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Cryptosporidium infections in suckler herd beef calves

Published online by Cambridge University Press:  22 April 2015

C. BJÖRKMAN*
Affiliation:
Department of Clinical Sciences, Swedish University of Agricultural Sciences, P.O. Box 7054, SE-750 07 Uppsala, Sweden
L. LINDSTRÖM
Affiliation:
Department of Clinical Sciences, Swedish University of Agricultural Sciences, P.O. Box 7054, SE-750 07 Uppsala, Sweden
C. OWESON
Affiliation:
Department of Clinical Sciences, Swedish University of Agricultural Sciences, P.O. Box 7054, SE-750 07 Uppsala, Sweden
H. AHOLA
Affiliation:
Department of Virology, Immunobiology and Parasitology, National Veterinary Institute, SE-751 89 Uppsala, Sweden
K. TROELL
Affiliation:
Department of Virology, Immunobiology and Parasitology, National Veterinary Institute, SE-751 89 Uppsala, Sweden
C. AXÉN
Affiliation:
Department of Animal Health and Antimicrobial Strategies, National Veterinary Institute, SE-751 89 Uppsala, Sweden
*
* Corresponding author: Department of Clinical Sciences, Swedish University of Agricultural Sciences, P.O. Box 7054, SE-750 07 Uppsala, Sweden. Email: camilla.bjorkman@slu.se

Summary

A study was carried out to investigate how common Cryptosporidium infections are in beef calves in Swedish suckler herds and to explore which species and subtypes that occur. We further aimed at identifying factors associated with shedding of Cryptosporidium oocysts in this type of calf management. The study was conducted in two regions in Sweden and included 30 herds. Faecal samples were collected from calves younger than 3 months. A brief clinical examination was done and a questionnaire was used to collect data on management routines. Faeces were cleaned and concentrated and oocysts identified by epifuorescence microscopy. Cryptosporidium positive samples were analyzed at the 18S rRNA and GP60 genes to determine species and Cryptosporidium parvum subtype, respectively. Logistic regression was used to identify factors associated with infection. Oocysts were detected in 122 (36·7%) calves from 29 (97%) herds, at 400 to 2·4 × 107 OPG. The youngest positive calves were only 1 and 2 days old. There was no association between age and Cryptosporidium infection. Cryptosporidium bovis, Cryptosporidium ryanae, C. parvum and Cryptosporidium ubiquitum were identified, with C. bovis being the major species. Two C. parvum subtypes, IIaA16G1R1 and IIdA27G1 were identified. Routines for cleaning calf pens and number of cows in calving pens were associated with infection.

Information

Type
Research Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
Copyright © Cambridge University Press 2015
Figure 0

Fig. 1. Age and Cryptosporidium spp. oocyst shedding of 332 calves sampled in 30 Swedish suckler herds. Faecal samples were cleaned and concentrated by saline-glucose flotation, stained with FITC-labelled monoclonal anti-Cryptosporidium antibodies and examined by epifluorescence microscopy. The lower detection limit of the method is approximately 400 oocysts per gram faeces (OPG; Maddox-Hyttel et al.2006).

Figure 1

Table 1. Age, faecal consistency and faecal colour in 122 Cryptosporidium spp. positive and 210 Cryptosporidium spp. negative calves in 30 Swedish suckler herds

Figure 2

Fig. 2. Cryptosporidium species distribution in 122 oocyst shedding calves in 30 Swedish suckler herds Faecal samples were cleaned and concentrated by saline-glucose flotation, stained with FITC-labelled monoclonal anti-Cryptosporidium antibodies and examined by epifluorescence microscopy. The positive samples were further analyzed at the 18S rRNA and the 60 kDa glycoprotein (GP60) genes to determine Cryptosporidium species.

Figure 3

Table 2. Variables significant at P ⩽ 0·2 in univariable modelling and final random effects logistic regression model of variables associated with a calf being infected with Cryptosporidium spp. at the time of sampling