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

Research output: Contribution to journalArticleResearchpeer-review

Abstract

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.

LanguageEnglish
Pages1-9
Number of pages9
JournalJournal of Microbiological Methods
Volume124
DOIs
Publication statusPublished - 1 May 2016

Fingerprint

Eimeria
Macropodidae
Polymerase Chain Reaction
Parasites
Metagenomics
Marsupialia
Oocysts
Nucleic Acid Databases
Consensus Sequence
Eukaryota
Sample Size
Costs and Cost Analysis

Keywords

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

Cite this

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abstract = "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.",
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Evaluation of next generation sequencing for the analysis of Eimeria communities in wildlife. / Vermeulen, Elke T.; Lott, Matthew J.; Eldridge, Mark D B; Power, Michelle L.

In: Journal of Microbiological Methods, Vol. 124, 01.05.2016, p. 1-9.

Research output: Contribution to journalArticleResearchpeer-review

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