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Mumame: A software tool for quantifying gene-specific point-mutations in shotgun metagenomic data

Artikel i vetenskaplig tidskrift
Författare Shruthi Magesh
Viktor Jonsson
Johan Bengtsson-Palme
Publicerad i Metabarcoding and Metagenomics
Volym 3
Sidor 59–67
ISSN 2534-9708
Publiceringsår 2019
Publicerad vid CARe - Centrum för antibiotikaresistensforskning
Institutionen för biomedicin, avdelningen för infektionssjukdomar
Sidor 59–67
Språk en
Länkar https://doi.org/10.3897/mbmg.3.3623...
https://mbmg.pensoft.net/article/36...
Ämnesord Antibiotic resistance, bioinformatic tools, metagenomics, mutation frequencies, mutation detection, statistical methods
Ämneskategorier Bioinformatik och systembiologi

Sammanfattning

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).

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