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Record W4206341757 · doi:10.1186/s40793-022-00398-1

Metagenomic community composition and resistome analysis in a full-scale cold climate wastewater treatment plant

2022· article· en· W4206341757 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueEnvironmental Microbiome · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicPharmaceutical and Antibiotic Environmental Impacts
Canadian institutionsUniversity of OttawaUniversity of Manitoba
FundersBritish Columbia Centre for Disease ControlUniversity of British ColumbiaUniversity of Manitoba
KeywordsResistomeIntegronBiologyActinobacteriaProteobacteriaSiphoviridaeMetagenomicsFirmicutesMicrobiologyAntibiotic resistanceBacteriophage16S ribosomal RNABacteriaGeneticsAntibioticsGene

Abstract

fetched live from OpenAlex

Abstract Background Wastewater treatment plants are an essential part of maintaining the health and safety of the general public. However, they are also an anthropogenic source of antibiotic resistance genes. In this study, we characterized the resistome, the distribution of classes 1–3 integron-integrase genes ( intI1, intI2, and intI3 ) as mobile genetic element biomarkers, and the bacterial and phage community compositions in the North End Sewage Treatment Plant in Winnipeg, Manitoba. Samples were collected from raw sewage, returned activated sludge, final effluent, and dewatered sludge. A total of 28 bacterial and viral metagenomes were sequenced over two seasons, fall and winter. Integron-integrase genes, the 16S rRNA gene, and the coliform beta-glucuronidase gene were also quantified during this time period. Results Bacterial classes observed above 1% relative abundance in all treatments were Actinobacteria (39.24% ± 0.25%), Beta-proteobacteria (23.99% ± 0.16%), Gamma-proteobacteria (11.06% ± 0.09%), and Alpha-proteobacteria (9.18 ± 0.04%). Families within the Caudovirales order: Siphoviridae (48.69% ± 0.10%), Podoviridae (23.99% ± 0.07%), and Myoviridae (19.94% ± 0.09%) were the dominant phage observed throughout the NESTP. The most abundant bacterial genera (in terms of average percent relative abundance) in influent, returned activated sludge, final effluent, and sludge, respectively, includes Mycobacterium (37.4%, 18.3%, 46.1%, and 7.7%), Acidovorax (8.9%, 10.8%, 5.4%, and 1.3%), and Polaromonas (2.5%, 3.3%, 1.4%, and 0.4%). The most abundant class of antibiotic resistance in bacterial samples was tetracycline resistance (17.86% ± 0.03%) followed by peptide antibiotics (14.24% ± 0.03%), and macrolides (10.63% ± 0.02%). Similarly, the phage samples contained a higher prevalence of macrolide (30.12% ± 0.30%), peptide antibiotic (10.78% ± 0.13%), and tetracycline (8.69% ± 0.11%) resistance. In addition, intI1 was the most abundant integron-integrase gene throughout treatment (1.14 × 10 4 gene copies/mL) followed by intI3 (4.97 × 10 3 gene copies/mL) while intI2 abundance remained low (6.4 × 10 1 gene copies/mL). Conclusions Wastewater treatment successfully reduced the abundance of bacteria, DNA phage and antibiotic resistance genes although many antibiotic resistance genes remained in effluent and biosolids. The presence of integron-integrase genes throughout treatment and in effluent suggests that antibiotic resistance genes could be actively disseminating resistance between both environmental and pathogenic bacteria.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.697
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.014
GPT teacher head0.228
Teacher spread0.214 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it