ASSESSING THE NEUROTOXICOLOGICAL RISK OF METHYLMERCURY EXPOSURE FOR BELUGA WHALES (DELPHINAPTERUS LEUCAS) HARVESTED IN THE MACKENZIE DELTA ESTUARY by Sonja Kerstin Ostertag B.Sc., McGill University, 2004 M.Sc., McGill University, 2008 THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTORATE OF PHILOSOPHY IN NATURAL RESOURCES AND ENVIRONMENTAL STUDIES UNIVERSITY OF NORTHERN BRITISH COLUMBIA February 2014 © Sonja Ostertag, 2014 UMI Number: 3581411 All rights reserved INFORMATION TO ALL USERS The quality of this reproduction is dependent upon the quality of the copy submitted. In the unlikely event that the author did not send a complete manuscript and there are missing pages, these will be noted. Also, if material had to be removed, a note will indicate the deletion. Di!ss0?t&iori Publishing UMI 3581411 Published by ProQuest LLC 2014. Copyright in the Dissertation held by the Author. Microform Edition © ProQuest LLC. All rights reserved. This work is protected against unauthorized copying under Title 17, United States Code. ProQuest LLC 789 East Eisenhower Parkway P.O. Box 1346 Ann Arbor, Ml 48106-1346 Approval Page Abstract Arctic marine mammals are exposed to numerous environmental contaminants and some o f these compounds are known to damage mammalian nervous systems. Three methods were used to assess neurotoxicological risk o f methylmercury (MeHg) exposure for beluga whales (Delphinapterus leucas) in the eastern Beaufort Sea population: characterization o f mercury (Hg) accumulation and speciation in brain tissue, neurochemical and molecular biomarkers, and behavioural observations. To conduct this research, I worked closely with the communities o f Tuktoyaktuk, NT and Inuvik, NT to conduct three field-sampling seasons on Hendrickson Island, NT, which is a traditional beluga-harvesting site used by Inuvialuit. Community members participated in this project as mentoring students, mentors, interviewees, and research assistants. Total Hg concentrations (median; mg kg'1 wet weight, ww) were 2.34 (0.06 to 22.6, 81) (range, n) in temporal lobe, 1.84 (0.12 to 21.9, 77) in frontal lobe 1.84 (0.05 to 16.9, 83) in cerebellum, 1.25 (0.02 to 11.1, 77) in spinal cord and 1.32 (0.13 to 15.2, 39) in brain stem. The concentrations o f MeHg ranged from 0.03 to 1.05 mg k g '1ww and labile inorganic Hg (iHg) ranged from below detection limit to 1.59 mg k g '1ww. Molar concentrations of selenium (Sex) consistently exceeded Hgx in the five brain regions analyzed. Harvesters (n=l 1) observed differences in evasive strategies used by beluga whales during the hunt, which varied with the concentration o f H gj analyzed in brain tissue. At molecular and/or neurochemical levels, components o f the dopaminergic, cholinergic, GABAergic and glutamatergic signaling pathways appeared to be sensitive to MeHg exposure. Furthermore, monoamine oxidase activity and muscarinic acetylcholine receptor binding were negatively associated with Hgr to Ser molar ratios {p < 0.05), and mRNA expression for mAChr m l was positively associated with Hgx to Sex ratio ip < 0.05). The weight o f evidence based on the outcomes from these studies suggests that MeHg exposure may be o f toxicological concern for beluga whales from the Eastern Beaufort Sea population. The implications o f MeHg-exposure for beluga whales from the eastern Beaufort Sea population at both physiological and population levels are still unclear. Table of Contents Approval Page.......................................................................................................................... ii Abstract.................................................................................................................................... iii Table o f Contents..................................................................................................................... v List of Tables........................................................................................................................... xi List of Figures....................................................................................................................... xiii G lossary................................................................................................................................ xvi Acknowledgements.............................................................................................................. xvii Dedication............................................................................................................................ xviii Chapter 1. Introduction.........................................................................................................19 Research Aim and Objectives.............................................................................................. 23 Thesis structure and contributions...................................................................................... 24 Structure.............................................................................................................................24 Contribution of Chapters.................................................................................................... 25 Chapter 2. Literature Review.............................................................................................. 27 1. Beluga Whales...................................................................................................................27 l.a Background...................................................................................................................27 l.b Harvesting....................................................................................................................28 l.c Beluga management in Canada..................................................................................... 29 1.d Traditional ecological knowledge................................................................................. 30 1.e Beluga whale research in the ISR................................................................................. 31 2. Arctic Contaminants........................................................................................................ 33 2.a Background...................................................................................................................33 v 2.b Beluga whale exposure to mercury andorganic contaminants........................................34 2.c Policies......................................................................................................................... 36 3. Mercury toxicokinetics and toxicity................................................................................. 37 3.a Background...................................................................................................................37 3.b Interaction of MeHg and iHg with neurochemical signaling pathways......................... 41 4. Assessing potential toxicity...............................................................................................45 4.a Characterizing the risk of toxicity in wildlife................................................................45 4 b. Methods.......................................................................................................................46 5. Responsibility and accountability in northern research.................................................50 Chapter 3. Mercury distribution and speciation in different brain regions of beluga whales (Delphinapterus leucas) ............................................................................................ 52 Names and Affiliations of Authors:......................................................................................52 Abstract................................................................................................................................. 53 Introduction.......................................................................................................................... 54 Material and methods...........................................................................................................56 Sample Collection...............................................................................................................56 Sample analysis..................................................................................................................57 Data analysis......................................................................................................................61 Results and Discussion..........................................................................................................62 Mercury concentration and distribution.............................................................................. 62 Hg and age.........................................................................................................................64 Hg speciation......................................................................................................................65 Co-accumulation of HgT and SeT........................................................................................ 67 Tissue distribution of Hg.....................................................................................................69 4. Conclusions........................................................................................................................ 70 5. Acknowledgements............................................................................................................78 Bridge....................................................................................................................................... 79 Chapter 4. Mercury and selenium exposure is associated with molecular and neurochemical biomarkers of Arctic beluga whales (Delphinapterus leucas).............80 Names and Affiliations of Authors:..................................................................................... 80 Abstract................................................................................................................................. 81 Introduction.......................................................................................................................... 82 Methods................................................................................................................................. 85 Sample collection...............................................................................................................85 Membrane preparation........................................................................................................86 Receptor binding assays......................................................................................................87 Expression of mRNA..........................................................................................................87 Data Analysis.....................................................................................................................90 Results................................................................................................................................... 90 Discussion............................................................................................................................ 108 GABAergic signaling pathway..........................................................................................108 Glutamatergic signaling pathway......................................................................................110 Messenger RNA expression and neurochemistry.............................................................. 111 Potential detoxification of mercury by selenium............................................................... 112 Acknowledgements.............................................................................................................. 113 Chapter 5. Methylmercury and selenium exposure were associated with biomarkers o f the cholinergic and dopaminergic signaling pathways in Arctic beluga whales (Delphinapterus leucas)........................................................................................................114 Names and Affiliations of Authors:....................................................................................114 Abstract............................................................................................................................... 115 Introduction........................................................................................................................ 117 vii Methods............................................................................................................................... 120 Sample collection............................................................................................................. 120 Mercury and Selenium analyses........................................................................................120 Receptor binding assays.................................................................................................... 121 Enzyme activity................................................................................................................ 122 Expression of mRNA........................................................................................................ 122 Data Analysis................................................................................................................... 124 Results................................................................................................................................. 124 Cholinergic signaling pathway..........................................................................................125 Dopaminergic signaling pathway......................................................................................127 Discussion............................................................................................................................ 137 Cholinergic signaling pathway..........................................................................................138 Dopaminergic signaling pathway......................................................................................140 Acknowledgements..............................................................................................................144 B ridge.....................................................................................................................................145 C hapter 6. Inuvialuit observations o f beluga whale (Delphinapterus leucas) link m ercury exposure and behaviour during harvesting activities................................... 146 Names and Affiliations of Authors:....................................................................................146 Abstract............................................................................................................................... 147 Methods............................................................................................................................... 151 Study area, people and context..........................................................................................151 Sampling.......................................................................................................................... 153 Questionnaire.................................................................................................................... 153 Respondents..................................................................................................................... 154 Data analysis.................................................................................................................... 154 Results..................................................................................................................................155 Mercury concentrations..................................................................................................... 155 Response rate.................................................................................................................... 156 General observations......................................................................................................... 156 Time to harpoon............................................................................................................... 157 Evasive strategies............................................................................................................. 157 Weather............................................................................................................................ 158 Discussion............................................................................................................................ 166 Integration of multiple lines of evidence........................................................................... 166 Behavioural observations as complementary line of evidence........................................... 167 Bridging TEK, local observations and science.................................................................. 169 Limitations....................................................................................................................... 171 Conclusions......................................................................................................................... 173 Chapter 7. Conclusions and Recommendations.............................................................177 Objectives and Significance................................................................................................177 The toxicological risk of MeHg exposure.......................................................................... 179 Mercury exposure thresholds............................................................................................179 Neurochemical and molecular variation associated with mercury exposure.......................180 Evasive behaviour during hunt and mercury exposure...................................................... 182 Limitations....................................................................................................................... 183 Community-based research approach............................................................................... 184 Communication................................................................................................................ 185 Conclusions and future research........................................................................................186 References........................................................................................................................... 188 Appendix 1. Scientific Research Licenses........................................................................204 ix Appendix 2. Ethics Approval............................................................................................. 207 Appendix 3. Harvester questionnaire/informed consent form.................................... 208 Appendix 4. Authorship Statements.................................................................................211 Appendix 5. Job application and contract for mentoring students............................215 x List of Tables Chapter 2 Table 2.1 Overview of management structure for beluga whales (Delphinapterus leucas) in Canada................................................................................................................30 Table 2.2 Neurochemical variation associated with MeHg exposure in select mammalian and avian species........................................................................................... 40 Chapter 3 Table 3.1 Concentrations (median and range, ww) o f total Hg, Se and molar ratio o f Hg:Se in beluga whales sampled during the summer harvests in the western Canadian Arctic in 2006, 2008 and 2010.......................................................................................... 75 Table 3.2 The concentrations o f Hgr, and percent MeHg reported for brain tissue from different mammalian wildlife species............................................................................... 76 Table 3.3 Concentrations (median, range) o f labile Hg species (MeHgx and i H g i a b i i e ) and iHg species complexed to proteins or selenium in the cerebellum, temporal lobe, frontal lobe and spinal cord of fetal, juvenile and adult beluga whales (« = 22) sampled on Hendrickson Island in 2008......................................................................... 77 Chapter 4 Table 4.1 Sequences o f primers and probes used for real time PCR............................. 98 Table 4.2 Summary o f backwards stepwise linear multiple regression analysis for the cerebellum and temporal cortex with GABAa receptor binding to [3H]-FNP, and mRNA expression (fold change) for GABAa ol2 and a4 as the three outcome variables tested.....................................................................................................................................99 Table 4.3 Summary of backwards stepwise linear multiple regression analysis for the cerebellum and temporal cortex with NMDA receptor binding to [3H]-801, and mRNA expression (fold change) for NMDA subunit 2b as the three outcome variables tested...................................................................................................................................100 C hapter 5 Table 5.1 Sequences o f primers and probes used for real time PCR.......................... 130 Table 5.2 Descriptive statistics are presented for total mercury (Hg), methylmercury (MeHg), labile inorganic mercury (iHgiabiie) and selenium (Set) concentrations and stoichiometric ratio of Hgj to Sex in the cerebellum and temporal cortex from beluga whales sampled at Hendrickson Island, NT, Canada in 2008 and 2010...................... 131 Table 5.3 Results from backward stepwise multiple regressions conducted for both brain regions, with binding o f [3H]-QNB to the muscarinic acetylcholine receptor (mAChR) and mRNA expression o f mAChR subtype ml as the outcome variables. .............................................................................................................................................132 Table 5.4 Results from backward stepwise multiple regressions conducted for both brain regions, with total monoamine oxidase (MAO) activity and mRNA expression of MAO A as the outcome variables..................................................................................133 C hapter 6 Table 6.1 Observations o f beluga whale behaviour during harvesting activities (n = 11)......................................................................................................................................165 C hapter 7 Table 7.1 Significant predictors (total mercury, Hg; methylmercury, MeHg; labile inorganic H g , i H g i a b i i e ) o f neurochemical and molecular variation in brain tissue from harvested beluga whales....................................................................................................... 182 List of Figures C hapter 3 Figure 3.1 Map o f the Inuvialuit Settlement Region. Sampling sites (Hendrickson Island and East Whitefish Station) and summering habitat o f the Eastern Beaufort Sea beluga whale population (Amundsen G ulf and southern Beaufort Sea)........................71 Figure 3.2 Speciation o f Hg and Se. Reverse phase HPLC-ICP-MS chromatograms showing the peaks of Hg (in black) and Se (in red) species in temporal lobe samples of ten beluga whales (A-J) from the Western Canadian Arctic, 2008. U1 and U2 denote two unidentified Hg and Se peaks, respectively.............................................................72 Figure 3.3 Relationship between age and cerebellar HgT concentration. Positive relationship between age and cerebellar HgT concentration in male (square) and female beluga whales (filled circle) (n = 76)...............................................................................73 Figure 3.4 The non-linear relationship (exponential one phase decay) between percent MeHg and Hgr concentrations. The percent MeHg decreased exponentially with increasing H gj in the spinal cord (n = 19), frontal lobe (n = 19), cerebellum (n = 22) and temporal lobe (n = 22) in brain samples collected from belugas (fetus, juvenile and adult whales) in 2008.................................................................................................. 74 C hapter 4 Figure 4.1 Correlations between GABA a receptor binding and mercury concentration (A), labile inorganic mercury concentration (B), selenium concentration (C), and stoichiometric ratio o f mercury to selenium (D) in the cerebellar cortex o f beluga whales {Delphinapterus leucas)...................................................................................... 101 Figure 4.2 Correlations between mRNA expression ofG A BA A subunit a2 (fold change) and total mercury (A) concentration (mg kg"1 dw) in the cerebellum (circle, o) and temporal cortex (diamond, ♦ ) . Correlations between mRNA expression of GABAa subunit a2 and labile mercury concentration (B), methylmercury concentration (C) and stoichiometric ratio o f mercury to selenium (D) in the temporal cortex (diamond, ♦ ) . Correlations between mRNA expression o f GABA a subunit a2 and selenium concentration in the cerebellum (circle, o) and temporal cortex (diamond, ♦ ) ...................................................................................................................103 Figure 4.3 Correlations between mRNA expression for target genes and corresponding neurochemical expression for GABAergic signaling pathway (A: GABAa-R a 2 and GABA-R; B: GABA a-R a4 and GABA-R) in the cerebellar cortex (unfilled circle, o) o f beluga whales.............................................................................. 106 Figure 4.4 Correlations between NMDA receptor binding to 3H MK-801 and Hg (A) and selenium (B) concentrations (mg kg'1 dw) in the temporal cortex o f beluga whales (Delphinapterus leucas)..................................................................................................107 C hapter 5 Figure 5.1 The correlation between muscarinic acetylcholine receptor binding to [3H]QNB and estimated age, based on tooth analysis (one growth layer per year), in the temporal cortex of beluga whales (Delphinapterus leucas)........................................ 134 Figure 5.2 The correlation between total monoamine oxidase activity and estimated age, based on tooth analysis (one growth layer per year), in the temporal cortex o f beluga whales (Delphinapterus leucas)........................................................................135 Figure 5.3 The correlation between mRNA expression (fold change) and selenium concentration in the cerebellum of beluga whales (Delphinapterus leucas). The expression o f mRNA was normalized to the internal control gene S9 and fold changes were calculated based on the lowest-exposed whales (n = 3 ) .....................................136 C hapter 6 Figure 6.1 This map depicts the location o f Hendrickson Island, a traditional belugaharvesting site in the Inuvialuit Settlement Region, NT (adapted from Wesche et al., 2011).................................................................................................................................160 Figure 6.2 Beluga hunting experience (years) o f the 11 participants o f this study. Harvesters were counted each time they hunted a beluga and responded to the questionnaire................................................................................................................... 161 xiv Figure 6.3 Harvesters’ observation o f normal (black column) and unusual behaviour (gray column) in whales during the harvest (w = 11), based on mercury (Hg) exposure (above or below the median Hg concentration measured)............................................ 162 Figure 6.4 Variables that may have affected time to harpoon and harvesters observations (black column = less time to harpoon; gray column = more or the same time to harpoon)................................................................................................................ 163 Figure 6.5 Observations o f evasive strategies (« = 7) demonstrated during beluga harvest and related mercury (Hg) exposure (more or less than median Hg)..............164 xv Glossary AMAP: Arctic Monitoring and Assessment Program CHL: chlordane; CBz: chlorobenzene DDT: dichlorodiphenyltrichloroethane dw: dry weight EBS: eastern Beaufort Sea FJMC: Fisheries Joint Management Committee FNP: flunitrazepam GABA: y-aminobutyric acid HBCD: hexabromocyclododecane HCH: hexachlorocyclohexane Hg: mercury iHg: inorganic Hg ISR: Inuvialuit Settlement Region OC: organic contaminant mAChR: muscarinic acetylcholine receptor MAO: monoamine oxidase MeHg: methylmercury M K-801: Dizocilpinehydrogen maleate NCP: Northern Contaminants Program nss: Not statistically significant NMDA: N-methyl-D-aspartate PAH: polycyclic aromatic hydrocarbon PBDE: polybrominated diphenyl ether PCB: polychlorinated biphenyl PCDD: polychlorinated dibenzo-p-dioxin PFC: perfluorinated compounds PFCA: perfluorinated carboxylic acid PFSA: perfluorinated sulfonic acid POP: persistent organic pollutant ww: wet weight QNB: quinuclidinyl benzilate Se: selenium TEK: Traditional Ecological Knowledge TSK: Tradtional Scientific Knowledge Acknowledgements A heartfelt thank you to the community o f Tuktoyaktuk for sharing your knowledge about beluga whales with me. This project would not have been possible without the kindness, teachings and support provided by Frank and Nellie Pokiak and their family. Thank you Robin Felix, Ronald Felix, Eric Loring, Lisa Loseto, Eddie Lucas, Marie Noel, Jocelyn Noksana, Kayla Nuyaviak, Dale Panaktolok, Mikkel Panaktolok, Charles Pokiak, James Pokiak, Maureen Pokiak, Myma Pokiak, Rebecca Pokiak, Verna Pokiak, Kate Snow, Brandon Voudrach and Ryan Walker for making the sampling program and community visits enjoyable and successful. I have greatly appreciated the opportunity to study with Dr. Laurie Chan and his UNBC research team. Laurie gave me the opportunity o f a lifetime to study beluga whales in the Beaufort Sea with an amazing group o f researchers and community members. I am grateful for Laurie’s guidance and support on this research journey. I am also very thankful for the support, friendship and guidance offered by Dr. Nil Basu and his students at the University o f Michigan. I appreciated the opportunity to collaborate with Drs. Feiyue Wang, Gary Stern and Marcos Lemes. I have benefitted from the feedback and support from my committee members: Drs. Andrea Gorrell, Stephen Raverty, Mark Shrimpton, and Gary Wilson. My family has been incredibly supportive during my entire PhD journey- from the move to Prince George, BC from Montreal, QC, to many field seasons in the Inuvialuit Settlement Region, and the ups and downs that life has to offer. Thank you Julia and Colleen for many inspiring conversations about this project, Sebastian and Dave for your support and understanding, Joachim and Matthias for your encouragement and positivity, and my grandparents for your curiosity, love and prayers. Living and learning in Prince George, British Columbia would not have been as fulfilling without the energy and dedication o f the PGSO, PGCM, CNSC and the Sea to Sands Conservation Alliance. Thank you Maria for teaching me about balance and mindfulness through our many sessions together. Finally, thank you to all o f you who became my Prince George family and are working towards making this world a better place. I have appreciated your friendship and company on the adventures that have been plentiful in the last seven years. Finally, this research would not have been possible without the generous financial support from Aboriginal Affairs and Northern Development Canada, BC Leadership Chair in Environmental and Aboriginal Health, Fisheries Joint Management Committee, N asiw ik Centre for Inuit Health and Changing Environments, the Natural Sciences and Engineering Research Council and University o f Northern British Columbia. Dedication This thesis is dedicated to Alyssa, for your knowledge and friendship; Anthony, for your youthful energy; and My grandmothers, for your love, prayers and chocolate. Chapter 1. Introduction Contaminants are transported from southern latitudes to the Arctic via atmospheric and oceanic circulation, and river discharges (Braune et al., 2005). Heavy metals, organic contaminants (OCs), and radionuclides bioaccumulate in Arctic aquatic ecosystems (Atwell et al., 1998; Dietz et al., 2000; Loseto et al., 2008b; Mackey et al., 1996; Stern et al., 2005; Tomy et al., 2004). The far-reaching impacts o f pollution were only recognized in the 1970s, when it was discovered that the Arctic was contaminated with organic pollutants (Barrie et al., 1992). Unlike most OCs, mercury (Hg) occurs naturally; however, anthropogenic activities are responsible for the release of the majority o f Hg into the environment (Nriagu and Pacyna, 1988). Marine mammals and humans are susceptible to accumulating contaminants such as persistent organic pollutants (POPs) and Hg due to their long life-spans and high trophic position (Chan et al., 1995; Dewailly et al., 1993; Hoekstra et al., 2003; Loseto et al., 2008b). Inuit continue to harvest marine mammal species including beluga whales (Delphinapterus leucas), narwhal (Monodon monoceros), polar bears (Ursus maritimus) and ringed seals (Pusa hispida), for food, employment, or both (Hovelsrud et al., 2008). Therefore, the accumulation o f persistent organic pollutants and heavy metals in the Canadian Arctic is an issue o f concern for both humans (Van Oostdam et al., 2005) and wildlife (Fisk et al., 2005). Past research has shown that beluga whales accumulate higher levels o f OCs and heavy metals than terrestrial mammals due to their trophic position and long life span (Dietz et al., 2000; Lockhart et al., 2005; Stern et al., 2005). Animal feeding trials have demonstrated that a number 19 of these contaminants are also capable of disrupting components o f mammalian systems integral to animal health (Bimbaum and Tuomisto, 2000; Clarkson, 1997; Costa et al., 2007; Fisk et al., 2005; Fournier et al., 2000; Lehmler et al., 2005; Mathieu et al., 1997). Contaminants in wildlife lead to increased exposure to toxins for consumers o f traditional foods (Van Oostdam et al., 2005), but may also cause adverse impacts to animal health. The effects of contaminants on marine mammal health are poorly understood in part due to the challenges associated with correlating contaminant exposure to various adverse health outcomes in wild populations (Fisk et al., 2005). Recent studies detected levels of Hg in the brains o f belugas in the western Arctic that exceed thresholds o f effect in other animal species (Lockhart et al., 2005), which suggests that mercury exposure could lead to adverse effects in beluga whales at current levels. Mercury is neurotoxic and may affect brain function in highly-exposed animals (Clarkson, 1997). Mercury neurotoxicity could lead to loss o f critical components of animal function required for thriving and surviving in the wild. For example, acute MeHg exposure in humans has been associated with negative impacts to the visual system and neuro-motor function, peripheral neuropathy, dysarthria, tremor, cerebellar ataxia, gait disturbance and audiological impairment (Council, 2000). Although lab-based studies are useful for addressing specific biochemical or physiological effects, field studies are essential for understanding the real-world effects o f chronic exposure to multiple contaminants (Rhind, 2009). Bringing together the results from diverse studies is necessary for the action o f pollutants on multiple species and ecosystem function to be elucidated (Rhind, 2009). Neurochemical changes may represent early and reversible indicators o f neurological harm because they occur prior to the onset o f overt 20 functional or structural damage (Manzo et al., 1996; Manzo et al., 2001). Neurochemical biomarkers from diverse signaling pathways have been used to assess potential neurotoxicological risk o f MeHg exposure in terrestrial mammals, avian species and marine mammals; results have suggested that environmental exposure to MeHg was associated with neurochemical variation in diverse species (Basu et al., 2005a; Basu et al., 2006a; Basu et al., 2005c; Basu et al., 2007b; Basu et al., 2007c; Basu et al., 2009; Hamilton et al., 2011; Rutkiewicz et al., 2010; Scheuhammer et al., 2008). Therefore, a neurochemical biomarker approach may provide valuable information about potential neurotoxicity in wildlife exposed to MeHg and other neurotoxins. Inuvialuit harvest beluga whales for food in the western Canadian Arctic, and through collaboration with northern organizations and harvesters, researchers have collected high quality samples for monitoring and research. Inuvialuit have a strong interest in conservation o f the environment; as Inuit Elder, Billy Day noted: “The land, the animals, the waters, the whales, and the fish were very important to our ancestors and still are to us. Even during negotiations for our land claim-settlement, our elders told us that the land and waters had looked after them for centuries and would look after us for many more if we looked after our environment” (Day, 2002). Therefore, the Fisheries Joint Management Committee (FJMC) was established under the Inuvialuit Final Agreement to provide advice on the administration o f the rights and obligations related to fish and marine mammals (Inuvialuit Final Agreement, 1987). Beluga whale research fits within one of the main objectives o f the FJMC’s beluga management plan “to provide for a 21 harvest that generates the greatest net benefit to the Inuvialuit while ensuring the long-term sustainability of beluga in the Canadian Beaufort Sea” (FJMC, 2001). Aboriginal knowledge has been increasingly recognized for its contribution to co-management and environmental impact assessments (Usher, 2000). Furthermore, it is likely that scientific and local observations of environmental change could be brought together to identify new avenues for further exploration, compare observations from different scales and discuss potential mechanisms that explain both sets of observations (Huntington et al., 2004). Inuit knowledge about beluga whales is gained through observations made during harvesting activities and travel (Byers and Roberts, 1995; Mymrin et al., 1999). Recent studies have attempted to bridge traditional ecological knowledge (TEK) and traditional scientific knowledge (TSK) in Arctic ecological research (Gagnon and Berteaux, 2009; Gilchrist et al., 2005; Huntington et al., 2004); finding ways to bridge TEK and TSK could potentially further our understanding o f beluga whale health in a changing environment. My thesis research was conducted over six years, which included three sampling seasons, three community visits and one large community workshop. My thesis reflects a collaborative approach to beluga research; I was a member o f a comprehensive beluga-sampling team for the Hendrickson Island Beluga Study (HIBS) from 2008 to 2012. The HIBS was a multi-year research program, aimed at studying the risk of contaminants and assessing the health o f harvested beluga whales. Samples were collected on Hendrickson Island from hunter-harvested beluga whales and the process of collecting samples from harvested whales gave me the opportunity to learn about a different culture and way o f life, and taught me first-hand about the 22 value placed on beluga whales by Inuvialuit. Although this thesis is focused on the assessment o f neurotoxicologicla risk o f MeHg exposure for beluga whales, this work would not have been possible without learning extensively about the relationship between people and their environment in the Arctic, and the linkages between environmental and human health research. Navigating the social dimension o f Arctic research is extremely important because poor communication strategies regarding contaminants have resulted in fear, confusion and health impacts in the communities involved (Furgal et al., 2005). Given that researchers conducting studies in the Arctic are predominantly non-Inuit, in part due to the low high school completion rates among Inuit residing in the Arctic (Richards, 2008), they must learn to communicate effectively to ensure that research studies taking place in the Arctic are addressing community needs and responding to community concerns. Research Aim and Objectives The central nervous system is particularly sensitive to MeHg toxicity (Clarkson and Magos, 2006) and preliminary analyses o f Hg in beluga brains suggested that recent exposure to MeHg might reach levels associated with toxicity in other animals (Lockhart et al., 2005). However, brain tissues samples are not routinely collected and analyzed in beluga whale biomonitoring programs to study Hg accumulation and potential toxicity. Therefore, the principle objective o f this thesis was to investigate the potential risk o f neurotoxicity associated with Hg exposure in beluga whales harvested in the Mackenzie Delta Estuary of the Inuvialuit Settlement Region. Consistent with the aim o f this research, four objectives were developed: 23 1. to assess toxicological risk of Hg exposure in harvested beluga by comparing Hg concentrations and speciation to threshold levels o f toxicity observed in mammals; 2. to determine the relationship between Hg concentration, speciation and stoichiometric relationship with selenium, to neurochemical and molecular biomarkers o f neurosignaling pathways; 3. to investigate the relationship between harvesters’ observations o f beluga whale behaviour during harvesting and Hg exposure; and, 4. to assess the toxicological significance o f Hg accumulation in beluga whales from the eastern Beaufort Sea population. Thesis structure and contributions Structure This thesis is made up o f four separate manuscripts that have been published or are in review for publication in peer-reviewed journals. The manuscripts were prepared with co-authors, whose contributions are outlined in the written statement (Appendix 4). Collaboration with co-authors has been particularly important for sample analysis, due to the diversity of methods used and tissue samples analyzed for the studies included in this thesis. Overall, collaboration with co­ authors provided the opportunity for the scope and depth o f analysis to be expanded for the research presented in this thesis. 24 Contribution of Chapters Chapter 1 provides the context for this research, outlines the goals and objectives, and presents the structure and contributions of the following five chapters. Chapter 2 provides a review o f the literature related to beluga whales, beluga whale research, Hg in the Arctic, and Hg toxicity. This chapter does not attempt to be an exhaustive review o f the literature, and instead strives to provide the context for the research studies presented in this thesis. Chapter 3 presents the first manuscript, “Mercury distribution and speciation in different brain regions o f beluga whales (Delphinapterus leu ca sf, which is published in the journal Science o f the Total Environment (Ostertag et al., 2013). The article provides analytical data on the distribution and speciation o f Hg in five brain regions sampled from hunter-harvested beluga whales. Furthermore, the stoichiometric relationship between Hg and selenium (Se) was explored, and the predictability o f mercury concentration in brain tissue based on Hg concentrations measured in more frequently sampled tissue (e.g. kidneys, liver, muktuk, muscle and blood). Chapter 4 presents the second manuscript, “Mercury and selenium exposure is associated with molecular and neurochemical biomarkers in two brains regions of Arctic beluga whales (Delphinapterus leucas)”. In this manuscript, I assessed the relationship between Hg concentration, speciation and co-accumulation with Se, with variation of neurochemical and 25 molecular components o f the GABAergic and glutamatergic signaling pathways in beluga whales. Chapter 5 presents the third manuscript, “Methylmercury and selenium exposure were associated with biomarkers o f the cholinergic and dopaminergic signaling pathways in Arctic beluga whales (Delphinapterus leucas)”. In this manuscript, I assessed the relationship between Hg concentration, speciation and co-accumulation with Se, with variation o f neurochemical and molecular components of the cholinergic and dopaminergic signaling pathways. Chapter 6 presents the fourth manuscript “Inuvialuit observations during harvesting activities linked mercury exposure to differences in beluga whale (Delphinapterus leucas) behaviour”. In this manuscript, I documented local observations o f beluga whale behaviour during harvesting activities, to assess whether differences in beluga whale behaviour were associated with mercury concentration. Chapter 7 provides a summary of key findings from the four research papers, presents conclusions regarding the toxicological risk o f Hg exposure for beluga whales from the eastern Beaufort Sea population, and discusses potential next steps for community-based monitoring in the I SR. 26 Chapter 2. Literature Review 1. Beluga Whales l.a Background Beluga whales (Delpinapterus leucas) have a semi-circumpolar distribution with significant populations inhabiting the northern coasts o f Alaska, Canada, Greenland and Norway (Jefferson, 2008). The main diet of beluga whales in the western Canadian Arctic is fish, squid and invertebrates (Loseto et al., 2009; Loseto et al., 2008a). Worldwide, the population o f beluga whales exceeds 150 000, with summering populations concentrated in western Hudson Bay and eastern Beaufort Sea (Jefferson, 2008). The eastern Beaufort Sea (EBS) beluga stock migrates seasonally to the southeastern Beaufort Sea and Amundsen Gulf; they are larger and older than animals harvested from eastern Arctic beluga populations (Luque and Ferguson, 2010). The Committee on the Status of Endangered Wildlife in Canada (COSEWIC) recognizes seven distinct populations o f beluga whales in Canadian waters based on their summer distributions and genetic differences (COSEWIC, 2004). Population estimates o f whales are based on aerial surveys followed by corrections for whales missed due to diving behaviour (O'Hammill et al., 2004). In the east, the estimated population o f the St. Lawrence population is 900-1000, the Ungava Bay population is too small to estimate and the eastern Hudson Bay population numbers around 2000 individuals but is declining rapidly. The western Hudson Bay population is a minimum o f approximately 23 000 animals, the eastern High Arctic - Baffin Bay population is estimated to be 20 000 animals, but it may be potentially two distinct populations: the west Greenland population numbering around 5000 belugas and the north Water population, which 27 numbers approximately 15 000 belugas. The Cumberland Sound population is made up of approximately 1500 animals (may have increased since the 1980s), and a conservative estimate of the EBS population is 39 000 animals. Genetic techniques have been used to distinguish stocks o f belugas based on mitochondrial DNA; however, there is evidence that stocks mingle during their seasonal migrations and the summer distribution o f whales in Hudson Bay do not reflect distinct stocks (DFO, 2001). The ranges o f some beluga populations are known to overlap and the distinction between eastern and western Hudson Bay stocks is disputed by Inuit in Nunavik (O'Hammill et al., 2004; Tyrrell, 2007). l.b Harvesting Beluga whales are harvested for subsistence throughout their circumpolar range, excluding Svalbard. Commercial hunting o f belugas in eastern Canada reduced their numbers and populations in the St. Lawrence Estuary and eastern Canadian Arctic, and many o f these stocks have not fully recovered (DFO, 2001; DFO, 2007). Hunting o f the High Arctic population in Greenland may be causing a significant decline in their population (Alvarez-Flores and HeideJorgensen, 2004). Commercial hunting is permitted in Greenland and the harvest rate has not declined, although the harvest has been regulated in recent years (Sejersen, 2001). Based on the archeological record, beluga whales made up approximately half o f the diet o f pre ­ contact Inuit o f the Mackenzie Delta (Friesen and Arnold, 1995). Beluga hunting typically occurs in the month o f July, when beluga whales migrate through the warm waters o f the Mackenzie Delta Estuary (Harwood and Smith, 2002). Inuvialuit beluga hunters commonly hunt 28 from 4.6 m long aluminum boats and harpoon the whale before killing it, to make retrieval easier (Harwood and Smith, 2002). Between 1990 and 1999, the total annual number o f landed beluga whales on the shores of the Beaufort Sea and Amundsen Coast was 111 (Harwood and Smith, 2002). Beluga whales from this population are also harvested by residents o f some coastal villages in Alaska (average 64 per year between 1995 and 2000) and possibly by residents of Chukotka, Russia (Harwood and Smith, 2002). Beluga whales travel through Kugmallit Bay in the Mackenzie River Estuary during their summer migrations (COSEWIC, 2004). Hunters from Tuktoyaktuk butcher beluga whales on Hendrickson Island following the hunt and generally return to Tuktoyaktuk immediately after butchering the whale to process the muktuk (skin and blubber) and mipku (dry meat). l.c Beluga management in Canada Local, regional and federal organizations manage the marine mammal resources in the three Canadian Inuit land claim regions in which belugas are harvested (table 2.1). In the Inuvialuit Settlement Region, the Fisheries Joint Management Committee (FJMC) was established under the Inuvialuit Final Agreement, in which the DFO and Hunters and Trappers Committees comanage the fisheries and beluga populations (FJMC, 2001). The beluga management plan was developed by the FJMC to ensure that Inuvialuit can continue to harvest beluga whales from the Canadian Beaufort Sea, while ensuring the long-term sustainability o f beluga in the Canadian Beaufort Sea” (FJMC, 2001). The St. Lawrence Estuary Beluga population is currently listed as threatened under Canada’s Species at Risk Act; Fisheries and Oceans Canada has led the recovery strategy, and responsibility for the recovery o f this population is shared between the 29 DFO, and other jurisdictions and agencies (DFO, 2012). Table 2.1 Overview of management structure for beluga whales {Delphinapterus leucas) in Canada. Federal International Local Region Regional Alaska and Inuvialuit Hunters and Fisheries Joint Inuvialuit Beluga Management Trappers Settlement Whale Committee Committee Committees Region Canada/Greenland Joint Commission Nunavut Wildlife Hunters and on the Conservation Management Nunavut Trappers Department and Management o f Associations Board o f Fisheries Narwhal and Beluga and Oceans Hunting Nunavik Marine Trapping and Region Wildlife Nunavik Fishing Board N/A Association Hunters and Tomgat Joint Trappers Nunatsiavut Fisheries Board Organization l.d Traditional ecological knowledge In recent decades, there has been increasing recognition that Indigenous knowledge could contribute to governance processes such as co-management and environmental impact assessments (Usher, 2000). This recognition was one o f the outcomes o f sustained advocacy, the negotiation o f comprehensive land claims across the north, and the development o f formal Environmental Impact Assessments and review processes, in addition to legal developments within the Supreme Court o f Canada and lower court rulings (Usher, 2000). In northern Canada, Indigenous knowledge is recognized in the Northwest Territories as “a valid and essential source o f information about the natural environment and its resources” (Territories, 2005). Internationally, specific recommendations to establish marine and Arctic programmes that 30 include the use o f traditional ecological knowledge (TEK) for the conservation o f biodiversity were presented during the workshop on traditional knowledge and biological diversity (Programme, 1997). More recently, efforts have been made in to integrate or bridge TEK with traditional scientific knowledge in Arctic ecological research (Gagnon and Berteaux, 2009; Gilchrist et al., 2005; Huntington et al., 2004). There are many definitions o f TEK, and one broad definition o f TEK is “knowledge gathered and maintained by groups o f people, based on intimate experience with their environment” (Huntington et al., 2004). Traditional ecological knowledge has provided valuable information about marine mammals in the Arctic (Carter and Nielsen, 2011; Ferguson et al., 2012). Inuit knowledge and wisdom about beluga whales is associated with decades of observations, and includes hunters’ and elders’ knowledge o f beluga whale behaviour and predation (Byers and Roberts, 1995). Observations o f beluga whale diving behaviour, feeding, migration, communication and response to disturbance were made by Indigenous hunters and elders of Chukotka, Russia while hunting beluga whales or pursuing walrus (Odobenus rosmarus divergens) and seals (Phoca spp. and Erignathus barbatus) (Mymrin et al., 1999). l.e Beluga whale research in the ISR Beluga whales have been sampled periodically since the 1970s in the Mackenzie Delta Estuary (Lockhart et al., 2005) in conjunction with beluga harvesting activities. The Pokiak family has sampled beluga whales for the DFO beluga-monitoring program since 2000 and whale monitors were hired annually by the FJMC to document information about harvested whales. The 31 Hendrickson Island Beluga Study (HIBS) began in 2008, to inform scientists, policy makers and Inuvialuit about the effects o f contaminants and climate change on beluga health. The HIBS is one of several community-based monitoring programs in the Inuvialuit Settlement Region, NWT. The main goals o f this study were to increase our understanding of beluga health, and to determine a baseline for beluga health as their summering habitat (Eastern Beaufort Sea) is undergoing changes. The HIBS research team was composed o f four researchers from government and university institutions: L. Loseto (Victoria, BC; Winnipeg, MB), M. Noel (Victoria, BC), S. Raverty (Abbotsford, BC) and S. Ostertag (Prince George, BC). During fieldwork, the research team worked alongside N. Pokiak and F. Pokiak (Tuktoyaktuk, NT), mentoring students and the local whale monitors. Students from Tuktoyaktuk and Inuvik, NT were hired in 2008, 2009, 2010 and 2011 to assist or lead with sampling and lab analyses. The research team collaborated with an extensive network of researchers including Gary Stern (Winnipeg, MB), Feiyue Wang (Winnipeg, MB), Marcos Lemes (Winnipeg, MB), Brian Laird (Ottawa, ON), Laurie Chan (Ottawa, ON), Lois Harwood (Yellowknife, NT), Ole Nielsen (Winnpeg, MB), Gregg Tomy (Winnipeg, MB), and Peter Ross (Victoria, BC). 32 2. Arctic Contaminants 2.a Background Mercury is released into the environment from natural and anthropogenic sources; gaseous elemental Hg(0) is degassed from soils and surface waters, and released during the combustion o f fossil fuels and incineration o f waste (Council, 2000). Elemental Hg(0) is easily volatilized and may be transported for a year or more on wind currents, before it is oxidized to its divalent state (Hg(II)) and deposited in the environment (Martin et al., 2011). Although the Arctic lacks point sources o f Hg emissions, up to 300 tonnes o f Hg are transported annually to the Arctic from southern latitudes (AMAP, 2003; Outridge et al., 2008; Skov et al., 2004). Following deposition, methylating bacteria can convert bioavailable inorganic Hg(II) to the highly toxic monomethylmercury (MeHg) (Kirk et al., 2008; Lindberg et al., 2007). Methylmercury is readily absorbed by organisms, with approximately 95% o f MeHg in fish being absorbed into the bloodstream o f humans (Clarkson and Magos, 2006). Methylmercury biomagnifies in aquatic ecosystems, and there is a millionfold increase in MeHg concentration from seawater to top predators (Clarkson and Magos, 2006). Mercury is transported to the Arctic from southern latitudes at a rate o f 200 to 300 tonnes per year, from both anthropogenic and natural sources (Dietz et al., 2009). Mercury levels in Arctic biota are an order o f magnitude higher today than in the pre-industrial period and approximately 74 to 94% of Hg in biota is estimated to originate from anthropogenic Hg emissions (Dietz et al., 2009). Mercury levels are consistently higher in biota from the western Canadian Arctic than the European Arctic (Riget et al., 2005). Concentrations o f cadmium, lead and arsenic have also 33 increased in the Arctic due to anthropogenic activities including agriculture and the combustion o f coal (Barrie et al., 1992). Organic contaminants o f concern in the Arctic include ‘legacy’ contaminants that were used in high volumes in the past and are now strictly regulated or banned (e.g. polychlorinated biphenyls, PCBs; dichlorodiphenyltrichloroethane, DDT), and current-use chemicals such as perfluorinated compounds (PFCs) and endosulfan (Barrie et al., 1992). Organic contaminants found in Arctic biota can be classified as industrial and commercial organic compounds (e.g. PCBs), chlorobenzenes, dioxins, PFCs and brominated flame retardants), organic pesticides (e.g. DDT, toxaphene, hexachlorocyclohexanes and chlordane) and polycyclic aromatic hydrocarbons (e.g. Benzo(a)pyrene) (Barrie et al., 1992; Letcher et al., 2010). Many OCs in the Arctic are now included in the Stockholm Convention due to their persistence, long-range transport and toxicity. From the 1970s to the 1990s, decreasing trends o f most ‘legacy’ contaminants have been observed; however, emerging contaminants o f concern have also surfaced (e.g. PFCs, brominated flame retardants) (Braune et al., 2005). In general, the concentration o f OCs in marine mammals were found in the following decreasing order: ZPCB > ECHL « EPFS A > ECBz * EHCH « EToxaphene * PFCA > EPBDE > HBCD (Letcher et al., 2010). 2.b Beluga whale exposure to mercury and organic contaminants Environmental contaminants of primary concern for beluga health in the Arctic have been identified as organic pesticides, polycyclic aromatic hydrocarbons (PAHs) and heavy metals (Fisk et al., 2005). Elevated Hg concentrations have been observed in marine mammals, 34 including beluga whales in the western Canadian Arctic compared to the eastern Canadian Arctic (Wagemann et al., 1998). Furthermore, a spike in age-adjusted Hg concentrations was observed in belugas from the Beaufort Sea in the 1990s (Braune et al., 2005). Although Hg concentrations have decreased in recent years in the eastern Beaufort Sea beluga population, Hg concentrations in this population o f whales are significantly higher than concentrations observed in the 1980s (Lockhart et al., 2005). Furthermore, modern beluga whales have Hg concentrations that are 4- to 17- times higher than pre-industrial levels, according to the analysis o f Hg in beluga whale teeth collected from archeological sites and harvest camps (Outridge et al., 2002; Outridge et al., 2009). However, Hg concentrations were consistently higher in belugas from the St. Lawrence Estuary (1.42 - 756 pg/g (n=35)) than the Arctic (0.04 - 182 pg/g (n=94); Beland et al., 1993). Concentrations o f OCs in Arctic belugas were highest in the eastern Canadian Arctic, east Greenland and Svalbard. Arctic beluga whales were exposed to PCBs (geometric mean, range for males only; 3690 (1250 - 10900) ng g'1lw), DDT (2521 (695 - 9150) ng g’1lw), cyclodienes (473 (48 - 4690) ng g'1lw), chlorobenzenes (377 (149 - 957) ng g '1lw), cyclodienes (473 (48 4690) ng g '1lw), hexachlorocyclohexane (lindanes, 119 (32 —440) ng g'1lw) and poly brominated diphenyl ethers (34 (13-96) ng g '1lw) (Kelly et al., 2008). In previous studies, OCs were consistently found at lower concentrations in brain tissue than in other organs (i.e. blubber, liver, kidney and muscle) o f east Pacific gray whales {Eschrichtius robustus, (Krahn et al., 2001)), Black Sea harbor porpoises (Phocoena phocoena relicta, (Weijs et al., 2010)) and harbor seals (Phoca vitulina) from the southern coast o f Norway (Bernhoft and Skaare, 1994). My thesis focused on the potential neurotoxicity associated with MeHg exposure for beluga whales because 35 ‘legacy’ OC concentrations appear to be decreasing in Arctic biota (Braune et al., 2005), the blood-brain-barrier may reduce the transfer o f OCs to the brain (Bemholt and Skaare, 1994), and OC concentrations are lower in biota from the western Canadian Arctic than other regions o f the Arctic (Letcher et al., 2010). Although concentrations o f OCs in brain tissue o f beluga whales in the Beaufort Sea may be relatively low and decreasing, OC exposure could be of neurotoxicological concern given the neurotoxicity o f certain PCB congeners associated in particular with in utero and lactational exposure (Kodavanti, 2005). 2.c Policies The ‘Minamata Convention on Mercury’ is a global, legally binding treaty developed to reduce Hg emissions to the environment. On January 19, 2013, governments agreed to the text o f the Minamata Convention and on October 10, 2013 the treaty was adopted and signed by 93 countries. The temporal trends from the past decades are inconsistent in biota; however, there is strong evidence that Hg levels have increased from pre-industrial times to the present in some Arctic biota (Braune et al., 2005; Dietz et al., 2009). Although Hg emissions have been reduced in many countries in recent years, one new coal-burning energy plant is coming on line every week in India and China (Berry and Ralston, 2008), therefore anthropogenic mercury releases will continue to be of global concern. 36 3. Mercury toxicokinetics and toxicity 3.a Background The half-life of MeHg in the body has been estimated to be approximately 44 d in humans, although the half-life of the body burden o f Hg was 98 d (Smith et al., 1994). In the brain, the half-life of MeHg likely varies between species, but it has been estimated to be on the order o f days or weeks for MeHg and months to years for iHg (Aschner and Aschner, 1990). Methylmercury is removed from the body by demethylation followed by excretion o f inorganic Hg (iHg) in feces and urine (Smith et al., 1994). In whale livers, it has been observed that iHg may form granules made up o f Hg and selenium (Se), to become inert (Lockhart et al., 2005). Mercury neurotoxicity varies with its speciation (i.e. inorganic or MeHg) (Clarkson and Magos, 2006; Michalke et al., 2009) and the complexes it forms with other molecules (e.g. MeHgcysteine or tiemannite). Methylmercury and iHg are both neurotoxic; however, Se may bind to iHg to form HgSe, a non-toxic Hg complex (Bjorkman et al., 1995). Demethylation of MeHg followed by the formation o f compounds similar to mercury selenide (HgSe) was linked to successful detoxification o f Hg-exposed humans (Korbas et al., 2010). Marine mammals and perhaps also some bird species are able to demethylate MeHg and immobilize it in the liver as HgSe (Riget et al., 2007). Previous studies have suggested that Se may be involved in a bio­ transformation process in the brain, which may be initiated by the demethylation o f MeHg followed by the formation o f inert HgSe granules (Nigro and Leonzio, 1996). Therefore, Se may also reduce the toxicity of Hg by reducing oxidative stress associated with Hg exposure, and by 37 forming inert compounds with Hg and forming bis(methylmercury) selenide (Khan and Wang, 2010). Modern day MeHg-poisoning events in Iraq and Japan increased our understanding o f the neurotoxicological risks o f MeHg exposure for adults and the developing fetus (Mergler et al., 2007), and similar outcomes have been observed in mammalian wildlife (Basu and Head, 2010). Methylmercury exposure has been linked to neurochemical disruption with resulting sensory and motor deficits (Sirois and Atchison, 1996). At a cellular level, Hg poisoning was associated with the loss o f neuronal cells in the granular layer o f the cerebellum and visual cortex o f adult humans (Hunter and Russell, 1954). Clinical symptoms o f Hg toxicity include cerebellar ataxia, constriction o f the visual field and damage to the auditory region o f the temporal lobe (Clarkson, 1997; Ekino et al., 2007). Clinical symptoms o f Hg intoxication include the loss o f motor coordination (Bellum et al., 2012), abnormal movements and convulsions (Takeuchi et al., 1977) and loss o f balance (Farina et al., 2005). Macaque monkeys had impaired high-frequency hearing and visual damage following postnatal MeHg exposure (Newland and Paletz, 2000). Prenatal exposure to MeHg caused mental retardation, severe neurological impairments, and diffUse damage to the brain (Clarkson, 1997; Mergler et al., 2007). Exposure to MeHg in utero has been linked to neurobehavioural deficits and decreases in fine motor function in the Faroe Islands and the Seychelles longitudinal studies, respectively (Mergler et al., 2007). Exposure to MeHg has been associated with neurochemical disruption in environmentallyexposed wildlife (see Table 2.2). Biomarkers o f neurochemical variation associated with Hg 38 exposure have been used in previous wildlife studies on piscivorous fish and mammals to relate MeHg exposure to neurochemical endpoints. Methylmercury exposure in loons, eagles, mink, otters and polar bears was associated with changes in receptors (density and/or binding affinity) and enzyme activity: NMDA receptor decreased with increasing total Hg (Hgr, EMeHg and iHg) levels in polar bears (Basu et al., 2009), wild mink (Basu et al., 2007c), loons and eagles (Scheuhammer et al., 2008); muscarinic receptor levels was positively correlated to Hg concentrations in wild mink (Basu et al., 2005a), loons and eagles (Scheuhammer et al., 2008) but the opposite relationship was found in river otters (Basu et al., 2005d). A negative correlation between H gi and the dopamine receptor was also observed in wild river otters and wild mink (Basu et al., 2005a). A negative relationship between GABA a receptor binding levels and Hg was observed in captive mink (Basu 2010), while monoamine oxidase and acetylcholinesterase activities were negatively correlated to brain Hg in wild river otters (Basu et al., 2007b). 39 Table 2.2 Variation of monoamine oxidase (MAO) activity, muscarinic acetylcholine receptor (mAChR), gammaaminobutyric acid receptor (GABA-R) and N-methyl-ZD-aspartate receptor (NMDA-R) associated with MeHg exposure in select mammalian and avian species. __________________________ _______________ ___________________________ Animal Mink (captive) (Mustela visori) Wild mink (mustela vison) River otter (Lontra cade is) Polar bear ( Ursus maritimus) Bald eagle (Haliaeetus leucocephalus) Common loon (Gavia immer) Herring gulls (Larus argentatus) Little brown bats (Myotis lucifugus) Spotted seatrout (Cynoscion nebulosus) MAO mAChR GABA-R NMDA-R (Basu et al., 2008; Basu et al., 2010; Basu et al., 2007c) - Reference 7t - - - (Basu et al., 2005a; Basu et al., 2007c) (Basu et al., 2005d; Basu et al., 2007b) - - - (Basu et al., 2009) - 71 - (Rutkiewicz et al., 2011; Scheuhammer et al., 2008) - 71 ns - - ns - il1 TP2 - - - - - - (Adams et al., 2010) - - (Berntssen et al., 2003) Salmon * (Salmo salar L.) 1 = contaminated site; 2 = non contaminated site; a = ml and m2 subunits for mAChR ns (Hamilton et al., 2011; Scheuhammer et al., 2008) ns (Rutkiewicz et al., 2010) (Nam et al., 2010) 40 3.b Interaction o f MeHg and iHg with neurochemical signaling pathways Previous studies have suggested that the interaction o f MeHg or iHg with cysteine residues may inhibit, stimulate or damage components o f the dopaminergic (Gomes et al., 1976), cholinergic (Castoldi et al., 1996), y-aminobutyric acid (GABA) (Huang and Narahashi, 1997; Narahashi et al., 1994), and glutamatergic (Albrecht and Matyja, 1996) signaling pathways. The following subsections provide a brief background about the cholinergic, dopaminergic, GABA-ergic, and glutamatergic signaling pathways, including an overview of potential interactions o f MeHg and iHg with select components of these signaling pathways. 3.b.l Cholinergic signaling pathway Cholinergic signaling pathways have been linked to essential physiological processes including learning, memory, stress response and modulation o f sensory information (Reis et al., 2009). The muscarinic acetylcholine receptor (mAChR) may play a critical role in physiological processes including thermoregulation, motor function and feeding (Bymaster et al., 2003; Wess, 2004). There are five mAChR subtypes (ml-m5) in mammals, and they each have distinct pharmacological and functional properties (Wess, 1996). The distribution o f mAChR subtypes is heterogeneous in mammalian brains, with m l abundance greater in the forebrain (i.e. cerebrum) and m2 more abundant in the hindbrain (i.e. cerebellum) (Wess, 1996). There are differences in signaling associated with the receptor subtypes. In particular, m l, m3 and m5 are coupled to G proteins of the Gq/u family, which mediate the activation of phospholipase C and subsequent release of Ca2+; the m2 and m4 mAChR subtypes are selectively linked to G-proteins o f the Gi/0 class, which mediate the inhibition of adenylyl cyclase but are not linked to Ca2+ release (Wess, 1996). 41 Methylmercury has a high affinity for sulfhydryl groups and was found to inhibit agonist binding to ml and m2 muscarinic receptors in rat brain cortical membranes (Castoldi et al., 1996). The ml subtype may be more sensitive than m2 to Hg exposure based on in vivo and in vitro experiments (Basu et al., 2008; Castoldi et al., 1996). Mercuric chloride and MeHg may modify mAChR activity by binding to the binding site o f the mAChR and competitively inhibiting ligand- binding (Abd-Elfattah and Shamoo, 1981). The binding of MeHg to mAChR has been linked to disruption of Ca2+ homeostasis in cerebellar granule cells, and has been suggested as a cause o f cell-regulated death (apoptosis) or the downregulation of mAChR (Limke et al., 2004). Furthermore, inhibiting binding o f the m3 mAChR reduced the effect o f MeHg on the amplitude o f Ca2+ elevations (Limke et al., 2004). Methylmercury and Hg2+ inhibited radioligand binding (in vitro) to the mAChR receptor in ringed seal brain homogenate (Basu et al., 2006a). An increase in mAChR density was observed in rat hippocampus and cerebellum following chronic exposure to low doses o f MeHg, which may have been due to the inhibition o f acetylcholine synthesis and the competitive antagonism o f MeHg at the receptors (Castoldi et al., 2003). 3.b.2 Dopaminergic signaling pathway Dopamine plays an important role in cognition, emotion, memory processes and learning (Dailey and Everitt, 2009). Monoamine oxidase (MAO) is present in two forms in the brain, and is responsible for the oxidative deamination o f a number o f biogenic amines including dopamine (Shih et al., 1999). Two forms o f MAO exist, MAO-A has higher affinity for the substrates serotonin, norepinephrine, dopamine, and the inhibitor clorgyline, whereas MAO-B has higher affinity for phenylethylamine, benzylamine, and the inhibitor deprenyl (Shih et al., 1999). Both 42 MAO-A and B are located throughout the brain in the outer membrane o f mitochondria (Green and Youdim, 1975) and are encoded by different genes (Bach et al., 1988; Grimsby et al., 1991). Methylmercury may exert an effect on MAO either by directly binding to thiol groups on the enzyme (Chakrabarti et al., 1998) or by altering mitochondrial function (Komulainen et al., 1995). 3.b.3 The GABA-ergic signaling pathway The GABAa receptors form GABA-gated chloride ion channels that are responsible for inhibitory synaptic transmission (Penschuck et al., 1999). The major GABAa receptor subtypes are made up o f a pentameric assembly o f distinct subunits (a, p and y2) including six unique a subunits (ai- a6) that have been cloned to date (Vicini and Ortinski, 2004). The decarboxylation o f glutamate gives rise to GABA, which is an inhibitory neurotransmitter. GABAa receptors are associated with sedation, sleep induction, and myorelaxation, as well as anxiety, seizures and amnesia (Vicini and Ortinski, 2004). Furthermore, the benzodiazepine binding site on the GABAa receptor modulates the activity o f the GABAa receptor (Chebib and Johnston, 1999). In cell cultures, MeHg chloride and mercury chloride (HgCh) inhibited the uptake o f GABA by cultured astrocytes from newborn rat cerebral cortex (Brookes and Kristt, 1989) and HgCh increased the affinity o f GABA a receptor for GABA (Huang and Narahashi, 1996). Mercury was found to modulate GABA-induced inward currents: HgCh induced a larger inward current and MeHg suppressed this inward current (Arakawa et al., 1991; Narahashi et al., 1994). In cerebellar granule cells in culture, inhibition o f GABA a receptor-mediated currents was observed when cells were exposed to 0.1 uM MeHg (Yuan et al., 2005). Following MeHg 43 exposure, a decrease in GABA a receptor levels could occur to maintain homeostasis of GABAergic signaling following Hg exposure (Basu et al., 2010). Decreased GABA a receptor levels occur in neurons following exposure to GABA and various GABA a receptor agonists (Barnes, 1996). Inhibition of the GABA a receptor could potentially lead to an excitatory effect (Sunol et al., 2008); therefore, receptors and enzymes that mediate GABAergic signaling are tightly regulated to protect neurons from excitotoxicity (Reis et al., 2009). Regulation o f GABA a receptors may include desensitization o f the receptor, endocytosis and degradation o f subunit polypeptides and the repression o f subunit gene expression (Barnes, 1996). 3.b.4 Glutamatergic signaling pathway The N-methyl-D-aspartate receptor (NMDA-R) is a separate class o f glutamate-gated ion channels, and is activated by the artificial glutamate analogue N-methyl-D-aspartate. Glutamate is thought to be one of the major excitatory transmitters in the brain and may be used by up to 40% o f synapses (Coyle and Puttfarcken, 1993). NMDA receptors are double-gated and open only when two conditions are met simultaneously; glutamate must be bound to the receptor and the membrane must be strongly depolarized (Johnson and Ascher, 1987). NMDA receptors are critical for longterm potentiation (Harris et al., 1984); however, overstimulation o f the NMDA R can cause neuronal excitotoxicity, and has been linked to the loss of neurons, Alzheimer’s disease, and other neurodegenerative diseases (Cull-Candy et al., 2001). A glutamate-mediated excitotoxic mechanism o f MeHg neurotoxicity is supported by several studies. Methylmercury induced an increase in extracellular glutamate (Juarez etal., 2002); the 44 activation of NMDA receptors was found to play a key role in glutamate-associated excitotoxicity of astrocyte cultures (Albrecht and Matyja, 1996). The NMDA receptor was linked to increased release o f dopamine following MeHg and iHg exposure in vivo, and the inhibition of nitric oxide synthase (NOS) activity reduced the release o f dopamine (Faro et al., 2002; Vidal et al., 2007). Astrocytes play a key role in regulating the transport and clearance o f neurotransmitters in the synaptic space (Fitsanakis and Aschner, 2005). Excitotoxicity can be caused by the overstimulation o f the NMDA receptor (Coyle and Puttfarcken, 1993); therefore, MeHg-associated increases in extracellular glutamate could have implications for neurotoxicity. Furthermore, the NMDA receptor was linked to DNA damage with MeHg exposure in vivo (Juarez et al., 2005), and increased Ca2+ influx and apoptosis of cerebellar granule cells following Hg2+ exposure (Rossi et al., 1997). 4. Assessing potential toxicity 4.a Characterizing the risk of toxicity in wildlife In general, two approaches have been taken to identify and characterize the risk o f toxicity associated with contaminants in Arctic species (Dietz et al., 2013). The first approach used a comparison o f the concentration o f contaminants in Arctic species and toxicity thresholds or known levels of toxicity. The extrapolation o f risk was based on threshold levels that are usually taken from laboratory studies or field studies. Challenges with extrapolation include the differences in exposure regimes between laboratory animals and wildlife (e.g. chronic vs acute, short term vs long-term, single contaminant vs mixtures of contaminants), inter-species 45 differences in sensitivity, and differences in additional stressors faced by free-ranging animals (Dietz et al., 2013). The second approach investigated potential toxic effects by studying the response o f biomarkers (indicators o f biological response) to contaminants (Skaare et al., 2002). Although biomarkers can involve any biological change from a molecular to ecosystem level, the term generally refers to changes at lower levels o f biological organization that are associated with exposure to contaminants (Skaare et al., 2002). To identify potential behavioural effects o f MeHg exposure, contaminant exposure data must be linked to whole-animal observations. Inuit observe beluga whales during harvesting activities and travel, and thereby gain substantial knowledge about these animals (Byers and Roberts, 1995; Mymrin et al., 1999). Collecting information about beluga whales using both traditional scientific knowledge (TSK) and traditional ecological knowledge (TEK) could provide the opportunity to compare observations made at different scales (i.e. chemical and whole-animal) (Huntington et al., 2004). 4 b. Methods Given the sensitivity o f the central nervous system (CNS) to the neurotoxic effects o f Hg, it is relevant to determine Hg concentrations, distribution, speciation and potential detoxification in the CNS to assess health risks due to MeHg exposure. Analysis of potential neurochemical disruption associated with MeHg exposure in beluga whales would provide much needed information about potential risk o f current MeHg exposure levels for these cetaceans. Finally, 46 integrating TSK and TEK could provide evidence o f a physiological effect o f MeHg exposure on beluga whales. The methods used for the studies presented in this thesis are outlined below. 4.b.l Radioligand binding assays Radioligand binding assays use a ligand that is labeled with a radioactive isotope (e.g. 3H, l25I or 35S) that binds to a receptor to make detection o f the receptor possible (Leysen et al., 2010). Either homogenized or sliced tissue, or cells in culture can be used for these assays. The tissue preparation is first incubated with the labeled ligand, and the bound labeled ligand is collected and detected using various techniques (e.g. filtration techniques combined with radioactivity counting) (Leysen et al., 2010). For 3H-labeled ligands, a liquid scintillation cocktail is added to the filters, the energy emitted by the radioisotopes first excites the aromatic solvent molecules in the cocktail, and the fluor molecules absorb and re-emit this energy, which is detected by a photomultiplier detector (Staff, 2004). To determine the maximum number o f receptor binding sites in the tissue preparation (Bmax), the specific binding is calculated by subtracting the non­ specific binding from the total binding (Leysen et al., 2010). The kd value is equal to half o f the maximum binding, and is calculated by nonlinear regression using a curve fitting program (e.g. GraphPad Prism; GraphPad software, La Jolla, USA) (Leysen et al., 2010). 4.b.2 Monoamine oxidase assay Monoamine oxidase activity may be quantified through a horseradish peroxidase-coupled reaction using Amplex Red (10-acetyl-3,7-dihydroxyphenoxazine ). Briefly, tyramine is a 47 substrate for both MAO-A and MAO-B, and the oxidation o f tyramine by MAO produces hydrogen peroxide. Amplex Red combined with horseradish peroxidase reacts with hydrogen peroxide in a 1:1 stoichiometry, to produce the fluorescent compound resorufin (Held, 2003). Quantification o f resorufin produced occurs via fluorescence spectroscopy, which records the excitation and emission spectra (Lakowicz, 2006). A microplate reader uses a xenon flash lamp as a light source, and the specific excitation wavelength is selected with a monochromator (Lakowicz, 2006). A mirror with a hole is used to transmit the excitation and also to direct the fluorescence toward the detector optics (Lakowicz, 2006). 4.b.3 Real Time Polymerase Chain Reaction Reverse transcriptase is a ribonucleic acid (RNA)-dependent DNA polymerase that synthesizes DNA complementary to an RNA template, using a mixture o f the four deoxyribonucleotides in the presence o f a short oligonucleotide primer or random hexamers (Rapley, 2010). Real time Polymerase Chain Reaction (RT PCR) generates an exponential increase in copies o f a DNA template, which can be quantified based on the relationship between the amount o f starting target and the amount o f PCR product (Arya et al., 2005). Specific detection o f PCR product (amplicons) is carried out based on two available chemistries: double-stranded DNA (dsDNA) binding dyes and fluorescent probes (Arya et al., 2005). In the case o f DNA-binding dyes, SYBR® Green 1 binds to dsDNA and emits a strong signal (Arya et al., 2005). The fluorescence signal increases during polymerization and decreases upon denaturing; therefore, measurement o f fluorescence occurs at the end o f the elongation step o f each PCR cycle (Arya et al., 2005). SYBR® Green 1 binds all dsDNA; therefore, amplification o f non-specific PCR products and 48 primer-dimers reduces the specificity o f the assay (Arya et al., 2005). Fluorescent probes (e.g. TaqMan probes) can be used in combination with specific forward and reverse primers; fluorescence emission increases during PCR amplification when the probe anneals to the target and Taq polymerase cleaves the probe (Arya et al., 2005). Absolute quantitation depends on quantifying the initial number o f target copies through the use of a standard curve (Livak and Schmittgen, 2001). The Pfaffl method provides a model for relative quantification of a target gene transcript in comparison to a reference gene transcript (Pfaffl, 2001). With this method, PCR efficiency ( E ) for each target and reference gene is calculated based on the crossing point (CP) cycle number and the input o f cDNA (ng), according to the equation: E = 10(' l/slope) (Pfaffl, 2001). The ratio is defined as the expression o f a target gene in the sample versus the control, compared to the reference gene: ratio = ( E t a r g e t ) ACP torget (control - s a m p ie )/(E re fe re n c e )ACP ref (c o n tro l -sample >_ The comparative threshold method is another commonly used method for calculating relative changes in gene expression, and does not require a standard curve (Arya et al., 2005). The 2"AACt is calculated based on the relative expression o f the target compared to the reference gene or calibrator (-AACt = ACt (sample) - ACt (control)) (Arya et al., 2005). This method requires similar amplification efficiencies for the target and reference genes (Arya et al., 2005). An internal reference gene or calibrator is required to minimize the errors associated with the starting amount o f RNA, the quality o f RNA, differences in cDNA synthesis efficiency and PCR amplification (Arya et al., 2005). Reference genes must be selected to normalize the RNA values, and their expression should be consistent at all stages o f development and throughout different experimental conditions (Arya et al., 2005). Typically, housekeeping 49 genes such as beta-actin, glyceraldehyde-3-phosphate dehydrogenase and ribosomal RNA are used for normalization (Arya et al., 2005). 4.b.4 Traditional ecological knowledge questionnaires There are many definitions o f TEK, and one broad definition o f TEK is “knowledge gathered and maintained by groups o f people, based on intimate experience with their environment” (Huntington et al., 2004). Questionnaires have been identified as one o f many methods for documenting TEK (Huntington, 2000). The strength o f questionnaires is that they provide consistency and allow comparisons to be made between respondents and over time; however, semi-directed interviews provide a greater depth and breadth o f knowledge and may reveal unanticipated information (Huntington, 2000). Traditional ecological knowledge has provided valuable information about marine mammals in the Arctic (Carter and Nielsen, 2011; Ferguson et al., 2012). Inuit knowledge and wisdom about beluga whales is associated with decades of observations, and includes hunters’ and elders’ knowledge o f beluga whale behaviour and predation (Byers and Roberts, 1995). 5. Responsibility and accountability in northern research Research that takes place in the north must abide by a number o f ethical principles (ACUNS, 2003; ITK and NRI, 2007) and regulatory requirements. In particular, Inuit communities expect meaningful consultation, inclusion and communication throughout the research process (ITK and NRI, 2007). Reporting o f research results is of particular concern among Inuit communities, 50 especially the timing and formatting o f researchers’ reporting procedures (ITK and NRI, 2007). In fact, early and frequent communication, local training, and community participation in research activities were identified as being critical for building trusting research relationships in natural science research in Nunavut (Gearheard and Shirley, 2007). This may be o f even more importance in beluga whale research, given the high cultural and nutritional value o f beluga for many Inuit. The significance o f beluga extends beyond the consumption of meat and muktuk, and includes the whale-hunting complex (Tyrrell, 2007), and food-sharing, which reinforces social relations (Condon et al., 1995). In general, whales play an important role in maintaining Inuit identities, culture and well-being (Freeman et al., 1998). Traditional harvesting activities are also linked to Inuit well-being: ‘the land teaches us not only the technical skills o f aiming a gun or harpoon or skinning a seal, but also what is required to survive, giving confidence to our people’ (Watt-Cloutier, 2003). 51 Chapter 3. Mercury distribution and speciation in different brain regions of beluga whales {Delphinapterus leucas) Names and Affiliations o f Authors: 1. Sonja K. Ostertag Natural Resources and Environmental Studies, University o f Northern British Columbia, Prince George, British Columbia, Canada, V2N 4Z9 ostertag@unbc.ca 2. Gary A. Stem Freshwater Institute, Fisheries and Oceans Canada, Winnipeg, Manitoba, Canada, R3T 2N6 Centre for Earth Observation Science, Department o f Environment and Geography, University o f Manitoba, Winnipeg, Manitoba, Canada, R3T 2N2 Gary.Stem@dfo-mpo.gc.ca 3. Feiyue Wang Centre for Earth Observation Science, Department o f Environment and Geography and Department o f Chemistry, University o f Manitoba, Winnipeg, Manitoba, Canada, R3T 2N2 feivue.wang@ad.umanitoba.ca 4. Marcos Lemes Centre for Earth Observation Science, Department o f Environment and Geography, University of Manitoba, Winnipeg, Manitoba, Canada R3T 2N2 Marco s. lemes@ad .umanitoba .ca 5. Hing Man Chan Center for Advanced Research in Environmental Genomics, University of Ottawa, Ottawa, Ontario, Canada KIN 6N5 laurie.chan@uottawa.ca 52 Abstract The toxicokinetics of mercury (Hg) in key species of Arctic ecosystem are poorly understood. We sampled five brain regions (frontal lobe, temporal lobe, cerebellum, brain stem and spinal cord) from beluga whales (Delphinapterus leucas) harvested in 2006, 2008, and 2010 from the eastern Beaufort Sea, Canada, and measured total mercury (HgT) and total selenium (SeT) by Inductively Coupled Plasma Mass Spectrometry (ICP-MS) or Hg analyzer, and the chemical forms using a HPLC-ICP-MS. At least 14% o f the beluga whales had HgT concentrations higher than levels o f observable adverse effect (6.0 mg kg'1 wet weight (ww)) in primates. The concentrations o f HgT differed between brain regions; median concentrations (mg kg"1ww) were 2.34 (0.06 to 22.6, 81) (range, n) in temporal lobe, 1.84 (0.12 to 21.9, 77) in frontal lobe, 1.84 (0.05 to 16.9, 83) in cerebellum, 1.25 (0.02 to 11.1, 77) in spinal cord and 1.32 (0.13 to 15.2, 39) in brain stem. Total Hg concentrations in the cerebellum increased with age (p < 0.05). Between 35 and 45% o f HgT was water-soluble, of which, 32 to 41% was methylmercury (MeHg) and 59 to 68% was labile inorganic Hg. The concentration of MeHg (range: 0.03 to 1.05 mg kg"1ww) was positively correlated with HgT concentration, and the percent MeHg (4 to 109%) decreased exponentially with increasing HgT concentration in the spinal cord, cerebellum, frontal lobe and temporal lobe. There was a positive correlation between SeT and HgT in all brain regions (p < 0.05) suggesting that Se may play a role in the detoxification o f Hg in the brain. The concentration of HgT in cerebellum was significantly correlated with HgT in other organs. Therefore, HgT concentrations in organs that are frequently sampled in bio-monitoring studies could be used to estimate HgT concentrations in the cerebellum, which is the target organ of MeHg toxicity. 53 Introduction Beluga whales (Delpinapterus leucas) have a semi-circumpolar distribution with significant populations inhabiting the northern coasts of Alaska, Canada, Greenland and Norway (Jefferson, 2008). Worldwide, the population of beluga whales exceeds 150 000, with summering populations concentrated in western Hudson Bay and eastern Beaufort Sea (Jefferson, 2008). The eastern Beaufort Sea beluga stock is known to migrate seasonally to the southeastern Beaufort Sea and Amundsen Gulf (Figure 3.1); they are larger and older than animals harvested from eastern Arctic beluga populations (Luque and Ferguson, 2010). The main diet o f beluga whale is fish, squid and invertebrates (Loseto et al., 2009; Loseto et al., 2008a). Beluga whales can accumulate high concentrations o f organic and metal contaminants due to their trophic position (Dietz et al., 2000; Lockhart et al., 2005; Stern et al., 2005) and long lifespans (Luque and Ferguson, 2010). Mercury (Hg) is a global pollutant and a potent neurotoxicant (Gladden et al., 1999). Elevated concentrations o f Hg (> 1 mg kg'1 ww) were reported in brain tissue o f beluga collected in the western Arctic from 1998 to 2002 (Lockhart et al., 2005). Mercury exposure has been associated with neurochemical disruption in environmentally-exposed wildlife (Basu et al., 2005b; Basu et al., 2005d; Basu et al., 2009; Scheuhammer et al., 2008). Therefore, beluga whales may be at risk o f Hg-related neurochemical disruption. Mercury concentrations in the Arctic have increased significantly due to anthropogenic activities, and current estimates suggest that 72 to 94 % o f Hg in biota in the Arctic comes from 54 anthropogenic emissions (Dietz et al., 2009). A previous study o f beluga teeth collected from recent harvests, and archeological sites in the Inuvialuit Settlement Region (ISR), NT, Canada, indicated that Hg concentrations have increased by an order o f magnitude since the 16th century, with Hg concentrations in older animals harvested in 1993 estimated to be 16.7 times greater than expected in their pre-industrial counterparts (Outridge et al., 2002). The risk o f increased Hg exposure in beluga whales is poorly understood. As beluga whale is an important part o f the Inuit diet, the well-being o f the beluga whale population has implications for food security and public health (Wesche and Chan, 2010). To assess toxicokinetics associated with Hg exposure in beluga whales, it is necessary to determine the concentrations, speciation and distribution of Hg in the brains o f exposed animals. Beluga whales are primarily exposed to methylmercury (MeHg) from the diet (Loseto et al., 2008b), which is the most neurotoxic Hg species (Yokel et al., 2006). More than 95% o f ingested MeHg is absorbed (Aberg et al., 1969) and may cross the blood brain barrier via neutral amino acid transporters (Aschner and Aschner, 1990). Methylmercury may undergo demethylation in the brain (Shapiro and Chan, 2008; Yokel et al., 2006), and co-exposure to selenium (Se) and Hg may increase the rates of MeHg uptake, demethylation, and inorganic Hg (iHg) retention in the brain(Bjorkman et al., 1995; Magos and Webb, 1980; Newland et al., 2006). In this study, we analyzed Hg concentration, distribution and speciation in beluga tissue samples from different brain regions in order to assess the toxicological significance o f current Hg and MeHg concentrations in the Arctic beluga whale populations. 55 Material and methods Sample Collection Five brain regions from harvested beluga whales were sampled at Hendrickson Island between June 30 and July 25 in 2006, 2008 and 2010, and at East Whitefish station in 2006 (Figure 3.1). These locations are two traditional beluga-hunting camps in Kugmallit Bay (KB), Inuvialuit Settlement Region (ISR), NT. Prior to each sampling season, a research permit and scientific license to fish were obtained from the Aurora Research Institute and Department o f Fisheries and Oceans. The sampling program was approved and supported by the Tuktoyaktuk and Inuvik Hunters and Trappers Committees for all sampling years. Grey matter (cortex) from the cerebellum (C), frontal lobe (FL), and temporal lobe (TL), and white matter from the brain stem (BS; only in 2010) and spinal cord (SC) were dissected and placed into pre-weighed, acid-washed scintillation vials. Whole brains were collected and frozen in the field in 2006 (« = 46) and later dissected at UNBC; in 2008 {n = 24) and 2010 (n = 15), samples were dissected in the field and frozen immediately (approx -20 °C). Whole blood was collected into BD Vacutainer® blood collection tubes (with K 2 EDTA; Becton Dickinson) from the neck of harvested whales in 2008. Kidney, muscle, muktuk (skin and fat), and liver samples were collected on Hendrickson Island and frozen on site in a portable freezer at -20 °C. Animal age was estimated from a thin section o f a tooth by counting individual growth layer groups in the dentine at the Freshwater Institute, Winnipeg, Manitoba, Canada (Stewart, 2006). 56 Sample analysis Brain samples were freeze-dried for 72 hours at -80 °C and homogenized individually with a glass rod. Blood samples were thawed at room temperature and vortexed thoroughly prior to analysis. Total Hg (Hgj) in blood and 2008 brain samples were measured using a total mercury analyzer (MA-2000, Nippon Instruments Corp., Osaka, Japan) and the methods are described in more detail elsewhere (Basu et al., 2005d). In brief, -1 0 mg freeze-dried sample or 100 pL blood (29 v/v % in RNA preservative solution; 70% ammonium sulfate (Omnipur), 25 mM sodium citrate (Omnipur), 10 mM EDTA disodium salt dihydrate (Omnipur) was embedded in carbonate powder (sodium carbonate (Sigma Aldrich), calcium hydroxide (Fisher) and activated alumina (Nippon Instruments Corp.), followed by thermal decomposition at 800 °C for six minutes. Mercury vapour was then trapped by gold amalgamation, thermally desorbed and then measured by cold-vapour atomic absorption spectrometry (wavelength = 253.7 nm). Recovery of Hgr in the standard reference material (DOLT-4; Dogfish Liver Certified Reference Material for Trace Metals; National Research Council) was 98.8 ± 0.7% o f the certified value and Hgr in blanks samples were -0.02 ± 0.06 ng mg'1 for a 10 mg sample. Total Hg concentration data from the MA-2000 were correlated to values obtained following acid digestion (r = 0.99, p < 0.05), and measured with Inductively Coupled Plasma Mass Spectrometry (ICP-MS) as described below. Total Hg and total selenium (Sej) in all brain samples (2006, 2008 and 2010) were analyzed by ICP-MS (Agilent Technologies, 7500 CX) following a modified acid digestion (Armstrong and Uthe, 1971). In brief, -1 0 mg dry weight (dw) homogenized sample was rinsed with acetone 57 (Omnisolv) to remove lipids, and digested using trace metal grades nitric acid (Fisher), hydrochloric acid (Sigma) and H 2 O 2 (Fisher), and heating at 100 °C for five hours. Total Hg (average o f mass 200, 201 and 202) and Ser (mass 82) were quantified by ICP-MS under the following parameters: plasma power 1550 W, nebulizer gas flow rate 1.05 L/min, Micromist Nebulizer (Glass Expansion™) flow rate 0.4 mL/min with a standard quartz 2.5 mm torch injector. Quantification was based on a four-point calibration curve, using 115In and 193Ir as internal standards for Se and Hg, respectively. Quality assurance/control (QA/QC) was monitored by including one blank, DOLT-4 in triplicate, and one sample in triplicate within each batch of 36 samples. Recovery of Hgr and Ser were 88 ± 1.6 and 92 ± 2.6 %, respectively (n = 18); Hgr and Set concentrations in the blanks were 0.30 ± 0.05 mg kg'1diy weight (dw) and 0.21 ± 0.06 mg kg'1 dw for a 10 mg sample, respectively (« = 17). Detection limits were 0.001 and 0.01 mg kg"1dw for a 10 mg sample, for Hgx and Set, respectively. Mercury speciation analysis was carried out following the method o f Krey et al. (2012). In brief, Hg species were extracted in triplicate from approximately 10 mg dw sample using a solution made up of 0.1% hydrochloric acid, 0.1% 2-mercaptoethanol (Sigma), and 0.15% potassium chloride (Sigma) in ultrapure H 2 O. Samples were sonicated for 30 minutes at 35 °C. Mercury species were collected from the sample by centrifugation at 3000 rpm for ten minutes at 30 °C, the supernatant was saved and the pellet was rinsed by centrifugation with extraction solution (same procedures as before). The combined supernatants were centrifuged at 4000 rpm for 10 minutes at 24 °C, filtered through a 0.45 p.m filter and analyzed using HPLC (Agilent 1200 series HPLC system, Agilent Technologies Canada Inc., Mississauga, ON, Canada), equipped with 58 autosampler, quaternary pump, and 100 ml injection loop. A ZORBAX Eclipse XDBC18 Column (2.1 x 50 mm, 5 pm) was connected to an ICP-MS (Agilent Technologies™, 7500 CX). Fifty pL of sample was injected into the guard column at 0.45 mL/min; the mobile phase used was an isocratic mixture of 94% mobile phase (0.1 % (v/v) 2-mercaptoethanol and 0.06 mol L-1 ammonium acetate (Fluka) plus 6% methanol (Sigma). The instrument parameters were as follows: plasma power (1550 W), nebulizer gas flow rate (Argon, 1.05 L/min), micromist nebulizer (Glass Expansion™) and standard quartz 2.5 mm torch injector. Acquisition was carried out over 500 seconds and Retention Times (RT) were 1.78 and 2.14 for MeHg and Hg, respectively; Hg isotope m/z monitored was 202, with 193Ir used as an internal standard. Quantification was based on five point external calibration curves for Hg and MeHg. With this method, the labile fraction of iHg (iHgiabiie) bound weakly to proteins or thiols was extracted; however, Hg associated with strong structural proteins ( H g b o u n d ) may not be extracted efficiently with this method (Wang et al., 2007). One blank and DOLT-4 in triplicate were included in each sample batch (n = 33) to ensure quality within and between batches. Recovery o f total MeHg and iHg (MeHgi and iHgx) in DOLT-4 were 130 ± 4.7% and 98.9 ±5.8 % ( n = 28), respectively. Both MeHgx and iHgx concentrations were below the level o f detection in all blanks analyzed (n = 7). The concentration o f Hgbound was estimated by subtracting the concentration o f MeHgx and iHgiabiie from the concentration o f Hgx (Equation 1). [H g b o u n d ] = [Hgx] - ([MeHgx] + [ i H g „ b a e ] ) (Eq 1) The temporal lobe samples collected in 2008 were further analyzed for MeHg and Se speciation at the Ultra-Clean Trace Elements Laboratory at the University o f Manitoba, as detailed 59 elsewhere (Lemes and Wang, 2009; 2011). In brief, 100 mg o f freeze-dried brain tissue was extracted, in a 15-ml polypropylene centrifuge tube, with 20 mg trypsin in a 10-ml acetate buffer solution (0.05 M ammonium acetate with 0.5% sodium dodecyl sulphate; pH = 8). The extraction was carried out at 37 °C inside an Isotemp oven (Fisher Scientific) on a tube rotator with rotisserie at 20 rpm for 4 h in the dark to prevent any possible photochemical reaction during the process. The extractant was centrifuged and the supernatant was decanted and filtered through a 0.2 pm pore-size hydrophilic polypropylene membrane (Pall), and diluted 10 times with ultrapure water. The diluted extractant was then analyzed for MeHg and Se speciation using reversed phase HPLC-ICP-MS (Lemes et al., 2011). Quality assurance and quality control o f the MeHg speciation analysis was monitored by analyzing the certified reference material DOLT-3 (CRM; dogfish liver, National Research Council o f Canada). Speciation analysis showed that MeHg in DOLT -3 was present exclusively as CHsHgSCys with a concentration o f 1.41 ± 0.16 mg/g (dry wt; n=9), which agreed very well with the certified MeHgx value o f 1.59 ± 0.12 mg/g (dry wt). Because no CRM was available for individual MeHg species, further quality assurance/quality control for the MeHg speciation analysis in the beluga temporal lobe tissue samples was performed by comparing the sum o f all the MeHg species (MeHgs) against the MeHgx concentration analyzed independently by HPLCICP-MS, as described above. The temporal lobe showed a good agreement for MeHgs / MeHgx = 75.2 ± 20.5 % (n=10) (Lemes et al., 2011). 60 The analytical method for selenium speciation monitored the following analytes: inorganic selenite Se(IV) and selenate Se(VI)), and organic selenomethionine (SeMet), methylselenocysteine (d-hSeCys), and selenocystine (CysSeSeCys). Details can be found elsewhere (Hu et al., 2009). As shown in Figure 3.2 below, some o f the speciation chromatograms showed a slight shift in the retention time. This was because analyses were done on different days with different batches o f columns and mobile phases. However, the retention times o f MeHg species were corrected on a daily basis using the standards before and after the sample analysis. For total Hg analysis o f kidney, liver, muktuk, and muscle, samples were weighed to approximately 0.15 g wet weight (ww). Samples were digested with a hydrochloric/nitric acid mixture (Aqua Regia) heated to 90 °C. The digested samples were analyzed for Hgx by Cold Vapour Atomic Absorption spectroscopy (CVAAS) (Armstrong and Uthe, 1971). The detection limit was 0.005 mg kg'1. Data analysis The concentrations o f Hgx, Sex, MeHgx and iHgiabiie were recovery-corrected based on the recovery o f DOLT-4, prior to data analysis. All brain values were converted from dw to ww concentrations based on the measured moisture for each sample. Data are reported as the median, followed by range in parentheses unless otherwise stated. All 61 statistical analyses were conducted using STATA vl2 (College Station, Texas) except for non­ linear regressions for exponential relationships that were conducted using GraphPad Prism for Mac v6.0b (La Jolla, CA). A p-value < 0.05 was selected to indicate a statistically significant result for all analyses, and all statistical tests were two-tailed. Scheffe post hoc multiple means comparison test was used to test differences in means following one-way analysis o f variance. Pearson and Spearman coefficients were used to analyze parametric and non-parametric data, respectively. Linear regressions o f ln-transformed HgT data were used to assess the relationship between cerebellar Hgr concentrations and blood, liver, kidney, muscle and muktuk Hgx concentrations. Results and Discussion Mercury concentration and distribution Total Hg concentrations in five brain regions are provided in Table 3.1. The difference in HgT between brain regions was statistically significant in the 37 whales for which we had samples available for all five brain regions (p < 0.05). Total Hg concentrations increased in the following order: Spinal cord (SC)a < Brain stem (BS)ab < Frontal lobe (FL)b < Cerebellum (C)b < Temporal lobe (TL)b (different superscripts designate brain regions that had significantly different HgT concentrations from each other). Relative Hgx concentrations in discrete brain regions normalized to Hgx in SC were: 1 : 1.6 : 1.9 : 2.3 : 2.8, respectively. 62 Total Hg concentrations in brain tissue o f beluga whales were similar to those reported in dolphins (G. griseus, S. coeruloalba and T. truncates) (Capelli et al., 2008; Meador et al., 1999), and much higher than concentrations reported for other mammals such as wild river otter (Lutra lutra) (Basu et al., 2005d), polar bear ( Ursus maritimus) (Krey et al., 2012), Arctic sledgedogs (Hansen and Danscher, 1995), wild mink (Mustela vison) (Basu et al., 2005a) and raccoon (Procyon lotor) (Porcella et al., 2004) (Table 3.2). Interspecies differences in brain H gr concentrations cannot be explained simply by trophic position. For example, polar bears are top predators in the Arctic and are known to bioaccumulate high concentrations o f Hg in their livers (Rush et al., 2008), yet the concentrations o f HgT in cerebellar cortex samples o f polar bears (n 22, age: 2 to 9 yr for 13 animals) harvested in Nunavik, northern Quebec were 0.23 ± 0.07 mg kg'1 dw (mean ± se, approx 0.06 ± 0.02 mg kg'1 ww) (Krey et al., 2012). Therefore, interspecies variation in HgT concentration in the brain may be associated with different rates o f MeHg excretion. Due to the absence o f Hg toxicity data pertaining to cetaceans, we compared HgT concentrations in beluga brain tissue to reported concentrations associated with neurotoxicity in humans, primates and fish-eating wildlife. The lethal concentration ofH gT in human brain tissue was 16.8 mg kg'1 ww in the cerebellum o f one individual (Eto et al., 1999). Dietary MeHg dosing studies on primate species indicated that Hg intoxication was associated with brain HgT concentrations between 6.0 and 12.0 mg kg"1 ww (Berlin et al., 1975a; Evans et al., 1977; Luschei et al., 1977; Stinson et al., 1989). Furthermore, concentrations below ~2 to 5 mg kg'1 ww were likely below thresholds o f overt MeHg intoxication in mink (Suzuki, 1979; Wobeser et al., 1976). In this 63 study, one whale (1 %) had cerebellar Hgx above 16.8 mg kg'1, four whales (5%) had cerebellar Hgi that exceeded 6.0 mg kg'1and 44 whales (53%) had cerebellar H gr below 2 mg kg'1. In the temporal lobe, Hgx exceeded 16.8 mg kg'1in three whales (3%), 6 mg kg'1 ww in 11 whales (14%) and was below 2 mg kg'1 in 38 whales (47%). The results from this study indicate that at least 14% of the beluga whales had Hgx concentrations in the temporal lobe exceeding concentrations associated with intoxication, but 47 to 53% had brain Hgx concentrations below thresholds of overt intoxication, assuming that the toxic threshold concentration for beluga is similar to other mammalian species. H g and age The ages o f whales were the following (mean ± se): 26 ± 8 yr in 2006 (n = 47), 33 ± 15 yr in 2008 {n = 19) and 23 ± 5 yr in 2010 (w = 15), and ranged from 0 (full-term fetus) to 60 yr. Males were predominantly sampled in all years; only three females were sampled in 2006, three females (including one pregnant female) were sampled in 2008 and no females were sampled in 2010. The concentration o f HgT was positively correlated to age in cerebellum (p < 0.05, n = 74; Figure 3.3). The lowest Hgx concentration was observed in the full term fetal cerebellum (0.05 mg kg'1ww). The median concentrations o f cerebellar Hgx were 0.77 and 3.37 mg kg'1 ww in the youngest (first quartile: 0-19 yr) and oldest (fourth quartile: 30 - 60 yr), respectively. Interestingly, the most elevated cerebellar Hgx concentrations (15.0 mg kg'1 ww and 16.9 mg kg' 1 ww) were not observed in the oldest whales, but in whales that were 47 yr and 36 yr, respectively. We are unsure about the reason for the elevated Hg in these two whales; however, these concentrations may reflect differences in feeding behaviour (Loseto et al., 2008a) and 64 therefore greater exposure to MeHg in these whales compared to their older counterparts. Elevated Hgx concentrations observed in brain tissue from beluga whales could be explained in part by accumulation o f Hg throughout their long lifespans. The developing brain is extremely sensitive to Hg exposure (Clarkson and Magos, 2006). Maternal transfer o f Hg to her fetus was investigated by collecting tissue samples from one female beluga (23 yr) and her full term male fetus. Total Hg concentrations in fetal tissues were (mg kg'1 ww, «=1): SC= 0.02, C = 0.05, FL = 0.07, TL = 0.06 and liver = 0.28. HgT in the fetal brain ranged from 3 to 14% of maternal brain Hgx, with the frontal lobe bearing the most elevated Hg for the fetus compared to the temporal lobe for the mother. Previously reported Hgx concentrations in one St. Lawrence Estuary neonate were 0.049 mg k g'1ww in brain tissue and 0.145 mg kg"1 ww in liver (Gauthier et al., 1998). Therefore, the Hgx concentrations observed in the full-term fetus from this study were similar to the concentrations observed from the neonate, although in general, adult belugas from this area have more elevated Hgx concentrations than their counterparts in the Arctic (Wagemann et al., 1990). The clinical significance o f in utero exposure on the developing beluga brain remains to be studied. H g speciation Between 34 and 44% o f Hgx in the four brain regions was soluble Hg (17 to 20% MeHgx and 18 to 28% i H g i a b i i e ) and the remaining 56 to 66% was bound to cell membranes (Table 3.3). O f the soluble fraction, 32 to 41% was organic Hg (MeHgx) and 59 to 68% was iH g b o u n d - The concentration o f MeHgx was positively correlated to concentration o f Hgx in all brain regions (p 65 < 0.05): SC (rs = 0.80,/? < 0.0001, n = 19), FL (rs = 0.77,/? = 0.0001, n = 19), C (rs = 0.68,/? = 0.0005, w = 22) and TL (rs = 0.73,/? = 0.0001, n = 22). The percent MeHgr o f Hgr decreased exponentially with increasing HgT concentration (p <0.05) in SC (R2 = 0.95; t'A —0.18 mg kg'1), FL (R2 = 0.93; t'A = 0.31 mg kg '). C (R2 = 0.96; t'A = 0.37 mg kg'1) and TL (R2 = 0.94; t'A = 0.37 mg kg'1) (Figure 3.4). The concentrations o f iHgiabiie were consistently higher than MeHgx in all brain regions, with the exception o f the full-term fetus, which had 100% MeHgx and one adult whale with the lowest brain Hgx concentration measured. The ratio o f organic mercury expressed as a percentage o f total mercury in brain samples varied greatly across species and suggests interspecies differences in in situ demethylation o f MeHg in the brain (Table 3.2). Previous studies have suggested that MeHg may be demethylated in the brains o f cetaceans (Augier et al., 1993; Cardellicchio et al., 2002; Joiris et al., 2001; Meador et al., 1999). Unlike cetaceans, the majority o f brain Hgx was composed o f MeHg in polar bears (Basu et al., 2009; Krey et al., 2012), raccoons (Porcella et al., 2004), and mink (Basu et al., 2005b). Demethylation o f MeHg followed by the formation o f compounds similar to mercury selenide (HgSe) was linked to successful detoxification o f Hg in organic Hg-exposed humans (Korbas et al., 2010). The low percentage o f MeHgx in brain tissue from beluga whales could be indicative of demethylation taking place in the four brain regions analyzed. When we compared the concentration o f MeHgx to threshold levels, we found that 100% o f the whales had MeHgx concentrations below 2 mg kg'1 in the four brain regions analyzed (n = 19 to 22). Therefore, if 66 MeHg is indeed the neurotoxic form o f Hg, biological monitoring o f beluga whales and other cetaceans must focus on the concentration o f MeHg in brain tissue to evaluate risk o f Hg exposure. Co-accumulation of Hgr and Ser The molar concentration o f Ser was significantly predicted by molar Hgx concentration in all brain regions {p < 0.001). The stoichiometric relationship o f Hg and Se co-accumulation in the BS was [Ser] = 1.0 x [Hgx] + 7.1 (r2= 0.98, n = 39), SC was [SeT] = 1.1 x [Hgx] + 5.5 (r*= 0.95, n = 77), FL was [Sex] = 0.98 x [Hgx] + 7.1 (r2 = 0.98, n = 77), C was [Ser] =1.1 x [Hgx] + 6.0 (r2 = 0.97, n = 83) and TL was [SeT] = 1.0 x [Hgx] + 7.0 (r2= 0.98, n = 81) for whales harvested in 2006, 2008 and 2010. The median and range o f molar ratios o f Hg:Se in the five brain regions were: BS = 0.48 (0.08-0.88), SC = 0.50 (0.03-0.87), FL = 0.55 (0.08 - 0.96), C = 0.60 (0.06 0.93) and TL = 0.58 (0.08-1.01) (Table 3.1). Molar concentrations o f Sex consistently exceeded Hgx in the five brain regions analyzed. The molar ratio o f Hg:Se was less than one, in 80 o f 81 whales analyzed. These consistent linear relationships between Hg and Se accumulation strongly suggest that an interaction occurs between these elements in the brains of belugas. The binding o f iHg to Se in a 1:1 ratio has been observed in the liver o f high trophic level mammals, and may partially protect organisms from MeHg-associated toxicity (Dietz et al., 2013). Selenium is an essential element in the nervous system, it is both a micronutrient and antioxidant, and adverse biological effects occur when bioavailable Se is below (deficiency) or above (toxicity) thresholds (Khan and Wang, 2009). It was suggested that the toxicity o f MeHg could be linked to its high binding affinities with Se, limiting the bioavailability o f Se for Se-dependent enzyme activity in 67 brain tissues (Watanabe et al., 1999). Our findings that the molar concentration o f Sex consistently exceeded Hgx (i.e. Hg:Se < 1:1) in different beluga brain regions suggest that this hypothesis of limited availability o f Se is not applicable. Previous studies have suggested that a bio-transformation process may occur in the brain, initiated by the demethylation o f MeHg followed by the formation o f inert HgSe granules (Nigro and Leonzio, 1996). Selenium may also reduce the toxicity o f Hg by reducing oxidative stress of Hg, forming inert compounds with Hg and forming bis(MeHg) selenide (Khan and Wang, 2010). In beluga brains, 30 to 40 % o f Hgx was MeHgx and iHgiabiie, and the remainder was an unidentified Hg moiety. An unknown peak (U l) was observed in almost all temporal lobe samples at the same retention time as a Se peak. Direct identification o f the chemical nature o f Ul was not successful due to the low concentrations involved. However, based on retention times o f known Hg and MeHg compounds, Ul cannot be the inert HgSe compound (Lemes et al., 2011); instead, it is most likely a mercuric cysteinate (Hg(SCys)2) or its selenocysteinate analogue (Hg(SeCys)2). Peaks identified as U2 are attributed to an organoseleno compound (Lemes et al., 2011). The co-accumulation o f Hg and Se and the detection o f an unidentified Hg moiety in the temporal lobe, suggests that Se may indeed play a role in the detoxification o f Hg in the brains o f beluga whales. A previous study showed that no Hg peak was detected along the Se peaks in the Se speciation method (Lemes et al., 2011). This suggests that Hg or MeHg is not present as a complex o f the identified Se species, such as SeMet, CHjSeCys, or inorganic Se (IV or VI). However, two sets 68 o f Hg and Se peaks overlapped in the MeHg speciation method (Figure 3.2), though the identities o f the compounds remain elusive. The presence of elevated Hg in the brain tissue o f beluga whales and other cetaceans may be due to the demethylation o f MeHg and co-accumulation o f Hg and Se. Co-exposure to Se and Hg has been linked to increased uptake o f MeHg in the brain (Chen et al., 1975); and the half-life o f iHg in the brain o f primates was estimated to be 230 to 540 d compared to 37 d for MeHg (Vahter et al., 1995). Therefore, although Se is likely involved in the detoxification of Hg in the brains o f belugas, dietary exposure to both Hg and Se may contribute to the elevated concentrations o f Hg detected in the beluga brains in this study. Tissue distribution of Hg The distribution o f H g in frequently sampled organs o f beluga whales could provide insight into neurotoxicological risk o f H g exposure, and contribute to biomonitoring studies. Mercury concentration in the cerebellum could be predicted by liver H g concentration ( l n ( H g cerebeiium) = 0.77 x ln(H giiver) - 1.5; r2 = 0.73; p < 0.05; n = 49), kidney H g concentration ( ln ( H g cerebeiium) = 0.88 x In(Hgkidney); r2= 0.64; p < 0.05; n = 17), muscle H g concentration (ln(Hgcerebeiium) = 1.3 x ln ( H g muscie) + 0.63; r2= 0.57;p < 0.05; n = 46) and blood H g concentration ( l n ( H g cerebeiium) = 1-7 x ln(H gbiood) -4 .7 ; r2 = 0.32;p < 0.05; n = 17). Therefore, H g r concentrations measured in frequently sampled organs could be used to predict H g x concentration in cerebellum and other brain regions. Total H g concentrations measured in blood samples from beluga whales suggest 69 that half o f the whales analyzed in 2008 had H g x concentrations exceeding the lowest effect level for H g x in blood (200 ng m g'1) from the Minamata and Iraqi outbreaks (Clarkson, 1997). 4. Conclusions A combination o f bioaccumulation and biomagnification o f MeHg and retention o f demethylated inorganic Hg may account for elevated Hgx concentrations observed in brain tissue o f beluga whales. Although demethylation and possible detoxification appear to occur in beluga whales, the effect o f Hg exposure on brain function is not known. Total Hg concentrations in some beluga whales exceeded thresholds o f toxicity reported for humans and primates; therefore, it is possible that Hg exposure in beluga whales from the eastern Beaufort Sea could be associated with neurotoxicity. Future work will involve the investigation o f neurochemical disruption and behavioural variation associated with Hg exposure in this whale population. Protecting beluga whales from Hg exposure and associated toxicity is essential to protecting ecosystem health, including the health of humans who rely on belugas for cultural and physical well-being (Sejersen, 2001; Tyrrell, 2007). 70 Inuvialurt S e ttle m e n t R egion Sachs Harbour! Amundsen Guff Beaufort Sea V i ( Hendnckson Inland ® A [East Whitefu Station J J Figure 3.1 Map of the Inuvialuit Settlement Region. Sampling sites (Hendrickson Island and East Whitefish Station) and summering habitat o f the Eastern Beaufort Sea beluga whale population (Amundsen G ulf and southern Beaufort Sea). 71 CM,HgSCys CHjHgSCy* CH,HgSCys Tim* | 150-1 oi 100- 0 X X i i * . 100- * 50- 50- 25 Total Hg (mg kg’1ww) Total Hg (mg kg’1 ww) Figure 3.4 The non-linear relationship (exponential one phase decay) between percent MeHg and Hgr concentrations. The percent MeHg decreased exponentially with increasing Hgx in the spinal cord (n = 19), frontal lobe (n = 19), cerebellum (n = 22) and temporal lobe (n = 22) in brain samples collected from belugas (fetus, juvenile and adult whales) in 2008. 74 Table 3.1 Concentrations (median and range, ww) of total Hg, Se and molar ratio o f Hg:Se in beluga whales sampled during the summer harvests in the western Canadian Arctic in 2006, 2008 and 2010. Tissue n HgT (mg kg'1 o r ng m L '1) M edian Range Sex (mg kg ‘) Range M edian M olar Ratio Hg:Se Median Range Brain stem 39 1.32 0.13-15.2 1.22 0 .5 6 -6 .7 9 0.48 0.08 - 0.88 Spinal Cord 77 1.25 0.0 2 -1 1 .1 0.98 0 .3 2 -5 .0 5 0.50 0 .0 3 -0 .8 7 Cerebellum 83 1.84 0 .0 5 -1 6 .9 1.20 0.28 - 7.20 0.60 0 .0 6 -0 .9 3 Temporal Lobe 81 2.34 0 .0 6 -2 2 .6 1.50 0 .3 0 -1 0 .4 0.58 0 .0 8 -1 .0 1 Frontal Lobe 77 1.84 0 .0 7 -2 1 .9 1.26 0 .5 1 -8 .9 8 0.55 0 .0 8 -0 .9 6 Liver 50 19.1 0 .2 8 -1 0 8 8.15 0 .8 4 -3 7 .5 0.93 0 .1 3 -2 .7 4 Kidney 23 4.90 0 .1 2 -1 0 .9 3.48 1 .1 3 -6 .6 2 0.50 0.04 - 0.95 M uktuk 24 0.35 0 .0 7 -0 .8 8 3.63 0 .6 2 -5 .9 7 0.04 0 .0 1 -0 .1 6 Muscle 57 1.10 0 .1 1 -3 .3 9 0.35 0 .1 9 -0 .8 6 1.21 0.23 - 2.79 Whole Blood 17 200 7 7 .4 -5 1 5 N/A N/A N/A N/A number of samples analyzed. Blood density is approx 1.02 mg pL' . Blood, kidney and muktuk samples were only available for 2008. Muktuk refers to blubber and outer skin layers. N/A denotes no sample available. 75 Table 3.2 The concentrations o f Hgi, and percent MeHg reported for brain tissue from different mammalian wildlife species. Approximate wet weight (ww) concentrations were calculated when necessary based on reported moisture content in brain tissue. Species Risso’s dolphin (G. griseus) Striped dolphin (S. coeruloalba) Bottlenose dolphin (T. truncates) Polar bear ( Ursus maritimus) Raccoon (Procyon lotor) Wild mink (Mustela vison) Wild river otter (Lutra lutra) Location [H gr] (mg kg'1 ww) MeHg (% ) -0 .7 1 - 3 9 .1 8 -5 1 - 0.99, 7.26 34, 90 -0 .2 1 , 12.5 61, N/A Nunavik, QC, CA - 0.06 ± 0.02 100 FL, USA 0.286 96 NS, ON and YT, CA - 0 .0 7 - 4 .9 0 88.8 ± 15.4 NS and ON, CA 0 .0 2 -3 .5 8 68 ± 3 4 .8 78 ±30.4 Northwest Mediterranean Reference (Capelli et al., 2008) (Krey et al., 2012) (Porcella et al., 2004) (Basu et al., 2005a) (Basu et al., 2005c) 76 Table 3.3 Concentrations (median, range) o f labile Hg species (MeHgx and i H g i a b i i e ) and iHg species complexed to proteins or selenium in the cerebellum, temporal lobe, frontal lobe and spinal cord o f fetal, juvenile and adult beluga whales (n = 22) sampled on Hendrickson Island in 2008. The percentages o f each Hg fraction over total Hg measured are presented as median and range. Labile Hg Species (mg kg'1 ww) Brain region N Cerebellum 22 Tem poral lobe Frontal lobe Spinal cord MeHg 0.27 (0.04-0.53 ) 12% (5 -1 0 7 % ) 0.44 (0.04-1.05 ) 22 11% (4 -1 0 9 % ) 0.34 (0.08-0.85 ) 19 12% (4 -1 0 9 % ) 0 .18(0.03-0.43 ) 19 11% (4 -1 0 8 % ) Bound Hg (mg kg'1ww) 0.56 (n d -1 .0 5 ) 1.70 (nd - 6.07) 68% (0 -8 4 % ) 20% (0 - 39%) 0.74 (n d -1 .5 9 ) 2.50 (nd - 19.9) 71% (0 -8 9 % ) 19% (0 - 27%) 0.70 (0.01 - 1.55) 1.98 (nd - 17.9) 20% (7 -4 1 % ) 66% ( 0 - 8 8 % ) 0.45 (n d -1 .0 5 ) 0.88 (nd - 5.78) 56% (0 - 85% 29% (0 - 44%) iHg 77 5. Acknowledgements This study was funded by NSERC Discovery (HMC and FW), the Fisheries Joint Management Committee (SKO), and Northern Contaminants Program (FW, GS). SKO was the recipient o f a NSERC Doctoral award, N asiw ik Doctoral award, NSTP Training Fund and UNBC travel awards. We thank M. Gillingham for guidance with statistical analyses, D. Stinson for mapping, A. Essler, A. Montgomery, S. Krause, A. Krey, G. Prkachin and A. Shaw for assistance in the laboratory, and L. Loseto, M. Noel, F. Pokiak, N. Pokiak, D. Sydney, R. Felix, K. Nuyaviak, B. Voudrach, R. Walker, K. Snow, C. Pokiak, Inuvialuit hunters, Tuktoyaktuk and Inuvik HTCs, and the DFO for their support in the field. 78 Bridge In the previous chapter, I identified that mercury (Hg) concentrations in brain tissue from beluga whales sampled from the Eastern Beaufort Sea population between 2006 and 2010 frequently exceeded concentrations previously associated with neurotoxicity and neurochemical disruption. Beluga whales in the Arctic may be at risk o f neurochemcial disruption associated with MeHg exposure given that neurochemical variation was associated with MeHg exposure in wildlife and laboratory animals (Basu et al., 2005a; Basu et al., 2005c; Basu et al., 2009; Scheuhammer et al., 2008). Therefore, in the next two chapters I use neurochemical and molecular biomarkers to assess the potential disruption of neurological signaling pathways associated with MeHg exposure in beluga whales. 79 Chapter 4. Mercury and selenium exposure is associated with molecular and neurochemical biomarkers of Arctic beluga whales (Delphinapterus leucas). Names and Affiliations o f Authors: 1. Sonja K. Ostertag Natural Resources and Environmental Studies, University of Northern British Columbia, Prince George, British Columbia, Canada, V2N 4Z9 ostertag@unbc.ca 2. Alyssa C. Shaw * Deceased 3. Niladri Basu Faculty o f Agricultural and Environmental Sciences Macdonald Campus, McGill University Ste-Anne-de-Bellevue, Quebec, Canada H9X 3 V9 Niladri.Basu@Mcgill.ca 4. Hing Man Chan Center for Advanced Research in Environmental Genomics, University of Ottawa, Ottawa, Ontario, Canada K IN 6N5 laurie.chan@uottawa.ca * A. Shaw passed away on August 29, 2011 80 Abstract Elevated concentrations o f mercury (Hg) were found in beluga whales (Delphinapterus leucas) from the eastern Beaufort Sea population but effects o f Hg on brain chemistry are not known. Brain tissue samples from the cerebellum and temporal cortex o f 35 harvested beluga whales from Hendrickson Island, Canada were collected in 2008 and 2010. Neurochemical and molecular biomarkers were measured with radioligand binding assays and quantitative Real Time polymerase-chain-reaction, respectively. Total Hg (Hgr) and selenium (Sej) concentrations were analyzed using inductively coupled plasma mass spectrometry (ICP-MS); methylmercury (MeHg) and labile inorganic Hg (iHgiabiie) were measured via high performance liquid chromatography ICP-MS. Total Hg concentration ranged from 1.7 to approx. 113 mg kg'1 dry weight (dw) in cerebellum and 2.6 —113 mg kg'1 dw in temporal cortex. Total Hg, MeHg and Sex were negatively associated with y-amminobutyric acid type A receptor (GABAa-R) binding in the cerebellum (p < 0.05). The expression o f mRNA for GABAa -R subunit a2 was negatively associated with Hgr and iHgiabiie concentration (p < 0.05). Furthermore, GABAa -R binding was positively correlated to mRNA expression for GABAa -R a2 subunit, and negatively correlated to the expression o f mRNA for GABAa -R a4 subunit (p < 0.05). Inorganic Hg was negatively associated with the expression of N-methyl-D-aspartate receptor (NMDA-R) subunit 2b mRNA expression in the cerebellum (p < 0.05). Based on these results, the GABAa -R might be more sensitive to Hg, MeHg and iHgiabiie exposure than the NMDA-R. These results suggest that variation o f molecular and/or biochemical components o f the GABAergic and glutamatergic signaling pathways were associated with MeHg exposure in beluga whales. 81 Introduction Contaminants have been monitored for decades in the eastern Beaufort Sea (EBS) beluga whale {Delphinapterus leucas) population in the western Canadian Arctic (Fisk et al., 2005). Mercury (Hg) is o f particular concern in this population o f beluga whales due to elevated concentrations observed in samples collected in the 1990s (Wagemann et al., 1998). Furthermore, total Hg (Hgi) concentrations in brain tissue of beluga whales sampled from the EBS population between 2006 and 2010 exceeded concentrations previously associated with neurotoxicity and neurochemical disruption (median Hgr concentration was 2.34 mg kg'1 wet weight (range, 0.06 to 22.6 mg kg'1 ww) in temporal lobe (n = 81)) (Ostertag et al., 2013). For example, the concentration o f HgT in brain tissue associated with lethal, acute onset MeHg poisoning was 16.8 mg kg'1 ww in the cerebellum of one adult human (Eto et al., 1999), and Hgi concentrations between 4.1 and 15.9 mg kg'1 ww in brain tissue o f captive mink (Wobeser et al., 1976) and between 6.6 and 18.0 mg kg'1 ww in primate species were associated with clinical symptoms of poisoning (e.g. visual impairment, lesions in the cerebral cortex, anorexia and incoordination) (Berlin etal., 1975a; Evans etal., 1977; Shaw etal., 1975). Mercury concentrations below ~2 to 5 mg kg'1 ww were likely below thresholds for overt clinical symptoms of MeHg toxicity in mink (Suzuki, 1979; Wobeser et al., 1976); however, Hgr concentrations ranging from 1.5 ± 0.34 to 15.4 ± 3.9 mg kg'1 dry weight (dw) in brain tissue were associated with neurochemical variation in captive mink (Basu et al., 2010; Basu et al., 2007c; Basu etal., 2006b). Methylmercury can pass the blood brain barrier and placenta to exert toxic effects on the central nervous system o f adults and fetuses (Clarkson and Magos, 2006; Magos and Clarkson, 2006). 82 Overall, the toxicity of MeHg has been linked to its reactivity with sulfhydryl groups (Chakrabarti et al., 1998). Examples o f how MeHg appears to exert its neurotoxicity include the disruption of intracellular calcium homeostasis (Anner et al., 1992; Sirois and Atchison, 2000; Yee and Choi, 1996), alteration of neurotransmission (Arakawa et al., 1991; Atchison and Hare, 1994; Narahashi et al., 1994; Vidal et al., 2007; Yuan et al., 2005) and causing oxidative stress (Yee and Choi, 1996; Young et al., 2002). Neurochemical changes are potential indicators of neurological harm because they may precede functional or structural damage o f the nervous system (Manzo et al., 2001). Previous studies have suggested that the interaction o f MeHg or inorganic Hg (iHg, Hg2+) with cysteine residues may inhibit, stimulate or damage components o f the dopaminergic (Gomes et al., 1976), cholinergic (Castoldi et al., 1996), GABAergic (Huang and Narahashi, 1997; Narahashi et al., 1994), and glutamatergic (Albrecht and Matyja, 1996) signaling pathways. In wildlife studies, MeHg exposure was associated with significant reductions in y-aminobutyric acid type A receptor (GABAa-R) binding in lab-exposed mink (Mustela vison) (Basu et al., 2010) and decreased N-methyl-D-aspartate receptor (NMDA-R) binding in several brain regions of MeHg-exposed bald eagles (Haliaeetus leucocephalus) (Rutkiewicz et al., 2011; Scheuhammer et al., 2008), mink (Basu et al., 2007c), and polar bears ( Ursus maritimus) (Basu et al., 2009). It is believed that such MeHg-associated neurochemical changes may have consequences to the whole organism as these receptors are components o f the main inhibitory and excitiatory pathways in the central nervous system, and they play important roles in animal behaviour, memory and motor function (Popescu, 2005; Reis et al., 2009; Vicini and Ortinski, 2004). 83 Arctic beluga whales may accumulate elevated concentrations of H gj in their brains due to their diet, long lifespans and the demethylation o f MeHg (Ostertag et al., 2013). Previous studies have indicated that Hgr concentrations in brain tissue from Arctic beluga whales may exceed mean concentrations observed in other Arctic biota (e.g. polar bears, seals and humans) (Dietz et al., 2013). Although 14 % o f Arctic beluga whales had Hg concentrations that exceeded 6.0 mg kg'1 ww (Ostertag et al., 2013), a concentration associated with toxicity in feeding trials (Berlin et al., 1975a; Evans et al., 1977; Luschei et al., 1977), the potential neurotoxicity o f MeHg exposure has not been explored to date in beluga whales. Previous research has shown that Hg concentrations were lower in the cerebellum than the temporal cortex o f Arctic beluga whales (Ostertag et al., 2013); however, the cerebellum is particularly sensitive to MeHg exposure and destruction of cerebellar granule cells characterizes MeHg intoxication in humans and wildlife (Basu and Head, 2010; Clarkson and Magos, 2006). Demethylation o f MeHg in Arctic beluga whales is likely, and labile iHg concentrations were consistently higher than MeHg concentrations in the temporal cortex, cerebellum, frontal cortex and spinal cord (Ostertag et al., 2013). Given that iHg cannot easily cross the blood-brain barrier, the presence o f iHg in the brain is likely due to in-situ demethylation o f MeHg (Clarkson and Magos, 2006). The brain is expected to be more sensitive to MeHg than iHg, based on brain pathology and symptoms associated with MeHg poisoning (Magos et al., 1985). Our previous findings o f co-accumulation o f Se and Hg suggested that Se may play a role in MeHg detoxification in beluga whales (Ostertag et al., 2013). Therefore, the potential neurotoxicity o f elevated Hgr requires further study in beluga whales, and should take into account Hg speciation and postential detoxification associated with Se co-accumulation. 84 The objective o f this study was to characterize the relationship between concentrations of different chemical forms o f Hg (Hgr, MeHg and iHg), total selenium (Ser), and the molar ratio o f Hg to Se, and various neurochemical and molecular biomarkers in different brain regions o f beluga whales. The overall hypothesis was that environmentally relevant Hg concentrations currently found in brain tissue o f Arctic beluga whales would be associated with neurochemical and molecular variation in components o f the GABAergic and glutamatergic signaling pathways. Methods Sample collection Harvested beluga whales were sampled on Hendrickson Island, NT, Canada in 2008 (n = 20) and 2010 (w = 15) as described previously (Ostertag et al., 2013). Prior to each sampling season, a research permit and scientific license to fish were obtained from the Aurora Research Institute and Department o f Fisheries and Oceans (DFO), respectively. The sampling program was approved and supported by the Tuktoyaktuk and Inuvik Hunters and Trappers Committees for all sampling years. Following the beluga harvest, the animal head was removed from the body by severing the joint between the skull and atlas with a knife according to the instructions given by Noel Raymond, an Inuvialuit beluga harvester (personal communication, July 1, 2006). The brain was removed from the skull using an autopsy saw (MOPEC®, Elmira, Michigan) and subsamples were collected and frozen within 3 h o f animal death. Subsamples o f cerebellum and temporal cortex were collected from harvested beluga whales in 2008 and 2010 to measure metal concentrations 85 and speciation, neurochemical biomarkers and mRNA expression. Samples (~ 0.5 - 3 g) for metals and speciation analyses were frozen at ~ -20 °C, samples for neurochemical analyses (~ 0.5-1 g) were flash-frozen and stored in liquid nitrogen, and samples (~ 0.07 g) for mRNA expression assays were flash-frozen in 2008. In 2010, samples were placed in RNALater™at approx 4 °C for 24 h prior to freezing at -20 °C. Sample numbers varied for the different assays due to subsample availability for the separate analyses. Age was estimated by counting individual growth layer groups in the dentine from a thin section o f tooth at the Freshwater Institute, Winnipeg, MB (Stewart, 2006). The concentrations o f Hgi, iHgiabiie, MeHg and SeT were determined previously for the cerebellar cortex and temporal cortex (Ostertag et al., 2013). Chemical forms of Hg were analyzed following the method developed by Krey et al. (2012) as described previously (Ostertag et al., 2013). Membrane preparation For receptor binding assays, membrane preparations were prepared by homogenizing frozen brain tissue (~ 2 g ww) in Na/K buffer (10 mL/g tissue) with a tissue tearer for 30 s using a previously described method (Basu et al., 2005c). Endogenous ligands were removed by centrifugation three times with Na/K buffer and membranes were re-suspended in buffer, aliquoted, flash frozen in liquid nitrogen and stored at -80 °C. Protein concentration was determined with the Bradford assay and bovine serum albumin was used as the standard. 86 Receptor binding assays Receptor binding assays were adapted from previous studies by Basu et al. (Basu et al., 2010; Basu et al., 2007c; Basu et al., 2009). In brief, 30 pg o f membrane preparation was re-suspended in buffer and added to a microplate containing a 1.0 mM GF/B glass filter (Millipore, Boston, MA, USA). Membrane protein was suspended in 100 pL Tris buffer (pH 7.4; NMDA: buffer contained 100 pM glycine and glutamate) and incubated for 30 min on ice with [3H]flunitrazepam ([3H]-FNP; 0.5 nM) or 120 min at room temp with [3H]-MK-801 (16 nM), respectively for GABA and NMDA. All incubation steps were carried out with gentle shaking and binding reactions were ended by vacuum filtration. The filters were rinsed three times with buffer and were then soaked for 72 h in 25 pL OptiPhase Supermix Cocktail (PerkinElmer). Radioactivity retained by the filters was quantified in a microplate detector (Wallac Microbeta, PerkinElmer) and counting efficiency was approx 40%. Specific binding was calculated as the difference between radioligand binding in the presence and absence o f inhibitor: 20 pM clonazepam for GABA a-R, and 100 pM MK-801 for NMDA-R. Receptor binding is reported as fmol of radioisotope bound per mg of membrane protein (fmol m g'1). Expression of mRNA Total RNA was extracted from approx. 80 mg samples using 1 mL Trizol using the Qiagen RNeasy™ Lipid Tissue kit. Total RNA was treated with Ambion™ DNase | buffer (6 pL), rDNAse | (1 pL) and DNase Inactivation reagent (6 pL), prior to quantification o f RNA-40 using a spectrophotometer (Nanodrop, ND-1000). Taqman reverse transcription reagents (Applied Biosystems) were used for the generation o f complementary DNA (cDNA) for all samples. A 87 master mix made up o f 10 pL 10 X Taqman Reverse Transcriptase buffer, 22 pL M gCh, 20 pL random hexamers (50 pM), 2 pL RNase inhibitors, 2.5 pL reverse transcriptase was made that was sufficient for all samples for one brain region (each sample: 1 pg RNA, total volume o f 100 pL). Concurrently, the identical reaction was performed without reverse transcriptase, to ensure the absence o f genomic DNA (No Reverse Transcriptase (NRT) control). The following thermocycler parameters were used for the generation o f cDNA archive: 25 °C for 10 min, 37 °C for 60 min, and 95 °C for 5 min (DYAD™, DNA Engine). Primer pairs were designed within conserved nucleotide regions of the genes o f interest based on the alignment o f genes from multiple species (human, cow, goat, pig, primate (chimpanzee and macaque), dog, cat and sheep) using the National Centre for Biotechnology Information (NCBI) website. These primers were used in polymerase chain reaction (PCR) reactions on cDNA from beluga cerebellum (n = 2) to develop species-specific primers and probes. The PCR products were direct-sequenced at UBC Okanagan (Fragment Analysis and DNA Sequencing Services, Kelowna, CA), which were then used to design species-specific primers. Chromatograms were edited and the retrieved sequences were run through the NCBI website (Standard Nucleotide BLAST) to ensure they matched the conserved sequences o f genes. The sequence obtained for NMDA-2c did not match the conserved sequence; therefore, the data for this target gene are not presented in this study. Species-specific primers and fluorogenic probes (IDT, Coralville, Iowa) were designed using Genscript RT-PCR primer design (Table 4.1). 88 All PCR runs were performed under identical conditions using the 7300 Real-Time PCR System (Applied Biosystems). Real time assays were performed in 96-well optical plates in duplicate. Simplex assays were run with iTaq™ Supermix with ROX kit (Biorad). PCR mastermix was prepared and each 25 pL reaction contained 12.5 pL iTaq mix, 500 nM of appropriate forward and reverse primers, 250 nM probes and 2.5 pL template for cerebellar cortex and 5.0 pL template for temporal cortex samples. The thermocycle program included an enzyme activation step at 95 °C (10 min) and 40 cycles o f 95 °C (15 sec) and 60 °C (1 min). Standard curves were generated for all genes from serial dilutions o f cDNA to calculate efficiencies for target and reference genes. The mean C t value for the three lowest Hg-exposed animals was used as the control. Pooled sample was included in triplicate for each plate to monitor inter-plate variability of s9 expression (reference gene). No-RT samples were included in each plate to ensure the absence of genomic DNA. The difference in thermal cycles for the control and sample were calculated for each target gene and reference (s9). Fold changes for each sample and target gene were calculated relative to the reference gene s9 (Pfaffl, 2001). RNA purity and quality was evaluated using a NanoDrop (ND-1000, NanoDrop Technologies, USA). The optical density (OD) ratio o f 260 nm/280 nm wavelengths was used as an indicator o f RNA quality, with ratios greater than 1.8 indicating good RNA quality (Fleige and Pfaffl 2006). RNA integrity was evaluated using Experion (Bio-Rad Laboratories, USA). The ratio o f 28S:18S and RNA Quality Indicator (RQI) value were used to evaluate degradation, with a 28S:18S ratio o f 2.0 (Fleige and Pfaffl, 2006) or RQI o f 10 indicating perfect integrity (Taylor et al., 2009). 89 Data Analysis Mercury concentrations were log-transformed to meet assumptions o f normality and homogeneity o f variance. Fold-change ratios and receptor densities were log-transformed when necessary to meet assumptions o f normal distribution and homogeneity o f variance. Nonparametric tests were used when necessary if transformations were unable to improve the fit o f data. The relationship between neurochemistry and the concentration of Hgx, Hg species and Se was explored using Pearson correlation coefficients followed by multiple linear regression analysis. A backwards stepwise approach was used to evaluate the statistical significance o f age, Hg (Hgr, iHgiabiie, MeHg, Sex, and Hg:Se) and sampling year on neurochemical or molecular biomarker. We removed influential outliers after examination o f studentized residuals, leverage and Cook’s D influence. Pearson correlation coefficients were calculated for the expression o f target genes and corresponding receptor binding levels. Correlations (Pearson and Spearman), Fvalues, Wilcoxon rank-sum test, and t-tests were considered to be statistically significant \ i p < 0.05. The sample size for females was <10 and could reduce our ability to detect a difference in biomarkers associated with gender. Data in tables and graphs are displayed in the original scale of measurement. Results The harvested whales ranged in estimated age from 16 to 60 yr, and the median age was 27 yr. Total Hg concentration ranged from 1.7 to ~ 113 mg kg'1 dw in cerebellum and 2.58 - 113 mg kg'1 dw in temporal cortex and were correlated between brain regions (r = 0.9, n = 28). Twenty whales were sampled in 2008 (16 male, 4 female) and 15 whales were sampled in 2010 (15 90 males, 0 females). Total Hg, MeHg and Se concentrations were higher in the temporal cortex than cerebellum, but the concentration o f iHgiabiie and molar ratio o f Hg to Se did not vary between brain regions. Age was correlated to Hgr and Ser in the cerebellum and temporal cortex, iHgiabiie and Hgr to Ser stoichiometric ratio in the temporal cortex but not cerebellum. The concentrations of iHgiablie and MeHg represented 38 % (11 —89 %) and 36 % (11 -104 %) of total Hg in cerebellum and temporal cortex, respectively. The remaining Hg was not identified or quantified in this study because it was not soluble in the extraction solution used for speciation analysis (Ostertag et al., 2013). In the cerebellum, non-specific binding represented 35% and 45% o f total binding for GABAa -R and NMDA-R, respectively. In the temporal cortex, non-specific binding represented 11% and 34% o f total binding for GABAa-R and NMDA-R, respectively. Inter-plate variability ranged from 11 to 15% for NMDA-R and GABAa -R binding assays. The optical density ratio was > 1.8 for all RNA samples indicating acceptable RNA purity. The ratio o f 28S:18S was < 2 and RNA quality index (RQI) was < 10 for a subset o f samples analyzed via Experion (BioRad). The median and range of28S:18S and RQI were 0.83 (0.3-1.87) and 6.9 (3.7-8.9), respectively fora subset o f samples (n = 12), which indicated acceptable RNA quality. The Ct values for the internal control gene (s9), did not vary with age or Hg concentration in the cerebellum or temporal cortex, therefore it was considered a suitable internal control for data analysis. There was no amplification of NRT control following RT PCR. 91 GABAergic signaling pathway Receptor binding was higher in the temporal cortex (median, range: 177,137 - 291 fmol m g'1 protein) than cerebellum (median, range: 37, 11 - 113 fmol m g'1 protein for GABAa-R ( z = -4.3, p < 0.0001). Total Hg and iHgiabiie concentrations were negatively correlated to GABAa -R binding in the cerebellum (Figure 4.1 A; r = -0.49,/? < 0.001), but not temporal cortex (Figure 4 .IB; r = -0.51,/? < 0.01)). Gender was not associated with differences in GABAa receptor binding in either cerebellum or temporal cortex, and age was not correlated to GABAa receptor binding in either brain region (data not shown). Receptor binding levels for GABAa were significantly higher in samples collected in 2010 than 2008 (t = -3.89, DF = 29,/? < 0.001) for cerebellum samples but not temporal cortex samples (t = -0.7306, DF = 22, p > 0.05). The results from three backward stepwise multiple regressions that included Hgr, MeHg or iHgiabiie, in combination with animal age and sampling year, for both brain regions, indicated that the following models significantly (p < 0.05) predicted log-transformed GABAa receptor binding levels in the cerebellum (Table 4.2): 1.8 + 0.17(year) -0.21(log(Hg)), 1.3 + 0.33(year) 0.25(log(MeHg)) + 0.008(age), and 1.6 + 0.19(year)* -0.25(log(iHg)). O f the Hg species tested as predictor variables, only Hg and MeHg were found to be significant (Table 4.2). The models tested did not significantly predict GABAa -R binding levels for the temporal cortex (Table 4.2). In the cerebellum and temporal cortex, H g r was negatively correlated to the expression of GABAa -R a 2 mRNA (Figure 4.2A: cerebellum: r = -0.48, p < 0.01, temporal cortex: r = -0.56,/? < 0.01). Methylmercury (r= -0.44,/? < 0.05) and i H g i a b i i e (r = -0.43,/? < 0.05) concentrations were also correlated to GABAa -R a2 mRNA expression in the temporal cortex (Figures 4.2B 92 and 4.2C), but not cerebellum. Gender was not associated with differences in mRNA expression for the target genes analyzed. The expression o f mRNA for GABAa cl4 was positively correlated to age in the cerebellum (r = 0.45,/? < 0.05), but age was negatively associated with GABAa a2 in temporal cortex (r = -0.38,/? < 0.05). There were differences in mRNA expression between sampling years for GABAa oc2 (cerebellum: z = -4.572, p < 0.0001; and temporal cortex: t = 3.91, DF = 28, p < 0.001) and GABAa a4 (cerebellum: t = 5.14, DF = 26, p < 0.0001; temporal cortex: z = -2.75, p < 0.01). The results from three backward stepwise multiple regressions that included Hgi, MeHg or iHgiabiie>in combination with animal age and sampling year, for both brain regions, indicated that the following models significantly (/? < 0.05) predicted logtransformed GABAa a2 mRNA expression (Table 4.2) in the cerebellum: -300 + 0.15(year) 0.15(log(Hg)), -326 + 0.16(year) - 0.13(log(MeHg)) and -340 + 0.17(year) - 0.16(log(iHg)), and in the temporal cortex: -283 + 0.14(year) - 0.10(log(Hg)), -315 + 0.16(year) - 0.26(log(MeHg)), and -304 + 0.15(year) - 0.09(log(iHg)). O f the Hg species tested as predictor variables, only Hgx was a significant predictor for GABAa a.2 mRNA expression in the cerebellum, and MeHg was a significant predictor of GABAa a2 mRNA expression in the temporal cortex (Table 4.2). However, iHgiabiie was not a significant predictor o f GABAa a.2 mRNA expression (p < 0.1) (Table 4.2). Only sampling year was a significant predictor o f GABAa a4 mRNA expression in both brain regions (data not shown). Selenium (r = -0.49,/? < 0.01) and the stoichiometric ratio o f Hg to Se (r = -0.40,/? < 0.05) were correlated to GABAa-R binding in the cerebellum (Figures 4.1C and 4 .ID), but not temporal cortex. The results from two backward stepwise multiple regressions that included Ser or the 93 stoichiometric ratio o f Hg to Se, in combination with animal age and sampling year, for both brain regions, indicated that the following models significantly (p < 0.05) predicted GABAa-R binding levels in the cerebellum (Table 4.2): 2.0 + 0.20(year) - 0.49(log(Se)) + 0.0067(age), and 1.4 + 0.23(year) - 0.39(log(HgSe)). The stoichiometric ratio o f Hg to Se was correlated to GABAa-R a2 mRNA expression in the temporal cortex but not cerebellum (Figure 4.2D; r = 0.43,/? < 0.05). Total Se concentration was also correlated to mRNA expression for GABAa-R a l in both brain regions (Figure 4.2E; cerebellum: r = -0.57, p < 0.01; temporal cortex: r = -0.59, p < 0.001), and GABAa -R a4 mRNA expression (Figure 4.2F; r = -0.49, p < 0.01) in the temporal cortex. The results from two backward stepwise multiple regressions that included Sex or the stoichiometric ratio of Hg to Se, in combination with animal age and sampling year, for both brain regions, indicated that the following models significantly (p < 0.05) predicted logtransformed GABAa-R ol2 mRNA expression (Table 4.2) in the cerebellum: -334 + 0.17(year) 0.11 (log(HgSe)) and -290 + 0.14(year) - 0.23(log(Se)); and, in the temporal cortex: -319 + .16(year) - 0.16(log(HgSe)) and -264 + 0.13(year) - 0.18(log(Se)). However, o f the seleniumrelated predictor variables tested, only the concentration o f Se in the cerebellum was a significant predictor o f log-transformed GABAa -R a 4 mRNA expression. Inconsistent relationships between mRNA expression for target genes and receptor binding or enzyme activity were observed. A significant positive correlation between GABAa -R a2 mRNA expression and GABAa receptor density was observed in the cerebellum (3A; r = 0.39, p < 0.05). A negative correlation was found between GABAa -R a4 mRNA expression and GABAa -R density in the cerebellum (Figure 4.3B; r = -0.38,/? < 0.1). Receptor binding and mRNA 94 expression were not correlated in the temporal cortex for either the target gene, nor the receptor analyzed (data not shown). Glutamatergic Signaling Pathway Binding levels were higher in the temporal cortex than cerebellum for NMDA-R (z = -3.5, p < 0.001). Total Hg was negatively correlated to NMDA-R binding in the temporal cortex (r = 0.42, p < 0.05) but not cerebellum (Figure 4.4A); however, MeHg and iHg were not correlated to NMDA-R binding. Gender was not associated with differences in NMDA-R binding in either cerebellum or temporal cortex. Age was not significantly correlated to NMDA-R binding in either brain region. Sampling year was associated with statistically significant differences in NMDA-R binding levels in the temporal cortex (t = -2.36,p = 0.03), but not cerebellum (t = 0.69, DF = 29, p = 0.50). The results from three backward stepwise multiple regressions that included Hgx, MeHg or iHgiabiie, in combination with animal age and sampling year, for both brain regions, indicated that only the following models tested for the temporal cortex (Table 4.3) were significant predictors o f NMDA-R binding levels: -55 + 0.029(year) - 0.1 l(log(Hg)), -110 + 0.055(year) -0.12(log(MeHg)) and -63 + 0.033(year) - 0.15(log(iHg)). However, the HgT, MeHg and iHgiabiie were not significant predictors o f log-transformed NMDA-R binding levels in the temporal cortex. The expression o f NMDA-R 2b was not correlated to Hg, MeHg or i H g i a b i i e in either brain region (data not shown). Gender was not associated with differences in mRNA expression for NMDA-R 2b. The expression o f mRNA for NMDA-R 2b was positively correlated to age in the cerebellum 95 (r = 0.37, p = 0.053) but not temporal cortex. There were statistically significant differences in mRNA expression and sampling year for NMDA-R 2b for the cerebellum (t = 5.99, DF = 28, p < 0.0001) but not temporal cortex. The results from three backward stepwise multiple regressions that included Hgx, MeHg or iHgiabiie, in combination with animal age and sampling year, for both brain regions, indicated that only the following models tested for the cerebellum (Table 4.3) were significant predictors of mRNA expression for NMDA-R subunit 2b: 352 - 0.17(year) 0.16(log(Hg)), 319-0.16(year)-0.13(log(M eH g))and347 -0.17(year) -0.27(log(iHg)). O f the H g species tested as predictor variables, only i H g i a b i i e was a significant predictor o f NDMA-R 2b mRNA expression in the cerebellum (Table 4.3). Furthermore, the expression o f mRNA for NMDA-R 2b and NMDA-R binding levels were not correlated in the temporal cortex or cerebellum (data not shown). Selenium concentration was correlated to NMDA-R binding in the temporal cortex but not cerebellum (Figure 4.4B, r = -0.43, p < 0.05). The molar ratio of Hg to Se was not correlated to NMDA-R binding in either brain region (data not shown). The results from two backward stepwise multiple regressions that included Sej or the stoichiometric ratio o f Hg to Se, in combination with animal age and sampling year, for both brain regions, indicated that the following models significantly ip < 0.05) predicted log-transformed NMDA-R binding levels in the temporal cortex (Table 4.3): -63 + 0.039(year) - 0.28(log(HgSe)) and -56 + 0.029(year) 0.15(log(Se)). However, the stoichiometric ratios o f Hg to Se, and the concentrations o f Ser were not significant predictors of NMDA-R binding levels in either brain region. Selenium concentration and the molar ratio o f Hg to Se were not correlated to NMDA-R subunit 2b mRNA 96 expression either brain region (data not shown). The results from two backward stepwise multiple regressions that included Sex or the stoichiometric ratio o f Hg to Se, in combination with animal age and sampling year, for both brain regions, indicated that the following models significantly (p < 0.05) predicted log-transformed NMDA-R 2b mRNA expression in the cerebellum (Table 4.3): 325 -0.16(year) - 0.35(log(HgSe)) and 360 - 0.16(year) - 0.30(log(Se)) + 0.003(age). However, o f the selenium-related predictor variables tested, only Sex was a significant predictor o f NMDA-R 2b mRNA expression in the cerebellum. 97 Table 4.1. Sequences o f primers and probes used for real time PCR. T arget gene Prim er sequence Fw NMDA-R ACAAGCGCTACTTCAGGGAC subunit 2b aa NMDA-2c ccttctacaggcacctactga Probe Rvs TGCGGCGAGGTCTCCTT tgcgggacttctacctggaccagttc ggtacccaccagggctgaa cctgggagggccgggacttctc cgcatagctgccaaatttc cgaatccaggatgatgggactctgct atg GABA a-R tgtccaatgcacttggaggat subunit a2 GABA a-R a tgtcccatgagattggtggat subunit a 4 S9 catctcactcttcggatag catgcatgccctttgaaatttgggag gcata gctgctgacgctggatgag cgcagcagggcattgc aagacccgcggcgtctgtttgaa 98 Table 4.2. Summary of backwards stepwise linear multiple regression analysis for the cerebellum and temporal cortex with GABAa receptor binding to [3HJ-FNP, and mRNA expression (fold change) for GABAa a2 and a4 as the three outcome variables tested. The predictor variables tested included total mercury (Hgj), methylmercury (MeHg), labile inorganic mercury ( i H g i a b i i e ) , total selenium (Sex), or the molar ratio of H g j to Ser, and sampling year, and animal age. Adjusted R squared values and F-values are provided for the models as indicated._______________ _____________________________________________ Cerebellum Temporal Cortex Biomarker Adjusted R2 Intercept 0.4 1.8 0.17(year)'-0.21(log(Hg))* F 2,24 = 0.4 1.3 0.33(year)* - 0.25(log(MeHg))* + 0.008(age) F s.is = w 2Cl < 1*2,24 = 0.19(year)* -0.25(log(iHg)) 0.3 1.4 0.23(year)* - 0.39(log(HgSe)) 0.5 2.0 0.20(year)* - 0.49(log(Se»* + 0.0067(age) F 3.19 = 0.8 -300 0.15 (year)* - 0.15(log(Hg))* F 2,24 = 0.8 -326 0.16(year)* - 0.13(log(MeHg)) < F2.24 = 3.3 -0.001 (year) 0.0.5(log_Hg) F 2 .2 , = -21 0.01(year)0.04(log_MeHg) F 2.21 = -6.9 0.004(year) — (0.05(logJHg)) F 2,21 = -0.002(year) 0.05(log_HgSe) F2.20 -0.009(year) 0.1 l(log(Se)) 0.14(year)* 0.10(log(Hg)) 0.16(year)* 0.26(log(MeHg))* 0.15(year)* — 0.09(log(iHg)) 0.16(year)* — 0.16(log(HgSe)) 0.13(year)* 0.18(log(Se)) F2,21 = 0.2 0.2 0.08 7.2 0.07 21 7.3* 0.8 -283 50* ij o 0.3 0.8 -315 * 8 F-value 7.2* N Ot1 < < 03 < Slope 7.6* II E Intercept 6.6* 1.6 03 Adjusted R2 8.9* 0.3 < o F-value U rn ^ < Slope 0.8 -340 0 .17(year)* - 0 .16(log(iHg))t F 2,25 = 0.8 -334 0.17(year)* - 0.1 l(log(HgSe)) F 2,26 = 0.8 -304 0.7 -319 44* 37.1* 0.8 -290 0 .14(year)* - 0.23(log(Se))* F 2,24 = 54* 0.8 -264 0.62 0.34 0.45 0.07 1.05 F 2,24 = 19.8* F 2,25 = 24.2* F2,25 = 19.8* F 2,25 = 19.6* F2.25 = 21.8* *p<0.05 ‘ < 0.10 99 Table 4.3. Summary o f backwards stepwise linear multiple regression analysis for the cerebellum and temporal cortex with NMDA receptor binding to [3H]-801, and mRNA expression (fold change) for NMDA subunit 2b as the three outcome variables tested. The predictor variables tested included total mercury (Hgy), methylmercury (MeHg), labile inorganic mercury ( i H g i a b i i e ) , total selenium (SeT), or the molar ratio of H g x to Sej, and sampling year, and animal age. Adjusted R squared values and F-values are provided for the models indicated._________________ ________ ____________________________ ______ _ Temporal Cortex Cerebellum Biomarker u 2 a s 06 < Adjusted R2 Intercept 0.2 2.9 Adjusted R2 Intercept Slope F-value 0.07(year) + 0.03(log(Hg)) 0.002(age) 1*3,19 = 0.71 0.6 -55 0.029(year) 0.1 KlogfHg))' F2 ,19 = 5.7* 0.1 2.9 0.06(year) + 0.09(log(MeHg)) 0.002(age) 1*3,19= 0.83 0.5 -110 0.055(year)* 0.12(log(MeHg)) F2 J 9 = 4.1* 0.2 2.9 0.08(year) + 0.07(log(iHg)) 0.002(age) t*3,I9 = 0.74 0.5 -63 0.033(year) O.lSOogOHg))' F2 J 9 = 5.6* 0.06(year) - 0.003(log(HgSe)) 0.002(age) F3,19 = 0.66 0.5 -76 0.039(year) O^OogCHgSe))' F2.19 = 5.5* 1*3,19 = 0.77 0.5 -56 1*2,24 = 26.1* 0.1 -28 F2,I9 = 5.3* F2.26 = 0.54 -48 0.029(year) O.ISOogCSe))' 0.01(year)0.02(log(Hg)) 0.02(year) + 0.2(log(MeHg)) 0.01 (year)0.05(log(iHg)) 0.02(year) 0.05(log(HgSe)) 0.02(year) 0.008(log(Se)) 0.2 2.9 2.8 0.8 352 0.08(year) + 0.07(log(Se)) 0.002(age) -0.17(year)* -0.16(log(Hg)) 0.8 319 -0.16(year)* -0.13(log(M eHg)) TJ L* * . * ii 0.1 0.8 347 -0.17(year)* - 0.27(log(iHg))* 1*2,24 _ 28.1* 0.1 -29 0.8 325 -0.16(year)* - 0.35(log(HgSe)) 1*2,24 24.8* 0.05 -39 0.8 360 -0.16(year) - 0.30(log(Se))* + 0.003(age) 1*3,20= 15.8* 0.1 -44 _ 0.2 so N Z < F-value Slope s .a z F2,27 0.85 F2,27 = 1.1 F2.27 = 0.95 F2,27 = 0.84 *p < 0.05 ‘ < 0.10 100 120 i so u a r = -0.49 p = 0.005 n = 31 100 O 80 s s i Q. Z b< O 60 O P O % 40 - O O °S>0o 20 3 8o ----- ,----- 0 20 40 60 100 80 120 Hg concentration (mg kg'1dw) B 120 - r = - 0.51 p = 0.009 n = 25 s B o u a bfi g i ■o s os ■C 100 80 60 40 - O °o° O 9) © CL zbu o°o 20 - 0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 Labile inorganic mercury concentration (mg kg'1dw) 7.0 8.0 120 r = -0.49 p = 0.005 n = 31 a 2o 100 u. a BO s 0 80 1■o 60 - S o 40 - B • fi a. zu< 20 Sc O O o ° (X 8 °c&Sb o O o --j-------------- ,-------------- ,-------------- ,-------------- 1--- 20 40 60 80 100 120 140 Selenium concentration (mg kg'1 dw) r = -0.40 p = 0.02 n = 31 a ioo 0.2 0.4 0.6 0.8 Stoichiometric ratio of m ercury to selenium (Hg:Se) Figure 4.1. Correlations between GABAa receptor binding and mercury concentration (A), labile inorganic mercury concentration (B), selenium concentration (C), and stoichiometric ratio o f mercury to selenium (D) in the cerebellar cortex of beluga whales (Delphinapterus leucas). 102 1.8 cerebellum (o ] r = -0.48 p = 0.007 n = 30 1.6 1A £ o.'jr £ M 1.2 H J3 1 tc u S 'O nS 08 jp 0.6 °o . 0<* temporal ctx ( ♦ ) r = -0.56 p = 0.002 n = 29 A 8» 0.4 0.2 100 120 Total m ercury concentration (mg kg-1 dw) 1.8 r = -0.41 p = 0.04 n = 25 1.6 ♦ ♦ 1.4 1.2 g2 0.8 N <2 8 w 0.6 ♦♦ ♦ 0.4 0.2 0.0 2.0 4.0 6.0 8.0 Labile inorganic m ercury concentration (mg kg'1 dw) 10.0 1.8 - 1.6 - « r = -0.44 p = 0.01 n = 30 1.4 - O.'TJ' H m of u 8 *8 1.2 - 0.8 - 8» 0.6 - ^ ♦♦ 0.4 0.2 - 0.0 1.0 3.0 4.0 5.0 2.0 M ethylmercury concentration (mg kg’1 dw) 6.0 1.8 - r = -0.43 p = 0.02 n = 30 1.6 - 1.4 I £ t I s OB ‘gI 2? i-z - 08 ■ 0.6 - 0.4 0.2 - 0.0 0.4 0.6 0.8 Stoichiometric ratio of m ercury to selenium (Hg:Se) 0.2 1.0 104 2 i cerebellum (o ) temporal ctx ( ♦ ) r = -0.57 r = -0.59 p = 0.001 p = 0.0006 n = 30 n = 30 1.8 c © 1.6 © ua . 1.4 -| ♦o § 1.2 ° qP '55 S' © I “ E2 N£ a» i < o o 1 0.8 H ♦ 0.6 0.4 * ° ? n

O o 0.6 0.4 o (P o oo 0.2 --f-20 40 60 80 100 120 [3H] FNP bound (ftnol mg'1protein) 20 i B 18 e o ‘5 5) V © u g-'sr S iafi!<■> S2 r = -0.38 p = 0.058 n = 25 16 i 14 12 10 8 O O O 6 -I CQ 3 O O O O 4 2 % o 1.8 for all RNA samples; therefore, RNA purity was considered acceptable. The ratio o f 28S:18S was < 2 and the RQI was < 10 for a subset o f samples analyzed via Experion (BioRad). The median and range o f 28S: 18S and RQI were 0.83 (0.3-1.87) and 6.9 (3.7-8.9), respectively for a subset of samples (n = 12), which indicated acceptable RNA quality. The Ct values for the internal control gene (s9) did not vary with age or Hg concentration in the cerebellum or temporal cortex. There was no amplification o f NRT control following RT PCR. Cholinergic signaling pathway Receptor binding levels were greater in the temporal cortex than cerebellum for mAChR (z = 4.1, p < 0.0001). Non-specific binding represented 60% and 15% o f total binding in the cerebellar and temporal cortex, respectively. Inter-plate variability ranged from 21-23% for mAChR assays. Muscarinic AChR binding to [3H]-QNB was not correlated to Hgr, MeHg or iHg concentration in either brain region (data not shown). Furthermore, gender was not associated with differences in mAChR binding in either cerebellum or temporal cortex (data not shown). However, age was negatively correlated with mAChR binding to [3H]-QNB in temporal cortex (Figure 5.1, r = -0.58,p < 0.05), but not cerebellum. The results from three backward 125 stepwise multiple regressions that included H gj, MeHg or iHgiabiie, in combination with animal age and sampling year, for both brain regions, indicated that mAChR binding was not significantly predicted by the models tested (Table 5.3). The expression o f mRNA for mAChR ml was not correlated to concentrations o f Hgx, MeHg, or iHgiabiie- Furthermore, age was not correlated to mRNA expression for mAChR m l, and there were no significant differences in mRNA expression for mAChR ml with sampling year or animal gender. The results from three backward stepwise multiple regressions that included H gj, MeHg or iHgiabiie, in combination with animal age and sampling year, for both brain regions, indicated that the following models were significant (p < 0.05) predictors o f log-transformed mRNA expression in the cerebellum (Table 5.3; data not available for temporal cortex): 230 0.1 (year) -0.7(log(Hg)) + 0.01 (age), 120 - 0.06(year) - 0.6(log(MeHg)) + 0.01 (age), and 204 0.2(year) -0.8(log(iHg)) + 0.04(age). However, the expression o f mRNA for mAChR m l was not correlated to mAChR binding to [3H)-QNB in the cerebellum (data for temporal cortex unavailable). Selenium concentration and the molar ratio o f Hg to Se were not correlated to mAChR binding (data not shown). However, the results from two backward stepwise multiple regressions that included Sej or the molar ratio o f Hg to Se, in combination with animal age and sampling year, for both brain regions, indicated that the following models significantly (p < 0.05) predicted logtransformed mAChR binding in the temporal cortex (Table 5.3): -140 + 0.07(year) + 0.3(log(HgSe)) - 0.004(age), and -110 + 0.06(year) - 0.06(log(Se)) - 0.003(age). However, only 126 the molar ratio o f Hg to Se, animal age and year were significant predictors o f mAChR binding in the temporal cortex. At a molecular level, the expression o f mRNA for mAChR m l was not correlated to the molar ratio of Hg to Se or to Sex concentration (data not shown). Yet, the results from two backward stepwise multiple regressions that included Ser or the molar ratio o f Hg to Se, in combination with animal age and sampling year, for both brain regions, indicated that the following models significantly (p < 0.05) predicted log-transformed mRNA expression mAChR ml in the cerebellum (Table 5.3): 207 - 0.1 (year) - 1.2(log(HgSe)) + 0.01 (age). The molar ratio of Hg to Se was the only significant predictor (p < 0.05) o f log-transformed mAChR mRNA expression in the cerebellum. Dopaminergic signaling pathway Total MAO (z = -2.5, p = 0.01) activity was greater in temporal cortex (median, range; 352 nM pg'1 min'1, 227 - 592 nM pg'1 min'1) than cerebellum (median, range; 161 nM pg'1 m in'1, 67 854 nM pg'1 min'1). Total MAO activity was not correlated to H g x , iHgiabiie or M e H g in either brain region. Gender was not associated with differences in total MAO activity in either cerebellum or temporal cortex. However, age was positively correlated to total MAO activity in the temporal cortex but not cerebellum (Figure 5.2; r = 0.50, p < 0.05). Sampling year was associated with statistically significant differences in total MAO activities in the cerebellum (t = -3.91, DF = 28, p < 0.001), but not temporal cortex (t = 0.99, DF = 23, p < 0.35). The results from three backward stepwise multiple regressions that included Hgx, MeHg or iHgiabiie, in combination with animal age and sampling year, for both brain regions, indicated that the following models significantly (p < 0.05) predicted log-transformed total MAO activity in 127 the cerebellum: -460 + 0.2(year) + 0.3(log(Hg)) + 0.01 (age), -434 + 0.2(year) + 0.1(log(MeHg)) + 0.01 (age), and -395 + 0.2(year) + 0.4(log(iHg)) + 0.01 (age); and, in the temporal cortex: 2.5 + 0.007(age) - 0.1 (log(Hg)), 2.5 + 0.005(age) -0.3(log(MeHg)), and 2.4 + 0.007(age) 0.2(log(iHg)). In the temporal cortex, only animal age, Hgj, MeHg and iHgiabiie in the temporal cortex were significant predictors o f log transformed MAO activity (Table 5.4). In the cerebellum, only sampling year was a significant predictor o f MAO activity (Table 5.4). Total Hg, MeHg and iHg were not correlated to the expression o f mRNA for MAO-A in either brain region analyzed (data not shown). Gender was not associated with differences in mRNA expression for the target genes analyzed (data not shown). The results from three backward stepwise multiple regressions that included H gj, MeHg or iHgiabiie, in combination with animal age and sampling year, for both brain regions, indicated that none o f the models that we tested predicted log-transformed mRNA expression for MAO-A (Table 5.4). Furthermore, the expression o f MAO-A mRNA was not correlated to MAO-A activity in the cerebellum or temporal cortex. Monoamine oxidase activity was not correlated to molar Hg to Se ratio or Se concentration in either brain region (data not shown). In contrast, Ser concentration was negatively correlated to mRNA expression for MAO-A in the cerebellum, but not temporal cortex (Figure 5.3; r = -0.36, p < 0.05). The results from two backward stepwise multiple regressions that included Sex or the molar ratio o f Hg to Se, in combination with animal age and sampling year, for both brain regions, indicated that the following models significantly (p < 0.05) predicted log-transformed 128 MAO-T activity in the cerebellum (Table 5.4): -452 + 0.2(year) + 0.2(log(HgSe)) + 0.01 (age), 491 + 0.3(year) + 0.3(log(Se)) + 0.01(log(Se)); and, in the temporal cortex (Table 5.4): 2.2 + 0.007(age) -0.4(log(HgSe)) and 2.5 + 0.006(age) -0.1(log(Se)). However, o f the selenium-related predictor variables, only the Hg to Se molar ratio was a significant predictor o f MAO-T activity in the temporal cortex. Furthermore, multiple linear regression models that we tested did not significantly predict mRNA expression MAO-A (Table 5.4). 129 Table 5.1. Sequences o f primers and probes used for real time PCR. T arget gene Prim er sequence Fw MAO-A GGCCAGGAACGGAAGTTTGT Probe Rvs CCCCGAGGAGGTGCATTA TGGATCTGGTCAAGT A AGCG AGCGG mAChR GCAACGCCTCGGTCATG GCCGGGTCACGG AG AAGT A subtype m l S9 CGGTCAACAACTACTTCCTG CTGAGCCTG GCTGCTGACGCTGGATGAG CGCAGCAGGGCATTGC AAGACCCGCGGCGTCTGTTT GAA 130 Table 5.2. Descriptive statistics for total mercury (Hg), methylmercury (MeHg), labile inorganic mercury (iHgiabiie) and selenium (Sex) concentrations and stoichiometric ratio of Hgx to Sex in the cerebellum and temporal cortex from beluga whales sampled at Hendrickson Island, NT, Canada in 2008 and 2010. Descriptive Statistics Variable Temporal Cortex Cerebellum Sample number (n) Total Hg concentration (mg kg'1 dw) MeHg concentration (mg kg'1dw) iHgiabiie concentration (mg kg'1dw) Sex concentration (mg kg'1dw) 31 35 1 5 .0 (1 .5 -1 1 3 ) 10.6(1.7 — 113) 1.9 (0.68 - 5.2) 1.4 (0 .4 5 -5 .2 ) 3.1 (0 .3 3 -8 .1 ) 2.6 (0 .6 0 -6 .7 ) 22.4 (7 .0 - 133) 19.1 (6 .1 -1 3 3 ) Hg:Se 0.6 (0.2 - 0.9) 0.6 (0.2 - 0.9) 131 Table 5.3. Results from backward stepwise multiple regressions conducted for both brain regions, with binding o f [3H]-QNB to the muscarinic acetylcholine receptor (mAChR) and mRNA expression o f mAChR subtype ml as the outcome variables. Concentrations o f mercury (total mercury (Hgx)), methylmercury (MeHg), labile inorganic mercury (iHg)), molar ratio o f Hg to Se (HgSe), or selenium (Se) concentration, and sampling year and animal age were tested as predictor variables. Temporal cortex Cerebellum Dependent variable mAChR Adjusted R2 Intercept Slope F-value Adjusted R2 Intercept Slope F-value -0.05 -44 0.02(year) + 0.01(log(Hg)) + 0 . 0 0 1 (age) F3,20 = 0.6 0.45 -1 1 0 0.06(year)* + 0.05 (log(Hg)) 0.003 (age)* F3. is = 6 .8 * -0.03 -38 0.02(year) + 0.06(log(MeHg)) + 0 . 0 0 1 (age) F3 20 = 0 . 8 0.33 -95 0.05 (year)* - 0.08(log(MeHg)) 0.003 (age) F3. ,3 = 3.6* -0.04 -33 0.02(year) - 0.03(log(iHg)) + (age) F3.20 = 0.7 0.43 -2 0 0 0.1 (year)* + 0.2(log(iHg)) O.Ol(age)' F3. , 8 = 6 .8 * 0.02(year) + 0.07(log(HgSe)) + 0 . 0 0 1 (age) F3,20 = 0.7 0.59 -140 0.07(year)* + 0.3(log(HgSe))* 0.004(age)* F3 ,i7= 1 0 .6 * F3,20 = 0.6 0.46 -1 1 0 0.06(year)* - 0.06(log(Se)) 0.003(age) F3.18 = 6 .6 * 0 .0 0 1 mAChR ml mRNA -0.03 -47 -0.05 -37 0.38 230 0.26 120 0.25 204 0.42 207 0.16 230 0.02(year) -0.01(log(Se)) + 0 . 0 0 1 (age) -0.1 (year)' -0.6 (log(Hg))* + 0 . 0 1 (age) -0.06(year) - 0.6(log(MeHg))* + 0 . 0 1 (age) -0.1 (year) -0.7(log(iHg))* + 0.0 Rage) -0.1(year)—1,2(Iog(HgSe))* + 0.0 Rage) -0.1 (year) -O ^ log^ e))’ + 0.007(age) F3. , 9 = 5.4* F3, 2 o ~ 3.7* F3, , 7 = 3.3* NA F3 .2 1 = 6.8* F3,22= 2.6 * p < 0.05 ‘p < 0.10 132 Table 5.4. Results from backward stepwise multiple regressions conducted for both brain regions, with total monoamine oxidase (MAO) activity and mRNA expression o f MAO A as the outcome variables. Concentrations o f mercury (total mercury (HgT)), methylmercury (MeHg), labile inorganic mercury (iHg)), molar ratio o f Hg to Se (HgSe), or selenium (Se) concentration, and Temporal cortex Cerebellum Dependent variable Total MAO MAO-A mRNA Adjusted R2 Intercept Slope F-value F 3,2o = 3 .6 * 0.35 2.5 0.007(age)* -0.1 (log(Hg))* F2 20 = 7.02* 0.2(year)* +0.1(log(MeHg)) + 0.01 (age) F3,2i=3.7 * 0.47 2.5 0.005(age)* -0.3(log(MeHg))* F 2,2o = 1 0 .7 * -395 0.2(year) + 0.4(log(iHg)) + 0.01(age) F3,is = 3.2* 0.41 2.4 0.007(age)* - 0.2(log(iHg))* F 2,2o = 8.81* 0.25 -452 0.2(year)* + 0.2(!og(HgSe)) + 0.0 Rage) F3,2i = 3.7* 0.48 2.2 0.007(age)* -0.4(log(HgSe))* F2,2o= H . 2 * 0.27 -491 0.3(year)* + 0.3(log(Se)) + 0.01(log(Se)) F3,2i = 3.9* 0.27 2.5 0.006(age)* -0.1(log(Se)) F 2,2o = 5 .1* 0.01 -2.3 0.001 (year) - 0.05(log(Hg)) 0.002(age) F3.,9 = l.l -0.09 -33 0.02(year) + 0.04(log(Hg)) 0.00 Rage) F322 = 0.28 -0.11 -6.8 0.003(year) + 0.06(log(MeHg)) - 0.00 Rage) F323 = 0.2 -0.11 -19 0.001 (year) + 0.002(MeHg) 0.0003(age) F3.22 = 0.1 1 0.01 28 -O.ORyear) - 0.07(log(iHg)) 0.004(age) F 3i18= 1.1 -0.07 -31 0.02(year) + 0.05(log(iHg)) 0.00 Rage) F3,22 = 0-3 -0.11 -10 0.01 (year) -0 .1 (log(HgSe)) 0.0003(age) F3,23 = 0.14 -0.07 -27 0.01 (year) + 0.1 (log(HgSe)) O.OORage) F3,22 = 0.5 F3,23 = 0.9 -0.01 -27 0.01 (year) + 0.04(log(Se)) O.OORage) F3.22=0.2 Adjusted R2 Intercept 0.3 -460 0.25 -434 0.26 -0.02 11 Slope 0.2(year)* + 0.3(log(Hg)) + 0.01 (age) -0.005(year) -0.14(log(Se)) + 0.0002(age) F-value *p < 0.05 ‘p < 0.10 133 2500 r = -0.58 p = 0.005 n = 22 c *+ 5* 3 o u 2000 a. ♦ OS ♦ ♦ s ♦♦ 2 1500 £ •o e so a ♦ 1000 * ♦ OB Z O' 500 20 40 60 80 Estimated age (1 grow th layer y r 1) Figure 5.1. The correlation between muscarinic acetylcholine receptor binding to [ H]QNB and estimated age, based on tooth analysis (one growth layer per year), in the temporal cortex of beluga whales (Delphinapterus leucas). 134 700 e 600 E w> 500 S c j j 400 > '6 « O < J * 300 r = 0.50 p = 0.01 n = 23 * * * * s ^ 200 • o H 100 10 20 30 40 50 60 70 Estimated age (1 growth layer y r 1) Figure 5.2. The correlation between total monoamine oxidase activity and estimated age, based on tooth analysis (one growth layer per year), in the temporal cortex o f beluga whales (Delphinapterus leucas). 135 1.8 1.6 = -0.36 = 0.05 = 30 1.4 1.2 0.8 0.6 0.4 0.2 40 60 80 100 120 140 Selenium concentration (mg kg'1dw) Figure 5.3. The correlation between mRNA expression (fold change) and selenium concentration in the cerebellum of beluga whales (Delphinapterus leucas). The expression o f mRNA was normalized to the internal control gene S9 and fold changes were calculated based on the lowest-exposed whales (« = 3). 136 Discussion The major findings from this study were that MeHg exposure was negatively associated with total MAO activity in the temporal cortex, and mRNA expression o f the mAChR subtype M l in the cerebellum, of beluga whales. Furthermore, our results suggest that co­ accumulation o f Se and Hg was associated with variation in MAO activity, mAChR binding and mRNA expression for mAChR m l. Variation observed in components o f both the cholinergic and dopaminergic signaling pathways in association with an increase in the molar ratio o f Hg to Se, suggests that Se may provide a protective effect from Hg exposure for these two signaling pathways. We did not observe a relationship between mRNA expression and receptor binding or enzyme activity, which may have been due to varied post-transcriptional mechanisms that convert mRNA to protein, variation in in vivo half- lives of proteins, and the error and noise associated with protein and mRNA experiments (Greenbaum et al., 2003). Furthermore, the prolonged time to collect wildlife samples may have resulted in the degradation of RNA. Between 33 and 48 percent of mRNA transcripts may have decayed during sample collection and preservation (approx. 3 hrs) based on reported hourly decay rates that ranged from 0.085 to 0.221 for mRNA transcripts from human cells (Yang et al., 2003). The post-mortem interval in our study may have had limited impact on overall mRNA integrity, given that a decrease in the 28S/18S ribosomal RNA ratio was only observed in mouse brain samples kept at ambient temperatures for 36 hrs after death (Catts et al., 2005). Overall, the results from this study complement previous findings (Ostertag et al., in review), and taken together, suggest that MeHg exposure may indeed be o f toxicological concern for beluga whales from the eastern Beaufort Sea population. We explore the 137 potential mechanisms o f action and physiological outcomes of these findings in relation to previous captive and wildlife animal studies, and in vitro studies. Cholinergic signaling pathway Cholinergic signaling pathways have been linked to essential physiological processes including learning, memory, stress response and modulation o f sensory information (Reis et al., 2009). The mAChR may play a critical role in physiological processes including thermoregulation, motor function and feeding (Bymaster et al., 2003; Wess, 2004). Our findings indicated a statistically significant positive relationship between mAChR density and the molar ratio o f Hg to Se in the temporal cortex, with a slight negative relationship between age and mAChR density. The relationships between mAChR binding and Hg (+), MeHg (-), iHg (+) and Se (-) concentrations were not statistically significant. Therefore, these results suggest that Se may play a role in modulating the interaction between Hg and the mAChR. It is possible that as the ratio of Hg to Se increased, the concentration o f unbound Hg increased, allowing Hg to interact more effectively with sulfhydryl groups and cause a homeostatic response at a neurochemical or molecular level. In the cerebellum there was not a significant relationship between Hg concentration, Hg to Se ratio, and mAChR binding; however, at a molecular level, the expression o f mRNA for mAChR ml was negatively associated with Hg species (Hgj, MeHg, iHg) and the ratio of Hg to Se. The lack of relationship between mAChR binding and expression o f mRNA for mAChR ml may be due to differences in agonist-induced receptor internalization and downregulation (Thangaraju and Sawyer, 2011). 138 In previous studies, an increase in the density o f mAChR was observed following MeHg dosing o f rats in vivo (Coccini et al., 2000; Coccini et al., 2007; Costa, 1988; Rajanna et al., 1997) and a positive relationship between Hg and mAChR levels was reported for wild mink (Basu et al., 2005a), loons and eagles (Scheuhammer et al., 2008). A negative relationship between MeHg and mAChR density was found in the cerebral cortex o f river otters (Basu et al., 2005c) and in rats exposed prenatally to MeHg (Zanoli et al., 1994). A previous avian study found that Hg exposure was not correlated to relative mRNA expression of nicotinic receptor a-7 in herring gulls with low brain Hg levels ranging from 0.14 - 2.0 pg g'1 dw (Rutkiewicz et al., 2010). Interestingly, we observed a negative relationship between mRNA expression for mAChR ml and Hg concentration and speciation (Hgx, MeHg, iHg and Hg to Se ratio) in the cerebellum. The concentration o f Hg and Hg species in beluga cerebellum (median, range; H gj: 10.6 mg kg'1 dw, 1.7 - 113 mg kg'1 dw) were much greater than those observed in herring gulls. Therefore, the different relationships between MeHg exposure and mRNA expression observed in beluga and herring gulls may be due to differences in Hg exposure, differences in sensitivity o f the nicotinic receptor a-7 and mAChR ml to Hg exposure, or other undetermined differences. Methylmercury was found to inhibit agonist binding to ml and m2 muscarinic receptors in rat brain cortical membranes (Castoldi et al., 1996). The binding o f agonists and antagonists to extracellular cysteine residues modulates muscarinic receptor activity; therefore, MeHg may modify mAChR activity by binding to this critical region o f the receptor and competitively inhibiting mAChR binding (Limke et al., 2004). The binding o f MeHg to mAChR has been linked to disruption o f Ca2+ in cerebellar granule cells, and 139 has been suggested as a cause o f cel I-regulated death (apoptosis) or the downregulation o f mAChR (Limke et al., 2004). Three subtypes o f the mAChR (m l, m3 and m5) are coupled to G proteins of the G q/n family, which mediate the activation o f phospholipase C and subsequent release of Ca2+ (Ehlert and Thomas, 1995). Therefore, the decrease in mRNA expression for mAChR ml associated with MeHg exposure could be explained by downregulation o f the mAChR, to protect the cerebellum from a disruption in Ca2+ homeostasis. Dopaminergic signaling pathway Monoamine oxidase plays an integral role in maintaining the homeostasis o f key neurotransmitters in the CNS and other organs (Bortolato and Shih, 2011). Our findings suggest that total MAO activity may be negatively associated with Hgx, MeHg, iHg concentrations, and ratio o f Hg to Se in the temporal cortex. This is consistent with findings of decreased MAO activity with Hgx and MeHg in the cerebral cortex but not cerebellum of wild river otters (Basu et al., 2007b). The statistically significant effect o f sampling year on MAO activity in the cerebellum may have obscured a relationship between enzyme activity and Hg concentration or speciation in this brain region. Another explanation for the regional difference in MAO activity and Hg exposure may be that the temporal cortex had more elevated concentrations o f Hg, iHgiabiie and MeHg compared to the cerebellum. The results from this study suggest that the ratio o f Hg to Se is a significant predictor of MAO activity in the temporal cortex; therefore, Se may play a role in reducing Hg availability and toxicity in beluga whales. 140 The lack of relationship between mRNA expression for MAO-A and total MAO activity, and mRNA expression for MAO-A and Hg concentration or speciation, suggests that MeHg exposure may result in disruption o f enzyme function but not mRNA transcription. For example, the decrease in total MAO activity in the temporal cortex associated with Hg concentration may have occurred due to alteration o f the mitochondrial structure (Franco et al., 2007; Shenker et al., 1999), leading to decreased MAO activity without related changes in mRNA transcription for the MAO-A target gene. The slight positive relationship between age and MAO-T activity was consistent with findings that in general, MAO-B activity increases with age in humans, although MAO-A activity remains stable with age (Nicotra et al., 2004). Exposure to MeHg has been associated with alterations o f neurotransmitter amine metabolism in the central nervous system (Chakrabarti et al., 1998). Monoamine oxidase is located on the outer mitochondrial membrane and catalyzes the oxidative deamination o f monoamine neurotransmitters (e.g. dopamine), neuro-modulators and hormones (Bortolato and Shih, 2011). Methylmercury may exert an effect on MAO either by directly binding to thiol groups on the enzyme or by altering mitochondrial function (Chakrabarti et al., 1998). Previous studies have found decreased mitochondrial activity associated with MeHg exposure in mitochondrial-enriched fractions of mouse cerebrum (Franco et al., 2007; Meinerz et al., 2011), and striatal synaptosomes from rats (Dreiem and Seegal, 2007). A decrease in MAO activity was observed in the cerebellum and cortex o f rats exposed to MeHg (Chakrabarti et al., 1998), and the intrastriatal administration o f MeHg in rats was associated with a concentration-related increase in striatal output of dopamine (Faro et al., 2003). Disruption o f MAO activity could lead to 141 downstream impacts on neuronal signaling pathways that involve monoamines that are associated with fight-or-flight response, emotion, motor activity and cognition (Beyrouty et al., 2006). Clinical observations indicate that disturbance o f dopaminergic neurotransmission is related to psychiatric symptoms (Reis et al., 2009). Variation o f mRNA expression and neurochemical biomarkers associated with Hg exposure in beluga whales may provide complementary evidence o f potential disruption o f neurosignaling pathways. Our results suggest that MAO and mAChR may be more impacted by MeHg exposure in the temporal cortex than the cerebellum, which may be due to more elevated concentrations o f Hg, MeHg and iHgiabiie present in the temporal cortex. Taken together with our previous findings (Ostertag et al., in review), the neurochemical components o f the cholinergic, dopaminergic and GABAergic signaling pathways may be good candidates as biomarkers o f neurochemical disruption in cetaceans. The relationships observed in this study between the molar ratio o f Hg to Se, and components of the cholinergic and dopaminergic signaling pathways confirms that including this ratio or the Se to Hg ratio in wildlife studies is important for evaluating the biological effects o f MeHg exposure (Burger et al., 2013). Furthermore, the results from our study support the use of both molecular and neurochemical biomarkers to improve our understanding of potential effects of MeHg exposure on wildlife. However, to fully understand the relationship between mRNA and protein expression, requires a better understanding o f the dynamics o f protein synthesis and degradation (Greenbaum et al., 2003). There is mounting evidence that chronic MeHg exposure in beluga whales is associated with variation in components o f diverse neurosignaling pathways (Ostertag et al., in review). These results suggest that MeHg exposure may lead to neurochemical 142 changes associated with maintaining homeostasis in the CNS. The impact o f chronic MeHg exposure for beluga health requires further study. 143 A cknowledge merits This study was funded by NSERC Discovery (HMC) and the Fisheries Joint Management Committee (SKO). SKO was the recipient o f a NSERC Doctoral award, Nasivvik Doctoral award, NSTP Training Fund and UNBC travel awards. We thank A. Philibert and M. Gillingham for guidance with statistical analyses, E. Montie for sharing dissection methods, A. Essler, A. Montgomery, S. Krause, L. Rose, A. Krey, and G. Prkachin for assistance in the laboratory, and L. Loseto, M. Noel, F. Pokiak, N. Pokiak, R. Felix, K. Nuyaviak, B. Voudrach, R. Walker, K. Snow, C. Pokiak, Inuvialuit hunters, Tuktoyaktuk and Inuvik HTC, and the DFO for their support in the field. 144 Bridge In the previous three chapters we assessed the neurotoxicological risk of methylmercury exposure through the comparison o f brain mercury concentrations with threshold levels and the use o f molecular and neurochemical biomarkers. We found that concentrations of Hg in brain tissue exceeded thresholds o f adverse effect, and were also associated with neurochemical and molecular variation. A particular challenge in risk assessments is determining causal linkages between biological responses to toxicant exposure in wildlife studies. Harvesters’ observations o f beluga whales may provide a unique and valuable line o f evidence to determine linkages between toxicant exposure and biological response. Therefore, for the next study, we worked with Inuvialuit beluga harvesters to document their observations o f the behaviour of beluga whales during harvesting activities. Our primary objectives were to develop a questionnaire to document local observations o f beluga whale behaviour during harvesting activities and to assess whether Hg levels were associated with differences in beluga whale behaviour. 145 Chapter 6. Inuvialuit observations of beluga whale (Delphinapterus leucas) link mercury exposure and behaviour during harvesting activities. Names and Affiliations o f Authors: 1. Sonja K. Ostertag Natural Resources and Environmental Studies, University o f Northern British Columbia, Prince George, British Columbia, Canada, V2N 4Z9 ostertag@unbc.ca 3. Hing Man Chan * Center for Advanced Research in Environmental Genomics, University o f Ottawa, Ottawa, Ontario, Canada K IN 6N5 laurie. chan@uottawa.ca 146 A bstract Beluga whales in the Beaufort Sea are facing many environmental changes associated with global climate change and pollution. Harvesters’ observations of beluga whales’ behaviour may provide key insights into linkages between toxicant exposure and biological response. The objective o f this study was to determine if there were differences in the behaviour o f beluga whales associated with mercury (Hg) exposure. We developed and administered a questionnaire (n = 11) to document hunters’ observations o f beluga whale behaviour during harvesting activities. The participation rate was 73 % and all respondents had ten or more years o f beluga hunting experience. Mercury concentrations were measured in cerebellar cortex samples using inductively-coupled plasma mass spectrometry, and ranged from 0.32 to 3.27 mg kg'1 wet weight (ww; median, 0.77 mg kg'1 ww). There was no evidence that the amount o f time required to harpoon the whales was associated with Hg concentrations. However, we detected slight differences in beluga whales’ use o f evasive strategies associated with Hg exposure. Fewer whales exhibited evasive behaviour when they had higher than median Hg than those with lower than median Hg (evasive behaviour and > median Hg: n = 1\ no evasive behaviour and > median Hg: n = 5). The small sample size precluded the use of statistical tests, but suggests that behaviour could vary with Hg exposure in this population o f beluga whales. We recommend that Inuvialuit harvesters’ observations o f beluga whale behaviour are documented in future community-based monitoring studies. In the long term, combining traditional ecological knowledge and traditional scientific knowledge may provide greater insight into how environmental change could impact this beluga population. 147 Introduction Anthropogenic activities including climate change (ACIA, 2005), industrial development (Prowse et al., 2009), shipping (AMSA, 2009) and long range transport o f pollutants (AMAP, 2011; Dietz et al., 2013; Muir and de Wit, 2010) are causing rapid changes to the Arctic. These changes pose a serious threat to the conservation o f Arctic marine mammals (as reviewed by Huntington (2009)). Recent studies on beluga whales (Delphinapterus leucas) from the Eastern Beaufort Sea beluga population in the western Canadian Arctic, found concentrations o f mercury (Hg) in brain tissue exceeded thresholds o f adverse effect (Ostertag et al., 2013) and were also associated with neurochemical variation (Ostertag et al., Submitted; Ostertag et al., in review). A particular challenge in risk assessments is determining causal linkages between biological responses to toxicant exposure in wildlife studies. The use o f multiple lines o f evidence, including field observational studies may increase confidence in the conclusions o f risk assessments (EPA, 1998). Inuvialuit travel every summer to traditional whaling camps along the Beaufort Sea coast to harvest beluga whales (Harwood et al., 2002). Harvesters’ observations of beluga whales may provide a unique and valuable line o f evidence to determine linkages between toxicant exposure and biological response. In the long term, combining traditional ecological knowledge (TEK) and traditional scientific knowledge (TSK) may provide useful insight into how environmental change is impacting Arctic ecosystems. As a result of global pollution, Hg concentrations in Arctic marine mammals have increased by an order o f magnitude since the preindustrial period (Dietz et al., 2009). The toxic effects of methylmercury (MeHg) are primarily due to its ability to cross the blood148 brain barrier (Aschner and Aschner, 1990) and damage the central nervous system (Clarkson and Magos, 2006). Methylmercury is the principle form ofH g consumed by Arctic beluga whales (Loseto et al., 2008a); Arctic beluga whales have also been identified as being particularly vulnerable compared to other Arctic marine mammals to MeHg exposure, due to elevated concentrations o f total Hg measured in brain tissue compared to other species (Dietz et al., 2013). Mercury exposure in beluga whales from the western Canadian Arctic exceeded levels associated with neurotoxicity (Ostertag et al., 2013) and showed variation in components o f neurochemical signaling pathways (Ostertag et al., Submitted; Ostertag et al., in review). Biochemical changes may be an indicator o f early-stage effects before the manifestation o f disease (Manzo et al., 1996). If beluga whales are equally sensitive to Hg toxicity as primates and mink, we would expect clinical symptoms to arise when total Hg concentrations in brain tissue exceeded 6.0 to 12.0 mg kg'1 wet weight (ww; Berlin et al., 1975b; Evans et al., 1977; Luschei et al., 1977; Stinson et al., 1989). Beluga whales inhabit the northern coasts o f Alaska, Canada, Greenland and Norway (Jefferson, 2008). Summering populations are concentrated in western Hudson Bay (WHB) and eastern Beaufort Sea (EBS) (Jefferson, 2008) and Inuit continue to highly value beluga whales as a source o f food (Harwood and Smith, 2002). Beluga whale monitoring has been taking place in the Mackenzie Delta since the 1970s (Harwood et al., 2002) and TEK has been fundamental to the success o f this program through the provision o f high quality samples from harvesters’ catch. However, harvesters’ observations have been minimally included in this program. Scientific and local observations o f environmental change can be brought together to identify new avenues 149 for further exploration, compare observations from different scales and discuss potential mechanisms that explain both sets o f observations (Huntington et al., 2004). Previous studies have documented Inuit observations o f beluga whale migration, feeding behaviour, calving, response to disturbance, changes in prey quantity and quality, and health (Carter and Nielsen, 2011; Fernandez-Gimenez et al., 2006; Huntington et al., 1999; Kilabuk, 1998; Mymrin et al., 1999). Elders and hunters have also provided possible explanations for changes in blubber thickness, prey availability, migration patterns and feeding behaviour based on their observations (e.g. Carter and Nielsen, 2011; Huntington et al., 1999; Kilabuk, 1998). Although TEK about beluga whales has been documented in the Arctic, to date, linking observed behaviour to body burden o f contaminants or physiological parameters has not been attempted. Such integration may provide insight into the potential effects o f neurotoxicants (e.g. MeHg) on beluga whale behaviour. There have been increasing calls to include or consider TEK in decision-making and environmental assessment in the north (Bennett, 2012). We chose to use a broad definition o f TEK as “knowledge gathered and maintained by groups of people, based on intimate experience with their environment” (Huntington et al., 2004). One approach for including TEK in assessing ecosystem changes includes observations of animal behaviour to assess animal health (Huntington et al., 2004). Traditional ecological knowledge has provided valuable information about marine mammals in the Arctic (Carter and Nielsen, 2011; Ferguson et al., 2012) and co-management (Dowsley, 2009). Inuvialuit knowledge and wisdom about beluga whales has been documented and confirms that hunters’ and elders’ knowledge o f beluga whale behaviour and predation is 150 associated with decades o f observations (Byers and Roberts, 1995). Indigenous hunters and elders o f Chukotka, Russia, shared their observations made while hunting beluga whales or pursuing walrus (Odobenus rosmarus divergens) and seals (Phoca spp. and Erignathus barbatus) of beluga whale diving behaviour, feeding, migration, communication and response to disturbance (Mymrin et al., 1999). In this study, we worked with Inuvialuit harvesters to document their observations of beluga whale behaviour made during harvesting activities. Our primary objectives were to develop a questionnaire to document local observations o f beluga whale and to assess whether differences in Hg concentrations were associated with beluga whale behaviour. We hypothesized that if whales were experiencing Hg-associated neurotoxicity, whales with higher concentrations o f brain Hg would behave abnormally, be harpooned more quickly and/or exhibit different evasive strategies during the hunt. Methods Study area, people and context This study was a component o f the Hendrickson Island Beluga Study, which was a collaborative study o f beluga whales from the Eastern Beaufort Sea population. We worked closely with Inuvialuit harvesters from Tuktoyaktuk (69.44° N, 133.03° W), a coastal community o f 930 people, located on the Beaufort Sea in the Inuvialuit Settlement Region (ISR), western Canada. In 2010, beluga whales were sampled and harvesters’ observations were collected on Hendrickson Island (69.50°N, 133.59° W), a 151 small island located in the southern Beaufort Sea, approximately 20 km west o f Tuktoyaktuk (Figure 6.1). Inuvialuit have a long history o f hunting beluga whales during their summer migration through the Mackenzie River Estuary. The beluga whale is known as qilalugaq in Inuvialuktun, the Indigenous language o f the Inuvialuit. Based on the archeological record, beluga whales made up approximately half o f the diet o f pre-contact Mackenzie Inuit (Friesen and Arnold, 1995). Beluga hunting typically occurs in the month o f July, when beluga whales migrate through the warm waters o f the Mackenzie Delta Estuary (Harwood et al., 2002). Beluga hunting in the ISR typically occurs from 4.6 m long aluminum boats and hunters harpoon the whale before killing it, to make retrieval easier (Harwood et al., 2002). The total annual number o f landed beluga whales on the shores o f the Beaufort Sea and Amundsen Coast was 111 between 1990 and 1999 (Harwood et al., 2002). Beluga whales from this population are also harvested by residents o f some coastal villages in Alaska (average 64 per year between 1995 and 2000) and possibly by residents o f Chukotka (Harwood et al., 2002). Beluga whales travel through Kugmallit Bay in the Mackenzie River Estuary during their summer migrations. The shallow waters in this bay make it an ideal location for harvesters to track and hunt beluga whales. Hunters from Tuktoyaktuk butcher beluga whales on Hendrickson Island following the hunt and generally return to Tuktoyaktuk immediately after butchering the whale to process the muktuk (skin and blubber) and to prepare mipku (dry meat). 152 Sampling Brain sampling occurred immediately following the harvest on the shores o f Hendrickson Island, after receiving informed consent from the harvesters. Details about sample collection and analysis are provided elsewhere (Ostertag et al., in review; Ostertag et al., 2013). Briefly, brain samples were collected on Hendrickson Island and the concentration ofH gw as analyzed by inductively-coupled plasma mass spectrometry (Agilent Technologies, 7500 CX) following a modified acid digestion (Armstrong and Uthe, 1971). Permission to collect samples was obtained from the Tuktoyaktuk Hunters’ and Trappers’ Committee and the Aurora Research Institute prior to sampling. Ethics approval to carry out this research was received from the Research Ethics Board at University ofNorthem British Columbia. Questionnaire A questionnaire was developed to document harvesters’ observations of beluga whale behaviour during harvesting activities. We chose to use a questionnaire to document harvesters’ observations about the behaviour o f beluga whales to enable comparison between whales, for efficient documentation in a field environment and to increase participation (Huntington, 2000). Nine questions were asked; three questions were multiple choice, two questions required one-word answers and four questions were openended questions. Topics covered were the beluga hunting experience of the harvesters, the weather and seasonal conditions for hunting and the behaviour o f the beluga during the hunt. Questions about beluga whale behaviour ranged from general questions such as “was there anything unusual about this whale’s behaviour”, to more specific questions 153 about the time it took harpoon the whale. Questions about behaviour were both multiple choice (“was there anything unusual about this whale’s behaviour”) and open-ended such as “how would you describe this whale’s behaviour” and “how did this beluga act when you were hunting it” to ensure that more detailed information could be recorded. Questions were included about harvesters’ beluga-hunting experience, perceived weather conditions for harvesting, and seasonal changes in beluga harvesting. The Tuktoyaktuk Hunters and Trappers Committee gave permission for S. Ostertag to administer this questionnaire on Hendrickson Island, with consenting harvesters. Respondents Generally, two hunters, a harpooner and a boat driver worked together to hunt one beluga whale. Occasionally, Elders accompany the harpooner and boat driver during the hunt. The questionnaire was administered to the boat drivers (n = 10) or in one case, an Elder (« =1), after the whale was brought to shore and the butchering was complete. The participants provided informed consent prior to completing the questionnaire. The questions were read aloud and S. Ostertag documented the answers. The drivers were all fluent in English. O f the 15 whales harvested during the 2010 field season, observations were recorded for 11 whales for the purpose o f this study. All participants provided informed consent and completed the questionnaire within 10 to 20 minutes. Data analysis The results from the questionnaire were entered into Microsoft® Excel (v 12.3.5). For each whale, the observations were cross-referenced with Hg concentration data for brain 154 tissue. Beluga whales were categorized as having brain Hg concentrations greater or lesser than the median concentration measured. The responses were categorized as follows: weather conditions (good or excellent, fair or poor), time to harpoon (more or the same time to harpoon, less time to harpoon), general behaviour (normal, unusual), swimming speed (fast, medium speed) and observed evasive strategies (yes: turned or charged; no: did not turn or charge, straightforward to harvest) (Table 6.1). The small sample size made statistical analysis unfeasible. Therefore, we grouped whales based on behaviour, ‘time to harpoon’, and evasive strategies for whales with relative Hg concentration measured in brain tissue, to have a visual representation o f the potential relationship between behaviour and Hg exposure. To assess variables that were associated with the ‘time to harpoon’ the whale, we investigated the potential relationships between weather conditions, water level and Hg exposure, with the relative time to harpoon the whale. Results Mercury concentrations The median Hg concentration in the cerebellar cortex was 0.77 mg kg'1 ww, and ranged from 0.32 to 3.27 mg kg'1 ww; therefore, none exceeded threshold levels for clinical symptoms from primate studies, which are between 6.0 and 12.0 mg kg’1 ww (Berlin et al., 1975b; Evans et al., 1977; Luschei et al., 1977; Stinson et al., 1989). Five beluga whales had Hg concentrations between 1.0 and 4.0 mg kg’1ww, which is the range in which we would expect to observe biochemical changes but not clinical symptoms (Basu 155 et al., 2007a; Basu et al., 2008; Suzuki, 1979; Wobeser et al., 1976). Overall, the concentrations o f Hg in brain tissue were below levels of clinical symptoms. Response rate The participation rate was 73 %. All respondents had ten or more years o f beluga hunting experience (Figure 6.2). In general, the driver had more hunting experience than the harpooner, which may be associated with the skill and knowledge required to successfully track beluga whales in the murky waters o f the Mackenzie Delta Estuary. The respondents compared the behaviour o f the harvested whale to the behaviour o f previously observed whales. The questionnaire was an efficient and effective mechanism for experienced hunters to share their observations about the whale’s behaviour with the beluga researchers at Hendrickson Island in 2010. Respondents generally provided detailed responses to the questions that were asked. General observations All o f the whales behaved normally when they were being hunted. For ten o f the eleven whales, no unusual observations were noted about their behaviour (Table 6.1). For example, one whale that was described to behave normally “just tried to get away from the hunters” and another whale that did not exhibit unusual behaviour “must be a healthy whale”. However, one whale that behaved normally prior to harpooning, and took approximately the same amount o f time to harpoon compared to other whales, began to act differently after it was harpooned. For example, it “wouldn’t leave the side o f the boat after harpooning” and it was “ swimming fast, in circles around the boat” (Elder, 156 Tuktoyaktuk). This was the first time that this behaviour was observed in this Elders’s experience. This whale did not have an elevated concentration o f brain Hg (0.8 mg kg'1 ww) and was median-aged (approx 16 yo) (Figure 6.3). The cause o f this abnormal behaviour was not determined; however this whale also had a large number o f nematodes in the auditory canal (personal obs). Time to harpoon Harvesters responded that 6 whales took less time to harpoon compared to other whales, and five whales took more or the same amount of time to harpoon (Table 6.1). O f the five whales with ‘higher than median’ Hg, three took less time to harpoon, and two took more or the same time to harpoon (Figure 6.4). Three whales with ‘lower than median’ Hg took less time to harpoon and the remaining three whales in this category took more or the same time to harpoon. In this study, therefore, the data indicates that whales with higher than median Hg were not harpooned in less time than whales with lower than median Hg concentration. Evasive strategies Based on the recorded observations about whale behaviour, we compared Hg concentrations in the whales that were “easy or straight forward to hunt” and those that used evasive strategies such as turning and charging. Four respondents described the whales as turning, charging or hiding during the hunt (Table 6.1). Three whales did not exhibit evasive behaviour and were straightforward to harpoon. Two whales “didn’t charge... didn’t give any trouble” or “never turned on us” . Four whales were 157 straightforward to harpoon, but o f these four, two also turned or charged; therefore, we grouped them with whales that exhibited evasive behaviour. The likely reason that these two whales were straightforward to harvest was that they were harvested during good weather and low tide and one was “impossible to lose” and the other whale was “easy to follow, after finding out what it would do”. Although the sample size was very small, fewer whales exhibited evasive strategies with higher than median Hg (n = 1) than with lower than median Hg (« = 3; Figure 6.5). Furthermore, whales with lower than median Hg exhibited evasive strategies more frequently (n = 3) than not (n = /). Weather The weather was predominantly good or excellent for hunting during harvesting activities (n = 7) compared to poor or fair (n = 3). Good weather was described as being calm or a little choppy with low water. Poor or fair weather was described as being windy with high water, “a bit choppy” or “water a bit high”. Harvesters provided explanations for differences in the time to harpoon, which included weather conditions or water level. For example, the low tide made it “impossible to lose sight o f the whale because it had a good wake on it”, shallow water made it easier to see the whale, and “[the] weather was good for tracking” . Whales that took more time to harpoon were in deeper water “so harder” to harpoon, “harder to track than other whales in its group... hiding lots.... waited for a long time before coming up for air”, “easy to follow after finding out what it would do”. Overall, whales took less time to harpoon when the weather was good (n = 5) and the water was low {n = 4), and took more or the same time to harpoon when the weather was poor or fair (n = 2) and the water was high (n = 2). There were also cases where whales 158 took less time to harpoon in poor weather (n = 1) and more time to harpoon in good weather (n = 2). One harvester stated that it was a ‘little harder’ to harvest the whale on July 18 than earlier in the season. Whales that were harvested later in the season may have been faster than whales harvested earlier; respondents observed whales to be ‘fast’ on July 13, 18 and 22. 159 Figure 6.1. This map depicts the location o f Hendrickson Island, a traditional belugaharvesting site in the Inuvialuit Settlement Region, NT (adapted from Wesche et al., 2011). 160 6 i 1 0 -1 9 2 0 -2 9 3 0 -3 9 40 or more Beluga hunting experience (years) Figure 6.2. Beluga hunting experience (years) o f the 11 participants of this study. Harvesters were counted each time they hunted a beluga and responded to the questionnaire. Therefore, some harvesters are counted more than once. 161 50% 45% 45% 45% >p c 40% a o 35% VI J3 & 0VI) 30% ■fi o 25% 3o 20% 15% e01 uu 0) a. 10% 5% 0% Hg > median Hg < median Figure 6.3. Harvesters’ observation o f normal (black column) and unusual behaviour (gray column) in whales during the harvest (n = 11), based on mercury (Hg) exposure (above or below the median Hg concentration measured). Median Hg concentration was 0.77 mg kg'1 wet weight. 162 O 30% « 20% Figure 6.4. Variables that may have affected time to harpoon and harvesters observations (black column = less time to harpoon; gray column = more or the same time to harpoon). Median mercury concentration in cerebellar cortex was 0.77 mg k g '1 ww. 163 45% 40% (A B O V n 01 JS 35% 30% 25% o 20% e0) u I. 01 a. 15% 10% 5% 0% Hg > median Hg < median Figure 6.5. Observations of evasive strategies (n = 7) demonstrated during beluga harvest and related mercury (Hg) exposure (more or less than median Hg). Whales that used evasive strategies (turning or diving; black column) or did not use evasive strategies (straightforward, did not turn; gray column) are presented according to Hg exposure. Median Hg concentration in cerebellar cortex was 0.77 mg kg’1 ww. 164 Table 6.1. Observations o f beluga whale behaviour during harvesting activities (n = 11). Behaviour “Less time to harpoon” Normal Swam fast Straight forward Turned or charged Yes 6 10 4 4 4 Observation No 5 1 1 2 2 Blank 0 0 6 5 5 165 D iscussion To our knowledge, this is the first time that behavioural observations and contaminant data were linked directly for individual beluga whales. The use of a questionnaire provided the opportunity for harvesters to have their observations o f beluga whales documented and cross-referenced with Hg-exposure data. Although conclusions about potential neurotoxicity associated with Hg could not be established, the key finding was that beluga whales with higher Hg were observed to use evasive strategies less frequently during the hunt than whales with lower Hg. Integration of multiple lines of evidence Mercury concentrations in brain tissue from the harvested whales were below the lowest observable adverse effects levels documented for primates (Berlin et al., 1975b; Evans et al., 1977; Luschei et al., 1977; Stinson et al., 1989). We would expect clinical symptoms of Hg intoxication to include the loss o f motor coordination (Bellum et al., 2012), abnormal movements and convulsions (Takeuchi et al., 1977), loss of balance (Farina et al., 2005), and reduced passive avoidance. The harvesters did not observe any abnormal movements or behaviour in the beluga whales prior to harpooning, which suggests that Hg exposure in the eleven whales analyzed in this study were not exhibiting clinical symptoms of Hg intoxication. The difference in evasive strategies observed in whales with more elevated Hg concentrations was consistent with behavioural symptoms o f Hg toxicity including the loss o f motor coordination. This study suggests that documenting observations o f evasive strategies may provide a sensitive measure o f changes in beluga behaviour that could be associated with Hg exposure. However, conclusions based on these results are limited by the small sample size. Further study into the potential effects 166 of Hg on beluga whale behaviour are merited given that the animal behaviour represents the integration o f sensory, motor and associative functions o f the nervous system (Tilson and Cabe, 1978). In general, the results from this study suggest that Hg concentrations in brain tissue ranging from 0.32 to 3.27 mg kg'1 ww were not associated with unusual behaviour and ‘time to harpoon’. Many variables could likely affect how quickly a beluga is harpooned including weather and timing. To harpoon a beluga, the boat driver has to track the beluga by following the wake that it creates in the water. Therefore, the association between weather and ‘time to harpoon’ reflects the importance o f good weather for hunting success and limits the usefulness o f ‘time to harpoon’ as an indicator o f the motor and cognitive function o f belugas. Behavioural observations as complementary line of evidence Behaviour has been monitored as an indicator o f stress in dogs (Bergeron et al., 2002) and macaques (Bercovitch and Clarke, 1995), as a response to physiological differences in rhesus monkeys (Laudenslager et al., 1999) or as a modulator o f the neuroendocrine and reproductive effects o f dominance interactions in baboons (Sapolsky, 1993; Sapolsky and Mott, 1987). Behavioural studies have also been used to complement physical examinations and blood analyses to assess the fitness o f stranded dolphins (Sampson et al., 2012). Beluga whale behaviour is particularly difficult to document in the wild because beluga whales spend approximately 85 % of their time below water (Kingsley et al., 2001). Furthermore, beluga whales are a protected species in Canadian waters under 167 the Fisheries Act and may not be disturbed except during fishing activities (Regulation 7, Marine mammal regulations, Fisheries Act (Canada, 1993)). Therefore, documenting the behaviour o f beluga whales during hunting activities provides a unique opportunity to capture detailed information without disturbing the animals unnecessarily. Combining behavioural observations with physiological data would be very difficult or impossible to achieve without the collaboration o f Inuvialuit harvesters. Given that the behavioural observations provided a complementary line o f evidence regarding potential effects o f Hg on beluga whales, we suggest that harvesters’ observations of beluga whale behaviour be used to complement, where possible, the physiological and toxicological parameters measured. This study documented one case in which a beluga whale was observed to behave very unusually after it was harpooned. To our knowledge, this was the first incidence in which abnormal behaviour in beluga was documented during harvesting activities. The use of the questionnaire provided the only opportunity for the observations of abnormal beluga behaviour to be documented in the Hendrickson Island beluga-monitoring program. Observations about abnormal behaviour are valuable to document in beluga monitoring because they could signal a potential risk to individual and population health, if increased parasite infestation occurred due to environmental change. Nematodes and flukes may be located within the external auditory system o f beluga whales and narwhal, and there is speculation that nematodes and flukes could affect echolocation and cause mass strandings (Vlasman and Campbell, 2004). During brain sampling, parasites were commonly observed in the auditory canals and brain tissue (pers. obs). Therefore, future 168 studies should systematically document the presence o f this parasite to monitor its presence, intensity o f infestation and animal behaviour. Bridging TEK, local observations and science We recommend that future monitoring be expanded to include harvesters’ observations in the ISR. Beluga whales have been harvested for centuries in the Mackenzie Delta Estuary and harvesters’ observations may provide key information about changes occurring in the marine ecosystem. In this study, harvesters were willing to respond to a brief questionnaire at the harvest camp on Hendrickson Island. Questionnaires have been identified as one o f many methods for documenting TEK (Huntington, 2000). The importance o f recording harvesters’ observations at the harvest site is that it allows these observations to be cross-referenced with health indicators and contaminant data for the same individual animal. The strength o f questionnaires is that they provide consistency and allow comparisons to be made between respondents and over time; however, semidirected interviews provide a greater depth and breadth o f knowledge and may reveal unanticipated information (Huntington, 2000). Conducting semi-directed interviews in this particular field camp would be challenging based on the short time that harvesters spend at Hendrickson Island following the hunt. Given that ethnographic, participatory and iterative methods may be more respectful and constructive approaches to engaging with Indigenous communities and local knowledge-holders (Thornton and Scheer, 2012), researchers may benefit from carrying out interviews in a location where harvesters are spending more time (i.e. in a permanent settlement or at a harvest camp), provided that these observations could be cross-referenced with other data that is collected. 169 Bringing together TEK and TSK in this study fit into developments at regional, national and international levels to include TEK in resource management and decision-making. In recent decades, there has been increasing recognition that Aboriginal knowledge could contribute to co-management and environmental impact assessments (Usher, 2000). This was the outcome o f advocacy, negotiation o f comprehensive land claims across the north, and the development o f formal Environmental Impact Assessments and review processes, in addition to legal developments within the Supreme Court o f Canada and lower court rulings (Usher, 2000). In northern Canada, Indigenous knowledge is recognized in the Northwest Territories as “a valid and essential source o f information about the natural environment and its resources” (Territories, 2005). Internationally, specific recommendations to establish marine and Arctic programmes that include the use o f TEK for the conservation o f biodiversity were presented during the workshop on traditional knowledge and biological diversity (Programme, 1997). More recently, efforts have been made to integrate or bridge TEK with TSK in Arctic ecological research (Gagnon and Berteaux, 2009; Gilchrist et al., 2005; Huntington et al., 2004). Bridging or linking western science with TEK has been recognized as particularly important when “identifying problems related to hazardous wastes and industrial pollution”(Wavey, 1993). To effectively bridge these ways o f knowing, southern scientists may not simply impose their views (Stevenson, 1996), but must support “the development o f permanent technical, scientific and support capacity under the control and direction o f Indigenous peoples” (Wavey, 1993). Challenges that have been identified in bridging TEK and TSK include the sharing of power (Berkes, 1993) and ownership of data (Wavey, 1993). Benefits that arise from bridging TSK and TEK 170 include the fact that people who spend long periods o f time on the land will see things “more often, for longer, and at more different times and places than is normally the case for scientists” (Usher, 2000). The observations that Inuvialuit beluga harvesters shared reflected knowledge gained from decades o f observing beluga during harvesting activities and travel in the Mackenzie Delta Estuary. Traditional Ecological Knowledge is comprised not only of factual knowledge about the environment and use o f the environment (past and present), but also values about the environment and a culturally-based cosmology (Usher, 2000). This study represents the documentation o f factual information gathered from experience beluga harvesters; however, this will hopefully be the starting point for greater inclusion o f TEK and local observations in beluga monitoring. Limitations Although the results from this study do not suggest that the whales sampled for this study were at risk o f Hg-associated toxicity, these conclusions should not be extrapolated to the eastern Beaufort Sea beluga population. Limitations in this study include the small sample size, low Hg concentrations measured in these whales compared to previously sampled beluga from the eastern Beaufort Sea population and lack o f specificity in the questions included in the questionnaire. Furthermore, relying solely on a questionnaire for documenting TEK o f beluga whales limited the type and quantity of data that was gathered. 171 The small sample size was due in part to the challenges associated with combining biological sampling of belugas with the harvester-questionnaires. One o f us (SO) was not able to administer the questionnaire to three harvesters (n ~ 3) due to challenges associated with collecting samples for laboratory analyses and administering the questionnaire before the hunters departed HI. The weather in the Mackenzie Delta changes rapidly; there are stronger and more frequent winds experienced by Inuvialuit in the summer, which reduces travel safety and shortens hunting trips in the summer (Wesche and Chan, 2010). Therefore, there was very little time to administer the questionnaire following the harvest. Furthermore, very few beluga whales were harvested during the 2010 sampling season compared to the 2006 and 2008 sampling season (n = 24 - 30 whales). Beluga whales harvested in 2008 had more elevated brain Hg concentrations than beluga whales harvested in 2010 (Ostertag et al., Submitted). The difference in Hg concentrations observed in 2008 and 2010 could be due to the younger age o f beluga whales harvested in 2010, and the small sample size (n = 15) that reduced the sampling o f whales at the extremes of Hg exposure. Increasing the number o f field seasons and sampling sites, and training whale monitors to administer questionnaires would increase sample size and provide greater understanding o f changes occurring in the eastern Beaufort Sea beluga population. The use of a questionnaire provided a rapid method for documenting harvesters’ observations following the hunt. Overall, the questionnaire was effective for documenting general observations such as ‘time to harpoon the whale’ and whether the whale behaved 172 normally. The use o f open-ended questions provided valuable additional information that was more specific about the whale’s behaviour. However, the use o f open-ended questions made it challenging to compare the specific observations for different whales, due to variability in the types o f observations that harvesters shared. This further reduced the sample size for the analysis of specific behavioural differences in whales related to Hg exposure. Including input from harvesters and community members on the content o f the questionnaire may have increased the specificity o f questions regarding behaviour. This could have resulted in more comparable responses regarding the specific behaviour o f the harvested whales. Results were presented to the harvesters in 2012; however, harvesters were not involved in the interpretation o f results. The observations documented in this study were analyzed semi-qualitatively, based on the dominant scientific paradigm, which reflects an imbalance o f power between the researchers and knowledge-holders (Stevenson 1996). We acknowledge that this study is merely a starting point towards a greater inclusion o f TEK in beluga monitoring research in the ISR. Conclusions We recommend that scientists and Inuvialuit knowledge-holders continue to work together to include TEK in beluga monitoring programs in the ISR. We suggest that semi­ directed interviews and focus groups be conducted with harvesters, elders, whale monitors and youth prior to the field season to identify observations that should be documented. Future studies that aim to bridge TEK and TSK are encouraged to use less 173 extractive methods o f documenting TEK and local observations through the use o f participatory research methods. Furthermore, additional methods for documenting and sharing TEK and TSK need to be identified through partnerships between researchers, harvesters and co-management boards. A participatory approach to community-based monitoring is recommended, in which whale monitors, Elders, harvesters and youth are equal participants in the documentation and sharing o f beluga TEK. Issues o f data ownership, interpretation o f results and research control must be negotiated in future ecological monitoring in the ISR to ensure the equal distribution o f power in decision­ making. This study clearly shows that harvesters’ observations o f beluga behaviour can quickly be documented following the harvest. The observations made by harvesters offered valuable information about beluga behaviour. This study suggested a possible relationship between observed evasive strategies and Hg exposure; therefore, the link between specific behaviour during harvesting and Hg exposure should be studied further. Beluga harvesters have a unique ability to observe whale behaviour during the hunt, and these observations could be documented and compared to contaminant exposure and other parameters in future studies. Further inclusion o f TEK and local observations o f beluga whales in monitoring programs will improve our understanding o f how environmental change may affect beluga whales from the eastern Beaufort Sea beluga population. Beluga whales in the Beaufort Sea face many challenges associated with increased shipping, offshore oil and gas exploration, climate change and contaminants exposure. A community based participatory research approach would facilitate co-learning and would 174 bring together different knowledge-holders to monitor changes in the health o f beluga whales and the ecosystem to which they belong. A collaborative and community-based approach can guide the ethical and respectful inclusion o f TEK in monitoring programs. Research partnerships should continue to be developed to bridge TSK and TEK to monitor the effects o f environmental change on beluga health at individual and population levels. 175 Acknowledgem ents This research presents the observations made by Inuvialuit beluga whale harvesters from Tuktoyaktuk in July 2010. We thank the hunters for sharing their knowledge for this research. We thank Frank and Nellie Pokiak for making this research possible by providing continuity in the beluga-sampling program at Hendrickson Island from 2001 to 2013. This study was possible due to funding provided by the Fisheries Joint Management Committee (L. Loseto, S. Ostertag, P. Ross) and NSERC Discovery (HMC). SKO was the recipient o f a NSERC Doctoral award, N asiw ik Doctoral award, NSTP Training Fund and UNBC travel awards. We thank A. Essler, A. Montgomery, S. Krause, A. Krey, and G. Prkachin for assistance in the laboratory, and L. Loseto, M. Noel, D. Sydney, R. Felix, K. Nuyaviak, B. Voudrach, R. Walker, K. Snow, C. Pokiak, J. Pokiak, Inuvialuit hunters, Tuktoyaktuk and Inuvik HTCs, and the DFO for their support in the field. 176 Chapter 7. Conclusions and Recommendations Objectives and Significance The goal of this dissertation was to further our understanding o f the toxicological risk posed by methylmercury (MeHg) exposure for beluga whales in the western Canadian Arctic, through community-based research methods. I worked closely with community research assistants, harvesters and youth to collect high quality samples, while also providing mentoring and training opportunities to northerners. To assess the toxicological risk o f MeHg exposure in harvested beluga whales, I measured total mercury (Hgr), MeHg and labile inorganic Hg (iHgiabiie) in various brain regions o f beluga whales and compared these concentrations to threshold levels. I used a biomarker approach to evaluate if Hg exposure was associated with neurochemical and molecular variation of components from the dopaminergic, y-aminobutyric acid (GABA), glutamatergic and cholinergic signaling pathways. Finally, I documented harvesters’ observations o f beluga whale behaviour and compared the behaviour o f whales with higher than median and lower than median Hg concentrations. The overall hypothesis was that H gj, iHgiabiie and MeHg concentrations would exceed threshold levels, and would be associated with behavioural, neurochemical and/or molecular variation, if MeHg exposure was of toxicological concern for this population o f beluga whales. The overarching goals o f this research and the Hendrickson Island Beluga Study were to carry out respectful and inclusive research in the Inuvialuit Settlement Region that would increase research capacity, respond to community concerns and questions, and develop research partnerships for long-term beluga monitoring in the region. Efforts were made 177 throughout the study period to engage youth, communicate effectively and provide training opportunities for northerners. The efforts made to involve community members and especially youth in the research process fostered good working relationships and strengthened the beluga-monitoring program. This dissertation has direct implications for policies at a regional and international level. In the Inuvialuit Settlement Region, the Fisheries Joint Management Committee is particularly concerned with ensuring that the beluga population is managed to “provide for a harvest that generates the greatest net benefit to the Inuvialuit while ensuring the long-term sustainability o f beluga in the Canadian Beaufort Sea” (FJMC, 2001). Therefore, research that furthers our understanding o f the potential negative impacts o f MeHg exposure in beluga may have management implications. Internationally, there have been increasing efforts to develop a legally-binding treaty on Hg emissions, and governments recently agreed to the text o f a global, legally binding document to reduce mercury emissions. High quality contaminants research carried out in the Arctic and the advocacy of Arctic peoples contributed to the success o f the Stockholm Convention, which regulates the production and use o f 21 organic chemical substances (Watt-Cloutier, 2003). Therefore, expanding our understanding of the potential neurotoxicity o f MeHg exposure in beluga whales will feed into policies to reduce Hg emissions and use. This dissertation represents an extension of previous studies focused on Hg accumulation and distribution in beluga whales from the western Canadian Arctic (Lockhart et al., 2005; Outridge et al., 2002; Outridge et al., 2009; Wagemann et al., 1990; Wagemann et al., 1998). We have expanded on the state o f knowledge of Hg accumulation in the 178 central nervous system (CNS) of beluga whales, and we have provided additional information about the forms o f Hg present in the CNS and the relationship between Hg and selenium accumulation in five brain regions. This dissertation increases our knowledge about how Hg accumulation in beluga whale CNS compares to other taxa, and provides possible explanations for elevated Hg accumulation in the CNS o f beluga whales. To our knowledge, this work represents the first use of neurochemical and molecular biomarkers to assess potential neurotoxicity associated with MeHg exposure in cetaceans. Furthermore, contaminant exposure assessments are rarely, if ever, combined with behavioural studies o f wildlife; therefore, this dissertation provides a unique example o f how behavioural observations can be linked to MeHg exposure studies in beluga whales. This method may be adapted and replicated in situations where hunter-harvested animals are sampled for contaminants analysis. The overall significance o f this work is that it provides the first species-specific analysis o f the potential risk of MeHg exposure for beluga whales. The toxicological risk o f MeHg exposure Mercury exposure thresholds Total Hg concentrations in some beluga whales exceeded thresholds of toxicity reported for humans and primates; therefore, it is possible that Hg exposure in beluga whales from the eastern Beaufort Sea could be associated with neurotoxicity. At least 14% o f the beluga whales had HgT concentrations higher than levels o f observable adverse effect (6.0 mg kg'1 wet weight (ww)) in primates. The concentration of MeHg (range: 0.03 to 179 1.05 mg kg'1ww) was positively associated with Hgx concentration, and was below levels o f observable effect in all animals sampled. The positive association between selenium (Se) and Hgx in all brain regions suggests that Se could play a role in the detoxification o f MeHg in the brain. Neurochemical and molecular variation associated with mercury exposure Total Hg concentrations (1.7 to 113 mg kg'1 dw), MeHg (0.5 - 5.2 mg kg'1 dw) and iHgiabiie (0.6 to 6.7 mg kg*1 dw) in the samples analyzed exceeded the concentrations of Hg associated with neurochemical variation in wild mink (Hgx = 0.27 to 18.84 mg kg'1 dw; MeHg = 0.26 to 13.52 mg kg'1 dw) (Basu et al., 2005a), river otter (Hgx = 0.09 to 14.31 mg kg'1 dw; iHg = 0.00 to 10.65 mg kg'1 dw; organic Hg = 0.08 - 8.54 mg kg'1 dw) (Basu et al., 2005c), polar bear (Hgx = 0.11 to 0.87 mg kg'1 dw) (Basu et al., 2009), common loons (Hgx = 0.2 to 68 mg kg'1 dw) and bald eagles (Hgx = 0.3 to 23 mg kg'1 dw) (Scheuhammer et al., 2008). My findings suggested that G A B A a - R binding was negatively associated with Hg and MeHg concentrations, NMDA-R binding was negatively associated with HgT and and iHgiabiie concentrations (nss), and MAO activity was negatively associated with Hgx, MeHg and iH giabiie concentrations (Table 7.1). Overall, these findings were consistent with results from previous avian and wildlife studies (Basu et al., 2005a; Basu et al., 2007b; Basu et al., 2008; Basu et al., 2007c; Basu et al., 2009; Rutkiewicz et al., 2011; Scheuhammer et al., 2008). The results from our analysis o f relative mRNA transcription levels for target genes for mAChR subtype m l, GABA a-R a2 and NMDA-R 2b were negatively associated with 180 H g x , M e H g and/or iHgiabiie concenterations (Table 7.1). The expression o f mRNA for NMDA-2b and GABAa subunit a2 target genes were positively correlated to receptor binding levels o f the NMDA-R and GABAa-R, respectively. Furthermore, mRNA expression for GABAa subunit a4 was negatively correlated to GABAa receptor binding levels, which could be explained by the lack of binding affinity o f the radioligand used ([3H]-FNP) and the GABAa receptor if it contains the a4 subunit. Selenium co-accumulation with Hgx may provide protective effects for MAO activity and mAChR binding, based on the relationship between Hgx and Ser molar ratio and receptor binding. Futhermore, mRNA expression for mAChR ml was also significantly associated with the molar ratio o f Hgx to Sex. In contrast, the results from the GABA-R or NMDAR binding assays did not indicate a significant relationship between receptor binding and the molar ratio o f Hgx to Sex. Therefore, potential protective effects of Hg and Se co­ accumulation for the glutamatergic and GABAergic signaling pathways were less evident in these studies. To our knowledge, these were the first reported data on neurochemical or molecular variation associated with MeHg exposure in beluga whales, or cetaceans in general. In general, the decrease in receptor binding and mRNA expression for target genes from neurosignaling pathways associated with Hgx, MeHg and/or iHgiabiie concentration may be explained by signaling pathways being downregulated, in response to increased stimulation (Duman et al., 1994). These results suggest that although MeHg is demethylated and possibly detoxified through an interaction with Se, current MeHg 181 exposure may nonetheless be o f toxicological concern for this population o f beluga whales. Table 7.1. Significant predictors (total mercury, Hg; methylmercury, MeHg; labile inorganic H g , iHgiabiie) o f neurochemical and molecular variation in brain tissue from harvested beluga whales. Total Hg MeHg iHgiabiie GABA a-R * h i' - M >s« £u £* NMDA-R * - h i‘ ®n O i ir 3 2 z Muscarinic ACh-R - - - MAO activity hi* h i' hi * ...... GABAa-R a 2 h i’ hi* hi GABA a-R a 4 “ - - NMDA-R 2b “ - h i' Muscarinic AChR ml h i* .... hi* ...... hi* MAO activity _ - - B iom arker u 8 u A so '£ u es s o Q § * p < 0.05 - p > 0.1 Evasive behaviour during hunt and m ercury exposure Behavioural changes associated with Hg toxicosis in one wild river otter were ataxia, scleral injection (red eyes) and lack o f fleeing response (Sleeman et al., 2010). One cat with 16.4 mg kg'1 total Hg from White Dog, ON developed convulsions, ataxia, jumping 182 and circling around (‘dancing’) after it was fed fish entrails from the English River (Takeuchi et al., 1977). Therefore, we would expect a lack of motor coordination (ataxia), convulsions and abnormal behaviour from whales suffering mercury toxicosis. Our findings suggested a possible relationship between beluga whales’ use o f evasive strategies and Hg exposure. Given that the harvesters observed the whales behaving normally during the hunt, it is unlikely that the Hg exposure in the eleven whales analyzed was associated with overt toxicity like that seen in the intoxicated wild river otter and cat studies. However, a larger study would allow further exploration o f the potential effect o f Hg accumulation on beluga behaviour. Beluga harvesters have a unique ability to observe whale behaviour during the hunt, and these observations could be documented and compared to contaminant exposure and other parameters in future studies. Overall, the inclusion o f traditional ecological knowledge and local observations o f beluga whales in monitoring programs would improve our understanding o f how environmental change may affect beluga whales from the eastern Beaufort Sea population. Limitations Assessing the significance o f the relationships between Hg exposure and neurochemical and molecular biomarkers is limited by a number o f factors. Specifically, this study lacked negative controls and had small sample sizes in each sampling year because samples were collected opportunistically from harvested beluga. Furthermore, sampling brain tissue from hunter-harvested whales affected the quality o f samples due to the time between whale death and sampling (~ 20 min to 1 h), the time required to remove the 183 brain from the harvested beluga (~ 30 min), and the additional time to sub-sample the brain tissue (30-60 min). Differences in neurochemistiy and mRNA expression between sampling years may have been due to sample instability over time, differences in Hg exposure between years, differences in age between years, or other differences in whale physiology between years. Other physiological differences in whales that could also impact neurochemistry and mRNA expression were not explored in this study due to limitations in sample size, and the lack o f baseline information about beluga whale physiology and neurological signaling pathways. Community-based research approach The research process relied on collaboration within the research team and with northern partners to sample beluga whales during the field season on Hendrickson Island. Having a multi-disciplinary and multi-institutional team made it possible to have more frequent and extended contact between the team and our northern partners. Fieldwork on Hendrickson Island provided an important interface for the research team and community members from Tuktoyaktuk. During fieldwork, the researchers had the unique opportunity to live at a traditional whaling site and to learn about Inuvialuit culture, traditions, and way o f life. Equally importantly, the researchers could learn first-hand from the local sampling team, youth, whale monitors and harvesters about the value of beluga and other country foods for Inuvialuit health and well-being. Finally, throughout the field season, the researchers were reminded o f the responsibilities and privilege associated sampling and studying beluga whales in the ISR. The research team relied on a number o f strategies to increase connectivity across the worlds o f academia and the Arctic. For example, the team connected to their northern 184 research partners through a diversity o f communication strategies ranging from teleconference and phone calls, emails, research reports and pamphlets. The best way to connect remotely was through emails and phone calls directly to the THTC. The research team also supported the participation o f mentoring students and northern research partners at scientific conferences and workshops in Ottawa, ON, Victoria, BC, and Montreal, QC. The best way for the research team to maintain communication and dialogue with Arctic partners and organizations was through community visits that included meetings, classroom presentations and family visits. Communication During fieldwork, the research team communicated with harvesters about the research that was taking place on Hendrickson Island. Unfortunately due to time restraints, dialogue was generally brief between researchers and harvesters. The intention for organizing a ‘Sharing Knowledge’ results workshop was for the Science Team to present their research findings to community members, provide a place to address and discuss questions from community members about our research, engage youth in learning about belugas and beluga research, and to discuss the future direction o f beluga research/monitoring in the Inuvialuit Settlement Region. Organizing this workshop required an extensive time commitment for the research team and Tuktoyaktuk HTC resource person. This investment by the team and HTC were made due to the sense of responsibility to adequately respond to the community’s questions following a three-year study period and ten-year beluga-monitoring program. The communication event in Tuktoyaktuk succeeded in bringing together diverse knowledge-holders and stakeholders 185 from the Hendrickson Island Beluga Study. The workshop and gatherings provided the opportunities for the research team to answer many o f questions about belugas and beluga health that were raised by harvesters and their families. Following the ‘Sharing Knowledge about Belugas’ workshop, the questions that arose from community members were summarized and the research team prepared answers to these questions. The final report from the Hendrickson Island Beluga Study aimed to present information about beluga whales based on the scientific studies that took place at Hendrickson Island, knowledge gained from the scientific literature and the knowledge held by Inuvialuit in Tuktoyaktuk, NT. The report was then transformed into a photo book using photos from fieldwork, conferences and community meetings, using iPhoto (Apple®). The draft book was sent to northern research partners and the Tuktoyaktuk HTC to receive additional feedback prior to publication. Community input was incorporated into the book and the final book was printed (250 copies) and distributed to harvesters, youth and community organizations in 2013. Conclusions andfuture research The weight-of-evidence from these studies suggests that Hg concentrations are indeed reaching levels associated with sub-clinical changes in neurochemistry in beluga whales from the eastern Beaufort Sea beluga population. Therefore, current MeHg exposure is of toxicological concern for beluga whales from this population. Although the response of beluga whales to MeHg exposure at a physiological and population level remains to be elucidated, further study is warranted to address potential adverse outcomes (e.g., tissue 186 pathologies, behavioural changes, motor impairment) associated with Hg toxicity in this population o f beluga whales. Another stressor that needs to be considered for this population a warming Arctic, which may have detrimental consequences for beluga whales due to increased Hg loading o f the Beaufort Sea from the Mackenzie River (Leitch et al., 2007), changes in ice regimes, decreased availability of food (e.g. Arctic cod), and increased risk o f predation (IPCC, 2007). Climate change may also affect beluga whales and other Arctic marine mammals indirectly, by increasing exposure to ships strikes and noise associated with human activities such as shipping, fishing and industry in the Arctic (Huntington, 2009). To date, harvest levels by subsistence harvesters is sustainable and represents a removal o f less than 0.6% of the estimated population (Harwood and Smith, 2002). Given that beluga whales are unable to change their diet to reduce exposure to MeHg, global efforts are required to reduce emissions o f Hg to protect Arctic beluga whales from MeHg exposure and potential intoxication. Furthermore, continued monitoring of beluga populations is required to ensure that changes in population size or health are documented early and mitigation efforts can be effective if possible. 187 References Abd-Elfattah AS, Shamoo AE. 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Anal Biochem 1997; 253: 162-8. 203 Licence No. 14717 File No. 12 402 846 May 11,2010 2010 Northwest Territories Scientific Research Licence Issued by: Aurora Research Institute - Aurora College Inuvik, Northwest Territories Issued to: Ms. Sonja K O stertag University of Northern British Columbia 3333 University Way Prince George, BC V2N 4Z9 C anada Phone: (250) 960-5676 Fax: (250) 960-5418 Email: ostertag@ unbc.ca Affiliation: University of Northern British Columbia Funding: Fisheries Joint M anagem ent Committee Team Members: Laurie Chan; Gary Stem ; Peter Ross; Marie Noel; S tephen Raverty; Lisa Loseto Title: Linking Neurochemistry to Contaminant Exposure In Belugas of the Mackenzie Delta Objectives: To collect brain sam ples from beluga whales harvested in the ISR for contaminant and brain analyses to establish whether a link exists betw een contam inant exposure and brain chemistry. Dates of data collection: Ju n e 1 5,2010 to August 15,2010 Location: Hendrickson Island (69 d eg rees N, 134 degrees W) 30 km from Tuktoyaktuk Licence No.14717 expires on December 31, 2010 Issued in the Town of Inuvik on May 11,2010 * original signed * Pippa Seccombe-Hett, Director, Aurora Research Institute 206 Appendix 3. Harvester questionnaire/informed consent form Information Letter and Consent Form Neurochemical changes and behavioral effects associated with mercury exposure in beluga whales {Delphinapterus leucas) in the Mackenzie Delta You are invited to participate in a study entitled Neurochemical and behavioral changes associated with mercury exposure in beluga whales (Delphinapterus leucas) in the Mackenzie Delta that is being conducted by Dr. Laurie Chan and his PhD student Sonja Ostertag from the University o f Northern British Columbia (UNBC). This project is part o f Sonja Ostertag’s PhD research in the Natural Resources and Environmental Studies Program at UNBC. The project is supported by the Tuktoyaktuk Hunters and Trappers Committee and is funded by the Natural Sciences and Engineering Research Council o f Canada and the Fisheries Joint Management Committee. Purpose and Objectives Mercury comes to the Canadian Arctic from air pollution. Mercury is toxic to the brain and can affect the health o f wildlife and humans. We want to study the effects of mercury on beluga whales. The objective is to see if a higher level o f mercury in the brain is related to changes in brain chemistry and behavioral changes observed by Inuit hunters. Importance of this Research Results o f this study will help us understand whether pollution is affecting the health o f beluga whales. Participants Selection You are being asked to participate in this study because you have experience in hunting beluga whales and your knowledge o f beluga behavior. What is involved If you agree to voluntarily participate in this research, your participation will include filling out the questionnaire regarding the behavior o f the whale that you harvested today. Inconvenience and risks It will take about 10 minutes to do the questionnaire. associated with completing this questionnaire. There is no perceived risk Benefits The community as a whole may benefit from knowing more about effects o f pollution on an important food source. Your observations provide important information about whether any observed changes in brain chemistry are also linked to unusual or abnormal animal behavior. This study will also help to champion for the control o f pollution. Compensation You will not receive compensation for participating in this study. 208 Voluntary Participation Your participation in this research is voluntary. If you do decide to participate, you may withdraw at any time without any consequences or any explanation. If you do withdraw from the study your responses to the questionnaire will not be used. Anonymity We will record your name in case o f follow up questions but your name will not be linked with any o f the data or presented in any way. Your responses will be linked to the ID of the beluga you harvested only for the analysis of the data. The whale IDs will be changed when we present/report the results o f this study to make sure that your responses cannot be linked to you. Confidentiality We will destroy the record o f your participation within one year. During this year, your name record will be kept in a locked file cabinet in Dr. Chan’s office. Dissemination of results Results of this study will be shared with the community and regional contaminants committee before being published in scientific reports and conference presentations. Disposal of Data In 2015, written interviews will be shredded and in 2020, the electronic version will be erased. Contacts If you have any questions, you can contact Sonja Ostertag at 250 960 5676 or ostertag@unbc.ca, or her supervisor Dr. Laurie Chan at 250 960 5237 or lchan@unbc.ca at any time. If you have any complaints, you may contact the Human Research Ethics Office at the University o f Northern British Columbia (Office o f research, Ethics Coordinator Debbie Krebs, phone 250 960 5650, email krebsd@unbc.ca) any time. Consent I understand the procedures described above. My questions have been answered to my satisfaction, and I agree to participate in this study. I have been given a copy o f this form. Printed Name o f Subject Signature of Subject Date Signature of Witness Date Please retain a copy o f this letter fo r your reference. 209 Questions for Beluga H unters Beluga ID ____________ Date When did you first start hunting whales? Driver:____ Hunter:_____________________ Weather Conditions: Hunting Conditions 1. How were the weather conditions for hunting today? excellent good fair poor 2. How does harvesting whales now compare with earlier this season? Harvesting this whale 3. How did this beluga act when you were hunting it? 4. How does that compare with other belugas you have hunted? 5. Did you find that it took more less the same amount o f time to harpoon this whale compared to other whales? Why do you think it took__________ time to harvest this whale compared to others? Behaviour 6. How would you describe this whale’s behaviour? 7. Was there anything unusual about this whale’s behaviour? Yes No Unsure 210 Appendix 5. Job application and contract for mentoring students Application: Field Assistant on Hendrickson Island Job Description □ 3 : □ D □ 3 Participate in the beluga health research program taking place in th e ISR A ssist with beluga sampling on Hendrickson Island from July 1 ** to July 20th Leam about hum an activities that could affect beluga health Initiate your own project of interest Participate in cam p m aintenance an d logistics o n Hendrickson Island E ngage youth back in Tuktoyaktuk and the ISR in beluga research Earn $100/day if this is your first time working on th e bel uga research team , $150/day if you have previous research experience. G Travel to university/government labs to leam about sam ple preparation and analysis (optional) □ Attend a conferences in th e fall/winter 2010 (optional) Phone Number: N am e:_____________________________ Why do you w ant this jo b ? ________________________________ How often do you go cam ping? Frequently S o m etim es Are you currently in: High School College Are you interested in research ? YES NO Rarely Never University Other: Have you helped research ers before? YES NO Have you worked with children/youth? YES NO Do you w ant to attend college or university? YES NO W hat are your future g o a ls ? ___________________________________________________________ Please contact Marie Noel (250-363-6414) or Rebecca Pokiak if you have any questions 215 Project Description The Beluga Health R esearch Program aim s to bring together scientists and local knowledge-holders to study the health of the Eastern Beaufort beluga population. The research team is com posed of scientists, graduate students and local researchers from Tuktoyaktuk who will share their knowledge of beluga health. As in the past several years, a group of researchers will be on Hendrickson Island this sum m er to collect beluga sam ples. We are interested in studying the possible effects of contam inant exposure on beluga health. W e will collect sam ples of blubber, blood, liver, brains, reproductive units and diseased tissues from harvested belugas. S am ples will be analyzed in university and government labs in BC and Manitoba. A research team led by Myma and R ebecca Pokiak will be collecting information from hunters and their families in Tuktoyaktuk to leam about belugas and their health. We would like to hire one or two students, between the ages of 16 and 29 to work with us this summer. In addition to field experience, there may also be opportunities to travel to our labs and to conferences in the fall/winter 2010/2011. R esea rch Team Dr. S te p h e n Raverty is a veterinarian from the animal health care center in BC. He will collect sam ples for the asse ssm e n t of illness and disease in the harvested whales. S onja O stertag is a PhD candidate at the University of Northern British Columbia, Prince George. S he will collect brains to evaluate the effects of contam inants on brain chemistry. Marie Noel is a PhD candidate at the University of Victoria and will collect the blood of belugas to examine their health. F rank an d Nellie Pokiak are participants of a monitoring program for Fisheries and O ceans Canada. They sam ple tissue for contam inants and record their observations. M ym a and R eb ec ca Pokiak are leading a research program in Tuktoyaktuk to gather knowledge from residents about beluga w hales and their health. 216 Beluga Health Research Team Student Employment Agreement This Agreement made between the following two parties as o f ______________ (Date) BETWEEN: (Student funded by Sharing Knowledge on Belugas and Beluga Health Team) And (Representative [Sonja Ostertag] for Sharing Knowledge on Belugas and Beluga Health Team) The two parties agree to the following arrangem ent from June 30, 2010 to July 20, 2010 : The student will: 1. Assist and participate in all sampling activities taking place on Hendrickson Island between June 30 and July 20 (weather dependent) 2. Assist with camp duties including cooking, washing dishes and camp clean up 3. Carry out an independent project with guidance from the research team 4. Be available to work at any time of the day or night to sample whales 5. Remain on Hendrickson Island between June 30 and July 20 (weather dependent) unless there is a family emergency or the agreement has been terminated The Beluga Health Research Team (Marie Noel, Sonja Ostertag, Stephen Raverty, Lisa Loseto) will: 1. Mentor and teach the student the sampling procedures 2. Provide guidance on designing and carrying out the independent project with the student 3. Provide a safe and supportive learning environment to the student 4. Provide transportation to and from Hendrickson Island If th e student a t any tim e does not agree to th e term s of this agreem ent, the contract can be term inated. By signing below, both individuals agree to the arrangements of this agreem ent. (Student) (Date) (Representative [Sonja Ostertag] (Date) (Witness) (Date) 217