Niche partitioning of diverse sulfur-oxidizing bacteria at hydrothermal vents

Abstract

At deep-sea hydrothermal vents, primary production is carried out by chemolithoautotrophic microorganisms, with the oxidation of reduced sulfur compounds being a major driver for microbial carbon fixation. Dense and highly diverse assemblies of sulfur-oxidizing bacteria (SOB) are observed, yet the principles of niche differentiation between the different SOB across geochemical gradients remain poorly understood. In this study niche differentiation of the key SOB was addressed by extensive sampling of active sulfidic vents at six different hydrothermal venting sites in the Manus Basin, off Papua New Guinea. We subjected 33 diffuse fluid and water column samples and 23 samples from surfaces of chimneys, rocks and fauna to a combined analysis of 16S rRNA gene sequences, metagenomes and real-time in situ measured geochemical parameters. We found Sulfurovum Epsilonproteobacteria mainly attached to surfaces exposed to diffuse venting, while the SUP05-clade dominated the bacterioplankton in highly diluted mixtures of vent fluids and seawater. We propose that the high diversity within Sulfurimonas- and Sulfurovum-related Epsilonproteobacteria observed in this study derives from the high variation of environmental parameters such as oxygen and sulfide concentrations across small spatial and temporal scales.

Figure 1

Relative abundances of 16S rRNA gene sequence reads according to their classification. Putative SOB are denoted in bold and are marked with a ‘*’. The cluster dendrogram depicts the average linkage hierarchical clustering based on a Bray-Curtis dissimilarity matrix of community compositions resolved down to MED-node level. ^#Co-sampling of sediment particles possible.

Figure 2

Distribution of SOB 16S rRNA gene sequences in fluid samples with geochemical data. (a) In situ determined geochemical parameters sorted from cold diluted to more hot and concentrated hydrothermal fluids (left to right) based on temperature. (b) Distribution of putative SOB genera based on 16S rRNA gene amplicon sequences in diffuse fluid samples.

Figure 3

Distance-based redundancy analysis (dbRDA) calculated based on a Bray-Curtis dissimilarity matrix and standardized, log-normalized geochemical parameters. The distance matrix was calculated based on relative abundances of microbial genera in 21 fluid samples with geochemical data. Results of a non-parametric permutational multivariate analysis of variance (perMANOVA) are stated in the frame adjacent to the dbRDA panel. perMANOVA was calculated using the ‘adonis’ function of the ‘vegan’ package in R (Oksanen et al., 2013).

Figure 4

Maximum likelihood tree of SoxY amino-acid sequences. In yellow—clusters containing epsilonproteobacterial bins, in blue—SUP05 bins, with respective bins indicated on the right. In purple—clusters containing other sequences encoded in the bulk metagenome assemblies. Numbers on the triangles indicate numbers of SoxY sequences from the bulk metagenome assemblies contained in the cluster. The tree was calculated with PhyML (Guindon et al., 2010) based on positions conserved in at least 25% of the sequences.

Figure 5

Schematic placement of niches of SUP05 (blue) and Sulfurimonas/Sulfurovum-related SOB (SM/SV; green to brown) in the mixing gradient. Being placed in the steep part of the gradient, Sulfurimonas and Sulfurovum-related bacteria are exposed to higher amplitudes of variation of environmental parameters, for example, hydrogen sulfide concentrations, which leads to diversification into different species, each one with its own microniche.