Antimicrobial Resistance Genes in Bangkok Toilet Waste by Income Area
by Narong Nuanmuang·Updated 2mo ago
2.6 MB1files
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Description
Narong Nuanmuang's study analyzes the comparative resistome from 27 toilet waste samples collected in March–April 2023 across low-, middle-, and high-income areas of Bangkok, Thailand. The metagenomic sequencing data was mapped to resistance gene databases, measuring abundance in fragments per kilobase per million mapped reads (FPKM). It highlights higher abundances of antibiotic, metal, and disinfectant resistance genes in low-income groups.
Use Cases
Compare antibiotic resistance gene (ARG) FPKM abundance across low-, middle-, and high-income area samples.
Analyze correlations between metal resistance gene and disinfectant resistance gene abundances within the 27 waste samples.
Investigate differences in individual ARG profiles, including acquired and intrinsic genes, between the nine collection sites.
Use metagenomic resistance gene data for city-level surveillance of antimicrobial resistance (AMR) in urban settings.
Strengths
Data is derived from 27 distinct toilet waste samples collected across nine sites.
Analysis includes genes associated with antibiotics, metals, and disinfectants, providing a multi-resistance profile.
Samples are temporally bounded from a single collection period (March–April 2023).
Focus on three distinct socioeconomic areas (low, middle, high income) within a single major city (Bangkok).
Limitations
Small sample size of 27 samples limits statistical power and generalizability.
Data is presented in a PDF report (2.6 MB), not in a structured, machine-readable tabular format.
Findings are specific to Bangkok, Thailand, and a single two-month period, limiting temporal and geographic transferability.
Provenance
Source
Narong Nuanmuang via figshare
Collection Method
Toilet waste samples collected and subjected to metagenomic sequencing, with sequences mapped to resistance gene and bacterial taxonomy databases.
Time Range
March–April 2023
Freshness
null
Geography
Bangkok, Thailand
Primary data is embedded within a PDF document; extraction and processing would be required for computational analysis. Licensed under CC BY 4.0.