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Part of book or chapter of book . 2020
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Publications at Bielefeld University
Part of book or chapter of book . 2020
License: CC BY NC
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https://doi.org/10.1007/978-3-...
Part of book or chapter of book . 2020 . Peer-reviewed
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Metabolic Engineering in Corynebacterium glutamicum

Authors: Wendisch, Volker F.; Lee, Jin-Ho; Inui, Masayuki; Toyoda, Koichi;

Metabolic Engineering in Corynebacterium glutamicum

Abstract

Corynebacterium glutamicum strain development has adopted each metabolic engineering tool immediately upon its conception and has contributed to developing these tools further. In the last more than five decades, C. glutamicum strains have been selected and screened after undirected mutagenesis. This approach yielded industrially relevant strains, however, it was limited by the little insight that could be gained hampering transfer to related processes. Genetic engineering, the complete genome sequence and omics tools, systems biology and synthetic biology have closed this gap and provided a profound knowledge base to develop engineering strategies driven by metabolic insight. Quite recently, serendipitous untargeted approaches came into focus again since mutants selected classically e.g. using genetically encoded biosensors or by adaptive laboratory evolution could be understood when genome resequencing was combined with genetic and biochemical experiments. We will discuss metabolic engineering from the classical, genetic engineering, systems biology eras to the era of synthetic biology for C. glutamicum strain development and forecast the impact of the most recent methods such as CRISPR technology and adaptive laboratory evolution.

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Germany
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
8
Top 10%
Average
Top 10%
Green
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