Knowledge of the origins and dissemination of antibiotic resistance genes (ARGs) is essential for understanding modern resistomes in the environment. The mechanisms of the dissemination of ARGs can be revealed through comparative studies on the metagenomic profiling of ARGs between relatively pristine and human-impacted environments. The deep ocean bed of the South China Sea (SCS) is considered to be largely devoid of anthropogenic impacts, while the Pearl River Estuary (PRE) in south China has been highly impacted by intensive human activities. Commonly used antibiotics (sulfamethazine, norfloxacin, ofloxacin, tetracycline, and erythromycin) have been detected through chemical analysis in the PRE sediments, but not in the SCS sediments. In the relatively pristine SCS sediments, the most prevalent and abundant ARGs are those related to resistance to macrolides and polypeptides, with efflux pumps as the predominant mechanism. In the contaminated PRE sediments, the typical ARG profiles suggest a prevailing resistance to antibiotics commonly used in human health and animal farming (including sulfonamides, fluoroquinolones, and aminoglycosides), and higher diversity in both genotype and resistance mechanism than those in the SCS. In particular, antibiotic inactivation significantly contributed to the resistance to aminoglycosides, β-lactams, and macrolides observed in the PRE sediments. There was a significant correlation in the levels of abundance of ARGs and those of mobile genetic elements (including integrons and plasmids), which serve as carriers in the dissemination of ARGs in the aquatic environment. The metagenomic results from the current study support the view that ARGs naturally originate in pristine environments, while human activities accelerate the dissemination of ARGs so that microbes would be able to tolerate selective environmental stress in response to anthropogenic impacts.
This study applied Illumina high-throughput sequencing to explore the microbial communities and functions in anaerobic digestion sludge (ADS) from two wastewater treatment plants based on a metagenomic view. Taxonomic analysis using SILVA SSU database indicated that Proteobacteria (9.52-13.50 %), Bacteroidetes (7.18 %-10.65 %) and Firmicutes (7.53 %-9.46 %) were the most abundant phyla in the ADS. Differences of microbial communities between the two types of ADS were identified. Genera of Methanosaeta and Methanosarcina were the major methanogens. Functional analysis by SEED subsystems showed that the basic metabolic functions of metagenomes in the four ADS samples had no significant difference among them, but they were different from other microbial communities from activated sludge, human faeces, ocean and soil. Abundances of genes in methanogenesis pathway were also quantified using a methanogenesis genes database extracted from KEGG. Results showed that acetotrophic was the major methanogenic pathway in the anaerobic sludge digestion.
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Arsenic contamination in a water system is an urgent environmental problem that has caused severe endemic arsenicosis in south and southeast Asian countries. It is well known that microbially mediated arsenic metabolism can enhance arsenic mobility, bioavailability, and toxicity. Here, for the first time, we applied the Illumina high-throughput metagenomic and metatranscriptomic approaches to study the distribution, diversity, abundance, and expression of microbial arsenic metabolism genes in activated sludge and five coastal sediments. An average depth of ~2.6 Gb clean data for each sample was finally obtained for BLAST analysis after quality filtration and normalization. The results revealed that: (1) highly diverse arsenic metabolism-like genes were found and the overall abundance varied from 0.18 % to 0.26 % in the six metagenomic data sets; (2) arsenic metabolism-like genes were expressed with extremely low levels or no expression at all in activated sludge; and (3) the distribution, diversity, and abundance of aioA-like, arrA-like, arsB-like, ACR3-like, and arsM-like genes varied significantly in the six surveyed environments. This study provided a novel perspective on understanding the ecology of arsenic metabolism in different water environments using high-throughput sequencing technique.
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