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MINTIA: a metagenomic INserT integrated assembly and annotation tool

The earth harbors trillions of bacterial species adapted to very diverse ecosystems thanks to specific metabolic function acquisition. Most of the genes responsible for these functions belong to uncultured bacteria and are still to be discovered. Functional metagenomics based on activity screening i...

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Autores principales: Bardou, Philippe, Laguerre, Sandrine, Maman Haddad, Sarah, Legoueix Rodriguez, Sabrina, Laville, Elisabeth, Dumon, Claire, Potocki-Veronese, Gabrielle, Klopp, Christophe
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8483015/
https://www.ncbi.nlm.nih.gov/pubmed/34692239
http://dx.doi.org/10.7717/peerj.11885
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author Bardou, Philippe
Laguerre, Sandrine
Maman Haddad, Sarah
Legoueix Rodriguez, Sabrina
Laville, Elisabeth
Dumon, Claire
Potocki-Veronese, Gabrielle
Klopp, Christophe
author_facet Bardou, Philippe
Laguerre, Sandrine
Maman Haddad, Sarah
Legoueix Rodriguez, Sabrina
Laville, Elisabeth
Dumon, Claire
Potocki-Veronese, Gabrielle
Klopp, Christophe
author_sort Bardou, Philippe
collection PubMed
description The earth harbors trillions of bacterial species adapted to very diverse ecosystems thanks to specific metabolic function acquisition. Most of the genes responsible for these functions belong to uncultured bacteria and are still to be discovered. Functional metagenomics based on activity screening is a classical way to retrieve these genes from microbiomes. This approach is based on the insertion of large metagenomic DNA fragments into a vector and transformation of a host to express heterologous genes. Metagenomic libraries are then screened for activities of interest, and the metagenomic DNA inserts of active clones are extracted to be sequenced and analysed to identify genes that are responsible for the detected activity. Hundreds of metagenomics sequences found using this strategy have already been published in public databases. Here we present the MINTIA software package enabling biologists to easily generate and analyze large metagenomic sequence sets, retrieved after activity-based screening. It filters reads, performs assembly, removes cloning vector, annotates open reading frames and generates user friendly reports as well as files ready for submission to international sequence repositories. The software package can be downloaded from https://github.com/Bios4Biol/MINTIA.
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spelling pubmed-84830152021-10-22 MINTIA: a metagenomic INserT integrated assembly and annotation tool Bardou, Philippe Laguerre, Sandrine Maman Haddad, Sarah Legoueix Rodriguez, Sabrina Laville, Elisabeth Dumon, Claire Potocki-Veronese, Gabrielle Klopp, Christophe PeerJ Biochemistry The earth harbors trillions of bacterial species adapted to very diverse ecosystems thanks to specific metabolic function acquisition. Most of the genes responsible for these functions belong to uncultured bacteria and are still to be discovered. Functional metagenomics based on activity screening is a classical way to retrieve these genes from microbiomes. This approach is based on the insertion of large metagenomic DNA fragments into a vector and transformation of a host to express heterologous genes. Metagenomic libraries are then screened for activities of interest, and the metagenomic DNA inserts of active clones are extracted to be sequenced and analysed to identify genes that are responsible for the detected activity. Hundreds of metagenomics sequences found using this strategy have already been published in public databases. Here we present the MINTIA software package enabling biologists to easily generate and analyze large metagenomic sequence sets, retrieved after activity-based screening. It filters reads, performs assembly, removes cloning vector, annotates open reading frames and generates user friendly reports as well as files ready for submission to international sequence repositories. The software package can be downloaded from https://github.com/Bios4Biol/MINTIA. PeerJ Inc. 2021-09-27 /pmc/articles/PMC8483015/ /pubmed/34692239 http://dx.doi.org/10.7717/peerj.11885 Text en ©2021 Bardou et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Biochemistry
Bardou, Philippe
Laguerre, Sandrine
Maman Haddad, Sarah
Legoueix Rodriguez, Sabrina
Laville, Elisabeth
Dumon, Claire
Potocki-Veronese, Gabrielle
Klopp, Christophe
MINTIA: a metagenomic INserT integrated assembly and annotation tool
title MINTIA: a metagenomic INserT integrated assembly and annotation tool
title_full MINTIA: a metagenomic INserT integrated assembly and annotation tool
title_fullStr MINTIA: a metagenomic INserT integrated assembly and annotation tool
title_full_unstemmed MINTIA: a metagenomic INserT integrated assembly and annotation tool
title_short MINTIA: a metagenomic INserT integrated assembly and annotation tool
title_sort mintia: a metagenomic insert integrated assembly and annotation tool
topic Biochemistry
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8483015/
https://www.ncbi.nlm.nih.gov/pubmed/34692239
http://dx.doi.org/10.7717/peerj.11885
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