Bacterial composition and cultural dynamics of microgreens-associated microbiota during selective enrichment for <i>Listeria monocytogenes</i>
Bibliographic record
Abstract
Widely regarded as a so-called "superfood," microgreens have become an increasingly significant food crop from both nutritional and agricultural standpoints. However, similar to other produce commodities that are also cultivated using modernized indoor farming methods, there have been mounting concerns over the potential risks of consuming microgreens contaminated by Listeria monocytogenes. To gain insights into the microbial properties of microgreens, this study characterized the bacterial composition of fresh microgreen retail products using amplicon sequencing of 16S rRNA genes. Dominated by Gammaproteobacteria, a total of 36 shared genera were identified as putative constituents of the microgreen core microbiome. By monitoring the dynamics of microgreen-borne bacteria undergoing a Listeria-selective cultural enrichment procedure, it was revealed that, regardless of the presence or absence of L. monocytogenes, off-target bacteria of the Klebsiella and Enterococcus genera were significantly enriched from microgreens by the primary enrichment step, with the secondary enrichment step continuing to promote the expansion of Enterococcus population. While Listeria was generally neither the most-enriched nor the dominant taxon in cultures sampled at different enrichment stages, significant enrichment of Lysinibacillus and Bacillus bacteria was detected in microgreens contaminated with L. monocytogenes, suggesting they could be co-enriched in competition with Listeria.
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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 | 0.000 | 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 | 0.000 | 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".