Occurrence and Antimicrobial Resistance of Escherichia coli in Oysters and Mussels from Atlantic Canada

Abstract

Acquiring antimicrobial-resistant (AMR) bacteria through consuming contaminated animal food products is an emerging public health concern, though the sources of contamination are not always clear. This study characterized the occurrence of AMR in Escherichia coli from bivalve molluscs and assessed for the possible sources in the Hillsborough river complex of Prince Edward Island, Canada in areas overlapping with an oyster fishery. Multivariable statistical analysis indicated that the probability of detecting E. coli increased as the estimated dosage of animal effluent contamination decreased. Isolates with AMR were only found from sampling sites closest to untreated human effluent sources. Twenty-seven percent (n=6 of 22) of the isolates were pathogenic, with virulence factors consistent with extraintestinal E. coli of human origin. Though there is more evidence of contamination arising from human effluent, more research is needed to identify driving sources.

Introduction

Antimicrobial resistant (AMR) bacteria are an emerging environmental contaminant that endangers public and animal health (World Health Organization, 2014). One way to acquire AMR bacteria is from consuming animal products containing bacteria conferring AMR that become part of the gut flora or incorporate AMR into the flora through horizontal gene transfer (Heuer et al., 2009; Martinez et al., 2014).

Bacteria, including those that confer AMR, can accumulate in bivalve molluscs through their process of filter-feeding and concentrating microorganisms (Newell and Langdon, 1996; Daramola et al., 2009; Barkovskii et al., 2010). Because some bivalves are consumed raw, it is possible that they inadvertently lead to the acquisition of AMR bacteria (Han et al., 2007; Woodring et al., 2012). Escherichia coli, an organism in the gastrointestinal tract most commonly found in avian and mammalian species, is a useful biological marker for assessing fecal contamination (Carattoli, 2008), and for providing insight on AMR occurrence given that E. coli have also been found to have resistance to third-generation cephalosporins and fluoroquinolones (Martinez et al., 2014).

Coastal aquatic environments can become contaminated from untreated human and animal effluent waste (Edge et al., 2012), though the sources leading to bacterial AMR of animal food products are not always clear and more primary research is needed in this area (Tuševljak et al., 2012; Wooldridge, 2012). The objectives of this study were to characterize the occurrence of AMR E. coli bacteria in a coastal environment containing a wild-oyster fishery where this has never been done, and assess for possible sources (i.e., human versus animal effluent). We hypothesized if contamination episodes were more severe when closer to one type of effluent source, then that type of source was the likely cause of contamination. The specific study objectives were to (1) determine the presence of E. coli, and the AMR profile of the E. coli isolates; (2) trace detected contamination to human and/or animal effluent sources given sampling location, types of virulence factors, and E. coli phylogeny; and (3) assess whether the existing oyster fishery management zones minimized consumption of contaminated bivalves. Mussels were not included in the final objective because there was no mussel fishery in the study area.

Materials and Methods

The Hillsborough River complex of Prince Edward Island, Canada (46.24°N 63.14°W) contains 3 rivers flowing through lightly forested and mostly agricultural land that meet near urban areas on entry into the Northumberland Strait (Fig. 1). There are occasionally point-sources of contamination from outflow of untreated human effluent during sewage overflow events from the Charlottetown area, and several secondary sewage-treatment sources, in addition to one tertiary sewage-treatment plant. Also, there is non-point contamination from surrounding agriculture. We selected 10 sampling sites with oysters and mussels within this system. Sites were at least 1 km apart and covered a range of effluent input from sewage sources (Fig. 1).

FIG. 1.

Study area and sampling site locations within open (black circles), restricted (black squares), and prohibited (black triangles) fishery zones, in the Hillsborough River complex. Surrounding landcover is summarized as urban (black), agriculture (light gray), and forest (dark gray). The combination black and white circular symbol indicates secondary sewage treatment plant locations and the tertiary plant (located closest to sampling site #4). The white outlines delineate the watershed boundaries.

Some of the sampling sites were located in an oyster fishery. No oysters are harvested for sale from the prohibited zone (sites 1, 2, 3, and 4). This area was closest to wastewater release sites for the largest municipalities (Charlottetown, Stratford) in the study area. The restricted zone (sites 5, 6, 9, and 10) bordered the prohibited zone. All harvested oysters from restricted areas are relayed in designated clean water systems (e.g., relay stations in noncontaminated areas) to filter out potentially harmful agents from the digestive tract of the oyster, in a process known as depuration. The open zone (sites 7 and 8) was farther from urban areas and closer to river headwaters. Oysters can be harvested from these areas in the autumn and sold without depuration (Fig. 1). Subsections of the restricted and open zones can be closed for fishing if bacterial contamination is too high based on the water and shellfish monitoring mandated under the Canadian Shellfish Sanitation Program (CSSP). The CSSP is administered by three federal entities: Environment Canada (water monitoring), Canadian Food Inspection Agency (shellfish meat monitoring), and Fisheries and Oceans Canada (enforcement of the laws and regulations) (http://www.inspection.gc.ca/food/fish-and-seafood/shellfish-sanitation/eng/1299826806807/1299826912745).

At each sampling site, 15 oysters and 15 mussels of market size (≥76 mm and ≥55 mm, respectively) were collected in May and again in July 2012 (n=600 bivalves). Both species are useful sentinels for bacterial contamination (Daramola et al., 2009; Barkovskii et al., 2010). Bivalves were stored at 4°C, and live samples were processed within 7 days of collection. From each sampling site and month, two 25-g pools (3–6 bivalves) of each species were selected and scrubbed for analysis. Within each group, bivalves were aseptically opened, tissue and liquor was collected, and a hand-held tissue homogenizer (Omni International) blended the pool for 1–2 min.

Isolation and identification of generic E. coli followed a modified version of the Canadian Integrated Program of Antimicrobial Resistance Surveillance (CIPARS) protocol for retail meat products (Government of Canada, 2010a). In brief, 225 mL of buffered peptone water (BPW) pre-enrichment broth (BD BBL™) was added to each pool and allowed to incubate at room temperature (1 h) to assist recovery of sublethally injured cells. Fifty milliliters of sample in pre-enrichment broth was added to 50 mL of double-strength EC broth (BD BBL) for a 100-mL final volume, mixed, and incubated aerobically (18–24 h at 45±1°C). For generic E. coli, 10 μL of the sample was inoculated onto an EMB agar plate (BD BBL). For extended-spectrum cephalosporin-resistant E. coli, 50 μL of sample was inoculated onto a tryptic soy agar plate with 5% sheep blood containing vancomycin (6 μg/mL), ceftazidime (2 μg/mL), amphotericin B (2 μg/mL), and clindamycin (1 μg/mL) (VACC). EMB and VACC agar plates were incubated aerobically (18–24 h at 35±1°C). A maximum of 3 morphologically different presumptive E. coli colonies from each EMB or VACC agar plates were confirmed to be E. coli using traditional bacteriologic techniques and frozen at −80°C in Brucella Broth with 15% glycerol.

Minimum inhibitory concentrations (MICs) were determined for recovered E. coli isolates following the CIPARS protocol using the Sensititre™ semiautomated broth microdilution system (Government of Canada, 2010b). Fifteen antimicrobials were assessed using the CMV2AGNF (Sensititre, Trek™ Diagnostic Systems) susceptibility plates of the National Antimicrobial Resistance Monitoring System (NARMS). MICs were interpreted following CLSI M100-43, except for two antimicrobials with no standard breakpoint data. Azithromycin and streptomycin MICs were interpreted using breakpoints determined by the distribution of MICs from CIPARS data in harmonization with those of the NARMS. E. coli with resistance to sulfisoxazole were examined for the presence of the sul gene using a previously validated multiplex polymerase chain reaction (PCR) for sul1, sul2, and sul3 genotypes (Kozak et al., 2009). E. coli isolates with resistance to ciprofloxacin and nalidixic acid were typed for plasmid-mediated quinolone resistance. A multiplex PCR reaction was used for qnr primers (qnrA, qnrB, and qnrS) and qepA primers as described by Gay et al. (2006) and Yamane et al. (2008), respectively. The assay was performed by using 25 μL mixtures and a Qiagen multiplex PCR kit (Qiagen, Mississauga, Ontario, Canada) according to manufacturer instructions. PCR conditions were 95°C for 15 s, 35 cycles of 94°C for 30 s, 60°C for 90 s, and 72°C for 1 min, with a final extension at 72°C for 10 min.

Molecular characterization for virulence factors given genes identifying the Shiga toxin–producing E. coli (STEC), (stx1, stx2), enteropathogenic E. coli (EPEC), (eae) and extraintestinal pathogenic E. coli, extraintestinal E. coli (ExPEC), (papC, cnf1, sfa, afa, iucD, kpsM II, and tsh) was carried out by PCR as described previously (Maluta et al., 2014) and according to a protocol of the OIE Reference Laboratory for Escherichia coli available at http://www.apzec.ca/en/APZEC/Protocols/APZEC_PCR_en.aspx. An E. coli isolate was defined as a human ExPEC if it had ≥2 genes papC, sfa, iucD, afa, and kpsM II (Johnson et al., 2003). Phylogenetic grouping of E. coli, as described by (Clermont et al., 2000), was performed to provide more evidence for classifying isolates from the same or different sources of fecal contamination (Carlos et al., 2010).

We used a mixed-effects logistic regression to assess whether the occurrence of E. coli in pooled samples was associated with fecal contamination from human and animal effluent sources. A random effect of site controlled for multiple sampling at the site level. Fixed effects controlled for additional correlated variation arising from sampling month and bivalve species. We estimated fecal contamination from two sources (human and agricultural) for each site. Human contamination (H) was measured as the seaway distance to the nearest point source, as calculated using statistical software R (R Development Core Team, 2012) and the gdistance package (van Etten, 2012). Animal contamination (A) was measured as the proportion of agriculture land in the immediate and upstream watersheds, assuming that untreated animal sewage and runoff from fields fertilized with animal sewage could drain into the rivers, as calculated using ArcGIS software (Environmental Systems Research Institute, Inc., Redlands, CA). H was centered by its mean and then scaled to one unit of standard deviation to bring the magnitude of values in closer scale with A.

Results

There were 80 pooled samples for analysis. All site–month–species combinations had two pools each, except for site 1/May/mussel having one pool and site 4/May/mussel having three pools. E. coli was detected in 19 (23.8%) of pools. For the MIC analysis, additional colonies were selected from 3 pools for further assessment, and thus providing a total of 22 isolates. Of these, 6 isolates (27.2%) from 3 sites were found to confer AMR to 1 or more antimicrobials (Table 1).

Table 1.

Escherichia coli Isolate Identifier, Sampling Site, Oyster Fishery Zone, Month, Bivalve Species, and the Corresponding Phylogenetic Group, Detected Virulence Factor Genes, Extraintestinal E. coli (ExPEC) Status, and Antimicrobial Resistance (AMR) for Amikacin (am), Chloramphenicol (chl), Streptomycin (strp), Sulfisoxazole (sulf), Trimethoprim–Sulpha (tms), Tetracycline (te), Cefoxitin (fox), Ciprofloxacin (cip), and Nalidixic Acid (nal)

Isolate ID	Site	Oyster fishery zone	Sample month	Species	Phylogenetic group	Virulence gene profile	ExPEC	AMR
58-1	7	Open	July	Oyster	D	tsh, kpsMTII
58-2	7	Open	July	Oyster	B1	Negative
59	7	Open	July	Oyster	B1	Negative
60-1	7	Open	July	Oyster	B1	Negative
60-2	7	Open	July	Oyster	D	tsh, kpsMTII
43	8	Open	July	Oyster	B1	Negative
13	6	Restricted	May	Oyster	D	papC, cnf1, sfa, kpsMII	yes
16	6	Restricted	May	Oyster	B1	Negative
10	10	Restricted	May	Oyster	D	papC, cnf1, sfa, kpsMII	yes
45	10	Restricted	July	Oyster	A	Negative
27-1	1	Prohibited	May	Mussel	A	Negative		am, strp, sulf, tms, te
27-2	1	Prohibited	May	Mussel	A	Negative		am, chl, strp, sulf, tms, te
61	1	Prohibited	July	Mussel	A	Negative		fox
62	1	Prohibited	July	Mussel	D	Negative
64	1	Prohibited	July	Mussel	D	Negative
31	3	Prohibited	May	Mussel	A	Negative
32	3	Prohibited	May	Mussel	B1	Negative
73	3	Prohibited	July	Mussel	D	kpsMTII
75	3	Prohibited	July	Mussel	D	iucD, kpsMTII	yes	am, cip, nal
28	4	Prohibited	May	Mussel	A	Negative		chl, fox
40	4	Prohibited	May	Mussel	D	papC, kpsMII	yes	te
77	4	Prohibited	July	Oyster	A	Negative

E. coli-positive as well as AMR-positive samples were found to have a lower proportion of agricultural lands (A) surrounding them and were closer to human effluent sources (H) than samples that were negative for E. coli. For pools with E. coli (A _E.coli 0.42±SD 7.0×10⁻², A _{no E. coli} 0.47±SD 8.0×10⁻², H _{E. coli} 3085.8±SD 3032.0, H _{no E. coli} 3553.3±SD 2644.5) and for isolates with AMR (A_AMR 0.39±SD 3.1×10⁻³, A _{no AMR} 0.42±SD 7.7×10⁻², H _AMR 1247.8±SD 802.0, H _{no AMR} 4286.6±SD 3302.1). For the multivariable model, the variance attributed to the random effect (i.e., site) was negligible. Therefore, we selected the most parsimonious model (i.e., no random effect) as the final model. In the resulting model, the occurrence of E. coli had a significant negative association with the variable for animal effluent contamination, but none of the other variables were significant (Table 2).

Table 2.

Beta Coefficient Estimates ( \documentclass{aastex}\usepackage{amsbsy}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{bm}\usepackage{mathrsfs}\usepackage{pifont}\usepackage{stmaryrd}\usepackage{textcomp}\usepackage{portland, xspace}\usepackage{amsmath, amsxtra}\pagestyle{empty}\DeclareMathSizes{10}{9}{7}{6}\begin{document}$${\hat{ \beta}}$$ \end{document} ), Standard Errors (SE), and p-Values (p) of the Explanatory Variables for the Probability of Detecting Escherichia coli in the Pooled Samples Given Fecal Contamination from Animal (A) and a Standardized Form of Human (H) Sources While Controlling for Sampling Month (M) and Bivalve Species (S)

Variable	\documentclass{aastex}\usepackage{amsbsy}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{bm}\usepackage{mathrsfs}\usepackage{pifont}\usepackage{stmaryrd}\usepackage{textcomp}\usepackage{portland, xspace}\usepackage{amsmath, amsxtra}\pagestyle{empty}\DeclareMathSizes{10}{9}{7}{6}\begin{document}$${\hat{ \beta}}$$ \end{document}	SE	p
Intercept	3.42	1.97	—
A	−9.49	4.46	0.03
H	−0.17	0.27	0.52
M (reference level=May)	−0.45	0.55	0.41
S (reference level=mussel)	−0.45	0.55	0.41

Two of the six AMR E. coli isolates were considered multidrug resistant, being nonsusceptible to at least one antimicrobial agent in three or more antimicrobial categories (Magiorakos et al., 2011). In the two isolates resistant to sulfisoxazole, resistance was conferred by the sul2 gene. The isolate with resistance to both quinolones (ciprofloxacin, nalidixic acid) tested negative for the qnr and qepA resistance genes.

Four E. coli isolates from four sites located close to municipal sewage outflows were identified as ExPEC. In addition, three isolates were possible ExPEC, possessing one or more of the ExPEC virulence genes but not fully meeting the human ExPEC definition (Aslam et al., 2014). Interestingly, all isolates possessing ExPEC virulence genes belonged to phylogenetic group D (Table 1). Also, most isolates close to human effluent sources were of phylogenetic groups A or D, whereas isolates farther away were of phylogenetic group B1. Only two of the four ExPEC isolates were resistant to at least one antimicrobial and were close to human effluent sources. The non-ExPEC isolates that demonstrated AMR all belonged to phylogenetic group A. Also, the possible ExPEC isolates with no AMR, but with detected virulence for tsh and kpsMTII, were located farthest from human effluent sources. None of the isolates in this study were STEC or EPEC.

Discussion

We found evidence of E. coli contamination of oysters and mussels at several sites in our study area. Bacterial contamination was most often detected in bivalves collected near point sources of human effluent, and AMR E. coli was only detected in samples from this area. This area likely has the greatest concentration of contamination because it was closest to point sources of untreated human effluent. Use of antimicrobials by human (or animal) populations increases the risk of AMR bacterial contamination in the environment when effluent is not properly treated (Wooldridge, 2012). This can occur via a few pathways. First, bacteria conferring AMR released into the environment can become established populations (Heuer et al., 2009). Second, antimicrobials are excreted in feces and urine largely unchanged and thus can increase selective pressure on ambient bacterial populations, leading to a higher frequency of AMR emergence (Kumar and Singh, 2013).

The types of AMR and virulence found in our study were common to E. coli. Though the detection of three isolates with multidrug resistance may support the occurrence of plasmid-mediated gene transfer, none of the detected virulence genes indicated that this mechanism was occurring. The isolate with resistance to both quinolones (ciprofloxacin, nalidixic acid) tested negative for the qnr and qepA resistance genes, suggesting the quinolone resistance likely originated from a chromosomal mutation and not transferable resistant genes. None of the E. coli isolates had a virulence factor consistent with EPEC or STEC, known to cause diarrhea, hemorrhagic colitis, and hemolytic uremic syndrome in humans (Kaper et al., 2004), but a few of the isolates had genes consistent with ExPEC, which can cause urinary tract infections, neonatal meningitis, and septicemia in humans (Moriel et al., 2010). These isolates were only detected in the prohibited and restricted sites. Shellfish harvesters from commercial efforts may become ill if molluscs are consumed from these zones; however, regulations are in place to protect the public. Oysters harvested for resale from restricted sites require a 4-week depuration and oysters in prohibited areas are never permitted to be harvested. The results of our study, similar to those of Sonier et al. (2006), reiterate the need for maintaining regulations on oyster-fishing areas.

The detection of E. coli in the open fishery zone was concerning, although the isolates detected were not considered to be common pathogenic strains and the wild fishery in these areas would only be open in the autumn when contamination may not be as common. However, this study suggests that it may be important to continue to monitor for pathogenic bacteria from open sites to ensure public health safety as aquaculture sites are found in water designated as “open” and these could be sold during the summer months.

It is likely that the sources of E. coli (i.e., human versus animal) vary over the study area, though it may be possible to narrow down some of these sources based on the virulence gene and phylogenetic typing data. For instance, certain ExPEC virulence genes, such as cnf1 and sfa, present in isolates in restricted areas in our study, are found mostly in ExPEC isolates from humans (Mellata, 2013). On the other hand, other ExPEC virulence genes, such as tsh, present in isolates in open areas in our study, are found more commonly in isolates from birds (Barbieri et al., 2013), although whether this was derived from poultry or wild birds was beyond the scope of this study. In addition, groups A and D isolates, predominant in restricted and prohibited areas in our study, are found mostly in humans, whereas group B1 isolates, predominant in open areas in our study, are more prevalent in cows, sheep, and goats than in humans (Carlos et al., 2010). Curiously, all ExPEC isolates in our study belonged to group D and none to B2. Human ExPEC with virulence gene profiles similar to those in our study usually belong to group B2 or D, often more commonly the former (Johnson et al., 2008; Aslam et al., 2014). Interestingly, we did not detect the sul3 gene, an indicator of E. coli from domestic swine (Perreten and Boerlin, 2003; Kozak et al., 2009). We did detect the sul2 gene, conferring sulphonamide resistance, in two isolates close to the human effluent point sources. This gene has been widely found in E. coli strains infecting humans and animals (Hammerum et al., 2006).

The association between E. coli detection and urban versus agricultural areas can also provide insight into sources of bacterial contamination. The results from our descriptive and multivariable statistical analysis suggest that E. coli contamination was mostly driven by human sources. Sites farther downstream were closer to human effluent point sources and had a lower proportion of agricultural lands in the surrounding watersheds. These sites tended to have a higher occurrence of E. coli and isolates conferring AMR (i.e., descriptive results), and the probability of detecting E. coli increased with a decreasing estimated dose effect from animal sources (i.e., multivariable results). Drawing firmer conclusions about the source of effluent contamination would benefit from further sample collection and analysis. Additional samples would increase the power of the statistical analysis to determine more confidently whether locations where E. coli was detected, and the resistance and pathogenicity of the isolates, were associated with the estimated dose effect from human and animal effluent.

Also, it is also worth noting that E. coli recovery may have been underestimated. Ideally, samples were processed within 24 h, but this could have extended up to 2 or 3 days given constraints in laboratory processing resources. Once collected, bivalves were held at 4°C to sustain their viability prior to processing, but may have contributed to the loss of bacterial titers.

Conclusions

Our study is the first to report detection of AMR E. coli in shellfish from Atlantic Canada. We found evidence of fecal contamination in the study area and also in areas where oysters are harvested for commercial sale. Oysters are often eaten raw, and thus can be a vehicle to disseminate pathogenic bacteria and resistance genes to the consumer. The current fishery zone restrictions appear appropriate to minimize consumption of resale oysters contaminated with E. coli and minimize the risk of transferring AMR to the consumer. Our findings reiterate the importance of monitoring for fecal contamination in oyster populations and have identified at least one possible marker for the presence of pathogenic E. coli in these populations, phylogenetic group D, which warrants further investigation. More research is needed to understand the drivers of AMR E. coli contamination in order to reduce environmental contamination and to ensure that raw and undercooked oyster and mussel consumption remains a safe food source. Furthermore, this study suggests that bivalves may be useful in assessing environmental contamination of AMR bacteria.

Footnotes

Acknowledgments

We are grateful to Patrick Boerlin's Laboratory, University of Guelph, Canada, for performing the molecular characterization of AMR. Many thanks for thoughtful discussions with Spencer Greenwood, UPEI. This research was funded, in part, by the Canada Excellence Research Chairs Program.

Disclosure Statement

No competing financial interests exist.

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