Escherichia coli and Salmonella spp. Early Diagnosis and Seasonal Monitoring in the Sewage Treatment Process by EMA-qPCR Method


Institute of Environmental Engineering, Czestochowa University of Technology, Czestochowa, Poland

*Corresponding author: A. Rorat, Institute of Environmental Engineering, Czestochowa University of Technology, Czestochowa, Poland; e-mail:

Submitted 25 September 2014, accepted 5 December 2014


Numerous studies have recently shown that molecular biology tools can allow for early diagnosis of pathogens and can substitute existing cost and time-taking traditional methods. One of them, the qPCR, is successfully used in microbiology and its utility has been assessed for many different biological materials. The aim of this study was to: 1) determine, optimize and apply qPCR as a method to detect Escherichia coli and Salmonella spp. in primary influents and final effluents from municipal wastewater treatment plant 2) define if addition of ethidium bromide monoazide (EMA) before DNA extraction can allow to distinguish between alive and dead bacteria, 3) quantify E. coli and Sal­monella spp. in wastewater during four seasons by qPCR and traditional spread plate method and determine the correlation between the indicator and pathogenic microorganisms. The obtained results has shown that qPCR can be used as a quantitative method in the diagnosis of investigated bacteria in wastewater with EMA pretreatment as a crucial step for a proper quantitative analysis of the presence of these bacteria in wastewater. Both E. coli and Salmonella spp. bacteria species were present in all samples of primary influents and final effluents. Our study shown that the quantity of investigated bacteria is strictly correlated with the season that they were obtained in.

Key words: Escherichia coli, Salmonella spp., ethidium bromide monoazide, qPCR, sewage treatment


Municipal wastewater effluents may constitute a significant contribution to drinking and recreational water pollution. To assess the danger to the environ­ment from the microbiological point of view, Total and Fecal Coliform Assays are used to indicate the hazard of the presence of pathogens associated with fecal mate­rial. Generally, it is expected that a reduction in their presence is equal to a reduction in quantity of all patho­gens in the analyzed material (Hagendorf et al., 2005). However this conventional method does not indicate the actual state of a microbiological pollution (Shannon et al., 2007). Traditional methods are time consuming and are limited by proper media content and culture conditions. Some microorganisms may also divide faster on media causing the incorrect interpretation of obtained data (Gilbride et al., 2006). In this case, the detection of indicator bacteria, like fecal coliforms or fecal streptococci is not sufficient, because inactiva­tion of pathogens depends strongly on their nature and applied system for sludge treatment in the wastewater treatment plant (Sidhu and Toze, 2009).

Escherichia coli is one of facultative anaerobes of human colonic flora, and some strains, like E. coli O157:H7 may cause very dangerous enteric diseases, including hemorrhagic diarrhea, abdominal cramps and hemolytic uremic syndrome. E. coli is the main indicator organism used commonly in the evaluation of microbiological contamination. This enterohaem­orrhagic E. coli may give rise to infections in the gas­trointestinal tract of mammals and cross contaminate humans. In 1993 the first report on the potential trans­fer of bacterial pathogens from land applied biosolids to humans was published. Besser et al. (1993) described cases after the consumption of cider made from apples collected from field treated with cow manure. Salmo­nella typhimurium is a pathogen which causes food-borne infections and salmonellosis and in general is present in raw and treated biosolids (Sahlstorm et al., 2004). According to the FDA (Food and Drug Admin­istration), the infective dose of Salmonella can be lower than 20 cells depending on the age and health of the host organism (FDA, 2003).

Pathogens may be easily detected with molecular biology methods in water, food and in samples coming from wastewater treatment plants. Since 1990 the poly­merase chain reaction (PCR) has been used as a method allowing for a completely culture-independent analysis of all microbial communities of bacteria (Giovannoni et al., 1990). In qPCR technique, an increasing fluores­cence signal is measured in real time, which enables the direct analysis of the results after PCR without addi­tional detection steps. However, DNA is isolated not only from live, but also from dead bacteria, so a positive PCR result can be obtained irrespective of the viability of cells (Fijałkowski et al., 2014). To avoid this prob­lem ethidium bromide monoazide (EMA) may be used. This substance is a dye, which intercalates the DNA only of damaged bacteria after photoactivation (Nogva et al., 2003). DNA with covalently bounded dye will not react in PCR reaction, thus completely eliminating the problem of live/dead cell differentiation.

The primary objective of the study discussed in this paper was to optimize the qPCR method for detection and identification of Salmonella spp. and E. coli in waste­water. We examined the SYBR® Green I dye, specific primers and EMA cross-linking to create an easy proto­col for determining the quantity of investigated bacteria in samples derived from wastewater treatment plants.

Materials and Methods

Wastewater samples. Wastewater (primary influ­ents and final effluents) samples were collected from a municipal wastewater treatment plant with second­ary treatment facilities based on an activated sludge process in southern Poland (unit per capita loading PE = 315 000, wastewater treatment plant capacity Q = 90 000 m3/d) during four different time periods (December-February = winter, March – May = spring, June August = summer, September-November = autumn). Samples were obtained in biological triplicates according to the Standard Methods for the Examina­tion of Water and Wastewater (APHA, 1995). Samples were transported in 5 l sterile plastic bottles in 4°C and analyzed within 6 h. Due to the varying amount of solid biomass contained in each type of wastewater samples, different volumes of wastewater were used for biomass collection by centrifugation at 5000 × g for 10 minutes at 4°C, respectively: 10–100 ml for primary influents, 100–300 ml for final effluents.

Bacterial strains (for standard curve in real time PCRreaction). Salmonella enterica subsp. enterica serovar Typhimurium str. LT2 (DSM 50912, DSMZ Germany) and E. coli (DSM 10235, DSMZ, Germany) bacterial strains were aseptically plated on Brain Heart Infu­sion broth (BHI) and incubated at 37°C with shaking at 350 rpm in thermomixer (Eppendorf, Germany) overnight. The actively growing cells were harvested by centrifugation 10000 × g for 5 minutes and used for genomic DNA extraction and bacteriological analysis. DNA was isolated using Qiagen DNeasy Blood & Tissue Kit (QIAGEN, Dusseldorf, Germany) according to the manufacturer’s protocol. The quantity and purity of the isolated DNA was determined spectrophotometrically at an absorbance of 260 nm and A260/A280, respec­tively. DNA was stored at a temperature of minus 80°C.

Genomic DNA isolation from wastewater. Waste­water samples were first filtered on an cellulose ace­tate membrane filter 0.45 μm (Whatman, USA) with a vacuum filtration system (Merck KGaA, Germany). DNA was isolated from the filter using MO BIO Pow­erWater® DNA Isolation Kit (Mo Bio Laboratories Inc., Carlsbad, USA) according to the manufacturer’s proto­col. DNA purity was confirmed by spectrophotometry (BioPhotometer, Eppendorf, Hamburg, Germany) as a A260/A280 ratio, which was in range 1.7–2.0 for all analyzed samples. Isolated DNA was stored at a temperature of minus 80°C (Innova range U101, New Brunswick Scientific co., Inc., New Jersey, USA).

EMA cross-linking. EMA dye was dissolved in water to a stock concentration of 5 mg/ml and stored at minus 20°C in the dark. EMA cross-linking was car­ried out according to Nocker and Camper (2006) for all studied wastewater samples. Membrane filters were placed in tubes containing 1 ml of sterile water and EMA was added. Final concentration of EMA in samples was 100 μg/ml. After a 5-min incubation in the dark, samples were light exposed for 1 min using a 650-W halogen light source placed 20 cm from the samples. Through whole procedure samples were placed on ice to avoid excessive heating. After EMA cross-linking, DNA was isolated from the filters as described above.

Real time quantitative PCR. Purified genomic DNA and primers were added to PCR reaction tubes containing 2 × PCR mastermix (Power SYBR® Green PCR Master Mix, Life Technologies Corp., USA) to final volume 20 μl. The final PCR solution contained 900 nM of each foward (reverse) primer and 10 to 100 ng of DNA. PCR was carried out in a Mastercycler Ep Real­plex2 (Eppendorf, Germany). The PCR reaction with all reaction components using sterile Milli-Q water (Merck KGaA, Germany) in place of DNA template was always run as a negative control in order to rule out any carry over contamination. Primers were as follows: forward 5’-GGTCTGCTGTACTCCACCTTCAG-3’ and reverse 5’-TTGGAGATCAGTACGCCGTTCT- 3’ (Calvó et al.,2008) for Salmonella spp. bipA gene and EcoF 5’-GTC­CAAAGCGGCGATTTG-3’ and EcoR 5’-GAGGCCA­GAAGTTCTTTTTCCA-3’ for uidA gene for E. coli (Lee et al., 2006). A standard curve was obtained by analysing 10-fold serial dilutions of DNA isolated from S. enterica subsp. enterica serovar Typhimurium str. LT2. Log-linear regression analysis showed a sig­nificant correlation (R2 = 0.995) between the CT values and the copy numbers of bipA gene of S. typhimurium. A similar standard curve was prepared for E. coli uidA gene analysis. The quantity of target gene copy number in analyzed samples was calculated from those stand­ard curves. The sample was considered negative if: the fluorescent signal did not increase within 40 cycles or its peak in melting curve was out of 80.7–82.0°C for Salmonella spp. and 76.1–77.6°C for E. coli.

The PCR program was as follows: initial denatura­tion at 95°C for 10 min and then 40 cycles at 95°C for 15 s, respectively: 64°C for 35 s for Salmonella spp. and 56°C for E. coli, followed by 72°C for 30 s. The melting curve program was: 95°C for 1 min, 60°C for 5 min then linear increase of temperature to 95°C in 30 min.

Traditional spread plate technique. The bacteriological analyses were conducted immediately after samples were transferred to the laboratory. Appropriate sample volumes in triplicate were diluted (10–2–10–6 dilution) in a phosphate saline buffer (140 mM NaCl, 10 mM phosphate buffer, and 3 mM KCl, pH 7.4) and varied according to sample source to ensure obtain­ing plates with 30–300 colonies. Inoculated plates were incubated for: 48 h at 37°C on Bismuth sulfite agar acc. to WILSON-BLAIR (Merck KGaA, Germany) for S. typhimurium detection and for 24 h at 37°C on Chro­mocult® Coliform Agar (Merck KGaA, Germany) for E. coli detection.

Statistical analysis. All results concerning the tar­get gene copy number and colony forming units were expressed as means ± standard errors. Differences between means were determined by the Tukey’s test, with the level of significance established at P < 0.05. The Pearson’s correlation was used to test the relationship between E. coli and Salmonella spp. concentrations in raw and treated waste water samples.

Results and Discussion

QPCR and EMA-qPCR analyses of Salmonella spp. and E. coli. Both Salmonella spp. and E. coli were pre­sent in primary influents samples during all analyzed time periods (Table I). EMA pretreatment resulted in statistically important decrease in detected target gene copies number for E. coli in all analyzed samples and for Salmonella spp. in samples taken in autumn and spring. The major differences among target gene copy numbers were observed between final effluents sam­ples. This is caused by the influence of the wastewater treatment process, in which microbiological contami­nation is partly reduced by chemical and biological treatment. Similar observations were done by Soejima et al. (2008) who discriminated live and heat-treated Listeria monocytogenes cells by EMA-qPCR. EMA-qPCR was also used to study E. coli O157, Salmonella spp. and L. monocytogenes survival under decontamina­tion and antibiotic treatments (Rudi et al., 2005). Those authors suggested the usage of this method for complex samples with mixed food borne bacterial communities, especially present in food. In this study, authors con­firmed that this method may be useful in the case of wastewater samples and may help to evaluate the effec­tiveness of the wastewater treatment process because of elimination of false positive results caused by detection of DNA from dead cells.

Table I
Enumeration of Salmonella spp. and E. coli in primary influents and final effluents by qPCR (target gene copy/100 ml) and traditional Petri dish method (C.F.U./100 ml). Results shown as means + SE n = 6
Primary influents Final effluents
Target gene copy/100ml x104 C.F.U/100ml x104 Target gene copy/100ml x104 C.F.U/100ml x104
Salmonella typhimurium
Summer 110.22±26.95 a 74.29±27.71 ab 25.00±7.07 b 27.98±1.7 a 6.28±0.28 b 2.00±0.00 b
Autumn 5810.00±438.41 a 9300±989.95 b 66.50±31.82 c 0 a 0 a 0 b
Winter 365.03±41.26 a 254.95±22.31 a 64.50±6.36 b 280.06±31.5 a 3.01±0.33 b 0 c
Spring 3427.53±7.88 a 1668.88±34.33 b 143.50±4.95 c 49.87±3.22 a 2.95±0.21 b 14.75±1.06 c
Escherichia coli
Summer 30.34±2.96 a 14.22±0.93 b 1160.00±84.85 c 4.88±2.07 ab 1.12±0.14a 0 c
Autumn 1206.64±135.26 a 491.35±31.44 b 626.5±2.12 a 2.75±0.48 a 0 b 3.50±0.71 b
Winter 85.81±13.98 a 38.45±4.33 b 105.00±22.63 ab 46.22±4.87 a 8.43±0.6 b 0 c
Spring 391.35±39.10 a 215.55±40.88 b 140.50±2.2 c 27.73±2.92 a 5.06±0.36 b 7.5±0.71 c
a, b, c – shows statistically significant differences within experimental groups in rows (p < 0.05)

On the other hand, many authors have been criticalof EMA treatment as a viability assay for qPCR-based methods, because at high concentrations it is able to penetrate viable cells resulting in lower qPCR results and reduced total DNA recovery (Gedalanga and Olson, 2009). Moreover, authors have shown how many fac­tors can influence EMA treatment regarding not only specific conditions of environmental samples (such as turbidity), but also specific cell membrane composi­tion or cell physiology of target organisms that naturally occur in wastewater.

Viable bacteria quantification by the spread plate method. Results obtained by qPCR method were com­pared with the traditional spread plate method. For all analyzed samples, the target gene copy number was higher than the number of colony forming units per 100 ml of sample (Table I). Similar conclusions were stated by Morio et al. (2008) while comparing tradi­tional and qPCR method for detection of Legionella pneumophila in environmental water samples. Lee et al. (2006) also explained that direct comparison between gene copy numbers and colony forming units is inap­propriate because of DNA isolation from dead bacterial cells. Moreover, even though we assume that there is only single copy of a gene in one bacterial cell, it may appear in other bacterial strains in multiple copies.

Evaluation of the effectiveness of wastewater treat­ment process by EMA-qPCR method. E. coli and Sal­monella spp. were present in primary influents during all four seasons (Fig. 1). According to Shannon (2007) the number of Salmonella spp. population ranges from 102–104 cells per 100 ml, which corresponds to the results obtained in this study. Salmonella spp. gene copies number was the highest in autumn and spring, medium in winter and the lowest in summer. E. coli was present mostly during spring and winter and was slightly detected during summer and autumn. Statis­tically important differences between all samples were observed. Similar results were obtained by Ulrich et al. (2005) who indicated that E. coli O157:H7 is sporadically present or absent in primary influents in warm seasons.

Quantification of bacteria in final effluents has shown very good effectiveness of treatment of wastewa­ter in the analyzed plant. Reduction in Salmonella spp. cells varied from 1.07 log units during summer, 1.92 log units in winter, 2.75 log units during spring, to more than 2.75 in autumn. Similar results were obtained for E. coli – 0.65 log units reduction in winter, 1.1 in sum­mer, 1.63 in spring and 1.92 reduction of viable bacteria in autumn, prove that the process leads to reducing the risk of contamination from pathogens.

Fig 1. Evaluation of effectiveness of wastewater treatment process by EMA-qPCR method: A) Escherichia coli uidA target gene copies/100 ml × 104 analyzed in primary influents (left) and final effluents (right) through four seasons; B) Salmonella spp. bipA target gene copies/100 ml × 104 analyzed in primary influents (left) and final effluents (right) through four seasons

Correlation between microorganisms. Pearson’s correlation analysis was used to identify whether any correlation existed between the concentration of indicator and pathogenic microorganisms in the dependence on the used identification method. The significant cor­relations were obtained in the case of primary effluents (Table II) independently on the used method. However for final effluents the values were lower, moreover no significant correlations were observed between E. coli and S. typhimurium presence when EMA was used. In the literature contradictory data can be found on the relationship between microorganisms occurring in water and wastewater. Some authors suggest that fecal coliforms (FC) are good indicators of the pres­ence in water of such microorganisms as Salmonella, Shigella, Klebsiella, E. coli, Vibrio or Pseudomonas (Patra et al., 2009). Others suggest no significant correlation between the concentration of E. coli and Salmonellae in wastewater (Song et al., 2010).

Table II
Relationships between indicators concentrations measured as tar­get gene copy number/100 ml by qPCR and EMA-qPCR method and colony forming units by traditional spread plate technique
Salmonella spp. E. coli
primary effluents 0.95* 0.98* -0.72*
final effluents 0.88* 0.09 0.85*
*Significant correlation for P < 0.05; qPCR- without ethidium ethidine monoazide, EMA-qPCR– with ethidium ethidine monoazide, CFU – colony forming units by traditional spread plate technique


In this study, EMA-qPCR was suc­cessfully used for determining the degree of contami­nation of wastewater with E. coli and Salmonella spp. cells. The analysis made in four different time periods allows to assess the rate of occurrence of pathogens in the municipal wastewater treatment plant in Poland.

The qPCR reaction is a highly sensitive molecular tool which allows for the quantification of bacterial cells in wastewater. Application of EMA – pre-treat­ment eliminates the problem of false-positive results in standard PCR reaction and may become an effective tool to assess the effectiveness of a wastewater treat­ment process. Compared to the traditional spread plate method, it is more precise and can give information about the presence of specific microorganism, not only the indicator bacteria. The most important advantage of using qPCR for diagnosis of pathogens is the pos­sibility of obtaining the result within 5 hours, which is sometimes crucial for a proper reaction.

The concentrations of E. coli and Salmonella spp. were higher when molecular methods (including EMA treatment) were used. In most cases significant correla­tions were observed between the concentration of the fecal indicator and pathogen. However taking into con­sideration negative results, E. coli could not be reliably used to predict the presence of pathogens in wastewater.

Moreover, in our opinion, further research is re-quired to understand the persistency of the traditional fecal indicators in environmental water samples in relation to other pathogenic microorganisms. Hence, quantitative PCR data could be required to assessthe survival of traditional fecal indicators along with the other pathogens depending on wastewater treat­ment and time.

The work was supported by the Polish Ministry of Science and Higher Education within project No N N523 612739 and BS PB 401-304/11. Agnieszka Rorat is a beneficient of the project „DoktoRIS – Scholarship Program for Innovative Silesia” funded by the European Union.


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