Evaluation of next generation sequencing for the analysis of Eimeria communities in wildlife

Elke T. Vermeulen*, Matthew J. Lott, Mark D B Eldridge, Michelle L. Power

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)


Next-generation sequencing (NGS) techniques are well-established for studying bacterial communities but not yet for microbial eukaryotes. Parasite communities remain poorly studied, due in part to the lack of reliable and accessible molecular methods to analyse eukaryotic communities. We aimed to develop and evaluate a methodology to analyse communities of the protozoan parasite Eimeria from populations of the Australian marsupial Petrogale penicillata (brush-tailed rock-wallaby) using NGS. An oocyst purification method for small sample sizes and polymerase chain reaction (PCR) protocol for the 18S rRNA locus targeting Eimeria was developed and optimised prior to sequencing on the Illumina MiSeq platform. A data analysis approach was developed by modifying methods from bacterial metagenomics and utilising existing Eimeria sequences in GenBank. Operational taxonomic unit (OTU) assignment at a high similarity threshold (97%) was more accurate at assigning Eimeria contigs into Eimeria OTUs but at a lower threshold (95%) there was greater resolution between OTU consensus sequences. The assessment of two amplification PCR methods prior to Illumina MiSeq, single and nested PCR, determined that single PCR was more sensitive to Eimeria as more Eimeria OTUs were detected in single amplicons. We have developed a simple and cost-effective approach to a data analysis pipeline for community analysis of eukaryotic organisms using Eimeria communities as a model. The pipeline provides a basis for evaluation using other eukaryotic organisms and potential for diverse community analysis studies.

Original languageEnglish
Pages (from-to)1-9
Number of pages9
JournalJournal of Microbiological Methods
Publication statusPublished - 1 May 2016


  • Next generation sequencing
  • Microbial eukaryotes
  • Eimeria
  • Community analysis
  • Data analysis
  • Wildlife


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