Databases of the marine metagenomics

Abstract

The metagenomic data obtained from marine environments is significantly useful for understanding marine microbial communities. In comparison with the conventional amplicon-based approach of metagenomics, the recent shotgun sequencing-based approach has become a powerful tool that provides an efficient way of grasping a diversity of the entire microbial community at a sampling point in the sea. However, this approach accelerates accumulation of the metagenome data as well as increase of data complexity. Moreover, when metagenomic approach is used for monitoring a time change of marine environments at multiple locations of the seawater, accumulation of metagenomics data will become tremendous with an enormous speed. Because this kind of situation has started becoming of reality at many marine research institutions and stations all over the world, it looks obvious that the data management and analysis will be confronted by the so-called Big Data issues such as how the database can be constructed in an efficient way and how useful knowledge should be extracted from a vast amount of the data. In this review, we summarize the outline of all the major databases of marine metagenome that are currently publically available, noting that database exclusively on marine metagenome is none but the number of metagenome databases including marine metagenome data are six, unexpectedly still small. We also extend our explanation to the databases, as reference database we call, that will be useful for constructing a marine metagenome database as well as complementing important information with the database. Then, we would point out a number of challenges to be conquered in constructing the marine metagenome database.

Integrated (Meta) Genomic and Synthetic Biology Approaches to Develop New Biocatalysts

“…The expansion of microbial genome sequencing over the last 20 years [ 125 ], through the increase of the speed of NGS and the decrease in cost of genome sequencing, has provided the basic tools for the in silico discovery of genes and gene clusters related to the production of novel marine natural products and biocatalysts [ 64 ]. However, the rapid increase of marine metagenomic DNA information in the database [ 126 ] has largely supplanted the directed genome approach. Recent efforts to decipher the extent of the oceans microbial biodiversity and the novelty of marine bioactives with biotechnological potential include the global Ocean Sampling Day; a simultaneous sampling campaign of the world’s oceans performed under the umbrella of the Micro B3 Project from the EU ( ) [ 127 ].…”

A robust metaproteomics pipeline for a holistic taxonomic and functional characterization of microbial communities from marine particles

“…The particulate fraction of 105 bacterioplankton has proven challenging to comprehensive meta-omics characterization, due 106 to its high complexity, presence of DNA/protein-binding polysaccharides, process-interfering 107 substances and lack of (meta)genomic information on marine particles (e.g. Wöhlbrand et al, 108 2017b), despite the fact that information on marine metagenomes is constantly growing 109 (reviewed by Mineta and Gojobori 2016;Alma'abadi et al, 2015). Previous experiments also 110 indicate that a high abundance of eukaryotic proteins contributes to these challenges (Smith 111 et al, 2017;Saito et al, 2019).…”

The MAR databases: development and implementation of databases specific for marine metagenomics

“…Most of these data as well as other marine metagenomic data are stored in publicly available metagenomic databases such as iMicrobe ( https://www.imicrobe.us/ ), Viral Informatics Resource for Metagenome Exploration (VIROME) ( 12 ), EBI metagenomics ( 13 ), Integrated Microbial Genomes and Microbiomes (IMG/M) ( 14 ) and Metagenomics Rapid Annotation using Subsystem Technology (MG-RAST) ( 15 ). Reference sequence databases with comprehensive metadata are essential for analyzing and interpreting of marine metagenomic data ( 16 , 17 ). There are several general microbial databases e.g.…”