食品科学 ›› 2011, Vol. 32 ›› Issue (7 ): 237-243.doi: 10.7506/spkx1002-6630-201107051

• 生物工程 • 上一篇    下一篇

螺旋藻β-胡萝卜素代谢控制分析及其新方法的研究

王 芳,庞广昌*,王景川   

  1. 天津市食品生物技术重点实验室,天津商业大学生物技术与食品科学学院
  • 收稿日期:2010-05-31 修回日期:2011-01-31 出版日期:2011-04-15 发布日期:2011-03-30
  • 通讯作者: 庞广昌 E-mail:pgc@tjcu.edu.cn
  • 基金资助:
    天津市重点科技攻关专项(06YFGZNC04200)

Metabolic Control Analysis of β-Carotene in Spirulina

WANG Fang,PANG Guang-chang*,WANG Jing-chuan   

  1. Tianjin Key Laboratory of Food Biotechnology, College of Biotechnology and Food Science, Tianjin University of
    Commerce, Tianjin 300134, China
  • Received:2010-05-31 Revised:2011-01-31 Online:2011-04-15 Published:2011-03-30

摘要: 代谢控制分析(MCA)的两大难题是获得酶活性的扰动和通量控制系数(FCC)的计算,需要借助基因操作和复杂的计算推理。研究表明数量性状基因座(QTL)效应和通量控制系数(FCC)具有极其相似的分布规律,均呈L形分布,即代谢通量具有与数量性状一致的遗传变异规律。因此,本实验将螺旋藻(spirulina)β-胡萝卜素(β-carotene)的代谢通量作为一个数量性状,运用主成分分析、通径分析等数量遗传学分析方法研究其代谢途径中酶对通量的影响方式和程度。在相关分析的基础上计算得到了基于主成分分析的控制系数Cpi和基于通径分析的控制系数R2i,对比分析表明这两组控制系数的变化规律基本一致,表明螺旋藻β-胡萝卜素合成途径中番茄红素-β-环化酶(LYC-B,CpLYC-B=0.161,R2LYC-B=0.2601)、RuBP羧化酶(RuBisCO,CpRuBisCO=0.121,R2RuBisCO=0.2453)、磷酸甘油酸变位酶(PGM,CpPGM=0.163,R2PGM=0.2320)、丙酮酸脱氢酶(PDHC,CpPDHC=0.119,R2PDHC=0.1584)和异柠檬酸脱氢酶(ICDH,CpICDH=0.172,R2ICDH= 0.1935)5种酶对β-胡萝卜素的代谢通量的分布或改变起主要控制作用。这两种方法简便易行,简化了实验操作和计算过程,可为代谢工程育种及代谢控制分析提供新方法。

关键词: 数量遗传学, 代谢控制分析, 主成分分析, 通径分析, β-胡萝卜素

Abstract: Two problems of metabolic control analysis are the acquisition of enzyme activity distribution and the calculation of flux control coefficient (FCC), which often needs gene manipulation and complicated calculation. A large number studies indicated that both quantitative trait loci (QTL) effect and flux control coefficient revealed similar L-shaped distribution. Therefore, metabolic flux of β-carotene in spirulina was considered as a quantitative trait. Principal component analysis and path analysis were used to explore the control effects of enzymes on metabolic flux for the first time. The control coefficients based on principal component analysis (Cpi) and path analysis (R2i) were established after correlation analysis between enzymes and metabolic flux. Comparative analysis results indicated control coefficients from both groups had a consistent change trend. Therefore, five enzymes including lycopene β-cyclase (LYC-B, CpLYC-B = 0.161, R2LYC-B = 0.2601), ribulose-1,5-bisphosphate carboxylase (RuBisCO, CpRuBisCO = 0.121, R2RuBisCO = 0.2453), phosphoglyceromutase (PGM, CpPGM = 0.163, R2PGM = 0.2320), pyruvate dehydrogenase (PDHC, CpPDHC = 0.119, R2PDHC = 0.1584) and isocitrate dehydrogenase (ICDH, CpICDH = 0.172, R2ICDH = 0.1935) played an important role in the flux of β-carotene. The two established methods in this study are simple and accurate so that these methods with simplified operation and calculation process will provide new strategies for metabolic engineering breeding and metabolic control analysis.

Key words: quantitative genetics, metabolic control analysis, principal component analysis, path analysis, β-carotene

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