Eco-friendly management of enteroviruses in wastewater
Abeer M. Hegazy a,∗, Azza H. El-Salakawy b, Mohamed M. Shaban c,Mohamed M. Yehia a, Mohamed S. AbuSalama d
a National Water Research Center (NWRC), Central Laboratories for Environmental Quality Monitoring (CLEQM), Egyptb Microbiology Department, Faculty of Medicine, Al-Azhar University, Egyptc Institute of Environmental Studies & Research, Ain Shams University, Egypt
d National Water Research Center (NWRC), Drainage Research Institute (DRI), Egypt
Available online 12 December 2013
bstract
The wastewater treatment facility in El-Manzala (sedimentation basins followed by vegetated cells) was investigated to evaluatets performance as a low cost treatment facility in managing viral pollution. Sedimentation basins are considered to be physicalreatment, while vegetated cells are considered as biological treatment. Enteroviruses were detected and determined using twoechniques, cell culture as infectivity assay and real time reverse transcriptase-polymerase chain reaction (real time RT-PCR) as aolecular biological technology.The results revealed that the wastewater treatment facility in El-Manzala showed good performance under Egyptian climatic
onditions. The aquatic macrophytes system (biological treatment) showed better performance compared to the sedimentationasins (physical treatment) in removing viral loads. Enteroviruses load at the wetland inlet ranged between 50 and 100% as viralnfectivity (VI) by cell culture, and between 4.9 × 104 and 59.5 × 105 gene copies (GC) by real time RT-PCR. The virus loadfter sedimentation basins ranged between 25 and 50% as VI and between 3.7 × 102 and 4.5 × 104 GC, while after the biologicalreatment recorded 0% as VI and between 0 and 2 GC.
An empirical model was developed to describe the relationship between the quantity of enteroviruses using molecular biologynd infective assay as a predictor variable.
The present study concluded that the wastewater treatment wetland in El-Manzala can be considered as an effective facility ineducing viral contamination of the Bahr El-Baqar drainage water.
2013 National Water Research Center. Production and hosting by Elsevier B.V. All rights reserved.
Drainage water reuse (DWR) has been practiced successfully as a water and nutrient resource in agriculture.owever, the major concern regarding this process is the potential hazards related to pathogen transport. One of
20 A.M. Hegazy et al. / Water Science 27 (2013) 19–29
the most polluted drains in Egypt is the Bahr El-Baqar drain (Abdel-Shafy and Aly, 2002). Bahr El-Baqar drainbasin is located in a densely populated area of the Eastern Nile Delta, passing through Qalubia, Sharkia and IsmailiaGovernments (Taha et al., 2004). The total wastewater discharged from Bahr El-Baqar drain into Lake Manzala is 1.4billion cubic meter/year (NAWQAM, 2005).
Wetlands, especially constructed wetlands are agri-environmental measures (AEM), mainly to improve nutrientretention and biodiversity in intensive agricultural areas. The use and implementation of these measures for constructionand/or management, vary greatly. One strong advantage of constructed wetlands over natural wetlands is that the finaleffluent can be chlorinated. The use of constructed wetlands can be a cost-effective treatment alternative (Baltic Deal,2011; Salomon and Sundberg, 2012). Wetlands also improve water quality through mechanical, physical, physico-chemical, biological and biochemical processes. These abilities are also used in constructed wetlands for wastewatertreatment but within a more controlled environment. In addition, wetlands provide the supporting services necessary forthe production of all other ecosystem services such as soil formation and retention, nutrient cycling, primary productionor water cycling. These ecosystem services improve water security, security from natural hazards and climate changeadaptation. In short, wetlands are clearly among the most valuable ecosystems on Earth (UNCSD, 2012). Constructedwetlands with emergent vegetation have been used to treat various types of wastewaters (Wallace and Knight, 2006).They are efficient in removal of organics through microbial degradation and settling of colloidal particles. Suspendedsolids are effectively removed via settling and filtration through the dense vegetation (Kadlec and Wallace, 2008).
Contamination of reused waters by infectious pathogens has the potential to affect the human health (Meinhardt,2002). Viral infections are now recognized as a major cause of illness in humans. Indeed each year, enteric viruses areresponsible for the majority of non-bacterial gastro-enteritis or infectious hepatitis (Koopmans et al., 2003). Virusesthat can multiply in the gastrointestinal tract of humans or animals are known as “enteric viruses.” There are morethan 140 enteric viruses known to infect humans (AWWA, 1999; Taylor et al., 2001; Nwachuku and Gerba, 2006).The Australian National Guidelines for Water Recycling recommended the use of enteroviruses as “representativesof viral pathogens” for the validation monitoring of wastewater treatment processes (NRMMC-EPHC, 2006). TheUS Environmental Protection Agency (USEPA) emphasized that waterborne viruses are research priority for pollutedwater, both drinking and recreational water have been shown to have transmitted viruses. Viral contamination of publicwaters is a leading health concern around the world, the transmission of viruses through consumption of/or contactwith contaminated water is well recognized (USEPA, 2010).
Enteroviruses belong to the Picornaviridae family, are spherical and non-enveloped viruses, with a genome consistingof a positive-sense single-stranded RNA. The 5′ terminal untranslated region (5′ UTR) is highly conserved and is usefulfor molecular identification purposes (Pallansch and Roos, 2001; Racaniello, 2001). There methods are capable ofdetecting and measuring viruses in water (Craun, 1992; Fields et al., 1996; Payment and Hunter, 2001). The RT-PCRmethod cannot distinguish between infectious and inactivated viral particles. Free viral RNA is known to survive brieflyin the environment due to the presence of bacterial endonucleases (Tsai et al., 1995). However, RT-PCR detection ofenterovirus genome is essentially due to well-protected RNA in viral particles which is inactivated or not (Haramotoet al., 2004). In addition, some studies showed correlations between the detection of viral RNA by RT-PCR and thedetection of viral infectivity (Le Guyader et al., 1994). Furthermore, enteric viruses have properties that make themvery stable in environment where they may remain infective after several months (Sair et al., 2002; Griffin et al., 2003).
The present study was conducted to evaluate the performance of El-Manzala constructed wetland as a low costfacility to remediate (physically and biologically) viral pollution in wastewater through sedimentation basins andphytoremediation treatment using planted cells; figure out the relation between enteric viral infectivity and quantityusing correlation analysis; and develop an empirical regression model to predict and describe this relation usinginfectivity assay (tissue culture) as a predictor variable.
2. Materials and methods
2.1. Study area
Lake Manzala Constructed Wetland (MCW) was established at the outlet of the Bahr El-Baqar drain in the northerneast of Egypt (Fig. 1) (31◦9′ N, 32◦11′ E, 6 ft above sea level). The MCW consists of intake structure, pump station,two sedimentation basins, ten free water surface cells, and reciprocating unit consisting of two subsurface flow cells(Rashed et al., 2000). The free water surface system was investigated. This system consists of two sedimentation basins
A.M. Hegazy et al. / Water Science 27 (2013) 19–29 21
tcp42
2
ffbw(
2
c
Fig. 1. Schematic diagram of the MCW locations.
hat ended with collection channel, followed by ten surface flow wetland treatment cells planted with reed (Phragmitesommunis) that also ended with collection channel. MCW employed two sedimentation basins, into which screwumps lift 25,000 m3/day of wastewater. The depth of water in the ponds is 1.5 m. After water is allowed to settle for8 h in the sedimentation basins, followed by surface flow cells divided into ten cells with approximate dimensions of50 m × 50 m and 55 cm average water depth (Allam, 2009).
.2. Monitoring locations
Water quality data were collected from December 2010 to September 2012. Water sampling was scheduled forour monitoring locations in the wetland. The sampling locations of the wetland surface flow treatment included theollowing: intake structure and pumping station, which contains three screw pumps (inlet) (1), two sedimentationasins and two dry beds end with collection channel (SB) (2), ten planted surface flow wetland treatment cells endith collection channel (VC) (3), water distribution and outflow channels and effluent reuse area used as a fish farm
Ponds “P”) (4) (Fig. 2).
.3. Sampling requirements
Eight water samples (40 L each) were collected from each location. All sampling and analyzing processes werearried out in accordance with standard methods for the examination of water and wastewater (APHA, 2005).
Fig. 2. Schematic diagram of the site MCW for sampling.
22 A.M. Hegazy et al. / Water Science 27 (2013) 19–29
2.4. Virus concentration
The method involves primary concentration by filtration, elution of solids or bio-solids associated viruses andsecondary concentration by precipitation.
The pH of each sample was adjusted to 3.5, then viruses were filtered using positive pressure and then applied at aconstant rate (under 10 bar) via a vacuum pump through positive charge nitrocellulose membrane filter (0.45 �m poresize, 142 mm diameter) (Kfir et al., 1995). The adsorbed viruses were eluted by 70 ml eluted solution consists of 3%beef extract (proteinaceous), 1% Tween 80 (dispersants) and 1 M Glycine (buffering agents), then adjusted pH 9.5,and collected in sterilized tubes. Re-concentration method was accomplished by organic flocculation as described by(Katzenelson et al., 1976). The precipitation occurred by lowering the elution’s pH 3.5 by HCl and distributed in tubesand centrifuged at 2500 rpm for 30 min. The supernatant was discarded and the precipitate was re-suspended in 3 mlof sterile 0.15 M Na2HPO4 then stored in aliquots at −80 ◦C till used (available for one year) for analysis.
2.5. Virological analysis
Enteroviruses in the concentrated sample were cultured in green monkey kidney (Vero) cells and detected by realtime RT-PCR.
2.5.1. Infectivity assayTo determine the infective enteroviruses, Vero cells were cultivated, which were supplemented with 10% fetal
calf serum (FCS) and 1% antibiotic–antimycotic mixture. After a confluent monolayer has developed, 0.1 ml of theconcentrated water samples were inoculated into Vero cells. Incubation was set as at 37 ◦C has done with dailymicroscopic examinated for CPE (Fout, 1999).
The cell culture procedure detects enteroviruses that are capable of infecting and producing cytopathic effects(CPE) in the Vero cell line, and characteristically showing rounding and detaching of cultured cells in six to eight days(Guttman-Bass, 1987; Morris, 1985). CPE was scored in four degrees as follow: first degree of CPE, were seen somesmall foci of cell destruction with an almost completely normal cell sheet (25%), second degree of CPE there weremore than a quarter of the cell sheet involved (50%), third degree of CPE, more than half of the cell sheet was separatedfrom the glass surface and the rest of the entire cell sheet was abnormal with many granular cells (75%), fourth degreeof CPE, most of cells were rounded and floated in the fluid (100%). For the CPE, examined under inverted microscope,the infectivity of enteroviruses can be accessed.
2.5.1.1. Molecular assay. The molecular method real time RT-PCR has been widely used to detect viruses in envi-ronmental waters (Borchardt et al., 2010). Concentrated water samples were tested for the enteroviruses by real timeRT-PCR to determine the quantification of gene copies (GC). One step RT-PCR was performed using QIAGEN OneStep RT-PCR kit (QIAGEN Company, USA).
2.5.1.2. RNA extraction. Viral RNA in the concentrated wastewater samples was extracted using QIAamp viral RNAmini kit (QIAGEN).
2.5.1.3. Real time RT-PCR. The RNA of enteroviruses was detected using one-step RT-PCR with universal primers andprobes. Detection of the genome of enteroviruses was performed (Ogorzaly and Gantzer, 2006). RNA concentrationspresent in wastewater samples were estimated using the standard curves (Fig. 3), according to the end-point dilution ofthe positive controls (Rutjes et al., 2005). Quantitative reverse transcription-PCR was performed using an MX3000Pdetection system (Stratagene, La Jolla, CA, USA).
2.6. Data analysis
2.6.1. Viral removal efficiencyPollutant removal efficiency, usually represented by a percentage, specifically refers to the pollutant reduction from
the inflow to the outflow of a system. Percentage removal efficiencies were calculated for each treatment in the wetlandsystem by estimating the total amount of enteroviruses retained by each treatment. The average reduction percentage
A.M. Hegazy et al. / Water Science 27 (2013) 19–29 23
o(
2
v
av
wrm
3
fe
3
da
itVpd
Fig. 3. Standard curve of enteroviruses by real time RT-PCR.
f each treatment was obtained from 8 replicates. The calculations have been shown as described by Matthew et al.2005)
Reduction % =(
100 −[(∑
effluent enteroviruses∑influent enteroviruses
)× 100
])(1)
.6.2. Empirical modelingThe present research aimed to quantify relationship between the gene quantity described as gene copies (GC) and
iral infectivity (VI) of enteroviruses concentrated from wastewater.Correlation and regression analyses were carried out to fit an equation to the previous data where GC was considered
s a response variable or dependent variable (Y) that was measured at the independent variable VI, also called inputariable, regressors, or predictor variable.
These two variables were introduced to the Table curve 2D v3 as a powerful exploratory tool. The analysis startedith evaluating the underlying assumptions including testing for normality of the examined variables, linearity of the
elationships between the dependent and the independent variables. Regression analysis was then used to develop aodel for predicting gene quantity GC from the independent variables VI.
. Results
The current study provided the first data on human enteric viruses and indicator microorganisms removal at dif-erent steps of wastewater treatment by constructed wetland in Egypt. Enteroviruses were concentrated from aquaticnvironment, and they were obtained from samples collected from different stages of El-Manzala constructed wetland.
.1. Removal efficiency
The average of final reduction R3 (after stages of wetland) of viable enteroviruses in treated wastewater usingifferent stages of constructed wetland were 100%, while the average of R1 (after SB) and R2 (after VC) were 56.3%,nd 100% respectively.
The average of reduction percentage was obtained from 8 replicates for each treatment, enteroviruses load at thenlet ranged between 50 and 100% viral infectivity (VI), and between 4.9 × 104 and 59.5 × 105 gene copies (GC) forhe real time RT-PCR. The virus load in SB ranged between 25 and 50% VI and between 3.7 × 102 and 4.5 × 104 GC.irus load MCW was 0% as VI and between 0 and 2 GC. The percentages of enteroviruses of VC were similar to the
ercentage of the ponds (fish farms). There was difference between the inlet and outlet virus load, but there was noifference between virus load after SB and VC (Figs. 4 and 5; Table 1).
24 A.M. Hegazy et al. / Water Science 27 (2013) 19–29
Fig. 4. The effect of MCW on eneteroviruses assayed by cell culture.
Fig. 5. The effect of MCW on eneteroviruses assayed by real time RT-PCR.
R2: Reduction percentage after VC.R3: Reduction percentage after fish farm.
3.2. Empirical modeling
The correlation analysis reported that VI appears to be related to the predictor variable GC (Table 2). In addition,the K–S and Shapiro–Wilk statistics were both non-significant (Sig. >0.05) for variables.
Consequently, variables introduced to regression analysis were not normally distributed. The model where GC isbtained from VI, (adjusted R2 = 0.962). The model appears to be very useful for making predictions since the value of2 is close to 1. The results of the model indicate that the regression model was significant at the 0.1% level indicating
hat there is enough evidence to conclude that the predictor VI is useful for predicting GC; therefore the model is usefulnd the regression is significant (Table 2). The regression coefficients are presented in (Table 3). It seems that the GCs significantly predicted by the VI of the model. This is a positive relationship, indicating that as VI increases, GCncreases too.
The model can be written as follows:
Y = c
√(X − a
b
)(2)
Using the previous equation, the value of the dependent variable for each case can be estimated. These estimatesill differ from the actual measured scores by an amount usually referred to as the residuals. Residuals therefore are aeasure of unexplained variance or error that remains in the dependent variable that cannot be explained or predicted
y the regression equation.
.3. Meeting assumptions
Residual analysis is used to examine the conformity of the regression analysis to the regression assumptions. Fig. 6hows the normal probability plot (studentized residuals versus standarized predicted values) that is commonly usedo evaluate whether or not the derived regression model violates the assumption of linearity and constant variance inhe dependence variable.
The normal probability plot for the regression standardized residuals shows that the residuals fit the expected pattern
straight line from 0.0 to 1.0) well enough to support a conclusion that the residuals are normally distributed (Table 4nd Fig. 6).
Fig. 6. Normal probability plot for the residuals.
26 A.M. Hegazy et al. / Water Science 27 (2013) 19–29
Table 4Test of normality for residuals.
Kolmogorov–Smirnova
Statistic df Sig.
Residuals 0.181 17.000 0.142
a Lilliefors significance correction.
4. Discussion
Many microbial agents that were not traditionally considered contaminants are now present in the environment in aglobal scale. These newly recognized contaminants are dispread in the environment as a result of domestic, commercialand industreial activities (Kolpin, 2002). Human sewage contains a wide variety of viruses which sometimes shed ina high numbers (Bosch et al., 2008). Even at low concentrations, these viruses can be responsible for a large rangeof human illnesses as paralysis, meningitis, respiratory diseases, myocarditis, congenital abnormalities, epidemicvomiting, diarrhea, and hepatitis (Kopecka et al., 1993). Most guidelines for viruses in water refer to the qualitativepresence or absence of viruses, but the acceptable quality and treatment of water could not be determined withoutquantitative assays.
During the current study, the presence of enteroviruses was detected in 100% of the influent wastewater samplesanalyzed with real-time RT-PCR. These results are consistent with past studies (Bofill et al., 2006; Carducci et al., 2008;Katayama et al., 2008; Rodriguez-Diaz et al., 2009). The final average removal efficiency of El-Manzala constructedwetland results were 100% VI and 99.9% GC, it is in agreement with other studies, such as Cypress wetlands inFlorida showed that enteric viruses were reduced by an average of 98% (Karpiscak et al., 1995). Another studyon average bacteriophage removal was 98.8%, the study suggests that a subsurface-flow wetland can decrease thevirus load by approximately 99% (Vidales et al., 2003). In the same context, the removal efficiency of a constructedwetlands subsurface flow systems (SFS) system was tested at Santee, California. An indicator of viral pollution (MS-2bacteriophages) was reported to be 98.3% removed (Zirschky and Reed, 1988).
Due to the fact that some viruses are more resistant to chlorination than bacteria (Kraus, 1977; Gersberg et al., 1987),so physical and biological wetland treatment used to control viral pollution are considered as ecological methods withoutusing chemicals. Physical and biological processes are used to remove pollutants in wetlands. The physical mechanismoccurs in sedimentation by gravitational settling (Schueler, 1992).
The phytoremediation technology is an invaluable tool box for wider application in the realm of environmentalprotection. This technology has become attractive alternative to conventional cleanup technologies due to relativelylow capital costs and their inherently esthetic nature (Vidales et al., 2006).
During the passage of the wastewater through the rhizosphere, the wastewater is treated by filtration, sorption andprecipitation processes in the soil and by microbiological degradation. The resulting biochemical processes correspondto the mechanical and biological processes in conventional mechanical treatment systems including denitrification. Theeffluent is collected at the outlet channel. The removal is due to microbial growth attached to plant roots, stems and leaflitter that has fallen into the water. The major sources of oxygen for these reactions are reaeration at the water surfaceand plant translocation of oxygen from the leaves to the rhizosphere (USEPA, 1980). Wetlands that facilitate wastewatertreatment are the adsorption/filtration potential of the aquatic plant roots and stems the ion exchange/adsorption capacityof wetlands’ natural sediments (Reed and Bastian, 1980). Plant roots are found in the anaerobic environment belowthe water surface and it excrete oxygen in a layer which surrounding the plant’s root hairs. This layer, a very large areaand is called the rhizo-sphere and is where much biological and chemical activity take places. Where it provides anenvironment for a wide range of aquatic organisms, where the root systems perform a mesh into the flow that effectivelyadsorbs both dissolved and suspended matter. Also the interface between the aerobic and anaerobic layers allows manycomplex reactions to occur. Also the photosynthesis is important mechanisms of pollutant removal (Abad et al., 1997).In this article, the ten surface flow wetland treatment cells were planted with reed (Phragmites communis). The removal
observed in the reed units at Manzala Constructed Wetland reflects the expanded aerobic zone made possible by theroot penetration of the plants.
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A.M. Hegazy et al. / Water Science 27 (2013) 19–29 27
Molecular techniques, such as real-time PCR has been increasingly used for detection of viruses (Archimbaud et al.,004; Brown et al., 2003; Leitch et al., 2009). Real time RT-PCR technique was used in this article, this method is moreensitive, compared to cell culture, allowing the detection of a small number of copies of the viral genome present inquatic environment, with high specificity and fast turnaround time. Furthermore, enteric viruses have properties thatake them very stable in environment where they may resist infectious after several months (Sair et al., 2002; Griffin
t al., 2003). In addition, some studies showed correlations between the detection of viral RNA by RT-PCR and theetection of viral infectivity (Le Guyader et al., 1994). In the present research, the enteric viruses were determinedualitatively and quantitively using real time RT-PCR and tissue culture teqnique. It was estimated that gene copiesGC) quantity increased with the increase of viral infectivity (VI) of enteroviruses, and that affect water quality. Theegression analysis indicated that VI was good predictor of GC. The sign of the correlation coefficient between VI andC was positive indicating proportional relation.
. Conclusion and recommendations
The results discussed above indicate that there are considerably high concentrations of enteroviruses in the Bahrl-Baqar drain. The concentrations of enteroviruses were found to decrease as drain water pass through sedimenta-
ion basins, and the surface flow systems (vegetated cells). Phytoremediation process operates through vegetation toequester, extract, or degrade viral pollutants in waste water. The article demonstrated this process on constructedetland.Relationship between gene copies and viral infectivity was evaluated and significant correlation was found, then
egression based modeling was developed as an effective tool for quantifying the relationship between the amount ofiral infectivity (VI) and its effect on gene copies (GC) as predictor variable. The results revealed that VI is a goodredictor of GC. Nowadays, should be given special attention for controlling the expansion of viral pollution.
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