Wastewater treatment plants are mainly monitored for quality in terms of their biological oxygen demand and microbiological constituents as stipulated in the specific discharge permit. Wastewater influents and effluents were taken from three WWTPs in South Africa over the summer and winter seasons. Previous toxicity tests such as the Vibrio fischeri bioluminescence assay and the Selenastrum capricornutum algal growth inhibition test have shown that the effluents displayed acute toxicity. To further investigate the quality of the effluent, the genotoxic potential was determined using the SOS Chromosome and UMU Chromosome test. The SOS Chromotest demonstrated induction factor values of above 1.5 for influents during both seasons indicating that the influents were genotoxic (p < 0.05). Effluents discharged during winter and summer also had induction factors greater than 1.5 (p < 0.05). A range of induction factors was detected with the UMU-Chromotest for influents and effluents (1.98 ± 0.38 and 2.40 ± 0.51, respectively). Findings show point sources in the area can lead to influents and effluents that are potentially genotoxic. Designing a monitoring programme that encompasses testing of both the regulatory determinants with additional specialized tests can provide a more holistic view of wastewater quality and the efficiency of WWTP to reduce the discharge of hazards.

  • Wastewater treatment plants are unable to remove genotoxic compounds present in effluents.

  • Wastewater treatment plants are poorly maintained and have failing infrastructure, consequently the discharge of untreated effluents into the environment.

  • Wastewater treatment plant managers should look at alternative methods of testing other than conventional methods in order to provide a holistic water quality.

  • The UMU-C test and the SOS Chromotest are relatively easy assays that can be used to determine.

  • Seasonal differences of the presence of genotoxic compounds in effluents can be seen.

A wide range of pollutants has been identified to be a potential threat to the environment (Bolong et al. 2009). The compounds are often reported to be emerging contaminants that have associated human health effects such as induction of the genotoxicity of cells. Pharmaceutical substances are not properly metabolized by humans and end up in wastewater treatment plants (WWTPs), where they are not adequately treated and are further discharged into receiving waters via wastewater effluents. Compounds such as pharmaceuticals, steroid hormones, and synthesized nanomaterials found in complex wastewater mixtures act as suspected carcinogens, mutagens, and genotoxins to humans and animals (Liu & Wong 2013).

WWTPs were not intended to eliminate a wide variety of contaminants but rather were created to process wastewater from urban areas. In South Africa, most WWTP processes are not sufficient to eliminate other types of micro-pollutants (Mema 2010). Studies also reveal that WWTPs in South Africa are releasing wastewater discharges that do not meet the minimum legal discharge standards (Mema 2010). Various factors are involved in the release of untreated or inadequately treated wastewater. Yearly population increases and residents seeking improved living conditions mean that more freshwater sources are being directed to domestic, industrial, and commercial areas. These sectors then produce larger quantities of wastewater and WWTPs cannot reliably manage the higher inflow loads (Mema 2010; Qadir et al. 2010).

Poor design and poor planning for the expansion of WWTPs also add to problems with inadequately treated wastewater and sewage discharge. Additionally, the absence of financial resources and lack of technical skills make maintenance of WWTPs difficult (Qadir et al. 2010). In turn, poorly maintained WWTPs have malfunctioning equipment which results in inefficient treatment of effluents (Samie et al. 2009; Moran 2017).

With variations in the discharge quality of wastewater effluents from WWTPs, the genotoxic evaluation of effluents becomes more apparent. Assessment of genotoxicity of wastewater influents and effluents can be carried out using various approaches. Genotoxicity assays can consist of bacterial assays such as the Salmonella mutagenicity test (Ames), the SOS Chromotest, and the UMU-Chromotest. These bacterial tests are based on the detection of DNA lesions which can result in DNA mutations (Guan et al. 2017). Induction factors (IFs) or ratios are used as a measure of genotoxicity when water samples are exposed to the SOS Chromotest and UMU-Chromotest. Moreover, the SOS Chromotest and the UMU-Chromotest are complementary, and their application can augment the uncovering of overall genotoxicity in a study (Guan et al. 2017).

WWTP effluents are mainly monitored for wastewater quality in terms of their biological oxygen demand, chemical oxygen demand, total suspended solids, total organic carbon, nitrogen, and phosphorus compounds (Thomas et al. 1997). It is rare that WWTP influents and effluents in South Africa are monitored for their genotoxic compounds. To provide a better understanding of the genotoxic potentials of WWTP influents and effluents, this study focuses on the application of the two bacterial assays, the SOS Chromotest and the UMU-Chromotest. Wastewater samples were collected from three different WWTPs during the winter and summer seasons. The WWTPs are situated along the Rietspruit River and Vaal River. The rivers are sources of water for rural communities, agriculture, mining, wildlife, recreational activities, and aquatic animals. It is thus important to monitor the efficiency of the three WWTPs to remove genotoxic compounds as these compounds may adversely affect the aquatic and human health and act as the main source of contamination.

Study area

In this study, WWTP A and WWTP B are situated in the Rietspruit Catchment area in the Gauteng Province of South Africa in the southern part of Johannesburg. The area surrounding the Rietspruit catchment is densely populated (1,000 people per km2) and consists of both developing and developed areas. Informal settlements, agricultural activities, manufacturing industries, and mining also take place in the surrounding areas. The WWTPs are point source inputs to the Rietspruit River. WWTP C discharges its effluents into the Vaal River. Moreover, the Rietspruit River and Vaal River are used as sources of water for recreational purposes, washing, laundry, fishing, and boating.

Sample collection

Prior to sampling, the bottles were washed with extran (Merck, Germany) and thoroughly rinsed with reverse osmosis water. Subsequently, the bottles were allowed to dry on a drying rack.

Influent and effluent samples were collected at the three different WWTPs once a week over a 4-week period in the winter and summer seasons, respectively. Water samples were collected in pre-cleaned amber glass bottles (1 l) at influent and effluent sampling points at the three WWTPs. Collected water samples were transported immediately to the laboratory in a cooler. Later, the collected water samples were analyzed for the physical parameters of water such as the pH, turbidity, dissolved oxygen (DO) content, temperature, total chlorine, and free chlorine content (results are not shown). Samples were stored at 4 ± 2 °C in a refrigerator. Later, analyses of samples for genotoxicity were performed.

Analyses of influent and effluent samples for genotoxicity using the SOS Chromotest assay

In this study, the SOS Chromotest from Environmental Bio Detection Products Incorporated (EBPI), Ontario, Canada was used to determine the genotoxicity of influents and effluents from the three sewage treatment plants over the 4-week period. The assay was performed according to the manufacturer's instructions. All reagents were supplied with the kit. Briefly, a growth medium was added to the lyophilized bacteria (Escherichia coli PQ37 strain) and incubated for 4–5 h at 37 °C. Thereafter, the turbidity/growth of the bacteria was tested by visual observation. Furthermore, bacterial growth was also determined at 600 nm using a microplate reader (Thermo Electron, Original Multiskan Ex). Thereafter, the bacterial suspension was diluted to give an optical density of 0.05 nm. Influent and effluent water samples were used undiluted in the assay. As a positive control, 4-NitroQuinoline Oxide (4-NQO) was used. Dimethyl sulfoxide (DMSO) in water was used as a negative control. Thereafter, 10 μl of each sample and control was added to a 96-well microtiter plate. Subsequently, 100 μl of the bacterial suspension was added to all the wells of the microtiter plate. The plate was then incubated for 2 h at 37 °C, followed by the addition of 100 μl of the substrate solution (β-galactosidase) to all the wells for 1 h. The colour reaction was stopped by adding 50 μl of the stop solution. Optical densities were then measured at 620 and 405 nm using the microplate reader.

Analyses of influent and effluent samples for genotoxicity using the UMU-Chromotest assay

In this study, the UMU-Chromotest from EBPI, Ontario, Canada was used to determine the genotoxicity of influents and effluents from the three sewage treatment plants over the 4-week period. The assay was performed according to the manufacturer's instructions. All reagents were supplied with the kit. Briefly, a growth medium was added to lyophilized bacteria and incubated for 16–18 h at 37 °C. Thereafter, the turbidity/growth of the bacteria was tested by visual observation. Furthermore, bacterial growth was also determined at 600 nm using a microplate reader (Thermo Electron, Original Multiskan Ex). Thereafter, the bacterial suspension was diluted to give an optical density of 0.05 nm. Influent and effluent water samples were used undiluted in the assay. As a positive control, 4-NQO was used. DMSO in water was used as a negative control. Thereafter, 180 μl of the sample and the control were added to all sample wells of the 96-well microtiter plate. Additionally, 20 μl of 10× TGA-culture media was dispensed to all wells. To the blank wells, approximately 70 μl of TGA-medium was added and mixed. Subsequently, 70 μl of bacteria (inoculum) were added to all the wells. The plate (Plate A) was incubated for 2 h at 37 °C. Toward the end of the incubation of Plate A, Plate B was prepared. Preparation of Plate B included adding 270 μl of the TGA-culture medium to all wells and adjusting the temperature of the plate to 37 °C. After the incubation period of Plate A, 30 μl from each well of Microplate A was added to the corresponding wells of Plate B. The absorbance was measured immediately at 600 nm and subsequently, the plate was incubated for 2 h at 37 °C. After the 2-h incubation period, Plate B was measured again at 600 nm. Plate C was then prepared by dispensing 120 μl of buffer to all wells, placing 30 μl of each well from Plate B to the corresponding wells of Plate C, adjusting the temperature of the plate to 27 °C, and followed by the addition of 30 μl of ortho-Nitrophenol-β-galactosidase (ONPG) solution. Plate C was then incubated for 30 min and thereafter 120 μl of the stop solution was added to all wells. Plate C was read at 420 nm using the microplate reader.

Statistical analyses

Induction factor (SOS chromotest)

To calculate the IF of the influents and the effluents from the three different sewage treatment plants, the following evaluation procedure was used according to Kümmerer et al. 2000. The criteria to consider the genotoxicity of the samples are slightly variable according to different authors (Ruiz & Marzin 1997; Kevekcordes et al. 1999; Jolibois et al. 2003). However, in this study, the influent and effluent samples were classified as not displaying genotoxicity if the IF remained <1.5, and as displaying positive genotoxicity if the IF was >1.5. Ten percent (10%) of DMSO was used as a negative control and 4NQO was used as a positive control.

The β-galactosidase and alkaline phosphatase activities were used to calculate the IF. The IF was calculated by obtaining the ratio of the β-galactosidase activity of the sample at 600 nm and the alkaline phosphatase activity of the sample at 420 nm. This ratio was then divided by the ratio of the activity of the β-galactosidase of the negative control at 600 nm and the activity of the alkaline phosphatase of the negative control at 420 nm (see the following equation).
formula

Growth factor (UMU-C test)

The growth factor for microplate B in the UMU-Chromotest after the 2-h incubation, the β-galactosidase activity (relative units) for microplate C after the half-hour incubation, and the induction ratio are calculated as follows:
formula
where A600S is the absorbance of the sample S at 600 nm; A600B is the absorbance of the blank at 600 nm; A600N is the absorbance of the negative control at 600 nm.

For the corresponding induction ratio to be considered valid, the growth ratio must be greater than 0.5. The expected value is between 0.5 and 1 since the bacteria is expected to grow less rapidly in a genotoxic environment. If the growth factor is below 0.5, then the relationship between bacteria and β-galactosidase activity is irregular and the results are invalid.

β-galactosidase activity (relative units UMU-Chromotest)

The β-galactosidase activity is a measure of how much ONPG was broken down to create a yellow colour in the sample, as compared to the negative control. Since it is expected that the sample will induce a genotoxic response and thus result in more β-galactosidase, it is expected that the negative control will have the lowest reading, while the other readings decrease as the concentration decreases. If the readings at the highest concentration are low, it may indicate acute toxicity, with the readings eventually rising rapidly, and then decreasing with decreasing concentration. To consider a sample genotoxic, the induction ratio must be greater than 1.5 and the growth factor greater than 0.5. Moreover, the whole test is considered valid if the positive controls reach an induction ratio of greater than 2. The β-galactosidase activity (Us) and the induction ratio for the UMU-Chromotest were calculated as follows:
formula
where A420S is the absorbance of the sample at 420 nm; A420B is the absorbance of the blank at 420 nm; A420N is the absorbance of the negative control at 420 nm.
Calculating the induction ratio:
formula

To determine a statistically significant difference in the induction factors between influents and effluents from the three sewage treatment plants, the Student's t-test was done using the statistical package GraphPad Prism Software, California, USA. p < 0.05 was considered statistically significant.

The results of the SOS Chromotest demonstrated IF values of above 1.5 for all three WWTP influents during the winter and summer seasons, indicating that the influents were all genotoxic (Table 1). Furthermore, only WWTP A and WTTP C were able to remove the genotoxic compounds from their influents during the winter season (p < 0.05) (Figure 1). The SOS Chromotest also demonstrated IFs greater than 1.5 for effluents from WWTP A, WWTP B, and WWTP C during the summer season, indicating that the WWTPs were unable to eliminate genotoxic compounds from its effluents (p < 0.05) (Figure 2).
Table 1

Induction factor (IF) ± standard deviation (SD) of influents and effluents from the three wastewater treatment plants using the SOS Chromotest assay during the winter months and summer months

Wastewater treatment plants
WeeksWWTP A (IF ± SD)
WWTP B (IF ± SD)
WWTP C (IF ± SD)
WinterSummerWinterSummerWinterSummer
Influents 1.76 ± 0.07 2.46 ± 0.00 1.60 ± 0.05 2.52 ± 0.05 1.69 ± 0.07 2.53 ± 0.13 
1.46 ± 0.03 1.54 ± 1.16 1.53 ± 0.02 2.32 ± 0.04 1.67 ± 0.07 2.96 ± 1.05 
1.96 ± 0.15 2.26 ± 0.05 1.49 ± 0.03 2.16 ± 0.04 1.79 ± 0.09 2.31 ± 0.15 
1.96 ± 0.02 2.08 ± 0.01 1.77 ± 0.06 2.09 ± 0.02 1.98 ± 0.04 2.31 ± 0.20 
Average  1.79 ± 0.07 2.09 ± 0.39 1.60 ± 0.04 2.27 ± 0.19 1.78 ± 0.07 2.53 ± 0.30 
Effluents 1.18 ± 0.02 1.95 ± 0.01 1.40 ± 0.05 2.21 ± 0.03 1.13 ± 0.05 2.12 ± 0.05 
1.18 ± 0.00 1.97 ± 0.04 1.43 ± 0.03 2.17 ± 0.03 1.26 ± 0.06 2.14 ± 0.05 
1.17 ± 0.02 2.00 ± 0.04 1.42 ± 0.05 2.19 ± 0.04 1.26 ± 0.04 2.18 ± 0.08 
1.14 ± 0.04 1.96 ± 0.08 2.33 ± 1.21 2.24 ± 0.09 1.27 ± 0.03 1.86 ± 0.23 
Average  1.17 ± 0.02 1.97 ± 0.02 1.65 ± 0.34 2.20 ± 0.02 1.27 ± 0.05 2.07 ± 0.14 
Positive Control  7.11 ± 0.13 12.02 ± 0.55     
Wastewater treatment plants
WeeksWWTP A (IF ± SD)
WWTP B (IF ± SD)
WWTP C (IF ± SD)
WinterSummerWinterSummerWinterSummer
Influents 1.76 ± 0.07 2.46 ± 0.00 1.60 ± 0.05 2.52 ± 0.05 1.69 ± 0.07 2.53 ± 0.13 
1.46 ± 0.03 1.54 ± 1.16 1.53 ± 0.02 2.32 ± 0.04 1.67 ± 0.07 2.96 ± 1.05 
1.96 ± 0.15 2.26 ± 0.05 1.49 ± 0.03 2.16 ± 0.04 1.79 ± 0.09 2.31 ± 0.15 
1.96 ± 0.02 2.08 ± 0.01 1.77 ± 0.06 2.09 ± 0.02 1.98 ± 0.04 2.31 ± 0.20 
Average  1.79 ± 0.07 2.09 ± 0.39 1.60 ± 0.04 2.27 ± 0.19 1.78 ± 0.07 2.53 ± 0.30 
Effluents 1.18 ± 0.02 1.95 ± 0.01 1.40 ± 0.05 2.21 ± 0.03 1.13 ± 0.05 2.12 ± 0.05 
1.18 ± 0.00 1.97 ± 0.04 1.43 ± 0.03 2.17 ± 0.03 1.26 ± 0.06 2.14 ± 0.05 
1.17 ± 0.02 2.00 ± 0.04 1.42 ± 0.05 2.19 ± 0.04 1.26 ± 0.04 2.18 ± 0.08 
1.14 ± 0.04 1.96 ± 0.08 2.33 ± 1.21 2.24 ± 0.09 1.27 ± 0.03 1.86 ± 0.23 
Average  1.17 ± 0.02 1.97 ± 0.02 1.65 ± 0.34 2.20 ± 0.02 1.27 ± 0.05 2.07 ± 0.14 
Positive Control  7.11 ± 0.13 12.02 ± 0.55     

The IF in italic indicates above the limit of 1.5 thereby indicating genotoxicity.

Figure 1

IFs of the (a) WWTP A, (b) WWTP B, and (c) WWTP C over the 4-week sampling period using the SOS Chromotest assay during the winter months. The line in red indicates the IF equal to 1.5 indicating genotoxicity of samples.

Figure 1

IFs of the (a) WWTP A, (b) WWTP B, and (c) WWTP C over the 4-week sampling period using the SOS Chromotest assay during the winter months. The line in red indicates the IF equal to 1.5 indicating genotoxicity of samples.

Close modal
Figure 2

IFs of the (a) WWTP A, (b) WWTP B, and (c) WWTP C over the 4-week sampling period using the SOS Chromotest assay during the summer months. The line in red indicates the IF equal to 1.5 indicating genotoxicity of samples.

Figure 2

IFs of the (a) WWTP A, (b) WWTP B, and (c) WWTP C over the 4-week sampling period using the SOS Chromotest assay during the summer months. The line in red indicates the IF equal to 1.5 indicating genotoxicity of samples.

Close modal
The results of the UMU-Chromotest were more variable with only the influents from WWTP A and WWTP B during the summer season being genotoxic (3.68 ± 3.30 and 2.42 ± 0.63, respectively) (Table 2). Additionally, with the UMU-Chromotest, WWTP B influents during the winter season were also genotoxic (2.43 ± 0.63) (Figure 3).
Table 2

Induction factor (IF) ± standard deviation (SD) of influents and effluents from the three wastewater treatment plants, using the UMU-Chromotest during the winter and summer months

Wastewater treatment plants
WeeksWWTP A (IF ± SD)
WWTP B (IF ± SD)
WWTP C (IF ± SD)
WinterSummerWinterSummerWinterSummer
Influents 1.51 ± 0.20 5.99 ± 3.59 1.08 ± 0.12 3.20 ± 0.84 1.06 ± 0.26 1.72 ± 0.10 
1.01 ± 0.02 1.98 ± 0.38 2.43 ± 2.57 2.40 ± 0.51 1.04 ± 0.00 1.32 ± 0.10 
1.30 ± 0.08 8.40 ± 7.43 5.31 ± 7.42 2.41 ± 0.65 0.96 ± 0.06 1.31 ± 0.26 
1.51 ± 0.13 1.51 ± 0.14 0.92 ± 0.43 1.65 ± 0.27 1.22 ± 0.06 1.08 ± 0.04 
Average  1.35 ± 0.10 3.68 ± 3.30 2.43 ± 2.63 2.42 ± 0.63 1.07 ± 0.10 1.36 ± 0.27 
Effluents 1.17 ± 0.67 5.03 ± 2.14 1.26 ± 0.05 6.39 ± 3.05 0.90 ± 0.15 1.20 ± 0.04 
0.04 ± 1.28 2.67 ± 0.86 1.26 ± 0.17 5.14 ± 1.81 0.93 ± 0.25 1.07 ± 0.15 
0.88 ± 0.04 3.90 ± 1.47 1.17 ± 0.19 3.04 ± 1.18 0.79 ± 0.06 1.10 ± 0.25 
0.79 ± 0.07 1.68 ± 0.35 1.38 ± 0.10 3.85 ± 2.38 1.05 ± 0.20 0.76 ± 0.50 
Average  0.72 ± 0.52 3.19 ± 1.46 1.27 ± 0.13 4.61 ± 1.47 0.92 ± 0.16 1.03 ± 0.19 
Positive Control  29.31 ± 0.4 21.28 ± 0.48     
Wastewater treatment plants
WeeksWWTP A (IF ± SD)
WWTP B (IF ± SD)
WWTP C (IF ± SD)
WinterSummerWinterSummerWinterSummer
Influents 1.51 ± 0.20 5.99 ± 3.59 1.08 ± 0.12 3.20 ± 0.84 1.06 ± 0.26 1.72 ± 0.10 
1.01 ± 0.02 1.98 ± 0.38 2.43 ± 2.57 2.40 ± 0.51 1.04 ± 0.00 1.32 ± 0.10 
1.30 ± 0.08 8.40 ± 7.43 5.31 ± 7.42 2.41 ± 0.65 0.96 ± 0.06 1.31 ± 0.26 
1.51 ± 0.13 1.51 ± 0.14 0.92 ± 0.43 1.65 ± 0.27 1.22 ± 0.06 1.08 ± 0.04 
Average  1.35 ± 0.10 3.68 ± 3.30 2.43 ± 2.63 2.42 ± 0.63 1.07 ± 0.10 1.36 ± 0.27 
Effluents 1.17 ± 0.67 5.03 ± 2.14 1.26 ± 0.05 6.39 ± 3.05 0.90 ± 0.15 1.20 ± 0.04 
0.04 ± 1.28 2.67 ± 0.86 1.26 ± 0.17 5.14 ± 1.81 0.93 ± 0.25 1.07 ± 0.15 
0.88 ± 0.04 3.90 ± 1.47 1.17 ± 0.19 3.04 ± 1.18 0.79 ± 0.06 1.10 ± 0.25 
0.79 ± 0.07 1.68 ± 0.35 1.38 ± 0.10 3.85 ± 2.38 1.05 ± 0.20 0.76 ± 0.50 
Average  0.72 ± 0.52 3.19 ± 1.46 1.27 ± 0.13 4.61 ± 1.47 0.92 ± 0.16 1.03 ± 0.19 
Positive Control  29.31 ± 0.4 21.28 ± 0.48     

The IF in italic indicates above the limit of 1.5 thereby indicating genotoxicity.

Figure 3

IFs of the (a) WWTP A, (b) WWTP B, and (c) WWTP C over the 4-week sampling period using the UMU-Chromotest assay during the winter months. The line in red indicates the IF equal to 1.5 indicating genotoxicity of samples.

Figure 3

IFs of the (a) WWTP A, (b) WWTP B, and (c) WWTP C over the 4-week sampling period using the UMU-Chromotest assay during the winter months. The line in red indicates the IF equal to 1.5 indicating genotoxicity of samples.

Close modal
Positive genotoxicity results were also demonstrated with the UMU-Chromotest with IFs greater than 1.5 for effluents from WWTP A and WWTP B during the summer season (Table 2). Moreover, the results show that WWTP A and WWTP B were unable to remove the genotoxic compounds from the effluents during the summer season (p < 0.05) (Figure 4).
Figure 4

IFs of the (a) WWTP A, (b) WWTP B, and (c) WWTP C over the 4-week sampling period using the UMU-Chromotest assay during the summer months. The line in red indicates the IF equal to 1.5 indicating genotoxicity of samples.

Figure 4

IFs of the (a) WWTP A, (b) WWTP B, and (c) WWTP C over the 4-week sampling period using the UMU-Chromotest assay during the summer months. The line in red indicates the IF equal to 1.5 indicating genotoxicity of samples.

Close modal

WWTPs discharge treated wastewater into rivers, lakes, and oceans. However, untreated wastewater also enters these water sources (Williams et al. 2019). Untreated and treated wastewater often contain contaminants such as pharmaceuticals, hormones, personal care products (PCPs), and industrial chemicals (Williams et al. 2019). Consequently, there is a concern that these contaminants can adversely affect organisms as well as humans (Grisolia et al. 2005). Many compounds that are known and unknown have in the recent past been identified as genotoxic in surface waters (Ohe et al. 2004). Moreover, the fluoroquinolone antibiotics in water have been found as DNA-damaging agents and as a positive genotoxin with the SOS bioassay (Hartmann et al. 1998). Furthermore, it has been demonstrated that antibiotic resistance is exacerbated by antibiotic discharge into the environment. Additionally, it is evident that the presence of pathogens in wastewater discharge has the potential to cause infectious outbreaks that worsen the pollution outcome. Industrial effluents contain pharmaceuticals and chemicals such as metals, salts, residual drugs and active residues of PCPs which have been found ubiquitously in wastewater discharges (Iloms et al. 2020). Industrial effluents containing aluminium, copper, and zinc contaminants are likely to result in cancer and contaminants such as lead causes genotoxic effects such as chromosome aberrations and DNA synthesis inhibition (Ibrahem et al. 2020). In both low-income countries and developed countries, wastewater discharges into the environment have resulted in chemical and pharmaceutical pollution of the soil, surface water, and groundwater with the potential of entering higher invertebrates as a result of food web transfer (Koopaei & Abdollahi 2017). Furthermore, musk compounds have been shown to persist in the environment because of the slow degradation of their particles, resulting in bioaccumulation in fatty tissues of aquatic wildlife (Bridges 2002). Similarly, oestrogen and oestrone at contaminant levels have been connected to thyroid issues, weakening of animal and bird immune systems, breast cancer in women and prostate cancer in men (Yazdan et al. 2022). Furthermore, the pharmaceutical carbamazepine has been found in the urine of humans after consuming vegetables that have been irrigated by reclaimed wastewater, albeit at low levels that may not have clinical effects, the study showed that xenobiotics can be transferred from reclaimed wastewater irrigated produce (Paltiel et al. 2016).

The findings of this study show that influents from all three WWTPs were positive for genotoxicity. WWTP A and WWTP B mainly receive influents from domestic point sources. Domestic wastewater comprises various substances such as intestinal bacteria, detergents, phosphates, surfactants, and nitrates. Laundry detergents or surfactants are known to persist in the environment and have resulted in human and environmental effects, such as reducing the resistance of aquatic biota to environmental stress (Badmus et al. 2021). On the other hand, WWTP C receives influents from both domestic and industrial sources. Moreover, 10% of the influent received by WWTP C are from abattoirs within the area. Abattoirs produce a large amount of wastewater with a high pollutant load. The abattoir effluents may contain partially digested feed (paunch contents), manure, fats, oils, greases, and uncollected blood (Mcgabe et al. 2013). Abattoir wastewater also contains high organic loads containing nitrogen, phosphorus, iron, and sulphur from chemicals used for cleaning. Additionally, abattoir effluents may contain compounds such as veterinary antibiotics which have been shown to be excreted after administration and reach municipal wastewater or sewage. All these compounds or substances may have contributed to the genotoxicity seen in the influents of WWTP C. Similarly, findings have shown that abattoir effluents had the presence of clastogens and cytotoxic compounds that resulted in genomic instability in aquatic biota (Alimba et al. 2015). The biodegradability of these compounds does not occur in sewage treatment plants and is often positively detected for its genotoxicity potential (Kümmerer et al. 2000).

The WWTPs used in this study use conventional treatment processes to treat wastewater influents. The design of a WWTP plays a major role in the elimination of these genotoxic compounds. Only WWTP A and WWTP C were able to remove genotoxic compounds during winter from influents as demonstrated with the SOS Chromotest. These results are consistent with results found by Hendricks & Pool (2012), in which influents from WWTPs were found to be genotoxic and subsequently genotoxins were removed by the treatment processes at the plants. However, at present, these WWTPs are not designed to quantitatively remove other types of pollutants such as pharmaceuticals and other genotoxic compounds. The WWTPs in the study do not have advanced treatment options to remove genotoxic compounds. Advanced treatment options such as activated carbon treatment and ozonation greatly reduced in vivo toxicity at various endpoints (Völker et al. 2019). Therefore, considering an upgrade to existing WWTPs with additional treatment options should result in further detoxification and potential compliance with environmental quality standards (Völker et al. 2019). Furthermore, treatment efficiency varies for WWTPs as it is dependent on the type of wastewater treatment processes that are present in the WWTP. It has been shown that WWTPs that have activated sludge processes were able to biodegrade antibiotics more effectively than those WWTPs that did not employ the use of biological degradation (Li & Zhang 2010; Hazra & Durso 2022). Likewise, WWTPs only operate at fixed DO concentrations in their aeration tanks of 2.0 mg/l of DO. Optimizing this process to the influent load fluctuations can result in energy savings and prevent wastage with the further potential to remove unwanted compounds and thereby enhance environmental protection (Qambar & Khalidy 2022).

The capacity of WWTPs also plays a role in the elimination of genotoxic compounds. With the increase in population yearly, WWTPs must treat several added megaliters of wastewater. The load, therefore, for WWTP B may have been markedly more than what it was designed for (36 Ml/day), consequently, inadequate elimination of genotoxic compounds is seen in effluents. Furthermore, the impact of poorly maintained WWTPs may have a negative effect on the surface water in South Africa with an increase in water pollution that may affect several communities (Mema 2010). Further exacerbating the situation are the lack of properly skilled and trained personnel, malfunctioning equipment, lack of finances to operate WWTPs, and poor planning and design for the expansion of WWTPs (Mema 2010). Previous studies done on WWTP in South Africa have shown that WWTPs are unable to manage the growing load of wastewater produced and often discharge untreated wastewater into the environment (Teklehaimanot et al. 2015; Phungela et al. 2021). Untreated wastewater discharged into rivers has a major impact on the economy, as the river water cannot be used for agricultural and industrial purposes. This water also poses a threat to humans who use river water as their only means of drinking water consumption (Phungela et al. 2021). Limited studies have been carried out on the genotoxicity of wastewater treatment effluents in South Africa and, therefore, the full extent of genotoxicity of effluents throughout the country is not presently known. To manage the capacity issue of WWTP, the only premise is to build more WWTPs (Koul et al. 2022). However, proper planning of these plants must be undertaken with the foresight of the growing and changing needs of water quality in South Africa. Planning and design considerations for advanced treatment options to eliminate genotoxic compounds must be evident.

Moreover, the treatment efficiency of WWTPs is also dependent on several other factors; for instance, the physico-chemical properties of the compounds, the treatment processes employed at the plant, the age of the activated sludge, the hydraulic retention time and environmental conditions such as temperature and light intensity (Andreozzi et al. 2003). Additionally, Zorita et al. (2009) have shown that diclofenac, a non-steroidal inflammatory drug, used to treat inflammation has been found in higher concentrations in effluents as compared to influents. Diclofenac has been demonstrated to result in genotoxic DNA damage and mutagenesis in isogenic mutant cell lines. Simultaneously, studies have shown that treatment plants can introduce mutagens (Mathur et al. 2007).

In this study, results showed that during the summer months, higher induction ratios (genotoxicity levels) were observed in influents and effluents at all three WWTPs. It is not always possible to compare seasonality differences since it may be dependent on the consumption and discharge of compounds. For instance, seasonal differences were observed for illicit drugs in Korea during the holiday season where more festivals and parties were prevalent (Kim et al. 2017). Moreover, higher levels of ibuprofen and diclofenac during winter were found in wastewater which could be related to its consumption pattern when more of the population are sick. On the other hand, during summer, higher concentrations of salicylic acid were found, indicative of an increase in discharge of these active reagents in shampoos and PCPs (Munoz et al. 2014).

When evaluating the genotoxicity results obtained by using the UMU-Chromotest assay as compared to genotoxicity results obtained by the SOS Chromotest assay results are contradictory. WWTP C showed genotoxic influents and effluents during the summer months with the SOS Chromotest but not with the UMU-Chromotest. The differences between these two tests are negligible based more on the type of bacterial strain that is genetically modified. Furthermore, the UMU-Chromotest assay uses a Salmonella typhimurium bacterial strain whereas the SOS Chromotest assays are composed of an E. coli K12 bacterial strain. Indeed, some studies have noted that the UMU-Chromotest assay was more sensitive than the SOS Chromotest due to the detection of lower genotoxic responses, which may have occurred due to the greater permeability of the genotoxins to the Salmonella tester strain wall. Additionally, the UMU-Chromotest reporter gene is placed on a multicopy plasmid while in the SOS Chromotest, it is placed on a single bacterial chromosome (De Maagd 2000). However, caution should be taken when comparing results as very few studies compare the differences in sensitivity of these two tests.

WWTPs in South Africa are often poorly maintained due to lack of finances, which in turn lead to malfunctioning of equipments, and as a result inadequately treated effluents are released into the environment. Additionally, due to the yearly increase in the population and higher inflow loads to WWTPs, plants are unable to treat wastewater effectively. The SOS Chromotest and the UMU-Chromotest indicated that influents and effluents from all the WWTPs induced genotoxicity. It is difficult to determine the exact compounds that induced genotoxicity as influents and effluents are complex mixtures and compounds may act synergistically or alone to produce a response. The SOS Chromotest and the UMU-Chromotest are complementary and when obtaining a positive result with the SOS Chromotest, it may be ideal to confirm results with a different test such as the UMU-Chromotest assay to eliminate false-positives. The absence of genotoxicity is potentially assay-dependent and its ability to detect certain chemicals or molecules by the assay plays a vital role in detection. On the other hand, the genotoxicity of samples can be attributed to the introduction of mutagens or genotoxic compounds during the treatment process.

Although seasonal differences can be seen, it is unclear whether the differences are due to temperature differences, compound use, or discharge by the population. Further studies should be undertaken to elucidate seasonality differences.

On the whole, these findings highlight that sewage treatment plants are capable of treating wastewater and discharging water with an adequate quality, and it may also be possible to treat other additional micro-pollutants such as pharmaceuticals, hormones, and PCPs.

The authors wish to thank Rand Water for its financial support.

R.H. provided the concept and designed the work; collected; analyzed; and interpreted the data; and drafted the article. R.H. and H.H.d.P. critically revised the article. H.H.d.P. approved the final paper.

All relevant data are included in the paper or its Supplementary Information.

The authors declare there is no conflict.

Alimba
C.
,
Ajayi
E.
,
Hassan
T.
,
Sowunmi
A.
&
Bakare
A.
2015
Cytogenotoxicity of Abbattoir Effluent in Clarias gariepinus (Burchell, 1822) using Micronucleus test
.
Chinese Journal of Biology
2015, 624524
.
Badmus
S.
,
Amusa
H.
,
Oyehan
T.
&
Saleh
T.
2021
Environmental risks and toxicity of surfactants: Overview of analysis, assessment, and remediation techniques
.
Environmental Science and Pollution
28
,
62085
62104
.
Bridges
B.
2002
Fragrance: Emerging health and environmental concerns
.
Flavour Fragrance Journal
17
,
361
371
.
De Maagd
P.
2000
Genotoxicity Tests for Effluents. Accepted Article
.
Grisolia
C.
,
de Oliveira
A.
,
Bonfirm
H.
&
Klautau-Guimarães
M.
2005
Genotoxicity evaluation of domestic sewage in a municipal wastewater treatment plant
.
Genetics and Molecular Biology
28
,
2
.
Guan
Y.
,
Wang
X.
,
Wong
M.
,
Sun
G.
,
An
T.
&
Zhang
G.
2017
Evaluation of genotoxic and mutagenic activity of organic extracts from drinking water sources
.
PLUS one
12
(
1
),
e017454
.
Hartmann
A.
,
Alder
A.
,
Koller
T.
&
Widmer
R.
1998
Identification of fluoroquinolone antibiotics as the main source of UMU-C genotoxicity in native hospital wastewater
.
Environmental Toxic Chemistry
17
,
377
382
.
Ibrahem
S.
,
Hassan
M.
,
Ibraheem
Q.
&
Arif
K.
2020
Genotoxic effect of lead and cadmium on workers at wastewater plant in Iraq
.
Journal of Environmental Research and Public Health
1
,
1
9
.
Iloms
E.
,
Ololade
O.
,
Ogola
H.
&
Selvarajan
R.
2020
Investigating industrial effluent impact on municipal wastewater treatment plant in Vaal, South Africa
.
International Journal of Environmental Research and Public Health
17
(
3
),
1096
.
Kevekordes
S.
,
Mersch-Sundermann
V.
,
Burghas
C.
,
Spielberger
J.
,
Schmeiser
H.
,
Arit
V.
&
Dunkelberg
H.
1999
SOS induction of naturally occurring substances in Escherichia coli. (SOS Chromotest)
.
Mutation Research
445
(
1
),
81
91
.
Koopaei
N.
&
Abdollahi
M.
2017
Health risks associated with the pharmaceuticals in wastewater
.
DARU Journal of Pharmaceutical Sciences
25
,
9
.
Koul
B.
,
Yadav
D.
,
Singh
S.
,
Kumar
M.
&
Song
M.
2022
Insights into the domestic wastewater treatment (DWWT) regimes: A review
.
Water
14
,
3542
.
Li
B.
&
Zhang
T.
2010
Biodegradation and adsorption of antibiotics in the activated sludge process
.
Environmental Science and Technology
44
,
3468
3473
.
Mathur
N.
,
Bhatnagar
P.
,
Mohan
K.
,
Bakre
P.
,
Nagar
P.
&
Bijarna
M.
2007
Mutagenicity evaluation of industrial sludge from common effluent treatment plant
.
Chemosphere
67
,
1229
1235
.
Mcgabe
B.
,
Hamawand
I.
&
Baille
C.
2013
Investigating wastewater modelling as a tool to predict decomposition and biogas yield of abattoir effluent
.
Journal of Environmental Chemical Engineering
1
,
1375
1379
.
Mema
V.
2010
Impact of poorly maintained wastewater sewage treatment plants-lessons from South Africa
.
Wastewater Management
12
(
3
),
60
65
.
Moran
S.
2017
Troubleshooting Wastewater Treatment Plants
.
American Institute of Chemical Engineers (AiChE)
.
Available from: http. Aiche.org/cep.
Ohe
T.
,
Watanabe
T.
&
Wakabayashi
K.
2004
Mutagens in surface waters: A review
.
Mutation Research
567
,
109
149
.
Paltiel
O.
,
Fedorova
G.
,
Tadmor
G.
,
Kleinstein
G.
,
Maor
Y.
&
Cheftz
B.
2016
Human exposure to wastewater-derived pharmaceuticals in fresh produce: A Radonmized controlled trial focusing on carbamazepine
.
Environmental Science and Technology
50
(
8
),
4476
7782
.
Phungela
T.
,
Gqomfa
B.
,
Maphanga
T.
&
Shale
K.
2021
The impact of wastewater treatment effluent on water resources: A South African perspective
.
Water Law
27
,
140
148
.
Qadir
M.
,
Wichelns
D.
,
Raschid-Sally
L.
,
McCornick
P.
,
Drechsel
P.
,
Bahri
A.
&
Minhas
P.
2010
The challenges of wastewater irrigation in developing countries
.
Agricultural Water Management
97
,
561
568
.
Samie
A.
,
Obi
C.
,
Igumbor
J.
&
Momba
M.
2009
Focus on 14 sewage treatment plants in the Mpumalanga Province, South Africa in order to gauge the efficiency of wastewater treatment
.
African Journal of Biotechnology
8
(
14
),
3276
3285
.
Teklehaimanot
G.
,
Kamika
I.
,
Coetzee
A.
&
Momba
M.
2015
Population growth and its impact on the design capacity and performance of the wastewater treatment plants in Sedibeng and Soshanguve, South Africa
.
Environmental Management
.
doi:10.1007/s00267-015-0564-3
.
Thomas
O.
,
Theraulaz
F.
,
Cerda
V.
,
Constant
D.
&
Quevauviller
P.
1997
Wastewater quality monitoring
.
Trends in Analytical Chemistry
16
(
7
),
419
424
.
Völker
J.
,
Stapf
M.
,
Miehe
U.
&
Wagner
M.
2019
Systematic review of toxicity removal by advanced wastewater treatment technologies via ozonation and activated carbon
.
Environmental Science and Technology
53
,
7215
7233
.
Williams
M.
,
Kookana
R.
,
Mehta
A.
,
Yadav
S.
,
Taylor
B.
&
Maheswari
B.
2019
Emerging contaminants in a river reeivingreceiving untreated wastewater from an Indian urban centre
.
Science of the Total Environment
647
,
1256
1265
.
Zorita
S.
,
Martensson
L.
&
Mathiasson
L.
2009
Occurrence and removal of pharmaceuticals in a municipal sewage treatment system in the south of Sweden
.
Science of the Total Environment
407
,
2760
2770
.
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