Molecular characterization of microbial communities in Canadian pulp and paper activated sludge and quantification of a novel<i>Thiothrix eikelboomii</i>-like bulking filament
Bibliographic record
Abstract
We examined the microbial community structure and quantified the levels of the filamentous bulking organism Thiothrix eikelboomii in samples of activated sludge mixed liquor suspended solids (MLSS) from Canadian pulp and paper mills. Libraries of chaperonin 60 (cpn60) gene sequences were prepared from MLSS total microbial community DNA and each was compared with cpnDB, a reference database of cpn60 sequences (http://cpndb.cbr.nrc.ca) for assignment of taxonomic identities. Sequences similar to but distinct from the type strain of T. eikelboomii AP3 (ATCC 49788T) (approximately 89% identity over 555 bp) were recovered at high frequency from a mill sample that was experiencing bulking problems at the time of sample collection, which corresponded to microscopic observations using fluorescent in situ hybridization with commercially available 16S rDNA-based probes. We enumerated this strain in five mill-derived MLSS samples using real-time quantitative PCR (qPCR) and found that two samples had high levels of the bulking strain (>1012 genomes/g MLSS) and two contained lower but detectable levels of this organism. None of the mill samples contained cpn60 sequences that were identical to the type strain of T. eikelboomii. This technique shows promise for monitoring pulp and paper mill wastewater treatment systems by detecting and enumerating this strain of T. eikelboomii, which may be specific to pulp and paper mill wastewater treatment systems.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".