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Serotyping of Toxoplasma gondii in Cats (Felis domesticus) Reveals Predominance of Type II Infections in Germany

Author

Listed:
  • Pavlo Maksimov
  • Johannes Zerweck
  • Jitender P Dubey
  • Nikola Pantchev
  • Caroline F Frey
  • Aline Maksimov
  • Ulf Reimer
  • Mike Schutkowski
  • Morteza Hosseininejad
  • Mario Ziller
  • Franz J Conraths
  • Gereon Schares

Abstract

Background: Cats are definitive hosts of Toxoplasma gondii and play an essential role in the epidemiology of this parasite. The study aims at clarifying whether cats are able to develop specific antibodies against different clonal types of T. gondii and to determine by serotyping the T. gondii clonal types prevailing in cats as intermediate hosts in Germany. Methodology: To establish a peptide-microarray serotyping test, we identified 24 suitable peptides using serological T. gondii positive (n=21) and negative cat sera (n=52). To determine the clonal type-specific antibody response of cats in Germany, 86 field sera from T. gondii seropositive naturally infected cats were tested. In addition, we analyzed the antibody response in cats experimentally infected with non-canonical T. gondii types (n=7). Findings: Positive cat reference sera reacted predominantly with peptides harbouring amino acid sequences specific for the clonal T. gondii type the cats were infected with. When the array was applied to field sera from Germany, 98.8% (85/86) of naturally-infected cats recognized similar peptide patterns as T. gondii type II reference sera and showed the strongest reaction intensities with clonal type II-specific peptides. In addition, naturally infected cats recognized type II-specific peptides significantly more frequently than peptides of other type-specificities. Cats infected with non-canonical types showed the strongest reactivity with peptides presenting amino-acid sequences specific for both, type I and type III. Conclusions: Cats are able to mount a clonal type-specific antibody response against T. gondii. Serotyping revealed for most seropositive field sera patterns resembling those observed after clonal type II-T. gondii infection. This finding is in accord with our previous results on the occurrence of T. gondii clonal types in oocysts shed by cats in Germany.

Suggested Citation

  • Pavlo Maksimov & Johannes Zerweck & Jitender P Dubey & Nikola Pantchev & Caroline F Frey & Aline Maksimov & Ulf Reimer & Mike Schutkowski & Morteza Hosseininejad & Mario Ziller & Franz J Conraths & Ge, 2013. "Serotyping of Toxoplasma gondii in Cats (Felis domesticus) Reveals Predominance of Type II Infections in Germany," PLOS ONE, Public Library of Science, vol. 8(11), pages 1-1, November.
  • Handle: RePEc:plo:pone00:0080213
    DOI: 10.1371/journal.pone.0080213
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    References listed on IDEAS

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    1. Meyer, David & Zeileis, Achim & Hornik, Kurt, 2006. "The Strucplot Framework: Visualizing Multi-way Contingency Tables with vcd," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 17(i03).
    2. Wehrens, Ron & Buydens, Lutgarde M. C., 2007. "Self- and Super-organizing Maps in R: The kohonen Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 21(i05).
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