In short
- A probiotic is a live microorganism that confers a health benefit on the host when given in adequate amounts. Safety has to be shown for each strain, not just each species.
- In the EU, WGS data are a requirement for the risk assessment of certain microorganisms used in the food chain, and EFSA publishes how those data should be generated and reported.
- A genome-based safety assessment answers four questions: is the strain's identity unambiguous, does it carry acquired resistance genes of clinical relevance, does it carry virulence or toxin genes, and could any of these move to other bacteria.
- Genome data guide the assessment but don't replace laboratory tests such as antimicrobial susceptibility testing.
Why safety is assessed strain by strain
The accepted definition of a probiotic is "live microorganisms which when administered in adequate amounts confer a health benefit on the host", a definition reaffirmed by an international expert panel in 2014 [1]. The benefit depends on the strain, and so does the risk. Two strains of the same species can differ in plasmids, prophages and acquired genes, so a species with a long history of safe use doesn't guarantee that every new isolate is safe.
Whole genome sequencing reads the entire strain at once. That makes it the most complete way to check for genes of concern before a strain goes into a product, a trial or a regulatory dossier.
What the regulators ask for
The European Food Safety Authority (EFSA) first set out its requirements for WGS analysis of microorganisms intentionally used in the food chain in 2021 [2]. An updated statement in 2024 replaced it [3]. According to EFSA, WGS data can provide unambiguous taxonomic identification of a strain and show the presence of genes of concern. These include genes for virulence factors, for resistance to antimicrobials of clinical relevance for humans and animals, and for the production of harmful metabolites or clinically relevant antimicrobials [3]. The statement also gives quality criteria for the sequencing data and lists what should be reported [3].
Requirements differ between product categories and between countries. If your analysis will support a regulatory submission, check the current guidance for your product type before sequencing, so the data meet the expected quality standards.
What a WGS safety assessment checks
| Question | What the genome shows | Typical approach |
|---|---|---|
| Is the identity unambiguous? | Species, by comparison with type strain genomes | Average nucleotide identity (ANI) |
| Does it carry acquired AMR genes? | Known genes for resistance to clinically relevant antimicrobials | ResFinder and other curated AMR databases |
| Is any resistance intrinsic or acquired? | Whether the gene is typical of the species or was gained | Comparison with the species, genomic context |
| Does it carry virulence or toxin genes? | Matches to known virulence factors and toxins | Virulence factor database (VFDB) search |
| Could genes of concern spread? | Whether genes sit on plasmids or other mobile elements | Plasmid replicon and mobile element detection |
| Could it make harmful metabolites? | Biosynthetic gene clusters for toxins or antimicrobials | antiSMASH genome mining |
Each step has its own article on this blog: species identification by ANI, AMR gene detection, plasmids and mobile genetic elements and biosynthetic gene clusters.
Reading virulence and resistance hits carefully
Virulence screening usually relies on VFDB, which groups known virulence factors from 32 genera of common bacterial pathogens into 14 basic categories [4]. A match to this database isn't a verdict. Genes for adhesion, stress tolerance or immune interaction can resemble virulence-associated genes, and in a probiotic they may be part of how the strain colonises and acts. Each hit has to be judged on its identity, coverage and biological context.
Resistance genes need the same care. Resistance that is intrinsic to a species is usually chromosomal and not transferable. An acquired gene, particularly one on a plasmid or next to a mobile element, raises more concern, because mobile genetic elements are the main route by which resistance genes spread between bacteria [5]. ResFinder 4.0 predicts phenotypes from genotypes, but it was validated mainly on pathogens [6], so predictions for lactic acid bacteria and other probiotic genera need extra caution.
Where the genome is not enough
- Phenotypic susceptibility testing (minimum inhibitory concentrations) is still part of most safety dossiers, alongside the genome.
- A gene's presence doesn't show that it is expressed, and an unknown gene won't appear in any database.
- Strain stability matters: plasmids can be gained or lost during production, so the sequenced culture should match the production strain.
- The genome says nothing about efficacy. Health benefits still have to be shown in studies.
How BacSeq Analytics supports a safety assessment
The Standard package covers species identification, AMR, virulence, plasmid and mobile genetic element analysis. Premium adds secondary metabolite screening with antiSMASH and a consultation. Each finding is reported with the database, thresholds and genomic context used, so it can be reviewed and reproduced. If the work will support a regulatory submission, share the relevant guidance with us when you upload your data.
BacSeq Analytics reports are for research use only. They are not a regulatory approval or a clinical safety opinion.
References
- Hill C, Guarner F, Reid G, et al. Expert consensus document. The International Scientific Association for Probiotics and Prebiotics consensus statement on the scope and appropriate use of the term probiotic. Nat Rev Gastroenterol Hepatol. 2014;11:506–514. doi:10.1038/nrgastro.2014.66
- EFSA (European Food Safety Authority). EFSA statement on the requirements for whole genome sequence analysis of microorganisms intentionally used in the food chain. EFSA J. 2021;19(7):e06506. doi:10.2903/j.efsa.2021.6506
- EFSA (European Food Safety Authority). EFSA statement on the requirements for whole genome sequence analysis of microorganisms intentionally used in the food chain. EFSA J. 2024;22(8):e8912. doi:10.2903/j.efsa.2024.8912
- Liu B, Zheng D, Zhou S, et al. VFDB 2022: a general classification scheme for bacterial virulence factors. Nucleic Acids Res. 2022;50:D912–D917. doi:10.1093/nar/gkab1107
- Partridge SR, Kwong SM, Firth N, et al. Mobile genetic elements associated with antimicrobial resistance. Clin Microbiol Rev. 2018;31(4):e00088-17. doi:10.1128/CMR.00088-17
- Bortolaia V, Kaas RS, Ruppe E, et al. ResFinder 4.0 for predictions of phenotypes from genotypes. J Antimicrob Chemother. 2020;75:3491–3500. doi:10.1093/jac/dkaa345