Active Microbial Communities Inhabit Sulphate-Methane Interphase in Deep Bedrock Fracture Fluids in Olkiluoto, Finland

Abstract

Active microbial communities of deep crystalline bedrock fracture water were investigated from seven different boreholes in Olkiluoto (Western Finland) using bacterial and archaeal 16S rRNA, dsrB, and mcrA gene transcript targeted 454 pyrosequencing. Over a depth range of 296-798 m below ground surface the microbial communities changed according to depth, salinity gradient, and sulphate and methane concentrations. The highest bacterial diversity was observed in the sulphate-methane mixing zone (SMMZ) at 250-350 m depth, whereas archaeal diversity was highest in the lowest boundaries of the SMMZ. Sulphide-oxidizing ε-proteobacteria (Sulfurimonas sp.) dominated in the SMMZ and γ-proteobacteria (Pseudomonas spp.) below the SMMZ. The active archaeal communities consisted mostly of ANME-2D and Thermoplasmatales groups, although Methermicoccaceae, Methanobacteriaceae, and Thermoplasmatales (SAGMEG, TMG) were more common at 415-559 m depth. Typical indicator microorganisms for sulphate-methane transition zones in marine sediments, such as ANME-1 archaea, α-, β- and δ-proteobacteria, JS1, Actinomycetes, Planctomycetes, Chloroflexi, and MBGB Crenarchaeota were detected at specific depths. DsrB genes were most numerous and most actively transcribed in the SMMZ while the mcrA gene concentration was highest in the deep methane rich groundwater. Our results demonstrate that active and highly diverse but sparse and stratified microbial communities inhabit the Fennoscandian deep bedrock ecosystems.

Figure 1

Map of Olkiluoto area where the different boreholes sampled in this study are indicated as open triangles. The arrows show the direction in which the boreholes lead. The scale bar is equal to 500 m.

Figure 2

The relative distribution of bacterial 16S rRNA sequence reads belonging to specific bacterial families. The relative abundance of sequence reads are highlighted by color, where green represents the lowest relative abundance, yellow represents medium abundance, and red represents high abundance. The samples were clustered using the Morisita-Horn algorithm in Mothur. The data were normalized between the different samples to include 893 random sequence reads from each sample.

Figure 3

The relative distribution of archaeal 16S rRNA sequence reads belonging to specific archaeal families. The relative abundances of sequence reads are highlighted as described in Figure 2. The samples were clustered as described in Figure 2. The data was normalized between the different samples to include 1200 random sequence reads from each sample.

Figure 4

Rarefaction curves of the sequence data obtained from each RNA extract normalized to equal number of sequence reads per sample: (a) bacterial 16S rRNA, (b) archaeal 16S rRNA, (c) dsrB transcripts, and (d) mcrA transcripts. The x-axis displays the number of sequence reads and the y-axis displays the number of different OTUs obtained. Figures (a)–(c) present rarefaction values at the distance 0.03 and (d) rarefaction for distance 0.01.

Figure 5

The relative distribution of dsrB transcript sequence reads belonging to specific SRB families according to the phylogenetic identification of the sequences presented in Figure 6. The relative abundance of sequence reads and the clustering of the samples are presented as described in Figure 2. The data were normalized between the different samples to include 2249 random sequence reads from each sample.

Figure 6

The phylogenetic distribution of the amino acid sequences of the OTUs of dsrB transcripts detected in this study presented as a maximum likelihood tree. The sequences detected in this study are shown in red. Bootstrap support for nodes was calculated with 1000 random repeats and nodes with more than 50% support are indicated. Sequences detected in this study are shown in red. The sequence name codes consist of the sequence IDENTIFIER and the OTU number|the number of sequence reads in that OTU followed by the depths from which this OTU has been detected.

Figure 7

The relative distribution of mcrA transcript sequence reads belonging to specific methanogenic archaeal families based on the phylogenetic identification of the mcrA reads as presented in Figure 8. The relative abundances of sequence reads are highlighted as described in Figure 2. The data was normalized between the different samples to include 2324 random sequence reads from each sample.

Figure 8

The phylogenetic distribution of the amino acid sequences of the OTUs of mcrA transcripts obtained detected in this study presented as a maximum likelihood tree. The sequences detected in this study are shown in red. Bootstrap support for nodes was calculated with 1000 random repeats and nodes with more than 50% support are indicated. The sequence codes are as described in Figure 6.