基于LC-MS的产核黄素枯草芽孢杆菌代谢物组的初步研究
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摘要
本文对四株不同产核黄素工程菌的胞内代谢物进行了比较研究。主要研究内容和结果如下:
首先对细胞灭活和胞内代谢物的提取方法进行了优化。确定了快速过滤收集菌体的方法分离获取细胞;采用高氯酸提取方法进行胞内代谢物提取。其次,本文确定了进行胞内代谢物检测的取样点。通过对菌体的生长状况的分析分别确定了对数生长期和稳定期的取样时间。
在此基础上,本文采取STD-MS/MS、STD、MS/MS、MS的方法,定性确定了24种胞内代谢物,并对其中11种胞内代谢物进行了精确定量分析。通过对四种不同产核黄素工程菌胞内代谢物的检测发现:purF基因过量表达加快了PRPP到PRA的反应速率,致使PRPP胞内浓度降低。在RH33-purF中,GMP、GDP、以及核黄素的重要前体物GTP的胞内浓度也随着增加,从而提高了目标产物核黄素的产量。
在RH44-purF中,同样的基因修饰并没有引起GTP浓度的增加,核黄素产量也并没有得到提高。这可能是由于在RH44-purF中,高浓度的PRPP对嘌呤操纵子的转录有很强的促进作用,使嘌呤合成途径不是RH44核黄素合成的限制因素。另外一个原因可能是由于ADP和GMP对purF编码的谷氨酰胺PRPP转酰胺酶的协同抑制作用降低了purF基因扩增的效果。
较高的胞内G6P和PEP浓度可能是造成RH33-purF葡萄糖的消耗速率缓慢的原因。另外还发现,在RH33系列菌株中,R5P的供给比较充足。因此,强化R5P向PRPP的转化可以继续提高其核黄素产量。
Intracellular metabolites of four riboflavin–producing Bacillus subtilis were investigated in this study. We gained some valuable result from the work.
First, quenching method and extracting process were optimized. Quick filtration method without quenching process was selected to separate cells from culture. We also compared four different extraction procedures, and finally chose the perchloric
acid extraction method. Second, sampling time points were established both in exponential growth phase and stationary phase thorough research on cell growth.
24 intracellular metabolites were qualitatively analyzed by STD-MS/MS, STD, MS/MS , MS methods, and 11 intracellular metabolites of them in four strains were quantitatively analyzed respectively.
The outcome showed that: Amplification of purF gene speeded up the key step of purine biosynthesis pathway—from PRPP to PRA, which led to decrease of PRPP. In RH33-purF, GMP, GDP and especially GTP, precursor for riboflavin, were increased compared to RH33. But in RH44-purF, GMP, GDP, GTP didn’t increased compared to RH44. This may be due to the reasons mentioned below: On one hand, high level PRPP strongly promoted the transcription of purine operon, so purine biosynthesis pathway was not inhibitive factor of riboflavin production in RH44. The other hand, the synergistic inhibition of ADP and GMP on glutamine PRPP amidotransferase reduced the effect of amplification of purF gene.
Significant increase of PEP and G6P slowed down the rate of glucose consumption in RH33-purF. Supply of R5P was sufficient in RH33 and RH33-purF, enhancing the transformation from R5P to PRPP would improve the yield of riboflavin.
首先对细胞灭活和胞内代谢物的提取方法进行了优化。确定了快速过滤收集菌体的方法分离获取细胞;采用高氯酸提取方法进行胞内代谢物提取。其次,本文确定了进行胞内代谢物检测的取样点。通过对菌体的生长状况的分析分别确定了对数生长期和稳定期的取样时间。
在此基础上,本文采取STD-MS/MS、STD、MS/MS、MS的方法,定性确定了24种胞内代谢物,并对其中11种胞内代谢物进行了精确定量分析。通过对四种不同产核黄素工程菌胞内代谢物的检测发现:purF基因过量表达加快了PRPP到PRA的反应速率,致使PRPP胞内浓度降低。在RH33-purF中,GMP、GDP、以及核黄素的重要前体物GTP的胞内浓度也随着增加,从而提高了目标产物核黄素的产量。
在RH44-purF中,同样的基因修饰并没有引起GTP浓度的增加,核黄素产量也并没有得到提高。这可能是由于在RH44-purF中,高浓度的PRPP对嘌呤操纵子的转录有很强的促进作用,使嘌呤合成途径不是RH44核黄素合成的限制因素。另外一个原因可能是由于ADP和GMP对purF编码的谷氨酰胺PRPP转酰胺酶的协同抑制作用降低了purF基因扩增的效果。
较高的胞内G6P和PEP浓度可能是造成RH33-purF葡萄糖的消耗速率缓慢的原因。另外还发现,在RH33系列菌株中,R5P的供给比较充足。因此,强化R5P向PRPP的转化可以继续提高其核黄素产量。
Intracellular metabolites of four riboflavin–producing Bacillus subtilis were investigated in this study. We gained some valuable result from the work.
First, quenching method and extracting process were optimized. Quick filtration method without quenching process was selected to separate cells from culture. We also compared four different extraction procedures, and finally chose the perchloric
acid extraction method. Second, sampling time points were established both in exponential growth phase and stationary phase thorough research on cell growth.
24 intracellular metabolites were qualitatively analyzed by STD-MS/MS, STD, MS/MS , MS methods, and 11 intracellular metabolites of them in four strains were quantitatively analyzed respectively.
The outcome showed that: Amplification of purF gene speeded up the key step of purine biosynthesis pathway—from PRPP to PRA, which led to decrease of PRPP. In RH33-purF, GMP, GDP and especially GTP, precursor for riboflavin, were increased compared to RH33. But in RH44-purF, GMP, GDP, GTP didn’t increased compared to RH44. This may be due to the reasons mentioned below: On one hand, high level PRPP strongly promoted the transcription of purine operon, so purine biosynthesis pathway was not inhibitive factor of riboflavin production in RH44. The other hand, the synergistic inhibition of ADP and GMP on glutamine PRPP amidotransferase reduced the effect of amplification of purF gene.
Significant increase of PEP and G6P slowed down the rate of glucose consumption in RH33-purF. Supply of R5P was sufficient in RH33 and RH33-purF, enhancing the transformation from R5P to PRPP would improve the yield of riboflavin.
引文
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[2]. Schlotterbeck G, Ross A, Dieterle F, Senn H, Metabolicprofiling technologies for biomarker discovery in biomedicineand drug development. Pharmacogenomics, 2006, :1055–1075
[3]. Horn I M, Murakam I S, Horn I E, et al. Analyses ofphospholip ids, ceramides, and cerebrosides by gas chromatographyand gas chromatography2mass spectrometry[ J ]. Am J Clin N utr,1971, 24 (9) : 1086 - 1096
[4]. Elsevier J, Chromatogr A 1986 , 379
[5]. Oliver S G, WinsonM K, Kell D B, Baganz F. Systematic functional analysis of the yeast genome. Trends Biotechnol ,1998,16:373–378
[6]. Tweeddale H, Notley-McRobb L, Ferenci T. Effect of slow growth on metabolism of Escherichia coli, as revealed by global metabolite pool (“metabolome”) analysis. J Bacteriol ,1998,180:5109–5116
[7]. Nicholson J.K., Lindon JC, Holmes E,‘Metabonomics’: understanding the metabolic responses of living systems to pathophysiological stimuli via multivariate statistical analysis of biological NMR spectroscopir data . Xenbiotica , 1999 , 29 :1181-1189
[8]. Griffin J L, Bolland M E, Lindon J C, et al. Metabonomics: a platform for studying drug toxicity and gene function. Nat. Rev. Drug Discov, 2002, 1: 153-162
[9]. Brimdle JT, Antti H, Nolmes E. et al. Rapid and noninvasice diagnosis of the presence and severity of corormary heart discase using H-NMR-based metabonomics. Nat. Med.,2002, 8(12):1439-1444
[10].干玉,产核黄素基因工程菌B.subtilis RH44代谢物组学的初步研究:[硕士学位论文],天津;天津大学,2007
[11]. Fiehn O, Metabolomics—the link between genotypes and phenotypes. Plant Mol Biol ,2002,48:155–171
[12]. Fiehn O. Combining genomics, metabolome analysis and biochemical modeling to understand metabolic networks, Comparative and FunctionalGenomics, 2001, 2 : 155-168
[13].毛煜,袁伯俊,代谢组学的研究现状与展望中国新药杂志,2007, 16 (13):1005-1009
[14]. Oldiges M, Lütz S, Pflug S, et al. Metabolomics: current state and evolving methodologies and tools.Appl Microbiol Biotechnol, 2007, 76:495–511
[15]. Oliver S G., Winson M K, Kell D B, Baganz F. Systematic functional analysis of the yeast genome.Trends Biotechnol ,1998,16:373–378
[16]. Weibel K E, Mor J R., Fiechter A. Rapid sampling of yeast cells and automated assays of adenylate, citrate, pyruvate and glucose-6-phosphate pools. Anal Biochem,1974,58:208–216
[17]. Holms H. Flux analysis and control of the central metabolic pathways in Escherichia coli. FEMS Microbiol Rev,1996, 19:85–116
[18]. Chassagnole C, Noisommit-Rizzi N, Schmid J W, et al. Dynamic modeling of the central carbon metabolism of Escherichia coli. Biotechnol Bioeng. 2002, 79:53-73
[19]. Mashego M R, van Gulik W M, Vinke J L, et al. Critical evaluation of sampling techniques for residual glucose determination in carbon-limited chemostat culture of Saccharomyces cerevisiae. Biotechnol Bioeng. 2003, 83:395-399
[20]. Weibel K E, Mor J R, Fiechter A. Rapid sampling of yeast cells and automated assays of adenylate, citrate, pyruvate and glucose-6-phosphate pools. Anal Biochem. 1974, 58:208-216
[21]. Visser D, van Zuylen G A, van Dam JC, et al. Rapid sampling for analysis of in vivo kinetics using the BioScope: a system for continuous pulse experiments. Biotechnol Bioeng. 2002, 79:674-681
[22]. Buziol S, Bashir I, Baumeister A, et al. New bioreactor-coupled rapid stopped-flow sampling technique for measurements of metabolite dynamics on a subsecond time scale. Biotechnol Bioeng. 2002, 80:632-636
[23]. Schaefer U, Boos W, Takors R, Weuster-Botz D. Automated sampling device for monitoring intracellular metabolite dynamics. Anal Biochem ,1999,270:88–96
[24]. Buchholz A, Hurlebaus J, Wandrey C, Takors R. Metabolomics: quantification of intracellular metabolite dynamics. Biomol Eng ,2002,19:5–15
[25]. Chassagnole C, Noisommit-Rizzi N, Schmid J W, Mauch K, Reuss M. Dynamic odeling of the central carbon metabolism of Escherichia coli. Biotechnol Bioeng ,2002,79:53–73
[26]. Visser D, van Zuylen G A, van Dam J C, Oudshoorn A, Eman MR, Ras C,van Gulik WM, Frank J, van Dedem GW, Heijnen JJ. Rapid sampling for analysis of in vivo kinetics using the BioScope: a system for continuous pulse experiments. Biotechnol Bioeng ,2002,79:674–681
[27]. Nasution U, van Gulik W M, Kleijn R J, van Winden W A, Proell A, Heijnen J J. Measurement of intracellular metabolites of primary metabolism and adenine nucleotides in chemostat cultivated Penicillium chrysogenum. Biotechnol Bioeng , 2006,94:159–166
[28]. Mashego M R, van Gulik W M, Heijnen J J. Metabolome dynamic responses of Saccharomyces cerevisiae on simultaneous rapid perturbations in external electron acceptor and electron donor. FEMS Yeast Res,2006, 00144.x 1567–1364
[29]. Jensen N B, Jokumsen K V, Villadsen J. Determination of the phosphorylated sugars of the Embden-Meyerhoff-Parnas pathway in Lactococcus lactis using a fast sampling technique and solid phase extraction. Biotechnol Bioeng. 1999, 63: 356-362
[30]. Mashego M R., Wu L, Van Dam J C, et al. MIRACLE: mass isotopomer ratio analysis of U–13C-labeled extracts. A new method for accurate quantification of changes in concentrations of intracellular metabolites. Biotechnol Bioeng. 2004, 85:620-628
[31]. Villas-Bo? as S G., Hojer-Pedersen J, Akesson M, Smedsgaard J, Nielsen J . Global metabolite analysis of yeast: evaluation of sample preparation methods. Yeast ,2005,22:1155–1169
[32]. Hajjaj H, Blanc P J, Goma G., Francois J. Sampling techniques and comparative extraction procedures for quantitative determination of intra- and extracellular metabolites in filamentous fungi. FEMS Microbiol Lett ,1998,164:195–200
[33]. Buchholz A, Takors R, Wandrey C. Quantification of intracellular metabolites in Escherichia coli K12 using liquid chromatographic-electrospray ionizationtandem mass spectrometric techniques. Anal Biochem ,2001,295:129–137
[34]. Wittmann C, Kro¨mer J O, Kiefer P, et al. Impact of the cold shock phenomenon on quantification of intracellular metabolites in bacteria. Anal Biochem. 2004, 327:135-139
[35]. Al Zaid Siddiquee K, Arauzo-Bravo M J, Shimizu K. Metabolic flux analysis of pykF gene knockout Escherichia coli based on 13C-labeling experiments together with measurements of enzyme activities and intracellular metabolite concentrations. Appl Microbiol Biotechnol. 2004, 63:407-417
[36]. Ruijter GJG., Visser J. Determination of intermediary metabolites in Aspergillus niger. J Microbiol Methods. 1996, 25:295-302
[37]. Castrillo J I, Hayes A, Mohammed S, Gaskell S J, Oliver SG . An optimized protocol for metabolome analysis in yeast using direct infusion electrospray mass spectrometry. Phytochemistry ,2003,62:929–937
[38]. Buziol S, Bashir I, Baumeister A, Claa?en W, Noisommit-Rizzi N, Mailinger W, Reuss M. New bioreactor-coupled rapid stopped-flow sampling technique for measurements of metabolite dynamics on a subsecond time scale. Biotechnol Bioeng ,2002,80:632–636
[39]. Neidhardt F C, Umbarger H E.Chemical composition of Escherichia coli. In: Neidhardt FC (ed) Escherichia coli and salmonella typhimurium—cellular and molecular biology. ASM, Washington, DC,1996
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