the paired two-tailed

student’s t test (Microsoft Excel) and graphs were generated using Prism 5.0 software

(GraphPad). Significant differences are represented by comparison to DMSO-treated control

samples with the following legend: * = p ≤ 0.05, ** = p ≤ 0.01 and *** = p ≤ 0.001. Significance

levels of p ≤ 0.05 were considered statistically significant.

51

3 Results

Contributions: Results described in sections 3.1 through 3.5 includes data collected and analyzed

by both myself and Raymond W. Wong as part of my undergraduate research project. The initial

screen of sixty compounds was done by Raymond W. Wong. The radioactive RT-PCR

examining the effect of the compounds on splice site selection within the HIV-1 MS RNAs was

done by Alan Cochrane from RNA samples prepared by me. Analysis of results outlined in

sections 3.6 and beyond describes studies conducted and analyzed by me as part of my graduate

research project. Testing of the compounds in SupT1 T cell lines was done by Raymond W.

Wong. The RT-PCR assessing the effect of the compounds on select cellular alternative splicing

events was done by Peter Stoilov using RNA samples prepared by me. RNAseq was performed

by the Donnelly Sequencing Centre with subsequent mapping of reads and calculation of percent

spliced in (PSI) scores and corrected RPKM values done by Sandy Pan. Testing of the maximum

tolerable doses of these compounds in mice models was done by Liang Ming.

3.1 Identification of four compounds that suppress HIV-1 gene expression in HeLa cells

The success of digoxin as a potent inhibitor of HIV-1 gene expression, described previously by

Wong et al. (2013), lead us to screen other small molecular compounds for activity against HIV.

We tested over sixty compounds identified as RNA splicing modulators using an SMN2 mini-

gene reporter (Dr. Peter Stoilov at West Virginia, unpublished) for their ability to inhibit HIV-1

gene expression. We identified four compounds, designated 191, 791, 833, and 892, as potent

inhibitors of HIV-1 gene expression (Figure 3.1). The four compounds differed in the number of

five and six-numbered rings they contained, but did not have a steroid-ring structure like digoxin

and other cardiatonic steroids (Figure 3.1A). Portions of both 791 and 191 structures resembled

nucleotide bases, while portions of 892 and 833 structures resembled amido-groups. In addition,

both 791 and 191 contained chlorine and/or fluorine groups at the ends of their structures. These

compounds were structurally dissimilar to each other and to previously characterized modulators

of HIV-1 RNA processing digoxin, 8-azaguanine, and 5350150, herein referred to as 8-aza and

150 (Wong et al, 2013).

52

Figure 3.1. Screen of RNA splicing modulators identifies four potent inhibitors of HIV-1

gene expression. (A) Structures of compounds tested. (B) Effect of compound treatment on

HIV-1 virion accumulation in culture supernatant as measured by p24 antigen ELISA and

expressed relative to DMSO-treated samples (N ≥ 17, *** = p ≤ 0.001). Uninduced, DMSO-

treated (DMSO, - Dox) samples were included as negative controls. Concentrations of the

compounds were as follows: 15 M for 892, 30 M for 791, and 2 M for 833 and 191.

A

B

53

3.1.1 Previously published literature for 191, 791, 833, and 892 activity

Since these compounds were active against HIV-1, I investigated whether the activity of these

compounds were previously described in scientific literature or in patent applications using

SciFinder. To date, 791 and 833 have not been published in literature or been patented, however,

there is limited information available for the activity of 191 and 892, as well as structures similar

to 791, in other contexts.

191 has been previously tested for activity against microsomal prostaglandin E synthase-1

(mPGES-1), an essential enzyme involved in inflammatory diseases such as rheumatoid arthritis,

fever, and pain (79). Since several compounds targeting human mPGES-1 were not specific for

murine models of mPGES-1, 191 was tested in a screen with three other compounds for their

activity against murine mPGES-1. 191 was shown to inhibit the enzymatic activity of murine

mPGES-1 by 71% when used at a concentration of 50 μM (79). In addition, binding of 191 to

mPGES-1 was modeled using protein homology to define molecular determinants of mPGES-1

ligand binding for further rationale-drug design (79).

892 and similarly structured compounds have been patented as putative activators of AMP-

activated protein kinase (AMPK) (WO 2012027548), modulators of telomerase binding (WO

20122097600 and US 201200160260), and activators of histone deacetylase 1 (HDAC1) (WO

2010011318). Interestingly, a compound that is structurally similar to 892 was tested for

inhibitory activity in the context of Hepatitis C virus (HCV) and was shown to inhibit enzymatic

activity of HCV protease by ~57% at 50 μM (80).

Two compounds resembling 791 were tested for the ability to inhibit the activity of cyclin

dependent kinase 2 (CDK2)/cyclin A. These compound differ in the side groups attached to the

core pyrimidine ring structure. One compound, designated 12a, has a phenol group in place of

the methyl group and a methyl group in place of the phenol ring with a chlorine in 791. 12a was

shown to inhibit CDK2/cyclin A activity in vitro at an IC50 of 0.25 μM (81).

54

3.2 191, 791, 833, and 892 potently inhibited HIV-1 gene expression in a dose-dependent manner

To determine the basis for the effect of the compounds on HIV-1 gene expression, we treated

HeLa cells containing a doxycycline-inducible HIV-1 provirus (Figure 2.1) with each of the

compounds added to the cell culture medium. Treatment of HeLa B2 cells with the compounds

and doxycyclin resulted in inhibition of HIV-1 viral production by 80-90% relative to DMSO

treatment, as measured by p24 antigen ELISA, at concentrations in the low M range (Figure

3.1B). Virus production from uninduced, DMSO-treated cells showed no p24 Gag expression, as

expected. Furthermore, inhibition of HIV-1 replication with compound treatment was dose-

dependent with no significant cytotoxicity observed with compounds 892, 833, or 191 at 24

hours post treatment (Figure 3.2). High doses of 791 (>30 M) had a significant effect on cell

viability, as measured by an XTT assay, in HeLa B2 cells, but did not show significant toxicity

in CD4+ SupT1 cells at that concentration (Raymond W. Wong, unpublished) and was active in

PBMCs at much lower concentrations with little to no cytotoxicity (preliminary data, see Figure

4.5). In addition, 791, 833, and 191 maintained their inhibitory activity in the context of HIV-1

replication in CD4+ SupT1 cells at concentrations which potently inhibited HIV-1 gene

expression in B2 cells, with no significant cytotoxicity (Raymond W. Wong., unpublished).

3.3 191, 791, 833, and 892 decreased HIV-1 structural and regulatory protein expression

Since compound-treatment potently inhibits virus production, we examined the effect of the

compounds on expression of multiple viral proteins. Following compound treatment and

doxycycline induction for 24 hours, cell lysates were harvested for protein and analyzed by SDS-

PAGE using antibodies to detect viral structural proteins Gag and Env, as well as regulatory

proteins Rev and Tat. Representative western blots from at least three independent experiments

are shown in Figure 3.3 and Figure 3.4. All four compounds reduced the levels of p55, p41, and

p24 Gag proteins and gp160 and gp120 Env proteins relative to DMSO treatment (Figure 3.3).

Furthermore, uninduced, DMSO-treated cells showed no viral protein expression, as expected.

Blotting for GAPDH or α-tubulin was used to ensure equal loading of total protein across all the

samples and allows for comparison of viral protein expression. The effect of the compounds on

viral regulatory proteins, however, is very different from that observed with previously

d

55

Figure 3.2. Compound treatment inhibits HIV-1 gene expression in a dose-dependent

manner. The dose range of the compounds which inhibit HIV-1 virion production in culture

supernatant was measured by p24 antigen ELISA and expressed relative to p24 Gag levels in

DMSO-treated samples (N ≥ 3, * = p ≤ 0.05, ** = p ≤ 0.01, and *** = p ≤ 0.001). The effect of

the compounds on cellular metabolism, at the ranges of concentrations tested, was measured

using an XTT assay as a readout of viable cells and expressed relative to absorbance reads of

DMSO-treated samples (N ≥ 3, * = p ≤ 0.05, ** = p ≤ 0.01, and *** = p ≤ 0.001). Error bars

indicate standard error of the mean (SEM).

56

characterized HIV-1 inhibitors (Figure 3.4). Digoxin treatment resulted in the depletion of Rev

and p14 Tat levels, but had no effect on the levels of p16 Tat, while 8-Aza and 150 treatment did

not affect either Rev or Tat levels relative to DMSO treatment. These results are consistent with

previously published data (Wong et al, 2013 and Wong et al, 2013). Together, these results

suggest that 191, 791, 833, and 892 potently inhibit HIV-1 protein expression in vitro by

blocking expression of both early (Rev, Tat) and late (Gag, Env) HIV-1 proteins.

3.4 191, 791, 833, and 892 reduced HIV-1 US and SS RNA but not MS RNA

To determine whether the dramatic loss of viral proteins is accompanied by changes in viral

mRNA levels, the effect of compound treatment on the abundance of HIV-1 RNA classes was

examined by qRT-PCR. Total RNA was isolated from DMSO- or compound-treated cells, and

qPCR was performed using forward and reverse primers specific to -actin (internal control for

normalization) as well as HIV-1 unspliced (US), singly-spliced (SS), and multiply spliced (MS)

RNAs. Analysis of HIV-1 RNA abundance revealed that the compounds reduced levels of HIV-1

US and SS RNAs with no significant changes in levels of MS RNA relative to DMSO treatment.

Uninduced, DMSO-treated cells showed no viral RNA expression, as expected (Figure 3.5). This

data correlated with the reduced levels of Gag, Env, and p14 Tat (Figures 3.3 and 3.4) since

these proteins are encoded by HIV-1 US and SS RNAs, respectively. However, the imbalance in

viral RNA classes suggested that the compounds may be altering viral RNA splicing, a critical

step in HIV-1 replication that relies heavily on regulation of splicing involving many cellular

factors.

57

Figure 3.3. Compound treatment dramatically decreases the expression of HIV-1 structural

proteins. Representative blots showing the effect of the compounds on HIV-1 (A) Gag protein

and (B) Env protein expression relative to GAPDH or α-tubulin expression as loading controls

(SDS-PAGE, N ≥ 3). Uninduced, DMSO-treated (DMSO, - Dox) samples and dox-induced,

DMSO-treated samples serve as negative and positive controls, respectively. Images showing

p55, p41, and p24 expression were cropped from same blot visualized at different exposure times

due to difference in abundance of these isoforms. Concentrations of the compounds were as

follows: 15 M for 892, 30 M for 791, and 2 M for 833 and 191.

A

B

58

Figure 3.4. 191, 791, 833, and 892 dramatically decrease the expression of HIV-1 regulatory

proteins, in contrast to previously characterized HIV-1 inhibitors. Representative blots

showing the effect of the compounds on HIV-1 Rev and Tat protein expression relative to α-

tubulin expression as loading control (SDS-PAGE, N ≥ 3). Uninduced, DMSO-treated (DMSO, -

Dox) samples and dox-induced, DMSO-treated samples serve as negative and positive controls,

respectively. For the blot shown, lanes were cropped from the same blot to show compound-

treated lanes adjacent to DMSO-treated control lanes. Concentrations of the compounds were as

follows: 0.1 M for digoxin, 50 M for 8-Aza, 15 M for 892, 30 M for 791, and 2 M for

833, 150 and 191.

59

Figure 3.5. The compounds dramatically decrease the levels of HIV-1 US and SS RNAs.

(A) Schematic of HIV-1 genome with the positions of the forward and reverse primers used for

qRT-PCR analysis indicated by the arrows. US = unspliced, SS = singly spliced and MS =

multiply spliced. (B) Quantification of viral mRNA levels in compound-treated samples were

normalized to -actin and the mean mRNA levels expressed relative to DMSO-treatment (N ≥ 4,

** = p ≤ 0.01, and *** = p ≤ 0.001). Error bars indicate standard error of the mean (SEM).

Concentrations of the compounds were as follows: 15-20 M for 892, 30 M for 791, and 2-2.5

M for 833 and 191.

A

B

60

3.5 191 and 791 did not alter splice site usage among HIV-1 MS RNA

Given that HIV-1 MS RNA abundance is unaffected by compound treatment but MS-encoded

viral regulatory proteins, Rev and Tat, are lost, the compounds could be inducing changes in

splice site usage, thereby altering the levels of splice variants within the MS RNA class such that

these proteins are no longer expressed. Hence, we analyzed whether the compounds induced

preferential selection of splice site within the MS RNAs by radioactive RT-PCR using forward

and reverse primers that amplify the differentially spliced isoforms within the MS RNA class.

Although the HIV-1 proviral genome in HeLa B2 cells contains modifications, it recapitulates

the splicing events of HIV-1 pre-RNA, so that the levels of most MS RNA isoforms (less

abundant isoforms are below the limit of detection) can be analyzed using this method (41, 82).

Amplified products were visualized and the levels of HIV-1 MS RNA isoforms were quantified

by densiometric analysis and designated according to size as described by Purcell and Martin

(82). No significant changes in splice site usage were observed with 791 and 191 treatment,

relative to DMSO treatment (Figure 3.6), suggesting that the loss of HIV-1 regulatory proteins

with compound treatment is not due to preferential production of specific viral MS RNAs

encoding these proteins. In contrast, 892 and 833 treatment caused modest decreases in levels of

Rev1/2 and Nef RNAs and increased Tat1 and Tat2 RNAs, relative to DMSO treatment.

However, these changes do not explain the loss of p16 Tat, which is encoded by the MS RNA,

when treated with 892 or 833. These results suggest that the compounds do not alter the

production of Rev and Tat MS RNAs (early phase of viral gene expression) since the MS RNAs

remain following compound treatment. Instead, the compounds appear to perturb the transition

from early to late HIV-1 gene expression, consistent with inhibition of Rev function.

Since compound treatment resulted in loss of HIV-1 MS-encoded regulatory proteins Rev and

Tat, but had no appreciable effect on the abundance or splice site usage within MS RNA, we

hypothesized that the compounds may inhibit HIV-1 gene expression by perturbing Rev-

mediated viral RNA transport, protein synthesis, or protein stability.

61

Figure 3.6. 191 and 791 do not alter splice site selection within HIV-1 MS RNAs.

(A) Schematic of HIV-1 genome with the positions of the forward and reverse primers used to

amplify the 1.8 kb class of HIV-1 RNAs indicated by the arrows. (B) Representative RT-PCR

gel with HIV-1 MS isoforms labelled on the right according to Purcell and Martin, 1993 (N ≥ 3).

(C) Quantification of PCR products was performed by densiometry analysis with the level of

each isoform expressed as the mean percentage of the total density of all RNA species within the

sample from at least three independent experiments. Error bars indicate standard error of the

mean (SEM) and statistical significance is indicated by * (p ≤ 0.05, N ≥ 3). Concentrations of the

compounds were as follows: 15-20 M for 892, 30 M for 791, and 2-2.5 M for 833 and 191.

C

A

B

62

3.6 Inhibition of cytoplasmic accumulation of HIV-1 US RNA and Gag with compound treatment was consistent with perturbation of Rev function

To assess the effect of the compounds on the Rev-dependent export of incompletely spliced viral

RNA, the subcellular localization of HIV-1 US RNA and Gag was examined by fluorescent in

situ hybridization (FISH). If the compounds perturb Rev function, we would expect to see

accumulation of US and SS viral RNAs in the nucleus with little to no expression in the

cytoplasm. Since the compounds caused depletion of Rev protein (Figure 3.4), it was likely that

HIV-1 US RNA were unable to be exported to the cytoplasm for subsequent virus particle

assembly and translation of viral structural proteins. To determine if this was the case, HeLa C7

cells were treated with DMSO or compounds as described previously (see Methods section for

data showing similar activity of the compounds in HeLa C7 cells) and inhibition of HIV-1 gene

expression was measured by FISH. Induction of HIV-1 gene expression (DMSO, +Dox) results

in US RNA localization in both the nucleus and cytoplasmic region with strong GagGFP

expression throughout the cell (Figure 3.6) Co-localization of viral US RNA and GagGFP is

indicated by the merged signal (yellow). In contrast, compound treatment prevents cytoplasmic

accumulation of HIV-1 US RNA and reduced GagGFP levels relative to DMSO treatment (N ≥

3). No US RNA and GagGFP expression was detected in uninduced cells, as expected. The

effect of the compounds on HIV-1 US RNA and GagGFP expression is consistent with US RNA

abundance and Gag protein expression measured by qRT-PCR and SDS-PAGE, respectively

(Figures 3.3 and 3.5). Furthermore, the nuclear retention of US RNA upon compound treatment

is consistent with the loss of Rev protein observed by SDS-PAGE (Figure 3.4). These results

suggest that the compounds prevent the early to late phase transition in HIV-1 gene expression

by inhibiting Rev-mediated viral RNA transport, thereby effectively hindering viral replication.

3.7 191, 791, 833, and 892 did not affect total protein synthesis

To determine whether the compounds caused depletion of viral proteins by inhibiting cellular

protein translation, the effect of compound treatment on protein synthesis was measured by

surface sensing of translation (SUnSET) as described by Schmidt et al (76). This nonradioactive

method to monitor protein synthesis uses puromycin, a structural analog of aminoacyl tRNAs

produced by Streptomyces alboniger, to “tag” nascent peptides by chain termination and allows

their detection following SDS-PAGE using a monoclonal antibody to puromycin. Following

63

Figure 3.7. Compounds inhibit cytoplasmic accumulation of HIV-1 US RNA.

Representative fluorescent in situ hybridization images of HeLa B2 cells treated with DMSO or

the indicated compounds (N ≥ 3). Cells were viewed at 630X (oil immersion) magnification.

Images are cropped to show a representative field of view.

DAPI US RNA GagGFP

64

compound treatment and induction of viral gene expression (24 hours), cells were “pulsed” with

puromycin and cell lysates were harvested to directly monitor levels of newly synthesized

proteins by western blotting. Analysis of blots from at least four independent experiments

indicated that the compounds did not induce significant changes to protein synthesis relative to

DMSO treatment by 24 hours post treatment (Figure 3.8). In contrast, cells incubated either in

cycloheximide (CHX), an inhibitor of translation elongation, or without puromycin, showed

relatively decreased puromycin-tagged polypeptides, as expected. These results suggest that the

loss of HIV-1 proteins is not a consequence of a global block of cellular protein translation, but

rather, is a selective effect on HIV-1 gene expression.

The observation that the compounds do not significantly perturb cellular protein synthesis is

corroborated by the long-term toxicity profiles of the compounds (Figure 3.9). If the compounds

induce a stress response or inhibit protein translation, a detrimental effect on cell proliferation

would have been observed in cells treated with compounds for a period longer than 24 hours. I

monitored cellular metabolism and cell proliferation in B2 cells up to four days post treatment by

XTT assay. Although, 191, 791, 833, and 892 treatment had significant effects on cell

growth/cellular metabolism at three and four days post treatment, both 191 and 791 were much

better tolerated by the cells over the four days compared to 892 or 833 treatment. In addition,

191 and 791 are active in primary cells at similar or lower concentrations than tested here up to

six days post treatment (refer to section 3.11 and Figures 3.16 and 3.17). These observations

suggest that the compounds do not directly perturb protein translation, but does not rule out

whether 833 and 892 induce signaling pathways involved in the stress response since these

compounds appeared to be more toxic with prolonged exposure in HeLa B2 cells.

65

Figure 3.8. The compounds do not affect total protein synthesis.

(A) Representative blot showing the effect of the compounds on protein synthesis by puromycin

labelling of nascent polypeptides (N ≥ 4). Samples not incubated with puromycin (No Puro) or

treated with cycloheximide (CHX), to block translation, served as negative controls. (B)

Quantification of protein synthesis in the presence of the compounds was measured by the

volume intensity in each lane normalized to GAPDH intensity and expressed relative to the

DMSO-treatment (N ≥ 4, *** = p ≤ 0.001). Error bars indicate standard error of the mean (SEM).

A

B

66

Figure 3.9. 191 and 791 had better long-term toxicity profiles than 833 and 892.

The graph shows cell proliferation as measured by XTT assay 1, 3, and 4 days post-treatment

with the compounds relative to DMSO-treated HeLa B2 cells (N = 3). Error bars depict standard

error of the mean and *, **, and *** indicate P values ≤ 0.05, 0.01, and 0.001, respectively.

67

3.8 The compounds did not alter the stability of existing HIV-1 Tat protein.

Since the compounds appeared to selectively decrease the viral regulatory proteins without

altering the levels of the MS RNAs encoding them, I examined whether compound treatment had

a direct effect on the stability of these proteins. To determine if the compounds directly caused

destabilization and/or degradation of HIV-1 MS-encoded proteins, the decay of HIV-1 Tat levels

was compared between DMSO-treated and compound-treated cells in the presence of

cycloheximide, an inhibitor of protein translation. Briefly, HeLa B2 cells were induced with

doxycylin for 24 hours to allow viral protein expression in the absence of the compounds.

Cycloheximide was then added, to block new protein synthesis, in combination with either

DMSO or the compounds. Cell lysates were harvested for protein every 2 hours to measure the

decay of HIV-1 Tat. If the compounds directly caused destabilization and/or degradation of Tat,

Tat expression would be lost much sooner with compound treatment than with DMSO treatment.

Representative western blots from at least two independent experiments are shown in Figure 3.10

with a summary of the data illustrated in the graph below. HIV-1 p14 Tat expression was lost

more quickly than p16 Tat, with both proteins lost by approximately 8 hours. Quantification of

multiple blots revealed that the compounds did not enhance the decay of Tat relative to DMSO

treatment since Tat levels in compound-treated samples fall within the standard error of the mean

described for Tat levels with DMSO treatment. This observation suggests that addition of the

compounds did not have an effect on the stability of existing Tat protein. Furthermore, the levels

of both Tat isoforms were rescued with the addition of proteasome inhibitor, MG132, suggesting

that HIV-1 Tat may be degraded by the proteasome degradation pathway. To determine whether

HIV-1 regulatory proteins can be protected from proteasomal degradation in the presence of the

compounds, HeLa B2 cells were treated with compounds and induced with doxycycline as

previously described, but were additionally treated with MG132 for eight hours prior to

harvesting cell lysates for protein analysis. Representative blots from at least three independent

experiments are shown in Figure 3.11. MG132 treatment dramatically increased the levels of

both p14 and p16 Tat, indicating that proteasomal inhibition rescued the accumulation of Tat

isoforms in the presence of the compounds. Thus, there was ongoing synthesis of Tat in the

presence of the compounds. This effect was not mirrored with respect to the levels of HIV-1

Gag. In fact, addition of MG132 to DMSO-treated cells resulted in a reduction in p24 Gag.

68

Gag.

Figure 3.10. Compounds do not affect the half-life of HIV-1 Tat relative to DMSO.

(A) Representative blots showing the decay of Tat protein in the presence of cycloheximide (10

M) and DMSO or indicated compounds (N ≥ 3, except for 833, N = 1-2). MG132 (10 μM) was

added for 8h as an additional control to determine whether inhibition of the proteasome prevents

protein degradation. All uninduced (unind.) and 0h samples were treated with DMSO. GAPDH

serves as loading control. (B) Summary of effect of compounds on HIV-1 Tat degradation. Band

volume intensities of both p14 and p16 Tat isoforms were calculated for each treatment relative

to that of the DMSO control treatment and were then normalized to corresponding GAPDH

bands (N ≥ 3, except for 833, N = 1-2). Error bars depict standard error of the mean, if possible.

B

A

69

Figure 3.11. HIV-1 Tat expression can be rescued with proteasome inhibition by MG132.

(A) Representative blot showing effect of the compounds on HIV-1 Gag and Tat expression in

the presence or absence of proteasome inhibitor MG132, relative to DMSO treatment in HeLa

B2 cells. GAPDH serves as loading control. (B) Summary of band intensities of HIV-1 p24 Gag

and p14 and p16 Tat with each treatment relative to that of the DMSO control normalized to the

corresponding GAPDH bands (N ≥ 3). Error bars depict standard error of the mean and *, **,

and *** indicate P values ≤ 0.05, 0.01, and 0.001, respectively (gray * reflects significance

relative to DMSO, + Dox, + MG132 treatment).

A

B

70

Together, these results indicate that Tat synthesis did indeed occur in the presence of the

compounds, since Tat accumulation was rescued with proteasomal inhibition, but that the

compounds did not directly induce Tat destabilization. This suggests that the compounds affect

processes that alter the rate of synthesis of HIV-1 regulatory proteins, their degradation, or both.

Furthermore, the lack of changes in the levels of Gag with MG132 treatment, suggests that the

compounds inhibit HIV-1 gene expression by other modes of action in addition to altering the

stability of viral regulatory proteins.

3.9 791 did not significantly affect cellular alternative splicing while 191, 833, and 892 had limited effects

To evaluate the effect of compound treatment on alternative splicing of select endogenous

transcripts (see Appendix for list) RT-PCR was performed using RNA isolated from DMSO and

compound-treated HeLa B2 cells and quantitated by capillary electrophoresis of the amplicons in

collaboration with Dr. Peter Stoilov (West Virginia). The ‘percent spliced in’ or PSI in annotated

cassette exons was determined and compared to DMSO treatment (Figure 3.12). Treatment with

791 showed no appreciable changes in alternative splicing of the examined events as most events

fell along the theoretical diagonal dotted line depicting no difference between compound and

DMSO treatments (Pearson correlation coefficient, R = 0.97). The other three compounds

showed some deviation from the diagonal line with a few events falling above or below the

diagonal indicating increased and decreased exon inclusion, respectively, but also correlated well

with DMSO treatment (R = 0.94). Changes in alternative splicing of endogenous

genes/transcripts with |PSI| ≥ 10% and 20% are represented as red and yellow dots,

respectively, and a subset of these genes are labelled next to their respective data points (Figure

3.12). Interestingly, three differentially spliced genes, fgfr1op2, macf1, and gm130/golga2 were

common among all four compounds, while an additional gene, nap1l1, was common to three of

the four compounds, within the subset of alternative splicing events examined (see Appendix,

events marked in bold font). The functions of these genes and the roles they may play in the

inhibition of HIV-1 gene expression is outlined in the Discussion section.

To determine the global effect of the compounds on alternative splicing of endogenous

transcripts in an unbiased fashion, paired-end RNAseq was performed on RNA isolated from

DMSO, 791, and 191 treated HeLa B2 cells. I focused on 791 and 191 since these two

71

compounds had the best long-term toxicity profiles of the four compounds (see Figure 3.9). To

calculate altered splicing events in response to 791 or 191 treatment, the PSI in annotated

cassette exons was determined and compared to DMSO treatment. Based on the analysis of

biological duplicates of the ≥ 9,000 alternatively spliced events detected, 791 treatment resulted

in very few altered splicing events (2 AS events with exon inclusion/exclusion ≥20% out of

>10,000 events) and correlated well (R = 0.99) with changes seen in DMSO treated samples

(Figure 3.13). 191 treatment induced more changes (25 AS events with exon inclusion/exclusion

≥20% out of >9,800 events) in endogenous alternative spliced events, but also correlated well (R

= 0.97) with splicing changes observed in DMSO treated samples (Figure 3.13). The patterns of

alternative splicing changes observed by RNAseq were consistent with data from the subset of

AS events measured by the Stoilov group. In fact, 791 altered splicing of fgfr1op2 with a PSI

score of -20% (p = 0.0004, N = 2, >9,000 events), relative to DMSO treatment. Together, these

results indicate that 191 and 791 did not significantly perturb cellular alternative splicing and

suggest that their inhibitory effect is selective to processes involved in HIV-1 gene expression.

This idea is corroborated by the lack of alternative splicing changes (|PSI| ≥ 20%), that are

common to both 191 and 791 (Figure 3.13C).

To determine whether signal induced changes in mRNA expression levels may have affected the

detection of exon inclusion changes, changes in total mRNA expression were compared with

changes in alternative spicing. The differential expression level of genes with DMSO, 191, or

791 treatment was quantified as corrected reads per kilobase of exon model per million mapped

(cRPKM) reads. The expression cutoff was a cRPKM value of 0.5, corresponding to ≥ 10 reads

that uniquely mapped to a single genomic locus. Genes were described as differentially

expressed (DE) if the cRPKM fold change was ≥ 2 or ≤ 0.5. Of 11,406 total genes examined,

relatively few DE genes were detected following compound treatment (Figure 3.14). In fact, 791

and 191 treatment only induced changes in 0.74% and 0.46% of total genes analyzed,

respectively, relative to DMSO treatment. 791 treatment resulted in more upregulated genes

while 191 treatment resulted in approximately equal numbers of upregulated and

downnregulated genes (Figure 3.14A). Of the genes whose expression levels were altered, trib3,

which encodes a putative protein kinase, was expressed about 9-fold more with 791 treatment

relative to DMSO treatment (N = 2; see Appendix). Examination of differentially expressed

genes that were shared between both 791 and 191 treatment revealed little overlap. In fact, only

72

c

Figure 3.12. Compounds have limited effects on cellular alternative splicing events.

Mean alternative splicing changes (PSI, percent spliced in) were plotted comparing DMSO and

compound treatment (N = 3, RT-PCR). Diagonal dotted line: no difference between treatments.

Dots above/below the diagonal: increased/decreased exon inclusion. |PSI| ≥ 10% and 20% are

indicated as red and yellow dots (labelled), respectively. Statistically significant alternative

splicing changes with |PSI| ≤ 10% are indicated by the gray dots (Student’s t-test, two-tailed).

Error bars not shown. Pearson correlations (R values) are shown.

73

Figure 3.13. 191 and 791 do not appreciably alter cellular alternative splicing events.

(A) Mean alternative splicing changes (PSI or percent spliced in) were plotted comparing DMSO

and compound treatment (N = 2, RNA-seq). |PSI| ≥ 10% and 20% are represented as red and

yellow dots, respectively. AS genes with exon inclusion/exclusion ≥ 20% are labelled or listed

on the right. Statistically significant alternative splicing changes with |PSI| ≤ 10% are indicated

by the gray dots (Student’s t test, two-tailed). Error bars not shown. (B) Summary of altered exon

inclusion or exclusion (Incl. or Excl.) with compound treatment (RNAseq, N = 2). (C) Venn

diagram comparing AS events with exon inclusion/exclusion ≥10% between 791 and 191

treatment (N = 2). Pearson correlations (R values) are shown.

15

791

191

66

A

B C

74

Figure 3.14. Differential host gene expression with 191 and 791 treatment.

(A) Differentially expressed (DE) genes described as cRPKM fold change ≥ 2 or ≤ 0.5 with

compound treatment relative to DMSO treatment (p ≤ 0.05, 11,406 genes, N = 2). (B) Venn

diagram comparing shared DE events between 791 and 191 treatment (N = 2). Orange and blue

indicate up- and downregulated genes, respectively. (C) Fold change distribution of

differentially expressed genes based on compound treatment relative to DMSO treatment within

the RNAseq dataset (p ≤ 0.05, 1,020 genes, N = 2). (D) Venn diagrams comparing DE and AS

(|PSI| ≥ 10%) events with 791 (left) and 191 (right) treatment (N = 2).

A B

C

D

75

six of the differentially expressed genes (three of which three genes were upregulated and

remaining three were downregulated) were common to both compounds (Figure 3.14B).

Furthermore, there was very little overlap in genes that showed altered splicing or differentially

expression (Figure 3.14D). To put these observations into perspective, Martinez et al

demonstrated that T cell activation, a normal cellular signaling process, results in changes in

alternative splicing in approximately 10% of the >10,000 events examined (83). Furthermore,

they also observed very little overlap between alternative spliced and differentially expressed

genes (83).

Together, these results suggest that 191 and 791 do not appreciably alter cellular alternative

splicing or gene expression, but instead, selectively alter the balance HIV-1 RNA splicing and

gene expression. Thus, it seems likely that these compounds do not primarily inhibit HIV-1 by

perturbing alternative splicing, but rather, induce the loss of HIV-1 Rev protein such that the

balance of viral RNAs is altered.

3.10 Preliminary analysis of the effect of the compounds on expression of cellular splicing factors

Given that HIV-1 RNA processing relies on host cell splicing machinery and since splicing

factors can selectively alter RNA splicing, the effect of the compounds on select cellular splicing

factors was examined. The expression of members of the SR protein family of splicing factors,

SRSF3 (SRp20), SRSF5 (SRp40), and SRSF6 (SRp55) was measured from at least three

independent experiments and normalized to either GAPDH or α-tubulin. Bands corresponding to

SRSF5 and SRSF6 were detected using the pan-SR antibody, 1H4, and designated based on their

predicted size. Treatment with the compounds modest changes in the expression of SRSF3 (N =

2-3), relative to DMSO treatment, but other members of the SR family (N = 2-4) were largely

unchanged across the treatments (Figure 3.15). These results suggest that the primary mechanism

of action of these compounds is not mediated by altering splicing but by perturbing the balance

of HIV-1 mRNAs. In contrast, digoxin alters HIV-1 splicing by decreasing the MS RNA

isoforms encoding Rev and has been shown to induce changes in post-translational modifications

of SRSF3 and Tra2β (72). Similarly, another cardiotonic steroid, digitoxin, was shown alter

splicing by depleting the levels of SRSF3 and Tra2β (84). Thus, the effect of 191, 791, 833, and

892 on SR proteins are consistent with the low degree of cellular alternative splicing changes

76

c

Figure 3.15. Compounds have limited effects on expression of cellular splicing factors.

Representative immunoblots showing the effect of the compounds on the expression of SR

proteins relative to GAPDH or α-tubulin expression (N = 2-4). Quantification of mean SRSF3

(SRp20), SRSF5 (SRp40), and SRSF6 (SRp55) protein levels (blot probed for pan-SR proteins

using 1H4 antibody) from multiple blots shown on the right. Error bars indicate SEM.

Concentrations of the compounds were: 892 (15 M), 791 (30 M), 833 (2 M) and 191 (2 M).

77

observed with compound treatment, but do not rule the involvement of signaling pathways in

splicing regulation as a way by which the compounds selectively inhibit HIV-1 RNA processing.

3.11 191 and 791 inhibit HIV-1 BaL replication in primary cells

The ability of the compounds to potently inhibit HIV-1 gene expression in the context of HeLa

cells led me to confirm their activity in the context of HIV-1 BaL replication in peripheral blood

mononuclear cells (PBMCs) from healthy donors. PBMCs were activated for three days prior to

infection with HIV-1 BaL (MOI < 0.01) and treatment with DMSO, 191, or 791. Cell culture

medium from compound-treated cells was sampled every two days to measure the effect of

compound treatment on virus production and cell viability. HIV-1 virus production in PBMCs

infected with HIV-1 in vitro was potently inhibited upon treatment with 191 and 791 in

comparison to the viral growth observed with DMSO alone in at least three independent

experiments using cells from two different donors (representative data shown in Figure 3.16).

Azidothymidine (AZT), one of the first drugs used to treat HIV-1 infection in patients,

completely inhibited virus production, as expected. In fact, treatment with either 191 or 791 was

able to inhibit HIV-1 virus replication similar to AZT up to 4 days post infection. Furthermore,

inhibition of HIV-1 replication with 191 and 791 treatment was dose-dependent with little to no

cytotoxicity observed at concentrations below 4 M (preliminary cell viability data, Figure 3.17).

Therefore, the compounds inhibited HIV-1 replication in a mixed cell population even under in

vitro HIV infection conditions where cell infection rates are substantially higher than in HIV+

patients. Furthermore, 191 and 791 maintain their inhibitory activity in primary cells against

replication-competent HIV-1 at similar or lower concentrations than needed in HeLa cells,

suggesting that these compounds are active at low μM concentrations in a physiologically

relevant context.

78

Figure 3.16. 191 and 791 inhibit HIV-1 replication in PBMCs.

Representative experiment from a single donor showing HIV-1 BaL virus replication over a

period of eight days post-infection (p.i.,) as measured by p24 antigen ELISA (N = 4, 2 donors).

PBMCs were infected with HIV-1 BaL (MOI < 0.01) and treated on days 0 and 4 post infection

with.DMSO, AZT (3.74 M), or 791 and 191 at the concentrations indicated. Uninfected control

PBMCs were similarly treated with DMSO on days 0 and 4. Error bars indicate standard error of

the mean (SEM) of replicate wells from an independent experiment.

79

Figure 3.17. 191 and 791 inhibit HIV-1 replication in PBMCs in a dose-dependent manner.

The effect of increasing concentrations of the compounds on HIV-1 BaL virion production in

PBMCs. Culture supernatant was measured by p24 antigen ELISA and expressed relative to p24

Gag levels with DMSO-treatment (N ≥ 3 for 0-3 M of 191 and 0-3.8 M of 791, N = 1-2 for

rest, 2 donors, * = p ≤ 0.05, ** = p ≤ 0.01, and *** = p ≤ 0.001). The effect of the compounds on

cell viability was measured by trypan blue exclusion as a percentage of total cells and expressed

relative to percent cell viability with DMSO-treatment (preliminary data; N = 2 for for 0-3 M of

191, N = 1 for rest, 1 donor). Error bars indicate standard error of the mean (SEM).

A

B

80

4 Discussion

Continued success in combating HIV infection globally relies on discovery of novel therapeutic

strategies against previously untargeted avenues of the HIV lifecycle. Current treatment options

for HIV-1 infection primarily target the activities of viral enzymes reverse transcriptase,

integrase and protease. Although this is a great strategy to specifically inhibit the HIV, viral

genetic diversity due to high viral replication rates and reverse transcriptase mutation rates,

means that there is a greater risk of developing drug resistant viruses. In contrast, novel

therapeutic strategies that exploit specific host-virus interactions without perturbing normal

cellular processes, would be more effective at preventing viral drug resistance across various

HIV subtypes. The requirement of HIV-1 for the host cellular splicing machinery for efficient

expression of viral proteins provides many opportunities for identifying novel therapeutic targets.

In fact, recent studies by Campos et al (2015) has validated this approach (73). The authors

showed that treatment of infected PBMCs with ABX464, a small molecule that interacts with the

cellular cap binding complex (CBC) and specifically prevents Rev-mediated RNA export, was

able to sustainably suppress viral load without selecting for resistance mutations (73). More

importantly, studies revealed a dramatic rebound of viral load within a week in HIV-infected

humanized mouse models after cessation of HAART treatment, while only a slight rebound was

observed by 52 days after cessation of ABX464 treatment alone (73). These findings suggest that

targeting cellular components required for efficient HIV replication is a promising strategy that

can complement existing anti-viral treatments.

Since HIV-1 requires strict regulation and processing of its RNA for efficient replication and

expression of viral proteins, our lab focused on perturbing this stage of the viral lifecycle using

small molecules. From a screen of compounds shown to modulate splicing of an SMN2 mini-

gene reporter (collaboration with Peter Stoilov), we identified four compounds that potently

inhibited HIV-1 gene expression. Although the four compounds are structurally very dissimilar,

each compound inhibited HIV-1 p24 Gag expression by 80-90% relative to DMSO-treated cells

(Figure 3.1). In addition, these four compounds are very different from previously characterized

HIV-1 inhibitors, digoxin (72), 8-azaguanine, and 5350150 – herein referred to as 8-Aza and

150, respectively. Digoxin, a cardiatonic steroid, inhibited HIV-1 by perturbing viral RNA

splicing in two ways. First, digoxin selectively decreased the levels of Rev1/2 mRNA by 73%

relative to the levels of mRev1/2 RNA observed with DMSO treatment, thereby dramatically

81

decreasing the levels of Rev present in the cytoplasm (72). Secondly, digoxin resulted in

oversplicing of HIV-1 RNAs, such that HIV-1 MS RNA abundance was greatly increased and

incompletely spliced RNA abundance was decreased (72). In this way, digoxin perturbs the

balance of HIV-1 RNAs and thus viral gene expression. The loss of both Rev protein and

incompletely spliced viral mRNAs severely impairs the export of viral genomic RNA and the

production of viral structural proteins. 8-Aza and 150, on the other hand, inhibited HIV-1 gene

expression by perturbing Rev-mediated viral RNA transport without affecting Rev expression

directly (71). Since 191, 791, 833, and 892 are structural dissimilar from digoxin, 8-Aza and 150,

there may be multiple ways to perturb HIV-1 replication via small molecule intervention. Indeed,

this appears to be the case, as the four compounds presented here inhibit HIV-1 gene expression

in a manner that results in the depletion of both Rev and Tat, in contrast to the previously

characterized HIV-1 RNA processing inhibitors.

191, 791, 833, and 892 inhibited HIV-1 in a dose-dependent manner at concentrations in the low

micromolar range in multiple contexts. Initial screening and characterization of the effect of the

compounds on HIV-1 gene expression was done using HeLa B2 cells (Figures 3.1 and 3.2), yet

191, 791, and 833 were also active at similar, if not identical, concentrations in the context of

CD4+ SupT1 cells (Raymond W. Wong, unpublished). Furthermore, I have shown that both 191

and 791 inhibit HIV-1 BaL replication in primary peripheral blood mononuclear cells (PBMCs)

at concentrations at or below those tested in HeLa B2 cells with little to no toxicity (Figures 3.16

and 3.17). To test the long-term effects of the compounds on cell growth, HeLa B2 cells were

incubated either with the compounds or with DMSO for a period of four days. Although the

compounds had a significant effect on cellular metabolism with prolonged treatment (Figure

3.9), 191 and 791 were much better tolerated by the cells than the remaining two compounds,

indicated that 191 and 791 would be less likely to induce adverse effects in vivo. Consistent with

this theory, both 191 and 791 were able to inhibit HIV-1 replication in PBMCs over a period of

six days (Figure 3.17). These results confirm activity of the compounds in a more

physiologically relevant context and suggest that small molecules can effectively be used to

inhibit HIV-1 replication as a novel strategy.

Analysis of HIV-1 protein expression following compound treatment, revealed that compound

treatment resulted in the loss of both early (Rev, Tat) and late (Gag, Env) viral proteins. The

compounds decreased the expression of HIV-1 structural proteins (Figure 3.3) that are dependent

82

on Rev function for their expression, as well as key viral regulatory proteins that are generated

early in HIV-1 replication (Figure 3.4). Inhibition of cytoplasmic localization of Rev by

Leptomycin B results in a similar reduction in cytoplasmic accumulation of HIV-1 US and SS

RNAs without affecting MS RNA accumulation (85)Alan Cochrane, unpublished). Thus, the loss

of the late proteins and p14 Tat can be explained by the decrease in US and SS RNA abundance

(Figures 3.5 and 3.7) given the requirement of Rev for the export and translation of these RNAs.

This was confirmed with inhibition of cytoplasmic accumulation of HIV-1 US RNA upon

compound treatment (Figure 3.7). The abundance of HIV-1 MS RNA, however, does not

correlate with the loss of Rev and p16 Tat. Furthermore, there was no significant variation in the

levels of splice variants within this class of RNAs with either 191 or 791 treatment (Figure 3.6),

suggesting that the compounds did not induce preferential selection of a viral splice sites. 892

and 833 treatment induced a few changes in the levels of splice variants encoding Rev, Nef and

Tat (Figure 3.6), however, these changes are much less profound than the changes in splice site

selection induced by digoxin (72). Together, these results suggest that perturbation of the balance

of HIV-1 splicing is a consequence of decreased Rev activity in exporting incompletely spliced

viral RNAs.

To verify that the compounds did not significantly or globally effect the splicing of endogenous

genes, the effect of the compounds on cellular splicing factors and either a panel (73 events) or a

library (>9,000) of alternatively spliced events was examined. Preliminary studies looking at the

effect of the compounds on the expression of endogenous cellular splicing factors revealed only

modest changes in the levels of SRSF3 (SRp20) and little to no changes in SRSF5 (SRp40) and

SRSF6 (SRp55) levels in the presence of the compounds relative to DMSO treatment (Figure

3.15). This is consistent with the minimal effects on global mRNA splicing observed (Figures

3.12 and 3.13). Since the activity of SR proteins is dependent on their phosphorylation status,

analysis of posttranslational modifications of these splicing factors may be more informative of

perturbations of cellular signaling events involved in RNA processing in the presence of the

compounds. Overall, the compounds had limited effects on global cellular alternative splicing

events (Figure 3.12) as there was a high correlation between compound-treated and DMSO-

treated samples (R = 0.94-0.99) and a similar conclusion was drawn when specific alternative

splicing events were examined. In contrast, 892 and 833 treatment resulted in changes of 30-50%

in the levels of HIV-1 MS RNA variants relative to DMSO treatment (Figure 3.6). This suggests

83

that the inhibitory effect of the compounds is selective to HIV-1. Consistent with this suggestion,

the compounds alter the splicing profile of HIV-1 by enhancing the expression of spliced viral

RNA and reducing the expression of incompletely spliced viral RNAs, without having any effect

on cellular splicing.

Since there was a disconnect between the levels of HIV-1 MS RNA and the expression of viral

regulatory factors, the compounds likely inhibit HIV-1 gene expression by perturbing mRNA

export, protein synthesis or protein stability. I have shown that the compounds do not effect

cellular protein synthesis (Figure 3.8) even though they induce significant depletion of viral

protein expression. Thus, these compounds selectively decrease HIV-1 protein expression

without perturbing global protein synthesis. Studies examining the immediate effects of the

compounds on the stability of HIV-1 regulatory proteins revealed that Tat degrades quite rapidly

(half-life approximately 8 hours) but the compounds do not directly alter the decay of Tat

relative to DMSO treatment (Figure 3.10). Further analysis of the effect of compound treatment

on the stability of viral proteins at a posttranslational level, revealed that expression of both p16

and p14 Tat could be rescued with proteasome inhibition after 24 hour treatment with the

compounds. In contrast, proteasome inhibition with MG132 caused a decrease in the levels of

HIV-1 p24 Gag. Previously, Schubert et al (86) demonstrated that MG132-induced proteasomal

inhibition severely decreases the budding, maturation, and infectivity of HIV-1 by reducing the

level of free ubiquitin in HIV-1-infected cells and thereby prevented mono-ubiquitination of

p6gag, which is important for virus assembly and release (86). Thus, decreased p24 Gag levels

with MG132 treatment is consistent with the requirement of functional proteasome for

proteolytic processing of HIV-1 Gag (86). Since, proteasome inhibition prevented the

compound-induced loss of p14 Tat (encoded on SS RNA), this suggests that Rev-mediated

export of incompletely spliced viral RNAs did indeed occur when viral regulatory proteins were

prevented from degradation. Therefore, the compounds most likely inhibit HIV-1 gene

expression by affecting Rev and Tat protein accumulation, which leads to perturbation of viral

US and SS RNA accumulation (see Figure 4.1 for proposed model of inhibition).

Examination of the effect of the compounds on differential alternative splicing may allow us to

implicate cellular signaling cascades involved in regulation of splicing and thereby identify

putative cellular factors that may be involved in the destabilization of the viral regulatory

proteins. The compounds induced limited changes in cellular alternative splicing events with

84

d

Figure 4.1 Proposed model for how the compounds inhibit HIV-1 gene expression.

Following transcription of the HIV-1 provirus, RNA processing (5’ capping, splicing, and 3’

polyadenylation) leads to the generation of MS, SS, and US RNAs. In the early phase of HIV-1

gene expression, only the MS RNAs are exported (via the TAP/NXF1 export pathway). The US

and SS RNAs, which require Rev for export, remain in the nucleus where they are degraded. In

the cytoplasm, translation of MS RNA results in the production of viral regulatory proteins Rev

and Tat (p16 isoform). The stability of Rev and Tat may be influenced by cellular chaperones

that promote protein function, or destabilizing factors that promote protein degradation. Our

studies suggest that these compounds lead to the loss of the viral regulatory proteins by

inhibiting the activity of chaperone proteins or by enhancing the effect of destabilizing factors

and subsequently inhibit the export and translation of Rev-dependent US and SS RNAs, and

virus replication.

85

RNAseq studies revealing that <1% of > 9,800 measured alternatively spliced events were

altered by 191 or 791, relative to DMSO. In contrast, previous studies have demonstrated that T

cell activation altered ~10% of >10,000 alternatively spliced events (83). T cell activation offers

a great comparison for assessing alternative splicing changes since CD4+ T cells are the natural

hosts for HIV-1 and the compounds may affect similar signaling cascades to inhibit HIV-1 gene

expression. Thus, a cellular process involved in immune response alters splicing more than these

compounds, suggesting that 191, 791, 833, and 892 do not primarily inhibit HIV-1 RNA

processing by altering splicing. Although the compounds did not significantly affect cellular

splicing events in general, the splicing of three genes, fgfr1op2, macf1, and gm130/ golga2, were

altered by all four compounds, while the splicing of an additional gene, nap1l1, was altered by

all compounds, with the exception of 791 (as determined by RT-PCR). Furthermore, the RNAseq

approach showed that splicing of fgfr1op2 was also altered by 791 (PSI = -20, p = 0.0004, N =

2). Given that only a few cellular alternatively spliced events were appreciably changed among

the total number of detected events, any changes that are common among the compounds would

be predicted to be involved in their shared activity as inhibitors of HIV-1 gene expression.

The macf1, gm130/golga2, and fgfr1op2 genes encode microtubule-actin crosslinking factor 1

(MACF1), Golgin A2, and fibroblast growth factor receptor 1 oncogene partner 2 (FGFR1OP2),

respectively. MACF1 is a large protein that form bridges between different cytoskeletal elements

and has been shown to regulate microtubule dynamics by GSK3 signaling in skin stem cells and

developing neurons (87, 88). These studies found that GSK3 binds and phosphorylates MACF1,

inhibiting MACF1’s ability to bind microtubules (87, 88). Thus, MACF1 appears to be a

downstream target of GSK3 signaling and further suggests that the compounds may impact the

GSK3/Wnt signaling pathway. Similarly, Golgin A2 appears to be involved in cytoskeletal

signaling pathways that regulate microtubule dynamics, as well as roles in the maintenance of

the Golgi apparatus and secretory pathway (89). Golgin A2 is phosphorylated by cyclin

dependent kinase 1 (Cdk1)-cyclin B and cyclin dependent kinase 5 (Cdk5) (90, 91). In turn,

Golgin A2 binds and promotes the auto-phosphorylation of yeast Ste20-like kinases YST1

(human homologue is Stk25) and MST4, implicating the involvement of Golgin A2 in the

MAPK signaling pathway (92). In contrast to MACF1 and Golgin A2, the function of

FGFR1OP2 is unknown, but is predicted to be translated into an evolutionarily conserved protein

containing coiled-coil domains and may also play a role in related FGFR1 signaling pathways

86

(93). The nap1l1 gene encodes for the histone chaperone, Nap1. Given that this gene is

alternatively spliced by three of the four compounds and has previously been shown to interact

with HIV-1 Rev and Tat and increase their activity (94-96), it can be predicted that perturbation

of alternative splicing or expression of Nap1 would affect HIV-1 gene expression. It has

previously been shown that siRNA knockdown of Nap1 altered HIV-1 Rev aggregation,

localization, import, and function (94). Hence, it would be worthwhile to determine whether the

compounds alter NAP1 function or perturb the Nap1-Rev interactions, thereby inhibiting Rev-

mediated export of viral RNAs. A model of inhibition can be proposed, whereby compound

treatment leads to the loss of Nap1 (depicted as chaperone protein in Figure 4.1), which in turn

leads to aggregation of HIV-1 Rev and their subsequent proteasomal degradation.

Furthermore, there was very little overlap between the alternatively spliced and differentially

expressed genes for each compound (Figures 3.15). This is consistent with mounting evidence

from genome-wide studies in support of a paradigm shift in the understanding that most genes

often undergo alternative splicing changes in protein isoforms largely without accompanying

changes in overall transcript levels (97, 98). Only a few genes (84 for 791 and 53 for 191) were

differentially expressed among the 11,406 genes examined upon compound treatment. In fact,

most of these differentially expressed genes were upregulated with 791 treatment while a

roughly equal portion of genes were upregulated or downregulated with 191 treatment (Figure

3.15). Of the few genes that were differentially expressed, trib3, the gene encoding Tribbles

pseudokinase 3 (TRIB3) was upregulated by over 9-fold with 791 treatment. TRIB3 is a putative

protein kinase that is induced by transcription factor NFκB, and involved in numerous cellular

processes (99). Some of its roles include, inhibiting the activation of Akt, regulating activation of

MAP kinases, and inhibiting APOBEC3A editing of nuclear DNA (99-101). Since TRIB3 plays

a role in regulating the PI3K/Akt signaling pathway and there is a dramatic difference in gene

expression with 791 treatment, it would be interesting to further examine the involvement of

TRIB3 during HIV-1 replication. Thus, the modest gene expression changes with 191 and 791

treatment and the few shared differentially expressed genes suggests that these compounds are

selective inhibitors of HIV-1 gene expression that have little effect on normal cellular processes.

Taken together, these results indicate that the compounds 192, 791, 833, and 892 inhibit HIV-1

gene expression by inducing the loss of key early viral regulatory proteins, which in turn leads to

a perturbation in the balance of HIV-1 RNAs and subsequent loss of viral structural proteins. The

87

molecular mechanism by which this occurs remains to be determined, but nonetheless, these

compounds offer another strategy to the list of possible ways to target HIV-1 RNA processing. In

addition to be structurally dissimilar to digoxin, 8-Aza, and 150, these four compounds are also

structurally distinct from NB-506, a splicing inhibitor that specifically blocks the kinase activity

of DNA topoisomerase I (59), and ABX464, an inhibitor of Rev-mediated RNA export (73). The

fact that small molecular compounds with distinct structures can effect gene expression by

modulating pre-mRNA splicing (NB-506, digoxin), mRNA transport (ABX464, 8-aza, 150), and

protein stability (191, 791, 833, and 892) validates using small molecules as drugs to target

specific cellular proteins implicated in disease or viral infections, which require the cellular

splicing machinery to persist. Furthermore, the similarities between the effects of these

compounds and ABX464 on both HIV and cellular splicing events, suggest that these

compounds may be able to inhibit HIV replication in vivo.

There are many challenges in translating the effect of small molecules in vitro to their

application as novel drugs in humans. The four compounds described here may not be directly

applicable in patients, as the systemic effects and therapeutic dose ranges remain unknown,

however, confirmation of the activity of the compounds against HIV-1 replication in the context

of primary human cells and in humanized mouse models is the closest to testing the application

of these compounds in physiological condition in the laboratory setting, prior to testing their

efficacy in humans in clinical trials. I have shown that 791 and 191 inhibit HIV-1 BaL (R5-

tropic) replication in peripheral blood mononuclear cells at comparable levels to AZT, one of the

first drugs used to treat HIV+ patients, up to six days post infection with no significant effects on

cell viability (Figures 3.16 and 3.17). Furthermore, initial studies looking at the maximum

tolerated doses of the four compounds in NOD SCID gamma (NSG) mice, were done by Dr.

Liang Ming, a post-doctoral fellow in the lab. NSG mice were injected intraperitoneal (IP) with

892, 791, 833, or 191 and monitored for changes in body weight and behavior for up to two

weeks. No significant changes in body weight or behavior were observed in NSG mice injected

with 892 (36 mg/kg or 300 M, once), 791 (210 mg/kg or 600 M, every two days), or 833 (78

mg/kg or 200 M, once) for one week or 191 (2.1 mg/kg or 6 M, daily) for up to two weeks.

Therefore, these compounds are tolerated in mouse models at 3-100x the IC90 concentrations

observed in HeLa B2 cells. These results are very promising for further testing and development

of these compounds as novel drugs for treatment of HIV-1 infection.

88

4.1 Future Directions

Future studies should address two aspects: 1) elucidating the mechanism of action of these

compounds in vitro and 2) confirming the efficacy of these compounds as therapeutic strategies

in more physiological contexts of HIV-1 infection.

Given that the compounds only induce a small proportion of alternative splicing changes any

changes that are common between the compounds could potentially be important for inhibition

of HIV-1 gene expression. Since all four compounds resulted in differentially splicing of

fgfr1op2, macf1, and gm130/golga2 it would be worthwhile to further examine their sequences

for motif analysis and study their roles in inhibiting viral gene expression using minigene

constructs combined with mutagenesis analysis. Motif discovery tools such as MEME

(http://meme.nbcr.net/meme/), RescueESE or ESE finder may be used to identify direct

regulators of the exons presumed to be co-regulated and the corresponding cis-acting sequences.

A consensus sequence can then be determined and used to identify putative cellular factors that

bind to these genes. These studies would allow us to pinpoint regulators and cellular signaling

cascades involved in inhibition of HIV-1 gene expression. Since analysis of common changes in

cellular alternative splicing suggest a role for NAP1 in 892, 833, and 191-induced inhibition of

HIV-1 gene expression, it would be interesting to determine whether NAP1 expression is altered

with compound treatment.

In parallel to these studies, it would be interesting to determine whether HIV-1 Rev expression

and viral RNA export can be rescued with proteasome inhibition, since the compound-induced

degradation of HIV-1 Tat isoforms, p16 (encoded on MS RNA) and p14 (encoded on SS RNA),

can be reversed with the addition of MG132. This can be assessed by examination of Rev

subcellular localization and abundance of HIV-1 US and SS RNAs Rev activity following

MG132 treatment in the presence of the compounds by immunofluorescence, fluorescent in situ

hybridization and qRT-PCR, as described previously. These studies would allow us to directly

determine whether the ability of Rev to shuttle between the nucleus and cytoplasm is perturbed

with compound treatment. Furthermore, it would be interesting to determine whether transfection

of HIV-1 Rev in trans in HeLa B2 cells can reverse inhibition of HIV-1 gene expression

following compound treatment. Examination of the effect of the compounds in the presence of

wildtype Rev or a mutant Rev incapable of binding HIV-1 RNA (negative control), would tell us

89

if addition of functional Rev could rescue the effect of the compounds on HIV-1 gene

expression, or whether a cellular factor or pathway is involved in the degradation of viral

regulatory proteins. Together, these studies will give insights to how these small molecule induce

destabilization of HIV-1 regulatory proteins, what cellular factors are involved, and whether this

is can be adapted as an effective strategy against HIV-1 replication in vivo.

In addition to mechanistic studies, there should also be focus on the application of these

compounds in more physiologically relevant contexts. I have shown that two of the compounds,

791 and 191, maintain their inhibitory effect on HIV-1 replication in the context of peripheral

blood mononuclear cells (PBMCs), obtained from healthy human donors, at similar or lower

doses than required in HeLa B2 cells without affecting cell viability. Future studies should

confirm whether the remaining two compounds, 892 and 833, are active in PBMCs in the context

of replicating HIV-1. Since HIV is characterized by high genetic diversity, subsequent

experiments should assess whether prolonged treatment with these compounds select for drug

resistant mutations in vitro. In addition, determination of the ability of these compounds to

suppress viral replication of drug-resistant strains, clinical isolates and viruses from different

HIV clades would further strengthen the validity of this strategy to control HIV infection and

complement existing anti-viral therapies.

Finally, to determine whether these compounds can be developed into safe, efficacious, anti-viral

drugs as treatment for HIV-infected individuals, the activity of these compounds should be tested

in humanized mice models. Initial testing of the maximum tolerated doses of the compounds in

NOD SCID gamma (NSG) mice revealed that the compounds are tolerated at 3-100x the IC90

concentrations in these mouse models. Thus, future studies should examine the effect of these

compounds in HIV-infected humanized mouse models (NSG mice transplanted with

haematopoietic progenitor cells isolated from umbilical cord blood) to assess their efficacy under

physiological conditions comparable to those in HIV-infected patients. Determination of the

therapeutic dose ranges and efficacy of these compounds in mouse models allows us to

recommend doses and treatment regimens for phase I clinical trials, the next step towards getting

these compounds out to the market as anti-HIV drugs. Even if these compounds do not progress

to clinical trials in humans, studying the mechanism of action of these compounds in vitro allows

us to identify key cellular factors that can be systematically targeted by rational drug design.

90

4.2 Conclusions

From a screen of small molecular modulators of RNA splicing, we identified four compounds,

191, 791, 833, and 892, that potently inhibited HIV-1 gene expression in vitro in the context of

both HeLa cells and peripheral blood mononuclear cells. Compound treatment resulted in loss of

viral structural and regulatory proteins as well as the abundance of incompletely spliced viral

RNAs, without affecting the abundance of viral MS RNAs or splice site usage within this class.

Furthermore, I have shown that compound treatment did not significantly affect protein synthesis

or cellular alternative splicing, suggesting that the effect of the compounds is selective to HIV-1

RNA processing. Examination of their effect on the stability of viral proteins at a post-

translational level, revealed that the compounds induced destabilization of viral regulatory

proteins Tat and Rev, thereby preventing Rev-mediated export of incompletely spliced viral

RNAs. Thus, destabilization of HIV-1 regulatory proteins appears to be a distinct way by which

these compounds alter the balance of HIV-1 RNA splicing and inhibit HIV-1 gene expression

and replication. The ability to differentially effect RNA processing without perturbing normal

cellular processes validates targeting this stage of the virus lifecycle as a novel therapeutic

strategy that can be developed to complement existing treatment regimens or used as a second

line of defense against drug-resistant HIV strains.

91

References

1. Blencowe BJ. Alternative splicing: new insights from global analyses. Cell. 2006 Jul

14;126(1):37-47.

2. Cowling VH. Regulation of mRNA cap methylation. Biochem J. 2009 Dec 23;425(2):295-

302.

3. Kelemen O, Convertini P, Zhang Z, Wen Y, Shen M, Falaleeva M, et al. Function of

alternative splicing. Gene. 2013 Feb 1;514(1):1-30.

4. Stamm S. Regulation of alternative splicing by reversible protein phosphorylation. J Biol

Chem. 2008 Jan 18;283(3):1223-7.

5. Braunschweig U, Gueroussov S, Plocik AM, Graveley BR, Blencowe BJ. Dynamic integration

of splicing within gene regulatory pathways. Cell. 2013 Mar 14;152(6):1252-69.

6. Proudfoot NJ. Ending the message: poly(A) signals then and now. Genes Dev. 2011 Sep

1;25(17):1770-82.

7. Shatkin AJ, Manley JL. The ends of the affair: capping and polyadenylation. Nat Struct Biol.

2000 Oct;7(10):838-42.

8. Izaurralde E. A novel family of nuclear transport receptors mediates the export of messenger

RNA to the cytoplasm. Eur J Cell Biol. 2002 Nov;81(11):577-84.

9. Erkmann JA, Kutay U. Nuclear export of mRNA: from the site of transcription to the

cytoplasm. Exp Cell Res. 2004 May 15;296(1):12-20.

10. Maquat LE, Hwang J, Sato H, Tang Y. CBP80-promoted mRNP rearrangements during the

pioneer round of translation, nonsense-mediated mRNA decay, and thereafter. Cold Spring

Harb Symp Quant Biol. 2010;75:127-34.

11. Jackson RJ, Hellen CU, Pestova TV. The mechanism of eukaryotic translation initiation and

principles of its regulation. Nat Rev Mol Cell Biol. 2010 Feb;11(2):113-27.

92

12. Sonenberg N, Hinnebusch AG. Regulation of translation initiation in eukaryotes:

mechanisms and biological targets. Cell. 2009 Feb 20;136(4):731-45.

13. Han J, Xiong J, Wang D, Fu XD. Pre-mRNA splicing: where and when in the nucleus.

Trends Cell Biol. 2011 Jun;21(6):336-43.

14. Stamm S, Smith CWJ, Lührmann R. Alternative pre-mRNA splicing. 2012:622.

15. Reed R, Maniatis T. A role for exon sequences and splice-site proximity in splice-site

selection. Cell. 1986 Aug 29;46(5):681-90.

16. Erkelenz S, Mueller WF, Evans MS, Busch A, Schoneweis K, Hertel KJ, et al. Position-

dependent splicing activation and repression by SR and hnRNP proteins rely on common

mechanisms. RNA. 2013 Jan;19(1):96-102.

17. Han N, Li W, Zhang M. The function of the RNA-binding protein hnRNP in cancer

metastasis. J Cancer Res Ther. 2013 Nov;9 Suppl:S129-34.

18. Zhou Z, Fu XD. Regulation of splicing by SR proteins and SR protein-specific kinases.

Chromosoma. 2013 Jun;122(3):191-207.

19. Patel NA, Kaneko S, Apostolatos HS, Bae SS, Watson JE, Davidowitz K, et al. Molecular

and genetic studies imply Akt-mediated signaling promotes protein kinase CbetaII

alternative splicing via phosphorylation of serine/arginine-rich splicing factor SRp40. J Biol

Chem. 2005 Apr 8;280(14):14302-9.

20. Blaustein M, Pelisch F, Tanos T, Munoz MJ, Wengier D, Quadrana L, et al. Concerted

regulation of nuclear and cytoplasmic activities of SR proteins by AKT. Nat Struct Mol

Biol. 2005 Dec;12(12):1037-44.

21. Diehl N, Schaal H. Make yourself at home: viral hijacking of the PI3K/Akt signaling

pathway. Viruses. 2013 Dec 16;5(12):3192-212.

22. Hillebrand F, Erkelenz S, Diehl N, Widera M, Noffke J, Avota E, et al. The PI3K pathway

acting on alternative HIV-1 pre-mRNA splicing. J Gen Virol. 2014 Aug;95(Pt 8):1809-15.

93

23. Heyd F, Lynch KW. Phosphorylation-dependent regulation of PSF by GSK3 controls CD45

alternative splicing. Mol Cell. 2010 Oct 8;40(1):126-37.

24. Lynch KW. Regulation of alternative splicing by signal transduction pathways. Adv Exp

Med Biol. 2007;623:161-74.

25. Matter N, Herrlich P, Konig H. Signal-dependent regulation of splicing via phosphorylation

of Sam68. Nature. 2002 Dec 12;420(6916):691-5.

26. van der Houven van Oordt,W., Diaz-Meco MT, Lozano J, Krainer AR, Moscat J, Caceres JF.

The MKK(3/6)-p38-signaling cascade alters the subcellular distribution of hnRNP A1 and

modulates alternative splicing regulation. J Cell Biol. 2000 Apr 17;149(2):307-16.

27. Tazi J, Bakkour N, Stamm S. Alternative splicing and disease. Biochim Biophys Acta. 2009

Jan;1792(1):14-26.

28. Naryshkin NA, Weetall M, Dakka A, Narasimhan J, Zhao X, Feng Z, et al. Motor neuron

disease. SMN2 splicing modifiers improve motor function and longevity in mice with spinal

muscular atrophy. Science. 2014 Aug 8;345(6197):688-93.

29. Acheson NH. Fundamentals of molecular virology. 2nd ed. Hoboken, NJ: John Wiley &

Sons; 2011.

30. Clavel F, Hance AJ. HIV drug resistance. N Engl J Med. 2004 Mar 4;350(10):1023-35.

31. Little SJ, Holte S, Routy JP, Daar ES, Markowitz M, Collier AC, et al. Antiretroviral-drug

resistance among patients recently infected with HIV. N Engl J Med. 2002 Aug

8;347(6):385-94.

32. Stoltzfus CM. Chapter 1. Regulation of HIV-1 alternative RNA splicing and its role in virus

replication. Adv Virus Res. 2009;74:1-40.

33. O'Reilly MM, McNally MT, Beemon KL. Two strong 5' splice sites and competing,

suboptimal 3' splice sites involved in alternative splicing of human immunodeficiency virus

type 1 RNA. Virology. 1995 Nov 10;213(2):373-85.

94

34. Stoltzfus CM, Madsen JM. Role of viral splicing elements and cellular RNA binding proteins

in regulation of HIV-1 alternative RNA splicing. Curr HIV Res. 2006 Jan;4(1):43-55.

35. Marchand V, Mereau A, Jacquenet S, Thomas D, Mougin A, Gattoni R, et al. A Janus

splicing regulatory element modulates HIV-1 tat and rev mRNA production by coordination

of hnRNP A1 cooperative binding. J Mol Biol. 2002 Nov 1;323(4):629-52.

36. Caputi M, Freund M, Kammler S, Asang C, Schaal H. A bidirectional SF2/ASF- and SRp40-

dependent splicing enhancer regulates human immunodeficiency virus type 1 rev, env, vpu,

and nef gene expression. J Virol. 2004 Jun;78(12):6517-26.

37. Exline CM, Feng Z, Stoltzfus CM. Negative and positive mRNA splicing elements act

competitively to regulate human immunodeficiency virus type 1 vif gene expression. J

Virol. 2008 Apr;82(8):3921-31.

38. Kammler S, Otte M, Hauber I, Kjems J, Hauber J, Schaal H. The strength of the HIV-1 3'

splice sites affects Rev function. Retrovirology. 2006 Dec 4;3:89.

39. Erkelenz S, Hillebrand F, Widera M, Theiss S, Fayyaz A, Degrandi D, et al. Balanced

splicing at the Tat-specific HIV-1 3'ss A3 is critical for HIV-1 replication. Retrovirology.

2015 Mar 28;12(1):29,015-0154-8.

40. Madsen JM, Stoltzfus CM. A suboptimal 5' splice site downstream of HIV-1 splice site A1 is

required for unspliced viral mRNA accumulation and efficient virus replication.

Retrovirology. 2006 Feb 3;3:10.

41. Lund N, Milev MP, Wong R, Sanmuganantham T, Woolaway K, Chabot B, et al.

Differential effects of hnRNP D/AUF1 isoforms on HIV-1 gene expression. Nucleic Acids

Res. 2012 Apr;40(8):3663-75.

42. Platt C, Calimano M, Nemet J, Bubenik J, Cochrane A. Differential Effects of Tra2ss

Isoforms on HIV-1 RNA Processing and Expression. PLoS One. 2015 May

13;10(5):e0125315.

95

43. Wong R, Balachandran A, Mao AY, Dobson W, Gray-Owen S, Cochrane A. Differential

effect of CLK SR Kinases on HIV-1 gene expression: potential novel targets for therapy.

Retrovirology. 2011 Jun 17;8:47,4690-8-47.

44. Taniguchi I, Mabuchi N, Ohno M. HIV-1 Rev protein specifies the viral RNA export

pathway by suppressing TAP/NXF1 recruitment. Nucleic Acids Res. 2014 Jun;42(10):6645-

58.

45. Hernandez-Lopez HR, Graham SV. Alternative splicing in human tumour viruses: a

therapeutic target? Biochem J. 2012 Jul 15;445(2):145-56.

46. Sumanasekera C, Watt DS, Stamm S. Substances that can change alternative splice-site

selection. Biochem Soc Trans. 2008 Jun;36(Pt 3):483-90.

47. Mohseni J, Zabidi-Hussin ZA, Sasongko TH. Histone deacetylase inhibitors as potential

treatment for spinal muscular atrophy. Genet Mol Biol. 2013 Sep;36(3):299-307.

48. Kaida D, Motoyoshi H, Tashiro E, Nojima T, Hagiwara M, Ishigami K, et al. Spliceostatin A

targets SF3b and inhibits both splicing and nuclear retention of pre-mRNA. Nat Chem Biol.

2007 Sep;3(9):576-83.

49. Fan L, Lagisetti C, Edwards CC, Webb TR, Potter PM. Sudemycins, novel small molecule

analogues of FR901464, induce alternative gene splicing. ACS Chem Biol. 2011 Jun

17;6(6):582-9.

50. Chang JG, Hsieh-Li HM, Jong YJ, Wang NM, Tsai CH, Li H. Treatment of spinal muscular

atrophy by sodium butyrate. Proc Natl Acad Sci U S A. 2001 Aug 14;98(17):9808-13.

51. Brichta L, Hofmann Y, Hahnen E, Siebzehnrubl FA, Raschke H, Blumcke I, et al. Valproic

acid increases the SMN2 protein level: a well-known drug as a potential therapy for spinal

muscular atrophy. Hum Mol Genet. 2003 Oct 1;12(19):2481-9.

52. Andreassi C, Angelozzi C, Tiziano FD, Vitali T, De Vincenzi E, Boninsegna A, et al.

Phenylbutyrate increases SMN expression in vitro: relevance for treatment of spinal

muscular atrophy. Eur J Hum Genet. 2004 Jan;12(1):59-65.

96

53. Riessland M, Brichta L, Hahnen E, Wirth B. The benzamide M344, a novel histone

deacetylase inhibitor, significantly increases SMN2 RNA/protein levels in spinal muscular

atrophy cells. Hum Genet. 2006 Aug;120(1):101-10.

54. Hahnen E, Eyupoglu IY, Brichta L, Haastert K, Trankle C, Siebzehnrubl FA, et al. In vitro

and ex vivo evaluation of second-generation histone deacetylase inhibitors for the treatment

of spinal muscular atrophy. J Neurochem. 2006 Jul;98(1):193-202.

55. Rossi F, Labourier E, Forne T, Divita G, Derancourt J, Riou JF, et al. Specific

phosphorylation of SR proteins by mammalian DNA topoisomerase I. Nature. 1996 May

2;381(6577):80-2.

56. Malanga M, Czubaty A, Girstun A, Staron K, Althaus FR. Poly(ADP-ribose) binds to the

splicing factor ASF/SF2 and regulates its phosphorylation by DNA topoisomerase I. J Biol

Chem. 2008 Jul 18;283(29):19991-8.

57. Tazi J, Bakkour N, Soret J, Zekri L, Hazra B, Laine W, et al. Selective inhibition of

topoisomerase I and various steps of spliceosome assembly by diospyrin derivatives. Mol

Pharmacol. 2005 Apr;67(4):1186-94.

58. Ting CY, Hsu CT, Hsu HT, Su JS, Chen TY, Tarn WY, et al. Isodiospyrin as a novel human

DNA topoisomerase I inhibitor. Biochem Pharmacol. 2003 Nov 15;66(10):1981-91.

59. Pilch B, Allemand E, Facompre M, Bailly C, Riou JF, Soret J, et al. Specific inhibition of

serine- and arginine-rich splicing factors phosphorylation, spliceosome assembly, and

splicing by the antitumor drug NB-506. Cancer Res. 2001 Sep 15;61(18):6876-84.

60. Bakkour N, Lin YL, Maire S, Ayadi L, Mahuteau-Betzer F, Nguyen CH, et al. Small-

molecule inhibition of HIV pre-mRNA splicing as a novel antiretroviral therapy to

overcome drug resistance. PLoS Pathog. 2007 Oct 26;3(10):1530-9.

61. Muraki M, Ohkawara B, Hosoya T, Onogi H, Koizumi J, Koizumi T, et al. Manipulation of

alternative splicing by a newly developed inhibitor of Clks. J Biol Chem. 2004 Jun

4;279(23):24246-54.

97

62. Younis I, Berg M, Kaida D, Dittmar K, Wang C, Dreyfuss G. Rapid-response splicing

reporter screens identify differential regulators of constitutive and alternative splicing. Mol

Cell Biol. 2010 Apr;30(7):1718-28.

63. Fedorov O, Huber K, Eisenreich A, Filippakopoulos P, King O, Bullock AN, et al. Specific

CLK inhibitors from a novel chemotype for regulation of alternative splicing. Chem Biol.

2011 Jan 28;18(1):67-76.

64. Debdab M, Carreaux F, Renault S, Soundararajan M, Fedorov O, Filippakopoulos P, et al.

Leucettines, a class of potent inhibitors of cdc2-like kinases and dual specificity, tyrosine

phosphorylation regulated kinases derived from the marine sponge leucettamine B:

modulation of alternative pre-RNA splicing. J Med Chem. 2011 Jun 23;54(12):4172-86.

65. Fukuhara T, Hosoya T, Shimizu S, Sumi K, Oshiro T, Yoshinaka Y, et al. Utilization of host

SR protein kinases and RNA-splicing machinery during viral replication. Proc Natl Acad

Sci U S A. 2006 Jul 25;103(30):11329-33.

66. Karakama Y, Sakamoto N, Itsui Y, Nakagawa M, Tasaka-Fujita M, Nishimura-Sakurai Y, et

al. Inhibition of hepatitis C virus replication by a specific inhibitor of serine-arginine-rich

protein kinase. Antimicrob Agents Chemother. 2010 Aug;54(8):3179-86.

67. Yadav AK, Vashishta V, Joshi N, Taneja P. AR-A 014418 Used against GSK3beta

Downregulates Expression of hnRNPA1 and SF2/ASF Splicing Factors. J Oncol.

2014;2014:695325.

68. Hernandez F, Perez M, Lucas JJ, Mata AM, Bhat R, Avila J. Glycogen synthase kinase-3

plays a crucial role in tau exon 10 splicing and intranuclear distribution of SC35.

Implications for Alzheimer's disease. J Biol Chem. 2004 Jan 30;279(5):3801-6.

69. Novoyatleva T, Heinrich B, Tang Y, Benderska N, Butchbach ME, Lorson CL, et al. Protein

phosphatase 1 binds to the RNA recognition motif of several splicing factors and regulates

alternative pre-mRNA processing. Hum Mol Genet. 2008 Jan 1;17(1):52-70.

70. Chalfant CE, Rathman K, Pinkerman RL, Wood RE, Obeid LM, Ogretmen B, et al. De novo

ceramide regulates the alternative splicing of caspase 9 and Bcl-x in A549 lung

98

adenocarcinoma cells. Dependence on protein phosphatase-1. J Biol Chem. 2002 Apr

12;277(15):12587-95.

71. Wong RW, Balachandran A, Haaland M, Stoilov P, Cochrane A. Characterization of novel

inhibitors of HIV-1 replication that function via alteration of viral RNA processing and rev

function. Nucleic Acids Res. 2013 Nov;41(20):9471-83.

72. Wong RW, Balachandran A, Ostrowski MA, Cochrane A. Digoxin suppresses HIV-1

replication by altering viral RNA processing. PLoS Pathog. 2013 Mar;9(3):e1003241.

73. Campos N, Myburgh R, Garcel A, Vautrin A, Lapasset L, Nadal ES, et al. Long lasting

control of viral rebound with a new drug ABX464 targeting Rev - mediated viral RNA

biogenesis. Retrovirology. 2015 Apr 9;12(1):30,015-0159-3.

74. Zhou X, Vink M, Klaver B, Berkhout B, Das AT. Optimization of the Tet-On system for

regulated gene expression through viral evolution. Gene Ther. 2006 Oct;13(19):1382-90.

75. Das AT, Zhou X, Vink M, Klaver B, Verhoef K, Marzio G, et al. Viral evolution as a tool to

improve the tetracycline-regulated gene expression system. J Biol Chem. 2004 Apr

30;279(18):18776-82.

76. Schmidt EK, Clavarino G, Ceppi M, Pierre P. SUnSET, a nonradioactive method to monitor

protein synthesis. Nat Methods. 2009 Apr;6(4):275-7.

77. Irimia M, Weatheritt RJ, Ellis JD, Parikshak NN, Gonatopoulos-Pournatzis T, Babor M, et al.

A highly conserved program of neuronal microexons is misregulated in autistic brains. Cell.

2014 Dec 18;159(7):1511-23.

78. Dobson-Belaire WN, Rebbapragada A, Malott RJ, Yue FY, Kovacs C, Kaul R, et al.

Neisseria gonorrhoeae effectively blocks HIV-1 replication by eliciting a potent TLR9-

dependent interferon-alpha response from plasmacytoid dendritic cells. Cell Microbiol.

2010 Dec;12(12):1703-17.

79. Corso G, Coletta I, Ombrato R. Murine mPGES-1 3D structure elucidation and inhibitors

binding mode predictions by homology modeling and site-directed mutagenesis. J Chem Inf

Model. 2013 Jul 22;53(7):1804-17.

99

80. Li J, Liu X, Li S, Wang Y, Zhou N, Luo C, et al. Identification of novel small molecules as

inhibitors of hepatitis C virus by structure-based virtual screening. Int J Mol Sci. 2013 Nov

20;14(11):22845-56.

81. Paruch K, Dwyer MP, Alvarez C, Brown C, Chan TY, Doll RJ, et al. Pyrazolo[1,5-

a]pyrimidines as orally available inhibitors of cyclin-dependent kinase 2. Bioorg Med Chem

Lett. 2007 Nov 15;17(22):6220-3.

82. Purcell DF, Martin MA. Alternative splicing of human immunodeficiency virus type 1

mRNA modulates viral protein expression, replication, and infectivity. J Virol. 1993

Nov;67(11):6365-78.

83. Martinez NM, Pan Q, Cole BS, Yarosh CA, Babcock GA, Heyd F, et al. Alternative splicing

networks regulated by signaling in human T cells. RNA. 2012 May;18(5):1029-40.

84. Anderson ES, Lin CH, Xiao X, Stoilov P, Burge CB, Black DL. The cardiotonic steroid

digitoxin regulates alternative splicing through depletion of the splicing factors SRSF3 and

TRA2B. RNA. 2012 May;18(5):1041-9.

85. Wolff B, Sanglier JJ, Wang Y. Leptomycin B is an inhibitor of nuclear export: inhibition of

nucleo-cytoplasmic translocation of the human immunodeficiency virus type 1 (HIV-1) Rev

protein and Rev-dependent mRNA. Chem Biol. 1997 Feb;4(2):139-47.

86. Schubert U, Ott DE, Chertova EN, Welker R, Tessmer U, Princiotta MF, et al. Proteasome

inhibition interferes with gag polyprotein processing, release, and maturation of HIV-1 and

HIV-2. Proc Natl Acad Sci U S A. 2000 Nov 21;97(24):13057-62.

87. Wu X, Shen QT, Oristian DS, Lu CP, Zheng Q, Wang HW, et al. Skin stem cells orchestrate

directional migration by regulating microtubule-ACF7 connections through GSK3beta. Cell.

2011 Feb 4;144(3):341-52.

88. Ka M, Jung EM, Mueller U, Kim WY. MACF1 regulates the migration of pyramidal neurons

via microtubule dynamics and GSK-3 signaling. Dev Biol. 2014 Nov 1;395(1):4-18.

89. Nakamura N. Emerging new roles of GM130, a cis-Golgi matrix protein, in higher order cell

functions. J Pharmacol Sci. 2010;112(3):255-64.

100

90. Lowe M, Rabouille C, Nakamura N, Watson R, Jackman M, Jamsa E, et al. Cdc2 kinase

directly phosphorylates the cis-Golgi matrix protein GM130 and is required for Golgi

fragmentation in mitosis. Cell. 1998 Sep 18;94(6):783-93.

91. Sun KH, de Pablo Y, Vincent F, Johnson EO, Chavers AK, Shah K. Novel genetic tools

reveal Cdk5's major role in Golgi fragmentation in Alzheimer's disease. Mol Biol Cell. 2008

Jul;19(7):3052-69.

92. Preisinger C, Short B, De Corte V, Bruyneel E, Haas A, Kopajtich R, et al. YSK1 is activated

by the Golgi matrix protein GM130 and plays a role in cell migration through its substrate

14-3-3zeta. J Cell Biol. 2004 Mar 29;164(7):1009-20.

93. Grand EK, Grand FH, Chase AJ, Ross FM, Corcoran MM, Oscier DG, et al. Identification of

a novel gene, FGFR1OP2, fused to FGFR1 in 8p11 myeloproliferative syndrome. Genes

Chromosomes Cancer. 2004 May;40(1):78-83.

94. Cochrane A, Murley LL, Gao M, Wong R, Clayton K, Brufatto N, et al. Stable complex

formation between HIV Rev and the nucleosome assembly protein, NAP1, affects Rev

function. Virology. 2009 May 25;388(1):103-11.

95. Vardabasso C, Manganaro L, Lusic M, Marcello A, Giacca M. The histone chaperone protein

Nucleosome Assembly Protein-1 (hNAP-1) binds HIV-1 Tat and promotes viral

transcription. Retrovirology. 2008 Jan 28;5:8,4690-5-8.

96. De Marco A, Dans PD, Knezevich A, Maiuri P, Pantano S, Marcello A. Subcellular

localization of the interaction between the human immunodeficiency virus transactivator Tat

and the nucleosome assembly protein 1. Amino Acids. 2010 May;38(5):1583-93.

97. Giudice J, Xia Z, Wang ET, Scavuzzo MA, Ward AJ, Kalsotra A, et al. Alternative splicing

regulates vesicular trafficking genes in cardiomyocytes during postnatal heart development.

Nat Commun. 2014 Apr 22;5:3603.

98. Martinez NM, Pan Q, Cole BS, Yarosh CA, Babcock GA, Heyd F, et al. Alternative splicing

networks regulated by signaling in human T cells. RNA. 2012 May;18(5):1029-40.

101

99. Kiss-Toth E, Bagstaff SM, Sung HY, Jozsa V, Dempsey C, Caunt JC, et al. Human tribbles,

a protein family controlling mitogen-activated protein kinase cascades. J Biol Chem. 2004

Oct 8;279(41):42703-8.

100. Du K, Herzig S, Kulkarni RN, Montminy M. TRB3: a tribbles homolog that inhibits

Akt/PKB activation by insulin in liver. Science. 2003 Jun 6;300(5625):1574-7.

101. Aynaud MM, Suspene R, Vidalain PO, Mussil B, Guetard D, Tangy F, et al. Human

Tribbles 3 protects nuclear DNA from cytidine deamination by APOBEC3A. J Biol Chem.

2012 Nov 9;287(46):39182-92.

102

Appendices

I. Analysis of cellular alternative splicing by RT-PCR

Table I-1 Effect of 892 treatment on a subset of cellular alternative splicing (AS).

HeLa B2 cells were treated as described previously. RT-PCR and analysis was done by Stoilov

group. For each splicing event, the percent spliced in (PSI) score, the mean change in exon

inclusion with compound treatment and the associated p value (student’s t test) is listed (N = 3).

AS events with |PSI| ≥ 10% are orange. Bolded events are common to multiple compounds.

Summary

Total count of AS events: 70

AS events with P ≤ 0.05: 18

AS events with PSI ≥ 10%: 2

AS events with PSI ≤ -10%: 7

PSI (25) PSI (26) PSI (27) PSI (25) PSI (26) PSI (27)

MACF1_1 62.00 65.00 64.00 76.00 85.00 84.00 18.00 0.004

EIF4A2_1 28.00 23.00 24.00 34.00 38.00 44.00 13.67 0.014

NUMB_2 20.00 15.00 17.00 26.00 26.00 26.00 8.67 0.004

EIF4A2_1 19.00 17.00 18.00 22.00 26.00 31.00 8.33 0.035

ZNF827_1 19.00 22.00 20.00 26.00 27.00 27.00 6.33 0.003

EXOC7_1 20.00 23.00 21.00 27.00 27.00 27.00 5.67 0.003

CAST_1 65.00 69.00 69.00 72.00 73.00 73.00 5.00 0.022

RAN_1 96.00 98.00 100.00 93.00 93.00 94.00 -4.67 0.018

APLP2_1 23.00 23.00 24.00 15.00 18.00 19.00 -6.00 0.009

FIP1L1_1 32.00 34.00 36.00 27.00 27.00 28.00 -6.67 0.005

NAP1L1_1 85.00 85.00 81.00 76.00 75.00 79.00 -7.00 0.018

FGFR1OP2_1 34.00 25.00 28.00 22.00 15.00 15.00 -11.67 0.030

MACF1_5 32.00 30.00 30.00 27.00 15.00 14.00 -12.00 0.047

SEC24B_1 13.00 24.00 29.00 7.00 9.00 8.00 -14.00 0.042

GM130_1 30.00 35.00 34.00 23.00 18.00 15.00 -14.33 0.007

DRCTNNB1A_1 21.00 27.00 24.00 7.00 7.00 6.00 -17.33 0.001

GGCT_1 48.00 61.00 60.00 24.00 24.00 26.00 -31.67 0.002

SMN2_1 94.00 95.00 91.00 39.00 44.00 46.00 -50.33 0.000

TRIM37_1 71.00 76.00 74.00 69.00 71.00 68.00 -4.33 0.063

FAM62B_1 31.00 35.00 36.00 26.00 31.00 29.00 -5.33 0.065

RPS24_1 7.00 8.00 7.00 8.00 13.00 12.00 3.67 0.079

MAP3K7_1 10.00 11.00 11.00 11.00 14.00 14.00 2.33 0.091

MRIP_1 30.00 31.00 30.00 32.00 31.00 31.00 1.00 0.101

NAP1L1_1 85.00 88.00 81.00 76.00 78.00 83.00 -5.67 0.123

DMSO 892PSI P ValueTranscript ID

103


PDCL_1 90.00 90.00 89.00 90.00 91.00 93.00 1.67 0.152

MVK_1 86.00 80.00 64.00 78.00 100.00 100.00 16.00 0.179

SMN2_2 70.00 73.00 71.00 71.00 76.00 77.00 3.33 0.180

SETD5_1 6.00 7.00 5.00 8.00 21.00 N/A 8.50 0.181

MBNL2_1 9.00 15.00 15.00 11.00 30.00 29.00 10.33 0.187

RAI14_1 81.00 89.00 89.00 86.00 95.00 95.00 5.67 0.231

KIF13A_1 23.00 23.00 22.00 22.00 26.00 25.00 1.67 0.252

APP_1 29.00 31.00 31.00 30.00 32.00 34.00 1.67 0.279

MFF_1 76.00 100.00 100.00 77.00 80.00 88.00 -10.33 0.298

TPM1_1 88.00 79.00 77.00 84.00 73.00 67.00 -6.67 0.330

TPM1_1 12.00 21.00 23.00 16.00 27.00 33.00 6.67 0.330

ATP6V0A1_1 77.00 81.00 76.00 81.00 86.00 77.00 3.33 0.331

AGPAT4_1 0.00 13.00 0.00 1.00 0.00 0.00 -4.00 0.409

POLDIP3_1 68.00 64.00 60.00 68.00 67.00 64.00 2.33 0.421

DNM1L_1 20.00 31.00 33.00 24.00 37.00 39.00 5.33 0.438

DNM1L_1 44.00 58.00 58.00 38.00 52.00 53.00 -5.67 0.447

EIF4H_1 17.00 13.00 12.00 17.00 12.00 20.00 2.33 0.450

MVK_1 63.00 54.00 41.00 64.00 74.00 45.00 8.33 0.477

SRPK2_1 16.00 7.00 8.00 14.00 5.00 2.00 -3.33 0.508

CRBN_1 99.00 100.00 100.00 100.00 99.00 99.00 -0.33 0.519

FAM104A_1 14.00 23.00 23.00 15.00 20.00 18.00 -2.33 0.523

NUMB_2 77.00 94.00 88.00 82.00 96.00 95.00 4.67 0.525

AGPAT4_1 97.00 95.00 96.00 96.00 100.00 79.00 -4.33 0.539

GRB10_1 97.00 99.00 100.00 97.00 98.00 99.00 -0.67 0.561

CASP9_1 36.00 45.00 41.00 36.00 47.00 46.00 2.33 0.622

POMT1_1 50.00 41.00 36.00 50.00 37.00 28.00 -4.00 0.626

POMT1_1 93.00 91.00 85.00 95.00 94.00 63.00 -5.67 0.627

SRPK2_1 90.00 95.00 96.00 90.00 97.00 99.00 1.67 0.640

MBD1_1 22.00 0.00 56.00 28.00 15.00 9.00 -8.67 0.641

ADD3_1 42.00 53.00 59.00 42.00 60.00 62.00 3.33 0.701

EXOC7_1 36.00 19.00 20.00 35.00 23.00 25.00 2.67 0.709

CA12_1 11.00 7.00 12.00 15.00 7.00 4.00 -1.33 0.731

MARK3_1 19.00 14.00 13.00 20.00 13.00 16.00 1.00 0.734

MARK3_1 12.00 10.00 10.00 11.00 9.00 11.00 -0.33 0.742

CLSTN1_2 11.00 12.00 12.00 10.00 11.00 13.00 -0.33 0.742

CA12_1 96.00 96.00 98.00 96.00 100.00 95.00 0.33 0.851

APP_1 73.00 79.00 79.00 71.00 77.00 81.00 -0.67 0.859

ZNF827_1 40.00 53.00 46.00 47.00 48.00 46.00 0.67 0.869

CTNND1_1 78.00 97.00 79.00 82.00 76.00 100.00 1.33 0.895

GLK_1 28.00 38.00 37.00 26.00 40.00 39.00 0.67 0.910

GGCT_1 81.00 91.00 89.00 83.00 90.00 89.00 0.33 0.934

CLSTN1_1 59.00 53.00 53.00 61.00 56.00 49.00 0.33 0.938

ERC1_1 35.00 52.00 54.00 36.00 55.00 52.00 0.67 0.941

CRBN_1 94.00 94.00 94.00 95.00 93.00 94.00 0.00 1.000

NPHP3_1 92.00 80.00 84.00 87.00 86.00 83.00 0.00 1.000

Transcript IDDMSO 892

PSI P Value

104






Summary






CAST_1 65.00 69.00 69.00 73.00 73.00 73.00 5.33 0.016

APLP2_1 23.00 23.00 24.00 24.00 25.00 25.00 1.33 0.047

FIP1L1_1 32.00 34.00 36.00 30.00 29.00 30.00 -4.33 0.023

EXOC7_1 20.00 23.00 21.00 16.00 16.00 18.00 -4.67 0.013

DRCTNNB1A_1 21.00 27.00 24.00 16.00 16.00 16.00 -8.00 0.010

FAM62B_1 31.00 35.00 36.00 23.00 26.00 28.00 -8.33 0.017

GM130_1 30.00 35.00 34.00 23.00 23.00 24.00 -9.67 0.003

FGFR1OP2_1 34.00 25.00 28.00 22.00 15.00 17.00 -11.00 0.031

MACF1_5 32.00 30.00 30.00 21.00 14.00 16.00 -13.67 0.003

RPS24_1 7.00 8.00 7.00 10.00 9.00 8.00 1.67 0.067

TRIM37_1 71.00 76.00 74.00 66.00 71.00 70.00 -4.67 0.091

SPAG9_1 26.00 22.00 20.00 21.00 13.00 14.00 -6.67 0.096

POMT1_1 93.00 91.00 85.00 96.00 97.00 93.00 5.67 0.103

CLSTN1_2 11.00 12.00 12.00 11.00 7.00 10.00 -2.33 0.135

KIF13A_1 23.00 23.00 22.00 20.00 22.00 22.00 -1.33 0.148

CLSTN1_1 59.00 53.00 53.00 55.00 44.00 40.00 -8.67 0.152

MVK_1 63.00 54.00 41.00 53.00 84.00 82.00 20.33 0.162

EIF4A2_1 19.00 17.00 18.00 18.00 20.00 22.00 2.00 0.196

EIF4A2_1 28.00 23.00 24.00 25.00 29.00 31.00 3.33 0.226

MACF1_1 62.00 65.00 64.00 63.00 71.00 67.00 3.33 0.249

PDCL_1 90.00 90.00 89.00 90.00 93.00 90.00 1.33 0.275

NUMB_2 77.00 94.00 88.00 89.00 95.00 95.00 6.67 0.282

MVK_1 86.00 80.00 64.00 81.00 100.00 82.00 11.00 0.289

AGPAT4_1 97.00 95.00 96.00 83.00 86.00 100.00 -6.33 0.296

POLDIP3_1 68.00 64.00 60.00 64.00 57.00 60.00 -3.67 0.299

DNM1L_1 20.00 31.00 33.00 24.00 43.00 44.00 9.00 0.305

CA12_1 11.00 7.00 12.00 22.00 12.00 10.00 4.67 0.310


PSI P Value

105


SMN2_2 70.00 73.00 71.00 71.00 75.00 73.00 1.67 0.315

NAP1L1_1 85.00 88.00 81.00 97.00 86.00 85.00 4.67 0.343

RAN_1 96.00 98.00 100.00 93.00 97.00 98.00 -2.00 0.355

SETD5_1 6.00 7.00 5.00 7.00 4.00 3.00 -1.33 0.374

MAP3K7_1 10.00 11.00 11.00 11.00 11.00 11.00 0.33 0.374

EXOC7_1 36.00 19.00 20.00 24.00 15.00 18.00 -6.00 0.382

POMT1_1 50.00 41.00 36.00 57.00 45.00 42.00 5.67 0.409

AGPAT4_1 0.00 13.00 0.00 1.00 0.00 0.00 -4.00 0.409

RAI14_1 81.00 89.00 89.00 84.00 94.00 92.00 3.67 0.417

GGCT_1 81.00 91.00 89.00 86.00 93.00 92.00 3.33 0.425

NAP1L1_1 85.00 85.00 81.00 97.00 86.00 81.00 4.33 0.427

MARK3_1 12.00 10.00 10.00 12.00 7.00 9.00 -1.33 0.451

ZNF827_1 19.00 22.00 20.00 19.00 18.00 21.00 -1.00 0.468

MRIP_1 30.00 31.00 30.00 34.00 30.00 30.00 1.00 0.507

SEC24B_1 13.00 24.00 29.00 11.00 22.00 21.00 -4.00 0.534

MARK3_1 19.00 14.00 13.00 20.00 8.00 10.00 -2.67 0.555

MBD1_1 22.00 0.00 56.00 23.00 15.00 12.00 -9.33 0.604

ZNF827_1 40.00 53.00 46.00 51.00 45.00 50.00 2.33 0.607

GGCT_1 48.00 61.00 60.00 50.00 64.00 65.00 3.33 0.630

MFF_1 76.00 100.00 100.00 89.00 100.00 100.00 4.33 0.648

APP_1 73.00 79.00 79.00 72.00 78.00 77.00 -1.33 0.651

CTNND1_1 78.00 97.00 79.00 86.00 90.00 65.00 -4.33 0.685

CASP9_1 36.00 45.00 41.00 33.00 44.00 41.00 -1.33 0.766

ERC1_1 35.00 52.00 54.00 38.00 54.00 57.00 2.67 0.768

ADD3_1 42.00 53.00 59.00 40.00 61.00 61.00 2.67 0.772

APP_1 29.00 31.00 31.00 29.00 32.00 31.00 0.33 0.778

GRB10_1 97.00 99.00 100.00 97.00 99.00 99.00 -0.33 0.778

TPM1_1 88.00 79.00 77.00 92.00 80.00 77.00 1.67 0.784

TPM1_1 12.00 21.00 23.00 8.00 20.00 23.00 -1.67 0.784

NUMB_2 20.00 15.00 17.00 19.00 14.00 21.00 0.67 0.806

FAM104A_1 14.00 23.00 23.00 14.00 20.00 23.00 -1.00 0.815

NPHP3_1 92.00 80.00 84.00 86.00 87.00 80.00 -1.00 0.821

DNM1L_1 44.00 58.00 58.00 37.00 58.00 59.00 -2.00 0.827

CA12_1 96.00 96.00 98.00 96.00 93.00 100.00 -0.33 0.883

SRPK2_1 16.00 7.00 8.00 23.00 0.00 5.00 -1.00 0.901

SMN2_1 94.00 95.00 91.00 98.00 93.00 90.00 0.33 0.905

MBNL2_1 9.00 15.00 15.00 6.00 19.00 15.00 0.33 0.942

GLK_1 28.00 38.00 37.00 26.00 36.00 40.00 -0.33 0.952

CRBN_1 99.00 100.00 100.00 100.00 100.00 99.00 0.00 1.000

CRBN_1 94.00 94.00 94.00 95.00 94.00 93.00 0.00 1.000

EIF4H_1 17.00 13.00 12.00 14.00 13.00 15.00 0.00 1.000

SRPK2_1 90.00 95.00 96.00 83.00 100.00 98.00 0.00 1.000


PSI P Value

106






Summary






MACF1_1 62.00 65.00 64.00 71.00 79.00 83.00 14.00 0.018

ATP6V0A1_1 77.00 81.00 76.00 83.00 87.00 84.00 6.67 0.027

SRPK2_1 90.00 95.00 96.00 100.00 98.00 100.00 5.67 0.045

PDCL_1 90.00 90.00 89.00 91.00 94.00 95.00 3.67 0.042

CRBN_1 94.00 94.00 94.00 93.00 92.00 91.00 -2.00 0.026

APLP2_1 23.00 23.00 24.00 19.00 21.00 22.00 -2.67 0.047

CLSTN1_2 11.00 12.00 12.00 7.00 8.00 6.00 -4.67 0.002

TRIM37_1 71.00 76.00 74.00 67.00 66.00 68.00 -6.67 0.013

SMN2_2 70.00 73.00 71.00 67.00 62.00 63.00 -7.33 0.014

EIF4A2_1 19.00 17.00 18.00 15.00 7.00 9.00 -7.67 0.036

DRCTNNB1A_1 21.00 27.00 24.00 15.00 15.00 17.00 -8.33 0.011

SRPK2_1 16.00 7.00 8.00 0.00 4.00 0.00 -9.00 0.046

SPAG9_1 26.00 22.00 20.00 17.00 7.00 8.00 -12.00 0.030

GLK_1 28.00 38.00 37.00 21.00 20.00 21.00 -13.67 0.013

FIP1L1_1 32.00 34.00 36.00 26.00 16.00 16.00 -14.67 0.014

NAP1L1_1 85.00 88.00 81.00 62.00 68.00 77.00 -15.67 0.031

CLSTN1_1 59.00 53.00 53.00 47.00 32.00 35.00 -17.00 0.027

NAP1L1_1 85.00 85.00 81.00 64.00 55.00 77.00 -18.33 0.048

MACF1_5 32.00 30.00 30.00 24.00 7.00 6.00 -18.33 0.036

GM130_1 30.00 35.00 34.00 20.00 14.00 10.00 -18.33 0.005

SEC24B_1 13.00 24.00 29.00 8.00 1.00 1.00 -18.67 0.024

FGFR1OP2_1 34.00 25.00 28.00 20.00 1.00 4.00 -20.67 0.033

MARK3_1 12.00 10.00 10.00 9.00 3.00 4.00 -5.33 0.054

EIF4H_1 17.00 13.00 12.00 11.00 7.00 9.00 -5.00 0.059

EIF4A2_1 28.00 23.00 24.00 22.00 9.00 12.00 -10.67 0.065

MRIP_1 30.00 31.00 30.00 29.00 21.00 22.00 -6.33 0.067

MARK3_1 19.00 14.00 13.00 13.00 3.00 3.00 -9.00 0.078


PSI P Value

107


POLDIP3_1 68.00 64.00 60.00 61.00 42.00 38.00 -17.00 0.085

MAP3K7_1 10.00 11.00 11.00 11.00 15.00 14.00 2.67 0.099

EXOC7_1 20.00 23.00 21.00 21.00 14.00 12.00 -5.67 0.119

SETD5_1 6.00 7.00 5.00 6.00 1.00 1.00 -3.33 0.132

CAST_1 65.00 69.00 69.00 66.00 62.00 65.00 -3.33 0.137

FAM62B_1 31.00 35.00 36.00 26.00 33.00 29.00 -4.67 0.140

ERC1_1 35.00 52.00 54.00 36.00 35.00 37.00 -11.00 0.143

MBNL2_1 9.00 15.00 15.00 11.00 41.00 39.00 17.33 0.154

NUMB_2 20.00 15.00 17.00 18.00 23.00 22.00 3.67 0.157

RPS24_1 7.00 8.00 7.00 7.00 13.00 11.00 3.00 0.170

NPHP3_1 92.00 80.00 84.00 83.00 76.00 77.00 -6.67 0.183

SMN2_1 94.00 95.00 91.00 94.00 97.00 96.00 2.33 0.193

MVK_1 86.00 80.00 64.00 77.00 100.00 100.00 15.67 0.196

MVK_1 63.00 54.00 41.00 68.00 53.00 87.00 16.67 0.228

RAN_1 96.00 98.00 100.00 94.00 97.00 97.00 -2.00 0.261

FAM104A_1 14.00 23.00 23.00 12.00 13.00 20.00 -5.00 0.271

DNM1L_1 20.00 31.00 33.00 26.00 39.00 42.00 7.67 0.294

MFF_1 76.00 100.00 100.00 69.00 85.00 87.00 -11.67 0.301

CA12_1 11.00 7.00 12.00 11.00 7.00 4.00 -2.67 0.353

AGPAT4_1 97.00 95.00 96.00 81.00 100.00 92.00 -5.00 0.418

APP_1 29.00 31.00 31.00 30.00 30.00 29.00 -0.67 0.422

GGCT_1 81.00 91.00 89.00 87.00 92.00 91.00 3.00 0.429

NUMB_2 77.00 94.00 88.00 82.00 99.00 97.00 6.33 0.436

RAI14_1 81.00 89.00 89.00 87.00 89.00 90.00 2.33 0.453

DNM1L_1 44.00 58.00 58.00 43.00 51.00 53.00 -4.33 0.481

AGPAT4_1 0.00 13.00 0.00 3.00 0.00 0.00 -3.33 0.495

KIF13A_1 23.00 23.00 22.00 23.00 22.00 22.00 -0.33 0.519

GRB10_1 97.00 99.00 100.00 99.00 99.00 100.00 0.67 0.519

POMT1_1 93.00 91.00 85.00 95.00 93.00 51.00 -10.00 0.530

CTNND1_1 78.00 97.00 79.00 86.00 N/A 70.00 -6.67 0.551

ADD3_1 42.00 53.00 59.00 41.00 62.00 64.00 4.33 0.651

POMT1_1 50.00 41.00 36.00 59.00 52.00 30.00 4.67 0.654

EXOC7_1 36.00 19.00 20.00 32.00 16.00 16.00 -3.67 0.657

CA12_1 96.00 96.00 98.00 97.00 100.00 95.00 0.67 0.698

CASP9_1 36.00 45.00 41.00 37.00 44.00 37.00 -1.33 0.722

APP_1 73.00 79.00 79.00 73.00 78.00 78.00 -0.67 0.811

TPM1_1 88.00 79.00 77.00 88.00 80.00 79.00 1.00 0.832

TPM1_1 12.00 21.00 23.00 12.00 20.00 21.00 -1.00 0.832

MBD1_1 22.00 0.00 56.00 17.00 37.00 14.00 -3.33 0.861

GGCT_1 48.00 61.00 60.00 49.00 59.00 60.00 -0.33 0.954

CRBN_1 99.00 100.00 100.00 100.00 100.00 99.00 0.00 1.000

ZNF827_1 19.00 22.00 20.00 23.00 14.00 24.00 0.00 1.000


PSI P Value

108






Summary






MACF1_1 62.00 65.00 64.00 67.00 73.00 69.00 6.00 0.038

AGPAT4_1 97.00 95.00 96.00 100.00 100.00 100.00 4.00 0.002

SETD5_1 6.00 7.00 5.00 2.00 1.00 0.00 -5.00 0.004

CAST_1 65.00 69.00 69.00 64.00 61.00 58.00 -6.67 0.038

MARK3_1 12.00 10.00 10.00 6.00 4.00 2.00 -6.67 0.007

MRIP_1 30.00 31.00 30.00 25.00 22.00 17.00 -9.00 0.019

MARK3_1 19.00 14.00 13.00 8.00 4.00 4.00 -10.00 0.012

SPAG9_1 26.00 22.00 20.00 16.00 12.00 6.00 -11.33 0.029

FAM104A_1 14.00 23.00 23.00 10.00 8.00 7.00 -11.67 0.020

TRIM37_1 71.00 76.00 74.00 63.00 65.00 58.00 -11.67 0.010

GM130_1 30.00 35.00 34.00 20.00 18.00 23.00 -12.67 0.004

GLK_1 28.00 38.00 37.00 24.00 19.00 19.00 -13.67 0.019

SMN2_2 70.00 73.00 71.00 58.00 57.00 57.00 -14.00 0.000

MACF1_5 32.00 30.00 30.00 22.00 19.00 8.00 -14.33 0.029

CLSTN1_1 59.00 53.00 53.00 43.00 42.00 35.00 -15.00 0.010

EIF4A2_1 19.00 17.00 18.00 2.00 2.00 4.00 -15.33 0.000

NAP1L1_1 85.00 88.00 81.00 65.00 71.00 N/A -16.67 0.017

NAP1L1_1 85.00 85.00 81.00 65.00 68.00 N/A -17.17 0.004

SEC24B_1 13.00 24.00 29.00 9.00 1.00 0.00 -18.67 0.028

FIP1L1_1 32.00 34.00 36.00 20.00 12.00 11.00 -19.67 0.003

EIF4A2_1 28.00 23.00 24.00 2.00 3.00 5.00 -21.67 0.000

ERC1_1 35.00 52.00 54.00 29.00 24.00 23.00 -21.67 0.026

CASP9_1 36.00 45.00 41.00 30.00 16.00 7.00 -23.00 0.033

FGFR1OP2_1 34.00 25.00 28.00 9.00 1.00 2.00 -25.00 0.002

POLDIP3_1 68.00 64.00 60.00 42.00 30.00 25.00 -31.67 0.005

KIF13A_1 23.00 23.00 22.00 21.00 14.00 12.00 -7.00 0.064

RAI14_1 81.00 89.00 89.00 79.00 76.00 64.00 -13.33 0.066


PSI P Value

109


RAN_1 96.00 98.00 100.00 96.00 93.00 91.00 -4.67 0.066

MAP3K7_1 10.00 11.00 11.00 10.00 8.00 7.00 -2.33 0.069

MBNL2_1 9.00 15.00 15.00 16.00 32.00 28.00 12.33 0.077

CA12_1 11.00 7.00 12.00 8.00 4.00 0.00 -6.00 0.096

CA12_1 96.00 96.00 98.00 90.00 96.00 88.00 -5.33 0.099

MVK_1 86.00 80.00 64.00 83.00 100.00 100.00 17.67 0.111

GGCT_1 81.00 91.00 89.00 81.00 82.00 78.00 -6.67 0.112

NUMB_2 77.00 94.00 88.00 94.00 97.00 100.00 10.67 0.113

GGCT_1 48.00 61.00 60.00 46.00 52.00 43.00 -9.33 0.132

APLP2_1 23.00 23.00 24.00 21.00 21.00 13.00 -5.00 0.136

CLSTN1_2 11.00 12.00 12.00 11.00 4.00 9.00 -3.67 0.157

PDCL_1 90.00 90.00 89.00 89.00 96.00 100.00 5.33 0.174

EXOC7_1 20.00 23.00 21.00 23.00 9.00 2.00 -10.00 0.184

SMN2_1 94.00 95.00 91.00 94.00 98.00 96.00 2.67 0.185

SRPK2_1 16.00 7.00 8.00 9.00 4.00 1.00 -5.67 0.199

APP_1 73.00 79.00 79.00 70.00 76.00 73.00 -4.00 0.205

DRCTNNB1A_1 21.00 27.00 24.00 17.00 0.00 24.00 -10.33 0.232

FAM62B_1 31.00 35.00 36.00 24.00 32.00 33.00 -4.33 0.251

ZNF827_1 40.00 53.00 46.00 26.00 7.00 54.00 -17.33 0.288

DNM1L_1 20.00 31.00 33.00 33.00 33.00 32.00 4.67 0.314

RPS24_1 7.00 8.00 7.00 10.00 13.00 6.00 2.33 0.320

ZNF827_1 19.00 22.00 20.00 23.00 15.00 9.00 -4.67 0.324

APP_1 29.00 31.00 31.00 30.00 30.00 27.00 -1.33 0.329

NUMB_2 20.00 15.00 17.00 20.00 16.00 23.00 2.33 0.403

CRBN_1 94.00 94.00 94.00 91.00 90.00 96.00 -1.67 0.420

MBD1_1 22.00 0.00 56.00 12.00 0.00 N/A -20.00 0.421

SRPK2_1 90.00 95.00 96.00 91.00 98.00 99.00 2.33 0.497

CRBN_1 99.00 100.00 100.00 99.00 99.00 100.00 -0.33 0.519

GRB10_1 97.00 99.00 100.00 99.00 99.00 100.00 0.67 0.519

EIF4H_1 17.00 13.00 12.00 12.00 11.00 15.00 -1.33 0.530

POMT1_1 50.00 41.00 36.00 48.00 37.00 28.00 -4.67 0.546

CTNND1_1 78.00 97.00 79.00 86.00 94.00 N/A 5.33 0.575

DNM1L_1 44.00 58.00 58.00 51.00 50.00 51.00 -2.67 0.599

AGPAT4_1 0.00 13.00 0.00 0.00 32.00 0.00 6.33 0.612

POMT1_1 93.00 91.00 85.00 95.00 94.00 63.00 -5.67 0.627

ATP6V0A1_1 77.00 81.00 76.00 81.00 80.00 68.00 -1.67 0.727

NPHP3_1 92.00 80.00 84.00 86.00 81.00 85.00 -1.33 0.746

TPM1_1 88.00 79.00 77.00 85.00 76.00 88.00 1.67 0.753

TPM1_1 12.00 21.00 23.00 15.00 24.00 12.00 -1.67 0.753

ADD3_1 42.00 53.00 59.00 41.00 56.00 51.00 -2.00 0.779

MFF_1 76.00 100.00 100.00 87.00 94.00 N/A -1.50 0.897

EXOC7_1 36.00 19.00 20.00 35.00 21.00 18.00 -0.33 0.967


PSI P Value

110

II. Global analysis of cellular alternative splicing and gene expression by RNA seq

Table II-1 Effect of 791 treatment on cellular alternative splicing (AS) by RNAseq.

HeLa B2 cells were treated as described previously. For each splicing event, the ‘percent spliced

in’ or PSI score is given. The mean change in exon inclusion with compound treatment and the

associated p value (student’s t test) is listed (N = 2). AS events with |PSI| ≥ 10% and ≥ 20% are

coloured orange and red, respectively.

Summary

Raw total count of AS events: 18,611

AS events with confidence: 10,001





PLEKHA7 27.56 25.64 43.86 41.94 39.26 64.81 16.30 0.0069

DPYD 81.98 85.23 98.60 100.00 92.52 94.55 15.70 0.0363

ALS2CL 48.05 50.82 63.27 66.67 62.75 69.23 15.54 0.0215

TATDN2 16.09 17.23 27.24 29.96 25.58 26.23 11.94 0.0422

MIPOL1 74.00 74.67 85.62 84.91 75.00 74.74 10.93 0.0020

SAPS2 67.45 69.22 79.00 78.37 72.16 70.24 10.35 0.0338

NT5C2 7.59 9.44 20.06 17.60 28.61 51.46 10.32 0.0260

ZFYVE9 79.64 78.57 88.73 87.88 77.78 76.00 9.20 0.0066

SRSF2 10.21 11.06 20.00 19.14 20.92 20.50 8.94 0.0045

TMEM18 8.90 9.46 18.53 17.67 15.46 17.97 8.92 0.0062

USP33 43.89 42.02 52.79 50.74 47.16 43.50 8.81 0.0244

SYCP2 65.95 63.49 72.12 74.86 61.91 65.99 8.77 0.0423

AC009533.2 8.82 11.32 19.09 17.44 39.66 52.60 8.20 0.0432

PODXL 24.89 23.00 32.57 31.49 32.46 43.38 8.09 0.0320

USP14 6.43 7.33 15.24 13.93 3.51 4.57 7.71 0.0153

ZNF616 21.88 20.65 27.23 29.33 10.94 13.59 7.02 0.0459

TIA1 14.10 13.09 21.19 19.53 19.27 20.22 6.77 0.0323

SRC 92.46 92.83 98.50 98.59 95.70 94.74 5.90 0.0141

SNRK 92.92 94.20 98.75 100.00 98.28 97.08 5.82 0.0229

[Undefined] 67.30 67.89 73.04 73.06 72.28 62.37 5.46 0.0342

DCAKD 9.24 7.57 14.34 13.10 13.69 14.92 5.32 0.0427

C6orf192 94.04 94.44 99.20 99.27 99.07 97.10 5.00 0.0215

KIF27 10.84 11.48 15.94 15.70 10.26 21.95 4.66 0.0245

TAF4B 95.14 95.60 100.00 100.00 100.00 94.48 4.63 0.0316

PRPF38B 8.41 9.61 13.37 13.88 8.94 4.65 4.62 0.0497

CEP135 95.56 95.74 100.00 100.00 100.00 93.89 4.35 0.0132

STARD3 88.48 88.14 92.35 92.54 93.17 95.92 4.14 0.0064

C8orf59 88.75 87.64 92.54 91.94 92.14 85.07 4.05 0.0432

DEM1 72.17 71.13 75.76 75.16 77.78 94.29 3.81 0.0403

IMPAD1 1.71 2.88 5.47 6.64 3.64 4.04 3.76 0.0452

BX004987.4 92.44 92.96 95.94 96.68 90.39 92.27 3.61 0.0208

P ValueGene IDDMSO 791 191 Mean

PSI

111


OSBPL5 86.15 86.32 89.82 89.61 93.37 98.55 3.48 0.0019

FANCC 88.84 89.51 93.02 92.16 96.63 98.82 3.41 0.0282

SUV420H2 60.25 61.17 63.58 64.66 60.68 52.38 3.41 0.0427

MED24 4.40 5.37 7.74 8.41 8.26 15.86 3.19 0.0417

KIAA1324L 92.00 92.20 95.19 95.26 98.99 96.38 3.13 0.0102

USP37 96.83 97.08 100.00 100.00 100.00 100.00 3.05 0.0261

TTC27 90.06 90.24 93.26 93.06 90.28 94.48 3.01 0.0021

TGDS 2.57 1.67 5.41 4.66 2.97 0.80 2.92 0.0406

FANCG 96.28 96.27 99.01 99.29 96.79 96.10 2.88 0.0308

CXXC1 4.84 5.54 7.59 8.53 10.56 13.65 2.87 0.0458

MPRIP 4.58 4.85 7.28 7.88 5.51 6.39 2.87 0.0352

KIAA0284 94.16 93.78 96.32 96.91 92.08 96.38 2.65 0.0261

C13orf27 92.12 91.74 94.40 94.69 97.71 94.03 2.62 0.0104

CHD2 92.12 92.51 94.74 95.02 100.00 98.37 2.56 0.0120

P4HA3 90.72 91.52 93.22 93.84 92.53 90.38 2.41 0.0465

TMEM199 3.48 3.05 5.84 5.33 8.11 9.68 2.32 0.0216

WDR77 4.99 5.57 7.91 7.26 7.09 9.30 2.31 0.0348

OSTF1 95.51 94.94 97.75 97.19 95.69 95.62 2.25 0.0303

FAM96A 2.18 2.17 4.43 4.30 2.17 3.61 2.19 0.0182

CCDC18 7.90 7.23 9.42 10.06 14.10 10.94 2.18 0.0427

SF3B1 4.65 4.30 6.66 6.52 6.99 6.86 2.12 0.0291

CCDC123 96.26 96.92 98.97 98.44 100.00 90.70 2.11 0.0414

NUP205 97.45 97.82 99.63 99.86 99.65 99.75 2.11 0.0182

MED4 95.04 94.92 97.04 97.04 98.19 96.98 2.06 0.0185

VIPAR 97.92 97.68 99.56 100.00 100.00 100.00 1.98 0.0311

DPY19L4 98.00 98.24 100.00 100.00 100.00 100.00 1.88 0.0406

BAG1 4.33 4.58 6.42 6.19 5.25 5.31 1.85 0.0085

ST3GAL1 94.48 94.85 96.66 96.36 97.72 96.86 1.85 0.0183

NTHL1 97.24 96.72 99.06 98.53 98.21 99.81 1.82 0.0394

ITPR1 97.19 97.58 99.22 99.09 98.94 98.86 1.77 0.0485

GAK 98.05 97.54 99.72 99.41 99.30 97.86 1.77 0.0419

CDCA3 96.44 96.16 98.09 97.97 98.41 99.55 1.73 0.0262

ADARB1 82.86 82.87 84.60 84.52 89.73 89.91 1.69 0.0136

RNF215 98.26 98.37 100.00 100.00 100.00 100.00 1.69 0.0208

FCHSD1 98.39 98.33 100.00 100.00 100.00 99.14 1.64 0.0116

DOCK11 98.34 98.45 100.00 100.00 100.00 100.00 1.61 0.0218

CDK17 96.77 97.07 98.61 98.40 92.34 97.41 1.59 0.0181

CABIN1 98.45 98.48 100.00 100.00 97.74 97.42 1.54 0.0062

PAM 97.76 98.03 99.35 99.51 97.72 97.70 1.54 0.0195

SFRS12 96.79 97.10 98.29 98.65 99.46 100.00 1.53 0.0247

MLLT6 97.59 97.62 99.02 99.08 98.75 95.83 1.44 0.0029

TELO2 98.55 98.23 100.00 99.59 99.08 100.00 1.41 0.0369

SIRT2 0.61 0.38 1.92 1.80 1.18 2.13 1.37 0.0216

NT5DC1 0.69 1.04 1.96 2.38 0.71 1.19 1.31 0.0438

SNRPD3 95.65 96.04 97.29 96.99 96.24 96.22 1.29 0.0391

FAT1 97.96 98.17 99.40 99.29 98.40 99.56 1.28 0.0207

MMAB 98.70 98.76 100.00 100.00 97.87 98.68 1.27 0.0150

LLGL1 98.70 98.88 100.00 100.00 99.48 100.00 1.21 0.0473

AHCYL2 98.71 98.89 100.00 100.00 100.00 100.00 1.20 0.0477

REXO4 98.64 98.79 99.77 100.00 98.84 100.00 1.17 0.0209

FNDC3B 97.54 97.92 99.08 98.72 99.54 96.91 1.17 0.0468


PSI

112


MRPS27 97.10 97.17 98.18 98.27 95.75 87.48 1.09 0.0036

TTC17 98.64 98.36 99.38 99.69 98.50 99.14 1.04 0.0392

41889 1.13 1.11 2.17 2.11 1.25 1.53 1.02 0.0097

CPT1A 98.63 98.68 99.57 99.72 99.12 100.00 0.99 0.0308

SMARCD2 98.94 99.09 100.00 100.00 100.00 99.74 0.98 0.0484

MAST2 98.76 99.01 100.00 99.74 100.00 100.00 0.98 0.0320

TMEM131 99.09 99.05 100.00 100.00 97.88 90.57 0.93 0.0137

SMARCAD1 99.03 99.13 100.00 100.00 95.73 73.31 0.92 0.0346

DDA1 97.91 98.12 98.80 99.02 97.87 93.37 0.89 0.0278

ATHL1 99.18 99.06 100.00 100.00 100.00 100.00 0.88 0.0433

NENF 98.94 98.87 99.75 99.77 99.59 99.01 0.85 0.0169

HTRA2 96.02 96.08 96.89 96.90 98.74 98.59 0.85 0.0193

RAE1 1.32 1.53 2.19 2.33 0.81 0.63 0.84 0.0310

DMXL1 99.22 99.24 100.00 100.00 100.00 100.00 0.77 0.0083

FNIP1 99.22 99.30 100.00 100.00 100.00 100.00 0.74 0.0344

MED12 99.21 99.32 100.00 100.00 100.00 99.13 0.74 0.0475

SLC25A40 99.26 99.35 100.00 100.00 100.00 100.00 0.70 0.0412

PHKA2 99.27 99.36 100.00 100.00 100.00 97.17 0.69 0.0418

NIN 99.35 99.33 100.00 100.00 97.80 99.16 0.66 0.0096

GBE1 99.34 99.38 100.00 100.00 99.67 95.74 0.64 0.0199

PPIG 1.39 1.31 1.93 2.03 3.09 1.88 0.63 0.0119

COL18A1 98.61 98.53 99.16 99.17 98.51 97.76 0.59 0.0398

AP3M1 99.21 99.13 99.76 99.75 99.69 100.00 0.59 0.0405

HDAC6 99.38 99.45 100.00 100.00 98.50 100.00 0.59 0.0380

C1orf77 99.42 99.41 100.00 100.00 99.63 99.82 0.59 0.0054

SLC7A6 99.46 99.43 100.00 100.00 100.00 100.00 0.56 0.0172

RNF213 99.41 99.49 100.00 100.00 97.91 100.00 0.55 0.0462

WRAP53 99.51 99.43 100.00 100.00 99.50 100.00 0.53 0.0480

RPS6KB1 98.88 98.96 99.42 99.46 100.00 100.00 0.52 0.0201

LAMB1 99.30 99.22 99.77 99.77 99.23 99.85 0.51 0.0498

ZMYM2 99.49 99.53 100.00 100.00 100.00 97.68 0.49 0.0260

MBD2 97.98 98.01 98.43 98.52 99.29 98.89 0.48 0.0399

CCDC6 99.53 99.51 100.00 100.00 99.56 100.00 0.48 0.0133

GIT1 99.31 99.42 99.81 99.76 100.00 98.88 0.42 0.0474

KARS 99.54 99.48 99.92 99.90 99.31 99.43 0.40 0.0304

KIAA1598 99.63 99.58 100.00 100.00 100.00 98.65 0.40 0.0402

SSR4 98.89 99.01 99.39 99.29 99.26 99.17 0.39 0.0404

AHCYL1 99.46 99.47 99.78 99.84 99.21 99.88 0.35 0.0495

PPP4C 95.30 95.30 95.67 95.62 95.41 95.55 0.35 0.0461

R3HCC1 99.44 99.33 99.76 99.69 100.00 99.54 0.34 0.0487

NCBP1 98.35 98.26 98.57 98.66 99.43 99.40 0.31 0.0397

LAMA5 99.70 99.68 100.00 100.00 99.23 99.86 0.31 0.0205

MVP 99.71 99.73 100.00 100.00 100.00 100.00 0.28 0.0227

CYFIP1 99.40 99.44 99.70 99.67 99.69 99.19 0.27 0.0113

ACO2 99.68 99.73 100.00 99.92 99.93 100.00 0.25 0.0470

LTBR 99.76 99.75 100.00 100.00 99.38 99.53 0.24 0.0130

CCT4 99.78 99.76 99.95 100.00 100.00 100.00 0.20 0.0481

CUEDC2 99.79 99.80 100.00 100.00 100.00 100.00 0.20 0.0155

C11orf48 99.86 99.84 100.00 100.00 100.00 100.00 0.15 0.0424

ATP6AP2 0.15 0.15 0.23 0.22 0.19 0.05 0.08 0.0424

AKIRIN2 100.00 100.00 99.86 99.84 100.00 99.59 -0.15 0.0424


PSI

113


HYOU1 100.00 100.00 99.84 99.86 100.00 99.86 -0.15 0.0424

DLG5 99.71 99.76 99.49 99.53 100.00 100.00 -0.23 0.0222

SRPR 100.00 100.00 99.76 99.77 100.00 98.86 -0.23 0.0135

AHSA1 99.31 99.28 99.02 99.06 99.26 99.74 -0.26 0.0121

SETD3 100.00 100.00 99.74 99.73 99.78 99.77 -0.27 0.0120

ECHS1 99.93 100.00 99.72 99.65 99.93 99.73 -0.28 0.0299

DCUN1D4 100.00 100.00 99.67 99.69 100.00 99.43 -0.32 0.0199

UBR4 100.00 100.00 99.67 99.66 100.00 99.61 -0.34 0.0095

HOMER3 99.77 99.83 99.43 99.49 99.50 99.72 -0.34 0.0152

U2AF1 99.94 100.00 99.63 99.58 99.52 99.35 -0.37 0.0125

RBM26 100.00 100.00 99.65 99.61 99.35 97.97 -0.37 0.0344

PLIN3 99.73 99.69 99.34 99.29 99.45 99.61 -0.39 0.0077

IBTK 100.00 100.00 99.60 99.61 99.06 97.14 -0.40 0.0081

EMP3 99.37 99.38 98.94 98.95 98.79 98.74 -0.43 0.0003

LPCAT4 100.00 100.00 99.58 99.52 100.00 100.00 -0.45 0.0424

PYGL 99.36 99.52 98.87 99.01 99.44 99.60 -0.50 0.0438

IMPA2 1.36 1.43 0.81 0.89 1.01 0.73 -0.55 0.0099

HACL1 100.00 100.00 99.48 99.40 99.19 98.87 -0.56 0.0454

ACTR8 100.00 100.00 99.43 99.44 100.00 100.00 -0.56 0.0056

ZNF276 100.00 100.00 99.44 99.37 100.00 100.00 -0.59 0.0374

YEATS2 100.00 100.00 99.35 99.43 100.00 99.54 -0.61 0.0417

DUSP11 99.58 99.65 99.03 98.91 98.76 98.56 -0.65 0.0218

GPD1L 100.00 100.00 99.33 99.32 100.00 100.00 -0.68 0.0047

NCKIPSD 99.08 99.01 98.32 98.40 98.50 99.08 -0.69 0.0064

41893 99.71 99.57 98.89 99.01 99.57 100.00 -0.69 0.0185

PNPLA2 99.42 99.54 98.69 98.87 99.26 98.63 -0.70 0.0322

RCN2 1.10 0.99 0.40 0.26 0.23 0.18 -0.72 0.0177

PDE3A 98.27 98.31 97.62 97.51 98.89 92.86 -0.72 0.0286

PPP2R5B 100.00 100.00 99.26 99.28 98.19 100.00 -0.73 0.0087

PLXNB1 100.00 100.00 99.22 99.30 99.25 100.00 -0.74 0.0344

MMS19 97.45 97.27 96.50 96.69 94.89 98.93 -0.77 0.0282

DCTD 100.00 100.00 99.23 99.22 99.05 99.10 -0.77 0.0041

EHMT1 100.00 100.00 99.20 99.18 99.76 96.14 -0.81 0.0079

SLC25A23 1.36 1.61 0.56 0.75 0.48 1.44 -0.83 0.0393

VPS33B 100.00 100.00 99.17 99.16 100.00 100.00 -0.84 0.0038

NT5DC2 99.36 99.53 98.68 98.52 99.28 98.93 -0.84 0.0187

ITGAV 99.54 99.31 98.66 98.43 99.54 97.32 -0.88 0.0325

BAIAP2 6.51 6.41 5.60 5.54 2.19 0.37 -0.89 0.0093

DDX23 100.00 99.84 98.95 99.10 100.00 100.00 -0.90 0.0149

WDR12 99.71 100.00 99.03 98.84 100.00 99.70 -0.92 0.0458

CEP250 100.00 100.00 99.07 99.09 100.00 99.61 -0.92 0.0069

ZNF791 100.00 100.00 99.08 98.96 99.10 95.54 -0.98 0.0389

BIRC6 100.00 100.00 98.94 98.99 99.03 100.00 -1.04 0.0154

SEC23A 99.85 99.85 98.72 98.87 98.83 99.28 -1.05 0.0452

GPSM2 100.00 100.00 98.88 99.01 98.88 96.21 -1.06 0.0392

PRKCZ 99.79 99.84 98.73 98.78 98.03 100.00 -1.06 0.0011

YARS2 98.62 98.93 97.82 97.61 98.39 92.23 -1.06 0.0395

C19orf63 5.23 5.06 4.04 4.03 9.44 6.14 -1.11 0.0479

RFC1 99.41 99.08 98.17 97.92 96.05 97.67 -1.20 0.0334

AGK 100.00 100.00 98.74 98.86 100.00 98.13 -1.20 0.0318

CEP57 99.57 99.44 98.23 98.32 94.49 65.95 -1.23 0.0066

Gene IDDMSO 791 191 Mean

PSIP Value

114


CLTC 99.37 99.76 98.04 98.30 98.86 99.22 -1.40 0.0370

AFF1 99.46 99.35 98.00 98.01 98.71 98.37 -1.40 0.0239

WDR43 99.51 99.53 98.14 98.07 97.55 86.85 -1.42 0.0094

AC099524.1 100.00 99.76 98.51 98.39 100.00 100.00 -1.43 0.0228

SMARCAD1 100.00 100.00 98.58 98.53 100.00 100.00 -1.45 0.0110

TEP1 100.00 100.00 98.53 98.57 100.00 100.00 -1.45 0.0088

SCD5 99.46 99.47 97.99 97.88 98.58 99.24 -1.53 0.0218

USP20 95.85 95.67 94.07 94.38 83.39 84.77 -1.54 0.0249

DNAJC11 99.55 99.02 97.94 97.49 97.43 99.15 -1.57 0.0479

CAB39 98.56 98.48 96.77 97.04 94.63 93.18 -1.62 0.0378

RUSC1 99.19 99.55 97.96 97.47 98.37 99.46 -1.66 0.0386

NEDD4 100.00 100.00 98.35 98.31 100.00 86.78 -1.67 0.0076

ERCC2 99.25 98.73 97.47 96.91 94.60 97.13 -1.80 0.0427

NCAPD3 98.65 99.20 97.27 96.71 99.11 97.23 -1.94 0.0388

EFR3A 100.00 100.00 97.98 98.10 100.00 97.80 -1.96 0.0195

DNMBP 97.48 97.74 95.56 95.65 97.97 96.45 -2.01 0.0246

MRPL13 98.99 98.94 96.97 96.93 98.11 97.33 -2.01 0.0003

MGAT5 97.55 97.84 95.93 95.41 97.67 95.76 -2.03 0.0379

POLA1 97.86 97.62 95.72 95.58 95.59 84.70 -2.09 0.0101

NFKBIZ 99.43 99.36 97.16 97.40 96.17 97.54 -2.12 0.0243

SURF6 99.02 99.37 96.96 97.19 98.08 98.07 -2.12 0.0154

SHMT2 98.36 97.95 96.35 95.71 98.12 97.70 -2.13 0.0432

AP001011.3 99.45 100.00 97.20 97.81 97.60 74.04 -2.22 0.0333

ARHGEF2 97.22 97.12 94.77 95.13 95.57 96.28 -2.22 0.0379

DHX38 98.43 98.29 95.99 96.24 97.35 97.83 -2.25 0.0103

RMND1 100.00 100.00 97.84 97.64 94.38 70.59 -2.26 0.0282

PKN2 97.82 97.61 95.69 95.17 95.47 97.76 -2.29 0.0436

ANKRD28 99.53 100.00 97.57 97.27 95.44 95.74 -2.35 0.0221

BLZF1 99.34 99.29 97.06 96.83 92.44 92.09 -2.37 0.0243

TDRD7 100.00 100.00 97.50 97.47 97.50 87.65 -2.52 0.0038

SH3BP4 100.00 99.59 97.36 97.15 99.48 97.86 -2.54 0.0208

SOX13 100.00 100.00 97.40 97.45 100.00 99.10 -2.58 0.0062

COL4A5 100.00 99.50 96.81 97.50 100.00 95.35 -2.60 0.0322

ZNF2 100.00 100.00 97.33 96.88 100.00 98.06 -2.90 0.0494

FOXM1 13.56 13.55 10.71 10.48 12.03 12.82 -2.96 0.0245

UBTF 41.61 41.32 38.46 38.15 31.83 34.20 -3.16 0.0046

ZNHIT6 95.44 94.86 92.41 91.57 86.00 73.68 -3.16 0.0332

CASC5 99.36 100.00 96.30 96.55 98.60 100.00 -3.26 0.0372

TRPM7 99.28 98.88 95.43 95.80 93.03 90.65 -3.47 0.0063

VPS35 93.46 93.28 89.95 89.82 95.87 94.89 -3.49 0.0017

CHD1 7.75 8.64 4.90 4.49 5.74 7.79 -3.50 0.0450

ORC3L 96.24 96.16 92.70 92.69 95.09 91.48 -3.51 0.0064

DENND1B 100.00 100.00 96.30 96.61 82.61 61.90 -3.55 0.0278

SOAT1 97.00 97.95 94.13 93.45 96.38 91.00 -3.69 0.0307

ELP3 98.84 100.00 94.97 96.08 98.39 88.51 -3.90 0.0401

EIF2C4 100.00 100.00 96.30 95.88 100.00 97.30 -3.91 0.0342

CLTC 6.44 7.43 3.19 2.51 2.46 2.74 -4.09 0.0284

HRSP12 96.72 97.34 93.50 92.39 92.70 88.28 -4.09 0.0412

KIAA0317 98.60 98.37 94.38 94.21 97.25 92.59 -4.19 0.0018

OSBPL3 94.94 95.97 90.32 91.65 88.43 68.86 -4.47 0.0382

C10orf75 43.87 44.11 38.81 39.70 57.09 63.00 -4.74 0.0456


PSI

115


TBC1D22B 92.83 91.54 86.88 87.54 81.76 59.44 -4.98 0.0418

UGGT1 91.92 90.76 86.37 85.38 82.30 77.80 -5.47 0.0202

WDR19 10.28 9.45 4.51 4.05 22.76 29.80 -5.59 0.0164

VLDLR 95.67 97.09 91.29 90.06 90.66 96.65 -5.71 0.0273

KIAA1919 96.33 96.26 90.20 90.32 86.05 89.57 -6.04 0.0006

PHF19 87.28 87.13 81.18 81.13 88.84 76.00 -6.05 0.0034

BTBD3 35.43 37.16 29.09 31.02 32.06 31.52 -6.24 0.0415

FAM114A2 94.48 96.63 90.13 88.34 77.63 66.67 -6.32 0.0485

FIS1 92.95 94.11 87.41 86.97 96.54 96.74 -6.34 0.0348

KDM6A 73.06 71.57 66.50 65.11 68.24 52.21 -6.51 0.0239

INTS4 16.48 14.47 9.61 8.14 8.13 8.57 -6.60 0.0406

KIF15 100.00 99.22 92.86 92.44 98.94 78.08 -6.96 0.0111

SRRM2 40.36 41.29 33.26 34.16 33.42 20.75 -7.12 0.0082

KNTC1 97.49 96.47 88.77 90.52 93.68 94.94 -7.34 0.0323

ARL6 94.87 93.33 87.10 86.21 75.00 69.77 -7.45 0.0260

VPS13C 96.83 96.06 88.24 89.47 85.37 85.54 -7.59 0.0159

MED17 95.00 93.62 86.05 86.30 83.33 71.55 -8.14 0.0473

OSBPL9 87.74 86.41 78.59 77.82 82.44 88.28 -8.87 0.0156

R3HDM1 31.91 34.32 23.67 24.82 25.49 25.35 -8.87 0.0477

AC136619.1 34.07 31.58 25.08 22.73 15.37 7.85 -8.92 0.0352

DCUN1D3 36.64 36.36 27.31 27.31 24.93 11.82 -9.19 0.0097

CHRNA5 93.55 93.83 83.51 84.47 87.34 89.74 -9.70 0.0207

SPAG1 96.88 100.00 87.10 90.16 97.10 85.19 -9.81 0.0462

NCOA5* 94.87 93.21 83.21 81.17 71.93 64.29 -11.85 0.0137

BTBD9 25.30 24.00 12.00 13.43 11.43 15.15 -11.94 0.0067

TNFAIP3 88.65 89.50 75.23 73.33 75.00 88.24 -14.80 0.0181

DST 82.57 79.68 65.99 65.09 69.22 49.41 -15.59 0.0413

RBMX 51.69 55.52 36.07 38.35 31.87 20.47 -16.40 0.0306

CCDC18 96.92 92.16 79.10 75.57 56.58 34.55 -17.21 0.0341

FGFR1OP2 71.43 71.87 51.40 51.71 49.51 25.08 -20.10 0.0004

C12orf29 61.70 65.24 40.44 37.44 41.06 15.17 -24.53 0.0097


PSIP Value

116

Table II-2 Effect of 191 treatment on cellular alternative splicing (AS) by RNAseq.

HeLa B2 cells were treated as described previously. For each splicing event, the ‘percent spliced

in’ or PSI score is given. The mean change in exon inclusion with compound treatment and the

associated p value (student’s t test) is listed (N = 2). AS events with |PSI| ≥ 10% are coloured

orange.

Summary

Raw total count of AS events: 18,611

AS events with confidence: 9,806





KIAA0649 29.13 27.10 32.69 18.53 54.06 53.83 25.83 0.0233

ANKRD9 76.11 71.84 81.07 83.26 95.49 99.23 23.39 0.0152

TCF19 68.55 72.16 76.09 79.93 91.82 94.12 22.62 0.0151

CLCN6 67.83 67.14 59.38 66.67 87.72 90.86 21.81 0.0372

AF011889.4 58.54 62.89 60.00 78.38 80.95 83.91 21.72 0.0206

IFT88 66.99 72.33 80.85 83.74 85.00 89.47 17.58 0.0395

TBCK 5.62 3.76 13.04 10.00 20.31 23.56 17.25 0.0228

STIL 29.29 26.05 32.21 27.90 41.54 45.99 16.10 0.0344

ZNF445 83.78 81.58 91.84 92.21 97.30 100.00 15.97 0.0132

ZNF317 71.90 73.64 77.69 70.71 86.43 90.32 15.61 0.0449

THSD1P1 43.75 40.00 32.37 31.78 60.00 54.84 15.55 0.0473

FUBP1 10.65 8.49 20.02 12.88 25.57 24.60 15.52 0.0201

SLC4A7 80.84 83.74 95.65 88.84 95.79 99.17 15.19 0.0221

WDR91 85.71 87.01 88.38 87.23 99.18 100.00 13.23 0.0068

HYAL3 78.08 81.92 88.14 83.43 91.43 94.12 12.78 0.0406

KITLG 73.83 75.71 78.54 82.31 86.09 88.94 12.75 0.0256

CEP170 77.40 79.39 77.65 80.51 89.56 92.06 12.42 0.0185

UBP1 38.96 38.84 52.11 48.56 50.54 50.23 11.49 0.0029

VPS41 2.03 1.70 3.07 1.47 12.17 13.63 11.04 0.0335

CRAMP1L 84.71 88.33 95.92 83.23 98.67 96.00 10.82 0.0478

XPO4 27.30 27.99 25.45 37.38 37.56 38.82 10.55 0.0119

STK19 86.26 84.70 90.37 89.56 95.84 96.03 10.46 0.0445

STK39 41.33 43.71 55.69 49.72 52.21 53.38 10.28 0.0370

SRSF2 10.21 11.06 20.00 19.14 20.92 20.50 10.08 0.0085

CENPE 90.56 88.89 88.19 85.44 100.00 99.15 9.85 0.0226

FBXO18 9.88 9.69 12.29 6.91 18.49 19.99 9.46 0.0471

TATDN2 16.09 17.23 27.24 29.96 25.58 26.23 9.25 0.0117

OGT 86.39 84.73 90.94 91.46 94.64 93.05 8.29 0.0188

ADARB1 82.86 82.87 84.60 84.52 89.73 89.91 6.96 0.0080

WDR90 88.64 89.22 95.64 88.69 95.73 95.88 6.88 0.0188

MFSD3 89.47 90.76 91.07 89.18 95.77 97.08 6.31 0.0206


PSI

117


TIA1 14.10 13.09 21.19 19.53 19.27 20.22 6.15 0.0126

PCNXL3 10.54 10.02 4.52 7.38 16.70 16.13 6.14 0.0041

CDCA7 16.21 17.72 19.84 17.33 23.41 22.60 6.04 0.0378

DCAKD 9.24 7.57 14.34 13.10 13.69 14.92 5.90 0.0356

CTC-338M12.5 12.51 14.13 16.52 19.57 18.10 19.97 5.72 0.0455

C19orf50 5.59 4.33 9.70 7.53 9.28 11.04 5.20 0.0492

ZER1 93.68 94.18 95.99 93.48 98.45 99.71 5.15 0.0486

C10orf35 94.68 95.21 96.67 100.00 100.00 100.00 5.06 0.0333

MLL3 88.89 90.05 93.52 91.23 95.31 93.67 5.02 0.0466

PDE8B 89.17 90.37 92.06 89.20 94.09 94.93 4.74 0.0302

CRELD2 5.03 4.44 4.43 4.26 9.61 9.25 4.70 0.0108

RUFY2 75.00 75.84 82.22 90.58 80.25 79.78 4.60 0.0223

METAP1 92.04 91.81 95.64 96.94 96.27 96.76 4.59 0.0130

MAP4K2 93.60 94.49 95.43 94.82 98.01 99.14 4.53 0.0276

POGZ 92.56 91.67 92.03 95.56 96.68 96.13 4.29 0.0242

INVS 95.52 95.94 96.26 98.10 100.00 100.00 4.27 0.0313

SNRK 92.92 94.20 98.75 100.00 98.28 97.08 4.12 0.0428

EML2 95.06 95.20 96.38 97.68 99.06 99.06 3.93 0.0113

ARVCF 96.34 95.99 91.79 100.00 100.00 100.00 3.84 0.0290

KIRREL 96.25 95.72 100.00 97.31 99.26 100.00 3.65 0.0201

KIAA1549 96.23 96.59 96.82 99.42 100.00 100.00 3.59 0.0319

ANAPC1 1.20 1.30 1.63 1.68 4.79 4.49 3.39 0.0160

NSUN2 2.26 2.65 2.76 2.10 5.33 5.89 3.16 0.0163

TMEM138 94.99 95.27 96.91 97.58 97.89 98.50 3.07 0.0321

UHRF1BP1L 96.44 95.79 97.84 97.63 98.73 99.59 3.05 0.0351

USP37 96.83 97.08 100.00 100.00 100.00 100.00 3.05 0.0261

CDCA7 16.17 15.79 19.92 23.26 18.97 18.91 2.96 0.0364

TNIP2 96.55 96.67 97.11 99.51 99.25 99.60 2.82 0.0236

SFRS12 96.79 97.10 98.29 98.65 99.46 100.00 2.79 0.0237

HTRA2 96.02 96.08 96.89 96.90 98.74 98.59 2.62 0.0073

MLKL 97.22 97.59 98.10 95.88 100.00 100.00 2.60 0.0453

C22orf13 96.33 96.87 94.99 98.47 98.92 99.41 2.57 0.0201

NCSTN 1.02 0.84 1.08 2.27 3.40 3.47 2.51 0.0102

C1orf93 97.70 97.31 100.00 98.61 100.00 100.00 2.50 0.0497

KIAA1109 3.42 2.99 2.94 2.91 6.01 5.34 2.47 0.0363

SF3B1 4.65 4.30 6.66 6.52 6.99 6.86 2.45 0.0260

STAG1 97.61 97.58 93.79 100.00 100.00 100.00 2.41 0.0040

ILKAP 1.88 1.28 4.23 0.51 3.59 4.36 2.40 0.0439

RRM2B 97.55 97.67 99.07 100.00 100.00 100.00 2.39 0.0160

BAT2L 97.49 97.71 98.66 98.27 99.85 100.00 2.33 0.0055

PREB 96.80 97.36 95.81 97.16 99.05 99.70 2.30 0.0348

DAGLA 97.85 97.65 96.30 93.97 100.00 100.00 2.25 0.0283

CTTNBP2 97.92 97.62 97.56 88.41 100.00 100.00 2.23 0.0428

VIPAR 97.92 97.68 99.56 100.00 100.00 100.00 2.20 0.0347

HPS3 97.31 97.89 98.89 100.00 100.00 99.43 2.12 0.0351

C7orf64 97.86 97.29 97.22 100.00 99.35 100.00 2.10 0.0412

MBD1 97.54 97.00 98.05 96.87 99.19 99.50 2.08 0.0376

NUP205 97.45 97.82 99.63 99.86 99.65 99.75 2.07 0.0431

NME4 6.83 6.97 8.37 6.99 8.91 9.02 2.07 0.0024

CACNA1H 97.80 97.24 98.98 98.13 99.65 99.15 1.88 0.0386

DPY19L4 98.00 98.24 100.00 100.00 100.00 100.00 1.88 0.0406


PSI

118


P4HA2 97.50 97.97 98.32 98.68 99.27 99.83 1.82 0.0406

PCNXL3 98.22 97.73 98.97 98.50 100.00 99.57 1.81 0.0321

FAIM 98.18 98.23 98.80 99.49 100.00 100.00 1.79 0.0089

CELF1 97.62 97.97 98.18 99.16 99.80 99.36 1.79 0.0270

STK11IP 98.29 98.25 100.00 95.60 100.00 100.00 1.73 0.0074

RNF215 98.26 98.37 100.00 100.00 100.00 100.00 1.69 0.0208

MAGOHB 3.42 3.53 4.64 6.70 4.98 5.31 1.67 0.0425

ACBD5 97.15 97.42 97.00 96.72 98.87 98.96 1.63 0.0343

DOCK11 98.34 98.45 100.00 100.00 100.00 100.00 1.61 0.0218

NEURL 98.13 97.79 98.74 99.76 99.51 99.32 1.46 0.0327

CXXC1 98.52 98.60 97.92 98.48 100.00 100.00 1.44 0.0177

ABCB6 90.07 89.97 91.71 89.76 91.48 91.37 1.41 0.0029

MRPL52 2.20 2.50 4.37 6.04 3.82 3.67 1.40 0.0326

RP6-109B7.3 2.44 2.75 3.48 2.65 4.08 3.84 1.37 0.0234

MIIP 97.91 98.06 98.71 97.25 99.25 99.13 1.21 0.0075

AHCYL2 98.71 98.89 100.00 100.00 100.00 100.00 1.20 0.0477

UNK 98.80 98.82 100.00 98.80 100.00 100.00 1.19 0.0053

ADNP 83.72 83.98 80.59 82.70 85.08 84.98 1.18 0.0436

DOCK9 98.86 98.81 99.08 100.00 100.00 100.00 1.17 0.0137

NCBP1 98.35 98.26 98.57 98.66 99.43 99.40 1.11 0.0144

BAT2L 98.80 98.67 98.79 99.38 99.87 99.80 1.10 0.0121

RPS6KB1 98.88 98.96 99.42 99.46 100.00 100.00 1.08 0.0236

WDFY3 98.97 98.88 98.09 100.00 100.00 100.00 1.08 0.0266

SNX2 98.68 98.94 99.27 99.89 99.75 100.00 1.07 0.0276

MED12 98.95 99.00 100.00 98.88 100.00 100.00 1.03 0.0155

ATHL1 99.18 99.06 100.00 100.00 100.00 100.00 0.88 0.0433

NAP1L4 0.48 0.41 0.62 0.90 1.32 1.30 0.87 0.0167

CCT6A 98.09 97.99 98.35 98.70 98.94 98.85 0.85 0.0064

SMARCD2 98.94 99.09 100.00 100.00 100.00 99.74 0.85 0.0476

DHX30 99.09 99.21 100.00 99.45 100.00 100.00 0.85 0.0449

ULK3 99.21 99.12 99.32 99.26 100.00 100.00 0.84 0.0343

IGHMBP2 99.13 99.25 99.35 100.00 100.00 100.00 0.81 0.0471

NCOA5 99.21 99.18 97.95 98.41 100.00 100.00 0.81 0.0119

CXXC1 99.22 99.20 99.41 99.27 100.00 100.00 0.79 0.0081

NKIRAS2 98.83 98.90 96.62 100.00 99.61 99.68 0.78 0.0040

STT3B 98.68 98.92 99.56 99.21 99.66 99.49 0.77 0.0425

DMXL1 99.22 99.24 100.00 100.00 100.00 100.00 0.77 0.0083

AP1M1 99.22 99.25 98.25 99.42 100.00 100.00 0.77 0.0125

FNIP1 99.22 99.30 100.00 100.00 100.00 100.00 0.74 0.0344

PICALM 99.14 99.10 99.85 99.38 99.84 99.84 0.72 0.0177

SLC25A40 99.26 99.35 100.00 100.00 100.00 100.00 0.70 0.0412

ITGA5 99.32 99.31 99.22 100.00 100.00 100.00 0.69 0.0046

TRABD 99.17 98.99 99.21 100.00 99.82 99.63 0.64 0.0390

NUP188 99.37 99.27 99.24 99.16 99.89 100.00 0.63 0.0142

UPF3B 99.42 99.35 99.31 99.60 100.00 100.00 0.62 0.0362

GMIP 99.37 99.40 98.80 97.60 100.00 100.00 0.61 0.0155

INO80 99.40 99.38 98.31 99.48 100.00 100.00 0.61 0.0104

KIF1B 99.41 99.45 99.36 100.00 100.00 100.00 0.57 0.0223

PNPLA6 99.43 99.46 99.69 100.00 100.00 100.00 0.56 0.0172

SLC7A6 99.46 99.43 100.00 100.00 100.00 100.00 0.56 0.0172

ALDH16A1 99.46 99.45 98.84 100.00 100.00 100.00 0.55 0.0058


PSIP Value

119


GAK 96.68 96.86 93.09 97.12 97.22 97.37 0.52 0.0492

MSLN 99.21 99.33 99.41 99.43 99.73 99.85 0.52 0.0256

AMPD2 97.00 97.14 98.00 96.36 97.50 97.66 0.51 0.0422

TRAPPC1 99.26 99.37 99.39 99.93 99.74 99.90 0.50 0.0448

DCTN2 99.34 99.35 99.26 99.37 99.79 99.86 0.48 0.0424

SRP68 99.59 99.58 99.85 100.00 100.00 100.00 0.41 0.0077

BTAF1 99.57 99.61 99.03 97.97 100.00 100.00 0.41 0.0310

STAM 99.39 99.38 100.00 99.78 99.78 99.81 0.41 0.0127

SH3GL1 99.16 99.15 99.27 99.64 99.55 99.58 0.41 0.0127

USP5 99.54 99.53 99.38 99.01 99.88 99.89 0.35 0.0004

CLPTM1 99.18 99.13 99.10 99.18 99.46 99.52 0.33 0.0147

YME1L1 99.50 99.48 99.51 99.79 99.79 99.82 0.31 0.0058

SLC25A24 99.70 99.72 99.28 98.31 100.00 100.00 0.29 0.0219

MVP 99.71 99.73 100.00 100.00 100.00 100.00 0.28 0.0227

DDX11 99.13 99.15 99.44 99.20 99.41 99.42 0.27 0.0067

TBL1Y 99.72 99.76 99.80 99.59 100.00 100.00 0.26 0.0489

ACO2 99.68 99.73 100.00 99.92 99.93 100.00 0.26 0.0332

EXOSC8 99.76 99.73 99.71 100.00 100.00 100.00 0.25 0.0374

DDX54 99.76 99.77 100.00 99.69 100.00 100.00 0.23 0.0135

CCT4 99.78 99.76 99.95 100.00 100.00 100.00 0.23 0.0277

FAM129B 99.70 99.70 99.63 99.85 99.94 99.91 0.22 0.0424

CUEDC2 99.79 99.80 100.00 100.00 100.00 100.00 0.20 0.0155

PTPN1 99.13 99.11 98.77 98.60 99.34 99.30 0.20 0.0294

BAT3 99.71 99.70 99.64 99.73 99.85 99.88 0.16 0.0399

C11orf48 99.86 99.84 100.00 100.00 100.00 100.00 0.15 0.0424

CCNG1 99.43 99.46 99.66 99.28 99.56 99.58 0.13 0.0286

ESYT1 100.00 100.00 100.00 99.69 99.89 99.90 -0.10 0.0303

P4HB 99.86 99.84 99.78 99.86 99.75 99.73 -0.11 0.0161

CENPF 99.13 99.15 99.04 98.22 98.98 99.02 -0.14 0.0492

DDX24 100.00 100.00 99.85 100.00 99.85 99.87 -0.14 0.0454

PDCD6IP 100.00 100.00 99.15 99.42 99.83 99.85 -0.16 0.0397

SETD3 100.00 100.00 99.74 99.73 99.78 99.77 -0.23 0.0141

SMARCA4 100.00 100.00 100.00 99.60 99.71 99.72 -0.29 0.0112

ISY1 0.62 0.61 0.20 0.43 0.33 0.32 -0.29 0.0006

CUL4A 99.91 100.00 99.71 100.00 99.69 99.62 -0.30 0.0388

SPHK1 100.00 100.00 99.35 100.00 99.62 99.63 -0.38 0.0085

HNRNPAB 99.95 99.94 99.89 99.75 99.55 99.58 -0.38 0.0140

RNF31 100.00 100.00 100.00 99.52 99.62 99.59 -0.39 0.0242

MTOR 99.66 99.66 99.67 99.27 99.29 99.23 -0.40 0.0477

DDX17 100.00 99.91 99.57 99.90 99.49 99.62 -0.40 0.0466

RRN3 100.00 100.00 100.00 100.00 99.57 99.63 -0.40 0.0477

ASAP3 100.00 100.00 99.14 100.00 99.60 99.57 -0.42 0.0230

AP1G1 99.48 99.51 96.27 99.53 99.04 99.11 -0.42 0.0272

ZC3H7B 100.00 100.00 98.97 99.65 99.56 99.60 -0.42 0.0303

RELA 99.59 99.49 98.47 99.50 99.12 99.06 -0.45 0.0280

VAMP1 100.00 100.00 100.00 100.00 99.58 99.52 -0.45 0.0424

MRTO4 99.71 99.82 99.56 99.46 99.27 99.35 -0.45 0.0271

USP32 100.00 100.00 100.00 99.08 99.56 99.52 -0.46 0.0277

LRBA 100.00 100.00 100.00 97.30 99.56 99.50 -0.47 0.0406

SAMM50 100.00 100.00 99.72 99.65 99.50 99.53 -0.48 0.0197

PCBP2 99.37 99.41 99.13 99.58 98.87 98.76 -0.57 0.0382


PSI

120


FASTKD1 100.00 100.00 98.48 99.52 99.41 99.44 -0.58 0.0166

RP11-313P13.3 99.32 99.28 99.26 99.61 98.74 98.68 -0.59 0.0065

EMP3 99.37 99.38 98.94 98.95 98.79 98.74 -0.61 0.0210

LIMCH1 0.87 0.99 0.70 0.79 0.25 0.34 -0.64 0.0171

NMT1 100.00 100.00 99.87 100.00 99.33 99.38 -0.65 0.0247

GLB1 99.80 99.85 99.83 99.68 99.22 99.10 -0.66 0.0312

FBXL2 100.00 100.00 100.00 100.00 99.37 99.28 -0.67 0.0424

RAE1 1.32 1.53 2.19 2.33 0.81 0.63 -0.71 0.0382

TINAGL1 100.00 100.00 100.00 99.31 99.27 99.32 -0.71 0.0226

DGCR14 98.77 98.82 97.34 98.90 98.11 97.95 -0.76 0.0475

EXOC3 99.65 99.78 99.19 100.00 99.03 98.81 -0.80 0.0403

DNM1L 1.11 1.28 1.19 0.31 0.49 0.30 -0.80 0.0252

EFNA1 97.93 97.86 97.97 97.79 97.17 97.00 -0.81 0.0385

RCN2 1.10 0.99 0.40 0.26 0.23 0.18 -0.84 0.0182

GFM2 100.00 100.00 99.51 100.00 99.18 99.11 -0.85 0.0260

PSMA5 98.74 98.87 97.78 98.58 97.83 98.05 -0.87 0.0352

SMG5 1.80 2.00 1.78 1.54 0.96 1.08 -0.88 0.0290

LTBP3 100.00 100.00 99.14 100.00 99.11 99.10 -0.90 0.0036

AZI2 98.86 98.79 98.18 98.68 97.88 97.93 -0.92 0.0035

BCL2L1 2.13 2.19 2.05 2.39 1.18 1.29 -0.93 0.0119

DCTD 100.00 100.00 99.23 99.22 99.05 99.10 -0.93 0.0172

DUSP11 99.58 99.65 99.03 98.91 98.76 98.56 -0.95 0.0440

SEC31B 97.85 97.70 91.58 95.00 96.75 96.89 -0.95 0.0115

CHCHD3 97.96 97.95 97.79 96.88 96.92 96.99 -1.00 0.0198

BAG2 2.42 2.30 2.03 3.24 1.47 1.22 -1.02 0.0414

CYLD 100.00 100.00 100.00 98.79 99.03 98.94 -1.02 0.0282

RTTN 100.00 100.00 97.56 98.65 98.94 98.99 -1.04 0.0154

PDCD4 98.68 98.91 99.33 96.56 97.86 97.60 -1.07 0.0265

BMS1 99.03 98.68 98.57 99.44 97.84 97.54 -1.17 0.0388

BRE 99.70 100.00 99.78 100.00 98.79 98.46 -1.23 0.0322

FBXL17 100.00 100.00 98.36 99.07 98.63 98.82 -1.28 0.0473

STK11IP 100.00 100.00 96.97 100.00 98.63 98.53 -1.42 0.0224

GREB1L 100.00 100.00 100.00 97.01 98.45 98.64 -1.46 0.0415

AP1G1 100.00 99.59 97.67 100.00 98.45 98.20 -1.47 0.0397

NPEPPS 99.23 99.09 98.44 97.78 97.52 97.84 -1.48 0.0378

ODF2 99.73 100.00 99.61 100.00 98.48 98.26 -1.50 0.0150

LRP5 99.09 99.40 97.77 98.66 97.95 97.50 -1.52 0.0399

SP110 91.58 91.40 72.88 100.00 89.90 90.00 -1.54 0.0113

PIKFYVE 100.00 100.00 100.00 94.28 98.48 98.36 -1.58 0.0242

MEGF9 100.00 99.64 99.41 98.53 98.35 98.11 -1.59 0.0259

MINA 100.00 100.00 99.03 100.00 98.19 98.41 -1.70 0.0411

C6orf125 3.19 3.71 4.53 4.24 1.52 1.78 -1.80 0.0500

TUBGCP5 95.60 95.65 93.98 97.41 93.68 93.81 -1.88 0.0098

NUF2 98.49 98.86 98.28 99.48 96.68 96.79 -1.94 0.0439

KIAA1429 100.00 100.00 99.47 100.00 97.88 98.14 -1.99 0.0415

DDX18 98.71 99.29 98.65 98.48 97.33 96.67 -2.00 0.0464

FUCA1 100.00 99.34 99.32 100.00 97.77 97.31 -2.13 0.0429

XPC 99.60 100.00 98.40 98.99 97.51 97.43 -2.33 0.0465

TTC31 99.60 100.00 98.98 97.98 97.77 97.12 -2.36 0.0387

EFHA1 99.14 99.53 99.63 100.00 96.87 96.89 -2.46 0.0499

BAZ1B 2.81 3.37 2.07 2.46 0.85 0.39 -2.47 0.0229


PSIP Value

121


PICK1 100.00 100.00 98.48 99.22 97.14 97.52 -2.67 0.0452

FNBP4 96.40 96.61 94.49 95.73 94.05 93.59 -2.69 0.0263

SNX4 4.47 3.78 3.28 3.72 1.08 1.72 -2.73 0.0289

CDAN1 100.00 100.00 97.44 100.00 97.10 97.45 -2.73 0.0408

SESTD1 98.26 98.24 97.84 90.79 95.68 95.26 -2.78 0.0475

TNPO2 3.88 4.76 3.89 4.22 1.97 1.07 -2.80 0.0470

TMEM219 11.26 11.53 8.59 7.36 8.88 8.26 -2.83 0.0388

GIT1 4.69 4.48 1.99 4.55 1.48 1.99 -2.85 0.0312

TAOK2 15.33 14.85 14.03 17.34 12.37 12.07 -2.87 0.0168

XRN2 99.34 99.72 96.07 98.99 96.20 96.85 -3.01 0.0276

ANAPC4 98.98 99.55 100.00 98.25 96.54 95.80 -3.10 0.0258

TAOK3 6.02 6.59 1.59 4.17 2.70 3.67 -3.12 0.0486

ZFYVE20 96.10 95.10 94.27 89.25 92.00 92.82 -3.19 0.0417

SF3B1 4.50 5.49 5.55 4.70 2.15 1.24 -3.30 0.0396

CCDC76 100.00 100.00 100.00 100.00 96.49 96.88 -3.32 0.0374

SSX2IP 100.00 99.42 97.75 100.00 96.63 96.13 -3.33 0.0138

NSMCE1 4.41 4.98 1.64 3.33 1.61 0.98 -3.40 0.0157

POLH 97.51 97.22 94.50 96.21 93.95 93.81 -3.49 0.0087

CEP250 98.75 99.45 96.45 97.87 95.08 96.07 -3.53 0.0359

CDCA2 4.67 4.78 2.69 3.98 1.12 0.88 -3.73 0.0067

ERMP1 96.93 96.22 95.20 97.74 92.34 93.01 -3.90 0.0155

PPP2R3B 5.80 6.52 2.50 4.58 1.97 2.35 -4.00 0.0235

KIAA0391 95.25 96.57 94.34 96.30 92.36 91.30 -4.08 0.0442

PGM2 100.00 99.31 99.23 100.00 95.42 95.69 -4.10 0.0304

AATF 99.36 100.00 97.89 99.06 95.31 95.83 -4.11 0.0113

ANKRD28 99.53 100.00 97.57 97.27 95.44 95.74 -4.18 0.0084

PRTG 100.00 100.00 100.00 88.00 96.08 95.56 -4.18 0.0395

ACOT9 87.77 87.86 88.90 86.59 83.75 83.20 -4.34 0.0356

ZNF770 96.83 97.35 97.60 99.21 92.36 92.91 -4.46 0.0072

ATR 100.00 100.00 100.00 99.15 95.72 95.31 -4.49 0.0291

MYO9B 99.60 100.00 94.33 99.05 94.55 95.29 -4.88 0.0176

TMEM55A 5.49 6.84 3.01 8.80 2.02 0.51 -4.90 0.0412

MXD3 97.14 96.24 90.64 92.35 92.44 91.06 -4.94 0.0376

PCBP4 91.82 92.72 93.90 91.83 86.63 87.82 -5.05 0.0254

COL4A3BP 6.12 6.94 4.51 6.01 1.77 0.86 -5.22 0.0140

CCNE2 99.16 100.00 100.00 100.00 94.03 94.37 -5.38 0.0266

ERCC8 97.81 98.94 95.64 99.25 93.61 92.37 -5.39 0.0239

RIOK3 94.84 94.38 89.02 92.94 88.83 89.32 -5.54 0.0037

PATZ1 13.22 14.06 14.47 13.33 8.36 7.75 -5.59 0.0116

TCERG1 9.06 10.33 12.79 9.84 4.20 3.63 -5.78 0.0377

MAP3K9 100.00 100.00 97.10 100.00 94.17 94.08 -5.88 0.0049

USP40 96.03 97.99 97.59 99.05 89.89 91.88 -6.13 0.0483

BCKDHB 98.27 99.66 97.34 97.11 91.60 93.56 -6.39 0.0418

INADL 100.00 100.00 100.00 94.50 93.45 93.44 -6.56 0.0005

GOLGA5 96.53 96.94 93.24 97.33 90.50 89.81 -6.58 0.0084

WRN 100.00 98.46 94.95 97.85 93.55 91.74 -6.59 0.0328

FIBP 94.00 94.23 89.16 90.92 86.99 87.81 -6.72 0.0272

TTLL5 23.50 25.13 22.70 19.44 18.02 17.15 -6.73 0.0363

ERBB2 98.08 96.65 93.88 94.57 90.66 90.03 -7.02 0.0347

DENND1A 98.45 97.55 94.74 98.42 90.71 91.20 -7.05 0.0134

BLZF1 99.34 99.29 97.06 96.83 92.44 92.09 -7.05 0.0138


PSI

122


FBF1 93.44 91.60 96.67 95.35 84.47 85.59 -7.49 0.0324

DPY19L3 100.00 100.00 89.83 98.18 91.84 92.52 -7.82 0.0277

LRRC16A 95.83 96.26 94.44 93.58 88.17 88.24 -7.84 0.0148

SOS1 100.00 98.10 99.34 100.00 90.55 91.61 -7.97 0.0338

PTPN4 95.97 95.22 95.41 95.52 86.74 87.85 -8.30 0.0103

ALDH5A1 19.91 19.45 16.05 13.36 10.39 11.95 -8.51 0.0422

DMXL1 95.65 92.67 98.30 97.54 84.31 86.52 -8.75 0.0492

GPR89B 97.52 98.43 94.16 98.20 88.36 89.13 -9.23 0.0046

BICC1 98.80 99.19 94.56 96.80 90.22 89.06 -9.36 0.0240

POLA1 99.67 98.31 98.74 97.75 89.02 89.53 -9.72 0.0251

PWWP2A 15.97 13.11 11.36 8.72 5.60 3.85 -9.82 0.0424

VPS13D 12.24 15.06 4.21 9.75 2.54 4.56 -10.10 0.0353

MATN2 97.83 100.00 100.00 100.00 89.19 86.67 -10.99 0.0234

VPS13C 96.83 96.06 88.24 89.47 85.37 85.54 -10.99 0.0169

PPP3CB 100.00 98.24 92.55 95.11 87.68 87.27 -11.65 0.0383

USP20 95.85 95.67 94.07 94.38 83.39 84.77 -11.68 0.0347

INSIG2 100.00 100.00 95.04 100.00 87.23 88.68 -12.05 0.0383

ZDHHC13 93.24 89.64 89.32 94.27 78.06 80.10 -12.36 0.0453

MCTP1 63.06 60.19 57.26 54.85 47.88 49.61 -12.88 0.0280

SLC19A2 95.35 96.61 91.71 96.20 84.62 81.47 -12.94 0.0480

SLC25A15 100.00 98.69 93.28 96.58 87.29 85.04 -13.18 0.0190

KLHL29 98.58 98.80 95.51 100.00 84.48 86.44 -13.23 0.0446

KIAA0586 98.47 95.12 94.59 100.00 85.19 81.25 -13.58 0.0363

MAP4K4 54.68 53.07 50.81 54.89 39.80 40.34 -13.81 0.0223

TMOD1 95.47 93.40 78.55 87.62 79.18 81.97 -13.86 0.0193

CHCHD7 38.41 40.37 39.53 46.10 24.09 22.57 -16.06 0.0074

HISPPD1 41.78 44.23 38.65 34.66 26.65 26.74 -16.31 0.0474

PIAS2 88.44 92.54 91.79 80.44 76.47 71.31 -16.60 0.0412

APLP1 81.61 85.71 76.98 81.22 65.40 68.25 -16.84 0.0284

ACVR2A 100.00 100.00 87.69 100.00 83.67 82.46 -16.94 0.0227

COL27A1 96.32 100.00 90.12 94.02 82.06 77.38 -18.44 0.0285

SAP130 49.87 54.88 52.21 57.10 35.98 30.79 -18.99 0.0343

C20orf4 31.28 28.87 27.78 22.70 11.26 9.30 -19.80 0.0071

SYNJ2 98.18 97.06 100.00 93.42 78.09 75.32 -20.92 0.0215

GUF1 48.98 53.78 47.44 33.96 33.33 27.32 -21.06 0.0353

NCOR2 42.48 44.72 30.15 47.90 23.34 21.45 -21.21 0.0053

RP11-187C18.3 65.10 68.72 51.44 62.43 40.96 46.87 -23.00 0.0346

AC009086.1 38.90 35.93 40.86 39.83 15.13 11.17 -24.27 0.0131

RALGAPA2 100.00 100.00 100.00 95.35 76.67 74.19 -24.57 0.0321

ACAD10 89.47 97.66 82.55 92.94 72.09 64.56 -25.24 0.0459

CASP8AP2 97.80 93.87 80.36 86.36 72.97 68.12 -25.29 0.0168

SMEK2 50.71 50.85 46.29 34.27 26.11 23.91 -25.77 0.0266

HOXC4 36.00 42.86 30.91 59.26 8.57 13.04 -28.63 0.0291

SMPDL3A 83.72 81.20 57.89 71.11 56.36 50.00 -29.28 0.0417

MBTD1 69.62 63.64 61.45 61.90 34.51 29.20 -34.78 0.0135

FAM48A 81.22 79.73 77.21 78.24 46.84 43.35 -35.38 0.0135

RFX3 82.86 76.81 76.62 82.98 38.89 47.22 -36.78 0.0242

TMEM20 58.54 56.32 30.77 23.36 17.65 14.81 -41.20 0.0025

C13orf23 95.95 96.15 92.52 93.78 53.00 50.35 -44.38 0.0184

KIAA0240 60.00 65.08 25.00 43.21 16.28 16.67 -46.07 0.0341

CCDC150 69.77 83.91 48.28 77.05 36.26 24.68 -46.37 0.0397

ALKBH8 75.86 60.66 46.51 59.49 25.00 13.04 -49.24 0.0407

WDFY3 76.56 68.75 52.17 41.77 27.27 12.09 -52.98 0.0481


PSIP Value

123

Table II-3 Effect of 791 treatment on gene expression by RNAseq.

HeLa B2 cells were treated as described previously. Expression level of genes with DMSO, 791

or 191 treatment is quantified as corrected RPKM values (reads per kilobase of exon model per

million mapped reads) with p value by student’s t test (N = 2). Expression cutoff is 0.5 RPKM

(≥10 reads that mapped uniquely to a single genomic locus). Mean fold changes > 2 and < 0.5 or

> 5 and < 0.2 are coloured orange and red, respectively. A subset of the data is shown. Bolded

events are common to both 791 and 191 treatment samples.

Summary

Raw total count of genes: 19,847

Genes with RPKM ≥ 0.5: 11,406

Gene expression with P ≤ 0.05: 1,020

Genes with fold change ≥ 2: 60

Genes with fold change ≤ 0.5: 24


TRIB3 23.20 14.75 176.50 161.73 40.12 27.00 9.286 0.0082

GDF15 81.71 59.28 493.65 563.64 163.40 249.66 7.775 0.0321

CHAC1 1.89 1.29 10.04 11.18 5.44 3.42 6.989 0.0139

ASNS 31.53 32.92 179.31 201.11 100.84 122.33 5.898 0.0431

WARS 37.85 28.74 137.22 155.32 50.62 53.59 4.515 0.0211

ETV4 6.37 4.56 21.62 23.66 15.83 15.65 4.291 0.0066

PCK2 20.17 23.70 82.27 90.50 42.69 46.11 3.949 0.0190

ARG2 2.93 1.77 8.22 7.81 4.53 4.11 3.609 0.0425

MAP1B 1.23 0.96 3.53 4.06 2.75 2.24 3.550 0.0280

CEBPG 12.90 10.61 40.79 40.87 26.14 21.72 3.507 0.0249

PSAT1 60.90 53.67 182.93 199.37 107.97 110.20 3.359 0.0174

ABCG1 3.18 4.36 11.35 13.31 5.73 4.95 3.311 0.0293

LARP6 6.80 7.04 20.37 22.48 12.27 11.30 3.094 0.0437

PHLDA1 5.64 4.96 15.18 16.42 12.73 13.21 3.001 0.0117

HSPB6 0.67 0.70 1.86 2.04 0.97 0.64 2.845 0.0401

FAM86B2 1.86 2.21 5.71 5.78 3.47 3.58 2.843 0.0244

AARS 72.29 77.97 206.19 219.44 123.92 150.85 2.833 0.0130

NUPR1 58.16 50.86 147.17 156.22 104.32 89.40 2.801 0.0043

MORN4 1.84 2.20 5.54 5.52 3.78 2.84 2.760 0.0321

GPT2 8.41 7.13 19.45 22.45 12.10 17.81 2.731 0.0415

PHGDH 102.68 99.49 286.35 265.58 160.29 149.92 2.729 0.0338

SARS 81.23 72.14 210.52 201.93 127.28 131.46 2.695 0.0024

ABCC3 14.28 19.73 41.17 49.34 23.03 11.37 2.692 0.0392

CTH 10.06 8.74 22.83 26.42 14.90 17.60 2.646 0.0492

RNF187 45.46 38.13 109.95 108.82 56.11 53.20 2.636 0.0307

AC068020.2 0.69 1.05 1.99 2.35 1.47 0.93 2.561 0.0363

FAM86B1 6.77 7.45 18.16 17.16 10.79 5.40 2.493 0.0056

GADD45A 26.88 21.10 59.67 58.26 40.92 58.14 2.491 0.0414

TM4SF19 1.81 1.35 4.04 3.61 2.55 3.27 2.453 0.0193

RP11-121N13.3 0.64 0.92 1.70 2.04 1.67 1.12 2.437 0.0414

AC138904.2 11.31 9.67 27.21 23.76 19.09 19.84 2.431 0.0379

Gene ID

DMSO 791 191 Mean fold

change

(RPKM)

P ValueGene ID

Mean fold

changeP Value

DMSO 791 191

Gene Expression (cRPKM)

124


RBCK1 19.01 21.56 47.83 49.79 29.32 32.32 2.413 0.0042

SNX10 4.38 3.80 10.48 9.14 6.53 8.06 2.399 0.0426

TCEA1 60.01 57.30 138.64 140.08 69.97 62.91 2.377 0.0018

FAM27E2 2.61 3.77 6.80 7.97 4.99 1.61 2.360 0.0365

CARS 31.92 29.23 70.48 71.80 51.18 53.88 2.332 0.0061

SLC22A15 1.07 0.72 2.19 1.87 1.46 1.18 2.322 0.0416

LONP1 68.63 62.86 150.24 153.02 86.16 95.69 2.312 0.0064

GPCPD1 3.18 3.59 7.52 7.93 7.27 12.56 2.287 0.0044

PGPEP1 8.46 8.58 18.63 19.54 12.78 15.50 2.240 0.0250

EIF4EBP1 79.98 78.73 172.40 182.87 115.37 127.50 2.239 0.0316

PSPH 16.17 14.54 32.31 35.82 17.79 17.38 2.231 0.0292

ARHGEF2 15.36 15.55 33.31 35.38 19.79 19.14 2.222 0.0334

MLPH 1.01 0.77 2.07 1.82 1.24 1.86 2.207 0.0260

AC004490.2 1.16 0.98 2.39 2.30 1.10 0.56 2.204 0.0177

PTP4A3 2.31 2.35 4.93 5.23 5.61 6.09 2.180 0.0318

HSPA9 245.42 185.92 477.68 446.89 277.97 269.17 2.175 0.0372

TOR3A 15.69 12.50 30.79 29.70 18.70 19.07 2.169 0.0417

TIMP4 3.73 3.42 7.83 7.17 4.12 2.70 2.098 0.0247

IFRD1 60.02 67.82 134.90 131.75 92.24 139.05 2.095 0.0173

SPRED2 5.67 6.22 12.14 12.56 8.95 6.94 2.080 0.0039

C19orf57 1.48 1.08 2.43 2.68 1.12 0.55 2.062 0.0470

C2orf18 18.41 16.50 36.87 34.84 17.79 14.88 2.057 0.0058

XPOT 47.93 44.72 92.78 97.05 63.15 64.02 2.053 0.0042

C6orf48 90.19 100.40 188.58 200.03 133.24 137.29 2.042 0.0062

PCLO 0.95 0.96 2.01 1.88 1.25 1.26 2.037 0.0406

WI2-3658N16.1 14.64 17.22 31.30 33.07 13.17 7.50 2.029 0.0136

TGFA 0.96 0.80 1.78 1.74 0.62 0.94 2.015 0.0456

SLC1A5 93.82 76.59 176.05 164.57 141.31 133.62 2.013 0.0214

B3GNT5 3.06 3.61 6.23 7.15 4.68 7.09 2.008 0.0393

PLK3 2.84 2.51 5.27 5.38 6.23 8.80 2.000 0.0243

RHBDD1 3.61 4.07 7.41 7.85 5.40 5.25 1.991 0.0070

ATP6AP1L 2.33 2.98 4.92 5.50 2.63 1.97 1.979 0.0287

GCC1 7.60 7.09 15.18 13.79 8.92 8.76 1.971 0.0388

KCTD15 8.37 7.08 14.78 15.32 8.02 6.15 1.965 0.0301

WDR86 2.19 2.50 4.67 4.45 4.03 2.42 1.956 0.0105

NFIL3 12.05 10.94 22.59 22.29 14.71 24.54 1.956 0.0225

LGALS9 1.49 1.22 2.84 2.43 2.47 3.26 1.949 0.0469

SEC31B 2.97 3.05 5.67 6.06 4.43 5.82 1.948 0.0361

CCNB1IP1 31.63 33.62 61.39 65.20 45.30 47.77 1.940 0.0137

PIGZ 0.89 0.80 1.58 1.67 1.25 1.00 1.931 0.0066

ALDH2 9.10 11.50 18.23 21.31 11.87 16.53 1.928 0.0448

EDA2R 1.51 1.80 3.01 3.34 2.41 5.06 1.924 0.0211

HAUS6 12.67 12.10 24.10 23.21 16.69 16.11 1.910 0.0046

CLEC2D 1.16 1.16 2.18 2.24 1.37 0.95 1.905 0.0182

GRPEL2 7.43 6.00 13.04 12.31 12.50 16.97 1.903 0.0374

CCDC40 1.82 1.49 3.00 3.18 2.54 1.91 1.891 0.0328

GOLGA9P 1.29 1.56 2.53 2.82 1.95 2.19 1.884 0.0245

ZNF25 0.52 0.62 0.99 1.15 0.94 1.69 1.879 0.0485

KCNJ2 2.33 2.27 4.13 4.48 2.33 1.98 1.873 0.0494

P ValueGene IDDMSO 791 191 Mean fold

change Gene ID

Mean fold

changeP Value

DMSO 791 191


125


DUSP8 1.43 1.55 0.79 0.93 0.70 1.42 0.576 0.0220

C9orf3 7.53 8.45 5.07 4.02 4.54 2.82 0.575 0.0400

CSRP2 55.89 54.82 30.49 33.02 46.40 59.17 0.574 0.0153

TAGLN2 352.40 354.27 214.11 190.98 353.61 472.42 0.573 0.0474

PDGFD 2.35 2.61 1.53 1.28 1.86 1.18 0.571 0.0271

NEXN 10.31 10.61 5.72 6.18 7.02 5.37 0.569 0.0068

MKL1 13.58 14.49 8.02 7.76 9.79 8.76 0.563 0.0336

PDGFRL 9.49 9.52 5.51 5.15 6.52 5.65 0.561 0.0264

SETBP1 1.58 1.81 0.85 1.05 0.92 0.66 0.559 0.0409

P2RY6 17.64 17.77 9.36 10.32 12.33 12.64 0.556 0.0356

PTRF 90.53 85.28 52.52 45.24 64.09 54.65 0.555 0.0172

MPPED2 12.35 13.74 6.88 7.54 8.43 4.65 0.553 0.0399

F2R 50.96 54.21 28.45 29.47 40.88 23.43 0.551 0.0288

SAMD14 1.40 1.40 0.78 0.76 1.25 0.50 0.550 0.0101

PROC 1.67 1.82 0.99 0.90 1.67 1.01 0.544 0.0213

TRIM5 5.68 6.07 3.09 3.26 4.28 5.45 0.541 0.0220

CYTH3 25.06 26.27 13.78 13.70 26.12 21.88 0.536 0.0316

MAP3K14 15.76 15.99 8.59 8.30 12.18 9.88 0.532 0.0008

SMTN 11.54 10.02 6.34 5.08 10.91 13.20 0.528 0.0385

ATP8B1 1.40 1.31 0.78 0.65 1.84 1.37 0.527 0.0208

USP43 1.86 2.04 0.89 1.17 1.60 1.11 0.526 0.0438

APOBEC3B 15.07 13.73 8.21 6.81 12.20 9.99 0.520 0.0193

CALD1 49.49 52.98 28.16 24.92 45.68 35.17 0.520 0.0093

CGN 2.51 2.48 1.21 1.38 1.86 1.39 0.519 0.0393

CAP2 13.18 12.19 6.21 6.88 8.95 6.56 0.518 0.0142

PRRX2 16.83 19.40 9.88 8.48 14.03 9.25 0.512 0.0460

DNMT3L 1.83 2.10 1.04 0.90 1.20 1.07 0.498 0.0441

IDI1 29.45 31.17 13.51 16.55 16.39 40.81 0.495 0.0251

PPP1R13L 30.53 33.16 15.94 15.16 35.80 29.49 0.490 0.0362

MYL9 134.60 116.42 67.03 54.32 153.15 109.37 0.482 0.0360

S100A10 202.14 192.72 105.38 81.16 165.12 161.70 0.471 0.0463

CDKN2AIP 13.14 14.08 6.15 6.57 10.26 8.71 0.467 0.0184

GDPD5 7.06 6.67 3.54 2.81 6.31 3.18 0.461 0.0267

FZD2 25.81 26.93 12.29 11.76 21.98 17.31 0.456 0.0082

APBB1 4.04 4.41 1.76 2.10 2.46 1.69 0.456 0.0120

ZNF488 1.79 1.63 0.89 0.67 1.97 1.62 0.454 0.0261

NUAK2 5.15 6.01 2.09 2.82 4.61 4.40 0.438 0.0329

CITED2 50.54 48.51 19.77 23.16 17.34 19.88 0.434 0.0105

GRAMD3 3.89 3.37 1.73 1.42 3.97 2.87 0.433 0.0347

CACNG4 3.73 3.22 1.85 1.18 3.46 1.41 0.431 0.0491

CAV1 54.45 48.76 24.86 18.51 45.74 27.64 0.418 0.0203

TAGLN 5.94 6.54 2.32 2.86 6.26 7.92 0.414 0.0124

C19orf21 16.31 17.87 5.87 7.62 15.45 16.18 0.393 0.0131

COL9A3 7.39 6.11 3.20 1.95 4.79 1.67 0.376 0.0430

CTGF 302.98 363.04 94.56 156.20 95.80 44.77 0.371 0.0404

CYR61 633.51 653.94 215.14 260.35 248.87 146.23 0.369 0.0146

CRISPLD2 2.02 1.85 0.72 0.70 3.42 4.46 0.367 0.0415

TMEM139 9.82 10.34 3.15 4.17 5.18 2.87 0.362 0.0205

CSDC2 13.86 15.78 6.05 4.53 13.43 6.57 0.362 0.0186

GPR146 2.16 2.36 0.62 0.86 0.89 1.18 0.326 0.0115


change Gene ID

Mean fold

changeP Value

DMSO 791 191


126

Table II-4 Effect of 191 treatment on gene expression by RNAseq.

HeLa B2 cells were treated as described previously. Expression level of genes with DMSO, 791

or 191 treatment is quantified as corrected RPKM values (reads per kilobase of exon model per

million mapped reads) with p value by student’s t test (N = 2). Expression cutoff is 0.5 RPKM

(≥10 reads that mapped uniquely to a single genomic locus). Mean fold changes > 2 and < 0.5 or

> 5 and < 0.2 are coloured orange and red, respectively. A subset of the data is shown. Bolded

events are common to both 791 and 191 treatment samples.

Summary

Raw total count of genes: 19,847

Genes with RPKM ≥ 0.5: 11,406

Gene expression with P ≤ 0.05: 540

Genes with fold change ≥ 2: 21

Genes with fold change ≤ 0.5: 32


AL138831.1 0.51 0.53 1.10 0.80 2.17 2.12 4.127 0.0032

TMEM178 0.70 0.54 2.03 2.97 2.11 2.51 3.831 0.0462

ADM2 1.95 1.70 10.48 12.72 4.82 4.91 2.680 0.0134

FBXO36 1.04 0.86 1.75 1.35 2.74 2.33 2.672 0.0480

MICAL2 1.31 1.27 1.41 1.56 3.20 3.34 2.536 0.0142

PTP4A3 2.31 2.35 4.93 5.23 5.61 6.09 2.510 0.0420

ZNF177 0.95 0.90 1.62 1.27 2.19 2.38 2.475 0.0330

PHLDA1 5.64 4.96 15.18 16.42 12.73 13.21 2.460 0.0047

PER2 1.50 1.66 1.50 1.28 3.75 3.93 2.434 0.0030

ZNF805 1.10 0.85 1.53 1.12 2.01 2.30 2.267 0.0267

SLC2A4 1.35 1.19 0.90 0.58 2.86 2.56 2.135 0.0289

RGPD8 3.72 3.68 6.32 5.41 8.13 7.60 2.125 0.0394

AC009133.2 0.87 0.73 1.31 1.22 1.76 1.61 2.114 0.0134

NT5DC3 2.19 2.22 2.73 2.69 4.77 4.46 2.094 0.0392

FAM176B 1.08 1.05 1.37 1.42 2.12 2.28 2.067 0.0384

C3orf71 1.25 1.59 2.37 2.98 2.70 3.13 2.064 0.0358

CCDC88B 3.41 2.68 4.64 3.39 6.58 5.87 2.060 0.0247

CTC-241N9.1 1.22 1.37 2.44 2.33 2.78 2.51 2.055 0.0259

TMEM231 2.66 3.08 4.65 4.61 5.84 5.75 2.031 0.0375

PCK2 20.17 23.70 82.27 90.50 42.69 46.11 2.031 0.0118

ZNF441 2.03 1.61 2.72 2.62 3.54 3.73 2.030 0.0402

SESN2 4.81 4.08 15.86 19.31 8.01 9.21 1.961 0.0419

SPOCD1 0.65 0.82 1.57 2.24 1.46 1.35 1.946 0.0323

ZBTB6 5.87 5.04 7.28 6.06 10.11 10.91 1.943 0.0128

ANKRD9 17.31 14.33 16.37 19.01 29.52 31.22 1.942 0.0260

ZNF555 0.63 0.53 0.82 0.66 1.05 1.17 1.937 0.0228

PSAT1 60.90 53.67 182.93 199.37 107.97 110.20 1.913 0.0297

GARS 110.53 85.61 239.79 240.42 176.43 190.82 1.913 0.0445

AC138904.2 11.31 9.67 27.21 23.76 19.09 19.84 1.870 0.0287

AC073995.2 13.55 13.41 14.79 15.37 25.12 24.53 1.842 0.0116

EIF4A2 95.46 125.19 120.27 125.03 188.24 214.22 1.842 0.0456

P ValueGene ID

DMSO 791 191 Mean fold

change

(RPKM)Gene ID

Mean fold

changeP Value

DMSO 791 191


127


ATP6V0E1 81.07 85.53 82.40 92.03 49.59 46.31 0.577 0.0083

NT5DC2 146.26 140.50 92.31 97.97 83.08 82.19 0.577 0.0267

MFSD11 7.63 8.51 7.95 9.86 4.88 4.35 0.575 0.0347

MLF1IP 11.23 10.50 9.36 11.71 6.52 5.85 0.569 0.0113

YJEFN3 1.59 1.61 1.58 2.10 0.91 0.91 0.569 0.0092

FBXO9 18.86 20.02 20.62 24.12 11.28 10.66 0.565 0.0153

TMEM140 7.75 8.58 10.66 12.80 4.82 4.30 0.562 0.0283

AC006486.1 1.16 1.08 0.73 0.81 0.65 0.60 0.558 0.0158

SLC35E3 4.26 4.66 3.63 4.43 2.61 2.31 0.554 0.0189

PARP12 1.88 2.15 1.51 1.87 1.18 1.01 0.549 0.0419

UPRT 3.67 3.86 3.54 4.43 2.18 1.93 0.547 0.0105

CHML 14.96 16.18 9.81 13.93 8.62 8.05 0.537 0.0250

C1orf145 1.34 1.17 1.64 1.71 0.74 0.61 0.537 0.0374

SGK1 101.75 118.62 73.67 77.05 52.87 65.64 0.536 0.0465

TCF7 9.69 11.25 6.60 8.94 6.29 4.69 0.533 0.0469

SIRPA 1.59 1.48 1.53 1.74 0.89 0.72 0.523 0.0280

SAMHD1 20.08 22.11 16.54 18.04 12.19 9.26 0.513 0.0367

WWP2 9.06 10.33 7.98 8.18 5.45 4.11 0.500 0.0337

RBM12 20.08 21.73 12.29 15.95 9.31 11.28 0.491 0.0157

GPR75 1.01 1.10 0.76 1.08 0.50 0.53 0.488 0.0346

C9orf156 5.88 5.64 5.73 6.45 2.96 2.62 0.484 0.0074

AL353791.1 6.86 7.63 3.87 6.53 3.35 3.65 0.483 0.0395

LMAN2L 9.97 11.04 8.93 10.67 5.40 4.57 0.478 0.0175

SETBP1 1.58 1.81 0.85 1.05 0.92 0.66 0.473 0.0360

RDH5 1.65 1.72 1.49 1.92 0.80 0.75 0.460 0.0035

GPR146 2.16 2.36 0.62 0.86 0.89 1.18 0.456 0.0272

MED17 12.18 11.52 10.94 11.12 5.63 5.18 0.456 0.0064

MEIS2 11.05 12.90 8.39 9.01 6.02 4.69 0.454 0.0353

DUSP1 382.44 368.48 278.63 269.45 175.44 164.85 0.453 0.0026

BRMS1L 5.04 4.71 3.49 4.02 2.52 1.90 0.452 0.0342

CCDC103 2.45 2.48 2.83 2.07 1.21 1.00 0.449 0.0450

C12orf26 1.57 1.82 1.01 1.40 0.84 0.65 0.446 0.0309

C7orf31 1.46 1.61 1.49 1.80 0.77 0.57 0.441 0.0246

SECTM1 8.84 9.94 7.56 7.61 4.28 3.93 0.440 0.0467

ZBED1 17.73 18.91 11.40 13.10 9.01 6.84 0.435 0.0284

NMI 1.84 2.05 1.83 2.41 0.91 0.76 0.433 0.0178

PHTF1 7.32 8.57 5.75 8.21 3.79 2.93 0.430 0.0347

AMIGO3 3.30 2.81 2.59 2.87 1.37 1.13 0.409 0.0466

AMH 5.88 6.43 5.71 7.83 2.90 2.05 0.406 0.0276

TMEM133 2.29 2.15 1.55 1.46 1.07 0.74 0.406 0.0475

C21orf67 1.50 1.63 2.28 2.65 0.75 0.50 0.403 0.0427

CITED2 50.54 48.51 19.77 23.16 17.34 19.88 0.376 0.0034

HYAL3 5.15 5.61 4.82 5.88 2.15 1.88 0.376 0.0132

AMOTL2 31.89 39.43 12.75 18.50 15.87 9.83 0.373 0.0460

SLC22A3 4.57 5.50 3.22 3.05 2.28 1.29 0.367 0.0413

C12orf4 4.38 4.09 3.94 3.59 1.83 1.17 0.352 0.0437

C5orf36 2.20 2.71 1.64 0.97 0.81 0.52 0.280 0.0436

CTGF 302.98 363.04 94.56 156.20 95.80 44.77 0.220 0.0232

NCOA5* 18.36 16.98 15.16 13.76 5.17 1.77 0.193 0.0464


change Gene ID

Mean fold

changeP Value

DMSO 791 191


Identification of Novel Compounds That Inhibit HIV-1 Gene … · 2016. 11. 20. · Expression by...

Documents

Transcript of Identification of Novel Compounds That Inhibit HIV-1 Gene … · 2016. 11. 20. · Expression by...