Targeted Next-Generation Sequencing and Informatics as an Effective Tool to Establish the Composition of Bovine Piroplasm Populations in Endemic Regions.

Abstract

Protists of the genera Babesia and Theileria (piroplasms) cause some of the most prevalent and debilitating diseases for bovines worldwide. In this study, we established and used a next-generation sequencing-informatic approach to explore the composition of Babesia and Theileria populations in cattle and water buffalo in a country (Pakistan) endemic for these pathogens. We collected individual blood samples from cattle (n = 212) and water buffalo (n = 154), extracted genomic DNAs, PCR-amplified the V4 hypervariable region of 18S small subunit rRNA gene from piroplasms, sequenced amplicons using Illumina technology, and then analysed data using bioinformatic platforms. The results revealed piroplasms in 68.9% (252/366) samples, with overall occurrence being markedly higher in cattle (85.8%) than in water buffaloes (45.5%). Babesia (B.) occultans and Theileria (T.) lestoquardi-like species were recorded for the first time in Pakistan, and, overall, T. annulata was most commonly detected (65.8%) followed by B. bovis (7.1%), B. bigemina (4.4%), and T. orientalis (0.5%), with the genetic variability within B. bovis being pronounced. The occurrence and composition of piroplasm species varied markedly across different agro-ecological zones. The high detection of T. annulata in asymptomatic animals suggested a relatively high level of endemic stability of tropical theileriosis in the bovine population.