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In Silico Prediction of Large-Scale Microbial Production Performance: Constraints for Getting Proper Data-Driven Models.

Abstract：

:Industrial bioreactors range from 10.000 to 700.000 L and characteristically show different zones of substrate availabilities, dissolved gas concentrations and pH values reflecting physical, technical and economic constraints of scale-up. Microbial producers are fluctuating inside the bioreactors thereby experiencing frequently changing micro-environmental conditions. The external stimuli induce responses on microbial metabolism and on transcriptional regulation programs. Both may deteriorate the expected microbial production performance in large scale compared to expectations deduced from ideal, well-mixed lab-scale conditions. Accordingly, predictive tools are needed to quantify large-scale impacts considering bioreactor heterogeneities. The review shows that the time is right to combine simulations of microbial kinetics with calculations of large-scale environmental conditions to predict the bioreactor performance. Accordingly, basic experimental procedures and computational tools are presented to derive proper microbial models and hydrodynamic conditions, and to link both for bioreactor modeling. Particular emphasis is laid on the identification of gene regulatory networks as the implementation of such models will surely gain momentum in future studies.

journal_name

Comput Struct Biotechnol J

journal_title

Computational and structural biotechnology journal

authors

Zieringer J,Takors R

doi

10.1016/j.csbj.2018.06.002

subject

Has Abstract

pub_date

2018-07-06 00:00:00

pages

246-256

issn

2001-0370

pii

S2001-0370(18)30019-9

journal_volume

16

pub_type

杂志文章,评审

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