Exploring variation of antibiotic resistance genes in activated sludge over a four-year period through a metagenomic approach

Environ Sci Technol. 2013 Sep 17;47(18):10197-205. doi: 10.1021/es4017365. Epub 2013 Aug 29.


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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Computational Biology
  • Drug Resistance, Microbial / genetics*
  • Environmental Monitoring
  • Hong Kong
  • Metagenomics
  • Sewage / analysis*


  • Sewage