the sublethal effects of cu exposure on the osmoregulatory and swimming performance in ... ·...

The sublethal effects of Cu exposure on the osmoregulatory and swimming performance in juvenile rainbow trout (Oncorhynchus mykiss)

by Sydney Alexandra Sherwood Love

B.Sc., Simon Fraser University, 2011

Project Submitted in Partial Fulfillment of the

Requirements for the Degree of

Master of Environmental Toxicology

in the

Department of Biological Sciences

Faculty of Science

© Sydney Alexandra Sherwood Love 2016

SIMON FRASER UNIVERSITY Spring 2016

ii

Approval

Name: Sydney Alexandra Sherwood Love

Degree: Master of Environmental Toxicology

Title: The sublethal effects of Cu exposure on the osmoregulatory and swimming performance in juvenile rainbow trout (Oncorhynchus mykiss)

Examining Committee: Chair: Dr. David LankAdjunct Professor

Dr. Christopher KennedySenior SupervisorProfessor

Dr. Timothy BeischlagSupervisorAssociate ProfessorFaculty of Health Sciences

Dr. Vicki MarlattInternal ExaminerAssistant Professor

Date Defended/Approved: April 21, 2016

Ethics Statement

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iv

Abstract

Cu is a widely occurring contaminant in aquatic systems and is acutely toxic to fish. The

current paradigm of copper’s toxic mechanism of action in fish is believed to be through

direct effects on several important functions of the teleost gill; therefore experiments

were conducted to examine Cu effects on the osmoregulatory ability and swimming

performance of juvenile rainbow trout (Oncorhynchus mykiss) in water of varying

hardness. Fish were exposed to three Cu concentrations (0, 20 and 60 µg/L in hard

water [100 mg/L CaCO3], and 0, 6 and 16 µg/L in soft water [6 mg/L CaCO3]), for 4, 8

and 16 d and then tested for their ability to osmoregulate and burst swim. Burst

swimming speed (Uburst) was not different between control and Cu-exposed fish in either

soft or hard water. Osmoregulatory ability following Cu exposure was examined through

several biochemical measurements related to osmoregulation and a seawater challenge.

Cu exposure did not elicit a change in any osmoregulatory-related measurement or

result in mortalities during the seawater challenge. These results indicate that the

current paradigm of Cu toxicity may not reflect the mechanism of sublethal Cu toxicity or

that compensatory mechanisms are offsetting major physiological disturbances caused

by Cu, at concentrations that are near those which typically cause mortality in salmonids.

Keywords: Rainbow trout; copper; sublethal toxicity; swimming performance; Uburst; osmoregulation

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Dedication

To Pam, Ernie and Avis for their continued support and

encouragement.

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Acknowledgements

First and foremost I would like to thank my senior supervisor, Dr. Chris Kennedy for his

guidance and support throughout this degree. Thank you also to Dr. Tim Beischlag for

his advice and encouragement as a member of my committee. Thanks also to Dr.

Heather Osachoff who was integral in involving me in this research project. This project

was funded by a S.T.A.G.E. grant to Environment Canada at the Pacific Environmental

Science Center (P.E.S.C.), and Dr. Kennedy.

Thank you to all the people at P.E.S.C. – Graham van Aggelen, Rachel Skirrow, Joy

Bruno, Craig Buday, – for their support and assistance with this project. Thanks also to

Bruce Leighton of SFU for keeping my fish alive, healthy and happy. Some analyses

took place in Dr. Colin Brauner’s lab at UBC, so thanks to Dr. Brauner and his PhD

student Mike Sackville for helping me out. Thank you to Dr. Carl Schwarz for his

assistance with my statistical analyses. Thank you to all my Kennedy lab-mates, both

former and present for their support, especially Heather Osachoff, Lindsay Du Gas,

Francine Venturini, Bonnie Lo and Ryan Lebek. A number of volunteers need thanks, as

this project couldn’t have been completed without them: Eric Tseung, Melanie Pylatuk,

Ashton Wickramaratne, Kathryn Marshall and Anup Sangha

Thank you to my parents, Pam Sherwood and Dr. Ernie Love and nana, Avis Sherwood,

for their continuous support throughout my education. In the process, I’m sure they’ve

learned more about fish than they would like. My study buddy Gabby has always known

when I needed to take a writing break and clear my head. Thanks to all my friends for

sticking by my side through this process, especially Alex Dibnah, Laura Hayes, and

Raime and Martha Fronstin. Last but not least, thanks to Ryan Lebek for all his support,

love and laughter.

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Table of Contents

Approval ............................................................................................................................. ii Ethics Statement ............................................................................................................... iii Abstract ............................................................................................................................. iv Dedication .......................................................................................................................... v Acknowledgements ........................................................................................................... vi Table of Contents ............................................................................................................. vii List of Tables ..................................................................................................................... ix List of Figures .................................................................................................................... x List of Acronyms and Abbreviations ................................................................................ xiii

Chapter 1. General Introduction ................................................................................. 1 1.1. The chemistry of Cu ................................................................................................. 1 1.2. Sources .................................................................................................................... 2 1.3. Environmental concentrations .................................................................................. 2 1.4. Cu chemistry in water............................................................................................... 3 1.5. Cu bioavailability and modifying factors ................................................................... 3 1.6. Toxicokinetics ........................................................................................................... 6 1.7. Mechanism of action .............................................................................................. 10 1.8. Acute toxicity .......................................................................................................... 11 1.9. Sublethal toxicity .................................................................................................... 14 1.10. Sublethal endpoints ............................................................................................... 17 1.11. Research objectives ............................................................................................... 19

Chapter 2. Materials and Methods ............................................................................ 20 2.1. Chemicals .............................................................................................................. 20 2.2. Fish ........................................................................................................................ 20 2.3. Acute toxicity tests ................................................................................................. 21 2.4. Sublethal Cu exposures ......................................................................................... 21 2.5. Cu exposures for swim experiments ...................................................................... 22 2.6. Swim performance protocol ................................................................................... 23 2.7. Seawater challenge ............................................................................................... 24 2.8. Osmoregulatory indicators ..................................................................................... 25 2.9. Calculations and statistics ...................................................................................... 26

Chapter 3. Results ..................................................................................................... 28 3.1. General .................................................................................................................. 28 3.2. LC50 determinations .............................................................................................. 28 3.3. Swimming performance ......................................................................................... 30 3.4. Osmoregulation ...................................................................................................... 31

3.4.1. Gill Na+/K+-ATPase (NKA) activity ............................................................. 31 3.4.2. Plasma ion concentrations and osmolality ................................................ 33 3.4.3. Seawater challenge ................................................................................... 37

3.5. Biochemical stress response ................................................................................. 37

viii

Chapter 4. Discussion ............................................................................................... 41

Chapter 5. Conclusion and Future Directions ......................................................... 51

References .................................................................................................................. 53

ix

List of Tables

Table 1.1. Summary of LC50 values across a range of species. N/A indicates information not available. Relatable indicates whether study is relevant to the present research (based on duration, life stage and other variables). (Modified from: Eisler, 2000) ....................................... 12

Table 2.1. Summary of off-site well water parameters (analyte concentration, water quality measurements). Values are mean ± SEM. ....................... 22

x

List of Figures

Figure 1.1. Schematic diagram of the biotic ligand model (From: Di Toro et al, 2001) ......................................................................................................... 6

Figure 1.2. Schematic diagram of Cu uptake in a teleost gill cell. CR = copper reductase, ENaC = epithelial Na+ channel, NHE3 = Na+/H+ antiporter, Na-K pump = Na+/K+-ATPase, CTR1 = copper transporter 1, GN = golgi network, MC = metallochaperone, MBP = metal binding protein. (Image courtesy of Ryan Lebek, adapted from: Bury et al., 2003 & Parker and Boron, 2013). .................................. 8

Figure 2.1 Schematic representation of the swim tunnel apparatus (From: Mackinnon and Farrell, 1992). ................................................................. 24

Figure 3.1 Mortality (%) of fish exposed to different Cu concentrations after 96 h, in hard water (A) and soft water (B). Mean values reported. N=10 ........................................................................................................ 29

Figure 3.2 Burst swimming speed (BL/s) of fish exposed to Cu. 4, 8 and 16 refers to days of Cu exposure, H = hard water (100 mg/L CaCO3), S = soft water (6 mg/L CaCO3). Low Cu treatments are 6 and 20 µg/L Cu in soft and hard water, respectively. High Cu treatments are 16 and 60 µg/L Cu in soft and hard water, respectively. Box indicates 25th and 75th quartiles, whiskers indicate 10th and 90th percentiles. Medians are indicated by a black line and means are indicated by a +. N=1 for each treatment group. Treatments connected by the same letter are not significantly different (p < 0.05). Tukey’s multiple comparisons test was used to determine differences between treatment groups. ................................................... 31

Figure 3.3 Gill Na+/K+-ATPase activity (µmole ADP/mg protein/h) of fish exposed to Cu. 4, 8 and 16 refers to days of Cu exposure, H = hard water (100 mg/L CaCO3), S = soft water (6 mg/L CaCO3). Low Cu treatments are 6 and 20 µg/L Cu in soft and hard water, respectively. High Cu treatments are 16 and 60 µg/L Cu in soft and hard water, respectively. Box indicates 25th and 75th quartiles, whiskers indicate 10th and 90th percentiles. Medians are indicated by a black line and means are indicated by a +. N=2 for each treatment group. Treatments connected by the same letter are not significantly different (p < 0.05). Tukey’s multiple comparisons test was used to determine differences between treatment groups. ....... 33

xi

Figure 3.4 Plasma Cl- concentration (mmol/L) of fish exposed to Cu. 4, 8 and 16 refers to days of Cu exposure, H = hard water (100 mg/L CaCO3), S = soft water (6 mg/L CaCO3). Low Cu treatments are 6 and 20 µg/L Cu in soft and hard water, respectively. High Cu treatments are 16 and 60 µg/L Cu in soft and hard water, respectively. Box indicates 25th and 75th quartiles, whiskers indicate 10th and 90th percentiles. Medians are indicated by a black line and means are indicated by +. N=2 for each treatment group. Treatments connected by the same letter are not significantly different (p < 0.05). Student’s t-test was used to determine differences between treatment groups. .................................. 34

Figure 3.5 Plasma Na+ ion concentration (mmol/L) of fish exposed to Cu. 4, 8 and 16 refers to days of Cu exposure, H = hard water (100 mg/L CaCO3), S = soft water (6 mg/L CaCO3). Low Cu treatments are 6 and 20 µg/L Cu in soft and hard water, respectively. High Cu treatments are 16 and 60 µg/L Cu in soft and hard water, respectively. Box indicates 25th and 75th quartiles, whiskers indicate 10th and 90th percentiles. Medians are indicated by a black line and means are indicated by a +. N=2 for each treatment group. Treatments connected by the same letter are not significantly different (p < 0.05). Tukey’s multiple comparisons test was used to determine differences between treatment groups. ....... 36

Figure 3.6 Plasma osmolality (mmol/kg) of fish exposed to Cu. 4, 8 and 16 refers to days of Cu exposure, H = hard water (100 mg/L CaCO3), S = soft water (6 mg/L CaCO3). Low Cu treatments are 6 and 20 µg/L Cu in soft and hard water, respectively. High Cu treatments are 16 and 60 µg/L Cu in soft and hard water, respectively. Box indicates 25th and 75th quartiles, whiskers indicate 10th and 90th percentiles. Medians are indicated by a black line and means are indicated by a +. N=2 for each treatment group. Treatments connected by the same letter are not significantly different (p < 0.05). Student’s t-test was used to determine differences between treatment groups. .................................................................................... 37

Figure 3.7 Hematocrit (%) in fish exposed to Cu. 4, 8 and 16 refers to days of Cu exposure, H = hard water (100 mg/L CaCO3), S = soft water (6 mg/L CaCO3). Low Cu treatments are 6 and 20 µg/L Cu in soft and hard water, respectively. High Cu treatments are 16 and 60 µg/L Cu in soft and hard water, respectively. Box indicates 25th and 75th quartiles, whiskers indicate 10th and 90th percentiles. Medians are indicated by a black line and means are indicated by a +. N=2 for each treatment group. Treatments connected by the same letter are not significantly different (p < 0.05). ............................... 38

xii

Figure 3.8 Plasma cortisol concentration (ng/ml) of fish exposed to Cu. 4, 8 and 16 refers to days of Cu exposure, H = hard water (100 mg/L CaCO3), S = soft water (6 mg/L CaCO3). Low Cu treatments are 6 and 20 µg/L Cu in soft and hard water, respectively. High Cu treatments are 16 and 60 µg/L Cu in soft and hard water, respectively. Box indicates 25th and 75th quartiles, whiskers indicate 10th and 90th percentiles. Medians are indicated by a black line and means are indicated by a +. N=2 for each treatment group. Treatments connected by the same letter are not significantly different (p < 0.05). Tukey’s multiple comparisons test was used to determine differences between treatment groups. ....... 40

xiii

List of Acronyms and Abbreviations

m month

w week

d day

h hour

min minute

s second

L liter

LC 50 lethal concentration to 50% of test subject

NKA Na+/K+-ATPase

SFU Simon Fraser University

SEM standard error of the mean

Cu copper

1

Chapter 1.

General Introduction

1.1. The chemistry of Cu

Metals can be classified as being either essential or nonessential. Nonessential

metals have no known biological role and include tin (Sn), aluminum (Al), cadmium (Cd),

mercury (Hg) and lead (Pb). For these metals, an increase in concentration corresponds

to an increase in toxicity. The essential metals have a known biological function and

include copper (Cu), zinc (Zn) and iron (Fe) (Kennedy, 2011). Essential metals are

incorporated into various proteins and participate in redox reactions (Vaishaly et al.,

2015). They are required at low concentration, and deficiencies can result in adverse

outcomes. At elevated concentrations these metals can be extremely toxic (Hassan,

2011). Metals can also be classified as either light or heavy (exceeding 50-Da molecular

weight), and can be further categorized with respect to their toxicity and essentiality.

Class A heavy metals are essential at high concentrations (e.g. Fe) and class B heavy

metals are nonessential and are nontoxic at low concentrations (e.g. strontium [Sr]).

Class C metals are essential though toxic at high concentrations (e.g. Cu, Zn), and

Class D metals are nonessential and toxic at low concentrations (e.g. Hg and Pb)

(Kennedy, 2011).

Copper is a heavy metal with a molecular mass of 63.54. It is a transition metal

found in Group 1B on the periodic table, existing in four oxidation states (Cu0, Cu1+, Cu2+,

Cu3+) with Cu2+ being the most common (CCME, 1997). Elemental copper (Cu0) is not

oxidized in water, and cuprous copper (Cu1+) only exists in water when involved in a

complex (Schroeder et al., 1966, Aaseth and Nortseth, 1986). The cupric ion (Cu2+) is

the ion most commonly found in water, and the trivalent ion (Cu3+) does not occur

2

naturally (Schroeder et al., 1966, ATSDR, 1990, Georgopoulos and Roy, 2001, Cuppett

et al., 2006).

1.2. Sources

Cu is naturally occurring and a widespread element, found in many minerals and

as an uncombined metal (Eisler, 2000). The weathering, oxidation and bacterial

breakdown of Cu minerals primarily release Cu2+ into the environment (Flemming and

Trevors, 1989, Georgopoulos and Roy, 2001). The input of Cu into aquatic systems has

increased drastically due to anthropogenic use; freshwater systems can be heavily

impacted by industrial discharges and the dissolution of Cu from bedrock (Nriagu, 1979,

Buhl and Hamilton, 1990, Martin and Goldblatt, 2007). Sources of industrial discharge

include mining, smelting, and the production of leather, textiles, electrical equipment and

plumbing fixtures (Spry et al., 1981, Patterson et al., 1998, ATSDR, 1990, Morrissey and

Edds, 1994). Residential sources release Cu into aquatic systems as well, primarily via

storm water runoff (Davis et al., 2001, McIntyre et al., 2012). This release arises through

Cu use in break pads, roofing material, and pesticide and fertilizer formulations used in

agriculture (Alva et al., 1995, Eisler, 2000).

1.3. Environmental concentrations

Cu is naturally present in freshwater systems in concentrations ranging from 0.2

to 30 µg/L, though rarely exceeding 5 µg/L (Bowen, 1985). Due to anthropogenic use,

Cu concentrations have been reported that greatly exceed background levels.

Freshwater systems receiving anthropogenic input have reported concentrations ranging

from background to 100 µg/L, although areas of urban and highway runoff can reach

concentrations as high as 200 µg/L (Davis et al., 2001, WHO, 2004, Martin and

Goldblatt, 2007). In areas of extreme contamination (e.g. mining areas), concentrations

up to 200 mg/L have been reported (Rock et al., 1985, Davis and Ashenberg, 1989).

3

1.4. Cu chemistry in water

In freshwater systems, free Cu is primarily found in its most stable state, as the

cupric ion (Cu2+), which can form complexes with many other compounds. It may

associate with water to form the aquo ion [Cu(H2O)6]2+, with organic or inorganic ligands,

or adsorb onto organic particulates (e.g. humic and fulvic acids), clays and sediments

(Spear and Pierce, 1979, Eisler, 2000, Georgopoulos and Roy, 2001). The majority of

Cu in waterbodies partitions to sediments, with Cu binding being dependent primarily on

particle size, although the type of sediment and redox potential are also important

(Singleton, 1987). Fine-grained sediments typically contain a higher Cu concentration

than coarse-grained sediments, due to the larger surface area of small particulates

(Stancil, 1980, Erickson et al., 1996)

In freshwater, Cu solubility is modified by pH, hardness and temperature (Nriagu,

1979). Under acidic conditions (pH < 5.0) the cupric ion (Cu2+) is the major species

present, and as water pH decreases, Cu carbamates (e.g. CuCO3, Cu(CO3)22-) and

copper hydroxides (eg. CuOH+) predominate (Spear and Pierce, 1979). The chemical

form of Cu in freshwater is crucial for determining the toxicity of Cu to organisms as the

cupric ion and Cu hydroxyl species are highly toxic to aquatic life, while the carbonate

species (e.g. CuHCO3+, CuCO3, Cu(CO3)2

-) are far less toxic (Meador, 1991).

1.5. Cu bioavailability and modifying factors

The toxicity of a metal is dependent on its potential to be taken up from the

environment and the resulting internal dose. Metal uptake rates and accumulation is

concentration-dependent and varies with metal species and their properties.

Bioavailability is defined as the fraction of a chemical that is transferred from the

environment into an organism, making it available for distribution to target tissues and

organs (USEPA, 2003a; USEPA, 2007). The differing uptake rates of each Cu species

will affect Cu bioavailability and resulting accumulations at target sites vary accordingly.

As well, the environmental concentrations of other metals or compounds that share the

same uptake mechanism or surface membrane target sites can result in competition and

reduce uptake, and therefore modify toxicity.

4

The properties of water (including pH and temperature) can affect Cu solubility,

uptake, and toxicity. Several other physical and chemical characteristics of water may

also affect Cu bioavailability and toxicity, and include alkalinity and the concentrations of

dissolved organic carbon compounds, suspended particulates, and inorganic cations

and anions (including those that contribute to water hardness (Meador, 1991). Of these,

pH is the most important for Cu speciation (Meador, 1991). The effect of pH on

speciation is due to Cu’s interaction with hydrogen ions (Peterson et al., 1984).

Concentrations of free Cu decrease roughly by one order of magnitude for every 0.5

increase in pH above pH 6 (Stumm and Morgan, 1981, Meador, 1991). Increasing

dissolved organic carbon (DOC) decreases Cu availability due to complexation with the

metal ions (Winner, 1985). Alkalinity has also been shown to decrease Cu bioavailability

(Chakoumakos et al., 1979). Research shows that Cu bound to organic ligands is not

bioavailable, therefore Cu toxicity is attributed to dissolved forms of Cu that are present

in the aquatic environment (Sprague, 1968, Chakoumakos et al., 1979, Erickson et al.,

1996, Eisler, 2000).

Water hardness is a measure of dissolved polyvalent metallic ions, primarily

calcium and magnesium, though strontium, manganese, iron and barium can also

contribute (USEPA, 1976). Hardness is usually expressed as the concentration of

calcium carbonate (CaCO3) in the solution. In harder waters, Ca2+ ions can be at

concentrations that outcompete metals for binding sites on the gills (one of the primary

uptake sites in fish), thus affecting their bioavailability and uptake of metals (Laurén and

McDonald, 1986, Saglam et al., 2013).

The biotic ligand model (BLM) has been used to predict the bioavailability of

metals and their accumulation at target sites, by taking into account the major factors

that affect metal bioavailability including DOC concentrations and water hardness. As

will be addressed in the section below on mechanism of action, the gills are the primary

target site of Cu toxicity and the site of the BLM. The BLM is derived from two earlier

models, the free-ion-activity model ([FIAM] Morel, 1983), and the gill surface interaction

model ([GSIM] Pagenkopf, 1983) (USEPA, 2003b). The FIAM states that the chemical

activity of the aquo ion of a given metal is a better predictor of its toxicity than the total

dissolved concentration. This model is considered limited as it does not take

5

interactions between organic and inorganic complexes and the biotic ligand into account

(Meyer et al., 2007). The GSIM estimates the concentration of a metal that accumulates

on the gill surface based on the competitive binding of various cations (e.g. Ca2+, Mg2+,

H+) (Meyer et al., 2007). The BLM integrates components from these two earlier models

and is generally based on the hypothesis that metal bioavailability is not only determined

by the total metal concentration, but is related to the physical and chemical properties of

the water that affect the metal bioavailability at the target site (Di Toro et al, 2001).

Metal toxicity is a result of free metal ions interacting with binding sites in the target

tissue (i.e. the gill surface). Organic (e.g. DOC) and inorganic (e.g. OH+, HCO3+ and Cl+)

complexes can form with metals and render them inert, and cations (e.g. Ca2+ and H+)

can compete with free metal ions for binding at the target sites (Figure 1.1).

6

Figure 1.1. Schematic diagram of the biotic ligand model (From: Di Toro et al,

2001)

1.6. Toxicokinetics

By acting as a cofactor for numerous proteins, Cu is an essential heavy metal

and is required in low concentrations, within the range of 1 to 4 mg Cu/kg (dry mass) in

teleost fish (Lanno et al., 1985b, Bury et al., 2003). At elevated concentrations, Cu is a

potent toxicant, and so body Cu concentrations are subject to tight homeostatic control

to prevent both deficiency and toxicity (Kamunde et al., 2002b).

Teleost fish, including rainbow trout, can obtain Cu either from their diet or from

water. Metals are present in their diet since they can be incorporated in prey organisms

(i.e. as metals bound in proteins or other organic molecules such as chitin) (Bryan, 1976;

Clearwater, et al., 2002). The uptake of Cu by teleosts following dietary exposure

occurs across the pyloric caecae and intestines (Handy et al., 1999). The molecular

mechanism of uptake has not been elucidated, however evidence supports its similarity

with that which occurs in mammalian systems (Handy, 1996; Handy et al., 2000).

2384 Environ. Toxicol. Chem. 20, 2001 D.M. Di Toro et al.

Fig. 1. Schematic diagram of the biotic ligand model.

with organic and inorganic ligands, as shown in the following.Of course, no way exists to verify directly which chemicalspecies are bioavailable. All one can do is to examine whetherthe consequences of these hypotheses agree with observations.It is for this reason that we concentrate on comparing predictedand observed toxicity as the test of the model’s utility.The toxicity of metals to organisms is assumed to occur as

the result of free metal ion reacting with the physiologicallyactive binding sites at the site of action. This is representedas the formation of a metal–biotic ligand complex. For fish,the biotic ligand appears to be sites on the surface membraneof the gill [22]. For modeling purposes, the site of action istreated as a biotic ligand—the biological counterpart of chem-ical ligands—to which metals can bind (Fig. 1, right side). Forfish, the metal binding results in the disruption of ionoregu-latory processes of the organism (e.g., sodium transfer acrossthe gill is restricted), which leads to mortality [22].The principal feature that distinguishes the BLM from con-

sidering only the free metal ion as the toxic species is that inthe BLM, the free metal ion competes with other cations (e.g.,Ca21 and H1) for binding at the biotic ligand as shown inFigure 1. As a result, the presence of these cations in solutioncan mitigate toxicity, with the degree of mitigation dependingon their concentrations and the strength of their binding to thebiotic ligand.

Model equations

The BLM is based on the hypothesis that the metal–bioticligand interaction can be represented in the same way as anyother reaction of a metal species with an organic or inorganicligand. Consider a ligand , in this case the biotic ligand,2Lband a divalent metal cation . The charge on the biotic ligand21Mi

is unknown. We assign a negative charge to be definite sinceit binds positive cations. However, this choice has no practicalsignificance. The concentration of the metal-ligand complexMi is determined by the mass action equation1Lb

1 21 2[ML ] 5 K [M ][L ]i b M L i bi b (1)

where is the stability constant for the metal-ligand com-KMLi b

plex and the square brackets denote molar concentration. It isassumed that protonation can also occur with the formation ofa proton biotic ligand complex HLb with concentration [HLb]and stability constant K :HLb

1 2[HL ] 5 K [H ][L ]b HL bb (2)

The mass balance equation associated with the biotic ligandis2Lb

NMi

2 2 1[L ] 5 [L ] 1 [HL ] 1 [M L ] (3)Ob T b b i bi51

where [ ]T is the total binding site density of the biotic ligand2Lb(e.g., nmol of available sites/g of tissue), [HLb] is the con-centration of protonated sites, and is the number of metalNMi

complexes Mi , e.g., Cu , Ca , etc., that form with the1 1 1L L Lb b b

biotic ligand .2LbThe analogous equations for the metal cation and the21M1

other aqueous ligands that form metal-ligand complexes2Ljare

1 21 2[M L ] 5 K [M ][L ] (4)i j M L i ji j

1 2[HL ] 5 K [H ][L ] (5)j HL jj

NMi

2 2 1[L ] 5 [L ] 1 [HL ] 1 [M L ] (6)Oj T j j i ji51

where and are the stability constants for these ligands.K KML HLi j j

The mass balance equations for the metal cations in the so-lution are

NLj21 21 1 1[M ] 5 [M ] 1 [M L ] 1 [M L ] (7)Oi T i i b i j

j51

where is the number of metal-ligand complexes, includingNLjhydroxyl complexes, that forms.21Mi

The quantity of metal bound to the biotic ligand [Mi ] is1Lbusually insignificant relative to the aqueous species, unless theconcentration of biota in the experimental vessel is quite large.Therefore Equation 7 becomes

NLj21 21 1[M ] 5 [M ] 1 [M L ] (8)Oi T i i j

j51

The aqueous chemistry speciation equations (Eqns. 4–6, 8)can be solved as discussed below. Then the biotic ligand equa-tions (Eqns. 1–3) can be evaluated. This convenient approachis adopted below.The parameters required that are specific to the BLM are

the conditional stability constants, and i 5 1, . . .K KHL M Lb i b

for the proton and metal biotic ligand complexes (Eqns.NMi

1–2), and the total site density [ ]T (Eqn. 3). For fish, the site2Ljdensities and stability constants are determined on the basisof experimental fish gill measurements. These are currentlyavailable for a number of metals, including copper, cadmium[11,23] and silver [12]. For other organisms, the values areobtained by fitting the model to observed mortality data, asdiscussed below.The model is based on the idea that mortality (or other toxic

effect) occurs if the concentration of metal on the biotic ligandreaches a critical concentration C* :Mi

1C* 5 [ML ]M i bi (9)

This critical concentration for mortality can only be determinedfrom toxicity experiments that establish the LC50 or EC50

7

Potential uptake pathways include entering enterocytes from the mucosal side by a non-

specific, ATP driven metal-ion transporter, DCT1 (Gunshin et al., 1997), a Cu

transporter, CTR1 (Dancis et al., 1994, Zhou and Gitschier, 1997) or by passive diffusion

through Na+ channels (Wapnir, 1991). On the basolateral membrane of enterocytes, a

Cu-ATPase or Cu/anion symporter are thought to be involved in Cu uptake (Harrison

and Dameron, 1999, Handy et al., 2000).

The observation that elevated aqueous Cu concentrations leads to increased Cu

concentrations in the gills provided the first evidence that the gills served as a Cu uptake

route (Buckley et al., 1982). Prior to transport across membranes, Cu2+ is reduced to

Cu+, potentially via a copper reductase (Bury et al., 2003). Grosell and Wood (2002)

identified two apical branchial uptake mechanisms in rainbow trout: a Na+-sensitive and

a Na+-insensitive pathway. Data suggests that Cu shares a similar uptake pathway as

Na+ since elevated aqueous Cu concentrations also results in impaired branchial Na+

uptake (via the Na+-sensitive pathway (Laurén and McDonald, 1985). This occurs

through an epithelial Na+ channel (ENaC) or an H+-ATPase-coupled Na+ (NHE3) channel

(Fenwick et al., 1999; Fig 1.2). This pathway is likely as Cu uptake is reduced following

the administration of phenamil, a known ENaC inhibitor (Kleymann and Cragoe, 1988).

Additionally, silver (Ag+), a known Cu analogue is taken up into fish by the apical Na+

pathway, further supporting the Na+-sensitive pathway (Bury and Wood, 1999). Na+-

insensitive uptake is due to a high-affinity Cu importer, the Ctr family of proteins (Grosell

and Wood, 2002). After entering epithelial cells, Cu can bind with metallochaperones,

bringing it to the Golgi network. Cu is then incorporated into metal binding proteins and

brought to the basolateral membrane for release into plasma via exocytosis (Bury et al.,

2003). On the basolateral membrane, if Cu remains free (i.e. doesn’t enter the

aforementioned pathway in the Golgi), Cu enters the interstitial fluid via Na+/K+-ATPase

(NKA) pumps (Wood, 2001)

8

Figure 1.2. Schematic diagram of Cu uptake in a teleost gill cell. CR = copper

reductase, ENaC = epithelial Na+ channel, NHE3 = Na+/H+ antiporter, Na-K pump = Na+/K+-ATPase, CTR1 = copper transporter 1, GN = golgi network, MC = metallochaperone, MBP = metal binding protein. (Image courtesy of Ryan Lebek, adapted from: Bury et al., 2003 & Parker and Boron, 2013).

Following uptake, Cu is transported in plasma bound to either ceruloplasmin, a

plasma protein that binds tightly and with high affinity to Cu, or albumin and other Cu

binding amino acids, which bind less tightly and are believed to transport Cu from uptake

sites (Gubbler et al., 1953; Marceau and Aspin, 1973; Grosell et al., 1998). In fish the

liver is the primary organ involved in Cu homeostasis (Grosell et al., 2000; Kamunde et

al., 2002a). The liver accumulates Cu absorbed from either dietary or branchial

!

NHE3

ENaC

Tight Junction

Interstitial Fluid Water

Gill Cell (Trout)

Cu2+

CR!

Cu+

Na+

(Cu+) H+

Na+

(Cu+)

CTR1!H+

Cu+

3 Na+

(Cu+)

Na(K!pump!

2 K+

GN

MC!

Cu+

Cu!MBP!

Cu!MBP!

9

exposure, and is the site of ceruloplasmin synthesis (Bury et al., 2003). The

accumulation of Cu in internal organs varies with the route of exposure and Cu

concentration (Clearwater et al., 2002). Dietary uptake initially results in accumulation in

the intestines and liver, and eventually (after 3 d to 1 w) is found throughout the body.

The highest concentrations are reported in the intestines, liver and gall bladder (in bile)

and in lower concentration in the gills, muscle tissue and kidney (Lanno et al., 1985a;

Clearwater et al., 2000; Kamunde et al., 2001). Waterborne Cu entering through the

gills achieve higher Cu concentrations in the gills and are lower throughout the

gastrointestinal (GI) tract (Clearwater et al., 2002).

Detoxification mechanisms for Cu primarily involve inducing metallothioneins,

allowing long-term retention after absorption without eliciting a toxic effect (Harrison,

1986; Carbonell and Tarazona, 1994). Metallothioneins (MT) are metal binding proteins

that help to regulate free metal ion concentrations by binding with essential metals such

as Cu and Zn. An increase in intracellular metal concentration induces MT production to

allow for binding and sequestration of excess metals (above essential concentrations)

(De Boeck et al., 2003). Differing capacities of MT induction is one potential explanation

for the varying tolerance to metals in fish (Olsson and Kille, 1997). As the liver is the

major detoxification organ in fish, it accumulates the highest levels of MTs in the body

(Hauser-Davis et al., 2014).

Fecal and hepatobiliary excretion are the two primary routes for Cu elimination in

fish, though branchial and renal excretion also occur (Clearwater et al., 2002). Within

the intestines, free Cu increases mucus production. This was determined using everted

gut sacs; when Cu was added to the incubation media, mucus production increased and

sloughed off the tissue (Handy et al., 2000). Mucus can complex with Cu, essentially

“trapping it” and allowing for fecal elimination (Clearwater et al., 2002). Handy et al.

(2000) found approximately 76% of Cu formed complexes with mucus. Cu exposure

increases the turnover rate and apoptosis of enterocytes, increasing the number of cells

sloughing off in the GI tract, possibly to increase fecal elimination in fish (Kamunde et al.,

2001). While renal excretion in fish does occur, the loss of Cu via urine is much lower

than in bile (Grosell et al., 1988). Research by Grosell et al. (2001) showed that some

Cu may also be lost via the gills, although the mechanism is still unknown.

10

1.7. Mechanism of action

As explained above, Cu is essential for cellular metabolism at low

concentrations, but at higher concentrations is extremely toxic (Hassan, 2011). The

specific toxic mechanism of action of Cu, however, is not fully elucidated. In general,

metals affect the respiratory and osmoregulatory (i.e. water and ion balance) systems of

teleost fish at both the physiological and biochemical levels, with the gills being the

primary target organ (Beaumont et al, 1995; Mazon, 2002; Saglam et al, 2013). This

occurs through physical changes to the gill epithelia and by affecting the activity of ion

ATPases (Laurén and McDonald, 1985; Wilson and Taylor, 1993a; Beaumont et al,

1995).

Gills are particularly vulnerable to waterborne pollutants that can cause

significant structural changes to the epithelial cells. Both epithelial cells and mucocytes

(mucus producing cells) of trout can undergo hyperplasia (cell proliferation) following

metal exposure (Beaumont et al., 2003). Mucus production is a general defence

mechanism against heavy metal exposure, as the mucus binds to metals and decreases

their rate of diffusion across the gills (Pärt and Lock, 1983; De Boeck et al., 1995).

Additionally, epithelial cells may swell and lift off the basement membrane, in addition to

the fusion or curling of gill lamellae upon exposure to metals such as Cu (Wilson and

Taylor, 1993a; Karan et al., 1998; Beaumont et al., 2003). Epithelial lifting and

hyperplasia are thought to be general defense mechanisms, increasing the diffusion

distance between aqueous toxicants and the blood (Karan et al., 1998). Lamellar fusion

and curling is likely due to heavy metal cations disrupting the charges on glycoproteins

located in the plasma membrane causing attraction between cells of adjacent lamellae

(Daoust et al., 1984). While hypothesized to be a general defense mechanism this is

likely a toxic effect from metal exposure. These effects all serve to disrupt the gill’s

effectiveness as a gas and ion exchange organ, through increasing the gas diffusion

distances and decreasing the rate of oxygen uptake (De Boeck et al., 2006). This can

be exacerbated during periods of exercise; Cu exposure (50-250 mg/L CaCO3) results in

reduced oxygen consumption (from 30-60% reduction) during swimming performance

trials in trout (Beaumont et al., 2003, McKenzie et al., 2003, De Boeck et al., 2006)

11

As previously mentioned, Cu shares an uptake pathway with Na+; it acts as a Na+

analogue and can out-compete Na+ for Na+/K+-ATPase transports that are found in the

both the gills and GI tract of fish including rainbow trout (Clearwater et al., 2002, De

Boeck et al, 2007). Disruption of Na+/K+-ATPase transports following Cu exposure

reduces ion uptake in freshwater fish. The opposite occurs in saltwater fish where Cu

exposure causes an increase in ion uptake resulting in ionoregulatory (i.e. ion balance)

failure (Wood, 2001, Grosell et al., 2002, Grosell et al., 2004). Cu exposure primarily

affects Na+ homeostasis via the disruption ion transporters; Na+ and Cl- influx is inhibited

in fresh water fish, including rainbow trout (Grosell et al., 2002, Taylor et al, 2003).

Chronically impaired ion transporters from Cu exposure are unable to maintain Na+

homeostasis, which can result in ionoregulatory failure. This involves reduced ion

concentrations decreasing plasma volume (and therefore it’s viscosity), which decreases

oxygen transport and heart rates, which can eventually lead to death (species include

rainbow trout and fathead minnows [Pimephales promelasI]) (Reid and McDonald, 1991,

Wilson and Taylor, 1993a, Kolok et al., 2002).

1.8. Acute toxicity

Cu is acutely toxic to fish, with LC50 values typically ranging from 10-1000 µg/L

(Eisler, 2000). This broad range of values is due to biotic factors (e.g. age, species and

size) and abiotic factors related to water quality (e.g. hardness, pH, DOC, temperature)

(Spear and Pierce, 1979, Pilgaard et al., 1994, Gensemer et al., 2002). In soft

freshwater, Cu is most acutely toxic with LC50 values between 10 and 20 µg/L (NAS

1977). Generally as alkalinity and hardness increase there is a decrease in Cu’s acute

toxicity, as complexes with carbonates are formed or competition with Ca2+ cations for

uptake at the gill occurs (Meyer et al., 2007). As a result, metal exposures in soft water

are more toxic than exposures in hard water. In all the taxonomic groups of fish studied

to date, there is an increase in LC50 values as water hardness increases (Spear and

Pierce, 1979, Laurén and McDonald, 1985). In soft water (30 mg/L CaCO3), the 96-h

LC50 for rainbow trout is between 20 and 30 µg/L (Howarth and Sprague, 1978). The

96-h LC50 rainbow trout exposed to Cu increases as hardness increases; for example

the 96-h LC50 is 90 µg/L in 120 mg/L CaCO3 (Taylor et al., 2000).

12

Cu binds to DOC present in solution, rendering the free metal inert; Cu toxicity

therefore decreases as DOC increases (Brown et al., 1974). Waterborne metals

including Na+ and cobalt can also protect against acute lethal Cu toxicity (Spear and

Pierce, 1979, Marr et al., 1998). Temperature has a variable effect on Cu toxicity.

Cairns et al. (1978) reported an increase in toxicity with a temperature increase from 5 to

30 oC whereas Hansen et al. (2002) reported a decrease in toxicity as temperature

increased (from 8 to 16 oC). Contrary to this, Carvalho and Fernandes (2006) reported

no effect of changing temperature on the acute toxicity of Cu.

Fish species vary in their sensitivity to Cu in acute tests (as measured by LC50

values). Salmonids (e.g. salmon and trout) appear to be the most sensitive, followed by

cyprinids (e.g. carps and minnows); anguillids (e.g. eels), centrarchids (e.g. bass) and

percids (e.g. perch) are the most resistant families of fish (Spear and Pierce, 1979). A

summary table of LC50 values for fish are found below in Table 1.1.

Table 1.1. Summary of LC50 values across a range of species. N/A indicates information not available. Relatable indicates whether study is relevant to the present research (based on duration, life stage and other variables). (Modified from: Eisler, 2000)

Taxonomic group, organism species

Cu concentration of LC50

Duration Life stage/age

Other variables

Relatable Reference

Topsmelt, Atherinops affinis

238 µg/L 96 h Larvae n/a No Anderson et al., 1991

Topsmelt, Atherinops affinis

365 µg/L 7 d Larvae n/a No McNulty et al., 1994

Goldfish, Carassius auratus

36 µg/L 96 h n/a 20 mg/L CaCO3

No USEPA, 1980

Goldfish, Carassius auratus


No USEPA, 1980

Catfish, Clarias sp.

425 µg/L 96 h n/a Nonresistant strain of fish

No Daramola and Oladimeji, 1980

13

African sharp-tooth catfish, Clarias gariepinus

1240 µg/L 96 h Juvenile Between 21-28 oC

No Van der Merwe et al., 1993

Pacific herring, Clupea harengus pallasi

33 µg/L 6 d Embryo n/a No USEPA, 1980

Mummichog, Fundulus heteroclitus

8000 µg/L 96 h n/a n/a No Lin and Dunson, 1993

Brown bullhead, Ictalurus nebulosus

170 µg/L 96 h Juvenile n/a No Brungs et al., 1973

Bluegill, Lepomis macrochirus

1100 µg/L 96 h Larvae n/a No Benoit, 1975

Tidewater silverside, Menidia peninsulae

140 µg/L 96 h Larvae n/a No Mayer, 1987

Striped bass, Morone saxatilis

150 µg/L 96 h Fingerling 68 mg/L CaCO3

No USEPA, 1980

Cutthroat trout, Oncorhynchus clarki


Yes USEPA, 1980

Cutthroat trout, Oncorhynchus clarki


No USEPA, 1980

Coho salmon, Oncorhynchus kisutch

31.9 µg/L 96 h Juvenile n/a Yes Buhl and Hamilton, 1990

Rainbow trout, Oncorhynchus mykiss

13.8 µg/L 96 h Juvenile n/a Yes Buhl and Hamilton, 1990



Yes USEPA, 1980



No USEPA, 1980

Fathead minnow, Pimephales promelas


No USEPA, 1980

14

Winter flounder, Pleuronectes americanus

129 µg/L 96 h Embryo n/a No USEPA, 1980

1.9. Sublethal toxicity

In addition to being acutely toxic to fish, a multitude of effects occur in fish

exposed to sublethal concentrations of Cu. At concentrations as low as 4 µg/L, effects

on growth and metabolism can occur, and at around 10 µg/L reproduction and survival

can be affected in sensitive species (Hodson et al., 1979). Copper has been shown to

reduce disease resistance (Anderson, 1990, Dethloff and Bailey, 1998), alter migration

(Lorz and McPherson, 1977), impair respiration and osmoregulation (Clearwater et al.,

2002, Grosell et al., 2002, Taylor et al, 2003, De Boeck et al, 2007), cause tissue

structure changes to the gills (Wilson and Taylor, 1993a, Karan et al., 1998, Beaumont

et al., 2003), disrupt lateral line mechanoreception (Linbo et al., 2006, Webb at al.,

2014), alter swimming performance (Beaumont et al., 1995, Kolok et al., 2002, Waser et

al., 2009), impair olfaction (Palm and Powell, 2010, McIntyre et al., 2012) and alter blood

chemistry (Christensen et al., 1972, Heath, 1995).

The primary target site of sublethal Cu toxicity fish is the gills, more specifically

the ion transport ATPases (Hansen et al., 1993). As discussed in the section on

mechanisms of action, Cu exposure alters ion homeostasis, primarily via disruption of

the Na+/K+-ATPases. This occurs either by Cu acting as a Na+ analogue and out-

competing Na+ for ATPases, or by Cu binding and inhibiting the ATPase pump (Laurén

and McDonald, 1986, De Boeck et al, 2007). The overall result is an impaired ion

exchange system with altered ion concentrations in fish. As a result of the altered ion

transport activity, Cu exposure in freshwater generally results in decreased plasma

osmolality, decreased plasma ion concentrations (e.g. Na+ and Cl-) and increased

hematocrit. (Lewis and Lewis, 1971, Christensen al., 1972, Courtois, 1976). Hematocrit

is inversely related to plasma volume; a change to plasma ion concentrations can

change plasma volume and therefore hematocrit (Brauner et al., 1994).

15

Fish growth can be used as a sensitive and reliable endpoint in sublethal toxicity

testing, due to decreases in food intake or increases in metabolic demands due to

detoxification processes (De Boeck et al., 1997). Cu exposure has been shown to

decrease appetite and alter energy stores (fat and glycogen), leading to a reduction in

growth in various fish species (Cu exposure concentrations vary based on species)

(Benoit, 1975, Buckley et al., 1982, De Boeck et al., 1997). Additionally, hematological

evaluation of fish blood can provide information about the physiological responses to

changes in the environment. As mentioned, altered plasma ion concentrations are

reported due to Cu’s ability to alter the activity of ion transport pumps. Cu exposure

decreases red blood cell numbers: hemoglobin, mean corpuscular volume (MCV;

average volume of red cells) and can increase white blood cell numbers (McLeay, 1973,

Larsson et al., 1985, Van Vuren et al., 1994). Blood glucose, lactate, bilirubin, urea,

cholesterol and acetylcholine increase in response to Cu exposures (Christensen et al.,

1972, Schrek and Lorz, 1978, Oikari and Nakari, 1982, Nemsock and Hughes, 1988,

Singh and Reddy, 1990, Heath, 1995). The mechanism underlying the alteration of

energy stores and haematological parameters is not fully elucidated to date. It is likely

due to the release of stress hormones including cortisol, inducing the secondary stress

response to provide physiological compensation during periods of stress, including Cu

exposure (Mazeaud et al., 1977, MacFarlane and Benville, 1986, De Boeck et al., 1997).

Activities reliant on swimming performance include migration, prey capture,

spawning, predator avoidance and maintenance of position in a current (Nikl & Farrel,

1993, Reidy et al., 1995). The effects of Cu on critical swimming speed is well

documented in many fish species including rainbow trout, brown trout and fathead

minnows (Beaumont et al., 1995, Kolok et al., 2002, Waser et al., 2009). Exposure to Cu

results in a significant reduction in maximum and sustained swimming speeds, which is

hypothesized to be caused by alterations to the gill structure or an increase in

ammonium production (Beaumont et al., 1995, Beaumont et al., 2003, van Heerden et

al., 2004, De Boeck et al., 2006).

Cu can also affect the peripheral olfactory system; olfactory neurons are

continuously exposed to water and are therefore highly vulnerable to contaminants

(McIntyre et al., 2012). Scent detection in fish is important as chemical cues released

16

either by conspecifics or other organisms can be crucial to survival, including the

detection of food, conspecific alarm scents or predator presence (Beyers and Farmer,

2001, Baldwin et al., 2003, Palm and Powell, 2010). In addition, Cu can interfere with

fish migration by either disrupting their ability to detect their natal stream or altering the

odour of the stream (Hasler and Scholtz, 1983).

Cu can affect the immune system of fish. Cu has been show to increase

infection and death rates by suppressing resistance to both viral and bacterial pathogens

(Hetrick et al., 1979, Rougier et al., 1992, Rougier et al., 1994). Fish exposed to 40 µg/L

Cu required fewer pathogens to induce a fatal infection (Baker et al., 1983).

Macrophage function including phagocytosis is affected, impairing the first line of

defense against foreign matter in the body (Secombes and Fletcher, 1992). The effects

on blastogenic (i.e. increase in number) and antibody-production response of

lymphyocytes (i.e. white blood cells) is mixed (Cu range of 5-30 µg/L), with both

increases and decreases reported, affecting the magnitude of humoral and cell-mediated

immunity (Khangarot and Tripathi, 1991, Roche and Boge, 1993, Dethloff and Bailey,

1998). The mechanism has not been elucidated to date.

The lateral line is a sensory organ that receives and integrates environmental

stimuli (e.g. water flow and pressure changes) (Webb, 2014). It is comprised of

neuromasts that have the mechanosensory hair cells, containing cilia to detect water

movement (Webb, 2014). Exposure to low Cu concentrations (10-635 µg/L) for short

durations (3 h) is reported to be toxic to hair cells (Hernandez et al., 2006, Linbo et al.,

2006). Initially the number of hair cells diminishes, followed by complete elimination of

all hair cells; at higher concentrations the accessory cells and regeneration ability of

neuromasts are also compromised (Hernández et al., 2006, Linbo et al., 2006, Linbo et

al., 2009). Other metals do not elicit similar effects to the lateral line, so it appears to be

particularly susceptible to Cu exposure (Hernandez et al., 2006). The information

provided by the lateral line is used for prey acquisition, predator avoidance and

schooling behaviours including navigation and communication: destruction of the hair

cells can have profound effects (Webb, 2014).

17

There is limited data, and with mixed results, relating Cu exposure to

reproductive endpoints, though generally reproductive success decreases. In one study,

during a 22 min exposure, concentrations of 32.5 µg/L affected the number of viable

eggs produced and hatchability in the brook trout (Salvelinus fontinalis). Cu

concentrations of 17 µg/L affected the survival and growth of alevins and juvenile trout,

and adult survival and growth was diminished at 32.5 µg/L (McKim and Benoit, 1971).

This is supported by research by Hodson et al. (1979) who reported effects on survival

and reproduction at 20 µg/L. Another study conducted over two generations in brook

trout reported no effects on reproductive endpoints at Cu concentrations up to 9.4 µg/L

(McKim and Benoit, 1974). During a chronic exposure (22 months) spawning success

measured as number of eggs of adult bluegill (Lepomis macrochirus) was reduced to 0

(no eggs survived) at 162 µg/L Cu (Benoit, 1975).

1.10. Sublethal endpoints

Sublethal effects of pollutants can be detected using various endpoints including

those at higher levels of biological organization such as swim performance and

behaviour (Beaumont et al., 1995). While not detected in standard acute toxicity tests

(e.g. LC50), sublethal toxicity can have severe effects on a fish’s ability to perform

essential life functions (e.g. swim, procure food, avoid predators and reproduce), which

can then affect survival at the population level (Smith and Weis, 1997). Whole animal

assays are useful for detecting sublethal effects of stressors as they may integrate

multiple physiological systems; effects on any subcomponent may result in changes in

whole animal performance.

Swimming performance has been widely used to detect the sublethal effects of

environmental contaminants (Beaumont et al., 1995, Jain et al., 1998, Kolok et al., 2002,

Tierney et al., 2007, Waser et al., 2009, Goulding et al., 2013). It can be studied

relatively easily in lab using a swim tunnel to measure swimming speed. Swimming

performance is organized into three categories: sustained, prolonged or burst, and

various exercise protocols have been established to evaluate each type of swimming.

These typically measure the swimming speed achieved within a set interval of time (min

or h) after experiencing water velocity changes (Hammer, 1995, Plaut, 2001). Sustained

18

swimming is the velocity that a fish can maintain for a long period of time (>200 min) and

is typically used for foraging and migration behaviour, as these only require low

velocities. Sustained swimming is measured as the maximum speed sustained or Umax

(Sepulveda and Dickson, 2000). Prolonged swimming is shorter in duration than

sustained swimming and is the most commonly studied (Brett, 1964). A common

measure of prolonged swimming is critical swimming speed (Ucrit) (Brauner et al., 1994,

Reidy et al., 1995, MacNutt et al., 2004, Kennedy and Farrell, 2006, Farrell, 2008).

Sustained and critical swimming speed have been extensively used, particularly with

salmonids, to assess the impact of environmental factors including ammonia, crude oil,

hypoxia, pesticides, metals, pulp and paper effluents, and temperature (Brett and Glass,

1973, Beamish, 1978, Waiwood and Beamish, 1978, Kumaraguru and Beamish, 1981,

Thomas and Rice, 1987, Nikl et al., 1993, Beaumont et al., 1995, Kennedy et al., 1995,

Shingles et al., 2001, Kolok et al., 2002, Wicks et al., 2002, Kennedy and Farrell, 2006,

Landman et al., 2006, Waser et al., 2009, Goulding et al., 2013, Yu et al., 2015).

Burst swimming is the maximum velocity a fish can maintain for a short period of

time, involving rapid sprint swimming (Nadeau et al., 2009). It is typically used for

predator avoidance and catching prey and typically lasts for up to 20 s. Burst swimming

uses anaerobic metabolism and results in fatigue for the fish. These swimming assays

involve a constant acceleration in the test chamber and measure the burst swimming

speed (Uburst) (Reidy et al., 1995, Pedersen & Malte, 2004, Farrell, 2008, Pedersen et al.,

2008, Nadeau et al., 2009). Far less research has been conducted assessing the

impact of environmental factors using burst swimming as the endpoint. Contaminants

studied to date include ammonia, pesticides, temperature and xenoestrogens

(Tudorache et al., 2010, Goulding et al., 2013, Osachoff et al., 2014).

As described in detail earlier (Mechanism of Action), the gill epithelium is the

primary osmoregulatory organ in fish, with the gastrointestinal tract and kidneys also

contributing (Wendelaar Bonga and Lock, 2008). Freshwater fish absorb ions from

water at the gills, reduce ion loss by decreasing paracellular ion movement at the gills

and absorb ions at the kidneys to reduce ion loss via urine (Evans et al., 2005). Gills are

composed of a variety of cell types, though the mitochondrion-rich (MR) cells (e.g.

chloride cells) are directly involved in osmoregulation. These cells are associated with

19

ion uptake in fish as they are the location of ion transport proteins on both the apical and

basolateral membranes (Chang et al., 2001, Hwang and Lee, 2007). Exposure to

toxicants can damage MR cell integrity (structural changes, necrosis) or alter ion

transport protein function, which can be detected using protein activity assays

(Wendelaar Bonga and Lock, 2008). Disrupted ion transporters can disturb ion

permeability, which will eventually lead to alterations in plasma ion levels and osmolality

(Wendelaar Bonga and Lock, 2008). Changes to ion ATPases (e.g. Na+/K+-ATPase

and Ca2+-ATPase) and plasma ion concentrations have been demonstrated in many fish

species following exposure to metals and other contaminants including: ammonia,

pesticides, polycyclic aromatic hydrocarbons, pulp and paper mill effluents and

xenoestrogens (Davis and Wedemeyer, 1971, Dangé, 1986, Laurén and McDonald,

1987, Schoenmakers et al., 1992, Pratap and Wendelaar Bonga, 1993, Twitchen and

Eddy, 1994, Tuvikene, 1995, Li et al., 1998, Berntssen et al., 1999, Pane et al., 2003,

Rogers et al., 2003, Matsuo et al., 2004, Parvez et al., 2006, Lerner et al., 2007, Firat et

al., 2011).

1.11. Research objectives

The overall aim of this study was to further examine the effects of Cu on

osmoregulation and swimming performance in rainbow trout. While the effects of Cu on

critical swimming speed in several species has been examined, its effects on burst

swimming have not been investigated. The importance of water quality to Cu toxicity

suggests that a link between alterations in swimming performance and osmoregulation

will exist. Endpoints at both the biochemical and whole animal levels of organization

were selected to assess these relationships. Juvenile rainbow trout were selected due

to increased species and life stage sensitivity to Cu exposure. As well, experiments

were performed to examine the effects of exposure duration on the magnitude of Cu

toxicity.

20

Chapter 2. Materials and Methods

2.1. Chemicals

Copper chloride (CuCl2 . 2H2O) was purchased from Thermo Fisher Scientific

(Mississauga, ON) and the various salts used to synthetically harden water (CaSO4 . ½

H2O; CaCl2; MgCl2 . 6H2O; KCl, NaCl, NaHCO3) were purchased from Sigma-Aldrich;

(Oakville, ON). Ferric nitrate (Fe(NO3)3) and mercuric thiocyanate (Hg(SCN)2) for

plasma chloride assays were purchased from Sigma-Aldrich (Oakville, ON). Sodium

deoxycholate, lactate dehydrogenase, pyruvate kinase, phosphoenolpyruvate, NADH,

ATP, ouabain and ADP were purchased from Sigma-Aldrich (Oakville, ON). Tricaine

methanesulfonate (MS222) was purchased from Syndel International Inc. (Vancouver,

BC).

2.2. Fish

Juvenile rainbow trout (Onchorhynchus. mykiss) with a fork length of 11.34 ±

0.07 cm (mean ± SEM) and a mass of 16.35 ± 0.35 g of mixed sex in an undetermined

ratio were obtained from Miracle Springs Hatchery (Mission, BC). Fish were maintained

in 500 L tanks, on a 12 h light:12 h dark photoperiod, supplied with dechlorinated

municipal water (oxygen saturation > 90%, water hardness 6.3 mg/L CaCO3 and pH

~7.0 ± 0.2) at 8 ± 1 oC. Fish were acclimated for a minimum of 2 weeks prior to starting

any experiment. Fish were fed ad libitum daily but were fasted for approximately 24 h

prior to use. Fish use and experimental protocols were approved by the Simon Fraser

University Animal Care Committee in accordance with Canadian Council on Animal Care

(CCAC) guidelines.

21

2.3. Acute toxicity tests

An initial 96-h LC50 test was conducted following the Environment Canada

protocol (EPS 1/RM/9, 1990) to determine the sublethal Cu concentrations for use in

subsequent experiments. Exposures were conducted in 170 L aerated fiberglass tanks

on a 12 h light:12 h dark photoperiod, and fish acclimated for approximately 24 h in the

exposure tanks in either hard or soft water prior to the addition of CuCl2. Fish (n=10) in

each treatment were exposed in duplicate tanks (n=5 per tank) to a range of Cu

concentrations in both hard (100 mg/L CaCO3, 0, 12.5, 25, 50, 100, 200, 250, 300 µg/L

Cu) and soft water (6 mg/L CaCO3, 0, 6.25, 12.5, 25, 50, 100 µg/L Cu). Fish mortality

was recorded at 5, 10, 20, 40, 80, 160 m, and 24, 48, 72 and 96 h. Water quality was

measured at the beginning and end of exposure (pH, D.O., temperature and

conductivity). LC50 values were calculated using CETIS (Tidepool Scientific Software)

and mortality vs. concentration curves were generated using GraphPad Prism version

5.0

2.4. Sublethal Cu exposures

All sublethal Cu treatments were conducted in duplicate (including controls) as

static renewal exposures in 170 L aerated fiberglass tanks. Exposures were conducted

in either soft or artificially hardened water. Municipal dechlorinated water with a baseline

hardness of 6 mg/L CaCO3 was used as the soft water. Salts were added to

dechlorinated municipal water to attain a value of 100 mg/L CaCO3 for the artificially

hardened water. Salts (CaSO4 ½ H2O; CaCl2; MgCl2 6H2O; KCl, NaCl, NaHCO3) were

dissolved in deionized water, before being added to municipal dechlorinated water to

achieve the appropriate hardness values. The water was hardened using this

methodology to match off-site well water used for studies done in collaboration with

Environment Canada (Pacific Environmental Science Centre [PESC], North Vancouver,

BC). A summary table of the well water parameters from PESC is found in Table 2.1.

Fish were acclimated for 24 h in exposure tanks in either hard or soft water prior to the

addition of CuCl2. Water samples were taken to measure water hardness and Cu

concentrations in the artificially hardened water and water analyses were conducted at

PESC. Water quality measurements (temperature, pH, dissolved oxygen and

22

conductivity) were measured at the start and end of an exposure in each tank.

Dissolved oxygen (D.O.) and temperature were measured using an oxygen meter (YSI

58 Dissolved Oxygen Meter, Yellow Springs, OH), pH with a pH pen (S96275B, Fisher

Science Education, Mississauga, ON) and conductivity with a pocket conductivity meter

(Oakton ECTestr 11 dual range, Vernon Hills, IL).

Table 2.1. Summary of off-site well water parameters (analyte concentration, water quality measurements). Values are mean ± SEM.

Well Water Parameter Value Chloride (Cl-) 94 ± 5 mg/L

Sulphate (SO42-) 7.9 ± 0.5 mg/L

Calcium (Ca2+) 36.7 ± 0.1 mg/L

Magnesium (Mg2+) 3.1 ± 0.1 mg/L

Potassium (K+) 3.7 ± 0.1 mg/L

Sodium (Na+) 44 ± 0.1 mg/L

Overall Hardness 100 ± 0.5 mg/L CaCO3

Conductivity 468.33 ± 1.83 µS

pH 7.73 ± 0.04

Temperature 14.65 ± 0.07 oC

2.5. Cu exposures for swim experiments

Fish (n=16 per treatment group) were exposed to one of three CuCl2

concentrations: control, low (15% of the 96-h LC50 concentration) or high (40% of the

96-h LC50 concentration). Nominal low and high concentrations in hard water were 20

and 60 µg/L, and soft water concentrations were 6 and 16 µg/L, respectively. Exposures

were 4, 8 and 16 d in duration. For the 8 and 16 d exposures, 50% of water was

renewed every 4 d (Report EPS 1/RM/44, 2004) without disturbing the fish. Water was

replaced with water of the appropriate hardness and CuCl2 concentrations for each

treatment.

23

2.6. Swim performance protocol

The swim tunnel apparatus used to measure swim performance (burst swimming

speed, or Uburst) was similar to that described in Mackinnon and Farrell (1992). It

consisted of a 2400 L fiberglass oval raceway containing an enclosed test chamber

along the long axis (Figure 2.1). A condensing cone directed water into the test chamber

which contained fish, and flow vanes at either curved end of the raceway maintained the

appropriate water velocities and laminar flow within the test chamber. Two electric

motors (Minn-Kota Endura C2-40, Poco Marine Ltd., Port Coquitlam, BC) were used to

generate the water current. These were connected to a voltage regulator to control the

velocity of the water in the raceway. The water level of the swim tunnel was maintained

at a constant volume and temperature (11.9 ± 0.1oC). Calibration curves for voltage vs.

water velocity were generated before each test using a current meter (Forestry Suppliers

Inc., Jackson, MI).

Following Cu exposure, fish were transferred to the test chamber in the swim

tunnel and acclimated for 20 min at a water speed of 10 cm/s (approximately 1 body

length per second (BL/s)) (Farrell, 2008). The burst-swimming test (Uburst) consisted of 1

m stepwise water velocity increments of 5 cm/s (~0.5 BL/s) until fish were fatigued

(Farrell, 2008, Nendick et al., 2009). Fish were considered fatigued when they rested on

the rear net of the test chamber and did not respond to mechanical stimulation. Once

fatigued, fish were removed and euthanized in 0.5 g/L buffered MS222. Fork length (LF)

and mass (M) of each fatigued fish were then measured.

24

Figure 2.1 Schematic representation of the swim tunnel apparatus (From:

Mackinnon and Farrell, 1992).

2.7. Seawater challenge

Fish were exposed to Cu in either soft or hard water for 4 or 16 d at 3 Cu

concentrations (control, low and high) as described above. At the end of the exposure

period, n = 14 fish per treatment were subjected to a seawater challenge measuring

mortality, and n = 10 fish were used for biochemical measures of osmoregulation and

stress.

For the seawater challenge, fish (n=14 per exposure treatment) were placed in

duplicate tanks containing 170 L seawater at 28 ppt (Bills and Kenworthy, 1986). The

seawater challenge occurred over 24 h; at the end of this period, fish mortality was

recorded. The remaining fish were euthanized in 0.5 g/L buffered MS222. Fork length

(LF) and mass (M) were measured for all fish.

1544 D.L. MACKINNON AND A.P. FARRELL

V O L T A G E R E G U L A T O R

ELECTRIC MOTOR

‘TESTING CHAMBER

Fig. 2. Diagrammatic representation of the apparatus used for examining critical swimming speed in fish.

tial preexposure period for all exposure concentrations. Characteristic circadian rhythms were apparent in all groups (Fig. 1).

The mean oxygen consumption rate of 91 mg O2 per kilogram per hour (SE = 1.7) for the carrier solution was not significantly different from the control, although a slight elevation of 102 mg O2 per kilogram per hour (SE = 2.9) did occur during the 0- to 24-h postexposure interval. Neither TCMTB nor the carrier compound exhibited significant chemical oxygen demand at 20 pg/L in the vessels without fish. One mortality occurred within the 20-pg/L TCMTB group at 46 h into the expo-

Table 1 . Measured TCMTB concentrations in water samples collected from treatment vessels containing

various nominal concentrations of TCTMB

Nominal concn Measured concn ( P d L ) (mean k SE, pg/L)

20 15 10 7.5 5 0

20.0 * 2.0 18.5 k 3.5 14.5 k 4.5 9.5 k 2.5 9.0 % 3.0

<5a

“HPLC detection limit for TCMTB = 5 pg/L.

sure. There was no significant change in the control oxygen consumption rate during the final three 24-h periods of the experiment.

In all treatment groups, the first exposure period (0-24 h) had a lower oxygen consumption rate than its paired preexposure value, although this effect was statistically significant only at 5 and 20 pg/L (Table 2) . During the second exposure period (24-48 h), oxygen consumption either remained at this low level (7.5 and 20 pg/L), showed a further decrease (15 pg/L), or increased to or above the preexposure level (5 and 10 pg/L). Thus, at lower TCMTB concentrations (5-10 pg/L), recovery was possible after an initially reduced oxygen consumption rate. At TCMTB concentrations 2 15 pg/L, oxygen consumption was depressed throughout the exposure period. A simple concentration-dependent change in oxygen consumption was not apparent.

Four out of five preexposure values for treatment groups were significantly lower than the control preexposure values (Table 2) . This intergroup variability also is reflected in the finding that the majority of the postexposure values for treatment groups were lower than the corresponding postexposure control values.

Significant elevations in plasma lactate were observed in all treatment groups exposed at and above 7.5 pg/L TCMTB (Fig. 3). Lactate levels reached

25

2.8. Osmoregulatory indicators

At the end of the Cu exposure period, n = 10 fish per exposure treatment were

euthanized in buffered MS222 and blood and gill tissue were sampled. To obtain

plasma, the caudal peduncle was severed (Congleton and LaVoie, 2001) and blood was

collected in heparinized capillary tubes (Chase Scientific Glass, Inc., Rockwood, TN).

Blood was centrifuged for 3 min in a microcapillary centrifuge (International Equipment

Company, Chattanooga, TN) at 13000 x g. Hematocrit was measured in duplicate and

plasma was then separated and placed in 1.5 mL centrifuge tubes and stored on dry ice

until being transferred to -80 oC for future analysis.

Gill filaments (10-15 filaments per sample) were collected in duplicate from the

left side and placed in 1.5 mL capillary tubes containing 125 µL SEI buffer (150 mM

sucrose, 10 mM EDTA, 50 mM imidazole, pH 7.3; McCormick, 1993). Two stainless

steel 2 mm beads (Retsch, Newtown, PA) were added to the tube and stored on dry ice

until they were transferred to -80 oC. These samples were later analyzed for gill Na+/K+-

ATPase (NKA) activity.

Plasma samples were measured in duplicate for osmolality, sodium ion (Na+),

chloride ion (Cl-) and cortisol concentrations. Osmolality was measured using a vapor

pressure osmometer, which measures the concentration of particles that reduce the

vapour pressure of a solution (Wescor Vapro 5520, EliTech Group, Logan, UT). Plasma

[Na+] was determined in duplicate using flame photometry on a Varian AA240FS Atomic

Absorption Spectrometer (Palo Alto, CA). Flame photometry is an atomic emission

method to determine the concentration of metal salts. Solutions are aspirated into a

flame, which causes the metals to atomize, and electrons to excite to a higher and

unstable energy state. The subsequent return to a stable energy state emits light at a

specific wavelength for each element, with light intensity being proportional to

concentration of the element in solution (Overman and Davis, 1947). Plasma [Cl-] was

measured in triplicate following the protocol in Osachoff et al. (2014). Chloride

concentration is determined via competition between Hg2+ and Fe2+ for 2,4,6-Tris(2-

pyridyl)-s-triazine (TPTZ). In the presence of Cl-, Hg2+ complexes to form HgCl2,

allowing Fe2+ to complex with TPTZ. While the Hg-TPTZ complex is colourless, Fe-

26

TPTZ results in a colorimetric product that is proportional to the concentration of Cl-

present and can be measured on a spectrophotometric plate reader. Cortisol

concentration was measured in duplicate using an ELISA (enzyme-linked

immunosorbent assay) kit (Neogen Corp., Lansing, MI). Cortisol competes with an

enzyme conjugate for binding sites on the plate, and the plate is subsequently washed to

remove any unbound materials. A substrate is added which binds to the enzyme

conjugate to generate a colour (inversely proportional to cortisol concentration), which

can be read on a spectrophotometric plate reader.

Gill NKA activity was determined following the protocol of McCormick (1993),

with the exception that gill homogenates were prepared using a bead mill homogenizer

(Mixer Mill 300; Qiagen, Mississauga, ON) set to a program of 20 Hz for 30 seconds.

Each sample was homogenized twice. Briefly, each gill samples (containing 10-15

filaments) was homogenized in SEID buffer (100 mL of SEI buffer with 0.5 g of

deoxycholic acid) and centrifuged (5000 x g) for 30 s. Each sample was analyzed in

microplates, with two sets of duplicates; the first set contained the assay mixture (4

U/mL lactate dehydrogenase, 5 U/mL pyruvate kinase, 2.8 mM phosphoenolpyruvate,

0.7 mM ATP, 0.22 mM NADH, 50 mM imidazole), and the second contained the assay

mixture with ouabain (0.5 mM). Microplates were read as a kinetic assay, every 30 s

over a 10 min period. For each sample, the difference in slopes between the two sets,

and standardized for protein content using a BCA protein assay kit (Thermo Fisher

Scientific, Mississauga, ON) resulted in the final ATPase activity, expressed as µmoles

ADP/mg protein/h. Plates for assays were read using a Bio-tek PowerWave Reader

(Bio-Tek, Winooski, VT) at the wavelength specified in the protocols. Standard curves

were run concurrently on each plate (R2 > 0.97).

2.9. Calculations and statistics

LC50 values were calculated via probit conversion followed by linear regression

in CETIS (Tidepool Scientific Software, v1.8.4). The percent mortality is converted to

probits (probability units) and the concentrations are log transformed. Plotting probits vs.

log concentrations transforms the sigmoid mortality curve to a linear relationship, to

which a regression line can be fit for calculation of the LC50 value. The Uburst water

27

velocity (the velocity fish fatigued at) for each fish was standardized by dividing by the

fish fork length, resulting in a final fatigue velocity in body lengths per second (BL/s)

(Goulding et al., 2013). To ensure overall fish health, condition factor (K) was calculated

using: 100 x (M ÷ LF3), with M = mass (g) and LF = fork length (cm). Graphs were

constructed using GraphPad Prism version 5.0 and statistical analyses were performed

using JMP version 10. For each endpoint, the statistical analyses were conducted on

the mean values from each exposure tank. Analysis for effects of Cu, duration of

exposure and water hardness (and their interactions) was performed using a three-factor

ANOVA. This was followed by Tukey’s multiple comparisons test (≥2 comparisons) or

Student’s t-test (1 comparison) to compare between treatments. Statistical significance

was set at p < 0.05. Grubbs’ test was used to detect and remove outliers (GraphPad

Software Inc., La Jolla, CA, USA). Coefficient of variation (CV) between duplicates

<20% were deemed acceptable (Reed et al., 2002). All data are presented as mean ±

standard error of the mean (SEM), with the number of fish (n) noted.

28

Chapter 3. Results

3.1. General

The water temperature in the exposure tanks was 11.8 ± 0.09 oC, dissolved

oxygen was 10.4 ± 0.04 mg/L and pH was 7.5 ± 0.03. Tanks with soft water had a

conductivity of 9.5 ± 0.76 µS, and 436.8 ± 3.63 µS in hard water. The water hardness

and concentration Cu in hard water exposures were measured. Artificially hardened

water had a nominal concentration of 100 mg/L CaCO3 and measured average

concentration of 108.40 ± 0.76 mg/L CaCO3. Control exposure water had an average

Cu concentration of 1.02 ± 0.18 µg/L, due to background Cu in municipal water. Low Cu

treatment water had a nominal target concentration of 20 µg/L Cu in hard water, and an

average measured concentration of 20.00 ± 1.70 µg/L Cu. High Cu treatment water had

a nominal target concentration of 60 µg/L Cu in hard water, and an average measured

concentration of 58.93 ± 3.36 µg/L Cu.

Condition factor (K), a general measure of fish health, was not significantly

different between exposed and control fish at any time point (p = 0.2012). In most cases

sample size was equal across treatments, however experimental conditions affected

sample size between groups. In swim trials, fish (≤2 fish per trial) escaped from the

swim chamber, could not be retrieved and were therefore not included in data analysis.

3.2. LC50 determinations

The 96-h LC50 values for the exposure conditions in this study, calculated by

probit analysis, were 40 and 150 µg/L Cu, for soft (6 mg/L CaCO3) and hard (100 mg/L

29

CaCO3) respectively. The mortality curves showing the average percent mortality at

each Cu concentration for hard and soft water are found in Fig 3.1

Figure 3.1 Mortality (%) of fish exposed to different Cu concentrations after 96

h, in hard water (A) and soft water (B). Mean values reported. N=10

0 100 200 3000

50

100

A)

Concentration (µg/L)

Mo

rta

lity (%

)

0 50 1000

50

100

B)

Concentration (µg/L)

Mo

rta

lity (%

)

30

3.3. Swimming performance

Burst swimming performance (Uburst) is the maximum velocity a fish can maintain

over a short period of time, and was assessed following Cu exposure using a swim

tunnel according to the methods of Osachoff et al. (2014). Juvenile fish (n=16 per

treatment; due to tank effects: n=1 for analyses) were exposed to either control

(municipal dechlorinated water), low (6 and 20 µg/L in soft [6 mg/L CaCO3] and hard

water [100 mg/L CaCO3], respectively) or high (16 and 60 µg/L in soft and hard water,

respectively) Cu concentrations for 4, 8 or 16 d.

Across all treatment groups, Uburst values ranged from 6.13 ± 0.11 to 7.53 ± 0.14

BL/s. Exposure to Cu did not alter burst swimming speed in any treatment group (p =

0.1120), therefore Cu treatment groups were pooled together for all further comparisons

of the effects of water hardness and exposure duration on Uburst values (Fig 3.2). The

duration of exposure, regardless of water hardness had no significant effect on Uburst (p =

0.2960). Uburst values at 4, 8 and 16 d of exposures were 6.88 ± 0.05, 6.75 ± 0.05 and

6.86 ± 0.05 BL/s, respectively. There was an interaction between the duration of

exposure and water hardness (p = 0.0011). Burst swimming speed for 4 d exposures

were significantly higher in soft water (7.43 ± 0.07 BL/s) compared to hard water (6.33 ±

0.07 BL/s; p = 0.0028). There was no difference in burst swimming speed in 8 d

exposures conducted in either soft or hard water (6.67 ± 0.07 and 6.84 ± 0.07 BL/s

respectively; p = 0.6047) or 16 d exposures conducted in either soft or hard water (6.67

± 0.07 and 7.04 ± 0.07 BL/s, respectively; p = 0.1305). For exposures conducted in hard

water, Uburst values were significantly lower for 4 d exposures (6.33 ± 0.07 BL/s)

compared to 8 (6.84 ± 0.07 BL/s; p = 0.0461) and 16 d (7.04 ± 0.07 BL/s; p = 0.0147).

For exposures conducted in soft water, Uburst velocities were significantly slower for 4 d

exposures (7.43 ± 0.07 BL/s) compared to 8 (6.67± 0.07 BL/s; p = 0.0109) and 16 d

(6.67 ± 0.07 BL/s; p = 0.0112).

31

Figure 3.2 Burst swimming speed (BL/s) of fish exposed to Cu. 4, 8 and 16 refers to days of Cu exposure, H = hard water (100 mg/L CaCO3), S = soft water (6 mg/L CaCO3). Low Cu treatments are 6 and 20 µg/L Cu in soft and hard water, respectively. High Cu treatments are 16 and 60 µg/L Cu in soft and hard water, respectively. Box indicates 25th and 75th quartiles, whiskers indicate 10th and 90th percentiles. Medians are indicated by a black line and means are indicated by a +. N=1 for each treatment group. Treatments connected by the same letter are not significantly different (p < 0.05). Tukey’s multiple comparisons test was used to determine differences between treatment groups.

3.4. Osmoregulation

3.4.1. Gill Na+/K+-ATPase (NKA) activity

Gill NKA activity was assessed in juvenile fish (n=10 per treatment; due to tank

effects, n=2 for analyses) following Cu exposure to either control (municipal

dechlorinated water), low Cu concentrations (6 and 20 µg/L in soft or hard water,

respectively) or high Cu concentrations (16 and 60 µg/L in soft or hard water,

4H 8H 16H 4S 8S 16

S

0

4

5

6

7

8

9Control

Low Cu

High Cu

Duration of Exposure, Water Hardness

Bu

rst s

wim

min

g s

pe

ed

(B

L/s

) c b ab a bc bc

32

respectively) for 4 and 16 d. NKA activity was assessed following the protocol of

McCormick (1993).

Gill NKA activity ranged from 0.27 ± 0.11 to 1.79 ± 0.09 µmole ADP/mg protein/h

across all treatment groups. Exposure to Cu did not alter gill NKA activity in any

treatment group (p = 0.2717), therefore Cu treatment groups were pooled together for all

further comparisons of the effects of water hardness and exposure duration (Fig 3.3).

There was a significant interaction effect between the duration of exposure and water

hardness (p < 0.0001). Gill NKA activity for 4 d exposures were significantly higher in

soft water (1.70 ± 0.05 µmole ADP/mg protein/h) compared to that in than hard water

(0.67 ± 0.05 µmole ADP/mg protein/h; p < 0.0001). For 16 d exposures, gill NKA activity

was significantly higher in hard water (1.23 ± 0.05 µmole ADP/mg protein/h) compared

to soft water (0.46 ± 0.05 µmole ADP/mg protein/h; p < 0.0001). In hard water (Fig

3.3A), gill NKA activity was significantly higher for 16 d (1.23 ± 0.05 µmole ADP/mg

protein/h) compared to 4 d exposures (0.67 ± 0.05 µmole ADP/mg protein/h; p <

0.0001). For exposures conducted in soft water (Fig 3.3B), gill NKA activity was

significantly elevated at 4 d (1.70 ± 0.05 µmole ADP/mg protein/h) compared to 16 d

(0.46 ± 0.05 µmole ADP/mg protein/h; p < 0.0001).

33

Figure 3.3 Gill Na+/K+-ATPase activity (µmole ADP/mg protein/h) of fish

exposed to Cu. 4, 8 and 16 refers to days of Cu exposure, H = hard water (100 mg/L CaCO3), S = soft water (6 mg/L CaCO3). Low Cu treatments are 6 and 20 µg/L Cu in soft and hard water, respectively. High Cu treatments are 16 and 60 µg/L Cu in soft and hard water, respectively. Box indicates 25th and 75th quartiles, whiskers indicate 10th and 90th percentiles. Medians are indicated by a black line and means are indicated by a +. N=2 for each treatment group. Treatments connected by the same letter are not significantly different (p < 0.05). Tukey’s multiple comparisons test was used to determine differences between treatment groups.

3.4.2. Plasma ion concentrations and osmolality

Exposures were conducted as described above. Briefly, fish (n=10 per

treatment; due to tank effects, n=2 for analyses) were exposed to either control

(municipal dechlorinated water), low Cu concentrations (6 and 20 µg/L in soft or hard

water, respectively) or high Cu concentrations (16 and 60 µg/L in soft or hard water,

respectively) for 4 and 16 d.

Across all treatment groups, plasma Cl- concentrations ranged from 98.20 ± 2.85

to 155.86 ± 2.89 mmol/L. Cu exposure did not alter Cl- concentration in any treatment

group (p = 0.6566), therefore Cu treatment groups were pooled together for all further

4H 16H 4S 16

S

0.0

0.5

1.0

1.5

2.0

2.5Control

Low Cu

High Cu

a b c d


Gill

Na

+/K

+-A

TP

ase

Activ

ity

(µm

ole

AD

P/m

g p

rote

in/h

34

comparisons of the effects of exposure duration and water hardness (Fig 3.4). Water

hardness did not affect Cl- concentration in any treatment group (p = 0.0969), with

plasma concentrations of 116.82 ± 3.10 and 124.72 ± 3.10 mmol/L in hard and soft

water, respectively. The duration of exposure had a significant effect on Cl-

concentration. Fish exposed for 16 d (126.61 ± 3.10 mmol/L) had a significantly higher

concentration of Cl- in plasma than fish exposed for 4 d (114.93 ± 3.10 mmol/L; p =

0.0208).

Figure 3.4 Plasma Cl- concentration (mmol/L) of fish exposed to Cu. 4, 8 and

16 refers to days of Cu exposure, H = hard water (100 mg/L CaCO3), S = soft water (6 mg/L CaCO3). Low Cu treatments are 6 and 20 µg/L Cu in soft and hard water, respectively. High Cu treatments are 16 and 60 µg/L Cu in soft and hard water, respectively. Box indicates 25th and 75th quartiles, whiskers indicate 10th and 90th percentiles. Medians are indicated by a black line and means are indicated by +. N=2 for each treatment group. Treatments connected by the same letter are not significantly different (p < 0.05). Student’s t-test was used to determine differences between treatment groups.

Plasma Na+ concentrations ranged from 91.56 ± 10.78 mmol/L to 123.24 ± 2.60

mmol/L across all treatment groups. Exposure to copper had no significant effect on

plasma Na+ concentrations (p = 0.1335), therefore Cu treatment groups were pooled

together for all further comparisons of the effects of water hardness and exposure

4H 16H 4S 16

S

0

60

80

100

120

140

160

180Control

Low Cu

High Cu

b ba a


Pla

sm

a [C

l- ] (m

mo

l/L)

35

duration (Fig 3.5). Water hardness did not affect Na+ concentration in any treatment

group (p = 0.3023), with plasma concentrations of 117.77 ± 1.39 and 115.65 ± 1.39

mmol/L in hard and soft water, respectively. There was a significant interaction between

duration of exposure and water hardness (p = 0.0195). Plasma Na+ concentration after 4

d of exposure was not significantly different between hard water exposures (118.19 ±

1.97 mmol/L) and soft water exposures (110.76 ± 1.97 mmol/L; p = 0.0835). After 16 d

exposures, there was no significant difference in plasma Na+ between hard (117.35 ±

1.97 mmol/L) and soft water (120.54 ± 1.97 mmol/L; p = 0.6711). There was no

significant difference for exposures conducted in hard water between 4 d (118.19 ± 1.97

mmol/L) and 16 d (117.35 ± 1.97 mmol/L; p = 0.9900; Fig 3.5A). For exposures

conducted in soft water, 16 d exposures had significantly elevated plasma Na+

concentration (120.54 ± 1.97 mmol/L) than 4 d exposures (110.76 ± 1.97 mmol/L; p =

0.0194; Fig 3.5B).

36

Figure 3.5 Plasma Na+ ion concentration (mmol/L) of fish exposed to Cu. 4, 8

and 16 refers to days of Cu exposure, H = hard water (100 mg/L CaCO3), S = soft water (6 mg/L CaCO3). Low Cu treatments are 6 and 20 µg/L Cu in soft and hard water, respectively. High Cu treatments are 16 and 60 µg/L Cu in soft and hard water, respectively. Box indicates 25th and 75th quartiles, whiskers indicate 10th and 90th percentiles. Medians are indicated by a black line and means are indicated by a +. N=2 for each treatment group. Treatments connected by the same letter are not significantly different (p < 0.05). Tukey’s multiple comparisons test was used to determine differences between treatment groups.

Across all treatment groups, plasma osmolality ranged from 263.20 ± 11.49

mmol/kg to 312.63 ± 3.94 mmol/kg (Fig 3.6). Exposure to copper did not alter osmolality

in any treatment group (p = 0.2148), therefore Cu treatment groups were pooled

together for all further comparisons of the effects of exposure duration and water

hardness. The duration of exposure had a significant effect on plasma osmolality (p =

0.0452). Osmolality after 4 d exposures (297.00 ± 2.12 mmol/kg) were significantly

higher then 16 d (290.30 ± 2.12 mmol/kg). Water hardness had a significant effect on

plasma osmolality (p < 0.0001); exposures in hard water (302.48 ± 2.12 mmol/kg; Fig

3.6A) were significantly higher than soft water exposures (284.83 ± 2.12 mmol/kg; Fig

3.6B).

4H 16H 4S 16

S

05060

80

100

120

140Control

Low Cu

High Cu

ab ab b a


Pla

sm

a [N

a+] (

mm

ol/L

)

37

Figure 3.6 Plasma osmolality (mmol/kg) of fish exposed to Cu. 4, 8 and 16

refers to days of Cu exposure, H = hard water (100 mg/L CaCO3), S = soft water (6 mg/L CaCO3). Low Cu treatments are 6 and 20 µg/L Cu in soft and hard water, respectively. High Cu treatments are 16 and 60 µg/L Cu in soft and hard water, respectively. Box indicates 25th and 75th quartiles, whiskers indicate 10th and 90th percentiles. Medians are indicated by a black line and means are indicated by a +. N=2 for each treatment group. Treatments connected by the same letter are not significantly different (p < 0.05). Student’s t-test was used to determine differences between treatment groups.

3.4.3. Seawater challenge

Fish were subjected to a seawater challenge following the exposure protocol

described above. Following 24 h in seawater, no mortalities occurred in any treatment

group.

3.5. Biochemical stress response

The stress response was assessed in fish (n=10 per treatment; due to tank

effects, n=2 for analyses) that were exposed to either control (municipal dechlorinated

4H 16H 4S 16

S

200

250

300

350Control

Low Cu

High Cu

a b a b

c d


Osm

ola

lity (m

mo

l/kg

)

38

water), low (6 and 20 µg/L in soft and hard water, respectively) or high (16 and 60 µg/L

in soft and hard water, respectively) Cu concentrations for 4 or 16 d.

Hematocrit values ranged from 35.06 ± 1.44 to 43.31 ± 1.56. Exposure to copper

resulted in no significant change to hematocrit (p = 0.4266), therefore Cu treatment

groups were pooled together for all further comparisons of the effects of exposure

duration and water hardness (Fig 3.7). The duration of exposure had no effect on

hematocrit (p = 0.0772), with 4 and 16 d exposures having hematocrit values of 38.46 ±

0.58 and 40.04 ± 0.58, respectively. Water hardness had no effect on hematocrit (p =

0.0545), with hard (Fig 3.7A) and soft (Fig 3.7B) having values of 38.35 ± 0.58 and 40.15

± 0.58, respectively.

Figure 3.7 Hematocrit (%) in fish exposed to Cu. 4, 8 and 16 refers to days of

Cu exposure, H = hard water (100 mg/L CaCO3), S = soft water (6 mg/L CaCO3). Low Cu treatments are 6 and 20 µg/L Cu in soft and hard water, respectively. High Cu treatments are 16 and 60 µg/L Cu in soft and hard water, respectively. Box indicates 25th and 75th quartiles, whiskers indicate 10th and 90th percentiles. Medians are indicated by a black line and means are indicated by a +. N=2 for each treatment group. Treatments connected by the same letter are not significantly different (p < 0.05).

4H 16H 4S 16

S

25

30

35

40

45

50

55Control

Low Cu

High Cu

a a a a


He

ma

tocrit (

%)

39

Plasma cortisol values ranged from 1.54 ± 0.37 to 131.01 ± 28.34 ng/ml. Copper

exposure did not alter plasma cortisol concentrations in any treatment groups (p =

0.1441), therefore Cu treatment groups were pooled together for all further comparisons

o the effects of water hardness and exposure duration (Fig 3.8). There was a significant

interaction between the duration of copper exposure and water hardness (p = 0.0021).

Fish exposed for 4 d had significantly elevated cortisol concentrations in soft water

(68.67 ± 8.31 ng/ml) compared to hard water (8.07 ± 8.31 ng/ml; p = 0.0012). For

exposures conducted over 16 d, there was no significant difference between hard (7.45

± 8.31 ng/ml) and soft water (3.16 ± 8.31 ng/ml; p = 0.9826). Hard water exposures

were not significantly different comparing 4 d (8.07 ± 8.31 ng/ml) and 16 d exposures

(7.45 ± 8.31 ng/ml; p = 0.9999; Fig 3.8A). Soft water exposures resulted in significantly

elevated plasma cortisol concentrations after 4 d of exposure (68.67 ± 8.31 ng/ml)

compared to 16 d (3.16 ± 8.31 ng/ml; p = 0.0006; Fig 3.8B).

40

Figure 3.8 Plasma cortisol concentration (ng/ml) of fish exposed to Cu. 4, 8

and 16 refers to days of Cu exposure, H = hard water (100 mg/L CaCO3), S = soft water (6 mg/L CaCO3). Low Cu treatments are 6 and 20 µg/L Cu in soft and hard water, respectively. High Cu treatments are 16 and 60 µg/L Cu in soft and hard water, respectively. Box indicates 25th and 75th quartiles, whiskers indicate 10th and 90th percentiles. Medians are indicated by a black line and means are indicated by a +. N=2 for each treatment group. Treatments connected by the same letter are not significantly different (p < 0.05). Tukey’s multiple comparisons test was used to determine differences between treatment groups.

4H 16H 4S 16

S

0

50

100

150200250


Pla

sm

a [C

ortis

ol]

(ng

/ml) Control

Low Cu

High Cu

b b a b

41

Chapter 4. Discussion

The gills, specifically the ion transport ATPases, are believed to be the primary

site of Cu toxicity in fish (Hansen et al., 1993). Exposure to Cu affects osmoregulation

by impairing ion exchange: Cu outcompetes Na+ for ATPase transporters (Laurén and

McDonald, 1986, De Boeck et al, 2007). Water hardness can affect metals toxicity,

including that of Cu. In hard water, calcium ions are at a high enough concentration that

they outcompete metals for binding sites on the gills and therefore decrease metal

bioavailability (Laurén and McDonald, 1986, Saglam et al., 2013). The link between

water hardness and Cu effects on osmoregulation is obvious. Proper gill function is

crucial for cardiovascular and respiratory function, and therefore a potential link between

swimming performance, water quality and Cu toxicity is also likely to exist. The

experiments in this study were conducted to determine the effects of Cu exposure on

several endpoints related to swimming performance and osmoregulation in a

representative salmonid species, the rainbow trout. Juveniles were selected due to their

sensitivity to Cu. The effects water hardness and the duration of exposure on the

magnitude of effects of sublethal Cu exposure were also examined. Durations were

selected that had previously shown effects to Cu in literature.

While Cu is an essential metal at low concentrations, it is extremely toxic at

elevated concentrations (Hassan, 2011). Cu is acutely toxic to fish in the range of 10-

1000 µg/L Cu, with a broad range due to biotic (e.g. fish species and age) and abiotic

(e.g. water hardness, temperature, pH, DOC) factors (Spear and Pierce, 1979, Pilgaard

et al., 1994, Eisler, 2000). LC50 values are significantly lower in soft water than hard

water. In hard water, with Ca2+ ions at a high enough concentration to outcompete Cu

for uptake at the gills, there is a reduction in Cu bioavailability resulting in reduced

lethality in harder water (Laurén and McDonald, 1986, Saglam et al., 2013). In the

present study, the LC50 values for Cu were 40 and 150 µg/L in soft and hard water,

42

respectively. These values fall within the range of published LC50 values for salmonids.

In soft freshwater (~30 mg/L CaCO3), Cu is most acutely toxic with 96 h LC50 values

between 10 and 30 µg/L (NAS 1977, Howarth and Sprague, 1978). In hard freshwater

(95-200 mg/L CaCO3), LC50 values range from 75 to 230 µg/L Cu, depending on

species (Lorz and McPherson, 1977, US EPA, 1980, Eyckmans et al., 2010).

In this study the exposure to sublethal concentrations of Cu had no significant

effect on any of the osmoregulatory endpoints selected, including gill Na+/K+-ATPase

activity, plasma [Na+] and [Cl-], plasma osmolality, or mortality during a seawater

challenge. Control values in this study were 1.04 ± 0.04 µmol/mg protein/h (gill Na+/K+

ATPase activity), 117.00 ± 171 mmol/L (plasma Na+), 119.50 ± 3.80 mmol/L (plasma Cl-)

and 291.93 ± 2.60 mmol/kg (osmolality), respectively. The control values for these

endpoints are within published ranges for acute sublethal exposure in freshwater fish.

Gill NKA activity in freshwater fish range from 0.5-4 µmol/mg protein/h (Monteiro et al.,

2005, Eyckmans et al., 2010, Kulac et al., 2013). Plasma Na+ ion values range from

120-197 mmol/L, plasma chloride ion values range from 120-150 mmol/L and osmolality

ranges from 280-300 mmol/kg. (McKim et al., 1970, Wilson and Taylor, 1993a, Pelgrom

et al., 1995, Monteiro et al., 2005, Eyckmans et al., 2010).

Copper is well known to disrupt osmoregulation and ionoregulation in fish. Acute

exposure in the range of 15 to 2000 µg/L Cu (large range due to species differences)

(31.3 µmol/L) has been shown to inhibit Na+/K+-ATPase activity (between 33 and 65%

reduction) and increase gill permeability to Na+ (between 20 and 60% ion loss) for

exposures conducted from 1 h to 14 d, in a range of water hardness values (1 – 250

mg/L CaCO3) (Laurén and McDonald, 1985, 1987a, 1987b, Wilson and Taylor, 1993a,

Monteiro et al., 2005, Hashemi et al., 2008, Eyckmans et al., 2010). Stimulation of ion

(Na+ and Cl-) efflux (between 18 and 30% ion loss) in freshwater fish can also occur,

likely occurring through the tight junctions in the branchial epithelium (Cu concentration

of ~5 µg/L, within 24 h of exposure) (Nieboer and Richardson, 1980, Wilson and Taylor,

1993b). Tight junction permeability is at least partially controlled by bound Ca2+ and Cu

is known to displace Ca2+ from negatively charged groups on the plasma membrane

(Nieboer and Richardson, 1980, Laurén and McDonald, 1985). As dissolved Cu

concentrations increase, Cu may displace Ca2+ and increase ion permeability through

43

the junctions (Laurén and McDonald, 1985). Together these disruptions (inhibited

Na+/K+-ATPase activity and stimulated ion efflux) lead to a loss of Na+ and Cl-,

decreasing plasma concentrations for both the ions (Laurén and McDonald, 1985,

Pelgrom et al., 1995, Eyckmans et al., 2010). The increased permeability of the gills

after Cu exposure leading to ion efflux may also be due to a disruption of the membrane

integrity in gill cells as concluded by Wilson and Taylor (1993b) (6 µg/L Cu for 24 h in

rainbow trout, unknown hardness) and Taylor et al. (2000) (2 & 60 µg/L, 30 d exposure

in rainbow trout, hardness 20 and 120 mg/L). Laurén and McDonald (1985) found that

water hardness had no effect on the net loss of Na+ and Cl- caused by exposure to 200

µg/L Cu (i.e. no significant difference in ion loss between hard [83 mg/L CaCO3] and soft

water [2 mg/L CaCO3]). Similar results were found by Taylor et al. (2000), with no

significant difference in ion loss after Cu exposure in hard and soft water (hard water =

120 mg/L CaCO3, 60 µg/L Cu, soft water = 20 mg/L CaCO3, 2 µg/L Cu).

In addition to the reduction in plasma [Na+] and [Cl-], it is well documented that

there is a decrease in plasma osmolality, due to reduced ion concentrations. Six and 21

d exposures to concentrations of 39 and 68 µg/L Cu (unknown hardness) significantly

reduced osmolality in yearling brook trout (between 5 and 13% reduction) (McKim et al.,

1970). The same effect is noted in other species; a 96 h exposure at 121 µg/L Cu

(unknown hardness) in the common carp (C. carpio) reduced osmolality significantly by

7% (De Boeck et al., 2001) and over the course of 21 d at 400 µg/L (75 mg/L CaCO3),

osmolality was significantly reduced by 40% in Oreochromis niloticus (Monteiro et al.,

2005).

While the previously cited literature indicates a reduction in Na+/K+-ATPase

activity, plasma [Na+] and [Cl-] following exposure to Cu in freshwater, a study conducted

by Eyckmans et al., (2010) support the findings of the present research. They noted a

reduction from control of branchial NKA activity only at 12 h of exposure to 20 µg/L Cu

(250 mg/L CaCO3) (10% the 96 h LC50) in rainbow trout; at all other time points (1 h, 24

h, 3 d, 1 w, 1 m) a response was not detected. This suggests the potential for a

transient reduction of NKA activity with a return to baseline values under some

circumstances. Based on these findings, the sampling times used in the present study

would not detect alterations in gill NKA activity if it occurred at an earlier point to

44

sampling. Compensatory mechanisms that returned values to baseline levels by the first

sampling period may be occurring. Eyckmans et al., (2010) also detected a reduction in

plasma [Na+] and [Cl-] within the first 24 h of exposure (including 1, 12 and 24 h),

however exposures of a longer duration (3 d, 1 w and 1 m) showed no difference from

baseline values.

A seawater challenge is a whole-animal performance assay that is used to

determine if freshwater fish can osmo- and ionoregulate in seawater (Bills and Kenworth,

1986, Marshall and Grosell, 2005). As anadromous or catadromous fish transition from

freshwater to seawater (e.g. during migration) the change in salinity can subject some

fish to severe osmotic stress (Eddy, 1981). Following exposure to a stressor (e.g. Cu),

fish are challenged by being transferred from freshwater directly into saltwater. It was

hypothesized that fish exposed to Cu would be unable to maintain normal ionoregulation

and would be unable to successfully survive the transition from freshwater to seawater.

No mortalities were recorded during the seawater challenge, supporting the findings

from the biochemical endpoints (NKA activity, plasma Na+ and Cl-concentrations and

osmolality) that Cu under these exposure conditions was not an ionoregulatory stressor.

Salmonids have been widely used to study osmoregulatory disturbance during transfer

to seawater; to our knowledge, the present study is the first time a seawater challenge

has been used following Cu exposure (Handeland et al., 1998, Shrimpton et al., 1994,

Türker et al., 2004, Shrimpton et al., 2005)

In the present study, control hematocrit values were 40.0 ± 0.7% across all

exposure conditions, and was unchanged after 4 and 16 d exposure to Cu. Hematocrit

has been shown in several studies to increase with Cu exposure. Studies have shown

an increase in hematocrit between 20 and 25% after Cu exposure (ranging from 30-70

µg/L Cu over 4-6 d) (McKim et al., 1970, Mazon et al., 2002, Bagdonas and Vosyliene,

2006, Carvalho and Fernandes, 2006). Hematocrit and plasma volume are inversely

related, and plasma ion concentrations can alter plasma volume (Brauner et al., 1994).

As there was no change to plasma ion concentrations in the present study, no change in

hematocrit would be expected

Metal exposure, including Cu are known stressors in fish and can trigger the

45

release of stress hormones, most notably cortisol, as well as both adrenaline and

noradrenaline (Wendelaar Bonga, 1993). Cortisol aids in water and ion homeostasis

and can trigger the biosynthesis of metallothioneins in fish for metal detoxification

(Wendelaar Bonga, 1993). In fish, plasma cortisol concentrations <30 ng/ml are

considered to indicate an unstressed condition; concentrations in the range of 30 to 300

ng/ml are typically found in fish exposed to acute stressors (Barton, 2002). Baseline

cortisol concentration in the present study across all exposure conditions was 9.45 ±

7.20 ng/ml, which is within the published range for unstressed fish (De Boeck et all,

2001, Gagnon et al., 2006, Osachoff et al., 2014).

In this study, Cu exposure did not result in an elevation of plasma cortisol

concentrations in any treatment group, indicating that Cu was not acting as an acute

stressor under the experimental conditions. These results differ from much of the

published literature, as Cu has been well documented to increase plasma cortisol

following exposure. For example, cortisol was significantly increased from 10 to 115

ng/ml following a 96 h exposure of common carp to 120 µg/L Cu (De Boeck et al., 2001).

In Oreochromis niloticus, a 3 d exposure to 40 and 400 µg/L (75 mg/L CaCO3) Cu

increased plasma cortisol concentrations from a control value of 28 ng/ml to 199 and

258 ng/ml, respectively (Monteiro et al., 2005). Increases in plasma cortisol

concentrations are usually transient. For example, Dethloff et al. (1999) noted a

significant increase in cortisol concentrations following 3 d of Cu exposure (to 29 µg/L

Cu; 45 mg/L CaCO3), which returned to control values by 21 d. The initial spike in

cortisol may have missed in our study as the first time point (4 d) could be too late for

detection. This theory is supported by the results of Pickering and Pottinger (1989) and

Kennedy and Farrell (2008), with an acute stressor resulting in an initial (between 1 to 24

h) cortisol spike (plasma cortisol concentrations between 40 to 100 ng/ml, depending on

stressor) in rainbow trout, with a return to baseline after 24 h.

The current paradigm of metal toxicity, including Cu, is supported by a broad

literature base and hundreds of studies. The apparent lack of effect on common

endpoints involved in the Cu toxicity mechanism (particularly at such high Cu

concentrations near the LC50 value) is unclear but several possible explanations exist.

Typically, when fish are exposed to a toxicant such as sublethal Cu, they enter into a

46

cycle of damage and repair in order to develop a tolerance to metals, that is comprised

of three phases (McDonald and Wood, 1993, McGeer et al., 2000, Tate-Boldt and Kolok,

2008). The initial ‘shock phase’ results in physical damage to the gill and disruptions to

the osmoregulatory and respiratory systems. These include reductions in Na+/K+-

ATPase activity, reduced Na+ influx and stimulated Na+ efflux in freshwater species

(Laurén and McDonald, 1985, 1987a, Pelgrom et al. 1995, Kolok et al., 2002). This is

followed by the ‘damage phase’ during which the effects from the ‘shock phase’ become

apparent, resulting in a net decrease in whole-animal Na+ concentrations (Kolok et al.,

2002). Following this second phase, fish can enter a ‘repair phase’ where Na+

concentrations return to pre-exposure (baseline) concentrations (Laurén and McDonald,

1987a, McGeer et al., 2000) which is achieved by increasing the biosynthetic pathways

responsible for repairing damage and correcting the physiological effects from exposure,

including an increase in metallothioneins for metal binding and up-regulation of

pathways that restore ion homeostasis (Laurén and McDonald, 1987a, Hogstrand and

Wood, 1996, McGeer et al., 2000). The time frame for each phase is not fully elucidated

and a general consensus has not been reached on the timing of each phase. It is likely

dependent on both exposure duration and concentration.

The paradigm of damage and repair is supported by several studies (Dethloff et

al., 1999, Eyckmans et al., 2010). They found that alterations to NKA activity, ion

concentrations, and plasma cortisol concentrations in rainbow trout were most evident

from 24 h (NKA activity and plasma ion concentrations) to 3 d (plasma cortisol) of Cu

exposure (Cu exposures between 20 and 50 µg/L for exposures up to 21 d), after which

all parameters returned to baseline values (after 3 d). This indicates that in the present

study, the initial shock and damage phases may have occurred by the first sampling

period of 4 d and that the sampling times of 4 and 16 d were well into the repair phase,

when altered endpoints have returned or are returning to baseline values. Species

differences may also dictate the length of each phase (along with exposure

concentration and duration). For example, common carp (Cyprinus carpio) and gibel

carp (Carassius auratus gibelio) exhibited altered gill NKA and ion concentrations

following Cu exposure, values which never returned to baseline levels (Eyckmans et al.,

2010). The present study indicates that following the initial shock phase, rainbow trout

may be better able to restore homeostatic values than some other freshwater species.

47

One of the postulated mechanisms involved in restoring osmoregulatory

regulation following metal exposure resides in the chloride cells, where the majority of

the NKA transport proteins reside within the gills. These are mitochondria-rich cells that

also contain branchial Na+/Ca+ exchangers (Flik et al., 1995, Perry, 1997). One process

involved in the restoration of ion homeostasis following Cu exposure involves the

turnover and proliferation of chloride cells, increasing their density in the gills (McDonald

and Wood, 1993, Pelgrom et al., 1995, Li et al., 1998, Tate-Boldt and Kolok, 2008,

Eyckmans et al., 2010). While some chloride cells degenerate due to necrosis following

Cu exposure, their increase in numbers after acute (< 6 d) Cu exposure may help

compensate for reductions in NKA activity and aid in maintaining ion balance (Pelgrom

et al., 1995).

In addition to gills, kidneys and intestines are also involved in osmoregulation.

Both organs contain Na+/K+-ATPases, Ca2+-ATPases and Na+/Ca2+ exchangers for ion

transport and ion homeostasis (Schoenmakers et al., 1993). Cu affects these ion

transporters in a similar manner as in the gills, although an increase in renal Na+ uptake

has been reported following sublethal Cu exposure (Laurén and McDonald, 1985). This

is believed to be a physiological response that compensates for reduced branchial NKA

activity, suggesting that renal NKA pumps may provide better protection against

disturbance than branchial NKA pumps to the effects of Cu. Renal Na+ reabsorption aids

to counterbalance the reduced Na+ absorption at the gills following sublethal Cu

exposure (Laurén and McDonald, 1987a, 1987b, Grosell et al., 1998). In the present

study, plasma Na+ and Cl- ion concentrations and osmolality were unaffected by Cu

exposure after 4 and 16 d exposure, potentially due, in part, to the upregulation of renal

NKA activity. As NKA activity was not measured in any tissue other than the gills, the

contribution of renal ion transport to ion homeostasis in the face of metal challenge

remains unknown.

Swimming performance has been utilized as an endpoint to determine the effects

of various stressors on fish, as it requires the integration of multiple organ systems to

function optimally (Osachoff et al., 2014). These include the respiratory and

cardiovascular systems as well as the musculature and skeletal systems, among others

(Bone, 1978, Jones and Randall, 1978). Adjustments to both the respiratory and cardiac

48

systems of fish occur during intense exercise in order to meet increased energetic

demand brought on by increased oxygen and energy demands, and it is during such

periods of maximum performance that all subsystems need to be working optimally

(Jones and Randall, 1978).

The respiratory system is responsible for gas exchange and is limited by factors

including the surface area over which gas exchange occurs (i.e. the gills), the surface’s

permeability to gases, and the distance across the exchange surface (Jones and

Randall, 1978). During exercise the amount of water flowing over the gills increases;

there is an increase in the contractions and expansions of both the buccal and opercular

pumps to achieve this, aided by the forward swimming motion of the fish (Kiceniuk and

Jones, 1977). This increased ventilation of the gills allows for increased oxygen uptake

necessary for swimming (Brett, 1964). Exercise in fish results in an increase in

peripheral blood flow in order to oxygenate muscles involved in locomotion (Jones and

Randall, 1978). This can occur by increasing the heart rate and stroke volume (i.e. the

volume of blood pumped out of the ventricle per beat; Jones and Randall, 1978).

Typically the increased cardiac output required for more rapid oxygen transport is

associated with changes to the stroke volume rather than heart rate (Randall, 1970).

Changes to heart rate vary greatly by species; at the onset of exercise both bradycardia

and tachycardia have been reported (Priede, 1974). Additionally, levels of hematocrit,

hemoglobin and plasma proteins increase during exercise to increase oxygen transport

(Cameron and Davis, 1970).

As the gills are in direct contact with water, they are vulnerable to many

waterborne toxicants including Cu (Beaumont et al., 2003). Cu exposure at

concentrations ranging from 5 to 100 µg/L and exposure from 6 to 96 h can interfere with

respiration by causing physical damage to gills, including swelling and lifting of epithelial

cells, fusion and collapse of gill lamellae, and an increase in mucus production (De

Boeck et al., 2001, Beaumont et al., 2003). The net effect of this physical damage is a

disruption of gas exchange through an increase in diffusion distance that decreases the

rate of oxygen uptake (De Boeck et al., 2006). The accumulation of carbon dioxide

results in an acidosis and an increase in blood viscosity. The combination of reduced

oxygen uptake and increased blood viscosity decreases O2 delivery during Cu exposure

49

(300 µg/L Cu for 24 h; Wilson and Taylor, 1993a). Oxygen consumption has been

shown to significantly decrease immediately (1 h) following exposure to Cu at

concentrations of 20 and 50 µg/L. After 7 d of continuous exposure to these

concentrations, oxygen consumption returned to control values for the 20 µg/L exposure

group, however the 50 µg/L group did not recover in this respect, suggesting the

possibility of a compensatory mechanism, especially in low Cu concentration range (De

Boeck et al., 1995).

Typically, a large proportion of a fish’s mass is muscle, and in salmonids

approximately 60% of their total body mass consists of locomotory muscles (Bainbridge,

1962). The most common swimming performance measure is critical swimming speed

(Ucrit) which is a long duration assay and is regarded as a measure of aerobic swimming,

utilizing primarily red muscle, which are slow twitch fibres that contain numerous

mitochondria (Bone, 1966, Farrell, 2008). As described earlier, an increase in blood

viscosity could decrease oxygen delivery to the locomotory muscles, affecting aerobic

cellular metabolism (Beaumont et al., 2000). Blood viscosity affects oxygen transport by

reducing heart stroke volume or reducing blood velocity through the capillaries (Randall

and Brauner, 1991, Wells and Weber, 1991). Burst swimming (Uburst) is a test of shorter

duration that measures the maximum speed a fish can sustain for a short period of time.

It is regarded as primarily anaerobic swimming, utilizing mostly white muscle or fast

twitch fibres, which contain fewer mitochondria (Bone, 1966, Farrell, 2008). This type of

exercise (exhaustive) is fuelled by the breakdown of glycogen to lactate; the depletion of

white muscle glycogen stores can account for reductions in Uburst (Beaumont et al.,

2000).

Few studies have examined the effects of Cu on swimming performance in fish,

and the research has typically focused on critical swimming speed, or the determination

of Ucrit, a long duration swimming test. For example, 2 h exposure to Cu at 105 µg/L

caused a significant reduction in critical swimming speed in trout (Brett, 1964, Waiwood

and Beamish, 1978, Beaumont et al., 1995, Kolok et al., 2002, De Boeck et al., 2006,

Waser et al., 2009). In addition to Cu, these studies altered several abiotic factors

during exposure, including pH and temperature. Copper concentrations in these studies

ranged between 5 and 30 µg/L (Brett, 1964, Beaumont et al., 1995) and between 10 and

50

200 µg/L (Waiwood and Beamish, 1978). Copper significantly reduces swimming speed

at low pH (6) vs. high pH (8) by 15% (Waiwood and Beamish, 1978) and by 40% in low

temperature (5 oC) vs. high (15 oC) (Beaumont et al., 1995). Taylor et al. (2000)

reported no change to critical swimming speed after a chronic (30 d) Cu exposure in

hard (120 mg/L CaCO3,60 µg/L Cu) and soft water (30 mg/L CaCO3, 2 µg/L Cu).

In the present study Cu exposure did not elicit a change in burst swimming

speed. Across treatments, Uburst values (6.13 to 7.53 BL/s) were all within published

burst swimming speed values (Pedersen and Malte, 2004, Pedersen and Malte, 2008,

Goulding et al., 2013, Osachoff et al., 2014). The lack of Cu effect is likely due to Uburst

being primarily fuelled by anaerobic metabolism. There is evidence of Cu exposure

decreasing muscle glycogen stores (Cu concentrations between 80 and 1400µg/L,

depending on species selected: carp and danionins), which could potentially result in a

reduced burst swimming speed (Radhakrishnaiah et al., 1992, Vutukuru et al., 2005,

Reddy et al., 2008). Reductions in oxygen uptake and consumption are more likely to

affect the longer duration swimming tests (such as Ucrit) as they are predominantly

fuelled by aerobic metabolism. As Uburst is predominately fuelled by anaerobic

metabolism, changes to the gills and decreased oxygen consumption would not have as

much of an effect on burst swimming as it would on critical swimming. To our

knowledge, this is the first study measuring Uburst following acute sublethal exposure to

copper in juvenile rainbow trout. In a study by Taylor et al. (2000) did not find an effect

on burst swimming after a chronic exposure (30 d) in hard (120 mg/L CaCO3; 60 µg/L

Cu) or soft water (20 mg/L CaCO3; 2 µg/L). While the Taylor et al. (2000) study is a

chronic Cu exposure, it does support the findings from the present study, with no effect

on Uburst following Cu exposure, and that water hardness did not affect swimming speed.

This could indicate Uburst may not be a suitable endpoint for Cu or heavy metal toxicity.

51

Chapter 5. Conclusion and Future Directions

It has been well documented since the 1970’s that Cu causes ionoregulatory

disturbances in fish through several mechanisms, most of which occur at the levels of

the gills. There is a small but growing body of evidence that suggests that some fish

species can acclimatize to, or compensate for the effects of Cu and under some

circumstances, the concentrations that incur toxicity may not be as straightforward as

previously thought. The present study aimed to examine the effects of Cu exposure on

swimming performance and osmoregulation in juvenile rainbow trout. The

concentrations selected were sublethal and environmentally relevant and the

experiments were conducted in both soft and artificially hardened water (4 and 16 d) in

order to determine how these additional factors might modulate Cu toxicity. It is possible

that the sampling time points selected were after damage had occurred and would

therefore not have been detected. It is also possible that under these conditions, Cu

was not acting as a stressor as there was no alteration to any swimming or

osmoregulatory endpoints.

There are multiple studies that could be conducted to follow up on these findings.

Histological examinations of the gill structure following Cu exposure would be a first step

in determining if physical damage is occurring. It is believed that the first 24 h of

exposure is when gill damage occurs, leading to ionoregulatory disruption. In order to

validate the proposed damage-repair model for compensation, selecting shorter

exposure durations and measuring endpoints would be desirable, as this would allow for

the examination of alterations that would occur in the ‘damage phase’ of Cu exposure.

While branchial Na+/K+-ATPase activity is the ionoregulatory endpoint typically studied,

measuring the activity of the branchial H+-ATPase-coupled Na+ channel would be useful

to determine Na+ flux into the gills of these fish. As we noted no change in branchial

52

NKA activity on the basolateral membrane, it would be interesting to determine the

activity of a sodium pump on the apical membrane. Additionally, as the kidney NKA

pump is thought to be involved with maintaining ion balance, determining the activity of

that pump after Cu exposure would provide further evidence for the kidney’s involvement

in Cu acclimatization.

In BC, the current standards for Cu exposure to aquatic life under the

Contaminated Sites Regulation (CSR) are 30 and 50 µg/L in soft water (<50 mg/L

CaCO3) and hard water (100-125 mg/L CaCO3), respectively (BC MoE, 2014). Based

on the data in the present study, these standards are protective to fish, as our LC50

values of 40 and 150 µg/L Cu (soft and hard water, respectively) are both higher than

those in the CSR. Aquatic life water quality guidelines in BC are determined using a

number of endpoints (lethal concentrations, effective concentrations and inhibitory

concentrations) across many species of aquatic life in an attempt to be protective for all

aquatic life (Meays and Nordin, 2013). As the sublethal endpoints in our study may not

be useful for setting regulatory guidelines, as no sublethal effects were found at

concentrations very close to lethal, our data provides further support to the quality of the

standards in protecting fish, based on acute toxicity. This is of importance as Cu

remains a contaminant of concern in BC, in part, due to extensive historical and current

mining sites (e.g. Britannia, Mount Polley, Highland Valley), and regulators must ensure

the standards set out in Regulations and Acts are protective of the fauna found in our

province.

53

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