Linking exocellular polysaccharide structures and biosynthetic genes in lactic acid bacteria by combinatorial...

Area of Science:

• Microbiology
• Biochemistry
• Bioinformatics

Background:

• Lactic acid bacteria synthesize exocellular polysaccharides (EPS) crucial for food and health.
• EPS functional properties are dictated by their chemical structure, which is challenging to determine experimentally.
• Predicting EPS structure from genomic data is limited by difficulties in inferring glycosyltransferase specificities.

Purpose of the Study:

• To develop a computational framework for associating glycosyltransferases with specific sugar residues in EPS repeat units.
• To improve genome-based prediction of EPS structure and genotype-phenotype relationships in lactic acid bacteria.

Main Methods:

• A constrained combinatorial optimization framework was developed.
• The framework integrates multi-strain data, predicted catalytic mechanisms, and experimental evidence.
• Applied to 10 newly elucidated and 15 published EPS repeat unit structures.

Main Results:

• Successfully mapped 42% of glycosyltransferases to specific repeat-unit residues.
• Determined donor specificity for 41% of glycosyltransferases.
• Partially mapped eps genes to exocellular polysaccharide structure.

Conclusions:

• The framework enhances the understanding of genotype-phenotype relationships in lactic acid bacteria regarding EPS production.
• Provides a foundation for genome-based selection of bacteria with desired EPS characteristics.
• Advances the prediction of exocellular polysaccharide structure from genomic data.