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Journal article

Systems Biology – A Guide for Understanding and Developing Improved Strains of Lactic Acid Bacteria

From

National Food Institute, Technical University of Denmark1

Research Group for Microbial Biotechnology and Biorefining, National Food Institute, Technical University of Denmark2

Colorado State University3

Lactic Acid Bacteria (LAB) are extensively employed in the production of various fermented foods, due to their safe status, ability to affect texture and flavor and finally due to the beneficial effect they have on shelf-life. More recently, LAB have also gained interest as production hosts for various useful compounds, particularly compounds with sensitive applications, such as food ingredients and therapeutics.

As for all industrial microorganisms, it is important to have a good understanding of the physiology and metabolism of LAB in order to fully exploit their potential, and for this purpose, many systems biology approaches are available. Systems metabolic engineering, an approach that combines optimization of metabolic enzymes/pathways at the systems level, synthetic biology as well as in silico model simulation, has been used to build microbial cell factories for production of biofuels, food ingredients and biochemicals.

When developing LAB for use in foods, genetic engineering is in general not an accepted approach. An alternative is to screen mutant libraries for candidates with desirable traits using high-throughput screening technologies or to use adaptive laboratory evolution to select for mutants with special properties.

In both cases, by using omics data and data-driven technologies to scrutinize these, it is possible to find the underlying cause for the desired attributes of such mutants. This review aims to describe how systems biology tools can be used for obtaining both engineered as well as non-engineered LAB with novel and desired properties.

Language: English
Publisher: Frontiers Media S.A.
Year: 2019
Pages: 876
ISSN: 1664302x
Types: Journal article
DOI: 10.3389/fmicb.2019.00876
ORCIDs: Liu, Jianming , Chen, Jun , Solem, Christian and Jensen, Peter Ruhdal

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