Anesthesiology, Peking University Cancer Hospital & Institute, Beijing, Beijing, China.
PeerJ. 2022 Sep 13;10:e13983. doi: 10.7717/peerj.13983. eCollection 2022.
BACKGROUND: Sepsis leads to multiple organ dysfunction caused by a dysregulated host response to infection with a high incidence and mortality. The effect of ferroptosis on the development of sepsis remains unclear. In this study, we aimed to identify the key ferroptosis-related genes involved in sepsis and further explore the potential biological functions of these ferroptosis-related genes in sepsis using bioinformatics analysis. METHODS: The GSE13904 (from children) and GSE28750 (from adults) datasets were downloaded from the Gene Expression Omnibus (GEO). The ferroptosis-related genes were obtained from the FerrDb database. The ferroptosis-related differentially expressed genes (DEGs) were screened by the limma R package. The DAVID online database or clusterProfiler R package was used for the functional enrichment analysis. Then, the STRING database was used to predict the interactions of proteins, and the CytoHubba plugin of Cytoscape was used to confirm key clustering modules. Then, the miRNAs and lncRNAs associated with the key clustering modules were predicted by miRWalk 2.0 and LncBase v.2 respectively. Finally, we generated a cecal ligation and puncture (CLP) polymicrobial sepsis model in C57 male mice and examined the expression of the mRNAs and noncoding RNAs of interest in peripheral blood leukocytes by PCR during the acute inflammation phase. RESULTS: In total, 34 ferroptosis-related DEGs were identified in both adult and pediatric septic patients. These ferroptosis-related DEGs were mainly enriched in inflammatory pathways. Then, a significant clustering module containing eight genes was identified. Among them, the following five genes were closely associated with the MAPK signaling pathway: MAPK14, MAPK8, DUSP1, MAP3K5 and MAPK1. Then, crucial miRNAs and lncRNAs associated with biomarker MAPK-related genes were also identified. In particular, let-7b-5p and NEAT1 were selected as noncoding RNAs of interest because of their correlation with ferroptosis in previous studies. Finally, we examined the mRNAs, miRNAs and lncRNAs of interest using CLP-induced sepsis in peripheral blood leukocytes of mice. The results showed that MAPK14, MAPK8, MAP3K5, MAPK1 and NEAT1 were upregulated, while DUSP1 and let-7b-5p were downregulated in the CLP group compared with the sham group. CONCLUSIONS: The MAPK signaling pathway may play a key role in regulating ferroptosis during sepsis. This study provides a valuable resource for future studies investigating the mechanism of MAPK-related ferroptosis in sepsis.
背景：脓毒症导致宿主对感染的反应失调，引起多器官功能障碍，发病率和死亡率均较高。铁死亡对脓毒症发展的影响尚不清楚。本研究旨在通过生物信息学分析，确定与脓毒症相关的关键铁死亡相关基因，并进一步探讨这些铁死亡相关基因在脓毒症中的潜在生物学功能。 方法：从基因表达综合数据库（GEO）中下载 GSE13904（儿童）和 GSE28750（成人）数据集。从 FerrDb 数据库中获取铁死亡相关基因。使用 limma R 包筛选铁死亡相关差异表达基因（DEGs）。使用 DAVID 在线数据库或 clusterProfiler R 包进行功能富集分析。然后，使用 STRING 数据库预测蛋白质相互作用，使用 Cytoscape 的 CytoHubba 插件确认关键聚类模块。然后，分别使用 miRWalk 2.0 和 LncBase v.2 预测与关键聚类模块相关的 miRNAs 和 lncRNAs。最后，我们在 C57 雄性小鼠中建立盲肠结扎穿孔（CLP）多微生物脓毒症模型，并在急性炎症期通过 PCR 检测外周血白细胞中感兴趣的 mRNA 和非编码 RNA 的表达。 结果：总共在成人和儿科脓毒症患者中鉴定出 34 个铁死亡相关 DEG。这些铁死亡相关 DEG 主要富集在炎症途径中。然后，确定了一个包含 8 个基因的显著聚类模块。其中，以下 5 个基因与 MAPK 信号通路密切相关：MAPK14、MAPK8、DUSP1、MAP3K5 和 MAPK1。然后，还鉴定了与生物标志物 MAPK 相关基因相关的关键 miRNAs 和 lncRNAs。特别是，由于先前的研究表明 let-7b-5p 和 NEAT1 与铁死亡有关，因此选择它们作为非编码 RNA 进行研究。最后，我们使用 CLP 诱导的小鼠外周血白细胞中的脓毒症检测了感兴趣的 mRNAs、miRNAs 和 lncRNAs。结果表明，与 sham 组相比，CLP 组 MAPK14、MAPK8、MAP3K5、MAPK1 和 NEAT1 上调，而 DUSP1 和 let-7b-5p 下调。 结论：MAPK 信号通路可能在脓毒症期间调节铁死亡中发挥关键作用。本研究为进一步研究 MAPK 相关铁死亡在脓毒症中的机制提供了有价值的资源。
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