Towards better understanding of an industrial cell factory: investigating the feasibility of real-time metabolic flux analysis in Pichia pastoris.
Towards better understanding of an industrial cell factory: investigating the feasibility of real-time metabolic flux analysis in Pichia pastoris.
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DOI：
10.1186/1475-2859-12-51
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发表时间：
2013-05-21
影响因子：
6.4
通讯作者：
McNeil B
中科院分区：
文献类型：
--
作者：
Fazenda ML;Dias JM;Harvey LM;Nordon A;Edrada-Ebel R;Littlejohn D;McNeil B
缩短生物制药漫长而昂贵的开发周期的新型分析工具是必不可少的。代谢通量分析(MFA)在改善我们对生物反应器中细胞工厂新陈代谢的理解方面显示出巨大的希望，但目前只提供使用传统离线方法的后处理信息。MFA与实时多分析物过程监控技术相结合，提供了一个宝贵的平台技术，使您能够实时了解生物反应器中细胞工厂的代谢反应。这可能会对生物加工行业产生重大影响，最终提高产品的一致性、生产率并缩短开发周期。这是首次使用近红外光谱(NIRS)原位结合代谢通量模型进行的研究，这既是对这些技术的重大挑战，也是相当大的扩展。我们在一个简化的模型系统中研究了我们的方法的可行性，使用工业主力毕赤氏酵母。亲本巴斯德毕赤酵母菌株(即不合成重组蛋白)被用来定义不同的代谢状态，只关注中央碳代谢中细胞内通量的预测。使用离线常规参照法和在线近红外预测(通过使用偏最小二乘算法的多变量分析计算)来确定细胞外流量。结果表明，该模型对生物量和甘油的预测精度较高，相关系数R2均在0.90以上，预测均方根误差RMSEP分别为1.17和2.90g/L。通过与实验室标准差(SEL)的直接比较，验证了NIR模型的分析质量，表明NIR模型的性能适合于定量生物量和甘油来计算胞外代谢物速率，并可作为MFA的独立输入(RMSEP小于1.5×SEL)。此外，两个数据集的MFA结果都通过了对每个稳态的一致性测试，表明在线NIRS的精度与离线测量的精度相当。这项研究的结果首次显示了近红外光谱作为MFA模型的输入生成的潜力，有助于实时优化细胞工厂的新陈代谢。
Novel analytical tools, which shorten the long and costly development cycles of biopharmaceuticals are essential. Metabolic flux analysis (MFA) shows great promise in improving our understanding of the metabolism of cell factories in bioreactors, but currently only provides information post-process using conventional off-line methods. MFA combined with real time multianalyte process monitoring techniques provides a valuable platform technology allowing real time insights into metabolic responses of cell factories in bioreactors. This could have a major impact in the bioprocessing industry, ultimately improving product consistency, productivity and shortening development cycles. This is the first investigation using Near Infrared Spectroscopy (NIRS) in situ combined with metabolic flux modelling which is both a significant challenge and considerable extension of these techniques. We investigated the feasibility of our approach using the industrial workhorse Pichia pastoris in a simplified model system. A parental P. pastoris strain (i.e. which does not synthesize recombinant protein) was used to allow definition of distinct metabolic states focusing solely upon the prediction of intracellular fluxes in central carbon metabolism. Extracellular fluxes were determined using off-line conventional reference methods and on-line NIR predictions (calculated by multivariate analysis using the partial least squares algorithm, PLS). The results showed that the PLS-NIRS models for biomass and glycerol were accurate: correlation coefficients, R2, above 0.90 and the root mean square error of prediction, RMSEP, of 1.17 and 2.90 g/L, respectively. The analytical quality of the NIR models was demonstrated by direct comparison with the standard error of the laboratory (SEL), which showed that performance of the NIR models was suitable for quantifying biomass and glycerol for calculating extracellular metabolite rates and used as independent inputs for the MFA (RMSEP lower than 1.5 × SEL). Furthermore, the results for the MFA from both datasets passed consistency tests performed for each steady state, showing that the precision of on-line NIRS is equivalent to that obtained by the off-line measurements. The findings of this study show for the first time the potential of NIRS as an input generating for MFA models, contributing to the optimization of cell factory metabolism in real-time.
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影响因子：
5
作者：
Almeida, Joao R. M.;Bertilsson, Magnus;Gorwa-Grauslund, Marie-F.
通讯作者：
Gorwa-Grauslund, Marie-F.
影响因子：
3.8
作者：
Heyland, Jan;Fu, Jianan;Schmid, Andreas
通讯作者：
Schmid, Andreas
影响因子：
8.4
作者：
Antoniewicz, Maciek R.;Kraynie, David F.;Stephanopoulos, Gregory
通讯作者：
Stephanopoulos, Gregory
影响因子：
3.8
作者：
Arnold, SA;Gaensakoo, R;McNeil, B
通讯作者：
McNeil, B
影响因子：
3.9
作者：
Matsuoka, Yu;Shimizu, Kazuyuki
通讯作者：
Shimizu, Kazuyuki