Metagenomic Assembly Reveals Hosts of Antibiotic Resistance Genes and the Shared Resistome in Pig, Chicken, and Human Feces - Ma, Liping; Xia, Yu; Li, Bing; Yang, Ying; Li, Li-Guan; Tiedje, James M; Zhang, Tong (Environmental science & technology, 2016)
The risk associated with antibiotic resistance disseminating from animal and human feces is an urgent public issue. In the present study, we sought to establish a pipeline for annotating antibiotic resistance genes (ARGs) based on metagenomic assembly to investigate ARGs and their co-occurrence with associated genetic elements. Genetic elements found on the assembled genomic fragments include mobile genetic elements (MGEs) and metal resistance genes (MRGs). We then explored the hosts of these resistance genes and the shared resistome of pig, chicken and human fecal samples. High levels of tetracycline, multidrug, erythromycin, and aminoglycoside resistance genes were discovered in these fecal samples. In particular, significantly high level of ARGs (7762 ×/Gb) was detected in adult chicken feces, indicating higher ARG contamination level than other fecal samples. Many ARGs arrangements (e.g., macA-macB and tetA-tetR) were discovered shared by chicken, pig and human feces. In addition, MGEs such as the aadA5-dfrA17-carrying class 1 integron were identified on an assembled scaffold of chicken feces, and are carried by human pathogens. Differential coverage binning analysis revealed significant ARG enrichment in adult chicken feces. A draft genome, annotated as multidrug resistant Escherichia coli, was retrieved from chicken feces metagenomes and was determined to carry diverse ARGs (multidrug, acriflavine, and macrolide). The present study demonstrates the determination of ARG hosts and the shared resistome from metagenomic data sets and successfully establishes the relationship between ARGs, hosts, and environments. This ARG annotation pipeline based on metagenomic assembly will help to bridge the knowledge gaps regarding ARG-associated genes and ARG hosts with metagenomic data sets. Moreover, this pipeline will facilitate the evaluation of environmental risks in the genetic context of ARGs.