Metabolic engineering applications of the Escherichia coli bacterial artificial chromosome
•The bacterial artificial chromosome (BAC) was investigated for metabolic engineering.•BAC increased 3HB productivity by 18% compared to multi-copy expression.•BAC expression of a native pathway closely mimicked chromosomal expression.•BAC allows pathway optimization compatible with subsequent chrom...
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Veröffentlicht in: | Journal of biotechnology 2019-11, Vol.305, p.43-50 |
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Sprache: | eng |
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Zusammenfassung: | •The bacterial artificial chromosome (BAC) was investigated for metabolic engineering.•BAC increased 3HB productivity by 18% compared to multi-copy expression.•BAC expression of a native pathway closely mimicked chromosomal expression.•BAC allows pathway optimization compatible with subsequent chromosomal integration.
In metabolic engineering and synthetic biology, the number of genes expressed to achieve better production and pathway regulation in each strain is steadily increasing. The method of choice for expression in Escherichia coli is usually one or several multi-copy plasmids. Meanwhile, the industry standard for long-term, robust production is chromosomal integration of the desired genes. Despite recent advances, genetic manipulation of the bacterial chromosome remains more time consuming than plasmid construction. To allow screening of different metabolic engineering strategies at a level closer to industry while maintaining the molecular-biology advantages of plasmid-based expression, we have investigated the single-copy bacterial artificial chromosome (BAC) as a development tool for metabolic engineering. Using (R)-3-hydroxybutyrate as a model product, we show that BAC can outperform multi-copy plasmids in terms of yield, productivity and specific growth rate, with respective increases of 12%, 18%, and 5%. We both show that gene expression by the BAC simplifies pathway optimization and that the phenotype of pathway expression from BAC is very close to that of chromosomal expression. From these results, we conclude that the BAC can provide a simple platform for performing pathway design and optimization. |
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ISSN: | 0168-1656 1873-4863 1873-4863 |
DOI: | 10.1016/j.jbiotec.2019.09.002 |