Suppr超能文献

用于预测高细胞密度培养物离心分离行为的适应性超微缩方法。

Adapted ultra scale-down approach for predicting the centrifugal separation behavior of high cell density cultures.

作者信息

Tustian Andrew D, Salte Heidi, Willoughby Nicholas A, Hassan Inass, Rose Michael H, Baganz Frank, Hoare Michael, Titchener-Hooker Nigel J

机构信息

The Advanced Centre for Biochemical Engineering, Department of Biochemical Engineering, University College London, Torrington Place, London WC1E 7JE, UK.

出版信息

Biotechnol Prog. 2007 Nov-Dec;23(6):1404-10. doi: 10.1021/bp070175d. Epub 2007 Oct 20.

Abstract

The work presented here describes an ultra scale-down (USD) methodology for predicting centrifugal clarification performance in the case of high cell density fermentation broths. Existing USD approaches generated for dilute systems led to a 5- to 10-fold overprediction of clarification performance when applied to such high cell density feeds. This is due to increased interparticle forces, leading to effects such as aggregation, flocculation, or even blanket sedimentation, occurring in the low shear environment of a laboratory centrifuge, which will not be apparent in the settling region of a continuous-flow industrial centrifuge. A USD methodology was created based upon the dilution of high solids feed material to approximately 2% wet wt/vol prior to the application of the clarification test. At this level of dilution cell-cell interactions are minimal. The dilution alters the level of hindered settling in the feed suspensions, and so mathematical corrections are applied to the resultant clarification curves to mimic the original feed accurately. The methodology was successfully verified: corrected USD curves accurately predicted pilot-scale clarification performance of high cell density broths of Saccharomyces cerevisiae and Escherichia coli cells. The USD method allows for the rapid prediction of large-scale clarification of high solids density material using millilitre quantities of feed. The advantages of this method to the biochemical engineer, such as the enabling of rapid process design and scale-up, are discussed.

摘要

本文介绍了一种超微缩(USD)方法,用于预测高细胞密度发酵液的离心澄清性能。现有的针对稀释系统生成的USD方法,应用于此类高细胞密度进料时,会导致澄清性能预测值高出5至10倍。这是由于颗粒间作用力增加,导致在实验室离心机的低剪切环境中出现聚集、絮凝甚至毯式沉降等效应,而这些效应在连续流工业离心机的沉降区域中并不明显。基于在进行澄清测试之前将高固体含量的进料稀释至约2%湿重/体积,创建了一种USD方法。在这种稀释水平下,细胞间相互作用最小。稀释改变了进料悬浮液中的受阻沉降水平,因此对所得澄清曲线进行数学校正,以准确模拟原始进料。该方法得到了成功验证:校正后的USD曲线准确预测了酿酒酵母和大肠杆菌细胞的高细胞密度发酵液的中试规模澄清性能。USD方法允许使用毫升量的进料快速预测高固体密度物料的大规模澄清。讨论了该方法对生化工程师的优势,如实现快速工艺设计和放大。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验