Abstract

Piroplasmosis is an important disease of domestic animals and wildlife and is caused by organisms from the genera Theileria and Babesia. Wildlife such as sika deer play an important role as reservoir hosts for several species of Theileria and Babesia. Using blood samples collected from sika deer, we investigated the epidemiology of Theileria spp. and Babesia spp. in sika deer from Jilin Province in China and identified those species that cause pathogenic infections in sika deer. Sixty-eight blood samples of sika deer were collected from three areas of the Jilin Province in Northeast China. Genomic DNA was extracted, and the V4 hypervariable region of the 18S rRNA of the piroplasms was amplified using the nested PCR method. The selected positive samples were sequenced to identify species of Babesia and Theileria. PCR detection revealed that 24 samples were positive for Theileria and Babesia spp. (35.29 %, 95 % CI = 11.8-46.8). After alignment, a sequenced fragment for Theileria cervi was found to be the most prevalent from the obtained samples (22.06 %, 95 % CI = 11.8-49.6). Six sika deer samples were identified as being infected with a Theileria sp. that was similar to a Theileria sp. found from spotted deer in India. In addition to the results above, for the first time, we identified T. annulata infection from one sample of sika deer and Babesia sp. from two samples, which showed high identity with Babesia motasi found in sheep from China. The present study offers new data on the pathogens of piroplasmosis in sika deer in northeastern China. For the first time, sika deer was confirmed as a reservoir host for the T. annulata of cattle and the B. motasi of sheep, which was found in China.

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Introduction

Erratum the original version of this article [1] contained an error. Within the results section, and in Fig. 1, the accession numbers KT683524-KT683536 should be KT863524-KT863536. Erratum to: Molecular detection and identification of piroplasms in sika deer (Cervus nippon) from Jilin Province, China Junlong Liu1,2*, Jifei Yang1,2, Guiquan Guan1,2, Aihong Liu1,2, Bingjie Wang1,2, Jianxun Luo1,2 and Hong Yin1,2

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