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Identification of novel and zoonotic Cryptosporidium species in marine fish
Veterinary Parasitology 168 (2010) 190–195
Contents lists available at ScienceDirect
Veterinary Parasitology journal homepage: www.elsevier.com/locate/vetpar
Identification of novel and zoonotic Cryptosporidium species in marine fish A. Reid a, A. Lymbery b, J. Ng a, S. Tweedle a, U. Ryan a,* a b
Division of Veterinary and Biomedical Sciences, Murdoch University, Murdoch, Western Australia 6150, Australia Fish Health Unit, Centre for Fish and Fisheries Research, Murdoch University, Murdoch, Western Australia 6150, Australia
A R T I C L E I N F O
A B S T R A C T
Article history: Received 21 October 2009 Received in revised form 18 November 2009 Accepted 20 November 2009
Little is known about the prevalence and genotypes of Cryptosporidium in fish. The present study investigated the prevalence of Cryptosporidium species in cultured fingerlings (n = 227), wild freshwater (n = 227) and wild marine/estuarine species (n = 255) of fish in Western Australia by PCR amplification at the 18S rRNA locus. Results revealed a low prevalence of Cryptosporidium infection in fish hosts; 0.8% (6/709). Four species of Cryptosporidium were identified including C. parvum, C. xiaoi and pig genotype II in whiting (Sillago vittata) and a novel Cryptosporidium spp. in mullets (Mugil cephalus). The identification of zoonotic species of Cryptosporidium in fish indicates that future research to gain a better understanding of the public health impacts is warranted. The detection of the protozoa in fish may also be a good sentinel for environmental contamination or ecosystem health. ß 2009 Elsevier B.V. All rights reserved.
Keywords: Cryptosporidium Fish 18S rRNA Actin GP60 Zoonotic New species
1. Introduction Current knowledge of the epidemiology, taxonomy, pathology and host specificity of Cryptosporidium species infecting piscine hosts is limited. There are two recognised species of Cryptosporidium in fish: Cryptosporidium molnari in gilthead sea bream (Sparus aurata) and European sea bass (Dicentrarchus labrax) and Cryptosporidium scophthalmi in turbot (Psetta maxima, syn. Scophthalmus maximus) (Alvarez-Pellitero and Sitja-Bobadilla, 2002; Alvarez-Pellitero et al., 2004). C. molnari primarily infects the stomach and seldom the intestinal epithelium (Alvarez-Pellitero and Sitja-Bobadilla, 2002), whereas C. scophthalmi mainly infects the intestinal epithelium and very seldom the stomach epithelium (Alvarez-Pellitero
* Corresponding author at: Division of Health Sciences, School of Veterinary and Biomedical Science, Murdoch University, Murdoch Drive, Murdoch, Perth, Western Australia 6150, Australia. Tel.: +61 89360 2482; fax: +61 89310 414. E-mail address: [email protected] (U. Ryan). 0304-4017/$ – see front matter ß 2009 Elsevier B.V. All rights reserved. doi:10.1016/j.vetpar.2009.11.015
et al., 2004). Unfortunately no genetic characterization has been conducted on C. molnari or C. scophthalmi and to date, only two genetic sequences are available from piscinederived Cryptosporidium spp.; an isolate from a guppy (Poecilia reticulate) (Ryan et al., 2004) and more recently from a freshwater angelfish (Pterophyllum scalare) (Murphy et al., 2009). Cryptosporidium has an environmentally resistant infective oocyst that can withstand standard water treatment systems (Xiao, in press). Given the increasing growth of the aquaculture industry, understanding the potential impact and pathology of these parasites on fish hosts is very important. In addition, fish are ubiquitous in marine and freshwater ecosystems and it is therefore critical to understand the potential zoonotic risks that Cryptosporidium infected fish pose. The detection of the protozoa in fish may be a good sentinel for environmental contamination or ecosystem health as detection of zoonotic Cryptosporidium spp. in fish may suggest a possible environmental source of human exposure and infection. The aim of the present study therefore was to determine the prevalence of different species of Cryptosporidium in wild freshwater and marine
A. Reid et al. / Veterinary Parasitology 168 (2010) 190–195
fishes sampled in Western Australia and from cultured fingerlings collected from hatcheries throughout Australia. 2. Materials and methods 2.1. Sample collection Three different groups of fish; cultured fingerlings (juvenile fish), wild freshwater species and wild marine/ estuarine species were screened (Table 1). Fingerlings (227 fish belonging to 8 freshwater and marine species) were collected from five commercial aquaculture hatcheries within Australia (Table 1). A total of 255 marine fish from 5 species from estuarine and coastal locations were obtained from commercial fishers. Wild freshwater fish species (227 fish belonging to 8 species) were collected from two river systems in the south west of Western Australia: the Canning/Swan River and the Blackwood River. On arrival in the laboratory, fish were measured for length and weight, dissected and using a scalpel blade, stomach and intestinal epithelial cells were scraped off and placed into a 1.5 mL eppendorf tube. Remaining stomach and intestinal tissue were stored separately in 70% ethanol.
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2.2. DNA extraction and PCR amplification DNA was extracted from 25 mg of intestinal and stomach tissue scrapings from each fish sample using a Qiagen DNeasy tissue kit (Qiagen, Germany). DNA was eluted in 50 mL of AE buffer to concentrate the DNA. All extracted DNA samples were stored at 20 8C until required for screening. All samples were screened at the 18S rRNA locus and positives were genotyped by sequencing. A two-step nested PCR protocol was used to amplify the 18S rDNA gene of Cryptosporidium as previously described (Ryan et al., 2003a). Isolates that were positive at the 18S locus by PCR were also amplified at the actin locus as previously described (Ng et al., 2006). Isolates were sub-genotyped at the GP60 gene locus using a two-step nested PCR which amplifies a secondary PCR fragment of 832 bp as previously described (Strong et al., 2000). PCR contamination controls were used including negative controls and separation of preparation and amplification areas. The amplified DNA fragments from the secondary PCR products were separated by gel electrophoresis and purified using the freeze–squeeze method (Ng et al., 2006). A spike analysis (addition of 0.5 mL of Cryptosporidium positive control into each sample) was conducted on randomly selected Cryptosporidium negative samples from each
Table 1 Cultured fingerlings, marine and freshwater fish species collected during this study. Fingerlings
Locations Hatchery 1
Hatchery 2
Hatchery 3
Hatchery 4
Hatchery 5
Black bream (Acanthopagrus butcheri) Snapper (Pagrus auratus) Barramundi (Lates calcarifer) Yellow tail kingfish (Seriola lalandi) Mulloway (Argyrosomus japonicus) Jade perch (Scortum barcoo) Silver perch (Bidyanus bidyanus) Murray cod (Maccullochella peelii peelii)
– – – – – – – 17
11 10 48 9 10 – – –
– – 28 – – – – –
– – – – – 20 33 –
– – – – 41 – – –
11 10 76 9 51 20 33 17
Total
17
88
28
53
41
227
Marine fish
Estuary sampling
Coastal sampling
Total
Total
Peel estuary
Leschenault estuary
Shark Bay
Sea mullet (Mugil cephalus) Common blow fish (Torguigener pleurogramma) King George whiting (Sillaginodes punctata) School whiting (Sillago vittata) Yellow eyed mullet (Aldrichetta forsteri)
55 – – – –
– 9 – – –
26 – – – –
30 – 40 55 40
111 9 40 55 40
Total
55
9
26
165
255
Blackwood River
Perth
Freshwater fish
Canning/Swan River
Western minnow (Galaxias occidentalis) Western hardyhead (Leptatherina wallacei) Mosquito fish (Gambusia holbrooki) Nightfish (Bostockia porosa) Western pigmy perch (Edelia vittata) One spot live bearer (Phalloceros caudimaculatus) Goldfish (Carassius auratus) Freshwater cobbler (Tandanus bostocki)
30 5 10 – 1 – – –
91 6 16 15 3 1 1 48
Total 121 11 26 15 4 1 1 48
Total
46
181
227
Location of hatcheries: hatchery 1 was located in Alexander, Victoria; hatchery 2 in Fremantle, Western Australia; hatchery 3 in West Beach, South Australia; hatchery 4 in Childers, Queensland; and hatchery 5 was located in West Beach, South Australia.
A. Reid et al. / Veterinary Parasitology 168 (2010) 190–195
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Table 2 Percent prevalence of Cryptosporidium in cultured, wild freshwater and wild marine fish. Upper and lower 95% confidence intervals are given in parentheses. No positive for Cryptosporidium
Cryptosporidium prevalence %
Cultured fish Freshwater fish Marine fish
0/227 0/227 6/255
0 0 2.4 (0.5,4.2)
Total
6/709
0.8 (0.2, 1.5)
group of DNA extractions to determine if negative results were due to PCR inhibition. 2.3. Sequence and phylogenetic analysis Purified PCR products were sequenced using an ABI PrismTM Dye Terminator cycle sequencing kit (Applied Biosystems, Foster City, California) according to the manufacturer’s instructions with the exception that the annealing temperature was raised to 58 8C. Nucleotide sequences were analyzed using Chromas lite version 2.0 (http://www.technelysium.com.au) and aligned with reference genotypes from GenBank using Clustal W (http://www.clustalw.genome.jp). Phylogenetic trees were constructed using additional isolates from GenBank. Distance estimation was conducted using TREECON (Van de Peer and De Wachter, 1994), based on evolutionary distances calculated with the Tamura-Nei model and grouped using Neighbour-Joining. Parsimony analyses were conducted using MEGA version 3.1 (MEGA3.1: Molecular Evolutionary Genetics Analysis software, Arizona State University, Tempe, Arizona, USA). Bootstrap analyses were conducted using 1000 replicates to assess the reliability of inferred tree topologies. Maximum likelihood (ML) analyses were conducted using the program PhyML (Dereeper et al., 2008) and the reliability of the inferred trees was assessed by the approximate likelihood ratio test (aLRT) (Anisimova and Gascuel, 2006). 2.4. Calculation of prevalences Prevalences were expressed as percentage of positive samples, with 95% confidence intervals calculated assuming a binomial distribution, using the software Quantitative Parasitology 3.0 (Rozsa et al., 2000). 2.5. Microscopy Tissue segments from samples that were PCR positive were transferred to formalin prior to processing,
embedded in paraffin and histological sections were cut at 5 mm and stained with hematoxylin and eosin. Parasites were examined with the aid of an ocular micrometer in a Zeiss Axioskop microscope at 1000 magnification. 3. Results 3.1. Prevalence of Cryptosporidium in fish hosts Of the 709 fish sampled during this study, only 0.8% of fish were positive by PCR and all positive samples were from the wild marine group with a prevalence of 2.4% for these hosts (Table 2). Infected hosts were school whiting (Sillago vittata), with a prevalence of 66.7% (95% CI = 27.1– 93.7%; n = 6) and sea mullet (Mugil cephalus), with a prevalence of 33.3% (95% CI = 6.3–72.9%; n = 6). 3.2. Identification of Cryptosporidium species in fish Partial sequences were obtained for all six positive isolates (Whit 1, Whit 4, Whit 5, Whit 7, M9 and M13) at the 18S rRNA locus, while isolates Whit 1, Whit 4, Whit 5 and Whit 7, but not M9 or M13, were also successfully amplified and sequenced at the actin locus (Table 3). The four isolates from whiting were all genetically identical, or very closely related to genotypes previously characterized at these loci. Isolate Whit 1 was genetically identical to C. parvum at both 18S rRNA and actin loci, and subtyping at the GP60 locus identified it as C. parvum subtype IIaA18G3R1. Isolate Whit 5 was genetically identical to Cryptosporidium pig genotype II at both loci, while isolate Whit 4 was identical to pig genotype II at the actin locus, and a genetic variant of pig genotype II, with an estimated genetic distance of 0.5%, at the 18S rRNA locus. Isolate Whit 7 was identical to Cryptosporidium xiaoi at the actin locus, while at the 18S rRNA locus, had one nucleotide difference with C. xiaoi and two with C. bovis. The two isolates from mullet (M9 and M13) were genetically identical, but distinct from all isolates previously characterized at the 18S rRNA locus. Distancebased, parsimony and ML analysis (Fig. 1 – NJ tree shown) of mullet-derived 18S rRNA sequences produced similar results and indicated that they clustered most closely with the freshwater angelfish isolate. The estimated genetic distance between the mullet isolates and the angelfish isolate was 5.7%, while that between the mullet isolates and all other Cryptosporidium species and genotypes was 12.6–18.2% (Table 4). Microscopic examination of the two mullet isolates in situ identified large numbers of the parasite associated with the intestinal mucosa and also deep within the epithelium (Fig. 2).
Table 3 Cryptosporidium sp./genotypes identified in marine fish. Sample
Host species
18S
Actin
GP60
Whit 1 Whit 4 Whit 5 Whit 7 ML9 ML13
School whiting School whiting School whiting School whiting Sea mullet Sea mullet
C. parvum Pig genotype II Pig genotype II C. xiaoi/C. bovis Novel genotype Novel genotype
C. parvum Pig genotype II Pig genotype II C. xiaoi – –
IIaA18G3R1 – – – – –
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Fig. 1. Evolutionary relationships of Cryptosporidium piscine-derived isolates inferred by Neighbour-Joining analysis of Kimura distances calculated from pairwise comparison of 18S rRNA sequences. Percentage bootstrap support (>50%) from 1000 pseudoreplicates from distance, parsimony and ML is indicated at the left of the supported node (ns = not supported).
3.3. Nucleotide sequence accession number The unique partial 18S rRNA sequence of the mullet genotype has been deposited in the GenBank database under accession number GQ925452.
4. Discussion In the present study, the overall prevalence of Cryptosporidium spp. in the 709 cultured, wild marine and wild freshwater fishes sampled was low; 0.8% (6/709). No Cryptosporidium isolates were detected from cultured
or freshwater fishes, and among the 255 wild marine fish only 6 were infected, giving a prevalence of 2.4%. Previous studies have reported a much higher prevalence of infection with Cryptosporidium, mostly among juvenile fish (Sitja`-Bobadilla et al., 2005; Alvarez-Pellitero et al., 2004; Murphy et al., 2009). Alvarez-Pellitero et al. (2004) reported that juvenile turbot up to 400 g were intensely parasitized with C. scophthalmi, with infection rates of up to 100%. In gilthead bream and European sea bass, a significant association between fish age and weight and infection with C. molnari was reported with infection levels peaking in the 30–100 g fish weight class, while no infections were observed in fish weighing over 300 g (Sitja`-
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Table 4 Percentage genetic distances between mullet isolates and other Cryptosporidium species at the 18S rRNA locus calculated using Kimura’s distance.
Mullet Angelfish Guppy C. muris C. baileyi C. parvum C. hominis
Mullet
Angelfish
Guppy
C. muris
C. baileyi
C. parvum
C. hominis
0 5.7 12.6 17.4 13.6 18.2 18.2
0 14.2 17.1 14.6 16.3 16.2
0 15.2 13.8 15.9 16.1
0 9.2 12.1 12.1
0 7.3 7.3
0 0.6
0
Fig. 2. H&E stained sections of mullet intestine showing (arrows) large numbers of Cryptosporidium organisms along the epithelial lining of the intestine and clusters of parasites located deep within the epithelium. Scale bar = 10 mm.
Bobadilla et al., 2005). Similarly, in a study of hatcheryreared cichlids (hybrids of Oreochromis aureus O. niloticus), only fry and fingerlings, not adults were infected with Cryptosporidium (Landsberg and Paperna, 1986). A more recent study monitored C. scophthalmi in four different cohorts of cultured turbot from fingerlings (10–50 g) until reaching market size (400–1400 g) and found that young animals in poor nutritional condition during the spring and summer and not infected with the myxozoan, Enteromyxum scophthalmi were most likely to be highly infected by C. scophthalmi (Alvarez-Pellitero et al., 2009). Increasing levels of C. scophthalmi abundance were associated with greater severity of C. scophthalmi-compatible lesions. The absence of Cryptosporidium infections in cultured fingerlings in our study may have been due to good disease control practices; all hatcheries had contaminant containment procedures and most used filtered water. The low prevalence among wild marine species may have been due to the age of the fish that were sampled (all were adult), seasonal influences (most were sampled in winter), lack of proximity to agriculture run-off and sewage discharge or to a naturally low prevalence of species of Cryptosporidium in the fish that were sampled in the coastal areas of Western Australia. In the present study, two new hosts for Cryptosporidium were identified; mullet (M. cephalus) and school whiting (S. vittata). This is also the first study in which C. parvum, C. xiaoi and pig genotype II have been identified in these fish hosts. C. xiaoi, pig genotype II and C. parvum were all identified in
marine whiting. A novel genotype was identified in two marine mullets, which is genetically very distinct and represents a new species of Cryptosporidium. Of significance to public health is the identification of C. parvum in a piscine host as this species is zoonotic and represents the most common source of zoonotic infection (Xiao, in press). Subtype analysis at the GP60 locus identified the C. parvum subtype IIaA18G3R1, which is one of the most commonly reported C. parvum subtype in humans and cattle in Australia and Ireland (Thompson et al., 2007; Jex et al., 2008; Ng et al., 2008; O’Brien et al., 2008; Waldron et al., 2009a,b; Zintl et al., 2009). C. xiaoi is a newly described species that infects sheep, while pig genotype II infects pigs (Ryan et al., 2003b; Fayer and Santı´n, 2009). Contamination of the marine environment with infective oocysts from human and agricultural effluent, may explain the presence of Cryptosporidium spp. usually observed in humans and livestock infections in fish hosts. Histological examination of intestinal/stomach tissue of infected mullet samples, confirmed the presence of the mullet genotype in intestinal villi and the presence of parasite stages deep within the epithelium. The pathogenesis of the mullet genotype is unknown. Studies on the related angelfish genotype, which was identified in a hatchery, revealed that infected fish exhibited variable levels of emaciation, poor growth rates, swollen coelomic cavities, anorexia, listlessness, and increased mortality (Murphy et al., 2009). In affected fish, large numbers of protozoa were identified both histologically and ultrastructurally associated with the gastric mucosa. Histological analysis of the mullet isolate identified large numbers of parasites associated with the intestinal mucosa and also deep within the epithelium. The guppy isolate was detected in the stomach and oogonial and sporogonial stages deep within the epithelium were observed, similar to C. molnari (Ryan et al., 2004). The mullet genotype has never been identified in a non-fish host which suggests that it is host specific, however further studies are required to establish this. Molecular and phylogenetic analysis of the mullet isolates at the 18S rRNA locus supports the species status of this genotype. The genetic distance between the genotypes from mullet and angelfish was 5.7% and that between the mullet genotype and all other Cryptosporidium species and genotypes was 12.6–18.2%. This is considerably greater than the genetic distance between most other Cryptosporidium species. For example, C. parvum and C. hominis differ by 0.6% and the genetic distance between C. parvum and all other intestinal species is 0.6–2.3%. Within
A. Reid et al. / Veterinary Parasitology 168 (2010) 190–195
Cryptosporidium taxonomy, if the genetic distance between a new genotype and its closest relative is equal to or greater than the genetic distance between established Cryptosporidium species, then this is regarded as a valid criterion for claiming species status (Xiao et al., 2004). By this criterion, the mullet isolates are clearly a separate species. The phylogeneic tree derived from 18S rRNA sequences indicated that the mullet genotype identified in this study, and the previously identified angelfish and guppy genotypes formed clades that were basal to all other Cryptosporidium species and genotypes in the tree, suggesting that fish-derived Cryptosporidium isolates may be the most primitive of Cryptosporidium species. In conclusion, a low prevalence of Cryptosporidium infection was identified in fish hosts in the present study, which may be due to a variety of factors. The detection of zoonotic and livestock species of Cryptosporidium in fish is significant and suggests that fish may be a good sentinel for contamination of water with sewage and agricultural runoff. The identification of zoonotic species of Cryptosporidium in fish indicates that future research to gain a better understanding of the public health impacts is warranted. Interestingly, a recent study reported that the mean probability of infection was nearly one for urban anglers while fishing and consuming caught fish (Roberts et al., 2007). A new ‘‘mullet’’ genotype was identified which is likely to be a new species. Further studies are required to more fully understand the phylogenetic relationships and evolutionary timelines of fish-derived Cryptosporidium isolates. References Alvarez-Pellitero, P., Sitja-Bobadilla, A., 2002. Cryptosporidium molnari n. sp. (Apicomplexa: Cryptosporidiidae) infecting two marine fish species, Sparus aurata L. and Dicentrarchus labrax L. Int. J. Parasitol. 32, 1007–1021. Alvarez-Pellitero, P., Quiroga, M.I., Sitja`-Bobadilla, A., Redondo, M.J., Palenzuela, O., Padro´s, F., Va´zquez, S., Nieto, J.M., 2004. Cryptosporidium scophthalmi n. sp. (Apicomplexa: Cryptosporidiidae) from cultured turbot Scophthalmus maximus. Light and electron microscope description and histopathological study. Dis. Aquat. Organ. 62, 133– 145. Alvarez-Pellitero, P., Perez, A., Quiroga, M.I., Redondo, M.J., Va´zquez, S., Riaza, A., Palenzuela, O., Sitja`-Bobadilla, A., Nieto, J.M., 2009. Host and environmental risk factors associated with Cryptosporidium scophthalmi (Apicomplexa) infection in cultured turbot, Psetta maxima (L.) (Pisces, Teleostei). Vet. Parasitol. 165, 207–215. Anisimova, M., Gascuel, O., 2006. Approximate likelihood-ratio test for branches: a fast, accurate, and powerful alternative. Syst. Biol. 55, 539–552. Dereeper, A., Guignon, V., Blanc, G., Audic, S., Buffet, S., Chevenet, F., Dufayard, J.F., Guindon, S., Lefort, V., Lescot, M., Claverie, J.M., Gascuel, O., 2008. Phylogeny.fr: robust phylogenetic analysis for the nonspecialist. Nucleic Acids Res. 36, W465–W469.
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Fayer, R., Santı´n, M., 2009. Cryptosporidium xiaoi n. sp. (Apicomplexa: Cryptosporidiidae) in sheep (Ovis aries). Vet. Parasitol. 164, 192–200. Jex, A.R., Pangasa, A., Campbell, B.E., Whipp, M., Hogg, G., Sinclair, M.I., Stevens, M., Gasser, R.B., 2008. Classification of Cryptosporidium species from patients with sporadic cryptosporidiosis by use of sequence-based multilocus analysis following mutation scanning. J. Clin. Microbiol. 46, 2252–2262. Landsberg, J.H., Paperna, I., 1986. Ultrastructural study of the coccidian Cryptosporidium sp. from stomachs of juvenile cichlid fish. Dis. Aquat. Organ. 2, 13–20. Murphy, B.G., Bradway, D., Walsh, T., Sanders, G.E., Snekvik, K., 2009. Gastric cryptosporidiosis in freshwater angelfish (Pterophyllum scalare). J. Vet. Diagn. Invest. 21, 722–727. Ng, J., Pavlasek, I., Ryan, U., 2006. Identification of novel Cryptosporidium genotypes from avian hosts. Appl. Environ. Microbiol. 72, 7548– 7553. Ng, J., Eastwood, K., Durrheim, D., Massey, P., Walker, B., Armson, A., Ryan, U., 2008. Evidence supporting zoonotic transmission of Cryptosporidium in regional New South Wales. Exp. Parasitol. 119, 192–195. O’Brien, E., McInnes, L., Ryan, U., 2008. Cryptosporidium GP60 genotypes from humans and domesticated animals in Australia, North America and Europe. Exp. Parasitol. 118, 118–121. Roberts, J.D., Silbergeld, E.K., Graczyk, T., 2007. A probabilistic risk assessment of Cryptosporidium exposure among Baltimore urban anglers. J. Toxicol. Environ. Health A 70, 1568–1576. Rozsa, L., Reiczigel, J., Majoros, G., 2000. Quantifying parasites in samples of hosts. J. Parasitol. 86, 228–232. Ryan, U., Xiao, L., Read, C., Zhou, L., Lal, A.A., Pavlasek, I., 2003a. Identification of novel Cryptosporidium genotypes from the Czech Republic. Appl. Environ. Microbiol. 69, 4302–4307. Ryan, U.M., Samarasinghe, B., Read, C., Buddle, J.R., Robertson, I.D., Thompson, R.C., 2003b. Identification of a novel genotype of Cryptosporidium in pigs. Appl. Environ. Microbiol. 69, 3970–3974. Ryan, U., O’Hara, A., Xiao, L., 2004. Molecular and biological characterization of Cryptosporidium molnari-like isolate from a guppy (Poecilia reticulata). Appl. Environ. Microbiol. 70, 3761–3765. Sitja`-Bobadilla, A., Padro´s, F., Aguilera, C., Alvarez-Pellitero, P., 2005. Epidemiology of Cryptosporidium molnari in Spanish Gilthead Sea Bream (Sparus aurata L.) and European Sea Bass (Dicentrarchus labrax L.) cultures: from hatchery to market size. Appl. Environ. Microbiol. 70, 131–139. Strong, W.B., Gut, J., Nelson, R.G., 2000. Cloning and sequence analysis of a highly polymorphic Cryptosporidium parvum gene encoding a 60kilodalton glycoprotein and characterization of its 15- and 45-kilodalton zoite surface antigen products. Infect. Immun. 68, 4117–4134. Thompson, H.P., Dooley, J.S., Kenny, J., McCoy, M., Lowery, C.J., Moore, J.E., Xiao, L., 2007. Subtypes and subtypes of Cryptosporidium spp. in neonatal calves in Northern Ireland. Parasitol. Res. 100, 619–624. Van de Peer, Y., De Wachter, R., 1994. TREECON for Windows: a software package for the construction and drawing of evolutionary trees for the Microsoft Windows environment. Comput. Appl. Biosci. 10, 569–570. Waldron, L.S., Ferrari, B.C., Gillings, M.R., Power, M.L., 2009a. Terminal restriction fragment length polymorphism for identification of Cryptosporidium species in human feces. Appl. Environ. Microbiol. 75, 108–112. Waldron, L.S., Ferrari, B.C., Power, M.L., 2009b. Glycoprotein 60 diversity in C. hominis and C. parvum causing human cryptosporidiosis in NSW, Australia. Exp. Parasitol. 122, 124–127. Xiao, L., Fayer, R., Ryan, U., Upton, S.J., 2004. Cryptosporidium taxonomy: recent advances and implications for public health. Clin. Microbiol. Rev. 17, 72–97. Xiao, L., in press. Molecular epidemiology of cryptosporidiosis: an update. Exp. Parasitol., doi:10.1016/j.exppara.2009.03.018. Zintl, A., Proctor, A.F., Read, C., Dewaal, T., Shanaghy, N., Fanning, S., Mulcahy, G., 2009. The prevalence of Cryptosporidium species and subtypes in human faecal samples in Ireland. Epidemiol. Infect. 137, 270–277.
Contents lists available at ScienceDirect
Veterinary Parasitology journal homepage: www.elsevier.com/locate/vetpar
Identification of novel and zoonotic Cryptosporidium species in marine fish A. Reid a, A. Lymbery b, J. Ng a, S. Tweedle a, U. Ryan a,* a b
Division of Veterinary and Biomedical Sciences, Murdoch University, Murdoch, Western Australia 6150, Australia Fish Health Unit, Centre for Fish and Fisheries Research, Murdoch University, Murdoch, Western Australia 6150, Australia
A R T I C L E I N F O
A B S T R A C T
Article history: Received 21 October 2009 Received in revised form 18 November 2009 Accepted 20 November 2009
Little is known about the prevalence and genotypes of Cryptosporidium in fish. The present study investigated the prevalence of Cryptosporidium species in cultured fingerlings (n = 227), wild freshwater (n = 227) and wild marine/estuarine species (n = 255) of fish in Western Australia by PCR amplification at the 18S rRNA locus. Results revealed a low prevalence of Cryptosporidium infection in fish hosts; 0.8% (6/709). Four species of Cryptosporidium were identified including C. parvum, C. xiaoi and pig genotype II in whiting (Sillago vittata) and a novel Cryptosporidium spp. in mullets (Mugil cephalus). The identification of zoonotic species of Cryptosporidium in fish indicates that future research to gain a better understanding of the public health impacts is warranted. The detection of the protozoa in fish may also be a good sentinel for environmental contamination or ecosystem health. ß 2009 Elsevier B.V. All rights reserved.
Keywords: Cryptosporidium Fish 18S rRNA Actin GP60 Zoonotic New species
1. Introduction Current knowledge of the epidemiology, taxonomy, pathology and host specificity of Cryptosporidium species infecting piscine hosts is limited. There are two recognised species of Cryptosporidium in fish: Cryptosporidium molnari in gilthead sea bream (Sparus aurata) and European sea bass (Dicentrarchus labrax) and Cryptosporidium scophthalmi in turbot (Psetta maxima, syn. Scophthalmus maximus) (Alvarez-Pellitero and Sitja-Bobadilla, 2002; Alvarez-Pellitero et al., 2004). C. molnari primarily infects the stomach and seldom the intestinal epithelium (Alvarez-Pellitero and Sitja-Bobadilla, 2002), whereas C. scophthalmi mainly infects the intestinal epithelium and very seldom the stomach epithelium (Alvarez-Pellitero
* Corresponding author at: Division of Health Sciences, School of Veterinary and Biomedical Science, Murdoch University, Murdoch Drive, Murdoch, Perth, Western Australia 6150, Australia. Tel.: +61 89360 2482; fax: +61 89310 414. E-mail address: [email protected] (U. Ryan). 0304-4017/$ – see front matter ß 2009 Elsevier B.V. All rights reserved. doi:10.1016/j.vetpar.2009.11.015
et al., 2004). Unfortunately no genetic characterization has been conducted on C. molnari or C. scophthalmi and to date, only two genetic sequences are available from piscinederived Cryptosporidium spp.; an isolate from a guppy (Poecilia reticulate) (Ryan et al., 2004) and more recently from a freshwater angelfish (Pterophyllum scalare) (Murphy et al., 2009). Cryptosporidium has an environmentally resistant infective oocyst that can withstand standard water treatment systems (Xiao, in press). Given the increasing growth of the aquaculture industry, understanding the potential impact and pathology of these parasites on fish hosts is very important. In addition, fish are ubiquitous in marine and freshwater ecosystems and it is therefore critical to understand the potential zoonotic risks that Cryptosporidium infected fish pose. The detection of the protozoa in fish may be a good sentinel for environmental contamination or ecosystem health as detection of zoonotic Cryptosporidium spp. in fish may suggest a possible environmental source of human exposure and infection. The aim of the present study therefore was to determine the prevalence of different species of Cryptosporidium in wild freshwater and marine
A. Reid et al. / Veterinary Parasitology 168 (2010) 190–195
fishes sampled in Western Australia and from cultured fingerlings collected from hatcheries throughout Australia. 2. Materials and methods 2.1. Sample collection Three different groups of fish; cultured fingerlings (juvenile fish), wild freshwater species and wild marine/ estuarine species were screened (Table 1). Fingerlings (227 fish belonging to 8 freshwater and marine species) were collected from five commercial aquaculture hatcheries within Australia (Table 1). A total of 255 marine fish from 5 species from estuarine and coastal locations were obtained from commercial fishers. Wild freshwater fish species (227 fish belonging to 8 species) were collected from two river systems in the south west of Western Australia: the Canning/Swan River and the Blackwood River. On arrival in the laboratory, fish were measured for length and weight, dissected and using a scalpel blade, stomach and intestinal epithelial cells were scraped off and placed into a 1.5 mL eppendorf tube. Remaining stomach and intestinal tissue were stored separately in 70% ethanol.
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2.2. DNA extraction and PCR amplification DNA was extracted from 25 mg of intestinal and stomach tissue scrapings from each fish sample using a Qiagen DNeasy tissue kit (Qiagen, Germany). DNA was eluted in 50 mL of AE buffer to concentrate the DNA. All extracted DNA samples were stored at 20 8C until required for screening. All samples were screened at the 18S rRNA locus and positives were genotyped by sequencing. A two-step nested PCR protocol was used to amplify the 18S rDNA gene of Cryptosporidium as previously described (Ryan et al., 2003a). Isolates that were positive at the 18S locus by PCR were also amplified at the actin locus as previously described (Ng et al., 2006). Isolates were sub-genotyped at the GP60 gene locus using a two-step nested PCR which amplifies a secondary PCR fragment of 832 bp as previously described (Strong et al., 2000). PCR contamination controls were used including negative controls and separation of preparation and amplification areas. The amplified DNA fragments from the secondary PCR products were separated by gel electrophoresis and purified using the freeze–squeeze method (Ng et al., 2006). A spike analysis (addition of 0.5 mL of Cryptosporidium positive control into each sample) was conducted on randomly selected Cryptosporidium negative samples from each
Table 1 Cultured fingerlings, marine and freshwater fish species collected during this study. Fingerlings
Locations Hatchery 1
Hatchery 2
Hatchery 3
Hatchery 4
Hatchery 5
Black bream (Acanthopagrus butcheri) Snapper (Pagrus auratus) Barramundi (Lates calcarifer) Yellow tail kingfish (Seriola lalandi) Mulloway (Argyrosomus japonicus) Jade perch (Scortum barcoo) Silver perch (Bidyanus bidyanus) Murray cod (Maccullochella peelii peelii)
– – – – – – – 17
11 10 48 9 10 – – –
– – 28 – – – – –
– – – – – 20 33 –
– – – – 41 – – –
11 10 76 9 51 20 33 17
Total
17
88
28
53
41
227
Marine fish
Estuary sampling
Coastal sampling
Total
Total
Peel estuary
Leschenault estuary
Shark Bay
Sea mullet (Mugil cephalus) Common blow fish (Torguigener pleurogramma) King George whiting (Sillaginodes punctata) School whiting (Sillago vittata) Yellow eyed mullet (Aldrichetta forsteri)
55 – – – –
– 9 – – –
26 – – – –
30 – 40 55 40
111 9 40 55 40
Total
55
9
26
165
255
Blackwood River
Perth
Freshwater fish
Canning/Swan River
Western minnow (Galaxias occidentalis) Western hardyhead (Leptatherina wallacei) Mosquito fish (Gambusia holbrooki) Nightfish (Bostockia porosa) Western pigmy perch (Edelia vittata) One spot live bearer (Phalloceros caudimaculatus) Goldfish (Carassius auratus) Freshwater cobbler (Tandanus bostocki)
30 5 10 – 1 – – –
91 6 16 15 3 1 1 48
Total 121 11 26 15 4 1 1 48
Total
46
181
227
Location of hatcheries: hatchery 1 was located in Alexander, Victoria; hatchery 2 in Fremantle, Western Australia; hatchery 3 in West Beach, South Australia; hatchery 4 in Childers, Queensland; and hatchery 5 was located in West Beach, South Australia.
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Table 2 Percent prevalence of Cryptosporidium in cultured, wild freshwater and wild marine fish. Upper and lower 95% confidence intervals are given in parentheses. No positive for Cryptosporidium
Cryptosporidium prevalence %
Cultured fish Freshwater fish Marine fish
0/227 0/227 6/255
0 0 2.4 (0.5,4.2)
Total
6/709
0.8 (0.2, 1.5)
group of DNA extractions to determine if negative results were due to PCR inhibition. 2.3. Sequence and phylogenetic analysis Purified PCR products were sequenced using an ABI PrismTM Dye Terminator cycle sequencing kit (Applied Biosystems, Foster City, California) according to the manufacturer’s instructions with the exception that the annealing temperature was raised to 58 8C. Nucleotide sequences were analyzed using Chromas lite version 2.0 (http://www.technelysium.com.au) and aligned with reference genotypes from GenBank using Clustal W (http://www.clustalw.genome.jp). Phylogenetic trees were constructed using additional isolates from GenBank. Distance estimation was conducted using TREECON (Van de Peer and De Wachter, 1994), based on evolutionary distances calculated with the Tamura-Nei model and grouped using Neighbour-Joining. Parsimony analyses were conducted using MEGA version 3.1 (MEGA3.1: Molecular Evolutionary Genetics Analysis software, Arizona State University, Tempe, Arizona, USA). Bootstrap analyses were conducted using 1000 replicates to assess the reliability of inferred tree topologies. Maximum likelihood (ML) analyses were conducted using the program PhyML (Dereeper et al., 2008) and the reliability of the inferred trees was assessed by the approximate likelihood ratio test (aLRT) (Anisimova and Gascuel, 2006). 2.4. Calculation of prevalences Prevalences were expressed as percentage of positive samples, with 95% confidence intervals calculated assuming a binomial distribution, using the software Quantitative Parasitology 3.0 (Rozsa et al., 2000). 2.5. Microscopy Tissue segments from samples that were PCR positive were transferred to formalin prior to processing,
embedded in paraffin and histological sections were cut at 5 mm and stained with hematoxylin and eosin. Parasites were examined with the aid of an ocular micrometer in a Zeiss Axioskop microscope at 1000 magnification. 3. Results 3.1. Prevalence of Cryptosporidium in fish hosts Of the 709 fish sampled during this study, only 0.8% of fish were positive by PCR and all positive samples were from the wild marine group with a prevalence of 2.4% for these hosts (Table 2). Infected hosts were school whiting (Sillago vittata), with a prevalence of 66.7% (95% CI = 27.1– 93.7%; n = 6) and sea mullet (Mugil cephalus), with a prevalence of 33.3% (95% CI = 6.3–72.9%; n = 6). 3.2. Identification of Cryptosporidium species in fish Partial sequences were obtained for all six positive isolates (Whit 1, Whit 4, Whit 5, Whit 7, M9 and M13) at the 18S rRNA locus, while isolates Whit 1, Whit 4, Whit 5 and Whit 7, but not M9 or M13, were also successfully amplified and sequenced at the actin locus (Table 3). The four isolates from whiting were all genetically identical, or very closely related to genotypes previously characterized at these loci. Isolate Whit 1 was genetically identical to C. parvum at both 18S rRNA and actin loci, and subtyping at the GP60 locus identified it as C. parvum subtype IIaA18G3R1. Isolate Whit 5 was genetically identical to Cryptosporidium pig genotype II at both loci, while isolate Whit 4 was identical to pig genotype II at the actin locus, and a genetic variant of pig genotype II, with an estimated genetic distance of 0.5%, at the 18S rRNA locus. Isolate Whit 7 was identical to Cryptosporidium xiaoi at the actin locus, while at the 18S rRNA locus, had one nucleotide difference with C. xiaoi and two with C. bovis. The two isolates from mullet (M9 and M13) were genetically identical, but distinct from all isolates previously characterized at the 18S rRNA locus. Distancebased, parsimony and ML analysis (Fig. 1 – NJ tree shown) of mullet-derived 18S rRNA sequences produced similar results and indicated that they clustered most closely with the freshwater angelfish isolate. The estimated genetic distance between the mullet isolates and the angelfish isolate was 5.7%, while that between the mullet isolates and all other Cryptosporidium species and genotypes was 12.6–18.2% (Table 4). Microscopic examination of the two mullet isolates in situ identified large numbers of the parasite associated with the intestinal mucosa and also deep within the epithelium (Fig. 2).
Table 3 Cryptosporidium sp./genotypes identified in marine fish. Sample
Host species
18S
Actin
GP60
Whit 1 Whit 4 Whit 5 Whit 7 ML9 ML13
School whiting School whiting School whiting School whiting Sea mullet Sea mullet
C. parvum Pig genotype II Pig genotype II C. xiaoi/C. bovis Novel genotype Novel genotype
C. parvum Pig genotype II Pig genotype II C. xiaoi – –
IIaA18G3R1 – – – – –
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Fig. 1. Evolutionary relationships of Cryptosporidium piscine-derived isolates inferred by Neighbour-Joining analysis of Kimura distances calculated from pairwise comparison of 18S rRNA sequences. Percentage bootstrap support (>50%) from 1000 pseudoreplicates from distance, parsimony and ML is indicated at the left of the supported node (ns = not supported).
3.3. Nucleotide sequence accession number The unique partial 18S rRNA sequence of the mullet genotype has been deposited in the GenBank database under accession number GQ925452.
4. Discussion In the present study, the overall prevalence of Cryptosporidium spp. in the 709 cultured, wild marine and wild freshwater fishes sampled was low; 0.8% (6/709). No Cryptosporidium isolates were detected from cultured
or freshwater fishes, and among the 255 wild marine fish only 6 were infected, giving a prevalence of 2.4%. Previous studies have reported a much higher prevalence of infection with Cryptosporidium, mostly among juvenile fish (Sitja`-Bobadilla et al., 2005; Alvarez-Pellitero et al., 2004; Murphy et al., 2009). Alvarez-Pellitero et al. (2004) reported that juvenile turbot up to 400 g were intensely parasitized with C. scophthalmi, with infection rates of up to 100%. In gilthead bream and European sea bass, a significant association between fish age and weight and infection with C. molnari was reported with infection levels peaking in the 30–100 g fish weight class, while no infections were observed in fish weighing over 300 g (Sitja`-
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Table 4 Percentage genetic distances between mullet isolates and other Cryptosporidium species at the 18S rRNA locus calculated using Kimura’s distance.
Mullet Angelfish Guppy C. muris C. baileyi C. parvum C. hominis
Mullet
Angelfish
Guppy
C. muris
C. baileyi
C. parvum
C. hominis
0 5.7 12.6 17.4 13.6 18.2 18.2
0 14.2 17.1 14.6 16.3 16.2
0 15.2 13.8 15.9 16.1
0 9.2 12.1 12.1
0 7.3 7.3
0 0.6
0
Fig. 2. H&E stained sections of mullet intestine showing (arrows) large numbers of Cryptosporidium organisms along the epithelial lining of the intestine and clusters of parasites located deep within the epithelium. Scale bar = 10 mm.
Bobadilla et al., 2005). Similarly, in a study of hatcheryreared cichlids (hybrids of Oreochromis aureus O. niloticus), only fry and fingerlings, not adults were infected with Cryptosporidium (Landsberg and Paperna, 1986). A more recent study monitored C. scophthalmi in four different cohorts of cultured turbot from fingerlings (10–50 g) until reaching market size (400–1400 g) and found that young animals in poor nutritional condition during the spring and summer and not infected with the myxozoan, Enteromyxum scophthalmi were most likely to be highly infected by C. scophthalmi (Alvarez-Pellitero et al., 2009). Increasing levels of C. scophthalmi abundance were associated with greater severity of C. scophthalmi-compatible lesions. The absence of Cryptosporidium infections in cultured fingerlings in our study may have been due to good disease control practices; all hatcheries had contaminant containment procedures and most used filtered water. The low prevalence among wild marine species may have been due to the age of the fish that were sampled (all were adult), seasonal influences (most were sampled in winter), lack of proximity to agriculture run-off and sewage discharge or to a naturally low prevalence of species of Cryptosporidium in the fish that were sampled in the coastal areas of Western Australia. In the present study, two new hosts for Cryptosporidium were identified; mullet (M. cephalus) and school whiting (S. vittata). This is also the first study in which C. parvum, C. xiaoi and pig genotype II have been identified in these fish hosts. C. xiaoi, pig genotype II and C. parvum were all identified in
marine whiting. A novel genotype was identified in two marine mullets, which is genetically very distinct and represents a new species of Cryptosporidium. Of significance to public health is the identification of C. parvum in a piscine host as this species is zoonotic and represents the most common source of zoonotic infection (Xiao, in press). Subtype analysis at the GP60 locus identified the C. parvum subtype IIaA18G3R1, which is one of the most commonly reported C. parvum subtype in humans and cattle in Australia and Ireland (Thompson et al., 2007; Jex et al., 2008; Ng et al., 2008; O’Brien et al., 2008; Waldron et al., 2009a,b; Zintl et al., 2009). C. xiaoi is a newly described species that infects sheep, while pig genotype II infects pigs (Ryan et al., 2003b; Fayer and Santı´n, 2009). Contamination of the marine environment with infective oocysts from human and agricultural effluent, may explain the presence of Cryptosporidium spp. usually observed in humans and livestock infections in fish hosts. Histological examination of intestinal/stomach tissue of infected mullet samples, confirmed the presence of the mullet genotype in intestinal villi and the presence of parasite stages deep within the epithelium. The pathogenesis of the mullet genotype is unknown. Studies on the related angelfish genotype, which was identified in a hatchery, revealed that infected fish exhibited variable levels of emaciation, poor growth rates, swollen coelomic cavities, anorexia, listlessness, and increased mortality (Murphy et al., 2009). In affected fish, large numbers of protozoa were identified both histologically and ultrastructurally associated with the gastric mucosa. Histological analysis of the mullet isolate identified large numbers of parasites associated with the intestinal mucosa and also deep within the epithelium. The guppy isolate was detected in the stomach and oogonial and sporogonial stages deep within the epithelium were observed, similar to C. molnari (Ryan et al., 2004). The mullet genotype has never been identified in a non-fish host which suggests that it is host specific, however further studies are required to establish this. Molecular and phylogenetic analysis of the mullet isolates at the 18S rRNA locus supports the species status of this genotype. The genetic distance between the genotypes from mullet and angelfish was 5.7% and that between the mullet genotype and all other Cryptosporidium species and genotypes was 12.6–18.2%. This is considerably greater than the genetic distance between most other Cryptosporidium species. For example, C. parvum and C. hominis differ by 0.6% and the genetic distance between C. parvum and all other intestinal species is 0.6–2.3%. Within
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Cryptosporidium taxonomy, if the genetic distance between a new genotype and its closest relative is equal to or greater than the genetic distance between established Cryptosporidium species, then this is regarded as a valid criterion for claiming species status (Xiao et al., 2004). By this criterion, the mullet isolates are clearly a separate species. The phylogeneic tree derived from 18S rRNA sequences indicated that the mullet genotype identified in this study, and the previously identified angelfish and guppy genotypes formed clades that were basal to all other Cryptosporidium species and genotypes in the tree, suggesting that fish-derived Cryptosporidium isolates may be the most primitive of Cryptosporidium species. In conclusion, a low prevalence of Cryptosporidium infection was identified in fish hosts in the present study, which may be due to a variety of factors. The detection of zoonotic and livestock species of Cryptosporidium in fish is significant and suggests that fish may be a good sentinel for contamination of water with sewage and agricultural runoff. The identification of zoonotic species of Cryptosporidium in fish indicates that future research to gain a better understanding of the public health impacts is warranted. Interestingly, a recent study reported that the mean probability of infection was nearly one for urban anglers while fishing and consuming caught fish (Roberts et al., 2007). A new ‘‘mullet’’ genotype was identified which is likely to be a new species. Further studies are required to more fully understand the phylogenetic relationships and evolutionary timelines of fish-derived Cryptosporidium isolates. References Alvarez-Pellitero, P., Sitja-Bobadilla, A., 2002. Cryptosporidium molnari n. sp. (Apicomplexa: Cryptosporidiidae) infecting two marine fish species, Sparus aurata L. and Dicentrarchus labrax L. Int. J. Parasitol. 32, 1007–1021. Alvarez-Pellitero, P., Quiroga, M.I., Sitja`-Bobadilla, A., Redondo, M.J., Palenzuela, O., Padro´s, F., Va´zquez, S., Nieto, J.M., 2004. Cryptosporidium scophthalmi n. sp. (Apicomplexa: Cryptosporidiidae) from cultured turbot Scophthalmus maximus. Light and electron microscope description and histopathological study. Dis. Aquat. Organ. 62, 133– 145. Alvarez-Pellitero, P., Perez, A., Quiroga, M.I., Redondo, M.J., Va´zquez, S., Riaza, A., Palenzuela, O., Sitja`-Bobadilla, A., Nieto, J.M., 2009. Host and environmental risk factors associated with Cryptosporidium scophthalmi (Apicomplexa) infection in cultured turbot, Psetta maxima (L.) (Pisces, Teleostei). Vet. Parasitol. 165, 207–215. Anisimova, M., Gascuel, O., 2006. Approximate likelihood-ratio test for branches: a fast, accurate, and powerful alternative. Syst. Biol. 55, 539–552. Dereeper, A., Guignon, V., Blanc, G., Audic, S., Buffet, S., Chevenet, F., Dufayard, J.F., Guindon, S., Lefort, V., Lescot, M., Claverie, J.M., Gascuel, O., 2008. Phylogeny.fr: robust phylogenetic analysis for the nonspecialist. Nucleic Acids Res. 36, W465–W469.
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