Changes in bacterial composition of biofilm in a metropolitan drinking water distribution system
Bibliographic record
Abstract
AIMS: This study examined the development of bacterial biofilms within a metropolitan distribution system. The distribution system is fed with different source water (i.e. groundwater, GW and surface water, SW) and undergoes different treatment processes in separate facilities. METHODS AND RESULTS: The biofilm community was characterized using 16S rRNA gene clone libraries and functional potential analysis, generated from total DNA extracted from coupons in biofilm annular reactors fed with onsite drinking water for up to 18 months. Differences in the bacterial community structure were observed between GW and SW. Representatives that explained the dissimilarity were associated with the classes Betaproteobacteria, Alphaproteobacteria, Actinobacteria, Gammaproteobacteria and Firmicutes. After 9 months the biofilm bacterial community from both GW and SW were dominated by Mycobacterium species. The distribution of the dominant operational taxonomic unit (OTU) (Mycobacterium) positively correlated with the drinking water distribution system (DWDS) temperature. CONCLUSIONS: In this study, the biofilm community structure observed between GW and SW were dissimilar, while communities from different locations receiving SW did not show significant differences. The results suggest that source water and/or the water quality shaped by their respective treatment processes may play an important role in shaping the bacterial communities in the distribution system. In addition, several bacterial groups were present in all samples, suggesting that they are an integral part of the core microbiota of this DWDS. SIGNIFICANCE AND IMPACT OF THE STUDY: These results provide an ecological insight into biofilm bacterial structure in chlorine-treated drinking water influenced by different water sources and their respective treatment processes.
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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 | 0.000 |
| 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 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".