Pathway Enrichment Research Articles

Elucidating the role of PPARG inhibition in enhancing MERS virus immune response: A network pharmacology and computational drug discovery

BackgroundMiddle East Respiratory Syndrome (MERS) has become a severe zoonotic disease, posing significant public health concerns due to the lack of specific medications. This urgently demands the development of novel therapeutic molecules. Understanding MERS's genetic underpinnings and potential therapeutic targets is crucial for developing effective treatments. MethodsTwo gene expression datasets (GSE81909 and GSE100504) were analyzed to identify differentially expressed genes (DEGs) using GEO2R. Furthermore, gene ontology (GO), pathway enrichment analysis, and protein-protein interaction (PPI) network were performed to understand the gene’s functions. A possible drug target was identified, and an FDA-approved drug library was screened against the selected target using molecular docking and validated the findings through molecular dynamics simulation, principal component analysis, free energy landscape, and MM/GBSA calculations. ResultsThe study on GSE81909 and GSE100504 datasets with icMERS and MOCK samples at 24 and 48 h revealed an upregulation in 73 and 267 DEGs, respectively. In the network pharmacology, STAT1, MX1, DDX58, EIF2AK2, ISG15, IFIT1, IFIH1, OAS1, IRF9, and OASL were identified as the top 10 hub genes. STAT1 was identified as the most connected hub gene among these top 10 hub genes, which plays a crucial role in the immune response to the MERS virus. Further study on STAT1 showed that PPARG helps reduce STAT1, which could modulate the immune response. Therefore, by inhibiting PPARG, the immunological response can be successfully enhanced. The known inhibitor of PPARG, 570 (Farglitazar), was used as a control. Further, screening using Tanimoto and K-mean clustering was performed, from which three compounds were identified: 2267, 3478, and 40326. Compound 3478 showed characteristics similar to the control, indicating robust binding to PPARG. 3478 showed the highest negative binding free energy with −41.20 kcal/mol, indicating strong binding with PPARG. ConclusionsThese findings suggest that 3478 promises to be a potential inhibitor of PPARG, and further experimental investigations can explore its potential as a MERS inhibitor.

Comparative analysis of meningeal transcriptomes in birds: Potential pathways of resilience to repeated impacts.

The meninges and associated vasculature (MAV) play a crucial role in maintaining cerebral integrity and homeostasis. Recent advances in transcriptomic analysis have illuminated the significance of the MAV in understanding the complex physiological interactions at the interface between the skull and the brain after exposure to mechanical stress. To investigate how physiological responses may confer resilience against repetitive mechanical stress, we performed the first transcriptomic analysis of avian MAV tissues using the Downy Woodpecker (Dryobates pubescens) and Tufted Titmouse (Baeolophus bicolor) as the comparison species. Our findings reveal divergences in gene expression profiles related to immune response, cellular stress management, and protein translation machinery. The male woodpeckers exhibit a tailored immune modulation strategy that potentially dampens neuroinflammation while preserving protective immunity. Overrepresented genes involved in cellular stress responses suggest enhanced mechanisms for mitigating damage and promoting repair. Additionally, the enrichment of translation-associated pathways hints at increased capacity for protein turnover and cellular remodeling vital for recovery. Our study not only fills a critical gap in avian neurobiology but also lays the groundwork for research in comparative neuroprotection.

Identification of the effects of hypoxia on the liver tissues of Nile tilapia Oreochromis Niloticus

BackgroundHypoxia stress resulted in mortality during the fish aquaculture program, affecting the sustainable development of the aquaculture industry. The Egyptian strain of O. niloticus showed a strong ability to hypoxia. In this study, a Nile tilapia strain that was kept and selected for 45 years by the author’s team was used to elucidate the mechanism of the hypoxia response in the liver, including the identification of metabolic pathways and genes, involved in the hypoxia response of this strain.ResultsThe effects of hypoxia stress were detected at 0-hour, 6-hour, and 72-hour time points (0 h, 6 h, 72 h) on tilapia liver at 1 mg/L dissolved oxygen conditions. The blood triglyceride, blood glucose and cholesterol values exhibited significantly different change trends, but the hemoglobin content showed no significant differences between 0 h, 6 h and 72 h (P > 0.05). The activities of catalase (CAT), glutathione peroxidase (GSH-PX), total antioxidant capacity (T-AOC), lactate dehydrogenase (LDH), and acid phosphatase (ACP) in the liver tissue gradually increased at 0 h, 6 h and 72 h (P < 0.05). Histological analyses revealed structural changes in intracellular lipid droplets, nuclear migration and dissolution, and cell vacuolization in liver tissues. Six pathways were identified as the main enriched metabolic pathways according to the transcriptome profiling analysis, which were protein processing in endoplasmic reticulum, steroid biosynthesis, peroxisome, PPAR signaling pathway, glycolysis/gluconeogenesis and Insulin signaling pathway. The expressions of the important differentially expressed genes were verified by qPCR analysis, including erola, LOC100692144, sqle, cratb, pipox, cpt1a2b, hik and acss2l, ehhadh, prkcz, fasn and plaa, which showed the same expressions trends as those of RNA-Seq.ConclusionsThe Nile tilapia strain improves the abilities of hypoxia response through energy metabolism. Antioxidant enzyme measurements in the liver indicate that these five antioxidant enzymes play important roles in protecting the body from hypoxic damage. The histological changes in liver cells indicate that the damage caused by hypoxia stress. The immune-related metabolic pathways and energy metabolism-related pathways were obtained by transcriptome profiling, and these metabolic pathways and the differentially expressed genes selected from these metabolic pathways may be involved in the mechanism of hypoxia tolerance in this strain. These findings provide a better understanding of the hypoxia response mechanism of fish, and represent a useful resource for the genetic breeding of O. niloticus.

In-silico analysis predicts disruption of normal angiogenesis as a causative factor in osteoporosis pathogenesis

Angiogenesis-osteogenesis coupling is critical for proper functioning and maintaining the health of bones. Any disruption in this coupling, associated with aging and disease, might lead to loss of bone mass. Osteoporosis (OP) is a debilitating bone metabolic disorder that affects the microarchitecture of bones, gradually leading to fracture. Computational analysis revealed that normal angiogenesis is disrupted during the progression of OP, especially postmenopausal osteoporosis (PMOP). The genes associated with OP and PMOP were retrieved from the DisGeNET database. Hub gene analysis and molecular pathway enrichment were performed via the Cytoscape plugins STRING, MCODE, CytoHubba, ClueGO and the web-based tool Enrichr. Twenty-eight (28) hub genes were identified, eight of which were transcription factors (HIF1A, JUN, TP53, ESR1, MYC, PPARG, RUNX2 and SOX9). Analysis of SNPs associated with hub genes via the gnomAD, I-Mutant2.0, MUpro, ConSurf and COACH servers revealed the substitution F201L in IL6 as the most deleterious. The IL6 protein was modeled in the SWISS-MODEL server and the substitution was analyzed via the YASARA FoldX plugin. A positive ΔΔG (1.936) of the F201L mutant indicates that the mutated structure is less stable than the wild-type structure is. Thirteen hub genes, including IL6 and the enriched molecular pathways were found to be profoundly involved in angiogenesis/endothelial function and immune signaling. Mechanical loading of bones through weight-bearing exercises can activate osteoblasts via mechanotransduction leading to increased bone formation. The present study suggests proper mechanical loading of bone as a preventive strategy for PMOP, by which angiogenesis and the immune status of the bone can be maintained. This in silico analysis could be used to understand the molecular etiology of OP and to develop novel therapeutic approaches.

Transcriptomic insights into mycorrhizal interactions with tomato root: a comparative study of short- and long-term post-inoculation responses.

Arbuscular mycorrhiza (AM) refers to a symbiotic association between plant roots and fungi that enhances the uptake of mineral nutrients from the soil and enables the plant to tolerate abiotic and biotic stresses. Although previously reported RNA-seq analyses have identified large numbers of AM-responsive genes in model plants, such as Solanum lycopersicum L., further studies are underway to comprehensively understand the complex interactions between plant roots and AM, especially in terms of the short- and long-term responses after inoculation. Herein, we used RNA-seq technology to obtain the transcriptomes of tomato roots inoculated with the fungus Rhizophagus irregularis at 7 and 30days post inoculation (dpi). Of the 1,019 differentially expressed genes (DEGs) in tomato roots, 635 genes showed differential expressions between mycorrhizal and non-mycorrhizal associations at the two time points. The number of upregulated DEGs far exceeded the number of downregulated ones at 7 dpi, and this difference decreased at 30dpi. Several notable genes were particularly involved in the plant defense, plant growth and development, ion transport, and biological processes, namely, GABAT, AGP, POD, NQO1, MT4, MTA, and AROGP3. In addition, the Kyoto encyclopedia of genes and genomes pathway enrichment analysis revealed that some of the genes were involved in different pathways, including those of ascorbic acid (AFRR, GME1, and APX), metabolism (CYP, GAPC2, and CAM2), and sterols (CYC1 and HMGR), as well as genes related to cell division and cell cycle (CDKB2 and PCNA). These findings provide valuable new data on AM-responsive genes in tomato roots at both short- and long-term postinoculation stages, enabling the deciphering of biological interactions between tomato roots and symbiotic fungi.

Bioinformatics-based analysis of EMT-related genes in cervical cancer patients

Background: In most cases, patients who are not screened canonically have advanced disease by the time they are first diagnosed. Therefore, invasive metastasis is the main feature and cause of death in patients with advanced cervical cancer. Methods: The GEO database was searched for analytical data on cervical cancer. The GSE9750 dataset was employed to identify differentially expressed genes (DEGs) in tumor samples compared to normal samples, carry out enrichment analysis, build protein-protein interaction (PPI) networks to identify key genes (Hub gene), and perform between diagnostic genes and immune infiltrated cells. Results: A total of 1440 DEGs and 46 differential genes linked to EMT were screened. GO enrichment produced 455 results, and Kyoto Encyclopedia of Genes and Genomes pathway enrichment （KEGG ）yielded a total of 18 pathways. A PPI network was built using 46 differential genes related to EMT, and 9 Hub genes were also validated. Nine hub genes had exactly the same up- and down-regulation trend as before in the external verification set, but only six hub genes were ultimately determined to be diagnostic genes after further validation by the external verification set. The results of the KM (Kaplan-Meier) survival study also revealed five prognostic genes related to survival, namely MMP1, CXCL8, SSP1, MMP3, and VCAM1. Conclusion: The genes MMP1, CXCL8, SSP1, MMP3, and VCAM1are crucial in the development of EMT in patients with cervical cancer and can be employed as both diagnostic and therapeutic targets during the progression of EMT in cervical cancer patients.

Jun modulates endoplasmic reticulum stress-associated ferroptosis in dorsal root ganglia neurons during neuropathic pain by regulating Timp1

Neuropathic pain (NP) is a complex disorder caused by lesions or diseases affecting the somatosensory nervous system, severely impacting patients' quality of life. Recent studies suggest ferroptosis may be involved in NP induction, but its precise mechanisms remain unclear. We used GO and KEGG pathway enrichment analyses to functionally annotate ferroptosis-related differentially expressed genes (FRDs). Through STRING and the maximum cluster centrality (MCC) algorithm, we identified five hub FRDs (Jun, Timp1, Egfr, Cdkn1a, Cdkn2a). Single-cell analysis revealed significant expression of Jun and Timp1 in neurons. Our study confirmed the association between ferroptosis and endoplasmic reticulum stress (ERS) in NP and validated changes in hub FRD expression across various NP animal models. In vitro experiments demonstrated that Jun regulates neuronal ferroptosis and ERS, particularly by modulating Timp1 expression. Transcription factor prediction and JASPAR binding site analysis elucidated the regulatory network involving Jun. ROC curve analysis of external datasets highlighted the diagnostic potential of hub FRDs and ERS-related differentially expressed genes (ERSRDs) in NP. Using the Comparative Toxicogenomics Database (CTD), we identified estradiol (E2) as a potential therapeutic drug targeting hub FRDs and ERSRDs. Molecular docking predicted its binding sites with Jun and Timp1, and in vivo experiments confirmed that E2 alleviated NP and reversed the expression of Jun and Timp1. This study underscores the crucial role of Jun and Timp1 in the interplay between ferroptosis and ERS, offering new insights and promising avenues for NP treatment.

Inflammatory profile of eosinophils in asthma-COPD overlap and eosinophilic COPD: a multi-omics study.

Elevated blood eosinophil levels in patients with chronic obstructive pulmonary disease (COPD) with or without asthma are linked to increased exacerbations and the effectiveness of inhaled corticosteroid treatment. This study aimed to delineate the inflammatory cellular properties of eosinophils in patients with asthma-COPD overlap (ACO) and eosinophilic COPD (eCOPD). Eosinophils were isolated from the peripheral blood of healthy volunteers, patients with non-eCOPD, and those with ACO/eCOPD. Multi-omics analysis involving transcriptomics, proteomics, and lipidomics was performed, followed by bioinformatic data analyses. In vitro experiments using eosinophils from healthy volunteers were conducted to investigate the molecular mechanisms underlying cellular alterations in eosinophils. Proteomics and transcriptomics analyses revealed cellular characteristics in overall COPD patients represented by viral infection (elevated expression of sterol regulatory element-binding protein-1) and inflammatory responses (elevated levels of IL1 receptor-like 1, Fc epsilon receptor Ig, and transmembrane protein 176B). Cholesterol metabolism enzymes were identified as ACO/eCOPD-related factors. Gene Ontology and pathway enrichment analyses demonstrated the key roles of antiviral responses, cholesterol metabolism, and inflammatory molecules-related signaling pathways in ACO/eCOPD. Lipidomics showed the impaired synthesis of cyclooxygenase-derived mediators including prostaglandin E2 (PGE2) in ACO/eCOPD. In vitro assessment confirmed that IL-33 or TNF-α stimulation combined with IL-5 and IFN-γ stimulation induced cellular signatures in eosinophils in ACO/eCOPD. Atorvastatin, dexamethasone, and PGE2 differentially modulated these inflammatory changes. ACO/eCOPD is associated with viral infection and an inflammatory milieu. Therapeutic strategies using statins and inhaled corticosteroids are recommended to control these pathogenic changes.

Whole‑exome sequencing insights into synchronous bilateral breast cancer with discordant molecular subtypes.

The incidence of synchronous bilateral breast cancer (SBBC) is very low, and SBBC with discordant molecular subtypes is even more uncommon. As such, little is known about the pathogenesis of SBBC with discordant molecular subtypes, and reports about this entity are scarce. In the present study, the case of a 72-year-old female patient who presented with SBBC with discordant molecular subtypes is reported, with a stage IA hormone receptor negative {human epidermal growth factor receptor-2 [HER2(+)]} tumor in the left breast and a stage IIIA hormone sensitive tumor [HER2(-)] in the right breast. Whole-exome sequencing was performed to identify the differential genetic variations in the BBC tissues. A total of 8 key mutated cancer susceptibility genes (ALK, BRCA1, FAT1, HNF1A, KDR, PTCH1, SDHA and SETBP1) were screened, and mutations were found in 10 vital cancer driver genes, including BRCA1, EBF1, MET, NF2, NUMA1 RALGAPA1, ROBO2, SMYD4, UBR5 and ZNF844. The high-frequency mutated genes mainly contained missense mutations, among which single nucleotide variants were the most common mutations, with C > T and C > A as the main forms. The pathways associated with the high frequency mutated genes were further elucidated by functional category and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses. Heterogeneity in the hormone receptor and HER2 status of SBBC poses unique therapeutic challenges. Future studies should aim to identify the optimal management strategy for this disease.

Identification and validation of an m7G-related lncRNAs signature for predicting prognosis, immune response and therapy landscapes in ovarian cancer.

Ovarian cancer is the most mortality malignancy in gynecology. N7-methylguanosine (m7G) is one of the most prevalent RNA modifications in the development and progression of cancer. The aim of this study is to investigate the effect of m7G-related lncRNA on ovarian cancer in terms of instruction prognosis and immunotherapy. After integrating and processing the RNA expression profiles with the clinical sample information in the TCGA database, we initially screened to the m7G-related lncRNAs by Spearman correlation analysis, and subsequently obtained a prognostic model constructed by five m7G-related lncRNAs with Univariate Cox analysis, LASSO regression analysis, and Multivariate Cox regression analysis, after which we further evaluated and validated the prognostic value of the model using Kaplan-Meier survival analysis, Principal component analysis, Nomogram, and ROC curve. In addition, based on this risk model, we explored the differentially enriched pathways and functions of the high and low risk groups, and characterized the immune cells, immune functions, gene mutations, and drug sensitivity between the two groups. After a series of rigorous filtering, we finally attained a prognostic risk model consisting of KRT7-AS, USP30-AS1, ZFHX4-AS1, ACAP2-IT1, and TWSG1-DT which is excellent in predicting the prognostic survival of ovarian cancer patients as well as existing as an independent prognostic factor. Moreover, the model has certain relevance in the immune cells and functions between high and low risk groups, and simultaneously, the signature has the role of guiding the option of immunotherapy and chemotherapeutic drugs. Altogether, our study established a tight connection between m7G-associated lncRNAs and ovarian cancer, with potential that the prognostic patterns contribute to steering the prognosis of ovarian cancer patients, measuring the efficacy of immunotherapeutic approaches, and detecting effective chemotherapeutic agents.

PyRforest: a comprehensive R package for genomic data analysis featuring scikit-learn Random Forests in R.

Random Forest models are widely used in genomic data analysis and can offer insights into complex biological mechanisms, particularly when features influence the target in interactive, nonlinear, or nonadditive ways. Currently, some of the most efficient Random Forest methods in terms of computational speed are implemented in Python. However, many biologists use R for genomic data analysis, as R offers a unified platform for performing additional statistical analysis and visualization. Here, we present an R package, pyRforest, which integrates Python scikit-learn "RandomForestClassifier" algorithms into the R environment. pyRforest inherits the efficient memory management and parallelization of Python, and is optimized for classification tasks on large genomic datasets, such as those from RNA-seq. pyRforest offers several additional capabilities, including a novel rank-based permutation method for biomarker identification. This method can be used to estimate and visualize P-values for individual features, allowing the researcher to identify a subset of features for which there is robust statistical evidence of an effect. In addition, pyRforest includes methods for the calculation and visualization of SHapley Additive exPlanations values. Finally, pyRforest includes support for comprehensive downstream analysis for gene ontology and pathway enrichment. pyRforest thus improves the implementation and interpretability of Random Forest models for genomic data analysis by merging the strengths of Python with R. pyRforest can be downloaded at: https://www.github.com/tkolisnik/pyRforest with an associated vignette at https://github.com/tkolisnik/pyRforest/blob/main/vignettes/pyRforest-vignette.pdf.

Exploring Synaptic Pathways in Traumatic Brain Injury: A Cross-Phenotype Genomics Approach.

Traumatic brain injury (TBI), a global leading cause of mortality and disability, lacks effective treatments to enhance recovery. Synaptic remodeling has been postulated as one mechanism that influences outcomes after TBI. We sought to investigate whether common mechanisms affecting synapse maintenance are shared between TBI and other neuropsychiatric conditions using pathway enrichment tools and genome-wide genotype data, with the goal of highlighting novel treatment targets. We leveraged an integrative approach, combining data from genome-wide association studies with pathway and gene-set enrichment analyses. Literature review-based and Reactome database-driven approaches were combined to identify synapse-related pathways of interest in TBI outcome and to assess for shared associations with conditions in which synapse-related pathobiological mechanisms have been implicated, including Alzheimer's disease, schizophrenia (SCZ), major depressive disorder, post-traumatic stress disorder, attention-deficit hyperactivity disorder, and autism spectrum disorder. Gene and pathway-level enrichment analyses were conducted using MAGMA and its extensions, e- and H-MAGMA, followed by Mendelian randomization to investigate potential causal associations. Of the 98 pathways tested, 32 were significantly enriched in the included conditions. In TBI outcome, we identified significant enrichment in five pathways: "Serotonin clearance from the synaptic cleft" (p = 0.0001), "Presynaptic nicotinic acetylcholine receptors" (p = 0.0003), "Postsynaptic nicotinic acetylcholine receptors" (p = 0.0003), "Highly sodium permeable postsynaptic acetylcholine nicotinic receptors" (p = 0.0001), and "Acetylcholine binding and downstream events" pathways (p = 0.0003). These associations highlight potential involvement of the cholinergic and serotonergic systems in post-TBI recovery. Three of those pathways were shared between TBI and SCZ, suggesting possible pathophysiologic commonalities. In this study, we utilize comparative and integrative genomic approaches across brain conditions that share synaptic mechanisms to explore the pathophysiology of TBI outcomes. Our results implicate associations between TBI outcome and synaptic pathways as well as pathobiological overlap with other neuropsychiatric diseases.

Toxic Metals Impact Gut Microbiota and Metabolic Risk in Five African-Origin Populations.

Exposure to toxic metals impacts obesity and type 2 diabetes (T2DM) risk. Yet, the underlying mechanisms remain largely unknown. Gut microbiota has been strongly associated with progression of cardiometabolic risk. To determine whether high metal exposures and gut dysbiosis interact to promote metabolic dysregulation and cardiometabolic risk, we assessed relationships between these factors. We analyzed cross-sectional associations between arsenic, lead, mercury, cadmium, and cardiometabolic health markers in 178 randomly selected African-origin adults (52% female, 51% obese, mean age=43.0±6.4 years) from Ghana, South Africa, Seychelles, Jamaica, and USA. Metal levels were dichotomized to high or low at the median level of each metal. We analyzed associations between gut microbiome taxa, metal levels, clinical measures (BMI, fasting blood glucose, and blood pressure) and diagnoses (hypertension, obesity, and diabetes status). High vs. low lead and arsenic exposures had a significant effect on beta diversity (p <0.05). 71 taxa were associated with high lead levels: 30 with elevated BMI, 22 with T2DM, and 23 with elevated fasting blood glucose (p<0.05). 115 taxa were associated with high arsenic levels: 32 with elevated BMI, 33 with T2DM, and 26 with elevated blood glucose (p<0.05). Of the taxa associated with high lead and arsenic exposure and either elevated BMI or fasting blood glucose, porphyrin metabolism was the most enriched metabolic pathway. These data collectively provide the first findings in a human study that the gut microbiome may drive the association between lead and arsenic exposure and obesity and T2DM risk.

Causal relationship between beta-2 microglobulin and B-cell malignancies: genome-wide meta-analysis and a bidirectional two-sample Mendelian randomization study.

Beta-2 microglobulin (β2M) is acknowledged as a prognostic biomarker for B-cell malignancies. However, insights into the impact of β2M on B-cell malignancy risk, and vice versa, are limited. We conducted a genome-wide meta-analysis (GWMA), bidirectional two-sample Mendelian randomization (TSMR) analysis, and pathway enrichment analysis to explore the causal relationship between β2M and B-cell malignancies and the underlying biological processes. The GWMA identified 55 lead SNPs across five genomic regions (three novel: WDR72, UMOD, and NLRC5) associated with β2M. In the UKB, genetically predicted β2M showed a positive association with diffuse large B-cell lymphoma (DLBCL; odds ratio [OR]: 1.742 per standard deviation increase in β2M; 95% confidence interval [CI]: 1.215-2.498; P = 3.00 × 10-3; FDR = 7.50× 10-3) and Hodgkin lymphoma (HL; OR: 2.270; 95% CI: 1.525-3.380; P = 5.15 × 10-5; FDR =2.58 × 10-4). However, no associations were found with follicular lymphoma (FL), chronic lymphoid leukemia (CLL), or multiple myeloma (MM). Reverse TSMR analysis revealed no association between genetically predicted B-cell malignancies and β2M. In FinnGen, β2M was found to be associated with an increased risk of DLBCL (OR: 2.098; 95% CI: 1.358-3.242; P = 8.28 × 10-4; FDR = 4.14 × 10-3), HL (OR: 1.581; 95% CI: 1.167-2.142; P = 3.13 × 10-3; FDR = 5.22 × 10-3), and FL (OR: 2.113; 95% CI: 1.292-3.455; P = 2.90 × 10-3; FDR = 5.22 × 10-3). However, no association was found with CLL or MM. Reverse TSMR analysis indicated that genetically predicted DLBCL, FL, and MM may perturb β2M levels. Pathway enrichment analysis suggested that the innate immune system represents a convergent biological process underlying β2M, DLBCL, and HL. Our findings suggested that elevated levels of β2M were associated with an increased risk of DLBCL and HL, which is potentially linked to dysfunction of the innate immune system.

Effect of Moniezia Benedeni infection on ileal transcriptome profile characteristics of sheep

BackgroundThe intestinal mucosal immune system, renowned for its precise and sensitive regulation, can provide comprehensive and effective protection for the body, among which the ileum is a critical induction site for regulating mucosal immune homeostasis. Moniezia benedeni parasitizes the small intestine of sheep and can cause serious pathological damage or even death to the host when the infection is severe. In this study, 5 sheep infected with Moniezia benedeni were selected as the infected group, and 5 uninfected sheep were selected as the control group. The ileal transcriptome profile characteristics of Moniezia benedeni infection were analyzed based on RNA-seq sequencing technology, aiming to lay a foundation for further exploring the perception mechanism of sheep intestines to Moniezia benedeni infection and formulating effective prevention and control strategies.ResultsThe results showed that a total of 3,891 differentially expressed genes (DEGs) were detected in the ileum tissues of sheep between the infected and control groups with 2,429 up-regulated genes and 1,462 down-regulated genes. GO and KEGG pathway enrichment analysis of differential genes, as well as Clue GO analysis showed that differential genes were significantly enriched in immune and metabolic-related biological processes and signaling pathways. Particularly, in immune-related signaling pathways, the B cell receptor signaling pathway was significantly down-regulated, while in metabolic regulation related signaling pathways, Bile secretion, Fat digestion and absorption and Vitamin digestion and absorption were notably up-regulated. On this basis, the differential core genes related to immune metabolism were verified by qRT-PCR method. The results showed that OVAR, CD3E, CD8A, CD4 and CD28 were significantly up-regulated (P < 0.05), while CIITA, BLNK, BCL6 and CD79A were significantly down-regulated (P < 0.05), which were consistent with transcriptome sequencing data.ConclusionsThe results demonstrated that Moniezia benedeni infection significantly affected the immune and metabolic processes in sheep ileum, particularly, it significantly inhibited the activation process of host B cells, and also led to an overactive function of bile acid metabolism. This finding provides a solid foundation for further elucidating the response mechanism of Peyer's patches in sheep ileum to Moniezia tapeworm infection.

Identification and validation of diagnostic markers related to immunogenic cell death and infiltration of immune cells in diabetic nephropathy

IntroductionImmunogenic cell death (ICD) is a unique cell death triggered by chemotherapy. However, studies elucidating the potential therapeutic role of ICD and the underlying mechanism in diabetic nephropathy (DN) are limited. MethodsWGCNA was conducted on the human kidney biopsy data linked to DN, analyzing gene sets associated with ICD. Gene Set Enrichment Analysis and Gene Set Variation Analysis were utilized to examine the discrepancy in biological function. We used Gene Ontology, the Kyoto Encyclopedia of Genes and Genomes, and the GeneMANIA database to investigate the function of the signature genes. An analysis using the receiver operating characteristic (ROC) was conducted to validate the diagnostic value of hub genes. Additionally, immune infiltration-related analyses were also performed. In conclusion, we examined the association between the glomerular filtration rate, serum creatinine, and hub genes. Hub genes were validated by immunohistochemistry using db/db mice kidneys. ResultsWGCNA revealed that the targets in the turquoise unit (1674 genes) exhibited the highest positive correlation with ICD. Furthermore, 4222 statistically significant DEGs were identified when comparing the DN and healthy control groups. Significantly, the KEGG pathway enrichment analysis indicated a connection between ICD and the nuclear factor-kappa B signaling pathway and the synthesis of cytokines (tumor necrosis factor superfamily). ROC analysis revealed that 16 hub genes exhibited strong discriminatory potential as biomarkers for DN. Therefore, immunohistochemical validation, with the potential involvement of chemokines (CCL11, CCR2, CCR7, CX3CR1, CXCL10, CXCL12, and CXCR5) and immune cells (CD3G, CD5, and CD247) may be crucial for the diagnosis and therapy of DN. ConclusionsDKK3, NR4A1, NR4A2, VEGFA, and DUSP1 may be associated with the development of DN. The pathogenesis of DN may specifically involve chemokines (CCL11, CCR2, CCR7, CX3CR1, CXCL10, CXCL12, and CXCR5) and immune cells (CD3G, CD5, and CD247), with LCP2 playing a significant role.

Identifying prothrombin and bone sialoprotein as potential drug targets for idiopathic pulmonary fibrosis

BackgroundIdiopathic Pulmonary Fibrosis (IPF) is a fatal disease with scarce therapeutic alternatives, which imposes a significant economic burden on society. The identification of novel drug targets is thus critically essential. Plasma proteins with discernible causal evidence hold promise as viable drug targets for this condition.MethodsWe performed a proteome-wide Mendelian randomization (MR) analysis to assess the causal effects of 4,907 circulating proteins from the deCODE study on the risk of IPF from the Finngen Database (2,018 cases vs. 373,064 controls). We further replicated the MR analysis in 1426 proteins from the ARIC study and IPF from the UK Biobank (1,369 cases vs. 435,866 controls). Then a series of analyses including Bayesian colocalization, Steiger filtering, and phenotype scanning were conducted to validate the credibility of the MR results. Subsequently, protein-protein interaction (PPI) analysis, pathway enrichment analysis, and druggability assessment were executed to elucidate the underlying mechanisms. Finally, the findings were corroborated using a bleomycin-induced pulmonary fibrosis mouse model.ResultsThe MR analysis bolstered by robust evidence of colocalization, indicated a significant positive association between Prothrombin and increased IPF risk (OR = 3.26,95%CI 1.75–6.07). Conversely, Bone Sialoprotein (IBSP) demonstrated an inverse association with IPF susceptibility (OR = 0.27,95%CI 0.14–0.55).ConclusionsThe integrative analysis suggests that Prothrombin and IBSP are promising candidates as potential drug targets for IPF. Additional clinical investigations are warranted to substantiate these findings.

Genomic and transcriptomic profiling of pre- and postneoadjuvant chemotherapy triple negative breast cancer tumors.

Our understanding of neoadjuvant treatment with microtubule inhibitors (MTIs) for triple negative breast cancer (TNBC) remains limited. To advance our understanding of the role of breast cancer driver genes' mutational status with pathological complete response (pCR; ypT0/isypN0) prediction and to identify distinct gene sets for MTIs like eribulin and paclitaxel, we carried out targeted genomic (n = 50) and whole transcriptomic profiling (n = 64) of TNBC tumor samples from the Japan Breast Cancer Research Group 22 (JBCRG-22) clinical trial. Lower PIK3CA, PTEN, and HRAS mutations were found in homologous recombination deficiency (HRD)-high (HRD score ≥ 42) tumors with higher pCR rates. When HRD-high tumors were stratified by tumor BRCA mutation status, the pCR rates in BRCA2-mutated tumors were higher (83% vs. 36%). Transcriptomic profiling of TP53-positive tumors identified downregulation of FGFR2 (false discovery rate p value = 2.07e-7), which was also the only common gene between HRD-high and -low tumors with pCR/quasi-pCR treated with paclitaxel and eribulin combined with carboplatin, respectively. Differential enrichment analysis of the HRD-high group posttreatment tumors revealed significant correlation (p = 0.006) of the glycan degradation pathway. FGFR2 expression and the differentially enriched pathways play a role in the response and resistance to MTIs containing carboplatin treatment in TNBC patients.

Exploring the hub Genes and Potential Mechanisms of Complement system-related Genes in Parkinson Disease: Based on Transcriptome Sequencing and Mendelian Randomization.

An accurate diagnosis of Parkinson's disease (PD) remains challenging and the exact cause of the disease is unclean. The aims are to identify hub genes associated with the complement system in PD and to explore their underlying molecular mechanisms. Initially, differentially expressed genes (DEGs) and key module genes related to PD were mined through differential expression analysis and WGCNA. Then, differentially expressed CSRGs (DE-CSRGs) were obtained by intersecting the DEGs, key module genes and CSRGs. Subsequently, MR analysis was executed to identify genes causally associated with PD. Based on genes with significant MR results, the expression level and diagnostic performance verification were achieved to yield hub genes. Functional enrichment and immune infiltration analyses were accomplished to insight into the pathogenesis of PD. qRT-PCR was employed to evaluate the expression levels of hub genes. After MR analysis and related verification, CD93, CTSS, PRKCD and TLR2 were finally identified as hub genes. Enrichment analysis indicated that the main enriched pathways for hub genes. Immune infiltration analysis found that the hub genes showed significant correlation with a variety of immune cells (such as myeloid-derived suppressor cell and macrophage). In the qRT-PCR results, the expression levels of CTSS, PRKCD and TLR2 were consistent with those we obtained from public databases. Hence, we mined four hub genes associated with complement system in PD which provided novel perspectives for the diagnosis and treatment of PD.

Mapping the proteomic landscape and anti-inflammatory role of Streptococcus parauberis extracellular vesicles

Bacterial extracellular vesicles (BEVs) are nanoscale membrane-bound structures involved in intercellular communication and transport of bioactive molecules. In this study, we described the proteomic insight and anti-inflammatory activity of Streptococcus parauberis BEVs (SpEVs). Proteomics analysis of SpEVs identified 6209 distinct peptides and 1039 proteins. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis demonstrated enrichment in pathways related to the biosynthesis of aminoacyl tRNA, amino acids, and secondary metabolites. Based on the predicted protein-protein interactions, we discovered key immunological proteins such as IL12A, IL12B, IL8, CD28, and NF-κB between SpEVs and human proteins. Functionally, SpEVs exhibit strong anti-inflammatory activity in LPS-stimulated Raw 264.7 cells by reducing the production of key inflammatory mediators. These include nitric oxide (NO), reactive oxygen species (ROS), inflammatory cytokines such as TNFα and IL6, as well as inflammation-related proteins like inducible nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2). qRT-PCR and immunoblotting results clearly indicate that SpEVs modulate the NF-κB and MAPK pathways to induce anti-inflammatory activity. Furthermore, in vivo experiments with zebrafish larvae demonstrated that SpEVs treatment reduced the NO and ROS production with minimal cell mortality. Finally, we validated the anti-inflammatory activity of SpEVs in vivo by systematically assessing the inhibition of NO production, reduction in ROS generation, prevention of cell death, and modulation of NF-κB and MAPK signaling pathways. In conclusion, SpEVs contain rich in unique proteins that play crucial roles in mediating anti-inflammatory effects.