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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
1
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
2
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
3
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
4
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.
6
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.
7
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.
8
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
9
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
10
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.
11
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
12
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
13
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
14
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.
15
Cited References
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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-
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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
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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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18
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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