Hostname: page-component-7479d7b7d-q6k6v Total loading time: 0 Render date: 2024-07-11T07:26:46.708Z Has data issue: false hasContentIssue false
  • English
  • Français

A comparison of sequence and length polymorphism for genotyping Cryptosporidium isolates

Published online by Cambridge University Press:  20 April 2015

G. WIDMER  and
S. M. CACCIÒ
G. WIDMER*
Affiliation:
Department of Infectious Disease and Global Health, Cummings School of Veterinary Medicine at Tufts University, North Grafton, Massachusetts, USA
S. M. CACCIÒ
Affiliation:
Department of Infectious, Parasitic and Immunomediated Diseases, Istituto Superiore di Sanità, Rome, Italy
*
*Corresponding author. Department of Infectious Disease and Global Health, Cummings School of Veterinary Medicine at Tufts University, 200 Westborough Road, North Grafton, Massachusetts 01536, USA. E-mail: giovanni.widmer@tufts.edu
Get access Rights & Permissions [Opens in a new window]

Summary

Simple sequence repeat markers have played an important role in elucidating the epidemiology of human and animal cryptosporidiosis. The drawback of sequence length polymorphisms is that nucleotide substitutions remain undetected. As some laboratories have opted for using length polymorphisms, while others have relied on sequencing, there is a need to compare both methods. We used a diversified set of unique length polymorphisms and matching nucleotide sequences to assess the ability of each genotyping protocol to discern clusters of related Cryptosporidium parvum isolates. We found a weak correlation between the two distance measures for individual markers. This analysis was extended to four-locus genotypes based on sequence length data or concatenated sequences from the same loci. We interrogated these data to assess whether one would reach the same conclusions regardless of the genotyping method. Clusters of isolates generated with the concatenated sequences were not observed with amplicon length, indicating that inferences on the structure of a Cryptosporidium population depend on the genotyping method. Moreover, isolate clusters derived from concatenated sequences were dependent on the algorithm used to calculate distances. These results emphasize the need for harmonizing genotyping tools, not only by selecting informative markers, but also by standardizing the entire genotyping method.

Keywords

Cryptosporidiumsimple sequence repeatsequence polymorphismprincipal coordinate analysisMantel test
Type
Research Article
Information
Parasitology , Volume 142 , Issue 8 , July 2015 , pp. 1080 - 1085
Check for updates
Copyright
Copyright © Cambridge University Press 2015 

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

Abrahamsen, M. S., Templeton, T. J., Enomoto, S., Abrahante, J. E., Zhu, G., Lancto, C. A., Deng, M., Liu, C., Widmer, G., Tzipori, S., Buck, G. A., Xu, P., Bankier, A. T., Dear, P. H., Konfortov, B. A., Spriggs, H. F., Iyer, L., Anantharaman, V., Aravind, L. and Kapur, V. (2004). Complete genome sequence of the apicomplexan, Cryptosporidium parvum . Science 304, 441–445.Google Scholar
Barnes, D. A., Bonnin, A., Huang, J. X., Gousset, L., Wu, J., Gut, J., Doyle, P., Dubremetz, J. F., Ward, H. and Petersen, C. (1998). A novel multi-domain mucin-like glycoprotein of Cryptosporidium parvum mediates invasion. Molecular and Biochemical Parasitology 96, 93–110.Google Scholar
Caccio, S., Spano, F. and Pozio, E. (2001). Large sequence variation at two microsatellite loci among zoonotic (genotype C) isolates of Cryptosporidium parvum . International Journal for Parasitology 31, 1082–1086.Google Scholar
Cevallos, A. M., Zhang, X., Waldor, M. K., Jaison, S., Zhou, X., Tzipori, S., Neutra, M. R. and Ward, H. D. (2000). Molecular cloning and expression of a gene encoding Cryptosporidium parvum glycoproteins gp40 and gp15. Infection and Immunity 68, 4108–4116.Google Scholar
Chalmers, R. M., Hadfield, S. J., Jackson, C. J., Elwin, K., Xiao, L. and Hunter, P. (2008). Geographic linkage and variation in Cryptosporidium hominis . Emerging Infection Diseases 14, 496–498.Google Scholar
Clarke, K. R. (1993). Nonparametric Multivariate analyses of changes in community structure. Australian Journal of Ecology 18, 117–143.Google Scholar
Drumo, R., Widmer, G., Morrison, L. J., Tait, A., Grelloni, V., D'Avino, N., Pozio, E. and Caccio, S. M. (2012). Evidence of host-associated populations of Cryptosporidium parvum in Italy. Applied and Environmental Microbiology 78, 3523–3529.Google Scholar
Escalante, A. A., Lal, A. A. and Ayala, F. J. (1998). Genetic polymorphism and natural selection in the malaria parasite Plasmodium falciparum . Genetics 149, 189–202.Google Scholar
Felsenstein, J. (1995). PHYLIP.[3·57 c]. Department of Genetics, University of Washington, Seattle.Google Scholar
Feng, X., Rich, S. M., Akiyoshi, D., Tumwine, J. K., Kekitiinwa, A., Nabukeera, N., Tzipori, S. and Widmer, G. (2000). Extensive polymorphism in Cryptosporidium parvum identified by multilocus microsatellite analysis. Applied and Environmental Microbiology 66, 3344–3349.Google Scholar
Feng, Y., Tiao, N., Li, N., Hlavsa, M. and Xiao, L. (2014). Multilocus sequence typing of an emerging Cryptosporidium hominis subtype in the United States. Journal of Clinical Microbiology 52, 524–530.Google Scholar
Gatei, W., Hart, C. A., Gilman, R. H., Das, P., Cama, V. and Xiao, L. (2006). Development of a multilocus sequence typing tool for Cryptosporidium hominis . Journal of Eukaryotic Microbiology 53(Supplement 1), S43–S48.CrossRefGoogle ScholarPubMed
Gatei, W., Das, P., Dutta, P., Sen, A., Cama, V., Lal, A. A. and Xiao, L. (2007). Multilocus sequence typing and genetic structure of Cryptosporidium hominis from children in Kolkata, India. Infection Genetics and Evolution 7, 197–205.CrossRefGoogle ScholarPubMed
Hammer, Ø., Harper, D. and Ryan, P. (2001). PAST: Paleontological Statistics Software Package for education and data analysis. Paleontologia Electronica 4, 1–9.Google Scholar
Heiges, M., Wang, H., Robinson, E., Aurrecoechea, C., Gao, X., Kaluskar, N., Rhodes, P., Wang, S., He, C. Z., Su, Y., Miller, J., Kraemer, E. and Kissinger, J. C. (2006). CryptoDB: a Cryptosporidium bioinformatics resource update. Nucleic Acids Research 34, D419–D422.Google Scholar
Laxer, M. A., Timblin, B. K. and Patel, R. J. (1991). DNA sequences for the specific detection of Cryptosporidium parvum by the polymerase chain reaction. American Journal of Tropical Medicine and Hygiene 45, 688–694.CrossRefGoogle ScholarPubMed
Legendre, P. and Legendre, L. F. (2012). Numerical Ecology. Elsevier Amsterdam, Boston, London, New York, Oxford, Paris, San Diego, San Francisco, Singapore, Sydney, Tokyo.Google Scholar
Madesis, P., Ganopoulos, I. and Tsaftaris, A. (2013). Microsatellites: evolution and contribution. Methods in Molecular Biology 1006, 1–13.CrossRefGoogle ScholarPubMed
Mallon, M., MacLeod, A., Wastling, J., Smith, H., Reilly, B. and Tait, A. (2003). Population structures and the role of genetic exchange in the zoonotic pathogen Cryptosporidium parvum . Journal of Molecular Evolution 56, 407–417.Google Scholar
Mantel, N. (1967). The detection of disease clustering and a generalized regression approach. Cancer Research 27, 209–220.Google Scholar
Morrison, L. J., Mallon, M. E., Smith, H. V., MacLeod, A., Xiao, L. and Tait, A. (2008). The population structure of the Cryptosporidium parvum population in Scotland: a complex picture. Infection Genetics and Evolution 8, 121–129.CrossRefGoogle ScholarPubMed
Peakall, R. and Smouse, P. E. (2012). GenAlEx 6·5: genetic analysis in Excel. Population genetic software for teaching and research – an update. Bioinformatics 28, 2537–2539.Google Scholar
Ryan, U. and Xiao, L. (2014). Taxonomy and molecular taxonomy. In Cryptosporidium: Parasite and Disease, (eds. Caccio, S.M., Widmer, G.) Springer Wien, Heidelberg, New York, Dordrecht, London, 3–41.Google Scholar
Schloss, P. D., Westcott, S. L., Ryabin, T., Hall, J. R., Hartmann, M., Hollister, E. B., Lesniewski, R. A., Oakley, B. B., Parks, D. H., Robinson, C. J., Sahl, J. W., Stres, B., Thallinger, G. G., Van Horn, D. J. and Weber, C. F. (2009). Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities. Applied and Environmental Microbiology 75, 7537–7541.Google Scholar
Sievers, F., Wilm, A., Dineen, D., Gibson, T. J., Karplus, K., Li, W., Lopez, R., McWilliam, H., Remmert, M., Soding, J., Thompson, J. D. and Higgins, D. G. (2011). Fast, scalable generation of high-quality protein multiple sequence alignments using Clustal Omega. Molecular System Biology 7, 539.CrossRefGoogle ScholarPubMed
Strong, W. B., Gut, J. and Nelson, R. G. (2000). Cloning and sequence analysis of a highly polymorphic Cryptosporidium parvum gene encoding a 60-kilodalton glycoprotein and characterization of its 15- and 45-kilodalton zoite surface antigen products. Infection and Immunity 68, 4117–4134.CrossRefGoogle ScholarPubMed
Tanriverdi, S. and Widmer, G. (2006). Differential evolution of repetitive sequences in Cryptosporidium parvum and Cryptosporidium hominis . Infection Genetics and Evolution 6, 113–122.CrossRefGoogle ScholarPubMed
Tautz, D. (1989). Hypervariability of simple sequences as a general source for polymorphic DNA markers. Nucleic Acids Research 17, 6463–6471.Google Scholar
Widmer, G. and Lee, Y. (2010). Comparison of single- and multilocus genetic diversity in the protozoan parasites Cryptosporidium parvum and C. hominis . Applied Environmental Microbiology 76, 6639–6644.Google Scholar
Widmer, G. and Sullivan, S. (2012). Genomics and population biology of Cryptosporidium species. Parasite Immunology 34, 61–71.Google Scholar
Xu, P., Widmer, G., Wang, Y., Ozaki, L. S., Alves, J. M., Serrano, M. G., Puiu, D., Manque, P., Akiyoshi, D., Mackey, A. J., Pearson, W. R., Dear, P. H., Bankier, A. T., Peterson, D. L., Abrahamsen, M. S., Kapur, V., Tzipori, S. and Buck, G. A. (2004). The genome of Cryptosporidium hominis . Nature 431, 1107–1112.Google Scholar