Genome-scale model for Clostridium acetobutylicum: Part I. Metabolic network resolution and analysis.
Genome-scale model for Clostridium acetobutylicum: Part I. Metabolic network resolution and analysis.
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DOI：
10.1002/bit.22010
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发表时间：
2008-12-01
影响因子：
3.8
通讯作者：
Papoutsakis, Eleftherios T.
中科院分区：
文献类型：
--
作者：
Senger, Ryan S.;Papoutsakis, Eleftherios T.
利用一种新的半自动逆向工程算法对乙酰丁基梭菌(ATCC 824)进行了基因组规模的代谢网络重建。该网络由参与552个反应的422个胞内代谢物组成，包括80个膜转运反应。代谢网络说明了梭状芽孢杆菌对尿素循环、细胞内L-谷氨酸溶质库以及乙酰鸟氨酸转氨酶从2-氧戊二酸前体生物合成氨基酸的依赖。半自动逆向工程算法确定了反应网络数据库中的差异，这些差异是全自动网络构建算法的主要障碍。拟议的半自动方法允许保存独特的梭状芽胞杆菌代谢途径，例如不完整的三氯乙酸循环。热力学分析被用来确定所提出的途径(例如，反向部分TCA循环和反向精氨酸生物合成途径)在何种生理条件下是可行的。重建的代谢网络被用来创建基因组规模的模型，该模型正确地描述了丁酸激酶基因敲除和溶血生成M5 pSOL1巨质粒退化菌株的特征。进行了系统的基因敲除模拟，以确定一组编码对硅藻生长至关重要的梭状芽胞杆菌酶的基因。
A genome-scale metabolic network reconstruction for Clostridium acetobutylicum (ATCC 824) was carried out using a new semi-automated reverse engineering algorithm. The network consists of 422 intracellular metabolites involved in 552 reactions and includes 80 membrane transport reactions. The metabolic network illustrates the reliance of clostridia on the urea cycle, intracellular l-glutamate solute pools, and the acetylornithine transaminase for amino acid biosynthesis from the 2-oxoglutarate precursor. The semi-automated reverse engineering algorithm identified discrepancies in reaction network databases that are major obstacles for fully automated network-building algorithms. The proposed semi-automated approach allowed for the conservation of unique clostridial metabolic pathways, such as an incomplete TCA cycle. A thermodynamic analysis was used to determine the physiological conditions under which proposed pathways (e.g., reverse partial TCA cycle and reverse arginine biosynthesis pathway) are feasible. The reconstructed metabolic network was used to create a genome-scale model that correctly characterized the butyrate kinase knock-out and the asolventogenic M5 pSOL1 megaplasmid degenerate strains. Systematic gene knock-out simulations were performed to identify a set of genes encoding clostridial enzymes essential for growth in silico.
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代谢组数据与代谢网络的集成揭示了报告基因反应。
影响因子：
9.9
作者：
Cakir, Tunahan;Patil, Kiran Raosaheb;Onsan, Zeynep iIsen;Ulgen, Kutlu Ozergin;Kirdar, Betul;Nielsen, Jens
通讯作者：
Nielsen, Jens
影响因子：
4
作者：
Atrih, A;Foster, SJ
通讯作者：
Foster, SJ
DOI：
10.1099/00221287-67-1-33
发表时间：
1971-01-01
期刊：
JOURNAL OF GENERAL MICROBIOLOGY
影响因子：
--
作者：
CUMMINS, CS;JOHNSON, JL
通讯作者：
JOHNSON, JL
影响因子：
4.1
作者：
Desai, RP;Nielsen, LK;Papoutsakis, ET
通讯作者：
Papoutsakis, ET
影响因子：
3.2
作者：
GIRBAL, L;SOUCAILLE, P
通讯作者：
SOUCAILLE, P