Department of Molecular Biology and Genetics, Cornell University, Ithaca, NY 14853, USA.
Mol Syst Biol. 2011 Dec 20;7:563. doi: 10.1038/msb.2011.96.
Progress in systems biology depends on accurate descriptions of biological networks. Connections in a regulatory network are identified as correlations of gene expression across a set of environmental or genetic perturbations. To use this information to predict system behavior, we must test how the nature of perturbations affects topologies of networks they reveal. To probe this question, we focused on metabolism of Drosophila melanogaster. Our source of perturbations is a set of crosses among 92 wild-derived lines from five populations, replicated in a manner permitting separate assessment of the effects of genetic variation and environmental fluctuation. We directly assayed activities of enzymes and levels of metabolites. Using a multivariate Bayesian model, we estimated covariance among metabolic parameters and built fine-grained probabilistic models of network topology. The environmental and genetic co-regulation networks are substantially the same among five populations. However, genetic and environmental perturbations reveal qualitative differences in metabolic regulation, suggesting that environmental shifts, such as diet modifications, produce different systemic effects than genetic changes, even if the primary targets are the same.
系统生物学的进展取决于对生物网络的准确描述。调控网络中的连接被确定为一组环境或遗传扰动中基因表达的相关性。为了利用这些信息来预测系统行为,我们必须测试扰动的性质如何影响它们揭示的网络拓扑结构。为了探究这个问题,我们专注于黑腹果蝇的新陈代谢。我们的扰动源是来自五个种群的 92 个野生衍生系的一组杂交,以允许分别评估遗传变异和环境波动影响的方式进行复制。我们直接测定了酶的活性和代谢物的水平。使用多元贝叶斯模型,我们估计了代谢参数之间的协方差,并构建了网络拓扑的精细概率模型。五个种群中的环境和遗传共同调控网络基本相同。然而,遗传和环境扰动揭示了代谢调控的定性差异,表明环境变化(如饮食改变)产生的系统效应与遗传变化不同,即使主要靶标相同也是如此。