摘要目的:分析高糖诱导的BV2小胶质细胞基因表达水平和信号通路改变，初步探讨转胶蛋白-2 (TAGLN2）调控细胞炎症反应和代谢进程的机制。方法:基础研究。BV2细胞分为甘露醇（Man）组、葡萄糖（Glu）组、过表达对照（Con）Glu组、过表达TAGLN2 Glu组、沉默Con Glu （shCon Glu）组、沉默TAGLN2 Glu （shTAGLN2 Glu）组。Man组细胞置于含25 mmol/L Man、25 mmol/L Glu的改良Eagle培养基（DMEM培养基）中培养；Glu组、Con Glu组、TAGLN2 Glu组、shCon Glu组、shTAGLN2 Glu组细胞置于含50 mmol/L葡萄糖的DMEM培养基中培养。培养24 h后，采用高通量测序技术对各组细胞进行转录组测序，筛选显著差异表达基因（DEG）。DEG筛选标准为|log 2（差异表达倍数）|≥1且 P≤0.05。对筛选得到的DEG进行基因注释（GO）功能富集分析、京都基因与基因组百科全书（KEGG）的信号通路富集分析和蛋白-蛋白互作网络分析。采用实时聚合酶链反应（RT-PCR）检测DEG mRNA相对表达量。组间数据比较采用独立样本 t检验。 结果:与Man组比较，Glu组共筛选出517个DEG，其中上调、下调基因分别为277、240个。KEGG通路分析结果显示，上调的DEG显著富集在核因子（NF）-κB和Jak-信号转导和转录激活因子（STAT）信号通路等免疫系统进程；下调的DEG显著富集在糖胺多聚糖的降解和甘油酯等代谢进程。与Con Glu组比较，TAGLN2 Glu组共筛选出480个DEG，其中上调、下调基因分别为147、333个。上调的DEG显著富集在脂肪酸、甘油脂和丙酮酸等代谢进程；下调的DEG显著富集在NF-κB、Jak-STAT和肿瘤坏死因子（TNF）信号通路等免疫系统进程。与shCon Glu组比较，shTAGLN2 Glu组共筛选出582个DEG，其中上调、下调基因分别为423、159个。上调的DEG显著富集在TNF、趋化因子信号通路等免疫系统进程；下调的DEG基因主要富集在模式识别受体信号通路。RT-PCR检测结果显示，与Con Glu组比较，TAGLN2 Glu组细胞中Card11 （ t= 13.530）、Icos （ t=3.482）、Chst3 （ t=6.949）、Kynu （ t=5.399 ）、白细胞介素（IL）-1β （ t=2.960）、TNF-α（ t=5.800）、IL-6 （ t=3.130）、干扰素-γ （ t=7.690）、IL-17 （ t=6.530）mRNA相对表达量显著下降，差异有统计学意义（ P<0.05 ）。 结论:TAGLN2可能通过NF-κB和Jak-STAT信号通路抑制高糖诱导的小胶质细胞炎症反应；Card11、Icos、Chst3、Kynu在TAGLN2抗炎过程中可能发挥了重要作用。

abstractsObjective:To analyze the change of differential genes and signaling pathways in high glucose induced BV2 cells, and to explore the mechanism of transgelin-2 (TAGLN2) regulating cellular inflammatory response and metabolic process.Methods:An experimental study. The cultured BV2 cells were divided into mannitol treatment (Man) group, glucose treatment (Glu) group, overexpression control Glu treatment (Con) group, overexpression TAGLN2 Glu treatment group, silence control Glu treatment (shCon Glu) group, and silence TAGLN2 Glu treatment (shTAGLN2 Glu) group. Cells in the Man group were cultured in modified Eagle high glucose medium (DMEM) containing 25 mmol/L mannitol and 25 mmol/L glucose, cells in other groups (Glu group, Con Glu group, TAGLN2 Glu group, shCon Glu group and shTAGLN2 Glu group) were cultured in DMEM medium containing 50 mmol/L glucose. After 24 hours of cells culture, transcriptome sequencing of cells in each group were performed using high-throughput sequencing technology, and significantly differentially expressed genes (DEG) were screened. |log 2 (fold change)|≥1 and P≤0.05 were adopted as criteria to screen for DEG. Gene Ontology (GO) function enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and protein-protein interaction network analysis were performed. Real-time polymerase chain reaction (RT-PCR) was used to detect the relative expression level of DEG mRNA. The data between groups were compared by independent sample t-test. Results:When compared with Man group, a total of 517 differentially expressed genes were screened in Glu group, which including 277 up-regulated genes and 240 down-regulated genes. KEGG pathway enrichment analysis showed that the up-regulated genes were significantly enriched in immune system processes such as nuclear factor (NF)-κB signal pathway, Jak-signal transducers and activators of transcription (STAT) signal pathway, while down-regulated genes were significantly enriched in glycosaminoglycan degradation and glyceride metabolic pathway. Compared with Con Glu group, a total of 480 DEG were screened in TAGLN2 Glu group, among which 147 up-regulated and 333 down-regulated genes were detected. Up-regulated genes were significantly enriched in the metabolic processes of fatty acid, glyceride and pyruvate, while down-regulated genes were significantly enriched in immune system processes such as NF-κB signal pathway, Jak-STAT signal pathway and tumor necrosis factor (TNF) signal pathway. Compared with shCon Glu group, a total of 582 DEG were screened in shTAGLN2 Glu group, among which 423 up-regulated and 159 down-regulated genes were detected. Up-regulated DEG were significantly enriched in immune system processes such as TNF signal pathway and chemokine signal pathway, while down-regulated DEG were significantly enriched in pattern recognition receptor signal pathway. RT-PCR results showed that the relative expression levels of DEG mRNA Card11 ( t=13.530), Icos ( t=3.482), Chst3 ( t=6.949), Kynu ( t=5.399), interleukin (IL)-1β ( t=2.960), TNF-α ( t=5.800), IL-6 ( t=3.130), interferon-γ ( t=7.690) and IL-17 ( t=6.530) in the TAGLN2 Glu treatment group were decreased significantly compared with Con Glu group, and the difference was statistically significant. Conclusion:TAGLN2 can inhibit glucose induced microglia inflammation by NF-κB and Jak-STAT signaling pathways, Card11, Icos, Chst3 and Kynu play an important role in the anti-inflammatory process of TAGLN2.