MEGGASENSE - the Metagenome/Genome Annotated Sequence Natural Language Search Engine: a Platform for the Construction of Sequence Data Warehouses

Abstract

SummaryThe MEGGASENSE platform constructs relational databases of DNA or protein sequences. The default functional analysis uses 14 106 hidden Markov model (HMM) profiles based on sequences in the KEGG database. The Solr search engine allows sophisticated queries and a BLAST search function is also incorporated. These standard capabilities were used to generate the SCATT database from the predicted proteome of Streptomyces cattleya. The implementation of a specialised metagenome database (AMYLOMICS) for bioprospecting of carbohydrate-modifying enzymes is described. In addition to standard assembly of reads, a novel 'functional' assembly was developed, in which screening of reads with the HMM profiles occurs before the assembly. The AMYLOMICS database incorporates additional HMM profiles for carbohydrate-modifying enzymes and it is illustrated how the combination of HMM and BLAST analyses helps identify interesting genes. A variety of different proteome and metagenome databases have been generated by MEG-GASENSE.

Bioprospecting for Genes Encoding Hydrocarbon-Degrading Enzymes from Metagenomic Samples Isolated from Northern Adriatic Sea Sediments

“…Total DNA was isolated from 10 g of each sample with the PowerMax Soil DNA Isolation Kit The REDPET database was constructed using the MEGGASENSE platform (11). HMMprofiles for hydrocarbon-degrading enzymes were generated using HMMER v 3.0 (10) using protein sequences downloaded from the KEGG database (12) as a primary source.…”

“…The results of the analyses of the metagenomes were used to construct the REDPET relational database (17), which was based on the MEGGASENSE platform (11) and incorporates the generic functionality of this platform. This includes assembly of reads, taxonomic analysis and an intelligent search engine.…”