Application of next generation sequencing for detection of protozoan pathogens in shellfish

Catherine DeMone, Mei Hua Hwang, Zeny Feng, J. Trenton McClure, Spencer J. Greenwood, Rebecca Fung, Minji Kim, J. Scott Weese, Karen Shapiro

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Food and waterborne protozoan pathogens can cause serious disease in people. Three common species Cryptosporidium parvum, Giardia enterica and Toxoplasma gondii can contaminate diverse shellfish species, including commercial oysters. Current methods of protozoan detection in shellfish are not standardized, and few are able to simultaneously identify multiple species. Here, we present a novel metabarcoding assay targeting the 18S rRNA gene followed by next generation sequencing (NGS) for simultaneous detection of Cryptosporidium spp., Giardia spp. and T. gondii spiked into oyster samples. We further developed a bioinformatic pipeline to process and analyze 18S rRNA data for protozoa classification. The ability of the NGS assay to detect protozoa was later compared with conventional PCR. Results demonstrated that background amplification of oyster and other eukaryotic DNA competed with that of protozoa for obtained sequence reads. Sequences of target protozoans were obtained across all spiking levels; however, low numbers of target sequences in negative controls imply that a threshold for true positives must be defined for assay interpretation. While this study focused on three target parasites, the ability of this approach to detect numerous known and potentially unknown protozoan pathogens make it a promising screening tool for monitoring protozoan contamination in food and water.

Original languageEnglish (US)
Article numbere00096
JournalFood and Waterborne Parasitology
Volume21
DOIs
StatePublished - Dec 2020
Externally publishedYes

Keywords

  • 18S rRNA
  • Cryptosporidium parvum
  • Giardia enterica
  • Metabarcoding
  • Oysters
  • Toxoplasma gondii

ASJC Scopus subject areas

  • Parasitology
  • Epidemiology

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