Sprott Center for Stem Cell Research, Ottawa Hospital Research Institute.
Department of Cellular and Molecular Medicine, University of Ottawa, Ottawa, Ontario, Canada.
Curr Opin Hematol. 2021 May 1;28(3):150-157. doi: 10.1097/MOH.0000000000000647.
Erythropoiesis is a hierarchical process by which hematopoietic stem cells give rise to red blood cells through gradual cell fate restriction and maturation. Deciphering this process requires the establishment of dynamic gene regulatory networks (GRNs) that predict the response of hematopoietic cells to signals from the environment. Although GRNs have historically been derived from transcriptomic data, recent proteomic studies have revealed a major role for posttranscriptional mechanisms in regulating gene expression during erythropoiesis. These new findings highlight the need to integrate proteomic data into GRNs for a refined understanding of erythropoiesis.
Here, we review recent proteomic studies that have furthered our understanding of erythropoiesis with a focus on quantitative mass spectrometry approaches to measure the abundance of transcription factors and cofactors during differentiation. Furthermore, we highlight challenges that remain in integrating transcriptomic, proteomic, and other omics data into a predictive model of erythropoiesis, and discuss the future prospect of single-cell proteomics.
Recent proteomic studies have considerably expanded our knowledge of erythropoiesis beyond the traditional transcriptomic-centric perspective. These findings have both opened up new avenues of research to increase our understanding of erythroid differentiation, while at the same time presenting new challenges in integrating multiple layers of information into a comprehensive gene regulatory model.
红细胞生成是一个层次化的过程,造血干细胞通过逐渐的细胞命运限制和成熟,产生红细胞。要揭示这个过程,需要建立动态的基因调控网络(GRNs),以预测造血细胞对环境信号的反应。尽管 GRNs 历史上是从转录组数据中得出的,但最近的蛋白质组学研究表明,在后转录水平上的机制在调节红细胞生成过程中的基因表达方面起着重要作用。这些新发现强调了将蛋白质组学数据纳入 GRNs 以更精细地理解红细胞生成的必要性。
在这里,我们回顾了最近的蛋白质组学研究,这些研究进一步加深了我们对红细胞生成的理解,重点是采用定量质谱方法来测量分化过程中转录因子和共因子的丰度。此外,我们还强调了将转录组学、蛋白质组学和其他组学数据整合到红细胞生成的预测模型中仍然存在的挑战,并讨论了单细胞蛋白质组学的未来前景。
最近的蛋白质组学研究极大地扩展了我们对红细胞生成的传统转录组学观点的认识。这些发现既为增加我们对红细胞分化的理解开辟了新的研究途径,同时又在将多个层次的信息整合到一个全面的基因调控模型中提出了新的挑战。