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Quantifying point-mutations in shotgun metagenomic data

Shruthi Magesh, Viktor Jonsson, Johan Bengtsson-Palme
doi: https://doi.org/10.1101/438572
Shruthi Magesh
1Wisconsin Institute of Discovery, University of Wisconsin-Madison, 330 North Orchard Street, Madison WI 53715, USA
2Department of Biotechnology, School of Bioengineering, SRM Institute of Science and Technology, Kattankulathur 603203, Tamil Nadu, India
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Viktor Jonsson
3Chalmers Computational Systems Biology Infrastructure, Chalmers University of Technology, SE-412 96, Gothenburg, Sweden
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Johan Bengtsson-Palme
1Wisconsin Institute of Discovery, University of Wisconsin-Madison, 330 North Orchard Street, Madison WI 53715, USA
4Department of Infectious Diseases, Institute of Biomedicine, The Sahlgrenska Academy, University of Gothenburg, Guldhedsgatan 10, SE-413 46, Gothenburg, Sweden
5Centre for Antibiotic Resistance research (CARe) at University of Gothenburg, Gothenburg, Sweden
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  • For correspondence: johan.bengtsson-palme@microbiology.se
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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 from http://microbiology.se/software/mumame

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted October 11, 2018.
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Quantifying point-mutations in shotgun metagenomic data
Shruthi Magesh, Viktor Jonsson, Johan Bengtsson-Palme
bioRxiv 438572; doi: https://doi.org/10.1101/438572
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Quantifying point-mutations in shotgun metagenomic data
Shruthi Magesh, Viktor Jonsson, Johan Bengtsson-Palme
bioRxiv 438572; doi: https://doi.org/10.1101/438572

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