Quantitative Proteomic Analysis To Identify Differentially Expressed

Subscriber access provided by University of Birmingham

Article

Quantitative proteomic analysis to identify differentially expressed proteins in the myocardium of epilepsy using iTRAQ coupled with nano-LC-MS/MS Peng Zhang, Li Zhang, Yongguo Li, Shisheng Zhu, Minzhu Zhao, Shijia Ding, and Jianbo Li J. Proteome Res., Just Accepted Manuscript • DOI: 10.1021/acs.jproteome.7b00579 • Publication Date (Web): 01 Nov 2017 Downloaded from http://pubs.acs.org on November 2, 2017

Just Accepted “Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides “Just Accepted” as a free service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are accessible to all readers and citable by the Digital Object Identifier (DOI®). “Just Accepted” is an optional service offered to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these “Just Accepted” manuscripts.

Journal of Proteome Research is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Published by American Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to original U.S. Government works, or works produced by employees of any Commonwealth realm Crown government in the course of their duties.

Page 1 of 43

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Journal of Proteome Research

Quantitative proteomic analysis to identify differentially expressed proteins in the myocardium of epilepsy using iTRAQ coupled with nano-LC-MS/MS Peng Zhanga,#, Li Zhanga,#, Yongguo Lia,b, Shisheng Zhuc, Minzhu Zhaoa,b, Shijia Dingb,d and Jianbo Lia,b* a

Department of Forensic Medicine, Faculty of Basic Medical Sciences, Chongqing Medical

University, Chongqing 400016, China b

Chongqing Engineering Research Center for Criminal Investigation Technology, Chongqing

400016, China c

Faculty of Medical Technology, Chongqing Medical and Pharmaceutical College, Chongqing

401331, China d

Key Laboratory of Clinical Laboratory Diagnostics (Ministry of Education), College of

Laboratory Medicine, Chongqing Medical University, Chongqing 400016, China #

*

These authors contributed equally to this work. Corresponding author: JB. Li, Postal Address: Yixueyuan Road 1#, Yuzhongqu, Chongqing

400016, China. Tel/Fax: +86-23-68485994. E-mail address: [email protected]

ACS Paragon Plus Environment


1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Abstract Epilepsy is a difficult-to-manage neurological disease that can result in organ damage, such as cardiac injury, that contributes to sudden unexpected death in epilepsy (SUDEP). Although recurrent seizure-induced cardiac dysregulation has been reported, the underlying molecular mechanisms are unclear. We established an epileptic model with Sprague–Dawley rats, applying isobaric tags for a relative and absolute quantification (iTRAQ)-based proteomics approach to identify differentially expressed proteins in myocardial tissue. A total of 7 proteins in the acute epilepsy group and 60 proteins in the chronic epilepsy group were identified as differentially expressed. Bioinformatics analysis suggested that the pathogenesis of cardiac injury in acute and chronic epilepsy may be due to different molecular mechanisms. Three proteins, a receptor for activated protein kinase C1 (RACK1), aldehyde dehydrogenase 6 family member A1 (ALDH6A1), and glycerol uptake/transporter 1 (Hhatl), were identified as playing crucial roles in cardiac injury during epilepsy, and were successfully confirmed by Western blot and immunohistochemistry analysis. Our study not only provides a deeper understanding of the pathophysiological mechanisms of myocardial damage in epilepsy, but also suggests some potential novel therapeutic targets for preventing cardiac injury and reducing the incidence of sudden death due to heart failure.

Key words epilepsy, cardiac injury, proteomics, rats, sudden death.


Page 2 of 43

Page 3 of 43

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Introduction Epilepsy is a difficult-to-treat neurological disorder caused by sudden and anomalous discharges of neurons and is characterized by recurrent and transient malfunction of the central nervous system.1 According to a recent epidemiological study, more than 70 million people worldwide have epilepsy and up to 90% of them live in developing countries, including China.2 Although most epileptic patients live normal lives in the interictal period, research shows that repeated seizures disrupt normal cardiopulmonary function and the autonomic nervous system, potentially reducing life expectancy.3,4 Cardiac dysregulation in epilepsy has gained extensive attention recently, largely due to greater awareness of sudden unexpected death in epilepsy (SUDEP).4,5 SUDEP accounts for 7.5–17% of all deaths among epileptic patients,4,5 and this is not due to trauma, drowning, status epilepticus, poisoning, or anatomical causes identified postmortem. However, there is evidence that it may be epilepsy-related.6 Seizure-induced cardiac injury is deemed to be one of the most important mechanisms in the sudden death process of patients.7 Despite much research, the precise pathophysiological mechanisms underlying SUDEP have not been elucidated, and it is still difficult for clinicians to conduct appropriate therapeutic interventions to prevent the physiological changes that complicate seizures and lead to SUDEP.8 These difficulties are due to the complexities of the mechanisms of SUDEP, the lack of an ideal animal model, and the patients’ rapid deterioration to death without



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 4 of 43

providing clinicians sufficient time to acquire complete information. Another important factor in these difficulties is that the detailed mechanisms of cardiac injury in epileptic patients is still unclear; this knowledge could provide clinicians with not only a better understanding of the mechanisms of SUDEP but also a reference for evaluating the risk of sudden death and conducting accurate interventions. Recurrent

seizure-induced

cardiac

dysregulation,

such

as

arrhythmia,

bradycardia, and asystole, has been observed in both animal experiments and clinical studies.5 Read’s group used Sprague–Dawley rats implanted with EEG/EKG electrodes and showed that prolonged seizure activity led to deterioration in cardiac structure and function.9 Al-Najafi’s group reported that unrecognized myocardial stunning with or without malignant arrhythmias could be a risk factor for SUDEP.10 However, other possible distinguishing characteristics, such as differentially expressed proteins in the myocardium of epileptic patients, have not been studied. Identifying significant changes in myocardial protein expressions and gaining a deeper understanding of the molecular mechanisms driving cardiac injury after recurrent seizures may facilitate improvement in clinical management and SUDEP prevention. Modern proteomic technology with automation, high throughput, and high accuracy for identifying and quantifying expressed proteins has been applied to study chronic bladder ischemia, kidney fibrosis, cardiac hypertrophy, striated muscle actin dynamics and differentiation, and neurodegenerative disease.11-17 In this study, we used a 4-plex isobaric tag for relative and absolute quantitation (iTRAQ) coupled with


Page 5 of 43

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


nano-liquid chromatography-tandem mass spectrometry (nano-LC-MS/MS) to confirm differentially expressed proteins in myocardial tissue of an epileptic rat model. Previous research showed that the 4-plex iTRAQ is well suited for large-scale quantitative proteomic experiments.18 Bioinformatics analysis of iTRAQ-based proteomics results was applied to find proteins involved in the pathophysiological mechanisms of cardiac injury in epilepsy. Validation of 3 selected altered proteins was performed by Western blotting and immunohistochemistry (IHC) analyses. These findings will offer us a better understanding of myocardial damage mechanisms at the molecular level after recurrent seizures and may provide clinicians with an important reference in the early evaluation and treatment, to assist in reducing the incidence of sudden death in patients with epilepsy.

Materials and methods 2.1 Animals and Ethics statement All animal procedures for this study were performed in accordance to the Guide for the Care and Use of Laboratory Animals and approved by the Animal Care and Use Committee of Chong Qing Medical University. Adult male Sprague-Dawley rats (N=40; 7 weeks-of-age, 200-250 g at the beginning of the experiment) were obtained from the C.Q. Medical University Laboratory Animal Center (Chongqing, China). Animals were housed under a 12-h light/dark cycle at 21-24 °C and relative humidity 40-70%. Food and water were available ad libitum. 2.2 Establishment of the Epileptic Rat Model 2.2.1 Experimental model



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Animals were randomized into 4 groups (N=10 rats/group): (1) chronic epilepsy controls, (2) chronic epilepsy, (3) acute epilepsy controls, and (4) acute epilepsy groups. The acute epilepsy model was induced with pentylenetetrazole (PTZ, 70 mg/kg, ip) dissolved in 1 ml normal saline once every second day 3 times (Days 1 to 5).19 The chronic epilepsy model was induced with PTZ (35 mg/kg, ip) once every second day 11 times (Days 1 to 21).20 Animals were observed for 1 h by 2 independent investigators after PTZ treatment. Seizure latency and severity scores were recorded and animals with more than 3 consecutive stage 4 or greater seizures were considered to be fully kindled. Animals in acute and chronic epilepsy control groups were treated with equal volumes of saline. Racine’s scale was used to evaluate seizure intensity : stage 0 = no response; stage 1 = mouth and facial clonus; stage 2 = head nodding and wet-dog shaking; stage 3 = forelimb clonus and rearing; stage 4 = turning over onto one side accompanied by bilateral seizure; and stage 5 = generalized tonic-clonic seizures.21 All animals in the acute epilepsy group had 3 consecutive stage 5 seizures, and animals in the chronic group had stage 4 or less severe seizures after the first 7 PTZ treatments. Animals in the chronic group had 4 consecutive stage 5 seizures during subsequent experiments. All animals (8 weeks-of-age, 250-300 g in acute epilepsy and acute epilepsy control groups; 10 weeks-of-age, 350-380 g in chronic epilepsy and chronic epilepsy control group) were sacrificed 1 day after the last injection. 2.2.2 EEG Experiments


Page 6 of 43

Page 7 of 43

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


In this study, EEG (electroencephalography) were measured and analyzed in rats using a RM6240C multi-channel physiological signal acquisition and processing system (Chengdu Instrument Factory, China) as described by Kong’s group.22 EEG activity was recorded for 30 min after PTZ or saline treatment to assess epileptic activity or epileptiform discharges. 2.2.3 Sample Collection Rats were anesthetized with chloral hydrate (10%, 0.35 ml/100 g, ip). After achieving anesthesia, thoracic cavities were opened, and whole hearts were quickly harvested after perfusion and washing with ice-cold normal saline to remove protein.23 Then atria and right ventricles were rapidly removed and the left ventricle was isolated and snap-frozen in liquid nitrogen temporarily. Three left ventricle samples from each group were stored at -80 °C until protein extraction. The remaining left ventricle samples were fixed in 10% phosphate buffered formalin, embedded in paraffin, and histopathologically studied for assessment of myocardial apoptosis and iTRAQ-identified altered protein validation. 2.3 Histopathological Examination One randomly selected left ventricle sample from each group was stained with hematoxylin and eosin (H&E) to observe histopathological changes in myocardial tissue. 2.4 Assessment of Apoptosis TUNEL staining was used on the remaining 24 formalin-fixed left ventricle samples (Roche Biochemicals, Indianapolis, IN) and analyzed under double-blind



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

conditions. Ten different high power fields (200×) of each tissue section were randomly selected to evaluate cardiomyocyte apoptosis.24 IHC for caspase-3 staining was performed in the myocardial sections using a rabbit anti-caspase-3 monoclonal antibody (1:100 dilution; Abcam Inc.) and evaluated by 2 independent investigators. For quantification of staining, total labeled cells were counted in 5 different high power fields (200×) from each section.25 2.5 iTRAQ Sample Preparation Three frozen left ventricular tissues from each group were homogenized and sonicated on ice, and 100 mg of homogenized tissue from each group was used for proteomic screening. Total protein for 4 samples was extracted using lysis buffer (8 M urea, 4% CHAPS, 0.001% bromophenol blue, 65 mM DTT, and 0.2% Bio-Lyte). Then samples were ultrasonicated and centrifuged at 16,000 rpm for 30 min at 4 °C to precipitate membranes and cellular debris. Protein was measured using the Bradford method. From each sample, 100 µg protein was digested with trypsin solution (1:50 w/w) for 24 h at 37 °C and labeled using an iTRAQ reagent 4-plex protein quantitation kit (AB SCIEX) as follows: chronic epilepsy control and chronic epilepsy samples were labeled with iTRAQ 114 and 115, respectively; acute epilepsy control and acute epilepsy samples were labeled with iTRAQ 116 and 117, respectively. The 4 iTRAQ-labeled samples were multiplexed and dried in a vacuum concentrator. 2.6 High pH Reverse Phase Separation and Nano-LC-MS/MS Analysis The iTRAQ-labeled peptide mixtures were redissolved with 150 µl buffer A (20 mM ammonium formate, pH = 10) and then fractionated using a Eksigent UPLC


Page 8 of 43

Page 9 of 43

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


system (Shimadzu Corporation, Kyoto, Japan), connected to a reverse phase column (Gemini-NX C18, 5 µm 110 Å, 4.6 mm x 250 mm, Shimadzu Corporation, Kyoto, Japan). High pH separation was then eluted in a linear gradient 5-38% of buffer B (20 mM ammonium formate and 80% acetonitrile, pH = 10) in 50 min at a flow rate of 800 µl/min. A total of 50 fractions were collected, each of which had the same time interval, and then pooled into 10 fractions by combining fractions 1, 11, 21, 31, 41; 2, 12, 22, 32, 42; and so on.26 The 10 fractions were vacuum-dried for later use. Each fraction was fractionated with an Eksigent NanoLC Ultra binary pump system (Shimadzu Corporation, Kyoto, Japan), which connected to a Triple-TOF 5600 mass spectrometer (AB SCIEX, Massachusetts, USA) coupled with a Turbo V ion source. The fractions were redissolved in 30 µl solution C (0.1 % formic acid and 2 % acetonitrile) and centrifuged at 12 000 rpm for 10 min at 4 °C; then, 8 µl supernatant was extracted. Peptides were loaded on a nano column (75 µm ID and 150 mm, Eksigent) and a nano trap column (200 µm ID and 0.5 mm, Eksigent), followed by a mobile phase elution with buffer D (2% acetonitrile and 0.1% formic acid) and buffer E (98% acetonitrile and 0.1% formic acid). Then the peptides were eluted with linear gradient of 12% to 43% of buffer E over 90 min and from 50% to 80% of buffer E over 15 min at a flow rate of 300 nl/min. MS and MS/MS analysis were performed on the liquid chromatography eluent with the Triple-TOF 5600 system (AB SCIEX, Massachusetts, USA). Mass spectrometry parameters were set as follows: ion spray voltage of the inlet: 2.3 kV; mass spectra range: 100-1500 m/z; accumulation time per spectrum: 100 ms; and dynamic exclusion time: 25 s.



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

2.7 Proteomic Data Analysis and Bioinformatics The iTRAQ-based proteomics data were acquired using the Analyst QS 1.1 software (Applied Biosystems). Protein identification and quantification were performed with the ABI ProteinPilot 4.0 software (AB SCIEX), which uses the Paragon database search algorithm and an integrated false discovery rate (FDR) analysis function for peptide identification.27,28 User-defined parameters were selected as follows: sample type, iTRAQ 4-plex; ID focus, biological modifications; database, RAT.4.5.0.0,1654; and FDR analysis, yes. All reported data were based on 95% confidence interval for protein and peptide identification as determined by Protein Pilot (Prot Score ≥ 1.3). Meanwhile, a cutoff of 1% FDR and 40% isolation interference for peptide spectrum matches (PSMs) was required for all reported proteins. Normalization was performed before screening differentially expressed proteins. To identify differentially expressed proteins, relative protein expression was compared between groups (acute epilepsy control group vs. acute epilepsy group, chronic epilepsy control group vs. chronic epilepsy group). Functional classifications of the iTRAQ-identified proteins were determined with Gene Ontology (GO) annotation using the online DAVID software Bioinformatics Resources 6.7 (http://david.abcc.ncifcrf.gov). 2.8 Verification of Differentially Expressed Proteins Using Western Blotting Western blot of 4 samples was performed to verify iTRAQ-based quantitative proteomic results. Briefly, 30 µg proteins from each group was resolved with 8% SDS-PAGE at 25 mA/gel for 2 h. Then, proteins were transferred to a nitrocellulose


Page 10 of 43

Page 11 of 43

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


membrane by semi-dry blotting (Bio-Rad) at 90 V for 45 min. Then the membranes were blocked in 5% non-fat milk for 1 h. Next, the membranes were incubated overnight at 4 °C with primary polyclonal antibodies, including antibodies against receptor for activated protein kinase C1 (RACK1), aldehyde dehydrogenase 6 family, member A1 (ALDH6A1), glycerol uptake/transporter 1 (Hhatl) and β-actin (both at 1:1000 dilution; Abcam Inc., Cambridge, UK) and followed by secondary antibodies (1:10000 dilution; Abcam Inc.). Immunoreactive signals were visualized with ECL (Amersham Biosciences) and proteins were quantified with an ImageQuant image analysis system (Storm Optical Scanner, Molecular Dynamics). Each western blot band was measured 3 times and theaverage optical density was calculated. 2.9 Immunohistochemistry IHC of the remaining 24 formalin-fixed left ventricle samples was performed to validate 3 significantly changed proteins. Primary antibodies included monoclonal anti-rat antibody to the protein RACK1 (1:100; Abcam Inc.) and polyclonal anti-rat antibody to the proteins ALDH6A1 (1:50; Abcam Inc.) and Hhatl (1:200; ThermoFisher Inc., Waltham, MA). One section of each formalin-fixed left ventricle sample was used to acquire data from five different fields of view in myocardia at high power magnification (200 ×) by 2 independent investigators to evaluate IHC staining. Tissue sections were scored based on percent immunopositive cells and staining intensity. Percent immunopositive cells were categorized as follows: 70%, corresponding to scores of 0, 1, 2, 3, and 4, respectively. Staining intensity was at 4 levels: none, mild, moderate, and intense,



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

corresponding to scores of 0, 1, 2, and 3, respectively.29 Scores for samples were calculated and used for quantitative analysis of IHC results. 2.10 Statistical Analysis The study data were expressed as mean ± standard deviation (SD). A Student’s t-test was used to compare TUNEL staining and IHC results of 2 groups (p 1.5 or < 0.67 and P-values < 0.05 in the myocardial tissue of the acute epilepsy and chronic epilepsy groups, respectively, were considered to be differentially expressed.16 Through comparative analysis, 7 proteins with fold change



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

of ≥ ± 1.5 (log2 0.58) were identified as differentially expressed in the myocardial tissue of the acute epilepsy group (Fig. 5A), and 6 were upregulated and 1 was downregulated (Table S1). The biological processes of these proteins were identified by GO analysis, which showed that these proteins were mainly involved in actin cytoskeleton organization and brown fat cell differentiation. Similarly, a comparison of the myocardial tissue between the control and chronic epilepsy groups identified 60 differentially expressed proteins (Fig. 5B), with 32 upregulated and 28 downregulated (Table S2). GO analysis showed that these proteins were major participants in cellular oxidant detoxification, anoxic response, and mitochondrial respiratory chain complex III assembly. We further compared the results from Table S1 and Table S2; the results showed that only 5 proteins were differentially expressed in both of acute and chronic epilepsy groups (Table 1). A total of 62 dysregulated proteins were identified in the myocardial tissue of either the acute or chronic epilepsy groups. GO annotation analysis was applied to classify these differentially expressed proteins in terms of their cellular components, molecular function, and biological processes (Fig. 6A-C). Bioinformatic analysis with DAVID software did not identify global proteomic changes suggesting systolic/diastolic functional or electrophysiological abnormalities, likely due to the short duration of the study. MS/MS spectrum of a differentially expressed protein and the relative reporter ion intensity is shown in Fig. 7 (ALDH6A1, upregulated in myocardial tissue of both the acute and chronic epilepsy group). Cluster analysis revealed changes in abundance in 62 differentially expressed proteins in myocardial tissue in the acute control and acute and chronic epilepsy


Page 14 of 43

Page 15 of 43

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


groups (Fig. 8). Of the 62 differentially expressed proteins, 3 proteins were significant increased in both acute and chronic epilepsy groups, 28 proteins were significant increased in the chronic epilepsy group, 2 proteins were significant increased in the acute epilepsy group, 1 protein was significantly decreased in both acute and chronic epilepsy groups, 1 protein was significant decreased in the chronic epilepsy group and increased in the acute epilepsy group, and 27 proteins were significant decreased in the chronic epilepsy group. Heat map data show that changes in protein abundance observed in the chronic epilepsy group were significantly different than those found in controls and the acute epilepsy group. 3.5 Western Blot Validation of the Quantitative Proteomic Analysis Three differentially expressed proteins, RACK1, Hhatl and ALDH6A1, were validated by Western blot to check the reliability of the iTRAQ-based quantitative proteomics results. The Western blot analysis results supported the iTRAQ results by demonstrating a lower expression level of RACK1 and a higher expression level of ALDH6A1 in epileptic myocardial tissue, and a higher expression level of Hhatl in the acute epileptic myocardial tissue and a lower expression level of Hhatl in the chronic epileptic myocardial tissue than in the control group (Fig. 9). 3.6 Validation of the Differentially Expressed Proteins Three significantly changed proteins of the acute and chronic epileptic myocardial tissue, RACK1, ALDH6A1 and Hhatl, were selected for IHC analysis based on their potential biological function in the process of cardiac injury during epilepsy. The IHC analysis results were in agreement with the iTRAQ coupled with



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

nano-LC-MS/MS results. Compared with the control group, RACK1 expression was significantly decreased in both the acute and chronic epilepsy groups, ALDH6A1 expression was remarkably increased in the acute and chronic epilepsy groups, and Hhatl expression was significantly increased in the acute and decreased in the chronic epilepsy groups (Fig. 10). Discussion Epilepsy is a complex neurological disorders that can cause organ injury.1,3-5 Intractable epilepsy and frequent therapeutic changes in antiepileptic drugs contribute to poor seizure control and increased mortality.31,32 SUDEP is thought to be difficult to predict and prevent,5 and studies show that SUDEP is a multi-stage biological process.6 Data from animal and clinical studies suggest that the postictal impairment of respiration and shutdown of cerebral and brainstem function play pivotal roles in the occurrence of sudden death.3,6 Recent studies indicate that cardiovascular changes and cardiac injury may be causative in SUDEP.4,5,9,10 Histopathological data confirmed cardiac injury in rats with epilepsy, and these data agreed with reported studies.9 In addition, TUNEL and caspase-3 staining shown that cardiomyocyte apoptosis is involved in the cardiac injury of epileptic rat. Chen F et al. used tremor rats to model epilepsy and found that Bcl-2 and ERK1/2 were decreased in rat hearts, but Bax, caspase-3, c-Jun NH2-terminal protein kinases and P-p38 were upregulated in rat hearts. Thus, cardiomyocyte apoptosis may be associated with activation of the mitogen-activated protein kinase pathway and mitochondria-initiated intrinsic pathway.30


Page 16 of 43

Page 17 of 43

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


While many studies have focused on noting changes in electrocardiogram measurements, blood pressure, and myocardial histopathology, the underlying molecular mechanisms and involved biological pathways associated with cardiac injury in epilepsy remain elusive. In this study, we used iTRAQ-based proteomics to examine rat myocardial tissue and to explore molecular proteomic differences to reveal physiological/pathological mechanisms leading to cardiac injury after recurrent seizures. iTRAQ can be used to measure 4 samples under a single condition, and we used this to identify differentially expressed proteins that contribute to myocardial damage in epilepsy. With this mass spectrometry-based technique, a total of 2345 proteins were reproducibly quantified from epileptic rat myocardial tissue. Of these, 7 proteins were found to be significantly varied in the acute epilepsy group and 60 proteins were identified as differentially expressed in the chronic epilepsy group. Comparative protein analysis of the acute and chronic epilepsy groups confirmed that 5 proteins were differentially expressed in both groups. Compared with previous proteomics studies, few proteins were identified differentially expressed in myocardium with epilepsy in our iTRAQ-based proteomics study, which suggests that cardiac injury component of epilepsy may due to activation of acute signaling pathways, rather than through gene expression changes.33,34 Cluster analysis of the 62 differentially expressed proteins in acute control and acute and chronic epilepsy groups indicated that protein changes in the chronic epilepsy group were significantly different from those in the acute control and acute epilepsy groups. Bioinformatics analysis of the



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

altered expressed proteins suggests that the pathogenesis of cardiac injury in acute and chronic epilepsy may be associated with different molecular mechanisms. Of the 5 significantly changed proteins, 3 were screened out based on their biological function in the process of cardiac injury in epilepsy, and all 3 were successfully verified in larger group of myocardial tissue samples by Western blotting and IHC. One differentially expressed protein was RACK1, which was significantly decreased in myocardial tissue of acute and chronic epilepsy groups compared with controls. RACK1 is a member of the tryptophan-aspartate repeat (WD-repeat) family of proteins and has a 7-bladed β-propeller structure, with each of the blades containing one WD40 repeat.35 Although RACK1 is known as a scaffold protein, it interacts with various proteins and plays an important role in multiple cellular processes including cellular stress, gene transcription, protein translation, vesicle fusion, tissue development, and cancer progression.36 Recent studies indicate that RACK1 is decreased in myocardial tissues after myocardial ischemia/reperfusion injury and alleviated in hypoxia/reoxygenation, suggesting that the reducted RACK1 in myocardial tissue contributes to cardiomyocyte apoptosis.34,35 Cardiomyocyte apoptosis in rats with epilepsy was measured using TUNEL and caspase-3 staining in this study. Data show that seizures can lead to an imbalance between the blood supply and the demands of cardiac muscle.37-39 Our research suggests that downregulation of RACK1 may be attributed to the myocardial ischemia/hypoxia caused by recurrent seizures. Moreover, research has also shown that RACK1 can repress hypertrophic responses in cardiomyocytes by interacting with zinc finger protein GATA4, which


Page 18 of 43

Page 19 of 43

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


could inhibit pathological cardiac hypertrophy and heart failure.40 These findings suggest that RACK1 plays an important role in the progression of cardiac injury in epilepsy and may be a promising therapeutic target for improving cardiac function in epileptic patients, especially for those with refractory epilepsy. Another selected protein in our study was ALDH6A1, which was significantly upregulated in epileptic myocardial tissue relative to the control animals. ALDH6A1 is present in the heart, liver, kidney, brain, and muscle mitochondria.41 As the only CoA-dependent aldehyde dehydrogenase (ALDH), ALDH6A1 is needed for catalyzing irreversible oxidative decarboxylation of malonate and methylmalonate to acetyl- and propionyl-CoA as well as for the degradation of valine and pyrimidine.42 Recent studies indicate that ALDH6A1 is associated with various metabolic diseases such as developmental delay, type 2 diabetes, kidney cancer, and hepatocellular carcinoma.41,43-45 In the present study, the level of ALDH6A1 in epileptic myocardial tissue increased significantly, showing a 2.4-fold elevation in the acute group and a 5.7-fold elevation in the chronic group over controls. Upregulation of ALDH6A1 can increase the formation of acetyl-CoA and propionyl-CoA, which are central to energy metabolism in vivo in the tricarboxylic acid cycle, and eventually leads to increased energy supplies.42,46 Previous research has demonstrated that seizures can lead to cardiac ischemia.42 Upregulation of ALDH6A1 may thus assist with relieving myocardial energy deficiency due to ischemia after recurrent seizures.47 In the present study, Hhatl was the only differentially expressed protein that upregulated in the acute epilepsy group and downregulated in the chronic epilepsy



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

group. As a member of the membrane-bound O-acyltransferase family, Hhatl was initially identified as being key to glycerol metabolism and transport, but other studies suggest that Hhatl is associated with many cellular processes involved in cell preservation and function, such as lipid metabolism, plasma membrane assembly and composition, membrane and wall integrity, and cytoskeleton polarization.48-50 Recently, Bleve’s group reported that overexpression of Hhatl induces the formation of proliferated structures that contain ER and Golgi resident proteins and ultimately affects global ER and Golgi structure.51 A study by Tulha et al. showed that cells lacking Hhatl undergo a necrotic cell death process instead of programmed cell death.52 Hhatl levels were increased 1.5-fold in our acute epilepsy group and decreased in the chronic epilepsy group, reaching a 12% reduction relative to the control. These findings not only demonstrated that the mechanism of cardiac injury in epilepsy is complicated and may be different in acute and chronic epilepsy, but also suggest that increasing expression of Hhatl in epileptic patients may inhibit myocardial necrosis and improve patient outcomes. In summary, an iTRAQ-based quantitative proteomics approach was applied to screen differentially expressed proteins associated with cardiac injury in epilepsy in rat epileptic myocardial tissue. Three significantly changed proteins (RACK1, ALDH6A1, and Hhatl) were identified as playing a crucial role in cardiac injury after recurrent seizures, and all were confirmed in the subsequent Western blot and IHC analysis. In conclusion, the results of our study offer new insight into the molecular mechanisms of cardiac injury and may provide some potential novel therapeutic


Page 20 of 43

Page 21 of 43

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


targets for preventing myocardial damage in epilepsy. Future studies are needed to confirm our preliminary data and establish a more precise molecular mechanism of cardiac injury in epilepsy. Supporting Information Table S1. Differentially expressed proteins in the left ventricular tissue of acute epilepsy group identified by the iTRAQ based quantitative proteomics approach. Table S2. Differentially expressed proteins in the left ventricular tissue of chronic epilepsy group identified by the iTRAQ based quantitative proteomics approach.

Author information #

These authors contributed equally to this work.

*

Corresponding author: JB. Li,

Postal Address: Yixueyuan Road 1#, Yuzhongqu, Chongqing 400016, China. Tel/Fax: +86-23-68485994. E-mail address: [email protected] Notes The authors declare no competing financial interest.

Acknowledgments This work was supported by the Social Science and Technology Innovation Projects of Chongqing (cstc2016shmszx00011), the Science and Technology Projects of Chongqing Education Commission (KJ1502703) and the Science and Technology Cooperation Projects of Guzhou (2015-7572).



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 22 of 43

References (1) Singh A.; Trevick S. The Epidemiology of Global Epilepsy. Neurol Clin. 2016, 34, 837-847. (2) Ngugi AK.; Bottomley C.; Kleinschmidt I.; Sander JW.; Newton CR. Estimation of the burden of active and life-time epilepsy: a meta-analytic approach. Epilepsia. 2010, 51, 883-990. (3) Devinsky O. Sudden, unexpected death in epilepsy. N Engl J Med. 2011, 365, 1801-1811. (4) Ryvlin P.; Nashef L.; Lhatoo SD.; Bateman LM.; Bird J.; Bleasel A. Incidence and mechanisms of cardiorespiratory arrests in epilepsy monitoring units (MORTEMUS): a retrospective study. Lancet Neurol. 2013, 12, 966-977. (5) Ravindran K.; Powell KL.; Todaro M.; O'Brien TJ. The pathophysiology of cardiac dysfunction in epilepsy. Epilepsy Res. 2016, 127, 19-29. (6) Nashef L.; Ryvlin P. Sudden unexpected death in epilepsy (SUDEP): update and reflections. Neurol Clin. 2009, 27, 1063-1074. (7) Eastaugh AJ.; Thompson T.; Vohra JK.; O'Brien TJ.; Winship I. Sudden unexpected death, epilepsy and familial cardiac pathology. J Clin Neurosci. 2015, 22, 1594-1600. (8)

Friedman

D.; Donner

Sudden unexpected

EJ.;

Stephens

death in epilepsy:

D.; Wright

C.;

Devinsky

O.

knowledge and experience among U.S.

and Canadian neurologists. Epilepsy Behav. 2014, 35, 13-18.


Page 23 of 43

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


(9) Read MI.; McCann DM.; Millen RN.; Harrison JC.; Kerr DS.; Sammut IA. Progressive development of cardiomyopathy following altered autonomic activity in status epilepticus. Am J Physiol Heart Circ Physiol. 2015, 309, H1554-1564. (10) Al-Najafi S.; Rosman H. Seizure-induced myocardial stunning: a possible cardiac link to sudden unexpected death inepilepsy (SUDEP). Seizure. 2015, 24, 137-139. (11) Su N.; Choi HP.; Wang F.; Su H.; Fei Z.; Yang JH. Quantitative Proteomic Analysis of Differentially Expressed Proteins and Downstream Signaling Pathways in Chronic Bladder Ischemia. J Urol. 2016, 195, 515-523. (12) Cao H.; Zhang A.; Sun H.; Zhou X.; Guan Y.; Liu Ql. Metabolomics-proteomics profiles delineate metabolic changes in kidney fibrosis disease. Proteomics. 2015, 15, 3699-3710. (13) Butterfield DA.; Palmieri EM.; Castegna A. Clinical implications from proteomic studies in neurodegenerative diseases: lessons frommitochondrial proteins. Expert Rev Proteomics. 2016, 13, 259-274. (14) Liu R.; Kenney JW.; Manousopoulou A.; Johnston HE.; Kamei M.; Woelk CH.; et al. Quantitative Non-canonical Amino Acid Tagging (QuaNCAT) Proteomics Identifies Distinct Patterns of Protein Synthesis Rapidly Induced by Hypertrophic Agents in Cardiomyocytes, Revealing New Aspects of Metabolic Remodeling. Mol Cell Proteomics. 2016, 15, 3170-3189. (15) Vafiadaki E.; Arvanitis DA.; Papalouka V.; Terzis G.; Roumeliotis TI.; Spengos K.;

et

al.

Muscle lim protein isoform negatively regulates striated muscle actin

dynamics and differentiation. FEBS J. 2014, 281, 3261-3279.



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 24 of 43

(16) Manousopoulou A.; Gatherer M.; Smith C.; Nicoll JAR.; Woelk CH.; Johnson M.; et

al.

Systems proteomic analysis reveals that clusterin and tissue inhibitor

of

metalloproteinases 3 increase in leptomeningeal arteries affected by cerebral amyloid angiopathy. Neuropathol Appl Neurobiol. 2017, 43, 492-504. (17) Manousopoulou

A.; Koutmani

Y.;

Karaliota

S.; Woelk

CH.; Manolakos

ES.; Karalis K.; et al. Hypothalamus proteomics from mouse models with obesity and anorexia reveals therapeutictargets of appetite regulation. Nutr Diabetes. 2016, 6, e204. (18) Pichler P.; Köcher T.; Holzmann J.; Mazanek M.; Taus T.; Ammerer G.; et al. Peptide labeling with isobaric tags yields higher identification rates using iTRAQ 4-plex compared to TMT 6-plex and iTRAQ 8-plex on LTQ Orbitrap. Anal Chem. 2010, 82, 6549-6558. (19) de Carvalho CR.; Hoeller AA.; Franco PL.; Martini AP.; Soares FM.; Lin K. The cannabinoid

CB2 receptor-specific agonist AM1241 increases

pentylenetetrazole-induced seizure severity in Wistar rats. Epilepsy Res. 2016, 127, 160-167. (20) Zhu X.; Dong J.; Shen K.; Bai Y.; Zhang Y.; Lv X. NMDA receptor NR2B subunits

contribute

to PTZ-kindling-induced hippocampal

astrocytosis

and

oxidative stress. Brain Res Bull. 2015, 114, 70-78. (21) Racine RJ. Modification of seizure activity by electrical stimulation. II. Motor seizure. Electroencephalogr Clin Neurophysiol. 1972, 32, 281-294.


Page 25 of 43

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


(22) Kong WL.; Min JW.; Liu YL.; Li JX.; He XH.; Peng BW. Role of TRPV1 in susceptibility to PTZ-induced seizure following repeated hyperthermia challenges in neonatal mice. Epilepsy Behav. 2014, 31, 276-280. (23) Su Z.; Zhu H.; Zhang M.; Wang L.; He H.; Jiang S. Salt-induced changes in cardiac phosphoproteome in a rat model of chronic renal failure. PLoS One. 2014, 9, e100331. (24) Kristen AV.; Ackermann K.; Buss S.; Lehmann L.; Schnabel PA.; Haunstetter A.; et al. Inhibition of apoptosis by the intrinsic but not the extrinsic apoptotic pathway in myocardial ischemia-reperfusion. Cardiovasc Pathol. 2013, 22, 280-286. (25) Snigdha S.; Berchtold N.; Astarita G.; Saing T.; Piomelli D.; Cotman CW.; Dietary and behavioral interventions protect against age related activation of caspase cascades in the canine brain. PLoS One. 2011, 6(9), e24652. (26)

Batth

TS.; Francavilla

C.; Olsen

JV.

Off-line high-pH reversed-phase

fractionation for in-depth phosphoproteomics. J Proteome Res. 2014, 13, 6176-6186. (27) Shilov IV.; Seymour SL.; Patel AA.; Loboda A.; Tang WH.; Keating SP. The Paragon Algorithm, a next generation search engine that uses sequence temperature values and feature probabilities to identify peptides from tandem mass spectra. Mol Cell Proteomics. 2007, 6, 1638-1655. (28) Lam H.; Deutsch EW.; Aebersold R. Artificial decoy spectral libraries for false discovery rate estimation in spectral librarysearching in proteomics. J Proteome Res 2010, 9, 605-610.



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 26 of 43

(29) Zhang P.; Zhu S.; Li Y.; Zhao M.; Liu M.; Gao J. Quantitative proteomics analysis to identify diffuse axonal injury biomarkers in rats using iTRAQ coupled LC-MS/MS. J Proteomics. 2016, 133, 93-99. (30) Chen F.; Cao YG.; Qi HP.; Li L.; Huang W.; Wang Y.; et al. Involvement of cardiomyocyte

apoptosis in myocardial injury of hereditary epileptic rats.

Can

J

Physiol Pharmacol. 2013, 91, 804-811. (31) Christensen J.; Pedersen CB.; Sidenius P.; Olsen J.; Vestergaard M. Long-term mortality in children and young adults with epilepsy--A population-based cohort study. Epilepsy Res. 2015, 114, 81-88. (32) Novy J.; Belluzzo M.; Caboclo LO.; Catarino CB.; Yogarajah M. The lifelong course of chronic epilepsy: the Chalfont experience. Brain. 2013, 136, 3187-3199. (33) Guo X.; Hu H.; Chen F.; Li Z.; Ye S.; Cheng S.; et al. iTRAQ-based comparative proteomic analysis of Vero cells infected with virulent and CV777 vaccine strain-like strains of porcine epidemic diarrhea virus. J Proteomics. 2016, 130, 65-75. (34) Ji W.; Cong R.; Li S.; Li R.; Qin Z.; Li Y.; et al. Comparative Proteomic Analysis of Soybean Leaves and Roots by iTRAQ Provides Insights into Response Mechanisms to Short-Term Salt Stress. Front Plant Sci. 2016, 7, 573. (35) Kong Q.; Gao L.; Niu Y.; Gongpan P.; Xu Y.; Li Y. RACK1 is required for adipogenesis. Am J Physiol Cell Physiol. 2016, 311, 831-836. (36) Qian L.; Shi J.; Zhang C.; Lu J.; Lu X.; Wu K. Downregulation of RACK1 is associated with cardiomyocyte apoptosis after myocardial ischemia/reperfusion injury in adult rats. In Vitro Cell Dev Biol Anim. 2016, 52, 305-313.


Page 27 of 43

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


(37) Surges R.; Adjei P.; Kallis C.; Erhuero J.; Scott CA.; Bell GS. Pathologic cardiac repolarization

in pharmacoresistant epilepsy

and

its potential

role in

sudden

unexpected death in epilepsy: a case-control study. Epilepsia. 2010, 51, 233-242. (38) Stollberger C.; Finsterer J. Evidence of cardiac ischemia during seizures in drug refractory epilepsy patients. Neurology. 2004, 62, 1238-1239. (39) Johnston SC.; Siedenberg R.; Min JK.; Jerome EH.; Laxer KD. Central apnea and acute cardiac ischemia in a sheep model of epileptic sudden death. Ann Neurol. 1997, 42, 588-594. (40) Suzuki H.; Katanasaka Y.; Sunagawa Y.; Miyazaki Y.; Funamoto M.; Wada H. Tyrosine

phosphorylation

of RACK1 triggers cardiomyocyte hypertrophy by

regulating the interaction between p300 and GATA4. Biochim Biophys Acta. 2016, 1862, 1544-1557. (41) Umehara T.; Usumoto Y.; Tsuji A.; Kudo K.; Ikeda N. Expression of material mRNA in the hypothalamus and frontal cortex in a rat model of fatal hypothermia. Leg Med (Tokyo). 2011, 13, 165-170. (42) Meierhofer D.; Halbach M.; Sen NE.; Gispert S.; Auburger G. Ataxin-2 (Atxn2)-Knock-Out

Mice Show Branched Chain Amino Acids and

Fatty Acids

Pathway Alterations. Mol Cell Proteomics. 2016, 15, 1728-1739. (43) Dharuri H.; 't Hoen PA.; van Klinken JB.; Henneman P.; Laros JF.; Lips MA. Downregulation of the acetyl-CoA metabolic network in adipose tissue of obese diabetic individuals and recovery after weight loss. Diabetologia. 2014, 57, 2384-2392.



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 28 of 43

(44) Johansson HJ.; Sanchez BC.; Forshed J.; Stål O.; Fohlin H.; Lewensohn R. Proteomics profiling identify CAPS as a potential predictive marker of tamoxifen resistance in estrogen receptor positive breast cancer. Clin Proteomics. 2015, 12, 8. (45) Liu Y.; Zhu X.; Zhu J.; Liao S.; Tang Q.; Liu K. Identification of differential expression

of genes in hepatocellular

carcinoma by

suppression

subtractive

hybridization combined cDNA microarray. Oncol Rep. 2007, 18, 943-951. (46) Shi L.; Tu BP. Acetyl-CoA and the regulation of metabolism: mechanisms and consequences. Curr Opin Cell Biol. 2015, 33, 125-131. (47) Tigaran S.; Mølgaard H.; McClelland R.; Dam M.; Jaffe AS. Evidence of cardiac ischemia during seizures in drug refractory epilepsy patients. Neurology. 2003, 60, 492-495. (48) Ferreira C.; Lucas C. The yeast O-acyltransferase Gup1p interferes in lipid metabolism

with direct consequences on

the sphingolipid-sterol-ordered domains

integrity/assembly. Biochim Biophys Acta. 2008, 1778, 2648-2653. (49) Ferreira C.; Silva S.; van Voorst F.; Aguiar C.; Kielland-Brandt MC.; Brandt A. Absence

of Gup1p in Saccharomyces cerevisiae results in defective cell wall

composition, assembly, stability and morphology. FEMS Yeast Res. 2006, 6, 1027-1038. (50) Ni L.; Snyder M. A genomic study of the bipolar bud site selection pattern in Saccharomyces cerevisiae. Mol Biol Cell. 2001, 12, 2147-2170. (51) Bleve G.; Di Sansebastiano GP.; Grieco F. Over-expression of functional Saccharomyces cerevisiae GUP1, induces proliferation of intracellular membranes


Page 29 of 43

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


containing ER and Golgi resident proteins. Biochim Biophys Acta. 2011, 1808, 733-744. (52) Tulha J.; Faria-Oliveira F.; Lucas C.; Ferreira C. Programmed cell death in Saccharomyces cerevisiae is hampered by the deletion of GUP1gene. BMC Microbiol. 2012, 12, 80.

Table 1. Differentially expressed proteins in the left ventricular tissue in both of the acute and chronic epilepsy group identified by the iTRAQ based quantitative proteomics approach. No.

Protein name

Gene name

Uniprot ID

1

Receptor of activated protein C kinase 1

Rack1

2

Gup1, glycerol uptake/transporter homolog

3

Chronic

Acute

Fold change

p-value

Fold change

p-value

P63245

0.546257019

0.01732057

0.417908096

0.01476768

Hhatl

D4A9P9

0.128233105

0.009269285

1.527565956

0.005530776

Aldehyde dehydrogenase family 6, subfamily A1

Aldh6a1

G3V7J0

5.754398823

0.000174551

2.466038942

0.009754184

4

Prefoldin 1

Pfdn1

D3ZX38

4.786301136

0.04405592

22.49054909

0.032977771

5

Uncharacterized protein

N/A

D3ZBJ7

4.786301136

0.045355938

5.754398823

0.04109792

Figure Legends Figure 1. Histopathological examination of left ventricular tissue samples from control and epilepsy groups. (A) Acute epilepsy control group; (B) acute epilepsy group; (C) chronic epilepsy control group; and (D) chronic epilepsy group. The morphological changes of myocardial cells and pathologic abnormalities were observed with H&E staining. (A, C) Normal myocardial tissue in control groups. (B)



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Myocardial hemorrhage and serous effusion in acute epilepsy group (arrows). (D) Myocardial hemorrhage and myocyte vacuolization in chronic epilepsy group (arrows).

Figure 2. Representative EEG recordings from the prefrontal cortex of rats in control and epilepsy groups. (A) Acute epilepsy control group; (B) acute epilepsy group; (C) chronic epilepsy control group; and (D) chronic epilepsy group. (A, C) Normal EEG recordings of controls. (B, D) Epileptic waves in acute and chronic epilepsy groups (arrows).

Figure 3. Cardiomyocyte apoptosis in rats with epilepsy determined by TUNEL staining. Nuclei stained brown were TUNEL-positive. (A) Representative images of TUNEL staining of all groups. (B) Apoptotic ratios of cardiomyocytes increased significantly in epilepsy groups.

Figure 4. IHC for caspase-3 staining to assess caspase-3 involvement after myocardial injury in rats with epilepsy. (A) IHC results for caspase-3 staining of all groups. (B) IHC quantitative analysis showed significant increase in expression of caspase-3 in epilepsy groups.

Figure 5. Differentially expressed proteins in myocardial tissue of acute epilepsy and chronic epilepsy groups. (A) Volcano plot of protein changes in myocardial tissue of


Page 30 of 43

Page 31 of 43

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


acute epilepsy and acute epilepsy control groups. There were 7 proteins with fold change of > 1.5 or < 0.67 and p-values < 0.05 were identified as significantly dysregulated. (B) Volcano plot of protein changes in myocardial tissue between chronic epilepsy and chronic epilepsy control groups. There were 60 proteins with fold change of > 1.5 or < 0.67 and p-values < 0.05 were identified as significantly dysregulated.

Figure 6. GO analysis of 62 differentially expressed proteins using DAVID and Gene Ontology annotations. The identified proteins were classified into cellular components (A), molecular function (B), and biological process (C).

Figure 7. Example of one of differentially expressed proteins identified by iTRAQ coupled with nano-LC-MS/MS analysis. (A) MS/MS spectrum of ALDH6A1 peptide (AITDAAMMAEELKK) upregulated in myocardial tissue of acute and chronic epilepsy groups. (B) Spectrum of relative reporter ion intensity for peptide (m/z; chronic epilepsy controls [114 tag]; chronic epilepsy samples [115 tag]; acute epilepsy controls [116 tag], and acute epilepsy samples [117 tag]).

Figure 8. Cluster analysis of 62 differentially expressed proteins in myocardial tissue of acute control and acute and chronic epilepsy groups (A: acute epilepsy control group; B: acute epilepsy group; C: chronic epilepsy group). Chronic controls were used to normalize fold changes in proteins in myocardial tissue.



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Figure 9. Western blot validation of RACK1, ALDH6A1 and Hhatl, identified by the iTRAQ-based proteomics approach. β-Actin was a loading control. Experiments were repeated 3 times.

Figure 10. IHC validation of the 3 differentially expressed proteins. RACK1 (A–B), ALDH6A1 (C), and Hhatl (D) were examined using the remaining 24 formalin-fixed left ventricular tissue samples. (A) IHC results for RACK1 in left ventricular tissues of all groups. (B-D) IHC quantitative analysis of RACK1, ALDH6A1, and Hhatl are shown as box plots (p < 0.05, independent t-test).


Page 32 of 43

Page 33 of 43

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Figure 1. Histopathological examination of left ventricular tissue samples from control and epilepsy groups. (A) Acute epilepsy control group; (B) acute epilepsy group; (C) chronic epilepsy control group; and (D) chronic epilepsy group. The morphological changes of myocardial cells and pathologic abnormalities were observed with H&E staining. (A, C) Normal myocardial tissue in control groups. (B) Myocardial hemorrhage and serous effusion in acute epilepsy group (arrows). (D) Myocardial hemorrhage and myocyte vacuolization in chronic epilepsy group (arrows). 151x101mm (300 x 300 DPI)



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 34 of 43

Figure 2. Representative EEG recordings from the prefrontal cortex of rats in control and epilepsy groups. (A) Acute epilepsy control group; (B) acute epilepsy group; (C) chronic epilepsy control group; and (D) chronic epilepsy group. (A, C) Normal EEG recordings of controls. (B, D) Epileptic waves in acute and chronic epilepsy groups (arrows). 73x41mm (300 x 300 DPI)


Page 35 of 43

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Figure 3. Cardiomyocyte apoptosis in rats with epilepsy determined by TUNEL staining. Nuclei stained brown were TUNEL-positive. (A) Representative images of TUNEL staining of all groups. (B) Apoptotic ratios of cardiomyocytes increased significantly in epilepsy groups. 81x130mm (300 x 300 DPI)



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Figure 4. IHC for caspase-3 staining to assess caspase-3 involvement after myocardial injury in rats with epilepsy. (A) IHC results for caspase-3 staining of all groups. (B) IHC quantitative analysis showed significant increase in expression of caspase-3 in epilepsy groups. 80x131mm (300 x 300 DPI)


Page 36 of 43

Page 37 of 43

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Figure 5. Differentially expressed proteins in myocardial tissue of acute epilepsy and chronic epilepsy groups. (A) Volcano plot of protein changes in myocardial tissue of acute epilepsy and acute epilepsy control groups. There were 7 proteins with fold change of > 1.5 or < 0.67 and p-values < 0.05 were identified as significantly dysregulated. (B) Volcano plot of protein changes in myocardial tissue between chronic epilepsy and chronic epilepsy control groups. There were 60 proteins with fold change of > 1.5 or < 0.67 and pvalues < 0.05 were identified as significantly dysregulated. 85x34mm (300 x 300 DPI)



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Figure 6. GO analysis of 62 differentially expressed proteins using DAVID and Gene Ontology annotations. The identified proteins were classified into cellular components (A), molecular function (B), and biological process (C). 155x82mm (300 x 300 DPI)


Page 38 of 43

Page 39 of 43

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Figure 7. Example of one of differentially expressed proteins identified by iTRAQ coupled with nano-LCMS/MS analysis. (A) MS/MS spectrum of ALDH6A1 peptide (AITDAAMMAEELKK) upregulated in myocardial tissue of acute and chronic epilepsy groups. (B) Spectrum of relative reporter ion intensity for peptide (m/z; chronic epilepsy controls [114 tag]; chronic epilepsy samples [115 tag]; acute epilepsy controls [116 tag], and acute epilepsy samples [117 tag]). 171x61mm (300 x 300 DPI)



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Figure 8. Cluster analysis of 62 differentially expressed proteins in myocardial tissue of acute control and acute and chronic epilepsy groups (A: acute epilepsy control group; B: acute epilepsy group; C: chronic epilepsy group). Chronic controls were used to normalize fold changes in proteins in myocardial tissue. 82x75mm (300 x 300 DPI)


Page 40 of 43

Page 41 of 43

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Figure 9. Western blot validation of RACK1, ALDH6A1 and Hhatl, identified by the iTRAQ-based proteomics approach. β-Actin was a loading control. Experiments were repeated 3 times. 87x123mm (300 x 300 DPI)



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Figure 10. IHC validation of the 3 differentially expressed proteins. RACK1 (A–B), ALDH6A1 (C), and Hhatl (D) were examined using the remaining 24 formalin-fixed left ventricular tissue samples. (A) IHC results for RACK1 in left ventricular tissues of all groups. (B-D) IHC quantitative analysis of RACK1, ALDH6A1, and Hhatl are shown as box plots (p < 0.05, independent t-test). 168x78mm (300 x 300 DPI)


Page 42 of 43

Page 43 of 43

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


graphic for manuscript 115x35mm (300 x 300 DPI)


Quantitative Proteomic Analysis To Identify Differentially Expressed

Recommend Documents