These PCTL were created by subjecting all the sampling equipment to experimental processing in the absence of sample, including assembly and processing within the lab and at the field site. Cells were dislodged from filters via vortexing in 10 mL of Buffer A [ mM tris hydroxymethyl aminomethane pH 8. Genomic DNA was extracted from the pelleted cells using a low biomass bead beating protocol Barton et al. Each sample was labeled with a unique barcode Kozich et al.
For alpha-diversity metrics, rarefied OTU tables were generated from sequence data in QIIME using a step size of sequences and an even sampling depth of 3, sequences. Species richness for each sample was calculated using the Chao 1 non-parametric estimator over 10 randomized iterations of sampling, with the median values used for a best fit line generated in R Chao, ; Venables and Ripley, ; Wickham, , There are a number of surface springs and wells near Wind Cave that provide access to water from the Madison aquifer Long and Valder, , of which two wells PW2 and STR and one spring BCS , are found in in the same hydrogeologic domain as Wind Cave as evidenced by the similarity in stable isotope values and chemistry to lakes found in the cave; Back, In order to determine how much water would need to be filtered to collect sufficient cells for DNA extraction, we carried out cell counts Table 2.
The lakes at WCL contained an average of 2. These cell numbers are much lower than anticipated, as previous observations of other karst springs have cell counts in the range of 10 5 - 10 6 cells mL -1 Farnleitner et al.
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The higher cell numbers seen in BCS 8. Culture-based analyses on selective media indicated that this microbial population included members of the Enterobacteriaceae data not shown , making it impossible to distinguish native from contaminant microorganisms, and no additional sampling was carried out at BCS. The comparatively high arsenic concentration in PW2 Table 1 , suggested that the water in this well was contaminated by a significant intrusion of water from the shallower Minnelusa aquifer Supplementary Figure S1 ; Back, , complicating the interpretation of the microbiology PW2 was subsequently sealed and made inaccessible by WCNP due to high arsenic levels.
To determine the contribution of archaea to these populations, we combined FISH with our cell counting methods. We were unable to count archaea in the STR sample above background control values Table 2. During our bacterial cell counts, no eukaryotes were visible in the WCL water samples. To confirm this, we counted cells in 10 L samples Table 2.
To determine whether the very low planktonic cell numbers in WCL represented a statistical outlier, samples were collected for counting from WCL over the course of six years and analyzed in two independent laboratories, using a variety of separation techniques to obtain more robust counting data. Our data Table 2 indicated that cell numbers within WCL are relatively constant, with at an average of 2. The results from all methods across three separate sampling periods ranged from 1.get link
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A rarefied analysis of the sequenced products Chao, ; Figure 2 suggested that the WCL community demonstrates a significantly higher species richness and diversity than that found at STR, despite the fold reduction in the amount of available organic carbon 0. Indeed, the rarefaction curve for WCL suggests that the lakes contains hundreds of unique species, while STR phylotypes are more broadly represented within the analyzed data as expected, there is limited diversity in the preparation control; Figure 2.
Chao 1 points were generated using median abundance values of sample replicates, randomly subsampled with replacement at even sampling depths over 10 iterations. A best fit curve was generated using a robust linear model. Analysis of the identified taxa revealed a broad phylum-level diversity within both the WCL and STR samples, with 14 and 11 represented phyla, respectively Figure 3. Three PCR replicates were performed for each sample.
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Past hydrological analyses have suggested that STR well provides a convenient access point to sample the same aquifer as that found in the cave; however, the observed microbiology data does not support this. The preparation control sample PCTL contained far fewer sequencing products, with only three phyla present, including the Proteobacteria, Firmicutes , and Actinobacteria ; this low diversity likely reflects the scant DNA amplified from pooled controls Figure 3. Despite the much lower available organic carbon in the WCL sample, the community appeared evenly distributed across several phyla, while STR is dominated by one phylotype Figure 3 and Supplementary Table S1.
In order to determine whether species richness was statistically different between samples, we used the reciprocal Simpson index to quantify the average proportional abundance of each taxa in the sample. The results Figure 4A suggest that there were more taxa represented in the WCL sample, with a higher proportional representation richness in the population Interlandi and Kilham, This analysis confirms the observation that STR is dominated by one species. Population differences between the sample sites were further visualized using a weighted Unifrac principle coordinate analysis PCoA; Figure 4B.
To determine whether the WCL and STR populations shared similarity with other karst communities despite being distinct from each other , we expanded our PCoA analysis to include comparable environments Figure 5A. These sites were chosen based on oligotrophic conditions, sampling of pelagic microbial communities, and pyrosequencing.
Analyses are therefore based on sequencing method pyrosequencing , PCR primers and average number of amplicons. Three different distance methods normalized-weighted Unifrac, unweighted Unifrac, and the non-phylogenetic Bray-Curtis metric were used to generate distance matrices for PCoA to visualize differences between the samples in this study and the data from the comparable environments. All metrics used generated similar grouping patterns in a principle coordinate analysis; due to the varying samples sizes used among studies we used the unweighted Unifrac metric which is qualitative, rather than quantitative; Figure 5A.
In order to determine whether there were similarities in species richness between the karst aquifers, we again we used a comparable Reciprocal Simpson index, with a best fit projection for samples with fewer available sequences Figure 5B. The results demonstrated that the site that shares the closest hydrogeological similarity to WCL, the German limestone aquifer, also demonstrated high species richness.
In all cases, STR had the lowest overall diversity, despite being structurally similar to WCL in terms of geologic isolation and aphotic conditions Figure 5B. Wind Cave is one of the most geologically complex caves in the world, the structure of which provides the rare opportunity to travel into the subsurface and directly sample the microbiology of the Madison aquifer Figure 1 ; Palmer and Palmer, Given the physical and technical challenges of examining the aquifer via the cave Figure 1A , we wanted to examine how the microbiology sampled through the cave compared to the more easily accessible surface wells PW2 and STR and spring BCS.
Despite purging more than three volumes 2, liters of water from STR as recommended in past protocols; Hose and Lategan, ; Korbel et al. Thus, while the main volume of water from STR may be from the same hydrogeologic domain as Wind Cave, it is mixing with the higher organic content, SO 4 2- , and microbiology of the Minnelusa Supplementary Figure S1 ; Atlas et al. There appears to be microbiological evidence for this water mixing within the STR well. While total cell numbers were comparable between the two sites 6.
This OTU had the greatest sequence identity to an uncultured Acidithiobacillales clone KCM-B, which has been found in environments with high hydrocarbon content Garrity et al.
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While this suggests that hydrocarbon breakdown may drive community energetics within STR, the closest cultured species, Thioalkalivibrio sulfidiphilus , is a chemolithotrophic, sulfur-oxidizer, suggesting that S-cycling may also be important Muyzer et al. Nonetheless, T.
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In contrast, WCL is completely contained within the Madison limestone formation and not exposed to the organic content of the Minnelusa Formation Supplementary Figure S1. Our work supports the findings of Korbel et al. Thus, while STR may be a more easily accessible sample site for access to the water chemistry of the Madison aquifer, accurate microbiological investigations of this important water source require sampling via the cave.
Consequently, the samples collected through the cave provide the most accurate window into the microbiology of the Madison aquifer. At the phylum level, in addition to Gammaproteobacteria , the WCL community contained members of the Actinobacteria and Firmicutes , and significant contributions from the Planctomycetales, Nitrospirae, Fusobacteria, Chloroflexi and Omnitrophica Figure 3.
The Actinobacteria and Firmicutes are dominated by members of the Actinomycetales, Bacillaceae, Pseudomonadales , associated with carbon turnover in soils Barton, It is unclear as to a potential source of this NO 3 - in WCL; however, the nearby South Dakota Badlands are comprised of caliche, which are nitrate-rich paleosols deposited when conditions were more arid in this semi-arid region.
Given the close association of the Badlands with a local recharge zone or the potential for deep burial, it may be that the waters pass through such deposits en route to WCL. Members of the Nitrospirae are primarily associated with nitrite oxidation, with some members capable of complete nitrification of ammonia to nitrate Daims et al.
The Nitrospirae have also been shown to be slow growing and metabolically flexible, with the ability to grow mixotrophically under microaerophilic or anaerobic conditions Fujitani et al. With limited or no cultured representatives, the metabolic activity of the Planctomycetales, Chloroflexi and Omnitrophica make their activity in the environment difficult to predict.
Nonetheless, these phyla are often highly represented in oligotrophic environments, particularly caves, where they appear to grow using oxidized-carbon compounds under extreme nutrient-limited conditions Fuerst and Sagulenko, ; Barton, Members of the Omnitrophica are widely distributed in subsurface environments Rinke et al. These data, along with the observation of other iron-cycling genera, such as Geothrix , suggest that iron which is abundant within Wind Cave may be an important driver of autotrophic growth Kolinko et al.
These data suggest that autotrophic growth within WCL may be driven by iron, nitrogen and carbon cycling, similar to that observed in similar German karst aquifer and the nearby deep Sandford Underground Research Facility Herrmann et al. At the phylum level, the taxa observed in WCL appeared to be similar to that seen in other karst environments aquifers and springs and remain distinct from communities influenced by surface nutrient sources, such as Lake Brienz Figure 5A. The WCL samples cluster together with the other karst aquifers, but remain distinct from the epigenic cave stream created where surface waters flows into the subsurface; Figure 5A.
This is likely due to similar sampling strategies, with the German limestone aquifer and Edwards aquifer using well access and similar primer sets; however, humanly accessible caves do not intersect these aquifers at depth, preventing in-cave sampling Engel and Randall, ; Herrmann et al. The PCTL itself was dominated by members of the Legionella , which generally live inside amoebae in the natural environment Harf and Monteil, We were unable to detect eukaryotic microorganisms within the lake via PCR amplification or direct microscopic observation, and the dominance of Legionella in the preparation control may reflect contamination of purchased buffers DNase- and RNase-free laboratory water controls did not contain such contamination.
Such contamination has been shown to be present in commercial laboratory reagents, further emphasizing the importance of PCTL when working with low biomass samples Shen et al. One of the most notable observations from this study was that the WCL samples, under the lowest nutrient conditions, had amongst the highest observed diversity Figure 5B.
Microbial ecologists have attempted to describe the differences that account for this phenomenon, arguing that environmental heterogeneity, mixing and even predation prevent the establishment of true competitive exclusion, allowing for high species richness even in the most starved environments Czaran et al.
An alternate explanation is that of Interlandi and Kilham , who examined planktonic diatom diversity in oligotrophic lake systems. These investigators argued that resource competition itself was driving high diversity: despite the bulk water chemistry being homogenous, at the scale of individual microbial cells, there is sufficient resource variation to promote competition between species even in low biomass environments; Interlandi and Kilham, The absence of light, low biomass, ultra-oligotrophic conditions, and limiting P may therefore contribute to the high diversity observed within both WCL and the German limestone aquifer Figure 5B ; Herrmann et al.
This work represents the first study of the microbiology of a deep, geologically isolated aquifer sampled directly via access through a cave. Our data suggest that Wind Cave provides a unique access point to study the microbial community of an aquifer without the confounding variables introduced via well or spring sampling Yanagawa et al. The data suggest very different community energetics than would have been suggested through sampling a well and indicate that the microbial communities have a much higher potential to influence the quality of drinking water than would have been determined from well-based analyses for example, denitrification; Herrmann et al.
Nonetheless, the growing population and development of the Black Hills region means that demand on the Madison aquifer has increased. If these wells draw water faster than the local recharge rates, this could result in a dramatic drop in the potentiometric surface of the Madison aquifer Greene, If the aquifer were to drop below the current level of the cave, access via Wind Cave and the unique ability to sample the microbiology independent of well access will be gone. It is therefore critical to carry out as many microbiological analyses of this important aquifer before the site is lost.
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. We would like to thank the staff at Wind Cave National Park for in cave assistance and carrying equipment to the sample sites, in particular Marc Ohms, for his never-ending patience with the repeated sampling expeditions over the years, and Jeff Hughes for his faith in the interesting microbiology of the Wind Cave lakes.
We would like to thank Juan Giarrizzo for the initial development of the sampling equipment that allowed us to filter L of water under the weight and size constraints of the cave, DNA extraction, PCR analysis and sequencing. We would also like to thank the contributions of the reviewers, whose comments greatly increased the quality of this paper.