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Quantifying the biases in metagenome mining for realistic assessment of microbial ecology of naturally fermented foods

Cultivation-independent investigation of microbial ecology is biased by the DNA extraction methods used. We aimed to quantify those biases by comparative analysis of the metagenome mined from four diverse naturally fermented foods (bamboo shoot, milk, fish, soybean) using eight different DNA extract...

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Autores principales: Keisam, Santosh, Romi, Wahengbam, Ahmed, Giasuddin, Jeyaram, Kumaraswamy
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5037447/
https://www.ncbi.nlm.nih.gov/pubmed/27669673
http://dx.doi.org/10.1038/srep34155
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author Keisam, Santosh
Romi, Wahengbam
Ahmed, Giasuddin
Jeyaram, Kumaraswamy
author_facet Keisam, Santosh
Romi, Wahengbam
Ahmed, Giasuddin
Jeyaram, Kumaraswamy
author_sort Keisam, Santosh
collection PubMed
description Cultivation-independent investigation of microbial ecology is biased by the DNA extraction methods used. We aimed to quantify those biases by comparative analysis of the metagenome mined from four diverse naturally fermented foods (bamboo shoot, milk, fish, soybean) using eight different DNA extraction methods with different cell lysis principles. Our findings revealed that the enzymatic lysis yielded higher eubacterial and yeast metagenomic DNA from the food matrices compared to the widely used chemical and mechanical lysis principles. Further analysis of the bacterial community structure by Illumina MiSeq amplicon sequencing revealed a high recovery of lactic acid bacteria by the enzymatic lysis in all food types. However, Bacillaceae, Acetobacteraceae, Clostridiaceae and Proteobacteria were more abundantly recovered when mechanical and chemical lysis principles were applied. The biases generated due to the differential recovery of operational taxonomic units (OTUs) by different DNA extraction methods including DNA and PCR amplicons mix from different methods have been quantitatively demonstrated here. The different methods shared only 29.9–52.0% of the total OTUs recovered. Although similar comparative research has been performed on other ecological niches, this is the first in-depth investigation of quantifying the biases in metagenome mining from naturally fermented foods.
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spelling pubmed-50374472016-09-30 Quantifying the biases in metagenome mining for realistic assessment of microbial ecology of naturally fermented foods Keisam, Santosh Romi, Wahengbam Ahmed, Giasuddin Jeyaram, Kumaraswamy Sci Rep Article Cultivation-independent investigation of microbial ecology is biased by the DNA extraction methods used. We aimed to quantify those biases by comparative analysis of the metagenome mined from four diverse naturally fermented foods (bamboo shoot, milk, fish, soybean) using eight different DNA extraction methods with different cell lysis principles. Our findings revealed that the enzymatic lysis yielded higher eubacterial and yeast metagenomic DNA from the food matrices compared to the widely used chemical and mechanical lysis principles. Further analysis of the bacterial community structure by Illumina MiSeq amplicon sequencing revealed a high recovery of lactic acid bacteria by the enzymatic lysis in all food types. However, Bacillaceae, Acetobacteraceae, Clostridiaceae and Proteobacteria were more abundantly recovered when mechanical and chemical lysis principles were applied. The biases generated due to the differential recovery of operational taxonomic units (OTUs) by different DNA extraction methods including DNA and PCR amplicons mix from different methods have been quantitatively demonstrated here. The different methods shared only 29.9–52.0% of the total OTUs recovered. Although similar comparative research has been performed on other ecological niches, this is the first in-depth investigation of quantifying the biases in metagenome mining from naturally fermented foods. Nature Publishing Group 2016-09-27 /pmc/articles/PMC5037447/ /pubmed/27669673 http://dx.doi.org/10.1038/srep34155 Text en Copyright © 2016, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Keisam, Santosh
Romi, Wahengbam
Ahmed, Giasuddin
Jeyaram, Kumaraswamy
Quantifying the biases in metagenome mining for realistic assessment of microbial ecology of naturally fermented foods
title Quantifying the biases in metagenome mining for realistic assessment of microbial ecology of naturally fermented foods
title_full Quantifying the biases in metagenome mining for realistic assessment of microbial ecology of naturally fermented foods
title_fullStr Quantifying the biases in metagenome mining for realistic assessment of microbial ecology of naturally fermented foods
title_full_unstemmed Quantifying the biases in metagenome mining for realistic assessment of microbial ecology of naturally fermented foods
title_short Quantifying the biases in metagenome mining for realistic assessment of microbial ecology of naturally fermented foods
title_sort quantifying the biases in metagenome mining for realistic assessment of microbial ecology of naturally fermented foods
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5037447/
https://www.ncbi.nlm.nih.gov/pubmed/27669673
http://dx.doi.org/10.1038/srep34155
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