AIM OF STUDY: The overall aim of this study was to investigate the gene expression profile of Ligno TG-K via de novo RNA-seq and pathway analysis. We also aimed to identify highly expressed genes encoding compounds that contribute to its cytotoxic and antioxidant properties, as well as perform a comparative transcriptomics analysis between Ligno TG-K and its sister species, L. rhinocerus TM02®.
MATERIALS AND METHODS: Total RNA from fresh 3-month-old cultivated L. tigris sclerotia (Ligno TG-K) was extracted and analyzed via de novo RNA sequencing. Expressed genes were analyzed using InterPro and NCBI-Nr databases for domain identification and homology search. Functional categorization based on gene functions and pathways was performed using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Clusters of Orthologous Genes (COG) databases. Selected genes were subsequently subjected to phylogenetic analysis.
RESULTS: Our transcriptomics analysis of Ligno TG-K revealed that 68.06% of its genes are expressed in the sclerotium; 80.38% of these were coding transcripts. Our analysis identified highly expressed transcripts encoding proteins with prospective medicinal properties. These included serine proteases (FPKM = 7356.68), deoxyribonucleases (FPKM = 3777.98), lectins (FPKM = 3690.87), and fungal immunomodulatory proteins (FPKM = 2337.84), all of which have known associations with anticancer activities. Transcripts linked to proteins with antioxidant activities, such as superoxide dismutase (FPKM = 1161.69) and catalase (FPKM = 1905.83), were also highly expressed. Results of our sequence alignments revealed that these genes and their orthologs can be found in other mushrooms. They exhibit significant sequence similarities, suggesting possible parallels in their anticancer and antioxidant bioactivities.
CONCLUSION: This study is the first to provide a reference transcriptome profile of genes expressed in the sclerotia of L. tigris. The current study also presents distinct COG profiles of highly expressed genes in Ligno TG-K and L. rhinocerus TM02®, highlighting that any distinctions uncovered may be attributed to their interspecies variations and inherent characteristics that are unique to each species. Our findings suggest that Ligno TG-K contains bioactive compounds with prospective medicinal properties that warrant further investigations.
CLASSIFICATION: Systems biology and omics.
METHODS: Based on the EM transcriptomic datasets GSE7305 and GSE23339, as well as the IBD transcriptomic datasets GSE87466 and GSE126124, differential gene analysis was performed using the limma package in the R environment. Co-expressed differentially expressed genes were identified, and a protein-protein interaction (PPI) network for the differentially expressed genes was constructed using the 11.5 version of the STRING database. The MCODE tool in Cytoscape facilitated filtering out protein interaction subnetworks. Key genes in the PPI network were identified through two topological analysis algorithms (MCC and Degree) from the CytoHubba plugin. Upset was used for visualization of these key genes. The diagnostic value of gene expression levels for these key genes was assessed using the Receiver Operating Characteristic (ROC) curve and Area Under the Curve (AUC) The CIBERSORT algorithm determined the infiltration status of 22 immune cell subtypes, exploring differences between EM and IBD patients in both control and disease groups. Finally, different gene expression trends shared by EM and IBD were input into CMap to identify small molecule compounds with potential therapeutic effects.
RESULTS: 113 differentially expressed genes (DEGs) that were co-expressed in EM and IBD have been identified, comprising 28 down-regulated genes and 86 up-regulated genes. The co-expression differential gene of EM and IBD in the functional enrichment analyses focused on immune response activation, circulating immunoglobulin-mediated humoral immune response and humoral immune response. Five hub genes (SERPING1、VCAM1、CLU、C3、CD55) were identified through the Protein-protein Interaction network and MCODE.High Area Under the Curve (AUC) values of Receiver Operating Characteristic (ROC) curves for 5hub genes indicate the predictive ability for disease occurrence.These hub genes could be used as potential biomarkers for the development of EM and IBD. Furthermore, the CMap database identified a total of 9 small molecule compounds (TTNPB、CAY-10577、PD-0325901 etc.) targeting therapeutic genes for EM and IBD.
DISCUSSION: Our research revealed common pathogenic mechanisms between EM and IBD, particularly emphasizing immune regulation and cell signalling, indicating the significance of immune factors in the occurence and progression of both diseases. By elucidating shared mechanisms, our study provides novel avenues for the prevention and treatment of EM and IBD.
METHODS: Circulating CD8+ T cells were analysed for differentiation status (CD45RO, CCR7), markers of activation (CD69 and CD25) and proliferation (Ki-67) in 14 newly diagnosed GCA patients and 18 healthy controls by flow cytometry. Proliferative capacity of CD8+ T cells upon anti-CD3 and anti-CD3/28 in vitro stimulation was assessed. Single-cell RNA sequencing of peripheral blood mononuclear cells of patients and controls (n = 3 each) was performed for mechanistic insight. Immunohistochemistry was used to detect CD3, CD8, Ki-67, TNF-α and IFN-γ in GCA-affected tissues.
RESULTS: GCA patients had decreased numbers of circulating effector memory CD8+ T cells but the percentage of Ki-67-expressing effector memory CD8+ T cells was increased. Circulating CD8+ T cells from GCA patients demonstrated reduced T cell receptor activation thresholds and displayed a gene expression profile that is concurrent with increased proliferation. CD8+ T cells were detected in GCA temporal arteries and aorta. These vascular CD8+ T cells expressed IFN-γ but not Ki-67.
CONCLUSION: In GCA, circulating effector memory CD8+ T cells demonstrate a proliferation-prone phenotype. The presence of CD8+ T cells in inflamed arteries seems to reflect recruitment of circulating cells rather than local expansion. CD8+ T cells in inflamed tissues produce IFN-γ, which is an important mediator of local inflammatory responses in GCA.
METHODS: Thirty-nine subjects were enrolled from various health clinics in Kelantan, Malaysia, and divided into two groups: patients with chronic HCV infection (HP) and healthy control (HS). The serum cytokines IL-6, TNF-a-were measured using Luminex assay, and serum TGF-β1 was measured by ELISA. The mRNA gene expression for IL-6, TNF-α and TGF-β1 was measured by real-time reverse transcriptase polymerase chain reaction (RT-PCR).
RESULTS: There were statistically significant differences in the mean serum levels of IL-6, and TGF-β1 in HP compared to HS group (p = 0.0180 and p = 0.0005, respectively). There was no significant difference in the mean serum level of TNF-α in HP compared to HS group. The gene expression for the studied cytokines showed no significant differences in HP compared to HS group.
CONCLUSION: Serum IL-6 was significantly associated with chronic HCV infection.
METHODS: This review was performed following the PRISMA guidelines. A systematic search of the study was conducted by retrieving articles from the electronic databases PubMed and Web of Science to identify articles focussed on gene expression and approaches for osteoblast and osteoclast differentiation.
RESULTS: Six articles were included in this review; there were original articles of in vitro human stem cell differentiation into osteoblasts and osteoclasts that involved gene expression profiling. Quantitative polymerase chain reaction (qPCR) was the most used technique for gene expression to detect differentiated human osteoblasts and osteoclasts. A total of 16 genes were found to be related to differentiating osteoblast and osteoclast differentiation.
CONCLUSION: Qualitative information of gene expression provided by qPCR could become a standard technique to analyse the differentiation of human stem cells into osteoblasts and osteoclasts rather than evaluating relative gene expression. RUNX2 and CTSK could be applied to detect osteoblasts and osteoclasts, respectively, while RANKL could be applied to detect both osteoblasts and osteoclasts. This review provides future researchers with a central source of relevant information on the vast variety of gene expression approaches in analysing the differentiation of human osteoblast and osteoclast cells. In addition, these findings should enable researchers to conduct accurately and efficiently studies involving isolated human stem cell differentiation into osteoblasts and osteoclasts.