Department of Anesthesiology, Shenzhen Hospital of Southern Medical University, Shenzhen 518110, China.
Department of Anesthesiology, The Third Affiliated Hospital of Southern Medical University, Guangzhou 510630, China.
Acta Biochim Biophys Sin (Shanghai). 2021 Mar 2;53(3):342-353. doi: 10.1093/abbs/gmab003.
Acute lung injury (ALI) is an inflammatory pulmonary disease that can easily develop into serious acute respiratory distress syndrome, which has high morbidity and mortality. However, the molecular mechanism of ALI remains unclear, and few molecular biomarkers for diagnosis and treatment have been identified. In this study, we aimed to identify novel molecular biomarkers using a bioinformatics approach. Gene expression data were obtained from the Gene Expression Omnibus database, co-expressed differentially expressed genes (CoDEGs) were identified using R software, and further functional enrichment analyses were conducted using the online tool Database for Annotation, Visualization, and Integrated Discovery. A protein-protein interaction network was established using the STRING database and Cytoscape software. Lipopolysaccharide (LPS)-induced ALI mouse model was constructed and verified. The hub genes were screened and validated in vivo. The transcription factors (TFs) and miRNAs associated with the hub genes were predicted using the NetworkAnalyst database. In total, 71 CoDEGs were screened and found to be mainly involved in the cytokine-cytokine receptor interactions, and the tumor necrosis factor and malaria signaling pathways. Animal experiments showed that the lung injury score, bronchoalveolar lavage fluid protein concentration, and wet-to-dry weight ratio were higher in the LPS group than those in the control group. Real-time polymerase chain reaction analysis indicated that most of the hub genes such as colony-stimulating factor 2 (Csf2) were overexpressed in the LPS group. A total of 20 TFs including nuclear respiratory factor 1 (NRF1) and two miRNAs were predicted to be regulators of the hub genes. In summary, Csf2 may serve as a novel diagnostic and therapeutic target for ALI. NRF1 and mmu-mir-122-5p may be key regulators in the development of ALI.
急性肺损伤（ALI）是一种炎症性肺病，容易发展为严重的急性呼吸窘迫综合征，其发病率和死亡率均较高。然而，ALI 的分子机制尚不清楚，也尚未确定用于诊断和治疗的分子生物标志物。在本研究中，我们旨在采用生物信息学方法鉴定新的分子生物标志物。从基因表达综合数据库中获取基因表达数据，使用 R 软件鉴定共表达差异表达基因（CoDEGs），并使用在线工具数据库进行进一步的功能富集分析，用于注释、可视化和综合发现。使用 STRING 数据库和 Cytoscape 软件构建蛋白质-蛋白质相互作用网络。构建脂多糖（LPS）诱导的 ALI 小鼠模型并进行验证。筛选和验证体内的枢纽基因。使用 NetworkAnalyst 数据库预测与枢纽基因相关的转录因子（TFs）和 microRNA。共筛选出 71 个 CoDEGs，主要涉及细胞因子-细胞因子受体相互作用、肿瘤坏死因子和疟疾信号通路。动物实验表明，LPS 组的肺损伤评分、支气管肺泡灌洗液蛋白浓度和湿重/干重比值均高于对照组。实时聚合酶链反应分析表明，LPS 组中大多数枢纽基因（如集落刺激因子 2（Csf2））均过度表达。共预测到包括核呼吸因子 1（NRF1）在内的 20 个 TFs 和两个 miRNAs 作为枢纽基因的调节剂。综上所述，Csf2 可能成为 ALI 的一种新的诊断和治疗靶点。NRF1 和 mmu-mir-122-5p 可能是 ALI 发展的关键调节因子。
