Molecular remodeling of ion channels, exchangers and pumps in atrial and ventricular myocytes in ischemic cardiomyopathy (original) (raw)

Channels (Austin). Author manuscript; available in PMC 2011 Mar 18.

Published in final edited form as:

PMCID: PMC2891309

NIHMSID: NIHMS170352

Naomi Gronich

1 National Institute on Aging; National Institutes of health; Baltimore, MD USA;

Azad Kumar

1 National Institute on Aging; National Institutes of health; Baltimore, MD USA;

Yuwei Zhang

1 National Institute on Aging; National Institutes of health; Baltimore, MD USA;

Igor R. Efimov

2 Washington University in Saint Louis; St. Louis, MO USA

Nikolai M. Soldatov

1 National Institute on Aging; National Institutes of health; Baltimore, MD USA;

1 National Institute on Aging; National Institutes of health; Baltimore, MD USA;

2 Washington University in Saint Louis; St. Louis, MO USA

*Correspondence to: Nikolai M. Soldatov; National Institute on Aging; NIH; 251 Bayview Blvd., Suite 100; Baltimore, MD 21224, USA; vog.hin.ain.crg@Nvotadlos

†Both authors have contributed equally in this study

‡Current address: Internal Medicine and Department of Community Medicine and Epidemiology, Carmel Medical Center, 7 Michal St., Haifa 34362, Israel.

§Current address: Cell Biology and Gene Expression Unit, Laboratory of Neurogenetics, NIA, NIH, Builiding 35, Room 1A1006, 35, Convent Drive, Bethesda, MD 20892, USA.

¶Current address: Surgery Branch, NCI, NIH, Building 10, 3-5848, Bethesda, MD 20892, USA.

Abstract

Existing molecular knowledge base of cardiovascular diseases is rudimentary because of lack of specific attribution to cell type and function. The aim of this study was to investigate cell-specific molecular remodeling in human atrial and ventricular myocytes associated with ischemic cardiomyopathy. Our strategy combines two technological innovations, laser-capture microdissection of identified cardiac cells in selected anatomical regions of the heart and splice microarray of a narrow catalog of the functionally most important genes regulating ion homeostasis. We focused on expression of a principal family of genes coding for ion channels, exchangers and pumps (CE&P genes) that are involved in electrical, mechanical and signaling functions of the heart and constitute the most utilized drug targets. We found that (1) CE&P genes remodel in a cell-specific manner: ischemic cardiomyopathy affected 63 CE&P genes in ventricular myocytes and 12 essentially different genes in atrial myocytes. (2) Only few of the identified CE&P genes were previously linked to human cardiac disfunctions. (3) The ischemia-affected CE&P genes include nuclear chloride channels, adrenoceptors, cyclic nucleotide-gated channels, auxiliary subunits of Na+, K+ and Ca2+ channels, and cell-surface CE&Ps. (4) In both atrial and ventricular myocytes ischemic cardiomyopathy reduced expression of CACNG7 and induced overexpression of FXYD1, the gene crucial for Na+ and K+ homeostasis. Thus, our cell-specific molecular profiling defined new landmarks for correct molecular modeling of ischemic cardiomyopathy and development of underlying targeted therapies.

Keywords: ischemic cardiomyopathy, molecular profiling, atrial myocytes, ventricular myocytes, ion channels, phospholemman, Na+, K+-ATPase, CLIC

Introduction

Cardiovascular disease is the leading cause of human morbidity and mortality. Ischemic cardiomyopathy1 (ICM) affects approximately 1 out of 100 people in the United States, most often middle-aged to elderly men. ICM is the most common form of cardiomyopathy leading to dilation of the cardiac chambers and congestive heart failure. In spite of great efforts, molecular markers and targets of ICM are not currently well understood.2 The tissue-specific pathogenesis pathways in the human heart reportedly include approximately 20 genes3 coding for structural proteins and those associated with Ca2+ homeostasis and energy metabolism. However, some of the implicated genes may be secondary to ICM because intrinsic noise of investigative platforms precludes from detecting low-signal cell-type-specific critical targets at the whole-tissue level. Different cell types remodel in the development and disease following their unique program. Moreover, this remodeling is anatomically heterogeneous. To overcome these problems and characterize ICM-induced molecular remodeling in a cell-type and anatomical region-specific fashion, we combined two technological innovations, laser-capture microdissection of cells of interest and microarray optimized for detection of alternative RNA splicing events in a narrow catalog of genes coding for ion channels, exchangers and pumps (CE&P genes), which comprise the most acclaimed target classes for top-selling prescription drugs. Because CE&P molecules are involved in electrical, signaling and mechanical functions of the heart, their remodeling in ICM may result in decreased cardiac contractile functions.4 It is likely that pathophysiological conditions of ICM affect regulation of expression of CE&P splice variants.5 Thus, molecular profiling of disease-induced CE&P remodeling may narrow the search for crucial players and enable better understanding of underlying disease mechanisms and effective ICM prevention and treatment. We focused our research on CE&P molecular remodeling in atrial and ventricular cardiomyocytes because of their ultimate role in cardiac contraction targeted by ICM. This research strategy addressed the complexity of cardiovascular system and tissue heterogeneity complicated by differential gene expression and splice variation. Our findings associate ICM with altered expression of CACNG7 and FXYD1 in atrial and ventricular myocytes and show that these cells remodel in ICM following their unique programs involving different subsets of CE&P genes.

Results

Laser capture microdissection is an established method for isolation with confidence of histochemically identified cells from heterogeneous cell populations allowing the rational design of comprehensive splice variant profiling of CE&P remodeling in cardiomyocytes. Results of microarray analysis are presented in Table 3 and summarized in Table 4. We found that ICM caused remodeling of 12 genes in atrial myocytes. Increased expression in relation to healthy hearts was found for the FXYD1 gene coding for protein regulator of Na+,K+-ATPase phospholemman (2.3-fold) and intracellular chloride channels CLIC1 and CLIC4 (both 1.6-fold). The other nine identified genes were significantly down-regulated including FXYD7, the inward rectifier Kir2.4 channel, the acetylcholine receptor α10 subunit, the Ca2+ channel Cavγ subunits, the AMPA-selective glutamate receptor 3, the Kv4.3 K+ channel involved in initial phase of repolarization and setting the plateau voltage of the action potential, the polyunsaturated fatty acids-activated and mechano-sensitive K2P4.1 channel, the Na+ channel Navβ1 subunit. In ventricular myocytes we identified 63 genes affected by ICM. An increase (2.5-fold) was found only for FXYD1. The other 62 CE&P genes were down-regulated 1.5–3.5 fold. Some of them belong to the same functional groups that are affected by ICM in atrial myocytes (Table 4) including FXYD3, three A-type K+ channels, two inward rectifiers, three tandem-pore-domain K+ channels, three Cavγ subunits, six acetylcholine receptor subunits, and the AMPA1 glutamate receptor. In addition, we identified three delayed rectifiers, the Ca2+-activated KCa3.1 channel, seven modifiers and β-subunits of K+ channels, six voltage-gated Ca2+ channels, two ENaC and trp channels, cyclic nucleotide-gated channels HCN2 and CNGA3, three connexins, NMDA and glycine receptors, GABA receptor subunits, and three adrenoceptors.

Table 3

Top-list ANOVA gene-score annotation for CE&P genes altered by ICM in atrial and ventricular myocytes as compared to healthy subjects

Gene Genbank # Variant accession # p-Value* (ICM/H) Gfold Change* (ICM/H)
Atrial myocytes
FXYD16,7 NM_021902 H75358 0.02859 2.3
CLIC18 NM_001288 BU173816 0.04412 1.6
CLIC48 NM_013943 BG436443 0.04047 1.6
KCNJ149,10 NM_013348 na 0.01289 −1.6†
FXYD7 NM_022006 CQ722304 0.01907 −1.6
CHRNA1011 NM_020402 CR744383 0.02780 −1.6
CACNG712 NM_031896 H19702 0.01039 −1.6
GRIA313 NM_000828 DA531074 0.01945 −1.7
KCND314 NM_004980 NM_172198 0.00837 −1.7
KCNK49,15 NM_016611 BE900958 0.01063 −1.8
SCN1B1618 NM_001037 DA062026 0.03059 −1.8
CACNG2 NM_006078 na 0.02046 −4.7
Ventricular myocytes
FXYD16,7 NM_021902 H75358 0.00511 2.5
KCNN4 NM_002250 AL552182 0.00551 −1.5
CLCN2 NM_004366 BM789394 0.00391 −1.5
CACNG7 NM_031896 H19702 0.00069 −1.5
CACNG8 NM_031895 CQ718803 0.00092 −1.5
CACNA1A NM_000068 BF529475 0.01245 −1.5
KCNH6 NM_173092 CQ730511 0.00758 −1.5
CACNG5 NM_145811 AX101266 0.03112 −1.5
GRIN2A NM_000833 BG718790 0.01562 −1.5
SCNN1D NM_002978 AK093372 0.00046 −1.6†
GABRA3 NM_000808 DA801686 0.00407 −1.6
CACNA1E19,20 NM_000721 L27745 0.00148 −1.6
KCNH19,21,22 NM_172362 DB021985 0.00092 −1.6
KCNV29,23 NM_133497 CQ724488 0.00935 −1.6
CHRNA6 NM_004198 DA415543 0.00817 −1.6
KCNK69,24 NM_004823 AW883970 0.02392 −1.6
CFTR25 NM_000492 BG386556 0.00212 −1.6
GLRA3 NM_006529 BG186165 0.00657 −1.6
TRPC426,27 NM_016179 AF421361 0.02904 −1.6
FXYD3 NM_021910 DR006067 0.01264 −1.6†
GRIN2D NM_000836 AB209292 0.00249 −1.6†,‡
CACNA1D9,28,29 NM_000720 CQ731466 0.00347 −1.7
HCN29,30 NM_001194 BX281160 0.00039 −1.7
KCNS19 NM_002251 DA231979 0.02663 −1.7
KCNK1831 NM_181840 AX319992 0.00469 −1.7
VMD232 NM_004183 AA205892 0.03238 −1.7
TRPM133 NM_002420 na 0.02334 −1.7
CHRND34 NM_000751 BF306695 0.01945 −1.7†
CLIC335 NM_004669 BE902424 0.01425 −1.7†
CACNA1H36,37 NM_021098 DB100395 0.00183 −1.7
CACNA1G29 NM_198396 BM451648 0.00045 −1.7
KCND23840 NM_012281 DA125095 0.01268 −1.7
CNGA3 NM_001298 AK131300 0.02203 −1.7
GABRG2 NM_198904 BI819259 0.02867 −1.8
KCNA49,28,3941 NM_002233 CQ741592 0.02019 −1.8
ADRA1B42 NM_000679 na 0.02796 −1.8†
CHRNA4 NM_000744 BC096291¶ 0.00353 −1.8
CACNA1I NM_021096 AX068892 0.00270 −1.8
GRIA1 NM_000827 DA749477 0.01665 −1.8
KCNJ19,43 NM_153767 NM_000220 0.00360 −1.8
KCNC39,28 NM_004977 BM474777 0.00913 −1.8
KCNQ49,44 NM_004700 AK074957 0.02336 −1.9
KCNMB245 NM_181361 BG185231 0.01402 −1.9
GABRG1 NM_173536 CQ714573 0.02843 −1.9
KCNG146 NM_172318 DA497732 0.02389 −1.9
KCNE114,47,48 NM_000219 AY789480 0.01744 −1.9
GLRA1 NM_000171 BP208426 0.01999 −2.0
CHRNA1 NM_000079 CD013888 0.02807 −2.0†
NOX149 NM_013954 NM_013955 0.00356 −2.0
GRID2 NM_001510 DB052812 0.00299 −2.0
CHRNA9 NM_017581 BF513332¶ 0.00625 −2.0
ADRA2C5053 NM_000683 T39448 0.00030 −2.1†
GJB1 NM_000166 BF571436 0.01233 −2.1
GABRR1 NM_002042 CB959800 0.01415 −2.1
SCNN1G9 NM_001039 CQ721445 0.00501 −2.2
CNGB3 NM_019098 BX104558 0.00254 −2.5
CHRNB3 NM_000749 DA127065 0.00064 −2.5
GJC154 NM_152219 na 0.00582 −2.5
ADRB152,55,56 NM_000684 na 0.00674 −2.5
KCNG4 NM_172347 CQ728641 0.01073 −2.8
KCTD11 NM_00100291 na 0.00300 −3.1†
KCNA29,16,28,57 NM_004974 BI907383 0.00795 −3.1
GJB6 NM_006783 AY789474 0.00040 −3.5

Table 4

CE&P genes altered by ICM in atrial and ventricular myocytes

CE&P class protein Atrial myocytes Ventricular myocytes
Cl− channel CLIC18, CLIC48 CLIC335, CLCN2*, CFTR25,58,59, VMD232
Transient outward (Ito) K+ channel, A-type Kv4.3 (KCND3)*14 Kv1.4 (KCNA4)*9,28,3941, Kv3.3 (KCNC3)9,28, Kv4.2 (KCND2)*3840
Delayed rectifier K+ channel Kv1.2 (KCNA2)*9,16,28,57, Kv7.4 (KCNQ4)*9,44, Kv10.1 (KCNH1)*9,21,22
K+ channel modifiers and β subunits Kv6.1 (KCNG1)46, Kv6.3 (KCNG4), Kv8.2 (KCNV2)*9,23, Kv9.1 (KCNS1)9, minK (KCNE1)*14,47,48,6062, tetramerization domain containing 11 (KCTD11)
Inward rectifier K+ channel Kir2.4 (KCNJ14)*9,10 Kir1.1 (KCNJ1)*9,43, Kv11.2 or HERG2 (KCNH6)
Tandem pore domain K+ channel K2P4.1 (KCNK4)9,15 K2P6.1 (KCNK6)*9,24, K2P18.1 (KCNK18)31
Ca2+-activated K+ channel KCa3.1 (KCNN4)*, β2 subunit of maxiK (KCNMB2)45
Voltage-gated Ca2+ channel α1 subunit63,64 Cav1.3α1D (CACNA1D)*9,28,29, Cav2.1α1A (CACNA1A)*, Cav2.3α1E (CACNA1E)*19,20, Cav3.1α1G (CACNA1G)*65,66, Cav3.1α1H (CACNA1H)*36,37,67, Cav3.1α1I (CACNA1I),
Ca2+ channel γ subunit Cavγ2 (CACNG2), Cavγ7 (CACNG7)12 Cavγ5 (CACNG5), Cavγ7 (CACNG7)12, Cavγ8 (CACNG8)
Na+ channel subunits Navβ1 (SCN1B)*17,18 ENaC-γ (SCNN1G)*9, ENaC-δ (SCNN1D)
TRP channel TRPC426,27,68, melastatin-1 (TRPM1)33
Cyclic nucleotide-gated channel69 HCN2*9,30, CNGA3
Connexin Cx32 (GJB1), Cx30 (GJB6), Cx31.9 (GJC1)54,70,71
Acetylcholine receptor72 α10 (CHRNA10)11 α1 (CHRNA1), α4 (CHRNA4), α6 (CHRNA6), α9 (CHRNA9), β3 (CHRNB3), δ(CHRND)34
Glycine receptor α1 (GLRA1), α3 (GLRA3)
GABA receptor α3 (GABRA3)*, γ1 (GABRG1), γ2 (GABRG2), rho (GABRR1)
NMDA receptor receptor73,74 2A (GRIN2A), 2D (GRIN2D)
Glutamate receptor receptor73,74 AMPA3 (GRIA3)*13 AMPA1 (GRIA1), d2 (GRID2)
Adrenergic receptor75 α1B (ADRA1B)42,7678, α2C (ADRA2C)50,52,53, β1 (ADRB1)*52,56
H+ channel NADPH oxidase (NOX1)49
Na+,K+-ATPase regulator FXYD1*7, FXYD7 FXYD1*7, FXYD3

To find out whether the splice microarray results reported in Table 3 are disease-type specific, we supplemented the same splice microarray of ICM ventricular myocytes with one additional sample prepared from left ventricle of a 41-years old dilated cardiomyopathy male donor. The top-list ANOVA gene score annotation for combined altered CE&P genes in ventricular myocytes (Table 3) was reduced from 63 to just 4 genes (FXYD1 (Gfold = +2.4), HCN2 (−1.5), GLRA1 (−1.8) and GJC1 (−2.3)). This result suggests that dilated and ischemic cardiomyopathy may affect different CE&P subsets and only four indicated genes may be common among the ones affected by these diseases, overexpression of FXYD1 being the most obvious characteristic feature.

Discussion

Our study is based on the precept that to characterize the ICM-induced molecular remodeling it is essential to investigate it at the level of cells and molecules responsible for altered cardiac function. To achieve this goal, we developed the investigative approach combining laser capture microdissection of identified cardiac cells from tissue biopsies with splice microarray of custom-narrowed sets of CE&P genes that play ultimate role in cardiac contraction targeted by ICM. Our approach for the first time enabled direct comparison of altered gene expression caused by ICM in atrial and ventricular myocytes and identified new essential players.

First of all, we found that atrial and ventricular myocytes remodel following their unique programs where ICM affects different CE&P genes. Although some of these genes were already reported to be expressed in the heart4,79 (see also references in Tables 3 and ​4), only few of them were previously linked to known cardiac pathologies.21,39,64,8084 These include (1) α1B, α2C and β1-adrenoceptors whose down-regulation in cardiomyopathy was linked to pathological remodeling in failing ventricular myocardium.42,51,85 (2). KCND2. In diabetic ventricle, a switch from Kv4.2 to Kv1.4 may underlie the slower kinetics of the Ito K+ current.40 (3). KCND3. Down- regulation of cardiac Kv4.3 and minK channels may be associated with arrhythmia and atrial fibrillation.14,61,62,86 It was reported that congestive heart failure and hypertrophy decrease Kv4.3 expression in terminally failing human hearts.87 In line with this finding, KCND3 gene transfer abrogates the hypertrophic response to aortic stenosis.88 (4) HCN2. Transfer of this gene was also tested as gene therapy for cardiac arrhythmias in experimental animals with positive results.89 However, the existing knowledge base remains rudimentary in the absence of attribution to certain cardiac cell types and functions.

We found that ICM does not alter expression of Cav1.2 and Nav5 channel isoforms and Na+,K+-ATPase but rather affects some of their accessory subunits. The most profound change in both atrial and ventricular myocytes was overexpression of phospholemman. Binding of phospholemman to Na+,K+-ATPase induces a decrease in the affinity of α1–β1 and α2–β1 isozymes to external K+ and approximately 2-fold decrease in the affinity to internal Na+.90 Inhibition of Na+/Ca2+ exchanger by phospholemman91 may add to the disbalance of Na+, K+ and Ca2+ gradients across the plasma membrane and contribute to hypertrophy of ICM muscle cells due to overexpression of FXYD1. Another unexpected finding that may have profound functional consequences is underexpression of Navβ1. Although the functional role of this single- membrane-spanning-repeat protein in the heart remains uncertain, it co-localizes with the Nav1.5 pore-forming α1 subunit in the T-tubule system and intercalating discs levels in cardiomyocytes17 and modulates Nav1.5 channels in the heart by increasing the Na+ current density.92 Confirming its crucial role in the heart, SCN1B knock-out caused prolongation of QT and RR intervals93 and development of cardiomyopathy.94 Post-transcriptional gene silencing of Navβ1 reduced mRNA and protein levels of Nav1.5, KChIP2 mRNA and Kv4.3 resulting in markedly decreased Na+ and Ito currents.95 Thus, underexpression of Navβ1 may lead to a suppression of Ito, action potential prolongation and increased susceptibility of the heart to ventricular arrhythmia.

Other new potential targets for drug discovery are _CLIC_s.8,35 Members of the p64 family, CLIC proteins localize to the cell nucleus and exhibit both nuclear and plasma-membrane chloride channel activity, but their functions are not well defined. CLIC2, which shares sequence similarity with CLIC1, modulates cardiac ryanodine receptors and inhibits Ca2+ release from the sarcoplasmic reticulum.96 Thus, ICM-induced remodeling of _CLIC_s in cardiomyocytes may affect membrane potential, intracellular pH and cell volume.

The four identified Cavγ calcium channel subunits downregulated in ICM show a broad spectrum of modulating activities that may have a role in cardiac myocytes. The γ7, which is homologous to γ5, regulates stability of certain mRNAs97 and, along with γ2 and γ8, controls trafficking and gating of AMPA receptors.98,99 It remains to be studied whether remodeling of AMPA receptors in ICM is associated with Cavγs. Acetylcholine,72 AMPA and NMDA receptors73, also downregulated in ICM, are present in cardiac neuromuscular junctions and intercalating disk, but little is known about their non-neuronal expression and roles in the heart.

Our study is the first step in molecular characterization of ICM with organ- and cell-specific annotation of altered expression of CE&P genes. Our study does not determine whether upregulation or downregulation of the identified CE&P genes are the primary drivers of ICM or reflect pathophysiological response to the disease. However, it provides an objective context within which it would be easier to find therapeutic targets among the elucidated markers of ICM. Future extension of this study may clarify links between CE&P genes expression and drug therapy, duration of disease, age, gender and race as potential factors in ICM and define key aspects of the principal gene network in relation to the development of ICM at the cellular and specific intercellular levels. In conjunction with protein and immunohistochemical analyses this may yield a more robust approach to better understanding mechanisms and pathophysiology of ICM - a critical need in the clinical utilization of this field.

Methods

Human cardiac tissue samples

Healthy (Table 1) and ICM hearts (Table 2) of anonymous donors were obtained from the Cardiac Transplantation Center at the Washington University in St. Louis, MO. Healthy hearts were excluded from transplantation after exceeding 6 h-limit of allograft ischemic time. Showing no evidence of hemorrhagic stroke, they retained normal structure and function evidenced by bimodal biophotonic imaging and optical mapping of the atrioventricular junction.100 There was no delay in collecting donor’s heart tissue. Decision on suitability for transplantation was made prior to harvest of organs, our team members were notified in advance (at least 2 h before cross clamping) and were present during organ harvest. Heart was cardioplegically arrested, harvested and transferred to us immediately after removal from the chest. Tissue samples (0.5–2 g) were dissected from the area outside of scar burden (if any) of left ventricle and left atrial appendages under cold cardiopledic arrest conditions within approximately 30–40 min after removal of the heart from donor’s chest. Tissue was washed in 4°C saline, immersed in Tissue-Tek OCT Compound (Electron Microscopy Sciences, Hatfield, PA), flash frozen in liquid nitrogen and stored at −80°C until use. Although availability of donors suitable for this study was limited, the number of selected human hearts (Tables 1 and ​2) is in full compliance with the NCBI-recommended MIAME guidelines to microarray101 and enabled us to analyze all individual donor’s samples, grouped by cell type, simultaneously on one microarray slide, thus excluding possible slide-to-slide variations.

Table 1

Characteristics of the healthy heart donors

Patient # Age Sex Cause of death Cardiac tissue studied
H1 58 F Intracerebral hemorrhage LV
H2 70 M Intracerebral hemorrhage LV, LAA
H3 40 M Brain tumor LV
H4 72 F Intracerebral hemorrhage LAA
H5 58 M Intracerebral hemorrhage LAA

Table 2

Characteristics of the ICM heart patients

Patient # Age Sex Complications prior and treatment PR (ms) HR (bpm) QRS (ms) EF (%)
D1 54 M CABG, VT, ICD 184 100 202 ND
D2 46 M VF, ICD 216 91 106 19
D3 50 M ICD 128 128 144 25

Laser-capture microdissection and isolation of mRNA

Serial cryostat sections (7–8 μm thick) were cut from the frozen tissue samples using Minotome Plus microtome cryostat. Before laser-capture microdissection, cardiomyocytes in the sections were quickly (10 s) stained with Eosin Y (Sigma-Aldrich, St. Louis, MO) according to standard procedure. Given the notably large size of cardiac muscle cells relative to other cells in the tissue, this method of identification is sufficient to distinguish stained cardiomyocytes from other cells under microscope. Laser-capture microdissection was performed with PixCell II system (Arcturus, Mountain View, CA) using a 7.5-μm laser spot as described earlier.5 The excised cardiomyocytes were picked up from the slide surface and captured on LCM Caps. To confirm the quality of cell isolation, the sectional images taken before and after microdissection were thoroughly inspected to exclude contamination with non-muscle cells, and only then the captured samples from serial sections were joined together. High-quality cellular RNA was recovered from the collected cells using PicoPure™ RNA isolation kit (Arcturus) and treated with RNase-free DNase (Qiagen, Valencia, CA). Quality of RNA was tested right before the labeling for microarray by measuring the OD and 28S/18S RNA ratios. On average, the OD ratio at 260/280 nm and 260/230 nm was > 1.8 and the ratio of 28S/18S in the RNA samples selected for experiments was ≥ 1.6. Individual samples of total RNA were optionally amplified without 3′-bias using the TransPlex™ Whole Transcriptome Amplification kit (Rubicon Genomics, Ann Arbor, MI). (The non-bias 3′-amplification was confirmed by the automated RT-PCR with capillary electrophoretic quantification of amplicons executed on a commercial human cardiac total RNA samples (Sigma) with primers to CACNA1C and CACNB2, calcium channel genes characterized by complex alternative splicing). The amplified products were purified using QIAquick PCR purification kit (Qiagen).

cDNA labeling and microarray

The PCR products were fragmented with DNase I, denatured and end-labeled with Cy-3 fluorescent dye. The individual donor’s samples, grouped according to cell type, were analyzed simultaneously on Human Ion Channel Splice Arrays 8-pack 4×44K slides (ExonHit Therapeutics, Gaithersburg, MD) manufactured on the Ion Channel Splice Array sv1.1 platform representing 287 human CE&P, including 248 alternatively spliced ones in total 1655 splicing events and supplemented with additional capabilities to recognize connexins and ryanodine receptors.

Microarray data analysis

The statistically significant differential expression patterns between ICM and healthy atrial and ventricular cell samples was analyzed using long- to short-form ratio statistics and expression level statistics to identify genes and splice events affected by ICM. All analyses were performed at ExonHit using Partek Genomics Suite. Principal Component Analysis was carried out to illustrate the level of spread between samples and experimental groups. A two-way ANOVA model was used to perform statistical tests on the probe set level intensities, to compare ICM vs. healthy cells. A Source of Variation plot was generated from this data to find the relative level of difference contributed by each factor. A cutoff level was determined to generate “top hit lists” of probe sets that indicate the most statistically significant differences between the sample groupings. The raw and transformed data sets are submitted to Gene Expression Omnibus, accession # GSE17294 and GSE17530. The method accounted for specific splice variants shown in the results, but did not evaluate the ICM-induced changes in alternative splicing. Low variability between the individual RNA samples in meaningful (p < 0.01) probesets, estimated as average of individual probesets standard deviations normalized to the respective mean values (0.08 ± 0.04, mean ± st.dev), suggests that differences in donor’s age and gender in our study have not notably affected the results of microarray. Additional details are presented in Supplementary Methods.

Supplementary Material

Acknowledgments

The authors thank Kevin Becker and William H. Wood (Gene Expression and Genomics Unit, NIA) for development of splice microarray slides, Heather Jordan and Weiyin Zhou (ExonHit Therapeutics) for help with splice microarray analysis, and Cardiac Transplantation Unit of the Washington University in St. Louis, MO for help with cardiac tissues. This work was supported in part by the Intramural Research Program of the National Institutes of Health, National Institute on Aging (Z01 AG000294-08 to N.M.S.) and by the National Heart, Lung and Blood Institute grant (RO1 HL085369 to I.R.E.).

Abbreviations

ICM

ischemic cardiomyopathy

CE&P

channels, exchangers and pumps

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