Multiplex PMA–qPCR Assay with Internal Amplification Control for

Oct 29, 2015 - This study for the first time explored a multiplex quantitative real-time PCR (qPCR) technique combined with propidium monoazide (PMA) ...
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Multiplex PMA−qPCR Assay with Internal Amplification Control for Simultaneous Detection of Viable Legionella pneumophila, Salmonella typhimurium, and Staphylococcus aureus in Environmental Waters Haiyan Li,†,∥ Hongyi Xin,‡,∥ and Sam Fong Yau Li*,†,§ †

Department of Chemistry, Faculty of Science, National University of Singapore, 3 Science Drive 3, Singapore 117543 Bioinformatics Institute, Agency for Science, Technology and Research, 30 Biopolis Street, Singapore 138671 § NUS Environmental Research Institute, National University of Singapore, 5A Engineering Drive 1, Singapore 117411 ‡

S Supporting Information *

ABSTRACT: Pathogenic microorganisms are responsible for many infectious diseases, and pathogen monitoring is important and necessary for water quality control. This study for the first time explored a multiplex quantitative real-time PCR (qPCR) technique combined with propidium monoazide (PMA) to simultaneously detect viable Legionella pneumophila, Salmonella typhimurium, and Staphylococcus aureus in one reaction from water samples. Sodium lauroyl sarcosinate (sarkosyl) was applied to enhance the dead bacterial permeability of PMA. The sensitivity of the multiplex PMA−qPCR assay achieved two colony-forming units (CFU) per reaction for L. pneumophila and three CFU per reaction for S. typhimurium and S. aureus. No PCR products were amplified from all nontarget control samples. Significantly, with comparable specificity and sensitivity, this newly invented multiplex PMA−qPCR assay took a much shorter time than did conventional culture assays when testing water samples with spiked bacteria and simulated environmental water treatment. The viable multiplex PMA−qPCR assay was further successfully applied to pathogen detection from rivers, canals, and tap water samples after simple water pretreatment.

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INTRODUCTION As an important part of water safety and security, water quality is emphasized worldwide nowadays. Water quality control includes water condition measurements of biological, chemical, and physical parameters. Among these parameters, microbiological risk is considered as a top priority in drinking water. Microbes in water are very diverse and include viruses, bacteria, and protozoa. Waterborne disease outbreaks have been reported every year around the world due to different microorganism contamination, especially pathogenic bacteria.1 Thus, rapid and reliable bacteriological monitoring is important and necessary for the advance warning of risk and the control of waterborne diseases. Escherichia coli bacteria are generally used as indicator organism to assess the microbiological quality of water samples. Some organisms, i.e., Legionella, Staphylococcus aureus, etc., are not quantitatively associated with the recommended the indicators2,3 and must be monitored separately at intervals. Legionella pneumophila, Staphylococcus aureus, and Salmonella typhimurium are widespread pathogens in various water sources,4−6 such as surface water sources. All of these organisms have the potential to form viable but nonculturable (VBNC) cells in strict environment,7−9 and the VBNC © 2015 American Chemical Society

pathogens can regain their ability to grow in favorable conditions. In addition, biofilms found on piping systems10,11 and natural aquatic systems12,13 can improve the bacterial survival in water environment, and these three pathogens have the function to form biofilm.14−16 The abilities of the pathogens to form biofilms and VBNC cells enhance the infection risk. The three pathogens also pose an important risk in community-acquired pneumonia (CAP),17,18 and they may potentially be developed as water-quality indicators or pathogen indictors.19−23 Traditional methods for bacterial pathogen detection in water rely on culture techniques because they are inexpensive and reliable. However, inherent problems, such as the timeconsuming and labor-intensive properties and the inability to detect VBNC species, exist for culture-based methods. To overcome the drawbacks of culture-based methods, molecularbiology-based assays, such as polymerase chain reaction (PCR), have been developed and widely used in current pathogens Received: Revised: Accepted: Published: 14249

July 24, 2015 October 23, 2015 October 29, 2015 October 29, 2015 DOI: 10.1021/acs.est.5b03583 Environ. Sci. Technol. 2015, 49, 14249−14256

Article

Environmental Science & Technology surveillance. PCR could serve as a rapid, specific, and highly sensitive detection approach for environmental water-quality control. However, its application was limited by its incapability to discriminate viable pathogens from dead ones. Nucleic acid dyes, such as ethidium monoazide (EMA) or propidium monoazide (PMA), can intercalate and modify DNAs by light activation to inhibit PCR reactions. By using the permeability differences between viable and nonviable cells, many researchers successfully developed the nucleic-acid dye-coupled PCR technique and applied it to detect viable pathogens in samples.24−26 However, the intercalating dyes cannot always suppress signals from dead cells, especially from high concentration cells, so as to overestimate the viable cells in samples,27,28 which limits the application of the methods. Some studies showed that treatment with bile salts or anionic detergents can improve the permeability of nonviable bacteria to intercalating dyes without compromising the viability of live cells.29−31 A study by Wang and colleagues indicated that the anionic detergent sarkosyl is more efficient for the membrane disruption of dead cells than the bile salts and may protect injured but viable cells from entry of PMA.29 Sarkosyl may be tested to enhance the permeability of PMA to dead bacteria. Multiplex qPCR assays can simultaneously detect and discriminate different pathogens in one sample and monitor the amplification of a targeted DNA molecule in real time. The multiplex qPCR assays not only possess all of the characteristics of regular PCR assays but also save both cost and time. Thus, they have been extensively used in the diagnosis and detection of pathogens. Until now, no publications reported the use of the nucleic acid dyes and sarkosyl coupled with multiplex qPCR to detect pathogens in any samples. In this study, the PMA coupled with multiplex qPCR assay was, for the first time, developed and applied for the simultaneous detection of viable L. pneumophila, S. typhimurium, and S. aureus in water systems.

Table 1. Organisms Strains Used in This Study and Their Information abbreviation

sourcea

Legionella pneumophila

L. pneumophila

Legionella maceachernii Salmonella sp.

Staphylococcus aureus

L. maceachernii S. Typhimurium S. Agonac S. Newportc S. aureus

Staphylococcus epidermidis Bacillus cereus Acanthamoeba castellanii Pseudomonas aeruginosa Saccharomyces cerevisiae Shigella dysenteriae Escherichia coli Bordetella pertussis Candida albicans Campylobacter jejuni A549 cells HEK239 cells Hela cells

S. epidermidis B. cereus A. castellanii P. aeruginosab S. cerevisiae S. dysenteriae E.coli B. pertussis C. albicans C. jejuni − − −

Philadelphia-1, ATCC 33152 serogroup 2b, ATCC 33154 serogroup 14b, ATCC 43703 ATCC 35300 ATCC 14028 ATCC BAA-707 ATCC 6962 ATCC 25923 N315d Mu 50d, ATCC 700699 ATCC 14990 ATCC 14579 ATCC 30010 NEA PA001 ATCC 201388 ATCC 13313 ATCC 53846 ATCC 9797 ATCC 10231 ATCC 29428 ATCC CCL-185 ATCC CRL-1573 ATCC CCL-2

organisms

a

ATCC, American Type Culture Collection, USA; NEA: National Environment Agency, Singapore. bStrains were taken from Professor Lee Yuan Kun’s lab, NUS. cStrains were taken from Professor Yuk Hyun-Gyun’s lab, NUS. dStrains were taken from Professor Chen John Yu-Shen’s lab, NUS.

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Primers and Probes Used for the Multiplex PMA− qPCR. The online software (http://www.idtdna.com/ Primerquest/Home/Index) was used to design oligonucleotide primers and TaqMan probes, and they were then checked with the online free Beacon Designer (http://www.premierbiosoft. com/qOligo/Oligo.jsp?PID=1). Primers and TaqMan probes were designed based on the species-specific L. pneumophila mip gene (GenBank accession no. AE017354), genus-specific S. typhimurium invA gene (GenBank accession no. CP001363), species-specific S. aureus nuc gene (GenBank accession no. CP007447.1), and B. cereus 16S rRNA gene (GenBank accession no. AE016877.1). All of the primers and probes were validated for the specificity by Blast analysis (NCBI) and synthesized by Integrated DNA Technologies (IDT, Coralville, Iowa, USA) in HPLC purification grade. The B. cereus 16S rRNA gene was used as internal amplification control (IAC) to prevent false negative results. The primers and probes sequences are listed in Table 2. All of the primers were analyzed by SYBR Green-based qPCR on Rotor-Gene Q (Qiagen, Hilden, Germany) for melting curve analysis. The TaqMan-based qPCR assay was done to check the signals of probes on a 7900HT Fast RealTime PCR System (Applied Biosystems, Foster City, CA, USA). The SYBR Green qPCR and TaqMan qPCR assays were shown in the Supporting Information. Genomic DNA Extraction. Bacterial genomic DNA was extracted with Wizard Genomic DNA Purification Kit (Promega Corp. Madison, WI, USA) according to the manufacturer’s guidelines. Rehydrated DNA was examined with spectrophotometer Nanodrop 2000 (Thermo Scientific,

METHODS AND MATERIALS All of the reagents were purchased from Sigma-Aldrich Inc. (St. Louis, MO, USA) except where noted otherwise. Bacteria Strain and Growth Conditions. L. pneumophila strain Philadelphia-1 (ATCC 33152), S. typhimurium (ATCC 14028), S. aureus (ATCC 25923), and Bacillus cereus (ATCC 14579) were obtained from the American Type Culture Collection (ATCC) and used to set up the multiplex PMA− qPCR. Strains L. pneumophila were grown on buffered charcoal yeast extract (BCYE) agar supplemented with L-cysteine and ferric pyrophosphate (Sigma-Aldrich) at 37 °C and 5% CO2 for 2 days. The other three bacteria were cultivated on Luria− Bertani (LB) agar (Sigma-Aldrich) at 37 °C and 5% CO2 for 24 h to 48 h. Single colonies of L. pneumophila or three other strains from the plates were selected to prepare liquid culture in ACES-buffered yeast extract (AYE, Sigma-Aldrich) and LB broth. Liquid bacterial cultures were grown at 37 °C in an orbital shaker incubator and collected at exponential growth phase.32−34 The spread plate technique was used for enumerating micro-organisms. Aliquots (0.1 mL) from the serial dilutions was spread onto the surface of corresponding agar plates. The agar plates were then inverted and incubated at 37 °C for 24 h, and the colonies on plates bearing 20 to 200 colonies were subsequently counted. The genomic DNAs for specificity verification were extracted from 19 other organisms, which are given in Table 1. Each sample was tested in duplicate reaction tubes by multiplex PMA−qPCR assay. 14250

DOI: 10.1021/acs.est.5b03583 Environ. Sci. Technol. 2015, 49, 14249−14256

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Environmental Science & Technology Table 2. Primers and Probes Used in the Viable Multiplex qPCR Assay pathogen

primer and probe name

product size/bp

primer sequence (5′−3′)

L. pneumophila

mip-F mip-R mip-P invA-F invA-R invA-P nuc-F nuc-R nuc-P 16S−F 16S-R 16S−P

80

GTTATCCCTGGATGGACAGAAG GCAAGACCTGAGGGAACATAA ATGCCAGCTGGATCAACTTGGGAA CACCGAAATACCGCCAATAAAG AGCGTACTGGAAAGGGAAAG ATCGCACCGTCAAAGGAACCGTAA CACCTGAAACAAAGCATCCTAAA CGCTAAGCCACGTCCATATT TGGTCCTGAAGCAAGTGCATTTACGA CGCAAGGCTGAAACTCAAAG GAGGATGTCAAGACCTGGTAAG ACAAGCGGTGGAGCATGTGGTTTA

S. typhimurium

S. aureus

B. cereus

123

149

105

modification

5′ 6-FAM/ZEN/3′ IBFQ

5′ TET/3′ BHQ1

5′ 6-JOEN/3′ BHQ1

5′ 6-TAMN/3′ BHQ2

F: Forward primer; R: reverse primer; P: probes.

light exposure on ice. Free PMA was removed by pelleting bacteria at 10000g for 10 min, and the pellets were washed twice before DNAs were extracted for qPCR. The minimal PMA concentration with maximal quantitative cycle (Cq) value was accepted as the optimal PMA conditions. Likewise, darkincubation time and light-exposure time were separately optimized. The extracted genomic DNAs were subjected to TaqMan-based qPCR. Each reaction was amplified in triplicate. Multiplex PMA−qPCR Assay. Reactions were performed in a 20 μL system containing 1 KAPA PROBE FAST qPCR Master Mix (Kapa Biosystems, Wilmington, MA, USA), 2 μL of sample templates, 0.5 μL of IAC template, 250 nM of each primer, and 500 nM of each probe. The cycling protocol was 95 °C for 15 min, 40 cycles of denaturation (94 °C, 10 s), and annealing and extension (60 °C, 1.5 min), using an Applied Biosystems 7900HT Fast Real-Time PCR System. Fluorescent data were acquired during the annealing and extension phase. A negative control using water was included in each qPCR reaction. The 16S rRNA gene of B. cereus was used as an internal amplification control. Standard Curves and Sensitivity of the Multiplex PMA−qPCR. The three viable bacteria suspensions prepared as above were serially tenfold diluted individually. To obtain viable bacterial mixtures, we equally mixed the different viable bacterial suspensions with the same dilution. Viable bacterial mixtures were then mixed with ∼104 CFU/mL corresponding killed cells. The serial bacterial mixtures were all processed with optimized sarkosyl and PMA treatment. The extracted genomic DNAs were used as a template for setting up the standard curve of multiplex PMA−qPCR. Each reaction was amplified in triplicate. Negative (no template) controls and internal amplification controls were included in each qPCR run. The lowest detectable quantities of bacteria per reaction system were defined as the analytical sensitivity. The different bacterial concentrations (log CFU for the reaction) were plotted against the corresponding Cq values. The slope and the linear relation of the curves were automatically calculated with Applied Biosystems SDS 2.4 software (Applied Biosystems, Foster City, CA, USA). The amplification efficiencies (E) were determined with the equation: E = 10−1/slope − 1. Validation of the Multiplex PMA−qPCR. Similarly as in standard curve assay, the serially tenfold diluted viable bacterial mixtures were prepared. Such samples were subjected to multiplex PMA−qPCR. At the same time, individual bacterial suspension was diluted to the same concentration as in the

Wilmington, MA, USA) for concentration and quality and stored at 4 °C until use. Optimization of Sarkosyl Treatment on Bacteria. Treatment conditions were adopted according to the previous report with slightly modification.29 Sarkosyl stock solution (20%, w/v) was prepared by dissolving sarkosyl in 0.1% (w/v) peptone water. The bacteria grown in the exponential phase were centrifuged at 5000g for 10 min at 4 °C, and the pellets were then suspended in 0.1% (w/v) peptone water with different concentration of sarkosyl. The suspensions were filtered with a 5 μm pore-size filter for separate bacterium cells and bacteria suspensions were treated at 40 °C for 30 min. The viability of the bacteria in the sarkosyl solutions with final concentrations of 0%, 0.1%, 0.2%, 0.3%, and 0.4% (w/v) were examined on appropriate plates. The loss of viability of the cells was tested by plating 100 μL of cell suspension on agar plates followed by corresponding incubation conditions. The optimized condition was chosen by maximizing sarkosyl concentration without sacrificing the viability of bacteria. Preparation of Viable and Dead Cells for Multiplex PMA−qPCR. The bacteria culture in the exponential phase were centrifuged at 5000g for 10 min at 4 °C, and the pellets were then suspended in 0.1% (w/v) peptone water.29 After being filtered with a 5 μm pore-size filter, the bacterial suspensions were adjusted to cell concentrations between 104 and 107 CFU/mL. The suspension was divided into two aliquots, and one aliquot was used to prepare death samples at 70 °C for 4 h.35,36 The others were used as viable samples, and viable cells were determined by enumeration assays. Optimization of PMA Treatment on Bacteria. Before PMA treatment, cells mixtures were prepared by mixing 250 μL of viable cells with 250 μL of killed cells followed by 0.2% sarkosyl treatment. For light-induced PMA−DNA cross-linking conditions, PMA concentration, incubation time, and lightexposure intensity should be optimized. In our assay, the conditions were examined with five concentrations of PMA (10, 20, 30, 40, and 60 μM), five dark incubation periods (5, 10, 15, 20, and 30 min), and four light exposure time (5, 10, 20, and 30 min) for three bacteria individually. Light exposure to 500 W halogen light source at 20 cm was applied for light intensity tests. Specifically, 10 mM PMA stock solution in 20% dimethyl sulfoxide (DMSO) was prepared and stored at −20 °C in the dark. Some of amount of PMA stock solution were added to cell mixtures of viable and killed cells up to 10, 20, 30, 40, and 60 μM final concentrations. The cells were then subjected to 15 min dark incubation at 40 °C37,38 and 10 min 14251

DOI: 10.1021/acs.est.5b03583 Environ. Sci. Technol. 2015, 49, 14249−14256

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Environmental Science & Technology bacterial mixture and subjected to simplex PMA−qPCR. Cq values obtained from the multiplex PMA−qPCR were compared with those obtained from the simplex PMA− qPCR. Each sample was tested in duplicate reaction, and mean Cq values with standard deviation (SD) were calculated for the experiments. In addition, samples spiked with different concentrations of the three bacteria and ∼104 CFU/mL of each killed cells were filtered with a 0.22 μm pore size polycarbonate filters and eluted with 0.1% (w/v) peptone water. The recovered bacteria were filtered with a 5 μm pore-size filter to separate cells into well-distributed suspensions, and the multiplex PMA−qPCR procedures were then performed with the suspensions. The bacterial samples were also subjected to enumeration assays on plates individually. Detection of Real Environmental Samples. A total of ten environmental water samples were tested in this study, including five tap water samples and five river and canal water samples from Singapore. For the rivers and canals water, sample 1 was collected from Singapore River, samples 2 and 3 were from two different sites in Bukit Panjiang canals, sample 4 was from the west coast canal, and sample 5 was collected in Chinese Garden. Each water sample of 1 L volume was collected and put in sterile screw-capped containers. All of the water samples were processed within 6 h of collection and kept in cold before extractions. The water samples were centrifuged with 1000g for 5 min at 4 °C, and the supernatants was filtered on 0.22 μm pore-size polycarbonate filters. Bacteria on the filter were eluted with 2 mL 0.1% (w/v) peptone water by repeated flushing, and then the filter was cut into small pieces that were immersed in 5 mL of 0.1% (w/v) peptone water in a 50 mL sterile centrifugation tube. With 5 min of sonication and 2 min of vortexing,36,38 the bacteria suspension was combined with the 2 mL elution. The suspensions were filtered with a 5 μm pore-size filter and processed with optimized sarkosyl and PMA treatment. Finally, multiplex PMA−qPCR was conducted as described above. Statistical Analysis. The data are presented as the mean ± standard deviation. In the optimization of sarkosyl concentration and the optimization of PMA cross-linking, data were analyzed by one-way ANOVA followed by a post hoc Tukey’s test. Other data were analyzed by a two-tailed paired Student’s t-test to determine whether or not these values were significantly different. With the standard curves, the average values of the slopes and y-intercepts were used to quantify viable bacteria. Statistical analysis to calculate the mean values and the standard deviation were performed using Microsoft Excel.

separately. The mean bacterial numbers on plates with different concentration of sarkosyl treatment were enumerated. The results were showed in Figure S2. In the figure, less than 0.2% sarkosyl has no influence on the viability of all the three bacteria, while 0.3% sarkosyl has significant influence on the viability of S. aureus (p < 0.05). Thus, 0.2% sarkosyl was selected as the treatment concentration for enhancing bacterial permeability to PMA. Optimization of the Cross-Linking Treatment with PMA. The PMA cross-linking conditions on three bacteria were individually optimized on PMA concentration, dark-incubation time, and light-exposure time. Significant differences were accepted at p < 0.05. DNA extracted from the samples after PMA treatment were subjected to TaqMan-based qPCR. The Cq mean values with standard deviation were showed in Figure 1. The condition with the highest Cq values was accepted as

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Figure 1. Optimization of PMA cross-linking conditions. (A) Optimization on PMA concentration; (B) optimization on dark incubation time; (C) light-exposure-time optimization.

RESULTS Validation of Primers and Probes. qPCR with SYBR green dye was used to perform the melting curve analysis of the amplicons. Melting peaks were automatically calculated by Rotor-Gene 6000 series software 1.7. The results showed that all three qPCR reactions with the designed primers resulted in single melting peak (Figure S1A), which meant the primers were suitable for the qPCR reaction. TaqMan-based qPCR reactions showed that all primers and probes can amplified the targets with strong fluorescence signal (Figure S1B). There existed clearly four bands of the products from multiplex qPCR by gel electrophoresis (Figure S1C). Optimization of Sarkosyl Treatment of Bacteria. Tolerance of the three bacteria to sarkosyl was studied

optimal condition. In Figure 1A, Cq values of all three bacteria were maximum at 30 μM PMA. Figure 1B showed that 20 min of dark incubation was enough for PMA to permeate the cell membrane. Figure 1C showed that maximum Cq values were obtained after 10 min of light exposure. The optimized PMA treatment condition was confirmed as 30 μM PMA with 20 min of dark incubation and 10 min of light exposure. Evaluation of Standard Curves and Sensitivity of the Multiplex PMA−qPCR. A PCR reaction with efficiency between 90% and 110% is considered a good reaction.39 In our standard curves (Figure 2), R2 values for all three bacteria 14252

DOI: 10.1021/acs.est.5b03583 Environ. Sci. Technol. 2015, 49, 14249−14256

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Environmental Science & Technology

Figure 2. Standard curves and sensitivity of the multiplex PMA−qPCR for different pathogens. DNA templates from tenfold-diluted bacteria were used.

Figure 3. Validation of viable multiplex qPCR by comparison of the viable multiplex qPCR and viable simplex qPCR. Genomic DNA templates (tenfold-diluted) from the bacteria were used.

were greater than 0.99, and the reaction efficiency ranges between 90% and 110% (Table S1) within the dynamic range from 2 to 3 × 105 CFU per reaction. The slopes of the standard curves for L. pneumophila, S. typhimurium, and S. aureus were −3.42, −3.30, and −3.38, respectively. The detection limits per reaction for L. pneumophila, S. typhimurium, and S. aureus were individually 2, 3, and 3 CFU per reaction. Validation of the Multiplex PMA−qPCR. Mean Cq values for each template of the bacterial mixture samples was compared to those of the single-template samples (Figure 3). The correlation (R2) for all simplex and multiplex PMA−qPCR were higher than 0.99, indicating high linearity. The efficiencies of both multiplex and simplex qPCR were between 90% and 110%. Student’s t tests showed that multiplex PMA−qPCR has no significantly difference with simplex PMA−qPCR (P > 0.05). Furthermore, to detect spiked bacterial samples, the calculated bacteria numbers from multiplex PMA−qPCR were not significantly different (P > 0.05) with the enumeration on culture plates (Table S2). These results meant that our developed multiplex qPCR is successful to simultaneously detect the three viable bacteria. Specificity of the Multiplex PMA−qPCR. DNA samples extracted from 19 organisms, which include bacteria, fungi, protozoa, and human cells, were separately used as template to perform multiplex PMA−qPCR. The results were showed in Figure 4 and Table S3. In all the reactions the IAC were amplified normally, while no other target products were

Figure 4. Specificity of the multiplex PMA−qPCR. Signals of IAC (yellow lines) were collected simultaneously through the TAMRA channels.

amplified from 13 organisms, which included A. castellanii, S. cerevisiae, S. dysenteriae, E. coli, B. pertussis, C. albicans, C. jejuni, A549 cells, HEK239 cells, Hela cells, P. aeruginosa, L. maceachernii, and S. epidermitidis (Figure 4). In addition, the other 6 bacterial strains (L. pneumophila Sgp.2, L. pneumophila Sgp.14, S. Agona, S. Newport, S. aureus N315 and S. aureus Mu50) were able to be detected by the multiplex PMA−qPCR and the CFU calculated from the multiplex PMA−qPCR were not significantly different with those from plate enumeration (Student’s t test) (Table S3). Such results indicated the 14253

DOI: 10.1021/acs.est.5b03583 Environ. Sci. Technol. 2015, 49, 14249−14256

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Environmental Science & Technology

lowest PMA concentration (30 μM) incorporated with sarkosyl and 5 μm filtration, which can suppress all of the killed cells’ signals. With the optimized conditions of sarkosyl treatment, PMA cross-linking procedure, and multiplex qPCR assay, the multiplex PMA−qPCR standard curves were successfully constructed. Although the sensitivities of the assay for L. pneumophila, S. typhimurium, and S. aureus were, respectively, 2, 3, and 3 CFU per reaction; such sensitivity may also be improved by changing the starting concentration of the samples. Considering the combined high concentration of killed bacteria for each dilution, the high linearity of the standard curves meant the dead bacteria signals had been suppressed completely. Furthermore, the results from our multiplex PMA−qPCR were comparable to that from the simplex qPCR in the dynamic range between 2 CFU per reaction and 3 × 105 CFU per reaction. The detection of spiked bacterial samples by the multiplex PMA−qPCR was not significantly different with the enumeration of CFU. Specificity testing showed that multiplex PMA−qPCR is specific to detect the three bacteria in water system. The assay is applicable to detect the samples with less than 107 total cells mL−1. For the samples with higher concentration of cells, appropriate dilution should be necessary. In addition, if the detection of water samples with very low bacteria concentrations, i.e., potable water, was required, it is essential to concentrate the samples before multiplex PMA-qPCR. Filters (0.22 μm) were used in our experiments to concentrate the water samples. The recovery of viable bacteria from the filter was above 98% by CFU counting (data not shown), which showed that the influence of the loss by filtering is negligible. With filtering and multiplex PMA−qPCR assay, five potable water samples were examined. The results showed that none of these three bacteria could be found in all of the potable water. The inspection of five water samples from rivers and canals showed that targeted bacteria in all the water samples were at a low level. While our multiplex PMA−qPCR assay showed great success for detecting the three viable bacteria, it still needs to be validated in the large scale before practical application because complexity of the content in environmental water samples may have an influence on the assay.47,48 For example, the dissolved saline level38 of water influence intercalating cross-linking with DNA and turbidity27 has influence on light penetration. Different water treatments may also have influence on application of the assay.49 Generally, water-sanitation-treatment techniques include chlorination, UV radiation, sand filtration, membrane filtration, and heating. The assay may be confined to some treatments.29,38,50 PCR inhibitors in environmental samples could be evaluated by IAC.51 In our assay, the 16S rRNA gene of Bacillus cereus was used as IAC to improve the reliability of false negative results from the multiplex PMA− qPCR application on environmental samples. It is necessary to monitor the degree of dead-cell signal reduction and its accountability for DNA losses during sample extraction by the implementation of sample-process controls.43

multiplex PMA−qPCR was species-specific to L. pneumophila, species-specific to S. aureus, and genus-specific to Salmonella. Application of the Multiplex PMA−qPCR Method on Environmental Water Samples. With the developed viable multiplex PMA−qPCR, ten environmental samples were examined. The results showed no bacteria were detected in all of the tap waters (Table 3). For the water samples from Table 3. Application of the Multiplex PMA−qPCR Method on Environmental Water Samples L. pneumophila tap water CFU/L

river CFU/L

1 2 3 4 5 1 2 3 4 5

ND ND ND ND ND ND 1.78 × 103 ND ND ND

S. typhimurium ND ND ND ND ND 5.67 8.59 1.17 2.96 1.68

× × × × ×

102 101 102 102 104

S. aureus ND ND ND ND ND 2.42 × 102 ND ND 8.99 × 101 ND

ND: not detected.

rivers and canals, L. pneumophila was only detected in one sample, and S. aureus was detected in two samples, whereas S. typhimurium could be detected in all the five samples though they were at a low level. The multiplex PMA−qPCR assay could be applied on environmental water samples successfully after simple pretreatment.

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DISCUSSION Rapid, sensitive, and specific methods using qPCR coupled with DNA intercalating dyes have been developed and applied to detect viable bacteria in samples.40 Of all the intercalating dyes, PMA and EMA were mostly used, while PMA were proven to be superior to EMA when used to differentiate the viable from dead cells due to EMA’s capacity to penetrate viable bacteria.41−43 In our current experiments, PMA was selected as the intercalating dye. However, as described above, the intercalating dyes could overestimate the viable cells in samples,27,28 which limits the use of the methods. The reason for the limitation should mainly be the lack of an effective mechanism for intercalating dyes to penetrate cell membranes. First, some inactivated bacteria still keep their membrane barrier to the dyes. Sarkosyl was adopted to enhance the permeability of dead bacteria to PMA in our assay. The viability assay showed that incubation with 0.2% sarkosyl at 40 °C for 30 min has no significant influence on all of the three live bacteria. The higher incubation temperature (40 °C) was adopted for PMA to penetrate dead cells.37,38 Second, clumped bacteria also hinder the dyes from penetrating effectively the cells and make the enumeration of CFU lack of accuracy.44 An earlier study showed that a 5 μm syringe-fitted filter rapidly dispersed the clumps of bacteria to a single cell culture.45 Considering the size differences of the three bacteria, we selected the filter with 5 μm pore size, through which the biggest bacteria Salmonella could pass. The CFU of the filtered bacteria were significantly higher than those from nonfiltered samples (data not shown). This meant that such filtration of the bacteria is suitable for the bacterial dispersion. A previous report showed that in 75 and 150 μM concentrations, PMA has the desirable effect on low concentrations of viable cells.46 In our study, we selected the

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ASSOCIATED CONTENT

S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.est.5b03583. 14254

DOI: 10.1021/acs.est.5b03583 Environ. Sci. Technol. 2015, 49, 14249−14256

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Additional details on real-time PCR assays. Figures showing the analysis of primers and probes in real-time qPCR and the optimization of sarkosyl concentration for treatment of bacteria. Tables showing the standard curve and amplification efficiencies, validation of the multiplex PMA−qPCR by comparison of the viable multiplex qPCR with conventional culture assay, and specificity results. (PDF)

AUTHOR INFORMATION

Corresponding Author

*Tel: (65)-6516-2681; fax: (65)-6779-1691; e-mail: chmlifys@ nus.edu.sg. Author Contributions ∥

These authors contributed equally

Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS We acknowledge financial support from the National University of Singapore, National Research Foundation, Environment and Water Industry Development Council Programme Office (EWI RFP 1301-IRIS-21 and EWI RFP 1301-IRIS-26), and the Ministry of Education (R-143-000-582-112 and R-143-000519-112). We thank the Shenzhen Development and Reform Commission (SZ DRC) for supporting our collaborative project with Peking University Shenzhen Graduate School.

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