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Research Proposal

Title: Occurrence of antibiotic resistant genes in water filtration plants in Puerto Rico

Project Summary

Antibiotic resistant genes (ARGs) and Antibiotic resistant bacteria (ARBs) are

becoming a major public health issue due to their occurrence in water environments

around the world. Hundreds of various ARGs encoding resistance to a broad range of

antibiotics have been found in municipal wastewater, surface water, agricultural runoff,

groundwater, drinking water and even tap water. Up to date, little is known about the

ARGs dynamics throughout a drinking water filtration plant (WFP).

In this study, we aim to investigate the fate and transport of ARBs and ARGs in

drinking water by assessing two WFP systems starting with the source water (river

intake) throughout the WFP system to the point in which water is ready to be distributed

to the public, including the reclaimed water from the plant’s sludge treatment system

(STS).

Bacteria will be isolated from WFP water in order to identify which bacteria are

carrying the ARGs. We will use multiplex Polymerase Chain Reaction (PCR) methods to

assess the presence/absence of several ARGs within a single sample. Our work will

increase the understanding of ARGs fate and transport through a WFP and STS. This

knowledge will further our understanding of ARGs dynamics and will provide necessary

information to better manage and prevent ARG distribution to humans, animals and

aquatic environments.

Introduction

The World Health Organization (WHO) has classified antibiotic resistance as one

of the most critical human health challenges of the next century and heralded the need

for “a global strategy to contain resistance” (Pruden et al. 2006). Antibiotic resistant

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genes (ARGs) are becoming a major public health issue due to their occurrence in water

environments around the world. Hundreds of various ARGs encoding resistance to a

broad range of antibiotics have been found in municipal wastewater, surface water,

agricultural runoff, groundwater, drinking water and even tap water (Zhang et al. 2009; Xi

et al. 2009; Dodd 2012).

The presence of ARGs in drinking water are worthy of attention as they can be

easily spread to humans and animal populations by continuous ingestion and has

potential health implications including acquisition of ARGs by pathogenic bacteria

populations. Previous research has suggested that chlorination, which is the disinfectant

of preference of drinking water treatment plants for its effectiveness and low cost,

contributes to the enrichment and spread of ARGs (Armstrong et al. 1981; Xi et al.

2009).

ARGs can be considered a class of emerging contaminants but have received

little attention in this context (Dodd 2012). ARGs are of greatest concern because they

are typically associated with mobile genetic elements, which enable them to be passed

among microorganisms via horizontal gene transfer (HGT), a phenomenon possible

even from dead to living cells by transformation (McKinney and Pruden 2012). Up to

date, little is known about ARGs transport throughout a drinking WFP and their fate after

each treatment, especially in the STS.

In this study, we aim to investigate the presence of ARGs in drinking water by

assessing two different drinking water treatment systems (WFP1 and WFP2) starting

with the source waters (Guaynabo, Bayamón, Canóvanas, and Canovanillas River

intakes) throughout the filtration system to the point in which the water is ready to be

distributed to the public, including the water from the STS of the plant. The reclaimed

water from the STS of the WFP is very important because it represents an additional

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route for environmental impact as the supernatant from the thickener is discharged into a

water body, while the dewatered sludge is disposed in landfills.

Considering that ARGs are wide spread in aquatic environments, applications of

molecular techniques are very useful to investigate the occurrence and fate of the ARGs

(Zhang et al. 2009). In our study, we will use multiplex PCR methods which will allow us

to amplify the DNA fragments of several ARGs at the same time within one PCR

reaction.

Our work will assess the presence of ARGs and their fate and transport through

the various steps of a WFP and STS. This knowledge will be vital to understand ARGs

dynamics and how to more efficiently stop their distribution to humans, animals and

aquatic environments. It will also allow us to assess presence of ARGs in STS and

compare their impact in aqueous vs. non aqueous systems. Our results will provide

information about ARGs in a tropical environment and whether their behavior is different

from those reported in colder climates.

An initial survey performed in the WFP1 on October 2013 confirmed the

presence of antibiotic resistant bacteria to four commonly used antibiotics

(chloramphenicol, ampicillin, amoxicillin and ciprofloxacin) in the source waters and

throughout the WFP to the point in which water was ready to be distributed to the public,

including the STS of the plant. These findings validate the importance of our work.

A Power Analysis, performed with the data from the pilot study indicated that 12

replicas are the minimum necessary to establish significant differences for the

presence/absence of ARBs in each plant. A value of 0.05 for a type I error (α) and 0.20

for a type II error (β) were chosen.

We are also interested in testing the effect of seasonality on the presence of ARB

and ARGs throughout the filtration system. In order to differentiate the dry months from

the wet months in both Canóvanas and Guaynabo counties we used the monthly rainfall

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maps for Puerto Rico and the United States Virgin Islands for the last 30 years (1981-

2010 Normals) from the NOAA National Weather Service San Juan. From this

information we have concluded that January, February, March and June are dry months

and therefore the rest of the months are going to be consider wet months for both

counties.

Literature Review

In September of 2013, The United States Center for Disease Control and

Prevention (CDC) reported that over 2 million Americans fall ill, and 23,000 Americans

die from antibiotic resistant infections every year. The spread of antibiotic resistant

pathogens is a growing problem not only in the United States of America (USA) but

around the world (Pruden et al. 2006). The World Health Organization (WHO) has

labeled antibiotic resistance as one of the most critical challenges of the next century.

Antibiotic resistant bacteria (ARB) are constantly released into aquatic

environments through the disposal of human and animal wastes as a result of the

intensive use of antibiotics in the treatment of bacterial infections (Stoll et al. 2012 and

Schwartz et al. 2003). The concern of the scientific community has increased lately

because aquatic environments have been identified as sources of ARB and reservoirs of

ARGs (Macedo et al. 2006; Barker-Reid et al 2010; Stoll et al. 2012).

Microbial aquatic ecosystems, mainly those integrating the urban water cycle,

represent important vehicles of dissemination of human associated microorganism and a

source of transmission of antibiotic resistant bacteria (Farkas et al. 2013). Application of

antibiotics in humans, veterinary medicine, and agriculture for nearly sixty years have

exerted a major impact on bacterial communities, resulting in various levels of antibiotic

resistance, which is genetically controlled by ARGs (Zhang et al. 2009). ARGs are

recognized as emerging contaminants that move readily between ecological niches

using water as a vector (Barker-Reid et al 2010). Water constitutes not only a way of

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dissemination of ARB, but also a route by which ARGs are introduced in natural bacterial

ecosystems (Baquero et al. 2008). ARGs are of greatest concern because they are

typically associated with mobile genetic elements, which enable them to be passed

between microorganisms via horizontal gene transfer (HGT), a phenomenon possible

even from dead to living cells by transformation (McKinney and Pruden 2012). HGT

enables the exchange of genetic material located on mobile elements (transposons,

integrons or plasmids) among related or unrelated bacterial species (Stoll et al. 2012). It

is important to highlight that human activities represent a selective pressure, increasing

the frequency of gene transfer and influencing bacterial evolution (Farkas et al. 2013).

Farkas et al. 2013 indicates that drinking water systems have a significant role in the

evolution of bacterial resistance since a dynamic exchange of individuals constantly

occurs between the attached and planktonic communities, and the way HGT generates

genetic diversity in bacterial populations.

Only in recent years has there been increased interest in the prevalence of ARGs

in water (Barker-Reid et al. 2010). ARGs have been detected in aquatic environments all

around the world such as municipal wastewater, surface water, agricultural runoff,

groundwater, drinking water and even tap water (Zhang et al. 2009; Xi et al. 2009; Dodd

2012). We have summarized published ARGs for tetracycline, aminoglycoside,

macrolide, chloramphenicol, vancomycin, sulphonamide, trimethoprim, β-Lactam and

penicillin by source at Table 1 in Appendix A.

Few reports have documented ARB and ARGs in finish drinking water and

drinking water distribution systems (Kim and Aga 2007). Armstrong et al. 1981

documented the occurrence of multiple antibiotic resistances (MAR) using standard plate

count (SPC) bacteria in potable drinking water. It was evident that the treatment of raw

water contributed to the enrichment of MAR members in the SPC population. SPC

bacteria from the finish drinking water of the treatment facility were more frequently

5

antibiotic resistant that their respective source water populations, especially after

chlorination. Changes in the population of MAR SPC bacteria occurred when raw water

passed through a water treatment system and was reflected by changes in the diversity

of the predominant organisms constituting the MAR populations. Their results

demonstrated that the MAR bacteria were in dynamic state of fluctuation within the

distribution system.

ARGs in drinking water pose a potential threat to humans even when cells

carrying ARGs have been killed. DNA released to the environment has been observed to

persist, and be protected from DNAse activity, especially in the presence of particles of

certain soil/clay compositions. This free DNA can be eventually transformed into other

cells (Pruden et al. 2006).

Xi et al. 2009 found ARB and ARGs in all finished water and tap water tested in

Michigan and Ohio from several drinking water systems, although the amounts were

small. The size of the general population of bacteria followed the order: source water >

tap water > finished water, indicating that there was re-growth of bacteria in drinking

water distribution systems; elevated resistance to some antibiotics was observed during

water treatment and in tap water. The study showed greater quantities of most ARGs in

tap water than in finished and source waters. The increase of ARGs suggests that water

treatment could increase the antibiotic resistance of surviving bacteria and/or induce

transfer of ARGs among certain bacterial populations. The study suggest that water

distribution systems could serve as an incubator for growth of certain ARB populations

and as an important reservoir for the spread of antibiotic resistance to opportunistic

pathogens.. It is important to note that Schwartz et al. 2003 found the presence of ARG

in drinking water biofilms once the ARG source bacteria was eliminated indicating

possible gene transfer to autochthonous drinking water bacteria.

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Most recently, Shi et al. 2013 investigated the chlorination effects on ARB and

ARGs in a drinking water treatment plant. They used biochemical identification, 16S

rRNA gene cloning and metagenomic analysis to study the ARB and ARGs. The

analysis indicated that ARB were predominantly classified as Proteobacteria. Chlorine

disinfection greatly affected microbial community structure where higher proportion of

the surviving bacteria was resistant to chloramphenicol, trimethoprim and cephalothin

after chlorination. This study revealed that sulI had the highest abundance among the

ARGs detected in the drinking water, followed by tetA and tetG. Chlorination caused

enrichment of ampC, aphA2, blaTEM-1, tetA, tetG, ermA and ermB, but sulI was

considerably removed. Also, metagenomic analysis in this study confirmed that

chlorination of drinking water could concentrate various ARGs, as well as plasmids,

insertion sequences, and integrons involved in horizontal transfer of the ARGs.

Research Objectives, Questions and Hypothesis

Our general objective is to assess the presence, fate and transport of ARB and

ARGs through the various steps of a WFP including the reclaimed water from the STS,

covering the system from source waters to drinking water. In order to address our

objective, we are proposing to develop methodology that will allow us to more efficiently

detect the presence of ARGs throughout the water filtration system, isolate and

sequence ARB, identify the temporal differences of the ARB and ARGs and assess the

changes in the microbial community structure as samples move through the different

treatments within the WFP.

Question 1

Can a multiplex PCR technique be used for the concomitant identification of various

ARGs present in discrete water samples from WFPs in Puerto Rico?

Null Hypothesis 1.1: Multiplex PCR technique will not be a useful tool for the

detection of ARGs in a single water sample.

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Objective 2.1: Design a rapid technique that can be used to simultaneously

detect multiple ARGs in water samples.

Methodological approach to address objectives:

Design a multiplex PCR for 4 antibiotic resistant genes related to beta-

lactam (ampC), tetracycline (tetA), chloramphenicol (floR), and

ciprofloxacin (aac(6’)-Ib-cr) resistance using primer sets previously

described by Stoll et al. 2012 and Figueroa et al. 2011.

Question 2

Which species of ARB are present in water samples collected from WFPs in Puerto Rico

and how do they differ between the dry and wet months?

Null Hypothesis 2.1: ARB are the not the same in both WFP regardless of the

geographical distance between the two plants.

Null Hypothesis 2.2: ARB do not differ between dry or wet months.

Objective 2.1: Verify presence of ARB in both WFPs in Puerto Rico isolate and

identify them.

Objective 2.2: Compare ARB profiles from dry and wet months, WFPs and within

each WFP.

Objective 2.3: Identify and compare the bacterial communities that are resistant

to the different antibiotics in each WFPs.

Methodological approach to address objectives:

Five water samples will be collected from each WFP three separate times

in the dry months (January, February, and March) and three more times

in the wet months ( September, October and November).

Two bacteria will be isolated randomly from each antibiotic enrichment

using membrane filtration, spread plate and streak plate technique.

Isolates will be identified by DNA sequencing.

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Communities from each antibiotic will be assessed using Terminal

Restriction Fragment Length Polymorphism (TRFLP). The DNA samples

to analyze the communities will be taken from the antibiotic plus broth

combination before the isolation of the bacteria.

Question 3

Which ARGs are present and how do they differ between the dry and wet months in

water samples collected from WFPs in Puerto Rico?

Null Hypothesis 3.1: ARGs are not present in water samples from both WFPs in

Puerto Rico.

Null Hypothesis 3.2: ARGs do not differ between dry and wet months, WFPs or

within the WFP.

Objective 3.1: Screen water samples collected from each WFP for presence of

ARGs.

Objective 3.2: Compare the ARG profiles from dry and wet months, between

WFPs and each sampling location within the WFP.

Methodological approach to address objective:

Five water samples with a replica will be collected from each WFP six

separate times during the wet months (April, September (2), October,

November (2)) and six more times in the dry months (January (2),

February, March (2), and June) for both WFPs.

Presence/absence of ARG will be assessed using multiplex PCR

procedure.

Methodology

Research Sites

The first research site is the WFP1 located in Guaynabo, Puerto Rico. The raw

water sources are the Bayamón River which flows by gravity into the plant and the

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waters from the Guaynabo River which are pumped into the WFP. WFP1 has a nominal

production capacity of 98,410 m3/d and consists of a raw water mixing chamber, two

rapid mix chambers, eight flocculators, five settling tanks, eighteen sand filters, and a

distribution tank. The WFP1 uses chlorine gas for disinfection and chlorine is added after

the sedimentation tank, filters and before the distribution tank. The STS of the WFP1

consists of a holding tank, thickener, dechlorination box and six vacuum assisted drying

beds. Figure 1 illustrates a sketch of WFP1.

Figure 1: WFP1 Sketch

The second research site is the WFP2 located in Canóvanas, Puerto Rico. The

raw water sources are the Canóvanas and Canovanillas Rivers. WFP2 has a nominal

production capacity of 37, 850 m3/d, and consist of two aerators, four rapid mix

chambers, four settling tanks, eight filters, and a distribution tank. WFP2 uses chlorine

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gas for disinfection and chlorine is added after the sedimentation tank, filters and before

the distribution tank. The STS of the WFP2 consists of two thickeners and four vacuum

assisted drying beds. Figure 2 illustrates a sketch of WFP2.

Figure 2: WFP2 Sketch

Drinking Water System Samples

Water samples will be taken at the raw water mixing chamber, after the

flocculators, after the sand filters, the distribution tank, and the supernatant from the

sludge at each WFP. All water samples will be collected in 2L sterile bottles, stored in ice

during transportation to the laboratory, and processed within six hours from their

collection.

Water Quality Measurements

Water temperature, pH, free chlorine and turbidity will be measure for all water

samples collected.

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Antibiotic Resistant Bacteria Isolation

Water samples will be filtered through a sterile 0.22 µm membrane filter using the

membrane filtration technique. The membrane filters will be incubated in buffered

peptone water at 37⁰C for 24 hours. One hundred micro-milliliters of each sample will be

transferred to buffered peptone water containing one of four selected Ab: Tetracycline

(TET, 12 µg/mL), Chloramphenicol (CLO, 25 µg/mL), Amoxicillin (AMX, 4 µg/mL),

Ciprofloxacin (CIP, 2 µg/mL), and Ampicillin (AMP, 10 µg/mL) and incubated at 37⁰C for

24 hours. After the 24 hour period, a 10 µL of each sample will be transferred to Muller

Hilton agar (38 g Muller Hilton Agar in 1L of water) containing the same antibiotic using

the spread plate technique. Samples will be incubated at 37⁰C for 16 hours. Two single

colonies per treatment will be selected and plated two additional times on Muller Hinton

+ Ab agar to ensure isolation of an axenic culture. Isolates will be preserved at -80⁰C

using LB broth containing 30% glycerol. All procedures will be performed in a biological

hood. Escherichia coli strains ATCC 25922 will be used as a control as recommended

by the Clinical and Laboratory Standards Institute.

DNA Extraction

Samples cultivated in peptone broth will be centrifuged for 6 min. at 10, 000 rpm in order

to get a pellet. Using a 100 µL of ABI Prepman Ultra (Applied Biosystems®) the pellet

will be resuspended. Samples will be heated to 100 ⁰C for 10 min and centrifuged for 3

minutes at 14,000 rpm. Finally, the supernatant will be transferred to a new tube and

stored at -20⁰C.

Identification of Isolates by Sequencing

Isolate identification by sequencing will be performed using ABI Big Dye

Terminator V 3.0. The sequencing reaction mixture contains Big Dye, 5X sequencing

buffer, primer, water and the sample DNA. Once the mixture is ready the tubes are

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placed in the thermal cycler and the cycling program starts as follow: Initial activation

step at 96⁰C for 1 minutes, 25 cycles: 10 seconds denaturation at 96⁰C, 5 seconds

annealing at 50⁰C and 4 minutes extension at 60⁰C. After the sequencing product is

precipitated using a mixture of water, 95% ethanol and sodium acetate. Finally, the

sample will be analyzed using the genetic analyzer ABI 3130.

Terminal Restriction Fragment Length Polymorphism (TRFLP)

TRFLP is a community fingerprinting method used to analyze the microbial

community diversity in which phylogenetic assignments may be inferred from Terminal

Restriction Fragments (TRF) sizes from known bacteria (Kent et al. 2003). TRF length

can be predicted from known sequences. Therefore, this method can potentially identify

specific organisms in a community based on their TRF length.

The TRFLP PCR reaction mixture contains Red Taq Ready mix, primer, water

and the sample DNA. Once the mixture is ready the tubes are placed in the thermal

cycler and the cycling program runs as follow: Initial activation step at 94⁰C for 2

minutes, 30-35 cycles: 30 seconds denaturation at 94⁰C, 30 seconds annealing at 55⁰C,

1 minutes extension at 72⁰C and 10 minutes final extension at 72⁰C . With the PCR

product we proceed with the enzymatic digestion using a mixture of buffer, enzyme,

water and the PCR product. This mixture is incubated for 120 minutes at 37⁰C. At the

end of the incubation the mixture is precipitated and finally resuspended in a solution of

HiDi Formamida and Gen Scan Liz Standard. At this time we are ready to precipitate the

TRFLP products with a mixture of water, 95% ethanol and sodium acetate. Finally, the

sample will be analyzed using the genetic analyzer ABI 3130.

Multiplex PCR Design for Antibiotic Resistant Genes Detection

We intent to design a multiplex PCR for the following 4 antibiotic resistant genes related

to resistance to Beta-lactam (ampC), tetracycline (tetA), chloramphenicol (floR), and

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ciprofloxacin (aac(6’)-Ib-cr). Primer design must follow this simple rules: primer length

of 18-24 bp or higher and a GC content of 35%-60%, thus having an annealing

temperature of 55 ⁰C-58⁰C or higher (Henegariu et al. 1997). The primer sets for these

genes were described by Stoll et al. 2012 and Figueroa et al. 2011. To calculate the

melting point and test for possible primer-primer interactions, software such as “Primers

1.2” will be used. To test for possible repetitive sequences, the primers must be aligned

with the sequence databases at the National Center for Biotechnology Information

(NCBI) using the Basic Alignment Search Tool (BLAST) family programs (Henegariu et

al. 1997). Before the multiplex PCR, we must ensure that single PCR amplifications yield

amplicons of the expected sizes. Amplified fragments of the ARGs will be used as

positive controls (Barker-Reid et al. 2010). Once we have our primers, we will follow the

Multiplex PCR protocol from the QIAGEN Multiplex PCR kit which is advertised as fast

and efficient without optimization. First, we will prepare a 50 µL reaction mix that

includes 25 µL 2X QIAGEN multiplex PCR master mix, 5 µL 10X primer mix, 1 µL

template DNA and complete the volume with RNase-free water. The reaction mix is

thoroughly vortexed and appropriate volumes are dispensed into PCR tubes. We will use

the following cycling program: Initial activation step at 95⁰C for 15 minutes, 30-40

cycles: 30 seconds denaturation at 94⁰C, 90 seconds annealing at 57-63⁰C and 90

seconds at 72⁰C and lastly a final extension step at 72⁰C for 10 minutes.

Statistical Analysis

A randomized block Two-way ANOVA will be used to compare four different

populations resistant to four different antibiotics within each water filtration plant. The

response variable is the resistance of the bacteria to the antibiotic, the treatments are

the four different antibiotics and the blocks are different sampling points throughout the

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water filtration plant. The purpose of this analysis is to reduce the within-treatment

variation to more easily detect differences between treatment means (Keller 2013).

If there are differences between treatments means, we would like to know

whether both WFPs affect the responses. In this case we will still use Two-way ANOVA

but we will use a complete factorial experiment approach. In a complete factorial

experiment the data for all possible combinations of the levels of the factors are

gathered (Keller 2013). This analysis will allow us to determine if there are differences

between WFPs, if only one WFP or both WFPs affect the response, and whether they do

so independently, or do they interact.

Frequency distributions and grouping will be used to assess the differences in

ARB profiles between the wet and dry months.

A non-metric Multidimensional scaling (MDS) technique will be used to analyze

TRFLP results expressing the similarities between the different samples. This method

attempts to place the most similar samples together by calculating a similarity matrix

between all the quadrates. A dendrogram will be used to illustrate the similarities

between samples that are not so easily identified in the MDS plots.

Species Richness (S), Species Evenness (E) and Shannon Weiner Diversity

Index (H) will be used to define our community structure and species diversity of our

samples.

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Cited References

Armstrong JL, Shigeno DS, Calomiris JJ, Seidler RJ. 1981. Antibiotic-resistant bacteria

in drinking water. Appl Environ Microbiol. 42(2): 277-283.

Armstrong JL, Calomiris JJ, Seidler RJ. 1982. Selection of antibiotic-resistant standard

plate count bacteria during water treatment. Appl Environ Microbiol. 44(2): 308-

316.

Barker-Reid F, Fox EM, Faggian R. 2010. Occurrence of antibiotic resistance genes in

reclaimed water and river water in the Werribee Basin, Australia. Journal of

Water and Health. 8(3): 521-531.

Baquero F, Martínez J, Cantón R. 2008. Antibiotics and antibiotic resistance in water

environments. Environmental Biotechnology. 19: 260-265.

Dodd MC. 2012. Potential impacts of disinfection processes on elimination and

deactivation of antibiotic resistance genes during water and wastewater

treatment. Journal of Environmental Monitoring. 14: 1754-1755.

Farkas A, Butiuc-Keul A, Ciataras D, Neamtu C, Craciunas C, Podar D, Dragan-Bularda

M. 2013. Microbial contamination and resistance genes in biofilms occurring

during the water treatment process. Science of the Total Environment. 443: 932-

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Figueroa V, Vaz-Moreira I, Silva M, Manaia CM. 2011. Diversity and antibiotic resistance

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Henegariu O, Hereema NA, Dlouhy GH, Vance GH, Vogt PH. 1997. Multiplex PCR:

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Keller G. 2013. Statistics for management and economics. 7th ed. Beltmont (CA): Thomson.

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Macedo AS, Freitas AR, Abreu C, Machado E, Peixe L, Sousa JC, Novais C. 2011.

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Microbiology. 145: 315-319.

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7445- 7450.

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bacteria and their resistance genes in wastewater, surface water, and drinking

water biofilms. FEMS Microbiology Ecology. 43: 325-335.

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Shi P, Jia S, Zhang X, Zhang T, Cheng S, Li A. 2013. Metagenomic insights into

chlorination effects on microbial antibiotic resistance in drinking water. Water

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Staphylococcus aureus.

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APPENDIX A

Table 1: Summary of published ARGs in water environments modified from Zhang et al.

2009.

Resistance gene for: Gene Source*

Tetracycline tetA AS,DW,EW,NW,SD,SW,US

Tetracycline tetA(41) NW

Tetracycline tetB AS,DW,EW,NW,SW,US

Tetracycline tetC, tetG AS,EW,SW,US

Tetracycline tetD AS,DW,EW,SW,US

Tetracycline tetE, tetQ, tetS AS,EW,SD,SW,US

Tetracycline tetH, tetJ, tetY, tetZ, tet33 SW

Tetracycline tet39, tetB(P), tetT SD,SW

Tetracycline otrB, otrA AS,NW,SW

Tetracycline tetM, tetO AS,EW,NW,SD,SW,US

Tetracycline tetW SD,NW,SW

Aminoglycoside aacA4, aadA5, strB AS,NW

Aminoglycoside aacA29b, aadA4, aadB AS

Aminoglycoside aacC1, aacC2, aacC3, aacC4, aphD NW,SW,US

Aminoglycoside aadA1 AS,EW,NW,SW,US

Aminoglycoside aadA2 AS,NW,SD,SW,US

Aminoglycoside aadA13 SW

19

Aminoglycoside aphA1 DW,NW

Aminoglycoside aphA2 DW

Aminoglycoside Aad(3”)-Ic -

Aminoglycoside nptII NW

Aminoglycoside sat1, sat2 NW,SW

Aminoglycoside strA AS,NW,SW

Macrolide ermA, ermB, ermC, ermF, ermT, ermX EW,SW

Macrolide ermE, ermV SW

Macrolide mphA AS

Chloramphenicol cmlA1, cmlA5, catB2 AS

Chloramphenicol catB3, catII, catIV SW

Chloramphenicol catI, catIII NW

Chloramphenicol floR DW,NW,SW

Vancomycin vanA DW,EW,NW,SW,UW

Vancomycin vanB EW,NW,UW

Trimethoprim drfA1 NW,SW

Trimethoprim drfA5, drfA7, drf18 NW

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Trimethoprim drfA12 DW,NW,SW

Trimethoprim drfA15 EW,NW

Trimethoprim drfA17 DW,NW

Sulphonamide sulI AS,DW,NW,SD,SW

Sulphonamide sulII DW,NW,SD,SW

Sulphonamide sulIII NW,SD

Sulphonamide sulA SD

Β-lactam ampC DW,NW,SW,US

Β-lactam blaPSE-1 EW,SD,SW,US

Β-lactam blaTEM-1 DW

Β-lactam blaOXA-1, blaOXA-10 AS

Β-lactam blaOXA-2 AS,EW,SW

Β-lactam blaOXA-30 SW

Β-lactam mecA DW,NW,US

Penicillin penA DW,SW

*The ARGs were detected in the following water environment: special water from hospital, animal production, and aquaculture area (SW); untreated sewage (US); activated sludge of sewage treatment plant (AS); effluent water of sewage water plant (EW); natural water (NW); sediments (SD); and drinking water (DW).

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