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

Area of Science:

• Microbiology
• Genomics
• Systems Biology

Background:

• Lactococcus lactis is crucial for dairy fermentation and enzyme production.
• Understanding genotype-phenotype diversity is key for annotating gene functions.
• Previous studies have characterized L. lactis strains but lacked comprehensive genotype-phenotype correlations.

Purpose of the Study:

• To identify and map relations between gene presence and phenotypes in Lactococcus lactis.
• To leverage large datasets for improved gene function annotation.
• To establish a foundation for screening bacterial collections for desired traits.

Main Methods:

• Utilized a collection of 207 phenotypes across 38 L. lactis strains.
• Employed an iterative gene selection procedure based on the Random Forest algorithm.
• Integrated gene occurrence and phenotype data to identify genotype-phenotype relations.

Main Results:

• Discovered 1388 gene-phenotype relations, confirming known associations (e.g., arabinose utilization in plant strains).
• Identified a novel gene cluster linked to melibiose utilization, serving as a potential genetic marker.
• Uncovered new relations, including genes associated with arsenite resistance and arginine metabolism.

Conclusions:

• Genotype-phenotype matching using integrated datasets can identify gene-phenotype relations and enhance gene function annotation.
• The identified relations can facilitate screening of bacterial culture collections for specific phenotypes.
• This study provides the largest dataset to date of phenotype data for 38 Lactococcus strains across 207 experiments.