Determination of redundancy and systems properties of the metabolic network of Helicobacter pylori using genome-scale extreme pathway analysis
Determination of redundancy and systems properties of the metabolic network of Helicobacter pylori using genome-scale extreme pathway analysis
复制标题
DOI：
10.1101/gr.218002
复制
发表时间：
2002-05-01
期刊：
影响因子：
7
通讯作者：
Palsson, BO
中科院分区：
文献类型：
--
作者：
Price, ND;Papin, JA;Palsson, BO
基因组规模的代谢网络的能力可以通过确定一组称为极端路径的系统独立和独特的通量图来描述。首次研究了在幽门螺杆菌中同时形成所有非必需氨基酸或核糖核苷酸的基因组规模的极端途径。得到了三个关键结果。首先，幽门螺杆菌产生单个氨基酸的极端途径显示，每个外部状态的内部状态比以前在流感嗜血杆菌中发现的要少得多，这表明一个更严格的代谢网络。其次，幽门螺杆菌中产生单个氨基酸和连接氨基酸集的途径冗余程度基本上相同，但大约是产生核糖核苷酸的两倍。第三，幽门螺杆菌的代谢网络无法将所消耗的氨基酸广泛转化为非必需氨基酸或核苷酸，从而将其大部分氮转移到氨生产中，这对其酸性栖息地的pH调节具有潜在的重要结果。基因组规模的极端途径阐明了系统范围内的紧急特性。极端通路分析正在成为分析代谢基因及其表型之间联系的一种潜在的重要方法。
The capabilities of genome-scale metabolic networks call be described through the determination of a set of systemically independent and unique flux maps called extreme pathways. The first Study of genome-scale extreme pathways for the simultaneous formation of all nonessential amino acids or ribonucleotides in Helicobacter pylori is presented. Three key results were obtained. First, the extreme pathways for the production of individual amino acids in H. pylori showed far fewer internal states per external state than previously found in Haemophilus influenzae, indicating a more rigid metabolic network. Second, the degree of pathway redundancy in H. pylori was essentially the same for the production of individual amino acids and linked amino acid sets, but was approximately twice that of the production of the ribonucleotides. Third, the metabolic network of H. pylori was unable to achieve extensive conversion of amino acids consumed to the set of either nonessential amino acids or ribonucleotides and thus diverted a large portion of its nitrogen to ammonia production, a potentially important result for pH regulation in its acidic habitat. Genome-scale extreme pathways elucidate emergent system-wide properties. Extreme pathway analysis is emerging as a potentially important method to analyze the link between the metabolic genotype and its phenotypes.