KEGG Research Articles

Rutin Attenuates Distraction Spinal Cord Injury by Inhibiting Microglial Inflammation Through Downregulation of P38 MAPK/NF-κB/STAT3 Pathway.

Distraction spinal cord injury (DSCI) is a severe complication followingscoliosis correction surgery, for which there are currently no effective clinical treatments. This study aims to evaluate the inhibitory effects of rutin, a natural product, on inflammation inDSCI and to investigate the underlying mechanisms. In vitro, microglial cells were exposed directly to rutin to assess its ability to inhibit lipopolysaccharide (LPS)-induced inflammation. In rats with DSCI, the inhibitory effect of rutin on DSCI was evaluated using behavioral tests. mRNA sequencing was performed on spinal cord tissues to elucidate the mechanism of rutin's action. Rutin significantly suppressed the LPS-induced increase in inflammatory factors in microglial cells. In DSCI rats treated with rutin, scores in the Basso-Beattie-Bresnahan (BBB) were significantly improved. The mechanism of rutin's action was found to be related to its ability to reduce inflammatory infiltration in spinal cord tissue, protecting neurons from apoptosis and microstructural demyelination. Through assays of transcriptomic differentially expressed genes (DEGs), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, and RT-qPCR validation of the top DEGs, MAPK13 (also known as P38 MAPK) was finally identified as the key target gene in promoting DSCI development. Further molecular docking analysis indicated an interaction between rutin and P38 MAPK, supporting the rutin's action and the underlying mechanism in anti-inflammation. In conclusion, rutin effectively inhibited the development of DSCI in rats. The mechanism of rutin's action was associated with its activity in blocking the P38 MAPK/NF-κB/STAT3 pathway in the microglial cells of spinal cord. Rutin could be developed as a potential anti-DSCI drug for clinical applications.

CCL4L2 participates in tendinopathy progression by promoting macrophage inflammatory responses: a single-cell analysis

BackgroundTendinopathy is very common in clinical practice, which is highly prevalent in athletes, sports enthusiasts and other people involved in high-load weight-bearing activities. Common types of tendinopathy include rotator cuff injury, Achilles tendinitis, tennis elbow and so on. Macrophages (Macs) are key immune cells in the pathogenesis of tendinopathy. In this study, CCL4L2+ M1-related signaling pathways were screened by combining single-cell RNA sequencing (scRNA-seq) to explore their significance in tendinopathy treatment.MethodsImmune cell populations were screened by Uniform Manifold Approximation and Projection (UMAP) downscaling, and Mac cell subsets were annotated using cell marker genes. The cellular communication mechanism between different cellular subsets such as Macs and tendon stem/progenitor cells (TSPCs) was demonstrated by cellular communication analysis. Based on cell marker genes of CCL4L2 + M1, Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment were performed to compare the expression differences in M1 and M2 between the Disease and Healthy groups. Associations between CCL4L2+ M1 and TSPCs were inferred by cell-cell communication analysis. The effects of CCL4L2 on Mac polarization and TSPCs were verified by enzyme-linked immunosorbent assay (ELISA) and real-time fluorescence quantitative PCR (qPCR).ResultsThe proportions of TSPCs, endothelial cells (ECs), smooth muscle cells (SMCs), and immune cells were significantly elevated in the Disease group. The proportion of M1 cells in the Disease group was higher than that in the Healthy group, while the proportion of M2 cells was lower than that in the Healthy group. M1 differentially expressed genes (DEGs) were mainly enriched to disease-related and immunoinflammation-related signaling pathways. Signaling intensities between M1 and TSPCs in pathways related to immunoinflammation and ischemic injury were significantly increased in the Disease group. The proportion of CCL4L2 + M1 in the Disease group was significantly higher than in the Healthy group, and communications between CCL4L2 + M1 and TSPCs varied significantly. Compared with the Control group, the expression levels of inflammatory cytokines were higher in the CCL4L2 group, and the expression levels of tendon differentiation markers (Egr1, Mkx, Scx, Type 1 collagen, Tnmd) were significantly down-regulated.ConclusionThe present study analyzed the heterogeneous alterations in the Healthy and Disease groups by scRNA-seq data and found that there was a significant inflammatory infiltrate in the Disease group with markedly increased Mac activity, which was associated with activation of the CCL4L2 + M1-associated signaling pathways. CCL4L2 promotes M1 polarization and inhibits TSPC differentiation through activating M1-related inflammatory signaling pathways. These findings contribute to a more comprehensive understanding of tendon injury progression and provide potential targets for tendinopathy treatment.

CMTM6 promotes hepatocellular carcinoma invasion and metastasis and tumor-associated neutrophil immunoinfiltration through the Wnt/β-catenin pathway

BackgroundCMTM6 has been closely associated with the onset and progression of various tumor types. However, the precise mechanism by which CMTM6 operates in hepatocellular carcinoma remains elusive, necessitating further investigation.MethodsExpression levels of CMTM6 in hepatocellular carcinoma tissues and cells were analyzed using immunohistochemistry and quantitative real-time PCR. The correlation between CMTM6 expression in hepatocellular carcinoma tissues and clinical pathological characteristics, as well as patient prognosis, was investigated. Proliferation and apoptosis of hepatocellular carcinoma cells with silenced or overexpressed CMTM6 were assessed, alongside measurements of β-catenin and Wnt1 protein expression levels. In vivo research was conducted utilizing a murine subcutaneous transplantation model. Gene Set Enrichment Analysis (GSEA) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed to elucidate the regulatory mechanism of CMTM6. Additionally, CD66b expression levels in tumor tissue were examined using immunohistochemistry, and the immune infiltration of CMTM6 and tumor-associated neutrophils (TANs) was analyzed.ResultsElevated expression levels of CMTM6 in hepatocellular carcinoma tissues and cells were found to be associated with poor patient prognosis. Overexpression of CMTM6 in hepatocellular carcinoma cells was demonstrated to promote cellular proliferation and inhibit apoptosis. Mechanistically, CMTM6 expression levels in hepatocellular carcinoma tissues were observed to positively correlate with β-catenin expression. GSEA and KEGG analysis revealed significant enrichment of CMTM6 in the Wnt/β-catenin pathway, indicating its involvement in pathway regulation. Furthermore, CMTM6 was found to be associated with immune infiltration of TANs in hepatocellular carcinoma tissues.ConclusionCMTM6 plays a pivotal role in the development and progression of hepatocellular carcinoma through regulation of the Wnt/β-catenin pathway via β-catenin. Moreover, CMTM6 demonstrates the capacity to promote immune infiltration of TANs in hepatocellular carcinoma tissues. Consequently, CMTM6 exhibits potential as both an early diagnostic marker and a novel therapeutic target for patients with hepatocellular carcinoma.

Exploring Beta-sitosterol’s Role in Breast Cancer Treatment via Integrated Network Pharmacological Analysis and In Vitro Validation

Background Beta-sitosterol, a phytosterol similar to cholesterol, is found in various plants and is recognized for its potential anticancer properties; still, the mechanism of breast cancer (BC) remains elusive. Purpose This study investigates the potential targets of beta-sitosterol in BC using network pharmacological analysis and in vitro validation. Methods Targets of beta-sitosterol and BC were identified from online databases, including Swiss Target Prediction, SuperPred, GeneCards, and DisGeNET. Protein–protein interactions of common targets were analyzed using STRING version 11.0, and network construction and core target screening were performed with Cytoscape 3.8.0. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and gene ontology (GO) annotation were conducted using the ShinyGO web tool. Molecular docking analysis was done with AutoDock Vina and the in vitro validation, including cell viability, apoptosis, and gene expression analysis was done using MTT assay, acridine orange/ethidium bromide staining, and polymerase chain reaction (PCR), respectively. Results Sixty-eight common targets for beta-sitosterol and BC were identified from 209 beta-sitosterol targets and 1,350 BC-related genes. Five core targets (HIF1A, ESR1, STAT3, TNF, and MAPK3) were identified. GO analysis linked common targets to biological processes, cellular components, and molecular functions. KEGG pathway analysis showed enrichment in pathways such as central carbon metabolism in cancer, vascular endothelial growth factor signaling, and prolactin signaling. Beta-sitosterol’s impact on MCF7 cell viability was assessed via MTT assay, and its molecular effects were explored through PCR. Results demonstrated beta-sitosterol’s ability to hinder tumor progression by modulating genes involved in ESR1, mitogen-activated protein kinase, and tumor necrosis factor signaling pathways. Conclusion These findings highlight beta-sitosterol’s potential as an anticancer agent, offering new perspectives for clinical investigations through the modulation of key signaling pathways in BC.

The Plasma Proteome and Risk of Future Venous Thromboembolism-Results from the HUNT Study.

This study aimed to identify novel plasma proteins associated with first-lifetime venous thromboembolism (VTE) and molecular pathways involved in VTE pathogenesis. A case-cohort comprising incident VTE cases (n = 294) and a randomly sampled age- and sex-weighted subcohort (n = 1,066) was derived from the Trøndelag Health Study (HUNT3, n = 50,800). Blood samples were collected and stored at cohort inclusion (2006-2008), and participants were followed up to 5 years. Proteome-wide analyses was performed using the 7k SomaScan® proteomics platform, and weighted Cox-regression models adjusted for age, sex, and sample batch were conducted, with the Bonferroni method applied to account for multiple testing. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were applied on the top-ranked 200 proteins associated with VTE. Out of 7,288 human proteins, 7 proteins were significantly associated with higher VTE risk with p-value <6.9 × 10-6 (hazard ratios per 1 standard deviation increase in protein levels ranging from 1.39 to 1.86). Except for coagulation factor VIII and tumor necrosis factor soluble receptor II, these proteins were novel associations and included collagen alpha-3(VI):BPTI/Kunitz inhibitor, histo-blood group ABO system transferase, peroxidasin, human epididymis protein 4, and regulator of G protein signaling 3. KEGG analyses of the top-ranked 200 proteins revealed significant pathway enrichment of nine proteins in the complement (mainly lectin pathway) and coagulation (mainly intrinsic pathway) cascades. Our proteome-wide analysis led to discovery of five novel protein candidates associated with 5-year risk of future VTE. KEGG analyses supported an interplay between the complement and coagulation pathways in the pathogenesis of VTE.

Prognostic significance of NUAK1 and its association with immune infiltration in stomach adenocarcinoma

BackgroundStomach adenocarcinoma (STAD) represents a significant global health burden, accounting for a considerable proportion of cancer-related mortalities, and NUAK1, a protein kinase, plays a crucial role in cellular metabolism, cell cycle regulation, migration, and tumor progression. However, its relationship with prognosis and immune infiltration in STAD has not been thoroughly investigated.MethodsRNA sequencing data from the Cancer Genome Atlas (TCGA) and Genotypic Tissue Expression Project (GTEx) databases were employed to assess disparities in NUAK1 expression between STAD tumour and normal tissues. Additionally, we investigated the correlation between NUAK1 expression and patient prognosis, in addition to the level of immune cell infiltration. The potential functions were elucidated through an examination of the Gene Ontology (GO) Encyclopedia, the Kyoto Encyclopedia of Genes and Genomes (KEGG), and an enrichment analysis (GSEA). The GeneMANIA was used to validate the functions of nuak1-related genes.ResultsOur analysis demonstrated that NUAK1 expression in tumour tissues exhibited a notable disparity from that observed in normal tissues, with elevated levels detected in STAD tissues. We used the GeneMANIA database to identify functionally similar genes with significantly higher expression for some genes in the unpaired group samples. An elevated NUAK1 expression level was found to correlate with a poorer overall survival (OS), disease-specific survival (DSS), and progression-free intervals (PFI). Additionally, immune infiltration analysis indicated a significant positive correlation between NUAK1 expression and various tumor-infiltrating immune cells, while a negative correlation was observed with T helper cell 17(Th17) cells. Furthermore, enrichment analysis was conducted to identify relevant biological features and pathways.ConclusionThe expression levels of NUAK1 are significantly increased in STAD, and this heightened expression correlates with diminished OS, DSS, and PFI among affected patients. These observations indicate that NUAK1 has the potential to function as a prognostic biomarker for STAD and may represent a viable therapeutic target for intervention in its management.

Integrating bioinformatics and machine learning to uncover lncRNA LINC00269 as a key regulator in Parkinson's disease via pyroptosis pathways

BackgroundPyroptosis, a specific type of programmed cell death, which has become a significant factor to Parkinson's disease (PD). Concurrently, long non-coding RNAs (lncRNAs) have garnered attention for their regulatory roles in neurodegenerative disorders. This study was designed to ascertain the key lncRNAs in pyroptosis pathways of PD and elucidate their regulatory mechanisms.MethodsEmploying a combination of bioinformatics and machine learning, we analyzed PD data sets GSE133347 and GSE110716. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) recognized different lncRNAs. Through various algorithms such as Least Absolute Shrinkage and Selection Operator (LASSO), Random Forest (RF), and Weighted Gene Co-expression Network Analysis (WGCNA), we recognized LINC01606 and LINC00269, which are key factors during the emergence and development of PD. Furthermore, experimental validation was conducted in PD mouse models to confirm these bioinformatics findings.ResultsThe analysis showed that there were a large number of apoptosis-related gene expression changes in Parkinson's syndrome, for example, CASP1 and GSDME were up-regulated, and CASP9 and AIM2 were down-regulated. Among the lncRNAs, LINC01606 and LINC00269 were identified as potential modulators of pyroptosis. Notably, LINC00269 was observed to be significantly downregulated in the brain tissues of a PD mouse model, supporting its involvement in PD. The study also highlighted potential interactions of these lncRNAs with genes like ONECUT2, PRLR, CTNNA3, and LRP2.ConclusionsThis study identifies LINC00269 as a potential contributor to pyroptosis pathways in PD. While further investigation is required to fully elucidate its role, these findings provide new insights into PD pathogenesis and suggest potential avenues for future research on diagnostic and therapeutic targets. The study underscores the importance of integrating bioinformatics with experimental validation in neurodegenerative disease research.

Identification of hub programmed cell death-related genes and immune infiltration in Crohn’s disease using bioinformatics

BackgroundCrohn’s disease (CD) is an immune-mediated disorder characterized by immune cell infiltration that induces persistent chronic inflammation of the gastrointestinal tract. Programmed cell death (PCD) plays a critical role in the pathogenesis of CD. This study identified vital PCD-related genes in CD based on immune infiltration using bioinformatic analysis.MethodsWe obtained two CD datasets from the Gene Expression Omnibus (GEO) database and examined immune cell infiltration to investigate immune cell dysregulation in CD. PCD-related genes were retrieved from the GeneCards database. Based on the differentially expressed genes (DEGs) and PCD gene sets, PCD-related DEGs were identified. Candidate hub genes were identified using a protein-protein interaction (PPI) network, and their diagnostic effectiveness was predicted using receiver operating characteristic (ROC) curve analysis. Functional enrichment and immune infiltration analyses were used to assess the distinct roles of the hub genes. Finally, the miRWalk and ENCORI databases were used to predict which microRNAs (miRNAs) regulated the hub genes and to verify gene expression in CD colonic tissues via transcriptome sequencing.ResultsA total of 335 PCD-related DEGs and 3 hub genes (MMP1, SAA1, and PLAU) were identified. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional analyses indicated the enrichment of these genes in the immune response. Infiltration analysis of immune cells showed abundant endothelial cells, plasma cells, dendritic cells, and monocytes in the CD samples. Based on the correlation analysis, the three hub genes were positively correlated with monocytes and negatively correlated with CD8 naïve T-cells. MMP1, SAA1, and PLAU correlated with the pathogenicity of CD and had good diagnostic value for CD. The three hub genes were highly expressed in the CD tissues, as confirmed using transcriptome sequencing.ConclusionThis study identified MMP1, SAA1, and PLAU as hub genes involved in PCD in patients with CD. These genes regulate immune cell function and their expression levels are closely related to immune cell infiltration. These findings provide novel insights into the mechanisms underlying CD pathogenesis. The identified PCD genes and regulatory miRNAs are potential biomarkers and therapeutic targets for CD.

Comprehensive analysis of lysine lactylation and its potential biological significance in clear cell renal cell carcinoma

BackgroundClear cell renal cell carcinoma (ccRCC) is a common histological subtype of malignant renal neoplasm. Protein lysine lactylation (Kla) plays a crucial role in tumor metabolic reprogramming. However, little is known regarding the distribution and potential biological functions of Kla in ccRCC. This study aimed to systematically investigate the role of Kla in ccRCC.MethodsA total of 12 ccRCC samples were collected from 6 patients. Western blotting was performed to determine the trend of Kla-modified proteins in ccRCC. Liquid chromatography–tandem mass spectrometry was used to quantitatively analyze Kla in ccRCC. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and protein–protein interaction (PPI) network analyses were conducted to clarify the biological functions and interactional relationships of differentially lactylated proteins (DLPs).ResultsIn total, 239 DLPs, including 441 lactylated sites, were identified by comparing ccRCC tissues with adjacent normal tissues. Kla-related enzymes have a higher affinity for alanine than for other amino acid residues in ccRCC. Subcellular localization analysis revealed that most DLPs were localized in the cytoplasm and mitochondria. GO enrichment analysis showed that most of the DLPs were enriched in metabolism-associated biological processes, including the purine ribonucleotide, monocarboxylic acid, ribonucleoside triphosphate, purine nucleoside triphosphate, and ATP metabolic processes. KEGG analysis indicated that most DLPs were also enriched in metabolism-related pathways, including glycolysis, amino acid (valine, leucine, and isoleucine) degradation, pyruvate metabolism, fatty acid degradation, and the citrate cycle. The top 20 hub proteins were screened from the PPI network based on their degree ranks.ConclusionsThis study revealed the role of Kla in ccRCC, which will extend our understanding of the potential molecular mechanisms underlying ccRCC formation and progression. These key Kla-modified proteins may be promising therapeutic targets for the treatment of ccRCC. However, further molecular experiments are required to validate these findings.

Comparative Transcriptome and Weighted Gene Co-Expression Network Analysis of Eggplant (Solanum melongena L.) Reveals Key Genes Responding to Ralstonia solanacearum Infection

Eggplant (Solanum melongena L.) is a widely cultivated vegetable belonging to the family Solanaceae. However, it is highly susceptible to yield reduction owing to soil-borne diseases caused by bacterial wilt (BW) (Ralstonia solanacearum L.). Therefore, understanding the mechanism of bacterial wilt resistance in eggplant is helpful for genetic improvement to create cultivars with strong bacterial wilt resistance. In this study, we conducted a comparative analysis of transcriptomics from eggplant varieties of different genotypes following infection with R. solanacearum. Transcriptome analysis revealed the majority of differentially expressed genes (DEGs) primarily implicated in pathways such as the MAPK signaling pathway, plant hormone signal transduction, and plant–pathogen interactions, as determined using Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. The expression profiles of hormone pathway genes suggest that salicylic acid, ethylene, and jasmonic acid may play significant roles in conferring bacterial wilt resistance. DEGs from the leaves, roots, and stems were partitioned into 14 modules. Among these, the black module exhibited the strongest correlation with target traits and 16 hub genes were identified using gene co-expression network analysis. Subsequently, seven hub genes were selected for validation using RT-qPCR, and the results were consistent with the RNA-seq data. Notably, upon gene annotation, a significant proportion of the hub genes were annotated as heat shock proteins (HSPs) or heat shock transcription factors (HSFs). These findings offer valuable insights for advancing research on the molecular genetic mechanisms through which HSPs/HSFs contribute to bacterial wilt resistance in eggplant.

Dissecting Interactions of Saccharomyces cerevisiae and Pichia kudriavzevii to Shape Kiwifruit Wine Flavor

Mixed fermentation with Saccharomyces cerevisiae and Pichia kudriavzevii has been shown to enhance wine aroma, yet the underlying mechanisms remain unclear. Monoculture of S. cerevisiae, monoculture of P. kudriavzevii, and mixed culture of S. cerevisiae and P. kudriavzevii were conducted, and the study analyzed and compared the biomass, flavor profile, and transcriptome responses of the three groups. Both yeast species exhibited growth inhibition in mixed culture, especially P. kudriavzevii. Significant differences were observed in three organic acids and the foremost 20 volatile compounds. Mixed fermentation enhanced esters (e.g., ethyl butyrate, isoamyl acetate) and volatile acids (e.g., hexanoic acid), but decreased isobutanol, phenylethyl alcohol, and quinic acid. Transcriptomic analysis revealed 294 and 332 differentially expressed genes (DEGs) in S. cerevisiae and P. kudriavzevii, respectively. The Kyoto Encyclopedia of Genes and Genomes (KEGG) annotation results indicated that DEGs in mixed fermentation were concentrated in carbohydrate metabolism and amino acid metabolism. Our integrated analysis suggested that genes such as TDH2, TDH3, and ENO2 were pivotal for ester biosynthesis. Moreover, ADH1, ADH2, HPA3, ALD6, and ARO8 were associated with quinic acid synthesis. Furthermore, ILV2, ILV5, ALD6, and others were central to the production of isobutanol and phenylethyl alcohol.

Identification and functional analysis of novel biomarkers related to retinal neovascularization in proliferative diabetic retinopathy

Background Proliferative diabetes retinopathy (PDR) seriously affects the vision of patients. Exploring the key genes of retinal neovascularization is crucial for developing new biomarkers and therapeutic targets. Objective This study aimed to identify key genes associated with retinal neovascularization in Proliferative Diabetic Retinopathy (PDR), intending to develop new biomarkers and therapeutic targets. This would further our understanding of the progression of diabetic retinopathy and improve patient prognosis. Methods The gene data from 36 diabetic retinopathy patient samples and 45 samples from healthy volunteers or diabetic patients were selected from the GEO DataSets (Gene Expression Omnibus), specifically datasets GSE102485 and GSE160310. Utilizing the SVA algorithm to merge datasets and the limma package in R to identify differentially expressed genes (DEGs), we conducted a bioinformatic analysis of diabetic retinopathy. Functional insights were gained through DAVID database analyses, while STRING database-derived Protein-Protein Interaction (PPI) networks visualized in Cytoscape provided further context. Key genes were identified through LASSO regression and SVM analyses, with ROC curves assessing their diagnostic value. Single gene set enrichment analysis (GSEA) enhanced our understanding of the perturbed biological processes and pathways, advancing knowledge of diabetic retinopathy at the genomic level. Results A rigorous bioinformatic analysis yielded a comprehensive list of 1139 differentially expressed genes (DEGs), of which six pivotal genes—KDM5D, AC007040.11, AC015688.3, NLRP2, GYPC, and TMSB4Y—were identified as central to the study. These six genes consistently demonstrated a high diagnostic accuracy, with each exhibiting an area under the receiver operating characteristic (ROC) curve (AUC) exceeding 0.75. Gene Ontology (GO) enrichment analysis elucidated their primary roles in intricate biological processes, including inflammatory and immune responses, T-cell activation, cell apoptosis, and angiogenesis. Moreover, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment revealed their involvement in crucial signaling cascades such as cytokine-cytokine receptor interactions, cell adhesion molecule pathways, PI3K-Akt signaling, and hematopoietic cell lineage, further substantiating their significance in the pathogenesis of diabetic retinopathy. Conclusions In this research, we conducted a comprehensive gene expression analysis in patients with and without PDR, identifying differentially expressed genes, pivotal biomarkers, and critical pathways potentially involved in PDR progression. Our findings enhance understanding of PDR's molecular dynamics and offer potential avenues for improved prognostication and therapeutic intervention, despite limitations due to sample group heterogeneity.

Non-Targeted Metabolomics Analysis Reveals Metabolite Profiles Change During Whey Fermentation with Kluyveromyces marxianus

Background: Whey fermentation could produce bioactive substances with immunomodulatory effects, metabolic syndrome modulation, and antioxidant properties, thereby imparting functional characteristics to products and facilitating the development of novel foods with health-promoting potential. Methods: A non-targeted metabolomics approach using liquid chromatography–mass spectrometry (LC-MS) was employed to investigate changes in the metabolite profiles of whey fermented by Kluyveromyces marxianus strain KM812 over varying fermentation durations. Results: The findings demonstrated a progressive enrichment of metabolites over time. A total of 151 differential metabolites were identified and categorized primarily into amino acids, peptides, and analogues, fatty acids and conjugates, and carbohydrates and conjugates, as well as benzoic acids and derivatives. The highest relative content of whey metabolites was observed at 48 h of fermentation, with a cumulative increase of 1.45-fold, 1.49-fold, 3.39-fold, and 1.24-fold for peptides and amino acids, peptides, and analogues, fatty acids and conjugates, and carbohydrates and conjugates, respectively. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed associations with 23 specific metabolites and delineated 9 metabolic pathways, predominantly involved in amino acid and lipid metabolism. Conclusions: Based on the above, KM812 could effectively degrade macromolecular substances in whey into small molecules such as L-isoleucine, ornithine, betaine, α-linolenic acid, and palmitoleic acid, thereby influencing the nutritional and functional properties of whey. In-depth analysis of the metabolic products in KM812-fermented whey could provide a theoretical basis for the development of functional foods derived from small molecules in the future.

Transcriptome Analysis Reveals Sertoli Cells Adapting Through Redox and Metabolic Pathways Under Heat Stress in Goats

Background/Objectives: Climate change-induced temperature elevations pose significant challenges to livestock reproduction, particularly affecting testicular function in small ruminants. This study investigates the acute heat-stress response in goat Sertoli cells (SCs), aiming to elucidate the molecular mechanisms underlying heat-induced damage to male reproductive tissues. Methods: SCs were isolated from testes of 4-month-old black goats and exposed to heat stress (44 °C for 2.5 h). We employed transcriptome sequencing, CCK-8 assay, electron microscopy, ROS measurement, autophagy detection, Western blot analysis, and lactate concentration measurement. Bioinformatics analyses including Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, and protein–protein interaction network analyses were performed on the transcriptome data. Results: Heat stress significantly reduced SC viability, induced oxidative stress and autophagy, and altered gene expression profiles. We identified 1231 significantly differentially expressed genes, with significant enrichment in membrane-related processes and metabolic pathways. Metabolism-related genes, including PKLR, ACOT11, and LPCT12, were significantly downregulated. Protein–protein interaction network analysis revealed ten hub genes potentially crucial in the heat-stress response: HSP90AA1, HSPA5, BAG3, IGF1, HSPH1, IL1A, CCL2, CXCL10, ALB, and CALML4. Conclusions: This study provides comprehensive insights into the molecular mechanisms underlying goat SC response to heat stress. The identified genes and pathways, particularly those related to metabolism and stress response, offer potential targets for developing strategies to mitigate heat-stress effects on livestock reproduction. These findings contribute to our understanding of climate change impacts on animal husbandry and may inform the development of heat-stress resistant livestock lines.

Identification of Key Post‐modification Enzymes Involved in the Biosynthesis of Lanostane‐type Triterpenoids in the Medicinal Mushroom Antrodia camphorata.

AbstractLanostane‐type triterpenoids are important bioactive secondary metabolites of mushrooms, though their biosynthetic study has been challenging due to scattered genes. Herein, the strategies of combining metabolomics and transcriptomics analyses, functional motif blast, and KEGG (Kyoto Encyclopedia of Genes and Genomes) annotation were used to discover three key post‐modification enzymes involved in the biosynthesis of lanostanoids in the medicinal mushroom Antrodia camphorata. The cytochrome P450 enzyme AcCYP4 could generate a Δ7,9(11) diene structure and introduce a 15α‐hydroxy group to the triterpene skeleton. The short‐chain dehydrogenase AcSDR6 could regio‐ and stereo‐ selectively catalyze the dehydrogenation of 3β‐OH to produce 3‐keto triterpenoids, and the catalytic mechanisms were interpreted by crystal structure analysis. AcSMT1 could introduce the methyl group at C‐24 to produce a unique 31‐carbon triterpene skeleton. This work elucidated the major biosynthetic pathway of Antrodia lanostanoids in vitro, and the discovered enzymes could be used to synthesize a series of bioactive triterpenoids.

Investigating the Potential Effects of 6PPDQ on Prostate Cancer Through Network Toxicology and Molecular Docking

(1) Background: N-(1,3-Dimethylbutyl)-N′-phenyl-p-phenylenediamine-quinone (6PPDQ), as a newly discovered environmental toxin, has been found more frequently in our living conditions. The literature reports that damage to the reproductive and cardiovascular system is associated with exposure to 6PPDQ. However, the relationship between 6PPDQ and cancer still requires more investigation. This research aims to investigate the association between 6PPDQ and prostate cancer. (2) Methods and Results: Based on the data retrieved from the Pharmmapper, CTD, SEA, SwissTargetPrediction, GeneCard, and OMIM databases, we summarized 239 potential targets utilizing the Venn tool. Through the STRING network database and Cytoscape software, we constructed a PPI network and confirmed ten core targets, including IGF1R, PIK3R1, PTPN11, EGFR, SRC, GRB2, JAK2, SOS1, KDR, and IRS1. We identified the potential pathways through which 6PPDQ acts on these core targets using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. Ultimately, through molecular docking methods, 6PPDQ binds closely with these ten core targets. These findings indicate that 6PPDQ may influence the proteins related to prostate cancer and may be linked to prostate cancer via several known signaling pathways. (3) Conclusions: This article employs innovative network toxicology to elucidate the prostate carcinogenic effects of 6PPDQ through its modulation of specific vital genes and signaling pathways, thereby establishing a foundational platform for future investigations into the impact of 6PPDQ on prostate cancer and potentially other tumors.

To explore the protective mechanism of promethazine against hippocampal neuron injury based on network pharmacology and experimental verification.

This study aims to investigate the effect of promethazine (PMZ) on hippocampal neuronal injury through network pharmacology and in vivo experiments. Network pharmacology: The intersection genes of PMZ and Alzheimer Disease (AD) were obtained, and the core genes of PMZ in AD were screened. The intersection genes were enriched by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. In the in vitro experiment, mouse hippocampal neurons (HT22) were divided into control, glutamate (GLU) model, and GLU + PMZ treatment groups. The control group was given a complete culture medium, the model group was given GLU for 24 hours, the treatment group was given PMZ pretreatment for 3 hours, and then GLU was administered for 24 hours. Cell viability was determined, cell morphology was observed by microscopy, reactive oxygen species levels and glutathione content were detected, and protein expression of P53, PTGS2, SLC7A11, and GPX4 was detected by western blotting. Network pharmacology: A total of 317 PMZ targets, 1934 AD genes, 125 intersection genes, and 18 core genes, including P53 and PTGS2. Gene Ontology enrichment analysis showed that the effect of PMZ on AD was mainly related to cell proliferation, inflammation, hypoxia, synaptic structure, plasma membrane, and oxidoreductase activity. Kyoto Encyclopedia of Genes and Genomes results showed neuroactive ligand-receptor interaction, cell senescence, cancer pathway, PI3K-AKT signal pathway, neurodegeneration, and HIF-1 signal pathway. In vitro experiments: PMZ improved the GLU-induced decrease in cell viability and morphological changes in hippocampal neurons. PMZ inhibited reactive oxygen species levels and increased glutathione content in injured hippocampal neurons. Up-regulated of P53, SLC7A11 and GPX4 expression, and inhibited expression of PTGS2. PMZ regulates the SLC7A11-GPX4 antioxidant system to protect hippocampal neurons from oxidative stress injury.

Identification of genetic associations between acute myocardial infarction and non-small cell lung cancer

IntroductionA growing body of evidence suggests a potential connection between myocardial infarction (MI) and lung cancer (LC). However, the underlying pathogenesis and molecular mechanisms remain unclear. This research aims to identify common genes and pathways between MI and LC through bioinformatics analysis.MethodsTwo public datasets (GSE166780 and GSE8569) were analyzed to identify differentially expressed genes (DEGs). Common DEGs were enriched using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). Hub genes were identified and their diagnostic performance was evaluated. Gene co-expression networks, as well as regulatory networks involving miRNA-hub genes and TF-hub genes, were also constructed. Finally, candidate drugs were predicted.ResultsAmong the datasets, 34 common trend DEGs were identified. Enrichment analysis linked these DEGs to key biological processes, cellular components, and molecular functions. Eight hub genes (CEBPA, TGFBR2, EZH2, JUNB, JUN, FOS, PLAU, COL1A1) were identified, demonstrating promising diagnostic accuracy. Key transcription factors associated with these hub genes include SP1, ESR1, CREB1, ETS1, NFKB1, and RELA, while key miRNAs include hsa-mir-101-3p, hsa-mir-124-3p, hsa-mir-29c-3p, hsa-mir-93-5p, and hsa-mir-155-5p. Additionally, potential therapeutic drugs were identified, with zoledronic acid anhydrous showing potential value in reducing the co-occurrence of the two diseases.DiscussionThis study identified eight common signature genes shared between NSCLC and AMI. Validation datasets confirmed the diagnostic value of key hub genes COL1A1 and PLAU. These findings suggest that shared hub genes may serve as novel therapeutic targets for patients with both diseases. Ten candidate drugs were predicted, with zoledronic acid showing potential for targeting dual hub genes, offering a promising therapeutic approach for the comorbidity of lung cancer and myocardial infarction.

Hypoxia reconstructed colorectal tumor microenvironment weakening anti-tumor immunity: construction of a new prognosis predicting model through transcriptome analysis

BackgroundHypoxia in the tumor microenvironment (TME) plays a pivotal role in the progression and prognosis of colorectal cancer (CRC). However, effective methods for assessing TME hypoxia remain lacking. This study aims to develop a novel hypoxia-related prognostic score (HPS) based on hypoxia-associated genes to improve CRC prognostication and inform treatment strategies.MethodsTranscriptomic data from CRC patients were analyzed using Lasso regression to identify hypoxia-associated genes with the strongest prognostic significance. The identified genes were validated in vitro by assessing their expression under normoxic and hypoxic conditions in normal intestinal epithelial cells and CRC tumor cell lines. Functional relevance was explored through differential gene expression analysis, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses, and protein-protein interaction (PPI) network construction. The association of HPS with extracellular matrix (ECM) composition, immune cell infiltration, and immune suppression was also investigated.ResultsSeven hypoxia-associated signature genes were identified, each demonstrating a strong correlation with CRC prognosis. The hypoxia-related prognostic score (HPS), derived from these genes, was significantly linked to changes in the TME. Specifically, HPS values were associated with alterations in ECM composition and distinct immune cell infiltration patterns. Higher HPS values corresponded to increased infiltration of immune-suppressive cells and reduced presence of anti-tumor immune cells. This imbalance promoted an immune-suppressive TME, facilitating tumor progression and immune evasion.ConclusionsThe hypoxia-related prognostic score (HPS) captures the regulatory influence of TME hypoxia on immune responses, offering valuable insights into its role in tumor progression. HPS holds promise as a prognostic tool and a guide for developing personalized treatment strategies in CRC.

Immune-related gene characterization and biological mechanisms in major depressive disorder revealed based on transcriptomics and network pharmacology

BackgroundMajor depressive disorder (MDD) is a severe psychiatric disorder characterized by complex etiology, with genetic determinants that are not fully understood. The objective of this study was to investigate the pathogenesis of MDD and to explore its association with the immune system by identifying hub biomarkers using bioinformatics analyses and examining immune infiltrates in human autopsy samples.MethodsGene microarray data were obtained from the Gene Expression Omnibus (GEO) datasets GSE32280, GSE76826, GSE98793, and GSE39653. Our approach included differential expression analysis, weighted gene co-expression network analysis (WGCNA), and protein-protein interaction (PPI) network analysis to identify hub genes associated with MDD. Subsequently, gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Cytoscape plugin CluGO, and Gene Set Enrichment Analysis (GSEA) were utilized to identify immune-related genes. The final selection of immune-related hub genes was determined through the least absolute shrinkage and selection operator (Lasso) regression analysis and PPI analysis. Immune cell infiltration in MDD patients was analyzed using CIBERSORT, and correlation analysis was performed between key immune cells and genes. The diagnostic accuracy of the identified hub genes was evaluated using receiver operating characteristic (ROC) curve analysis. Furthermore, we conducted a study involving 10 MDD patients and 10 healthy controls (HCs) meeting specific criteria to assess the expression levels of these hub genes in their peripheral blood mononuclear cells (PBMCs). The Herbal Ingredient Target Database (HIT) was employed to screen for herbal components that target these genes, potentially identifying novel therapeutic agents.ResultsA total of 159 down-regulated and 51 up-regulated genes were identified for further analysis. WGCNA revealed 12 co-expression modules, with modules “darked”, “darkurquoise” and “light yellow” showing significant positive associations with MDD. Functional enrichment pathway analysis indicated that these differential genes were associated with immune functions. Integration of differential and immune-related gene analysis identified 21 common genes. The Lasso algorithm confirmed 4 hub genes as potential biomarkers for MDD. GSEA analysis suggested that these genes may be involved in biological processes such as protein export, RNA degradation, and fc gamma r mediated cytotoxis. Pathway enrichment analysis identified three highly enriched immune-related pathways associated with the 4 hub genes. ROC curve analysis indicated that these hub genes possess good diagnostic value. Quantitative reverse transcription-polymerase chain reaction (RT-qPCR) demonstrated significant expression differences of these hub genes in PBMCs between MDD patients and HCs. Immune infiltration analysis revealed significant correlations between immune cells, including Mast cells resting, T cells CD8, NK cells resting, and Neutrophils, which were significantly correlated with the hub genes expression. HIT identified one herb target related to IL7R and 14 targets related to TLR2.ConclusionsThe study identified four immune-related hub genes (TLR2, RETN, HP, and IL7R) in MDD that may impact the diagnosis and treatment of the disorder. By leveraging the GEO database, our findings contribute to the understanding of the relationship between MDD and immunity, presenting potential therapeutic targets.