Identification of Biomarkers Related to Liquid-Liquid Phase Separation for Ulcerative Colitis Based on Single-Cell and Bulk RNA Transcriptome Sequencing Data.

Jicheng Lu, Xu Lu, Bin Chen
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Abstract

Background: Liquid-Liquid Phase Separation (LLPS) is a process involved in the formation of established organelles and various condensates that lack membranes; however, the relationship between LLPS and Ulcerative Colitis (UC) remains unclear.

Aims: This study aimed to comprehensively clarify the correlation between ulcerative colitis (UC) and liquid-liquid phase separation (LLPS).

Objectives: In this study, bioinformatics analyses and public databases were applied to screen and validate key genes associated with LLPS in UC. Furthermore, the roles of these key genes in UC were comprehensively analyzed.

Methods: Based on the single-cell transcriptomic data of UC obtained from the Gene Expression Omnibus (GEO) database, differences between patients with UC and their controls were compared using the limma package. The single-cell data were then filtered and normalized by the 'Seurat' package and subjected to dimension reduction by the Uniform Manifold Approximation and Projection (UMAP) algorithm. The LLPS-related genes (LLPSRGs) were searched on the Dr- LLPS website to obtain cross-correlated genes, which were scored using the ssGSEA algorithm. Next, functional enrichment, interaction network, immune landscape, and diagnostic and drug prediction of the LLPSRGs were comprehensively explored. Finally, the results were validated using external datasets and quantitative real-time PCR (qRT-PCR).

Results: A total of eight cell types in UC were classified, namely, fibroblasts, macrophages, endothelial cells, neutrophils, NK cells, B cells, epithelial cells, and T cells. The intersection between differently expressed genes (DEGs) among the eight cell types identified 44 key genes, which were predominantly enriched in immune- and infection-related pathways. According to receiver operating characteristic (ROC) curves, PLA2G2A, GZMK, CD69, HSP90B1, and S100A11 reached an AUC value of 0.94, 0.95, 0.86, 0.89, and 0.93, respectively. Drug prediction revealed that decitabine, tetrachlorodibenzodioxin, tetradecanoylphorbol acetate, thapsigargin, and cisplatin were the potential small molecular compounds for PLA2G2A, GZMK, CD69, HSP90B1, and S100A11. Immune cell infiltration analysis demonstrated that the infiltration of CD4 memory T cell activation, macrophage M1, T macrophage M0, neutrophils, and mast cell activation was higher in the UC group than in the normal group.

Conclusion: The LLPSRGs play crucial roles in UC and can be used as prognostic and diagnostic markers for UC. The current findings contribute to the management of UC.

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基于单细胞和大量RNA转录组测序数据的溃疡性结肠炎液-液相分离相关生物标志物鉴定
背景:液-液相分离(LLPS)是一个过程,涉及形成既定的细胞器和各种冷凝物缺乏膜;然而,LLPS与溃疡性结肠炎(UC)之间的关系尚不清楚。目的:本研究旨在全面阐明溃疡性结肠炎(UC)与液-液相分离(LLPS)的相关性。目的:本研究采用生物信息学分析和公共数据库技术筛选和验证UC中与LLPS相关的关键基因。并对这些关键基因在UC中的作用进行了综合分析。方法:基于从Gene Expression Omnibus (GEO)数据库获得的UC单细胞转录组数据,使用limma软件包比较UC患者与对照组的差异。然后,通过Seurat包对单细胞数据进行过滤和归一化,并通过均匀流形逼近和投影(UMAP)算法进行降维。在Dr- LLPS网站上搜索LLPS相关基因(LLPSRGs),获得交叉相关基因,使用ssGSEA算法进行评分。接下来,对LLPSRGs的功能富集、相互作用网络、免疫景观、诊断和药物预测进行了全面的探索。最后,使用外部数据集和定量实时PCR (qRT-PCR)验证结果。结果:UC共分为8种细胞类型,分别为成纤维细胞、巨噬细胞、内皮细胞、中性粒细胞、NK细胞、B细胞、上皮细胞和T细胞。不同表达基因(DEGs)在8种细胞类型之间的交集鉴定出44个关键基因,这些基因主要富集于免疫和感染相关途径。受试者工作特征(ROC)曲线显示,PLA2G2A、GZMK、CD69、HSP90B1、S100A11的AUC值分别为0.94、0.95、0.86、0.89、0.93。药物预测结果显示,地西他滨、四氯二苯并二氧嘧啶、醋酸十四烷酰磷、塔普sigargin和顺铂是PLA2G2A、GZMK、CD69、HSP90B1和S100A11的潜在小分子化合物。免疫细胞浸润分析显示UC组CD4记忆T细胞活化、巨噬细胞M1、T巨噬细胞M0、中性粒细胞浸润、肥大细胞活化均高于正常组。结论:LLPSRGs在UC中起重要作用,可作为UC的预后和诊断指标。目前的研究结果有助于UC的管理。
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