Subscriber access provided by Fudan University
Article
MUTAGENICITY IN SURFACE WATERS: SYNERGISTIC EFFECTS OF CARBOLINE ALKALOIDS AND AROMATIC AMINES Melis Muz, Martin Krauss, Stela Kutsarova, Tobias Schulze, and Werner Brack Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.6b05468 • Publication Date (Web): 03 Jan 2017 Downloaded from http://pubs.acs.org on January 4, 2017
Just Accepted “Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides “Just Accepted” as a free service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are accessible to all readers and citable by the Digital Object Identifier (DOI®). “Just Accepted” is an optional service offered to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these “Just Accepted” manuscripts.
Environmental Science & Technology is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Published by American Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to original U.S. Government works, or works produced by employees of any Commonwealth realm Crown government in the course of their duties.
Page 1 of 30
Environmental Science & Technology
1
MUTAGENICITY IN SURFACE WATERS: SYNERGISTIC EFFECTS OF
2
CARBOLINE ALKALOIDS AND AROMATIC AMINES
3 4
Melis MUZ a,b*, Martin KRAUSS a, Stela KUTSAROVAc, Tobias SCHULZE a, Werner BRACK a,b
5 6
a
7
Permoserstraße 15, 04318 Leipzig, Germany
8
b
9
Research,Worringerweg 1, 52074 Aachen, Germany
Department Effect-Directed Analysis, Helmholtz Centre for Environmental Research - UFZ,
RWTH Aachen University, Department of Ecosystem Analyses, Institute for Environmental
10
c
11
8010 Bourgas, Bulgaria
Laboratory of Mathematical Chemistry, University “Prof. Assen Zlatarov”, 1 Yakimov Street,
12 13
*Corresponding author:
14
e-mail
[email protected]; Phone: +49-341-235 1823
15
1 ACS Paragon Plus Environment
Environmental Science & Technology
Page 2 of 30
16
ABSTRACT
17
Since decades mutagenicity has been observed in many surface waters with a possible link to the
18
presence of aromatic amines. River Rhine is a well-known example of this phenomenon but
19
responsible compound(s) are still unknown. To identify the mutagenic compounds, we applied
20
effect-directed analysis (EDA) utilizing novel analytical and biological approaches to a water
21
sample extract from the lower Rhine. We could identify 21 environmental contaminants
22
including two weakly mutagenic aromatic amines, and the known alkaloid co-mutagen
23
norharman along with two related β-carboline alkaloids, carboline and 5-carboline, which were
24
reported the first time in surface waters. Results of mixture tests showed a strong synergism of
25
the identified aromatic amines not only with norharman, but also with carboline and 5-carboline.
26
Additionally, other nitrogen-containing compounds also contributed to the mutagenicity when
27
aromatic amines were present. Thus, co-mutagenicity of β-carboline alkaloids with aromatic
28
amines is shown to occur in surface waters. These results strongly suggest that surface water
29
mutagenicity is highly complex and driven by synergistic mechanisms of a complex compound
30
mixture (of which many are yet unidentified) rather than by single compounds. Therefore,
31
mixture effects should be considered not only from mutagens alone, but also including possible
32
co-mutagens and non-mutagenic compounds.
33 34
TOC/Abstract Art
35
2 ACS Paragon Plus Environment
Page 3 of 30
Environmental Science & Technology
36
INTRODUCTION
37
Mutagenicity is frequently observed in surface waters due to the presence of chemicals of
38
anthropogenic and natural origin 1. Mutagens entering freshwaters due to incomplete removal in
39
wastewater treatment systems and occurring in drinking water abstracted from polluted lakes and
40
rivers result in adverse effects on aquatic 2, 3 and human life 4. Although several studies tried to
41
identify the chemicals that cause the mutagenicity in the rivers, in only few cases individual
42
chemicals could be identified as the cause of the observed effect 5-9, whereas in other studies the
43
origin of mutagenicity was inconclusive and could not be explained by identified compounds 10-
44
12
45
aromatic amines are an important compound class with many suspected or known environmental
46
mutagens15-17. Aromatic amines are used as industrial chemicals and may be formed by
47
transformation of pesticides, dyes and nitroaromatic compounds18-22. Compounds like
48
naphthylamines23, substituted anilines24,
49
mutagenic/carcinogenic potentials. Furthermore, it was shown that heterocyclic aromatic amines
50
such
51
methylimidazo[4,5-f]quinoline (IQ), 2-amino-alpha-carboline (AαC) or 2-amino-1-methyl-6-
52
phenylimidazo[4,5-b]pyridine (PhIP) originating from grilled/fried meat and fish are discharged
53
by sewage effluents and contribute significantly to the mutagenicity of surface waters
54
of these compound groups require metabolic activation by the N-oxidation to aryl-N-
55
hydroxylamines, which in turn form nitrenium ions, the reactive electrophilic metabolite which
56
covalently binds to DNA 29. Therefore, in water samples showing an increased mutagenicity with
57
metabolic activation, the presence of mutagenic aromatic amines may be hypothesized. Many
58
PAHs are also mutagenic after metabolic activation
. Along with polycyclic aromatic hydrocarbons (PAHs)
as
25
13
and nitro-aromatic compounds
14
,
or benzidine analogues26 are well-studied for their
2-amino-3,8-dimethylimidazo[4,5-f]quinoxaline
30
(MeIQx),
2-amino-3-
27, 28
. All
and often predominate mutagenicity in
3 ACS Paragon Plus Environment
Environmental Science & Technology
31
and sediments
Page 4 of 30
32
59
soils
, but their concentrations in water are generally very low due to their
60
hydrophobicity.
61
Since the 1970s, mutagenicity that increases with metabolic activation has been observed in
62
different in vitro mutagenicity assays 33, 34 in samples from the lower stretch of the River Rhine.
63
Although some aromatic amines were detected in the river 35-37, the causative chemical(s) for the
64
observed effect remained unidentified up to now. These findings raise concerns, since the River
65
Rhine serves as a source of drinking water for 20 million people in Germany and the Netherlands
66
38
67
Effect directed analysis (EDA) is a valuable tool to unveil the chemicals contributing to adverse
68
effects of an environmental sample by integrating effect testing, fractionation and non-target
69
analysis of active fractions to identify the chemicals driving the observed effects
70
EDA studies were successful in identifying compounds responsible for mutagenic effects in
71
sediments
72
contributions were found such as phenylbenzotriazoles (PBTAs)5, 43 or benzidine derivatives (5-
73
nitro-DCB)7, the causes of mutagenicity remain largely inconclusive in many surface waters 10 or
74
wastewater effluents
75
liquid chromatography-mass spectrometry (LC-MS) data and to the limited information of
76
analytical data for a reliable compound identification. However, it might be also hypothesized
77
that mutagenicity in water samples is less clearly related to individual pre-dominant mutagens,
78
but the result of mixture effects involving a larger number of chemicals.
79
In this study we make a new attempt to unravel surface water mutagenicity by combining EDA
80
based on Ames testing with different Salmonella strains with novel analytical and prediction
81
tools. A recently developed derivatization method44 was applied for peak selection and pH
.
41, 42
39, 40
. Several
. Although in some cases a limited number of novel key toxicants with major
11
. This might be attributed to the lack of extensive spectral libraries for
4 ACS Paragon Plus Environment
Page 5 of 30
Environmental Science & Technology
82
dependent LC retention and hydrogen-deuterium exchange experiments were conducted to
83
reduce candidate numbers. In addition to the well-known nitrenium calculation model45, 46, the
84
tissue metabolic simulator AMES mutagenicity model (TIMES version 11.11)47 was used to
85
discriminate possible mutagenic chemicals. Finally the mutagenicities of confirmed candidates
86
were evaluated for single compounds and in mixture effect experiments.
87
MATERIALS AND METHODS
88
Details on the solvents and reagents used are given in the Supporting Information (SI), section
89
S1.
90
Sampling and sample preparation
91
The sample was taken in May 2014 from the Lower Rhine at the Dutch monitoring station in
92
Lobith over a period of 42 hours. A large volume solid phase extraction (LVSPE) instrument was
93
used to collect 800 L of water on site using three stacked sorbent cartridges containing 160 g of
94
Chromabond HR-X, 100g of Chromabond HR-XAW, and 100 g of Chromabond HR-XCW
95
(Macherey Nagel, Düren, Germany) in the direction of the water flow48. Sorbents were freeze
96
dried and eluted. The eluates were combined and the final volume was reduced to 500 mL by
97
means of a rotary evaporator. Additionally, a blank simulating a sample of 1000 L equivalent
98
was prepared. More details on the sample preparation are given in the SI, section S1.1.
99
Mutagenicity Assay
100
The Ames test utilizing several strains with characteristic metabolic pathways or different
101
mutations yields information regarding specific groups of mutagens and was shown to be a
102
successful approach in the identification of environmental mutagens
49
. In our study, the Ames 5
ACS Paragon Plus Environment
Environmental Science & Technology
Page 6 of 30
103
fluctuation assay (Ames II test) was performed using strain TA98 with and without metabolic
104
activation by S9 and strain YG1024 only with metabolic activation by S9 as described in
105
Reifferscheid et al.50 with slight modifications. YG1024 is characterized by an elevated o-
106
acetyltransferase activity making it more sensitive for aromatic amines, when S9 is included 51.
107
The mutagenic activity was determined in triplicates for every test and calculated by fitting the
108
results to an exponential equation reaching a maximum of 48 (Eq. S1). Mutagenicity is
109
quantified by the slope of this curve at the origin52 and given as number of revertants per liter of
110
water equivalent. More details on the test are given in the SI, section S1.2.
111
Fractionation
112
An aliquot of the LVSPE extract corresponding to 62.5 L of water was fractionated on a C18 LC
113
column (Agilent Zorbax Extend-C18, 9.4 x 250 mm, particle size 5 µm). In total 27 two-minute
114
fractions were collected. The fractions were diluted with H2O to have a maximum content of 5%
115
of MeOH and extracted by solid phase extraction using 200 mg of HR-X in between two PE frits
116
in glass cartridges. Cartridges were eluted using 10 mL of MeOH:EtAc (1:1, v:v), evaporated to
117
dryness under a mild nitrogen stream and re-dissolved in 1 mL of MeOH for further biological
118
and chemical analysis. All fractions were tested at two concentrations corresponding to relative
119
enrichment factors (REF) of 1000 and 2000 with both strains with S9 activation. More details on
120
the fractionation procedure are given in the SI, section S1.3.
121
Derivatization
122
Mutagenic fractions with increased activity on YG1024 compared to TA98 were subjected to a
123
derivatization method for amines described in Muz et. al44. Briefly, an aliquot of 30 µL was
124
taken from each fraction. Volumes of 10 µL of the derivatization reagent 4-fluoro-7-nitro-2,1,36 ACS Paragon Plus Environment
Page 7 of 30
Environmental Science & Technology
125
benzoxadiazole (NBD-F) and 2 µL of 20 mM ammonium acetate buffer (pH 5.7) were added and
126
the mixture was heated to 80°C for 30 minutes. All aliquots were derivatized with two different
127
concentrations of reagent (0.8 and 10 mM NBD-F).
128
LC-HRMS Analysis and Data Evaluation
129
Derivatized and underivatized samples were analyzed by LC-HRMS using a Thermo Ultimate
130
3000 LC system equipped with a ternary pump, autosampler and a column oven connected to an
131
LTQ Orbitrap XL (Thermo). A phenyl-hexyl column (Accucore PhenylHexyl 150 x 3 mm, 2.6
132
µm particle size, Thermo) was used for chromatographic separation at 30°C. HRMS analyses
133
were conducted in positive ion mode with a heated electrospray ionization source. Full scan
134
spectra were acquired in the mass range of m/z 100-1000 at a nominal resolving power of
135
100,000 (at m/z 400). Product ion spectra (MS/MS) were acquired with a data-dependent method
136
triggered for the two highest intensity peaks recorded at the full scan analysis. Details are given
137
in the SI, section S1.4.
138
Peak lists of derivatized and underivatized samples from the full scan chromatograms were
139
obtained using the software MZmine 2.1053. Detailed software settings are given in the SI,
140
section S1.5. A data matrix was created to find the analyte derivative matches by using the
141
accurate mass difference that resulted from the addition of an NBD-F molecule (163.0018 ±
142
0.0008, corresponding to 5 ppm). Separate matrices were prepared for the peak lists obtained
143
with different NBD-F concentrations. The derivatives were confirmed by the occurrence of 1-8
144
diagnostic fragments observed in the MS/MS spectra.
145
Masses of interests in the active fractions were selected which can be categorized as: (i) masses
146
of confirmed derivatives and (ii) masses that match with a potential derivative peak that is only
147
present in the derivatized sample but did not trigger an MS/MS. Both derivatized and 7 ACS Paragon Plus Environment
Environmental Science & Technology
Page 8 of 30
148
underivatized fractions were re-run with a Q-Exactive Plus instrument (Thermo). Details are
149
given in the SI, section S1.4. Molecular formulas of the peaks of interest were assigned using the
150
XCalibur software (Thermo) by limiting the elements according to isotope patterns. A workflow
151
summarizing the steps until molecular formula assignment is given in Figure S1 in the SI.
152
Candidate structure lists from the analyte MS/MS spectra with the highest number of meaningful
153
fragments were obtained using the software MetFrag 2.2 (command line version
154
ChemSpider (Royal Society of Chemistry) as the compound search database. Details of the
155
settings for MetFrag are given in the SI, section S1.6. A score cut-off of 0.7 was used and the
156
remaining candidates were sorted according to the number of references in ChemSpider giving
157
an indication on the potential commercial and environmental relevance of the compound. For the
158
lists without candidates with a high number of references (>10), 0.6 was used as the score cut-
159
off. Additionally, the spectra of the analytes were compared with the spectra present in
160
MassBank
161
confirmation was done and is reported according to the confidence levels proposed by
162
Schymanski et al.
163
procedure above were confirmed with reference standards and reported as confirmed structures
164
(level 1). Analytes having mass spectra in full agreement with MassBank spectra and plausibility
165
as environmental pollutants were directly accepted for final confirmation with standards. For the
166
confirmation of a compound, not only the match of retention time (RT) and MS/MS of the
167
analyte but also of the NBD-F derivatives were compared.
168
Confirmed compounds were then tested for their mutagenicity with both Ames strains in the
169
presence of S9 metabolic activation.
55
54
) with
for the same molecular formula when available. Compound identification and
56
. Whenever possible, plausible candidates selected according to the
8 ACS Paragon Plus Environment
Page 9 of 30
Environmental Science & Technology
170
Complementary Approaches for Candidate Selection and Confirmation
171
In cases without outstanding candidates with spectra closely similar to Massbank
172
those with more than 100 references showing commercial and probable environmental relevance,
173
two additional methods were applied to reduce the number of plausible candidates for a given
174
molecular formula.
175
The applied workflow for the selection or exclusion of candidates for generated molecular
176
formulas and the subsequent mutagenicity prediction and evaluation of confirmed compounds is
177
summarized in Figure 1.
55
spectra or
178 179
Figure 1. Applied workflow summarized for compound identification and mutagenicity
180
evaluation.
181 9 ACS Paragon Plus Environment
Environmental Science & Technology
Page 10 of 30
182
The candidate satisfying the criteria of both methods and having the highest number of
183
references was accepted as the most plausible structure and a confirmation with reference
184
standards was done.
185 186
pH-dependent LC retention
187
The LC retention of ionizable molecules such as amines depends strongly on their charge and
188
thus on the pH of the eluent. Thus, we compared the retention of the unknowns of interest at a
189
mobile phase pH of 2.6, 6.4, and 10.0.
190
As most aromatic amines should have pKa values between 2.6 and 5.5, their retention times are
191
expected to be lower at pH 2.6 and higher at pH 6.4 and 10.0, while aliphatic amines with pKa
192
values above 8 are expected to have similar retention times at pH 2.6 and 6.4, but higher ones at
193
pH 10.0, and neutral compounds should have similar retention times at all three pH values.
194
Candidate structures in disagreement with expected retention behavior at different pH were
195
rejected. The acidic and basic pKa values of candidate structures were calculated using the
196
Calculator Plugins JChem for Excel (version 6.3.0, Chemaxon)57. Those candidates showing pKa
197
values compatible with the observed RT shifts were further processed. Details on the method and
198
criteria for candidate selection based on observed retention time shifts and calculated pKa values
199
are given in the SI, section 1.7.
200 201
Hydrogen Deuterium Exchange
202
Hydrogen deuterium exchange (HDX) LC-HRMS analysis was used to determine the number of
203
exchangeable hydrogen atoms (i.e., typically those connected to heteroatoms) of the selected
204
unknowns of interest and candidate lists were limited to those molecules corresponding to that
10 ACS Paragon Plus Environment
Page 11 of 30
Environmental Science & Technology
58-60
205
number to gain information about the presence and number of polar functional groups
. For
206
HDX experiments, a 50-min LC gradient elution program was applied. Eluent A was replaced by
207
deuterium oxide (99.9 atom % D, Sigma-Aldrich) with 0.1% formic acid and eluent B was
208
replaced by methan-d1-ol (99.8 atom % D, Sigma-Aldrich). Aliquots were analyzed with a
209
nominal resolving power of 140,000 (at m/z 200) in the mass range of 100-700 m/z using a
210
QExactive Plus instrument. The HDX full scan spectra were searched manually using the
211
Xcalibur QualBrowser for peaks with an m/z value corresponding to an increasing number of
212
hydrogens exchanged based on the “normal” run m/z. For each candidate structure, the number
213
of heteroatom-attached hydrogens was calculated by the substructure search function of JChem
214
for Excel57 and candidates fitting with the observed exchanged hydrogen counts were further
215
evaluated.
216 217
Mutagenicity Prediction via Nitrenium Ion Stability for Primary Amines
218
In accordance with Ford et al
219
or heterocyclic aromatic primary amine (ArNH2) relative to the baseline compound-aniline
220
(PhNH2) was used to predict their mutagenicity. Heat of formation values (∆Hf) of the
221
compounds and their respective nitrenium ions were calculated by the semi empirical model
222
PM7 by using MOPAC
223
equation S2 in SI. A negative value of the enthalpy change indicates a more stable nitrenium ion
224
for the aromatic amine (ArNH+) compared to the non-mutagenic reference compound aniline
225
(PhNH+), which correlates positively with the mutagenic activity. Compounds with a ∆∆E < 0.0
226
kcal/mol were accepted as probably Ames positive. Details are given in the SI, section S1.8.
61
45
and Bentzien et al 46, the stability of nitrenium ions of aromatic
and the difference in enthalpy (∆∆E) was obtained according to
11 ACS Paragon Plus Environment
Environmental Science & Technology
Page 12 of 30
227
TIMES Ames Mutagenicity Model
228
TIMES Ames mutagenicity model is a SAR approach that predicts the DNA mutagenicity of
229
chemicals to any of the Salmonella typhimirium strains that are typically used in an Ames test47.
230
There are two types of TIMES Ames models - with and without rat liver S9 metabolic activation.
231
In order to provide predictions for a parent chemical and its stable S9 metabolites, TIMES Ames
232
with S9 activation model combines reactivity of chemicals to DNA and the S9 metabolic
233
simulator. So far this model has not been used as a candidate selection criterion. The
234
mutagenicity of the candidates and their S9 metabolites was predicted according to the model
235
version “TIMES in vitro Ames mutagenicity S9 activated” v.11.11.
236 237
RESULTS AND DISCUSSION
238
Mutagenicity Testing and Identification of Active Fractions for Candidate Mutagen
239
Identification
240
The water extract exhibited a mutagenic response with and without S9 in TA98. Metabolic
241
activation by S9 enhanced the response of TA98 strain, while the response of YG1024 was 4.6
242
times higher than of TA98 (both with S9) (Fig. S2) confirming the contribution of mutagenic
243
amines51. The mutagenic activities were calculated as: 461, 101 and 24 rev L-1 water eq. with
244
strains YG1024, TA98 with S9 and TA98 without S9, respectively. The processed blank did not
245
show mutagenicity with either of the strains.
246
Among the collected fractions, nine showed mutagenicity with TA98 with S9. In total, 14
247
fractions exerted an increased response with YG1024 and were accounted as active fractions.
248
Recovery of the mutagenic activity after fractionation was confirmed through both strains
249
comparing the activity of a recombination of all fractions with the original water extract (RAW)
12 ACS Paragon Plus Environment
Page 13 of 30
Environmental Science & Technology
250
using both strains with S9 (see Fig. 2). Results of all fractions are given in Table S2 in the SI.
251
These results revealed the presence of a larger number of mutagenic compounds and mixtures
252
than expected with a wide range of lipophilicity and thus were not helpful to relate the observed
253
effects to individual compounds. However, fractionation was crucial for selective analytical
254
identification of aromatic amines. The derivatization yield for most amines showed a high
255
dependency on matrix load44, which could be significantly reduced by fractionation serving as an
256
efficient clean up strategy without any significant losses in overall mutagenicity. Based on these
257
findings we followed the strategy to identify candidate mutagens in the fractions, but to consider
258
them as components of one mixture representing the parent water extract. 48 44
TA98 REF1000 TA98 REF2000 YG1024 REF1000 YG1024 REF2000
40
number of revertants (max=48)
36 32 28 24 20 16 12 8 4 0
Fractions(min)
259 260
Figure 2. Mutagenicity of active fractions with TA98 and with YG1024 strain with addition of
261
S9.
13 ACS Paragon Plus Environment
Environmental Science & Technology
Page 14 of 30
262
Screening for parent candidate-derivative pairs
263
Based on the mass difference before and after derivatization with NBD-F (163.0018 ± 5 ppm), in
264
total 237 candidate parent-derivative matches were found in the active fractions. Eleven and 148
265
matches were found in the matrices created with the peak lists of 0.8 mM and 10 mM NBD-F
266
derivatized fractions, respectively, and 39 matches were detected in the matrices of both
267
concentrations. From all candidates, 83 derivatives were confirmed with diagnostic fragments.
268
Among them 78 showed more than one diagnostic fragment, while 23 of the candidates exhibited
269
no diagnostic fragment in the MS/MS spectra and 23 of them were detected also in the
270
underivatized fractions. Both sets of candidates were eliminated from further data processing.
271
The remaining 63 matches included 37
272
more than one analyte peak but one visible derivative peak and eight matches with more than one
273
derivative peak but one visible analyte peak. The candidates with confirmed derivatives (83)
274
were evaluated manually in XCalibur and molecular formulas for 70 analyte peaks could be
275
assigned based on accurate mass and isotope patterns. For six out of these a Chemspider search
276
revealed no aromatic compounds and thus these were removed from further evaluations. A
277
number of 13 peaks were eliminated due to broad, dispersed or not well separated peak shapes
278
and unclear links between the analyte peak and the detected derivative.
279
Compound Identification and Confirmation
13
C isotope peak-derivative matches, 18 matches with
280 281
Out of 64 candidates with confirmed derivatives and successfully assigned molecular formula,
282
21 micropollutants from different compound classes that are commonly detected in surface
283
waters and rather new carboline alkaloids were identified and confirmed with reference standards
284
as shown in Table 1. A more detailed summary is given in Table S3 in SI. Among the identified 14 ACS Paragon Plus Environment
Page 15 of 30
Environmental Science & Technology
285
compounds, eight of them without MassBank spectra similarity had in total 705 candidates with
286
a score higher than 0.7 and 279 of them exhibited more than 10 references. Candidate exclusion
287
using pH-dependent retention reduced the number of possible structures to 427, of which 142
288
had more than 10 references. The use of HDX for candidate exclusion selected 274 possible
289
candidate structures, 95 of them with more than 10 references. 125 candidates with a score
290
higher than 0.7 were in compliance with HDX and pH-dependent retention with only 50 of them
291
with more than 10 references.
292
The identified compounds include eight pharmaceuticals: 4-aminoantipyrine, candesartan,
293
sotalol, sitagliptin, metoprolol, lamotrigine, 2- and 4-phenylpyridine, five industrial chemicals:
294
4-dimethylaminopyridine
295
quinolinol and isoquinolone, two agricultural chemicals: metamitron-desamino and isopentenyl
296
adenine, two industrial aromatic amines: o-toluidine and 2,6-xylidine used as dye precursors and
297
four alkaloids: cotinine and the three carboline isomers norharman, carboline and 5-carboline.
298
After confirming the presence of metamitron-desamino, metamitron was searched manually and
299
found in the same fraction and confirmed with the reference standard. All the reference standards
300
were also derivatized and used for confirmation of the respective derivative peaks when possible.
301
The concentrations of the confirmed compounds were semi-quantified with a comparison of peak
302
areas found in the fractions with the peak areas of the reference standards. The MS/MS spectra
303
for all the analyte peaks and the corresponding reference standards are given in SI, section S2.2.
304
In addition to the positively identified chemicals a large number of peaks remained unidentified
305
(Table S4) although the applied filtering approach reduced the number of plausible candidate
306
structures to a large extent. Many of the remaining candidates were predicted positive with either
307
one of the mutagenicity models and in some cases, the only candidate left was predicted positive
(4-DMAP),
1H-benzotriazole,
5-methyl-1H-benzotriazole,
6-
15 ACS Paragon Plus Environment
Environmental Science & Technology
Page 16 of 30
308
with both models. These results showed that there are many unidentified compounds with
309
mutagenic potential in the active fractions that could be contributing to the overall mutagenicity.
310
Among the chemical signals that were detected in the mutagenic fractions, but could not be
311
positively identified, several peaks were found having the same exact mass as the carboline
312
isomers norharman, carboline and 5-carboline and showing common fragments with the
313
carboline isomers in the MS/MS spectra. Four to eight common fragments were observed for
314
each peak as summarized in Table S5 in SI. Furthermore, these unknowns showed the same pH
315
dependent LC retention shifts and the same number of exchangeable hydrogen atoms in the HDX
316
method, suggesting that these unknowns are further closely related isomers. Possible candidate
317
compounds are listed in Table S6 in SI.
318
16 ACS Paragon Plus Environment
Page 17 of 30
Environmental Science & Technology
319
Table 1. Summary of identified compounds in the active fractions. All were confirmed by
320
reference standards. Found in
Formula
Fraction
Candidates with
MassBank
# of Candidates
Compound
Rank / Score
a score > 0.7
Similarity
complying with
Name
(Ref#) in
( ref#>10)
both LC methods
Use/origin
MetFrag Lists
(Ref >10) 4-dimethyl 4_5
C7H10N2
273 (85)
no
33 (3)
1 / 0.96 (520)
catalyst
beta blocker drug
aminopyridine
4_5
C12H20N2O3S
*
yes
-
sotalol
1 / 0.36 (1554)
6_7
C10H12N2O
925 (61)
yes
-
(S)-(-)-cotinine
3 / 0.95 (136)
alkaloid, human nicotine metabolite
14_15
C24H20N6O3
59 (4)
yes
-
14_15
C11H13N3O
1901 (74)
yes
-
candesartan
1 / 0.72 (1090)
antihypertensive drug
1 / 0.85 (721)
anti-inflammatory drug
4-amino antipyrine 1H14_15
C6H5N3
30 (14)ǁ
yes
-
corrosion 1 / 0.67 (635)
benzotriazole
16_17
C15H25NO3
670 (8)
yes
-
16_17
C10H9N3O
439 (38)
yes
-
metoprolol
inhibitor
1 / 0.92 (3665)
metamitron-
beta blocker drug
transformation product of 2 / 0.74 (96)
desamino
metamitron
16_17
C10H10N4O
-
-
-
metamitron
-
herbicide
16_17
C9H7NO
129 (41)
no
14 (14)
6-quinolinol
9 / 0.70 (175)
chelating agent
16_17
C9H7NO
61 (28)
no
16 (6)
isoquinolone
3 / 0.86 (234)
chelating agent
16_17
C11H8N2
133 (35)
no
18 (9)
5-carboline
3 / 0.61 (64)
alkaloid
18_19
C7H9N
26 (4)
yes
-
o-toluidine
3 / 0.98 (523)
dye precursor
¥
17 ACS Paragon Plus Environment
Environmental Science & Technology
Page 18 of 30
Cont`d Found in
Formula
Fraction
Candidates with
MassBank
# of Candidates
Compound
Rank / Score
a score > 0.7
Similarity
complying with
Name
(Ref#) in
( ref#>10)
both LC methods
Use/origin
MetFrag Lists
(Ref >10)
18_19
C16H15F6N5O
8 (2)
yes
-
sitagliptin
1 / 1.0 (120)
antidiabetic drug
18_19
C9H7Cl2N5
26 (4)
yes
-
lamotrigine
1 / 0.94 (2011)
anticonvulsant drug
18_19
C7H7N3
32 (16)
yes
-
5-methyl
corrosion 1 / 0.70 (195)
benzotriazole
22_23
C8H11N
32 (16)
yes
-
22_23
C10H13N5
83 (6)
yes
-
2,6-xylidine
inhibitor
3 / 0.93 (285)
dye precursor
1 / 1.0 (104)
plant growth regulator
isopentenyl adenine ¥
26_27
C11H8N2
147 (35)
28_29
C11H8N2
28_29
C11H9N
no
18 (6)
norharman
1 / 0.61 (323)
alkaloid
157 (43)
no
16 (6)
carboline
2 / 0.62 (82)
alkaloid
39 (6)
no
5 (3)
¥
4-phenyl
monoamine oxidase 2 / 0.70 (180)
pyridine
(MAO) inhibitor
2-phenyl 28_29
C11H9N
39 (6)
no
5 (3) pyridine
321 322 323 324 325 326
monoamine oxidase 1 / 0.71 (324) (MAO) inhibitor
* For the mass 272.1194, only 12 candidates had a reference number higher than 10 with scores between 0.15-0.36. Therefore, no score cut-off was applied. ǁ
For the mass 119.0483, with a score cut off 0.7, the sole candidate with a reference number higher than 10 was phenylazide. Since the structure
of phenylazide is not favorable for yielding a derivative, 0.6 was used as the score cut off. ¥
For the mass of 168.0687, with a score cut off 0.7, no environmental relevance was found for the sole candidate with a reference number higher
than 10. Therefore, 0.6 was used as the score cut off.
18 ACS Paragon Plus Environment
Page 19 of 30
Environmental Science & Technology
327
Contribution of identified compounds and mixtures thereof to sample
328
mutagenicity
329
In order to identify probable causes of observed mutagenicity, literature was searched for data on
330
mutagenicity of the identified compounds. Ames mutagenicity was predicted by both the TIMES
331
and the nitrenium ion stability models. The aromatic amines o-toluidine and 2,6-xylidine were
332
predicted positive with both models and also have been reported as weak mutagens in the Ames
333
test with strains TA98 and TA100, respectively, with metabolic activation in previous studies 25,
334
62
335
were predicted to be Ames positive with S9 according to the TIMES model. One should
336
emphasize that the predictions did not belong to the model domain, which decreases their
337
reliability.
338
The identified compounds were tested separately and in mixtures with relative concentrations in
339
agreement with the original sample composition. Absolute test concentrations up to 1000-fold
340
above the concentration in the sample were used to establish the concentration-response models
341
as shown in S2.4 in SI (Figs. S3-5). The test mixtures were designed by grouping the chemicals
342
as 1) aromatic amines with known mutagenic potency (o-toluidine and 2,6-xylidine), 2) possible
343
mutagens predicted by TIMES (metamitron, lamotrigine and 4-phenylpyridine), 3) norharman,
344
carboline and 5-carboline that might act as co-mutagens63-67, and 4) all other identified
345
compounds predicted to be non-mutagenic (others). All compounds and mixtures were tested
346
with YG1024 with S9 activation (Fig. 3).
. In addition to o-toluidine and 2,6-xylidine, 4-phenylpyridine, lamotrigine and metamitron
19 ACS Paragon Plus Environment
Environmental Science & Technology
Page 20 of 30
400 350
10-3 rev / L water eq.
300 250 200 150 100 50 0
347 348
Figure 3. Mutagenicity of artificial mixtures designed according to the relative composition of
349
the parent sample in 10-3revertants (rev) per L water equivalent derived from the slope of full
350
concentration response relationships of strain YG1024 with S9. o-toluidine: OTO, 2,6-xylidine:
351
XYL, norharman: NH, carboline: CB, 5-carboline: 5CB, possible mutagens predicted by
352
TIMES (metamitron, lamotrigine and 4-phenylpyridine): pms, other compounds predicted to be
353
non-mutagenic: others
354 355
No mutagenicity was observed for any of the single compounds identified by either TA98 or
356
YG1024 with S9, up to 1000-fold enhanced concentrations compared to original water samples.
357
This held also true for the mixture of the two aromatic amines o-toluidine/2,6-xylidine, for
358
norharman alone and in combination with other carbolines. o-toluidine with norharman resulted
359
in significant mutagenicity of 10 × 10-3 rev/L water eq which increased to 14 × 10-3 rev/L water
20 ACS Paragon Plus Environment
Page 21 of 30
Environmental Science & Technology
360
eq when 2,6-xylidine was added. The mutagenicity was enhanced by a factor of 14 for o-
361
toluidine to 139 × 10-3 rev/L water eq. and by a factor of 16 for o-toluidine/2,6-xylidine to 230 ×
362
10-3 rev/L water eq. if all three identified carbolines were present in the relative concentrations
363
found in the water sample. Co-exposure of YG1024 to o-toluidine/2,6-xylidine together with the
364
three TIMES-predicted mutagenic substances did not result in any mutagenic response up to a
365
concentration 1000-fold above the original water concentrations. Along with norharman 120 ×
366
10-3 rev/L water eq. were observed, 8 times more than without TIMES-predicted mutagenic
367
substances. Involving all three carbolines the effect was doubled (250 × 10-3 rev/L water eq.).
368
The mixture of identified compounds (without carbolines) exhibited some mutagenicity (19 × 10-
369
3
370
rev/L water eq. respectively) and strongly increased by norharman to 168 × 10-3 rev/L water eq..
371
However, it should be considered that the concentrations of carboline and 5-carboline where
372
about one order of magnitude below the norharman concentration. All compounds together at
373
relative concentrations resembling the original sample exhibited a mutagenic effect of 302 × 10-3
374
rev/L water eq. This is still three orders of magnitude below the effect of the raw sample. Thus,
375
the identified compounds still only explain a minor fraction of measured mutagenicity but they
376
clearly illustrate the synergism of mutagenic effects of typical water contaminants even without
377
components with a significant individual effect.
378
The results suggest a particularly strong synergistic effect between carbolines and aromatic
379
amines. This effect has been shown for norharman and some other β-carboline alkaloids
380
including harman, harmine, harmol, harmaline and harmalol found in plants, tobacco smoke,
381
well-cooked foods68 and roasted coffee69 together with aniline70,
382
isomers66. There are different mechanisms proposed, all starting with a reaction of the aromatic
rev/L water eq.) that was slightly increased by carboline and 5-carboline (29 and 43 × 10-3
71
and different toluidine
21 ACS Paragon Plus Environment
Environmental Science & Technology
Page 22 of 30
383
amine with the pyrrole nitrogen under the catalysis of cytochrome P450 oxygenases to (in the
384
case of norharman and aniline) aminophenylnorharman67,
385
further activated by N-hydroxylation and acetylation resulting in a nitrenium ion that is the final
386
electrophile that forms DNA-adducts67 or (2) forms hydroxamino- and nitrosophenylnorharman
387
causing oxidative DNA damage71. Aminophenylnorharman has been reported as a carcinogen in
388
mouse and rat73, 74 and was detected in human urine samples75.
389
There is only one previous study that detected norharman and some chlorinated harmans in the
390
effluent of a sewage treatment plant76 while neither carboline nor 5-carboline have ever been
391
detected as environmental contaminants before. The results of the present study strongly suggest
392
that the synergistic effects of carbolines and aromatic amines might play an important role in
393
environmental mutagenicity and contribute to the explanation of mutagenic effects in river water.
394
It could be also shown that besides norharman also other less known compounds such as
395
carboline and 5-carboline strongly contribute to the synergistic effect. In previous studies it had
396
been shown that other β -carbolines like harman and harmin68, 77 and also 3-methylindole and
397
indole78 caused an enhancement in the mutagenicity of aromatic amines.
398
The occurrence of many different carbolines and indoles probably acting as co-mutagens in
399
addition to the possible mutagens (as listed in Table S5) might also help to explain parts of the
400
still substantial mismatch between the mutagenicity detected in the water sample fractions and
401
the mutagenicity exerted by identified chemicals. In the present study in 10 of the 14 active
402
fractions peaks with the exact mass of norharman were detected. At the same time the present
403
results indicate that if some aromatic amines that can undergo the reaction with carbolines are
404
present (without o-toluidine/2,6-xylidine no mutagenicity was observed even with norharman)
405
additional nitrogen-containing compounds can further enhance mutagenicity even if they do not
70, 72
. This intermediate is either (1)
22 ACS Paragon Plus Environment
Page 23 of 30
Environmental Science & Technology
406
show any mutagenicity individually. The mechanism behind this finding is unknown. Mixture
407
mutagenicity assessment typically follows an effect addition model summing up the number of
408
revertants induced per amount of compound or fraction determined as the slope of linear
409
concentration-relationships and thus being also in agreement with the model of concentration
410
addition. This approach has been successfully applied for airborne particles79 and sediments80,
411
where mutagenicity is predominated by polycyclic aromatic hydrocarbons and related
412
compounds. Deviations have been reported for high concentrations or increasing mixture
413
complexity resulting in lower numbers of revertants than expected from additivity due to an
414
interference of inhibiting processes41. So far, mixture effects and particularly synergism in
415
mutagenicity of water samples have been rarely reported81 but may be hypothesized as one of the
416
reasons that explains why previous studies failed to identify individual compounds as the cause
417
of mutagenicity in river waters10,
418
YG1024 for aromatic amines- should be considered which is shown to act as an effective
419
diagnostic tool to unveil not only the mutagenicity of single compounds, but also mutagenicity of
420
mixtures involving these compound classes. Moreover, a systematic filtering of candidates using
421
HDX, pH dependent retention time shifts and number of references improved the candidate
422
selection significantly, suggesting this approach as useful for the identification of
423
environmentally relevant pollutants when mass spectral libraries lack a similar entry, although
424
biasing candidate lists towards more well-studied compounds.
425
The mixture mutagenicity experiments in the present study were driven by the attempt to explain
426
the mutagenic potency in the analyzed sample and thus based on a mixture design mimicking the
427
original water composition. However, it indicates that a rigorous investigation of mixture
428
mutagenicity involving aromatic amines, carbolines and related co-mutagens as well as other
52
. For that purpose, employing different strains -such as
23 ACS Paragon Plus Environment
Environmental Science & Technology
Page 24 of 30
429
mutagenic and non-mutagenic water contaminants is required in order to understand the
430
mechanisms behind the mixture effects found in this study and to identify the drivers of the
431
effects in surface waters. At the same time, those drivers identified in the River Rhine including
432
particularly aromatic amines (e.g., from industrial processes) and carbolines, which might be
433
largely natural alkaloids, should be included into water monitoring in order to assess the
434
potential risks and the sources of these water contaminants for aquatic ecosystems and
435
particularly for drinking water abstraction.
436 437
SUPPORTING INFORMATION
438
Detailed information on sample preparation, fractionation, LC-HRMS analysis and additionally
439
bioassay results, spectra of identified compounds, unidentified possible mutagens and
440
concentration-response plots of designed mixtures are given in SI.
441 442
ACKNOWLEDGEMENTS
443
This work was funded by the EDA-EMERGE project (FP7-PEOPLE-2011-ITN, grant agreement
444
290100) and the SOLUTIONS project (grant agreement 603437), both supported by the EU
445
Seventh Framework Programme, and the ToxBox project funded by the German Federal
446
Ministry for Education and Research (BMBF) under the grant agreement 02WRS1282C. We
447
thank Jörg Ahlheim and Margit Petre for their technical support and Arnold Bahlmann for his
448
valuable ideas. We express our gratitude to Takehiko Nohmi and Masami Yamada from National
449
Institute of Health Sciences, Japan, who generously provide the YG1024 strains and also Canan
450
Karakoc, for her precious assistance in handling the strains. Chemaxon (Budapest, Hungary) is
24 ACS Paragon Plus Environment
Page 25 of 30
Environmental Science & Technology
451
acknowledged for providing an academic license of JChem for Excel, Marvin and the Calculator
452
Plugins. A free academic license of MOPAC2016 was kindly granted by James J.P. Stewart.
25 ACS Paragon Plus Environment
Environmental Science & Technology
Page 26 of 30
453
REFERENCES
454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497
1. Ohe, T.; Watanabe, T.; Wakabayashi, K., Mutagens in surface waters: a review. Mutat. Res. Rev. Mutat. Res. 2004, 567, (2–3), 109-149. 2. Devaux, A.; Fiat, L.; Gillet, C.; Bony, S., Reproduction impairment following paternal genotoxin exposure in brown trout (Salmo trutta) and Arctic charr (Salvelinus alpinus). Aquat. Toxicol. 2011, 101, (2), 405-411. 3. Liney, K. E.; Hagger, J. A.; Tyler, C. R.; Depledge, M. H.; Galloway, T. S.; Jobling, S., Health effects in fish of long-term exposure to effluents from wastewater treatment works. Environ. Health Perspect. 2006, 114 Suppl 1, 81-89. 4. Grabow, W. O. K.; Van Rossum, P. G.; Grabow, N. A.; Denkhaus, R., Relationship of the raw water quality to mutagens detectable by the Ames Salmonella/microsome assay in a drinking-water supply. Water Res. 1981, 15, (9), 1037-1043. 5. Nukaya, H.; Yamashita, J.; Tsuji, K.; Terao, Y.; Ohe, T.; Sawanishi, H.; Katsuhara, T.; Kiyokawa, K.; Tezuka, M.; Oguri, A.; Sugimura, T.; Wakabayashi, K., Isolation and Chemical−Structural Determination of a Novel Aromatic Amine Mutagen in Water from the Nishitakase River in Kyoto. Chem. Res. Toxicol. 1997, 10, (10), 1061-1066. 6. Oguri, A.; Shiozawa, T.; Terao, Y.; Nukaya, H.; Yamashita, J.; Ohe, T.; Sawanishi, H.; Katsuhara, T.; Sugimura, T.; Wakabayashi, K., Identification of a 2-Phenylbenzotriazole (PBTA)-Type Mutagen, PBTA-2, in Water from the Nishitakase River in Kyoto. Chem. Res. Toxicol. 1998, 11, (10), 1195-1200. 7. Ohe, T.; Watanabe, T.; Nonouchi, Y.; Hasei, T.; Agou, Y.; Tani, M.; Wakabayashi, K., Identification of a new mutagen, 4,4′-diamino-3,3′-dichloro-5-nitrobiphenyl, in river water flowing through an industrial area in Wakayama, Japan. Mutat. Res. Genet. Toxicol. Environ. Mutagen. 2008, 655, (1–2), 28-35. 8. Meier, J. R., Genotoxic activity of organic chemicals in drinking water. Mutat. Res. Rev. Genet. 1988, 196, (3), 211-245. 9. de Aragão Umbuzeiro, G.; Freeman, H. S.; Warren, S. H.; de Oliveira, D. P.; Terao, Y.; Watanabe, T.; Claxton, L. D., The contribution of azo dyes to the mutagenic activity of the Cristais River. Chemosphere 2005, 60, (1), 55-64. 10. Gallampois, C. M. J.; Schymanski, E. L.; Krauss, M.; Ulrich, N.; Bataineh, M.; Brack, W., Multicriteria Approach To Select Polyaromatic River Mutagen Candidates. Environ. Sci. Technol. 2015, 49, (5), 2959-2968. 11. Hug, C.; Sievers, M.; Ottermanns, R.; Hollert, H.; Brack, W.; Krauss, M., Linking mutagenic activity to micropollutant concentrations in wastewater samples by partial least square regression and subsequent identification of variables. Chemosphere 2015, 138, 176-182. 12. Maruoka, S.; Yamanaka, S. i.; Yamamoto, Y., Isolation of mutagenic components by highperformance liquid chromatography from XAD extract of water from the Nishitakase river, Kyoto city, Japan. Sci. Total Environ. 1986, 57, 29-38. 13. Brookes, P., Mutagenicity of polycyclic aromatic hydrocarbons. Mutat. Res. Rev. Genet. 1977, 39, (3), 257-283. 14. Purohit, V.; Basu, A. K., Mutagenicity of Nitroaromatic Compounds. Chem. Res. Toxicol. 2000, 13, (8), 673-692. 15. Chung, K.-T.; Kirkovsky, L.; Kirkovsky, A.; Purcell, W. P., Review of mutagenicity of monocyclic aromatic amines: quantitative structure–activity relationships. Mutat. Res. Rev. Mutat. Res. 1997, 387, (1), 1-16.
26 ACS Paragon Plus Environment
Page 27 of 30
498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545
Environmental Science & Technology
16.
Benigni, R.; Passerini, L.; Gallo, G.; Giorgi, F.; Cotta-Ramusino, M., QSAR models for discriminating between mutagenic and nonmutagenic aromatic and heteroaromatic amines. Environ. Mol. Mutag. 1998, 32, (1), 75-83. 17. Skipper, P. L.; Kim, M. Y.; Sun, H. L. P.; Wogan, G. N.; Tannenbaum, S. R., Monocyclic aromatic amines as potential human carcinogens: old is new again. Carcinogenesis 2010, 31, (1), 50-58. 18. Onuska, F. I.; Terry, K. A.; Maguire, R., Analysis of aromatic amines in industrial wastewater by capillary gas chromatography-mass spectrometry. Water Qual. Res. J. Can. 2000, 35, (2), 245-261. 19. Hallas, L. E.; Alexander, M., Microbial transformation of nitroaromatic compounds in sewage effluent. Appl. Environ. Microbiol. 1983, 45, (4), 1234-1241. 20. Voyksner, R. D.; Straub, R.; Keever, J. T.; Freeman, H. S.; Hsu, W.-N., Determination of aromatic amines originating from azo dyes by chemical reduction combined with liquid chromatography/mass spectrometry. Environ. Sci. Technol. 1993, 27, (8), 1665-1672. 21. Dupret, J.-M.; Cocaign, A.; Mougin, C.; Rodrigues-Lima, F.; Busi, F.; Dairou, J.; Martins, M.; Silar, P., Pesticide-derived aromatic amines and their biotransformation. In Pesticides in the Modern World - Pests Control and Pesticides Exposure and Toxicity Assessment, Stoytcheva, M., Ed. INTECH Open Access Publisher: 2011; pp 601-614. 22. White, P. A.; Rasmussen, J. B., The genotoxic hazards of domestic wastes in surface waters1. Mutat. Res. Rev. Mutat. Res. 1998, 410, (3), 223-236. 23. Stoltz, D.; Bendall, R.; Starvic, B.; Munro, I., Selection of species for cancer bioassay for naphthylamine-containing food colours on the basis of tissue-mediated mutagenicity. Mutat. Res. Envir. Muta. 1978, 53, (2), 267-268. 24. Zimmer, D.; Mazurek, J.; Petzold, G.; Bhuyan, B. K., Bacterial mutagenicity and mammalian cell DNA damage by several substituted anilines. Mutat. Res. Genet. Tox. 1980, 77, (4), 317-326. 25. Kugler-Steigmeier, M. E.; Friederich, U.; Graf, U.; Lutz, W. K.; Maier, P.; Schlatter, C., Genotoxicity of aniline derivatives in various short-term tests. Mutat. Res. Fund. Mol. M. 1989, 211, (2), 279-289. 26. Golka, K.; Kopps, S.; Myslak, Z. W., Carcinogenicity of azo colorants: influence of solubility and bioavailability. Toxicol. Lett. 2004, 151, (1), 203-210. 27. Ohe, T., Quantification of mutagenic/carcinogenic heterocyclic amines, MeIQx, Trp-P-1, Trp-P-2 and PhIP, contributing highly to genotoxicity of river water. Mutat. Res. Genet. Toxicol. Environ. Mutagen. 1997, 393, (1–2), 73-79. 28. Kataoka, H.; Hayatsu, T.; Hietsch, G.; Steinkellner, H.; Nishioka, S.; Narimatsu, S.; Knasmüller, S.; Hayatsu, H., Identification of mutagenic heterocyclic amines (IQ, Trp-P-1 and AαC) in the water of the Danube River. Mutat. Res. Genet. Toxicol. Environ. Mutagen. 2000, 466, (1), 27-35. 29. Borosky, G. L., Ultimate Carcinogenic Metabolites from Aromatic and Heterocyclic Aromatic Amines: A Computational Study in Relation to Their Mutagenic Potency. Chem. Res. Toxicol. 2007, 20, (2), 171-180. 30. Xue, W.; Warshawsky, D., Metabolic activation of polycyclic and heterocyclic aromatic hydrocarbons and DNA damage: A review. Toxicol. Appl. Pharmacol. 2005, 206, (1), 73-93. 31. White, P. A.; Claxton, L. D., Mutagens in contaminated soil: a review. Mutat. Res. Rev. Mutat. Res. 2004, 567, (2–3), 227-345. 32. Cachot, J.; Geffard, O.; Augagneur, S.; Lacroix, S.; Le Menach, K.; Peluhet, L.; Couteau, J.; Denier, X.; Devier, M. H.; Pottier, D.; Budzinski, H., Evidence of genotoxicity related to high PAH content of sediments in the upper part of the Seine estuary (Normandy, France). Aquat. Toxicol. 2006, 79, (3), 257-267. 33. Hendriks, A. J.; Maas-Diepeveen, J. L.; Noordsij, A.; Van der Gaag, M. A., Monitoring response of XAD-concentrated water in the rhine delta: A major part of the toxic compounds remains unidentified. Water Res. 1994, 28, (3), 581-598.
27 ACS Paragon Plus Environment
Environmental Science & Technology
546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594
Page 28 of 30
34.
Penders, E.; Hoogenboezem, W., Evaluation of the Ames TA98, Umu and Comet assay for quality monitoring surface water. Association of River Waterworks-RIWA: 2003. 35. Ruff, M.; Mueller, M. S.; Loos, M.; Singer, H. P., Quantitative target and systematic non-target analysis of polar organic micro-pollutants along the river Rhine using high-resolution mass-spectrometry – Identification of unknown sources and compounds. Water Res. 2015, 87, 145-154. 36. Wegman, R. C. C.; De Korte, G. A. L., Aromatic amines in surface waters of The Netherlands. Water Res. 1981, 15, (3), 391-394. 37. Börnick, H., Schmidt, T. C., Amines. In Organic Pollutants in the Water Cycle, Reemtsma, T., Jekel, M., Ed. Wiley-VCH Verlag GmbH & Co. KGaA: Weinheim, 2006; pp 181-209. 38. ICPR International Commission for the Protection of the Rhine-Drinking water. http://www.iksr.org/en/uses/drinking-water/index.html 39. Brack, W., Effect-directed analysis: a promising tool for the identification of organic toxicants in complex mixtures? Anal. Bioanal. Chem. 2003, 377, (3), 397-407. 40. 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.-B.; Tindall, A. J.; De Aragão Umbuzeiro, G.; Vrana, B.; Krauss, M., Effect-directed analysis supporting monitoring of aquatic environments — An in-depth overview. Sci. Total Environ. 2016, 544, 1073-1118. 41. Brack, W.; Schirmer, K.; Erdinger, L.; Hollert, H., Effect-directed analysis of mutagens and ethoxyresorufin-O-deethylase inducers in aquatic sediments. Environ. Toxicol. Chem. 2005, 24, (10), 2445-2458. 42. Reifferscheid, G.; Buchinger, S.; Cao, Z.; Claus, E., Identification of mutagens in freshwater sediments by the Ames-fluctuation assay using nitroreductase and acetyltransferase overproducing test strains. Environ. Mol. Mutag. 2011, 52, (5), 397-408. 43. Shiozawa, T.; Tada, A.; Nukaya, H.; Watanabe, T.; Takahashi, Y.; Asanoma, M.; Ohe, T.; Sawanishi, H.; Katsuhara, T.; Sugimura, T.; Wakabayashi, K.; Terao, Y., Isolation and Identification of a New 2-Phenylbenzotriazole-Type Mutagen (PBTA-3) in the Nikko River in Aichi, Japan. Chem. Res. Toxicol. 2000, 13, (7), 535-540. 44. Muz, M.; Ost, N.; Kühne, R.; Schüürmann, G.; Brack, W.; Krauss, M., Nontargeted detection and identification of (aromatic) amines in environmental samples based on diagnostic derivatization and LChigh resolution mass spectrometry. Chemosphere 2017, 166, 300-310. 45. Ford, G. P.; Griffin, G. R., Relative stabilities of nitrenium ions derived from heterocyclic amine food carcinogens: Relationship to mutagenicity. Chem.-Biol. Interact. 1992, 81, (1), 19-33. 46. Bentzien, J.; Hickey, E. R.; Kemper, R. A.; Brewer, M. L.; Dyekjær, J. D.; East, S. P.; Whittaker, M., An in Silico Method for Predicting Ames Activities of Primary Aromatic Amines by Calculating the Stabilities of Nitrenium Ions. J. Chem. Inf. Model. 2010, 50, (2), 274-297. 47. Serafimova, R.; Todorov, M.; Pavlov, T.; Kotov, S.; Jacob, E.; Aptula, A.; Mekenyan, O., Identification of the Structural Requirements for Mutagencitiy, by Incorporating Molecular Flexibility and Metabolic Activation of Chemicals. II. General Ames Mutagenicity Model. Chem. Res. Toxicol. 2007, 20, (4), 662-676. 48. Schulze, T.; Ahel, M.; Ahlheim, J.; Aït-Aïssa, S.; Brion, F.; Di Paolo, C.; Fromet, J.; Hidasi, A. O.; Hollender, J.; Hollert, H.; Hu, M.; Kloß, A.; Koprivica, S.; Krauss, M.; Muz, M.; Oswald, P.; Petre, M.; Schollée, J. E.; Seiler, T.-B.; Shao, Y.; Slobodník, J.; Sonavane, M.; Suter, M. J.-F.; Tollefsen, K. E.; Tousova, Z.; Walz, K.-H.; Brack, W., Assessment of a novel device for onsite integrative large-volume solid phase extraction of water samples to enable a comprehensive chemical and effect-based analysis. Sci. Total Environ. 2016. 49. Umbuzeiro, G.; Machala, M.; Weiss, J., Diagnostic Tools for Effect-Directed Analysis of Mutagens, AhR Agonists, and Endocrine Disruptors. In Effect-Directed Analysis of Complex 28 ACS Paragon Plus Environment
Page 29 of 30
595 596 597 598 599 600 601 602 603 604 605 606 607 608 609 610 611 612 613 614 615 616 617 618 619 620 621 622 623 624 625 626 627 628 629 630 631 632 633 634 635 636 637 638 639 640 641 642
Environmental Science & Technology
Environmental Contamination, Brack, W., Ed. Springer Berlin Heidelberg: Berlin, Heidelberg, 2011; pp 69-82. 50. Reifferscheid, G.; Maes, H. M.; Allner, B.; Badurova, J.; Belkin, S.; Bluhm, K.; Brauer, F.; Bressling, J.; Domeneghetti, S.; Elad, T.; Flückiger-Isler, S.; Grummt, H. J.; Gürtler, R.; Hecht, A.; Heringa, M. B.; Hollert, H.; Huber, S.; Kramer, M.; Magdeburg, A.; Ratte, H. T.; Sauerborn-Klobucar, R.; Sokolowski, A.; Soldan, P.; Smital, T.; Stalter, D.; Venier, P.; Ziemann, C.; Zipperle, J.; Buchinger, S., International round-robin study on the Ames fluctuation test. Environ. Mol. Mutag. 2012, 53, (3), 185197. 51. Watanabe, M.; Ishidate, M.; Nohmi, T., Sensitive method for the detection of mutagenic nitroarenes and aromatic amines: new derivatives of Salmonella typhimurium tester strains possessing elevated O-acetyltransferase levels. Mutat. Res. Envir. Muta. 1990, 234, (5), 337-348. 52. Gallampois, C. J.; Schymanski, E.; Bataineh, M.; Buchinger, S.; Krauss, M.; Reifferscheid, G.; Brack, W., Integrated biological–chemical approach for the isolation and selection of polyaromatic mutagens in surface waters. Anal. Bioanal. Chem. 2013, 405, (28), 9101-9112. 53. Pluskal, T.; Castillo, S.; Villar-Briones, A.; Orešič, M., MZmine 2: Modular framework for processing, visualizing, and analyzing mass spectrometry-based molecular profile data. BMC Bioinformatics 2010, 11, (1), 1-11. 54. Ruttkies, C.; Schymanski, E. L.; Wolf, S.; Hollender, J.; Neumann, S., MetFrag relaunched: incorporating strategies beyond in silico fragmentation. J. Cheminform. 2016, 8, (1), 1-16. 55. Horai, H.; Arita, M.; Kanaya, S.; Nihei, Y.; Ikeda, T.; Suwa, K.; Ojima, Y.; Tanaka, K.; Tanaka, S.; Aoshima, K.; Oda, Y.; Kakazu, Y.; Kusano, M.; Tohge, T.; Matsuda, F.; Sawada, Y.; Hirai, M. Y.; Nakanishi, H.; Ikeda, K.; Akimoto, N.; Maoka, T.; Takahashi, H.; Ara, T.; Sakurai, N.; Suzuki, H.; Shibata, D.; Neumann, S.; Iida, T.; Tanaka, K.; Funatsu, K.; Matsuura, F.; Soga, T.; Taguchi, R.; Saito, K.; Nishioka, T., MassBank: a public repository for sharing mass spectral data for life sciences. J. Mass Spectrom. 2010, 45, (7), 703-714. 56. Schymanski, E. L.; Jeon, J.; Gulde, R.; Fenner, K.; Ruff, M.; Singer, H. P.; Hollender, J., Identifying Small Molecules via High Resolution Mass Spectrometry: Communicating Confidence. Environ. Sci. Technol. 2014, 48, (4), 2097-2098. 57. ChemAxon JChem for Excel 15.7.2700.2799. http://www.chemaxon.com 58. Prakash, C.; Shaffer, C. L.; Nedderman, A., Analytical strategies for identifying drug metabolites. Mass Spectrom. Rev. 2007, 26, (3), 340-369. 59. Liu, D. Q.; Wu, L.; Sun, M.; MacGregor, P. A., On-line H/D exchange LC–MS strategy for structural elucidation of pharmaceutical impurities. J. Pharm. Biomed. Anal. 2007, 44, (2), 320-329. 60. Pfeifer, T.; Tuerk, J.; Fuchs, R., Structural Characterization of Sulfadiazine Metabolites Using H/D Exchange Combined with Various MS/MS Experiments. J. Am. Soc. Mass Spectrom. 2005, 16, (10), 1687-1694. 61. Stewart, J. J. P., Optimization of parameters for semiempirical methods VI: more modifications to the NDDO approximations and re-optimization of parameters. J. Mol. Model. 2013, 19, (1), 1-32. 62. Kamber, M.; Flückiger-Isler, S.; Engelhardt, G.; Jaeckh, R.; Zeiger, E., Comparison of the Ames II and traditional Ames test responses with respect to mutagenicity, strain specificities, need for metabolism and correlation with rodent carcinogenicity. Mutagenesis 2009, 24, (4), 359-366. 63. Totsuka, Y.; Takamura-Enya, T.; Nishigaki, R.; Sugimura, T.; Wakabayashi, K., Mutagens formed from β-carbolines with aromatic amines. J. Chromatogr. B 2004, 802, (1), 135-141. 64. Nagao, M.; Yahagi, T.; Sugimura, T., Differences in effects of norharman with various classes of chemical mutagens and amounts of S-9. Biochem. Biophys. Res. Commun. 1978, 83, (2), 373-378. 65. Totsuka, Y.; Takamura-Enya, T.; Kawahara, N.; Nishigaki, R.; Sugimura, T.; Wakabayashi, K., Structure of DNA Adduct Formed with Aminophenylnorharman, Being Responsible for the Comutagenic Action of Norharman with Aniline. Chem. Res. Toxicol. 2002, 15, (10), 1288-1294.
29 ACS Paragon Plus Environment
Environmental Science & Technology
643 644 645 646 647 648 649 650 651 652 653 654 655 656 657 658 659 660 661 662 663 664 665 666 667 668 669 670 671 672 673 674 675 676 677 678 679 680 681 682 683 684 685 686 687 688 689 690 691
Page 30 of 30
66.
Hada, N.; Totsuka, Y.; Enya, T.; Tsurumaki, K.; Nakazawa, M.; Kawahara, N.; Murakami, Y.; Yokoyama, Y.; Sugimura, T.; Wakabayashi, K., Structures of mutagens produced by the co-mutagen norharman with o- and m-toluidine isomers. Mutat. Res. Genet. Toxicol. Environ. Mutagen. 2001, 493, (1–2), 115-126. 67. Oda, Y.; Totsuka, Y.; Wakabayashi, K.; Guengerich, F. P.; Shimada, T., Activation of aminophenylnorharman, aminomethylphenylnorharman and aminophenylharman to genotoxic metabolites by human N-acetyltransferases and cytochrome P450 enzymes expressed in Salmonella typhimurium umu tester strains. Mutagenesis 2006, 21, (6), 411-416. 68. Picada, J. N.; da Silva, K. V. C. L.; Erdtmann, B.; Henriques, A. T.; Henriques, J. A. P., Genotoxic effects of structurally related β-carboline alkaloids. Mutat. Res. Fund. Mol. M. 1997, 379, (2), 135-149. 69. Gross, G. A.; Turesky, R. J.; Fay, L. B.; Stillwell, W. G.; Skipper, P. L.; Tannenbaum, S. R., Heterocyclic aromatic amine formation in grilled bacon, beef and fish and in grill scrapings. Carcinogenesis 1993, 14, (11), 2313-2318. 70. Totsuka, Y.; Kataoka, H.; Takamura-Enya, T.; Sugimura, T.; Wakabayashi, K., In vitro and in vivo formation of aminophenylnorharman from norharman and aniline. Mutat. Res. Fund. Mol. M. 2002, 506–507, 49-54. 71. Ohnishi, S.; Murata, M.; Oikawa, S.; Totsuka, Y.; Takamura, T.; Wakabayashi, K.; Kawanishi, S., Oxidative DNA damage by an N-hydroxy metabolite of the mutagenic compound formed from norharman and aniline. Mutat. Res. Genet. Toxicol. Environ. Mutagen. 2001, 494, (1–2), 63-72. 72. Guengerich, F. P., Common and Uncommon Cytochrome P450 Reactions Related to Metabolism and Chemical Toxicity. Chem. Res. Toxicol. 2001, 14, (6), 611-650. 73. Kawamori, T.; Totsuka, Y.; Uchiya, N.; Kitamura, T.; Shibata, H.; Sugimura, T.; Wakabayashi, K., Carcinogenicity of aminophenylnorharman, a possible novel endogenous mutagen, formed from norharman and aniline, in F344 rats. Carcinogenesis 2004, 25, (10), 1967-1972. 74. Kohno, H.; Totsuka, Y.; Yasui, Y.; Suzuki, R.; Sugie, S.; Wakabayashi, K.; Tanaka, T., Tumorinitiating potency of a novel heterocyclic amine, aminophenylnorharman in mouse colonic carcinogenesis model. Int. J. Cancer 2007, 121, (8), 1659-1664. 75. Nishigaki, R.; Totsuka, Y.; Kataoka, H.; Ushiyama, H.; Goto, S.; Akasu, T.; Watanabe, T.; Sugimura, T.; Wakabayashi, K., Detection of aminophenylnorharman, a possible endogenous mutagenic and carcinogenic compound, in human urine samples. Cancer Epidemiol. Biomarkers Prev. 2007, 16, (1), 151-156. 76. Fukazawa, H.; Matsushita, H.; Terao, Y., Identification of co-mutagenic chlorinated harmans in final effluent from a sewage treatment plant. Mutat. Res. Genet. Toxicol. Environ. Mutagen. 2001, 491, (1–2), 65-70. 77. Boeira, J. M.; Viana, A. F.; Picada, J. N.; Henriques, J. A. P., Genotoxic and recombinogenic activities of the two β-carboline alkaloids harman and harmine in Saccharomyces cerevisiae. Mutat. Res. Fund. Mol. M. 2002, 500, (1–2), 39-48. 78. Stoltz, D. R., Detection of Cocarcinogens and Anticarcinogens with Microbial Mutagenicity Assays. In Short-Term Tests for Chemical Carcinogens, Stich, H. F., San, R. H. C., Ed. Springer: New York, 1981; pp 438-448. 79. Moeller, M.; Alfheim, I.; Larssen, S.; Mikalsen, A., Mutagenicity of airborne particles in relation to traffic and air pollution parameters. Environ. Sci. Technol. 1982, 16, (4), 221-225. 80. Marvin, C. H.; Lundrigan, J. A.; McCarry, B. E.; Bryant, D. W., Determination and genotoxicity of high molecular mass polycyclic aromatic hydrocarbons isolated from coal-tar-contaminated sediment. Environ. Toxicol. Chem. 1995, 14, (12), 2059-2066. 81. Mäki-Paakkanen, J.; Komulainen, H.; Kronberg, L., Bacterial and mammalian-cell genotoxicity of mixtures of chlorohydroxyfuranones, by-products of water chlorination. Environ. Mol. Mutag. 2004, 43, (4), 217-225. 30 ACS Paragon Plus Environment