Linking patterns of microbial diversity with hydrothermal processes

A.L. Reysenbach*¹, G. Flores¹, & M.K. Tivey²

Corresponding author: reysenbacha@pdx.edu
¹Portland State University, Biology Dept., Portland, OR 97201
²Woods Hole Oceanographic Institution, Woods Hole, MA

Abstract:
At deep-sea hydrothermal vents, the microbial colonization and growth is tightly linked to the geochemical conditions providing habitats for chemolithoautotrophs, heterotrophs, mesophiles and thermophiles. Over the past decade or so, much of this microbial diversity has been described, and certain patterns are beginning to emerge (Takai et al., 2006). However, very few studies have tried to link the diversity assessments with the geochemical and physical processes occurring in these hydrothermal systems. We have been investigating the bacterial and archaeal diversity associated with actively venting deep-sea vent sulfide deposits using high throughput sequencing of two different hypervariable regions of the small-subunit (SSU) rRNA gene. Eight samples were analyzed from deep-sea vent sites along the Eastern Lau Spreading center and Valu Fa Ridge, and 5 samples were analyzed from deep-sea vents on the Mid-Atlantic Ridge (Lucky Strike, Rainbow and TAG). All samples were colonized by the archaeal sulfate reducer, Archaeoglobus, but the relative abundance of methanogens such as Methanocaldococcus differed significantly from sample to sample. Epsilon-Proteobacteria dominated all except the Mariner samples. The diversity of the epsilons differed between samples, some dominated by Nautiales. Gamma Proteobacteria were present in all samples, but most prevalent in the Mariner samples. These differences may be explained by deep mantle processes, fluid flow, mixing styles and temporal changes of colonization. In addition, the composition of the lower abundance thermophilic lineages such as Thermales, Thermoprotei, Desulfurococci and Aquificales differed between samples and may be good indicator ‘species’ for predictions of different geochemistries and physical factors influencing microbial community structure.

Contributions to Integration and Synthesis:
These data can build on other microbial datasets from different vent environment. This will begin to build a synthesis of microbial diversity at vents. Ecological and statistical tools such as analyses of co-occurrence etc. can then also be applied to these datasets. Integration of relevant geochemical, mineralogical and geological datasets will provide ways to explore how other factors might influence the observed microbial patterns.