A database on the abundance of environmental antibiotic resistance genes.
Journal
Scientific data
ISSN: 2052-4463
Titre abrégé: Sci Data
Pays: England
ID NLM: 101640192
Informations de publication
Date de publication:
27 Feb 2024
27 Feb 2024
Historique:
received:
05
10
2023
accepted:
20
02
2024
medline:
29
2
2024
pubmed:
28
2
2024
entrez:
27
2
2024
Statut:
epublish
Résumé
Antimicrobial resistance (AMR) poses a severe threat to global health. The wide distribution of environmental antibiotic resistance genes (ARGs), which can be transferred between microbiota, especially clinical pathogens and human commensals, contributed significantly to AMR. However, few databases on the spatiotemporal distribution, abundance, and health risk of ARGs from multiple environments have been developed, especially on the absolute level. In this study, we compiled the ARG occurrence data generated by a high-throughput quantitative PCR platform from 1,403 samples in 653 sampling sites across 18 provinces in China. The database possessed 291,870 records from five types of habitats on the abundance of 290 ARGs, as well as 8,057 records on the abundance of 30 mobile genetic elements (MGEs) from 2013 to 2020. These ARGs conferred resistance to major common types of antibiotics (a total of 15 types) and represented five major resistance mechanisms, as well as four risk ranks. The database can provide information for studies on the dynamics of ARGs and is useful for the health risk assessment of AMR.
Identifiants
pubmed: 38413616
doi: 10.1038/s41597-024-03084-8
pii: 10.1038/s41597-024-03084-8
pmc: PMC10899624
doi:
Substances chimiques
Anti-Bacterial Agents
0
Types de publication
Dataset
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
250Subventions
Organisme : National Natural Science Foundation of China (National Science Foundation of China)
ID : 32161143016
Organisme : National Natural Science Foundation of China (National Science Foundation of China)
ID : 42177362
Organisme : National Natural Science Foundation of China (National Science Foundation of China)
ID : 42250410328
Organisme : Belarusian Republican Foundation for Fundamental Research (BRFFR)
ID : GPNI GR no. 20212317
Informations de copyright
© 2024. The Author(s).
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