生物信息学与多层实验验证的整合揭示了乙酰化相关基因在椎间盘退变中的新功能。

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
Jun Zhu , Tongqu Song , Zheng Li , Wei Zheng , Yong Liu , Hao Li , Song Wang , Jinlong Tang , Shuo Feng , Lei Wang , Xiaoqing Lu , Feng Yuan , Zhengya Zhu
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引用次数: 0

摘要

背景:椎间盘变性(IDD)的分子机制仍然鲜为人知。这项工作的目的是阐明关键分子并研究乙酰化相关 RNA 及其相关通路在 IDD 中的作用:方法:从基因表达总库(Gene Expression Omnibus,GEO)中获取数据集 GSE70362 和 GSE124272,并将其合并以研究与健康对照组相比,IDD 患者中与乙酰化相关的差异表达基因(DEGs)。通过整合 GO、KEGG 和 PPI 网络,确定了关键基因。此外,还利用 IBERSORTx 分析法研究了不同组间免疫细胞浸润的差异,并通过 GSEA 和 GSVA 计算了生物过程(BP)、细胞成分(CC)和分子功能(MF)。此外,还纳入了单细胞数据库 GSE165722,以验证细胞中枢基因的特定表达模式,并确定不同的细胞亚型。这为更深入地了解关键细胞亚型在 IDD 过程中所起的作用提供了理论基础。随后,研究人员收集了不同变性程度的 IVD 组织,利用 Western 印迹、RT-qPCR 和免疫荧光染色等方法证实了关键 DEGs:结果:通过整合各种数据集和参考文献,我们共发现了 1620 个乙酰化相关基因。我们将这些基因与本研究数据库中的 DEGs 进行了综合分析,发现了 358 个乙酰化相关差异表达基因(ARDEGs)。通过与三个数据库中的差异表达基因进行比较分析,发现了 19 个 ARDEGs。根据蛋白质相互作用关系,PPI 网络突出显示了前 10 个基因(IL1B、LAMP1、PPIA、SOD2、LAMP2、FBL、MBP、SELL、IRF1 和 KHDRBS1)。CIBERSORTx 免疫浸润分析表明,基因 IL1β 与肥大细胞活化(Mast.cell.activated)之间存在中度正相关,基因 IRF1 与肥大细胞活化(Mast.cell.activated)之间也存在类似的相关性。单细胞数据集用于识别细胞类型,并说明枢纽基因在不同细胞类型中的分布情况。对 AUCell 得分最高的两种细胞类型(中性粒细胞和单核细胞)进行了进一步探索,从而将中性粒细胞细分为两种新的细胞亚型:S100A9型中性粒细胞和MARCKS型中性粒细胞。单核细胞被标记为 HLA-DRA9 型单核细胞和 IGHG3 型单核细胞。最后,采用分子生物学技术验证了前 10 个中心基因的表达。其中,4 个基因(IL1β、SOD2、LAMP2 和 IRF1)在基因水平上得到证实,2 个基因(IL1β 和 SOD2)在蛋白质水平上得到验证:在这项研究中,我们对三个数据库进行了全面分析,以确定并比较 IDD 患者与健康人之间的 ARDEGs。此外,我们还利用分子生物学技术在临床样本中验证了这些基因的子集。这些不同表达基因的鉴定有可能为诊断和治疗 IDD 提供新的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Integration of bioinformatics and multi-layered experimental validation reveals novel functions of acetylation-related genes in intervertebral disc degeneration

Background

The molecular mechanisms underlying intervertebral disc degeneration (IDD) remain poorly understood. The purpose of this work is to elucidate key molecules and investigate the roles of acetylation-related RNAs and their associated pathways in IDD.

Method

Datasets GSE70362 and GSE124272 were obtained from the Gene Expression Omnibus (GEO) and combined to investigate differentially expressed genes (DEGs) associated with acetylation in IDD patients compared to healthy controls. Critical genes were pinpointed by integrating GO, KEGG and PPI networks. Furthermore, CIBERSORTx analysis was used to investigate the differences in immune cell infiltration between different groups and the biological processes (BP), cellular components (CC) and molecular functions (MF) were calculated by GSEA and GSVA. In addition, The single-cell database GSE165722 was incorporated to validate the specific expression patterns of hub genes in cells and identify distinct cell subtypes. This provides a theoretical basis for a more in-depth understanding of the roles played by critical cell subtypes in the process of IDD. Subsequently, tissues from IVD with varying degrees of degeneration were collected to corroborate the key DEGs using western blot, RT-qPCR, and immunofluorescence staining.

Results

By integrating various datasets and references, we identified a total of 1620 acetylation-related genes. These genes were subjected to a combined analysis with the DEGs from the databases included in this study, resulting in the discovery of 358 acetylation-related differentially expressed genes (ARDEGs). A comparative analysis with differentially expressed genes obtained from three databases yielded 19 ARDEGs. The PPI network highlighted the top 10 genes (IL1B, LAMP1, PPIA, SOD2, LAMP2, FBL, MBP, SELL, IRF1 and KHDRBS1) based on their protein interaction relationships. CIBERSORTx immune infiltration analysis revealed a moderate positive correlation between the gene IL1β and Mast.cells.activated, as well as a similar correlation between the gene IRF1 and Mast.cells.activated. Single-cell dataset was used to identify cell types and illustrate the distribution of hub genes in different cell types. The two cell types with the highest AUCell scores (Neutrophils and Monocytes) were further explored, leading to the subdivision of Neutrophils into two new cell subtypes: S100A9-type Neutrophils and MARCKS-type Neutrophils. Monocytes were labeled as HLA-DRA9-type Monocytes and IGHG3-type Monocytes. Finally, molecular biology techniques were employed to validate the expression of the top 10 hub genes. Among them, four genes (IL1β, SOD2, LAMP2, and IRF1) were confirmed at the gene level, while two (IL1β and SOD2) were validated at the protein level.

Conclusion

In this study, we carried out a thorough analysis across three databases to identify and compare ARDEGs between IDD patients and healthy individuals. Furthermore, we validated a subset of these genes using molecular biology techniques on clinical samples. The identification of these differently expressed genes has the potential to offer new insights for diagnosing and treating IDD.
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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