A Validated Real-Time PCR Method for the Specific Identification of Probiotic Strain <i>Lactobacillus rhamnosus</i> GG (ATCC 53103)
Bibliographic record
Abstract
BACKGROUND: Strain Lactobacillus rhamnosus GG is one of the best-studied and most widely used probiotic strains, with various health benefits. Because probiotic health benefits and safety are strain specific, the availability of a reliable assay for specific identification of Lactobacillus rhamnosus GG is vital to ensure probiotic efficacy. OBJECTIVE: To design and validate a probe-based real-time PCR assay for specific identification of strain Lactobacillus rhamnosus GG. METHOD: Rapid Annotation using Subsystem Technology (RAST) was used to find a unique sequence region in the genome of Lactobacillus rhamnosus GG. A probe-based assay was designed and evaluated for specificity, sensitivity, efficiency, repeatability, and reproducibility. RESULTS: RAST identified a unique gene coding for a hypothetical protein in the genome of Lactobacillus rhamnosus GG. The assay successfully amplified all 22 target samples and did not amplify any of the 28 non-target strains, achieving 100% true positive and 0% false positive results. The Limit of Detection (LOD) was determined to be 0.001 ng. Reaction efficiency values, from three dilution series, were 96.4%, 93.3%, and 96.8% with R square values of 0.9974, 0.9981, and 0.9998, respectively. Relative standard deviation (RSD, %) of repeatability was below 1% and RSD of reproducibility was below 4%. CONCLUSIONS: This Lactobacillus rhamnosus GG specific assay proved to be specific, sensitive, efficient, and reproducible. Since the assay was evaluated on two real-time PCR platforms, including a portable one, the assay can be used for onsite testing throughout the supply chain. HIGHLIGHTS: The availability of validated and reliable assays for strain-specific identification plays a vital role in achieving compliance in probiotic products.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".