Taxonomy

Microorganisms comprise the majority of Earth’s biological diversity, and they play essential functional roles in virtually all ecosystems. In particular, human-associated microbial communities play a fundamentally important role in health and disease. In many environments, however, more than 99% of the microorganisms cannot be

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cultured by standard techniques. In order to understand the genetic diversity, population structure, and ecological roles of novel organisms, metagenomic approaches analyze the microbial genomic DNA obtained directly from the environment.

A major goal of metagenomics is to characterize the microbial composition of an environment. The most popular approach relies on 16S rRNA sequencing, however this approach can generate biased estimates due to differences in the copy number of the gene between even closely related organisms, and due to PCR artifacts. The taxonomic composition can also be determined from metagenomic shotgun sequencing data by matching individual reads against a database of reference sequences. One major limitation of prior computational methods used for this purpose is the use of a universal classification threshold for all genes at all taxonomic levels.

In this research, scientists proposed that better classification results can be obtained by tuning the taxonomic classifier to each matching length, reference gene, and taxonomic level. We present a novel taxonomic classifier MetaPhyler (http://metaphyler.cbcb.umd.edu website), which uses phylogenetic marker genes as a taxonomic reference. Results on simulated datasets demonstrate that MetaPhyler outperforms other tools commonly used in this context (CARMA, Megan and PhymmBL). They are also presenting interesting results by analyzing a real metagenomic dataset.

Compared with previous approaches, MetaPhyler is much more accurate in estimating the phylogenetic composition. In addition, we have shown that MetaPhyler can be used to guide the discovery of novel organisms from metagenomic samples.

Authors: Bo Liu, Theodore Gibbons, Mohammad Ghodsi, Todd Treangen and Mihai Pop

Source: BMC Genomics 2011, 12(Suppl 2):S4

DOI: 10.1186/1471-2164-12-S2-S4. 27 July 2011

Link: http://www.biomedcentral.com/1471-2164/12/S2/S4