Elucidating selection processes for antibiotic resistance in sewage treatment plants using metagenomics
Graphical abstract
Introduction
The development of antibiotic resistant bacteria has rapidly become a global health concern, accounting for hundreds of thousands of deaths yearly (Review on Antimicrobial Resistance, 2014). Although overuse and misuse of antibiotics for humans and animals are undoubtedly major drivers behind the development of resistance in human pathogens, there is increasing recognition of the involvement of other factors and settings in resistance emergence and dissemination (Ashbolt et al., 2013, Finley et al., 2013), necessitating a “one health” approach to resistance development. Sewage treatment plants (STPs) have been proposed as hotspots for resistance development (Berendonk et al., 2015, Berglund et al., 2015, Laht et al., 2014, Rizzo et al., 2013, Yang et al., 2014) as well as point sources for dissemination of resistance genes and resistant bacteria (LaPara et al., 2011, Pruden, 2014). To facilitate emergence of novel resistance determinants, a selection pressure from antibiotics and/or other antibacterial agents is likely critical, as it constitutes a prerequisite for fixation of mutations or gene transfer events in bacterial populations. In addition, antibiotics have the potential to increase the likelihood for such events, as they have been shown to – at sufficient concentrations – increase the rates of mutation (Chow et al., 2015, Morero et al., 2011), induce transposon activity (Barraud and Ploy, 2015, Hocquet et al., 2012), recombination (López and Blázquez, 2009), and mobilization of DNA (Johnson et al., 2015, Jutkina et al., 2016, López and Blázquez, 2009, Prudhomme et al., 2006). In addition, antibiotic selection may increase the number of donors of resistance factors, if these have a selective advantage over susceptible bacteria, in turn increasing transfer opportunities. It is known that antibiotics are present in STPs at varying concentrations (Lindberg et al., 2005, Marx et al., 2015, Michael et al., 2013), but knowledge about whether these concentrations are selective is currently lacking (Ågerstrand et al., 2015, Boxall et al., 2012). Although antibiotics concentrations seldom or never reach minimal inhibitory concentrations (MICs) for most bacteria (European Committee on Antimicrobial Susceptibility Testing,, Michael et al., 2013), antibiotics can exert a selection pressure at levels far below the inhibitory concentrations (Gullberg et al., 2011, Lundström et al., 2016). We recently published predicted no-effect concentrations for resistance selection for 111 antibiotics (Bengtsson-Palme and Larsson, 2016) and thus for the first time have a comprehensive reference framework to compare measured concentrations of antibiotics to.
To understand the selection processes for antibiotic resistance in STPs it is fundamental to compare the frequencies of resistance genes and resistant bacteria coming into and leaving the treatment plants. There is conflicting evidence regarding the efficiency of resistance gene removal in STPs. A large diversity of resistance genes can be detected both in activated sludge and treated effluent (Szczepanowski et al., 2009), but most studies have reported efficient reduction of resistance gene abundances in effluent water (Al-Jassim et al., 2015, Auerbach et al., 2007, Yang et al., 2014). In contrast, Mao et al. (2015) reported little effect of sewage treatment on the relative resistance gene abundances in effluent water. The efficiency of resistance gene removal in sludge seems to be highly variable, with large differences of removal rates for different resistance genes in Chinese STPs, and some genes being enriched regardless of comparing to bacterial gene content or sample volumes (Yang et al., 2014, Zhang et al., 2015). However, antibiotic resistance genes and resistant bacteria can increase in relative abundance through the treatment process even in the absence of direct selection by a specific antibacterial substance. Both co- and cross-resistance between different types of antibiotic substances is well-known (Alekshun and Levy, 2007, Nikaido, 2009). In addition, metals and biocides have the potential to co-select for antibiotic resistance genes (Baker-Austin et al., 2006, Pal et al., 2014). The severity of the risk associated with a resistance gene finding is also highly context dependent – if a resistance gene is found on a mobile genetic element, risks for transmission increase substantially (Bengtsson-Palme and Larsson, 2015, Dantas and Sommer, 2012, Martinez et al., 2015). Thus, investigation of the regions surrounding each resistance gene is of high importance, but to gain a comprehensive picture of these regions is not straightforward, as most bacteria in the environment cannot be cultured (Amann et al., 1995) and assembly of metagenomic sequence data is difficult, particularly for resistance regions (Bengtsson-Palme et al., 2014). It is also possible that various biotic and abiotic factors in STPs shape the bacterial communities such that species carrying certain types of resistance genes increase in abundance even in the absence of any selection pressure from antibacterials. Thus, analysis of changes of resistance gene abundances should preferably be done in relation to taxonomic changes.
In this paper we aim to shed light on whether antibiotics exert a direct selection pressure for resistant bacteria in STPs. To this end, we have combined chemical measurements of antibiotics concentrations with shotgun metagenomic DNA sequencing to explore the relative abundances of antibiotic resistance genes throughout the treatment process, and interpret these abundances in relation to estimated minimal selective concentrations and genetic contexts. Furthermore, we want to assess the alternative hypothesis that increases of antibiotic resistance genes could be due to selection by other potentially selective agents than the antibiotic they confer resistance to. Therefore, we have also analyzed the concentrations of metals and biocides and the frequencies of resistance genes towards these compounds, along with changes in taxonomic composition. We find that although STPs greatly reduced the number of resistance genes per volume of water, their relative abundance per bacterial 16S rRNA was only moderately decreased. Worryingly, a few resistance genes, including the carbapenemase gene OXA-48, were enriched in the treatment process, underscoring the importance of considering dissemination in the risk assessment of STPs in relation to antibiotic resistance.
Section snippets
Sample collection
Water and sludge samples were collected from three different municipal STPs: Henriksdal (Stockholm, Sweden), Kungsängsverket (Uppsala, Sweden) and Käppala (Lidingö, Sweden) (Table S1). The Henriksdal samples were collected on 2012-09-25, and the Uppsala and Käppala samples on 2012-09-26. These STPs serve between 164,000 and 782,000 persons and receive a mix of sewage from municipal, hospital and industrial sources as well as storm water (full details in Table S2). Both those days were
Concentrations of antibiotics, metals and antibacterial biocides
We detected ten out of sixteen investigated antibiotics in the influent and seven in the effluent (Table S3). Ciprofloxacin, norfloxacin, ofloxacin, oxytetracycline and tetracycline were all efficiently removed in the treated water, while sulfamethoxazole was only partially removed. Concentrations of clarithromycin, clindamycin, fluconazole and trimethoprim were not substantially affected by the treatment process. Both ciprofloxacin (up to 910 ng/L) and tetracycline (up to 4553 ng/L) were
Discussion
To our best knowledge, this study represents the most comprehensive investigation to date of resistance genes against antibiotics, biocides and metals and their co-selection potential in sewage treatment plants. In some influent samples, ciprofloxacin and tetracycline were found at concentrations predicted to select for resistance. Despite this, there does not seem to be direct selection for resistance genes to any particular antibiotic classes in the STPs. Furthermore, we found limited support
Conclusions
This broad and explorative analysis of resistance genes provides no clear evidence for direct selection by any particular class of antibiotics in Swedish STPs. Similarly, we find no strong evidence for selection of biocide and metal resistance, and thus co-selection of antibiotic resistance genes. Throughout the treatment process, other selective pressures, such as oxygen availability, are likely to influence the composition of resistance genes more than antibiotic selection does. Changes in
Acknowledgements
The authors acknowledge financial support from the Swedish Research Council (VR), the Swedish Research Council for Environment, Agriculture and Spatial Planning (FORMAS), the Swedish Foundation for Strategic Environmental Research (MISTRA), and the Centre for Antibiotic Resistance Research at University of Gothenburg (CARe). The authors thank the personnel at the Käppala, Henriksdal and Kungsängsverket treatment plants for their co-operation and assistance with the sampling, Olle Sundin and
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Present address: Science for Life Laboratory, Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Box 1031, SE-171 21 Solna, Stockholm, Sweden.