Abstract
SummaryMetagenomic studies use high-throughput sequence data to investigate microbial communities in situ. However, considerable challenges remain in the analysis of these data, particularly with regard to speed and reliable analysis of microbial species as opposed to higher level taxa such as phyla. We here present Genometa, a computationally undemanding graphical user interface program that enables identification of bacterial species and gene content from datasets generated by inexpensive high-throughput short read sequencing technologies. Our approach was first verified on two simulated metagenomic short read datasets, detecting 100% and 94% of the bacterial species included with few false positives or false negatives. Subsequent comparative benchmarking analysis against three popular metagenomic algorithms on an Illumina human gut dataset revealed Genometa to attribute the most reads to bacteria at species level (i.e. including all strains of that species) and demonstrate similar or better accuracy than the other programs. Lastly, speed was demonstrated to be many times that of BLAST due to the use of modern short read aligners. Our method is highly accurate if bacteria in the sample are represented by genomes in the reference sequence but cannot find species absent from the reference. This method is one of the most user-friendly and resource efficient approaches and is thus feasible for rapidly analysing millions of short reads on a personal computer.AvailabilityThe Genometa program, a step by step tutorial and Java source code are freely available from http://genomics1.mh-hannover.de/genometa/ and on http://code.google.com/p/genometa/. This program has been tested on Ubuntu Linux and Windows XP/7.
Highlights
Metagenomics, the analysis of microbial communities directly within their natural environments, continues to gain traction in both the environment and in the clinic
Sequence reads in bacterial metagenomic analyses can be derived by whole genome shotgun sequencing, or targeted sequencing of 16S rRNA amplicons
We introduce a novel standalone metagenomic program designed for the challenges of whole genome short read analysis
Summary
Metagenomics, the analysis of microbial communities directly within their natural environments, continues to gain traction in both the environment and in the clinic. Sequence reads in bacterial metagenomic analyses can be derived by whole genome shotgun sequencing, or targeted sequencing of 16S rRNA amplicons These alternative techniques do lead to significant taxonomic differences in results, based upon the evaluation of 33 metagenomes [5]. The number of copies of the rRNA gene in bacteria range from 1–15 [9], rendering rRNA-based approaches more suitable for qualitative than quantitative metagenomics. Because of these reasons, we anticipate whole genome shotgun metagenomes will be preferable to sequencing of rRNA amplicons in the future
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