The Antibiotic Resistance of Heterotrophic Bacteria in Tap Waters in London

R. Destiani* and M.R. Templeton

Department of Civil and Environmental Engineering, Imperial College London, London

United Kingdom, SW7 2AZ

*corresponding author e-mail : r.destiani14@imperial.ac.uk ; telephone number: +44 (0)20 7594 6120

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 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.

Keywords: Antibiotic resistant bacteria, drinking water quality, heterotrophic plate count

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, Bergeon et al., 2015, Khan et al., 2016), and

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 Acitenobacter, Pseudomonas, and

various Enterobacteriaceae, including E. coli, Klebsiella and Serratia (WHO, 2017). Drinking water

regulation in most countries do not regulate the number of heterotrophic plate number (HPC) bacteria in

finished water, however United States Environmental Protection Agency (EPA) stated the HPCs number in

drinking water should be below 500 colony forming unit per millilitre (CFU/ml) (EPA, 2012). However, 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 system 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 which

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 in some cases (Amstrong 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 and the genes that impart antibiotic resistance in tap waters, whether this varies

significantly temporarily and spatially within a water network, and what are the most common types of

antibiotic-resistant bacteria present.

The present study was designed to address (1) what is the prevalence of antibiotic resistant bacteria and

antibiotic resistance genes in tap water in London, UK; (2) whether seasonal differences affect the prevalence

of antibiotic resistant bacteria and genes; and (3) what are the most common antibiotic resistant bacteria

species found in tap water samples.

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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 enter 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 water sample

chemistry was analysed, including pH measured using a pH meter (Fisher Scientific, Loughborough, UK),

total organic carbon was measured using 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 (AWWA, 2005).

Most of the population of London is serviced by Thames Water, with six water treatment plants serving

Greater London, including Ashford Common, Hampton and Kempton Park water treatment works in west

London, and Walthamstow water treatment works, 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 water treatment plants (WTPs) located in west

London area, while WTPs in the north London area abstract their water from Lee Valley reservoir and

groundwater (DWI, 2015). Typical surface water treatment processes employed in England include

screening, slow sand filtration, clarification, aeration, ozonation, granular activated carbon filtration, and

chlorination (DWI, 2015).

Figure 1 illustrates the location of water treatment plants 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 point 3 and 9: E (east), sampling point 4 and 7:

SW (south west), sampling point 5 and 6: W (west), and sampling point 8: N (north) of London.

Enumeration of total cultivable bacteria and antibiotic resistant bacteria

Membrane filtration was used to enumerate both total cultivable and resistant bacteria based on Standard

Method for the Examination Water and Wastewater (AWWA, 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 addition of antibiotics, as follow: 15 mg/l of tetracycline; 10 mg/l of amoxicillin; 5 mg/l of

ciprofloxacin; 5 mg/l of trimethoprim m, 8 mg/l of vancomycin and 5 mg/l of erythromycin. These

antibiotics were selected because they are among the most prescribed antibiotics for human in England

(Public Health England, 2016). 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

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study were purchased from Sigma Aldrich (St. Louis, Missouri, USA) and were in reagent grade (≥98%

purity).

DNA extraction

Relatively large water volumes were necessary to obtain a measurable amount of DNA; thus, 2-3 litre of tap

water sample was collected for DNA extraction each time. Genomic DNA was isolated and purified using a

commercial DNA isolation kit, 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 added into

a bead beating tube, followed by vortex mixing whereby cell lysis occurred. The next step was removal of

proteins and inhibitors, with total genomic DNA then 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 260 nm and 280 nm, with the DNA 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 antibiotic resistance genes. 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 117kb

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 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

20µl volume using Dynamo Flash SYBR green master mix (Thermo Fisher, Waltham, Massachusetts, USA)

in a PikoReal PCR machine (Thermo Fisher, Waltham, Massachusetts, USA). Each 20µl volume consisted of

10µl 2x master mix, 10 mM forward and reverse primer, 2 µl of DNA template, 0.4 µl ROXTM 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.

Identification of phenotypes

Representative antibiotic-resistant colonies were isolated from the plates for identification. API 20NE

identification system from BioMerieux 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

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oxidase positive isolates were then identified with API 20NE identification system from Biomerieux, France,

as per the manufacturer’s recommendation. There are four possible identification results: 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 antibiotic resistance

genes 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/100ml. 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 the April and July sampling times at sampling

point 1, 4, 5, 8 and sampling point 2, 3, and 7, respectively. Sampling point 9 had consistently the lowest

HPC number in all sampling rounds, with an average of 23 cfu/100ml, while sampling point 5 was the

highest with an average of 270 cfu/100ml.

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 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 x 102 to 2 x 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 endure in a viable but non-culturable state (Byrd et al.,

1991). On the other hand, the molecular-based method that was used cannot distinguish between viable or

dead cell and so would overestimate viable microbial content of water samples if used on its own.

Antibiotic-resistant bacteria 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 antibiotic-

resistant bacteria divided by the total heterotrophic plate count. The resistance fluctuated considerably

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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.

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, with 71% of vancomycin resistant

bacteria was recovered from urban wastewater. In this study, vancomycin resistant bacteria were detected at

all sampling points, with resistance ranging from 2% to 41% percent.

Amoxicillin resistant bacteria were found in all sampling locations and the percentage of resistant were in the

range of 8 to 43%. The occurrence of amoxicillin resistance have been previously widely reported in drinking

water distribution networks (Xi et al., 2009), drinking water (Vaz-Moreira et al., 2012; Khan et al., 2016) and

even in bottled mineral water (Falcone-dias et al., 2011).

Erythromycin resistant bacteria were detected in all sampling points, the lowest resistance 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, US.

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 antibiotic 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 and Huovinen, 2001). The occurrences of trimethoprim resistant in drinking water and drinking

water distribution systems were 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

different 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

resistances patterns of the other tested antibiotic 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 and

Goel (2014) previously reported that the occurrence of multiple antibiotic resistant bacteria in two rivers in

India were higher in post monsoon, followed by winter then summer.

Antibiotic resistance genes in the water samples

Antibiotic resistance genes and total bacteria genomes were quantified using real-time qPCR. Figure 5

summarises the proportion of antibiotic resistance genes and 16S rRNA gene in the 100 ml water sample. All

ARGs tested were detected in all sampling points, except for mph(A) and Bla-TEM1 gene which were not

detected in sampling point 4 and 7, respectively. In general, the abundances of the resistance genes were

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lower in the July 2016 sampling compared to the April 2016 sampling time and it was significantly different

for all studied genes.

Sul1 gene was found in all sampling points, with the highest concentration detected at sampling point 5. The

likely reason for the high abundance of sul1 because it is located in 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 sul1 gene in drinking water samples (Shi et al., 2013; Adesoji et al., 2016,

Khan et al., 2016), wastewater and surface water (Chen et al., 2015; Koczura et al., 2016).

Bla-TEM1 is the most common genes coding beta-lactamases and extended spectrum beta-lactamase which are

responsible for resistance towards beta-lactam antibiotics. In this study, Bla-TEM1 gene was detected in eight

of the nine sampling points. Xi et al., (2009) observed higher proportion of 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 tetracycline resistance gene were also

found in all sampling points, with the highest proportion in sampling point 2 for dfrA7 and in sampling point

1 for tet(A). Dfr genes encoded modification of target enzymes dihydrofolate reductase (dfr), which

responsible for most of trimethoprim resistance. Adesouji 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 determinant, such as sulfamethoxazole.

Tetracycline is one of the most frequent use antibiotic in animal farming industry in the UK with the 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 and Gousia, 2015). The presence of tet-

A gene in Europe is well documented with the majority was detected in wastewater and surface waters.

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 was observed at sampling point 2.

Macrolide resistance is becoming more common, with several genes encoded its resistance, including

erm(A), erm(B), mph(A), mph(B) and mef(A). The occurrence of mph(A) gene in drinking water has not

been reported, to 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 and Gallert, 2014), and a

drinking water reservoir in Spain (Huerta et al., 2013).

Antibiotic resistance genes to β-lactams, sulphonamides, aminoglycoside, tetracycline and quinolone were

detected in chlorinated drinking water system in China (Jia et al., 2015), with the relative abundance of sul1

gene the highest. It has been suggested that chlorine might enhanced the expression of antibiotic resistance

genes in drinking water by pumping the efflux pump out the disinfectant agent along with the antibiotic (Xi

et al., 2009).

Identification of antibiotic-resistant phenotypes

Table 2 shows the identification results of antibiotic-resistant bacteria from selected sampling points. The

data presented here are characterised as ≥ 90% identification; in total, 48 of resistant colonies were identified

as very good to excellent identification. API 20NE identification system consists of a microtube containing

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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.

The dominant HPC bacteria were identified as Pseudomonas genus. Pseudomonas was found in all the

London sampling locations, with P. flourescens detected in seven out of nine locations and P. aeruginosa

found in one of the sampling locations. Erythromycin and amoxicillin resistant P. flourescens was detected in

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 pathogen 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, increases 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 in four sampling locations. The occurrence of resistant Aeromonas in drinking water has been reported

Koksal et al., (2006) 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 were detected in 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 shown that S. maltophilia contaminate sinks, faucets and taps in

hospital (Cervia et al., 2008) and in water treatment plants (Hoefel et al., 2005). S. 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, found in two sampling locations in April 2015, July 2015 and

April 2016 sampling periods.

The risk to the general population of infections 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 which

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 that further research

into methods for reducing the occurrence of antibiotic-resistant opportunistic pathogens in distribution

system is warranted.

Conclusions

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Heterotrophic plate count 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 sul1 gene being

almost abundant. The occurrence of mph(A) gene in drinking water was observed for the first time, to our

knowledge.

Six antibiotic resistant HPC genus were identified from the water sample, with species of Pseudomonas

being predominant, including some opportunistic pathogens species.

Acknowledgements

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

first author.

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Figures List

Figure 1. Sampling points and water treatment plant locations in the Greater London area.

365

366

367

1 2 3 4 5 6 7 8 90

100

200

300

400

500

600Jan-15Apr-15Jul-15Oct-15Apr-16Jul-16

Sampling points

cfu/

100

mL

Figure 2. Total heterotrophic plate count bacteria in nine sampling points over a year period. Sampling

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

368

369

370

1 2 3 4 5 6 7 8 90

1

2

3

4

5

6

7

8

0

1

2

3

4

5

6

7

8

16s rRNA (Apr-16) 16s rRNA (Jul-16) HPC (Apr-16) HPC (Jul-16)

Sampling points

Lg (1

6S rR

NA

/100

ml)

Lg (c

fu/1

00m

l)

Figure 3. Heterotrophic plate count 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.

371

372

373

Jan 15 Apr 15 Jul 15 Oct 15 Apr 16 Jul 160

20

40

60

80

100

sampling point 1

% o

f res

istan

t bac

teria

Jan 15 Apr 15 Jul 15 Oct 15 Apr 16 Jul 160

20

40

60

80

100

sampling point 2

% o

f res

istan

t bac

teria

Jan 15 Apr 15 Jul 15 Oct 15 Apr 16 Jul 160

20

40

60

80

100

sampling point 3

% o

f res

istan

t bac

teria

Jan 15 Apr 15 Jul 15 Oct 15 Apr 16 Jul 160

20

40

60

80

100

sampling point 4

% o

f res

istan

t bac

teria

Jan 15 Apr 15 Jul 15 Oct 15 Apr 16 Jul 160

102030405060708090

sampling point 5

% o

f res

istan

t bac

teria

Jan 15 Apr 15 Jul 15 Oct 15 Apr 16 Jul 160

102030405060708090

100 sampling point 6

% o

f res

istan

t bac

teria

Jan-15 Apr-15 Jul-15 Oct-15 Apr-16 Jul-160

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sampling point 7

% o

f res

istan

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Jan 15 Apr 15 Jul 15 Okt 15 Apr 16 Jul-160

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sampling point 8

% o

f res

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Jan 15 Apr 15 Jul 15 Okt 15 Apr 16 Jul-160

102030405060708090

100 sampling point 9

% o

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t bac

teria

Figure 4. Percentage of bacteria found in London tap water samples that were antibiotic-resistant. Data is

from nine sampling points, six sampling times, and four replicates per sampling time. Sampling points

indicate different area across London, UK as shown in Figure

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1 2 3 4 5 6 7 8 9

-8

-7

-6

-5

-4

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0

tet-A bla-tem1 dfrA7 mph(A) sul1

Sampling points

Lg (r

esis

tsnt g

ene

copy

/ 16

S rR

NA

)

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 area across London, UK as shown in Figure 1.

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Table List

Table 1. Primers used in this study for PCR analyses (FW=forward primer, RV=reverse primer)

Target gene Primers Sequence Condition Ref

16S rRNA27f AGAGTTTGATCATGGCTCAG Annealing

temperature 54°C (Hoefel et al., 2015)1492r GGCTACCTTGTTACGACTT

tet-Atet-A FW GGTCATTTTCGGCGAGGATC Annealing

temperature 68°C This studytet-A RV GAAGGCAAGCAGGATGTAGC

mph(A)mph(A) FW ACCATCGCAGTCGAGTCTTC Annealing

temperature 68°C This studymph(A) RV GCCGATACCTCCCAACTGTA

bla-TEM1

bla-TEM1FW GCGCCAACTTACTTCTGACAACG Annealing temperature 68°C (Xi et al.,

2009)bla-TEM1RV CTTTATCCGCCTCCATCCAGTCTA

sul1sul1 FW CGCACCGGAAACATCGCTGCAC Annealing

temperature 65°C (Xi et al., 2009)sul1 RV TGAAGTTCCGCCGCAAGGCTCG

dfrA7dfrA7 FW CAACGATGTTACGCAGCAGG Annealing

temperature 68°C This studydfrA7 RV GGACCACTACCGATTACGCC

382

383

384

385

Table 2. Antibiotic-resistant HPCs identified using API 20NE identification system. Sampling points

indicate different area across London, UK as shown in Figure 1.

Sampling points

Antibiotic

Erythromycin Amoxicillin Trimethoprim Tetracycline Ciprofloxacin

1B. cepacia P. flourescens B. cepacia

D. acidovorans

2P. flourescens A. hydrophila P. flourescens S. paucimobilis

A. salmonicida

3

P. fluorescens P. alcaligenes P. aeruginosa

P. aeruginosa P. fluorescens

P. aeruginosa

4

D. acidovorans S. maltophilia P. luteola

5

P.flourescens P. flourescens

R. radiobacter

6 P.flourescens

7D.acidovorans P. flourescens O. anthropi B.cepacia

A.salmonicida P.flourescens

8P.flourescens S. maltophilia A.salmonicida B. vesicularis

P. fluorescens P. putida

9P.luteola A.salmonicida

P.putida

386

387

388