Transcriptomic characterization of Trichoderma harzianum T34 primed tomato plants: assessment of biocontrol agent induced host specific gene expression and plant growth promotion.

In this study, we investigated the intricate interplay between Trichoderma and the tomato genome, focusing on the transcriptional and metabolic changes triggered during the late colonization event. Microarray probe set (GSE76332) was utilized to analyze the gene expression profiles changes of the un-inoculated control (tomato) and Trichoderma-tomato interactions for identification of the differentially expressed significant genes. Based on principal component analysis and R-based correlation, we observed a positive correlation between the two cross-comaparable groups, corroborating the existence of transcriptional responses in the host triggered by Trichoderma priming. The statistically significant genes based on different p-value cut-off scores [(padj-values or q-value); padj-value < 0.05], [(pcal-values); pcal-value < 0.05; pcal < 0.01; pcal < 0.001)] were cross compared. Through cross-comparison, we identified 156 common genes that were consistently significant across all probability thresholds, and showing a strong positive corelation between p-value and q-value in the selected probe sets. We reported TD2, CPT1, pectin synthase, EXT-3 (extensin-3), Lox C, and pyruvate kinase (PK), which exhibited upregulated expression, and Glb1 and nitrate reductase (nii), which demonstrated downregulated expression during Trichoderma-tomato interaction. In addition, microbial priming with Trichoderma resulted into differential expression of transcription factors related to systemic defense and flowering including MYB13, MYB78, ERF2, ERF3, ERF5, ERF-1B, NAC, MADS box, ZF3, ZAT10, A20/AN1, polyol sugar transporter like zinc finger proteins, and a novel plant defensin protein. The potential bottleneck and hub genes involved in this dynamic response were also identified. The protein-protein interaction (PPI) network analysis based on 25 topmost DEGS (pcal-value < 0.05) and the Weighted Correlation Gene Network Analysis (WGCNA) of the 1786 significant DEGs (pcal-value < 0.05) we reported the hits associated with carbohydrate metabolism, secondary metabolite biosynthesis, and the nitrogen metabolism. We conclude that the Trichoderma-induced microbial priming re-programmed the host genome for transcriptional response during the late colonization event and were characterized by metabolic shifting and biochemical changes specific to plant growth and development. The work also highlights the relevance of statistical parameters in understanding the gene regulatory dynamics and complex regulatory networks based on differential expression, co-expression, and protein interaction networks orchestrating the host responses to beneficial microbial interactions.

Identification and validation of IRF6 related to ovarian cancer and biological function and prognostic value.

BACKGROUND: Ovarian cancer (OC) is a severe gynecological malignancy with significant diagnostic and therapeutic challenges. The discovery of reliable cancer biomarkers can be used to adjust diagnosis and improve patient care. However, serous OC lacks effective biomarkers. We aimed to identify novel biomarkers for OC and their pathogenic causes. METHODS: The present study used the differentially expressed genes (DEGs) obtained from the "Limma" package and WGCNA modules for intersection analysis to obtain DEGs in OC. Three hub genes were identified-claudin 3 (CLDN3), interferon regulatory factor 6 (IRF6), and prostasin (PRSS8)-by searching for hub genes through the PPI network and verifying them in GSE14407, GSE18520, GSE66957, and TCGA + GTEx databases. The correlation between IRF6 and the prognosis of OC patients was further confirmed in Kaplan-Miller Plotter. RT-qPCR and IHC confirmed the RNA and protein levels of IRF6 in the OC samples. The effect of IRF6 on OC was explored using transwell invasion and scratch wound assays. Finally, we constructed a ceRNA network of hub genes and used bioinformatics tools to predict drug sensitivity. RESULTS: The joint analysis results of TCGA, GTEx, and GEO databases indicated that IRF6 RNA and protein levels were significantly upregulated in serous OC and were associated with OS and PFS. Cell function experiments revealed that IRF6 knockdown inhibited SKOV3 cell proliferation, migration and invasion. CONCLUSION: IRF6 is closely correlated with OC development and progression and could be considered a novel biomarker and therapeutic target for OC patients.

Discovering KYNU as a feature gene in hidradenitis suppurativa.

BACKGROUND: Hidradenitis suppurativa (HS) is a chronic auto-inflammatory skin condition characterized by nodules, abscesses, and fistulae in skin folds. The underlying pathogenesis of HS remains unclear, and effective therapeutic drugs are limited. METHODS: We acquired mRNA expression profiles from the Gene Expression Omnibus (GEO) database and conducted differential expression analysis between control and HS samples using R software. Four machine learning algorithms (SVM, RF, ANN, and lasso) and WCGNA were utilized to identify feature genes. GO, KEGG, Metascape, and GSVA were utilized for the enrichment analysis. CIBERSORT and ssGSEA were employed to analyze immune infiltration. RESULTS: A total of 29 DEGs were identified, with the majority showing up-regulation in HS. Enrichment analysis revealed their involvement in immune responses and cytokine activities. KEGG analysis highlighted pathways such as IL-17 signaling, rheumatoid arthritis, and TNF signaling in HS. Immune infiltration analysis revealed the predominant presence of neutrophils, monocytes, and CD8 T cells. Machine learning algorithms and WCGNA identified KYNU as a feature gene associated with HS. We have also identified 59 potential drugs for HS based on the DEGs. Additionally, ceRNA network analysis identified the MUC19_hsa-miR-382-5p_KYNU pathway as a potential regulatory pathway. CONCLUSIONS: KYNU emerged as a feature gene associated with HS, and the ceRNA network analysis identified the MUC19_hsa-miR-382-5p_KYNU pathway as a potential regulator.

Exploring the key genetic association between chronic pancreatitis and pancreatic ductal adenocarcinoma through integrated bioinformatics.

Background: Pancreatic ductal adenocarcinoma (PDAC) develops rapidly and has a poor prognosis. It has been demonstrated that pancreatic ductal adenocarcinoma and chronic pancreatitis (CP) have a close connection. However, the underlying mechanisms for chronic pancreatitis transforming into pancreatic ductal adenocarcinoma are still unclear. The purpose of this study was to identify real hub genes in the development of chronic pancreatitis and pancreatic ductal adenocarcinoma. Methods: RNA-seq data of chronic pancreatitis and pancreatic ductal adenocarcinoma were downloaded from the Gene Expression Omnibus (GEO) database. Weighted gene co-expression network analysis (WGCNA) was performed to construct a gene co-expression network between chronic pancreatitis and pancreatic ductal adenocarcinoma. GEO2R and a Venn diagram were used to identify differentially expressed genes. Then visualized networks were constructed with ClueGO, and modules of PPI network were calculated by MCODE plugin. Further validation of the results was carried out in two additional cohorts. Analyses of CEL-coexpressed genes and regulators including miRNAs and transcription factors were performed by using the corresponding online web tool. Finally, the influence of CEL in the tumor immune microenvironment (TIME) was assessed by immune contextual analysis. Results: With the help of WGCNA and GEO2R, four co-expression modules and six hub genes were identified, respectively. ClueGO enrichment analysis and MCODE cluster analysis revealed that the dysfunctional transport of nutrients and trace elements might contribute to chronic pancreatitis and pancreatic ductal adenocarcinoma development. The real hub gene CEL was identified with a markedly low expression in pancreatic ductal adenocarcinoma in external validation sets. According to the miRNA-gene network construction, hsa-miR-198 may be the key miRNA. A strong correlation exists between CEL and TIME after an evaluation of the influence of CEL in TIME. Conclusion: Our study revealed the dysfunctional transport of nutrients and trace elements may be common pathogenesis of pancreatic ductal adenocarcinoma and chronic pancreatitis. Examination on these common pathways and real hub genes may shed light on the underlying mechanism.

Identification of unique transcriptomic signatures and key genes through RNA sequencing and integrated WGCNA and PPI network analysis in HIV infected lung cancer.

With the widespread use of highly active antiretroviral therapy (HARRT), the survival time of AIDS patients has been greatly extended. However, the incidence of lung cancer in HIV-infected patients is increasing and has become a major problem threatening the survival of AIDS patients. The aim of this study is to use Weighted Gene Co-expression Network Analysis (WGCNA) and differential gene analysis to find possible key genes involved in HIV-infected lung cancer. In this study, using lung tissue samples from five pairs of HIV-infected lung cancer patients, second-generation sequencing was performed and transcriptomic data were obtained. A total of 132 HIV-infected lung cancer-related genes were screened out by WGCNA and differential gene expression analysis methods. Based on gene annotation analysis, these genes were mainly enriched in mitosis-related functions and pathways. In addition, in protein-protein interaction (PPI) analysis, a total of 39 hub genes were identified. Among them, five genes (ASPM, CDCA8, CENPF, CEP55, and PLK1) were present in both three hub gene lists (intersection gene, DEGs, and WCGNA module) suggesting that these five genes may become key genes involved in HIV-infected lung cancer.

Mining TCGA Data for Key Biomarkers Related to Immune Microenvironment in Endometrial cancer by Immune Score and Weighted Correlation Network Analysis.

Background: Endometrial cancer (EC) is one of the most lethal gynecological cancers around the world. The aim of this study is to identify the potential immune microenvironment-related biomarkers associated with the prognosis for EC. Methods: RNA-seq data and clinical information of EC patients were derived from The Cancer Genome Atlas (TCGA). The immune score of each EC sample was obtained by ESTIMATE algorithm. Weighted gene co-expression network analysis (WGCNA) was used to identify the interesting module and potential key genes concerning the immune score. The expression patterns of the key genes were then verified via the GEPIA database. Finally, CIBERSORT was applied to evaluate the relative abundances of 22 immune cell types in EC. Results: Immune scores were significantly associated with tumor grade and histology of EC, and high immune scores may exert a protective influence on the survival outcome for EC. WGCNA indicated that the black module was significantly correlated with the immune score. Function analysis revealed it mainly involved in those terms related to immune regulation and inflammatory response. Moreover, 11 key genes (APOL3, C10orf54, CLEC2B, GIMAP1, GIMAP4, GIMAP6, GIMAP7, GIMAP8, GYPC, IFFO1, TAGAP) were identified from the black module, validated by the GEPIA database, and revealed strong correlations with infiltration levels of multiple immune cell types, as was the prognosis of EC. Conclusion: In this study, 11 key genes showed abnormal expressions and strong correlations with immune infiltration in EC, most of which were significantly associated with the prognosis of EC. These findings made them promising therapeutic targets for the treatment of EC.

Association of Circulating, Inflammatory-Response Exosomal mRNAs With Acute Myocardial Infarction.

Background: Although many cardiovascular disease studies have focused on the microRNAs of circulating exosomes, the profile and the potential clinical diagnostic value of plasma exosomal long RNAs (exoLRs) are unknown for acute myocardial infarction (AMI). Methods: In this study, the exoLR profile of 10 AMI patients, eight stable coronary artery disease (CAD) patients, and 10 healthy individuals was assessed by RNA sequencing. Bioinformatic approaches were used to investigate the characteristics and potential clinical value of exoLRs. Results: Exosomal mRNAs comprised the majority of total exoLRs. Immune cell types analyzed by CIBERSORT showed that neutrophils and monocytes were significantly enriched in AMI patients, consistent with clinical baseline values. Biological process enrichment analysis and co-expression network analysis demonstrated neutrophil activation processes to be enriched in AMI patients. Furthermore, two exosomal mRNAs, ALPL and CXCR2, were identified as AMI biomarkers that may be useful for evaluation of the acute inflammatory response mediated by neutrophils. Conclusions: ExoLRs were assessed in AMI patients and found to be associated with the acute inflammatory response mediated by neutrophils. Exosomal mRNAs, ALPL and CXCR2, were identified as potentially useful biomarkers for the study of AMI.

Construction of ceRNA Network to Reveal Potential Biomarkers in Crohn's Disease and Validation in a TNBS Induced Mice Model.

PURPOSE: We aimed to construct a competing endogenous RNA (ceRNA) network and explore the potential biomarkers in Crohn's disease (CD) via bioinformatics analysis. Validation of candidate biomarkers in a 2,4,6-trinitrobenzene sulfonic acid (TNBS) induced experimental colitis model and ceRNA network in an HCT116 cell line was also an aim, along with purposing to reveal the pathogenesis of CD. METHODS: GSE102134 and GSE67106 datasets were obtained and used to screen the differentially expressed genes. WCGNA was applied to identify the relative model to construct the ceRNA network. Furthermore, the relationship between candidate gene and immune infiltration was investigated. Then, the expression of potential biomarkers was validated via qRT-PCR in a TNBS induced experimental colitis model. Finally, the ceRNA network was confirmed by RNAi experiments in an HCT116 cell line. RESULTS: The ceRNA network, consisting of four lncRNAs, four miRNAs, and eight mRNAs, was constructed and the ROC analysis showed four mRNAs (PTGS2, LPL, STAT1, and TRIB2) had high diagnostic accuracy (AUC>0.9). In addition, upregulated PTGS2 was positively correlated with immune cell infiltration, including Natural killer cells, exhausted T-cells, monocytes, and Dendritic cells. The outcome of this TNBS induced experimental colitis model verified that the expression of PTGS2 and mir-429 was consistent with results of previous bioinformatics analysis. Furthermore, the predicted ceRNA network MIR3142HG/mir-429/PTGS2 were validated via RNA interference. Knockout of MIR3142HG decreased the mRNA level of PTGS2, whereas inhibition of mir-429 increased the mRNA level of PTGS2 in the HCT116 cell line. CONCLUSION: The exploration of the ceRNA network in this work might contribute to understanding the pathogenesis of CD. The constructed MIR3142HG/mir-429/PTGS2 ceRNA network may play a role in CD, and PTGS2 can be a potential immune-related biomarker in CD.

COL5A2 Promotes Proliferation and Invasion in Prostate Cancer and Is One of Seven Gleason-Related Genes That Predict Recurrence-Free Survival.

Extensive research has revealed that the score derived from the Gleason grading system plays a pivotal role in predicting prostate cancer (PCa) progression. However, the underlying involvement of Gleason-related genes in PCa requires further investigation. This study aimed to identify Gleason-related genes with the potential to guide PCa therapy and future research. Differentially expressed genes (DEGs) were identified by comparing PCa tissues with high or low Gleason scores using the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) databases. R v3.6.1, SPSS v23, and ImageJ software were used for all analyses. An effective recurrence-free survival (RFS) predictive model based on seven Gleason-related genes was established and validated (TCGA, AUC = 0.803; five years, AUC = 0.740; three years, AUC = 0.722; one year, AUC = 0.711; GSE46602, AUC = 0.766; five years, AUC = 0.808; three years, AUC = 0.723; one year, AUC = 0.656; GSE116918, AUC = 0.788; five years, AUC = 0.704; three years, AUC = 0.693; one year, AUC = 0.996). Calibration and nomogram plots were conducted. Weighted correlation network analysis (WGCNA) was used, and COL5A2 was selected for further analysis. The results from in vitro experiments demonstrated that COL5A2 was upregulated in PCa with high Gleason scores. The knockdown of COL5A2 inhibited cell proliferation and invasion in PC-3 and LNCaP cell lines. Meanwhile, COL5A2 displayed a strong association with immune infiltration, which might be an underlying immunotherapy target for PCa. We successfully established a robust RFS predictive model. The findings from this study indicated that COL5A2 could promote cell proliferation and invasion in PCa.

Exploring Specific miRNA-mRNA Axes With Relationship to Taxanes-Resistance in Breast Cancer.

Breast cancer is the most prevalent type of malignancy in women worldwide. Taxanes (paclitaxel and docetaxel) are widely applied as first-line chemotherapeutic agents, while the therapeutic effect is seriously limited by the development of drug resistance. In the present study, we screened out several miRNAs dysregulated in taxanes-resistant breast cancer samples and confirmed that two miRNAs (miR-335-5p and let-7c-5p) played a major role in cell proliferation, apoptosis, and chemo-resistance. In addition, the weighted gene co-expression network analysis (WGCNA) for potential target genes of miR-335-5p and let-7c-5p identified three hub genes (CXCL9, CCR7, and SOCS1) with a positive relationship to taxanes-sensitivity. Further, target relationships between miR-335-5p and CXCL9, let-7c-5p and CCR7/SOCS1 were confirmed by dual-luciferase reporter assays. Importantly, the regulatory functions of CXCL9, CCR7, and SOCS1 on proliferation and chemoresistance were validated. In conclusion, our study shed light on clinical theragnostic relationships between miR-335-5p/CXCL9, let-7c-5p/CCR7/SOCS1 axes, and taxanes-resistance in breast cancer.

Mechanistic Differences in Neuropathic Pain Modalities Revealed by Correlating Behavior with Global Expression Profiling.

Chronic neuropathic pain is a major morbidity of neural injury, yet its mechanisms are incompletely understood. Hypersensitivity to previously non-noxious stimuli (allodynia) is a common symptom. Here, we demonstrate that the onset of cold hypersensitivity precedes tactile allodynia in a model of partial nerve injury, and this temporal divergence was associated with major differences in global gene expression in innervating dorsal root ganglia. Transcripts whose expression change correlates with the onset of cold allodynia were nociceptor related, whereas those correlating with tactile hypersensitivity were immune cell centric. Ablation of TrpV1 lineage nociceptors resulted in mice that did not acquire cold allodynia but developed normal tactile hypersensitivity, whereas depletion of macrophages or T cells reduced neuropathic tactile allodynia but not cold hypersensitivity. We conclude that neuropathic pain incorporates reactive processes of sensory neurons and immune cells, each leading to distinct forms of hypersensitivity, potentially allowing drug development targeted to each pain type.