ATP-sensitive K+ channel knockout induces cardiac proteome remodeling predictive of heart disease susceptibility

Abstract

Forecasting disease susceptibility requires detection of maladaptive signatures prior to onset of overt symptoms. A case-in-point are cardiac ATP-sensitive K+ (K(ATP)) channelopathies, for which the substrate underlying disease vulnerability remains to be identified. Resolving molecular pathobiology, even for single genetic defects, mandates a systems platform to reliably diagnose disease predisposition. High-throughput proteomic analysis was here integrated with network biology to decode consequences of Kir6.2 K(ATP) channel pore deletion. Differential two-dimensional gel electrophoresis reproducibly resolved >800 protein species from hearts of asymptomatic wild-type and Kir6.2-knockout counterparts. K(ATP) channel ablation remodeled the cardiac proteome, significantly altering 71 protein spots, from which 102 unique identities were assigned following hybrid linear ion trap quadrupole-Orbitrap tandem mass spectrometry. Ontological annotation stratified the K(ATP) channel-dependent protein cohort into a predominant bioenergetic module (63 resolved identities), with additional focused sets representing signaling molecules (6), oxidoreductases (8), chaperones (6), and proteins involved in catabolism (6), cytostructure (8), and transcription and translation (5). Protein interaction mapping, in conjunction with expression level changes, localized a K(ATP) channel-associated subproteome within a nonstochastic scale-free network. Global assessment of the K(ATP) channel deficient environment verified the primary impact on metabolic pathways and revealed overrepresentation of markers associated with cardiovascular disease. Experimental imposition of graded stress precipitated exaggerated structural and functional myocardial defects in the Kir6.2-knockout, decreasing survivorship and validating the forecast of disease susceptibility. Proteomic cartography thus provides an integral view of molecular remodeling in the heart induced by K(ATP) channel deletion, establishing a systems approach that predicts outcome at a presymptomatic stage.

Figure 1

Kir6.2 deletion remodels the ventricular proteome. (A) Adult age and sex-matched wild-type (WT) and Kir6.2-knockout (KO) mice assessed under stress-free conditions by ventricular M-mode echocardiography exhibited no apparent differences in function (solid and dotted yellow lines indicate extent of systolic and diastolic wall motion, respectively), nor were there differences in gross heart morphology or heart to body weight ratio. (B) Silver-stained 2-D gels of left ventricular cytoplasmic protein extracts (100 μg per gel) from WT and KO mice resolved by pH 3–10 IEF, 12.5% SDS-PAGE. Differentially expressed spots are circled and numbered to cross-reference with corresponding protein assignments determined by LTQ-Orbitrap MS/MS analysis of excised tryptic digests. (C) Gel reproducibility was demonstrated by consistent numbers of detected protein species and strong correlation (R² = 0.925) across treatments between average normalized intensities of matching protein spots from WT and KO gels. (D) Example of spot quantification (top), indicating 2-D gel position and 3-D rendering of the quantified spot from all resolved gels (bottom, n = 4 for WT and KO). (E) Densitometric analysis comparing WT to KO revealed that 71 of 804 spots differed (P < 0.05), including 23 up-regulated and 48 down-regulated protein species.

Figure 2

Metabolic remodeling is the primary effect of K_ATP channel deficiency. Proteins assigned by LTQ-Orbitrap MS/MS analysis from significantly altered spots were functionally categorized by Swiss-Prot ontological annotations. The primary association was with metabolic processes, as 63/102 protein assignments encompassed mitochondrial, cytoplasmic, and amino or nucleic acid metabolic functions. Protein names are listed with their Swiss-Prot gene name (for Node Symbol) to locate them in the protein interaction network, and with their corresponding spot numbers from their 2-D gel positions. Protein accession number, Mascot score, number of unique identified peptides, % sequence cov. (coverage), predicted M_r and pI for each protein (following expected post-translational processing, e.g., removal of a known or predicted mitochondrial signal peptide), and fold change (KO versus WT) are indicated. For proteins detected in more than one spot, maximum score and number of unique peptides are reported. Fold change was calculated as described in experimental procedures, and for proteins detected in both increasing and decreasing spots (**), both values are indicated. Complete MS/MS data for all proteins is outlined in Supplementary Table 1 (Supporting Information). (*TrEMBL entry; ** Contains both up- and down-regulated spots; † Node not detected for network analysis by Ingenuity Pathways; ‡ M_r/pI calculated after TargetP 1.1 prediction of mitochondrial localization and signal peptide cleavage site).

Figure 3

Secondary functions associated with K_ATP channel deficiency form an infrastructure supporting metabolism. Ontological categorization indicated that a secondary functional group consisting of the remaining identified proteins (39/102) comprises a number of functions supporting cellular metabolic activity. These proteins function as oxidoreductases, in cytostructure and scaffolding, as stress-related chaperones, or in protein catabolism, signaling regulation, or transcription and translation. Protein names are listed with their Swiss-Prot gene name (for Node Symbol) to locate them in the protein interaction network, and with their corresponding spot numbers from their 2-D gel positions. Protein accession number, Mascot score, number of unique identified peptides, % sequence cov. (coverage), predicted M_r and pI for each protein (following expected post-translational processing, for example, removal of a mitochondrial signal peptide), and fold change (KO versus WT) are indicated. For proteins detected in more than one spot, maximum score and number of unique peptides are reported. Fold change was calculated as described in experimental procedures, and for proteins detected in both increasing and decreasing spots (**), both values are indicated. Complete MS/MS data for all proteins is outlined in Supplementary Table 1 (Supporting Information). (**Contains both up- and down-regulated spots; † Node not detected for network analysis by Ingenuity Pathways; ‡ M_r/pI calculated after TargetP 1.1 prediction of mitochondrial localization and signal peptide cleavage site).

Figure 4

Network analysis of the Kir6.2-dependent proteome. (A) The distribution of Swiss-Prot annotated primary ontological functions of altered proteins (Proteomic Analysis) carry through to the expanded protein interaction network (Network Analysis), with metabolism predominant in both. (B) Differentially expressed proteins of the Kir6.2-dependent subproteome submitted to Ingenuity Pathways Analysis as focus nodes generated a 221 protein interaction network. Nodes are listed by Swiss-Prot gene designations, with the exception of nodes representing protein families. Node color corresponds to ontological function (from A), while node shape (legend) indicates directionality of expression level change for proteins characterized during proteomic analysis. (C) Network degree distribution, (P[k]) versus degree (k), followed a power law distribution indicating nonstochastic scale-free network architecture characteristic of biological networks.

Figure 5

Biological processes linked to the K_ATP channel-dependent protein interaction network. (A) K_ATP channel-dependent protein interaction network was interrogated with the Cytoscape module BiNGO to identify network-linked Gene Ontology (GO) biological processes, including evidence of overrepresentation. The derived GO network consisted of 962 processes (nodes), of which 55 were significantly overrepresented (colored nodes, P < 0.001), with nodes connected by GO hierarchical relationships. Node size is proportional to the number of network proteins annotated to that biological process, while node shading represents a 5-log gradient of significant, false discovery rate-corrected P-values, with gray nodes not significantly overrepresented. (B) Hierarchical layout of overrepresented biological processes from panel A, with node size/color retained and identities indicated. Of note, all 55 colored nodes involve metabolic processes. Functional interdependencies within the GO hierarchy translated into significant overrepresentation by entire hierarchical branches, with the most significant nodes furthest down the hierarchy offering the strongest interpretive explanation. Processes linked to “Glycolysis”, the “TCA cycle”, “Fatty acid metabolism” and “Protein catabolism” demonstrated the greatest overrepresentation.

Figure 6

Predicted outcome of K_ATP channel deficit and functional validation. (A) “Cardiovascular disease” was significantly overrepresented as a consequence of K_ATP channel deficit based on Ingenuity Pathways Analysis of both the K_ATP channel-dependent altered proteins (Proteome) and their derived protein network (Interactome). (B–D) Functional confirmation of predicted outcome. While wild-type (WT) and Kir6.2-knockout (KO) counterparts exhibited no difference in structural or functional parameters in the absence of imposed stress, progressively greater challenge by mild (chronic repetitive aquatic exercise), moderate (deoxycorticosterone acetate/salt-induced hypertension) or severe (transverse aortic constriction) stress led to aggravated increases in left ventricular (LV) mass (B; *P < 0.05) and decreases in LV fractional shortening, FS (C; *P < 0.05, **P < 0.01), with K_ATP channel deletion ultimately leading to decreasing post-stress survival (D; **P < 0.01 versus WT).