wagner2017

Prévia do material em texto

1Q5
2Q9
3
4Q6Q7
5Q8
6
7
910
11
12
13
14
15
35
36
37
3839
40
41
4243
44
45
46
47
J O U R N A L O F E N V I R O N M E N T A L S C I E N C E S X X ( 2 0 1 7 ) X X X – X X X
Ava i l ab l e on l i ne a t www.sc i enced i r ec t . com
ScienceDirect
www.e l sev i e r . com/ loca te / j es
JES-01151; No of Pages 13
F
Invited Article
CHO cell cytotoxicity and genotoxicity analyses of disinfection
by-products: An updated review
O
O
Elizabeth D. Wagner⁎, Michael J. Plewa
Safe Global Water Institute, University of Illinois at Urbana-Champaign, 1101 W Peabody Dr., Urbana, IL 61801, United States
Department of Crop Sciences, University of Illinois at Urbana-Champaign, 1101 W Peabody Dr., Urbana, IL 61801, United States
R
A R T I C L E I N F O
O
R
⁎ Corresponding author. E-mail: edwagner@il
http://dx.doi.org/10.1016/j.jes.2017.04.021
1001-0742 © 2017 The Research Center for Ec
Please cite this article as:Wagner, E.D., Ple
updated review, J. Environ. Sci. (2017), htt
A B S T R A C T
 P
16
17
18
19
20
Article history:
Received 1 February 2017
Revised 25 March 2017
Accepted 20 April 2017
Available online xxxx
21
22
23
24
25
26
27
28
29
30
31
32
33
34
R
E
C
T
E
D
 The disinfection of drinking water is an important public health service that generates high
quality, safe and palatable tap water. The disinfection of drinking water to reduce
waterborne disease was an outstanding public health achievement of the 20th century.
An unintended consequence is the reaction of disinfectants with natural organic matter,
anthropogenic contaminants and bromide/iodide to form disinfection by-products (DBPs).
A large number of DBPs are cytotoxic, neurotoxic, mutagenic, genotoxic, carcinogenic and
teratogenic. Epidemiological studies demonstrated low but significant associations
between disinfected drinking water and adverse health effects. The distribution of DBPs
in disinfected waters has been well defined by advances in high precision analytical
chemistry. Progress in the analytical biology and toxicology of DBPs has been forthcoming.
The objective of this review was to provide a detailed presentation of the methodology for
the quantitative, comparative analyses on the induction of cytotoxicity and genotoxicity of
103 DBPs using an identical analytical biological platform and endpoints. A single Chinese
hamster ovary cell line was employed in the assays. The data presented are derived from
papers published in the literature as well as additional new data and represent the largest
direct quantitative comparison on the toxic potency of both regulated and emerging DBPs.
These data may form the foundation of novel research to define the major forcing agents of
DBP-mediated toxicity in disinfected water andmay play an important role in achieving the
goal of making safe drinking water better.
© 2017 The Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences.
Published by Elsevier B.V.
C
N
Contents
 U
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0
1. Materials and methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0
1.1. Chinese hamster ovary cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0
1.2. CHO cell chronic cytotoxicity assay . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0
linois.edu (Elizabeth D. Wagner).
o-Environmental Sciences, Chinese Academy of Sciences. Published by Elsevier B.V.
wa,M.J., CHO cell cytotoxicity and genotoxicity analyses of disinfection by-products: An
p://dx.doi.org/10.1016/j.jes.2017.04.021
http://dx.doi.org/10.1016/j.jes.2017.04.021
mailto:edwagner@illinois.edu
Journal logo
http://dx.doi.org/10.1016/j.jes.2017.04.021
Imprint logo
http://dx.doi.org/10.1016/j.jes.2017.04.021
48
49
50
51
52
53
54
55
5657
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
2 J O U R N A L O F E N V I R O N M E N T A L S C I E N C E S X X ( 2 0 1 7 ) X X X – X X X
1.3. Normalization of CHO cytotoxicity data and statistical analyses . . . . . . . . . . . . . . . . . . . . . . . . . . 0
1.4. CHO cell acute genotoxicity assay . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0
1.5. Normalization of CHO genotoxicity data and statistical analyses . . . . . . . . . . . . . . . . . . . . . . . . . . 0
2. Results and discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0
2.1. Review of CHO cell cytotoxicity and genotoxicity data for DBPs . . . . . . . . . . . . . . . . . . . . . . . . . . . 0
3. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0
T
105106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
U
N
C
O
R
R
E
C
Introduction
The drinking water community provides an exceedingly
important public health service for the nations they serve
by its generation of high quality, safe and palatable tapwater.
The disinfection of drinking water to reduce waterborne
disease was arguably the greatest public health achievement
of the 20th century (Calderon, 2000). Chemical and physical
disinfectants inactivate pathogens in source water. An
unintended consequence is the reaction of disinfectants
with natural organic matter, anthropogenic contaminants
and bromide/iodide to form disinfection by-products (DBPs)
(Richardson and Postigo, 2015). Characteristics of the source
water including the concentration and type of organic
matter, pH, temperature, disinfectant type and concentra-
tion, and contact time affect the formation of DBPs (Hong et
al., 2013; Singer, 1994). The most widely employed disinfec-
tants include chlorine, chloramines, chlorine dioxide, and
ozone. Each disinfectant generates DBPs with a different
spectra of chemical classes (Hua and Reckhow, 2007; Zhang et
al., 2000). Since the discovery of DBPs (Bellar et al., 1974; Rook,
1974) over 600 DBPs have been identified (Richardson and
Postigo, 2015). This number of DBPs represents only a fraction
of the total organic halogen generated in disinfected water.
Of this number, approximately 100 have undergone system-
atic, quantitative, comparative toxicological analyses (Plewa
and Wagner, 2015). A large number of DBPs are cytotoxic,
neurotoxic, mutagenic, genotoxic, carcinogenic and terato-
genic (Richardson et al., 2007). Epidemiological research
demonstrated low but significant associations between
disinfected drinking water and adverse health effects
(Richardson et al., 2007) including cancer of the bladder
(Bove et al., 2007b; Costet et al., 2011; Villanueva et al., 2004),
colon (King et al., 2000; Rahman et al., 2010) and rectum (Bove
et al., 2007a). Some studies report a weak association with
adverse pregnancy outcomes and DBPs, however, the evi-
dence is inconclusive (Bove et al., 2002; Colman et al., 2011;
Grellier et al., 2010; Rivera-Nunez andWright, 2013; Wright et
al., 2016).
The objective of this review was to provide a detailed
presentation of the methodology for the quantitative, compar-
ative analyses on the induction of cytotoxicity and genotoxicity
of 103DBPs using an identical analytical biological platformand
endpoints. Chinese hamster ovary (CHO) cells were employed
as themammalian cells used in the assays. The data presented
are derived from papers published in the literature as well as
additional new data and represent the largestdirect quantita-
tive comparison on the toxic potency of both regulated and
emerging DBPs.
Please cite this article as:Wagner, E.D., Plewa,M.J., CHO cell cytotox
updated review, J. Environ. Sci. (2017), http://dx.doi.org/10.1016/j.je
E
D
 P
R
O
O
F
1. Materials and methods
1.1. Chinese hamster ovary cells
CHO cells are widely used in toxicology. CHO cell line AS52
(Tindall and Stankowski, 1989; Tindall et al., 1984) was derived
from K1-BH4 (Hsie et al., 1975a, 1975b). Clone 11-4-8 was
isolated from AS52 by E. Wagner and it expresses a stable
chromosome complement and a consistent cell doubling time
(Wagner et al., 1998a, 1998b). The cells are immortalized;
however, they express cell contact inhibition and thus are not
neoplastic. The cells contain a mutant allele of p53, however,
the missense mutation at codon 211 has no effect on the
functional properties of the protein. (Hu et al., 1999; Tzang et
al., 1999). Stock cultures of the CHO cells were frozen in a
solution of 90% fetal bovine serum (FBS):10% dimethyl
sulfoxide (DMSO) (v/v) and stored at −80°C. The CHO cells
weremaintained in Ham's F12medium containing 5% FBS, 1%
antibiotics (100 U/mL sodium penicillin G, 100 μg/mL strepto-
mycin sulfate, 0.25 μg/mL amphotericin B in 0.85% saline), and
1% glutamine at 37°C in a humidified atmosphere of 5% CO2.
The cells exhibit adherent, normal morphology, express cell
contact inhibition and grow as a monolayer without expres-
sion of neoplastic foci. CHO cells were transferred to a new
culture plate when the culture became confluent.
1.2. CHO cell chronic cytotoxicity assay
The CHO cell microplate chronic cytotoxicity assaymeasures the
reduction in cell density within amicroplate well as a function of
the concentration of the test agent over a 72 hr period (Plewa et
al., 2002; Plewa andWagner, 2009). A sterile 96-well flat-bottomed
microplate was used to evaluate a series of chemical concentra-
tions. One column of eight microplate wells served as the blank
control consisting of 200 μL of F12 + FBS medium only. The
concurrent negative control column consisted of eight wells with
3 × 103 CHO cells plus F12 + FBS medium. The wells of the
remaining columns contained 3 × 103 CHO cells, F12 + FBS and
knownDBP concentrations in a total of 200 μL perwell. Thewells
were covered with a sheet of sterile AlumnaSeal™ and the cells
were incubated for several cell generations at 72 hr at 37°C in 5%
CO2. After the treatment time, the medium from each well was
aspirated, the cells fixed in methanol for 5 min and stained for
5 min with a 1% crystal violet solution in 50% methanol. The
microplate was repeatedly washed in tap water, 50 μL of a
solution of DMSO/methanol (3:1 v/v) was added to eachwell, and
the plate was incubated at room temperature for 10 min in dim
light. The microplate was analyzed at 595 nm with a microplate
reader; the absorbance of eachwell was recorded and stored on a
icity and genotoxicity analyses of disinfection by-products: An
s.2017.04.021
http://dx.doi.org/10.1016/j.jes.2017.04.021
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
3J O U R N A L O F E N V I R O N M E N T A L S C I E N C E S X X ( 2 0 1 7 ) X X X – X X X
spreadsheet file. This assay was calibrated and there is a direct
relationship between the absorbance of the crystal violet dye
associated with the cell membranes and the number of viable
cells (Plewa et al., 2002; Plewa andWagner, 2009). A flow diagram
for the CHO cell chronic cytotoxicity assay is presented in Fig. 1.
1.3. Normalization of CHO cytotoxicity data and statistical
analyses
The data from the microplate reader were transferred to an
Excel spreadsheet (Table 1A). The averaged absorbance of the
blank wells was subtracted from the absorbance data from
U
N
C
O
R
R
E
C
T
Fig. 1 – Flow diagram for the CHO cell chronic cyt
Please cite this article as:Wagner, E.D., Plewa,M.J., CHO cell cytotox
updated review, J. Environ. Sci. (2017), http://dx.doi.org/10.1016/j.je
each well to yield blank-corrected data (Table 1B). The mean
blank-corrected absorbance value of the negative control was
set at 100% and the absorbance for each treatment group well
was converted into a percentage of the concurrent negative
control (Table 1C). This procedure normalized the data,
maintained the variance and allowed for the combination of
data from multiple microplates to generate a summary sheet
(Table 2). In general, a range-finding experiment was con-
ducted, followed by experiments with 4 wells or 8 wells per
concentration for each DBP analyzed. These data were used to
generate a concentration–response curve for each DBP (Fig. 2,
left panel). Regression analysis was applied to each DBP
E
D
 P
R
O
O
F
otoxicity assay. CHO: Chinese hamster ovary.
icity and genotoxicity analyses of disinfection by-products: An
s.2017.04.021
http://dx.doi.org/10.1016/j.jes.2017.04.021
E
C
T
E
D
 P
R
O
O
F
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
Table 1t1:1 – Normalization of CHO cell cytotoxicity data for iodoacetamide.Q1Q2
t1:2t1:3
t1:4 Iodoacetamide experiment CHO cytotoxicity RAW DATA
t1:5 0 Blank 0.5 1 1.1 1.2 1.25 1.375 1.5 1.75 2 2.5 μM
t1:6 0.372 0.131 0.312 0.304 0.334 0.289 0.297 0.285 0.321 0.227 0.223 0.147
t1:7 0.335 0.125 0.326 0.235 0.231 0.240 0.219 0.240 0.206 0.173 0.166 0.147
t1:8 0.363 0.124 0.256 0.291 0.256 0.245 0.219 0.211 0.204 0.179 0.155 0.132
t1:9 0.304 0.126 0.255 0.286 0.248 0.252 0.225 0.221 0.248 0.174 0.152 0.118 A
t1:10 0.348 0.129 0.314 0.305 0.261 0.265 0.243 0.220 0.203 0.186 0.154 0.116
t1:11 0.384 0.138 0.241 0.242 0.271 0.227 0.235 0.206 0.220 0.205 0.134 0.144
t1:12 0.357 0.164 0.290 0.254 0.259 0.247 0.254 0.250 0.227 0.186 0.157 0.139
t1:13 0.389 0.153 0.282 0.272 0.298 0.293 0.284 0.312 0.256 0.213 0.198 0.140
t1:14 0.136
t1:15 Iodoacetamide experiment CHO cytotoxicity BLANK CORRECTED DATA
t1:16 0 Blank 0.5 1 1.1 1.2 1.25 1.375 1.5 1.75 2 2.5 μM
t1:17 0.236 0.176 0.168 0.198 0.153 0.161 0.149 0.185 0.091 0.087 0.011
t1:18 0.199 0.190 0.099 0.095 0.104 0.083 0.104 0.070 0.037 0.030 0.011
t1:19 0.227 0.120 0.155 0.120 0.109 0.083 0.075 0.068 0.043 0.019 −0.004
t1:20 0.168 0.119 0.150 0.112 0.116 0.089 0.085 0.112 0.038 0.016 −0.018 B
t1:21 0.212 0.178 0.169 0.125 0.129 0.107 0.084 0.067 0.050 0.018 −0.020
t1:22 0.248 0.105 0.106 0.135 0.091 0.099 0.070 0.084 0.069 0.002 0.008
t1:23 0.221 0.154 0.118 0.123 0.111 0.118 0.114 0.091 0.050 0.021 0.003
t1:24 0.253 0.146 0.136 0.162 0.157 0.148 0.176 0.120 0.077 0.062 0.004
t1:25 0.221
t1:26 Iodoacetamide experiment CHO cytotoxicity % NEGATIVE CONTROL
t1:27 0 Blank 0.5 1 1.1 1.2 1.25 1.375 1.5 1.75 2 2.5 μM
t1:28 106.79 79.64 76.02 89.59 69.23 72.85 67.42 83.71 41.18 39.37 4.98
t1:29 90.05 85.97 44.80 42.99 47.06 37.56 47.06 31.67 16.74 13.57 4.98
t1:30 102.71 54.30 70.14 54.30 49.32 37.56 33.94 30.77 19.46 8.60 −1.81
t1:31 76.02 53.85 67.87 50.68 52.49 40.27 38.46 50.68 17.19 7.24 −8.14 CQ3
t1:32 95.93 80.54 76.47 56.56 58.37 48.42 38.01 30.32 22.62 8.14 −9.05
t1:33 112.22 47.51 47.96 61.09 41.18 44.80 31.67 38.01 31.22 −0.90 3.62
t1:34 100.00 69.68 53.39 55.66 50.23 53.39 51.58 41.18 22.62 9.50 1.36
t1:35 114.48 66.06 61.54 73.30 71.04 66.97 79.64 54.30 34.84 28.05 1.81
t1:36 CHO: Chinese hamster ovary.t1:37
4 J O U R N A L O F E N V I R O N M E N T A L S C I E N C E S X X ( 2 0 1 7 ) X X X – X X X
U
N
C
O
R
R
concentration–response curve, which was used to calculate
the LC50 value. The LC50 value is the calculated DBP concen-
tration, from the regression analyses, that induced a cell
density that was 50% of the negative control.
For each concentration of a DBP within a concentration–
response curve, the lowest concentration that induced a
significant level of cytotoxicity was determined using an
analysis of variance (ANOVA) test statistic (Box et al., 1978).If
a significant F value of p ≤ 0.05 was obtained, a Holm-Sidak
multiple comparison versus the control group analysis was
conducted. The power of the test statistic (1 − β) was main-
tained as ≥0.8 at α = 0.05. Should this statistical power notmeet
this standard, the experiment was repeated until the power of
the statistic equaled ≥0.8.
Todetermine significant differences amongdifferentDBPs, a
bootstrap statistical approach was used to generate a series of
multiple LC50 values for each DBP (Singh and Xie, 2008; Varian,
2005). With this approach, ANOVA tests for significance among
individual DBPs can be conducted. Using a CHO cell cytotoxicity
summary sheet as illustrated in Table 2, the empty cells are
filled by copying a cell at a specific concentration, using a
random number generator (Excel), and pasting into an empty
cell. An example of a balanced table is presented in Table 3.
Please cite this article as:Wagner, E.D., Plewa,M.J., CHO cell cytotox
updated review, J. Environ. Sci. (2017), http://dx.doi.org/10.1016/j.je
Multiple LC50 values were generated. For each LC50 value a
cytotoxicity index (CTI) value was calculated as (LC50−1)(103) (Table
3, Fig. 2, right panel). Although increased CTI values represent
increased toxicity, the relationship is not directly proportional
when directly compared with the LC50 values. These values were
then analyzed using an ANOVA test to determine significant
differences among the DBPs within a chemical class (Fig. 2).
1.4. CHO cell acute genotoxicity assay
The genotoxic endpoint employed in this comparison of DBPs
was single cell gel electrophoresis (SCGE). The SCGE or Comet
assay is a molecular genetic assay that can quantitatively
measure the level of genomic DNA damage induced in
individual nuclei of cells (Fairbairn et al., 1995; Rundell et al.,
2003; Tice et al., 2000). We adapted the assay to be used in
96-well microplates with a treatment volume of 25 μL (Wagner
and Plewa, 2009). The day prior to treatment, 4 × 104 CHO cells
were added to each microplate well in 200 μL of F12 + 5% FBS
medium and incubated. The next day the cells were washed
with Hank's balanced salt solution (HBSS) and treated with a
series of concentrations of a specific DBP in F12 medium
without FBS in a total volume of 25 μL for 4 hr at 37°C, 5% CO2.
icity and genotoxicity analyses of disinfection by-products: An
s.2017.04.021
http://dx.doi.org/10.1016/j.jes.2017.04.021
R
R
E
C
T
E
D
 P
R
O
O
F
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
Table 2t2:1 – Summary sheet of multiple CHO experiments on the cytotoxicity of iodoacetamide.
t2:2t2:3
t2:4 Iodoacetamide: CHO cell cytotoxicity percent negative control summary sheet
t2:5 0 0.01 0.025 0.05 0.1 0.25 0.5 0.75 1 1.1 1.15 1.2 1.25 1.375 1.5 1.75 2 2.5 μM
t2:6 119.08 109.35 92.37 90.27 92.94 83.02 80.53 78.63 84.54 13.36 0.19
t2:7 89.12 87.02 91.03 89.69 103.24 79.39 77.48 83.78 82.63 11.07 −3.24
t2:8 96.95 92.37 100.57 97.14 100.19 81.87 88.74 79.20 77.86 15.65 −1.15
t2:9 92.37 92.75 91.41 92.18 95.80 95.61 75.19 68.13 63.17 12.40 −0.19
t2:10 86.64 85.50 99.05 86.26 94.08 94.85 72.14 79.58 56.87 22.71 −0.19
t2:11 97.14 85.11 86.64 83.97 91.03 80.73 79.39 78.24 66.22 12.21 −1.34
t2:12 116.03 89.31 95.04 94.08 102.10 102.86 88.74 82.25 63.74 17.75 −0.19
t2:13 103.05 83.40 91.41 96.76 82.82 84.54 83.59 74.43 62.79 13.36 −1.91
t2:14 70.30 125.50 117.62 94.97 86.07 89.93 78.69 81.21 54.87 17.28 −3.36
t2:15 87.08 92.45 111.07 79.53 77.35 67.28 66.44 66.44 43.12 19.13 −0.67
t2:16 102.85 97.65 110.91 95.81 93.96 93.29 83.89 56.88 45.64 15.94 −0.50
t2:17 107.89 97.32 108.22 84.23 84.06 82.55 69.13 56.71 38.59 11.24 −0.50
t2:18 97.65 110.40 115.77 104.19 76.17 68.79 83.56 57.89 38.26 18.79 1.68
t2:19 118.96 117.28 100.67 111.41 82.72 75.50 83.56 55.70 33.72 15.10 −4.36
t2:20 99.66 107.38 116.44 106.54 99.50 80.54 84.06 95.13 43.46 31.71 3.19
t2:21 116.11 94.13 102.18 92.79 86.41 83.72 78.36 80.03 41.78 16.95 2.35
t2:22 68.12 101.93 102.90 68.60 86.96 69.57 63.77 47.83 19.81 9.66 −5.80
t2:23 80.68 85.02 72.95 72.46 80.19 76.81 66.67 50.72 15.46 1.45 −21.26
t2:24 114.49 85.99 82.61 70.53 59.90 60.39 47.34 46.38 7.25 −4.35 −22.71
t2:25 108.70 90.82 86.96 67.15 77.78 72.95 77.29 52.17 8.70 0.97
t2:26 113.04 95.17 83.57 74.88 71.50 80.19 57.49 43.96 8.70 5.31 −15.46
t2:27 112.08 85.51 67.15 63.77 71.50 57.49 66.18 43.96 12.08 −4.35 −19.32
t2:28 103.86 114.01 83.09 95.65 82.13 75.85 59.90 73.43 41.06 10.63 −11.11
t2:29 106.79 77.78 64.73 69.57 75.85 74.40 69.57 39.13 30.92 15.46 18.84
t2:30 90.05 79.64 76.02 89.59 69.23 72.85 67.42 83.71 41.18 39.37 4.98
t2:31 102.71 85.97 44.80 42.99 47.06 37.56 47.06 31.67 16.74 13.57 4.98
t2:32 76.02 54.30 70.14 54.30 49.32 37.56 33.94 30.77 19.46 8.60 −1.81
t2:33 95.93 53.85 67.87 50.68 52.49 40.27 38.46 50.68 17.19 7.24 −8.14
t2:34 112.22 80.54 76.47 56.56 58.37 48.42 38.01 30.32 22.62 8.14 −9.05
t2:35 100.00 47.51 47.96 61.09 41.18 44.80 31.67 38.01 31.22 −0.90 3.62
t2:36 114.48 69.68 53.39 55.66 50.23 53.39 51.58 41.18 22.62 9.50 1.36
t2:37 100.00 66.06 61.54 73.30 71.04 66.97 79.64 54.30 34.84 28.05 1.81
t2:38 32 8 8 8 8 16 32 8 24 24 16 24 24 16 32 16 24 31 Number
t2:39 100.00 90.60 93.44 91.29 95.28 96.56 87.58 78.03 82.14 73.63 70.36 69.68 63.31 56.00 38.00 21.87 12.27 −2.88 Average
t2:40 2.43 2.93 1.62 1.66 2.37 3.37 3.31 1.72 3.15 2.82 3.90 2.78 3.11 3.82 3.07 2.77 2.18 1.51 SE
t2:41 13.74 8.30 4.57 4.71 6.70 13.50 18.75 4.87 15.43 13.82 15.59 13.63 15.24 15.29 17.39 11.06 10.68 8.41 SD
t2:42 CHO: Chinese hamster ovary.t2:43
5J O U R N A L O F E N V I R O N M E N T A L S C I E N C E S X X ( 2 0 1 7 ) X X X – X X X
U
N
C
OThis treatment time was determined empirically to capture theinduction of genomic DNA damage while reducing the impact
of DNA repair on restoring nuclei integrity (Komaki, 2013;
Rundell et al., 2003). The wells were covered with sterile
AlumnaSeal™ to prevent the escape of volatiles from the
microplate well. With each experiment, a negative control, a
positive control of 3.8 mM ethyl methanesulfonate, (EMS) and 9
concentrations of a specific DBP were conducted concurrently.
After incubation the cells were washed 2× with HBSS and
harvestedwith 50 μL of 0.01% trypsin +53 μMEDTA. The trypsin
was inactivated with 70 μL of F12 + FBS. To measure acute
cytotoxicity (after a 4-h exposure) a 10 μL aliquot of cell
suspension was mixed with 10 μL of 0.05% trypan blue vital
dye in phosphate-buffered saline (PBS) (Phillips, 1973). SCGE
data were not used if the acute cytotoxicity exceeded 30%. Prior
to the experiment, clear microscope slides were coated with a
layer of 1% normal melting point agarose prepared with
deionized water and dried overnight. After cell treatment and
harvesting, the cell suspension from each well was embedded
in a layer of molten (42°C) low melting point agarose prepared
Please cite this article as:Wagner, E.D., Plewa,M.J., CHO cell cytotox
updated review, J. Environ. Sci. (2017), http://dx.doi.org/10.1016/j.je
with PBS and placed upon the prepared slides. After the
microgels solidified on a tray placed over ice, a final layer of
molten 0.5% low melting point agarose prepared with PBS was
placed upon the previous layers. The cellular membranes were
removed by an overnight immersion in lysing solution at 4°C.
The slides were placed in an alkaline buffer (pH 13.5) in an
electrophoresis tank and the DNA was denatured for 20 min.
The microgels were electrophoresed at 25 V, 300 mA (0.72 V/
cm) for 40 min at 4°C. The microgels were removed from the
tank, neutralized with Tris buffer, pH 7.5, rinsed in cold water,
dehydrated in cold methanol, dried at 50°C and stored at room
temperature in a covered slide box.
For microscopic analysis, the microgels were hydrated in
cold water for 20–30 min and stained with 65 μL of ethidium
bromide (20 μg/mL) for 3 min. Themicrogelswere rinsed in cold
water and were analyzed witha Zeiss fluorescencemicroscope
with an excitation filter of 546/10 nm and a barrier filter of
590 nm. For each experiment, 2 microgels were prepared per
treatment group. Twenty-five randomly chosen nuclei were
analyzed in each microgel using a charged coupled device
icity and genotoxicity analyses of disinfection by-products: An
s.2017.04.021
http://dx.doi.org/10.1016/j.jes.2017.04.021
R
O
O
F
257
258
259
260
261
262
263
264
Fig. 2 – Concentration–response curves for the cytotoxicity of iodoacetamide (IAM), bromoacetamide (BAM) or chloroacetamide
(CAM) (left panel). Comparison of the cytotoxicity index values for IAM, BAM and CAM (right panel). Using themean CTI values
and conducting an ANOVA all pair-wise analyses these three samples followed the rank order of IAM > BAM >> CAM andwere
statistically significantly different from each other (F2, 78 = 606.9; p < 0.001). CTI: cytotoxicity index.
t3:1
t3:2
t3:3
t3:4
t3:5
t3:6
t3:7
t3:8
t3:9
t3:10
t3:11
t3:12
t3:13
t3:14
t3:15
t3:16
t3:17
t3:18
t3:19
t3:20
t3:21
t3:22
t3:23
t3:24
t3:25
t3:26
t3:27
t3:28
t3:29
t3:30t3:31
t3:32
Q4 t3:33
6 J O U R N A L O F E N V I R O N M E N T A L S C I E N C E S X X ( 2 0 1 7 ) X X X – X X X
camera. A computerized image analysis system (CometAssay IV;
Perceptive Instruments Ltd., Suffolk, UK) was used to measure a
number of specific SCGE parameters of 25 randomly chosen
nuclei permicrogel. The intensity of the DNA thatmigrated away
U
N
C
O
R
R
E
C
T
Table 3 – Generation of multiple LC50 values and cytotoxicity in
chloroacetamide.
Chloroacetamide: CHO Cytotoxicity Percent Nega
0 5 10 25 35 50 75 100 120
100 83.75 90.20 92.44 103.42 75.63 55.74 61.90 58.75
100 95.80 95.24 97.76 111.97 73.39 71.99 52.94 61.54
100 83.75 90.20 100.00 111.97 114.53 88.03 79.49 81.20
100 95.80 95.24 108.55 94.87 93.16 76.92 68.38 66.67
100 83.75 90.20 106.84 98.29 94.87 76.07 69.23 61.54
100 95.80 95.24 96.58 103.42 95.73 82.05 72.65 62.39
100 83.75 90.20 105.13 91.45 91.45 82.05 85.47 58.97
100 95.80 95.24 93.16 100.85 85.47 74.36 68.38 61.54
100 83.75 90.20 130.77 117.95 108.55 100.00 88.03 88.03
100 95.80 95.24 100.00 73.50 96.58 80.34 64.96 62.39
100 83.75 90.20 77.50 91.45 91.45 72.00 95.50 66.50
100 95.80 95.24 84.00 117.95 108.55 75.50 78.75 60.50
100 83.75 90.20 97.75 94.87 91.45 97.00 71.00 69.00
100 95.80 95.24 93.25 73.50 75.63 88.25 72.00 61.75
100 83.75 90.20 96.50 100.85 108.55 87.00 72.00 58.75
100 95.80 95.24 90.50 111.97 91.45 75.25 73.00 67.25
100 83.75 90.20 124.50 98.29 96.58 83.50 80.25 74.75
100 95.80 95.24 107.00 111.97 94.87 85.00 80.75 72.50
CHO: Chinese hamster ovary.
a Regression of each response in the concentration and the calculation o
b Calculation of a CTI value for each line.
c LC50 value from the concentration–response curve.
Please cite this article as:Wagner, E.D., Plewa,M.J., CHO cell cytotox
updated review, J. Environ. Sci. (2017), http://dx.doi.org/10.1016/j.je
D
 Pfrom the nucleus (%Tail DNA) was the primary metric of DNA
damage that was used for the concentration–response curves
(Kumaravel and Jha, 2006). In older publications we reported tail
moment (integrated value ofmigratedDNAdensitymultiplied by
E
dex (CTI) values from the concentration–response data for
tive Control Bootstrap Statistic Summary Sheet
140 160 180 200 500 LC50 a CTI b c μM
40.25 33.00 34.25 22.13 9.00 122.17 8.18
41.88 45.75 17.09 15.97 −0.75 125.35 7.98
47.86 43.59 29.91 21.37 9.75 148.19 6.75
46.15 38.46 21.37 17.09 9.00 134.94 7.41
53.85 27.35 17.09 29.91 0.00 135.61 2.37
40.17 30.77 15.38 21.37 9.75 130.19 7.68
41.88 27.35 19.66 23.93 −0.75 134.61 7.43
38.46 29.91 11.97 13.68 −2.75 126.90 7.88
64.96 48.72 38.46 31.62 9.75 162.56 6.15
54.70 41.88 34.19 25.64 1.75 143.68 6.96
40.25 33.00 32.25 28.75 −0.75 144.68 6.91
52.25 39.50 34.75 31.25 −0.75 147.78 6.77
53.50 46.50 24.25 21.25 0.00 148.19 6.75
54.25 44.50 34.25 26.00 −2.75 146.93 6.81
53.00 45.75 37.25 33.00 −1.75 152.37 6.56
56.75 50.75 39.75 41.00 1.75 161.80 6.18
81.25 65.50 49.50 50.00 9.75 193.70 5.16
72.50 63.50 53.00 47.25 9.00 190.81 5.24
147.68 6.77
19 19 Number
147.27 6.89 Average
4.46 0.19 SE
19.45 0.82 SD
f an LC50 value for each horizontal line.
icity and genotoxicity analyses of disinfection by-products: An
s.2017.04.021
http://dx.doi.org/10.1016/j.jes.2017.04.021
U
N
C
O
R
R
E
C
T
E
D
 P
R
O
O
F
Fig. 3 – Flow diagram for the CHO cell acute genotoxicity assay. CHO: Chinese hamster ovary.
Table 4t4:1 – Summary sheet of multiple CHO experiments on the genotoxicity of bromoacetaldehyde.
t4:2t4:3
t4:4 Bromoacetaldehyde: SCGE Mean % Tail DNA values
t4:5 μM Mean % Tail DNA Values Num Average SE SD % Via
Cells
t4:6 Conc Slide
A
Slide
B
Slide
A
Slide
B
Slide
A
Slide
B
Slide
C
Slide
D
Slide
A
Slide
B
Slide
C
Slide
D
t4:7 0 1.60 0.70 2.47 2.77 1.53 2.24 2.66 2.00 8 2.00 0.25 0.70 100.0
t4:8 100 2.30 2.01 1.36 2.92 4 2.15 0.32 0.65 98.1
t4:9 150 8.29 6.73 4.35 5.88 8.77 3.24 0.52 3.03 6 6.21 0.89 2.17 100.0
t4:10 200 12.04 8.67 12.40 8.65 23.40 8.55 18.25 14.99 8 13.37 1.88 5.31 99.3
t4:11 250 36.77 26.84 27.62 40.51 7.88 12.94 21.39 4.53 6 25.42 5.25 12.86 100.0
t4:12 300 39.27 22.42 28.71 29.81 34.58 54.75 41.18 47.71 8 37.30 3.76 10.63 96.7
t4:13 350 43.05 41.10 63.06 61.58 25.06 22.94 18.90 36.88 6 42.80 7.01 17.18 98.4
t4:14 400 53.69 59.14 52.17 48.93 49.27 49.42 53.16 50.95 8 52.09 1.19 3.37 94.7
t4:15 450 62.26 61.99 48.69 57.86 50.77 44.37 53.71 45.45 6 54.32 3.04 7.45 92.9
t4:16 500 66.92 60.89 74.78 72.37 70.12 67.05 70.85 81.29 8 70.53 2.14 6.04 89.5
t4:17 550 69.16 54.50 71.60 3 65.09 5.99 10.37 85.5
t4:18 600 68.16 1 68.16 57.3
t4:19 CHO: Chinese hamster ovary.t4:20
7J O U R N A L O F E N V I R O N M E N T A L S C I E N C E S X X ( 2 0 1 7 ) X X X – X X X
Please cite this article as:Wagner, E.D., Plewa,M.J., CHO cell cytotoxicity and genotoxicity analyses of disinfection by-products: An
updated review, J. Environ. Sci. (2017), http://dx.doi.org/10.1016/j.jes.2017.04.021
http://dx.doi.org/10.1016/j.jes.2017.04.021
T
P
R
O
O
F
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
Fig. 4 – Concentration–response curves for the genotoxicity of iodoacetaldehyde (IAL), bromoacetaldehyde (BAL) or
chloroacetaldehyde (CAL) (left panel). Comparison of the genotoxicity index values for IAL, BAL and CAL (right panel). Using the
mean GTI values and conducting an ANOVA all pair-wise analyses these three samples followed the rank order of
CAL > BAL > IAL and were statistically significantly different from each other (F2, 30 = 247.6; p < 0.001). GTI: genotoxicity index.
8 J O U R N A L O F E N V I R O N M E N T A L S C I E N C E S X X ( 2 0 1 7 ) X X X – X X X
U
N
C
O
R
R
E
C
the migration distance) of the nuclei as a measure of DNA
damage. Both of these metrics generate statistically similar
results (Kumaravel and Jha, 2006). The digitalized data were
automatically transferred to a computer-based spreadsheet for
subsequent statistical analysis. The experimentswere repeated 3
times for each DBP. A flow diagram of the CHO SCGE assay is
presented in Fig. 3.
1.5. Normalization of CHO genotoxicity data and statistical
analyses
Table 4 presents the summary data spreadsheet for
bromoacetaldehyde. Within the DBP concentration range
that allowed for 70% or greater viable cells, a concentration–
response curve was generated. The data were plotted and a
regression analysis was used to fit the curve (Fig. 4, left
panel). The SCGE 50% Tail DNA value or the mid-point of the
tail moment concentration–response curve was used as the
primary metric to compare the genotoxic potency for each
DBP. For the SCGE assay, the %Tail DNA values or the tail
moment values are not normally distributed which limits
the useof parametric statistics (Box et al., 1978). The mean
%Tail DNA value or the median tail moment value for each
microgel was calculated and these values were averaged
among the microgels for each DBP concentration. Applying
the central limit theorem these distributions are normally
distributed (Box et al., 1978). For each DBP a one-way ANOVA
test was conducted on the averaged genotoxicity values. If a
significant F value of p ≤ 0.05 was obtained, a Holm–Sidak
multiple comparison versus the control group analysis was
conducted with the power (1 − β) ≥ 0.8 at α = 0.05.
To determine significant differences among DBPs, a boot-
strap statistical approach was used to generate a series of
multiple 50% Tail DNA values. A genotoxicity index (GTI) value
was calculatedas (50%TailDNA−1) (103). These valueswere then
analyzed using an ANOVA test to determine statistically
significant differences among DBPs (Fig. 4, right panel).
Please cite this article as:Wagner, E.D., Plewa,M.J., CHO cell cytotox
updated review, J. Environ. Sci. (2017), http://dx.doi.org/10.1016/j.je
E
D
 
2. Results and discussion
2.1. Review of CHO cell cytotoxicity and genotoxicity data for
DBPs
The objective of this reviewwas to update the cytotoxicity and
genotoxicity databases with a single mammalian cell plat-
form and quantitatively compare all of the DBPs that our
laboratory has analyzed. Each DBP, the lowest cytotoxic
concentration (M), its LC50 value (M), the lowest concentration
that induced a genotoxic response (M) and themidpoint of the
DNA Tail moment value or the 50% Tail DNA value (M) are
presented in Table 5 with their corresponding references.
These DBPs were individually analyzed using the same
biological system and the identical endpoints and thus allows
a molecule-by-molecule comparison of their cytotoxic and
genotoxic potency.
Research on the analytical chemistry of DBPs was essential
to the current understanding of the formation of DBPs in
disinfected waters (Richardson and Postigo, 2015). Evidence
indicates that emerging DBPs (especially nitrogen-containing
DBPs and iodo-DBPs) are more toxic than their chemical
analogues as well as those DBPs that are currently regulated
by the U.S. EPA and listed by the World Health Organization
(Plewa et al., 2008b; Richardson et al., 2007; U. S. Environmental
Protection Agency, 2006). The high precision of analytical
chemistry research can define the distribution of DBPs present
in disinfected water (Jeong et al., 2012; Krasner et al., 2006; Yang
and Zhang, 2016). Most epidemiological studies associating
disease and DBPs continue to employ the dose of trihalometh-
anes (THMs) tohumanpopulations as themetric ofDBP exposure
(Kogevinas, 2011; Nieuwenhuijsen et al., 2009). However, the data
presented in this paper demonstrate that THMs induce less toxic
insult to cells than many emerging DBPs. This fact calls into
question the use of THMs as the primary measure of DBP
concentration in health-related research. The use of analytical
icity and genotoxicity analyses of disinfection by-products: An
s.2017.04.021
http://dx.doi.org/10.1016/j.jes.2017.04.021
U
N
C
O
R
R
E
C
T
E
D
 P
R
O
O
F
Table 5t5:1 – Summary of DBPs analyzed with the CHO chronic cytotoxicity assay and the CHO SCGE genotoxicity assay.
t5:2t5:3
t5:4 Disinfection by-product Lowest
Cytotox.
Conc. (M)
LC50 (M) Lowest
Genotox.
Conc. (M)
50% TDNA or
midpoint of Tail
moment (M)
Reference
t5:5 Haloacetic acids
t5:6 Bromoacetic acid 2.0 × 10−6 9.60 × 10−6 1.3 × 10−5 1.70 × 10−5 Plewa et al. (2002, 2010, 2004b)
t5:7 Chloroacetic acid 2.5 × 10−4 8.10 × 10−4 3.0 × 10−4 4.11 × 10−4 Plewa et al. (2002, 2010, 2004b)
t5:8 Iodoacetic acid 5.0 × 10−7 2.95 × 10−6 5.0 × 10−6 8.70 × 10−6 (Plewa et al., 2010, 2004b;
Richardson et al., 2008)
t5:9 Dibromoacetic acid 2.0 × 10−4 5.90 × 10−4 7.5 × 10−4 1.76 × 10−3 Plewa et al. (2002, 2010)
t5:10 Dichloroacetic acid 2.0 × 10−3 7.30 × 10−3 NS NA Plewa et al. (2010)
t5:11 Diiodoacetic acid 1.0 × 10−4 3.32 × 10−4 1.0 × 10−3 1.98 × 10−3 (Plewa and Wagner, 2009;
Richardson et al., 2008)
t5:12 Bromochloroacetic acid 3.0 × 10−4 7.78 × 10−4 3.0 × 10−3 3.64 × 10−3 (Plewa et al., 2010; Plewa and
Wagner, 2009)
t5:13 Bromoiodoacetic acid 2.5 × 10−4 8.97 × 10−4 2.5 × 10−3 3.16 × 10−3 (Plewa and Wagner, 2009;
Richardson et al., 2008)
t5:14 Chloroiodoacetic acid 1.7 × 10−4 3.04 × 10−4 NA NA Unpublished report
t5:15 Tribromoacetic acid 5.0 × 10−6 8.50 × 10−5 3.0 × 10−3 2.46 × 10−3 Plewa et al. (2002, 2010)
t5:16 Trichloroacetic acid 4.0 × 10−4 2.40 × 10−3 NS NA Plewa et al. (2010)
t5:17 Chlorodibromoacetic acid 1.0 × 10−4 2.02 × 10−4 1.3 × 10−2 1.36 × 10−2 (Plewa et al., 2010; Plewa and
Wagner, 2009)
t5:18 Bromodichloroacetic acid 5.0 × 10−4 6.85 × 10−4 NS NA (Plewa et al., 2010; Plewa and
Wagner, 2009)
t5:19
t5:20 Halo acids
t5:21 3,3-Dibromo-4-oxopentanoic acid 5.0 × 10−6 1.64 × 10−5 5.0 × 10−5 9.03 × 10−5 Plewa and Wagner (2009)
t5:22 3-Bromo-3-chloro-4-oxopentanoic acid 1.0 × 10−5 2.89 × 10−5 3.25 × 10−4 3.58 × 10−4 Plewa and Wagner (2009)
t5:23 (Z)-3-Bromo-3-iodo-propenoic acid 7.5 × 10−5 1.89 × 10−4 NS NA (Plewa and Wagner, 2009;
Richardson et al., 2008)
t5:24 (E)-3-Bromo-3-iodo-propenoic acid 2.5 × 10−5 1.45 × 10−4 5.0 × 10−3 6.35 × 10−3 Richardson et al. (2008)
t5:25 (E)-3-Bromo-2-iodo-propenoic acid 1.8 × 10−5 4.36 × 10−5 7.5 × 10−3 7.58 × 10−3 Richardson et al. (2008)
t5:26 3,3-Dibromopropenoic acid 2.5 × 10−5 2.95 × 10−4 NS NA Plewa and Wagner (2009)
t5:27 (E)-2-Iodo-3-methylbutenedioic acid 7.0 × 10−4 9.44 × 10−4 6.0 × 10−3 6.0 × 10−3 (Plewa and Wagner, 2009;
Richardson et al., 2008)
t5:28 2,3,3-Tribromopropenoic acid 7.5 × 10−4 1.64 × 10−3 NS NA Plewa and Wagner (2009)
t5:29 2-Bromobutenedioic acid 1.0 × 10−3 2.06 × 10−3 6.0 × 10−3 5.90 × 10−3 Plewa and Wagner (2009)
t5:30 2,3-Dibromopropenoic acid 1.0 × 10−3 2.20 × 10−3 1.0 × 10−3 7.85 × 10−3 Plewa and Wagner (2009)
t5:31 2-Bromo-3-methyl-butenedioic acid 4.8 × 10−3 5.27 × 10−3 NS NA Plewa and Wagner (2009)
t5:32
t5:33 Halophenolics
t5:34 4-Hydroxy-3,5-diiodo-1-phenyl 3.3 × 10−5 3.32 × 10−5 NA NA Unpublished report
t5:35 2,4,6-Triiodo-1-phenol 6.0 × 10−5 7.01 × 10−5 NA NA Unpublished report
t5:36 4-Hydroxy-3-iodo-1-phenolic acid 1.5 × 10−4 3.18 × 10−4 NA NA Unpublished report
t5:37 4-Hydroxy-3,5-diiodo-1-phenolic acid 1.1 × 10−4 2.88 × 10−4 NA NA Unpublished report
t5:38 4-Hydroxy-3-iodophenyl 1.0 × 10−4 4.08 × 10−4 NA NA Unpublished report
t5:39
t5:40 Haloacetonitriles
t5:41 Bromoacetonitrile 1.0 × 10−6 3.21 × 10−6 4.0 × 10−5 3.85 × 10−5 Muellner et al. (2007)
t5:42 Chloroacetonitrile 5.0 × 10−5 6.83 × 10−5 2.5 × 10−5 6.01 × 10−4 Muellner et al. (2007)
t5:43 Iodoacetonitrile 1.0 × 10−7 3.30 × 10−6 3.0 × 10−5 3.71 × 10−5 Muellner et al. (2007)
t5:44 Dibromoacetonitrile 1.0 × 10−6 2.85 × 10−6 3.0 × 10−5 4.71 × 10−5 Muellner et al. (2007)
t5:45 Dichloroacetonitrile 1.0 × 10−5 5.73 × 10−5 2.4 × 10−3 2.75 × 10−3 Muellner et al. (2007)
t5:46 Bromochloroacetonitrile 7.0 × 10−6 8.46 × 10−6 2.5 × 10−4 3.24 × 10−4 Muellner et al. (2007)
t5:47 Trichloroacetonitrile 2.5 × 10−5 1.60 × 10−4 1.0 × 10−3 1.01 × 10−3 Muellner et al. (2007)
t5:48
t5:49 Cyanogen halides
t5:50 Cyanogen bromide 1.0 × 10−6 2.09 × 10−5 5.0 × 10−4 5.0 × 10−4 Pals (2009)
t5:51 Cyanogen chloride 3.0 × 10−3 3.25 × 10−3 NS NA Pals (2009)
t5:52 Cyanogen iodide 1.0 × 10−6 9.01 × 10−5 2.0 × 10−4 2.14 × 10−4 Pals (2009)
t5:53
t5:54 Nitrosamines and nitramines
t5:55 N-nitrosodimethylamine NS NA NA 2.39 × 10−3a Wagner et al. (2014)
t5:56 N-nitrosomorpholine NA 1.11 × 10−2 NA 5.22 × 10−2 Wagner et al. (2014)
t5:57 N-nitrosodiethanolamine NS NA NS NA Wagner et al. (2014)
t5:58 1,4-Dinitrosopiperazine NA 1.28 × 10−2 NA 6.39 × 10−2 Wagner et al. (2014)
t5:59 1-Nitrosopiperazine NA 9.51 × 10−3 NS NA Wagner et al. (2014)
(continued on next page)
9J O U R N A L O F E N V I R O N M E N T A L S C I E N C E S X X ( 2 0 1 7 ) X X X – X X X
Please cite this article as:Wagner, E.D., Plewa,M.J., CHO cell cytotoxicity and genotoxicity analyses of disinfection by-products: An
updated review,J. Environ. Sci. (2017), http://dx.doi.org/10.1016/j.jes.2017.04.021
http://dx.doi.org/10.1016/j.jes.2017.04.021
U
N
C
O
R
R
E
C
T
E
D
 P
R
O
O
F
t5:60 Table 5 (continued)
t5:61 Disinfection by-product Lowest
Cytotox.
Conc. (M)
LC50 (M) Lowest
Genotox.
Conc. (M)
50% TDNA or
midpoint of Tail
moment (M)
Reference
t5:62 N-nitrodimethylamine NS NA NS NA Wagner et al. (2014)
t5:63 N-nitromorpholine NA 8.46 × 10−2 NS NA Wagner et al. (2014)
t5:64 N-nitrodiethanolamine NA 1.26 × 10−2 NS NA Wagner et al. (2014)
t5:65 1-Nitropiperazine NA 8.89 × 10−3 NS NA Wagner et al. (2014)
t5:66 1,4-Dinitropiperazine NA 2.85 × 10−3 NS NA Wagner et al. (2014)
t5:67 N-nitromonoethanolamine NA NA NS NA Wagner et al. (2014)
t5:68
t5:69 Halomethanes
t5:70 Chlorodiiodomethane 1.0 × 10−4 2.41 × 10−3 2.0 × 10−3 2.95 × 10−3 Plewa and Wagner (2009)
t5:71 Triiodomethane 1.0 × 10−5 6.60 × 10−5 NS NA (Plewa and Wagner, 2009;
Richardson et al., 2008)
t5:72 Dibromoiodomethane 1.5 × 10−3 1.91 × 10−3 NS NA (Plewa and Wagner, 2009;
Richardson et al., 2008)
t5:73 Bromochloroiodomethane 2.2 × 10−3 2.42 × 10−3 NS NA (Plewa and Wagner, 2009;
Richardson et al., 2008)
t5:74 Tribromomethane 1.0 × 10−4 3.96 × 10−3 NS NA Plewa and Wagner (2009)
t5:75 Chlorodibromomethane 7.5 × 10−4 5.36 × 10−3 NS NA Plewa and Wagner (2009)
t5:76 Trichloromethane 6.0 × 10−3 9.62 × 10−3 NS NA Plewa and Wagner (2009)
t5:77 Bromodichloromethane 4.0 × 10−3 1.15 × 10−2 NS NA Plewa and Wagner (2009)
t5:78 Dichloroiodomethane 2.0 × 10−3 4.13 × 10−3 NS NA (Plewa and Wagner, 2009;
Richardson et al., 2008)
t5:79 Bromodiiodomethane 1.5 × 10−3 1.40 × 10−3 NS NA Richardson et al. (2008)
t5:80
t5:81 Haloacetaldehydes
t5:82 Bromoacetaldehyde 8.0 × 10−6 1.73 × 10−5 2.0 × 10−4 3.81 × 10−4 Jeong et al. (2015)
t5:83 Chloroacetaldehyde 5.0 × 10−7 3.51 × 10−6 1.0 × 10−4 1.43 × 10−4 Jeong et al. (2015)
t5:84 Iodoacetaldehyde 5.0 × 10−6 6.00 × 10−6 9.0 × 10−4 1.01 × 10−3 Jeong et al. (2015)
t5:85 Dibromoacetaldehyde 2.0 × 10−6 4.70 × 10−6 5.0 × 10−5 1.11 × 10−4 Jeong et al. (2015)
t5:86 Dichloroacetaldehyde 8.0 × 10−6 2.92 × 10−5 8.0 × 10−4 7.95 × 10−4 Jeong et al. (2015)
t5:87 Bromochloroacetaldehyde 2.5 × 10−6 5.34 × 10−6 5.0 × 10−4 6.21 × 10−4 Jeong et al. (2015)
t5:88 Tribromoacetaldehyde 2.0 × 10−6 3.58 × 10−6 1.0 × 10−4 3.40 × 10−4 Jeong et al. (2015)
t5:89 Trichloroacetaldehyde 3.7 × 10−4 1.16 × 10−3 NS NA Jeong et al. (2015)
t5:90 Dibromochloroacet-aldehyde 4.0 × 10−6 5.15 × 10−6 1.0 × 10−4 1.44 × 10−4 Jeong et al. (2015)
t5:91 Bromodichloroace-taldehyde 1.0 × 10−5 2.04 × 10−5 3.0 × 10−4 4.70 × 10−4 Jeong et al. (2015)
t5:92
t5:93 Halonitromethanes
t5:94 Bromonitromethane NA 7.08 × 10−6 NA 1.36 × 10−4 Plewa et al. (2004a)
t5:95 Chloronitromethane NA 5.29 × 10−4 NA 2.15 × 10−3 Plewa et al. (2004a)
t5:96 Dibromonitromethane NA 6.09 × 10−6 NA 2.62 × 10−5 Plewa et al. (2004a)
t5:97 Dichloronitromethane NA 3.73 × 10−4 NA 4.21 × 10−4 Plewa et al. (2004a)
t5:98 Bromochloronitromethane NA 4.05 × 10−5 NA 1.65 × 10−4 Plewa et al. (2004a)
t5:99 Tribromonitromethane NA 8.57 × 10−6 NA 6.99 × 10−5 Plewa et al. (2004a)
t5:100 Trichloronitromethane NA 5.36 × 10−4 NA 9.34 × 10−5 Plewa et al. (2004a)
t5:101 Bromodichloronitro-methane NA 1.32 × 10−5 NA 6.32 × 10−5 Plewa et al. (2004a)
t5:102 Dibromochloronitro-methane NA 6.88 × 10−6 NA 1.43 × 10−4 Plewa et al. (2004a)
t5:103
t5:104 Haloacetamides
t5:105 Bromoacetamide 5.0 × 10−7 1.89 × 10−6 2.5 × 10−5 3.68 × 10−5 Plewa et al. (2008a)
t5:106 Chloroacetamide 7.5 × 10−5 1.48 × 10−4 7.5 × 10−4 1.38 × 10−3 Plewa et al. (2008a)
t5:107 Iodoacetamide 5.0 × 10−7 1.42 × 10−6 3.0 × 10−5 3.41 × 10−5 Plewa et al. (2008a)
t5:108 Dibromoacetamide 2.5 × 10−6 1.22 × 10−5 5.0 × 10−4 7.44 × 10−4 Plewa et al. (2008a)
t5:109 Dichloroacetamide 8.0 × 10−4 1.92 × 10−3 NS NA Plewa et al. (2008a)
t5:110 Diiodoacetamide 2.5 × 10−8 6.78 × 10−7 2.5 × 10−5 3.39 × 10−5 Plewa et al. (2008a)
t5:111 Bromoiodoacetamide 2.0 × 10−6 3.81 × 10−6 2.5 × 10−5 7.21 × 10−5 Plewa et al. (2008a)
t5:112 Chloroiodoacetamide 2.0 × 10−6 5.97 × 10−6 2.0 × 10−4 3.02 × 10−4 Plewa et al. (2008a)
t5:113 Tribromoacetamide 2.0 × 10−6 3.14 × 10−6 3.0 × 10−5 3.25 × 10−5 Plewa et al. (2008a)
t5:114 Bromochloroacetamide 1.0 × 10−6 1.71 × 10−5 4.0 × 10−4 5.83 × 10−4 Plewa et al. (2008a)
t5:115 Dibromochloroacetamide 1.0 × 10−6 4.75 × 10−6 2.5 × 10−5 6.94 × 10−5 Plewa et al. (2008a)
t5:116 Bromodichloroacetamide 2.0 × 10−6 8.68 × 10−6 7.5 × 10−5 1.46 × 10−4 Plewa et al. (2008a)
t5:117 Trichloroacetamide 5.0 × 10−4 2.05 × 10−3 5.0 × 10−3 6.54 × 10−3 Plewa et al. (2008a)
t5:118
t5:119 Other DBPs
t5:120 Bromate NA 9.63 × 10−4 NA 7.19 × 10−3 Plewa et al. (2002)
10 J O U R N A L O F E N V I R O N M E N T A L S C I E N C E S X X ( 2 0 1 7 ) X X X – X X X
Please cite this article as:Wagner, E.D., Plewa,M.J., CHO cell cytotoxicity and genotoxicity analyses of disinfection by-products: An
updated review, J. Environ. Sci. (2017), http://dx.doi.org/10.1016/j.jes.2017.04.021
http://dx.doi.org/10.1016/j.jes.2017.04.021
T
 P
R
O
O
F
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
37 6
377
378
379
380
381
382
383
384
385
386
387
388
t5:121 Table 5 (continued)
t5:122 Disinfection by-product Lowest
Cytotox.
Conc. (M)
LC50 (M) Lowest
Genotox.
Conc. (M)
50% TDNA or
midpoint of Tail
moment (M)
Reference
t5:123 MX (3-chloro-4(dichloromethyl)-
5-hydroxy-2[5H]-furanone
NA 2.75 × 10−4 NA 2.44 × 10−4 Plewa et al. (2002)
t5:124 4-Hydroxy-3,5-diiodo-1-nitrobenzine 2.0 × 10−5 3.35 × 10−5 NA NA Unpublished report
t5:125 Tribromopyrrole 1.0 × 10−5 6.10 × 10−5 2.50 × 10−4 2.99 × 10−4 Richardson et al. (2003)
t5:126 2,6-Dichloro-p-benzoquinone 5.0 × 10−6 1.12 × 10−5 NA NA Prochazka et al. (2015)
t5:127 2,6-Dibromo-p-benzoquinone 1.0 × 10−5 1.44 × 10−5 NA NA Prochazka et al. (2015)
t5:128 5-Amino-N1,N3-bis(1,3-dihydroxypropan-2-yl)-2,4,
6-triiodoisophthalamide
9.0 × 10−4 1.44 × 10−3 NS NA Wendel et al. (2016)
t5:129 2-(3,5-Bis((1,3-dihydroxypropan-2-yl)carbamoyl)-2,4,
6- triiodophenoxy) propanoic acid
NS NA NS NA Wendel et al. (2016)
t5:130 N1,N3-Bis(1,3-dihydroxy-propan-2-yl)-2,4,
6-triiodo-5-nitroisophthalamide
9.0 × 10−4 9.34 × 10−4 NS NA Wendel et al. (2016)
t5:131 4-Chloro-N1,N3-bis(1,3-dihydroxypropan-2-yl)-2,
6-diiodo-5-nitroiso-phthalamide
1.0 × 10−3 1.30 × 10−3 NS NA Wendel et al. (2016)
t5:132 4,6-Dichloro-N1,N3-bis(1,3-dihydroxypropan-2-yl)-
2-iodo-5-nitroisophthalamide
2.5 × 10−4 8.23 × 10−4 NS NA Wendel et al. (2016)
t5:133 NS = not statistically significant against the negative control.
t5:134t5:135 NA = not applicable or data not available.
t5:136t5:137 CHO: Chinese hamster ovary; DBPs: disinfection by-products; SCGE: single cell gel electrophoresis.
t5:138
a With S9B150 metabolic activation.t5:139
11J O U R N A L O F E N V I R O N M E N T A L S C I E N C E S X X ( 2 0 1 7 ) X X X – X X X
U
N
C
O
R
R
E
C
endpoints within a single cell type allows for the direct
comparison of the relative toxic potency of DBP classes and
individual DBPs. Recently these data have been used to evaluate
the forcing agents that may be driving the toxicity of disinfected
waters (Krasner et al., 2016; Zeng et al., 2016).
The data presented in this paper focus on the cytotoxicity
and genotoxicity of individual DBPs. However, these assays
have been used to evaluate complex mixtures such as the
organics derived from specific drinking waters (Jeong et al., in
press, 2012; Plewa et al., 2012), recreational pool waters (Liviac
et al., 2010; Plewa et al., 2011), and wastewaters (Dong et al.,
2016, in press; Le Roux et al., in press).
Scientists and engineers must work together to resolve
problems posed by hazardous DBPs and other micropollutants
in water. The approach outlined in this review provides one
route of a systematic, comparative in vitro toxicology approach
thatmay be used as a feed-back information loop for innovative
engineering processesto remove and degrade micropollutants
and disinfect water. The biological mechanisms of DBP toxicity
must be included in epidemiological studies. By integrating the
efforts of biologists, chemists and engineers to address the
problem of unintended toxic consequences, we will progress in
the implementation of new methods to desalinate, decontam-
inate, reuse and disinfect water (Plewa and Wagner, 2015).
389
390
391
392
393
394
395
396
397
398
399
400
3. Conclusion
The objective of this review was to provide the quantitative,
comparative analyses on the induction of cytotoxicity and
genotoxicity of 103 DBPs using an identical analytical biological
platformandendpoints. EmergingDBPsmay bemore toxic than
DBPs regulated by the U.S. EPA or WHO and research is needed
to identify those DBPs that are the forcing agents that generate
Please cite this article as:Wagner, E.D., Plewa,M.J., CHO cell cytotox
updated review, J. Environ. Sci. (2017), http://dx.doi.org/10.1016/j.je
E
D
DBP-mediated toxicity in drinking water. Attention should be
placed on nitrogen-containing DBPs and on iodinated DBPs
because they are generally more toxic than their brominated
and chlorinated analogs. New classes of DBPs such as the
haloketones and halophenolics need to be evaluated for their
toxicity. These data may form the foundation of novel research
to define the major forcing agents of DBP-mediated toxicity in
disinfected water and may play an important role in achieving
the goal of making safe drinking water better.
R E F E R E N C E S
Bellar, T.A., Lichtenberg, J.J., Kroner, R.C., 1974. The occurrence of
organohalides in chlorinated drinking waters. J. Am. Water
Works Assoc. 66, 703–706.
Bove, F., Shim, Y., Zeitz, P., 2002. Drinking water contaminants
and adverse pregnancy outcomes: a review. Environ. Health
Perspect. 110 (Suppl. 1), 61–74.
Bove Jr., G.E., Rogerson, P.A., Vena, J.E., 2007a. Case control study
of the geographic variability of exposure to disinfectant
byproducts and risk for rectal cancer. Int. J. Health Geogr. 6, 18.
Bove, G.E., Rogerson, P.A., Vena, J.E., 2007b. Case-control study of
the effects of trihalomethanes on urinary bladder cancer risk.
Arch. Environ. Occup. Health 62, 39–47.
Box, G.E.P., Hunter, W.G., Hunter, J.S., 1978. Statistics for
Experimenters: An Introduction to Design, Data Analysis, and
Model Building. Wiley & Sons Inc., New York, NY.
Calderon, R.L., 2000. The epidemiology of chemical contaminants
of drinking water. Food Chem. Toxicol. 38, S13–S20.
Colman, J., Rice, G.E., Wright, J.M., Hunter III, E.S., Teuschler, L.K.,
Lipscomb, J.C., Hertzberg, R.C., Simmons, J.E., Fransen, M., Osier,
M., Narotsky, M.G., 2011. Identification of developmentally toxic
drinking water disinfection byproducts and evaluation of data
relevant to mode of action. Toxicol. Appl. Pharmacol. 254,
100–126.
icity and genotoxicity analyses of disinfection by-products: An
s.2017.04.021
http://dx.doi.org/10.1016/j.jes.2017.04.021
T
401
402
403
404
405
406
407
408
409
410
411
412
413
414Q10
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458Q11
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
484Q12
485
486
487
488
489
490
491
492
493
494
495
496
497
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
12 J O U R N A L O F E N V I R O N M E N T A L S C I E N C E S X X ( 2 0 1 7 ) X X X – X X X
U
N
C
O
R
R
E
C
Costet, N., Villanueva, C.M., Jaakkola, J.J., Kogevinas, M., Cantor,
K.P., King, W.D., Lynch, C.F., Nieuwenhuijsen, M.J., Cordier, S.,
2011. Water disinfection by-products and bladder cancer: is
there a European specificity? A pooled and meta-analysis of
European case-control studies. Occup. Environ. Med. 68,
379–385.
Dong, S., Lu, J., Plewa, M.J., Nguyen, T.H., 2016. Comparative
mammalian cell cytotoxicity of wastewaters for agricultural
reuse after ozonation or chlorination. Environ. Sci. Technol. 50,
11752–11759.
Dong, S., Nguyen, T.H., Plewa, M.J., 2017. Comparative mammalian
cell cytotoxicity of wastewater for reuse after chlorination,
chloramination, or ozonation disinfection with elevated
bromide and iodide. J. Environ. Sci. (in press).
Fairbairn, D.W., Olive, P.L., O'Neill, K.L., 1995. The comet assay: a
comprehensive review. Mutat. Res. 339, 37–59.
Grellier, J., Bennett, J., Patelarou, E., Smith, R.B., Toledano, M.B.,
Rushton, L., Briggs, D.J., Nieuwenhuijsen, M.J., 2010. Exposure to
disinfection by-products, fetal growth, and prematurity: a
systematic review andmeta-analysis. Epidemiology 21, 300–313.
Hong, H., Xiong, Y., Ruan, M., Liao, F., Lin, H., Liang, Y., 2013.
Factors affecting THMs, HAAs and HNMs formation of Jin Lan
reservoir water exposed to chlorine and monochloramine. Sci.
Total Environ. 444, 196–204.
Hsie, A.W., Brimer, P.A., Mitchell, T.J., Gosslee, D.G., 1975a. The
dose-response relationship for ethyl methanesulfonate-
induced mutations at the hypoxanthine-guanine
phosphoribosyl transferase locus in Chinese hamster ovary
cells. Somatic Cell Genet. 1, 247–261.
Hsie, A.W., Brimer, P.A., Mitchell, T.J., Gosslee, D.G., 1975b. The
dose-response relationship for ultraviolet-light-induced
mutations at the hypoxanthine-guanine
phosphoribosyltransferase locus in Chinese hamster ovary
cells. Somatic Cell Genet. 1, 383–389.
Hu, T., Miller, C.M., Ridder, G.M., Aardema, M.J., 1999.
Characterization of p53 in Chinese hamster cell lines CHO-K1,
CHO-WBL, and CHL: implications for genotoxicity testing.
Mutat. Res. 426, 51–62.
Hua, G.H., Reckhow, D.A., 2007. Comparison of disinfection byproduct
formation from chlorine and alternative disinfectants. Water Res.
41, 1667–1678.
Jeong, C.H., Wagner, E.D., Siebert, V.R., Anduri, S., Richardson,
S.D., Daiber, E.J., McKague, A.B., Kogevinas, M., Villanueva,
C.M., Goslan, E.H., Luo, W., Isabelle, L.M., Pankow, J.F.,
Grazuleviciene, R., Cordier, S., Edwards, S.C., Righi, E.,
Nieuwenhuijsen, M.J., Plewa, M.J., 2012. The occurrence and
toxicity of disinfection byproducts in European drinking
waters in relation with the HIWATE epidemiology study.
Environ. Sci. Technol. 46, 12120–12128.
Jeong, C.H., Postigo, C., Richardson, S.D., Simmons, J.E., Kimura,
S.Y., Marinas, B.J., Barcelo, D., Liang, P., Wagner, E.D., Plewa,
M.J., 2015. Occurrence and comparative toxicity of
haloacetaldehyde disinfection byproducts in drinking water.
Environ. Sci. Technol. 49, 13749–13759.
Jeong, C.H.,Machek, E., Shakeri,M., Duirk, S., Ternes, T.A., Richardson,
S.D.,Wagner, E.D., Plewa,M.J., 2017. The impact of iodinated X-ray
contrast agents on formation and toxicity of disinfection
by-products in drinking water. J. Environ. Sci. (in press).
King, W.D., Marrett, L.D., Woolcott, C.G., 2000. Case-control study
of colon and rectal cancers and chlorination by-products in
treated water. Cancer Epidemiol. Biomark. Prev. 9, 813–818.
Kogevinas, M., 2011. Epidemiological approaches in the
investigation of environmental causes of cancer: the case of
dioxins and water disinfection by-products. Environ. Health 10
(Suppl. 1), S3.
Komaki, Y., 2013. Toxicity Effects on Model Mammalian Cells by
Monohalogenated Disinfection Byproducts: Haloacetic Acids
and Haloacetonitriles, Civil and Environmental Engineering.
University of Illinois, Urbana, IL.
Please cite this article as:Wagner, E.D., Plewa,M.J., CHO cell cytotox
updated review, J. Environ. Sci. (2017), http://dx.doi.org/10.1016/j.je
E
D
 P
R
O
O
F
Krasner, S.W., Weinberg, H.S., Richardson, S.D., Pastor, S.J., Chinn,
R., Sclimenti, M.J., Onstad, G.D., Thruston Jr., A.D., 2006. The
occurrence of a new generation of disinfection by-products.
Environ. Sci. Technol. 40, 7175–7185.
Krasner, S.W., Lee,T.C., Westerhoff, P., Fischer, N., Hanigan, D.,
Karanfil, T., Beita-Sandi, W., Taylor-Edmonds, L., Andrews,
R.C., 2016. Granular activated carbon treatment may result in
higher predicted genotoxicity in the presence of bromide.
Environ. Sci. Technol. 50, 9583–9591.
Kumaravel, T.S., Jha, A.N., 2006. Reliable Comet assaymeasurements
for detecting DNA damage induced by ionising radiation and
chemicals. Mutat. Res. 605, 7–16.
Le Roux, J., Plewa, M.J., Wagner, E.D., Nihemaiti, M., Dad, A., Croué,
J.P., 2017. Chloramination of wastewater effluent: toxicity and
formation of disinfection byproducts. J. Environ. Sci. (in press).
Liviac, D., Wagner, E.D., Mitch, W.A., Altonji, M.J., Plewa, M.J., 2010.
Genotoxicity of water concentrates from recreational pools
after various disinfection methods. Environ. Sci. Technol. 44,
3527–3532.
Muellner, M.G., Wagner, E.D., McCalla, K., Richardson, S.D., Woo,
Y.T., Plewa, M.J., 2007. Haloacetonitriles vs. regulated
haloacetic acids: are nitrogen containing DBPs more toxic?
Environ. Sci. Technol. 41, 645–651.
Nieuwenhuijsen, M.J., Grellier, J., Smith, R., Iszatt, N., Bennett, J.,
Best, N., Toledano, M., 2009. The epidemiology and possible
mechanisms of disinfection by-products in drinking water.
Philos. Trans. R. Soc. A 367, 4043–4076.
Pals, J.A., 2009. Comparative Cytotoxicity, Genotoxicity and DNA
Repair Kinetics of Drinking Water Disinfection by-Products,
Crop Sciences. University of Illinois, Urbana, IL.
Phillips, H.J., 1973. Dye exclusion tests for cell viability. In: Kruse,
P.F., Patterson, M.J. (Eds.), Tissue Culture: Methods and
Applications. Academic Press, New York, p. 406.
Plewa, M.J., Wagner, E.D., 2009. Mammalian Cell Cytotoxicity and
Genotoxicity of Disinfection by-Products. Water Research
Foundation, Denver, CO.
Plewa, M.J., Wagner, E.D., 2015. Charting a new path to resolve the
adverse health effects of DBPs. In: Karanfil, T., Mitch, W.,
Westerhoff, P., Xie, Y. (Eds.), Occurrence, Formation, Health
Effects, and Control of Disinfection by-Products. Am. Chem.
Soc., Washington, D.C., pp. 3–23.
Plewa, M.J., Kargalioglu, Y., Vankerk, D., Minear, R.A., Wagner,
E.D., 2002. Mammalian cell cytotoxicity and genotoxicity
analysis of drinking water disinfection by-products. Environ.
Mol. Mutagen. 40, 134–142.
Plewa, M.J., Wagner, E.D., Jazwierska, P., Richardson, S.D., Chen,
P.H., McKague, A.B., 2004a. Halonitromethane drinking water
disinfection byproducts: chemical characterization and
mammalian cell cytotoxicity and genotoxicity. Environ. Sci.
Technol. 38, 62–68.
Plewa, M.J., Wagner, E.D., Richardson, S.D., Thruston Jr., A.D.,
Woo, Y.T., McKague, A.B., 2004b. Chemical and biological
characterization of newly discovered iodoacid drinking water
disinfection byproducts. Environ. Sci. Technol. 38, 4713–4722.
Plewa,M.J.,Muellner,M.G., Richardson, S.D., Fasano, F., Buettner, K.M.,
Woo, Y.T., McKague, A.B., Wagner, E.D., 2008a. Occurrence,
synthesis and mammalian cell cytotoxicity and genotoxicity of
haloacetamides: an emerging class of nitrogenous drinking water
disinfection by-products. Environ. Sci. Technol. 42, 955–961.
Plewa, M.J., Wagner, E.D., Muellner, M.G., Hsu, K.M., Richardson,
S.D., 2008b. Comparative mammalian cell toxicity of N-DBPs
and C-DBPs. In: Karanfil, T., Krasner, S.W., Westerhoff, P., Xie,
Y. (Eds.), Occurrence, Formation, Health Effects and Control of
Disinfection By-products in Drinking Water. American
Chemical Society, Washington, D.C., pp. 36–50.
Plewa, M.J., Simmons, J.E., Richardson, S.D., Wagner, E.D., 2010.
Mammalian cell cytotoxicity and genotoxicity of the haloacetic
acids, a major class of drinking water disinfection by-products.
Environ. Mol. Mutagen. 51, 871–878.
icity and genotoxicity analyses of disinfection by-products: An
s.2017.04.021
http://dx.doi.org/10.1016/j.jes.2017.04.021
T
539
540
541
542
543
544
545
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
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
643
644
645
646
647
13J O U R N A L O F E N V I R O N M E N T A L S C I E N C E S X X ( 2 0 1 7 ) X X X – X X X
U
N
C
O
R
R
E
C
Plewa,M.J.,Wagner, E.D.,Mitch,W.A., 2011. Comparativemammalian
cell cytotoxicity of water concentrates from disinfected
recreational pools. Environ. Sci. Technol. 45, 4159–4165.
Plewa, M.J., Wagner, E.D., Metz, D.H., Kashinkunti, R., Jamriska,
K.J., Meyer, M., 2012. Differential toxicity of drinking water
disinfected with combinations of ultraviolet radiation and
chlorine. Environ. Sci. Technol. 46, 7811–7817.
Prochazka, E., Escher, B.I., Plewa, M.J., Leusch, F.D., 2015. In vitro
cytotoxicity and adaptive stress responses to selected
haloacetic acid and halobenzoquinone water disinfection
byproducts. Chem. Res. Toxicol. 28, 2059–2068.
Rahman, M.B., Driscoll, T., Cowie, C., Armstrong, B.K., 2010.
Disinfection by-products in drinking water and colorectal
cancer: a meta-analysis. Int. J. Epidemiol. 39, 733–745.
Richardson, S.D., Postigo, C., 2015. Formation of DBPs: state of the
science. In: Karanfil, T., Mitch, W.A., Westerhoff, P., Xie, Y.
(Eds.), Recent Advances in Disinfection By-products. Am.
Chem. Society, Washington, DC, pp. 189–214.
Richardson, S.D., Thruston Jr., A.D., Rav-Acha, C., Groisman, L.,
Popilevsky, I., Juraev, O., Glezer, V., McKague, A.B., Plewa, M.J.,
Wagner, E.D., 2003. Tribromopyrrole, brominated acids, and
other disinfection byproducts produced by disinfection of
drinking water rich in bromide. Environ. Sci. Technol. 37,
3782–3793.
Richardson, S.D., Plewa, M.J., Wagner, E.D., Schoeny, R., DeMarini,
D.M., 2007. Occurrence, genotoxicity, and carcinogenicity of
regulated and emerging disinfection by-products in drinking
water: a review and roadmap for research. Mutat. Res. 636,
178–242.
Richardson, S.D., Fasano, F., Ellington, J.J., Crumley, F.G., Buettner,
K.M., Evans, J.J., Blount, B.C., Silva, L.K., Waite, T.J., Luther,
G.W., McKague, A.B., Miltner, R.J., Wagner, E.D., Plewa, M.J.,
2008. Occurrence and mammalian cell toxicity of iodinated
disinfection byproducts in drinking water. Environ. Sci.
Technol. 42, 8330–8338.
Rivera-Nunez, Z., Wright, J.M., 2013. Association of brominated
trihalomethane and haloacetic acid exposure with fetal
growth and preterm delivery in Massachusetts. J. Occup.
Environ. Med. 55, 1125–1134.
Rook, J.J., 1974. Formation of haloforms during chlorination of
natural waters. Water Treat. Examination 23, 234–243.
Rundell, M.S., Wagner, E.D., Plewa, M.J., 2003. The comet assay:
genotoxic damage or nuclear fragmentation? Environ. Mol.
Mutagen. 42, 61–67.
Singer, P.C., 1994. Control of disinfection by-products in drinking
water. J. Environ. Eng. 120, 727–744.
Singh, K., Xie, M., 2008. Bootstrap: A Statistical Method. Rutgers
University, New Brunswick, NJ, p. 14.
Tice, R.R., Agurell, E., Anderson, D., Burlinson, B., Hartmann, A.,
Kobayashi, H., Miyamae, Y., Rojas, E., Ryu, J.C., Sasaki, Y.F.,
2000. Single cell gel/comet assay: guidelines for in vitro and in
vivo genetic toxicology testing. Environ. Mol. Mutagen. 35,
206–221.
Tindall, K.R., Stankowski Jr., L.F., 1989. Molecular analysis of
spontaneous mutations at the gpt locus in Chinese hamster
ovary (AS52) cells. Mutat. Res. 220, 241–253.
Please cite this article as:Wagner, E.D., Plewa,M.J., CHO cell cytotox
updated review, J. Environ. Sci. (2017), http://dx.doi.org/10.1016/j.je
E
D
 P
R
O
O
F
Tindall, K.R., Stankowski Jr., L.F., Machanoff, R., Hsie, A.W., 1984.
Detection of deletion mutations in pSV2gpt-transformed cells.
Mol. Cell. Biol. 4, 1411–1415.
Tzang, B.S., Lai, Y.C., Hsu, M., Chang, H.W., Chang, C.C., Huang, P.C.,
Liu, Y.C., 1999. Function and sequence analyses of tumor
suppressorgene p53 of CHO.K1 cells. DNA Cell Biol. 18, 315–321.
U. S. Environmental Protection Agency, 2006. National primary
drinking water regulations: stage 2 disinfectants and
disinfection byproducts rule. Fed. Regist. 71, 387–493.
Varian, H., 2005. Bootstrap tutorial. Mathematica J. 9, 768–775.
Villanueva, C.M., Cantor, K.P., Cordier, S., Jaakkola, J.J., King, W.D.,
Lynch, C.F., Porru, S., Kogevinas, M., 2004. Disinfection
byproducts and bladder cancer: a pooled analysis. Epidemiology
15, 357–367.
Wagner, E.D., Plewa, M.J., 2009. Microplate-based comet assay. In:
Dhawan, A., Anderson, D. (Eds.), The Comet Assay in Toxicology.
Royal Society of Chemistry, London, pp. 79–97.
Wagner, E.D., Rayburn, A.L., Anderson, D., Plewa, M.J., 1998a.
Analysis of mutagens with single cell gel electrophoresis, flow
cytometry, and forward mutation assays in an isolated clone
of Chinese hamster ovary cells. Environ. Mol. Mutagen. 32,
360–368.
Wagner, E.D., Rayburn, A.L., Anderson, D., Plewa, M.J., 1998b.
Calibration of the single cell gel electrophoresis assay, flow
cytometry analysis and forward mutation in Chinese hamster
ovary cells. Mutagenesis 13, 81–84.
Wagner, E.D., Osiol, J., Mitch, W.A., Plewa, M.J., 2014. Comparative
in vitro toxicity of nitrosamines and nitramines associated
with amine-based carbon capture and storage. Environ. Sci.
Technol. 48, 8203–8211.
Wendel, F.M., Ternes, T., Richardson, S.D., Duirk, S.E., Pals, J.,
Wagner, E.D., Plewa, M.J., 2016. Comparative toxicity of high
molecular weight iopamidol transformation products.
Environ. Sci. Technol. Lett. 3, 81–84.
Wright, J.M., Evans, A., Kaufman, J.A., Rivera-Núñez, Z., Narotsky,
M.G., 2016. Disinfection by-product exposures and the risk of
specific cardiac birth defects. Environ. Health Perspect. http://
dx.doi.org/10.1289/EHP103.
Yang, M., Zhang, X., 2016. Current trends in the analysis and
identification of emerging disinfection byproducts. Trends
Environ. Anal. Chem. 10, 24–34.
Zeng, T., Plewa, M.J., Mitch, W.A., 2016. Chemical and toxicological
assessment of N-nitrosamines and halogenated disinfection
byproducts in potable reuse treatment trains. Water Res. 101,
176–186.
Zhang, X., Echigo, S.,Minear, R.A., Plewa,M.J., 2000. Characterization
and comparison of disinfection by-products of four major
disinfectants. In: Barrett, S.E., Krasner, S.W., Amy, G.L. (Eds.),
Natural Organic Matter and Disinfection By-products:
Characterization and Control in Drinking Water. American
Chemical Society, Washington, D.C., pp. 299–314.
icity and genotoxicity analyses of disinfection by-products: An
s.2017.04.021
http://dx.doi.org/10.1289/EHP103
http://dx.doi.org/10.1016/j.jes.2017.04.021
	CHO cell cytotoxicity and genotoxicity analyses of disinfection by-products: An updated review...
	Introduction
	1. Materials and methods
	1.1. Chinese hamster ovary cells
	1.2. CHO cell chronic cytotoxicity assay...
	1.3. Normalization of CHO cytotoxicity data and statistical analyses...
	1.4. CHO cell acute genotoxicity assay
	1.5. Normalization of CHO genotoxicity data and statistical analyses...
	2. Results and discussion
	2.1. Review of CHO cell cytotoxicity and genotoxicity data for DBPs...
	3. Conclusion
	References