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.
Humans ; Ischemic Stroke ; Brain/metabolism* ; Macrophages ; Brain Ischemia/metabolism* ; Microglia/metabolism* ; Gene Expression Profiling ; Anti-Inflammatory Agents ; Neuronal Plasticity/physiology* ; Infarction/metabolism*

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.
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 Microenvironment

Humans ; Female ; Breast Neoplasms/genetics* ; Prognosis ; Gene Expression Profiling ; Biomarkers, Tumor/genetics* ; Gene Expression Regulation, Neoplastic/genetics* ; Receptor, ErbB-2/metabolism* ; Gene Regulatory Networks/genetics*

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.
Musa/metabolism* ; Phylogeny ; Abscisic Acid/metabolism* ; Temperature ; Stress, Physiological/genetics* ; Hormones/metabolism* ; Gene Expression Regulation, Plant ; Plant Proteins/metabolism* ; Gene Expression Profiling

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.
MADS Domain Proteins/metabolism* ; Phylogeny ; Gene Expression Regulation, Plant ; Genes, Plant ; Transcription Factors/genetics* ; Plant Proteins/metabolism* ; Gene Expression Profiling

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.
Flavonoids/metabolism* ; Fruit/genetics* ; Gene Expression Profiling/methods* ; Gene Expression Regulation, Plant ; Lycium/metabolism* ; Metabolic Networks and Pathways ; Transcriptome

Uridine diphosphate glycosyltransferase(UGT) is a highly conserved protein in plants, which usually functions in secondary metabolic pathways. This study used the Hidden Markov Model(HMM) to screen out members of UGT gene family in the whole genome of Dendrobium officinale, and 44 UGT genes were identified. Bioinformatics was used to analyze the structure, phylogeny, and promoter region components of D. officinale genes. The results showed that UGT gene family could be divided into four subfamilies, and UGT gene structure was relatively conserved in each subfamily, with nine conserved domains. The upstream promoter region of UGT gene contained a variety of cis-acting elements related to plant hormones and environmental factors, indicating that UGT gene expression may be induced by plant hormones and external environmental factors. UGT gene expression in different tissues of D. officinale was compared, and UGT gene expression was found in all parts of D. officinale. It was speculated that UGT gene played an important role in many tissues of D. officinale. Through transcriptome analysis of D. officinale mycorrhizal symbiosis environment, low temperature stress, and phosphorus deficiency stress, this study found that only one gene was up-regulated in all three conditions. The results of this study can help understand the functions of UGT gene family in Orchidaceae plants and provide a basis for further study on the molecular regulation mechanism of polysaccharide metabolism pathway in D. officinale.
Dendrobium/genetics* ; Plant Growth Regulators ; Glycosyltransferases/metabolism* ; Gene Expression Profiling ; Mycorrhizae ; Phylogeny ; Plant Proteins/metabolism*

The immunomodulatory effect of Saposhnikoviae Radix polysaccharide(SRP) was evaluated based on the zebrafish mo-del, and its mechanism was explored by transcriptome sequencing and real-time fluorescence-based quantitative PCR(RT-qPCR). The immune-compromised model was induced by navelbine in the immunofluorescence-labeled transgenic zebrafish Tg(lyz: DsRed), and the effect of SRP on the density and distribution of macrophages in zebrafish was evaluated. The effect of SRP on the numbers of macrophages and neutrophils in wild-type AB zebrafish was detected by neutral red and Sudan black B staining. The content of NO in zebrafish was detected by DAF-FM DA fluorescence probe. The content of IL-1β and IL-6 in zebrafish was detected by ELISA. The differentially expressed genes(DEGs) of zebrafish in the blank control group, the model group, and the SRP treatment group were analyzed by transcriptome sequencing. The immune regulation mechanism was analyzed by Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment, and the expression levels of key genes were verified by RT-qPCR. The results showed that SRP could significantly increase the density of immune cells in zebrafish, increase the number of macrophages and neutrophils, and reduce the content of NO, IL-1β, and IL-6 in immune-compromised zebrafish. The results of transcriptome sequencing analysis showed that SRP could affect the expression level of immune-related genes on Toll-like receptor pathway and herpes simplex infection pathway to affect the release of downstream cytokines and interferon, thereby completing the activation process of T cells and playing a role in regulating the immune activity of the body.
Animals ; Zebrafish/genetics* ; Interleukin-6/genetics* ; Gene Expression Profiling ; Cytokines/genetics* ; Macrophages ; Transcriptome

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.
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 Proteins

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.
Humans ; Prognosis ; Adenocarcinoma/genetics* ; Colonic Neoplasms/genetics* ; Gene Expression Profiling ; Lectins