Microbiota formed on attached stainless steel coupons correlates with the natural biofilm of the sink surface in domestic kitchens
Bibliographic record
Abstract
Stainless steel coupons are frequently used in biofilm studies in the laboratory, as this material is commonly used in the food industry. The coupons are attached to different surfaces to create a "natural" biofilm to be studied further in laboratory trials. However, little has been done to investigate how well the microbiota on such coupons represents the surrounding environment. The microbiota on sink wall surfaces and on new stainless steel coupons attached to the sink wall for 3 months in 8 domestic kitchen sinks was investigated by next-generation sequencing (MiSeq) of the 16S rRNA gene derived from DNA and RNA (cDNA), and by plating and identification of colonies. The mean number of colony-forming units was about 10-fold higher for coupons than sink surfaces, and more variation in bacterial counts between kitchens was seen on sink surfaces than coupons. The microbiota in the majority of biofilms was dominated by Moraxellaceae (genus Moraxella/Enhydrobacter) and Micrococcaceae (genus Kocuria). The results demonstrated that the variation in the microbiota was mainly due to differences between kitchens (38.2%), followed by the different nucleic acid template (DNA vs RNA) (10.8%), and that only 5.1% of the variation was a result of differences between coupons and sink surfaces. The microbiota variation between sink surfaces and coupons was smaller for samples based on their RNA than on their DNA. Overall, our results suggest that new stainless steel coupons are suited to model the dominating part of the natural microbiota of the surrounding environment and, furthermore, are suitable for different downstream studies.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".