EXPOSURE ASSESSMENT FOR MERCURY AND OTHER METALS IN
COMMONLY CONSUMED FISH OF WEST PENINSULAR MALAYSIA
Zurahanim Fasha Anual
PhD in Applied Science
Faculty of Education, Science, Technology & Mathematics
University of Canberra
ACT
Submitted for PhD in Applied Science
January 2014
Acknowledgements
Many people have contributed to the success of my PhD project. I would like to take this
opportunity to thank those who have significantly contributed either directly or indirectly to this.
First and foremost, my ultimate gratitude goes to Allah Almighty for giving me this golden
opportunity to complete my PhD despite the challenges and obstacles experienced during my stay
in Australia. This has certainly made me grow as a better person each and every single day.
Thank you Allah.
I would like to also thank my first supervisor, Dr. Simon Foster for your time and assistance
throughout my project and making sure that everything worked well. A big thank you goes to
Prof Bill Maher, my second supervisor for prompt review in checking my thesis chapters even
though I found it hard to decipher the handwritings sometimes. Thank you also to Frank Krikowa
for assistance in conducting analyses for my project and giving advice to optimize my project. To
my fellow labmates; Rod, Chamani, Rajani thank you for your help in solving statistics questions
and assistance in lab analysis. Thanks a lot also to Larissa who have motivated me to write my
thesis and assisted me in reviewing some of the chapters. To Max and Sally, I really appreciate
your assistance in running the SDS-PAGE. Not forgetting my housemate cum my best friend and
travel buddy, Nur Hafizah who shared my ups and downs as well as providing emotional support,
I will treasure our friendship till the end of time. To my fellow Malaysian friends in Canberra,
thank you for your friendship.
Last but not least, I would like to thank my families in Malaysia, Mama, Along, Baby, uncles,
aunts, cousins and friends for emotional support and motivations to keep me going. I would like
to also dedicate this PhD to my late father. Thank you Ayah! Without you, I won’t be where I am
now.
v
Abstract
Fish is a cheap supply of protein and is considered among the main source of protein for majority
of populations in Asia. Eating fish has always been associated with health benefits due to high
content of omega-3 fatty acids (EPA and DHA). As consumption of fish is the main route of
exposure to pollutants in humans, it is the main interest of this study to determine the
concentrations of metals (with special interest in mercury) in commonly consumed fish in West
Peninsular Malaysia. Due to the toxicity of mercury which depends on its bioavailability and
chemical form, it is insufficient to measure only total concentrations of mercury. Hence, mercury
speciation was also measured in this study. As mercury has a high affinity for sulphur, the most
likely binding ligand of mercury is free sulfhydryl groups in protein cysteine residues. There is
limited information, however, on the binding sites of mercury in fish proteins. A more detailed
examination on the biochemical associations of mercury in fish proteins was assessed using size
exclusion chromatography and SDS-PAGE to determine the molecular weights of protein bound
mercury. Reversed phase chromatography was then used to determine the chemical associations
of mercury. The implications for the metabolism and toxicity of mercury in fish were discussed.
vii
Table of Contents
Certificate of Authorship _______________________________________________________ iii
Acknowledgements _____________________________________________________________ v
Abstract _____________________________________________________________________ vii
CHAPTER 1 __________________________________________________________________ 1
INTRODUCTION AND RATIONALE _____________________________________________ 1
1.1
INTRODUCTION AND RATIONALE _______________________________________________ 1
1.2
RESEARCH AIMS _____________________________________________________________ 4
1.3
SPECIFIC OBJECTIVES _________________________________________________________ 5
CHAPTER 2 __________________________________________________________________ 7
LITERATURE REVIEW ________________________________________________________ 7
2.1
Mercury species in the environment______________________________________________ 7
2.2 History of use _________________________________________________________________ 8
2.3
Sources of mercury ___________________________________________________________ 9
2.4
Toxicological effects of mercury _______________________________________________ 11
2.5
Biogeochemical cycling of mercury _____________________________________________ 13
2.6
Methylation of mercury ______________________________________________________ 14
2.7
Demethylation of mercury ____________________________________________________ 16
2.8
Pathways of human exposure to methyl mercury _________________________________ 16
2.9
Absorption, distribution and excretion of mercury in humans _______________________ 19
2.10
Biomarkers of exposure ______________________________________________________ 22
2.11
Mercury in fish _____________________________________________________________ 23
2.12
Consumption advisories for mercury in fish ______________________________________ 25
2.13
Bioaccumulation of mercury in marine food webs _________________________________ 27
2.14
Speciation analysis __________________________________________________________ 30
2.16
Separation of proteins _______________________________________________________ 35
2.16.1 Polyacrylamide gel electrophoresis (PAGE) ______________________________________________ 35
2.16.2 Size exclusion chromatography (SEC) __________________________________________________ 36
2.17 Protein characterization and identification ________________________________________ 37
ix
2.18 Metallothioneins ________________________________________________________ 39
Concluding Remarks ____________________________________________________ 40
2.19
CHAPTER 3 _________________________________________________________________ 43
THE ASSESSMENT OF TOTAL MERCURY AND METHYL MERCURY IN FISH
TISSUES FROM WEST PENINSULAR MALAYSIA _______________________________ 43
3.1 INTRODUCTION _______________________________________________________________ 43
3.2
MATERIALS AND METHODS ___________________________________________________ 46
3.2.1
3.2.2
3.2.3
3.2.4
3.2.5
3.2.6
3.3
INTRODUCTION __________________________________________________________________
SELECTION OF SITES _____________________________________________________________
COLLECTION OF FISH AND SEAFOOD _____________________________________________
LABORATORY ANALYSES ________________________________________________________
STATISTICAL ANALYSIS _________________________________________________________
CLASSIFICATION OF SPECIES _____________________________________________________
46
46
46
48
49
50
RESULTS ___________________________________________________________________ 50
3.3.1 Quality assurance of analytical results ___________________________________________________
3.3.2 Nitrogen and carbon stable isotopes _____________________________________________________
3.3.3 Total mercury and methyl mercury concentrations _________________________________________
3.3.4
Inter species variation in total mercury and methyl mercury concentrations ___________________
3.3.4.1 Interspecific differences in total mercury concentrations ________________________________
3.3.4.2 Interspecific differences in methyl mercury concentrations ______________________________
3.3.4.3 Differences in total mercury concentrations between trophic levels ________________________
3.3.4.4
Differences in methyl mercury concentrations between trophic levels __________________
3.3.4.5
Differences in total mercury concentrations between feeding mode _____________________
3.3.4.6
Differences in methyl mercury concentrations between feeding mode ___________________
3.3.4.7 Percentage ratios of methyl mercury to mercury _______________________________________
3.3.5 Relationship of mercury concentrations with length _______________________________________
3.3.6 Relationship of methyl mercury concentrations with length _________________________________
3.3.7 Trophic level and biomagnification ____________________________________________________
50
51
55
55
55
57
57
57
58
58
59
60
61
62
3.3.7.1 Relationship between 15N and log mercury concentrations ______________________________ 62
3.3.7.2 Relationship between 15N and log methyl mercury concentrations ________________________ 63
3.3.8 Comparison with fish consumption guidelines ___________________________________________ 64
3.3.9 Estimation of potential health risk _____________________________________________________ 64
3.4
3.4.1
3.4.2
3.4.3
3.4.4
3.4.5
3.4.6
3.4.7
3.4.8
DISCUSSION________________________________________________________________ 67
Nitrogen and carbon stable isotope analysis ______________________________________________
Interspecific differences in total mercury concentrations ___________________________________
Interspecific differences in methyl mercury concentrations _________________________________
Differences in total mercury concentrations between trophic levels ___________________________
Differences in methyl mercury concentrations between trophic levels _________________________
Differences in total mercury concentrations between feeding mode ___________________________
Differences in methyl mercury concentrations between feeding mode _________________________
Relationship of total mercury concentrations and length ____________________________________
x
67
68
69
71
71
72
72
72
3.4.9 Relationship of methyl mercury concentrations and length __________________________________
3.4.10 Percentage ratios of methyl mercury to mercury __________________________________________
3.4.11
Trophic level and biomagnification __________________________________________________
3.4.12 Comparison with fish consumption guidelines ____________________________________________
3.4.13
Estimation of potential health risk ___________________________________________________
3.5
73
74
74
75
76
Summary and conclusions ____________________________________________________ 77
CHAPTER 4 _________________________________________________________________ 79
ASSESSMENT OF METALS IN COMMONLY CONSUMED FISH OF WEST
PENINSULAR MALAYSIA ____________________________________________________ 79
4.1 INTRODUCTION _______________________________________________________________ 79
4.2
MATERIALS AND METHODS ___________________________________________________ 82
4.2.1 SELECTION OF SITES _____________________________________________________________
4.2.2 COLLECTION OF FISH AND SEAFOOD _____________________________________________
4.2.3 LABORATORY ANALYSIS ________________________________________________________
4.2.3.1
MEASUREMENT OF FISH AND SEAFOOD ______________________________________
4.2.3.2
SAMPLE PREPARATION ______________________________________________________
4.2.3.3
MEASUREMENT OF METAL CONCENTRATIONS ______________________________
4.2.3.4
ANALYSIS OF CARBON AND NITROGEN STABLE ISOTOPES ____________________
4.2.4 STATISTICAL ANALYSIS _________________________________________________________
4.2.5 CLASSIFICATION OF SPECIES _____________________________________________________
4.3
82
82
83
83
83
83
84
84
84
RESULTS___________________________________________________________________ 85
4.3.1 Quality assurance of analytical results ___________________________________________________ 85
4.3.2 Nitrogen and carbon stable isotopes ____________________________________________________ 86
4.3.3 Trophic transfer of metals ____________________________________________________________ 88
4.3.4 Metal concentrations ________________________________________________________________ 88
4.3.4.1 Arsenic (As) ____________________________________________________________________ 88
4.3.4.2
Cadmium (Cd) ________________________________________________________________ 93
4.3.4.3 Lead (Pb) _______________________________________________________________________ 93
4.3.4.4
Selenium (Se) ________________________________________________________________ 93
4.3.4.5 Copper (Cu) _____________________________________________________________________ 93
4.3.4.6 Zinc (Zn) ______________________________________________________________________ 94
4.3.4.7 Iron (Fe)________________________________________________________________________ 94
4.3.5 Relationship of metal concentrations with length _________________________________________ 96
4.3.6
Relationship between metal concentrations _____________________________________________ 96
4.3.6.1 Correlations with all metal concentrations ____________________________________________ 96
4.3.6.2
Interactions between mercury and selenium concentrations ___________________________ 98
4.3.7 Estimation of potential health risk ____________________________________________________ 101
4.4
DISCUSSION_______________________________________________________________ 103
4.4.1 Stable isotope analysis _____________________________________________________________
4.4.2 Trophic transfer of metals ___________________________________________________________
4.4.3
Metal concentrations ______________________________________________________________
4.4.3.1 Arsenic (As) __________________________________________________________________
xi
103
103
104
104
4.4.3.2 Cadmium (Cd)_________________________________________________________________
4.4.3.3 Lead (Pb) _____________________________________________________________________
4.4.3.4 Selenium (Se) __________________________________________________________________
4.4.3.5 Copper (Cu) ___________________________________________________________________
4.4.3.6
Zinc (Zn) ___________________________________________________________________
4.4.3.7 Iron (Fe) ______________________________________________________________________
4.4.4 Relationship of metal concentrations and feeding habit ____________________________________
4.4.5 Relationship of metal concentrations and length __________________________________________
4.4.6
Relationship between metal concentrations __________________________________________
4.4.6.1
Correlations __________________________________________________________________
4.4.6.2
Mercury and selenium concentrations ____________________________________________
4.4.7 Estimation of potential health risk ____________________________________________________
4.5
106
107
108
109
110
111
112
113
113
113
114
115
Summary and Conclusions ___________________________________________________ 116
CHAPTER 5 ________________________________________________________________ 119
A STUDY ON MERCURY-BINDING PROTEIN IN FISH __________________________ 119
5.1
INTRODUCTION ____________________________________________________________ 119
5.2
MATERIALS AND METHODS ___________________________________________________ 121
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5
5.2.6
5.2.7
5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5
5.4
5.4.1
5.4.2
5.4.4
5.4.5
General remarks __________________________________________________________________
Chemicals _______________________________________________________________________
Protein extraction from fish _________________________________________________________
Sodium dodecyl sulphate-polyacrylamide gel electrophoresis (SDS-PAGE) ___________________
Inductively coupled plasma-mass spectrometry (ICP-MS) _________________________________
High Performance Liquid Chromatography (HPLC) ______________________________________
Digestion of SDS-PAGE gel _________________________________________________________
121
121
121
122
122
123
124
RESULTS _________________________________________________________________ 124
Protein extraction from fish _________________________________________________________
Mercury-containing proteins in fish extracts ____________________________________________
SDS-PAGE _______________________________________________________________________
Digestion of SDS-PAGE gels ________________________________________________________
Separation of mercury-containing proteins______________________________________________
124
125
126
127
128
DISCUSSION ______________________________________________________________ 131
Protein extraction from fish ________________________________________________________
Mercury-containing proteins in fish extracts ____________________________________________
Digestion of SDS-PAGE gels ________________________________________________________
Separation of mercury-containing proteins _____________________________________________
131
131
133
133
5.5 Summary and conclusions _____________________________________________________ 134
CHAPTER 6 ________________________________________________________________ 137
SYNOPSIS AND GENERAL CONCLUSIONS ____________________________________ 137
6.1.1 The assessment of total mercury and methyl mercury in fish tissues from West Peninsular
Malaysia _______________________________________________________________________ 137
xii
6.1.2 Assessment of metals in commonly consumed fish of West Peninsular Malaysia ________ 138
6.1.3 A study on mercury-binding protein in fish ______________________________________ 139
REFERENCES _____________________________________________________________ 143
xiii
List of Figures
Figure 2.1 Proportion of global anthropogenic emissions of mercury to air from different regions
of the world (AMAP/UNEP 2008)................................................................................................. 10
Figure 2.2 Global mercury consumption by application and by region in 2005 ............................ 12
Figure 2.3 Global biogeochemical cycling of mercury. Natural (preindustrial) fluxes (Mg) year-1
and inventories are noted in black, anthropogenic contributions are in red. Natural fluxes
enhanced by anthropogenic activities are noted by red and black dot-red line. ............................. 14
Table 2.1 The major effects of different mercury species.............................................................. 21
Figure 2.4 The chemical structure of the complex of methyl mercury with the amino acidcysteine and methionine. Adapted from Clarkson et al. (2007) ..................................................... 22
Figure 2.5 Varying concentrations of mercury in different types of fish and seafood (Source:
Blanchard J., Sierra Magazine 2011) .................................................................................................
Figure 2.6 Illustrative diagram of typical analytical steps involved to obtain comprehensive
metalloproteomics information ...................................................................................................... 35
Figure 3.1 Map of fish complexes and wholesale markets in West Peninsular Malaysia ............. 47
Table 3.1 The most preferred seafood consumed among Malaysians based on dietary survey in
Peninsular Malaysia (reprinted from Nurul Izzah 2009) ............................................................... 47
Table 3.2 The mean certified and measured values of mercury and methyl mercury (MeHg)
concentrations (mean ± standard deviation) in µg/g dry mass in certified reference material
DORM-2......................................................................................................................................... 50
Table 3.4 Mercury and methyl mercury concentrations (mean ± S.D. µg/g dry mass) in selected
species of fish from West Peninsular Malaysia ............................................................................. 55
Figure 3.3 The mean mercury concentrations in fish by species ................................................... 56
Figure 4.1 Map of fish complexes and wholesale markets in West Peninsular Malaysia ............. 82
xv
List of Table
Table 2.1 The major effects of different mercury species...........................................................21
Table 2.2 Applications of hyphenated technique using ICP-MS as detector..............................34
Table 3.1 The most preferred seafood consumed among Malaysians based on dietary survey in
Peninsular Malaysia .......................................................................................................................47
Table 3.2 The mean certified and measured values of mercury and methyl mercury (MeHg)
concentrations (mean ± standard deviation) in µg/g dry mass in certified reference
material DORM-2 ..........................................................................................................................50
Table 3.3 Total mercury concentrations (mean ± S.D. µg/g dry mass) and stable isotope
analysis in fish from West Peninsular Malaysia.............................................................................53
Table 3.4 Mercury and methyl mercury concentrations (mean ± S.D. µg/g dry mass) in selected
species of fish from West Peninsular Malaysia..............................................................................55
Table 3.5 Mean total Hg concentrations (µg/g dry mass) in various species of fish reported in
the literature, including results from this study .............................................................................70
Table 4.1 The mean certified and measured values of metal concentrations (mean ± standard
error) in µg/g dry mass in certified reference material DORM-2..................................................85
Table 4.2 The nitrogen and carbon stable isotope analysis in commonly consumed fish of West
Peninsular Malaysia.......................................................................................................................89
Table 4.3 Metal concentrations (µg/g dry mass) in commonly consumed fish of West
Peninsular Malaysia……………………………………………………………….......................91
Table 4.4 Correlation analyses between metals…………………………………………….......98
Table 4.5 Mass, molar concentrations and molar ratios of mercury and selenium in fish
species ……………………………………………………………………………......................100
Table 4.6 The Provisional Tolerable Daily and Weekly Intake for all metals in fish from West
Peninsular Malaysia………………………………………………………………......................102
Table 5.1 NexION 300Q Instrumental Parameters ……………………………………….......122
Table 5.2 The extraction efficiencies by different extraction procedures in fish………….......123
Table 5.3 Total mercury content with corresponding protein bands......................................................127
Table 5.4 List of protein spots identified by various techniques in specific species..............................134
xvii
CHAPTER 1
INTRODUCTION AND RATIONALE
1.1
INTRODUCTION AND RATIONALE
Mercury has a long history of use and is still regarded as one of the most important metalloids in
global context (Clarkson and Magos 2006). Its wide application in mining, medicine, industry,
agriculture, coal combustion and several other fields continues to be a major concern to the
general population (Clarkson et al. 2003a). Mercury occurs naturally in the environment and can
exist as either elemental (or metallic); inorganic (e.g mercury chloride, mercury sulfide) as well
as organic (e.g. ethyl and methyl mercury) (Clarkson and Magos 2006). The forms in which
mercury exists in the environment play a vital role as different forms of mercury have varying
effects on humans as well as to flora and fauna.
Elemental mercury exists as a liquid at room temperature and vaporizes readily, which plays a
major role in global cycling of mercury (UNEP 2002). Volcanic and geological activity naturally
mobilizes mercury from deep reservoirs in the earth into the atmosphere (Fitzgerald 2005). Coal
combustion is regarded as the largest anthropogenic sources of mercury emission into the
atmosphere (UNEP 2008; Pacyna et al. 2010). Mercury vapour has an atmospheric residence time
of about 0.5 - 1 year and is a chemically stable monatomic gas, thus is well mixed in the
atmosphere (Lin and Pehkonnen 1999; Clarkson 2002). The combination of natural and
anthropogenic sources releases mercury in the environment and results in long range atmospheric
transport, global deposition and revolatilization by which mercury ultimately settles in sediments
of lakes, rivers or the ocean (Selin 2009).
Sulfate reducing bacteria are the main microbial communities responsible for methylation of
inorganic mercury to organic mercury in both marine and freshwater systems (Clarkson and
Magos 2006). In aquatic sediment, methyl mercury is produced from biomethylation process and
enters aquatic food chains. Through a process known as biomagnification, methyl mercury
reaches its highest concentrations in tissues of fish at the top predatory level. Another possible
pathway for methyl mercury formation is through chemical and photochemical methylation
which play important roles in transformation, transport and biogeochemical cycle of metals,
1
metalloids and nonmetallic elements (Keppler et al. 2000; Hamilton et al. 2003). Yin et al. (2012)
demonstrated the possibility of alkylation of inorganic Hg2+ to methyl mercury and/or ethyl
mercury by ketones, aldehydes and low molecular weight organic acids in aqueous solution under
UV irradiation. Methyl mercury concentrations were reported to be approximately 1-10 million
times greater in fish at the top of the aquatic food chain than dissolved methyl mercury
concentrations in surrounding waters (Lawrence and Mason 2001; US Environmental Protection
Agency 2001). In fish tissue, methyl mercury was found to be attached to the thiol group of
cysteine residues in fish protein (Harris et al. 2003). Freije and Awadh (2009) found that more
than 95 % of total mercury from fish samples in their study in Bahrain comprised of methyl
mercury.
The most prominent case of human poisoning demonstrating bioaccumulation was perhaps
exhibited in the infamous Minamata disease outbreak (Harada 1995). Back in the early 1950s, a
spill occurred in Minamata, Japan from an acetaldehyde manufacturing company which used
inorganic mercury salts as catalysts. The mercury was chemically converted to methylmercury
that was released in waste waters into Minamata Bay (Harada 1994). As a result, fish populations
were severely contaminated with methyl mercury and the local community who ate contaminated
fish suffered from acute and chronic mercury poisoning which was later known as Minamata
Disease (Harada 1994; Harada 1995). It is estimated that around 200 000 people were exposed to
methyl mercury poisoning with 17 000 residents have claimed to be certified victims of the
disaster and so far only 2264 people have been certified with the disease (Syversen and Kaur
2012). Among the manifested neurological signs from patients diagnosed with the disease
include losses of sensation in the hands and the feet, hearing impairment, blurred vision,
difficulty in coordination of hands and feet and speech impediments (Harada 1995; Yorifuji et al.
2008).
The other classic example of methyl mercury poisoning occurred in Iraq during the winter of
1971-1972. Seed grain which was treated with organic mercury fungicide containing ethyl and
methyl mercury and not intended for human consumption was mistakenly distributed as food.
The seeds were then used to prepare homemade bread resulting in poisoning cases amounting to a
total of 40 000 people while 6 000 others were hospitalized. No observable immediate effects or
2
symptoms were detected among the Iraqi victims during the period of bread consumption due to
latency period of methyl mercury neurotoxicity (Syversen and Kaur 2012). The symptoms were
dose dependent and effects such as blurred vision, slurred speech, hearing difficulties and ataxia
(difficulty in coordination movements) were observed (Bakir et al. 1973).
There appears to be two major transport mechanisms for methyl mercury in the human body.
Methyl mercury enters into cells as a complex with cysteine and homocysteine on the large
neutral acid amino carriers and exit from the cell as a complex with glutathione on the
endogenous glutathione carriers (Clarkson and Magos 2006). Fish are the predominant source of
mercury to humans and about 95% of ingested methyl mercury in fish is absorbed into the
bloodstream (WHO 1990). The half life of methyl mercury in the body is about 70 days
(Clarkson et al. 2003b). Methyl mercury concentration in brain is about 5 times on that in the
blood and in hair, about 250 times higher than the concentrations in blood (Clarkson and Magos
2006).
As fish is regarded as one of the cheapest sources of proteins for South East Asian countries
especially Malaysia, measuring the concentrations of mercury as well as methyl mercury in fish
and seafood is of high importance. On average, Malaysians consume 59 – 63 kg year-1 of marine
fish and demand for fish is increasing (Hajeb et al. 2009). It is reported that methyl mercury in
fish is bound to tissue protein rather than in fatty deposits; hence, trimming and skinning of
mercury-contaminated fish does not reduce the mercury content of the fillet portion (WHO
2008). In addition, methylmercury concentrations in fish remains constant even after cooking
(WHO 2008). The Joint Food and Agriculture Organization of the United Nations/World Health
Organization FAO/WHO Expert Committee on Food Additives (JECFA) has established
provisional tolerable weekly intakes (PTWIs) for total mercury at 5 μg/kg body weight and for
methylmercury at 1.6 μg/kg body weight (WHO 2008). Various organisations have also
published reference levels for methyl mercury in humans such as United States Environmental
Protection Agency (USEPA) at 0.7 μg/kg body weight per week, Bureau of Chemical Safety
Canada at 1.4 μg/kg body weight per week and Food Safety Commission Japan (2.0 μg/kg body
weight per week)(WHO 2008).
3
Studies on mercury concentrations in fish and seafood are well documented elsewhere (Freije and
Awadh 2009; Al Majed and Preston 2000; Hyo-Bang Moon et al. 2011) but somewhat limited in
Malaysia. The most recent studies by Hajeb et al. (2009) and Agusa et al (2007; 2005) assessed
mercury concentrations from marine fish bought from local markets in the west and east coast of
Peninsular Malaysia with emphasis on total mercury concentrations. Only a few studies reported
methyl mercury concentrations in marine fish (Rahman et al. 1997; Hajeb et al. 2010).
1.2
RESEARCH AIMS
This study aimed to assess concentrations of mercury and associated metals in commonly
consumed fish in Malaysia. As fish is considered as one of the main supply of cheap protein in
the diet of the population of Malaysia, it is vital to ensure that the fish consumed is within
permissible national guidelines. While emphasis of this study is on mercury concentrations in
fish, other metals of particular interests were also measured to gain an insight into metal
concentrations in fish and seafood of selected locations in West Peninsular Malaysia. The forms
of mercury which exist in fish are critical as they determine the toxicity of mercury. Therefore,
the speciation study of mercury was measured to assess the methyl mercury (MeHg)
concentrations in fish was conducted.
Apart from total metals and mercury speciation assessment, this study also used stable isotope
analysis which is able to quantify trophic position of organisms, energy flow pathways as well as
bioaccumulation of contaminants in the food web. In comparison with gut analysis of organism
which is often laborious and requires considerable taxonomic expertise, stable isotope analysis is
preferred in this context.
Numerous studies on speciation of mercury focus only on MeHg and Hg2+ and do not take into
account its real chemical form MeHgX in which X may represent low molecular ions, peptides,
proteins or even other potential binding partners. Hence, the potential binding partners of methyl
mercury in fish was investigated. This was achieved through extraction of fish protein which was
then passed through a size exclusion column, high performance liquid chromatographyinductively coupled plasma mass spectrometry (HPLC-ICPMS) and further analysed by mass
spectrometry.
4
1.3
SPECIFIC OBJECTIVES
The specific objectives of this study were:
1. To measure concentrations of metals (mercury, arsenic, lead, selenium, cadmium, copper, zinc,
iron) in commonly consumed fish in West Peninsular Malaysia.
2. To determine mercury species in commonly consumed fish in West Peninsular Malaysia.
3. To determine whether metal concentrations in fish are influenced by feeding group (omnivore,
carnivore, secondary carnivore), length and habitat (benthic, pelagic).
4. To compare metal concentrations with permissible national (Malaysian Food Regulations
1985) as well as international guidelines (JECFA, WHO, Australia Food Standards).
5. To investigate the potential binding partners of methyl mercury in fish.
5
CHAPTER 2
LITERATURE REVIEW
This literature review discusses the current understanding of bioaccumulation of mercury in
marine food webs and factors influencing bioaccumulation in the ecosystem. The mercury
concentrations in various types of fish and seafood are presented and the consumption advisories
issued for mercury in fish by different organizations are briefly outlined. Speciation of mercury
as well as techniques to identify mercury binding proteins in fish tissue is further examined. This
review begins by summarizing current knowledge regarding the sources and biogeochemical
cycling of mercury in the environment, toxicological effects of mercury in humans and how
mercury are absorbed, distributed and excreted in human body.
2.1
Mercury species in the environment
Mercury (Hg) is one of the most toxic elements in the environment and exists in various physical
and chemical species. Mercury can occur in three different oxidation states owing to a complex
chemical transformation in the mercury cycle (Barbosa et al. 2001). Elemental mercury (Hg0) is
inorganic mercury which exists as liquid at room temperature hence the name quicksilver due to
its silvery manifestation and mobility as liquid (Clarkson et al. 2003b). Although elemental
mercury shows poor absorption in liquid form, it is extremely volatile and the mercury vapour is
well absorbed in the lung and can rapidly pass the blood-brain barrier (Pamphlett and Cotte
1998). Elemental mercury is still being used extensively in thermometers, fluorescent light bulbs,
medical equipment such as blood pressure cuffs and in chemical industry (Clarkson et al. 2003b).
Mercuric (Hg2+) and mercurious (Hg+) forms of mercury can be transformed into organic
mercury (CH3Hg+) through biomethylation by aquatic microorganisms and then accumulate in
the food chain (Aschner and Aschner 1990). Organic mercury species contain a covalent Hgcarbon bond, with methyl mercury (MeHg) being the major and most toxic form of mercury in
the environment (Mahalingam 2004). At present, humans are exposed to mercury from three
different sources: mercury vapour from dental amalgams, exposure to methyl mercury from
consumption of fish as well as ethylmercury in the form of thimerosal used as a preservative in
vaccines (Clarkson et al 2007). However, the most common form of human exposure is through
consumption of fish contaminated with methyl mercury.
7
2.2
History of use
Mercury has a long history of use. Recognised as one of the most ancient metal existing in the
world, mercury was widely used in art, science, medicine, religion, agriculture and many
industrial applications (Clarkson et al. 2003a). Calomel which is a form of mercurous chloride,
was used in children’s teething powders and in laxatives in the mid-20th century when it was
learnt that these practices caused acrodynia by which children with acrodynia suffered joint
pains, experiencing autonomic instability with pink sweaty hands and feet, irritability and
photophobic which were believed to be a result of hypersensitivity reaction (Warkany and
Hubbard 1953; Clarkson et al. 2003b). More than 3000 years ago, cinnabars (mercury in the form
of red ore) have been used by the Chinese to prepare red ink (Clarkson and Magos 2006).
Mercury was also found in Egyptian tombs as a preservative as well as a protector against evil
spirits (Clarkson and Magos 2006). The Middle Ages saw the use of mercury as a treatment for
syphilis where a little was particularly useful but too much proved to be fatal (Clarkson et al.
2007). Mercuric nitrate was also used in the carroting of felt hats which gave rise to use of terms
such as “mad as a hatter” (Clarkson and Magos 2006).
Organomercurials (methyl and ethyl mercury) were widely used in agriculture as antifungal
agents in seed grain until the 1970s and the use were discontinued after numerous accounts of
mercury poisonings in humans and certain wildlife species (Bakir et al. 1973). In the industrial
era, mercury is being used widely in barometers and thermometers, as an electrode in the
electrolytic production of chlorine and caustic soda from saline as well as in electrical switches.
The vapour from metallic mercury is also used in mercury arc lamps and incandescent lights
(Clarkson and Magos 2006).
Mercury use in batteries although still considerable, continues to decline with many countries
implement policies to mitigate problems related to diffuse mercury releases. For instance, while
mercury use in Chinese batteries was relatively high through the year 2000, the majority of
Chinese manufactures are reported to have shifted to battery designs with low mercury content
abiding by international legislations and trends in customer demands in other countries (NRDC
2006).
8
2.3
Sources of mercury
Mercury is released to the environment from two major sources: natural (emissions from natural
deposits) and anthropogenic (from human activities). Natural processes which emit significant
mercury can be outgassing of soils and water bodies, biomass burning, geothermal process and
volcanoes; which are considered as one of the most important natural sources of mercury
(Rasmusen 1994; Schroeder and Munthe 1998). Industrial processes that release mercury to the
atmosphere are cement production, nonferrous metal production, pig iron and steel production,
caustic soda production, gold production, and waste disposal, as well as direct mercury
production (Selin 2009).
Estimates of direct, present-day anthropogenic emissions of mercury to the atmosphere range
from 2200–4000 Megagram year−1 (Lamborg et al. 2002). Emissions of atmospheric mercury
differ greatly by region. In Europe, about 40% of the total mercury released every year is from
natural origin (Pacyna et al. 2001) whereas in the US, natural sources contribute from 6% to 59%
for the overall annual mercury emission (Seignur et al. 2003; 2004). Atmospheric mercury
emissions has increased by 20 fold since pre-industrial times and about 70% of the total mercury
input derived from anthropogenic origin (Schuster et al. 2002).
Since 1990, the global total atmospheric mercury emission has become fairly constant (Pacyna et
al. 2006). The use of technologies such as flue gas desulfurization, electrostatic precipitators and
fabric filters to control sulphur or particulates are among the key factors which have been found
to reduce mercury emissions to the atmosphere (UNEP 2002) where it can remove up to one-third
of mercury emitted by coal burning plants (UNEP 2008). When combined with sulfur dioxide
and nitrogen oxide control devices, up to 95 % of the mercury can be captured (UNEP 2008). The
introduction of mercury-specific emissions regulations in the U.S. on medical waste incineration
and municipal waste combustion also has led to significant decreases in mercury emissions in the
1990s (USEPA 2008), from an estimated 220 tonnes in 1990, to 105 tonnes of mercury in 1999.
Nevertheless, a slightly different scenario is witnessed in Asia. While other regions are
experiencing decline in mercury emissions, mercury emissions in Asia continue to increase as
China and other rapidly developing countries are relying heavily on coal-based electricity.
Emissions from Asia represent more than half of the global mercury emissions (Pacyna et al.
9
2010) with China estimated to release mercury at 536 ± 236 Mg/year of mercury (Streets et al.
2005)(Figure 2.1).
The most prominent anthropogenic emissions of mercury can be derived from coal combustion,
mining and smelting activities, gold mining as well as production and disposal of electrical and
electronic products (Wong et al. 2006). The global mercury consumption by application and by
region in 2005 is shown in Figure 2.2. The largest contributor of mercury emission is the artisanal
and small scale gold mining which involves at least 100 million people in more than 55 countries
particularly in Africa, Asia and South America (Telmer 2008).
Figure 2.1 Proportion of global anthropogenic emissions of mercury to air from different regions
of the world (AMAP/UNEP 2008)
10
2.4
Toxicological effects of mercury
Perhaps the most profound examples of human exposure to methyl mercury poisoning followed
were first discovered in Minamata Bay and Niigata regions of Japan in 1956. It took several years
before symptoms of methyl mercury toxicity were able to be identified. Chisso Co. Ltd produced
acetaldehyde by using inorganic mercury as a catalyst. Methyl mercury; the by-product of this
process was emitted as a waste effluent into waterways. As time passed by, bioaccumulation of
methyl mercury in aquatic ecosystem occurred to levels that were hazardous to health. Residents
surrounding Minamata Bay who regularly ate fish high in methyl mercury concentrations were
found to suffer severe health effects and sometimes death which was later known as Minamata
disease (Mineralogical Association of Canada 2005). Sediments near the scupper of Chisso plant
was detected with mercury of more than 2000 ppm while fish and shellfish in the bay contained
20 to 40 ppm of mercury (wet weight). The extent of the methyl mercury contamination was also
evident in the hair of residents living 20 kilometres away from Minamata Bay who were not
suffering from Minamata disease with hair mercury concentrations ranging from 191-920 ppm
(Harada 1994). Congenital methyl mercury poisoning was also brought to the attention of the
public by which infants showed severe cerebral palsy-like symptoms, mental retardation,
cerebellar ataxia, primitive reflexes, dysarthria as well as hyperkinesias when mothers were
exposed to mild or no manifestation of methyl mercury poisoning (Mergler et al. 2007). In 1995,
Minamata disease was officially acknowledged by the Japanese government with close to 20 000
people seeking compensation due to the health impacts suffered (Mineralogical Association of
Canada 2005).
Similarly in Iraq, methyl mercury poisoning cases occurred in winter 1971-1972 due to grains
which were treated with organomercurial fungicide and unintentionally released to the local
population. The poisonous breads which were baked with treated wheat and barley flour caused
the loss of lives of 459 people and 6530 reported cases of methyl mercury poisoning. Among the
symptoms include paresthesia, visual disorders, dysarthria, deafness and death due to failure of
the central nervous systems (CNS)(Mineralogical Association of Canada 2005).
11
Figure 2.2 Global mercury consumption by application and by region in 2005
(AMAP/UNEP 2008)
(note: East and South East Asia bar is split)
12
2.5
Biogeochemical cycling of mercury
Mercury is naturally mobilized from deep reservoirs in the earth to the atmosphere through
volcanic and geological activity. The natural biogeochemical cycle of mercury involves
atmospheric transport, deposition to land and ocean and revolatilization. Ultimately, mercury is
buried in the deep-ocean sediments however, this process occurs very slowly (Selin 2009).
The biogeochemical cycling of mercury begins with the evaporation of mercury vapor from land
and sea surfaces with volcanoes being an important natural source (Fitzgerald and Mason 1997).
The burning of fossil fuel, especially coal combustion is the major anthropogenic sources
representing 60% of the year 2000 mercury emission (Pacyna et al. 2006). Mercury vapor is a
chemically stable monatomic gas. Its residence time in the general atmosphere is estimated to be
about 1 year (Lin and Pehkonen 1999). Thus, mercury vapor is globally distributed even from
point sources. By processes not yet fully understood, the vapor is oxidized in the upper
atmosphere to water-soluble ionic mercury, which is returned to the earth’s surface in rainwater
(Clarkson 2002). Some of the mercury in rainfall reaches the aquatic environment, mainly the
oceans. About 90% of the total Hg input to oceans is recycled to the atmosphere and less than
10% reaches the sediments. However, 2% is methylated in the biota resulting in accumulation in
the food chain. Only a small fraction is lost to the atmosphere, mainly as highly volatile dimethyl
mercury (Fitzgerald and Mason 1997). The global cycling of mercury (Figure 2.3) modulates
mercury toxicity and results in the distribution of mercury to the most remote regions of the
planet. For example, environmental mercury levels even in arctic water are similar to those in
more southern latitudes (Muckle et al. 2001).
13
Figure 2.3 Global biogeochemical cycling of mercury. Natural (preindustrial) fluxes (Mg) year-1
and inventories are noted in black, anthropogenic contributions are in red. Natural fluxes
enhanced by anthropogenic activities are noted by red and black dot-red line.
Adapted from Selin et al. (2008)
2.6
Methylation of mercury
The chemistry of mercury in the environment is complex and a shift in its physical form and
valence state can occur due to subtle change in chemical, physical, biological and hydrologic
conditions. In the environmental mercury cycle, the methylation of inorganic mercury (HgII) is
considered as one of the most toxicologically significant transformation as not only the
bioavailability and toxicity of mercury is increased, in fact exposure of fauna and human to
methyl mercury increases too (Mineralogicalogical Association of Canada 2005). Mercury
methylation occurs when inorganic mercury (HgII) is converted to methyl mercury by sulfate
reducing bacteria (King et al. 2001a) by a methyl-group donor. It is widely claimed that biotic
methylation of mercury within the watershed is the principal mechanism for methyl mercury
14
formation (Driscoll et al. 1998). Wood et al. (1968) suspected that microbial mercury methylation
is influenced by methylcobalamin, a vitamin B12 derivative (methylcorrinoid) and suggested that
the process involves nonenzymatic transfer of methyl group methylcobalamin to the mercuric
ion.
Sulfate reducing bacteria (SRB) are the primary methylators of mercury in the environment
(Compeau and Bartha 1987; Gilmour et al. 1992; King et al. 2001b) although how mercury is
methylated by SRB is not well defined. Three pathways have been proposed; (1) the acetyl
Coenzyme A pathway in which methyl-tetrahydrofolaten is the methyl group donor (Choi et al.
1994); (2) the acetate metabolic pathway using methyltransferase enzymes (King et al. 2000) and
(3) the within methionine synthase (Siciliano and Lean 2001). None of these pathways alone
satisfactorily explain methylation in all SRB. It is certain that more than one mechanism may
exist, but it is likely that the true pathway behind mercury methylation is yet to be revealed.
Mercury methylation is influenced by several factors under favourable conditions such as
moderately high temperatures, acidic conditions, low salinity, low sulphide concentrations,
anaerobic conditions and high levels of dissolved organic matter (Bisinoti et al. 2007; Power et
al. 2002). It is noteworthy that these factors are not stand alone and often interact to form a
complex system of synergistic as well as antagonistic effects (Ullrich et al. 2001).
Methylation rates in aquatic systems are mostly higher during the summer months (Bubb et al.
1993; Watras 1998) compared to winter due to lower rates of bacterial growth and lower
microbial activity (Hintelmann and Wilken 1995). Decreasing pH in lake waters have been found
to escalate methyl mercury concentrations and increased methyl mercury concentrations have
been observed in fish from low pH lakes (Miskimmin et al. 1992; Winfrey and Rudd 1990).The
amount of inorganic mercury in pore water is greatly reduced by acidification of sediments,
presumably due to the formation of insoluble mercury sulfide hence the decrease in methylation
(Ramlal et al. 1985). Salinity affects methylation, with higher rates of methyl mercury formation
observed in fresh waters than in estuarine or marine environments (Compeau and Bartha 1987;
Olson and Cooper 1976). When sulphate ions are microbially reduced to sulphide in anaerobic
conditions, the effect of high salinity is most pronounced as methylation is inhibited (Ullrich et
15
al. 2001). High dissolved organic matter concentrations enhance the formation of Hg0 from Hg2+
in photochemical reactions (Allard and Arsenie 1991; Xiao et al. 1995; Ravichandran et al.
2000), which could reduce the availability of mercury for methylation and bioaccumulation
(Miskimmin et al. 1992; Ravichandran 2004; Bisinoti et. al 2007).
Methylation in the water column does not occur as much as in the sediments due to low amounts
of nutrients and bacteria. In the water column, methylation is readily concentrated by
phytoplankton, the biological conduit for transferring the contaminant to pelagic and benthic food
webs (Lindqvist et al. 1991; Watras and Bloom 1992; Mason et al. 1996). Plankton absorbs the
methyl mercury and as the smaller fish eat the plankton and the larger predatory fish consume the
smaller fish, the methyl mercury bioaccumulates up the food chain to humans. Bioaccumulation
results in larger, predatory fish having higher amounts of methyl mercury than smaller nonpredatory fish. All fish contain methyl mercury regardless of the size or the geographic location
of the waters from which the fish is caught, although size and type of fish as well as the
geographical location of waters can influence lower or higher amounts of methyl mercury.
2.7
Demethylation of mercury
Demethylation of methyl mercury encompasses both biotic and abiotic processes. In reductive
demethylation process, methyl mercury is converted to Hg0 whereas oxidative demethylation
results in the production of Hg(II) (Barkay and Wagner-Döbbler 2005). Through the merdetoxification pathway, biotic degradation may occur by bacteria possessing genes of the meroperon (Marvin-DiPasquale et al. 2000; Schaefer et al. 2004). The mer- detoxification process
involves mer-B gene which encodes organomercurial-lyase enzyme that cleaves methyl mercury,
forming methane and Hg(II) as by-products while mer-A gene reduces Hg(II) to Hg0 and thus
methyl mercury is converted to a form that may readily volatize from the immediate environment
(Marvin-DiPasquale et al. 2000; Schaefer et al. 2004).
2.8
Pathways of human exposure to methyl mercury
Humans can be exposed to mercury via three different routes namely consumption of fish,
mercury vapour from amalgam tooth fillings as well as ethyl mercury in the form of thimerosal in
16
vaccines (Clarkson 2002). Nevertheless, consumption of fish is the primary route of exposure to
methyl mercury in humans today (Clarkson and Magos 2006).
Fish is a nutritious food, being a good source of protein, rich in certain vitamins and minerals and
containing long chain n3 polyunsaturated fatty acids (LC n3-PUFAs. Bioaccumulation of methyl
mercury in the marine environment particularly in fish is a widespread concern as upper level
consumers including wildlife and humans can be adversely affected (Clarkson 1990; Wolfe et al.
1998; Weiner et al. 2003).
Of recent, the form of methyl mercury that exist in fish tissue has been recognized as attached to
thiol group of the cysteine residues in fish protein (Harris et al. 2003). Methyl mercury are
present between 75 to 90 percent of total mercury in fish (Mahaffey 2004). Several authors have
reported on dietary habits and cooking methods that can affect mercury levels in fish. Since
methyl mercury resides in tissues of fish, no method of cleaning or cooking will reduce the
amount of mercury in a meal of contaminated fish (Clarkson 2002; NRC 2000). Burger et al.
(2003) reported that deep-fried fish had higher mercury concentrations when compared to raw
fish. Morgan et al. (1997) studied the effect of cooking practices in two commonly caught fish in
Lake Wisconsin and observed that raw fish were 1.1 to 1.6 times lower in concentrations than
corresponding pan-fried, boiled and baked fish fillets due to water loss when heat was applied. In
addition, mercury amounts before and after cooking remain constant suggesting that mercury was
not removed from fish tissue (Morgan et al. 1997). Meanwhile, eating fibres such as fruits and
drinking teas have shown to chelate mercury and thus inhibit its bioavailability (Passos et al.
2003; Canuel et al. 2006) resulting in less mercury taken up by the body.
Methyl mercury exposure is of particular concern because it is a well established human
neurotoxin and the developing fetus is most sensitive to its adverse effects. Methyl mercury is
also classified as a Group C possible human carcinogen (USEPA 2004b). Once exposed to
methyl mercury, humans can show adverse range of health effects with severity highly dependent
on magnitude of dose and duration of exposure. The central nervous system is usually the main
target area when humans are exposed to methyl mercury (Health Canada 2007; Clarkson 2002).
Non-specific symptoms such as paresthesia, malaise and blurred vision are among the earliest
neurological effects for short to long term exposures as well as exposures to high levels of methyl
17
mercury. Other signs such as concentric constriction of the visual field, deafness, dysarthria and
ataxia appear consequently. Methyl mercury poisoning at very high exposures may result in coma
and death (Health Canada 2007). The varying effects from different forms of mercury are as
shown in Table 2.1.
Cases of neurotoxicity of methyl mercury and some fatalities in humans have been reported since
the late nineteenth century. In 1989, The Joint Food and Agriculture Organization of the United
Nations/World Health Organization Expert Committee on Food Additives (JECFA) noted that
developmental neurotoxicity appeared to be the most sensitive endpoint and therefore, pregnant
and nursing mothers were likely to be more susceptible to methyl mercury (Maycock and
Benford 2007). Epidemiological studies have shown that maternal mercury levels were inversely
associated with children scores on neuropsychological tests in some populations of high fish
consumers in New Zealand and Faroe Islands (Davidson et al. 2004; Grandjean et al. 1997).
The body of evidence available to date still suggests that the developing fetus is the most
sensitive sub-population (Health Canada 2007; Grandjean et al. 1997) as methyl mercury readily
crosses the placenta and blood-brain barriers (Myers and Davidson 1998). Fetal exposure to
methylmercury may affect the developing nervous system at substantially lower doses than in
adults. A recent follow-up study of a Faroe Islands cohort, characterized by a diet rich in seafood
and pilot whales, have employed very sensitive neurobehavioural tests to observe subtle
neurodevelopmental effects in children at the age of 14 years. The children display deficits in
motor, attention and verbal tests, indicating that the damage induced by methyl mercury probably
is permanent (Debes et al. 2006). So far, no clear correlation between the effects of methyl
mercury exposure and adverse effects has been demonstrated in young children from a fish-eating
population in the Seychelles (Myers et al. 2003). It has been suggested that adverse effects caused
by methyl mercury may become evident in higher cognitive functions that develop with age
(Debes et al. 2006).
Several studies have reported associations between cardiovascular disease and mercury, in
particular methyl mercury. Guallar et al. (2002) in their study found that mercury concentrations
have a direct relationship with risk of myocardial infarction whereas no such association exist
18
when case-control study were conducted among more than 300 000 health professionals
(Yoshizawa et al. 2002).
2.9
Absorption, distribution and excretion of mercury in humans
Information on the uptake, distribution and excretion of methyl mercury in humans are well
described making it possible to quantify levels in indicator media such as blood and hair to daily
intake as well as estimation of mercury levels in target tissue such as brain (Clarkson and Magos
2006). Methyl mercury is rapidly absorbed from the gastrointestinal tract (Clarkson 1972) and
deposits in various organs including blood, kidney and brain (Swensson and Ulfvarson 1968).
Following absorption from the gastrointestinal tract, methyl mercury binds to red blood cells and
is distributed throughout the body (ATSDR 1999). Approximately 95% of the methyl mercury
ingested is absorbed in the gastrointestinal tract (ATSDR 1999; Clarkson et al. 2003b) and it is
distributed to all tissues in a process completed in 30 hours (Clarkson 2002). Methyl mercury is
able to cross plasma membranes more readily than inorganic mercury compounds, and readily
crosses the blood brain barrier and the placenta (Ask et al. 2002). The blood compartment halflife is approximately 44 days (Nuttall 2004). If an individual’s rate of intake exceeds their rate of
excretion, methyl mercury can accumulate in the body posing a risk of damage to the central
nervous system, cardiovascular system and kidneys (Maycock and Benford 2007; Knobeloch et
al. 2007).
Evidence from earlier research has shown that the high mobility of methyl mercury in the body
which can pass through the blood-brain and placental barriers is due to its lipid solubility
(Aschner and Aschner 1990). However, there is current evidence to suggest that methyl mercury
forms water soluble complexes in body tissues attached to thiol groups in proteins, certain
peptides as well as amino acids (Clarkson and Magos 2006). Kerper et al. (1992) and SimmonsWillis et al. (2002) showed that methyl mercury enters the endothelial cells of the blood-brain
barrier as a complex with cysteine. The high mobility of methyl mercury in the body is due to
the formation of small molecular weight thiol complexes that are readily transported across cell
membranes (Clarkson and Magos 2006). The attachment of methyl mercury to the thiol ligand in
the amino acid cysteine results in a complex whose structure mimics that of methionine as shown
19
in Figure 2.4. As a result, the methyl mercury–cysteine complex enters cells on the neutral amino
acid carriers (Clarkson et al. 2007).
Gluthathione carriers transport methyl mercury out of liver cells into bile as a complex with
reduced gluthathione (Ballatori et al. 1995). The two key processes; entry into the cell as cysteine
complex and exit via the gluthathione pathway are enough to describe the mobility in the body
(Clarkson and Magos 2006). Methyl mercury is eliminated from the body mainly via the fecal
route which accounts up to 90% of total excretion in animal studies (Clarkson and Magos 2006).
After secretion into bile, the methl mercury-gluthathione complex is hydrolysed by gamma
glutamyl-transpeptidase and dipeptidase enzymes to release its constituent amino acids and
methyl mercury as a complex with cysteine (Dutczak and Ballatori 1992). This is then reabsorbed
back into the bloodstream in the gallbladder hence limiting the amount of methyl mercury
entering the gastrointestinal tract (Dutczak et al. 1991).
20
Table 2.1 The major effects of different mercury species
Variable
Route of
exposure
Target Organ
Inorganic
Methyl
mercury
Inhalation
Oral
Oral (from fish
consumption)
Ethyl
mercury
Parenteral
(through
vaccines)
CNS, PNS, kidney
kidney
CNS
CNS, kidney
Bronchial irritation,
pneumonitis2
-
-
-
Metallic taste,
stomatitis,
-
-
Proteinuria3
Proteinuria,
tubular
necrosis
-
Tubular
necrosis
Peripheral neuropathy3
Acrodynia
-
Acrodynia
Paresthesia,
ataxia,
visual and
hearing loss 4
Paresthesia,
ataxia,
visual and
hearing loss
20 days in
adults, 7 days
in infants
Elemental
Local Clinical
Signs
Lungs
Gastrointestinal
tract
Metallic taste, stomatitis,
gingivitis, increased
salivation2
gastroenteritis
Urticaria,
vesication
Skin
Systemic
Clinical Signs
Kidney
PNS
CNS
Approximate
half-life in whole
body
3,
Erethism tremor
-
60 days
40 days
70 days
*CNS: central nervous system, PNS: peripheral nervous system
2
: at (>1000 µg.m-3 of air); 3: at (>500 µg.m-3 of air); 4: at (>200 µg.L-3 of blood)
Reference: Mineralogical Associations of Canada (2005)
21
THE METHIONINE CONNECTION
Figure 2.4 The chemical structure of the complex of methyl mercury with the amino acidcysteine and methionine. Adapted from Clarkson et al. (2007)
2.10
Biomarkers of exposure
The biomarkers of exposure for inorganic mercury are very well different from elemental and
organic mercury. Urine samples are considered the best indicator for long term exposure to
elemental and inorganic mercury (Risher et al. 2002). In cases of acute and higher levels of
exposure to mercury, blood samples are useful as an estimate of recent exposure although not as
reliable as urine samples which are used to indicate total body burden in long term exposures
(Risher et al. 2002). As for methyl mercury, scalp hair is the most suitable and appropriate
biomarker of past exposure (Dakeishi et al. 2005).
Mercury in hair constitutes 80 – 90% of total mercury and is predominantly in the form of methyl
mercury. In general, hair mercury levels are about 250 – 300 times higher than blood mercury
22
levels (IPCS 1990). However, cord blood contains higher mercury concentrations due to binding
to fetal haemoglobin, hence making the difference from hair only about 180-fold (Grandjean et
al. 1992). A few studies have reported the use of urinary mercury levels (Berglund et al. 2005;
Ohno et al. 2007). Nevertheless, mercury levels in urine reflect inorganic mercury and hence
urinary mercury levels are not a useful biomarker to reflect methyl mercury exposure (Berglund
et al. 2005).
Studies conducted for methyl mercury exposure in fish-eating populations conclude that
populations that eat fish are exposed to methyl mercury at higher concentrations compared to
populations of non-fisheaters. In Faroe Islands, the median mercury concentration of maternal
hair is 4.5 µg/g with 27% of the population had above 10 µg/g mercury (Grandjean et al. 1992)
while in the Seychelles an average of 5.8 µg/g of mercury was recorded (Cernichiari et al. 1995).
In the Amazon, communities who rely heavily on freshwater fish have median hair mercury
levels ranging from 5 to 15 µg/g (Cordier et al. 1998; Dorea et al. 2003). High mercury levels in
blood and hair were also reported in Chinese adults and children (Choy et al., 2002; Ip et al.,
2004). The elevated mercury levels are attributed by the consumption of shark fin soup, which is
a popular delicacy among this ethnic group (Choy et al. 2002).
2.11
Mercury in fish
From a human health perspective, the amount of methyl mercury is fairly crucial as compared to
inorganic mercury. Methyl mercury is much more readily absorbed into the human bloodstream
(ATSDR 1999). This is why speciation studies are of paramount importance in determining the
concentration of methyl mercury in fish samples. The United States Environmental Protection
Agency (2004) have stated that sharks, king mackerel, swordfish and tilefish are among predatory
fish with high mercury concentrations (0.73-1.45 ppm of mercury) and these fishes are to be
avoided by women of childbearing age and young children.
The concentrations of mercury in various types of fish and seafood ranging from low to high
mercury are illustrated in Figure 2.5. Several studies have quantified the actual concentrations of
mercury in fish and the mercury levels vary even among fish from the same species. For instance,
Forsyth et al. (2004) found that the percentage of mercury present as methyl mercury in various
23
species of tuna ranged from 61% to 94% whereas Yamashita et al (2005) found methyl mercury
percentage of 70 to 77 in similar samples of fish. Forsyth et al. 2004 also found that ten samples
of swordfish had methyl mercury between 43% to 76% and in three marlin samples, from 51% to
63%. Yamashita et al (2005) in their studies reported similar results with an average methyl
mercury percentage of 72% in seven swordfish samples and 43% in seven blue marlin samples.
The difference in the percentage of methyl mercury in different fish species indicates that methyl
mercury levels are species–specific.
In a study by Groth (2010), he reported the mercury levels on 51 varieties of fish in the United
States market obtained from the United States Food and Drug Administration (USFDA). All the
different fish had varying mercury levels and it was shown that the important source of mercury
in the diet is not necessarily from the fish with the highest mercury levels. In this particular
example, the highest total mercury inputs come from a variety of tuna as well as haddock, hake
and monkfish. Groth (2010) also gave a guideline to consumers for fish with varying
concentrations of mercury namely very low mercury, below average mercury, above average
mercury, moderately high mercury, high mercury and very high mercury to ease consumers in
making sound choices based on known mercury concentrations.
24
Figure 2.5 Varying concentrations of mercury in different types of fish and
seafood (Source: Blanchard J., Sierra Magazine 2011)
2.12
Consumption advisories for mercury in fish
Nutrition, health and diet experts agree on one common thing which is encouraging people to eat
more fish. Fish contains docosahexaenoic acid (DHA), an omega-3 fatty acid which can help to
reduce blood cholesterol, aid in positive pregnancy outcomes as well as improve child
development (Oken et al. 2008). Consumption of fish may also reduce the incidence of heart
disease, stroke and pre-mature delivery (Daviglus et al. 2008; Patterson 2002). Whilst fish
consumption is associated with positive health benefits, methyl mercury seem to counteract the
cardioprotective effects of omega-3 fatty acids (Guallar et al. 2002) as high methyl mercury
levels are adequate to cause adverse health effects to populations consuming large quantities of
fish (Hightower and Moore 2003; Gochfeld 2003). Hence, people who rely heavily on fish for
daily protein intake may be at risk from chronic, high exposure of methyl mercury in addition to
other persistent organic pollutants in the environment (Grandjean et al. 1997).
25
The increasing mercury concentrations measured in fish in recent decades have prompted United
States Food and Drug Administration (USFDA) and United States of Environmental Protection
Agency (USEPA) to issue consumption advisories. The consumption advisory is strictly not a
regulation, it is merely a recommendation issued to help protect public health (USEPA 2013).
The advisory is based on methyl mercury which suggest that pregnant women and women of
childbearing age who may become pregnant should limit their fish consumption (USFDA
2001).They should also avoid eating four types of marine fish which include shark, swordfish,
king mackerel and tilefish as well as limit consumption of all other fish to just 12 oz (342 g) per
week (USFDA 2001). The revised fish consumption advisory by USFDA released in 2004 stated
that five of the most commonly eaten fish that are low in mercury are shrimp, canned light tuna,
salmon, pollock, and catfish which can be safely consumed (USFDA/USEPA 2004a).
Furthermore, USFDA/USEPA (2004a) included that albacore tuna has more mercury than canned
light tuna and suggested that consumers should be aware of what types of fish they consume each
week to ensure their health is not jeopardised from eating contaminated fish.
In addition to the fish consumption advice from USFDA and USEPA, the USEPA recommended
a reference dose (RfD) for methyl mercury of 0.1 µg/kg body weight per day (NRC 2000). These
are based on the evidence for neurodevelopmental toxicity from birth cohort studies from the
Japan and Iraqi methyl mercury tragedy (Oken et al. 2012). Rice et al. (2003) stated that “the RfD
is an estimate of a daily oral exposure to the human population (including sensitive subgroups)
that is likely to be without an appreciable risk of deleterious effects during a lifetime”. A tenfold
“uncertainty factor” is also incorporated by the USEPA to allow for differences in susceptibility,
distribution and elimination (Rice et al. 2003). Nonetheless, Karagas et al. (2012) in a review
paper reported evidence from recent studies in U.S populations whereby childhood
neurodevelopmental effects occur from prenatal methyl mercury exposure even below the RfD.
All fish can be contaminated with pollutants, to a greater or lesser degree. In principle, the more
fish consumed the higher the chance of an individual to be exposed to pollutants. Types and
quantities of fish consumed, the amount of methyl mercury in fish consumed as well as
characteristics of population (such as being female and of childbearing age) are important factors
that determine exposure to methyl mercury. Therefore, the inclusion of a tenfold uncertainty
26
criteria recognizes these factors and hence may reduce consumers’ exposure to methyl mercury in
order to prevent adverse effects on public health.
Besides USFDA/USEPA fish consumption advisories, Joint FAO/WHO Expert Committee on
Food Additives (JECFA) set a provisional tolerable weekly intake (PTWI) of 3.3 µg/kg body
weight for the general population in the year 2000, but highlighted that foetus and infants may be
at a greater risk of toxic effects. Three years after its inception, the PTWI was reduced to 1.6
µg/kg body weight following further risk assessment. This value is considered sufficient to
protect the developing fetus, which is most susceptible to methyl mercury toxicity. The JECFA
committee also considered that if adults were to consume 2 times higher than the existing PTWI
of 1.6 µg/kg body weight, no risk of neurotoxicity would be observed. As for women of
childbearing age, intake should not exceed PTWI in order to protect fetus (UNEP 2013).
With regards to fish consumption advisories envisioned by either USFDA or JECFA, advice
serves strictly as guidance. Personal preference of seafood varieties by individual as well as
tolerance for risk will continue to be the main factors that drive most of consumer’s seafood
choices. Therefore, a person equipped with knowledge on mercury levels in fish may generally
make sounder choices which will then assist in managing risk better than a person with zero
knowledge in this matter (Groth 2010).
2.13
Bioaccumulation of mercury in marine food webs
Mercury deposition rates in lake sediments have increased by a factor of three to five compared
to background values from about 3-3.5/g Hg m-2 year-1 to 10-20 m-2 year-1 (Biester 2007). The
largest contributor of anthropogenic sources of mercury derives from coal-burning power plants
(Pacyna and Pacyna 2002). Being one of the ubiquitous metalloids in the environment, mercury
has the ability to bioaccummulate and biomagnify in food webs (Clarkson and Magos 2006;
Fitzgerald et al. 2007; Ullrich et al 2001). However, bioaccumulation of methyl mercury may be
influenced by seasonal change due to differing ratios of methyl mercury to total mercury in
invertebrates and bioavailability of methyl mercury to organisms (Harris and Bodaly 1998;
Greenfield et al. 2005). For example, methyl mercury concentrations were found to be seasonally
elevated especially in spring and summer within intertidal mudflat surface sediment and
27
sediment-dwelling polychaetes (Nereis diversicolor) of the Scheldt Estuary, Belgium (Muhaya et
al. 1997). This can be attributed to increasing temperatures and higher activities of sulphate
reducing bacteria hence higher methylation rates and higher methyl mercury concentrations in
sediments.
Bioaccumulation is the net uptake of contaminants over time in an organism experiencing
continual exposure (Burgess 2005). The rate of methyl mercury uptake which is greater than the
rate of elimination in body tissue explains why methyl mercury bioaccumulation occurs in
organisms as they grow older (Burgess 2005). There are several biological and environmental
factors which may affect the uptake and accumulation of methyl mercury in aquatic food webs
which include age, body size, dietary preference, trophic position, gender, metabolic rate and
geographic diversity (Weiner et al. 2003; Das et al 2003a). The larger or older the fish and those
feeding at higher trophic levels bioaccummulate and biomagnify more methyl mercury than
smaller fish at lower trophic levels (Weiner et al. 2003). Variations in methyl mercury levels in
fish may also be explained by differences in feeding strategies, mobility, foraging locations as
well as migratory behaviours (Dorea et al 2006).
As bioaccumulation correlates well with increasing organism body size and age,
biomagnification on the other hand demonstrates increment of mercury concentration between
successive consumer levels of the food chain (Pouilly et al. 2012). Secondary predators are
usually expected to possess higher mercury concentrations when compared to the primary
consumers (Pouilly et al. 2012). Meili (1997) reported a two to five fold biomagnification of
mercury from one trophic level to the higher trophic level in temperate ecosystems.
In ecosystems, interactions between organisms occur through complex trophic relationships,
which involve energy and nutrient flow between trophic levels. Hence, in order to comprehend
the ecosystem structure, it is of essential importance to understand trophic relationships besides
quantitative assessment of trophic levels. In relation to this, carbon and nitrogen stable isotope
measurements have been successfully used for determination of potential sources of primary
productivity, as well as for assessing trophic levels in food webs (Das et al. 2003b; Michener and
Kaufman 2007). Carbon and nitrogen isotope analysis is a useful tool for studying
28
biogeochemical cycles and is capable to provide important information about trophic structures
and energy flow through ecological communities (Cabana and Rasmussen 1996, Wada 2009).
As mentioned earlier, trophic relationships are complex and involve not only one species. More
often than not, numerous species of prey and aquatic invertebrates are involved. Researchers
previously inferred the trophic position of organisms from the literature. In recent years, stable
nitrogen isotope ratios have been successfully used in coastal ecosystems which add to
knowledge of trophic ecology in marine ecosystems. The use of stable carbon isotope makes it
possible to understand the relative importance of each carbon source to organisms in food webs
as carbon isotope ratios remain relatively unaffected by trophic transfer. Using nitrogen isotopes,
organisms occupying different trophic levels can be accurately determined (Fry 1991). As
nitrogen enrichment is fairly consistent at each trophic transfer, it provides a quantifiable
determination of relative trophic position within a food web and thus may be correlated with
contaminant concentrations to enable estimation of metal concentrations and rates of
biomagnification (Fisk et al. 2001; Hobson et al. 2002).
Stable isotope analysis particularly the use of the ratio of
13
C/12 C and
14
N/15N as a measure of
trophic status in studies of mercury accumulation has been extensively reported in a variety of
species (Atwell et al. 1998; Bearhop et al. 2000; Kidd et al. 1995; Faye et al. 2011) although
relationship with other metals are less apparent (Camuso et al. 1998; Das et al. 2000). Nitrogen
isotopic signatures (15N/14N) are effective at quantifying the trophic position of an organism
because enrichment of the heavier isotope (15N) occurs incrementally across trophic levels at a
constant rate (~3–4‰; Michener and Kaufman 2007). On the contrary, carbon isotopic signatures
(13C/12C) are consistent across trophic levels (<1‰ change between primary producer and
consumer but are valuable biomarkers for identifying different sources of primary production
(e.g., salt marsh grasses, macroalgae, benthic microalgae, and phytoplankton) (Peterson and
Howarth 1987), and therefore are effective at distinguishing between benthic and pelagic trophic
linkages (France 1995).
29
2.14
Speciation analysis
Total metal analysis has been widely used in measurement of trace metals in biological tissues.
Until recently, it is proven that total metal analysis fails to provide comprehensive analytical
information on elements analysed. As toxicity of metals depends on the chemical forms they are
present at, it is imperative to know what chemical species are contained in a biological sample.
Thus, speciation analysis in recent years has gained much attention over total metal analysis.
According to International Union of Pure and Applied Chemistry (IUPAC), speciation analysis is
defined as “the analytical process of identifying and/or measuring quantities of one or more
individual chemical forms in a sample, and speciation of an element is defined as the distribution
of an element among defined chemical species in a system”.
In terms of the analytical approach, trace element speciation analysis requires a method that
would be both species-selective (able to discriminate between the different species of a given
element) and extremely sensitive since the species of interest usually accounts for only a small
fraction of the total trace element concentration which is often below 0.1 µg/ g (Szpunar 2000).
‘Hyphenated techniques’ which involve coupling the separation of elements of interest with a
sensitive detection method is widely used currently in chemical speciation (Lobinski and Spunar
1999; Kot and Namiesnèik 2000). The most effective instrumental-based techniques for chemical
speciation analysis rely on the use of chromatography mainly gas chromatography (GC) or liquid
chromatography (LC) coupled to a specific and sensitive detector, such as ICP-MS. Compared
with GC, LC is the preferred separation technique used for mercury speciation, because the
mercury species do not need to be derived to volatile compounds before HPLC separation
(Rodrigues et al. 2010).
In speciation analysis, ICP-MS is being used extensively as a detector. Some applications of ICPMS as detector are as shown in Table 2.2. Low detection limit of ICP-MS that is able to detect
down to sub-ng/l allows the detection of ultra trace species in biological and environmental
matrices. The capability of ICP-MS for multi elements detection concurrently enables the
observation of individual isotopes, which permits the use of isotopic-dilution techniques for
30
internal standardization as well as observation of species transformation that may occur during
sample pre-treatment or separation (Alonso et al 2002).
ICP-MS is a powerful tool for determination of elements in the periodic table, but ICP-MS by
itself does not give information on the chemical or structural form of the analytes present. The
chemical form of metal is crucial as it determines toxicity. Hence, ICP-MS has to be utilized in
combination with a highly efficient separation technique in order to address the distribution of an
element in its species.
In spite of the advantages of ICP-MS as a powerful detection tool in chemical speciation, there
are a number of difficulties encountered when ICP-MS is coupled with HPLC. Organic solvents
in high concentrations may cause instability of plasma plus accumulation of carbon deposit on
the sampling cone (Taylor et al. 1998). The addition of oxygen to the nebulizer gas flow,
increasing the plasma RF power or using a platinum sampling cone can alleviate the problems to
a certain extent (Larsen 1998). Sample matrix is another common problem associated in dealing
with hyphenated techniques. As biological and environmental samples contain complex matrices,
the use of buffer with high ionic strength is required when HPLC is utilised. High salt
concentrations may suppress signal in ICP-MS as a result of amplified space-charge effects
which defocus the ion beam (Horlick and Montaser 1998). Problems with matrix in the ICP can
be improved by altering argon gas flow rates, performing sample pretreatment, modifying
interface configurations and voltages of by post-column dilution (Niu and Houk 1996).
Prior to determination of samples with HPLC-ICP-MS, one crucial step that needs to be taken
into account is sample preparation. Samples that are in solid form have to be converted into
liquid before analysis. The traditional extraction methods include acid leaching (Westőő 1966),
alkaline digestion (Bloom 1992) and steam distillation (Collett et al. 1980) which often involved
complicated procedure, low efficiency, high consumption of solvents and loss of mercury during
pretreatment. In addition, various extraction techniques such as distillation, acid and alkaline
extraction demonstrated the tendency to form artifactual methyl mercury from inorganic mercury
during sample preparation (Hintelman et al. 1997). Of late, extraction using microwave (Rahman
et al. 2008) as well as ultrasound assisted extraction (Batista et al. 2011) have been used to
31
extract mercury species. After extraction, most of the methods need a further derivatization
treatment or pH adjustment of the extracted solution prior to injection into HPLC. In order to
avoid some of the aforementioned limitations, alternative extraction procedures have been
suggested with reagents containing thiol ligands, such as mercaptoethanol (Meng et al. 2007), or
L-cysteine (Chiou et al. 2001) as well as enzymatic hydrolysis (Rai et al. 2002) which have
shown to separate mercury species effectively.
2.15
Metal-binding proteins
Metal ions play an important role in biological activity by which the studies of these metallic ions
leads to understanding of the toxicity as well as biochemical impact on living organisms.
Majority of the metal ions are bound to specific proteins or enzymes and exert their effects as
active or structural centres of proteins (Garcia et al. 2006). Approximately, about 30% of proteins
and enzymes which are present in a biological system contain metal or metalloid ions in their
structures and about 40% of these elements are essential to maintaining protein biological
functions (Sussulini and Becker 2011).
Novel developments and improvements in analytical instrumentation and methodologies
observed in the last decades have significantly boost the ability in the identification and
quantification of metals and metalloids bound proteins, hence the introduction of metallomics as
a new research field (Szpunar 2005; Qin et al. 2011). Metallomics is defined as the
comprehensive analysis of the entirety of metal and metalloid species within a cell or tissue type
(Sussulini and Becker 2011; Lobinski et al. 2010). From a biomedical perspective, metallomics
enable the investigation on how metals bind to biomolecules, characterize metalloproteins and/or
metalloenzymes allowing studies on the mechanisms of enzymatic and biochemical reactions as
well as providing measures to investigate the pathophysiological mechanism of diseases (Qin et
al. 2011). With the increasing applications of metallomics in a wide variety of fields which are
not limited only to medicine, biochemistry andelemental speciation among others, it is not
surprising that metallomics are becoming one of the topics of highlight among researchers
worldwide (Ferrarello et al. 2002; Hasegawa et al. 2005; Huang et al. 2005; Hauser-Davis et al.
2005; Gonzalez-Fernández 2011).
32
In recent years, more sophisticated methods for investigation of metal(oid) and its species are
widely explored. In general, the methods usually involve one or more separation steps to isolate
the biomolecules of interest or eliminate disturbing matrices. It is vital that the integrity of metal
complexes before and during identification/determination is assured when investigation of
biomolecules and their interaction is conducted. Hence, to avoid misinterpretation of analytical
results, knowledge with regards to potential alterations of sample is of major importance (Mesko
et al. 2011). In metalloproteomics, the analytical strategies which are commonly applied are that
the proteins firstly have to be separated from sample of interest and later metals or metalloids
bound to protein are detected using mass spectrometry (MALDI-, ESI- of FTICR-MS) to obtain
the structure, dynamics and functions of metal-protein complexes (Sussulini and Becker 2011).
Separation of protein can be achieved by techniques such as capillary electrophoresis (CE), liquid
chromatography (HPLC) or polyacrylamide gel electrophoresis (PAGE). Figure 2.6 depicts the
diagram elucidating typical steps required to obtain proteomics information in a biological
system.
33
Sample
Seawater (MeHg)
Column
Alltima HP C-18 3 µm
(Reverse Phase)
Mobile phase
0.5% (m/v) L-cysteine;
0.05% v/v 2mercapthoethanol
Detection
HPLC-ICP-MS
Reference
Cairns et
al. (2008)
Fish and hair
certified reference
material (MeHg)
Advanced Chromatography
Technologies ACE 3 C-18
1 : 1 methanol: water (v/v)
containing 0.01% 2mercaptoethanol
HPLC-ICP-MS
Vidler et
al. (2007)
Seafood (Hg,
MeHg)
Synergi Hydro–RP,
C-18
0.1% w/v L-cysteine +
0.1% w/v Lcysteine·HCl·H2O
HPLC-ICP-MS
Hight and
Cheng
(2006)
Fish samples
(MeHg)
Gemini C-18
2.5 mmolL−1 L-cysteine,
12.5 mmolL−1
(NH4)2HPO4, 0.05%
triethylamine
HPLC-ICP-MS
Santoyo et
al. (2009)
Fish samples
(MeHg)
Synergy Hydro RP18
HPLC-ICP-MS
Wang et al.
(2013)
Chicken liver (Hg,
Se)
Biosep-SEC-2000
25 mMTris-HCl–50
mMKCl
SEC-ICP-MS
Legume seed
extracts (Cu, Zn)
Superdex
75 HR 10/30 column
0.02 mol l−1Tris–HCl
SEC-ICP-MS
Cabańero
et al.
(2005)
Mestek et
al. (2002)
Carp cytosol
(Metallothioniens)
SUPELCO TSK gel G 3000
30 mmol l-1Tris-HCl
SE-HPLC-ICPTOF-MS
Infante et
al. (2004)
Mytilus edulis
cytosol (Al, Ca, V,
Cr, Mn, Fe, Co,
Ni, Zn)
Cerebrospinal
fluid (CSF)-Trace
elements
Sephadex G-75
10 mMTris.HCl- 5 mM 2mercaptoethanol -0.1
mM PMSF–25 mMNaCl
SEC-DF-ICP-MS
Ferrarello
et al.
(2002)
Superdex 75 (10/300GL)
0.02 M Tris with 65%
HNO3
SEC-HR-ICP-MS
Gellein et
al. (2007)
0.1 % L-cysteine and
0.1 % L-cysteine·HCl
Table 2.2 Applications of hyphenated technique using ICP-MS as detector
34
Figure 2.6 Illustrative diagram of typical analytical steps involved to obtain comprehensive
metalloproteomics information
Reference: Sussulini and Becker (2011)
2.16
Separation of proteins
2.16.1 Polyacrylamide gel electrophoresis (PAGE)
Proteins can be separated from one another on the basis of solubility, size, charge and binding
ability (Berg et al. 2007). Polyacrylamide gel electrophoresis (PAGE) is by far the most
extensively used method for protein separation due to its high resolving power and good
reproducibility (Sussulini and Becker 2011; Garcia et al. 2006). Electrophoresis was initially
introduced in 1930 by a Swedish chemist, Arne Tiselius where his investigation in chemistry of
serum proteins led to the development of specialized devices and hence the methodology of
electrophoresis (Garcia et al. 2006).
35
In electrophoresis, electric field is applied to separate charged species and electrophoretic
separation are usually conducted in gels as the gel serves as a molecular sieve that enhances
separation (Berg et al. 2007). The charged species can be produced by either dissociation
reactions of amino and carboxylic groups or by uniform coating of proteins with anionic
surfactant such as sodium dodecyl sulfate (SDS) (Garcia et al. 2006). SDS is a detergent which is
used as a reducing agent, by which detergents disrupt the cell membranes, breaking lipid–protein
interaction and consequently, solubilizing the metal-binding proteins and preventing hydrophobic
interactions (Mesko et al. 2011). Combination of SDS protein treatment with PAGE is known as
SDS-PAGE, which was originally described by Laemmli (1970) which is used to determine
molecular weights of polypeptide in protein samples (Mesko et al. 2011). Smaller proteins move
rapidly through the gel compared to the larger proteins. Once the electrophoresis is completed,
the proteins in the gel is stained using either silver or Coomassie blue which reveals a series of
bands (Berg et al. 2007).
2.16.2 Size exclusion chromatography (SEC)
Chromatography techniques allow purification of biomolecules that are separated according to
differences in their specific properties. Properties of proteins such as size can be purified using
gel filtration or also known as size exclusion. Similarly, other properties of protein like charge
can be purified using ion exchange chromatography while reverse phase chromatography (RPC)
may well purify proteins according to hydrophobicity.
Gel filtration is by far the simplest and mildest of all chromatography techniques and separates
molecules on the basis of differences in size. Contrary to ion exchange or affinity
chromatography, buffer composition does not directly affect resolution (how well peaks are
separated between each other) as molecules do not bind to the chromatography medium (Szpunar
2000). In SEC, samples are eluted isocratically, which means that the same buffer can be used
throughout the entire separation without the need to have different buffer. As the name implies,
molecules are separated solely on the molecular weights or size. Larger molecules are eluted first
leaving smaller molecules that diffuse into the pores of the column and delayed in their passage
down the column eluting last (Berg et al. 2007).
36
Various hyphenated techniques in metal speciation studies have been conducted successfully
using HPLC (Weiyue et al. 2011) or electrophoresis with atomic spectrometry (Sanz-Medel et al.
2003). Among the emerging hyphenated techniques, size exclusion chromatography (SEC)
coupled with ICP-MS offers unique advantages for studying metal-containing proteins. Among
the advantages are isolation of proteins can be achieved by means of isocratic elution with
aqueous mobile phase containing a low salt concentration which is tolerable to ICP-MS and can
be injected directly to the nebulizer. This ensures good long-term stability of ICP-MS signal
(Mestek et al. 2002). Additionally, evaluation of protein size can be measured using a calibration
curve of standard proteins (Wang et al. 2007b). One of the main challenges in obtaining accurate
and reliable quantification of species analysed is the instabilities of ICP-MS particularly signal
shift and matrix effects (Wang et al. 2007b). The instrument instabilities can be overcome by
using isotope dilution analysis (IDA) which is based on the measurement of isotope ratio
(Rodríguez-González et al. 2005).
Numerous studies have been reported in the literature regarding the application of size exclusionbased chromatographic separations in combination with ICP-MS (Table 1). The fractionation of
trace metals which are bound to biomolecules of different size in cytosols have been studied in
marine invertebrates, fish, legumes, human brains as well as rat brains (Ferrarello et al. 2000;
Infante et al. 2002; Mestek et al. 2002; Richarz and Brätter et al. 2002; Wang et al. 2008). Yun et
al. (2013) characterized mercury-containing protein in human plasma using two dimensional
HPLC and SEC. Due to the presence of mercury-containing molecules which are often detected
at ultra-trace level in biomedical samples, isotopic tracer method with its unique merits of high
sensitivity, high selectivity and free of interference coupled with SEC and isotope dilution ICPMS has been studied in maternal rats and their offsprings by Shi et al. (2007). The isotopic tracer
method has ben shown to improve detection sensitivity as well as eliminate ‘artefact’ species due
to ‘strong’ memory effect which are commonly observed in trace element speciation studies
especially when dealing with mercury.
2.17 Protein characterization and identification
The vast development in protein analysis in recent years enables a more sophisticated technique
to be employed along with the modern analytical tool in protein characterization and
37
identification. Determination of protein masses with high accuracy is now possible of up to one
mass unit or less in favourable cases due to modifications to the well-established technique of
mass spectrometry (Berg et al. 2007). In comparison with classical methods for peptide
sequencing such as Edman degradation (Edman 1949), mass spectrometry truly offers heaps of
advantages. For instance, only a small amount of sample is needed for peptide identification
(several femtomole instead of µmol) as well as shorter time of analysis (several minutes instead
of hours) (Garcia et al. 2006).
The mass spectrometry technique is based on the generation of charged atomic or molecular
species, which are then separated in a mass analyser according to mass to charge ratio (m/z). The
number of ions of a particular mass to charge ratio are counted by a detection system which
subsequently produces a mass spectrum (ion intensity versus m/z) or to obtain intensity profile
for one or various m/z ratios during a chromatographic run (Berg et al. 2007; Garcia et al. 2006)
hence significant structural information can be acquired. The ionization of molecules is formed
by inducing a gain or loss of charge through electron ejection, deprotonation or protonation
(Garcia et al. 2006). The most common ionization techniques in biomolecule analysis are matrix
assisted laser desorption/ionization (MALDI) and electrospray ionization (ESI).
Dihazi et al. (2001) used aldolase from rabbit muscle in 10% SDS-PAGE and optimized the ingel digestion protocol prior to MALDI-TOF (time of flight) analysis. The mass spectrum of the
aldolasetryptic digestion obtained from the dried gels showed no significant differences in
comparison with the moist gel hence enabling the identification of proteins by MALDI-TOF-MS
analysis using proteins obtained during earlier work or conserved in dried polyacrylamide gels at
room temperature for years. In addition, proteomic analysis study investigating the molecular
mechanism of human brain aging and associated brain disease was conducted by Chen et al.
(2003) using young and old human brain tissues, separating by 2D gel electrophoresis prior to
MALDI-TOF-MS analysis. It was observed that five protein spots were found down-regulated in
older brains although protein expressions did not differ significantly.
38
2.18
Metallothioneins
Metallothioneins (MTs) were first discovered in 1957 by Margoshee and Valee as newly
identified proteins isolated from a horse renal cortex tissue (Ryvolova et al. 2011). MTs widely
occur in different classes of organisms and have been isolated and characterized from fungus,
yeasts, plants, crustaceans as well as mammals. MTs are non-enzymatic proteins with low
molecular weight, high cysteine content, no aromatic amino acids and are heat stable. The high
cysteine content present in MTs provides these proteins with a high affinity for different divalent
metals because of the presence of reactive sulfhydryl (-SH) in their amino acid structure (Wanick
et al.2011). MTs can strongly bind with essential (Cu, Zn) or non-essential metals (Hg, Cd, Ag).
Binding capacity of MT is 7 and 12 atoms for divalent and monovalent ions, respectively
(Ryvolova et al. 2011).
There are many isoforms of MTs that forms different structural MT classes due to the alignment
of Cys-Cys, Cys-X-Cys and Cys-X-YCys sequences where X and Y are amino acids other than
cysteine (Amiard et al. 2006). Four different isoforms designated MT-1 to MT-4 have been found
in mammals. MT-1 and MT-2 are present in all organs, MT-3 is expressed mainly in brain but
also in hearts, kidneys and reproductive organs and MT-4 is most abundant in certain stratified
tissues (Vasak 2005, Ryvolova et al. 2011).
The physiological roles of MTs have been disputed for quite some time and remain a
controversy. However, it is recognized that MTs play a key role in detoxification of metals by
strongly binding to metals and reducing its availability in ionic (or other low molecular weight
exchangeable) form in the cytoplasm (Wang and Rainbow 2010). MTs are also important in
regulating the homeostasis of essential metal in metabolism such as donating Cu or Zn to
appropriate receptor molecules (Brouwer et al. 2002) or in metal elimination (Roesijadi et al.
1982; Viarengo and Nott 1993). MTs can also perform several additional specific tasks such as
metal ion reservoirs, metal transport and/or metal delivery to target metalloproteins (Feng et al.
2005) as well as protection against ionizing radiation (Cai et al. 1999).
On the other hand, the capacity of the thiol groups to be oxidized by mild oxidizing agents would
facilitate their role as a first defense against oxidative stress (Kumari et al. 1998). Hence, MTs are
39
capable of reacting with ROS (reactive oxygen species) and RNS (reactive nitrogen species)
scavenging (Yoshida et al. 2005) thus protecting the most vulnerable cell components, such as
DNA, proteins, and lipid membrane structures as a result of the induction of MT which seems to
limit the effects of hydroxyl (OH) and superoxide (O2−) radicals (Amiard et al 2006).
2.19
Concluding Remarks
Being one of the ubiquitous metals which exist in the environment along with its multi-functional
uses in a variety of fields, mercury continues to be the element of interest by many researchers.
With its ubiquitous nature originating from fossil fuel such as coal and petroleum as well as
predominant sources like volcanoes, anthropogenic sources particularly from coal combustion
and gold mining intensify mercury emission into the environment. These combined emissions
from natural and anthropogenic sources contribute significantly towards global mercury
emission. Since pre-industrial times, atmospheric mercury emissions have increased considerably
by 20-fold and almost 70% of the total emission derives from man-made sources (Schuster et al.
2002).
Mercury is highly toxic as different forms of mercury (elemental, inorganic or organic mercury)
exhibit different effects to flora and fauna. Through processes such as biogeochemical cycling of
mercury, methylation as well as demethylation of mercury, mercury tends to have a long
residence time in the environment and finally works its way into the aquatic system. Perhaps the
most toxic form of mercury to human is from the consumption of fish which are contaminated
with methyl mercury. This was clearly portrayed in the Minamata Disease episode occurred in
the 1950s which was an example of organic mercury toxicity in fish. The discharge from a
factory contained inorganic mercury which was methylated by bacteria which were later ingested
by fish and finally ate by humans. Local residents who consumed the fish began to demonstrate
signs of neurologic damages and more importantly babies exposed to methyl mercury from
pregnant mothers were severely affected. As mercury was also discovered in the breast milk of
the mothers, the babies’ exposure to methyl mercury continued after birth.
The World Health Organization (2002) reported that the global average apparent per capita
consumption of fish has increased from 9 kg per year in early 1960s to 16.3 kg in 1999. This
40
figure evidently shows that fish is a preferred choice of protein and demands have been
increasing tremendously worldwide. On the same token, the Food and Agriculture Organisation
(FAO) stated that Malaysia is one of the top-fish consuming countries in Asia (above 40
kg/capita/year) which is almost double the average in Thailand and China, albeit below the levels
in Japan and South Korea (Teh 2012). Bearing the statistics in mind, it is vital to assess the levels
of heavy metals (particularly mercury and other metals) in fish to ensure that the supply of cheap
protein is fit for human consumption. As different forms of mercury may reveal differing
toxicities and mobilities in the environment, it is clearly of prominence to be able to distinguish
between the individual species present in selected fish species through speciation studies.
The levels of heavy metals in fish are influenced by several biological and environmental factors
which include age, body size, dietary preference, trophic position, habitat, gender, metabolic rate
and geographic diversity (Weiner et al. 2003; Das et al 2003b). Fish at higher trophic level
bioaccummulate more mercury and hence are expected to contain more mercury than fish at
lower trophic levels. Body size or length of organisms correlates well with mercury
concentrations and older fish usually have higher mercury concentrations than younger ones.
Likewise, benthic fish are predicted to have higher mercury concentrations than pelagic fish as
they live in close association with sediments compared to pelagic fish. Similarly, females tend to
have higher mercury concentrations than males as higher energy intakes are associated with the
reproduction process involved in female organisms.
Speciation study of mercury only measures mercury species without taking into account the
chemical form of methyl mercury as methyl mercury may be bound to peptides, proteins or other
potential binding partners. Hence, hyphenated techniques coupling ICP-MS with HPLC as well
as SEC are becoming a widely used technique in determining the presence of metals bound to
macromolecular ligands. Protein separation can also be conducted using SDS-PAGE and further
identified by mass spectrometry such as MALDI or ESI-MS. Although investigation of
metalloproteins is often complex and complicated, the rapid advances in mass spectrometry and
analytical chemistry over the last few decades has in a way helped to overcome the lack of tool
available and thus ease the analysis in metalloproteomics.
41
CHAPTER 3
THE ASSESSMENT OF TOTAL MERCURY AND METHYL MERCURY IN FISH
TISSUES FROM WEST PENINSULAR MALAYSIA
3.1 INTRODUCTION
Mercury contamination in aquatic and terrestrial ecosystems is an environmental problem
worldwide (Avila et al. 1998; Glasby et al. 2004). Mercury is a known human neurotoxin and has
traditionally been used in medicine, cosmetics, paint, laboratory equipment, fungicides as well as
tooth fillings (Clarkson et al. 2003a). Mercury is ubiquitous in the environment and can be found
either naturally (geothermal process, biomass burning, volcanoes) or anthropogenically (coalfired utility plants, gold mining operations, waste incineration and discharge from chlor-alkali
and cement production) (Wang et al. 2004; Selin 2009; Sloss 2012, UNEP 2013). The airborne
mercury particles from atmospheric sources that reach aquatic systems through rainfall can be
converted to methyl mercury, the toxic form of mercury by means of microbial process and
adherence to sediment particles (Sunderland 2007). Bioaccumulation and biomagnification at
each trophic level occur when large predator fish at the top trophic level have relatively high
methyl mercury concentrations than smaller non predatory fish in the food chain (Morel et al
1998; Orihel 2007).
Fish are widely recognised as a major and cheap source of protein providing essential fatty acids;
docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA) which aid to reduce cholesterol
levels and incidence of heart disease (Daviglus et al. 2002). The omega-3 poly-unsaturated fatty
acids supplied by some fish and shellfish are important for prenatal development of the brain and
visual system (Daniels et al. 2004). Fish consumption may also reduce the risk of Alzheimer’s
disease (Morris et al. 2003). Although eating fish is beneficial to human health, human exposure
to mercury can occur primarily through consumption of fish and is a public health concern
worldwide (Mahaffey 2004). About 95% of the methylmercury in ingested fish is absorbed into
the bloodstreams of humans and within 6 hours, peak blood methylmercury concentrations are
reached (National Research Council 2000; JECFA 2006). Methylmercury is able to cross plasma
membranes more readily than inorganic mercury species and readily crosses the blood-brain
barrier and the placenta (Maycock and Benford 2007). Low-dose mercury exposure in fetuses,
43
infants and children is associated with developmental delays, learning disabilities and possibly
behavioural problems (Budtz-Jorgensen et al. 2002).
In Malaysia, fish have always been a popular choice of protein for the majority of the population
compared to other sources of protein such as pork, chicken, beef and mutton (Abdullah and
Baharomshah 1999). Statistics in the year 2000 showed that per capita food supply from fish and
fishery products is 58 kg per person (Nurnadia et al. 2011). A report from the Malaysian Adult
Nutrition Survey (MANS) conducted in 2008 stated a high prevalence of daily consumption of
marine fish among rural and urban adults at 51% and 34% respectively (Norimah et al. 2008).
Metal concentrations in fish and other biota has been reported in different coastal areas in
Malaysia (Yap et al. 2008; Agusa et al. 2005) as well as from local wholesale markets in
commonly consumed fish (Hajeb et al. 2009). Factors influencing heavy metal concentrations in
fish are size and length of fish, age, diet, trophic levels, food habit as well as environmental
parameters (e.g pH, temperature) and the accumulation of other metals (Fairey et al. 1997; Burger
et al. 2001, Bidone et al. 1997). In general, metal concentrations in fish increase with size and
length (Trudel and Rasmussen 2006; Sonesten 2003) although it is not always the case (Stafford
and Haines, 2001). Fish from the top of the food chain (predatory) usually have higher metal
concentrations compared to non-predatory fish (Morel et al. 1998). Some metals tend to
accumulate concentrations in fish while others ameliorate the effects of metals. For example,
selenium is known to counteract the negative effects of cadmium and mercury (Rooney 2007;
Jones et al. 2013).
Stable isotope analysis has been used to obtain information on the feeding ecology of marine
species. Estimation of the trophic level of a food chain can be done by utilising the nitrogen
isotopes by which 15N value typically increases about 3‰ with every increasing trophic level
within a food chain (Hobson and Welch 1992; Minagawa and Wada 1984) as opposed to about
1‰ in the 13C value (DeNiro and Epstein 1981). Additionally, carbon isotopes can be used to
provide an estimation of the relative contributions to the diet of various organic carbon sources
(Kelly 2000) indicating aquatic versus terrestrial, pelagic versus benthic or inshore versus
offshore to food intake (Hobson et al., 1995; Dauby et al., 1998). Besides the ability to obtain
44
food web structures, the variation in stable isotope ratios of carbon and nitrogen has been utilised
as a useful tracer of energy flow as well as estimation of biomagnification of contaminants in
marine and freshwater ecosystems (Jarman et al. 1996; Atwell et al. 1998; Bargagli et al. 1998;
Quinn et al. 2003; Dehn et al. 2006). In general, organisms at the top of the food web have higher
15N values relative to their prey with carnivores expected to be occupying the highest trophic
level (Atwell et al. 1998; Nfon et al. 2009).
Consumption of fish and seafood is the major route of exposure to mercury in humans (Clarkson
2002) with top predator fish containing considerably elevated concentrations of mercury (Kaneko
and Ralston 2007). Realizing the importance of fish as a commodity among Malaysian
population, it is vital to assess the levels of mercury and methyl mercury in fish in order to ensure
that these nutritious foods can be safely consumed by the public and not posing significant health
risk. Guidelines for mercury concentrations in predatory fish are 1.0 µg/g wet weight while for
non-predatory fish are 0.5 µg/g wet weight (JECFA 2006; Malaysian Food Regulations 1985).
Hence, the specific objectives of this study are: (1) to characterize the trophic position of
commonly consumed fish in West Peninsular Malaysia through nitrogen and carbon stable
isotope analysis, (2) to determine the concentrations of mercury and methyl mercury in
commonly consumed fish in West Peninsular Malaysia, (3) to assess if there are differences in
mercury and methyl mercury concentrations between organisms of different trophic levels (4) to
determine if difference in mean concentrations of mercury exists between benthic and pelagic
fishes, (5) to investigate whether older fish have higher mercury and methyl mercury
concentrations than younger fish, (6) to investigate if biomagnification of mercury is occurring in
organisms across trophic levels, (7) to compare mercury concentrations with maximum allowable
limits stipulated by various international bodies, (8) to compare the Provisional Tolerable Weekly
Intake (PTWI) for Malaysian population with existing PTWI outlined by JECFA.
45
3.2
MATERIALS AND METHODS
3.2.1 INTRODUCTION
This study is part of a larger study entitled “Exposure assessment of contaminants from
consumption of seafood in Peninsular Malaysia” (Nurul Izzah 2009). A total of eleven sampling
sites from 10 different states were selected in the study. For this study, however only a few sites
were selected which will be explained in subsequent sections.
3.2.2 SELECTION OF SITES
This study comprised two major sites which were main fish complexes and wholesale markets.
Main fish complexes are referred to complexes which accept and market the fish and seafood
whereas wholesale markets are where the fish and seafood are sold to consumers. Selection of
sites was decided upon after discussion with personnel from Marketing Department of Malaysian
Fisheries Development Board to determine the major landing sites for fish and seafood in
Peninsular Malaysia.
All fish and seafood for this study were obtained from West Peninsular Malaysia. A total of three
different sites were selected namely M1, M2 and L1 (Figure 3.1). M1 and M2 were sites
comprising wholesale markets in Perak and Selangor respectively while L1 was from fish landing
site in Selangor.
Visits to fish complex and wholesale markets were conducted between June to December 2009.
Fish and seafood at the fish complex were obtained according to the time the fish landed at the
fish complex while purchase of fish at the wholesale markets was done between 12 am to 2 am.
3.2.3 COLLECTION OF FISH AND SEAFOOD
A total of 111 composite samples from 45 different species of fish and seafood were obtained
from fish complex and wholesale markets. The selection of fish and seafood were based upon the
results of food dietary survey conducted among 3536 subjects in Peninsular Malaysia (Nurul
Izzah 2009). Table 3.1 shows the most commonly consumed fish among Malaysians obtained
from the dietary survey.
46
Figure 3.1 Map of fish complexes and wholesale markets in West Peninsular Malaysia
Table 3.1 The most preferred seafood consumed among Malaysians based on dietary survey in
Peninsular Malaysia (reprinted from Nurul Izzah 2009)
Types of seafood
Mackerel
Prawn
Yellow tail scad
Black pomfret
Tuna
Hair-tail scad
Spanish mackerel
Squid
Red snapper
Threadfin bream
Stingray
Catfish
Barramundi
Croaker
Frequencies (%)
70.9
26.6
26.2
22.6
21.8
20.9
20.9
21.3
14.7
11.2
10.6
7.3
7.2
5.4
47
3.2.4 LABORATORY ANALYSES
3.2.4.1 BIOMETRIC MEASUREMENTS OF FISH AND SEAFOOD
All fish and seafood obtained were recorded for length. The overall measurement of fish was
taken from the snout on the upper jaw to the end of the tail. Squids and octopus lengths were
measured from its arms to the fin whereas shrimps and prawn length were recorded from the
distance of the posterior edge of the eye orbit to the posterior end of the telson.
3.2.4.2 SAMPLE PREPARATION
All samples were delivered in the ice box for transport to the laboratory. Only edible portions of
fish and seafood were used for analysis. Hence, samples were filleted, homogenized and wrapped
in aluminium foil before being inserted into labeled plastic bags. For fish with scales, the scales
on fish were removed prior to filleting. Similar to prawns and shrimps, the outer shells were also
removed. Samples which have been wrapped and labeled were kept in freezer at -20◦C until
further analysis. All samples received from Malaysia were freeze dried and ground into fine
powder using a mill before being put into 50 ml polypropylene tubes and sent to Australia by
courier service.
3.2.4.3 ANALYSIS OF CARBON AND NITROGEN STABLE ISOTOPES
The samples for stable isotope analysis were analysed at the Water Studies Centre (Monash
University) on an ANCA GSL2 elemental analyser interfaced to a Hydra 20-22 continuous-flow
isotope ratio mass-spectrometer (Sercon Ltd., UK). The precision of the elemental analysis was
0.5 µg for both C and N (n = 5). The precision of the stable isotope analysis was ±0.1‰ for δ13C
and ±0.2‰ for 15N (SD for n=5). Stable isotope data are expressed in the delta notation (δ13C
and δ15N), relative to the stable isotopic ratio of Vienna Pee Dee Belemnite standard (RVPDB=
0.0111797) for C and atmospheric N2 (RAir = 0.0036765) for nitrogen.
3.2.4.4 MEASUREMENT OF TOTAL MERCURY CONCENTRATIONS
Total mercury concentrations in fish samples were determined by nitric acid digestion. A total of
0.07 g of freeze-dried fish sample was weighed into 7 ml polytetrafluroacetate digestion vessels
(A.I. Scientific Australia) and 1 ml of concentrated nitric acid (Aristar, BDH, Australia) added.
Samples were digested at 600 W for 2 min, 0 W for 2 min and 450 W for 45 min (Baldwin et al.
48
1994). After cooling, digests were diluted to 10 ml with de-ionised water (Milli Q, Millipore,
Australia) in 10 ml polyethylene vials (Sarstedt, Australia). Total element concentrations and
mercury in digests and enzyme extracts acidified to 1% with nitric acid (Aristar, BDH, Australia)
were measured by ICP-MS (Maher et al. 2001). External calibration standards used for
quantitation were made up from a 10 mg/L Reference Standard, ICP-MS Calibration Multi
Element Standard 2 (AccuTrace ™) in 1% (v/v) HNO3 acid as 0.1, 1, 10 and 100 mg/L solutions.
3.2.4.5 MEASUREMENT OF METHYL MERCURY CONCENTRATIONS
Methyl mercury was measured in fish and seafood samples according to method by Rai et al.
(2002). Fish muscle tissues were freeze-dried for approximately 24 h (Labconco, Australia) and
ground to a homogenous powder using a ZM 100 ultra-centrifugal mill. Freeze-dried samples
(0.2 g) were weighed into 5 ml glass culture tubes with 20 mg of protease type XIV (Sigma,
Australia) and 8 ml of phosphate buffer (pH 7.5) containing 0.05% cysteine. The tubes were
incubated for 2 hours in a hybridisation oven (XTRON HI 2002, Bartlett Instruments) at 37C
with rotation of samples at 20 rpm. Extracts were transferred to acid washed 10 ml polypropylene
centrifuge tubes (Sarstedt, Australia), made up to a final volume of 10 ml with buffer and
centrifuged for 20 min at 3000 rpm. Supernatants were filtered through Acrodisc LC 13-mm
Syringe filter with 0.2 mm PVDF membrane (Gelman, USA) before analysis.
3.2.5 STATISTICAL ANALYSIS
In order to use parametric tests, the assumptions of normality and homogeneity of variances were
checked by examining plots of residuals. If the residuals were not normally distributed, data were
log transformed and parametric tests were used. A one-way ANOVA was used to determine if
there was significant difference between log-transformed data for mercury concentrations with
trophic levels (omnivores, carnivores, secondary carnivores). A post-hoc Tukey test was then
performed to identify trophic groups that differed significantly (p<0.05). Linear regression
models were used to determine (1) the relationships between mercury concentrations in fish with
size and (2) the relationships between 15N and log-transformed mercury concentrations. T-test
was used to compare mean of mercury between habitat (benthic and pelagic). Statistical analysis
for all data was executed using IBM SPSS Statistics Version 21. A p value of less than 0.05 was
considered to indicate statistical significance in this study. For data points that are statistically
49
inconsistent with the rest of data, the modified Thompson Tau technique is used to determine
whether to keep or discard outliers at 95% confidence level.
3.2.6 CLASSIFICATION OF SPECIES
For the purpose of data analysis, all species were classified into two different categories namely;
trophic levels and habitat. For trophic levels, species were classified into three different trophic
levels which were omnivores (organisms feeding on both plant and animal materials), carnivores
(organisms feeding on omnivores) and secondary carnivores (organisms which consume
carnivores). As for feeding mode, species were classified according to benthic (organisms which
are usually found on the sea floor) and pelagic (organisms living near the surface of water).
Classification of fish and seafood according to their feeding behaviour was conducted based on
information obtained from www.fishbase.org and Mansor et al. (1998).
3.3
RESULTS
3.3.1 Quality assurance of analytical results
The accuracy of the test method was determined by repeated analysis of certified reference
materials, DORM-2 (Dogfish muscle) from National Research Council Canada. The results for
the analysis of CRM are presented in Table 3.2. These compare well to certified value for total
mercury concentration and attest to the accuracy of the method.
Table 3.2 The mean certified and measured values of mercury and methyl mercury (MeHg)
concentrations (mean ± standard deviation) in µg/g dry mass in certified reference material
DORM-2
Element
Hg
MeHg
DORM-2
Certified value
4.64 ± 0.26
Measured value
4.87 ± 0.51 (n=21)
4.47 ± 0.32
4.78 ± 0.04 (n=6)
50
The calibration curves generated for total Hg and MeHg determination were highly linear (r 2 >
0.999). The limit of detection (3 times the standard deviation of procedural blank values) for total
Hg measurements was 0.05 μg/L (equivalent to approximately 70 μg/kg dry mass in tissue). The
limit of detection for MeHg concentrations was 0.1 μg/g wet mass (equivalent to approximately
50 μg/kg dry mass in tissue).
3.3.2 Nitrogen and carbon stable isotopes
The nitrogen and carbon stable isotopes analysis were used to confirm the assignment of fish to
trophic groups namely omnivores, carnivores and secondary carnivores. The structure of
organisms based on stable nitrogen and carbon isotope analysis with species associated with it is
shown in Figure 3.2.
51
δ15N
15N
Secondary carnivore
Carnivore
Omnivore
13C
Figure 3.2 The structure of organisms based on stable nitrogen and carbon isotope analysis
Description of species- 1. Cistopus indicus 2. Clarias batrachus 3. Dasyatis kuhlii 4. Decapterus russelli 5.
Eythynnus affinis 6.Gymnosarda unicolor 7. Himantura gerrardi 8. Himantura uarnak 9. Lates calcarifer
10. Loligo duvaucelli 11. Loligo edulis 12. Loligo sibogae 13. Loligo uyii 14. Lutjanus johnii 15. Lutjanus
argentimaculatus 16. Lutjanus malabaricus 17. Lutjanus sebae 18. Megalaspis cordyla 19. Metapenaeopsis
barbata 20. Metapenaeus affinis 21. Metapenaeus brevicornis 22. Nemipterus bathybius 23. Nemipterus
japonicus 24. Nemipterus nematophorus 25. Nibea soldado 26. Otolithes ruber 27. Otolithoides biauritus 28.
Parapenaeopsis sculptilis 29. Parapenaeopsis hardwickii 30. Parastromateus niger 31. Penaeus indicus 32.
Penaeus merguiensis 33. Penaeus monodon 34. Rastrelliger faughni 35. Rastrelliger brachysoma 36.
Rastreliger kanagurta 37. Scomber australasicus 38. Scomberomorus commerson 39. Scombermorus guttatus
40. Selar boops 41. Selaroides leptolepis 42. Seriola dumerili 43. Thunnus tonggol
52
0.32
0.88 ± 0.81
0.29
0.37 ± 0.19
0.46
0.13
0.35 ± 0.41
0.30
0.34
0.74 ± 0.49
1.54
0.77 ± 0.41
3.29
0.59 ± 0.23
B
B
B
B
B
B
B
B
B
P
B
B
B
B
11.93
11.29
8.26
14.54
12.19
N.A.
10.87
13.76
13.52
13.39
11.21
12.04
10.04
13.46
-15.12
-16.71
-19.05
-14.34
-15.02
N.A.
-18.00
-16.50
-16.99
-16.70
-17.26
-18.03
-17.38
-16.89
1
4
1
2
1
1
6
1
1
4
1
5
1
6
Carnivore
Old women octopus
Bluespotted stingray
Slander scad
Sharpnose stingray
Honeycomb stingray
Mitre squid
Indian squid
Sibogae squid
Little Squid
Torpedo scad
Yellowbelly threadfin bream
Japanese threadfin bream
Doublewhip threadfin bream
Soldier croaker
Cistopus indicus
Dasyatis kuhlii
Decapterus russelli
Himantura gerrardi
Himantura uarnak
Loligo chinensis
Loligo duvaucelli
Loligo sibogae
Loligo uyii
Megalaspis cordyla
Nemipterus bathybius
Nemipterus japonicus
Nemipterus nematophorus
Nibea soldado
-18.95
-15.42
-14.23
-15.59
-14.21
-15.67
-16.71
-15.15
-15.85
-14.64
δ13C*
(‰)
Table 3.3 Total mercury concentrations (mean ± S.D. µg/g dry mass) and stable isotope analysis in fish
from West Peninsular Malaysia
δ15N*
Common name
Scientific name
n
Mercury
Feeding mode
(‰)
Omnivore
Catfish
Clarias batrachus
4
0.12 ± 0.09
B
6.58
Sand velvet shrimp
Metapenaeopsis barbata
1
0.13
B
10.68
Pink shrimp
Metapenaeus affinis
2
0.39 ± 0.31
B
12.13
Yellow shrimp
Metapenaeus brevicornis
3
0.13 ± 0.03
B
11.34
Rainbow shrimp
Parapenaeopsis sculptilis
3
0.32 ± 0.08
B
12.13
Spear shrimp
Parapenaeospsis hardwickii
1
0.31 ± 0.04
B
11.68
Black pomfret
Parastromateus niger
5
0.25 ± 0.10
P
13.62
Indian white prawn
Penaeus indicus
2
0.12 ± 0.02
B
11.97
Banana prawn
Penaeus merguiensis
2
0.33 ± 0.39
B
11.09
Giant tiger prawn
Penaeus monodon
1
0.22
B
12.24
53
Lates calcarifer
Euthynnus affinis
Loligo edulis
Lutjanus sebae
Lutjanus malabaricus
Secondary carnivore
Barramundi
Kawakawa
Sword tip squid
Emperor red snapper
Malabar blood snapper
4
2
3
3
5
1
1
3
2
2
3
4
6
1
3
1
1
2
3
1
1.07 ± 0.35
0.44 ± 0.13
0.29 ± 0.13
0.53 ± 0.22
0.55 ± 0.28
0.48
0.85
0.26 ± 0.07
0.12 ± 0.02
0.25 ± 0.07
0.41 ± 0.16
0.42 ± 0.12
0.48 ± 0.39
0.86
0.34 ± 0.22
0.48
0.55
1.41 ± 1.40
1.29 ± 0.24
2.64
P
P
B
B
B
B
B
P
P
P
P
P
P
P
B
P
P
P
B
B
15.68
15.65
15.78
15.83
16.26
13.67
13.11
8.35
11.78
10.73
9.77
10.52
11.62
12.83
9.52
13.65
9.49
12.75
11.27
12.10
-14.87
-15.35
-16.55
-14.97
-14.48
-14.27
-16.44
-18.65
-16.52
-18.18
-18.10
-17.07
-18.42
-17.59
-18.95
-18.02
-17.98
-15.06
-17.37
-16.06
* Analysis of nitrogen and carbon stable isotope was conducted only on one sample representing each species. NA denotes not available. P: pelagic, B: benthic
Otolithes ruber
Otolithoides biauritus
Rastrelliger faughni
Rastrelliger brachysoma
Rastrelliger kanagurta
Scomber australasicus
Scomberomorus commerson
Scomberomorus guttatus
Selar boops
Selaroides leptolepis
Seriola dumerili
Thunnus tonggol
Gymnosarda unicolor
Lutjanus argentimaculatus
Lutjanus johnii
Tigertooth croaker
Bronze croaker
Faughni mackerel
Indo-Pacific mackerel
Indian mackerel
Slimy mackerel
Narrowbarredspanish mackerel
Indo-Pacific king mackerel
Oxeye scad
Yellowstripe scad
Greater amberjack
Longtail tuna
Dogtooth tuna
Mangrove red snapper
John's snapper
54
Table 3.4 Mercury and methyl mercury concentrations (mean ± S.D. µg/g dry mass) in selected
species of fish from West Peninsular Malaysia
Common name
Scientific name
n
Hg
MeHg
% MeHg
Omnivore
Pink Shrimp
Metapenaeus affinis
1
0.61
0.30
49
Carnivore
Bluespotted stingray
Dasyatis kuhlii
2
1.49 ± 0.65
1.44 ± 0.66
96
Indian squid
Loligo duvaucelli
1
1.17
0.95
81
Torpedo scad
Megalaspis cordyla
3
0.93 ± 0.37
0.85 ± 0.42
91
Yellowbelly threadfin bream
Nemipterus bathybius
1
1.54
1.43
93
Japanese threadfin bream
Nemipterus japonicus
2
1.18 ± 0.30
1.09 ± 0.33
92
Doublewhip threadfin bream
Nemipterus nematophorus
1
3.29
3.25
99
Soldier croaker
Nibea soldado
4
0.72 ± 0.12
0.65 ± 0.13
90
Indo-Pacific king mackerel
Scomberomoru sguttatus
2
0.98 ± 0.16
0.95 ± 0.17
97
Oxeye scad
Selar boops
1
0.86
0.78
91
Dogtooth tuna
Gymnosarda unicolor
1
2.40
2.36
98
John's snapper
Lutjanus johnii
1
2.64
2.57
97
Mangrove red snapper
Lutjanus argentimaculatus
3
1.29 ± 0.24
1.23 ± 0.27
95
Secondary carnivore
Barramundi
Lates calcarifer
4
1.07 ± 0.35
1.02 ± 0.36
95
Malabar blood snapper
Lutjanus malabaricus
3
0.74 ± 0.08
0.68 ± 0.13
92
Emperor red snapper
Lutjanus sebae
1
0.70
0.60
86
S.D.: standard deviation
3.3.3
Total mercury and methyl mercury concentrations
The mean of total mercury concentrations in all fish and seafood tissues are as reported in Table
3.3. The mean methyl mercury concentrations in selected fish tissues are provided in Table 3.4.
3.3.4
Inter species variation in total mercury and methyl mercury concentrations
3.3.4.1
Interspecific differences in total mercury concentrations
All fish and seafood samples were analysed for total mercury. The overall mean mercury
concentration among all organisms was 0.65 ± 1.21 µg/g dry mass. Mean mercury concentration
was found lowest in Clarias batrachus (0.12 ± 0.09 µg/g dry mass) and highest in Nemipterus
nematophorus (3.29 µg/g dry mass). Significant differences in mercury concentrations were
55
found between some species but not all (p<0.05; Mann Whitney post-hoc test). It was observed
that majority of the fish species had mercury concentrations less than 0.5µg/g dry mass. (One fish
sample, Lutjanus johnii was excluded and removed from analysis [had about 19 times higher than
the overall mean mercury concentration]). The mean mercury concentrations by species is as
shown in Figure 3.3. Catfish and prawn had among the lowest mean mercury concentrations
while bream, barramundi and snapper were among the top three carnivores with highest mean
Snapper
Tuna
Barramundi
Amberjack
Mackerel
Croaker
Bream
Stingray
Squid
Prawn
Pomfret
Shrimp
Scad
Catfish
Hg concentrations (µg/g dry mass)
mercury concentrations.
Figure 3.3 The mean mercury concentrations in fish by species
56
3.3.4.2
Interspecific differences in methyl mercury concentrations
A total of 31 organisms were analysed for methyl mercury. The selection criteria for mercury
speciation were for organisms containing at least 0.5 µg/g of total mercury. The overall mean
methyl mercury among all organisms was 1.09 ± 0.65 dry mass. The lowest methyl mercury was
observed in Metapenaeus affinis (0.30 µg/g dry mass) while the highest methyl mercury
concentration was found in Nemipterus nematophorus (3.25 µg/g dry mass).
3.3.4.3
Differences in total mercury concentrations between trophic levels
The mean mercury concentrations were different between trophic levels following the order:
omnivores < secondary carnivores < carnivores (0.23 ± 0.15; 0.64 ± 0.62 and 0.61 ± 0.36 µg/g
dry mass respectively). A one-way ANOVA test showed that mercury concentrations were
significantly different between trophic levels F2,
107
= 14.26, p <0.000. Post hoc comparisons
using Tukey test revealed that mercury concentrations were significantly different between
omnivores and carnivores as well as omnivores and secondary carnivores. No significant
differences were found between mean mercury concentrations of carnivores and secondary
carnivores. Box plot showing the range and median values for total mercury concentrations
between the trophic levels are presented in Figure 3.4. As observed in Figure 3.4, mercury
concentrations were not found to increase across trophic levels.
3.3.4.4
Differences in methyl mercury concentrations between trophic levels
The mean methyl mercury concentrations were highest in the following order: carnivores >
secondary carnivores > omnivores (0.84 ± 0.31; 1.22 ± 0.70; 0.20 µg/g dry mass). Box plot
showing the range and median values for methyl mercury concentrations between the trophic
levels are presented in Figure 3.5. Kruskal Wallis test revealed that mean methyl mercury
concentrations were not significantly different between trophic levels (χ2=1.865, df=2, p=0.394).
57
Log Hg concentration
.
Omnivore
Carnivore
Secondary carnivore
Trophic Level
Figure 3.4 Total mercury concentrations among different trophic levels
(µg/g dry mass). Measure of central tendency is median, boxes indicate
data from 25th to 75th percentiles, whiskers indicate range from 0 to 100 th
percentile and individual point outliers. Please note the log scale in Y axis.
3.3.4.5 Differences in total mercury concentrations between feeding mode
Mean mercury concentrations for both benthic and pelagic organisms were 0.55 ± 0.58 and 0.54
± 0.46 µg/g dry mass respectively. No significant differences were found between mercury
concentrations in benthic or pelagic organisms (Student’s T-test, p = 0.874).
3.3.4.6 Differences in methyl mercury concentrations between feeding mode
The mean methyl mercury concentrations for both benthic and pelagic organisms in this study
were 1.14 ± 0.72 and 1.06 ± 0.52 µg/g dry mass respectively. No significant differences between
58
mean mercury concentrations of the benthic and pelagic organisms were observed when Kruskal
Log MeHg concentrations
Wallis test was performed (χ2=-0.021, df =1, p=0.885).
Omnivore
Carnivore
Secondary carnivore
Trophic Level
Figure 3.5 Total methyl mercury (MeHg) concentrations among different
trophic levels (µg/g dry mass). Measure of central tendency is median,
boxes indicate data from 25th to 75th percentiles, whiskers indicate range
from 0 to 100th percentile and individual point outliers. Please note the log
scale in Y axis.
3.3.4.7 Percentage ratios of methyl mercury to mercury
The percentage ratios of methyl mercury in fish and seafood measured in this study are shown in
Table 3.4. Methyl mercury level as a percentage of total mercury ranged from 49% in
Metapenaeus affinis to 99% in Nemipterus nematophorus. All species had above 80% of mercury
as methyl mercury except for pink shrimp (Metapenaeus affinis) which exhibit only 49% of
59
methyl mercury. A Spearman’s rho correlation analysis showed significant positive relationship
between mercury and methyl mercury concentrations in all organisms (ρ= 0.982; p = 0.000).
3.3.5 Relationship of mercury concentrations with length
In order to test the relationship of mercury concentrations with length, a simple linear regression
was conducted. A significant linear regression was found between log mercury concentrations
Log Hg concentrations
and length (slope = 0.006, adjusted r2 = 0.064, F1,104= 8.144, p = 0.005)(Figure 3.6).
Length
Figure 3.6 The regression analysis between log transformed mercury
concentrations and length (in centimetres) for commonly consumed
fish in West Peninsular Malaysia
60
3.3.6 Relationship of methyl mercury concentrations with length
In order to test the relationship of methyl mercury concentrations with length, a simple linear
regression was conducted. A positive relationship was found between log methyl mercury
concentrations and length although the relationship was not significant (slope = 0.06, adjusted r2
Log MeHg concentrations
= 0.051, F1,28= 2.549, p = 0.122)(Figure 3.7)
Length
Figure 3.7 The regression analysis between log
transformed methyl mercury concentrations and length
(in centimetres) for commonly consumed fish in West
Peninsular Malaysia
61
3.3.7
Trophic level and biomagnification
3.3.7.1 Relationship between 15N and log mercury concentrations
A linear regression analysis conducted between 15N and log mercury concentrations found a
positive relationship between the two variables although the relationship was not significant
Log Hg concentrations
(slope = 0.015, adjusted r2 = -0.022, F 1, 41 = 0.076, p = 0.784) as shown in Figure 3.8.
15N
Figure 3.8 The regression analysis between log transformed
mercury concentrations and δ15N (‰) for commonly consumed
fish in West Peninsular Malaysia
62
3.3.7.2 Relationship between 15N and log methyl mercury concentrations
A linear regression analysis conducted between 15N and log methyl mercury concentrations
found a significant negative relationship between the two variables (slope = -0.015, adjusted r2 =
-0.064, F 1, 14 = 0.159, p = 0.696) as shown in Figure 3.9.
Log MeHg concentrations
Log
Me
Hg
conc
entr
atio
ns
15N
Figure 3.9 The regression analysis between log transformed
methyl mercury concentrations and δ15N (‰) for commonly
consumed fish in West Peninsular Malaysia
63
3.3.8 Comparison with fish consumption guidelines
The mercury concentrations observed in this study were compared with guidelines available from
various organizations (Appendix 3.1). As the recommended mercury limits were expressed in wet
mass, for comparative purposes, the dry mass was converted into wet mass by a factor of 0.17
(Yap 1999). All fish were well below the maximum allowable limits for mercury and methyl
mercury as stipulated by various organizations except for a fish species double whip threadfin
bream (Nemipterus nematophorus) which slightly exceed the limit.
3.3.9 Estimation of potential health risk
In order to evaluate the potential health risk of population through consumption of fish and
seafood, the weekly intake rates for all species were estimated (Figure 3.10). The provisional
tolerable weekly intake (PTWI) value for mercury is 5 µg/kg body weight (FAO/JECFA 2006).
Daily fish consumption by the Malaysian population is 160 g/person/day (FAO 2009) with an
average weight of an individual of 64 kg (Lim et al. 2000). The PTWI values for mercury by an
adult (µg/kg-1 body weight) for each species were calculated using the formula below:
PTWI (µg/kg-1) = Mean Hg in fish (µg/g-1 wet weight) x Weekly fish consumption (g)
Body weight (kg)
The assessment of PTWI values observed in this study against the stipulated PTWI values
recommended by JECFA revealed that two fish species exceeded the PTWI values of 5 µg/kg
body weight for mercury. The two fish species were doublewhip threadfin bream (Nempiterus
nematophorus) and John’s snapper (Lutjanus johnii). The rest of the fish species showed PTWI
values within the recommended intake for mercury.
64
PTWI = 5 µg/kg bw
65
Figure 3.10 The provisional tolerable weekly intake (PTWI) for mercury in commonly consumed fish in West Peninsular Malaysia
3.4
DISCUSSION
3.4.1 Nitrogen and carbon stable isotope analysis
Stable isotope analysis (15N and 13C) is now used to determine food web structure (Minagawa
and Wada 1984). The values of 15N can be used as an indicator of trophic position of organisms
and can provide accurate assignment of species to their respective trophic levels (Figure 3.2).
The values of 13C may very well indicate potential food sources whether aquatic or terrestrial,
inshore or offshore as well as pelagic or benthic environment (Hobson et al. 1995, Dauby et al.
1998). It was observed in this study that 13C values in benthic organisms (-16.1‰) were
significantly higher than pelagic organisms (-17.2‰). This is in agreement with Asante et al.
(2010) who reported significantly higher 13C values in demersal fish (-17.5‰) than pelagic fish
(-18.2‰) in Sulu Sea. Similarly, 13C values were found to be more enriched in benthic fish from
lake, estuary and ocean compared to pelagic fish (Bootsma et al., 1996; Deegan and Garritt,
1997; Gorbatenko et al. 2008).
Numerous researchers reported positive correlations between 15N and mercury concentrations
indicating biomagnification of mercury in food web studied (Atwell et al. 1998; Bowles et al.
2001; Campbell et al. 2003, 2005; Ikemoto et al. 2008; Yoshinaga et al. 1992). This is in contrast
to the findings of this study by which regression analysis conducted between nitrogen isotope
values and mercury concentrations revealed that the relationship was not significant thus
confirming that biomagnification is not occurring.
The 15N values observed were highly variable for fish from the same family. Although
occupying the same habitat, these organisms may have different feeding tactics. For instance,
mangrove red snapper (Lutjanus argentimaculatus) had 15N values of 11.3‰ while malabar
blood snapper (Lutjanus malabaricus) had 15N values of 16.26‰. This discrepancy showed that
15N values are species specific and this discrimination is needed to assign trophic levels.
Initial classification of the fish and seafood species was conducted based on information obtained
from the diet of organisms as mentioned earlier in methodology section (refer to section 3.2.6)
67
however, comparison of data from the original classification and the 15N values revealed that
discrepancies exist when species were assigned to their respective trophic levels. For instance, a
couple of species were originally assigned as secondary carnivores but the 15N values showed
that they were carnivores. Hence, the 15N values can provide accurate assignment of species to
the appropriate trophic levels and should be used instead of relying on information obtained from
available database.
3.4.2 Interspecific differences in total mercury concentrations
The overall mean mercury concentrations for all organisms observed in this study was 0.65 ±
1.21 µ/g dry mass. Mercury concentrations in general i.e. for Rastrelliger brachysoma,
Scomberomorus commerson, Euthynnus affinis, Lates calcarifer, Parastromateus niger,
Megalaspis cordyla and Selaroides leptolepis were comparable with data published from other
studies conducted in Malaysia (Hajeb et al. 2010; Agusa et al. 2005). Higher mean mercury
concentrations were measured in this study for several fish species relative to the mean mercury
concentrations found in those two studies aforementioned (i.e Lates calcarifer, Megalaspis
cordyla). These discrepancies in mercury concentrations could be explained by the locations
where the fish species were obtained from. Hajeb et al. (2010) reported higher mean mercury
concentrations in fish from the East Coast of Peninsular Malaysia compared to the West Coast of
Peninsular Malaysia which was in agreement with Agusa et al (2005) who reported similar trend
in their studies. Mok et al. (2012) reported higher lead and mercury levels in seabass from West
Malaysia compared to East Malaysia. Nevertheless, fish species in this study were obtained from
West Peninsular Malaysia which is nearby to Straits of Malacca and the higher mercury
concentrations in some of the species may be due to higher mercury concentrations in the
sediments. The West Peninsular Malaysia is more developed than the East Peninsular Malaysia
with more than 60% of Malaysians resides in West Malaysia and most of the development
activities occur in these vicinities (Ismail et al. 1993). Chlor alkali plants, pharmaceutical and
other chemical plants which are present in these developed localities may be important local
point sources of mercury to coastal sediments (Neff 2002) by which sediment bacteria play an
important role in mobilizing sediment mercury into food webs. The Department of Environment
(2009) reported that a total of 10311 sources were identified as manufacturing industry and agrobased industry pollution where 9513 sources were from West Malaysia and 798 sources were
68
from East Malaysia confirming the fact that higher mercury concentrations are expected in fish
originating from West Malaysia compared to East Malaysia.
A number of studies have reported total mercury concentrations in several species of fish from
various countries particularly in the South East Asian region. Notably higher mercury
concentrations were observed in this study for selected species (Megalaspis cordyla, Nemipterus
japonicus, Lates calcarifer, Scomberomorus commerson, Lutjanus malabaricus) compared to the
findings from other studies (Table 3.5). While other studies measured concentrations of mercury
in muscles, livers (Agusa et al. 2007; Hajeb et al. 2010), gills (Kamaruzzaman et al. 2011) and
gonads (Chi et al. 2007) of fish, this study focused only on edible muscle tissues as they provide
a reliable measure of long term exposure and bioaccumulation. In addition, edible muscles
indicate the most commonly eaten part associated with human health risk implications and thus
reflect a more accurate exposure (Palace et al. 2007; Henry et al. 2004).
3.4.3 Interspecific differences in methyl mercury concentrations
The mean methyl mercury concentrations in this study in the overall species did not vary
considerably between one another. Methyl mercury concentrations ranged from 0.02 to 2.42 µg/g
dry mass with mean methyl mercury concentrations of 0.45 ± 0.27 µg/g dry mass. Comparable
methyl mercury concentrations in fish were reported by several researchers. Andersen and
Depledge (1997) reported mean methyl mercury concentrations in fish species from Azorean
Waters ranging from 0.036 – 0.410 µg/g wet weight while Al Majed and Preston (2000) reported
mean methyl mercury concentrations ranging from 0.07 - 3.92 µg/g dry mass in several fish
species from Kuwait waters.
A highly significant relationship between total mercury and methyl mercury concentrations was
observed in the fish and seafood samples (Spearman rho correlation = 0.982). This is in
accordance with findings from several researchers who reported significant positive correlations
between mercury and methyl mercury in fish (Al Majed and Preston 2000; Andersen and
Depledge 1997).
69
Table 3.5 Mean total Hg concentrations (µg/g dry mass) in various species of fish reported in the
literature, including results from this study
Species
Location
Megalaspis cordyla
Krabi, Thailand
Mean Hg
(µg/g dry weight)
0.22
Author(s) and year
Megalaspis cordyla
Kuala Pari, Malaysia
0.64
This study
Nemipterus japonicus
Panimbang, Indonesia
0.11
Agusa et al. (2007)
Nemipterus japonicus
Hong Kong
0.03**
Centre for Food Safety (2008)
Nemipterus japonicus
Kuala Pari, Malaysia
0.41
This study
Lates calcarifer
Ranong, Thailand
0.48
Agusa et al. (2007)
Lates calcarifer
Hong Kong
0.09**
Centre for Food Safety (2008)
Lates calcarifer
Pelabuhan Klang,
1.38
This study
Agusa et al. (2007)
Malaysia
Scomberomorus commerson
Hong Kong
0.08**
Centre for Food Safety (2008)
Scomberomorus commerson
Koh Kong, Cambodia
0.18*
Agusa et al. (2007)
Scomberomorus commerson
Selayang, Malaysia
0.54
This study
Scomberomorus guttatus
Hong Kong
0.08
Centre for Food Safety (2008)
Scomberomorus guttatus
Selayang, Malaysia
0.87
This study
Lutjanus malabaricus
Hong Kong
0.10
Centre for Food Safety (2008)
Lutjanus malabaricus
Ranong, Thailand
0.23
Agusa et al. (2007)
Lutjanus malabaricus
Kuala Pari, Malaysia
0.70
This study
* µg/g wet weight ** not classified either as dry weight or wet weight
70
3.4.4 Differences in total mercury concentrations between trophic levels
Bioaccumulation of mercury can be influenced by both environmental (water chemistry, pH,
season) and biological (species, sex, trophic level, habitat, body size, age) factors (Amundsen et
al. 1997; Trudel and Rasmussen 2006; Schwindt et al. 2008). Predatory fishes have the tendency
to accumulate higher mercury concentrations than non-predatory fishes (Hajeb et al. 2010) as a
result of bioaccumulation and biomagnification of mercury (Riisgard and Hansen 1990).
Mercury concentrations in all organisms analysed were observed highest in carnivores followed
by secondary carnivores and omnivores (Figure 3.4). In general, it is expected that mercury
concentrations to be increasing with successive trophic levels indicating occurrence of
biomagnification. However, this was not observed in species studied as mean mercury
concentrations were highest in carnivores instead of secondary carnivores. Although
biomagnification was not observed, higher mean mercury concentrations were reported in
carnivores and secondary carnivores in comparison with omnivores. The observation of higher
mercury concentrations in predatory fishes than non-predatory fishes is in good agreement with
data from other researchers. Ruelas-Inzunza and Páez-Osuna (2005) reported that carnivorous
fish and sharks from two coastal lagoons in the Gulf of California had higher mercury
concentrations than non-carnivorous fish. Likewise, Nakagawa et al. (1997) found that large
predatory fish such as tuna and swordfish presented the highest mercury concentrations among
collected fish and shellfish. Olivero et al. (1998) found that mercury concentrations in
carnivorous species were higher than in non-carnivorous species in northwestern Colombia.
3.4.5 Differences in methyl mercury concentrations between trophic levels
It is observed that methyl mercury concentrations are higher in secondary carnivores compared to
carnivores and omnivores; indicating that species occupying higher trophic levels contain higher
methyl mercury concentrations. Agah et al. (2007) found similar trends in species at higher
trophic levels feeding on mollusks and small fishes having higher methyl mercury concentrations
than species at lower trophic levels feeding on detritus and phytoplanktons.
71
3.4.6 Differences in total mercury concentrations between feeding mode
Variations in mercury concentrations can partly be attributed by fish habitat. Bottom-dwelling
fish ingesting sediments can have higher mercury concentrations than predators. For instance,
Campbell (1994) found that bottom-dwelling red-ear sunfish (Lepomis microlophus) had higher
mercury concentrations than bass or bluegill sunfish in Florida. In this study, no significant
differences were found between benthic and pelagic fish analysed. A comparable finding by
Kehrig et al. (2009) found that median mercury concentrations between benthic carnivorous and
pelagic carnivorous fish muscle tissues in Guanabara Bay, Brazil were similar. This is contrary to
the findings from Storelli et al. (1998) who reported that mean mercury concentrations in benthic
fish were two times higher than pelagic fish in Italy. The higher mercury concentrations in
benthic fish compared to pelagic fish is due to the bioavailability of mercury in the sediments
which the benthic fish are more exposed to than pelagic fish since they live in close associations
with the sediments and total mercury concentrations are usually higher in sediments than in water
(Luoma 1989; Merian 2004).
3.4.7 Differences in methyl mercury concentrations between feeding mode
The mean methyl mercury concentrations between benthic and pelagic species in this study were
similar indicating that no differences exist in methyl mercury concentrations between feeding
mode. This is contrary to the finding reported by Chen et al. (2009) who found that methyl
mercury concentrations were higher in pelagic feeding fauna than benthic feeding fauna in the
Gulf of Maine. On the other hand, Carasso et al. (2011) reported higher methyl mercury
percentages in benthivorous European catfish, Silurus glanis (89%) compared to piscivorous
common carp, Cyprinus carpio (77%) from Ebro River, Spain. Zhu et al. (2013) also found that
methyl mercury concentrations in demersal fish species of South China Sea were higher than
epipelagic and mesopelagic fish species.
3.4.8 Relationship of total mercury concentrations and length
An important factor in determining the rate of uptake, distribution as well as elimination of
pollutants is fish size (Lange et al. 1994). This is particularly true for mercury. As the mercury in
fish increases with body size, larger and older fish usually have higher mercury concentrations
72
than smaller, younger fish (Storelli et al. 2002). It is difficult to determine the age of fish and size
is normally used as surrogate for age (Boening 2000).
There are numerous studies in the literature reporting positive correlation of mercury with fish
size and age (Boening 2000; Waldron and Kerstan 2001; Storelli et al. 2002; Panfili et al. 2010;
Bacha et al., 2012) although Stafford and Haines (2001) and Liu et al. (2012) found contradicting
findings in their studies. Strong correlations between size and mercury concentrations were
reported for swordfish (Xiphias gladius) and Bluefin tuna (Thunnus thynnus) from the
Mediterranean Sea by Storelli and Marcotrigiano (2001), for pelagic fish from the Adriatic Sea
(Storelli 2008) as well as for S. pilchardus from Tunisia (Joiris et al. 1999).
A significant relationship between log transformed mercury concentrations and length was
observed for all fish species analysed. Although significantly related, length of organism has a
small influence on mercury concentrations (adjusted r2 value of 0.064).The positive relationship
between fish size and mercury tends to suggest that consumers that eat larger fish would be
exposed to higher concentrations of mercury than those who eat smaller fish. Hence, by eating
smaller fish, exposure to mercury could be greatly reduced.
3.4.9 Relationship of methyl mercury concentrations and length
Variations in metal concentrations can be associated primarily with length of fish (Somers and
Jackson 1993; Sonesten 2003). Similar to mercury, methyl mercury concentrations can be
influenced by a variety of different factors namely trophic levels (Cai et al. 2007), environmental
parameters (Pickhardt et al. 2002), locations (Colaco et al. 2006) and perhaps most commonly,
size (Boening 2000). Storelli et al. (2003) reported significant relationship between methyl
mercury and size of fish from Mediterranean Sea. The importance of size to body mercury
loading is highly recognized in marine organisms. In general, older individuals indicate mature
fish and exhibit higher mercury concentrations in comparison with the younger ones due to
longer exposure time to contaminants (Dixon and Jones, 1994; Lansen et al. 1991; Storelli and
Marcotrigiano 2000; Trudel and Rasmussen 2006). The methyl mercury concentrations for the
selected species measured in this study were not significantly correlated with lengths although
positive relationship was observed.
73
3.4.10 Percentage ratios of methyl mercury to mercury
The mean percentage of methyl mercury to total mercury in all species was 92% ± 9.3 indicating
that predominant form of mercury present in organism. This is in good agreement with findings
from other studies (Agah et al. 2007; Hajeb et al. 2010; Andersen and Depledge 1997; Yamashita
et al. 2005) by which majority of mercury which are present in fish are as methyl mercury (more
than 70%).
3.4.11 Trophic level and biomagnification
Mean mercury concentrations were found not to be increasing successively with increasing
trophic levels and were not significantly different between the trophic levels (Figure 3.4). The
highest mercury concentrations were observed in carnivores followed by secondary carnivores
and omnivores. As mercury concentrations were not increasing with trophic levels, this means
that bioaccumulation is not occurring between carnivores and secondary carnivores.
Biomagnification of mercury can be reflected by the significantly positive regressions of logmetal concentrations versus 15N for both total and organic mercury forms (Coelho et al. 2013).
As mercury biomagnifies in aquatic food web (Lawson and Mason 1998), a positive linear
relationship between 15N values and log mercury concentrations was expected. Bisi et al. (2012)
found that mercury concentrations of Guanabara and Ilha Grande Bay, Brazil were positively
associated with 15N values. Endo et al. (2013) reported similar findings in muscles and livers of
star-spotted dogfish (Mustelus manazo) in Japan. Also, Lavoie (2010) revealed that mercury was
biomagnified in the food web of Gulf of St. Lawrence, Canada.
This study found positive relationship between log transformed mercury concentrations and 15N
values although the relationship was not significant. To further elucidate this, Nemipterus
nematophorous is taken as an example. In Table 3.3, mercury concentration for this fish was 3.29
µg/g dry mass which was the highest mercury concentration observed for all the species. Despite
having the highest mercury concentration, the 15N value for this species was 10.04‰ which was
not the highest 15N value. The highest 15N value was measured in Lutjanus malabaricus which
had only 0.84 µg/g dry mass of mercury. A similar finding was observed in Sepetiba Bay by Bisi
et al. (2012) by which Guiana dolphin showed the highest mean mercury concentration (269.23
74
ng/g) but not the highest 15N value. Das et al. (2003a) also found that 15N values were not
significantly related with mercury concentrations in northeast atlantic marine mammals.
Significant negative relationship was found between log methyl mercury concentrations and 15N
values. This could be due to the inclusion of fish species in the analysis and other organisms from
lower trophic positions (e.g phytoplankton, zooplankton, and invertebrates) and predators at
higher trophic levels (e.g birds, marine mammals) were ignored. This is in agreement with
findings by Zhu et al. (2013) who reported similar findings in Pearl River Estuary and Beihai of
South China Sea by which log methyl mercury concentrations were negatively associated with
15N values.
3.4.12 Comparison with fish consumption guidelines
Intake of mercury particularly methyl mercury from fish is considered the most serious general
impact on humans since the potential of bioaccumulation and biomagnification of mercury in
aquatic organisms. Based on risk assessments and several other considerations, international
organisations have established risk evaluation tools such as limits or guidelines for maximum
concentrations in fish and fish consumption advisories. The guidelines values obtained from
various countries indicate that mercury is present all over the globe (especially in fish) although
guidelines values presented are somewhat limited (not showing values from other countries
across the world).
Fish species analysed in this study appear to be safe for human consumption and had lower
mercury concentrations than the limits stipulated by the Malaysian Food Act 1983 and Malaysian
Food Regulations 1985. However, a fish species, doublewhip threadfin bream (Nemipterus
nematophorus) is deemed unfit for human consumption as the mercury concentrations in the
tissues exceeded the maximum allowable limits slightly. Studies done by Alina et al. (2012) and
Taweel et al. (2013) both in fish from Straits of Malacca as well as Langat River and Engineering
Lake respectively in Malaysia reported that heavy metals concentrations in all fish species
studied were safe for human consumption.
75
3.4.13 Estimation of potential health risk
Mercury and methyl mercury exposure to humans has been extensively studied since the
Minamata Disease and Iraqi outbreak. The most sensitive target for methyl mercury toxicity is
the developing fetus while the most sensitive outcomes for prenatal exposure is
neurodevelopmental deficits (Chang et al 1977). In recent years, the United States Environmental
Protection Agency (EPA) has developed fish consumption advisory for the general public once
mercury contamination becomes a widespread problem in the United States. The joint advisory
by the EPA and the US Food and Drug Administration (USFDA) was issued to warn susceptible
groups (pregnant women, nursing mothers as well as young children) to avoid eating some types
of fish and shellfish that contain high levels of mercury (USEPA 2004).
All fish and seafood analysed were well below the PTWI of 5 µg/kg body weight for mercury
with the exception for two species (Nemipterus nematophorus and Lutjanus johnii). Although the
two species of fish exceeded the PTWI, these calculations were done base upon weekly intake
assuming that the fish were consumed every day for a week. Consumption of fish by the
population is most likely to include a wide variety of fish and not limited to only one specific
type of fish. Bearing this in mind, the risk of population consuming fish which contain high
mercury concentrations can be significantly reduced and thus protect them from health effects of
mercury exposure through consumption of contaminated fish. In addition, if the two fish species
were excluded from the main diet of the population, there are still a wide variety of fish that one
can choose from as human health risk associated with consumption of fish high in mercury can
be detrimental.
On the same token, Hajeb et al. (2010) in a study conducted in 55 fish samples from West
Peninsular Malaysia reported that Rastrelliger brachysoma and Thunnus tonggol exceeded the
PTWI of 5 µg/kg body weight. In contrast, Mok et al. (2012) found that none of the aquaculture
food products from 37 aquaculture farms in Malaysia exceeded the PTWI for mercury thus
confirming that the aquaculture products are safe for human consumption.
Fish advisory is intended to inform consumers of the positive and negative attributes of their
potential choices (Burger 2005; Knuth et al. 2003) which should lead to appropriate behavioural
76
changes when choosing types of fish to consume. Nevertheless, Scherer et al. (2008) indicate that
many advisories emphasize more on the risk information rather than the benefits of fish
consumption. Due to the health benefits of fish (Park and Johnson 2006), fish advisories should
not reduce fish consumption (Vardeman and Aldoory 2008) even among women of high risk
groups (Lyman 2003; USFDA/ USEPA 2004). As a matter of fact, appropriate change in
behaviour should be to shift from consuming highly contaminated fish to those fish which are
less contaminated and safer to eat (Cohen et al. 2005; Shimshack and Ward 2010).
3.5
Summary and conclusions
Mercury and methyl mercury concentrations in fish species were found not to be increasing
successively across trophic level. The hypothesis that mercury concentrations were higher in
benthic species rather than pelagic was not proven in this study. Both mercury and methyl
mercury concentrations in benthic and pelagic fish did not show any significant differences,
indicating that the mean mercury and methyl mercury concentrations were similar. Furthermore,
mercury concentrations in fish seem to be affected by length of fish by which higher mercury
concentrations can be observed in older, adult fish species.
The regression of δ15 N values and log transformed mercury concentrations was not significant
thus mercury is not biomagnifying in the fish food web examined despite mercury concentrations
being significantly different across the trophic levels (based on ANOVA analysis).
The mercury concentrations observed in fish species in this study were well within the maximum
allowable limits for mercury in fish stipulated by various international bodies (The Malaysian
Food Act 1983 and Food Regulations 1985, FAO/ WHO Codex alimentarius, The Australian
Food Standards Code, USFDA) with the exception for a fish species, doublewhip threadfin
bream (Nemipterus nematophorus). As for the PTWI values for mercury, Nemipterus
nematophorus and Lutjanus johnii were found to exceed the recommended PTWI values of 5
µg/kg body weight.
In summary, all fish species studied can be safely consumed except for the two fish species
aforementioned which exceed the PTWI. Other fish species do not seem to pose any health risk to
77
the population. Whilst most fish are deemed safe for human consumption, consumers should
choose wisely on what type of fish to be eaten. It is important to eat a variety of fish and avoid
fish which contain high mercury concentrations especially for high risk groups such as children
and pregnant mothers.
78
CHAPTER 4
ASSESSMENT OF METALS IN COMMONLY CONSUMED FISH OF WEST
PENINSULAR MALAYSIA
4.1 INTRODUCTION
Globally, the consumption of seafood is more prominent in developing countries and a
preferred source of protein which consists of almost one third of animal protein intake (FRDC
2011). The world seafood consumption is growing at 2.5% a year and consumption of fish is
seen the highest in developing countries especially in Asia where by fish provided 22% of all
meat protein consumed, compared to Africa (18%), the World (16%), Europe and Oceania
(11%), North America (8%), and Latin America including the Caribbean (7%) (FRDC 2011).
The FAO (2010) estimates that global fish consumption per capita is at 17 kg in 2007, a sharp
rise of almost double from 9.9 kg per capita in 1960s. With the increasing demand of fish as
cheap supply of protein, it is imperative that the fish consumed are safe to be eaten by the
public.
The consumption of fish has been recommended to the public since a few decades ago due to
its valuable health effects (Kinsella et al. 1990; Kris-Etherton et al. 2002) which are
associated with eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA); which are
polyunsaturated omega-3 fatty acids (omega-3 PUFAs) formed from alpha-linolenic acid
(Castro-Gonzalez and M. Mendez-Armenta 2008). The fatty acids are produced by
phytoplankton and bioaccumulate in marine fish (Judé et al. 2006). The intake of DHA and
EPA has been shown to reduce high blood pressure and significantly reduce blood
triglyceride levels as reported by Harris (1997). Recent evidence from randomized controlled
trials suggests that regular consumption of fish oil/omega-3 supplements reduces the risk of
non-fatal heart attack, fatal heart attack and sudden death for people with history of heart
attack (Oomen et al. 2000; Kris-Etherton et al. 2002; Din et al. 2004; Harris 2004;
Mozaffarian et al. 2005; Jarvinen et al. 2006). Fish intake were also reported to be beneficial
for rheumatoid arthritis (Cleland et al. 2003; Rahman et al. 2008), psychiatric disorders
(Cherubini et al. 2007; Peet and Strokes 2005) as well as lung diseases (Romieu and Trenga
2001; Cerchietti et al. 2007).
Although regarded as a cheap supply of protein along with its health benefits, dietary fish
intake also may result in the intake of metals (Herreros et al. 2008). Emissions from
79
anthropogenic as well as natural sources have been identified as the key sources of metals into
the environment (Zukowska and Biziuk 2008). The discharge of metals into the marine
environment can damage species diversity and the ecosystems as the metals are easily
assimilated and bioaccumulated in organisms (Ebrahimpour et al. 2011) thus posing a risk to
human health due to consumption of contaminated food.
Metals occur naturally in the environment and the concentrations vary across geographic
regions (Pan and Wang 2012). As metals are ubiquitous in nature, all marine organisms
contain metals as normal constituents in their tissues (Neff 2002). Essential metals are
required by marine organisms for specific physiological or biochemical functions while some
others, though apparently not essential, may accumulate in high concentrations in tissues of
marine organisms (Simkiss and Taylor 1989). Some metals such as copper, zinc and iron are
advantageous for fish metabolism (Bohn et al. 2001) whereas metals like cadmium, arsenic
and mercury are proven to be harmful and have no known functions in biological systems.
Accumulation of metals in aquatic organisms such as fish and shellfish are usually several
times higher than the levels in sediment and water. For example, mercury concentrations in
fish tissues were found to be six times higher than in the water column (Scudder et al. 2009).
A number of studies have found that the cardioprotective effect of fish intake may be offset
by high mercury concentrations in fish (Salonen et al. 2000; Yoshizawa et al. 2002) while
cadmium injures kidneys and cause impaired kidney function, hypertension, tumours and
hepatic dysfunction (Rahman and Islam 2010; Al-Busaidi et al. 2011). Consumption of fish
containing high concentrations of cadmium, lead and/or arsenic have correspondingly been
linked with detrimental health effects in adults and children as reported by a number of
researchers (Abernathy et al. 2003; Burger and Gochfeld 2005; Andreji et al. 2006). Hence,
communities which rely heavily on fish as daily protein requirement may be at risk from
chronic to high exposure to metals (Grandjean et al. 1997) as fish consumption is the major
route of exposure in humans.
Stable isotope analysis has been studied quite extensively by numerous researchers.
Biomagnification of lipophilic contaminants in freshwater and marine ecosystems were
reported by Cabana and Rasmussen (1994) and Kiriluk et al. (1995). Broman et al. (1992)
examined stable isotope analysis and organochlorines and developed biomagnification models
for two Baltic marine food webs utilising 15N as representative of trophic position. Kidd et
80
al. (1995) found that mercury bioaccumulation occurred in fish from several freshwater lakes
in Canada from the association observed between mercury and 15N. In a more recent study,
Aita et al. (2011) studied the potential use of stable isotope ratios as tracers of biogeochemical
cycles of zooplanktons at life cycle levels in Japan where by with that information, variation
in carbon and nitrogen isotope ratios of higher trophic levels could be understand better. Faye
et al. (2011) studied seasonal and structure variability of fish from the analysis of stable
isotope in Senegal and found that the fish food web varied largely with season in faunal
composition and food chain length.
As fish consumption is important to the majority of populations in Asia, it is vital to ensure
that this commodity is safe for human consumption and free of metals contamination. Thus,
the objectives of this study are to: (1) to characterize the trophic position of commonly
consumed fish in West Peninsular Malaysia through nitrogen and carbon stable isotope
analysis, (2) to determine the metal concentrations (As, Cd, Pb, Se, Cu, Zn, Fe) in commonly
consumed fish in West Peninsular Malaysia, (3) to assess if there are differences in metal
concentrations between organisms of different trophic levels, (4) to determine if there is a
difference in mean concentrations of metals of benthic and pelagic fish, (5) to investigate if
older fish have higher metal concentrations than younger fish, (6) to investigate if
biomagnification of metals is occurring in organisms across trophic levels, (7) to assess the
relationship between metal concentrations, (8) to compare metal concentrations with
maximum allowable limits stipulated by various international bodies, (9) to compare the
Provisional Tolerable Weekly Intake (PTWI) for metals for Malaysian population with
existing PTWI outlined by JECFA.
81
4.2
MATERIALS AND METHODS
4.2.1 SELECTION OF SITES
This study involves two sites namely fish landing complex and wholesale markets in
Peninsular Malaysia as shown in Figure 4.1. M1 and M2 signify wholesale markets while L1
indicate fish landing complex. Further details of selection of sites are described in Chapter 3.
Figure 4.1 Map of fish complexes and wholesale markets in West Peninsular Malaysia
4.2.2 COLLECTION OF FISH AND SEAFOOD
A total of 111 composite samples from 43 different species of fish and seafood were obtained
from fish complex and wholesale markets. The selection of fish and seafood were based upon
the results of food dietary survey conducted among 3536 subjects in Peninsular Malaysia
(Nurul Izzah 2009). A description on fish and seafood collected for this study is explained in
further details in Chapter 3.
82
4.2.3 LABORATORY ANALYSIS
4.2.3.1 MEASUREMENT OF FISH AND SEAFOOD
All fish and seafood obtained were recorded for length. The overall measurement of fish was
taken from the snout on the upper jaw to the end of the tail. Squids and octopus lengths were
measured from its arms to the fin whereas shrimps and prawn length were recorded from the
distance of the posterior edge of the eye orbit to the posterior end of the telson.
4.2.3.2 SAMPLE PREPARATION
All samples were delivered in the ice box for transport to the laboratory. Only edible portions
of fish and seafood were used for analysis. Hence, samples were filleted, homogenized and
wrapped in aluminium foil before being inserted into labeled plastic bags. For fish with
scales, the scales on fish were removed prior to filleting. Similar to prawns and shrimps, the
outer shells were also removed. Samples which have been wrapped and labeled were kept in
freezer at -20◦C until further analysis. All samples received from Malaysia were freeze dried
and ground into fine powder before being put into 50 ml polypropylene tubes and sent to
Australia by courier service.
4.2.3.3 MEASUREMENT OF METAL CONCENTRATIONS
A total of 45 species comprising 111 composite samples were analysed for trace element
concentrations namely arsenic (As), cadmium (Cd), lead (Pb), selenium (Se), copper (Cu),
zinc (Zn) and iron (Fe). The organisms consisted of 31 fish species, 6 species of squids, 3
species of prawns and 5 species of shrimps.
Trace element concentrations in fish samples were determined by nitric acid digestion. A total
of 0.07 g of freeze-dried fish sample was weighed into 7 ml polytetrafluroacetate digestion
vessels (A.I. Scientific Australia) and 1 ml of concentrated nitric acid (Aristar, BDH,
Australia) added. Samples were digested at 600 W for 2 min, 0 W for 2 min and 450 W for 45
min (Baldwin et al. 1994). After cooling, digests were diluted to 10 ml with de-ionised water
(Milli Q, Millipore, Australia) in 10 ml polyethylene vials (Sarstedt, Australia). Total element
concentrations and mercury in digests and enzyme extracts acidified to 1% with nitric acid
(Aristar, BDH, Australia) were measured by ICP-MS (Maher et al. 2001).
Certified reference materials (DORM 2- Dogfish muscle from National Research Council
Canada) were analyzed along with each series of digestion to ensure accuracy of the method.
83
External calibration standards used for quantitation were made up from a 10 mg/L Reference
Standard, ICP-MS Calibration Multi Element Standard 2 (AccuTrace ™) in 1% (v/v) HNO3
acid as 0.1, 1, 10 and 100 mg/L solutions.
4.2.3.4 ANALYSIS OF CARBON AND NITROGEN STABLE ISOTOPES
The samples for stable isotope analysis were analysed at the Water Studies Centre (Monash
University) on an ANCA GSL2 elemental analyser interfaced to a Hydra 20-22 continuousflow isotope ratio mass-spectrometer (Sercon Ltd., UK). The precision of the elemental
analysis was 0.5 µg for both C and N (n = 5). The precision of the stable isotope analysis was
±0.1‰ for 13C and ±0.2‰ for 15N (SD for n=5). Stable isotope data are expressed in the
delta notation (δ13C and δ15N), relative to the stable isotopic ratio of Vienna Pee Dee
Belemnite standard (RVPDB= 0.0111797) for C and atmospheric N2 (RAir = 0.0036765) for
nitrogen.
4.2.4 STATISTICAL ANALYSIS
In order to use parametric tests, the assumptions of normality and homogeneity of variances
were checked by examining plots of residuals. If the residuals were not normally distributed,
data were log transformed and parametric tests were used.
A one-way ANOVA was used to determine if there was difference between log-transformed
data for trace element concentrations with trophic levels (omnivores, carnivores, secondary
carnivores). A post-hoc Tukey test was then performed to identify trophic groups that differed
significantly (p<0.05). Linear regression models were used to determine (1) the relationships
between trace element concentrations in fish with size and (2) the relationships between 15N
and log-transformed trace element concentrations.
Statistical analysis for all data was executed using IBM SPSS Statistics Version 21. A p value
of less than 0.05 was considered to indicate statistical significance in this study.
4.2.5 CLASSIFICATION OF SPECIES
For the purpose of data analysis, all species were classified into two different categories
namely; trophic levels and habitat. For trophic levels, species were classified into three
different trophic levels which were omnivores (organisms feeding on both plant and animal
84
materials), carnivores (organisms feeding on omnivores) and secondary carnivores (organisms
which consume carnivores).
As for habitat, species were classified according to benthic (organisms which are usually
found on the sea floor) and pelagic (organisms living near the surface of water). Classification
of fish and seafood according to their feeding behaviour was conducted based on information
obtained from www.fishbase.org and Mansor et al. (1998).
4.3
RESULTS
4.3.1 Quality assurance of analytical results
The accuracy of the test method was determined by repeated analysis of certified reference
materials, DORM-2 (Dogfish muscle) from National Research Council Canada. The results
for the analysis of CRM are presented in Table 4.1. These compare well to certified value for
total mercury concentration and attest to the accuracy of the method.
Table 4.1 The mean certified and measured values of metal concentrations (mean ± standard
error) in µg/g dry mass in certified reference material DORM-2
DORM-2
Reference
value
(RV)
Average
RV
Average
Measured
Error
Measured
Recovery
As
75
µg / g
Cd
114
µg / g
Se
77
µg / g
Cu
65
µg / g
Zn
64
µg / g
Fe
54
µg / g
µg / g
18.0 ± 1.1
0.043 ± 0.008
1.4 ± 0.09
2.34 ± 0.16
25.6 ± 2.3
142 ± 10
µg / g
18
0.043
1.4
2.34
25.6
142
µg / g
18.1
0.1
1.4
2.1
25.3
129.9
0.8
0.0
0.3
0.2
3.1
33.5
100
130
98
91
99
91
µg / g
(%)
The calibration curves generated for metals determination were highly linear (r2 > 0.999). The
limit of detection (3 times the standard deviation of procedural blank values) for total metals
measurements was 0.05 μg/L (equivalent to approximately 70 μg/kg dry mass in tissue).
85
4.3.2 Nitrogen and carbon stable isotopes
A total of 43 species of organisms were analysed for carbon and stable isotopes and the
results are as shown in Table 4.2. The highest 15N value was found in Parastromateus niger
representing the omnivores, whereas Loligo edulis and Lutjanus malabaricus recorded the
highest 15N values for carnivores and secondary carnivores respectively. The 15N for
omnivore, carnivore and secondary carnivore ranged from 6.58 to 13.62‰, 8.26 to 15.78‰
and 9.49 to 16.26‰ accordingly.
The 13C values were observed lowest in Decapterus russelli from the omnivore,
Selaroides leptolepis from the carnivore and Thunnus tonggol from the secondary carnivore
groups correspondingly. The 13C ranged from -19.05 to -14.21 in omnivores, -18.95 to 14.27 in carnivores and -17.98 to -14.48 in secondary carnivores. A one way ANOVA test
showed that no significant differences were observed between 13C values and the different
feeding groups (F=3.24; df=2, p=0.05).
The 15N values were not significantly different between benthic and pelagic species
(Student’s T-test, p=0.614) although the 13C showed significant differences between benthic
and pelagic species (Student’s T-test, p=0.016).
Stable nitrogen and carbon isotope data were used to indicate trophic positions of all fish
analysed which is as shown in Figure 4.2. In general, all fish species are occupying respective
trophic levels (omnivore, carnivore and secondary carnivore) based on δ15N values.
Secondary carnivores had clear representation of trophic levels according to 15N values but
omnivores and carnivores had mixed 15N values. Based on information obtained from
literature, discrepancies exist when assigning species to its trophic levels thus 15N values
were used as it provides more accurate information.
86
15N
Secondary carnivore
Carnivore
Omnivore
13C
Figure 4.2 The structure of organisms based on stable nitrogen and carbon
isotope analysis
Description of species- 1. Cistopus indicus 2. Clarias batrachus 3. Dasyatis kuhlii 4. Decapterus russelli 5.
Eythynnus affinis 6. Gymnosarda unicolor 7. Himantura gerrardi 8. Himantura uarnak 9. Lates calcarifer
10. Loligo duvaucelli 11. Loligo edulis 12. Loligo sibogae 13. Loligo uyii 14.Lutjanus johnii 15. Lutjanus
argentimaculatus 16. Lutjanus malabaricus 17. Lutjanus sebae 18. Megalaspis cordyla 19. Metapenaeopsis
barbata 20. Metapenaeus affinis 21. Metapenaeus brevicornis 22. Nemipterus bathybius 23. Nemipterus
japonicus 24. Nemipterus nematophorus 25. Nibea soldado 26. Otolithes ruber 27. Otolithoides biauritus
28. Parapenaeopsis sculptilis 29. Parapenaeopsis hardwickii 30. Parastromateus niger 31. Penaeus indicus
32. Penaeus merguiensis 33. Penaeus monodon 34. Rastrelliger faughni 35. Rastrelliger brachysoma 36.
Rastreliger kanagurta 37. Scomber australasicus 38. Scomberomorus commerson 39. Scombermorus
guttatus 40. Selar boops 41. Selaroides leptolepis 42. Seriola dumerili 43. Thunnus tonggol
87
4.3.3 Trophic transfer of metals
The trophic transfer potentials of the metals were estimated using relationships between the
metal concentrations and the 15N values of the fish species. Linear regressions of log arsenic
and 15N (slope = 0.016, r2 = 0.004, F
1, 41
= 0.170, p = 0.683), log lead and 15N (slope =
0.020, r2 = 0.000, F 1, 41 = 0.003, p = 0.956), log cadmium and 15N (slope = 0.031, r2 = 0.011,
F 1, 41 = 0.277, p = 0.603), log copper and 15N (slope = 0.006, r2 = 0.001, F 1, 41 = 0.042, p =
0.838) showed positive relationships although not significant. Log selenium and 15N (slope =
-0.03, r2 = 0.000, F 1, 41 = 0.007, p = 0.935), log zinc and 15N (slope = -0.016, r2 = 0.012, F 1,
41
= 0.510, p = 0.479) and log iron and 15N (slope = -0.030, r2 = 0.061, F
1, 41
= 2.678, p =
0.109) showed negative non-significant relationships.
4.3.4 Metal concentrations
The mean concentrations of metals in all species with classification according to trophic
levels and habitats are as shown in Table 4.3.
4.3.4.1 Arsenic (As)
Arsenic concentrations ranged from <0.05 to 55.38 µg/g dry mass in Himantura uarnak with
overall mean arsenic concentration of 8.07 ± 9.50 µg/g. It was observed that mean arsenic
concentrations in some species in the secondary carnivores (Lutjanus argentimaculatus,
Euthynnus affinis, Lutjanus johnii and Lates calcarifer) were somewhat lower than mean
arsenic concentrations in the omnivores (Table 4.3). There were no significant differences in
log-transformed arsenic concentrations between trophic levels (F2,
107
= 1.991; p=0.142)
however mean arsenic concentrations were highest in carnivores (9.31 ± 11.27 μg/g dry mass)
> secondary carnivores (5.52 ± 6.02 μg/g dry mass) > omnivores (6.44 ± 4.45 μg/g dry mass).
Significant differences were found between benthic and pelagic mean arsenic concentrations
(p=0.039) with mean benthic arsenic concentrations (9.48 ± 10.45 µg/g dry mass) higher than
pelagic organisms (5.60 ± 7.03 µg/g dry mass).
88
4
1
2
3
3
1
5
2
2
1
Clarias batrachus
Metapenaeopsis barbata
Metapenaeus affinis
Metapenaeus brevicornis
Parapenaeopsis sculptilis
Parapenaeospsis hardwickii
Parastromateus niger
Penaeus indicus
Penaeus merguiensis
Penaeus monodon
Cistopus indicus
Dasyatis kuhlii
Decapterus russelli
Himantura gerrardi
Himantura uarnak
Loligo chinensis
Loligo duvaucelli
Loligo sibogae
Loligo uyii
Megalaspis cordyla
Nemipterus bathybius
Nemipterus japonicus
Nemipterus nematophorus
Nibea soldado
Otolithes ruber
Otolithoides biauritus
Carnivores
Old women octopus
Bluespotted stingray
Slander scad
Sharpnose stingray
Honeycomb stingray
Mitre squid
Indian squid
Sibogae squid
Little Squid
Torpedo scad
Yellowbelly threadfin bream
Japanese threadfin bream
Doublewhip threadfin bream
Soldier croaker
Tigertooth croaker
Bronze croaker
1
4
1
2
1
1
6
1
1
4
1
5
1
6
1
1
n
Scientific name
Common name
Omnivores
Catfish
Sand velvet shrimp
Pink shrimp
Yellow shrimp
Rainbow shrimp
Spear shrimp
Black pomfret
Indian white prawn
Banana prawn
Giant tiger prawn
B
B
B
B
B
B
B
B
B
P
B
B
B
B
B
B
B
B
B
B
B
B
P
B
B
B
Feeding mode
11.93
11.29
8.26
14.54
12.19
N.A.
10.87
13.76
13.52
13.39
11.21
12.04
10.04
13.46
13.67
13.11
6.58
10.68
12.13
11.34
12.13
11.68
13.62
11.97
11.09
12.24
δ15N (‰)*
-15.12
-16.71
-19.05
-14.34
-15.02
N.A.
-18.00
-16.50
-16.99
-16.70
-17.26
-18.03
-17.38
-16.89
-14.27
-16.44
-18.95
-15.42
-14.23
-15.59
-14.21
-15.67
-16.71
-15.15
-15.85
-14.64
δ13C (‰)*
Table 4.2 The nitrogen and carbon stable isotope analysis in commonly consumed fish of West Peninsular Malaysia
89
Lates calcarifer
Euthynnus affinis
Loligo edulis
Lutjanus sebae
Lutjanus malabaricus
Secondary carnivores
Barramundi
Kawakawa
Sword tip squid
Emperor red snapper
Malabar blood snapper
4
2
3
3
5
3
2
2
3
4
6
1
3
1
1
2
3
2
P
P
B
B
B
P
P
P
P
P
P
P
B
P
P
P
B
B
15.68
15.65
15.78
15.83
16.26
8.35
11.78
10.73
9.77
10.52
11.62
12.83
9.52
13.65
9.49
12.75
11.27
12.10
-14.87
-15.35
-16.55
-14.97
-14.48
-18.65
-16.52
-18.18
-18.10
-17.07
-18.42
-17.59
-18.95
-18.02
-17.98
-15.06
-17.37
-16.06
*Note that stable nitrogen and carbon isotope analysis were conducted only on one sample representing each species; B: benthic; P: pelagic
Rastrelliger faughni
Rastrelliger brachysoma
Rastrelliger kanagurta
Scomber australasicus
Scomberomorus commerson
Scomberomorus guttatus
Selar boops
Selaroides leptolepis
Seriola dumerili
Thunnus tonggol
Gymnosarda unicolor
Lutjanus argentimaculatus
Lutjanus johnii
Faughni mackerel
Indo-Pacific mackerel
Indian mackerel
Slimy mackerel
Narrowbarred spanish mackerel
Indo-Pacific king mackerel
Oxeye scad
Yellowstripe scad
Greater amberjack
Longtail tuna
Dogtooth tuna
Mangrove red snapper
John's snapper
90
Metapenaeopsis barbata
Metapenaeus affinis
Metapenaeus brevicornis
Parapenaeopsis sculptilis
Parapenaeospsis hardwickii
Parastromateus niger
Penaeus indicus
Penaeus merguiensis
Penaeus monodon
Pink shrimp
Yellow Shrimp
Rainbow shrimp
Spear Shrimp
Black pomfret
Indian white Prawn
Banana Prawn
Giant Tiger Prawn
Cistopus indicus
Dasyatis kuhlii
Decapterus russelli
Himantura gerrardi
Himantura uarnak
Loligo chinensis
Loligo duvaucelli
Loligo sibogae
Loligo uyii
Megalaspis cordyla
Nemipterus bathybius
Nemipterus japonicus
Nemipterus nematophorus
Old women octopus
Bluespotted stingray
Slander scad
Sharpnose stingray
Honeycomb stingray
Mitre squid
Indian squid
Sibogae squid
Little Squid
Torpedo scad
Yellowbelly threadfin bream
Japanese threadfin bream
Doublewhip threadfin bream
Carnivores
Clarias batrachus
Sand velvet shrimp
Scientific name
Catfish
Omnivores
Common name
1
5
1
4
1
1
6
1
1
2
1
4
1
1
2
2
5
1
3
3
2
1
4
n
13.97
9.29 ± 3.11
8.36
4.09 ± 1.16
6.57
8.17
10.26 ± 3.80
16.25
55.38
15.97 ± 1.61
7.86
25.83 ± 23.38
39.18
9.61
5.53 ± 3.18
5.84 ± 3.65
9.27 ± 4.46
5.24
11.56 ± 2.96
5.26 ± 2.10
7.29 ± 5.50
4.53
BDL
Arsenic
(As)
2.5
2.00 ± 0.72
2.89
3.13 ± 1.04
2.56
3.06
2.36 ± 1.00
1.55
3.07
2.60 ± 0.17
2.31
5.20 ± 2.45
1.3
3.96
2.28 ± 0.81
1.62 ± 1.53
3.02 ± 0.58
0.91
2.15 ± 0.65
1.09 ± 0.62
1.47 ± 0.06
0.34
0.55 ± 0.66
Selenium
(Se)
0.05
0.29 ± 0.51
0.05
2.03 ± 4.03
0.1
0.05
0.05
0.05
0.05
0.05
0.05
0.11 ± 0.12
0.18
BDL
BDL
BDL
0.57 ± 1.17
BDL
0.07 ± 0.03
BDL
0.28 ± 0.33
BDL
BDL
Lead
(Pb)
0.12
0.03 ± 0.05
0.01
0.01 ± 0.05
0.47
0.6
0.51 ± 0.62
2.36
BDL
N.D
0.09
N.D
0.46
0.03
0.10 ± 0.12
N.D
0.11 ± 0.14
BDL
0.02 ± 0.00
0.04 ± 0.03
BDL
0.02
BDL
Cadmium
(Cd)
0.37
0.57 ± 0.61
0.15
3.78 ± 6.48
2.51
1.22
0.80 ± 0.40
0.79
0.09
0.38 ± 0.19
0.5
0.35 ± 0.24
1.85
1.69
1.06 ± 0.61
0.95 ± 0.14
1.32 ± 2.17
1.04
2.01 ± 0.52
1.62 ± 0.30
1.23 ± 0.33
1.58
0.30 ± 0.14
Copper
(Cu)
1.58
1.16 ± 0.67
0.96
4.37 ± 5.31
4.22
4.17
4.25 ± 1.77
3.61
1.16
1.57 ± 0.07
2.27
1.23 ± 0.34
9.7
9.13
3.33 ± 0.05
4.05 ± 1.23
2.38 ± 1.69
2.93
6.48 ± 0.91
3.81 ± 0.83
3.39 ± 0.57
3.23
1.48 ± 0.09
Zinc
(Zn)
Table 4.3 Metal concentrations (µg/g dry mass) in commonly consumed fish of West Peninsular Malaysia
3.61
91
2.10 ± 1.25
1.56
4.30 ± 0.62
1.23
3.17
1.76 ± 0.66
1.32
2.64
2.11 ± 0.05
2.84
2.25 ± 1.91
4.45
4.29
1.95 ± 1.63
5.06 ± 5.33
1.83 ± 0.30
1.27
2.49 ± 0.89
1.69 ± 0.50
4.49 ± 4.39
1.44
1.65 ± 0.39
Iron
(Fe)
Otolithes ruber
Otolithoides biauritus
Rastrelliger faughni
Rastrelliger brachysoma
Rastrelliger kanagurta
Scomber australasicus
Scomberomorus commerson
Scomberomorus guttatus
Selar boops
Selaroides leptolepis
Seriola dumerili
Thunnus tonggol
Gymnosarda unicolor
Lutjanus argentimaculatus
Lutjanus johnii
Tigertooth croaker
Bronze croaker
Faughni mackerel
Indo-Pacific mackerel
Indian mackerel
Slimy mackerel
Narrowbarred spanish mackerel
Indo-Pacific king mackerel
Oxeye scad
Yellowstripe scad
Greater amberjack
Longtail tuna
Dogtooth tuna
Mangrove red snapper
John's snapper
Euthynnus affinis
Loligo edulis
Lutjanus malabaricus
Lutjanus sebae
Kawakawa
Sword tip squid
Malabar blood snapper
Emperor red snapper
BDL: below detection limit; N.D.: not detected
Lates calcarifes
Barramundi
Secondary carnivores
Nibea soldado
Soldier croaker
3
5
3
2
4
2
3
2
1
1
3
1
6
4
3
2
2
3
1
1
6
5.73 ± 4.77
8.13 ± 10.58
5.52 ± 1.71
3.05 ± 3.41
3.33 ± 0.94
4.56 ± 4.72
2.25 ± 2.49
23.50 ± 29.34
5.41
15.42
6.37 ± 2.64
3.47
4.42 ± 0.99
3.39 ± 2.06
3.50 ± 0.78
3.89 ± 0.99
1.84 ± 0.15
2.86 ± 0.58
10.07
6.16
5.61 ± 1.88
2.49 ± 1.55
3.16 ± 1.63
2.59 ± 0.72
2.15 ± 2.97
1.48 ± 0.97
3.79 ± 1.43
2.10 ± 1.54
6.49 ± 3.96
5.77
1.41
3.06 ± 0.29
0.89
2.47 ± 0.99
2.71 ± 0.40
3.95 ± 1.70
2.62 ± 0.52
3.97 ± 1.47
2.45 ± 0.40
4.48
3.34
1.80 ± 0.49
0.05
0.04
0.19
0.05
0.05
0.05
0.05
0.06
-0.01
1
0.06
0.05
0.06
0.03
0.41 ± 0.38
0.05
0.05
0.05
0.05
0.05
0.13 ± 0.18
0.01 ±0.03
0.01 ± 0.04
0.25 ± 0.09
0.02 ± 0.07
BDL
0.01 ± 0.03
BDL
N.D
0.01
1
BDL
0.01
0.04 ± 0.12
BDL
0.03 ± 0.05
0.15 ±0.04
0.01 ± 0.04
0.03 ± 0.04
0.02
BDL
N.D
0.37 ± 0.11
0.78 ± 0.98
1.44 ± 0.68
0.44 ± 0.10
0.20 ± 0.05
0.21 ± 0.03
0.39 ± 0.15
0.53 ± 0.28
0.01
0.25
0.37 ± 0.04
0.24
0.28 ± 0.12
0.71 ± 0.65
0.81 ± 0.28
0.55 ± 0.00
0.29 ± 0.06
0.43 ± 0.11
0.18
0.65
0.42 ± 0.15
0.93 ± 0.17
0.75 ± 0.20
4.04 ± 0.60
2.19 ± 1.90
3.28 ± 4.07
1.08 ± 0.32
1.29 ± 0.28
1.65 ± 1.08
0.01
2.41
2.57 ± 0.47
3.15
1.72 ± 0.66
1.33 ± 0.41
2.18 ± 0.15
3.41 ± 2.28
4.00 ± 0.73
3.24 ± 1.90
1.45
2.16
1.88 ± 0.91
92
1.78 ± 0.82
1.32 ± 0.99
1.58 ± 0.27
2.83 ± 2.92
1.24 ± 0.55
1.63 ± 0.18
3.60 ± 4.08
4.22 ± 3.10
0.01
2.41
2.40 ± 0.61
4.71
1.71 ± 0.78
1.65 ± 0.48
3.67 ± 2.09
6.85 ± 0.21
3.42 ± 0.88
4.48 ± 3.49
2.67
3.35
4.02 ± 6.00
4.3.4.2 Cadmium (Cd)
Cadmium concentrations ranged from <0.05 to 2.36 µg/g dry mass in Loligo chinensis with
overall mean of 0.09 ± 0.30 µg/g (Table 4.3). There were no significant differences in logtransformed cadmium concentrations between trophic levels (F2, 107 = 0.867; p=0.423). The
mean cadmium concentrations were highest in carnivores (0.12 ± 0.37 μg/g dry mass)
followed by omnivores (0.03 ± 0.08 μg/g dry mass) and secondary carnivores (0.05 ± 0.10
μg/g dry mass). No significant differences were observed between benthic and pelagic mean
cadmium concentrations (p=0.141) when Student’s T-Test was conducted.
4.3.4.3 Lead (Pb)
Lead concentrations ranged from <0.05 µg/g dry mass to 8.08 µg/g in Megalaspis cordyla
with an overall mean of 0.19 ± 0.82 µg /g (Table 4.3). There were no significant differences
in log-transformed lead concentrations between trophic levels (F2, 105 = 0.270; p=0.764). Mean
lead concentrations were highest in carnivores (0.23 ± 1.01 μg/g dry mass) followed by
omnivores (0.18 ± 0.53 μg/g dry mass) and secondary carnivores (0.07 ± 0.01 μg/g dry mass).
Benthic and pelagic organisms showed no significant differences (p=0.0709) in lead
concentrations when Student’s T-Test was performed.
4.3.4.4 Selenium (Se)
Selenium concentrations ranged from 0.05 µg/g dry mass in Clarias batrachus to 9.29 µg/g in
Gymnosarda unicolor with overall mean of 2.56 ± 1.49 µg/g (Table 4.3). Significant
differences were observed in log-transformed Se concentrations between trophic levels (F2, 107
= 5.111; p=0.008)(Figure 4.3). Mean Se concentrations were significantly different between
omnivores and carnivores. Mean selenium concentrations were highest in carnivores (2.88 ±
1.53 µg/g dry mass), followed by secondary carnivores (2.43 ± 1.47 µg/g dry mass) and
omnivores (1.81 ± 1.15 µg/g dry mass). Benthic and pelagic organisms showed no significant
differences (p=0.195) in selenium concentrations when Student’s T-Test was performed.
4.3.4.5 Copper (Cu)
Copper concentrations were observed lowest in Himantura uarnak (0.09 µg/g) and highest in
Megalaspis cordyla (13.50 µg/g) with overall mean copper concentration of 0.82 ± 1.41 µg/g
dry mass (Table 4.3). There were significant differences in log-transformed copper
concentrations between trophic levels (F2,
107
= 5.603; p=0.005)(Figure 4.3). Mean Cu
concentrations were significantly different between omnivores and carnivores as well as
93
between omnivores and secondary omnivores. Mean copper concentrations were highest in
omnivores (1.20 ± 1.06 µg/g dry mass), followed by carnivores (0.73 ± 1.63 µg/g dry mass)
and secondary carnivores (0.65 ± 0.70 µg/g dry mass). Benthic and pelagic organisms showed
no significant differences (p=0.734) in copper concentrations when Student’s T-Test was
performed.
4.3.4.6 Zinc (Zn)
Zinc concentrations ranged from 0.47 µg/g dry mass in Lutjanus malabaricus to 12.31 µg/g in
Megalaspis cordyla with overall mean Zn concentration of 2.65 ± 2.09 µg/g (Table 4.3).
There were significant differences in log-transformed zinc concentrations between trophic
levels (F2,
107
= 6.900; p=0.002)(Figure 4.3). Mean Zn concentrations were significantly
different between omnivores and carnivores as well as between omnivores and secondary
carnivores. The highest zinc concentration was observed in omnivores (3.51 ± 2.04 µg/g dry
mass), carnivores (2.46 ± 2.00 µg/g dry mass) and secondary carnivores (2.13 ± 2.09 µg/g dry
mass). No significant differences in Zn concentrations were found between benthic and
pelagic organisms (p=0.902).
4.3.4.7 Iron (Fe)
Iron concentrations ranged from 0.32 µg/g dry mass in Lutjanus malabaricus to 16.03 µg/g
dry mass in Nibea soldado with overall iron concentration of 2.64 ± 2.20 µg/g (Table 4.3).
Significant differences were found in iron concentrations between trophic levels (F2,
107
=
5.289; p=0.006)(Figure 4.3). Mean iron concentrations were significantly different between
carnivores and secondary carnivores. The mean iron concentrations were highest in carnivores
(2.97 ± 2.42 µg/g dry mass) > omnivores (2.45 ± 1.91 µg/g dry mass) > secondary carnivores
(1.60 ± 1.09 µg/g dry mass). No significant difference was found between benthic and pelagic
organisms (p=0.207) when Student’s T-test was conducted.
94
Log 10 Zn concentrations
Log 10 Se concentrations
Omnivore
Omnivore
Carnivore
Secondary Carnivore
Omnivore
Log 10 Fe concentrations
Log 10 Cu concentrations
Carnivore Secondary Carnivore
Trophic Level
Level
Trophic
Trophic Level
Omnivore
Carnivore
Secondary Carnivore
Trophic Level
Trophic Level
Omnivore
Carnivore
Secondary Carnivore
Trophic Level
Trophic Level
Figure 4.3: Box plots showing selenium, copper, zinc and iron
concentrations between trophic levels (µg/g dry mass). Measure of
central tendency is median, boxes indicate data from 25th to 75th
percentiles, whiskers indicate range from 0 to 100th percentile and
individual point outliers. (Note that boxplots are representing only
metals which show significant differences between trophic levels).
95
4.3.5 Relationship of metal concentrations with length
In order to test the relationship of metals concentrations and length, simple linear regressions
were employed. Linear regressions of log copper concentration and length (slope = -0.007,
adjusted r2 = 0.096, F 1, 107 = 12.433, p = 0.001), log zinc concentration and length (slope = 0.006, adjusted r2 = 0.091, F
1, 107
= 11.822, p = 0.001), log iron concentration and length
(slope = -0.004, adjusted r2 = 0.047, F
1, 107
= 6.367, p = 0.013) showed significant negative
relationships (Figure 4.4). Log arsenic concentration and length (slope = -0.002, adjusted r2 =
0.007, F1,
105
= 0.702, p = 0.404), log cadmium concentration and length (slope = 0.007,
adjusted r2 = -0.011, F
1,57
= 0.939, p = 0.337), log lead concentration and length (slope = -
0.004, adjusted r2 = 0.013, F
1,104
= 2.406, p =0.124), log selenium concentration and length
(slope = -0.003, adjusted r2 = 0.004, F1, 107 = 1.454, p = 0.231), did not show any significant
relationships.
4.3.6
Relationship between metal concentrations
4.3.6.1 Correlations with all metal concentrations
In general, mean concentrations in organisms are in the following order: As > Zn > Fe > Se >
Cu > Hg > Pb > Cd. Correlation analyses are shown in Table 4.4. For the purpose of
comparison, mercury concentrations are included in the correlation analyses. A more detailed
description of mercury concentrations are given in Chapter 3.
Mercury concentrations
showed significant negative correlations with cadmium, copper and zinc concentrations.
Arsenic concentrations had significant positive correlations with selenium and cadmium
concentrations. Lead concentrations were positively correlated with copper concentrations
whereas iron concentrations were positively correlated with zinc concentrations. Cadmium
concentrations were positively correlated with copper and zinc concentrations.
96
Log10 Cu concentrations
Log10 Zn concentrations
Length (cm)
Log10 Fe concentrations
Length (cm)
Figure 4.4:
Relationships between
log10 copper, zinc and
iron concentrations
(µg/g dry mass) and
length (in centimetres)
in commonly consumed
fish of West Peninsular
Malaysia. (Note that
regressions are
representing only
metals which show
significant differences
between metal
concentrations and
length of organism)
Length (cm)
97
Table 4.4 Correlation analyses between metals
Hg
Hg
1
As
0.117
Se
0.099
Pb
0.162
Cd
-0.217*
Cu
-0.295**
Zn
-0.504**
Fe
-0.063
As
0.117
1
0.217*
0.18
0.415**
0.095
0.111
-0.002
Se
0.099
0.217*
1
0.018
0.141
-0.067
-0.057
0.153
Pb
0.162
0.162
0.018
1
0.098
0.194*
0.182
0.11
Cd
-0.217*
0.415**
0.141
0.098
1
0.296**
0.362**
0.073
Cu
-0.295**
0.095
-0.067
0.194*
0.296**
1
0.592**
0.152
Zn
-0.504**
0.111
-0.057
0.182
0.362**
0.592**
1
0.403**
Fe
-0.063
-0.002
0.153
0.11
0.073
0.152
0.403**
1
* significant at 0.05 level ** significant at 0.01 level
4.3.6.2
Interactions between mercury and selenium concentrations
The mean molar concentrations of mercury and selenium are shown in Figure 4.5. For ease of
reference, fish from the same family were classified in the same group. In general, mean
molar ratios of selenium were higher than mean molar ratios of mercury in all fish.
Calculated molar ratios of selenium and mercury are presented in Table 4.5. Although
mercury was present in all species, it was observed that there was molar excess of selenium
over mercury in all species of fish. Prawns, pomfrets and mackerels were among species with
particularly high selenium : mercury ratios.
98
Figure 4.5 Molar concentrations of mercury and selenium in fish. Data are expressed as mean
± standard deviation.
99
Table 4.5 Mass, molar concentrations and molar ratios of mercury and selenium in fish species
n
Mercury content
μg / g Hg
μmol / kg
(ww)
Hg
Selenium content
μg / g Se
μmol / kg
(ww)
Se
Se:Hg Hg:Se
Se HBV
Catfish
4
0.02 ± 0.02
0.12 ± 0.09
0.11 ± 0.13
1.38 ± 1.68
11.36
0.09
1.24
Shrimp
10
0.05 ± 0.03
0.25 ± 0.16
0.28 ± 0.15
3.52 ± 1.88
13.87
0.07
3.85
Pomfret
5
0.05 ± 0.02
0.25 ± 0.10
0.60 ± 0.12
7.64 ± 1.48
30.36
0.03
18.31
Prawn
5
0.05 ± 0.04
0.23 ± 0.22
0.47 ± 0.26
5.95 ± 3.27
26.40
0.04
12.41
Stingray
7
0.13 ± 0.13
0.67 ± 0.63
0.83 ± 0.43
10.53 ± 5.51
15.71
0.06
13.05
Squid
13
0.06 ± 0.31
0.31 ± 0.28
0.47 ± 0.17
5.92 ± 2.13
18.97
0.05
8.87
Scad
9
0.11 ± 0.08
0.57 ± 0.39
0.55 ± 0.21
7.00 ± 2.52
12.27
0.08
6.78
Bream
7
0.25 ± 0.20
1.24 ± 1.00
0.44 ± 0.14
5.57 ± 1.74
4.50
0.22
1.92
Croaker
8
0.12 ± 0.04
0.60 ± 0.22
0.47 ± 0.22
5.90 ± 1.23
9.77
0.10
4.54
Mackerel
20
0.07 ± 0.05
0.36 ± 0.25
0.58 ± 0.21
7.35 ± 2.70
20.16
0.05
11.70
Amberjack
1
0.10
0.48
0.28
3.57
7.43
0.13
2.08
Barramundi
4
0.21 ± 0.07
1.07 ± 0.35
0.30 ± 0.19
3.74 ± 2.44
3.50
0.29
0.97
Tuna
5
0.17 ± 0.17
0.85 ± 0.87
0.93 ± 0.66
11.68 ± 8.50
13.80
0.07
12.82
Snapper
12
0.18 ± 0.13
0.90 ± 0.67
0.54 ± 0.29
6.83 ± 3.61
7.58
0.13
4.06
The selenium health benefit value (Se HBV) was calculated as (Se/Hg molar ratio x Total Se) – (Hg/Se molar ratio x total
mercury). Ww denotes concentrations of fish in wet weight.
100
4.3.7 Estimation of potential health risk
The evaluation of human health risk pertaining to consumption of fish was calculated through
the provisional tolerable daily intake (PTWI) for each metal analysed. The estimated daily
and weekly tolerable intakes for all metals in fish are presented in Table 4.6. For ease of
comparison, fish from the same family were classified in the same group. The fish ingestion
rate is 160 g/ day/ person (FAO 2009) whereas average body weight for Malaysian population
is 64 kg (Lim et al. 2000). The estimated weekly intake (EWI) values for metals by an adult
(µg/kg-1 body weight) for various family of fish were calculated using the formula below:
EWI (µg/kg-1) = Mean metal concentrations in fish (µg/g-1 wet weight) x Weekly fish consumption (g)
Body weight (kg)
Among all metals, none of the fish exceeded the estimated daily intake (TDI) and estimated
weekly intake (TWI) except for arsenic. Arsenic daily and weekly intakes were violated in all
fish with the exception for mackerel and barramundi.
101
Selenium*
TDI
TWI
0.27
1.91
0.70
4.87
1.51
10.56
1.18
8.23
2.08
14.55
1.17
8.18
1.10
7.70
1.17
8.16
1.45
10.16
1.38
9.68
0.70
4.93
0.74
5.17
2.31
16.14
1.35
9.43
1.22
8.55
60
420
Lead
TDI TWI
0.03 0.18
0.05 0.36
0.29 2.01
0.04 0.30
0.05 0.33
0.11 0.77
0.05 0.38
0.05 0.36
0.47 3.26
0.50 3.50
0.50 3.50
0.03 0.18
0.02 0.14
0.02 0.16
0.16 1.10
3.60
25
Cadmium
TDI TWI
BDL
0.01
0.05
0.05
0.38
0.02
0.16
0.00 -0.01
0.30
2.07
0.02
0.13
BDL
0.01
0.10
0.01
0.04
0.06
0.41
BDL
BDL 0.03
BDL 0.01
0.05
0.34
1
7
Copper
TDI TWI
0.15 1.04
0.80 5.59
0.66 4.61
0.57 4.00
0.16 1.13
0.60 4.18
0.24 1.70
0.21 1.46
0.25 1.74
0.94 6.60
0.12 0.87
0.10 0.71
0.26 1.80
0.27 1.87
0.38 2.66
500 3500
Zinc
TDI TWI
0.74
5.17
2.19 15.33
1.19
8.34
2.39 16.72
0.66
4.60
2.28 15.97
0.60
4.17
0.93
6.50
1.17
8.18
1.70 11.91
1.20
8.43
1.64 11.49
0.97
6.81
0.47
3.29
1.30
9.07
100
700
Iron
TDI TWI
0.83
5.79
1.21
8.49
0.92
6.41
1.83 12.82
1.13
7.94
0.98
6.86
1.12
7.84
1.88 13.19
1.55 10.83
1.77 12.42
1.24
8.67
0.62
4.33
1.92 13.41
1.01
7.06
1.29
9.00
800
5600
Tolerable Daily Intake (TDI) for all metals except for selenium is expressed as µg/kg body weight/day. Tolerable Weekly Intake (TWI) is expressed as µg/kg
body weight/week. *Reference Nutrient Intake (RNI) is expressed as µg / day. BDL denotes below detection limit.
Catfish
Shrimp
Pomfret
Prawn
Stingray
Squid
Bream
Croaker
Mackerel
Scad
Amberjack
Barramundi
Tuna
Snapper
Average
PTWI / RNI*
n
4
10
5
5
7
13
9
7
8
20
1
4
5
12
Arsenic
TDI
TWI
BDL
3.74
26.18
4.63
32.44
3.23
22.64
13.62
95.32
5.70
39.93
4.91
34.39
3.12
21.83
1.77
12.36
2.60
18.20
7.71
53.97
1.66
11.65
5.85
40.95
3.02
21.14
4.74
33.15
2.1
15
Table 4.6 The Provisional Tolerable Daily and Weekly Intake for all metals in fish from West Peninsular Malaysia
102
4.4
DISCUSSION
4.4.1 Stable isotope analysis
From the trophic structure of carbon and nitrogen in fish depicted in Figure 4.1, it was
observed that the classification of organisms according to information obtained from
www.fishbase.org and Mansor et al. (1998) showed some discrepancies with the result from
stable isotope analysis. Two distinct species were classified as secondary carnivores but the
trophic structure from stable isotope analysis revealed that those two species were in similar
range of 15N values of the carnivorous species. Hence, stable isotope of nitrogen can be used
to determine food web structure (Minagawa and Wada 1984) and provide accurate assignment
of species to its respective trophic levels. This agrees well with findings from previous
researchers [DeNiro and Epstein (1981); Lajtha and Michener (1994); Post (2002)] who
reported that 15N values provide a more accurate description of trophic level occupied by a
specific organism.
4.4.2 Trophic transfer of metals
Traditionally, biomagnification of contaminants in aquatic food web is evaluated by
comparisons of contaminants in tissues of preys and predators, feeding behaviour or analysis
of stomach content (Suedel et al. 1994). Biomagnification can be defined as continuous
bioconcentration of metals with increasing trophic level and the potential of biomagnification
can be described as the ratio of metal concentration in predator organism to metal
concentration in its prey. Biomagnification is likely to occur if this ratio is > 1 (Reinfelder et
al. 1998). In this study, the biomagnification of metals (As, Cd, Pb, Se, Cu and Zn) and the
15N values of the fish species were investigated. In general, a significant positive correlation
between metal concentrations and 15N indicates that the substance is biomagnified through a
food chain, whereas a negative correlation suggests that biodilution has occurred.
It was observed that none of the metal concentrations were significantly correlated with 15N
values even though metals such as arsenic, lead, cadmium and copper showed positive albeit
non-significant relationships. Selenium, zinc and iron had non-significant negative
relationships with the 15N values. Thus, no metal is being biomagnified whereas Se, Zn and
Fe were being biodimuniated.
103
Previous studies (Asante et al. 2010; Zhu et al. 2013) have revealed positive relationship
between some metal concentrations and 15N with the value of regression slopes ranging from
0.06 to 0.34. The slope values observed in this study are lower hence resulting in the nonsignificant positive relationship between metal concentrations and the 15N values.
Furthermore, the negative slopes observed could be attributed to the fact that only fish and
seafood communities were included in the study while other organisms at lower trophic levels
such as phytoplankton, zooplankton and invertebrates were not studied (Zhu et al. 2013).
Earlier studies have reported conflicting results for the biomagnification of metals in marine
organisms. Asante et al. (2010) showed that arsenic concentrations biomagnify in fish from
the Sulu Sea. Suedel et al. (1994) suggested that arsenic has the potential to biomagnify in
aquatic ecosystem. Arsenic concentrations were reported to be positively correlated with 15N
in liver and muscle of seabirds from Arctic marine food web (Campbell et al. 2005b). Dietz et
al. (2000) reported evidence of cadmium biomagnification in food chains of freshwater and
marine ecosystems. Bismuth concentration was also found to biomagnify in fish and
crustaceans from the East China Sea (Asante et al. 2008). Kehrig et al. (2013) reported
biomagnification of selenium and mercury in coastal food web of Brazil.
Some studies have reported no significant correlations between 15N or the trophic level and
metal concentrations, which suggested no occurrence of biomagnification or biodilution.
Zhang and Wang (2012) conducted a large scale investigation of twelve metal concentrations
and stable isotopes in marine wild fish from Chinese waters and found that none of the metal
concentrations were showing positive relationship with 15N values. Similarly, arsenic is
generally not known to biomagnify through the food chain (Kubota et al. 2001; Kunito et al.
2008). Ikemoto et al. (2008) found that trace elements in their study were not biomagnified or
biodiluted through the food chain in Mekong River Delta.
4.4.3
Metal concentrations
4.4.3.1
Arsenic (As)
In general, most of marine organisms contain detectable concentrations of inorganic and
organic arsenic in their tissues (Neff 2002). Sources of arsenic exposure include emissions of
ore mining and processing industry, dye manufacturing facilities, tanneries, thermal power
plants and application of certain pesticides, herbicides and insecticides (Sarkar and Datta
104
2004). Similar to mercury, arsenic can occur in the environment in several oxidation states
with the non-toxic form normally encountered in the aquatic organisms (Moore 1991).
Organo-arsenic species such as arsenobetaine, arsenoribosides and arsenocholine are among
the non-toxic forms of arsenic (Shrain et al. 1999). The inorganic form of arsenic, trivalent
arsenite is more mobile, more soluble and are 50 times more toxic than pentavalent inorganic
arsenate, and several hundred times more toxic than monomethylarsonic acid (MMA) and
dimethylarsinic acid (DMA) (Jain and Ali 2000).
The mean arsenic concentration in this study was 8.14 ± 0.92 μg/g dry mass with the highest
mean arsenic concentration found in Himantura uarnak, a stingray species with arsenic
concentration of 55.38 μg/g dry mass. In a study by Saei-Dehkordi et al. (2010) in the Persian
Gulf, a much lower mean arsenic concentration was measured in Epinephelus coioides, an
Estuary cod at 0.83 ± 0.41 μg/g wet weight. Likewise, arsenic concentrations in three pelagic
fish from the Atlantic Ocean (Sardine pilchardus, Scomber japonicus and Trachurus
trachurus) exhibited low arsenic concentrations with a range of 0.81 – 0.99 μg/g wet weight
(equivalent to 4.04 – 4.95 μg/g dry mass).
It was observed that although arsenic concentrations did not significantly differ between the
trophic levels, the mean arsenic concentrations were highest in carnivores > omnivores >
secondary carnivores. This finding corresponds with the result reported by Hao et al. (2013)
that arsenic concentrations in fish from Lake Taihu, China were not significantly different
across the trophic levels although mean arsenic concentrations they measured found to be
increasing from herbivores to omnivores to carnivores.
The Australian Foods Standard Code allows a maximum of 1 mg/kg inorganic arsenic in fish.
When the mean arsenic concentrations in fish were compared with the permissible level, some
of the fish exceeded the 1 mg/kg limit however, it should be noted that arsenic is commonly
occurring in seafood as arsenobetaine; which is non-toxic, not metabolized in vivo and
eliminated rapidly via kidneys (half-time of 18 hours)(Buchet et al. 1980; Maher and Butler
1988; Francesconi 2007). Hence, regardless of the high arsenic concentrations detected in
some of the fish tissues, consumption of these fish do not pose threat to human health.
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4.4.3.2
Cadmium (Cd)
Cadmium is an industrial and environmental contaminant that may affect humans due to its
toxicity. Every year, it is estimated that 30 000 tonnes of cadmium are released into the
environment, with an approximate of 4 000 to 13 000 tonnes originating from anthropogenic
sources (ATSDR 2003). Cadmium environmental levels may increase as a result of both
natural and man-made activities including industrial emissions as well as the application of
fertilizer and sewage sludge to farm land (ATSDR 2003). Even though cadmium is present in
aquatic organisms and marine environment in minute amounts, salinity can affect speciation
of cadmium while bioaccumulation is affected both by temperature and salinity (Ray 1986).
The absorption of cadmium in humans and animals occurs through similar process as the
absorption of essential metals such as iron by which the absorption process is enhanced by
dietary deficiencies of calcium and iron and by low protein diets (Goyer and Clarksom 2001).
Cadmium was detected in 65 (59%) samples of all samples analysed (Table 4.3). The mean
cadmium concentration in this study was 0.09 ± 0.30 μg/g dry mass. This is comparable to the
findings of several other researchers who reported cadmium concentrations of 0.03 μg/g wet
mass in the fish species; Epinehelus aerolatus (Ganbi 2010) and Etroplus suratensis
(Sivaperumal et al. 2007). In addition, the mean cadmium concentration of 0.04 ± 0.12 μg/g
dry mass for Scomberomorus guttatus in this study was found to be 3.8 times lower than the
mean cadmium concentration of the same fish species reported by Sivaperumal et al. (2007).
Bashir et al. (2012) found similar cadmium concentrations for Arius thalassinus and Pennahia
anea (both 0.02 ± 0.01 µg/g dry mass) in Kapar and Mersing of Peninsular Malaysia which
are in good agreement with findings from this study.
Similar to arsenic, cadmium concentrations were not significantly different between the
trophic levels. The mean cadmium concentrations were highest in carnivores followed by
secondary carnivores and omnivores. Evidence of cadmium biomagnification up the food
chain has been inconsistently reported (Roméo et al. 1999; Storelli and Marcotrigiano 2004).
The inter-species difference in cadmium concentrations might be influenced by feeding
behaviour and intrinsic factors such as different rates of physiological process and uptake of
metals (Storelli and Marcotrigiano 2004; Storelli et al. 2005).
The Malaysian Food Regulations (1985) sets maximum allowable cadmium in fish as 1 μg/g
while the Codex Committee on Food Additives and Contaminants recommends cadmium
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limit of 0.5 mg/kg (Ikem and Egiebor 2005). None of the fish species exceeded the
permissible level and thus the fish are safe for consumption.
4.4.3.3 Lead (Pb)
Similar to mercury, lead is ubiquitous in the environment (Castro-Gonzaléz and Méndez
Armenta (2008). Lead is being used widely in lead smelting and refining industries, battery
manufacturing plants as well as plastics and printing industries (Goyer 1993). Lead may enter
the body through intestines, ingestion; through the lungs, inhalation; through the skin,
adsorption; or by direct swallowing and ingestion (Goyer and Clarksom 2001). Lead in blood
has an estimate half-life of 35 days, in soft tissue 40 days and in bones 20–30 years with
longer biological half-life of lead observed in children compared to adults (Papanikolaou et al.
2005). Environmental lead exposure remains an important public health issue despite
extensive control measures particularly in the use of lead-based paints and leaded fuel
(Oulhote et al. 2011). In France and the USA, the primary source for lead in children is from
lead-based paint with blood lead level recorded at more than 100 µg/L in non-industrial
environments (Jacobs et al. 2002).
Among all metals analysed, detectable lead concentrations were present in only 19 (17%)
samples (Table 4.3). The majority of the samples were below detectable limit. One fish
sample, Megalaspis cordyla had the highest lead concentration (8.08 μg/g dry mass) and was
treated as an outlier. When this particular species was removed from the dataset, the mean
concentration of lead became 0.12 ± 0.30 μg/g dry mass instead of 0.19 ± 0.82 μg/g dry mass.
The mean lead concentrations measured in this study is comparable with the mean lead
concentrations reported by Burger and Gochfeld (2005) in commercial fish (croaker, red
snapper, whiting, shrimps, flounder, yellowfin tuna) in New Jersey (0.20-1.70 μg/g dry mass).
Al-Busaidi et al. (2011) also measured lead concentrations in commercial marine fish in
Oman and mean lead concentrations of 0.10 – 0.98 μg/g dry mass were reported. Sivaperumal
et al. (2007) confirmed that lead was present in 25% of the total samples of fish, shellfish and
fish products analysed with lead concentrations in the range of <0.07-1.32 μg/g wet mass.
Morgano et al. (2011) reported higher lead concentrations in four different species of fish in
Brazil with mean lead concentrations of 0.13 – 2.41 μg/g dry mass).
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Similar to the trends portrayed by arsenic and cadmium, lead concentrations showed no
significant differences between the trophic levels. Mean lead concentrations were highest in
carnivores followed by omnivores and secondary carnivores. This is in agreement with Dietz
et al. (2000) who reported that lead concentrations were not increasing towards higher trophic
levels indicating that biomagnification of lead is not occurring in the marine food web.
The European Union (EU) acceptable limit for lead is 0.3 μg/g wet weight. According to the
Malaysian Food Regulations (1985), permissible limit of lead is 2 μg/g wet weight; which is
higher than the EU limit. Overall, all fish based on lead concentrations are safe for human
consumption.
4.4.3.4 Selenium (Se)
Selenium is an essential micronutrient although it can be toxic at high concentrations (Coyle
et al. 1993). The threshold level for selenium toxicity in some fish is about 1 µg/g (wet
weight) while muscle concentrations of 2.6 µg/g are associated with adverse effects in the fish
themselves (Lemley 1993). It is hard to find a balance between essentiality and toxicity as
selenium demonstrates a narrow concentration range between these two aspects (Sappington
2002).
Selenium was present in 109 (98%) samples analysed (Table 4.3). The mean selenium
concentration of 2.56 ± 1.49 µg/g dry mass in this study is lower than the mean selenium
concentration observed in fish from Lake Macquarie (6.9 ± 0.4 µg/g dry mass) reported by
Barwick and Maher (2003). Burger et al. (2001) reported much lower selenium concentrations
in a variety of fish species of Savannah River, ranging from 0.70 - 2.50 µg/g dry mass.
Olmedo et al. (2013) found median concentrations of selenium for a mackerel species,
Scomber scombrus at 1.12 µg/g dry mass compared to mean selenium concentrations of 2.90
µg/g dry mass for various mackerel species in this study.
Mean selenium concentrations were found to be increasing in the following order: omnivores
< secondary carnivores < carnivores (Figure 4.3). Selenium concentrations were significantly
different between omnivores and carnivores. Selenium concentrations were found to be not
increasing with trophic levels. This is contrary to finding from Barwick and Maher (2003)
who reported that mean selenium concentration were increasing towards higher trophic level.
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A study conducted by Saiki et al. (1993) in San Joaquin River system reported that selenium
concentrations were increased in the food chain from filamentous algae to invertebrates, but
the selenium concentrations from invertebrates to fish did not. This implies that seleniumenriched detritus is an important vector for the transfer of selenium through the food chain
and predatory fish from higher trophic levels accumulates less selenium than their prey which
feed on high concentrations of dietary selenium.
The National Health and Medical Research Council of Australia (NHMRC) (Bebbington et al.
(1977) recommends a maximum of 2 ppm wet weight of selenium in seafood. No permissible
value for selenium was available by the Malaysian Food Regulations (1985). All fish
measured for selenium were within permissible level of selenium set by the NHMRC.
4.4.3.5
Copper (Cu)
Copper is an essential element for growth and metabolism of living organisms (Carbonell and
Tarazona 1994) and it is found naturally in water as a free ion or as a complex with humic
acids, carbonate and other inorganic and organic molecules (Stratham 1987). The major
sources of copper may originate from mining operations, agriculture, sludge from publiclyowned treatment works (POTWs) and municipal and industrial solid waste (ATSDR 2004). In
humans, exposure to copper may be derived from drinking water (water distribution system)
and food (consumption of shellfish, organ meats such as liver and kidney, legumes and nuts)
(ATSDR 2004).
Copper was present in all samples analysed (Table 4.3) The mean copper concentration
measured was similar to concentrations reported in fish from uncontaminated sites (0.2-4.75
µg/g dry mass) (Brooks and Rumsey 1974; Denton and Burdon-Jones 1986). Olmedo et al.
(2013) found copper concentrations of 8.78 µg/g dry mass in scad and 10.47 µg/g dry mass in
mackerel. Copper concentrations in scad and mackerel in this study are 5 and 23 times lower
than those found by Olmedo et al. (2013). Papetti and Rossi (2009) also found almost similar
concentrations to those reported by Olmedo et al. (2013) by which copper concentrations
were 17.31 µg/g dry mass in mackerel and 13.23 µg/g dry mass in scad.
While majority of the fish and seafood samples exhibited low copper concentrations (below
than 1 µg/g dry mass), a few species showed notable higher copper concentrations especially
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in shrimps and prawns (range between 1.00 – 2.57 µg/g dry mass). The higher copper
concentrations found in these crustaceans could probably reflect active accumulation of
copper by these species for incorporation into the respiratory pigment haemocyanin; a copperbased pigment found in blood of many species of molluscs and crustacean (Clarke 1986).
These results are in accordance with those found by Storelli (2009) who reported higher
copper concentrations of 23.77 mg/kg wet weight in cephalopods compared to 1.35 mg/kg
wet weight in fish.
Mean copper concentrations were observed highest in omnivores, followed closely by
carnivores and secondary carnivores (Figure 4.3). Mean copper concentrations differed
significantly between omnivores and carnivores as well as between omnivores and secondary
carnivores. Barwick and Maher (2003) reported contrary results; copper concentrations were
not increasing with the increasing trophic level in temperate seagrass ecosystem in Lake
Macquarie, Australia. Similarly, Schafer et al. (1982) reported that copper concentrations
showed no clear differences between trophic level and body burden in three food webs, two
off Southern California and the third in the tropical Pacific Ocean.
The Malaysian Food Regulations (1985) has set maximum level of 30 μg/g of copper whereas
the Australian Foods Standard Code regulates copper level of 10 μg/g. In comparison with the
copper concentrations in fish, none of the fish exceeds the permissible copper limit indicating
that the fish is not posing health risk to the consumers.
4.4.3.6 Zinc (Zn)
Zinc is an essential trace element in all living organisms (Eisler 1993). It is abundant in the
environment, constituting 20–200 ppm of the Earth's crust and zinc is not found as elemental
zinc in nature, instead being found mainly as zinc oxide or sphalerite (ZnS) (ATSDR 2004).
Zinc is released into the environment as the result of mining, smelting of zinc, lead and
cadmium ores, steel production, coal burning and burning of wastes (ATDSR 2004).
Zinc was present in all samples (Table 4.3). Zinc concentrations measured in this study were
similar to those reported for uncontaminated sites (2.5 – 180 µg/g dry mass) (Bebbington et
al. 1977; Brooks and Rumsey 1974; Denton and Burdon-Jones 1986). The highest mean zinc
concentration by species is attributed by Parapenaeopsis sculptilis, a shrimp species (6.48 ±
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0.91). Zinc concentrations reported by Olmedo et al. (2013) in scad and mackerel were 70.46
µg/g and 40.45 µg/g dry mass respectively which were 21 and 17 times higher than zinc
concentrations in scad and mackerel observed in this study. Likewise, Papetti and Rossi
(2009) also found higher zinc concentrations in mackerels in Italy ranging from 20 – 145 µg/g
dry mass.
It is widely reported in the literature that some marine animals contain more zinc than others.
For example, Ruiz and Saez-Salinas (2000) reported that zinc concentrations in the soft
tissues of deposit-feeding clams from the Bilbao Estuary, Spain vary seasonally between 1700
and 4140 µg/g dry mass and the digestive glands of the clams may contain up to 8000 µg/g
dry mass suggesting that the clams are ingesting and retaining zinc-contaminated sediment
particles. Equally, some barnacles in Hong Kong had nearly 20 000 µg/g dry mass of zinc
(Phillips and Rainbow 1988) while barnacles, Balanus improvises from the Gulf of Gdansk,
Poland had zinc in the range of 5 000 to 11 000 µg/g dry mass (Rainbow et al. 2000).
Mean zinc concentrations were found highest in omnivores followed by secondary carnivores
and carnivores (Figure 4.3). Significant differences in mean zinc concentrations were found
between omnivores and carnivores. Biomagnification across trophic levels was not occurring
with zinc concentrations. This is consistent with previous investigations that zinc did not
biomagnify through the food web examined (Hao et al. 2013; Barwick and Maher 2003; Ward
et al. 1986). Zinc biomagnification, however reported to occur in an estuarine food web
(Amiard et al. 1980) and littoral food web (Timmermans et al. 1989).
The maximum permitted concentration of zinc for human consumption regulated by the
Malaysian Food Regulations (1985) is 100 μg/g. Zinc concentrations in fish studied were
relatively low and thus pose no threat to humans.
4.4.3.7 Iron (Fe)
Iron is ubiquitous in nature and is one of the essential metal which is involved in oxygen
transfer, respiratory chain reactions, DNA synthesis and immune function (Bury et al. 2012).
Regarded as one of the most important metals to be mined in the world, about 98% of iron
extracted is used in steel production, a key component for the majority of manufacturing,
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transport, and building industries (Bury et al. 2012) as well as being used in remediation of
contaminated water (Zhang 2003).
Similar to zinc, iron was present in all fish analysed (Table 4.3). Higher iron concentrations
were reported by Tuzen (2009a) for ten different fish species from the Black Sea, Turkey with
mean iron ranging from 36.2 - 145 µg/g wet mass. Similarly, iron concentrations in the
literature have been reported in the range of 0.82 – 27.35 µg/g dry mass in fish from
Iskenderun Bay, Northern East of Mediterranean Sea, Turkey (Turkmen et al. 2005), 1.86 53.1 µg/g dry mass in fish from Taihu Lake, China (Hao et al. 2013) and 10.4 - 249.7 µg/g
dry mass in fish from North East Coast of India (Kumar et al. 2012).
The mean iron concentrations were highest in carnivores, omnivores and secondary
carnivores (Figure 4.3) indicating that biomagnification of iron is not occurring with iron
concentrations. This is in agreement with Hao et al. (2013) who reported that iron was not
biomagnifying through the food web examined. The biomagnification of iron in the metalimpacted Baltic Sea was studied by Nfon et al. (2009). Total iron concentrations were found
to be decreasing with successive trophic enrichments of δ15N in zooplankton, mysids and
herring which indicates biodilution in marine food chain.
While World Health Organization (1989) regulates iron concentration at 50 µg/g, permissible
level of iron is not stipulated by the Malaysian Food Regulations (1985). Overall, none of the
fish studied pose risk to health as the iron permissible level is not exceeded.
4.4.4
Relationship of metal concentrations and feeding habit
All metal concentrations showed no differences between feeding habit with the exception for
one metal. Mean arsenic concentrations significantly differed between benthic and pelagic
organisms with higher mean arsenic concentrations observed in benthic organisms. This is in
agreement with Bustamante et al. (2003) who reported higher mean concentrations of Cd and
Zn concentrations in benthic fish compared to pelagic fish from Kerguelen Islands. Similarly,
Rejomon et al. (2010) reported higher concentrations of Fe, Ni and Cu in Caranx
melampygus, a bottom-dwelling fish in comparison with other fish species studied from
coastal waters off Mangalore. Higher concentration of metals are expected in benthic species
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than the pelagic species, which may be related to the greater exposure to metal enriched
bottom sediments and its interaction with benthic organisms (Campbell et al. 1988).
4.4.5
Relationship of metal concentrations and length
It was observed that some metals had significant negative relationship between length and
metal concentrations (Figure 4.4) while some metals did not show any distinct trends. Log
copper, zinc and iron concentrations showed significant negative relationships with length
whereas log arsenic, cadmium, lead and selenium concentrations did not show any discernible
significant relationships with length. This shows that older organisms tend to have lower
metal concentrations in the body.
Canli and Atli (2003) reported that the accumulation of Cd, Cr, Cu, Fe, Pb and Zn decreased
with an increment in the size of some fish species from the Mediterranean Sea which is in line
with the findings of this study with the exception for iron concentrations which were found to
be significantly related with length. Al-Yousuf (2000) found that the length of Lethrinus
lentjan was negatively correlated with cadmium and copper concentrations while no clear
relationship between zinc concentrations and length were observed. Farkas (2003) reported
significant lead and mercury concentrations with length of bream, Abramis brama L. in Lake
Balaton, Hungary. Widianarko et al. (2000) observed significant associations between lead
concentrations with body weight of guppy Poecilia reticulata in Semarang, Indonesia
whereas zinc and copper concentrations were found to be independent of body weight.
4.4.6
Relationship between metal concentrations
4.4.6.1
Correlations
Metals in the aquatic ecosystem can be taken up and bioaccumulated by fish. Several
environmental factors may affect this process such as water temperature, water hardness,
salinity, availability of metals to fish as well as intrinsic factors such as species, trophic level,
habitat, age, size and metabolic rate of fish (Spry and Weiner 1991; Pourang 1995;
Widianarko 2000). The accumulation of certain metals may be altered by the presence of
other metals (Pelgrom et al. 1995). As metals in the natural environment are co-occurring
with each other, interactions among them may result in either synergistic or additive effects
but in some instances antagonistic effect are likely to occur (Jezierska and Witeska 2001).
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Inter-metal correlations of fish species were assessed and presented in Table 4.3. Several
metals such as arsenic and selenium, copper and zinc, iron and zinc, lead and copper, arsenic
and cadmium were showing correlations with each other signifying similar accumulation
behavior of these metals in fish (Kumar et al. 2011). Significant correlations among metals
may reflect a common source of metals and may indicate similar biogeochemical pathways
for accumulation of metals in fish tissues.
4.4.6.2 Mercury and selenium concentrations
A body of literature suggested that selenium have protective effects over mercury (Kai et al.
1995, Ganther and Sunde 2007; Berry and Ralston 2008). Methyl mercury is intimately linked
to its high binding affinities with selenium (Berry and Ralston 2008) by which methyl
mercury inhibits selenoprotein; which play an important role in reversing or preventing
oxidative brain damage due to mercury toxicity (Ralston et al. 2008). A positive correlation
between selenium and mercury in fish from the mercury-contaminated Madeira River was
reported by Dorea et al. (1998) and a higher molar ratio (Hg:Se) in piscivorous compared to
herbivorous fish was observed.
This study found that Se: Hg molar ratios in all fish species were more than 1 and ranged
from 4.50 to 30.36. This is in accordance with the findings of some researchers (Kaneko and
Ralston 2007; Kehrig et al. 2009; Burger and Gochfeld 2012; Seixas et al. 2012) who reported
that marine fish tend to have Se:Hg molar ratios above 1:1. Se:Hg ratios of more than 1
provide the protection of selenium against adverse mercury effects (Peterson et al. 2009) and
thus allows seleno-enzyme processes to continue unaltered (Ralston et al. 2008).
Nevertheless, it is difficult to utilize the Se:Hg molar ratio in risk assessment and risk
management as information of the interaction between mercury and selenium is somewhat
limited and further studies have to be conducted on the relationship between the molar ratios
and health outcomes (Burger and Gochfeld 2012).
It was observed that all the Se-HBV calculated in this study were positive and did not have a
wide variation. As a result of higher selenium and lower mercury concentrations, all studied
species presented a positive mean Se-HBV, ranging from 0.97 in barramundi to 18.31 in
pomfret. The positive Se-HBV values suggest that they showed selenium to potentially
protect them and their consumers against mercury toxicity. In comparison with other Se-HBV
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from the literature, Jones et al. (2013) reported positive as well as negative Se-HBV for sand
flathead obtained from three different regions in Australia. Kaneko and Ralston (2007)
measured Se-HBV in pelagic fish from North Pacific Ocean and found that all fish had
positive Se-HBV except for mako shark which showed higher molar excess of mercury over
selenium ratio. Likewise, Kehrig et al. (2013) observed that median Se-HBV for commonly
consumed seafood in Brazil showed positive values in the seafood studied with the exception
of 1.1% of the overall samples.
4.4.7 Estimation of potential health risk
The ‘tolerable intake’ is widely used to describe ‘safe’ levels of intake; and can be expressed
on either a daily basis (TDI or tolerable daily intake) or a weekly basis (TWI or tolerable
weekly intake). The tolerable intake of heavy metals as PTWI (Provisional Tolerable Weekly
Intake), are set by the Food and Agriculture Organization/World Health Organization
(FAO/WHO) Joint Expert Committee on Food Additives (JECFA). PTWI is the maximum
amount of a contaminant to which a person can be exposed per week over a lifetime without
an unacceptable risk of health effects.
All fish analysed were well within the PTWI except for one metal. Arsenic intakes estimates
showed levels of concern in majority of fish. The arsenic TDI and TWI ranged from 1.4 to 6.5
times higher than the allowable PTWI for arsenic. Different forms of arsenic can be present in
marine fish which vary in toxicity. Arsenic can exist in inorganic forms as arsenite (As3+) and
arsenate (As5+) as well as organic forms such as monomethylarsonic acid (MMA),
dimethylarsenic acid (DMA), arsenobetaine (AsB), arsenocholine (AsC) and a series of
arsenolipids and arsenosugars (Elci et al. 2008). Inorganic arsenic, arsenite (As3+) and
arsenate (As5+) are the most toxic form of arsenic (Tuzen et al. 2009b). In the diet, organic
arsenic are the most prevalent form of arsenic and inorganic arsenic typically accounts for 13% of the total arsenic found in food (FSA 2004). In most fish and seafood, arsenobetaine
which is the major form of organic arsenic; are not metabolised in humans, is excreted
unchanged and is widely assumed to be of no toxicological concern to humans (EFSA 2009).
As for selenium, no PTWI values were established by JECFA. Thus, reference nutrient intake
(RNI) was used as surrogate to compare selenium intakes in humans with other metals. The
United Kingdom RNI of 75 µg/day for men and 60 µg/day for women (Rayman 2000) has
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been determined as the intake believed to be necessary to maximise the antioxidant
selenoenzyme GPx in plasma, which occurs at a plasma selenium concentration around 95
μg/L (Thomson et al. 1993). A much lower selenium intake by WHO/FAO/IAEA expert
group recommends only 40 µg/day for men and 30 µg/day for women on the basis that only
two-thirds of the full expression of GPx activity was required (WHO 1996).
Based on the PTWI calculated for metals in fish in this study, PTWI for copper, cadmium and
zinc reported by Tύrkmen et al. (2008) were considerably higher than PTWI for copper,
cadmium and zinc in fish of Mediterranean Seas, Turkey ranging from 0.048 mg to 2.34 mg,
0.003 mg to 0.042 mg and 2.5 mg to 10.12 mg respectively. The weekly fish consumption in
Turkey was 140 g with adult average body weight of 70 kg. Mukherjee and Bhupander (2011)
also reported higher PTWI for cadmium in fish of Bay of Bengal, India (0.91 µg/kg body
weight per week) while PTWI for arsenic (1.28 µg/kg body weight per week) was higher than
reported in this study.
4.5
Summary and Conclusions
Fish is a commodity of potential public health concern as fish are prone to contamination
from a wide range of environmentally persistent chemicals including polychlorinated
biphenyls (PCBs), pesticides as well as heavy metals. As the fish intake of the Malaysian
population is high at 58 kg per capita per person, consumption of fish with high levels of
contaminants may pose significant risk to health due to the tendency of fish to
bioaccummulate metals through the food chain.
This study aimed to measure the metal concentrations (arsenic, cadmium, lead, selenium,
zinc, copper, iron) in commonly consumed fish of West Peninsular, Malaysia and to identify
potential health risks that might be associated with current dietary intakes of these
commodities. All fish species studied were well within the maximum permitted
concentrations of metals stipulated by the Malaysian Food Regulations, the World Health
Organization, the European Commission, the Australian Foods Standard Code as well as the
Australian National Health and Medical Research Council except for arsenic which exceeded
the permissible limit. Nevertheless, as the level recommended for arsenic by the regulation is
for inorganic arsenic, the measured arsenic concentrations is not a matter of concern as
marine fish tends to accumulate arsenic in the form of arsenobetaine, which is not toxic.
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The accumulation of metals in fish can be influenced by several factors such as trophic levels,
habitat, age, length of fish, intra and interspecies variation as well as metabolism. Mean
selenium, copper, zinc and iron concentrations showed significant differences between trophic
levels while only arsenic exhibited significant differences in mean concentrations between
benthic and pelagic fish. Inverse relationships between length of fish and metal concentrations
were observed for copper, zinc and iron. Despite significant differences observed between
trophic levels and metal concentrations, there was no evidence of biomagnification of metals
as demonstrated when the δ15N values were regressed with the metal concentrations.
Considering the protective effects of selenium over mercury, the selenium:mercury molar
ratios were calculated for fish species studied. All fish with Se:Hg molar ratios of more than 1
signifies protection against mercury toxicity. In addition, the selenium health benefit value
observed in this study was positive, indication of expected health benefits from fish
consumption. In addition, the Provisional Tolerable Weekly Intake (PTWI) calculated for all
metals showed that all fish are safe for human consumption except for arsenic. As mentioned
previously that most arsenic in fish are present as arsenobetaine which is the non-toxic form
of arsenic, thus this is not a major health issue to the public.
In summary, this study has provided insights into the metal concentrations found in
commonly consumed fish of West Peninsular Malaysia. Based on the results of this study, the
metal concentrations in fish are within the maximum permitted concentrations of the
guidelines and can be safely consumed by the public without posing any significant health
risk. It is worth to note that the frequency of fish consumed is different from one person to
another and hence the risk associated with high fish consumption may pose adverse health
effects.
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CHAPTER 5
A STUDY ON MERCURY-BINDING PROTEIN IN FISH
5.1
INTRODUCTION
Regarded among one of hazardous metals in the environment, mercury has no known
biological function for living organisms and is widely distributed throughout the aquatic
environment (Jackson 1998). Mercury can exist in three different oxidation states namely
elemental, inorganic and organic with methyl mercury being the most toxic form of organic
mercury (Clarkson and Magos 2006; Storelli et al. 2002). Mercury is among a few pollutants
which can biomagnify in the aquatic food chain (Ribeiro et al. 1996) and has a high affinity to
lipids which enables it to cross cell membranes easily, hence interferes with cell metabolism
(Pinho et al. 2002; Storelli et al. 2002). Bioaccumulation of fish occurs mainly in muscle
tissue as methyl mercury is readily absorbed across the gills and gut of fish (Klinck et al.
2005). Although humans can be exposed to mercury via thimerosal which release ethyl
mercury after oral administration as well as release of inorganic mercury from dental
amalgams, consumption of fish high in mercury concentrations is regarded as the major route
of exposure to humans (Clarkson et al. 2003).
Toxicity, biochemical behaviour and transport of mercury in the environment are clearly
dependent on its chemical form (Baeyen 1992). Recently, considerable interest in
determination and speciation of mercury is gaining popularity among researchers as
speciation of methyl mercury is crucial for the understanding of the bioavailability and
toxicity of methyl mercury (Lemes and Wang 2009). Studies on mercury speciation have been
reported in various matrices such as in fish tissues (Chang et al. 2007; Lemes and Wang 2009;
Santoyo et al. 2009; Krishna et al. 2010; Carasso et al. 2011), human blood (Rodrigues et al.
2010; Baxter et al. 2007) and seafood (Batista et al. 2011; Lόpez et al. 2010).
Extraction of mercury species from a complex sample is regarded as one of the most
fundamental steps before their determination. Not only speciation studies require high
extraction efficiency to ensure successful extraction procedure but more importantly, all
original species must be kept intact prior to analysis (Meng et al. 2007). Extraction of fish by
organic solvents like benzene or toluene after hydrolysis using mineral acids (Westőő 1966,
Rahman et al. 2009) or alkaline solutions (Shafer et al. 1975; Gibicar et al. 2007) have been
119
previously reported. Other extraction procedures include ultrasound-assisted extraction (RioSegade and Bendicho 1999; Batista et al. 2011), enzymatic hydrolysis (Rai et al. 2002; Lemes
and Wang 2006) and extraction using reagents containing thiol ligands such as
mercaptoethanol (Meng et al. 2007) and L-cysteine (Chiou et al. 2001).
The most effective instrumental based techniques for chemical speciation analysis rely on the
use of chromatography (mainly gas chromatography-GC) (Baxter et al. 2007; Gibicar et al.,
2007; Yan et al. 2008, Rahman et al. 2009) or liquid chromatography (Chiou et al. 2001;
Morton et al. 2002; Meng et al., 2007; Carbonell et al. 2009; Qvarnstrom and Frech 2002;
Santoyo et al. 2009) coupled to a sensitive and specific detector such as ICP-MS. Compared
with GC, LC is the preferred separation technique used for mercury speciation, because the
mercury species do not need to be derived to volatile compounds before HPLC separation
(Batista et al. 2011).
The most common application of mercury speciation in biota focused on the distinction
between inorganic mercury and methyl mercury in the forms of Hg2+ and MeHg+.
Considerable interest in mercury speciation takes into account only the mercury species
present in biological matrices leaving unaccounted the real counterion or partner by which
methyl mercury is present as MeHgX (X may potentially be low-molecular ions, peptides,
proteins or other binding ligands)(Krupp et al. 2008). More often than not, mercury and
methyl mercury are bound to sulphur-containing biomolecules e.g. in fish (Harris et al. 2003)
or present as chloride complex e.g. in seawater (Morel et al. 1998) and are unlikely to occur
as free cations (Krupp et al. 2008).
Most mercury-containing protein studies involve the coupling of liquid chromatography to
ICP-MS. Shi et al. (2007) studied pregnant rats which were fed with MeHg+ synthesized with
Hg enriched in isotopes
196
Hg and
198
Hg. SEC-ICP-MS analysis revealed that serum of dam
and pup rats showed three signals (≥ 300 kDa, 300 kDa and 120 kDa) while brain cytosol
showed two signals (60 kDa and 1.8 kDa). Subsequent quantification with isotope dilution
analysis (IDA) showed that differences in distribution of mercury between dam and pup rats
exist. Kutscher et al. (2012) studied mercury-binding protein in tuna using metallomics
approach. These include separation of protein using sodium dodecyl sulphate-polyacrylamide
gel electrophoresis (SDS-PAGE) and size exclusion chromatography (SEC). A high
120
molecular weight protein (> 200 kDa) identified as skeletal muscle myosin heavy chain was
able to be identified after tryptic digestion and capillary LC-ESI-MS/MS. Li et al. (2007)
studied the interactions of inorganic mercury (Hg2+), methylmercury (MeHg), ethylmercury
(EtHg+) and phenylmercury (PhHg+) with human serum albumin (HSA) in terms of
electrophoretic behaviours, stoichiometry, thermodynamics and kinetics using a new hybrid
technique, capillary electrophoresis on-line coupled with electrothermal atomic absorption
spectroscopy. Two types of binding sites in HSA were observed for the binding of mercurial
species indicating strong affinity of mercury species for HSA.
The study of mercury-containing proteins in biological matrices is still limited (Shi et al.
2007). Although mercury toxicity has been extensively studied, there are still gaps in the
binding mechanisms of mercury-containing proteins in biological organisms. Hence, this
study aims to investigate the potential binding partners of methyl mercury in fish.
5.2
MATERIALS AND METHODS
5.2.1 General remarks
As mercury is a toxic compound, appropriate means of protection (laboratory coat, gloves)
were applied when dealing with mercury. Preparation of buffers and solutions was conducted
using analytical weighing balance and dissolved in respective solvents.
5.2.2 Chemicals
All chemicals used were of highest purity available. All solutions were prepared in ultra-pure
water (18 MΩ from a Mili-Q water purification system, Milipore Corporation). Chemicals
used in this study consisted of tris (BDH chemicals), sodium dodecyl sulphate (SDS) (SigmaAldrich),
ammonium
dihydrogen
phosphate
(Merck,
Germany),
phenylmethanesulfonylfluoride (PMSF), TCEP (tris(2-carboxyethyl)phosphine) and ethanol
were purchased from Sigma-Aldrich.
5.2.3 Protein extraction from fish
In this study, extraction of fish was conducted on two types of fish namely John’s snapper
(Lutjanus johnii) and a certified reference material, DORM-2 (National Research Council,
Canada). Three different extraction solutions were tested. For extraction, approximately 0.1 g
of freeze-dried fish was weighed into a 15 mL polypropylene centrifuge tube. About 4 mL of
121
the respective extraction solution were added, so that the final Hg concentration was expected
to be in the order of 100 μg·L-1, if quantitative extraction occurs.
The extraction conditions tested were adapted from Kutscher et al. (2012) and were the
following:
A: 30 mmol L-1 TRIS pH 8.0, 4 hours at 25°C
B: 4 % SDS, 30 mmol L-1 TRIS pH 8.0, 4 hours at 80°C
C: 4 % SDS, 30 mmol L-1 TRIS pH 8.0, 14 hours at 37°C
After the extraction protocol was completed, the samples were centrifuged for 20 minutes at
5,000 g to separate remaining solid particles such as cell debris or DNA. The supernatant was
removed and filtered through a membrane filter with a pore size of 0.45 µm.
5.2.4 Sodium dodecyl sulphate-polyacrylamide gel electrophoresis (SDS-PAGE)
Denaturing slab-gel electrophoresis was carried out using precast gels with an acrylamide
concentration of 7.5 % (Bio-Rad Laboratories, USA). Samples were first incubated in sample
buffer (62.5 mmol L-1 TRIS, 2 % SDS, 25 % glycerine and 0.01 % bromophenolblue), boiled
for 10 minutes at 60◦C and then 20 µL were loaded onto different wells in the gel. The
running buffer for electrophoresis contained 25 mmol L-1 TRIS, 192 mmol L-1 glycine and 0.1
% of SDS. Electrophoretic separation was carried out using the MiniProtean Tetra Cell (also
Bio-Rad Laboratories) at 200 V until bromophenolblue had migrated to the end of the
separation gel (approximately 40 minutes). After that, the gels were stained using Coomassie
blue (1 g L-1 in 20 % methanol and 10 % acetic acid). After 1 hour, the gels were destained
using 50 % methanol and 10 % acetic acid. Destaining is run overnight on a rocker with
destaining solution being changed every hour for the first few hours until the protein bands
were clearly visible. After desired bands are visible, gel was washed with ultra pure water to
remove residues. Gel was then scanned using an imager.
5.2.5 Inductively coupled plasma-mass spectrometry (ICP-MS)
The ICP-MS used for analysis was Perkin Elmer NexION 300Q. The instrument was tuned
daily with a multi-element tuning solution containing 10 ng/mL of various elements. Standard
solutions from a 10 mg/L multi element standard were used for calibration of standards
122
(Perkin Elmer USA). The optimal operation conditions for the ICP-MS are shown in Table
5.1.
Table 5.1 NexION 300Q Instrumental Parameters
Instrument
RF power
Sample and skimmer
cones
Hyper skimmer
Plasma gas (argon)
Nebuliser gas (argon)
Auxiliary Gas Flow
(argon)
Sweep readings
Dwell time
Detector Mode
Pulse stage voltage
Analogue voltage
Lens voltage
Nebulizer
Spray Chamber
Integration time
Sample uptake rates
Replicates
5.2.6
Total metal analysis
Perkin Elmer NexION 300D
1300W
Speciation analysis
Perkin Elmer NexION 300D
1300W
Nickel
Nickel
Aluminum 7071
17 L min-1
~0.9 L min-1
Aluminum 7071
17 L min-1
~0.9 L min-1
1.2 L min-1
1.2 L min-1
15
20 ms
Dual detector
1250 volts
1750 volts
Optimised daily
Meinhard, quartz concentric,
A3
Peltier chilled Quartz
Cyclonic
300 ms
1 mL min-1
3
1
250 ms
Dual detector
1250 volts
1750 volts
Optimised daily
Meinhard, quartz concentric,
A3
Peltier chilled Quartz Cyclonic
250 ms
1.5 mL min-1
1
High Performance Liquid Chromatography (HPLC)
For size exclusion chromatography (SEC), coupling to ICP-MS was realised by directly
connecting the column outlet to the nebulizer. A Perkin Elmer series instruments were used
(Perkin Elmer USA). A Superdex 75 10/300 GL (10 mm x 300 mm) was used to separate
proteins ranging from 3 kDa to 70 kDa (GE Healthcare). Mobile phase consisted of 50 mmol
L-1 ammonium acetate. Separations were carried out in the isocratic mode with flow rates of
0.3 mL min-1. The injected sample amount was 10-50 µL. For peptide separation, an Agilent
XDB C8 150 mm x 4.6 mm x 5 µm column was used. Mobile phase for gradient elution
consisted of 50 mM ammonium hydrogen carbonate from 5% -75% methanol over 15
minutes holding 75% for 10 minutes. All gradients included a 10 minute cleaning step at 95
123
% B as well as 15 minutes for column equilibration at the initial solvent composition.
5.2.7 Digestion of SDS-PAGE gel
After visual observation of protein bands, the desired bands of protein containing mercury
were excised with scalpel and subject to further analysis. The gels were placed in 1.5 ml
polypropylene centrifuge tubes. The presence of Hg in the protein spots excised from SDSPAGE was determined after digestion of the spots in 100 µL of concentrated nitric acid. After
24 hours, the supernatant liquid was removed after centrifugation and diluted in 2% nitric acid
for ICP-MS analysis.
5.3
RESULTS
5.3.1
Protein extraction from fish
Different extraction procedures were assessed for the extraction of possible mercurycontaining proteins. Fish protein was extracted using DORM-2 and analysed for mercury by
ICP-MS. The results of extraction efficiencies in fish by different extraction procedures are
shown in Table 5.2.
Table 5.2: The extraction efficiencies by different extraction procedures
Extraction procedure
Extraction efficiencies
(%)
A: 30 mmol L-1 TRIS pH 8.0, 4 hours at 25°C
B: 4 % SDS, 30 mmol L-1 ammonium phosphate buffer pH 8.0,
4 hours at 80°C
C: 4 % SDS, 30 mmol L-1 TRIS pH 8.0, 14 hours at 37°C
8
66
45
The results from Table 5.2 showed that extraction procedure A exhibited the poorest
extraction recovery compared to extraction procedure B and C which yielded almost similar
percentage recoveries between the two procedures. In this study, extraction procedure B was
selected as the extraction efficiencies is by far the highest in comparison with extraction
procedure A and C.
124
5.3.2 Mercury-containing proteins in fish extracts
Size-exclusion column (Superdex 75 10/300 GL) was used for fish protein separation, which
is better to isolate the complexes with molecular weights from 3 kDa to 70 k Da. A group of
molecular weight markers blue dextrin (2,000 kDa), bovine serum albumin (67 kDa),
ovalbumin (43 kDa), ribonuclease (13.7 kDa), cytochrome c (12.4 kDa), aprotinin (6.512
kDa) and vitamin B12 (1.355 kDa) were used for calibration. The protein peaks were
monitored by UV/VIS detector at 256 nm. The chromatogram presents a satisfactory
separation of the standard proteins by the column (Figure 5.1). According to the molecular
weights of the protein marker, blue dextrin eluted first at around 15.5 minutes followed by
bovine serum albumin at 16 minutes and ovalbumin at 18 minutes. Vitamin B12 eluted
approximately at 36 minutes.
Figure 5.2 shows the size exclusion profile for fish extracts. The chromatogram depicted that
four peaks were observed for John’s snapper while only one peak was observed for DORM-2.
The highest peak for John’s snapper eluted at approximately 15-20 minutes corresponding to
50 kDa, 22-25 minutes (32 kDa), 25-26 minutes (18 kDa) and 36-37 minutes (14 kDa).
DORM-2 had only a peak eluting between 15-20 minutes which corresponds to 50 kDa.
Figure 5.1 The calibration of molecular weight markers for protein monitored at absorbance
256 nm.
125
DORM-2
John’s snapper
50 500-50 700 DaJohn’s
32 000-34 000 Da
18 200 Da
14
200
Da
14
200
Da
14,
200
Da
Figure 5.2 The size exclusion profiles of fish extracts
5.3.3
SDS-PAGE
The extraction solution of procedure B was incubated in sample buffer and subjected to slab
gel electrophoresis. Figure 5.3 shows the image of coomassie blue stained gel after scanning
with an imager. The lane labeled A showed the molecular weight markers ranging from 18.3
kDa to 215 kDa. As indicated by Figure 5.3, five protein spots could be identified for fish
extract B1 to B4 whereas only one protein spot was identified in fish extract C1 to C4.
126
A
B1
B2
B3
B4
C1
C2
C3
C4
Figure 5.3 Image of a stained gel after separation of fish muscle tissue
extract prepared by extraction procedure B (A denotes molecular weight
marker, B: John’s snapper, C: CRM DORM-2)
5.3.4
Digestion of SDS-PAGE gels
The protein bands of interest were carefully excised to ensure that only respective protein
bands were included for analysis. The digested protein spots were then analysed by ICP-MS
for total mercury content. The results for total mercury corresponding to respective protein
bands are shown in Table 5.3. The highest mercury concentrations were observed in protein
spot number 3 which corresponds to 60 kDa, followed by spot number 1 (215 kDa) and spot
no 2 (84 kDa).
127
Table 5.3 Total mercury content with corresponding protein bands
Spot No.
Molecular weight (kDa)
1
215
15 ± 1
2
84
11 ± 1
3
60
31 ± 2
4
39
BDL*
5
28
BDL*
6
60
BDL*
ng Hg ± CI
*BDL: below detection limit; CI: confidence interval
5.3.5
Separation of mercury-containing proteins
In order to investigate the binding of mercury in protein from fish extracts, DORM-2 fish
extracts were injected into three different columns namely reversed-phase, cation exchange as
well as anion exchange columns. Similar procedure for fish extraction (refer to 5.2.3) was
employed with addition of 0.01 M PMSF and 0.1 M TCEP to 0.1 g of fish sample. The
extraction does not involve heating, instead fish sample was sonicated for 15 minutes and left
in rotary evaporation system for 2 hours. Extracts were then centrifuged for 15 minutes at 5
000 rpm. The chromatograms from the separation by reversed-phase and cation exchange
columns are shown in Figure 5.4 and 5.5.
The reversed-phase chromatogram in Figure 5.4 indicated that inorganic and organic mercury
peaks were well resolved between each other. However, this is not the case for DORM-2
which was observed to elute in the void and has no retention. The results from cation
exchange chromatogram (Figure 5.5) showed similar trend to the reversed-phase
chromatogram. Inorganic mercury, organic mercury and DORM-2 were observed to elute in
the void and has no retention. As for anion exchange column, nothing was eluted from the
column and only blank baseline was observed.
128
DORM-2
Figure 5.4 The chromatogram for the separation of fish extracts using reverse phase column Agilent
XDB C8 150 mm x 4.6 mm x 5 µm, 50 mM ammonium carbonate gradient from 5% -75%
methanol over 15 min holding 75% for 10 min. (100 ppb inorganic mercury, 250 ppb methyl
mercury and DORM-2)
129
A)
A)
B)
B)
C)
C)
Figure 5.5 The chromatograms for the separation of fish extracts by cation
exchange column Agilent SCX 150 mm x 4.6 mm x 5 µm, 5 mM pyridine
with 0.05% V/V formic acid. A) 100 ppb inorganic mercury B) 100 ppb
MeHg C) DORM-2
130
5.4
DISCUSSION
5.4.1
Protein extraction from fish
The extraction of possible mercury-containing protein was evaluated by different extraction
procedures adapted from Kutscher et al. (2012). The extraction efficiencies of fish proteins by
three different procedures exhibited varying results (Table 5.2). The lowest extraction
recovery which was only 8% shown by extraction procedure A using only Tris was therefore
not used for further analysis. As for procedure B and C, initially 4% SDS was used with 30
mM of Tris at different temperature. Optimization of these two extraction procedures revealed
that higher temperature within shorter period of time produced better extraction efficiencies
for mercury-containing protein in fish hence procedure B was selected for extraction.
It is worthy to note that some problems aroused when optimizing the extraction procedure
which has caused a major delay in this study. The use of Tris resulted in problems such as
tailing effects of mercury, suppression of mercury signals as well as long washing time to
remove mercury residues in tubings. All of these Tris related issues have led to the use of
ammonium phosphate buffer in combination with SDS hence Tris was no longer used in fish
extraction procedure.
5.4.2
Mercury-containing proteins in fish extracts
The SEC chromatogram as shown in Figure 5.2 showed that elution time for the first peak for
both fish extracts was similar although John’s snapper exhibited broader peak compared to
DORM-2. Both of the peaks which were eluting at similar time can be associated with a
medium molecular weight protein (around 50 kDa). The elutions of subsequent peaks for
John’s snapper were observed to be somewhat smaller.
SEC-HPLC–ICP-MS has been shown to be a valuable tool in detecting metalloproteins
(Prange and Schaumloffel 2002). SEC separates proteins according to size with larger size
protein eluting faster than smaller proteins (Guntiñas et al. 2002). The SEC profiles of the fish
extracts for both John’s snapper and DORM-2 confirm that the mercury associated proteins
are not metallothioneins (MT). MT have been extensively studied in a wide variety of matrix
including fish bile (Hauser-Davis et al. 2012), human cerebrospinal fluid (Gellein et al. 2007),
rat liver and kidney (Polec et al. 2002), liver cytosols of fish (Rodriguez-Cea et al. 2006) and
human brain cytosol (Richarz and Bratter 2002). MTs are low-molecular weight proteins and
131
have a molecular weight ranging from 6-7 kDa (Rigby and Stillman 2004). From the studies
conducted by aforementioned researchers, the elution profiles of MT in all matrices were
similar and did not show any similarities with the SEC profiles of fish extracts observed in
this study. A typical MT elution profile is as shown in Figure 5.6.
Figure 5.6 The elution profile of MT in tilapia, separated by Cd113, Zn64, Pb202,
Cu63 and Hg208 (Hauser-Davis et al. 2012)
5.4.3 SDS-PAGE
Gel electrophoresis is a technique used to separate proteins based on their electrophoretic
mobility and due to its simplicity and sensitivity of application, gel electrophoresis is widely
used in biochemistry (Hames 1998). The PAGE gel from this study revealed that 5 major
protein spots were identified in John’s snapper while only one protein spot was identified for
DORM-2 (Figure 5.3). The protein spots observed in fish extracts particularly John’s snapper
corresponded well with the SEC profile (Figure 5.2). In addition, two protein bands at 84 kDa
and 215 kDa were observed in the PAGE gel but not the SEC chromatogram. Observation
from PAGE gel confirms the fact that mercury is associated with medium to high molecular
weight protein (28-215 kDa) in this study.
In a study by Kutscher et al. (2012), they found that mercury is associated with a high
molecular weight protein (approximately 220 kDa). Other mercury-containing proteins were
also observed from the PAGE gel corresponding to molecular weight ranging from
132
approximately 40 – 100 kDa. This is similar to the finding from this study by which mercurycontaining proteins were in the range of medium to high molecular weight.
5.4.4 Digestion of SDS-PAGE gels
The highest total mercury concentrations were found in protein spot number 3 (60 kDa),
followed closely by spot number 1 (215 kDa) and spot number 2 (84 kDa)(Table 5.3). Spot
number 4, 5 and 6 however were below detection limit. Kutscher et al. (2012) found five
protein spots ranging from 50-215 kDa with the highest mercury content detected in spot
number 1 (215 kDa) corresponding to skeletal muscle myosin heavy chain after tryptic
digestion and capillary LC-ESI-MS/MS. Studies on mercury-containing protein is still scarce
and information on identified mercury proteins is limited as shown in Table 5.4.
5.4.5 Separation of mercury-containing proteins
The evaluation of mercury-binding proteins in fish was conducted using DORM-2 fish
extracts. Three different columns were used for this purpose which included reversed-phase,
cation exchange and anion exchange columns. The chromatograms for reversed-phase and
cation exchange as depicted in Figure 5.4 and Figure 5.5 showed similar findings for DORM2 by which DORM-2 eluted in the void and has no retention. In contrast to results from
Figure 5.4 and Figure 5.5, the anion exchange chromatogram depicted an opposite trend.
DORM-2 extracts were not eluting at all and being retained in the column. This finding
revealed that the mercury-containing protein is highly anionic as it strongly binds to the anion
exchange column.
The investigation of mercury-binding protein usually involves tryptic digestion prior to
identification of specific protein using ESI-MS (Kutscher et al. 2012, Wang et al. 2007). In
this study however, direct extraction of fish was employed without tryptic digestion.
Mercury-containing proteins have been successfully separated using reverse phased columns
by various researchers (Bramanti et al. 2004; Infante et al. 2004; Poleć et al. 2002). Reversed
phase chromatography separates proteins on the basis of their hydrophobicity. The full
process of protein separation is still not well understood, although different theories have
been proposed (Kastner 2000). In general, the larger the protein the more hydrophobic it is, so
that to avoid losses of protein by irreversible binding to the solid phase, it is convenient to use
133
stationary phases with short alkyl chains (C2, C4)(Guntiñas et al. 2002). Reversed-phase
HPLC seems to be superior to SEC and ion exchange chromatography (IEC) for the
separation of metal biomolecule complexes because the packing material for reversed-phase
chromatography is principally free of ligands for metals (Lobinski et al. 1998).
5.5 Summary and conclusions
This study aimed to investigate the potential binding partners of methyl mercury in fish.
Although speciation of methyl mercury is an extensively investigated topic in analytical
chemistry, most studies focused only on the speciation of MeHg+ and Hg2+ thus leaving its
real chemical form of MeHgX unaccounted. X may represent either low-molecular ions,
peptides, proteins or other potential binding partners.
In this study, separation of mercury-containing protein was conducted by size exclusion
chromatography (SEC) and SDS-PAGE. Results from SEC indicated that mercury is
associated to medium molecular weight protein. A good correlation between the SEC and
SDS-PAGE results were observed showing that both methods can be used hand in hand for
identification of proteins at certain molecular weights. Digestion of protein spots suggested
that protein spot number 3 from John’s snapper showed the highest total mercury
concentration. It can be confirmed that mercury-containing protein from this study is not a
metallothionein. Chromatograms of reverse-phase and cation exchange revealed that the
mercury-containing protein is highly anionic.
134
Danio rerio
Ictalurus punctatus
Carassius auratus
Oryzias latipes
Keratin 8
α -actin
Keratin 18
Β-actin
Type-1 keratin-like protein
Lamin type B
Oxidative stress response
Peroxiredoxin 4
Peroxiredoxin 6
Gluthathione S-transferase
Superoxidase dismutase [Cu-Zn]
Signal transduction
Annexin 4
14-3-3E1 protein
14-3-3 protein
Liver
Liver
Liver
Liver
Liver
Liver
Liver
Liver
Liver
Liver
Liver
Liver
Liver
Liver
Liver
Danio rerio
Cell structure
α-Tubulin 1
Liver
Oncorhynchus mykiss
Oreochromis
mossambicus
Danio rerio
Channa maculata
Oreochromis
mossambicus
Salmo salar
Danio rerio
Acipenser baerii
Sparus aurata
T. obesus
Beta-enolase (Epinephelus coioides]
OBE
T. albacares
T. alalunga
T. thynnus
Species
Fast skeletal
muscle troponin T subunits (Gadus
morhua)
muscle (Danio rerio)
Pyruvate kinase
isomerase (Priapulus caudatus)
Triosephosphate
Protein
ALBA
ALA
THY
Spot ID
27.68
29.41
35.95
16.08
26.03
24.66
29.43
68.29
35.52
42.05
49.21
42.33
57.78
50.62
47.5
27.2
58.6
22.9
MW
(kDa)
4.67
4.67
6.07
5.94
8.24
5.46
6.3
5.98
4.94
5.29
5.6
5.3
5.15
4.97
6.29
9.48
6.54
6.51
pI
543
101
231
354
70
345
222
66
195
1060
168
289
427
MALDI TOF-TOF MS
MALDI TOF-TOF MS
MALDI TOF-TOF MS
MALDI TOF-TOF MS
MALDI TOF-TOF MS
MALDI TOF-TOF MS
MALDI TOF-TOF MS
MALDI TOF-TOF MS
MALDI TOF-TOF MS
MALDI TOF-TOF MS
MALDI TOF-TOF MS
MALDI TOF-TOF MS
MALDI TOF-TOF MS
MALDI TOF-TOF MS
MALDI
BLAST 269
MASCOT
159
1330
LC-MS/MS
LC-MS/MS
LC-MS/MS
Analysis method
BLAST 421
MASCOT
93
BLAST
1052
MASCOT
92
Protein
Score
MASCOT
83
Table 5.4 List of protein spots identified by various techniques in specific species
135
Wang et al. (2011)
Wang et al. (2011)
Wang et al. (2011)
Wang et al. (2011)
Wang et al. (2011)
Wang et al. (2011)
Wang et al. (2011)
Wang et al. (2011)
Wang et al. (2011)
Wang et al. (2011)
Wang et al. (2011)
Wang et al. (2011)
Wang et al. (2011)
Wang et al. (2011)
Pepe et al. (2012)
Pepe et al. (2012)
Pepe et al. (2012)
Pepe et al. (2012)
Reference
223.6
128.0
Osmerus mordax
Canis familiaris
Gallus gallus
Homo sapiens
Mus musculus
Homo sapiens
Gallus gallus
Metabolism
Homogentisate 1,2-dioxygenase
Alanyl-tRNA synthetase,
cytoplasmic
Dihydrolipoamide Sacetyltransferase
Adenosylhomocysteinase
Pyruvate dehydrogenase E1
component subunit, alpha, somatic
form, mitochondrial
Brain-type fatty acid binding protein
Methionein adenosyltransferase-like
S-formylgluthathione hydrolase
Myosin-1
Myosin heavy chain
Myosin-4
Myosin-7
Myosin -13
Myosin heavy chain cardiac muscle
isoform
Liver
Liver
Liver
Liver
Liver
Liver
Liver
Liver
Danio rerio
Oryzias latipes
Salmo salar
Salmo salar
Danio rerio
Salmo salar
Danio rerio
222.8
223.1
223.1
223.1
31.54
43.55
15.04
44.59
48.51
69.68
107.92
50.65
29.51
Liver
Danio rerio
53.23
Proteasome alpha 1 subunit
Oreochromis niloticus
Liver
Liver
Protein modification
Cystosolic nonspecific dipeptidase
Liver
6.33
16.26
18.87
32.21
36.54
37.01
6.06
6.38
5.8
6.52
6.43
8.8
5.35
6.2
6.2
5.54
6.33
16.26
18.87
32.21
36.54
37.01
113
101
128
142
752
121
183
75
133
251
LC-ESI-MS/MS
LC-ESI-MS/MS
LC-ESI-MS/MS
LC-ESI-MS/MS
LC-ESI-MS/MS
LC-ESI-MS/MS
MALDI TOF-TOF MS
MALDI TOF-TOF MS
MALDI TOF-TOF MS
MALDI TOF-TOF MS
MALDI TOF-TOF MS
MALDI TOF-TOF MS
MALDI TOF-TOF MS
MALDI TOF-TOF MS
MALDI TOF-TOF MS
MALDI TOF-TOF MS
MALDI TOF-TOF MS
136
Wang et al. (2011)
Kutcsher et al.
(2012)
Kutcsher et al.
(2012)
Kutcsher et al.
(2012)
Kutcsher et al.
(2012)
Kutcsher et al.
(2012)
Kutcsher et al.
(2012)
Wang et al. (2011)
Wang et al. (2011)
Wang et al. (2011)
Wang et al. (2011)
Wang et al. (2011)
Wang et al. (2011)
Wang et al. (2011)
Wang et al. (2011)
Wang et al. (2011)
Wang et al. (2011)
CHAPTER 6
SYNOPSIS AND GENERAL CONCLUSIONS
The findings presented in the synopsis relate to the objectives established for the project
(Section 1.3). The thesis deals with three different aspects of mercury in fish. Firstly, it
assesses the total mercury and methyl mercury concentrations in fish from West Peninsular
Malaysia, secondly it assesses the metal concentrations in fish and evaluates their relationship
with mercury, and finally it deals with detection of mercury-binding proteins in fish. This
section aims to integrate issues discussed earlier in various chapters as well as providing
recommendations and the need for further research.
6.1
Introduction
From a nutritional perspective, fish is regarded as a cheap source of protein and regular
consumption of fish is deemed beneficial as it contains essential fatty acids. From a
toxicological perspective, fish is associated with environmental contaminants such as heavy
metals, which pose potential threats to humans. As fish is a popular choice of protein by
majority of the population in Malaysia, it is vital to assess the concentrations of metals in fish
to ensure that this commodity is fit for human consumption. The study aims to measure
concentrations of metals (Hg, As, Pb, Se, Cd, Cu, Zn, Fe) and mercury species (MeHg) in
commonly consumed fish in West Peninsular Malaysia, determines factors influencing metal
concentrations in fish, compares metal concentrations with permissible national and
international guidelines as well as investigates the potential binding partners of methyl
mercury in fish.
6.1.1 The assessment of total mercury and methyl mercury in fish tissues from West
Peninsular Malaysia
Generally, most humans are exposed to mercury from consumption of seafood although
exposure can also occur from release of mercury vapour from amalgam tooth fillings and
thimerosal from vaccines. The mean mercury and methyl mercury concentrations measured in
the overall 111 fish species were 0.65 ± 1.21 µg/g dry mass and 1.09 ± 0.65 dry mass
respectively. A sample, Nemipterus nematophorus exceeded the maximum permitted
concentration of 0.5 µg/g wet mass. It was observed that some fish species have the tendency
to accumulate more mercury than others. The mean mercury concentrations in carnivores
were higher in comparison with secondary carnivores and omnivores. Similarly for methyl
mercury, mean methyl mercury concentrations were higher in carnivores compared to
137
secondary carnivores and omnivore. The mercury and methyl mercury concentrations in fish
species were found not to be increasing successively across the trophic level signifying no
evidence of biomagnification.
Studies have shown that mercury concentrations in fish can be influenced by various factors
such as feeding modes, habitat, trophic level as well as length of fish. Similar concentrations
of mercury and methyl mercury were found between benthic and pelagic fish indicating that
no differences were observed between the two different feeding modes in fish. Length of fish
affects mercury concentrations and older, adult fish were observed having higher mercury
concentrations than younger fish. Mercury was present as methyl mercury in the range of 81
to 99% in carnivorous fish. No evidence of biomagnification observed when log transformed
mercury concentrations were regressed against δ15 N values. As for the PTWI, Nemipterus
nematophorus and Lutjanus johnii exceeded the recommended PTWI values of 5 µg/kg body
weight.
6.1.2 Assessment of metals in commonly consumed fish of West Peninsular Malaysia
As fish dietary intake in Malaysian population is high at 58 kg per capita per person, potential
contaminants such as heavy metals can cause adverse health effects if consumed in sufficient
quantities. The metal contaminants of interest in this study were arsenic, selenium, lead,
cadmium, copper, zinc and iron. All fish species measured were within the maximum
permitted concentrations stipulated by Malaysian Food Regulations, the World Health
Organization, the European Commission, the Australian Foods Standard Code as well as the
Australian National Health and Medical Research Council with the exception for arsenic. In
contrast with mercury, inorganic arsenic is the more toxic form of arsenic than organic
arsenic. Although arsenic concentrations were exceeded, this is not a matter of concern as
marine fish tends to accumulate arsenic in the form of arsenobetaine, which is not metabolised
in humans and widely assumed to be of no toxicological concern to human.
Concentrations of metals may be influenced by trophic levels, age, feeding habits and length
of organism. Mean selenium, copper, zinc and iron concentrations showed significant
differences between trophic levels while only arsenic exhibited significant differences in
mean concentrations between benthic and pelagic fish. Inverse relationships between length of
fish and metal concentrations were observed for copper, zinc and iron. Despite significant
differences observed between trophic levels and metal concentrations, there was no evidence
138
of biomagnification of metals as demonstrated when the δ15N values were regressed with the
metal concentrations. Significant differences between benthic and pelagic fish were observed
only for arsenic. Length was observed not to affect metal concentrations as log copper, log
zinc and log iron concentrations were found to be showing inverse relationship with length of
organisms. As for interactions between mercury and selenium, all fish portrayed Se:Hg molar
ratios of more than 1 signifying protection against mercury toxicity. In addition, the selenium
health benefit value observed in this study was positive, indication of expected health benefits
from fish consumption. All fish did not exceed the PTWI for all metals with the exception for
arsenic indicating that all fish species are safe for human consumption.
6.1.3 A study on mercury-binding protein in fish
In this study, separation of mercury-containing protein was conducted by size exclusion
chromatography (SEC) and SDS-PAGE. Results from SEC indicated that mercury is
associated to medium molecular weight protein. A good correlation between the SEC and
SDS-PAGE results were observed showing that both methods can be used hand in hand for
identification of proteins at certain molecular weights. Digestion of protein spots suggested
that protein spot number 3 from John’s snapper (Lutjanus johnii) showed the highest total
mercury concentration. It can be confirmed that mercury-containing protein from this study is
not a metallothionein. Chromatograms of reversed-phase and cation exchange revealed that
the mercury-containing protein is highly anionic.
6.2 Major contributions of this study
This study provides information on metal concentrations (Hg, MeHg, As, Pb, Se, Cd, Cu, Zn,
Fe) in specific types of fish consumed by population from West Peninsular Malaysia.
Although studies on metals in fish are abundant, speciation study of mercury is somewhat
deficient. There are many instances in earlier studies conducted that total mercury
concentrations were assumed as methyl mercury which is a conservative way of assessment.
Hence, the information on methyl mercury concentrations in fish adds to existing baseline
data. Such information will be useful in development of risk management strategy and risk
communications in order to protect public health.
Malaysians are generally not aware of the health risk associated with consumption of fish
containing high concentration of mercury. This is particularly true for rural population who
are under privilege and not well educated. With information of mercury and methyl mercury
139
concentrations measured in fish from this study, the population can be informed on choices
they can make and what types of fish to avoid to minimize their exposure to mercury in fish.
More often than not, mercury and selenium concentrations in fish are being assessed in
isolation. The Se:Hg molar ratio of mercury and selenium together with Se-HBV information
from this study add to knowledge of mercury risk assessment.
6.3 Conclusions
This study has managed to assess the concentrations of metals particularly mercury, methyl
mercury, arsenic, selenium, lead, cadmium, copper, zinc and iron in fish of West Peninsular
Malaysia. It also evaluated the potential health risk that could be associated with current
dietary intakes of fish based on comparison with existing guidelines as well as the PTWI. The
concentrations of metals in fish were generally low and within acceptable limits except for a
few samples which exceeded the stipulated guidelines. Where regulatory standards were
exceeded (e.g arsenic), public health was not necessarily compromised. In this instance, the
organic form of arsenic is not a major concern as it exists as arsenobetaine which is not a
toxicological concern in humans. Furthermore, the calculation of PTWI was based on a
generic fish intake for the population and not specific to a particular group of people.
Inadequate data on dietary habits of consumers with high consumption warrants further study
to ensure data are specific and represent real scenario. In addition, the preliminary
investigation of Hg-protein binding interactions serves as exploratory data and further study is
needed to characterize the protein-binding Hg. In summary, the levels of metals in fish from
this study are generally low and do not pose health risk to fish-consuming population. Some
sub-groups of the population may however need to be advised about safe level of
consumption. It is essential that any communications to the public include information on the
health benefits of fish consumption alongside information on the risks of methylmercury
exposure so that they can consider both the benefits and risks in reaching their own decisions
about appropriate fish consumption. Studies on the nutritional benefits of fish are supportive
of efforts to influence consumers’ behaviour by modifying the types of fish regularly chosen
rather than by decreasing overall fish consumption.
140
6.4 Recommendations
As the number of samples obtained was relatively small and was not representative of each
species, future studies should include higher number of fish for each species in order to ease
analysis. With a higher number of samples, difference in mercury concentrations between
sampling locations can be conducted and therefore adds new knowledge to existing
information.
In the future, a more advanced metallomics and proteomics approach can be employed using
LC-ESI-MS/MS and MALDI-TOF to obtain better separation and more accurate molecular
weight for Hg-containing protein. This is important as the findings from such investigation
will contribute to better understanding of biological pathways and metabolism of mercurycontaining protein.
The establishment of guidelines for fish consumption is an important part of public health
practice. Currently, there is no policy statement or advice on safe consumption of fish for high
risk group such as pregnant women and women of child-bearing age in Malaysia. As pre-natal
exposure to mercury has been associated with neurodevelopmental disorders in fetus and child
such as in Japan, it is particularly important to develop local fish consumption advisories to
limit fish intake and minimize exposure to mercury.
141
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WHO/FAO
Australia
Malaysia
Organization
Country
/
fish
(e.g.
shark,
0.5 mg /kg methyl
mercury
Predatory fish (e.g. shark,
swordfish, tuna, pike and others) 1 mg/kg methyl mercury
All fish except predatory fish
0.5 mg /kg mercury
All other species of
crustaceans and mollusks
fish,
1.0 mg/kg mercury
1 mg/kg methyl mercury
0.5 mg /kg methyl
mercury
recommended levels*
Maximum allowed /
Fish known to contain high levels
of mercury
e.g. swordfish ,
southern
bluefin
tuna,
barramundi, ling, orange roughy,
rays, shark
swordfish, tuna, pike and others)
Predatory
All fish except predatory fish
Fish Type
FAO/ WHO
Codex
alimentarius
guideline level
The Australian
Food Standards
Code
Food Act 1983 and
Food Regulations
1985
Type of Measure
JECFA
provisional
tolerable weekly intake:
3.3
μg/kg
methyl
mercury body weight
per week
Tolerable
Weekly
Intake: 2.8 μg/ kg Hg
body weight per week
for pregnant women
Tolerable intake levels
Appendix 3.1 The recommended levels for mercury and methyl mercury in fish and seafood by various organizations
APPENDICES
183
Local trigger level
FDA action level
Type of Measure
US EPA reference dose:
0.1 μg/ kg methyl
mercury body weight
per week.
Tolerable intake levels
*It is assumed that fish limit values not mentioned as wet weight are most likely also based on wet weight, as this is normally the case for analysis used
by researchers worldwide.
States, tribes and territories are
responsible for issuing fish 0.5 ppm methyl mercury
consumption advise for locally
caught fish; Trigger level for
many state health departments
1 ppm methyl mercury
Fish, shellfish and other aquatic
animals (FDA)
Maximum allowed /
United States of
America
Fish Type
recommended levels*
/
Organization
Country
184