Literature DB >> 28987922

The Impact of Systems Biology on Bioprocessing.

Kate Campbell1, Jianye Xia2, Jens Nielsen3.   

Abstract

Bioprocessing offers a sustainable and green approach to the production of chemicals. However, a bottleneck in introducing bioprocesses is cell factory development, which is costly and time-consuming. A systems biology approach can expedite cell factory design by using genome-wide analyses alongside mathematical modeling to characterize and predict cellular physiology. This approach can drive cycles of design, build, test, and learn implemented by metabolic engineers to optimize the cell factory performance. Streamlining of the design phase requires a clearer understanding of metabolism and its regulation, which can be achieved using quantitative and integrated omic characterization, alongside more advanced analytical methods. We discuss here the current impact of systems biology and challenges of closing the gap between bioprocessing and more traditional methods of chemical production.
Copyright © 2017 Elsevier Ltd. All rights reserved.

Keywords:  GEMs; cell factory; metabolism; omics; systems biology

Mesh:

Substances:

Year:  2017        PMID: 28987922     DOI: 10.1016/j.tibtech.2017.08.011

Source DB:  PubMed          Journal:  Trends Biotechnol        ISSN: 0167-7799            Impact factor:   19.536


  13 in total

1.  Integrated Analysis Reveals Altered Lipid and Glucose Metabolism and Identifies NOTCH2 as a Biomarker for Parkinson's Disease Related Depression.

Authors:  Mei-Xue Dong; Xia Feng; Xiao-Min Xu; Ling Hu; Yang Liu; Si-Yu Jia; Bo Li; Wei Chen; You-Dong Wei
Journal:  Front Mol Neurosci       Date:  2018-08-31       Impact factor: 5.639

2.  Mechanism-based tuning of insect 3,4-dihydroxyphenylacetaldehyde synthase for synthetic bioproduction of benzylisoquinoline alkaloids.

Authors:  Christopher J Vavricka; Takanobu Yoshida; Yuki Kuriya; Shunsuke Takahashi; Teppei Ogawa; Fumie Ono; Kazuko Agari; Hiromasa Kiyota; Jianyong Li; Jun Ishii; Kenji Tsuge; Hiromichi Minami; Michihiro Araki; Tomohisa Hasunuma; Akihiko Kondo
Journal:  Nat Commun       Date:  2019-05-01       Impact factor: 14.919

3.  Vibrio sp. dhg as a platform for the biorefinery of brown macroalgae.

Authors:  Hyun Gyu Lim; Dong Hun Kwak; Sungwoo Park; Sunghwa Woo; Jae-Seong Yang; Chae Won Kang; Beomhee Kim; Myung Hyun Noh; Sang Woo Seo; Gyoo Yeol Jung
Journal:  Nat Commun       Date:  2019-06-06       Impact factor: 14.919

Review 4.  Genome editing of lactic acid bacteria: opportunities for food, feed, pharma and biotech.

Authors:  Rosa A Börner; Vijayalakshmi Kandasamy; Amalie M Axelsen; Alex T Nielsen; Elleke F Bosma
Journal:  FEMS Microbiol Lett       Date:  2019-01-01       Impact factor: 2.742

Review 5.  Machine and deep learning meet genome-scale metabolic modeling.

Authors:  Guido Zampieri; Supreeta Vijayakumar; Elisabeth Yaneske; Claudio Angione
Journal:  PLoS Comput Biol       Date:  2019-07-11       Impact factor: 4.475

6.  Application of Stable Isotope Tracing to Elucidate Metabolic Dynamics During Yarrowia lipolytica α-Ionone Fermentation.

Authors:  Jeffrey J Czajka; Shrikaar Kambhampati; Yinjie J Tang; Yechun Wang; Doug K Allen
Journal:  iScience       Date:  2020-01-22

Review 7.  Systems and Synthetic Biology Approaches to Engineer Fungi for Fine Chemical Production.

Authors:  Leonardo Martins-Santana; Luisa C Nora; Ananda Sanches-Medeiros; Gabriel L Lovate; Murilo H A Cassiano; Rafael Silva-Rocha
Journal:  Front Bioeng Biotechnol       Date:  2018-10-03

8.  Microbial Platform for Terpenoid Production: Escherichia coli and Yeast.

Authors:  Chonglong Wang; Mudanguli Liwei; Ji-Bin Park; Seong-Hee Jeong; Gongyuan Wei; Yujun Wang; Seon-Won Kim
Journal:  Front Microbiol       Date:  2018-10-12       Impact factor: 5.640

9.  Breaking the state-of-the-art in the chemical industry with new-to-Nature products via synthetic microbiology.

Authors:  Laura Martinelli; Pablo I Nikel
Journal:  Microb Biotechnol       Date:  2019-01-31       Impact factor: 5.813

10.  Gene Tags Assessment by Comparative Genomics (GTACG): A User-Friendly Framework for Bacterial Comparative Genomics.

Authors:  Caio Rafael do Nascimento Santiago; Renata de Almeida Barbosa Assis; Leandro Marcio Moreira; Luciano Antonio Digiampietri
Journal:  Front Genet       Date:  2019-08-26       Impact factor: 4.599

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