A metagenomic approach and network analysis was used to investigate the wide-spectrum profiles of antibiotic resistance genes (ARGs) and their co-occurrence patterns in 50 samples from 10 typical environments. In total, 260 ARG subtypes belonging to 18 ARG types were detected with an abundance range of 5.4 × 10 − 6 -2.2 × 10 −1 copy of ARG per copy of 16S-rRNA gene. The trend of the total ARG abundances in environments matched well with the levels of anthropogenic impacts on these environments. From the less impacted environments to the seriously impacted environments, the total ARG abundances increased up to three orders of magnitude, that is, from 3.2 × 10 − 3 to 3.1 × 10 0 copy of ARG per copy of 16S-rRNA gene. The abundant ARGs were associated with aminoglycoside, bacitracin, β-lactam, chloramphenicol, macrolide-lincosamide-streptogramin, quinolone, sulphonamide and tetracycline, in agreement with the antibiotics extensively used in human medicine or veterinary medicine/promoters. The widespread occurrences and abundance variation trend of vancomycin resistance genes in different environments might imply the spread of vancomycin resistance genes because of the selective pressure resulting from vancomycin use. The simultaneous enrichment of 12 ARG types in adult chicken faeces suggests the coselection of multiple ARGs in this production system. Non-metric multidimensional scaling analysis revealed that samples belonging to the same environment generally possessed similar ARG compositions. Based on the co-occurrence pattern revealed by network analysis, tetM and aminoglycoside resistance protein, the hubs of the ARG network, are proposed to be indicators to quantitatively estimate the abundance of 23 other co-occurring ARG subtypes by power functions.

Understanding environmental and biological influences on the dynamics of microbial communities has received great attention in microbial ecology. Here, utilizing large time-series 16S rRNA gene data, we show that in activated sludge of an environmentally important municipal wastewater treatment plant, 5-year temporal dynamics of bacterial community shows no significant seasonal succession, but is consistent with deterministic assemblage by taxonomic relatedness. Biological interactions are dominant drivers in determining the bacterial community assembly, whereas environmental conditions (mainly sludge retention time and inorganic nitrogen) partially explain phylogenetic and quantitative variances and indirectly influence bacterial assembly. We demonstrate a correlation-based statistical method to integrate bacterial association networks with their taxonomic affiliations to predict community-wide co-occurrence and co-exclusion patterns. The results show that although taxonomically closely related bacteria tend to positively co-occur (for example, out of a cooperative relationship), negative co-excluding correlations are deterministically observed between taxonomically less related species, probably implicating roles of competition in determining bacterial assembly. Overall, disclosures of the positive and negative species-species relations will improve our understanding of ecological niches occupied by unknown species and help to predict their biological functions in ecosystems.

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.

Wastewater treatment plants (WWTPs) are implicated as hotspots for the dissemination of antibacterial resistance into the environment. However, the in situ processes governing removal, persistence, and evolution of resistance genes during wastewater treatment remain poorly understood. Here, we used quantitative metagenomic and metatranscriptomic approaches to achieve a broad-spectrum view of the flow and expression of genes related to antibacterial resistance to over 20 classes of antibiotics, 65 biocides, and 22 metals. All compartments of 12 WWTPs share persistent resistance genes with detectable transcriptional activities that were comparatively higher in the secondary effluent, where mobility genes also show higher relative abundance and expression ratios. The richness and abundance of resistance genes vary greatly across metagenomes from different treatment compartments, and their relative and absolute abundances correlate with bacterial community composition and biomass concentration. No strong drivers of resistome composition could be identified among the chemical stressors analyzed, although the sub-inhibitory concentration (hundreds of ng/L) of macrolide antibiotics in wastewater correlates with macrolide and vancomycin resistance genes. Contig-based analysis shows considerable colocalization between resistance and mobility genes and implies a history of substantial horizontal resistance transfer involving human bacterial pathogens. Based on these findings, we propose future inclusion of mobility incidence (M%) and host pathogenicity of antibiotic resistance genes in their quantitative health risk ranking models with an ultimate goal to assess the biological significance of wastewater resistomes with regard to disease control in humans or domestic livestock.

Activated sludge (AS), which has been in use for 100 years, has been the most popular biological process in various wastewater treatment plants (WWTPs), in which bacteria plays central roles in pollutant removal. However, the potential relationship between bacteria taxa and the niches occupied by specific functional bacteria in AS are largely unknown. Here, correlation-based network analysis was applied to a 16S rRNA gene pyrosequencing dataset containing > 760 000 sequences of 50 AS samples from globally distributed full-scale WWTPs. The results showed that (i) bacterial assembly in AS was nonrandomly arranged by taxonomic relatedness and (ii) intra- and inter-phylum/class co-occurrence higher than expected by chance was induced by multiple deterministic processes, such as habitat filtering and competition. Moreover, based on bacterial occupancy, a prevalent core set of cosmopolitan functional bacteria (e.g. multiple nitrogen-cycling-related bacteria) was widely distributed in the AS of different WWTPs, showing strong ecological associations among them. Additionally, the AS network has statistical and structural characteristics similar to those of previously reported ecological networks, such as power-law connectivity distribution and nonrandomly connected properties. Overall, this work provides novel insights into the bacterial associations within AS and sheds light on the ecological rules guiding bacterial assembly in WWTPs.

Human sewage pollution is a major threat to public health because sewage always comes with pathogens. Human sewage is usually received and treated by wastewater treatment plants (WWTPs) to control pathogenic risks and ameliorate environmental health. However, untreated sewage that flows into water environments may cause serious waterborne diseases, as reported in India and Bangladesh. To examine the fate of the human sewage microbiome in a local municipal WWTP of Hong Kong, we used massively parallel sequencing of 16S rRNA gene to systematically profile microbial communities in samples from three sections (i.e., influent, activated sludge, and effluent) obtained monthly throughout 1 year. The results indicated that: (1) influent sewage bacterial profile reflected the human microbiome; (2) human gut bacterial community was the dominant force shaping influent sewage bacterial profile; (3) most human sewage bacteria could be effectively removed by the WWTP; (4) a total of 75 genera were profiled as potentially pathogenic bacteria, most of which were still present in the effluent although at a very low level; (5) a grouped pattern of bacterial community was observed among the same section samples but a dispersed pattern was found among the different section samples; and (6) activated sludge was less affected by the influent sewage bacteria, but it showed a significant impact on the effluent bacteria. All of these findings provide novel insights toward a mechanistic understanding of the fate of human sewage microbiome in the WWTP.

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Although the health of rivers is threatened by multiple anthropogenic stressors with increasing frequency, it remains an open question how riverine microbial communities respond to emerging micropollutants. Here, by using 16S rDNA amplicon sequencing of 60 water samples collected during different hydrological seasons, we investigated the spatio-temporal variation and the co-occurrence patterns of microbial communities in the anthropogenically impacted Jiulong River in China. The results indicated that the riverine microbial co-occurrence network had a nonrandom, modular structure, which was mainly shaped by the taxonomic relatedness of co-occurring species. Fecal indicator bacteria may survive for prolonged periods of time in river water, but they formed an independent module which had fewer interactions with typical freshwater bacteria. Multivariate analysis demonstrated that nutrients and micropollutants [i.e., pharmaceuticals and personal care products (PPCPs)] exerted combined effects in shaping α- and β-diversity of riverine microbial communities. Remarkably, we showed that a hitherto unrecognized disruptive effect of PPCPs on the abundance variations of central species and module communities was stronger than the influence of physicochemical factors, suggesting the key role played by micropollutants for the microbial co-occurrence relationships in lotic ecosystems. Overall, our findings provide novel insights into community assembly in aquatic environments experiencing anthropogenic stresses.