[1]王 云,肖 宁,段欢欢.基于GEO数据库筛选金黄色葡萄球菌脓毒症中差异表达的ceRNA及验证[J].现代检验医学杂志,2026,41(03):115-118+125.[doi:10.3969/j.issn.1671-7414.2026.03.021]
　WANG Yun,XIAO Ning,DUAN Huanhuan.Screening and Validation of Differentially Expressed ceRNA in Staphylococcus Aureus Sepsis Based on GEO Database[J].Journal of Modern Laboratory Medicine,2026,41(03):115-118+125.[doi:10.3969/j.issn.1671-7414.2026.03.021]
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基于GEO数据库筛选金黄色葡萄球菌脓毒症中差异表达的ceRNA及验证()

《现代检验医学杂志》[ISSN:/CN:]

卷:
第41卷
期数:
2026年03期
页码:
115-118+125
栏目:
论著
出版日期:
2026-05-13

文章信息/Info

Title:
Screening and Validation of Differentially Expressed ceRNA in Staphylococcus Aureus Sepsis Based on GEO Database
文章编号:
1671-7414（2026）03-115-05
作者:
王 云，肖 宁，段欢欢
邯郸市中心医院，河北邯郸 056001
Author(s):
WANG Yun，XIAO Ning，DUAN Huanhuan
Handan Central Hospital，Hebei Handan 056001，China
关键词:
金黄色葡萄球菌; 脓毒症; 差异表达基因; 生物信息学分析; 竞争性内源RNA; 血流感染
分类号:
R378.11；Q786
DOI:
10.3969/j.issn.1671-7414.2026.03.021
文献标志码:
A
摘要:
目的?基于基因表达综合(GEO)数据库，筛选金黄色葡萄球菌脓毒症的差异表达基因（DGEs），并构建竞争性内源RNA(ceRNA)调控网络，以便深入了解金黄色葡萄球菌脓毒症发病机制。方法在GEO数据库中检索金黄色葡萄球菌血流感染（BSI）基因表达数据集，下载使用GSE33341数据集，筛选金黄色葡萄球菌脓毒症的DGEs，采用京都基因与基因组百科全书(KEGG)对DGEs进行富集分析。基于ceRNA的理论，构建长链非编码RNA（lnRNA）的调控网络。最后，收集2022年1月～2023年12月于邯郸市中心医院治疗的84例脓毒症患者为研究对象，根据是否为金黄色葡萄球菌感染分为金黄色葡萄球菌组(n=42)和对照组(n=42)，提取样本RNA，采用实时荧光定量PCR(qRT-PCR)方法对筛选基因验证。结果获得81个lncRNA，114个miRNA，76个mRNA构建lncRNA-miRNA-mRNA的ceRNA调控网络，最终共获得3个金黄色葡萄球菌相关致病基因，具体为lncRNAX染色体失活特异转录因子（XIST）、核旁斑组装转录本1（NEAT1）和肺腺癌转移相关转录本1（MALAT1）。KEGG富集分析显示差异基因主要通过Th17细胞分化、Th1和Th2细胞分化、T细胞受体信号通路、鞘脂信号通路、逆行内源性大麻素信号、Ras信号通路、磷酸酰肌醇3激酶（PI3K）-蛋白激酶B（Akt）信号通路、氧化磷酸化、自然杀伤（NK）细胞介导的细胞毒性、丝裂原活化蛋白激酶（MAPK）信号通路、叉头框O（FoxO）信号通路、FcεRI信号通路、细胞凋亡生物过程参与金黄色葡萄球菌的感染。qRT-PCR对临床样本中关键基因表达检测显示，相对于对照组，金黄色葡萄球菌组血液中表达上调的基因有lncRNAXIST、lncRNANEAT1和lncRNAMALAT1，差异具有统计学意义（t=11.387、10.444、23.183，均P<0.001）；实验结果与生物信息学分析结果一致。结论通过生物信息学筛选出金黄色葡萄球菌脓毒症关键基因lncRNAXIST、NEAT1和MALAT1，可能成为金黄色葡萄球菌脓毒症诊断和治疗的潜在靶点，为金黄色葡萄球菌脓毒症的临床诊疗提供新的思路。
Abstract:
Objective To screen differentially expressed genes (DGEs) in staphylococcus aureus sepsis and construct a competing endogenous RNA (ceRNA) regulatory network based on the Gene Expression Omnibus (GEO) database, in order to gain deeper insights into the pathogenesis of Staphylococcus aureus sepsis. Methods The gene expression data set of Staphylococcus aureus bloodstream infection (BSI) was retrieved from GEO database, and the differentially expressed genes of Staphylococcus aureus sepsis were screened using GSE33341 dataset. The enrichment analysis on DGEs was performed using the Kyoto Encyclopedia of Genes and Genomes (KEGG). The regulatory network of for long non-coding RNAs (lnRNAs) was constructed based on ceR-NA theory. Finally, 84 patients with sepsis treated in Handan Central Hospital from January 2022 to December 2023 were col-lected as research objects. Patients were divided into a Staphylococcus aureus group (n=42) and a control group (n=42) based on infection status. RNA was extracted from samples, and the selected genes were validated using quantitative real time polymerase chain reaction (qRT-PCR). Results 81 lncRNAs, 114 miRNAs and 76 mRNAs were obtained to construct the ceRNA regulatory network of lncRNA-miRNA-mRNA. Finally, a total of 3 pathogenic genes related to staphylococcus aureus were obtained, spe-cifically lncRNA XIST, NEAT1 and MALAT1. KEGG enrichment analysis showed that the DEGs primarily functioned through Th17 cell differentiation, Th1 and Th2 cell differentiation, T cell receptor signaling, sphingolipid signaling, retrograde endo-cannabinoid signaling, Ras signaling, PI3K-Akt signaling, oxidative phosphorylation, natural killer cell-mediated cytotoxicity, MAPK signaling, FoxO signaling, FCεRI signaling, apoptotic biological processes involved in staphylococcus aureus infection.RT-qPCR detection of key gene expression in clinical samples showed that compared with the control group, the Staphylococcus aureus group exhibited statistically significant upregulation of lncRNA XIST, lncRNA NEAT1, lncRNA MALAT1 in blood sam-ples, the differences were statistically significant (t=11.387, 10.444, 23.183, all P<0.001). The experimental results were consis-tent with bioinformatics analysis findings. Conclusions Bioinformatics screening identified lncRNA XIST, NEAT1 and MALAT1 as key genes in Staphylococcus aureus sepsis. These may serve as potential targets for diagnosis and treatment of Staphylococcus aureus sepsis, offering new insights for clinical management.

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备注/Memo

备注/Memo:
基金项目：河北省中医药管理局科研计划项目（编号：2022660）。
作者简介：王云(1984-)，女，本科，主管护师，研究方向：金黄色葡萄球菌脓毒症，E-mail：wy667712@126.com。
通讯作者：肖宁(1979-)，女，硕士，副主任医师，主要研究方向：金黄色葡萄球菌脓毒症，E-mail：xiaoning2017@126.com。
更新日期/Last Update: 2026-05-15