ABSTRACT
The World Health Organization (WHO) and the Food and Agriculture Organization (FAO) have developed strategies to control trypanosomiasis in humans and livestock in endemic areas. These require a better understanding of the distribution of different Trypanosoma species and improved predictions of where they might appear in the future, based on accurate diagnosis and robust surveillance systems. Here, we describe a metabarcoding deep amplicon sequencing method to identify and determine the Trypanosoma species in co-infecting communities. First, four morphological verified Trypanosoma species (T. brucei, T. congolense, T. vivax and T. theileri) were used to prepare test DNA pools derived from different numbers of parasites to evaluate the method's detection threshold for each of the four species and to assess the accuracy of their proportional quantification. Having demonstrated the accurate determination of species composition in Trypanosoma communities, the method was applied to determine its detection threshold using blood samples collected from cattle with confirmed Trypanosoma infections based on a PCR assay. Each sample showed a different Trypanosoma species composition based on the proportion of MiSeq reads. Finally, we applied the assay to field samples to develop new insight into the species composition of Trypanosoma communities in cattle, camels, buffalo, horses, sheep, and goat in endemically infected regions of Pakistan. We confirmed that Trypanosoma evansi is the major species in Pakistan and for the first time showed the presence of Trypanosoma theileri. The metabarcoding deep amplicon sequencing method and bioinformatics pathway have several potential applications in animal and human research, including evaluation of drug treatment responses, understanding of the emergence and spread of drug resistance, and description of species interactions during co-infections and determination of host and geographic distribution of trypanosomiasis in humans and livestock.
