Analysis of bacterial diversity in soils from Blowing Spring Cave (Lauderdale County, AL).
Subterranean environments have been shown to display relatively simple bacterial communities. More data on the diversity of bacteria present in these subterranean environments would help to establish a baseline for these ecosystems. Cave environments typically have limited light penetration and varied amounts of nutrient influx. Due to the limited availability of nutrition and the subsequent competition for these resources, these areas could reveal interesting bacterial community structures and interactions. Blowing Spring Cave (Lauderdale County, Alabama) was selected for this study and environmental DNA samples were isolated from soil samples taken from Blowing Spring Cave. A highly conserved region within the 16S rRNA gene was PCR amplified from these environmental DNA samples. 16S rRNA libraries representative of the soil bacterial community were generated and sequences from these libraries were compared to other 16S rRNA sequences available in GenBank. The most prevalent phylum in this cave soil sample was proteobacteria, with 43% of the sequences grouping into three sub-phyla: gamma-proteobacteria (23%), alpha-proteobacteria (19%), and beta-proteobacteria (1%). The remaining 57% separated into the following phyla: planctomycetales (12%), actinobacteria (9%), gemmatimonadetes (9%), firmicutes (5%), chloroflexi (5%), acidobacteria (4%), and 13% of unknown bacterial origin.
Caves represent unique environments because they offer the ability to study organisms that have limited contact with the surface and photosynthetic carbon sources, and therefore represent areas with low nutrient availability (Engel et al., 2004; Simons et al., 2008). Blowing Spring Cave is a limestone formation created via carbonic acid and water erosion. A small creek runs through it year round and exits at the cave's mouth. The hydrology of this environment can have a profound impact on the nutrition of the ecosystem and transient members of the consortia can be deposited from flush and sediment. The water flow also provides potential nutrient input from both dissolved organic carbon and coarse particulate organic matter (Simons et al., 2008). Limestone can also be rich in reduced sulfur, iron, and manganese compounds, which microbes can use via redox reactions (Northrup and Lavoie, 2001).
Some cave microbial communities have been shown to have low biotic composition complexity (Engel et al., 2004). Thus, it is easier to study community microbial interactions of this limited consortium. Soil bacterial concentrations are typically higher when associated with the soil interspaces found near the plant rhizosphere (Housman et al., 2007). Due to a lack of vegetation in caves, the bacterial community has evolved methods to obtain carbon from other sources, such as animal or microbial. It has been reported that there is an abundance of anaerobic activity in caves, where high concentrations of unoxidized organic matter are present (Hose et al., 2000). This unoxidized matter is possibly a carbon source that could compensate for the lack of vegetation.
Some studies have indicated chemolithotrophic bacteria activities in caves, causing biofilms and snottites, which form as extensions of microbial biofilms that coat the walls and ceilings of caves (Hose et al., 2000). Interesting microbial interactions may be present within these biological formations. According to Groth, et al., (1999) there is evidence to show that certain cave bacteria, namely actinobacteria, can produce chemicals with potential benefits to the field of medicine and industry, with (bbyproducts) useful as antibiotics and anticancer agents. Past reviews have shown that both detrital and productive systems exist in caves. Productive systems require an energy source, and in subterranean environments, the sources are typically of a geochemical nature in contrast to the photosynthetic sources of surface organisms (Stevens, 1997).
Caves are environments that can vary greatly from those found on the surface and are typically energetically stable with relatively high humidity and low constant temperature (Laiz et al., 1999). Subterranean microorganisms tend to have a low metabolic rate, creating a scenario that favors maintenance over growth (Stevens, 1997). Studies by Schabereiter-Gurtner et al. (2004) in two Spanish caves (Llonin and La Garma) and Engel et al. (2004) in Lower Kane Cave, Wyoming, both found proteobacteria to be the most common phylum present in those cave soils. Lower Kane Cave samples were taken from microbial mats and consisted of epsilon-proteobacteria (67%), gamma-proteobacteria (12%), beta-proteobacteria (12%), delta-proteobacteria (1%), acidobacteria (6%), and bacteroides and chlorobi (2%). The Spanish cave samples were taken from cave paintings and the surrounding rock surfaces and consisted of proteobacteria (41%)), acidobacteria (16%), actinobacteria (20%), firmicutes (11%), cytophaga/flexibacter/bacteroides (6%), nitrospira (4%), chloroflexi (1%), and candidate WS3 division (1%). Distinct differences in sampling sites characterized the Engel et al. (2004) study, which pertained to a sulfuric acid pool and had lower diversity than that of the Schabereiter-Gurtner et al. (2004) study, which pertained to samples taken from cave paintings and their surroundings.
Research focusing on CAVEcave ecosystems has been rather limited and most of the work concerning the bacterial diversity in caves has utilized conventional culturing methods. These methods are problematic in that they only allow detection of culturable bacteria, which typically represent less than 5% of the bacteria present in any given sample (Desai et al., 2006). In this study, we utilized polymerase chain reaction (PCR), cloning, and sequencing of a portion of the 16S rRNA gene to evaluate the bacterial community of the cave soil sample environment of Blowing Spring Cave (Lauderdale County, AL). These molecular techniques have a greater scope of bacterial identification than traditional culture techniques (Schabereiter-Gurtner et al., 2004).
MATERIALS AND METHODS
Site selection and sample collection
Blowing Spring Cave (Lauderdale County, AL., T2S, R7W, Section 19; 34.8644[degrees], -87.3039[degrees]) is located on a 60 acre tract under the management of the Alabama Department of Conservation and Natural Resources (AL-DCNR). This location is a maternal gray bat colony site and is closed to the public, and therefore represents a It is relatively pristine cave system. with limited human contamination and due to the stream it represented a hydraulically unique sample site. Soil samples were collected in duplicate from two sites within the cave using sterile 20 mL centrifuge tubes. One soil sample from was taken from a rock shelf layer that was approximately one meter above the floor; while the second soil sample was taken directly from the cave floor. Samples sets were taken by scraping the top 2.5 cm of the soil, which displayed no observable layers at this sampling depth. Approximately 5 grams of soil per site was collected and stored at -20[degrees].
DNA isolation and 16S rRNA gene amplification
DNA was isolated from 0.25 g of soil from each of the two collection sites (sampled in duplicate for a total of four processed samples) using PowerSoil[tm] DNA Isolation Kit (MoBio Laboratories Inc., Carlsbad, CA) with a modification of the published protocol (additional incubation at 70 [degrees]C for 10 min.). Standard concentrations (200ng/uL) of DNA taken from both cave shelf and cave floor were pooled (1:1 ratio), mixed and then used as template in subsequent PCRs. The final concentrations per reaction were WAS: 3 units of hot start Taq polymerase, 200 uM dNTPs, 4mM [MgCl.sub.2], 0.4 mM 27F (5'-AGAGTTTGATCCTGGCTCAG-3') and 0.4 mM 1492R (5'-GGTTACCTTGTTACGACTT-3') 16S eubacterial primers (Dojka; et al, 1998), and 1 uL of DNA template with final reaction volume of 25 [micro]l. The PCR parameters were as follows: initial melt at 94[degrees]C for 12 min followed by 25 cycles of 94 [degrees]C for 30 sec, (SEC??) 50 [degrees]C for 30 sec (SEC??) and 72 [degrees]C for 60 sec (SEC??) and a final hold at 72[degrees]C for 5 min. The PCR amplified products (approximately 1,400 bp in length) were analyzed using agarose (0.9%) gel electrophoresis.
Clonal library construction
PCR products were cloned using the pCR8/GW/Topo[R] vector (Invitrogen Inc., Carlsbad, CA). Transformations were performed using One Shot[R] competent E. coli via manufacturer's protocol (Invitrogen Inc., Carlsbad, CA). The transformed cells were grown overnight at 37 [degrees]C on LB/agar plates containing 100 [micro]g/ml of spectinomycin. A total of 120 colonies were selected for screening and plated onto LB/agar grid plates with spectinomycin (l00ug/ml) and incubated at 37 [degrees]C overnight. Selected clones were grown in 5 ml LB broth with 50[micro]g/ml of spectinomycin and incubated overnight at 37 [degrees]C. Recombinant plasmids were isolated from the selected clones using a QIA prep[R] Spin Mini Prep Kit (Qiagen Inc., Valencia, CA) per manufacturer's protocol. The quantity and quality of each plasmid preparation was analyzed via spectrophotometer and then stored at 4 [degrees]C.
Sequencing was conducted using Beckman Coulter GenomeLab [tm] Dye Terminator Sequencing with Quick Start Kit (Beckman Coulter Inc., Fullerton, CA). Sequencing reactions were setup using the following reaction conditions: 100 ng of plasmid, 1.6 [micro]M of 16S forward primer (27F), 2 [micro]1 of dye terminator cycle sequencing reaction (DTCS) mix and sterile water was added to bring the total volume to 10 [micro]l The cycling conditions were as follows: initial melt at 96 [degrees]C for 1 min, followed by 30 cycles of 96 [degrees]C for 20 sec, 50 [degrees]C for 20 sec, 60 [degrees]C for 4 min. Following the PCR amplification reaction, each reaction product was purified via ethanol precipitation. These PCR amplified products were then analyzed using the Beckman Coulter CEQ 8000 Genetic Analysis System (Beckman Coulter, Inc., Fullerton, CA).
Analysis was performed using the MEGA4.0 software (http://www.megasoftware.net). All sequences used in these analyses were a minimum of 500 base pairs after quality-based trimming on both the 5' and 3' ends. Results were compared to known sequences using the NCB1 database Basic Local Alignment Search Tool (BLAST). Select sequence matches from BLAST (with similarities >97%) and those from the cave were aligned and trimmed with the CLUSTAL alignment tool. Phylogenetic trees based on 16S rRNA sequences were constructed using the Neighbor-Joining (NJ) method of analysis. Further, the reliability of each tree was estimated by conducting bootstrap sampling. Bootstrap values were based on 100 bootstrap replicates. Rarefaction data was calculated, based on phyla, using RarefactWin software (http://www.uga.edu/strata/software/) to determine the optimal number of sequences utilized for phylogenetic analysis in this study (i.e., coverage of the bacterial community at the sample site). GenBank accession numbers for the bacterial 16S rRNA gene sequences used for phylogenetic analysis and tree construction were as follows: Acidobacteria (DQ167080), Actinobacteria (AF409026), Actinobacteria (AY795640), Firmicutes (AJ544784), Gemmatimonadetes (AY795731), Alpha-proteobacteria (AY795711), Alpha-proteobacteria (AY371423), Alpha-proteobacteria (EF575560), Alpha-proteobacteria (EF018616), Alpha-proteobacteria (FJ543062), Beta-proteobacteria (123791). Gamma-proteobacteria (AY795728). GenBank accession numbers for non-redundant bacterial 16S rRNA gene sequences identified in this study are as follows: Uncultured bacterium--clone 7 (GU944688), Uncultured bacterium--clone 13 (GU944687), Uncultured bacterium--clone 26 (GU944686), Uncultured bacterium--clone 28 (GU944685), Uncultured bacterium--clone 44 (GU944684), Uncultured bacterium clone 79 (GU944683), Uncultured bacterium--clone 89 (GU944682), Uncultured bacterium--clone 106 (GU944681), Uncultured bacterium--clone 1 17 (GU944680).
A total of 120 clones were sequenced in this study. Seventy eight of the clones met the minimum criteria for inclusion in the final analysis, which consisted of a 500 bp partial 16S rRNA sequence from forward priming. Sixty one unique sequences were found of these 78 clones. Those with greater than 98% similarity were considered to be replicates. Sequences were grouped with their most closely related phyla/sub-phyla using NCBI database. MEGA 4.0 genetic analysis software suite was used to create a phylogenetic analysis of the 16S clones from Blowing Spring Cave, with bootstrapping analysis (i.e., 100 bootstrap replicates) of tree reliability (Fig. 1).
[FIGURE 1 OMITTED]
A total of seven known phyla were found, including proteobacteria. Two distinctive unknown groups were reported as unknown-1 and unknown-2 and were not categorized within any known phylum. The most prevalent phylum was proteobacteria with 43% of the total organisms found grouping into three sub-phyla: gamma-proteobacteria (23%), alpha-proteobacteria (19%), and beta-proteobacteria (1%). Remaining sequences separated into the following phyla: planctomycetales (12%), actinobacteria (9%), gemmatimonadetes (9%), firmicutes (5%), chloroflexi (5%), and acidobacteria (4%). Both unknown-1 and unknown-2 represented 6% of the total organisms (Fig. 1). Rarefaction data was completed using phyla organization to determine coverage of the bacterial diversity for the sample site. This rarefaction data indicated that the point where additional sampling produced no additional information about the number of phyla present in the Blowing Spring Cave soil samples (ie., optimal number of sequences utilized) was 60 sequences.
Phyla-based analysis is typical of studies from extreme environments due to the rarity of individual species; therefore, the data from this study are presented at the level of phyla present in the soil samples. This limitation of specificity was due to method resolution and lack of species specificity in known 16S rRNA gene sequences. Phyla based analysis is typical of studies from extreme and unique environments due to the rarity of individual species and this method allows better comparisons with both culture and molecular methods in the literature. Rarefaction analysis was used to determine phyla-based curves. While rarefaction was designed as a species richness tool, it has been reported to be useful on higher taxonomic levels as well (Raup, 1975). Schabereiter-Gurtner et al. (2004) and Engel et al. (2004) both reported that the highest number of sequences at their study sites grouped with proteobacteria, as did 43% of sequences analyzed from Blowing Spring Cave (Table 1).
Table 1. Comparison of bacterial phyla present in three cave studies (Blowing Spring Cave, AL, Lower Cane Cave (Engel; et al, 2004), and Spanish Caves (Schabereiter et al., 2004)) and five forest & agricultural samples from Horse Shoe Bend, GA (Upchurch et al., 2008). Bacteria Present Cave Sample (% Present) Blowing Lower Llonin Springs Cane and La Cave Cave Garma Caves Acidobacteria 4 5.6 16.5 Actinobacteria 9 20 Bacteroides 1.7 5.9 Chlorofexi 5 1.2 Firmicutes 5 10.6 Gemmatimonadetes 9 Nitrospira 3.5 Planetomycetales 12 Proteobactcria 43 92.7 41.1 Verrucomicrobia WS3 division 1.2 Unknown 13 Bacteria Present Forest and Agricultural Samples (% Present) CT5 NT2 NT5 NF5 OF2 OF5 Acidobacteria Actinobacteria 4.3 10 13.8 10.1 1.1 8 Bacteroides 4.3 1.8 1.7 3 2.1 Chlorofexi 1 Firmicutes 1 1.8 0.9 4 1.1 Gemmatimonadetes 5.3 1.8 6.8 2 1.1 1.1 Nitrospira 1.1 1 1.1 Planetomycetales 7.3 0.8 2 1.1 3.4 Proteobactcria 33.3 33.9 51 32.3 43.9 32.1 Verrucomicrobia 4.3 6.4 5.1 4 13.1 3.4 WS3 division Unknown 45 37 19.9 41.6 37.6 49.8
Comparisons of these samples indicated distinct differences between the subterranean and forest/agricultural environments; most notably the phylum acidobacteria, which was only reported in the cave samples, while the phylum verrucomicrobia only showed up in the forest and agricultural samples (Upchurch et al, 2008). The phylum chloroflexi was also more prevalent in cave samples, only showing up at a low percentage (1%) in one of the five forest and agricultural samples. Rarefaction analysis was performed on the sample sites at Horse Shoe Bend, Lower Cane Cave, Llonin and La Garma Caves, and Blowing Spring Cave. The phyla-based diversity differed more within each particular environment than between the two types of environments (caves versus forest/agricultural). There were similarities between the caves and forest/agricultural environments, including proteobacteria being the most prevalent phylum.
Proteobacteria is a highly diverse phyla with five associated sub-phyla, three of which were found in the Blowing Spring Cave sample. One of the 16S rRNA sequences (sequence 31) displayed a homology of 98.2% to that of beta-proteobacteria genus Nitrosospira, which is a known ammonia oxidizing bacteria having the ability to transform ammonia ([NH.sub.3],) to nitrite ([NO.sub.2]") and can do these processes in relatively low concentrations (less than 1 mM) of ammonia versus other genera, such as Nitrosomonas, which tend to thrive in higher concentrations (Taylor et al., 2006). The alpha-protcobacteria associated families of Rhodobacteraceae, Phyllobacteriaceae, and Rhizobiaceae were also present in the Blowing Spring Cave soil samples. Rhizobiaceae includes several species that are known to be associated with nitrogen fixation, as well as other environmental roles. (De Castro et al., 2008). Planctomyeetales was the second highest represented phyla (12%) in Blowing Spring Cave soil samples, and according to Barion et al. (2007), it may have been one of the first groups to diverge in Domain Bacteria. Planctomyeetales contain slow-growing bacteria and has been reported to have anaerobic ammonium-oxidizing species often found working in consortium with chloroflexi and proteobacteria (Liu et al, 2008), both of which were present in the Blowing Spring Cave soil samples. Actinobacteria, a phylum with known chitinolytic species, was also found in Blowing Spring Cave soil samples (9%). Some of these chitinolytic species can also produce antifungal agents specifically against organisms in Fusarium, the causative agent of white nose syndrome in bats in the northeastern United States (Yasir et al., 2009). The phylum gemmatimonadetes is a newly recognized phylum and was found to be present in Blowing Spring Cave soil samples (9%). Little is known about this phylum, but appears to be ubiquitous in environmental soil samples. Firmicutes, specifically Bacillus spp., have the ability to reduce nitrate to ammonia (Rajakumar et al., 2008), have protease, chitinase and [beta]-keratinase activities (Brar et al., 2009). Species from this genus have been studied as bioremediaiors, as antibiotic producing bacteria, and have been used in other applications. Chloroflexi (5%) include many photosynthetic bacteria, and species within this phylum have been used in the dechlorination of poly chlorinated biphenyls (PCBs) and other bioremediation applications (Field et al., 2008). Acidobacteria is also a relatively new phylum and is not yet well understood, but it is prevalent in many environments, including this cave soil sample (4%). The two groups, unknown-1 and 2, each represented 6% of total sequences and clearly separate from one another (and consequently from the other eight phyla). These two groups also had no close matches (<75% homologies) in GenBank.
This study establishes a baseline for the study of microbial communities in Blowing Spring Cave and contributes to the understanding of bacterial communities in OTHERother cave systems. Further, it is possible that the loss of natural microflora, such as actinobacteria (which are know to produce antifungal compounds) could allow Fusarium to proliferate and infect the bat populations within the cave (Yasir et al., 2009). Loss of naturally occurring bacteria in such cave systems could also allow for the influx of invasive and/or pathogenic bacteria, which could subsequently affect yet other natural microflora and other organisms in the ecosystems. Competition or antimicrobial properties of novel microbes may remove or change the metabolic activities of the natural microflora, which could remove an important link in the native nutrient chain in these cave systems.
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Samual K. Barron (1), Chris A. Murdock (1) *, Benjie G. Blair (1) Barron, Benjie Blair, Mark E. Meade (1) and T. Wayne Barger (2)
(1) Department of Biology, Jacksonville State University, 700 Pelham Road N., Jacksonville, AL 36265
(2) Alabama Department of Conservation and Natural Resources, 64 North Union Street, Montgomery, Alabama 36130
Corresponding: Chris A. Murdock (firstname.lastname@example.org)
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|Author:||Barron, Samual K.; Murdock, Chris A.; Barron, Benjie, Blair G.; Blair, Benjie; Meade, Mark E.; Barge|
|Publication:||Journal of the Alabama Academy of Science|
|Date:||Jan 1, 2010|
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