The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Metagenomic Profiles of Antibiotic Resistance Genes (ARGs) between Human Impacted Estuary and Deep Ocean Sediments
Abstract
Knowledge of the origins and dissemination of antibiotic resistance genes (ARGs) is essential for understanding modern resistomes in the environment. The mechanisms of the dissemination of ARGs can be revealed through comparative studies on the metagenomic profiling of ARGs between relatively pristine and human-impacted environments. The deep ocean bed of the South China Sea (SCS) is considered to be largely devoid of anthropogenic impacts, while the Pearl River Estuary (PRE) in south China has been highly impacted by intensive human activities. Commonly used antibiotics (sulfamethazine, norfloxacin, ofloxacin, tetracycline, and erythromycin) have been detected through chemical analysis in the PRE sediments, but not in the SCS sediments. In the relatively pristine SCS sediments, the most prevalent and abundant ARGs are those related to resistance to macrolides and polypeptides, with efflux pumps as the predominant mechanism. In the contaminated PRE sediments, the typical ARG profiles suggest a prevailing resistance to antibiotics commonly used in human health and animal farming (including sulfonamides, fluoroquinolones, and aminoglycosides), and higher diversity in both genotype and resistance mechanism than those in the SCS. In particular, antibiotic inactivation significantly contributed to the resistance to aminoglycosides, β-lactams, and macrolides observed in the PRE sediments. There was a significant correlation in the levels of abundance of ARGs and those of mobile genetic elements (including integrons and plasmids), which serve as carriers in the dissemination of ARGs in the aquatic environment. The metagenomic results from the current study support the view that ARGs naturally originate in pristine environments, while human activities accelerate the dissemination of ARGs so that microbes would be able to tolerate selective environmental stress in response to anthropogenic impacts.
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.
Integrity signals
Registry
Cites
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.
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
Antibiotic resistance is ancient
D’Costa, V. M., King, C. E., Kalan, L., Morar, M., Sung, W. W. L., Schwarz, C., Froese, D., Zazula, G., Calmels, F., Debruyne, R., et al. (2011) · Nature · doi:10.1038/nature10388 · Cited by 2,720
The shared antibiotic resistome of soil bacteria and human pathogens
Forsberg, K. J., Reyes, A., Wang, B., Selleck, E. M., Sommer, M. O. A., & Dantas, G. (2012) · Science · doi:10.1126/science.1220761 · Cited by 1,650
Sampling the Antibiotic Resistome
D'Costa, V. M., McGrann, K. M., Hughes, D. W., & Wright, G. D. (2006) · Science · doi:10.1126/science.1120800 · Cited by 1,594
Functional characterization of the antibiotic resistance reservoir in the human microflora
Sommer, M. O. A., Dantas, G., & Church, G. M. (2009) · Science · doi:10.1126/science.1176950 · Cited by 878
Antibiotic resistance is prevalent in an isolated cave microbiome
Bhullar, K., Waglechner, N., Pawlowski, A., Koteva, K., Banks, E. D., Johnston, M. D., Barton, H. A., & Wright, G. D. (2012) · PLoS ONE · doi:10.1371/journal.pone.0034953 · Cited by 736
The emergence of antibiotic resistance by mutation
Woodford, N., & Ellington, M. J. (2007) · Clinical Microbiology and Infection · doi:10.1111/j.1469-0691.2006.01492.x · Cited by 417
Cited by
Ma, L., Xia, Y., Li, B., Yang, Y., Li, L.-G., Tiedje, J. M., & Zhang, T. (2016) · Environmental Science & Technology · doi:10.1021/acs.est.5b03522 · Cited by 423
Self-citationStormwater loadings of antibiotic resistance genes in an urban stream
Garner, E., Benitez, R., von Wagoner, E., Sawyer, R., Schaberg, E., Hession, W. C., Krometis, L.-A. H., Badgley, B. D., & Pruden, A. (2017) · Water Research · doi:10.1016/j.watres.2017.06.046 · Cited by 131
Metadata
- Authors
- Chen, B., Yang, Y., Liang, X., Yu, K., Zhang, T., & Li, X.
- Venue
- Environmental Science & Technology
- Publisher
- American Chemical Society (ACS)
- Published
- 2013-11-04
- Volume
- 47
- Issue
- 22
- Pages
- 12753-12760
- ISSN
- 0013-936X (ISSN-L)
- 1520-5851
- OpenAlex
- W2091424319
- Cited by
- 415
- References
- 6
- FWCI
- 11.99
- 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.