Serum tsncRNAs Reveals Novel Potential Therapeutic Targets of Salvianolic Acid B on Atherosclerosis
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA884351 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR21710559.fastq.gz | Fastqsanger.gz | |||
| SRR21710560.fastq.gz | Fastqsanger.gz | |||
| SRR21710561.fastq.gz | Fastqsanger.gz | |||
| SRR21710562.fastq.gz | Fastqsanger.gz | |||
| SRR21710563.fastq.gz | Fastqsanger.gz |
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Project description:Objective: Salvianolic Acid B (SalB) extracted from the roots and rhizomes of Salvia Miltiorrhiza Bunge has been utilized to delay the progression of atherosclerosis (AS). Its therapeutic mechanisms remain unclear. Pre-transfer RNA and mature transfer RNA (tsncRNAs) is a novel class of short non-coding RNA possessing potential regulating functions. In this study the novel therapeutic targets of SalB by tsncRNAs-sequencing were explored. Methods: Mice were randomly divided into three groups: control group (CON) AS model group (MOD) and SalB-treated group (SAB). The weight change aortic sinus plaque and inflammatory cytokines (IL-6 IL-10 TNF-) were assessed. Total RNA was extracted from serum to obtain tsncRNAs followed expression profiling by the Illumina NextSeq instrument. Subsequently tRNAscan and TargetScan were used to predict tsncRNAs targets. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway were used to predict the bioinformatics analysis. Quantitative real-time PCR (qPCR) was the method to validate potential tsncRNAs and related targets. Results: A total of 8 tsncRNAs (fold change >1.5 and P-value <0.05) were significantly decreased in MOD group compared to CON group. Among them tRNA-Glu-CTC-014 and tRNA-Gly-GCC-074 were markedly increased by SalB treatment and validated with quantitative real-time PCR. GO analysis revealed that the altered target genes of the selected tsncRNAs were most enriched in protein binding and cellular process. Moreover KEGG pathway analysis demonstrated that altered target genes of tsncRNAs were most enriched in mitogen-activated protein kinase (MAPK) signaling pathway. Conclusion: In conclusion tRNA-Glu-CTC-014 and tRNA-Gly-GCC-074 were the potential therapeutic targets of SalB on AS treatment.
2023-08-31 | GSE214198 | GEO
Project description:Atherosclerosis is a persistent inflammatory state accompanied by lipid overload. Vascular fibrosis is one of the primary causes of atherosclerosis development. Although ligustilide (Lig) was shown to exert obvious antiatherogenic effects in previous studies, its precise mechanism has not been comprehensively discussed. In this paper, pharmacologic studies were performed to explore the pharmacodynamic effects of Lig on protecting aorta vascular wall structures and modulating serum inflammatory factors in ApoE-/- mice. Chemical proteomics based on a Lig-derived photoaffinity labelling (Lig-PAL) probe were applied to identify potential therapeutic targets. Mothers against decapentaplegic homologue 3 (SMAD3), which is closely related to the development of vascular fibrosis and atherosclerosis, was identified as a potential target of Lig. Lig suppressed the phosphorylation and nuclear translocation of SMAD3 by blocking the interaction between SMAD3 and transforming growth factor-β (TGF-β) receptor 1, thereby inhibiting the collagen synthesis process, preventing vascular fibrosis and improving atherosclerosis. The quantitative proteomics results from Lig-treated atherosclerotic ApoE-/- mice also indicated that Lig inhibits the expression of collagens I and III, interferes with collagen fibril organization processes and protects the aorta from vascular fibrosis. Hence, developing a novel SMAD3 inhibitor may present another therapeutic option for preventing atherosclerosis.
2020-01-21 | PXD017125 | Pride
Project description:Smooth muscle cells (SMC) play significant roles in atherosclerosis via phenotypic switching, a pathological process in which SMC dedifferentiation, migration and transdifferentiation into other cell types. Yet, how SMC contribute to pathophysiology of atherosclerosis remains elusive. To reveal the trajectories of SMC transdifferentiation during atherosclerosis and to identify molecular targets for disease therapy, we combined SMC fate mapping and single-cell RNA sequencing of both mouse and human atherosclerotic plaques.
2020-10-06 | GSE155513 | GEO
Project description:Smooth muscle cells (SMC) play significant roles in atherosclerosis via phenotypic switching, a pathological process in which SMC dedifferentiation, migration and transdifferentiation into other cell types. Yet, how SMC contribute to pathophysiology of atherosclerosis remains elusive. To reveal the trajectories of SMC transdifferentiation during atherosclerosis and to identify molecular targets for disease therapy, we combined SMC fate mapping and single-cell RNA sequencing of both mouse and human atherosclerotic plaques.
2020-10-06 | GSE155512 | GEO
Project description:Cardiovascular diseases represent a leading cause of deaths globally; of which atherosclerosis is a major contributor. Selective retention of circulating apolipoprotein B particles in the sub endothelial space by arterial wall proteoglycans and their subsequent modification is currently thought to be a hallmark of the disease. The exact mechanism responsible for lesion development is not fully understood. Currently, ultrasonic assessment of carotid artery intima media thickness (IMT) is commonly used as a pre-clinical marker of atherosclerosis. However, as the onset of atherosclerotic process and the appearance of carotid artery plaque can vary, the identification of additional biomarkers showing potential etiological aspects of disease is an important goal. This study describes the use of a label free mass spectrometry approach in the proteomics analysis of serum samples from control and atherosclerotic subjects. The samples were from a study cohort recruited in The Cardiovascular Risk in Young Finns Study, with a goal of identifying biomarkers for atherosclerosis. Samples from 43 individuals with a early non-obstructive plaques and 43 controls were used (Matched by age, sex, body size and systolic blood pressure).
2018-07-30 | PXD008278 | Pride
Project description:Application of EIIP / ISM bioinformatics platform in detection of new therapeutic targets and potential therapeutic molecules. Study of the molecular basis of rare human diseases
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2021-08-04 | PXD027696 |
Project description:BackgroundVascular disease is the second most common cause of dementia. The prevalence of vascular dementia (VaD) has increased over the past decade. However, there are no licensed treatments for this disease. Carotid atherosclerosis (CAS) is highly prevalent and is the main cause of ischemic stroke and VaD. We studied co-expressed genes to understand the relationships between CAS and VaD and further reveal the potential biomarkers and therapeutic targets of CAS and VaD.MethodsCAS and VaD differentially expressed genes (DEGs) were identified through bioinformatic analysis Gene Expression Omnibus (GEO) datasets GSE43292 and GSE122063, respectively. Furthermore, a variety of target prediction methods and network analysis approaches were used to assess the protein-protein interaction (PPI) networks, the Gene Ontology (GO) terms, and the pathway enrichment for DEGs, and the top 7 hub genes, coupled with corresponding predicted miRNAs involved in CAS and VaD, were assessed as well.ResultA total of 60 upregulated DEGs and 159 downregulated DEGs were identified, of which the top 7 hub genes with a high degree of connectivity were selected. Overexpression of these hub genes was associated with CAS and VaD. Finally, the top 7 hub genes were coupled with corresponding predicted miRNAs. hsa-miR-567 and hsa-miR-4652-5p may be significantly associated with CAS and VaD.
| S-EPMC9872033 | biostudies-literature
Project description:SBML and SBGN-ML models of atherosclerosis and atheroma formation.
This model is described in the publication: New models of atherosclerosis and multi-drug therapeutic interventions.
Andrew Parton, Victoria McGilligan, Melody Chemaly, Maurice O’Kane, Steven Watterson
Bioinformatics, bty980, https://doi.org/10.1093/bioinformatics/bty980
Motivation. Atherosclerosis is amongst the leading causes of death globally. However, it is challenging to study in vivo or in vitro and no detailed, openly-available computational models exist. Clinical studies hint that pharmaceutical therapy may be possible. Here we develop the first detailed, computational model of atherosclerosis and use it to develop multi-drug therapeutic hypotheses.
Results. We assembled a network describing atheroma development from the literature. Maps and mathematical models were produced using the Systems Biology Graphical Notation (SBGN) and Systems Biology Markup Language (SBML), respectively. The model was constrained against clinical and laboratory data. We identified five drugs that together potentially reverse advanced atheroma formation.
Availability and Implementation. The map is available in the supplementary information in SBGN-ML format. The model is available in the supplementary material and from BioModels, a repository of SBML models, containing CellDesigner markup.
2019-05-20 | MODEL1812100001 | BioModels
Project description:SBML and SBGN-ML models of atherosclerosis and atheroma formation.
This model is described in the publication: New models of atherosclerosis and multi-drug therapeutic interventions.
Andrew Parton, Victoria McGilligan, Melody Chemaly, Maurice O’Kane, Steven Watterson
Bioinformatics, bty980, https://doi.org/10.1093/bioinformatics/bty980
Motivation. Atherosclerosis is amongst the leading causes of death globally. However, it is challenging to study in vivo or in vitro and no detailed, openly-available computational models exist. Clinical studies hint that pharmaceutical therapy may be possible. Here we develop the first detailed, computational model of atherosclerosis and use it to develop multi-drug therapeutic hypotheses.
Results. We assembled a network describing atheroma development from the literature. Maps and mathematical models were produced using the Systems Biology Graphical Notation (SBGN) and Systems Biology Markup Language (SBML), respectively. The model was constrained against clinical and laboratory data. We identified five drugs that together potentially reverse advanced atheroma formation.
Availability and Implementation. The map is available in the supplementary information in SBGN-ML format. The model is available in the supplementary material and from BioModels, a repository of SBML models, containing CellDesigner markup.
2019-05-20 | MODEL1812100001 | BioModels