Taxator-tk: precise taxonomic assignment of metagenomes by fast approximation of evolutionary neighborhoods.

J Dröge,I Gregor,A C Mchardy

doi:10.1093/bioinformatics/btu745

Abstract

Motivation: Metagenomics characterizes microbial communities by random shotgun sequencing of DNA isolated directly from an environment of interest. An essential step in computational metagenome analysis is taxonomic sequence assignment, which allows identifying the sequenced community members and reconstructing taxonomic bins with sequence data for the individual taxa. For the massive datasets generated by next-generation sequencing technologies, this cannot be performed with de-novo phylogenetic inference methods. We describe an algorithm and the accompanying software, taxator-tk, which performs taxonomic sequence assignment by fast approximate determination of evolutionary neighbors from sequence similarities.Results: Taxator-tk was precise in its taxonomic assignment across all ranks and taxa for a range of evolutionary distances and for short as well as for long sequences. In addition to the taxonomic binning of metagenomes, it is well suited for profiling microbial communities from metagenome samples because it identifies bacterial, archaeal and eukaryotic community members without being affected by varying primer binding strengths, as in marker gene amplification, or copy number variations of marker genes across different taxa. Taxator-tk has an efficient, parallelized implementation that allows the assignment of 6 Gb of sequence data per day on a standard multiprocessor system with 10 CPU cores and microbial RefSeq as the genomic reference data.Availability and implementation: Taxator-tk source and binary program files are publicly available at http://algbio.cs.uni-duesseldorf.de/software/.Contact: Alice.McHardy@uni-duesseldorf.deSupplementary information: Supplementary data are available at Bioinformatics online.

Highlights

Metagenomics allows us to study microbial communities from natural environments without the need to obtain pure cultures of the individual member species (Hugenholtz, 2002; Riesenfeld et al, 2004)
To provide a fair comparison, we invested extensive effort into ensuring that we evaluated all methods under identical conditions with the same reference sequences, test datasets and background taxonomies, using their recommended settings
We evaluated a wide range of evolutionary distances between the query and reference sequences using leave-one-taxon-out cross-validation

Summary

Introduction

Metagenomics allows us to study microbial communities from natural environments without the need to obtain pure cultures of the individual member species (Hugenholtz, 2002; Riesenfeld et al, 2004). By computational analyses of metagenome sequence samples, we can estimate the abundances of different taxa for the sampled communities, known as taxonomic profiling, characterize their functional and metabolic potential based on the predicted proteins and resolve the contributions of individual taxa to the latter by reconstructing ‘bins’ of unassembled or assembled sequences that originate from the same taxon.

Methods

Results

Conclusion