脓毒症相关肠黏膜屏障损伤关键基因和信号通路的转录组学分析
Transcriptomic Analysis of Key Genes and Signaling Pathways in Sepsis-Associated Intestinal Mucosal Barrier Damage
DOI: 10.12677/acm.2024.1451707, PDF, HTML, XML, 下载: 54  浏览: 120 
作者: 高 昭, 高 鹏*:青岛大学附属医院急诊外科,山东 青岛;黄 海:常州市武进人民医院急诊科,江苏 常州
关键词: 脓毒症肠道屏障差异表达基因转录组测序Sepsis Intestinal Barrier Differentially Expressed Genes Transcriptome Sequencing
摘要: 目的:分析脓毒症相关肠黏膜屏障损伤小鼠差异表达基因(DEG),从转录组水平探讨脓毒症相关肠黏膜屏障损伤的早期诊断和保护机制。方法:收集行盲肠结扎穿孔术(CLP)和假手术的健康雄性C57BL/6J小鼠小肠组织,采用illumina Hiseq测序平台的两端测序模式进行高通量测序。对差异表达基因进行基因本体论(GO)和京都基因与基因组百科全书(KEGG)分析。利用STRING数据库构建蛋白–蛋白相互作用(PPI)网络,利用Cytoscape筛选关键基因。采用实时荧光定量聚合酶链反应(RT-qPCR)对Hub基因进行验证。结果:共筛选出239个DEG,其中上调基因49个,下调基因130个。KEGG富集分析发现DEG主要涉及细胞因子–细胞因子受体相互作用、Th1和Th2细胞分化、病毒蛋白与细胞因子和细胞因子受体相互作用、IL-17信号通路等。利用cytoHubba插件筛选出前10个hub基因。经实验验证,TBX21、CSF3、IL-6、CXCR3、CXCL9的表达与测序结果一致。结论:TBX21、CSF3、IL-6、CXCR3和CXCL9可能是脓毒症相关肠黏膜屏障早期诊断和治疗的潜在生物学标志物。
Abstract: Objectives: To analyze the differentially expressed genes (DEG) in mice with sepsis-related intestinal mucosal barrier damage and to explore the early diagnosis and protection mechanism of sepsis-related intestinal mucosal barrier damage at the transcriptome level. Methods: The healthy male C57BL/6J mice small intestinal tissues of Cecal ligation and puncture (CLP) and sham-operation were collected, and the two-end sequencing mode of the illumina Hiseq sequencing platform was commissioned for high-throughput sequencing. Followed by Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of DEGs. A protein-protein interaction (PPI) network was constructed using the STRING database, and hub genes were selected using Cytoscape. Hub genes were verified using quantitative real-time polymerase chain reaction (RT-qPCR). Results: A total of 239 DEG were selected, including 49 up-regulated genes and 130 downregulated genes. KEGG enrichment analysis revealed that DEG mainly involved cytokine-cytokine receptor interaction, Th1 and Th2 cell differentiation, viral protein interaction with cytokine and cytokine receptor, and IL-17 signaling pathway. The cyto Hubba plugin was used to select the top 10 hub genes. After experimental verification, the expression of TBX21, CSF3, IL-6, CXCR3, and CXCL9 was in agreement with the sequencing results. Conclusion: TBX21, CSF3, IL-6, CXCR3, and CXCL9 may be potential biological markers for the early diagnosis and treatment the sepsis-associated intestinal mucosal barrier.
文章引用:高昭, 黄海, 高鹏. 脓毒症相关肠黏膜屏障损伤关键基因和信号通路的转录组学分析[J]. 临床医学进展, 2024, 14(5): 2457-2470. https://doi.org/10.12677/acm.2024.1451707

1. 引言

脓毒症是机体对感染 [1] 反应功能障碍导致危及生命的器官功能障碍。机体失控的感染反应导致全身炎症反应综合征(SIRS),进一步发展为脓毒性休克和多器官功能障碍综合征(MODS) [2] ,具有高度异质性。关于脓毒症的发病机制,早在1986年就有研究提出胃肠道是MODS的发动机——肠源性假说 [3] 。在许多没有明确感染灶的MODS患者中,约30%存在脓毒症 [4] [5] 。肠道是机体的主要消化器官,具有内分泌、免疫等功能 [6] 。同时,肠道也是体内细菌和内毒素的最大储存库,在病理状态下会成为机体重要的感染源 [7] 。肠道屏障是抵御外来病原体的第一道防线。它由机械、化学、生物和免疫屏障组成,在隔离机体内环境与外部病原体方面起着至关重要的作用 [8] 。多种因素可减弱或破坏肠屏障功能,包括急性损伤、肠缺血、再灌注损伤和感染 [9] 。肠屏障功能受损导致肠道通透性增加,肠道中的细菌和毒素可通过受损的肠黏膜屏障迁移到血液中,导致肠源性脓毒症。脓毒症继发的全身炎症反应进一步加重肠屏障功能的损伤,甚至导致脓毒性休克和MODS [10] 。因此,肠道既是脓毒症的“始发者”,也是脓毒症的“受害者”。对肠屏障功能的保护不仅减少了并发症的发生,还改善了重症患者的预后和生存率。因此,防治肠屏障功能障碍是降低脓毒症患者病死率的关键 [11] 。

本研究通过对盲肠结扎造模后的小肠组织进行转录组测序,探索肠黏膜屏障损伤过程中参与变化的关键基因及相关信号通路,以期为脓毒症相关肠黏膜屏障损伤的早期防治提供新思路。

2. 材料与方法

2.1. 动物与分组

采用48只健康雄性C57BL/6J小鼠(北京卫通力华,许可证号:SYXK (北京) 2022-0052),8周龄,体质量20~25 g。所有实验小鼠在实验前1周置于控制温度的笼子中,自由进食和饮水,并适应环境。所有实验均按照美国国立卫生研究院(NIH)发布的指南和青岛大学附属医院相关伦理规定(伦理号:QYFY WZLL 27932)进行。采用随机数字表法将其分为Sham 6 h组、Sham 12 h组、Sham 24 h组、CLP 6 h组、CLP 12 h组和CLP 24 h组,每组5只。

2.2. 盲肠结扎穿孔(CLP)小鼠模型

采用经典CLP模型诱导脓毒症 [12] 。简单地说,禁食12 h后,用3%戊巴比妥钠麻醉小鼠,腹部皮肤消毒,在腹部中线处做1 cm切口,暴露盲肠。结扎盲肠远端极与基底部之间的中段可诱发中度脓毒症。采用21-G穿刺针在结扎部位与盲肠尖端之间进行全盲肠穿刺。从穿刺部位挤出少量粪便。将盲肠放回腹腔,用无菌6-0线固定腹膜、筋膜和腹壁肌肉。术后对皮肤进行消毒。手术组皮下注射生理盐水50 ml/kg;假手术组采用相同的手术方法,但不进行CLP (图1)。

Figure 1. CLP was used to induce intestinal barrier injury in septic mice. (A) Schematic representation of cecal ligation puncture in mice. (B) The 6 h, 12 h and 24 h mouse models of sepsis-associated intestinal barrier injury induced by CLP were established. Sham 6 h (n = 8), Sham 12 h (n = 8), Sham 24 h (n = 8), CLP 6 h (n = 8), CLP 12 h (n = 8), CLP 24 h (n = 8)

图1. 采用CLP诱导脓毒症小鼠肠屏障损伤。(A) 小鼠盲肠结扎穿刺示意图。(B) 建立CLP诱导的脓毒症相关肠屏障损伤6 h、12 h和24 h小鼠模型。假手术6 h (n = 8)、假手术12 h (n = 8)、假手术24 h (n = 8),CLP 6 h (n = 8)、CLP 12 h (n = 8)、CLP 24 h (n = 8)

2.3. 蛋白提取和Western Blotting检测

用冷磷酸盐缓冲液(PBS)洗涤所有细胞,用RIPA缓冲液(RIPA: PMSF: 磷酸酶抑制剂,100:1:1)在冰上切割20分钟。然后在4℃、12,000 rpm、4℃离心20分钟。离心后上清液与5倍样品缓冲液混合,煮沸5 min使蛋白变性。蛋白质在10%十二烷基硫酸钠聚丙烯酰胺凝胶电泳(SDS-PAGE)凝胶上进行电泳,并转移到PVDF膜(Millipore,美国)。一抗在4℃孵育过夜,二抗在室温孵育2 h。使用以下一抗:抗claudin 1抗体(Proteintech, 13050-1-AP, 1:1000稀释度)、抗zo-1抗体(Proteintech, 21773-1-AP, 1:1000稀释度)和抗β-actin抗体(CST, 8457S, 1:500稀释度)。二抗为酶标抗兔IgG (Abcam, ab270144, 1:8000稀释)。用一抗和二抗稀释液(Boster,中国,AR1017)稀释所有抗体。

2.4. 细胞培养

Caco-2细胞购自Prenoxel (Procell, CL-0050),用MEM (Procell, PM150410)培养。加入20% FBS (Procell, 164210)和1% P/S (Procell, PB180120)在37℃ 5% CO2中生长,脂多糖(LPS)购自Solarbio (L8880),用无菌水配制成10 mg/ml溶液,稀释后使用。

2.5. 酶联免疫吸附测定

采用ELISA试剂盒(Boster)检测小鼠血液中IL-1β (Boster, EK0394)和TNF-α (Boster, EK0527)的表达水平。

2.6. RNA提取和定量RT-PCR

使用TransZol Up Plus RNA试剂盒(TransGen,中国)提取细胞总RNA。提取的RNA用Evo M-MLV RT Mix试剂盒(precision Biology, China)逆转录为cDNA。以cDNA为模板,采用LightCycler 96系统和FastStart DNA Master SYBR Green Kit (Roche,德国)检测mRNA转录水平。采用基于SYBR Green的比较Ct法分析靶基因表达与内参基因β-actin表达的关系(相对变化倍数 = 2−ΔΔCt)。

2.7. Hematoxylin-Eosin染色

小肠标本在4%多聚甲醛中固定48 h,然后在不同浓度(70%~100%)的乙醇中脱水40 min。它们被包裹在石蜡中,储存起来以备后续实验。将蜡块切成4毫米的切片,置于二甲苯、无水乙醇和乙醇中,依次脱蜡。小肠标本行苏木精–伊红(HE)染色。细胞苏木精染色5 min,水冲洗,恢复蓝色后,伊红染色1~3 min。光镜(德国徕卡)观察组织学形态。肠损伤程度由不知晓实验的胃肠病理医师按照Chiu等的方法进行评估 [13] 。

2.8. 测序

收集两组小鼠的小肠组织进行真核转录组测序,使用百麦客公司(Bio Marker, China)的Illumina测序平台进行测序。

2.9. 功能和通路富集分析

利用DAVID数据库(https://david.ncifcrf.gov/home/jsp)进行基因本体(GO)功能注释和京都基因与基因组百科全书(KEGG)通路分析。GO功能注释包括分子功能(MF)、生物过程(BP)和细胞成分(CC) 3部分。GO和KEGG富集分析的阈值均为P < 0.05。使用在线数据分析和可视化平台https://www.bioinformatics.com.cn绘制图表。

2.10. 构建PPI网络并筛选关键基因

将DEGs导入STRING数据库(https://string-db.org/),选取置信水平 > 0.4进行PPI网络分析,构建可视化蛋白质相互作用网络(PPI)。将PPI网络数据文件导入Cytoscape (V3.9.1)软件,利用其插件cytoHubba中的Degree算法计算前10位hub基因。

2.11. 构建mRNA-miRNA网络

miRDB(http://www.mirdb.org/mirdb/index.html)是一个在线的miRNA靶点预测数据库,可以预测潜在的miRNA靶点枢纽基因。将得到的miRNA-mRNA靶向关系导入Cytoscape (V3.9.1)软件绘制mRNA-miRNA网络。

2.12. 统计分析

数据以均数 ± 标准差表示。使用GraphPad Prism 8 (GraphPad, La Jolla, CA,USA)进行统计分析。两组间正态数据比较采用非配对t检验。统计参数均在图中说明,所有实验至少重复3次。

3. 结果

3.1. 模型构建与验证

为研究CLP与肠屏障损伤的相关性,分别于CLP术后6 h、12 h和24 h抽取小鼠静脉血和小肠组织。与sham组比较,CLP组IL-1β和TNF-α浓度在12 h达峰值(P < 0.0001) (图2(A)~(B))。Western blotting结果显示,CLP 24 h组肠道屏障蛋白ZO-1和Claudin 1表达最低(P < 0.001) (图2(C)~(E))。CLP术后24 h, Sham 6 h、Sham 12 h和Sham 24 h组小鼠小肠结构正常,镜下(200×)小肠上皮细胞排列正常,无水肿和炎性细

Figure 2. CLP induces intestinal barrier damage in sepsis. (A)~(B) The levels of TNF-α and IL-1β in plasma were determined by ELISA in a mouse model (n = 8 in each group). (C)~(E) Expression of tight junction protein claudin-1 and ZO-1 was measured by Western blotting. (F)~(G) H & E staining of intestinal tissue sections (200×) and pathological scores. *P< 0.05, **P< 0.01, ***P < 0.001, and ****P < 0.0001

图2. CLP可导致脓毒症时肠屏障损伤。(A)~(B) ELISA法检测血浆中TNF-α和il-1β水平(每组8只)。(C)~(E) 采用Western blot法检测紧密连接蛋白claudin-1和ZO-1的表达。(F)~(G) 肠组织切片he染色(200×)并进行病理评分。*P < 0.05,**P < 0.01,***P < 0.001,****P < 0.0001

胞浸润,绒毛完整、丰富;CLP组大鼠小肠上皮紧密连接消失,局部炎性细胞浸润,绒毛水肿、断裂较多,绒毛完整性消失,小肠Chiu’s评分明显升高(P < 0.0001) (图2(F)~(G))。因此,CLP 24 h肠屏障损伤可能最为严重。因此,分别于盲肠结扎后24 h和假手术后24 h收集小鼠小肠组织进行转录组测序。

3.2. 差异基因的筛选

首先,我们对基因表达矩阵进行了PCA、UMAP和tSNE降维聚类分析(图3)。CLP组的样本与Sham组明显分离。随后,我们使用limma包对基因表达谱进行差异分析,以确定Sham组和CLP组之间的差异表达基因(图4图5)。与Sham组比较,CLP组共鉴定出239个DEGs,其中49个基因表达上调,190个基因表达下调。

(A) (B) (C)

Figure 3. (A) PCA analysis plot of gene expression matrix; (B) UMAP analysis plot of gene expression matrix; (C) tSNE analysis plot of gene expression matrix

图3. (A) 基因表达矩阵PCA分析图;(B) 基因表达矩阵的UMAP分析图;(C) 基因表达矩阵的tSNE分析图

Figure 4. Volcano plot of the DEGs

图4. DEGs的火山图

Figure 5. Heat map of the DEGs

图5. DEGs的热图

3.3. 差异表达基因的功能富集和通路分析

为了进一步研究DEGs在黏膜屏障损伤中的分子作用,对这些基因进行GO富集分析,并根据其功能进行分类。结果分为3类:在生物学过程方面,这些基因主要富集在正向T细胞选择、趋化因子介导的信号通路、T细胞活化和T细胞选择。在分子功能方面,这些基因在受体配体活性、CXCR趋化因子受体结合和信号受体激活活性方面尤为丰富。在细胞组分模块中,这些基因参与了质膜外侧面、含胶原的细胞外基质和免疫突触(图6(A))。基于KEGG数据库对这些基因进行通路分析发现,上述基因与细胞因子-细胞因子受体相互作用、Th1和Th2细胞分化、病毒蛋白与细胞因子和细胞因子受体相互作用、IL-17信号通路等密切相关(图6(B))。

(A)(B)

Figure 6. (A) GO analysis of up-regulated genes; (B) KEGG analysis of up-regulated genes

图6. (A) 上调基因的GO分析;(B) 上调基因的KEGG分析

3.4. 构建PPI网络并筛选关键基因

将DEGs导入Cytoscape软件,使用内置String App构建PPI网络。将PPI网络数据文件导入Cytoscape软件,使用cytoHubba插件计算排名前10位的hub基因:CXCL9、CXCR3、PRF1、GZMB、CD27、CD3D、CD2、CSF3、TBX21和IL6 (图7)。

Figure 7. The network of top 10 hub genes from the PPI network

图7. PPI网络中排名前10位的hub基因的网络

3.5. 构建miRNA-mRNA网络

利用miRDB数据库预测潜在的mirna靶基因。将预测结果导入Cytoscape软件,绘制miRNA-mRNA网络(图8)。我们发现靶向多个hub基因的mirna同时存在,靶向CXCL9的mirna数量最多,共19个潜在mirna;未发现与CD3D相关的miRNA。

Figure 8. The network of miRNA-mRNA. The red ellipse represents the hub genes, the green diamond represents the hsa-miRNA

图8. miRNA-mRNA网络。红色椭圆代表核心基因,绿色菱形代表hsa-miRNA

3.6. qRT-PCR验证

为进一步验证测序结果,采用LPS诱导Caco-2细胞肠上皮屏障功能障碍,通过qRT-PCR检测TNF-α和IL-6 mRNA验证炎症模型。TBX 21、CSF3、IL-6、CXCR3和CXCL9的表达差异与测序结果一致(图9)。未检测到CD2的表达,有几个基因的表达与测序结果不一致。

Figure 9. The differential gene expression was verified in caco-2 cells. (A) The levels of inflammatory cytokines in Caco-2 cells, including TNF-α and IL-6, were measured by qPCR; (B) The levels of differentially expressed genes in Caco-2 cells, including PRF-1, CD3D, TBX21, CD27, CSF3, GZMB, CD2, IL-6, CXCR3 and CXCL9, were measured by qPCR.Data were represented as the mean ± standard deviation. *P < 0.05, **P < 0.01 and ***P < 0.001

图9. 在caco-2细胞中验证差异基因表达。(A) qPCR检测Caco-2细胞中炎症因子TNF-α和IL-6的水平;(B) 通过qPCR检测Caco-2细胞中差异表达基因PRF-1、CD3D、TBX21、CD27、CSF3、GZMB、CD2、IL-6、CXCR3和CXCL9的表达水平。数据以均数 ± 标准差表示。*P < 0.05,**P < 0.01,***P < 0.001

4. 讨论

肠道屏障作为机体抵御外来病原体的主要屏障,在将机体内环境与潜在的入侵者隔离开来方面起着至关重要的作用 [14] 。急性损伤、肠缺血再灌注损伤、感染、饥饿或禁食、长期肠外营养、抗肿瘤药物的使用、免疫抑制化疗或放疗等多种因素均可损害或损害的功能 [15] 。因此,这些因素导致肠道屏障功能受损和肠道通透性增加。这种受损状态使肠道内的细菌和毒素通过受损黏膜屏障的缺口转移到血流中,最终导致肠源性脓毒症。同时,继发于脓毒症的全身炎症反应进一步加重肠屏障功能受损,甚至可能导致脓毒性休克和多器官功能障碍综合征(MODS) [16] 。

首先,基于转录组测序的结果,我们使用limma包筛选了CLP组和sham组的DEGs,从中我们发现了两组之间的许多DEGs。然后,我们对DEGs进行GO和KEGG分析。KEGG分析结果显示,差异表达基因与细胞因子–细胞因子受体相互作用、Th1和Th2细胞分化、病毒蛋白与细胞因子和细胞因子受体相互作用、IL-17信号通路等信号通路显著相关。在临床实践中发现,危重型COVID-19患者表现出典型的脓毒症相关临床表现,包括多器官功能障碍综合征、凝血病、脓毒性休克等,并且已证实重症COVID-19有许多与脓毒症反应密切相关的通路,如细胞因子–细胞因子受体相互作用通路、细胞因子风暴、血液平衡破坏后的高凝状态、中性粒细胞功能障碍等 [17] 。众所周知,脓毒症患者通常存在免疫抑制,表现为原发感染无法根除,易继发医院感染,迟发型超敏反应减弱 [18] 。动物实验表明,脓毒症时脾脏、淋巴结和骨髓中GR-1 cd11b细胞数量抑制CD8+ T细胞产生IFN-γ,导致向Th1向th2极化 [19] 。在大量的临床实验中,Th1/Th2比值与脓毒症、脓毒症器官损伤及脓毒症病死率有一定的预测价值 [20] 。相应的,脓毒症中CD8+T细胞的耗竭导致对继发感染的易感性,以及慢性淋巴细胞脉络丛脑膜炎病毒(LCMV)感染中原发性ag特异性CD8+T细胞应答的近远期效应表明,脓毒症增加了对慢性病毒感染的易感性,并加速了CD8 T细胞耗竭的途径 [21] [22] 。IL-17可由多种细胞群产生,包括Th 17细胞、γδ T细胞、NKT细胞、3型固有淋巴样细胞(ILC 3s)、CD8 (Tc 17)细胞、中性粒细胞、小胶质细胞和肥大细胞,主要促进黏膜组织的炎症反应,是多发伤患者发生脓毒症和死亡的预测因子 [23] 。IL-17A是研究最多的IL-17家族成员,它与各种介质(如GM-CSF、IFN-γ、IL-22、IL-1β、TNF-α)相互作用,发挥其促炎作用,以及IL-17A介导的下游通路,诱导炎症分子、趋化因子、抗菌肽(AMP)和重塑蛋白 [24] 。IL-17A在宿主防御、细胞运输、免疫调节和组织修复中发挥关键作用,在诱导固有免疫防御中发挥关键作用;其基因突变与革兰阳性菌感染的易感性增加和严重脓毒症的死亡率增加相关 [25] 。白细胞介素17受体E (Interleukin 17 receptor E, IL-17RE)是IL-17特有的孤儿受体,在宿主黏膜抵抗感染中发挥重要作用 [26] 。IL-17A介导的病理反应通过抑制肠上皮细胞增殖和诱导细胞凋亡,破坏肠上皮屏障功能,增加肠通透性,引起肠道细菌移位 [27] 。中和IL-17保护了脓毒症小鼠模型肠道屏障的完整性,减少了系统性炎症和细菌播散,并降低了死亡率 [28] 。

此外,我们利用Cytoscape中的cytoHubba插件计算出前10个枢纽基因。CLP组仅IL6表达上调,CXCL9、CXCR3、PRF1、GZMB、CD27、CD3D、CD2、CSF3、TBX21表达下调。qRT-PCR实验验证,TBX21、CSF3、IL-6、CXCR3、CXCL9的表达变化与测序结果一致。

众所周知,脓毒症早期免疫系统的过度激活和大量免疫因子的耗竭导致了脓毒症后期的免疫抑制。在脓毒症后期,T细胞和NK细胞数量减少或凋亡增加,INF-γ产生减少,可导致继发感染甚至死亡 [29] 。NK细胞通过直接分泌穿孔素和颗粒酶破坏细菌细胞壁的完整性,参与NK细胞免疫的prf1、GZMB和klrk1基因突变可能导致NK细胞数量减少和穿孔素功能障碍,进而降低宿主对细菌的免疫 [30] 。粒细胞集落刺激因子(Granulocyte-colony-stimulating factor, CSF3)是一种促炎细胞因子,主要刺激中性粒细胞祖细胞和成熟中性粒细胞的存活、增殖和分化。在脓毒症患者的免疫抑制过程中也受到抑制,外源性给予CSF3可提高脓毒症患者的生存率 [31] 。参与T细胞免疫的基因(CD27、CD3D、CD2、TBX21、ZAP70、CD3E、CD8A)与SOFA、病死率呈负相关,表明T细胞在脓毒症免疫中的重要地位可作为脓毒症的标志物,免疫抑制期已成为脓毒症治疗的重点 [32] [33] 。CXCL9是趋化因子受体CXCR3的配体之一,由多种细胞类型分泌,包括免疫细胞(T淋巴细胞、NK细胞、树突状细胞、巨噬细胞和嗜酸性粒细胞)和非免疫细胞(肝星状细胞、前脂肪细胞、甲状腺细胞、内皮细胞、肿瘤细胞和成纤维细胞等)。CXCL9在肿瘤生长、血管生成和转移中发挥作用,但也参与免疫调节和炎症过程 [34] 。CXCL9与其受体CXCR3结合,募集CXCR3+细胞,如效应T细胞、调节性T细胞(regulatory T cells, Tregs)和CD8+细胞毒性T细胞等,在其启动和维持过程中参与各种生理疾病的发病机制。Danahy发现,在脓毒症细胞因子风暴中,快速产生的IFN-γ导致血管内皮中IFN-γr1表达减少,以及皮肤内皮细胞中黏附分子和趋化因子(VCAM1和CXCL9)表达减少,导致效应细胞募集欠佳,并增加病原体复发的易感性。外源性给予CXCL9/10足以纠正脓毒症诱导的TRM抗原识别局部位点效应细胞募集的屏障损伤 [35] 。

5. 结论

综上所述,脓毒症相关肠黏膜屏障损伤可能涉及细胞因子–细胞因子受体相互作用、Th1和Th2细胞分化、病毒蛋白与细胞因子和细胞因子受体相互作用以及IL-17信号通路等过程。TBX 21、CSF3、IL-6、CXCR3、CXCL9可能是脓毒症相关肠黏膜屏障早期诊断和治疗的潜在生物学标志物。

NOTES

*通讯作者。

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