GLOBAL ISSUES IN AMPHIBIAN DISEASES By SIEARA CLARICE CLAYTOR A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULLFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE UNIVERSITY OF FLORIDA 2016
2016 Sieara Claytor
To my grandmother
ACKNOWLEDGMENTS I would like to thank my committee members, Dr. Samantha Wisely, Dr. Thomas Waltzek and Dr. Christina Romagosa, for their mentorship and guidance with my research and degree. I would also like to thank Dr. Matthew Gray and Dr. Gregory Chinc har for providing the ranaviral isol ates used in my genome analysis, Dr. Kuttichantran Subramanian for his help with genome assembly, Dr. Marco Salemi for helping me with interpretation of results, and Patrick Thompson for training and a ssisting me with ce ll culture
5 TABLE OF CONTENTS page ACKNOWLEDGMENT S ................................ ................................ ................................ ............... 4 LIST OF TABLES ................................ ................................ ................................ ........................... 7 LIST OF FIGURE S ................................ ................................ ................................ ......................... 8 ABSTRACT ... 9 CHAPTER 1 DRIVING FACTORS IN THE EMERGENCE OF INFECTIOUS DISEASE IN AMPHIBIANS ................................ ................................ ................................ ....................... 11 Introduction ................................ ................................ ................................ ............................. 11 Amphibian Pathogens ................................ ................................ ................................ ............. 12 Parasitic Diseases ................................ ................................ ................................ ............ 12 Protozoan Diseases ................................ ................................ ................................ .......... 13 Bacterial Diseases ................................ ................................ ................................ ............ 15 Fungal Diseases ................................ ................................ ................................ ............... 16 Viral Diseases ................................ ................................ ................................ .................. 18 Drivers of Emergence ................................ ................................ ................................ ............. 19 Climate Change ................................ ................................ ................................ ............... 19 Land Use Change ................................ ................................ ................................ ............ 22 Pollutants ................................ ................................ ................................ ......................... 23 Wildlife Trade ................................ ................................ ................................ ................. 24 Conclusion ................................ ................................ ................................ .............................. 26 2 ISOLATION OF COMMON MIDWIFE TOAD VIRUS AND A RECOM BINANT FROG VIRUS 3 STRAIN FROM NORTH AMERICAN BULLFROGS ( Lithobates catesbeianus ) ................................ ................................ ................................ .......................... 27 3 METHODS ................................ ................................ ................................ ............................. 30 Isolate Collec tion ................................ ................................ ................................ .................... 30 Cell Culture, Virus Purification, and DNA Extraction ................................ ........................... 30 Library Preparation, Next Generation Sequencing, de novo Assembly ................................ 31 Genome Annotation, BLASTp Analysis, and Alignment ................................ ...................... 31 Phylogenomic Analyses ................................ ................................ ................................ .......... 32 4 RESULTS ................................ ................................ ................................ ............................... 37 Genome Annotation, BLASTp Analysis, and Alignment ................................ ...................... 37 Phylogenetic Analysis ................................ ................................ ................................ ............ 37
6 5 DISCUSSION ................................ ................................ ................................ ......................... 57 LIST OF REFERENCES ................................ ................................ ................................ ............... 61 BIOGRAPHICAL SKETCH ................................ ................................ ................................ ......... 77
7 LIST OF TABLES Table page 3 1 Virus isolate ID, host common names, host scientific name, year of isolation, reference, accession number and genome size of 17 ranaviral isolates used for phylogenetic analysis ................................ ................................ ................................ ......... 34 4 1 Predicted open reading frames for the 2006 ranavirus isolate (RI 1) genome ................... 39 4 2 Predicted open reading frames for the 1998 ranavirus isolate (RI 2) genome ................... 44 4 3 Substitution models, phylogenetic signal and substitution saturation in the 52 gene concatenated gene alignment for 17 ranavirus species ................................ ...................... 48 4 4 Summary of substitution models for PartitionFinder and JModelTest ............................... 51 4 5 The nineteen significant recombination events for the RDP4 analysis. Events were reported if four or more detection softwares reported significant re combination. ............ 52
8 LIST OF FIGURES Figure page 3 1 Map of sample isolation locations for 17 ranavi ral isolates shown in Table 3 1 ............... 35 3 2 Flow chart of cell culture and phylogenetic methods used in thi s study ............................ 36 4 1 Map of recombination events in the concatenated alignment of 52 conserved genes in RC15021:RC_2006_GA_Gray (R I 1) ................................ ................................ ............... 54 4 2 Cladogram depicting the relationship of RI 1 and RI 2 to representatives of the genus Ranavirus based on the concatenated nucleotide alignment of 52 conserved genes ....... 55 4 3 Phylogram depicting the relationship of RI 1 and RI 2 to representatives of the genus Ranavirus based on the concatenated nucleotide alignment of 52 conserved genes ................................ ................................ ................................ ................................ 56
9 Abstract of Thesis Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science GLOBAL ISSUES IN AMPHIBIAN DISEASES By Sieara Clarice Claytor May 2016 Chair: Samantha Wisely Coc hair: Thomas Waltzek Major: Wildlife Ecology and Conservation The global decline of amphibians has been attributed to many factors such as loss of habitat, climate change, pollution, introduced species, UV radiation, population fluctuations and disease. Outbreaks of i nfectious diseases, such as the amphibian chytrid fungus Batrachochytrium dendrobatidis (Bd ) and Ranavirus are recognized as major contributors to i nternational amphibian declines and a nt hropogenic factors contribute to the rise of emerging infectious dise ases in amphibians. The first chapter presents a review of the driving factors of the emerging infectious diseases of amphibians. It begins with a brief review of amphibian pathogens, and then discusses the factors that drive these disease emergences. The second chapter presents a study on two viral isolates from North American bullfrogs (Lithobates catesbeian us ), both from the same commercial ranaculture facility, collected in 1998 and 2006. The goal of this chapter was to isolate and sequence the genomes of two ranaviruses from a ranculture epizootic, during different years. The genomes of the two viral isol ates were sequenced and phylogenomic analyses were used to compare the viral isolates to 15 other ranaviruses genomes The sequencing efforts revealed that common midwife toad virus (CMTV)/ Chinese giant salamander virus (CGSV) was responsible for an outbreak in North American cultured bullfrogs in 1998. The 2006 isolate was shown to be a chimeric FV3 strain,
10 with regions of the genome showing recombinat ion with the CMTV/CGSV strain previously isolated from the same ranaculture facility. Our study is the first to show that bullfrogs in a ranaculture facility were infected with chimeric ranaviral strains. Also, we present evidence of the earliest CMTV infe ction in an amphibian. North American bullfrogs are the most frequently imported amphibian species. FV3 and CMTV have low host specificity and are able to infect multiple classes of animals. To reduce the threat of nave populations to pathogen pollution c aused by ranavirus, it is important to understand the probable role that ranaculture facilities may have in harboring chimeric strains of ranaviruses. Due to the high density of amphibians in ranaculture facilities, there is an increased chance of transmis sion between hosts. It is critical to consider the probable risk that the transportation and release of infected animals could have on wild and endangered populations.
11 CHAPTER 1 DRIVING FACTORS IN THE EMERGENCE OF INFECTIOUS DISEASE IN AMPHIBIANS Introduction The global decline of amphibian populations was first recognized in the early 1990s (Wake 1991). According to Stuart et al. (2004), of the approximate 6,600 species of amphibians, 32 .5 % are threate ne d by extinc tion, while 43 .2 % are declining and 22 .5 % do not have sufficient data to assess their status The decline of global amphibian populations has been attributed to many factors, such as habitat loss and fragmentation (Dodd and Smith 2003), climate change (Don nelley and Crump 1998, Pounds et al. 1999), pollution (Blaustein et al. 2003), introduced exotic species (Knapp 1996; Gillespie 2001), increase in ultraviolet radiation (Blaustein and Wake 1995), natural fluctuations in populations (Pechmann et al. 1991) a nd disease (Blaustein et al. 1994). It has also been suggested that many factors can work synergistically with disease (Fellers et al. 2001) to accelerate population decline Disease ecology examines the mechanisms that determine how parasites spread thro ugh individual hosts and effect host populations and communities (Hudson et al. 2002). In amphibians, the causes of population declines and extinction for a particular species may vary from region to region (Blaustein et al. 2010). Amphibians are exposed t o many stressors throughout their life cycles (Blaustein et al. 2011), which can affect the molecular, physiological, individual, population and community levels. Anthropogenic factors are suggested to contribute to the rise of emerging infectious disease s in amphibians. Though disease is a key threat to animal populations, little is understood about their ecology in comparison to human p athogens (Daszak et al. 2000). Many pathogens are introduced anthropogenically into new regions, potentially giving the pathogen a new host range. Emerging amphibian diseases, such as chytridiomycosis and ranaviral infections are now found
12 globally, and are believed to have spread by the human movement of hosts. T he goal of this review is to first describe and summarize maj or infectious diseases reported in amphibians, and then discuss anthropogenic drivers to these emerging diseases. Amphibian Pathogens Parasitic D iseases Macroparasites (typically helminth s and some arthropods) were once believed to cause little pathology to amphibians (Pruhoe and Bray 1982). Research from experimental and field studies have now shown that some macroparasites can be significant amphibian pathogens. Pesticides, eutrophication, and landscape change are important drivers of amphibian macropara site infections (Kiesecker 2002). These drivers can alter the immunity of hosts behavior, and host and parasite abundance. Amphibian pathology likely occurs under high intensity infections. Some individual frogs can support dozens of macroparasite species and several thousand individual parasites (Sutherland 2005). Many macroparasites have complex life cycles that require a developmental period in one or more intermediate hosts before they can mature in the definitive host. In a variety of parasites, amphi bians are both intermediate and definitive hosts (Koprivnikar 2012). The effects of macroparasites on amphibian populations are generally unexplored. Macroparasitic infections can influence host growth and reproductive rates, which may contribute to popula tion fluctuations (Hudson et al. 1998). In the early life stages of amphibians, they often have highly variable recruitment and mortality. Macroparasites unlikely cause rapid die offs or complete extirpation of host populations, and therefore detecting any population level effects is difficult. For example, trematodes can reduce amphibian recruitment via direct mortality and deformities. The effects are difficult to detect without long term data that considers
13 the possible resc ue e ffect from populations fro m nearby infection free sites (Martinez Solano and Gonzales 2008). Amphibians can become parasitized at various developmental stages. Fish louse ( Argulus ) and Lernaea copepods are known to infect the aquatic life stages (Crawshaw 1992). These crustaceans a ttach to the amphibian h ost to feed and cause lesions on the animal. Postmetamorphic amphibians also suffer from lesions due to trombiculid mites (chiggers)(Sladky et al. 2000). Amphibians at various life stages can be parasitized by maggots, which are la rval dipterid flies (Menin and Giaretta 2003; Duellman and Trueb 1986). Monogenes can externally and internally infect amphibians (Poynton and Whitaker 2011). Heavy infections can cause health problems and increase susceptibility to secondary infection. Amphibians can be secondary intermediate or final hosts of trematodes (flukes). Thes e trematodes cause lesions by encysting or attaching to the host. Infections with Ribeiroia metacercariae (encysted larvae) can cause developmental deformation in their amphibian hosts and increase their mortality (Johnson et al. 1999). Nematodes (roundworms) (Williams 1960; Patterson Kane et al. 2001; Cunningham et al. 1996) and cestodes (Wright 2006; Pessier 2002) also infect amphibians. Protozoan Diseases Various species of protozoans have been found in wild and captive amphibians. Many intestinal protozoa usually do not cause disease in their host due to their commensal relationship (Densmore 2007). Amoebia sis is a disease of stressed amphibians caused by amoeba, often from the genera Entamoeba (Wright 2006). These parasites generally occur internally and are usually found in the gastrointestinal tract, liver or kidney of the hosts (Wright 2006). Larval fro gs from the genera Lithobates and Acris have suffered mass mortality events in the United States caused by a protist (Davis et al. 2007; Green et al. 2003). Davis et al. (2007)
14 histologically examined tadpole tissues and found thousands of small spherical cells infecting the livers of Southern Leopard Frogs ( Lithobates sphenocephalus ) from a mass mortality event in Georgia. The lineage of protist found was closely related to Perkinsus which parasitizes marine bivalves (Azevedo 1989). Chambouvet et al. (201 5) used small subunit (SSU) ribosomal DNA (rDNA) sequencing to test for Perkinsea like lineages in the livers of 182 tadpoles from many different frog families. A distinct Perkinsea clade was f ound; different from the previously associated lineage to tadpo le events of mass mortality (Chambouvet et al. 2015). This clade of protist was found in 38 tadpoles from 14 distinct genera, from five countries and three continents (Chambouvet et al. 2015). This study showed that Perkinsea like protists infect tadpoles from a variety of frogs in tropical and temperate environments (Chambouvet et al. 2015). Ciliates (Pessier 2002) flagellates, trypanosomes (Poyton and Whitaker 2001; Wright 2006), sporozoans, cocc i dia (Poyton and Whitaker 2001) and microspsoridians have al so been associated with amphibian infections (Poynton and Whitaker 2001). In salamanders, mortality can be caused by the ciliate Tetrahymena (Pessier 2002). Trichodinids parasitize the external surface and urinary bladders of the host, causing clinical dis ease with large parasite loads (Poynton and Whitaker 2001). Flagellates, particularly the genera Piscinoodinium and Ichthyoboda can cause severe skin or gill lesions in high numbers on their host (Poynton and Whitaker 2001). Hemoflagellates generally are nonpathogenic (Poyton and Whitaker 2001). Some trypanosome species can cause fatal infections to their amphibian hosts (Wright 2006). Sporozoan parasites, such as apicomplexans, have been associated with diseased amphibians. Many apicomplexan genera have b een found in amphibian blood, gastrointestinal tracts, and other organs and tissue with varying degrees of pathogenicity (Densmore 2007). Coccidia from the genera Eimeria and Isospora have been found in as gastrointestinal fauna in
15 many species of amphibia ns (Poynton and Whitaker 2001). Microsporidian can cause disease in amphibians, particularly in anuran species. Bacterial Diseases Bacterial infections of amphibians are relatively common. Some bacteria are quite ubiquito us and commonly cause secondary in fections in amphibians. Some bacterial pathogens ( Aeromonas hydrophila ) have been associated with massive die offs of mountain yellow legged frogs ( Rana muscosa ) in Kings Canyon National Park, in California in 1979 (Bradford 1991) and boreal toads ( Bufo bo reas boreas ) (Carey 1993) The most overdiagnosed and misdiagnosed disease of amphibians is red leg syndrome or bacterial dermatosepticemia. Red leg syndrome is a bacterial infection (by A. hydrophila ) of amphibians, which causes cutaneous erythema (superf icial reddening of the skin). Clinical signs include anorexia, swelling, edema, coelomic effusions (coelomic fluid buildup ), epidermal erosions, ulcers, sloughing or necro sis (Densmore and Green 2007). This disease is considered widespread with reports dat ing from over 100 years ago for many species of captive and wild amphibians. Many outbreaks of red leg diseases in North American and Europe before 1990 were credited primarily by their symptoms. The symptoms of red leg are general, consistent with other a mphibian diseases. It is likely that many of these outbreaks were caused by other diseases such as chytridiomycosis or ranaviral infections (Green et al. 2002). Flavobacteriosis is a bacterial disease found widely in aquatic environments of captive and wil d amphibians, as well as of other lower vertebrates. Bacteria from the genus Flavobacterium cause this disease. Mortality in captive anurans is suggested to be significant (Green et al. 1999). Mycobacteriosis is a chronic and progressive disease that affec ts amphibians, caused by bacilli bacteria from the genus Mycobacterium. Gross lesions and chronic granulomatous inflammation (immune cell masses that form at the infection site) are signs of
16 mycobacteriosis (Densmore 2007). The skin of the mouth and digits the liver, spleen, intestines and kidney are commonly infected (Densmore 2007). Chla mydiosis has been reported in both wild and captive anurans (Berger et al 1999). This disease is caused by Chlamydophila sp ., which is a coccoid, intracellular pathogen ( Bodetti et al. 2002). Fungal Diseases Fungal organisms are relatively common pathogens of lower vertebrates in aquatic environments. Since many fungi are ubiquitous in nature, stressed, injured, or immunocompromised individuals are greatly affected. Funga l spores are much more durable and long lasting than bacteria and viruses and can easily be transferred globally by humans. Fungi can also reproduce sexually, which allows fungi that encounter other fungi in new habitats to recombine into potentially more virulent strains. Chytridiomycosis caused by the chytrid fungus Batrachochytrium dendrobatidis (Bd) is the most well described pathogen of amphibians. This fungal pathogen has been associated with severe population declines, extirpations and extinctions globally. It was first reported in Australia (Berger et al. 1998) and Central America (Pessier et al. 1999) in the mid 1990s. Chytrids are ubiquitous, keratinophilic or chitinophilic, sporozooic fungi that are found in moist and aquatic environments (Densm ore 2007 ). Some studies have identified Bd in diseased amphibians from the 1930s (Weldon et al. 2004). Bd infections target the keratin layers of amphibian skin. In anuran tadpoles, chytridiomycosis causes a loss of the black coloration of the mouth parts and rounding of the edges of the jaw sheaths. Postmetamorphic anurans show an alteration in the physiological functions of the epidermis and sometimes also oppo rtunistic secondary infections. Clinical signs of infection include lethargy, dehydration, dysec dysis (abnormal shedding of the skin), skin
17 hyperemia (increased blood flow), neurological signs showing abnormal posture, righting reflex loss and behavioral changes (Densmore 2007). Batrachochytrium salamandrivorans has recently been discovered to infect fire salamanders ( Salamandra salamandra ) in the Netherlands (Martel et al. 2013). In experimentally infected salamanders, erosive skin disease and mortality occurred (Martel et al. 2013). A phylogenetic study showed that B. salamandrivorans formed a disti nct clade with B. dendrobatidis Martel et al. 2013). In an experimental setting, midwife toads ( Alytes obstetricans ) were not successfully infected with B. salamandrivorans (Martel et al. 2013). B. salamandrivorans also preferred a lower temperature than B dendrobatidis (Martel et al. 2013). The results suggest that B. salamandrivornas has a unique niche (Martel et al. 2013). Zygomycoses is a disease that has been reported in captive and wild anurans from the fungal subclass Zygomycetes (Taylor 2001). Zygomycetes is ubiquitous in moist environments with soil and decaying material. Zygomycoses may occur as a secondary infection in an amphibian with a compromised immune system or introduction through the skin, ingestion or inhalation of fungal spores (Taylor et al. 2001). Chromomycoses is another disease caused by a fungi found in soil and dead plant matter (Juopperi et al. 2002). For larval amphibians, water molds can be a primary skin or oral pathogen (Densmore 2007). Water molds can cause superficial secondary infections in amphibians because they are ubiquitous in aquatic environments. Saprolegniasis is an infectious disease o f aquatic lower vertebrates caused by water mold species (Densmore 2007). Interclass transmission of Saprolegnia can occur from fish to amphibians (Kiesecker et al. 2001). Amphibian eggs can be affected by Sparolegniasis, which can cause high levels of egg mortality (Blaustein et al. 1994).
18 Viral Diseases There are few described viruses that affect amphibians. There has been an increased concern over the health of wild amphibian populations and an increase use of amphibians for commercial uses, research an d public display (Densmore and Green 2007). Viral diseases of amphibians were historically under diagnosed, but in the 1960s, cell culture technology and virology of ectothermic vertebrates began to advance. Recently, molecular diagnostic techniques, ident ification and characterization has become more advanced and allowed better characterization of amphibian viruses. Amphibian viruses, particularly ranaviruses, have been associated with mass mortality of amphibians in wild and captive populations globally, such as the common frog ( Rana temporaria ) (Cunningham et al. 1996) and the federally listed Sonora tiger salamanders ( Ambystoma tigrinum stebbinsi ) (Jancovich et al. 1997). Trade of amphibians is be lieved to be one driver of the global spread of viral dise ases Ranaviruses are the best described pathogenic viruses of amphibians. Ranaviruses are double stranded icosohedral DNA viruses from the genus Ranavirus and the family Iridoviridae. Many ranaviruses affect fish, amphibians and reptiles. Transmission o ccurs by direct contact with infected animals, cannibalism, ingestion of virus, or contact via the water column (Johnson a nd Wellehan 2005). The disease is usually systemic and presents itself within days to 2 weeks (Wolf et al. 1969). Clinical signs are l ethargy, anorexia, abnormal bodyposture, abnormal swimming behavior, buoyancy deficits, erythematous skin from hemorrhage, skin lesions, and swelling (Wolf et al. 1969 ; Docherty et al. 2003; Johnson and Wellehan 2005 ). Frog virus 3 (FV3) is the type speci es of ranavirus affecting anurans. It was first described in 1965 (Granoff et al. 1965), and affects most ly premetamorphic life stages. Tadpole edema virus (TEV) is another ranavirus closely related to FV3, which was originally isolated from frogs in the 1 960s (Wolf et al. 1969). Both FV3 and TEV are associated with amphibian
19 die off in the United States (Green et al. 2002). Bohle iridovirus (BIV) is found primarily in Australian anurans (Speare and Smith 1992). Ambystoma tigrinum virus (ATV) has been assoc iated with die offs of tiger salamander tadpoles ( Ambystoma tigrinum ) in the western USA (Docherty et al 2003; Jancovich et al. 1997). Lucke herpesvirus or ranid herpesvirus 1 (RaHV 1) is an onocogenic virus of amphibians. It was first described in 1934, as being associated with a renal carcinoma from a northern leopard frog ( Lithobates pipien s ) (Lucke 1934). Light and electron microscopy is currently the only means for diagnosis. Ranid herpesvirus 2, Rana dalmatina herpesvirus (Essbauer and Ahne 2001) and frog erythrocytic virus (FEV) an iridovirus like virus infecting the erythrocytes (Gruia Gray and Desser 1992), have also caused disease in frogs. Frog adenovirus 1 (FrAdV 1) was isolated from the kidney tumors of a leopard frog (Granoff 1989), Crotalus calicivirus type 1 (Cro ( Ceratophrys ornata ) (Smith et al. 1986) and retroviruses were isolated from different hybrid Asian frogs and toads (Johnson and Wellehan 2005). The pathology of these viruses have not fully been determined. Drivers of Emergence Climate Change Research has shown that there is no single cause of amphibian population declines. Environmental stressors affect amphibians in complex ways and the causes of a given species may differ between regions or populations of the same species (Blaustein et al. 2010). Climate change may act synergistically with disease to affect amphibians at individual, population and community levels (Blaustein et al. 2010) Fluctuations in weather and changes in climate often are linked to the exposure of organisms to increased ultraviolet B radiation (UV B) (Andrady et al. 2009). Levels of UV B
20 radiation have increased since 197 9 in the tropics and temperate regions (Kerr et al. 1993). UV B radiation can cause mutations and c ell death (Cockell and Blaustein 2001). On an individual scale, UV B radiation can slow growth rates, cause dysfunction in immunity, cause sublethal damage and cause mortality (Cockell and Balustein 2001). Long term temperature and precipitation changes likely will affect amphibians indirectly. By the end of the 21 st century, global surface tempera ture is likely to exceed 1.5C and the contrast between wet and dry regions and wet and dry seasons will increase (IPCC 2013). Changes may include impacts on te rrestrial and aquatic habitats, food webs, community level interaction, spread of diseases, and the intera ction of these factors. The changes in long term temperature and precipitation may ultimately lead to changes in species occurrence and range shifts ( Raxworthy et al. 2008). Directly, climate change has influenced amphibian breeding phenology. Timing of breeding is usually driven by environmental cues such as temperature and precipitation (Carey and Alexander 2003). As temperatures increase, breeding i n some species has been seen to occur earlier in the year (Beebee 1995). Host pathogen interactions can be altered by changes in temperature. Increasing global temperatures will allow pathogens to experience a faster growth and reproduction that could incr ease the severity of infectious diseases (McMenamin et al. 2008). Warmer winters and nighttime temperatures can potentially reduce the cycle of pathogen die off that occurs normally during colder times (Burdon and Elmquist 1996). Higher water temperatures can cause eutrophication with blooms of algae, bacteria, protozoans and small metazoans (Schindler 1997). Changes in precipitation or hydrology could alter host pathogen relationships. The Intergovernmental Panel on Climate Change (IPCC) has suggested that the annu al precipitation
21 will increase in higher latitudes in both hemispheres. T he t otal annual precipitation is also suggested to decrease in low to mid norther n latitudes and mid southern latitudes (IPCC 2007). Aquatic amphibian pathogens such as oomyc etes, trematodes and certain fungi, are transmitted aquatically. Increased rainfall causes more standing water, which could increase transmission rates. The amphibian chytrid fungus Bd, is sensitive to water conditions, and dies after 2 hours of desiccatio n (Johnson et al 2003). In laboratory settings, high temperatures can inhibit growth or kill Bd (Longcore et al. 1999). Pounds et al. (2006) suggested that climate change has made environmental conditions more favorable for amphibian diseases. Warmer night time temperatures and mistier daytime temperatures in Costa Rica, allow a better growth spectrum for Bd (Pounds et al. 2006). Local environmental changes can decrease immunity and lead to outbreaks of pathogens and mortality. Synergistic effects between c limate change, pathogens, UV B radiation and amphibian population decli nes have been reported (Kiesecker et al. 2001). El Nio and Southern Oscillations (ENSO) events caused decreased winter precipitation in the Cascad e Range of Oregon, USA. The reduction in winter snow pack caused lower water levels in the spring when western toads ( Bufo boreas ) breed. S hallower water for toad embryos to develop caused the embryos to suffer higher exposure to UV B radiatio n (Kiesecker et al. 2001). Higher UV=B radiation e xposure caused i ncreased mortality of the embryos by the pathogenic oomycete, Saprolegnia ferax (Kiesecker et al. 2001). Climate change may shift the ranges of pathogens, hosts, or pathogen vectors. When local habitats are altered by climate change, new ar eas may become suitable for the host or patho gen. In the Andes M ountains, amphibians and Bd have shifted their range upward. High elevation
22 sites are losing glaciers, which opens up new habitats for amphibians (Seimon et al. 2007). In these new sites, Bd h as been detected on amphibians (Seimon et al. 2007). Changing precipitation patterns, warmer temperatures and warm ENSO are causing extreme climatic events, which have had severe e ffects on amphibians (Reaser, Pomer ance and Thomas 2000). Harvell (2002) sug gested that climate change will cause th e range of pathogens to expand. In contrast, Lafferty ( 2009 ) argued that climate change will causes a pole ward shift in the suitable areas for disease, due to higher latitudes becoming warmer, while areas near the e quato r become too hot These two views have caused a debate whether climate change will cause an expansion or shift in the range of pathogens. Land Use Change Habitat destruction, alteration and fragmentation are serious causes of amphibian population decl ines. Amphibians have a variety of habitat requirements, varying between species and life stages. In California, habitat destruction and urbanization is reported to significantly contribute to population declines in the California red legged frog ( Rana dra ytonii ) (Davidson et al. 2002). For salamanders in the Appalachian Mountains, clear cutting affected species richness and abundance (Petranka et al. 1993). For many amphibians, a metapopulation structure is common (Marsh and Trenham 2001). Models predict t hat populations that are isolated are more likely to become extinct than those that a re connected (Hanski 1999). Isolated populations could change. Amphi bians are particularly vulnerable to changes and degradation of terrestrial and aquatic habitats. This vulnerability may be due to relatively low ability of amphibians to migrate (which intensifies the effects of habitat fragmentation) (Sinsch 1990), high vulnerability to dying when crossing roads and inhospitable terrain (Fahrig et al. 1995), narrow habitat tolerance, which
23 worsens the effects of habitat loss, degradation and edge effects (Findlay and Houlahan 1997), and high vulnerability to pathogens, in vasive species, climate change, UV B radiation, and pollution (Pounds et al. 1999). Pollutants Pollutants have been documented to have lethal to sublethal effects on amphibians, ranging from decreased development and growth, increased frequency of abnormal development, diseases susceptibility and chang es in behavior (Bridges 1999). Due to the diversity of pollutants and their mode of action, amphibians are affected differentially. The contamination of freshwater systems by heavy metals that come from industrial and agricultural sources are one factor that highly permeable skin, which allows them to rapidly absorb metal ions, anuran amphibians are susceptible to the uptake of heavy metals. Tadpoles also ingest sediment that has accumulated high levels of heavy metals (Hopkins and Rowe 2010). Sublethal concentrations of metals can have harmful effects, which include reduced growth rates, delayed metamorphosis and impaired behavior responses (Hopkins et al. 2000). The susceptibility of amphibians to the effects of metal exposure varies between species because of different physiological tolerances, habitat requirements, developmental periods and patterns of breeding (Snodgrass et al. 2004). In a study by Parris and Baud (2004), the heavy metal copper increased the larval period length of Gray Treefrogs ( Hyla chrysoscelis ) while infected with Bd The results show that copper may lessen some of the negative effects of B d. Agricultural chemicals can also affect disease in amphibian populations. In aquatic ecosystems, anthropogenic eutrophication is caused by inputs of nitrogen and/or phosphorus, from agriculture, livestock, erosion, sewage waste, and atmo spheric depositio n (Schindler 2006). Primary production can be limited by nitrogen and phosphorus (Schindler 2006). Global
24 agriculture and application of fertilizer is projected to increase (Millennium Ecosystem Assessment 2005). Anthropogenic phosphorus is also shown to r emain persistent in soil used for agriculture and aquatic systems (Bennett et al. 2001). In the next century, eutrophication is believed to become major pr oblem (Lafferty and Holt 2003 ). Johnson et al. (2007) showed that aquatic eutrophication promotes pa thogenic infection of amphibians by Ribeiroia a trematode parasite that infects freshwater snails, larval amphibians and water birds. The malformations caused by this parasite can reduce amphibian survival, which could contribute to population declines (K iesecker 2002). In a study by Rohr et al. (2008), the commonly used herbicide atrazine, was shown to be the best predictor of larval trematode infections in the northern leopard frog ( Lithobates pipiens ). Wildlife Trade Pathogen pollution is the introducti on of a pathogen to a new host species, population or geographic region by humans (Cunningham 2003). Many countries do not track their import and export of wildlife shipment, and records are often difficult to obtain from the countries that do record shipm ents (Smith et al. 2012). There are a large number of individuals and species shipped internationally, which increases the likelihood of emergence of a novel pathogen (Smith et al. 2012). In the United States, 69% of the animals imported come from Southeas t Asia, which has been suggested to be a trade hotspot for future emerging diseases (Jones et al. 2008). Inter specific interactions can allow for pathogen transmission due to the shipping practices in shipping containers and breeding facilities (Smith et al. 2012). For amphibians, live animal trade is theorized to be a major force in spreading pathogens globally. The parasitic fungus Batrachochytrium dendrobatidis (Bd) is believed to have spread globally through the transportation of live animals. The Nor th American bullfrog ( Lithobates catesbeian us ) is one species that is commonly traded internationally. This bullfrog is farmed for
25 frog legs and exotic populations have been reported outside of its historical range. Many captive bred and introduced bullfro gs have tested positive for Bd (Pessier et al. 1999). In Brazil, North American bullfrog farms have reported genetically similar infections of Bd to those in native amphibians from Central and South America. The genetic similarity between farmed and native amphibians suggests that infection could be due to transmission between wild and captive populations (Schloegel et al. 2010). To minimize pathogen pollution via live animal trade standardized protocols for import and export should be implemented. The Aq uatic Animal Health Code (Aquatic Code) is published and regularly updated by the World Organization for Animal Health (OIE). The goal of this code is to insure a standard of health and welfare to farmed fish and safe and sanitary trade of aquatic animals and their products (World Organization for Animal Health 2015). The OIE has recently listed two emerging amphibian diseases that have caused significant amphibian declines, chytridiomycosis (caused by the fungus Batrachochytrium dendrobatidis ) and viral di To reduce the emergence of disease in wildlife trade, many methods have been suggested. As of January 28 th 2016 the importation and interstate transportation of 201 listed salamander species has been pr ohibited, due to the risk of Bs, under the Lacey Act (USFWS 2016). Smith et al. (2012) suggests pre import risk analysis, support for science on disease risks associated with imports, allocation of resources to agencies that enforce trade, not allowing imp roperly labeled wildlife shipments to be imported, work with stakeholders to create incentives for participation in risk reduction programs and finally, to work with other counties to require third party screening for high priority animals and pathogens.
26 C onclusion Drivers of infectious diseases in amphibians have many complex causes. To reduce the effects of infectious diseases Plowright et al. (2012) suggested promoting ecological resilience by maintaining biodiversity and preserving large landscapes for conservation. Ecological resilience is the ability of a system to buffer disruption (Holling et al. 1996). It is believed that enhancing ecological resilience will buffer the effects of infectious disease (Plowright et al. 2012). More sustainable agricultu re could reduce contaminant runoff and eutrophication, mitigating climate change could lessen its global impact, and standardized protocols for amphibian import and export would minimize the introduction of pathogens into new populations. Amphibians are im portant bioindicators of ecosystem health. Amphibian eggs are vulnerable to chemical pollutants and UV radiation, which can disrupt the development of the embryo. The permeable skin of amphibians also makes them susceptible to toxins and chemicals. Amphibi ans are important parts of aquatic and terrestrial communities, inhabiting many different niches and act as abundant prey for wildlife. Responses of amphibians to contaminants and other environmental disturbance can indicate changes in their environments. It is important to identify the key anthropogenic and environmental factors that regulate host susceptibility and disease dynamics of populations. This will allow for new disease intervention measures. With many of the worlds amphibian population threatene d by land use change, pollution, habitat fragmentation, climate change and disease, it is all too clear that adaptive management strategies should reduce anthropogenic environmental change to protect amphibians from further decline.
27 CHAPTER 2 ISOLATION O F COMMON MIDWIFE TOAD VIRUS AND A RECOMBINANT FROG VIRUS 3 STRAIN FROM NORTH AMERICAN BULLFROGS ( Lithobates catesbeian us ) Members of the family Iridoviridae include enveloped double stranded DNA viruses with a nucleocapsid that displays an icosahedral symmetry (Jancovich et al. 2012). The nucleocapsid diameter varies in size between 120 300 nm and contains a linear terminally redundant genome ranging from 140 330 kbp in size (Jancovich et al. 2012). The family includes two genera that infect invertebrat es ( Chloriridovirus Iridovirus ), two genera that infect fishes ( Lymphocystivirus and Megalocytivirus ) and the genus Ranavirus that infect fish, amphibians, and reptiles (Gray and Chinchar 2015, Duffus et al. 2015). Currently, there are six species of rana viruses and three are know n to infect amphibians : Ambystoma tigrinum virus (Jancovich et al. 1997), Bohle iridovirus (Speare and Smith 1992), and Frog virus 3 (FV3) (Granoff et al. 1965). Ranaviruses are considered g lobally emerging pathogens because they appear to be increasing in distribution, prevalence, and host range (Daszak et al. 1999, Gray and Chinchar 2015, Duffus et al. 2015). They are known to infect no fewer than 175 species across 53 families of ectothermic vertebrates on every continent except Antarctica (Duffus et al. 2015). There is e vidence that ranaviruses pose a threat to poikilothermic vertebrate biodiversity including species of conservation concern such as the Chinese giant salamander ( Andrias davidianus) gopher tortoise ( Gopheru s polyphemus ), and pallid sturgeon ( Scaphirhynchus albus ) (Geng et al. 2011 Waltzek et al. 2014, Gray and Chinchar 2015). The risk to species of conservation concern is especially alarming for amphibians as the Global Amphibian Assessment (GAA) has report ed that 43% of amphibian populations are in decline, with 32% considered threatened (Stuart et al. 2004). For example, d eclines in wild populations of the common frog ( Rana temporaria ) in England have been attributed to a strain of Frog virus 3 (FV3) that may have been introduced by
28 the movement of infected animals from North America (Hyatt et al. 2000, Teacher et al. 2010). The recent emergence of a novel ranavirus in Europe, the common midwife toad virus (CMTV), has been responsible for notable amphibian epizootics in Spain since 2007 (Balseiro et al. 2009, 2010, Price et al. 2014) and the Netherlands since 2010 (Kik et al. 2011, van Beurden et al. 2014). CMTV has also been detected in invasive populations of bullfrogs ( Lithobates catesbeianus ) in Belgium (Sharifian Fard et al. 2011). Ranaviruses including FV3 and CMTV /ADRV are a growing threat to the global ranaculture and aquaculture industries. The cultivation of North American pig frog ( Lithobates g r y lio ) for food in China began in the 1980s and since 1995 an FV3 like virus has negatively impacted culture efforts (Zhang et al. 2001). Similarly, the cultivation of tiger frogs ( Hoplobatrachus tigerinus ) in China (He et al. 2002) and Thailand (Kanchanakhan et al. 2002) have been negatively impacted by rel ated ranaviruses. The North America bullfrog ( Lithobates catesbeianus ) is perhaps the most widely cultured amphibian in the world and not surprisingly FV3 epizootics have been reported at ranaculture facilities in the state of Georgia, USA (Majji et al. 20 06, Miller et al. 2007), Brazil (Mazzoni et al. 2009), and Korea (Kim et al. 2011). A FV3 like agent was responsible for an epizootic in marbled sleeper goby ( Oxyeleotris marmoratus ) farm in Thailand (Prasankok et al. 2005). Repeated outbreaks have been re ported on North American aquaculture facilities rearing sturgeon for food and restoration efforts (Waltzek et al. 2014). The culture of Chinese softshell turtle ( Pelodiscus sinesis ) has been impeded by a FV3 like virus (Huang et al. 2009). Since 2010, a le thal CMTV like virus has spread to most farms in China rearing the critically endangered Chinese giant salamander ( Andrias davidianus ) for food and medicinal purposes (Geng et al. 2011, Chen et al. 2013). The recent global detection of closely related FV3 and CMTV strains is strong evidence of their anthropogenic spread via the
29 live animal trade for human consumption, pets, bait, laboratory research, zoological exhibition, and biocontrol (Picco et al 2010). Despite a number of ranavirus epizootics at ranacu lture and aquaculture facilities in the United States (Majji et al. 2006, Miller et al. 2007, Waltzek et al. 2014), no genomic sequencing efforts have been conducted to elucidate molecular epidemiological patterns. In this investigation, we sequenced the complete genomes of two American bullfrog ranavirus isolates from separate epizootics at the same ranaculture facility and then performed phylogenomic analyses to compar e them to 15 other ranaviruses available within GenBank database
30 CHAPTER 3 METHODS I solate Collection Two ranaviral isolates were obtained from separate American bullfrog ( Lithobates catesbei a nus ) epizootics in 2006 (RI 1 ) (Miller et al. 2007) and 1998 (RI 2) (Maijji et al. 2006) at the same aquaculture (Ge orgia, USA) facility. RI 2 was i solated from visceral tissue from a moribund bullfrog tadpole. RI 1 was isolated from visceral tissue in a bullfrog that had recently underg one metamorphosis. Isolate RI 1was provided by co author MG and isolate R1 2 by co author GC (Table 3 1; Figure 3 1) Cell Culture, Virus Purification, and DNA Extraction The isolates were propagated in epithelioma papulosum cells (EPC) (Figure 3 2) grown to confluency at 20C in MEM with 10% FBS, 50 IU penicillin ml 1 1 and 2 mM L glutamine in four 175 cm 2 flasks The two isolates were grown i n separate months to reduce the risk of cross contamination Following a 60 min virus adsorption period, 50 mL of MEM with 2% FBS was added and the cells held at 23C until complete cytopathic effect was o bserved. Cells were harvested by using a cell scraper to remove any remaining cells from flasks and this supernatant was frozen at 80C. Virion purification was performed as described by Maijji et al. (2006) with minor modifications. Briefly, viral cultur es (approximately 200 mL per isolate) were thawed three times, to release the virus from the cells. The supernatants were centrifuged at 5,509 x g at 4C for 20 min using a Beckman JA 14 fixed angle rotor. Virus particles were then pelleted from the clarif ied supernatant by ultracentrifugation at 100,000 x g at 4C for 60 min in a Beckman Type 50.2 Ti rotor. The resulting pellet was resuspended in 3 mL resuspension buffer ( RSB; 10 mM Tris HCl, pH 7.6, 10 mM KCl, 1.5 mM MgCl 2 ). To remove adventi ti ously associated cellular DNA, concentrated virions (3 mL) were treated with DNAse
31 1 Sigma) in the presence of 10 mM MgCl 2 for 60 min at 37 o C. After 1 h the reaction was stopped by adding EDTA to a final concentration of 50 mM, and the virions were layered over a 20% (w/w) sucrose RSB cushion and centrifuged at 150 000 g for 90 min at 4C in in a Beckman Type 50.2 Ti rotor. The overlay was removed by aspiration and the pelleted virions were resuspended in RSB prior to extraction using a Qiagen DN e asy extraction kit as specified by the manufacturer. The resulting DNA concentration was measured by fluorometry using a Qubit dsDNA BR Assay Kit. Library Preparation, Next Generation Sequencing, de novo Assembly A dual indexed viral DNA library was prepared using a TruSeq Dual Index HT DNA PCR free Library Preparation Kit (Illumina) as specified by the manufacturer. The quality of the libraries was assessed by submitting samples for bioanalysis and qPCR at the Interdisciplinary Center for Biotechnol ogy Research (ICBR) at the University of Florida, USA. Sequencing was performed using v3 chemistry on the MiSeq platform (Illumina). De novo assembly of paired end reads was performed in SPAdes 3.5.0 genome assembly algorithm (Bankevich et al., 2012) using default settings. The quality of the assembly was verified by mapping reads against the final genome consensus using Bowtie 2 2.1.0 (Langmead and Salzberg, 2012) and visualized in Tablet 18.104.22.168 (Milne et al. 2010). Genom e Annotation BLASTp Analysis, and Alignment The genomes of the two bullfrog isolates were annotated using the Genome Annotation Transfer Utility (GATU) with Frog virus 3 (FV3; Genbank NC_005946) as the reference genome. Additional putative open reading frames (ORFs) were identified us ing Gene M arkS (Besemer et al. 2001) and the functions were predicted based on BLAST P searches against the Gen B ank non redundan t protein sequence database provided b y the National Center for Biotechnology Information (NCBI) An additional 15 ranavirus genom es were obtained from
32 GenBank (Table 3 1 ; Figure 3 1 ). The GATU software wa s used to identify 52 conserved genes from all 17 ranavirus genomes used in the subsequent phylogenomic analyses (Jancovich 2010). The nucleotide sequence alignment of i ndividual genes were obtained based on the back translation of amino acid alignments performed in TranslatorX (Abascal et al 2010) using the uncleaned Multiple Alignment using Fast Fourier Transformation (MAFFT) (Katoh et al. 2002) option. The 52 individual gene al ignments were then concatenated into the final dataset in Geneious v.7 (Kearse et al. 2012). Phylogenomic Analyses The final aligned dataset was subjected to a suite of analyses prior to generating phylogenetic hypotheses in order to determine the appropri ate evolutiona r y model(s) by gene and codon position. Analyses were also conducted to determine if genes within the dataset displayed 1) phylogenetic signal 2) significant substitution saturation, and 3) recombination. The best substitution model for each codon position of a gene was determined using PartitionFinder with default parameters (Lanfear et al. 2012). A second analysis to determine the best substitution model for each gene was performed in JModelTest using the AIC, AICc, and BIC options (Darriba et al. 2012; Guindon and Gascuel 2003). TreePuzzle version 5.2 was used to determine the phylogenetically informative genes using the likelihood mapping method (Schmidt et al. 2002). To determine whether any genes contained significant substitution satura tion the DAMBE5 software package was utilized with default settings (Xia 2013). The dataset was subjected to a suite of recombination software s (RDP, GENECONV, Boot S can, Max C hi, Chimaera, SiScan, PhylPro, LARD, 3Seq) within the RDP4Beta 4.67 package (Marti n et al. 2015). A recombination event was reported if f our or more of the nine implemented softwares detected significant recombination. The significant recombination sites
33 were then removed from the final concatenated alig nment in RDP4Beta 4.67 prior to p hylogenetic analyses. A Maximum Likelihood phylogenetic analysis was performed on the final dataset in IQ TREE wi th 1,000 bootstraps (Nguyen et al. 2015). A Bayesian phylogenetic analysis was performed in MrBayes v. 3.2 (Ronquist et al. 2012) with default priors for topology (uniform) and branch lengths (Exp and 10). The Markov chain was run for a maximum of 1.1 million generations. Four independent analyses were conducted, each with 1 cold and 3 heated chains with the default heating parameter (temperature = 0.2). Every 1,000 generations were sampled and the first 25% of MCMC samples discarded as burn in.
34 Table 3 1 Virus isolate ID, host common names, host scientific name, year of isolation, reference, a ccession number and genome size of 17 ranaviral isolates used for phylogenetic analysis Isolate ID Common Name Scientific Name Year of Isolation Reference Accession No. Genome size (bps) CMTVM:MAC_2008_Spain_Balseiro Alpine Newt Mesotriton alpestris cyreni 2008 Mavian et al. (2012) JQ231222 106,878 RC15027 :RC_1998_IDGA_Chinchar a Bullfrog Lithobates catesbeianus 1998 Majji et al. (2006) This study 106,890 RC:15021 :RC_2006_GA_Gray b Bullfrog Lithobates catesbeianus 2006 Miller et al. (2007) This study 104,968 SGIV:ET_1998_Singapore_Song Brown Spotted Grouper Epinephelus tauvina 1998 Song et al. (2004 ) NC_006549 140,131 ADRV:AD_2010_China_Jiang Chinese Giant Salamander Andrias davidianus 2010 Jiang et al. (2011) KF033124 106,719 CMTVVB:PKE_2013_Netherlands_VanBeurden Edible Frog Pelophylax esculentus 2013 van Beurden et al. (2014) KP056312 107,772 TORV:TK_1996_Germany_Marschang Egyptian Tortoise Testudo kleinmann 1996 Stohr et al. (2015) KP266743 103,876 GGRV: UF_2001_Germany_Marschang Leaf tailed Gecko Uroplatus fimbriatus 2001 Stohr et al. (2015) KP266742 103,681 FV3:RP_1963_WIMN_Tan Leopard Frog Lithobates pipiens 1963 Tan et al. (2004) NC_005946 105,903 RGV:RG_China_1995_Lei Pig Frog Lithobates grylio 1995 Lei et al. (2012) JQ654586 105,791 EHNV:PF_1984_Australia_Jancovich Redfin Perch Perca fluviatilis 1984 Jancovich et al. (2010) NC_028461 127,011 ESV:SG_1989_Germany_Mavian Sheatfish Silurus glanis 1989 Mavian et al. (2012) NC_017940 127,732 STIV:TS_China_1997_Chen Soft shelled Turtle Trionyx sinesensis 1997 Huang et al. (2009) EU627010 105,890 ATV:AT_1995_AZ_Jancovich Sonoran Tiger Salamander Ambystoma tigrinum stebbinsi 1995 Jancovich et al. (2003) NC_005832 106,332 SSME:AM_1998_ME_Morrison Spotted Salamander Ambystoma maculatum 1998 Morrison et al. (2014) KJ175144 105,070 TFV:RTR_1999_China_He Tiger Frog Hoplobatrachus tigerinus 1999 He et al. (2002) AF389451 105,057 GIV:EA_2000_Taiwan_Tsai Yellow Grouper Epinephelus awoara 2000 Tsai et al. (2005) AY666015 139,793 a D enoted as ranaculture isolate (RI 1) b D enoted as ranaculture isolate ( RI 2)
35 Figure 3 1 Map of sample isolation locations for 17 ranaviral isolates shown in Table 3 1. Call outs show the virus abbreviation and the scientific name of the host; d ark blue call outs represent genomes obtained from NCBI GenBank; purple call outs represent isolates that we sequenced the full genome; ADRV = Andrias davidianus ranavirus ; CMTV = common midwife toad viru s ; ECV = European catfish virus ; FV3 = F rog virus 3 ; GGRV = German gecko ranavirus ; RGV = Rana grylio virus ; SSME = spotted salamander Maine ; STIV = soft shelled turtle iridovirus ; T o RV = tortoise ranavirus ; TFV = tiger frog virus
36 Figure 3 2 Flow chart of cell culture and phylogenetic methods used in this study Bayesian tree generated in MrBayes Maximum Liklihood tree generated in IQ Tree RDP4 run t o evaluate recombination TreePuzzle run for phylogenetic signal DAMBE run to evaluate substitution saturation PartitionFinder and JModel Test run to find best model for each gene 52 gene alignments concatenated in Geneious Individual genes were aligned in TranslatorX using MAFFT 52 individual genes were aligned individually in GATU Sequence data assembled de novo using SPAdes Purified viral DNA sequenced via Illumina MiSeq platform Isolates purified via sucrose cushion 2 Ranavirus isolates grown in cell culture on Epithelioma Papulosum Cyprini (EPC) cells
37 CHAPTER 4 RESULTS Genome Annotation, BLASTp Analysis, and Alignment De novo assembly of 4,3 30,026 paired end reads for RI 1 generated the full viral genome in a single contiguous sequence of 104,968 bps encoding a 110 putative o pen reading frames ( ORFs ) ranging from 17 1,234 amino acids and a G+C content of 56.08%. A total of 2 903,694 paired end reads (67.06%) mapped back to the genome consensus sequence at an average coverage of 7,494 per nucleotide. The BLAST P searches revealed the majority of ORFs with highest identity (typically 97% or greater) to FV3 or FV3 like viruses (e.g., RGV, STIV)(Table 4 1 ) Best hits from 29 ORFs displayed greatest identity with members of the CMTV or CMTV like viruses (e.g., ADRV, CGSI REV, THIV, TRV). De novo assembly of 4,3 88,046 paired end reads for RI 2 generated the full viral genome in a single contiguous sequence of 106,890 bps encoding 1 08 putative ORFs ranging from 16 1,294 amino acids and a G+C content of 55.5%. A total of 2,419,906 paired end reads (55.15%) mapped back to the genome sequence at an average coverage of 5,883 per nucleotide. The BLAST P searches revealed the majority of OR Fs with highest identity (typically 97% or greater) to CMTV or CMTV like viruses (e.g., ADRV, CGSIV, REV, THIV, TRV)( Table 4 2 ). Best hits from 6 ORFs displayed greatest identity with FV3 and 2 ORF with ESV. Phylogenetic Analysis PartitionFinder found the most common evolutionary model to be GTR+G and TVM+I+G for the first codon position, TVM+I+G for the second codon position, and TIM+G for the third codon position (Table 4 3 Table 4 4 ). The best evolutionary model from JModelTest was TIM1+I and TIM1+I+G according to the AIC method, TIM1+I+G for the AICc method, and TPM1+I+ G for the BIC method (Table 4 3, Table 4 4 ). Based on these results and
38 the availability of models implemented in phylogenetic software, the GTR+I+G evolutionary model was run in the Maximum Likelihood and Bayesian phylogenetic analyses. All genes showed little substitution saturation for the first and second codon position as well as when analyzed for the third codon position (Table 4 3). F orty eight ORFs showed significant phylogenetic signal (<34%)(Table 4 3 ). ORFs 4R (38.9%), 33R (38%), 75L (37.5%), and 76R (35.7%) were not excluded from the phylogenetic analyses because they were close to the arbitrary cut off value. ORFs 75L and 76R were within regions of re combination (see below) The recombination analysis detected 19 total significant recombination events in the concatenated conserved gene alignment (Table 4 5) Eight of t hose events occurred in the RI 1 recombinant involving a total of 16 genes (4 1 4 5 ) In the RI 1 recombinant ORFs within the recombination regions inclu ded: putative myristylated membrane protein (2L ), Putative tyrosine kinase (27R ), n eurofilament triplet H1 like protein (32R ), Putative interleukin 1 beta convertase precursor (64R ), r ibonucleoside diphosphate reductase beta subunit like protein (67L ), putative LITAF/PIG7 possible membrane associated motif in LPS induced tumor necrosis factor alpha factor (75L ), p utative ATPase dependent protease (79R ), ribonuclease III (80L ) and ORFs of unknown function ( 10R, 11R, 12L, 24R, 72L, 74L, 76R 89R ) After removal of the significant recombination sites, the final aligned concatenated dataset (5 2 genes for 17 taxa) contained 68,136 nucleotide characters including gaps. The Bayesi an and M aximum L ikelihood analys es generated identical trees that also match recently published ranavirus topologies (Jancovich et al. 2015). RI 1 grouped in the FV3 clade as the sister group to FV3 and SSME with high posterior probabilit y and bootstrap su pport (Figures 4 2, 4 3). RI 2 grouped within the CMTV clade as the sister species to Andrias davidianus ranavirus, with high posterior probability and bootstrap support (Figures 4 2, 4 3 ).
39 Table 4 1 Predicted open reading frames for the 2006 ranav irus isolate ( RI 1 ) genome ORFs highlighted in gray were within recombination events from the RDP 4 analysis ORF Position (nt range) Product size (aa) Predicted function and conserved domain or signature Best BLAST hit a CMTV ortholog b FV3 ortholog c ORF %ID Accession no. ORF %ID ORF %ID 1R 262 1,032 257 Putative replicating factor STIV1R 99 ACF42220.1 1R 99.219 1R 99.219 2L 1,748 2,803 352 Putative myristylated membrane protein CGSI72R 99 AGK44996.1 2L 100 2L 99.237 2.5 L 2,841 3,680 280 RGV3L 100 AFG73045.1 3L 99.219 10R 43.75 3R 3,610 4,926 439 Orf229L protein like protein FV33R 100 YP_031581.1 4R 96.04 3R 100 4R 4,967 5,149 61 FV34R 100 YP_031582.1 5R 98.33 4R 100 5R 104,336 104,968 211 Orf250 like protein STIV104R 98 ACF42322.1 6R 51.852 5R 49.735 7R 6,122 6,508 129 FV37R 99 YP_031585.1 46R 60 7R 99.219 7.5L 6,092 6,520 143 STIV9L 96 ACF42228.1 7L 96.479 8R 6,599 10,480 1,294 DNA dependent RNA polymerase II largest sub unit FV38R 99 AHM26087.1 61R 40.625 8R 99.768 9L 10,880 13,726 949 Putative NTPase FV39L 99 YP_031587.1 9L 99.051 9L 99.367 10R 13,742 14,155 138 ADRV11R 100 AGV20542.1 10R 98.54 10R 95.62 10.5R 14,546 14,764 73 CGSI13L 100 AHA80857.1 11L 100 62L 60 11R 101,914 102,126 71 CMTV99L 100 AFA45004.1 99L 100 11R 97.143 12L 100,955 101,848 298 ADRV98R 100 AGV20629.1 54L 45.833 12L 97.306 12.5L 32,921 33,127 69 CMTV106R 100 AHA80951.1 97R 87.5 35L 83.333 13R 33,205 33,411 69 FV313R 97 YP_031591.1 2L 42.857 13R 97.059 14R 33,426 33,785 120 FV314R 100 YP_031592.1 95L 97.458 14R 100 15R 33,881 34,870 330 AAA ATPase FV315R 98 YP_031593.1 94L 94.833 15R 96.96 16R 35,150 35,977 276 Putative integrase like protein FV316R 99 YP_031594.1 93L 97.368 16R 99.624 16.5L 35,234 36,181 316 GGRV13L 99 AJR29171.1 92R 99.048 22R 47.059 17L 36,218 37,726 503 ADRV93R 99 AGV20624.1 90R 99.004 17L 99.402 18L 37,763 37,999 79 ADRV92R 100 AGV20623.1 89R 97.436 18L 96.154 19R 38,052 40,652 867 Uncharacterized conserved protein FV319R 99 AIX94586.1 88L 95.035 19R 94.804 20R 40,700 41,146 149 STIV23R 99 ACF42242.1 87L 97.973 20R 94.595 21L 41,369 42,028 220 Orf56L protein like protein FV321L 100 AHM26100.1 86R 99.087 21L 98.63 22R 42,158 45,079 974 Putative D5 family NTPase/ATPase FV322R 99 AHM26101.1 85L 99.282 22R 99.692 23R 45,457 46,605 383 FV323R 98 AIX94588.1 84L 97.12 23R 97.382 24R 47,015 48,085 357 CGSI90L 99 AHA80935.1 83L 99.157 24R 97.753
40 Table 4 1 Continued ORF Position (nt range) Product size (aa) Predicted function and conserved domain or signature Best BLAST hit a CMTV ortholog b FV3 ortholog c ORF %ID Accession no. ORF %ID ORF %ID 25R 48,279 49,067 263 P31K protein THIV62L 99 AJR29145.1 82L 98.723 25R 99.574 26R 49,134 49,364 77 Truncated putative e1F 2alpha like protein FV326R 100 YP_031604.1 81L 82.222 26R 100 27R 49,897 52,809 971 Putative tyrosine kinase FV327R 99 YP_031605.1 80L 97.643 27R 99.485 28R 52,858 53,346 163 FV328R 99 YP_031606.1 79L 97.531 28R 99.383 29L 53,525 53,821 99 FV329L 100 YP_031607.1 16L 45.455 29L 100 30R 53,772 53,903 44 ECV91R 87 YP_006347683.1 93L 71.429 43R 83.333 31R 54,238 54,657 140 FV331R 100 YP_031609.1 77L 95.683 31R 100 32R 54,707 56,686 660 Neurofilament triplet H1 like protein STIV35R 95 ACF42253.1 76L 86.97 32R 79.464 33R 56,769 56,960 64 FV333R 100 YP_031611.1 28L 100 33R 100 34R 57,104 57,424 107 L protein like protein FV334R 100 YP_031612.1 74L 95.283 34R 100 35L 57,516 57,977 154 FV335L 99 AHM26114.1 73R 88.312 35L 98.039 36L 57,949 58,629 227 FV336L 70 YP_031614.1 71R 88.506 36L 90.909 37R 59,025 59,660 212 Putative NIF/NLI interacting factor FV337R 100 AHM26116.1 70L 98.039 37R 100 38R 59,801 61,498 566 Ribonucleoside diphosphate reductase alpha subunit barrel domain FV338R 99 YP_031616.1 69L 98.23 38R 99.646 39R 61,604 61,954 117 Putative hydrolase of the metallo beta lactamase superfamily FV339R 100 YP_031617.1 68L 93.103 39R 100 40R 62,042 62,590 183 FV340R 98 AHM26119.1 32R 35.714 40R 97.802 40.5R 62,776 63,066 97 CMTV66L 96 AIW68559.1 66L 95.556 27R 47.368 41R 62,972 66,469 1,166 Orf2 like protein FV341R 100 AHM26120.1 65L 98.369 41R 99.914 42L 67,056 67,313 86 FV342L 99 YP_031620.1 64R 98.824 42L 98.824 43R 66,774 66,905 44 23L 62.5 83R 62.5 44R 67,865 68,050 62 FV344R 100 YP_031622.1 44R 100 45L 68,326 68,736 137 Orf88 like protein FV345L 99 YP_031623.1 63R 99.265 45L 99.265 46L 68,790 69,170 127 Neurofilament triplet H1 like protein RGV47L 86 AFG73089.1 76L 68 32R 60.87 47L 69,296 69,712 139 FV347L 100 YP_031625.1 61R 99.275 47L 100 48L 69,715 69,966 84 FV348L 100 YP_031626.1 60R 93.976 48L 100 49L 70,075 70,824 250 Orf58 like protein FV349/50L 99 AHM26127.1 59R 97.177 49L 98.795
41 Table 4 1 Continued ORF Position (nt range) Product size (aa) Predicted function and conserved domain or signature Best BLAST hit a CMTV ortholog b FV3 ortholog c ORF %ID Accession no. ORF %ID ORF %ID 50L 71,402 71,872 157 FV350L 97 YP_031628.1 59R 92 50L 99 51R 71,952 73,637 562 FV351R 99 YP_031629.1 58L 97.861 51R 99.822 52L 73,894 74,961 356 Putative 3 beta hydroxy delta 5 C27 steroid oxidoreductase like protein FV352L 99 YP_031630.1 57R 97.746 52L 99.718 53R 75,300 76,868 523 Orf20 like protein FV353R 99 YP_031631.1 56L 97.701 53R 99.808 54L 77,093 77,323 77 Putative nuclear calmodulin binding protein FV354L 100 YP_031632.1 40R 46.154 54L 100 55L 77,361 78,656 432 Helicase like protein FV355L 99 YP_031633.1 54R 97.448 55L 99.536 55R 77,505 78,644 380 40 kDa protein FV355R 99 YP_031634.1 54L 96.042 55R 99.736 55.5L 78,664 78,813 50 Hypothetical protein STIV58L 100 ACF42276.1 53R 95.918 24R 58.333 56R 78,744 79,181 146 FV356R 100 YP_031635.1 81L 42.857 57R 99.799 57R 7 9,295 80,791 499 Putative phosphotransferase FV357R 99 YP_031636.1 51L 98.795 58R 98.734 57.5R 80,874 80,975 34 CMTV50L 100 AIW68542.1 50L 100 53R 30.303 58R 81,116 81,988 291 CMTV49L 97 AIW68541.1 49L 97.071 58R 98.734 58.5R 81,243 81,797 185 CGSI27R 100 AGK44973.1 49L 68.75 53R 30.303 59L 83,416 84,474 353 FV359L 99 AIX94616.1 48R 95.739 59L 97.727 60R 84,636 87,677 1,014 DNA polymerase like protein FV360R 99 AHM26138.1 47L 99.013 60R 99.803 61L 87,686 87,868 61 FV361L 100 YP_031640.1 27R 44.444 61L 100 62L 88,301 91,966 1,222 DNA dependent RNA polymerase II second largest subunit domain 6,7,3,2 beta subunit FV362L 99 YP_031641.1 46R 99.314 62L 99.829 62.5R 91,692 92,228 179 CMTV45L 99 AIW68537.1 45L 99.438 22R 47.368 63R 92,345 92,839 165 Putative dUTPase like protein FV363R 100 YP_031642.1 44L 97.561 63R 100 64R 92,949 93,236 96 Putative interleukin 1 beta convertase precursor FV364R 99 YP_031643.1 43L 90.526 64R 98.947 65L 57,896 58,168 91 STIV40R 92 ACF42258.1 73R 60 35L 60 66L 93,495 93,584 30 CMTV41R 100 AFA44946.1 41R 89.474 66L 78.947 67L 93,639 94,802 388 Ribonucleoside diphosphate reductase beta subunit like protein CMTV40R 99 AFA44945.1 40R 98.708 67L 98.191 68R 94,838 95,107 90 ADRV41L 100 AGV20572.1 40R 28 68R 86.667
42 Table 4 1 Continued ORF Position (nt range) Product size (aa) Predicted function and conserved domain or signature Best BLAST hit a CMTV ortholog b FV3 ortholog c ORF %ID Accession no. ORF %ID ORF %ID 69R 95,239 95,505 89 FV369R 100 YP_031648.1 38L 98.864 69R 100 70R 95,523 95,897 125 FV370R 99 YP_031649.1 37L 97.581 70R 99.194 71R 95,937 96,170 78 FV371R 99 YP_031650.1 36L 95.312 71R 98.438 71.5R 96,455 96,937 161 STIV77R 99 ACF42295.1 35L 97.5 59L 28.205 72L 96,227 96,943 239 FV372L 99 YP_031651.1 35R 96.639 72L 98.739 73L 97,335 98,309 325 Putative NTPase/helicase like protein ADRV35R 98 AGV20566.1 2L 43.75 73L 97.531 74L 98,528 99,709 394 ADRV34R 100 AGV20565.1 33R 97.201 74L 84.987 75L 99,766 100,020 85 putative LITAF/PIG7 possible membrane associated motif in LPS induced tumor necrosis factor alpha factor FV375L 100 YP_031654.1 32R 100 75L 100 76R 100,083 100,304 74 CGSI43R 97 AGK44982.1 31L 97.26 76R 98.63 77L 100,301 100,648 116 LCDV1 orf2 like protein FV377L 99 YP_031656.1 30R 99.13 77L 99.13 78L 32,067 32,441 125 TRV26R 100 AJR29109.1 29R 98.387 78L 99.065 79R 30,306 31,982 559 Putative ATPase dependent protease TRV25L 99 AJR29108.1 28L 95.629 79R 92.028 80L 28,566 29,681 372 Ribonuclease III GGRV58L 99 AJR29216.1 27R 99.461 80L 99.461 81R 28,232 28,510 93 Transcription elongation factor SII CMTV26L 100 AIW68517.1 26L 100 81R 98.913 82R 27,630 28,103 158 Immediate early protein ICP 18 FV382R 100 YP_031661.1 25L 92.994 82R 100 83R 26,536 27,180 215 Cytosine DNA methyltransferase FV383R 99 YP_031662.1 23L 99.065 83R 99.533 84R 25,394 26,131 246 LCDV1 like proliferating cell nuclear antigen FV384R 99 YP_031663.1 22L 98.367 84R 99.592 85R 24,732 25,319 196 Putative deoxynucleoside kinase FV385R 100 YP_031664.1 21L 97.436 85R 100 86L 24,157 24,342 62 FV386L 100 YP_031665.1 20R 76.056 86L 100 87L 21,951 23,804 618 99 ADO14141.1 19R 100 87L 100 88R 21,466 21,918 151 Putative Evrl air augmenter of liver regeneration FV388R 100 YP_031667.1 18L 98.667 88R 100 89R 20,274 21,398 375 FV389R 97 AIX94641.1 17L 100 89R 100 90R 18,790 20,181 464 Major capsid protein REV 99 ACO90020.1 16L 98.488 90R 98.056
43 Table 4 1 Continued ORF Position (nt range) Product size (aa) Predicted function and conserved domain or signature Best BLAST hit a CMTV ortholog b FV3 ortholog c ORF %ID Accession no. ORF %ID ORF %ID 91R 17,479 18,666 396 Immediate early protein ICP 46 FV391R 99 YP_031670.1 15L 97.468 91R 99.241 92R 16,913 17,176 88 ADRV15L 100 AGV20546.1 93L 55.556 92R 82.759 93L 16,556 16,723 56 ADRV14R 100 AGV20545.1 65L 37.5 93L 96.364 94L 15,979 16,446 156 P8.141C like protein FV394L 100 YP_031673.1 13R 98.065 94L 100 95R 14,795 15,886 364 Putative DNA repair protein RAD2 STIV 99 ACF42318.1 12L 97.802 95R 99.449 96R 102,607 103,293 229 TRV74R 98 AJR29157.1 101R 96.491 96R 97.309 96.5L 102,365 102,415 17 CMTV100L 88 AIW68593.1 100L 87.5 73L 100 97R 103,359 103,772 138 MCL 1 region STIV103R 100 ACF42321.1 102R 94.444 97R 99.27 98R 104,336 104,968 222 STIV104R 98 ACF42322.1 6R 51.031 5R 49.479 a S ignificant hits using NCBI BLASTP against b BLASTP against van Beurden et al. (2014) c BLASTP against Tan et al. (2004) Abbreviations: nt, nucleotides; aa, amino acids; ID, identity ADRV= Andrias davidianus ranavirus ; CMTV= common midwife toad virus ; CGSI= Chin ese giant salamander iridovirus ; ECV= European catfish virus ; FV3= frog virus 3 ; GGRV= German gecko ranavirus ; REV= Rana esculenta virus ; RGV= Rana grylio virus ; STIV= soft shelled turtle iridovirus ; TRV= tortoise ran a virus
44 Table 4 2 Predicted open reading frames for the 1998 ranavirus isolate ( RI 2 ) genome ORF Position (nt range) Product size (aa) Predicted function and conserved domain or signature Best BLAST hit a CMTV ortholog b FV3 ortholog c ORF %ID Accession no. ORF %ID ORF %ID 1R 105,942 106,712 256 Putative replication factor ADRV1R 99 AGV20532.1 1R 99.219 1R 98.438 2L 104,146 105,162 338 Putative myristylated membrane protein CGSI72R 96 AGK44996.1 2L 100 2L 89.349 3L 103,269 104,108 279 CGSI71R 99 AGK44995.1 3L 98.566 10R 43.75 4R 102,024 103,238 404 TRV4R 99 AJR29087.1 4R 98.02 3R 95.05 5R 101,802 101,984 60 CMTV5R 100 AIW68496.1 5R 100 4R 98.333 6R 100,708 101,368 221 CGSI6R 99 AHA80850.1 26L 43.75 6R 97.222 6.5R 100,513 100,731 72 ADRV7R 100 AGV20538.1 6R 94.57 5R 84.653 7R 99,336 99,722 128 THR6L 99 AJR29089.1 7L 96.479 7L 99,324 99,752 142 ADRV8R 100 AGV20539.1 46R 72.727 7R 95.312 8R 95,360 99,244 1,294 DNA dependent RNA polymerase largest subunit ADRV9R 99 AGV20540.1 61R 40.625 8R 98.608 9L 92,165 95,011 948 Helicase CGSI64R 99 AGK44993.1 9L 99.578 9L 98.629 10R 91,736 92,149 137 ADRV11R 100 AGV20542.1 10R 98.54 10R 95.62 12L 90,005 91,096 363 Putative DNA repair protein RGV 100 AAY43134.1 12L 98.352 95R 98.898 13R 89,912 89,445 155 ADRV13R 100 AGV20544.1 13R 98.71 94L 98.065 14.5L 88,715 88,978 87 ADRV15L 100 AGV20546.1 93L 55.556 92R 82.759 14.75R 89,168 89,335 55 ADRV14R 100 AGV20545.1 65L 37.5 93L 96.364 15L 87,225 88,412 395 Immediate early protein ICP 46 CGSI58R 100 AGK44991.1 15L 98.228 91R 97.468 16L 85,710 87,101 463 Major capsid protein REV 100 ACO90020.1 16L 99.568 90R 97.84 17L 84,412 85,617 401 ADRV18L 96 AHA42286.1 17L 100 89R 97.297 18L 83,892 84,344 150 Thiol oxidoreductase ADRV19L 100 AGV20550.1 18L 99.333 88R 98 19R 82,042 83,859 605 ADRV20R 99 AGV20551.1 19R 99.275 87L 98.911 20R 81,504 81,689 61 SSME86L 98 AHM26162.1 20R 83.099 86L 88.525 21L 80,466 81,053 195 Thymidine kinase CGSI52R 99 AGK44988.1 21L 98.974 85R 96.923 22L 79,654 80,391 245 Proliferating cell nuclear antigen CGSI51R 100 AGK44987.1 22L 99.592 84R 98.367 23L 78,608 79,252 241 Cytosine DNA methyltransferase CGSI50R 99 AGK44986.1 23L 99.533 83R 98.131 24L 77,954 78,241 95 Thymidylate synthase ADRV25L 100 AGV20556.1 24L 98.947 60R 58.333 25L 77,184 77,657 157 Putative immediate early protein TRV22L 97 AJR29105.1 25L 96.178 82R 89.809 26L 76,777 77,055 92 Transcription elongation factor SII CGSI48R 100 AGK44984.1 26L 98.913 81R 97.826
45 Table 4 2 Continued ORF Position (nt range) Product size (aa) Predicted function and conserved domain or signature Best BLAST hit a CMTV ortholog b FV3 ortholog c ORF %ID Accession no. ORF %ID ORF %ID 27R 75,600 76,718 372 Ribonuclease III ADRV28R 99 AGV20559.1 27R 98.656 80L 98.656 28L 73,262 75,013 583 TRV25L 93 AJR29108.1 28L 89.615 79R 89.112 29R 72,803 73,177 124 TRV26R 100 AJR29109.1 29R 98.387 78L 99.065 30R 71,334 71,681 115 FV377L 100 YP_031656.1 30R 100 77L 100 31L 71,116 71,337 73 CGSI43R 99 AGK44982.1 31L 98.63 76R 97.26 32R 70,799 71,053 84 Lipopolysaccharide induced TNF alpha factor (LITAF) like protein ADRV33R 100 AGV20564.1 32R 98.81 75L 98.81 33R 69,561 70,742 393 ADRV34R 100 AGV20565.1 33R 97.201 74L 84.987 35R 67,129 67,845 238 ADRV36R 99 AGV20567.1 35L 99.375 82R 24 35L 67,357 67,839 160 TRV30L 100 AJR29113.1 35R 96.218 72L 95.798 36L 66,839 67,072 77 CGSI38R 100 AGK44980.1 36L 98.438 71R 95.312 37L 66,425 66,799 124 CMTV37L 99 AFA44942.1 37L 98.387 70R 97.581 38L 66,141 66,407 88 ADRV39L 99 AGV20570.1 38L 97.727 69R 98.864 39R 65,749 66,027 92 ADRV40R 100 AGV20571.1 39R 93.056 74L 66.667 40R 64,541 65,704 387 Ribonucleotide reductase small subunit CMTV40R 99 AFA44945.1 40R 98.45 67L 97.933 41R 64,397 64,486 29 CMTV41R 100 AFA44946.1 41R 89.474 66L 78.947 42R 29,398 29,469 23 51L 83.333 57R 83.333 43L 63,850 64,137 95 CARD like caspase CGSI33R 99 AGK44977.1 43L 95.789 64R 93.684 44L 63,261 63,755 164 dUTPase CGSI32R 100 AGK44976.1 44L 100 63R 97.561 45L 62,607 63,143 178 ADRV45L 100 AGV20576.1 45L 99.438 22R 47.368 46R 59,216 62,881 1,221 DNA dependent RNA polymerase b subunit ADRV46R 99 AGV20577.1 46R 99.345 62L 99.057 47L 55,550 58,591 1,013 DNA polymerase CGSI29R 100 AGK44974.1 47L 99.309 60R 98.717 48R 54,330 55,388 352 ADRV48R 99 AGV20579.1 48R 96.591 59L 94.602 49L 51,789 51,890 33 CMTV50L 100 AIW68542.1 50L 100 27R 71.429 49.5L 52,192 52,713 173 CGSI27R 100 AGK44973.1 56L 37.5 53R 30.303 50L 51,789 51,890 33 CMTV50L 100 AIW68542.1 50L 100 27R 71.429 51L 50,209 51,705 498 Putative phosphotransferase CGSI26R 99 AGK44972.1 51L 99.398 57R 98.394 52L 49,764 50,168 134 ADRV52L 100 AGV20583.1 52L 99.254 78L 66.667 53R 49,578 49,727 49 ECV70R 100 YP_00634766 2.1 53R 100 24R 58.333 54L 48,419 49,558 379 ADRV55L 99 AGV20586.1 54L 97.889 55R 95.778 54R 48,275 49,570 431 Helicase ADRV54R 99 AGV20585.1 54R 98.376 55L 96.984 55R 48,042 48,362 106 ADRV56R 100 AGV20587.1 55R 98.113 82R 29.167
46 Table 4 2 Continued ORF Position (nt range) Product size (aa) Predicted function and conserved domain or signature Best BLAST hit a CMTV ortholog b FV3 ortholog c ORF %ID Accession no. ORF %ID ORF %ID 56L 46,272 47,840 522 Myristylated membrane protein CGSI21R 99 AGK44970.1 56L 98.851 53R 98.659 57R 44,866 45,936 356 3beta hydroxysteroid dehydrogenase CMTV57R 99 AFA44963.1 57R 98.876 52L 98.596 58L 42,924 44,609 561 TRV43L 99 AJR29126.1 58L 99.287 51R 97.861 59R 41,303 42,844 513 CGSI57L 99 AHA80901.1 59R 98.198 49L 97.571 60R 40,944 41,255 103 TRV45R 99 AJR29128.1 60R 97.087 48L 92.771 61R 40,525 40,941 138 ADRV64R 100 AGV20595.1 61R 99.275 47L 98.551 62R 39,762 40,400 212 Neurofilament triplet H1 like protein ADRV66R 84 AHA42334.1 62R 100 46L 94.915 63R 39,298 39,708 136 ADRV66R 100 AGV20597.1 63R 100 45L 99.265 64R 38,280 39,170 296 TFV46L 98 ABB92307.1 64R 100 42L 74.359 65L 34,320 37,817 1,165 CGSI11R 100 AGK44968.1 65L 98.712 41R 98.541 66L 34,066 34,230 54 CMTV66L 95 AIW68559.1 66L 95.238 13R 35.294 67L 33,123 33,359 78 CMTV67L 97 AIW68560.1 67L 97.436 77L 43.75 68L 32,757 33,083 108 TRV52L 100 AJR29135.1 68L 98.901 39R 93.407 69L 30,952 32,649 565 Ribonucleoside diphosphate reductase large subunit TRV53L 100 AJR29136.1 69L 99.115 38R 98.407 70L 30,178 30,813 211 Putative NIF/NLI interacting factor CGSI7R 100 AGK44965.1 70L 98.995 37R 98.995 71R 29,494 29,784 96 ADRV73R 98 AGV20604.1 71R 90.909 36L 82.759 72R 29,211 29,456 81 ADRV74R 100 AGV20605.1 72R 96.296 36L 93.75 73R 28,658 29,056 132 FV335L 84 AHM26114.1 73R 94.737 35L 92.105 74L 28,325 28,645 106 CGSI4R 100 AGK44963.1 74L 99.057 34R 95.283 75L 27,992 28,183 63 CGSI3R 100 AGK44962.1 28L 100 79R 100 76L 26,101 27,909 602 Neurofilament triplet H1 like protein ADRV79L 90 AGV20610.1 76L 97.436 32R 97.436 77L 25,632 26,051 139 ECV92R 100 YP_00634768 4.1 77L 98.561 31R 97.122 77.5L 25,073 25,123 16 56R 66.667 78L 24,696 24,950 84 CGSI85L 100 AHA80930.1 78L 95.238 95R 44.828 79L 24,071 24,559 162 ADRV82L 100 AHA42350.1 79L 98.148 28R 97.531 80L 21,110 24,022 970 Putative tyrosine kinase ADRV83L 99 AHA42351.1 80L 98.216 27R 97.587 81L 19,850 20,551 233 ElF2a like protein RCVZ 100 AAY86037.1 81L 96.996 26R 82.222 82L 18,744 19,526 260 P31K protein TRV62L 99 AJR29145.1 82L 98.723 25R 99.574 83L 17,453 18,550 365 FV324R 100 AIX94589.1 83L 98.63 24R 97.808
47 Table 4 2 Continued ORF Position (nt range) Product size (aa) Predicted function and conserved domain or signature Best BLAST hit a CMTV ortholog b FV3 ortholog c ORF %ID Accession no. ORF %ID ORF %ID 84L 15,922 17,070 382 FV323R 99 YP_031601.1 84L 99.215 23R 99.476 85L 12,617 15,544 975 Putative D5 family NTPase/ATPase TRV65L 99 AJR29148.1 85L 99.692 22R 98.872 86R 11,828 12,487 219 FV356L 100 YP_031599.1 86R 98.63 21L 100 87L 11,145 11,591 148 FV320R 100 YP_031598.1 87L 96.622 20R 100 88L 8,278 11,097 939 CGSI96L 99 AHA80941.1 88L 96.379 19R 99.295 89R 8,253 8,489 78 ADRV92R 100 AGV20623.1 89R 97.436 18L 96.154 90R 6,708 8,216 502 ADRV93R 99 AGV20624.1 90R 99.402 17L 98.606 91L 6,991 7,497 168 CGSI100L 99 AHA80945.1 91L 98.81 92R 5,724 6,671 315 ADRV94R 100 AGV20625.1 92R 99.048 41R 57.143 93L 5,817 6,467 216 Putative integrase like protein CGSI102L 99 AHA80947.1 93L 97.685 16R 97.222 94L 4,414 5,361 315 Putative A32 like virion packaging ATPase CGSI80R 100 AGK44999.1 94L 99.683 15R 96.894 95L 3,958 4,317 119 TRV72L 100 AJR29155.1 95L 97.479 14R 98.305 96L 3,688 3,792 34 CMTV96L 94 AIW68589.1 48R 100 59L 100 97R 3,453 3,647 64 CGSI106R 100 AHA80951.1 97R 87.5 35L 71.429 98R 3,174 3,341 55 CMTV98R 94 AFA45003.1 98R 72 99L 2,021 2,233 70 CMTV99L 100 AFA45004.1 99L 100 11R 97.143 100L 1,732 1,782 16 CMTV100L 88 AIW68593.1 100L 87.5 73L 100 101R 855 1,541 228 TRV74R 100 AJR29157.1 101R 98.684 96R 95.067 102R 376 789 137 ADRV101R 99 AGV20632.1 102R 93.103 97R 97.794 103R 100,703 101,185 160 ADRV6R 99 AHA42274.1 6R 94.375 5R 80.851 a S i gnificant hits using NCBI BLASTP b BLASTP against van Beurden et al. (2014) c BLASTP against Tan et al. (2004) Abbreviations: nt, nucleotides; aa, amino acids; ID, identity ADRV= Andrias davidianus ranavirus ; CMTV= common midwife toad virus; CGSI= Chin ese giant salamander iridovirus ; ECV= European catfish virus ; FV3= frog virus 3 ; SSME= spotted salamander M aine ; RCVZ= Rana catesbeiana virus Z TRV= tortoise ranavirus
48 Table 4 3 Substitution models, phylogenetic signal and substitution saturation in the 52 gene concatenated gene alignment for 17 ranavirus species Gene Location in alignment PartitionFinder JModelTest Phylogenetic Signal (%) Substitution Saturation Codon 1 Codon 2 Codon 3 AIC AICc BIC Codon 1&2 Codon 3 1R 1 804 TVM+G GTR+I+G K81+G TPM1uf+G TPM1uf+G TPM1uf+G 10.6 Little Little 2L 805 1926 HKY+G TIM+I+G K81uf+G TVM+I+G TVM+I+G TPM2uf+G 10.0 Little Little 2.5L 1927 2799 TVM+G GTR+G TVM+G TIM1+G TIM1+G TPM1uf+G 19.1 Little Little 4R 2800 2991 K81uf+I TVM+G TVM+G TIM1+G TIM1+G TPM1uf+G 38.9 Little Little 7.5L 2992 3945 K81uf+I+G TIM+I+G SYM SYM+I SYM+I TPM1+I 24.0 Little Little 8R 3946 7881 TIM+G TVM+I+G GTR+I+G TIM1+I+G TIM1+I+G TIM1+G 2.7 Little Little 9L 7882 10812 GTR+G TVM+I+G GTR+I+G TIM1+I+G TIM1+I+G TIM1+G 1.1 Little Little 10R 10813 11289 GTR+G TIM+I+G TIM+G TIM1+I TPM1uf+I TPM1+I 9.5 Little Little 11R 11290 11598 GTR+G GTR+G K80 TVMef TVMef TPM1 30.8 Little Little 12L 11599 12570 TVM+G GTR+I+G TIM+G TIM1+I TIM1+I TPM1uf+I 11.4 Little Little 15R 12571 13638 GTR+I+G GTR+I+G GTR+I+G TIM1+I+G TIM1+I+G TPM1+G 23.8 Little Little 16R 13639 14610 TVM+I+G TVM+G TIM+G TVM+G TVM+G TPM1uf+G 12.9 Little Little 16.5R 14611 15582 TVM+I+G TVM+G TIM+G TVM+G TVM+G TPM1uf+G 12.9 Little Little 17L 15583 17595 GTR+G GTR+G TIM+G TIM1+G TIM1+G TIM1+G 6.5 Little Little 19R 17596 21159 TVM+I+G TIM+I+G GTR+G GTR+I+G GTR+I+G TIM1+I+G 7.9 Little Little 21L 21160 21840 GTR+G TVM+I+G GTR+I+G TVM+I TVM+I TPM1+I 17.2 Little Little 22R 21841 24798 GTR+I+G GTR+I+G GTR+I+G TIM1+I TIM1+I TIM1+I 3.2 Little Little 24R 24799 26127 K81uf+I+G TVM+I+G K81+G TPM1uf+I+G TPM1uf+I+G TPM1+I+G 10.2 Little Little 27R 26128 29175 TVM+I+G TVM+G GTR+G TVM+I+G TVM+I+G TPM1uf+G 2.6 Little Little
49 Table 4 3 Continued Gene Location in alignment PartitionFinder JModelTest Phylogenetic Signal (%) Substitution Saturation Codon 1 Codon 2 Codon 3 AIC AICc BIC Codon 1&2 Codon 3 31R 29176 29613 TIMef+G TIM+I+G K81+G TVMef+I+G TVMef+I K80+G 15.3 Little Little 32R 29614 33480 GTR+G TVM+I+G TVM+G GTR+G GTR+G TPM3uf+G 2.2 Little Little 33R 33481 33672 GTR+G HKY+G GTR+G TIM3ef+G TPM3+G K80+I 38.0 Little Little 34R 33673 34122 K81uf+G TVM+I+G TVM+G TVMef+G TVMef+G K80 24.5 Little Little 37R 34123 34767 TVM+I+G GTR+G K81uf+G HKY+G HKY+G K80+G 30.6 Little Little 41R 34768 38337 TVM+G TVM+I+G GTR+G TIM1+I+G TIM1+I+G TPM1uf+G 2.7 Little Little 47L 38338 38820 TVM+I+G TIM+I+G TIM+G TIM1+I TIM1+I K80+I 21.7 Little Little 53R 38821 40422 TVM+G TVM+I+G GTR+G TIM1+I+G TIM1+I+G TPM1uf+I 9.9 Little Little 55.5L 40423 40575 TVM+G TIMef+G TIM+G TVMef TPM1 TPM1 33.4 Little Little 57R 40576 42114 TVM+I+G TVM+I+G TIM+G GTR+I+G GTR+I+G TIM1+G 9.7 Little Little 58.5R 42115 42675 TVM+G TVM+I+G TIM+G TIM1+G TIM1+G TPM1uf+G 25.2 Little Little 59L 42676 43797 TVM+G TVM+I+G TIM+G GTR+G GTR+G TVMef+G 14.0 Little Little 60R 43798 46857 K81uf+I GTR+I+G GTR+I+G TIM1+I+G TIM1+I+G TIM1+I 3.5 Little Little 62L 46858 50685 GTR+G GTR+I+G GTR+I+G TIM1+I+G TIM1+I+G TIM1+I 2.6 Little Little 63R 50686 51204 TVM+I+G GTR+G TVM+G TIM1+I+G TIM1+I+G TIM1+I 28.7 Little Little 64R 51205 51492 GTR+G TVM+I+G GTR+G TPM1+I TPM1+I TPM1+I 21.4 Little Little 67L 51493 52659 GTR+I+G GTR+I+G GTR+I+G TIM1+I TIM1+I TIM1ef+I 10.8 Little Little
50 Table 4 3 Continued Gene Location in alignment PartitionFinder JModelTest Phylogenetic Signal (%) Substitution Saturation Codon 1 Codon 2 Codon 3 AIC AICc BIC Codon 1&2 Codon 3 72L 52660 53538 TVM+I+G TIM+I+G TIM+G TVM+I TVM+I TPM1+I 19.2 Little Little 74L 53539 55293 K81uf+G TVM+I+G TIM+G TIM2+I+G TIM2+I+G HKY+G 3.9 Little Little 75L 55294 55608 GTR+G HKY+G K81uf+G TPM1+I TPM1+I TPM1 35.7 Little Little 76R 55609 55860 GTR+G TVM+I+G TVM+G TPM1uf+G TPM1+G TPM1+G 37.5 Little Little 79R 55861 58035 K81uf+G TVM+I+G TVMef+G TPM1uf+I+G TPM1uf+I+G TPM1uf+G 12.4 Little Little 80L 58036 59199 K81uf+G GTR+G GTR+G TIM1+I TIM1+I TIM1+I 8.4 Little Little 81R 59200 59487 K81uf+I TrNef+I TIM+G TIM1+I TIM1+I TIM1+I 21.6 Little Little 82R 59488 59967 TVM+I+G TVM+I+G K81uf+G TVMef+G TVMef+G TPM1+G 7.8 Little Little 84R 59968 60798 TVM+G GTR+G K81uf+G TVMef+I TVMef+I TPM3 18.9 Little Little 85R 60799 61386 TVM+G GTR+G TIM+G TIM1+I TIM1+I TPM1+I 19.2 Little Little 88R 61387 61863 K81uf+I TrNef+I TVMef+G TPM1+I TPM1+I K80+I 21.8 Little Little 89R 61864 63576 K81uf+G TIM+G TIM+G TIM1+G TIM1+G TIM1+G 11.9 Little Little 90R 63577 64968 GTR+G TVM+I+G TVM+G GTR+G GTR+G TPM1uf+G 2.9 Little Little 91R 64969 66156 TVM+I+G TVM+I+G K81uf+G TPM1uf+I+G TPM1uf+G TPM1+G 9.4 Little Little 94L 66157 66972 K81uf+I HKY+G TIM+G TIM1ef+I TIM1ef+I TPM1+I 11.1 Little Little 95R 66973 68136 TVM+I+G TVM+I+G GTR+I+G TPM1uf+G TPM1uf+G TPM1uf+G 24.5 Little Little
51 Table 4 4 Summary of substitution models for PartitionFinder and JModelTest. PartitionFinder models are shown by their frequency in each codon position. JModel Test models are shown by their frequency using the AIC, AICc and BIC selection criteria Partiti onFinder JModelTest Codon 1 Freq. Codon 2 Freq. Codon 3 Freq. AIC Freq. AICc Freq. BIC Freq. Model Model Model Model Model Model GTR+G 12 GTR+G 8 GTR+G 7 GTR+G 3 GTR+G 3 HKY+G 1 GTR+I+G 3 GTR+I+G 7 GTR+I+G 9 GTR+I+G 2 GTR+I+G 2 K80 1 HKY+G 1 HKY+G 3 K80 1 HKY+G 1 HKY+G 1 K80+G 2 K81uf+G 5 TIM+G 1 K81+G 3 SYM+I 1 SYM+I 1 K80+I 3 K81+uf+I 5 TIMef+G 1 K81uf+G 6 TIM1+G 5 TIM1+G 5 TIM1+G 5 K81uf+I+G 2 TIM+I+G 7 SYM 1 TIM1+I 8 TIM1+I 7 TIM1+I 6 TIM+G 1 TrNef+I 2 TIM+G 16 TIM1+I+G 8 TIM1+I+G 8 TIM1+I+G 1 TIMef+G 1 TVM+G 4 TVM+G 7 TIM1ef+I 1 TIM1ef+I 1 TIM1ef+I 1 TVM+G 10 TVM+I+G 19 TVMef+G 2 TIM2+I+G 1 TIM2+I+G 1 TPM1 3 TVM+I+G 12 TIM3ef+G 1 TPM1 1 TPM1+G 4 TPM1+I 3 TPM1+G 1 TPM1+I 7 TPM1uf+G 3 TPM1+I 3 TPM1+I+G 12 TPM1uf+I+G 3 TPM1uf+G 3 TPM1uf+I 2 TVM+G 2 TPMuf+I 1 TPM2uf+G 1 TVM+I 2 TPM1uf+I+G 2 TPM3 1 TVM+I+G 2 TPM3+G 1 TPM3uf+G 1 TVMef 2 TVM+G 2 TVMef+G 1 TVMef+G 2 TVM+I 2 TVMef+I 1 TVM+I+G 2 TVMef+I+G 1 TVMef 1 TVMef+G 2 TVMef+I 2
52 Table 4 5 The nineteen s ignificant r ecombination events for the RDP4 analysis Events were reported if four or more detection softwares reported significant recombination. Values in th e detection methods denote significan ce or lack of significance (i.e. not significant; NS). Eight events are highlighted in gray in which the RI 1 ( RC15021:RC_2006_GA_Gray ) genome was found to be the recombinant sequence Breakpoint Positions Detect ion Methods In Alignment In Recombinant Sequence Relative to ADRV Recombination Event Number Number In .RDP File Begin End Begin End Begin End Recombinant Sequence(s) Minor Parental Sequence(s) Major Parental Sequence(s) RDP GENECONV Bootscan Maxchi Chimaera SiSscan PhylPro LARD 3Seq 1 2 29720 34143 26639 28989 26639 28989 ADRV RGV Unknown (FV3) 1.30E 32 2.99E 40 2.46E 40 1.02E 11 7.27E 07 1.32E 23 NS NS 2.36E 11 STIV Unknown (SSME) 2 3 17638 21892 15844 19078 15919 19225 FV3 RC15027 SSME 6.45E 37 3.33E 27 5.72E 26 1.14E 10 6.33E 10 1.77E 07 NS NS NS ADRV 3 4 29938 30178 26779 26989 26803 27013 RC15021 RGV Unknown (FV3) 4.26E 33 1.47E 33 2.74E 33 5.21E 11 7.88E 09 7.93E 21 NS NS NS ADRV Unknown (SSME) STIV 4 8 51452 58796 45836 51836 45806 51968 RC15021 RC15027 SSME 3.08E 24 1.05E 22 9.59E 19 5.39E 15 1.06E 14 NS NS NS 0.0006 ADRV FV3 5 9 30188* 31420 26997* 27280 27021* 27283 RC15021 Unknown (CMTVM) SSME 2.51E 17 NS 2.84E 16 1.07E 07 3.61E 07 NS NS NS NS FV3 6 10 10840 12588 10036 11538 10039 11541 RC15021 RC15027 FV3 2.48E 17 1.49E 15 2.40E 17 1.36E 07 5.44E 06 3.21E 12 NS NS NS ADRV RGV SSME STIV 7 11 25155 27084 22380 24120 22401 24141 RC15021 RC15027 SSME 4.05E 16 4.48E 13 2.45E 09 5.46E 08 6.84E 08 3.10E 08 NS NS NS FV3 8 13 30168 30646 26943 27076 27009 27090 ESV Unknown (ATV) GGRV 8.74E 09 6.40E 14 1.14E 07 0.01028 NS 9.36E 09 NS NS NS 9 14 1978* 2748 1903* 2616 1903* 2616 RC15021 ADRV STIV 5.29E 12 1.50E 12 4.66E 12 3.39E 06 4.90E 06 NS NS NS NS RC15027 RGV 10 15 26911 27694 23968 24751 23968 24751 ADRV STIV RC15027 6.06E 12 1.24E 10 5.79E 12 0.02224 0.02094 NS NS NS NS FV3 RGV SSME 11 16 23188 25352 20521 22598 20521 22598 ADRV STIV RC15027 2.55E 11 3.99E 05 3.20E 05 0.00936 0.04218 0.00014 NS NS NS RGV
53 Table 4 5 Continued Breakpoint Positions Detection Methods In Alignment In Recombinant Sequence Relative to ADRV Recombination Event Number Number In .RDP File Begin End Begin End Begin End Recombinant Sequence(s) Minor Parental Sequence(s) Major Parental Sequence(s) RDP GENECONV Bootscan Maxchi Chimaera SiSscan PhylPro LARD 3Seq 12 17 41132 42428 35792 37055 35792 37055 ADRV STIV RC15027 1.33E 12 5.80E 08 6.00E 05 2.95E 05 NS NS NS NS NS FV3 RGV SSME 13 19 23301 25037 20475 22136 20628 22289 FV3 RC15027 STIV 5.67E 09 3.11E 05 0.001356 0.04178 0.04159 0.00906 NS NS NS SSME RGV 14 22 62993 63444 55340 55521 55730 55986 FV3 Unknown (TORV) STIV 3.97E 07 NS 1.42E 07 0.00242 NS 1.75E 05 NS NS NS RC15021 Unknown (ADRV) RGV SSME Unknown (CMTVVB) Unknown (RC15027) 15 25 54614 55182 48479 48807 48740 48975 ESV CMTVVB Unknown (SSME) 0.000201 7.02E 07 0.000746 0.00609 0.01211 NS NS NS NS EHNV ADRV Unknown (FV3) CMTVM Unknown (STIV) RC15021 RC15027 16 27 56100 56200 49401 49501 49761 49792 EHNV Unknown (ATV) ESV NS 3.76E 06 2.81E 08 NS 0.00195 9.07E 06 NS NS NS 17 28 54634 54748 47215 47278 48760 48823 GGRV ATV SSME 6.64E 06 0.00012843 5.49E 06 0.00061 0.00075 0.00011 NS NS NS ADRV ADRV FV3 CMTVM CMTVM STIV CMTVVB RC15021 RC15021 RC15027 RC15027 18 29 62932 63462 54187 54402 55675 56004 GGRV ESV STIV 6.69E 05 0.0165612 5.40E 05 0.00645 0.00431 0.02429 NS NS NS 1 9 38 31389* 31556 27240* 27377 27261* 27407 TORV Unknown (ESV) GGRV 0.006794 0.006222 4.82E 06 NS NS 2.92E 05 NS NS NS CMTV = The actual brea kpoint position is undetermined.
54 Figure 4 1 Map of recombination events in the concatenated alignment of 52 conserved genes in RC15021:RC_2006_GA_Gray (RI 1 ); block adjacent to recombinant sequence represent s minor parent with sequence name below block, with the ORF and function, if known
55 Figure 4 2 Cladogram depicting the relationship of RI 1 and RI 2 to representatives of the genus Ranavi rus based on the concatenated nucleotide alignment of 52 conserved genes. Numbers above each node represent posterior probabilities ( values >8 0 shown ) from the Bayesian analysis. Numbers below each node represent bootstrap values ( values >70 shown ) from the M aximum L ikelihood analysis. The branch lengths represent the number of inferred substitutions as shown by the scale
56 Figure 4 3 Phylogram depicting the relationship of RI 1 and RI 2 to representatives of the genus Ranavirus based on the concatenated nucleotide alignment of 52 conserved genes. The branch lengths represent the number of inferred substitutions as shown by the scale.
57 CHAPTER 5 DISCUSSION In this study we sequenced the full genome s of two ranaviruses isolated from the same ranaculture facility and compared them to 15 other available ranavirus genomes. Our next generation sequencing revealed the 1998 isolate (RI 2) originally characterized by Maijji and colleagues (2006) belongs to the rec ently discovered clade of ranaviuses known as CMTV in Europe (Balseiro et al. 2009, 2010, Kik et al. 2011, Mavian et al. 2012 van Beurden et al. 2014 Price et al. 2015 ) and ADRV in China (Figure 4 2) Our data are consistent with the findings of Majji an d colleagues (2006) who reported that the novel RI 2 isolate differed from wildtype FV3 in its virulence (greater virulence in RI 2), restriction fragment profile s and possession of a full length copy of the viral homolog of eukaryotic initiation factor 2 alpha (eIF The discovery of CMTV in a North American ranaculture facility in 1998 is currently the earliest known case of CMTV and expands the known host and geographic ra nge of this emerging pathogen. Region s of the mostly FV3 isolate from 2006 (RI 1) appear to have recombined with one or more CMTV/ADRV ranavirus (es) The RI 1 isolate contained a majority of genes with greatest sequence identity to FV3 (Table 4 1); however, eight significant recombination events involving 16 genes were detected in which RI 2 or an other CMTV /ADRV ranavirus served as the minor parent (donor) Although r ecombination in FV3 has been p revious ly reported by Chinchar and Granoff (1986) and recently in ATV ( Jancovich et al. 2003; Epstein and Storfer 2016) our study is t he first to demonstrate bullfrog s in a ranaculture suffering from a chimeric ranavirus strain (genome resulting from the recombination of at least two viral parents) Interestingly, Hoverman et al. (2010) report ed greater mortality in amphibians exposed to the same bullfrog ranavirus isolate (RI 1) analyzed i n our study as compared to wild type FV3.
58 R ecombination can serve as a driver of viral virulence /pathogenesis and host range evolution ( Worob e y and Holmes 1999; Martin et al. 2011). Our recombination analysis showed that in RI 1, the ORF2L was included within a recombination event. He et al. (2004) showed that ORF2L (myrist y lated protein) in R ana g rylio v irus (RGV) function s as an envelope protein Though better studied in the African Swine Fever virus the myrist y lated pr otein homolog is believed to facilitate viral entry into cell s and thus could influence both host range and virulence (Chinchar et al. 2011 ) Although the functions of many of the genes observed in the eight significant recombination e vents reported here for RI 1 are unknown, perhaps the mixing of genes among ranaviruses may serve as an important genetic mechanism influencing the evolution of virulence and host range in these e merging pathogens The common midwife toad virus (CMTV) was first reported in Spain in 2007 (Balseiro et a l. 2009). To our knowledge, our 1998 isolate (RI 2) predates all other records of CMTV infection in amphibians. Since RI 2 was isolated from a commonly traded species in a ranaculture facility, it is possible that CMTV has been transmitted between North America and Europe. It has been suggested that amphibians in the live animal trade can carry exotic pests and parasites (Franke and Telecky 2001) and spread diseases (Daszak et al. 1999). Amphibians are t raded internationally for a variety of uses including : as pets (Andreaone et al. 2006) or as part of zoological collections for food (Schlaepfer et al. 2005) for education or scientific research, as fishing bait, and for biologic al control The trade in amphib ians, by the United States alone is estimated at millions of individuals, body parts, and products annually (Schlaepfer et al. 2005). The bait trade of salamanders has been suggested to contribute to the dissemination of amphibian diseases. In the western U nited S tates populations of tiger salamanders have become infected with Ambystoma tigrinum viurus through this pathway (Jancovich et al. 2005).
59 In our study we compared two bullfrog rana viral isolates, RI 1 and RI 2, to 15 different ranavirus es isolat ed from poikilothermic vertebrate hosts around the world. Some of the host species of these isolates came from animals not native to the region they were colle cted. For example, RGV was isolated from the p ig f rog ( Lithobates grylio ) in China, though it is native to the southeastern United States. The North American bullfrog is both the most commonly cultivated amphibian for human consumption and is the most frequently traded species globally (Schlaepfer et al. 2005 ; Daszak and Schloegel 2006 ). From 2008 2013, approximately 8,331,215 individual American bullfrogs were imported into and 17,133 individuals were exported from the United States ( Data from C.M. Romagosa compilation of USFWS Form 3 177 data ). Wh en exported, bullfrogs are usually live but some international trade calls for frozen fr og legs (Teixeira et al. 2001). The major countri es that import frog legs are France, the United States, Belgium and Luxembourg (United Nations Statistics Division 2008). It is believed that the trade in North Am erican bullfrogs may have contributed to the spread o f the amphibian fungus Batrachochytrium dendrobatidis (Daszak et al. 2004) and ranavirus into new areas (Schloegel et al. 2009). In the United States, little disease surveillance is performed on imported animals. The housing before importation and the importation process usually keeps animals at high densities, grouped w ith many other species, which allows opportunities for transmission and amplification of pathogens between species (Pavlin et al. 2009). FV3 and CMTV lik e ranaviruses have low host specificity and are able to infect three class es of poikilothermic vertebrate animals Multiple species reared in close proximity to each other and/or in high densities could facilitate ranavirus transmission. Stressful conditions associated with ranaculture facilities may result in host immunosuppression predisposing cultivated amphibians to ranaviral infections. Given the high densities of amphibians in
60 ranaculture facilities, pathogen virulence is theorized t o increase due to the high transmission rates between hosts (Ewald 1994). Thus, c ertain amphibians such as the North American bullfrog may have played an important role in the global dissemination of lethal ranaviruses given they : 1) are commonly cultivate d/traded 2) are susceptible to multiple ranavirus es (e.g. FV3 and CMTV) and 3) may serve as mixing vessel s for the evolution of novel chimeric strains. It is noteworthy that ranavirus outbreaks have occurred in cultivated bullfrogs in North America (Maij ji et al. 2006, Miller et al. 2007) and South America (Mazzonni et al. 2009 ) as well as in invasive bullfrog populations in Japan (Ume et al. 2009) and Belgium (Sharifian Fard et al. 2011). R anaculture facilities may pose a significant risk to wild fish, a mphibians, and reptiles if infected animals or water is released into the environment. Continued efforts are needed to properly evaluate the risk ranaculture facilities may pose to wildlife through pathogen pollution and the role international trade has pl ayed in the global emergence of ranavirus epizootics (Picco et al 2008).
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77 BIOGRAPHICAL SKETCH Sieara completed a n MS in wildlife e cology and conservation at the University of Florida She previously holds a n MS in biology and certificate in car tography and geographic information s ystems from California State University, Los Ange les. She also received a BS in b iology and BA in Spanish at Kansas State University.