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Impact of wastewater treatment processes on antimicrobial resistance genes and their cooccurrence with virulence genes in Escherichia coli Basanta Kumar Biswal a, Alberto Mazza b, Luke Masson b, Ronald Gehr a, Dominic Frigon a,* a b

Department of Civil Engineering and Applied Mechanics, McGill University, Montre´al, Que´bec H3A 0C3, Canada National Research Council of Canada, Montre´al, Que´bec H4P 2R2, Canada

article info

abstract

Article history:

An increase in the frequency of antimicrobial resistance genes (ARGs) in bacteria including

Received 27 July 2013

Escherichia coli could be a threat to public health. This study investigated the impact of

Received in revised form

activated sludge and physicochemical wastewater treatment processes on the prevalence

29 November 2013

of ARGs in E. coli isolates. In total, 719 E. coli were isolated from the influent and effluent

Accepted 30 November 2013

(prior to disinfection) of two activated sludge and two physicochemical municipal treat-

Available online 12 December 2013

ment plants, and genotyped using DNA microarrays. Changes in the abundance of ARGs in the E. coli population were different for the two treatment processes. Activated sludge

Keywords:

treatment did not change the prevalence of ARG-possessing E. coli but increased the

Antimicrobial resistance genes

abundance of ARGs in the E. coli genome while physicochemical treatment reduced both

Escherichia coli

the prevalence of ARG-carrying E. coli as well as the frequency of ARGs in the E. coli genome.

Activated sludge

Most E. coli isolates from the four treatment plants possessed ARGs of multiple antimi-

Physicochemical

crobial classes, mainly aminoglycoside, b-lactams, quinolone and tetracyclines. In addition

DNA microarray

these isolates harboured DNA insertion sequence elements including integrase and

Insertion sequence elements

transposase. A significant positive association was found between the occurrence of ARGs and virulence genotypes. ª 2013 Elsevier Ltd. All rights reserved.

1.

Introduction

An increase in the prevalence of antimicrobial resistant bacterial strains in the environment is a major concern worldwide because of the likely transmission of antimicrobial resistance genes (ARGs) to both non-pathogenic and pathogenic strains (Bouki et al., 2013). There is evidence indicating that the human intestine is an important habitat for ARG transfer in bacteria (Salyers et al., 2004). Municipal wastewater

treatment plants (WWTPs) are also likely to be important habitats because of the continuous influx of ARGs and antibiotics (Rizzo et al., 2013). Although numerous studies have been conducted on the antimicrobial resistance profile of Escherichia coli originating from municipal wastewaters (e.g. Czekalski et al., 2012; Finch and Smith, 1986; Lefkowitz and Duran, 2009; Mezrioui and Baleux, 1994), little is known on the effects of various wastewater treatment processes on the transfer of ARGs among the E. coli population and on the mechanisms leading to the phylogenetically distant

* Corresponding author. Tel.: þ1 514 398 2475; fax: þ1 514 398 7361. E-mail address: [email protected] (D. Frigon). 0043-1354/$ e see front matter ª 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.watres.2013.11.047

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dissemination of ARGs. A significant fraction of the antimicrobial agents used in various human and animal treatments is received by WWTPs either unchanged or partially metabolized (Zhang and Li, 2011). Though the concentrations of antimicrobial agents in wastewaters are relatively low (mostly in the order of ng/L to a few mg/L) (Zhang and Li, 2011), these antimicrobial levels are sufficient to exert selective pressure for resistance development among pathogenic and nonpathogenic E. coli (Tello et al., 2012). Therefore, further studies comparing the dynamics of ARGs in wastewater treatment processes are necessary to support the design of new processes capable of controlling the dissemination of ARGs. Metagenomics revealed that Escherichia is among the 30 most commonly observed genera found in the human gut microbiome, but it does not dominate the flora as previously believed (Arumugam et al., 2011). Although normally considered as a commensal, several strains of E. coli cause human and animal diseases, both intra-intestinally (e.g., E. coli O157:H7) and extra-intestinally (e.g., uropathogenic E. coli, UPEC) (Kaper et al., 2004). Pathogenic E. coli are good candidates to carry ARGs from the external environment back to the human gut for several reasons. First, they are well adapted to grow in the gut environment and to grow outside the host (Winfield and Groisman, 2003). Second, ARG-carrying pathogenic E. coli will survive antimicrobial treatment of infections longer than non-resistant strains, which will increase the likelihood of resistance gene transmission to the rest of the microbial community. Third, extraintestinal virulence factors provide competitive advantages for intestinal colonization (Diard et al., 2010). Consequently, extraintestinal pathogens carrying ARGs would more likely transmit these genes to other members of the intestinal flora due to their longer residence time than non- extraintestinal pathogens. Finally, cooccurrence of ARG and virulence genes has been observed in studies of clinical isolates (Lee et al., 2010; Vila et al., 2002). Therefore, understanding variation in co-occurrence of ARGs and virulence genes in E. coli through wastewater treatment systems is important. Phenotypic or genotypic methods have been used to monitor the levels of E. coli-resistant strains. Phenotypic studies indicated that wastewater treatment processes increase the prevalence of E. coli strains resistant to both single and multiple antimicrobial classes (Finch and Smith, 1986; Lefkowitz and Duran, 2009; Mezrioui and Baleux, 1994). To our knowledge, only a few qPCR-based genotyping studies have examined the change of ARG abundance in the microbial biomass of biological treatment systems, usually through the detection of ARGs of some selected antimicrobials (e.g. Czekalski et al., 2012), and no studies have been published on the effect of physicochemical treatment. Furthermore, more than 40% of the municipal wastewater in the province of Quebec is treated by physicochemical processes. The current study goes beyond the previous studies by testing for the presence of 70 antimicrobial resistance genes against 11 antimicrobial classes in E. coli isolates from both biological and physicochemical treatment systems. This study complements a previously published study on the same isolate collection (Frigon et al., 2013). By microarray genotyping, it had been found that extraintestinal

uropathogenic E. coli (UPEC) and intestinal shiga-toxin producing E. coli (STEC) were the main pathotypes in municipal wastewaters. Comparing influent and effluent samples before disinfection, it had been determined that both activated sludge and physicochemical treatment processes reduced the prevalence of pathogenic E. coli (Frigon et al., 2013). Similarly to the virulence genes, the prevalence of antimicrobial resistance genes may change through wastewater treatment processes, which is of interest in the current study. The objectives of the current study were (1) to compare the impact of conventional activated sludge and physicochemical wastewater treatment processes on ARG prevalence in E. coli isolates, and (2) to assess the co-occurrence of ARGs and virulence genes in these E. coli. To meet these objectives, ARG and virulence gene composition data were generated using a customized DNA microarray containing 70 ARGs representing 11 commonly used antimicrobial classes, 195 virulence genes, as well as 8 genes encoding DNA insertion sequence elements (ISEs) including integron and transposon markers. This rapid microarray genotyping technique allowed us to comprehensively determine the incidence of ARG and virulence genes in E. coli isolates from the influents and effluents of two activated sludge and two physicochemical WWTPs.

2.

Materials and methods

2.1. coli

Wastewater quality analysis and enumeration of E.

The data presented in this study are from the same E. coli isolate collection published previously. A detailed description of wastewater sampling, characterization of samples and enumeration of E. coli was reported in that publication (Frigon et al., 2013). Briefly, grab samples (influent and effluent without disinfection) were collected from two activated sludge treatment plants (called AS1 and AS2) and two physicochemical treatment plants (called PC1 and PC2). E. coli enumeration was performed at 44.5  C on mFC media using the standard membrane filtration technique (APHA. et al., 2005). Confirmation of E. coli was made using Chromocult agar (EMD chemicals, Germany) and Kovac’s reagent (EMD chemicals, Germany). After isolation, between 83 and 93 confirmed E. coli from the influent and effluent of each treatment plant (a total of 719 isolates) were used for DNA microarray genotyping. E. coli isolates which showed the presence of the uidA (b-glucuronidase) gene by DNA microarray were included for the analysis.

2.2. Genomic DNA labelling, microarray hybridization and data analysis The current study used the additional data from the same DNA microarrays that were reported previously (Frigon et al., 2013), where a detailed description on the microarray methodology was also given. Briefly, DNA was extracted from 1 mL of overnight LB cultures then labelled with Cy5-dCTP (GE Healthcare, Little Chalfont, UK) by DNA polymerase followed by proper quality controls. Overnight hybridization of the

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microarray was performed at 50  C with supplemented DIG Easy Hyb buffer (Roche Diagnostics, Laval, Quebec, Canada), and three 5-min post-hybridization washes were performed at 37  C in 0.1  SSC/0.1% SDS. Microarray hybridization signals were finally obtained using a microarray scanner and image processing software. Average duplicate signals for each probe were divided by the average background signal, and a ratio greater than 3 was considered positive. Following this approach, the same isolate analysed more than once would show the same gene profile for each hybridization. The current microarray (70-base pair probes) contains 413 probes including 311 probes targeting different alleles and versions of 195 virulence or virulence-related genes, 70 probes detecting ARGs of 11 antimicrobial classes, 8 probes for DNA insertion sequence elements (ISEs), 20 positive-control probes and 5 negative control probes. A complete list of probes encoding ARGs and ISEs is given in the supplementary material (Table S1), while their sequences can be found in Jakobsen et al. (2011). E. coli isolates which did not possess any of the tested ARGs were presumed to be non-antimicrobial resistance isolates. A list of virulence gene probes, their sequences and the rules to identify pathotypes was published previously (Frigon et al., 2013; Hamelin et al., 2007; Jakobsen et al., 2011). Specifically for the current report, shiga toxin carrying E. coli (STEC) were identified as such if one of the two shiga toxin (stx1/stx2) genes were detected, while uropathogenic E. coli (UPEC) pathotypes were identified as such if a combination of five virulence genes among four virulence factors (adherence: 2 genes, capsule: 1 gene, iron uptake: 1 gene and toxins: 1 gene) were detected. The presence of STEC and UPEC pathotypes was assessed simply based on the combination of virulence genes (Frigon et al., 2013). Phylogenetic classification was performed following Clermont et al. (2000). Uropathogenic E. coli (UPEC) pathogenicity islands (PAIs) were determined based on the combination of virulence genes (Table S2).

2.3.

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Fig. 1 e Proportion of (a) antimicrobial resistance gene (ARG)-carrying E. coli and (b) the average number of ARG classes carried in E. coli from the influents (Inf) and effluents (Eff) of activated sludge (AS1 and AS2) and physicochemical (PC1 and PC2) treatment plants. Error bars represent the standard error as calculated using the loglinear model. The value in parentheses represents the number of E. coli isolates analysed.

Statistical analyses

Statistical significance of the variation in the proportions of ARG-carrying E. coli isolates between treatment plants/processes was evaluated using tools for categorical data. The loglinear model (LLM) was used to test the variations in frequencies through the samples (Sokal and Rohlf, 1994). Computations were performed with the CATMOD procedure of the SAS statistical software (SAS version 9.2, SAS Institute, Inc., Cary, NC). Each treatment plant is considered as an independent sample and all the statistical tests were two tailed. Due to the high variability of wastewater qualities and complex flow patterns in wastewater treatment plants, the statistical significance was evaluated at a P-value 68%) possessed several genes conferring resistance to multiple antimicrobial classes (multiple ARG classes isolates), and as high as nine ARG classes were detected in the isolates from influents and effluents of three of the four locations (see Table S3). The average number of ARG classes in those isolates carrying them actually increased by 15.3% in the activated sludge plants, while it decreased by 11.8% in the physicochemical plants (Table 1). Because the experiment was designed to analyse categorical data, it was not possible to test the statistical significance of these differences. Instead, we tested changes in the frequencies of each ARG class (i.e. class-by-

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Table 1 e Occurrence of antimicrobial resistance genes (ARGs) in various antimicrobial classes. Isolates/ antimicrobial class Isolates ARG-carrying Mean ARG class Aminoglycoside Beta-Lactams Macrolides Phenicols QAC Quinolones Sulfonamides Tetracyclines Trimethoprim Olaquindox a b c d e f g h

No. of E. coli isolates carrying antimicrobial resistance gene a

b

Activated sludge c

d

Physicochemical e

Inf

Eff

% Change

Inf

Eff

% Change

182 58 3.0 25 32 15 15 8 37 13 28 8 0

180 59 3.5 30 35 23 20 6 32 17 35 15 2

NAg þ2.9 þ15.3 þ21.3 þ10.6 þ55.0 þ34.8 24.2 12.6 þ32.2 þ26.4 þ89.6 NDh

174 81 3.3 39 47 24 24 13 46 18 35 22 0

183 66 2.9 25 35 10 15 7 32 17 33 15 1

NA 22.5 11.8 39.1 29.2 60.4 40.6 48.8 33.9 10.2 10.4 35.2 ND

Stat. sig. of difference in frequencyf Overall Inf/ Variation in Inf/Eff changes Eff change between processes NA e NA e e e e e þ e e e ND

NA þ NA þ e þ þ e e e e þ ND

Activated sludge includes both AS1 and AS2 plants. Physicochemical includes both PC1 and PC2 plants. Inf: Influent. Eff: Effluent. % Change: increase (þ) or decrease (). Significant (P < 0.10) changes were italicized. Stat. Sig (statistical significance): P < 0.10: þ, P > 0.10: . NA: Not applicable. ND: Not determined due to the low occurrence (i.e., frequency close to 0).

class) because this provided categorical data in line with the experimental design. This test found significant differences in the variations of ARG classes through the two types of treatment processes (Table 1). Thus, the observed ARG dynamics can be summarized as follows: isolates carrying multiple ARG classes tend to increase through activated sludge plants, while isolates carrying at least one ARG tend to decrease through physicochemical plants. As a complement to this analysis, the gene frequency is presented in Table S4. A closer analysis of the frequency of each ARG class revealed that of the 11 antimicrobial classes tested, 10 were detected; only the ARG of the rifampicin class were not (Table 1). The prevalence of ARG-carrying isolates was higher for four classes: aminoglycoside, beta-lactams, quinolones, and tetracyclines. On assessing the impact of treatment systems on changes in the frequency of the 10 ARG classes, the observed pattern shows that the frequency of seven ARG classes increased (þ10.6% to þ89.6%) through the activated sludge plants whereas it decreased (10.2% to 60.4%) through the physicochemical plants. The differences in behaviour between the processes (increasing at activated sludge plants and decreasing at physicochemical plants) were statistically significant for four of the seven classes: aminoglycosides, macrolides, phenicols and trimethoprim (Table 1). Notably, quinolone and quaternary ammonium compounds (QAC) resistance genes were reduced in both treatment types, and the overall reduction for quinolone ARGs was significant (Table 1). A total of 67 combinations of ARG classes were observed in multiple ARGs-carrying isolates (Table S3). The most common combinations were: aminoglycoside  beta-lactams, betalactams e tetracyclines, beta-lactams e quinolonones, quinolonones e tetracyclines, aminoglycoside  beta-lactams e

tetracyclines, and aminoglycoside  beta-lactams e quinolones. The influents and effluents carried different combinations of multiple class resistance genes (Table S3), therefore WWTP systems may be selecting for different ARG combinations.

3.2. Co-occurrence of ARGs with DNA insertion sequence elements (ISEs) The occurrence of ISEs such as class 1, 2 and 3 integrons (intI13), transposon Tn 21 (tnpM), and other markers included in the class 1 integron (qacED1-sulI and 30 conserved sequence [30 CS]) was determined in the E. coli isolates, and their enrichment in non-ARG and ARG-carrying (single ARG and multiple ARG classes) E. coli isolates was evaluated. Among the 719 E. coli isolates, the integrons and the transposon were detected in 12.8% and 5.8% of the isolates, respectively, while the qacED1sulI and 30 CS integrons were found in 7.2% and 11.7%, respectively. Among the integrases, the prevalence of classes 1 and 2 was the same (10%), while the class 3 integrase was detected in only 2.1% of the isolates. The frequency of integrase genes increased on average by 2.9% (1.1%e6.1%) through the activated sludge processes, while it decreased on average by 32.4% (23.9%e38.2%) through the physicochemical plants. The transposase, qacED1-sulI genes and 30 CS marker decreased in both types of treatment systems by an average of 21.8% (data not shown). For the transposase gene only, the difference between the activated sludge and physicochemical processes was statistically significant. Of the 719 E. coli isolates analysed, 455 did not contain any ARGs (“zero ARG isolates”) while 101 were single ARG class and 163 were multiple ARGs classes. On examining the distribution of ISEs, very few zero ARG isolates (