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Journal of Stress Physiology & Biochemistry, Vol. 16, No. 1, 2020, pp. 31-38 ISSN 1997-0838 Original Text Copyright © 2020 by Basel Saleh
ORIGINAL ARTICLE
OPEN/J! ACCESS
Heavy Metals Pollution and its Genotoxicity Assessment through the Green Marine Ulva lactuca (Chlorophyceae) Algae in the Lattakia-Coastline, Syria
Basel Saleh
Department of Molecular Biology and Biotechnology, AECS, P.O. Box 6091, Damascus, Syria
*E-Mail: ascientific@aec. orq.sy
Received December 4, 2019
The current study was conducted to investigate pollution level in Lattakia-coastline, Syria using Ulva lactuca (Chlorophyta) algae as bioindicator for sea water pollution based on Zn, Pb, Cu and Cd concentration using Atomic Absorption Spectrometry (AAS) technique. On the other hand, to investigate pollution genotoxicity on U. lactuca algae based on Genomic Template Stability (GTS%) estimations yielded by Touch-down Directed Amplification of Minisatellite DNA (Td-DAMD) marker. AAS analysis indicated that the Lattakia coastline is not polluted by the mentioned pollutants (Zn, Pb, Cu and Cd) at least regarding these metals. As for GTS%, it is not correlated with observed pollutants concentration in the mentioned sites. Further studies focused especially on determination of other elements than those studied herein and investigation their influence on DNA changes profile are needed.
Key words: Ulva lactuca algae, Heavy metals pollution, Atomic Absorption Spectrometry (AAS) technique, Genomic Template Stability (GTS%)
Air, soil and water pollution became a serious problem worldwide due to daily increased human activities in terrestrial and aquatic ecosystems. According to US Environmental Protection Agency (EPA), cadmium (Cd), mercury (Hg) and lead (Pb) were considered as the most three contaminants of greatest threat to the environment (Jamers et al., 2013). Pollution caused deleterious effects on water quality and biomass physiology, morphology and molecular approaches. Many analytical methods successfully employed for detecting heavy metals pollution in ecosystems; e.g. Inductively Coupled Plasma Mass Spectrometry (ICPMS) and Instrumental Neutron Activation Analysis (INAA) (Gaudry et al., 2007; Chakraborty and Owens 2014); Energy-Dispersive X-Ray Fluorescence spectrometry (EDXRF) (Apaydin et al., 2010); Flame Atomic Absorption Spectroscopy (FAAS) (Allam et al., 2016); Atomic Absorption Spectrometry (AAS) (Annabi et al., 2018; Jayasinghe et al., 2018; Cadar et al., 2018); Inductively Coupled Plasma Atomic Emission Spectroscopy (ICP-AES) (van Ginneken and de Vries 2018) and Inductively Coupled Plasma-Optical Emission Spectrometry (ICP-OES) (Chen et al., 2018) techniques.
Seaweeds displayed a critical role in many applications; e.g. industry, cosmetics, food, animal feed, agriculture, horticulture and agronomy, environmental monitoring and bioremediation and thalassic and wellness (Apaydin et al., 2010; Saleh 2018a).
Living organisms are proved to be an effective tool for environmental genotoxicity monitoring in ecosystems. In this regards, Aras et al. (2011) applied Pseudevernia furfuracea (L.) Zopf lichen to detect air pollution in Turkey. As for aquatic pollution: for example, Dourado et al. (2017) applied animal (Astyanax altiparanae fish) and plant (Allium cepa) for water pollution monitoring in Brazil.
Among living organisms, algae were successfully employed worldwide for detecting heavy metals pollution in marine ecosystems. In this regards, in Hong Kong (Wong et al. 1982); Egypt (Mohamed and Khaled 2005); Atlantic Moroccan coast (Gaudry et al., 2007); Turkish marine coast (Topcuoglu et al., 2010; Apaydin et al., 2010); Aegean sea (Akcali and Kucuksezgin 2011); Gulf
of Kutch in India (Chakraborty et al., 2014); Australia (Chakraborty and Owens 2014); and Algeria (Laib and Leghouchi 2012; Allam et al., 2016). Recently in Tunisia (Annabi et al., 2018); China (Chen et al., 2018); Sri Lanka (Jayasinghe et al., 2018); Black Sea (Cadar et al., 2018) and oceans (van Ginneken and de Vries 2018).
Heavy metals pollution has deleterious effects on living organisms at morphological, physiological, biochemical and molecular levels. Molecular markers approach was widely and successfully employed for detecting DNA changes. Genomic template stability (GTS%) evaluation was considered as a qualitative measure reflecting DNA changes induced by abiotic and biotic stresses (Aras et al. 2011; Saleh 2016a, b;2018b).
Thereby, the current work aimed to monitoring the Lattakia-coastline, Syria pollution by determination of heavy metals (Zn, Pb, Cu and Cd) content in on hand; and to detecting DNA changes induced by the mentioned pollutants based on GTS% estimation resulting from Touch-down directed amplification of minisatellite DNA (Td-DAMD) marker application, on the other hand.
MATERIALS AND METHODS
Sampling procedure
Samples [sea water (SW) and algal thalli (A)] were collected from 8 sites located along the Lattakia-Syrian coast of the Mediterranean Sea (Table 1). Samples collection was carried out from 35°44'459"E latitude to 35°43'995"E at 4 km North Lattakia - Syria. The collection site S8 was considered as a control due its location so far from any contamination kind. Whereas, the site S5 was located at dischargeinfluence of river entering the Mediterranean Sea and exposed to our local pollutant emissions.
Only individual with the similar size was harvested manually with disposable gloves, biomass was washed with seawater where the algae were collected and then transported within a flask with (5 l) seawater to laboratory. Upon algae arrival to laboratory, they were washed twice with double distillate water (ddH2O). To facilitate their drying, they were drained and transported to Whatman filter paper. Samples were divided into two sets; the first one was kept in liquid nitrogen for DNA
extraction serving for molecular study. Whereas, the second onewas shade dried for two weeks, then powdered by special electric mill and stored separately in polyethylene bags until analysis.
Moreover, seawater (250 ml) samples were also collected from the same locations where the natural habitant of algae. Due to the rocky nature location of sites, sediments involving sand samples did not included in the analysis.
Heavy metals measurement
Heavy metals (Zn, Pb, Cu and Cd) concentration in seawater (SW) and algae (A) samples collected from the 8 examined sites were measured by atomic absorption spectrometry (AAS) technique. Genomic DNA extraction
Algal genomic DNA was extracted from algae thalli collected from the 8 examined sites, using CTAB (cetyltrimethylammonium bromide) protocol as described by Doyle and Doyle (1987). DNA was kept at -80°C until used. Td-DAMD molecular marker
Algal DNA changes induced by pollution was investigation using sixteen DAMD primers (Table 2) in Td-DAMD analysis. Td-DAMD analysis was carried out in 25 Ml total volume as reported by Ince & Karaca (2012). Final PCR products were separated on a 2 % ethidium bromide-stained agarose (Bio-Rad) in 0.5x Tris-borate-EDTA (TBE) buffer. A VC 100bp Plus DNA Ladder (Vivantis) ladder standard was used to estimate molecular weight of Td-DAMD-PCR amplification products size.
Genomic Template Stability (GTS%) estimations
Algal DNA changes were determined based on genomic template stability (GTS%). The polymorphism between control (non-polluted site) and polluted sites was calculated by recording the appearance of new bands and disappearance of bands in polluted sites, compared to their respective control band profiles.
Genomic template stability (GTS%) was calculated according to Atienzar et al. (2002) as follows: GST% = (1- a/n) x 100 Where (a) is the DNA polymorphism profile in each polluted site and (n) the number of total bands in the
control. Polymorphism observed in Td-DAMD profiles included disappearance of a normal band and appearance of a new band in comparison to the control Td-DAMD profiles. Statistical analysis
Metals content in SW and A samples was performed in three replicates and the results were presented as a mean ± SD. One-way ANOVA test was performed using the STATVIEW statistical software package (Abacus 1996) at the 5% significance level (P = 0.05). Variance analysis (ANOVA) has been carried out to determine differences means between examined sites via selected samples (SW & A). Fisher's least significant difference (PLSD) test was performed to detect significant differences between means.
RESULTS AND DISCUSSION
AAS analysis revealed that Zn concentration was ranged between 0.207 (S8) - 0.633 (S1) |g/g in SW samples and it was ranged between 0.460 (S8) - 1.767 (S5) |g/g dw in A samples (Table 3). Whereas, Pb concentration was ranged between <0.200 (S1, S2, S3, S4, S5, S6 & S8) - 0.207 (S7) |g/g in SW samples and it was ranged between <0.200 (S1, S2, S3, S4, S6, S7 & S8) - 1.300 (S5) |g/g dw in A samples (Table 3). As for Cu, its concentration was presented in similar manner in scarce amounts (<0.050 |g/g) in SW samples regardless collection sites; and it was ranged between <0.050 (S1, S2, S3, S4, S6, S7 & S8) - 0.533 (S5) |g/g dw in A samples (Table 3). While, Cd concentration was presented in scarce amounts (<0.050 |g/g) regardless sample type or/and collection sites.
From data obtained herein, algal thalli grown in S5 accumulated the highest Zn, Pb and Cu concentrations than the other examined sites.
As for genotoxicity assessment, algal DNA change profiles in the examined sites, using Td-DAMD marker as yielded by URP1F, HBV3 and 33.6 DAMD primers into U. lactuca algae have been presented in Figure 1. The results mentioned that the GTS% was recorded to be 46.472, 56.64,57.418, 67.453, 58.983, 65.566 and 58.405% for S1, S2, S3, S4, S5, S6 and S7 sites, respectively (Table 4).
Sea water and algal thalli samples were collected from 8 sites located along the Lattakia-Syrian coast of
the Mediterranean Sea. Pollution level in Lattakia-coastline, Syria has been investigated using U. lactuca (Chlorophyta) algae as bioindicator for sea water pollution based on Zn, Pb, Cu and Cd concentration using AAS technique. Otherwise, pollution genotoxicity on U. lactuca algae based on GTS% estimation has been assessed.
AAS analysis indicated that the examined sites showed different pollutants pattern (Table3). In this regards, site S5 showed the highest heavy metals content compared to the other examined sites. This difference can attribute to the fact that the mentioned site located at discharge influence of river entering the Mediterranean Sea and exposed to our local pollutants emissions.
Based upon AAS data, we can suggest that the Lattakia-coastline is not polluted by the mentioned pollutants at least regarding studied metals. This observation has been established based on other investigations recently published; e.g. in Honaine coastline- Algeria (Allam et al., 2016); oceans (Ginneken and de Vries 2018) and South Eastern coast of Tunisia (Annabi et al., 2018).
Statistical analysis revealed that the samples (SW and A), site collection and interaction samples with site collection significantly affected Zn, Cu and Pb metals content and noticeably Zn one (Table 3).
Topcuoglu et al. (2010) reported that the Corallina mediterranea, C. officinalis and U. lactuca algae were the most accumulators for Cd, Fe, Ni, Pb and Zn among the examined 11 algae species in Turkey. Whereas, Akcali and Kucuksezgin (2011) reported that Ulva sp. accumulated the highest amounts of Cu among the three examined seaweeds in Aegean sea.
It was noticed that U. lactuca thalli highly accumulated Zn metal than the other measured metals. This observation was in coherent with Chakraborty and Owens (2014); Allam et al., (2016); Cadar et al. (2018), Annabi et al. (2018) and Jayasinghe et al. (2018) investigations.
In our case study, AAS analysis revealed that the Zn concentration was ranged between 0.207- 0.633 |ig/g in SW and between 0.460 - 1.767 |g/g dw in A samples (Table 3). Whereas, Pb concentration was ranged
between <0.200- 0.207 |g/g in SW samples and between <0.200- 1.300 |g/g dw in A samples (Table 3). As for Cu, its concentration was presented in similar manner in scarce amounts (<0.050 |g/g) in SW samples regardless collection sites; and it was ranged between <0.050 - 0.533 |g/g dw in A samples (Table 3). While, Cd concentration was presented in scarce amounts (<0.050 |g/g) regardless sample type or/and collection sites.
Chakraborty and Owens (2014) reported that Zn was ranged between 41.6-112 |g/g dw, Pb was ranged between 3.6-17.9 |g/g dw, Cu was ranged between 45.5-46.7 |g/g dw and Cd was ranged between 0.060.11 |g/g dw in U. lactuca thalli in South Australian coastline. Whereas, Allam et al. (2016) applied U. lactuca algae for detecting water pollution in Honaine-Algerian coast. They reported that the U. lactuca content of heavy metals was ranged between 0.45-0.46, 1.442.2, 2.81-3.54 and between 0.15-0.16 |g/g dw for Cu, Pb, Zn and Cd, respectively. Indeed, Annabi et al. (2018) reported the heavy metals (Fe, Zn, Cu, Pb, Cd and Mn) accumulation pattern by U. lactuca thalli collected from 3 different sites located at South Eastern Coast of Tunisia. They reported that Zn concentration was ranged between 0.02-1.615 |g/g dw and between 0.650-1.422 |g/g dw in SW and A samples, respectively. Whereas, Pb concentration was ranged between 0.040.140 |g/g dw in algae thalli. As for Cu, it was ranged between 0.245-2.429 |g/g dw and between 0.037-0.187 ig/g dw in SW and A samples respectively. While, Cd concentration was ranged between 0.018-0.041 |g/g dw and between 0.228-0.578 |g/g dw in SW and A samples, respectively. Whereas, Cadar et al. (2018) reported that the content of heavy metals in U. lactuca was recorded to be 19.28, 3.01, 0.201 and 3.05 mg/kg and to be 19.40, 4.30, 0.266 and 2.95 mg/kg for Zn, Cu, Cd and Pb, respectively during 2016 and 2017, respectively in detecting water pollution in Black Sea. Moreover, Jayasinghe et al. (2018) reported that the Zn concentration in U. lactuca was ranged between 4.7582.00 mg/kg dw, Cu was ranged between 1.82-135.94 mg/kg dw, Cd was ranged between 0.170-0.608 mg/kg dw; whereas, Hg was not detected (LOD<0.07 mg/kg dw).
Table 1. Location sites where samples (U. lactuca and sea water) were collected.
Site N°_Longitude_Latitude
1 35°34'255"N 35°44'459"E
2 35°34'113''N 35°44'435''E
3 35°34'161''N 35°44'460''E
4 35°33'990''N 35°44'288''E
5 35°33'917''N 35°44'179''E
6 35°33'789''N 35°43'995''E
7 35°33'790''N 35°43'996''E
8 35°33'771''N 35°43'995''E
Table 2. DAMD primers used in the current study.
_Primer N°_Primer name_Primer Sequence 5' to 3'
1 URP1F ATCCAAGGTCCGAGACAACC
2 URP2R CCCAGCAACTGATCGCACAC
3 URP4R AGGACTCGATAACAGGCTCC
4 URP25F GATGTGTTCTTGGAGCCTGT
5 URP30F GGACAAGAAGAGGATGTGGA
6 FVIIex8 ATGCACACACACAGG
7 HBV3 GGTGAAGCACAGGTG
8 YNZ22 CTCTGGGTGTGGTGC
9 33.6 GGAGGTGGGCA
10 M13 GAGGGTGGCGGCTCT
11 HBVb GGTGTAGAGAGAGGGGT
12 URP2F GTGTGCGATCAGTTGCTGGG
13 URP6R GGCAAGCTGGTGGGAGGTAC
14 M13 GAGGGTGGCGGTTCCT
15 HVA AGGATGGAAAGGAGGC
16 HVV GGTGTAGAGAGGGGT
Table 3. Heavy metals concentrations in sea water (SW) and U. lactuca algae (A) samples in the examined sites.
Zn Pb Cu Cd
Site SW A SW A SW A SW A
S1 0.633±0.058 Ba 1.200±0.300 Ab <0.200±0.000 Ab <0.200±0.000 Ab <0.050±0.000 A; a 0.100±0.000 Ab <0.050±0.000 <0.050±0.000
S2 0.600±0.000 Bb 0.730±0.026 Ad <0.200±0.000 Ab <0.200±0.000 Ab <0.050±0.000 A; a <0.050±0.000 Ab <0.050±0.000 <0.050±0.000
S3 0.300±0.000 Bg 0.833±0.058 Ac <0.200±0.000 Ab <0.200±0.000 Ab <0.050±0.000 A; a <0.050±0.000 Ab <0.050±0.000 <0.050±0.000
S4 0.453±0.076 Bd 0.710±0.017 Ad <0.200±0.000 Ab <0.200±0.000 Ab <0.050±0.000 A; a <0.050±0.000 Ab <0.050±0.000 <0.050±0.000
S5 0.557±0.040 Bc 1.767±0.058 Aa <0.200±0.000 Bb 1.300±0.000 Aa <0.050±0.000 B; a 0.553±0.005 Aa <0.050±0.000 <0.050±0.000
S6 0.307±0.012 Bf 0.600±0.000 Ae <0.200±0.000 Ab <0.200±0.000 Ab <0.050±0.000 A; a <0.050±0.000 Ab <0.050±0.000 <0.050±0.000
S7 0.377±0.035 Be 1.133±0.058 Ab 0.207±0.011 Aa <0.200±0.000 Bb <0.050±0.000 A; a <0.050±0.000 Ab <0.050±0.000 <0.050±0.000
S8 0.207±0.012 Bh 0.460±0.056 Af <0.200±0.000 Ab <0.200±0.000 Ab <0.050±0.000 A; a <0.050±0.000 Ab <0.050±0.000 <0.050±0.000
Same lowercase letters (columns) and capital letters (rows) are not significantly different at P=0.05 probability by Fisher's PLSD test
LSD0.05 Zn=0.1; Pb=0.003 and Cu=0.002.
Data were presented as average (3n) ± standard deviation and expressed in Mg/gof dry weight.
Table 4. Estimated genomic template stability (GTS%) yielded by Td-DAMD marker.
Primer C S1 S2 S3 S4 S5 S6 S7
URP1F 100.000 57.143 100.000 100.000 100.000 57.143 100.000 85.714
URP2R 100.000 42.857 57.143 28.571 57.143 57.143 42.857 28.571
URP4R 100.000 90.909 72.727 72.727 72.727 54.545 72.727 72.727
URP25F 100.000 71.429 85.714 85.714 100.000 85.714 85.714 85.714
URP30F 100.000 60.000 100.000 100.000 100.000 80.000 80.000 100.000
FVIIex8 100.000 61.538 61.538 69.231 69.231 69.231 61.538 61.538
HBV3 100.000 72.727 63.636 63.636 54.545 63.636 81.818 45.455
YNZ22 100.000 50.000 50.000 0.000 50.000 50.000 0.000 50.000
33.6 100.000 57.143 57.143 57.143 71.429 71.429 78.571 71.429
M13 100.000 37.500 50.000 50.000 75.000 50.000 75.000 87.500
HBVb 100.000 33.333 66.667 66.667 50.000 33.333 33.333 16.667
URP2F 100.000 0.000 50.000 75.000 75.000 100.000 100.000 100.000
URP6R 100.000 50.000 50.000 37.500 25.000 37.500 62.500 50.000
M13 100.000 37.500 50.000 37.500 62.500 75.000 75.000 62.500
HVA 100.000 16.667 66.667 50.000 66.667 33.333 50.000 16.667
HVV 100.000 0.000 25.000 25.000 50.000 25.000 50.000 0.000
Average
100.000
46.472
56.64
57.418
67.453
58.983
65.566
58.405
Bill
Figure 1. Td-DAMD profile yielded by URP1F, HBV3 and 33.6 DAMD primers into U. lactuca showing DNA change profiles in the examined sites from 1-7 lanes. Lane 8 = control sample. M: A VC 100bp Plus DNA Ladder (Vivantis) ladder standard.
Laib and Leghouchi (2012) reported Cd, Cr, Cu, Pb, and Zn concentration in seaweeds (green, red and brown). They reported that the Zn was accumulated in the highest concentration in the examined seaweeds.
To detect pollution genotoxicity in the Lattakia-coastline, Syria, DNA changes induced by pollutants in the mentioned sites were investigated based on GTS% estimation in U. lactuca using Td-DAMD marker.
Overall, GTS% was recorded to be 46.472, 56.64, 57.418,67.453,58.983,65.566 and 58.405% for S1, S2, S3, S4, S5, S6 and S7 sites, respectively. Based upon
this observation, GTS% value is not correlated with observed pollutants concentration in the mentioned sites. This could explain by the fact that, AAS analysis indicated that the Lattakia-coastline, is not polluted by the mentioned pollutants (Zn, Pb, Cu and Cd) at least regarding these metals. On the other hand, the observed algal DNA changes reflecting in GTS% assessed by Td-DAMD marker, could related to other elements that are not emphasized in the current study.
Aras et al. (2011) applied P. furfuracea lichen to detect air pollution in Turkey in 10 sites using 10 RAPD
primers. They reported that GTS% value ranged between 81.3-96% according to the studied site.
Under laboratory experiments, Saleh (2015) reported that GTS% value was found to be 65.215, 64.630, 59.835 and 59.250% for Pb, Cu, Cd and Zn exposure, respectively after 5 days exposure using random amplified microsatellite polymorphism (RAMP) marker in U. lactuca algae. Whereas, Saleh (2016a) reported that, GTS% value was found to be 45.4, 69.0 and 72.8% with Cd treatment of 2.5, 5 and 10 mg/L, respectively after 4 days exposure using random Amplified Polymorphic DNA (RAPD) marker in the same algae phyla. Moreover, Saleh (2018b) reported that, GTS% value was found to be 87.274, 84.174 and 70.667 % with Pb treatment of 2, 4 and 8 mg/L, respectively after 4 days exposure using RAPD marker in the same algae phyla.
CONCLUSION
Heavy metals (Zn, Pb, Cu and Cd) content in U. lactuca algae and sea water has been investigated in 8 collection sites from Lattakia-coastline, Syria. AAS analysis indicated that the Lattakia coastline is not polluted by the mentioned pollutants ((Zn, Pb, Cu and Cd) at least regarding these metals. As for GTS%, it is not correlated with observed pollutants concentration in the mentioned sites. Further studies focused especially on determination of other elements than those studied herein and investigation their influence on DNA changes profile are needed.
ACKNOWLEDGEMENTS
I thank Dr. I. Othman (Director General of AECS) and Dr. N. Mirali (Head of Molecular Biology and Biotechnology Department in AECS) for their support, and also the PlantBiotechnology group for technical assistance.
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