Combined Targeted and Non-targeted PCR Based Methods Reveal High Levels of Compliance in Probiotic Products Sold as Dietary Supplements in United States and Canada
Bibliographic record
Abstract
Probiotics are defined as “live microorganisms that, when administered in adequate amounts, confer a health benefit on the host”. The diverse health benefits have contributed to rapid increase in probiotic consumption and in the value of probiotic market, valued at USD 46 billion in 2019. For probiotics to be effective, the correct species/strains should be delivered viable in an adequate dose. The most commonly used methods for species/strain identification are DNA based methods including targeted and non-targeted methods (e.g. high-throughput sequencing, HTS). Using different DNA based methods, previous studies reported several cases of non-compliance in probiotic products. The objectives of this study are to evaluate levels of compliance in probiotic products (presence of all declared species/strains, absence of any contaminants or undeclared species, and meeting the declared minimum viable cell count) and to compare the performance of targeted and non-targeted methods in probiotic authentication. To the best of our knowledge, this is the largest study of its kind, testing 182 probiotic products, containing a total of 520 strains, collected from USA and Canada. Using species-specific assays, 11 species could not be detected in ten products. Missing species were Lactobacillus casei in seven products, Bifidobacterium longum and B. bifidum in one product, B. longum in one product while B. longum subsp. longum was mislabelled as B. longum subsp. infantis in another. Additionally, undeclared B. animalis subsp. lactis was detected in one product. Viable count was determined for 72 samples and was found to be lower than declared in five samples, including one product showing no viable cells. Overall, non-compliance was observed in 15 out of 182 products (8%). Additionally, undeclared species at relative abundance of ~1-2% were found in 14 products using HTS, however, their presence could not be confirmed using species-specific assays. The results show that targeted PCR based methods enable species and strain level identification. The results also highlight the need to continue to develop strain-specific assays appropriate for use with multi-strain products. True strain-specific assays will enable strain authentication in both single-strain products and multi-strain products to ensure probiotic products meet the label claims and ensure probiotic efficacy.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".