Screening of municipal effluents with the peroxidase toxicity assay

Screening of municipal effluents with the peroxidase toxicity assay | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Screening of municipal effluents with the peroxidase toxicity assay Francois Gagné, Chantale André, Shirley -Ann Smyth This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4547007/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The peroxidase (Per) reaction is a quick and inexpensive biosensor for the screening of environmental contaminants. The purpose of this study was to screen various municipal wastewaters before and after 7 different types of treatment processes. Wastewater samples before (influents) and after the following treatments (effluent) were tested using the Per activity test: advanced biofiltration, biofiltration, aerated lagoons, secondary aeration sludge, trickling filter, secondary membrane filtration, and primary. The influents and effluents were collected for 3 days composites and concentrated to 500 X on a reverse-phase (C18) extraction cartridge. The ethanol extracts were examined for dissolved organic carbon, plastic-like materials, polyaromatic hydrocarbons and polystyrene nanoplastics. The samples were then tested using the Per reaction alone and in the presence of DNA to detect DNA binding agents. The result show that population size tended to increase Per activity and 60% of the effluents decreased Per activity leading to H 2 O 2 persistence. More advanced treatments (biofiltration, membrane biofiltration, secondary aeration) produced stronger changes from the corresponding untreated influents. The addition of DNA during the Per reaction revealed that population size had no influence and that significant changes occurred in 60% of treated effluents suggesting release of genotoxic compounds in the aquatic environment by most treated wastewaters. The toxic implications of these results to aquatic organisms are discussed. peroxidase DNA protection wastewater quality dissolved organic matter plastics Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Peroxidases (Per) are hemoproteins involved in the oxidation reactions with hydrogen peroxide (H 2 O 2 ). Per belong to a large family of oxido-reductases and found in living organisms. The size of these heme containing proteins ranges between 35-100 kDalton (O’ Brien, 2000). Although Per could use a large variety of electron donor compounds, some use specific ones such as glutathione. Although Per have a major protection role against reactive oxygen species such as H 2 O 2 , they can lead to deleterious reactions involving the oxidation of endogenous substrates and xenobiotics leading to tissue damage, lipoprotein oxidation and carcinogenesis. They are considered antioxidant enzymes to keep H 2 O 2 at safe levels to protect cells and tissues. Indeed, the estimated toxicity of H 2 O 2 is 0.1 µg/L after 96 h at 17 o C in trout (Rach et al., 1997). Given that between 1-2% of consumed O 2 during respiration transforms into oxygen radicals (*OH) and to H 2 O 2 by superoxide dismutase (Cadenas and Davies, 2000), the levels of H 2 O 2 needs to be tightly regulated by antioxidant mechanisms involving catalase and Per. On the other hand, the long-term of activity of Per could lead to the accumulation of oxidized compounds (from electron donors) such as oxidized vitamins/cofactors and xenobiotics leading to DNA adduct and DNA (8-oxoguanine) oxidation (Cavalieri et al., 1983). Indeed, reactive species generated by mitochondria or other sites in the cytoplasm, cause damage to mitochondria and organelles and initiate degradative processes involved in aging. Oxidative stress can modify lipids, DNA, RNA and proteins/enzymes, which require them to be removed by DNA repair enzymes, protein (protein degradation/turnover) and (damaged) unsaturated lipids (hydrolysis). Hence, the Per enzymes are two edged swords i.e., they can removes toxic levels of H 2 O 2 at the expenses of electron donor products in cells (vitamins, NADH, guanosine, glutathione, amino acids etc.) leading to the accumulation of oxidatively damaged products on the long-term. In fish collected at rivers polluted by heavy metal, the fish accumulated zinc, chromium, nickel, cobalt and copper with a concomitant rise in Per activity in the liver, gills and muscles (Javed et al., 2020). This suggests that these metals lead to H 2 O 2 perhaps at the expense of antioxidant levels (i.e., reduced antoxidant capacity) The Per assay was used to screen various industrial effluents and revealed inhibition in the reaction rates (Gagné and Blaise, 1997). It was noteworthy that the Per inhibition potential was significantly associated to trout mortality where the toxic effluents produced the strongest inhibition at low effluent concentration. An interesting variation of this assay was to include DNA during the Per assay to detect interactions between DNA and the effluents. While DNA alone did not affect Per activity, the addition of DNA with the effluents reversed the inhibition suggesting interactions with the contaminants. Effluents showing DNA interactions with the Per reaction were genotoxic 70% of the cases using an SOS DNA repair test in bacteria (Gagné and Blaise, 1997). A luminol-based Per reaction was also proposed as a mean for water quality assessments with single substances and pesticide formulations (Ilyina et al., 2000). Preincubation of Per with herbicides, detergents/surfactant, phenol, metals (Hg, Co, Ni) had an inhibitory effect of Per activity. However, some other compounds could stimulate Per activity at low concentrations (an hormetic response), which was followed by decreased activity. Some insecticide formulation revealed a sustained increase in Per activity suggesting perhaps that other compounds present in these formulations (stabilizers, antioxidants etc) could increase H 2 O 2 degradation rates. The Per reaction offers a very rapid and efficient means to screen for potentially toxic mixtures such as industrial and municipal wastewaters. In the context of reducing the sacrifice of fish and other vertebrates in toxicity tests, new alternative methods (NAMs) are urgently needed for toxicity screening purposes and the Per assay was seemingly predictive of trout mortality with very few or no false negatives. The purpose of this study was therefore to use the Per and DNA-protection variation assay as a screening tool to evaluate the impacts of wastewaters on water quality and potential toxicity from 8 townships in Canada. Municipal wastewaters before (influent) and after 7 different treatment processes (effluents) were concentrated on a C18 reverse phase columns (ethanol elution) for the Per assay. An attempt was made to understand the contribution of population size and the performance of various treatments processes to alleviate changes in Per assay and the DNA protection effects. Methods Sample preparation All reagents were purchased from Sigma Chemical Company (On, Canada) at the highest purity available. Horseradish peroxidase and serum bovine albumin were prepared at 1 mg/mL in phosphate buffered saline (PBS: 140 mM NaCl, 5 mM KH 2 PO 4 and 1 mM NaHCO 3 , pH 7.5) and kept for non-longer than one week at 4 o C in the dark. For DNA, 10 mg of salmon sperm DNA was dissolved in 10 mL of 0.25 X PBS, heated at 70 o C for 10 min and stored at 4 o C. The reagent dihydrofluorescein diacetate (DHFDA) was dissolved at 1 mg/mL in 10 % ethanol. Hydrogen peroxide solutions were prepared at 1% concentration and stored at 4 o C for non-longer than one week. The untreated (influent) and treated effluents from 8 townships of various treatment process and sizes in Canada were 24 h composites and collected for 3 days (Table 1). The wastewaters (1 L) were transported back to the laboratory and stored at 4 o C in the dark. The influent and corresponding effluent samples were filtered on 0.45 µm pore cellulose filter and 500 mL was passed through a reverse phase C18 cartridge (500 mg; Sulpeco). After washing with MilliQ water (10 ml), the material was eluted with 5 mL ethanol and concentrated to 1 mL under nitrogen stream (500 X concentrate). The ethanol samples were stored at -20 o C until analysis. Wastewater extract characteristics The dissolved organic matter (DOC) in the ethanol extract was determined by the spectrometric methodology (Brandstetter et al., 1996). The DOC levels were estimated based on the following relationship: DOC (mg/L) = 0.45A +1 for organic-rich surface waters. The levels of plastic-like substances associated to the organic matter were determined by the copper fluorescence quenching methodology (Lee et al., 2021). The decreased in fluorescence for humic/fulvic acids (265 nm excitation/463 nm emission), polypropylene-derived materials (250 nm excitation/324 nm emission) and polyvinyl chloride /polystyrene-derived materials (295 nm excitation/411 nm emission) were determined before and after the addition of one volume of 100 µM of CuCl 2 . The difference between fluorescence without Cu – fluorescence with Cu was calculated and standard solutions of polystyrene (20 nm diameter) and polypropylene (100 nm diameter) were used for calibration. The data were then normalized to the DOC in the samples. The levels of light, medium and heavy polyaromatic hydrocarbons were determined in the ethanol extracts using fixed wavelength fluorometry (Aas et al., 1995). Briefly, 100 µL of ethanol extracts were placed in dark 96-wells microplate and fluorescence measured at 290 nm excitation/340 nm emission (light PAhs: naphthalene), 325 nm excitation/370 nm emission (medium Pahs: pyrene) and 385 nm excitation /440 nm emission (heavy Pahs: benzo(a)pyrene) using a fluorescence microplate reader (Neo-2 Synergy, Biotek Instruments, USA). Standard solutions of the Pahs were used for calibration. Recovery of each Pahs size class were between 80-95% in the C18 extraction columns. The levels of polystyrene nanoplastics (PsNPs) were determined using a molecular rotor probe 9(dicyanovinyl)-julolidine as described (Gagne, 2019). Briefly, 10 µL if effluent extract were mixed with 190 uL of 10 uM of the probe (diluted in MilliQ water) and fluorescence were taken at 450 nm excitation and 620 nm emission (Neo-2, Synergy-4, Biotech Instruments, USA). Standard solutions of polystyrene nanoparticles (50 nm Polyscience, USA) were used for calibration. Solvatochromatic analysis of the ethanol extracts to detect plastic-like substances using the Nile red methodology were also performed (Gagne et al., 2019). Briefly, 25 µL of the ethanol extracts were mixed with 225 µL of 50 uM Nile red (in PBS buffer) and the emission spectra were recorded between 520-700 nm at 485 nm excitation. The first derivative of the spectra revealed that PsNPs emitted at 600-620 nm and this signal was taken as a measured of plastic-like materials. The data were expressed as relative fluorescence units (600 nm) corrected for the organic matter contents. The levels of melamine were determined using a nano-gold plasmonic sensor (Gao et al., 2018). Briefly, citrate coated nano-gold (10 nm diameter, NanoComposix, USA) were centrifuged at 20 000 x g for 10 min and the pellet resuspended in 0.001 % Triton X-100. A 10 µL sample of the extract was mixed in 100 µL of nano-gold suspension, mixed for 5 min and the absorbance was taken between 500-700 nm (Neo-2, Synergy IV, Biotech Instruments, USA). The aggregation ratio was measured at 650 nm/520 nm. Blanks consisted of ethanol and standard solutions of melamine was used for calibration. The data were expressed as µg melamine/dissolved organic carbon content. In vitro peroxidase assay The in vitro peroxidase (Per) assay was based on a previous methodology for industrial effluents toxicity screening (Gagne and Blaise, 1997). The Per assay principle is explained in Figure 1, where Per and albumin are exposed to municipal effluent samples. DNA could be added to seek out interactions with municipal wastewaters extracts. The reagent DHFDA was used instead of luminol for fluorometric detection at 485 nm excitation and 530 nm emission for fluorescein. The reaction media contained horseradish Per and albumin at 0.1 µg/mL in PBS in a total volume of 160 µL followed by the addition of 10-20 µL of the ethanolic extract and incubated for 5 min. After this period, 20 µL of 1 µM DCFDA and 0.01 % H 2 O 2 were added. The reaction was allowed to proceed at 25 o C for 30 min with readings taken at each 3 min fluorescein (excitation 485 nm/emission 530 nm). The same procedure was repeated with the ethanol extract pre-incubated for 5 min with 1 µg/mL DNA to determine the influence of DNA on Per reaction rates. The DNA protection index is defined as: Per activity with DNA/Per activity. Blanks consisted of ethanol only and CdNO 3 was used as a negative control (1 µg/L CdNO 3 decreases Per activity by 30-40%). This Cd concentration is in the same range to trout toxicity (LC50 between 0.7-3 µg/L) for rainbow trout embryos and larvae (Jurgelene et al., 2019). Data analysis The in vitro exposure experiments to the various influents/effluents from 8 cities were repeated three times in the absence and presence of added DNA to determine DNA protection of the Per reaction. The population size of each (anonymous) cities and the various types of wastewater treatment were as follows (Table 1): aerated lagoon (Lag), lagoon with facultative aeration (LagF), advanced biofiltration (Adv), biological filtration (Bio), secondary activated sludge (Sec), secondary membrane bioreactor (SecM) and primary physico-chemical treatment (Prim). The untreated effluents were denoted by None. In this study the influence of treatment processes was obtained from cities differing in population sizes. To understand the influence of population size and the effluents properties from different treatment scenarios, the influents properties were first examined by population size (to keep the anonymity of the cities). The effluents properties were then examined by covariance analysis (ANCOVA) on log-transformed data with the treatment processes as the main variable and population size as the covariate. Critical differences between the absence (Influent) of wastewater treatments and the following the 7 different treatment processes were determined by the LSD test. Significance was set at α=0.05. The relationships between the endpoints were examined using hierarchical tree analysis using the Pearson moment correlation coefficient as the measure of distances (1-r). Discriminant function analysis was also used to seek the difference of wastewater properties before and after the treatment processes. All statistical analyses were performed using the Statsoft software package (USA). Results In this study, the comparison of various treatments is complicated by population densities across the cities. To mitigate these effects, the data for untreated wastewaters (influents or Inf) were examined with increasing population size to seek out population effects on incoming raw wastewater systems. For comparisons between the treatment processes (and anonymous cities), an analysis of covariance was performed using population estimates as the covariate and the treatment types as the main variable. The basic chemical properties of the wastewaters was provided in table 1S. The population densities ranged from 1200-1800000 inhabitants and cities 7 and 8 were the most populated, industrialized and emitters of TSS. The pH values ranged between 6.56 to 7.88 and total ammonia values ranged from 0.2 to 21.3 mg/L. The dissolved organic carbon contents (DOCs) were examined (Table 1). ANCOVA revealed that both treatment processes (p=0.001) and population size (p<0.001) were significantly related to DOCs. The analysis revealed that the LagF, Prim, Sec and SecM DOCs levels were significantly lower than the influents. In respect to population effects, the DOCs levels increased with population size (r=0.42; p=0.01). The relative levels of humic and fulvic acids (HA/FA) were also examined (Table 1). The analysis revealed that only the treatment types was significant with the SecM, Prim effluents showing lower levels compared to untreated influents. The levels of HA/FA were significantly increased in the Bio-treated effluents compared to the untreated influents. This suggests a greater input of natural organic matter from water sources. The levels of light and heavy Pahs were significantly affected by both population size and treatment processes while med Pahs were only affected by the treatment processes. The lights PaHs were significantly lower for the Sec, LagF and SecM effluents compared to untreated influents. The heavy Pahs were significantly reduced by Prim, LagF, and SecM effluents compared to the Inf sites. In respect to population size, the levels of light and heavy Pahs increased with the population size at r=0.3 and r=0.54 respectively. For Med Pahs, the levels were significantly lower for lagF, SecM effluents but higher at the Bio effluent. The levels of melamine were also determined in these samples. The analysis revealed that only the treatment types (p<0.01) influenced the levels of melamine (Table 2). The levels of melamine were significantly higher in the Lag, Sec and SecM effluents. In this study, the levels of plastic related compounds were examined in the dissolved organic matrix (Table 3). The levels of polystyrene nanoplastic particles (PsNPs) were significantly influenced by the population levels only (treatment types at p=0.12; population at p<0.001). The levels of PSNPs were significantly associated with population size (r=0.64) and the treatment processes were seemingly invariable towards PSNPs. PSNPs were significantly related with TSS for population (r= 0.37) and treatment type where the nanoparticles were lower for Lag and Prim treatments even after compensating for population differences. This suggests PsNPs are associated to the TSS fraction in wastewaters. For polypropylene-like materials, the analysis revealed that only the treatment types were significant (treatment at p=0.001; population at p=0.145). The levels of PP-like substances were significantly removed for the Bio and Sec effluents compared to the Inf. In respect to PS/PVC-like substances, only the treatment processes significantly differed (ANCOVA, treatments p<0.001, population p=0.34). In terms of untreated influents, the levels were somewhat higher in lower city population (r=0.25; p=0.05). The extracts were examined for the presence of plastic-like materials based on the solvatochromic properties of NR (Table 3). PsNPs emit at 600-620 nm in the presence of NR in the ethanol extracts and considered a signal for plastics materials. The analysis revealed that the treatment types (p<0.001) only affected the levels of NR signal with no influence of population size (p=0.32). NR signals were higher in the Adv, Lag, LagF, Sec and SecM treatments. The activity of Per was measured in the presence of various influents and effluents in the presence and absence of added DNA (Figure 1) The analysis revealed that both the population size and treatment types significantly influenced Per activity (p<0.001 for both variables) (Figure 3A). The activity was significantly changed by all treatment types considering population size for Adv (decreased activity), Lag (increased), Prim (decreased), Sec(increased), SecM (increased) effluents following correction for population compared to controls. Indeed, activity in Per was positively correlated with population number (Figure 3B, r=0.50; p<0.001). The DNA protection potential was significantly influenced by the treatment types (Figure 4). Although most cities (by population number) produced DNA protection, suggesting a general release of genotoxic compounds, no trends were observed with population size. The following treatments increased the DNA protection potential relative to controls: Adv, Bio, Prim, Lag and the influents (no treatment). In the attempt to gain a more global view of the various endpoints, a hierarchical tree analysis and discriminant function analyses (Figure 4A and B). For the hierarchical tree analysis, the relative distance between the various endpoints were based on the correlation coefficient (1-r). The Per activity assay was closely related with the DNA-Per assay and were both related with the antioxidant melamine levels. The levels of PsNPs were closely related with heavy Pahs while light/medium Pahs were closely related with the dissolved organic content (DOC). The relative levels of HA/FA acids were closely related to PS/PVC-like substances. Population size was significantly related to Pahs, DOC and PSNPs. In the attempt to understand the performance of the treatment types, a discriminant function analysis was performed (Figure 4B). The mean classification was 88% and the following markers had the highest factorial weights: melamine, Per, light/med Pahs and PS-like substances. The Adv, Bio, SecM and Sec produced the most difference between the influents and effluents based on the above endpoints. The Lag and Prim produced less difference between the untreated influents and treated effluents suggesting that the effluents were closely related in properties to the untreated effluents. Discussion The in vitro Per assay was first introduced as a rapid and inexpensive screening tool for water quality assessments for urban, agriculture and industrial inputs in aquatic ecosystems (Ilyina et al., 2000 ; Whitehead et al., 1993 ). Application of this assay directly on wastewaters could also pick up the presence of microorganisms if the samples are not filtered or extracted first (Buk ad Roslev, 2011). When this assay was used on filtered (0.2 µm) industrial effluents, Per inhibitions were significantly associated trout survival and Ceriodaphnia dubia survival and reproduction data (Gagné and Blaise, 1997 ) giving a toxicological interpretation for this in vitro assay and its potential use as a NAMs for toxicity testing. The composition of this assay is strikingly simple with Per enzyme and albumin in solution with H 2 O 2 and DHFDA as the antioxidant molecule. In addition, DNA could be added to identify samples that prevent changes in Per activity, hence DNA protection assay. On the one hand, inhibition of Per activity was associate to acute toxicity from H 2 O 2 build-up in cells. On the other hand, the increase in Per activity, while maintaining H 2 O 2 at safe levels, involves the accumulation of harmful oxidized products on the long-term basis. This assay could suggest the presence of hydroperoxides (oxidized polyunsaturated lipids), which are substrates for Per (Schwarz et al., 2023 ). These peroxidase usually use glutathione as co-substrates and lipid hydroperoxide instead of H 2 O 2 . Municipal effluents, flocs and sludge flocs were shown to contain unsaturated lipids, which could be oxidized especially is those using aeration with sunlight or UV treatments (Conrad et al., 2003 ). Moreover, the formation of biofilms rich in extracellular substances was particularly rich in unsaturated fatty acids. This is in keeping with lagoons using secondary aeration or UV treatment (Sec, SecM and AL), which showed the highest levels of induction in Per activity. Oxidative stress often involves the activation of catalase, superoxide dismutase and Per leading to the accumulation of oxidative damage (lipids, proteins and DNA) on the long-term (Correia et al, 2020 ; Kurhaluk, 2019 ). For example, increased Per activity was often associated with oxidative damage such as lipid peroxidation and DNA damage (Rodrigues et al., 2017 ; Antunes et al., 2016 ). This suggests that sustained Per activity although contributing to lower H 2 O 2 levels could decreases the antioxidant capacity of cells on the long-term. The production of H 2 O 2 by superoxide dismutase (SOD) is usually controlled by catalase and peroxidases. While catalase eliminates H 2 O 2 into O 2 and H 2 O, Per involves the co-oxidation of endogenous and exogenous compounds. While xenobiotics could be oxidized by Per, the enzyme co-oxidizes various endogenous ligands such as vitamin C, glutathione and perhaps endogenous nucleotides (DNA oxidation), polyunsaturated lipids (lipid peroxidation) and proteins (carbonylation). It is not clear whether H 2 O 2 alone or in combination with Per contributes mainly to the formation of DNA damage and lipids. It is assumed, that H 2 O 2 alone directly oxidizes lipids and DNA in cells. For example, aromatic hydrocarbons could form DNA adducts leading to strand breaks in the presence of H 2 O 2 and Per (Cavalieri et al, 1983 ). In our controls, Per activity was not significantly changed (albeit somewhat lower) in the presence of DNA suggesting that DNA was not a direct substrate for Per. More research would be needed to clarify this point. It is noteworthy that melamine levels were significantly correlated with Per activity with or without added DNA. Melamine has 2 oxidation sites leading to ammelide and cyanuric acid (Shallileh et al., 2023), where melamine-cyanuric acid complex can lead to DNA damage and renal damage (Xu et al., 2020 ). Interestingly, single exposures of either cyanuric acid or melamine in human embryonic kidney 293 cells did not lead to DNA strand breaks but co-exposure to them produced DNA strand breaks. Melamine could also act as an enhancer in the Per reaction where melamine would act as secondary substrate the peroxidation of DHFDA (Zhang et al., 201). Enhancers of the Per oxidation usually are nitrogen aromatic compounds such as aniline, phenothiazine and benzidine. If this holds true, melamine (and its oxidized products ammelide and cyanuric acid) could accept one electron from Per and the melamine radical would, in turn, oxidize the substrate DHFDA more quickly than Per. It was shown that melamine could increased the peroxidase properties of gold nanoparticles in the presence of H 2 O 2 and tetramethylbenzidine (Ni et al.., 2014 ), which supports this hypothesis. In a previous study with industrial effluents, DNA protection of the Per reaction (increased DNA-Per activity compared to Per activity alone) was associated in 70% of cases with increased DNA (SOS) repair activity in bacteria (Gagné and Blaise, 1997 ) making it a suitable rapid screening test for genotoxicity. Although the maximum reduction on Per activity (0.2 fold of the control activity) was observed at 50 X concentrations suggesting that toxic effects are unlikely at effluent concentrations < 100%. This observation is consistent with the general absence of trout toxicity for these municipal effluents during regulatory compliance testing ( https://open.canada.ca/data/en/dataset/471736af-e236-444a-9888-b4d99052c927 ). This provides evidence that the Per assay did not produce any false negative municipal effluents in respect to rainbow trout toxicity. Although the Per assay was significantly related with trout and Ceriodaphnia dubia survival tests (multiple regression r = 0.65; p = 0.02), positive results with Per and or the DNA protection assay should be confirmed at the fish/daphnid levels to further confirm the observed trend observed for industrial effluents (Gagné and Blaise, 1997 ). Nevertheless, increased Per activity by enhancers could present a more long-term stress since these compounds are usually (geno)toxic in addition to the presence of endocrine disruption in domestic wastewaters. It is noteworthy that the untreated influents inhibited Per more strongly in smaller populated townships suggesting perhaps some limitation of basic municipal effluents. In respect to sublethal effects, SOD gene expression, involved in the production of H 2 O 2 , was examined in rainbow trout hepatocytes exposed to municipal effluent extracts from 12 Canadia cities (Gagné et al., 2013 ). Over 75% of the effluents produced changes in SOD gene expression indicating the production of reactive oxygen species and supporting the knowledge that municipal effluents produce oxidative stress in organisms. Compared to the untreated influents, SOD gene expression was increased in 3 of the tested effluents and that population and DOC were significantly related to SOD gene expression. It was noteworthy that the DNA protection assay revealed significant protection in 5/8 (63%) of the wastewaters providing evidence that municipal effluents are often genotoxic to aquatic organisms. This observation corroborates previous findings showing that municipal effluents from a primary and advanced biofiltration with secondary UV-treatment were equally genotoxic in fathead minnows exposed for 3 months to these effluents (Lacaze et al., 2017 ). This suggests that genotoxic compounds were impervious to differing water treatments and that the occurrence of DNA damaging compounds in relatively common in treated wastewaters. Genotoxicity calculations of the effluent of the Montreal (Quebec, Canada) revealed that it releases over 31 kg of benzo(a)pyrene equivalents per day using a bacterial DNA-repair assay- SOS Chromotest (White and Rasmussen, 1998 ). Moreover, the data also revealed that 90% of the genotoxic loadings was nonindustrial in origin i.e., from domestic wastes and street runoffs. In a following study with mussels caged to the municipal dispersion plume of the City of Montreal for 1 month, DNA strand breaks were detected in hemocytes using the Comet assay (Lacaze et al., 2013 ). The genotoxicity of treated and untreated municipal effluents was also observed in Elliptio complanata mussels hemocytes exposed in vitro to municipal effluent extracts (Gilroy et al., 2023 ). The study revealed that genotoxicity persists following treatment in other municipalities suggesting the continuous release of genotoxic compounds in the aquatic environment. In conclusion, the water quality of municipal wastewaters was examined with the Per assay using a DNA protection variation. The study revealed that Per activity of wastewaters influents were influenced by population size and the wastewater treatment types. The more advanced treatments (biofiltration, membrane biofiltration, secondary aeration) produced stronger changes compared to the corresponding untreated influents. Per activity changes were also associated to the DOC, Pahs and plastic-like substances and nanoparticle loadings in the effluents. A positive relationship was observed with melamine suggesting that other reduced substances could act as substrates for Per as well and could explain in part interactions with DNA and perhaps genotoxicity. In conclusion, the data show that municipal effluents are generally not acutely lethal based on inhibitions of the Per activity but could in some instances increase Per activity leading to more long-term toxicity by the accumulation of oxidizes endogenous substrates. The DNA protection assay revealed that 60% of the effluents have genotoxic potential providing some evidence on the released of genotoxic compounds in aquatic ecosystems. Declarations Declaration of interest The authors declare no competing interests in the preparation and revision of this manuscript. Ethical Approval Not applicable The authors consent to publish Funding No external funding Availability of data and materials Data available upon request. Acknowledgements This work was funded by the Saint-Lawrence Action Plan and the Wastewater monitoring of Environment and Climate Change Canada. The helpful assistance of Joelle Auclair and Hiba Quichach in effluent preparation are recognized. References Aas E, Beyer J, Goksoyr A 1995. PAHs in fish bile detected by fixed wavelength fluorescence. Mar. Environ. Res. 46, 225–228. Antunes SC, Nunes B, Rodrigues S, Nunes R, Fernandes J, Correia AT 2016. Effects of chronic exposure to benzalkonium chloride in Oncorhynchus mykiss : cholinergic neurotoxicity, oxidative stress, peroxidative damage and genotoxicity. Environ Toxicol Pharm 45, 115-122. Brandstetter A, Sletten RS, Mentler A, Wenzel WW 1996. Estimating dissolved organic carbon in natural waters by UV absorbance (254 nm). J Plant Nut Soil Sci 159, 605-607. Bukh AS, Roslev P 2011. 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Genotoxic impact of a municipal effluent dispersion plume in the freshwater mussel Elliptio complanata : an in situ study. J. Xenobiotics 3, e6. Lee YK, Hong S, Hur J 2021 Copper-binding properties of microplastic-derived dissolved organic matter revealed by fluorescence spectroscopy and two-dimensional correlation spectroscopy. Water Res 190, 116775. NiP, Dai H, Wang Y, Sun Y, Shi Y, Hu J, Li Z 2014. Visual detection of melamine based on the peroxidase-like activity enhancement of bare gold nanoparticles. Biosens Bioelectron 60, 286-291. O’Brien P J 2000. Peroxidase. Chem-Biol Inter 129, 113-139. Rach JJ, Schreier TM, Howe GE, Redman SD 1997. Effect of Species, Life Stage, and Water Temperature on the Toxicity of Hydrogen Peroxide to Fish. The Progressive Fish culturist 59:41-46. Rodrigues S, Antunes SC, Correia AT, Nunes B2017. Rainbow trout (Oncorhynchus mykiss) pro-oxidant and genotoxic responses following acute and chronic exposure to the antibiotic oxytetracycline. Ecotoxicology 26, 104-117. Shalileh F, Sabahi H, Golbashy M, Dadmehr M, Hosseini M 2023. Recent developments in DNA nanostructure-based biosensors for the detection of melamine adulteration in milk. Microchemical J 195, 109316. Schwarz M, Löser A, Cheng Q, Wichmann-Costaganna M, Schädel P, Werz O, Arnér ES, Kipp AP. 2023. 2023. Side-by-side comparison of recombinant human glutathione peroxidases identifies overlapping substrate specificities for soluble hydroperoxides. Redox Biol 59:102593. White PA, Rasmussen JB 1998. The genotoxic hazards of domestic wastes in surface waters. Mutation Research 410 1998 223–236. Whitehead, T. P., G. Thorpe, M. Lane, A. Watson, and C. Billings. 1993. A rapid and simple chemiluminescent assay for water quality and monitoring. Biol Perspect 377-381. Xu X, Lu J, Sheng H, Zhang L, Gan T, Zhang J, Xu Y, Zhu X, Yang J 2020. Evaluation of the cytotoxic and genotoxic effects by melamine and cyanuric acid co-exposure in human embryonic kidney 293 cells. Braz J Med Biol Res 53, e9331. Tables Table 1. City characteristics Townships Population Treatment Type Dissolved organic carbon (mg/L) Influent Effluent 1 1 214 Lagoon, facultative aeration (LagF) 1.28 1.046 ±0.008 ±0.005 2 16 000 Biological Filtration (Bio) 1.19 1.18 ±0.11 ±0.006 3 33 761 Advanced Biofiltration (Adv) 1.17 1.19 ±0.09 ±0.13 4 119 360 Aeration Lagoons (Lag) 1.24 1.18 ±0.1 ±0.006 5 129 500 Lagoon, facultative aeration (LagF) 1.07 1.04 ±0.01 ±0.005 6 523 000 Secondary membrane bioreactor (SecM) 1.25 1.1 ±0.16 ±0.02 7 570 000 Secondary Aeration sludge (Sec) 1.46 1.18 ±0.15 ±0.04 8 1 800 000 Physico-chemical (Prim) 1.26 1.23 ±0.16 ±0.07 Table 2 Relative levels of light, medium and heavy PAHS and melamine in wastewaters. Treatment Humic/fulvic acids (RFU) Light PAHs µg/L Medium PAHs µg/L Heavy PAHs µg/L Melamine µg/L None 0.9±0.1 33±6 4.5±0.7 0.23±0.03 1±0.3 LagF 0.74±0.05 8±0.8* 1.2±0.09* 0.20±0.007 0.4±0.04* Adv 0.87±0.1 13±4* 2.7±0.8 0.5±0.2 0.8±0.08 Bio 1.8±0.4* 57±12 10±1* 0.3±0.03 0.3±0.04* Sec 0.7±0.1 28±6 7±2.7 0.53±0.1* 11±2* Lag 0.8±0.1 28±0.8 1.8±0.1* 0.3±0.08 6.2±1.8* SecM 0.49±0.2* 3.8±0.8* 1.3±0.4* 0.07±0.02* 21±2* Prim 0.37±0.1* 20±6* 3±0.6 0.12±0.03* 0.15±0.1 * significant from the influents (before treatments; None). Na: not analyzed. Table 3. Plastic nanoparticles and related materials Treatments PsNPs µg/L PP µg/L Extended PS/PVC µg/L NR 600 nm µg/L None 1.7±0.2 0.07±0.06 0.077±0.01 0.066±0.01 LagF 1.1±0.1* 1±0.3* 0.04±0.01* 0.11±0.03* Adv 2.5±0.8 0.01±0.005* 0.05±0.03 0.06±0.03 Bio 0.65±0.3* 0.02±0.05* 0.22±0.009* 0.07±0.01 Sec 3.1±0.5* 0.005±0.001* 0.024±0.011* 0.16±0.02* Lag 1±0.6 0.02±0.005* 0.077±0.011 0.09±0.05 SecM 2.3±0.8 0.006±0.002* 0.075±0.011 0.11±0.036 Prim 0.7±0.2* 0.09±0.002* 0.031±0.006* 0.085±0.01 Additional Declarations No competing interests reported. Supplementary Files Supplfile.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4547007","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":320009030,"identity":"bc88776a-d540-4ab2-98a2-06e18fe982f1","order_by":0,"name":"Francois Gagné","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/klEQVRIiWNgGAWjYBAC9gYwJQHj2xDWwnMAVUsa0Vrg4DARWqQPP3vwo8LCnoF/8ePXBRXn5fgb2C9+YKixw62FL83csOeMRGKDxDMz6xlnbhtLHOAplmA4loxTiz0Pg5k0Y5tEAoPEATNj3rbbiRsYeNIYGBuYcdvCw/4NpMWeQeL4N2Pef+fqoVrq8WjhAdvC2MDfY/yYt+FAggED+zGgFtzhANRSJgnyS5sETxkzz7FkwxmHeZglEo4dx+ewbRI/Kurs+fmPb/7MU2Mnz9/e/vDDh5pqnFrggE0igQ0Socw8BgwJhDUAAf8B5g8QFvsDojSMglEwCkbBiAEAQPxHOCrAxqEAAAAASUVORK5CYII=","orcid":"","institution":"Environment and Climate change Canada","correspondingAuthor":true,"prefix":"","firstName":"Francois","middleName":"","lastName":"Gagné","suffix":""},{"id":320009031,"identity":"4cae61c1-f2d6-455d-919c-88100d47c442","order_by":1,"name":"Chantale André","email":"","orcid":"","institution":"Environment and Climate change Canada","correspondingAuthor":false,"prefix":"","firstName":"Chantale","middleName":"","lastName":"André","suffix":""},{"id":320009032,"identity":"bf8d2e2e-3fe0-4203-8d80-f1fca45405c1","order_by":2,"name":"Shirley -Ann Smyth","email":"","orcid":"","institution":"Environment and Climate change Canada","correspondingAuthor":false,"prefix":"","firstName":"Shirley","middleName":"-Ann","lastName":"Smyth","suffix":""}],"badges":[],"createdAt":"2024-06-07 15:26:20","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4547007/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4547007/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":60660183,"identity":"93beaa64-6e50-43d2-b7c3-492326c43b1f","added_by":"auto","created_at":"2024-07-19 08:24:23","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":83882,"visible":true,"origin":"","legend":"\u003cp\u003ePrinciple of the \u003cem\u003ein vitro\u003c/em\u003e peroxidase assay.\u003c/p\u003e\n\u003cp\u003ePeroxidase catalyze the oxidation of organic (electron donor) compounds for the elimination of H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e. A secondary reaction involves the peroxidase-oxidase reaction where O\u003csub\u003e2\u003c/sub\u003e and NADH replaces H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e and electron donor compounds. The inhibition of peroxidase leads to the accumulation of H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e, which rapidly produce toxicity and was associated to fish mortality (Gagné and Blaise, 1997). Conversely, the activation of peroxidase leads to depletion of electron donors (e.g. ascorbic acids, glutathione/amino acids, DNA, RNA) and produce oxidative stress on the long-term. The DNA protection assay is calculated by the ratio (Per with DNA/Per alone) and indicates oxidative mediated affinity to DNA.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4547007/v1/567ca63966287daec007b3f0.png"},{"id":60660187,"identity":"33c62480-d088-455f-be6e-7c9cdb63d7d7","added_by":"auto","created_at":"2024-07-19 08:24:24","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":16890,"visible":true,"origin":"","legend":"\u003cp\u003eFigure 3. Peroxidase activity in influents and effluents extracts.\u003c/p\u003e\n\u003cp\u003eThe influents and effluents were extracted on a C18-SPE columns and eluted with ethanol (corresponding to 500X). The extracts (50 X) were then tested with the peroxidase assay for the untreated effluents (A) and different wastewater treatment (WWT) type (B). The solid lines correspond to the control activity of peroxidase with the dotted lines corresponding to normal variation of 15%. In B, none is the mean value of the untreated influents in A. The star symbol * indicates significant difference from the control activity.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-4547007/v1/3e9cf496291e1c83127c826c.png"},{"id":60660184,"identity":"9afc3d4c-00fe-4d3f-bf9b-ca06806ba49d","added_by":"auto","created_at":"2024-07-19 08:24:23","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":19459,"visible":true,"origin":"","legend":"\u003cp\u003eFigure 4. DNA protection assay of the peroxidase activity assay.\u003c/p\u003e\n\u003cp\u003eThe influents and effluents were extracted on a C18-SPE column and eluted with ethanol (corresponding to 500X). The extracts (50 X) were then tested with the peroxidase assay in the presence of DNA for the untreated effluents (A) and different wastewater treatment (WWT) type (B). The DNA protection was defined as Peroxidase with DNA (0.1 µg/mL) /peroxidase without DNA. The solid lines correspond to the absence of effects of DNA and the dotted lines corresponding to normal variation of 15%. In B, none is the mean value of the untreated influents in A. The star symbol * indicates significant difference from the control (absence of DNA effects).\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-4547007/v1/dea675292e9ddfffed362e7a.png"},{"id":60660185,"identity":"688363f6-d30e-45e0-9e7b-8b01f5b188fa","added_by":"auto","created_at":"2024-07-19 08:24:23","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":16312,"visible":true,"origin":"","legend":"\u003cp\u003eFigure 5. Hierarchical tree and discriminant function analyses of influents and effluents contaminants.\u003c/p\u003e\n\u003cp\u003eTree analysis was provided using the Pearson moment correlation coefficient (1-r) (A). The dotted line represents the significance limit of the correlation coefficients. Discriminant function analysis is provided to seek out changes by the various treatment processes, before and after treatment (B). The untreated influents and effluents are highlighted as orange and green respectively.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-4547007/v1/0c72ae78471c40555185a1ca.png"},{"id":65194984,"identity":"9eaf4feb-d975-493e-960d-597a1c33bf97","added_by":"auto","created_at":"2024-09-24 15:17:20","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":593808,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4547007/v1/40da17b8-d7a8-43ac-80e6-e918efe70913.pdf"},{"id":60661469,"identity":"e7532221-7563-49c4-a96f-e9c46a1f8e13","added_by":"auto","created_at":"2024-07-19 08:40:24","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":17077,"visible":true,"origin":"","legend":"","description":"","filename":"Supplfile.docx","url":"https://assets-eu.researchsquare.com/files/rs-4547007/v1/e64052c766522e3a2042c9fd.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Screening of municipal effluents with the peroxidase toxicity assay","fulltext":[{"header":"Introduction","content":"\u003cp\u003ePeroxidases (Per) are hemoproteins involved in the oxidation reactions with hydrogen peroxide (H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e). Per belong to a large family of oxido-reductases and found in living organisms. The size of these heme containing proteins ranges between 35-100 kDalton (O’ Brien, 2000).\u0026nbsp;\u0026nbsp;Although Per could use a large variety of electron donor compounds, some use specific ones such as glutathione. Although Per have a major protection role against reactive oxygen species such as H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e, they can lead to deleterious reactions involving the oxidation of endogenous substrates and xenobiotics leading to tissue damage, lipoprotein oxidation and carcinogenesis.\u0026nbsp;They are considered antioxidant enzymes to keep H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e at safe levels to protect cells and tissues. Indeed, the estimated toxicity of H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e is 0.1 µg/L after 96 h at 17\u003csup\u003eo\u003c/sup\u003eC in trout (Rach et al., 1997). Given that between 1-2% of consumed O\u003csub\u003e2\u003c/sub\u003e during respiration transforms into oxygen radicals (*OH) and to H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e by superoxide dismutase (Cadenas and Davies, 2000), the levels of H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e needs to be tightly regulated by antioxidant mechanisms involving catalase and Per. On the other hand, the long-term of activity of Per could lead to the accumulation of oxidized compounds (from electron donors) such as oxidized vitamins/cofactors and xenobiotics leading to DNA adduct and DNA (8-oxoguanine) oxidation (Cavalieri et al., 1983). Indeed, reactive species generated by mitochondria or other sites in the cytoplasm, cause damage to mitochondria and organelles and initiate degradative processes involved in aging. Oxidative stress can modify lipids, DNA, RNA and proteins/enzymes, which require them to be removed by DNA repair enzymes, protein (protein degradation/turnover) and (damaged) unsaturated lipids (hydrolysis). Hence, the Per enzymes are two edged swords i.e., they can removes toxic levels of H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e at the expenses of electron donor products in cells (vitamins, NADH, guanosine, glutathione, amino acids etc.) leading to the accumulation of oxidatively damaged products on the long-term. In fish collected at rivers polluted by heavy metal, the fish accumulated zinc, chromium, nickel, cobalt and copper with a concomitant rise in Per activity in the liver, gills and muscles (Javed et al., 2020). This suggests that these metals lead to H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e perhaps at the expense of antioxidant levels (i.e., reduced antoxidant capacity)\u003c/p\u003e\n\u003cp\u003eThe Per assay was used to screen various industrial effluents and revealed inhibition in the reaction rates (Gagné and Blaise, 1997). It was noteworthy that the Per inhibition potential was significantly associated to trout mortality where the toxic effluents produced the strongest inhibition at low effluent concentration. An interesting variation of this assay was to include DNA during the Per assay to detect interactions between DNA and the effluents. While DNA alone did not affect Per activity, the addition of DNA with the effluents reversed the inhibition suggesting interactions with the contaminants. Effluents showing DNA interactions with the Per reaction were genotoxic 70% of the cases using an SOS DNA repair test in bacteria (Gagné and Blaise, 1997). A luminol-based Per reaction was also proposed as a mean for water quality assessments with single substances and pesticide formulations (Ilyina et al., 2000). Preincubation of Per with herbicides, detergents/surfactant, phenol, metals (Hg, Co, Ni) had an inhibitory effect of Per activity. However, some other compounds could stimulate Per activity at low concentrations (an hormetic response), which was followed by decreased activity. Some insecticide formulation revealed a sustained increase in Per activity suggesting perhaps that other compounds present in these formulations (stabilizers, antioxidants etc) could increase H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e degradation rates. The Per reaction offers a very rapid and efficient means to screen for potentially toxic mixtures such as industrial and municipal wastewaters. In the context of reducing the sacrifice of fish and other vertebrates in toxicity tests, new alternative methods (NAMs) are urgently needed for toxicity screening purposes and the Per assay was seemingly predictive of trout mortality with very few or no false negatives.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe purpose of this study was therefore to use the Per and DNA-protection variation assay as a screening tool to evaluate the impacts of wastewaters on water quality and potential toxicity from 8 townships in Canada. Municipal wastewaters before (influent) and after 7 different treatment processes (effluents) were concentrated on a C18 reverse phase columns (ethanol elution) for the Per assay. An attempt was made to understand the contribution of population size and the performance of various treatments processes to alleviate changes in Per assay and the DNA protection effects.\u0026nbsp;\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eSample preparation\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll reagents were purchased from Sigma Chemical Company (On, Canada) at the highest purity available. Horseradish peroxidase and serum bovine albumin were prepared at 1 mg/mL in phosphate buffered saline (PBS: 140 mM NaCl, 5 mM KH\u003csub\u003e2\u003c/sub\u003ePO\u003csub\u003e4\u003c/sub\u003e and 1 mM NaHCO\u003csub\u003e3\u003c/sub\u003e, pH 7.5) and kept for non-longer than one week at 4\u003csup\u003eo\u003c/sup\u003eC in the dark. For DNA, 10 mg of salmon sperm DNA was dissolved in 10 mL of 0.25 X PBS, heated at 70\u003csup\u003eo\u003c/sup\u003eC for 10 min and stored at 4\u003csup\u003eo\u003c/sup\u003eC. \u0026nbsp;The reagent dihydrofluorescein diacetate (DHFDA) was dissolved at 1 mg/mL in 10 % ethanol. Hydrogen peroxide solutions were prepared at 1% concentration and stored at 4\u003csup\u003eo\u003c/sup\u003eC for non-longer than one week.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe untreated (influent) and treated effluents from 8 townships of various treatment process and sizes in Canada were 24 h composites and collected for 3 days (Table 1). The wastewaters (1 L) were transported back to the laboratory and stored at 4\u003csup\u003eo\u003c/sup\u003eC in the dark. The influent and corresponding effluent samples were filtered on 0.45 µm pore cellulose filter and 500 mL was passed through a reverse phase C18 cartridge (500 mg; Sulpeco). After washing with MilliQ water (10 ml), the material was eluted with 5 mL ethanol and concentrated to 1 mL under nitrogen stream (500 X concentrate). \u0026nbsp;The ethanol samples were stored at -20\u003csup\u003eo\u003c/sup\u003eC until analysis.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eWastewater extract characteristics\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe dissolved organic matter (DOC) in the ethanol extract was determined by the spectrometric methodology (Brandstetter et al., 1996). The DOC levels were estimated based on the following relationship: DOC (mg/L) = 0.45A +1 for organic-rich surface waters. The levels of plastic-like substances associated to the organic matter were determined by the copper fluorescence quenching methodology (Lee et al., 2021). The decreased in fluorescence for humic/fulvic acids (265 nm excitation/463 nm emission), polypropylene-derived materials (250 nm excitation/324 nm emission) and polyvinyl chloride /polystyrene-derived materials (295 nm excitation/411 nm emission) were determined before and after the addition of one volume of 100 µM of CuCl\u003csub\u003e2\u003c/sub\u003e. The difference between fluorescence without Cu – fluorescence with Cu was calculated and standard solutions of polystyrene (20 nm diameter) and polypropylene (100 nm diameter) were used for calibration. The data were then normalized to the DOC in the samples.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe levels of light, medium and heavy polyaromatic hydrocarbons were determined in the ethanol extracts using fixed wavelength fluorometry (Aas et al., 1995). Briefly, 100 µL of ethanol extracts were placed in dark 96-wells microplate and fluorescence measured at 290 nm excitation/340 nm emission (light PAhs: naphthalene), 325 nm excitation/370 nm emission (medium Pahs: pyrene) and 385 nm excitation /440 nm emission (heavy Pahs: benzo(a)pyrene) using a fluorescence microplate reader (Neo-2 Synergy, Biotek Instruments, USA). Standard solutions of the Pahs were used for calibration. Recovery of each Pahs size class were between 80-95% in the C18 extraction columns. The levels of polystyrene nanoplastics (PsNPs) were determined using a molecular rotor probe 9(dicyanovinyl)-julolidine as described (Gagne, 2019). Briefly, 10 µL if effluent extract were mixed with 190 uL of 10 uM of the probe (diluted in MilliQ water) and fluorescence were taken at 450 nm excitation and 620 nm emission (Neo-2, Synergy-4, Biotech Instruments, USA). Standard solutions of polystyrene nanoparticles (50 nm Polyscience, USA) were used for calibration. Solvatochromatic analysis of the ethanol extracts to detect plastic-like substances using the Nile red methodology were also performed (Gagne et al., 2019). Briefly, 25 µL of the ethanol extracts were mixed with 225 µL of 50 uM Nile red (in PBS buffer) and the emission spectra were recorded between 520-700 nm at 485 nm excitation. The first derivative of the spectra revealed that PsNPs emitted at 600-620 nm and this signal was taken as a measured of plastic-like materials. The data were expressed as relative fluorescence units (600 nm) corrected for the organic matter contents. The levels of melamine were determined using a nano-gold plasmonic sensor (Gao et al., 2018). Briefly, citrate coated nano-gold (10 nm diameter, NanoComposix, USA) were centrifuged at 20 000 x g for 10 min and the pellet resuspended in 0.001 % Triton X-100. A 10 µL sample of the extract was mixed in 100 µL of nano-gold suspension, mixed for 5 min and the absorbance was taken between 500-700 nm (Neo-2, Synergy IV, Biotech Instruments, USA). The aggregation ratio was measured at 650 nm/520 nm. Blanks consisted of ethanol and standard solutions of melamine was used for calibration. The data were expressed as µg melamine/dissolved organic carbon content. \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eIn vitro peroxidase assay\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe \u003cem\u003ein vitro\u003c/em\u003e peroxidase (Per) assay was based on a previous methodology for industrial effluents toxicity screening (Gagne and Blaise, 1997). The Per assay principle is explained in Figure 1, where Per and albumin are exposed to municipal effluent samples. DNA could be added to seek out interactions with municipal wastewaters extracts. The reagent DHFDA was used instead of luminol for fluorometric detection at 485 nm excitation and 530 nm emission for fluorescein. The reaction media contained horseradish Per and albumin at 0.1 µg/mL in PBS in a total volume of 160 µL followed by the addition of 10-20 µL of the ethanolic extract and incubated for 5 min. After this period, 20 µL of 1 µM DCFDA and 0.01 % H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e were added. The reaction was allowed to proceed at 25\u003csup\u003eo\u003c/sup\u003eC for 30 min with readings taken at each 3 min fluorescein (excitation 485 nm/emission 530 nm). The same procedure was repeated with the ethanol extract pre-incubated for 5 min with 1 µg/mL DNA to determine the influence of DNA on Per reaction rates. The DNA protection index is defined as: Per activity with DNA/Per activity. Blanks consisted of ethanol only and CdNO\u003csub\u003e3\u003c/sub\u003e was used as a negative control (1 µg/L CdNO\u003csub\u003e3\u003c/sub\u003e decreases Per activity by 30-40%). This Cd concentration is in the same range to trout toxicity (LC50 between 0.7-3 µg/L) for rainbow trout embryos and larvae (Jurgelene et al., 2019).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eData analysis\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe \u003cem\u003ein vitro\u003c/em\u003e exposure experiments to the various influents/effluents from 8 cities were repeated three times in the absence and presence of added DNA to determine DNA protection of the Per reaction. The population size of each (anonymous) cities and the various types of wastewater treatment were as follows (Table 1): aerated lagoon (Lag), lagoon with facultative aeration (LagF), advanced biofiltration (Adv), biological filtration (Bio), secondary activated sludge (Sec), secondary membrane bioreactor (SecM) and primary physico-chemical treatment (Prim). The untreated effluents were denoted by None. In this study the influence of treatment processes was obtained from cities differing in population sizes. To understand the influence of population size and the effluents properties from different treatment scenarios, the influents properties were first examined by population size (to keep the anonymity of the cities). The effluents properties were then examined by covariance analysis (ANCOVA) on log-transformed data with the treatment processes as the main variable and population size as the covariate. Critical differences between the absence (Influent) of wastewater treatments and the following the 7 different treatment processes were determined by the LSD test. Significance was set at α=0.05. The relationships between the endpoints were examined using hierarchical tree analysis using the Pearson moment correlation coefficient as the measure of distances (1-r). Discriminant function analysis was also used to seek the difference of wastewater properties before and after the treatment processes. All statistical analyses were performed using the Statsoft software package (USA).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eIn this study, the comparison of various treatments is complicated by population densities across the cities. To mitigate these effects, the data for untreated wastewaters (influents or Inf) were examined with increasing population size to seek out population effects on incoming raw wastewater systems. For comparisons between the treatment processes (and anonymous cities), an analysis of covariance was performed using population estimates as the covariate and the treatment types as the main variable. The basic chemical properties of the wastewaters was provided in table 1S. The population densities ranged from 1200-1800000 inhabitants and cities 7 and 8 were the most populated, industrialized and emitters of TSS. The pH values ranged between 6.56 to 7.88 and total ammonia values ranged from 0.2 to 21.3 mg/L. The dissolved organic carbon contents (DOCs) were examined (Table 1). \u0026nbsp; ANCOVA revealed that both treatment processes (p=0.001) and population size (p\u0026lt;0.001) were significantly related to DOCs. The analysis revealed that the LagF, Prim, Sec and SecM DOCs levels were significantly lower than the influents. In respect to population effects, the DOCs levels increased with population size (r=0.42; p=0.01).\u0026nbsp;The relative levels of humic and fulvic acids (HA/FA) were also examined (Table 1). The analysis revealed that only the treatment types was significant with the SecM, Prim effluents showing lower levels compared to untreated influents. The levels of HA/FA were significantly increased in the Bio-treated effluents compared to the untreated influents. This suggests a greater input of natural organic matter from water sources. The levels of light and heavy Pahs were significantly affected by both population size and treatment processes while med Pahs were only affected by the treatment processes. The lights PaHs were significantly lower for the Sec, LagF and SecM effluents compared to untreated influents. The heavy Pahs were significantly reduced by\u0026nbsp;Prim, LagF, and SecM effluents\u0026nbsp;compared to the Inf sites. In respect to population size, the levels of light and heavy Pahs increased with the population size at r=0.3 and r=0.54 respectively. For Med Pahs, the levels were significantly lower for lagF, SecM effluents but higher at the Bio effluent. The levels of melamine were also determined in these samples. The analysis revealed that only the treatment types (p\u0026lt;0.01) influenced the levels of melamine (Table 2). The levels of melamine were significantly higher in the Lag, Sec and SecM effluents.\u003c/p\u003e\n\u003cp\u003eIn this study, the levels of plastic related compounds were examined in the dissolved organic matrix (Table 3). The levels of polystyrene nanoplastic particles (PsNPs) were significantly influenced by the population levels only (treatment types at p=0.12; population at p\u0026lt;0.001). The levels of PSNPs were significantly associated with population size (r=0.64) and the treatment processes were seemingly invariable towards PSNPs. PSNPs were significantly related with TSS for population (r= 0.37) and treatment type where the nanoparticles were lower for Lag and Prim treatments even after compensating for population differences. This suggests PsNPs are associated to the TSS fraction in wastewaters. For polypropylene-like materials, the analysis revealed that only the treatment types were significant (treatment at p=0.001; population at p=0.145). The levels of PP-like substances were significantly removed for the Bio and Sec effluents compared to the Inf. In respect to PS/PVC-like substances, only the treatment processes significantly differed (ANCOVA, treatments p\u0026lt;0.001, population p=0.34). In terms of untreated influents, the levels were somewhat higher in lower city population (r=0.25; p=0.05). The extracts were examined for the presence of plastic-like materials based on the solvatochromic properties of NR (Table 3). PsNPs emit at 600-620 nm in the presence of NR in the ethanol extracts and considered a signal for plastics materials. The analysis revealed that the treatment types (p\u0026lt;0.001) only affected the levels of NR signal with no influence of population size (p=0.32). NR signals were higher in the Adv, Lag, LagF, Sec and SecM treatments. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe activity of Per was measured in the presence of various influents and effluents in the presence and absence of added DNA (Figure 1) The analysis revealed that both the population size and treatment types significantly influenced Per activity (p\u0026lt;0.001 for both variables) (Figure 3A). The activity was significantly changed by all treatment types considering population size for Adv (decreased activity), Lag (increased), Prim (decreased), Sec(increased), SecM (increased)\u0026nbsp;effluents following correction for population compared to controls. Indeed, activity in Per was positively correlated with population number (Figure 3B, r=0.50; p\u0026lt;0.001). The DNA protection potential was significantly influenced by the treatment types (Figure 4). Although most cities (by population number) produced DNA protection, suggesting a general release of genotoxic compounds, no trends were observed with population size. The following treatments increased the DNA protection potential relative to controls: Adv, Bio, Prim, Lag and the influents (no treatment).\u003c/p\u003e\n\u003cp\u003eIn the attempt to gain a more global view of the various endpoints, a hierarchical tree analysis and discriminant function analyses (Figure 4A and B). For the hierarchical tree analysis, the relative distance between the various endpoints were based on the correlation coefficient (1-r). The Per activity assay was closely related with the DNA-Per assay and were both related with the antioxidant melamine levels. The levels of PsNPs were closely related with heavy Pahs while light/medium Pahs were closely related with the dissolved organic content (DOC). The relative levels of HA/FA acids were closely related to PS/PVC-like substances. Population size was significantly related to Pahs, DOC and PSNPs. In the attempt to understand the performance of the treatment types, a discriminant function analysis was performed (Figure 4B). The mean classification was 88% and the following markers had the highest factorial weights: melamine, Per, light/med Pahs and PS-like substances. The Adv, Bio, SecM and Sec produced the most difference between the influents and effluents based on the above endpoints. The Lag and Prim produced less difference between the untreated influents and treated effluents suggesting that the effluents were closely related in properties to the untreated effluents. \u0026nbsp;\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe \u003cem\u003ein vitro\u003c/em\u003e Per assay was first introduced as a rapid and inexpensive screening tool for water quality assessments for urban, agriculture and industrial inputs in aquatic ecosystems (Ilyina et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Whitehead et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e1993\u003c/span\u003e). Application of this assay directly on wastewaters could also pick up the presence of microorganisms if the samples are not filtered or extracted first (Buk ad Roslev, 2011). When this assay was used on filtered (0.2 \u0026micro;m) industrial effluents, Per inhibitions were significantly associated trout survival and \u003cem\u003eCeriodaphnia dubia\u003c/em\u003e survival and reproduction data (Gagn\u0026eacute; and Blaise, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e1997\u003c/span\u003e) giving a toxicological interpretation for this \u003cem\u003ein vitro\u003c/em\u003e assay and its potential use as a NAMs for toxicity testing. The composition of this assay is strikingly simple with Per enzyme and albumin in solution with H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e and DHFDA as the antioxidant molecule. In addition, DNA could be added to identify samples that prevent changes in Per activity, hence DNA protection assay. On the one hand, inhibition of Per activity was associate to acute toxicity from H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e build-up in cells. On the other hand, the increase in Per activity, while maintaining H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e at safe levels, involves the accumulation of harmful oxidized products on the long-term basis. This assay could suggest the presence of hydroperoxides (oxidized polyunsaturated lipids), which are substrates for Per (Schwarz et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). These peroxidase usually use glutathione as co-substrates and lipid hydroperoxide instead of H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e. Municipal effluents, flocs and sludge flocs were shown to contain unsaturated lipids, which could be oxidized especially is those using aeration with sunlight or UV treatments (Conrad et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). Moreover, the formation of biofilms rich in extracellular substances was particularly rich in unsaturated fatty acids. This is in keeping with lagoons using secondary aeration or UV treatment (Sec, SecM and AL), which showed the highest levels of induction in Per activity.\u003c/p\u003e \u003cp\u003eOxidative stress often involves the activation of catalase, superoxide dismutase and Per leading to the accumulation of oxidative damage (lipids, proteins and DNA) on the long-term (Correia et al, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Kurhaluk, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). For example, increased Per activity was often associated with oxidative damage such as lipid peroxidation and DNA damage (Rodrigues et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Antunes et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). This suggests that sustained Per activity although contributing to lower H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e levels could decreases the antioxidant capacity of cells on the long-term. The production of H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e by superoxide dismutase (SOD) is usually controlled by catalase and peroxidases. While catalase eliminates H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e into O\u003csub\u003e2\u003c/sub\u003e and H\u003csub\u003e2\u003c/sub\u003eO, Per involves the co-oxidation of endogenous and exogenous compounds. While xenobiotics could be oxidized by Per, the enzyme co-oxidizes various endogenous ligands such as vitamin C, glutathione and perhaps endogenous nucleotides (DNA oxidation), polyunsaturated lipids (lipid peroxidation) and proteins (carbonylation). It is not clear whether H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e alone or in combination with Per contributes mainly to the formation of DNA damage and lipids. It is assumed, that H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e alone directly oxidizes lipids and DNA in cells. For example, aromatic hydrocarbons could form DNA adducts leading to strand breaks in the presence of H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e and Per (Cavalieri et al, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1983\u003c/span\u003e). In our controls, Per activity was not significantly changed (albeit somewhat lower) in the presence of DNA suggesting that DNA was not a direct substrate for Per. More research would be needed to clarify this point. It is noteworthy that melamine levels were significantly correlated with Per activity with or without added DNA. Melamine has 2 oxidation sites leading to ammelide and cyanuric acid (Shallileh et al., 2023), where melamine-cyanuric acid complex can lead to DNA damage and renal damage (Xu et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Interestingly, single exposures of either cyanuric acid or melamine in human embryonic kidney 293 cells did not lead to DNA strand breaks but co-exposure to them produced DNA strand breaks. Melamine could also act as an enhancer in the Per reaction where melamine would act as secondary substrate the peroxidation of DHFDA (Zhang et al., 201). Enhancers of the Per oxidation usually are nitrogen aromatic compounds such as aniline, phenothiazine and benzidine. If this holds true, melamine (and its oxidized products ammelide and cyanuric acid) could accept one electron from Per and the melamine radical would, in turn, oxidize the substrate DHFDA more quickly than Per. It was shown that melamine could increased the peroxidase properties of gold nanoparticles in the presence of H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e and tetramethylbenzidine (Ni et al.., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), which supports this hypothesis.\u003c/p\u003e \u003cp\u003eIn a previous study with industrial effluents, DNA protection of the Per reaction (increased DNA-Per activity compared to Per activity alone) was associated in 70% of cases with increased DNA (SOS) repair activity in bacteria (Gagn\u0026eacute; and Blaise, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e1997\u003c/span\u003e) making it a suitable rapid screening test for genotoxicity. Although the maximum reduction on Per activity (0.2 fold of the control activity) was observed at 50 X concentrations suggesting that toxic effects are unlikely at effluent concentrations\u0026thinsp;\u0026lt;\u0026thinsp;100%. This observation is consistent with the general absence of trout toxicity for these municipal effluents during regulatory compliance testing (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://open.canada.ca/data/en/dataset/471736af-e236-444a-9888-b4d99052c927\u003c/span\u003e\u003cspan address=\"https://open.canada.ca/data/en/dataset/471736af-e236-444a-9888-b4d99052c927\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). This provides evidence that the Per assay did not produce any false negative municipal effluents in respect to rainbow trout toxicity. Although the Per assay was significantly related with trout and \u003cem\u003eCeriodaphnia dubia\u003c/em\u003e survival tests (multiple regression r\u0026thinsp;=\u0026thinsp;0.65; p\u0026thinsp;=\u0026thinsp;0.02), positive results with Per and or the DNA protection assay should be confirmed at the fish/daphnid levels to further confirm the observed trend observed for industrial effluents (Gagn\u0026eacute; and Blaise, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e1997\u003c/span\u003e). Nevertheless, increased Per activity by enhancers could present a more long-term stress since these compounds are usually (geno)toxic in addition to the presence of endocrine disruption in domestic wastewaters. It is noteworthy that the untreated influents inhibited Per more strongly in smaller populated townships suggesting perhaps some limitation of basic municipal effluents. In respect to sublethal effects, SOD gene expression, involved in the production of H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e, was examined in rainbow trout hepatocytes exposed to municipal effluent extracts from 12 Canadia cities (Gagn\u0026eacute; et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Over 75% of the effluents produced changes in SOD gene expression indicating the production of reactive oxygen species and supporting the knowledge that municipal effluents produce oxidative stress in organisms. Compared to the untreated influents, SOD gene expression was increased in 3 of the tested effluents and that population and DOC were significantly related to SOD gene expression.\u003c/p\u003e \u003cp\u003eIt was noteworthy that the DNA protection assay revealed significant protection in 5/8 (63%) of the wastewaters providing evidence that municipal effluents are often genotoxic to aquatic organisms. This observation corroborates previous findings showing that municipal effluents from a primary and advanced biofiltration with secondary UV-treatment were equally genotoxic in fathead minnows exposed for 3 months to these effluents (Lacaze et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). This suggests that genotoxic compounds were impervious to differing water treatments and that the occurrence of DNA damaging compounds in relatively common in treated wastewaters. Genotoxicity calculations of the effluent of the Montreal (Quebec, Canada) revealed that it releases over 31 kg of benzo(a)pyrene equivalents per day using a bacterial DNA-repair assay- \u003cem\u003eSOS\u003c/em\u003e Chromotest (White and Rasmussen, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). Moreover, the data also revealed that 90% of the genotoxic loadings was nonindustrial in origin i.e., from domestic wastes and street runoffs. In a following study with mussels caged to the municipal dispersion plume of the City of Montreal for 1 month, DNA strand breaks were detected in hemocytes using the Comet assay (Lacaze et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). The genotoxicity of treated and untreated municipal effluents was also observed in \u003cem\u003eElliptio complanata\u003c/em\u003e mussels hemocytes exposed \u003cem\u003ein vitro\u003c/em\u003e to municipal effluent extracts (Gilroy et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The study revealed that genotoxicity persists following treatment in other municipalities suggesting the continuous release of genotoxic compounds in the aquatic environment.\u003c/p\u003e \u003cp\u003eIn conclusion, the water quality of municipal wastewaters was examined with the Per assay using a DNA protection variation. The study revealed that Per activity of wastewaters influents were influenced by population size and the wastewater treatment types. The more advanced treatments (biofiltration, membrane biofiltration, secondary aeration) produced stronger changes compared to the corresponding untreated influents. Per activity changes were also associated to the DOC, Pahs and plastic-like substances and nanoparticle loadings in the effluents. A positive relationship was observed with melamine suggesting that other reduced substances could act as substrates for Per as well and could explain in part interactions with DNA and perhaps genotoxicity. In conclusion, the data show that municipal effluents are generally not acutely lethal based on inhibitions of the Per activity but could in some instances increase Per activity leading to more long-term toxicity by the accumulation of oxidizes endogenous substrates. The DNA protection assay revealed that 60% of the effluents have genotoxic potential providing some evidence on the released of genotoxic compounds in aquatic ecosystems.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eDeclaration of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe authors declare no competing interests in the preparation and revision of this manuscript.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical Approval\u003c/strong\u003e \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe authors consent to publish\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo external funding\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eData available upon request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was funded by the Saint-Lawrence Action Plan and the Wastewater monitoring of Environment and Climate Change Canada. The helpful assistance of Joelle Auclair and Hiba Quichach in effluent preparation are recognized.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAas E, Beyer J, Goksoyr A 1995. PAHs in fish bile detected by fixed wavelength fluorescence. Mar. Environ. Res. 46, 225\u0026ndash;228.\u003c/li\u003e\n\u003cli\u003eAntunes SC, Nunes B, Rodrigues S, Nunes R, Fernandes J, Correia AT 2016. Effects of chronic exposure to benzalkonium chloride in \u003cem\u003eOncorhynchus mykiss\u003c/em\u003e: cholinergic neurotoxicity, oxidative stress, peroxidative damage and genotoxicity. Environ Toxicol Pharm 45, 115-122.\u003c/li\u003e\n\u003cli\u003eBrandstetter A, Sletten RS, Mentler A, Wenzel WW 1996. Estimating dissolved organic carbon in natural waters by UV absorbance (254 nm). J Plant Nut Soil Sci 159, 605-607.\u003c/li\u003e\n\u003cli\u003eBukh AS, Roslev P 2011. 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J Xenobiotics 9\u003cstrong\u003e,\u003c/strong\u003e 8147-8149.\u003c/li\u003e\n\u003cli\u003eGagn\u0026eacute; F, Auclair J, Quinn B 2019. Detection of polystyrene nanoplastics in biological samples based on the solvatochromic properties of Nile red: application in \u003cem\u003eHydra attenuata\u003c/em\u003e exposed to nanoplastics. Environ Sci Poll Res 26, 33524-33531.\u003c/li\u003e\n\u003cli\u003eGagn\u0026eacute; F, Smyth SA, Andr\u0026eacute; C, Douville M, G\u0026eacute;linas M, Barclay K 2013. Stress-related gene expression changes in rainbow trout hepatocytes exposed to various municipal wastewater treatment influents and effluents. Environ Sci Pollut Res 20, 1706\u0026ndash;1718\u003c/li\u003e\n\u003cli\u003eGilroy EAM, Kleinert C, Lacaze E, Campbell SD, Verbaan S, Andr\u0026eacute; C, Chan K, Gillis PL, Klinck JS, Gagn\u0026eacute; F, Fournier M, de Solla SR 2023. In vitro assessment of the genotoxicity and immunotoxicity of treated and untreated municipal effluents and receiving waters in freshwater organisms. Environ Sci Poll Res https://doi.org/10.1007/s11356-023-26845-1.\u003c/li\u003e\n\u003cli\u003eIlyina AD, Martinez Hernandez JL, 1 Lujan BHL, Benavides JEM, Garcia JR, Martinez JR1 2000. Water quality monitoring using an enhanced chemiluminescent assay based on peroxidase-catalyzed peroxidation of luminol. Appl Biochem Biotech 88, 45-58.\u003c/li\u003e\n\u003cli\u003eJaved M, Abbas K, Ahmed T, Abdullah S, Naz H, Amjad H 2020.Metal pollutants induced peroxidase activity in different body tissues of freshwater fish, \u003cem\u003eLabeo rohita\u003c/em\u003e. Environmental Chemistry and Ecotoxicology 2,162-167.\u003c/li\u003e\n\u003cli\u003eJurgelėnė Z, Stankevičiūtė M, Kazlauskienė N, Bar\u0026scaron;ienė J, Jok\u0026scaron;as K, Markuckas A 2019. Toxicological Potential of Cadmium Impact on Rainbow Trout (Oncorhynchus mykiss) in Early Development. Bull Environ Contam Toxicol 103, 544-550.\u003c/li\u003e\n\u003cli\u003eKurhaluk N 2019. Formation of an antioxidant profile in the sea trout (Salmo trutta m. trutta L.) from the Slupia River. Zoology (Jena) 133, 54-65.\u003c/li\u003e\n\u003cli\u003eLacaze E, Gauthier C, Couture P, Andr\u0026eacute; C, Cloutier F, Fournier M, Gagn\u0026eacute;, F 2017. The effects of municipal effluents on oxidative stress, immunocompetence and DNA integrity in fathead minnow juveniles. Cur Top Toxicol 13, 69-80.\u003c/li\u003e\n\u003cli\u003eLacaze E, Devaux A, Bony S, Bruneau A, Andr\u0026eacute; C, Pelletier M, Gagn\u0026eacute; F 2013. Genotoxic impact of a municipal effluent dispersion plume in the freshwater mussel \u003cem\u003eElliptio complanata\u003c/em\u003e: an \u003cem\u003ein situ\u003c/em\u003e study. J. Xenobiotics 3, e6.\u003c/li\u003e\n\u003cli\u003eLee YK, Hong S, Hur\u003cstrong\u003e J \u003c/strong\u003e2021 Copper-binding properties of microplastic-derived dissolved organic matter revealed by fluorescence spectroscopy and two-dimensional correlation spectroscopy. Water Res 190, 116775.\u003c/li\u003e\n\u003cli\u003eNiP, Dai H, Wang Y, Sun Y, Shi Y, Hu J, Li Z 2014. Visual detection of melamine based on the peroxidase-like activity enhancement of bare gold nanoparticles. Biosens Bioelectron 60, 286-291.\u003c/li\u003e\n\u003cli\u003eO\u0026rsquo;Brien P J 2000. Peroxidase. Chem-Biol Inter 129, 113-139. \u003c/li\u003e\n\u003cli\u003eRach JJ, Schreier TM, Howe GE, Redman SD 1997. Effect of Species, Life Stage, and Water Temperature on the Toxicity of Hydrogen Peroxide to Fish. The Progressive Fish culturist 59:41-46.\u003c/li\u003e\n\u003cli\u003eRodrigues S, Antunes SC, Correia AT, Nunes B2017. Rainbow trout (Oncorhynchus mykiss) pro-oxidant and genotoxic responses following acute and chronic exposure to the antibiotic oxytetracycline. Ecotoxicology 26, 104-117.\u003c/li\u003e\n\u003cli\u003eShalileh F, Sabahi H, Golbashy M, Dadmehr M, Hosseini M 2023. Recent developments in DNA nanostructure-based biosensors for the detection of melamine adulteration in milk. Microchemical J 195, 109316.\u003c/li\u003e\n\u003cli\u003eSchwarz M, L\u0026ouml;ser A, Cheng Q, Wichmann-Costaganna M, Sch\u0026auml;del P, Werz O, Arn\u0026eacute;r ES, Kipp AP. 2023. 2023. Side-by-side comparison of recombinant human glutathione peroxidases identifies overlapping substrate specificities for soluble hydroperoxides. Redox Biol 59:102593.\u003c/li\u003e\n\u003cli\u003eWhite PA, Rasmussen JB 1998. The genotoxic hazards of domestic wastes in surface waters. Mutation Research 410 1998 223\u0026ndash;236.\u003c/li\u003e\n\u003cli\u003eWhitehead, T. P., G. Thorpe, M. Lane, A. Watson, and C. Billings. 1993. A rapid and simple chemiluminescent assay for water quality and monitoring. Biol Perspect 377-381.\u003c/li\u003e\n\u003cli\u003eXu X, Lu J, Sheng H, Zhang L, Gan T, Zhang J, Xu Y, Zhu X, Yang J 2020. Evaluation of the cytotoxic and genotoxic effects by melamine and cyanuric acid co-exposure in human embryonic kidney 293 cells. Braz J Med Biol Res 53, e9331.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1. City characteristics\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"491\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.276422764227643%\" valign=\"top\"\u003e\n \u003cp\u003eTownships\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.682926829268293%\" valign=\"top\"\u003e\n \u003cp\u003ePopulation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.48780487804878%\" valign=\"top\"\u003e\n \u003cp\u003eTreatment\u003c/p\u003e\n \u003cp\u003eType\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.552845528455286%\" valign=\"top\"\u003e\n \u003cp\u003eDissolved organic carbon (mg/L)\u003c/p\u003e\n \u003cp\u003eInfluent \u0026nbsp; \u0026nbsp; \u0026nbsp; Effluent\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.276422764227643%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.682926829268293%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;1 214\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.48780487804878%\" valign=\"top\"\u003e\n \u003cp\u003eLagoon,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003efacultative aeration\u003c/p\u003e\n \u003cp\u003e(LagF)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.552845528455286%\" valign=\"top\"\u003e\n \u003cp\u003e1.28 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;1.046\u003c/p\u003e\n \u003cp\u003e\u0026plusmn;0.008 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026plusmn;0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.276422764227643%\" valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.682926829268293%\" valign=\"top\"\u003e\n \u003cp\u003e16\u0026nbsp;000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.48780487804878%\" valign=\"top\"\u003e\n \u003cp\u003eBiological\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eFiltration (Bio)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.552845528455286%\" valign=\"top\"\u003e\n \u003cp\u003e1.19 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;1.18\u003c/p\u003e\n \u003cp\u003e\u0026plusmn;0.11 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026plusmn;0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.276422764227643%\" valign=\"top\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.682926829268293%\" valign=\"top\"\u003e\n \u003cp\u003e33\u0026nbsp;761\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.48780487804878%\" valign=\"top\"\u003e\n \u003cp\u003eAdvanced\u003c/p\u003e\n \u003cp\u003eBiofiltration (Adv)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.552845528455286%\" valign=\"top\"\u003e\n \u003cp\u003e1.17 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 1.19\u003c/p\u003e\n \u003cp\u003e\u0026plusmn;0.09 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026plusmn;0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.276422764227643%\" valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.682926829268293%\" valign=\"top\"\u003e\n \u003cp\u003e119\u0026nbsp;360\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.48780487804878%\" valign=\"top\"\u003e\n \u003cp\u003eAeration\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eLagoons (Lag)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.552845528455286%\" valign=\"top\"\u003e\n \u003cp\u003e1.24 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 1.18\u003c/p\u003e\n \u003cp\u003e\u0026plusmn;0.1 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026plusmn;0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.276422764227643%\" valign=\"top\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.682926829268293%\" valign=\"top\"\u003e\n \u003cp\u003e129\u0026nbsp;500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.48780487804878%\" valign=\"top\"\u003e\n \u003cp\u003eLagoon,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003efacultative aeration (LagF)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.552845528455286%\" valign=\"top\"\u003e\n \u003cp\u003e1.07 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 1.04\u003c/p\u003e\n \u003cp\u003e\u0026plusmn;0.01 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026plusmn;0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.276422764227643%\" valign=\"top\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.682926829268293%\" valign=\"top\"\u003e\n \u003cp\u003e523\u0026nbsp;000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.48780487804878%\" valign=\"top\"\u003e\n \u003cp\u003eSecondary\u0026nbsp;\u003c/p\u003e\n \u003cp\u003emembrane bioreactor\u003c/p\u003e\n \u003cp\u003e(SecM)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.552845528455286%\" valign=\"top\"\u003e\n \u003cp\u003e1.25 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 1.1\u003c/p\u003e\n \u003cp\u003e\u0026plusmn;0.16 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.276422764227643%\" valign=\"top\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.682926829268293%\" valign=\"top\"\u003e\n \u003cp\u003e570\u0026nbsp;000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.48780487804878%\" valign=\"top\"\u003e\n \u003cp\u003eSecondary\u003c/p\u003e\n \u003cp\u003eAeration sludge (Sec)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.552845528455286%\" valign=\"top\"\u003e\n \u003cp\u003e1.46 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;1.18 \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026plusmn;0.15 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026plusmn;0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.276422764227643%\" valign=\"top\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.682926829268293%\" valign=\"top\"\u003e\n \u003cp\u003e1\u0026nbsp;800 000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.48780487804878%\" valign=\"top\"\u003e\n \u003cp\u003ePhysico-chemical\u003c/p\u003e\n \u003cp\u003e(Prim)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.552845528455286%\" valign=\"top\"\u003e\n \u003cp\u003e1.26 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;1.23\u003c/p\u003e\n \u003cp\u003e\u0026plusmn;0.16 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026plusmn;0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 2 Relative levels of light, medium and heavy PAHS and melamine in wastewaters.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.656500802568218%\" valign=\"top\"\u003e\n \u003cp\u003eTreatment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.459069020866774%\" valign=\"top\"\u003e\n \u003cp\u003eHumic/fulvic acids (RFU)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.051364365971107%\" valign=\"top\"\u003e\n \u003cp\u003eLight PAHs\u003c/p\u003e\n \u003cp\u003e\u0026micro;g/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.014446227929373%\" valign=\"top\"\u003e\n \u003cp\u003eMedium PAHs\u003c/p\u003e\n \u003cp\u003e\u0026micro;g/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.37239165329053%\" valign=\"top\"\u003e\n \u003cp\u003eHeavy PAHs\u003c/p\u003e\n \u003cp\u003e\u0026micro;g/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.446227929373997%\" valign=\"top\"\u003e\n \u003cp\u003eMelamine\u003c/p\u003e\n \u003cp\u003e\u0026micro;g/L\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.656500802568218%\" valign=\"top\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.459069020866774%\" valign=\"top\"\u003e\n \u003cp\u003e0.9\u0026plusmn;0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.051364365971107%\" valign=\"top\"\u003e\n \u003cp\u003e33\u0026plusmn;6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.014446227929373%\" valign=\"top\"\u003e\n \u003cp\u003e4.5\u0026plusmn;0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.37239165329053%\" valign=\"top\"\u003e\n \u003cp\u003e0.23\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.446227929373997%\" valign=\"top\"\u003e\n \u003cp\u003e1\u0026plusmn;0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.656500802568218%\" valign=\"top\"\u003e\n \u003cp\u003eLagF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.459069020866774%\" valign=\"top\"\u003e\n \u003cp\u003e0.74\u0026plusmn;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.051364365971107%\" valign=\"top\"\u003e\n \u003cp\u003e8\u0026plusmn;0.8*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.014446227929373%\" valign=\"top\"\u003e\n \u003cp\u003e1.2\u0026plusmn;0.09*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.37239165329053%\" valign=\"top\"\u003e\n \u003cp\u003e0.20\u0026plusmn;0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.446227929373997%\" valign=\"top\"\u003e\n \u003cp\u003e0.4\u0026plusmn;0.04*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.656500802568218%\" valign=\"top\"\u003e\n \u003cp\u003eAdv\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.459069020866774%\" valign=\"top\"\u003e\n \u003cp\u003e0.87\u0026plusmn;0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.051364365971107%\" valign=\"top\"\u003e\n \u003cp\u003e13\u0026plusmn;4*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.014446227929373%\" valign=\"top\"\u003e\n \u003cp\u003e2.7\u0026plusmn;0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.37239165329053%\" valign=\"top\"\u003e\n \u003cp\u003e0.5\u0026plusmn;0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.446227929373997%\" valign=\"top\"\u003e\n \u003cp\u003e0.8\u0026plusmn;0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.656500802568218%\" valign=\"top\"\u003e\n \u003cp\u003eBio\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.459069020866774%\" valign=\"top\"\u003e\n \u003cp\u003e1.8\u0026plusmn;0.4*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.051364365971107%\" valign=\"top\"\u003e\n \u003cp\u003e57\u0026plusmn;12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.014446227929373%\" valign=\"top\"\u003e\n \u003cp\u003e10\u0026plusmn;1*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.37239165329053%\" valign=\"top\"\u003e\n \u003cp\u003e0.3\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.446227929373997%\" valign=\"top\"\u003e\n \u003cp\u003e0.3\u0026plusmn;0.04*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.656500802568218%\" valign=\"top\"\u003e\n \u003cp\u003eSec\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.459069020866774%\" valign=\"top\"\u003e\n \u003cp\u003e0.7\u0026plusmn;0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.051364365971107%\" valign=\"top\"\u003e\n \u003cp\u003e28\u0026plusmn;6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.014446227929373%\" valign=\"top\"\u003e\n \u003cp\u003e7\u0026plusmn;2.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.37239165329053%\" valign=\"top\"\u003e\n \u003cp\u003e0.53\u0026plusmn;0.1*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.446227929373997%\" valign=\"top\"\u003e\n \u003cp\u003e11\u0026plusmn;2*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.656500802568218%\" valign=\"top\"\u003e\n \u003cp\u003eLag\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.459069020866774%\" valign=\"top\"\u003e\n \u003cp\u003e0.8\u0026plusmn;0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.051364365971107%\" valign=\"top\"\u003e\n \u003cp\u003e28\u0026plusmn;0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.014446227929373%\" valign=\"top\"\u003e\n \u003cp\u003e1.8\u0026plusmn;0.1*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.37239165329053%\" valign=\"top\"\u003e\n \u003cp\u003e0.3\u0026plusmn;0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.446227929373997%\" valign=\"top\"\u003e\n \u003cp\u003e6.2\u0026plusmn;1.8*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.656500802568218%\" valign=\"top\"\u003e\n \u003cp\u003eSecM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.459069020866774%\" valign=\"top\"\u003e\n \u003cp\u003e0.49\u0026plusmn;0.2*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.051364365971107%\" valign=\"top\"\u003e\n \u003cp\u003e3.8\u0026plusmn;0.8*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.014446227929373%\" valign=\"top\"\u003e\n \u003cp\u003e1.3\u0026plusmn;0.4*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.37239165329053%\" valign=\"top\"\u003e\n \u003cp\u003e0.07\u0026plusmn;0.02*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.446227929373997%\" valign=\"top\"\u003e\n \u003cp\u003e21\u0026plusmn;2*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.656500802568218%\" valign=\"top\"\u003e\n \u003cp\u003ePrim\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.459069020866774%\" valign=\"top\"\u003e\n \u003cp\u003e0.37\u0026plusmn;0.1*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.051364365971107%\" valign=\"top\"\u003e\n \u003cp\u003e20\u0026plusmn;6*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.014446227929373%\" valign=\"top\"\u003e\n \u003cp\u003e3\u0026plusmn;0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.37239165329053%\" valign=\"top\"\u003e\n \u003cp\u003e0.12\u0026plusmn;0.03*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.446227929373997%\" valign=\"top\"\u003e\n \u003cp\u003e0.15\u0026plusmn;0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e* significant from the influents (before treatments; None).\u003c/p\u003e\n\u003cp\u003eNa: not analyzed.\u003c/p\u003e\n\u003cp\u003eTable 3. Plastic nanoparticles and related materials\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003eTreatments\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003ePsNPs\u003c/p\u003e\n \u003cp\u003e\u0026micro;g/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003ePP\u003c/p\u003e\n \u003cp\u003e\u0026micro;g/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003eExtended PS/PVC\u003c/p\u003e\n \u003cp\u003e\u0026micro;g/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003eNR 600 nm\u003c/p\u003e\n \u003cp\u003e\u0026micro;g/L\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e1.7\u0026plusmn;0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e0.07\u0026plusmn;0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e0.077\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e0.066\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003eLagF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e1.1\u0026plusmn;0.1*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e1\u0026plusmn;0.3*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e0.04\u0026plusmn;0.01*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e0.11\u0026plusmn;0.03*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003eAdv\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e2.5\u0026plusmn;0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e0.01\u0026plusmn;0.005*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e0.05\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e0.06\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003eBio\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e0.65\u0026plusmn;0.3*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n 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\u003cp\u003eLag\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e1\u0026plusmn;0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e0.02\u0026plusmn;0.005*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e0.077\u0026plusmn;0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e0.09\u0026plusmn;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003eSecM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e2.3\u0026plusmn;0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e0.006\u0026plusmn;0.002*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e0.075\u0026plusmn;0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e0.11\u0026plusmn;0.036\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003ePrim\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e0.7\u0026plusmn;0.2*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e0.09\u0026plusmn;0.002*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e0.031\u0026plusmn;0.006*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e0.085\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"peroxidase, DNA protection, wastewater quality, dissolved organic matter, plastics","lastPublishedDoi":"10.21203/rs.3.rs-4547007/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4547007/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe peroxidase (Per) reaction is a quick and inexpensive biosensor for the screening of environmental contaminants. The purpose of this study was to screen various municipal wastewaters before and after 7 different types of treatment processes. Wastewater samples before (influents) and after the following treatments (effluent) were tested using the Per activity test: advanced biofiltration, biofiltration, aerated lagoons, secondary aeration sludge, trickling filter, secondary membrane filtration, and primary. The influents and effluents were collected for 3 days composites and concentrated to 500 X on a reverse-phase (C18) extraction cartridge. The ethanol extracts were examined for dissolved organic carbon, plastic-like materials, polyaromatic hydrocarbons and polystyrene nanoplastics. The samples were then tested using the Per reaction alone and in the presence of DNA to detect DNA binding agents. The result show that population size tended to increase Per activity and 60% of the effluents decreased Per activity leading to H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e persistence. More advanced treatments (biofiltration, membrane biofiltration, secondary aeration) produced stronger changes from the corresponding untreated influents. The addition of DNA during the Per reaction revealed that population size had no influence and that significant changes occurred in 60% of treated effluents suggesting release of genotoxic compounds in the aquatic environment by most treated wastewaters. The toxic implications of these results to aquatic organisms are discussed.\u0026nbsp; \u0026nbsp;\u003c/p\u003e","manuscriptTitle":"Screening of municipal effluents with the peroxidase toxicity assay","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-19 08:24:19","doi":"10.21203/rs.3.rs-4547007/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"4173b216-d7d0-4242-b5a7-6cb051367736","owner":[],"postedDate":"July 19th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-10-07T09:23:07+00:00","versionOfRecord":[],"versionCreatedAt":"2024-07-19 08:24:19","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4547007","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4547007","identity":"rs-4547007","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}