Metagenomics accelerates species discovery and unravel great biodiversity of benthic invertebrates in marine sediments in Campos basin, Brazil

Sediment fauna characterization and monitoring are mandatory requirements for obtaining oil and gas (O&G) environmental licensing for exploration and production (E&P) activities. Currently, for environmental characterizations and monitoring, biodiversity is assessed through morphological taxonomy, a time-consuming process. Taxonomists are constantly failing to meet the demands for biodiversity assessment required in monitoring programs. Thus, we combined three different phylogenetic markers(rDNA 18S, rDNA 28S and COI), HTS and Bioinformatics to identify benthic invertebrate organisms from sediment samples collected in five stations in the Campos Basin in southeast Brazil, an important oil extraction area and one of the best-studied marine biota in Brazil. Our results obtained with metagenomics were compared to morphology data provided by the Habitats Project whereas the database Global Biodiversity Information Facility ( www.gbif.org ) was used for organism localization. We obtained around 4.83 μg of DNA from 15 samples. A total of 3.3 million sequences were clustered in Operational Taxonomic Units and more than 1.6 million sequences (about 50% of all reads) were assigned to 957 prokaryotes and 577 eukaryotes. BLAST identified 23 phyla, 60 classes, 62 orders, 70 families, 67 genus and 46 species of eukaryotes. Our metagenomic analysis identified phyla that are traditionally found in samples of marine benthos, such as Annelida, Arthropoda, Mollusca and Chordata, as well as more rarely found phyla such as Bryozoa, Cnidaria, Echinodermata, Nematoda, Nemertea, Platyhelminthes, Porifera and Priapulida; and even more rare phyla like Entoprocta and Gastrotricha. The low availability of genetic markers for Brazilian species in Genebank impaired our ability to compare our findings with those obtained morphologically for which no sequences were found in Genebank. Our study shows that metagenomics can be applied for environmental characterization and monitoring programs and, with the possibility of automating the method, may reduce from years to few months the time currently required for species identification and biodiversity determination, which will certainly accelerate species discovery.