Science of the Total Environment 601–602 (2017) 230–236 Contents lists available at ScienceDirect Science of the Total Environment j ourna l homepage: www.e lsev ie r .com/ locate /sc i totenv Quantifying the contribution of dyes to themutagenicity of waters under the influence of textile activities Francine Inforçato Vacchi a,b, Josiane Aparecida de Souza Vendemiatti b, Bianca Ferreira da Silva c, Maria Valnice Boldrin Zanoni c, Gisela de Aragão Umbuzeiro a,b,⁎ a Faculty of Pharmaceutical Sciences, University of São Paulo, USP, São Paulo, SP, Brazil b School of Technology, State University of Campinas, UNICAMP, Limeira, SP, Brazil c Institute of Chemistry, State University of São Paulo UNESP, Araraquara, SP, Brazil H I G H L I G H T S G R A P H I C A L A B S T R A C T • Six disperse dyes were detected in the tested environmental samples. • Highest mutagenic potency was found in Piracicaba River downstream. • Disperse dyes contributed up to 44% to the observed mutagenicity. • Combination of chemical analysis and bioassays identified new priority pollut- ants. ⁎ Corresponding author at: School of Technology, State E-mail address: giselau@ft.unicamp.br (G.A. Umbuzeir http://dx.doi.org/10.1016/j.scitotenv.2017.05.103 0048-9697/© 2017 Elsevier B.V. All rights reserved. a b s t r a c t a r t i c l e i n f o Article history: Received 31 March 2017 Received in revised form 9 May 2017 Accepted 11 May 2017 Available online 26 May 2017 The combination of chemical analyses and bioassays allows the identification of potentially mutagenic com- pounds in different types of samples. Dyes can be considered as emergent contaminants and were detected in waters, under the influence of textile activities. The objective of this study was to evaluate the contribution of 9 azo dyes to the mutagenicity of representative environmental samples. Samples were collected along one year in the largest conglomerate of textile industries of Brazil. We analyzed water samples from an important water body, Piracicaba River, upstream and downstream twomain discharges, the effluent of awastewater treat- ment plant (WWTP) and the tributary Quilombo River, which receives untreated effluent from local industries. Samples were analyzed using a LC-MS/MS and tested for mutagenicity in the Salmonella/microsome microsuspension assay with TA98 and YG1041. Six dyes were detected in the collected samples, Disperse Blue 291, Disperse Blue 373, Disperse Orange 30, Disperse Red 1, Disperse Violet 93, and Disperse Yellow 3. The most sensitive condition for the detection of the mutagenicity was the strain YG1041 with S9. The concentration of dyes and mutagenicity levels varied along time and the dry season represented the worst condition. Disperse Blue 373 andDisperse Violet 93were themajor contributors to themutagenicity.We conclude that dyes are con- tributing for the mutagenicity of Piracicaba River water; and both discharges, WWTP effluent and Quilombo River, increase themutagenicity of Piracicaba Riverwaters in about 10-fold. The combination of chemical analysis and bioassays were key in the identification the main drivers of the water mutagenicity and allows the selection Keywords: Dyes Mutagenicity Salmonella/microsome assay Surface water University of Campinas, Limeira, SP, Brazil. o). http://crossmark.crossref.org/dialog/?doi=10.1016/j.scitotenv.2017.05.103&domain=pdf http://dx.doi.org/10.1016/j.scitotenv.2017.05.103 mailto:giselau@ft.unicamp.br Journal logo http://dx.doi.org/10.1016/j.scitotenv.2017.05.103 Unlabelled image http://www.sciencedirect.com/science/journal/00489697 www.elsevier.com/locate/scitotenv 231F.I. Vacchi et al. / Science of the Total Environment 601–602 (2017) 230–236 of priority compounds to be included inmonitoring programs aswell for the enforcing actions required to protect the water quality for multiple uses. © 2017 Elsevier B.V. All rights reserved. 1. Introduction The combination of chemical analyses and bioassays, such as Effect Directed Analysis (EDA) allows the identification of mutagenic com- pounds in different types of samples (Brack, 2003). This approach is very interesting for water quality monitoring because the biological tools can be selected based on their ability to detect specific effects and their biological significance. This strategy can identify river basin priority pollutants that are not included in monitoring programs (Brack et al., 2016). Bioassays, such as the Salmonella/microsome mutagenicity assay, produce an interesting response to a complex mixture evaluation with- out prior knowledge of the chemical sample composition (Claxton et al., 2004). Because the test can be performedwith strains containing differ- ent mutation targets and metabolic capacities it allows the identifica- tion of several classes of mutagens which would not be identified by targeted chemical analysis (Umbuzeiro et al., 2011; Umbuzeiro et al., 2016). This assay is also considered an important bioanalytical tool and the responses can be linked to specific adverse outcome pathways when the ultimate goal is to protect the quality of the environment at the population level (Altenburger et al., 2015). Several studies have identified water contaminants when applied the combination of chem- ical analysis and the Salmonella assay (Gallampois et al., 2013; Liu et al., 2015; Muz et al., 2017; Umbuzeiro et al., 2005b). Themost used organic dyes for textiles contain an azo group in their structure (Bafana et al., 2011) and several are genotoxic and mutagenic in mammalian and bacterial tests (Chequer et al., 2009; Josephy et al., 2016; Oliveira et al., 2010; Rajaguru et al., 1999; Tsuboy et al., 2007; Umbuzeiro et al., 2005a). Recently, azo dyes were identified as predom- inant brominated compounds in house dust and also exhibit mutagenic responses at environmentally relevant concentrations (Peng et al., 2016). Waters containing textile discharges can exhibit genotoxic and mutagenic activity that has been related to the presence of certain dyes and aromatic amines (Oliveira et al., 2007; Umbuzeiro et al., 2005b). However, in the case study of the Cristais River, mutagenic dyes were detected but not quantified and it was not possible to know their contribution in the mutagenicity of the river water (Umbuzeiro et al., 2005b). Considering this, the objective of this studywas to identify selected azo dyes in environmental samples following textile discharges and to verify their contribution to the mutagenicity of those samples. 2. Materials and methods 2.1. Study area and sampling The biggest pole of textile industries of Brazil is located in Americana city, São Paulo state. Piracicaba River, one of the most important rivers in São Paulo, is the main receiving water body for the liquid effluents generated by the industries. At the same time the river quality is protected by law and must be preserved for multiple uses, including aquatic life protection and human consumption. A wastewater treat- ment plant (WWTP) is responsible for the collection and treatment of several of the industrial effluents from the textile pole. It uses a biolog- ical treatment and the final effluent is discharged into the Piracicaba River. Unfortunately, this type of biological treatment alone is not effi- cient for the removal of disperse dyes (USEPA, 1990), so it is possible that dyes would remain in the final effluent. Furthermore, the capacity of the WWTP is not sufficient to treat all industrial effluents generated in the area, and several textile factories discharge their effluents, without proper treatment, directly to a tributary of Piracicaba River, called Quilombo. Four sampling campaigns were performed in April, June, August and October of 2013. Samples were collected from the WWTP outflow, Quilombo River and Piracicaba River, upstream and downstream the discharges (Fig. 1). Samples (4 l) were collected using amber glass flasks, transported to the laboratory on ice and imme- diately processed (APHA, 1999). 2.2. Liquid–liquid extraction/concentration procedures Water samples were liquid-liquid extracted using dichloromethane (DCM) andmethanol (2.5:1) as already adopted in other related textile studies (Umbuzeiro et al., 2004). Extracts were rotary evaporated and completely dried with purified nitrogen gas. Extracts were carefully kept frozen and stored in amber vials. For themutagenicity tests the sol- vent was exchanged. Adequate volumes of dimethyl sulfoxide (DMSO) were added to the extracts previous diluted in DCM and then DCM was completely evaporated using purified nitrogen gas. 2.3. HPLC-MS/MS analysis Chemical analyses were performed on the same extracts tested for mutagenicity. Analysis were conducted in a High Performance Liquid Chromatography (HPLC) Agilent 1200 system (Waldbronn, Germany) coupled to an AB Sciex 3200 QTRAP hybrid triple quadrupole/linear ion trap mass spectrometer (MS). Extracts were completely dried using purified nitrogen gas and re-suspended in methanol:water (50:50, v/v) containing 0.1% formic acid. Chromatographic separation was performed in Kinetex PFP analytical column (150 mm × 4.6 mm; 5 μm, Phenomenex). As mobile phase water (A) and acetonitrile (B), spiked with 0.1% formic acid, were used at a flow rate of 1.5 mL min−1 and a gradient program for water/acetonitrile: 0–1 min, 5% B; 1–5.5 min, 5–9% B; 5.5–6.5 min, 9–25% B; 6.5–9.5 min, 25–40% B; 9.5–11.5 min, 40–45.5% B; 11.5–16.5 min, 45.5–60.5% B; 16.5– 18.5 min, 60.5–100% B, 18.5–23 min, 100% B and re-established by 5% B over 7 min. Column temperature was set to 40 °C, injection volume was 20 μL, and total run length was 30 min. The 3200 QTRAP was coupled to the chromatographic apparatus via an electrospray ioniza- tion (ESI) source operating in positive ion mode with specific parame- ters: spray voltage, 5500 V; capillary temperature, 650 °C; the nebulizing gas (nitrogen, 45 psi); the heating gas (nitrogen, 45 psi) and the curtain gas, 15 psi. Selected reaction monitoring (SRM) mode, with two SRM transitions to eliminate false results were used in the identification of the compounds of interest. Fragmentation parameters were optimized by direct infusion of individual compounds solutions at 0.1 mg L−1 in methanol/water (50:50, v/v) containing 0.1% formic acid, using a flow of 10 μL min−1. In this step, the following parameters were analyzed: Collision Energy (CE), Declustering Potential (DP), En- trance Potential (EP), Cell Entrance Potential (CEP) and Collision Cell Exit (CXP). All properties and parameters of each compound analyzed are summarized in Table 1 and chromatograms are available at Supple- mentary Material. The instrumental limit of detection (LOD) and limit of quantification (LOQ) were defined as the minimum amount of the selected compound analyzed by LC-MS/MS considering the signal-to-noise (S/N) ratio of 3 and a S/N of 10, respectively. The compounds were identified by their re- tention times and their specific SRM transitions. The validation protocol was adapted based on criteria accepted by different institutions (APHA, 1999; USEPA, 1997). The adaptation of different validation guides was Fig. 1. Sampling sites in Americana city, São Paulo state, Brazil: Piracicaba River upstream (A), Quilombo River (B), wastewater treatment plant (C) and Piracicaba River downstream (D). 232 F.I. Vacchi et al. / Science of the Total Environment 601–602 (2017) 230–236 necessary due to the lack of specific guides for analyzing textile dyes in aqueous samples. Analytical curves with five different concentrations were constructed by standard spiking, using triplicate for all points. The calibration curve was obtained by plotting the area of the chro- matographic band of each dye versus the standard analyte concentra- tion (river water spiked to each standard). Standards and MeOH blanks were injected periodically to ensure that the instrument re- sponse was not drifting and that the blanks were free of the analytes. Recoveries (percent of standard added to sample thatwas recovered following extraction) were obtained by spiking river water samples be- fore and after extraction in three different concentrations in triplicate. Laboratory blanks and laboratory-fortified blanks were also evaluated to ensure that the analytical method and laboratory equipment were free from outside contamination and to compare recoveries. The study of recovery (Rec) was performed according to the equation Rec (%) = (A/B) × 100, where A refers to the area of the spiked sample prior to ex- traction and B the analyte area in the post-extraction spiked sample. Table 1 Properties and parameters of each disperse azo dye analyzed by HLPC-MS/MS, using SRM mod Compounds CAS number Supplier/purity Chemical structure Retention tim (min) Disperse Blue 291 56548-64-2 Shanghai Orgchem Co. Ltd./95% 19.2 Disperse Blue 373 51868-46-3 Shanghai Orgchem Co. Ltd./95% 19.1 Disperse Orange 1 2581-69-3 Sigma Aldrich/96% 18.5 Disperse Orange 30 12223-23-3 Shanghai Orgchem Co. Ltd./95% 17.5 Disperse Orange 37 13301-61-6 Sigma Aldrich/96% 18.3 Disperse Red 1 2872-52-8 Sigma Aldrich/95% 15.1 Disperse Violet 93 52697-38-8 Shanghai Orgchem Co. Ltd./95% 18.7 Disperse Yellow 3 2832-40-8 Sigma Aldrich/96% 13.8 Disperse Yellow 7 6300-37-4 Sigma Aldrich/95% 18.1 SRM: selected reaction monitoring; MS: mass spectrometer; CE: collision energy; DP: decluste 2.4. Salmonella/microsome microsuspension assay The microsuspension protocol of the Salmonella/microsome assay was used because of its high sensitivity (Kado et al., 1983). Because the strain TA98 has been the most used in monitoring studies and pro- vides the majority of the positive responses for surface water testing (Ohe et al., 2004; Umbuzeiro et al., 2001) we included it in this study. We also selected the strain YG1041 (a derivative of the TA98 that over- produces nitroreductase and O-acetyltransferase) (Hagiwara et al., 1993) because it has proven to be very sensitive to the detection of mu- tagenicity of textile plant effluents containing azo dyes (Freeman, 2013; Oliveira et al., 2006; Umbuzeiro et al., 2005b). If nitroaromatics or aro- matic amines are contributing to themutagenic response of the sample, an increase in the responsewith YG1041 in relation to its parental strain TA98, is expected. For nitroaromatics the increased response would be obtained without S9 and for aromatic amines, in the presence of S9 (Umbuzeiro et al., 2011). e. e SRM MS/MS Precursor ion (m/z) Fragment ion (m/z) Dwell time (ms) DP (V) EP (V) CEP (V) CE (V) CXP (V) 511 207 5 56 8.5 22 39 4 511 192 5 56 8.5 22 47 4 533 260.4 5 66 5 24 25 4 533 245.4 5 66 5 24 33 4 319 169.2 5 56 4 24 35 4 319 122.2 5 56 4 24 29 4 450 87 5 46 7.5 24 49 4 450 132 5 46 7.5 24 33 4 392 351 5 51 5 32 21 6 392 133 5 51 5 32 51 4 315 134 5 51 4 24 33 4 315 255 5 51 4 24 29 4 481 191 5 56 7.5 20 37 4 481 206 5 56 7.5 20 25 4 270.2 107.2 5 41 5.5 18 33 4 270.2 108.1 5 41 5.5 18 39 4 317.1 77 5 51 4 22 47 4 317.1 105.1 5 51 4 22 29 4 ring potential; EP: entrance potential: CEP: cell entrance potential; CXP: collision cell exit. Image of Fig. 1 Unlabelled image 233F.I. Vacchi et al. / Science of the Total Environment 601–602 (2017) 230–236 We tested six doses 0.07 to 40ml equivalent/plate in duplicates. We included negative, solvent and positive controls. Salmonella cultures were centrifuged at 10,000g at 4 °C for 10 min and re-suspended in 0.015 M sodium phosphate buffer. We employed as exogenous meta- bolic activation system using 4% (v/v) Aroclor-1254-induced rat liver S9 fraction (Moltox Inc., Boone, NC) and cofactors. Volumes of 5 μl of each extract were incubated at 37 °C for 90 min without shaking with 50 μl of cell suspension, 50 μl of 0.015 M sodium phosphate buffer (or S9 mix). After addition of the top agar, plates were incubated at 37 °C for 72 h. Colonies were manually counted under a stereoscope. Visual observation of the background under a stereoscope was used to evalu- ate toxicity. Positive controls for TA98 were 0.125 μg/plate of 4- nitroquinoline-oxide (4NQO) (Sigma-Aldrich) without S9 and 0.625 μg/plate of 2-aminoanthracene (2AA) (Sigma-Aldrich) with S9, both dissolved in DMSO. For YG1041, 2.5 μg/plate of 4-nitro-o- phenylenediamine (4NOP) (Sigma-Aldrich) without S9 and 0.03125 μg/ plate of 2-aminoanthracene (2AA) (Sigma-Aldrich) with S9, dissolved in DMSO. Data were statistically analyzed using an ANOVA followed by linear regression using the Bernstein model (Bernstein et al., 1982). Samples were considered positive when significant ANOVA (p b 0.05) and positive dose responses were obtained (p b 0.05). 3. Results & discussion 3.1. Chemical analysis The methodology developed in this study was efficient for separa- tion and identification of dyes in environmental matrices, since 6 differ- ent dyes were detected and quantified in the samples, Disperse Blue 291, Disperse Blue 373, DisperseOrange 30, Disperse Red 1, Disperse Vi- olet 93, and Disperse Yellow 3, in the range of 0.01 to 6.81 μg L−1 (Table 2). All the values are in the interval of acceptable recoveries, from 70 to 120% (APHA, 1999; USEPA, 1997), except for Disperse Blue 373 and Dis- perse Orange 37, which presented higher recoveries. Because the focus of the work was to apply a method able to analyze all the target dyes at the same time, use the same extracts to test for mutagenicity and verify their contribution we accepted recoveries that were out of the recom- mended interval for those dyes (Table 2). Disperse Orange 1, Disperse Orange 37 and Disperse Yellow 7 were not quantified in any sample because their concentrations were lower than their respective detection limits (LOD). The other disperse dyes were detected at least one time during the study (Table 2). Disperse Red 1, Disperse Blue 373 and Disperse Violet 93 dyes were also found Table 2 Recovery (%), limits (μg L−1), concentrations (μg L−1) and frequency (%) of azo dyes analyzed Dyes Recovery (%) Limits (μg L−1) Sampling 1 (μg L−1) Samp LOD LOQ A B C D A B Disperse Blue 291 107 0.0022 0.0075 – – – – – – Disperse Blue 373 130 0.0016 0.0054 – – 0.35 – – – Disperse Orange 1 89 0.0022 0.0072 – – – – – – Disperse Orange 30 70 0.0128 0.0427 – – – – – – Disperse Orange 37 166 0.0136 0.0228 – – – – – – Disperse Red 1 120 0.0003 0.0010 0.52 – 0.03 – – – Disperse Violet 93 91 0.0064 0.0214 – 0.08 – – – 0 Disperse Yellow 3 89 0.0020 0.0066 – – – – – – Disperse Yellow 7 81 0.0010 0.0032 – – – – – – – bLOD. LOD: limit of detection. LOQ: limit of quantification. A: Piracicaba River upstream. B: Quilombo River. C: WWTP effluent. D: Piracicaba River downstream. in waters under the influence of textile discharges in previous studies (Umbuzeiro et al., 2005b; Zocolo et al., 2015). The sampling campaign performed during the dry season (Sampling 3 - August/2013), was themost representative of the study. In this cam- paign six dyes of the nine target dyeswere found and in the highest con- centrations. These findings highlight the importance of collecting different samples along time to have a reliable study. The fact that the samples from the dry season were the most mutagenic corroborates with the conclusion that the industrial discharges are in fact the main drivers of the mutagenicity of Piracicaba River. When mutagenicity is higher in the wet season it can be related to runoff and not to point sources discharges, which is the case of our study (Valent et al., 1993). 3.2. Salmonella/microsome microsuspension assay The same organic extracts that were chemically analyzed were test- ed for mutagenicity with Salmonella strains TA98 and YG1041, in the presence and absence of exogenous metabolic activation (S9). TA98 is the most used strain in water mutagenicity studies and responsible for the majority of the positive responses (Ohe et al., 2004; Watanabe et al., 2006; 2002). But in our study all samples presented a negative re- sponse with and without S9 for this strain except for one sample from Quilombo River. This sample was positive with TA98 without S9 (Table 3) with a mutagenic potency of 5,500 rev L−1. Umbuzeiro et al. (2001) developed a surface water mutagenicity classification based on the responses of TA98 and TA100, which was also applied by Ohe et al. (2004). This sample is classified as extremely mutagenic (N5,000 rev L−1) revealing a high level of contamination of this water body. When the YG1041 strain was applied, the mutagenicity was detect- ed in 15 of the 16 samples analyzed, with higher responses with S9 (Table 3). This fact suggests that aromatic amines or compounds con- taining amino groups such as some of our target dyes (Table 2) could be responsible for at least part of the observedmutagenicity. The poten- cies of the Piracicaba River sampleswere compared to the ones found in the Cristais River, São Paulo, Brazil that was also impacted with textile discharges (Umbuzeiro et al., 2005b) and tested with YG1041. The po- tencies observed for Piracicaba River were 10 to 100 times higher than the ones reported for Cristais River. The tributary Quilombo River and the WWTP effluent presented, on average, samples 10 times more po- tent than Piracicaba River downstream therefore both discharges are contributing to the increase in the mutagenicity observed in Piracicaba River (Fig. 2). in environmental samples. ling 2 (μg L−1) Sampling 3 (μg L−1) Sampling 4 (μg L−1) Frequency (%)C D A B C D A B C D – – 0.04 – 0.05 – – – – – 12.50 0.08 – – 1.38 0.15 3.13 – 0.54 – 0.28 43.75 – – – – – – – – – – 0 – – – 0.14 – – – – – – 6.25 – – – – – – – – – – 0 0.19 – – 0.09 0.08 0.11 – 0.15 – 0.13 50.00 .08 – – – 2.81 – 6.81 – – – – 25.00 – – – 0.01 – 0.03 – 0.41 – 0.02 25.00 – – – – – – – – – – 0 Table 3 Mutagenic potencies (rev L−1) of environmental samples tested with strains TA98 and YG1041, without (‐\\S9) and with (+S9) metabolic activation. TA98 (rev L−1) YG1041 (rev L−1) –S9 +S9 –S9 +S9 Sampling 1 A 0 0 6,000 4,000 B 0 0 0 68,000 C 0 0 0 145,000 D 0 0 9,000 10,000 Sampling 2 A 0 0 30,000 13,000 B 0 0 2,000 34,000 C 0 0 82,000 65,000 D 0 0 41,000 28,000 Sampling 3 A 0 0 3,000 0 B 5,500 0 5,800 50,550 C 0 0 0 85,000 D 0 0 3,400 149,000 Sampling 4 A 0 0 8,000 0 B 0 0 0 0 C 0 0 0 37,000 D 0 0 21,000 11,000 A: Piracicaba River upstream. B: Quilombo River. C: WWTP effluent. D: Piracicaba River downstream. 234 F.I. Vacchi et al. / Science of the Total Environment 601–602 (2017) 230–236 3.3. Contribution of target dyes to the observed mutagenicity We calculated the individual contributions of the analyzed dyes con- sidering their concentration in each sample and their respective muta- genic potencies in the most mutagenic scenario (YG1041 with S9) (Table 4). Mutagenic potencies of Disperse Blue 291, Disperse Blue 373, Disperse Violet 93 and Disperse Red 1 were previously published for YG1041 and their potencies with S9 are 180; 6,300; 4,600 and 207 rev μg−1, respectively (Umbuzeiro et al., 2005a, 2005b; Vacchi et al., 2013). No mutagenicity data was found in the literature for the other two dyes detected in the analyzed samples. Therefore, we tested Disperse Orange 30 and Disperse Yellow 3 with the strain YG1041 and their potencies with S9were 5.9 and 5.5 rev μg−1, respectively (Supple- mentary Material). Disperse Red 1, despite being the most frequent dye detected in the samples, contributed only with 0.004 to 2.7% of the mutagenicity. But the importance of Disperse Red 1 as an aquatic contaminant should Fig. 2.Mutagenic potencies (rev L−1) for YG1041, with S9, of Piracicaba River upstream, Quilombo River, WWTP effluent and Piracicaba River downstream. not be overruled. Its concentrations, in both Piracicaba and Quilombo rivers were detected above 60 ng L−1, the Predicted No-Effect Concen- tration (PNEC) derived by Vacchi et al. (2016b) representing a potential risk to the local biota. Disperse Blue 373 and Disperse Violet 93 were the major contribu- tors to the mutagenicity in Quilombo River, WWTP effluent and Piracicaba River downstream (up to 17.2 and 25.6%, respectively) (Table 4) and indeed they have substituted amines in their structure confirming the mutagenic type of response obtained for the analyzed samples. Dyes were found in the WWTP effluents as expected but showed a small contribution to the mutagenicity in comparison to Quilombo River. The high potencies observed for the WWTP samples could be attributed to their breakdown products generates during the treatment process. In fact, Vacchi et al. (2016a) quantified severalmuta- genic aromatic amines in the same samples but it was not possible to calculate their contribution because the respectivemutagenic potencies were not available. Several authors have used the combination of chemical analyses and bioassays in water and sediment samples to determine which com- pounds were causing the observed effect such as in Effect-Directed Analysis (EDA) (Brack et al., 2016). These studies usually include a frac- tionation step of the samples based on their different physicochemical properties, followed by bioassays to reduce the chemical complexity of fractions and facilitate chemical analysis (Brack, 2003). Highly potent nitro-PAHs such as dinitropyrene (DNP) isomers, 3-nitrobenzanthrone (3-NBA) and nitrobenzo[a]pyrenes have been detected in samples of sediment in an industrial area in Germany and, in some fractions of the samples, 1,8-DNP and 3-NBA explained together N70% of the muta- genicity (50% 1,8-DNP and 21% 3-NBA) (Lübcke-von Varel et al., 2012). In our work, we didn't apply a fractionation step but we could explain N40% of the mutagenicity by using strains with different sensitivities combined with the previous knowledge of the possible chemical com- pounds present in the samples according to the discharge source. This approach has also been successfully applied by Muz et al. (2017) en- abling the discovery of new mutagenic compounds in the Danube River in Europe. It is very important to identify the major compounds that are caus- ing mutagenicity in water bodies, because this provides an opportunity to define new specificwater basin priority pollutants that can be includ- ed in the monitoring programs. Although there are no cut off values for mutagenicity in surface waters, this type of study provides the basis for enforcement actions to reduce the mutagenic sources minimizing the exposure of humans and biota in rivers with multiple uses, such as Piracicaba River. 4. Conclusion Of the nine selected dyes, six were found in the studied area, Dis- perse Blue 291, Disperse Blue 373, Disperse Orange 30, Disperse Red 1, Disperse Violet 93, and Disperse Yellow 3, in concentrations from 0.01 to 6.81 μg L−1. Samples from the Piracicaba River downstream, Quilombo River, and WWTP effluent presented high levels of mutage- nicity up to 149,000 rev L−1. Disperse Blue 373 and Disperse Violet 93 were the major contributors to the mutagenicity of Quilombo River, WWTP effluent and Piracicaba River downstream. Disperse Red 1, al- though the most frequent dye, detected in 50% of the samples, accounted for a small contribution to the mutagenicity. The use of Sal- monella strains with high sensitivity to the class of the selected dyes (YG1041) was essential to reveal their contribution in these mutagenic environmental water samples. Finally, the combination of chemical analysis and bioassays were key in the identification the main drivers of the water mutagenicity and provides the required tools for the selec- tion of priority compounds to be included in monitoring programs as well for the enforcing actions required to protect the water quality for multiple uses. Image of Fig. 2 Table 4 Contribution of the dyes to the mutagenicity of samples using strain YG1041 with S9. Sample site Sampling Sample potency Dye Dye concentration Dye potency Contribution Total (rev μg−1) (μg L−1) (rev μg−1) (rev L−1) (%) (%) Piracicaba River upstream 1 4,000 Disperse Red 1 0.52 207a 107.6 2.7 2.7 2 13,000 – – 0 0 0 3 0 Disperse Blue 291 0.04 180b 0 0 4 0 – – 0 0 0 Quilombo River 1 68,000 Disperse Violet 93 0.08 4,600c 368 0.5 44.4 2 34,000 Disperse Violet 93 0.08 4,600c 368 1.08 3 50,550 Disperse Blue 373 1.38 6,300c 8,694 17.2 Disperse Orange 30 0.14 5.9 0.83 0.001 Disperse Red 1 0.09 207a 18.63 0.03 Disperse Violet 93 2.81 4,600c 12,926 25.6 Disperse Yellow 3 0.01 5.5 0.06 0.0001 4 0 Disperse Blue 373 0.54 6,300c 0 0 Disperse Red 1 0.15 207a 0 0 Disperse Yellow 3 0.41 5.5 0 0 WWTP effluent 1 145,000 Disperse Blue 373 0.35 6,300c 2,205 1.52 3.5 Disperse Red 1 0.03 207a 6.2 0.004 2 65,000 Disperse Blue 373 0.08 6,300c 504 0.78 Disperse Red 1 0.19 207a 39.3 0.06 3 85,000 Disperse Blue 291 0.05 180b 9 0.01 Disperse Blue 373 0.15 6,300c 945 1.11 Disperse Red 1 0.08 207a 16.6 0.02 4 37,000 – – 0 0 0 Piracicaba River downstream 1 10,000 – – 0 0 0 34.5 2 28,000 – – 0 0 0 3 149,000 Disperse Blue 373 3.13 6,300c 19,719 13 Disperse Red 1 0.11 207a 22.77 0.01 Disperse Violet 93 6.81 4,600c 31,326 21 Disperse Yellow 3 0.03 5.5 0.17 0.0001 4 11,000 Disperse Blue 373 0.28 6,300c 1.8 0.016 Disperse Red 1 0.13 207a 47.6 0.43 Disperse Yellow 3 0.02 5.5 0.11 0.001 – bLOQ. a Vacchi et al. (2013). b Umbuzeiro et al. (2005b). c Umbuzeiro et al. (2005a). 235F.I. Vacchi et al. / Science of the Total Environment 601–602 (2017) 230–236 Acknowledgment The authors thank FAPESP (2008/10449-7 and 2012/13344-7) and CAPES (PNPD fellowship) for financial support; Department of Water & Sewage of Americana City/SP, Brazil, especially to Msc. Guilherme Thiago Maziviero; and Dr. Errol Zeiger for his valuable suggestions. Appendix A. Supplementary data Supplementary data to this article can be found online at http://dx. doi.org/10.1016/j.scitotenv.2017.05.103. References Altenburger, R., Ait-Aissa, S., Antczak, P., Backhaus, T., Barceló, D., Seiler, T.-B., Brion, F., Busch, W., Chipman, K., de Alda, M.L., de Aragão Umbuzeiro, G., Escher, B.I., Falciani, F., Faust, M., Focks, A., Hilscherova, K., Hollender, J., Hollert, H., Jäger, F., Jahnke, A., Kortenkamp, A., Krauss, M., Lemkine, G.F., Munthe, J., Neumann, S., Schymanski, E.L., Scrimshaw, M., Segner, H., Slobodnik, J., Smedes, F., Kughathas, S., Teodorovic, I., Tindall, A.J., Tollefsen, K.E., Walz, K.-H., Williams, T.D., Van den Brink, P.J., van Gils, J., Vrana, B., Zhang, X., Brack, W., 2015. Future water quality monitoring — adapting tools to deal with mixtures of pollutants in water resource management. Sci. Total Environ. 512–513:540–551. http://dx.doi.org/10.1016/j.scitotenv.2014.12. 057. APHA, 1999. Standard methods for the examination of water and wastewater. Am. Public Heal. Assoc. Am. Water Work. Assoc. Water Environ. Fed. 541. Bafana, A., Devi, S., Chakrabarti, T., 2011. Azo dyes: past, present and the future. Environ. Rev. 370:350–370. http://dx.doi.org/10.1139/A11-018. Bernstein, L., Kaldor, J., McCann, J., Pike, M.C., 1982. An empirical approach to the statisti- cal analysis of mutagenesis data from the Salmonella test. Mutat. Res. 97, 267–281. Brack, W., 2003. Effect-directed analysis: a promising tool for the identification of organic toxicants in complex mixtures? Anal. Bioanal. Chem. 377:397–407. http://dx.doi.org/ 10.1007/s00216-003-2139-z. Brack, W., Ait-Aissa, S., Burgess, R.M., Busch, W., Creusot, N., Di Paolo, C., Escher, B.I., Mark Hewitt, L., Hilscherova, K., Hollender, J., Hollert, H., Jonker, W., Kool, J., Lamoree, M., Muschket, M., Neumann, S., Rostkowski, P., Ruttkies, C., Schollee, J., Schymanski, E.L., Schulze, T., Seiler, T., Tindall, A.J., De Aragão Umbuzeiro, G., Vrana, B., Krauss, M., 2016. Effect-directed analysis supporting monitoring of aquatic environments — an in-depth overview. Sci. Total Environ. 544:1073–1118. http://dx.doi.org/10. 1016/j.scitotenv.2015.11.102. Chequer, F.M.D., Angeli, J.P.F., Ferraz, E.R.A., Tsuboy, M.S., Marcarini, J.C., Mantovani, M.S., de Oliveira, D.P., 2009. The azo dyes disperse red 1 and disperse orange 1 increase the micronuclei frequencies in human lymphocytes and in HepG2 cells. Mutat. Res. 676: 83–86. http://dx.doi.org/10.1016/j.mrgentox.2009.04.004. Claxton, L.D., Matthews, P.P., Warren, S.H., 2004. The genotoxicity of ambient outdoor air, a review: Salmonella mutagenicity. Mutat. Res. 567:347–399. http://dx.doi.org/10. 1016/j.mrrev.2004.08.002. Freeman, H., 2013. Aromatic amines: use in azo dye chemistry. Front. Biosci. 18:145–164. http://dx.doi.org/10.2741/4093. Gallampois, C.M.J., Schymanski, E.L., Bataineh, M., Buchinger, S., Krauss, M., Reifferscheid, G., Brack, W., 2013. Integrated biological-chemical approach for the isolation and se- lection of polyaromatic mutagens in surface waters. Anal. Bioanal. Chem. 405: 9101–9112. http://dx.doi.org/10.1007/s00216-013-7349-4. Hagiwara, Y., Watanabe, M., Oda, Y., Sofuni, T., Nohmi, T., 1993. Specificity and sensitivity of Salmonella typhimurium YG1041 and YG1042 strains possessing elevated levels of both nitroreductase and acetyltransferase activity. Mutat. Res. 291, 171–180. Josephy, P.D., Zahid, M., Dhanoa, J., de Souza, G.B.D., Groom, H., Lambie, M., 2016. Potent mutagenicity in the Ames test of 2-cyano-4-nitroaniline and 2,6-dicyano-4- nitroaniline, components of disperse dyes. Environ. Mol. Mutagen. 57:10–16. http:// dx.doi.org/10.1002/em.21983. Kado, N.Y., Langley, D., Eisenstadt, E., 1983. A simplemodification of the Salmonella liquid- incubation assay. Increased sensitivity for detectingmutagens in human urine.Mutat. Res. 121, 25–32. Liu, L., Chen, L., Floehr, T., Xiao, H., Bluhm, K., Hollert, H., Wu, L., 2015. Assessment of the mutagenicity of sediments from Yangtze River estuary using Salmonella typhimurium/ microsome assay. PLoS One 10, e0143522. http://dx.doi.org/10.1371/journal.pone. 0143522. Lübcke-von Varel, U., Bataineh, M., Lohrmann, S., Löffler, I., Schulze, T., Flückiger-Isler, S., Neca, J., Machala, M., Brack, W., 2012. Identification and quantitative confirmation of dinitropyrenes and 3-nitrobenzanthrone as major mutagens in contaminated sed- iments. Environ. Int. 44:31–39. http://dx.doi.org/10.1016/j.envint.2012.01.010. Muz, M., Krauss, M., Kutsarova, S., Schulze, T., Brack, W., 2017. Mutagenicity in surface waters: synergistic effects of carboline alkaloids and aromatic amines. Environ. Sci. Technol. 51:1830–1839. http://dx.doi.org/10.1021/acs.est.6b05468. Ohe, T., Watanabe, T., Wakabayashi, K., 2004. Mutagens in surface waters: a review. Mutat. Res. 567:109–149. http://dx.doi.org/10.1016/j.mrrev.2004.08.003. http://dx.doi.org/10.1016/j.scitotenv.2017.05.103 http://dx.doi.org/10.1016/j.scitotenv.2017.05.103 http://dx.doi.org/10.1016/j.scitotenv.2014.12.057 http://dx.doi.org/10.1016/j.scitotenv.2014.12.057 http://refhub.elsevier.com/S0048-9697(17)31201-9/rf0010 http://refhub.elsevier.com/S0048-9697(17)31201-9/rf0010 http://dx.doi.org/10.1139/A11-018 http://refhub.elsevier.com/S0048-9697(17)31201-9/rf0020 http://refhub.elsevier.com/S0048-9697(17)31201-9/rf0020 http://dx.doi.org/10.1007/s00216-003-2139-z http://dx.doi.org/10.1016/j.scitotenv.2015.11.102 http://dx.doi.org/10.1016/j.scitotenv.2015.11.102 http://dx.doi.org/10.1016/j.mrgentox.2009.04.004 http://dx.doi.org/10.1016/j.mrrev.2004.08.002 http://dx.doi.org/10.1016/j.mrrev.2004.08.002 http://dx.doi.org/10.2741/4093 http://dx.doi.org/10.1007/s00216-013-7349-4 http://refhub.elsevier.com/S0048-9697(17)31201-9/rf0055 http://refhub.elsevier.com/S0048-9697(17)31201-9/rf0055 http://refhub.elsevier.com/S0048-9697(17)31201-9/rf0055 http://dx.doi.org/10.1002/em.21983 http://refhub.elsevier.com/S0048-9697(17)31201-9/rf0065 http://refhub.elsevier.com/S0048-9697(17)31201-9/rf0065 http://refhub.elsevier.com/S0048-9697(17)31201-9/rf0065 http://dx.doi.org/10.1371/journal.pone.0143522 http://dx.doi.org/10.1371/journal.pone.0143522 http://dx.doi.org/10.1016/j.envint.2012.01.010 http://dx.doi.org/10.1021/acs.est.6b05468 http://dx.doi.org/10.1016/j.mrrev.2004.08.003 236 F.I. Vacchi et al. / Science of the Total Environment 601–602 (2017) 230–236 Oliveira, D.P., Carneiro, P.A., Rech, C.M., Zanoni, M.V.B., Claxton, L.D., Umbuzeiro, G.A., 2006. Mutagenic compounds generated from the chlorination of disperse azo-dyes and their presence in drinking water. Environ. Sci. Technol. 40:6682–6689. http:// dx.doi.org/10.1021/es061020p. Oliveira, D.P., Carneiro, P.A., Sakagami, M.K., Zanoni, M.V.B., Umbuzeiro, G.A., 2007. Chem- ical characterization of a dye processing plant effluent — identification of the muta- genic components. Mutat. Res. 626:135–142. http://dx.doi.org/10.1016/j.mrgentox. 2006.09.008. Oliveira, G.A.R., Ferraz, E.R.A., Chequer, F.M.D., Grando, M.D., Angeli, J.P.F., Tsuboy, M.S., Marcarini, J.C., Mantovani, M.S., Osugi, M.E., Lizier, T.M., Zanoni, M.V.B., Oliveira, D.P., 2010. Chlorination treatment of aqueous samples reduces, but does not elimi- nate, themutagenic effect of the azo dyes disperse red 1, disperse red 13 and disperse Orange 1. Mutat. Res. 703:200–208. http://dx.doi.org/10.1016/j.mrgentox.2010.09. 001. Peng, H., Saunders, D.M.V., Sun, J., Jones, P.D., Wong, C.K.C., Liu, H., Giesy, J.P., 2016. Muta- genic azo dyes, rather than flame retardants, are the predominant brominated com- pounds in house dust. Environ. Sci. Technol. 50:12669–12677. http://dx.doi.org/10. 1021/acs.est.6b03954. Rajaguru, P., Fairbairn, L., Ashby, J., 1999. Genotoxicity studies on the azo dye direct red 2 using the in vivo mouse bone marrow micronucleus test. Mutat. Res. 444, 175–180. Tsuboy, M.S., Angeli, J.P.F., Mantovani, M.S., Knasmüller, S., Umbuzeiro, G.A., Ribeiro, L.R., 2007. Genotoxic, mutagenic and cytotoxic effects of the commercial dye CI disperse Blue 291 in the human hepatic cell line HepG2. Toxicol. in Vitro 21, 1650–1655. Umbuzeiro, G.A., Roubicek, D.A., Sanchez, P.S., Sato, M.I., 2001. The Salmonellamutagenic- ity assay in a surface water quality monitoring program based on a 20-year survey. Mutat. Res. 491, 119–126. Umbuzeiro, G., Roubicek, D.A., Rech, C.M., Sato, M.I.Z., Claxton, L.D., 2004. Investigating the sources of the mutagenic activity found in a river using the Salmonella assay and dif- ferent water extraction procedures. Chemosphere 54:1589–1597. http://dx.doi.org/ 10.1016/j.chemosphere.2003.09.009. Umbuzeiro, G.A., Freeman, H., Warren, S.H., Kummrow, F., Claxton, L.D., 2005a. Mutage- nicity evaluation of the commercial product CI disperse Blue 291 using different pro- tocols of the Salmonella assay. Food Chem. Toxicol. 43, 49–56. Umbuzeiro, G.A., Freeman, H.S., Warren, S.H., de Oliveira, D.P., Terao, Y., Watanabe, T., Claxton, L.D., 2005b. The contribution of azo dyes to the mutagenic activity of the Cristais River. Chemosphere 60:55–64. http://dx.doi.org/10.1016/j.chemosphere. 2004.11.100. Umbuzeiro, G., Machala, M., Weiss, J., 2011. Diagnostic tools for effect-directed analysis of mutagens, AhR agonists, and endocrine disruptors. In: Brack, W. (Ed.), Effect-Directed Analysis of Complex Environmental Contamination, The Handbook of Environmental Chemistry. Springer, Berlin Heidelberg, Berlin, Heidelberg http://dx.doi.org/10.1007/ 978-3-642-18384-3. Umbuzeiro, G.D.A., Heringa, M., Zeiger, E., 2016. In vitro genotoxicity testing: significance and use in environmental monitoring. Advances in Biochemical Engineering/Biotech- nology http://dx.doi.org/10.1007/10_2015_5018. USEPA, 1990. Aerobic and anaerobic treatment of C.I. Disperse Blue 79., United States En- vironmental Protection Agency. United States Environmental Protection Agency, Cin- cinnati, USA. USEPA, 1997. Manual for the Certification of Laboratories Analyzing Drinking Water: criteria and Procedures, 45268. EPA 815 B-97-001. United States Environmental Pro- tection Agency, Cincinnati, USA. Vacchi, F.I., Albuquerque, A.F., Vendemiatti, J.A., Morales, D.A., Ormond, A.B., Freeman, H.S., Zocolo, G.J., Zanoni, M.V.B., Umbuzeiro, G., 2013. Chlorine disinfection of dye wastewater: implications for a commercial azo dye mixture. Sci. Total Environ. 442: 302–309. http://dx.doi.org/10.1016/j.scitotenv.2012.10.019. Vacchi, F.I., Vendemiatti, J.A.S., Brosselin, V., Ferreira da Silva, B.B., Zanoni, M.V., DeMeo, M., Bony, S., Devaux, A., Umbuzeiro, G.A., 2016a. Combining different assays and chemical analysis to characterize the genotoxicity of waters impacted by textile dis- charges. Environ. Mol. Mutagen. 57:559–571. http://dx.doi.org/10.1002/em.22034. Vacchi, F.I., Von der Ohe, P.C., de Albuquerque, A.F., Vendemiatti, J.A. de S., Azevedo, C.C.J., Honório, J.G., da Silva, B.F., Zanoni, M.V.B., Henry, T.B., Nogueira, A.J., Umbuzeiro, G. de A., 2016b. Occurrence and risk assessment of an azo dye — the case of disperse red 1. Chemosphere 156:95–100. http://dx.doi.org/10.1016/j.chemosphere.2016.04.121. Valent, G.U., Sato, M.I.Z., Cristina, M., Coelho, L.S., Coimbrão, C.A., Sanchez, P.S., Martins, M.T., Bonatelli, R., 1993. Monitoring São Paulo state rivers in brazil for mutagenic ac- tivity using the Ames test. Environ. Toxicol.Water Qual. 8:371–381. http://dx.doi.org/ 10.1002/tox.2530080403. Watanabe, T., Shiozawa, T., Takahashi, Y., Takahashi, T., Terao, Y., Nukaya, H., Takamura, T., Sawanishi, H., Ohe, T., Hirayama, T., Wakabayashi, K., 2002. Mutagenicity of two 2- phenylbenzotriazole derivatives, 2-[2-(acetylamino)-4-(diethylamino)-5- methoxyphenyl]-5-amino-7-bromo-4-chloro-2H-benzotriazole and 2-[2- (acetylamino)-4-(diallylamino)-5-methoxyphenyl]-5-amino-7-bromo-4-chloro-2H- benzotriazole and t. Mutagenesis 17:293–299. http://dx.doi.org/10.1093/mutage/17. 4.293. Watanabe, T., Ohba, H., Asanoma, M., Hasei, T., Takamura, T., Terao, Y., Shiozawa, T., Hirayama, T., Wakabayashi, K., Nukaya, H., 2006. Isolation and identification of non- chlorinated phenylbenzotriazole (non-ClPBTA)-typemutagens in the Ho River in Shi- zuoka Prefecture, Japan. Mutat. Res. Genet. Toxicol. Environ. Mutagen. 609:137–145. http://dx.doi.org/10.1016/j.mrgentox.2006.06.033. Zocolo, G.J., Pilon dos Santos, G., Vendemiatti, J., Vacchi, F.I., Umbuzeiro, G. de A., Zanoni, M.V.B., 2015. Using SPE-LC-ESI-MS/MS analysis to assess disperse dyes in environ- mental water samples. J. Chromatogr. Sci. 53:1257–1264. http://dx.doi.org/10.1093/ chromsci/bmu221. http://dx.doi.org/10.1021/es061020p http://dx.doi.org/10.1016/j.mrgentox.2006.09.008 http://dx.doi.org/10.1016/j.mrgentox.2006.09.008 http://dx.doi.org/10.1016/j.mrgentox.2010.09.001 http://dx.doi.org/10.1016/j.mrgentox.2010.09.001 http://dx.doi.org/10.1021/acs.est.6b03954 http://dx.doi.org/10.1021/acs.est.6b03954 http://refhub.elsevier.com/S0048-9697(17)31201-9/rf0110 http://refhub.elsevier.com/S0048-9697(17)31201-9/rf0110 http://refhub.elsevier.com/S0048-9697(17)31201-9/rf0115 http://refhub.elsevier.com/S0048-9697(17)31201-9/rf0115 http://refhub.elsevier.com/S0048-9697(17)31201-9/rf0120 http://refhub.elsevier.com/S0048-9697(17)31201-9/rf0120 http://refhub.elsevier.com/S0048-9697(17)31201-9/rf0120 http://dx.doi.org/10.1016/j.chemosphere.2003.09.009 http://refhub.elsevier.com/S0048-9697(17)31201-9/rf0130 http://refhub.elsevier.com/S0048-9697(17)31201-9/rf0130 http://refhub.elsevier.com/S0048-9697(17)31201-9/rf0130 http://dx.doi.org/10.1016/j.chemosphere.2004.11.100 http://dx.doi.org/10.1016/j.chemosphere.2004.11.100 http://dx.doi.org/10.1007/978-3-642-18384-3 http://dx.doi.org/10.1007/978-3-642-18384-3 http://dx.doi.org/10.1007/10_2015_5018 http://refhub.elsevier.com/S0048-9697(17)31201-9/rf0150 http://refhub.elsevier.com/S0048-9697(17)31201-9/rf0150 http://refhub.elsevier.com/S0048-9697(17)31201-9/rf0150 http://refhub.elsevier.com/S0048-9697(17)31201-9/rf0155 http://refhub.elsevier.com/S0048-9697(17)31201-9/rf0155 http://refhub.elsevier.com/S0048-9697(17)31201-9/rf0155 http://dx.doi.org/10.1016/j.scitotenv.2012.10.019 http://dx.doi.org/10.1002/em.22034 http://dx.doi.org/10.1016/j.chemosphere.2016.04.121 http://dx.doi.org/10.1002/tox.2530080403 http://dx.doi.org/10.1093/mutage/17.4.293 http://dx.doi.org/10.1093/mutage/17.4.293 http://dx.doi.org/10.1016/j.mrgentox.2006.06.033 http://dx.doi.org/10.1093/chromsci/bmu221 http://dx.doi.org/10.1093/chromsci/bmu221 Quantifying the contribution of dyes to the mutagenicity of waters under the influence of textile activities 1. Introduction 2. Materials and methods 2.1. Study area and sampling 2.2. Liquid–liquid extraction/concentration procedures 2.3. HPLC-MS/MS analysis 2.4. Salmonella/microsome microsuspension assay 3. Results & discussion 3.1. Chemical analysis 3.2. Salmonella/microsome microsuspension assay 3.3. Contribution of target dyes to the observed mutagenicity 4. Conclusion Acknowledgment Appendix A. Supplementary data References