Abstract

This study assessed the occurrence and prevalence of antibiotic-resistant bacteria (ARBs) and antibiotic resistance genes (ARGs) in tap water sampled across London, United Kingdom. Sampling was conducted seasonally from nine locations spread geographically across the city. ARBs and ARGs (tet(A), dfrA7, and sul1) were detected in all sampling locations in all sampling rounds. Resistance to trimethoprim was the highest among the tested antibiotics and the sul1 gene was the most abundant resistance gene detected. Several opportunistic pathogens were identified amongst the ARBs in the water samples, including Pseudomonas aeruginosa and Stenotrophomonas maltophilia.

INTRODUCTION

In recent years, studies have demonstrated the emergence of antibiotic-resistant heterotrophic bacteria in drinking water in various parts of the world (Ribeiro et al. 2014; Bergeron et al. 2015; Khan et al. 2016). The World Health Organization (WHO) recently published 12 species of antibiotic-resistant waterborne bacteria, which they consider may pose a threat to human health, including Acinetobacter, Pseudomonas, and various Enterobacteriaceae, including Escherichia coli, Klebsiella and Serratia (WHO 2017). In most countries, drinking water regulations do not regulate the number of heterotrophic plate number (HPC) bacteria in finished water; however, United States Environmental Protection Agency (EPA) stated that the HPCs number in drinking water should be below 500 colony-forming units per millilitre (cfu/ml) (EPA 2012). Nevertheless, the presence of persistent heterotrophic bacteria in drinking water distribution systems is inevitable, since even properly operated drinking water treatment processes do not completely sterilise the water. Conditions in drinking water distribution systems such as low (or lack of) disinfectant residual, pipe corrosion and biofilm presence can also lead to elevated microbial content in tap water. Some of these heterotrophic bacteria that are present might also be opportunistic pathogens.

Some studies have shown that drinking water treatment processes might increase the percentage of bacteria that are resistant to antibiotics (Armstrong et al. 1982; Xi et al. 2009; Guo et al. 2013; Jia et al. 2015). However, there is limited information available regarding the typical occurrence levels of antibiotic-resistant bacteria (ARBs) and the genes that impart antibiotic resistance in tap waters, whether this varies significantly temporarily and spatially within a water network, and what the most common types of ARBs present are.

The present study was designed to address (1) what is the prevalence of ARBs and antibiotic resistance genes (ARGs) in tap water in London, UK; (2) whether seasonal differences affect the prevalence of ARBs and genes; and (3) what are the most common ARBs species found in tap water samples.

MATERIALS AND METHODS

Study area and sample collection

Tap water samples were collected from residential properties at nine locations across London, United Kingdom. The locations were selected randomly to capture a geographical spread across the city. A total of four replicate water samples were collected from each location six times between January 2015 and July 2016.

The majority of the faucets were metallic mixer taps. Prior to sample collection, each faucet was wiped with 70% ethanol to ensure no contamination entered the water samples. Tap water was then allowed to run for two to three minutes before sample collection. To quench any residual chlorine, 100 μl of 2 g/l of sodium thiosulfate was added to the sterile Schott sampling bottles. Each water sample (100 ml) was stored in an ice bath during transportation to the laboratory and processed within 2–4 hours of collection. The physical and chemical quality of water samples was analysed, including pH using a pH meter (Fisher Scientific, Loughborough, UK), total organic carbon using a TOC analyser (Shimadzu Corporation, Kyoto, Japan), water temperature using a portable thermometer (Hanna Instruments, Woonsocket, USA) and chlorine residual was determined by (N,N-diethyl-p-phenylenediamine) DPD ferrous titration method (APHA, AWWA, WEF 2005).

Most of the population of London is serviced by Thames Water, with six water treatment plants (WTPs) serving Greater London, including Ashford Common, Hampton and Kempton Park water treatment works in west London, and Walthamstow, Desborough Island and Hornsey water treatment works in north London (DWI 2015a). The majority of drinking water for Greater London originates from surface water, abstracted from the Thames river; the rest of the water supply is from groundwater (DWI 2015a). Lower Thames reservoir serves as the main water source for WTPs located in the west London area, while WTPs in the north London area abstract their water from Lee Valley reservoir and groundwater (DWI 2015a). Typical surface water treatment processes employed in England include screening, slow sand filtration, clarification, aeration, ozonation, granular activated carbon filtration, and chlorination (DWI 2015b).

Figure 1 illustrates the location of WTPs in Greater London and the nine sampling points used in this study. The sampling locations were differentiated by postcodes, as follows: sampling point 1: SE (South East), sampling point 2: NW (North West), sampling points 3 and 9: E (East), sampling points 4 and 7: SW (South West), sampling points 5 and 6: W (West), and sampling point 8: N (North) of London.

Figure 1

Sampling points and WTP locations in the Greater London area.

Figure 1

Sampling points and WTP locations in the Greater London area.

Enumeration of total cultivable bacteria and antibiotic resistant bacteria

Membrane filtration was used to enumerate both total cultivable and resistant bacteria based on the Standard Methods for the Examination of Water and Wastewater (APHA, AWWA, WEF 2005). A total of 100 ml of water sample was filtered through a 0.45-μm pore size, 47-mm diameter sterile membrane filter. The filter then was placed into R2A agar with the addition of antibiotics, as follows: 15 mg/l of tetracycline; 10 mg/l of amoxicillin; 5 mg/l of ciprofloxacin; 5 mg/l of trimethoprim, 8 mg/l of vancomycin and 5 mg/l of erythromycin. These antibiotics were selected because they are among the most prescribed antibiotics for humans in England (Public Health England 2015). As for total cultivable bacteria, the filter was placed in R2A agar without the addition of any antibiotics. All plates were then incubated at 25 °C for 72 hours. All chemicals used in this study were purchased from Sigma Aldrich (St Louis, Missouri, USA) and were of reagent grade (≥98% purity).

DNA extraction

Relatively large water volumes were necessary to obtain a measurable amount of DNA; thus, 2–3 litres of tap water sample were collected for DNA extraction each time. Genomic DNA was isolated and purified using a commercial DNA isolation kit, the PowerWater® DNA isolation kit (Mobio Company, San Diego, California, USA) according to the manufacturer's recommendations. Briefly, water samples were filtered through a 0.45-μm pore size filter membrane (Pall Corporation, New York, USA). The membrane was then placed into a bead beating tube, followed by vortex mixing whereby cell lysis occurred. The next step was removal of proteins and inhibitors, then total genomic DNA was captured on a silica spin column. Tris buffer was then used to elute the DNA from the spin column. DNA quantity and quality were measured using a UV spectrophotometer at wavelengths of 260 nm and 280 nm, the DNA was then stored at −20 °C until further analysis.

PCR analysis

Real-time quantitative polymerase chain reaction (qPCR) was used for broad-scale screening of the presence or absence and to quantify the copy number of five ARGs. These resistance genes were (1) tet(A) for tetracycline resistance (2) bla-TEM1 for beta-lactam resistance (3) mph(A) for macrolides resistance (4) sulI for sulphonamides resistance and (5) dfrA7 for trimethoprim resistance. Universal primer targeting Eubacterial 16S rRNA was used to quantify the total bacteria populations in the samples. As positive control, E. coli NCTC 13400 obtained from Public Health England, UK, harbouring the 117 kb plasmid pEK499 carrying ten resistance genes, including tet(A), bla-TEM1, sul1, mph(A), blaCTX-M-15, blaOXA-1, aac6’-Ib-cr and dfrA7, was used. Plasmid DNA was isolated using an UltraClean® Maxi plasmid preparation kit (Mobio Company, San Diego, California, USA). Standard curves were then prepared from serial dilution of the plasmid serving as the positive control for the resistance gene. Dilution series were prepared as recommended by the Applied Biosystems tutorial ‘Creating Standard Curves with Genomic DNA or Plasmid DNA for use in Quantitative PCR’ (Thermo Fisher, Waltham, Massachusetts, USA). Reactions were run in 20 μl volume using Dynamo Flash SYBR green master mix (Thermo Fisher, Waltham, Massachusetts, USA) in a PikoReal PCR machine (Thermo Fisher, Waltham, Massachusetts, USA). Each 20 μl volume consisted of 10 μl 2× master mix, 10 mM forward and reverse primer, 2 μl of DNA template, 0.4 μl ROX™ passive reference dye, and sterile RNase/DNase-free water. Table 1 summarises the primers and reaction conditions used during the PCR analyses. The copy number of each ARG in100 ml water was calculated and normalised to the copy number of 16S rRNA, to obtain the relative abundance of each ARG in each water sample.

Table 1

Primers used in this study for PCR analyses (FW = forward primer, RV = reverse primer)

Target genePrimersSequenceConditionReference
16S rRNA 27f AGAGTTTGATCATGGCTCAG Annealing temperature 54 °C Hoefel et al. (2005)  
1492r GGCTACCTTGTTACGACTT 
tet-A tet-A FW GGTCATTTTCGGCGAGGATC Annealing temperature 68 °C This study 
tet-A RV GAAGGCAAGCAGGATGTAGC 
mph(A) mph(A) FW ACCATCGCAGTCGAGTCTTC Annealing temperature 68 °C This study 
mph(A) RV GCCGATACCTCCCAACTGTA 
bla-TEM1 bla-TEM1FW GCGCCAACTTACTTCTGACAACG Annealing temperature 68 °C Xi et al. (2009)  
bla-TEM1RV CTTTATCCGCCTCCATCCAGTCTA 
sul1 sul1 FW CGCACCGGAAACATCGCTGCAC Annealing temperature 65 °C Xi et al. (2009)  
sul1 RV TGAAGTTCCGCCGCAAGGCTCG 
dfrA7 dfrA7 FW CAACGATGTTACGCAGCAGG Annealing temperature 68 °C This study 
dfrA7 RV GGACCACTACCGATTACGCC 
Target genePrimersSequenceConditionReference
16S rRNA 27f AGAGTTTGATCATGGCTCAG Annealing temperature 54 °C Hoefel et al. (2005)  
1492r GGCTACCTTGTTACGACTT 
tet-A tet-A FW GGTCATTTTCGGCGAGGATC Annealing temperature 68 °C This study 
tet-A RV GAAGGCAAGCAGGATGTAGC 
mph(A) mph(A) FW ACCATCGCAGTCGAGTCTTC Annealing temperature 68 °C This study 
mph(A) RV GCCGATACCTCCCAACTGTA 
bla-TEM1 bla-TEM1FW GCGCCAACTTACTTCTGACAACG Annealing temperature 68 °C Xi et al. (2009)  
bla-TEM1RV CTTTATCCGCCTCCATCCAGTCTA 
sul1 sul1 FW CGCACCGGAAACATCGCTGCAC Annealing temperature 65 °C Xi et al. (2009)  
sul1 RV TGAAGTTCCGCCGCAAGGCTCG 
dfrA7 dfrA7 FW CAACGATGTTACGCAGCAGG Annealing temperature 68 °C This study 
dfrA7 RV GGACCACTACCGATTACGCC 

Identification of phenotypes

Representative antibiotic-resistant colonies were isolated from the plates for identification. An API 20NE identification system from BioMérieux France was used for the identification. API 20NE is a standard test used for the identification of non-fastidious, non-enteric, Gram-negative bacteria. Therefore, selected isolates were initially screened with a Gram staining test and cytochrome oxidase test. Only Gram-negative and oxidase-positive isolates were then identified with the API 20NE identification system from BioMérieux, France, as per the manufacturer's recommendation. There are four possible identification results, including excellent, very good, good and acceptable identification, defined as ≥99.99, ≥99, ≥90 and ≥80% certainty of identification, respectively.

Statistical analysis

Statistical analysis of the data was performed using SPSS version 23. The analysis of variance (ANOVA) test was used to assess the significance of differences between different sampling locations by defining the percentage of resistance to each antibiotic or heterotrophic plate count (HPC) number or ARGs as the dependent variable, and sampling location or sampling time as the factor. P < 0.05 was considered as statistically significant.

RESULTS AND DISCUSSION

HPCs in tap water samples

Figure 2 shows the number of total HPCs in the water samples. The HPC number ranged from 10 to 500 cfu/100 ml. Higher HPC numbers were generally observed during warmer months (April to July); however, the seasonal difference was not statistically significant. There were significant differences between the six sampling rounds at each location, except for one sampling point (number 8) which was reasonably consistent between rounds. The highest HPC number was observed in April and July sampling times at sampling points 1, 4, 5, 8 and sampling points 2, 3, and 7, respectively. Sampling point 9 had consistently the lowest HPC number in all sampling rounds, with an average of 23 cfu/100 ml, while sampling point 5 was the highest with an average of 270 cfu/100 ml.

Figure 2

Total HPC bacteria in nine sampling points over a year period. Sampling points indicate different areas across London, UK, as shown in Figure 1.

Figure 2

Total HPC bacteria in nine sampling points over a year period. Sampling points indicate different areas across London, UK, as shown in Figure 1.

In this study, the concentrations of total organic carbon detected in water samples were in the range of 0.8 to 3 mg/L, pH was 7.2 to 7.8, the temperature in cold months ranged from 7.3 °C to 11 °C, temperature in the warmer months were in the range of 16.4 °C to 21 °C, and the residual chlorine was in the range of 0.2 to 0.8 mg/L. There were no consistently observable trends between these water quality parameters and the HPC numbers, other than the previously mentioned link to increased water temperatures between April and July.

Tap water samples during the sampling period April to July 2016 were also analysed using a molecular technique (qPCR). Figure 3 summarises the number of universal gene 16S rRNA and HPC bacteria measured in the water samples. The copy numbers of 16S rRNA were in the range of 2.2 × 102 to 2 × 107 copies/100 ml water. The value is higher by 2- to 4- log compared to the HPC numbers measured. This suggests that cultivable bacteria in tap water only account for a small percentage of the total bacteria biomass. Furthermore, many bacterial species in drinking water undergo a viable but nonculturable state (Byrd et al. 1991). On the other hand, the molecular-based method that was used cannot distinguish between viable or dead cells and so would overestimate viable microbial content of water samples if used on its own.

Figure 3

HPC and 16S rRNA genes in samples from nine sampling points over a six-month period. Sampling points indicate different area across London, UK, as shown in Figure 1.

Figure 3

HPC and 16S rRNA genes in samples from nine sampling points over a six-month period. Sampling points indicate different area across London, UK, as shown in Figure 1.

ARBs in the water samples

Figure 4 summarises the percentage of the bacteria in the sampled tap waters in London that were found to be antibiotic-resistant. The percentage of resistant-bacteria was calculated from the number of each ARB divided by the total HPC. The resistance fluctuated considerably between the sampling rounds, from January 2015 to July 2016 (Figure 4). There were significant differences in erythromycin, amoxicillin, ciprofloxacin, tetracycline and trimethoprim resistance across the sampling locations. The percentage of resistant bacteria tended to be higher in warmer months, i.e. from April to July.

Figure 4

Percentage of bacteria found in London tap water samples that were antibiotic-resistant. Data are from nine sampling points, six sampling times, and four replicates per sampling time. Sampling points indicate different areas across London, UK, as shown in Figure 1.

Figure 4

Percentage of bacteria found in London tap water samples that were antibiotic-resistant. Data are from nine sampling points, six sampling times, and four replicates per sampling time. Sampling points indicate different areas across London, UK, as shown in Figure 1.

Resistance to vancomycin is due to the presence of operons that encode enzymes responsible for modifying the vancomycin binding target (Arthur et al. 1996). Caplin et al. (2008) reported the occurrence and diversity of vancomycin resistant enterococci from wastewaters in Brighton, UK, which 71% of vancomycin resistant bacteria were recovered from urban wastewater. In this study, vancomycin resistant bacteria were detected at all sampling points, with resistance ranging from 2% to 41%.

Amoxicillin resistant bacteria were found in all sampling locations and the percentage of resistance was in the range of 8% to 43%. The occurrences of amoxicillin resistance have been previously reported in drinking water distribution networks (Xi et al. 2009), tap water (Vaz-Moreira et al. 2012; Khan et al. 2016) and even in bottled mineral water (Falcone-dias et al. 2012).

Erythromycin resistant bacteria were detected in all sampling points, the lowest resistance was found at sampling point 9, with the average of 13% and the highest resistance detected at sampling point 6 with an average of 38%.

Ciprofloxacin and tetracycline resistant bacteria were the lowest in all sampling points, ranging from 1.5% to 14%. The trend was similar with several studies that also reported relatively low tetracycline and ciprofloxacin resistant bacteria in drinking water samples, with Xi et al. (2009) reporting 10–13% of bacteria being ciprofloxacin resistant and 0.04–3.78% of bacteria being tetracycline resistant in tap water samples in Michigan, USA.

The percentage of trimethoprim resistant bacteria was in the range of 26% to 70%, higher than the other antibiotics. Trimethoprim is usually used in the treatment of urinary tract infections and in combination with other kinds of antibiotics to treat certain types of pneumonia (Huovinen et al. 1995). Resistance to trimethoprim may be either intrinsic or acquired by horizontal acquisition via plasmid or conjugation (Eliopoulos & Huovinen 2001). The occurrence of trimethoprim resistance in drinking water and drinking water distribution systems has been previously reported (Shi et al. 2013; Ribeiro et al. 2014).

In terms of temporal variations from year-to-year, amoxicillin and vancomycin resistances were statistically higher in July 2015 versus July 2016 in six of the sampling locations. Meanwhile, for trimethoprim resistance, there were only three locations with significant differences between July 2015 and July 2016. The resistance patterns of the other tested antibiotics did not vary significantly between the same sampling times in different years, i.e. April 2015 versus April 2016 or July 2015 versus July 2016. However, Mohanta & Goel (2014) previously reported that the occurrences of multiple antibiotic resistant bacteria in two rivers in India were higher post monsoon, followed by winter then summer.

ARGs in the water samples

ARGs and total bacteria genomes were quantified using real-time qPCR. Figure 5 summarises the proportion of ARGs and 16S rRNA gene in the 100 ml water sample. All ARGs that were tested, were detected at all sampling points, except for mph(A) and bla-TEM1 genes, which were not detected at sampling points 4 and 7, respectively. In general, the abundance of the mph(A) gene was lower and the abundance of the sul1 gene was higher compared to the other resistance genes, and statistically significantly different.

Figure 5

Quantities of antibiotic-resistance genes from nine London tap water sample locations. The data represent the copy number of resistance genes normalised to 16S rRNA gene copy number in a 100 ml water sample. Sampling points indicate different areas across London, UK, as shown in Figure 1.

Figure 5

Quantities of antibiotic-resistance genes from nine London tap water sample locations. The data represent the copy number of resistance genes normalised to 16S rRNA gene copy number in a 100 ml water sample. Sampling points indicate different areas across London, UK, as shown in Figure 1.

The sul1 gene was found at all sampling points, with the highest concentration detected at sampling point 5. The likely reason for the high abundance of the sul1 gene is that it is located in the mobile genetic element, known as class I integron, making it possible to transfer the gene between bacteria (Hsu et al. 2014). Previous studies have also shown the high abundance of the sul1 gene in drinking water samples (Shi et al. 2013; Adesoji et al. 2016; Khan et al. 2016), and wastewater and surface water (Chen et al. 2015; Koczura et al. 2016).

Bla-TEM1 is the most common gene coding beta-lactamases and extended spectrum beta-lactamases, which are responsible for resistance towards beta-lactam antibiotics. In this study, the bla-TEM1 gene was detected at eight of the nine sampling points. Xi et al. (2009) observed a higher proportion of the bla-TEM1 gene in tap water samples than in samples from the WTP, which suggests that the spread of this gene occurs in water distribution systems.

DfrA7, which encodes resistance toward trimethoprim and tet(A) for the tetracycline resistance gene, were also found at all sampling points, with the highest proportion at sampling points 2 and 1, for dfrA7 and tet(A), respectively. Dfr genes encoded modification of target enzyme dihydrofolate reductase (dfr), which is responsible for most trimethoprim resistance. Adesoji et al. (2016) detected dfrA15, dfr7, and dfrA1 resistance genes from drinking water in southwestern Nigeria. Most of the dfrA7 gene is located in the integron cassette, which can be transferred horizontally (Blahna et al. 2006). Studies have suggested that trimethoprim resistance genes can be associated with other resistance determinants, such as sulfamethoxazole. Tetracycline is one of the most frequently used antibiotics in the animal farming industry in the UK with an average use of 183 tonnes per year (Public Health England 2015). It is well known that the veterinary industry is an important source for antibiotic resistance dissemination (Economou & Gousia 2015). The presence of the tet-A gene in Europe is well documented, with the majority of them detected in wastewater and surface waters.

The mph(A) gene was found in eight of the nine locations, though the abundance of mph(A) was between 2- and 7-log lower than the others, with the highest abundance of the gene observed at sampling point 2. Macrolide resistance is becoming more common, with several genes encoding its resistance, including erm(A), erm(B), mph(A), mph(B) and mef(A). The occurrence of the mph(A) gene in drinking water has not been reported, to the best of our knowledge. However, other types of macrolides resistance genes, for instance, erm(A) and erm(B), were previously detected in treated sewage water in Germany (Hess & Gallert 2014), and a drinking water reservoir in Spain (Huerta et al. 2013).

ARGs to β-lactams, sulphonamides, aminoglycoside, tetracycline and quinolone were detected in chlorinated drinking water systems in China (Jia et al. 2015), with the relative abundance of the sul1 gene the highest. It has been suggested that chlorine might enhance the expression of ARGs in drinking water by pumping out the disinfectant agent along with the antibiotic via the efflux pump (Xi et al. 2009).

Identification of antibiotic-resistant phenotypes

Table 2 shows the identification results of ARBs from selected sampling points. The data presented here are characterised as ≥90% identification; in total, 48 of the resistant colonies were identified as very good to excellent identification. The API 20NE identification system consists of a microtube containing dehydrated substrates to detect enzymatic activity or assimilation of sugars by the inoculated organisms. The generated profiles were then compared against the API 20NE online database. Burkholderia, Pseudomonas, Delftia, Aeromonas, Sphingomonas and Rhizobium genus were identified. Khan et al. (2016) also reported the presence of amoxicillin resistant Burkholderia and Sphingomonas from drinking water in Scotland.

Table 2

Antibiotic-resistant HPCs identified using the API 20NE identification system

Sampling pointsAntibiotic
ErythromycinAmoxicillinTrimethoprimTetracyclineCiprofloxacin
 B. cepacia P. fluorescens B. cepacia  
D. acidovorans 
P. fluorescens A. hydrophila P. fluorescens  S. paucimobilis 
A. salmonicida 
P. fluorescens P. alcaligenes P. aeruginosa   
P. aeruginosa P. fluorescens 
P. aeruginosa 
D. acidovorans S. maltophilia P. luteola   
 P. fluorescens P. fluorescens 
R. radiobacter 
P. fluorescens     
D. acidovorans P. fluorescens O. anthropi B. cepacia  
A. salmonicida P. fluorescens 
P. fluorescens S. maltophilia A. salmonicida  B. vesicularis 
P. fluorescens P. putida 
P. luteola  A. salmonicida   
P. putida 
Sampling pointsAntibiotic
ErythromycinAmoxicillinTrimethoprimTetracyclineCiprofloxacin
 B. cepacia P. fluorescens B. cepacia  
D. acidovorans 
P. fluorescens A. hydrophila P. fluorescens  S. paucimobilis 
A. salmonicida 
P. fluorescens P. alcaligenes P. aeruginosa   
P. aeruginosa P. fluorescens 
P. aeruginosa 
D. acidovorans S. maltophilia P. luteola   
 P. fluorescens P. fluorescens 
R. radiobacter 
P. fluorescens     
D. acidovorans P. fluorescens O. anthropi B. cepacia  
A. salmonicida P. fluorescens 
P. fluorescens S. maltophilia A. salmonicida  B. vesicularis 
P. fluorescens P. putida 
P. luteola  A. salmonicida   
P. putida 

Sampling points indicate different areas across London, UK, as shown in Figure 1.

The dominant HPC bacteria were identified as Pseudomonas genus. Pseudomonas was found at all the London sampling locations, with P. fluorescens detected at seven out of nine locations and P. aeruginosa found at one of the sampling locations. Erythromycin and amoxicillin resistant P. fluorescens was detected at all sampling points, while erythromycin, amoxicillin and trimethoprim resistant P. aeruginosa was found at sampling point 3. Due to its metabolic versatility and the ability to survive in different forms of stress, the presence of Pseudomonads in treated water, including drinking water, is not a surprise (Vaz-Moreira et al. 2012). Pseudomonas spp. are considered opportunistic pathogens that can affect humans via food or water contamination. In addition to being opportunistic pathogens, Pseudomonas spp. also play a role in spreading resistance genes, particularly if the genes are located in mobile genetic elements. Shrivastava reported that antibiotic-resistant Pseudomonas spp. are more resistant to chlorination than other species and might possess selection to chlorine (Shrivastava et al. 2004). Furthermore, increase in the abundance of antibiotic-resistant Pseudomonas and Sphingomonas have been observed after chlorination (Jia et al. 2015).

Amoxicillin and trimethoprim resistant Aeromonas, identified as A. hydrophila and A. salmonicida, were found at four sampling locations. The occurrence of resistant Aeromonas in drinking water has been reported. Koksal et al. (2007) found 41% amoxicillin resistance among Aeromonas strains from the drinking water system in Istanbul, Turkey. Several species of Aeromonads are linked with gastroenteritis, muscle infection and skin disease (Igbinosa et al. 2012).

Stenotrophomonas maltophilia resistant to amoxicillin was detected at two sampling points, sampling point 4 and 8. Stenotrophomonas maltophilia is an aerobic Gram-negative bacillus that is found in various aqueous environments. One of the important characteristics of this bacterium is the ability to form biofilm in water-associated environments. Various studies have shown that S. maltophilia contaminates sinks, faucets and taps in hospitals (Cervia et al. 2008) and in WTPs (Hoefel et al. 2005). Stenotrophomonas maltophilia has emerged as an important opportunistic pathogen, particularly among hospitalised patients, causing pulmonary and bacteremia infection (Brooke 2012).

Another important opportunistic pathogen found in the London tap water samples was amoxicillin and tetracycline resistant Burkholderia cepacia, which was found at two sampling locations in the April 2015, July 2015 and April 2016 sampling periods.

The risk of infections to the general population caused by heterotrophic plate bacteria is low (Rusin et al. 1997); however, this study found a number of opportunistic pathogen species of HPCs in tap water that were also antibiotic resistant. This suggests that the further purification of tap water before consumption by individuals considered to be at elevated risk of opportunistic infections is important, and further research into methods for reducing the occurrence of antibiotic-resistant opportunistic pathogens in the distribution system is warranted.

CONCLUSIONS

  • HPC bacteria that were resistant to vancomycin, erythromycin, amoxicillin and trimethoprim were detected in all sampling locations.

  • Seasonal trends in antibiotic resistance were different according to sampling location and the antibiotic in question.

  • Tet(A), bla-TEM1, sul1, mph(A) and dfrA7 genes were detected in all water samples, with the sul1 gene being almost abundant. The occurrence of the mph(A) gene in drinking water was observed for the first time, to the best of our knowledge.

  • Six antibiotic resistant HPC genus were identified from the water sample, with species of Pseudomonas being predominant, including some opportunistic pathogen species.

ACKNOWLEDGEMENTS

The authors acknowledge the Indonesian Endowment Fund for Education (LPDP) for the PhD funding of the first author.

REFERENCES

REFERENCES
APHA, AWWA, WEF
2005
Standard Methods for the Examination of Water and Wastewater
, 21st edn.
American Public Health Association, American Water Works Association, Water Environment Federation
,
Washington, DC
,
USA
.
Armstrong
J. L.
,
Calomiris
J. J.
&
Seidler
R. J.
1982
Selection of antibiotic-resistant standard plate count bacteria during water treatment
.
Applied and Environmental Microbiology
44
(
2
),
308
316
.
Arthur
M.
,
Reynolds
P.
&
Courvalin
P.
1996
Glycopeptide resistance in enterococci
.
Trends in Microbiology
4
(
10
),
401
407
.
Bergeron
S.
,
Boopathy
R.
,
Nathaniel
R.
,
Corbin
A.
&
LaFleur
G.
2015
Presence of antibiotic resistant bacteria and antibiotic resistance genes in raw source water and treated drinking water
.
International Biodeterioration and Biodegradation
102
,
370
374
.
Blahna
M. T.
,
Zalewski
C. A.
,
Reuer
J.
,
Kahlmeter
G.
,
Foxman
B.
&
Marrs
C. F.
2006
The role of horizontal gene transfer in the spread of trimethoprim-sulfamethoxazole resistance among uropathogenic Escherichia coli in Europe and Canada
.
Journal of Antimicrobial Chemotherapy
57
(
4
),
666
672
.
Byrd
J. J.
,
Xu
H. S.
&
Colwell
R. R.
1991
Viable but nonculturable bacteria in drinking-water
.
Applied and Environmental Microbiology
57
(
3
),
875
878
.
Cervia
J. S.
,
Ortolano
G. A.
&
Canonica
F. P.
2008
Hospital tap water as a source of Stenotrophomonas maltophilia infection
.
Clinical Infectious Disease
46
(
9
),
1485
1487
.
Drinking Water Inspectorate (DWI)
2015a
Public Water Supplies in the London and South-East Region of England, A Report by the Chief Inspector of Drinking Water
.
Drinking Water Inspectorate (DWI)
2015b
Drinking Water Inspectorate Guidance to Water Companies
. .
Eliopoulos
G. M.
&
Huovinen
P.
2001
Resistance to trimethoprim-sulfamethoxazole
.
Clinical Infectious Diseases
32
(
11
)
1608
1614
.
Environmental Protection Agency
2012
2012 Edition of the Drinking Water Standards and Health Advisories
.
Office of Water, US Environmental Protection Agency
,
Washington, DC
.
Falcone-Dias
M. F.
,
Vaz-Moreira
I.
&
Manaia
C. M.
2012
Bottled mineral water as a potential source of antibiotic resistant bacteria
.
Water Research
46
(
11
)
3612
3622
.
Hoefel
D.
,
Monis
P. T.
,
Grooby
W. L.
,
Andrews
S.
&
Saint
C. P.
2005
Profiling bacterial survival through a water treatment process and subsequent distribution system
.
Journal of Applied Microbiology
99
(
1
),
175
186
.
Huerta
B.
,
Marti
E.
,
Gros
M.
,
López
P.
,
Pompêo
M.
,
Armengol
J.
,
Barcelo
D.
,
Balcazar
J. L.
,
Rodriguez-Mozaz
S.
&
Marcé
R.
2013
Exploring the links between antibiotic occurrence, antibiotic resistance, and bacterial communities in water supply reservoirs
.
Science of the Total Environment
456–457
,
161
170
.
Huovinen
P.
,
Sundstrom
L.
,
Swedberg
G.
&
Skold
O.
1995
Trimethoprim and sulfonamide resistance
.
Antimicrobial Agents and Chemotherapy
39
(
2
),
279
289
.
Igbinosa
I. H.
,
Igumbor
E. U.
,
Aghdasi
F.
,
Tom
M.
&
Okoh
A. I.
2012
Emerging Aeromonas species infections and their significance in public health
.
The Scientific World Journal
2012
,
Article ID 625023, 13 pages
.
Jia
S.
,
Shi
P.
,
Hu
Q.
,
Li
B.
,
Zhang
T.
&
Zhang
X. X.
2015
Bacterial community shift drives antibiotic resistance promotion during drinking water chlorination
.
Environmental Science and Technology
49
(
20
),
12271
12279
.
Public Health England
2015
UK One Health Report joint report on human and animal antibiotic use, sales and resistance, 2013
. .
Ribeiro
F. A.
,
Bodilis
J.
,
Alonso
L.
,
Buquet
S.
,
Feuilloley
M.
,
Dupont
J. P.
&
Pawlak
B.
2014
Occurrence of multi-antibiotic resistant Pseudomonas spp. in drinking water produced from karstic hydrosystems
.
Science of the Total Environment
490
,
370
378
.
Rusin
F. A.
,
Rose
J. B.
,
Haas
C. N.
&
Gerba
C. P.
1997
Risk assessment of opportunistic bacterial pathogens in drinking water
.
Reviews of Environmental Contamination and Toxicology
152
,
57
83
.
Shi
P.
,
Jia
S.
,
Zhang
X. X.
,
Zhang
T.
,
Cheng
S.
&
Li
A.
2013
Metagenomic insights into chlorination effects on microbial antibiotic resistance in drinking water
.
Water Research
47
(
1
),
111
120
.
Shrivastava
R.
,
Upreti
R. K.
,
Jain
S. R.
,
Prasad
K. N.
,
Seth
P. K.
&
Chaturvedi
U. C.
2004
Suboptimal chlorine treatment of drinking water leads to selection of multidrug-resistant Pseudomonas aeruginosa
.
Ecotoxicology and Environmental Safety
58
(
2
),
277
283
.
Vaz-Moreira
I.
,
Nunes
O. C.
&
Manaia
C. M.
2012
Diversity and antibiotic resistance in Pseudomonas spp. from drinking water
.
Science of the Total Environment
426
,
366
374
.
WHO
2017
Global Priority of Antibiotic-Resistant Bacteria to Guide Research, Discovery, and Development of new Antibiotics
.
Xi
C.
,
Zhang
Y.
,
Marrs
C. F.
,
Ye
W.
,
Simon
C.
,
Foxman
B.
&
Nriagu
J.
2009
Prevalence of antibiotic resistance in drinking water treatment and distribution systems
.
Applied and Environmental Microbiology
75
(
17
),
5714
5718
.