Cargando…

Survey of metaproteomics software tools for functional microbiome analysis

To gain a thorough appreciation of microbiome dynamics, researchers characterize the functional relevance of expressed microbial genes or proteins. This can be accomplished through metaproteomics, which characterizes the protein expression of microbiomes. Several software tools exist for analyzing m...

Descripción completa

Detalles Bibliográficos
Autores principales: Sajulga, Ray, Easterly, Caleb, Riffle, Michael, Mesuere, Bart, Muth, Thilo, Mehta, Subina, Kumar, Praveen, Johnson, James, Gruening, Bjoern Andreas, Schiebenhoefer, Henning, Kolmeder, Carolin A., Fuchs, Stephan, Nunn, Brook L., Rudney, Joel, Griffin, Timothy J., Jagtap, Pratik D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7654790/
https://www.ncbi.nlm.nih.gov/pubmed/33170893
http://dx.doi.org/10.1371/journal.pone.0241503
_version_ 1783608118206267392
author Sajulga, Ray
Easterly, Caleb
Riffle, Michael
Mesuere, Bart
Muth, Thilo
Mehta, Subina
Kumar, Praveen
Johnson, James
Gruening, Bjoern Andreas
Schiebenhoefer, Henning
Kolmeder, Carolin A.
Fuchs, Stephan
Nunn, Brook L.
Rudney, Joel
Griffin, Timothy J.
Jagtap, Pratik D.
author_facet Sajulga, Ray
Easterly, Caleb
Riffle, Michael
Mesuere, Bart
Muth, Thilo
Mehta, Subina
Kumar, Praveen
Johnson, James
Gruening, Bjoern Andreas
Schiebenhoefer, Henning
Kolmeder, Carolin A.
Fuchs, Stephan
Nunn, Brook L.
Rudney, Joel
Griffin, Timothy J.
Jagtap, Pratik D.
author_sort Sajulga, Ray
collection PubMed
description To gain a thorough appreciation of microbiome dynamics, researchers characterize the functional relevance of expressed microbial genes or proteins. This can be accomplished through metaproteomics, which characterizes the protein expression of microbiomes. Several software tools exist for analyzing microbiomes at the functional level by measuring their combined proteome-level response to environmental perturbations. In this survey, we explore the performance of six available tools, to enable researchers to make informed decisions regarding software choice based on their research goals. Tandem mass spectrometry-based proteomic data obtained from dental caries plaque samples grown with and without sucrose in paired biofilm reactors were used as representative data for this evaluation. Microbial peptides from one sample pair were identified by the X! tandem search algorithm via SearchGUI and subjected to functional analysis using software tools including eggNOG-mapper, MEGAN5, MetaGOmics, MetaProteomeAnalyzer (MPA), ProPHAnE, and Unipept to generate functional annotation through Gene Ontology (GO) terms. Among these software tools, notable differences in functional annotation were detected after comparing differentially expressed protein functional groups. Based on the generated GO terms of these tools we performed a peptide-level comparison to evaluate the quality of their functional annotations. A BLAST analysis against the NCBI non-redundant database revealed that the sensitivity and specificity of functional annotation varied between tools. For example, eggNOG-mapper mapped to the most number of GO terms, while Unipept generated more accurate GO terms. Based on our evaluation, metaproteomics researchers can choose the software according to their analytical needs and developers can use the resulting feedback to further optimize their algorithms. To make more of these tools accessible via scalable metaproteomics workflows, eggNOG-mapper and Unipept 4.0 were incorporated into the Galaxy platform.
format Online
Article
Text
id pubmed-7654790
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-76547902020-11-18 Survey of metaproteomics software tools for functional microbiome analysis Sajulga, Ray Easterly, Caleb Riffle, Michael Mesuere, Bart Muth, Thilo Mehta, Subina Kumar, Praveen Johnson, James Gruening, Bjoern Andreas Schiebenhoefer, Henning Kolmeder, Carolin A. Fuchs, Stephan Nunn, Brook L. Rudney, Joel Griffin, Timothy J. Jagtap, Pratik D. PLoS One Research Article To gain a thorough appreciation of microbiome dynamics, researchers characterize the functional relevance of expressed microbial genes or proteins. This can be accomplished through metaproteomics, which characterizes the protein expression of microbiomes. Several software tools exist for analyzing microbiomes at the functional level by measuring their combined proteome-level response to environmental perturbations. In this survey, we explore the performance of six available tools, to enable researchers to make informed decisions regarding software choice based on their research goals. Tandem mass spectrometry-based proteomic data obtained from dental caries plaque samples grown with and without sucrose in paired biofilm reactors were used as representative data for this evaluation. Microbial peptides from one sample pair were identified by the X! tandem search algorithm via SearchGUI and subjected to functional analysis using software tools including eggNOG-mapper, MEGAN5, MetaGOmics, MetaProteomeAnalyzer (MPA), ProPHAnE, and Unipept to generate functional annotation through Gene Ontology (GO) terms. Among these software tools, notable differences in functional annotation were detected after comparing differentially expressed protein functional groups. Based on the generated GO terms of these tools we performed a peptide-level comparison to evaluate the quality of their functional annotations. A BLAST analysis against the NCBI non-redundant database revealed that the sensitivity and specificity of functional annotation varied between tools. For example, eggNOG-mapper mapped to the most number of GO terms, while Unipept generated more accurate GO terms. Based on our evaluation, metaproteomics researchers can choose the software according to their analytical needs and developers can use the resulting feedback to further optimize their algorithms. To make more of these tools accessible via scalable metaproteomics workflows, eggNOG-mapper and Unipept 4.0 were incorporated into the Galaxy platform. Public Library of Science 2020-11-10 /pmc/articles/PMC7654790/ /pubmed/33170893 http://dx.doi.org/10.1371/journal.pone.0241503 Text en https://creativecommons.org/publicdomain/zero/1.0/ This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 (https://creativecommons.org/publicdomain/zero/1.0/) public domain dedication.
spellingShingle Research Article
Sajulga, Ray
Easterly, Caleb
Riffle, Michael
Mesuere, Bart
Muth, Thilo
Mehta, Subina
Kumar, Praveen
Johnson, James
Gruening, Bjoern Andreas
Schiebenhoefer, Henning
Kolmeder, Carolin A.
Fuchs, Stephan
Nunn, Brook L.
Rudney, Joel
Griffin, Timothy J.
Jagtap, Pratik D.
Survey of metaproteomics software tools for functional microbiome analysis
title Survey of metaproteomics software tools for functional microbiome analysis
title_full Survey of metaproteomics software tools for functional microbiome analysis
title_fullStr Survey of metaproteomics software tools for functional microbiome analysis
title_full_unstemmed Survey of metaproteomics software tools for functional microbiome analysis
title_short Survey of metaproteomics software tools for functional microbiome analysis
title_sort survey of metaproteomics software tools for functional microbiome analysis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7654790/
https://www.ncbi.nlm.nih.gov/pubmed/33170893
http://dx.doi.org/10.1371/journal.pone.0241503
work_keys_str_mv AT sajulgaray surveyofmetaproteomicssoftwaretoolsforfunctionalmicrobiomeanalysis
AT easterlycaleb surveyofmetaproteomicssoftwaretoolsforfunctionalmicrobiomeanalysis
AT rifflemichael surveyofmetaproteomicssoftwaretoolsforfunctionalmicrobiomeanalysis
AT mesuerebart surveyofmetaproteomicssoftwaretoolsforfunctionalmicrobiomeanalysis
AT muththilo surveyofmetaproteomicssoftwaretoolsforfunctionalmicrobiomeanalysis
AT mehtasubina surveyofmetaproteomicssoftwaretoolsforfunctionalmicrobiomeanalysis
AT kumarpraveen surveyofmetaproteomicssoftwaretoolsforfunctionalmicrobiomeanalysis
AT johnsonjames surveyofmetaproteomicssoftwaretoolsforfunctionalmicrobiomeanalysis
AT grueningbjoernandreas surveyofmetaproteomicssoftwaretoolsforfunctionalmicrobiomeanalysis
AT schiebenhoeferhenning surveyofmetaproteomicssoftwaretoolsforfunctionalmicrobiomeanalysis
AT kolmedercarolina surveyofmetaproteomicssoftwaretoolsforfunctionalmicrobiomeanalysis
AT fuchsstephan surveyofmetaproteomicssoftwaretoolsforfunctionalmicrobiomeanalysis
AT nunnbrookl surveyofmetaproteomicssoftwaretoolsforfunctionalmicrobiomeanalysis
AT rudneyjoel surveyofmetaproteomicssoftwaretoolsforfunctionalmicrobiomeanalysis
AT griffintimothyj surveyofmetaproteomicssoftwaretoolsforfunctionalmicrobiomeanalysis
AT jagtappratikd surveyofmetaproteomicssoftwaretoolsforfunctionalmicrobiomeanalysis