Attempt to Detect a Salmon Viral Pathogen from Seawater Collected in British Columbia

by

Lindsey Ogston

A thesis submitted in conformity with the requirements for the degree of Master of Science

The Department of Ecology and Evolution University of Toronto

© Copyright by Lindsey Ogston 2015

ii

Attempt to Detect a Salmon Viral Pathogen from Seawater Collected in British Columbia

Lindsey Ogston

Master of Science

The Department of Ecology and Evolution

University of Toronto

2015

Abstract

Wild Pacific salmon populations are subject to multiple anthropogenic stressors leading to

marked declines in British Columbia. One important stressor may be disease, and disease

linkages between Atlantic salmon aquaculture and wild Pacific salmon populations.

Macroparasite transmission between farmed Atlantic salmon and wild Pacific salmon has been

studied extensively in British Columbia. The potential for viral transmission and the abundance

of viral pathogens in the marine environment has not been rigorously assessed. We collected

water samples from 62 fish farm sites in B.C., where roughly half were active farms and half

were inactive. Presence of the salmon viral pathogen piscine reovirus (PRV) was analyzed using

quantitative PCR. PCR detection of common picorna-like virus was used to test for amplifiable

material. Ultimately, the methods failed to detect PRV, most likely due to sample degradation

linked to the relative instability of RNA.

iii

Acknowledgments

First and foremost, I'd like to thank my two supervisors; Marty Krkosek and Steven Short for

their expertise, patience and advice. I want to thank both of you for taking the time to teach me

so much; I feel like I crammed an impossible amount of knowledge into my brain over the past

16 months, and it is because of you guys.

Thank you to the various funding organizations who made this project possible, including

Natural Sciences and Engineering Research Council of Canada (NSERC).

I'd like to extend big thanks to my field assistants, Andrew Bateman and Luke Rogers. I

consider myself very lucky to have had two amazing scientists help me collect data. I learned so

much over those few months (boats and charts and tides, oh my), I think it's most appropriate to

refer to these two as field mentors rather than assistants. I'd also like to thank the three

volunteers who took time out of their schedules to help collect bottles of seawater: Chris

Guinchard, Lauren Ogston (this being the second time helping her sister with field work), and

Jenni Schine. I'd like to thank everyone who was out at Salmon Coast Field Station: Zephyr

Polk, Coady Webb, Lauren Portner, Stephanie Peacock, and Mack Bartlet.

I'd also like to thank everyone along the central coast who extended warm hospitality, unending

dinner invitations, fresh caught fish, and dock space. All the folks at God's Pocket Dive Resort

(Bill Weeks, Annie Ceschi, and Stacey Hrushowy), we showed up unannounced and you still

invited us to dinner! I had an amazing time and if I ever get better at diving, I know where I'm

going. To Farlyn Campbell and Jodie Eriksson on Sonora Island, thank you much for opening

your home (and your neighbours' home) to us, for the fresh caught crab and fresh laid ducks

eggs. To all the folks at the Dent Island Lodge, thank you so much for letting four crazy

academics stay at your very fancy dock. We placed a moratorium on drinking beer (much to the

dismay of Jenni) so that we would have more to share with you, and it was well worth it!

I'd also like to thank John Volpe and his lab at the University of Victoria for help with planning

and organizing the field work and for use of his boat and lab space.

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I'd like to thank the graduate and undergraduate students in the Short lab: Michael Staniewski,

Andrew Long, and Samia Mirza. I had what seemed like a million questions for you each day;

thank you for being patient and helping me.

I'd like to thank all my committee members: Nicole Mideo, Becky Raboy, Helen Rodd and Nick

Mandrak.

I'd like to thank the post-docs, graduate and undergraduate students in the MK lab: Andrew

Bateman, Luke Rogers, Pepijn Luijckx, Stefan Myer, Stephanie Peacock, Sean Godwin, Melissa

Orobko, Devin Kirk, Abby Daigle and Jessica Phillips. You've all been wonderful support and

wonderful friends.

Thanks also to my friends, Olivera Joksimovic, Ana Bedard, Tia Harrison, Amanda Xuereb and

Adriana Salcedo for all your support and love. Big thanks to Carissa Graydon for making the

map of the sample sites.

Finally, thank you to my parents. You guys are the best. I couldn't have done this without you.

Love you lots, and a preemptive thanks to my mom for proofreading this!

v

Table of Contents

List of Tables....................................................................................................................... viii

List of Figures........................................................................................................................ ix

1. Introduction............................................................................................................................ 1

1.1. Food Security and Global Fish Stocks........................................................................... 1

1.2. Aquaculture and Disease................................................................................................. 2

1.2.1. Expansion of Modern Aquaculture...................................................................... 2

1.2.2. Aquaculture, Disease and Fisheries Management................................................ 3

1.3. Wild Pacific Salmon in British Columbia....................................................................... 4

1.3.1. Natural History of Pacific Salmon....................................................................... 4

1.3.2. Importance of Pacific Salmon.............................................................................. 5

1.4. Piscine Reovirus (PRV) .................................................................................................. 6

1.5. Picorna-like Viruses........................................................................................................ 7

1.6. Overview of Questions and Hypothesis.......................................................................... 8

2. Methods.................................................................................................................................. 9

2.1. Sample Collection............................................................................................................ 9

2.1.1. Study area............................................................................................................. 9

2.1.2. Seawater Collection............................................................................................ 10

2.2. Sample Processing......................................................................................................... 11

2.2.1. Filtering Natural Seawater.................................................................................. 12

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2.2.2. Iron Flocculation................................................................................................ 13

2.2.3. Filtering Fe-Virus Precipitate............................................................................. 13

2.3. Laboratory Methods...................................................................................................... 13

2.3.1. Viral Resuspension............................................................................................. 18

2.3.2. RNA Extraction.................................................................................................. 18

2.3.3. cDNA Synthesis.................................................................................................. 19

2.3.4. PCR for Detection of Picorna-like Viruses........................................................ 19

2.3.5. Standard Design.................................................................................................. 19

2.3.6. Primer Design..................................................................................................... 22

2.3.7. Quantitative PCR of PRV................................................................................... 23

3. Results................................................................................................................................... 23

3.1. Field Methods................................................................................................................ 23

3.2. Laboratory Methods...................................................................................................... 25

3.2.1. RNA Extraction and cDNA Synthesis................................................................ 25

3.2.2. PCR for Detection of Picorna-like Viruses........................................................ 29

3.2.3. Quantitative PCR of PRV................................................................................... 32

4. Discussion............................................................................................................................. 33

4.1. Field Methods................................................................................................................ 34

4.1.1. Iron Flocculation................................................................................................. 34

4.2. Laboratory Methods...................................................................................................... 35

vii

4.2.1. Viral Resuspension............................................................................................. 35

4.2.2. RNA Extraction and cDNA Synthesis................................................................ 38

4.2.3. PCR for Detection of Picorna-like Viruses........................................................ 39

4.2.4. Quantitative PCR of PRV................................................................................... 40

4.2.5. Conclusions......................................................................................................... 41

References...................................................................................................................... 42

viii

List of Tables

Table 1: Timeline of laboratory methods................................................................................... 14

Table 2: Top five non Target BLAST results for de novo PRV primers and probes................ 22

Table 3: Site names, coordinates and date of collection for all samples sites........................... 24

Table 4: RNA and cDNA concentrations (ng/µL) and purity (260/280)................................... 26

ix

List of Figures

Figure 1: Map of sampling site.................................................................................................. 10

Figure 2: Flow chart of steps for field sample collection.......................................................... 11

Figure 3: Set up of filtration equipment..................................................................................... 12

Figure 4: Flow chart of steps for laboratory methods................................................................ 13

Figure 5: Schematic diagram of work flow1 and work flow 2.................................................. 17

Figure 6: Results of plasmid digest............................................................................................ 21

Figure 7: Gel electrophoresis of PCR for picorna-like viruses for three sites........................... 30

Figure 8: Gel electrophoresis of PCR for picorna-like viruses on all sites............................... 31

Figure 9: qPCR Plots Generated by Standards.......................................................................... 32

Figure 10: Results of qPCR analysis for site PH3DUL........................................................... 33

Figure 11: Example of Fe-virus precipitate changing colour.................................................... 37

1

Chapter 1 Introduction

1.1 Food Security and Global Fish Stocks

In one hundred years, from 1900 to 2000, the human population increased from 1.6 billion to 6.1

billion people. While the period of most rapid growth (1965-70) has already passed, the

population is still increasing and is estimated to reach 9.6 billion people by 2050 (Gerland et al.,

2014; Roberts, 2011). The marked increase in global population has been coupled with a

dramatic increase in global food production, which has outpaced population growth and reduced

global hunger (Godfray et al., 2010).

Prevalence of undernourishment has gone from 18.7 percent in 1990-92 to 11.3 percent in 2012-

2014; however, there still are 805 million people who go hungry, making food security (access

to a sufficient quantity of affordable, nutritious food) a global concern (FAO, 2014a). Fisheries

production is a focal point for this concern. Global population growth has decelerated with

increasing wealth, which comes with a greater demand for "luxury" foods, including some

seafood like tuna and salmon (Godfray et al., 2010). In many developing countries; however,

fish consumption consists of subsistence fisheries and is an essential part of people's diet (FAO,

2014b). In countries where fishing is an important subsistence activity, declines in fish stocks

can have lasting effects on local economies and people's ability to escape poverty. Declines in

fish can act as a "poverty trap" for the poorest fishers, where they are less likely than the

wealthier fishers to exit a declining fisheries (Cinner, Daw, & McClanahan, 2009; Costanza,

2014).

While the human population has increased, the global catch of wild fish has remained constant

for the past twenty-five years. The proportion of assessed marine fish stocks in State of World

Fisheries and Aquaculture 2014 (SOFIA 2014) that were fished within biologically sustainable

(according to the FAO's designation) levels declined from 90 percent in 1974 to 71.2 percent in

2011.Thus 28.8 percent of fish stocks are currently estimated to be fished at a biologically

unsustainable levels and, therefore, overfished (FAO, 2014b).

2

Additionally, since robust fisheries stock assessments don't extend before the 1950s there is a

"missing baseline" of what fish populations before modern day industrial fishing commenced.

Estimates of large predatory fish biomass being at only 10% of pre-industrial levels have been

made (Myers & Worm, 2003). The mean trophic level of fish caught worldwide has declined

substantially; as fisheries deplete, larger, predaceous fish stocks then transition to increasingly

smaller species (Hilborn et al., 2003; Pauly, 1998). The North Sea provided a stark example of

fishing down marine food webs where cod (Gadus morhua) were so overfished that fisherman

focused on catching Norway pout (Trisopterus esmarkii), which had cascading negative effects

on other wildlife such as seabirds and krill (Furness, 2002; Pauly, 1998). While the North Sea

provided a strong example of fishing down marine food webs, there has been evidence that this

concept is not occurring globally, but is restricted to a few cases within fisheries (Branch et al.,

2010).

Despite a history of overexploitation, increasing efforts to restore fish stocks are underway as

the average exploitation rate has recently declined in many fisheries of developed nations.

However 63%1 of assessed fish stocks worldwide still require rebuilding, and the impacts of

international fishing fleets from wealthy countries and the lack of sustainable alternatives to

fishing create a difficult situation for rebuilding fisheries in many poorer regions (Worm et al.,

2009).

1.2 Aquaculture and Disease

1.2.1 Expansion of Modern Aquaculture

While the capture rate of wild fish has stagnated, overall fish consumption has increased,

reaching almost 160 million tonnes in 2012. Responding to high seafood demand and fisheries

1 This estimate is calculated labeling stocks where catch biomass has dropped below the traditional single-species

management target of maximum sustainable yield (MSY) as overfished, as opposed to the estimate of 28.8% of

stocks that are overfished by FAO which is calculated by looking at the decline of fish stocks that are fished

sustainably from 1970-present.

3

saturation, aquaculture has expanded rapidly, and now produces approximately 40% of all

seafood consumed worldwide (FAO, 2014b; Goldburg & Naylor, 2005).

In only ten years (from 1987 to 1997) global aquaculture production more than doubled (FAO

1999) and from 1992 to 2002 that number almost tripled (FAO, 2004). There is evidence;

however, that aquaculture can have negative effects on wild fish populations through pollution

such as fish waste and pesticides, and infectious disease (Goldburg & Naylor, 2005; Naylor et

al., 2000).

1.2.2 Aquaculture, Disease and Fisheries Management

Infectious disease is a particular concern because it can have serious negative impacts on both

farm and wild fish populations. In the past 35 years there have been large outbreaks of

infectious diseases across many different kinds of farmed fish and shellfish (Asche, Hansen,

Tveteras, & Tveterås, 2009; Walker & Winton, 2010). Fish farmed in high-density

monocultures are vulnerable to disease (Kibenge et al., 2012), and are susceptible to chronic

infection cycles through transmission and feedback with sympatric wild fish populations

(Daszak, Cunningham, & Hyatt, 2000; Walker & Winton, 2010). Crowding in high density

aquaculture environments can enhance pathogen transmission opportunities, as well as the

accumulation of ammonia from wastes and increased oxygen demand. These limiting factors

can affect a host's ability to ward of disease (Snieszko, 1974).

Furthermore, genetic variation of farmed organisms is often less than that of their wild

counterparts (McGinnity et al., 1997; Valles-Jimenez & Perez-Enriquez, 2004), which may

contribute to a susceptibility to disease. For example, practices in Atlantic salmon aquaculture

such as breeding related individuals and using a small number of parents for broodstock can

decrease genetic variation of the farmed stocks (Norris, Bradley, & Cunningham, 1999). The

effects of this decreased genetic variation include moderate to high inbreeding depression of

survival and growth traits (farmed salmon are bred to grow faster than wild salmon) (Su,

Liljedahl, & Gall, 1996).

Additionally, most marine species used in aquaculture have been domesticated recently (e.g.

1900's) as opposed to their terrestrial counterparts (e.g. 9,000 BC) (Duarte, Marbá, & Holmer,

2007). Since the species used in aquaculture are so recently derived from wild strains they may

4

not have enough time to adapt to a high density domestication environment (Rodríguez-Ramilo

et al., 2011). This can lead to chronic stress (Yada & Nakanishi, 2002) which can create an

environment ripe for the emergence of infectious diseases (Kibenge et al., 2012).

Emerging infectious diseases include: (1) previously unknown diseases; (2) previously known

diseases appearing in a new species (expanding host range); (3) previously known diseases

appearing in a new location (expanding geographic range); and (4) previously known diseases

with different symptoms or higher virulence. These emerging pathogens often cause significant

losses to farmed stocks, producing economic losses and threats to wild fish (Walker & Winton,

2010). There is also evidence that the aquaculture environment promotes selection for virulent

strains of disease and can lead to the evolution of more virulent pathogens. This has occurred

with the bacterial disease Flavobacterium columnare in Finland, where evidence for the cause

of increased occurrence of the disease over 23 years in Atlantic salmon farm was evolutionary

changes in bacterial virulence in the high density of homogenous fish environment (Pulkkinen et

al., 2010).

Emerging infectious diseases have been recorded frequently in aquaculture over the past 20

years, specifically in Atlantic salmon aquacultures. Infectious salmon anemia (ISA) in farmed

salmon in Chile compounded by poor management resulted in the worst disease outbreak ever

recorded in salmon aquaculture. Production of stocks was reduced from 400,000 tonnes in 2005,

to 100,000 tonnes in 2010, damaging the local economy (Asche et al., 2009). The 2001-2003

outbreak of infectious haematopoietic necrosis (IHN) disease in British Columbia, Canada in

farmed salmon was spread through farming practices, with the initial infection occurring when 3

farms received smolts infected with IHN (Saksida, 2006).

1.3 Wild Pacific Salmon Conservation in British Columbia

1.3.1 Natural History of Pacific Salmon

There are seven species of genus Oncorhynchus (Pacific salmon) in British Columbia: chum (O.

keta), Chinook (O. tshawytscha), sockeye (O. nerka), pink (O. gorbuscha), coho (O.

kisutch), and two species commonly known as trout; cutthroat (O. clarki) and steelhead (O.

mykiss). Chum, Chinook, pink and coho are anadromous and migrate from the marine to

5

freshwater environments to spawn. Most sockeye are also anadromous, except for landlocked

populations (dubbed " kokanee") which live and spawn in freshwater. Steelhead can have an

anadromous form or a freshwater rainbow trout form, while cutthroat trout can also have a sea-

run form that spawns in freshwater. While cuttthroat and steelhead are iteroparous, all other

species are semelaprous and die after spawning (Cederholm, Kunze, Murota, & Sibatani, 1991).

1.3.2 Importance of Pacific Salmon

Pacific salmon are of vital economical, cultural, and ecological importance in B.C., where they

support recreational and commercial fisheries, First Nations cultural practices, and significant

ecological processes (Cederholm et al., 1991; Willson, Gende, & Marston, 2010; Field and

Reynolds, 2011).

However, wild Pacific salmon populations are subject to multiple anthropogenic stressors,

including fishery harvest and habitat degradation, leading to marked declines in British

Columbia (Slaney, Hyatt, Northcote, & Fielden, 1996; Cohen, 2012).

Historically, Pacific salmon populations have declined severely since the 1800s as a

consequence of over-harvest, dams, and widespread habitat degradation from land use (Finney,

Gregory-eaves, Douglas, & Smol, 2002; Meengs & Lackey, 2005). Currently, populations still

face these historical factors as well as new stressors from climate change and aquaculture

(Krkosek, Lewis, Morton, Frazer, & Volpe, 2006; Welch, Ward, Smith, & Eveson, 2000).

One important Pacific salmon stock is the Fraser River sockeye. This stock is important for

commercial, recreational, and Aboriginal fisheries (Cooke et al., 2004; Buhle et al., 2009; Field

& Reynolds, 2011). The Fraser River sockeye stocks have been declining since the 1990's

(Miller et al., 2011), and in 2009 experienced such a drastic decline, in which only 1.6 million of

the estimated 10 million sockeye returned to spawn, that it spurred a $25 million federal inquiry,

the Cohen commission, to identify factors that contributed to the decline. The commission found

that sockeye salmon faced a variety of stressors and called for research into these stressors to

gain a better understanding of potential effects on wild Pacific salmon (Cohen, 2012). Of note,

in 2010 the returns were the most sockeye that have returned to British Columbia's Fraser River

in almost a century. There is evidence; however, that this may not be a long term trend, but

rather a particular anomaly due to stochastic aboitic factors. In particular, the 2008 eruption of

6

Mt. Kasatoshi in Alaska, which the effects caused a large bloom of diatoms in the area where

Fraser River sockeye are known to frequent. This could have has bottom up effects in term of

salmon productivity. Additionally, the salmon returning in 2010 would have been in the

midpoint of their growth cycle, and could benefit most from these bottom up effects (Parsons &

Whitney, 2012).

One important stressor that the commission identified is disease, and disease linkages between

Atlantic salmon aquaculture and wild Pacific salmon populations. Sockeye smolts (juvenile fish)

outmigrate from their natal fresh water streams to the open ocean by passing through the Inside

Passage between Vancouver Island and mainland British Columbia. This area also has a high

concentration of Atlantic salmon aquaculture sites, with 69 farms being reported by BC's

Ministry of Agriculture in 2010. Transmission of parasites between farmed Atlantic salmon and

wild Pacific salmon has been studied extensively in British Columbia (Krkosek et al., 2006).

Specifically transmission of the parasitic salmon sea louse (Lepeophtherius salmonis). Sea lice

are surface macroparasites and feed on host surface tissues. While infection causes mortality at

high infection intensities (Pike & Wadsworth, 2000), there are also indirect effects on

survivorship due to changes in behavior; in that infected juvenile fish were at a greater risk of

predation due to increased risk-taking behaviours (Krkosek et al., 2011).

However, potential for viral transmission between farmed Atlantic salmon and wild Pacific

salmon has not been rigorously assessed, and the abundance of salmon viruses in the marine

environment is unknown. For this project we chose to examine the viral salmon pathogen

piscine reovirus, due to anecdotal evidence of its high prevalence in Atlantic salmon aquaculture

in B.C. (Feinburg, 2012), and its ubiquity in Atlantic salmon aquaculture in other countries

(Palacios et al., 2010).

1.4 Piscine Reovirus (PRV)

Heart and skeletal muscle inflammation (HSMI) disease was first reported in Norwegian

Atlantic salmon farms in 1991 (Kongtorp, Kjerstad, Taksdal, Guttvik, & Falk, 2004). It causes

myocardial necrosis (death of heart cells) and has been to reported cause 20% mortality in

farmed Atlantic salmon (Kongtorp, Taksdal, & Lyngøy, 2004). The source of the disease

remained unclear, with virus-like particles being observed in tissue samples infected with HSMI

(Watanabe et al., 2006), but the exact infectious agent remaining unknown until recently. In

7

2010 RNA from infected Atlantic salmon heart tissue was provided evidence linking HSMI

with a novel reovirus, which was named piscine reovirus (PRV) (Palacios et al., 2010). The

virus has not been formally classified by the International Committee on the Taxonomy of

Viruses (ICTV), and the name PRV is a common name rather than a formal classification (ICTV

2013).

This emerging infectious disease of salmon has since been reported in hundreds of farms in

Norway, as well as the United Kingdom (Ferguson, Kongtorp, Taksdal, Graham, & Falk, 2005).

It has been detected at low prevalence in wild Atlantic salmon populations in Norway (Palacios

et al., 2010), as well as other species of local marine fish including Atlantic herring (Clupea

harengus) and capelin (Mallotus villosus) (Wiik-Nielsen et al. 2012). The virus has also been

detected in farmed Atlantic salmon in Chile (Bustos et al., 2011). There is evidence for the

presence of PRV in both farmed Atlantic salmon and wild Pacific salmon in British Columbia

(M. Kibenge et al., 2013; Miller et al., 2014), with antidotal reports from within fish farm

management of 75% of farms testing positive for PRV (Feinburg, 2012).

The PRV genome consists of double-stranded RNA (dsRNA) and is transmitted horizontally

(transmitted host to host) (Kibenge et al. 2013). Vertical transmission (transmitted from the

mother to offspring), is not a major route of transmission of PRV (Wiik-Nielsen et al. 2012).

The pathogenicity of PRV is not fully understood. In Norwegian fish farms the virus is

ubiquitous, but the viral load is significantly higher during an HSMI outbreak (Palacios et al.

2010). HSMI has a 20% mortality rate (Kongtorp, Taksdal, et al., 2004), and surviving fish will

typically recover, but seem to be lifelong carriers of PRV (Wiik-Nielsen et al. 2012). Other

reports describe PRV as an opportunistic virus (Løvoll et al., 2010; Wiik‐Nielsen & Løvoll,

2012) or non-pathogenic virus (Garseth, Biering, & Tengs, 2012). However, as seen with sea

lice, there can also be indirect effects on salmon mortality due to disease.

1.5 Picorna-like viruses

As a positive control to validate the methods for this experiment we tested for the presence of a

common group of marine virus: the picorna-like viruses. Presence of these viruses were used as

a general marker to test if RNA material in the samples was intact, as the two viruses are both

8

double-stranded RNA viruses, therefore the methods to detect both types are essentially the

same.

Viruses are the most common biological entities in the oceans (Breitbart, Thompson, Suttle, &

Sullivan, 2007), with estimates of the abundance of marine viral genotypes in the order of

hundreds of thousands (Angly et al., 2006). The common hosts of marine viruses, marine

microbial prokaryotes and eukaryotes, are also incredibly diverse (Irigoien, Huisman, and Harris

2004; Witman, Etter, and Smith 2004;Worden 2006), and multiple host-specific viruses

infecting each marine organism is probable (Sullivan, Waterbury, & Chisholm, 2003; Wichels et

al., 1998).

Marine RNA viruses that infect microbial organisms have been poorly studied compared to

DNA marine viruses; however, they are widespread and ubiquitous (Culley, Lang, & Suttle,

2003; Culley, Suttle, & Steward, 2010). Previous studies have shown that one order of RNA

viruses that are common in marine environments are the picorna-like viruses (order:

Picornavirales) (Culley et al., 2003). Picorna-like viruses have single-stranded positive sense

RNA genomes (Le Gall et al., 2008), and contain a conserved RNA-dependent RNA polymerase

(RdRp) protein (Culley et al., 2003). The RdRp sequence in picorna-like virus genome is highly

conserved, (Culley et al., 2003, 2010) , and so we use that as a general marker to test if RNA

material in the samples was intact. Both PRV and the picorna-like viruses are RNA virus; RNA

is more unstable than DNA due to the elaborate proofreading and repair mechanisms that have

evolved in DNA, which makes it replicated with much greater fidelity. As well as the presence a

hydroxyl group on the RNA sugar ribose which can cause hydrolysis of the phosphate bond,

cleaving the RNA.

1.6 Research questions

For this study we sought to bring together the interactions between a vital but declining wild fish

stock, presence of aquaculture along the wild fish migration route, and a viral disease known to

be present in aquaculture. While ultimate question may be "is disease from Atlantic salmon fish

farms negatively effecting wild sockeye populations?" There are many research questions to be

answered before proceeding to the ultimate question. What is the viral shedding rate for infected

9

fish? What is the rate and timing of transmission between the farmed and wild fish? What are

the diseases that are being transmitted, what are their effects on wild salmon? My research

focused on developing methods that could be used to determine how the concentrations of PRV

in the water column vary with the presence of active Atlantic salmon fish farms.

Chapter 2

Methods

2.1 Sample collection

2.1.1 Study Area

Natural seawater was collected from March 30 to April 18, 2014 in southern British Columbia,

Canada (Table 1). The sampling region extended from Hope Island, near Port Hardy, south

through the Broughton Archipelago and ended in the Discovery Islands. There were 67 sites

sampled altogether (Figure 1). Fish farm locations were tabulated by using information available

from both the Ministry of Agriculture and the Living Oceans Society websites. Sites were

designated: an active farm (fish farm with fish or feeding structures visible), an inactive farm in

fallow year (farm structure present but nets furled or no fish present), or an inactive farm with

no farm structure present (tenure site but no structure present).

10

Figure 1. Map of sample site. Black squares with an "A" denote active fish farms, black squares with an "I" denote

an inactive farm, and grey circles with an "I" denote a tenure site but no structure present.

2.1.2 Seawater Collection

If a farm structure was present the number of pens, number of active pens, size of fish

(estimated by sight) were recorded. If no farm structure was present the site was recorded as

inactive, and that no structure was present. Water was collected ~15 m from the pens and three

sides of the farm were sampled, collecting 2 L of water on each side, resulting in 6 L of water

for each site. At each point where 2 L was collected, water temperature using a thermometer,

salinity using a refractometer and water transparency using a Secchi disk were recorded. If

present, collection was omitted from the side of the farm with a float house (where employees

live and work); if not, the side closest to shore was omitted. If there were no farm structures,

water was collected from the GPS coordinate given from the Ministry of Agriculture or Living

Oceans Society as well as two adjacent sites (~5m away from original site at 20⁰).

11

Samples were collected in 1L high-density polyethylene (HDPE) bottles (Fisher Scientific,

Ottawa, Ontario). Before sampling began all bottles were cleaned using 5% HCL and rinsed

with distilled water. Clean bottles were used to collect filtrate, and initial sample water was

collected with previously used bottles. Used bottles were rinsed three times with ocean water

from the focal sample location, disposing of each rinse collection on the opposite side of the

boat. To collect the sample after the rinsing was completed, the bottle was submerged with a lid

on ~20 cm below the surface of the water, filled, and closed at this depth. Bottles were labeled,

and sheltered from UV radiation at~ 4⁰ C until subsequent processing could occur. To minimize

decay of viruses, samples were processed within three hours (Garver, Mahony, & Stucchi,

2013).

2.2 Sample Processing

Filtration and iron flocculation was carried out following (John et al., 2011) and (John, Poulos,

& Schirmer, 2014) for isolating, concentrating, and stabilizing the viruses for long term storage.

The paper states that the Fe-virus flocculate is amenable to long term storage with or without the

resuspension buffer, and found that after 4 months of storage (dark, 4°C), 85% of virus particles

were recovered from Pacific Ocean viral-fraction concentrates. However, these viruses were

DNA viruses (marine "cyanophages"), and it is not stated whether this was with or without the

resuspension buffer. Natural sea water was collected, then filtered through a 0.22µm pore size

filter. The filtration removes large viral predators such as flagellates (Suttle & Chen, 1992). The

filtrate was then treated with iron chloride (FeCl3) which binds to the viruses and then

precipitates out of solution. The solution was filtered again through a 0.22 µm pore size

Sterivex™ filter, collecting the precipitate on the filter. The Fe-virus precipitate was then

shipped to the University of Toronto and resuspended with a buffer in the lab and analyzed.

Figure 2. Flow chart of steps for field sample collection.

12

2.2.1 Filtering Natural Sea Water

Filtration followed a protocol from John et al.,( 2011). Samples were pressure filtered at 2 psi

through a 142-mm-diameter 934/AH glass fiber filter (Whatman, Baie d’Urfe, Quebec) and 142-

mm-diameter 0.22μm pore size PVDF membrane filter (Millipore, Bedford, Mass.) connected in

series. Early in the season one 0.22μm pore size filter was sufficient to process samples;

however, approximately 2 weeks into sampling, processing time increased due the .22μm filter

clogging, and a glass fiber filter was added in series to the .22μm filter (Figure 3).

Before each sample was processed, 500mL of distilled water was added to the pressure canister ,

agitated, and pumped through the system with no filters in the stands, to clean the pressure

canister and filter stands. Filters were then added with filter forceps sterilized with ethanol. Then

the 6L of sample water were poured into the pressure canister, and 1L of sample water was

flushed through the system, measured by filling a clean 1L bottle. Then two clean 1L bottles

were filled, and labeled and immediately flocculated.

Figure 3. Photo of equipment used in first filtering step. Components includes pressure pump (A), pressure canister

(B), and one 142mm diameter filter stand (C).

13

2.2.2 Iron Flocculation

The flocculation protocol was carried out following the protocol from (John et al., 2011) and

(John et al., 2014). A concentrated 10g/L Fe stock solution was made following protocol from

(John et al., 2014). Samples were flocculated by pipetting 100µL of the 10g/L Fe stock solution

to each 1L of filtered sample water. Samples were agitated by hand for 1min to enhance Fe-

virus binding and sheltered from UV radiation for 1 to 3 hours.

2.2.3 Filtering Fe-Virus Precipitate

Samples were filtered again to collect the Fe-virus precipitate; 2L of flocculated sample water

were processed through a 0.22μm pore size filter Sterivex™ (Millipore, Bedford, Mass.) filter

using a peristaltic pump. Sterivex™ filters were placed in sterile Whirl-Pak®s and placed into a

4⁰C fridge. Samples were then shipped on ice to the University of Toronto's Mississauga

campus and placed into a 4⁰C refrigerator.

2.3 Laboratory Methods

Figure 4: Flow chart of steps for laboratory analysis.

The work in the laboratory consisted of two work flows (Table 1). Work flow 1 ran from May

21, 2014 to June 4, 2014, and followed the steps of viral resuspension, to RNA extraction, to

cDNA synthesis to PCR for the picorna-like virus. The second work flow ran from June 17,

2014 to September 16, 2014 and followed the steps of viral resuspension, to RNA extraction, to

cDNA synthesis to qPCR of PRV and then PCR for the picorna-like virus.

14

Table 1: Date viral resuspension, RNA extraction, and cDNA synthesis. Sites from laboratory

work flow 1 are bold, sites from laboratory work flow 2 are not.

Site Buffer resuspension RNA Extraction cDNA Synthesis

Ph01HB June 18 2014 August 6 2014 August 15 2014

PH02Dol June 18 2014 July 21 2014 August 15 2014

PH03Dul June 19 2014 July 17 2014 July 17 2014

PH04BI June 17 2014 July 31 2014 August 15 2014

PH05WI June 17 2014 July 30 2014 August 17 2014

PH06SB May 27 2014 May 30 2014 June 3 2014

PH07RI Date not recorded June 19 2014 June 19 2014

PH08MB Date not recorded June 19 2014 June 19 2014

PH09VI May 27 2014 May 30 2014 June 3 2014

PH10BU June 17 2014 N/A N/A

PH11HI June 18 2014 July 22 2014 August 15 2014

BA01WB June 17 2014 July 30 2014 August 15 2014

BA02MSB June 18 2014 July 29 2014 August 17 2014

BA03MI June 17 2014 July 30 2014 August 17 2014

BA04CI June 18 2014 August 6 2014 August 15 2014

BA05CH June 17 2014 July 30 2014 August 15 2014

BA06SEB June 18 2014 July 22 2014 August 15 2014

BA07CB June 18 2014 August 2 2014 August 15 2014

BA08WP June 17 2014 July 28 2014 August 15 2014

BA09RP June 19 2014 N/A N/A

BA10SR June 18 2014 N/A N/A

BA11WC June 19 2014 July 22 2014 August 15 2014

BA12BP June 18 2014 July 31 2014 August 15 2014

BA13URP (II) June 17 2014 July 21 2014 September 12 2014

15

BA14AP June 19 2014 July 22 2014 August 15 2014

BA15MI June 18 2014 July 21 2014 August 15 2014

BA16PB June 18 2014 August 6 2014 August 15 2014

BA17SI June 18 2014 July 29 2014 August 15 2014

BA18LI June 19 2014 July 22 2014 August 15 2014

BA19DP June 18 2014 July 30 2014 August 15 2014

BA20PE June 17 2014 July 29 2014 August 17 2014

BA21BP June 17 2014 July 31 2014 August 15 2014

BA22DI June 19 2014 July 22 2014 August 17 2014

BA23HR June 18 2014 July 29 2014 August 15 2014

BA24SP June 17 2014 August 6 2014 August 17 2014

DI01MP June 18 2014 August 6 2014 August 17 2014

DI02YI June 17 2014 July 21 2014 August 17 2014

DI03DU June 17 2014 July 21 2014 August 17 2014

DI05CB June 19 2014 July 16 2014 July 17 2014

DI06CP June 17 2014 July 16 2014 July 17 2014

DI07CR June 19 2014 July 16 2014 July 17 2014

DI08BN June 18 2014 July 31 2014 August 17 2014

DI09SN June 18 2014 July 29 2014 August 17 2014

DI10VN June 17 2014 July 28 2014 August 17 2014

DI11BI June 18 2014 August 2 2014 August 17 2014

DI12YP June 18 2014 July 28 2014 August 17 2014

DI13SP June 17 2014 August 6 2014 August 17 2014

DI14FA June 19 2014 July 22 2014 August 17 2014

DI15SEG June 19 2014 July 22 2014 August 17 2014

DI16FS June 17 2014 August 6 2014 August 17 2014

16

DI17OP June 17 2014 July 29 2014 August 17 2014

DI18TR June 17 2014 July 28 2014 August 17 2014

DI19BR June 17 2014 August 2 2014 August 18 2014

DI21MP June 18 2014 N/A N/A

DI22BK June 17 2014 August 6 2014 August 18 2014

DI23PA June 19 2014 July 17 2014 July 17 2014

DI24CN June 17 2014 July 29 2014 August 18 2014

DI25LB June 17 2014 July 29 2014 August 18 2014

DI26HA June 17 2014 July 21 2014 August 18 2014

DI27AL June 18 2014 August 6 2014 August 18 2014

DI28CH June 18 2014 August 6 2014 August 18 2014

DI29RZ June 17 2014 August 2 2014 August 18 2014

DI30DB June 19 2014 July 17 2014 July 17 2014

DI31HO June 18 2014 July 28 2014 August 18 2014

DI32YI June 18 2014 August 2 2014 August 18 2014

DI33SP June 18 2014 July 30 2014 August 18 2014

BA13URP (I) May 21 2014 May 23 2014 June 03 2014

17

Figure 5: A schematic diagram outlining work flow 1 and work flow 2. Orange boxes denote methods, blue boxes

denote information between steps including number of samples (n), average number of days between each step (µ),

and standard deviation for number of days between each step (SD).

18

2.3.1 Viral Resuspension

To analyze the samples for the presence of viruses, I first resuspended the virus material from

the filters using 0.2 M ascorbate-EDTA buffer. The resuspension buffer was added to the

Sterivex™ filters with Fe-virus precipitate to maximize virus recovery off of the filter. A 0.2 M

ascorbate-EDTA buffer was made following the protocol from S. John et al., 2014. The buffer

was prepared and used within 48 hours and stored in at 4⁰ C. Average time from final filtration

to addition of resuspension buffer was 57 days for work flow 1, and 62 days for work flow 2

(Table 2). Using a syringe 2 ml of the ascorbate-EDTA buffer was added to the Sterivex™

filters, covering the Fe-virus precipitate on the filter. The ends of the Sterivex™ were capped

with parafilm, agitated vigorously and stored in a 4⁰ C refrigerator until ready to process,

ranging 2 to 3 days for work flow 1 and 27 to 49 days for work flow 2 (Table 2).

2.3.2 RNA Extraction

Using a syringe, 2 ml of the Fe-virus-buffer solution was transferred from each Sterivex™ filter

into two 1.5 ml screw-cap tubes. RNA extraction was carried out on this solution using a

QIAamp® Viral RNA Mini Kit (Qiagen, Valencia, U.S.A), with protocol slightly modified from

the manufacturer's instructions in that centrifugation was conducted for 3 minutes (rather than 1

minute) following the ethanol wash step. Additionally, 11.2 µL of carrier RNA was added per

280µL of Fe-virus-buffer solution which was processed into 80µL of RNA. In all cases, the

extracted RNA was eluted in 80µL of buffer AVE. Each site was processed twice

simultaneously (i.e. two unique elutions), resulting in a total of 560µL Fe-virus-buffer used, and

two tubes of 80µL of RNA for each site. One tube was stored in a -20⁰C freezer for subsequent

analysis, and the other tube was stored in a -80⁰C freezer for long term storage.

RNA was extracted following the manufacturer's instructions for conditions of low density of

target molecules in the samples which resulted in the addition of carrier RNA, which enhances

binding of viral nucleic acids to the spin column membrane to increase viral RNA recovery. The

addition of carrier RNA adds a level of complexity to quantifying RNA yields as elution will

contain both viral nucleic acids and carrier RNA, and the abundance of carrier RNA can greatly

exceed the amount of viral nucleic acid. Quantification and purity of samples used in subsequent

19

analysis was analyzed using the NanoDrop ND-1000 spectrophotometer (Thermo Fisher

Scientific, Waltham, U.S.A) (Table 3).

2.3.3 cDNA Synthesis

Complementary DNA (cDNA) was synthesized using SuperScript® Vilo™ cDNA synthesis Kit

(Invitrogen, Burlington, ON) following manufacturer's instructions. This product does not use

specific primers (which would only make a cDNA copy of specific gene fragments), but rather

random hexamers (which make a copy of all RNA in sample). 10 µL of RNA was used and

resulted in 30 µL of cDNA. Reaction conditions were 10 min at 25⁰ C, 60 min at 42⁰ C, and 5

min at 85⁰ C. Sample sites BA13URP(I), PH09VI, and PH06SB were checked for successful

cDNA synthesis using PCR amplification of RdRp gene fragments, which was checked using

gel electrophoresis (Figure 5).

2.3.4 PCR for Detection of Picorna-like Viruses

In order to test for amplifiable cDNA, PCR to detect picorna-like viruses using amplification of

an RNA-dependent RNA polymerase (RdRp) gene fragment was done following the protocol in

Culley et al. (2010). From work flow 1, PCR was conducted on three samples (BA13URP(I),

PH06SB, and PH09VI) on June 5th to confirm that amplification was possible. The PCR results

were analyzed using agarose gel electrophoresis, but were not confirmed via gene sequencing.

In work flow 2, PCR was conducted on all samples (including BA13URP(I), PH06SB and

PH09VI) on September 15 and 16. The primers used were the RdRp 1 and RdRp 2 primers

outlined in (Culley et al., 2010); RdRp 1 [5 -GGR GAY TAC ASC IRW TTT GAT - 3], and

RdRp 2 [5 -MAC CCA ACK MCK CTT SAR RAA- 3]. The 25µL reactions contained

concentrations of 1× Platinum Taq buffer, 3 mM MgCl2, 0.2mM of each dNTP, 1 µM of each

primer, and 1 unit of Platinum Taq DNA polymerase (Invitrogen, Burlington, ON). Results of

PCR were analyzed using agarose gel electrophoresis run at 95V for 1h20min.

2.3.5 Standard Design

Since piscine reovirus DNA was not available, synthetic DNA was used to create standards for

quantitative PCR (qPCR). A gBlocks™ Gene Fragment (Integrated DNA Technologies,

Coralville, Iowa) for a 170bp fragment (from position 2371 to 2541) of the piscine reovirus

20

genome (accession number: KC715679.1). This portion of the genome codes for a core shell

protein and has been previously used for primer creation (Haugland et al., 2011). The gBlocks™

DNA was resuspended according with IDTE (1X TE solution) for a final concentration of

10ng/µL.

Then 50ng of the gBlocks™ DNA resuspended solution was used in a 10µL A-tailing reaction.

Reagents were 1µL Fermentas 10x Taq buffer, 2µL of dATP (1nm), 1µL of MgCl2 (25nM),

and 1µL Fermentas Taq DNA polymerase (Thermo Fisher Scientific, Waltham, U.S.A).

Reaction conditions for incubation were 70⁰C for 30 minutes. The DNA was then ligated into

pGem T-vector plasmid using 1µL of tailed gBlocks™ DNA, 5µL 2x rapid ligation buffer, 1µL

ligase, and 1µL of pGem T-vector (Promega, Madison, U.S.A). The 10µL reaction was

incubated in a 4⁰C refrigerator for 19 hours.

The product (plasmid containing the gBlocks™ Gene Fragment) was then transformed using

Subcloning Efficiency™ DH5α™ Competent Cells (Invitrogen, Burlington, ON). 50µL of

competent cells were mixed with 5µL of ligation product incubated on ice for 30 minutes, heat

shocked at 42⁰C for 20 seconds then put back on ice for 2 minutes. 950µL of LB media was

added and the product was plated on agar, and incubated in 37⁰C incubator for 20 hours. Using

blue-white screening the white bacterial colonies were harvested and cultured at 37⁰C for 16

hours in a shaker running at 275 rpm. Bacterial cultures were minipreped (lysed and purified)

using Qiaprep® spin miniprep kit (Qiagen, Valencia, U.S.A) following manufacturer's

instructions. Products were quantified for concentration and purity using a NanoDrop ND-1000

spectrophotometer (Thermo Fisher Scientific, Waltham, U.S.A), and were sequenced at TCAG

facilities at the Centre for Applied genomics and were 100% match.

The plasmid was then digested using ApaI enzyme (New England Biolabs, Ipswich, U.S.A)

which was verified (using information from the New England Biolabs website) to only cut the

plasmid once and not within the desired sequence. The 50 µL reaction conditions were 5µL

cutsmart buffer, and 1µL 50 Ku/mL ApaI enzyme, 39.9 µL distilled water and 4.5 µL miniprep

product (231.6 ng/µL). The results of the digest were verified through agarose gel

electrophoresis (Figure 6). The bands of the successful digests (Figure 6, lanes 3,4,7,8, and 10)

were cut out and pooled (results of sequencing and gels showed they were exactly the same).

21

They were then purified using QIAquick PCR Purification kit (Qiagen, Valencia, U.S.A)

following manufactures instructions.

Figure 6: Agarose gel electrophoresis of PCR of digested and undigested plasmids containing the gBlocks™ Gene

Fragment. Lanes 1, 2, 5, 6, and 9 are undigested miniprep products. Lanes 3, 4, 7, 8, and 10 are successful digested

plasmids. L denotes 100-bp ladder (Invitrogen, Burlington, ON).

Concentration and purity of purified PCR products was analyzed using the NanoDrop ND-1000

spectrophotometer (Thermo Fisher Scientific, Waltham, U.S.A), the sample was analyzed twice

and the average concentration was calculated. Number of copies of DNA per µL was calculated

using the equation below.

d

)2)(( czy

AX

Where: X= number of copies per µL (molecules/µL)

A= plasmid concentration (g/µL)

y= length of the plasmid (bp)

z=length of the gBlocks™ Gene Fragment (bp)

c= weigh of a single nucleotide (330 daltons)

d= Avogadro's number 6.0221413 x1023

22

The digests were then serially diluted ten times using 500 µg/mL λDNA (New England

Biolabs, Ipswich, U.S.A) as a medium. Final concentrations ranged from 3.04 x100 to 3.04 x10

7

copies of DNA per 2 µL.

2.3.6 Primer Design

Quantitative PCR primers and probes were designed using Beacon Designer 7.0 (Premier

Biosoft International) with default parameters for TaqMan® probe design. Primer and probes

were optimized for high quality scores and greatest number of mismatchs with non target

sequences (Table 2). The 5'-3' sequences of the primer and probe for PRV are: SReoV Li F [5 -

CCC TCA CAT ATG GAT ATA TG - 3], SReoV Li R [5 - CTG GAA TGG TAT TTG GAA -

3],and Taqman® probe SReoV Li P [5 - AGT TGG CGA TGA TTT CAC CCA C - 3]. All

Taqman were labeled 5' with FAM (6-carboxyfluorescien), and 3' labeled with Iowa black® FQ

(Intergrated DNA Technologies, Coralville, U.S.A).

Table 2: Top 5 non-target BLAST hits for primers and probes designed, query cover for all is below 100%.

Primers and probes were optimized for high quality scores and greatest number of mismatchs with non target

sequence. Information includes: GenBank accession number (Asc.), bit score (derived from raw alignment score),

percent identity (% Identity), and query cover.

23

2.3.7 Quantitative PCR of PRv

Quantitative PCR was carried out on cDNA, synthesized as previously described, using an

MX3000 qPCR system (Stratagene). The 20µL reactions contained 2 µL of 10x Platinium® Taq

buffer (manufacture-supplied reaction buffer), 5 mM MgCl2, 0.8 mM dNTPs, 0.4 µm of both

forward and reverse primer, 0.25 µm TaqMan® probe, 30 nM 1:500 ROX reference dye, 0.5U

Platinum® Taq DNA polymerase (Invitrogen, Burlington, ON), and nuclease-free water

(Integrated DNA Technologies, Coralville, U.S.A) to bring to volume up to 18 µL. The final 2

µL consisted of template DNA. Reaction conditions were 5 minutes at 95⁰ C, 12 seconds at 95⁰

C and 1 minute at 60⁰ C for 40 cycles. Each site was run in triplicate. Each set of reactions also

contained duplicates of eight ten-fold serially diluted standards (linear plasmid molecules

containing the target PRV fragment). The standards were prepared as described in section 3.4,

and ranged from 3.04 x100 to 3.04 x10

7 copies of fragment per 2 µL. Triplicate no template

controls containing 2 µL of nuclease-free water (Integrated DNA Technologies, Coralville,

U.S.A) instead of template DNA were also run for each set of reactions.

Chapter 3

Results

3.1 Field Methods

A total of 66 farms were sampled, with one farm (BA13URP) sampled twice resulting in a total

of 67 samples. Of the farms: 27 were active fish farms, 15 were inactive farms in a fallow year,

and 24 were tenure sites but no farm structure was present (Table 1) . The average water

temperature was 8.2⁰ C (SD=0.79), the average water salinity was 28.48% (SD=3.53), and the

average water transparency was 10.1m (SD=2.97).

24

Table 3. Site names, coordinates and date of collection for all sample sites. Sites were designated: an active farm

(fish farm with fish or feeding structures visible), an inactive farm in a fallow year (farm structure present, but nets

furled or no fish present), or an inactive farm with no farm structure present (tenure site but no structure present).

Average water temperature, salinity, and water transparency for three points in the sample area using a

thermometer, refractometer, and a Secchi disk. Site BA13URP was sampled once on Match 28th and again on April

18th 2014 due to inconsistencies in sampling protocol. (Continued on next page)

25

3.2 Laboratory Methods

3.2.1 RNA Extraction and cDNA Synthesis

RNA concentrations ranged from 91.2 ng/µL to 187.0 ng/µL per sample with an average of

132.3 ng/µL, and purity (260/280 ratio) ranged from 0.86 to 3.21 with an average of 2.99 (Table

4). For RNA a ratio of ~2.0 is normally acceptable for purity. Low 260/280 ratios generally

indicate that the sample is either contaminated by protein or that there was an issue with

measurement. High 260/280 purity ratios are not necessarily indicative of an issue (Thermo

26

Fisher Scientific – NanoDrop Products 2011). Nucleic acid concentration consists of both

carrier RNA and potential sample RNA.

cDNA concentrations ranged from 1310.3ng/µL to 5274.3ng/µL per sample with an average of

2667.8 ng/µL, and purity (260/280 ratio) ranged from 1.47 to 2.32 with an average of 1.88

(Table 4). For DNA ratio of ~1.8 is normally accepted for purity. Similarly, low 260/280 purity

ratios indicate contamination, while high 260/280 purity ratios not necessarily indicative of an

issue (Thermo Fisher Scientific – NanoDrop Products 2011).

Table 4: RNA concentrations (ng/µL) and purity (260/280). cDNA concentrations (ng/µL) and purity (260/280).

For DNA ratio of ~1.8 is normally accepted for purity. The results of the nanodrop for both RNA and cDNA do not

give an indication if the target gene is present or if the target gene is able to be amplified. Samples processed in

work flow 1 are in bold.

Site RNA concentration

(ng/µL)

RNA

purity

(260/280)

cDNA concentration

(ng/µL)

cDNA

purity

(260/280)

Notes

Ph01HB 133.7 3.10 2351.7 1.89

PH02Dol 141.1 3.10 Ran out of cDNA

PH03Dul 91.2 3.12 2256.0 1.89

PH04BI 141.1 3.15 2175.6 1.91

PH05WI 137.3 3.07 1907.5 1.92

PH06SB 164.3 2.73 2360.6 1.90

PH07RI 113.3 3.15 1310.3 1.91

PH08MB 165.8 3.21 1937.6 1.89

PH09VI 146.2 0.86 2294.7 1.90

PH10BU Buffer leaked in

Whirl-Pak®

PH11HI 139.8 3.12 3901.3 1.84

BA01WB 110.7 3.00 2498.9 1.89

BA02MSB 142.4 3.03 2732.2 1.90

BA03MI 146.7 2.98 1954.0 1.92

27

BA04CI 119.3 2.99 2509.8 1.89

BA05CH 125.3 2.99 2273.6 1.90

BA06SEB 142.5 3.00 3040.1 1.88

BA07CB 109.0 2.99 2881.7 1.89

BA08WP 127.7 3.10 2145.5 1.91

BA09RP Buffer leaked in

Whirl-Pak®

BA10SR Buffer leaked in

Whirl-Pak®

BA11WC 137.4 3.08 3181.4 1.89

BA12BP 143.3 3.02 2099.0 1.91

BA13URP (II)

127.9 3.11 5216.9 1.55

BA14AP 151.0 3.13 3155.4 1.89

BA15MI 150.0 3.10 2081.3 1.90

BA16PB 110.7 3.00 2167.2 1.90

BA17SI 141.2 2.97 2387.4 1.90

BA18LI 155.4 3.05 2661.6 1.89

BA19DP 136.2 2.71 2848.7 1.89

BA20PE 129.9 2.98 4668.8 1.74

BA21BP 116.7 3.06 3205.7 1.88

BA22DI 122.7 3.03 3910.7 1.84

BA23HR 141.3 3.09 2758.0 1.89

BA24SP 102.8 2.95 2023.5 1.86

DI01MP 116.9 3.02 1749.6 1.92

DI02YI 97.2 2.97 2331.2 2.32

DI03DU 148.1 3.05 1984.2 1.93

DI05CB 127.9 3.12 3061.1 1.86

28

DI06CP 91.8 3.09 2589.7 1.87

DI07CR 156.5 3.17 2311.3 1.89

DI08BN 99.2 2.98 2187.1 1.90

DI09SN 146.9 3.03 3007.0 1.90

DI10VN 143.8 3.12 2728.5 1.91

DI11BI 110.6 3.02 2315.9 1.88

DI12YP 130.1 3.04 1985.3 1.93

DI13SP 132.1 2.95 1901.7 1.93

DI14FA 140.2 2.99 4736.7 1.75

DI15SEG 152.6 3.03 5274.3 1.47

DI16FS 135.8 3.03 3243.5 1.90

DI17OP 110.3 2.94 2295.0 1.91

DI18TR 147.6 3.15 2483.2 1.92

DI19BR 130.7 2.97 2578.3 1.88

DI21MP Sterivex lost

DI22BK 129.7 3.03 3731.7 1.83

DI23PA 111.5 3.13 Ran out of cDNA

DI24CN 104.5 2.98 2512.9 1.88

DI25LB 125.5 3.02 2630.8 1.88

DI26HA 141.8 2.97 2136.2 1.88

DI27AL 124.1 3.01 2292.7 1.87

DI28CH 103.1 2.88 2419.7 1.87

DI29RZ 137.5 2.97 2160.3 1.89

DI30DB 109.2 3.07 Ran out of cDNA

DI31HO 187.0 3.12 2478.3 1.88

DI32YI 135.3 3.03 2465.1 1.89

29

DI33SP 142.5 3.00 3364.2 1.91

BA13URP (I)

189.8 2.36 2216.8 1.89

3.2.2 PCR for Detection of Picorna-like Viruses

PCR for RdRp gene fragment from picorna-like marine viruses in work flow 1 was conducted

on three samples before qPCR of PRv (months later in work flow 2) to confirm that

amplification on the samples was possible. Agarose gel electrophoresis of duplicates of sample

sites BA13URP(I), PH09VI and PH06SB using 1 µL and 2 µL of template (Figure 7), showed

positive amplification at the appropriate product size (~450bp (Culley et al., 2010)) for all sites

and all volumes of template. In work flow 2, agarose gel electrophoresis for sites BA13URP(I),

PH09VI, PH06SB, DI11BI and BA8WP showed positive amplification at the appropriate

product size (~450bp (Culley et al., 2010)). In all other 58 sites the RdRp gene was not detected

(Figure 8).

30

Figure 7. Agarose gel electrophoresis PCR for RdRp of picorna-like viruses using cDNA synthesized from RNA

extracted from water samples using 1µl of template (Lanes 2 -4) and 2µl of template (Lanes 6-8) and no template

(Lane 1). 5 denotes 100-bp ladder (Invitrogen, Burlington, ON) . Sample sites are BA13URP(I) (Lanes 1 and 5),

PH09VI (Lanes 2 and 6), and PH06SB (Lanes 3 and 7).

31

Figure 8. Agarose gel electrophoresis of PCR for RdRp of picorna-like virsues using cDNA synthesized from RNA

extracted from water samples using 2µl template. Sample sites that had positive results are BA13URP(I) (Lanes 14

and 49), PH09VI (Lanes 33 and 63), PH06SB (Lane 23), BA08WP (Lane 45), and DI11BI (Lane 22). L and

L2 denotes 100-bp ladder (Invitrogen, Burlington, ON).

32

3.2.3 qPCR of PRv

The reaction efficiency and r2 values for standard curve generated were RE=97.3% r

2=0.997,

which is within acceptable ranges (91 to 100% efficiency, r2>0.99) (Figure 9).

Figure 9. The amplification plots were generated by serial ten-fold dilutions of an DNA samples containing

3 107 targets of the PRv fragment. Two replicates were run for each dilution point. The horizontal blue line marks

the threshold, at which the Ct values are obtained. The standard curve (insert) generated from these amplification

plots is linear over 8 logs, with a slope of -3.389 and an R2 of 0.997.

All reactions of samples were performed in triplicate. With one exception (PH03DUL) all

replicates of all samples had negative results (CT = 0). On September 11 2014 one of the

replicates for the site PH03DUL had gene copies that were detectable at the lower limit of

detection (CT = 37.92) (Figure 10). Site PH03DUL was reanalyzed in triplicate on September

22 2014 and the amount of template was increased from 2 µL to 5 µL since the previous results

suggested the target gene was present at a low density. For all qPCR reactions triplicate no-

template controls reactions were negative, so no amplification was detected, and the positive

results was unable to be replicated.

33

Figure 10. Results of qPCR analysis for PRv in sites DI24-DI32; PH01-02; PH04-PH07 (CT = 0), PH03DUL (CT

= 37.92) and no template control (CT = 0). The standard curve (insert) generated from these amplification plots is

linear over 8 logs, with a slope of -3.449 and an R2 of 0.996.

Chapter 4 Discussion

Responding to high demand and declining or saturated fisheries (Myers and Worm 2003; Pauley

et al. 1998) aquaculture has expanded rapidly, and now produces approximately 40% of all

seafood consumed worldwide (Goldburg & Naylor, 2005). There is evidence; however, that

aquaculture can have negative effects on wild fish populations through harmful by-products,

including infectious disease (Goldberg and Naylor 2005; Naylor et al. 2000). In British

Columbia, macroparasite transmission between farmed Atlantic salmon and wild Pacific salmon

has been studied extensively (Krkosek et al. 2006); however, the viral disease linkages between

Atlantic salmon aquaculture and wild Pacific salmon populations are poorly understood. I

attempted to detect and quantify salmon viral pathogens from sea water, using chemical

flocculation to stabilize viruses, and qPCR to detect the virus.

34

My results failed to detect or quantify the salmon viral pathogen PRV in samples of seawater

collected from locations of salmon farms around Vancouver Island. However, the positive

detections of the picorna-like viruses in work flow 1, but the negative results (expect for one

replicate of one site) for the picorna-like viruses in work flow 2 suggest that perhaps the RNA in

work flow 2 had degraded, or some other laboratory error nullified the detection of virus

material. Because PRV was only analyzed in work flow 2, it is not possible to conclude whether

or not PRV was or was not present in the samples. The positive results for picorna-like virus in

work flow 1 suggest that the methodology we used may be a valuable tool for detecting,

quantifying, and comparing salmon virus communities across locations based on sea water

sampling, but below I discuss the strengths, weaknesses, and areas for possible improvement on

the methodology.

4.1 Field methods

4.1.1 Iron Flocculation

Examining marine viral communities in a natural environment often depends on concentrating

large volumes of water, and viruses that are not abundant in the wild can often only be observed

through these methods (Seeley & Primrose, 1979). PRV is a newly described virus (Kibenge et

al. 2013) and its densities in coastal BC waters are unknown. Therefore, we decided to proceed

under the assumption that PRV viruses were at low densities.

Flocculation was chosen because alternate methods of concentrating viruses with centrifugal

ultrafiltration devices had undesirable characteristics for this project, including: adsorption of

viruses to the filters resulting in low virus yield (Percival et al. 2004), the logistics of using

easily damaged ultrafiltration equipment in a field environment, and low or variable recovery

yields of viruses (Colombet et al., 2007; Fuhrman, 1999).

Although chemical flocculation protocols require less initial volume than other methods such as

tangential flow filtration (TFF), the amount of collected seawater per sample is suggested to be

20 L (John et al. 2010). Because of lengthy filtration times (for 3 L the average initial filtration

time was 23 minutes and for 2 L the average peristaltic filtration time was 69 minutes)

combined with time constraints, the number of sites was prioritized over initial sample volume.

35

In order to determine if the null results of the qPCR were affected by an inadequate initial

sample volume, a pilot study involving collecting and processing increasing volumes of water

could be explored. However, while initial sample volume is an important aspect to consider for

future directions of the study, it does not fully explain the discrepancy between the results of

work flow 1 and work flow 2 (Figure 5). This difference is a result of processes within the

laboratory methods.

4.2 Laboratory Methods

4.2.1 Viral Resuspension

Fe-virus precipitate resuspension to recover viruses of the filter was done through adding 0.2M

ascorbate-EDTA buffer. Protocols outline the use of two different buffers based on the acid that

is used: oxalic acid or ascorbate acid. The oxalic acid buffer initially offered some advantages

over the ascorbate buffer. While viral yields were the same between buffers, the oxalic buffer is

more stable at room temperature and is more effective at maintaining viral infectivity in

recovery (John et al. 2010). I attempted to use the oxalic acid buffer to preserve infectivity for

possible future experiments. Protocols called for the use of Mg2EDTA in preparation of the

buffer; however, the manufacturing company (JT Baker Center Valley, U.S.A) no longer

produces this compound and it is not available through any other companies. An alternate

protocol for the preparation of Mg2EDTA from NA2EDTA and Mg2Cl was used (John et al.,

2014). However, using oxalic acid in this protocol caused a precipitate to form. Changing the

order of the reagents and adding heat did not cause the precipitate go into solution.

Therefore, the ascorbate buffer was used to recover viruses off of the filter, and buffer

effectiveness was assumed to be ensured by using within 48 hours of making and storing at 4⁰ C

(Tovar-Sanchez et al., 2003). This make it unlikely that using ascorbate buffer as opposed to the

oxalate buffer caused any confouding effects. Additionally, the resuspension buffer causes the

iron in the Fe-virus precipitate to change from the ferric (Fe(III)) form to the ferrous (Fe(II)),

one indication that this reaction had occurred is a colour change of the precipitate (John, Poulos,

and Schirmer 2014). The addition of the buffer to the Sterivex™ filters caused colour changes

of the precipitate for all sites; the assumption was then that the reaction had occurred for all sites

(Figure 11).

36

The time between of the addition of the resuspension buffer and RNA extraction was one

difference between work flow 1 and work flow 2. In work flow 1 the average time between the

resuspension buffer step and RNA extraction was 3 days (SD=0.58 days). In work flow 2 the

average time between the resuspension buffer step and RNA extraction was 40 days (SD=6.82

days) (Figure 5). According to the protocols followed for resuspension (John et al., 2011) and

(John et al., 2014) the Fe-virus flocculate is amenable to long term storage with or without the

resuspension buffer, and after 4 months of storage (dark, 4°C), 85% of virus particles were

recovered from Pacific Ocean viral-fraction concentrates. However, these viruses were DNA

viruses (marine "cyanophages"), and it is not stated whether this was with or without the

resuspension buffer. The stability of RNA viruses may not be the same between the Fe-virus

precipitate and the Fe-virus-buffer solution. This may explain why in work flow 1 there were

positive results for all three tested sites for the presence of the picorna-like virus (Figure 7), but

in work flow 2 there were positive results for only two of the 57 sites. It is possible that there

was viral degradation occurring as samples remained in the Fe-virus-buffer solution form. Not

only is RNA is more unstable than DNA (Steinhauer & Holland, 1987), but neither filtration or

flocculation removes RNases (enzymes that break down RNA). This may cause the RNA

viruses in the Fe-virus-buffer solution to be susceptible to degradation in storage.

Additionally, the resuspension buffer needs to be in contact with the filter in order for the

reaction to take place. The protocol was vague about the timing (it specified "a couple of days"),

therefore I proceeded to use the change in colour of the filter as an indicator of the progresses of

the reaction. After 3 days in the resuspension buffer most of the filter had turned from a dark

brown to a light tan colour (Figure 11), and any part of the filter that had not been in contact

with the resuspension buffer (due to the angle of the Sterivex™) remained a dark brown.

37

Figure 11. The change in colour observed before (A) and after (B) the addition of the resuspension buffer.

Based on these qualitative observations I proceeded to increase the amount of time the filters

were in contact with the resuspension buffer and stacked the Sterivex™ filters vertically to

insure that the entirety of the filter was covered with the buffer. Because I assumed that an

increased amount of time for the filter and resuspension buffer to interact would maximize

recovery of viruses off the filter, I did not prioritize transferring the Fe-virus-buffer solution to

1.5mL screwcap tubes. I instead focused on testing two methods of RNA extraction (the

QIAamp®Viral RNA kit which uses carrier RNA, and the TRIzol® Reagent which does not use

carrier RNA) using the samples from work flow 1.

This led to another difference between work flow 1 and 2: time spent in Sterivex™ filter with

resuspension buffer. While all samples at the resuspension buffer stage were kept at a 4⁰

refrigerator, there was a difference in the time spent in the Sterivex™ as opposed to a 1.5mL

screwcap tubes. While the 1.5mL screwcap tubes were kept in a box, sheltered from UV light,

the Sterivex™ filters were not covered and were exposed to the refrigerator light turning on

each time the door was opened. The samples from work flow 1 were in the fridge for an average

of 2 days, while the samples from workflow 2 were there for 35 days. While there is evidence

38

that RNA is more UV resistant than DNA (Kundu, Linne, Marahiel, & Carell, 2004), UV light

is a significant source of viral decay (both for DNA and RNA viruses) in coastal ocean waters

(Suttle & Chen, 1992). While most incandescent light bulbs are designed to minimize UV light,

a small part of the light that they produce consists of UV light (Moseley, 2011). The UV light

from the refrigerator light may have caused sample degradation and contributed to the

difference in results between work flow 1 and 2.

4.2.2 RNA Extraction and cDNA Synthesis

RNA was extracted following the manufacturer's instructions for low density of target

molecules in the sample, which resulted in the addition of carrier RNA that enhances binding of

viral nucleic acids to the spin column membrane. However, the addition of carrier RNA makes

it difficult to quantify RNA yields as the elution will contain both viral RNA and carrier RNA,

and the abundance of carrier RNA can greatly exceed the amount of viral nucleic acid. Which

can mean that detection of extracted RNA may not be possible unless it greatly exceeds the

amount of carrier RNA added. This does not; however, solidly indicate a failure in extraction.

The final RNA may be a mixture of carrier RNA and environmental RNA, but at undefined

relative proportions. The results do not shed light on whether the extracted RNA was intact viral

genomes or if the target RNA is present in the sample. The RNA extracted in work flow 2 could

have been affected by extended time in the Fe-virus-buffer solution, and UV light from the

refrigerator light, and while extraction succeeded the RNA may have degraded to a point where

amplification (through PCR or qPCR) was not possible. The results of the nanodrop for RNA do

not give an indication if the target gene is present or if the target gene is able to be amplified.

The SuperScript® Vilo™ cDNA synthesis Kit (Invitrogen, Burlington, ON) uses random

hexamers not gene-specific primers. The random hexamers create a cDNA copy of all RNA in

the sample rather than targeting a specific gene. So while the concentration of cDNA for all sites

was non-zero, it does not mean that the target gene is present. For example, the target gene may

not have been present in the sample, but since filtration methods are not virus specific and a

copy of all RNA is made and cDNA concentration could be non-zero without the presence of

39

the target gene. Additionally, the RNA does not have to be in a complete genome to be copied.

The RNA could have been degraded and broken down and the random hexamers could have

made cDNA copies of the RNA fragments.

Additionally, while the secondary structure of tRNA is slightly inhibitory, it can be copied into

cDNA. As well, creating a cDNA library from RNA requires the RNA to be of extremely high

quality (Life Technologies 2014). Because of this, non-zero cDNA concentrations are not

indicative of the target gene being present or if the target gene is able to be amplified.

4.2.3 PCR for Detection of Picorna-like Viruses

In work flow 1 all three sites tested showed positive amplification at the appropriate product

size for the RdRp gene (450 bp) (Table 2). In agarose gel electrophoresis false positives can

occur when amplicons of incorrect size are called positives after agarose gel electrophoresis due

to sufficient similarity to the expected amplicon size (Mutschall, Ross, Buchanan, & Taboada,

2010). The work flow 1 PCR products were not sequenced because the detection of picorna-like

viruses was done to confirm that the samples contained amplifiable DNA. The probability of

false positives in this case are low due to using a primer set that has been reliable in the past

(Culley et al., 2010), as well as all the bands being in the exact same spot relative to each other.

In work flow 2, the three sites from work flow 1, as well as two sites from work flow 2 showed

positive amplification at the appropriate product size for the RdRp gene (450bp). The rest of the

sites from work flow 2 did not amplify or showed non-specific amplification. The results that

two sites from work flow 2 had positive results (Figure 8: lanes 45 and 22), while many sites did

not amplify at all (Figure 8: examples lanes 25 and 31), and other sites showed non-specific

amplification (Figure 8: example lanes 6, 42, and 59) provides evidence that the RNA was

degraded. If RNA extraction failed in work flow 2 there would have been zero positive results

from work flow two. We would expect a similar result if cDNA synthesis failed as well. If it

was a matter of presence or absence of target gene there would have been only positive or

negative results, and no non-specific amplification. However, if the RNA was partially degraded

and thus contained smaller regions of target RNA the cDNA synthesis would be able to create

DNA copies of target fragments. The fragments that contained the primer annealing site(s)

40

would be amplified by PCR, but would not show the appropriate product size, since the

fragment would smaller than total target gene.

4.2.4 qPCR of PRv

Although previous studies have provided guidelines for detecting PRV from infected salmon

tissues, detection of PRV from concentrated sea water samples has not been done (Palacios et al.

2010; Wiik-Nielsen et al. 2012; Kibenge et al. 2013). For the tissues, samples were either

analyzed immediately or stored in RNAlater® (Life Technologies, Carlsbad U.S.A), and the

virus was identified through sequencing and qPCR. The location in the PRV genome that

contained the primer set used in (Haugland et al., 2011) was to create the qPCR standards and

primers in my experiment. However, methods for collecting and processing tissue samples were

not relevant to my study.

The results of the standard curve show that the production of standards for PRV were

successful. We found that the 170 bp segment of the PRv genome that was used to create the

standards functioned at the appropriate level of efficiency. Due to the difference in results

between work flow 1 and work flow 2 , and because PRV was only analyzed in workflow 2, it is

not possible to conclude whether PRV was or was not present in the samples. While site

PH03DUL did show one positive result for one replicate, the results could not be replicated. The

inability of replication may suggest that the positive detection was a result of contamination.

The gene copies were detectable at the lower limit of detection (CT=37.92) where the standard

concentration was 3.04 molecules per 2 µl. The results suggest that there were 2-3 gene copies

of PRV present in the sample. While there was no detectable amplification in the no-template

controls and measures were taken to limit contamination (the standards remained in the freezer

and were not thawed until NTC and sample wells had been sealed). The lack of repeatability

does not inspire confidence. The most parsimonious explanation may be that contamination

occurred, but it is not impossible for only three copies of the PRV to be in the sample, given that

only 2 L of seawater were processed and the concentration of PRV in the water column in

unknown.

If the 2-3 gene copies were not due to contamination, using the results from work flow 1 and

work flow 2, and assuming that RNA degradation for the picorna-like viruses and PRV was

41

similar, we can estimate what the abundance of PRV in the initial sample was. In work flow 1

there was a 100% positive results for all number of tests were seen, while in work flow 2 there

was 3% positive results for the number of tests. This was a decrease of 97% in detection.

Assuming the two viruses degraded similarity, an 97% increase in detection for PRV would

result in being able to detect 183 out of the 189 tests for PRV showing in a positive result if

PRV was present in the sample.

4.2.5 Conclusions

Ultimately, my results failed to detect or quantify the salmon viral pathogen PRV in samples of

seawater samples, most likely due to sample degradation.

Special attention needs to be made for RNA viruses as the instability of the molecule appears to

be at the crux of what resulted in the failure to detect. The samples from work flow 2 remained

in the Fe-virus-buffer solution for over 10 times as long as the samples from work flow 1, while

I tested two alternate methods for RNA extraction. While there is evidence that DNA viruses are

stable for long term storage in the Fe-virus-buffer solution (John et al., 2011), the results of my

study indicate that may not be the case for RNA viruses. Additionally, I needed to give more

consideration to shield the samples from UV light during the resuspension buffer stage.

However, there is important information to take away from my results. The "ground truthing" of

the location and status of Atlantic salmon fish farms in B.C., as the information available online

often does not differentiate between a tenure site and an existing fish farm. The protocols for

filtering and flocculating adapted to a field and boat environment will also be useful for future

studies. Finally, the success of work flow 1 provides evidence that when done in an expedient

manner, these methods may be a valuable tool for detecting, quantifying, and comparing salmon

virus communities in the future.

42

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