Genetics, Bioinformatics, and Computational Biology PhD Program, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, United States of America.
PLoS One. 2011 Jan 5;6(1):e15247. doi: 10.1371/journal.pone.0015247.
The liver plays a vital role in glucose homeostasis, the synthesis of bile acids and the detoxification of foreign substances. Liver culture systems are widely used to test adverse effects of drugs and environmental toxicants. The two most prevalent liver culture systems are hepatocyte monolayers (HMs) and collagen sandwiches (CS). Despite their wide use, comprehensive transcriptional programs and interaction networks in these culture systems have not been systematically investigated. We integrated an existing temporal transcriptional dataset for HM and CS cultures of rat hepatocytes with a functional interaction network of rat genes. We aimed to exploit the functional interactions to identify statistically significant linkages between perturbed biological processes. To this end, we developed a novel approach to compute Contextual Biological Process Linkage Networks (CBPLNs). CBPLNs revealed numerous meaningful connections between different biological processes and gene sets, which we were successful in interpreting within the context of liver metabolism. Multiple phenomena captured by CBPLNs at the process level such as regulation, downstream effects, and feedback loops have well described counterparts at the gene and protein level. CBPLNs reveal high-level linkages between pathways and processes, making the identification of important biological trends more tractable than through interactions between individual genes and molecules alone. Our approach may provide a new route to explore, analyze, and understand cellular responses to internal and external cues within the context of the intricate networks of molecular interactions that control cellular behavior.
肝脏在葡萄糖稳态、胆汁酸合成和外来物质解毒中起着至关重要的作用。肝脏培养系统广泛用于测试药物和环境毒物的不良影响。两种最常见的肝脏培养系统是肝细胞单层(HMs)和胶原三明治(CS)。尽管它们被广泛使用,但这些培养系统中的全面转录程序和相互作用网络尚未得到系统研究。我们整合了现有的大鼠肝细胞 HM 和 CS 培养的时间转录数据集,以及大鼠基因的功能相互作用网络。我们旨在利用功能相互作用来识别受扰生物过程之间具有统计学意义的联系。为此,我们开发了一种计算上下文生物过程链接网络(CBPLN)的新方法。CBPLN 揭示了不同生物过程和基因集之间的许多有意义的联系,我们成功地在肝脏代谢的背景下对其进行了解释。CBPLN 在过程水平上捕获的多个现象,如调节、下游效应和反馈回路,在基因和蛋白质水平上都有很好的描述。CBPLN 揭示了途径和过程之间的高级联系,使得识别重要的生物趋势比单独通过单个基因和分子之间的相互作用更容易。我们的方法可以为探索、分析和理解在控制细胞行为的复杂分子相互作用网络的背景下,细胞对内部和外部信号的反应提供一条新途径。