Department of Signal Processing, Tampere University of Technology, Tampere, Finland.
PLoS One. 2010 May 14;5(5):e10662. doi: 10.1371/journal.pone.0010662.
Molecular interaction networks establish all cell biological processes. The networks are under intensive research that is facilitated by new high-throughput measurement techniques for the detection, quantification, and characterization of molecules and their physical interactions. For the common model organism yeast Saccharomyces cerevisiae, public databases store a significant part of the accumulated information and, on the way to better understanding of the cellular processes, there is a need to integrate this information into a consistent reconstruction of the molecular interaction network. This work presents and validates RefRec, the most comprehensive molecular interaction network reconstruction currently available for yeast. The reconstruction integrates protein synthesis pathways, a metabolic network, and a protein-protein interaction network from major biological databases. The core of the reconstruction is based on a reference object approach in which genes, transcripts, and proteins are identified using their primary sequences. This enables their unambiguous identification and non-redundant integration. The obtained total number of different molecular species and their connecting interactions is approximately 67,000. In order to demonstrate the capacity of RefRec for functional predictions, it was used for simulating the gene knockout damage propagation in the molecular interaction network in approximately 590,000 experimentally validated mutant strains. Based on the simulation results, a statistical classifier was subsequently able to correctly predict the viability of most of the strains. The results also showed that the usage of different types of molecular species in the reconstruction is important for accurate phenotype prediction. In general, the findings demonstrate the benefits of global reconstructions of molecular interaction networks. With all the molecular species and their physical interactions explicitly modeled, our reconstruction is able to serve as a valuable resource in additional analyses involving objects from multiple molecular -omes. For that purpose, RefRec is freely available in the Systems Biology Markup Language format.
分子相互作用网络建立了所有的细胞生物学过程。这些网络是目前研究的热点,这得益于新的高通量测量技术,这些技术可用于检测、定量和表征分子及其物理相互作用。对于常见的模式生物酿酒酵母(Saccharomyces cerevisiae),公共数据库存储了大量已积累的信息,为了更好地理解细胞过程,需要将这些信息整合到一个一致的分子相互作用网络重建中。本工作提出并验证了 RefRec,这是目前可用于酵母的最全面的分子相互作用网络重建。该重建整合了蛋白质合成途径、代谢网络和来自主要生物数据库的蛋白质-蛋白质相互作用网络。重建的核心是基于参考对象的方法,该方法使用其一级序列来识别基因、转录物和蛋白质,从而能够对它们进行明确的识别和非冗余的整合。获得的不同分子种类及其连接相互作用的总数约为 67000 个。为了展示 RefRec 进行功能预测的能力,我们使用它模拟了分子相互作用网络中基因敲除损伤的传播,涉及大约 590000 个经过实验验证的突变株。基于模拟结果,随后可以使用统计分类器正确预测大多数菌株的生存能力。结果还表明,在重建中使用不同类型的分子种类对于准确的表型预测很重要。总的来说,这些发现表明了全局分子相互作用网络重建的好处。由于明确地对所有分子种类及其物理相互作用进行建模,我们的重建可以作为涉及多个分子组学对象的额外分析的有价值资源。为此,RefRec 以系统生物学标记语言(Systems Biology Markup Language)格式免费提供。