Chinese Journal of Tissue Engineering Research ›› 2024, Vol. 28 ›› Issue (32): 5122-5129.doi: 10.12307/2024.510
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Chen Guanting1, Zhang Linqi2, Wang Xixi2, Chen Xu2
Received:
2023-03-29
Accepted:
2023-10-10
Online:
2024-11-18
Published:
2023-12-28
Contact:
Zhang Linqi, Professor, Chief physician, Doctoral supervisor, The First Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou 450003, Henan Province, China
About author:
Chen Guanting, MD candidate, The First Clinical Medical College of Henan University of Chinese Medicine, Zhengzhou 450003, Henan Province, China
Supported by:
CLC Number:
Chen Guanting, Zhang Linqi, Wang Xixi, Chen Xu. Autophagy, ferroptosis-related targets and renal function progression in patients with chronic kidney disease: bioinformatics analysis and experimental verification[J]. Chinese Journal of Tissue Engineering Research, 2024, 28(32): 5122-5129.
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2.2 富集分析结果 实验通过仙桃学术、Metascape、WebGestalt数据库对铁死亡及自噬相关差异基因进行富集分析,GO-BP表明,铁死亡相关差异基因主要涉及对生物体内内肽酶活性、激素水平、能量代谢过程以及ERK1/2级联信号通路的调控,自噬相关差异基因主要涉及生物体内细胞形态、代谢过程及对刺激的响应等方面的调控;GO-CC方面,铁死亡相关差异基因主要涉及施拉弗纤维CA1突触、基于肌动蛋白的细胞突触、细胞外空间及囊泡等,自噬相关差异基因主要涉及生物膜、内膜系统、微体腔室、波尔体基质;GO-MF方面,铁死亡相关差异基因主要涉及蛋白质结合、离子结合、免疫受体活性、电子转移活性,自噬相关差异基因主要涉及氧化还原酶活性、外肽酶活性、蛋白质结合、离子结合等;Wiki,Reactome及KEGG等富集结果表明,铁死亡相关差异基因主要涉及硫氨基酸代谢、血小板胞浆Ca2+升高及中性粒细胞脱粒等生物学过程及铁死亡信号通路,与细胞代谢、免疫响应、细胞生存和细胞死亡等多个方面息息相关;自噬相关差异基因主要富集于血小板脱颗粒、RAC3 GTP酶循环、细胞外基质降解、中性粒细胞脱颗粒以及受体酪氨酸激酶的信号传导,这些过程可能在免疫反应、细胞迁移、组织修复和炎症等生理和病理情况中扮演重要角色。结果如图2,3所示。"
2.3 蛋白互作网络构建 将铁死亡及自噬相关差异基因导入STRING 11.5数据库进行分析,获取PPI网络信息并导入Cytoscape 3.9.1软件进行可视化分析;运用分子复合物检测(molecular complex detection,MCODE)及CytoHubba筛选PPI网络中关键基因,其中MCODE插件旨在庞大的网络中根据节点与边的关系,使用定点加权(Vertex-Weighting)方案发现网络中局部高密度区域并寻找出关键的子网络和基因;CytoHubba插件则是根据节点在网络中的属性进行排名,共有11种拓扑方法,其中以最大集团中心性(maximal clique centrality,MCC)算法精准度最高,结果显示二者高度相似,选取其交集为该实验的潜在核心靶点,其中自噬相关靶点为簇分化抗原44(cluster of differentiation 44,CD44)、白蛋白(albumin,ALB)、纤溶酶原(plasminogen,PLG)、CC类趋化因子配体2(chemokine C-C motif ligand 2,CCL2),铁死亡相关靶点为基质金属蛋白酶抑制剂1(tissue Inhibitor of metalloproteinases 1,TIMP1)、二肽基肽酶4(dipeptidyl peptidase-4,DPP4),结果如图4所示。"
2.4 免疫浸润分析结果 实验根据Timer 2.0数据库中Cibersort算法[12],对不同组别人群的肾组织进行组间免疫浸润细胞相对比例差异分析,并通过WPS CORREL函数计算差异表达细胞与核心靶点之间的相关性。结果如图5所示,队列1两组患者肾组织中休息状态髓样树突细胞(Myeloid dendritic cell resting)具有显著差异性(P < 0.05),其核心靶点CD44,TIMP1,CCL2与其呈中等正相关,ALB与其呈中等负相关;队列2两组患者肾组织中记忆休息状态CD4+记忆性T细胞(T cell CD4+ memory resting),休息状态自然杀伤细胞(NK cell resting),激活状态自然杀伤细胞(NK cell activated),单核细胞(Monocyte)具有显著差异性(P < 0.05),其核心靶点CD44,TIMP1与休息状态自然杀伤细胞呈强正相关,CD44,TIMP1,CCL2与激活状态自然杀伤细胞呈强负相关,DPP4与激活状态自然杀伤细胞呈强正相关。"
2.6 潜在核心靶点与肾损伤严重程度的相关性 将该实验获取潜在核心靶点分别与队列1中位随访期60个月eGFR进展及队列2患者eGFR及肾小管间质纤维化(renal tubulointerstitial fibrosis,TIF)程度做相关性分析,结果见表4。相关性分析显示,在队列1中CD44,TIMP1,CCL2与eGFR进展呈正相关(P < 0.05),ALB,PLG,DPP4与其呈负相关(P < 0.05);队列2中ALB,PLG,DPP4与eGFR呈正相关(P < 0.05),与TIF呈负相关(P < 0.05),CD44,TIMP1,CCL2与eGFR呈负相关(P < 0.05),与TIF呈正相关(P < 0.05)。"
2.7 核心靶点预测慢性肾病患者肾功能进展的效能 通过对GSE137570数据集中核心靶点进行ROC曲线分析,结果如图6所示,CD44,ALB,TIMP1,PLG,CCL2及DPP4可较好地预测肾功能进展,在队列1中,CD44,ALB,TIMP1,PLG,CCL2及DPP4 AUC值分别为0.844(95%CI:0.679-1.000)、0.773(95%CI:0.569-0.977)、0.75(95%CI:0.543-0.957)、0.945(95%CI:0.855-1.000)、0.836(95%CI:0.657-1.000)、0.852(95%CI:0.680-1.000);在队列2中,其AUC值分别为0.944(95%CI:0.827-1.000)、0.750(95%CI:0.482-1.000)、0.931(95%CI:0.788-1.000)、0.750(95%CI:0.495-1.000)、0.733(95%CI:0.568-0.878)、0.639(95%CI:0.827-1.000)。"
2.8 单细胞测序验证结果 实验利用Single Cell Portal数据库对实验所筛选潜在核心靶点进行单细胞测序分析,如图7所示,与对照组小鼠相比,抗肾小球基底膜肾炎小鼠模型及阿霉素肾病小鼠模型肾组织中CD44,TIMP1,CCL2表达量显著升高,ALB,DPP4表达显著降低,PLG无显著变化;糖尿病肾病小鼠模型肾组织中CCL2表达量显著升高,ALB,DPP4表达显著降低,CD44,TIMP1,PLG无显著变化;CD2关联蛋白敲除小鼠模型肾组织中CD44,ALB,CCL2,DPP4表达显著降低,TIMP1表达量显著升高,PLG无显著变化。除PLG外,各模型组小鼠肾组织靶点基因表达与该实验结果基本一致。"
2.9 流式细胞术检测结果 MitoSOX red及Mito-Tracker Deep Red FM是一种荧光染色探针,具有线粒体特异性,主要定位于线粒体内。MitoSOX red与线粒体内产生的活性氧发生反应,一般情况下,MitoSOX red荧光强度与活性氧的表达量呈正相关关系,即活性氧水平升高,MitoSOX的荧光强度也会增加;Mito-Tracker Deep Red FM因其本身具有正电荷,这个正电荷使得Mito-Tracker Deep Red FM在细胞外部的负电势区域更容易进入细胞内,而在细胞内具有负电荷的线粒体内膜更容易吸引和累积Mito-Tracker Deep Red FM,这个积累是与线粒体膜电位的高低成正比的,因此,当线粒体膜电位较高时,Mito-Tracker Deep Red FM分子在线粒体内膜上的积累也相对较高。结果如图8,9所示,与空白组比较,模型组TCMK1细胞内活性氧荧光强度显著增加(P < 0.05),线粒体膜电位显著降低(P < 0.05)。"
2.10 RT-PCR检测结果 对于自噬及铁死亡表型的验证,结果如图10A所示,与空白组比较,模型组中微管相关蛋白1轻链3(microtubule-associated protein1light chain3,LC3B)、核因子E2相关因子2(nuclear factor erythroid 2-related factor 2,Nrf2)、系统Xc-蛋白(solute carrier family 7 member 11,SLC7A11)mRNA表达显著降低(P < 0.05),螯合体1(sequestosome 1,SQSTM1/P62)mRNA表达显著增高(P < 0.05),Bcl-2同源结构域蛋白1(Beclin-1)及谷胱甘肽过氧化物酶4(glutathione peroxidase 4,GPX4)mRNA表达有所降低,但无显著性;潜在核心靶点验证方面,结果如图10B所示,与空白组比较,模型组中ALB,PLG mRNA表达显著降低(P < 0.05),TIMP1,CCL2 mRNA表达显著升高(P < 0.05),CD44 mRNA表达有所升高,但无显著性。DPP4未检出。"
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