Survival strategies of an anoxic microbial ecosystem in Lake Untersee, a potential analog for Enceladus

Abstract

Lake Untersee located in Eastern Antarctica, is a perennially ice-covered lake. At the bottom of its southern basin lies 20 m of anoxic, methane rich, stratified water, making it a good analog for Enceladus, a moon of Saturn. Here we present the first metagenomic study of this basin and detail the community composition and functional potential of the microbial communities at 92 m, 99 m depths and within the anoxic sediment. A diverse and well-populated microbial community was found, presenting the potential for Enceladus to have a diverse and abundant community. We also explored methanogenesis, sulfur metabolism, and nitrogen metabolism, given the potential presence of these compounds on Enceladus. We found an abundance of these pathways offering a variety of metabolic strategies. Additionally, the extreme conditions of the anoxic basin make it optimal for testing spaceflight technology and life detection methods for future Enceladus exploration.

Full text

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Survival strategies of an anoxic
microbial ecosystem in Lake
Untersee, a potential analog
for Enceladus
Nicole Yasmin Wagner1, Dale T. Andersen2, Aria S. Hahn3 & Sarah Stewart Johnson1,4*
Lake Untersee located in Eastern Antarctica, is a perennially ice-covered lake. At the bottom of
its southern basin lies 20 m of anoxic, methane rich, stratied water, making it a good analog for
Enceladus, a moon of Saturn. Here we present the rst metagenomic study of this basin and detail
the community composition and functional potential of the microbial communities at 92 m, 99 m
depths and within the anoxic sediment. A diverse and well-populated microbial community was found,
presenting the potential for Enceladus to have a diverse and abundant community. We also explored
methanogenesis, sulfur metabolism, and nitrogen metabolism, given the potential presence of these
compounds on Enceladus. We found an abundance of these pathways oering a variety of metabolic
strategies. Additionally, the extreme conditions of the anoxic basin make it optimal for testing
spaceight technology and life detection methods for future Enceladus exploration.
Antarctic Lake Untersee. e discovery of extreme environments and the study of the organisms that
inhabit them have made the search for life beyond Earth amore plausible endeavor1. One of the most extreme
environments on Earth is Antarctica, a vast polar desert where temperatures dip to the lowest levels on the
planet. Where local conditions allow for the presence of liquid water, isolated oases of life exist2. ese include
ice-covered lakes where microbial extremophiles have developed strategies to live in cold, low-light, oligotrophic
conditions. While seasonally ice-covered lakes tend to have geochemically dierent environments in winter and
summer, perennially ice-covered lakes in Antarctica are more physiochemically stable3,4. e thick, perennial
ice-cover dampens the eects of turbulent winds and attenuates the penetration ofsummer sunlight, which
thendrops to zero during the long polar winter.
One such lake, Untersee, is a perennially ice-covered, ultra-oligotrophic lake located at 71.34°S, 13.46°E in the
Gruber Mountains of central Dronning Maud Land5–7. Elevations in the oasis range from 600 to 2790m and local
geology consists of norite, anorthosite, and anorthosite–norite alternations of the Eliseev anorthosite massif8.
e lake is located within a closed basin at c. 610m a.s.l. and is dammed at its northern end by the Anuchin
Glacier where pressure ridges form at the lake–glacier interface. Lake Untersee is 2.5km wide and 6.5km long
and is among the largest lakes in central Queen Maud Land5.
A result of the intense evaporation and sublimation is that summer melt does not provide signicant amounts
of water for recharge. e only large contributions of liquid water occur from melt of the Anuchin Glacier beneath
the lake ice cover, and sub-glacial/groundwater discharge. A 16S rRNA amplicon study showed that this glacier
does not function as a standalone ecosystem but functions as part of the lake itself as a larger scale microbial
system52. e lack of streams entering into the lake or formation of summer moats results in an environment
that is essentially sealed o, with no direct contact with the atmosphere5,9.
Lake Untersee loses c. 1% of its water annually from the sublimation of the 2.5–4m thick ice cover. To main-
tain hydrological balance the lake must be recharged by an equal inow5,10. e lake is dammed at its northern
end by the Anuchin Glacier and mass balance calculations suggest that subaqueous melting of terminus ice
contributes 40–45% of the annual water budget with subglacial meltwater contributing the remainder5. Based on
δD-δ18O of the water column, the lake has not developed a moat for at least the past 300–500years providing
OPEN
1Department of Biology, Georgetown University, 3700 O Street NW, Washington, DC 20057, USA. 2SETI Institute,
Mountain View, CA, USA. 3Koonkie Inc, Menlo Park, CA, USA. 4Science, Technology, and International Aairs
Program, Georgetown University, Washington, DC, USA. *email: sarah.johnson@georgetown.edu
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another indication of just how isolated this lake is from the atmosphere or other external inputs11. Information
on the properties of the water column can be found in Fig.1 as well as Supplementary TableS4.
An exclusively microbial ecosystem is found along Lake Untersee’s bed with photosynthetic microbial mat
communities observed to depths of at least 160 m12 (DaleAndersen, unpublished data). e microbialmats
are composed of lamentous cyanophytes that form at, prostratemats, cm-scale cuspate pinnacles, and large
conical stromatolites that rise up to 70cm above the lake oor. ese larger microbial structures provide an
exampleof modern, unlithied stromatoliteswith a morphology similarto the large, conicalstromatolites that
existed during the Archaean era53. Two unusual features of the lake are a high concentration of dissolved methane
(> 20mM) in the deep part of the anoxic basin, and a pH of ≥ 10.5 in the mixed layer of the lake. e primary
source of methane has been identied as microbial reduction of carbon dioxide using hydrogen13. e high pHof
the poorly buered lake water is partly, if not primarily, due to CO2 uptake by the photosynthetic microbial mats
and subglacial weathering of plagioclase9,12,14.
Possibility of life on Enceladus. e anoxia, darkness, and chemical composition of Lake Untersee’s
anoxic southern basin (dissolved H2, CO2, CH4, NH3, etc.) make it a relevant environment for studying the
potential for life in the oceans of icy moons in our solar system (Fig.2)14. One of these bodies is Enceladus, the
sixth-largest moon of Saturn. Although 25 times smaller than Earth, Enceladus harbors what is believed to be
a global ocean covered by a global ice sheet15. In 2005, the National Aeronautics and Space Administration’s
(NASA) Cassini mission discovered plumes of gas and icy particles venting into space over the Saturnian moon’s
south polar region16,17. To date, the Cosmic Dust Analyzer (CDA) instrument detected biologically available
nitrogen in the form of amines, traces of H2S, inorganic salts, and carbon dioxide and molecular hydrogen that
can function as a redox pair for methanogenesis in anoxic environments. Methanogenesis is one of the oldest
known energetic pathways on Earth. e presence of salts and all the compounds necessary for life (C, H, N, O, P,
S) together with the presence of liquid water, indicate a habitable environment18,19,31.Future missions searching
for evidence of life may collect venting particles during ybys through the plumes, or landers may obtain larger
sample quantities from particles that fall back onto the surface of Enceladus, thus providing a means for high-
sensitivity measurements for the detection of trace elements and any potential biosignatures.
Analog study objectives. e deep waters of the southern basin of Lake Untersee harbor carbon dioxide,
hydrogen, methane, and ammonia, which in combination with low mean temperatures represents a physical,
chemical, and possibly biological analog for Enceladus9. Lake Untersee’s anoxic basin dominated by a low-tem-
perature anaerobic microbial ecosystem. us studying Lake Untersee’s anoxic basin, especially the energetic
pathways within the microbial communities inhabiting the lake, can shed light on the potential habitability of
Enceladus. Here, four samples from the anoxic water column as well as a sample of the anoxic sediment were
collected. We sequenced the microbial communities using a whole genome shotgun approach in order to chart
the taxonomic composition of these communities and identify metabolic pathways and strategies used to survive
these extreme conditions.
Results
Water samples were ltered twice (see Methods), rst through a large lter (0.45µm, LF or “Large Filter”) and
then the ltrate was passed through a small lter (0.05µm, UF or “Ultrane Fraction”).Using whole genome
shotgun metagenomics from four water samples (LF92and UF92from the 92 m depth, LF99and UF99from
the 99 m depth) as well as one sediment sample, we provide the rst comprehensive whole genome shotgun
metagenomics investigation of this section of the lake and highlight both thetaxonomic compositionand poten-
tial metabolic strategies for survival, as well as identify areas for deeper investigation.
Cell counts and dissolved nutrients. In order to determine the habitability of the anoxic basin, the cell
counts were measured in the oxycline (75m depth) and the anoxic region (92 and 99m depth), where oxy-
gen content is < 1mg/L (Fig.1). e cell counts were 84,129 cells/mLat 75m, 895,516 cells/mLat 92 m, and
775,404 cells/mLat 99m. In the anoxic depths, the cell counts were roughly an order of magnitude higher than
the count at 75m depth. Dissolved nutrient levels were also signicantly higher in the anoxic section than the
oxycline (Table1). e ammonium content at 92m was 1675.98µmol/L, double the amount at 99m, which
was 758.53µmol/L. e concentration was much lower in the oxycline at 4.11µmol/L. e phosphate content
in the oxycline was0.06µmol/L. e concentration was over three orders of magnitude higherin the anoxic
region, measuring 35.19µmol/L at the 92m depth and 47.30µmol/L at the 99m depth. e silicate content
in the oxycline was 86.76µmol/L. e concentration was once again higher in the anoxic region, measuring
387.62µmol/Lat 92 m and 664.60µmol/Lat 99 m.
Taxonomic proling. Unclassied organisms. Taxonomic annotationswere performed using the Lowest
Common Ancestor Staralgorithm (LCA*) with the RefSeq database21. With this annotation tool, any organism
that could not be assigned a taxonomic classication beyond the superphylum level (bacteria, archaea, prokary-
otes, root) was designated as “unclassied”. LCA* was able to classify an average of 60% of the contigs across all
samples. Kaiju22 and Kraken223 were able to classify an average of 18.75% and 19.5% of the reads from all samples
respectively. Given that LCA* was able to annotate the greatest fraction of the reads, we focused on these results.
e percentage of unclassied organisms increased with depth, from 37% at 92m to 43% at 99m to 45% of the
community in the sediment layer. At the phylum level, 97–99% of the unclassied organisms were assigned to
the bacterial superphylum. In each sample, fewer than three percent of the unclassied organisms belonged to
the archaea superphylum (FigureS1).
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Figure1. An Overview of Lake Untersee’s Anoxic Basin. (A) Satellite view of Lake Untersee and a cross-section
of the bathymetry of the lake with the location of the anoxic trough in the South basin. (B) Dissolved methane
concentrations within the South basin. (C) Dissolved oxygenconcentrations and temperature within the South
basin. (D) pH and conductivity in the South basin. Image credit: satellite imagery (©Maxar) provided by
NextView License, depth proles modied from Wand etal., 2006 and Dale Andersen, unpublished data.
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Classied organisms. Archaea make up 2% of classied organisms at the 92m depth and 4% of classied organ-
isms at the 99m depth and in the sediments. Bacteria make up 98% of classied organisms at the 92m depth,
and 96% of classied organisms at 99m depth and in the sediment. Specics of classied and unclassied organ-
isms per sample as well as deeper taxonomic classications may be found in the Supplementary Information
(FiguresS1 and S2).
Classied archaea. e total percentage of archaea in the samples doubles from 1% of the community at the
92m depth to 2% at 99m andin the sediment (Fig.3). Archaea are almost entirely classied at or beyond the
phylum level in these samples. Euryarchaea are the most abundant archaeal phylum in all samples. ey make up
97% of archaea, or 1% of all organisms at the92m depth. At the 99m depth and the sediment layer, they make up
over 99% of archaea, or 2% of all organisms. Euryarchaea are well-known anoxic methanogens, andtheir higher
abundance at 99m and inthe sediment could explain why the concentration of dissolvedmethane was found
to be highest at the deep anoxic layer near the water–sediment interface (Fig.1)13. More details on the archaeal
community may be found in Table2 andin the Supplementary Information.
Classied bacteria. Proteobacteria are the most abundant classied bacteria in the system. e classes present
include Alphaproteobacteria, which make up 1% of organisms in LF92, 2% in UF92, and 1% in LF99, UF99, and
the sediment. Betaproteobacteria make up 8% of organisms in LF92, 10% of organisms in UF92, 5% in UF99, 4%
in LF99, and 6% in the sediment. Deltaproteobacteria make up 16% of the community in LF92, 9% in UF92 and
UF99, 13% in LF99, and 15% in the sediment. Gammaproteobacteria make up 2% of the organisms in LF92, 3%
of organisms in UF92, 2% in UF99 and LF99, and 1% of the community in the sediment. Planctomycetes make
up 2% of all organisms in LF92, 0.5% of organisms in UF92 and 0.3% in UF99, and 3% of organisms in LF99.
e most abundant class belonging to this phylum is Planctomycetia. Actinobacteria make up 1% of organisms
in the LF92, UF92 and LF99 samples, 2% of organisms in UF99, and a total of 3% of classied organisms. e
only major annotated class within Actinobacteria is also named Actinobacteria and makes up more than 70%
of this phylum in the water column and 48% of the phylum in the sediment. Bacteroidetes make up 10% of the
community in LF92, 15% of the community in UF92, 12% of the community in UF99, 9% of the community
in LF99 and 3% of the community in the sediment. e major annotated classes belonging to Bacteroidetes are
Marinilaceae, Cytophagaceae and Chitinophagaceae. Firmicutes constitute 8% of the organisms withinLF92,
11% of UF92 and UF99, 9% of LF99, and 5% of the sediment. e major annotated classes within this phylum
Figure2. (A) View of a cross section of Enceladus and the ocean of Enceladus. (A) Enceladus ocean and icy
crust. (B) Cross section of Enceladus’s icy crust, ocean and core. Image credit: illustration by N.Y. Wagner,
drawing upon schematic renderings from NASA/JPL-Caltech and the Southwest Research Institute.
Table 1. Summary of anoxic lake properties, including cell counts and dissolved nutrients.
Site Cell count #cells/mL Nitrate + Nitrite µmol/L Ammonium µmol/L Phosphate µmol/L Silicate µmol/L
75m 84,129 < 0.040 4.11 0.06 86.76
92m 895,516 < 0.040 1675.98 35.19 387.62
99m 775,404 < 0.040 758.53 47.30 664.60
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are Clostridia and Bacili. A summary can be found in Table2 and more detail is included in the Supplementary
Information.
Taxonomic dierences between fraction sizes. To ascertainif cellsize played a role in survival capa-
bilities in this extreme environment, we assessed the metabolic potential within the size fractions. While the
percentage of Proteobacteria in the community is more related to depth than lter size in the water column,
within the Proteobacteria, we found the large fraction samples had 13–16% of the community classied as Del-
taproteobacteria. In contrast, only 9% belong to ultrane fractions. At 15%, the fraction of Deltaproteobacteria
in the sediment is similar to that of the LF samples. Planctomycetes make up 2–3% of the LF samples, while they
make up only 0.3–0.5% of the UF communities. Planctomycetes make up 4% of the community within thesedi-
ment. More details on these dierences can be found in Table2. e size of the organisms did not seem to aect
survival.
Functional analysis and metabolic pathways of interest. To determine how organisms use energy
sources available to them, MetaPathways V2.524 was used to assign metabolic pathways to the open reading
frames (ORFs) and predicted metabolic pathways using pathwaytools25. An average of 830 (standard devia-
tion of 170) pathways per sample were identied. 310 pathways were shared among all samples while an aver-
age of 27 (standard deviation of 15) pathways were unique to each sample. An average of 43 pathways were
unique to unclassied organisms among the samples, and 101 pathways were unique to classied organisms
among all samples. Overall, an average of 1.3% of all the pathways were responsible for biosynthesis, 14.2% of
pathways were responsible for degradation, and an average of 0.2% of all the pathways belonged to metabolite
precursor generation. e greatest pathways abundance, with an average of 84.1% of all pathways, belonged to
energy metabolism. To link function and taxonomy, we used the LCA annotation (obtained using the RefSeq
database26) assigned to the ORF that corresponded to a pathway.
Figure3. e taxonomic composition of the communities at the phyla level. Classied organisms in the gure
only include phyla that make up more than 1% of the community.
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Next, we focused on pathways relevant to the survival on Enceladus. First, the metabolic pathways related to
methanogenesis were examined; wethen investigated pathways related to nitrogen and sulfur compounds that
have either been detected or couldpotentially exist on Enceladus.
Methane metabolic pathways. Because the high concentration of dissolved methane in the anoxic water
is believed to be due to biotic methanogenesis13, the pathways for methanogenesis in the environment were
explored and linked to the organisms annotated to those pathways (Fig.4). Methanogenesis from (x)methyl-
amine resulted in three times fewer methanogenesis pathways in LF92 (21.2%) and LF99 (26.40%) than in UF92
(70.40%). In the sediments, however, it made up only 9% of methanogenesis pathways. In the water column,
these pathways were present in unclassied organisms, Firmicutes, Deltaproteobacteria, and Euryarchaea. In
the sediments, (x)methylamine methanogenesis pathways were only present in unclassied organisms and Del-
taproteobacteria.
Methanogenesis from CO2 was most abundant in theUF92 (19.8%) and LF92 (16.3%) samples, atalmost
double what was found in LF99 (9.7%). In the sediments, 16% of methanogenesis pathways belonged to metha-
nogenesis from CO2. Methanogenesis from CO2 was the main methanogenesis pathways present in Euryarchaea
in every sample. Except for LF92, pathways formethanogenesis from CO2 were only present in Euryarchaea and
unclassied organisms.
Pathways belonging to methanogenesis from acetate were similar among LF92 (60.5%), LF99 (54.9%), and
thesediment (74.9%). In all samples, methanogenesis from acetate was themost abundant in unclassied organ-
isms, Deltaproteobacteria, Betaproteobacteria, and Firmicutes.
Table 2. Summary of organisms in the anoxic basin. Taxonomic abundances in dierent samples arebased on
results from LCA* (RefSeq database).
LF92 (%) UF92 (%) UF99(%) LF99 (%) Sediment (%)
Unclassied Organ-
isms 36 30 42 41 45
Bacteria
Alphaproteobacteria
Rhizobiales
1 2 1 1 1Rhodospirillales
other
Betaproteobacteria Burkholderiales 8 10 5 4 6
Other
Deltaproteobacteria
Desulfovibrionales
16 9 9 13 15
Myxococcales
Desulfobacterales
Dusulfarculaceae
Desulfuromonadales
Other
Gammaproteobacteria
Pseudomonadale
2 3 2 2 1Mythlococcales
Other
Bacteroidetes
Marinilaceae
10 15 12 9 3
Cytophagaceae
Chitinophagaceae
Other
Firmicutes
Clostridia
8 11 11 9 5Bacilli
Other
Planctomycetes Planctomycetia 2 0.50 0.30 3 4
Other
Actinobacteria Actinobacteria 1 1 2 1 3
other
Other Other 25 27 25 25 25
Archaea
ermoprotei Other 0.02 0.01 0 0.02 0.002
aumarchaea Other 0.005 0.007 0.000 0.010 0.002
Euryarchaea
Methanomicrobia
1 1 0.50 2 2
Methanobacteriales
Methanococcales
Other
Other 0.001 0.001 0.000 0.006 0.008
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Nitrogen. Nitrogen metabolism plays an important role in every ecosystem and nitrogen-bearing organic
compounds have been detected in the plumes of Enceladus. In order to determine how nitrogen is cycled in
this environment, we investigated the presence and abundance of nitrogen metabolic pathwaysand found that
nitrate reduction pathways were the most abundantin our samples, including assimilatory, dissimilatory, and
denitrication pathways. While assimilatory and denitrication pathways were mainly present in the water col-
umn (and were the most abundant in the water), other nitrogen pathways were present in both water and within
the sediment, including assimilatory nitrate reduction, nitrogen xation, ammonia assimilation, urea degrada-
tion, and denitrication (Fig.5).
Assimilatory nitrate reduction was the most abundant nitrogen pathway, making up between 39–64.9% of
nitrogen metabolism pathways in the water column and only 4.7% within the sediment community (Fig.5). is
pathway was mainly found in unclassied organisms, but was also present in large abundance in Deltaproteo-
bacteria, Bacteroidetes, and Firmicutes.
e ammonia assimilation cycle made up between 35.4 and 49.2% of nitrogen metabolism pathways in the
water column, however, unlike assimilatory nitrate reduction, in the sediment this pathway represented 60.4%
of the nitrogen metabolism pathways. is pathway was present in nearly all major phyla in UF92, LF99, and
thesediment. It was most abundant in unclassied organisms.
Denitrication was present in unclassied organisms and Bacteroidetes. is pathway made up 9% of nitrogen
metabolism pathways in the water column but was absent in the sediment, suggesting that the environmental
conditions in the sediment are not conducive to denitrication.
Sulfur. Sulfate is an eective electron acceptor in anoxic environments and an important metabolic compound
in anoxic environments. Additionally, current evidence suggests that a possible biosphere within the oceans of
Enceladus may not be limited by the availability of sulfur31. Sulfur reducing bacteria and methane oxidizers have
been found to work alongside each other. Given the connection of sulfur pathways with methane metabolism
and the high concentration of methane in the anoxic basin, sulfur metabolism pathways in this environment
were also examined. In the anoxic basin, the pathways responsible for sulfur metabolism were sulfate activation
for sulfonation, sulfate reduction, and hydrogen sulde biosynthesis (Fig.6).
e highest abundance of sulfur pathways belonged to sulfate reduction. is pathway made up 64.5% of sul-
fur metabolism pathways in the LF92 sample. It made up 66% of sulfur metabolism pathways in the UF92 sample
and 56.2% of sulfur metabolism pathways in the LF99 sample. Only 8.1% of sulfur metabolism pathways in the
sediments belonged to sulfate reduction. Within the sediments, only unclassied organisms had this pathway. In
Figure4. An overview of the methanogenesis pathways. (A) Shows the methanogenesis pathway abundances
in the phyla. (B) Indicates the methanogenesis pathway abundances in each sample. Since only 44% of the reads
mapped back to the UF99sample, not much information can be inferred from the data belonging to this sample.
Here, we view methane metabolism from carbon dioxide to be the main pathway present in Euryarchaea
(theonly known anoxic methanogens). Methanogenesis from acetate is another pathway seen abundantly in
non-methanogens. is could indicate acetate as a source of energy in this anoxic environment.
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the water column, this pathway was found in unclassied organisms, Deltaproteobacteria, Betaproteobacteria,
and Bacteroidetes.
e hydrogen sulde biosynthesis pathway was only present in the LF99 (6.2%) and sediment samples (33%).
is pathway is present in unclassied organisms, Actinobacteria, Betaproteobacteria, and Deltaproteobacteria.
Discussion
High cell count and diverse taxa despite harsh conditions. e waters of the anoxic basin support a
thriving community,containing 8 × 105–9 × 105 cells/mL. e cell count in the deep waters was higher than simi-
lar environments, such as Antarctic subglacial Lake Whillans, which harbors 6.6 × 104–3.7 × 105 cells/mL within
the anoxic water27,28 as well as the anoxic subglacial water beneath Vatnajökull in Iceland, which harbors 5 × 105
cells/mL29. e cell count in the Untersee anoxic basin was also an order of magnitude higher than the anoxic
subglacial waters feeding Blood Falls in Antarctica, which harbor 6 × 104 cells/mL30, as well as the cell count in
Lake Vostok, estimated to be ~ 105 cells/mL28. Wealso compared the anoxic basin to less extreme communities
such as lakes in the McMurdo Dry Valleys. A study conducted at Lake Fryxell found that the cell counts in these
lakes decreased with depth, with the highest cell counts at approximately 4 × 105 cells/mL54. While these values
are of the same order of magnitude as the anoxic basin, they arestill slightly lower. is suggests the harsh, dark,
cold environment of the anoxic basin of Untersee can support diverse life, mirroring the results of our taxonomic
analysis. Even though 36% of the community at 92m, 43% at 99m, and 45% of the community in the sediment
were unclassied, the classied members comprised 52 phylain total. A 16S rRNA study done on the waters of
Lake Fryxell and Lake Miers in the McMurdo Dry Valleys found that the most diverse microbial community was
Lake Fryxell, with 49 annotated phyla55. is suggests that Lake Untersee is similar in diversity to other Antarctic
lakes used as analogs.
Together, the presence of diverse phyla (Fig.3) along with the relatively high cell counts demonstrates that
this analog environment is well suited to support life. If life exists on ocean worlds, it is oen envisioned to be
low biomass, largely as a result of the dark, cold conditions. Yet, in this analog environment, microbial life is
both thriving and diverse.
Complete and incomplete methanogenesis pathways in Untersee indicate varied sources of
energy. e pathway for methanogenesis from CO2/H2 was detected in the anoxic basin in Euryarchaea
and unclassied organisms (with the exception of LF92, where it is also found at low levels in Deltaproteobac-
teria). ere is a high concentration of dissolved methane in this environment, and substantial levels of meth-
Figure5. An overview of the nitrogen metabolism pathways. (A) Shows the nitrogen metabolism pathway
abundances in the phyla. (B) Shows the nitrogen metabolism pathways abundance in each sample. Since
only 44% of the reads mapped back to theUF99sample, not much information can be inferred from the data
belonging to this sample. Nitrate reduction, the most abundant nitrogen metabolism reaction, can couple with
methane oxidation and facilitate the usage of methane as an energy source.
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ane and CO2 and H2have been detected in the Enceladus plumes. Methane may play an important role in the
metabolic cycle of life that may exist in the sub-ice environments of Enceladus just as it does beneath the ice of
Lake Untersee19. e low levels of this pathway detected in the Deltaproteobacteria could signify the presence
of a partial pathway in these organisms. Euryarchaea are the only known anoxic methanogens, suggesting this
pathway is likely to be carried to completion with the production of methane. is nding is consistent with
Wand etal. (2006), which posits that methanogenesis in Untersee likely occurs near the sediment and is from
a CO2/H2 source. Hydrogenotrophic methanogenesis also dominates the methane production mechanism in
the anoxic sediment of Lake Vanda in the McMurdo Dry Valleys, even though traces of methylotrophic and
acetoclastic methanogenesis were present in those sediments, similar to the pathways present in the organisms
in Lake Untersee. From this, it is evident using hydrogen as the electron donor for methanogenesis occurs in
other extreme environments as well. e escape rates of H2 and methane in the plumes of Enceladus cannot be
explained purely by abiotic production via serpentinization32. Hydrogenotrophic methanogenesis may also be
used by potential life on Enceladus, just as it is a source of biotic methane in Lake Untersee.
e pathway for methanogenesis from acetate was present in higher abundance in the genomic DNA than
any other methanogenesis pathway. However, although methanogenesis in Untersee is derived mainly from
CO2 reduction using hydrogen, the pathways we found in Untersee for acetate-based methanogenesis have
been reported to be the principal mechanism for methane production in other anoxic sediments such as those
of Lake Fryxell56. Within the anoxic water column of Lake Untersee, methanogenesis from acetate was present
in nearly all major phyla in the water and sediment, including non-methanogenic phyla such as Deltaproteo-
bacteria, Betaproteobacteria, and Firmicutes. Given that these phyla are not known for anoxic methanogenesis,
it is likely that they are able to use acetate as their carbon energy source, therefore implying that the compound
may be an important source of energy for life in this anoxic environment. Indeed, acetate may well be present
within the oceans of Enceladus. We draw this conclusion based on evidence that acetate is the most abundantly
present water-soluble organicmolecule in carbonaceous chondrites33. Silica nanoparticles have been detected
in the E-ring of Saturn, which originated from the plumes of Enceladus34, and in order to sustain these silica
particles within the ring, Enceladus’s core must also contain carbonaceous chondrites35. e lack of detection of
acetate in the plumes can be explained by the basic pH of Enceladus. In this environment, acetate will most likely
be present in the form of an ionized organic (C2H3O). Ionized organics are water soluble and non-volatile, thus
they would evade detection by Cassini’s instrument suite36. e presence of abiotic acetate on Enceladus could
serve as yet another source of energy in this analog environment.
Other energetic pathways for life. In the microbial communities of the anoxic basin, sulfate reduction
pathways were found to dominate sulfur metabolism within the water column13. Sulfate is an ecient electron
acceptor in anoxic environments and its reduction in anoxic environments can be linked to methane oxidation.
is can be seen in other environments such as Lake Fryxell and Lake Vanda in the McMurdo Dry Valleys,
Figure6. An overview of the sulfur metabolism pathways. (A) Shows the sulfur metabolism pathway
abundances in the phyla. (B) Shows the sulfur metabolism pathways abundance in each sample. Since only 44%
of the reads mapped back to theUF99sample, not much information can be inferred from the data belonging
to this sample. Sulfate reduction, the most abundant sulfur metabolism reaction, can couple with methane
oxidation and facilitate the usage of methane as an energy source.
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where anaerobic methane oxidation is known to take place in the anoxic water columns. is reaction has been
found to be coupled with sulfate reduction, allowing organisms to use sulfate as the electron acceptor in the
upper and lower anoxic sections56,57. e presence of this pathway in the water can facilitate methane oxidation
in the water [Equation (1)]37.
While compounds detected in the Enceladus plumes indicate the potential for life, life with similar terrestrial
biochemistry would require organic forms of these compounds in order to use them for metabolic purposes.
While traces of HS may have been detected in the plumes, the presence of sulfate within the ocean can fortify
the possibility of life. Sulfate can be produced by the interaction of radiolytically produced H2 with sulfur ions
from the chondritic core. Given that sulfate is soluble in water, it would have escaped detection by Cassini36.
Nitrogen compounds are necessary for terrestrial life, and their presence in the plumes of Enceladus could
present another potential source of energy. Nitrogen metabolism pathways were present in the samples, with
nitrate reduction being the most abundant pathway. It was present in nearly all phyla within the water samples,
suggesting that many phyla can use nitrate as an energy source. Nitrate is known to be an ecient electron
acceptor in anoxic environments and the reduction of nitrate is a preferred mode of nitrogen metabolism in the
absence of oxygen38. However, in the anoxic basin of Untersee, nitrate levels were measured at below detectable
limits (Table1). Nitrate may be the limiting compound in this reaction, meaning that nitrate is being used as
a nutrient source by the community to the point of depletion. e nitrate reduction pathway could also be an
inactive pathway or a potential cryptic pathway that could be activated under specic conditions39. One way to
answer this question is by studying the metatranscriptomics of the community in which pathways are active.
In addition to acting as ecient electron acceptors, nitrite and nitrate reduction in the community can assist
in the anaerobic oxidation of methane. e nitrogen detected in the Enceladus plumes was in organic forms,
such as HCN (~ 1%) and NH3 (~ 1%), both of which are readily available for microorganisms to use40. Nitrite
and nitrate could act as anoxic electron acceptors that could not only introduce redox possibility in the oceans
of Enceladus, but also allow for more ecient use of the methane as an energy source.
A potential repository of cells. e anoxic basin of Lake Untersee may act as a potential repository of
cells. Near the bottom of the basin and in the sediment, taxa and pathways that were not expected to be present
in an anoxic environment were observed. ese pathways could belong to organisms that live in the aerobic
section but have sunk down to the anoxic basin and sediment. While most classied organisms were members
of taxonomic groups that are known to survive in anoxic environments, such as Methanomicrobia and Desul-
furobacterales, we also identied Cyanobacteria, a phylum known to use both oxygen and light to survive, in the
water column (< 1%). e presence of a small number of Cyanobacteria (~ 1%) within the sediment suggests the
sediment too may be harbor a record of cellular life from the overlying lake. Cyanobacterial mats are alsoknown
to be present in Lake Untersee’sshallower, oxygenated waters.
In addition, the superoxide radical degradation pathway was identied in the sediment. is pathway pre-
vents oxygen toxicity from oxygen produced from metabolic processes in organisms which live in aerobic
environments41. In the anoxic zone, there is no evidence of oxygen production, and therefore this pathway is
unlikely to have evolved in organisms that live there. We hypothesize that this pathway isn’t active at depth,
something future metatranscriptomic analysis of the sediment could help to clarify.
e presence of a deep cell repository could have a range of important implications. It could provide addi-
tional sources of sustenance for organisms that live in the anoxic zone, and it could play an important role in
the nutrient cycling of the lake. It mayalso suggest that the sediment–water interface on Enceladus could be a
prime place to look for records of not only active but also past life.
Conclusion
Despite the harsh environmental conditions in the anoxic waters of Lake Untersee, the many metabolic pathways
and chemical sources of energy have led to a taxonomically and metabolically diverse community. e high
cell counts and diversity of microbial life in the anoxic basin also demonstrate that the environment is highly
habitable, suggesting that methane-rich ocean worlds like Enceladus may be capable of maintaining diverse and
thriving ecosystems despite the cold, dark conditions. Life may have originated independently within the sub-ice
ocean of Enceladus—studies of the adaptive strategies used by the metabolically diverse microorganisms within
the anoxic water and sediment of Lake Untersee provide additional condence that such an ecosystem, using a
similar suite of metabolically important compounds as identied in the plumes of Enceladus, could be sustained
within the depths of that distant icy ocean world.
Lake Untersee’s ecosystem provides many opportunities for future work. e presence of a large percentage
of unclassied organisms in the community, also known as microbial dark matter, is in part due to the limita-
tions of our understanding of the evolution and physiology of organisms in extreme environments42. Ice-covered
Antarctic lakes have been little studiedusing modern molecular techniques, leading to a paucity of identica-
tions in our databases; by using Metagenome Assembled Genomes (MAGs) obtained from the assemblies, the
representation of organisms from extreme environments in current databases can be increased43.
With regard to life detection on ocean worlds, future work should focus on developing exploration and life-
detection strategies for Enceladus. While nucleobases are common in space58, XNA sequencing is not yet on the
horizon for near-term space missions, and life on Enceladus of course may be based on dierent biochemistry
than life on Earth. Nevertheless, genomic studies of analog environments oer insights into the byproducts and
other chemical biosignatures that life may leave behind in anoxic conditions, thereby helping to hone life detec-
tion targets and strategies for ocean worlds.
(1)
CH
4+SO
2
−
4
→HCO−
3
+HS−+H2
O
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Methods
Sample collection. Water (1L from each depth) and sediment samples were collected at Lake Untersee in
the Fall of 2018. Samples were collected from a hole drilled using Jiy drills (Feldmann Engineering) with 20-cm
diameter bits to provide access to the water column below the thick lake ice of the anoxic basin (S71.3556°1,
E013.42493°). Water samples were takenwith a 2.5L, model 1010 Niskin Water Sampler (General Oceanics,
Miami, FL) which was cleaned with 95% ethanol (Sigma-Alrdrich, Munich, Germany) and RNase Away (er-
mosher, Waltham, MA) prior to being lowered into the water. Water was collected from depths of 75m—the
oxycline—as well as 92m and 99m in the stratied anoxic section of the column. Water was collected from the
shallower depths rst (75m, 92m, and 99m in order) to avoid disturbing the water column. Anoxic sediments at
100m were collected using a stainless steel Ekman dredge sampler (6 × 6 × 6 inches, Wildco, Yulee, FL) targeting
the upper top 10cm of sediment. e sediment sample was collected from the same hole ve days aer the water
collection. e dredge was cleaned with ethanol and RNase Away.
Sample preparation. Aer collection, the sediment samples were transferred to cryotubes using ster-
ile sampling tools, then placed in a liquid nitrogen primed MVE cryoshipper (LabRepCo, Horsham, PA) at
− 180°C. Before being placed in the cryoshipper, water samples were ltered using an InnovaPrep Concentrating
Pipette (InnovaPrep, Drexel, MO). e turbid nature of the water made it impossible to work with only one lter
size. e particulates present would have clogged a small lter almost immediately, while using only a larger lter
would have resulted in losing many of the organisms present. In order to avoid these problems, the water was
ltered twice through a large and a small lter. e samples were initially ltered through a 0.45µm hollow ber
lter in order to collect any particulates and larger cells (designated as LF for “Large Fraction”). e ltrate was
then passed through a 0.05µm hollow ber lter in order to collect cells using the smallest available lters for the
InnovaPrep Concentrating Pipette (designated as UF for “Ultrane Fraction”). e ltered cells were diluted in
Tris elution buer. e ltrate was then pipetted into cryovials and transferred to the cryoshipper. e cryovial
samples were transported in the primed cryoshipper back to Georgetown University where they were stored in
a −80°C freezer.
Non-ltered water samples were collected in 1L wide-mouth amber Nalgene bottles. ey were stored in
coolers placed in open Antarctic weather conditions, which did not exceed 0°C during the expedition. ey
were stored at − 20°C in Cape Town for 20days before being shipped to Georgetown University on dry ice. Upon
arrival, they were stored in a − 80°C freezer.
Cell counts. Cell counts were carried out on non-ltered water at Georgetown’s Flow Cytometry and Cell
Sorting Shared Resource Center. In order to separate the cells from particulates, SYTO 40 uorescent nucleic
acid stain was used to stain the cells and count them using the ow cytometer (BD FACSAria IIu Cell Sorter with
laser set at 400nm, FCSExpress 7 soware used). In order to count the absolute number of cells, a comparison
with Trucount beads (BD Biosciences, San Jose, CA), which have a predetermined number of uorescent beads,
was done. Cell counts were carried out for all water samples, 75m, 92m and 99m (Table1). e SYTO 40 dye
does not dierentiate between living and dead cells, and the values obtained reect the total number of cells pre-
sent in the samples. Because inecient cell detachment and separation from matrix particles complicate results
from ow cytometry, we did not collect cell counts for the sediment sample.
Nutrient analysis. Duplicate 10mL non-ltered samples were placed in acid-washed bottles and sent to
Woods Hole Oceanic Institute Nutrient Analytical Facility in Woods Hole, MA. Samples were analyzed on a
four-channel segmented ow AA3 HR Autoanalyzer to determine dissolved nutrient concentration in aquatic
ecosystems, specically nitrate + nitrite, ammonium, phosphate, and silicate (Table1).
Extraction. All extractions were carried out in an AirClean Systems ISO 5 laminar ow hood at Georgetown
University. DNA from the sediment was extracted in duplicate. To lyse the cells, 500mg of sample was added to
500 µL of phenol–chloroform-isopropanol solution at a 25:24:1 concentration (Sigma-Alrdrich, Munich, Ger-
many) in Lysis Matrix E tubes (MPBio, Santa Ana, CA) subjected to high velocity bead-beating with a FastPrep
24 5G (Qiagen, Inc., Valencia, CA) at 5.5m/s for 30s. e genomic material was then separated from the organ-
ics in the sample by rapid centrifugation of the lysate at 4˚C, at a speed of 16,000g for 5min along with 500µL
chloroform-isopropanol alcohol in a phase lock heavy gel tube. e genomic material (phase separated from the
organics) was moved to a clean tube and le to incubate at room temperature for an hour. Aer this preparation
step, a Qiagen AllPrep DNA/RNA Extraction Kit (Qiagen Inc., Valencia, CA) was used to purify the DNA out of
the sample alongside sample blanks to track contamination.
For the cells concentrated out of the anoxic sample water—the focus of this study—ultrane (0.05–0.45µm)
and large fractions (> 0.45μm) concentrated from both 92m and 99m depths were extracted in duplicate, for
a total of four extractions. 250µL of cellsconcentrated in Elution Buer (InnovaPrep, Drexel, MO) along with
500µL of 25:24:1 phenol–chloroform-isopropanol bead-beated at 5.5m/s for 30s in Lysis Matrix E tube followed
by a Qiagen AllPrep DNA/RNA extraction kit was used to extract and purify DNA from the cells. Sample blanks
were again used to ensure no contamination.
e yield from the samples was measured using the high sensitivity dsDNA Qubit Assay kit (ermosher,
Waltham, MA). All replicate extractions were measured before sequencing to ensure the samples had enough
DNA.
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Sequencing and data analysis. e DNA extractions from the sediment were sequenced on the Illumina
MiSeq platform at 300bp paired-end MiSeq reads sequenced at the Georgetown University Genomics and Epi-
genomics Shared Resource Center.
DNA extractions from the water samples, which were generally low-yield, were prepared with the Accel-
NGS® 1S Plus DNA Library Kit (Swi Biosciences, Ann Arbor, MI). e sequencing was then completed using
the paired-end 250bp Illumina NextSeq platform. e samples were sequenced at the University of Illinois at
Chicago Genome Research Core. Due to constraints in laboratory services during the COVID-19 pandemic, we
were unable to send this nal sample to the same facility. Although both sequencing platforms used Illumina
technology, it should be noted that the dierence in the sequencing platform used for the water samples versus
the sediment sample may bias the results, and this should be considered when interpreting the data.
e raw reads were trimmed and the reads above Q30 threshold were selected using Trimmomatic using
default settings44. e quality of the reads was checked with FastQC45. Details about the number of reads, number
of ORFs, and read lengths are presented in Supplementary Tables1, 2 and 3. e assemblies were built with the
MEGAHIT pipeline with default settings46.
MetaPathways V2.524 was used to annotate the assemblies using several databases including RefSeq26, KEGG47,
and MetaCyc48. e samples were normalized using RPKM (Reads Per Kilobase per Million mapped reads)24.
While both read and assembly-based methods were used, in order to have high quality alignment and func-
tional annotation20, we used metagenomic assemblies for our downstream analyses. More details can be found
in the Supplementary Information.
Taxonomic proles. e taxonomic prole of the community was made using several dierent soware tools
including, Kraken223, Kaiju22, and Lowest Common Ancestor Staralgorithm (LCA*)21, a method that assigns
taxonomy to contigs instead of open reading frames using the least common ancestor algorithm and voting
theory method. e LowestCommon Ancestor Starmethod cannot assign a deep taxonomic classication to
housekeeping genes since they are ubiquitous in organisms.
Functional analysis. Where possible we linked the function to taxonomy at the contig level using LCA*. e
quality of the UF99 sample is poorer than that of other assemblies; there are fewer reads mapped in this assembly
(TableS2), thus fewer ORFs were found and annotated in this sample.
Functional annotation and pathway prediction were done using MetaPathways V2.524, a modular pipeline
for open reading frame (ORF) prediction, functional and taxonomic annotation using the RefSeq database, ORF
count normalization (for both sequencing depth and ORF length), and the creation of environmental pathway
genome databases (ePGDBs) based on a well-curated database of metabolic pathways and components repre-
senting all domains of life24,25,49. ORF counts were normalized using Reads Per Kilobase per Million mapped
reads (RPKM). Still, it is important to note that given dierent cell counts, read depth and coverage vary among
samples. Here focus was placed on pathways responsible for nitrogen, sulfur and methane metabolism and detox
pathways. Data was visualized in R 3.5.350, with ggplot251.
Data availability
All genomic data is available from the NCBI Sequence Read Archive under BioProject #PRJNA783029 (https://
www. ncbi. nlm. nih. gov/ biopr oject/? term= PRJNA 783029).
Received: 11 December 2021; Accepted: 23 March 2022
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Scientic Reports | (2022) 12:7376 | https://doi.org/10.1038/s41598-022-10876-8
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Acknowledgements
is work was supported by the TAWANI Foundation, the Trottier Family Foundation, NASA’s Exobiology
program (80NSSC18K1094) and the Arctic and Antarctic Research Institute/Russian Antarctic Expedition.
Logistical support was provided by the Antarctic Logistics Centre International, Cape Town, South Africa. We
are grateful to Colonel (IL) J. N. Pritzker, IL ARNG (retired), Lorne Trottier, and fellow eld team members for
their support during the expedition.
Author contributions
N.Y.W. and D.T.A. completed eld work, N.Y.W. conducted lab work, N.Y.W. and A.S.H. analyzed the data,
and S.S.J. supervised the research. N.Y.W., with assistance from A.S.H., D.T.A. and S.S.J., wrote the manuscript.
Competing interests
e authors declare no competing interests.
Additional information
Supplementary Information e online version contains supplementary material available at https:// doi. org/
10. 1038/ s41598- 022- 10876-8.
Correspondence and requests for materials should be addressed to S.S.J.
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