Quantitative cardiac phosphoproteomics profiling during ischemia-reperfusion in an immature swine model
Abstract
Ischemia-reperfusion (I/R) results in altered metabolic and molecular responses, and phosphorylation is one of the most noted regulatory mechanisms mediating signaling mechanisms during physiological stresses. To expand our knowledge of the potential phosphoproteomic changes in the myocardium during I/R, we used Isobaric Tags for Relative and Absolute Quantitation-based analyses in left ventricular samples obtained from porcine hearts under control or I/R conditions. The data are available via ProteomeXchange with identifier PXD006066. We identified 1,896 phosphopeptides within left ventricular control and I/R porcine samples. Significant differential phosphorylation between control and I/R groups was discovered in 111 phosphopeptides from 86 proteins. Analysis of the phosphopeptides using Motif-x identified five motifs: (..R..S..), (..SP..), (..S.S..), (..S…S..), and (..S.T..). Semiquantitative immunoblots confirmed site location and directional changes in phosphorylation for phospholamban and pyruvate dehydrogenase E1, two proteins known to be altered by I/R and identified by this study. Novel phosphorylation sites associated with I/R were also identified. Functional characterization of the phosphopeptides identified by our methodology could expand our understanding of the signaling mechanisms involved during I/R damage in the heart as well as identify new areas to target therapeutic strategies.
NEW & NOTEWORTHY We used Isobaric Tags for Relative and Absolute Quantitation technology to investigate the phosphoproteomic changes that occur in cardiac tissue under ischemia-reperfusion conditions. The results of this study provide an extensive catalog of phosphoproteins, both predicted and novel, associated with ischemia-reperfusion, thereby identifying new pathways for investigation.
cardiovascular disease (CVD) is one of the leading causes of mortality and morbidity worldwide (21), and dysregulation of phosphorylation events has been associated with the initiation and progression of CVD (53, 86). Protein phosphorylation serves as a ubiquitous regulatory mechanism that plays a critical role in processes such as energy metabolism, signal transduction, apoptosis, and cell survival (23, 39); mass spectrometry proteomics suggests that at least a third of human proteins are phosphorylated (13, 54). Changes in phosphorylation states can result in allosteric conformational changes that modulate enzymatic activity (67), differential recruitment of partner protein(s) (69), and/or changes to subcellular localization and stability (13). Over 500 putative protein kinases have been identified, and together they represent one the largest family of genes in eukaryotes, supporting the important role protein phosphorylation plays in cellular mechanisms (13, 62). However, caution is warranted, as not all phosphosites are functional. A study examining phosphosites based on evolutionary information predicted that ~65% of phosphoproteomic sites may not be functional (54). Xiao et al. (104) developed a website, Predict Functional Phosphopeptides (http://pfp.biosci.org), for users to query phosphosites for likely functionality based on evolutionary conservation, kinase association, disorder score, and secondary structure.
Phosphorylation profiling has been useful in identifying regulators affected by pathological states. Phosphoproteomic studies have been used to delineate signaling mechanisms involved in excitation-contraction coupling of the heart (59), remote ischemic preconditioning (1), and oxidative stress (11). Not surprisingly, dysregulation of kinases and phosphatases, the proteins regulating phosphorylation, has also been associated with diseased cardiac physiology (52, 61). However, most studies have evaluated only a limited number of phosphorylation sites using either semiquantitative immunoblot technology or top-down liquid chromotography-tandem mass spectroscopy (LC-MS/MS). Therefore, the overall phosphorylation response to acute stressors, such as ischemia-reperfusion (I/R), has not been studied using high-throughput methods.
Cardiac I/R injuries are the compounded tissue damage that occurs after an ischemic event in the heart, thereby limiting recovery of function (31, 95). Numerous physiological, metabolic, and molecular changes occur during this stressful period and can be responsible for ongoing myocardial damage and dysfunction (5, 34, 108). Identification of the proteins and sites that display altered phosphorylation in response to I/R could provide potential therapeutic opportunities to limit this damage or improve recovery.
We used a clinically relevant juvenile swine model to determine the overall phosphoproteomic signature in response to I/R in the heart. We have previously characterized this model and demonstrated moderate cardiac dysfunction after I/R (20). These functional abnormalities occur in association with impairments in metabolic pathways, including pyruvate decarboxylation and citric acid cycling. Accordingly, we evaluated the entire porcine cardiomyocyte phosphoproteome instead of focusing on specific proteins or compartments. We identified differences in phosphorylation according to the condition via the quantitative proteomic strategy using Isobaric Tags for Relative and Absolute Quantitation (iTRAQ) (77).
MATERIALS AND METHODS
Porcine model in situ.
Twelve male Yorkshire piglets between 25 and 48 days of age and weighing between 12.3 and 16.7 kg were prepared as previously described (20, 75). Seattle Children's Institutional Animal Use and Care Committee approved all experimental procedures. Sedation was achieved by intramuscular injection of ketamine (33 mg/kg, VEDCO) and xylazine (2 mg/kg, VEDCO), and the animals were placed on a circulating warming blanket. Monitors were placed for ECG, pulse oximetry (Radical SET, Masimo), and rectal temperature. A PowerLab 16/30 recorder (AD Instruments) was used to continuously record data throughout all protocols. A cut-down tracheostomy was performed, and animals underwent general anesthesia under inhaled isoflurane (1-2%, Baxter Healthcare). Venous and arterial access was then obtained for continuous blood pressure monitoring, blood sampling, and infusion of maintenance fluids. Arterial pH, Pco2, Po2, and hemoglobin were measured at regular intervals by use of a Radiometer ABL 800 device (Radiometer America). After the performance of a median sternotomy, a 5-Fr high‐fidelity pressure catheter (Millar Instruments) was inserted into the apex of the left ventricle. Baseline hemodynamic assessments were made at this point. Piglets were separated into two groups. Piglets in I/R were also subject to open chest and coronary occlusion for 10 min followed by reperfusion. Piglets in the control group were also subject to open chest but did not undergo coronary ischemia. At the end of the procedure (2 h), the apex of the heart from both groups was rapidly excised, freeze clamped, and stored in liquid nitrogen for further analysis (Fig. 1).
Fig. 1.Phosphoproteome analysis of cardiac tissue after ischemia-reperfusion (I/R). Schema illustrates the workflow of control or I/R-treated piglets. The total number of phosphopeptides are identified, and the distributions of the identified sites are according to the serine (s*), threonine (t*), and tyrosine (y*) amino acid are shown. iTRAQ, Isobaric Tags for Relative and Absolute Quantitation; LC MS/MS, liquid chromatography-tandem mass spectroscopy.
Protein extraction and Western blot analysis.
Left ventricular tissue was homogenized in RIPA buffer [20 mM Tris·HCl (pH 7.5), 150 mM NaCl, 1 mM Na2EDTA, 0.1% SDS, 1.0% sodium deoxycholate, and 1× protease/phosphatase inhibitor (ThermoScientific)]. Thirty micrograms of total protein extract from pig tissue was resolved using 15% SDS-PAGE and electroblotted onto polyvinylidene difluoride (PVDF) membranes. Standard Western blot protocols were followed. Horseradish peroxidase-conjugated secondary antibodies were used and visualized with enhanced chemiluminescence upon exposure to Kodak BioMax Light ML-1 film. Membranes were stripped by washing them 2 × 15 min with 100 mM DTT, 2% (wt/vol) SDS, and 62.5 mM Tris·HCl (pH 6.7) at 70°C followed by three 10-min washes with Tris-buffered saline. Efficiency of protein transfer to the PVDF membrane was determined using the Pierce Reversible Protein Stain Kit for PVDF membranes (no. 24585, Thermo Scientific). Densitometry analyses were performed using ImageJ and Quantity One (Bio-Rad). All Western blots were performed in duplicate. Statistical analyses were performed using Student's t-tests between groups. The criterion for significance was P < 0.05 for all comparisons. Error bars in figures indicate SEs.
The primary antibodies used in this study were pyruvate dehydrogenase (PDH; 2784S) from Cell Signaling Technologies, phospholamban (L-15, sc-21923), phosphorylated (p-)phospholamban (Ser16, sc-12963) from Santa Cruz Biotechnology, and p-PDH (Ser293, ABS204) from EMD Millipore. Antibodies (sc-21923 and sc-12963) and (2784S and ABS204) were validated for use in pigs by the manufacturer or Ledee et al. (55), respectively.
Labeling and enrichment of phosphopeptides.
Tissue lysates were prepared by homogenization in 1 ml of freshly made 8 M urea in 50 mM ammonium bicarbonate (pH 8.0) containing a 1× concentration of phosphatase inhibitor (ThermoFisher Scientific). After incubation on ice for 30 min, insoluble matter was removed by centrifugation at 16,000 g for 20 min. Proteins were reduced, alkylated, digested with trypsin, and desalted using solid-phase extraction (9). Peptides from one biological replicate of each condition were separately methyl esterified (28) and labeled with two units of a different four-plexed iTRAQ reagent (Applied Biosystems) according to the manufacturer’s recommendations. After iTRAQ labeling, samples were mixed and desalted, and phosphopeptides were enriched using immobilized metal ion (Fe3+) affinity chromatography (IMAC) (28). Four sets of iTRAQ experiments were performed for four biological replicates. The four iTRAQ labels were rotated in each case to minimize potential isotope bias of the iTRAQ labels (71).
LC-MS analysis.
Phosphopeptides were separated using an automated dual-column phosphoproteome nano-HPLC platform assembled in house and analyzed using an LTQ-Orbitrap MS instrument (ThermoFisher Scientific) (101). This high-resolution, dual-column LC-MS system extends the dynamic range of detection and reduces multiplexing issues [i.e., adjacent, or overlapping, precursor mass-to-ion charge (m/z) values selected for fragmentation simultaneously] and potential manufacturing impurities associated with the iTRAQ method (71). Pulsed-Q dissociation (PQD) with an optimized normalized collision energy of 22 was used for label quantification via sequential PQD and collision activated dissociation (PQD-CAD) or sequential PQD and multistage activation dissociation (PQD-MSA) (105, 106) for the three most abundant species from each parent ion spectrum (MS). Two LC-MS analyses, one with PQD-CAD and the other with PQD-MSA, were performed for each sample (technical replicates). MS/MS were searched against a collection of Sus scrofus proteins from Uniprot (2013_07) (ftp://ftp.uniprot.org/pub/databases/uniprot/previous_releases/release-2013_07/) coupled with commonly observed contaminants (trypsin, albumin, keratins, etc.) to identify phosphopeptides using a MSGF+ Q-value ≤ 0.01 ± 20 ppm parent mass tolerance, partially tryptic peptide cleavages, fixed modifications of carbamidomethylation of cysteine (+57.0215 Da), and iTRAQ 8-Plex addition (+304.2053 Da) to lysine and peptide NH2-termini as well as variable phosphorylation (+79.9663 Da) of serine, threonine, or tyrosine (46). Results were filtered for a false discovery rate of <1% (MSGF+ Q-value ≥ 0.01) using a decoy approach (19). The updated in-house developed MASIC software program (66) was applied to extract the maximum peak intensity within ±0.5 Da of each expected iTRAQ reporter ion (PQD: 114-117 m/z) from each fragmentation spectrum using correction factors provided by Applied Biosystems to quantify phosphopeptides identified from either CAD or MSA spectra. The MS proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the data set identifiers PXD006066 and 10.6019/PXD006066 (98).
Statistical analyses.
To work in a linear space, the abundance scores were transformed to log2 values. The log abundances were averaged across the biological replicates requiring at least two observations of the presence of a peptide to make this average. Next, we subtracted the averaged peptide log abundances of the two samples to obtain a log ratio between the two samples at the peptide level, calculated 2SDs of these log ratios, and tested the observed absolute value of the log ratios against the 2 σ-value. If a peptide shows a difference of larger than 2σ, it was considered significant. We plotted a histogram of the log ratios to show zero centeredness, indicating that the data are normally distributed and a 2σ significance is meaningful (25). The differentially phosphorylated peptides (DPPs) had absolute log ratios of >1.27 or ≤ −1.27 (fold change of 2.4) or greater. Z scores were used for the DPP cluster analysis.
Bioinformatics and motif analysis.
The gene ontology (GO) suite Database for Annotation, Visualization and Integrated Discovery (DAVID; https://david.ncifcrf.gov) (36, 37) was used to assign molecular function to the DPPs.
Motif-X online software (http://motif-x.med.harvard.edu/motif-x.html) was used to determine whether the phosphorylation sites of the cardiac proteins shared common phosphorylation site motifs (12, 83). The parameters were set to peptide length = 13, occurrence = 20, and statistical significance for P values of <0.000001. The DPPs were compared against two background data sets, IPI.Human Proteome or the iTRAQ LC-MS/MS gene list from this experiment. The search tool for the retrieval of interacting genes/proteins (STRING, http://string-db.org/) (92) was used to construct protein-protein interactions between the differentially phosphorylated proteins.
RESULTS
Protein identification.
Analysis of data comparing nonischemic with I/R hearts identified 1,896 phosphopeptides, where 111 of the phosphopeptides from 86 proteins showed a significant difference between groups, >2.4-fold change. Hierarchical clustering based on Z scores of the log2 values of the 111 phosphopeptides clearly distinguished the increased phosphopeptides from the decreased phosphopeptides (Fig. 2). Of the 111 phosphopeptides, 44 phosphopeptides showed increased phosphorylation, whereas 67 phosphopeptides showed decreased phosphorylation in relation to control animals. The human ortholog was compared with the porcine phosphoprotein to assess conservation of the predicted phosphorylated sites, and, based on sequence alignments, 104 of 111 phosphopeptides showed a conservation at the potentially phosphorylated site between humans and pigs (Supplemental Table S1 in the Supplemental Material; Supplemental Material for this article is available at the American Journal of Physiology Heart and Circulatory Physiology website).
Fig. 2.Cluster analysis of the differentially expressed phosphoproteins. Each row represents a single protein, and each column represents a single sample. The data are colored red for decreased phosphorylation and green for increased phosphorylation. Gene names designate the protein (n = 4 per group).
The breakdown of distribution of serine, threonine, and tyrosine phosphorylated sites observed was 89.5%, 9.9%, and 0.6%, respectively (Fig. 1). Further analysis predicted 76.5% of the phosphopeptides contained one phosphorylated site, 21.3% contained two phosphorylated sites, and 2.2% contained three or more phosphorylated sites (Fig. 1).
Phosphoproteome characterization and classification.
To gain insights into molecular functions of the processes altered by I/R, we performed a GO enrichment analysis using DAVID software. We tested our gene list using either the S. scrofa or Homo sapiens background as the default. We divided our gene list into three groups: the first group contained all 111 DPPs, the second group contained only the 44 increased DPPs, and the third group contained the 67 decreased DPPs. Tables 1 and 2 show a summary of these analyses. A cutoff P value of 0.05 was used in creating the tables; however, it is important to note that the more conservative statistical tests did not always support the significance observed for the P value. The enriched terms for molecular functions involved actin binding, protein binding, and structural roles, suggesting a large involvement of these genes in protein complexes and cell architecture. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis identified cell-cell junction and cellular energetics pathways. Analysis of the increased DPPs did not retrieve any enriched terms for molecular functions in the S. scrofa background or any KEGG pathways for either background. The use of S. scrofa as the background identified fewer enriched terms compared with the H. sapiens background, but overlap between the two was near 100%.
| Term | Fold Enrichment | P Value | Bonferroni | Benjamini | False Discovery Rate |
|---|---|---|---|---|---|
| All DPPs (n = 111) | |||||
| Homo sapiens background | |||||
| GO:0003779: actin binding | 13.0 | 1.6e−13 | 3e−11 | 3.04e−11 | 2e−12 |
| GO:0005515: protein binding | 1.5 | 3.3e−6 | 6e−4 | 3.19e−4 | 4.2e−5 |
| GO:0044822: poly(A) RNA binding* | 3.0 | 2e−4 | 0.04 | 0.012 | 0.002 |
| GO:0098641: cadherin binding involved in cell-cell adhesion | 5.8 | 4e−4 | 0.07 | 0.019 | 0.005 |
| GO:0005198: structural molecule activity | 6.0 | 0.001 | 0.18 | 0.038 | 0.010 |
| GO:0008092: cytoskeletal protein binding | 17.6 | 0.001 | 0.24 | 0.044 | 0.020 |
| GO:0030507: spectrin binding | 24.3 | 0.006 | 0.70 | 0.160 | 0.080 |
| GO:0005516: calmodulin binding | 5.6 | 0.010 | 0.89 | 0.240 | 0.130 |
| GO:0005200: structural constituent of cytoskeleton* | 7.7 | 0.010 | 0.94 | 0.260 | 0.160 |
| GO:0017124: SH3 domain binding | 7.1 | 0.020 | 0.96 | 0.290 | 0.200 |
| GO:0005070: SH3/SH2 adaptor activity | 11.3 | 0.030 | 0.99 | 0.380 | 0.290 |
| GO:0034604: pyruvate dehydrogenase (NAD+) activity* | 52.8 | 0.040 | 1.00 | 0.440 | 0.370 |
| GO:0051371: muscle α-actinin binding | 46.9 | 0.040 | 1.00 | 0.450 | 0.400 |
| GO:0051117: ATPase binding | 8.6 | 0.040 | 1.00 | 0.470 | 0.440 |
| Sus scrofa background | |||||
| GO:0044822: poly(A) RNA binding | 3.5 | 0.002 | 0.18 | 0.180 | 0.030 |
| GO:0005200: structural constituent of cytoskeleton | 15.7 | 0.010 | 0.64 | 0.400 | 0.140 |
| GO:0034604: pyruvate dehydrogenase (NAD+) activity | 102.8 | 0.020 | 0.73 | 0.350 | 0.170 |
| Decreased DPPs (n = 67) | |||||
| Homo sapiens background | |||||
| GO:0003779: actin binding | 13.0 | 7e−9 | 1e−6 | 1.06e−6 | 8.6e−8 |
| GO:0005515: protein binding | 1.5 | 1e−4 | 0.02 | 0.010 | 0.002 |
| GO:0044822: poly(A) RNA binding* | 3.5 | 4e−4 | 0.05 | 0.018 | 0.005 |
| GO:0098641: cadherin binding involved in cell-cell adhesion | 6.8 | 0.002 | 0.21 | 0.050 | 0.001 |
| GO:0005198: structural molecule activity | 6.7 | 0.006 | 0.59 | 0.160 | 0.070 |
| GO:0008092: cytoskeletal protein binding | 20.7 | 0.008 | 0.73 | 0.190 | 0.100 |
| GO:0005516: calmodulin binding | 7.0 | 0.010 | 0.93 | 0.320 | 0.190 |
| GO:0051117: ATPase binding | 13.4 | 0.020 | 0.95 | 0.310 | 0.210 |
| GO:0034604: pyruvate dehydrogenase (NAD+) activity* | 82.8 | 0.020 | 0.97 | 0.320 | 0.240 |
| Sus scrofa background | |||||
| GO:0044822: poly(A) RNA binding | 4.5 | 0.0020 | 0.12 | 0.120 | 0.027 |
| GO:0034604: pyruvate dehydrogenase (NAD+) activity | 169.0 | 0.010 | 0.39 | 0.220 | 0.100 |
| Increased DPPs (n = 44) | |||||
| Homo sapiens background | |||||
| GO:0003779: actin binding | 15.00 | 4.48e−7 | 3.41e−5 | 3.41e−5 | 4.72e−6 |
| GO:0005515: protein binding | 1.48 | 0.005 | 0.31 | 0.17 | 0.05 |
| Term | Fold Enrichment | P Value | Bonferroni | Benjamini | False Discovery Rate |
|---|---|---|---|---|---|
| All DPPs | |||||
| Homo sapiens background | |||||
| hsa04530: tight junction | 7.4 | 0.004 | 0.32 | 0.32 | 0.04 |
| hsa04520: adherens junction | 11.4 | 0.005 | 0.36 | 0.20 | 0.05 |
| hsa00620: pyruvate metabolism* | 15.2 | 0.020 | 0.78 | 0.40 | 0.15 |
| hsa00010: glycolysis/gluconeogenesis* | 9.1 | 0.040 | 0.98 | 0.64 | 0.36 |
| hsa04020: Ca2+ signaling pathway* | 4.5 | 0.050 | 0.99 | 0.66 | 0.45 |
| Sus scrofa background | |||||
| ssc00620: pyruvate metabolism | 20.3 | 0.009 | 0.55 | 0.55 | 0.09 |
| ssc00010: glycolysis/gluconeogenesis | 13.6 | 0.020 | 0.82 | 0.57 | 0.18 |
| ssc04020: calcium signaling pathway | 5.6 | 0.030 | 0.93 | 0.60 | 0.28 |
| ssc05414: dilated cardiomyopathy | 9.1 | 0.040 | 0.97 | 0.60 | 0.35 |
| Decreased DPPs | |||||
| Homo sapiens background | |||||
| hsa04520: adherens junction | 12.2 | 0.020 | 0.84 | 0.84 | 0.21 |
| hsa05414: dilated cardiomyopathy* | 10.3 | 0.030 | 0.92 | 0.72 | 0.28 |
| Sus scrofa background | |||||
| ssc05414: dilated cardiomyopathy | 12.7 | 0.020 | 0.79 | 0.79 | 0.19 |
Phosphopeptide motif discovery.
Enriched sequence motifs were identified using either the ipi.HUMAN.fasta (IHF) database or the iTRAQ LC-MS/MS generated phosphopeptide (iLM) list of this study as background. Table 3 shows the motifs identified, the number of hits observed per data set, the fold increase, and the potential kinases that recognize the motifs. The (..SP..), (..R..S..), and (..S…S..) motifs were observed when the entire DPP data set was used independent of background database, but motifs (..S.S..) and (..S.T..) were only observed in the iLM background database. An analysis of the motifs after separation of the DPPs into increased and decreased groups identified the motif (..SP..) for the increased DPP group regardless of the background data set. The decreased DPP data set identified only the (..S.S..) motif using the iLM data set as the background and the (..S.S..) and (..R..S..) motifs when the IHF background was used. The more detailed position-weighted matrixes of this data are shown in Supplemental Fig. S1.
| Motif
|
Increased DPPs (n = 44) |
Decreased DPPs (n = 67) |
|||||
|---|---|---|---|---|---|---|---|
| Hits | Fold increase | Hits | Fold increase | Hits | Fold increase | Potential Kinases | |
| Background database: ipi.Human.fasta | |||||||
| ..SP.. | 46 | 2.87 | 31 | 4.28 | CDKs, MAPKs, JNKs | ||
| ..S…S.. | 44 | 2.51 | MAPKKK | ||||
| ..R..S.. | 42 | 2.76 | 31 | 3.32 | PKA, PKC, AKT, ROCK | ||
| ..S.S.. | 35 | 2.64 | TGFBR1 | ||||
| Background database: iTRAQ LC-MS/MS phosphopeptides | |||||||
| ..SP.. | 33 | 12.24 | 31 | 18.80 | CDKs, MAPKs, JNKs | ||
| …S.T… | 24 | 16.48 | SGK1 | ||||
| ..R..S… | 21 | 3.63 | PKA, PKC, AKT, ROCK | ||||
| ..S.S.. | 58 | 26.34 | 41 | 30.35 | TGFBR1 | ||
| ..S…S.. | 25 | 5.83 | MAPKKK | ||||
Protein-protein interaction network.
To explore the functional connectivity between the phosphoproteins, STRING software was used to construct a protein-protein interaction network based on an edge confidence of ≥0.4 (i.e., medium to high confidence) (Fig. 3A). All 86 phosphoproteins (nodes) were analyzed, and 62 pairwise interactions were identified. Not all phosphoproteins possessed identifiable associations within this data set in that 39 of the phosphoproteins were unlinked (Fig. 3B). In Fig. 3B, the line thickness indicates the strength of data supporting the interaction between nodes and nodes with red borders correspond to increased DPPs, the black-bordered nodes correspond to decreased DPPs, the DPPs lettered green are phosphoproteins containing multiple potential phosphosites, and the nodes with green borders are phosphoproteins that have phosphosites in the increased and decreased data sets.
Fig. 3.A: protein-protein interaction network among phosphoproteins. The line thickness represents the supported confidence (correlation coefficient) between nodes. Nodes with red and black borders are phosphoproteins with increased and decreased phosphorylated sites in the I/R group compared with the control group, respectively. The green-lettered phosphoproteins contain multiple phosphopeptide sites, and the phosphoproteins with green borders have multiple phosphorylation sites with both increased and decreased phosphorylation states. The grayed-in phosphoproteins were confirmed by immunoblot analysis. The majority of the phosphoproteins (unencapsulated) have roles in cell junctions. The phosphoproteins encircled in purple have roles in RNA processing, and the phosphoproteins encircled in blue have roles in energy production. B: 39 of the 86 altered phosphoproteins had no associative network identified based on this data set.
Analysis of the data set using KEGG revealed that the majority of the phosphoproteins (Fig. 3A) not encircled were involved in cell-junction communication functions; the two groups encircled were involved in RNA processing (purple) and energy metabolism (blue).
Immunoblot analysis.
Western blots of four antibodies previously shown to work in pigs confirmed the LC-MS/MS data. Figures 4A and 5A show immunoblots representing antibodies to total PDH, p-PDH (Ser293), phospholamban (PLN), and p-PLN (Ser16). PLN and PDH E1α mapped to the cardiac muscle contraction (KEGG pathway: map04260) and glycolysis/gluconeogenesis (KEGG pathway: map00010) pathways, respectively. In each case, phosphorylation in the I/R samples displayed an approximately four- to fivefold decrease at the serine phosphorylation site for the I/R group as predicted by the LC-MS/MS data. Figures 4B and 5B show the interactions/pathways involving PLN or PDH E1α and other altered phosphoproteins identified in this data set, respectively.
Fig. 4.A: representative blots for expression profiles of phospholamban (PLN) and phosphorylated (p-)PLN (Ser16) comparing control and I/R treatment. Phosphorylation levels were normalized to total levels. Values are means ± SE; n = 3 per group. All experiments were performed in duplicate. *P < 0.01. B: illustration of the cardiac muscle contraction pathway. *Highlights phosphoproteins identified in this study as significantly (de)phosphorylated. TNNI1, troponin I; MYBPC3, myosin-binding protein-C; MYH7, myosin 7.
Fig. 5.A: representative blots for expression profiles of total pyruvate dehydrogenase (PDH) and p-PDH (Ser293) comparing control and I/R treatment. Phosphorylation levels were normalized to total levels. Values are means ± SE; n = 3 per group. All experiments were performed in duplicate. *P < 0.01. B: illustration of acetyl-CoA synthesis pathways. *Highlights phosphopeptides identified in this study as significantly (de)phosphorylated. DLAT, dihydrolipoamide S-acetyltransferase; DLD, dihydrolipoamide dehydrogenase; PDHX, E3-binding protein; ACSS2, acetyl-CoA synthetase, PDK, pyruvate dehydrogenase kinases; PDP, PDH phosphatase; DCA, dichloroacetate.
DISCUSSION
Our study provides an extensive cataloguing of the cardiac phosphoproteomic signature in response to I/R in vivo. We performed the study in a controlled juvenile porcine model, which produces limited individual variability, particularly compared with prior phosphoproteomic profiling in human heart failure (81). The porcine model is a widely used model in cardiovascular research because the heart size, architecture, and arterial anatomy are similar to humans (15, 91, 110). Also, in addition to the morphological similarities, the porcine heart resembles the temporal and spatial development of myocardial infarction observed in the human heart (33) and provides ample tissue for performance of multiple assays. Furthermore, we have previously documented both functional and metabolic abnormalities induced by this I/R protocol (20, 44) in these pigs. Ten minutes of total coronary artery occlusion in this model reduces systolic and diastolic performance and markedly depresses high-energy phosphate stores. Thus, we hypothesized that these marked changes in both phosphocreatine and ATP would promote alterations in phosphorylation of various peptides. The protocol revealed the phosphorylation state of peptides in the heart during the functional and metabolic state after 2 h of reperfusion. Overall, we identified 1,896 peptide phosphorylation sites; 111 of these on 86 proteins showed differential phosphorylation, meeting our statistical requirements according to condition. Conservation of the predicted phosphopeptide sites was confirmed for all but seven compared with the human orthologous protein. Multiple phosphorylation sites within a protein altered in response to I/R were observed for 15 of the proteins. We produced this extensive list despite limited availability of data for porcine genomic and protein sequences.
Analysis of the DPPs using the KEGG pathway database demonstrated that the largest category of proteins identified was involved in cell junction functions (Fig. 3A). Cell junction proteins create integral connections that occur between endothelial and epicardial cells regulating the anchoring or transport between cells and cells or between cells and the matrix (70), and I/R has been demonstrated to alter cell junctions, resulting in significant alterations in the structural integrity, cell-cell electrical uncoupling, and functional recovery (10, 32, 93). Cell junction communications are regulated by signaling molecules, such as kinases, phosphatases, and GTPases, which are represented in our observed data set. For example, Ca2+/calmodulin-dependent protein kinase type II (CAMK2), of which CAMK2G is a member, contributes to controlling the interactions between myosin and cardiac myosin-binding protein-C3 regulating force generation in the myocardium (7); additionally, it phosphorylates PLN on Thr17, which stimulates Ca2+ pump activity by the sarcoplasmic reticulum (14). Kinases and phosphatases, too, are regulated by phosphorylation, thereby affecting downstream signaling cascades, and have been shown to affect functional outcomes after I/R injury (30, 109), making them targets of interest in therapeutic developments.
Two additional categories identified based on KEGG pathway analysis were RNA processing and energy metabolism. RNA processing generates a mature mRNA or functional tRNA or rRNA from a pre-RNA transcript. One of the steps in RNA processing uses spliceosomes, which are complexes composed of small nuclear RNAs and assorted proteins involved in RNA splicing, a process that >95% of mRNAs undergo (99). Aberrant splicing has been shown to be the cause and the consequence of disease or injury (100). Missplicing of CAMK-δ and several sarcoplasmic genes has been observed in ischemic cardiomyopathy (50) and dilated cardiomyopathy (17). Therefore, identification of several spliceosome-associated proteins suggests that stress may affect the downstream expression of the correct isoform integral to cardiac structure and function. The next category included proteins involved in energy metabolism. This is not surprising because, during ischemia, there is a shift in cardiac metabolism from fatty acid oxidation to glycolysis, and several of the observed phosphoproteins are involved in pathways that use alternative energy substrates, such as pyruvate or acetate. The PDH complex activation has been shown to protect against ischemic injury by modulating the ischemia-induced AMP-activated protein kinase (AMPK) signaling pathway (90); however, the reciprocal occurs, as AMPK (79) also plays a role in the activation of PDH. The connectivity of the pathways is on display, as AMPK is a critical energy sensor altering the AMP-to-ATP ratio based on the cellular environment. One of its principle modes of activation is phosphorylation by CAMK (102), as discussed above in reference to cell junctions. The protein interaction network (Fig. 3A) yields insight into the complex and diverse pathways affected by I/R injury.
A common thread shared between the categories involves Ca2+ metabolism. Ca2+ gates and promotes transjunctional interactions (47), stimulates enzymes of the tricarboxylic acid cycle involved in ATP production (18), and mediates proteins involved in regulating spliceosomal complexes (57) and muscle contraction (40). Additionally, Ca2+ overload may be related to postischemic myocardium impairments (43). The two phosphoproteins tested to substantiate the iTRAQ data have publications detailing their involvement in postischemic damage and/or recovery and relationship with Ca2+ homeostasis, supporting their use in verification.
PLN is part of the network regulating sarcomeric function. The cardiac sarcomere is the basic contractile unit of myocytes. Cardiac muscle contraction is modulated by the cyclical interactions of actin and myosin, which, in turn, are modulated by regulatory proteins, such as troponin I, myosin-binding protein-C, and intracellular levels of Ca2+. Immunoblot analysis confirmed PLN (Ser16) as a site of phosphorylation in this study. PLN is a small integral membrane protein that regulates the Ca2+ pump in cardiac and skeletal muscle cells and is phosphorylated at Ser16 by PKA and Thr17 by CAMK2 (60, 85, 96). Phosphorylation of PLN has been shown to be important in regulating the modulation of cardiomyocyte sarcoplasmic reticulum Ca2+ uptake and contractile function (45, 111), and disruption of PLN function can cause dilated cardiomyopathy with refractory congestive heart failure (22, 82). Several studies investigating the functional role of the phosphorylation sites in postischemic recovery have shown reduced contractile recovery in PLN-impaired rodents compared with wild-type rodents, suggesting that phosphorylation of PLN may favor recovery of myocardial relaxation after ischemia (63, 68, 80). Also, phosphorylation at either PLN Ser16 or Thr17 is sufficient to inhibit the sarcoplasmic reticulum pump (27, 97). Therefore, the observation that PLN Ser16 phosphorylation levels were reduced in the I/R group compared with the control group is consistent with that observed by others (96), supporting the data set generated.
Acetyl-CoA is an important molecule in many biochemical reactions, and one of its primary functions is its utilization in the tricarboxylic acid cycle for energy production. Several pathways are available for the production of acetyl-CoA, such as pyruvate metabolism, fatty acid oxidation, or acetate/acetyl-CoA metabolism. One pathway involves the PDH complex, which decarboxylates pyruvate to form acetyl-CoA before entry into the tricarboxylic acid cycle. The PDH complex comprises three catalytic enzymes: PDH (E1), dihydrolipoamide S-acetyltransferase (DLAT or E2), and dihydrolipoamide dehydrogenase (DLD or E3); two regulatory subunits, E1 kinase and E1 phosphatase; and a noncatalytic subunit, E3 binding protein (PDHX). Two of the six subunits (PDHE1 and DLD) were identified and observed as having altered phosphorylation states by I/R in this study. The porcine PDH E1α-subunit within the complex possesses three phosphorylation sites, all with high homology to the human sequence (49, 89). The Ser293 phosphorylation site demonstrates the highest affinity for phosphate among the three, resulting in enzyme inhibition (29, 51, 84, 107). The PDH complex is the rate-limiting enzyme for glucose oxidation; several studies have reported an increase in the inactive (phosphorylated) PDH form during the early phase of reperfusion (10-15 min) followed by decreased phosphorylation to normal or below normal levels (48, 72). Additionally, stimulation of PDH with dichloroacetate, which decreases Ser293 phosphorylation, can improve cardiac efficiency and recovery of contractile function in the postischemic heart (6, 87). Also of interest is the metabolic shift from free fatty acid oxidation to glycolysis during an ischemic event, and, although upon reperfusion fatty acid oxidation resumes, glucose utilization remains increased compared with the normal myocardium (58, 64). The need for the increased glucose utilization is unclear, but the need to restore ion homeostasis during early reperfusion has been suggested (43). Increased levels of Ca2+ have been reported during ischemia and early perfusion, and high Ca2+ activates PDH phosphatase, which, in turn, activates PDH (24, 88). Jeremy et al. (43) reported on the relationship between Ca2+ overload and I/R injury and the importance of glycolysis in the restoration of Ca2+ homeostasis and myocardium functional recovery postischemia. Ca2+-triggered PDH dephosphorylation results in NADH production (26), thereby affecting oxidative phosphorylation. Our immunoblots targeting both total PDH E1α and p-PDH E1α (Ser293) observed decreased phosphorylation similar to that reported in the literature for PDH after prolonged reperfusion. The immunoblots also confirmed the phosphorylation changes detected by our iTRAQ methodology.
Thus, both immunoblot data and our present techniques showed that I/R decreased phosphorylation at the PDH E1 site, which should lead to enzyme activation. In contrast, previous flux experiments performed in these pigs in vivo demonstrated reduced flux through PDH just before tissue sampling for phosphorylation status (20). The physiological implications of this response require clarification. Conceivably, the Ser293 phosphorylation state change may occur in response to flux rather than the inverse during reperfusion.
Proteins with previously unidentified links to I/R involvement were also observed. For example, the DLD phosphoprotein has a predicted phosphoserine at position 502 that is conserved between S. scrofa and H. sapiens. DLD is a component of the PDH complex, and phosphorylation of DLD is of particular interest because mutations yielding deficiencies or structural alterations of this component cause human disease (3, 4). DLD, the E3 component of the PDH complex, is a flavoprotein disulphide oxioreductase, converting dihydrolipoic acid and NAD+ into lipoic acid and NADH and has been noted to play a role in regulating activity of the complex (56). A literature search found that DLD regulation involved primarily tyrosine phosphorylation events (56, 65); therefore, this study would be the first to predict a previously undescribed regulatory site in this complex.
Another example is acetyl-CoA synthetase, an enzyme used in acetate to acetyl-CoA production. This study identified a conserved Ser263 site between pigs and humans that displayed increased phosphorylation in I/R samples. Presently, there is no literature yielding insights into the role of phosphorylation on this enzyme.
The phosphopeptide sequences were analyzed for kinase/phosphatase recognition motifs as a means of understanding which signaling pathways were implicated in altering phosphorylation homeostasis. Analysis of the phosphopeptide sites recognized several motifs: (R..S), arginine-directed serine phosphorylation; (..SP..), proline-directed serine phosphorylation; and (..S…S..), (..S.S..), and (..S.T..). Proline-directed serine phosphorylations are mediated by enzymes such as cyclin-dependent protein kinases, MAPKs, and JNKs (16, 73), and the majority of the proline-directed sites occurred in the increased DPPs. The arginine-directed kinases include CAMK, PKA, PKC, Akt, and Rho-kinase 1 (2, 73, 74, 76) and occurred predominantly in the decreased DPPs. The (..S.S..) motif, also predominantly located in the decreased DPPs, is recognized by transforming growth factor-β type I receptor kinase (103). The (..S…S..) motif is recognized by MAPKKKs and was only identified when the entire DPP data set was used, whereas (..S.T..) was only identified for the entire DPP data set based on the iLM background. In contrast, enzymes that reverse the phosphorylation process were also at work and included phosphatase 2A and calcineurin, but their substrate specificity has not been well defined (41, 78). Each of these kinase/phosphatase enzymes plays important roles in cellular responses, such as growth and development, transcriptional regulation, and stress responses (8, 38, 42, 94); therefore, the identification of previously unknown substrates could further elucidate pathways and mechanisms involved in I/R as well as offer potential therapeutic targets in alleviating I/R damage.
Limitations.
The iTRAQ methodology for identifying quantitative changes in phosphopeptides of different samples is a powerful tool. However, there are limitations to consider, including 1) the loss of sample during processing; 2) the potential for multiple phosphorylation sites within a peptide can confound identifying the precise modification position; 3) the phosphopeptide enrichment is not 100% specific to phosphopeptides, as it uses the charged stationary phase to trap the phosphate moiety, which can be mimicked by other amino acid structures; 4) targets with low stoichiometry of phosphorylation can be missed; and 5) the potential to underestimate the fold change (compression effect). Additionally, to reassert, this study profiled the changes that occurred because of phosphorylation events affecting the proteome as a whole. Therefore, changes in phosphorylation levels attributable to changes in total protein levels were not detected here and cannot be ruled out as an explanation for some of the DPPs observed.
Conclusions.
Our study used iTRAQ technology to perform a quantitative phosphoproteomic analysis to determine the response to I/R in vivo. This technique identified traditional as well as novel proteins that underwent changes in phosphorylation with these conditions. Many of these sites do not have antibodies developed for detection and would therefore not be considered or evaluated using traditional immunoblot technology. Thus, the present study expands the repertoire of proteins considered to play a role in response in vivo.
GRANTS
This work was supported by National Heart, Lung, and Blood Institute Grant HL-60666 (to M. Portman).
DISCLOSURES
No conflicts of interest, financial or otherwise, are declared by the authors.
AUTHOR CONTRIBUTIONS
D.R.L., M. Kang, M. Kajimoto, S.P., and H.B. performed experiments; D.R.L., S.P., and H.B. analyzed data; D.R.L. interpreted results of experiments; D.R.L. and M. Kang prepared figures; D.R.L. drafted manuscript; D.R.L. and M.A.P. edited and revised manuscript; D.R.L., L.P.-T., and M.A.P. approved final version of manuscript; L.P.-T. and M.A.P. conceived and designed research.
ACKNOWLEDGMENTS
A portion of the research was performed using the Environmental Molecular Sciences Laboratory, a national scientific user facility sponsored by the Department of Energy's Office of Biological and Environmental Research and located at Pacific Northwest National Laboratory.
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AUTHOR NOTES
Supplemental data
- Phosphoproteins_and_their_phosphopeptide_sequence.xlsx (24.85 kb)
- Phosphoprotiens_Quantification_Table.xlsx (679.44 kb)
- Position_weighted_matrices.docx (1.91 MB)
