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Sistema de Información Científica
Red de Revistas Científicas de América Latina y el Caribe, España y Portugal
Rev. Int. Contam. Ambie. 29 (1) 117-140, 2013
BIOMARKERS OF EXPOSURE FOR ASSESSING ENVIRONMENTAL METAL POLLUTION:
FROM MOLECULES TO ECOSYSTEMS
Patricia MUSSALI-GALANTE
1*
, Efraín TOVAR-SÁNCHEZ
2
, Mahara VALVERDE
1
and
Emilio ROJAS DEL CASTILLO
1
1
Departamento de Medicina Genómica y Toxicología Ambiental, Instituto de Investigaciones Biomédicas,
Universidad Nacional Autónoma de México
2
Departamento de Sistemática y Evolución, Centro de Investigación en Biodiversidad y Conservación, Uni-
versidad Autónoma del Estado de Morelos, Av. Universidad 1001, Col. Chamilpa, Cuernavaca, Morelos. CP.
62209, México
*Autora responsable: pmussali@yahoo.com.mx
(Recibido marzo 2012, aceptado enero 2013)
Key words: metals, biomarkers, ecological markers, genetic toxicology, ecotoxicology, “omic” technologies
ABSTRACT
Metals are among the most prevalent substances released into the environment that have
a profound effect on living organisms. Chronic environmental exposures usually exert a
continuum of biological responses across levels of biological organization, ranging from
alterations in molecules, compromising individual health and putting ecosystem integrity
at risk. Such scenarios have triggered the research to establish “early-warning” signals,
or “biomarkers”, refecting the adverse biological responses towards environmental pol
-
lution. In this review, we assess the different types of biomarkers most used to analyze
environmental metal pollution across all levels of biological organization and in each
section representative examples in human and animal species and/or wild populations
are given. Also, the “omics” approach is described and how these novel technologies
are reinventing the Feld o± toxicology, providing “molecular signatures” o± exposure,
enabling a more robust risk assessment than has ever been achieved previously. Finally,
conclusions and suggestions are given, highlighting why future efforts must focus on
integrating biomarker response across levels of biological organization, which integrate
realistic exposures using multi-species and multiple-biomarkers with prognostic value to
resolve or at least have a closer insight into complex environmental problems.
Palabras clave: metales, biomarcadores, marcadores ecológicos, genética toxicológica, ecotoxicología, tecnología
genómica
RESUMEN
Los metales se incluyen dentro de las substancias más persistentes emitidas al am-
biente, los cuales tiene efectos importantes sobre los seres vivos. La exposición
ambiental crónica a los metales generalmente resulta en un continuo de respuestas
biológicas que se da en todos los niveles de organización biológica. Estas respuestas
pueden observarse desde alteraciones a nivel molecular, comprometiendo la salud del
individuo, hasta poner en riesgo la salud del ecosistema. Lo anterior ha impulsado la
REVIEW
P. Mussali-Galante
et al.
118
investigación científca para establecer “señales tempranas de alerta” mediante el uso
de “biomarcadores”, los cuales reFejen los e±ectos biológicos adversos producidos
por los contaminantes ambientales. En este trabajo se revisan los biomarcadores más
utilizados para estudiar la contaminación ambiental producida por metales, en todos
los niveles de organización biológica y en cada sección se dan ejemplos representativos
en humanos, especies animales y poblaciones silvestres. Además, se describe desde la
perspectiva de las ciencias ómicas, como estas metodologías han reinventado el campo
de la toxicología, proporcionando “huellas moleculares” de exposición, permitiendo así
un análisis de riesgo más robusto el cual no se había alcanzado antes. Finalmente, se
dan conclusiones y sugerencias resaltando la razones de por qué los esfuerzos futuros
deben enfocarse en la integración de las respuestas proporcionadas por los biomar-
cadores en todos los niveles de organización biológica, que consideren exposiciones
más apegadas a la realidad, mediante diseños experimentales más rigurosos utilizando
multiespecies y multibiomarcadores con valor predictivo para resolver, o entender
mejor los problemas ambientales complejos.
INTRODUCTION
The environment is continuously loaded with fo-
reign chemical substances, released by anthropogenic
activities. As a result, many wildlife and human po-
pulations are exposed to a variety of chemical agents
which may lead to a collection of biological effects.
Among environmental pollutants, metals have been
identifed among the most toxic elements to nearly
all living organisms (EPA 2000). The relationship
between metal toxicity and a plethora of effects is
well established. Studies from populations exposed
to metals, were among the frst to establish quantita
-
tive relationships between the external exposure, the
internal dose, and the early effects (Bernard 2008).
Organisms integrate exposure to contaminants in
their environment and respond in some measurable
and predictable way, being these responses observed
and measurable across different levels of biological
organization (Bickham
et al
. 2000). In the feld o±
toxicology, it is essential to be able to measure the
exposure to a toxic agent, the extent of any toxic
response and also to predict the likely effects. Hence,
integrating measures of different types of responses to
toxic stress of exposed individuals and populations,
offers a powerful tool for documenting the extent
of exposure and the effects of environmental metal
contamination. Tools that enable this to be done are
called “biological markers” or “biomarkers”. For
these reasons, the use of biomarkers for environmen-
tal monitoring of individuals and populations exposed
to chemical pollution has gained much attention in
the last decades, because it offers great opportunities
for a fast and sensitive detection of chemical stresses
within organisms (Peakall and Shugart 1992, Handy
et al
. 2003).
The use of biomarkers in environmental health
was described in a series of publications issued by
the Board of Environmental Studies in Toxicology of
the National Research Council (NRC 1987, 1989) of
the USA. The NRC defnes biomarkers as “Indicators
of events in biological systems or samples” and was
further described as “tools that can be used to clarify
the relationship, if any, between exposure to a xeno-
biotic substance and disease”. Also, the NRC classifed
biomarkers into three categories based on their relation
to the exposure-disease continuum: biomarkers of
exposure, effect and susceptibility. Some years later,
Lagadic
et al
. (1994) referred to biomarkers as “bio-
chemical sub-lethal changes resulting from individual
exposure to xenobiotics”. These defnitions denote that
many researches focus on biomarkers as measures at
the cellular or sub-cellular levels, as in the case of
molecular epidemiology and genetic toxicology, where
measurements of toxic responses are routinely used
to infer cause-effect relationships between biomarker
response and health effects of the exposed individuals
(Perera 2000). Also, the ±ormer defnitions restrict the
term biomarker to measurements at or below the level
of individuals. Hence, it becomes important to consider
that there are other types of biomarkers that attempt
to measure effects of chemical pollution at the popu-
lation, community and even at the ecosystem level
(ecotoxicology). This reFects the ±act that pollutants
can exert their inFuence at all levels o± biological or
-
ganization (Lagadic
et al
. 1994, Peakall 1994). In this
context, Handy
et al
. (2003) expanded the concept as
“the identifcation o± specifc molecular, biochemical,
physiological and behavioral changes in populations
following pollutant exposure”. Both approaches try
to reveal cause-effect relationships between the initial
exposure and the subsequent effects, based on the use
BIOMARKERS OF METAL EXPOSURE: FROM MOLECULES TO ECOSYSTEMS
119
of biomarkers, but in different levels of biological
organization.
In this review, we assess the most common bio-
markers used in each level of biological organization.
The frst section, deals with biological responses
exerted by metals from molecules to individuals. The
next section, addresses biological responses from
populations to ecosystems. In each section, repre-
sentative examples concerning environmental metal
exposures in humans and animal species (individuals
and populations) are given, in order to illustrate how
the use of biomarkers is suitable for studying metal
exposures.
Also, a new approach is described, the “omics”
approach, where the search for new biomarkers
becomes possible. These novel technologies offer
added value compared with classical testing with
whole organisms because they provide information
concerning the molecular basis of exposure “mole-
cular signatures” and act as “early warning” signals,
enabling a more robust environmental monitoring
than has ever been achieved previously (Snape
et
al.
2004).
DEFINITIONS AND TYPES OF
BIOMARKERS: FROM MOLECULES
TO INDIVIDUALS
Many metals are essential to living organisms but
some of them are highly toxic or become toxic at
high concentrations, these include iron (Fe), Copper
(Cu), Zinc (Zn), Cobalt (Co), Molybdenum (Mo), and
Manganese (Mn). Light metals such as Sodium (Na),
Potassium (K), and Calcium (Ca) play important
biological roles. Metals such as Mercury (Hg), Lead
(Pb), Niquel (Ni), Chromium (Cr), Cadmium (Cd),
and Arsenic (As) are generally not required for meta-
bolic activity and are toxic to living organisms at qui-
te low concentrations (Valavanidis and Vlachogianni
2010). Other metals such as Vanadium (V) which is
present in almost all-living organisms but its essen-
tiality in cellular functions is yet to be established,
is also capable of inducing toxic effects in various
species (Rodríguez-Mercado and Altamirano-Lozano
2006). As a consequence, the toxicological effects of
metals have been widely studied, where it has been
recognized that the relationship between exposure
and disease is as a multistage process which includes
external exposure, internal dose, early biological
eFFects, altered structure and Function and fnally
clinical changes or disease (Link
et al
. 1995, Vanden-
Heuvel and Davis 1999).
When characterizing toxicological responses, it is
desirable to distinguish each step in this continuum.
Biomarkers signify these alterations in biological
systems and may be indicators of exposure, effect
or susceptibility and may overlap sometimes (Perera
1996, Perera and Weinstein 2000, Jakubowski and
Trzcinka-Ochoka 2005, Nordberg 2010).
Biomarkers of exposure
:
“An exogenous substan-
ce or its metabolite or the product of an interaction
between a xenobiotic agent and some target molecule
or cell that it is measured in a compartment within
an organism”. These types of biomarkers are also
known as “biological dosimeters” or biomarkers of
internal dose, and when they measure the product
of the interaction with target molecules they are re-
garded as “biomarkers of biological effective dose”
(Timbrell 1998).
Biomarkers of effect
:
A measurable biochemical,
genetic, physiological, behavioral or other alteration
within an organism that, depending on the magnitude,
can be recognized as associated with an established or
early health impairment or disease” (Timbrell 1998).
Biomarkers of susceptibility
:
“An indicator of
an inherent or acquired ability of an organism to
respond to the challenge oF exposure to a specifc
xenobiotic substance” (Pavanello and Clonfero 2000,
Sakai 2000).
TYPES OF BIOMARKERS OF EXPOSURE
Biomarkers of internal dose:
these are the most
used, because of their precision, reliability and rele-
vance to individual risk (Perera and Weinstein 2000,
Aitio
et al
. 2007, Nordberg 2010). They have been
used in combination with measures of external expo-
sure. Currently, highly sensitive analytical methodo-
logies make possible to measure very low concen-
trations of a chemical substance or its metabolite in
various cell types, organs or body ±uids. These types
of biomarkers take into account individual differen-
ces in absorption, metabolism, bioaccumulation and
excretion of the compound in question and indicate
the actual dose of the substance within an organism
and in specifc tissues (Perera and Weinstein 2000).
Examples of internal dosimeters of metal exposu-
re include: hair, nail, blood, and urinary levels of total
inorganic As or its metabolites (Hughes 2006, Fowler
et al
. 2007), Pb blood concentrations (Bjorkman
et
al
. 2000,
Aitio
et al
. 2007), Cd blood, urine and kid-
P. Mussali-Galante
et al.
120
ney concentrations (Clarkson
et al
. 1988, Nordberg
et al
. 2007, Nordberg 2010) and methylmercury in
hair (Jakubowski and Trzcinka-Ochocka 2005) and
V concentrations in kidney and liver (Gummow
et
al
. 2006). For a more detailed review and examples
see Fowler (1987, 1992).
Although biomarkers of internal dose are a valua-
ble tool for assessing chemical exposures, they do not
indicate the extent to which a given compound has
interacted with molecular and cellular targets. For
this reason assays have been developed to measure
the “biological effective dose” (Perera and Weinstein
2000).
Biomarkers of biological effective dose
:
These
types of biomarkers occur early in the exposure-to-
disease pathway. Some of them have been shown
to be associated with increased risk of developing
diseases such as cancer. As a result, they are conside-
red as important tools for investigating mechanisms
behind exposure-induced adverse health effects
(Perera 2000, Sorensen
et al.
2003). The best known
examples are DNA-adducts.
The study of DNA-adducts is motivated by the
fact that many environmental contaminants and
some metals are thought to exert their genotoxic
effects through covalent binding with DNA (Perera
and Weinstein
et al
. 2000, Poirier 2004, Gallo
et al
.
2008). DNA-adducts are addition products formed
by covalent binding of all or part of a metal molecule
to chemical moieties in DNA; adducts are formed
when an activated chemical species (electrophilic,
positively charged metabolite) binds covalently to
negatively charged moieties. In other words, they
represent the amount of a given metal that has reacted
with critical cellular macromolecules such as DNA
or proteins in a given tissue (Ehrenberg
et al
. 1996).
In this context, DNA-adducts are among the most
informative biomarkers of exposure to genotoxic
agents (Poirier 2004).
The quantifcation oF DNA-adducts gives inFor
-
mation about the biologically effective dose of a
metal reaching the DNA in cells. As a result, they
represent the amount of the metal that has been ab-
sorbed by the body, undergone metabolic activation,
become bound to cellular DNA and has not been
repaired (Rundle
et al
. 2002, Gallo
et al
. 2008). DNA-
adducts if not repaired or repaired inadequately, may
lead to mutation and alteration of gene function
(Farmer 2004, Jakubowski and Trzcinka-Ochocka
2005, Swenberg
et al
. 2008).
Early studies utilized column chromatography
to examine adduct formation, but this technique
has a detection limit of 1 adduct per 10
6
nucleotides
(Swenberg
et al
. 2008). Thereafter, Randerath
et al
.
(1994) developed one of the most used techniques
to analyze the extent of DNA-adducts, which is
32
P-postlabelling, detecting at least one adduct per
10
8
nucleotides. Recently, using accelerator mass
spectrometry, 1 adduct per 10
12
bases are possible to
detect, which is probably 1 adduct per cell (Singh and
Farmer 2006, Swenberg
et al
. 2008). It is important to
mention that although the formation of DNA-adducts
is not the main mechanism of toxicity of metals, many
authors mention that they may form DNA-adducts
directly, as in the case of Cr (Singh
et al
. 1998, Zhi-
tkovich 2005) and water soluble Ni compounds (Mu-
ller
et al
. 1999), and indirectly (through formation of
free radicals and reactive oxygen species (ROS)) as
in the case of As (Wang
et al
. 2001, Bau
et al
. 2002,
Rossman 2003, Méndez-Gómez
et al
. 2008).
TYPES OF BIOMARKERS OF EFFECT
Biomarkers of effect are perhaps best regarded
as indicators of early changes that could later lead
to clinical disease (Mutti 1995). There are situations
where biomarkers oF exposure are not suFfcient to
predict potential adverse effects. In such situations,
biomarkers of effect are used to understand if a
change in their distribution has occurred as a result to
the chemical exposure. Hence, biomarkers of effect
are not proof of disease caused by environmental
pollution but tools to understand a process that might
eventually lead to adverse effects (Watson and Mutti
2004). Biomarkers of effect give measures of the
alterations on important genetic targets like DNA,
causing DNA-breaks, chromosome aberrations and
micronucleus. Biomarkers of biochemical effect pro-
vide information about oxidative damage in DNA and
proteins, alterations in a wide range of enzymes like
DNA-repair enzymes, and metal-binding proteins,
among others (Frenzilli
et al
. 2009, Rojas 2009).
DNA single (SSB) and double strand breaks
(DSB)
:
Another approach for evaluating the possible
consequences of environmental metal pollution in-
volves the assessment of genotoxic damage measured
as DNA-breaks. Most metals interact indirectly with
DNA, via generation of ROS, causing single and
double strand breaks (Valko
et al
. 2006, Mussali-
Galante
et al
. 2007, Frenzilli
et al
. 2009).
The DNA molecule must undergo continuous
maintenance to sustain its integrity. Several key
mechanisms in DNA-repair processes involve the
BIOMARKERS OF METAL EXPOSURE: FROM MOLECULES TO ECOSYSTEMS
121
degradation of a short stretch of DNA leading to a
transitory break in a single DNA strand. The inciden-
ce of such strand breaks may be enhanced both as a
direct result of metal exposure or as an indirect effect
of repair processes (Shugart and Theodorakis 1994,
Hebert and Murdoch 1996). Measurement of DNA-
breaks induced by metal exposure is common there
are several approaches to quantify the frequency of
DNA strand breakage: the alkaline unwinding assay
(Shugart 1988), the single cell gel electrophoresis
assay or “comet assay” (Rojas
et al
. 1999), chromo-
somal aberrations (Obe
et al.
2002), alkaline elution
(Koch and Giandomenico 1994) and sister chromatid
exchanges (Perry and Wolf 1974), among others
(Ahnstrom 1988, Lindberg
et al
. 2007).
The comet assay, is a rapid, simple, and sensitive
technique for analyzing DNA breakage of single
and double strands, depending of pH conditions, in
individual cells (Singh
et al
. 1988, Silva
et al
. 2000,
Tice
et al
. 2000, Mussali-Galante
et al
. 2005, Rojas
2009). In principle, any organism is suitable for
the comet assay and small cell samples are needed.
As a result, the comet assay has become one of the
major tools for environmental biomonitoring studies
(Valverde and Rojas 2009). It is important to mention
that even when the Comet assay is sensitive to detect
strand breaks, it is a nonspeciFc chemical biomarker
of genotoxicity (Dhawan
et al
. 2009). However, the
versatility in terms of cell types used to determine
DNA-breaks as a consequence of metal exposure
is illustrated in the following examples: Humans
exposed to As (Abernathy
et al
. 1999, Calderón
et
al
. 2003, Pandey
et al
. 2007), humans exposed to V
(Ehrlich
et al
. 2008), coelomocytes exposed to Ni
(Reinecke and Reinecke 2004), earthworms exposed
to Cd (Fourie
et al
. 2007), grasshoppers exposed to
Zn (Augustyniak
et al
. 2006), birds (Baos
et al
. 2006,
Pastor
et al
. 2001, 2004), mussels (Machella
et al
.
2006) and wild mice species exposed to heavy metal
mixtures (Leon
et al
. 2007, Tovar-Sánchez
et al
.
2012). More detailed examples are given by Dhawan
et al
. (2009) and Frenzilli
et al
. (2009).
Chromosome aberrations (CA):
From the vast
scientiFc literature assessing CA as a biomarker of
effect, it is evident that cytogenetic biomarkers have
been a valuable tool for studying the most important
environmental hazards occurring in the past decades.
The use of valid biomarkers of risk in populations
exposed to genotoxic agents is the most suitable and
well-established approach for analyzing many mo-
dern exposures (Tucker and Preston 1996, Bonassi
et al
. 2005). CA are induced by agents that damage
chromosomal DNA (Natarajan 1976). A large amount
of evidence demonstrates that DNA-DSB are the
principal lesions in the process of CA formation (Pfei-
ffer
et al
. 2000). DSB arise spontaneously at high
frequencies through a variety of cellular processes
(Natarajan 1976, Bonassi
et al
. 2005). However, the
majority of chemical mutagens are not able to induce
DSB directly but lead to other lesions in chromoso-
mal DNA which, during repair or DNA synthesis,
may give rise to DSB and eventually to CA (Tucker
and Preston 1996, Obe
et al
. 2002).
Many studies assessing the frequency of CA and
other genotoxic endpoints resulting for environ-
mental metal exposure have been conducted in As
exposed human populations (Ostrosky-Wegman
et al
.
1991, Gonsebatt
et al
. 1997) and in animal species in-
habiting superfund sites. In this context, the studies of
McBee
et al
. (1987) and McBee and Bickham (1988)
where the Frst to report higher levels of karyological
damage in two wild rodent species living in a metal
contaminated site. Also in many Fsh species (Prein
et
al
. 1978, Hooftman and Vink 1981) in orthopterans
(
Tetrix tenuicornis)
living in zinc-lead mine spoils
(Warchałowska-Śliwa
et al
. 2005), and in dipterans
(
Chironomus riparius
) inhabiting a polluted site (Zn,
Cd, Pb, Cu) (Michailova
et al
. 1996).
It is important to mention that unlike chemical
DNA-adducts, chromosomal aberrations are a non-
chemical speciFc biomarker (Perera 2000).
Micronuclei (MN):
As their name suggests,
micronuclei are masses of DNA (resembling small
nuclei) found in the cytoplasm, rather than being
contained within the nuclear membrane. Micronuclei
form when acentric or centromeric chromosome
fragments are unable to attach to a spindle Fber du
-
ring cell division or when an intact chromosome is
excluded from the nucleus because of defective cell
division. Hence, micronuclei may be a consequence
of either chromosomal breakage or dysfunction of
the spindle mechanism (Lindberg
et al
. 2007). These
types of micronuclei can be distinguished (Boei and
Natarajan 1995), and there is evidence that genotoxic
agents can be differentiated by whether they induce
chromosomal breakage or loss (Chen
et al
. 1994,
±enech and Crott 2002) and/or centromeric modiF
-
cations (Fenech
et al.
1999). They have been studied
for many years, in experimental research as well as
in environmental monitoring. In the last decade, MN
assay has gained a lot of attention because it offers
several advantages: a) MN can be observed in almost
any eukaryotic cell type, b) Speed, ease and low cost
of the analysis, and c) the non-requirement for me-
P. Mussali-Galante
et al.
122
taphase cells. Thus, MN analyses can be employed
in studies with different experimental conditions, in a
wide variety of animal species (Bonassi
et al
. 2005).
For many years, research employing the MN assay
in environmental exposures has been conducted in
individuals exposed to As in drinking water (Fenech
et al
. 1999, Basu
et al
. 2004).
Recently, research has been carried out to evaluate
the clastogenic and/or aneugenic activity of different
environmental metal pollutants in natural animal
populations (Bolognesi and Hayashi 2011). For this
purpose, the fsh erythrocyte micronucleus test has
been used as an informative biomarker to evaluate
the clastogenic potential of metals in water (Al-Sabti
1994, Minissi
et al
. 1996, Russo
et al
. 2004). Other
examples that report statistically high frequencies of
MN include, eels (
Anguilla anguilla
) exposed to Cd
and Hg (Sánchez-Galán
et al
. 2001), and the wood
mouse (
Apodemus silvaticus
) exposed to Cd, Fe, Zn,
Cu, Mn, Mo and Cr (Sánchez-Chardi
et al
. 2007).
Sister chromatid exchange (SCE):
This assay is a
well-known cytogenetic technique that has been used
extensively to assess DNA damage at the chromoso-
mal level (Hagmar
et al
. 1994). SCE occur as a nor-
mal feature of cell division in mammalian cells. They
are believed to represent the interchange of DNA
replication products at apparently homologous loci
which involve DNA breakage and reunion (Gauthier
et al
. 1999, Wilson and Thompson 2007). During
the S-phase of the cell cycle, DNA is replicated, and
each chromosome becomes duplicated into two clo-
sely associated daughter chromatids that are linked
tightly at the centromere. Sister chromatids are visible
cytologically in late prophase and early metaphase
of mitosis before chromosome segregation occurs
(Latt 1973, Kaina 2004). Hence, SCE is the process
whereby the sister chromatids effectively break and
rejoin with one another, physically exchanging re
-
gions (Kato 1974, Perry and Wolf 1974, Wilson and
Thompson 2007). While SCE are readily observed
experimentally, the mechanisms that mediate SCE are
not fully understood and controversial results have
been reported (Ohno
et al
. 1982, Hartmann and Speit
1994, Fogu
et al
. 2000, Wilson and Thompson 2007,
Tapisso
et al
. 2009). Particular types of genotoxic
chemicals like bifunctional alkylating agents are in
general potent inducers of SCE, presumably because
homologous recombination is required to repair the
resulting broken replication forks that arise during
crosslink releasing (Thompson 2005). Metals that
are known to induce SCE are cadmium, chromium,
aluminum, arsenic, lead, vanadium and zinc (Siviko-
va and Dianovsky 1995, Bilban 1998, Mouron
et al
.
2004). This evidence comes mainly from
in vitro
(Fan
et al
. 1996, Basu
et al
. 2001, Rodriguez-Mercado
et
al
. 2003, Mouron
et al
. 2004) and
in vivo
(Mukherjee
et al
. 1988, Gennart
et al
. 1993, Lai
et al
. 1998,
Ta-
pisso
et al
. 2009) studies or from studies of humans
exposed to arsenic in drinking water (Ostrosky
et al
.
1991, Lerda 1994, Basu
et al
. 2001, Rossman 2003).
However, there are very few studies assessing the
induction of SCE in wild animal populations [Arctic
beluga whale (
Delphinapterus leucas
), Gauthier
et
al
. 1999] exposed to environmental metal stress in
comparison with other biomarkers of early effect.
Since these biomarkers (SSB, DSB, MN, CA) analy-
ze different types of DNA damage, which can have
dissimilar sensitivities to metals, these assays should
be used complementary, along with the inclusion
of SCE for biomonitoring exposure to genotoxic
compounds in the natural habitat of different animal
populations.
BIOMARKERS OF BIOCHEMICAL EFFECT
Oxidative damage
:
Under normal physiological
conditions in all aerobic organisms, there is a ba-
lance maintained between endogenous oxidants and
numerous enzymatic and non-enzymatic antioxidant
defenses (Halliwell and Gutteridge 1999). When
an imbalance occurs, oxidants produce extensive
oxidative damage to macromolecules such as DNA,
proteins and lipids, which, in turn, contributes to
aging, cancer, and other degenerative diseases.
Nearly 100 diFFerent oxidative DNA modifcations
have been identifed, ranging From modifed bases to
DNA-breaks in a wide variety of animals and human
cells exposed to chemical agents (Dizdaroglu 1992,
Cadet
et al
. 2002). In all cells, altered DNA is repaired
enzymatically, while misrepaired DNA can result in
mutations leading to genomic instability and cancer
(Kawanishi
et al
. 2001). Although a broad range of
DNA alterations are produced during oxidative da-
mage to DNA, most interest has focused on guanine
oxidation products, among them are, 8-hydroxy-
guanine (8-oxo-G), 8- hydroxyguanosine (8-oxy-
Guo) and 8-hydroxy-2-deoxyguanosine (8-OHdG).
One of the most abundant
lesions is 8-OHdG, which
is formed
in vivo
and can be measured quantitatively
in cells following hydrolysis of the DNA to compo-
nent bases (Valavanidis
et al
. 2009). This lesion is a
major product oF hydroxyl radical attack on DNA and
of maximum biological importance. Also, 8-OHdG
has attracted particular attention because it causes
BIOMARKERS OF METAL EXPOSURE: FROM MOLECULES TO ECOSYSTEMS
123
G-to-T transversions and its presence may lead to
mutagenesis (Hayes 1997, Wong
et al
. 2005, Vala-
vanidis
et al
. 2009). Measurements of 8-OHdG, or
its corresponding nucleoside, after repair processes
results in the excised 8-OHdG adduct being excreted
in urine, and because of its easy collection, these
biomarkers are among the most widely used markers
of oxidative DNA damage (Wong
et al
. 2005). The
8-OHdG level in DNA isolated from tissue is believed
to exemplify the steady state damage of DNA being a
result of damage and repair, while 8-OHdG excreted
in urine is alleged to be an indicator of total DNA
excision repair within an organism. As it is assumed
that DNA repair under normal conditions is almost
complete, 8-OHdG excretion is also a marker of the
rate of total DNA damage (Loft and Poulsen 1999,
Sorensen
et al
. 2003).
Because of its capacity to lose electrons, a metal is
primarily thought to be toxic by virtue of its genera-
tion of ROS. Thus, exposure to high concentrations of
a single heavy metal might result in its accumulation
and potentially, oxidative damage (Limón-Pacheco
and Gonsebatt 2009). Metals such as Fe, Mn, Ni, Cu,
Cr, and V can generate ROS in biological systems
causing oxidative damage in DNA and proteins (De
Flora and Wetterhahn 1989, Gurgueira
et al
. 2002,
Valavanidis
et al
. 2005, 2009, Valko
et al
. 2005).
Specifcally, the induction oF 8-OHdG has been re
-
ported after
in vivo
exposure to As (Rossman 2003),
Cd (Filipic and Hei 2004), Co (II) (Mao
et al
. 1996),
Cr (VI) (Kuo
et al
. 2003), and V (Shi
et al.
1996,
Rodríguez-Mercado
et al.
2003).
DNA repair enzymes:
A general mechanism of
carcinogenicity of As, Cd, Co, and Ni seems to be the
inhibition of DNA repair enzymes and the consequent
enhancement of DNA damage originally caused by
other agents or raised spontaneously (Beyersmann
2002). Even though, the inhibition of DNA repair
processes appears to be a common mechanism of
action of some metal compounds, the steps affected
seem to be rather different. One mechanism of repair
inhibition is the displacement of essential metal ions
such as Zn, Mn, Ni, and Co (Hartwig
et al
. 2002,
Rossman 2003).
Some toxic metal ions have high aFfnities toward
sulfhydryl (SH) groups, as a result, potential targets
are the so called “zinc fnger proteins”. Although
most zinc fnger structures have been described as
DNA-binding motifs in transcription factors, they
have also been identifed in several DNA repair en
-
zymes (Rossman 2003). They include the mammalian
XPA protein, the bacterial Fpg protein and the poly
(ADP-ribose) polymerase.
Specifcally, the ±pg protein is inhibited by Cd,
Cu, and Hg and Ni and Co inhibit DNA binding of
XPA (Asmuss
et al
. 2000). Also, poly (ADP-ribose)
polymerase is inhibited by arsenite in mammalian
cells (Hartwig
et al
. 2002, Schoen
et al
. 2004).
For more comprehensive examples and molecular
mechanisms see Hartwig
et al
. (1997) and Hartwig
(1998, 2001).
These proteins have been used as biomarkers
to analyze response to toxic metals. These fndings
have been observed at low concentrations, in most
cases more than ten-fold below the cytotoxic level.
Thus, under environmental exposure conditions,
repair inhibition may contribute significantly to
metal-induced toxicity and carcinogenicity (Méndez-
Gómez
et al
. 2008). However, environmental ex-
posures analyzing alterations in repair enzymes are
scarce because the diFfculty to link specifc enzyme
alterations exclusively to metal exposure.
Metallothioneins:
For metals, much of the work
in the area of biomarkers has focused on metallothio-
neins or metallothionein-like proteins (MT). These
low-molecular weight, cysteine-rich metal-binding
proteins are reported to play a key role in the bin-
ding and transport of various metals (Costa
et al
.
2008, 2009). The structure of these highly conserved
proteins is linked to their role in the homeostasis of
essential metals such as Zn and Cu and detoxifca
-
tion of toxic elements such as Cd and Hg. MT have
several isoforms, apparently induced by different
metals, the best known of which, MT-I and MT-II,
are greatly induced by Cd and Zn (Viarengo
et al
.
1999, Romero-Isart and Vasak 2002).
MT induction is considered as a biochemical bio-
marker of exposure and of biologically effective dose,
and can be used to point trace metal environmental
exposures (Langston
et al
. 1998, Olsvik
et al
. 2001).
Another possible use of MT as a biomarker, invol-
ves the examination of the intracellular distribution
of metals among cytosolic ligands, including MT.
These types of changes offer several advantages as
biomarkers; since molecular alterations are normally
the frst detectable, it becomes possible to quantiFy
early responses to environmental metal stress. As a
result, some authors have suggested that they may
serve as markers of both exposure and effect (George
and Olsson 1994, Olsvik
et al
. 2001). Hence, their
use in environmental metal monitoring surveys has
been well established (Perceval
et al
. 2004).
There is a considerable amount of literature
concerning MT induction following metal envi-
P. Mussali-Galante
et al.
124
ronmental exposure. Most of the studies have been
conducted in humans and in aquatic animals. Some
representative examples include: MT levels in liver
and kidney of Canadian individuals exposed to
Cd and Zn (Chung
et al.
1986), MT induction in
peripheral lymphocytes from Chinese individuals
exposed to Cd (Lu
et al
. 2005), brown trout (
Salmo
trutta
) exposed to Zn, Cd, Cu (Olsvik
et al
. 2001),
the great tit (
Parus major
), along a metal pollution
gradient (Pb, Cd) (Vanparys
et al
. 2008), and the
fsh (
Solea senegalensis
) exposed to As, Cd, Cr,
Cu, Ni, Pb and Zn (Costa
et al.
2009) and mussels
(
Mytillus
sp.) exposed to V from an oil spill (Amiard
et al.
2008). All these studies conclude that MT are
modulated by heavy metals, being an informative
and specific biomarker of chronic heavy metal
exposure. More examples are reviewed in Petering
and Fowler (1986), Nordberg (1998).
Aminolevulinic acid dehydratase (ALAD):
It is well
known that individuals exposed to lead may develop
anemia, mainly from the interaction of lead with
some enzymatic processes responsible for heme
synthesis, like the inhibition of ALAD. ALAD is the
second enzyme in the heme biosynthetic pathway
which catalyses the condensation of two molecules
of aminolevulinic acid to form one molecule of por-
phobilinogen. Erythrocyte ALAD activity is rapidly
inhibited by lead exposure (Sakai
et al
. 1981). The-
refore, determination of ALAD activity in erythro-
cytes is one of the most useful and well established
biomakers for evaluating lead exposure, because
the activity is extremely sensitive to and specifc
for blood lead concentration. If ALAD is inhibited,
it is a clear indication of the presence of biological
signifcant quantities oF lead, but measurements oF
the activity of ALAD do not provide information
on the presence of any other pollutants (Sakai
et al
.
1996, Sakai and Morita 1996, Sakai 2000). ALAD
activity has been frequently measured in human
adult individuals and children, as well as in animals
after Pb environmental exposures were detected. For
example, ALAD activity was signifcantly lower in
a population of Indian children with the highest lead
blood levels when compared to children with medium
and low lead blood levels (Ahamed
et al
. 2005). Si-
milar results were obtained among urban adolescents
(Ahamed
et al
. 2006) and among adults and elderly
people (Todd
et al
. 1996, Lee
et al
. 2006). In animals,
ALAD activity has been frequently measured in birds
(Johnson
et al
. 1999, Strom
et al
. 2002, Beyer
et al
.
2004, Vanparys
et al.
2008), amphibians (Arrieta
et
al
. 2004) and tortoises (Martinez
et al
. 2010).
BIOMARKERS OF SUSCEPTIBILITY
Given the fundamental role of metabolism in
toxicological research, increasing attention in the
role of genetic variation in toxic responses, and
therefore variations in susceptibility and markers
of such susceptibility, are of great interest (Timbrell
1998). Initial biomarker research into host factors has
been directed at the identifcation oF inter-individual
differences in metabolic pathways. A wide range of
enzymes that may be associated with disease have
been explored, demonstrating substantial differences
in levels of activity within the population, such as N-
acetyltransferase, several cytochromes P-450 (CYP),
and glutathione transferase (GST), among others
(Cullen and Redlich 1995, Timbrell 1998, Pavanello
and ClonFero 2000). Specifcally, trace metals are
reported to regulate the expression of CYP as well as
heavy metals like Hg and Pb (Ki
et al
. 2009). Each of
these enzymes has a potential role in the activation or
detoxifcation oF chemical exposures. As the genetic
loci of these and other metabolic enzymes have been
recognized, the identifcation oF polymorphisms and
phenotypic differences in the population has become
possible. Polymorphisms and/or acquired differences
in enzyme function might be, in part, the cause for
differential responses to metals (Cullen and Redlich
1995). As a consequence, the study and identifca
-
tion of single nucleotide polymorphisms (SNPs),
becomes essential when studying responses to metal
exposures. SNPs are the most abundant forms of
DNA sequence variation in the human genome, and
contribute to phenotypic diversity, in±uencing risk
of certain diseases, and variable response to the en-
vironment (Pavanello and Clonfero 2000).
In the last 20 years, many research groups have
been involved on assessing the genotoxic risk of
exposed populations according to their genetically
determined metabolic characteristics (Timbrell 1998,
Pavanello and Clonfero 2000). Unfortunately, in
humans most susceptibility studies have focused on
infectious diseases or risk factors for cardiovascular
disease or cancer and very little attention has been
devoted to susceptibility to metal toxicity. Among the
Few examples analyzing the in±uence oF SNPs on me
-
tal exposure responses are: Gundacker
et al
. (2007)
analyzing the relationship between polymorphisms
in GST genes in individuals exposed to Hg. Also,
Tekin
et al
. (2012) determined MT polymorphism in
pregnant woman and lead blood levels, concluding
that enzyme polymorphisms are well correlated with
metal concentrations and with individual suscepti-
bility to toxic effects of metals. For detailed review
BIOMARKERS OF METAL EXPOSURE: FROM MOLECULES TO ECOSYSTEMS
125
of MT polimorphisms as biomarkers of individual
susceptibility, see Nordberg (1998).
Studies with inorganic arsenic have contributed
to a great extent to the knowledge of differences in
metal exposure metabolism-responses. Studies con-
cerning the effects of polymorphic forms of arsenic
methyl-transferase (AsMT) in regulating the toxicity
of AsIII in mice (Stýblo
et al
. 2002, Aposhian
et al
.
2004, Wang
et al
. 2008) highlighted the importan-
ce of polymorphisms in the metabolic pathway in
mediating formation of toxic methylated arsenical
metabolites.
In relation to the susceptibility of lead effect on
heme metabolism, several groups have investigated
the relationships between ALAD polymorphism
and susceptibility to lead toxicity (Schwartz
et al
.
1995, Sakai
et al
. 1996, Alexander
et al
. 1998).
These studies concluded that ALAD1 homozygotes
might be more susceptible for disturbance in heme
biosynthesis than ALAD2 carriers, supported by the
fact that ALAD2 protein may bind lead more tightly
than ALAD1 protein.
In general, differences in response to heavy metal-
associated effects based on genetic variability are not
well understood. The only genetic background is far
better known for arsenic, mercury and lead, than for
the rest of the metals (Gundacker
et al
. 2010).
One reason for the scarce literature on suscep-
tibility of metals is the difFculty of measuring it in
isolation; it cannot be separated from other exposures,
and controlled exposures are seldom used in humans
and difFcult to Fnd in natural animal populations.
DEFINITIONS AND TYPES OF
BIOMARKERS:
FROM INDIVIDUALS TO ECOSYSTEMS
Until now, we have observed that the use of
biomarkers at the cellular or sub-cellular levels for
analyzing environmental metal exposure is adequate,
useful and in some cases, well established. For many
years, studies in genetic toxicology and molecular
epidemiology have focused on the effects of acute
exposures to single toxicants at high doses. Therefore,
such biomarkers contribute little to the prediction
of the direct consequences for the population in
question, hence to the community and ecosystem
health. On the contrary, in ecotoxicology threats to
populations and communities rising from chronic
exposures to mixtures of chemical agents at lower
doses (realistic exposures) are the point of interest
(Depledge 1994) (
Table I
). Hence, establishing links
between cellular and sub-cellular effects and their
possible consequences at higher levels of biological
organization becomes essential. This is possible by
the use of biomarkers in each level of biological
organization (
Fig. 1
).
However, incorporation of the biomarker con-
cept in ecotoxicology calls for a redeFnition of
terms. DeFnition of biomarkers for ecotoxicology
should expand the concept to include changes at
the population, community and ecosystem levels,
since chemical agents exert their effects at all levels
of biological organization. Many studies from the
ecotoxicological point of view refer to responses to
toxic effects as “
Ecological indicators
” (Cairns and
McCormick 1992, Hunsaker 1993). In many other
cases, the same responses are regarded as “Biomar-
kers at population and community levels” where
shifts in population and community parameters
due to chemical pollution are included (Fossi 1994,
Depledge and Fossi 1994, Evenden and Depledge
1997, Moore
et al
. 2004, Bernard 2008). At this
point, biomarkers or ecological indicators should
give additional information that cannot be obtained
from chemical analysis of pollutant concentrations
alone, and they may integrate effects of mixtures
of chemicals over long exposure periods (Handy
et al
. 2003).
TABLE I.
DIFFERENCES BETWEEN BIOMARKER RESEARCH APPROACHES FOR ASSESSING ENVIRON-
MENTAL METAL POLLUTION
Molecules to individuals
Individuals to ecosystems
Usually single compounds
Complex mixtures
High doses, acute exposures
Low doses, chronic exposures
Animal models or occupationally exposed populations
Sentinel species, natural populations
Biomarkers at lower levels of biological organization
Biomarkers at higher levels of biological organization,
considering responses at lower levels
Usually non-neutral markers
Usually neutral markers
Concerned with individual and population susceptibility
Concerned with population and ecosystem health
Mechanistic importance
Ecological importance
Time scale decreases
Time scale increases
P. Mussali-Galante
et al.
126
Peakall (1994) suggested that when integrating
biomarkers to ecotoxicology, three assumptions must
be taken into account, since responses to chemical
stress from the molecular to the ecosystem level is a
continuum of events.
First, the timescale increases, moving from se-
conds or minutes to years or even decades. Second,
the ecological importance increases. Third, it beco-
mes difFcult to relate effects to causes as one move
up to this continuum (because speciFc biomarkers
for a given chemical agent are more difFcult to
Fnd). In our opinion, another assumption needs
to be taken into account: Mechanistic information
about the modes of action of chemical agents is
inferred in the lowest levels from this continuum
(
Table I
,
Fig. 2
). Additionally, biomarkers should
be chosen so that they re±ect changes in the Ftness
of the population (premature death, ability to mate,
fecundity, viability of offspring, etc.) (Evenden and
Depledge 1997).
Population level biomarkers
Large phenotypic shifts can evolve in populations
over a short period of time. For example, large and
rapid evolutionary changes (microevolution) are
evident from population responses to pollutants
Environmentalmetal exposure
Metal
concentration
in biological
samples
Biomarkers of
exposure
-DNA adducts
-Oxidative
damage
-Metallothionein
induction
Cellularand
molecular
effects
Biomarkers of
effect
-DNA breaks
-MN, CA
-Alterations in
DNA repair
enzymes
Individual
effects
Biomarkers of
suceptibility
-SNP s
-Metabolism
enzyme induction
-Different DNA
repair capacity
-Riskofdisease
-Cancer
-Aging
-Chronic diseases
-Decreased
longevity
-Decreased
fertilityand
fecundity
Population
effects
Ecological indicators
“Permanent
biomarkers”
-Sex proportion
alterations
-Age structure
alterations
-Low reproductive
succes
-Inbreeding
-Genetic diversity
alterations
-Low fitness
-Population
declines
Community
effects
Evolutionary
effects
-Shiftsin diversity
andspecies
richness
-Changein
dominant species
-Changein species
composition
Biodiversity loss
Ecosystem
effects
Evolutionary
effects
-Alterations in
energy and
nutrient cycles
-Foodweb
alterations
Earlywarning to individual health
Earlywarning from populationtoecosystem health
Fig. 1.
Environmental pollutants –such as metals– can exert their effects at all levels of biological
organization. Most used biomarkers for assessing toxic responses are listed in each level.
MN= micronuclei, CA= chromosome aberrations, SNPs= single nucleotide polymorphisms.
Fig. 2.
Assumptions that need to be taken into account when using
biomarkers to infer environmental pollution effects at different
levels of biological organization. Arrows represent directionality
at each level of biological organization for each assumption.
-
Biomarker specificity
decreases
-
More difficult to assess
causes-effect
relationships
-
Increasing ecological
relevance
-
Time scale increases
Ecosystem
Community
Population
Individual
Cellular
Molecular
BIOLOGICAL ORGANIZATION
LEVEL
-
Biomarker specificity
increases
-
Easier to assess
causes-effect
relationships
-
Mechanistic relevance
increases
-
Time scale decreases
BIOMARKERS OF METAL EXPOSURE: FROM MOLECULES TO ECOSYSTEMS
127
and chemical stress (Luoma 1977). Underlying
these microevolutionary changes are shifts in allele
frequencies at loci. These changes have long been
considered as having potential for monitoring envi-
ronmental stress.
This process was defned by Medina
et al
. (2007)
as “Microevolution due to pollution”, it occurs ra-
pidly, in years or after few generations instead of
centuries or millennia, involving a variety of phy-
siological, morphological and life-history traits. This
fact makes possible to use microevolutionary changes
as biomarkers for assessing effects of chemical po-
llution at the population level (Hoffman and Dabron
2007, Mussali-Galante
et al
. 2012).
Among studies that deal with metal stress popu-
lations, the most used approach is to address changes
in genetic diversity
and allele frequency patterns by
using neutral molecular biomarkers (Bickham
et al.
2000). A neutral biomarker is a sequence of DNA that
is polymorphic within a population or a species and
that is not under selection. They play an important
role in estimating the genetic diversity among indivi-
duals by comparing the genotypes at a number of po-
lymorphic loci (Arif and Khan 2009). These markers
inform about population demographic processes and
have the potential to measure shifts in population size
arising from environmental change and adaptation
(Bickham and Smolen 1994, Harper-Arabie
et al
.
2004). This fact has led to the hypothesis that neutral
markers could be used to monitor pollution effects
in populations (Medina
et al
. 2007).
A number of neutral biomarkers which include nu-
clear and mitochondrial DNA (mtDNA) analyses, such
as allozymes, RFLPs (Restriction Fragment Length
Polymorphism), SSRs (Simple Sequence Repeats or
microsatellite markers), RAPDs (Random Amplifed
Polymorphic DNA), DNA sequencing of mtDNA, and
AFLPs (Amplifed Fragment Length Polymorphism)
are available with application to genetic ecotoxicolo-
gical research. However, in the last decade the most
used biomarkers to assess genetic diversity in animal
populations exposed to metal pollution are: Allozymes,
SSR’s and mtDNA-sequencing.
Allozyme analysis
: This is one of the oldest tech-
niques to assess genetic variability in natural popu-
lations. This method analyzes electrophoretic shifts
in the charge characteristics of enzymatic proteins
produced by amino-acid substitutions. The majority
of allozymes show co-dominant inheritance, and the
variants are attributed to nucleotide substitutions
causing charged amino-acid replacement. This te-
chnique detects one-third of amino acid substitution.
However, the generally low level of polymorphism
at allozyme loci often limits their resolving power
in detecting population differences (Diamond
et al
.
1989). Despite their limited resolution, allozyme
analysis remains the simplest and most rapid tech-
nique for surveying genetic diversity in single copy
nuclear genes (Bickham
et al
. 2000). For example,
Maes
et al
. (2005) used allozymes and SSRs to
analyze allele and genotypic frequencies, levels of
polymorphisms and heterozygosity in the European
eel (
Anguilla anguilla
) exposed to a mixture of metals
(Hg, Cd, Pb, Ni, Cr, As, Se, Cu, Zn). They reported
a negative correlation between the level of bioaccu-
mulation and allozymatic multi-locus heterozygosity.
Hence, an individual’s enzymatic heterozygosity
seems to play an important role in the potential to
counteract pollutant bioaccumulation. Also, Benton
et al
. (2000) observed decreased heterozygosity in
the snail (
Pleurocera canaliculatum
) exposed to Hg
using allozymes as biomarkers, reinforcing the use of
allozyme analysis as a marker of contamination and
possible selection for pollution resistance.
Microsatellites
(SSRs):
Broadly used for genetic
structure and variability analyses, these are short
tandem repeats of mono-to tetra-nucleotide repeats
which are assumed to be randomly distributed
through out the nuclear and mitochondrial genomes.
SSRs detects length variation that results from chan-
ges in the number of repeat units and their mode of
inheritance is co-dominant. Mutations in SSRs are
high compared to other DNA markers,
therefore, they
are considered one of the best molecular markers
(Yauk and Quinn 1996, Athrey
et al
. 2007, Tremblay
et al
. 2008) to analyze genetic variability within
and between populations. Unfortunately, the identi-
fcation o± SSRs is expensive and requires cloning
and sequencing, whilst SSRs primer pairs appear to
be species-specifc, cross species amplifcation has
been revealed although reduced variability has been
observed.
A study conducted by Athrey
et al
. (2007) in
which selection ±or Cd resistance in the least killifsh
(
Heterandria formosa
) led to increased levels of
resistance, but also a decrease in genetic variation
as measured by microsatellites. Also, Bourret
et al
.
(2008) using SSRs showed that chronic exposure to
metal contamination (Cd, Cu) have impacted genetic
diversity among populations of the wild yellow perch
(
Perca favescens
), which may affect the capacity of
populations to respond to environmental changes.
Similar results were obtained by Ungherese
et al
.
(2010) who observed decreased genetic diversity in
P. Mussali-Galante
et al.
128
Hg exposed populations of the sandhopper (
Talitrus
saltator
), and by Mussali-Galante
et al.
(2012) in the
small mammal (
Peromyscus melanophrys
) exposed
to a metal mixture (Pb, As, Cd, Cu, Al).
Mitochondrial DNA analyses:
One of the most
powerful tools of modern molecular population
genetics is nucleotide sequence analysis of mtDNA
(Bickham
et al
. 2000). The mitochondrial-protein-
coding regions are regarded as powerful markers for
genetic diversity analysis. One of the most studied
mitochondrial genes in genetic diversity analyses is
the cytochrome b, the NADH dehydrogenase and mt-
cytochrome oxidase I. Also, the highly polymorphic
non-coding region of the mtDNA, termed the control
region, has been used in genetic diversity analyses
due to its role in replication and transcription of mt-
DNA. Advantages of the sequence approach include
the ability to target different mitochondrial genes,
thus, selecting for targets with an appropriate evolu-
tionary rate as well as the higher resolution obtained
by revealing the nucleotide sequence. Moreover, and
advantage of the PCR-RFLP analysis of the mt-DNA
is that homo and heterozygosity values and allele/ge-
notype frequencies can be determined for the genetic
loci analyzed (D’Surney
et al
. 2001, Arif and Kahn
2009). Some illustrative examples include: Matson
et
al
. (2006) using mtDNA-sequencing, observed that
genetic diversity decreased signifcantly in exposed
populations (Hg) of the marsh frog (
Rana ridibunda
).
The authors concluded that environmental degrada-
tion due to Hg contamination is the most likely cause
of the regional reductions of genetic diversity. On the
contrary, Eeva
et al
. (2006) using the same biomarker
observed increased nucleotide diversity in popula-
tions oF the Pied ±ycatcher (
Parus major)
in polluted
sites (Cd, Zn, Cu, Pb, Ni, Al, As, Cr) suggesting high
mutation rates. These results are in accordance to
various feld studies which have demonstrated that
mutations accumulate more rapidly in more polluted
environments (Yauk and Quinn 1996, Clements 2000,
Peles
et al
. 2003, Gardestrom
et al
. 2008).
The majority oF studies assessing population
genetic responses have observed that populations in-
habiting more contaminated environments by heavy
metals, hold fairly less genetic diversity, as well as,
population differentiation, low reproductive success,
reduction oF the adaptive potential and lower ftness.
Also, these responses have been associated with high
levels of DNA damage (Blaise
et al.
2003, Farag
et
al.
2003). Therefore, a potential association between
metal contamination and changes in population ge-
netic structure has been suggested.
Finally, the aforementioned studies clearly illus-
trate that the concept of biomarkers is successful and
deserves a place within the theoretical framework
of modern ecotoxicology. Bickham
et al
. (2000)
suggested that “because population genetic changes
are expected to be independent of the mechanisms of
toxicity, and sensitive indicators of transgenerational
effects, they represent the ultimate biomarker of
effect”. Because genetic changes, especially the loss
of genetic variability, might be permanent (depending
on the population size and mutation rates), once va-
riability is lost the population cannot recover to what
it was prior to the environmental impact. Also, there
is strong evidence suggesting that genetic population
diversity may be a useful biomarker of the health of
the ecosystem.
Community level biomarkers
At the community level, changes in composi-
tion, richness and species diversity may occur as a
consequence of exposure to heavily polluted sites,
such as superfund sites, where high levels of heavy
metals are found. Due to species interactions, such
effects cannot be accurately predicted from effects
at the population level, as was recognized by Forbes
and Forbes (1993), Hopkin (1993), Smith and Cairns
(1993), and Lagadic
et al
.
(1994).
Studies assessing community level responses to
environmental metal stress are mostly conducted
in aquatic ecosystems using invertebrate and fsh
communities. Among the few studies conducted in te-
rrestrial ecosystems, insect communities are the unit
of analysis. For example, Theodorakis
et al
. (2000)
analyzed the relationship between biomarkers of
eFFect and changes in fsh community structure (diver
-
sity and percent pollution-tolerant species) exposed
to Hg in sediments. They showed a reduction in spe-
cies diversity at the most contaminated sites, which
tended to increase with increasing distance from the
pollution source. They concluded that biomarkers
of effect are related to community level responses.
Also, Clark and Clements (2006) conducted feld and
stream microcosm experiments to assess community-
level responses (composition, species richness) of
macro-invertebrates exposed to heavy metals. They
established concentration-response relationships
between heavy metals and species richness. Similar
results were obtained by Pollard and Yuan (2006)
with benthic invertebrate communities along a metal
pollution gradient. Moreover,
Lefcort
et al.
(2010)
found that even after a period of 70 years, heavy
metals from mining wastes may still be impacting
insect abundance and community structure. Speci-
BIOMARKERS OF METAL EXPOSURE: FROM MOLECULES TO ECOSYSTEMS
129
fcally, they Found that increased Cd and Zn levels
were associated with decreased community diversity.
Ecosystem level biomarkers
At this point, it becomes more diFfcult to relate
ecosystem effects exclusively to metal exposure.
Therefore, various authors have recommended more
rigorous experimental designs coupled with multidis-
ciplinary research, in order to overcome this problem
(Medina
et al
. 2007, Hoffmann and Willi 2008). In
spite of this, there are concepts that help to unders-
tand ecosystems under chemical stress. Here, some
of these concepts are addressed.
Risks to the ecosystem and its components are
expected to increase as the amount of pollutant
entering the system increases, especially when the
ecosystem is polluted by heavy metals, because of
their bioaccumulation properties and persistence for
long periods of time (Hoffmann and Willi 2008).
After the ecosystem health is compromised due to
heavy metal pollution, there will be a degree of self-
compensation in each ecosystem which will tend to
preserve its dynamics somewhat. This is known as
ecosystem “resistance” (Moriarty 1999), which is
analogous to the compensatory responses exhibited
by individual organisms exposed to pollutants (Bel-
fore and Anderson 1998). A resistant ecosystem may
show little change in its dynamics if, for instance, loss
of one or more species from the ecosystem following
pollutant exposure is associated with replacement by
alternative species that serve the same role. However,
if key species are lost or mostly impaired, such that
ecosystem structure and/or function are affected, then
the ensuing ecosystem change shows that ecosystem
resistance has been overcome (Moriarty 1999). In-
terestingly, the replacement of sensitive species by
more tolerant species without signifcant changes in
ecosystem structure and function could in itself be
interpreted as an “early warning” of a pollutant im-
pact if loss of the species can be directly attributed to
exposure to a particular chemical. If biomarkers were
to be used to measure toxicity in a sentinel species,
population decline might well be detected at an even
earlier stage. This illustrates an important principle,
namely that monitoring changes in populations of
sentinel species might provide a valuable insight
into the status of the whole ecosystem (Depledge
and Fossi 1994).
Many studies have examined the prevalence and
distribution of trace and heavy metals in terrestrial
food webs (Hunter and Johnson 1982, Beyer
et al
.
1985, Hunter
et al
. 1987). Patterns of uptake and
bioaccumulation have been investigated by studying
relationships between metal concentrations in soils
and plants and in soils and tissues of co-occurring
animals (Sharma and Shupe 1977, Otte
et al
. 1990,
Shore 1995). These patterns can reveal general trends
of exposure, uptake, translocation, and assimilation
of metals within organisms. Trophic transfer of
metals within the food web may be demonstrated
by relating metal levels in dietary components with
those assimilated by an animal (Torres and Jhonson
2001). Finally, bioaccumulation of metals in orga-
nisms should be included when analyzing ecosystem
effects, since some metal effects may only be recog-
nized in a later phase of life, are multi-generation
effects or manifest only in higher members of a
food-web. Hence, bioaccumulation of chemicals in
biota may be a prerequisite for adverse effects on
ecosystems (Van der Oost
et al
. 2003).
IN SEARCH FOR NEW BIOMARKERS OF
EXPOSURE TO METAL POLLUTION:
THE “OMIC” APPROACH
The feld oF toxicology has recently begun the
process of reinventing itself in view of the rapid
technological and conceptual change in molecular
biology and genomics. The “omic” approach com-
prises technologies such as genomics, proteomics,
metabolomics, transcriptomics, etc. These new
‘‘omics’’ disciplines apply high-throughput methodo-
logies which changes in expression of hundreds to
thousands of genes (genomics), proteins (proteomics)
and metabolites (metabolomics) thatare assessed si-
multaneously (Snape
et al
. 2004). The combination
of high-throughput methodologies such as microarray
technology and toxicology led to the development of
a new scientifc discipline, “toxicogenomics” which
is the fusion of toxicology, molecular biology, and
bioinformatics (Nuwaysir
et al
. 1999). In particular,
toxicogenomics oFFers not just the possibility oF de
-
termining which molecular pathways are perturbed
by toxic compounds, but also a way of exploiting this
information, either for the development of new tests
or for the development of new biomarkers (Tugwood
et al
. 2003).
The grand goal of toxicology in the post-genome
era is to characterize the entire set of genes and proteins
that are affected when humans are exposed to environ-
mental xenobiotics. As a consequence, environmental
health scientists can conduct large-scale studies of the
effects of toxicants on gene expression at the mRNA
and protein levels, while simultaneously monitoring
metabolite profles to gain insight into the activity
P. Mussali-Galante
et al.
130
state of all relevant genes and gene-products. A direct
comparison of expression values obtained for a control
versus an altered condition reveals a set of biomarkers
indicative of that altered state. This exposure ‘‘signatu-
re’’ can then be used as a tool for classifying chemical
exposures and predicting mode of action (Hamadeh
et
al
. 2002, Olden 2006). Specifcally For metal exposure
assessment, very recently, “metallomics” has emerged
as a new sub-discipline of toxicogenomics, which
investigates the interrelationships of metal-induced
proteome and metabolome changes. In this regard,
searches for genes encoding metal-responsive proteins
could be interesting targets for reporter genes fusions
in biomarker establishing (Haferburg and Kothe 2010).
Furthermore, the integration of the “omic” approach
with ecotoxicology, led to the term “ecotoxicogeno-
mics” which includes gene-protein level responses that
directly affect population and community dynamics
via developmental or reproductive perturbations (Sna-
pe
et al
. 2004). Effort towards linking these molecular
signatures with alterations in the genetic pool of the
affected populations is envisaged. Only then, we will
be able to say that “omic” technologies not only help
to provide novel biomarkers but also a close look to
the continuum of toxic responses from molecules to
ecosystems. However, traditional biomarkers targeted
for these affected systems should be used to validate
the toxic mechanisms of the contaminant. Additio-
nally, one must consider that an expression profle
is merely a “snapshot” of a highly dynamic system,
and temporal changes in gene and protein expression
should be anticipated.
To date, most of the work using DNA microarrays
have focused on genetically well characterized orga-
nisms, including
Saccharomyces cerevisiae
,
Drosophi-
la melanogaster
,
Caenorhabditis elegans
,
Mus muscu-
lus
, and
Homo sapiens
. However, a major obstacle to
the application of microarrays in ecotoxicology, is the
lack of genomic or cDNA sequence data for sentinel
species and non-model organisms (Snape
et al
. 2004,
Mehinto
et al
. 2012). In spite of this, gene expression
arrays are being developed for a number of non-model
organisms; in a variety oF fsh species (Gracey
et al
.
2001, Jeffries
et al
. 2012), frogs (Altmann
et al
. 2001,
Blackshear
et al
. 2001) and birds (Morgan
et al
. 2001,
Neiman
et al
. 2001).
One of the best examples when trying to search
for new biomarkers of exposure to environmental
pollution, was the study conducted by Venier
et al.
(2006) who uncovered over 40 novel biomarkers
whose expression levels were regulated similarly in
the laboratory and feld exposures. Other examples
that have illustrated the usefulness of these tech-
nologies and have discovered new biomarkers for
environmental metal exposures are Wang and Fowler
(2008), Ki
et al
. (2009), and Menzel
et al.
(2009).
One oF the major disadvantages oF gene ex
-
pression microarrays, is that the analysis of data
is complex. There has been some consensus about
analysis approaches (Allison
et al
. 2006) but lack of
standardization in approaches has introduced diFf
-
culties when comparing results between laboratories
(Quackenbush 2006).
In spite of these limitations, these novel techno-
logies offer added value compared with classical
testing with whole organisms because they provide
information concerning the molecular basis of ex-
posure and act as “early warning” signs, enabling
a more robust risk assessment than has ever been
achieved previously. These new methods might
also help to provide data that could reduce much
of the uncertainty in extrapolating from laboratory
animals to human exposures. Moreover from an
ecotoxicological perspective, it is expected that
these new methods will provide a better understan-
ding on the application of uncertainty factors that
are used to extrapolate data From laboratory to feld
and from sentinel species to the whole-ecosystem
level. More studies are needed to Further defne the
potential applications and limitations of genomics
in biomarker research.
CONCLUSIONS AND FINAL REMARKS
From the examples given in these review, it is
clear that environmental metal exposure can elicit a
plethora of biological effects, ranging from altera-
tions in molecules, compromising individual health
and putting ecosystem integrity at risk. Therefore,
in each level of biological organization a set of
biomarkers can be measured in order to integrate
an holistic perspective of complex environmental
exposures. Biomarkers at the cellular or sub-cellular
levels are adequate, useful and in some cases, well
established. However, the use of biomarkers beyond
the individual level has not always allowed for cause-
effect relationships, since more confounding factors
are present, Few specifc biomarkers are available
and oFten measuring biological responses in feld
situations becomes diFfcult.
A major limitation oF biomarker use is that a
variety oF responses have been identifed in exposed
organisms, making diFfcult to link environmental
exposure to specifc chemical entities and subse
-
quent biological effects. In this case, the use of a
BIOMARKERS OF METAL EXPOSURE: FROM MOLECULES TO ECOSYSTEMS
131
multi-biomarker approach, in a range of species
using sentinel organisms, becomes necessary to re-
solve or at least have a closer insight into complex
environmental problems. Also, there is a recognized
need for biomarker research to move toward a more
holistic approach, a proposal that is in harmony with
the power of genomics as a tool for understanding
toxicant impacts in a diversity of species.
Overall, approaches that integrate responses
across levels of organization are especially valuable
because they help to understand the mechanistic
linkages between the biomarkers responses and the
ecologically relevant responses. Therefore, choosing
the appropriate biomarker must be based on the bio-
logical level of organization in question.
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