Affiliation:
1. Bioinformatics & Modeling, R&D Digital Innovation, Chr. Hansen A/S , Bøge Allé 10-12, 2970 Hørsholm , Denmark
Abstract
Abstract
When selecting microbial strains for the production of fermented foods, various microbial phenotypes need to be taken into account to achieve target product characteristics, such as biosafety, flavor, texture, and health-promoting effects. Through continuous advances in sequencing technologies, microbial whole-genome sequences of increasing quality can now be obtained both cheaper and faster, which increases the relevance of genome-based characterization of microbial phenotypes. Prediction of microbial phenotypes from genome sequences makes it possible to quickly screen large strain collections in silico to identify candidates with desirable traits. Several microbial phenotypes relevant to the production of fermented foods can be predicted using knowledge-based approaches, leveraging our existing understanding of the genetic and molecular mechanisms underlying those phenotypes. In the absence of this knowledge, data-driven approaches can be applied to estimate genotype–phenotype relationships based on large experimental datasets. Here, we review computational methods that implement knowledge- and data-driven approaches for phenotype prediction, as well as methods that combine elements from both approaches. Furthermore, we provide examples of how these methods have been applied in industrial biotechnology, with special focus on the fermented food industry.
Publisher
Oxford University Press (OUP)
Subject
Infectious Diseases,Microbiology
Reference238 articles.
1. Hierarchy of non-glucose sugars in Escherichia coli;Aidelberg;BMC Syst Biol,2014
2. CARD 2020: antibiotic resistome surveillance with the comprehensive antibiotic resistance database;Alcock;Nucleic Acids Res,2020
3. Physicochemical modelling of cell signalling pathways;Aldridge;Nat Cell Biol,2006
4. Forest and trees: exploring bacterial virulence with genome-wide association studies and machine learning;Allen;Trends Microbiol,2021
5. Basic local alignment search tool;Altschul;J Mol Biol,1990
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