skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: MaxBin 2.0: an automated binning algorithm to recover genomes from multiple metagenomic datasets

Abstract

The recovery of genomes from metagenomic datasets is a critical step to defining the functional roles of the underlying uncultivated populations. We previously developed MaxBin, an automated binning approach for high-throughput recovery of microbial genomes from metagenomes. Here, we present an expanded binning algorithm, MaxBin 2.0, which recovers genomes from co-assembly of a collection of metagenomic datasets. Tests on simulated datasets revealed that MaxBin 2.0 is highly accurate in recovering individual genomes, and the application of MaxBin 2.0 to several metagenomes from environmental samples demonstrated that it could achieve two complementary goals: recovering more bacterial genomes compared to binning a single sample as well as comparing the microbial community composition between different sampling environments. Availability and implementation: MaxBin 2.0 is freely available at http://sourceforge.net/projects/maxbin/ under BSD license. Supplementary information: Supplementary data are available at Bioinformatics online.

Authors:
 [1];  [1];  [1]
  1. Joint BioEnergy Inst. (JBEI), Emeryville, CA (United States); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Publication Date:
Research Org.:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
OSTI Identifier:
1407392
DOE Contract Number:  
AC02-05CH11231
Resource Type:
Journal Article
Journal Name:
Bioinformatics
Additional Journal Information:
Journal Volume: 32; Journal Issue: 4; Journal ID: ISSN 1367-4803
Publisher:
Oxford University Press
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING; 59 BASIC BIOLOGICAL SCIENCES

Citation Formats

Wu, Yu-Wei, Simmons, Blake A., and Singer, Steven W. MaxBin 2.0: an automated binning algorithm to recover genomes from multiple metagenomic datasets. United States: N. p., 2015. Web. doi:10.1093/bioinformatics/btv638.
Wu, Yu-Wei, Simmons, Blake A., & Singer, Steven W. MaxBin 2.0: an automated binning algorithm to recover genomes from multiple metagenomic datasets. United States. doi:10.1093/bioinformatics/btv638.
Wu, Yu-Wei, Simmons, Blake A., and Singer, Steven W. Thu . "MaxBin 2.0: an automated binning algorithm to recover genomes from multiple metagenomic datasets". United States. doi:10.1093/bioinformatics/btv638.
@article{osti_1407392,
title = {MaxBin 2.0: an automated binning algorithm to recover genomes from multiple metagenomic datasets},
author = {Wu, Yu-Wei and Simmons, Blake A. and Singer, Steven W.},
abstractNote = {The recovery of genomes from metagenomic datasets is a critical step to defining the functional roles of the underlying uncultivated populations. We previously developed MaxBin, an automated binning approach for high-throughput recovery of microbial genomes from metagenomes. Here, we present an expanded binning algorithm, MaxBin 2.0, which recovers genomes from co-assembly of a collection of metagenomic datasets. Tests on simulated datasets revealed that MaxBin 2.0 is highly accurate in recovering individual genomes, and the application of MaxBin 2.0 to several metagenomes from environmental samples demonstrated that it could achieve two complementary goals: recovering more bacterial genomes compared to binning a single sample as well as comparing the microbial community composition between different sampling environments. Availability and implementation: MaxBin 2.0 is freely available at http://sourceforge.net/projects/maxbin/ under BSD license. Supplementary information: Supplementary data are available at Bioinformatics online.},
doi = {10.1093/bioinformatics/btv638},
journal = {Bioinformatics},
issn = {1367-4803},
number = 4,
volume = 32,
place = {United States},
year = {2015},
month = {10}
}

Works referenced in this record:

Genome sequences of rare, uncultured bacteria obtained by differential coverage binning of multiple metagenomes
journal, May 2013

  • Albertsen, Mads; Hugenholtz, Philip; Skarshewski, Adam
  • Nature Biotechnology, Vol. 31, Issue 6
  • DOI: 10.1038/nbt.2579

Binning metagenomic contigs by coverage and composition
journal, September 2014

  • Alneberg, Johannes; Bjarnason, Brynjar Smári; de Bruijn, Ino
  • Nature Methods, Vol. 11, Issue 11
  • DOI: 10.1038/nmeth.3103

Community-wide analysis of microbial genome sequence signatures
journal, January 2009

  • Dick, Gregory J.; Andersson, Anders F.; Baker, Brett J.
  • Genome Biology, Vol. 10, Issue 8
  • DOI: 10.1186/gb-2009-10-8-r85

GroopM: an automated tool for the recovery of population genomes from related metagenomes
journal, January 2014

  • Imelfort, Michael; Parks, Donovan; Woodcroft, Ben J.
  • PeerJ, Vol. 2
  • DOI: 10.7717/peerj.603

Untangling Genomes from Metagenomes: Revealing an Uncultured Class of Marine Euryarchaeota
journal, February 2012


MEGAHIT: an ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph
journal, January 2015


MetaBAT, an efficient tool for accurately reconstructing single genomes from complex microbial communities
journal, January 2015


Metagenomic analysis of a permafrost microbial community reveals a rapid response to thaw
journal, November 2011

  • Mackelprang, Rachel; Waldrop, Mark P.; DeAngelis, Kristen M.
  • Nature, Vol. 480, Issue 7377
  • DOI: 10.1038/nature10576

MetaSim—A Sequencing Simulator for Genomics and Metagenomics
journal, October 2008


Time series community genomics analysis reveals rapid shifts in bacterial species, strains, and phage during infant gut colonization
journal, August 2012

  • Sharon, I.; Morowitz, M. J.; Thomas, B. C.
  • Genome Research, Vol. 23, Issue 1
  • DOI: 10.1101/gr.142315.112

MetaCluster 5.0: a two-round binning approach for metagenomic data for low-abundance species in a noisy sample
journal, September 2012


Fermentation, Hydrogen, and Sulfur Metabolism in Multiple Uncultivated Bacterial Phyla
journal, September 2012


A Novel Abundance-Based Algorithm for Binning Metagenomic Sequences Using l -tuples
journal, March 2011


MaxBin: an automated binning method to recover individual genomes from metagenomes using an expectation-maximization algorithm
journal, August 2014