Metagenomic and Resistome Analysis of a Full-Scale Municipal Wastewater Treatment Plant in Singapore Containing Membrane Bioreactors
Bibliographic record
Abstract
Reclaimed water provides an alternative source of water supply to address problems of water scarcity in urbanized cities with high living densities and limited natural water resources. In this study, wastewater metagenomes from 6 stages of a wastewater treatment plant (WWTP) integrating conventional and membrane bioreactor (MBR) treatment were evaluated for diversity of antibiotic resistance genes (ARGs) and bacteria, and relative abundance of class 1 integron integrases (intl1). ARGs confering resistance to 12 classes of antibiotics (ARG types) persisted through the treatment stages, which included genes that confer resistance to aminoglycoside (aadA, aph(6)-I, aph(3’)-I, aac(6’)-I, aac(6’)-II, ant(2”)-I), beta-lactams [class A, class C, class D beta-lactamases (blaOXA)], chloramphenicol (acetyltransferase, exporters, floR, cmIA), fosmidomycin (rosAB), macrolide-lincosamide-streptogramin (macAB, ereA, ermFB), multidrug resistance (subunits of transporters), polymyxin (arnA), quinolone (qnrS), rifamycin (arr), sulfonamide (sul1, sul2) and tetracycline (tetM, tetG, tetE, tet36, tet39, tetR, tet43, tetQ, tetX). Although the ARG subtypes in sludge and MBR effluents reduced in diversity relative to the influent, clinically relevant beta lactamases (i.e. blaKPC, blaOXA) were detected, casting light on other potential point sources of ARG dissemination within the wastewater treatment process. To gain a deeper insight into the types of bacteria that may survive the MBR removal process, genome bins were recovered from metagenomic data of MBR effluents. A total of 101 close to complete draft genomes were assembled and annotated to reveal a variety of bacteria bearing metal resistance genes and ARGs in the MBR effluent. Three bins in particular were affiliated to Mycobacterium smegmatis, Acinetobacter Iwoffii, and Flavobacterium psychrophila, and carried aquired ARGs aac(2’)-Ib, blaOXA-278, and tet36 respectively. In terms of indicator organisms, cumulative log removal values (LRV) of Escherichia coli, Enterococci, and P. aeruginosa from influent to conventional treated effluent was lower (0-2.4), compared to MBR effluent (5.3-7.4). We conclude that MBR is an effective treatment method for reducing fecal indicators and ARGs; however, incomplete removal of P. aeruginosa in MBR treated effluents (<8 MPN/100 mL) and the presence of ARGs and intl1 underscores the need to establish if further treatment should be applied prior to reuse.
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.
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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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".