Literature DB >> 20226723

Toward design-based engineering of industrial microbes.

Keith E J Tyo1, Kanokarn Kocharin, Jens Nielsen.   

Abstract

Engineering industrial microbes has been hampered by incomplete knowledge of cell biology. Thus an iterative engineering cycle of modeling, implementation, and analysis has been used to increase knowledge of the underlying biology while achieving engineering goals. Recent advances in Systems Biology technologies have drastically improved the amount of information that can be collected in each iteration. As well, Synthetic Biology tools are melding modeling and molecular implementation. These advances promise to move microbial engineering from the iterative approach to a design-oriented paradigm, similar to electrical circuits and architectural design. Genome-scale metabolic models, new tools for controlling expression, and integrated -omics analysis are described as key contributors in moving the field toward Design-based Engineering. Copyright 2010 Elsevier Ltd. All rights reserved.

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Year:  2010        PMID: 20226723      PMCID: PMC2885540          DOI: 10.1016/j.mib.2010.02.001

Source DB:  PubMed          Journal:  Curr Opin Microbiol        ISSN: 1369-5274            Impact factor:   7.934


  58 in total

1.  Integrating high-throughput and computational data elucidates bacterial networks.

Authors:  Markus W Covert; Eric M Knight; Jennifer L Reed; Markus J Herrgard; Bernhard O Palsson
Journal:  Nature       Date:  2004-05-06       Impact factor: 49.962

Review 2.  Use of genome-scale microbial models for metabolic engineering.

Authors:  Kiran Raosaheb Patil; Mats Akesson; Jens Nielsen
Journal:  Curr Opin Biotechnol       Date:  2004-02       Impact factor: 9.740

Review 3.  The growing scope of applications of genome-scale metabolic reconstructions using Escherichia coli.

Authors:  Adam M Feist; Bernhard Ø Palsson
Journal:  Nat Biotechnol       Date:  2008-06       Impact factor: 54.908

4.  Genome-scale analysis of Streptomyces coelicolor A3(2) metabolism.

Authors:  Irina Borodina; Preben Krabben; Jens Nielsen
Journal:  Genome Res       Date:  2005-06       Impact factor: 9.043

5.  Enhancing sesquiterpene production in Saccharomyces cerevisiae through in silico driven metabolic engineering.

Authors:  Mohammad A Asadollahi; Jérôme Maury; Kiran Raosaheb Patil; Michel Schalk; Anthony Clark; Jens Nielsen
Journal:  Metab Eng       Date:  2009-07-18       Impact factor: 9.783

6.  High-throughput quantitative metabolomics: workflow for cultivation, quenching, and analysis of yeast in a multiwell format.

Authors:  Jennifer Christina Ewald; Stéphanie Heux; Nicola Zamboni
Journal:  Anal Chem       Date:  2009-05-01       Impact factor: 6.986

Review 7.  RNA-Seq: a revolutionary tool for transcriptomics.

Authors:  Zhong Wang; Mark Gerstein; Michael Snyder
Journal:  Nat Rev Genet       Date:  2009-01       Impact factor: 53.242

8.  Modeling Lactococcus lactis using a genome-scale flux model.

Authors:  Ana Paula Oliveira; Jens Nielsen; Jochen Förster
Journal:  BMC Microbiol       Date:  2005-06-27       Impact factor: 3.605

9.  Reconstruction of the yeast Snf1 kinase regulatory network reveals its role as a global energy regulator.

Authors:  Renata Usaite; Michael C Jewett; Ana Paula Oliveira; John R Yates; Lisbeth Olsson; Jens Nielsen
Journal:  Mol Syst Biol       Date:  2009-11-03       Impact factor: 11.429

10.  PROMOT: modular modeling for systems biology.

Authors:  Sebastian Mirschel; Katrin Steinmetz; Michael Rempel; Martin Ginkel; Ernst Dieter Gilles
Journal:  Bioinformatics       Date:  2009-01-15       Impact factor: 6.937

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  21 in total

Review 1.  Computational tools for the synthetic design of biochemical pathways.

Authors:  Marnix H Medema; Renske van Raaphorst; Eriko Takano; Rainer Breitling
Journal:  Nat Rev Microbiol       Date:  2012-01-23       Impact factor: 60.633

2.  C4GEM, a genome-scale metabolic model to study C4 plant metabolism.

Authors:  Cristiana Gomes de Oliveira Dal'Molin; Lake-Ee Quek; Robin William Palfreyman; Stevens Michael Brumbley; Lars Keld Nielsen
Journal:  Plant Physiol       Date:  2010-10-25       Impact factor: 8.340

Review 3.  Metabolic engineering of Saccharomyces cerevisiae: a key cell factory platform for future biorefineries.

Authors:  Kuk-Ki Hong; Jens Nielsen
Journal:  Cell Mol Life Sci       Date:  2012-03-03       Impact factor: 9.261

Review 4.  The future of metabolic engineering and synthetic biology: towards a systematic practice.

Authors:  Vikramaditya G Yadav; Marjan De Mey; Chin Giaw Lim; Parayil Kumaran Ajikumar; Gregory Stephanopoulos
Journal:  Metab Eng       Date:  2012-05       Impact factor: 9.783

Review 5.  Engineering synergy in biotechnology.

Authors:  Jens Nielsen; Martin Fussenegger; Jay Keasling; Sang Yup Lee; James C Liao; Kristala Prather; Bernhard Palsson
Journal:  Nat Chem Biol       Date:  2014-05       Impact factor: 15.040

6.  Dynamic knockdown of E. coli central metabolism for redirecting fluxes of primary metabolites.

Authors:  Irene M Brockman; Kristala L J Prather
Journal:  Metab Eng       Date:  2014-12-24       Impact factor: 9.783

7.  Enhanced production of L-phenylalanine in Corynebacterium glutamicum due to the introduction of Escherichia coli wild-type gene aroH.

Authors:  Chuanzhi Zhang; Junli Zhang; Zhen Kang; Guocheng Du; Xiaobin Yu; Tianwen Wang; Jian Chen
Journal:  J Ind Microbiol Biotechnol       Date:  2013-03-23       Impact factor: 3.346

8.  Optimizing pentose utilization in yeast: the need for novel tools and approaches.

Authors:  Eric Young; Sun-Mi Lee; Hal Alper
Journal:  Biotechnol Biofuels       Date:  2010-11-16       Impact factor: 6.040

9.  Rewiring yeast sugar transporter preference through modifying a conserved protein motif.

Authors:  Eric M Young; Alice Tong; Hang Bui; Caitlin Spofford; Hal S Alper
Journal:  Proc Natl Acad Sci U S A       Date:  2013-12-16       Impact factor: 11.205

10.  Genome-scale consequences of cofactor balancing in engineered pentose utilization pathways in Saccharomyces cerevisiae.

Authors:  Amit Ghosh; Huimin Zhao; Nathan D Price
Journal:  PLoS One       Date:  2011-11-04       Impact factor: 3.240

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