Metabarcoding using nanopore long-read sequencing for the unbiased characterization of apicomplexan haemoparasites

Abstract

Apicomplexan haemoparasites generate significant morbidity and mortality in humans and other animals, particularly in many low-to-middle income countries. Malaria caused by Plasmodium remains responsible for some of the highest numbers of annual deaths of any human pathogen, whilst piroplasmids, such as Babesia and Theileria can have immense negative economic effects through livestock loss. Diagnosing haemoparasites via traditional methods like microscopy is challenging due to low-level and transient parasitaemia. PCR-based diagnostics overcome these limitations by being both highly sensitive and specific, but they may be unable to accurately detect coinfections or identify novel species. In contrast, next-generation sequencing (NGS)-based methods can characterize all pathogens from a group of interest concurrently, although, the short-read platforms previously used have been limited in the taxonomic resolution achievable. Here, we used Oxford Nanopore Technologies' (ONT) long-read MinION™ sequencer to conduct apicomplexan haemoparasite metabarcoding via sequencing the near full-length 18S ribosomal RNA gene, demonstrating its ability to detect Babesia, Hepatozoon, Neospora, Plasmodium, Theileria and Toxoplasma species. This method was tested on blood-extracted DNA from 100 dogs and the results benchmarked against qPCR and Illumina-based metabarcoding. For two common haemoparasites, nanopore sequencing performed as well as qPCR (kappa agreement statistics > 0.98), whilst also detecting one pathogen, Hepatozoon felis, missed by the other techniques. The long-reads obtained by nanopore sequencing provide an improved species-level taxonomic resolution whilst the method's broad applicability mean it can be used to explore apicomplexan communities from diverse mammalian hosts, on a portable sequencer that easily permits adaptation to field use.