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免疫系统中促炎和促修复脂质介质生物合成的细胞类型特异性基因调控网络。

Cell-Type-Specific Gene Regulatory Networks of Pro-Inflammatory and Pro-Resolving Lipid Mediator Biosynthesis in the Immune System.

机构信息

Department of Systems Biology and Bioinformatics, University of Rostock, 18055 Rostock, Germany.

Heel GmbH, 76532 Baden-Baden, Germany.

出版信息

Int J Mol Sci. 2023 Feb 22;24(5):4342. doi: 10.3390/ijms24054342.

Abstract

Lipid mediators are important regulators in inflammatory responses, and their biosynthetic pathways are targeted by commonly used anti-inflammatory drugs. Switching from pro-inflammatory lipid mediators (PIMs) to specialized pro-resolving (SPMs) is a critical step toward acute inflammation resolution and preventing chronic inflammation. Although the biosynthetic pathways and enzymes for PIMs and SPMs have now been largely identified, the actual transcriptional profiles underlying the immune cell type-specific transcriptional profiles of these mediators are still unknown. Using the Atlas of Inflammation Resolution, we created a large network of gene regulatory interactions linked to the biosynthesis of SPMs and PIMs. By mapping single-cell sequencing data, we identified cell type-specific gene regulatory networks of the lipid mediator biosynthesis. Using machine learning approaches combined with network features, we identified cell clusters of similar transcriptional regulation and demonstrated how specific immune cell activation affects PIM and SPM profiles. We found substantial differences in regulatory networks in related cells, accounting for network-based preprocessing in functional single-cell analyses. Our results not only provide further insight into the gene regulation of lipid mediators in the immune response but also shed light on the contribution of selected cell types in their biosynthesis.

摘要

脂类介质是炎症反应的重要调节剂,其生物合成途径是常用抗炎药物的作用靶点。从促炎脂质介质(PIMs)向特异性促炎消退介质(SPMs)的转变是急性炎症消退和预防慢性炎症的关键步骤。尽管 PIMs 和 SPMs 的生物合成途径和酶已基本确定,但这些介质的免疫细胞类型特异性转录谱背后的实际转录谱仍不清楚。我们使用炎症消退图谱,创建了一个与 SPM 和 PIM 生物合成相关的大型基因调控相互作用网络。通过映射单细胞测序数据,我们确定了脂质介质生物合成的细胞类型特异性基因调控网络。我们使用机器学习方法结合网络特征,识别了具有相似转录调控的细胞簇,并展示了特定免疫细胞激活如何影响 PIM 和 SPM 谱。我们发现相关细胞中的调控网络存在显著差异,这说明了基于网络的预处理在功能单细胞分析中的重要性。我们的研究结果不仅为免疫反应中脂质介质的基因调控提供了更深入的了解,还揭示了选定细胞类型在其生物合成中的贡献。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c445/10001763/f0a28ac6922f/ijms-24-04342-g001.jpg

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