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TransAAP: an automated annotation pipeline for membrane transporter prediction in bacterial genomes

Membrane transporters are a large group of proteins that span cell membranes and contribute to critical cell processes, including delivery of essential nutrients, ejection of waste products, and assisting the cell in sensing environmental conditions. Obtaining an accurate and specific annotation of...

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Autores principales: Elbourne, Liam D. H., Wilson-Mortier, Brendan, Ren, Qinghu, Hassan, Karl A., Tetu, Sasha G., Paulsen, Ian T.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Microbiology Society 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9973855/
https://www.ncbi.nlm.nih.gov/pubmed/36748555
http://dx.doi.org/10.1099/mgen.0.000927
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author Elbourne, Liam D. H.
Wilson-Mortier, Brendan
Ren, Qinghu
Hassan, Karl A.
Tetu, Sasha G.
Paulsen, Ian T.
author_facet Elbourne, Liam D. H.
Wilson-Mortier, Brendan
Ren, Qinghu
Hassan, Karl A.
Tetu, Sasha G.
Paulsen, Ian T.
author_sort Elbourne, Liam D. H.
collection PubMed
description Membrane transporters are a large group of proteins that span cell membranes and contribute to critical cell processes, including delivery of essential nutrients, ejection of waste products, and assisting the cell in sensing environmental conditions. Obtaining an accurate and specific annotation of the transporter proteins encoded by a micro-organism can provide details of its likely nutritional preferences and environmental niche(s), and identify novel transporters that could be utilized in small molecule production in industrial biotechnology. The Transporter Automated Annotation Pipeline (TransAAP) (http://www.membranetransport.org/transportDB2/TransAAP_login.html) is a fully automated web service for the prediction and annotation of membrane transport proteins in an organism from its genome sequence, by using comparisons with both curated databases such as the TCDB (Transporter Classification Database) and TDB, as well as selected Pfams and TIGRFAMs of transporter families and other methodologies. TransAAP was used to annotate transporter genes in the prokaryotic genomes in the National Center for Biotechnology Information (NCBI) RefSeq; these are presented in the transporter database TransportDB (http://www.membranetransport.org) website, which has a suite of data visualization and analysis tools. Creation and maintenance of a bioinformatic database specific for transporters in all genomic datasets is essential for microbiology research groups and the general research/biotechnology community to obtain a detailed picture of membrane transporter systems in various environments, as well as comprehensive information on specific membrane transport proteins.
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spelling pubmed-99738552023-03-01 TransAAP: an automated annotation pipeline for membrane transporter prediction in bacterial genomes Elbourne, Liam D. H. Wilson-Mortier, Brendan Ren, Qinghu Hassan, Karl A. Tetu, Sasha G. Paulsen, Ian T. Microb Genom Bioresources Membrane transporters are a large group of proteins that span cell membranes and contribute to critical cell processes, including delivery of essential nutrients, ejection of waste products, and assisting the cell in sensing environmental conditions. Obtaining an accurate and specific annotation of the transporter proteins encoded by a micro-organism can provide details of its likely nutritional preferences and environmental niche(s), and identify novel transporters that could be utilized in small molecule production in industrial biotechnology. The Transporter Automated Annotation Pipeline (TransAAP) (http://www.membranetransport.org/transportDB2/TransAAP_login.html) is a fully automated web service for the prediction and annotation of membrane transport proteins in an organism from its genome sequence, by using comparisons with both curated databases such as the TCDB (Transporter Classification Database) and TDB, as well as selected Pfams and TIGRFAMs of transporter families and other methodologies. TransAAP was used to annotate transporter genes in the prokaryotic genomes in the National Center for Biotechnology Information (NCBI) RefSeq; these are presented in the transporter database TransportDB (http://www.membranetransport.org) website, which has a suite of data visualization and analysis tools. Creation and maintenance of a bioinformatic database specific for transporters in all genomic datasets is essential for microbiology research groups and the general research/biotechnology community to obtain a detailed picture of membrane transporter systems in various environments, as well as comprehensive information on specific membrane transport proteins. Microbiology Society 2023-01-18 /pmc/articles/PMC9973855/ /pubmed/36748555 http://dx.doi.org/10.1099/mgen.0.000927 Text en © 2023 The Authors https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License. This article was made open access via a Publish and Read agreement between the Microbiology Society and the corresponding author’s institution.
spellingShingle Bioresources
Elbourne, Liam D. H.
Wilson-Mortier, Brendan
Ren, Qinghu
Hassan, Karl A.
Tetu, Sasha G.
Paulsen, Ian T.
TransAAP: an automated annotation pipeline for membrane transporter prediction in bacterial genomes
title TransAAP: an automated annotation pipeline for membrane transporter prediction in bacterial genomes
title_full TransAAP: an automated annotation pipeline for membrane transporter prediction in bacterial genomes
title_fullStr TransAAP: an automated annotation pipeline for membrane transporter prediction in bacterial genomes
title_full_unstemmed TransAAP: an automated annotation pipeline for membrane transporter prediction in bacterial genomes
title_short TransAAP: an automated annotation pipeline for membrane transporter prediction in bacterial genomes
title_sort transaap: an automated annotation pipeline for membrane transporter prediction in bacterial genomes
topic Bioresources
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9973855/
https://www.ncbi.nlm.nih.gov/pubmed/36748555
http://dx.doi.org/10.1099/mgen.0.000927
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