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Comparisons of the composition and biogeographic distribution of the bacterial communities occupying South African thermal springs with those inhabiting deep subsurface fracture water.

Magnabosco C, Tekere M, Lau MC, Linage B, Kuloyo O, Erasmus M, Cason E, van Heerden E, Borgonie G, Kieft TL, Olivier J, Onstott TC - Front Microbiol (2014)

Bottom Line: Proteobacteria were identified as the dominant phylum within both subsurface and thermal spring environments, but only one genera, Rheinheimera, was identified among all samples.Using Morisita similarity indices as a metric for pairwise comparisons between sites, we found that the communities of thermal springs are highly distinct from subsurface datasets.Although the Limpopo thermal springs do not appear to provide a new window for viewing subsurface bacterial communities, we report that the taxonomic compositions of the subsurface sites studied are more similar than previous results would indicate and provide evidence that the microbial communities sampled at depth are more correlated to subsurface conditions than geographical distance.

View Article: PubMed Central - PubMed

Affiliation: Department of Geosciences, Princeton University Princeton, NJ, USA.

ABSTRACT
South Africa has numerous thermal springs that represent topographically driven meteoric water migrating along major fracture zones. The temperature (40-70°C) and pH (8-9) of the thermal springs in the Limpopo Province are very similar to those of the low salinity fracture water encountered in the South African mines at depths ranging from 1.0 to 3.1 km. The major cation and anion composition of these thermal springs are very similar to that of the deep fracture water with the exception of the dissolved inorganic carbon and dissolved O2, both of which are typically higher in the springs than in the deep fracture water. The in situ biological relatedness of such thermal springs and the subsurface fracture fluids that feed them has not previously been evaluated. In this study, we evaluated the microbial diversity of six thermal spring and six subsurface sites in South Africa using high-throughput sequencing of 16S rRNA gene hypervariable regions. Proteobacteria were identified as the dominant phylum within both subsurface and thermal spring environments, but only one genera, Rheinheimera, was identified among all samples. Using Morisita similarity indices as a metric for pairwise comparisons between sites, we found that the communities of thermal springs are highly distinct from subsurface datasets. Although the Limpopo thermal springs do not appear to provide a new window for viewing subsurface bacterial communities, we report that the taxonomic compositions of the subsurface sites studied are more similar than previous results would indicate and provide evidence that the microbial communities sampled at depth are more correlated to subsurface conditions than geographical distance.

No MeSH data available.


Related in: MedlinePlus

Measurements of similarity between thermal spring and subsurface sites. Pair-wise comparisons have been made by counting the total number genera shared between sites (A) and calculation of the Sorensen similarity index (B) and Morisita dissimilarity indices (1-Morisita index) (D). Color-coding of (A,B,D) are purely for visual aid where red indicates more similar pairs and blue is indicative of more distant pairs. The diagonal of (A) indicates the number of genera identified in the sample. (C) is a visual representation of the hierarchical clustering of the Morisita dissimilarity matrix (D). Subsurface sites in (C) are labeled with pink squares and thermal spring sites are labeled with green circles. The columns of (D) are indicated by the branches of (C) whereas the columns of (A,B) are labeled. Black squares labeled 0.00 in (D) indicate the same sample in the row and (C)'s branch.
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Figure 5: Measurements of similarity between thermal spring and subsurface sites. Pair-wise comparisons have been made by counting the total number genera shared between sites (A) and calculation of the Sorensen similarity index (B) and Morisita dissimilarity indices (1-Morisita index) (D). Color-coding of (A,B,D) are purely for visual aid where red indicates more similar pairs and blue is indicative of more distant pairs. The diagonal of (A) indicates the number of genera identified in the sample. (C) is a visual representation of the hierarchical clustering of the Morisita dissimilarity matrix (D). Subsurface sites in (C) are labeled with pink squares and thermal spring sites are labeled with green circles. The columns of (D) are indicated by the branches of (C) whereas the columns of (A,B) are labeled. Black squares labeled 0.00 in (D) indicate the same sample in the row and (C)'s branch.

Mentions: There was a very large difference between the communities of individual thermal springs. No individual sequence was found in multiple thermal spring sites, however, when sequences were clustered into OTUs at a distance of 0.03, two OTU0.03 were shared between Eiland and Mpephu, one OTU0.03 was shared between Eiland and Sagole, and one OTU0.03 was shared between Sagole and Siloam. At the genus level, Sagole and Siloam shared the greatest number of genera (n = 41; Sørensen index = 0.35) while Souting and Tshipise shared the lowest number of genera (n = 5; Sørensen Index = 0.14) (Figures 5A,B).


Comparisons of the composition and biogeographic distribution of the bacterial communities occupying South African thermal springs with those inhabiting deep subsurface fracture water.

Magnabosco C, Tekere M, Lau MC, Linage B, Kuloyo O, Erasmus M, Cason E, van Heerden E, Borgonie G, Kieft TL, Olivier J, Onstott TC - Front Microbiol (2014)

Measurements of similarity between thermal spring and subsurface sites. Pair-wise comparisons have been made by counting the total number genera shared between sites (A) and calculation of the Sorensen similarity index (B) and Morisita dissimilarity indices (1-Morisita index) (D). Color-coding of (A,B,D) are purely for visual aid where red indicates more similar pairs and blue is indicative of more distant pairs. The diagonal of (A) indicates the number of genera identified in the sample. (C) is a visual representation of the hierarchical clustering of the Morisita dissimilarity matrix (D). Subsurface sites in (C) are labeled with pink squares and thermal spring sites are labeled with green circles. The columns of (D) are indicated by the branches of (C) whereas the columns of (A,B) are labeled. Black squares labeled 0.00 in (D) indicate the same sample in the row and (C)'s branch.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4269199&req=5

Figure 5: Measurements of similarity between thermal spring and subsurface sites. Pair-wise comparisons have been made by counting the total number genera shared between sites (A) and calculation of the Sorensen similarity index (B) and Morisita dissimilarity indices (1-Morisita index) (D). Color-coding of (A,B,D) are purely for visual aid where red indicates more similar pairs and blue is indicative of more distant pairs. The diagonal of (A) indicates the number of genera identified in the sample. (C) is a visual representation of the hierarchical clustering of the Morisita dissimilarity matrix (D). Subsurface sites in (C) are labeled with pink squares and thermal spring sites are labeled with green circles. The columns of (D) are indicated by the branches of (C) whereas the columns of (A,B) are labeled. Black squares labeled 0.00 in (D) indicate the same sample in the row and (C)'s branch.
Mentions: There was a very large difference between the communities of individual thermal springs. No individual sequence was found in multiple thermal spring sites, however, when sequences were clustered into OTUs at a distance of 0.03, two OTU0.03 were shared between Eiland and Mpephu, one OTU0.03 was shared between Eiland and Sagole, and one OTU0.03 was shared between Sagole and Siloam. At the genus level, Sagole and Siloam shared the greatest number of genera (n = 41; Sørensen index = 0.35) while Souting and Tshipise shared the lowest number of genera (n = 5; Sørensen Index = 0.14) (Figures 5A,B).

Bottom Line: Proteobacteria were identified as the dominant phylum within both subsurface and thermal spring environments, but only one genera, Rheinheimera, was identified among all samples.Using Morisita similarity indices as a metric for pairwise comparisons between sites, we found that the communities of thermal springs are highly distinct from subsurface datasets.Although the Limpopo thermal springs do not appear to provide a new window for viewing subsurface bacterial communities, we report that the taxonomic compositions of the subsurface sites studied are more similar than previous results would indicate and provide evidence that the microbial communities sampled at depth are more correlated to subsurface conditions than geographical distance.

View Article: PubMed Central - PubMed

Affiliation: Department of Geosciences, Princeton University Princeton, NJ, USA.

ABSTRACT
South Africa has numerous thermal springs that represent topographically driven meteoric water migrating along major fracture zones. The temperature (40-70°C) and pH (8-9) of the thermal springs in the Limpopo Province are very similar to those of the low salinity fracture water encountered in the South African mines at depths ranging from 1.0 to 3.1 km. The major cation and anion composition of these thermal springs are very similar to that of the deep fracture water with the exception of the dissolved inorganic carbon and dissolved O2, both of which are typically higher in the springs than in the deep fracture water. The in situ biological relatedness of such thermal springs and the subsurface fracture fluids that feed them has not previously been evaluated. In this study, we evaluated the microbial diversity of six thermal spring and six subsurface sites in South Africa using high-throughput sequencing of 16S rRNA gene hypervariable regions. Proteobacteria were identified as the dominant phylum within both subsurface and thermal spring environments, but only one genera, Rheinheimera, was identified among all samples. Using Morisita similarity indices as a metric for pairwise comparisons between sites, we found that the communities of thermal springs are highly distinct from subsurface datasets. Although the Limpopo thermal springs do not appear to provide a new window for viewing subsurface bacterial communities, we report that the taxonomic compositions of the subsurface sites studied are more similar than previous results would indicate and provide evidence that the microbial communities sampled at depth are more correlated to subsurface conditions than geographical distance.

No MeSH data available.


Related in: MedlinePlus