一SC:一个用于回顾细胞状态转换的计算平台
Da Peng1, Patrick Cahan1,2,3
1Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, 21205, USA.
bioRxiv : the preprint server for biology
|June 19, 2024
概括
使用转录因子网络,OneSC模拟合成细胞以建模发育轨迹. 这种计算工具准确地预测了细胞命运的变化,使得在发育和癌症生物学研究中更快地进行了体实验.
科学领域:
- 发展生物学 发展生物学
- 计算生物学 计算生物学
- 系统生物学 系统生物学
背景情况:
- 细胞状态转换的计算建模对于理解发育生物学,癌症生物学和细胞命运工程至关重要.
- 单细胞RNA测序 (scRNA-seq) 在转变过程中提供了细胞状态的高分辨率时间快照.
- 现有的方法往往难以忠实地模仿生物细胞状态过渡和稳定状态.
研究的目的:
- 介绍OneSC,这是一个用于模拟跨发育轨迹的合成细胞的新平台.
- 开发基于随机微分方程和核心转录因子 (TF) 监管网络的计算模型.
- 为了生成精确复制细胞状态转换和稳定状态的布尔网络.
主要方法:
- OneSC使用由核心TF监管网络管理的随机微分方程系统.
- 该平台将生成布尔网络作为忠实细胞状态过渡和稳定状态模拟的优先事项.
- 应用于小鼠骨髓原体scRNA-seq数据,以推断一个核心TF网络.
主要成果:
- 使用推断网络进行的动态模拟准确地回顾了四个髓状细胞分化轨迹.
- 生成合成单细胞表达特征,模仿分化的细胞状态 (红细胞,大细胞,粒细胞,单细胞).
- 核心网络的in silico扰动准确地预测了TF扰动诱导的细胞命运偏差.
结论:
- 一个SC提供了一个强大的工具,用于模拟细胞状态转换和发育轨迹的in silico模拟.
- 该平台预测TF扰动效应的能力为实验设计提供了宝贵的见解.
- OneSC通过快速,经济高效的扰动实验来推进发育和癌症生物学中的计算方法.
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