Hybrid metabolic flux analysis: combining stoichiometric and statistical constraints to model the formation of complex recombinant products.
Hybrid metabolic flux analysis: combining stoichiometric and statistical constraints to model the formation of complex recombinant products.
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DOI：
10.1186/1752-0509-5-34
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发表时间：
2011-02-25
影响因子：
--
通讯作者：
Oliveira R
中科院分区：
文献类型：
--
作者：
Carinhas N;Bernal V;Teixeira AP;Carrondo MJ;Alves PM;Oliveira R
化学计量模型构成了代谢工程领域中通量组定量的基本框架。然而，一个经常性的瓶颈是建立一致的化学计量模型的重组蛋白质或病毒的合成。虽然优化算法的计算机代谢重新设计已经开发的背景下，基因组规模的化学计量模型的小分子生产，仍然是基本的知识，不同的细胞水平是如何调节和表型表达，防止其完全适用于复杂的产品优化。提出了一种混合框架，将经典的代谢通量分析与潜在结构的投影相结合，以进一步将估计的代谢通量与测量的生产率联系起来。我们首先从实验数据中探索杆状病毒产生昆虫细胞系的功能代谢分解，突出TCA循环和线粒体呼吸作为与病毒复制密切相关的途径。为了减少代谢靶点识别的不确定性，使用Monte Carlo抽样方法来选择与靶点有意义的关联，由于弱相关性和/或高估计误差，必须从中筛选出66%的估计通量体。然后使用初步实验的子集来验证所提出的混合模型，以确定相同的决定因素途径，同时预测独立培养物的生产力。总的来说，结果表明，我们的混合代谢通量分析框架是一个有利的工具，代谢识别和量化不完整或不明确的代谢网络。由于构建全面的全球细胞模型的实验和计算解决方案正在开发中，混合代谢通量分析的贡献应构成对当前计算平台的有价值的补充，以改善细胞培养性能，从而将代谢状态与细胞培养性能联系起来。
Stoichiometric models constitute the basic framework for fluxome quantification in the realm of metabolic engineering. A recurrent bottleneck, however, is the establishment of consistent stoichiometric models for the synthesis of recombinant proteins or viruses. Although optimization algorithms for in silico metabolic redesign have been developed in the context of genome-scale stoichiometric models for small molecule production, still rudimentary knowledge of how different cellular levels are regulated and phenotypically expressed prevents their full applicability for complex product optimization. A hybrid framework is presented combining classical metabolic flux analysis with projection to latent structures to further link estimated metabolic fluxes with measured productivities. We first explore the functional metabolic decomposition of a baculovirus-producing insect cell line from experimental data, highlighting the TCA cycle and mitochondrial respiration as pathways strongly associated with viral replication. To reduce uncertainty in metabolic target identification, a Monte Carlo sampling method was used to select meaningful associations with the target, from which 66% of the estimated fluxome had to be screened out due to weak correlations and/or high estimation errors. The proposed hybrid model was then validated using a subset of preliminary experiments to pinpoint the same determinant pathways, while predicting the productivity of independent cultures. Overall, the results indicate our hybrid metabolic flux analysis framework is an advantageous tool for metabolic identification and quantification in incomplete or ill-defined metabolic networks. As experimental and computational solutions for constructing comprehensive global cellular models are in development, the contribution of hybrid metabolic flux analysis should constitute a valuable complement to current computational platforms in bridging the metabolic state with improved cell culture performance.
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DOI：
10.1016/s0169-7439(00)00071-x
发表时间：
2000-08-14
影响因子：
3.9
作者：
Andersson, CA;Bro, R
通讯作者：
Bro, R
影响因子：
9.5
作者：
Boulesteix, Anne-Laure;Strimmer, Korbinian
通讯作者：
Strimmer, Korbinian
影响因子：
2.5
作者：
Cordes, D;Haughton, V;Maravilla, K
通讯作者：
Maravilla, K
大肠杆菌的系统代谢工程，用于L-苏氨酸生产。
影响因子：
9.9
作者：
Lee, Kwang Ho;Park, Jin Hwan;Kim, Tae Yong;Kim, Hyun Uk;Lee, Sang Yup
通讯作者：
Lee, Sang Yup
影响因子：
4.3
作者：
Lee, Jong Min;Gianchandani, Erwin P.;Eddy, James A.;Papin, Jason A.
通讯作者：
Papin, Jason A.