Download Mixtures of Nickel and Cobalt Chlorides Induce

Ann. occup. Hyg., Vol. 45, No. 5, pp. 409-418, 2001
© 2001 British Occupational Hygiene Society
Published by Elsevicr Science Ltd. All rights reserved
Pergamon
PII: S0003-4878(00)00069-7
Mixtures of Nickel and Cobalt Chlorides Induce
Synergistic Cytotoxic Effects: Implications for
Inhalation Exposure Modeling
DAISY P. CROSSf, GURUMURTHY RAMACHANDRAN* and
ELIZABETH V. WATTENBERG
Division of Environmental and Occupational Health, School of Public Health, University of
Minnesota, Mayo Mail Code 807, 420 Delaware Street SE, Minneapolis, MN 55455, USA
Workers are often simultaneously exposed to two or more chemicals, yet little is known about
the toxicity of most chemical mixtures. The traditional assumption, in the absence of further
information, has been that the chemical components of a mixture have mutually independent
effects, and the toxic response to multiple chemicals is additive. The data presented here
show that mixtures of NiCl2 and CoCl2 induce a synergistic (that is, greater than additive)
toxic response in cell culture. Immortalized alveolar epithelial type II cells were incubated
for 4 h with various concentrations of either NiCI2, CoCl2, or NiCl2 and CoCl2 together, and
cell viability assessed 24 h later. The LD50 for NiCl2 was 5.7 mM. CoCl2, with an LD50 of
1.1 mM, was about five times more potent than NiCl2. Mixtures of NiCl2 and CoCl2 decreased
cell viability synergistically. For example, a mixture of 750 (JLM NiCl2 and 750 |xM CoCl2
reduced cell viability by more than three times the value predicted by the additive approach.
We used concentration-response data from these studies in a mathematical model; this model
describes the equivalent inhalation exposure to an aerosol composed of a mixture of chemicals
with different toxicities and also accounts for synergistic responses to these chemicals. Our
results along with previous studies using an animal model suggest that these synergisms
should be taken into account when conducting future exposure assessments. © 2001 British
Occupational Hygiene Society. Published by Elsevier Science Ltd. All rights reserved
Keywords: mixtures; exposure; synergism; nickel; cobalt; inhalation; dosimetry
INTRODUCTION
Many occupations involve exposure to mixtures or
chemicals, yet most toxicology studies investigate
adverse responses to individual chemicals, not mixtures of chemicals. The traditional assumption, in the
absence of further information, has been that, if the
.
.
.
.
.
.
.
•
,
,
,
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i i
J
•
individual chemicals have the same health end-point,
then the chemical components of a mixture have
.. . ,
,
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,.
.
mutually independent effects and the toxic response
to multiple chemicals is additive.
Nickel and cobalt are two metals that are frequently
found together in workplaces such as mines, smelters,
refineries, and in factories that manufacture nickel
and cobalt alloys (Mastromatteo, 1967). For example,
cobalt is a byproduct or nickel ore processing, cobalt
alloys often include nickel (Lauwerys and Lison,
1994), and cobalt shortages have torced hard metal
manufacturers to substitute pure cobalt with mixtures
of nickel and cobalt in the process of sintering
.„
.
, r i r i o x „,
.
~
°
(Scansetti et al., i1998).
The major route of exposure
to these metals in the workplace is inhalation.
Several studies have addressed the adverse effects
of nickel or cobalt individually. The lung is a target
_ ., ,
Received 20 March 2000; in final form 18 September 2000.
* Author to whom correspondence should be addressed. Tel.:
+ 1-612-626-5428;
fax:
+1-612-626-0650;
E-mail:
[email protected]
Current address: Materials and Biosciences Center, Medtronic. Inc., Minneapolis, MN 55430, USA.
409
,
, ,
. . . .
°, .
.
.
of nickel and cobalt toxicity in humans and in animal
models. Epidemiological studies indicate a link
between inhalation of nickel and lung cancer (Costa,
1991; Kaldor et al., 1986). In animal models, inhalation of nickel causes inflammation and respiratory
degeneration (Benson et al, 1987), renal damage
(Norseth, 1983), immune system suppression
(Smialowicz et al, 1984), and possibly teratogenesis
(Norseth, 1983). Cell culture studies have shown that
410
D. P. Cross et al.
nickel can bind to protein, RNA, and DNA (Harnett
etal., 1982); nickel subsulfide (Ni3S2) and nickel sulfate (NiSO4) can induce DNA-protein crosslinks
(Chakrabarti et al., 1999); and nickel hydroxy carbonate (NiHC) can induce the release of the inflammatory
mediators, tumor necrosis factor-a and interleukin-6
(Arsalane et al., 1994). No epidemiology studies have
established a link between inhalation of cobalt and
lung cancer in humans, although cobalt can cause
allergic asthma or 'work-related wheeze', which may
lead to interstitial fibrosis (Lauwerys and Lison,
1994). In animal models, cobalt sulfate (CoSO4) aerosol can induce alveolar and bronchiolar tumor formation and can cause reductions in lung compliance
(Bucher et al., 1999). Other adverse effects of cobalt
exposure in animal models include polycythemia and
decreased cytochrome P450 levels (Bucher et al.,
1999).
Although studies such as those mentioned above
have investigated the toxicity of nickel and cobalt
alone, little is known about the toxic effects of mixtures of nickel and cobalt on most tissues and organs.
A study by Johansson et al. (1991) suggests that inhalation exposure to mixtures of nickel and cobalt chlorides affect certain aspects of pulmonary morphology
in a synergistic manner. They conducted an inhalation
study in which rabbits were exposed to either 0.5
mg/m3 CoCl2 alone or to 0.5 mg/m3 CoCl2 and 0.5
mg/m3 NiCl2 together for 6 h per day, 5 days a week
for 4 months. A previous inhalation study by the same
authors investigated the toxic effects of 0.6 mg/m3
NiCl2 alone under the same exposure regimen
(Johansson et al., 1989). Data from these studies
showed that mixtures of NiCl2 and CoCl2 induced a
synergistic response in the respiratory tract, as indicated by type II cell aggregates and concentrations
of phospholipids.
Since the Johansson et al. (1991) study suggested
that using the additive model may not always be
valid, we hypothesized that concentration-response
data describing the toxic responses induced by mixtures of compounds might be used to develop a mathematical model for estimating equivalent occupational exposures that accounts for synergistic
responses to mixtures. We used a cell culture model
with a binary-chemical exposure to generate the concentration-response data. We exposed immortalized
alveolar epithelial type II cells to various concentrations of NiCl2, CoCl2, or mixtures of NiCl2 and
CoCl2, and then measured cell viability. We chose an
alveolar epithelial type II cell line because type II
cells are likely to be damaged when humans inhale
NiCl2 and CoCl2. The ratio of the LD5Os (the concentrations at which there is a 50% decrease in cell
viability) for NiCl2 and CoCl2 in this system was
similar to the ratio of the TLVs for these metals. In
this system, as in the rabbit model, the toxic response
to mixtures of NiCl2 and CoCl2 was synergistic. We
used concentration-response data from these studies
in a mathematical model that describes the relationship between exposures to chemical mixtures and toxicity so that the model now accounts for synergistic
responses to mixtures.
THEORETICAL FRAMEWORK
We modified a model developed by Ramachandran
et al. (1996) which describes exposures to mixtures
of chemicals with different toxicities, to incorporate
the effects of synergistic interactions. A brief description of the model is given below.
If the mass of a single aerosol species / deposited in
region j of the respiratory tract is Ajh then the internal
exposure to this species, in relation to a specific
health effect or toxic response, is a non-uniformly
weighted sum of the masses deposited in the n different regions,
(1)
where a}i represents weighting factors that account
for differences in the degree to which a chemical
species contributes to a biological response /?; a can
range from 0 to 1. This model is based on the assumption that deposited particles, which are not removed
by clearance mechanisms, contribute to the observed
health effect; thus a is a measure of biological uptake
of the deposited particles. A later section describes
how values for a were obtained.
For a multi-species aerosol composed of m chemicals with differing toxicities that lead to the same
toxic response, we need to consider the relative toxicities of the different species. The overall exposure
(Eh) to the mixture is expressed as
(2)
where h^t is the toxicity ratio of each chemical / in
relation to a reference chemical.
A simplified description of the pulmonary system
divides it into the extrathoracic (ET), tracheobronchial (TB), and alveolar (ALV) regions. Equation (2)
can therefore be expressed by:
— 2-1 IpiX&ET,AET./ +
(3)
where AET h ATBh and /4 ALV , a r e the masses penetrating into the extrathoracic, tracheo-bronchial, and
alveolar regions, respectively. The above equation is
based on the assumption that the value for /3 is the
same for all three pulmonary regions. Since (5 normalizes effects relative to a reference chemical, the
NiCl2 and CoCl2-induced synergistic response
calculated value for the overall exposure Eh is
numerically equivalent to an exposure to the reference chemical alone. The Eh value can be compared
to the existing occupational exposure limit (OEL) of
that reference chemical to determine if a worker has
been exposed to an unsafe mixture of chemicals.
The purpose of the studies described here was to
quantify the toxicity ratio, /3, for mixtures of nickel
and cobalt chlorides. In our in vitro system, the reference chemical was nickel chloride (NiCl2), and h represented the biological endpoint of cell viability.
Ramachandran et al. (1996) proposed that the toxicity
ratio, p\ for a chemical such as cobalt chloride
(CoCl2) be calculated as:
PTLV.COCU —
TLV f ,, c/l
{ocET y\ET
(4)
j + 0CT
(7)
Clearly, the value of jSLDso.mixture w iU depend on the
relative proportion of the different chemicals in the
mixture.
This more general expression encompasses the special case when the responses are purely additive when
j3LD5o,mixture *s r e l a t e d to the (3 of the individual chemicals by the relation
PLD50,mixture
TLV w c / 2
411
2J
=
(°)
fPi I &ET,AET,I
+ &TB,ATB,I
+ ^ALV./^ALV.i)
i= 1
The [5 for NiCl2 is unity by definition, since NiCl2 is
the reference chemical. The calculation of /3 TLV from
Eq. (4) uses the threshold limit values (TLVs) set by
the ACGIH, which in turn, are based on available
health-related toxicology and epidemiology data. One
limitation of this approach is that TLVs are based on
a range of health effects, and not necessarily on a
single health end-point as Ramachandran et al. (1996)
have assumed in their model.
To avoid the limitation of non-specific health-endpoints, we used specific toxicology data. The determination of a median lethal dose (LD50) value is usually
the first piece of data obtained for a chemical's toxicological profile. The LD50 values were substituted
for TLVs into Eq. (4) to re-define j5:
LD S0 ,MC/ 2
7^
(5)
Equations (4) and (5) implicitly assume that the
response to a mixture of chemicals is additive, that
is, it is equal to the sum of the responses to the individual components of the mixture. This also implies
that the effects of the components of the mixture are
mutually independent. Hence the equivalent exposure
is simply the weighted sum of the exposures to the
different chemicals where the weights are the relative
toxicities of the chemicals. Thus a more toxic chemical will have a proportionally greater contribution to
the equivalent exposure.
However, if there are synergistic or antagonistic
effects, then the equivalent exposure should be
greater (or less) than that calculated using Eqs (4) and
(5). Since in such instances, the mixture behaves very
differently than the sum of its parts, it is appropriate
to define a /3 for the whole mixture (instead of its
components):
pLD.SO.mixture ~
LD50,mixture
Then Eq. (3) can be more simply written as
(6)
2
{^ET.^ET,, + (XTBATBJ + «ALV,^ALV,,}
In other words, for the additive case pYoscmixmre is a
weighted average of the /3 of the individual chemical,
with the weights being the amounts of each chemical
being taken up biologically. If there are synergisms
or antagonisms, then the value of pYD50,miXture will be
greater than or less than the right-hand side of Eq.
(8), respectively.
METHODS
Cell culture
MP48 cells, originally isolated from a fetal rat lung
(Mallampalli et al., 1992), were grown in a gassed
(5% CO 2 ), humidified incubator at 37°C in Waymouth's MB 752/1 medium (Life Technologies, Inc.,
Rockville, MD) containing 10% fetal bovine serum
(FBS) (Life Technologies). We used cells between
passages 40 and 80. Agents were added directly to
the medium after cells had grown to confluency.
Cell viability measurements
Stock solutions (100 mM) of NiCl2 (Sigma Chemical, St Louis, MO) and CoCl2 (Spectrum Chemical
Manufacturing Corp., Redondo Beach, CA) were prepared in serum-free medium and stored at 4°C. Cells
were treated with 20 jiM gramicidin (Sigma
Chemical), NiCl2, or CoCl2 in the presence of 10%
FBS. After the cells were incubated with the agents
for 4 h, they were rinsed twice with phosphate-buffered saline (PBS). Fresh medium containing 10%
FBS was added, and the cells were incubated at 37°C
for an additional 24 h.
We used the CellTiter 96 Cell Proliferation Assay
(Promega Corp., Madison, WI) to monitor cell
viability. Briefly, 3-(4,5-dimethylthiazol-2-yl)2,5diphenyl tetrazolium bromide (MTT) dye was added
to each well and incubated at 37°C for 1 h, 47 min
D. P. Cross et al.
412
before adding the Stop Solution supplied with the kit.
Absorbance was measured at 570 and 650 nm using
a spectrophotometer. Observed cell viability (Obs
%V) of cells exposed to a concentration of metal salt
or a mixture of metal salts was determined by
Obs %V =
"°
65
°
)
where A570 and A650 are the absorbances at 570 and
650 nm, E is the metal salt-exposed cells, G is the
positive-control cells treated with gramicidin, and V is
the vehicle control (treatment with serum-free media
only). In live cells, MTT dye is converted to a formazan product which has a maximal absorbance at 570
nm (A570). To reduce background from nonspecific
absorbance, such as cell debris or fingerprints, the
absorbance at a reference wavelength above 630 nm
was measured and subtracted from the A510 value.
Because the raw absorbance values may vary slightly
between each experiment, negative and positive controls were performed with each trial. The negative
control cells were untreated (exposed to the vehicle
only, represented by V); the positive control cells
were treated with a known cytotoxic agent, gramicidin, to ensure the death of all of the cells (these
absorbance values are represented by G). Equation (9)
normalizes the raw absorbance values of each treated
sample such that they are represented as percentages
of the untreated cell population. Cell viability equals
0% for the positive control and 100% for the negative control.
Regression fits
Cell viability data used in modeling was fit to the
logistic equation
1
dM
— = r-XM
dt
(ID
xl00
(9)
Cell viability =
Their model includes an equation to describe changes
in the lung mass burden over time due to soluble
nickel (NiSO4):
where r is the rate of deposition, M is the mass burden, and A is the overall clearance rate coefficient,
defined as
-*?
(day")
(12)
In humans, the dimensionless clearance rate coefficients a, b, and c for NiSO4 are 10.285, 17.16, and
0.105, respectively (Hsieh et al, 1999). The term ms
is equal to MIS where M is the mass burden of nickel
in the lung and S is the alveolar surface area
(6.27x105 cm2 for humans). For the application of
Eqs (11) and (12) in our model, that is, Eq. (7), we
assumed that the clearance kinetics of NiCU and
NiSO4 were identical since both are soluble nickel
compounds.
Andersen and Svenes (1989) autopsied employees
who had worked in a nickel refinery and measured
their lung nickel content. The mass burdens measured
by them were the result of complex exposures to a
number of nickel compounds of different particle
sizes and solubilities. Recognizing these limitations
in their data, while using their reported values to represent the mass burden M, we chose the lowest and
highest values for our calculation of the nickel clearance rate. We used deposition rate calculations (0.143
and 0.297 |ig min ' for 'at rest' and 'at work' breathing parameters, respectively) performed by Ramachandran et al. (1996) to calculate the degree of biological uptake, a:
(10)
a=
deposition rate—clearance rate
deposition rate
(13)
where
1 « o ^[median]
1.658
a = -1.658
and b = In (Ta
In
Agent concentration (C) on the abscissa was plotted
against the percent cell viability function on the ordinate. The median of the curve represented the LD 50
concentration; <7g is a measure of the steepness of the
concentration-response curve and is calculated by the
ratio LD 84 /LD 50 .
RESULTS AND DISCUSSION
Obtaining estimates of oc
We used the modeling results of Hsieh et al. (1999)
to derive a value for the biological uptake factor, a.
Equation (13) assumes that any particles deposited in
the lung that are not removed by clearance mechanisms are biologically absorbed by the organism
and, therefore, contribute to the observed biological
effect.
Using deposition rate values from Ramachandran
et al. (1996) and nickel burden data from Andersen
and Svenes (1989) and Eq. (13), we found that
a= 1.00 for every situation. The uniform a = 1.00
values calculated for biological uptake mean that all
of the deposited particles will be taken up by the
organism almost immediately upon contact in the
lung, regardless of the workers' breathing parameters.
This makes sense, since NiSO4 and NiCl2 are soluble
compounds. We assume that a = 1.00 for CoCl2 as
well, since it is also a soluble metal salt.
NiCl2 and CoCl2-induced synergistic response
Obtaining estimates of ft
We set out to determine the value of the toxicity
parameter for our model, ft, that we can use in Eqs
(3) and (7). In the model we propose, we assume that
the toxicity ratio, /3, calculated from cellular assays
can be extrapolated to human inhalation exposures.
As we have noted earlier, the parameter p can be
calculated in three different ways. W e quantified the
toxicity ratio, /3, DS(), in terms of NiCl 2 /CoCl 2 mixtures
in the following manner. After fitting logistic curves
to the individual concentration-responses for NiCl 2
and CoCl 2 alone (Fig. 1), we found that the LD SO for
NiCl 2 -induced decreased cell viability was 5.7 m M ,
whereas the LD 5 0 for CoCl 2 -induced decreased cell
viability was 1.1 mM. These values were substituted
into Eq. (5) to calculate the toxicity ratio, /3, of CoCl 2
relative to NiCL:
LD S( ,
5.7 m M
LDsa
1.1 mM
= 5.2
413
plotted against the A C G I H ' s current TLVs (ACGIH,
1999). Although regression analyses revealed better
correlations
for L C 5 0 versus T L V (adjusted
R = 0 . 8 5 9 - 0 . 9 1 2 ) compared to L D 5 0 versus TLV
(adjusted R = 0 . 6 1 6 - 0 . 7 1 7 ) , we feel that the favorable correlations justify our substitution.
However, the use of these values of j3 calculated
in Eqs (4) and (5) are limited to additive models. W e
therefore used the more general expression given in
Eq. (6). For the special cases of pure NiCl 2 and CoCl 2
exposures, this general expression should yield the
same result as Eq. (5), illustrated by the following
calculation. Using LD 5() mixture values stated in Table
1, and LD30,yv,c/2 = 5.7 m M , when [NiCl 2 ] = 0,
5.7
J
Similarly, when [CoCl 2 ] = 0, we obtain
^D5O,/V/C7T
This value is very close to that calculated using Eq.
(4):
TLV,
-'TLV.CoCU —
TLVO)C/i
0.10 m g m 3
3 = 5.0
0.02 mg m
This is consistent with an analysis performed by Suda
et al. (1999) who found good correlation between
TLV and LD 5 0 values derived from animal models.
In their investigation, LD S 0 and median lethal air concentration (LC 5 0 ) values as listed in the Registry of
Toxic Effects of Chemical Substances (RTECS) were
100
LD<
^^50,NiCI-,
5.7
LD,
5.7
W e chose to represent mixture composition as the
fraction of one metal salt normalized to the total agent
concentration. Although the fraction of either metal
salt could have been chosen as data for testing the
model, we chose to use the CoCl 2 fraction (F C o ). F C o
was calculated by the following:
[CoCl 2 ]
103
10
Concentration [
Fig. 1. Percentage viability of alveolar cells exposed to various
concentrations of pure CoCU (solid line) and NiCl2 (dashed
line). The solid and open circles are the actual experimental
data±standard error (SE) and the curves are logistic regression
fits to the data.
=1
W e then investigated the effects of mixtures of
NiCl 2 and CoCl 2 on cell viability. CoCl 2 was held
constant at six different concentrations (0, 100, 300,
500, 600, and 750 |iM) while the concentration of
NiCl 2 varied (Fig. 2). The results of holding [NiCl 2 ]
constant at 0, 100, 300, 500, 600, and 750 | i M while
varying [CoCl 2 ] are shown in Fig. 3. Figures 2 and
3 show only the logistic regression fits to the concentration-response data.
[CoCl 2 ] + [NiCl 2 ]
10
= 5.2
50,CoCI2
(14)
Table 1 lists the mixtures shown in Figs. 2 and 3 that
induced 5 0 % decreases in cell viability, along with
the corresponding F C o values.
As stated earlier, exposure to nickel is linked with
lung cancer in humans (Costa, 1991; Kaldor et al.,
1986), and cobalt induces alveolar and bronchiolar
tumor formation in animal models (Bucher et al.,
1999). Consequently, Eq. (7) can be simplified to
describe only the effects of NiCl 2 and CoCl 2 in the
tracheobronchial and alveolar portions of the lung, so
that a E T = 0 and a T B = a A L V = 1 '•
— f>LD50,mixture
(15)
(A TB + A A L V ) C o C 1
D. P. Cross et al.
414
Table 1. Combinations of [NiCl2] and [CoCl2] from concentration-response curves in Figs. 3 and 4 that result in 50</£
cell
viability.
For
each
combination,
the
fractional
cobalt
concentration
is
calculated
as
FCo = [CoCl2]/([CoCl2] + [NiCl2])
CoCl 2 (mM)
LD50, mixturc
NiCl2 (mM)
0
0.1
0.3
0.5
0.6
5.709
3.243
1.100
0.774
0.689
0
0.030
0.214
0.393
0.465
1
1.76
5.19
7.38
8.28
1
0.895
0.713
0.571
0.516
0.426
5.29
6.71
7.66
8.56
8.92
10.26
NiCl2 (mM)
LD50, mixture
CoCl 2 (mM)
1.079
0.851
0.745
0.667
0.640
0.556
0
0.1
0.3
0.5
0.6
0.75
"Calculated at the LD 50 .
100
100
100uMCoCI2
300uMCoCI2
500 uM CoCI2
600uMCoCI2
750uMCoCI2
No NiCI2
-100uMNiCI2
300uMNiCI2
500uMNiCI2
600|jMNiCI2
750 uM NiCI2
75 -
\\\
\
25
\
i
1
400
10
NiCI Concentration [ uM]
Fig. 2. Percentage viability of alveolar cells exposed to mixtures of NiCl2 and CoCl2 with CoCl2 held constant at the concentrations shown in the inset. Curves are logistic fits to data
points (not shown). The arrow illustrates how an LD50 value
for a particular mixture (LD50-mixlure) was obtained. In this
example, the LD50 of NiCl2 alone (no CoCl2) was determined
to be 5.7 mM.
The a terms have been removed from the above
expression since they are all equal to one. To quantify
the synergistic effects of NiCl 2 /CoCl 2 mixtures, we
first determined the cell viability values expected for
an additive interaction. For the additive case,
/^LD5o,mixture is a weighted average of the (5 values of
NiCl 2 and CoCl 2 , with the weights
being
(A TB + A ALV ) N ici 2 and (A TB + A A L V )coa 2 , respectively.
In a plot of /^LDso.mixture versus F C o , using the (5 values
i
i
i
I.
i
800
"r
^
l ^
1200
1
1
r-1—1
1600
1
1
1
2000
CoCI Concentration [ uM ]
Fig. 3. Percentage viability of alveolar cells exposed to mixtures of NiCl2 and CoCl2 with NiCl2 held constant at the concentrations shown in the inset. Curves are logistic fits to data
points (not shown). The arrow illustrates how an LD,,,.mixlllIx.
value was obtained. In this example, the LD5() of CoCl2 alone
(no NiCl2) was determined to be 1.1 mM.
for pure NiCl2 and pure CoCl2 (obtained earlier) as
the endpoints, a straight line was drawn to represent
the additive interaction (dashed line, Fig. 4). The equation describing this line is
B LD50,mixture = 4.2
[Co]
+ I
[Co] + [Ni]
(16)
However, the actual measurements of /3LD.so.mixiure a t
various values of FCo did not fall on this straight line.
NiCl2 and CoCl2-induced synergistic response
Synergistic Model
Additive Model
— —
•
12 -
p Calculated from Observed Data Points
•
* 10
s
a
S 6 -
C2.
r
,
i
1
0.2
,
,
,
1
0.4
,
,
,
1
0.6
,
,
,
1
,
0.8
Fig. 4. Variation of j3 = LDS0A,,r,yLDS() „„,„„.,, with fractional
cobalt content in the mixture. The additive model is represented
by the dashed line. The proposed synergistic model has the
best-fit equation (S = -22.778(F Co ) 2 + 26.796(FCo) + 0.9808
(R2 = 0.93).
and therefore did not match the proposed additive
model (Fig. 4). The values of /3LD5o,mixture lay above
the linear additive model, suggesting a synergistic
response to the mixture. A second-order polynomial
equation was found to fit the data well.
[Co]
= -22.778
[Co] + [Ni
[Co]
+ 0.9808
+ 26.796
[Co] + [Ni;
(17)
While this equation is merely a regression fit and no
physical significance should be attached to it, it can
be used to quantitatively describe the synergistic cytotoxic effects of NiCl2/CoCl2 mixtures on MP48 cells.
For a particular NiCl2/CoCl2 mixture composition, the
equivalent NiCl2 exposure is obtained by substituting
Eq. (17) into Eq. (15).
Incorporating synergism between chemicals while estimating equivalent exposures
We use Eq. (17) to extrapolate to human inhalation
exposures by using the amounts of airborne nickel
and cobalt mass deposited in various parts of the respiratory tract (instead of concentrations of these metal
salts in solution used in our cell culture experiments).
Ramachandran et al. (1996) used personal cascade
impactor data obtained at the copper electro-winning
process of a nickel refinery to obtain particle mass
size distributions of nickel and cobalt aerosols. These
were used with results of particle deposition
efficiency curves developed by Heyder et al. (1986)
415
from experimental studies of inhalation with human
volunteers. Table 2 identifies the values for the thoracic and alveolar mass concentrations of nickel and
cobalt used to calculate the health-related nickel-equivalent exposure, Eh (see Ramachandran et al. (1996)
for details). We used these data to calculate equivalent exposures first assuming additivity, and then
incorporating synergistic effects. For these two cases,
we examined conditions that can be related to 'at rest'
and 'at work', that is, 7.5 breaths per min with 1 1.
per breath (or 7.5 1. min"'), and 15 breaths per min
with 1.5 1. per breath (or 22.5 1. min '), respectively.
Table 3 lists the equivalent exposures and the dose
rates for all these cases. As an example, substituting
the mass concentrations for 'at work' deposition conditions into the additive model (Eq. (16)), we obtain:
Eh — 13.7 jig m 3. If we use the same mass concentration values to calculate ft for the synergistic model
(Eq. (17)), we obtain: /3LD50,mixture = 6.1, leading to the
nickel-equivalent exposure of Eh = 41.5 |ig/m 3 which
is about three times greater than the additive interaction.
The mass deposition rate, or dose, that an individual receives is more relevant to health. The exposure
values calculated above, along with the corresponding
breathing rates for 'at work' conditions, lead to a
nickel equivalent dose according to the additive
model of 0.308 |ig min" 1 , but the corresponding
nickel equivalent dose 'at work' according to the synergistic model is 0.934 |ig min" 1 .
NiCU- and CoCl2-induced cytotoxicity
Our observation that mixtures of NiCl2 and CoCl2
induce a synergistic toxic response in cell culture is
remarkably consistent with Johansson et al.'s finding
that mixtures of NiCl2 and CoCl2 induce a synergistic
response in vivo (Johansson et al., 1989, 1991).
Johansson et a/.'s subchronic inhalation studies
showed that mixtures of NiCl2 and CoCl2 induced a
synergistic response in the respiratory tract of rabbits,
as indicated by changes in the concentrations of phosphatidylcholine and phospholipid levels in the wet
lung and formation of type II cell aggregates
(Johansson et al., 1989, 1991). For example, exposure
of rabbits for 6 h per day, 5 days a week for 4 months
to aerosols of either NiCl2 (0.5 mg m" 3 ) or CoCl2
alone (0.5 mg m~3) increased phosphatidylcholine
levels in the lung by 20% and 30%, respectively, relative to the unexposed controls. Exposure of rabbits to
a mixture of NiCl2 and CoCl2 (0.5 mg m 3 of each
salt) increased the phosphatidylcholine levels by
180% — more than a three-fold increase over what
would be expected from an additive response. Likewise, phospholipid concentrations increased synergistically in response to exposure to mixtures of NiCl2
and CoCl2. Exposure of rabbits to aerosols of either
NiCl2 or CoCl2 alone increased phospholipid levels in
the lung by 20%, relative to the unexposed controls.
Exposure of rabbits to a mixture of NiCl2 and CoCl2
416
D. P. Cross et al.
Table 2. Parameters used to calculate exposure (E,,) and dose for different breathing conditions
Cobalt
Nickel
(ug m 3 ) a
'At rest', 7.5 1. min ' breathing rate
'At work', 22.5 1. min" 1 breathing
rate
a
2.7
2.3
4.9
2.9
ATB
( u g m •1)a
0.7
0.6
(ug m
1.6
1.0
From Ramachandran et al. (1996).
Table 3. Equivalent exposures and dose rates given additive and synergistic responses to Ni/Co mixtures for 'at rest'
and 'at work' conditions
3
E,, (ug m~ )
'At rest', 7.5 1. min ' breathing rate
'At work' , 22.5 1. min ~' breathing
rate
Ni-equivalent dose (ug min ')
Additive
Synergistic
Additive
Synergistic
19.5
13.7
58.8
41.5
0.146
0.308
0.411
0.934
(0.5 mg m 3 of each salt) increased the phospholipid
levels by 130% — again, more than a three-fold
increase over what would be expected from an additive response. In addition, Johansson et al. reported
that CoCl2 alone, but not NiCl2 alone, induced the
formation of aggregates of type II cells. The formation of these aggregates was more pronounced after
exposure to CoCl2 and NiCl2 together than to CoCl2
alone. This suggests that NiCl2 potentiates the effects
of CoCl2 in the formation of these aggregates when
these metal salts are presented together.
The mechanisms by which mixtures of NiCl2 and
CoCl2 interact to induce a synergistic toxic response
are not yet clear. One possibility is that each metal
potentiates the cellular uptake of the other metal.
Costa demonstrated that the carcinogenic potency of
a nickel species is positively correlated with the
degree to which it is phagocytosed (Costa and Mollenhauer, 1980). Insoluble nickel, which is carcinogenic, is phagocytosed to a greater extent than soluble
nickel salts, such as NiCl2, which are not carcinogenic. Further work is needed to determine if CoCl2
increases the rate of cellular uptake of NiCl2 through
either phagocytosis or another transport mechanism.
Little is known about cellular transport of cobalt or
alternate transport mechanisms for NiCl2. There is a
bacterial transport system, called CorA, which can
transport Mg2+, Co 2+ and Ni 2+ (Bijvelds et al, 1998).
A similar transport system may also exist in mammalian cells. Interestingly, Mg 2+ uptake is inhibited
by Co 2+ and Ni 2+ in rat jejunal bursh boarder membrane vesicles (Bijvelds et al., 1998). This suggests
that Co 2+ and Ni 2+ may compete with magnesium for
a common transport system in mammalian cells.
Once in the cell, NiCl2 and CoCl2 may cause toxicity by damaging DNA or modulating critical enzymatic reactions. For example, some investigators sug-
gest that NiCl2 causes single-strand breaks in DNA
by generating hydroxyl radicals (OH) (Costa, 1991;
Stohs and Bagchi, 1995). NiCl2 also induces the formation DNA-protein adducts linking preferentially to
the amino acids histidine, cysteine, and tyrosine
(Costa et al, 1994). Ni3S2 and NiSO4 also induce
DNA-protein adducts (Chakrabarti et al, 1999).
Cobalt can also damage DNA; CoSO4 exposure
causes a G to T nucleic acid transversion (Bucher et
al, 1999). A cell containing DNA damage may
induce its own death, for example though apoptosis.
In addition, cobalt can substitute for other divalent
cations such as Mg2+ and Ca2+ in certain biological
reactions (Jennette, 1981), which may also affect cell
fate and function. The similarities between the synergistic response of our cell culture model and Johansson et al's in vivo model to mixtures of NiCl2 and
CoCl2 suggest that our model system may be useful
for investigating the cellular and molecular mechanisms underlying the synergistic toxic responses to
mixtures of NiCli and CoCU.
CONCLUSIONS
Our results suggest that the traditional assumption
of an additive response to exposure to a mixture of
chemicals is not always appropriate, and neglecting
synergistic interactions may cause an underestimation
of the equivalent exposure to mixtures. Experiments
in a cell culture system showed that mixtures of NiCl2
and CoCl2 induced a synergistic response. These
results were incorporated into a human inhalation
model for calculating equivalent exposures to mixtures of different aerosol species. Using particle sizeselective exposure data from an occupational environment, we calculated the equivalent exposure to a mixture of nickel and cobalt aerosols. Our calculations
NiCl2 and CoCl2-induced synergistic response
showed that not including synergisms between the
different species in a mixture may underestimate the
equivalent exposure to mixtures by a factor of three
or more.
Although our studies used relatively high concentrations of NiCl2 and CoCl2, two lines of evidence
suggest that our results may also apply to estimating
human exposures to relatively low airborne concentrations. First, results from our studies regarding the
synergistic response to mixtures of NiCl2 and CoCl2
are remarkably consistent with the results of Johansson et a/.'s in vivo studies, in which rabbits were
exposed to much lower concentrations of NiCl2 and
CoCl2 (Johansson et al., 1989, 1991). These striking
similarities suggest that the results from our cell culture system may indeed reflect the synergistic actions
of NiCl2 and CoCl2 in vivo at lower concentrations.
Second, our model uses the parameter fi, which is the
ratio of the toxicity of a chemical relative to a reference chemical. For the additive case, the value of
j3i.Dso.coci;, = (LD50Jv,(/2)/(LD5o,o)C/2) obtained from in
vitro experiments done at high solution concentrations is 5.2. This is very close to the value of
J3TLV.COCI, = (TLWNiCl2)/(TLVcoa2) = 5.0,
obtained
from relatively low TLVs that are derived from a synthesis of both epidemiology and toxicology studies.
Recognizing that a toxicity ratio derived from in vitro
experiments cannot be extrapolated to estimate
human cancer risks, further research is required to
confirm that the results from our cell culture studies
can be applied directly to human inhalation
exposures. In any case, our results, together with the
results from Johansson et a/.'s in vivo studies, underscore the importance of considering the potential synergistic actions of mixtures when conducting
exposure assessment.
Acknowledgements—This work was supported by a Grant-inAid of Research, Artistry and Scholarship from the University
of Minnesota and by a University of Minnesota Academic
Health Center Faculty Development Grant. The MP-48 alveolar
cells were the gift of Dr David H. Ingbar, Department of Medicine. University of Minnesota. We also thank Anita Wichmann
for excellent technical assistance.
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