Metagenomic characterization of swine slurry in a North American swine farm operation
Abstract Modern day large-scale, high-density farming environments are inherently susceptible to viral outbreaks, inadvertently creating conditions that favor increased pathogen transmission and potential zoonotic spread. Metagenomic sequencing has proven to be a useful tool for characterizing the m...
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Nature Portfolio
2021
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oai:doaj.org-article:64a79984c7984b568d14762ba0b264f12021-12-02T17:08:35ZMetagenomic characterization of swine slurry in a North American swine farm operation10.1038/s41598-021-95804-y2045-2322https://doaj.org/article/64a79984c7984b568d14762ba0b264f12021-08-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-95804-yhttps://doaj.org/toc/2045-2322Abstract Modern day large-scale, high-density farming environments are inherently susceptible to viral outbreaks, inadvertently creating conditions that favor increased pathogen transmission and potential zoonotic spread. Metagenomic sequencing has proven to be a useful tool for characterizing the microbial burden in both people, livestock, and environmental samples. International efforts have been successful at characterizing pathogens in commercial farming environments, especially swine farms, however it is unclear whether the full extent of microbial agents have been adequately captured or is representative of farms elsewhere. To augment international efforts we performed metagenomic next-generation sequencing on nine swine slurry and three environmental samples from a United States of America (U.S.A.) farm operation, characterized the microbial composition of slurry, and identified novel viruses. We assembled a remarkable total of 1792 viral genomes, of which 554 were novel/divergent. We assembled 1637 Picobirnavirus genome segments, of which 538 are novel. In addition, we discovered 10 new viruses belonging to a novel taxon: porcine Statoviruses; which have only been previously reported in human, macaques, mouse, and cows. We assembled 3 divergent Posaviruses and 3 swine Picornaviruses. In addition to viruses described, we found other eukaryotic genera such as Entamoeba and Blastocystis, and bacterial genera such as Listeria, Treponema, Peptoclostridium and Bordetella in the slurry. Of these, two species Entamoeba histolytica and Listeria monocytogenes known to cause human disease were detected. Further, antimicrobial resistance genes such as tetracycline and MLS (macrolide, lincosamide, streptogramin) were also identified. Metagenomic surveillance in swine fecal slurry has great potential for novel and antimicrobial resistant pathogen detection.Akshaya RameshEmily S. BaileyVida AhyongCharles LangelierMaira PhelpsNorma NeffRene SitCristina TatoJoseph L. DeRisiAnnette G. GreerGregory C. GrayNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-9 (2021) |
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Medicine R Science Q Akshaya Ramesh Emily S. Bailey Vida Ahyong Charles Langelier Maira Phelps Norma Neff Rene Sit Cristina Tato Joseph L. DeRisi Annette G. Greer Gregory C. Gray Metagenomic characterization of swine slurry in a North American swine farm operation |
description |
Abstract Modern day large-scale, high-density farming environments are inherently susceptible to viral outbreaks, inadvertently creating conditions that favor increased pathogen transmission and potential zoonotic spread. Metagenomic sequencing has proven to be a useful tool for characterizing the microbial burden in both people, livestock, and environmental samples. International efforts have been successful at characterizing pathogens in commercial farming environments, especially swine farms, however it is unclear whether the full extent of microbial agents have been adequately captured or is representative of farms elsewhere. To augment international efforts we performed metagenomic next-generation sequencing on nine swine slurry and three environmental samples from a United States of America (U.S.A.) farm operation, characterized the microbial composition of slurry, and identified novel viruses. We assembled a remarkable total of 1792 viral genomes, of which 554 were novel/divergent. We assembled 1637 Picobirnavirus genome segments, of which 538 are novel. In addition, we discovered 10 new viruses belonging to a novel taxon: porcine Statoviruses; which have only been previously reported in human, macaques, mouse, and cows. We assembled 3 divergent Posaviruses and 3 swine Picornaviruses. In addition to viruses described, we found other eukaryotic genera such as Entamoeba and Blastocystis, and bacterial genera such as Listeria, Treponema, Peptoclostridium and Bordetella in the slurry. Of these, two species Entamoeba histolytica and Listeria monocytogenes known to cause human disease were detected. Further, antimicrobial resistance genes such as tetracycline and MLS (macrolide, lincosamide, streptogramin) were also identified. Metagenomic surveillance in swine fecal slurry has great potential for novel and antimicrobial resistant pathogen detection. |
format |
article |
author |
Akshaya Ramesh Emily S. Bailey Vida Ahyong Charles Langelier Maira Phelps Norma Neff Rene Sit Cristina Tato Joseph L. DeRisi Annette G. Greer Gregory C. Gray |
author_facet |
Akshaya Ramesh Emily S. Bailey Vida Ahyong Charles Langelier Maira Phelps Norma Neff Rene Sit Cristina Tato Joseph L. DeRisi Annette G. Greer Gregory C. Gray |
author_sort |
Akshaya Ramesh |
title |
Metagenomic characterization of swine slurry in a North American swine farm operation |
title_short |
Metagenomic characterization of swine slurry in a North American swine farm operation |
title_full |
Metagenomic characterization of swine slurry in a North American swine farm operation |
title_fullStr |
Metagenomic characterization of swine slurry in a North American swine farm operation |
title_full_unstemmed |
Metagenomic characterization of swine slurry in a North American swine farm operation |
title_sort |
metagenomic characterization of swine slurry in a north american swine farm operation |
publisher |
Nature Portfolio |
publishDate |
2021 |
url |
https://doaj.org/article/64a79984c7984b568d14762ba0b264f1 |
work_keys_str_mv |
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