FEMS Microbiology Ecology 51 (2004) 31–53
www.fems-microbiology.org
Bacterial diversity and ecosystem function of filamentous
microbial mats from aphotic (cave) sulfidic springs dominated by
chemolithoautotrophic ‘‘Epsilonproteobacteria’’
Annette Summers Engel a,*,1, Megan L. Porter b, Libby A. Stern a,
Sarah Quinlan c, Philip C. Bennett a
a
Department of Geological Sciences, Research Group for Microbial Geochemistry, University of Texas at Austin, Austin, TX 78712, USA
b
Department of Microbiology and Molecular Biology, Brigham Young University, Provo, UT 84602, USA
c
Department of Integrative Biology, Brigham Young University, Provo, UT 84602, USA
Received 29 December 2003; received in revised form 9 June 2004; accepted 12 July 2004
First published online 7 August 2004
Abstract
Filamentous microbial mats from three aphotic sulfidic springs in Lower Kane Cave, Wyoming, were assessed with regard to
bacterial diversity, community structure, and ecosystem function using a 16S rDNA-based phylogenetic approach combined with
elemental content and stable carbon isotope ratio analyses. The most prevalent mat morphotype consisted of white filament bundles,
with low C:N ratios (3.5–5.4) and high sulfur content (16.1–51.2%). White filament bundles and two other mat morphotypes had
organic carbon isotope values (mean d13C = 34.7&, 1r = 3.6) consistent with chemolithoautotrophic carbon fixation from a dissolved inorganic carbon reservoir (cave water, mean d13C = 7.4& for two springs, n = 8). Bacterial diversity was low overall in the
clone libraries, and the most abundant taxonomic group was affiliated with the ‘‘Epsilonproteobacteria’’ (68%), with other bacterial
sequences affiliated with Gammaproteobacteria (12.2%), Betaproteobacteria (11.7%), Deltaproteobacteria (0.8%), and the Acidobacterium (5.6%) and Bacteriodetes/Chlorobi (1.7%) divisions. Six distinct epsilonproteobacterial taxonomic groups were identified
from the microbial mats. Epsilonproteobacterial and bacterial group abundances and community structure shifted from the spring
orifices downstream, corresponding to changes in dissolved sulfide and oxygen concentrations and metabolic requirements of certain
bacterial groups. Most of the clone sequences for epsilonproteobacterial groups were retrieved from areas with high sulfide and low
oxygen concentrations, whereas Thiothrix spp. and Thiobacillus spp. had higher retrieved clone abundances where conditions of low
sulfide and high oxygen concentrations were measured. Genetic and metabolic diversity among the ‘‘Epsilonproteobacteria’’ maximizes overall cave ecosystem function, and these organisms play a significant role in providing chemolithoautotrophic energy to the
otherwise nutrient-poor cave habitat. Our results demonstrate that sulfur cycling supports subsurface ecosystems through chemolithoautotrophy and expand the evolutionary and ecological views of ‘‘Epsilonproteobacteria’’ in terrestrial habitats.
2004 Federation of European Microbiological Societies. Published by Elsevier B.V. All rights reserved.
Keywords: Cave; 16S rRNA; Clone library; Carbon isotopes; Chemolithoautotrophy; Epsilonproteobacteria
1. Introduction
*
Corresponding author. Tel.: +1 512 471 5413; fax: +1 512 471
5766.
E-mail address: [email protected] (A.S. Engel).
1
Current address: Department of Geology and Geophysics, Louisiana State University, Baton Rouge, LA 70803. Tel.: 1 225 578 2469;
fax: 1 225 578 2302.
Microbial processes occurring in the absence of light
have generally been considered insufficient to support
ecosystem-level processes, and until recently the dogma
has been that life processes in the subsurface are
0168-6496/$22.00 2004 Federation of European Microbiological Societies. Published by Elsevier B.V. All rights reserved.
doi:10.1016/j.femsec.2004.07.004
32
A.S. Engel et al. / FEMS Microbiology Ecology 51 (2004) 31–53
dominated by heterotrophic consumption of surfacederived carbon [1–4]. But the absence of light does not
preclude life, as reactive mineral surfaces and solute-rich
groundwater provide energy sources sufficient for chemolithoautotrophic growth in the subsurface [5,6]. Chemolithoautotrophy is now recognized as an important
ecosystem-level process in aphotic terrestrial environments, including deep aquifers [2,6] and caves [7–9]. Because subsurface habitats are relatively difficult to
access, however, less is known about the biodiversity
and community structure, or ecosystem functioning
and carbon cycling of terrestrial chemolithoautotrophically-based microbial ecosystems.
Caves represent distinctive habitats with complete
darkness, relatively constant air and water temperatures,
and a poor supply of easily degradable organic matter.
Consequently, most cave ecosystems depend on allochthonous organic material for energy [10,11]. Previous
investigations describing microorganisms from caves
and karst settings [1,12,13], including from both moist
sediments and aquatic habitats, have suggested that
most cave microbes originate from surface environments
and are only active under optimal growth conditions
[14]. However, groundwater bearing dissolved hydrogen
sulfide and negligible allochthonous carbon discharges
as springs into the passages of some caves [7,15–17];
hydrogen sulfide is an energy-yielding substrate for
some microorganisms, and areas of these sulfidic cave
springs are colonized by thick subaqueous microbial
mats.
As photosynthesis is not possible in a cave, aphotic
chemolithoautotrophic primary productivity can be directly investigated. Stable carbon isotope measurements
and 14C-radiolabeled substrate experiments from bulk
microbial mats in several sulfidic caves suggest that
chemolithoautotrophy is the base of these ecosystems
[7,18,19]. Molecular phylogenetic studies based on 16S
rRNA gene sequences have expanded our understanding
of the microbial diversity in caves [14], including those
with sulfidic groundwater [8,16,20,21] and those without
[9,22–25]. In sulfidic caves, the dominant bacterial
groups from some subaqueous microbial mat communities belong to the ‘‘Epsilonproteobacteria’’ [16,21,26],
while culture-based methods identified chemolithoautotrophic sulfur-oxidizing bacterial groups, including the
genera Thiothrix and Thiobacillus [20,21,27]. There has
been little done, however, to examine the ecology of
dominant microbial groups involved with energy and
nutrient transfers in cave settings, or of the physical or
chemical controls that govern community structure
and dynamics.
This study is part of an ongoing project to describe
microbial ecosystems and nutrient cycling in sulfidic
cave habitats, as proxies for deeper subsurface environments such as carbonate aquifers. We have been studying microbial mats associated with sulfidic springs in
Lower Kane Cave, a small system located in the Bighorn
Basin, Wyoming. The objectives of this investigation are
to describe the genetic and functional diversity of microbial groups, as well as to define how community structure is controlled by habitat geochemistry. We
hypothesized that community composition and structure would reflect substrate availability, and specifically
that community composition would shift with changes
in dissolved oxygen and hydrogen sulfide concentrations. As it is often difficult to ascertain the metabolism
of certain organisms based on 16S rDNA-based phylogenies [28], elemental composition (carbon to nitrogen
ratios and sulfur content) and stable carbon isotope ratio analysis of specific mat morphotypes were combined
with 16S rDNA sequence phylogenies to link hypotheses
of ecosystem functionality with genetic identity for the
as yet uncultured microorganisms [3,29,30]. The current
study complements previous investigations in which we
quantified dominant epsilonproteobacterial populations
in filamentous microbial mat morphotypes from Lower
Kane Cave based on preliminary clone library construction and the development of two 16S rRNA-specific
‘‘Epsilonproteobacteria’’ fluorescence in situ hybridization (FISH) probes [26]. Our characterization of this
cave ecosystem expands the ecological understanding
of ‘‘Epsilonproteobacteria’’ and demonstrates that sulfur
cycling supports this subsurface ecosystem through
chemolithoautotrophy.
2. Materials and methods
2.1. The study site and sample collection
Lower Kane Cave (LKC) is located in the north-central portion of the Bighorn Basin and is forming within
the Madison Limestone (Mississippian age); the basic
hydrogeological setting is described in Egemeier [15].
There are four hydrogen sulfide-bearing springs that discharge into the cave along a fracture trace (Fig. 1(a)).
The cave is actively undergoing sulfuric acid speleogenesis, a biogeochemical process by which hydrogen sulfide oxidizes to sulfuric acid in the subaqueous
environment by microorganisms or subaerially on
cave-wall surfaces due to sulfide gas volatilization [31].
The acid reacts with and replaces the limestone hostrock
with gypsum, which is readily dissolved by groundwater
undersaturated with respect to gypsum [15,31]. The net
results are the removal of mass and an increase in void
volume. At each of the three largest springs, dissolution
of the host carbonate rock has resulted in fracture
enlargement and each spring orifice area has a pool
and outflow stream channel. Sparse filaments are found
in all the spring orifice pools, and thick carpets of filamentous microbial mats occur along the outflow streams
discharging from each spring. The Fissure and Upper
A.S. Engel et al. / FEMS Microbiology Ecology 51 (2004) 31–53
33
Fig. 1. (a) Plan-view map of Lower Kane Cave, Wyoming, showing the cave entrance, and major springs. Map modified from Egemeier [15].
(b) Dissolved hydrogen sulfide (squares) and oxygen (diamonds) profiles for Fissure Spring and Upper Spring, Lower Kane Cave. Distance was
measured from the back of the cave toward the entrance, in the direction of water flow.
Spring mats extend for 20 m, while the Lower Spring
mats are 1 m in length.
Samples of each microbial mat morphotype were
aseptically collected from three spring sites and aliquots were used for bulk biomass, elemental analysis, carbon isotope analysis, and DNA extraction and clone
library construction. To preserve the integrity of this
sensitive ecological system, conservative quantities of
microbiological materials were collected. Microbial
mat morphotypes were collected separately and distinguished as white filament bundles (denoted as ÔfÕ), white
webs (denoted as ÔwÕ), yellow-white patches (denoted as
ÔyÕ), and gray filaments (denoted as ÔgÕ). White filament
bundles in the water column or filaments from the surface of the mats were targeted for clone library construction; however, one small library was constructed
with gray filaments 2 cm below the top of the mat
for comparison. Sampling sites were numbered according to their location in meters from the back of the
cave, with flow always toward the cave entrance (i.e.
longer distances) (Fig. 1(a)): Fissure Spring (124-, and
127-m), Upper Spring (190-, 195-, 198-, and 203-m),
and Lower Spring (one orifice and one mat sample
from 248-m).
2.2. Geochemical analysis
Geochemical data were acquired at the major
microbiological sample locations, as well as throughout the cave, over three years of ongoing research.
Unstable parameters (pH, EH, and dissolved oxygen)
were measured using electrode methods [32]. Dissolved
hydrogen sulfide, ferrous iron (Fe2+), and trace level
dissolved oxygen were measured in the field using
the Methylene Blue, Ferrozine, and Rhodazine D
colorimetric methods, respectively, using CHEMetrics chemistries (Calverton, VA) with a MiniSpec
20 field spectrophotometer [32]. Vertical profiles of
dissolved oxygen through the mats were determined
by fluorescence-quenching optical methods (Ocean Optics, Inc., Dunedin, FL). Unstable and reactive parameters (pH, oxygen, hydrogen sulfide, etc.) were also
measured at several transects along and across the
cave stream channels. Alkalinity (as total titratable
bases, here dominated by bicarbonate) was determined
in the field by titration to pH 4.5, and verified in the
laboratory by end-point seeking autotitration [32].
Anions and acid-preserved metals were determined
by ion chromatography (Environmental Protection
Agency (EPA) method 9056; Manual SW-846, Test
Methods for Evaluating Solid Waste, Physical/Chemical Methods; http://www.epa.gov/epaoswer/hazwaste/
test/main.htm) and inductively coupled plasma mass
spectrometry (EPA method 6020; Manual SW-846),
respectively. Dissolved organic and inorganic carbon
(DOC and DIC, respectively) were determined by
Dorhman DC-180 wet-oxidation carbon analyzer
(EPA method 9060; Manual SW-846). Dissolved gas
species (e.g. methane, aromatic hydrocarbons, hydrogen sulfide, organosulfur gases) from the spring and
stream water were analyzed by headspace gas chromatography (EPA method 5021; Manual SW-846).
34
A.S. Engel et al. / FEMS Microbiology Ecology 51 (2004) 31–53
2.3. Mat carbon, nitrogen, and sulfur content
Each mat sample was individually homogenized,
acidified with dilute HCl, rinsed with dH2O, repeated
at least twice to ensure dissolution of carbonate mineral
phases, and freeze-dried. Total organic carbon and
nitrogen contents were determined by elemental analyzer interfaced with a mass spectrometer, simultaneously with carbon isotope ratio analysis (see below).
Total sulfur content, as inorganic and organic sulfur
compounds, was determined on a EuroEA3000 elemental analyzer (EuroVector, Milan, Italy).
Minimum bulk mat biomass was determined from dry
weight analysis of the mats followed by comparison of
the percent carbon in each 1 ml aliquot, using methods
described in and modified from Bratbak and Dundas
[33]. Briefly, replicate samples were individually homogenized, acidified with dilute HCl, weighed, freeze-dried,
and re-weighed to obtain the dry weight. The percentage
of carbon in each dried aliquot was determined by elemental analyzer. Cell carbon content was estimated from
the standard conversion factor of 350 fg C cell1 (assuming an average cell size of 1 lm3; [33]) to determine the
approximate number of cells per ml.
2.4. Carbon isotope methods
For carbon isotope ratio (13C/12C) analysis, organic
carbon of 1–2 ml mat was prepared by acidifying the
sample in dilute HCl to ensure removal of carbonate
mineral phases. Most measurements were made by elemental analyzer interfaced with a continuous flow FinniganMAT Delta Plus mass spectrometer, but some
measurements were also made by sealed tube combustion, vacuum purification, and dual-inlet VG Prism II
mass spectrometer. Microbial mat carbon isotope values
were compared to the values obtained from dissolved
inorganic carbon (DIC), a composite of CO2(aq),
2
HCO
from the cave water. DIC was ex3 , and CO3
13
tracted for C analysis by acidifying under vacuum with
100% phosphoric acid followed by cryogenic purification of the resulting CO2, using the method modified
from Hassan [34]. At the pH and temperature of the
cave water (pH 7.3 at 21.5 C), the dominant DIC
species was HCO
3 (90%) based on dissociation con2
species. Carbon
stants for H2CO3, HCO
3 , and CO3
isotope values for the limestone were also measured by
reaction with 100% phosphoric acid at 90 C [35]. Carbon isotope values are expressed in delta (d) notation
with respect to the international standard V-PDB.
2.5. DNA extraction and PCR amplification of 16S
rRNA gene sequences
Approximately 0.2–0.5 ml mat material were aseptically collected and placed into tubes containing steri-
lized DNA extraction buffer, identical to methods
described in Engel et al. [26]. DNA purity and concentration for each extraction were determined on a GeneQuantII spectrophotometer (Amersdam Biosciences,
Piscataway, NJ). Nearly full-length 16S rRNA gene
sequences were PCR-amplified using the eubacterial
primer pair 27f (forward, 5 0 -AGAGTTTGATCCTGGCTCAG-3 0 ) and 1492r (reverse, 5 0 -GGTTACCTTGTTACGACTT-3 0 ) [36]. Amplification was
performed with a Perkin Elmer 9700 thermal cycler
and AmpliTaq Gold (Applied Biosystems, Branchburg,
New Jersey), under the following conditions repeated
for 35 cycles: denaturation at 94 C for 1 min, primer
annealing at 42 C for 1 min, chain extension at 72 C
for 1.5 min.
2.6. 16S rDNA clone library construction, clone sequencing, and phylogenetic analysis
Amplified PCR products were purified with the
GeneClean II Kit (Bio101, Inc., Vista, CA), following
manufacturer recommendations. Purified PCR products
were cloned using the TOPO TA Cloning kit with Escherichia coli TOP10FÕ cells, according to manufacturer
instructions (Invitrogen, Carlsbad, CA), and eleven bacterial clone libraries were constructed from different mat
morphotypes. Plasmids containing 16S rDNA inserts
were extracted using a standard alkaline lysis miniprep
method [37]. Clone plasmids were digested simultaneously using EcoRI and RsaI (1U each) according to
manufacturer instructions (New England Biolabs) for
restriction fragment length polymorphism (RFLP) analysis. RFLP patterns were visualized on 2% agarose gels
stained with ethidium bromide and run in TBE (Tris–
borate–EDTA)-buffer. Clones representing unique patterns from each library were selected for sequencing,
and inserts from the plasmid minipreps for each clone
to be analyzed were sequenced as described in Engel
et al. [26].
DNA sequences were submitted to the CHECKCHIMERA program of the Ribosomal Data Base Project (RDP) II (http://rdp.cme.msu.edu/html/) [38] to
screen for and to eliminate chimeric sequences. Clone sequences were subjected to BLAST searches within the
GenBank database (http://www.ncbi.nlm.nih.gov/) to
determine 16S rDNA sequence similarities to culturable
and not yet cultured organisms.
Nucleotide sequences were initially aligned using Clustal X [39] and then manually adjusted based on conserved primary and secondary structures. Nucleotide
segments were removed that could not be unambiguously aligned, corresponding to E. coli 16s rRNA secondary structure helices 9 and 10 (bp 181–226; all
alignments) (all base pair positions correspond to E. coli
numbering; [40]), helix 17 (bp 452–481; all but the Betaproteobacteria alignment), helices 25 and 26 (bp 822–860;
A.S. Engel et al. / FEMS Microbiology Ecology 51 (2004) 31–53
Gammaproteobacteria and Bacteroidetes/Chlorobi-Acidobacterium alignments), helix 30 (bp 1028–1032;
Betaproteobacteria and Deltaproteobacteria alignments),
and helix 33 (bp 995–1045; ‘‘Epsilonproteobacteria’’ and
Bacteroidetes/Chlorobi-Acidobacterium alignments).
Phylogenetic analyses were done using minimum evolution criteria in PAUP* [41], maximum likelihood criteria using a genetic algorithm (MLga) in MetaPIGA [42],
and Bayesian inference coupled with Markov chain
Monte Carlo techniques (BMCMC) in MrBayes version
3.0b4 [43]. For minimum evolution and BMCMC
searches, a model of evolution was chosen based on likelihood ratio tests [44], as implemented in Modeltest 3.06
[45]. For the MLga search, Metapiga has model choice
constraints; therefore, the model was set at the most
complex model allowable by the program. Minimum
evolution heuristic searches were run using random
addition for 500 replicates. BMCMC searches were
run for 4 · 106 cycles sampling every 20,000 generations
at least twice to check for convergence and then combined, burning in five trees from each chain. MLga
searches were run for one replicate using 16 populations
of 10 individuals each. As an indication of nodal support, bootstrap analyses were performed for minimum
evolution using full heuristic searches and posterior
probabilities were calculated for BMCMC and MLga
analyses [42,43]. Sequence similarity was calculated for
the closely related clone sequences from the ‘‘Epsilonproteobacteria’’ using corrected distances based on the
model selected by Modeltest 3.06 [45].
2.7. Statistical analysis and sequence population diversity
To determine if the number of clones in each of the
clone libraries was representative of the microbial diversity, rarefaction curves were produced using the approximation algorithm aRarefactWin (Analytic Rarefaction,
version 1.3, S. Holland, http://www.uga.edu/~strata/
software/). Curves having 95% confidence levels were
constructed by comparing the number of clones in each
16S rRNA gene library to the number of phylotypes
from a particular library.
Clone library species richness and species dominance/
evenness indices (combined to represent heterogeneity;
e.g., [46,47]) were calculated based on the number of
phylotypes identified from RFLP and taxonomic affiliations from BLAST searches [48–50]. The nonparametric
methods Abundance-based Coverage Estimator (ACE)
and Chao1, and the Shannon–Wiener biodiversity function expressed as the Shannon index (H 0 ) were computed for each library using EstimateS (version 6.0b1,
R.K. Colwell, http://viceroy.eeb.uconn.edu/estimates).
The Shannon Evenness index (E) and the SimpsonÕs
Dominance index (D) were also calculated based on
equations presented in Hill et al. [50].
35
2.8. Nucleotide sequence accession numbers
Nucleotide sequence data reported in this study are
available in the GenBank database under the accession
numbers AY208806 to AY208817 for LKC2-labeled
clones, and AY510166 to AY510267 for LKC3-labeled
clones.
3. Results
3.1. Geochemistry and morphologic description of microbial mats
Major ion geochemistry did not vary significantly
from sample period to sample period, and waters were
2
ions (calall dominated by Ca2+, HCO
3 , and SO4
cium–bicarbonate–sulfate water type) (Table 1).
Although the cave is forming from sulfuric acid dissolution of limestone [15,31], the spring and stream waters
are buffered to circum-neutral pH by ongoing carbonate
dissolution. Incoming spring water had dissolved sulfide
concentrations >35 lmol l1 and non-detectable dissolved oxygen (Table 1). The concentration of dissolved
sulfide and oxygen changed downstream at all the
springs, such that at the end of the microbial mats sulfide decreased to non-detectable and the concentration
of dissolved oxygen exceeded 40 lmol 1. The concentration of DOC in all the incoming spring waters was
low at <80 lmol l1 including methane.
We observed four mat morphotypes along the springstream flowpaths (Fig. 2). All three spring orifice pools
had gray benthic sediment and long white filament bundles were suspended in the water column. The Lower
Spring (248 m) had the densest concentration of filament
bundles in the orifice (Fig. 2(a)), and the microbial mat
below the Lower Spring orifice was 2–5 cm thick but less
than 1 m in length; overall the mat was yellowish-white
in appearance (Fig. 2(b)). The Upper Spring had the
longest filament bundles, at more than a meter in length
in the orifice pool (Fig. 2(c) and (d)). White filament
bundles coalesced on the edges of the outflow channel
downstream, where the dissolved sulfide concentration
decreased and dissolved oxygen concentration increased
(Fig. 1(b)). Very thin, short (1 cm in length) whitish-gray
filaments covered stream sediments in flowing water at
the bottom of the Upper Spring outflow channel (195
m). Approximately 6 m downstream from the Upper
Spring orifice, the gray filaments thickened by several
centimeters and were covered by thin white webs and
long white filament bundles. Some of the webs at 203
m had a bumpy or knobby texture (Fig. 2(e)). Oxygen
microelectrode profiles at 203 m showed oxygen tension
abruptly decreased 3 mm below the mat–water interface and anaerobic conditions ðP O2 < 10 PaÞ persisted
within the 5 cm-thick mat interior, demonstrating that
A.S. Engel et al. / FEMS Microbiology Ecology 51 (2004) 31–53
0.12
0.14
0.14
0.13
0.001
0.001
0.001
0.002
1.19
1.15
1.22
1.18
0.17
0.17
0.17
0.17
the mats are geochemically stratified. Although the focus of this study was on the white microbial mat morphotypes, gray filaments within the mat at 203 m (2–5 cm
below the white mat surface) were sampled to determine
if there were general differences in community structure
vertically. For both the Upper and Lower Spring channel mats, dense white mats, with small (1–2 cm diameter)
discontinuous yellow patches and feathery (i.e. short,
thick, and branching filaments) bundles, dominated
the lower reach of the outflow channels (Fig. 2(f)). Filament bundles near the orifice of the Fissure Spring (118
m) (Fig. 2(g)) were also associated with web-like structures and gas bubbles entrained within the mats
(125 m) (Fig. 2(h)).
c
b
a
Dissolved oxygen, measured by the rhodazine D colorimetric method (CHEMetrics).
Dissolved sulfide (as total dissolved sulfide, including H2S and HS), measured by the Methylene Blue colorimetric method (CHEMetrics).
Nonpurgable organic carbon, plus CH4.
3.43
3.46
3.48
3.42
0.94
0.96
0.92
0.91
7.30
7.39
7.43
7.22
Fissure Spring (118 m)
Upper Spring (189 m)
Stream Channel (205 m)
Lower Spring (248 m)
22
21.3
22
22.1
580
577
587
575
<0.2
<0.2
40
<02
39.7
35.3
5.6
39.4
0.66
0
0.2
0.13
0.25
0.26
0.25
0.25
0.009
0.009
0.008
0.009
0.012
0.025
0.014
0.025
1.69
1.75
1.74
1.66
HCO
3
Mg2+
Ca2+
NHþ
4
K+
Na+
NPOC (mg C l1)c
S2 (lMol l1)b
DO (lMol l1)a
Cond (lS)
T (C)
pH
Site
Table 1
Geochemical parameters from representative Lower Kane Cave spring and stream water samples from August 2001, reported in mMol l1, unless otherwise noted
Cl
NO
3
SO2
4
Si
36
3.2. Biomass estimates, C:N ratios, and sulfur content
The biomass of the microbial mat samples was 1010
cells ml1 (Table 2), with gray filaments from the Lower
and Upper Springs having the highest biomass. Biomass
values reported here may underestimate the actual biomass because current cell conversion factors are for
rod-shaped cells [33], and previous FISH analyses reveal
that the mats are dominated by filamentous morphotypes [26].
The N content varied by mat morphotype, and white
filament bundles and white webs had the highest N content compared to gray filaments or gray sediment (Table
2). Generally, the lower the C:N ratio, the higher the
quality of the mat as a food source for the ecosystem
[51,52]. The mean C:N ratios for white filament morphotypes from all the mats was 5.0 (1r = 0.8), suggesting a
high quality food source. The C:N ratios of gray filaments were higher and more variable than white morphotypes, with a mean of 15.0 (1r = 10.5). The C:N ratios
were highest for gray filaments and sediment from
spring orifice sites, while the C:N ratios of gray filaments
at the end of the microbial mats approached those of the
white mat morphotypes (Table 2).
The sulfur content of white filament bundles was
higher than the gray filaments (Table 2), presumably
reflecting intracellular sulfur (as elemental S0) rather
than organosulfur compounds. Typically, the highest
sulfur content in bacterial cells, in the absence of stored
sulfur, ranges up to 1% (w/w) [52]. However, the sulfur
content of white filament bundles had a mean of
30.0% (1r = 11.2%), and the white webs had consistently
the highest sulfur content (Table 2). The gray filaments
and sediment had significantly lower sulfur contents,
with a mean of 1.9% (1r = 0.6%), consistent with what
would be predicted for bacterial biomass [52]. The sulfur
content of white filaments was generally the same at the
extreme upstream and downstream samples of the
Upper Spring transect, but decreased by up to 10% in
the middle stream reach (Table 2).
A.S. Engel et al. / FEMS Microbiology Ecology 51 (2004) 31–53
37
Fig. 2. Microbial mat sampling sites and springs in Lower Kane Cave. Black arrows indicate direction of water flow. (a) Lower Spring orifice (248 m)
occupied by emergent sulfidic groundwater (flowing over the lip at the lower left) and white filament bundles. A thick white filamentous mat forms at
the edge of the orifice. Orifice walls are made of limestone, while gypsum forms piles around the edge of the orifice pool (upper right). (b) End of thick
microbial mat below Lower Spring (248 m). The mat is composed of white filaments and gel-like yellow masses. Black spots on rocks at the edge of
the mat (upper left) are snails, Physa spelunca. Gas bubbles of carbon dioxide, methane, and hydrogen sulfide gases form in this portion of the mat.
(c) Upper Spring Pool (190 m) area, looking upstream, with gray sediment on the orifice pool bottom and white filaments suspended in the water
column. Water depth at the deepest part of the pool is 2 m, although average water depth is 30 cm. (d) Upper Spring filament bundles suspended in
the water column (190 m). (e) Knobby white webs forming on the surface of the mat within the Upper Spring channel (203 m). Thin white filaments
are suspended in the water column above the webs. (f) Yellowish-white patches within white filament area at 203 m from the Upper Spring channel
(white arrows). The edge of the stream (lower center and lower left) is composed of chert fragments. Gas bubbles have also been observed at this
locale. (g) Fissure Spring orifice (118 m). The orifice pool area consists of limestone cobbles and gray sediment, mostly clay. (h) Thin white filament
bundles and white webs in the Fissure Spring outflow channel (125 m). Gas bubbles are also present.
38
A.S. Engel et al. / FEMS Microbiology Ecology 51 (2004) 31–53
Table 2
Elemental analysis and carbon to nitrogen ratios for microbial mat morphotypes
Site (m)
Mat morphotype
120
128
189
192
192.5
196.5
198
201
203
248
248
201
204
201
203
203
118
120
125
128
189
192
198
203
204
248
248
White filament bundles
White filament bundles and webs
White filament bundles
White filament bundles
White filament bundles
White filament bundles
White filament bundles
White filament bundles
White filament bundles
White filament bundles
White filament and feathers
White feathers
White feathers
White webs
White webs
Yellow patches
Gray sediment
Gray filaments and sediment
Gray sediment
Gray filaments and sediment
Gray sediment
Gray filaments
Gray filaments
Gray filaments
Gray filaments
Gray filaments
Gray filaments
Biomass (1010 cells ml1)
1.8
1.8
2.0
2.9
1.4
2.9
2.6
1.8
7.6
0.73
1.8
4.7
%N
C:N
%S
0.7
4.2
4.1
4.0
6.1
2.4
2.4
4.6
5.5
5.8
5.6
7.3
6.1
2.3
4.1
8.1
0.3
0.3
0.4
1.2
0.2
0.2
0.6
2.3
3.9
0.2
5.5
5.4
5.1
3.6
4.4
3.6
5.3
5.2
3.5
4.2
4.9
6.6
4.2
4.2
4.4
4.7
4.7
28.8
28.0
17.1
9.5
23.6
13.8
7.9
6.8
6.0
35.1
6.7
24.4
17.7
38.1
51.2
41.6
16.1
26.7
26.6
50.0
32.7
27.0
16.1
37.3
38.5
35.4
8.6
0.3
0.5
1.5
1.0
1.7
2.1
1.3
2.0
2.0
1.8
1.5
Site locations refer to distance (in meters) from the back of the cave.
3.3. Carbon isotope systematics
The d13C value for the Madison Limestone from the
cave was +0.95&, and the DIC reservoir along the
Upper Spring transect had an average d13C value of
7.5& (n = 7, 1r = 0.1&), and DIC from the Fissure
Spring orifice water had a slightly higher d13C value of
7.2&. Microbial mat morphotypes had d13C values
ranging from 23& to 41& (mean 34.1&,
1r = 4.1) (Fig. 3). The low d13C values reflect the large
discrimination against 13C exhibited by autotrophs
(e.g., 25& relative to total DIC for sulfur-oxidizing
bacteria [53]).
Microbial mat morphotypes showed systematic variations in their carbon isotope compositions at most
locations (Fig. 3). At all three spring locations, gray filaments consistently had among the highest d13C values,
whereas all coexisting white filament bundles had lower
d13C values. More specifically, near the distal portions
of the Upper Spring mats, white feathery bundles and
yellow patches (Fig. 2(f)) had some of the lowest d13C
values, whereas the white webs and gray filaments had
the highest d13C values (Fig. 3). In contrast, however, the
feathery bundles from the more proximal region of the
Upper Spring mats (196 m) had among the highest
d13C values. Moving downstream, the d13C values of
white filament bundles in both Upper Spring and Fissure Spring, decreased (Fig. 3).
3.4. Clone library coverage, species richness, and diversity
Eleven bacterial 16S rDNA clone libraries from four
different microbial mat morphotypes were constructed
and over 1000 clones were screened using RFLP. Nearly-full length 16S rRNA genes (>1300 bp) were sequenced in both directions from selected clones.
Sequences from the same RFLP pattern that were
P98% similar to each other were grouped as a phylotype
(Table 3), and we used this classification scheme to estimate community diversity (Table 4). This level of sequence similarity takes into account micro-variations
in genetic sequences due to PCR and cloning biases
and variations in 16S rRNA gene copies [54,55].
Approximately 2% of the 16S rRNA gene sequences
were chimera and removed from further analyses. Of
the phylotypes identified, 44% had sequences that were
P95% identical to GenBank sequences, corresponding
to genus-level relationships [56], and 30% of the sequences were P98% identical to GenBank sequences,
approximating species-level relationships [56]. The
remaining phylotype sequences had P90% sequence
similarity to GenBank sequences (Table 3).
A.S. Engel et al. / FEMS Microbiology Ecology 51 (2004) 31–53
(a) -25.00
39
Fissure Spring
δ13C
-30.00
-35.00
-40.00
gray
filament
web
-45.00
118
120
122
124
126
128
130
Distance (m)
(b) -25.00
Upper Spring
δ13C
-30.00
-35.00
gray
-40.00
filament
feather
web
yellow
-45.00
188
190
192
194
196
198
200
202
204
206
Distance (m)
Fig. 3. Carbon isotope composition for microbial mat morphotypes from the (a) Fissure Spring and (b) Upper Spring, Lower Kane Cave, Wyoming.
The size of the morphotype symbol is greater than the uncertainty of the measurement.
Rarefaction analysis was done to determine if the
libraries had saturated coverage based on the number
of clones obtained per library. The rarefaction curves
indicated different patterns of diversity for different
morphotype libraries (Fig. 4). In the non-filament clone
libraries (203g, 203w, 203y, and 248y), diversity was not
fully covered compared to the saturation plateau
reached for most of the white filament bundle libraries
(124f, 127f, 190f, 198f) (Fig. 4). As there was an overall
increase in the rate of phylotype accumulation in these
unsaturated curves, major diversity within these libraries
may not be well represented, although some of these
libraries (e.g., 203y) do have high dominance values
(Table 4).
Species heterogeneity among the clone libraries was
generally low and many of the white filament libraries
showed overwhelming dominance by one of two phylotypes. Species richness was higher for the non-filament
morphotypes, with the white webs from 203 m and the
yellow patches from 203 to 248 m showing the most diverse taxonomic representation among the eleven bacterial clone libraries (Table 3), even though observed
species richness was lower than expected based on
ACE and Chao1 values (Table 4). In comparison,
although species richness of the white filament libraries
varied, ranging from one to ten observed phylotypes,
ACE and Chao1 estimates for the white filament libraries indicated that the observed phylotype numbers were
close to the calculated values due to near-complete clone
coverage for most of those libraries (Table 4). The diversity/dominance indices changed for the white filament
clone libraries downstream for both the Upper and
Lower Spring transects, such that the H 0 values increased and D values decreased (Table 4).
3.5. 16S rRNA gene clone libraries
The 16S rDNA clones were affiliated with several
bacterial phyla (Table 3; Figs. 5 and 6). The majority
of the sequences identified from the clone libraries
belonged to the Proteobacteria taxonomic division, specifically the ‘‘Epsilonproteobacteria,’’ (68%) Gammaproteobacteria (12.2%), Betaproteobacteria (11.7%), and
40
Table 3
Distribution of bacterial clones as they appeared in the microbial mat clones libraries
Phylogenetic affiliationa
Representative
clone sequences
and phylotypes
Closest relativea
Sequence
similarity %a
Library location and number clones in library
Fissure
Spring
22
127f
57
190f
270
195f
66
77
28
7
8
4
47
54
6
1
2
LKC3_22.5 (2)d
LKC3_190.31
LKC3_127.1 (7)
LKC2_270.19 (3)
LKC3_127.28 (3)
LKC3_156.15
Sulfidic spring clone sipK119
Sulfidic spring clone sipK94
Sulfidic spring clone sipK119
Groundwater clone 1028
Sulfidic spring clone sipK94
Acid mine clone 44a-B1-1
98
98
96
96
95
96
80
3
5
Gammaproteobacteria
Thiothrix unzii
Beggiatoa spp.
Pantoea spp.
Serratia spp.
LKC3_22.33
LKC3_19B.17
LKC3_125.3
LKC3_125.46
Sulfidic spring clone sipK4
Beggiatoa MS-81-1c strain
Pantoea agglomerans
Serratia marcescens
99
90
99
99
12
4
Betaproteobacteria
Group I
Group II
LKC3_102B.25
LKC3_198.35 (2)
Thiobacillus clone 44a-B2-21
Thiobacillus aquaesulis
94
95
Deltaproteobacteria
LKC3_190.37 (3)
Desulfocapsa thiozymogenes
96
Bacteroidetes/Chlorobi
Group I
Group II
Group III
Group IV
LKC3_198.43
LKC3_156.56
LKC3_270.15
LKC3_102B.33
Lake clone TLM10/dgge01
Digestor clone vadinHA54
Groundwater clone ECP-C1
Groundwater clone
WCHA1-01
Gas hydrate clone Hyd.B2.1
Gas hydrate clone Hyd-B2-1
97
92
94
91
7
90
96
1
Groundwater clone SJA-36
92
Groundwater clone SJA-36
97
Acidobacterium
Total clones
a
b
c
d
LKC2_127.25
LKC3_19.50
LKC3_102B.59
LKC3_156.13
LKC3_156.1
4
Lower
Spring
190
198f
127
203f
81
2
29
30
4
102
203y
125
203g
1
7
1
1
1
11
2
199
248f
198
248y
76
10
17
3
3
41
156
203w
4
2
1
14
6
5
18
6
6
1
43
1
70
6
1
1
3
1
1
1
1
1
1
1
116
2
111
127
117
87
2
46
3
81
74
79
Based on taxonomic classifications from BLAST searches.
Clone library reference number for phylogenetic trees (Figs. 5 and 6).
Meter location along the cave stream; letter corresponds to morphotype: f, white filaments; w, white webs; y, yellowish-white mat; g, gray filaments.
Number in parentheses represents number of phylotypes for each group if more than one, with phylotype defined as P98% sequence similarity.
1
26
76
91
A.S. Engel et al. / FEMS Microbiology Ecology 51 (2004) 31–53
19b
124fc
Proteobacteria
Epsilonproteobacteria
Group I
Group II
Group III
Group IV
Group V
Group VI
Group V
Group VI
Group VII
Unclassified
Upper Spring
A.S. Engel et al. / FEMS Microbiology Ecology 51 (2004) 31–53
41
Table 4
Bacterial clone library coverage and ecological indices
Library (m)
Mat typea
No. clones
Number phylotypes
observed
ACEb,c
Chao1c
Shannon–Wiener (H 0 )c,d
Evenness (E)d
SimpsonÕs index (D)d
124
127
190
195
198
203
203
203
203
248
248
f
f
f
f
f
f
w
y
g
f
y
116
111
127
117
87
81
74
79
26
76
91
9
4
10
10
3
10
9
7
4
1
11
10.55
4.0
10.33
12.0
2.0
14.66
20.84
13.24
8.04
1.0
15.48
11.0
4.0
10.05
10.66
2.0
11.62
21.5
10.5
6
1.0
14.5
1.18
0.88
1.36
1.24
0.28
1.53
1.27
0.55
0.84
0
1.69
0.49
0.63
0.39
0.54
0.40
0.73
0.52
0.26
0.37
0
0.66
0.49
0.47
0.65
0.38
0.87
0.45
0.42
0.79
0.54
1.0
0.27
a
b
c
d
Letter corresponds to morphotype: f, white filaments; w, white webs; y, yellowish-white mat; g, gray filaments.
Abundance-based coverage estimator.
Calculated by EstimateS, ver. 6.01b (http://viceroy.eeb.uconn.edu/estimates).
H 0 , E, and D calculated from equations provided in Hill et al. [50].
12
number of phylotypes
10
8
124f
127f
190f
195f
198f
203f
203w
203y
203g
248y
6
4
2
0
0
10
20
30
40
50
60
70
80
90
100
110
120
130
number of clones
Fig. 4. Rarefaction curves of the diversity in ten of the eleven 16S rRNA gene sequence bacterial clone libraries based on phylotypes identified from
RFLP patterns. Library 248f was excluded because only one RFLP phylotype was identified.
Deltaproteobacteria (0.8%) classes, as well as from other
bacterial divisions, including the Acidobacterium (5.6%)
and Bacteroides/Chlorobi (1.7%) divisions.
3.5.1. The ‘‘Epsilonproteobacteria’’ class
The highest numbers of clones from all the libraries
(68%) were assigned to the ‘‘Epsilonproteobacteria’’
(Fig. 5; Table 3). Epsilonproteobacterial sequences from
17 phylotypes clustered into six groups based on phylogenetic position and sequence similarity, which suggests
that genetic microdiversity in the microbial mats was
high [57] (Fig. 5). Interestingly, regardless of morphotype location or site geochemistry, at least one epsilonproteobacterial phylotype was found in all clone
libraries (Table 3). The epsilonproteobacterial groups
identified from LKC have few closely related sequences
from the public databases, suggesting that the diversity
of these groups, and the ‘‘Epsilonproteobacteria’’ in general, is only now being realized.
The most abundant epsilonproteobacterial groups
from all three springs formed two distinct clades, previously described as LKC group I and group II [26]. The
closest relatives to the LKC groups I and II were the two
environmental clones, sipK119 and sipK94, respectively
(98–99% similar in nucleotide sequence), from microbial
mats with a string-of-pearls morphology in sulfidic
marsh springs at the Sippenauer Moor, Regensburg,
Germany [58,59]. Clone sequences from LKC group I
were also closely related (97–99% similar in nucleotide
sequence) to environmental clones obtained from a
petroleum-contaminated sulfidic groundwater storage
cavity in Japan [60,61] and two clones from microbial
mats from the sulfidic Cesspool Cave, Virginia [21]
(Fig. 5). The closest cultured relative to LKC group I
42
A.S. Engel et al. / FEMS Microbiology Ecology 51 (2004) 31–53
LKC3 22.17 [AY510189]
LKC3 57B.57 [AY510193]
Sulfidic spring clone sipK119 [AJ307940]
LKC3 22.54 [AY510180]
LKC3 57B.49 [AY510194]
LKC3 57B.17 [AY510188]
LKC3 22.53 [AY510181]
LKC3 57C.15 [AY510190]
LKC3 57C.33 [AY510195]
LKC2 270.64 [AY208817]
LKC2 57.8 [AY208807]
LKC3 57B.2 [AY510196]
LKC3 22.5 [AY510183]
LKC3 198.20 [AY510185]
LKC3 57.20 [AY510184]
LKC3 127B.2 [AY510182]
LKC3 19.39 [AY510191]
99/89/LKC3 22.81 [AY510192]
LKC3 198.15 [AY510186]
Petroleum-contaminated groundwater clone 1043 [AB030601]
Uncultured groundwater clone FTL212 [AF529098]
LKC3 22.72 [AY510167]
LKC3 57B.41 [AY510197]
Petroleum-contaminated
groundwater clone 1049 [AB030606]
64/-/Petroleum-contaminated groundwater clone 1011 [AB030607]
Sulfuricurvum kujiense [AB080643]
99/89/61/-/- LKC3 57B.22 [AY510200]
Cesspool Cave clone group CC-4 [AF207530]
LKC3 57C.10 [AY510199]
LKC2 270 19 [AY208816]
Cesspool Cave clone group CC-9 [AF207534]
Groundwater clone RA9C8 [AF407391]
LKC3 127.40 [AY510174]
LKC3 127.14 [AY510175]
LKC2 127.32 [AY208810]
LKC3 127.6 [AY510169]
LKC3 127.46 [AY510170]
LKC3 127.23 [AY510173]
LKC3 127B.27 [AY510171]
LKC3 127.39 [AY510172]
LKC3 57B.54 [AY510168]
LKC3 127B.26 [AY510177]
LKC3
270.5 [AY510187]
64/-/LKC3 127.43 [AY510176]
Petroleum-contaminated groundwater clone 1023 [AB030610]
56/-/Petroleum-contaminated groundwater clone KB2C [AB07495]
LKC2 270.16 AY208815]
68/-/LKC3 270.58 [AY510178]
52/-/LKC3 127.1 [AY510179]
LKC3 270.13 [AY510198]
LKC3 57B.56 [AY510201]
/-/100
Thiomicrospira sp. [U46506]
97/100/100
Thiomicrospira denitrificans [L40808]
99/100/100
Pele’s Vent clone PVB 55 [U15105]
Sulfurimonas autotrophica [AB088432]
90/100/100 72/100/100
Thiovulum sp. [M92323]
Meromictic lake sediment clone PENDANT-10 [AF142923]
100/100/100
53/-/- Sulfidic spring clone sipK94 [AJ307941]
LKC3 190 31 [AY510209]
50/-/- LKC3 127.4 [AY510206]
LKC3 102.21 [AY510214]
LKC3 57.4 [AY510210]
LKC3 270.57 [AY510215]
LKC3 159.12 [AY510213]
LKC3 156.14 [AY510208]
LKC3 127.29 [AY510216]
85/88/100
LKC3 125.31 [AY510207]
98/94/80 LKC3 57C.13 [AY510212]
LKC3
199.1 [AY510205]
86/-/LKC3 198.26 [AY510211]
85/88/100
LKC2 127 53 [AY208813]
Deep-sea hydrothermal field strain EM9I37-1 [AB091299]
Alvinella pompejana epibiont [L35521]
LKC3 127.36 [AY510203]
LKC3 127.28 [AY510204]
100/100/99
LKC3 198B.17 [AY510202]
Parker Cave clone SRang51 [AF047630]
60/100/- 85/100/100
-/62/Activated sludge clone rA10 [AF047626]
Hydrocarbon seep sediment clone GCA014 [AF154101]
77/-/99
Hydrothermal vent clone 49MY [AB091293]
-/81/100
Marine
sediment clone NKB9 [AB013261]
-/-/64
Marine sediment clone JTB315 [AB015258]
78/-/65 94/100/100
Marine sediment clone a2b004 [AF420345]
Deep-sea hydrothermal field clone 42BKT [AB091292]
77/100/71
Deep-sea hydrothermal field strain E9S37-1 [AB091300]
73/-/56
Sulfidic spring clone ZB50 [AY327163]
Hydrothermal vent clone VC2_1 Bac1 [AF068783]
Riftia pachyptila’s tube clone R103-B22 [AF449234]
Estuarine sediment clone 2BP-7 [AF121887]
Benzene-mineralizing consortium clone SB-17 [AF029044]
67/75/100
Rimicaris exoculata ectosymbiont [U29081]
LKC Group I
LKC Group IV
LKC Group II
LKC Group V
Miscellaneous
strains & clones
(marine & freshwater)
Parker Cave clone SrangJ [AF047633]
Sulfidic spring clone ZB43 [AY327156]
Parker Cave clone SRang1.27 [AF047626]
68/100/100
Sulfidic groundwater clone 1065 [AB030598]
Candidatus ‘Arcobacter’ sulfidicus [AY035822]
91/100/100
Marine sediment clone NB1-k [AB013832]
96/100/100
Arcobacter butzlerii [L14626]
67/100/100
Oilfield groundwater strain FWKOB [AF144693]
56/-/Geospirillium sp. [Y18254]
90/-/69
100/100/100
Petroleum-contaminated groundwater clone 1014 [AB030587]
Sulfurospirillum deleyianum [Y13671]
-/69/Campylobacter jejuni [AF393203]
99/100/100
71/-/Helicobacter winghamensis [AF363063]
87/100/100
Flexispira rappini [AF034135]
Helicobacter pylori isolate MC123 [U01328]
99/100/100
Wolinella succinogenes [AF273252]
LKC3 156.15 [AY510218]
65/-/94/100/100
LKC3 102B.55 [AY510219]
100/100/100 LKC3 156.74 [AY510217]
LKC3 156.38 [AY510221]
100/100/100
LKC3 102B.15 [AY510220]
Acid mine drainage clone 44a-B1-40 [AY082468]
83/100/100
Acid mine drainage clone 44a-B1-1 [AY082456]
Petroleum-contaminated groundwater clone 1070 [AB030590]
100/100/100
100/100/100
Caminibacter hydrogeniphilus [AJ309655]
Nautilia lithotrophica [AJ404370]
Desulfocapsa thiozymogenes [X95181]
Desulfovibrio fairfieldensis [U42221]
-/88/100
Hydrogenophaga pseudoflava [AF078770]
92/100/100
100/100/100
Leptothrix.discophora [L33975]
95/100/Thiobacillus 44a.B2.21 [AY082471]
81/-/79
Thiothrix unzii [L79961]
Beggiatoa sp. [AF110276]
91/-/Escherichia coli K12 [NC_000913]
Cytophaga .sp [AB015525]
Bacteroides sp. [AB021162]
100/100/100
Thermotoga.subterranea [U22664]
Thermus aquaticus [L09663]
“Epsilonproteobacteria”
LKC Group III
96/88/100
100/100/100
LKC Group VI
Caminibacter
Nautilia
Outgroups
-/-/81
Arcobacter
Geospirillum
Sulfurospirillum
Campylobacter
Helicobacter/ Flexispira
Wolinella
0.01 substitutions/site
Fig. 5. 16S rRNA gene-based phylogenetic tree showing the phylogenetic position of clones from Lower Kane Cave within the ‘‘Epsilonproteobacteria’’. Clones are labeled in bold with corresponding sample and clone numbers. Reference sequences (with GenBank accession numbers) were
chosen to represent the diversity of the ‘‘Epsilonproteobacteria’’. The tree was rooted with Proteobacteria representatives and other bacterial divisions.
The tree is a representative topology from 188 trees of the same score inferred from minimum evolution analysis, with the differences among the
minimum evolution trees due only to changes in the relative position of sequences within clades of Lower Kane Cave clones. The phylogenetic
affiliations of the clones were confirmed by comparison with different reconstruction methods (data not shown). Numbers along tree branches refer to
support values for each node, corresponding to minimum evolution bootstrap proportions, MLga and BMCMC posterior probabilities.
A.S. Engel et al. / FEMS Microbiology Ecology 51 (2004) 31–53
43
Fig. 6. 16S rRNA gene-based phylogenetic trees showing the phylogenetic position of bacterial clones from Lower Kane Cave: (a)
Gammaproteobacteria; (b) Betaproteobacteria; (c) Deltaproteobacteria; and (d) Bacteroidetes/Chlorobi and Acidobacterium divisions. Clones are
labeled in bold with corresponding sample and clone numbers. Reference sequences (including GenBank accession numbers) were chosen from the
RDP to represent the diversity of each division. Each tree was rooted with different members of the Proteobacteria and other bacterial divisions. Tree
topology was inferred from the results of minimum evolution (ME) analysis, and the phylogenetic affiliations of the clones were confirmed by
comparison with different reconstruction methods (data not shown). The Gammaproteobacteria tree is a representative topology from 14 trees and the
Betaproteobacteria tree is a representative topology of 2 trees of the same score inferred from ME analyses, with the differences among the ME trees
from the same search due only to changes in the relative position of sequences within clades of the LKC clones. The ME analysis of the
Deltaproteobacteria and Bacteroidetes/Chlorobi-Acidobacterium alignments resulted in a single tree. Numbers along tree branches refer to support
values for each node corresponding to ME bootstrap proportions, MLga and BMCMC posterior probabilities.
44
A.S. Engel et al. / FEMS Microbiology Ecology 51 (2004) 31–53
Fig. 6 (continued)
clones was Sulfuricurvum kujiense; this organism is a
slightly curved rod isolated as a chemolithoautotrophic
sulfur-oxidizer, capable of growth on thiosulfate, ele-
mental sulfur, and hydrogen sulfide, and able to use
molecular oxygen, nitrate, or ferric iron as electron
acceptors [62]. LKC group II clones were more distantly
A.S. Engel et al. / FEMS Microbiology Ecology 51 (2004) 31–53
related (90–94% similar) to miscellaneous marine,
hydrothermal vent field and epibiont clones [63,64]
and clones from a sulfidic cave microbial mat in Parker
Cave, Kentucky [16] (Fig. 5). The phylogenetic affinities
(Fig. 5) and sequence similarity of these two groups
demonstrate that they are distinct from each other at
more than the genus-level (85–87% similar).
LKC group III did not form a distinct phylogenetic
cluster and was defined by several phylotypes from five
libraries, supported by the range of sequence similarities
among the sequences (91–99% similar in nucleotide sequence) and moderate boot-strap node values (Fig. 5).
No LKC group III clones were found at the Lower
Spring. LKC group IV, comprised of clones only from
the Upper Spring, clustered closely with S. kujiense,
and groundwater and cave environmental clones (Fig.
5). LKC group V had a range of sequence similarities
among the group sequences (97–99% similar), indicating
additional diversity that could not be resolved by RFLP.
Seventeen clones from morphologically and geochemically diverse libraries, but mostly white filament bundle
morphotypes, belonged to the novel sequence cluster
LKC group VI (Fig. 5). The closest relatives to LKC
group IV clones were environmental clones from acid
mine drainage (95–96% similar).
3.5.2. The Gammaproteobacteria class
Twelve percent of all the clones belonged to the Gammaproteobacteria (Fig. 6(a)). Eighty-one clones formed the
most abundant phylotype, closely related (99–100% similar in nucleotide sequence) to the environmental clone
sipK4 from sulfidic marsh springs [58], which is also closely related to Thiothrix unzii. Several Thiothrix spp. have
been identified from sulfidic caves, including Parker Cave,
Kentucky [16], underwater caves and karst springs in
Florida [27], and Cesspool Cave [21]. Clone library 203g
was dominated by clones belonging to the Enterobacteriaceae, specifically the Pantoea and Serratia genera (Fig.
6(a)). The libraries 203g and 248y had six clones each that
were closely related (99% similar) to Serratia marcescens.
Nine sequences from the 124f and 203w libraries were distantly related to Beggiatoa sequences (90% similar), with
one relative being the isolate Beggiatoa sp. MS-81-1c (Ahmad et al., unpublished Genbank submission) (Table 3;
Fig. 6(a)). The weak sequence similarity to known Beggiatoa sequences, however, indicates that LKC clones may
belong to a different, unclassified bacterial group within
the Gammaproteobacteria. Beggiatoa-like filaments have
been described from a marine cave in Italy using microscopy [65] and from microbial mats in Parker Cave [66],
although phylogenetic investigations from Parker Cave
did not support the presence of Beggiatoa [16].
3.5.3. The Betaproteobacteria class
Nearly twelve percent of the clones were affiliated with
the Betaprotoebacteria, and were most closely related to
45
Thiobacillus spp. (Fig. 6(b)). Three phylotypes were identified from two libraries. The closest relatives (94–95%
similar in nucleotide sequence) were the environmental
clone 44a-B2-21 from acid mine drainage (Labrenz and
Banfield, unpublished Genbank submission) and Thiobacillus aquaesulis, a sulfur-oxidizing, facultative chemolithoautotroph [67]. Thiobacilli have been previously
described from caves and mines [8,16,20,21,68], but environmental clones from those studies were not closely related to the LKC groups (Fig. 6(b)).
3.5.4. The Deltaproteobacteria class
Less than 1% of the clones were closely related (96–
97% similar in nucleotide sequence) to Desulfocapsa thiozymogenes, the environmental clone sipK94 from the
string-of-pearls mats in Germany [59], and the environmental clones SRB348 and SRB282 identified from the
chemocline of the meromictic Lake Cadagno, Switzerland [69] (Table 3; Fig. 6(c)). D. thiozymogenes disproportionates thiosulfate, sulfite, or elemental sulfur to
sulfate and sulfide [70].
3.5.5. The Acidobacterium division
One phylotype representing 5.6% of all the clones obtained from this study was closely related (96–97% similar in nucleotide sequence) to uncultured environmental
clones within the Acidobacterium division. Library
203w was dominated by this clone group, and rare
clones from this phylotype were found in five additional
libraries (Table 3). Acidobacteria have not been identified from sulfidic cave microbial mats, but they have
been identified from molecular surveys of Paleolithic
cave paintings [9,25] and from submerged cave walls
[23]. The closest relative was clone SJA-36 identified
from an anaerobic bioreactor with trichlorobenzene
contamination [71] (Fig. 6(d)). The LKC phylotype also
expands the Acidobacteria-group 7 described by Liles
et al. [72], which consisted of only a few environmental
clones from soil, as well as the Acidobacteria-subgroup-b
described by Schabereiter-Gurtner et al. [9] from La
Garma Cave, Spain. Clone LKC3_156.13 had 92% sequence similarity to clone SJA-36, but also clustered
as an unclassified taxonomic group within the Bacteroidetes phylum by phylogenetic analysis (Fig. 6(d)).
3.5.6. The Bacteroidetes/Chlorobi division
Seven phylotypes, each represented by rare ÔsingletonÕ
or ÔdoubletonÕ clones, belonged to the Bacteroidetes/
Chlorobi (BC) taxonomic group (Table 3; Fig. 6(d)).
Three phylotypes (BC I–III) were closely related to environmental clones within the Bacteroides class, including
environmental clones from lakes and contaminated
groundwater. Four phylotypes (BC IV–VII) were related to environmental clones within the Sphingobacteria
class (including the genus Cytophaga) obtained from a
wide habitat range, including deep-sea hydrothermal
46
A.S. Engel et al. / FEMS Microbiology Ecology 51 (2004) 31–53
vent metazoans, gas hydrate sediment, soil, and contaminated groundwater.
4. Discussion
Terrestrial subsurface environments are often inaccessible for study, limiting our understanding of ecosystem structure and dynamics, elemental cycling, and the
impacts to earth and atmospheric biogeochemical processes. This investigation is part of an ongoing research
program to investigate biogeochemical cycling in subterranean habitats, and we have been studying sulfidic
caves as proxies for less accessible sulfidic karst aquifers.
In this report our main research goals were to identify
the bacterial groups comprising the cave microbial mats,
to gain an understanding of how geochemistry may control microbial community diversity within the aphotic
environment, and to elucidate potential ecosystem functioning and the impact of sulfur cycling and chemolithoautotrophy on the ecosystem. The results of this work
demonstrate that similar microbial communities and
concomitant microbially mediated biogeochemical cycles may be more widely dispersed in sulfidic groundwater habitats than previously recognized.
4.1. Geochemical controls on community structure and
ecosystem function
Studies from other aquatic environments suggest that
shifts in community structure could result from changes
in nutrient availability, salinity, light penetration, turbidity, oxygen content, sulfide, or pH [73,74]. At present, however, there have not been any investigations
that describe the controls on changing community structure from a freshwater aphotic habitat. Specifically, light
penetration, turbidity, and salinity are not critical
physicochemical conditions to influence these cave
microbial communities, and changes in pH of the cave
waters are not important because of pH buffering to circum-neutral by dissolving carbonate rock. Instead, we
propose that (1) downstream variations in dissolved
hydrogen sulfide concentrations, (2) increasing dissolved
oxygen concentrations downstream, (3) colonization of
the springs and outflow channels by ‘‘Epsilonproteobacteria’’, and (4) changes in the organic carbon production
and storage as a result of chemolithoautotrophy by epsilonproteobacterial groups are the most critical parameters affecting microbial community structure within the
microbial mats.
The high concentrations of dissolved sulfide discharging from the springs would provide a rich energy source
for sulfur-oxidizing bacteria. Although it is unlikely that
abiotic autoxidation (i.e., chemical oxidation) and volatilization cause sulfide loss exclusively, there was an observed decrease in dissolved sulfide concentrations
downstream (Fig. 1(b)). Abiotic autoxidation is extremely slow in poorly oxygenated water at pH 7.4 (the
autoxidation half-life was calculated at >800 h;
H2S:HS pK 7.04) and sulfide volatilization from the
water to the cave atmosphere accounts for <8% of the
sulfide loss in the cave stream based on gas flux experiments [31]. With no other mechanism for sulfide loss,
there would be, for example, significantly higher sulfide
concentrations at the end of the Upper Spring microbial
mat, as well as at the cave entrance 150 m further downstream. However, we observe a very rapid decrease in
dissolved sulfide at each of the springs (Fig. 1(b)), and
have demonstrated in an independent investigation that
the loss is caused by microbial catalysis, even under
microaerophilic conditions [31]. As the microbial mats
are overwhelmingly dominated by metabolically active
‘‘Epsilonproteobacteria’’ based on previous investigations using FISH [26], we suggest that these organisms
consume the dissolved sulfide in the cave as sulfur-oxidizers [31]. Although there is comparatively little information from culture-based studies [62,75–82],
‘‘Epsilonproteobacteria’’ are implicated in the oxidation
of reduced sulfur compounds at low oxygen tensions
in many sulfidic environments, including caves
[16,21,26], deep aquifers [83], terrestrial springs and
groundwater [58–62,84], oil fields [85], deep marine sediments and ocean water [86–89], hydrothermal vent sites
[63,75,90–95], in association with deep-sea animal life at
vent sites [64,96–100], and in engineered systems including sewage sludge and contaminated waste [101,102].
The relative abundances of epsilonproteobacterial
and other taxonomic groups shifted through the microbial mats moving downstream with changing dissolved
sulfide and oxygen concentrations. In general, the
abundances of both epsilonproteobacterial LKC groups
I and II decreased from the orifice pools downstream,
and the highest abundance of LKC group I was from
samples where the concentration of dissolved oxygen
was very low at both the Fissure and Upper Springs.
Clone libraries from the three spring orifices, which
originated from habitats that are continuously replenished by sulfidic spring water, were dominated by one
epsilonproteobacterial group, whereas downstream
libraries had higher bacterial diversity (Tables 3 and
4). For example, at the Lower Spring all clones
screened by RFLP belonged to the epsilonproteobacterial LKC group II, whereas one meter downstream in
the microbial mat there were nine other bacterial
groups identified, including those belonging to the
Gammaproteobacteria and Betaproteobacteria (Table
3). At the Upper Spring, LKC group III was most
abundant in downstream clone libraries (e.g., 203f)
where the dissolved oxygen concentration was higher,
suggesting that while this group may be involved with
sulfur cycling, this group may prefer higher habitat
oxygen content. At the three springs, there was also
A.S. Engel et al. / FEMS Microbiology Ecology 51 (2004) 31–53
an increase in the abundance of Thiothrix- and/or Thiobacillus-like clones downstream, which is in accordance
with the characterized metabolism of sulfide and oxygen gradient preferences for these groups [103,104] (Table 3). The pattern of occurrence for Acidobacteria, and
dominance from the 203w clone library and not from
upstream samples, suggests that these organisms also
prefer higher habitat oxygen and lower sulfide concentrations.
Sulfur storage in the microbial mats from the three
springs, as indicated by sulfur content, also changed
downstream. There is no indication from cultures that
‘‘Epsilonproteobacteria’’ store sulfur intracellularly like
Thiothrix spp. [103], although the marine epsilonproteobacterial strain ‘‘Candidatus Arcobacter sulfidicus’’
forms extracellular sulfur filaments [105,106] and cultures of nitrate-reducing sulfur-oxidizing ‘‘Epsilonproteobacteria’’ form sulfur as the metabolic end-product
when nitrate is limiting or absent [77,80]. Therefore,
the high sulfur content of white filaments from spring
orifice samples (Table 2), which were dominated by
‘‘Epsilonproteobacteria’’ (Table 3), could be due to
extracellular sulfur or sulfur accumulation due to nitrate-reduction. Higher sulfur content in downstream
mat samples could also be due to incomplete sulfide oxidation to elemental sulfur by Thiothrix. The lower sulfur
content for the 203y sample (8.6%) compared to the
other morphotypes from the mat surface (Table 2)
may be because the thiobacilli oxidize the sulfur within
the mat due to the diminished dissolved sulfide concentration in the stream water.
While there are no known cultivated organisms closely related to LKC groups II, V, or VI clones, the closest cultured relative for LKC group I clones is strain
YK-1, or S. kujiens [62]. It is possible that the organisms
represented by LKC group I may also have similar
metabolism to S. kujiense and grow under microaerophilic to anaerobic conditions, although nitrate and ferric iron concentrations are exceptionally low in the cave
waters (Table 1). It should be noted, however, that closely related phylogenetic groups do not necessarily indicate similar ecophysiological characteristics [57], as
Takai et al. [75] showed that the observed phylogenetic
distribution of epsilonproteobacterial cultures isolated
from deep-sea vents did not correlate with substrate or
electron acceptor preferences, oxygen requirements, or
geographic location. The fact that there are few sequences from the public databases that are closely related LKC epsilonproteobacterial groups suggests that
the metabolic diversity of these environmental groups
in the terrestrial subsurface has yet to be explored. This
study expands the geographic distribution of ‘‘Epsilonproteobacteria’’, significantly increases the number of sequences for ‘‘Epsilonproteobacteria’’ from terrestrial
subsurface environments, and more importantly, characterizes the distribution of different epsilonproteobac-
47
terial groups according to physicochemical habitat and
possibly ecosystem function.
Based on experiments at deep-sea vent sites where
‘‘Epsilonproteobacteria’’ are the first to colonize virgin
surfaces, López-Garcı́a et al. [100] suggest that epsilonproteobacterial groups initially and rapidly diversify
metabolically within a habitat (natural or artificial),
and thereby create microniches (such as anoxic regions)
where other bacteria will subsequently colonize. High
diversity among the specialized ‘‘Epsilonproteobacteria’’
would essentially maximize ecosystem functionality of
other microbial groups and make the entire system more
productive because of high growth rates, significantly
high biomass, and quick adaptations to specific geochemical conditions of the habitat. However, Chesson
et al. [30] also describe the tendency for the most productive species to also be the most dominant in a habitat, and thereby push others species to comparatively
lower densities. These ecological caveats may explain
why the microbial mats in Lower Kane Cave have high
diversity within the ‘‘Epsilonproteobacteria’’, but lower
bacterial diversity overall.
The bacterial composition of the 203g clone library is
one of the most telling examples of the control geochemistry has on community composition, and perhaps as an
ecological consequence of ‘‘Epsilonproteobacteria’’ creating anoxic regions within the mat. The interior of the mat
was dominated by clones closely related to two groups of
Gammaproteobacteria that are characterized as facultative anaerobes with diverse metabolic capabilities
[107,108]. Although rare clones closely related to D. thiozymogenes were also identified from some samples (Table 3), preliminary culture-based investigations of gray
filaments and other mat samples suggest that sulfate-reducing bacterial guilds are also present in the mats, with
<106 cells ml1 [109]. While molecular methods allow
for the characterization of organisms that are difficult, if
not impossible, to cultivate [110], unfortunately molecular methods can create significant biases and underestimates of particular microbial groups, especially if
groups have abundances 6107 cells per volume [55,111].
Therefore, because this study focused on the white filament bundle morphotypes that were overwhelmingly
dominated by ‘‘Epsilonproteobacteria’’, it is likely that
the diversity of anaerobes is underrepresented with respect to the total genetic diversity of the cave microbial
ecosystem, and combined culture- and molecular-based
approaches are currently being employed to better describe the diversity of the lesser abundant, anaerobic
groups.
4.2. Chemolithoautotrophy in the subsurface
Most caves are energy- and nutrient-limited, commonly fed by surface streams in which photosynthetically-derived
organic
matter,
sediments,
and
48
A.S. Engel et al. / FEMS Microbiology Ecology 51 (2004) 31–53
microorganisms are washed into the subsurface and
deposited [10,11]. Previous studies have shown that
microorganisms in caves associated with surface input
are not chemolithoautotrophs, but instead are translocated soil heterotrophs, chemoorganotrophs, or fecal
coliform bacteria from contaminated surface water
[10]. Mikell et al. [12] estimate that P75% of microbial
communities in most caves are heterotrophs. While we
recognize that in the past the Bighorn River near the
cave entrance may have had a role in inoculating the
cave with microorganisms during previous flood stages,
we believe that the LKC microbial communities are endemic to the cave and unaffected by surface hydrologic
conditions because (1) the filamentous microbial biomass in LKC is significantly higher than the 102 to 104
cells ml1 commonly found in other aquatic cave systems [112], and (2) the discharging springs contribute little to no allochthonous DOC or particulate organic
carbon to the microbial community (Table 1). Because
the geochemistry of the cave waters is consistent with reduced sulfur compounds being important energy sources
for the microbial ecosystem and because most of the
microbial groups can be associated with sulfur metabolism [31], we hypothesized that primary productivity was
linked to the sulfur cycle.
We applied stable carbon isotope systematics to interpret the source of carbon to the LKC microbial mats, as
well as how carbon is cycled within the mats. The overall
organic carbon isotope compositions of the microbial
biomass reflect significant isotopic discrimination
against 13C relative to the inorganic carbon source, with
77% of the microbial mat samples having d13C values
630&, well below that of terrestrial biomass [113]; this
demonstrates that photosynthetically-derived material
is not important to the LKC ecosystem and that carbon
for the ecosystem originates from chemolithoautotrophic inorganic carbon fixation. Porter [18] verified
chemolithoautotrophic productivity from the white filamentous microbial mats at the Lower Spring by
H14CO3-assimilation, which suggested that there was
more than six times higher autotrophic productivity than
14
C-leucine-incorporation that tested for heterotrophy.
Chemolithoautotrophy in a cave ecosystem is important because it serves as the base for the cave food web,
increasing both food quality and quantity [5,10]. Movile
Cave, Romania, also a sulfidic cave system, has the first
documented chemolithoautotrophically-based cave and
groundwater ecosystem [7], and subsequently, chemolithoautotrophic microbial growth has been found in
other active sulfidic cave systems, including marine
caves from Cape Palinuro, Italy [65], Parker Cave [16],
the Frasassi Caves, Italy [8,19], Cueva de Villa Luz,
Mexico [17], Cesspool Cave [21], and the flooded Nullarbor caves, Australia [23]. The bulk of the LKC white filament bundle biomass had low C:N ratios averaging
5.0, compared to a C:N ratio of 5.7 for microbial mats
from Movile Cave [5]. The C:N ratios for LKC white
mat morphotypes also match previously reported ratios
for bacterial cells (C:N = 3–5, [114]), but also to
periphyton in surface streams (C:N = 4–8, [115]) and
bacteria from a marine hydrothermal vent (C:N = 3.8–
9.4, [116]). The C:N ratios are consistent with an insignificant influx and processing of allochthonous carbon,
and instead suggest that carbon is provided in situ
through autotrophy. In contrast, the high C:N ratios
in the gray filaments samples proximal to the spring orifices, from the same locations as white filament bundles,
indicate that the two microbial communities are not in
communication. The high C:N ratios suggest that there
is an abundant carbon supply, carbon storage due to an
accumulation of processed biomass, and a reduction in
nitrogen availability. Downstream the gray filament
samples have C:N ratios similar to the white filament
morphotypes, indicating that the white and gray microbial mat communities are in contact with each other
structurally and that the gray filaments are no longer
limited in nitrogen relative to the abundant supply of
carbon (Table 2). The especially low C:N ratios suggest
a high quality food that could be used by higher trophic
levels [51,52]. Incidentally, there are large populations of
endemic snails (Physa spelunca) that graze upon the
microbial mats at all the LKC springs [117].
The mechanisms for inorganic carbon fixation were
not evident based on carbon isotope analyses, as there
are several different pathways for inorganic carbon fixation, and not all fixation pathways and their isotopic effects are known. Microorganisms that fix CO2 by the
Calvin–Benson–Bassham cycle, the predominate and
most important carbon fixation pathway for photosynthetic and chemosynthetic bacteria, have isotopic values
that fall into two categories based on the form of CO2fixing enzyme, ribulose-1,5-bisphosphate carboxylase/
oxygenase (RubisCO) [118]. Nearly all of the mat samples from LKC have d13C values that fit into the RubisCO form I group with d13C values ranging between
27& and 35& (the Ô30& groupÕ) [118]. The chemolithoautotrophic pathway using the reductive citric
acid (TCA) cycle imparts a smaller (10&) carbon
isotope fractionation [105,106,119]. Physicochemical
conditions, such as flow velocity, water depth, temperature, pH, and CO2 concentrations, can affect the effective isotope discrimination of autotrophs, which would
result in tremendously different isotopic discrimination
values [119–121]; however, the stream water in the
Upper Spring transect maintains constant chemistry
and turbulent flow, suggesting that these physical conditions are not important.
Variations in the carbon isotope composition among
the different microbial mat morphotypes in downstream
transects suggest carbon cycling between chemolithoautotrophs and heterotrophs. The carbon isotope ratios
for each of the morphotypes upstream were higher than
A.S. Engel et al. / FEMS Microbiology Ecology 51 (2004) 31–53
the same morphotypes downstream, especially for samples from the Upper Spring transect (Fig. 3). The systematic differences in the carbon isotope composition among
the mat morphotypes at any location suggest that there
may be distinct carbon isotope effects imparted by specific populations during carbon fixation. Compartmentalization of the microbial populations within a
morphotype and changing abundances of bacterial populations downstream could account for the observed
trend if the downstream populations express larger 13C
discrimination. However, an alternative explanation for
the downstream trend may be that mat stratification,
due to redox conditions, creates an environment for
nutrient spiraling [122]. The autotrophically-fixed carbon, when respired as CO2, has a low d13C value, and
may be transported downstream and preferentially reassimilated by autotrophs at the mat boundary layer; the
proportion and amount of autotrophic recycling of the
fixed carbon derived from respiration should increase
downstream [122]. Carbon isotope compositions of aerobic and anaerobic mat components reflect a complicated relationship between primary production and
carbon recycling, with isotope ratios tending to increase
with enhanced carbon recycling. The d13C values of the
anaerobic (gray filament) mat components are generally
higher than coexisting white filament bundles or web and
yellow patch morphotypes, and progressively converge
upon those of the white morphotypes dominated by
autotrophic ‘‘Epsilonproteobacteria’’ (Fig. 3). This reflects the assimilation and respiration of autotrophically-produced organic carbon by anaerobic
heterotrophic bacteria downstream. Nutrient spiraling,
as it pertains to carbon cycling, has not been previously
described from chemosynthetic or subterranean ecosystems. In the future, more detailed carbon isotope ratio
analyses, microautoradiography to test for specific carbon substrate uptake [123], using primer sets to amplify
partial subunits of RubisCO (forms I and II) enzyme
from DNA [4], and culturing of specific microbial groups
will better address the type and extent of autotrophy and
carbon cycling.
In this study, we combined molecular techniques with
stable organic carbon isotope ratio analysis to examine
the dynamics of microbial community structure and
nutrient cycling in microbial mats occupying aphotic sulfidic springs. Building on our previous work describing
the dominance of the cave microbial mats by ‘‘Epsilonproteobacteria’’ [26], we found several additional evolutionary lineages within the ‘‘Epsilonproteobacteria’’,
increasing the geographic diversity of this class to subsurface environments. Microbial mat bacterial diversity
was low overall; certain bacterial groups were found only
in one microbial mat morphotype, and most bacterial
groups were rarely found or were completely absent in
other morphotypes. The concentration of dissolved oxygen and dissolved sulfide controlled the distribution of
49
sulfur-oxidizers with differing requirements for oxygen,
such that those preferring higher oxygen conditions were
found at the end of the microbial mats where dissolved
oxygen was highest. The ‘‘Epsilonproteobacteria’’ provide chemolithoautotrophic energy to the ecosystem
and colonize the nutrient-poor habitat and diversify
genetically and metabolically, creating new habitats
due to the formation of a dense mat, which increases species richness downstream. The resulting stratification of
distinct microbial groups within the mats based on geochemistry and stream advection increase nutrient availability downstream, and perpetuates spiraling of carbon
among multiple components of the microbial ecosystem.
Future work will address the extent to which the ‘‘Epsilonproteobacteria’’ are distributed in other aphotic habitats, and what role these organisms may play in nutrient
cycling and changing subsurface habitat conditions.
Acknowledgement
We thank the Bureau of Land Management for continuing to permit this research. We thank S. Engel,
T. Dogwiler, M. Edwards, K. Mabin, R. Payn, and
J. Deans for field assistance, and K. Crandall for laboratory support and critical insights. This work was supported by a National Science Foundation LExEn
grant (EAR-0085576), Brigham Young University, and
the Geology Foundation of the University of Texas at
Austin.
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