Caffeine modulates post-transcriptional regulation of SRSF2

1

Methylxanthines Increase Expression of the Splicing Factor SRSF2 by Regulating Multiple

Post-Transcriptional Mechanisms

Jia Shi, Kirk Pabon, Kathleen W. Scotto1

From the Rutgers Cancer Institute of New Jersey,

the Robert Wood Johnson Medical School and the Graduate School of Biomedical Sciences

Rutgers, The State University of New Jersey, New Brunswick, NJ 08903

*Running title: Caffeine modulates post-transcriptional regulation of SRSF2

To whom correspondence should be addressed: Kathleen W. Scotto. Rutgers Cancer Institute of New

Jersey, Rutgers, the State University of New Jersey, 195 Little Albany Street, New Brunswick, NJ 08903,

USA, Tel: (732) 235-4266; Fax: (732)-235-6596; Email: scottoka@cinj.rutgers.edu

Keywords: SRSF2, alternative splicing, microRNA, caffeine, methylxanthines, translational efficiency,

nonsense-mediated decay, homeostasis

Background: Caffeine regulates alternative

splicing by increasing SRSF2, normally

constrained by a negative feedback loop.

Results: Caffeine blocks nonsense-mediated

decay, induces 3’UTR alternative splicing, and

down-regulates SRSF2-targeting microRNAs,

thereby breaking the negative feedback loop to

increase SRSF2.

Conclusion: Caffeine modulates multiple post-

transcriptional processes to increase SRSF2.

Significance: This study expands our

understanding of SRSF2 regulation, and may

provide insight into SRSF2 dysregulation in

disease.

ABSTRACT

We have previously reported that the

methylxanthine caffeine increases expression

of the splicing factor SRSF2, the levels of

which are normally controlled by a negative

auto-regulatory loop. In the present study we

have investigated the mechanism by which

methylxanthines induce this aberrant

overexpression. RT-PCR analyses suggested

little impact of caffeine on SRSF2 total

mRNA levels. Instead, caffeine induced

changes in the levels of SRSF2 3ʹUTR splice

variants. While some of these variant were

substrates for nonsense-medicated decay

(NMD), and could potentially have been

stabilized by caffeine-mediated inhibition of

NMD, downregulation of NMD by a genetic

approach was not sufficient to reproduce the

phenotype. Furthermore, cell-based assays

demonstrated that some of the caffeine-

induced variants were intrinsically more

efficiently translated than others; the

addition of caffeine increased the

translational efficiency of most SRSF2

transcripts. MicroRNA array analyses

revealed a significant caffeine-mediated

decrease in the expression of two SRSF2-

targeting miRs, both of which were shown to

repress translation of specific SRSF2 splice

variants. These data support a complex

model whereby caffeine downregulates

SRSF2-targeting microRNAs, leading to an

increase in SRSF2 translation, which in turn

induces SRSF2 splicing. SRSF2 splice

variants are then stabilized by caffeine-

mediated NMD inhibition, breaking the

normal negative feedback loop and allowing

the aberrant increase in SRSF2 protein levels.

These findings highlight the complexity of

SRSF2 gene regulation, and suggest ways in

which SRSF2 expression may be dysregulated

in disease.

Alternative splicing (AS) of pre-mRNA is a

fundamental cellular process that selectively

joins alternate exons together to produce

different mRNA variants from a single gene.

More than 90% of human genes undergo

alternative splicing, resulting in strikingly high

levels of mRNA complexity (1-3). In some

cases, AS leads to the selective inclusion or

http://www.jbc.org/cgi/doi/10.1074/jbc.M114.624254The latest version is at JBC Papers in Press. Published on March 28, 2015 as Manuscript M114.624254

Copyright 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

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Caffeine modulates post-transcriptional regulation of SRSF2

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skipping of one or more protein-coding exons,

resulting in functionally different protein

isoforms with altered domains; this contributes

significantly to proteomic diversity. In other

cases, untranslated regions (UTRs) are altered or

premature termination codons (PTCs) are

introduced by AS, thereby generating complex

mRNA populations that are substrates for post-

transcriptional regulation at the level of

translational efficiency, mRNA localization

and/or mRNA stability (4-7).

The potential for AS to exert a complex and

profound effect on gene expression requires that

tightly controlled regulatory processes are in

place. This control is primarily executed by

positively- or negatively-acting splicing factors

that bind to cis-elements within pre-mRNA near

the regulated splice sites, modulating their

recognition efficiency by the multi-protein

spliceosome (8). Two major families of splicing

factors have been characterized: the

serine/arginine-rich (SR) protein family and the

HnRNP protein family, while additional RNA-

binding proteins have also been identified

(9,10). Splicing factors work antagonistically

such that their relative concentration in a given

cell is a critical determinant of the fate of

targeted exons (11,12). Accordingly, under

steady-state conditions the relative levels of

splicing factors are expected to remain constant,

while intrinsic (i.e. during differentiation and

development) or extrinsic (i.e. environmental

cues, stressor) signals can alter this ratio, thereby

altering AS choices and, potentially, cell fate.

An additional layer of control is exerted by

nonsense-mediated decay (NMD), an RNA

surveillance system that ensures the fidelity of

gene expression by degrading non-productive

mRNAs containing premature termination

codons (PTCs)(13), including those produced by

AS. Recent genome-scale studies revealed that

many splicing regulators employ a dual

mechanism, alternative splicing coupled with

nonsense-mediated decay (AS-NMD), to limit

their own expression and prevent excessive

accumulation that can be deleterious to the cell

(14,15).

SRSF2 (SC35) is a ubiquitous splicing factor

that plays a critical role in both constitutive and

alternative splicing (16,17), most often

functioning as an activator to enhance the

recognition of particular splice sites. Studies

using SRSF2 conditional knockout mice and

SRSF2-/-

MEFs have suggest that this protein is

essential for cell proliferation and the

maintenance of genomic stability, at least during

thymus and pituitary development (18). It was

also suggested that SRSF2 plays a role in the

regulation of transcription elongation (19,20).

Additionally, transcription of SRSF2 has been

shown to be regulated by E2F1, and is required

for E2F1-induced apoptosis (21). Alkylating

agent-induced apoptosis was shown to be

accompanied by a significant increase in both

E2F1 and SRSF2, suggesting a possible role for

SRSF2 in genotoxic stress response (21).

Interestingly, a recent study suggested that

SRSF2 is the most enriched splicing factor in

human pluripotent stem cells, where SRSF2 is

regulated by OCT4 and required for

pluripotency via its ability to regulate the AS of

MBD2, the methyl-CpG binding protein (22).

Given the key role of SRSF2 in multiple

regulatory pathways, its dysregulation is likely

to be pathological; indeed, several studies have

identified a strong correlation between SRSF2

mutations and subclassification and

prognostication of myelodysplastic syndrome

(MDS), a heterogeneous group of myeloid

neoplasms that predispose to acute myeloid

leukemia (23-26).

SRSF2 levels are carefully controlled. In

addition to transcriptional regulatory controls,

SRSF2 RNA is subjected to negative auto-

regulation via AS-NMD (27). In this scenario,

when levels of SRSF2 protein exceed the

tolerable cellular threshold, SRSF2 induces

alternative splicing of its own transcript,

resulting in the expression of two novel PTC-

containing splice variants at the expense of the

primary SRSF2 transcript. These variants are

destined for degradation by NMD; through this

feedback loop, overall SRSF2 mRNA levels are

reduced and SRSF2 protein expression returns to

steady state levels (27). Although a recent

study suggested that both HnRNP H and

TARDBP (TDP-43) act as antagonists to SRSF2

in regulating a retained intron in this

unproductive alternative splicing at the 3’UTR

(28), the complexity of SRSF2 mRNA variant

formation, its regulation and the functional

implications are poorly understood.

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We have previously shown that caffeine can

alter the AS of a subset of genes associated with

the cancer phenotype. This is accomplished, at

least in part, by the induction of high levels of

SRSF2 (29). In the present report we extend our

analyses by addressing the mechanism(s) that

lead to increased levels of SRSF2 protein. We

now show that this caffeine-mediated SRSF2

increase involves a complex series of events that

includes down-regulation of SRSF2-targeting

microRNAs, inhibition of NMD, and induction

of novel SRSF2 splice variants with altered

translational efficiency. As a consequence, the

SRSF2 negative feedback loop is broken,

allowing for sustained increase of SRSF2

protein in the cell. This study advances our

understanding of SRSF2 gene regulation,

highlighting the multifaceted mechanisms at the

post-transcriptional level that regulate SRSF2-

mediated AS decisions, and provides a basis to

investigate dysfunction of AS during

pathogenesis.

EXPERIMENTAL PROCEDURES

Cell culture and chemical reagents -- The

human cervical carcinoma HeLa cells line

(ATCC®, CCL-2) was maintained in DMEM

supplemented with 10% (v/v) FBS and 2.0 mM

glutamine. Caffeine and cycloheximide were

purchased from Sigma and prepared

immediately prior to use.

Cytotoxicity Assay – HeLa cells were seeded

in 96-well plates at a density of 7,500 cells per

well. Various concentrations (1.75 ~21 mM) of

xanthine derivatives, including caffeine,

pentoxifylline, theophylline, and isocaffeine,

were added to wells with 8 repeats for each

experimental condition. MTT assays were

performed three days after treatment following

manufacturer’s instructions (Promega).

Semi-quantitative RT-PCR Assays -- Total

RNA was prepared with Trizol reagent

(Invitrogen) and analysed using SS One-step

RT-PCR reagents (Invitrogen) according to the

manufacturer’s recommendations. RNAse-free

DNAse I treatment was performed when needed.

The initial RNA input was 300 ng, and the

number of amplification cycles was pre-

determined to ensure a linear range

amplification of targeted transcripts (28 cycles

to assay total SRSF2 mRNA levels, 40 cycles to

assay individual transcript groups including GA,

GB, GC, and GD. Primers for SRSF2 total

mRNA: a: 5’-CTG AGG ACG CTA TGG ATG

CCA-3’ ; b: 5’-GAC TTG GAC TTG GAC CTT

CGT-3’; Primers for SRSF2 3’UTRs: c: 5’-CCA

AGT CTC CTG AAG AGG AAG G-3’; d: 5’-

CTG AGA AAA GCT AAC ACC AAG-3’; e:

5’-GAA AAT GGT AAT GTC TGG GAA TC-

3’; f: 5’-GTC AGG AGG CCA CAA ATT

AGG-3’.

Real-time quantitative RT-PCR -- Purified

RNA was first treated with RNAse-free DNase I

and then reverse-transcribed into cDNA using

the High-Capacity cDNA Reverse Transcription

Kit (AB Applied Biosystems/Life Technologies)

following manufacturer’s instructions. Real-

time PCR was performed using SYBR® Green

PCR Master Mix (AB Applied Biosystems/Life

Technologies) and individually designed primer

sets. For total SRSF2 mRNA, sense: 5’-CTG

AGG ACG CTA TGG ATG CCA-3’; antisense:

5’-GAC TTG GAC TTG GAC CTT CGT-3’; for

β2M, the same as previously reported (29); for

Flag-SRSF2, sense: 5’-CGA CTC ACT ATA

GGG AGA CC-3’, antisense: 5’-GAG GTG

CGG TAG GTC AGG TT-3’; for GFP, sense:

5’- GGG TGA AGG TGA TGC AAC ATA C-

3’, antisense: 5’- CTC GCA AAG CAT TGA

ACA CCA-3’. The final Ct value was an

average of 3 repeats of each assay, repeated

three times. The relative amount of mRNA in

samples was determined using the 2-ΔΔCt

method.

RNA Interference Assay -- 3 X 104 HeLa

cells in 0.5-mL DMEM without antibiotics were

seeded into each well of a 24-well plate and

incubated overnight. 100 nM siRNA

(SiGENOME SMARTpool reagent,

DHARMACON) was mixed with

Oligofectamine reagent (Invitrogen), incubated

at room temperature for 20 min and added drop-

wise to cells. 72 hours after siRNA transfection,

cells were harvested for either RNA isolation or

whole cell lysates, and assayed by either RT-

PCR or Western blot analysis.

Western Blot Analysis -- Cells were washed

twice with cold PBS and lysed in RIPA buffer

(50 mM Tris- HCl, pH 7.4, 150 mM NaCl, 1.0%

Triton X-100, 0.1% SDS, 1% deoxycholate plus

protease inhibitor cocktail (Roche Diagnostics),

1 mM sodium fluoride, 1 mM sodium

orthovanadate, and 100 mg/ml

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Caffeine modulates post-transcriptional regulation of SRSF2

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phenylmethylsulfonyl fluoride. The protein

concentration of cell lysates was determined

using the Pierce BCA protein assay. Equal

amounts of total protein (15-25 ug) were

analyzed by 10% SDS-PAGE followed by

immunoblotting using the following antibodies:

rabbit anti-TARBP (GeneTex, 1:1000), mouse

anti-HnRNP F/H (Abcam, 1: 1000), goat anti-

hUpf1 (Abcam, 1:1000), mouse anti- SRSF2

(provided by Drs Cyril Bourgois and James

Stevenin, 1:20), mouse anti-Flag (Agilent,

1:2000) or mouse anti-tubulin (Santa Cruz

Biotechnology, 1:1000). The secondary

antibody was either HRP-conjugated donkey

anti-goat IgG (Santa Cruz Biotechnology,

1:2500), HRP-conjugated goat-anti-rabbit IgG

(Santa Cruz Biotechnology, 1:2500), or HRP-

conjugated goat-anti-mouse IgG (Upstate

Technology, 1:2500). Immunoreactive bands

were visualized using the Visualizer™ Western

Blot Detection Kit (Upstate Technology)

following manufacturer’s directions.

SRSF2 transcript expression vectors --

SRSF2 cDNAs with variations in their 3’UTR

were amplified by RT-PCR as described in

Results and Figures using primers with

restriction enzyme linker EcoR I (attached to

primers c and e) and Xba I (attached to primers

d and f). Each of the RT-PCR products were

gel-purified and digested with EcoR I and Xba I,

then individually cloned into pcDNA3.1-Flag-

SRSF2 downstream of the SRSF2 coding

region. Resulting constructs (pcDNA3.1-Flag-

SRSF2-3’UTRs: A1, A2, A3, D1, D2, D3, etc.)

were verified by sequencing.

In vitro translation assay -- Equal amounts

(125 ng) of each SRSF2 splice variant construct

(A1,A2, A3, D1, D2, or D3) was assayed in the

presence of EasyTag™ L-[35

S]-Methionine

(PerkinElmer) using the TNT® Quick Coupled

Transcription/translation System (Promega).

Translated protein was analyzed by SDS-PAGE

followed by radiography using the Bio-Rad

phosphor Imager. Signals were quantified using

Bio-Rad Quantity One software.

Cell-based translational assa -- HeLa cells

were seeded at 1.25 X 105 cells per well in 12-

well plates. The next day 200 ng plasmid DNA

of each SRSF2 variant construct was

individually co-transfected with 37.5 ng plasmid

DNA of GFP construct (pN3-GFP) in duplicate

using Lipofectamine 2000 (Invitrogen). Seven

hours post- transfection, cells were untreated or

treated with caffeine; 3 hrs later, cells were

collected from each well and divided in half.

One half was dissolved in RIPA buffer for

western blot analysis using anti-Flag (Agilent,

1:2000) and anti-GFP antibodies (Santa Cruz

Technologies, 1:500) in a single procedure. The

other half was subjected to RNA purification

using trizol (Invitrogen) for real-time RT-PCR

analyses of Flag-SRSF2 and GFP mRNAs.

Translational efficiency was determined by

normalizing Flag-SRSF2 expression levels to

corresponding GFP levels.

MicroRNA (miR) array analysis -- HeLa

cells were treated with caffeine (14 mM) for

either 3 hrs or 24 hrs. Treated samples and

untreated controls were collected for total RNA

using miRCURYTM

RNA Isolation Kits

(Exiqon), and labeled with appropriate dyes

using miRCURY LNATM

microRNA Array Hi-

power Labeling Kit. The miRCURY LNATM

microRNA Array, v11.0-human, was the

platform utilized. Hybridization and processing

of arrays were performed by the CINJ DNA

Core Facility. Each experimental condition was

repeated 6 times including three biological

replicates and two technical replicates for each

biological replicate. The average signal density

was normalized by standard protocols (CINJ

Bioinformatics Core Facility) as well as internal

controls provided on the miRCURY LNATM

microRNA Array platform using miRCURY

LNATM

microRNA Array Analysis software.

miR qRT-PCR -- Total RNA was isolated

using miRCURYTM

RNA Isolation Kits

(Exiqon), and cDNA was prepared using the

Universal cDNA Synthesis Kit (Exiqon)

following manufacturers’ instructions.

Individually pre-designed LNA™-enhanced

microRNA qPCR primer sets were purchased

from Exiqon. qPCR was performed using

SYBR® Green Master Mix Kit (Exiqon) and a

Stratagene MX3000p qPCR system. RNA input

was normalized by U1 snRNA and SNORD49a.

RT-PCR efficiency was normalized using the

RNA Spike-in kit (Exiqon). The final Ct value

was an average of 5 repeats of each assay,

repeated three times. The relative amount of

mRNA in samples was determined using the 2-

ΔΔCt method.

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Anti-miR and miR-mimic co-transfections--

HeLa cells were seeded at ~80,000 cells/well in

12-well plates and incubated overnight. Either

mirVana™ miRNA mimics or inhibitors

(Ambion, Invitrogen), at 30~50 nM (determined

empirically), were co-transfected with 150 ng of

indicated SRSF2 3’UTR plasmid DNA as well

as 37.5 ng of a GFP expression construct (pN3-

GFP). Lipofectamine 2000 reagent (Invitrogen)

was used following manufacturer’s instructions.

18~22 hrs after transfection, whole cell lysates

were collected for western blot analyses of Flag-

SRSF2 expression. GFP was used to control for

transfection efficiency.

To assay the effect of anti-miR and miR

mimics on SRSF2 expression, HeLa cells were

seeded at ~80,000 cells/well in 12-well plates

and incubated overnight. For miR mimics

experiment, 45nM of mirVana™ miRNA mimic

(Ambion, Invitrogen) was co-transfected with

the KLF6 minigene (29) as described. Caffeine

was added 18 hrs after transfection, and 10 hrs

later, cells were harvested for either western blot

analysis of SRSF2 expression or RT-PCR of

KLF6. For miR inhibitor experiments, 45nM of

mirVana™ miRNA inhibitor (Ambion,

Invitrogen) was co-transfected with hSMG-1

siRNA (100 nM, Dharmacon, GE Healthcare)

and the KLF6 minigene as described. Following

a 46-hr incubation, cells were harvested for

western blot analysis and RT-PCR performed as

above.

Statistical analysis -- All statistical analyses

were performed using GraphPad PRISM version

6 software, nonparametric t tests. A difference

with a p value < 0.05 was considered significant.

Error bars represent the mean ± SD.

RESULTS

Methylxanthines differentially induce KLF6

splice variants and increase levels of SRSF2

protein. We have previously reported that

caffeine, a tri-methylxanthine derivative, can

induce alternative splicing of a subset of cancer-

associated genes, including the tumor suppressor

gene KLF6. This induction is due, at least in

part, to a caffeine-mediated increase (up to 6-

fold) of the splicing factor SRSF2. In HeLa

cells this increase can be observed as early as 1

hour post caffeine treatment and is sustained for

at least 24 hours (29). To evaluate the impact of

other members of this class on splicing, we

examined the ability of several xanthine

derivatives, including pentoxifylline, caffeine,

theophylline, and isocaffeine, on induction of

the KLF6 splice variant, SpKLF6 (Figure 1A).

Within 18hrs of treatment, pentoxifylline

exhibited the strongest induction among the

group, followed by caffeine and theophylline.

Isocaffeine had minimal effect on SpKLF6

expression. This corresponded to the degree of

induction of SRSF2 by these compounds (Figure

1B), further supporting our observation that

caffeine-induced SpKLF6 expression is

mediated by SRSF2. Although pentoxifylline

induced the highest level of SRSF2, it also

caused severe cell death at the concentrations

used (14 mM) (Figure 1C). Therefore, caffeine

was used as the model drug to investigate the

mechanisms by which methylxanthines increase

SRSF2.

Caffeine does not impact total SRSF2 mRNA

levels. To investigate the molecular basis for the

increase in SRSF2 protein, we first considered

the possibility that caffeine was working at the

level of SRSF2 transcription. To evaluate this,

we employed both semi-quantitative and

quantitative RT-PCR to examine the total

SRSF2 mRNA following caffeine treatment.

Previous studies have described three SRSF2

transcripts that differ in the splicing of exon 3

(E3) and/or intron 4/5 (I4/5) at the 3’UTR

(Figure 2A) (27). Public databases (NCBI-

Aceview and Ensembl) suggested the existence

of additional splice variants of SRSF2 mRNA

that differ in their 3’UTR splicing choices and

polyadenylation sites (Figure 2A).

Interestingly, there are no alternative splice sites

documented within the SRSF2 coding region

that spans Exon 1 (E1) and 2 (E2), indicating

that both the known and predicted SRSF2

transcript variants would encode the same

protein. To account for all known and predicted

transcripts, primers located within the two

protein coding exons, E1 and E2 (Figure 2A,

primers ―a‖ and ―b‖), were chosen for analysis

of RNAs isolated from HeLa cells either

untreated or treated with caffeine for times

indicated. After careful linear range

optimization and quantitative analyses, both

semi-quantitative RT-PCR (Figure 2B) and

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quantitative RT-PCR (Figure 2C) identified no

significant change in total SRSF2 mRNA

following caffeine treatment, suggesting that

caffeine regulates SRSF2 protein levels post-

transcriptionally.

Caffeine influences splicing decisions at the

SRSF2 3’UTR. Since there was no apparent

increase in total SRSF2 mRNA levels

concomitant with the caffeine-induced increase

in SRSF2 protein, and cycloheximide

experiments did not indicate a caffeine-mediated

change in SRSF2 protein stability (data not

shown), we next considered the possibility that

caffeine may impact SRSF2 splicing choices at

the 3’UTR, yielding transcripts with different

stability and/or translatability.

Four possible groups of SRSF2 transcripts

have been either described before or predicted

by the aforementioned databases. The major

SRSF2 transcript (hereafter referred to as A1)

includes the canonical E1, E2 and

polyadenylation site, but skips E3 and retains

intron 4/5 (Figure 3A, diagram). Two additional

SRSF2 transcripts, A2 and A3, can be induced

by high levels of SRSF2 protein via AS at the

3’UTR (Figure 3A, diagrams). Since A2 and A3

each contain a PTC, they are potential substrates

for NMD (27,30) and therefore can be quickly

degraded to restore normal levels of SRSF2

protein. Together, we refer to these mRNAs as

Group A (GA) transcripts. The predicted Group

B (GB) transcripts are similar to GA transcripts

in that they skip E3, but they utilize an alternate

polyadenylation site (Figure 3B, diagram).

Group C (GC) transcripts are predicted to

resemble GA transcripts in that they use the

canonical polyadenylation site, but contain an

elongated E2 due to differential utilization of the

E2 5’ splice site (Figure 3C, diagram). Finally,

predicted Group D (GD) transcripts resemble

GC transcripts in their E2 5’splicing but use the

alternative polyadenylation site (Figure 3D,

diagram).

To systematically examine the impact of

caffeine on all the identified and predicted

variants of SRSF2 RNA, multiplex RT-PCR

assays were developed to detect transcripts in

the four distinct groups in untreated and

caffeine-treated HeLa cells. Multiplex RT-PCR

using primer ―c‖ and ―d‖ was used to detect the

GA transcripts. Following a one hour exposure

to caffeine, a ―switch‖ in the expression of

splice variants was observed, with a significant

increase in expression of A2 and, to a lesser

extent A3, at the expense of A1 (Figure 3A).

Examination of putative GB transcripts using

primers ―c‖ and ―f‖ detected B2 but not B1 in

untreated samples, suggesting that SRSF2

transcripts that utilize the canonical E2 and the

alternative polyadenylation site selectively skip

E3; caffeine had a negligible effect on

expression of this group (Figure 3B). Multiplex

RT-PCR using primers ―e‖ and ―d‖ detected a

novel group of SRSF2 transcripts that contain an

elongated E2 with alternative 5’ splice site

choices at 1101 nt (C1), 389 nt (C2 and C4), 543

nt (C3), or 60 nt (C5) downstream of the stop

codon (Figure 3C). The impact of caffeine on

GC transcripts was similar to what was observed

for GA transcripts, in that alternative splicing of

intron 4/5 was induced (C1) at the expense of C2

(Figure 3C). In addition, utilization of novel 5’

splice sites 543 nt (C3) and 60 nt (C5) was

promoted (Figure 2C, note increased expression

of C3 and C5). Notably, GC transcripts were

not well represented in the population

(visualization required 5 additional PCR

amplification cycles). In contrast, GD

transcripts D1, D2 and D3, also novel splice

variants with similar alternative 5’ splice sites as

GC transcripts which utilize the alternative

polyadenylation site, are well expressed.

Caffeine increased the GD transcripts that utilize

5’ splice sites at 543 nt (D1) and 60 nt (D3), at

the expense of D2.

To summarize, caffeine significantly changed

the AS pattern of SRSF2 transcripts within the

3’UTR. This effect was fairly rapid; as shown

in Figure 3E, upper panel, the effect of caffeine

on A1 (decrease) and A2/A3 (increase) could be

observed as early as one hour, with maximum

levels achieved by 8 hrs. Similar kinetics was

obtained with GD transcripts (lower panel). As

basal GC transcript expression was negligible,

and caffeine had a minimal effect on the splicing

of GB transcripts, we focused on GA and GD

transcripts for the remainder of the study.

Caffeine does not change the levels of known

repressors of SRSF2 3’UTR alternative splicing.

It has been previously reported that two negative

splicing regulators, TARBP and HnRNP H, can

antagonize SRSF2-mediated splicing of intron

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4/5 (28). We therefore considered the

possibility that the expression of one or both of

these negative regulators could be altered by

caffeine, leading to the skipping of intron 4/5.

To examine this possibility, TARBP and

HnRNP H levels were analysed following

treatment with or without caffeine; no

significant change in levels of either factor was

observed over a 24 hr period (Figure 4),

suggesting that they are not responsible for

caffeine-induced SRSF2 3’UTR alternative

splicing.

Inhibition of NMD is not sufficient to increase

SRSF2. One of the well-documented effects of

caffeine is inhibition of NMD, due to the

negative impact of caffeine on phosphorylation

of the essential factor hUpf1 (31-34). Since

several of the caffeine-induced SRSF2

transcripts (A2, A3, D1, D2, and D3) are

potential substrates for NMD, we next

considered the possibility that inhibition of

NMD by caffeine was sufficient to allow NMD-

sensitive isoforms to be stabilized and

accumulated. First, cycloheximide (CHX) was

used to inhibit the pioneer round of protein

translation that is required for NMD (33,35). As

shown in Figure 5A, CHX treatment alone

partially altered the GA and GD expression

profiles (compare lane 3 to lane 1); however,

treatment with CHX and caffeine resulted in a

distinctive splicing pattern within the 3’UTR

(compare lane 3 to lane 2), indicating that CHX-

mediated NMD inhibition could not reproduce

the effect of caffeine on SRSF2 variants

expression. To directly determine whether

NMD inhibition alone was sufficient to generate

alternate SRSF2 transcripts as well as increased

SRSF2 protein levels, an RNAi approach was

used to knockdown hUpf1 (36-38). As shown in

Figure 5B, hUpf1 levels were decreased by at

least ~ 85% using a targeted SiRNA smart pool

(Dharmacon), resulting in inhibition of NMD as

evidenced by the accumulation of a known

NMD substrate, the alternatively spliced, exon

11(34 nt)-skipped PTB1(39). Further RT-PCR

analyses on GA and GD transcripts revealed

that, although hUpf1 knockdown induced some

changes in SRSF2 splice variant expression

(Figure 5C, compare lane 3 to lane 1), it was not

sufficient to induce the full spectrum of changes

that is observed in the presence of caffeine.

Importantly, NMD inhibition was not sufficient

to induce an increase in SRSF2 protein (Figure

5D, lane 3 vs. lane 2). We have previously

shown that caffeine had no effect on other SR

proteins that employ AS-NMD as their auto-

regulatory mechanism (15,29,33), consistent

with our hypothesis that NMD inhibition itself is

not sufficient to induce SRSF2 protein and an

additional, gene-specific mechanism must be in

place.

SRSF2 transcripts with varied 3’UTRs exhibit

different translational efficiencies. Given that

caffeine altered the SRSF2 3’UTR alternative

splicing choices without changing the total

mRNA levels and that the 3’UTR is known to

play a critical role in the regulation of

translational efficiency (40-42), we considered

the possibility that the caffeine-regulated AS

transcripts had different translational

efficiencies. Both in vitro translation assays and

cell-based translational assays were employed to

evaluate this possibility. Initially, the individual

3’UTR of SRSF2 transcripts were inserted into a

renilla luciferase reporter vector to test for

relative translational efficiency, while firefly

luciferase vector served as a transfection control,

as is standard in the field. Unfortunately,

caffeine interfered with detection of luciferase

activity in this assay. Therefore, Flag-SRSF2

cDNA (created by fusing a Flag tag to the N-

terminal of each construct) was used instead of

renilla luciferase cDNA as a reporter and GFP

replaced firefly luciferase as a control for

transfection efficiency. Under these conditions,

transcription of each variant (A1, A2, A3, and

D1, D2, D3, complete mRNA) is controlled by

the same promoter, and products of each can be

distinguished from endogenous SRSF2 using the

anti-Flag antibody.

Plasmid DNA was prepared and carefully

quantitated for each construct. The same

amount of input DNA was assayed the TNT®

Quick Coupled Transcription/Translation

System (Promega). As shown in Figure 6A,

transcripts A2 and A3 exhibited significantly

higher intrinsic translational efficiency than A1

in this assay, while translation of GD group

members were similar. Next, cell-based

translation was assayed by co-transfecting each

of the SRSF2 transcript constructs with a GFP

expression construct to serve as a control for

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transfection efficiency (43). Approximately 7

hours post transfection, cells were either

untreated or treated with caffeine. After 3 hours,

cells were harvested for western blot analysis of

both Flag-SRSF2 and GFP. The translational

efficiency of each SRSF2 transcript was

determined by normalizing Flag-SRSF2

expression to the expression of GFP. To assure

that the expression/stability of mRNA did not

differ among the transcripts, mRNA levels of

each Flag-SRSF2 and GFP were examined using

real-time quantitative RT-PCR assay. When

normalized to GFP, the levels of Flag-SRSF2

mRNA remained constant for all transcripts

tested (A1-A3, D1-D3) (Figure 6C).

As shown in Figure 6B, GA transcripts with

shorter 3’UTRs (A2, A3) exhibited higher

translation efficiency than A1 (left panel), while

the GD transcript D2 was translated with the

highest efficiency among the GD members

(right panel). Importantly, caffeine significantly

increased translational efficiency of every

variant tested by approximately 2-3 fold. This

moderate regulation of translation was

reminiscent of the impact of microRNAs (miRs)

on translation efficiency (44).

Caffeine-mediated downregulation of miR-183-

5p and miR-33a-5p alters protein translation

efficiency of specific SRSF2 transcripts.

MicroRNAs are small non-coding RNAs that

regulate gene expression by base-pairing with

specific mRNA molecules, usually resulting in

altered protein translation or mRNA stability

(45,46). MicroRNA-mediated translation

repression has recently been suggested as a

mechanism for SRSF2 regulation in amygdala

during acute stress (miR-183-5p) (47) and in

hepatocellular carcinoma during the acquisition

of drug resistance (miR-193a-5p) (48).

To determine whether caffeine regulates the

expression of miRs that could in turn impact

SRSF2 expression, microarrays were carried out

using the miRCURY LNATM

microRNA Array

platform and total RNA isolated from either

untreated HeLa cells or cells treated for 3 hrs or

24 hrs with caffeine. Each condition was

repeated three times and data was normalized to

internal controls present on the array. After

careful data mining using common criteria, ~

8% of the MiRs examined (99 out of ~1200)

were found to be downregulated by caffeine

(Supplementary Data Table 1 and 2). This

group of miRs was aligned with computationally

predicted SRSF2-targeting miRs (185 miRs,

based on the miRscan database,

http://genes.mit.edu/mirscan/), then further

limited to miRs that were abundantly expressed

in untreated control cells. Two microRNAs,

miR-183-5p and miR-33a-5p, were found to be

significantly down-regulated by caffeine; miR-

183-5p has previously been suggested to repress

SRSF2 translation (47) by interacting with the

SRSF2 transcript at position 1159 nt within the

3’UTR. MiR-33a-5p was suggested to target the

SRSF2 3'UTR at position 1746nt

(http://www.microrna.org/) (Figure 7A).

Therefore, miR-183-5p would likely target A1,

D1, D2, and D3 and miR-33a-5p could impact

translation of A1, A2 and A3 (Figure 7A). qRT-

PCR analysis of RNAs isolated from untreated

and treated HeLa cells was performed to validate

the downregulation of these miRs by caffeine.

As shown in Figure 7B, following 3-hr of

caffeine treatment, miR-183-5p was decreased

dramatically (5~6-fold) while miR-33q-5p levels

remain largely unchanged. However, following

24-hr of caffeine treatment, expression of miR-

183-5p was still decreased and miR-33a-5p was

decreased by almost half, similar to what was

observed in the microarray analysis.

To test the hypothesis that these miRs

impacted translation of specific SRSF2

transcripts, the levels of miR-183-5p and miR-

33a-5p were manipulated using either specific

miR mimics or specific miR inhibitors, which

were co-transfected into HeLa cells along with

one of the putative target SRSF2 transcripts. We

reasoned that if the miR indeed regulated the

translation of the co-transfected SRSF2

transcripts, differences should be observed in

their translational efficiency when compared to

controls. Similar to what was employed for the

cell-based transfection-translation assays in

Figure 6, a GFP expression plasmid was used to

control for transfection efficiency. 18-20 hours

post transfection, both flag-SRSF2 and GFP

levels were assessed by western blotting, and

translation efficiency was determined by

normalizing Flag-SRSF2 levels to GFP levels.

As showed in Figure 7C, the translation

efficiency of the wild-type A1 transcript (A1-

WT), predicted to be repressed by miR-183-5p,

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was further decreased by miR-183-5p mimics

and increased by miR-183-5p inhibitors.

Importantly, when the putative miR-183-5p

binding site within A1 was mutated (A1-

183Mut), neither the miR-183-5p mimic nor the

inhibitor had a significant impact on A1-183

mutant translation. Moreover, neither the miR-

183-5p mimic nor inhibitor had an effect on

translation of A2, which lacks the miR-183-5p

binding site. Taken together, these results

identify miR-183-5p as an SRSF2 (A1)-

targeting miR that binds to the 3’UTR at 1159-nt

downstream of the stop codon to repress A1

translation. Similar assays using A2 WT and

A2-33aMut also identified miR-33a-5p as an

SRSF2-targeting miR imposing translational

regulation (Figure 7D), with D1 serving as a

negative control.

To further confirm the effect of miR-183-5p

and miR-33a-5p on caffeine-mediated SRSF2

translation, miR-183-5p and miR-33a-5p mimics

were co-transfected with the KLF6 minigene,

followed by caffeine treatment. As shown in

Figure 7E (left panel, top), while caffeine

increased endogenous SRSF2 by almost 4-fold

in the presence of non-specific miR mimics, this

effect was largely reduced in the presence of the

specific miR mimics with a concomitant

decrease in KLF6 alternative splicing (~ 3-fold,

from 89% to 32%). We next investigated the

effect that downregulation of miR-183-5p and

miR-33a-5p had on SRSF2 and KLF6, reasoning

that this should mimic at least some of the

effects of caffeine. Since our data suggested that

caffeine has two activities that regulate

SRSF2/KLF6 – downregulation of the SRSF2-

targeting miRs and inhibition of NMD, we

inhibited NMD by siRNA-mediated

downregulation of the key NMD protein,

hSMG1(37), which is also the direct target of

caffeine (31,32), in this experiment. As shown

in Figure 7E, right panel, when NMD is

inhibited, downregulation of the miRs increased

SRSF2 levels (~3-fold) and KLF6 alternative

splicing (~ 3-fold, from 23% to 68%). Taken

together, our results reveal a novel effect of

caffeine on miR regulation that in turn impacts

SRSF2 translation and KLF6 alternative

splicing, supporting the hypothesis that caffeine-

induced SRSF2 translational regulation

contributes significantly to caffeine-induced

increases in SRSF2 protein levels and alternative

splicing decisions.

DISCUSSION

We have previously reported that caffeine

can impact alternative splicing (AS) of a subset

of cancer-related genes. Using KLF6 as a

model, we demonstrated that the change in

KLF6 splicing pattern could not be mimicked by

inhibition of nonsense-mediated decay (NMD),

even though the caffeine-induced KLF6 splice

variant was a potential target for this RNA

surveillance mechanism. Instead, the altered

splicing of KLF6 was a result, at least in part, of

a caffeine-induced increase (~6-fold) in levels of

the splicing factor SRSF2 (29). In this report,

we show that additional methylxanthines can

also induce AS of KLF6, with a concomitant

increase in SRSF2 levels. SRSF2 gene

expression is known to be guarded by a negative

feedback loop, and a low steady level of SRSF2

is important for homeostasis of isoform

expression as well as cell proliferation and

genome stability (18). Thus, it was important to

understand how methylxanthines, using caffeine

as a prototype, had affected this normally

unsustainable increase of SRSF2. We

demonstrate that, in addition to its ability to

inhibit NMD, caffeine can also regulate the

expression of specific microRNAs, resulting in

changes in translation efficiency of SRSF2

transcripts. Together, these modifications result

in increased translation of certain SRSF2

variants and stabilization of NMD-sensitive

SRSF2 transcripts with higher intrinsic

translational efficiency; together these caffeine-

induced changes lead to a surge of SRSF2

protein levels and an increase in SRSF2 splice

variants designated for degradation by NMD,

and the cycle continued. Thus, caffeine breaks

the negative feedback loop controlling SRSF2

gene expression and further enforces a positive

feed-forward loop that fuels the increased

production of SRSF2 (See Model, Figure 8).

While we have not yet determined whether

caffeine plays a similar role in vivo, it is likely

that it is mimicking an endogenous process or

processes that are responsible for fine-tuning

SRSF2 gene expression in response to

developmental or environmental signals, or

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during pathogenesis. Thus, caffeine represents a

valuable tool to dissect this mechanism.

Previous studies have identified two SRSF2

3’UTR variants induced by increased SRSF2

levels or depletion of the splicing repressor

HnRNP H (27,28,30). These SRSF2 variants of

the major transcript, A1, correspond to A2 and

A3 in this study. In this study, we identified

additional groups of transcripts, GB, GC, and

GD. Most of these novel variants are potential

targets of NMD, indicating that they are

probably part of the AS-NMD circuit regulating

SRSF2 protein levels (3,49). For the major GA

transcripts, translation of the variants in cultured

cells fit the general dogma – variants with

shorter 3’UTRs were translated with the highest

efficiency (50). However, translation of GD

variants was less conventional, in that the

variant with the intermediate size 3’UTR (D2)

was translated with the highest efficiency

(Figure 6). Interestingly, this difference among

GD transcripts was not obvious in cell-free

transcription/translation assays (Figure 6A),

suggesting that other cellular processes/signals,

most likely interacting with the 3’UTR

sequence between 60 to 543nt downstream of

the stop codon, are involved. The GD

transcripts account for a relatively small portion

of the total SRSF2 mRNAs in HeLa cells, but

appear to make a marked contribution to SRSF2

gene regulation, which may be more critical in

tissue types or cell lines that preferentially

utilize the alternative polyadenylation site (51).

Our study is the most thorough examination of

SRSF2 transcripts and their translational

efficiency to date. While the expression and role

of these variants in different cells/tissues, and

under different physiological and pathological

conditions, has yet to be determined, this study,

together with the comprehensive analysis of

SRSF1 by the Krainer group (52), contributes to

our understanding of the complex regulation of

SR proteins gene expression.

One unexpected result of these studies was

that depletion of hUpf1, best known as an

essential factor in the NMD pathway, had little

effect on SRSF2 levels alone, but prevented

induction of SRSF2 by caffeine (Figure 5C).

Interestingly, recent studies suggest additional

functions of hUpf1 other than in NMD,

including a role in the regulation of protein

translation. Yoneda and colleagues recently

reported that hUpf1 was required for Stau2

overexpression-mediated induction of translation

(53), while Moore and colleagues suggested that

hUpf1, when associated with Exon junction

complex (EJC), may contribute to the translation

of spliced mRNAs (54). Indeed, NMD factors

may be involved in both RNA degradation and

enhanced translation when splicing efficiency is

improved (55). Given that our model indicates a

substantial contribution from caffeine-

stabilized/NMD-targeted SRSF2 transcripts to

caffeine-mediated SRSF2 increase, we speculate

that hUpf1 may be required in translation of

these transcripts. Further studies will be needed

to validate this hypothesis.

While searching for a second mechanism for

the caffeine induction of SRSF2, we identified a

novel action of this methylxanthine, the

regulation of miR expression. MiR-mediated

gene expression regulation is a well-recognized

post-transcriptional mechanism that either

represses translation and/or destabilizes mRNA

transcripts to control protein production (44,56-

58). Nearly 60% of protein-coding genes are

predicted to be targeted by microRNAs and most

microRNAs act by base-pairing with the 3’UTR

of the targeted mRNA (59). One gene could

potentially be targeted by multiple microRNAs;

however, it is unlikely that all of them would be

functional at the same time because miRs are

expressed in a tissue- and development-specific

manner (44,56-58,60). For SRSF2, algorithms

including microRNA (www.microrna.org) and

miRScan (http://genes.mit.edu/mirscan) predict

~185 putative miR binding sites within the

3’UTR. Only two of these have been previously

validated: miR-183-5p in stress response (47)

and miR-193a-3p in cancer drug resistance (48).

We now show that caffeine can regulate a subset

of miRs, including miR-183-5p, which targets

A1 and possibly all GD members (Figure 7). The down-regulation of miR-183-5p by caffeine

was rapid, dramatic, and persistent (Figure 7B

and Supplement Table 1 and 2), supporting a

significant role of this downregulation in

caffeine-mediated SRSF2 protein induction. In

addition, we have for the first time validated

miR-33a-5p as an SRSF2-targeting miR, and

shown that this miR is also downregulated by

caffeine. Because the putative binding site for

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miR-33a-5p is located 1746 nt downstream of

the stop codon, this miR primarily impacted

protein production of transcripts using the

canonical polyadenylation site such as the GA

group, the major group of SRSF2 transcripts.

It should be noted that the miR-183-5p

binding site, shared by A1 and D1-D3, overlaps

a putative ARE (A-U rich element)(56). AREs

are found in the 3’UTR of many mRNAs and

can interact with a number of proteins to either

stabilize (the Hu family of proteins) or

destabilize (AUF1, TTP, BRF1, TIA-1, TIAR,

and KSRP) the mRNA (57-60), a common

determinant of RNA stability. To date, the

putative AREs within SRSF2 3’UTR have not

been functionally tested, nor have their cognate

binding proteins, either stabilizing or

destabilizing, been identified. Nevertheless, it is

feasible that their proximity to the miR binding

site may impact miR activity under certain

conditions. The function of these AREs and

their potential impact on the miR activity and

SFSF2 RNA stability (or vice versa) is currently

under investigation.

Our results suggest that aberrant expression

of either miR-183-5p or miR-33a-5p would have

a marked impact on SRSF2 protein production,

which in turn could influence alternative

splicing choices in SRSF2-targeted genes,

including many cancer-related genes. Indeed,

abnormal levels of miR-183-5p have been

observed in various tumors (61), where it

appears to play a role in tumor progression due

to its impact on proliferation, apoptosis, and

metastasis (62-65). Altered regulation of miR-

183-5p has also made it an attractive biomarker

candidate (66-72). miR-33a-5p has also been

suggested to play a role in tumorigenesis (73-

75), as well as in controlling cholesterol and

lipid metabolism (76,77). However, to date

there has been no evidence to link aberrant

expression of these miRs to AS in cancers.

Therefore, our observation that alteration of

these miRs can have a profound effect on the

expression of SRSF2, a critical splicing factor

regulating genes involved in cell proliferation,

cell death and metastasis, warrants further

studies.

It is not yet known how caffeine modulates

levels of miR-183-5p, miR-33a-5p, or other

miRs. Since transcriptional regulation can be

influenced by caffeine (78,79 ,80), we compared

the effects of caffeine on miR-183-5p levels to

that of two additional miRs within the miR-183-

96-182 cluster, miR-96 or miR-182, because

they share the same promoter (81,82). No

significant effect was observed (Supplement,

Table 1 and 2), suggesting that transcriptional

regulation is unlikely to be the underlying

mechanism. Given the pleiotropic effect of

caffeine on cells (83-85), it is possible that

multiple mechanisms may be involved in

caffeine-mediated miR regulation.

In summary, we have shown that caffeine

regulates expression of SRSF2 through a

complex set of post-transcriptional mechanisms

that work together to break the AS-NMD

feedback loop and foster a feed-forward loop

that increases SRSF2 protein levels. Our studies

to date underscore the complicated interplay of

multiple mechanisms needed to control SRSF2

expression that in turn controls the expression of

a large subset of target genes. This knowledge

may provide a foundation for exploring the

aberrant regulation of SRSF2 and target genes in

pathogenesis.

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Acknowledgments—The authors thank Drs Cyril F. Bourgeois and James Stevenin at Institut de

Je´ne´tique et de Biologie Mole´culaire et Cellulaire, France, for generously providing SRSF2(SC35)

monoclonal antibody. This research was supported by the Microarray Core facility and Bioinformatics

Core facility of the Rutgers Cancer Institute of New Jersey (P30CA072720).

FOOTNOTES

*This work was supported by NCI-R01 CA 122573 (K.W. S.) and NCI-P30CA072720 to the Rutgers

Cancer Institute of New Jersey.

1 To whom correspondence should be addressed: Kathleen W. Scotto. Rutgers Cancer Institute of New

Jersey, Rutgers, the State University of New Jersey, 195 Little Albany Street, New Brunswick, NJ 08903,

USA, Tel: (732) 235-4266; Fax: (732)-235-6596; Email: scottoka@cinj.rutgers.edu

FIGURE LEGENDS

Figure 1. Methylxanthines induce alternative splicing of KLF6 and increase levels of SRSF2. (A)

RT-PCR analyses on samples treated with methylxanthines (14 mM), including pentoxifylline, caffeine,

theophylline, and isocaffeine, revealed various degrees of SpKLF6 induction following 18hrs of treatment.

(B) Western blotting analyses detected increased levels of SRSF2 in samples treated with pentoxifylline,

caffeine, and theophylline; isocaffeine had a minimal effect. The order of magnitude of SRSF2 increase is

pentoxifylline>caffeine>theophylline>isocaffeine, which coincided with the degree of SpKLF6 AS

induction. (C) Cytotoxicity assays revealed considerable cell death following pentoxifylline treatment

when compared to caffeine, at the effective concentration (14 mM) used to induce maximal alternative

splicing of KLF6.

Figure 2. Caffeine does not change total SRSF2 mRNA levels. (A) Schematic illustration of SRSF2

gene structure. ―E1‖: exon 1; ―E2‖: exon 2; The canonical polyadenylation site is found 2046 nt

downstream of the stop codon, while an alternative polyadenylation site is located at 1341 nt downstream

of the stop codon. (B) Semi-quantitative RT-PCR analysis using primers ―a‖ and ―b‖ on RNA samples

collected from Hela cells with or without caffeine treatment at different time points. No change in SRSF2

total mRNA was observed following caffeine (14 mM) treatment. β2M RNA was used as a loading

control. This assay was repeated at least three times with consistent results. Statistical analyses were

performed using GraphPad Prism 6 software, and significance was determined by the non-parametric t

tests. A P < 0.05 was considered significant. (C) SYBR® real-time RT-PCR analyses confirmed the

results from semi-quantitative RT-PCR, i.e. that no significant change in total SRSF2 mRNA was induced

by caffeine. Error bars represent Mean ± SD.

Figure 3. Caffeine induces rapid changes in the 3’UTR of SRSF2 RNA (A-D). The known Group A

(GA) transcripts as well as the putative Group B, C and D (GB, GC, GD) transcripts are schematically

depicted in the left panels. Semi-quantitative RT-PCR was performed with different primers to query the

existence of both known and putative SRSF2 transcripts in HeLa cells. (A) Analyses using primers ―c‖

and ―d‖ on samples with or without 1hr-caffeine treatment revealed rapid changes in levels of the GA

splice variants (right panel). (B) Analysis using primers ―c‖ and ―f‖ confirmed the existence of putative

GB SRSF2 transcripts that utilize the alternative polyadenylation site instead of the canonical

polyadenylation site. Caffeine treatment (14 mM) had minimal effect on the B1 transcript (inclusion of

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E3) (right panel). Note that primers ―c’ and ―f‖ will also amplify A1. (C) Analysis using primers ―e‖ and

―d‖ confirmed the presence of GC transcripts that utilize the canonical polyadenylation site but select

alternative E2 5’splice sites at positions 1101 nt (C1), 389 nt (C2 and C4), 543 nt (C3), or 60 nt (C5)

downstream of the stop codon. Caffeine induced changes in GC transcripts. GC transcripts are poorly

expressed because they required 5 additional cycles of PCR to be comparably visualized. (D) Analysis

using primers ―e‖ and ―f‖ confirmed novel GD transcripts that utilize the alternative polyadenylation site

as well as alternative E2 5’splice sites. Caffeine (1 hr) induced D1 and D3 at the expense of D2. (E)

Time course analyses of caffeine-induced alternative splicing changes within the 3’UTR among GA and

GD transcripts.

Figure 4. Caffeine (14 mM) does not change the levels of TARDBP and HnRNP F/H to influence

SRSF2 AS at the 3’UTR. Western blotting analysis was performed on samples collected at indicated

time points. Tubulin was used as the internal control.

Figure 5. Inhibition of NMD is not sufficient to increase SRSF2 levels. (A) Cycloheximide-mediated

NMD inhibition only resulted in partial mimics of the effect of caffeine on alternative splicing pattern in

GA and GD transcripts. (B) RNAi reduced the hUpf1 level by ~85%, inhibiting NMD as evidenced by

the accumulation of a PTB1 splice variant (exon 11-skipped PTB1), known to be an NMD target. Note

that caffeine treatment alone (lane 2) also resulted in accumulation of exon 11-skipped PTB1, indicating

some degree of inhibition of NMD by caffeine. (C) The SRSF2 3’UTR splicing pattern induced by

caffeine was only partially reproduced by hUpf1 knockdown-mediated NMD inhibition. (D) Western

blot analysis revealed that hUpf1 RNAi-mediated NMD inhibition was not sufficient to increase levels of

SRSF2 protein. Quantitation was normalized to input control tubulin. Statistical analysis was performed

based on data from at least three experiments. Error bars represent Mean ± SD.

Figure 6. GA and GD SRSF2 variants exhibit different translational efficiencies and caffeine (14

mM) increases their translation. (A) In vitro translation assays detected a higher intrinsic translational

efficiency of A2 and A3 when compared to A1 transcripts. No significant difference was detected among

GD SRSF2 variants by this assay. (B) Cell-based translation assays also indicated that the caffeine-

induced transcripts A2 and A3 were translated at a higher rate as compared to A1. Caffeine increased

translational efficiency of all SRSF2 variants. SRSF2 cDNA in frame with an N-terminal FLAG tag was

tethered with individual SRSF2 3’UTRs and inserted into a mammalian expression plasmid. Co-

transfection assays introduced both SRSF2 and GFP constructs into HeLa cells. Western blot analysis

was utilized to quantitate relative translation efficiency. GFP was used as a control for transfection

efficiency. (C) Real-time RT-PCR analyses of Flag-SRSF2 and GFP mRNA in the cell-based

translational efficiency assay. The relative levels of Flag-SRSF2 mRNA of each SRSF2 variants were

normalized to levels of GFP mRNA from the same cell populations/experimental conditions. Statistical

analysis was performed based on data from at least three repeats using GraphPad PRISM 6 software, non-

parametric t tests. A difference with a P < 0.05 was considered significant. Error bars represent Mean ±

SD.

Figure 7. Caffeine decreases levels of SRSF2-targeting miRs to increase translational efficiency of

certain SRSF2 transcripts. (A) Strategy for identifying putative caffeine-decreased SRSF2-targeting

miRs in HeLa cells (lower, left) and schematic of miR binding sites within the SRSF2 3’UTR (top). Two

candidates were selected (miR-183-5p and miR-33a-5p) and mapped to GA and GD transcripts. (B)

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MicroRNA array analyses revealed caffeine-mediated decreases in the levels of miR-183-5p and miR-

33a-5p (left). This decrease was validated by quantitative RT-PCR (right). The final Ct value was an

average of 5 repeats of each assay, and each assay was repeated three times. A difference with a P < 0.05

was considered significant. (C) The miR-183-5p binding site in the Flag-SRSF2 A1 transcript was

disabled by site-directed mutagenesis (top). Either A-1WT or A1-183Mut was co-transfected with either

miR-183-5p mimics or inhibitor. GFP was included in the transfection cocktail as transfection efficiency

control. Each assay was repeated three times. A difference at P < 0.05 was considered significant. (D)

The miR-33a-5p binding site in Flag-SRSF2 A2 transcript was disabled by site-directed mutagenesis (top).

Either A-2WT or A2-33aMut was co-transfected together with miR-33a-5p mimics or inhibitors. GFP

was included as the transfection efficiency control. (E) Levels of endogenous SRSF2 and alternative

splicing of KLF6 minigene were analyzed after cells were transfected with miR mimics in the presence

of caffeine (left panel) or miR inhibitors in the presence of hSMG1 siRNA to block NMD (right panel).

Non-specific miRs served as controls. Each assay was repeated three times. Statistical analyses were

performed using GraphPad Prism version 6 software, and significance was determined by the non-

parametric t test. A difference with a P < 0.05 was considered significant. Error bars represent Mean ±

SD.

Figure 8. Proposed model illustrating the mechanisms by which caffeine increases SRSF2 protein

expression. Under normal conditions, SRSF2 homeostasis is maintained by a complex interplay of post-

transcriptional mechanisms including microRNA-mediated translation repression (left panel) and an

alternative splicing associated NMD (AS-NMD)--the autoregulatory feedback loop (middle panel).

Translation of the major SRSF2 transcripts A1 and D2 are suppressed by specific miRs binding to the

3’UTR. When SRSF2 levels are increased due to intrinsic or environmental signals, the increased SRSF2

promotes alternative splicing at the 3’UTR, resulting in multiple splice variants such as A2, A3, D1, and

D3. These transcripts are destined for NMD, thereby decreasing the level of SRSF2 mRNA and the

production of SRSF2 protein. Caffeine has two key effects on SRSF2 homeostasis regulation. First,

caffeine decreases the levels of SRSF2-targeting miRs, releasing translational repression of the major

SRSF2 transcripts, allowing a surge of SRSF2 protein synthesis. This increased SRSF2 triggers the

synthesis of splice variants A2, A3, D1, and D3, normally substrates for NMD. However, caffeine also

inhibits NMD, blocking the degradation of SRSF2 transcript variants. Thus, caffeine affects multiple

regulatory mechanisms breaking the negative feedback loop resulting in a sustained increase of SRSF2

protein.

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B.

A. UT

RT-PCR: KLF6

RT-PCR: β2M

SpKLF6

KLF6+SpKLF6 <1 (%) 92±2 78±6

18hrs

25±4 7±3

C.

Pentoxifylline Caffeine

Theophylline Isocaffeine

WB: SRSF2

WB: actin

- + - +

4hr 18hr

WB: SRSF2

WB: actin

- + - +

4hr 18hr

- + - +

4hr 18hr

WB: SRSF2

WB: actin

- + - +

4hr 18hr

WB: SRSF2

WB: actin

1 3.2 1 9.4 1 2.25 1 6.3

1 1.5 1 4.1 1 1.1 1 1.8

Figure 1 Caffeine modulates post-transcriptional regulation of SRSF2

Pentoxifylline Caffeine Theophylline isocaffeine

Fo

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ty

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Figure 2

B.

A.

+

8hr

RT-PCR with primers a and b:

- +

1hr

- +

2hr

- +

4hr

- +

6hr

- Caffeine

β2M

SRSF2

-

0hr

Caff +/-

Caffeine modulates post-transcriptional regulation of SRSF2

1 286 389 1003 1101 1600 ATG

STOP E1 E2 E3 E4 E5 I 4/5

Alt. PolyA

1341-nt

Canonical

PolyA

2046-nt a b

C. SYBR Real-time qPCR with primers a and b following universal RT reactions

Re

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Figure 3A/3B

A.

B.

RT-PCR with primers c and d :

650bp

1 kb A1

A2

A3

850bp

1-hr Caff - +

Group A transcripts:

A2

A3

A1

2046 1 286 389 1003 1101 1600

c d ATG

STOP E1 E2 E3 E4 E5 I 4/5

RT-PCR with primers c and f:

- + 1-hr Caff

B1

B2+A1

650bp

500bp

400bp

Group B transcripts:

B1

B2

2046 1 389 1003 1101 1600

c

ATG

STOP

Alt. PolyA

1341

f

286

E1 E2 E3 E4 E5 I 4/5

Caffeine modulates post-transcriptional regulation of SRSF2

0%

20%

40%

60%

80%

100%

UT Caff

A1 80% 61%

A2 3% 14%

A3 17% 25%

A1

A2

A3

1-hr

0%

20%

40%

60%

80%

100%

UT Caff

B1 0% 0%

B2+A1 100% 100%

B1

B2+A1

1-hr

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Cont’ Figure 3C/3D/3E

C.

D.

Group D transcripts:

D1

D2

D3

2046 1 389 1003 1101 1600 ATG

STOP

Alt. PolyA

1341 286

e

E1 E2 E3 E4 E5 I 4/5

f

RT-PCR with primers e and d,:

- + 1 hr Caff

C1

C2

C3

C4

C5 650bp

1.0kb

1.65kb Group C transcripts:

C5

C4

C3

C2

C1

2046 1 286 389 1003 1101 1600

d ATG

STOP E1 E2 E3 E4 E5 I 4/5

e

RT-PCR with primers e and f:

E.

Group A

Transcripts

Caff - + - + - + - +

2hr 4hr 6hr 8hr

- +

1hr

A3 A2

A1

β2M

Group D

Transcripts

D1

D2

D3

1-hr Caff -

D1

D2

D3

650bp

850bp

+

Caffeine modulates post-transcriptional regulation of SRSF2

0%

20%

40%

60%

80%

100%

UT Caff

A1 96% 1%

A2 1% 50%

A3 5% 49%

A1

A2

A3

8-hr

0%

20%

40%

60%

80%

100%

UT Caff

D1 10% 44%

D2 85% 37%

D3 5% 19%

D1

D2

D3

8-hr

0%

20%

40%

60%

80%

100%

UT Caff

D1 10% 53%

D2 80% 26%

D3 10% 21%

D1

D2

D3

1-hr

0%

20%

40%

60%

80%

100%

UT Caff

C1 7% 13%

C2 49% 4%

C3 5% 45%

C4 35% 32%

C5 4% 6%

C1

C2

C3

C4

C5

1-hr

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Figure 4

Caffeine modulates post-transcriptional regulation of SRSF2

WB:TARDBP

WB: HnRNP H/F

WB: Tubulin

2-hr 6-hr 24-hr Caff

- + - + - +

1.8 2.0 1.9 1.8 1.7 1.8

1.1 1.3 1.2 1.3 1.4 1.3

6.5 7.1 6.3 6.1 6.6 6.7

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Figure 5

A.

Caffeine modulates post-transcriptional regulation of SRSF2

B.

RT-PCR: Exon 11

skipped PTB1

WB: Upf1

WB: tubulin

SiRNA

Caff

Control

- + -

hUpf1

+

1 1 0.13 0.15

1 2 3 4

24-hr

D.

1

WB: SRSF2

WB: tubulin

1 2 3 4

siRNA

Caff

Control

- + -

hUpf1

+

24-hr

C.

A1

A2

A3

- + Caff

10-hr

+ + CHX

-

-

D1

D2

D3

+

-

1 2 3 4

RT-PCR: GA

A1

A2

A3

RT-PCR: GD

D1

D2

D3

1 2 3 4

SiRNA

Caff

Control

- + -

hUpf1

+

24-hr

Rel

ativ

e le

vels

of

SR

SF2

pro

tein

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Figure 6 Caffeine modulates post-transcriptional regulation of SRSF2

A. In vitro translation assay:

Flag-SRSF2

1 1.8 1.9 1 0.88 0.73

A1 A2 A3 D1 D2 D3

Re

lati

ve q

uan

tita

tio

n

of

Flag

-SR

SF2

Re

lati

ve q

uan

tita

tio

n

of

Flag

-SR

SF2

B. Cell-based translation assay:

A2 A1 A3

- + - + - + D2 D1 D3

- + - + - +

WB: Flag-SRSF2

WB: GFP

Caffeine

Re

lati

ve q

uan

tita

tio

n o

f

Flag

-SR

SF2

No

rmal

ize

d b

y G

FP

Re

lati

ve q

uan

tita

tio

n

of

Flag

-SR

SF2

no

rmal

ize

d b

y G

FP

2.8 4.9 3.6 10.8 4.6 9.8 2.9 7.8 6.4 12.3 3.5 6.5

Rela

tive l

evels

of

Fla

g-S

C35 m

RN

A

no

rmalized

by l

evels

of

GF

P m

RN

A

C.

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Figure 7A/7B

Caffeine modulates post-transcriptional regulation of SRSF2

A.

99 MicroRNAs

down-

regulated

by caffeine

154 MicroRNAs

abundantly

expressed in HeLa

185 MicroRNAs

target for SRSF2

as predicted

miR-183

miR-33a 3' acgUUACGUUGA--UGUU-ACGUg 5' hsa-miR-33a

| | | | | | | | | | | | | | | 1746:5' uaaAAUGC----CUGACAACUGCAc 3' SRSF2

3' ucacuUAAGAUGGUCACGGUAu 5' hsa-miR-183

| | | : | | : | | | | | | | 1159:5’ acuucAUUUUAU---GUGCCAUu 3' SRSF2

2046 1 389 1003 1101 1600 ATG

STOP

Alt. PolyA

1341 286

miR-183

(1159 nt-)

miR-33a

(1746nt-)

Canonical

PolyA

D1

D2

D3

A2

A3

A1

B. ARRAY ANALYSIS

3hr 24hr 3hr 24hr

qRT-PCR

Rela

tiv

e lev

els

of

miR

s

3hr 24hr 3hr 24hr

Rela

tiv

e lev

els

of

miR

s

miR-183-5p

miR-33a-5p miR-33a-5p

miR-183-5p

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3’ ucacuUAAGAUGGUCACGGUAu 5' hsa-miR-183

| | | : | | : | | | | | | | 1159: 5’ acuucAUUUUAU----GUGCCAUu 3' A1- WT

A1-183Mut

hsa-miR-183 3’ ucacuUAAGAUGGUCACGGUAu 5’

c a gg tUu t U--- acuucAaaU-a c

: :

2046 1 389 1003 1101 1600 ATG

STOP

Alt. PolyA

1341 286

miR-183

(1159 nt-)

Canonical

PolyA

A2

A1

C.

Mimic Inhibitor Mimic Inhibitor NS NS 183 183

A1-WT A1-183Mut

Caffeine modulates post-transcriptional regulation of SRSF2

Figure 7C

A2

NS 183 NS 183

WB: Flag-SRSF2

WB: GFP

Rela

tive

tran

sla

tio

na

l eff

icie

nc

y

NS NS 183 183

A1-WT A1-183Mut

1.0 0.3 1.1 1.1 1.0 3.6 0.9 1.1 1.0 1.0 1.1 1.0

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3' acgUUACGUUGA-UGUU--ACGUg 5' hsa-miR-33a

| | | | | | | | | | | | | | | 1746: 5' uaaAAUGC----CUGACAACUGCAc 3' A2-WT

A2-33aMut uaaAta c-g----gUGtg t tC ac-gAc 3' acgUUACGUUGA-UGUU-ACGUg 5' hsa-miR-33a

2046 1 389 1003 1101 1600 ATG

STOP

Alt. PolyA

1341 286

miR-33a

(1746nt-)

Canonical

PolyA

D1

A2

Figure 7D/E

Caffeine modulates post-transcriptional regulation of SRSF2

Mimic Inhibitor

NS NS 33a 33a

A2-WT A2-33aMut

NS NS 33a 33a

A2-WT A2-33aMut D1

33a 33a NS NS Mimic Inhibitor

Rela

tive

tran

sla

tio

na

l eff

icie

nc

y

1.0 0.4 1.2 1.2 1.0 2.1 1.2 1.2 1.0 0.9 1.1 1.1

D.

WB: Flag-SRSF2

WB: GFP

E.

*p=0.04

*

Rel

ativ

e q

uan

tity

of

SRSF

2 *p=0.04

*

Rel

ativ

e q

uan

tity

of

SRSF

2

SpKLF6

KLF6

NS NS 183+33a

Caff (14 mM)

miR Mimic

- + +

WB: SRSF2

RT-PCR: KLF6minigene

WB: tubulin

None NS 183+33a

miR Inhibitor

hSMG1 siRNA (blocking NMD)

1.0 3.5 1.5 1.0 0.9 2.8

SpKLF6

KLF6+SpKLF6 (%)

15 89 32 28 23 64

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5’ 3’

SRSF2 pre-mRNA miR

Normal SRSF2 Homeostasis

5’ 3’

High Levels of SRSF2 Protein

5’ 3’

SRSF2 AS mRNA (A2, A3, D1,D3)

5’ 3’

PTC

5’

3’

NMD

PTC

PTC

PTC

5’ 3’

5’ 3’

SRSF2 major mRNA (A1, D2)

Low Levels of SRSF2 Protein

SRSF2 protein

Caffeine

5’ 3’

5’ 3’

5’ 3’

5’ 3’

SRSF2 AS mRNA (A2, A3, D1,D3)

5’ 3’

5’ 3’

NMD SRSF2 protein

SRSF2 protein

miR

Figure 8

Caffeine modulates post-transcriptional regulation of SRSF2

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Jia Shi, Kirk Pabon and Kathleen W. ScottoMultiple Post-Transcriptional Mechanisms

Methylxanthines Increase Expression of the Splicing Factor SRSF2 by Regulating

published online March 28, 2015J. Biol. Chem. 

  10.1074/jbc.M114.624254Access the most updated version of this article at doi:

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Supplemental material:

  http://www.jbc.org/content/suppl/2015/04/09/M114.624254.DC1

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