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

By

Magesh, Shruthi
Jonsson, Viktor
Bengtsson-Palme, Johan

Type

Article

Date of Publication

2019-9-4

Original Publication

Metabarcoding and metagenomics

Volume

3

Pages

1--9

Subjects

Antibiotic resistance , bioinformatic tools , Metagenomics , mutation detection , mutation frequencies , Statistical methods

Contributed by

Pensoft Publishers

Language

English

Published by

Bulgaria Pensoft Publishers 2017-

Identifiers

DOI: https://doi.org/10.3897/mbmg.3.36236

 

Abstract

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).