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首页> 外文期刊>The FEBS journal >Prediction of missing enzyme genes in a bacterial metabolic network - Reconstruction of the lysine-degradation pathway of Pseudomonas aeruginosa
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Prediction of missing enzyme genes in a bacterial metabolic network - Reconstruction of the lysine-degradation pathway of Pseudomonas aeruginosa

机译：细菌代谢网络中缺失酶基因的预测-铜绿假单胞菌赖氨酸降解途径的重建

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摘要

The metabolic network is an important biological network which consists of enzymes and chemical compounds. However, a large number of metabolic pathways remains unknown, and most organism-specific metabolic pathways contain many missing enzymes. We present a novel method to identify the genes coding for missing enzymes using available genomic and chemical information from bacterial genomes. The proposed method consists of two steps: (a) estimation of the functional association between the genes with respect to chromosomal proximity and evolutionary association, using supervised network inference; and (b) selection of gene candidates for missing enzymes based on the original candidate score and the chemical reaction information encoded in the EC number. We applied the proposed methods to infer the metabolic network for the bacteria Pseudomonas aeruginosa from two genomic datasets: gene position and phylogenetic profiles. Next, we predicted several missing enzyme genes to reconstruct the lysine-degradation pathway in P. aeruginosa using EC number information. As a result, we identified PA0266 as a putative 5-aminovalerate aminotransferase (EC 2.6.1.48) and PA0265 as a putative glutarate semialdehyde dehydrogenase (EC 1.2.1.20). To verify our prediction, we conducted biochemical assays and examined the activity of the products of the predicted genes, PA0265 and PA0266, in a coupled reaction. We observed that the predicted gene products catalyzed the expected reactions; no activity was seen when both gene products were omitted from the reaction.
机译：代谢网络是一种重要的生物网络，由酶和化合物组成。但是，仍然不清楚大量的代谢途径，并且大多数特定于生物的代谢途径都包含许多缺失的酶。我们提供了一种新颖的方法，可使用细菌基因组中可用的基因组和化学信息来鉴定编码缺失酶的基因。所提出的方法包括两个步骤：（a）使用监督网络推论来估计基因之间关于染色体邻近性和进化关联的功能关联; （b）根据原始候选评分和以EC号编码的化学反应信息选择缺失酶的基因候选。我们应用提出的方法从两个基因组数据集推断铜绿假单胞菌细菌的代谢网络：基因位置和系统发育谱。接下来，我们使用EC号信息预测了几种缺失的酶基因来重建铜绿假单胞菌的赖氨酸降解途径。结果，我们将PA0266确定为推定的5-氨基戊酸氨基转移酶（EC 2.6.1.48），将PA0265确定为假定的戊二酸半醛脱氢酶（EC 1.2.1.20）。为了验证我们的预测，我们进行了生化分析，并在偶联反应中检查了预测基因PA0265和PA0266的产物活性。我们观察到预测的基因产物催化了预期的反应。当两个基因产物从反应中省略时，没有看到活性。

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