Cytoscape: a software environment for integrated models of biomolecular interaction networks

Pro-resolving lipid mediator reduces amyloid-β42-induced gene expression in human monocyte-derived microglia

JOURNAL/nrgr/04.03/01300535-202503000-00031/figure1/v/2024-06-17T092413Z/r/image-tiff Specialized pro-resolving lipid mediators including maresin 1 mediate resolution but the levels of these are reduced in Alzheimer's disease brain, suggesting that they constitute a novel target for the treatment of Alzheimer's disease to prevent/stop inflammation and combat disease pathology. Therefore, it is important to clarify whether they counteract the expression of genes and proteins induced by amyloid-β. With this objective, we analyzed the relevance of human monocyte-derived microglia for in vitro modeling of neuroinflammation and its resolution in the context of Alzheimer's disease and investigated the pro-resolving bioactivity of maresin 1 on amyloid-β42-induced Alzheimer's disease-like inflammation. Analysis of RNA-sequencing data and secreted proteins in supernatants from the monocyte-derived microglia showed that the monocyte-derived microglia resembled Alzheimer's disease-like neuroinflammation in human brain microglia after incubation with amyloid-β42. Maresin 1 restored homeostasis by down-regulating inflammatory pathway related gene expression induced by amyloid-β42 in monocyte-derived microglia, protection of maresin 1 against the effects of amyloid-β42 is mediated by a re-balancing of inflammatory transcriptional networks in which modulation of gene transcription in the nuclear factor-kappa B pathway plays a major part. We pinpointed molecular targets that are associated with both neuroinflammation in Alzheimer's disease and therapeutic targets by maresin 1. In conclusion, monocyte-derived microglia represent a relevant in vitro microglial model for studies on Alzheimer's disease-like inflammation and drug response for individual patients. Maresin 1 ameliorates amyloid-β42-induced changes in several genes of importance in Alzheimer's disease, highlighting its potential as a therapeutic target for Alzheimer's disease.

Impact of residual antibiotics on microbial decomposition of livestock manures in Eutric Regosol: Implications for sustainable nutrient recycling and soil carbon sequestration

The land application of livestock manure has been widely acknowledged as a beneficial approach for nutrient recycling and environmental protection. However, the impact of residual antibiotics, a common contaminant of manure, on the degradation of organic compounds and nutrient release in Eutric Regosol is not well understood. Here, we studied, how oxytetracycline (OTC) and ciprofloxacin (CIP) affect the decomposition, microbial community structure, extracellular enzyme activities and nutrient release from cattle and pig manure using litterbag incubation experiments. Results showed that OTC and CIP greatly inhibited livestock manure decomposition, causing a decreased rate of carbon (28%-87%), nitrogen (15%-44%) and phosphorus (26%-43%) release. The relative abundance of gram-negative (G-) bacteria was reduced by 4.0%-13% while fungi increased by 7.0%-71% during a 28-day incubation period. Co-occurrence network analysis showed that antibiotic exposure disrupted microbial interactions, particularly among G- bacteria, G+ bacteria, and actinomycetes. These changes in microbial community structure and function resulted in decreased activity of urease, β-1,4-N-acetyl-glucosaminidase, alkaline protease, chitinase, and catalase, causing reduced decomposition and nutrient release in cattle and pig manures. These findings advance our understanding of decomposition and nutrient recycling from manure-contaminated antibiotics, which will help facilitate sustainable agricultural production and soil carbon sequestration.

Stiff extracellular matrix drives the differentiation of mesenchymal stem cells toward osteogenesis by the multiscale 3D genome reorganization

Extracellular matrix (ECM) stiffness is a major driver of stem cell fate. However, the involvement of the three-dimensional (3D) genomic reorganization in response to ECM stiffness remains unclear. Here, we generated comprehensive 3D chromatin landscapes of mesenchymal stem cells (MSCs) exposed to various ECM stiffness. We found that there were more long-range chromatin interactions, but less compartment A in MSCs cultured on stiff ECM than those cultured on soft ECM. However, the switch from compartment B in MSCs cultured on soft ECM to compartment A in MSCs cultured on stiff ECM included genes encoding proteins primarily enriched in cytoskeleton organization. At the topologically associating domains (TADs) level, stiff ECM tends to have merged TADs on soft ECM. These merged TADs on stiff ECM include upregulated genes encoding proteins enriched in osteogenesis, such as SP1, ETS1, and DCHS1, which were validated by quantitative real-time polymerase chain reaction and found to be consistent with the increase of alkaline phosphatase staining. Knockdown of SP1 or ETS1 led to the downregulation of osteogenic marker genes, including COL1A1, RUNX2, ALP, and OCN in MSCs cultured on stiff ECM. Our study provides an important insight into the stiff ECM-mediated promotion of MSC differentiation towards osteogenesis, emphasizing the influence of mechanical cues on the reorganization of 3D genome architecture and stem cell fate.

Identification of key mitochondria-related genes and their potential crosstalk role with immune pattern in Idiopathic pulmonary fibrosis

BACKGROUND

Idiopathic pulmonary fibrosis (IPF) stands out as a life-threatening and one of the most severe interstitial lung diseases. The pathogenesis of IPF is not fully understood, while recent studies have highlighted the association of mitochondrial dysfunction with IPF. This study is dedicated to pinpointing crucial genes related to mitochondria that potentially impact the advancement of IPF, thereby offering new perspectives on the pathogenesis of this condition.

METHODS

The Gene Expression Omnibus (GEO) database was utilized to download three datasets (GSE32537, GSE92592, and GSE150910), following which a comprehensive analysis was conducted to identify differentially expressed mitochondria-related genes (DEMTRGs) in the IPF lung tissues. Subsequently, GO and KEGG enrichment analysis of the DEMTRGs was performed. Next, external datasets and in vivo experiments were performed to validate their expression. Additionally, a Logistic regression model based on key DEMTRGs was constructed, and the model's ability to distinguish between IPF and controls was evaluated using the area under the receiver operating characteristic (ROC) curve (AUC). Finally, gene set enrichment analysis (GSEA) and CIBERSORT algorithm were conducted.

RESULTS

We identified five key DEMTRGs (ALDH18A1, ALDH1B1, MCCC1, ACAT1, and PDHA1), ALDH18A1 and ALDH1B1 exhibited upregulated expression levels, whereas MCCC1, ACAT1, and PDHA1 showed downregulation in the lung tissue of individuals with IPF. The expression levels of these key DEMTRGs were validated by an independent external dataset (GSE53845) and the bleomycin-induced pulmonary fibrosis mice. In addition, the ROCs indicated that the diagnostic model constructed based on key DEMTRGs could effectively distinguish between IPF and controls (AUC>0.8). GSEA analysis and immune-related analysis shed light on the potential mechanisms through which these key DEMTRGs influence IPF.

CONCLUSION

Our research has pinpointed key genes associated with mitochondria that may ultimately contribute to the progression of IPF by exerting regulatory effects on mitochondrial function, thereby influencing multiple cellular processes.

Molecular insights into epoxyazadiradione induced death in triple-negative breast cancer cells: A system biology approach

Epoxyazadiradione is an important limonoid with immense pharmacological potential. We have reported previously that epoxyazadiradione (EAD) induces apoptosis in triple negative breast cancer cells (MDA-MB 231) by modulating diverse cellular targets. Here, we identify the key genes/pathways responsible for this effect through next-generation sequencing of the transcriptome from EAD treated cells and integrated molecular data analysis using bioinformatics. In silico analysis indicated that EAD displayed favourable drug-like properties and could target multiple macromolecules relevant to TNBC. RNA sequencing revealed that EAD treatment results in the differential expression of 1838 genes in MDA-MB 231 cells, with 752 downregulated and 1086 upregulated. Gene set enrichment analysis of these genes suggested that EAD disrupts protein folding in the endoplasmic reticulum, triggering the unfolded protein response (UPR) and potentially leading to cell death. EAD also induced oxidative stress and DNA damage, downregulated pathways linked to metabolism, cell cycle progression, pro-survival signalling, cell adhesion, motility and inflammatory response. The identification of protein cluster and hub genes were also done. The validation of the identified hub genes gave an inverse correlation between their expression in EAD treated cells and TNBC patient samples. Thus, the identified hub genes could be explored as therapeutic or diagnostic markers for TNBC. Hence, EAD appears to be a promising therapeutic candidate for TNBC by targeting various hallmarks of cancer, including cell death resistance, uncontrolled proliferation and metastasis. To conclude, the identified pathways and validated targets for EAD will provide a roadmap for further in vivo studies and preclinical/clinical validation required for potential drug development.

Differential gene expression analysis pipelines and bioinformatic tools for the identification of specific biomarkers: A review

In recent years, the role of bioinformatics and computational biology together with omics techniques and transcriptomics has gained tremendous importance in biomedicine and healthcare, particularly for the identification of biomarkers for precision medicine and drug discovery. Differential gene expression (DGE) analysis is one of the most used techniques for RNA-sequencing (RNA-seq) data analysis. This tool, which is typically used in various RNA-seq data processing applications, allows the identification of differentially expressed genes across two or more sample sets. Functional enrichment analyses can then be performed to annotate and contextualize the resulting gene lists. These studies provide valuable information about disease-causing biological processes and can help in identifying molecular targets for novel therapies. This review focuses on differential gene expression (DGE) analysis pipelines and bioinformatic techniques commonly used to identify specific biomarkers and discuss the advantages and disadvantages of these techniques.

Testacosides A-D, glycoglycerolipids produced by Microbacterium testaceum isolated from Tedania brasiliensis

Marine bacteria living in association with marine sponges have proven to be a reliable source of biologically active secondary metabolites. However, no studies have yet reported natural products from Microbacterium testaceum spp. We herein report the isolation of a M. testaceum strain from the sponge Tedania brasiliensis. Molecular networking analysis of bioactive pre-fractionated extracts from culture media of M. testaceum enabled the discovery of testacosides A-D. Analysis of spectroscopic data and chemical derivatizations allowed the identification of testacosides A-D as glycoglycerolipids bearing a 1-[α-glucopyranosyl-(1 → 3)-(α-mannopyranosyl)]-glycerol moiety connected to 12-methyltetradecanoic acid for testacoside A (1), 14-methylpentadecanoic acid for testacoside B (2), and 14-methylhexadecanoic acid for testacosides C (3) and D (4). The absolute configuration of the monosaccharide residues was determined by 1H-NMR analysis of the respective diastereomeric thiazolidine derivatives. This is the first report of natural products isolated from cultures of M. testaceum. KEY POINTS: • The first report of metabolites produced by Microbacterium testaceum. • 1-[α-Glucopyranosyl-(1 → 3)-(α-mannopyranosyl)]-glycerol lipids isolated and identified. • Microbacterium testaceum strain isolated from the sponge Tedania brasiliensis.

Identification of HIST1H2BH as the hub gene associated with multiple myeloma using integrated bioinformatics analysis

OBJECTIVES

Identifying the specific biomarkers and molecular signatures of MM might provide novel evidence for MM prognosis and targeted therapy.

METHODS

Bioinformatic analyses were performed through GEO and TCGA datasets. The differential expression of HIST1H2BH in MM sample was validated by the qRT-PCR. And the CCK-8 assay was performed to detect the proliferation activity of HIST1H2BH on MM cell lines.

RESULTS

A total of 793 DEGs were identified between bone marrow plasma cells from newly diagnosed myeloma and normal donors in GSE6477. Among them, four vital genes (HIST1H2AC, HIST1H2BH, CCND1 and TCF7L2) modeling were constructed. The increased HIST1H2BH expression was correlated with worse survival of MM based on TCGA datasets. The transcriptional expression of HIST1H2BH was significantly up-regulated in primary MM patients. And knockdown HIST1H2BH decreased the proliferation of MM cell lines.

CONCLUSIONS

We have identified up-regulated HIST1H2BH in MM patients associated with poor prognosis using integrated bioinformatical methods.

HiOmics: A cloud-based one-stop platform for the comprehensive analysis of large-scale omics data

Analyzing the vast amount of omics data generated comprehensively by high-throughput sequencing technology is of utmost importance for scientists. In this context, we propose HiOmics, a cloud-based platform equipped with nearly 300 plugins designed for the comprehensive analysis and visualization of omics data. HiOmics utilizes the Element Plus framework to craft a user-friendly interface and harnesses Docker container technology to ensure the reliability and reproducibility of data analysis results. Furthermore, HiOmics employs the Workflow Description Language and Cromwell engine to construct workflows, ensuring the portability of data analysis and simplifying the examination of intricate data. Additionally, HiOmics has developed DataCheck, a tool based on Golang, which verifies and converts data formats. Finally, by leveraging the object storage technology and batch computing capabilities of public cloud platforms, HiOmics enables the storage and processing of large-scale data while maintaining resource independence among users.

Screening biomarkers for spinal cord injury using weighted gene co-expression network analysis and machine learning

JOURNAL/nrgr/04.03/01300535-202412000-00028/figure1/v/2024-04-08T165401Z/r/image-tiff Immune changes and inflammatory responses have been identified as central events in the pathological process of spinal cord injury. They can greatly affect nerve regeneration and functional recovery. However, there is still limited understanding of the peripheral immune inflammatory response in spinal cord injury. In this study, we obtained microRNA expression profiles from the peripheral blood of patients with spinal cord injury using high-throughput sequencing. We also obtained the mRNA expression profile of spinal cord injury patients from the Gene Expression Omnibus (GEO) database (GSE151371). We identified 54 differentially expressed microRNAs and 1656 differentially expressed genes using bioinformatics approaches. Functional enrichment analysis revealed that various common immune and inflammation-related signaling pathways, such as neutrophil extracellular trap formation pathway, T cell receptor signaling pathway, and nuclear factor-κB signal pathway, were abnormally activated or inhibited in spinal cord injury patient samples. We applied an integrated strategy that combines weighted gene co-expression network analysis, LASSO logistic regression, and SVM-RFE algorithm and identified three biomarkers associated with spinal cord injury: ANO10, BST1, and ZFP36L2. We verified the expression levels and diagnostic performance of these three genes in the original training dataset and clinical samples through the receiver operating characteristic curve. Quantitative polymerase chain reaction results showed that ANO10 and BST1 mRNA levels were increased and ZFP36L2 mRNA was decreased in the peripheral blood of spinal cord injury patients. We also constructed a small RNA-mRNA interaction network using Cytoscape. Additionally, we evaluated the proportion of 22 types of immune cells in the peripheral blood of spinal cord injury patients using the CIBERSORT tool. The proportions of naïve B cells, plasma cells, monocytes, and neutrophils were increased while the proportions of memory B cells, CD8+ T cells, resting natural killer cells, resting dendritic cells, and eosinophils were markedly decreased in spinal cord injury patients increased compared with healthy subjects, and ANO10, BST1 and ZFP26L2 were closely related to the proportion of certain immune cell types. The findings from this study provide new directions for the development of treatment strategies related to immune inflammation in spinal cord injury and suggest that ANO10, BST1, and ZFP36L2 are potential biomarkers for spinal cord injury. The study was registered in the Chinese Clinical Trial Registry (registration No. ChiCTR2200066985, December 12, 2022).

Changes of composition and antibiotic resistance of fecal coliform bacteria in municipal wastewater treatment plant

The dynamics of the composition and antibiotic resistance of the fecal coliform bacteria (FCB) in a typical wastewater treatment plant (WWTP) were investigated concerning the seasonal changes. Results showed that WWTP could remove the FCB concentration by 3∼5 logs within the effluent of 104∼105 CFU/L, but the antibiotic resistant rate of FCB species increased significantly after WWTP. The dominant FCB changed from Escherichia coli in the influent (∼73.0%) to Klebsiella pneumoniae in the effluent (∼53.3%) after WWTP, where the Escherichia coli was removed the most, while Klebsiella pneumoniae was the most persistent. The secondary tank removed the most of FCB (by 3∼4 logs) compared to other processes, but increased all the concerned antibiotic resistant rate. The potential super bugs of FCB community showing resistance to all the target antibiotics were selected in the biological treatment unit of WWTP. The FCB showed the highest multiple antibiotic resistance (92.9%) in total which even increased to 100% in the effluent. Klebsiella has the highest antibiotic resistant rate in FCB, with a multiple antibiotic resistance rate of 98.4%. These indicated that the Klebsiella pneumoniae not just Escherichia coli should be specially emphasized after WWTP concerning the health risk associated with FCB community.

Visualizing metagenomic and metatranscriptomic data: A comprehensive review

The fields of Metagenomics and Metatranscriptomics involve the examination of complete nucleotide sequences, gene identification, and analysis of potential biological functions within diverse organisms or environmental samples. Despite the vast opportunities for discovery in metagenomics, the sheer volume and complexity of sequence data often present challenges in processing analysis and visualization. This article highlights the critical role of advanced visualization tools in enabling effective exploration, querying, and analysis of these complex datasets. Emphasizing the importance of accessibility, the article categorizes various visualizers based on their intended applications and highlights their utility in empowering bioinformaticians and non-bioinformaticians to interpret and derive insights from meta-omics data effectively.

Elucidating the role of Rhodiola rosea L. in sepsis-induced acute lung injury via network pharmacology: emphasis on inflammatory response, oxidative stress, and the PI3K-AKT pathway

CONTEXT

Sepsis-induced acute lung injury (ALI) is associated with high morbidity and mortality. Rhodiola rosea L. (Crassulaceae) (RR) and its extracts have shown anti-inflammatory, antioxidant, immunomodulatory, and lung-protective effects.

OBJECTIVE

This study elucidates the molecular mechanisms of RR against sepsis-induced ALI.

MATERIALS AND METHODS

The pivotal targets of RR against sepsis-induced ALI and underlying mechanisms were revealed by network pharmacology and molecular docking. Human umbilical vein endothelial cells (HUVECs) were stimulated by 1 μg/mL lipopolysaccharide for 0.5 h and treated with 6.3, 12.5, 25, 50, 100, and 200 μg/mL RR for 24 h. Then, the lipopolysaccharide-stimulated HUVECs were subjected to cell counting kit-8 (CCK-8), enzyme-linked immunosorbent, apoptosis, and Western blot analyses. C57BL/6 mice were divided into sham, model, low-dose (40 mg/kg), mid-dose (80 mg/kg), and high-dose (160 mg/kg) RR groups. The mouse model was constructed through caecal ligation and puncture, and histological, apoptosis, and Western blot analyses were performed for further validation.

RESULTS

We identified six hub targets (MPO, HRAS, PPARG, FGF2, JUN, and IL6), and the PI3K-AKT pathway was the core pathway. CCK-8 assays showed that RR promoted the viability of the lipopolysaccharide-stimulated HUVECs [median effective dose (ED50) = 18.98 μg/mL]. Furthermore, RR inhibited inflammation, oxidative stress, cell apoptosis, and PI3K-AKT activation in lipopolysaccharide-stimulated HUVECs and ALI mice, which was consistent with the network pharmacology results.

DISCUSSION AND CONCLUSION

This study provides foundational knowledge of the effective components, potential targets, and molecular mechanisms of RR against ALI, which could be critical for developing targeted therapeutic strategies for sepsis-induced ALI.

Elucidating molecular mechanism and chemical space of chalcones through biological networks and machine learning approaches

We developed a bio-cheminformatics method, exploring disease inhibition mechanisms using machine learning-enhanced quantitative structure-activity relationship (ML-QSAR) models and knowledge-driven neural networks. ML-QSAR models were developed using molecular fingerprint descriptors and the Random Forest algorithm to explore the chemical spaces of Chalcones inhibitors against diverse disease properties, including antifungal, anti-inflammatory, anticancer, antimicrobial, and antiviral effects. We generated and validated robust machine learning-based bioactivity prediction models (https://github.com/RatulChemoinformatics/QSAR) for the top genes. These models underwent ROC and applicability domain analysis, followed by molecular docking studies to elucidate the molecular mechanisms of the molecules. Through comprehensive neural network analysis, crucial genes such as AKT1, HSP90AA1, SRC, and STAT3 were identified. The PubChem fingerprint-based model revealed key descriptors: PubchemFP521 for AKT1, PubchemFP180 for SRC, PubchemFP633 for HSP90AA1, and PubchemFP145 and PubchemFP338 for STAT3, consistently contributing to bioactivity across targets. Notably, chalcone derivatives demonstrated significant bioactivity against target genes, with compound RA1 displaying a predictive pIC50 value of 5.76 against HSP90AA1 and strong binding affinities across other targets. Compounds RA5 to RA7 also exhibited high binding affinity scores comparable to or exceeding existing drugs. These findings emphasize the importance of knowledge-based neural network-based research for developing effective drugs against diverse disease properties. These interactions warrant further in vitro and in vivo investigations to elucidate their potential in rational drug design. The presented models provide valuable insights for inhibitor design and hold promise for drug development. Future research will prioritize investigating these molecules for mycobacterium tuberculosis, enhancing the comprehension of effectiveness in addressing infectious diseases.

Stress-induced epigenetic effects driven by maternal lactation in dairy cattle: a comethylation network approach

Epigenetic marks do not follow the Mendelian laws of inheritance. The environment can alter the epigenotype of an individual when exposed to different external stressors. In lactating cows, the first stages of gestation overlap with the lactation peak, creating a negative energy balance that is difficult to overcome with diet. This negative energy balance could affect early embryo development that must compete with the mammary tissue for nutrients. We hypothesize that the methylation profiles of calves born to nonlactating heifers are different from those of calves born to lactating cows. We found 50,277 differentially methylated cytosines and 2,281 differentially methylated regions between these two groups of animals. A comethylation network was constructed to study the correlation between the phenotypes of the mothers and the epigenome of the calves, revealing 265 regions associated with the phenotypes. Our study revealed the presence of DMCs and DMRs in calves gestated by heifers and lactating cows, which were linked to the dam's lactation and the calves' ICAP and milk EBV. Gene-specific analysis highlighted associations with vasculature and organ morphogenesis and cell communication and signalling. These finding support the hypothesis that calves gestated by nonlactating mothers have a different methylation profile than those gestated by lactating cows.

Identification the role of necroptosis in rheumatoid arthritis by WGCNA network

Rheumatoid arthritis (RA) is the predominant manifestation of inflammatory arthritis, distinguished by an increasing burden of morbidity and mortality. The intricate interplay of genes and signalling pathways involved in synovial inflammation in patients with RA remains inadequately comprehended. This study aimed to ascertain the role of necroptosis in RA, as along with their associations with immune cell infiltration. Differential expression analysis and weighted gene co-expression network analysis (WGCNA) were employed to identify central genes for RA. In this study, identified total of 28 differentially expressed genes (DEGs) were identified in RA. Utilising WGCNA, two co-expression modules were generated, with one module demonstrating the strongest correlation with RA. Through the integration of differential gene expression analysis, a total of 5 intersecting genes were discovered. These 5 hub genes, namely fused in sarcoma (FUS), transformer 2 beta homolog (TRA2B), eukaryotic translation elongation factor 2 (EEF2), cleavage and polyadenylation specific factor 6 (CPSF6) and signal transducer and activator of transcription 3 (STAT3) were found to possess significant diagnostic value as determined by receiver operating characteristic (ROC) curve analysis. The close association between the concentrations of various immune cells is anticipated to contribute to the diagnosis and treatment of RA. Furthermore, the infiltration of immune cells mentioned earlier is likely to exert a substantial influence on the initiation of this disease.

Databases of ligand-binding pockets and protein-ligand interactions

Many research groups and institutions have created a variety of databases curating experimental and predicted data related to protein-ligand binding. The landscape of available databases is dynamic, with new databases emerging and established databases becoming defunct. Here, we review the current state of databases that contain binding pockets and protein-ligand binding interactions. We have compiled a list of such databases, fifty-three of which are currently available for use. We discuss variation in how binding pockets are defined and summarize pocket-finding methods. We organize the fifty-three databases into subgroups based on goals and contents, and describe standard use cases. We also illustrate that pockets within the same protein are characterized differently across different databases. Finally, we assess critical issues of sustainability, accessibility and redundancy.

Identification and prognostic analysis of metabolic genes associated with TP53 mutation in multiple myeloma

BACKGROUND

TP53 gene mutation is crucial in determining the prognosis of Multiple Myeloma (MM) patients. Understanding metabolic genes linked to TP53 mutation is vital for developing targeted therapies for these patients.

METHOD

We analyzed The Cancer Genome Atlas (TCGA) dataset to identify genes related to TP53 mutation and metabolism. Using univariate Cox regression and protein-protein interaction (PPI) analysis, we identified key genes. We categorized patients into high and low metabolism groups via non-negative matrix factorization (NMF) clustering, which led to the discovery of relevant differential genes. Integrating these with genes from the Gene Expression Omnibus (GEO) datasets and PPI interactions, we pinpointed crucial metabolic genes associated with TP53 mutation in MM. Additionally, we conducted prognostic analyses involving survival curves and receiver operating characteristic (ROC) charts.

RESULTS

Our study reveals that the metabolic gene ribonucleotide reductase M2 (RRM2), linked to TP53 mutation, correlates positively with the International Staging System (ISS) stage in MM patients and is an independent prognostic risk factor. In the TCGA dataset, among the 767 patients, the 35 MM patients with TP53 mutation generally had poor survival outcomes. Specifically, the patients with both TP53 mutation and high RRM2 expression had a 2-year survival rate of only 38.87%, whereas those with normal TP53 function and low RRM2 expression had a 2-year survival rate of 86.31% (p < 0.001).

CONCLUSION

RRM2 significantly impacts MM prognosis and is associated with TP53 mutation, presenting itself as a potential therapeutic target and prognostic marker for MM.

T4SEpp: A pipeline integrating protein language models to predict bacterial type IV secreted effectors

Many pathogenic bacteria use type IV secretion systems (T4SSs) to deliver effectors (T4SEs) into the cytoplasm of eukaryotic cells, causing diseases. The identification of effectors is a crucial step in understanding the mechanisms of bacterial pathogenicity, but this remains a major challenge. In this study, we used the full-length embedding features generated by six pre-trained protein language models to train classifiers predicting T4SEs and compared their performance. We integrated three modules into a model called T4SEpp. The first module searched for full-length homologs of known T4SEs, signal sequences, and effector domains; the second module fine-tuned a machine learning model using data for a signal sequence feature; and the third module used the three best-performing pre-trained protein language models. T4SEpp outperformed other state-of-the-art (SOTA) software tools, achieving ∼0.98 accuracy at a high specificity of ∼0.99, based on the assessment of an independent validation dataset. T4SEpp predicted 13 T4SEs from Helicobacter pylori, including the well-known CagA and 12 other potential ones, among which eleven could potentially interact with human proteins. This suggests that these potential T4SEs may be associated with the pathogenicity of H. pylori. Overall, T4SEpp provides a better solution to assist in the identification of bacterial T4SEs and facilitates studies of bacterial pathogenicity. T4SEpp is freely accessible at https://bis.zju.edu.cn/T4SEpp.

Gene regulatory network analysis identifies MYL1, MDH2, GLS, and TRIM28 as the principal proteins in the response of mesenchymal stem cells to Mg2+ ions

Magnesium (Mg)-based implants have emerged as a promising alternative for orthopedic applications, owing to their bioactive properties and biodegradability. As the implants degrade, Mg2+ ions are released, influencing all surrounding cell types, especially mesenchymal stem cells (MSCs). MSCs are vital for bone tissue regeneration, therefore, it is essential to understand their molecular response to Mg2+ ions in order to maximize the potential of Mg-based biomaterials. In this study, we conducted a gene regulatory network (GRN) analysis to examine the molecular responses of MSCs to Mg2+ ions. We used time-series proteomics data collected at 11 time points across a 21-day period for the GRN construction. We studied the impact of Mg2+ ions on the resulting networks and identified the key proteins and protein interactions affected by the application of Mg2+ ions. Our analysis highlights MYL1, MDH2, GLS, and TRIM28 as the primary targets of Mg2+ ions in the response of MSCs during 1-21 days phase. Our results also identify MDH2-MYL1, MDH2-RPS26, TRIM28-AK1, TRIM28-SOD2, and GLS-AK1 as the critical protein relationships affected by Mg2+ ions. By offering a comprehensive understanding of the regulatory role of Mg2+ ions on MSCs, our study contributes valuable insights into the molecular response of MSCs to Mg-based materials, thereby facilitating the development of innovative therapeutic strategies for orthopedic applications.

Pseudomonas aeruginosa quorum sensing and biofilm attenuation by a di-hydroxy derivative of piperlongumine (PL-18)

Bacterial communication, Quorum Sensing (QS), is a target against virulence and prevention of antibiotic-resistant infections. 16 derivatives of Piperlongumine (PL), an amide alkaloid from Piper longum L., were screened for QS inhibition. PL-18 had the best QSI activity. PL-18 inhibited the lasR-lasI, rhlR-rhlI, and pqs QS systems of Pseudomonas aeruginosa. PL-18 inhibited pyocyanin and rhamnolipids that are QS-controlled virulence elements. Iron is an essential element for pathogenicity, biofilm formation and resilience in harsh environments, its uptake was inhibited by PL-18. Pl-18 significantly reduced the biofilm biovolume including in established biofilms. PL-18-coated silicon tubes significantly inhibited biofilm formation. The transcriptome study of treated P. aeruginosa showed that PL-18 indeed reduced the expression of QS and iron homeostasis related genes, and up regulated sulfur metabolism related genes. Altogether, PL-18 inhibits QS, virulence, iron uptake, and biofilm formation. Thus, PL-18 should be further developed against bacterial infection, antibiotic resistance, and biofilm formation.

Thousands of oscillating LncRNAs in the mouse testis

The long noncoding RNAs (lncRNAs) are involved in numerous fundamental biological processes, including circadian regulation. Although recent studies have revealed insights into the functions of lncRNAs, how the lncRNAs regulate circadian rhythms still requires a deeper investigation. In this study, we generate two datasets of RNA-seq profiles of the mouse (Mus musculus) testis under light-dark (LD) cycle. The first dataset included 18,613 unannotated transcripts measured at 12 time points, each with duplicate samples, under LD conditions; while the second dataset included 21,414 unannotated transcripts measured at six time points, each with three replicates, under desynchronized and control conditions. We identified 5964 testicular lncRNAs in each dataset by BLASTing these transcripts against the known mouse lncRNAs from the NONCODE database. MetaCycle analyses were performed to identify 519, 475, and 494 rhythmically expressed mouse testicular lncRNAs in the 12-time-point dataset, the six-time-point control dataset, and the six-time-point desynchronized dataset, respectively. A comparison of the expression profiles of the lncRNAs under desynchronized and control conditions revealed that 427 rhythmically expressed lncRNAs from the control condition became arrhythmic under the desynchronized condition, suggesting a possible loss of rhythmicity. In contrast, 446 arrhythmic lncRNAs from the control condition became rhythmic under the desynchronized condition, suggesting a possible gain of rhythmicity. Interestingly, 48 lncRNAs were rhythmically expressed under both desynchronized and control conditions. These oscillating lncRNAs were divided into morning lncRNAs, evening lncRNAs, and night lncRNAs based on their time-course expression patterns. We interrogated the promoter regions of these rhythmically expressed mouse testicular lncRNAs to predict their possible regulation by the E-box, D-box, or RORE promoter motifs. GO and KEGG analyses were performed to identify the possible biological functions of these rhythmically expressed mouse testicular lncRNAs. Further, we conducted conservation analyses of the rhythmically expressed mouse testicular lncRNAs with lncRNAs from humans, rats, and zebrafish, and uncovered three mouse testicular lncRNAs conserved across these four species. Finally, we computationally predicted the conserved lncRNA-encoded peptides and their 3D structures from each of the four species. Taken together, our study revealed thousands of rhythmically expressed lncRNAs in the mouse testis, setting the stage for further computational and experimental validations.

Analysis and identification of ferroptosis-related diagnostic markers in rheumatoid arthritis

BACKGROUND

Rheumatoid arthritis (RA) is an autoimmune, inflammatory joint disease. There is growing evidence that ferroptosis is involved in the pathogenesis of RA. This study aimed to search for diagnostic markers of ferroptosis in RA and to analyse the potential mechanisms and clinical value.

MATERIALS AND METHODS

RA-associated datasets were used from the publicly available GEO database. Three methods of machine learning were applied to screen biomarkers. The diagnostic efficacy of the results was also verified by receiver operating characteristic (ROC) curve, external dataset, qRT-PCR and Western blot. Enrichment analysis was performed in this process, while protein-protein interaction (PPI) analysis and immune infiltration correlation analysis were performed using biomarkers, and competing endogenous RNA (ceRNA) networks were constructed to search for prospective therapeutic targets.

RESULTS

MMP13 and GABARAPL1 can be used as ferroptosis diagnostic genes in RA. The ROC curve and PPI result demonstrated that MMP13 and GABARAPL1 had an excellent diagnostic value. The results of signature genes in the external dataset, qRT-PCR and Western blot further confirm our findings. The enrichment analysis showed that p53, MAPK and NOD-like receptor signalling pathways may be involved in the process of ferroptosis in RA. In addition, two ferroptosis diagnostic genes in RA participate in the occurrence of ferroptosis in RA via oxidative stress, metabolism and immune response. Immune infiltration analysis showed that RA extensively infiltrated B cells, T cells, macrophages and other immune cells. Persistent immune activation may be an essential reason for the progression of ferroptosis in RA. We also obtained five potential therapeutic agents for RA and some long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) regulating ferroptosis diagnostic genes.

CONCLUSIONS

Our study suggests that MMP13 and GABARAPL1, which are closely linked with oxidative stress and immunological modulation, can be used as ferroptosis-related potential diagnostic markers in RA and provide new clues regarding the diagnostic and therapeutic targets of ferroptosis in RA.

Potential mechanism of Qinggong Shoutao pill alleviating age-associated memory decline based on integration strategy

CONTEXT

Qinggong Shoutao Wan (QGSTW) is a pill used as a traditional medicine to treat age-associated memory decline (AAMI). However, its potential mechanisms are unclear.

OBJECTIVE

This study elucidates the possible mechanisms of QGSTW in treating AAMI.

MATERIALS AND METHODS

Network pharmacology and molecular docking approaches were utilized to identify the potential pathway by which QGSTW alleviates AAMI. C57BL/6J mice were divided randomly into control, model, and QGSTW groups. A mouse model of AAMI was established by d-galactose, and the pathways that QGSTW acts on to ameliorate AAMI were determined by ELISA, immunofluorescence staining and Western blotting after treatment with d-gal (100 mg/kg) and QGSTW (20 mL/kg) for 12 weeks.

RESULTS

Network pharmacology demonstrated that the targets of the active components were significantly enriched in the cAMP signaling pathway. AKT1, FOS, GRIN2B, and GRIN1 were the core target proteins. QGSTW treatment increased the discrimination index from -16.92 ± 7.06 to 23.88 ± 15.94% in the novel location test and from -19.54 ± 5.71 to 17.55 ± 6.73% in the novel object recognition test. ELISA showed that QGSTW could increase the levels of cAMP. Western blot analysis revealed that QGSTW could upregulate the expression of PKA, CREB, c-Fos, GluN1, GluA1, CaMKII-α, and SYN. Immunostaining revealed that the expression of SYN was decreased in the CA1 and DG.

DISCUSSION AND CONCLUSIONS

This study not only provides new insights into the mechanism of QGSTW in the treatment of AAMI but also provides important information and new research ideas for the discovery of traditional Chinese medicine compounds that can treat AAMI.

The effect of ethanol extracts of loulu flower on LPS-induced acute lung injury in mice

ETHNOPHARMACOLOGICAL RELEVANCE

In Mongolian medicine, Loulu flower (LLF), the dried inflorescence of Rhaponticum uniflorum (L.) DC. from the Compositae family, has been used to clear heat and relieve toxicity for millennia, particularly in the treatment of pneumonia.

AIM OF THIS STUDY

To reveal the effects of LLF on mice with lipopolysaccharide (LPS)-stimulated acute lung injury (ALI) and elucidate the underlying mechanisms.

MATERIALS AND METHODS

ALI was established in BALB/c mice via nasal drops administration of LPS (5 mg/kg). The mice were then orally administrated with various doses of LLF extracts and the positive drug dexamethasone (DEX, 5 mg/kg), once daily for seven consecutive days. Last day, after being stimulated with LPS for 6h, the mice were closed dislocation of cervical vertebra, the serum, bronchus alveolar lavage fluid (BALF) and lung tissue were put into the EP tube and stored at -80 °C for further analysis. The changes of histopathology were tested by hematoxylin and eosin stain (H&E), the levels of, IL-1β, IL-18, TNF-α and IL-4 in BALF and serum were measured by ELISA. The pathways related to the treatment of ALI were predicted by network pharmacology. The expression levels of TLR4/NF-κB and NLRP3 signaling pathway-associated proteins, COX-2 and ERK were tested by western blotting. The levels of P65 and NLRP3 in lung tissues were determined by immunofluorescence analysis.

RESULTS

LLF total extract and the extract parts could alleviate the inflammatory cell infiltration, thicken the alveolar walls in lung tissues, reduce the levels of IL-18, IL-1β in BALF, the TNF-α in both BALF and serum, meantime enhance the level of IL-4 in BALF and serum in mice with LPS-induced ALI. Our network pharmacology and comprehensive gene ontology analyses revealed the active constituents of LLF and the pathways, including TLR4/NF-κB, NLRP3 and MAPK signaling pathways, which play significant roles in ALI. Furthermore, both the total extract and its extraction portions suppressed the expressions of proteins related with the COX-2, p-ERK and TLR4/NF-κB signaling pathway (TLR4, p-IκB, p-p65), as well as the NLRP3 signaling pathway (NLRP3, cleaved caspase-1, caspase-1, IL-1β).

CONCLUSION

LLF could improve the pathological changes and reducing inflammatory reactions in mice induced by LPS. The mechanism may be related to the modulation of the TLR4/NLRP3 signaling pathways.

Identification of potential inhibitors for drug resistance in acute lymphoblastic leukemia through differentially expressed gene analysis and in silico screening

Acute lymphoblastic leukemia (ALL) is a disease of lymphocyte origin predominantly diagnosed in children. While its 5-year survival rate is high, resistance to chemotherapy drugs is still an obstacle. Our aim is to determine differentially expressed genes (DEGs) related to Asparaginase, Daunorubicin, Prednisolone, and Vincristine resistance and identify potential inhibitors via docking. Three datasets were accessed from the Gene Expression Omnibus database; GSE635, GSE19143, and GSE22529. The microarray data was analyzed using R4.2.0 and Bioconductor packages, and pathway and protein-protein interaction analysis were performed. We identified 1294 upregulated DEGs, with 12 genes consistently upregulated in all four resistant groups. KEGG analysis revealed an association with the PI3K-Akt pathway. Among DEGs, 33 hub genes including MDM2 and USP7 were pinpointed. Within common genes, CLDN9 and HS3ST3A1 were subjected to molecular docking against 3556 molecules. Following ADMET analysis, three drugs emerged as potential inhibitors: Flunarizine, Talniflumate, and Eltrombopag. Molecular dynamics analysis for HS3ST3A1 indicated all candidates had the potential to overcome drug resistance, Eltrombopag displaying particularly promising results. This study promotes a further understanding of drug resistance in ALL, introducing novel genes for consideration in diagnostic screening. It also presents potential inhibitor candidates to tackle drug resistance through repurposing.

Identification of feature genes and molecular mechanisms involved in cell communication in uveal melanoma through analysis of single‑cell sequencing data

Uveal melanoma (UM) is a highly metastatic cancer with resistance to immunotherapy. The present study aimed to identify novel feature genes and molecular mechanisms in UM through analysis of single-cell sequencing data. For this purpose, data were downloaded from The Cancer Genome Atlas and National Center for Biotechnology Information Gene Expression Omnibus public databases. The statistical analysis function of the CellPhoneDB software package was used to analyze the ligand-receptor relationships of the feature genes. The Metascape database was used to perform the functional annotation of notable gene sets. The randomForestSRC package and random survival forest algorithm were applied to screen feature genes. The CIBERSORT algorithm was used to analyze the RNA-sequencing data and infer the relative proportions of the 22 immune-infiltrating cell types. In vitro, small interfering RNAs were used to knockdown the expression of target genes in C918 cells. The migration capability and viability of these cells were then assessed by gap closure and Cell Counting Kit-8 assays. In total, 13 single-cell sample subtypes were clustered by t-distributed Stochastic Neighbor Embedding and annotated by the R package, SingleR, into 7 cell categories: Tissue stem cells, epithelial cells, fibroblasts, macrophages, natural killer cells, neurons and endothelial cells. The interactions in NK cells|Endothelial cells, Neurons|Endothelial cells, CD74_APP, and SPP1_PTGER4 were more significant than those in the other subsets. T-Box transcription factor 2, tropomyosin 4, plexin D1 (PLXND1), G protein subunit α I2 (GNAI2) and SEC14-like lipid binding 1 were identified as the feature genes in UM. These marker genes were found to be significantly enriched in pathways such as vasculature development, focal adhesion and cell adhesion molecule binding. Significant correlations were observed between key genes and immune cells as well as immune factors. Relationships were also observed between the expression levels of the key genes and multiple disease-related genes. Knockdown of PLXND1 and GNAI2 expression led to significantly lower viability and gap closure rates of C918 cells. Therefore, the results of the present study uncovered cell communication between endothelial cells and other cell types, identified innovative key genes and provided potential targets of gene therapy in UM.

Thyroid transcriptomic profiling reveals the differential regulation of lncRNA and mRNA related to prolificacy in small tail han sheep with FecB BB genotype

BACKGROUND

The thyroid gland is an important endocrine gland in animals that secretes thyroid hormones and acts on various organs throughout the body. lncRNAs are long non-coding RNAs that play an important role in animal reproduction; however, there is a lack of understanding of their expression patterns and potential roles in the thyroid gland of the Small Tail Han (STH) sheep. In this study, we used RNA-Seq technology to examine the transcriptome expression pattern of the thyroid from the luteal phase (LP) and follicular phase (FP) of FecB BB (MM) STH sheep.

RESULTS

We identified a total of 122 and 1287 differential expression lncRNAs (DELs) and differential expression mRNAs (DEGs), respectively, which were significantly differentially expressed. These DELs target genes and DEGs can be enriched in several signalling pathways related to the animal reproduction process.

CONCLUSIONS

The expression profiles of DELs and DEGs in thyroid glands provide a more comprehensive resource for elucidating the reproductive regulatory mechanisms of STH sheep.

Integrated network pharmacology and GC-MS-based metabolomics to investigate the chemical profile and efficacy of Anemarrhenae Rhizoma and its processed products

RATIONALE

Anemarrhenae Rhizoma (AR) has been a frequently utilized traditional Chinese medicine (TCM) for an extended period, with its salt-processed variant being a prevalent application form. Contemporary pharmacological investigations have demonstrated that the salt-processed iteration exhibits a multitude of markedly augmented pharmacological properties. However, whether the pharmacodynamic material basis of this change is related to volatile substances remains unclear. The aim of this study was to develop a strategy to screen volatile pharmacodynamic substances in AR and salt-processed AR (SAR).

METHODS

A comprehensive approach was developed to identify volatile pharmacodynamic compounds by integrating plant metabolomics, target network pharmacology, and molecular docking technology. Plant metabolomics using GC-MS analysis was conducted to identify volatile chemical markers distinguishing between AR and SAR. Subsequently, network pharmacology was utilized to investigate the correlation between chemical markers and associated diseases. Following this, molecular docking technology was utilized to explore the correlation between chemical markers and disease targets, resulting in the discovery of potential quality control markers.

RESULTS

Fifty volatile compounds were isolated and identified in the salt of AR and SAR. The findings from plant metabolomics analysis demonstrated a distinct differentiation, revealing 13 volatile chemical markers that distinguish between AR and SAR. A target (PPARG) associated with diabetes was identified through target network pharmacology analysis. Thirteen volatile components were subsequently chosen as potential quality markers, taking into account their hypoglycemic activity.

CONCLUSIONS

The method developed provides a novel strategy for the identification of pharmacophores in AR and SAR, as well as establishing a foundation for the exploration of the volatile differential components and pharmacodynamics in various processed products of TCMs. Additionally, the findings of this study can serve as a theoretical framework for the development and utilization of volatile components in AR and its processed derivatives.

Exploring the anti-inflammatory and immune regulatory effects of Taohe Chengqi decoction in sepsis-induced lung injury

ETHNOPHARMACOLOGICAL RELEVANCE

Sepsis presents complex pathophysiological challenges. Taohe Chengqi Decoction (THCQ), a traditional Chinese medicine, offers potential in managing sepsis-related complications, though its exact mechanisms are not fully understood.

AIM OF THE STUDY

This research aimed to assess the therapeutic efficacy and underlying mechanisms of THCQ on sepsis-induced lung injury.

MATERIALS AND METHODS

The study began with validating THCQ's anti-inflammatory effects through in vitro and in vivo experiments. Network pharmacology was employed for mechanistic exploration, incorporating GO, KEGG, and PPI analyses of targets. Hub gene-immune cell correlations were assessed using CIBERSORT, with further scrutiny at clinical and single-cell levels. Molecular docking explored THCQ's drug-gene interactions, culminating in qPCR and WB validations of hub gene expressions in sepsis and post-THCQ treatment scenarios.

RESULTS

THCQ demonstrated efficacy in modulating inflammatory responses in sepsis, identified through network pharmacology. Key genes like MAPK14, MAPK3, MMP9, STAT3, LYN, AKT1, PTPN11, and HSP90AA1 emerged as central targets. Molecular docking revealed interactions between these genes and THCQ components. qPCR results showed significant modulation of these genes, indicating THCQ's potential in reducing inflammation and regulating immune responses in sepsis.

CONCLUSION

This study sheds light on THCQ's anti-inflammatory and immune regulatory mechanisms in sepsis, providing a foundation for further research and potential clinical application.

Biological network comparison identifies a novel synergistic mechanism of Ginseng Radix-Astragali Radix herb pair in cancer-related fatigue

ETHNOPHARMACOLOGICAL RELEVANCE

Ginseng Radix and Astragali Radix are commonly combined to tonify Qi and alleviate fatigue. Previous studies have employed biological networks to investigate the mechanisms of herb pairs in treating different diseases. However, these studies have only elucidated a single network for each herb pair, without emphasizing the superiority of the herb combination over individual herbs.

AIM OF THE STUDY

This study proposes an approach of comparing biological networks to highlight the synergistic effect of the pair in treating cancer-related fatigue (CRF).

METHODS

The compounds and targets of Ginseng Radix, Astragali Radix, and CRF diseases were collected and predicted using different databases. Subsequently, the overlapping targets between herbs and disease were imported into the STRING and DAVID tools to build protein-protein interaction (PPI) networks and analyze enriched KEGG pathways. The biological networks of Ginseng Radix and Astragali Radix were compared separately or together using the DyNet application. Molecular docking was used to verify the predicted results. Further, in vitro experiments were conducted to validate the synergistic pathways identified in in silico studies.

RESULTS

In the PPI network comparison, the combination created 89 new interactions and an increased average degree (11.260) when compared to single herbs (10.296 and 9.394). The new interactions concentrated on HRAS, STAT3, JUN, and IL6. The topological analysis identified 20 core targets of the combination, including three Ginseng Radix-specific targets, three Astragali Radix-specific targets, and 14 shared targets. In KEGG enrichment analysis, the combination regulated additional signaling pathways (152) more than Ginseng Radix (146) and Astragali Radix (134) alone. The targets of the herb pair synergistically regulated cancer pathways, specifically hypoxia-inducible factor 1 (HIF-1) signaling pathway. In vitro experiments including enzyme-linked immunosorbent assay and Western blot demonstrated that two herbs combination could up-regulate HIF-1α signaling pathway at different combined concentrations compared to either single herb alone.

CONCLUSION

The herb pair increased protein interactions and adjusted metabolic pathways more than single herbs. This study provides insights into the combination of Ginseng Radix and Astragali Radix in clinical practice.

De novo mutations promote inflammation in children with STAT3 gain-of-function syndrome by affecting IL-1β expression

STAT3 gain-of-function syndrome, characterized by early-onset autoimmunity and primary immune regulatory disorder, remains poorly understood in terms of its immunological mechanisms. We employed whole-genome sequencing of familial trios to elucidate the pivotal role of de novo mutations in genetic diseases. We identified 37 high-risk pathogenic loci affecting 23 genes, including a novel STAT3 c.508G>A mutation. We also observed significant down-regulation of pathogenic genes in affected individuals, potentially associated with inflammatory responses regulated by PTPN14 via miR378c. These findings enhance our understanding of the pathogenesis of STAT3 gain-of-function syndrome and suggest potential therapeutic strategies. Notably, combined JAK inhibitors and IL-6R antagonists may offer promising treatment avenues for mitigating the severity of STAT3 gain-of-function syndrome.

LncRNA-mRNA co-expression analysis reveals aquaporin-9-promoted neutrophil extracellular trap formation and inflammatory activation in sepsis

Sepsis is a life-threatening condition caused by an excessive inflammatory response to an infection. However, the precise regulatory mechanism of sepsis remains unclear. Using a strand-specific RNA-sequencing, we identified 115 hub differentially expressed long noncoding RNAs (lncRNAs) and 443 mRNAs in septic patients, primarily participated in crucial pathways including neutrophil extracellular trap (NET) formation and toll-like receptor signaling. Notably, NETs related gene aquaporin-9 (AQP9) and its associated lncRNAs exhibited significant upregulation in septic neutrophils. Functional experiments revealed AQP9 interacts with its lncRNAs to augment the formation of neutrophil NETs. In murine sepsis models, AQP9 inhibition with phloretin reduced proinflammatory cytokine production and lung damage. These findings provide crucial insights into the regulatory role of AQP9 in sepsis, unraveling its interaction with associated lncRNAs in transmitting downstream signals, holding promise in informing the development of novel therapeutic strategies aimed at ameliorating the debilitating effects of sepsis.

Unraveling the antifungal composition of bitter orange decoction against the melon pathogen Fusarium jinanense

Bitter orange (Citrus aurantium) is an important source of essential oils with high antimicrobial activities, however the composition and antifungal potential of the decoction peels is little explored. This study assessed the peel decoction's chemical profile at the secondary metabolism level and its antifungal activity against the melon phytopathogen Fusarium jinanense. The decoction's antifungal potential was investigated using a bioassay-guided fractionation approach based on Solid-Phase Extraction (SPE) and LC-HRMS/MS analysis. Coumarins and flavones were the most abundant classes of compounds in the high-value fractions responsible for up to 61% of the mycelial inhibition of F. jinanense. Overall, this study has presented for the first time the chemical composition, the antifungal potential of the decoction of C. aurantium peels and the compounds associated with these results. This strategy can guide the exploration of under-explored food sources and add value to compounds or fractions enriched with bioactive compounds.

Distinct planting patterns exert legacy effects on the networks and assembly of root-associated microbiomes in subsequent crops

Soil legacy effects from previous crops can significantly influence plant-soil interactions in crop rotations. However, the microbial mechanism underlying this effect in subsequent root-associated compartments remains unclear. We investigated the effects of planting patterns (four-year continuous maize [MM], three-year winter wheat and one-year maize rotation [WM], and three-year potato and one-year maize rotation [PM]) on the microbial composition and structure of root-associated compartments, the effect of distinct crops on subsequent microbial co-occurrence patterns, and the assembly mechanism by which the root-associated compartments (bulk soil, rhizosphere, and roots) in subsequent crops regulate the microbiome habitat. Compared with MM, the relative abundance of Acidobacteria in WM was 29.7 % lower, whereas that of Bacteroidota in PM was 37.9 % higher in all three compartments. The co-occurrence patterns of the microbial communities exhibited varied responses to different planting patterns. Indicator taxon analysis revealed less shared and specific species in the root bacterial and fungal networks. The planting pattern elicited specific responses from modules within bacterial and fungal co-occurrence networks in all three compartments. Moreover, the planting patterns and root-associated compartments collectively drove the assembly process of root-associated microorganisms. The neutral model showed that, compared with MM, the stochasticity of bacterial assembly decreased under WM and PM but increased for fungal assembly. WM and PM increased the relative effects of the homogenized dispersal of fungal assemblies in roots. We conclude that previous crops exhibit marked legacy effects in the root-associated microbiome. Therefore, soil heritage should not be ignored when discussing microbiome recruitment strategies and co-occurrence patterns in subsequent crops.

Unravelling the influence of microplastics with/without additives on radish (Raphanus sativus) and microbiota in two agricultural soils differing in pH

Here we investigated the effects of three types of microplastics (MPs), i.e., PS (P), ABS (B), PVC (V), and each with additive (MPAs) (PA, BA, and VA), on soil health, microbial community, and plant growth in two acidic and slightly alkaline soils. Incubation experiment revealed that although MPs and MPAs consistently stimulated soil nutrients and heavy metals (e.g., Mn, Cu) in weakly alkaline soils, only BA and VA led to increase in soil nutrients and heavy metals in acidic soils. This suggests distinct response patterns in the two soils depending on their initial pH. Concerning microorganisms, MPs and MPAs reduced the assembly degree of bacteria in acidic soils, with a reduction of Chloroflexi and Acidobacteriota but an increase of WPS-2 in VA. Culture experiment showed consistent positive or negative responses in radish seed germination, roots, and antioxidant activity across MPs and MPAs types in both soils, while the responses of seed heavy metals (e.g., Cr, Cd) were consistent in acidic soils but dependent on MPs and MPAs types in alkaline soils. Therefore, our study strongly suggests that the effects of MPs on soil-microbial-plant systems were highly dependent on initial soil characteristics and the types of MPs with plastic additives.

Bu-Shen-Ning-Xin decoction ameliorates premature ovarian insufficiency by suppressing oxidative stress through rno_circRNA_012284/rno_miR-760-3p/HBEGF pathway

BACKGROUND

POI (premature ovarian insufficiency) refers to premature and rapid decline of ovarian reserve function in women before the age of 40, which can be manifested as menstrual disorders, endocrine abnormalities and low fertility. Bu-Shen-Ning-Xin decoction (BSNXD) has been found to have therapeutic effects on POI. Nevertheless, how it exerts therapeutic effects remains elusive.

PURPOSE

This research aims to clarify the pharmacological mechanisms of BSNXD.

METHODS

We applied Ultra Performance Liquid Chromatography (UPLC) to identify the main components of BSNXD.4-vinylcyclohexene diepoxide(VCD)was used to induce POI models. ELISA detected the serum level of hormones. H&E staining evaluated the morphology of ovarian tissues.CircRNA and mRNA expression profiles in the ovaries of both POI rats and those treated with BSNXD were detected. Then, dysregulated circRNAs and mRNAs that were potentially altered by BSNXD were screened. Network pharmacology analysis was performed to identify drug targets of BSNXD active ingredients. A circRNA-miRNA-mRNA network and an oxidative stress(OS)-related subnetwork were constructed. Expression of rno_circRNA_012284, rno_miR-760-3p, and HBEGF(Heparin-binding epidermal growth factor-like growth factor) was measured by RT-PCR and their binding were verified by dual-luciferase reporter assays. ROS was measured through DCFH-DA fluorescence probes. The HBEGF target was selected for molecular docking with key active ingredients.Surface plasmon resonance(SPR) was applied to verify the binding ability and affinity between components and HBEGF.

RESULTS

UPLC analysis indicated that 6 chemical compounds including berberine, paeoniflorin, morroniside,gallic acid, loganin, baicalin were identified.Elevated FSH and LH levels, suppressed E2 and AMH levels in the serum, and inhibited follicles and corpus luteums in the ovarian tissues of VCD-induced rats were notably reversed by BSNXD.In total, 992 up- and 1135 down-regulated circRNAs, and 205 up- and 243 down-regulated mRNAs were found in POI rat ovaries following BSNXD administration. Furthermore, 198 drug targets of BSNXD were identified. An OS-related and BSNXD-targeted ceRNA subnetwork composed of rno_circRNA_012284/rno_miR-760-3p/HBEGF was established. rno_circRNA_012284 and HBEGF were up-regulated and rno_miR-760-3p was down-regulated in POI ovarian granulosa cells (OGCs) after BSNXD administration. rno_circRNA_012284 was a sponge of rno_miR-760-3p to elevate HBEGF expression. Moreover, rno_circRNA_012284 overexpression alleviated POI-induced excessive ROS generation in ovarian granulosa cells, while rno_circRNA_012284 inhibition exerted the opposite effect. Finally,molecular docking speculated active ingredients of each herb acted on HBEGF to reduce the OS. SPR tests showed that Berberine,Baicalein,Quercetin,Pachymic acid,Paeoniflorin exhibited satisfying affinity with HBEGF protein.

CONCLUSION

This study demonstrates that BSNXD ameliorates POI partly by attenuating OS in ovarian granulosa cells via rno_circRNA_012284/rno_miR-760-3p/HBEGF axis, uncovering the pharmacological mechanisms of BSNXD in alleviating POI.

Proteomics and metabolomics analysis of American shad (Alosa sapidissima) liver responses to heat stress

The dramatic changes in the global climate pose a major threat to the survival of many organisms, including fish. To date, the regulatory mechanisms behind the physiological responses of fish to temperature changes have been studied, and a comprehensive analysis of the regulatory mechanisms of temperature tolerance will help to propose effective strategies for fish to cope with global warming. In this study, we investigated the expression profiles of proteins and metabolites in liver tissues of American shad (Alosa sapidissima) corresponding to different water temperatures (24 °C, 27 °C and 30 °C) at various times (1-month intervals) under natural culture conditions. Proteomic analysis showed that the expression levels of the heat shock protein family (e.g. HSPE1, HSP70, HSPA5 and HSPA.1) increase significantly with temperature and that many differentially expressed proteins were highly enriched especially in pathways related to the endoplasmic reticulum, oxidative phosphorylation and glycolysis/gluconeogenesis processes. In addition, the results of conjoint metabolomics and proteomics analysis suggested that the contents of several important amino acids and chemical compounds, including L-serine, L-isoleucine, L-cystine, choline and betaine, changed significantly under high-temperature environmental stress, affecting the metabolic levels of starch, amino acid and glucose, which is thought to represent a possible energy conservation method for A. sapidissima to cope with rapid changes in external temperature. In summary, our findings demonstrate that living under high temperatures for a long period of time leads to different physiological defense responses in A. sapidissima, which provides some new ideas for analyzing the molecular regulatory patterns of adaptation to high temperature and also provides a theoretical basis for the subsequent improvement of fish culture in response to global warming.

Identification of diterpenoids from Salvia castanea Diels f. tomentosa Stib and their antitumor activities

Four new diterpenoid tropolones, salvirrddones A-D (1-4), and four new icetexanes, salvirrddices A-D (9-12), along with thirteen new 11,12-seco-norabietane diterpenoids, salvirrddnor A-M (14-24, 31, 32) and sixteen known compounds (5-8, 13, 25-30, 33-37), were isolated from the roots and rhizomes of Salvia castanea Diels f. tomentosa Stib. Their structures were elucidated by comprehensive spectroscopic analyses, quantum chemical calculations, and X-ray crystallography. Structurally, compounds 1-8 represent a class of rare natural products featuring a unique cyclohepta-2,4,6-trienone moiety with diterpenoid skeletons. Bioassays showed that only diterpenoid tropolones 3, 5, 6, and 7 exhibited significant activity against several human cancer cell lines with IC50 values ranging from 3.01 to 11.63 μM. Additionally, 3 was shown to inhibit Hep3B cell proliferation, block the G0/G1 phase of the cell cycle, induce mitochondrial dysfunction and oxidative stress, promote apoptosis, as well as inhibit migration and invasion in vitro. Meanwhile, 3 demonstrated anti-proliferative, pro-apoptotic, and migration-inhibitory effects in the Hep3B xenograft zebrafish model in vivo. Network pharmacological analysis and molecular docking results suggested that 3 may treat hepatocellular carcinoma (HCC) through the PI3K-Akt signaling pathway, as well as by binding PARP1 and CDK2 targets. Overall, the present results extremely expand the repertoire of diterpenoids from natural products and may provide a novel chemical scaffold for the discovery of new antitumor drugs.

Neurodegenerative pathways and metabolic changes in the hippocampus and cortex of mice exposed to urban particulate matter: Insights from an integrated interactome analysis

Recently, urban particulate matter (UPM) exposure has been associated with the development of brain disorders. This study uses bioinformatic analyses to elucidate the molecular unexplored mechanisms underlying the effects of UPM exposure on the brain. Mice are exposed to UPM (from 3 days to 20 weeks), and their behavioral patterns measured. We measure pathology and gene expression in the hippocampus and cortical regions of the brain. An integrated interactome of genes is established, which enriches information on metabolic processes. Using this network, we isolate the core genes that are differentially expressed in the samples. We observe cognitive loss and pathological changes in the brains of mice at 16 or 20 weeks of exposure. Through network analysis of core-differential genes and measurement of pathway activity, we identify differences in the response to UPM exposure between the hippocampus and cortex. However, neurodegenerative disease pathways are implicated in both tissues following short-term exposure to UPM. There were also significant changes in metabolic function in both tissues depending on UPM exposure time. Additionally, the cortex of UPM-exposed mice shows more similarities with psychiatric disorders than with neurodegenerative diseases. The connectivity map database is used to isolate genes contributing to changes in expression due to UPM exposure. New approaches for inhibiting or preventing the brain damage caused by UPM exposure can be developed by targeting the functions and selected genes identified in this study.

Unravelling the involvement of protein disorder in cyanobacterial stress responses

This study has explored the involvement of Intrinsically Disordered Proteins (IDPs) in cyanobacterial stress response. IDPs possess distinct physicochemical properties, which allow them to execute diverse functions. Anabaena PCC 7120, the model photosynthetic, nitrogen-fixing cyanobacterium encodes 688 proteins (11 % of the total proteome) with at least one intrinsically disordered region (IDR). Of these, 130 proteins that showed >30 % overall disorder were designated as IDPs. Physico-chemical analysis, showed these IDPs to adopt shapes ranging from 'globular' to 'tadpole-like'. Upon exposure to NaCl, 41 IDP-encoding genes were found to be differentially expressed. Surprisingly, most of these were induced, indicating the importance of IDP-accumulation in overcoming salt stress. Subsequently, six IDPs were identified to be induced by multiple stresses (salt, ammonium and selenite). Interestingly, the presence of these 6-multiple stress-induced IDPs was conserved in filamentous cyanobacteria. Utilizing the experimental proteomic data of Anabaena, these 6 IDPs were found to interact with many proteins involved in diverse pathways, underscoring their physiological importance as protein hubs. This study lays the framework for IDP-related research in Anabaena by (a) identifying, as well as physiochemically characterizing, all the disordered proteins and (b) uncovering a subset of IDPs that are likely to be critical in adaptation to environmental stresses.

Physiological and molecular mechanisms of carbon quantum dots alleviating Cu2+ toxicity in Salvia miltiorrhiza bunge

Excessive Cu2+ is toxic to plants. Carbon quantum dots (CQDs) exhibit certain chelating properties towards heavy metals, and they also demonstrate antioxidant activities. To explore the mechanism for alleviating the Cu2+ toxicity of Salvia miltiorrhiza Bunge mediated by CQDs, CQDs that contained CC, CO, H-O, C-N and C-O functional groups with particle size less than 10 nm and that emitted blue fluorescence were prepared. S. miltiorrhiza seedlings were treated with 200 μM of Cu2+ and 500 mg/L of CQDs to relieve stress. Exogenous CQDs effectively restored plant phenotype; reduced Cu2+, H2O2 and malondialdehyde contents and restored total superoxide dismutase, peroxidase and catalase activities under Cu2+ toxicity. Simultaneously, an association network of Cu2+ transport-related and metabolic pathway genes of phenolic acids and terpenoids was established on the basis of cross-species transcriptome analysis. Combined with reverse transcription quantitative real-time polymerase chain reaction analysis, the potential molecular mechanism of CQDs, i.e. promoting phenolic acid biosynthesis to alleviate Cu2+ toxicity, was revealed by activating the expression of key enzyme genes of phenolic acid synthesis. This study provides a theoretical basis for Cu2+ pollution prevention and control in plants. It also laid a foundation for alleviating Cu stress by using CQDs in agricultural production.

An integrated bioinformatics approach reveals the potential role of microRNA-30b-5p and let-7a-5p during SARS CoV-2 spike-1 mediated neuroinflammation

SARS-CoV-2 induced neuroinflammation contributing to neurological sequelae is one of the critical outcomes of long-COVID, however underlying regulatory mechanisms involved therein are poorly understood. We deciphered the profile of dysregulated microRNAs, their targets, associated pathways, protein-protein interactions (PPI), transcription factor-hub genes interaction networks, hub genes-microRNA co-regulatory networks in SARS-CoV-2 Spike-1 (S1) stimulated microglial cells along with candidate drug prediction using RNA-sequencing and multiple bioinformatics approaches. We identified 11 dysregulated microRNAs in the S1-stimulated microglial cells (p < 0.05). KEGG analysis revealed involvement of important neuroinflammatory pathways such as MAPK signalling, PI3K-AKT signalling, Ras signalling and axon guidance. PPI analysis further identified 11 hub genes involved in these pathways. Real time PCR validation confirmed a significant upregulation of microRNA-30b-5p and let-7a-5p; proinflammatory cytokines- IL-6, TNF-α, IL-1β, GM-CSF; and inflammatory genes- PIK3CA and AKT in the S1-stimulated microglial cells, while PTEN and SHIP1 expression was decreased as compared to the non-stimulated cells. Drug prediction analysis further indicated resveratrol, diclofenac and rapamycin as the potential drugs based on their degree of interaction with hub genes. Thus, targeting of these microRNAs and/or their intermediate signalling molecules would be a prospective immunotherapeutic approach in alleviating SARS-CoV-2-S1 mediated neuroinflammation; and needs further investigations.

Whole exome sequencing analyses reveal novel genes in telomere length and their biomedical implications

Telomere length is a putative biomarker of aging and is associated with multiple age-related diseases. There are limited data on the landscape of rare genetic variations in telomere length. Here, we systematically characterize the rare variant associations with leukocyte telomere length (LTL) through exome-wide association study (ExWAS) among 390,231 individuals in the UK Biobank. We identified 18 robust rare-variant genes for LTL, most of which estimated effects on LTL were significant (> 0.2 standard deviation per allele). The biological functions of the rare-variant genes were associated with telomere maintenance and capping and several genes were specifically expressed in the testis. Three novel genes (ASXL1, CFAP58, and TET2) associated with LTL were identified. Phenotypic association analyses indicated significant associations of ASXL1 and TET2 with cancers, age-related diseases, blood assays, and cardiovascular traits. Survival analyses suggested that carriers of ASXL1 or TET2 variants were at increased risk for cancers; diseases of the circulatory, respiratory, and genitourinary systems; and all-cause and cause-specific deaths. The CFAP58 carriers were at elevated risk of deaths due to cancers. Collectively, the present whole exome sequencing study provides novel insights into the genetic landscape of LTL, identifying novel genes associated with LTL and their implications on human health and facilitating a better understanding of aging, thus pinpointing the genetic relevance of LTL with clonal hematopoiesis, biomedical traits, and health-related outcomes.

lncRNA-gene network analysis reveals the effects of early maternal nutrition on mineral homeostasis and energy metabolism in the fetal liver transcriptome of beef heifers

Maternal nutrition during pregnancy influences fetal development; however, the regulatory markers of fetal programming across different gestational phases remain underexplored in livestock models. Herein, we investigated the regulatory role of long non-coding RNAs (lncRNAs) on fetal liver gene expression, the impacts of maternal vitamin and mineral supplementation, and the rate of maternal body weight gain during the periconceptual period. To this end, crossbred Angus heifers (n=31) were randomly assigned to a 2×2 factorial design to evaluate the main effects of the rate of weight gain (low gain [LG, avg. daily gain of 0.28 kg/day] vs. moderate gain [MG, avg. daily gain of 0.79 kg/day]) and vitamins and minerals supplementation (VTM vs. NoVTM). On day 83±0.27 of gestation, fetuses were collected for morphometric measurements, and fetal liver was collected for transcriptomic and mineral analyses. The maternal diet significantly affected fetal liver development and mineral reserves. Using an RNA-Seq approach, we identified 320 unique differentially expressed genes (DEGs) across all six comparisons (FDR <0.05). Furthermore, lncRNAs were predicted through the FEELnc pipeline, revealing 99 unique differentially expressed lncRNAs (DELs). The over-represented pathways and biological processes (BPs) were associated with energy metabolism, Wnt signaling, CoA carboxylase activity, and fatty acid metabolism. The DEL-regulated BPs were associated with metal ion transport, pyrimidine metabolism, and classical energy metabolism-related glycolytic, gluconeogenic, and TCA cycle pathways. Our findings suggest that lncRNAs regulate mineral homeostasis- and energy metabolism-related gene networks in the fetal liver in response to early maternal nutrition.

Weighted gene co-expression network analysis identifies important modules and hub genes involved in the regulation of breast muscle yield in broilers

OBJECTIVE

Increasing breast meat production is one of the primary goals of the broiler industry. Over the past few decades, tremendous progress has been made in genetic selection and the identification of candidate genes for improving the breast muscle mass. However, the molecular network contributing to muscle production traits in chickens still needs to be further illuminated.

METHODS

A total of 150 1-day-old male 817 broilers were reared in a floor litter system. At the market age of 50 d, eighteen healthy 817 broilers were slaughtered and the left pectoralis major muscle sample from each bird was collected for RNA-seq sequencing. The birds were then plucked and eviscerated and the whole breast muscle was removed and weighed. Breast muscle yield was calculated as the ratio of the breast muscle weight to the eviscerated weight. To identify the co-expression networks and hub genes contributing to breast muscle yield in chickens, we performed weighted gene co-expression network analysis (WGCNA) based on the 18 transcriptome datasets of pectoralis major muscle from eighteen 817 broilers.

RESULTS

The WGCNA analysis classified all co-expressed genes in the pectoral muscle of 817 broilers into 44 modules. Among these modules, the turquoise and skyblue3 modules were found to be most significantly positively (r = 0.78, p = 1e-04) and negatively (r = -0.57, p = 0.01) associated with breast meat yield, respectively. Further analysis identified several hub genes (e.g., DLX3, SH3RF2, TPM1, CAV3, MYF6, and CFL2) that involved in muscle structure and muscle development were identified as potential regulators of breast meat production.

CONCLUSION

The present study has advanced our understanding of the molecular regulatory networks contributing to muscle growth and breast muscle production and will contribute to the molecular breeding of chickens in the future.

The short-term effect of microplastics in lettuce involves size- and dose-dependent coordinate shaping of root metabolome, exudation profile and rhizomicrobiome

Micro- and nano-plastics (MNPs) in the soil can impact the microbial diversity within rhizospheres and induce modifications in plants' morphological, physiological, and biochemical parameters. However, a significant knowledge gap still needs to be addressed regarding the specific effects of varying particle sizes and concentrations on the comprehensive interplay among soil dynamics, root exudation, and the overall plant system. In this sense, different omics techniques were employed to clarify the mechanisms of the action exerted by four different particle sizes of polyethylene plastics considering four different concentrations on the soil-roots exudates-plant system was studied using lettuce (Lactuca sativa L. var. capitata) as a model plant. The impact of MNPs was investigated using a multi-omics integrated approach, focusing on the tripartite interaction between the root metabolic process, exudation pattern, and rhizosphere microbial modulation. Our results showed that particle size and their concentrations significantly modulated the soil-roots exudates-plant system. Untargeted metabolomics highlighted that fatty acids, amino acids, and hormone biosynthesis pathways were significantly affected by MNPs. Additionally, they were associated with the reduction of rhizosphere bacterial α-diversity, following a size-dependent trend for specific taxa. The omics data integration highlighted a correlation between Pseudomonadata and Actinomycetota phyla and Bacillaceae family (Peribacillus simplex) and the exudation of flavonoids, phenolic acids, and lignans in lettuce exposed to increasing sizes of MNPs. This study provides a novel insight into the potential effects of different particle sizes and concentrations of MNPs on the soil-plant continuum, providing evidence about size- and concentration-dependent effects, suggesting the need for further investigation focused on medium- to long-term exposure.

Diesel exhaust particle extract elicits an oxPAPC-like transcriptomic profile in macrophages across multiple mouse strains

Air pollution is a prominent cause of cardiopulmonary illness, but uncertainties remain regarding the mechanisms mediating those effects as well as individual susceptibility. Macrophages are highly responsive to particles, and we hypothesized that their responses would be dependent on their genetic backgrounds. We conducted a genome-wide analysis of peritoneal macrophages harvested from 24 inbred strains of mice from the Hybrid Mouse Diversity Panel (HMDP). Cells were treated with a DEP methanol extract (DEPe) to elucidate potential pathways that mediate acute responses to air pollution exposures. This analysis showed that 1247 genes were upregulated and 1383 genes were downregulated with DEPe treatment across strains. Pathway analysis identified oxidative stress responses among the most prominent upregulated pathways; indeed, many of the upregulated genes included antioxidants such as Hmox1, Txnrd1, Srxn1, and Gclm, with NRF2 (official gene symbol: Nfe2l2) being the most significant driver. DEPe induced a Mox-like transcriptomic profile, a macrophage subtype typically induced by oxidized phospholipids and likely dependent on NRF2 expression. Analysis of individual strains revealed consistency of overall responses to DEPe and yet differences in the degree of Mox-like polarization across the various strains, indicating DEPe × genetic interactions. These results suggest a role for macrophage polarization in the cardiopulmonary toxicity induced by air pollution.

Dysregulated Genes and Signaling Pathways in the Formation and Rupture of Intracranial Aneurysm

Intracranial aneurysm (IA) has the potential to rupture. Despite scientific advances, we are still not in a position to screen patients for IA and identify those at risk of rupture. It is critical to comprehend the molecular basis of disease to facilitate the development of novel diagnostic strategies. We used transcriptomics to identify the dysregulated genes and understand their role in the disease biology. In particular, RNA-Seq was performed in tissue samples of controls, unruptured IA, and ruptured IA. Dysregulated genes (DGs) were identified and analyzed to understand the functional aspects of molecules. Subsequently, candidate genes were validated at both transcript and protein level. There were 314 DGs in patients with unruptured IA when compared to control samples. Out of these, SPARC and OSM were validated as candidate molecules in unruptured IA. PI3K-AKT signaling pathway was found to be an important pathway for the formation of IA. Similarly, 301 DGs were identified in the samples of ruptured IA when compared with unruptured IAs. CTSL was found to be a key candidate molecule which along with Hippo signaling pathway may be involved in the rupture of IA. We conclude that activation of PI3K-AKT signaling pathway by OSM along with up-regulation of SPARC is important for the formation of IA. Further, regulation of Hippo pathway through PI3K-AKT signaling results in the down-regulation of YAP1 gene. This along with up-regulation of CTSL leads to further weakening of aneurysm wall and its subsequent rupture.