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Identification of fungi in shotgun metagenomics datasets
Metagenomics uses nucleic acid sequencing to characterize species diversity in different niches such as environmental biomes or the human microbiome. Most studies have used 16S rRNA amplicon sequencing to identify bacteria. However, the decreasing cost of sequencing has resulted in a gradual shift a...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5812651/ https://www.ncbi.nlm.nih.gov/pubmed/29444186 http://dx.doi.org/10.1371/journal.pone.0192898 |
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author | Donovan, Paul D. Gonzalez, Gabriel Higgins, Desmond G. Butler, Geraldine Ito, Kimihito |
author_facet | Donovan, Paul D. Gonzalez, Gabriel Higgins, Desmond G. Butler, Geraldine Ito, Kimihito |
author_sort | Donovan, Paul D. |
collection | PubMed |
description | Metagenomics uses nucleic acid sequencing to characterize species diversity in different niches such as environmental biomes or the human microbiome. Most studies have used 16S rRNA amplicon sequencing to identify bacteria. However, the decreasing cost of sequencing has resulted in a gradual shift away from amplicon analyses and towards shotgun metagenomic sequencing. Shotgun metagenomic data can be used to identify a wide range of species, but have rarely been applied to fungal identification. Here, we develop a sequence classification pipeline, FindFungi, and use it to identify fungal sequences in public metagenome datasets. We focus primarily on animal metagenomes, especially those from pig and mouse microbiomes. We identified fungi in 39 of 70 datasets comprising 71 fungal species. At least 11 pathogenic species with zoonotic potential were identified, including Candida tropicalis. We identified Pseudogymnoascus species from 13 Antarctic soil samples initially analyzed for the presence of bacteria capable of degrading diesel oil. We also show that Candida tropicalis and Candida loboi are likely the same species. In addition, we identify several examples where contaminating DNA was erroneously included in fungal genome assemblies. |
format | Online Article Text |
id | pubmed-5812651 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-58126512018-02-28 Identification of fungi in shotgun metagenomics datasets Donovan, Paul D. Gonzalez, Gabriel Higgins, Desmond G. Butler, Geraldine Ito, Kimihito PLoS One Research Article Metagenomics uses nucleic acid sequencing to characterize species diversity in different niches such as environmental biomes or the human microbiome. Most studies have used 16S rRNA amplicon sequencing to identify bacteria. However, the decreasing cost of sequencing has resulted in a gradual shift away from amplicon analyses and towards shotgun metagenomic sequencing. Shotgun metagenomic data can be used to identify a wide range of species, but have rarely been applied to fungal identification. Here, we develop a sequence classification pipeline, FindFungi, and use it to identify fungal sequences in public metagenome datasets. We focus primarily on animal metagenomes, especially those from pig and mouse microbiomes. We identified fungi in 39 of 70 datasets comprising 71 fungal species. At least 11 pathogenic species with zoonotic potential were identified, including Candida tropicalis. We identified Pseudogymnoascus species from 13 Antarctic soil samples initially analyzed for the presence of bacteria capable of degrading diesel oil. We also show that Candida tropicalis and Candida loboi are likely the same species. In addition, we identify several examples where contaminating DNA was erroneously included in fungal genome assemblies. Public Library of Science 2018-02-14 /pmc/articles/PMC5812651/ /pubmed/29444186 http://dx.doi.org/10.1371/journal.pone.0192898 Text en © 2018 Donovan et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Donovan, Paul D. Gonzalez, Gabriel Higgins, Desmond G. Butler, Geraldine Ito, Kimihito Identification of fungi in shotgun metagenomics datasets |
title | Identification of fungi in shotgun metagenomics datasets |
title_full | Identification of fungi in shotgun metagenomics datasets |
title_fullStr | Identification of fungi in shotgun metagenomics datasets |
title_full_unstemmed | Identification of fungi in shotgun metagenomics datasets |
title_short | Identification of fungi in shotgun metagenomics datasets |
title_sort | identification of fungi in shotgun metagenomics datasets |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5812651/ https://www.ncbi.nlm.nih.gov/pubmed/29444186 http://dx.doi.org/10.1371/journal.pone.0192898 |
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