A review of genome-scale metabolic flux modeling of anaerobiosis in biotechnology

被引:11
|
作者
Senger, Ryan S. [1 ]
Yen, Jiun Y. [1 ]
Fong, Stephen S. [2 ]
机构
[1] Virginia Tech, Dept Biol Syst Engn, Blacksburg, VA 24061 USA
[2] Virginia Commonwealth Univ, Dept Chem & Life Sci Engn, Richmond, VA USA
基金
美国国家科学基金会;
关键词
IN-SILICO ANALYSIS; SACCHAROMYCES-CEREVISIAE; KLEBSIELLA-OXYTOCA; ESCHERICHIA-COLI; RECONSTRUCTION; ACID; GENERATION; CONVERSION;
D O I
10.1016/j.coche.2014.08.003
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
The genome-scale metabolic flux modeling of anaerobic metabolism relevant to biotechnology has recently expanded in focus. In particular, there is interest in modeling facultative anaerobes (including yeast) to learn how to effectively eliminate microaerobic environments in favor of anaerobiosis. This is advantageous to bioprocessing and maximizes product formation from metabolic pathways that require substantial reducing power. Recent modeling efforts have also focused on CO/CO2 and lignocellulosic sugar utilization for the production of advanced biofuels and chemicals. Several genome-scale models (GEMs), representing diverse metabolic traits, now exist for the non-pathogenic clostridia, methanogen, and Geobacter spp. obligate anaerobes, and microbial consortia interactions are now being modeled. Several new modeling tools to automate GEM construction, incorporate -omics datasets, and derive metabolic engineering strategies can now apply to anaerobiosis.
引用
收藏
页码:33 / 42
页数:10
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