Nodeomics: Pathogen detection in vertebrate lymph nodes using meta-transcriptomics

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Abstract

The ongoing emergence of human infections originating from wildlife highlights the need for better knowledge of the microbial community in wildlife species where traditional diagnostic approaches are limited. Here we evaluate the microbial biota in healthy mule deer (Odocoileus hemionus) by analyses of lymph node meta-transcriptomes. cDNA libraries from five individuals and two pools of samples were prepared from retropharyngeal lymph node RNA enriched for polyadenylated RNA and sequenced using Roche-454 Life Sciences technology. Protein-coding and 16S ribosomal RNA (rRNA) sequences were taxonomically profiled using protein and rRNA specific databases. Representatives of all bacterial phyla were detected in the seven libraries based on protein-coding transcripts indicating that viable microbiota were present in lymph nodes. Residents of skin and rumen, and those ubiquitous in mule deer habitat dominated classifiable bacterial species. Based on detection of both rRNA and protein-coding transcripts, we identified two new proteobacterial species; a Helicobacter closely related to Helicobacter cetorum in the Helicobacter pylori/Helicobacter acinonychis complex and an Acinetobacter related to Acinetobacter schindleri. Among viruses, a novel gamma retrovirus and other members of the Poxviridae and Retroviridae were identified. We additionally evaluated bacterial diversity by amplicon sequencing the hypervariable V6 region of 16S rRNA and demonstrate that overall taxonomic diversity is higher with the meta-transcriptomic approach. These data provide the most complete picture to date of the microbial diversity within a wildlife host. Our research advances the use of meta-transcriptomics to study microbiota in wildlife tissues, which will facilitate detection of novel organisms with pathogenic potential to human and animals.
Publication type Article
Publication Subtype Journal Article
Title Nodeomics: Pathogen detection in vertebrate lymph nodes using meta-transcriptomics
Series title PLoS
DOI 10.1371/journal.pone.0013432
Volume 5
Issue 10
Year Published 2010
Language English
Publisher PloS
Contributing office(s) Northern Rocky Mountain Science Center, Contaminant Biology Program
Description e13432; 10 p.
First page 1
Last page 10
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