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Lack of miR-133a decreases contractility in diabetic hearts: a role for novel cross-talk
between tyrosine aminotransferase and tyrosine hydroxylase
Shyam Sundar Nandi1, Hong Zheng
1, Neeru M. Sharma
1, Hamid R. Shahshahan
1, Kaushik P.
Patel1
and Paras K. Mishra1, 2
Affiliations:
1. Department of Cellular and Integrative Physiology, University of Nebraska Medical
Center, 985850 Nebraska Medical Center, Omaha, NE 68198, USA
2. Department of Anesthesiology, University of Nebraska Medical Center, 985850
Nebraska Medical Center, Omaha, NE 68198, USA.
Running title: MiR-133a regulates cardiac contractility
Corresponding author:
Paras Kumar Mishra
Department of Cellular and Integrative Physiology
University of Nebraska Medical Center
985850 Nebraska Medical Center
Omaha, NE-68198, USA
Phone: 402-559-8524
Fax: 402-559-4438
Email: paraskumar.mishra@unmc.edu
Page 1 of 63 Diabetes
Diabetes Publish Ahead of Print, published online July 13, 2016
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Abstract
MicroRNAs have a fundamental role in diabetic heart failure. The cardioprotective microRNA-
133a (miR-133a) is downregulated, and contractility is decreased in diabetic hearts.
Norepinephrine (NE) is a key catecholamine that stimulates contractility by activating beta-
adrenergic receptors (β-AR). NE is synthesized from tyrosine by the rate-limiting enzyme,
tyrosine hydroxylase (TH), and tyrosine is catabolized by tyrosine aminotransferase (TAT).
However, the cross-talk/link between TAT and TH in the heart is unclear. To determine whether
miR-133a plays a role in the cross-talk between TH and TAT, and regulates contractility by
influencing NE biosynthesis and/or β-AR levels in diabetic hearts, Sprague-Dawley rats and
miR-133a transgenic (miR-133aTg) mice were injected with streptozotocin to induce diabetes.
The diabetic rats were then treated with miR-133a mimic or scrambled miRNA. Our results
revealed that miR-133a mimic treatment improved the contractility of the diabetic rat’s heart
concomitant with upregulation of TH, cardiac NE, β-AR, and downregulation of TAT and
plasma levels of NE. In miR-133aTg mice, cardiac specific miR-133a overexpression prevented
upregulation of TAT and suppression of TH in the heart after streptozotocin treatment.
Moreover, miR-133a overexpression in CATH.a neuronal cells suppressed TAT with
concomitant upregulation of TH, whereas knockdown and overexpression of TAT demonstrated
that TAT inhibited TH. Luciferase reporter assay confirmed that miR-133a targets TAT. In
conclusion, miR-133a controls the contractility of diabetic hearts by targeting TAT, regulating
NE biosynthesis, and consequently β-AR and cardiac function.
Key Words: microRNA, diabetes, heart failure, β-adrenergic receptors, norepinephrine
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INTRODUCTION
MicroRNAs (miRNAs) are non-coding, regulatory RNAs that play a crucial role in the
pathophysiology of several diseases including heart failure and diabetic cardiomyopathy (1). A
number of cardioprotective miRNAs are downregulated in the failing heart, which contributes to
pathological cardiac remodeling (2). MiRNA-133a (miR-133a) is one of the most abundant
miRNAs in the heart (3). It is shared between the central nervous system and the heart (4) and
has a multifaceted cardioprotective role (5). It is downregulated in failing hearts in humans and
mice (6). Downregulation of miR-133a is associated with upregulation of cardiac autophagy in
humans with diabetic heart failure (7). On the other hand, transgenic over-expression of miR-
133a in mice protects the diabetic heart from cardiac fibrosis (8). Albeit, the cardioprotective role
for miR-133a has been demonstrated at the myocardial level, its role in catecholamine
biosynthesis and action via adrenergic receptors that is required for neurohumoral stimulation of
cardiac contractility in diabetic hearts is poorly understood.
Diabetes mellitus (DM) is a complex disease caused due to insufficient insulin secretion
from pancreatic beta cells (T1D), and/or insulin resistance (T2D) that results in an increased
blood glucose level leading to morbidity and mortality (9). The number of DM patients are
increasing at an alarming rate in the world (10;11). However, the causes for increased prevalence
of DM and DM-mediated cardiomyopathy are poorly understood. Diabetes is a miRNA-
associated disease (12), which causes heart failure independent of coronary artery disease,
hypertension or valvular disease (13). In DM hearts, miR-133a is downregulated (7;8) and
contractility is decreased (14). Decreased contractility is caused primarily due to
inactivation/reduction of beta-adrenergic receptors (β-ARs) (15). β-ARs are G-protein-coupled
receptors, and β1-AR and β2-AR are the predominant subtypes in the heart. They are present in
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the ratio of 70:30 in the left ventricle, respectively, and increase contractility of the heart (16;17).
β-AR activation augments calcium uptake and increases sarco-endoplasmic reticulum activity by
upregulating sarco-endoplasmic reticulum ATPase-2a (SERCA-2a), which increases contractility
of the cardiomyocytes (18). In diabetic hearts, SERCA-2a is decreased (18), and β1-AR and β2-
AR are downregulated (19). The activation of β-AR depends on release of neuronal
norepinephrine (NE), a key catecholamine of sympathetic nervous system (20), into the synaptic
cleft, where it binds to β-AR on the cardiomyocyte membrane (21). Decreased contractility due
to β-AR inactivity/reduction may be a consequence of increased sympatho-excitation (22). The
biosynthesis of NE is achieved through a cascade of reactions beginning with the rate-limiting
enzyme tyrosine hydroxylase (TH), which converts tyrosine to dihydroxyphenylalanine, and TH
is decreased in diabetic hearts (23). Tyrosine, which is a precursor for NE biosynthesis (20), is
catabolized by the enzyme tyrosine aminotransferase (TAT). TAT catalyzes transamination of
tyrosine in the liver, and deficiency of this enzyme causes tyrosinemia (24). In addition to liver,
TAT is present in the heart, brain and kidney (25). However, the interaction between TH and
TAT for the regulation of NE biosynthesis in the heart under normal and diseased conditions
such as diabetes is unknown.
The purpose of the present study was to determine the role of miR-133a in the regulation
of TAT, cross-talk between TH and TAT, and contractility by influencing NE biosynthesis
and/or β-AR levels in diabetic hearts.
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RESEARCH DESIGN AND METHODS
Ethics statement
All animal studies were performed following the guidelines of the National Institutes of Health
and protocol approved by the Institutional Animal Care and Use Committee (IACUC) of the
University of Nebraska Medical Center.
Animal model and treatment
Male Sprague-Dawley rats were obtained from the Charles River Laboratory. Each rat was caged
individually in the animal care facility of the University of Nebraska Medical Center. Rats were
kept in an ambient environment with the temperature maintained at 22°C and humidity at 30–
40% with diurnal cycle of 12 hour dark and 12 hour light. Laboratory chow and water was made
available to the rats ad libitum. Eight week male rats (~225 g) were injected with streptozotocin
(STZ, 45 mg/kg i.v., cat # S0130, Sigma-Aldrich, Saint Louis, MO, USA) to induce diabetes.
Control animals were treated with citrate buffer in which streptozotocin was dissolved. Four
weeks after streptozotocin treatment, blood glucose was measured to ensure rats developed
diabetic phenotype (blood glucose >350 mg/dL). To assess the effect of miR-133a
overexpression on diabetic hearts, these diabetic rats were treated with lentivirus containing
either miR-133a mimic or scrambled miRNA and sacrificed at the age of fourteen weeks
(Supplementary Figure 1A).
The miR-133a transgenic (miR-133aTg) mouse was a kind gift from Dr. Scot Matkovich,
Washington University, St. Louis, USA. C57BL/6J (WT) mice were procured from the Jackson
Laboratory. Both strains of the mouse were maintained in the animal facility of University of
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Nebraska Medical Center. Eight weeks male WT and miR-133aTg mice were treated with
streptozotocin (65 mg/Kg, i. p.) following a previously published protocol (8) for five
consecutive days. At the tenth-week blood glucose level was measured to ensure diabetic
phenotype (blood glucose >300mg/dL). At the fourteenth-week hemodynamic measurements
were performed, mice were sacrificed, and heart tissue was collected (Supplementary Figure
1B). No exogenous insulin was administered at any time to either rats or mice.
Assessment of Cardiac Function: In vivo hemodynamics
Left ventricular pressure and rate of change of left ventricular pressure (±dP/dt) was evaluated in
the controls, diabetic rats treated with scrambled miRNA or miR-133a mimic. Rats were
anesthetized with α-chloralose (70 mg/kg, i. p.) and urethane (0.75 g/kg, i. p.), and a Millar
catheter (Millar Instruments, Houston, TX, USA) containing a pressure transducer was
introduced into the left ventricle via the right carotid artery. Another catheter was inserted via the
right femoral vein for administration of isoproterenol. Cardiac hemodynamic parameters were
measured in the anesthetized state. After assessing basal parameters, a bolus dose (0.05, 0.1, 0.25
µg/kg) of isoproterenol, a β-AR agonist was administered into the right femoral vein to assess the
responsiveness of the heart to β-AR stimulation. A Powerlab data-acquisition system (AD
Instruments, Colorado Springs, CO, USA) was used for acquiring data.
Plasmids and constructs
MiR-133a (cat # MmiR3445-MR03), scrambled miRNA (cat # CmiR0001-MR03), anti-miR-
133a (cat # MmiR-AN0880-AM04) and TAT 3/ UTR clones (WT 3
/ UTR: cat # RmiT048999-
MT01 and Mutant 3/
UTR: CS-RmiT048999-MT01-01) were purchased from GeneCopoeia,
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Rockville, MD. TAT mouse cDNA clone (Cat # MC204147) was purchased from OriGene
Technologies, Inc. Rockville, MD, USA. TAT siRNA and negative control siRNA
oligonucleotides (cat # 4390771 and cat # 4390843) were purchased from Life Technologies,
Carlsbad, CA, USA.
In vitro model, Cell culture and transfection
In vitro studies were performed on a CATH.a neuronal (dopaminergic) cell line using standard
protocol and medium (RPMI, cat # R8758 with 8% horse serum and 4% fetal bovine serum, Life
Technologies, Carlsbad, CA, USA). In brief, cells were cultured and differentiated by treating
N6, 2′-O-Dibutyryladenosine 3′,5′-cyclic monophosphate (DB-cAMP, cat # D0627, Sigma-
Aldrich, St. Louis, MO, USA) for 48 hours. Then they were transfected with plasmid or siRNA
oligonucleotides for 24 hours using Lipofectamine 2000 (cat # 11668-019, Life Technologies,
Carlsbad, CA, USA). Transfected cells were processed for immunocytochemistry or harvested
for protein isolation at 48 hour post transfection.
Lentiviral packaging
The 293T cells were cultured on 10 cm2 plate up to ~90% confluence. 20µg of the vector (miR-
133a or scrambled) and 10 µg of each of RSV-REV, VSVG, and pMDLg/p RRE (plasmids for
virus proteins packaging) were co-transfected by using Opti-MEM media and lipofectamine
2000 (cat # 11668-019 and cat # 31985-070, Life Technologies, Carlsbad, CA, USA). Viral
supernatant was collected at 48 and 72 hours after transfection, and precipitated with sterile PEG
solution (cat # 81280, Sigma-Aldrich, St. Louis, MO, USA; 1 volume PEG to 4 volume viral
supernatant collection). The virus pellets were collected by centrifuging the PEG-precipitated
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viral supernatant solution at 2300 rpm for 2 hours at 40C. The virus pellets were re-suspended in
PBS and aliquoted in PCR tubes and kept at -800C until used. The virus titer was calculated by
infecting virus aliquots (2, 4, 8, 16 µL) in a 6-well plate seeded with 293T cell. After two days,
GFP-tagged (miR-133a-GFP and scm-GFP positive) cells were counted at 40X magnification in
four different fields of view for each well. The average number of GFP positive cells per 40X
magnification view was counted. The titer was calculated with the formula: total number of virus
particle/µL(volume) = average number of GFP +ve cell in 40X field of view x 4900/the volume
of virus infected in the cell culture well.
MiR-133a assay
MiRNA was isolated from the heart tissue (left ventricle) using the mirVana™ miRNA isolation
kit (cat # AM1560, Life Technologies, Carlsbad, CA, USA). The purity of RNA was determined
by NanoDrop 2000c (Thermo Scientific Inc., Wilmington, DE, USA), and highly pure RNA
(ratio of 260/280 ≥ 1.8 and 260/230 ≥ 1.8) was used for the assays. Individual miR-133a assay
was performed using miRNA-133a primers (Assay ID: 002246, Life Technologies, Carlsbad,
CA, USA) specific for RT and Taqman qPCR. U6 SnRNA primer (Assay ID: 001973, Life
Technologies, Carlsbad, CA, USA) was used for endogenous control. MiRNA amplification was
performed following manufacturer’s instructions using TaqMan Universal PCR Master Mix (cat
# 4427788, Life Technologies, Carlsbad, CA, USA). RT-qPCR was performed in a Bio-Rad
CFX qPCR System and the results were analyzed by using BioRad CFX Manager3.0 software
(Bio-Rad Laboratories, Hercules, CA, USA).
Reverse Transcription (RT)
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High-quality RNA was used for reverse transcription polymerase chain reaction (RT-PCR). First
strand cDNA was synthesized from an aliquot of 1 µg of RNA using iScript™ cDNA synthesis
kit (cat # 170-8841, Bio-Rad Laboratories, Hercules, CA, USA). The reaction was performed
with priming at 25°C for 5 min, reverse transcription at 42°C for 5 min and RT inactivation at
85°C for 5 min in a thermal cycler (C1000 Touch, Bio-Rad Laboratories, Hercules, CA, USA).
Quantitative RT-polymerase chains reaction (qRT-PCR)
The qPCR was performed using gene-specific oligonucleotide primers (Supplementary Table 1).
The assay was performed using 2X iTaq Universal SYBR Green Supermix (cat #172-5121, Bio-
Rad Laboratories, Hercules, CA, USA) according to the manufacturer’s instructions. In brief, the
PCR program was 95°C for 3 min and then 40 cycles of 95°C for 15 sec; 55°C for 30 sec and
72°C for 45 sec. The quantitative PCR reaction was performed in duplicate and it included: 4.5
µl, cDNA template diluted in nuclease free water (100 ng); 5 µl iTaq Universal SYBR Green
Supermix and 0.5 µl gene specific primer (10 pm). The forward and reverse primer sequences of
different genes are listed in Supplementary Table1. Bio-Rad CFX qPCR System was used for
RT-qPCR and data were analyzed using BioRad CFX Manager3.0 software (Bio-Rad
Laboratories, Hercules, CA, USA). Relative quantification in fold change (2-∆∆Ct
) was
normalized from expression of endogenous control 18s RNA.
Western blotting
The standard Western blotting protocol was followed after protein estimation by Pierce™ BCA
protein assay kit (cat # 23227, Pierce Biotechnology, Rockford, IL, USA). RIPA buffer (cat #
BP-115, Boston BioProducts, Worcester, MA, USA) supplemented with protease inhibitor
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cocktail (cat # MSSAFE, Sigma-Aldrich, St. Louis, MO, USA) was used for whole protein
extraction from rat hearts. For protein quantification, 40 µg of protein extracts were subjected to
10% SDS-PAGE and transferred onto nitrocellulose membrane (cat # 1620115, Bio-Rad
Laboratories, Hercules, CA, USA). Transferred membrane was blocked overnight with 5%
blocking solution (TBS with 5% non-fat dried milk). The primary antibodies used were β1-AR,
β2-AR , β-actin, β-tubulin (cat # sc-568, sc-570, sc-47778, and sc-23949, respectively from
Santa-Cruz Biotechnology, CA, USA), tyrosine hydroxylase (cat # 22941, ImmunoStar, Inc.
Hudson, WI, USA), tyrosine aminotransferase (cat # EPR6121, GeneTex Inc. Irvine, CA, USA)
for rat study, and cat # ab125000, Abcam, Cambridge, MA, USA) for mice study, SERCA-2a, β-
MHC and tyrosine hydroxylase antibodies were raised in rabbit and used for multiplex Western
blotting (cat # ab2861, ab172967, and ab112, respectively, Abcam, Cambridge, MA, USA),
GAPDH (cat # MAB374, Millipore, Temecula, CA, USA). Antibodies were diluted in the ratio
of 1:1000 and incubated for overnight at 4°C. Respective secondary antibodies with HRP
conjugates (anti-rabbit-HRP, cat # sc-2054, anti-mouse-HRP, cat # sc-2005, Santa-Cruz
Biotechnology, CA, USA) and fluorophore conjugates (anti-rabbit Alexa Fluor® 488, cat # A-
21441, anti-mouse Alexa Fluor® 594, cat # A-21201, Life Technologies, Carlsbad, CA, USA)
were diluted at 1:5000 and incubated at room temperature for 2 hours. The blots were developed
using ECL substrate (cat # 170-5061, Bio-Rad Laboratories, Hercules, CA, USA) or by
multichannel fluorescence imaging using Molecular Imager Chemi-DocTM
XRS with Image Lab
software, version 3.0 (Bio-Rad Laboratories, Hercules, CA, USA). The band intensity was
measured using the Image Lab software (Bio-Rad Laboratories, Hercules, CA, USA).
Immunocytochemistry
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Immunocytochemistry staining was performed on CATH.a neuronal cells differentiated with
DB-cAMP. Cells were transfected with 2 µg of scrambled miRNA or miR-133a mimic plasmid.
After treatment and transfection, the medium was removed and cells were washed in 1x
phosphate buffered saline (1xPBS) pH-7.4, and then fixed in 4% paraformaldehyde (cat #
158127, Sigma-Aldrich, St. Louis, MO, USA) for 30 minutes. After fixation, cells were washed
in 1xPBS for 3x5 minutes and then permeabilized in 0.02% Triton-X-100 (cat # 215682500,
Acros Organics, NJ, USA) in 1xPBS for 20 minutes. They were blocked in 1% BSA in 1xPBS
for 1 hour. They were then washed in 1xPBS for 3x5 minutes and incubated with diluted primary
antibodies in 1xPBS with 0.1% BSA at 4°C for overnight. The primary antibodies used were
1:400 dilution of anti-tyrosine hydroxylase (cat # 22941, ImmunoStar, Hudson, WI, USA) and
1:200 dilution of anti-tyrosine aminotransferase (cat # EPR6121, GeneTex, Irvine, CA, USA).
On next day, primary antibody was removed, and cells were washed in 1xPBS for 3x5 minutes
and incubated with anti-mouse AlexaFluor 594 (cat # A21201, Life Technologies, Carlsbad, CA,
USA) or anti-rabbit AlexaFluor 488 (cat # A21441, Life Technologies, Carlsbad, CA, USA) for
1 hour in dark. The secondary antibody was removed and cells were washed with 1xPBS for 3x5
minutes. They were then incubated with 1µg/ml DAPI in 1xPBS (cat # A1001, AppliChem, St.
Louis, MO, USA) for 20 minutes. After that, cells were washed twice in 1xPBS and mounted
with a coverslip using the Fluoromount-G mounting medium (Cat # 0100-01, Southern Biotech,
Birmingham, AL, USA). Images were captured by EVOS Cell Imaging Systems (Life
Technologies, Carlsbad, CA, USA) and analyzed by Image J software (NIH, USA).
Bioinformatics analyses of TAT 3/-UTR
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In silico analyses predicts TAT as a putative target of miR-133a. The search websites were
TargetScan (www.targetscan.org) and miRDB (www.mirdb.org).
Noradrenaline assay
Norepinephrine (NE) content was measured by Norepinephrine ELISA Assay Kit (cat # NOR31-
K01, Eagle Biosciences, Inc. Nashua, NH, USA). Blood plasma and left ventricular tissue lysate
from treated rats were used for norepinephrine assay. Plasma was isolated by collecting the
blood from renal vein in a 1 ml syringe with EDTA and separated from blood clot by
centrifuging in a 2 ml centrifuge tube at 2000 rpm. Cleared plasma after centrifugation was
stored at -80°C until use. For tissues, the dissected left ventricle of the heart was rinsed with ice-
cold saline and frozen immediately on dry ice and weighed. Norepinephrine was extracted from
the tissue by homogenization in 10 volumes of 0.1 mol/L HCl followed by centrifugation at
5000×g, for 20 min at 4°C.
Sucrose-Phosphate-Glyoxylic acid (SPG) chemifluorescence
The glyoxylic acid condensation reaction was used for fluorescence detection and distribution of
catecholaminergic nerves on 15 µm histological cryosections. The staining was followed as per
previously described protocol (26). In brief, frozen histological sections were adhered onto glass
slides and immersed promptly in sucrose-phosphate-glyoxylic acid solution (1% glyoxylic acid,
0.23 M monobasic KH2PO4, 0.2 M sucrose, pH 7.4) for 5 sec. Slides were dried entirely under a
cool stream of air and heated to 95°C for 2.5 min after applying a thin layer of mineral oil on
tissue surface. Slides were then cooled to room temperature and sealed with cover slip. Bluish-
white fluorescence of catecholamine on tissue section was captured by fluorescence microscopy
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with UV filter (Life Technologies, Carlsbad, CA, USA) and images were quantified by Image J
software (NIH, USA).
DAB-HRP Immunohistochemistry
Immunohistochemistry was performed on 5 µm transverse cryosections. In brief, the histological
section was dipped in 1xPBS to dissolve the freezing medium, processed for citrate antigen
retrieval (heating-cooling) and fixed in 4% paraformaldehyde for 30 min at room temperature.
Endogenous peroxidase activity was quenched by incubating slides in peroxidase suppressor
solution (3% H2O2). After quenching, slides were blocked in 1% serum (goat or horse) in 1xPBS
for 30 minutes. Slides were washed two times for 3 minutes with 1xPBS and incubated with
primary antibodies for 3 hours at 4°C. Primary antibodies used were tyrosine hydroxylase, 1:400
(cat # 22941, ImmunoStar, Hudson, WI, USA), tyrosine aminotransferase, 1:200 (cat #
EPR6121, GeneTex, Irvine, CA, USA), and anti-GFP horseradish peroxidase (HRP) conjugate,
1:500 (cat # A10260, Life Technologies, Carlsbad, CA, USA). Sections were washed in 1xPBS
for 3x5 minutes and incubated with respective HRP-conjugated secondary antibodies, anti-
rabbit-HRP (cat # sc-2054, Santa-Cruz Biotechnology, CA, USA) or anti-mouse-HRP (cat # sc-
2005, Santa-Cruz Biotechnology, CA, USA), as applicable, for 1 hour at room temperature in a
humidified chamber. Secondary antibody was removed and sections were washed with 1xPBS
for 3x5 minutes and incubated with fresh Sigma FAST DAB tablet solution (cat # D4293,
Sigma-Aldrich, St. Louis, MO, USA). Sections were then washed twice in 1xPBS and
counterstained with Harris modified Hematoxylin (Cat # 1859352, Pierce Biotechnology,
Rockford, IL, USA), and mounted with a coverslip using Permount Mounting Media (cat #
SP15-100, Thermo Scientific Inc., Waltham, MA, USA). Images were captured by bright field
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colored microscope (Leica Microsystems, Buffalo Grove, IL, USA) with image Pro 7.0 capture
tool.
Fluorescence Immunohistochemistry
Fluorescence immunohistochemistry was performed on 5 µm transverse cryosections following
standard protocol. Primary antibodies used were anti-sercomeric alpha actinin, 1:100 (cat #
ab9465, Abcam, Cambridge, MA, USA) and anti-GFP, 1:500 (cat # ab13970, Abcam,
Cambridge, MA, USA). Secondary antibodies used were anti-mouse AlexaFluor 488 (cat #
A21200, Life Technologies, Carlsbad, CA, USA) and anti-chicken AlexaFluor 594 (cat #
ab150176, Abcam, Cambridge, MA, USA).
Wheat Germ Agglutinin (WGA) staining
Wheat germ agglutinin staining was performed to stain cardiomyocyte cell boundaries and was
used for measurement of cell area and hypertrophy. Frozen histological sections of the heart
were kept in 1xPBS for 5 min to dissolve the freezing medium. Hydrated sections were fixed
with freshly prepared 4% formaldehyde for 15 min at 37°C and then washed 3×5 min with
1xPBS. Next, 100-200 µL of 5 µg/mL wheat germ agglutinin (cat # W834, Life Technologies,
Carlsbad, CA, USA) conjugate solution was applied onto the sections and incubated for 1 hour at
room temperature. The sections were counterstained with DAPI. Slides are mounted with a
coverslip and observed under microscope. The images were captured by EVOS Cell Imaging
Systems (Life Technologies, Carlsbad, CA, USA) and analyzed by Image J software (NIH,
USA).
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Luciferase reporter assay
To measure luciferase activity, CATH.a cells were plated (60% confluence) in incomplete RPMI
medium. Cells were co-transfected with 1µg of 3/UTR clone with 0 µg, 1 µg and 2 µg of
scrambled miRNA or miR-133a mimic plasmid. Luciferase reporter assay was performed after
48 hours of transfection using Dual-Glow luciferase assay kit (cat # E2920, Promega
Corporation, Madison, WI, USA) following the manufacturer’s instructions in a GloMax®-
Multi+ Detection System (Promega, Madison, WI, USA).
Statistical analyses
The statistical values were expressed as mean ± standard error of mean (SEM). The reverse
transcription, qPCR and Western blotting experiments were repeated at least thrice in three
independent samples unless otherwise represented. Statistical analysis was performed by paired
Student's t-test and one-way ANOVA was used to compare among groups. P <0.05 value are
considered as statistically significant.
RESULTS
Decreased contractility of the diabetic heart is normalized by miR-133a mimic treatment
Previous studies have shown that miR-133a has a role in the contractility of pressure overload
heart (27) and miR-133a is downregulated in diabetic hearts (28). To determine whether the lack
of miR-133a decreased the contractility of the diabetic heart, we overexpressed miR-133a in the
diabetic hearts by miR-133a mimic treatment and validated the upregulated miR-133a in the
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diabetic hearts by individual miR-133a assay (Supplementary Figures 2A-C). We measured left
ventricular (LV) pressure and rate of contraction and relaxation (±dP/dt) of the miR-133a mimic-
treated diabetic hearts at the basal level and after isoproterenol (a β-AR agonist) infusion using a
Millar catheter. Our results showed that miR-133a mimic treatment normalized the decreased LV
pressure and ±dP/dt in the diabetic hearts (Figures 1A-B), suggesting that reduced level of miR-
133a may contribute to decreased contractility of the diabetic hearts. Interestingly, the rate of
contraction (dP/dt) was significantly improved by miR-133a mimic after isoproterenol treatment
(Figure 1B), suggesting that β-AR may be an important player in miR-133a-mediated
improvement in the contractility of the diabetic hearts.
MiR-133a mimic treatment upregulates β-AR and SERCA-2a in diabetic hearts
To investigate if miR-133a influenced β-AR expression in diabetic hearts, we measured β1-AR
and β2-AR mRNA and protein levels in scrambled miRNA-, and miR-133a mimic- treated
diabetic hearts. The mRNA and protein levels of both β1-AR and β2-AR were increased in miR-
133a mimic-treated hearts (Figures 2A-D), suggesting that miR-133a overexpression has
upregulated β-AR in the diabetic hearts. β-AR activation normally upregulates calcium influx in
the cytoplasm, which triggers sarco-endoplastic reticulum activity for sarcomeric contraction that
increases the contractility of the heart. Decreased sarco-endoplasmic reticulum activity
contributes to decreased contractility of diabetic hearts (14;18). To determine whether miR-133a
improved the contractility of the diabetic heart by influencing sarco-endoplasmic reticulum
activity, we measured the protein level of SERCA-2a, a calcium handling enzyme in sarco-
endoplasmic reticulum, in the heart. Our results showed that miR-133a mimic treatment
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upregulated SERCA-2a in the diabetic hearts (Figure 2E). Overall, these results suggest that
miR-133a improved the contractility of the diabetic hearts by upregulating β-AR and SERCA-2a.
To support that miR-133a mimic treatment had a similar effect on the diabetic heart as
previously reported, we investigated cardiac hypertrophy in miR-133a mimic-treated diabetic
hearts because the anti-hypertrophy effect of miR-133a, possibly by suppression of GLUT4 via
targeting KLF15 (29), was documented in the non-diabetic (6) and diabetic (30) hearts. To
determine cardiac hypertrophy, we measured the level of β-myosin heavy chain (β-MHC), a
molecular marker for hypertrophy (Supplementary Figure 3A), and cross-sectional area of
cardiomyocytes in histological sections of the heart (Supplementary Figure 3B). Our results
showed that miR-133a mimic treatment mitigated cardiac hypertrophy in the diabetic hearts
(Supplementary Figure 3) demonstrating that miR-133a had a similar impact on the diabetic
hearts as previously reported.
MiR-133a upregulates norepinephrine in diabetic hearts
To determine the role of miR-133a on upstream signaling molecules that might have activated β-
AR in the diabetic heart, we measured NE levels because NE activates β-AR, and cardiac NE is
decreased in the failing heart (31). Notably, miRNAs are associated with reduced NE level in
chronic heart failure (32). Therefore, we sought to determine the impact of miR-133a
overexpression on NE level in diabetic hearts. Before measuring the cardiac NE level, we
measured the plasma NE level because it is documented that plasma NE level is increased in
most forms of heart failure (33). The plasma NE level was increased in the scrambled miRNA-
treated diabetic rats. However, it was decreased in miR-133a mimic-treated diabetic rats (Figure
3A), suggesting that miR-133a mimic treatment decreases the plasma NE level in diabetic rats.
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Then we measured the cardiac tissue level of NE in miR-133a mimic-treated diabetic hearts.
Contrary to the plasma NE level, the cardiac NE level was lower in the scrambled miRNA-
treated diabetic rats, and it was restored after miR-133a mimic treatment (Figure 3B). These
findings suggest that miR-133a has a crucial role in regulating the cardiac and plasma NE levels
in diabetics.
The endogenously released NE is stored in the nerve endings and intraneuronal storage of NE
is decreased in diabetic hearts (34). To determine the role of miR-133a in intraneuronal storage
of NE in diabetic hearts, we stained cryosections of the heart with sucrose-phosphate-glyoxylic
acid (SPG). The SPG binds to catecholamines and detects catecholamine storage in sympathetic
neuron terminals in the heart by chemifluorescence (Figure 3C (i)). Our results showed that miR-
133a mimic treatment increased cardiac NE storage in the diabetic hearts (Figure 3C (ii-iii)),
which further support that miR-133a overexpression upregulated cardiac NE in the diabetic
hearts. Overall, these findings demonstrated that miR-133a has a pivotal role in maintaining
plasma and cardiac NE levels in diabetic rats. However, it was unclear how miR-133a
normalized the NE levels in diabetics.
MiR-133a mimic treatment upregulates tyrosine hydroxylase in diabetic hearts
To understand the underlying mechanism of miR-133a-mediated regulation of NE levels, it was
imperative to investigate the biosynthesis of NE. Since NE is synthesized from tyrosine by TH,
we determined TH levels in miR-133a mimic-treated diabetic hearts. The messenger RNA and
protein levels of TH were upregulated in miR-133a mimic-treated diabetic hearts (Figures 4A-B)
suggesting that miR-133a induces TH gene expression. To determine the expression of neuronal
TH in diabetic hearts, we performed immunohistochemistry of TH in cryosections of the diabetic
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hearts. Our results showed increased intensity of neuronal TH in miR-133a mimic-treated
diabetic hearts (Figure 4C) corroborating that miR-133a mimic treatment increased the neuronal
TH in the diabetic hearts.
To validate that increase in the TH level was neuronal, we stained the heart sections with
TH and a neuronal marker, microtubule-associated protein 2 (MAP2). The imaging of the heart
sections showed co-localization of MAP2 with TH (Supplementary Figure 4A) demonstrating
that increases in the TH level in the miR-133a mimic-treated diabetic hearts was indeed
neuronal. Further, we used the same antibody that stains neuronal TH in the heart
(Supplementary Figure 4B) to assess the expression of TH in CATH.a cells, a validated
catecholaminergic neuronal cell line (Supplementary Figure 4D), which corroborated that TH
expressed in the heart was neuronal.
To determine the specific role of miR-133a in the regulation of neuronal TH level, we
treated CATH.a neuronal cells that express miR-133a (Supplementary Figure 4C) with
scrambled, miR-133a mimic and anti-miR-133a, and determined the protein level of TH in these
three groups. Our results demonstrated that miR-133a mimic treatment upregulated TH (Figures
4D-E). However, there was no change in the TH level in anti-miR-133a-treated neurons (Figure
4E) suggesting that miR-133a may not have a direct or causative role in the regulation of TH
level in neurons. Since miRNA mostly inhibits genes, we infer that miR-133a mimic treatment
might have upregulated TH by inhibiting another gene that normally suppresses TH.
Tyrosine aminotransferase inhibits tyrosine hydroxylase in neuronal cells
Since tyrosine is a substrate for TH and tyrosine is catabolized by TAT (24), we suspected that
TAT might have an influence on TH level. Although TAT has been reported to be present in the
Page 19 of 63 Diabetes
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heart (25), its role in the heart remains unclear. To determine the specific effect of TAT on the
TH level, we first validated whether TAT was present in the neurons. For that, CATH.a neuronal
cells were stained with anti-TAT antibody and cellular level of TAT was observed. As
speculated, TAT was present in the neuronal cells (Supplementary Figure 4E). Then, we either
overexpressed or inhibited TAT in CATH.a neuronal cells (Supplementary Figures 4F-G) and
measured the levels of TH. Our results revealed that suppression of TAT upregulated TH
(Figures 5A-B), whereas overexpression of TAT downregulated TH in neuronal cells (Figure
5A, C). These findings suggest that TAT has an inhibitory effect on TH. Since TH is the rate-
limiting enzyme in NE biosynthesis, TAT might have an indirect influence on NE biosynthesis.
MiR-133a modulates tyrosine aminotransferase in diabetic hearts
Although our results demonstrated that miR-133a mimic treatment increased the level of TH in
diabetic hearts (Figure 4), it was unclear whether miR-133a upregulated TH by downregulating
TAT in the heart. To determine the role of miR-133a on TAT level, we measured mRNA and
protein levels of TAT in scrambled miRNA-, and miR-133a mimic- treated diabetic hearts. Our
results revealed that miR-133a mimic treatment decreased TAT expression in the diabetic hearts
(Figures 6A-B) suggesting that miR-133a suppresses TAT. Since TAT inhibited neuronal TH,
we sought to determine whether miR-133a decreased neuronal TAT in diabetic hearts. For that,
neuronal TAT was stained in diabetic heart sections and was observed under a microscope. Our
results showed that miR-133a mimic treatment reduced the levels of neuronal TAT in diabetic
hearts (Figure 6C).
To determine whether miR-133a had a direct role in inhibition of neuronal TAT, we
treated CATH.a neuronal cells with scrambled miRNA, miR-133a mimic, and anti-miR-133a,
Page 20 of 63Diabetes
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and then measured the levels of TAT. Our results demonstrated that miR-133a mimic treatment
downregulated TAT expression at cellular and protein levels (Figure 6D-E), whereas anti-miR-
133a treatment upregulated TAT expression (Figure 6E). These findings suggest that miR-133a
might have a direct role in regulating TAT expression in neuronal cells.
Cardiac-specific overexpression of miR-133a in mice prevents streptozotocin-induced
upregulation of TAT and downregulation of TH in the heart
To rule out the systemic effect of miR-133a mimic delivery and to validate the cross-species role
of miR-133a on TAT and TH, we used miR-133Tg mice and treated them with streptozotocin
(Supplementary Figure 1B). We also genotyped (Supplementary Figure 2D) and measured the
cardiac levels of miR-133a (Supplementary Figure 2E) in these mice before measuring the TAT
and TH levels in the heart. The comparison of TH levels in WT and miR-133a transgenic mice
(miRTg) treated with and without streptozotocin demonstrated that TH level was decreased in
streptozotocin-treated WT mice, but it remained upregulated in streptozotocin-treated miR-
133aTg mice (Figures 7A (i and ii)). On the contrary, protein levels of TAT were elevated in
streptozotocin-treated WT mice, but it remained decreased in streptozotocin-treated miR-133aTg
mice (Figures 7A (i and iii)). Based on these results we infer that cardiac specific overexpression
of miR-133a prevents diabetes-mediated upregulation of TAT and downregulation of TH in the
heart. Moreover, we also performed immunohistochemistry for TAT and TH in the heart sections
of WT and miR-133aTg mice treated with or without streptozotocin. We observed that
streptozotocin treatment decreased the number of neurons expressing TH in WT, but the number
Page 21 of 63 Diabetes
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of TH-expressing neurons remained comparatively high in miR-133aTg mice after streptozotocin
treatment (Figure 7B (i)). Then we measured the levels of TAT-expressing neurons. In contrast
to TH, the number of TAT-expressing neurons were increased in streptozotocin-treated WT
hearts. However, it remained downregulated in streptozotocin-treated miR-133aTg hearts (Figure
7B (ii)). Overall, these results revealed that the inhibitory effect of miR-133a on TAT is common
in both mice and rat species, and overexpression of miR-133a suppresses TAT and induces TH
in diabetic hearts of mice and rats.
MiR-133a targets tyrosine aminotransferase
MiRNA modulates gene expression by targeting 3 prime untranslated region (3´UTR) of mRNA.
Therefore, we performed in silico analyses for miR-133a predicted targets, and found that TAT
was a target for miR-133a (Figure 8A). The binding site for miR-133a on TAT 3´UTR was
conserved in mouse and rat, however, mouse had three binding sites whereas rat had a single
binding site (Supplementary Figure 5). To determine whether the TAT was a direct target for
miR-133a, we used TAT 3´UTR, and the miR-133a binding sequence mutant TAT 3´UTR
(Figure 8B), and performed luciferase reporter assay on CATH.a neuronal cells. Our results
showed that miR-133a downregulated luciferase activity of 3´UTR of TAT, which was nullified
in the mutant 3´UTR of TAT (Figures 8C-D). These findings revealed that miR-133a targets
TAT.
Overall, our results demonstrated that miR-133a has a direct role in suppressing TAT. Since
TAT inhibited TH, miR-133a mimic might be indirectly upregulating TH and thus regulates NE
biosynthesis, which consequently leads to upregulation of β-AR and improved myocardial
contractility in diabetics.
Page 22 of 63Diabetes
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DISCUSSION
In the present study, we demonstrate that lack of miR-133a contributes to decreased contractility
of diabetic hearts and miR-133a mimic treatment can improve the contractility of diabetic hearts.
We propose that downregulation of miR-133a in the diabetic heart increases TAT level that in
turn suppresses TH and decreases cardiac NE level, which compromises β-AR activation and the
contractility of the diabetic hearts. MiR-133a mimic treatment normalizes TAT and restores the
levels of TH, NE, β-AR, and the contractility of the diabetic hearts (Figure 8E). In this study, we
reveal several novel regulatory mechanisms such as miR-133a acts as an inducer of β-AR by
regulating upstream activators of β-AR in diabetic hearts. Lack of miR-133a decreases the
contractility of diabetic hearts. TAT is present in the neurons of diabetic hearts and it inhibits
TH, which may influence NE biosynthesis and β-AR in diabetic hearts. MiR-133a directly
modulates TAT expression in diabetic hearts.
MiRNAs play a crucial role in regulating the contractility of the heart. Several miRNAs
decrease the contractility while others increase the contractility of the heart. In human heart
failure, upregulation of miR-765 decreases contractility by regulating protein phosphatase
inhibitor-1 (35). In mice and humans, SERCA-2a is regulated by miR-25. The inhibition of miR-
25 improves the contractility of the failing heart by upregulating SERCA-2a (36). In a rabbit
model of congestive heart failure, pacing improves contractility concomitant with upregulation
of SERCA-2a and miR-133a (37). In heart failure and diabetic cardiomyopathy, SERCA-2a is
downregulated (38). Our results demonstrate that miR-133a mimic treatment upregulates
SERCA-2a in diabetic hearts (Figure 2E) and improves contractility (Figures 1A-B), which
further support that miRNAs have a pivotal role in SERCA-2a regulation and cardiac
contractility. Calcium influx also plays an important role during contractility of cardiomyocytes
Page 23 of 63 Diabetes
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and it is regulated by the sodium/calcium exchanger1 (Ncx1). MiR-214 regulates Ncx1 and
improves the contractility of the ischemic heart (39). In the pressure-overload model of heart
failure, miR-133a modulates β1-AR and its downstream signaling molecules that regulate the
contractility of the heart (27). In abdominal aortic constriction-induced pressure-overload model
in mice, deficiency of insulin-like growth factor-1 upregulates miR-133a to alleviate myocardial
contractile dysfunction (40). However, the role of miRNAs in regulation of the contractility of
diabetic hearts is poorly understood. In this study, we reveal that miR-133a, which is anti-
hypertrophy (30) and anti-fibrotic (8) in diabetic hearts, regulates contractility of the heart.
Although miR-133a has been reported to modulate β-AR and its downstream signaling
cascade in a pressure overload heart failure (27), the role of miRNAs in the regulation of
upstream activators of β-AR have not been elucidated. Our data show for the first time that miR-
133a has a crucial role in controlling the upstream activators of β-AR, especially NE
biosynthesis in diabetic hearts (Figure 3). Our results also support a previous report indicating
that miRNA expression is associated with catecholamine sensitivity (32). However, miR-133a-
mediated activation of β-AR in diabetic hearts (Figures 2A-D) differs from miR-133a-mediated
inhibition of β1-AR in the pressure overload heart (27). The different roles of miR-133a in β-AR
activation in the diabetic and pressure overload hearts suggest that miR-133a may normalize the
contractility of diabetic hearts by targeting other upstream signaling molecules that activate β-
AR in the diabetic hearts. Another reason could be that diabetic heart differs from other failing
hearts in the metabolic conditions (9). Further, we overexpressed miR-133a in rats by delivering
miR-133a mimic, whereas in the pressure overload model miR-133a transgenic mice were used
(27). In the miR-133a transgenic mice, there are discrepancies in the results on cardiac functions
depending on the α-myosin heavy chain (MHC) or β-MHC promoter being used (41;42). Our
Page 24 of 63Diabetes
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studies on miR-133a transgenic mice with α-MHC promoter revealed that cardiac specific
overexpression of miR-133a prevents downregulation of TH in diabetic condition (Figure 7),
which is similar to our results with diabetic rats (Figures 4A-C, 6A-C). Further studies on other
models of heart failure will provide insight on the miR-133a-mediated regulation of TAT, NE
and β-AR in the heart.
Increased plasma NE level is common in all forms of heart failure including diabetic
heart failure (33;34;43;44). Our results show that miR-133a mimic treatment decreases plasma
NE level (Figure 3A). There is a possibility that miR-133a either mitigates the conditions that
increase plasma NE level or stimulates the conditions that decrease plasma NE level or both.
Since miR-133a increases the cardiac NE storage in diabetic hearts (Figures 3B-C), it is a
possibility that miR-133a may decrease/influence NE release/spill over from nerve terminals in
the heart that reduce plasma NE level. Although these processes remain to be elucidated, it was
interesting to observe that miR-133a mimic treatment decreases plasma NE level in diabetic rats.
Cardiac NE level may not be same in the heart failure (45) and diabetic cardiomyopathy (22).
The level of cardiac NE depends on NE storage in the nerve endings and its release in the
myocardium. By using [3H] NE, it is reported that intraneuronal storage granules of NE in the
diabetic myocardium is defective (34) suggesting that storage of cardiac NE may be
compromised in diabetic hearts. SPG–induced histofluorescence has been used to visualize the
nerve profile in the heart and to demonstrate that loss of noradrenergic nerve terminal contributes
to right heart failure (45). We also used SPG to assess nerve profile in miR-133a mimic-treated
diabetic hearts. Our results reveal that miR-133a mimic treatment increases the number of NE
containing nerves in the diabetic heart (Figure 3C) suggesting that miR-133a mimic treatment
protects the diabetic heart from noradrenergic nerve loss. Moreover, our results are consistent
Page 25 of 63 Diabetes
26
with the previous report that nerve density is reduced in diabetic hearts (23). It also supports that
miRNAs are involved in catecholamine level in heart failure patients (32).
The biosynthesis of NE is increased by upregulation of TH (20). TH gene has a
tetranucleotide repeat in intron 1, which is associated with regulation of NE level and
hypertension (46). The cardiac level of TH is decreased in the diabetic (23;47) and failing hearts
(31). Our results show that miR-133a mimic treatment increased TH level in diabetic hearts
(Figure 4). However, the regulation of TH in the diabetic heart has not been completely
understood and the impact of TAT on NE biosynthesis was unknown. For the first time, we
elucidate that neuronal TH is regulated by TAT (Figure 5). Therefore, our results provide a novel
insight into a possibility of TAT-mediated indirect regulation of NE biosynthesis. It opens a new
window to understanding the regulation of TH in different disease conditions including
hypertension and heart failure.
TAT has a crucial role in tyrosinemia type II, hepatitis and hepatic carcinoma (24). It
regulates glucocorticoids in the liver of diabetic rodents (48). Although TAT is present in the
heart (49), its functional role in the heart is yet unclear. In the present study, we reveal that TAT
is a regulator of TH and elevated level of TAT downregulates TH in nerve terminals in the
diabetic heart (Figure 5). Interestingly, TAT is a target for miR-133a (Figures 8A-D) and miR-
133a mimic treatment decreases the level of TAT in nerve terminals (Figure 6D-E). The miR-
133a mimic-treated diabetic hearts also show decreased levels of TAT (Figures 6A-C) indicating
a novel regulatory role for miR-133a on TAT expression. Our results also open an avenue for
exploring the role of miR-133a in TAT-regulated diseases such as tyrosinemia type II, hepatitis
and hepatic carcinoma.
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Diabetic heart failure is a multifactorial disease that increases the risk of heart failure (50)
and ultimately causes multi-organ failure. Despite the advancement of medical research, the
prevalence of diabetes is increasing at an alarming rate (10;11), which warrants novel therapeutic
strategies to combat its complications. MicroRNA-based therapy offers a novel and advanced
approach for developing the treatment strategy for several diseases (51) including cancer, where
miR-34 is currently in clinical trial (ClinicalTrails.gov Identifier: NCT01829971). Therefore,
miRNA-based therapy could be a promising approach to normalizing diabetes-mediated
complications in the heart. Considering the multi-faceted cardioprotective role of miR-133a (5)
and the results of the present study, it is suggested that miR-133a could be a novel candidate for
exploring future therapeutic modality for diabetic heart failure.
In conclusion, we demonstrate a novel, cardioprotective role of miR-133a in the diabetic
heart. We show that miR-133a protects the heart of streptozotocin-treated diabetic rats/mice by
directly targeting TAT and TAT-TH crosstalk. TH and TAT enzymes are critically involved in
the biosynthesis of NE, a key catecholamine stimulating the contractility of the heart muscle. Our
results also demonstrate that miR-133a mimic treatment decreased plasma NE levels. These
findings by elucidating the cardio-neuronal cross-talk may help to understand the molecular
mechanisms underlying diabetic and non-diabetic forms of heart failure.
Limitations
The role of miR-133a in the pathophysiology of diabetic hearts and impact of hyperglycemia on
miR-133a functions are poorly understood. Further, the results obtained from mice or rat data
may vary from humans with diabetic heart failure. Our results in the present study are focused on
Page 27 of 63 Diabetes
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T1D model using streptozotocin treatment that needs to be further validated with other models of
T1D as well as T2D.
Acknowledgments
We would like to thank Dr. Scot Matkovich, Washington University, St. Louis, USA for giving
us cardiac specific miR-133a transgenic mice, Dr. Howard S. Fox, University of Nebraska
Medical Center for his generous gift of SH-SY5Y neuronal cell line, and Xuefei Liu from our
Department for his technical support.
Funding
This work was supported, in parts, by the National Institutes of Health grants HL-113281 and
HL-116205 to Paras K. Mishra.
Duality of Interest
No conflict of interest relevant to this article was reported.
Author Contributions
SSN designed the study, performed experiments, analyzed results, and contributed to discussion
and writing of the manuscript, HZ, NMS, HRS contributed to experiments and data analyses,
KPP contributed to discussion and correcting the manuscript draft, PKM conceptualized the idea,
supervised the project, and wrote the manuscript. PKM is the guarantor for this study and has full
Page 28 of 63Diabetes
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access to the data in the study and takes responsibility for the integrity of the data and accuracy
of the data analyses.
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rats]. Biokhimiia 55:59-64, 1990
50. Grundy,SM, Benjamin,IJ, Burke,GL, Chait,A, Eckel,RH, Howard,BV, Mitch,W,
Smith,SC, Jr., Sowers,JR: Diabetes and cardiovascular disease: a statement for healthcare
professionals from the American Heart Association. Circulation 100:1134-1146, 1999
51. van,RE, Purcell,AL, Levin,AA: Developing microRNA therapeutics. Circ Res 110:496-
507, 2012
Page 32 of 63Diabetes
33
Figures Legends
Figure 1. MiR-133a mimic treatment improves contractility of the diabetic heart. A,
Pressure-volume loop study on control, scrambled miRNA treated diabetic (DM+scm), and miR-
133a mimic treated diabetic (DM+miR) rats. A(i), Representative left ventricular pressure
recordings of hearts from three groups. A(ii), Bar graph showing the mean values of left
ventricular pressure with standard error. B(i), Representative recordings of rates of left
ventricular pressure changes over time (± dp/dt) in hearts from the three groups at the basal level
and after treatment with 0.1µg/kg isoproterenol (a β-AR agonist). B(ii), Bar graph showing the
mean value of dp/dt with standard error of mean in the three groups at the basal level and with
two increasing doses of isoproterenol. N, Sham=5, DM+scm=6, DM+miR-133a=5.
Page 33 of 63 Diabetes
34
Figure 2. MiR-133a mimic treatment upregulates β1-AR, β2-AR, and SERCA-2a in the
diabetic heart. RT- qPCR and Western blot analyses was performed to assess the levels of β1-
AR, β2-AR, and SERCA-2a in diabetic hearts treated with scrambled miRNA (DM+scm) and
miR-133a mimic (DM+miR). A, Bar graph represents relative fold change of β1-AR mRNA.
18sRNA was used as an internal control. B, Top, representative Western blot bands of β1-AR and
actin (a loading control); Bottom, bar graph represents densitometric quantification of band
intensity in fold change. C, Bar graph represents relative fold change of β2-AR mRNA. 18sRNA
was used as an internal control. D, Top, representative Western blot bands of β2-AR and actin
(loading control); Bottom, bar graph represents densitometric quantification of band intensity in
fold change. E, Top, representative Western blot bands of SERCA-2a and tubulin (a loading
control); Bottom, bar graph represents densitometric quantification of band intensity in fold
change. The values are mean±SEM. n=6.
Figure 3. MiR-133a mimic treatment decreases plasma norepinephrine (NE) and increases
cardiac NE in diabetic rats. A, ELISA based quantification of NE level from plasma samples
and B, from left ventricle tissue sample. The bar diagram shows NE level in ng/ml of plasma or
ng/mg of tissue. The values are mean±SEM. N, control=3, DM+scm=6, DM+miR=6. C,
Visualization of nerve profile in the cryosections of the heart by sucrose-phosphate-glyoxylic
acid (SPG) histofluorescence. C (i), Representative images showing histofluorescence of SPG in
15 µm transverse sections of left ventricle in different color channels. The arrow points to white
regions where catecholamine are stored in sympathetic nerve terminals. The merged green and
red channels on right panel validate the purity and source of intense signal from innervated
sympathetic neuron terminals (arrows) and the level of background autofluorescence. Scale bar:
100 µm. C (ii), Representative SPG histofluorescence images of cryosections of the heart from
Page 34 of 63Diabetes
35
DM+scm and DM+miR groups. The intense white color (arrows) represents SPG
chemifluorescence of catecholamine from sympathetic neuron terminals, image are transformed
from RGB to gray scale for better clarity. C (iii), Bar diagram shows quantification of SPG
fluorescence intensity and represented as fold change. The values are mean ±SEM, n=3. Scale
bar: 200 µm.
Figure 4. MiR-133a mimic treatment increases tyrosine hydroxylase in diabetic hearts. A,
Evaluation of tyrosine hydroxylase (TH) mRNA in diabetic hearts treated with scrambled
miRNA (DM+scm) and miR-133a mimic (DM+miR) by RT-qPCR. 18sRNA was used as an
endogenous control. The mRNA expression is presented as fold change. The values are mean
±SEM, n=3. B, Western blot analysis of TH protein in the hearts from the above two groups.
Top, representative bands of TH and gapdh (a loading control); Bottom, bar graph shows
densitometric analyses of relative TH protein in the heart and represented as fold change. The
values are mean ±SEM, n=6. C, left, Schematic drawing shows the area of cryosections of the
heart and sympathetic innervations in the heart. Transverse section of the heart is observed for
sympathetic innervations. LV, Left Ventricle and RV, Right Ventricle. Right, Representative
diaminobenzidine (DAB) immunohistochemical staining of TH and counterstaining of
hematoxylin in the heart sections of the two groups. Scale bar: 200µm. D, MiR-133a mimic
treatment induces TH in CATH.a neuron cell. Undifferentiated CATH. a neuron cells were
transfected with miR-133a mimic plasmid for 24 hour, and the cellular level of miR-133a (green,
shown by an arrow) and TH (red, shown by an arrowhead) was observed in the neuronal cells.
DAPI (blue) stains nucleus. The miR-133a overexpressing cells have high expression of TH. E,
CATH.a cells were treated with either scrambled miRNA (scm), miR-133a mimic (miR), or
Page 35 of 63 Diabetes
36
antimiR-133a (anti-miR), and proteins were extracted after 24 hour. Top panel, representative
Western blot of TH and gapdh (control) from the three groups. The bottom panel shows
densitometry analyses of bands and represented as fold change. The values are mean ±SEM.
n=3.
Figure 5. TAT inhibits TH in neurons. CATH.a cells were transfected with TAT plasmid or
TAT siRNA for 24 hours and proteins were extracted from treated cells for evaluation of TH
level by Western blotting. A, Representative Western blot bands of TH in TAT knockdown (si-
TAT) and overexpressing (OE-TAT) cells. Gapdh is a loading control. B, Densitometric analyses
of TH level in the TAT knockdown neuronal cells. The bar graph shows relative upregulation of
TH after knockdown of TAT. C, Densitometric analyses of TH level in the TAT overexpressing
cells. The bar graph shows relative downregulation of TH after TAT overexpression. Values are
mean ± SEM. N=3.
Figure 6. MiR-133a mimic treatment decreases tyrosine hydroxylase in the diabetic heart.
RT-qPCR and Western blotting was performed for measuring TAT mRNA and protein levels,
respectively in the diabetic hearts treated with scrambled miRNA (DM+scm) and miR-133a
mimic (DM+miR). A, The bar graph shows TAT mRNA level and represented as fold change.
18sRNA is an endogenous control. The values are mean ±SEM, n=3. B, Top, representative
Western blot bands of TAT and actin (loading control). Bottom, densitometric analyses of the
bands of TAT and the relative expression of TAT is represented as fold change. The values are
mean ±SEM, n=3. C, left, Schematics showing the area of heart section used for staining of
TAT. LV, Left Ventricle and RV, Right Ventricle. Right, Representative diaminobenzidine
(DAB) immunohistochemical staining of TAT in the heart sections of DM+scm and DM+miR.
Page 36 of 63Diabetes
37
Sections were counterstained with Hematoxylin. Scale bar: 200 µm. D, MiR-133a mimic
treatment inhibits TAT in CATH. a neuron cells. Undifferentiated CATH.a neuron cells were
transfected with miR-133a mimic plasmid for 24 hour, and stained for TAT. Representative
immunofluorescence showing the expression of miR-133a (green, shown by an arrow) and TAT
(red, shown by an arrowhead) in the neuronal cells. DAPI (blue) stains nuclei. The miR-133a
overexpressing cells have less expression of TAT. E, CATH.a cells were treated with either
scrambled miRNA (scm), miR-133a mimic (miR), or antimiR-133a (anti-miR), and proteins
were extracted after 24 hour. Top panel, representative Western blot of TAT and tubulin (a
control) from the three groups. The bottom panel shows densitometry analyses of bands and
represented as fold change. The values are mean ±SEM. n=4.
Figure 7. Cardiac specific overexpression of miR-133a prevents diabetes-mediated
downregulation of TH and upregulation of TAT in the mouse heart. WT and miR-133aTg
(TG) mice were treated with or without STZ to induce diabetes. In the heart, protein levels of
TH and TAT was determined by Western blotting. A (i), Representative Western blot bands for
TH, TAT and actin (a loading control). A (ii), Bar graph showing densitometric analyses of band
intensity for TH in the four groups. N, WT= 6, WT+STZ=7, miRTg+STZ=5; miRTg=6. A (iii),
Bar graph showing densitometric analyses of band intensity of TAT in the four groups. N, WT=
5, WT+STZ=5, miRTg+STZ=4; miRTg=3. The values are mean ±SEM. B, Representative
diaminobenzidine (DAB) immunohistochemical staining of TH (i) and TAT (ii), and
counterstaining of hematoxylin in the heart sections of the four groups. Scale bar: 200µm.
Page 37 of 63 Diabetes
38
Figure 8. Regulatory role of miR-133a in diabetic hearts. A-D. MiR-133a targets 3/UTR of
TAT. A, The binding sequence of miR-133a with TAT 3/UTR in rat. B, The plasmid clone of
TAT 3/UTR used for luciferase reporter assay. The mutant plasmid is identical except the miR-
133a binding site is deleted. C, The luciferase reporter assay results with TAT 3/UTR and D,
mutant TAT 3/UTR. The relative luciferase activity is measured in CATH.a cells treated with
3/UTR and increasing doses of miR-133a. The values are mean ±SEM. n=6. E. MiR-133a
regulates contractility by targeting TAT in diabetic hearts. Schematic showing that reduced
level of miR-133a upregulates tyrosine aminotransferase (TAT) in diabetic hearts. Elevated TAT
inhibits tyrosine hydroxylase (TH) that decreases cardiac norepinephrine (c-NE) level. It results
into inactivation of β1-AR and β2-AR that decreases contractility in diabetic hearts. On the other
hand, treatment with miR-133a mimic increases miR-133a level in the diabetic heart that
decreases TAT by binding to its 3/UTR. Decreased TAT increases the level of TH, which
induces c-NE biosynthesis. The elevated level of c-NE induces β-AR and improves the
contractility of diabetic hearts.
Page 38 of 63Diabetes
0 2.0 1.5 1.0 0.5 0
20
40
60
80
100
Time (Sec)
Control
0 2.0 1.5 1.0 0.5 0
20
40
60
80
100
Time (Sec)
DM+scm
0 2.0 1.5 1.0 0.5 0
20
40
60
80
100
Time (Sec)
DM+miR
Le
ft V
en
tric
ula
r
Pre
ssu
re (
mm
Hg)
Le
ft V
en
tric
ula
r
Pre
ssu
re (
mm
Hg)
Le
ft V
en
tric
ula
r
Pre
ssu
re (
mm
Hg)
A (i)
Figure 1
60
80
100
120
Le
ft V
en
tric
ula
r P
ressu
re (
mm
Hg)
Sham DM+scm DM+miR
P=0.09
P=0.09
A (ii)
Page 39 of 63 Diabetes
Basal
-4000
-12000
-8000
-4000
0 4000
8000
12000
16000
1.5 1.0 0.5 0 2.0
± d
p/d
t (m
mH
g/s
ec)
± d
p/d
t (m
mH
g/s
ec)
-4000
-12000
-8000
-4000
0 4000
8000
12000
16000
1.5 1.0 0.5 0 2.0
-12000
-8000
-4000
0 4000
8000
12000
16000
1.5 1.0 0.5 0 2.0
Control
DM+scm
DM+miR
Time (Sec) Time (Sec)
Time (Sec) Time (Sec)
Time (Sec) Time (Sec)
-12000
-8000
-4000
0 4000
8000
12000
16000
1.5 1.0 0.5 0 2.0
-12000
-8000
0 4000
8000
12000
16000
1.5 1.0 0.5 0 2.0
-12000
-8000
0 4000
8000
12000
16000
1.5 1.0 0.5 0 2.0
± d
p/d
t (m
mH
g/s
ec)
Figure 1
B (i)
Isoproterenol 0.1ug/kg
Page 40 of 63Diabetes
B (ii)
Figure 1
0
4000
8000
12000
16000
20000
Basal 0.05ug/kg 0.1ug/kg
dp
/dt (m
mH
g/s
ec)
P=0.02
P=0.002
P=0.2
P=0.03
Control
DM+scm
DM+miR
Page 41 of 63 Diabetes
A
β1-A
R:1
8S
(F
old
ch
an
ge
)
0
1
2
3
4
5P=0.03
DM+scm DM+miR
B
C
0
1
2
3
4
5
β2-A
R:1
8S
(F
old
ch
an
ge
) P=0.04
D
DM+scm DM+miR
E
Figure 2
β1-AR
Actin 43 kDa
65 kDa
β1-A
R:a
ctin
(F
old
ch
an
ge
) P=0.01
DM+scm DM+miR
0
1
2
3
0
1
2
3
β2-AR
Actin 43 kDa
65 kDa
β2-A
R:a
ctin
(F
old
ch
an
ge
) P=0.002
DM+scm DM+miR
SE
RC
A-2
a:t
ubulin
(F
old
ch
an
ge
)
DM+scm DM+miR
Tubulin
Serca2a 110 kDa
55 kDa
P=0.04
0
1
2
Page 42 of 63Diabetes
A C(i)
B C(ii)
P=0.04
Sham DM+scm DM+miR 0
0.09
0.18
0.27
0.36
0.45
0.54
P=0.02
p-N
E (
ng/m
l)
0
0.09
0.18
0.27 P=0.01 P=0.02
Sham DM+scm DM+miR
c-N
E (
ng/m
g t
issue
)
Figure 3
DM+scm DM+miR
Le
ft v
en
tric
le
0
0.5
1
1.5
2
2.5
SP
G f
luo
rescence
(Fo
ld c
ha
nge
)
P=0.03
DM+scm DM+miR
C(iii)
Le
ft v
en
tric
le
Blue channel Blue+green channel Blue+red channel
Page 43 of 63 Diabetes
A B
Le
ft v
en
tric
le
TH
200µm 200µm
C C
Sym
pa
the
tic inn
erv
atio
ns
Heart
RV
LV
Transverse Section
(i) (ii)
DM+scm DM+miR Figure 4
0
3
6
9
TH
:18
S (
Fo
ld c
ha
nge
)
DM+scm DM+miR
P=0.01
0
1
2
3
4
Gapdh
TH 60 kDa
37 kDa
TH
:ga
pd
h (
Fold
ch
an
ge
)
DM+scm DM+miR
P=0.01
Page 44 of 63Diabetes
miR-133a TH miR-133a + TH + DAPI
25µm 25µm 25µm
D
E
Figure 4
Gapdh
TH 60 kDa
37kDa
scm miR anti-miR
P=0.02
P=0.02
TH
:ga
pd
h (
Fold
ch
an
ge
)
0
0.5
1
1.5
2
Page 45 of 63 Diabetes
0
0.5
1
1.5
2
TH
:ga
pd
h (F
old
ch
an
ge
)
P=0.04
Negative si-TAT 0
0.2
0.4
0.6
0.8
1
1.2
TH
:ga
pd
h (
Fold
ch
an
ge
)
P=0.005
Negative OE-TAT Figure 5
B C
TH
Gapdh
60kDa
si-T
AT
Nega
tive
OE
-TA
T
37kDa
Nega
tive
si-T
AT
Nega
tive
si-T
AT
Nega
tive
OE
-TA
T
OE
-TA
T
Nega
tive
Nega
tive
Ma
rker
A Page 46 of 63Diabetes
0
0.5
1
Actin
TAT 50 kDa
43 kDa
A B
TAT
Le
ft v
en
tric
le
200µm 200µm
C C
Sym
pa
the
tic inn
erv
atio
ns
Heart
RV
LV
Transverse Section
(i) (ii)
TA
T:1
8S
(F
old
ch
an
ge
) P=0.04
DM+scm DM+miR
0
0.5
1
TA
T:a
ctin (
Fold
ch
an
ge
)
P=0.03
DM+scm DM+miR
DM+scm DM+miR Figure 6
Page 47 of 63 Diabetes
miR-133a TAT miR-133a + TAT + DAPI
25µm 25µm 25µm
D
E
Figure 6
Tubulin
TAT 50 kDa
55 kDa
scm miR anti-miR
P=0.004
P=0.00003
TA
T:t
ubu
lin (
Fold
ch
an
ge
)
0
0.5
1
1.5
Page 48 of 63Diabetes
0
0.5
1
1.5
2
0
0.5
1
1.5
2
Figure 7
A
60 kDa TH
WT WT+STZ TG+STZ TG
TAT
43 kDa
50 kDa
Actin
TA
T: a
ctin
(F
old
ch
an
ge
) P=0.002 P=0.038 T
H: a
ctin
(F
old
ch
an
ge
)
P= 0.015
P= 0.009
WT WT miRTg miRTg
+STZ +STZ
WT WT miRTg miRTg
+STZ +STZ
Page 49 of 63 Diabetes
Figure 7
WT+Vehicle WT+STZ
miRTg+Vehicle miRTg+STZ
200µm
WT+Vehicle WT+STZ
miRTg+Vehicle miRTg+STZ
200µm
B (i)
B (ii)
TAT
TH
Page 50 of 63Diabetes
TAT 3/UTR 237: 5' auccugaggguaucaGACCAAu 3'
| | | | | |
rno-miR-133a 3' gucgaccaacuucccCUGGUUu 5' Rat TAT
A
0
0.2
0.4
0.6
0.8
1
1.2
miR
scm
P=0.001
Ga
ussia
:renill
a lucife
rase
activity
(Fo
ld c
ha
nge
)
miR-133a : 0μg 1μgg 2μg
TAT 3/-UTR : 1µg 1µg 1µg
TAT 3/UTR hLuc hRLuc SV40 CMV
miR-133a binding sites
TAT 3/UTR-pEZX clone
Figure 8
B
C
Ga
ussia
:renill
a lu
cife
rase
activity
(Fo
ld c
ha
nge
)
miR-133a : 0μg 1μgg 2μg
Mutant-TAT 3/-UTR : 1µg 1µg 1µg
0
0.2
0.4
0.6
0.8
1
1.2
D
Page 51 of 63 Diabetes
Figure 8E
Contractility Diabetic heart
β1 & β2-ARs
MiR-133a Tyrosine
TAT
Homogentisate
Pathway
MiR-133a Tyrosine
TAT
Homogentisate
Pathway
miR-133a mimic-treated
diabetic heart
TH
c-NE
TH
c-NE
Page 52 of 63Diabetes
1
SUPPLEMENTAL MATERIAL
MiR-133a regulates contractility of diabetic hearts: a novel role for cross-talk between
tyrosine aminotransferase and tyrosine hydroxylase
Shyam Sundar Nandi1, Hong Zheng
1, Neeru M. Sharma
1, Hamid R. Shahshahan
1, Kaushik P.
Patel1
and Paras K. Mishra1, 2
Affiliations:
1. Department of Cellular and Integrative Physiology, University of Nebraska Medical
Center, 985850 Nebraska Medical Center, Omaha, NE 68198, USA
2. Department of Anesthesiology, University of Nebraska Medical Center, 985850
Nebraska Medical Center, Omaha, NE 68198, USA.
Running title: MiR-133a regulates cardiac contractility
Corresponding author:
Paras Kumar Mishra
Department of Cellular and Integrative Physiology
University of Nebraska Medical Center
985850 Nebraska Medical Center
Omaha, NE-68198, USA
Phone: 402-559-8524
Fax: 402-559-4438
Email: paraskumar.mishra@unmc.edu
Page 53 of 63 Diabetes
2
SUPPLEMENTARY FIGURE LEGENDS
Supplementary Figure 1. Schematic illustration of the treatment protocol. Eight week
Sprague-Dawley male rats were treated with streptozotocin and after four weeks blood glucose
level was measured. Rats with more than 350 mg/dL glucose level were considered diabetic and
used for lentivirus treatment. Both miR-133a and scrambled plasmids were GFP tagged and were
packaged into lentivirus, and 10^6 lentivirus particles were injected into diabetic rats through tail
vein. After two weeks, physiological data were acquired and rats were sacrificed for tissue
collection.
Supplementary Figure 2. Treatment with miR-133a mimic upregulated cardiac miR-133a
in diabetic hearts. Lentivirus containing miR-133a mimic or scrambled miRNA (GFP-tagged)
were injected into diabetic rat through tail vein and the levels of cardiac miR-133a was
determined. A, Individual miR-133a assay was performed and relative expression of miR-133a
was measured by qRT-PCR in scrambled miRNA (DM+scm)-, and miR-133a mimic
(DM+miR)- treated diabetic hearts. U6 was used as an endogenous control. The values are
expressed as mean ±SEM, n=3. B, Immunohistochemistry was performed on cryosections of the
heart from DM+miR group. The expression of miR-133a (red, anti-GFP) was co-localized with
cardiomyocyte marker α-actinin (green). The merged images show the expression of miR-133a,
α-actinin and dapi (blue, nuclear stain). C, Anti-GFP-HRP antibody was used to stain the
cryosections from “B” group. The brown color in the left panel show the expression of miR-
133a. D, Genotyping for miR-133Tg mice was performed. MiR-133aTg showed a band at
670kb, which was absent in C57BL/6J (WT control) mice. E, Individual miR-133a assay was
Page 54 of 63Diabetes
3
performed to validate that cardiac levels of miR-133a was increased in miR-133aTg mice. U6
was an endogenous control.
Supplementary Figure 3. MiR-133a mimic treatment decreases cardiac hypertrophy in
diabetic hearts. A, Western blot analyses of beta-myosin heavy chain (β-MHC) protein in the
heart tissue obtained from scrambled miRNA (DM+scm)-, and miR-133a mimic (DM+miR)-
treated diabetic hearts. Top, representative bands of β-MHC and tubulin (loading control);
Bottom, bar graph showing densitometric quantification of band intensity, which is represented
as fold change. The values are mean ±SEM, n=3. B, Wheat Germ Agglutinin staining of
histological cryosections the heart from the above two groups of the diabetic rats. Green color
demarcates cell boundaries and asterisks denote typical cell sizes. Scale bars: 100µm. C,
Quantification of cell size per unit cross sectional area of left ventricle. Bar graph represents cell
size per unit area in fold change, values are mean ±SEM, n=3.
Supplementary Figure 4. Tyrosine hydroxylase and tyrosine amino transferase are present
in the neuronal terminals of the diabetic heart. Validation of presence of neuronal tyrosine
hydroxylase (TH) in diabetic hearts and in CATH.a neuronal cell line. A, Histological sections of
diabetic hearts treated with miR-133a mimic (DM+miR) were stained for neuronal marker,
microtubule associated protein-2 (MAP2, green) and TH (red). The merged image were
magnified 400X to show that TH is localized in neuronal terminals in the diabetic heart. Scale
bar: 100µm. B, Anti-HRP antibody was used for staining TH and TAT in the cryosections of the
heart. C, Validation of presence of miR-133a in neuronal cells. Individual miR-133a assay was
performed on two different neuronal cells: CATH.a (mouse origin) and SH-SY5Y (human
Page 55 of 63 Diabetes
4
origin) to validate that neuronal cells express miR-133a. U6 was an endogenous control. D,
Expression of TH in CATH.a neuronal cells. The neuronal cells were stained with anti-TH
antibody (red) and dapi (blue), and observed under a fluorescent microscope. Scale bar: 25µm.
E, Expression of TAT in CATH.a neuronal cells. The neuronal cells were stained with anti-TAT
antibody (green) and dapi (blue) and observed under a fluorescent microscope. F, Validation of
TAT siRNA in CATH.a cells. G, Validation of TAT overexpression in CATH.a cells.
Supplementary Figure 5. Tyrosine aminotransferase (TAT) is a predicted target for miR-133a.
A, The binding site for miR-133a on 3´UTR of TAT in rat. B, The binding site for miR-133a on
3´UTR of TAT in mouse. C, Conserved binding sequences and sites of miR-133a on 3´UTR of
TAT in rat and mouse (sequence highlighted by colored box in “A” and “B”) and other species.
The highlighted color represents conserved nucleotides among different species.
Page 56 of 63Diabetes
Streptozotocin (STZ)
injection
Sprague-Dawley rat
Blood glucose measurement
(>350mg/dL)
Sham Diabetic
+miR-133a
Diabetic
+scrambled
Treatments
miR-133a mimic or scrambled
injection by tail vein
(106 lentivirus/one time)
8 weeks 12th weeks 14th weeks
Diabetic
±dP/dt measurement,
sacrifice, and tissue
collection
Groups
Supplementary Figure 1A
Steptozotocin (STZ)
injection (65mg/Kg BW)
cardiac specific
miR-133a transgenic or
C57BL/6J mice
Blood glucose measurement
(>300mg/dL)
WT+Veh. miR-133aTg
Diabetic miR-133aTg+Veh.
8 weeks 10th week 14th week
Diabetic
±dP/dt measurement,
sacrifice, and tissue
collection
Groups
Treatments
0
Supplementary Figure 1B
Page 57 of 63 Diabetes
Anti-α-actinin-488 Anti-GFP-594 Merged+DAPI
DM
+m
iR
B
50µm DM+scm DM+miR
miR
-13
3a:U
6 s
nR
NA
(Fold
ch
an
ge
)
A
P=0.001
0
1
2
3
4
Supplementary Figure 2
C Anti-GFP-HRP Negative control
100kb
200kb
300kb
400kb
500kb
850kb
miR-Tg WT
670 bp
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
2
WT miR-133aTg
P=0.008
miR
-13
3a:U
6S
nR
NA
(F
old
ch
an
ge
)
3 4
D E
Page 58 of 63Diabetes
Ca
rdio
myo
cyte
siz
e/u
nit a
rea
(F
old
ch
an
ge
)
P=0.005
* * *
*
DM+scm DM+miR
Le
ft v
en
tric
le
WGA staining B A
DM+scm DM+miR
β-M
HC
: tu
bu
lin (
Fo
ld c
ha
nge
)
P=0.002
0
0.5
1
DM+scm DM+miR
C
Supplementary Figure 3
223 KDa
Tubulin
β-MHC
55 KDa
DM+scm DM+miR
0
0.4
0.8
1.2
Page 59 of 63 Diabetes
Anti-TH-594
CA
TH
.a C
ell
25µm
Supplementary Figure 4
C
CA
TH
.a C
ell
Anti-TAT-488
A
B Anti-TH Anti-TAT
DM
+m
iR
D E
0
0.05
0.1
0.15
0.2
0.25
0.3
CATH.a SH-SY5Y
miR
-13
3a:U
6S
nR
NA
(Re
lative
qu
an
tity
)
DM
+m
iR
Anti-MAP2-488+Anti-TH-594
100µm
400X
Page 60 of 63Diabetes
Actin
TAT 50 kDa
43 kDa
Si-TAT - +
0
0.2
0.4
0.6
0.8
1
1.2
Control siRNA
P=0.003
TA
T: a
ctin
(F
old
ch
an
ge
)
F G
Supplementary Figure 4
Actin
TAT 50 kDa
43 kDa
OE-TAT - +
0
0.2
0.4
0.6
0.8
1
1.2
1.4
Control OverEx
P=0.047
TA
T: a
ctin
(F
old
ch
an
ge
)
Page 61 of 63 Diabetes
TAT 3/UTR 237: 5' auccugaggguaucaGACCAAu 3'
| | | | | |
rno-miR-133a 3' gucgaccaacuucccCUGGUUu 5' Rat TAT
TAT 3/UTR 290: 5' ugagGGUACCAGUUUACCAGa 3'
| | | | | | | | | | | | | |
mmu-miR-133a* 3' uaaaCCAAGGUAAAAUGGUCg 5' Mouse TAT
A
B
TA
T 3
' UT
R
C SITE1 SITE3 SITE2
Supplementary Figure 5
Page 62 of 63Diabetes
SUPPLEMENTAL TABLE
Table 1. The forward and reverse primers sequences used for RT-PCR and qPCR.
Gene Forward sequences (5′–3′) Reverse sequences (5′–3′)
TAT TACAGACCCTGAAGTTACCC CCTTGGAATGAGGATGTTT
TH CTTGTCTCGGGCTGTAAA CACTTTTCTTGGGAACCA
β1-AR GCCGATCTGGTCATGGGA GTTGTAGCAGCGGCGCG
β2-AR ACCTCCTCCTTGCCTATCCA TAGGTTTTCGAAGAAGACCG
18s GATACCGCAGCTAGGAATAA ATCGTTTATGGTCGGAACTA
Page 63 of 63 Diabetes
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