Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 360

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Exploring Variation of Antibiotic Resistance Genes in Activated Sludge over a Four-Year Period through a Metagenomic Approach

Yang, Ying, Li, Bing, Ju, Feng, Zhang, Tong·2013·Environmental Science & Technology

Abstract

In this study, the profiles of ARGs in activated sludge from the Shatin WWTP of Hong Kong were investigated using metagenomic analysis over a four-year period. Forty giga base pairs of metagenomic data were generated from eight activated sludge samples collected biannually at two seasons (winter and summer) from July 2007 to January 2011. A structured database of ARGs was proposed and constructed to facilitate the classification of ARGs in the collected samples from metagenomic data using a customized script. Analysis of the data showed the existence of a broad-spectrum of different ARGs, some of which have never been reported in activated sludge before. The most abundant ARGs were aminoglycoside and tetracycline resistance genes, followed by resistance genes of sulfonamide, multidrug, and chloramphenicol. Seasonal fluctuations were observed for 3 types of ARGs, that is, resistance genes of tetracycline, sulfonamide, and vancomycin. The abundances of these resistance genes were generally higher in the samples collected in the winters than the samples collected in the contiguous summer. Further analyses were carried out for the presence of subtypes of ARGs for aminoglycoside, tetracycline, and beta-lactam. The abundances of some ARGs subtypes were inconsistent with those reported in previous studies of activated sludge using the PCR approach. Statistical analyses showed that the activated sludge data sets from this study can be distinguished from other types of samples based on their ARGs profiles. Furthermore, the results of this study demonstrate that a high throughput-based metagenomic approach combined with a structured database of ARGs provides a powerful tool for a comprehensive survey of the various ARGs not only in the activated sludge of a WWTP but in other environmental samples as well. Thus, the profiling of ARGs in other ecologically important environmental matrixes may help elucidate those environmental factors contributing to the spread of ARGs.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1021/es4017365

Cites

2 of 2 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Cited by

See all 360

Metadata

Authors
Yang, Y., Li, B., Ju, F., & Zhang, T.
Venue
Environmental Science & Technology
Published
2013-08-29
Volume
47
Issue
18
Pages
10197-10205
ISSN
  • 0013-936X (ISSN-L)
  • 1520-5851
OpenAlex
W1989688741
Cited by
360
References
2
FWCI
13.95
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.