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Plant RNA Virus Sequences Identified in Kimchi by Microbial Metatranscriptome Analysis

  • Kim, Dong Seon (Department of Life Science, Research Center for Biomolecules and Biosystems, Chung-Ang University) ;
  • Jung, Ji Young (Department of Life Science, Research Center for Biomolecules and Biosystems, Chung-Ang University) ;
  • Wang, Yao (Department of Life Science, Research Center for Biomolecules and Biosystems, Chung-Ang University) ;
  • Oh, Hye Ji (Department of Life Science, Research Center for Biomolecules and Biosystems, Chung-Ang University) ;
  • Choi, Dongjin (Department of Life Science, Research Center for Biomolecules and Biosystems, Chung-Ang University) ;
  • Jeon, Che Ok (Department of Life Science, Research Center for Biomolecules and Biosystems, Chung-Ang University) ;
  • Hahn, Yoonsoo (Department of Life Science, Research Center for Biomolecules and Biosystems, Chung-Ang University)
  • Received : 2014.04.10
  • Accepted : 2014.05.16
  • Published : 2014.07.28

Abstract

Plant pathogenic RNA viruses are present in a variety of plant-based foods. When ingested by humans, these viruses can survive the passage through the digestive tract, and are frequently detected in human feces. Kimchi is a traditional fermented Korean food made from cabbage or vegetables, with a variety of other plant-based ingredients, including ground red pepper and garlic paste. We analyzed microbial metatranscriptome data from kimchi at five fermentation stages to identify plant RNA virus-derived sequences. We successfully identified a substantial amount of plant RNA virus sequences, especially during the early stages of fermentation: 23.47% and 16.45% of total clean reads on days 7 and 13, respectively. The most abundant plant RNA virus sequences were from pepper mild mottle virus, a major pathogen of red peppers; this constituted 95% of the total RNA virus sequences identified throughout the fermentation period. We observed distinct sequencing read-depth distributions for plant RNA virus genomes, possibly implying intrinsic and/or technical biases during the metatranscriptome generation procedure. We also identified RNA virus sequences in publicly available microbial metatranscriptome data sets. We propose that metatranscriptome data may serve as a valuable resource for RNA virus detection, and a systematic screening of the ingredients may help prevent the use of virus-infected low-quality materials for food production.

Keywords

References

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