Teixeira Ana P, Dias João Ml, Carinhas Nuno, Sousa Marcos, Clemente João J, Cunha António E, von Stosch Moritz, Alves Paula M, Carrondo Manuel Jt, Oliveira Rui
Instituto de Tecnologia Química e Biológica - Universidade Nova de Lisboa (ITQB-UNL), Av, República, Quinta do Marquês, Oeiras, Portugal.
BMC Syst Biol. 2011 Jun 6;5:92. doi: 10.1186/1752-0509-5-92.
While functional genomics, focused on gene functions and gene-gene interactions, has become a very active field of research in molecular biology, equivalent methodologies embracing the environment and gene-environment interactions are relatively less developed. Understanding the function of environmental factors is, however, of paramount importance given the complex, interactive nature of environmental and genetic factors across multiple time scales.
Here, we propose a systems biology framework, where the function of environmental factors is set at its core. We set forth a "reverse" functional analysis approach, whereby cellular functions are reconstructed from the analysis of dynamic envirome data. Our results show these data sets can be mapped to less than 20 core cellular functions in a typical mammalian cell culture, while explaining over 90% of flux data variance. A functional enviromics map can be created, which provides a template for manipulating the environmental factors to induce a desired phenotypic trait.
Our results support the feasibility of cellular function reconstruction guided by the analysis and manipulation of dynamic envirome data.
虽然专注于基因功能和基因-基因相互作用的功能基因组学已成为分子生物学中一个非常活跃的研究领域,但涵盖环境以及基因-环境相互作用的等效方法相对不太发达。然而,鉴于环境和遗传因素在多个时间尺度上的复杂、交互性质,了解环境因素的功能至关重要。
在此,我们提出了一个系统生物学框架,将环境因素的功能置于其核心。我们提出了一种“反向”功能分析方法,通过对动态环境组数据的分析来重建细胞功能。我们的结果表明,在典型的哺乳动物细胞培养中,这些数据集可以映射到少于20种核心细胞功能,同时解释超过90%的通量数据方差。可以创建一个功能环境组学图谱,它为操纵环境因素以诱导所需表型特征提供了一个模板。
我们的结果支持了以动态环境组数据的分析和操纵为指导进行细胞功能重建的可行性。