Hostname: page-component-8448b6f56d-c47g7 Total loading time: 0 Render date: 2024-04-17T21:51:29.543Z Has data issue: false hasContentIssue false
  • English
  • Français

Cryptosporidium in fish: alternative sequencing approaches and analyses at multiple loci to resolve mixed infections

Published online by Cambridge University Press:  14 August 2017

ANDREA PAPARINI Open the ORCID record for ANDREA PAPARINI [Opens in a new window] ,
RONGCHANG YANG ,
LINDA CHEN ,
KAISING TONG ,
SUSAN GIBSON-KUEH ,
ALAN LYMBERY  and
UNA M. RYAN
ANDREA PAPARINI*
Affiliation:
Vector and Water-Borne Pathogen Research Group, School of Veterinary & Life Sciences, Murdoch University, WA, Australia
RONGCHANG YANG
Affiliation:
Vector and Water-Borne Pathogen Research Group, School of Veterinary & Life Sciences, Murdoch University, WA, Australia
LINDA CHEN
Affiliation:
Vector and Water-Borne Pathogen Research Group, School of Veterinary & Life Sciences, Murdoch University, WA, Australia
KAISING TONG
Affiliation:
Vector and Water-Borne Pathogen Research Group, School of Veterinary & Life Sciences, Murdoch University, WA, Australia
SUSAN GIBSON-KUEH
Affiliation:
Freshwater Fish Group and Fish Health Unit, School of Veterinary and Life Sciences, Murdoch University, Murdoch, Western 6150, Australia
ALAN LYMBERY
Affiliation:
Freshwater Fish Group and Fish Health Unit, School of Veterinary and Life Sciences, Murdoch University, Murdoch, Western 6150, Australia
UNA M. RYAN
Affiliation:
Vector and Water-Borne Pathogen Research Group, School of Veterinary & Life Sciences, Murdoch University, WA, Australia
*
*Corresponding author: Vector- and Water-Borne Pathogen Research Group, School of Veterinary & Life Sciences, Molecular and Biomedical Sciences, Murdoch University, 90 South Street, Murdoch WA, 6150, Australia. E-mail: A.Paparini@murdoch.edu.au
Get access Rights & Permissions [Opens in a new window]

Summary

Currently, the systematics, biology and epidemiology of piscine Cryptosporidium species are poorly understood. Here, we compared Sanger ‒ and next-generation ‒ sequencing (NGS), of piscine Cryptosporidium, at the 18S rRNA and actin genes. The hosts comprised 11 ornamental fish species, spanning four orders and eight families. The objectives were: to (i) confirm the rich genetic diversity of the parasite and the high frequency of mixed infections; and (ii) explore the potential of NGS in the presence of complex genetic mixtures. By Sanger sequencing, four main genotypes were obtained at the actin locus, while for the 18S locus, seven genotypes were identified. At both loci, NGS revealed frequent mixed infections, consisting of one highly dominant variant plus substantially rarer genotypes. Both sequencing methods detected novel Cryptosporidium genotypes at both loci, including a novel and highly abundant actin genotype that was identified by both Sanger sequencing and NGS. Importantly, this genotype accounted for 68·9% of all NGS reads from all samples (249 585/362 372). The present study confirms that aquarium fish can harbour a large and unexplored Cryptosporidium genetic diversity. Although commonly used in molecular parasitology studies, nested PCR prevents quantitative comparisons and thwarts the advantages of NGS, when this latter approach is used to investigate multiple infections.

Keywords

Cryptosporidiumfishnext-generation sequencing (NGS)18S rRNA geneactin geneSanger sequencingmolecular phylogenymolecular systematicsparasitologymixed infections
Type
Research Article
Information
Parasitology , Volume 144 , Issue 13 , November 2017 , pp. 1811 - 1820
Check for updates
Copyright
Copyright © Cambridge University Press 2017 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Alvarez-Pellitero, P. and Sitja-Bobadilla, A. (2002). Cryptosporidium molnari n. sp. (Apicomplexa: Cryptosporidiidae) infecting two marine fish species, Sparus aurata L. and Dicentrarchus labrax L . International Journal for Parasitology 32, 1007–1021.Google Scholar
Alvarez-Pellitero, P., Quiroga, M. I., Sitja-Bobadilla, A., Redondo, M. J., Palenzuela, O., Padros, F., Vazquez, S. and Nieto, J. M. (2004). Cryptosporidium scophthalmi n. sp. (Apicomplexa: Cryptosporidiidae) from cultured turbot Scophthalmus maximus. Light and electron microscope description and histopathological study. Diseases of Aquatic Organisms 62, 133–145.Google Scholar
Boutin, S., Sevellec, M., Pavey, S. A., Bernatchez, L. and Derome, N. (2012). A fast, highly sensitive double-nested PCR-based method to screen fish immunobiomes. Molecular Ecology Resources 12, 1027–1039.Google Scholar
Caporaso, J. G., Kuczynski, J., Stombaugh, J., Bittinger, K., Bushman, F. D., Costello, E. K., Fierer, N., Pena, A. G., Goodrich, J. K., Gordon, J. I., Huttley, G. A., Kelley, S. T., Knights, D., Koenig, J. E., Ley, R. E., Lozupone, C. A., McDonald, D., Muegge, B. D., Pirrung, M., Reeder, J., Sevinsky, J. R., Tumbaugh, P. J., Walters, W. A., Widmann, J., Yatsunenko, T., Zaneveld, J. and Knight, R. (2010). QIIME allows analysis of high-throughput community sequencing data. Nature Methods 7, 335–336.CrossRefGoogle ScholarPubMed
Edgar, R. C. (2010). Search and clustering orders of magnitude faster than BLAST. Bioinformatics 26, 2460–2461.Google Scholar
Edgar, R. C. (2013). UPARSE: highly accurate OTU sequences from microbial amplicon reads. Nature Methods 10, 996–8.Google Scholar
Edgar, R. C., Haas, B. J., Clemente, J. C., Quince, C. and Knight, R. (2011). UCHIME improves sensitivity and speed of chimera detection. Bioinformatics 27, 2194–2200.CrossRefGoogle ScholarPubMed
Ghedin, E., Laplante, J., DePasse, J., Wentworth, D. E., Santos, R. P., Lepow, M. L., Porter, J., Stellrecht, K., Lin, X., Operario, D., Griesemer, S., Fitch, A., Halpin, R. A., Stockwell, T. B., Spiro, D. J., Holmes, E. C. and St George, K. (2011). Deep sequencing reveals mixed infection with 2009 pandemic influenza A (H1N1) virus strains and the emergence of oseltamivir resistance. Journal of Infectious Diseases 203, 168–174.Google Scholar
Gorzer, I., Guelly, C., Trajanoski, S. and Puchhammer-Stockl, E. (2010). Deep sequencing reveals highly complex dynamics of human cytomegalovirus genotypes in transplant patients over time. Journal of Virology 84, 7195–7203.Google Scholar
Katoh, K. and Standley, D. M. (2013). MAFFT multiple sequence alignment software version 7: improvements in performance and usability. Molecular Biology and Evolution 30, 772–780.Google Scholar
Kearse, M., Moir, R., Wilson, A., Stones-Havas, S., Cheung, M., Sturrock, S., Buxton, S., Cooper, A., Markowitz, S., Duran, C., Thierer, T., Ashton, B., Meintjes, P. and Drummond, A. (2012). Geneious basic: an integrated and extendable desktop software platform for the organization and analysis of sequence data. Bioinformatics 28, 1647–1649.Google Scholar
Koinari, M., Karl, S., Ng-Hublin, J., Lymbery, A. J. and Ryan, U. M. (2013). Identification of novel and zoonotic Cryptosporidium species in fish from Papua New Guinea. Veterinary Parasitology 198, 1–9.Google Scholar
Morgan, U. M., Constantine, C. C., Forbes, D. A. and Thompson, R. C. A. (1997). Differentiation between human and animal isolates of Cryptosporidium parvum using rDNA sequencing and direct PCR analysis. Journal of Parasitology 83, 825–830.CrossRefGoogle ScholarPubMed
Morine, M., Yang, R., Ng, J., Kueh, S., Lymbery, A. J. and Ryan, U. M. (2012). Additional novel Cryptosporidium genotypes in ornamental fishes. Veterinary Parasitology 190, 578–582.Google Scholar
Murphy, B. G., Bradway, D., Walsh, T., Sanders, G. E. and Snekvik, K. (2009). Gastric cryptosporidiosis in freshwater angelfish (Pterophyllum scalare). Journal of Veterinary Diagnostic Investigation 21, 722–727.Google Scholar
Palenzuela, O., Alvarez-Pellitero, P. and Sitja-Bobadilla, A. (2010). Molecular characterization of Cryptosporidium molnari reveals a distinct piscine clade. Applied and Environmental Microbiology 76, 7646–7649.Google Scholar
Paparini, A., Gofton, A., Yang, R. C., White, N., Bunce, M. and Ryan, U. M. (2015). Comparison of Sanger and next generation sequencing performance for genotyping Cryptosporidium isolates at the 18S rRNA and actin loci. Experimental Parasitology 151, 21–27.Google Scholar
Park, J. W. and Crowley, D. E. (2010). Nested PCR bias: a case study of Pseudomonas spp. in soil microcosms. Journal of Environmental Monitoring 12, 985–988.Google Scholar
Price, M. N., Dehal, P. S. and Arkin, A. P. (2010). FastTree 2-approximately maximum-likelihood trees for large alignments. PLoS ONE 5, e9490.Google Scholar
Reid, A., Lymbery, A., Ng, J., Tweedle, S. and Ryan, U. (2010). Identification of novel and zoonotic Cryptosporidium species in marine fish. Veterinary Parasitology 168, 190–195.Google Scholar
Ryan, U., Xiao, L., Read, C., Zhou, L., Lal, A. A. and Pavlasek, I. (2003). Identification of novel Cryptosporidium genotypes from the Czech Republic. Applied and Environmental Microbiology 69, 4302–4307.Google Scholar
Ryan, U., Paparini, A., Tong, K., Yang, R., Gibson-Kueh, S., O'Hara, A., Lymbery, A. and Xiao, L. (2015). Cryptosporidium huwi n. sp. (Apicomplexa: Eimeriidae) from the guppy (Poecilia reticulata). Experimental Parasitology 150, 31–35.Google Scholar
Silva, S. O., Richtzenhain, L. J., Barros, I. N., Gomes, A. M., Silva, A. V., Kozerski, N. D., de Araujo Ceranto, J. B., Keid, L. B. and Soares, R. M. (2013). A new set of primers directed to 18S rRNA gene for molecular identification of Cryptosporidium spp. and their performance in the detection and differentiation of oocysts shed by synanthropic rodents. Experimental Parasitology 135, 551–557.Google Scholar
Tamura, K., Stecher, G., Peterson, D., Filipski, A. and Kumar, S. (2013). MEGA6: molecular evolutionary genetics analysis version 6.0. Molecular Biology and Evolution 30, 2725–2729.Google Scholar
Whiteley, A. S., Jenkins, S., Waite, I., Kresoje, N., Payne, H., Mullan, B., Allcock, R. and O'Donnell, A. (2012). Microbial 16S rRNA Ion Tag and community metagenome sequencing using the Ion Torrent (PGM) Platform. Journal of Microbiological Methods 91, 80–88.Google Scholar
Yang, R., Murphy, C., Song, Y., Ng-Hublin, J., Estcourt, A., Hijjawi, N., Chalmers, R., Hadfield, S., Bath, A., Gordon, C. and Ryan, U. (2013). Specific and quantitative detection and identification of Cryptosporidium hominis and C. parvum in clinical and environmental samples. Experimental Parasitology 135, 142–147.Google Scholar
Yang, R., Palermo, C., Chen, L., Edwards, A., Paparini, A., Tong, K., Gibson-Kueh, S., Lymbery, A. and Ryan, U. (2015). Genetic diversity of Cryptosporidium in fish at the 18S and actin loci and high levels of mixed infections. Veterinary Parasitology 214, 255–263.Google Scholar
Zanguee, N., Lymbery, J. A., Lau, J., Suzuki, A., Yang, R., Ng, J. and Ryan, U. (2010). Identification of novel Cryptosporidium species in aquarium fish. Veterinary Parasitology 174, 43–48.Google Scholar
Supplementary material: File

Paparini supplementary material

Figures S1-S3

Download Paparini supplementary material(File)
File 499.2 KB
Supplementary material: File

Paparini supplementary material

Table S1

Download Paparini supplementary material(File)
File 818 KB
Supplementary material: File

Paparini supplementary material

Table S2

Download Paparini supplementary material(File)
File 16.6 KB