系统生物学水平解析维生素C生产菌株生理特性与相互作用关系
详细信息    本馆镜像全文|  推荐本文 |  |   获取CNKI官网全文
摘要
本论文以维生素C工业生产菌株生酮基古龙酸菌(Ketogulonicigenium vulgareWSH001)和巨大芽孢杆菌(Bacillus megaterium WSH002)组成的人工微生物生态系统为研究对象,结合目前关于两菌生理生化水平和组学水平(基因组学、蛋白组学、代谢组学)研究结果,通过构建基因组规模代谢网络模型(Genome scale metabolic model, GSMM)和基于约束的算法(constraints-based methods),从系统生物学水平解析K. vulgare的生理特性及其与B. megaterium之间的相互作用机制,主要研究结果如下:
     1.基于RAST、KAAS、PRIAM、本地BLASTp注释K. vulgare基因组,共有834个蛋白注释出EC号且具有较高可信度。根据KAAS和本地BLASTp搜索TCDB数据库注释K. vulgare基因组共预测476个转运蛋白。基于本地BLASTp和比较基因组学显示K. vulgare RAST新注释的231个蛋白中186个具有功能注释或在K. vulgareY25中存在对应同源蛋白;B. megaterium RAST新注释的219个蛋白中153个具有功能注释或在B. megaterium QM B1551或DSM319中存在对应同源蛋白;
     2.通过代谢网络自动构建服务器Model SEED与KAAS,结合文献调研K. vulgare相关的生化信息、公共数据库、已报道实验结果等构建了K. vulgare的GSMM,命名为iWZ663,该模型包含663个基因、649个代谢物和830个反应。模型iWZ663中基因覆盖率达21.4%,反应可分为14个代谢亚系统,其中转运系统、碳水化合物代谢、氨基酸代谢所占比例最大,分别为16.5%、15.3%、15.2%;代谢物中与能量相关(ATP、ADP、NADP、NADPH、NAD、NADH)和氮代谢相关(谷氨酸、胺离子、甘氨酸)的代谢物在网络中占较大的连通度。模型注释K. vulgare山梨糖代谢途径发现山梨糖不仅可以转化成2-KLG或维生素C,也可进入中心碳代谢,为细胞生长提供能量和骨架;
     3.运用基于约束的算法结合Cobra工具箱在MATLAB平台上对K. vulgare GSMMiWZ663系统分析,发现模型iWZ663中116个基因被预测为生长必需基因,且均位于染色体上;153个反应被预测为生长必需反应。K. vulgare单独生长微弱的原因在于:(1)天冬酰胺、半胱氨酸、甲硫氨酸、生物素、烟酸、焦磷酸硫胺素、二氢叶酸的合成途径不完整;(2) K. vulgare代谢山梨糖主要通过ED (Entner-Doudoroff)途径和戊糖磷酸途径而不是酵解途径,其中戊糖磷酸途径流量仅占碳流的5.7%,低水平的戊糖磷酸途径影响细胞还原力(NADPH)和碳骨架(戊糖等)的供给;(3) K. vulgare不能还原硫酸盐生成亚硫酸盐,阻碍了半胱氨酸和甲硫氨酸的合成并进一步影响胞内辅酶A和谷胱甘肽的合成。K. vulgare具有强大的多肽转运和水解能力,K. vulgare能代谢天冬酰胺、天冬氨酸、谷氨酸、谷氨酰胺、甘氨酸、丙氨酸、脯氨酸、丝氨酸、苏氨酸参与TCA循环或核苷酸代谢;
     4.整合RAST新注释基因、代谢组学数据、碳氮源生长数据、亚细胞定位信息,将前期实验室构建的B. megaterium代谢网络模型iMZ992精炼升级为iMZ1055,该模型包含1055个基因、1137个代谢反应、1011个代谢物。统一K. vulgare与B. megateriumGSMM格式得到修饰后的两菌模型iWZ663a和iMZ1055a,二者共有453个反应和548代谢物相同。比较两菌GSMMs发现iMZ1055a的代谢能力更为多样,表现在:(1)具有15个特有的代谢亚系统而iWZ663a只有一个;(2)相比于iWZ663a,在组氨酸代谢、缬氨酸、亮氨酸和异亮氨酸生物合成、丙氨酸、天冬氨酸和谷氨酸代谢、核黄素代谢中也具备特殊的代谢功能;(3)必需反应分析显示iWZ663a中必需反应所占模型总反应比例是iMZ1055a的2倍多,iMZ1055a有51个非必需共有反应在iWZ663a是必需的,主要分布在嘌呤代谢、嘧啶代谢、核黄素代谢、泛酸与辅酶A生物合成等;(4) iMZ1055a可以合成并转运到胞外的代谢物有78种,而iWZ663a仅能合成和分泌22种代谢物。另外两者GSMMs在果糖与甘露糖代谢、泛醌与其他类萜醌生物合成、硫代谢和苯甲酸降解、转运系统中存在不同的代谢机制;
     5.整合模型iWZ663a和iMZ1055a构建维生素C二步发酵两菌代谢互作模型,命名为iWZ-KV-663-BM-1055,包含1718个基因、1583个代谢物和1910个反应。FBA与鲁棒性分析显示两菌间既存在共生也存在竞争的生理关系。FVA与必需反应分析显示B. megaterium伴生下:42个K. vulgare单菌模型时无流量通过的代谢反应有流量通过;36个在K. vulgare单菌模型时的必需反应转变为非必需反应;38个B.megaterium单菌模型中的非必需反应,主要参与合成K. vulgare的必需营养物质如焦磷酸硫胺素、生物素、烟酸、泛酸、二氢叶酸等,可以影响K. vulgare在混菌系统中达到最大生长速率。基于iWZ-KV-663-BM-1055分析两菌相互作用机制为:(1)K. vulgare与B. megaterium之间的相互作用主要通过胞外代谢物和反应相联系;(2)B. megaterium分泌23种代谢物到K. vulgare,其中15种营养物质K. vulgare自身也能合成;(3) K. vulgare自身的多数氨基酸、维生素和辅酶的合成途径无流量通过,但不同核苷酸之间的回补反应、亮氨酸、异亮氨酸、缬氨酸、脯氨酸的合成却有流量通过;(4)两菌代谢相互作用受两菌转运系统注释水平的影响。
This dissertation focuses on the elucidation of physiological chrateristics and interactionof an artificial microbial ecosystem (AME) consisting of Ketogulonicigenium vulgare andBacillus megaterium, which was used in the vitamin C industrial production. This can berealized by reconstruction of genome scale metabolic model (GSMM) of these two bacteriaon the basis of information of biochemical and omics studies (such as genomics, proteomics,metabolomics). With GSMMs, constraints-based methods can be used to investigate thephysiological features and ineractions with B. megaterium. The main results are as follows:
     1. The genome of K. vulgare WSH001was annotated by four approaches: RAST, KAAS,PRIAM, and a local sequence similarity search (BLASTp) of UniProtKB/Swiss-Protdatabase. Totally,834proteins were annotated and assigned with an EnzymeCommission (EC) number, which can be further used in the metabolic reconstruction.For transport proteins, KAAS annotation and a BLASTp with TCDB database wereperformed and476transportors were annotated. In addition, new annotated genesidentified during the RAST annotation were rechecked by a BLASTp ofUniProtKB/Swiss-Prot database and a comparative genomics analysis:186genes out of231new genes in K. vulgare and153genes out of219new genes in B. megaterium wereproved because of a high similarity or having homologous protein(s) in other strains ofits species.
     2. We constructed the GSMM of K. vulgare, iWZ663, on the basis of Model SEED, KAAS,literature mining, public databases, and experimental data. It consists of663genes,649metabolites and830reactions. The gene coverage of model iWZ663is21.4%. Themodel reactions were divided into14metabolic subsystems, among which Transportingsystem, Carbohydrate metabolism, and Amino acid metabolism occupy the largestproportions:16.5%,15.3%, and15.2%, respectively. Metabolites that associated withenergy generation and nitrogen metabolism have the most extensive connectivities iniWZ663. Annotation of L-sorbose metabolic pathway indicated that L-sorbose can notonly be converted into2-KLG or vitamin C, but also enter into the central carbonmetabolism for the production of energy and biomass precursors.
     3. Model iWZ663was comprehensive analyzed with Cobra toolbox on MATLAB. Essentialgene analysis was performed and116genes were predicted to be essential, and all theessential genes are located on chromosome. In addition,153reactions were predicted asessential reactions. Flux balance analysis (FBA) was carried out to investigate thereasons for the poor growth of K. vulgare, and three main reasons were included:(1) K.vulgare could not de novo biosynthesize asparigine, L-cysteine, L-methionine, biotin,nicotinate, thiamine diphosphate, and dihydrofolate (DHF);(2) the carbon flux mainlyenter into the ED pathway and only5.7%into the PP pathway, resulting a lower level ofreducing power (NADPH) and shortage of carbon backbones such as ribose;(3) thedefect in sulfate metabolism hampering the syntheses of L-cysteine, L-methionine,coenzyme A (CoA), and glutathione. Meanwhile, K. vulgare has aboundant peptide transportors and peptidase and was capable of assimilating L-asparagine, L-aspartic acid,L-glutamic acid, L-glutamine, glycine, L-alanine, L-proline, L-serine, and L-threonineinto TCA cycle or purine metabolism.
     4. The previous B. megaterium GSMM iMZ992was reifined by integrating the informationof RAST new annotations, metabolomics data, growth phenotype data on differentcarbon and nitrogen sources, and protein sublocation information. The new model namediMZ1055, comprised of1055genes,1137reactions, and1011metabolites. Then, the twomodels iMZ1055and iWZ663were reconciled (named iMZ1055a and iWZ663a,respectively) and compared. It was found that they share453reactions and548metabolites. Comparison of the two GSMMs suggested that B. megaterium has a morediversity metabolism, because:(1) iMZ1055a has15unique metabolic subsystems whileiWZ663a has only one;(2) iMZ1055a has some special metabolic functions in Histidinemetabolism, Valine, leucine and isoleucine biosynthesis, Alanine, aspartate andglutamate metabolism, and Riboflavin metabolism;(3) the percentage of essentialreactions in iWZ663a was more than two folds of that in iMZ1055a, and iMZ1055a has51non-essential shared reactions which were essential for. These51reactions mainlydistributed in Purine metabolism, Pyrimidine metabolism, Riboflavin metabolism,Pantothenate and CoA biosynthesis;(4) iMZ1055a could biosynthesize and transport out78metabolites, while K. vulgare only22metabolites. In addition, the two models havedifferent metabolic mechanisms in Fructose and mannose metabolism, Ubiquinone andother terpenoid-quinone biosynthesis, Sulfur metabolism, Benzoate degradation, andTransporting system.
     5. A two-species metabolic interaction model of AME in vitamin C production wasconstructed by integrating iWZ663a and iMZ1055a. The resulted model, namediWZ-KV-663-BM-1055, consists of1718genes,1583metabolites, and1910reactions.FBA and robustness analysis found both mutualism and competition exist between K.vulgare and B. megaterium. Futher, FVA and essential reactions analysis revealed thatwith the companion of B. megaterium: forty-two reactions that could not carry flux iniWZ663a were capable of carrying flux; thirty-three reactions that were essential iniWZ663a became non-essential in iWZ-KV-663-BM-1055; thirty-eight non-essentialreactions in B. megaterium could affect K. vulgare reach its maximum growth rate.Further, analysis of metablic interactions between K. vulgare and B. megaterium shows:(1) metabolism of K. vulgare and B. megterium were connected mainly by extracelluarmetabolites and reactions;(2) B. megaterium could secrets23to K. vulgare, amongwhich15metabolites can be biosynthesized by K. vulgare;(3) most of reactions inamino acids, vitamins and cofactors pathways has no flux, excepting several reactions innucleotide salvage pathway and the biosynthesis of leucine, isoleucine, valine, and proline;(4) predictions of metabolic interaction were affected by the accuracy oftransporter annotations in iWZ-KV-663-BM-1055.
引文
[1] Macauley S, McNeil B, Harvey LM. The genus Gluconobacter and its applications inbiotechnology [J]. Crit Rev Biotechnol,2001,21(1):1-25.
    [2] Bremus C, Herrmann U, Bringer-Meyer S, et al. The use of microorganisms inL-ascorbic acid production [J]. J Biotechnol,2006,124(1):196-205.
    [3] Reichstein T, Grüssner A. Eine ergiebige Synthese der l-Ascorbins ure (C-Vitamin)[J].Helv Chim Acta,1934,17(1):311-328.
    [4] Yin GL, Tao ZX, Yan ZZ, et al. Fermentation process [P]. US Patent,1990,4935359.
    [5] Hancock RD, Viola R. Biotechnological approaches for L-ascorbic acid production [J].Trends Biotechnol,2002,20(7):299-305.
    [6]尹光琳,陶增鑫,于龙华等. L-山梨糖发酵生产维生素C前体—2-酮基-L-古龙酸的研究I.菌种的分离筛选和鉴定[J].微生物学报,1980,20(3):246-251.
    [7] Hancock RD. Recent patents on vitamin C: opportunities for crop improvement andsingle-step biological manufacture [J]. Recent Pat Food Nutr Agric,2009,1(1):39-49.
    [8] Urbance JW, Bratina BJ, Stoddard SF, et al. Taxonomic characterization ofKetogulonigenium vulgare gen. nov., sp. nov. and Ketogulonigenium robustum sp. nov.,which oxidize L-sorbose to2-keto-L-gulonic acid [J]. Int J Syst Evol Microbiol,2001,51(3):1059-1070.
    [9] Asakura A, Hoshino T. Isolation and characterization of a new Quinoproteindehydrogenase, L-sorbose/L-sorbosone dehydrogenase [J]. Biosci BiotechnolBiochem,1999,63(1):46-53.
    [10] Sugisawa T, Miyazaki T, Hoshino T. Microbial production of L-ascorbic acid fromD-sorbitol, L-sorbose, L-gulose, and L-sorbosone by Ketogulonicigenium vulgareDSM4025[J]. Biosci Biotechnol Biochem,2005,69(3):659-662.
    [11] Miyazaki T, Sugisawa T, Hoshino T. Pyrroloquinoline quinone-dependentdehydrogenases from Ketogulonicigenium vulgare catalyze the direct conversion ofL-sorbosone to L-ascorbic acid [J]. Appl Environ Microbiol,2006,72(2):1487-1495.
    [12]谢莉,张铎,窦燕峰等.醇醛脱氢酶的分离纯化及其基因文库的构建和筛选[J].生物工程学报,2007,23(5):891-895.
    [13] Hoshino T, Shinjoh M. Process for producing L-ascorbic acid [P]. US Patent,2005,20050244940.
    [14] Leduc S, de Troostembergh JC, Lebeault JM. Folate requirements of the2-keto-L-gulonic acid-producing strain Ketogulonigenium vulgare LMP P-20356inL-sorbose/CSL medium [J]. Appl Microbiol Biotechnol,2004,65(2):163-167.
    [15]尹光琳,何建明,任双喜等.新组合菌系SCB329-SCB933利用L-山梨糖发酵产生维生素C前体—2-酮基-L-古龙酸的研究[J].工业微生物,1997,27(1):1-7.
    [16] Vary PS. Prime time for Bacillus megaterium [J]. Microbiology,1994,140:1001-1013.
    [17] Vary PS, Biedendieck R, Fuerch T, et al. Bacillus megaterium from simple soilbacterium to industrial protein production host [J]. Appl Microbiol Biotechnol,2007,76(5):957-967.
    [18] Przybulewska K, Wieczorek A, Nowak A. Isolation of microorganisms capable ofstyrene degradation [J]. Pol J Environ Stud,2006,15(5):777-783.
    [19] Crawford RL. Degradation of3-hydroxybenzoate by bacteria of the genus Bacillus [J].Appl Microbiol,1975,30(3):439-444.
    [20] Homann A, Biedendieck R, Goetze S, et al. Insights into polymer versusoligosaccharide synthesis: mutagenesis and mechanistic studies of a novellevansucrase from Bacillus megaterium [J]. Biochem J,2007,407:189-198.
    [21] Pueyo MT, Bloch C, Jr., Carmona-Ribeiro AM, et al. Lipopeptides produced by a soilBacillus megaterium strain [J]. Microb Ecol,2009,57(2):367-378.
    [22] Biedendieck R, Malten M, Barg H, et al. Metabolic engineering of cobalamin (vitaminB(12)) production in Bacillus megaterium [J]. Microb Biotechnol,2010,3(1):24-37.
    [23] Morita M, Tomita K, Ishizawa M, et al. Cloning of oxetanocin A biosynthetic andresistance genes that reside on a plasmid of Bacillus megaterium strain NK84-0128[J].Biosci Biotechnol Biochem,1999,63(3):563-566.
    [24] Vary P. Development of genetic engineering in Bacillus megaterium [J].Biotechnology,1992,22:251-310.
    [25] Yang Y, Malten M, Grote A, et al. Codon optimized Thermobifida fusca hydrolasesecreted by Bacillus megaterium [J]. Biotechnol Bioeng,2007,96(4):780-794.
    [26] Marina Pinotti L, Ribeiro de Souza V, de Campos Giordano R, et al. The penicillin Gacylase production by B. megaterium is amino acid consumption dependent [J].Biotechnol Bioeng,2007,97(2):346-353.
    [27] Vihinen M, Mantsala P. Microbial amylolytic enzymes [J]. Crit Rev Biochem MolBiol,1989,24(4):329-418.
    [28]冯树,孙传宝,张忠泽等.维生素C二步发酵中巨大芽抱杆菌对氧化葡萄糖酸杆菌生长和产酸的影响[J].微生物学杂志,1998,18(1):6-9.
    [29] Zhang J, Liu J, Shi ZP, et al. Manipulation of B. megaterium growth for efficient2-KLG production by K. vulgare [J]. Process Biochem,2010,45(4):602-606.
    [30] Ma Q, Zhou J, Zhang W, et al. Integrated proteomic and metabolomic analysis of anartificial microbial community for two-step production of vitamin C [J]. PLoS ONE,2011,6(10):e26108.
    [31] Takagi Y, Sugisawa T, Hoshino T. Continuous2-Keto-L-gulonic acid fermentation bymixed culture of Ketogulonicigenium vulgare DSM4025and Bacillus megaterium orXanthomonas maltophilia [J]. Appl Microbiol Biotechnol,2010,86(2):469-480.
    [32]吕群燕,王书锦,潘霞明. L-山梨糖发酵生产2-酮基-L-古龙酸的最佳组合新菌系的生物特性的研究[J].生物技术,1994,4(6):23-27.
    [33]仲崇斌,于海,吕主奎等.维生素C二步发酵的新组合菌系[J].生物技术,2001,11(2):25-27.
    [34] Liu L, Chen K, Zhang J, et al. Gelatin enhances2-keto-l-gulonic acid productionbased on Ketogulonigenium vulgare genome annotation [J]. J Biotechnol,2011,156(3):182-187.
    [35] Zhu Y, Liu J, Du G, et al. Sporulation and spore stability of Bacillus megateriumenhance Ketogulonigenium vulgare propagation and2-keto-L-gulonic acidbiosynthesis [J]. Bioresour Technol,2012,107:399-404.
    [36]冯树,张舟,张成刚等.混合培养中巨大芽孢杆菌对氧化葡萄糖酸杆菌的作用[J].应用生态学报,2000,11(1):119-122.
    [37]吕淑霞,冯树,张忠泽等. Vc二步发酵中伴生菌的作用机制[J].微生物学通报,2001,28(5):10-13.
    [38]李国才,张忠泽.2-KLG产生菌混合发酵特性及最佳混生模式的研究[J].微生物学杂志,1997,17(2):1-4.
    [39] Zhou J, Ma Q, Yi H, et al. Metabolome profiling reveals metabolic cooperationbetween Bacillus megaterium and Ketogulonicigenium vulgare during induced swarmmotility [J]. Appl Environ Microbiol,2011,77(19):7023-7030.
    [40] Raes J, Bork P. Molecular eco-systems biology: towards an understanding ofcommunity function [J]. Nat Rev Microbiol,2008,6(9):693-699.
    [41] Roling WFM, Ferrer M, Golyshin PN. Systems approaches to microbial communitiesand their functioning [J]. Curr Opin Biotechnol,2010,21(4):532-538.
    [42]张静.基于生化策略与组学技术的维生素C生产菌株间生理关系解析[D]:[博士学位论文].无锡:江南大学生物工程学院,2010.
    [43] Ma Q, Zhang W, Zhang L, et al. Proteomic analysis of Ketogulonicigenium vulgareunder glutathione reveals high demand for thiamin transport and antioxidantprotection [J]. PLoS ONE,2012,7(2):e32156.
    [44] Du J, Zhou J, Xue J, et al. Metabolomic profiling elucidates community dynamics ofthe Ketogulonicigenium vulgare-Bacillus megaterium consortium [J]. Metabolomics,2012,8(5):960-973.
    [45] Zhou J, Yi H, Wang L, et al. Metabolomic analysis of the positive effects onKetogulonigenium vulgare growth and2-keto-L-gulonic acid production by reducedglutathione [J]. OMICS,2012,16(7-8):387-396.
    [46] Liu L, Li Y, Zhang J, et al. Complete genome sequence of the industrial strainKetogulonicigenium vulgare WSH-001[J]. J Bacteriol,2011,193(21):6108-6109.
    [47] Liu L, Li Y, Zhang J, et al. Complete genome sequence of the industrial strain Bacillusmegaterium WSH-002[J]. J Bacteriol,2011,193(22):6389-6390.
    [48] Dejonghe W, Berteloot E, Goris J, et al. Synergistic degradation of linuron by abacterial consortium and isolation of a single linuron-degrading Variovorax strain [J].Appl Environ Microbiol,2003,69(3):1532-1541.
    [49]杨帆,贾茜,熊朝晖等.酮古龙酸菌WB0104的全基因组分析[J].科学通报,2006,51(8):923-927.
    [50] Xiong XH, Han S, Wang JH, et al. Complete genome sequence of the bacteriumKetogulonicigenium vulgare Y25[J]. J Bacteriol,2011,193(1):315-316.
    [51] Eppinger M, Bunk B, Johns MA, et al. Genome sequences of the biotechnologicallyimportant Bacillus megaterium strains QM B1551and DSM319[J]. J Bacteriol,2011,193(16):4199-4213.
    [52]朱可丽,张海宏,孙传宝等.维生素C二步发酵混菌接种控制[J].微生物学杂志,1998,18(2):13-15.
    [53]张静,周景文,刘立明等.分阶段pH调控提高2-酮基-L-古龙酸生产[J].生物工程学报,2010,26(9):1263-1268.
    [54]陈克杰,周景文,刘立明等.高渗条件下利用蔗糖提升2-酮基-L-古龙酸生产效率[J].生物工程学报,2010,26(11):1507-1513.
    [55] Cai L, Yuan MQ, Li ZJ, et al. Genetic engineering of Ketogulonigenium vulgare forenhanced production of2-keto-L-gulonic acid [J]. J Biotechnol,2012,157(2):320-325.
    [56] Zhang J, Zhou J, Liu J, et al. Development of chemically defined media supportinghigh cell density growth of Ketogulonicigenium vulgare and Bacillus megaterium [J].Bioresour Technol,2011,102(7):4807-4814.
    [57] Gao Y, Yuan YJ. Comprehensive quality evaluation of corn steep liquor in2-keto-L-gulonic acid fermentation [J]. J Agric Food Chem,2011,59(18):9845-9853.
    [58]陈克杰.基于生理特性解析的2-酮基-L-古龙酸发酵工艺研究[D]:[硕士学位论文].无锡:江南大学生物工程学院,2011.
    [59]李强,刁劲羽,向波涛等.山梨糖发酵产生2-酮基-L-古龙酸氮源代谢规律[J].微生物学报,1996,36(1):19-24.
    [60]魏东芝,袁渭康,尹光琳等.维生素C二步发酵过程动力学模型的研究[J].生物工程学报,1992,8(3):277-282.
    [61] Takagi Y, Sugisawa T, Hoshino T. Continuous2-keto-L-gulonic acid fermentationfrom L-sorbose by Ketogulonigenium vulgare DSM4025[J]. Appl MicrobiolBiotechnol,2009,82(6):1049-1056.
    [62] Feist AM, Herrgard MJ, Thiele I, et al. Reconstruction of biochemical networks inmicroorganisms [J]. Nat Rev Microbiol,2009,7(2):129-143.
    [63] Liu LM, Agren R, Bordel S, et al. Use of genome-scale metabolic models forunderstanding microbial physiology [J]. FEBS Lett,2010,584(12):2556-2564.
    [64] Oberhardt MA, Palsson BO, Papin JA. Applications of genome-scale metabolicreconstructions [J]. Mol Syst Biol,2009,5:320.
    [65] Feist AM, Palsson BO. The growing scope of applications of genome-scale metabolicreconstructions using Escherichia coli [J]. Nat Biotechnol,2008,26(6):659-667.
    [66] Durot M, Bourguignon PY, Schachter V. Genome-scale models of bacterialmetabolism: reconstruction and applications [J]. FEMS Microbiol Rev,2009,33(1):164-190.
    [67] Price ND, Reed JL, Palsson BO. Genome-scale models of microbial cells: Evaluatingthe consequences of constraints [J]. Nat Rev Microbiol,2004,2(11):886-897.
    [68] Zengler K, Palsson BO. A road map for the development of community systems(CoSy) biology [J]. Nat Rev Microbiol,2012,10(5):366-372.
    [69]周冒达.巨大芽孢杆菌WSH-002全基因组规模代谢网络模型的构建与分析[D]:
    [硕士学位论文].无锡:江南大学生物工程学院,2012.
    [70] Ideker T, Galitski T, Hood L. A new approach to decoding life: systems biology [J].Annu Rev Genomics Hum Genet,2001,2:343-372.
    [71] Thiele I, Palsson BO. A protocol for generating a high-quality genome-scale metabolicreconstruction [J]. Nat Protoc,2010,5(1):93-121.
    [72] Siezen RJ, van Hijum SAFT. Genome (re-)annotation and open-source annotationpipelines [J]. Microb Biotechnol,2010,3(4):362-369.
    [73] Henry CS, DeJongh M, Best AA, et al. High-throughput generation, optimization andanalysis of genome-scale metabolic models [J]. Nat Biotechnol,2010,28(9):977-982.
    [74] Moriya Y, Itoh M, Okuda S, et al. KAAS: an automatic genome annotation andpathway reconstruction server [J]. Nucleic Acids Res,2007,35(Web Serverissue):W182-185.
    [75] Bakke P, Carney N, Deloache W, et al. Evaluation of three automated genomeannotations for Halorhabdus utahensis [J]. PLoS ONE,2009,4(7):e6291.
    [76] Altschul SF, Madden TL, Schaffer AA, et al. Gapped BLAST and PSI-BLAST: a newgeneration of protein database search programs [J]. Nucleic Acids Res,1997,25(17):3389-3402.
    [77] Pearson WR, Lipman DJ. Improved tools for biological sequence comparison [J]. ProcNatl Acad Sci U S A,1988,85(8):2444-2448.
    [78] Eddy SR. Accelerated Profile HMM Searches [J]. PLoS Comput Biol,2011,7(10):e1002195.
    [79] Aziz RK, Bartels D, Best AA, et al. The RAST Server: rapid annotations usingsubsystems technology [J]. BMC Genomics,2008,9:75.
    [80] Claudel-Renard C, Chevalet C, Faraut T, et al. Enzyme-specific profiles for genomeannotation: PRIAM [J]. Nucleic Acids Res,2003,31(22):6633-6639.
    [81] Poptsova MS, Gogarten JP. Using comparative genome analysis to identify problemsin annotated microbial genomes [J]. Microbiology-Sgm,2010,156:1909-1917.
    [82] Schnoes AM, Brown SD, Dodevski I, et al. Annotation error in public databases:misannotation of molecular function in enzyme superfamilies [J]. PLoS Comput Biol,2009,5(12):e1000605.
    [83] Liao YC, Huang TW, Chen FC, et al. An experimentally validated genome-scalemetabolic reconstruction of Klebsiella pneumoniae MGH78578, iYL1228[J]. JBacteriol,2011,193(7):1710-1717.
    [84] Kanehisa M, Araki M, Goto S, et al. KEGG for linking genomes to life and theenvironment [J]. Nucleic Acids Res,2008,36(Database issue):D480-484.
    [85] Saier MH, Tran CV, Barabote RD. TCDB: the Transporter Classification Database formembrane transport protein analyses and information [J]. Nucleic Acids Res,2006,34:D181-186.
    [86] Wong WC, Maurer-Stroh S, Eisenhaber F. More than1,001problems with proteindomain databases: transmembrane regions, signal peptides and the issue of sequencehomology [J]. PLoS Comput Biol,2010,6(7):e1000867.
    [87] Gelfand MS, Rodionov DA. Comparative genomics and functional annotation ofbacterial transporters [J]. Phys Life Rev,2008,5(1):22-49.
    [88] Felder M, Gupta A, Verma V, et al. The pyrroloquinoline quinone synthesis genes ofGluconobacter oxydans [J]. FEMS Microbiol Lett,2000,193(2):231-236.
    [89] Toyama H, Lidstrom ME. pqqA is not required for biosynthesis of pyrroloquinolinequinone in Methylobacterium extorquens AM1[J]. Microbiology,1998,144(1):183-191.
    [90] Palsson BO. Systems biology: properties of reconstructed networks [M]. New York:Cambridge University Press,2006.5-6.
    [91] Kim TY, Sohn SB, Kim YB, et al. Recent advances in reconstruction and applicationsof genome-scale metabolic models [J]. Curr Opin Biotechnol,2012,23(4):617-623.
    [92] Reed JL, Famili I, Thiele I, et al. Towards multidimensional genome annotation [J].Nat Rev Genet,2006,7(2):130-141.
    [93] Fernandez-Suarez XM, Galperin MY. The2013Nucleic Acids Research DatabaseIssue and the online molecular biology database collection [J]. Nucleic Acids Res,2013,41(Database issue):D1-7.
    [94] Benson DA, Karsch-Mizrachi I, Clark K, et al. GenBank [J]. Nucleic Acids Res,2012,40(Database issue):D48-53.
    [95] Jain E, Bairoch A, Duvaud S, et al. Infrastructure for the life sciences: design andimplementation of the UniProt website [J]. BMC Bioinformatics,2009,10:136.
    [96] Kanehisa M, Goto S, Furumichi M, et al. KEGG for representation and analysis ofmolecular networks involving diseases and drugs [J]. Nucleic Acids Res,2010,38(Database issue):D355-360.
    [97] Scheer M, Grote A, Chang A, et al. BRENDA, the enzyme information system in2011[J]. Nucleic Acids Res,2011,39(Database issue):D670-676.
    [98] Saier MH, Yen MR, Noto K, et al. The Transporter Classification Database: recentadvances [J]. Nucleic Acids Res,2009,37:D274-278.
    [99] Caspi R, Altman T, Dale JM, et al. The MetaCyc database of metabolic pathways andenzymes and the BioCyc collection of pathway/genome databases [J]. Nucleic AcidsRes,2010,38(Database issue):D473-479.
    [100] Degtyarenko K, de Matos P, Ennis M, et al. ChEBI: a database and ontology forchemical entities of biological interest [J]. Nucleic Acids Res,2008,36(Databaseissue):D344-350.
    [101] Schellenberger J, Park J, Conrad T, et al. BiGG: a Biochemical Genetic and Genomicknowledgebase of large scale metabolic reconstructions [J]. BMC Bioinformatics,2010,11(1):213.
    [102] Yu CS, Chen YC, Lu CH, et al. Prediction of protein subcellular localization [J].Proteins,2006,64(3):643-651.
    [103] Schellenberger J, Que R, Fleming RM, et al. Quantitative prediction of cellularmetabolism with constraint-based models: the COBRA Toolbox v2.0[J]. Nat Protoc,2011,6(9):1290-1307.
    [104]周冒达,邹伟,刘立明等.基于文献挖掘的巨大芽胞杆菌代谢网络模型的构建与分析[J].微生物学报,2012,52(4):457-465.
    [105] Feist AM, Henry CS, Reed JL, et al. A genome-scale metabolic reconstruction forEscherichia coli K-12MG1655that accounts for1260ORFs and thermodynamicinformation [J]. Mol Syst Biol,2007,3:121.
    [106] Ingraham JL, Maaloee O, Neidhardt FC. Growth of the bacterial cell. Sunderland:Sinauer Associates,1983.1-435.
    [107] Orth JD, Thiele I, Palsson BO. What is flux balance analysis?[J]. Nat Biotechnol,2010,28(3):245-248.
    [108] Feist AM, Palsson BO. The biomass objective function [J]. Curr Opin Microbiol,2010,13(3):344-349.
    [109] Reed JL, Vo TD, Schilling CH, et al. An expanded genome-scale model of Escherichiacoli K-12(iJR904GSM/GPR)[J]. Genome Biol,2003,4(9):R54.
    [110] Sugisawa T, Ojima, S.,Matzinger, K. P., Hoshino, T. Isolation and characterization of anew vitamin C producing enzyme (L-gulono-γ-lactone dehydrogenase) of bacterialorigin [J]. Biosci Biotechnol Biochem,1995,59:190-196.
    [111] Asakura A, Hoshino T, Kiyasu T, et al. Manufacture of L-ascorbic acid andD-erythorbic acid [P]. US Patent,2000:6146860.
    [112] Lewis NE, Nagarajan H, Palsson BO. Constraining the metabolic genotype-phenotyperelationship using a phylogeny of in silico methods [J]. Nat Rev Microbiol,2012,10(4):291-305.
    [113] de Figueiredo LF, Podhorski A, Rubio A, et al. Computing the shortest elementary fluxmodes in genome-scale metabolic networks [J]. Bioinformatics,2009,25(23):3158-3165.
    [114] Papin JA, Stelling J, Price ND, et al. Comparison of network-based pathway analysismethods [J]. Trends Biotechnol,2004,22(8):400-405.
    [115] Raman K, Chandra N. Flux balance analysis of biological systems: applications andchallenges [J]. Brief Bioinform,2009,10(4):435-449.
    [116] Gudmundsson S, Thiele I. Computationally efficient flux variability analysis [J]. BMCBioinformatics,2010,11:489.
    [117] Zomorrodi AR, Maranas CD. Improving the iMM904S. cerevisiae metabolic modelusing essentiality and synthetic lethality data [J]. BMC Syst Biol,2010,4:178.
    [118] Burgard AP, Pharkya P, Maranas CD. Optknock: a bilevel programming frameworkfor identifying gene knockout strategies for microbial strain optimization [J].Biotechnol Bioeng,2003,84(6):647-657.
    [119] Pharkya P, Burgard AP, Maranas CD. OptStrain: a computational framework forredesign of microbial production systems [J]. Genome Res,2004,14(11):2367-2376.
    [120] Chandrasekaran S, Price ND. Probabilistic integrative modeling of genome-scalemetabolic and regulatory networks in Escherichia coli and Mycobacteriumtuberculosis [J]. Proc Natl Acad Sci U S A,2010,107(41):17845-17850.
    [121] Covert MW, Xiao N, Chen TJ, et al. Integrating metabolic, transcriptional regulatoryand signal transduction models in Escherichia coli [J]. Bioinformatics,2008,24(18):2044-2050.
    [122] Becker SA, Feist AM, Mo ML, et al. Quantitative prediction of cellular metabolismwith constraint-based models: the COBRA Toolbox [J]. Nat Protoc,2007,2(3):727-738.
    [123] Cvijovic M, Olivares-Hernandez R, Agren R, et al. BioMet Toolbox: genome-wideanalysis of metabolism [J]. Nucleic Acids Res,2010,38Suppl:W144-149.
    [124] Hoppe A, Hoffmann S, Gerasch A, et al. FASIMU: flexible software for flux-balancecomputation series in large metabolic networks [J]. BMC Bioinformatics,2011,12:28.
    [125] Huang Z, Zou W, Liu J, et al. Glutathione enhances2-keto-L-gulonic acid productionbased on Ketogulonicigenium vulgare model iWZ663[J]. J Biotechnol,2013,164(4):454-460.
    [126] Begley TP, Kinsland C, Strauss E. The biosynthesis of coenzyme A in bacteria [J].Vitam Horm,2001,61:157-171.
    [127] Smirnova GV, Oktyabrsky ON. Glutathione in bacteria [J]. Biochemistry (Mosc),2005,70(11):1199-1211.
    [128] Masip L, Veeravalli K, Georgiou G. The many faces of glutathione in bacteria [J].Antioxid Redox Signal,2006,8(5-6):753-762.
    [129] Edwards JS, Palsson BO. The Escherichia coli MG1655in silico metabolic genotype:its definition, characteristics, and capabilities [J]. Proc Natl Acad Sci U S A,2000,97(10):5528-5533.
    [130] Orth JD, Conrad TM, Na J, et al. A comprehensive genome-scale reconstruction ofEscherichia coli metabolism--2011[J]. Mol Syst Biol,2011,7:535.
    [131] Teusink B, Westerhoff HV, Bruggeman FJ. Comparative systems biology: frombacteria to man [J]. Wiley Interdiscip Rev Syst Biol Med,2010,2(5):518-532.
    [132] Oberhardt MA, Puchalka J, Martins dos Santos VA, et al. Reconciliation ofgenome-scale metabolic reconstructions for comparative systems analysis [J]. PLoSComput Biol,2011,7(3):e1001116.
    [133] Alam MT, Medema MH, Takano E, et al. Comparative genome-scale metabolicmodeling of actinomycetes: the topology of essential core metabolism [J]. FEBS Lett,2011,585(14):2389-2394.
    [134] Hamilton JJ, Reed JL. Identification of functional differences in metabolic networksusing comparative genomics and constraint-based models [J]. PLoS ONE,2012,7(4):e34670.
    [135] Fürch T, Wittmann C, Wang W, et al. Effect of different carbon sources on centralmetabolic fluxes and the recombinant production of a hydrolase from Thermobifidafusca in Bacillus megaterium [J]. J Biotechnol,2007,132(4):385-394.
    [136] Hyatt MT, Levinson HS. Effect of sugars and other carbon compounds on germinationand postgerminative development of Bacillus megaterium spores [J]. J Bacteriol,1964,88:1403-1415.
    [137] Vazquez GJ, Pettinari MJ, Mendez BS. Phosphotransbutyrylase expression in Bacillusmegaterium [J]. Curr Microbiol,2001,42(5):345-349.
    [138] Sharma BS, Blumenthal HJ. Catabolism of D-gluaric acid to alpha-ketoglutarate inBacillus megaterium [J]. J Bacteriol,1973,116(3):1346-1354.
    [139] Hagedorn SR, Bradley G, Chapman PJ. Glutathione-independent isomerization ofmaleylpyruvate by Bacillus megaterium and other gram-positive bacteria [J]. JBacteriol,1985,163(2):640-647.
    [140] Levinson HS, Hyatt MT. Nitrogenous compounds in germination and postgerminativedevelopment of Bacillus megaterium spores [J]. J Bacteriol,1962,83:1224-1230.
    [141] Kulpreecha S, Boonruangthavorn A, Meksiriporn B, et al. Inexpensive fed-batchcultivation for high poly(3-hydroxybutyrate) production by a new isolate of Bacillusmegaterium [J]. J Biosci Bioeng,2009,107(3):240-245.
    [142] Mangalo R, Wachsman JT. Effect of8-azaguanine on growth and viability of Bacillusmegaterium [J]. J Bacteriol,1962,83:27-34.
    [143] Rossignol DP, Vary JC. Biochemistry of L-proline-triggered germination of Bacillusmegaterium spores [J]. J Bacteriol,1979,138(2):431-441.
    [144] Wolf JB, Brey RN. Isolation and genetic characterizations of Bacillus megateriumcobalamin biosynthesis-deficient mutants [J]. J Bacteriol,1986,166(1):51-58.
    [145] Raux E, Lanois A, Warren MJ, et al. Cobalamin (vitamin B12) biosynthesis:identification and characterization of a Bacillus megaterium cobI operon [J]. BiochemJ,1998,335(1):159-166.
    [146] Henry CS, Zinner JF, Cohoon MP, et al. iBsu1103: a new genome-scale metabolicmodel of Bacillus subtilis based on SEED annotations [J]. Genome Biol,2009,10(6):R69.
    [147] Oh YK, Palsson BO, Park SM, et al. Genome-scale reconstruction of metabolicnetwork in Bacillus subtilis based on high-throughput phenotyping and geneessentiality data [J]. J Biol Chem,2007,282:28791-28799.
    [148] Wilkinson BJ, Ellar DJ. Morphogenesis of the membrane-bound electron-transportsystem in sporulating Bacillus megaterium KM [J]. Eur J Biochem,1975,55(1):131-139.
    [149] Blencke HM, Homuth G, Ludwig H, et al. Transcriptional profiling of gene expressionin response to glucose in Bacillus subtilis: regulation of the central metabolicpathways [J]. Metab Eng,2003,5(2):133-149.
    [150] Fürch T, Hollmann R, Wittmann C, et al. Comparative study on central metabolicfluxes of Bacillus megaterium strains in continuous culture using C-13labelledsubstrates [J]. Bioprocess Biosyst Eng,2007,30(1):47-59.
    [151] Swainston N, Smallbone K, Mendes P, et al. The SuBliMinaL Toolbox: automatingsteps in the reconstruction of metabolic networks [J]. J Integr Bioinform,2011,8(2):186.
    [152] Caspeta L, Shoaie S, Agren R, et al. Genome-scale metabolic reconstructions ofPichia stipitis and Pichia pastoris and in silico evaluation of their potentials [J]. BMCSyst Biol,2012,6:24.
    [153] Roberts SB, Gowen CM, Brooks JP, et al. Genome-scale metabolic analysis ofClostridium thermocellum for bioethanol production [J]. BMC Syst Biol,2010,4:31.
    [154] Kieldsen KR, Nielsen J. In silico genome-scale reconstruction and validation of theCorynebacterium glutamicum metabolic network [J]. Biotechnol Bioeng,2009,102(2):583-597.
    [155] Tyo KEJ, Kocharin K, Nielsen J. Toward design-based engineering of industrialmicrobes [J]. Curr Opin Microbiol,2010,13(3):255-262.
    [156] Lee KY, Park JM, Kim TY, et al. The genome-scale metabolic network analysis ofZymomonas mobilis ZM4explains physiological features and suggests ethanol andsuccinic acid production strategies [J]. Microb Cell Fact,2010,9(1):94.
    [157] Yim H, Haselbeck R, Niu W, et al. Metabolic engineering of Escherichia coli fordirect production of1,4-butanediol [J]. Nat Chem Biol,2011,7(7):445-452.
    [158] Park JM, Kim TY, Lee SY. Constraints-based genome-scale metabolic simulation forsystems metabolic engineering [J]. Biotechnol Adv,2009,27(6):979-988.
    [159] Kleerebezem R, van Loosdrecht MCM. Mixed culture biotechnology for bioenergyproduction [J]. Curr Opin Biotechnol,2007,18(3):207-212.
    [160] Sabra W, Dietz D, Tjahjasari D, et al. Biosystems analysis and engineering ofmicrobial consortia for industrial biotechnology [J]. Eng Life Sci,2010,10(5):407-421.
    [161] Bader J, Mast-Gerlach E, Popovic MK, et al. Relevance of microbial coculturefermentations in biotechnology [J]. J Appl Microbiol,2010,109(2):371-387.
    [162] Salehizadeh H, Van Loosdrecht MCM. Production of polyhydroxyalkanoates bymixed culture: recent trends and biotechnological importance [J]. Biotechnol Adv,2004,22(3):261-279.
    [163] Zhuang K, Izallalen M, Mouser P, et al. Genome-scale dynamic modeling of thecompetition between Rhodoferax and Geobacter in anoxic subsurface environments[J]. ISME J,2011,5(2):305-316.
    [164] Stolyar S, Van Dien S, Hillesland KL, et al. Metabolic modeling of a mutualisticmicrobial community [J]. Mol Syst Biol,2007,3:92.
    [165] Karlsson FH, Nookaew I, Petranovic D, et al. Prospects for systems biology andmodeling of the gut microbiome [J]. Trends Biotechnol,2011,29(6):251-258.
    [166] Branco Dos Santos F, de Vos WM, Teusink B. Towards metagenome-scale models forindustrial applications-the case of Lactic Acid Bacteria [J]. Curr Opin Biotechnol,2013,24(2):200-206.
    [167] Klitgord N, Segre D. Environments that induce synthetic microbial ecosystems [J].PLoS Comput Biol,2010,6(11):e1001002.
    [168] Wintermute EH, Silver PA. Emergent cooperation in microbial metabolism [J]. MolSyst Biol,2010,6:407.
    [169] Freilich S, Zarecki R, Eilam O, et al. Competitive and cooperative metabolicinteractions in bacterial communities [J]. Nat Commun,2011,2:589.
    [170] Bordbar A, Lewis NE, Schellenberger J, et al. Insight into human alveolar macrophageand M. tuberculosis interactions via metabolic reconstructions [J]. Mol Syst Biol,2010,6:422.
    [171] Pal C, Papp B, Lercher MJ, et al. Chance and necessity in the evolution of minimalmetabolic networks [J]. Nature,2006,440(7084):667-670.
    [172] Yizhak K, Tuller T, Papp B, et al. Metabolic modeling of endosymbiont genomereduction on a temporal scale [J]. Mol Syst Biol,2011,7:479.
    [173] Mahadevan R, Schilling CH. The effects of alternate optimal solutions inconstraint-based genome-scale metabolic models [J]. Metab Eng,2003,5(4):264-276.
    [174] Saito R, Smoot ME, Ono K, et al. A travel guide to Cytoscape plugins [J]. NatMethods,2012,9(11):1069-1076.
    [175] Little AE, Robinson CJ, Peterson SB, et al. Rules of engagement: interspeciesinteractions that regulate microbial communities [J]. Annu Rev Microbiol,2008,62:375-401.
    [176] Phelan VV, Liu W-T, Pogliano K, et al. Microbial metabolic exchange-thechemotype-to-phenotype link [J]. Nat Chem Biol,2012,8(1):26-35.

© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号

地址:北京市海淀区学院路29号 邮编:100083

电话:办公室:(+86 10)66554848;文献借阅、咨询服务、科技查新:66554700