Frontiers in Genetics (May 2019)

ANASTASIA: An Automated Metagenomic Analysis Pipeline for Novel Enzyme Discovery Exploiting Next Generation Sequencing Data

  • Theodoros Koutsandreas,
  • Theodoros Koutsandreas,
  • Efthymios Ladoukakis,
  • Efthymios Ladoukakis,
  • Eleftherios Pilalis,
  • Eleftherios Pilalis,
  • Dimitra Zarafeta,
  • Fragiskos N. Kolisis,
  • Fragiskos N. Kolisis,
  • Georgios Skretas,
  • Aristotelis A. Chatziioannou,
  • Aristotelis A. Chatziioannou

DOI
https://doi.org/10.3389/fgene.2019.00469
Journal volume & issue
Vol. 10

Abstract

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Metagenomic analysis of environmental samples provides deep insight into the enzymatic mixture of the corresponding niches, capable of revealing peptide sequences with novel functional properties exploiting the high performance of next-generation sequencing (NGS) technologies. At the same time due to their ever increasing complexity, there is a compelling need for ever larger computational configurations to ensure proper bioinformatic analysis, and fine annotation. With the aiming to address the challenges of such an endeavor, we have developed a novel web-based application named ANASTASIA (automated nucleotide aminoacid sequences translational plAtform for systemic interpretation and analysis). ANASTASIA provides a rich environment of bioinformatic tools, either publicly available or novel, proprietary algorithms, integrated within numerous automated algorithmic workflows, and which enables versatile data processing tasks for (meta)genomic sequence datasets. ANASTASIA was initially developed in the framework of the European FP7 project HotZyme, whose aim was to perform exhaustive analysis of metagenomes derived from thermal springs around the globe and to discover new enzymes of industrial interest. ANASTASIA has evolved to become a stable and extensible environment for diversified, metagenomic, functional analyses for a range of applications overarching industrial biotechnology to biomedicine, within the frames of the ELIXIR-GR project. As a showcase, we report the successful in silico mining of a novel thermostable esterase termed “EstDZ4” from a metagenomic sample collected from a hot spring located in Krisuvik, Iceland.

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