Hypoxia Tolerance and Anaerobic Capacity in Danio and Devario

HYPOXIA TOLERANCE AND ANAEROBIC CAPACITY IN DANIO AND DEVARIO

Lili Yao

B.Sc., Zhejiang University, 2008

A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF

THE REQUIREMENTS FOR THE DEGREE OF

MASTER OF SCIENCE

THE FACULTY OF GRADUATE STUDIES

(Zoology)

THE UNIVERSITY OF BRITISH COLUMBIA

(Vancouver)

December, 2012

ABSTRACT

It has been long suggested that hypoxia tolerant species should have a great capacity to generate energy through anaerobic pathways to maintain energy balance when oxygen is limited; however, this assertion has not been rigorously tested. In the present study, I characterized hypoxia tolerance in 12 groups representing 10 species from the genera Danio and Devario (with three strains of D. rerio) and examined whether there is a phylogenetically independent relationship between variation in hypoxia tolerance and anaerobic capacity as judged by enzyme activity and anaerobic substrate concentrations present in various tissues. Hypoxia tolerance was assessed using two measures: time to loss of equilibrium (LOE) and the oxygen tension that yields 50% LOE in a group of fish over 8 hr (TLE50). Time to LOE to low oxygen was very sensitive to changes in water

PO2, with no LOE seen over 8 hr in some species at 16 torr (2.1 kPa) and complete LOE within 30 min at 8 torr (1.1 kPa). At 12 torr (1.6 kPa) however, there was significant variation in time to LOE among all the species investigated. In three species (Danio rerio, Danio albolineatus and Danio choprai) time to LOE at 12 torr showed the same pattern of hypoxia tolerance as TLE50. Despite the variation in hypoxia tolerance seen among the species under study, there was very little variation in the critical oxygen tension (Pcrit), which is the environmental PO2 at which fish transition from an oxyregulating strategy to an oxyconforming strategy. Routine M varied between the O2 species, but the variation was primarily explained by body size and not hypoxia tolerance.

Anaerobic energy capacity was estimated by measuring maximal enzyme activities of pyruvate kinase (PK), lactate dehydrogenase (LDH) and creatine phosphokinase (CPK), and concentrations of glycogen and glucose in muscle, liver and brain, plus creatine

ii phosphate (CrP) and ATP in muscle. Through comparative analysis, I showed that the variation in hypoxia tolerance seen among species was related to some aspects of anaerobic energy metabolism, but not in a consistent fashion, indicating that other factors contribute to describing the variation in hypoxia tolerance.

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TABLE OF CONTENTS

ABSTRACT ...... ii TABLE OF CONTENTS ...... iv LIST OF TABLES ...... vi LIST OF FIGURES ...... vii LIST OF ABBREVIATIONS ...... viii ACKNOWLEDGEMENTS ...... x CHAPTER ONE: INTRODUCTION ...... 1 1.1 Causes of low oxygen in aquatic environments ...... 1 1.2 Definition of aquatic hypoxia ...... 2 1.3 Oxygen and energy production ...... 3 1.4 Why hypoxia is bad for fish ...... 4 1.5 Strategies to enhance hypoxia survival ...... 5 1.5.1 Enhancing oxygen extraction ...... 5 1.5.2 Suppressing metabolic rate ...... 7 1.5.3 Upregulating anaerobic ATP production ...... 7 1.6 Comparative analysis ...... 8 1.7 Danio and Devario ...... 10 1.8 Assessment of hypoxia tolerance and anaerobic capacity ...... 11 1.9 Thesis objective and hypothesis ...... 12 CHAPTER TWO: HYPOXIA TOLERANCE AND ANAEROBIC CAPACITY IN DANIO AND DEVARIO ...... 13 2.1 Introduction ...... 13 2.2 Materials and methods ...... 16 2.2.1 Experimental animals ...... 16 2.2.2 Experimental protocols ...... 17 2.2.3 Analytical procedures ...... 21 2.2.4 Phylogenetic analyses ...... 23 2.2.5 Statistical analyses ...... 24 2.3 Results ...... 25 2.3.1 Phylogenetic relationship ...... 25 2.3.2 Hypoxia tolerance and respirometry ...... 25 2.3.3 Anaerobic capacity ...... 26

2.3.4 Scaling ...... 29 2.4 Discussion ...... 30 2.4.1 The model system ...... 30 2.4.2 Hypoxia tolerance ...... 32 2.4.3 Hypoxia tolerance and oxygen uptake ...... 36 2.4.4 Hypoxia tolerance and anaerobic capacity ...... 38 2.4.5 Conclusion ...... 43 CHAPTER THREE: GENERAL DISCUSSION...... 54 BIBLIOGRAPHY ...... 60

LIST OF TABLES

Table 2.1 Maximal enzyme activities in 10 species of Danio and Devario …..……… 52

Table 2.2 Metabolite concentrations in 10 species of Danio and Devario ………..….. 53

LIST OF FIGURES

Figure 2.1 Time to LOE at 12 torr (a), critical oxygen tension (Pcrit; b), and phylogeny (c) for the Danio spp. and Devario spp. used in this study ……………………………….. 45

Figure 2.2 Correlation between time to LOE at 12 torr and TLE50 …………………… 46

Figure 2.3 M curves in P trials for the Danio spp. and Devario spp. used in this O2 crit study ………………………………………………………………………………….… 47

Figure 2.7 Correlation between fish whole-body mass and routine M for the Danio O2 spp. and Devario spp. used in this study except for Devario aequipinnatus …………... 51

vii

LIST OF ABBREVIATIONS

ADP adenosine diphosphate ANOVA analysis of variance ASR aquatic surface respiration ATP adenosine triphosphate °C degrees Celsius

CO2 carbon dioxide CPK creatine phosphokinase CrP creatine phosphate cyt cytochrome EDTA ethylenediaminetetraacetic acid DNA deoxyribonucleic acid Hb hemoglobin

Hb P50 partial pressure at 50% saturation of hemoglobin by oxygen HEPES hydroxyethyl piperazineethanesulfonic acid HK hexokinase hr hour LDH lactate dehydrogenase LOE loss of equilibrium min minute

M oxygen consumption rate O2 mRNA messenger ribonucleic acid

N nitrogen 2 NAD+ nicotinamide adenine dinucleotide

O oxygen 2 PCR polymerase chain reaction

P critical oxygen tension crit

viii

PFK phosphofructokinase

PIC phylogenetically independent contrast

PK pyruvate kinase

PO partial pressure of oxygen 2 TLE tension at loss of equilibrium 50 V maximum catalytic activity max

ACKNOWLEDGEMENTS

To my supervisor, Dr. Jeff Richards: Thanks for accepting me, this "random" student from across the ocean, into the wonderful lab you created, and being an amazing supervisor in every aspect.

To Gigi Lau, Rush Dhillon and Mark Scott: Thanks for being very helpful and supportive, especially when I first came to Canada, patiently explaining all the common sense in this country that I know nothing about.

To Ben Speers-Roesch, Milica Mandic and Tammy Rodela: Thanks for being so helpful whenever I had any research-related and unrelated questions, being almost like a second supervisor.

To Andrew Thompson, Matthew Regan, Dave Allen and Derrick Groom: Thanks for all the help and mental support in many random aspects.

To the whole Richards' Lab (again): Thanks for all the laughter-sharing moments; all the nerd talks and chitchats; all the inspirations in science, life and fashion. I feel very privileged to have been able to complete my M.Sc. program in such a wonderful lab.

To my committee members Drs. Bill Milsom and Colin Brauner: Thanks for the valuable suggestions concerning this project, and many inspirations.

To many people in the Department of Zoology, UBC: Thanks for being so helpful all the time. I am truly grateful for being a member of such a great department.

To Dr. Yuxiang Wang: Thanks for organizing an amazing China-Canada joint field course, and introducing me to this wonderful group of comparative physiologists. That was a great turning point in my life.

To Li: Thanks for all the patience when I was late due to unexpected delays during experiments, and all the unconditional support throughout the years. 尽在不言中。

CHAPTER ONE: INTRODUCTION

1.1 Causes of low oxygen in aquatic environments

Periods of low oxygen are common in aquatic systems due to phenomenon like winter ice cover, stratification, diurnal oscillations of algal respiration, and anthropogenic causes like pollution and eutrophication (Diaz & Breitburg 2009). In areas with cold winters, ice cover on lakes prevents diffusion of oxygen from the air to the surface water layer and the reduced light penetration and cold temperatures reduce photosynthesis in aquatic plants (Greenbank 1945). Furthermore oxygen levels are driven down by oxygen consumption of aquatic animals, plants (during the dark cycle) and bacteria. Severe depletions of oxygen or even complete anoxia can be present for weeks or even months in ice covered lakes (Greenbank 1945). Similarly, water column stratification can result in reductions in oxygen, particularly in the bottom layer of water and in sediments (CENR

2010). Apart from the possible long-term depletions in oxygen created by ice cover and stratification, short-term (eg. diel) oscillations in oxygen can occur in any isolated or stagnant body of water especially those with rich organic matter (CENR 2010). For example, tide pools, small ponds, rice paddies and shallow creeks can experience low oxygen tensions at night when photosynthesis stops and both aquatic animals and vegetation consume oxygen. More recently, anthropogenic causes of low oxygen are more prevalent, especially in eutrophic water where the respiratory needs of algae and other organisms surpass the oxygen exchange at the water surface. Red tides, one of the most severe forms of eutrophication can cause a complete depletion of oxygen in water

(Landsberg et al. 2009).

1.2 Definition of aquatic hypoxia

In its simplest form, hypoxia refers to oxygen levels that are below what is considered “normal”. Water quality regulators often define aquatic hypoxia as dissolved

O2 concentrations below 2–3 mg O2/L in marine and estuarine environments and below

5–6 mg O2/L in freshwater environments (Diaz & Breitburg 2009). From a biological perspective however, this definition is clearly too simple and defining what is hypoxic for a particular animal is complex. Animals vary in their ability to function under oxygen limited conditions and therefore what may elicit hypoxia-induced changes in one animal may not be perceived as hypoxic by other animals. Therefore, to take this variation into account, another definition of aquatic hypoxia is the water PO2 at which physiological function is first compromised, i.e., a sublethal effect in toxicological terms (Farrell &

Richards 2009), which yields a species-specific definition of hypoxia. Some of the sublethal effects are changes in behaviour (Kramer & McClure 1982; Nilsson et al. 1993;

Martin 1995), decreases in maximal metabolic rate, or the onset of hypoxemia (Farrell &

Richards 2009), which is a deficiency of oxygen in arterial blood.

Even for the same animal, its responses to hypoxia can be affected by many factors. Oxygen depletion can vary temporally, which can lead to different biological responses. Other shifts in environmental condition can also impact an organism’s response to hypoxia. For example, temperature affects metabolic rate (and dissolved oxygen levels), which further impacts upon the biological responses of aquatic organisms to reduced oxygen (Pörtner & Lanning 2009). Exercise, digestion, development and reproduction increase the energy demand of fish, which is likely to increase their sensitivity to hypoxia (Wang et al. 2009; Wu 2009). Overall, the development of a

2 biologically-relevant definition of hypoxia is complicated by many factors, but for the purpose of this thesis I define hypoxia as the water PO2 at which physiological function is compromised and severe hypoxia is the water PO2 that leads to cellular hypoxia in investigated species.

1.3 Oxygen and energy production

Most biological functions, including ion transport, protein synthesis and muscle contraction require energy in the form of ATP. ATP can be generated either by oxidative phosphorylation (commonly called aerobic metabolism) or substrate-level phosphorylation (commonly called anaerobic metabolism). Greater than 95% of the O2 consumed by a fish in normoxia is used as the terminal electron acceptor by the mitochondrial electron transport chain for ATP production via oxidative phosphorylation

(Richards 2009), which generates more than 95% of the ATP required by cells for fish and most other animals under fully aerobic, resting conditions (Wang & Richards 2011).

However, ATP can also be derived from oxygen-independent pathways, referred to as substrate-level phosphorylation, including creatine phosphate (CrP) hydrolysis and glycolysis (yielding lactate). Creatine phosphate serves as a phosphate energy buffer in the cell, which can rapidly donate phosphate groups to ADP forming ATP when catalyzed by creatine phosphokinase. Glycolysis is a series of 10 enzymatic reactions that generate ATP by partially oxidizing glucose, which is usually stored as the carbohydrate polymer, glycogen. Pyruvate, the end product of glycolysis, is transported into mitochondria and enters the Kreb Cycle under aerobic conditions. When oxygen is limited however, pyruvate is converted to lactate by the enzyme lactate dehydrogenase

(LDH), which decreases the concentration of pyruvate and maintains cellular [NAD+] concentration high to ensure that glycolysis can continue (Wang & Richards 2011).

1.4 Why hypoxia is bad for fish

Although ATP can be generated with or without oxygen, anaerobic energy production is much less efficient and only yields 1/15-1/30 ATP per mole of substrate consumed (Wang & Richards 2011). Thus when exposed to hypoxia, fish are facing the challenge of insufficient energy supply from aerobic pathways since oxidative phosphorylation is curtailed, or quick depletion of substrate (e.g. glycogen) if they drastically upregulate anaerobic metabolism to meet their routine metabolic rate.

Reductions in energy supply can compromise physiological functions of fish and other organisms. One of the sublethal effects of mild hypoxia to fish is reduced swimming capacity (Farrell & Richards 2009), which may affect the capability of fish to capture prey, escape predators or migrate. Hypoxia can also lead to retarded or suspended growth, primarily due to a reduced appetite (Wang et al. 2009). Reproduction and development can also be impaired by hypoxia through altered reproductive behaviors, affected quality of sperm and egg, reduced fertilization success, reduced hatching success and increased the incidence of malformation (Wu 2009).

Under severe hypoxia, apart from the challenge to maintain energy balance, fish also need to cope with ion disturbance associated with inadequate energy supply and the acidosis associated with anaerobic metabolism (Hochachka 1997; Bickler & Buck 2007).

Severe disturbance of cellular function can lead to cellular necrosis, which eventually leads to death of the whole animal (Richards 2009). Boutilier and St-Pierre (2000) hypothesized a hypoxia-induced sequence of events leading to cellular necrosis. During

4 hypoxia exposure, hypoxia-sensitive animals are unable to maintain cellular ATP levels at which point ATP-dependent cellular functions fail (e.g. ion regulation and protein synthesis). Failure of ion transporters results in depolarization of plasma and organelle membranes, Ca2+ accumulation in the cytosol, activation of phospholipases and Ca2+- dependent proteases and rupture of membranes, which lead to necrotic cell death

(Boutilier & St-Pierre 2000). The accumulation of cellular necrosis in crucial tissues like brain and heart will ultimately lead to death of fish (Vornanen et al. 2009).

1.5 Strategies to enhance hypoxia survival

Many species of fish thrive in natural aquatic habitats that experience hypoxia, and some of these species have been intensely investigated to elucidate the possible mechanisms that enhance hypoxia survival. When exposed to hypoxia, the first response of a fish is typically to try to increase efficiency of oxygen extraction and delivery from environment to tissues, followed by a suppression of their energy demands and an enhanced reliance on anaerobic sources for ATP production (Burggren & Randall 1978;

Hochachka & Somero 1984; West & Boutilier 1998).

1.5.1 Enhancing oxygen extraction

There are several ways fish improve their capacity to extract oxygen from the oxygen depleted environment. Behaviourally, fish can simply escape the stress by swimming away from hypoxic zones if possible. If this is not an option, fish can perform aquatic surface respiration (ASR), which allows them to access the more oxygenated water at the water-air interface (Kramer & McClure 1982). Some fish species also voluntarily emerge from the water to respire in air to increase O2 uptake. (Martin 1995).

Air breathing is another pronounced behavioral response found in a number of fish

5 species that can gulp air at the water surface and store it in an air-breathing organ e.g. modified swimbladder, gut or branchial chamber (Graham 1997).

The physiological strategies that facilitate oxygen uptake include, among other responses, increased perfusion of the gills, increased gill surface area, increased blood oxygen-carrying capacity and hemoglobin (Hb)-O2 binding affinity (Wells & Weber

1990; Nikinmaa 2002; Nilsson 2007; Wells 2009). Increased oxygen uptake at the gills can be achieved by altering gill ventilation by adjusting the volume and frequency of buccal pumping (Nilsson 2007). Previous studies have also shown that anoxia tolerant crucian carp (Carassius carassius) and goldfish (Carassius auratus) can remodel their gills to remove part of the interlamellar cell mass through apoptosis, which increases respiratory surface area for gas exchange (Nilsson 2007).

Blood oxygen-carrying capacity and Hb-O2 binding affinity are also known to be modified in hypoxia in various ways. Exposure to hypoxia can result in an increase in Hb concentration through release of erythrocytes from the spleen (Wells & Weber 1990).

Hypoxia exposure can also trigger the release of catecholamines into the circulation

(Randall & Perry 1992; Gamperl et al. 1994; Lowe & Wells 1996), which bind to erythrocyte surface receptors for adrenaline and noradrenaline and raise the pH in

+ + erythrocytes by affecting the Na /H pump, which in turn increases Hb-O2 affinity

(Nikinmaa & Heustis 1984; Nickerson et al. 2003; Nikinmaa 2002). Hemoglobin-O2 binding affinity can also be affected by changing intracellular concentrations of allosteric modulators like phosphate, chloride ion and water molecule. In the case of responding to hypoxia, the more relevant modulator is phosphate, which can bind to specific sites in the central cavity of the Hb and stabilize the structure in the low-affinity conformation

(Weber & Wells 1989; Val 2000). Under hypoxic conditions, anaerobic metabolism with accompanying acidosis leads to a reduction of intracellular ATP and GTP, thus less ATP and GTP can bind to Hb to decrease its affinity for oxygen, which results in an increase of blood-oxygen affinity (Wells 2009).

1.5.2 Suppressing metabolic rate

At oxygen tension below the point where the behavioural and physiological strategies that enhance oxygen uptake are effective, animals must modify cellular metabolism to either reduce metabolic demands or generate more energy using oxygen- independent means. The ability to suppress energy demand to match the limited capacity for oxygen-independent energy production is a prominent strategy for hypoxia survival

(Hochachka et al. 1996). Up to 70% reduction of metabolic rate (indicated by heat production) during hypoxia exposure has been observed in hypoxia tolerant species like goldfish (Carassius auratus; van Waversveld et al. 1989), tilapia (Oreochromis mossambiscus; van Ginneken et al. 1997) and crucian carp (Carassius carassius;

Johansson et al. 1995). Metabolic suppression can be achieved through behavioral strategies such as a reduction in locomotory activity (Nilsson et al. 1993; Schurmann &

Steffensen 1994) and moving to lower temperatures (Randall et al. 2006), or through biochemical processes that include the arrest of cellular process like protein synthesis, ion channel activity, RNA transcription and glyconeogenesis. (Buck & Hochachka 1993;

Hochachka et al. 1996; Lewis et al. 2007).

1.5.3 Upregulating anaerobic ATP production

Although ATP can be generated without oxygen, anaerobic energy production only yields 1/15-1/30 ATP per mole of substrate consumed compared with the full

7 oxidation of substrates via oxidative phosphorylation (Wang & Richards 2011). Thus, in order to maintain energy supply when oxygen is limited, upregulation of anaerobic metabolism is required. Many previous studies have shown that fish exposed to hypoxia elicit a strong activation of anaerobic energy production via glycolysis and CrP hydrolysis. This can be achieved by transcriptional upregulation of key enzymes in anaerobic pathways (Gracey et al. 2001; Martínez et al. 2006; Ngan & Wang 2009), and/or creating a large reservoir of anaerobic pathway substrates, mainly glycogen, before hypoxia exposure, which enable the fish to produce more ATP for longer periods of time at lower O2 levels (van den Thillart et al. 1980; van den Thillart & van Raaij,

1995).

1.6 Comparative analysis

Several researchers have examined anaerobic capacity in fish in relation to hypoxia tolerance (Gracey et al. 2001; Martínez et al. 2006; Ngan & Wang 2009), but most of our knowledge is from studies on single species under sometimes vastly different conditions, thus making it difficult to compare responses of different fish to hypoxia.

Furthermore, many of these studies also focus on the most hypoxia tolerant species.

Carefully performed comparative analysis that uses a number of species that vary in hypoxia tolerance and integrates phylogenetic information, is needed to better define the relationship between hypoxia tolerance and the capacity for anaerobic energy production.

With the development of the comparative approach, it is now possible to use the natural variation in hypoxia tolerance in fishes to assist in understanding the evolution of mechanisms underlying hypoxia tolerance.

Analysis that does not incorporate phylogenetic information makes the statistical assumption that all the species studied are equally distantly related to each other, that is they descended along a phylogeny with equal-length branches. However, in reality, the ancestral associations of species in the model system are usually hierarchical (Garland et al. 2005). Comparative methods that incorporate phylogenetic information have been applied in previous studies to examine environmental adaptations. Pierce and Crawford

(1997) found a correlation between the maximal activities of three glycolytic enzymes and environmental temperature in various species or subspecies in the genus Fundulus when the influence of phylogenetic relatedness was factored out, suggesting that high activities of these enzymes may be an adaptation to low environmental temperature.

Knight and Ackerly (2001) showed a strong negative phylogenetically independent correlation between heat shock protein levels following heat shock and maximum habitat temperature in eight species of Ceanothus (California Lilacs). Mandic et al. (2009) examined 12 species of sculpins and found phylogenetically independent correlations between hypoxia tolerance and low routine M , large gill surface area and low whole O2 blood haemoglobin-O2-binding affinity. Recently, Mandic et al. (in press) also found phylogenetically independent correlations between hypoxia tolerance and high anaerobic enzyme activities in brain in sculpins.

In the present study, phylogenetically independent contrast (PIC; Felsenstein 1985;

Garland et al. 1992) were applied to incorporate phylogenetic information to look for repeated evolution of a trait (hypoxia tolerance) correlated with putatively selective variables (capacity for anaerobic energy production) while factoring out the possible effects of shared ancestry among species (Feder et al. 2000). For the purpose of this study,

I used 10 species of Danio and Devario to investigate the relationship between hypoxia tolerance and capacity for anaerobic energy production.

1.7 Danio and Devario

Over the past twenty years, the zebrafish (Danio rerio) has emerged as one of the most important vertebrate models for genetics and developmental biology (Fishman,

2001). It is a tropical freshwater fish belonging to the family Cyprinidae of the order Cypriniformes. It is small and can be kept in large numbers in the laboratory with relative ease. It breeds all year round with large numbers of offspring. It develops rapidly and has a short generation time, with optical transparency during early development.

These attributes account for its popularity as a model species, and as a result, a large and growing amount of background information and genetic tools are available for this species (see www.zfin.org).

Despite its popularity in genetics and developmental biology, very little work has been done to investigate environmental adaptations using zebrafish. In the present study,

I employed a comparative approach, using 12 groups of zebrafish and its closely related species, i.e. Danio and Devario to investigate aspects of environmental adaptations.

Danio and Devario are popular aquarium fish, thus many strains and species are available from local pet fish suppliers. All 12 groups of fish (10 species) investigated in this study originated from south Asia. Their natural habitats include relatively still and shallow waterbodies, e.g. stagnant or slow-moving pools, rice paddies and small streams

(McClure et al. 2006; Spence et al. 2006; Engeszer et al. 2007; Roberts 2007). Thus, it is likely that these species experience short-term hypoxia at night when both aquatic animals and vegetation consume oxygen.

1.8 Assessment of hypoxia tolerance and anaerobic capacity

Hypoxia tolerance can be predicted using several methods. Two common methods are time to loss of equilibrium (LOE) and the oxygen tension that yields 50% LOE in a group (tension at loss of equilibrium; TLE50) (Chapman et al. 1995; Barnes et al. 2011).

Time to LOE and TLE50 are both direct measures of survival under hypoxic conditions.

Higher time to LOE means longer survival time at a certain water oxygen tension, thus it is an indicator of higher hypoxia tolerance. Similarly, lower TLE50 means 50% of the fish are capable of surviving at a lower oxygen tension, indicating higher hypoxia tolerance.

With both measurements, the indicator of failure to survive hypoxia is LOE, which suggests brain failure under hypoxic conditions. The lack of ATP in hypoxia leads to a rapid rise in extracellular K+ levels and a subsequent glutamate outflow, which results in a rise in intracellular Ca2+ and the activation of degenerative pathways, eventually leading to brain failure (Nilsson et al.1993; Arundine & Tymianski 2003).

Capacity for anaerobic energy production can be examined by measuring maximum catalytic activity (Vmax) of regulatory enzymes and concentrations of key substrates in anaerobic pathways. Important enzymes in anaerobic pathways include hexokinase (HK), phosphofructokinase (PFK), pyruvate kinase (PK), lactate dehydrogenase (LDH) and creatine phosphokinase (CPK). Hexokinase, PFK and PK are regulatory enzymes in the glycolytic pathway, thus indicators of overall glycolytic capacity. Lactate dehydrogenase, the terminal dehydrogenase in the production of lactate, can be measured as an indicator of the capacity for anaerobic glycolysis. Creatine phosphokinase, which generates ATP from phosphocreatine and ADP, is considered an

11 indicator of the capacity for ATP production from CrP hydrolysis, especially in tissues that consume ATP rapidly.

Key substrates in anaerobic pathways include glycogen, glucose and creatine phosphate (CrP). Glucose, the substrate of glycolysis, is usually stored in the form of glycogen. Energy stored as CrP can be rapidly mobilized to produce ATP. Thus, these metabolites can be considered as indicators of the capacity for oxygen-independent energy production that is important in oxygen-depleted environments.

Finally, previous studies have found tissue-specific responses to hypoxia (Gracey et al. 2001; Martínez et al. 2006; Ngan & Wang 2009), indicating that there may be tissue-specific adaptations to hypoxia. Thus, analysis of anaerobic capacity in multiple tissues is required to obtain a comprehensive picture of the role of anaerobic capacity in hypoxia tolerance.

1.9 Thesis objective and hypothesis

The objective of this thesis was to rigorously characterize hypoxia tolerance in various species from the genera Danio and Devario and attempt to determine whether there is a relationship between hypoxia tolerance and the capacity to generate ATP anaerobically. I hypothesized that more hypoxia tolerant species would have a greater capacity for anaerobic ATP production compared to intolerant species.

CHAPTER TWO: HYPOXIA TOLERANCE AND ANAEROBIC CAPACITY IN DANIO AND DEVARIO

2.1 Introduction

Periods of low oxygen (termed hypoxia) are common in natural aquatic systems due to factors such as winter ice cover, stratification or diurnal oscillations of algal respiration. The frequent occurrence and prevalence of hypoxia in the aquatic environment is thought, in some cases, to have played an important role in the selection of traits that increase tolerance to hypoxia. Indeed, among phylogenetically diverse fish species, there is variation in hypoxia tolerance with some species, such as the crucian carp (Carassius carassius) being able to survive months of severe hypoxia or even anoxia at cool temperatures (Nilsson & Renshaw 2004). On the other hand, active species like the Atlantic salmon, (Salmo salar) show obvious signs of distress (i.e. loss of equilibrium) even when exposed to short bouts of relatively mild hypoxia (e.g. 2.19 mg/L; Barnes et al.

2011). This remarkable variation in hypoxia tolerance across broad phylogenetic groups has lead to numerous investigators employing fish to examine the underlying mechanisms responsible for explaining variation in hypoxic tolerance.

Hypoxia tolerance is a complex trait that is dictated by physiological, biochemical, and cellular responses that are heavily influenced by the severity and length of hypoxia exposure. Due to large variation in sensitivity to hypoxia among species, the water PO2 at which these responses occur is likely to differ vastly between species. There are three main strategies used by hypoxia tolerance fishes to survive low oxygen conditions and all species studied to date employ some aspect of each strategy. When environmental oxygen tensions begin to decrease or only decrease by a relatively small amount, fish

13 employ changes that enhance oxygen extraction to maintain routine metabolic rate. For instance, increasing gill surface area (Nilsson 2007) and Hb-O2 binding affinity (Jensen

& Weber 1982; Claireaux et al. 1988) facilitate the extraction and delivery of oxygen to tissues under hypoxia. When oxygen tension drops further and fish are incapable of extracting enough oxygen from water anymore (below their Pcrit), they face the challenge of maintaining cellular energy balance, since they can no longer produce enough energy aerobically and therefore must rely on less efficient anaerobic energy production (Wang

& Richards 2011). As such, it has been suggested that hypoxia tolerant species should have a greater capacity to generate energy through anaerobic pathways. When fish are exposed to hypoxia, they upregulate certain aspects of anaerobic capacity, including maximal activities of the regulatory enzymes in anaerobic pathways (Martínez et al.

2006). In addition, anoxia-resistant species such as crucian carp (Carassius carassius) and goldfish (Carassius auratus) possess higher glycogen reserves compared to intolerant species like rainbow trout (Oncorhynchus mykiss) (van den Thillart & van Raaij, 1995).

Farwell et al. (2007) found higher levels of white muscle lactate dehydrogenase in the hypoxia tolerant species, pumpkinseed sunfish (Lepomis gibbosus), compared to the hypoxia sensitive bluegill sunfish (Lepomis macrochirus). Thus, capacity for anaerobic energy production likely plays an important role in hypoxia survival.

Although many studies have investigated the mechanisms of hypoxia tolerance, few studies have attempted to understand the evolution of these traits using a comparative approach. Chapman et al. (2002) studied multiple fish species in the Lake Victoria region in Uganda. By comparing swamp and lake-dwelling species, they described several mechanisms that may facilitate hypoxia survival, including low Pcrit, high

14 hemoglobin concentration, high hematocrit and large gill surface area. However, phylogenetic information among the species was not taken into account in this study.

With the introduction of the modern comparative approach, it is now possible to use the natural variation in hypoxia tolerance present in fishes to assist in understanding the evolution of mechanisms underlying hypoxia tolerance. This approach, termed phylogenetically independent contrast analysis (PIC; Felsenstein 1985; Garland et al.

1992), incorporates phylogenetic information to isolate selection-based traits from those merely due to phylogenetic history. This methodology has been adopted in previous studies to investigate the evolution of hypoxia tolerance. Mandic et al. (2009 & in-press) examined 12 species of sculpins and found phylogenetically independent correlations between hypoxia tolerance and low routine M , large gill surface area, low whole blood O2 haemoglobin-O2-binding affinity and high anaerobic enzyme activity in brain.

The objective of the present study was to rigorously characterize hypoxia tolerance in 10 species from the genera Danio and Devario (zebrafish and its closely related species including three strains of zebrafish) and examine whether there is a relationship between hypoxia tolerance and the capacity to generate ATP anaerobically. I hypothesize that hypoxia tolerant species will have a greater capacity for anaerobic ATP production compared to intolerant species. Zebrafish (Danio rerio) are a commonly used model organism in biology, particularly developmental biology (Meyer et al. 1993; Webb

& Schilling 2006). As a result, much is known of their genetics, but very little is known of this species’ environmental adaptations. Zebrafish and its closely related species originated from south Asia and are found in relatively still and shallow waterbodies

(McClure et al. 2006), which are likely to have nocturnal hypoxic conditions. Hypoxia

15 tolerance of these species was assessed using measures of time to loss of equilibrium

(LOE) at 8, 12 and 16 torr oxygen partial pressure, and the oxygen tension that yields

50% LOE in 8 hr (tension at loss of equilibrium; TLE50). Oxygen uptake capacity was assessed by measuring critical oxygen tension (Pcrit), which is the environmental PO2 at which fish transition from an oxyregulating strategy to an oxyconforming strategy

(Pörtner & Grieshaber 1993). Anaerobic energy capacity was examined by measuring maximal activities of regulatory enzymes and concentrations of key substrates in anaerobic pathways, including pyruvate kinase (PK), lactate dehydrogenase (LDH), creatine phosphokinase (CPK), glycogen and glucose in muscle, liver and brain, plus creatine phosphate (CrP) and ATP in muscle only.

2.2 Materials and methods

2.2.1 Experimental animals

Experimental animals were obtained from a number of sources. Three strains of

Danio rerio (zebra danio, leopard danio and golden long-fin danio) and Danio choprai,

Danio albolineatus, Danio margaritatus, Danio kyathit, Danio dangila, Devario sondhii and Devario aequipinnatus were obtained from two local aquarium fish supplier (Noah’s

Pet Ark & Aquarium West, Vancouver, British Columbia). Danio nigrofasciatus was obtained from Global Aquatics from Singapore. Danio meghalayensis was obtained from

Modern Pet in India.

Fish were transported to University of British Columbia and each species was held separately in 10 L tanks in a stand-alone, recirculating zebrafish rack system

(Aquatic Habitats, Apopka, USA). The recirculating system was filled with dechlorinated, buffered and well-aerated City of Vancouver tap water regulated at 27°C. Partial water

16 changes and water chemistry analysis were performed weekly. Fish were fed daily with

Hagen Tropical Fish Flakes, except 24 hr before experimental trials. All fish were allowed at least two weeks of recovery from transportation stress before experimentation.

All experimental procedures were approved by the UBC Animal Care Committee under protocol #A09-0611.

2.2.2 Experimental protocols

Time to LOE

I performed time to LOE analysis at three different oxygen tensions (8, 12 & 16 torr), using slightly different experimental setups. For the determination of time to LOE at 8 and 16 torr, I placed eight individuals of the same species into one of four 2-liter polyethylene mesh boxes that were held inside a 75-liter glass aquarium. The mesh boxes were weighed down with pebbles so that the top of the box was beneath the water surface to prevent ASR and the boxes were fitted with a hatch through which fish could be removed once they lost equilibrium. For the determination of time to LOE at 12 torr, I placed four individuals of each species into a 38-liter glass aquarium. The aquarium was divided into two equal sized chambers using 3 mm polyethylene mesh and the two chambers were used to separate larger species (> 40 mm; > 0.6 g) from smaller species (<

40 mm; <0.6 g). Each chamber was capped with polyethylene mesh that was suspended 1 cm beneath the surface to prevent ASR and the mesh caps were fitted with a hatch through which fish could be removed once they lost equilibrium. In both experimental setups, I used submersible pumps to circulate water and at least two gas diffuser stones for aeration. For all trials, water temperature was maintained at 27°C with a submersible

17 aquarium heater. After transfer, fish were allowed to habituate to the test apparatus for at least 12 hr under normoxic conditions before the determination of time to LOE. At the end of the habituation period, the gas supplying the gas diffuser stone was switched from air to N2 to induce hypoxia. The rate of water PO2 decrease was consistent among trials and within ~30 min, water PO2 stabilized at the desired level (8, 12 or 16 torr). Plastic bubble wrap was laid on the surface of the water in the aquaria to limit O2 ingress during hypoxia exposure. Water PO2 was monitored continuously in each mesh chamber using calibrated fibre optic oxygen probes (NeoFox, Ocean Optics Inc, Florida, USA). Oxygen tension was maintained at the desired level by adjusting N2 flow into the aquarium. Fish behaviour was monitored throughout the trials. When a fish showed loss of equilibrium, time was recorded, the fish was subsequently removed from the aquarium, species identified and then each individual was placed into a well-aerated aquarium for recovery.

A total of two trials were conducted at 8 torr resulting in 7 to 11 individuals tested from each of four species (Danio rerio (zebra danio), Devario aequipinnatus, Danio choprai and Danio albolineatus). Similarly, two trials were conducted at 12 torr yielding a n = 8 for all ten species (including three strains of Danio rerio). At 16 torr, a total of six trials were conducted for a n = 24 for each of the six species (Devario aequipinnatus, Danio choprai, Danio albolineatus, Danio margaritatus, Danio kyathit and three strains of

Danio rerio (zebra danio, leopard danio and golden long-fin danio)).

TLE50

Due to the number of fish needed per species per TLE50 trial, plus the difficulty to maintain various levels of hypoxia in different aquaria at the same time, it was not feasible to measure TLE50 in all 12 groups of fish, thus three species (Danio rerio (zebra

18 danio), Danio albolineatus and Danio choprai) with a good spread in hypoxia tolerance in time to LOE trials were chosen for TLE50 trials. To determine the TLE50, 10 individuals of each of three species were placed into eight, 10-liter glass aquaria filled with dechlorinated City of Vancouver tap water. Each aquarium was capped with polyethylene mesh that was suspended 1 cm beneath the surface of the water to prevent the fish from accessing the water-air interface, and bubble wrap covered the water surface to help minimize O2 ingress during hypoxia exposure. The mesh caps were fitted with a hatch through which fish could be removed once they lost equilibrium. Each aquarium was equipped with a gas diffuser stone. All aquaria were held in a temperature regulated water bath maintained at 27°C with a submersible aquarium heater. The water bath was also equipped with a small submersible pump to circulate water. After transfer, fish were allowed to habituate to the test apparatus for at least 12 hr under normoxic conditions before the determination of TLE50. At the end of the habituation period, the gas supplying the gas diffuser stone was switched from air to N2 to induce hypoxia. The water PO2 in the eight aquaria were decreased to one of eight different oxygen tensions over a 30 min period. The eight oxygen tensions used for the determination of TLE50 were 12, 15, 20, 25, 30, 35, 40 and 45 torr. Water PO2 was monitored every two minutes in each aquarium using calibrated NeoFox probes and oxygen tension was maintained at the desired level by adjusting N2 flow into the aquarium. Water oxygen tensions never deviated from the set point by more than 2 torr. Fish behaviour was monitored throughout the trials. When a fish showed LOE, it was removed from the aquarium and placed into a well-aerated aquarium for recovery. At the end of the 8 hr exposure the numbers of fish of each species that did not lose equilibrium were recorded.

Routine M & P O2 crit

Routine M and P were determined by closed respirometry using modified O2 crit protocols from Henriksson et al. (2008). Briefly, individual fish were placed into a respirometer modified from a 20 or 50ml plastic syringe with adjustable volume to match body mass to a 50-100× respirometer volume. The respirometer was submerged in a water bath containing dechlorinated and well-aerated City of Vancouver tap water set at

27°C. Each respirometer was affixed with inflow from a recirculating header tank that drew water from the water bath and circulated it through the respirometer back into the waterbath. After transfer, fish were allowed to habituate for at least 12 hr under normoxic conditions with continuous water circulation. At the beginning of the trial, the inflow and outflow of the respirometer were stopped and a fibre optic oxygen probe was inserted into the respirometer. The water in the respirometer was continuously stirred with a magnetic stir bar at one end to ensure a good mixing of water. Water PO2 was monitored continuously as the fish consumed oxygen and the trial was stopped when PO2 in the respirometer reached a point where it changed less than 2 torr over a period of 2 minutes.

At this point, the fish was removed from the respirometer, weighed and then placed into a well-aerated aquarium for recovery. The water in the respirometer was also weighed to determine the respirometer volume. Each trial took about 1 hr to complete. Except in

Danio choprai, no mortality was observed.

M was calculated from the slope of changes in water PO over time, corrected O2 2 for fish body mass and respirometer volume, and then plotted against the mean of water

PO2 for each 2-min intervals using the procedures described in Henriksson et al. (2008).

Critical oxygen tensions were calculated using the Pcrit Calculator software based on the

BASIC program designed by Yeager and Ultsch (1989), and further developed by

Department of Biology, Queen’s University. The calculated Pcrit was then confirmed by visual examination of the curve generated by plotting M versus environmental PO . If O2 2 the visual examination did not support the calculated Pcrit (mostly caused by fish struggling during the trial), the corresponding fish was removed from the data set.

Routine M was calculated as the average M at water PO above 40 torr, where O2 O2 2

M is constant and not influenced by changes in environmental PO . O2 2

Tissue sampling

Eight individuals per species were sampled from the normoxic holding tanks for biochemical analysis. Individual fish of each species were netted from their stock tanks and quickly euthanized with an overdose of benzocaine (250 mg/L; Sigma-Aldrich).

Once they lost equilibrium (usually within ~10 seconds), individuals were removed from the anaesthetic, blotted dry & weighed. Muscle (middle of trunk to caudal fin without tail, fins or skin), liver and brain were sampled from each fish, weighed, immediately frozen in liquid N2, and stored at -80°C until analysis. I was able to acquire samples of all tissues from all species, except Danio margaritatus, which were too small to collect liver.

Heart was not sampled in this study, because the hearts of the investigated species are too small (~1mg) for biochemical assays.

2.2.3 Analytical procedures

Enzyme activities

Tissue samples were prepared for enzyme analysis using similar protocols to those described in Mandic et al. (in press). Briefly, ~25 mg of muscle or 4 mg of liver or brain were sonicated in 250μl or 110μl, respectively of homogenization buffer (5 mM

EDTA and 0.1% Triton X-100 in 50 mM HEPES, pH 7.4) using a Kontes micro- ultrasonic cell disruptor. Homogenates were then centrifuged at 10,000 g and aliquots of supernatant were immediately frozen in liquid N2, and stored at -80°C until analysis.

These homogenates were used for the determination of the maximal activities of lactate pyruvate kinase (PK), lactate dehydrogenase (LDH) and creatine phosphokinase (CPK) using standard spectrophotometric assays (Mandic et al. in press).

Metabolite concentrations

Tissue samples were prepared for measurement of metabolite concentrations using similar protocols to those described in Mandic et al. (in press). Briefly, ~25 mg of muscle or 4 mg of liver or brain were sonicated in 500μl, 300μl or 150μl, respectively of

8% HClO4 using a Kontes micro-ultrasonic cell disruptor. Homogenates were vortexed and 50μl of homogenate slurry was removed from each sample and immediately frozen at

-80°C for glycogen analysis. The remaining homogenate was then centrifuged at 10,000 g.

The supernatants were immediately neutralized with 3M K2CO3 to pH 7-8, and centrifuged again. Aliquots of supernatant were assayed immediately for CrP and ATP, or frozen at -80°C for analysis of glucose. Concentrations of glycogen and glucose in brain, liver and muscle and CrP and ATP in muscle were determined using standard spectrophotometric assays (Bergmeyer 1983; Mandic et al. in press).

2.2.4 Phylogenetic analyses

DNA from two individuals per species for cyt b and three individuals per species for mitochondria 16s were extracted from muscle or gill using a DNeasy Tissue Kit

(Qiagen, Canada). Cyt b was amplified from each sample by PCR using universal primers:

5’-GACTTGAAAAACCACCGTTG-3’; 5’-CTCCGATCTCCGGATTACAAGAC-3’.

16s was amplified from each sample using universal primers: 16Sar-L, 5’-

CGCCTGTTTATCAAAAACAT-3’; 16Sbr-H, 5’-CCGGTCTGAACTCAGATCACGT-

3’ (Palumbi et al. 2002). PCR products were examined by gel and then sequenced by

NAPS Unit, Michael Smith Laboratories, UBC. The PCR product of each sample was sequenced in both directions and a consensus sequence for each species was established from all individuals of the species. Gene sequences of cyt b and 16s of each species were concatenated as the sequence for this species to generate the species tree. The concatenated sequences were aligned using MEGA 5.05 software and formatted as a nexus file in Mesquite version 2.75. Sequences were then imported into PAUP (v. 4,

Sinauer Associates, Inc. Publishers, USA) to construct maximum-parsimony, maximum- likelihood and neighbor joining gene trees. MODELTEST (Posada & Crandall 1998) was used to determine the likelihood model parameters that best fit the sequence data.

Heuristics searches were used to create the trees with bootstrap analysis of 1000 pseudoreplicates. A Bayesian consensus tree was created from 10 000 Bayesian trees generated using MRBAYES v. 3.0 (Ronquist & Huelsenbeck 2003). For all of our phylogenetic analysis, Oreochromis niloticus (tilapia) was used as an outgroup to root the tree.

Phylogenetically independent contrast (PIC)

In order to take phylogeny into account in our comparative analysis, I performed phylogenetically independent contrast (PIC; Felsenstein 1985; Garland et al. 1992) according to the methods outlined in Mandic et al. (2009). Briefly, the maximum- parsimony tree with branch lengths was imported into MESQUITE (Maddison &

Maddison 2007). PIC analysis was then performed with the PDAP module (Midford et al.

2003) in MESQUITE. I pruned the phylogenetic tree in MESQUITE to include only the species for which character data were available. I excluded the outgroup, Oreochromis niloticus, for all the PIC analysis as well as Danio margaritatus for analysis of liver character data. The branch lengths were log transformed so that the independent contrasts can first be standardized and receive equal weighting in subsequent correlation or regression analyses (Garland et al. 1992). P values, R squares and 95% confident intervals were exported from PDAP.

2.2.5 Statistical analyses

One way ANOVA, conventional (non-PIC) regressions and Pearson correlations were performed in SigmaStat v. 3.0. TLE50 and its 95% confidence intervals were calculated according to the Spearman-Karber Method (USEPA, 2002). PIC correlations were analysed in MESQUITE. Statistical significance was assumed at p<0.05.

There was variation in body mass of the species investigated. The effect of the variation in body mass in correlative analysis was taken into account by analysis of residuals.

2.3 Results

2.3.1 Phylogenetic relationship

In the present study, I constructed a reasonably well-resolved maximum- parsimony phylogeny based on concatenated sequences composed of ~1000 bp of cyt b sequence and ~600 bp of mitochondrial 16s gene from 10 species of Danio and Devario, plus Oreochromis niloticus (Figure 2.1). The phylogeny is supported by bootstrap values above 50 and there is general agreement with other published phylogenies containing

Danio and Devario species (Meyer et al. 1993; Sanger & McCune 2002; Parichy 2006;

Mayden et al. 2007).

2.3.2 Hypoxia tolerance and respirometry

The time to LOE was heavily influenced by oxygen tension. At 8 torr, which represents a PO2 corresponding to ~25% of Pcrit (see below) all species lost equilibrium within 30 minutes and there was no discernable difference in time to LOE between the species investigated. At 16 torr, which is a PO2 that corresponds to ~50% of Pcrit, many of the individuals investigated showed no behavioural signs of stress nor a loss of equilibrium over 8 hr exposure. Among the 24 individuals of each species examined, 16

Danio rerio (zebra danio), 7 Danio rerio (golden long-fin danio), 24 Danio rerio (leopard danio), 6 Danio albolineatus, 20 Danio kyathit, 4 Danio choprai, 9 Danio margaritatus and 1 Devario aequipinnatus showed no signs of LOE within 8 hr and no discernable signs of stress. However, among all species, roughly 82% (86 out of 105) of the individuals that did not last 8 hr showed LOE within the first hour of hypoxia exposure.

At 12 torr, which corresponds to ~38% of Pcrit, all species lost equilibrium within 2 hr and

25 there was significant variation in time to LOE among the species investigated (Figure

2.1). Danio nigrofasciatus was the most tolerant species investigated and Danio choprai was the least hypoxia-tolerant species investigated.

In three species (Danio rerio (zebra danio), Danio albolineatus and Danio choprai), there was significant variation in TLE50, which was correlated with the time to

LOE determined at 12 torr (Figure 2.2). Danio rerio is the most hypoxia tolerant, followed by Danio albolineatus, and the least hypoxia tolerant species is Danio choprai.

All species, except Devario aequipinnatus, showed a typical two-phase response in their M to decreases in environmental oxygen tension (Figure 2.3). At high oxygen O2 tensions >35 torr, M did not vary with decreases in water PO (oxyregulatory), while O2 2 at water PO <35 torr, M decreased with decreases in oxygen (oxyconforming). The 2 O2 oxygen consumption rate of Devario aequipinnatus showed an oxyconforming strategy across all PO examined (Figure 2.3) and therefore no discernable routine M or P 2 O2 crit was available for this species. Of the remaining 9 species, there was no significant variation in routine M among the species examined. There was very little variation in O2

Pcrit among the species investigated, except in Danio kyathit which had a significantly lower Pcrit than the majority of the other species except golden long-fin danio (a strain of

Danio rerio).

2.3.3 Anaerobic capacity

In this section, the data of the three species that differ in TLE50 will be presented first, followed by the complete data set on the ten species.

Anaerobic capacity among the three species that differ in TLE50

In brain, among the three species (Danio rerio, Danio albolineatus and Danio choprai), the activities of PK and LDH were significantly correlated with TLE50 and time to LOE at 12 torr where those species with low TLE50 and high time to LOE (i.e. hypoxia tolerant) had higher brain PK and LDH activities (Figure 2.4). Brain CPK activity was not correlated with TLE50 or time to LOE among these three species. For brain metabolites, there was no significant relationship between glycogen or glucose and TLE50 or time to LOE.

In liver, among the three species (Danio rerio, Danio albolineatus and Danio choprai), PK activity was significantly correlated with TLE50 and time to LOE at 12 torr, where species with low TLE50 and high time to LOE (i.e. hypoxia tolerant) had higher liver PK activity (Figure 2.5). However, liver LDH or CPK were not correlated with

TLE50 or time to LOE. For liver metabolites, there was no significant relationship between glycogen or glucose and TLE50 or time to LOE.

In muscle, among the three species (Danio rerio, Danio albolineatus and Danio choprai), PK activity was significantly correlated with TLE50 and time to LOE at 12 torr, where species with low TLE50 and high time to LOE (i.e. hypoxia tolerant) had lower muscle PK activity (Figure 2.6). Muscle LDH or CPK were not correlated with either

TLE50 or time to LOE. For muscle metabolites, muscle glycogen, glucose or CrP were not correlated with either TLE50 or time to LOE among the three species. However, muscle ATP was correlated with TLE50 and time to LOE, where species with low TLE50 or high time to LOE (i.e. hypoxia tolerant) had lower muscle ATP activity (Figure 2.6).

Anaerobic capacity among ten species that differ in time to LOE

In brain, among all ten species of Danio and Devario, there was significant variation in the activity of all enzymes examined (PK, LDH & CPK; Table 2.1). There was no correlation between brain PK or LDH and time to LOE at 12 torr (Figure 2.4).

There was also no conventional (Pearson) correlation between brain CPK and time to

LOE (p=0.079). However, there was a significant phylogenetically independent correlation between brain CPK and time to LOE (p=0.030; Figure 2.4). Species with high time to LOE (i.e. hypoxia tolerant) had higher brain CPK. For brain metabolites, there was no significant variation in glycogen or glucose among the ten species examined

(Table 2.2) and there was no significant relationship between these measures and time to

LOE.

In liver, among all ten species of Danio and Devario, there was significant variation in the activity of all enzymes examined (PK, LDH & CPK; Table 2.1). There was no correlation between liver PK and time to LOE among all species (Figure 2.5).

There was also no conventional (Pearson) correlation between liver LDH and time to

LOE (p=0.073). However, after correction with phylogeny, liver LDH was correlated with time to LOE (p=0.020; Figure 2.5). Species with high time to LOE (i.e. hypoxia tolerant) had lower liver LDH. There was no significant relationship between liver CPK and time to LOE. For liver metabolites, there was significant variation in glycogen and glucose among the ten species examined (Table 2.2) but there was no significant relationship between these measures and time to LOE.

In muscle, among all ten species of Danio and Devario, there was significant variation in all enzyme activities examined (PK, LDH & CPK; Table 2.1). However, there was no correlation between any muscle enzyme activities and time to LOE among all species. For muscle metabolites, there was significant variation in glycogen, glucose,

CrP and ATP among the ten species examined (Table 2.2), but there was no correlation between muscle metabolite concentrations and time to LOE.

2.3.4 Scaling

Allometric scaling is known to effect physiological variables (Goolish 1991;

Nilsson & Ostlund-Nilsson 2008). In the present study, there was significant variation in body mass among Danio and Devario. There was a significant correlation between body mass and routine M , which fits the widely recognized model that R=aMb (R as routine O2

M and M as body mass) and the value of mass exponent b here is -0.27 (Figure 2.7). O2

However, body mass was not correlated to time to LOE, TLE50 or Pcrit. Among all 10 species in this study, body mass did not regress with enzymes and metabolites except for brain LDH (r2=0.417, p=0.023), liver PK (r2=0.514, p=0.013), liver CPK (r2=0.387, p=0.041) and liver glycogen (r2=0.500, p=0.015). If we regress time to LOE against residuals of enzyme/metabolite levels to body mass, there are no significant correlations between time to LOE and brain LDH (r2=0.318, p=0.056), liver PK (r2=0.046, p=0.527), liver CPK (r2=0.006, p=0.827) and liver glycogen (r2=0.146, p=0.246). Among 3 species in which TLE50 was examined (Danio rerio (zebra danio), Danio albolineatus and Danio choprai), body mass did not regress with enzymes and metabolites except for brain

2 glycogen (r = 0.995, p=0.045). If we regress TLE50 against brain glycogen residuals of

29 body mass, the relationship is not significant (r2=0.891, p=0.214). Overall, our analysis suggests that the variation in body mass among species did not affect the determination of variation in time to LOE and TLE50, nor the relationship between these hypoxia tolerance measures and enzymes activities or metabolite concentrations.

2.4 Discussion

The goal of the present study was to determine whether there is a relationship between hypoxia tolerance and cellular capacity for anaerobic energy production. In order to examine this relationship while factoring out possible effects of phylogeny, I adopted a comparative approach using a model system of twelve groups of Danio and

Devario (three sub-species of Danio rerio, seven other Danio species and two Devario species). In the present study, I found variation in hypoxia tolerance among the species examined. Pcrit was not related to our measures of hypoxia tolerance. The variation in hypoxia tolerance seen among species was related to some aspects of anaerobic energy metabolism, but not in a consistent fashion.

2.4.1 The model system

The phylogenetic relationship among these fish (Figure 2.1) is in general agreement with other published phylogenies containing some of the same species (Meyer et al. 1993;

Sanger & McCune 2002; Parichy 2006; Mayden et al. 2007), with the exception of the phylogenetic position of Danio nigrofasciatus. In the present study, Danio albolineatus is closer to Danio rerio than Danio nigrofasciatus, while in Parichy (2006) Danio nigrofasciatus is closer to Danio rerio. However, all published phylogenies on Danio and

Devario, as well as our phylogeny, have nodes with bootstrap value less than 75, which mean that they are not very well supported. This may be due to insufficient divergence

30 among Danio and Devario to provide reliable phylogenies using the available sequences.

This may also explain the discrepancy between our and the published phylogenies, since both Danio albolineatus and Danio nigrofasciatus were branched from nodes that were not very well supported.

All species of Danio and Devario used in this study originated from south Asia where they are native to shallow ponds, small streams and rice paddies (McClure et al.

2006; Spence et al. 2006; Engeszer et al. 2007; Roberts 2007), which can experience periods of hypoxia, especially at night when both animals and vegetation consume oxygen. However, the majority of fish used in this study were not wild-caught from natural habitats but rather they were obtained from aquarium fish hatcheries that either breed fish or in a small number of cases collected fish from the wild in India and Burma.

As a result, our analysis is performed on a mix population of hatchery reared fish and wild-caught fish. Domestication in hatchery-reared fish is well known to alter behavioural and physiological traits, e.g. increased boldness, food intake, feeding latency and growth rate in Danio rerio (Moretz et al. 2007; Oswald & Robison 2008), which could also impact hypoxia tolerance. Furthermore, hatchery reared fish are likely to be reared under common-garden conditions without hypoxia exposure, while wild-caught fish are likely to be exposed to hypoxia in the natural habitats, which may also affect their hypoxia tolerance due to phenotypic plasticity (Rees et al. 2001; Barrionuevo et al. 2010).

Despite the possible effect of domestication and environmental influences, our study measured the phenotypic hypoxia tolerance and anaerobic capacity, thus the relationship between hypoxia tolerance and anaerobic capacity should not be affected by the mixed

31 source of fish. However, evolutionary arguments must be viewed cautiously due to our inability to directly link environmental conditions to the traits under study.

2.4.2 Hypoxia tolerance

Hypoxia tolerance is a complex trait that is heavily influenced by the severity and length of hypoxia exposure. When first exposed to hypoxia or exposed to mild hypoxia, fish will generally attempt to enhance oxygen uptake from the oxygen-depleted environment by modifying behaviour, respiratory and oxygen delivery function. When oxygen drops further and the mechanism to enhance oxygen uptake still cannot sustain

ATP turnover, fish need to either suppress their metabolic rate or increase anaerobic energy production to maintain the energy balance in the body. Due to the physiological and biochemical complexity underlying an organism’s response to hypoxia, analysis of hypoxia tolerance should be done using multiple techniques. The present study is one of the first studies to use multiple methods (time to LOE and TLE50) to examine variation in hypoxia tolerance among closely related species. Time to LOE and TLE50 are both direct measures of survival under relatively severe hypoxic conditions of short duration. In all cases, I monitored LOE, which suggests the brain failure under hypoxic conditions caused by the rise in extracellular K+ levels and subsequent glutamate outflow, which results in a rise in intracellular Ca2+ and eventually the activation of degenerative pathways (Nilsson et al.1993; Arundine & Tymianski 2003). Time to LOE in species of

Danio and Devario is highly dependent upon the level of oxygen used in the analysis. For example, at a PO2 of 12 torr, Danio kyathit and Danio albolineatus had similar time to

LOE (20.3±3.7 min and 21.5±1.5 min, respectively), but at 16 torr, Danio kyathit survived longer than Danio albolineatus (406.8±34.2 min and 154.4±35.3 min,

32 respectively). TLE50 measures the water PO2 at which 50% of the fish lose equilibrium in a certain time frame. It includes measures of tolerance to various levels of hypoxia. Plus in TLE50 trials, there was a pattern that the fish either lost equilibrium at the beginning of the trial, or they lasted for more than 8 hr, thus the choice of time frame is not likely to affect the result significantly. As a result, TLE50 may be a better measurement of hypoxia tolerance. However, due to the number of fish needed per species per trial, plus the difficulty to maintain various levels of hypoxia in different aquaria at the same time, it was not feasible to measure TLE50 in all 12 groups of fish, which is why three species with a good spread in hypoxia tolerance in time to LOE trials were chosen for TLE50 trials.

Critical oxygen tension for M (P ) have also been used as an indicator of O2 crit hypoxia tolerance in many studies (Mandic et al. 2009; Herbert et al. 2010; Barnes et al.

2011). However, Pcrit is not a direct measure of hypoxia survival, rather it is the water

PO2 at which fish transition from an oxyregulating strategy to an oxyconforming strategy

(Pörtner & Grieshaber 1993), thus Pcrit should be considered to be an indicator of animal’s capacity to extract oxygen from the environment rather than an explicit measure of survival and tolerance (Chapman et al. 2002). It is generally accepted that a lower Pcrit is beneficial in that it allows an animal to maintain routine M in lower oxygen tensions O2 compared with an animal with a higher Pcrit. This opinion is not shared by all however. It has been proposed that organisms with higher Pcrit values could benefit from reducing their metabolic rate at higher water PO2 values and therefore reducing overall metabolic demands before hypoxia gets too severe (Burggren & Randall, 1978). This latter proposal is not supported by recent analysis by Mandic et al. (in press) who demonstrated that

33 among 11 species of fish from the family Cottidae (sculpins), fish with lower Pcrit values also showed longer times to LOE at 6.4 torr compared with fish with higher Pcrit values.

Despite a significant relationship between Pcrit and time to LOE at 6.4 torr in sculpins

(Mandic et al. in press), in the present study, Pcrit is considered to be an indicator of oxygen extraction capacity rather than an indicator of hypoxia tolerance.

In the present study, hypoxia tolerance as assessed by time to LOE at 12 torr and

TLE50 was distributed across the proposed Danio and Devario phylogeny (Figure 2.1) showing potentially independent evolution of the trait in sister species. The two least hypoxia tolerant species (Danio choprai and Devario aequipinnatus) were on separate phylogenetic clades and the most hypoxia tolerant Danio investigated (Danio nigrofasciatus) was also separated from other hypoxia tolerant Danio spp. Some sister species had similar times to LOE at 12 torr (e.g. Danio dangila and Danio meghalayensis), while some sister species showed large differences in time to LOE at 12 torr (e.g. Danio kyathit and Danio nigrofasciatus). In general, the hypoxia tolerant/intolerant species were well spread out among the different phylogenetic clades, which, in theory, enhanced our ability to show a phylogenetically independent signal in the mechanisms underlying hypoxia tolerance.

The result of time to LOE also showed that within the same species, survival time was sensitive to water PO2. For example, survival time in Danio rerio exposed to 12 torr was only 31.6 minutes whereas at 16 torr, more than 75% of the individuals survived more than 8 hr. This high level of sensitivity to oxygen tension may be explained by sensitivity of oxygen uptake capacity at different water PO2, possibly due to high Hill coefficients in their Hb-O2 binding affinity, which result in steep slopes of Hb-O2

34 dissociation curve. Thus, small changes in PO2 would result in big differences in percent saturation of Hb-O2 binding, which leads to great differences in the amount of O2 delivered to tissue for hypoxia survival. Further investigation of Hb-O2 binding affinity in

Danio and Devario is needed to test this hypothesis.

In addition, during our analysis of both time to LOE at 16 torr and TLE50, there was a pattern that within the same species, fish either lost equilibrium at the beginning, or they lasted for more than 8 hr. For example, among the 24 individuals of Danio rerio

(zebra danio), 7 of them lost equilibrium within the first 40 minutes, but the rest lasted more than 8 hr. Similar phenomenon (LOE at beginning or never) was reported in other studies (Zhou et al. 2000; Ngan & Wang 2009). One possible explanation of this phenomenon is the shifting of Hb-O2 binding curve in the investigated individuals as a response to hypoxia during the trial. Previous studies found hypoxia exposure triggers the release of catecholamines into circulation (Randall & Perry 1992; Gamperl et al. 1994;

Lowe & Wells 1996). This could increase the O2-carrying capacity of the blood in fish by raising the pH of the erythrocyte, and thereby increasing Hb-O2 affinity via the Bohr effect (Nikinmaa & Heustis 1984; Nickerson et al. 2003; Nikinmaa 2002). Hemoglobin-

O2 binding affinity can also be modulated by altering concentration of organic phosphate

(Weber & Wells 1989; Val 2000). Under hypoxia, acidosis from anaerobic metabolism decreased the concentration of ATP and GTP, which in turn results in an increase of blood-O2 affinity (Wells 2009). Furthermore, hypoxia can lead to an increase in Hb concentration through release of erythrocytes from the spleen, which increases the O2- carrying capacity of the blood (Wells & Weber 1990). All these responses to hypoxia may enhance oxygen delivery to the tissue for energy production. Before these responses,

35 individuals in time to LOE and TLE50 trials may have had slightly varied Hb-O2 affinity or Hb concentration that some reached LOE sooner and some would survive slightly longer. However, those that survived longer had the added benefit of having enough time to trigger those responses to hypoxia discussed above, which greatly increases their survival time.

2.4.3 Hypoxia tolerance and oxygen uptake

To study the mechanisms behind variation in hypoxia tolerance, I used Pcrit as an indicator of oxygen uptake capacity from the environment when oxygen is limited

(Chapman et al. 2002). Pcrit represents the point at which oxygen uptake is first compromised. Oxygen uptake will start to drop when water PO2 drops below Pcrit. When fish are exposed to water PO2 far below Pcrit, mechanisms for maintaining cellular energy balance (metabolic rate suppression and anaerobic energy metabolism) are activated

(Farrell & Richards 2009).

In the present study, most species had similar Pcrit values, thus it is likely that they have similar capability of oxygen extraction, in spite of the variation in time to LOE and

TLE50 seen among our species. This disagrees with the study of Mandic et al. (in press), who found a correlation between LOE50 and Pcrit among 11 species of sculpin. Thus it is likely that the variation in hypoxia tolerance among sculpins can be partially explained by variation of oxygen uptake capacity, while the variation among Danio and Devario is likely to be caused by something other than variation of oxygen uptake capacity. Since time to LOE was measured at oxygen tensions far below Pcrit, when oxygen uptake was greatly compromised, it is likely that the variation in hypoxia tolerance in Danio and

Devario can be explained by variation in their capability to maintain energy balance

(suppress metabolic rate and/or enhance anaerobic energy production) under severe hypoxia.

Another observation from Pcrit trials was a unique response from Devario aequipinnatus. All species, except Devario aequipinnatus, showed a typical transformation between oxyregulation and oxyconformation as a response to decreases in environmental oxygen tension (Figure 2.3). However, Devario aequipinnatus appears to be an oxygen conformer that does not have a Pcrit (Figure 2.3). This has also been observed in toad-fish, Opsanus tau (Hall 1929), brown bullhead catfish, Ictalurus nebulosus (Marvin & Heath 1968), sturgeon, Acipenser transmontanus (Burggren &

Randall 1978) and plaice, Pleuronectes platessa (Steffensen et al. 1982). This could be an indicator of an inferior ability to maintain oxygen uptake during a reduction in water oxygen tension (Steffensen et al. 1982), which is likely to be the case for Devario aequipinnatus, since it was the second least hypoxia tolerant species among species investigated. However, oxygen conforming could also be an early onset of metabolic suppression under hypoxia exposure so that less anaerobiosis is needed (Burggren &

Randall 1978).

Routine M is a measure of the resting energy demands of the fish that takes into O2 account random movements and other basic life functions e.g. maintenance of ion gradients and protein synthesis. Previous studies found that species with low routine M O2 tend to have greater hypoxia tolerance. Mandic et al. (2009) found a significant phylogenetically independent correlation between P and routine M among 12 crit O2 sculpin species investigated. Species with low routine M had low P . However, in the O2 crit

37 present study, there was no significant correlation between routine M and time to LOE O2 at 12 torr or P . Instead, there was a significant correlation between body mass and M , crit O2 which showed the allometric scaling of metabolic rate with body mass with typical scaling coefficient R=10.76*M-0.27 (R as mass-specific routine M , M as body mass and O2 the exponent is the scaling coefficient). If we express this scaling relationship as B=aMb where B is whole organism metabolic rate, i.e. R*M, mass exponent b is then -0.27

+1=0.73. Our result agrees with Kleiber's ¾ law (Kleiber 1932; Kleiber 1961). More specifically for fish, Jobling (1985) concluded that the b values usually fell in the range of 0.65-0.90. Clarke (1999) summarized the data from 138 studies of 69 species of teleost fish and found that the b value ranged from 0.40 to 1.29, 80% of which ranged from 0.65-

0.95. Our exponent b values fell within the range. Apart from the scaling relationship between body mass and M , I did not see relationships between body mass and the O2 measured variables, or the variation in body mass did not affect the relationship between hypoxia tolerance measures and enzymes activities or metabolite concentrations, as verified by residual analysis.

2.4.4 Hypoxia tolerance and anaerobic capacity

High anaerobic capacity is an advantage for fish when exposed to severe hypoxia.

During exposure to hypoxia, fish upregulate the key enzymes in anaerobic pathways to increase anaerobic energy production in a tissue specific manner (Gracey et al. 2001;

Martínez et al. 2006; Ngan & Wang 2009). However, since LDH, PK and CPK are all regulated transcriptionally instead of post-translationally, there is a protracted timeframe for increasing the levels of activity for these enzymes. As a result, transcriptional

38 regulation is frequently utilized in order to respond to chronic stresses (days to weeks)

(Ngan & Wang 2009). However, in their natural habitats, both Danio and Devario likely experience diurnal fluctuations in O2, instead of prolonged hypoxia. In the present study, their hypoxia tolerance was also measured under acute hypoxia exposure (<8 hr), which is not adequate time for the fish to transcriptionally upregulate the enzymes measured.

Thus, in order to survive in their O2 variable environment, members of the Danio and

Devario genera must have pathways already primed for hypoxia or be able to non- transcriptionally upregulate their capacity to survive low oxygen conditions.

In brain, there was a significant correlation between TLE50/time to LOE and both

PK and LDH levels among the three species (Danio rerio, Danio albolineatus and Danio choprai). In addition, there was also a significant phylogenetically independent correlation between time to LOE and brain CPK among all 12 groups of fish (the conventional non-PIC correlation was close to but not significant (p=0.079)). Species with higher activities of these enzymes were more hypoxia tolerant (lower TLE50 or higher time to LOE). These results are in agreement with those of Mandic et al. (in press), who found a phylogenetically independent relationship between hypoxia tolerance and brain LDH, PK and CPK activities in 12 species of sculpins. Other studies also found that when fish are exposed to prolonged hypoxia, they tend to upregulate their brain anaerobic enzymes. Martínez et al. (2006) found increased activities of hexokinase, triose phosphate isomerise and phosphoglycerokinase in Fundulus grandis brain after a 4-week hypoxia exposure. Ngan & Wang (2009) found that Danio rerio brain showed an increase in LDHa transcript level, when exposed to 48 and 96 hr of hypoxia. Overall, our data and

39 that of others suggest that higher anaerobic capacity in brain is related to hypoxia survival and represents a putative adaptation to hypoxia survival.

In liver, there was a significant correlation between TLE50/time to LOE and PK among the three species. Species with higher liver PK activities were more hypoxia tolerant. This agrees with previous studies showing that when exposed to prolonged hypoxia, fish upregulate their liver anaerobic enzymes as a strategy to cope with the stress. Martínez et al. (2006) found increased activities of five glycolytic enzymes in

Fundulus grandis liver after a 4-week hypoxia exposure. Gracey et al. (2001) found elevated mRNA levels of glycolytic enzymes in Gillichthys mirabilis liver after 24, 72 and 144 hours of hypoxia exposure. Thus, higher liver glycolytic capacity may contribute to hypoxia survival.

Moreover, a significant phylogenetically independent correlation between liver

LDH and time to LOE was found among all species (the conventional non-PIC correlation was close to, but not significant (p=0.073)). However in this correlation, species with higher hypoxia tolerance (higher time to LOE) had lower LDH, which seems to be contradictory to the hypothesis that higher anaerobic capacity enhances hypoxia survival. One possible explanation is that in the present study, LDH activity was measured by the speed of conversion from pyruvate to lactate. Under hypoxic conditions, the liver plays an important gluconeogenic role, producing glucose for other tissues

(Zhou et al. 2000). The lactate produced from other tissues may be transported to liver and serves as the substrate for glyconeogenesis, which can convert lactate to glucose

(Phillips & Hird 1977). Thus higher capacity for glyconeogenesis in liver could appear as lower general liver LDH activity in the assay I used. Martínez et al. (2006) also found

40 that activities of gluconeogenic enzymes like malate dehydrogenase and fructose-1,6- bisphosphatase increased in Fundulus grandis liver after 4-week hypoxia exposure.

In muscle, a negative correlation was found between hypoxia tolerance (indicated by TLE50 and time to LOE) and both muscle PK and ATP among the three species.

Species with lower muscle PK and ATP were more hypoxia tolerant. This agrees with the previous findings where hypoxia exposed fish have a tendency to downregulate metabolism in white muscle in order to conserve energy (Hochachka, 1986; Guppy &

Withers, 1999; Gracey et al. 2001; Martínez et al. 2006), since tissues other than muscle, like brain, heart and liver are more crucial for hypoxia survival.

From the data shown in Figure 2.4-2.6, we can see that there were large differences in the relationships between the measures of hypoxia tolerance and the enzyme/metabolite data when we chose different groups of species to look at. For example, there was a significant correlation between brain PK or LDH and hypoxia tolerance among the three species (Danio rerio, Danio albolineatus and Danio choprai), but not among all ten species; brain CPK was related to hypoxia tolerance among ten species, but not among those three species. In general, among the three species for which

I have the TLE50 data, capacity for anaerobic energy production seems to be a good explanation for the variation in hypoxia tolerance. The three species selected for TLE50 measurements showed a good spread in hypoxia tolerance. However, when I added the rest of the species, which are mostly intermediate hypoxia tolerant species to the analysis, the relationship between hypoxia tolerance and anaerobic capacity became much weaker.

The difference in this relationship among different groups of fish is likely due to the complexity of hypoxia tolerance. It is possible that the three species (Danio rerio, Danio

41 albolineatus and Danio choprai) have similar oxygen delivery capacity or metabolic rate alteration under hypoxic conditions, and their variation in hypoxia tolerance is mostly due to the variation in anaerobic capacity; but this is possible not the case for the other species. Mandic et al. (2009) found that hypoxia tolerance was related to mass-specific gill surface area and whole blood Hb-O2 binding affinity (P50) among 12 species of sculpins. Thus, among the species of Danio and Devario for which TLE50 was not measured, the variation in hypoxia tolerance might be explain by variation in mass- specific gill surface area or Hb P50, which can be examined in future studies. Furthermore, the correlations between hypoxia tolerance and anaerobic capacity were phylogenetically corrected among ten species, but not among those three species (due to the insufficient degrees of freedom). However, from the phylogeny for the Danio and Devario (Figure

2.1), we can see that Danio rerio is more closely related to Danio albolineatus than

Danio choprai, thus we may need to take extra caution when interpreting the results for these three species shown in Figure 2.4-2.6.

In the present study, our comparative analysis among all 10 species (12 groups of fish), yielded some significant correlations between time to LOE and some of the enzymes or metabolites measured, but only a small portion of them. Thus, in this model system, variation in anaerobic capacity does not seem to provide a strong explanation of the variation in hypoxia tolerance.

It is well established that variation in substrate of anaerobic energy production

(glycogen, glucose or CrP) can impact hypoxia survival (Richards 2009). However, this idea is primarily supported by studies that compared very hypoxic tolerant species to very intolerant ones. For example, studies found that anoxia-resistant species such as crucian

42 carp (Carassius carassius) and goldfish (Carassius auratus) possess higher glycogen reserves compared to intolerant species like rainbow trout and bluegill sunfish (van den

Thillart & van Raaij, 1995). Those hypoxia tolerant champions (crucian carp or goldfish) need to cope with long-term hypoxia/anoxia (weeks and even months) when anaerobic fuel storage is crucial. Thus, large anaerobic fuel storage may be advantageous for long- term hypoxia, but not the short-term hypoxia that Danio and Devario encounter in both their natural habitats and in this experiment.

During hypoxia exposure, besides the challenge of keeping energy balance, animals also need to cope with acidosis (proton and lactate) from anaerobic metabolism and ion disturbance associated with inadequate energy, which are the main reasons for death in hypoxia (Hochachka 1997; Bickler & Buck 2007; Richards 2009). In the present study, the variation in hypoxia tolerance cannot be explained well by the capacity for oxygen uptake (as measured by Pcrit) or anaerobic metabolism. Thus the cause of the variation in hypoxia tolerance may be due to the ability of different species to direct more energy to maintaining ion balance, or coping with acidosis. Further study is clearly required.

2.4.5 Conclusion

In conclusion, our study showed that there was variation in hypoxia tolerance among species of Danio and Devario. The time to LOE was very sensitive to changes in water PO2. Through comparative analysis, I showed that there was no relationship between Pcrit and our measures of hypoxia tolerance, suggesting that differences in oxygen uptake by different species is not likely to be responsible for explaining the variation in hypoxia tolerance. The variation in hypoxia tolerance seen among species of

Danio and Devario was related to some aspects of anaerobic energy metabolism, but not

43 in a consistent fashion, indicating that other factors contribute to describing the variation in hypoxia tolerance.

Figure 2.1 Time to LOE at 12 torr (a), critical oxygen tension (Pcrit; b), and phylogeny (c) for the Danio spp. and Devario spp. used in this study. In panel (c), the numbers on the left of the branches are bootstrap values of maximum-parsimony tree. The numbers in italic on the right of the branches are clade credibility value of the Bayesian analysis. The neighbor-joining and maximum methods yield the same tree topologies but with 1 or 3 uncertain clades (bootstrap value <50). In panels (a) and (b), the error bars are standard errors, and the letters above the bars denote significant differences where bars that share a letter are not significantly different (P>0.05). In panel (b), N/D above D. aequipinnatus refers to not determined because they are oxyconformers.

Figure 2.2 Correlation between time to LOE at 12 torr and TLE50 (y = -0.29x+26.64, r2=0.998, p= 0.029). The error bars of time to LOE show the standard errors. The error bars of TLE50 show the 95% confidence intervals. Numbers 1–3 represent different species: (1) Danio rerio (zebra danio), (2) Danio albolineatus, (3) Danio choprai.

Figure 2.3 M curves in P trials for the Danio spp. and Devario spp. used in this O2 crit study. The error bars show the standard errors. The x-axes for all graphs are PO2 presented in torr. The y-axes for all graphs are M presented in µmol/g/h. P of D. O2 crit aequipinnatus is not available because they are oxyconformers.

Figure 2.4 Correlations between TLE50 (Conventional, non-PIC) among 3 species / time to LOE (Conventional, non-PIC) among 3 species / time to LOE (PIC) among 10 species and brain PK (a: r2=1.000, p=0.004; b: r2=0.997, p=0.033; c: non-PIC: r2=0.001, p=0.928, PIC: r2=0.018, p=0.695), brain LDH (d: r2=0.995, p=0.045; e: r2=0.999, p=0.016; f: non- PIC: r2=0.217, p=0.127, PIC: r2=0.165, p=0.214), and brain CPK (g: r2=0.824, p=0.275; h: r2=0.789, p=0.304; i: non-PIC: r2=0.278, p=0.079, PIC: r2=0.423, p=0.030). The solid lines in TLE50 correlations and time to LOE correlations among 3 species are non-PIC regressions. The solid lines in time to LOE correlations among 10 species are PIC regressions. The dash lines are non-PIC regressions. The dotted lines are PIC 95% confidence intervals. The error bars show the standard errors. The scales of axes between the graphs of 3 species and 10 species are not the same. Time to LOE data in this figure are time to LOE at 12 torr. Numbers 1–12 represent different species/sub-species: (1) Danio rerio (zebra danio), (2) Danio albolineatus, (3) Danio choprai, (4) Danio rerio (golden long-fin danio), (5) Danio rerio (leopard danio), (6) Danio kyathit, (7) Danio nigrofasciatus, (8) Danio margaritatus, (9) Danio dangila, (10) Danio meghalayensis, (11) Devario sondhii, (12) Devario aequipinnatus.

Figure 2.5 Correlations between TLE50 (Conventional, non-PIC) among 3 species / time to LOE (Conventional, non-PIC) among 3 species / time to LOE (PIC) among 9 species and liver PK (a: r2=0.999, p=0.024; b: r2=1.000, p=0.005; c: non-PIC: r2=0.006, p=0.816, PIC: r2=0.005, p=0.844) and liver LDH (d: r2=0.012, p=0.931; e: r2=0.004, p=0.960; f: non-PIC: r2=0.314, p=0.073, PIC: r2=0.513, p=0.020). See figure 2.4 caption for more details.

Figure 2.6 Correlations between TLE50 (Conventional, non-PIC) among 3 species / time to LOE (Conventional, non-PIC) among 3 species / time to LOE (PIC) among 10 species and muscle PK (a: r2=1.000, p=0.007; b: r2=0.999, p=0.022; c: non-PIC: r2=0.156, p=0.204, PIC: r2=0.263, p=0.107) and muscle ATP (d: r2=0.999, p=0.025; e: r2=1.000, p=0.004; f: non-PIC: r2=0.027, p=0.612, PIC: r2=0.001, p=0.924). See figure 2.4 caption for more details.

Figure 2.7 Correlation between fish whole-body mass and routine M for all the Danio O2 spp. and Devario spp. used in this study except for Devario aequipinnatus (y = 10.76x-0.27, r2= 0.736, p= 0.0007). The error bars show the standard errors. Numbers 1–11 represent different species/sub-species: (1) Danio rerio (zebra danio), (2) Danio albolineatus, (3) Danio choprai, (4) Danio rerio (golden long-fin danio), (5) Danio rerio (leopard danio), (6) Danio kyathit, (7) Danio nigrofasciatus, (8) Danio margaritatus, (9) Danio dangila, (10) Danio meghalayensis, (11) Devario sondhii.

Table 2.1 Maximal enzyme activities in 10 species of Danio and Devario.

Brain Liver Muscle

PK LDH CPK PK LDH CPK PK LDH CPK

Danio choprai 6.94±0.33 a,b,c,e 116.67±2.74a 834.83±24.20 a,b 1.85±0.40 a,b 153.31±16.93 b,c 77.50±17.55 b,e 5.75±0.29 c,d 236.72±12.00 c,d,e 5597.34±152.71a

Devario 6.29±0.25 a,b,e 87.98±2.03b 771.66±26.29 a 1.13±0.31 a,c 179.58±13.72 a,c 14.22±1.67 d 5.78±0.38 c,d 278.26±23.01 b,e,f 5357.57±154.52b aequipinnatus

Danio margaritatus 4.78±0.24 d,e 128.45±2.86 a 763.28±12.68 a N/A N/A N/A 3.79±0.34 d 219.11±19.55 d,e,f 4325.78±33.76c

Danio kyathit 5.21±0.38 d,e 134.55±2.27 a 782.82±46.00 a 3.70±0.49 b 191.74±16.06 a,b 76.24±8.91 b,e,f 4.85±0.52 d 324.32±22.44 a,b 5939.68±80.35d

Danio albolineatus 8.07±0.22 a,b,c 122.84±3.67 a 841.34±11.61 a,b 2.66±0.67 a,b 242.44±23.81 a 51.99±7.96 c,d,e 5.02±0.21 d 280.20±16.00 b,e 6289.50±109.99e

Danio rerio (golden 8.29±0.30 a,b,c 132.26±6.51 a 790.11±25.89 a 2.84±0.31 b,c 133.57±18.15 b,c 111.08±8.05 a,b 3.57±0.26 d 180.00±13.96 d 5731.79±109.83f long-fin)

Devario sondhii 4.94±0.24 d,e 127.26±5.62 a 754.06±39.67 a 2.30±0.58 a,b 121.95±19.15 b,c 21.56±3.87 c,d 21.79±1.39 a 411.92±20.56 a 4725.46±94.88g

Danio rerio 8.51±0.51 b,c 125.17±2.53 a 818.26±15.48 a 3.42±0.41 b 141.88±19.51 b,c 113.72±5.10 a,b 4.25±0.29 d 212.24±14.96 d,e,f 6577.71±106.84h (leopard) Danio 4.87±0.42 d,e 120.34±1.68 a 695.24±26.66 a 0.76±0.15 a 104.71±13.06 c 76.22±9.16 b,e,f 23.61±0.85 a 234.64±14.53 d,c,e,f 4896.67±132.77i meghalayensis

Danio rerio (zebra) 9.22±0.85 c 131.08±5.21 a 842.18±32.76 a,b 3.62±0.46 b 164.96±15.99 a,c 143.53±13.08 a 4.23±0.30 d 194.89±20.65 d,f 5973.26±167.01j

Danio dangila 3.34±0.08 d 126.91±1.88 a 787.28±20.35 a 0.87±0.14 a 111.41±8.90 c 36.27±2.72 d,c,f 7.78±0.39 c 309.84±14.34 b,c 5334.78±110.19k

Danio 6.09±1.14 a,e 132.43±8.33 a 1014.77±100.47b 2.62±0.24 a,b 119.77±9.77 b,c 56.86±3.74 c,e 13.01±0.97 b 317.32±20.39 b,c 5142.34±108.78l nigrofasciatus Data are mean±SE, presented in µm/min/g wet tissue. Sample size was 8 for all species except for 6 for Devario sondhii. No liver data available for Danio margaritatus. Within a given column, values that share a superscript letter are not significantly different.

Table 2.2 Metabolite concentrations in 10 species of Danio and Devario. Brain Liver Muscle

glycogen glucose glycogen glucose glycogen glucose CrP ATP

a a a,b a b a,b b,d b,c Danio choprai 10.62±2.53 1.30±0.29 558.31±99.25 8.65±0.80 18.93±2.18 0.91±0.10 7.24±0.73 7.07±0.61

a a a,b a a,b a,b b,c,f b Devario aequipinnatus 5.85±1.12 0.67±0.15 627.12±41.60 14.26±1.78 34.34±4.66 0.90±0.10 7.70±0.78 7.66±0.51

a a b a b a,b Danio margaritatus 16.88±5.24 1.77±0.29 N/A N/A 18.80±3.75 0.23±0.09 4.56±0.62 4.32±0.43

a a a,b a a,b a a,b,c,f a,c,d Danio kyathit 7.24±0.84 0.70±0.19 659.49±68.29 8.77±0.48 23.61±2.22 0.39±0.16 9.58±1.05 4.30±0.82

a a a,b a b b a,b,c,f a,b Danio albolineatus 7.63±0.82 1.23±0.15 547.38±46.50 12.61±2.10 18.79±2.07 1.22±0.16 8.50±1.03 4.95±0.77

a a a a b a,b b,c,f a,b Danio rerio (golden long-fin) 17.26±5.18 1.48±0.36 378.76±62.80 11.45±1.35 22.80±3.88 0.63±0.07 8.22±1.00 5.30±0.79

a a a,b b a a,b a,e a,b Devario sondhii 16.73±4.66 0.72±0.09 734.67±78.44 29.06±1.72 42.13±3.43 0.53±0.22 13.93±0.67 4.72±1.17

a a a,b a a,b a,b b,c a,d Danio rerio (leopard) 9.62±0.92 1.42±0.29 510.41±89.71 12.40±2.51 28.58±4.58 0.65±0.09 5.94±0.69 3.45±0.56

a a a,b a a,b a,b d,c,e b,d Danio meghalayensis 7.99±1.53 0.48±0.08 632.06±114.64 8.69±1.29 34.25±6.31 0.56±0.23 11.01±1.97 6.45±0.45

a a a a b a,b b a Danio rerio (zebra) 9.39±0.99 1.68±0.56 376.92±89.94 9.49±1.86 20.79±3.60 0.57±0.15 5.77±0.42 2.41±0.78

a a b a b a,b e,f b,d Danio dangila 6.34±0.67 0.64±0.21 803.18±95.29 11.92±1.02 18.96±2.69 0.77±0.21 12.46±1.16 6.37±0.83

a a a a b a,b b,c,f b,d Danio nigrofasciatus 9.91±1.17 0.97±0.23 402.39±46.98 11.11±1.26 16.63±1.23 0.73±0.12 7.87±1.44 5.90±0.50

Data are mean±SE, presented in µmol/g wet tissue. Sample size was 8 for all species except for 6 for Devario sondhii. No liver data available for Danio margaritatus. Within a given column, values that share a superscript letter are not significantly different.

CHAPTER THREE: GENERAL DISCUSSION

Under hypoxic conditions, fish rely on anaerobic pathways to produce ATP to

maintain energy balance, thus it has been long suggested that hypoxia tolerant species

should have a greater capacity to generate energy through anaerobic pathways than more

hypoxia intolerant species. However, few studies have attempted to rigorously test whether enhanced anaerobic capacity is an adaptive trait underlying hypoxia tolerance.

With the introduction of phylogenetically independent contrast (Felsenstein 1985;

Garland et al. 1992), it is now possible to incorporate phylogenetic information into comparative analysis to isolate selection-based traits from those merely due to phylogenetic history. The goal of this study is to determine whether there is a phylogenetically independent relationship between hypoxia tolerance and the capacity to generate ATP anaerobically in various species and strains of Danio and Devario, which, if present, would suggest that anaerobic capacity is an adaptive trait underlying hypoxia tolerance.

In the present study, I used two methods (time to LOE and TLE50) to characterize

hypoxia tolerance in Danio and Devario. The results of these two measurements

correlated tightly with each other. There was significant variation in hypoxia tolerance

among the species investigated and the hypoxia tolerant/intolerant species were well

distributed among the different phylogenetic clades. In the attempt to explain the

mechanism behind this variation, I performed conventional and phylogenetically

independent correlations between the measures of hypoxia tolerance and Pcrit (as an indicator of oxygen uptake capacity), enzyme activities and metabolite concentrations in anaerobic pathways (as measurements of capacity to produce energy anaerobically). Pcrit

did not correlate with measures of hypoxia tolerance among the species under study.

Variation in hypoxia tolerance was related to some aspects of anaerobic energy

metabolism, but not in a consistent fashion. Thus Pcrit and anaerobic capacity did not seem to be good explanations for the variation of hypoxia tolerance, which suggests that there should be other aspects that can explain this variation.

When we look at the big picture of how fish cope with hypoxia, they typically try to

increase efficiency of oxygen extraction from the environment as a first response. When

water PO2 drops further and the tissues do not get enough oxygen to maintain routine

functions, fish need to maintain energy balance by either suppressing their energy

demands or deriving more energy from anaerobic sources (Burggren and Randall 1978;

Hochachka & Somero 1984; West & Boutilier 1998). The analysis performed in this

thesis does not lend strong support for the hypothesis that differences in anaerobic

capacity explain variation in hypoxia tolerance in species of Danio and Devario; however,

this conclusion should be viewed cautiously. Although I measured the concentrations of

anaerobic substrate and maximal enzyme activities in various tissues in our study species,

overall flux through anaerobic pathways is controlled at multiple levels beyond substrate

availability and maximum activity. For example, covalent modification of proteins in

anaerobic pathways, such as glycogen phosphorylation at the beginning of glycolysis and

allosteric modulation of enzymes can play an important role is dictating metabolic flux.

Analysis of the factors that affect in vivo metabolic flux were not performed in the

present study due to a lack of tissue, but future studies should attempt to correlate

accurate measurements of in vivo flux with variation in hypoxia tolerance.

For oxygen extraction capacity, I used Pcrit as an indicator. Pcrit shows how well an

animal can extract enough oxygen to maintain routine M (Chapman et al. 2002). O2

However, Pcrit is more of an indicator of oxygen extraction capacity under relatively mild hypoxia. Even if species have similar Pcrit, they may have different oxygen extraction

capacity at water PO2 below Pcrit, e.g. 12 torr, at which time to LOE was measured. Thus,

what I performed was not a comprehensive analysis of the factors that could contribute to

variation in O2 extraction among the study species, which may include differences in gill

surface area, gill diffusion distance, and Hb-O2 binding affinity, to name a few factors

and further analysis should be performed. I predict however, given that I did not see

differences in Pcrit between species that there will not be substantial differences in these factors, but analysis is still warranted.

Furthermore, it would also be informative to examine variation in the capacity for metabolic suppression under hypoxia in the study species. However, a previous study showed that zebrafish (Danio rerio) increase their metabolic rate (measured by heat production) under hypoxia (Stangl & Wegener, 1996), instead of suppressing metabolic rate like goldfish (Carassius auratus; van Waversveld et al. 1989) or tilapia

(Oreochromis mossambiscus; van Ginneken et al. 1997). Preliminary analysis performed by Regan et al. (unpublished data) found that Danio rerio and Danio margaritatus increased heat production under hypoxia, which indicates increased metabolic rate. This may be due to hypoxia-induced movement and escape behavior (Stangl & Wegener,

1996). However, it is possible that among 10 species of Danio and Devario investigated, some species are capable of suppressing their metabolic rate in hypoxia, unlike Danio rerio and Danio margaritatus. It is also possible that some species increase their

metabolic rate in hypoxia to a larger extent than others, which depletes cellular ATP

faster when ATP production is compromised, which in turn leads to LOE faster than

other species.

Besides the aspects of hypoxia tolerance discussed above, survival time can also be

affected by how well fish can cope with negative consequences of anaerobic energy

production or metabolic suppression, and how well fish can direct energy to important

physiological functions for hypoxia survival. Anaerobic energy production and ATP

hydrolysis can lead to acidosis, which disturbs cellular pH balance (Bickler & Buck

2007). Another challenge due to insufficient cellular energy is to maintain cellular ion

balance, which is considered to be the crucial aspect for whole animal survival under

severe hypoxia (Boutilier & St-Pierre 2000). Thus, it is possible that the variation in

hypoxia tolerance of species investigated can be explained by variation in the capability to cope with acidosis, or to direct more energy to maintain ion balance, which can be investigated in the future studies.

Apart from possible future studies of other adaptive traits involved in hypoxia survival, the present study also raised several interesting questions for further investigation. First, what is the relationship between hypoxia tolerance and Pcrit? Pcrit has

been used as an indicator of hypoxia tolerance in many studies (Mandic et al. 2009;

Herbert et al. 2010; Barnes et al. 2011); however, we know Pcrit is not a direct measure of

hypoxia survival. Defined as the water PO2 at which fish transition from an oxyregulating

strategy to an oxyconforming strategy (Pörtner & Grieshaber 1993), Pcrit is more of an

indicator of animal’s capacity to extract oxygen from the environment (Chapman et al.

2002). It is generally accepted that a lower Pcrit shows that an animal can maintain routine

M under lower oxygen tensions, indicating higher hypoxia tolerance. Mandic et al. (in O2 press) also demonstrated that among 11 species of sculpins, fish with higher hypoxia tolerance (measured as times to LOE) had lower Pcrit values. However, this opinion is not

shared by all. In the present study, I did not find a relationship between hypoxia tolerance

and Pcrit. It has also been proposed that organisms with higher Pcrit values could benefit

from reducing their metabolic rate at higher water PO2 values, therefore reducing overall

metabolic demands before hypoxia gets too severe (Burggren & Randall, 1978). Thus,

further studies on different model systems are required to examine whether Pcrit is directly

related to measures of hypoxia survival.

Another problem the present study raised is the choice of species for comparative

studies. In this study, when I chose different groups of species to look at I found different

answers to the question I was asking (what the relationship is between hypoxia tolerance

and anaerobic capacity). Future studies are required to explain those different answers.

This also showed that successful comparative analyses require careful choices of species.

One of the suggestions of choosing species for comparative analyses is to have a large

number of species. Studies on a small number of species (2-3) may lead to difficulties to

factor out possible effects of phylogeny. It would also be preferable to have a group of

model species that shows a good spread in the variable of interest. It is possible that in

the model system of this study, the variation of hypoxia tolerance is not sufficient (time

to LOE at 12 torr ranged from 10 to 57 min) which increases the difficulty of finding

adaptive traits underlying hypoxia tolerance. Further comparative studies may reveal

other important clues for choosing model species.

Lastly, we have accumulated a large amount of information on how animals respond to hypoxia; however, few studies have attempted to replicate natural

environmental conditions when studying hypoxia tolerance. For example, many animals

(including Danio and Devario) living in isolated or richly-vegetated waterbodies are

likely to be exposed to dial hypoxia, together with dial fluctuations of temperature, CO2 tension and pH. However, in the present study, the fish were only exposed to one-time hypoxia, instead of the oscillations of hypoxia, or hypoxia together with low temperature

which they may experience in their natural habitats at night. Previous studies have found that the strategies to cope with one environmental stress may be beneficial for tolerating another environmental stress (Pörtner & Lanning 2009). Thus, studies that carefully replicate environmental conditions may provide us insights into ecologically relevant tolerance, i.e. how animals cope with the suite of environmental stresses they encounter in their natural habitats.

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