ABSTRACT
Interactions between brain-resident and peripheral infiltrated immune cells are thought to contribute to neuroplasticity after cerebral ischemia. However, conventional bulk sequencing makes it challenging to depict this complex immune network. Using single-cell RNA sequencing, we mapped compositional and transcriptional features of peri-infarct immune cells. Microglia were the predominant cell type in the peri-infarct region, displaying a more diverse activation pattern than the typical pro- and anti-inflammatory state, with axon tract-associated microglia (ATMs) being associated with neuronal regeneration. Trajectory inference suggested that infiltrated monocyte-derived macrophages (MDMs) exhibited a gradual fate trajectory transition to activated MDMs. Inter-cellular crosstalk between MDMs and microglia orchestrated anti-inflammatory and repair-promoting microglia phenotypes and promoted post-stroke neurogenesis, with SOX2 and related Akt/CREB signaling as the underlying mechanisms. This description of the brain's immune landscape and its relationship with neurogenesis provides new insight into promoting neural repair by regulating neuroinflammatory responses.
Subject(s)
Humans , Ischemic Stroke , Brain/metabolism , Macrophages , Brain Ischemia/metabolism , Microglia/metabolism , Gene Expression Profiling , Anti-Inflammatory Agents , Neuronal Plasticity/physiology , Infarction/metabolismABSTRACT
Tumor progression is closely related to tumor tissue metabolism and reshaping of the microenvironment. Oral squamous cell carcinoma (OSCC), a representative hypoxic tumor, has a heterogeneous internal metabolic environment. To clarify the relationship between different metabolic regions and the tumor immune microenvironment (TME) in OSCC, Single cell (SC) and spatial transcriptomics (ST) sequencing of OSCC tissues were performed. The proportion of TME in the ST data was obtained through SPOTlight deconvolution using SC and GSE103322 data. The metabolic activity of each spot was calculated using scMetabolism, and k-means clustering was used to classify all spots into hyper-, normal-, or hypometabolic regions. CD4T cell infiltration and TGF-β expression is higher in the hypermetabolic regions than in the others. Through CellPhoneDB and NicheNet cell-cell communication analysis, it was found that in the hypermetabolic region, fibroblasts can utilize the lactate produced by glycolysis of epithelial cells to transform into inflammatory cancer-associated fibroblasts (iCAFs), and the increased expression of HIF1A in iCAFs promotes the transcriptional expression of CXCL12. The secretion of CXCL12 recruits regulatory T cells (Tregs), leading to Treg infiltration and increased TGF-β secretion in the microenvironment and promotes the formation of a tumor immunosuppressive microenvironment. This study delineates the coordinate work axis of epithelial cells-iCAFs-Tregs in OSCC using SC, ST and TCGA bulk data, and highlights potential targets for therapy.
Subject(s)
Humans , Carcinoma, Squamous Cell/metabolism , Squamous Cell Carcinoma of Head and Neck , Mouth Neoplasms/metabolism , Immunosuppression Therapy , Transforming Growth Factor beta , Head and Neck Neoplasms , Gene Expression Profiling , Tumor MicroenvironmentABSTRACT
PURPOSE@#To identify the potential target genes of blast lung injury (BLI) for the diagnosis and treatment.@*METHODS@#This is an experimental study. The BLI models in rats and goats were established by conducting a fuel-air explosive power test in an unobstructed environment, which was subsequently validated through hematoxylin-eosin staining. Transcriptome sequencing was performed on lung tissues from both goats and rats. Differentially expressed genes were identified using the criteria of q ≤ 0.05 and |log2 fold change| ≥ 1. Following that, enrichment analyses were conducted for gene ontology and the Kyoto Encyclopedia of Genes and Genomes pathways. The potential target genes were further confirmed through quantitative real-time polymerase chain reaction and enzyme linked immunosorbent assay.@*RESULTS@#Observations through microscopy unveiled the presence of reddish edema fluid, erythrocytes, and instances of focal or patchy bleeding within the alveolar cavity. Transcriptome sequencing analysis identified a total of 83 differentially expressed genes in both rats and goats. Notably, 49 genes exhibited a consistent expression pattern, with 38 genes displaying up-regulation and 11 genes demonstrating down-regulation. Enrichment analysis highlighted the potential involvement of the interleukin-17 signaling pathway and vascular smooth muscle contraction pathway in the underlying mechanism of BLI. Furthermore, the experimental findings in both goats and rats demonstrated a strong association between BLI and several key genes, including anterior gradient 2, ankyrin repeat domain 65, bactericidal/permeability-increasing fold containing family A member 1, bactericidal/permeability-increasing fold containing family B member 1, and keratin 4, which exhibited up-regulation.@*CONCLUSIONS@#Anterior gradient 2, ankyrin repeat domain 65, bactericidal/permeability-increasing fold containing family A member 1, bactericidal/permeability-increasing fold containing family B member 1, and keratin 4 hold potential as target genes for the prognosis, diagnosis, and treatment of BLI.
Subject(s)
Rats , Animals , Lung Injury/genetics , Goats/genetics , Keratin-4 , Gene Expression Profiling , Gene ExpressionABSTRACT
Long non-coding RNAs (lncRNAs) play a significant role in maintaining tissue morphology and functions, and their precise regulatory effectiveness is closely related to expression patterns. However, the spatial expression patterns of lncRNAs in humans are poorly characterized. Here, we constructed five comprehensive transcriptomic atlases of human lncRNAs covering thousands of major tissue samples in normal and disease states. The lncRNA transcriptomes exhibited high consistency within the same tissues across resources, and even higher complexity in specialized tissues. Tissue-elevated (TE) lncRNAs were identified in each resource and robust TE lncRNAs were refined by integrative analysis. We detected 1 to 4684 robust TE lncRNAs across tissues; the highest number was in testis tissue, followed by brain tissue. Functional analyses of TE lncRNAs indicated important roles in corresponding tissue-related pathways. Moreover, we found that the expression features of robust TE lncRNAs made them be effective biomarkers to distinguish tissues; TE lncRNAs also tended to be associated with cancer, and exhibited differential expression or were correlated with patient survival. In summary, spatial classification of lncRNAs is the starting point for elucidating the function of lncRNAs in both maintenance of tissue morphology and progress of tissue-constricted diseases.
Subject(s)
Humans , Gene Expression Profiling , Neoplasms/genetics , Organ Specificity , RNA, Long Noncoding/genetics , TranscriptomeABSTRACT
Background@#Sepsis is a life-threatening multiple-organ dysfunction caused by a dysregulated host response to infection and is the leading cause of death in non-cardiac intensive care facilities. Early reliable prediction of sepsis outcomes leads to cost-efficient resource allocation and therapeutic strategies. However, there are still no reliable markers to predict the outcome of patients at the initial stage of sepsis. Analyzing transcription profiles enables researchers to predict early outcomes using transcripts and their expression patterns. Transcriptomic profiling of septic patients has been done recently; however, analysis of prognostic outcomes is still scarce.@*Objective@#This study aimed to determine transcriptional indicators that may be useful in the prognosis of the severity of sepsis.@*Methods@#This is a prospective cohort study of Filipino patients admitted for sepsis at the national tertiary referral hospital in Manila, Philippines. We conducted differentially expressed gene analysis, network analyses, and area under the curve study of publicly available datasets of surviving vs. non-surviving sepsis patients to identify candidate prognosticator markers. Quantitative PCR was used to characterize the expression of each marker. A model using ordinal logistic regression analysis was done to determine which among the markers can best predict the outcome of sepsis severity.@*Results@#We identified ACTB, RAC1, STAT3, and UBQLN1 as candidate mRNA prognosticators. The expression of STAT3, a gene involved in immunosuppression, is inversely correlated with the severity of sepsis.@*Conclusion@#Transcriptomic markers such as STAT3 can predict the severity of patients with sepsis. Early detection of its inverse expression may prompt early and more aggressive management of patients.
Subject(s)
Sepsis , Data Mining , Gene Expression ProfilingABSTRACT
Glutamate receptor-like (GLR) is an important class of Ca2+ channel proteins, playing important roles in plant growth and development as well as in response to biotic and abiotic stresses. In this paper, we performed genome-wide identification of banana GLR gene family based on banana genomic data. Moreover, we analyzed the basic physicochemical properties, gene structure, conserved motifs, promoter cis-acting elements, evolutionary relationships, and used real-time fluorescence quantitative polymerase chain reaction (RT-qPCR) to verify the expression patterns of some GLR family members under low temperature of 4 ℃ and different hormone treatments. The results showed that there were 19 MaGLR family members in Musa acuminata, 16 MbGLR family members in Musa balbisiana and 14 MiGLR family members in Musa itinerans. Most of the members were stable proteins and had signal peptides, all of them had 3-6 transmembrane structures. Prediction of subcellular localization indicated that all of them were localized on the plasma membrane and irregularly distributed on the chromosome. Phylogenetic analysis revealed that banana GLRs could be divided into 3 subclades. The results of promoter cis-acting elements and transcription factor binding site prediction showed that there were multiple hormone- and stress-related response elements and 18 TFBS in banana GLR. RT-qPCR analysis showed that MaGLR1.1 and MaGLR3.5 responded positively to low temperature stress and were significantly expressed in abscisic acid/methyl jasmonate treatments. In conclusion, the results of this study suggest that GLR, a highly conserved family of ion channels, may play an important role in the growth and development process and stress resistance of banana.
Subject(s)
Musa/metabolism , Phylogeny , Abscisic Acid/metabolism , Temperature , Stress, Physiological/genetics , Hormones/metabolism , Gene Expression Regulation, Plant , Plant Proteins/metabolism , Gene Expression ProfilingABSTRACT
MADS-box gene family is a significant transcription factor family that plays a crucial role in regulating plant growth, development, signal transduction, and other processes. In order to study the characteristics of MADS-box gene family in Docynia delavayi (Franch.) Schneid. and its expression during different stages of seed germination, this study used seedlings at different stages of germination as materials and screened MADS-box transcription factors from the transcriptome database of D. delavayi using bioinformatics methods based on transcriptome sequencing. The physical and chemical properties, protein conservative motifs, phylogenetic evolution, and expression patterns of the MADS-box transcription factors were analyzed. Quantitative real-time PCR (qRT-PCR) was used to verify the expression of MADS-box gene family members during different stages of seed germination in D. delavayi. The results showed that 81 genes of MADS-box gene family were identified from the transcriptome data of D. delavayi, with the molecular weight distribution ranged of 6 211.34-173 512.77 Da and the theoretical isoelectric point ranged from 5.21 to 10.97. Phylogenetic analysis showed that the 81 genes could be divided into 15 subgroups, among which DdMADS27, DdMADS42, DdMADS45, DdMADS46, DdMADS53, DdMADS61, DdMADS76, DdMADS77 and DdMADS79 might be involved in the regulation of ovule development in D. delavayi. The combination of the transcriptome data and the qRT-PCR analysis results of D. delavayi seeds indicated that DdMADS25 and DdMADS42 might be involved in the regulation of seed development, and that DdMADS37 and DdMADS38 might have negative regulation effects on seed dormancy. Previous studies have reported that the MIKC* subgroup is mainly involved in regulating flower organ development. For the first time, we found that the transcription factors of the MIKC* subgroup exhibited a high expression level at the early stage of seed germination, so we speculated that the MIKC* subgroup played a regulatory role in the process of seed germination. To verify the accuracy of this speculation, we selected DdMADS60 and DdMADS75 from the MIKC* subgroup for qRT-PCR experiments, and the experimental results were consistent with the expression trend of transcriptome sequencing. This study provides a reference for further research on the biological function of D. delavayi MADS-box gene family from the perspective of molecular evolution.
Subject(s)
MADS Domain Proteins/metabolism , Phylogeny , Gene Expression Regulation, Plant , Genes, Plant , Transcription Factors/genetics , Plant Proteins/metabolism , Gene Expression ProfilingABSTRACT
To explore the differentially expressed genes (DEGs) related to biosynthesis of active ingredients in wolfberry fruits of different varieties of Lycium barbarum L. and reveal the molecular mechanism of the differences of active ingredients, we utilized Illumina NovaSeq 6000 high-throughput sequencing technology to conduct transcriptome sequencing on the fruits of 'Ningqi No.1' and 'Ningqi No.7' during the green fruit stage, color turning stage and maturity stage. Subsequently, we compared the profiles of related gene expression in the fruits of the two varieties at different development stages. The results showed that a total of 811 818 178 clean reads were obtained, resulting in 121.76 Gb of valid data. There were 2 827, 2 552 and 2 311 DEGs obtained during the green fruit stage, color turning stage and maturity stage of 'Ningqi No. 1' and 'Ningqi No. 7', respectively, among which 2 153, 2 050 and 1 825 genes were annotated in six databases, including gene ontology (GO), Kyoto encyclopedia of genes and genomes (KEGG) and clusters of orthologous groups of proteins (KOG). In GO database, 1 307, 865 and 624 DEGs of green fruit stage, color turning stage and maturity stage were found to be enriched in biological processes, cell components and molecular functions, respectively. In the KEGG database, the DEGs at three developmental stages were mainly concentrated in metabolic pathways, biosynthesis of secondary metabolites and plant-pathogen interaction. In KOG database, 1 775, 1 751 and 1 541 DEGs were annotated at three developmental stages, respectively. Searching the annotated genes against the PubMed database revealed 18, 26 and 24 DEGs related to the synthesis of active ingredients were mined at the green fruit stage, color turning stage and maturity stage, respectively. These genes are involved in carotenoid, flavonoid, terpenoid, alkaloid, vitamin metabolic pathways, etc. Seven DEGs were verified by RT-qPCR, which showed consistent results with transcriptome sequencing. This study provides preliminary evidences for the differences in the content of active ingredients in different Lycium barbarum L. varieties from the transcriptional level. These evidences may facilitate further exploring the key genes for active ingredients biosynthesis in Lycium barbarum L. and analyzing their expression regulation mechanism.
Subject(s)
Flavonoids/metabolism , Fruit/genetics , Gene Expression Profiling/methods , Gene Expression Regulation, Plant , Lycium/metabolism , Metabolic Networks and Pathways , TranscriptomeABSTRACT
Objective: Bioinformatics analysis was used to screen differentially expressed genes (DEGs) in macrophages of sepsis myocardial injury and to verify key genes. Methods: Experiment 1 (gene chip and bioinformatics analysis): The gene chip data GSE104342 of cardiac macrophages in septic mice was downloaded from Gene Expression Omnibus database. DEGs were obtained by R language analysis. DAVID online database was used to obtain gene ontology and kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis of DEGs. STRING online database was used for protein-protein interaction network analysis of DEGs, and then key genes were screened by using Cytoscape software and molecular complex detection (MCODE) plug-ins. Experiment 2 (sepsis model construction and related protein verification): Ten male C57BL/6 mice, aged 8-14 weeks. Five mice were randomly selected as control group, and 5 mice were selected as the sepsis group by building a mice sepsis model in vivo. Echocardiography was used to detect the cardiac function. Hematoxylin-eosin staining was used to assess the cardiac morphology. TUNEL staining was used to evaluate cardiomyocyte apoptosis. Immunofluorescence staining was used to detect the expression of differentiation antigen cluster 206 (CD206),inducible nitric oxide synthases (iNOS),F4/80,suppressor of cytokine signaling 3 (Socs3) ,interleukin 1 receptor antagonist (Il1rn) and chemokine C-C motif ligand 7 (Ccl7) protein. RAW264.7 macrophages were cultured in vitro and divided into 2 groups: LPS groupstimulated by lipopolysaccharide (LPS, 1 mg/L) and blank control group treated with equal-volume phosphate buffer solution. Reverse transcription-polymerase chain reaction (RT-PCR) was used to evaluate the expression of Socs3, Il1rn and Ccl7 in vitro. Results: Experiment 1: 24 647 genes were screened in GSE104342 dataset and 177 genes (0.72%) were differential expression, including 120 up-regulated genes and 57 down-regulated genes. Gene ontology enrichment analysis showed that DEGs were mainly involved in inflammatory response, immune response, apoptosis regulation and antigen processing and presentation. KEGG signaling pathway analysis showed that DEGs in cardiac macrophages of septic mice were mainly enriched in cytokine-cytokine receptor interaction, tumor necrosis factor signaling pathway, NOD like receptor signaling pathway. Three hub genes were obtained by STRING and Cytoscape analysis, including Socs3, Il1rn and Ccl7. Experiment 2: In vivo, it was found that compared with the control group, the cardiac function of the sepsis mice decreased significantly, the myocardial cells were significantly edema, inflammatory cell infiltration, myocardial fiber rupture, some myocardial nuclei dissolved and disappeared, and the cardiomyocyte apoptosis increased, suggesting that the sepsis myocardial injury model of mice was successfully constructed. Compared with the control group, the expression of CD206 in the myocardium of septic mice was down-regulated, the expression of iNOS, F4/80, Socs3, Il1rn and Ccl7 were up-regulated. In addition, there was co-localization between Socs3, Il1rn, Ccl7 and F4/80 protein. Compared with the blank control group, the expression of Socs3, Il1rn and Ccl7 significantly upregulated after LPS intervention in vitro by RT-PCR. Conclusions: The selected key genes Socs3, Il1rn and Ccl7 were up-regulated in myocardial macrophages of septic mice. Socs3, Il1rn and Ccl7 are expected to become new targets for the diagnosis and treatment of sepsis cardiac injury.
Subject(s)
Male , Mice , Animals , Lipopolysaccharides , Mice, Inbred C57BL , Myocardium , Computational Biology , Sepsis , Macrophages , Cytokines , Gene Expression ProfilingABSTRACT
Objective: Using bioinformatics methods to analyze the core pathogenic genes and related pathways in elderly osteoporosis. Methods: From November 2020 and August 2021, eight elderly osteoporosis patients who received treatment and five healthy participants who underwent physical examinations in Beijing Jishuitan Hospital were selected as subjects. The expression level of RNA in the peripheral blood of eight elderly osteoporosis patients and five healthy participants was collected for high-throughput transcriptome sequencing and analysis. The gene ontology (GO) analysis Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was performed for the differentially expressed genes (DEGs). The protein-protein interaction (PPI) network was constructed using the STRING website and Cytoscape software, and the most significant modules and hub genes were screened out. Results: Among the eight elderly osteoporosis patients, there were seven females and one male, with an average age of 72.4 years (SD=4.2). Among the five healthy participants, there were four females and one male, with an average age of 68.2 years (SD=5.7). A total of 1 635 DEGs (847 up-regulated and 788 down-regulated) were identified. GO analysis revealed that the molecular functions of DEGs were mainly enriched in structural constituents of the ribosome, protein dimerization activity, and cellular components were mainly enriched in the nucleosome, DNA packaging complex, cytosolic part, protein-DNA complex and the cytosolic ribosome. KEGG pathway analysis showed that DEGs were mainly enriched in systemic lupus erythematosus and ribosome. Gene UBA52, UBB, RPS27A, RPS15, RPS12, RPL13A, RPL23A, RPL10A, RPS25 and RPS6 were selected and seven of them could encode ribosome proteins. Conclusion: The pathogenesis of elderly osteoporosis may be associated with ribosome-related genes and pathways.
Subject(s)
Female , Humans , Male , Aged , Gene Expression Profiling/methods , Transcriptome , Protein Interaction Maps/genetics , Computational Biology/methods , Osteoporosis/geneticsABSTRACT
Objective: To identify the expression profile of circular RNA (circRNA) in placenta of pre-eclampsia (PE) pregnant women by high-throughput sequencing, and to construct the circRNA-microRNA (miRNA)-messenger RNA (mRNA) interaction network, so as to reveal the related pathways and regulatory mechanisms of PE. Methods: The clinical data and placentas of 42 women with PE (PE group) and 30 normal pregnant women (control group) who delivered in West China Second University Hospital from November 2019 to June 2021 were collected. (1) High-throughput sequencing was used to establish the differentially expressed circRNA profiles in placental tissues of 5 pairs of PE group and the control group. (2) Real-time quantitative PCR (qRT-PCR) was used to verify the expression levels of 6 differentially expressed circRNAs in placental tissues of PE group and control group. (3) Bioinformatics analysis was used to predict the target miRNA and analyze the co-expressed mRNA to construct a competitive endogenous RNA (ceRNA) network. The differentially expressed circRNAs were analyzed by Gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathways. (4) Logistic regression analysis, Pearson correlation and Kendall's tau-b correlation analysis were used to test the correlation between the three differentially expressed circRNAs and the risk of PE and clinical characteristics. (5) circRNA_05393 was selected for subsequent functional study. Small interfering RNA (siRNA) and overexpression plasmid were used to knock down or increase the expression level of circRNA_05393 in trophoblast cell line HTR-8/SVneo cells, respectively. Transwell assay was used to detect the migration and invasion ability of the trophoblasts in vitro. Cell counting kit-8 assay was used to detect the proliferation ability of the trophoblasts. Results: (1) Seventy-two differentially expressed circRNAs were identified by high-throughput sequencing, of which 35 were up-regulated and 37 were down-regulated. (2) qRT-PCR showed that compared with the control group, circRNA_00673 (1.306±0.168 vs 2.059±0.242; t=2.356, P=0.021) and circRNA_07796 (1.275±0.232 vs 1.954±0.230; t=2.018, P=0.047) were significantly increased, while circRNA_05393 (1.846±0.377 vs 0.790±0.094; t=3.138, P=0.002) was significantly decreased. (3) The circRNA-miRNA-mRNA interaction network contained 3 circRNAs, 8 miRNAs and 53 mRNAs. GO functional annotation analysis showed that the biological process was mainly enriched in iron ion homeostasis, membrane depolarization during action potential and neuronal action potential. In terms of cellular components, they were mainly enriched in cytoskeleton and membrane components. In terms of molecular function, they were mainly enriched in the activity of voltage-gated sodium channel and basic amino acid transmembrane transporter. KEGG pathway enrichment analysis showed that mRNAs in the interaction network were mainly enriched in complement and coagulation cascade, glycine, serine and threonine metabolism, p53 signaling pathway and peroxisome proliferators-activated receptors (PPAR) signaling pathway. (4) Logistic regression analysis showed that down-regulation of circRNA_05393 expression was a risk factor for PE (OR=0.044, 95%CI: 0.003-0.596; P=0.019). Correlation analysis showed that circRNA_05393 was significantly correlated with systolic blood pressure and diastolic blood pressure in PE pregnant women (both P<0.05). (5) Knock down or overexpression of circRNA_05393 significantly reduced or increased the migration and invasion abilities of HTR-8/SVneo cells (all P<0.05), but had no significant effect on the ability of tube formation and proliferation (all P>0.05). Conclusions: The construction of circRNA expression profile in placenta and the exploration of circRNA-miRNA-mRNA interaction network provide the possibility to reveal the regulatory mechanism of specific circRNA involved in PE. Inhibition of circRNA_05393 may induce the progression of PE by reducing the migration and invasion of trophoblasts.
Subject(s)
Female , Humans , Pregnancy , MicroRNAs/metabolism , RNA, Circular/metabolism , RNA, Messenger/metabolism , Pre-Eclampsia/metabolism , Placenta/metabolism , RNA/metabolism , RNA, Small Interfering , Gene Expression ProfilingABSTRACT
Gelsemium elegans is a traditional Chinese herb of medicinal importance, with indole terpene alkaloids as its main active components. To study the expression of the most suitable housekeeping reference genes in G. elegans, the root bark, stem segments, leaves and inflorescences of four different parts of G. elegans were used as materials in this study. The expression stability of 10 candidate housekeeping reference genes (18S, GAPDH, Actin, TUA, TUB, SAND, EF-1α, UBC, UBQ, and cdc25) was assessed through real-time fluorescence quantitative PCR, GeNorm, NormFinder, BestKeeper, ΔCT, and RefFinder. The results showed that EF-1α was stably expressed in all four parts of G. elegans and was the most suitable housekeeping gene. Based on the coexpression pattern of genome, full-length transcriptome and metabolome, the key candidate targets of 18 related genes (AS, AnPRT, PRAI, IGPS, TSA, TSB, TDC, GES, G8H, 8-HGO, IS, 7-DLS, 7-DLGT, 7-DLH, LAMT, SLS, STR, and SGD) involved in the Gelsemium alkaloid biosynthesis were obtained. The expression of 18 related enzyme genes were analyzed by qRT-PCR using the housekeeping gene EF-1α as a reference. The results showed that these genes' expression and gelsenicine content trends were correlated and were likely to be involved in the biosynthesis of the Gelsemium alkaloid, gelsenicine.
Subject(s)
Genes, Essential , Gelsemium/genetics , Peptide Elongation Factor 1/genetics , Transcriptome , Gene Expression Profiling/methods , Alkaloids , Real-Time Polymerase Chain Reaction/methods , Reference StandardsABSTRACT
Objective To screen antigen targets for immunotherapy by analyzing over-expressed genes, and to identify significant pathways and molecular mechanisms in esophageal cancer by using bioinformatic methods such as enrichment analysis, protein-protein interaction (PPI) network, and survival analysis based on the Gene Expression Omnibus (GEO) database.Methods By screening with highly expressed genes, we mainly analyzed proteins MUC13 and EPCAM with transmembrane domain and antigen epitope from TMHMM and IEDB websites. Significant genes and pathways associated with the pathogenesis of esophageal cancer were identified using enrichment analysis, PPI network, and survival analysis. Several software and platforms including Prism 8, R language, Cytoscape, DAVID, STRING, and GEPIA platform were used in the search and/or figure creation.Results Genes MUC13 and EPCAM were over-expressed with several antigen epitopes in esophageal squamous cell carcinoma (ESCC) tissue. Enrichment analysis revealed that the process of keratinization was focused and a series of genes were related with the development of esophageal cancer. Four genes including ALDH3A1, C2, SLC6A1,and ZBTB7C were screened with significant P value of survival curve.Conclusions Genes MUC13 and EPCAM may be promising antigen targets or biomarkers for esophageal cancer. Keratinization may greatly impact the pathogenesis of esophageal cancer. Genes ALDH3A1, C2, SLC6A1,and ZBTB7C may play important roles in the development of esophageal cancer.
Subject(s)
Humans , Esophageal Neoplasms/metabolism , Esophageal Squamous Cell Carcinoma/metabolism , Epithelial Cell Adhesion Molecule/metabolism , Gene Expression Profiling/methods , Gene Regulatory Networks , Gene Expression , Gene Expression Regulation, Neoplastic , Intracellular Signaling Peptides and ProteinsABSTRACT
Objective To identify immune-related molecular markers in an attempt to predict prognosis of colon adenocarcinoma (COAD). Methods Immune related genes (IREGs) was analyzed based on the TCGA database. Weighted gene co-expression network analysis (WGCNA) and Cox regression analysis were used to establish risk models. According to the median risk score, COAD patients were divided into high risk and low risk groups. The prognostic difference were compared between the two groups. The function of the model was validated using GEO. Results A total of 1015 IREGs was obtained. The established model consisted of three genes: RAR related orphan receptor C (RORC), leucine-rich repeat Fli-I-interacting protein 2 (LRRFIP2) and lectin galactoside-binding soluble galectin 4 (LGALS4). The high-risk group had significantly poorer prognosis than low-risk group in the GEO database, and it was validated using a GEO database. Further analysis via univariate and multivariate Cox regression analyses revealed that risk model could function as independent prognostic factor for COAD patients. Conclusion The risk model based on IREGs can predict the prognosis of patients with COAD.
Subject(s)
Humans , Prognosis , Adenocarcinoma/genetics , Colonic Neoplasms/genetics , Gene Expression Profiling , LectinsABSTRACT
Objective To investigate the effects of lipopolysaccharide (LPS) on human pulmonary vascular endothelial cells (HPVECs) cytoskeleton and perform biological analysis of the microRNA (miRNA) spectrum. Methods The morphology of HPVECs was observed by microscope, the cytoskeleton by FITC-phalloidin staining, and the expression of VE-cadherin was detected by immunofluorescence cytochemical staining; the tube formation assay was conducted to examine the angiogenesis, along with cell migration test to detect the migration, and JC-1 mitochondrial membrane potential to detect the apoptosis. Illumina small-RNA sequencing was used to identify differentially expressed miRNAs in NC and LPS group. The target genes of differentially expressed miRNAs were predicted by miRanda and TargetScan, and the functional and pathway enrichment analysis was performed on Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Further biological analysis of related miRNAs was carried out. Results After the LPS got induced, the cells became round and the integrity of cytoskeleton was destroyed. The decreased expression of VE-cadherin was also observed, along with the decreased ability of angiogenesis and migration, and increased apoptosis. Sequencing results showed a total of 229 differential miRNAs, of which 84 miRNA were up-regulated and 145 miRNA were down-regulated. The target gene prediction and functional enrichment analysis of these differential miRNA showed that they were mainly concentrated in pathways related to cell connection and cytoskeleton regulation, cell adhesion process and inflammation. Conclusion In vitro model of lung injury, multiple miRNAs are involved in the process of HPVECs cytoskeleton remodeling, the reduction of barrier function, angiogenesis, migration and apoptosis.
Subject(s)
Humans , Lipopolysaccharides/pharmacology , Endothelial Cells/metabolism , MicroRNAs/metabolism , Lung/metabolism , Cytoskeleton , Gene Expression ProfilingABSTRACT
OBJECTIVES@#Laryngeal cancer (LC) is a globally prevalent and highly lethal tumor. Despite extensive efforts, the underlying mechanisms of LC remain inadequately understood. This study aims to conduct an innovative bioinformatic analysis to identify hub genes that could potentially serve as biomarkers or therapeutic targets in LC.@*METHODS@#We acquired a dataset consisting of 117 LC patient samples, 16 746 LC gene RNA sequencing data points, and 9 clinical features from the Cancer Genome Atlas (TCGA) database in the United States. We employed weighted gene co-expression network analysis (WGCNA) to construct multiple co-expression gene modules. Subsequently, we assessed the correlations between these co-expression modules and clinical features to validate their associations. We also explored the interplay between modules to identify pivotal genes within disease pathways. Finally, we used the Kaplan-Meier plotter to validate the correlation between enriched genes and LC prognosis.@*RESULTS@#WGCNA analysis led to the creation of a total of 16 co-expression gene modules related to LC. Four of these modules (designated as the yellow, magenta, black, and brown modules) exhibited significant correlations with 3 clinical features: The age of initial pathological diagnosis, cancer status, and pathological N stage. Specifically, the yellow and magenta gene modules displayed negative correlations with the age of pathological diagnosis (r=-0.23, P<0.05; r=-0.33, P<0.05), while the black and brown gene modules demonstrated negative associations with cancer status (r=-0.39, P<0.05; r=-0.50, P<0.05). The brown gene module displayed a positive correlation with pathological N stage. Gene Ontology (GO) enrichment analysis identified 77 items, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis identified 30 related signaling pathways, including the calcium signaling pathway, cytokine-cytokine receptor interaction, neuro active ligand-receptor interaction, and regulation of lipolysis in adipocytes, etc. Consequently, central genes within these modules that were significantly linked to the overall survival rate of LC patients were identified. Central genes included CHRNB4, FOXL2, KCNG1, LOC440173, ADAMTS15, BMP2, FAP, and KIAA1644.@*CONCLUSIONS@#This study, utilizing WGCNA and subsequent validation, pinpointed 8 genes with potential as gene biomarkers for LC. These findings offer valuable references for the clinical diagnosis, prognosis, and treatment of LC.
Subject(s)
Humans , Laryngeal Neoplasms/genetics , Rosaniline Dyes , Biomarkers , Adipocytes , Gene Regulatory Networks , Gene Expression ProfilingABSTRACT
Dental primary afferent (DPA) neurons and proprioceptive mesencephalic trigeminal nucleus (MTN) neurons, located in the trigeminal ganglion and the brainstem, respectively, are essential for controlling masticatory functions. Despite extensive transcriptomic studies on various somatosensory neurons, there is still a lack of knowledge about the molecular identities of these populations due to technical challenges in their circuit-validated isolation. Here, we employed high-depth single-cell RNA sequencing (scRNA-seq) in combination with retrograde tracing in mice to identify intrinsic transcriptional features of DPA and MTN neurons. Our transcriptome analysis revealed five major types of DPA neurons with cell type-specific gene enrichment, some of which exhibit unique mechano-nociceptive properties capable of transmitting nociception in response to innocuous mechanical stimuli in the teeth. Furthermore, we discovered cellular heterogeneity within MTN neurons that potentially contribute to their responsiveness to mechanical stretch in the masseter muscle spindles. Additionally, DPA and MTN neurons represented sensory compartments with distinct molecular profiles characterized by various ion channels, receptors, neuropeptides, and mechanoreceptors. Together, our study provides new biological insights regarding the highly specialized mechanosensory functions of DPA and MTN neurons in pain and proprioception.
Subject(s)
Animals , Mice , Neurons , Proprioception , Gene Expression Profiling , Pain , Sequence Analysis, RNAABSTRACT
A small proportion of mononuclear diploid cardiomyocytes (MNDCMs), with regeneration potential, could persist in adult mammalian heart. However, the heterogeneity of MNDCMs and changes during development remains to be illuminated. To this end, 12 645 cardiac cells were generated from embryonic day 17.5 and postnatal days 2 and 8 mice by single-cell RNA sequencing. Three cardiac developmental paths were identified: two switching to cardiomyocytes (CM) maturation with close CM-fibroblast (FB) communications and one maintaining MNDCM status with least CM-FB communications. Proliferative MNDCMs having interactions with macrophages and non-proliferative MNDCMs (non-pMNDCMs) with minimal cell-cell communications were identified in the third path. The non-pMNDCMs possessed distinct properties: the lowest mitochondrial metabolisms, the highest glycolysis, and high expression of Myl4 and Tnni1. Single-nucleus RNA sequencing and immunohistochemical staining further proved that the Myl4+Tnni1+ MNDCMs persisted in embryonic and adult hearts. These MNDCMs were mapped to the heart by integrating the spatial and single-cell transcriptomic data. In conclusion, a novel non-pMNDCM subpopulation with minimal cell-cell communications was unveiled, highlighting the importance of microenvironment contribution to CM fate during maturation. These findings could improve the understanding of MNDCM heterogeneity and cardiac development, thus providing new clues for approaches to effective cardiac regeneration.
Subject(s)
Animals , Mice , Diploidy , Heart , Myocytes, Cardiac/metabolism , Cell Communication , Gene Expression Profiling , Mitochondria , Regeneration , Mammals/geneticsABSTRACT
Objective To identify immune-related dysregulation mechanisms and potential diagnostic predictive biomarkers in osteoporosis. Methods Gene expression data for both osteoporosis and control populations were retrieved from the GSE35958 and GSE56815 datasets. Immune-related differentially expressed genes (DEGs) were obtained by screening DEGs and were compared with the immunology database and analysis portal (ImmPort) database. Enrichment analysis of these immune-related DEGs was conducted using the Clusterprofiler software package. A protein-protein interaction network was built with the STRING database, which is a search tool for finding interacting genes/proteins, and the top 10 genes with the highest network connectivity were identified as candidate genes. Subsequently, the diagnostic predictive effect of candidate genes was evaluated using receiver operating characteristic (ROC) curves, logistic regression, and column plots. Finally, PCR and Western blot analysis were applied to detect the differential expression of these genes in bone marrow tissue of patients with osteoporosis. Results A total of 138 immune-related DEGs were obtained through intersection analysis. The results of the enrichment analysis indicated that these genes were involved in biological functions such as immune inflammation and signaling pathways including T cell receptors, mitogen activated protein kinase (MAPK), rat sarcoma virus oncogene homologs (Ras), osteoclast differentiation, and B cell receptors. In addition, among the candidate genes, upregulated vascular endothelial growth factor A (VEGFA) and epidermal growth factor receptor (EGFR) and downregulated AKT1, SRC, and JUN in osteoporosis showed the highest connectivity. Among them, VEGFA, EGFR, JUN, and AKT1 demonstrated the best diagnostic predictive value. Conclusion The screening of immune-related DEGs will enhance the understanding of osteoporosis and facilitate the development of immunotherapy targets.
Subject(s)
Humans , Vascular Endothelial Growth Factor A/genetics , Biomarkers , Osteoporosis/genetics , Computational Biology/methods , ErbB Receptors/genetics , Gene Expression Profiling/methodsABSTRACT
OBJECTIVES@#To investigate possible cross-talk genes, associated pathways, and transcription factors between chronic periodontitis (CP) and chronic obstructive pulmonary disease (COPD).@*METHODS@#The gene expression profiles of CP (GSE10334 and GSE16134) and COPD (GSE76925) were downloaded from the GEO database. Differential expression and functional clustering analyses were performed. The protein‑protein interaction (PPI) network was constructed. The core cross-talk genes were filtered using four topological analysis algorithms and modular segmentation. Then, functional clustering analysis was performed again.@*RESULTS@#GSE10334 detected 164 differentially expressed genes (DEGs) (119 upregulated and 45 downregulated). GSE16134 identified 208 DEGs (154 upregulated and 54 downregulated). GSE76925 identified 1 408 DEGs (557 upregulated and 851 downregulated). The PPI network included 21 nodes and 20 edges. The final screening included seven cross-talk genes: CD79A, FCRLA, CD19, IRF4, CD27, SELL, and CXCL13. Relevant pathways included primary immunodeficiency, the B-cell receptor signaling pathway, and cytokine-cytokine receptor interaction.@*CONCLUSIONS@#This study indicates the probability of shared pathophysiology between CP and COPD, and their cross-talk genes, associated pathways, and transcription factors may offer novel concepts for future mechanistic investigations.