Literature DB >> 28400137

Tools for the determination of population heterogeneity caused by inhomogeneous cultivation conditions.

Anja Lemoine1, Frank Delvigne2, Anika Bockisch1, Peter Neubauer1, Stefan Junne3.   

Abstract

Population heterogeneity among a microbial culture can occur in various stages of a bioprocess. When a nutrient-limited fed-batch process is applied in the large scale, gradient formation (e.g. at the substrate concentration or the pH-value) can have a tremendous impact on the process performance. It might also have an impact on population heterogeneity, as the cells are opposed to stressful conditions that is an oscillating environment, when they pass the different zones evolved in the liquid phase. Nevertheless, the question whether these conditions support heterogeneity of a culture has not been clearly answered so far. Furthermore, if such a heterogeneity affects product formation, the usual analysis tools, which do not rely on a single-cell basis, certainly do not gain sufficiently suitable information for process optimization. This overview on the one hand provides information about the contribution of an oscillating environment to the formation of heterogeneities within a population and on the other hand a summary of tools, which can be used to investigate physiologic and morphologic heterogeneity during process development, scale up and production. If these techniques are considered, the identification of targets for accelerated process optimization on a single-cell basis becomes easier and faster.
Copyright © 2017 Elsevier B.V. All rights reserved.

Keywords:  Biological noise; Gradients; Microbial population; Population heterogeneity; Process analytical tools

Mesh:

Year:  2017        PMID: 28400137     DOI: 10.1016/j.jbiotec.2017.03.020

Source DB:  PubMed          Journal:  J Biotechnol        ISSN: 0168-1656            Impact factor:   3.307


  5 in total

1.  Potential of Integrating Model-Based Design of Experiments Approaches and Process Analytical Technologies for Bioprocess Scale-Down.

Authors:  Peter Neubauer; Emmanuel Anane; Stefan Junne; Mariano Nicolas Cruz Bournazou
Journal:  Adv Biochem Eng Biotechnol       Date:  2021       Impact factor: 2.635

2.  Bioprocess scale-up/down as integrative enabling technology: from fluid mechanics to systems biology and beyond.

Authors:  Frank Delvigne; Ralf Takors; Rob Mudde; Walter van Gulik; Henk Noorman
Journal:  Microb Biotechnol       Date:  2017-08-14       Impact factor: 5.813

3.  Using Raman spectroscopy and chemometrics to identify the growth phase of Lactobacillus casei Zhang during batch culture at the single-cell level.

Authors:  Yan Ren; Yuetong Ji; Lin Teng; Heping Zhang
Journal:  Microb Cell Fact       Date:  2017-12-23       Impact factor: 5.328

4.  Quantitative Flow Cytometry to Understand Population Heterogeneity in Response to Changes in Substrate Availability in Escherichia coli and Saccharomyces cerevisiae Chemostats.

Authors:  Anna-Lena Heins; Ted Johanson; Shanshan Han; Luisa Lundin; Magnus Carlquist; Krist V Gernaey; Søren J Sørensen; Anna Eliasson Lantz
Journal:  Front Bioeng Biotechnol       Date:  2019-08-05

Review 5.  In Silico Prediction of Large-Scale Microbial Production Performance: Constraints for Getting Proper Data-Driven Models.

Authors:  Julia Zieringer; Ralf Takors
Journal:  Comput Struct Biotechnol J       Date:  2018-07-06       Impact factor: 7.271

  5 in total

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