Food Technology and Biotechnology (Jan 2017)

MEGGASENSE – The Metagenome/Genome Annotated Sequence Natural Language Search Engine: A Platform for the Construction of Sequence Data Warehouses

  • Ranko Gacesa,
  • Jurica Zucko,
  • Solveig K. Petursdottir,
  • Elisabet Eik Gudmundsdottir,
  • Olafur H. Fridjonsson,
  • Janko Diminic,
  • Paul F. Long,
  • John Cullum,
  • Daslav Hranueli,
  • Gudmundur O. Hreggvidsson,
  • Antonio Starcevic

DOI
https://doi.org/10.17113/ftb.55.02.17.4749
Journal volume & issue
Vol. 55, no. 2
pp. 251 – 257

Abstract

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The 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 MEGGASENSE.

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