Protein-protein Interaction Network Analysis Research Articles

Exercise and tumor proteome: Insights from a neuroblastoma model

Background/Aim: The impact of exercise on pediatric tumor biology is essentially unknown. We investigated the effects of regular exercise on tumor proteome profile (as assessed with liquid chromatography with tandem mass spectrometry) in a mouse model of one of the most aggressive childhood malignancies, high-risk neuroblastoma (HR-NB). Methods: Tumor samples of 14 male mice (aged 6-8 weeks) that were randomly allocated into an exercise (5-week combined aerobic and resistance training) or nonexercise control group (6 and 8 mice per group, respectively) were analyzed. The Search Tool for the Retrieval of Interacting Genes/Proteins database was used to generate a protein-protein interaction (PPI) network and enrichment analyses. The Systems Biology Triangle (SBT) algorithm was applied for analyses at the functional category level. Results: Tumors of exercised mice showed a higher and lower abundance of 101 and 150 proteins, respectively, compared to controls [false discovery rate (FDR)<0.05], which were enriched in metabolic pathways, aminoacid metabolism, regulation of hormone levels, and peroxisome proliferator-activated receptor signaling pathway (FDR<0.05). The SBT algorithm indicated that 184 and 126 categories showed a lower and higher abundance, respectively, in the tumors of exercised mice (FDR<0.01). Categories with lower abundance were involved in energy production while those with higher abundance were related to transcription/translation, apoptosis, and tumor suppression. Conclusion: Regular exercise altered the abundance of hundreds of intratumoral proteins and molecular pathways, particularly those involved in energy metabolism, apoptosis, and tumor suppression. These findings provide preliminary evidence of the molecular mechanisms underlying potential effects of exercise in HR-NB.

Unveiling the role of IGF1R in autism spectrum disorder: a multi-omics approach to decipher common pathogenic mechanisms in the IGF signaling pathway.

Autism spectrum disorder (ASD) is a complex neurodevelopmental condition marked by impairments in social interaction, communication, and repetitive behaviors. Emerging evidence suggests that the insulin-like growth factor (IGF) signaling pathway plays a critical role in ASD pathogenesis; however, the precise pathogenic mechanisms remain elusive. This study utilizes multi-omics approaches to investigate the pathogenic mechanisms of ASD susceptibility genes within the IGF pathway. Whole-exome sequencing (WES) revealed a significant enrichment of rare variants in key IGF signaling components, particularly the IGF receptor 1 (IGF1R), in a cohort of Chinese Han individuals diagnosed with ASD, as well as in ASD patients from the SFARI SPARK WES database. Subsequent single-cell RNA sequencing (scRNA-seq) of cortical tissues from children with ASD demonstrated elevated expression of IGF receptors in parvalbumin (PV) interneurons, suggesting a substantial impact on their development. Notably, IGF1R appears to mediate the effects of IGF2R on these neurons. Additionally, transcriptomic analysis of brain organoids derived from ASD patients indicated a significant association between IGF1R and ASD. Protein-protein interaction (PPI) and gene regulatory network (GRN) analyses further identified ASD susceptibility genes that interact with and regulate IGF1R expression. In conclusion, IGF1R emerges as a central node within the IGF signaling pathway, representing a potential common pathogenic mechanism and therapeutic target for ASD. These findings highlight the need for further investigation into the modulation of this pathway as a strategy for ASD intervention.

Rps3 Attenuates Gastric Precancerous Lesions by Promoting Dendritic Cells Maturation via AKT/β-Catenin Pathway.

This study aimed to investigate the dysregulated proteins and the underlying mechanisms of gastric precancerous lesions. Proteomic and phosphoproteomic methods were used to characterize the proteome and phosphoproteome profiles of N-methyl-N-nitro-N-nitrosoguanidine (MNNG)-induced gastric precancerous lesions. The hub differentially expressed proteins (DEPs) and phosphoproteins (DEPPs) were identified by using differential expression and protein-protein interaction network analyses. Western blot assay, quantitative reverse transcription (qRT)-PCR, and CCK-8 assays detected the expression of Rps3, N-cadherin, E-cadherin, AKT, p-AKT, and β-catenin and verified the roles of Rps3 on the MNNG-induced human gastric epithelial cell line (GES-1) cells. Hub DEPs and phosphoproteins Rps3, Akt1, and Ctnnb1 were significantly correlated with five dendritic cells (DCs) pathways, and Akt1 and Ctnnb1 were significantly negatively correlated with Rps3. MNNG administration markedly reduced the Rps3 mRNA and protein expression levels (all P < 0.05). Overexpression of Rps3 significantly inhibited tumorigenesis of MNNG-induced GES-1 cells (all P < 0.01) and changed the protein levels of N-cadherin, E-cadherin, AKT, p-AKT, and β-catenin. Similarly, SC79 treatment substantially increased the expression of interleukin (IL)-6, IL-10, and vascular endothelial growth factor (all P < 0.05). Rps3 was poorly expressed in precancerous gastric lesions. Correspondingly, overexpression of Rps3 promoted DC maturation via the AKT/β-catenin pathway, inhibiting the progression of gastric precancerous lesions.

Decoding the duration of fertility of laying chicken through phenotypic and proteomic evaluation

ABSTRACT 1. This study determined the effective indicators and proteins involved in long-duration fertility (DF) in chickens. 2. Three lines of Chinese Xinhua chickens (900) were compared using seven phenotypic trait indicators, and the best was determined based on repeatability value. Subsequently, differential expression analysis, functional annotation and protein-protein interaction (PPI) network analyses were performed to investigate the pathways and hub proteins. Finally, qPCR analysis was conducted to validate the expression of identified hub proteins, and functional annotation with previously published genes was performed to explain how hub proteins work to maintain the trait. 3. The study found that the number of fertilised eggs (FN) and maximum fertilised eggs (MCF) were the most repeatable among the seven indicators. It identified 231 differentially expressed proteins, with 144 being down-regulated and 87 being up-regulated. The differentially expressed proteins exhibited high clustering within various cellular compartments, including the cytosol and cytoplasm and GTP binding. Multiple pathways were identified, including tight and adherens junctions, TGF-beta signalling, autophagy-animal, regulation of actin cytoskeleton and the ribosome that may regulate the trait. Three hub proteins, KRAS, RPL5 (p < 0.001), and HSPA4 (p < 0.01), were significantly differentially expressed between high and low DF groups. 4. This study identified FN and MCF as effective indicators for addressing DF. As it is a quantitative trait, KRAS, HSPA4, and RPL5 are potential hub proteins that work with other genes to maintain the trait.

Proteomic analysis illustrates the potential involvement of motor proteins in cleft palate development

Cleft palate (CP) is a congenital condition characterized by a complex etiology and limited diagnostic and therapeutic options. In this study, we delved into the molecular mechanisms associated with retinoic acid (RA)-induced CP in Kun Ming mice. Proteomic analysis of control and RA-induced CP samples at embryonic day 15.5 revealed 25 upregulated and 19 downregulated proteins. Further analysis identified these differentially expressed proteins (DEPs) as being involved in extracellular matrix organization, actin cytoskeleton, and myosin complex. Moreover, these DEPs were found to be enriched in pathways related to motor protein activity and extracellular matrix-receptor interaction. Protein-protein interaction network analysis identified 10 hub proteins, including motor proteins and ECM-related proteins, which exhibited higher expression levels in CP compared to control tissues. These findings provide insights into the molecular mechanisms underlying CP and highlight potential targets for diagnostic and therapeutic purposes.

Identification of novel targets associated with cholesterol metabolism in nonalcoholic fatty liver disease: a comprehensive study using Mendelian randomization combined with transcriptome analysis.

There is limited research on cholesterol metabolism-related genes (CM-RGs) in non-alcoholic fatty liver disease (NAFLD), despite hypercholesterolemia being a recognized risk factor. The role of CM-RGs in NAFLD remains unclear. The differentially expressed genes (DEGs) between NAFLD and control were acquired by differential expression analysis. The differentially expressed genes associated with cholesterol metabolism (DE-CM-RGs) were identified and functional enrichment analyses were performed. Protein-protein interaction network analysis and a two-sample Mendelian randomization study were utilized for identifying hub genes. Nomogram model, competing endogenous RNA and messenger RNA-drug networks were established. In addition, immunoinfiltration analysis was performed. We identified four hub genes (MVK, HMGCS1, TM7SF2, and FDPS) linked to NAFLD risk. MVK and TM7SF2 were protective factors, HMGCS1 and FDPS were risk factors for NAFLD. The area under the curve values of nomograms in GSE135251 and GSE126848 were 0.79 and 0.848, respectively. The gene set enrichment analysis indicated that hub genes participated in calcium signaling pathways and biosynthesis of unsaturated fatty acids. NAFLD patients showed increased CD56dim NK cells and Th17. Tretinoin, alendronate, zoledronic acid, and quercetin are potential target agents in NAFLD. Our study has linked cholesterol metabolism genes (MVK, HMGCS1, TM7SF2, and FDPS) to NAFLD, providing a promising diagnostic framework, identifying treatment targets, and offering novel perspectives into its mechanisms.

A combined transcriptomics and proteomics approach reveals S100A4 as a potential biomarker for Graves' orbitopathy.

There are no reliable biomarkers to identify Graves' disease patients who will develop severe Graves' orbitopathy (GO). We hypothesize that integrating various omics platforms can enhance our understanding of disease mechanisms and uncover potential biomarkers. This study aimed to (1) elucidate the differential gene expression profile of orbital fibroblasts in GO during early adipogenesis to better understand disease mechanisms and (2) compare tear protein profiles from our earlier study and the transcriptome profiles of orbital fibroblasts (OFs) to identify possible biomarkers of the disease. OFs were grown from orbital adipose tissue obtained from nine GO patients (three for discovery and six for validation experiments). Total RNA was extracted from OFs on day 0 as the baseline for each sample and from differentiated OFs on days 4 and 8. Protein-protein interaction (PPI) analysis and functional enrichment analysis were also carried out. The differentially expressed genes (DEGs) from the RNA sequencing experiments were then compared to the full tear proteome profile from the author's previous study, which examined the tear protein changes of GO patients based on fold change > 1.6 or < -1.6. FDR < 0.05 was applied within all datasets. Further validation of S100 calcium-binding protein A4 (S100A4) downregulation in GO was performed via quantitative real-time PCR (qPCR). The whole transcriptomic analysis revealed 9 upregulated genes and 15 downregulated genes in common between the discovery and validation experiments. From the PPI network analysis, an interaction network containing six identified DEGs (ALDH2, MAP2K6, MT2A, SOCS3, S100A4, and THBD) was observed. The functional enrichment network analysis identified a set of genes related to oxysterol production. S100A4 was found to be consistently downregulated in both our transcriptome studies and the full-tear proteome profile from the author's previous study. Our study identified several DEGs and potential gene pathways in GO patients, which concurred with the results of other studies. Tear S100A4 may serve as a biomarker for the propensity to develop thyroid eye disease (TED) in patients with autoimmune thyroid disease (AITD) before clinical manifestation and should be confirmed in future studies.

Utilize proteomic analysis to identify potential therapeutic targets for combating sepsis and sepsis-related death.

Sepsis is an inflammatory disease that leads to severe mortality, highlighting the urgent need to identify new therapeutic strategies for sepsis. Proteomic research serves as a primary source for drug target identification. We employed proteome-wide Mendelian randomization (MR), genetic correlation analysis, and colocalization analysis to identify potential targets for sepsis and sepsis-related death. Genetic data for plasma proteomics were obtained from 35,559 Icelandic individuals and an initial MR analysis was conducted using 13,531 sepsis cases from the FinnGen R10 cohort to identify associations between plasma proteins and sepsis. Subsequently, significant proteins underwent genetic correlation analysis, followed by replication in 54,306 participants from the UK Biobank Pharma Proteomics Project and validation in 11,643 sepsis cases from the UK Biobank. The identified proteins were then subjected to colocalization analysis, enrichment analysis, and protein-protein interaction network analysis. Additionally, we also investigated a MR analysis using plasma proteins on 1,896 sepsis cases with 28-day mortality from the UK Biobank. After FDR correction, MR analysis results showed a significant causal relationship between 113 plasma proteins and sepsis. Genetic correlation analysis revealed that only 8 proteins had genetic correlations with sepsis. In the UKB-PPP replication analysis, only 4 proteins were found to be closely associated with sepsis, while validation in the UK Biobank sepsis cases found overlaps for 21 proteins. In total, 30 proteins were identified in the aforementioned analyses, and colocalization analysis revealed that only 2 of these proteins were closely associated with sepsis. Additionally, in the 28-day mortality MR analysis of sepsis, we also found that only 2 proteins were significant. The identified plasma proteins and their associated metabolic pathways have enhanced our understanding of the complex relationship between proteins and sepsis. This provides new avenues for the development of drug targets and paves the way for further research in this field.

Assessing the causal effect of inflammation-related genes on myocarditis: A Mendelian randomization study.

Prior evidence has shown a significant link between inflammation and the development of myocarditis. This study aimed to investigate the causal relationship between inflammation-related genes (IRGs) and myocarditis. In this study, the causal relationship between 167 IRGs and myocarditis were investigated using datasets from the Gene Set Enrichment Analysis and Integrative Epidemiology Unit open genome-wide association study (IEU OpenGWAS) databases. The GWAS data (finn-b-I9 MYOCARD) contained single nucleotide polymorphisms (SNPs) data from 117755 myocarditis samples (16379455 SNPs, 829 cases vs. 116926 controls). Five algorithms [MR-Egger, weighted median, inverse variance weighted (IVW), simple mode, and weighted mode regression] were employed for the MR analysis, with IVW as the primary method, and sensitivity analysis was conducted. Subcellular localization and protein-protein interaction (PPI) network analyses were performed for selected biomarkers. Results were verified in ebi-a-GCST90018882 (24180570 SNPs, 633 cases vs. 427278 controls) and finn-b-I9 MYOCARD EXNONE (16380466 SNPs, 829 cases vs. 217963 controls) to enhance reliability. IRF7 and ADORA2B were shown to be two exposure factors after screening. Univariable MR (UVMR) analysis revealed that IRF7 was a risk factor for myocarditis [IVW: odd ratio (OR)=1.041, 95% confidence interval (CI)=1.018-1.955, P=0.039], while ADORA2B was a protective factors for myocarditis (IVW: OR=0.799, 95% CI=0.640-0.997, P=0.047). Sensitivity analysis confirmed the robustness of these findings. Multivariable MR (MVMR) analysis further demonstrated a direct causal role of ADORA2B in preventing myocarditis. Subcellular localization analysis indicated predominant cytoplasmic expression and limited mitochondrial expression for both genes. The results of PPI analysis showed that 20 genes were predicted to be associated with IRF7 function, such as response to type I interferon, pattern recognition receptor signalling pathway, and toll-like receptor signalling pathway. The results in finn-b-I9 MYOCARD EXNONE were consistent with MR analysis. The findings indicated there was a causal connection between IRGs (IRF7 and ADORA2B) and myocarditis, which offered a crucial point of reference and guidance for future studies and myocarditis treatment.

Construction and analysis of protein-protein interaction network for esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) is a prevalent malignant tumor of the digestive tract. Clinical findings reveal that the five-year survival rate for mid-to late-stage ESCC patients is merely around 20 %, whereas those diagnosed at an early stage can achieve up to a 95 % survival rate. Consequently, early detection is paramount to improving ESCC patient survival. Protein markers are essential for diagnosing diseases, and the identification of new candidate proteins associated with ESCC through the protein-protein interaction (PPI) network is aimed for in this paper. The PPI network related to ESCC was constructed using protein data, comprising 2094 nodes and 19,660 edges. To assess the nodes' importance in the network, three metrics—degree centrality, betweenness centrality, and closeness centrality—were employed, leading to the identification of 81 key proteins. Subsequently, the biological significance of these proteins in the network was explored, combining biomedical knowledge from three perspectives: network, node, and cluster. The results demonstrated that 52 out of 81 key proteins were confirmed to be linked to ESCC. Among the remaining 29 unreported proteins, 18 displayed significant biological significance, indicating their potential as protein markers related to ESCC.

Exploring the mechanism of action of Bidens pilosa L. in combating hepatic fibrosis through network pharmacology and molecular docking: An observational study.

Based on network pharmacology and molecular docking methods, to explore the possible targets and mechanisms of Bidens pilosa L. in treatment of liver fibrosis. The TCMSP, GeneCard, OMIM, TTD and DrugBank databases were used to obtain the targets of Bidens pilosa L and liver fibrosis, than the intersection targets were screened out by Venny 2.1.0, the protein-protein interaction (PPI) network and the core targets were obtained by the STRING database. Use Cytoscape3.7.2 software to draw the "traditional Chinese medicine-component-target-disease" network. The DAVID database platform was explored to analyze the biological process and pathway, and predict the anti-liver fibrosis mechanism of Bidens pilosa L. AutoDock and PyMol were used to verify the molecular docking between the active ingredients of Bidens pilosa L. and the core targets. Six active components of Bidens pilosa L. and 106 intersection targets were screened. PIK3R1, HSP90AA1, SRC, TP53, AKT1, RELA and other core targets were screened by PPI network analysis. The results of GO and KEGG enrichment analysis showed that the anti-liver fibrosis of Bidens pilosa L mainly involved in the regulation and negative regulation of apoptosis process, positive regulation of protein kinase B signal transduction, positive regulation of cell migration and other biological processes. Pathways acting on cancer, fluid shear stress and atherosclerosis, lipids and atherosclerosis, PI3K-AKT signaling pathway, MAPK signaling pathway and other signaling pathways. Molecular docking showed that the active components of Bidens pilosa L. displayed good binding activity with core target proteins, and the average binding energy was -7.47 kcal/mol. The possible mechanism of the active components against liver fibrosis is to regulate the PI3K-AKT, MAPK, and other signaling pathways by acting on core targets such as PIK3R1, HSP90AA1, SRC, TP53, AKT1, RELA, and induce the apoptosis of activated HSC cells to reverse and improve liver fibrosis.

A Comprehensive Pan-Cancer Analysis Identified that TRIB3 was Associated with Immune Cell Infiltration and Poor Prognosis.

Previous studies have demonstrated that TRIB3 plays a carcinogenic role in tumor progression. However, the exploration of TRIB3 at the pan-cancer level has not been reported. This study aimed to conduct a comprehensive pan-cancer analysis of TRIB3. We explored the expression pattern and functional mechanism of TRIB3 on the basis of multiple databases. We first explored the expression level of TRIB3 in the TCGA database. Then, the receiver operation characteristic curve (ROC), Kaplan-Meier plotter, and Cox regression were used to estimate the diagnostic and prognostic value of TRIB3, respectively. We also explored the relationship between TRIB3 and the infiltration of tumor immune cells, as well as the expression of immune checkpoint molecules. Gene enrichment and protein interaction network analysis were carried out to identify possible carcinogenic molecular mechanisms and functional pathways. Finally, we compared the non-promoter region methylation of TRIB3 in normal and tumor tissues and explored potential systems with unique functions in TRIB3-mediated tumorigenesis. The expression level of TRIB3 was elevated in multiple tumor types, and the high expression of TRIB3 was associated with poor prognosis. TRIB3 had a higher frequency of genetic changes in several tumors and showed varying trends in TRIB3 methylation levels. Additionally, high expression of TRIB3 was also associated with infiltration of cancer-related fibroblasts and different types of immune cells and was positively correlated with the expression of immune checkpoint molecules. Furthermore, gene enrichment analysis suggested that TRIB3 may play a role in the malignant progression of cancer by participating in protein post-translational modifications and activating transcription initiation factors. Our pan-cancer analysis provided the potential carcinogenic role of TRIB3 in tumors and verified a promising target for clinical immune treatment.

Genome-Wide Characterization and Expression Analysis of CsPALs in Cucumber (Cucumis sativus L.) Reveal Their Potential Roles in Abiotic Stress and Aphid Stress Tolerance.

Phenylalanine ammonia lyase (PAL) is a pivotal enzyme in the phenylalanine metabolic pathway in plants and has a crucial role in the plant's response to environmental stress. Although the PAL family has been widely studied in many plant species, limited is known about its particular role in cucumbers under stress. We investigated the physicochemical properties, gene structure, gene duplication events, conserved motifs, cis-acting elements, protein interaction networks, stress-related transcriptome data, and quantitatively validated key stress-related genes. The main results indicated that 15 PAL genes were grouped into four clades: I, II, and III when arranged in a phylogenetic tree of PAL genes in angiosperms. The analysis of the promoter sequence revealed the presence of multiple cis-acting elements related to hormones and stress responses in the cucumber PAL genes (CsPALs). The analysis of protein interaction networks suggested that CsPAL1 interacts with eight other members of the PAL family through CsELI5 and CsHISNA, and directly interacts with multiple proteins in the 4CL family. Further investigation into the expression patterns of CsPAL genes in different tissues and under various stress treatments (NaCl, Cu2+, Zn2+, PEG6000, aphids) demonstrated significant differential expression of CsPALs across cucumber tissues. In summary, our characterization of the CsPAL family offers valuable insights and provides important clues regarding the molecular mechanisms of CsPALs in managing abiotic and biotic stress interactions in cucumbers.

The Vital Role of the CAMTA Gene Family in Phoebe bournei in Response to Drought, Heat, and Light Stress.

The calmodulin-binding transcriptional activator (CAMTA) is a small, conserved gene family in plants that plays a crucial role in regulating growth, development, and responses to various abiotic stress. Given the significance of the CAMTA gene family, various studies have been dedicated to uncovering its functional characteristics. In this study, genome-wide identification and bioinformatics analysis were conducted to explore CAMTAs in Phoebe bournei. A total of 17 CAMTA genes, each containing at least one domain from CG-1, TIG, ANK, or IQ, were identified in the P. bournei genome. The diversity of PbCAMTAs could be varied depending on their subcellular localization. An analysis of protein motifs, domains, and gene structure revealed that members within the same subgroup exhibited similar organization, supporting the results of the phylogenetic analysis. Gene duplications occurred among members of the PbCAMTA gene family. According to the cis-regulatory element prediction and protein-protein interaction network analysis, eight genes were subjected to qRT-PCR under drought, heat, and light stresses. The expression profiles indicated that PbCAMTAs, particularly PbCAMTA2, PbCAMTA12, and PbCAMTA16, were induced by abiotic stress. This study provides profound insights into the functions of CAMTAs in P. bournei.

Key Disease-Related Genes and Immune Cell Infiltration Landscape in Inflammatory Bowel Disease: A Bioinformatics Investigation.

Inflammatory Bowel Diseases (IBD), which encompass ulcerative colitis (UC) and Crohn's disease (CD), are characterized by chronic inflammation and tissue damage of the gastrointestinal tract. This study aimed to uncover novel disease-gene signatures, dysregulated pathways, and the immune cell infiltration landscape of inflamed tissues. Eight publicly available transcriptomic datasets, including inflamed and non-inflamed tissues from CD and UC patients were analyzed. Common differentially expressed genes (DEGs) were identified through meta-analysis, revealing 180 DEGs. DEGs were implicated in leukocyte transendothelial migration, PI3K-Akt, chemokine, NOD-like receptors, TNF signaling pathways, and pathways in cancer. Protein-protein interaction network and cluster analysis identified 14 central IBD players, which were validated using eight external datasets. Disease module construction using the NeDRex platform identified nine out of 14 disease-associated genes (CYBB, RAC2, GNAI2, ITGA4, CYBA, NCF4, CPT1A, NCF2, and PCK1). Immune infiltration profile assessment revealed a significantly higher degree of infiltration of neutrophils, activated dendritic cells, plasma cells, mast cells (resting/activated), B cells (memory/naïve), regulatory T cells, and M0 and M1 macrophages in inflamed IBD tissue. Collectively, this study identified the immune infiltration profile and nine disease-associated genes as potential modulators of IBD pathogenesis, offering insights into disease molecular mechanisms, and highlighting potential disease modulators and immune cell dynamics.

Lipoteichoic Acid from Heyndrickxia coagulans HOM5301 Modulates the Immune Response of RAW 264.7 Macrophages.

Heyndrickxia coagulans (formerly Bacillus coagulans) has been increasingly utilized as an immunomodulatory probiotics. Oral administration of H. coagulans HOM5301 significantly boosted both innate and adaptive immunity in mice, particularly by increasing the phagocytic capacity of monocytes/macrophages. Lipoteichoic acid (LTA), a major microbe-associated molecular pattern (MAMP) in Gram-positive bacteria, exhibits differential immunomodulatory effects due to its structural heterogeneity. We extracted, purified, and characterized LTA from H. coagulans HOM5301. The results showed that HOM5301 LTA consists of a glycerophosphate backbone. Its molecular weight is in the range of 10-16 kDa. HOM5301 LTA induced greater productions of nitric oxide, TNFα, and IL-6 in RAW 264.7 macrophages compared to Staphylococcus aureus LTA. Comparative transcriptome and proteome analyses identified the differentially expressed genes and proteins triggered by HOM5301 LTA. KEGG analyses revealed that HOM5301 LTA transcriptionally and translationally activated macrophages through two immune-related pathways: cytokine-cytokine receptor interaction and phagosome formation. Protein-protein interaction network analysis indicated that the pro-inflammatory response elicited by HOM5301 LTA was TLR2-dependent, possibly requiring the coreceptor CD14, and is mediated via the MAPK and NF-kappaB pathways. Our results demonstrate that LTA is an important MAMP of H. coagulans HOM5301 that boosts immune responses, suggesting that HOM5301 LTA may be a promising immunoadjuvant.

Identification of HDAC10 as a candidate oncogene in clear cell renal carcinoma that facilitates tumor proliferation and metastasis

BackgroundClear cell renal cell carcinoma (ccRCC) remains one of the most lethal urological malignancies even though a great number of improvements in diagnosis and management have achieved over the past few decades. Accumulated evidence revealed that histone deacetylases (HDACs) play vital role in cell proliferation, differentiation and apoptosis. Nevertheless, the biological functions of histone deacetylation modification related genes in ccRCC remains poorly understood.MethodBulk transcriptomic data and clinical information of ccRCC patients were obtained from the TCGA database and collected from the Chinese PLA General Hospital. A total of 36 histone deacetylation genes were selected and studied in our research. Univariate cox regression analysis, least absolute shrinkage and selection operator (LASSO) regression, random forest (RF) analysis, and protein-protein interaction (PPI) network analysis were applied to identify key genes affecting the prognosis of ccRCC. The ‘oncoPredict’ algorithm was utilized for drug-sensitive analysis. Gene Set Enrichment Analysis (GSEA) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis was used to explore the potential biological function. The ssGSEA algorithm was used for tumor immune microenvironment analysis. The expression levels of HDAC10 were validated by RT-PCR and immunohistochemistry (IHC). 5-ethynyl-2′-deoxyuridine (EdU assay), CCK-8 assay, cell transwell migration and invasion assay and colony formation assay were performed to detect the proliferation and invasion ability of ccRCC cells. A nomogram incorporating HDAC10 and clinicopathological characteristics was established to predict the prognosis of ccRCC patients.ResultTwo machine learning algorithms and PPI analysis identified four histone deacetylation genes that have a significant association with the prognosis of ccRCC, with HDAC10 being the key gene among them. HDAC10 is highly expressed in ccRCC and its high expression is associated with poor prognosis for ccRCC patients. Pathway enrichment and the experiments of EdU staining, CCK-8 assay, cell transwell migration and invasion assay and colony formation assay demonstrated that HDAC10 mediated the proliferation and metastasis of ccRCC cells and involved in reshaping the tumor microenvironment (TME) of ccRCC. A clinically reliable prognostic predictive model was established by incorporating HDAC10 and other clinicopathological characteristics ( https://nomogramhdac10.shinyapps.io/HDAC10_Nomogram/ ).ConclusionOur study found the increased expression of HDAC10 was closely associated with poor prognosis of ccRCC patients. HDAC10 showed a pro-tumorigenic effect on ccRCC and promote the proliferation and metastasis of ccRCC, which may provide new light on targeted therapy for ccRCC.

Transcriptomic landscape of quiescent and proliferating human corneal stromal fibroblasts

This study analyzed the transcriptional changes in primary human corneal stromal fibroblasts (hCSFs) grown under quiescent (serum-free) and proliferating (serum-supplemented) culture conditions to identify genes, pathways, and protein‒protein interaction networks influencing corneal repair and regeneration. Primary hCSFs were isolated from donor human corneas and maintained in serum-free or serum-laden conditions. RNA was extracted from confluent cultures using Qiagen kit and subjected to RNA sequencing (RNAseq) analysis. Differential gene expression (DGE) and pathway enrichment analyses were conducted using DESeq2 and Gene Set Enrichment Analysis (GSEA), respectively. Protein‒protein interaction (PPI) networks were created exploiting the STRING database and analyzed with Cytoscape and the cytoHubba plugin. RNA-seq revealed 5,181 genes that were significantly differentially expressed/changed among the 18,812 annotated genes (p value ˂0.05). A cutoff value of a log2-fold change of ±1.5 or greater was used to identify 674 significantly upregulated and 771 downregulated genes between quiescent and proliferating hCSFs. Pathway enrichment analysis revealed significant changes in genes linked to cell cycle regulation, inflammatory, and oxidative stress response pathways, such as E2F Targets, G2M Checkpoint, and MYC Targets, TNFA signaling via NF-kB, and oxidative phosphorylation. Protein-protein interaction network analysis highlighted critical hub genes. The FGF22, CD34, ASPN, DPT, LUM, FGF10, PDGFRB, ECM2, DCN, VEGFD, OMD, OGN, ANGPT1, CDH5, and PRELP were upregulated, whereas genes linked to cell cycle regulation and mitotic progression, such as BUB1, TTK, KIF23, KIF11, BUB1B, DLGAP5, NUSAP1, CCNA2, CCNB1, BIRC5, CDK1, KIF20A, AURKB, KIF2C, and CDCA8, were downregulated. The RNA sequences and gene count files have been submitted to the Gene Expression Omnibus (accession # GSE260476). Our study provides a comprehensive information on the transcriptional and molecular changes in hCSFs under quiescent and proliferative conditions and highlights key pathways and hub genes.

Analysis of gut microbiota-derived metabolites regulating pituitary neuroendocrine tumors through network pharmacology.

Pituitary neuroendocrine tumors (PitNETs) are a special class of tumors of the central nervous system that are closely related to metabolism, endocrine functions, and immunity. In this study, network pharmacology was used to explore the metabolites and pharmacological mechanisms of PitNET regulation by gut microbiota. The metabolites of the gut microbiota were obtained from the gutMGene database, and the targets related to the metabolites and PitNETs were determined using public databases. A total of 208 metabolites were mined from the gutMGene database; 1,192 metabolite targets were screened from the similarity ensemble approach database; and 2,303 PitNET-related targets were screened from the GeneCards database. From these, 392 overlapping targets were screened between the metabolite and PitNET-related targets, and the intersection between these overlapping and gutMGene database targets (223 targets) were obtained as the core targets (43 targets). Using the protein-protein interaction (PPI) network analysis, Kyoto encyclopedia of genes and genomes (KEGG) signaling pathway and metabolic pathway analysis, CXCL8 was obtained as a hub target, tryptophan metabolism was found to be a key metabolic pathway, and IL-17 signaling was screened as the key KEGG signaling pathway. In addition, molecular docking analysis of the active metabolites and target were performed, and the results showed that baicalin, baicalein, and compound K had good binding activities with CXCL8. We also describe the potential mechanisms for treating PitNETs using the information on the microbiota (Bifidobacterium adolescentis), signaling pathway (IL-17), target (CXCL8), and metabolites (baicalin, baicalein, and compound K); we expect that these will provide a scientific basis for further study.

A protein risk score for all-cause and respiratory-specific mortality in non-Hispanic white and African American individuals who smoke

Protein biomarkers are associated with mortality in cardiovascular disease, but their effect on predicting respiratory and all-cause mortality is not clear. We tested whether a protein risk score (protRS) can improve prediction of all-cause mortality over clinical risk factors in smokers. We utilized smoking-enriched (COPDGene, LSC, SPIROMICS) and general population-based (MESA) cohorts with SomaScan proteomic and mortality data. We split COPDGene into training and testing sets (50:50) and developed a protRS based on respiratory mortality effect size and parsimony. We tested multivariable associations of the protRS with all-cause, respiratory, and cardiovascular mortality, and performed meta-analysis, area-under-the-curve (AUC), and network analyses. We included 2232 participants. In COPDGene, a penalized regression-based protRS was most highly associated with respiratory mortality (OR 9.2) and parsimonious (15 proteins). This protRS was associated with all-cause mortality (random effects HR 1.79 [95% CI 1.31–2.43]). Adding the protRS to clinical covariates improved all-cause mortality prediction in COPDGene (AUC 0.87 vs 0.82) and SPIROMICS (0.74 vs 0.6), but not in LSC and MESA. Protein–protein interaction network analyses implicate cytokine signaling, innate immune responses, and extracellular matrix turnover. A blood-based protein risk score predicts all-cause and respiratory mortality, identifies potential drivers of mortality, and demonstrates heterogeneity in effects amongst cohorts.