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Curr Opin Biotechnol. 2015 Apr;32:1-7. doi: 10.1016/j.copbio.2014.09.003. Epub 2014 Sep 29.

Evolutionary engineering to enhance starter culture performance in food fermentations.

Author information

1
NIZO Food Research, Kernhemseweg 2, 6718 ZB Ede, The Netherlands; Top Institute Food and Nutrition, P.O. Box 557, 6700 AN Wageningen, The Netherlands. Electronic address: herwig.bachmann@nizo.com.
2
Department of Biotechnology, Delft University of Technology, Julianalaan 67, 2628 BC Delft, The Netherlands; Kluyver Centre for Genomics of Industrial Fermentation, Julianalaan 67, 2628 BC Delft, The Netherlands.
3
NIZO Food Research, Kernhemseweg 2, 6718 ZB Ede, The Netherlands; Top Institute Food and Nutrition, P.O. Box 557, 6700 AN Wageningen, The Netherlands; Kluyver Centre for Genomics of Industrial Fermentation, Julianalaan 67, 2628 BC Delft, The Netherlands; Host-Microbe Interactomics Group, Wageningen University, P.O. Box 338, 6700 AH Wageningen, The Netherlands.
4
Systems Bioinformatics/Center for Integrative Bioinformatics Vrije Universiteit, Amsterdam Institute for Molecules Medicines and Systems, Vrije Universiteit Amsterdam, de Boelelaan 1085, 1081 HV Amsterdam, The Netherlands; Kluyver Centre for Genomics of Industrial Fermentation, Julianalaan 67, 2628 BC Delft, The Netherlands.

Abstract

Microbial starter cultures are essential for consistent product quality and functional properties such as flavor, texture, pH or the alcohol content of various fermented foods. Strain improvement programs to achieve desired properties in starter cultures are diverse, but developments in next-generation sequencing lead to an increased interest in evolutionary engineering of desired phenotypes. We here discuss recent developments of strain selection protocols and how computational approaches can assist such experimental design. Furthermore the analysis of evolved phenotypes and possibilities with complex consortia are highlighted. Studies carried out with mainly yeast and lactic acid bacteria demonstrate the power of evolutionary engineering to deliver strains with novel phenotypes as well as insight into underlying mechanisms.

PMID:
25269887
DOI:
10.1016/j.copbio.2014.09.003
[Indexed for MEDLINE]

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