Tick diversity and pathogen infection in Khao Chi-On non hunting area and banglamung wildlife breeding center, Chonburi province, Thailand

Abstract

Ixodid ticks are important vectors in the transmission cycle of various tick-borne diseases in both humans and animals. Wildlife are considered important reservoirs of these diseases. This study aims to examine tick diversity, and tick-borne protozoal and bacterial infection in questing ticks in wildlife habitats by using PCR and DNA sequencing techniques. In 2015, questing ixodid ticks were collected from Khao Chi-On Non Hunting Area and Banglamung Wildlife Breeding Center, Chonburi province. All 12,184 ticks were identified using morphological characteristics and representative ticks were confirmed species by PCR that targeted tick mitochondrial 16S rRNA gene. Three tick species were identified including Haemaphysalis lagrangei (92.82%), H. wellingtoni (0.13%), and Rhipicephalus (Boophilus) microplus (7.05%). Totally, 419 tick samples (Individual adult and nymph, and pooled larvae) were examined by using PCR which amplified a fragment of 18S rRNA gene of Babesia and Theileria, and 16S rRNA gene of bacteria in family Anaplasmataceae. Out of 419 analyzed tick samples, four pathogens and one bacterial symbiont were detected, with the highest infection rate of Anaplasma spp. at 55.61% (233/419) with three genotype groups including Anaplasma closely related to A. bovis, A. platys, and unidentified Anaplasma. While Theileria spp. had lower infection rate at 4.30% (18/419) with three genotypes consisted of Theileria closely related to T. cervi, T. capreoli, and unidentified Theileria, and only one sequence (1/419; 0.24%) of Babesia spp., Ehrlichia spp. and Wolbachia spp. were detected. These findings provided the information of tick diversity in wildlife habitats, and the association with detected tick-borne protozoa and bacteria. It suggested the evidences that these tick species are possible vectors to transmit tick-borne diseases in forest of Thailand. Furthermore, these data would be useful for designing treatment, prevention, and control strategies of tick-borne diseases.