INSACOG
收藏NIAID Data Ecosystem2026-05-02 收录
下载链接:
https://www.ncbi.nlm.nih.gov/sra/ERP165266
下载链接
链接失效反馈官方服务:
资源简介:
Antimicrobial resistance is a global and challenging issue and it needs to be tackled in the context of environmental and clinical settings to reduce its spread and minimize the therapeutic failure. Considering this, studying sewage water is a good proxy to understand the resistant and emerging bacterial communities that are risking the healthcare system and human health. The current surveillance data from different parts of the country especially from Faridabad, Haryana will help to precisely monitor and characterize the distribution of emerging bacterial pathogens and their AMR profile which are important for tracking changes in resistance patterns in the microbes living in the environment over time and would be of national and global priorities. This sewage-based surveillance is likely to provide predictive possibilities for many pathogens thereby providing important insights in public health policy. Assessing the pathogen load in the sewage water and identifying new kinds of AMR functions and their genetic linkage with mobile genetic elements will reduce the risk of any potential outbreaks of resistant pathogens. Finding the linkage of antimicrobial-resistant genes with mobile genetic elements in this study will help to understand the major vehicles responsible for the horizontal transfer of these resistant genes in the community settings and linking the data with hospital-based studies will help for better understanding of the source and clonal expansion of the resistant genes. The study also generates baseline data for key pathogens, including MDR and XDR, critical and high-priority bacteria on a Pan-India scale. To reduce the threat of AMR, it is very necessary to minimize the blanket prescription and usage of antibiotics in hospital, clinical agricultural and veterinary settings. This study will also help to understand the antibiotic contaminants in sewage water and their correlation with the prevalence of XDR pathogens and correlation with clinical pathogenic infections.
创建时间:
2025-04-19



