Differentially Expressed Genes Research Articles

Development and validation of biomarkers related to anoikis in liver cirrhosis based on bioinformatics analysis

BACKGROUND According to study, anoikis-related genes (ARGs) have been demonstrated to play a significant impact in cirrhosis, a major disease threatening human health worldwide. AIM To investigate the relationship between ARGs and cirrhosis development to provide insights into the clinical treatment of cirrhosis. METHODS RNA-sequencing data related to cirrhosis were obtained from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) between cirrhotic and normal tissues were intersected with ARGs to derive differentially expressed ARGs (DEARGs). The DEARGs were filtered using the least absolute shrinkage and selection operator, support vector machine recursive feature elimination, and random forest algorithms to identify biomarkers for cirrhosis. These biomarkers were used to create a nomogram for predicting the prognosis of cirrhosis. The proportions of diverse immune cell subsets in cirrhotic vs normal tissues were compared using the CIBERSORT computational method. In addition, the linkage between immune cells and biomarkers was assessed, and a regulatory network of mRNA, miRNA, and transcription factors was constructed relying on the biomarkers. RESULTS The comparison of cirrhotic and normal tissue samples led to the identification of 635 DEGs. Subsequent intersection of the DEGs with ARGs produced a set of 26 DEARGs. Subsequently, three DEARGs, namely, ACTG1 , STAT1 , and CCR7 , were identified as biomarkers using three machine-learning algorithms. The proportions of M1 and M2 macrophages, resting CD4 memory T cells, resting mast cells, and plasma cells significantly differed between cirrhotic and normal tissue samples. The proportions of M1 and M2 macrophages, resting CD4 memory T cells, and resting mast cells were significantly correlated with the expression of the three biomarkers. The mRNA–miRNA–TF network showed that ACTG1 , CCR7 , and STAT1 were regulated by 28, 42, and 35 miRNAs, respectively. Moreover, AR, MAX, EP300, and FOXA1 were found to regulate four miRNAs related to the biomarkers. CONCLUSION This study revealed ACTG1 , STAT1 , and CCR7 as biomarkers of cirrhosis, providing a reference for developing novel diagnostic and therapeutic strategies for cirrhosis.

NMI, POLR3G and APIP are the key molecules connecting glaucoma with high intraocular pressure: a clue for early diagnostic biomarker candidates

AIM: To understand the molecular connectivity between the intraocular pressure (IOP) and glaucoma which will provide possible clues for biomarker candidates. METHODS: The current study uncovers the important genes connecting IOP with the core functional modules of glaucoma. An integrated analysis was performed using glaucoma and IOP microarray datasets to screen for differentially expressed genes (DEGs) in both conditions. To the selected DEGs, the protein interaction network was constructed and dissected to determine the core functional clusters of glaucoma. For the clusters, the connectivity of IOP DEGs was determined. Further, enrichment analyses were performed to assess the functional annotation and potential pathways of the crucial clusters. RESULTS: The gene expression analysis of glaucoma and IOP with normal control showed that 408 DEGs (277 glaucoma and 131 IOP genes) were discovered from two GEO datasets. The 290 DEGs of glaucoma were extended to form a network containing 1495 proteins with 9462 edges. Using ClusterONE, the network was dissected to have 12 clusters. Among them, three clusters were linked with three IOP DEGs [N-Myc and STAT Interactor (NMI), POLR3G (RNA Polymerase III Subunit G), and APAF1-interacting protein (APIP)]. In the clusters, ontology analysis revealed that RNA processing and transport, p53 class mediators resulting in cell cycle arrest, cellular response to cytokine stimulus, regulation of phosphorylation, regulation of type I interferon production, DNA deamination, and cellular response to hypoxia were significantly enriched to be implicated in the development of glaucoma. Finally, NMI, POLR3G, and APIP may have roles that were noticed altered in glaucoma and IOP conditions. CONCLUSION: Our findings could help to discover new potential biomarkers, elucidate the underlying pathophysiology, and identify new therapeutic targets for glaucoma.

Transcriptomic and Metabolomics Joint Analyses Reveal the Influence of Gene and Metabolite Expression in Blood on the Lactation Performance of Dual-Purpose Cattle (Bos taurus)

Blood is an important component for maintaining animal lives and synthesizing sugars, lipids, and proteins in organs. Revealing the relationship between genes and metabolite expression and milk somatic cell count (SCC), milk fat percentage, milk protein percentage, and lactose percentage in blood is helpful for understanding the molecular regulation mechanism of milk formation. Therefore, we separated the buffy coat and plasma from the blood of Xinjiang Brown cattle (XJBC) and Chinese Simmental cattle (CSC), which exhibit high and low SCC/milk fat percentage/milk protein percentage/lactose percentages, respectively. The expression of genes in blood and the metabolites in plasma was detected via RNA-Seq and LC-MS/MS, respectively. Based on the weighted gene coexpression network analysis (WGCNA) and functional enrichment analysis of differentially expressed genes (DEGs), we further found that the expression of genes in the blood mainly affected the SCC and milk fat percentage. Immune or inflammatory-response-related pathways were involved in the regulation of SCC, milk fat percentage, milk protein percentage, and lactose percentage. The joint analysis of the metabolome and transcriptome further indicated that, in blood, the metabolism pathways of purine, glutathione, glycerophospholipid, glycine, arginine, and proline are also associated with SCC, while lipid metabolism and amino-acid-related metabolism pathways are associated with milk fat percentage and milk protein percentage, respectively. Finally, related SCC, milk fat percentage, and milk protein percentage DEGs and DEMs were mainly identified in the blood.

Time-course RNA sequencing reveals high similarity in mRNAome between hepatic stellate cells activated by agalactosyl IgG and TGF-β1.

Previous studies have demonstrated the clinical relevance of aberrant serum immunoglobulin G (IgG) N-glycomic profiles in liver fibrosis and the pathogenic effects of agalactosyl IgG on activating hepatic stellate cells (HSCs). However, the dynamics of gene expression changes during HSC activation by agalactosyl IgG remain poorly understood. We performed RNA sequencing to analyze the mRNAome of human LX-2 HSCs at multiple time points after treatment with agalactosyl IgG and then compared these results with those obtained after normal IgG and transforming growth factor (TGF)-β1 treatments. Gene expression changes were significantly pronounced on day 5 and subsided by day 11 after HSC activation. A high degree of similarity in gene expression patterns between HSCs treated with agalactosyl IgG and TGF-β1 was observed, of which 1796 and 1785 differentially expressed genes (DEGs) were identified, respectively. Disease ontology analyses revealed that 114 and 105 DEGs in activated HSCs following agalactosyl IgG and TGF-β1 treatments, respectively, were linked to liver cirrhosis, hepatitis, fatty liver disease, hepatitis B, and alcoholic hepatitis, with CCL5 and FAS being the most commonly affected genes. DEGs associated with liver fibrosis or aforementioned liver diseases involved in gene annotation, physiological functions, and signaling pathways regarding secretion of cytokines and chemokines, expression of fibrosis-related growth factors and their receptors, modification of extracellular matrices, and regulation of cell viability in activated HSCs. In conclusion, this study characterized the dynamics of mRNAome and gene networks and identified the liver fibrosis-related DEGs during HSC activation by agalactosyl IgG and TGF-β1.

Tongguanteng injection exerts anti-osteosarcoma effects through the ER stress-associated IRE1/CHOP pathway.

In China, Tongguanteng injection (TGT) is widely used in the treatment or adjuvant treatment of various types of cancer. However, the effect and mechanism of TGT in osteosarcoma is not clear. The 143B and MG-63 cells were treated with different concentrations of TGT. Cell proliferation, migration, invasion and apoptosis were detected using CCK8 assay, transwell assay and flow cytometry. Differentially expressed genes (DEGs) were screened using RNA sequencing (RNA-seq). The identified mRNA and protein expression associated with the IRE1/CHOP pathway was validated by RT-PCR and western blot assay. To explore the underlying mechanisms, 4-phenylbutyric acid (4-PBA) was selected as a specific endoplasmic reticulum (ER) stress inhibitor. Small interfering RNA (siRNA) or pEX-3-ERN1 plasmid was transfected into 143B cells to silence or overexpress IRE1, respectively. The potential downstream proteins, including CHOP, and apoptosis associated proteins, caspase-3 and PARP1 were determined. Furthermore, the effect of TGT was demonstrated in 143B cell tumor-bearing mice in vivo. H&E staining, TUNEL staining and immunohistochemistry were conducted in tumor tissues obtained from the xenograft mouse model. TGT was shown to dramatically suppress the proliferation, migration and invasion, and induce apoptosis of osteosarcoma 143B and MG-63 cells in vitro. The identified DEGs included HSPA5 (encoding BiP) and ERN1 (encoding the IRE1 protein), as well as apoptosis-associated gene DDIT3 (encoding the CHOP protein). The term "IRE1-mediated unfolded protein response" was screened to be the most enriched biological process GO term. The expression of ER stress-associated proteins including ATF6, BiP, p-IRE1, XBP1s and CHOP, as well as apoptosis-associated cleaved caspase-3 and cleaved PARP1 proteins, was significantly upregulated by TGT treatment in osteosarcoma 143B cells, suggesting that TGT might promote the apoptosis of osteosarcoma 143B cells through the IRE1/CHOP pathway. Furthermore, knocking down IRE1 with si-IRE1 or inhibiting of ER stress with 4-PBA suppressed the expression of ATF6, BiP, XBP1s and CHOP induced by TGT, as well as the expression of cleaved caspase-3 and cleaved PARP1. On the contrary, overexpressing IRE1 promoted CHOP expression and induced osteosarcoma cell apoptosis. Consistent with in vitro results, TGT dramatically inhibited the tumor growth and promoted the expression of p-IRE1 and CHOP in tumor-bearing mice. The findings suggest that TGT exerts an anti-osteosarcoma effect in vitro and in vivo. The underlying mechanism might be associated with the activation of IRE1/CHOP pathway in ER stress. Our findings suggest that targeting IRE1/CHOP pathway might be a potential novel approach for osteosarcoma treatment.

Single-cell data revealed the regulatory mechanism of TNK cell heterogeneity in liver metastasis from gastric cancer.

The present work set out to classify cell subpopulations related to liver metastasis from gastric cancer (GC) and the mechanisms of their interactions with other immune cell subpopulations. GC is characterized by a high degree of heterogeneity and liver metastasis. Exploring the mechanism of liver metastasis of GC from the perspective of heterogeneity of the tumor microenvironment (TME) might help improve the efficacy of GC treatment. Based on the cellular subpopulation characteristics of GC with liver metastasis, the regulatory mechanisms contributing to GC progression were analyzed, with special focuses on the roles of signaling pathways, transcription factors (TFs) and ligand-receptor pairs. The GSE163558 dataset was downloaded from the Gene Expression Omnibus (GEO) database to collect single-cell transcriptomic data of GC patients and their metastasis groups for cell clustering and relevant analyses. Differentially expressed genes (DEGs) in the GC and GC liver metastasis groups were screened and subjected to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. SCENIC analysis was used to mine TFs that affected cellular subpopulations during liver metastasis from GC. The relative expression levels of TFs in GC were determined using qRT-PCR. Transwell and wound healing assays were utilized to verify the regulation of the TFs on the migration and invasion of GC cells. Interaction network between the cellular subpopulations was developed applying CellChat. Single-cell clustering was performed to group six major cell subpopulations, namely, Myeloid cells, B cells, Mast cells, Epithelial cells, Fibroblasts, and TNK cells, among which the number of TNK cells was significantly increased in the GC liver metastasis group. Differentially enriched pathways of TNK cells between GC and GC liver metastasis groups mainly included IL-17 and Pi3k-Akt signaling pathways. TNK cell subsets could be further categorized into CD8 T cells, Exhausted T cells, NK cells, NKT cells, and Treg cells, with the GC liver metastasis group showing significantly more CD8 T cells and NKT cells. FOS and JUNB were the TFs of TNK cell marker genes that contributed to liver metastasis from GC and the invasion and migration of GC cell lines. Significant differences in immune cell communication ligand-receptor pairs existed between the GC and GC liver metastasis groups. This study revealed the critical role of TNK cell subsets in GC with liver metastasis applying single-cell transcriptomics analysis. The findings provided an important theoretical basis for developing novel therapies to inhibit liver metastasis from GC.

Bioinformatics combined with network pharmacology and experimental validation to identify key biomarkers of hepatocellular carcinoma and corresponding compounds in Radix Astragali and Pueraria Mirifica.

The occurrence and death rates of primary hepatocellular carcinoma (HCC) are increasing, and there remains a shortage of effective oral medications with minimal side effects. We aim to identify potential biomarkers and compounds from Radix Astragali (RA) and Pueraria Mirifica (PM) to treat liver cancer and improve prognosis. Differentially expressed genes (DEGs) associated with HCC were identified by bioinformatics analysis of three datasets, GSE112791, GSE101685, and GSE45114. Using public databases to predict the bioactive components and possible targets of RA and PM. Target crossover from Gene Expression Omnibus (GEO) and public databases were used to identify potential biomarkers for HCC. Subsequently, validation and prognostic value analyses were performed using the Gene Expression Profile Interaction Analysis (GEPIA) platform. The Cytoscape software created a network of "compound targets" to pinpoint compounds linked to the biomarkers. Molecular docking techniques were utilized to validate the connection between these compounds and the identified biomarkers. Ultimately, the HepG2 liver cancer cell line was chosen to assess the inhibitory effect of Hederagenin (HDG) and to confirm the expression of ADH1B through Western blot analysis. In this study, four key biomarkers (NR1I2, ADH1B, NQO1, GHR) were identified. Molecular docking showed that these four core targets could form stable conformations with the corresponding compounds. As the drug concentration decreases, the inhibitory effect on HepG2 diminishes, and the survival rate of HepG2 cells significantly declines following the administration of 100 µmol/L HDG. Compared to the control, the expression of ADH1B protein is significantly increased in HepG2 cells treated with 100 µmol/L HDG. The study identified four key biomarkers (ADH1B, GHR, NQO1, NR1I2) that have prognostic ability for HCC. This study provides biomarkers and potential targeted monomeric medicines for treating HCC.

Machine learning model based on SERPING1, C1QB, and C1QC: A novel diagnostic approach for latent tuberculosis infection

AbstractBackgroundLatent tuberculosis infection (LTBI) is a significant source of active tuberculosis (ATB), yet distinguishing between them is challenging because specific biomarkers are lacking.MethodsWe analyzed four microarray datasets (GSE19491, GSE37250, GSE54992, GSE28623) from the gene expression omnibus to identify differentially expressed genes (DEGs). Using protein–protein interaction (PPI) networks and LASSO‐SVM algorithms, we selected three candidate biomarkers and evaluated their diagnostic efficacy. The expression levels of core genes were validated by RNA sequencing of healthy, ATB, and LTBI groups in a real‐world cohort. We conducted Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses, predicted shared upstream miRNAs, constructed miRNA–hub and transcription factor (TF)–hub gene networks, and performed immune infiltration analysis.ResultsThree hub genes (SERPING1, C1QC, C1QB) were identified from 45 DEGs by PPI networks and machine learning screening. The diagnostic model based on the three hub genes had an area under the curve (AUC) value of 0.843 in the training set GSE19491 and 0.865 in the validation set GSE28623. Real‐world transcriptome sequencing confirmed the expression trends of the hub genes across healthy, LTBI, and ATB groups. GO analysis showed that the 45 hub genes were primarily associated with immune inflammatory responses and pattern recognition receptors, whereas KEGG analysis indicated enrichment in complement and coagulation cascades. The miRNA–hub and TF–hub gene network analysis identified nine miRNAs and the zinc finger TF GATA2 as potential co‐regulators of SERPING1, C1QC, and C1QB. Immune cell infiltration analysis identified significant differences in the immune microenvironment between LTBI and ATB, with macrophages and natural killer cells showing significant correlations with tuberculosis infection.ConclusionThe diagnostic model with SERPING1, C1QC, and C1QB shows promise in distinguishing LTBI from ATB, indicating its potential as a diagnostic tool.

RNA-Seq Profiling in Chicken Spleen and Thymus Infected with Newcastle Disease Virus of Varying Virulence

Newcastle disease virus (NDV), known as avian paramyxovirus-1, poses a significant threat to poultry production worldwide. Vaccination currently stands as the most effective strategy for Newcastle disease control. However, the mesogenic vaccine strain Mukteswar has been observed to evolve into a velogenic variant JS/7/05/Ch during poultry immunization. Here, we aimed to explore the mechanisms underlying virulence enhancement of the two viruses. Pathogenically, JS/7/05/Ch mediated stronger virulence and pathogenicity in vivo compared to Mukteswar. Comparative transcriptome analysis revealed 834 differentially expressed genes (DEGs), comprising 339 up-regulated and 495 down-regulated genes, in the spleen, and 716 DEGs, with 313 up-regulated and 403 down-regulated genes, in the thymus. Gene Ontology (GO) analysis indicated that these candidate targets primarily participated in cell and biological development, extracellular part and membrane composition, as well as receptor and binding activity. Furthermore, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis unveiled a substantial portion of candidate genes predominantly involved in cellular processes, environmental information processing, metabolism, and organismal systems. Additionally, five DEGs (TRAT1, JUP, LPAR4, CYB561A3, and CXCR5) were randomly identified through RNA-seq analysis and subsequently confirmed via quantitative real-time polymerase chain reaction (qRT-PCR). The findings revealed a marked up-regulation in the expression levels of these DEGs induced by JS/7/05/Ch compared to Mukteswar, with CYB561A3 and CXCR5 exhibiting significant increases. The findings corroborated the sequencing accuracy, offering promising research directions. Taken together, we comprehensively evaluated transcriptomic alterations in chicken immune organs infected by NDV strains of diverse virulence. This study establishes a basis and direction for NDV virulence research.

Integrative hyperspectral, transcriptomic, and metabolomic analysis reveals the mechanism of tea plants in response to sooty mold disease.

Sooty mold (SM), caused by Cladosporium species, is a pervasive threat to tea plant health, affecting both canopy structure and crop yield. Despite its significance, understanding the complex interplay between defense genes and metabolites in tea plants across various SM-infected canopy layers remains limited. Our study employed hyperspectral imaging, transcriptomic profiling, and metabolomic analysis to decipher the intricate mechanisms underlying the tea plant's response to SM infection. Our hyperspectral imaging identified three critical wavelengths (552, 673, and 800nm) inflection points associated with varying degrees of SM infection. This non-invasive method allows for the precise assessment of disease progression. Concurrently, transcriptome analysis revealed a wealth of differentially expressed genes (DEGs) enriched in metabolic pathways, secondary metabolite biosynthesis, and plant-pathogen interactions. Cluster analysis highlighted an intensified immune response in A2 and A3 samples. A comprehensive metabolomic profile identified 733 co-changed metabolites in SM-infected leaves, with alcohols, lipids (free fatty acids), hydrocarbons, and amino acids significantly accumulating in A1, while flavonoids were predominantly upregulated in A2 and A3. Weighted Gene Co-Expression Network Analysis (WGCNA) uncovered five hub genes (Dormancy-associated protein, Serine/threonine-protein phosphatase, ABC transporter, and some uncharacterized proteins) and two hub metabolites (D-Mannitol and 17-Hydroxylinolenic Acid) that exhibit significant relationships with DEGs and metabolites. Further co-expression analysis indicated that tea plants mainly employed genes and metabolites related to the biosynthesis of secondary metabolites, plant hormone signal transduction, and plant-pathogen interaction to combat SM. This study establishes a foundation for understanding the immune mechanisms of tea plants across different canopy layers in response to SM infection. It not only sheds light on the complex defense strategies employed by tea plants but also identifies candidate genes and metabolites crucial for enhancing tea plant breeding and resistance to SM.

Network pharmacology and in vitro experiments to investigate the anti-gastric cancer effects of paeoniflorin through the RAS/MAPK signaling pathway.

The aim of this study was to investigate the key targets and signaling pathways of paeoniflorin (PF) for the treatment of gastric cancer (GC). First, the differentially expressed genes (DEGs) of gastric cancer were obtained by analyzing GSE118916 Gene Chip, and then the active components of paeoniflorin and their targets of action were found. And the intersection genes of the two were analyzed for target and pathway analysis. In addition, cell viability after PF intervention was detected by CCK-8. Clone formation assay, wound scratch assay, transwell assay were used to detect cell migration and invasion. The qRT-PCR and Western blot methods were used to verify the mechanism of action. The results showed that a total of 286 paeoniflorin targets and 1799 DEGs were obtained. Secondly, we found that PF could treat gastric cancer through RAS/MAPK signaling pathway. In addition, through in vitro cellular experiments, we also found that PF had a significant therapeutic effect on gastric cancer. Therefore, we believe that PF inhibits the proliferation and metastasis of gastric cancer, and its effect may be exerted by regulating the RAS/MAPK signaling pathway. PF is a promising drug for the treatment of gastric cancer. Combined with the in vitro experiments, we found that the therapeutic effect of PF is related to the regulation of the RAS/MAPK signaling pathway, and the results of the present study preliminarily revealed its complex mechanism, which will lay the foundation for future clinical treatment.

Transcriptional profiling of the M. complexus in naked neck chickens suggest a direct pleiotropic effect of GDF7 on feathering and reduced hatchability.

The locus for naked neck (Na) in chickens reduces feather coverage and leads to increased heat dissipation from the body surface resulting in better adaptability to hot conditions. However, the Na gene is linked to significantly lower hatchability due to an increased late embryonic mortality. It has been argued that the causative gene GDF7 may have a direct pleiotropic effect on hatchability via its effect on muscle development. Thus, the study presented here analyses the transcriptome of the hatching muscle (M. complexus) and shows how GDF7 impacts development leading to reduced hatching rates in Na chickens. Using 12 chicken embryos (6 x wildtype (Wt) and 6 x Na) RNA was extracted from the M. complexus of each embryo and sequenced. The resulting differential expression analyses led to the discovery of 461 differentially expressed (DE) genes in the M. complexus of the experimental group. Among those, 77 genes were of uncertain function (LOC symbols), with 31 were classified as uncharacterised. The regulation of a number of pathways involved in normal embryonic development, were found to be negatively influenced by the Na genotype. Further pathways involved in cell-cell adhesion, cell signalling pathways, and amino acid (AA) metabolism/transport were also observed. GDF7 (alias BMP12), whose localised overexpression in the neck skin causes the Na/Na phenotype, was significantly overexpressed in the M. complexus of Na/Na embryos, and shows a significant increase in the number of binding sites for the transcription factor PITX2 was also observed. In Na chickens, GDF7 is under the control of a mutated cis-regulatory element, whose actions are known to suppress the development and distribution of feathers through the sensitizing action of retinoic acid. In this study, a number of DE genes with over 10 retinoic acid response elements (RAREs) in close proximity were observed, indicating changes to the retinol metabolism. With the understanding that the Na/Na mutation leads to increased retinoic acid activity, this indicates a high likelihood of GDF7 excerpting a direct pleiotropic effect, not just in the observed reduction in feather patterning, but also impacting the development of the M.complexus, and consequently leading to the reduced hatchability observed in birds with the Na/Na genotype. Furthermore, the enrichment of PITX2 binding sites in proximity to DE genes in the M. complexus, also indicates that muscle development is still ongoing in Na embryos. This suggests that the M. complexus is not yet fully developed, further increasing the potential for late embryonic mortality in Na chicks at hatching.

HC-HA/PTX3 from Human Amniotic Membrane Induced Differential Gene Expressions in DRG Neurons: Insights into the Modulation of Pain

Background: The biologics derived from human amniotic membranes (AMs) demonstrate potential pain-inhibitory effects in clinical settings. However, the molecular basis underlying this therapeutic effect remains elusive. HC-HA/PTX3 is a unique water-soluble regenerative matrix that is purified from human AMs. We examined whether HC-HA/PTX3 can modulate the gene networks and transcriptional signatures in the dorsal root ganglia (DRG) neurons transmitting peripheral sensory inputs to the spinal cord. Methods: We conducted bulk RNA-sequencing (RNA-seq) of mouse DRG neurons after treating them with HC-HA/PTX3 (15 µg/mL) for 10 min and 24 h in culture. Differential gene expression analysis was performed using the limma package, and Gene Ontology (GO) and protein–protein interaction (PPI) analyses were conducted to identify the networks of pain-related genes. Western blotting and in vitro calcium imaging were used to examine the protein levels and signaling of pro-opiomelanocortin (POMC) in DRG neurons. Results: Compared to the vehicle-treated group, 24 h treatment with HC-HA/PTX3 induced 2047 differentially expressed genes (DEGs), which were centered on the ATPase activity, receptor–ligand activity, and extracellular matrix pathways. Importantly, PPI analysis revealed that over 50 of these DEGs are closely related to pain and analgesia. Notably, HC-HA/PTX3 increased the expression and signaling pathway of POMC, which may affect opioid analgesia. Conclusions: HC-HA/PTX3 induced profound changes in the gene expression in DRG neurons, centered around various neurochemical mechanisms associated with pain modulation. Our findings suggest that HC-HA/PTX3 may be an important biological active component in human AMs that partly underlies its pain inhibitory effect, presenting a new strategy for pain treatment.

Transcriptome and interactome-based analyses to unravel crucial proteins and pathways involved in Acinetobacter baumannii pathogenesis.

The present study employed an integrated transcriptome and interactome-based analyses to identify key proteins and pathways associated with Acinetobacter baumannii infection towards the development of novel therapeutics against this pathogen. Transcriptome analysis of A.baumannii strains (ATCC 17978 and AbH12O-A2) identified 253 and 619 differentially expressed genes (DEGs), respectively. These genes were involved in essential molecular functions, including DNA binding, metal ion binding, and oxidoreductase activity. The centrality and module analyses of these identified DEGs had shortlisted 27 and 41 hub proteins, which were central to the ATCC 17978 and AbH12O-A2 networks, and essential for bacterial survival. Significantly, three proteins (SecA, glutathione synthase, and aromatic-amino-acid transaminase) from the ATCC 17978 strain and seven proteins (ATP synthase subunit alpha, translation initiation factor IF-2, SecY, elongation factors G, Tu, and Ts, and tRNA guanine-N1-methyltransferase) from the AbH12O-A2 strain showed interactions with human proteins, identified through host-pathogen interaction (HPI) analysis of hub proteins (referred as hub-HPI proteins). These proteins were observed to participate in vital pathways, including glutathione metabolism, secondary metabolite biosynthesis and quorum sensing. Targeting these hub-HPI proteins through novel therapeutic strategies holds the potential to disrupt the critical bacterial pathways, thereby controlling A. baumannii infections. Furthermore, their localization analysis indicated that nine proteins were cytoplasmic and one was membrane protein. Among them, six were druggable and four were novel proteins. Overall, this comprehensive study provides valuable insights into the crucial proteins and pathways involved during A. baumannii infection, and offers potential therapeutic targets for designing novel antimicrobial agents to tackle the pathogen.

Blood mir-331-3p is a potential diagnostic marker for giant panda (Ailuropoda melanoleuca) testicular tumor.

In recent years, several giant pandas have suffered from testicular tumor, which has seriously affected giant panda health. However, the pathogenesis of testicular tumor in giant panda is still unclear. Studies have shown that miRNAs are involved in the occurrence and development of a variety of cancers. However, the effect of miRNAs on giant panda testicular tumor has been little studied. Therefore, this study explored the pathogenesis of giant panda testicular tumor through miRNA and mRNA sequencing, and screened out diagnostic markers of testicular tumor. Combined with phenotypic symptoms and pathological section results, three giant pandas were diagnosed with testicular tumor and divided into tumor group, and three other giant pandas were divided into normal group. A total of 29 differentially expressed miRNAs (DEmiRNAs) were screened by blood miRNA-seq, and 3149 target gene candidates were predicted. Functional enrichment analysis showed that the target genes were mainly involved in intermembrane lipid transfer and ATP-dependent chromatin remodeling. However, only 5 DEmiRNAs were screened by miRNA-seq of blood-derived exosomes and 364 target genes were predicted, which were mainly involved in antigen processing and presentation. In addition, 216 differentially expressed genes (DEGs) were screened by RNA-seq, and functional enrichment analysis showed that tumor-specific DEGs significantly enriched to protein phosphorylation. Spearman correlation analysis of miRNA-mRNA showed that the expressions of miR-331-3p and PKIG were significantly positively correlated (spearman = 0.943, p < 0.01), while the expressions of miR-331-3p and ENSAMEG00000013628 were significantly negatively correlated (spearman= -0.829, p < 0.05). RT-PCR showed that the expression of miR-331-3p was significantly decreased in giant panda with tumor (p < 0.01). blood miRNAs and exosomal miRNAs exhibit distinct regulatory patterns concerning giant panda testicular tumor, potentially reflecting divergent biological processes in the disease's etiology. Meanwhile, miR-331-3p could be used as a potential diagnostic marker for giant panda testicular tumor. Our findings are conducive to the rapid clinical diagnosis of testicular tumor in giant pandas, and are also expected to provide scientific reference for further research on the pathogenesis of testicular tumor.

Critical radicle length window governing loss of dehydration tolerance in germinated Perilla seeds: insights from physiological and transcriptomic analyses.

Perilla (Perilla frutescens L. Britt.) is an important oilseed and medicinal crop that frequently faces seasonal drought stress during seed germination, leading to a loss of dehydration tolerance (DT), which affects seed emergence and significantly reduces yield. DT has been successfully re-established for many species seeds. However, the physiological mechanisms and gene networks that regulate Perilla's response to DT loss remain unclear. Phenotypic analysis determined that the window for DT in Perilla seeds occurs at radicle lengths of 0-4mm. Integrating physiological and transcriptomic analyses revealed that the loss of DT promotes the production of reactive oxygen species (ROS) and regulates oxidase activity and gene expression. This implies that DT may influence seed germination by modulating ROS activity. Four radicle length (i.e., 0, 1, 3, and 4mm) stages were analyzed, and 262 differentially expressed genes (DEGs) were identified that responded to DT. The majority of these genes were associated with epigenetics, cell function, and transport mechanisms. Analysis of expression data shows that desiccation inhibits the signaling network of genes encoding small secreted peptides (SSPs) and receptor-like protein kinases (RLKs). Finally, a relevant network diagram of DT response was proposed. Based on this information, we have revealed the metabolism regulation maps of the four main pathways involving these DEGs (i.e., metabolic pathways, cell cycle, plant hormone signal transduction, and motor proteins). In conclusion, these findings deepen our understanding of gene network responses to DT during Perilla seed germination and provide potential target genes for the genetic improvement of drought resistance in this crop.

Comprehensive assessment of cellular senescence in intestinal immunity and biologic therapy response in ulcerative colitis.

Ulcerative Colitis (UC) is an inflammatory disorder characterized by chronic intestinal inflammation and immune dysregulation. Despite a clear association between cellular senescence and chronic inflammation and immune dysregulation, the mechanisms underlying cellular senescence in UC remain unclear. We screened differentially expressed genes (DEGs) associated with cellular senescence in multiple UC datasets, performed immune infiltration analysis, and constructed clinical diagnostic models. Additionally, we investigated the relationship between key genes related to cellular senescence and disease remission in UC patients undergoing biologic therapy, validating their expression in a single-cell dataset. We identified six DEGs associated with cellular senescence (TWIST1, IGFBP5, MME, IFNG, ME1, FOS). Immune infiltration results indicated strong correlations of four of these genes with immune cells and pathways. Through WGCNA, GO, and KEGG analyses, we found that gene modules strongly associated with the expression of hub genes in cellular senescence were enriched in inflammation-related pathways. In the single-cell dataset, the expression of these six key genes exhibited similarities with Immune infiltration results. Additionally, we constructed a nomogram using these six genes for diagnosing UC, demonstrating good diagnostic capability and clinical efficacy. Kaplan-Meier survival analysis revealed a significant association between changes in the expression levels of these cell genes and disease remission in UC patients undergoing biologic therapy. This study utilizes bioinformatic analysis and machine learning to identify and analyze features associated with cellular senescence in multiple UC datasets. It provides insights into the role of cellular senescence in the premature onset of intestinal aging in UC and offers new perspectives for exploring novel therapeutic targets.

Subtyping colorectal cancer based on septic shock-associated genes: prognosis and immune characteristics

BackgroundSepsis and colorectal cancer (CRC) are leading causes of death. Given their mutual dependence for susceptibility, we used bioinformatics to explore potential connections between septic shock (SS) and CRC.MethodsWe identified 452 co-expressed genes between SS-related differential expression genes (SS-DEGs) and CRC patient-expressed genes (TCGA-CRC genes). CRC samples were categorized into two cluster subgroups through hierarchical clustering. We then compared the prognosis and immune landscapes of the two cluster subgroups through survival analysis, immune microenvironment analysis, and immune therapy response evaluation.ResultsClustering analysis of the 452 CRC patient-expressed SS-DEGs identified two subtypes: SS-like CRC (SL-CRC) and non-SS-like CRC (NSL-CRC). There were no significant differences in overall survival between the CRC subtypes. However, the subtypes displayed significant differences in immune score, stromal score, and ESTIMATE score. Based on immune therapy databases, there were also significant differences in responses to anti-CTLA-4 and anti-PD-1 immune checkpoint inhibitors between the subtypes.ConclusionOur study reveals significant differences in the immune microenvironment and immune therapy responses between SL-CRC and NSL-CRC subtypes. These findings provide a foundation for identifying new therapeutic targets and developing personalized treatment strategies for specific CRC subtypes.

Transcriptome profiling uncovers differentially expressed genes linked to nutritional quality in vegetable soybean.

Vegetative soybean (maodou or edamame) serves as a nutrient-rich food source with significant potential for mitigating global nutritional deficiencies. This study undertook a thorough examination of the nutritional profiles and transcriptomic landscapes of six soybean cultivars, including three common cultivars (Heinong551, Heinong562, and Heinong63) and three fresh maodou cultivars (Heinong527, HeinongXS4, and HeinongXS5). Nutrient analysis of the seeds disclosed notable differences in the levels of protein, fat, soluble sugars, vitamin E, calcium, potassium, magnesium, manganese, iron, and zinc across the cultivars. Through comparative transcriptome profiling and RNA sequencing, distinct variations in differentially expressed genes (DEGs) were identified between fresh and traditional maodou cultivars. Functional enrichment analyses underscored the involvement of DEGs in critical biological processes, such as nutrient biosynthesis, seed development, and stress responses. Additionally, association studies demonstrated robust correlations between specific DEG expression patterns and seed nutrient compositions across the different cultivars. Sankey diagrams illustrated that DEGs are strongly linked with seed quality traits, revealing potential molecular determinants that govern variations in nutritional content. The identified DEGs and their relationships with nutritional profiles offer valuable insights for breeding programs focused on developing cultivars with improved nutritional quality, tailored to specific dietary needs or industrial applications.

Effect of acute exercise on gene expression in peripheral blood mononuclear cells of puberty children.

Studies have shown that acute exercise alters the expression of circulating neutrophil and peripheral blood mononuclear cell (PBMC) genes, affecting a wide range of processes from cellular growth to the promotion of inflammatory and anti-inflammatory responses. In this study, we identified differential gene expression associated with acute exercise and PBMC in puberty children through the GEO database. We utilized bioinformatics technology to analyze the impact of acute exercise on PBMC and identified key genes involving the puberty children. Combining two datasets of gene expression, we identified 197 shared differentially expressed genes (DEGs) in PBMC before and after exercise. We conducted pathway analysis of these DEGs and built a gene co-expression network. The identification of hub genes was achieved through the utilization of protein-protein interaction (PPI) networks. 268 shared DEGs were identified in the GSE11761 dataset in pre- and post-exercise groups, while 352 differential genes were identified between the pre- and post-exercise groups of females in the GSE14642 dataset. A total of 197 shared genes were identified between the two datasets. Seven core genes were identified by MCODE and CytoHubba, namely IL2RB, KLRD1, GZMB, TBX21, PRF1, HAVCR2, and GZMA. Bioinformatics techniques are effective in screening and analyzing PBMC-associated DEGs in children undergoing acute pre- and post-exercise puberty. Microarray analysis of PBMCs in children undergoing puberty can identify molecules that may predict acute exercise responses. This study provides insights for further exploration of the mechanisms and targets of acute exercise on the organism.