ANASTASIA: An Automated Metagenomic Analysis Pipeline for Novel Enzyme Discovery Exploiting Next Generation Sequencing Data - Koutsandreas, Theodoros; Ladoukakis, Efthymios; Pilalis, Eleftherios; Zarafeta, Dimitra; Kolisis, Fragiskos N.; Skretas, Georgios; Chatziioannou, Aristotelis A. (Frontiers in Genetics, 2019)
Metagenomic analysis of environmental samples provides deep insight into the corresponding niches' enzymatic arsenal, revealing peptide sequences of novel functional properties. Next generation sequencing methodologies have revolutionized the collection of massive (meta)genomic data but simultaneously have also untapped their complexity , concomitantly requesting ever larger computational configurations to ensure efficient bioinformatic analysis and fine annotation. Aiming to tackle 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 suite of computational tools, either publicly available or novel in-house customized algorithms, integrated within numerous automated algorithmic workflows, enabling versatile data processing tasks for (meta)genomic sequence datasets. ANASTASIA initially developed and inspired by the bioinformatics tasks of the FP7 project HotZyme, which targeted to the exhaustive analysis of metagenomes in thermal springs, with the scope of tracing proteins with interesting enzymatic properties, has evolved to become a stable and extensible environment for diversified metagenomic functional analysis for a range of applications from Industrial Biotechnology to the Biomedicine, within the frames of ELIXIR-GR project. As a showcase, we report the successful in silico mining of a novel thermostable esterase named 'EstDZ4' from a metagenomic sample taken from a hot spring from Grendsdalur, Iceland.