Cook Daniel, Manchel Alexandra, Ogunnaike Babatunde A, Vadigepalli Rajanikanth
Department of Chemical and Biomolecular Engineering, University of Delaware, Newark, Delaware19716, United States.
Daniel Baugh Institute for Functional Genomics and Computational Biology, Department of Pathology and Genomic Medicine, Thomas Jefferson University, Philadelphia, Pennsylvania19107, United States.
Ind Eng Chem Res. 2023 Jan 27;62(5):2275-2287. doi: 10.1021/acs.iecr.2c03579. eCollection 2023 Feb 8.
Recent experimental investigations of liver homeostatic renewal have identified high replication capacity hepatocyte populations as the primary maintainers of liver mass. However, the molecular and cellular processes controlling liver homeostatic renewal remain unknown. To address this problem, we developed and analyzed a mathematical model describing cellular network interactions underlying liver homeostatic renewal. Model simulation results demonstrate that without feedback control, basic homeostatic renewal is not robust to disruptions, leading to tissue loss under persistent/repetitive insults. Consequently, we extended our basic model to incorporate putative regulatory interactions and investigated how such interactions may confer robustness on the homeostatic renewal process. We utilized a Design of Experiments approach to identify the combination of feedback interactions that yields a cell network model of homeostatic renewal capable of maintaining liver mass robustly during persistent/repetitive injury. Simulations of this robust model indicate that repeated injury destabilizes liver homeostasis within several months, which differs from epidemiological observations of a much slower decay of liver function occurring over several years. To address this discrepancy, we extended the model to include feedback control by liver nonparenchymal cells. Simulations and analysis of the final multicellular feedback control network suggest that achieving robust liver homeostatic renewal requires intrinsic stability in a hepatocellular network combined with feedback control by nonparenchymal cells.
最近关于肝脏稳态更新的实验研究已经确定,具有高复制能力的肝细胞群体是肝脏质量的主要维持者。然而,控制肝脏稳态更新的分子和细胞过程仍然未知。为了解决这个问题,我们开发并分析了一个数学模型,该模型描述了肝脏稳态更新背后的细胞网络相互作用。模型模拟结果表明,在没有反馈控制的情况下,基本的稳态更新对干扰不具有鲁棒性,导致在持续/重复损伤下组织损失。因此,我们扩展了基本模型以纳入假定的调节相互作用,并研究了这些相互作用如何赋予稳态更新过程鲁棒性。我们采用实验设计方法来确定反馈相互作用的组合,从而产生一个稳态更新的细胞网络模型,该模型能够在持续/重复损伤期间稳健地维持肝脏质量。这个鲁棒模型的模拟表明,重复损伤会在几个月内破坏肝脏稳态,这与在几年内发生的肝功能更缓慢衰退的流行病学观察结果不同。为了解决这一差异,我们扩展了模型以纳入肝脏非实质细胞的反馈控制。对最终多细胞反馈控制网络的模拟和分析表明,实现稳健的肝脏稳态更新需要肝细胞网络的内在稳定性以及非实质细胞的反馈控制。