454 Pyrosequencing reveals bacterial diversity of activated sludge from 14 sewage treatment plants
Bibliographic record
Abstract
Activated sludge (AS) contains highly complex microbial communities. In this study, PCR-based 454 pyrosequencing was applied to investigate the bacterial communities of AS samples from 14 sewage treatment plants of Asia (mainland China, Hong Kong, and Singapore), and North America (Canada and the United States). A total of 259 K effective sequences of 16S rRNA gene V4 region were obtained from these AS samples. These sequences revealed huge amount of operational taxonomic units (OTUs) in AS, that is, 1183-3567 OTUs in a sludge sample, at 3% cutoff level and sequencing depth of 16,489 sequences. Clear geographical differences among the AS samples from Asia and North America were revealed by (1) cluster analyses based on abundances of OTUs or the genus/family/order assigned by Ribosomal Database Project (RDP) and (2) the principal coordinate analyses based on OTUs abundances, RDP taxa abundances and UniFrac of OTUs and their distances. In addition to certain unique bacterial populations in each AS sample, some genera were dominant, and core populations shared by multiple samples, including two commonly reported genera of Zoogloea and Dechloromonas, three genera not frequently reported (i.e., Prosthecobacter, Caldilinea and Tricoccus) and three genera not well described so far (i.e., Gp4 and Gp6 in Acidobacteria and Subdivision3 genera incertae sedis of Verrucomicrobia). Pyrosequencing analyses of multiple AS samples in this study also revealed the minority populations that are hard to be explored by traditional molecular methods and showed that a large proportion of sequences could not be assigned to taxonomic affiliations even at the phylum/class levels.
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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 | 0.001 | 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".