Waiting
Login processing...

Trial ends in Request Full Access Tell Your Colleague About Jove

Environment

Isolation and Identification of Waterborne Antibiotic-Resistant Bacteria and Molecular Characterization of their Antibiotic Resistance Genes

Published: March 3, 2023 doi: 10.3791/63934

Summary

Here, we present a detailed protocol for the isolation and identification of antibiotic-resistant bacteria from water and the molecular characterization of their antibiotic resistance genes (ARGs). The use of culture-based and non-culture-based (metagenomic analysis) techniques provides complete information about the total bacterial diversity and the total pool of different ARGs present in freshwaters from Mumbai, India.

Abstract

The development and spread of antibiotic resistance (AR) through microbiota associated with freshwater bodies is a major global health concern. In the present study, freshwater samples were collected and analyzed with respect to the total bacterial diversity and AR genes (ARGs) using both conventional culture-based techniques and a high-throughput culture-independent metagenomic approach. This paper presents a systematic protocol for the enumeration of the total and antibiotic-resistant culturable bacteria from freshwater samples and the determination of phenotypic and genotypic resistance in the culturable isolates. Further, we report the use of whole metagenomic analysis of the total metagenomic DNA extracted from the freshwater sample for the identification of the overall bacterial diversity, including non-culturable bacteria, and the identification of the total pool of different ARGs (resistome) in the water body. Following these detailed protocols, we observed a high antibiotic-resistant bacteria load in the range of 9.6 × 105-1.2 × 109 CFU/mL. Most isolates were resistant to the multiple tested antibiotics, including cefotaxime, ampicillin, levofloxacin, chloramphenicol, ceftriaxone, gentamicin, neomycin, trimethoprim, and ciprofloxacin, with multiple antibiotic resistance (MAR) indexes of ≥0.2, indicating high levels of resistance in the isolates. The 16S rRNA sequencing identified potential human pathogens, such as Klebsiella pneumoniae, and opportunistic bacteria, such as Comamonas spp., Micrococcus spp., Arthrobacter spp., and Aeromonas spp. The molecular characterization of the isolates showed the presence of various ARGs, such as blaTEM, blaCTX-M (β-lactams), aadA, aac (6')-Ib (aminoglycosides), and dfr1 (trimethoprims), which was also confirmed by the whole metagenomic DNA analysis. A high prevalence of other ARGs encoding for antibiotic efflux pumps-mtrA, macB, mdtA, acrD, β-lactamases-SMB-1, VIM-20, ccrA, ampC, blaZ, the chloramphenicol acetyltransferase gene catB10, and the rifampicin resistance gene rphB-was also detected in the metagenomic DNA. With the help of the protocols discussed in this study, we confirmed the presence of waterborne MAR bacteria with diverse AR phenotypic and genotypic traits. Thus, whole metagenomic DNA analysis can be used as a complementary technique to conventional culture-based techniques to determine the overall AR status of a water body.

Introduction

Antimicrobial resistance (AMR) has been identified as one of the most pressing global problems. The rapid evolution of AMR and its worldwide spread are one of the greatest threats to human health and the global economy in terms of the health costs associated with it1. The overuse and misuse of antibiotics have led to an increase in AR. This has been highlighted by the COVID-19 pandemic, during which the treatment of associated secondary infections, in many cases, was hugely compromised due to AMR in the affected patients2. Besides the direct use/misuse of antibiotics by humans, the overuse and misuse of antibiotics in agriculture and animal husbandry and their inappropriate discharge into the environment, including water bodies, are a major concern3. The rise of new resistance traits and multidrug resistance in bacteria urgently highlights the need for a better understanding of the factors leading to the development of AR and its dissemination. Multiple antibiotic-resistant bacteria, which often carry multiple AR genes (ARGs) on mobile genetic elements such as plasmids, can transfer these resistance genes to non-resistant microorganisms, including potential human pathogens, thus leading to the emergence of superbugs that are untreatable with even last-resort antibiotics4. These multiple antibiotic-resistant bacteria, if present in water ecosystems, can directly enter the human gut via the consumption of contaminated water-based foods such as fish, crabs, and mollusks. Previous studies have shown that the spread of AR bacteria in naturally occurring water systems can also reach other water supplies, including drinking water, and, thus, can enter the human food chain5,6,7.

The aim of the present study is to provide a comprehensive protocol using a combination of culture-based and non-culture-based (whole metagenomic analysis) techniques to obtain complete information about the total bacterial diversity and the total pool of different ARGs present in a water body in Mumbai, India. Conventionally, culture-based techniques have been used to study the bacterial diversity in water bodies. As culturable microorganisms constitute only a small percentage of the total microbiota in any niche, to have a better understanding of the overall status of bacterial diversity and the various resistant traits prevalent in any sample, various culture-based and culture-independent techniques must be used in tandem. One such robust and reliable culture-independent technique is whole metagenomic DNA analysis. This high-throughput method has been successfully utilized in various studies on bacterial diversity or the functional annotations of various ARGs8,9. This technique uses the metagenome (the total genetic material in a sample) as the starting material for various analyses and, hence, is culture-independent. The protocols in the present study can be used for whole metagenomic DNA analysis to obtain information about the total bacterial diversity and various ARGs (resistome) in water samples.

Subscription Required. Please recommend JoVE to your librarian.

Protocol

1. Sample collection and processing

  1. Sample collection
    1. Collect the appropriate volume of the water sample in sterile sample container(s), ensuring that not more than 3/4 of the container is filled.
    2. Transport the samples to the laboratory under aseptic conditions as soon as possible after collection and immediately process them.
  2. Sample processing
    1. Aseptically filter the water sample through a sterile muslin cloth to remove any particulate matter.
    2. Carry out appropriate serial dilutions of the filtered water for further analysis.

2. Estimation of the total bacterial load and the antibiotic-resistant bacteria count

  1. Determination of the total bacterial load
    1. Suspend 18.12 g of R2A Agar, Modified powder in 1,000 mL of double-distilled water, and dissolve the mixture by heating. Autoclave the dissolved mixture at 121 °C, 15 psi for 20 min. Prepare R2A Agar, Modified plates by pouring the appropriate quantity of the autoclaved mixture into sterile Petri plates (e.g., add approximately 20 mL of autoclaved sterile medium to a 90 mm sterile Petri plate).
    2. Evenly spread 100 µL of the appropriate dilutions of the filtered water sample on the R2A Agar, Modified plate once the medium solidifies. Perform the experiment in duplicate.
    3. Incubate all the above plates at 35-37 °C for 48 h (vary the temperature and incubation time depending upon the media used for isolation).
    4. Express the total bacterial load in terms of colony-forming units per milliliter (CFU/mL) using equation (1):
      Equation 1   (1)
  2. Determination of the AR bacterial count
    1. Follow steps 2.1.1-2.1.4. However, instead of R2A Agar, Modified plates, use R2A Agar, Modified plates supplemented individually with five different antibiotics, namely cefotaxime (3 µg/mL), ciprofloxacin (0.5 µg/mL), erythromycin (20 µg/mL), kanamycin (15 µg/mL), and vancomycin (3 µg/mL).
    2. Add the antibiotics separately into tubes containing 20 mL of sterile molten R2A Agar, Modified (with the temperature of the molten R2A Agar, Modified at ≤40 °C) to achieve the final antibiotic concentration as mentioned in step 2.2.1.
    3. Swirl for even mixing and pour onto sterile Petri plates before the agar solidifies. Perform the experiment in duplicate.
    4. Incubate all the above plates at 35-37 °C for 48 h (if using a different media, the temperature and incubation time may vary).
    5. For quality control and checking the efficacy of the antibiotics, spread 100 µL of bacterial suspensions of the Escherichia coli ATCC 25922 and Staphylococcus aureus ATCC 29213 strains onto their respective antibiotic-containing R2A Agar, Modified plates (ensure that the density of the fresh culture used for the inoculation is OD = 0.5 at 600 nm).
    6. Determine the antibiotic-resistant bacterial count in terms of CFU/mL as described in step 2.1.4.
  3. Glycerol stocks of the isolates
    1. Select morphologically distinct AR colonies.
    2. Suspend a single isolated colony in 2 mL of sterile Luria-Bertani broth containing the respective antibiotic (e.g., if a colony was selected from a plate containing cefotaxime, inoculate the colony from step 2.3.1 in sterile Luria-Bertani broth containing cefotaxime at its respective concentration).
    3. Incubate the inoculated tubes at 37 °C at 80 rpm until the OD600 reaches 0.5.
    4. Prepare glycerol stocks of the isolates by mixing 750 µL of the culture suspension from step 2.3.3 into 250 µL of sterile 100% glycerol under aseptic conditions.
    5. Store the glycerol stocks at −80 °C until further analysis.
      NOTE: For the revival of the cultures from the glycerol stocks, thaw the glycerol stocks at 4 °C. Inoculate a loopful of this stock into 2 mL of sterile Luria-Bertani broth containing the respective antibiotic and allow to grow.

3. Identification of culturable bacteria by 16S rRNA gene sequencing

  1. Preparation of DNA template from the isolates for PCR
    NOTE: The protocol described for the preparation of DNA template for PCR for the isolation of crude DNA from the bacteria is given by Carlson et al.10.
    1. Using a sterile toothpick, take a single, isolated, pure colony of the isolate growing on a Petri plate. Suspend the bacterial colony in 100 µL of sterile double-distilled water in a sterile microcentrifuge tube and boil for 10 min.
    2. Centrifuge the suspension at 10,000 × g for 2 min to pellet the debris, and transfer the supernatant to a fresh sterile microcentrifuge tube for use as the crude DNA template.
  2. Targeted PCR amplification of the V3 region of the 16S rRNA gene and sequencing
    1. Prepare 40 µL of the reaction mixture in a PCR tube for PCR amplification, as mentioned in Table 1.
      NOTE: The DNA preparation should be carried out on an ice block while minimizing the chance of contamination (wear gloves while handling the reagents, and clean the work surface thoroughly with 70% ethanol).
    2. Place the tube in the thermal block, and run the appropriate program in the PCR thermal cycler. See Table 2 for the standardized PCR cycling conditions and the primer information for the amplification of the V3 regions of the 16S rRNA genes.
    3. For resolving the amplicons and visualization, carry out agarose gel electrophoresis (AGE). Mix 10 µL of the amplified PCR product and 2 µL of 6x gel loading buffer (Table 3), and load this mixture into wells on 1.5% agarose gel (dissolve 1.5 g of agarose powder in 100 mL of 1x TAE buffer [Table 3]) containing 5 µL of 10 mg/mL ethidium bromide (EtBr) to a final concentration of 0.5 µg/mL EtBr in 100 mL of the agarose gel.
      CAUTION: EtBr is a potent carcinogen. Gloves should be worn at all times while handling EtBr and gels containing EtBr.
    4. Add DNA ladder for the estimation of the size of the amplicons.
    5. Carry out electrophoresis of the gel in a TAE tank buffer at 80-100 V.
    6. Once the tracking dye runs 3/4 of the gel, stop the electrophoresis, and visualize the amplicon bands under a UV transilluminator.
    7. Use the PCR product (amplicon) for 16S rRNA gene sequencing to identify the isolate.
    8. Quantify the amplicon by subjecting it to spectrophotometric analysis using equation (2).
      Equation 2   (2)
    9. To check the purity of the DNA, calculate the ratio of A260/A280.
      NOTE: Ideally, this number should be above 1.5 and, preferably, between 1.8 and 2.0.
    10. To identify the isolates, compare the sequences that are obtained with sequence databases using an appropriate alignment search tool.

4. Detection of antibiotic resistance in the isolates using antibiotic susceptibility testing

NOTE: This protocol describes the method for antibiotic susceptibility testing (AST) by disc diffusion. The following antibiotic discs were used: cefotaxime (5 µg), ampicillin (10 µg), levofloxacin (5 µg), chloramphenicol (30 µg), tigecycline (15 µg), ceftriaxone (30 µg), imipenem (10 µg), gentamicin (10 µg), neomycin (10 µg), trimethoprim (5 µg), and ciprofloxacin (5 µg).

  1. Preparation of the inoculum for the AST
    1. Aseptically inoculate a single, isolated, purified AR colony using a sterile loop in 2 mL of a sterile non-selective medium, such as Luria-Bertani broth (without any antibiotic), and incubate at 37 °C at 80 rpm overnight.
    2. Resuspend by taking 100-150 µL of the overnight grown culture (approximately, OD600 = 1.8-2.0) in 2 mL of fresh non-selective Luria-Bertani broth medium and incubate for 2-4 h (until the OD600 reaches 0.4-0.5).
    3. Dilute this freshly grown culture suspension using sterile 0.85% saline solution such that the density of the culture is equal to 0.5 McFarland standard (approximately, OD600 = 0.1), which roughly corresponds to 1-2 × 108 cells/mL.
    4. Gently mix the bacterial suspension for an even cell distribution.
    5. Use the above suspension within 15 min of dilution.
  2. Inoculation of the agar plates
    1. Prepare Mueller-Hinton Agar (MHA) plates for performing the AST by mixing 38 g of MHA in 1,000 mL of double-distilled water, and dissolve the mixture by heating. Autoclave the dissolved mixture at 121 °C, 15 psi for 15 min.
    2. Ensure that the depth of MHA in the plates is 4 mm (25 mL of medium per plate).
    3. Simultaneously, remove the antibiotic discs from the freezer and warm them to room temperature.
      NOTE: The antibiotic discs should be gradually thawed by initially thawing the discs at 4 °C and later at room temperature to reduce any potential danger of condensation on the discs, which may subsequently affect the zone of inhibition (ZOI).
    4. Under aseptic conditions, dip a sterile cotton swab into the inoculum prepared in step 4.1, and remove excess suspension to avoid over-inoculation of the plates.
    5. Spread the culture evenly on the plates, starting from the top of the MHA plate and going back and forth from edge to edge. Rotate the plate by 60° while swabbing.
  3. Application of the antibiotic discs
    1. With the help of flame-sterilized forceps, aseptically transfer the antibiotic discs onto the inoculated MHA plates, and press the discs gently to ensure complete level contact with the agar.
      NOTE: This procedure has to be done within 15 min of the inoculation of the culture on the plates.
    2. Place the appropriate number of antibiotic discs on the agar plate by taking into account the organism, the antibiotic used, and the size of the plate to avoid overlapping of the zones of inhibition.
      NOTE: Four to five discs can be accommodated on a 90 mm circular plate.
  4. Incubation of the plates
    1. Within 15 min of the application of the antibiotic discs, invert the plates and incubate at 37 °C overnight.
  5. Interpretation of the results
    1. Measure the ZOI diameter in millimeters (mm), and interpret according to the breakpoint values given by EUCAST11. See the two examples given below.
      1. The zone diameter breakpoint (mm) for a ciprofloxacin antibiotic disc (5 µg) for Enterobacterales is S ≥ 25 and R < 22, which means that it is considered to be sensitive (S) if ZOI ≥ 25 mm, while it is resistant (R) if ZOI < 22 mm. If the ZOI diameter falls between 22 and 25, the isolate is considered to be intermediate (I).
      2. The zone diameter breakpoint (mm) for a chloramphenicol antibiotic disc (30 µg) for Staphylococcus spp. is S ≥ 18 and R < 18, which means that it is considered to be sensitive if ZOI ≥ 18 mm, while it is resistant if ZOI < 18 mm.
    2. Determine the multiple antibiotic resistance (MAR) index by finding the ratio of the number of antibiotics to which the isolate is resistant to the total number of antibiotics to which the isolate is exposed.
      ​NOTE: For quality control, E. coli ATCC 25922 and S. aureus ATCC 29213 are used as reference strains following the protocol as in step 4.

5. PCR-based detection of antibiotic resistance genes in the isolates

  1. Use a standard PCR protocol for the identification of ARGs in the isolates. Prepare the DNA template using the protocol given in step 3.1.
    NOTE: The PCR cycling conditions used in this study were 94 °C for 10 min, followed by 35 cycles of 94 °C for 30 s, annealing for 30 s at the appropriate temperature (as standardized for each primer set), extension at 72 °C for 40 s, and a final extension at 72 °C for 5 min. The reaction mixture is described in Table 4. The list of ARGs, primers, and annealing temperatures is given in Table 5.
  2. To resolve, visualize, and check the purity of the amplicons, follow steps 3.2.3-3.2.10.

6. Whole metagenomic DNA analysis for the identification of the total bacterial diversity and the detection of ARGs in the metagenome

  1. Extraction of the total DNA (metagenome) from the water sample
    1. Extract the metagenomic DNA from the filtered water samples.
      NOTE: In the current study, the metagenomic DNA (total DNA) was extracted from the filtered water samples using the referenced DNA isolation kit following the manufacturer's protocol (see the Table of Materials).
    2. Check the quality of the DNA by loading 3 µL of the extracted metagenomic DNA onto a 0.8% agarose gel, and run the gel at 80-110 V for approximately 30 min.
    3. Check for the presence of a single intact band.
    4. Check the DNA concentration using a fluorometer.
  2. Determination of bacterial diversity and detection of ARGs using whole metagenomic DNA sequencing
    1. Library preparation and PCR amplification:
      1. Prepare a paired-end sequencing library using the referenced DNA library prep kit (see the Table of Materials).
      2. Ready the DNA for adapter ligation by taking 200 ng of DNA and mechanically shearing it into smaller fragments, followed by a continuous step of end-repair in which an "A" is added to the 3' ends.
      3. Depending on the platform used for sequencing, ligate specific adapters to both ends of the DNA fragments.
        NOTE: Sequences crucial for binding dual-barcoded libraries to a flow cell for sequencing are present in these adapters. This allows for PCR amplification of the adapter-ligated fragments and binding the standard sequencing primers.
      4. To check the quality and quantity, analyze the amplified library using a high-sensitivity DNA chip as per the manufacturer's instructions.
    2. Cluster generation and sequencing:
      1. Load the amplified library onto the appropriate sequencing platform for cluster generation and subsequent sequencing.
        NOTE: The library molecules bind to the complementary adapter oligos on the paired-end flow cell. During sequencing, the forward strands are selectively cleaved after the resynthesis of the reverse strand. This copied reverse strand is then sequenced from the opposite end of the fragment.
    3. Bioinformatic analysis:
      1. Generate scaffolds from the high-quality data using the appropriate platform.
      2. Subject these scaffolds to bioinformatics analysis for the taxonomic classification and identification of the ARGs.
        NOTE: The workflow for the whole metagenomic DNA analysis for the identification of the total bacterial diversity and the detection of ARGs in the metagenome is given in Figure 1. A flowsheet of the complete methodology described in the manuscript is given in Figure 2.

Subscription Required. Please recommend JoVE to your librarian.

Representative Results

Total bacterial load and antibiotic-resistant (AR) bacteria count
The enumeration of the total bacterial load was carried out by spreading 10−4 to 10−6 fold dilutions of the water samples on R2A Agar, Modified medium. For the enumeration of the AR bacteria count, 10−3 to 10−6 fold dilutions were spread on media plates containing antibiotics (Figure 3). The total and AR bacteria counts were calculated as CFU/mL, and all the plating experiments were performed in duplicate. Following the above protocols, the present study showed the total bacteria count to be 3.0 × 109 CFU/mL. The AR bacterial load was found to be high, in the range of 9.6 × 105-1.2 × 109 CFU/mL (Table 6).

Identification of culturable bacteria by 16S rRNAgene sequencing
Crude DNA from each isolate was used as a template to perform 16S rRNA gene-specific PCR. In the total of 15 AR isolates sequenced, 10 belonged to the Enterobacteriaceae family, with most being Escherichia coli and Klebsiella pneumoniae. Rare opportunistic bacteria such as Comamonas spp. belonging to the family Comamonadaceae, Micrococcus spp. and Arthrobacter spp. belonging to the family Micrococcaceae, and Aeromonas spp. belonging to the family Aeromonadaceae were also identified from the water sample (Table 7).

Detection of antibiotic resistance in the culturable bacteria using antibiotic susceptibility testing
The antibiotic resistance profile of the above identified isolates was generated by performing AST using the disc diffusion method (Figure 4). Out of the 15 isolates tested, 8 had an MAR index of ≥0.2, indicating a high degree of resistance. Moreover, many of the isolates showed co-resistance profiles (resistance to the same set of antibiotics). However, isolates such as Comamonas spp. and Arthrobacter spp. did not show resistance to any of the antibiotics tested (Table 8).

Detection and identification of antibiotic resistance genes in the culturable bacteria
A total of 10 AR isolates were screened for the presence of ARGs using PCR. The most prevalent ARG in the culturable isolates was blaTEM encoding for β-lactamase, followed by the aminoglycoside resistance gene aadA. Other amplified ARGs were blaCTX-M, dfr1, and aac(6')-Ib conferring resistance to β-lactams, trimethoprim, and aminoglycosides, respectively. The representative results of the amplification of the ARGs are shown in Figure 5. For most of the identified isolates, phenotypic resistance (AST) was confirmed at the molecular level via PCR-based genotypic AR profiling.

Identification of the total bacterial diversity in the metagenomic DNA
To check for the presence of all possible bacteria (both culturable and non-culturable) and to identify their relative abundances, a metagenomic DNA analysis for the total bacterial diversity was carried out. Using the high-throughput next-generation sequencing (HT-NGS) approach, ~96.94% of the total sequence reads were obtained, resulting in high coverage. Taxonomic annotation was carried out to classify the reads into different taxonomic groups from the phylum to the genus level (Figure 6 and Figure 7). A total of 50 phyla could be identified in the metagenome, indicating the high bacterial diversity in the water sample. Proteobacteria was the most dominant phylum, consisting of the Alphaproteobacteria, Betaproteobacteria, and Gammaproteobacteria classes. At the order level, Burkholderiales was the most prevalent order, belonging to the Betaproteobacteria class. Pseudomonas, Acinetobacter, Pedobacter, Prosthecobacter, Limnohabitans, Flavobacterium, and Comamonas were some of the abundant genera found in the water sample.

Detection of ARGs from the metagenomic DNA
To understand the total pool of ARGs in the metagenome of the water sample, whole metagenomic sequencing was carried out, followed by the identification of ARGs using appropriate bioinformatics tools. The metagenomic approach ensures that the ARGs present in both culturable and non-culturable microorganisms in the sample are detected. A variety of genes conferring resistance to β-lactams (SMB-1, ampC1, VIM-20, ccrA, nmcR, ARL-1, blaZ); aminogylcosides (aac(6')-34); quinolones (qnrS6, qnrVC5); antibiotic efflux pumps-resistance-nodulation-cell division (RND) (evgA, mtrA, mdtA, acrD), ATP-binding cassette (ABC) (oleC, macB, patA, bcrA), and major facilitator superfamily (MFS) (abaQ); trimethoprim-resistant dihydrofolate reductase (dfrD, dfrA20); rifampin phosphotransferase (rphB); and chloramphenicol acetyltransferase (CAT) (catB10) were detected in the metagenome. The ARGs detected via PCR in the culturable isolates (blaTEM, blaCTX-M, aadA, aac(6')-Ib, dfr1) were also detected by whole metagenomic sequencing, thus confirming their presence in the water sample. The representative results of the ARGs identified in the metagenome using whole metagenomic DNA analysis are given in Table 9.

Figure 1
Figure 1: Workflow for whole metagenomic DNA analysis. The stepwise workflow for the identification of the total bacterial diversity and the detection of the ARGs from the metagenome is presented. The overall steps involve metagenomic DNA preparation, amplification, and identification. Please click here to view a larger version of this figure.

Figure 2
Figure 2: Flowsheet of the complete methodology. The stepwise workflow of the methodology used in the present study. A combination of both culture-based and non-culture-based techniques is used to get complete information about the bacterial diversity and the identity of the ARGs present in the water sample. Please click here to view a larger version of this figure.

Figure 3
Figure 3: Representative images of isolated colonies on antibiotic-containing R2A Agar, Modified plates. Water samples plated on cefotaxime (3 µg/mL)-containing R2A Agar, Modified plates. The sample was serially diluted and plated in duplicate-A1, A2: 10−4; B1, B2: 10−5; C1, C2: 10−6. After the appropriate incubation period, the isolated colonies were visible on the B1, B2, C1, and C2 plates. Please click here to view a larger version of this figure.

Figure 4
Figure 4: Antibiotic susceptibility test by the disc diffusion method. Representative images of AST by the disc diffusion method for an Escherichia coli isolate. AST was performed in duplicate-A1, A2: CTX, IPM, C, CIP; B1, B2: LE, TGC, AMP, GEN; C1, C2: TR, N, K, CTR. The diameters of the ZOIs were measured in millimeters (mm). To interpret if the isolate is resistant or susceptible to the antibiotic used, the ZOI was compared with the latest EUCAST tables. Abbreviations: AST = antibiotic susceptibility test; CTX = cefotaxime; IPM = imipenem; C = chloramphenicol; CIP = ciprofloxacin; LE = levofloxacin; TGC = tigecycline; AMP = ampicillin; GEN = gentamicin; TR = trimethoprim; N = neomycin; K = kanamycin; CTR = ceftriaxone; ZOI = zone of inhibition; EUCAST = European Committee on Antibiotic Susceptibility Testing. Please click here to view a larger version of this figure.

Figure 5
Figure 5: PCR amplification of antibiotic-resistance genes from culturable bacteria. Agarose gel electrophoresis post PCR was carried out for the visualization of amplified bands to check for the presence of ARGs in the isolates. Separated bands of PCR amplicons can be seen on the gel. The size of the individual PCR amplicons is compared with an appropriate DNA marker. Lane L1: 100 bp DNA ladder; Lanes 1-5: 1: dfr1 (425 bp); Lane 2: blaTEM (310 bp); Lane 3: blaCTX-M (500 bp); Lane 4: aac(6')-Ib (395 bp); Lane 5: aadA (624 bp). Abbreviation: ARGs = antibiotic-resistance genes. Please click here to view a larger version of this figure.

Figure 6
Figure 6: Taxonomical classification for the phylum and class levels. (A) Bar chart showing the phylum-level taxonomic abundance distribution of the bacterial metagenome in the water sample. A total of 50 bacterial phyla were identified by the metagenomic analysis. The first 12 dominant phyla of bacteria are shown. (B) Bar chart showing the class-level taxonomic abundance distribution of the bacterial metagenome in the water sample. A total of 50 bacterial classes were identified by the metagenomic analysis. The first 15 dominant classes of bacteria are shown. Please click here to view a larger version of this figure.

Figure 7
Figure 7: Taxonomical classification for the order and genus levels. (A) Bar chart showing the order-level taxonomic abundance distribution of the bacterial metagenome in the water sample. A total of 50 bacterial orders were identified by the metagenomic analysis. The first 14 dominant orders of bacteria are shown in the figure. (B) Bar chart showing the genus-level taxonomic abundance distribution of the bacterial metagenome in the water sample. A total of 50 bacterial genera were identified by the metagenomic analysis. The first 15 dominant genera of bacteria are shown are shown in the figure. Please click here to view a larger version of this figure.

PCR reagents Volume (μL)
2x Taq Master Mix 20
Forward primer (10 pico mole) 1.5
Reverse primer (10 pico mole) 1.5
Crude DNA template 1.5
Sterile molecular biology water 15.5
Total volume 40

Table 1: PCR mastermix constituents. The reaction mixture composition of various PCR reagents.

Direction Primer Sequence 5’ – 3’ PCR conditions No. of cycles
Forward GGAGGCAGCAGTAAGGAAT 94 °C for 10 min  1
Denaturation at 94 °C for 30 s 35
Annealing at 50 °C for 30 s
Extension at 72 °C for 40 s
Reverse  CTACCGGGGTATCTAATCC Final extension at 72 °C for 5 min 1

Table 2: PCR cycle conditions for amplification of the 16S rRNA gene. The PCR cycle conditions required for 16S rRNA gene amplification are shown. The steps include an initial denaturation step, followed by 35 cycles of denaturation, annealing and extension, and a final extension step.

6x loading gel
Contents Quantity
Bromophenol blue 25 mg
85% Glycerol 7.06 mL
Milli-Q water 2.94 mL
Total volume 10 mL
50x Tris-acetate-EDTA (TAE) stock buffer composition
Contents Quantity
Tris base 242 g in 700 mL of double-distilled water
Glacial Acetic Acid (GAA) 57.1 mL
0.5 M (EDTA) pH 8.0 100 mL
Adjust the pH to 8.5 and make up the volume to 1000 mL with double distilled water
For 1x TAE: 20 mL of 50x TAE buffer + 980 mL of double-distilled water

Table 3: Composition of the 6x gel loading buffer and 50x Tris-acetate-EDTA stock buffer. The 6x gel loading buffer is mixed with the sample to be run on agarose gel electrophoresis. It contains bromophenol blue as the tracking dye. Glycerol increases the density of the sample being loaded for proper loading into the wells. The composition of the various reagents required for the preparation of the 50xTAE stock buffer is also shown. TAE buffer is one of the most common buffers used for AGE, and it maintains the pH at 8.5 and enables the migration of amplified DNA during AGE. Abbreviations: TAE = Tris-acetate-EDTA; AGE = agarose gel electrophoresis.

PCR reagents Volume (μL)
2x Taq Master Mix 5
Forward primer (10 pico mole) 0.5
Reverse primer (10 pico mole) 0.5
Crude DNA template 1.5
Sterile molecular biology-grade water 2.5
Total volume 10

Table 4: PCR mastermix composition for the identification of ARGs. The reaction mixture composition of various PCR reagents required for performing the PCR experiment.

Sr. No. Target gene Resistance to Primer Primer sequence (5’-3’) Amplicon size (bp) Annealing temperature (°C) References
1 dfrA Trimethoprim  Forward TGGTAGCTATATC
GAAGAATGGAGT
425 59 Racewicz et al., 19
Reverse TATGTTAGAGGCG
AAGTCTTGGGTA
2 blaTEM β – lactams Forward GCACGAGTGGG
TTACATCGA
310 60 Gebreyes, Thakur20
Reverse GGTCCTCCGAT
CGTTGTCAG
3 blaCTX-M β – lactams Forward CGATGGGACG
ATGTCACTG
500 52 Li et al. 21
Reverse CGGCTTTCTG
CCTTAGGTT
4 aac(6')-Ib Aminoglycosides Forward TATGAGTGGC
TAAATCGAT
395 50 Akers et al. 22
Reverse CCCGCTTTCT
CGTAGCA
5 aadA Aminoglycosides Forward ACCGTAAGGC
TTGATGAAACA
624 58 Ciesielczuk 23
Reverse GCCGACTACC
TTGGTGATCTC

Table 5: Primers for the PCR of ARGs in culturable bacteria. The different ARGs used in the present study along with their respective primer sequences are shown. The expected size of the amplicon is given in base pairs. The annealing temperature of each primer set is also mentioned.

Antibiotic  Concentration of antibiotic (µg/mL) CFU/mL
- - 3.0 x 10
CTX 3 4.5 x 107
CIP 0.5 3.2 x 108
K 15 9.6 x 105
E 20 1.6 x 108
VA 3 1.2 x 109

Table 6: Total and antibiotic-resistant bacteria counts. Five antibiotics were used for the initial isolation of the antibiotic-resistant bacteria from the water sample. The total bacteria counts (without antibiotics) and the AR bacteria counts are presented in terms of colony-forming units per milliliter (CFU/mL). Abbreviations: AR = antibiotic resistant; CFU = colony-forming units; CTX = cefotaxime; CIP = ciprofloxacin; K = kanamycin; E = erythromycin; VA = vancomycin.

Isolate code Microorganisms Family
1 Escherichia coli Enterobacteriaceae
2 Escherichia coli Enterobacteriaceae
3 Escherichia coli Enterobacteriaceae
4 Escherichia coli Enterobacteriaceae
5 Escherichia coli Enterobacteriaceae
6 Escherichia coli Enterobacteriaceae
7 Klebsiella pneumoniae Enterobacteriaceae
8 Klebsiella pneumoniae Enterobacteriaceae
9 Klebsiella pneumoniae Enterobacteriaceae
10 Klebsiella pneumoniae Enterobacteriaceae
11 Comamonas spp. Comamonadaceae
12 Comamonas spp. Comamonadaceae
13 Micrococcus spp. Micrococcaceae
14 Arthrobacter spp. Micrococcaceae
15 Aeromonas spp. Aeromonadaceae

Table 7: Identification of antibiotic-resistant isolates by 16S rRNA gene sequencing. Colony PCR was performed for each isolate using 16S rRNA gene-specific primers. The amplicons obtained were then sequenced and identified using appropriate bioinformatics tools.

Isolate No. Isolate CTX AMP LE C TGC CTR IPM GEN N TR CIP MAR MAR index
1 Escherichia coli 13R 0R 0R 28S 23S 11R 39S 20S 18S 0R 0R 6 0.5
2 Escherichia coli 31S 0R 12R 29S 23S 32S 37S 19S 16S 0R 14R 4 0.4
3 Escherichia coli 14R 0R 14R 14R 21S 10R 34S 17S 11R 24S 16R 7 0.6
4 Escherichia coli 28S 13R 18R 26S 21S 28S 32S 16R 11R 24S 19R 5 0.4
5 Escherichia coli 11R 0R 12R 26S 21S 10R 31S 17S 16S 22S 11R 5 0.4
6 Escherichia coli 27S 0R 12R 12R 22S 30S 32S 19S 11R 0R 14R 6 0.5
7 Klebsiella pneumoniae 28S 0R 17R 27S 22S 30S 32S 18S 22S 0R 16R 4 0.4
8 Klebsiella pneumoniae 29S 11R 26S 24S 22S 30S 28S 17S 16S 24S 23S 1 0.1
9 Klebsiella pneumoniae 29S 13R 25S 24S 22S 28S 29S 18S 17S 24S 25S 1 0.1
10 Klebsiella pneumoniae 33S 14S 26S 28S 22S 31S 32S 19S 20S 24S 29S 0 0
11 Comamonas spp. - - - 23S - - 37S - - - - 0 0
12 Comamonas spp. - - - 27S - - 42S - - - - 0 0
13 Micrococcus spp. 25S 17R 24S 32S 22S 34S 28S 20S - 21S 26S 1 0.1
14 Arthrobacter spp. 45S 57S 28S 26S 34S 27S 39S 26S - 28S 28S 0 0
15 Aeromonas spp. - - 20R - - - - - - - 20R 2 1

Table 8: Antibiotic resistance phenotype of the bacterial isolates analyzed by AST. Phenotypic resistance in the isolates was analyzed using the disc diffusion method. The numbers indicate the ZOI in millimeters (mm). For the MAR index, the numbers indicate the total number of antibiotics to which an isolate is resistant. Abbreviations: AST = antibiotic susceptibility test; CTX = cefotaxime; AMP = ampicillin; LE = levofloxacin; C = chloramphenicol; TGC = tigecycline; CTR = ceftriaxone; IPM = imipenem; GEN = gentamicin; N = neomycin; TR = trimethoprim; CIP = ciprofloxacin; R = resistant; S = sensitive; MAR = multiple antibiotic resistance; ZOI = zone of inhibition.

AMR GENE FAMILY GENE(S)
SMB beta-lactamase SMB-1
ampC-type beta-lactamase ampC1
VIM beta-lactamase VIM-20
CcrA beta-lactamase ccrA
NmcA beta-lactamase nmcR
ARL Beta-lactamase ARL-1
blaZ beta-lactamase blaZ
blaTEM beta-lactamase blaTEM*
blaCTX beta-lactamase blaCTX
AAC(6') aac(6')-Ib, aac(6')-34
ANT(3'') aadA
quinolone resistance protein (qnr) qnrS6, qnrVC5
resistance-nodulation-cell division (RND) antibiotic efflux pump evgA, mtrA, mdtA, acrD
ATP-binding cassette (ABC) antibiotic efflux pump oleC, macB, patA, bcrA
major facilitator superfamily (MFS) antibiotic efflux pump abaQ
trimethoprim resistant dihydrofolate reductase dfr dfr1, dfrD, dfrA20
rifampin phosphotransferase rphB
undecaprenyl pyrophosphate related proteins bcrC
methicillin resistant PBP2 mecD
vanJ membrane protein vanJ
tetracycline-resistant ribosomal protection protein tetT
chloramphenicol acetyltransferase (CAT) catB10
Erm 23S ribosomal RNA methyltransferase erm(37)
glycopeptide resistance gene cluster vanRB, vanRE, vanRD
MCR phosphoethanolamine transferase mcr-9
sulfonamide resistant sul sul3
*underlined genes were also detected in the culturable microorganisms

Table 9: ARGs identified using whole metagenomic DNA analysis. The total metagenome of the water sample was used for whole metagenomic sequencing, and the obtained sequences were annotated using the appropriate ARG database. The representative results of some of the important ARGs identified in the metagenomic DNA are shown. The underlined genes were also detected in the culturable microorganisms. Abbreviation: ARG = antibiotic-resistant gene.

Subscription Required. Please recommend JoVE to your librarian.

Discussion

The sample collection and processing play a significant role and might affect the results and interpretation of the study. Hence, to rule out variability in the samples, it is important to carry out sampling at multiple locations of the freshwater body being studied. Maintaining proper aseptic environmental conditions when handling such samples can prevent contamination. Moreover, to prevent changes in the bacterial composition that may influence the quality and quantity of extracted nucleic acids, the transit conditions should be maintained at 4 °C, with a minimal time lapse from the point of sample collection to the subsequent processing. Several studies have highlighted that this interim period between sample collection and processing can give variable results during later stages of analysis if not done carefully12,13.

Using a range of dilutions for plating ensures that colonies neither clump together nor are there too few colonies to count. Performing the experiments in duplicate is necessary to account for variations in CFU/mL that might arise due to pipetting/handling errors. Moreover, control plates are maintained for every experiment to ensure that the antibiotics used are working effectively and that false-positive results are eliminated. Hence, the control plates should have no visible colony growth. This indicates the efficacy of the antibiotics used.

During AST, the inoculum culture density and the thickness of the agar plate can influence the diameter of the ZOI and, hence, the interpretation of the results. Therefore, care should be taken to keep these two factors uniform when performing the AST experiments. The most critical aspect is the number of bacterial cells present in the inoculum. Generally, 1 × 108-2 × 108 CFU/mL of cells are used as the inoculum, which is equal to the 0.5 McFarland standard14. This concentration of the inoculum must be kept constant to avoid any variation in the results. Any concentration higher or lower than the required concentration must be diluted with the help of sterile saline and used immediately for inoculation within 15 min. While spreading the inoculum on the agar plates, care must be taken to avoid an excessive amount of inoculum. Excess inoculum can be removed by pressing the swab on the sides of the bacterial suspension tube before inoculating it to the MHA plate. Any deviation from the standard AST procedure can significantly impact the data obtained from such protocols11,15. A previous study showed that an MAR index value of ≥0.2 indicates high resistance in the isolates16. Since the interpretation of the results of the AST is based on the ZOI, under-inoculation or over-inoculation of the culture should be avoided.

For the PCR, the mastermix should be prepared on an ice block to minimize the chance of degradation of the ingredients and loss of activity of the enzyme. Wearing gloves while setting up the reaction minimizes the chance of external contamination17. The voltage during the AGE should not be too high, as this may lead to a heating effect and degradation of the loaded samples. Performing the AGE at an optimum voltage ensures that the bands are well separated and are sharp without any dragging or smudging effects.

Studies carried out in the past few decades have demonstrated the use of 16S rRNA gene amplicon sequencing for the identification of different microorganisms. For 16S rRNA gene sequencing, the choice of method for the extraction of the template DNA can cause biases, which, in turn, may affect the downstream analysis. Gram-positive bacteria have a thick peptidoglycan cell wall that can make it difficult to extract the nucleic acid. Therefore, the choice of the extraction method should be such that it effectively captures all the types of microbial DNA. The traditional boiling method to extract crude template DNA is one such efficient method to extract the contents of the cell, thus reducing biases in the results.

To understand the complete bacterial community of the water body, the high-throughput next-generation sequencing (HT-NGS) technique was used in this study. Whole metagenomic DNA analysis allows the study of the whole metagenome of a given sample. Culture-based techniques mainly give an aerobic count of the bacterial load, indicating the microbiological quality of a sample. However, culturable microorganisms constitute only 1% of the total microorganisms. The remaining microflora, which comprise a diverse range of species, including anaerobes, are poorly characterized and often ignored. These microorganisms might carry AR traits. Moreover, commensal microorganisms are a reservoir of AR genes that can be transmitted to pathogens via various genetic exchange events18. Many of these commensals are non-culturable and can be studied by a metagenomic approach involving HT-NGS, providing larger coverage for the identification of diverse microflora in any sample. Using metagenomic analysis, a detailed profile of the bacterial taxa was obtained, which complemented the culturable data. Moreover, such complementary approaches can provide an idea of the overall AR status of the water body under study.

In the present study, using a combination of both conventional culture-based and non-culture-based metagenomic techniques, we were able to identify the total bacterial diversity, different antibiotic-resistant bacteria, and the total pool of water-borne ARGs. The methodology described in this study can be replicated and customized for the identification of AR pathogens in any other water source-coastal water, natural water, and man-made drinking water. It can also be used for tracking the transmission of waterborne nosocomial pathogens and for monitoring hospital-associated infections in hospital and clinic settings through water sources such as sinks, toilets, bathtubs, and humidifiers. This will help in the surveillance of AMR and the identification of water-based AMR hotspots.

Subscription Required. Please recommend JoVE to your librarian.

Disclosures

The authors have no conflicting interests to disclose.

Acknowledgments

This work was partially supported by financial grants from the Department of Science and Technology-Promotion of University Research and Scientific Excellence (DST-PURSE) Scheme of the University of Mumbai. Devika Ghadigaonkar worked as a Project Fellow under the scheme. The technical help provided by Harshali Shinde, Senior Research Fellow under the Department of Science and Technology-Science and Engineering Research Board (DST-SERB) Project no: CRG/2018/003624, is acknowledged.

Materials

Name Company Catalog Number Comments
100 bp DNA ladder Himedia MBT049-50LN For estimation of size of the amplicons
2x PCR Taq mastermix HiMedia MBT061-50R For making PCR reaction mixture
37 °C Incubator GS-192, Gayatri Scientific NA For incubation of bacteria
6x Gel Loading Buffer HiMedia ML015-1ML Loading and Tracking dye which helps to weigh down the DNA sample and track the progress of electrophoresis
Agarose powder Himedia MB229-50G For resolving amplicons during Agarose Gel Electrophoresis (AGE)
Ampicillin antibiotic disc HiMedia SD002 For performing AST
Autoclave Equitron NA Required for sterilization of media, glass plates, test tubes, etc
Bioanalyzer 2100 Agilent Technologies NA To check the quality and quantity of the amplified library
Bisafety B2 Cabinet IMSET IMSET BSC-Class II Type B2 Used for microbiological work like bacterial culturing, AST etc.
Cefotaxime antibiotic disc HiMedia SD295E-5VL For performing AST
Cefotaxime antibiotic powder HiMedia TC352-5G For preparation of antibiotic stock solution required during isolation of antibiotic resistant bacteria
Ceftriaxone antibiotic disc HiMedia SD065 For performing AST
Centrifuge Minispin Eppendorf Minispin Plus-5453 Used to pellet the debris during crude DNA preparation
Chloramphenicol antibiotic disc HiMedia SD006-5x50DS For performing AST
Ciprofloxacin antibiotic disc HiMedia SD060-5x50DS For performing AST
Ciprofloxacin antibiotic powder HiMedia TC447-5G For preparation of antibiotic stock solution required during isolation of antibiotic resistant bacteria
Colorimeter Quest NA For checking the OD of culture suspensions
Comprehensive Antibiotic Resistance Database (CARD) database functional annotation of ARGs; https://card.mcmaster.ca/
Cooling Shaker Incubator BTL41 Allied Scientific NA For incubation of media plates for culturing bacteria
Deep Freezer (-40 °C)  Haier DW40L, Haier Biomedicals For storage of glycerol stocks
DNA Library Prep Kit NEB Next Ultra DNA Library Prep Kit for Illumina NA Paired-end sequencing library preparation
EDTA HiMedia GRM1195-100G For preparation of Gel running buffer for Agarose Gel Electrophoresis (AGE)
Electrophoresis Apparatus TechResource 15 cm gel casting tray For making the agarose gel  and carrying out electrophoresis 
Electrophoresis Power pack with electrodes Genei NA For running the AGE 
Erythromycin antibiotic disc HiMedia SD222-5VL For performing AST
Erythromycin antibiotic powder HiMedia CMS528-1G For preparation of antibiotic stock solution required during isolation of antibiotic resistant bacteria
Erythromycin antibiotic powder HiMedia TC024-5G For preparation of antibiotic stock solution required during isolation of antibiotic resistant bacteria
Escherichia coli ATCC 25922     HiMedia 0335X-1 Used as a control while performing AST
Ethidium Bromide HiMedia MB071-1G Intercalating agent and visualizaion of DNA after electrophoresis under Gel Documentation System
Fluorometer Qubit 2.0 NA For determining concentration of extracted metagenomic DNA
Gel Documentation System BioRad Used for visualizing PCR amplicons after electrophoresis
Gentamicin antibiotic disc HiMedia SD170-5x50DS For performing AST
Glacial Acetic Acid HiMedia AS119-500ML For preparation of Gel running buffer for Agarose Gel Electrophoresis (AGE)
Glycerol HiMedia GRM1027-500ML For making glycerol stocks
Imipenem antibiotic disc HiMedia SD073 For performing AST
Kaiju Database NA NA For taxonomical classification of reads; https://kaiju.binf.ku.dk/
Kanamycin antibiotic disc HiMedia SD017-5x50DS For performing AST
Kanamycin antibiotic powder HiMedia MB105-5G For preparation of antibiotic stock solution required during isolation of antibiotic resistant bacteria
Levofloxacin antibiotic disc HiMedia SD216-5VL For performing AST
Luria Bertani broth Himedia M1245-500G For enrichment of cultures
McFarland Standards Himedia R092-1No To compare density of culture suspension
Molecular Biology water HiMedia TCL018-500ML For making PCR reaction mixture
Mueller-Hinton Agar (MHA)  HiMedia M173-500G For performing Antibiotc Susceptibility Testing (AST)
Neomycin antibiotic disc HiMedia SD731-5x50DS For performing AST
PCR Gradient Thermal Cycler Eppendorf Mastercycler Nexus Gradient 230V/50-60 Hz  Used for performing PCR for amplification of 16S rRNA region and various Antibiotic Resistance genes
Primers  Xcelris NA For PCR amplication 
R2A Agar, Modified HiMedia M1743 For preparation of media plates for isolation of total and antibiotic resistant (AR) bacterial load
Scaffold generation CLC Genomics Workbench 6.0 NA For generation of scaffolds
Sequencer Illumina platform (2 x 150 bp chemistry) NA Sequencing of amplified library
Sodium Chloride  HiMedia TC046-500G For preparation of 0.85% saline for serially diluting the water sample
Soil DNA isolation Kit Xcelgen NA For extraction of whole metagenomic DNA from the filtered water sample 
Staphylococcus aureus subsp. aureus ATCC 29213 HiMedia 0365P Used as a control while performing AST
Taxonomical Classification Kaiju ioinformatics tool NA For classification of reads into different taxonomic groups from phylum to genus level 
The Comprehensive Antibiotic Resistance Database (CARD) NA NA For functional annotation of ARGs
Tigecycline antibiotic disc HiMedia SD278 For performing AST
Trimethoprim antibiotic disc HiMedia SD039-5x50DS For performing AST
Tris base HiMedia TC072-500G For preparation of Gel running buffer for Agarose Gel Electrophoresis (AGE)
Vancomycin antibiotic powder HiMedia CMS217 For preparation of antibiotic stock solution required during isolation of antibiotic resistant bacteria
Weighing Balance Mettler Toledo ME204 Mettler Toledo Used for weighing media powders, reagent powders etc.
NA - Not Applicable

DOWNLOAD MATERIALS LIST

References

  1. Prestinaci, F., Pezzotti, P., Pantosti, A. Antimicrobial resistance: A global multifaceted phenomenon. Pathogens and Global Health. 109 (7), 309-318 (2015).
  2. Knight, G., et al. Antimicrobial resistance and COVID-19: Intersections and implications. Elife. 10, 64139 (2021).
  3. Ventola, C. L. The antibiotic resistance crisis: Part 1: Causes and threats. Pharmacy and Therapeutics. 40 (4), 277-283 (2015).
  4. Naik, O. A., Shashidhar, R., Rath, D., Bandekar, J. R., Rath, A. Metagenomic analysis of total microbial diversity and antibiotic resistance of culturable microorganisms in raw chicken meat and mung sprouts (Phaseolus aureus) sold in retail markets of Mumbai. India. Current Science. 113 (1), 71-79 (2017).
  5. Naik, O. A., Shashidhar, R., Rath, D., Bandekar, J., Rath, A. Characterization of multiple antibiotic resistance of culturable microorganisms and metagenomic analysis of total microbial diversity of marine fish sold in retail shops in Mumbai, India. Environmental Science and Pollution Research. 25 (7), 6228-6239 (2018).
  6. Czekalski, N., GascónDíez, E., Bürgmann, H. Wastewater as a point source of antibiotic-resistance genes in the sediment of a freshwater lake. The ISME Journal. 8 (7), 1381-1390 (2014).
  7. Kraemer, S., Ramachandran, A., Perron, G. Antibiotic pollution in the environment: From microbial ecology to public policy. Microorganisms. 7 (6), 180 (2019).
  8. Edmonds-Wilson, S., Nurinova, N., Zapka, C., Fierer, N., Wilson, M. Review of human hand microbiome research. Journal of Dermatological Science. 80 (1), 3-12 (2015).
  9. de Abreu, V., Perdigão, J., Almeida, S. Metagenomic approaches to analyze antimicrobial resistance: An overview. Frontiers in Genetics. 11, 575592 (2021).
  10. Carlson, S., et al. Detection of multiresistant Salmonella typhimurium DT104 using multiplex and fluorogenic PCR. Molecular and Cellular Probes. 13 (3), 213-222 (1999).
  11. Breakpoint tables for interpretation of MICs and zone diameters, Version 12.0. European Committee on Antimicrobial Susceptibility Testing. , Available from: https://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Breakpoint_tables/v_12.0_Breakpoint_Tables.pdf (2022).
  12. Bharti, R., Grimm, D. Current challenges and best-practice protocols for microbiome analysis. Briefings in Bioinformatics. 22 (1), 178-193 (2019).
  13. Choo, J., Leong, L., Rogers, G. Sample storage conditions significantly influence faecal microbiome profiles. Scientific Reports. 5, 16350 (2015).
  14. Clinical and Laboratory Standards Institute. Methods for Dilution Antimicrobial Susceptibility Tests for Bacteria that Grow Aerobically, 11th edition. , Clinical and Laboratory Standards Institute. Wayne, PA. (2015).
  15. Bayot, M., Bragg, B. Antimicrobial Susceptibility Testing. StatPearls. , StatPearls Publishing. Treasure Island, FL. (2021).
  16. Joseph, A. A., Odimayo, M. S., Olokoba, L. B., Olokoba, A. B., Popoola, G. O. Multiple antibiotic resistance index of Escherichia coli isolates in a tertiary hospital in South-West Nigeria. Medical Journal of Zambia. 44 (4), 225-232 (2017).
  17. Lorenz, T. Polymerase chain reaction: Basic protocol plus troubleshooting and optimization strategies. Journal of Visualized Experiments. (63), e3998 (2012).
  18. Rolin, J. Food and human gut as reservoirs of transferable antibiotic resistance encoding genes. Frontiers in Microbiology. 4, 173 (2013).
  19. Racewicz, P., et al. Prevalence and characterisation of antimicrobial resistance genes and class 1 and 2 integrons in multiresistant Escherichia coli isolated from poultry production. Scientific Reports. 12, 6062 (2022).
  20. Gebreyes, W., Thakur, S. Multidrug-resistant Salmonella enterica serovar Muenchen from pigs and humans and potential interserovar transfer of antimicrobial resistance. Antimicrobial Agents and Chemotherapy. 49 (2), 503-511 (2005).
  21. Li, L., et al. Prevalence and characteristics of extended-spectrum β-lactamase and plasmid-mediated fluoroquinolone resistance genes in Escherichia coli isolated from chickens in Anhui Province, China. PLoS One. 9 (8), 104356 (2014).
  22. Akers, K., et al. Aminoglycoside resistance and susceptibility testing errors in Acinetobacter baumannii-calcoaceticus complex. Journal Of Clinical Microbiology. 48 (4), 1132-1138 (2010).
  23. Ciesielczuk, H. Extra-intestinal pathogenic Escherichia coli in the UK: The importance in bacteraemia versus urinary tract infection, colonisation of widespread clones and specific virulence factors. , Queen Mary University of London. PhD thesis (2015).

Tags

Isolation Identification Waterborne Antibiotic-resistant Bacteria Molecular Characterization Antibiotic Resistance Genes Overall Load Bacteria Identity Antibiotic Resistant Traits Antibiotic Resistant Genes Protocol Lab-grown Bacteria Culture-based Techniques Culture-independent Techniques Sewage Sample Pharmaceutical Effluence Sample Hospital Effluence Sample Clinical Settings Sample Nonclinical Settings Sample Experimental Procedures Water Sample Processing Filtering Particulate Matter Removal Serial Dilution Total Bacterial Load Determination
Isolation and Identification of Waterborne Antibiotic-Resistant Bacteria and Molecular Characterization of their Antibiotic Resistance Genes
Play Video
PDF DOI DOWNLOAD MATERIALS LIST

Cite this Article

Ghadigaonkar, D., Rath, A. Isolation More

Ghadigaonkar, D., Rath, A. Isolation and Identification of Waterborne Antibiotic-Resistant Bacteria and Molecular Characterization of their Antibiotic Resistance Genes. J. Vis. Exp. (193), e63934, doi:10.3791/63934 (2023).

Less
Copy Citation Download Citation Reprints and Permissions
View Video

Get cutting-edge science videos from JoVE sent straight to your inbox every month.

Waiting X
Simple Hit Counter