Identification of Potential Gene Interactions in Heart Failure Caused by Idiopathic Dilated Cardiomyopathy

Identification of common mechanisms and biomarkers of atrial fibrillation and heart failure based on machine learning

AIMS

Atrial fibrillation (AF) is the most common arrhythmia. Heart failure (HF) is a disease caused by heart dysfunction. The prevalence of AF and HF were progressively increasing over time. The co-existence of AF and HF presents a significant therapeutic challenge. In order to provide new ideas for the diagnosis of AF and HF, it is necessary to carry out biomarker related studies.

METHODS AND RESULTS

The training set and validation set data of AF and HF patient samples were downloaded from the GEO database, 'limma' was used to compare the differences in gene expression levels between the disease group and the normal group to screen for differentially expressed genes (DEGs). Weighted correlation network analysis (WGCNA) identified the modules with the highest positive correlation with AF and HF. Functional enrichment and PPI network construction of key genes were carried out. Biomarkers were screened by machine learning. The infiltration of immune cells in AF and HF groups was evaluated by R-packet 'CIBERSORT'. The miRNA network was constructed and potential therapeutic agents for biomarker genes were predicted through the drugbank database. Through WGCNA analysis, it was found that the modules most positively correlated with AF and HF were MEturquoise (r = 0.21, P value = 0.09) and MEbrown (r = 0.62, P value = 8e-12), respectively. We screened 25 genes that were highly correlated with both AF and HF. Lasso regression analysis results showed 7 and 20 core genes in AF and HF groups, respectively. The top 20 important genes in AF and HF groups were obtained as core genes by RF model analysis. Four biomarkers were obtained after the intersection of core genes in four groups, namely, GLUL, NCF2, S100A12, and SRGN. The diagnostic efficacy of four genes in AF validation sets was good (AUC: GLUL 0.76, NCF2 0.64, S100A12 0.68, and SRGN 0.76), as well as in the HF validation set (AUC: GLUL 0.76, NCF2 0.84, S100A12 0.92, and SRGN 0.68). The highest correlation with neutrophils was observed for GLUL, NCF2, and S100A12, while SRGN exhibited the strongest correlation with T cells CD4 memory resting in the AF group. GLUL, NCF2, S100A12, and SRGN were most associated with neutrophils in the HF group. A total of 101 miRNAs were predicted by four genes, and GLUL, NCF2, and S100A12 predicted a total of 10 potential therapeutic agents.

CONCLUSIONS

We identified four biological markers that are highly correlated with AF and HF, namely, GLUL, NCF2, S100A12, and SRGN. Our findings provide theoretical basis for the clinical diagnosis and treatment of AF and HF.

Integrated analysis of single-cell RNA sequencing and bulk RNA data reveals gene regulatory networks and targets in dilated cardiomyopathy

Dilated cardiomyopathy (DCM) is a common cause of heart failure, thromboembolism, arrhythmias, and sudden cardiac death. The quality of life and long-term survival rates of patients with dilated DCM have greatly improved in recent decades. Nevertheless, the clinical prognosis for DCM patients remains unfavorable. The primary driving factors underlying the pathogenesis of DCM remain incompletely understood. The present study aimed to identify driving factors underlying the pathogenesis of DCM from the perspective of gene regulatory networks. Single-cell RNA sequencing data and bulk RNA data were obtained from the Gene Expression Omnibus (GEO) database. Differential gene analysis, single-cell genomics analysis, and functional enrichment analysis were conducted using R software. The construction of Gene Regulatory Networks was performed using Python. We used the pySCENIC method to analyze the single-cell data and identified 401 regulons. Through variance decomposition, we selected 19 regulons that showed significant responsiveness to DCM. Next, we employed the ssGSEA method to assess regulons in two bulk RNA datasets. Significant statistical differences were observed in 9 and 13 regulons in each dataset. By intersecting these differentiated regulons and identifying shared targets that appeared at least twice, we successfully pinpointed three differentially expressed targets across both datasets. In this study, we assessed and identified 19 gene regulatory networks that were responsive to the disease. Furthermore, we validated these networks using two bulk RNA datasets of DCM. The elucidation of dysregulated regulons and targets (CDKN1A, SAT1, ZFP36) enhances the molecular understanding of DCM, aiding in the development of tailored therapies for patients.

RNA sequencing of formalin fixed paraffin-embedded heart tissue provides transcriptomic information about chemotherapy-induced cardiotoxicity

Gene expression of formalin-fixed paraffin-embedded (FFPE) tissue may serve for molecular studies on cardiovascular diseases. Chemotherapeutics, such as doxorubicin (DOX) may cause heart injury, but the mechanisms of these side effects of DOX are not well understood. This study aimed to investigate whether DOX-induced gene expression in archival FFPE heart tissue in experimental rats would correlate with the gene expression in fresh-frozen heart tissue by applying RNA sequencing technology. The results showed RNA from FFPE samples was degraded, resulting in a lower number of uniquely mapped reads. However, DOX-induced differentially expressed genes in FFPE were related to molecular mechanisms of DOX-induced cardiotoxicity, such as inflammation, calcium binding, endothelial dysfunction, senescence, and cardiac hypertrophy signaling. Our data suggest that, despite the limitations, RNA sequencing of archival FFPE heart tissue supports utilizing FFPE tissues from retrospective studies on cardiovascular disorders, including DOX-induced cardiotoxicity.

Integrated bioinformatics analysis for identifying key genes and pathways in female and male patients with dilated cardiomyopathy

Dilated cardiomyopathy (DCM) is a common cause of heart failure, and males are more likely to suffer from DCM than females. This research aimed at exploring possible DCM-associated genes and their latent regulatory effects in female and male patients. WGCNA analysis found that in the yellow module, 341 and 367 key DEGs were identified in females and males, respectively. A total of 22 hub genes in females and 17 hub genes in males were identified from the PPI networks of the key DEGs based on Metascape database. And twelve and eight potential TFs of the key DEGs were also identified in females and males, respectively. Eight miRNAs of 15 key DEGs were screened in both females and males, which may be differentially expressed in females and males. Dual-luciferase reporter assay demonstrated that miR-21-5P could directly target the key gene MATN2. Furthermore, Sex differences in KEGG pathways were identified. Both KOBAS and GSEA analysis identified 19 significantly enriched pathways related to immune response in both females and males, and the TGF-β signaling pathway was exclusively identified in males. Network pharmacology analysis revealed that seven key DEGs were potential targets for the treatment of DCM, of which the OLR1 gene was only identified in males, the expression levels of the seven genes were verified by RT-PCR. The above results could offer a novel understanding of sex differences in key genes and pathways in DCM progression.

Identification of Biomarkers Associated with Heart Failure Caused by Idiopathic Dilated Cardiomyopathy Using WGCNA and Machine Learning Algorithms

Background

The genetic factors and pathogenesis of idiopathic dilated cardiomyopathy-induced heart failure (IDCM-HF) have not been understood thoroughly; there is a lack of specific diagnostic markers and treatment methods for the disease. Hence, we aimed to identify the mechanisms of action at the molecular level and potential molecular markers for this disease.

Methods

Gene expression profiles of IDCM-HF and non-heart failure (NF) specimens were acquired from the database of Gene Expression Omnibus (GEO). We then identified the differentially expressed genes (DEGs) and analyzed their functions and related pathways by using "Metascape". Weighted gene co-expression network analysis (WGCNA) was utilized to search for key module genes. Candidate genes were identified by intersecting the key module genes identified via WGCNA with DEGs and further screened via the support vector machine-recursive feature elimination (SVM-RFE) method and the least absolute shrinkage and selection operator (LASSO) algorithm. At last, the biomarkers were validated and evaluated the diagnostic efficacy by the area under curve (AUC) value and further confirmed the differential expression in the IDCM-HF and NF groups using an external database.

Results

We detected 490 genes exhibiting differential expression between IDCM-HF and NF specimens from the GSE57338 dataset, with most of them being concentrated in the extracellular matrix (ECM) of cells related to biological processes and pathways. After screening, 13 candidate genes were identified. Aquaporin 3 (AQP3) and cytochrome P450 2J2 (CYP2J2) showed high diagnostic efficacy in the GSE57338 and GSE6406 datasets, respectively. In comparison to the NF group, AQP3 was significantly down-regulated in the IDCM-HF group, while CYP2J2 was significantly up-regulated.

Conclusion

As far as we know, this is the first study that combines WGCNA and machine learning algorithms to screen for potential biomarkers of IDCM-HF. Our findings suggest that AQP3 and CYP2J2 could be used as novel diagnostic markers and treatment targets of IDCM-HF.

Bioinformatics prediction of potential mechanisms and biomarkers underlying dilated cardiomyopathy

BACKGROUND

Heart failure is a health burden responsible for high morbidity and mortality worldwide, and dilated cardiomyopathy (DCM) is one of the most common causes of heart failure. DCM is a disease of the heart muscle and is characterized by enlargement and dilation of at least one ventricle alongside impaired contractility with left ventricular ejection fraction < 40%. It is also associated with abnormalities in cytoskeletal proteins, mitochondrial ATP transporter, microvasculature, and fibrosis. However, the pathogenesis and potential biomarkers of DCM remain to be investigated.

AIM

To investigate the candidate genes and pathways involved in DCM patients.

METHODS

Two expression datasets (GSE3585 and GSE5406) were downloaded from the Gene Expression Omnibus database. The differentially expressed genes (DEGs) between the DCM patients and healthy individuals were identified using the R package "linear models for microarray data." The pathways with common DEGs were analyzed via Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene set enrichment analyses. Moreover, a protein-protein interaction network (PPI) was constructed to identify the hub genes and modules. The MicroRNA Database was applied to predict the microRNAs (miRNAs) targeting the hub genes. Additionally, immune cell infiltration in DCM was analyzed using CIBERSORT.

RESULTS

In total, 97 DEGs (47 upregulated and 50 downregulated) were identified. GO analysis showed that the DEGs were mainly enriched in "response to growth factor," "extracellular matrix," and "extracellular matrix structural constituent." KEGG pathway analysis indicated that the DEGs were mainly enriched in "protein digestion and absorption" and "interleukin 17 (IL-17) signaling pathway." The PPI network suggested that collagen type III alpha 1 chain (COL3A1) and COL1A2 contribute to the pathogenesis of DCM. Additionally, visualization of the interactions between miRNAs and the hub genes revealed that hsa-miR-5682 and hsa-miR-4500 interacted with both COL3A1 and COL1A2, and thus these miRNAs might play roles in DCM. Immune cell infiltration analysis revealed that DCM patients had more infiltrated plasma cells and fewer infiltrated B memory cells, T follicular helper cells, and resting dendritic cells.

CONCLUSION

COL1A2 and COL3A1 and their targeting miRNAs, hsa-miR-5682 and hsa-miR-4500, may play critical roles in the pathogenesis of DCM, which are closely related to the IL-17 signaling pathway and acute inflammatory response. These results may provide useful clues for the diagnosis and treatment of DCM.

Exploring Key Genes to Construct a Diagnosis Model of Dilated Cardiomyopathy

Background

Dilated cardiomyopathy (DCM) is characterized by left ventricular dilatation and systolic dysfunction. The pathogenesis and etiologies of DCM remain elusive. This study aims to identify the key genes to construct a genetic diagnosis model of DCM.

Methods

A total of 257 DCM samples from five independent cohorts were enrolled. The Weighted Gene Co-Expression Network Analysis (WGCNA) was performed to identify the key modules associated with DCM. The latent mechanisms and protein-protein interaction network underlying the key modules were further revealed. Subsequently, we developed and validated a LASSO diagnostic model in five independent cohorts.

Results

Two key modules were identified using WGCNA. Novel mechanisms related to the extracellular, mitochondrial matrix or IL-17 signaling pathway were pinpointed, which might significantly influence DCM. Besides, 23 key genes were screened out by combining WGCNA and differential expression analysis. Based on the key genes, a genetic diagnosis model was constructed and validated using five cohorts with excellent AUCs (0.975, 0.954, 0.722, 0.850, 0.988). Finally, significant differences in immune infiltration were observed between the two groups divided by the diagnostic model.

Conclusion

Our study revealed several novel pathways and key genes to provide potential targets and biomarkers for DCM treatment. A key genes’ diagnosis model was built to offer a new tool for diagnosing DCM.

LsrB, the hub of ABC transporters involved in the membrane damage mechanisms of heavy ion irradiation in Escherichia coli

BACKGROUND

Ionizing radiation, especially heavy ion (HI) beams, has been widely used in biology and medicine. However, the mechanism of membrane damage by such radiation remains primarily uncharacterized.

PURPOSE

Transcriptomic profiles of Escherichia coli (E. coli) treated with HI illustrated the response mechanisms of the membrane, mainly ABC transporters, related genes regulated by antibiotics treatment through enrichment analyses of GO and KEGG. The networks of protein-protein interactions indicated that LsrB was the crucial one among the ABC transporters specially regulated by HI through the calculation of plugins MCODE and cytoHubba of Cytoscape. Finally, the expression pattern, GO/KEGG enrichment terms, and the interaction between nine LuxS/AI-2 quorum sensing system members were investigated.

CONCLUSIONS

Above all, results suggested that HI might perform membrane damage through regulated material transport, inhibited LuxS/AI-2 system, finally impeded biofilm formation. This work provides further evidence for the role of ABC transporters, especially LsrB, in membrane damage of E. coli to HI. It will provide new strategies for improving the precise application of HI.

Omics analyses indicate the routes of lignin related metabolites regulated by trypsin during storage of pitaya (Hylocereus undatus)

The storage quality of Hylocereus undatus was significantly improved by trypsin, a novel preservative. The transcriptomic results revealed that antioxidant signal pathways were induced, while lignin catabolic process was impeded by trypsin. In addition, the results of protein-protein interaction (PPI) network networks suggested that flavone 3'-O-methyltransferase 1 (OMT1), ferulic acid 5-hydroxylase 1 (CYP84A1), cellulose synthase isomer (CEV1), and 4-coumarate-CoA ligase 3 (4CL3) act as hubs of peroxidases, lignin related proteins, and proteins involved in the phenylpropanoid metabolism (PLPs) induced by trypsin. Trypsin also regulated the biosynthesis of lignin, chlorogenic acid, and flavonoids. Caffeic acid might be the hub in the metabolic network of the early pathways of phenylpropanoid biosynthesis. It has been hypothesized that trypsin might quickly induce lignin biosynthesis and then up-regulated bioactive metabolites to enhance storage quality of H. undatus.

Troponin T amino acid mutation (ΔK210) knock-in mice as a neonatal dilated cardiomyopathy model

BACKGROUND

Dilated cardiomyopathy (DCM) in children is often associated with poor morbidity and mortality and exhibits distinct pathological entities from those of adult DCM. Owing to the limited number of patients and the lack of a good animal model, the molecular mechanisms underlying pediatric DCM remain poorly understood. The purpose of this study is to establish an animal model of neonatal DCM and identify early progression factors.

METHODS

Cardiac phenotypes and comprehensive gene expression profiles in homozygous ΔK210 knock-in (TNNT2^{ΔK210/ΔK210}) mice were analyzed and compared to TNNT2^+/ΔK210 and wild-type mice at 0 days and 1 week of age.

RESULTS

Immediately after birth, the cardiac weight in TNNT2^{ΔK210/ΔK210} mice was already increased compared to that in TNNT2^+/ΔK210 and wild-type mice. Echocardiographic examination of 0-day-old and 1-week-old TNNT2^{ΔK210/ΔK210} mice revealed similar phenotypes of pediatric DCM. In addition, several genes were significantly upregulated in the ventricular tissues of TNNT2^{ΔK210/ΔK210} mice, and the KEGG PATHWAY analysis revealed several important pathways such as cancer and focal adhesion that might be associated with the pathogenesis and development of DCM.

CONCLUSIONS

TNNT2^{ΔK210/ΔK210} mice have already developed DCM at birth, indicating that they should be an excellent animal model to identify early progression factors of DCM.

IMPACT

TNNT2^{ΔK210/ΔK210} mice are excellent animal model for DCM. TNNT2^{ΔK210/ΔK210} mice are excellent animal model to identify early progression factors of DCM. KEGG PATHWAY analysis revealed that several important pathways such as cancer and focal adhesion might be associated with the pathogenesis and development of neonatal DCM.

Human Hsp90 cochaperones: perspectives on tissue-specific expression and identification of cochaperones with similar in vivo functions

The Hsp90 molecular chaperone is required for the function of hundreds of different cellular proteins. Hsp90 and a cohort of interacting proteins called cochaperones interact with clients in an ATP-dependent cycle. Cochaperone functions include targeting clients to Hsp90, regulating Hsp90 ATPase activity, and/or promoting Hsp90 conformational changes as it progresses through the cycle. Over the last 20 years, the list of cochaperones identified in human cells has grown from the initial six identified in complex with steroid hormone receptors and protein kinases to about fifty different cochaperones found in Hsp90-client complexes. These cochaperones may be placed into three groups based on shared Hsp90 interaction domains. Available evidence indicates that cochaperones vary in client specificity, abundance, and tissue distribution. Many of the cochaperones have critical roles in regulation of cancer and neurodegeneration. A more limited set of cochaperones have cellular functions that may be limited to tissues such as muscle and testis. It is likely that a small set of cochaperones are part of the core Hsp90 machinery required for the folding of a wide range of clients. The presence of more selective cochaperones may allow greater control of Hsp90 activities across different tissues or during development.

Investigation of hub genes and immune status in heart transplant rejection using endomyocardial biopsies

T cell‒mediated rejection (TCMR) and antibody‐mediated rejection (ABMR) are severe post‐transplantation complications for heart transplantation (HTx), whose molecular and immunological pathogenesis remains unclear. In the present study, the mRNA microarray data set GSE124897 containing 645 stable, 52 TCMR and 144 ABMR endomyocardial biopsies was obtained to screen for differentially expressed genes (DEGs) between rejected and stable HTx samples and to investigate immune cell infiltration. Functional enrichment analyses indicated roles of the DEGs primarily in immune‐related mechanisms. Protein‐protein interaction networks were then constructed, and ICAM1, CD44, HLA‐A and HLA‐B were identified as hub genes using the maximal clique centrality method. Immune cell infiltration analysis revealed differences in adaptive and innate immune cell populations between TCMR, ABMR and stable HTx samples. Additionally, hub gene expression levels significantly correlated with the degree and composition of immune cell infiltration in HTx rejection samples. Furthermore, drug‐gene interactions were constructed, and 12 FDA‐approved drugs were predicted to target hub genes. Finally, an external GSE2596 data set was used to validate the expression of the hub genes, and ROC curves indicated all four hub genes had promising diagnostic value for HTx rejection. This study provides a comprehensive perspective of molecular and immunological regulatory mechanisms underlying HTx rejection.

Hub genes and sub-networks of stoma-related genes in Hylocereus undatus through trypsin treatment during storage revealed by transcriptomic analysis

To further investigate the preservation mechanisms of trypsin, the synergistic mechanisms of trypsin and stoma-related genes were evaluated in Hylocereus undatus. Trypsin significantly induced the stoma closure and improved the storage quality of H. undatus. Transcriptomic analyses of H. undatus revealed that important antioxidant signal pathway, such as SREBP signaling pathway, cellular response to H₂ O₂ or cellular response to molecule of bacterial origin, were induced; while responses to water deprivation were impeded by trypsin. These results indicated that trypsin relieved pitaya of pressure of water deprivation and exhibited the protection on pitaya during storage. Furthermore, the analyses of networks of protein-protein interaction suggested that OST1, HK5, AT4G27585, and HIR1 act as hubs of stoma-related proteins induced by trypsin during storage of H. undatus. PRACTICAL APPLICATIONS: Preservation of fruit is becoming increasingly important to the world. Keep the balance of production and scavenging of reactive oxygen species is efficient to improve the storage quality of fruit. Trypsin had a novel superoxide anion scavenging activity and protect fruit cells from cellular injury induced by excess ROS. This article investigates the hub genes and interaction mechanisms of stoma closure induced by trypsin during the storage of H. undatus. The application of trypsin provides a new strategy for the quality control of fruit storage. Trypsin will have a broad market and development potential in the area of food additives.

Transcriptomic analysis reveals hub genes and subnetworks related to ROS metabolism in Hylocereus undatus through novel superoxide scavenger trypsin treatment during storage

BACKGROUND

It was demonstrated in our previous research that trypsin scavenges superoxide anions. In this study, the mechanisms of storage quality improvement by trypsin were evaluated in H. undatus.

RESULTS

Trypsin significantly delayed the weight loss and decreased the levels of ROS and membrane lipid peroxidation. Transcriptome profiles of H. undatus treated with trypsin revealed the pathways and regulatory mechanisms of ROS genes that were up- or downregulated following trypsin treatment by gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses. The current results showed that through the regulation of the expression of hub redox enzymes, especially thioredoxin-related proteins, trypsin can maintain low levels of endogenous active oxygen species, reduce malondialdehyde content and delay fruit aging. In addition, the results of protein-protein interaction networks suggested that the downregulated NAD(P) H and lignin pathways might be the key regulatory mechanisms governed by trypsin.

CONCLUSIONS

Trypsin significantly prolonged the storage life of H. undatus through regulatory on the endogenous ROS metabolism. As a new biopreservative, trypsin is highly efficient, safe and economical. Therefore, trypsin possesses technical feasibility for the quality control of fruit storage.

Global analysis of histone modifications and long-range chromatin interactions revealed the differential cistrome changes and novel transcriptional players in human dilated cardiomyopathy

BACKGROUND

Acetylation and methylation of histones alter the chromatin structure and accessibility that affect transcriptional regulators binding to enhancers and promoters. The binding of transcriptional regulators enables the interaction between enhancers and promoters, thus affecting gene expression. However, our knowledge of these epigenetic alternations in patients with heart failure remains limited.

METHODS AND RESULTS

From the comprehensive analysis of major histone modifications, 3-dimensional chromatin interactions, and transcriptome in left ventricular (LV) tissues from dilated cardiomyopathy (DCM) patients and non-heart failure (NF) donors, differential active enhancer and promoter regions were identified between NF and DCM. Moreover, the genome-wide average promoter signal is significantly lower in DCM than in NF. Super-enhancer (SE) analysis revealed that fewer SEs were found in DCM LVs than in NF ones, and three unique SE-associated genes between NF and DCM were identified. Moreover, SEs are enriched within the genomic region associated with long-range chromatin interactions. The differential enhancer-promoter interactions were observed in the known heart failure gene loci and are correlated with the gene expression levels. Motif analysis identified known cardiac factors and possible novel players for DCM.

CONCLUSIONS

We have established the cistrome of four histone modifications and chromatin interactome for enhancers and promoters in NF and DCM tissues. Differential histone modifications and enhancer-promoter interactions were found in DCM, which were associated with gene expression levels of a subset of disease-associated genes in human heart failure.

Precision medicine in distinct heart failure phenotypes: Focus on clinical epigenetics

Heart failure (HF) management is challenging due to high clinical heterogeneity of this disease which makes patients responding differently to evidence-based standard therapy established by the current reductionist approach. Better understanding of the genetic and epigenetic interactions may clarify molecular signatures underlying maladaptive responses in HF, including metabolic shift, myocardial injury, fibrosis, and mitochondrial dysfunction. DNA methylation, histone modifications and micro-RNA (miRNAs) may be major epigenetic players in the pathogenesis of HF. DNA hypermethylation of the kruppel-like factor 15 (KLF15) gene plays a key role in switching the failing heart from oxidative to glycolytic metabolism. Moreover, hypomethylation at H3K9 promoter level of atrial natriuretic peptide (ANP) and brain natriuretic peptide (BNP) genes also leads to reactivation of fetal genes in man. The role of miRNAs has been investigated in HF patients undergoing heart transplantation, for whom miR-10a, miR-155, miR-31, and miR-92 may be putative useful prognostic biomarkers. Recently, higher RNA methylation levels have been observed in ischemic human hearts, opening the era of "epitranscriptome" in the pathogenesis of HF. Currently, hydralazine, statins, apabetalone, and omega-3 polyunsatured fatty acids (PUFA) are being tested in clinical trials to provide epigenetic-driven therapeutic interventions. Moreover, network-oriented analysis could advance current medical practice by focusing on protein-protein interactions (PPIs) perturbing the "cardiac" interactome. In this review, we provide an epigenetic map of maladaptive responses in HF patients. Furthermore, we propose the "EPi-transgeneratIonal network mOdeling for STratificatiOn of heaRt Morbidity" (EPIKO-STORM), a clinical research strategy offering novel opportunities to stratify the natural history of HF.

Integrated microarray analysis to identify potential biomarkers and therapeutic targets in dilated cardiomyopathy

Dilated cardiomyopathy (DCM) is a primary cardiomyopathy with high mortality. The aim of the present study was to identify the related genes in DCM. The four expression profiles (GSE17800, GSE21610, GSE42955 and GSE79962) downloaded from the Gene Expression Omnibus (GEO) database were analyzed using RankProd and metaMA R packages to identify differentially expressed genes (DEGs). DEGs were uploaded to the Database for Annotation, Visualization and Integrated Discovery (DAVID), for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. A protein-protein interaction (PPI) network of the DEGs was constructed using the STRING database. In addition, hub genes were identified using the Cytoscape plugin cytoHubba. A mouse DCM model, which established via intraperitoneal injection with doxorubicin (DOX), was used to validate the hub genes. A total of 898 DEGs were identified across the four microarrays. Furthermore, GO analysis demonstrated that these DEGs were mainly enriched in cell adhesion, negative regulation of cell proliferation, negative regulation of apoptotic process and potassium ion transport. In addition, KEGG analysis revealed that DEGs were mainly enriched in the ECM-receptor interaction, the p53 signaling pathway, cardiac muscle contraction and the hypoxia-inducible factor signaling pathway. Proenkephalin (PENK), chordin like 1 (CHRDL1), calumenin (CALU), apolipoprotein L1, insulin-like growth factor binding protein 3 (IGFBP3) and ceruloplasmin (CP) were identified as hub genes in the PPI network. Furthermore, the expression levels of PENK, CHRDL1, IGFBP3, CP and CALU in hearts with DCM were validated using a mouse model. In conclusion, the present study identified six hub genes related to DCM. Therefore, the present results may provide a potential mechanism for DCM involving these hub genes, which may serve as biomarkers for screening and diagnosis in the clinic.

Transcriptomic Analysis Reveals Cu/Zn SODs Acting as Hub Genes of SODs in Hylocereus undatus Induced by Trypsin during Storage

It has been revealed by us that superoxide scavenging is a new activity of trypsin. In this study, the synergistic mechanisms of trypsin and superoxide dismutases (SODs) were evaluated in Hylocereus undatus (pitaya). Trypsin significantly improved the storage quality of H. undatus, including weight loss impediment and decrease of cellular injury. The regulatory mechanisms of 16 SOD genes by trypsin were revealed using transcriptomic analysis on H. undatus. Results revealed that important physiological metabolisms, such as antioxidant activities or metal ion transport were induced, and defense responses were inhibited by trypsin. Furthermore, the results of protein–protein interaction (PPI) networks showed that besides the entire ROS network, the tiny SODs sub-network was also a scale-free network. Cu/Zn SODs acted as the hub that SODs synergized with trypsin during the storage of H. undatus.

Cellular Processes Involved in Jurkat Cells Exposed to Nanosecond Pulsed Electric Field

Recently, nanosecond pulsed electric field (nsPEF) has been considered as a new tool for tumor therapy, but its molecular mechanism of function remains to be fully elucidated. Here, we explored the cellular processes of Jurkat cells exposed to nanosecond pulsed electric field. Differentially expressed genes (DEGs) were acquired from the GEO2R, followed by analysis with a series of bioinformatics tools. Subsequently, 3D protein models of hub genes were modeled by Modeller 9.21 and Rosetta 3.9. Then, a 100 ns molecular dynamics simulation for each hub protein was performed with GROMACS 2018.2. Finally, three kinds of nsPEF voltages (0.01, 0.05, and 0.5 mV/mm) were used to simulate the molecular dynamics of hub proteins for 100 ns. A total of 1769 DEGs and eight hub genes were obtained. Molecular dynamic analysis, including root mean square deviation (RMSD), root mean square fluctuation (RMSF), and the Rg, demonstrated that the 3D structure of hub proteins was built, and the structural characteristics of hub proteins under different nsPEFs were acquired. In conclusion, we explored the effect of nsPEF on Jurkat cell signaling pathway from the perspective of molecular informatics, which will be helpful in understanding the complex effects of nsPEF on acute T-cell leukemia Jurkat cells.