Unraveling yeast diversity in food fermentation using ITS1-2 amplicon-based metabarcoding

Area of Science:

• Microbiology
• Food Science
• Genomics

Background:

• Fermented foods are crucial to human diets, yet characterizing their yeast ecosystems remains challenging.
• Current culture-independent methods often limit yeast identification to the genus level.
• Long-read sequencing technologies have been underutilized for yeast species identification in food fermentation.

Purpose of the Study:

• To develop and validate a long-read sequencing approach for accurate yeast species identification in fermented food processes.
• To assess the method's performance using mock communities representing sourdough, lambic beer, and cocoa fermentations.
• To apply the validated method to real fermented food samples.

Main Methods:

• An amplicon-based metabarcoding strategy targeting the full internal transcribed spacer (ITS) region (ITS1, 5.8S rRNA gene, ITS2).
• Utilized the PacBio HiFi sequencing platform for long-read sequencing.
• Validated the method with DNA-based mock communities and applied it to sourdough and lambic beer samples.

Main Results:

• Achieved accurate species-level identification for most yeast species in mock communities.
• Identified challenges in species-level resolution for the *Saccharomyces* genus.
• Observed underestimation of relative abundance for species with shorter ITS regions (e.g., *Pichia*, *Brettanomyces*).

Conclusions:

• The developed PacBio HiFi-based metabarcoding method enables unprecedented species-level yeast composition analysis in fermented foods.
• This methodology offers a significant advancement for studying fermented food microbiomes and other complex microbial communities.
• Further refinement is needed for precise identification within *Saccharomyces* and accurate abundance quantification of short-ITS species.