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单细胞RNA测序分析揭示了细胞衰老的多步骤过程。

Single-cell RNA-seq analysis reveals the multi-step process of cellular senescence.

作者信息

Ahn Minseo, Kim Junil, Seo Jae Ho

机构信息

Department of Biochemistry, Wonkwang University School of Medicine, Iksan, 54538, Republic of Korea.

Sarcopenia Total Solution Center, Wonkwang University School of Medicine, Iksan, 54538, Republic of Korea.

出版信息

Biochem Biophys Rep. 2025 May 11;42:102042. doi: 10.1016/j.bbrep.2025.102042. eCollection 2025 Jun.

Abstract

Cellular senescence is a phenomenon marked by an irreversible growth arrest with altered physiological properties. Many studies have focused on the characteristics of cells that have already entered a senescent state. However, to elucidate the mechanisms of cellular aging, it is essential to investigate the gradual transition of proliferative cells into senescent cells. We hypothesized that cellular senescence is a complex, multi-step process in which each stage is characterized by distinct cellular features and transcription factor expression patterns. To test this hypothesis, we utilized publicly available single-cell RNA-Seq (scRNA-Seq) data from human umbilical vein endothelial cells (HUVECs) undergoing replicative senescence. We employed Seurat and Monocle 3 to capture the transition from proliferating to senescent states in HUVECs. Four clusters were identified, and each cluster displayed distinct expression patterns of cellular senescence markers and the senescence-associated secretory phenotypes (SASPs). We also employed SCENIC to identify the expression patterns of core transcription factors (TFs) during replicative senescence. While the majority of TFs exhibited a linear trend, HMGB1, FOSL1, SMC3, RAD21, SOX4, and XBP1 showed fluctuating expression patterns during replicative senescence. Furthermore, the expression of these TFs exhibited different patterns in the ionizing radiation (IR) model of senescence. Overall, our study unveils the distinct characteristics of each phase during replicative senescence and identifies expression trends in SASPs and TFs that may play pivotal roles in this process. Unlike previous bulk RNA-seq studies, this work uniquely integrates single-cell trajectory and transcription factor dynamics to decode phase-specific molecular signatures during replicative senescence. Here, we identify key transcription factors potentially involved in senescence induction and provide novel insights into the regulatory complexity of cellular aging.

摘要

细胞衰老 是一种以不可逆生长停滞和生理特性改变为特征的现象。许多研究都集中在已经进入衰老状态的细胞的特征上。然而,为了阐明细胞衰老的机制,研究增殖细胞向衰老细胞的逐渐转变至关重要。我们假设细胞衰老是一个复杂的多步骤过程,其中每个阶段都具有独特的细胞特征和转录因子表达模式。为了验证这一假设,我们利用了来自经历复制性衰老的人脐静脉内皮细胞(HUVEC)的公开可用单细胞RNA测序(scRNA-Seq)数据。我们使用Seurat和Monocle 3来捕捉HUVEC中从增殖状态到衰老状态的转变。识别出四个细胞簇,每个簇都显示出细胞衰老标志物和衰老相关分泌表型(SASP)的独特表达模式。我们还使用SCENIC来识别复制性衰老过程中核心转录因子(TF)的表达模式。虽然大多数TF呈现线性趋势,但HMGB1、FOSL1、SMC3、RAD21、SOX4和XBP1在复制性衰老过程中表现出波动的表达模式。此外,这些TF的表达在衰老的电离辐射(IR)模型中呈现出不同的模式。总体而言,我们的研究揭示了复制性衰老过程中每个阶段的独特特征,并确定了可能在这一过程中起关键作用的SASP和TF的表达趋势。与以往的批量RNA测序研究不同,这项工作独特地整合了单细胞轨迹和转录因子动力学,以解码复制性衰老过程中阶段特异性的分子特征。在这里,我们识别出可能参与衰老诱导的关键转录因子,并为细胞衰老的调控复杂性提供了新的见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fb9c/12138942/3aa20088c722/gr1.jpg

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本文引用的文献

2
An introduction to representation learning for single-cell data analysis.
Cell Rep Methods. 2023 Aug 2;3(8):100547. doi: 10.1016/j.crmeth.2023.100547. eCollection 2023 Aug 28.
3
4
The Role of SOX Transcription Factors in Ageing and Age-Related Diseases.
Int J Mol Sci. 2023 Jan 3;24(1):851. doi: 10.3390/ijms24010851.
5
Unfolded protein response IRE1/XBP1 signaling is required for healthy mammalian brain aging.
EMBO J. 2022 Nov 17;41(22):e111952. doi: 10.15252/embj.2022111952. Epub 2022 Oct 31.
6
Temporal modelling using single-cell transcriptomics.
Nat Rev Genet. 2022 Jun;23(6):355-368. doi: 10.1038/s41576-021-00444-7. Epub 2022 Jan 31.
7
ROS/TGF-β signal mediated accumulation of SOX4 in OA-FLS promotes cell senescence.
Exp Gerontol. 2021 Dec;156:111616. doi: 10.1016/j.exger.2021.111616. Epub 2021 Nov 3.
8
Persistent JunB activation in fibroblasts disrupts stem cell niche interactions enforcing skin aging.
Cell Rep. 2021 Aug 31;36(9):109634. doi: 10.1016/j.celrep.2021.109634.
9
Integrated analysis of multimodal single-cell data.
Cell. 2021 Jun 24;184(13):3573-3587.e29. doi: 10.1016/j.cell.2021.04.048. Epub 2021 May 31.

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