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HumanMycobiomeScan: a new bioinformatics tool for the characterization of the fungal fraction in metagenomic samples
BACKGROUND: Modern metagenomic analysis of complex microbial communities produces large amounts of sequence data containing information on the microbiome in terms of bacterial, archaeal, viral and eukaryotic composition. The bioinformatics tools available are mainly devoted to profiling the bacteria...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6570844/ https://www.ncbi.nlm.nih.gov/pubmed/31202277 http://dx.doi.org/10.1186/s12864-019-5883-y |
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author | Soverini, Matteo Turroni, Silvia Biagi, Elena Brigidi, Patrizia Candela, Marco Rampelli, Simone |
author_facet | Soverini, Matteo Turroni, Silvia Biagi, Elena Brigidi, Patrizia Candela, Marco Rampelli, Simone |
author_sort | Soverini, Matteo |
collection | PubMed |
description | BACKGROUND: Modern metagenomic analysis of complex microbial communities produces large amounts of sequence data containing information on the microbiome in terms of bacterial, archaeal, viral and eukaryotic composition. The bioinformatics tools available are mainly devoted to profiling the bacterial and viral fractions and only a few software packages consider fungi. As the human fungal microbiome (human mycobiome) can play an important role in the onset and progression of diseases, a comprehensive description of host-microbiota interactions cannot ignore this component. RESULTS: HumanMycobiomeScan is a bioinformatics tool for the taxonomic profiling of the mycobiome directly from raw data of next-generation sequencing. The tool uses hierarchical databases of fungi in order to unambiguously assign reads to fungal species more accurately and > 10,000 times faster than other comparable approaches. HumanMycobiomeScan was validated using in silico generated synthetic communities and then applied to metagenomic data, to characterize the intestinal fungal components in subjects adhering to different subsistence strategies. CONCLUSIONS: Although blind to unknown species, HumanMycobiomeScan allows the characterization of the fungal fraction of complex microbial ecosystems with good performance in terms of sample denoising from reads belonging to other microorganisms. HumanMycobiomeScan is most appropriate for well-studied microbiomes, for which most of the fungal species have been fully sequenced. This released version is functionally implemented to work with human-associated microbiota samples. In combination with other microbial profiling tools, HumanMycobiomeScan is a frugal and efficient tool for comprehensive characterization of microbial ecosystems through shotgun metagenomics sequencing. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12864-019-5883-y) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6570844 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-65708442019-06-27 HumanMycobiomeScan: a new bioinformatics tool for the characterization of the fungal fraction in metagenomic samples Soverini, Matteo Turroni, Silvia Biagi, Elena Brigidi, Patrizia Candela, Marco Rampelli, Simone BMC Genomics Software BACKGROUND: Modern metagenomic analysis of complex microbial communities produces large amounts of sequence data containing information on the microbiome in terms of bacterial, archaeal, viral and eukaryotic composition. The bioinformatics tools available are mainly devoted to profiling the bacterial and viral fractions and only a few software packages consider fungi. As the human fungal microbiome (human mycobiome) can play an important role in the onset and progression of diseases, a comprehensive description of host-microbiota interactions cannot ignore this component. RESULTS: HumanMycobiomeScan is a bioinformatics tool for the taxonomic profiling of the mycobiome directly from raw data of next-generation sequencing. The tool uses hierarchical databases of fungi in order to unambiguously assign reads to fungal species more accurately and > 10,000 times faster than other comparable approaches. HumanMycobiomeScan was validated using in silico generated synthetic communities and then applied to metagenomic data, to characterize the intestinal fungal components in subjects adhering to different subsistence strategies. CONCLUSIONS: Although blind to unknown species, HumanMycobiomeScan allows the characterization of the fungal fraction of complex microbial ecosystems with good performance in terms of sample denoising from reads belonging to other microorganisms. HumanMycobiomeScan is most appropriate for well-studied microbiomes, for which most of the fungal species have been fully sequenced. This released version is functionally implemented to work with human-associated microbiota samples. In combination with other microbial profiling tools, HumanMycobiomeScan is a frugal and efficient tool for comprehensive characterization of microbial ecosystems through shotgun metagenomics sequencing. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12864-019-5883-y) contains supplementary material, which is available to authorized users. BioMed Central 2019-06-15 /pmc/articles/PMC6570844/ /pubmed/31202277 http://dx.doi.org/10.1186/s12864-019-5883-y Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Software Soverini, Matteo Turroni, Silvia Biagi, Elena Brigidi, Patrizia Candela, Marco Rampelli, Simone HumanMycobiomeScan: a new bioinformatics tool for the characterization of the fungal fraction in metagenomic samples |
title | HumanMycobiomeScan: a new bioinformatics tool for the characterization of the fungal fraction in metagenomic samples |
title_full | HumanMycobiomeScan: a new bioinformatics tool for the characterization of the fungal fraction in metagenomic samples |
title_fullStr | HumanMycobiomeScan: a new bioinformatics tool for the characterization of the fungal fraction in metagenomic samples |
title_full_unstemmed | HumanMycobiomeScan: a new bioinformatics tool for the characterization of the fungal fraction in metagenomic samples |
title_short | HumanMycobiomeScan: a new bioinformatics tool for the characterization of the fungal fraction in metagenomic samples |
title_sort | humanmycobiomescan: a new bioinformatics tool for the characterization of the fungal fraction in metagenomic samples |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6570844/ https://www.ncbi.nlm.nih.gov/pubmed/31202277 http://dx.doi.org/10.1186/s12864-019-5883-y |
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