Advances in Bioscience and Bioengineering [615945]

Advances in Bioscience and Bioengineering
2017; 5(5): 86-91
http://www.sciencepublishinggroup.com/j/abb
doi: 10.11648/j.abb.20170505.13
ISSN: 2330-4154 (Print); ISSN: 2330-4162 (Online)

Efficiency of Polychaete Nereis (Neanthes) Succinea as
Biomonitor for Heavy Metals Pollution in the Red Sea, Egypt
Rashad El Sayed Mohammed Said1, *, AbdAllah Tharwat AbdAllah1, Mohsen Abdelhafez Mostafa1,
Nasser Abdellatif El-Shimy2
1Department of Zoology, Faculty of Science, Al Azhar University, Assiut Branch, Egypt
2Department of Zoology, Faculty of Science, Assiut University, Assiut, Egypt
Email address:
[anonimizat] (R. E. S. M. Said)
*Corresponding author
To cite this article:
Rashad El Sayed Mohammed Said, AbdAllah Tharwat AbdAllah, Mohsen Abdelhafez Mostafa, Nasser Abdellatif El-Shimy. Efficiency of
Polychaete Nereis (Neanthes) Succinea as Biomonitor for Heavy Metals Pollution in the Red Sea, Egypt. Advances in Bioscience and
Bioengineering. Vol. 5, No. 5, 2017, pp. 86-91. doi: 10.11648/j.abb.20170505.13
Received : January 8, 2017; Accepted : January 18, 2017; Published : October 30, 2017

Abstract: Polychaetes nereids groups are the most common in shallow marine habitats and abundant in benthic
communities. This group was proved to tolerate a high burden of heavy metals within their tissues. The current work assesses
the effect of water criteria; sea water temperature, hydrogen ion concentration (pH), dissolved oxygen concentration, turbidity,
conductivity and salinity on the uptake and storage of four heavy metals; Mn,, Pb, Cd and Cu in tissues of the marine
polychaete worm Nereis succinea collected from two sites at Hurghada, Red sea; the Marine Biological Station (MBS) and the
Fishing Port at Sakala (FPS). Bioaccumulation Factors (BAFs) were determined to evaluate the capability of the investigated
annelid worm to accumulate heavy metals, so as to be used as sentinel species for monitoring metal pollutants. Population
density of the investigated polychaete was determined at both studied sites as related to water criteria. ANOVA statistical
analysis has indicated significant higher concentration of Mn, Pb, Cd and Cu in water at FBS than MBS (P<0.01) and high
tissue concentration of Mn, Cd, Pb and Cu at individuals collected from FBS (P<0.01). The highest value of annual mean of
BAF at Nereis tissues were recorded for Cu (1023.09±816.55), while the lowest BAF was for Pb (162.97±118.03). Polychaete
abundance was significantly higher at MBS. Significant effect was found for water criteria on metal bioaccumulation and
population density of Nereis . Data were discussed to evaluate the sensitivity of N. succinea to heavy metal pollutants and its
possible use as biological monitor for metal contaminants at marine habitats.
Keywords: Nereis succinea , Heavy Metals, Bioaccumulation, Population Density

1. Introduction
Environmental pollution has remarkably increased in the
last decades due to a great number of different source;
industrial, commercial, agricultural, and domestic waste,
effluents and emissions as well as hazardous substances.
The majority of environmental pollutants are threatening
initially human and environmental health but also the
integrity and function of ecosystems [1]. In fact, aquatic
pollution became a worldwide problem where many
waterways are being polluted with organic and inorganic
compounds such as pesticides and heavy metals from
various sources as industries and mining activities; but heavy metals, unlike organic pollutants, cannot be
detoxified via degradation and thus they persist in the
ecosystem [2-5]. Aquatic environments particularly coastal
areas are characterized by sensitivity to various inorganic
and organic pollutants. Globally, accepted procedures for
environmental / ecological impact and risk assessment have
been attributed to anthropogenic activities and impact on
coastal environments. Many chemical contaminants,
including organochlorine compounds, herbicides, petroleum
products and heavy metals are now recognized to have
adverse effects on ocean environments, even when released
at low levels. Little attention had been given to this
problem until shortly before the 19th century. Metal

87 Rashad El Sayed Mohammed Said et al. : Efficiency of Polychaete Nereis (Neanthes) Succinea as
Biomonitor for Heavy Metals Pollution in the Red Sea, Egypt
pollution may damage marine organisms at the cellular
level and possibly affect the ecological balance. Exposure
and ingestion of polluted marine organisms as sea foods can
cause health problems in people and animals including
neurological and reproductive problems [6]. Heavy metals
are natural trace components of the aquatic environment,
but their levels have increased due to industrial, agricultural
and mining activities. As a result, aquatic animals are
exposed to elevated levels of heavy metals. The levels of
metals in upper members of the food web like fish can
reach values many times higher than those found in aquatic
environments or in sediments [7]. There are different routes
for metal uptake; this process depends on the ecology,
biology and behavior of organisms and species. A
biomonitor is an organism that can give information about
the concentration of the contaminant in the environment [8-
12]. Several rules for selection of the appropriate
biomonitors should be considered. The selected organism
should have the ability to detoxify the contaminant turning
it into non-harmful compound and should store them
several folds of the inhabitant water or sediments. Also,
stored contaminant should not affect the healthy status of
organism. The selected organism should have a life cycle of at least on year to allow the following of contaminant
concentration within its tissue throughout different seasons.
It should be of big size to allow analysis of soft tissue to
determine the concentration of different contaminants.
2. Materials and Methods
2.1. Study Area and Sampling Protocol
Two sites were chosen to cover the purpose of the current
work. The first one was the Marine Biological Station
(MBS), and the second site was the Fishing Port at Sakala
(FPS). Both sites (Figure 1) are located on the Red Sea coast
at Hurghada city (Red Sea governorate). For detailed study,
sampling was carried out for polychaete and water samples,
from two main sites during a period of one year; from winter
2006 until autumn 2007. Worms were picked from sediments
by hand and rinsed with freshwater to remove sand and
debris. For metal analysis, worms were kept in freezer after
transported to lab in ice bags. Also water samples were taken
in polyethylene acid washed bottles, and then acidified with
drops of pure nitric acid.

Figure 1. Area of study, Site 1; Marine Biological Station (MBS), site 2; The Fishing Port at Sakala (FPS).
2.2. Measurement of Ecological Factors
Some parameters were measured at the field directly. At
the two main sites, seasonal measurements of water
temperatures, hydrogen ion concentration pH, dissolved
oxygen O2, water electric conductivity, salinity and turbidity,
were carried out in the field by using Water, Quality Checker
type U-10 code: 10040801000 F6. These measurements were carried out three times for each parameter.
2.3. Determination of Heavy Metals
2.3.1. In Water
The concentrations of four heavy metals were seasonally
determined; Lead (Pb), Cadmium (Cd), Copper (Cu) and
Manganese (Mn), according to the methods of [13, 14].

Advances in Bioscience and Bioengineering 2017; 5(5): 86-91 88

2.3.2. In Tissues
Stored animals samples were prepared for metal analysis
according to [11, 15]. The whole tissue of Nereis was taken
for analysis. Prior to the analysis, the specimens were
thawed, rinsed, and weighed. Special care was taken to
eliminate sediment particles adhering to the animals.
Digestion was performed with analar nitric acid in a water
bath till complete digestion. 5ml conc. nitric acid was added
to each tissue sample of the frozen tissue. The tissue was
then heated gently in water bath till boiling and vortexed to
help the tissue solubilization. The dissolved tissue was
cooled at room temperature and additional 0.25 ml of the
concentrated nitric acid was added. Then, the solution was
heated until it starts to turn brown. The solubilized tissue was
cooled. A third addition of 0.1 ml nitric acid was done and
the volume was reduced to approximately 0.5 ml. The
addition of 0.1 ml concentrated nitric acid was repeated until
the solution turns clear. The digested tissue was diluted with
bidistilled water to 10 ml and analyzed for heavy metals
determination using the graphite furnace. Heavy metals were
determined by a Perkin-Elmer spectrometer with a specific-
hollow cathode lamp for each metal. The metal concentration
was calculated according to [15, 16]. The metal concentration
was calculated in µg/g wet weight for tissue and µg/l for
water as follows:
Tissue concentration of metals
=
 × 


 ()
Bioaccumulation factor (BAF)
Bioaccumulation factor BAF was calculated according to
[11] according to the formula
BAF=... 
 ∗
...  
*Heavy metal concentration
2.4. Statistical Analysis
Analysis of variance on SPSS software package program
(Version 17) was used to test the current data. In the case of
significant differences, the Multiple Range Comparisons
(Least Significant Difference; LSD) was selected from Post
Hoc window on the same statistical package to detect the
significant difference between means. Also, Pearson
correlation coefficients were applied in the present data to
compare the effects of Physico-chemical parameters on the
concentration of heavy metals in water and tissue and the
bioaccumulation factors. Probability values ≤0.05 were
defined as significant throughout the current work. However,
the values > 0.05 were considered non-significant.
Probability values between 0.05 and 0.01 (both are included)
were evaluated as significant. Statistically non-significant,
significant and highly significant outputs were accompanied
by symbols NS, a and aa respectively.
3. Results and Discussion In the present work, the two investigated sites are
differed in their nature. The 1st site was subjected to
protection by the environment affairs agency, and hence it
could be considered as more protected compared to the 2nd
one. This site, namely, the fishing port at Sakala region is
impacted by several activities of fishing. All the
investigated annelid polychaetes worms belong to family
nereidae and represented the same specie Nereis succinea .
The difference between the two sites in some
morphological characters of their studied polychaete Nereis
such as width, size or weight is not evidence and don’t
confirm that the studied samples are different two species.
This in fact may be attributed to the difference between the
two sites in nutritive state, eutrophication levels and may
also be due to ecological factors affecting the physiological
status of the animals. The biological activities of the same
specie polychaete, for example Nereis divirsicolor was
differed significantly from clean to polluted habitats [17].
They [17] explained these differences by the different
characteristics of the two sites. On the other hand disturbed
environments tend to be characterized by small reselected
species [18].
3.1. Physico-chemical Parameters
The investigated parameters of water quality were
presented in (Table 1) as mean ± SD. In site 1 (Table 1), the
water temperature was seasonally fluctuated from
(17.23±32șC) in winter to (26.83±0.56șC) in summer with
annual mean of (22.75±4.26șC); while at site 2 temperature
was (28.13± 0.15șC) in summer with mean (23.58±4.06șC).
There was a clear slight temperature increase from site (1)
to site (2) in the summer and a reverse trend during the
winter with significance level (p<0.01) between the four
seasons except in the case of summer and autumn, which
was insignificant at site 1. These results are in agreement
with [19, 20] and lower than data recorded by [21] who
found that in the central Red Sea, the water temperature
was fluctuated from (22.8șC) in winter to (31.5șC) in
summer and [22] who reported that the water temperature
reported that the water temperature value increased from
(27.8șC) to (31.7șC) at five stations from the Red Sea coast
in Jeddah. Water acidity is known to influence the
solubility, availability and toxicity of metals in the aquatic
ecosystems [23]. In the present investigation, the level of
hydrogen ion (pH) in water at site (1) increased from
(7.53±0.47) in summer to a similar pattern of (8.13±0.11) in
winter and spring and (8.16±0.05) in autumn with mean
annual value of (7.99±0.35) with significance level (p<0.01)
between summer and autumn, while at site (2) the pH of
water showed a fairly stable pattern with total annual mean
(8.25±0.25) with (p<0.01) in winter and any other season.
The mean seasonal variation of dissolved oxygen recorded
in the present study displayed similar pattern at the two
sites. It fluctuated from 5.63±0.11 to 6.30±0.26 mg/l from
autumn to spring at site (1) and from 5.10±0.10 to
6.06±0.11 mg/l from winter to spring at site (2). These
records are in accordance with some measurements carried

89 Rashad El Sayed Mohammed Said et al. : Efficiency of Polychaete Nereis (Neanthes) Succinea as
Biomonitor for Heavy Metals Pollution in the Red Sea, Egypt
out within the Red Sea e.g. [24]. On the other hand, [22]
recorded lower values of dissolved oxygen from Saudi
Arabia coast ranged from (5.80–5.83mg/l). This variation in
concentration of dissolved oxygen is attributed to the effect
of decomposition of organic matter [25]. Moreover, the
second site in the present work received wastewater from
different sources leading to the agitation of sea water, hence
increasing its content of oxygen.
Nearly, all water parameter scored from site were
deteriorated compared to site 1. For example, the mean of
pH (8.25±0.25), dissolved oxygen (5.71±0.43) and turbidity
(12.19±3.25) have deviated from the standard values, while
in site 1 these values are in accordance with known values;
pH (7.99±0.35), dissolved oxygen (6.03±0.29) and turbidity
(7.10±1.90). Site 2 is located closed to the main road and is
exposed to many sources and types of pollution. In addition
this site receives high discharges of municipal wastes.
Domestic runoff contains different types of detergents,
wastes of cars repair and backwash of fish sales and
cleaning (Personal obtained data). Hydrocarbons are
organic substances require high amount of oxygen of
decomposition. These organic pollutants come from car
repair wastes using benzene solar, oil and gasoline.
Consequently, the process of degradation of such
compounds lead to depletion of oxygen, thereby increasing chemical oxygen demand. The higher turbidity at site 2 is
expected to be high at such circumstances. Detergents
contains alkaline contents and affect pH was in alkaline
side. Marine biological station, namely the 1st site is
subjected to protection from anthropogenic activates and
has more attention from the Egyptian environmental affairs.
Accordingly, water variables there are somewhat in save
side. [20] Recorded similar data from MBS for site (1) and
were not similar to measurements of turbidity observed in
site 2. Conductivity is an important property of seawater
because it is one measurement commonly used to calculate
the salinity of seawater; in addition, it provides more
insight into solvent structure [23]. Also the mean value of
conductivity in the 2nd site (63.74±0.77 µs/cm) was higher
than the 1st site (62.91±0.55 µs/cm). Salinity is considered
as a characteristic factor of sea water quality, it is an
indicator for wastes and pollutants discharge [19]. High
salinity might be due to high evaporation, low precipitation
and the lack of a major river inflow [26]. [22, 24, 27]
scored such values for site 1. Furthermore, the one way
ANOVA (Table 2) has revealed that the means of hydrogen
ion, dissolved oxygen, turbidity and conductivity between
the two sites exhibited high significant differences
(0.05>p<0.01).
Table 1. Annual means ±SD of ecological factors at site (1) during the period of investigation.
Site W. Temp. pH O2 Conductivity Salinity Turbidity
Site 1 22.75±4.26 7.99±0.35 6.03±0.29 62.91±0.55 42.76±0.33 7.10±1.90
Site 2 23.58±4.06 8.25±0.25 5.71±0.43 63.74±0.77 42.77±0.40 12.19±3.25
Table 2. One way ANOVA testing ecological factors between the two sites.
Source Sum of Squares df Mean Square F Sig.
Water temperature Between groups 4.084 1 4.08
0.23 0.63 Within groups 381.18 4 17.32
Total 385.27 5
Hydrogen ion Between groups 0.400 1 0.400
4.19 0.05 Within groups 2.099 4 0.095
Total 2.500 5
Dissolved oxygen Between groups 0.602 1 0.602
4.29 0.05 Within groups 3.083 4 0.140
Total 3.685 5
Turbidity Between groups 155.04 1 155.04
21.84 0.00 Within groups 156.13 4 7.097
Total 311.18 5
Conductivity Between groups 4.084 1 4.084
8.96 0.007 Within groups 10.026 4 0.456
Total 14.110 5
Salinity Between groups 0.0004 1 0.0004
0.002 0.96 Within groups 3.729 4 0.170
Total 3.730 5

3.2. Heavy Metals Concentrations in Tissue at the Two
Studied Sites
As well as ecological parameters, the accumulations of
heavy metals in tissues of Nereis were higher (Table 3) in
the 2nd site than the 1st one. The mean values of
manganese (0.87±0.56), cadmium (0.85±0.33) and copper (0.95±0.13) were more than three folds in the 2nd site
when compared with those of the 1st site; (0.18±0.02),
cadmium (0.26±0.23) and copper (0.31±0.34). To
understand the interaction between metal concentrations
in tissues and habitat, some considerations must be
considered: First, some metals may be balanced by
uptake-excretion regulation mechanism [28].
Second (Bioavailability of metals and factors affecting

Advances in Bioscience and Bioengineering 2017; 5(5): 86-91 90

them). The biologically available form of metal is usually the
dissolved ionic form, but not all ionic forms pose the same
biological hazard. In the present work statistical analysis has
indicted the presence of strong relation between metal
availability in water and physicochemical parameters. For
example, all metals were observed to increase (Table 4) as
water turbidity increase, for example in the case of
manganese r=.956, p<0.01), lead r=.964, p<0.01). On the
other hand, the concentrations of heavy metals in tissues
were correlated negatively with pH metallic ions (Table 4).
Hydrogen ion (pH) concentration in water was known to play
important role in metal bioavailability. If the water is acidic
with a low pH, metals are released much more rapidly than
when the water is more alkaline and pH is comparatively
high [29, 30]. In the present work, the available form of all
metals was negatively affected by the associated water pH
(p<0.01).
Table 3. Heavy metal concentrations (µg/g) in tissue of Nereis at the two
sites.
Site Mn Pb Cd Cu
Site 1 0.18±0.02 0.59±0.46 0.26±0.23 0.31±0.34
Site 2 0.87±0.56 0.78±0.67 0.85±0.33 0.95±0.13 Table 4. Correlation between metals concentration in tissues and pH &
turbidity.
Variables pH Turbidity
rSignificance rSignificance
Mn -.882-aa .956aa
Pb -.886-aa .964aa
Cd -.952-aa .904aa
Cu -.807-aa .974aa
aa. Correlation is significant at the 0.05 level (2-tailed).
3.3. Bioaccumulation Factor
Based on bioaccumulation factor (BAF) data (Table 5),
bioaccumulation of heavy metals at soft tissues of the
polychaete Nereis inhabiting marine biological station can be
arranged as follows:
Cu (784.98±878.58)> Mn (686.66± 518.16)>Cd
(326.35±323.1)>Pb (191.31±138.85) at fishing biological
station (FBS) heavy metal bioaccumulation can be ranked as
follows; Cu (1261.2±706.05)> Cd (984.62±519)> Mn
(686.66± 518.16) > Pb (191.31±138.85). The highest value
of annual mean of BAF at Nereis tissues were recorded for
Cu (1023.09±816.55), while the lowest BAF was for Pb
(162.97±118.03).
Table 5. Mean annual values of bioaccumulation factors for different heavy metals in tissues of Nereis at site (1) and site (2) during the period of study.

One way ANOVA (Table 6) for the bioaccumulation factor
(BAF) of the four studied heavy metals at soft tissues of the
polychaete Nereis inhabiting MBS and FBS showed highly
significant increase (P<0.01) for bioaccumulation factor of chromium and cadmium at fish biological station. Non-
significant difference was shown for bioaccumulation factor
of manganese, iron, lead and copper at the polychaete worm
inhabiting two sites.
Table 6. One way ANOVA, showing the significance between BAF at the two sites during the period of study.
Source Sum of Squares df Mean Square F Sig.
Manganese BAF Between groups 37881.760 1 37881.760
0.214 0.648 Within groups 3893661.136 4 176984.597
Total 3931542.896 5
Lead BAF Between groups 19283.670 1 19283.670
1.40 0.248 Within groups 301178.159 4 13689.916
Total 320461.830 5
Cadmium BAF Between groups 2599942.688 1 2599942.68
13.88 0.001 Within groups 4118364.047 4 187198.366
Total 6718306.735 5
Copper BAF Between groups 1360741.504 1 1360741.50
2.14 0.157 Within groups 13974694.946 4 635213.407
Total 15335436.450 5

4. Conclusion
The present results have clarified the ability of the selected
polychaete Nereis succinea to uptake metals from their habitat.
This biochemical behavior was confirmed when metals
distributions in tissues were compared between reference and
impacted areas. This study revealed the presence of higher
concentration of Mn, Pb, Cd and Cu in water at FBS than MBS
(P<0.01) and high tissue concentration of Mn, Cd, Pb and Cu at individuals collected from FBS (P<0.01). Higher BAF at Nereis
tissues were recorded for Cu (1023.09±816.55), while the
lowest BAF was for Pb (162.97±118.03).

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Mean 646.93±413.44 162.97±118.03 655.48±540.46 1023.09±816.55

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