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Open Access Research article

Genotype-phenotype matching analysis of 38 Lactococcus lactis strains using random forest methods

Jumamurat R Bayjanov12, Marjo JC Starrenburg3, Marijke R van der Sijde146, Roland J Siezen1245 and Sacha AFT van Hijum12345*

Author Affiliations

1 Centre for Molecular and Biomolecular Informatics, Radboud University Medical Centre, PO Box 9101, Nijmegen, The Netherlands

2 Netherlands Bioinformatics Centre, 260 NBIC, P.O. Box 9101, Nijmegen 6500 HB, The Netherlands

3 NIZO Food Research, P.O. Box 20, BA Ede 6710, The Netherlands

4 TI Food and Nutrition, P.O. Box 557, Wageningen 6700 AN, The Netherlands

5 Kluyver Centre for Genomics of Industrial Fermentation, P.O. Box 5057, Delft, GA 2600, The Netherlands

6 Present address: Department of Genetics, University Medical Center Groningen, University of Groningen, Hanzeplein 1, Groningen 9713 GZ, The Netherlands

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BMC Microbiology 2013, 13:68  doi:10.1186/1471-2180-13-68

Published: 26 March 2013

Abstract

Background

Lactococcus lactis is used in dairy food fermentation and for the efficient production of industrially relevant enzymes. The genome content and different phenotypes have been determined for multiple L. lactis strains in order to understand intra-species genotype and phenotype diversity and annotate gene functions. In this study, we identified relations between gene presence and a collection of 207 phenotypes across 38 L. lactis strains of dairy and plant origin. Gene occurrence and phenotype data were used in an iterative gene selection procedure, based on the Random Forest algorithm, to identify genotype-phenotype relations.

Results

A total of 1388 gene-phenotype relations were found, of which some confirmed known gene-phenotype relations, such as the importance of arabinose utilization genes only for strains of plant origin. We also identified a gene cluster related to growth on melibiose, a plant disaccharide; this cluster is present only in melibiose-positive strains and can be used as a genetic marker in trait improvement. Additionally, several novel gene-phenotype relations were uncovered, for instance, genes related to arsenite resistance or arginine metabolism.

Conclusions

Our results indicate that genotype-phenotype matching by integrating large data sets provides the possibility to identify gene-phenotype relations, possibly improve gene function annotation and identified relations can be used for screening bacterial culture collections for desired phenotypes. In addition to all gene-phenotype relations, we also provide coherent phenotype data for 38 Lactococcus strains assessed in 207 different phenotyping experiments, which to our knowledge is the largest to date for the Lactococcus lactis species.