Energy Landscapes in Hydrothermal Chimneys Shape Distributions of Primary Producers

Hydrothermal systems are excellent natural laboratories for the study of how chemical energy landscapes shape microbial communities. Yet, only a few attempts have been made to quantify relationships between energy availability and microbial community structure in these systems. Here, we have investigated how microbial communities and chemical energy availabilities vary along cross-sections of two hydrothermal chimneys from the Soria Moria Vent Field and the Bruse Vent Field. Both vent fields are located on the Arctic Mid-Ocean Ridge, north of the Jan Mayen Island and the investigated chimneys were venting fluids with markedly different H(2)S:CH(4) ratios. Energy landscapes were inferred from a stepwise in silico mixing of hydrothermal fluids (HFs) with seawater, where Gibbs energies of relevant redox-reactions were calculated at each step. These calculations formed the basis for simulations of relative abundances of primary producers in microbial communities. The simulations were compared with an analysis of 24 samples from chimney wall transects by sequencing of 16S rRNA gene amplicons using 454 sequencing. Patterns in relative abundances of sulfide oxidizing Epsilonproteobacteria and methane oxidizing Methylococcales and ANME-1, were consistent with simulations. However, even though H(2) was present in HFs from both chimneys, the observed abundances of putative hydrogen oxidizing anaerobic sulfate reducers (Archaeoglobales) and methanogens (Methanococcales) in the inner parts of the Soria Moria Chimney were considerably higher than predicted by simulations. This indicates biogenic production of H(2) in the chimney wall by fermentation, and suggests that biological activity inside the chimneys may modulate energy landscapes significantly. Our results are consistent with the notion that energy landscapes largely shape the distribution of primary producers in hydrothermal systems. Our study demonstrates how a combination of modeling and field observations can be useful in deciphering connections between chemical energy landscapes and metabolic networks within microbial communities.