Using systems biology approaches to understand cardiac inflammation and extracellular matrix remodeling in the setting of myocardial infarction

Network topology analysis of essential genes interactome of Helicobacter pylori to explore novel therapeutic targets

The Helicobacter pylori chronic colonization produces a wide range of gastric diseases in the gastric mucosa by abetting inflammation. Amidst coevolution and reorganization of its metabolism with humans, it has become difficult still imperative to understand and prevent its growth. This study focus to explore functional insights into identification of hub proteins/genes by aggregating the behavior of genes connected in a protein-protein interaction (PPI) network. We have constructed a PPI network of 123 essential genes along with 1213 interactions in H. pylori 26695. The degree and other centrality measures analysis assist in identifying the important hub nodes, which are top-ranked proteins. A total of nine proteins (recA, guaA, dnaK, rpsB, rplQ, rpmA, rpmC, rpmF, and rpsE) were obtained with high degree (k), betweenness centrality (BC) value. Gene ontology analysis reveals 8, 5 and 3 GO terms correspond to biological processes, cellular components and molecular function respectively. Gene complexes of hypothetical proteins (HPs) were related to aminoacyl-tRNA biosynthesis, biosynthesis of secondary metabolites, bacterial secretion system and protein export. The MCODE analysis revealed that protein from module M1, M3 and M6 include the proteins which have highest degree and BC values. It is noteworthy to mention that the bifunctional GMP synthase/glutamine amidotransferase protein (guaA), molecular chaperon (dnaK), recombinase A (recA) constitute as hub proteins. As a result, these genes are considered as network hub nodes that might be used as therapeutic targets. Our analysis affords a detailed understanding of the molecular process and pathways regulated by the essential genes in H. pylori 26695.

Network Analysis Reveals a Distinct Axis of Macrophage Activation in Response to Conflicting Inflammatory Cues

Macrophages are subject to a wide range of cytokine and pathogen signals in vivo, which contribute to differential activation and modulation of inflammation. Understanding the response to multiple, often-conflicting cues that macrophages experience requires a network perspective. In this study, we integrate data from literature curation and mRNA expression profiles obtained from wild type C57/BL6J mice macrophages to develop a large-scale computational model of the macrophage signaling network. In response to stimulation across all pairs of nine cytokine inputs, the model predicted activation along the classic M1-M2 polarization axis but also a second axis of macrophage activation that distinguishes unstimulated macrophages from a mixed phenotype induced by conflicting cues. Along this second axis, combinations of conflicting stimuli, IL-4 with LPS, IFN-γ, IFN-β, or TNF-α, produced mutual inhibition of several signaling pathways, e.g., NF-κB and STAT6, but also mutual activation of the PI3K signaling module. In response to combined IFN-γ and IL-4, the model predicted genes whose expression was mutually inhibited, e.g., iNOS or Nos2 and Arg1, or mutually enhanced, e.g., Il4rα and Socs1, validated by independent experimental data. Knockdown simulations further predicted network mechanisms underlying functional cross-talk, such as mutual STAT3/STAT6-mediated enhancement of Il4rα expression. In summary, the computational model predicts that network cross-talk mediates a broadened spectrum of macrophage activation in response to mixed pro- and anti-inflammatory cytokine cues, making it useful for modeling in vivo scenarios.

Construction and Analysis of Protein-Protein Interaction Network of Heroin Use Disorder

Heroin use disorder (HUD) is a complex disease resulting from interactions among genetic and other factors (e.g., environmental factors). The mechanism of HUD development remains unknown. Newly developed network medicine tools provide a platform for exploring complex diseases at the system level. This study proposes that protein–protein interactions (PPIs), particularly those among proteins encoded by casual or susceptibility genes, are extremely crucial for HUD development. The giant component of our constructed PPI network comprised 111 nodes with 553 edges, including 16 proteins with large degree (k) or high betweenness centrality (BC), which were further identified as the backbone of the network. JUN with the largest degree was suggested to be central to the PPI network associated with HUD. Moreover, PCK1 with the highest BC and MAPK14 with the secondary largest degree and 9^th highest BC might be involved in the development HUD and other substance diseases.

Matrix Signaling Subsequent to a Myocardial Infarction: A Proteomic Profile of Tissue Factor Microparticles

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The occurrence of an MI activates production of TFMPs.

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We induced an MI in Yucatan miniswine and collected plasma samples over a 6-month period post-MI.

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Experimental groups consisted of infarcted but untreated animals and infarcted animals treated with CRT plus β-blocker.

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Using proteomic profiling, we confirm the heterogeneity of TFMP protein content with respect to physiological status of the host temporally.

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Spatially, the contents of the TFMPs provided information about multiple entities supplemental to what we obtained from assessing a set of 8 currently used cardiac biomarkers.

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The results from this study support recommending TFMP protein content profiling be used prospectively as a viable investigative methodology for chronic ischemic cardiomyopathy to help improve our understanding of β-adrenergic receptor signaling after an MI.

This study investigated the release and proteomic profile of tissue factor microparticles (TFMPs) prospectively (up to 6 months) following a myocardial infarction (MI) in a chronic porcine model to establish their utility in tracking cellular level activities that predict physiologic outcomes. Our animal groups (n = 6 to 8 each) consisted of control, noninfarcted (negative control); infarcted only (positive control); and infarcted animals treated with cardiac resynchronization therapy (CRT) and a β-blocker (BB) (metoprolol succinate). The authors found different protein profiles in TFMPs between the control, infarcted only group, and the CRT + BB treated group with predictive impact on the outward phenotype of pathological remodeling after an MI within and between groups. This novel approach of monitoring cellular level activities by profiling the content of TFMPs has the potential of addressing a shortfall of the current crop of cardiac biomarkers, which is the inability to capture composite molecular changes associated with chronic maladaptive signaling in a spatial and temporal manner.

Myocardial infarction remodeling that progresses to heart failure: a signaling misunderstanding

After myocardial infarction, remodeling of the left ventricle involves a wound-healing orchestra involving a variety of cell types. In order for wound healing to be optimal, appropriate communication must occur; these cells all need to come in at the right time, be activated at the right time in the right amount, and know when to exit at the right time. When this occurs, a new homeostasis is obtained within the infarct, such that infarct scar size and quality are sufficient to maintain left ventricular size and shape. The ideal scenario does not always occur in reality. Often, miscommunication can occur between infarct and remote spaces, across the temporal wound-healing spectrum, and across organs. When miscommunication occurs, adverse remodeling can progress to heart failure. This review discusses current knowledge gaps and recent development of the roles of inflammation and the extracellular matrix in myocardial infarction remodeling. In particular, the macrophage is one cell type that provides direct and indirect regulation of both the inflammatory and scar-forming responses. We summarize current research efforts focused on identifying biomarker indicators that reflect the status of each component of the wound-healing process to better predict outcomes.

miRNA Expression Profile and Effect of Wenxin Granule in Rats with Ligation-Induced Myocardial Infarction

Wenxin Granule (WXKL) is a traditional Chinese medicine used for treatment of myocardial infarction (MI) and arrhythmias. However, the genomic pathological mechanisms of MI and mechanisms of WXKL are largely unknown. This study aims to investigate a comprehensive miRNA expression profile, and the predicted correlation pathways to be targeted by differentially expressed miRNAs in MI, and mechanisms of WXKL from a gene level. MI rat model was established by a coronary artery ligation surgery. miRNA expression microarrays were performed and the data were deposited in Gene Expression Omnibus (GEO number GSE95855). And, pathway analysis was performed by using the DIANA-miRPath v3.0 online tool. The expressions of miR-1, miR-133, Cx43, and Cx45 were detected by quantitative real-time PCR. It was found that 35 differentially expressed miRNAs and 23 predicted pathways, including miR-1, miR-133, and gap junction pathway, are involved in the pathogenesis of MI. And, WXKL increased the expressions of miR-1 and miR-133, while also increased the mRNA levels of Cx43 and Cx45, and, especially, recovered the Cx43/Cx45 ratio near to normal level. The results suggest that regulatory effects on miR-1, miR-133, Cx43, and Cx45 might be a possible mechanism of WXKL in the treatment of MI at the gene level.

Knowledge gaps to understanding cardiac macrophage polarization following myocardial infarction

Following myocardial infarction (MI), macrophages coordinate both pro-inflammatory and reparative responses of the left ventricle (LV) by reacting to and secreting cytokines, chemokines, and growth factors and by stimulating endothelial cells and fibroblasts to modulate neovascularization and scar formation. Healing of the infarcted LV can be divided into three distinct, but overlapping phases: inflammatory, proliferative, and maturation. Macrophages are involved in all phases. Despite macrophages being a major leukocyte cell type in the post-MI LV, how this cell type regulates LV remodeling over the post-MI time continuum is not completely understood. In this review, we summarize the current literature as a foundation to discuss the major knowledge gaps that remain. Defining the post-MI temporal macrophage phenotypes to establish a classification system is the first step in exploring how macrophage phenotypes are regulated, how temporal stimulation and secretion profiles evolve, and how best to modify stimuli to yield predictable cell responses. This article is part of a Special Issue entitled: The role of post-translational protein modifications on heart and vascular metabolism edited by Jason R.B. Dyck & Jan F.C. Glatz.

Temporal neutrophil polarization following myocardial infarction

AIMS

Although macrophage phenotypes have been well studied in the myocardial infarction (MI) setting, this study investigated temporal neutrophil polarization and activation mechanisms.

METHODS AND RESULTS

Neutrophils isolated from the infarcted left ventricle (LV) of mice showed high expression of proinflammatory markers at Day 1 and anti-inflammatory markers at Days 5 and 7 post-MI, indicating distinct neutrophil phenotypes along the post-MI time continuum. Flow cytometry analysis revealed that although proinflammatory N1 neutrophils were always predominant (>80% of total neutrophils at each time point), the percentage of N2 neutrophils increased post-MI from 2.4 ± 0.6% at Day 1 to 18.1 ± 3.0% at Day 7. In vitro, peripheral blood neutrophils were polarized to proinflammatory N1 by lipopolysaccharide and interferon-γ or anti-inflammatory N2 by interleukin-4, indicating high plasticity potential. The in vivo post-MI relevant LV damage-associated molecular patterns (DAMPs) polarized neutrophils to a proinflammatory N1 phenotype by activating toll-like receptor-4. Transforming growth factor-β1 inhibited proinflammatory production in neutrophils. N1 neutrophils positively correlated with infarct wall thinning at Day 7 post-MI, possibly due to high production of matrix metalloproteinases-12 and -25.

CONCLUSION

This study is the first to identify the existence of N1 and N2 neutrophils in the infarct region and reveals that N1 polarization could be mediated by DAMPs.

Nodes with high centrality in protein interaction networks are responsible for driving signaling pathways in diabetic nephropathy

In spite of huge efforts, chronic diseases remain an unresolved problem in medicine. Systems biology could assist to develop more efficient therapies through providing quantitative holistic sights to these complex disorders. In this study, we have re-analyzed a microarray dataset to identify critical signaling pathways related to diabetic nephropathy. GSE1009 dataset was downloaded from Gene Expression Omnibus database and the gene expression profile of glomeruli from diabetic nephropathy patients and those from healthy individuals were compared. The protein-protein interaction network for differentially expressed genes was constructed and enriched. In addition, topology of the network was analyzed to identify the genes with high centrality parameters and then pathway enrichment analysis was performed. We found 49 genes to be variably expressed between the two groups. The network of these genes had few interactions so it was enriched and a network with 137 nodes was constructed. Based on different parameters, 34 nodes were considered to have high centrality in this network. Pathway enrichment analysis with these central genes identified 62 inter-connected signaling pathways related to diabetic nephropathy. Interestingly, the central nodes were more informative for pathway enrichment analysis compared to all network nodes and also 49 differentially expressed genes. In conclusion, we here show that central nodes in protein interaction networks tend to be present in pathways that co-occur in a biological state. Also, this study suggests a computational method for inferring underlying mechanisms of complex disorders from raw high-throughput data.

Transformative Impact of Proteomics on Cardiovascular Health and Disease: A Scientific Statement From the American Heart Association

The year 2014 marked the 20th anniversary of the coining of the term proteomics. The purpose of this scientific statement is to summarize advances over this period that have catalyzed our capacity to address the experimental, translational, and clinical implications of proteomics as applied to cardiovascular health and disease and to evaluate the current status of the field. Key successes that have energized the field are delineated; opportunities for proteomics to drive basic science research, facilitate clinical translation, and establish diagnostic and therapeutic healthcare algorithms are discussed; and challenges that remain to be solved before proteomic technologies can be readily translated from scientific discoveries to meaningful advances in cardiovascular care are addressed. Proteomics is the result of disruptive technologies, namely, mass spectrometry and database searching, which drove protein analysis from 1 protein at a time to protein mixture analyses that enable large-scale analysis of proteins and facilitate paradigm shifts in biological concepts that address important clinical questions. Over the past 20 years, the field of proteomics has matured, yet it is still developing rapidly. The scope of this statement will extend beyond the reaches of a typical review article and offer guidance on the use of next-generation proteomics for future scientific discovery in the basic research laboratory and clinical settings.