The microbiome of the Black Sea water column analyzed by shotgun and genome centric metagenomics

Abstract

Background: The Black Sea is the largest brackish water body in the world, although it is connected to the Mediterranean Sea and presents an upper water layer similar to some regions of the former, albeit with lower salinity and temperature. Despite its well-known hydrology and physicochemical features, this enormous water mass remains poorly studied at the microbial genomics level.

Results: We have sampled its different water masses and analyzed the microbiome by shotgun and genome-resolved metagenomics, generating a large number of metagenome-assembled genomes (MAGs) from them. We found various similarities with previously described Black Sea metagenomic datasets, that show remarkable stability in its microbiome. Our datasets are also comparable to other marine anoxic water columns like the Cariaco Basin. The oxic zone resembles to standard marine (e.g. Mediterranean) photic zones, with Cyanobacteria (Synechococcus but a conspicuously absent Prochlorococcus), and photoheterotrophs domination (largely again with marine relatives). The chemocline presents very different characteristics from the oxic surface with many examples of chemolithotrophic metabolism (Thioglobus) and facultatively anaerobic microbes. The euxinic anaerobic zone presents, as expected, features in common with the bottom of meromictic lakes with a massive dominance of sulfate reduction as energy-generating metabolism, a few (but detectable) methanogenesis marker genes, and a large number of "dark matter" streamlined genomes of largely unpredictable ecology.

Conclusions: The Black Sea oxic zone presents many similarities to the global ocean while the redoxcline and euxinic water masses have similarities to other similar aquatic environments of marine (Cariaco Basin or other Black Sea regions) or freshwater (meromictic monimolimnion strata) origin. The MAG collection represents very well the different types of metabolisms expected in this kind of environment. We are adding critical information about this unique and important ecosystem and its microbiome.

Keywords: Black Sea microbiota; Euxinic waters; Genome-resolved metagenomics; Redoxcline.

Fig. 1

Black Sea sampling, physicochemical parameters and raw reads analysis. a A map of the Black Sea basin showing the red circle-coded sampling points of this study. b Bar plot showing the different environmental parameters and physicochemical profiles measured. Each environmental measurement is color-coded. c Black Sea phylum level 16S rRNA gene taxonomic classification assessed with unassembled reads individually mapped into SILVA138 database. d Metabolic profiles assessed with abundance values obtained from reads and SEED subsystems and pathways, pecific proteins/genes or microbial systems. A blue row Z-score scale was applied to statistically assess abundance values differing between samples

Fig. 2

Black Sea distance-based redundancy analysis (dbRDA) between different samples (depths), environmental parameters and the metabolic pathways assessed by read abundance from SEED subsystems. Each Black Sea sample is red square-coded. Environmental parameters are blue triangle-coded an SEED pathways are cream triangle-coded

Fig. 3

Black Sea Distance-based redundancy analysis (dbRDA) between different samples (depths), environmental parameters and MAGs abundance values obtained from the RPKGs.. We provided MAG names for class (_c), order (_o), family (_f), genus (_g) or species (_s) according to the last GTDB classification scheme followed in Table 1 and Table 2. Each Black Sea sample is red square-coded. Environmental parameters are blue triangle-coded and MAGs are green triangle-coded

Fig. 4

Recruitment analysis of the 50 most abundant Black Sea MAGs retrieved from our datasets (in red) and detected at highest values at various Black Sea metagenomes from the NCBI (Bioproject PRJNA649215). Reads were recruited at > 95% of identity and > 50 bp of alignment lengths. The predominant metabolism is characteristic of each MAG and was detected in the genome with KEGG, SEED, COG, TIGFRAMs and NCBI-nr databases