[1] BAILEY J E. Toward a science of metabolic engineering.[J]. Science,1991,252(5013):1668-1675.
[2] 赵学明,陈涛,王智文. 代谢工程[M]. 北京:高等教育出版社,2015. ZHAO X M,CHEN T,WANG Z W. Metabolic engineering[M]. Beijing:Higher Education Press,2015.
[3] 郝彤,马红武,赵学明. 基因组尺度代谢网络自动重构及分析工具研究进展[J]. 生物工程学报,2012,28(6):661-670. HAO T,MA H W,ZHAO X M. Progress in automatic reconstruction and analysis tools of genome-scale metabolic network[J]. Chinese Journal of Biotechnology,2012,28(6):661-670.
[4] KING Z A,LU J,DRÄGER A,et al. BiGG models:a platform for integrating,standardizing and sharing genome-scale models[J]. Nucleic Acids Research,2016,44(D1):D515-D522.
[5] MORETTI S,MARTIN O,VAN DU TRAN T,et al. MetaNetX/MNXref——reconciliation of metabolites and biochemical reactions to bring together genome-scale metabolic networks[J]. Nucleic Acids Research,2016,44(D1):D523-D526.
[6] KIM W J,KIM H U,LEE S Y. Current state and applications of microbial genome-scale metabolic models[J]. Current Opinion in Systems Biology,2017,2:9-17.
[7] 李培顺,马红武,赵学明,等. 基于代谢网络预测菌种基因改造靶点方法的研究进展[J]. 生物工程学报,2016,32(1):1-13. LI P S,MA H W,ZHAO X M,et al. Predicting genetic modification targets based on metabolic network analysis:a review[J]. Chinese Journal of Biotechnology,2016,32(1):1-13.
[8] JIAN X,ZHOU S,ZHANG C,et al. In silico identification of gene amplification targets based on analysis of production and growth coupling[J]. Biosystems,2016,145:1-8.
[9] LIN Z Q,ZHANG Y,YUAN Q Q,et al. Metabolic engineering of Escherichia coli for poly(3-hydroxybutyrate) production viathreonine bypass[J]. Microbial Cell Factories,2015,14(1):185.
[10] EDWARDS J S,PALSSON B O. Systems properties of the Haemophilus influenzae Rd metabolic genotype[J]. Journal of Biological Chemistry,1999,274(25):17410-17416.
[11] EDWARDS J S,PALSSON B O. The Escherichia coli MG1655 in silico metabolic genotype?:its definition,characteristics,and capabilities[J]. Proceedings of the National Academy of Sciences,2000,97:5528-5533.
[12] FÖRSTER J,FAMILI I,FU P,et al. Genome-scale reconstruction of the Saccharomyces cerevisiae metabolic network[J]. Genome Research,2003,13(2):244-253.
[13] OH Y-K,PALSSON B O,PARK S M,et al. Genome-scale reconstruction of metabolic network in Bacillus subtilis based on high-throughput phenotyping and gene essentiality data[J]. Journal of Biological Chemistry,2007,282(39):28791-28799.
[14] CHOI H S,LEE S Y,KIM T Y,et al. In silico identification of gene amplification targets for improvement of lycopene production[J]. Applied and Environmental Microbiology,2010,76(10):3097-3105.
[15] MOON S Y,HONG S H,KIM T Y,et al. Metabolic engineering of Escherichia colifor the production of malic acid[J]. Biochemical Engineering Journal,2008,40(2):312-320.
[16] FONG S S,BURGARD A P,HERRING C D,et al. In silico design and adaptive evolution of Escherichia coli for production of lactic Bcid[J]. Biotechnology and Bioengineering,2005,91(5):643-648.
[17] PARK J H,LEE K H,KIM T Y,et al. Metabolic engineering of Escherichia coli for the production of L-valine based on transcriptome analysis and in silico gene knockout simulation[J]. Proceedings of the National Academy of Sciences,2007,104(19):7797-7802.
[18] XU P,RANGANATHAN S,FOWLER Z L,et al. Genome-scale metabolic network modeling results in minimal interventions that cooperatively force carbon flux towards malonyl-CoA[J]. Metabolic Engineering,2011,13(5):578-587.
[19] BOGHIGIAN B A,ARMANDO J,SALAS D,et al. Computational identification of gene over-expression targets for metabolic engineering of taxadiene production[J]. Applied Microbiology and Biotechnology,2012,93(5):2063-2073.
[20] CHOON Y W,MOHAMAD M S,DERIS S. A hybrid of bees algorithm and flux balance analysis(BAFBA) for the optimisation of microbial strains[J]. International Journal of Data Mining and Bioinformatics,2014,10(2):225-238.
[21] HAKIM A,SALLEH M,MOHAMAD M S,et al. Gene knockout identification for metabolite production improvement using a hybrid of genetic ant colony optimization and flux balance analysis[J]. Biotechnology and Bioprocess Engineering,2015,20(4):685-693.
[22] CHUA P S,SALLEH A H M,MOHAMAD M S,et al. Identifying a gene knockout strategy using a hybrid of the bat algorithm and flux balance analysis to enhance the production of succinate and lactate in Escherichia coli[J]. Biotechnology and Bioprocess Engineering,2015,20(2):349-357.
[23] BRO C,REGENBERG B,FÖRSTER J,et al. In silico aided metabolic engineering of Saccharomyces cerevisiae for improved bioethanol production[J]. Metabolic Engineering,2006,8(2):102-111.
[24] HJERSTED J L,HENSON M A. Steady-state and dynamic flux balance analysis of ethanol production by Saccharomyces cerevisiae[J]. IET Systems Biology,2009,3(3):167-179.
[25] HANLY T J,HENSON M A. Dynamic model-based analysis of furfural and HMF detoxification by pure and mixed batch cultures of S. cerevisiae and S. stipitis[M]. Biotechnology and Bioengineering,2014,111(2):272-284.
[26] ASADOLLAHI M A,MAURY J,PATIL K R,et al. Enhancing sesquiterpene production in Saccharomyces cerevisiaethrough in silico driven metabolic engineering[J]. Metabolic Engineering,2009,11(6):328-334.
[27] AGREN R,OTERO J M,NIELSEN J. Genome-scale modeling enables metabolic engineering of Saccharomyces cerevisiae for succinic acid production[J]. Journal of Industrial Microbiology & Biotechnology,2013,40(7):735-747.
[28] BROCHADO A R,MATOS C,MØLLER B L,et al. Improved vanillin production in baker's yeast through in silico design[J]. Microbial Cell Factories,2010,9(1):84.
[29] AZHAR A H,MOHAMAD M S,DERIS S. A hybrid of ant colony optimization and flux variability analysis to improve the production of L-phenylalanine and biohydrogen[J]. International Journal of Advances in Soft Computing & Its Applications,2016,8(2):161-180.
[30] LU S J,SALLEH A H M,MOHAMAD M S,et al. Identification of gene knockout strategies using a hybrid of an ant colony optimization algorithm and flux balance analysis to optimize microbial strains[J]. Computational Biology and Chemistry,2014,53:175-183.
[31] YIN L H,CHOON Y W,MOHAMAD M S,et al. Prediction of vanillin and glutamate productions in yeast using a hybrid of continuous bees algorithm and flux balance analysis (CBAFBA)[J]. Current Bioinformatics,2014,9(3):284-294.
[32] THIELE I,PALSSON B Ø. A protocol for generating a high-quality genome-scale metabolic reconstruction[J]. Nature Protocols,2010,5(1):93-121.
[33] HENRY C S,DEJONGH M,BEST A a,et al. High-throughput generation,optimization and analysis of genome-scale metabolic models.[J]. Nature Biotechnology,2010,28(9):977-982.
[34] AGREN R,LIU L,SHOAIE S,et al. The RAVEN toolbox and its use for generating a genome-scale metabolic model for Penicillium chrysogenum[J]. PLoS Computational Biology,2013,9(3):e1002980.
[35] DIAS O,ROCHA M,FERREIRA E C,et al. Reconstructing genome-scale metabolic models with Merlin[J]. Nucleic Acids Research,2015,43(8):3899-3910.
[36] ORTH J D,THIELE I,PALSSON B Ø. What is flux balance analysis?[J]. Nature Biotechnology,2010,28(3):245-248.
[37] MAHADEVAN R,SCHILLING C H. The effects of alternate optimal solutions in constraint-based genome-scale metabolic models[J]. Metabolic Engineering,2003,5(4):264-276.
[38] SEGRÈ D,VITKUP D,CHURCH G M. Analysis of optimality in natural and perturbed metabolic networks[J]. PNAS,2002,99(23):15112-15117.
[39] BURGARD A P,PHARKYA P,MARANAS C D. OptKnock?:a bilevel programming framework for identifying gene knockout strategies for microbial strain optimization[J]. Biotechnology and Bioengineering,2003,84(6):647-657.
[40] BECKER S A,FEIST A M,MO M L,et al. Quantitative prediction of cellular metabolism with constraint-based models:the COBRA toolbox[J]. Nat. Protocols,2007,2(3):727-738.
[41] SCHELLENBERGER J,QUE R,FLEMING R M T,et al. Quantitative prediction of cellular metabolism with constraint-based models:the cobra toolbox v2.0.[J]. Nature Protocols,2011,6(9):1290-1307.
[42] EBRAHIM A,LERMAN J A,PALSSON B O,et al. Cobrapy:constraints-based reconstruction and analysis for python[J]. BMC Systems Biology,2013,7(1):74.
[43] MÜLLER S,CERDAN R,RADULESCU O. Understanding protozoan parasite metabolism and identifying drug targets through constraint-based modeling[M]//Comprehensive Analysis of Parasite Biology:From Metabolism to Drug Discovery. New York:John Wiley & Sons,2016:487-512.
[44] ZUÑIGA C,LI C T,HUELSMAN T,et al. Genome-scale metabolic model for the green alga Chlorella vulgaris UTEX 395 accurately predicts phenotypes under autotrophic,heterotrophic,and mixotrophic growth conditions[J]. Plant Physiology,2016,172(1):589-602.
[45] YUAN Q,HUANG T,LI P,et al. Pathway-consensus approach to metabolic network reconstruction for Pseudomonas putidaKT2440 by systematic comparison of[J]. PLoS One,2017,12(1):1-19.
[46] HERRGÅRD M J,SWAINSTON N,DOBSON P,et al. A consensus yeast metabolic network reconstruction obtained from a community approach to systems biology[J]. Nature Biotechnology,2008,26(10):1155-1160.
[47] THIELE I,HYDUKE D R,STEEB B,et al. A community effort towards a knowledge-base and mathematical model of the human pathogen Salmonella TyphimuriumLT2.[J]. BMC Systems Biology,2011,5(1):8.
[48] THIELE I,SWAINSTON N,FLEMING R M T,et al. A community-driven global reconstruction of human metabolism[J]. Nature Biotechnology,2013,31(5):419-425.
[49] DOBSON P D,SMALLBONE K,JAMESON D,et al. Further developments towards a genome-scale metabolic model of yeast[J]. BMC Systems Biology,2010,4(1):145.
[50] GANTER M,BERNARD T,MORETTI S,et al. MetaNetX.org:a website and repository for accessing,analysing and manipulating metabolic networks[J]. Bioinformatics,2013,29(6):815-816.
[51] VAN HECK R G A,GANTER M,MARTINS DOS SANTOS V A P,et al. Efficient reconstruction of predictive consensus metabolic network models[J]. PLoS Computational Biology,2016,12(8):e1005085.
[52] ZHANG X,TERVO C J,REED J L. Metabolic assessment of E. coli as a biofactory for commercial products[J]. Metabolic Engineering,2016,35:64-74.
[53] CHATSURACHAI S,FURUSAWA C,SHIMIZU H. An in silico platform for the design of heterologous pathways in nonnative metabolite production[J]. BMC Bioinformatics,2012,13(1):1-11
[54] CHATSURACHAI S,FURUSAWA C,SHIMIZU H. Art path design:rational heterologous pathway design system for the production of nonnative metabolites[J]. Journal of Bioscience and Bioengineering,2013,116(4):524-527.
[55] HIRASAWA T,IDA Y,FURUASAWA C,et al. Potential of a Saccharomyces cerevisiae recombinant strain lacking ethanol and glycerol biosynthesis pathways in efficient anaerobic bioproduction[J]. Bioengineered,2014,5(2):123-128.
[56] BAR-EVEN A,NOOR E,LEWIS N N E,et al. Design and analysis of synthetic carbon fixation pathways[J]. Proceedings of the National Academy of Sciences of the United States of America,2010,107(19):8889-8894.
[57] ANTONOVSKY N,GLEIZER S,NOOR E,et al. Sugar synthesis from CO2 in Escherichia coli[J]. Cell,2016,166(1):115-125.
[58] BOGORAD I W,LIN T S,LIAO J C. Synthetic non-oxidative glycolysis enables complete carbon conservation[J]. Nature,2013,502(7473):693-697.
[59] YANG X,YUAN Q,ZHENG Y,et al. An engineered non-oxidative glycolysis pathway for acetone production in Escherichia coli[J]. Biotechnology Letters,2016,38(8):1359-1365.
[60] MEADOWS A L,HAWKINS K M,TSEGAYE Y,et al. Rewriting yeast central carbon metabolism for industrial isoprenoid production[J]. Nature,2016,537(7622):694-697.
[61] BURGARD A P,MARANAS C D. Probing the performance limits of the escherichia coli metabolic network subject to gene additions or deletions[J]. Biotechnology and Bioengineering,2001,74(5):364-375.
[62] PHARKYA P,BURGARD A P,MARANAS C D. Opt strain?:a computational framework for redesign of microbial production systems[J]. Genome Research,2004,14(11):2367-2376.
[63] KIM J,REED J L,MARAVELIAS C T. Large-scale Bi-level strain design approaches and mixed-integer programming solution techniques[J]. PLoS One,2011,6(9):e24162.
[64] MARTÍNEZ V S,QUEK L-E,NIELSEN L K. Network thermodynamic curation of human and yeast genome-scale metabolic models[J]. Biophysical Journal,2014,107(2):493-503.
[65] PRIGENT S,FRIOUX C,DITTAMI S M,et al. Meneco,a topology-based gap-filling tool applicable to degraded genome-wide metabolic networks[J]. PLoS Computational Biology,2017,13(1):e1005276. |