Literature DB >> 27378496

Engineering E. coli for large-scale production - Strategies considering ATP expenses and transcriptional responses.

Michael Löffler1, Joana Danica Simen1, Günter Jäger2, Karin Schäferhoff2, Andreas Freund1, Ralf Takors3.   

Abstract

Microbial producers such as Escherichia coli are evolutionarily trained to adapt to changing substrate availabilities. Being exposed to large-scale production conditions, their complex, multilayered regulatory programs are frequently activated because they face changing substrate supply due to limited mixing. Here, we show that E. coli can adopt both short- and long-term strategies to withstand these stress conditions. Experiments in which glucose availability was changed over a short time scale were performed in a two-compartment bioreactor system. Quick metabolic responses were observed during the first 30s of glucose shortage, and after 70s, fundamental transcriptional programs were initiated. Since cells are fluctuating under simulated large-scale conditions, this scenario represents a continuous on/off switching of about 600 genes. Furthermore, the resulting ATP maintenance demands were increased by about 40-50%, allowing us to conclude that hyper-producing strains could become ATP-limited under large-scale production conditions. Based on the observed transcriptional patterns, we identified a number of candidate gene deletions that may reduce unwanted ATP losses. In summary, we present a theoretical framework that provides biological targets that could be used to engineer novel E. coli strains such that large-scale performance equals laboratory-scale expectations.
Copyright © 2016 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  ATP expense; Escherichia coli; Glucose limitation; Maintenance; Scale-up/scale-down; Transcriptional response

Mesh:

Substances:

Year:  2016        PMID: 27378496     DOI: 10.1016/j.ymben.2016.06.008

Source DB:  PubMed          Journal:  Metab Eng        ISSN: 1096-7176            Impact factor:   9.783


  20 in total

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2.  Euler-Lagrangian Simulations: A Proper Tool for Predicting Cellular Performance in Industrial Scale Bioreactors.

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Journal:  Adv Biochem Eng Biotechnol       Date:  2021       Impact factor: 2.635

3.  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

4.  The effect of metabolic stress on genome stability of a synthetic biology chassis Escherichia coli K12 strain.

Authors:  Jillian M Couto; Anne McGarrity; Julie Russell; William T Sloan
Journal:  Microb Cell Fact       Date:  2018-01-22       Impact factor: 5.328

5.  Scale-up/Scale-down of microbial bioprocesses: a modern light on an old issue.

Authors:  Frank Delvigne; Henk Noorman
Journal:  Microb Biotechnol       Date:  2017-05-29       Impact factor: 5.813

6.  Repetitive Short-Term Stimuli Imposed in Poor Mixing Zones Induce Long-Term Adaptation of E. coli Cultures in Large-Scale Bioreactors: Experimental Evidence and Mathematical Model.

Authors:  Alexander Nieß; Michael Löffler; Joana D Simen; Ralf Takors
Journal:  Front Microbiol       Date:  2017-06-28       Impact factor: 5.640

7.  Lagrangian Trajectories to Predict the Formation of Population Heterogeneity in Large-Scale Bioreactors.

Authors:  Maike Kuschel; Flora Siebler; Ralf Takors
Journal:  Bioengineering (Basel)       Date:  2017-03-29

8.  Transcriptional response of Escherichia coli to ammonia and glucose fluctuations.

Authors:  Joana Danica Simen; Michael Löffler; Günter Jäger; Karin Schäferhoff; Andreas Freund; Jakob Matthes; Jan Müller; Ralf Takors
Journal:  Microb Biotechnol       Date:  2017-04-26       Impact factor: 5.813

9.  Rapid Sampling of Escherichia coli After Changing Oxygen Conditions Reveals Transcriptional Dynamics.

Authors:  Joachim von Wulffen; Andreas Ulmer; Günter Jäger; Oliver Sawodny; Ronny Feuer
Journal:  Genes (Basel)       Date:  2017-02-28       Impact factor: 4.096

10.  Comparative performance of different scale-down simulators of substrate gradients in Penicillium chrysogenum cultures: the need of a biological systems response analysis.

Authors:  Guan Wang; Junfei Zhao; Cees Haringa; Wenjun Tang; Jianye Xia; Ju Chu; Yingping Zhuang; Siliang Zhang; Amit T Deshmukh; Walter van Gulik; Joseph J Heijnen; Henk J Noorman
Journal:  Microb Biotechnol       Date:  2018-01-15       Impact factor: 5.813

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