利用单细胞转录组分析和慢病毒条形码技术对体内具有不同细胞命运的人类 HSPC 进行分子鉴定。

IF 7.9 1区 医学 Q1 MEDICINE, RESEARCH & EXPERIMENTAL
Junnan Hua, Ke Wang, Yue Chen, Xiaojing Xu, Guoyi Dong, Yue Li, Rui Liu, Yecheng Xiong, Jiabin Ding, Tingting Zhang, Xinru Zeng, Yuxi Li, Haixi Sun, Ying Gu, Sixi Liu, Wenjie Ouyang, Chao Liu
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引用次数: 0

摘要

造血干细胞和祖细胞(HSPCs)具有终生产生所有类型血细胞的潜能。众所周知,造血干细胞具有异质性,这对其临床应用和治疗与造血干细胞相关的疾病具有重要意义。本研究提出了一种名为 "单细胞转录组分析和慢病毒条形码(SCALeBa)"的新技术,用于研究人HSPCs体内异质性的分子机制。SCALeBa 结合了转录条码库和算法,可同时分析单个细胞的命运及其基因表达谱。我们利用 SCALeBa 的研究结果显示,干性较强的 HSPCs 亚群高表达 MYL6B、ATP2A2、MYO19、MDN1、ING3 等基因。COA3、RIF1、RAB14和GOLGA4的高表达可能有助于HSPCs的多能系分化。此外,本研究揭示的代表基因在HPSC干性方面的作用也得到了生物学实验的证实。表达MRPL23和RBM4基因的HSPC可能会分别导致髓系和淋巴系的分化偏向。此外,还发现了淋巴和髓系分化偏向HSPCs亚群的转录因子(TF)特征,并与之前发现的基因相关联。此外,用SCALeBa鉴定出的干性、多能性和分化偏倚基因在另一个独立的HSPCs数据集中也得到了验证。最后,本研究建议使用 SCALeBa 生成的追踪轨迹来提高伪时分析结果的准确性。总之,我们的研究为了解人体内 HSPCs 的异质性提供了有价值的见解,并介绍了一种新型技术 SCALeBa,它有望得到更广泛的应用。要点:开发 SCALeBa 及其算法是为了研究人类 HSPCs 特性和功能的分子机制。表达 MYL6B、MYO19、ATP2A2、MDN1、ING3 和 PHF20 的人类 HSPCs 可能具有高干性。表达 COA3、RIF1、RAB14 和 GOLGA4 的人类 HSPC 可能具有多能系分化能力。表达 MRPL23 和 RBM4 基因的人类 HSPCs 可能具有在体内分别向髓系和淋巴系分化的能力。利用生物学实验和公开的人类 HSPCs 数据集验证了 SCALeBa 所鉴定基因的合法性。SCALeBa 提高了基于 monocle2 的伪时间分析中分化轨迹的准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Molecular characterization of human HSPCs with different cell fates in vivo using single-cell transcriptome analysis and lentiviral barcoding technology

Molecular characterization of human HSPCs with different cell fates in vivo using single-cell transcriptome analysis and lentiviral barcoding technology

Hematopoietic stem and progenitor cells (HSPCs) possess the potential to produce all types of blood cells throughout their lives. It is well recognized that HSPCs are heterogeneous, which is of great significance for their clinical applications and the treatment of diseases associated with HSPCs. This study presents a novel technology called Single-Cell transcriptome Analysis and Lentiviral Barcoding (SCALeBa) to investigate the molecular mechanisms underlying the heterogeneity of human HSPCs in vivo. The SCALeBa incorporates a transcribed barcoding library and algorithm to analyze the individual cell fates and their gene expression profiles simultaneously. Our findings using SCALeBa reveal that HSPCs subset with stronger stemness highly expressed MYL6B, ATP2A2, MYO19, MDN1, ING3, and so on. The high expression of COA3, RIF1, RAB14, and GOLGA4 may contribute to the pluripotent-lineage differentiation of HSPCs. Moreover, the roles of the representative genes revealed in this study regarding the stemness of HPSCs were confirmed with biological experiments. HSPCs expressing MRPL23 and RBM4 genes may contribute to differentiation bias into myeloid and lymphoid lineage, respectively. In addition, transcription factor (TF) characteristics of lymphoid and myeloid differentiation bias HSPCs subsets were identified and linked to previously identified genes. Furthermore, the stemness, pluripotency, and differentiation-bias genes identified with SCALeBa were verified in another independent HSPCs dataset. Finally, this study proposes using the SCALeBa-generated tracking trajectory to improve the accuracy of pseudo-time analysis results. In summary, our study provides valuable insights for understanding the heterogeneity of human HSPCs in vivo and introduces a novel technology, SCALeBa, which holds promise for broader applications.

Key points

  • SCALeBa and its algorithm are developed to study the molecular mechanism underlying human HSPCs identity and function.
  • The human HSPCs expressing MYL6B, MYO19, ATP2A2, MDN1, ING3, and PHF20 may have the capability for high stemness.
  • The human HSPCs expressing COA3, RIF1, RAB14, and GOLGA4 may have the capability for pluripotent-lineage differentiation.
  • The human HSPCs expressing MRPL23 and RBM4 genes may have the capability to differentiate into myeloid and lymphoid lineage respectively in vivo.
  • The legitimacy of the identified genes with SCALeBa was validated using biological experiments and a public human HSPCs dataset.
  • SCALeBa improves the accuracy of differentiation trajectories in monocle2-based pseudo-time analysis.
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来源期刊
CiteScore
15.90
自引率
1.90%
发文量
450
审稿时长
4 weeks
期刊介绍: Clinical and Translational Medicine (CTM) is an international, peer-reviewed, open-access journal dedicated to accelerating the translation of preclinical research into clinical applications and fostering communication between basic and clinical scientists. It highlights the clinical potential and application of various fields including biotechnologies, biomaterials, bioengineering, biomarkers, molecular medicine, omics science, bioinformatics, immunology, molecular imaging, drug discovery, regulation, and health policy. With a focus on the bench-to-bedside approach, CTM prioritizes studies and clinical observations that generate hypotheses relevant to patients and diseases, guiding investigations in cellular and molecular medicine. The journal encourages submissions from clinicians, researchers, policymakers, and industry professionals.
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