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使用B样条曲线进行动态代谢通量分析以研究温度变化对CHO细胞代谢的影响。

Dynamic metabolic flux analysis using B-splines to study the effects of temperature shift on CHO cell metabolism.

作者信息

Martínez Verónica S, Buchsteiner Maria, Gray Peter, Nielsen Lars K, Quek Lake-Ee

机构信息

Australian Institute for Bioengineering and Nanotechnology (AIBN), The University of Queensland, Brisbane, QLD 4072, Australia.

出版信息

Metab Eng Commun. 2015 Jun 19;2:46-57. doi: 10.1016/j.meteno.2015.06.001. eCollection 2015 Dec.

DOI:10.1016/j.meteno.2015.06.001
PMID:34150508
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8193249/
Abstract

Metabolic flux analysis (MFA) is widely used to estimate intracellular fluxes. Conventional MFA, however, is limited to continuous cultures and the mid-exponential growth phase of batch cultures. Dynamic MFA (DMFA) has emerged to characterize time-resolved metabolic fluxes for the entire culture period. Here, the linear DMFA approach was extended using B-spline fitting (B-DMFA) to estimate mass balanced fluxes. Smoother fits were achieved using reduced number of knots and parameters. Additionally, computation time was greatly reduced using a new heuristic algorithm for knot placement. B-DMFA revealed that Chinese hamster ovary cells shifted from 37 °C to 32 °C maintained a constant IgG volume-specific productivity, whereas the productivity for the controls peaked during mid-exponential growth phase and declined afterward. The observed 42% increase in product titer at 32 °C was explained by a prolonged cell growth with high cell viability, a larger cell volume and a more stable volume-specific productivity.

摘要

代谢通量分析(MFA)被广泛用于估计细胞内通量。然而,传统的MFA仅限于连续培养和分批培养的指数生长中期。动态MFA(DMFA)已出现,用于表征整个培养期间的时间分辨代谢通量。在此,使用B样条拟合(B-DMFA)扩展了线性DMFA方法,以估计质量平衡通量。通过减少节点和参数的数量实现了更平滑的拟合。此外,使用一种新的节点放置启发式算法大大减少了计算时间。B-DMFA表明,从37°C转移到32°C的中国仓鼠卵巢细胞保持恒定的IgG体积比生产率,而对照的生产率在指数生长中期达到峰值,随后下降。在32°C下观察到的产物滴度增加42%,是由于细胞生长延长、细胞活力高、细胞体积大以及体积比生产率更稳定。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/23ab/8193249/ae789506644d/gr8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/23ab/8193249/e1d76b6c81c6/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/23ab/8193249/bd5106c39922/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/23ab/8193249/41b82f48275d/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/23ab/8193249/4c9b0d7b6f7e/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/23ab/8193249/3f4efed66997/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/23ab/8193249/3e8db8091013/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/23ab/8193249/dae3774f4acb/gr7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/23ab/8193249/ae789506644d/gr8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/23ab/8193249/e1d76b6c81c6/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/23ab/8193249/bd5106c39922/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/23ab/8193249/41b82f48275d/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/23ab/8193249/4c9b0d7b6f7e/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/23ab/8193249/3f4efed66997/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/23ab/8193249/3e8db8091013/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/23ab/8193249/dae3774f4acb/gr7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/23ab/8193249/ae789506644d/gr8.jpg

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