Physiological stress indicators such as some hematological and blood parameters
could be useful to evaluate the effects of contaminants such as heavy metals
in fish but the application of these findings to preparation of environmental
diagnoses will need a more detailed investigation and must be validated in situ
before establishing them as biomarkers (Ribeiro et al.,
The finding of suitable biomarkers for the best possible diagnoses is very
critical for ecotoxicological studies. Blood indices are considered pathophysiological
parameters of the whole body and therefore are important in diagnosing the structural
and functional status of fish exposed to xenobiotics (Adhikari
et al., 2004).
Although fish blood indices have been increasingly examined in ecosystem monitoring
programs as valuable parameters of physiological changes in the presence of
xenobiotics, the lack of basic knowledge about the blood response to stressors
mainly from tropical species is the most important leakage to using these indices
in environmental monitoring programs (Affonso et al.,
Physiological changes induced by xenobiotics are also apparent at the biochemical
and physiological level, such as in the carbohydrate and protein metabolism
and in hematology. In cases where these alternations are adaptive they are referred
to as stress responses, while they are considered effects when they have a negative
cause on the physiological condition or even survival of the fish (Barton
and Iwama, 1991).
Hematotoxins change quantitative and qualitative characteristics of blood cells to produce toxic symptoms. Hematotoxicity happen when some of these different blood components are present or structural anomalies occurring in blood components interfere with normal functioning.
Several biochemical and physiological responses occur when a fish exposed to
the xenobiotics, if fish can not tolerate and acclimatized it may lead to toxicity
(Begun, 2004). Fish blood is sensitive to pollution-induced
stress and changes in the hematological and metabolic parameters can be used
as toxicity indices of xenobiotics (Sancho et al.,
Glucose is a carbohydrate that has a major role in the bioenergetics of animals,
being transformed to chemical energy (ATP) which in turn can be expressed as
mechanical energy (Lucas, 1996). Levels of glucose were
measured as conventional stress markers to assess the reliability of stress
response triggered under our test condition.
Most biochemical defenses respond to cellular injury by increasing levels of
defenses through self-regulating signal transduction mechanisms. These defenses
are usually proteins that serve numerous cellular functions (Safahieh
et al., 2010). Thus, measuring these systems may provide early warning
of danger to the cell as well as help elucidate potential mechanisms of cellular
To date, little is known about the blood parameters of stressed fish. In current
study blood biomarkers were measured in order to investigate patterns of response
and to quantify the extent of alterations caused by the mercury pollution, so
in this study, a multi factorial approach, involving determination of bloods
parameters along with serum metabolites during the environmental exposure of
mercury pollution was used. The information gained from this study may be useful
for future strategies in monitoring and predicting the effects of mercury exposure
and also in developing indices to measure stress during sea bream culture.
MATERIALS AND METHODS
Environmental test: In natural condition, at first with mercury analysis of water and sediment (method details in bellow) of 26 creeks in Mahshahr region (northwest of Persian Gulf) (Fig. 1) we choose four more pollutant (Jafari, Ghazaleh, Majidieh and Petroshimi) and one less pollutant creeks (Zangi).
For every creek we choose three station and in every station one water and sediment sample collected, also two yellowfin sea bream with the same size (200 g) and same sex (all immature male) were caught.
Mercury analysis: In laboratory water samples were filtered with Millipore
strainer mesh size 0.45 μm, the filtrate was then acidified with 2 mg L-1
of 20% K2Cr2O7 (w/v) prepared at nitric acid
(American Public Health Association, 2005) and soluble
store at -4°C until mercury analyses.
For stabilization of weight, the sediments were freeze-dried (Shi
et al., 2005), then were sieved through 63 μ mesh and were allowed
to settle, the supernatant water decanted and homogenized, finely powdered sediment
subsamples were dissolved in 60 mL container 4 mL of concentrated nitric acid
and 2 mL of concentrated sulfuric acid. The mixture was digested at 90°C
for l-2 h in hot plate. Upon cooling, 1 mL K2Cr2O7
or 0.5 mL BrCl was added. The solution was filtered using Whatman No.
1 filter paper and diluted to 50 mL with deionized water (Moopam,
1999) and preserved prior to Hg analysis.
Mercury concentrations were determined by the Department of Marine Chemistry
Laboratory, Khorramshahr University of Marine Science and Technology using a
standard cold vapor atomic absorption (CV-AAS) method (Unicam 919) equipped
with Hg cold vapor generator (VGA 77) (EPA, 1992).
|| Environmental test area
Blood sampling: To obtain blood samples, fish were quickly taken out
from the water and held firmly on a bench with a cloth covering the head and
blood was withdrawn from caudal vessels (Savari et al.,
2010) were for hematology and leukocyte analysis and the second were centrifuged
to obtain serum. The serums were separated into aliquots and were frozen and
stored at -80°C until metabolite analyses.
Hematological analysis: Numbers of Blood leukocytes (Lk count 104 cells
mL-1) was performed by diluting heparinized blood with Giemsa stain
at 1:30 dilution and cells were counted using a hemocytometer Neubauer under
the light microscope (Stevens, 1997).
The leukocyte differential count was made in peripheral blood smears stained
by Merck Giemsa (Beutler et al., 2001), giving
the Neutrophils value of differential neutrophils (100 leukocytes count) and
the Mononuclear value of differential lymphocytes plus monocyte and eosinophile
(100 leukocytes count).
Blood centrifuged in a microhematocrit centrifuge (Hettich, Germany) then measuring
the packed cell volume (Beutler et al., 2001).
Hematocrit readings were performed with the aid of a microhematocrit reader.
Hemoglobin levels (Hb mg L-1) were determined colorimetrically by
measuring the formation of cyanomethemoglobin according to Lee
et al. (1998).
MCHC Mean cell hemoglobin concentration; relative quantity of Hb per erythrocyte;
measured directly from the optical properties of the cell, or derived as MCHC
(mg L-1) = Hb (mg dL-1)/Ht (ratio) (Evans,
Metabolite analyses: Serum glucose was measured photometrically according
to a method modified from Banauch et al. (1975)
based on the quantification of NADH after a glucose oxidation catalyzed by glucose
dehydrogenase. The quantity of NADH formed is proportional to the glucose concentration.
Serum total protein levels were determined using Pars Azmoon, Iran (1 500 028)
kit, with bovine serum albumin serving as standard by the method of Lowry at
546 nm and 37°C (Hedayati et al., 2010).
Statistical procedures: For each biomarker, the data were tested for
normality and homogeneity. One-way analysis of variance ANOVA with Duncan Post
Hoc was used to determine significant differences to evaluate the effect of
mercury on parameters. To investigate associations between bioaccumulation and
its effects, Pearson correlation coefficients (r) were calculated between mercury
concentrations and blood parameters. The differences between means were analyzed
at the 5% probability level. Data are reported as mseans±standard deviation
The software SPSS, version 11.5 (SPSS, Richmond, Virginia, USA) was used as
described by Dytham (1999).
Mercury: In different creeks significant differences were found between the sampling stations. The range of mercury concentrations found in the creeks water and specially sediments along the Mahshahr coast was high. From the stations it was possible to observe a gradient of metal contamination. Station Zangi had lower levels of mercury contamination in all measurements and choose as clean station. Other Stations had higher levels of mercury contamination in allmeasurements and were choosed as infected station. Stations Majidieh and Petroshimi were noticeably close to an area of industrial activities (oil and petrochemistry, respectively) and higher amount were predictable.
The analytical data were normalized to the distance from the creeks with water and sediment mercury (Fig. 2). Concentrations of both water and sediment mercury were strongly higher in infected creeks than the clean one, however this increase in water mercury was realizable. In general, the highest concentrations of mercury for water and sediment had same progress. These observations strongly suggest that anthropogenic activities can significantly increased mercury levels in the water and sediment even in closed creek. These differences denote a contamination gradient according to the distance to the point source of mercury into the system, Petroshimi and Majidieh being the closest and Zangi and Jafari the furthest creeks to the anthropogenic activities near the Mahshahr coast.
Hematological and immunological analysis: All indices exhibited high
significant analysis of variance (p<0.05) except differential eosinophils
(Table 1). Environmental result declared significance increase
of differential monocyte and neutrophil within higher considerable values than
those of the control group, beside significance decrease of Hb, Ht, leukocyte
count, differential lymphocyte, eosinophyle and MCHC (p>0.05) with lower
considerable values than those of the control group.
||Environmental concentration of mercury chloride (μg L-1)
in the water and sediment of different creeks in Mahshahr coast with different
source of pollutant (box plots contain mean and standard deviation)
|| Environmental hematological and immunological activities
of yellowfin seabream exposed to water mercury
|Different alphabets with all the values within same row indicates
significant difference at p>0.05
|| Environmental correlation of hematological and immunological
activities of yellowfin seabream with water mercury
|*Correlation is significant at the 0.05 level, ** Correlation
is significant at the 0.01 level
Correlation coefficients between water mercury concentrations and hematological and immunological indices were significant in Hb, Ht, Monocyte, Neutrophil and Eosinophils (p<0.05), that among significant parameters Monocyte, Neutrophil, Eosinophils were positive and Hb, Ht correlation were negative in correlate with water mercury and among insignificant indices only Monocyte had positive and other indices had negative correlation (Table 2).
Result of sediment correlation show only Leukocyte had significant negative correlate whereas within insignificant parameter Hb, MCHC, Monocyte and Eosinophils had positive correlation with sediment mercury and Ht, Lymphocyte and Neutrophil had negative correlation (Table 3).
||Metabolites response (Glucose and Total protein) of the yellowfin
seabream during environmental exposed to different concentration of mercury
chloride (box plots contain mean and standard deviation for glucose, beside
line chart for total protein)
|| Environmental correlation of hematological and immunological
activities of yellowfin seabream with sediment mercury
|*Correlation is significant at the 0.05 level
|| Environmental correlation of metabolites activities of yellowfin
seabream with water mercury
|*Correlation is significant at the 0.05 level
|| Environmental correlation of metabolites activities of yellowfin
seabream with sediment mercury
|*Correlation is significant at the 0.05 level
Biochemical analysis: Values recorded for activity of total protein show significant depletion in infected creeks with respect to clean creek. Glucose was significantly increased in infected creeks with respect to clean creek (Fig. 3).
Correlation coefficients between water mercury concentrations and biochemical indices wasnt significant (p<0.05), however both correlation were negative in correlate with water mercury (Table 4). Result of sediment correlation show only glucose had significant positive correlate whereas glucose parameter had negative correlation with sediment mercury (Table 5).
The range of mercury concentrations founded in the creeks water and specially sediments along the Mahshahr coast was higher than other marine environment, so it reveals that is an area requiring a special concern in order to avoid future environmental problems.
Correlation results and analytical results show that there werent high correlation between surrounded mercury and candidate indices and all indices show admissible correlate in total condition. So eventually it was declared that between hematological indices MCHC gain suitable qualification to become a suitable biomarker and between immunological indices leukocyte count, neutrophil and lymphocyte can consider as suitable and effective biomarker of mercury pollution in yellowfin seabream. Also between metabolite indices we can introduce Total protein as suitable and effective biomarker of mercury pollution.
The most common hematology findings in toxicology studies are mild decreases
in RBC count, hemoglobin concentration and hematocrit. Although specific mechanisms
for the erythrocyte effects are typically not identified, there appears to be
a generalized reduction of anabolic processes, including erythropoiesis. Decreased
physical activity and correspondingly decreased tissue oxygen demand can also
contribute to reduced erythropoiesis (Gad, 2007). For
example, Palackova et al. (1994) found an elevation
in both parameters after exposure to Cadmium. Therefore, the effects of heavy
metal on these two blood parameters appear variable and dependent on the exposure
scenario and acclimatization conditions of the fish (Smet
and Blust, 2001).
In anemic animals, decreases in RBC count and hematocrit that approximate the
proportionate decrease in hemoglobin are typically observed. Decreases in red
cell parameters may be caused by hemorrhage, hemolysis, or decreased kidny production.
Hyperbilirubinemia, hemogolbinemia and hemoglobinuria (the latter two with intravascular
hemolysis only) may be associated with hemolytic anemia but not with anemia
of decreased production or blood loss (Haschek et al.,
The most common cause of relative polycythemia, increased RBC count, is simple
dehydration which causes systemic hypoxia and trigger erythropoietin production.
A similar mechanism occurs with systemic alkalosis. By increasing the affinity
of hemoglobin for oxygen, alkalosis causes the renal tissue sensors to detect
hypoxia, triggering erythropoietin production (Gad, 2007).
Some toxicants (e.g., heavy metals) can cause RBCs to be released from the
kidny. Proportionate increases in red cell numbers, hemoglobin, or hematocrit
generally reflect hemoconcentration and dehydration (Haschek
et al., 2009).
An intracellular Mean Cell Hemoglobin Concentration (MCHC) of approximately
0.34 mg L-1 appears to be an important factor that limits cell divisions
and this MCHC value of approximately 0.34 mg L-1 is found across
all of the healthy adult common laboratory animals, whereas other erythrocytic
parameters differ more between species (Evans, 2008).
Ribeiro et al. (2006) find no significant effects
in MCHC for all tested metals in fish Hoplias malabaricus. This parameter reflect
increased production and release of reticulocytes that are larger in size and
have decreased hemoglobin content compared to mature RBCs (Haschek
et al., 2009). The chemicals that stimulate blood cell/hemoglobin
production, generally induce a hypoxic condition in fish that stimulated the
spleen which produces the blood cells in fish (Fange, 1992),
to contract and release stored erythrocytes into the circulation.
Increased significantly the values of hematocrit after subchronic exposure,
indicating the importance of the route of contamination. Results observed accord
with those of Chowdhury et al. (2004), who noted
an increase of blood hematocrit and hemoglobin during environmental hypoxia
and chronic to waterborne metals to increase blood oxygen carrying capacity
when impairment of gas exchange occurs.
Although environmental conditions such as suboptimal temperatures or nutritional
state could be responsible for the suppression of immune responses (Mattsson
et al., 2001) and for the high blood hematocrit and high hemoglobin
values in fish (Cole et al., 2001), many authors
have recently described the use of hematological endpoints as reasonable biomarkers
of fish health (Affonso et al., 2002; Cole
et al., 2001).
The cell population numbers may be increased and termed cytosis or philia;
reductions of cell numbers are termed penia. Our result show decreased
in lymphocyte and eosinophils in contrast to increase of monocyte and neutrophil
during mercury exposure, so Lymphocytopenia, Eosinopenia versus Monocytosis
and Neutrophilia were happened in current results that bellow are explained.
A stress-induced leukocyte response refers to a combination of changes observed
in animals receiving corticosteroids or producing increased endogenous corticosteroids
because of some stressful condition. It generally consists of neutrophilia,
lymphopenia and sometimes monocytosis depending on the animal species. The neutrophilia
develops as a consequence of increased release of segmented cells from the kidny
storage pool, decreased margination of cells, decreased movement of cells into
tissues and increased stability of lysosomal membranes (Gad,
2007). Lymphopenia results from steroid-induced lysis and cell redistribution.
Eosinopenia develops as a result of decreased production and release from the
kidny (Evans, 2008). Monocytosis, when it occurs, is thought
to result from mobilization of marginated cells. It is interesting that the
stress-induced leukocyte response is a relatively infrequent finding in toxicology
studies even though the study design or the test material often creates physical
conditions that appear to be quite stressful (Gad, 2007).
It is believed that neutrophils and monocytes have phagocytic activity which
might explain their increased percentage during infectious situations. Lee
et al. (1998) also found an increase of neutrophil counts in channel
catfish exposed to high doses of potassium permanganate.
Adhikari et al. (2004) find a reduction in some
immunological parameters (leukocyte and lymphocyte counts) and the increase
in neutrophil and monocyte percentages were demonstrated in HgCl2
It is known that mercury can induce abnormal responses in the immune system,
including leukocyte count, a marker of cellular defense (Beutler
et al., 2001). The increase in neutrophil and monocyte percentages
which represents the activity of the first and second lines of defense against
the cellular damage, has been reported after mercury exposure (Elia
et al., 2003).
Ribeiro et al. (2006) confirmed significant
decrease of mononuclear (differential lymphocytes plus monocytes) and significant
increased of differential neutrophil to methyl mercury and inorganic lead.
It is known that changes in leukocyte counts after exposure to pollutants may
be associated to a decrease in nonspecific immunity of the fish. Ribeiro
et al. (2006) show decrease of leukocytes count to inorganic lead in
fish Hoplias malabaricus.
According to Wedemeyer et al. (1990), the suppression
of the immune system increases the susceptibility to diseases in fish, a very
important aspect considering the presence of heavy metals in natural ecosystems
as a result of human activities. However, results of leukocyte count in pollution
exposure are different and some researcher show decrease of leukocyte count
in exposure, like our study (Evans, 2008) for Thomomys
talpoides and Lopes et al. (2001) for Apodemus
Lohner et al. (2001) find Leukopenia (reduced
Leukocyte counts) and increase in both Neutrophils and Monocyte of Sunfish Populations
(Lepomis sp.) in different creeks.
WBC abundance provides an indication of fish health and a high WBC count may
indicate a subclinical infection. An extremely low WBC count indicates either
suppression of circulating lymphocytes, a characteristic acute stress response,
or that an active bacterial infection has induced leukocytolysis (Evans,
Result of current study show same progress of biochemical indices in both test condition with elevation in glucose and depletion in total protein (Hyperglycemia and Hypoproteinemia, respectively).
The most frequently encountered causes of hyperglycemia are failure to fast
an animal and catecholamine release secondary to excitement or fear (Gad,
2007). In suboptimum or stressful conditions (internal or external) the
chromaffin cells release catecholamine hormones, adrenaline and noradrenaline
toward blood circulation (Reid et al., 1998).
Those stress hormones in conjunction with cortisol mobilize and elevate glucose
production in fish through glucogenesis and glycogenolysis pathways (Iwama
et al., 1999) to cope with the energy demand produced by the stressor,
Glucose is then released toward blood circulation and enters into cells through
the insulin action (Nelson and Cox, 2005).
Levels of glucose often increase during the first phase of the stress response
due to an elevated breakdown of glycogen (Wendelaar-Bonga,
1997). Significant increases in glucose were observed as a result of toxic
effect of Cu (Abdel-Tawwab et al., 2007). These
results may be attributed to the hepatocellular damage. The plasma glucose concentration
of gilthead sea bream exposed to acute confinement was increased (Saera-Vila
et al., 2009). From aspect of increase, our observations show no disagreement
with the literature values.
Under stress situations may constitute a physiological mechanism with an important
role in providing energy to cope with the stress situation. Therefore, depletion
of total protein (hypoproteinemia) content might also be attributed to the destruction
or necrosis of cellular function and consequent impairment in protein synthetic
machinery (David et al., 2004). When an animal
is under toxic stress, diversification of energy occurs to accomplish the impending
energy demands and hence the protein level is depleted (Neff,
1997). The depletion of total protein content may be due to breakdown of
protein into free amino acid under the effect of mercury chloride at the lower
exposure period (Shakoori et al., 2004).
Some studies indicate a decrease in total protein content during heavy metal
exposure. Such decreases were, for example, found in the edible crab Scylla
serrata exposed to cadmium or in the freshwater fish Sarotherodon mossambicus
and the common carp exposed to mercury (Canli, 1996).
Depletion in the protein content of the Catla catla exposed to mercury chloride
sub-lethal concentrations were estimated (Prasath and Arivoli,
The major findings of this study are that mercury is a toxic substance in yellowfin sea bream, with many severs change on blood parameters to various concentrations. Results of the present investigation indicated that chronic mercury concentrations tested may cause several changes in the hematological and metabolite parameters of the studied fish and we can use these changes as biomarkers of mercury detection.
The authors are thankful to the Iranian National Science Foundation (INSF) with grant number 88000678 for providing financial support and necessary facilities.