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

Abstract

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.

XynDZ5: A New Thermostable GH10 Xylanase

“…The figure was prepared using UCSF Chimera (Pettersen et al, 2004). sequencing reads were uploaded to our customized data analysis platform ANASTASIA (Koutsandreas et al, 2019). Assembly into contigs, de novo prediction of coding sequences within the contigs, and employment of three different types of integrated tools, each based on a different machine-learning model, were applied to identify 3,000 putative gene sequences, which were subsequently submitted to homology analysis.…”

Carboxylic Ester Hydrolases in Bacteria: Active Site, Structure, Function and Application

“…The development of sequencing technology enables the identification of new enzymes from various organisms, including bacteria, and even from the metagenome [212][213][214][215][216]. Functional annotation of those enzymes has been followed by direct or indirect approaches, such as computational sequence/structure analysis and comparison with characterized enzymes [217].…”

MetaDEGalaxy: Galaxy workflow for differential abundance analysis of 16s metagenomic data

“…There are comparable web and/or GUI based tools such as QIIME/QIIME2 2 , MetaPipe 20 , MG-RAST 21 , MOCAT2 22 , Calypso 23 , Explicet 24 , and Megan 25 , however none of these tools except QIIME2 are currently available within the popular Galaxy framework. Within Galaxy there are several metagenomics offerings including ASaiM 5 , GmT 7 , A-Game 8 , and ANASTASIA 9 .…”

“…Despite this, challenges remain in fast moving research areas such as metagenomics with only a handful of complete metagenomic offerings currently available within the popular Galaxy framework. Currently, existing metagenomics options in Galaxy include ASaiM 5 , FROGS 6 , GmT 7 , A-Game 8 , and ANASTASIA 9 with QIIME2 recently becoming available in the Galaxy Toolshed. While there is overlap between their workflows, MetaDEGalaxy differs in its focus on differential abundance by incorporating the capabilities of phyloseq 10 and DESeq2 11 for complex differential analysis.…”