Mumame: a software tool for quantifying gene-specific point-mutations in shotgun metagenomic data
Metagenomics has emerged as a central technique for studying the structure and function of microbial communities. Often the functional analysis is restricted to classification into broad functional categories. However, important phenotypic differences, such as resistance to antibio...
Main Authors: | , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Pensoft Publishers
2019-09-01
|
Series: | Metabarcoding and Metagenomics |
Online Access: | https://mbmg.pensoft.net/article/36236/download/pdf/ |
id |
doaj-69c1869819d2417980553b2f6470332d |
---|---|
record_format |
Article |
spelling |
doaj-69c1869819d2417980553b2f6470332d2020-11-25T00:46:46ZengPensoft PublishersMetabarcoding and Metagenomics 2534-97082019-09-013596710.3897/mbmg.3.3623636236Mumame: a software tool for quantifying gene-specific point-mutations in shotgun metagenomic dataShruthi Magesh0Viktor Jonsson1Johan Bengtsson-Palme2University of Wisconsin-MadisonChalmers University of TechnologyUniversity of Gothenburg Metagenomics has emerged as a central technique for studying the structure and function of microbial communities. Often the functional analysis is restricted to classification into broad functional categories. However, important phenotypic differences, such as resistance to antibiotics, are often the result of just one or a few point mutations in otherwise identical sequences. Bioinformatic methods for metagenomic analysis have generally been poor at accounting for this fact, resulting in a somewhat limited picture of important aspects of microbial communities. Here, we address this problem by providing a software tool called Mumame, which can distinguish between wildtype and mutated sequences in shotgun metagenomic data and quantify their relative abundances. We demonstrate the utility of the tool by quantifying antibiotic resistance mutations in several publicly available metagenomic data sets. We also identified that sequencing depth is a key factor to detect rare mutations. Therefore, much larger numbers of sequences may be required for reliable detection of mutations than for most other applications of shotgun metagenomics. Mumame is freely available online (http://microbiology.se/software/mumame). https://mbmg.pensoft.net/article/36236/download/pdf/ |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Shruthi Magesh Viktor Jonsson Johan Bengtsson-Palme |
spellingShingle |
Shruthi Magesh Viktor Jonsson Johan Bengtsson-Palme Mumame: a software tool for quantifying gene-specific point-mutations in shotgun metagenomic data Metabarcoding and Metagenomics |
author_facet |
Shruthi Magesh Viktor Jonsson Johan Bengtsson-Palme |
author_sort |
Shruthi Magesh |
title |
Mumame: a software tool for quantifying gene-specific point-mutations in shotgun metagenomic data |
title_short |
Mumame: a software tool for quantifying gene-specific point-mutations in shotgun metagenomic data |
title_full |
Mumame: a software tool for quantifying gene-specific point-mutations in shotgun metagenomic data |
title_fullStr |
Mumame: a software tool for quantifying gene-specific point-mutations in shotgun metagenomic data |
title_full_unstemmed |
Mumame: a software tool for quantifying gene-specific point-mutations in shotgun metagenomic data |
title_sort |
mumame: a software tool for quantifying gene-specific point-mutations in shotgun metagenomic data |
publisher |
Pensoft Publishers |
series |
Metabarcoding and Metagenomics |
issn |
2534-9708 |
publishDate |
2019-09-01 |
description |
Metagenomics has emerged as a central technique for studying the structure and function of microbial communities. Often the functional analysis is restricted to classification into broad functional categories. However, important phenotypic differences, such as resistance to antibiotics, are often the result of just one or a few point mutations in otherwise identical sequences. Bioinformatic methods for metagenomic analysis have generally been poor at accounting for this fact, resulting in a somewhat limited picture of important aspects of microbial communities. Here, we address this problem by providing a software tool called Mumame, which can distinguish between wildtype and mutated sequences in shotgun metagenomic data and quantify their relative abundances. We demonstrate the utility of the tool by quantifying antibiotic resistance mutations in several publicly available metagenomic data sets. We also identified that sequencing depth is a key factor to detect rare mutations. Therefore, much larger numbers of sequences may be required for reliable detection of mutations than for most other applications of shotgun metagenomics. Mumame is freely available online (http://microbiology.se/software/mumame).
|
url |
https://mbmg.pensoft.net/article/36236/download/pdf/ |
work_keys_str_mv |
AT shruthimagesh mumameasoftwaretoolforquantifyinggenespecificpointmutationsinshotgunmetagenomicdata AT viktorjonsson mumameasoftwaretoolforquantifyinggenespecificpointmutationsinshotgunmetagenomicdata AT johanbengtssonpalme mumameasoftwaretoolforquantifyinggenespecificpointmutationsinshotgunmetagenomicdata |
_version_ |
1715929497623068672 |