{"title":"Single-cell transcriptome sequencing revealed the metabolic changes and microenvironment changes of cardiomyocytes induced by diabetes","authors":"Weiyu Zhou, Haiqiao Yu, Shuang Yan","doi":"10.1016/j.compbiolchem.2024.108136","DOIUrl":null,"url":null,"abstract":"<div><h3>Purpose</h3><p>Diabetes is a chronic metabolic disorder characterized by elevated blood glucose levels. This study aimed to analyze the changes underlying heterogeneities and communication properties of CMs in diabetes mellitus (DM).</p></div><div><h3>Methods</h3><p>GSE213337 dataset was retrieved from NCBI Gene Expression Omnibus, containing the single-cell RNA sequencing data of hearts from the control and streptozotocin-induced diabetic mice. GSEA and GSVA were used to explore the function enrichment of DEGs in CM. Cell communication analysis was carried out to study the altered signals and significant ligand-receptor interactions.</p></div><div><h3>Results</h3><p>Seventeen cell types were identified between DM and the controls. The increasing ratio of CM suggested the occurrence of diabetes induces potential pathological changes of CM proliferation. A total of 1144 DEGs were identified in CM. GSEA and GSVA analysis indicated the enhancing lipid metabolism involving in DM. The results of cell communication analysis suggested that high glucose activated the ability of CM receiving fibroblast and LEC, while inhibited the capacity of receiving ECC and pericyte. Furthermore, GAS and ANGPTL were significantly decreased under DM, which was consistent with the results of GSEA and GSVA. Finally, the ligand-receptor interactions such as vegfc-vegfr2, angptl1 were changes in CM.</p></div><div><h3>Conclusions</h3><p>The CM showed the significant heterogeneities in DM, which played an important role in myocardial fibrosis induce by hyperglycemia.</p></div>","PeriodicalId":10616,"journal":{"name":"Computational Biology and Chemistry","volume":null,"pages":null},"PeriodicalIF":2.6000,"publicationDate":"2024-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computational Biology and Chemistry","FirstCategoryId":"99","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1476927124001245","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Purpose
Diabetes is a chronic metabolic disorder characterized by elevated blood glucose levels. This study aimed to analyze the changes underlying heterogeneities and communication properties of CMs in diabetes mellitus (DM).
Methods
GSE213337 dataset was retrieved from NCBI Gene Expression Omnibus, containing the single-cell RNA sequencing data of hearts from the control and streptozotocin-induced diabetic mice. GSEA and GSVA were used to explore the function enrichment of DEGs in CM. Cell communication analysis was carried out to study the altered signals and significant ligand-receptor interactions.
Results
Seventeen cell types were identified between DM and the controls. The increasing ratio of CM suggested the occurrence of diabetes induces potential pathological changes of CM proliferation. A total of 1144 DEGs were identified in CM. GSEA and GSVA analysis indicated the enhancing lipid metabolism involving in DM. The results of cell communication analysis suggested that high glucose activated the ability of CM receiving fibroblast and LEC, while inhibited the capacity of receiving ECC and pericyte. Furthermore, GAS and ANGPTL were significantly decreased under DM, which was consistent with the results of GSEA and GSVA. Finally, the ligand-receptor interactions such as vegfc-vegfr2, angptl1 were changes in CM.
Conclusions
The CM showed the significant heterogeneities in DM, which played an important role in myocardial fibrosis induce by hyperglycemia.
期刊介绍：
Computational Biology and Chemistry publishes original research papers and review articles in all areas of computational life sciences. High quality research contributions with a major computational component in the areas of nucleic acid and protein sequence research, molecular evolution, molecular genetics (functional genomics and proteomics), theory and practice of either biology-specific or chemical-biology-specific modeling, and structural biology of nucleic acids and proteins are particularly welcome. Exceptionally high quality research work in bioinformatics, systems biology, ecology, computational pharmacology, metabolism, biomedical engineering, epidemiology, and statistical genetics will also be considered.
Given their inherent uncertainty, protein modeling and molecular docking studies should be thoroughly validated. In the absence of experimental results for validation, the use of molecular dynamics simulations along with detailed free energy calculations, for example, should be used as complementary techniques to support the major conclusions. Submissions of premature modeling exercises without additional biological insights will not be considered.
Review articles will generally be commissioned by the editors and should not be submitted to the journal without explicit invitation. However prospective authors are welcome to send a brief (one to three pages) synopsis, which will be evaluated by the editors.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
