Reconstructing Waddington Landscape from Cell Migration and Proliferation.

IF 3.9 2区 生物学 Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Yourui Han, Bolin Chen, Zhongwen Bi, Jianjun Zhang, Youpeng Hu, Jun Bian, Ruiming Kang, Xuequn Shang
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引用次数: 0

Abstract

The Waddington landscape was initially proposed to depict cell differentiation, and has been extended to explain phenomena such as reprogramming. The landscape serves as a concrete representation of cellular differentiation potential, yet the precise representation of this potential remains an unsolved problem, posing significant challenges to reconstructing the Waddington landscape. The characterization of cellular differentiation potential relies on transcriptomic signatures of known markers typically. Numerous computational models based on various energy indicators, such as Shannon entropy, have been proposed. While these models can effectively characterize cellular differentiation potential, most of them lack corresponding dynamical interpretations, which are crucial for enhancing our understanding of cell fate transitions. Therefore, from the perspective of cell migration and proliferation, a feasible framework was developed for calculating the dynamically interpretable energy indicator to reconstruct Waddington landscape based on sparse autoencoders and the reaction diffusion advection equation. Within this framework, typical cellular developmental processes, such as hematopoiesis and reprogramming processes, were dynamically simulated and their corresponding Waddington landscapes were reconstructed. Furthermore, dynamic simulation and reconstruction were also conducted for special developmental processes, such as embryogenesis and Epithelial-Mesenchymal Transition process. Ultimately, these diverse cell fate transitions were amalgamated into a unified Waddington landscape.

从细胞迁移和增殖重构沃丁顿景观。
沃丁顿景观最初被提出用来描述细胞分化,并被扩展到解释重编程等现象。景观作为细胞分化潜力的具体表现,然而这种潜力的精确表现仍然是一个未解决的问题,这对重建沃丁顿景观构成了重大挑战。细胞分化潜能的表征通常依赖于已知标记物的转录组特征。许多基于各种能量指标的计算模型,如香农熵,已经被提出。虽然这些模型可以有效地表征细胞分化潜力,但大多数模型缺乏相应的动力学解释,这对于增强我们对细胞命运转变的理解至关重要。因此,从细胞迁移和增殖的角度出发,提出了一种基于稀疏自编码器和反应扩散平流方程计算动态可解释能量指标重构Waddington景观的可行框架。在此框架内,动态模拟了典型的细胞发育过程,如造血和重编程过程,并重建了相应的Waddington景观。此外,还对胚胎发生、上皮-间质转化等特殊发育过程进行了动态模拟和重建。最终,这些不同的细胞命运转变被合并成一个统一的沃丁顿景观。
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来源期刊
Interdisciplinary Sciences: Computational Life Sciences
Interdisciplinary Sciences: Computational Life Sciences MATHEMATICAL & COMPUTATIONAL BIOLOGY-
CiteScore
8.60
自引率
4.20%
发文量
55
期刊介绍: Interdisciplinary Sciences--Computational Life Sciences aims to cover the most recent and outstanding developments in interdisciplinary areas of sciences, especially focusing on computational life sciences, an area that is enjoying rapid development at the forefront of scientific research and technology. The journal publishes original papers of significant general interest covering recent research and developments. Articles will be published rapidly by taking full advantage of internet technology for online submission and peer-reviewing of manuscripts, and then by publishing OnlineFirstTM through SpringerLink even before the issue is built or sent to the printer. The editorial board consists of many leading scientists with international reputation, among others, Luc Montagnier (UNESCO, France), Dennis Salahub (University of Calgary, Canada), Weitao Yang (Duke University, USA). Prof. Dongqing Wei at the Shanghai Jiatong University is appointed as the editor-in-chief; he made important contributions in bioinformatics and computational physics and is best known for his ground-breaking works on the theory of ferroelectric liquids. With the help from a team of associate editors and the editorial board, an international journal with sound reputation shall be created.
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