BACKGROUND: Metagenomics is a powerful methodology to study microbial 
communities, but it is highly dependent on nucleotide sequence similarity 
searching against sequence databases. Metagenomic analyses with next-generation 
sequencing technologies produce enormous numbers of reads from microbial 
communities, and many reads are derived from microbes whose genomes have not yet 
been sequenced, limiting the usefulness of existing sequence similarity search 
tools. Therefore, there is a clear need for a sequence similarity search tool 
that can rapidly detect weak similarity in large datasets.
RESULTS: We developed a tool, which we named CLAST (CUDA implemented large-scale 
alignment search tool), that enables analyses of millions of reads and thousands 
of reference genome sequences, and runs on NVIDIA Fermi architecture graphics 
processing units. CLAST has four main advantages over existing alignment tools. 
First, CLAST was capable of identifying sequence similarities ~80.8 times faster 
than BLAST and 9.6 times faster than BLAT. Second, CLAST executes global 
alignment as the default (local alignment is also an option), enabling CLAST to 
assign reads to taxonomic and functional groups based on evolutionarily distant 
nucleotide sequences with high accuracy. Third, CLAST does not need a 
preprocessed sequence database like Burrows-Wheeler Transform-based tools, and 
this enables CLAST to incorporate large, frequently updated sequence databases. 
Fourth, CLAST requires <2 GB of main memory, making it possible to run CLAST on 
a standard desktop computer or server node.
CONCLUSIONS: CLAST achieved very high speed (similar to the Burrows-Wheeler 
Transform-based Bowtie 2 for long reads) and sensitivity (equal to BLAST, BLAT, 
and FR-HIT) without the need for extensive database preprocessing or a 
specialized computing platform. Our results demonstrate that CLAST has the 
potential to be one of the most powerful and realistic approaches to analyze the 
massive amount of sequence data from next-generation sequencing technologies.