Literature DB >> 28901715

Engineering Microbial Metabolite Dynamics and Heterogeneity.

Alexander C Schmitz1, Christopher J Hartline1, Fuzhong Zhang1,2.   

Abstract

As yields for biological chemical production in microorganisms approach their theoretical maximum, metabolic engineering requires new tools, and approaches for improvements beyond what traditional strategies can achieve. Engineering metabolite dynamics and metabolite heterogeneity is necessary to achieve further improvements in product titers, productivities, and yields. Metabolite dynamics, the ensemble change in metabolite concentration over time, arise from the need for microbes to adapt their metabolism in response to the extracellular environment and are important for controlling growth and productivity in industrial fermentations. Metabolite heterogeneity, the cell-to-cell variation in a metabolite concentration in an isoclonal population, has a significant impact on ensemble productivity. Recent advances in single cell analysis enable a more complete understanding of the processes driving metabolite heterogeneity and reveal metabolic engineering targets. The authors present an overview of the mechanistic origins of metabolite dynamics and heterogeneity, why they are important, their potential effects in chemical production processes, and tools and strategies for engineering metabolite dynamics and heterogeneity. The authors emphasize that the ability to control metabolite dynamics and heterogeneity will bring new avenues of engineering to increase productivity of microbial strains.
© 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Keywords:  cell-to-cell variation; metabolic engineering; metabolite dynamics; metabolite heterogeneity; synthetic biology

Mesh:

Substances:

Year:  2017        PMID: 28901715     DOI: 10.1002/biot.201700422

Source DB:  PubMed          Journal:  Biotechnol J        ISSN: 1860-6768            Impact factor:   4.677


  8 in total

1.  Dynamic metabolic control: towards precision engineering of metabolism.

Authors:  Di Liu; Ahmad A Mannan; Yichao Han; Diego A Oyarzún; Fuzhong Zhang
Journal:  J Ind Microbiol Biotechnol       Date:  2018-01-29       Impact factor: 3.346

Review 2.  Bacterial metabolic heterogeneity: origins and applications in engineering and infectious disease.

Authors:  Trent D Evans; Fuzhong Zhang
Journal:  Curr Opin Biotechnol       Date:  2020-06-20       Impact factor: 9.740

3.  Design of a programmable biosensor-CRISPRi genetic circuits for dynamic and autonomous dual-control of metabolic flux in Bacillus subtilis.

Authors:  Yaokang Wu; Taichi Chen; Yanfeng Liu; Rongzhen Tian; Xueqin Lv; Jianghua Li; Guocheng Du; Jian Chen; Rodrigo Ledesma-Amaro; Long Liu
Journal:  Nucleic Acids Res       Date:  2020-01-24       Impact factor: 16.971

4.  Computation of Single-Cell Metabolite Distributions Using Mixture Models.

Authors:  Mona K Tonn; Philipp Thomas; Mauricio Barahona; Diego A Oyarzún
Journal:  Front Cell Dev Biol       Date:  2020-12-22

5.  Massively parallel gene expression variation measurement of a synonymous codon library.

Authors:  Alexander Schmitz; Fuzhong Zhang
Journal:  BMC Genomics       Date:  2021-03-02       Impact factor: 3.969

6.  Transient Antibiotic Tolerance Triggered by Nutrient Shifts From Gluconeogenic Carbon Sources to Fatty Acid.

Authors:  Christopher J Hartline; Ruixue Zhang; Fuzhong Zhang
Journal:  Front Microbiol       Date:  2022-03-11       Impact factor: 5.640

Review 7.  Microbial metabolic noise.

Authors:  Andreas E Vasdekis; Abhyudai Singh
Journal:  WIREs Mech Dis       Date:  2020-11-23

Review 8.  Dynamic control in metabolic engineering: Theories, tools, and applications.

Authors:  Christopher J Hartline; Alexander C Schmitz; Yichao Han; Fuzhong Zhang
Journal:  Metab Eng       Date:  2020-09-11       Impact factor: 9.783

  8 in total

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