Whole genome sequencing for the risk assessment of probiotic lactic acid bacteria

Probiotic bacteria exhibit beneficial effects on human and/or animal health, and have been widely used in foods and fermented products for decades. Most probiotics consist of lactic acid bacteria (LAB), which are used in the production of various food products but have also been shown to have the ability to prevent certain diseases. With the expansion of applications for probiotic LAB, there is an increasing concern with regard to safety, as cases with adverse effects, i.e., severe infections, transfer of antimicrobial resistance genes, etc., can occur. Currently, in vitro assays remain the primary way to assess the properties of LAB. However, such methodologies are not meeting the needs of strain risk assessment on a high-throughput scale, in the context of the evolving concept of food safety. Analyzing the complete genetic information, including potential virulence genes and other determinants with a negative impact on health, allows for assessing the safe use of the product, for which whole-genome sequencing (WGS) of individual LAB strains can be employed. Genomic data can also be used to understand subtle differences in the strain level important for beneficial effects, or protect patents. Here, we propose that WGS-based bioinformatics analyses are an ideal and cost-effective approach for the initial in silico microbial risk evaluation, while the technique may also increase our understanding of LAB strains for food safety and probiotic property evaluation.

Automated summary

The use of probiotic bacteria in foods and fermented products can have positive effects on human and animal health. However, there is increasing concern about their safety and potential adverse effects. Currently, in vitro assays are the primary method for evaluating probiotic properties, but they may not be sufficient for high-throughput strain risk assessment. Whole-genome sequencing (WGS) of individual LAB strains can provide valuable genetic information for assessing safety and understanding strain differences. WGS-based bioinformatics analyses are suggested as an ideal and cost-effective approach for in silico microbial risk evaluation and improving our understanding of LAB strains for food safety and probiotic property evaluation.