bioRxiv preprint doi: https://doi.org/10.1101/776849; this version posted September 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
1 Carbon Assimilation Strategies in Ultrabasic Groundwater: Clues from the Integrated
2 Study of a Serpentinization-Influenced Aquifer
3
4 L.M. Seyler, W.J. Brazelton, C. McLean, L.I. Putman, A. Hyer, M.D.Y. Kubo, T. Hoehler, D.
5 Cardace, M.O. Schrenk
6
7 Abstract
8 Serpentinization is a low-temperature metamorphic process by which ultramafic rock
9 chemically reacts with water. These reactions provide energy and materials that may be
10 harnessed by chemosynthetic microbial communities at hydrothermal springs and in the
11 subsurface. However, the biogeochemistry of microbial populations that inhabit these
12 environments are understudied and are complicated by overlapping biotic and abiotic processes.
13 We applied metagenomics, metatranscriptomics, and untargeted metabolomics techniques to
14 environmental samples taken from the Coast Range Ophiolite Microbial Observatory (CROMO),
15 a subsurface observatory consisting of twelve wells drilled into the ultramafic and serpentinite
16 mélange of the Coast Range Ophiolite in California. Using a combination of DNA and RNA
17 sequence data and mass spectrometry data, we determined that several carbon assimilation
18 strategies, including the Calvin-Benson-Bassham cycle, the reverse tricarboxylic acid cycle, the
19 reductive acetyl-CoA pathway, and methylotrophy are used by the microbial communities
20 inhabiting the serpentinite-hosted aquifer. Our data also suggests that the microbial inhabitants of
21 CROMO use products of the serpentinization process, including methane and formate, as carbon
22 sources in a hyperalkaline environment where dissolved inorganic carbon is unavailable.
23 bioRxiv preprint doi: https://doi.org/10.1101/776849; this version posted September 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
24 Importance
25 This study describes the metabolic pathways by which microbial communities in a
26 serpentinite-influenced aquifer may produce biomass from the products of serpentinization.
27 Serpentinization is a widespread geochemical process, taking place over large regions of the
28 seafloor, particularly in slow-spreading mid ocean ridge and subduction zone environments. The
29 serpentinization process is implicated in the origin of life on Earth and as a possible environment
30 for the discovery of life on other worlds in our solar system. Because of the difficulty in
31 delineating abiotic and biotic processes in these environments, major questions remain related to
32 microbial contributions to the carbon cycle and physiological adaptation to serpentinite habitats.
33 This research explores multiple mechanisms of carbon assimilation in serpentinite-hosted
34 microbial communities.
35
36 Introduction
37 Serpentinization is the process by which ultramafic rock in the lower crust and upper
38 mantle of the Earth is hydrated, leading to the oxidation of ferrous iron in the minerals olivine
- 39 and pyroxene, and the release of hydrogen (H2) and hydroxyl ions (OH ). The reducing power
40 supplied by serpentinization, when mixed with oxidants from surface and subsurface fluids,
41 creates chemical disequilibria that microbial populations can harness (McCollom, 2007; Amend
42 et al., 2011; Cardace et al., 2015). However, due to the release of cations during rock weathering
43 much of the dissolved inorganic carbon (DIC) in serpentinite systems is precipitated as calcite
44 and aragonite (Barnes et al., 1978). Consequently, small carbon-bearing compounds including
45 methane, carbon monoxide, and formate can take on important roles in sustaining microbial
46 ecosystems in serpentinites. The high pH and limited availability of both DIC and electron bioRxiv preprint doi: https://doi.org/10.1101/776849; this version posted September 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
47 acceptors creates a challenging environment for microbial communities hosted in
48 serpentinization-influenced environments (Twing et al. 2017).
49 Overlapping biogenic and abiogenic processes in serpentinizing rocks make it difficult to
50 delineate carbon cycling pathways used in these environments (Figure 1). Under highly reducing
51 conditions, in the presence of specific mineral catalysts, hydrogen reacts with carbon dioxide
52 (CO2) or carbon monoxide (CO) to form methane (CH4) and small-chain hydrocarbons via
53 Fischer-Tropsch type reactions (McCollom and Seewald, 2001; Charlou et al., 2002;
54 Proskurowski et al., 2008; McCollom, 2013). These same compounds may also be formed by
55 biological activity, or diagenesis of organic matter (Sephton and Hazen, 2013). For example,
56 high concentrations of dissolved organic material, produced by past microbiological activity that
57 may have been supported by the by-products of serpentinization, have been detected in close
58 association with serpentine-hosted hydrogarnets recovered from the Mid-Atlantic Ridge (Ménez
59 et al., 2012). Acetate in endmember fluids at Lost City is also likely produced by biological
60 activity (Lang et al., 2010), but other hydrocarbons in the rock-hosted fluids do not have a clear
+ 61 biotic or abiotic source (Delacour et al., 2008), though formate and C2 alkanes appear to be
62 produced abiotically (Proskurowski et al., 2008; Lang et al., 2010). Biotic versus abiotic sources
63 of methane in serpentinizing systems are likewise difficult to resolve and vary from site to site
64 (Bradley and Summons, 2010; Etiope et al., 2013; Wang et al., 2015; Kohl et al., 2016).
65 In situ microbial communities may utilize the products of serpentinization - including
66 methane, carbon monoxide, formate, and acetate - as sources of carbon (Schrenk et al., 2004;
67 Lang et al., 2010; Brazelton et al., 2011; Brazelton et al., 2012; Lang et al., 2012; Brazelton et
68 al., 2013; Crespo-Medina et al., 2014). Microbial communities in serpentinite springs in the
69 Voltri Massif, Italy, appear to perform both aerobic methanotrophy and methanogenesis using bioRxiv preprint doi: https://doi.org/10.1101/776849; this version posted September 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
70 CO2 liberated from acetate (Brazelton et al., 2017). Methanogens in The Cedars, CA, are capable
71 of producing methane from both inorganic carbon and a variety of organic carbon substrates:
72 acetate may be produced through fermentation (Kohl et al., 2016), and communities that reside
73 deeper in the springs also possess a reductive acetyl-CoA pathway for autotrophic acetogenesis
74 (Suzuki et al., 2017). Carbon monoxide may also be used as a substrate by microbial
75 communities in the Tablelands, Canada, but it appears to be primarily used as a source of energy
76 rather than carbon (Morrill et al., 2014). The carbonate chimneys of the Lost City Hydrothermal
77 Field are dominated by a single species of archaea that may be capable of both production and
78 consumption of methane in tandem (Brazelton et al., 2011). Genes encoding NAD(+)-dependent
79 formate dehydrogenase in metagenomes recovered from the Samail Ophiolite aquifer suggest
80 that formate is an important source of carbon in these DIC-limited hyperalkaline waters (Fones et
81 al., 2019). In short, carbon assimilation in these environments is both enigmatic to researchers
82 and challenging for in situ microbial communities, but pathways and strategies utilizing alternate
83 sources of carbon supplied by serpentinization appear to be prevalent.
84 In this study, we examined the microbial metabolic potential and biogeochemistry of a
85 serpentinization-influenced aquifer in the Coast Range Ophiolite Microbial Observatory
86 (CROMO), California. Wells have been drilled at various depths and locations at CROMO such
87 that microbial processes can be explored across a wide range of physical and chemical
88 conditions. Carbon assimilation pathways in the microbial communities at CROMO were
89 investigated using a combination of metagenomic, metatranscriptomic, and metabolomic
90 approaches. Metagenomic data sets from nine of the twelve CROMO wells, and
91 metatranscriptomic data sets from four wells, obtained over multiple sampling trips, were
92 queried for complete pathways and individual genes associated with carbon assimilation. We bioRxiv preprint doi: https://doi.org/10.1101/776849; this version posted September 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
93 then applied environmental metabolomics, an emerging approach used to directly assess the
94 products of ecosystem activity, on intra- and extracellular extracts from the two most alkaline
95 wells (CSW1.1 and QV1.1) to describe the dissolved organic carbon pools in these wells. This
96 study links the genetic potential of serpentinite-hosted communities to the observed
97 biogeochemistry of the groundwater in CROMO.
98
99 Materials and Methods
100 Site Description
101 The Coast Range Ophiolite in northern California is a 155–170 million-year-old portion
102 of oceanic crust tectonically emplaced on the North American continental margin. Trapped
103 Cretaceous seawater and circulating meteoric water reacts with ultramafic rock (Peters, 1993;
104 Shervais et al., 2005) as evidenced by numerous calcium hydroxide rich springs throughout the
105 formation (Barnes and O’Neil, 1971). Previous studies of continental serpentinite environments
106 have sampled similar springs in the Tablelands, Newfoundland, Canada (Brazelton et al., 2012;
107 Brazelton et al., 2013) and The Cedars, California (Suzuki et al., 2013), providing information on
108 the surface expression of subsurface biogeochemical processes. In order to directly access the
109 serpentinite subsurface environment and monitor groundwater biogeochemistry with minimal
110 contamination, a microbial observatory was established in the Coast Range Ophiolite at the UC-
111 Davis McLaughlin Natural Reserve (Lower Lake, CA) (Cardace et al., 2013). The Coast Range
112 Ophiolite Microbial Observatory (CROMO) consists of two sets of wells 1.4 km apart—the
113 Quarry Valley (QV) and Core Shed Wells (CSW)—each with an uncased main borehole
114 (designated “1.1”) surrounded by two or four monitoring wells, respectively. In addition to the
115 eight newly drilled wells, monitoring wells (N08A, N08B, and N08C at Quarry Valley, and bioRxiv preprint doi: https://doi.org/10.1101/776849; this version posted September 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
116 CSWold) were previously drilled by the Homestake Mining Company, Inc. more than 30 years
117 prior, in conjunction with mining operations conducted in the area. All of the wells are cased
118 with PVC, with the exception of the 1.1 wells which are only cased to bedrock, leaving the
119 bottom of the hole uncased.
120
121 Extraction of DNA and RNA
122 For each environmental sample from the CROMO wells, four liters of fluid were pumped
123 via slow flow bladder pump (Cardace et al., 2013) and immediately filtered through Sterivex 0.2
124 µm filter cartridges (Millipore, Billerica, MA) using a portable peristaltic pump (Masterflex®,
125 Cole Parmer, Vernon Hills, IL). Cartridges were kept on ice during filtration, immediately stored
126 in liquid nitrogen upon completion, shipped to the home laboratory, and stored at -80℃ until
127 processing. Total genomic DNA extractions were completed as previously described by
128 Brazelton et al., (2017), Crespo-Medina et al., (2017) and Twing et al., (2017) and briefly
129 described here. Freeze/thaw cycles and lysozyme/Proteinase K treatment were performed to lyse
130 cells, followed by purification with phenol-chloroform, precipitation using ethanol, and
131 purification using QiaAmp (Qiagen, Hilden, Germany) columns according to the manufacturer's
132 instructions. A Qubit 2.0 fluorometer (ThermoFisher, Waltham, MA) was used to quantify
133 extracted DNA using a Qubit dsDNA High Sensitivity Assay kit.
134 Extractions for RNA from CROMO wells were performed as described previously with
135 slight modifications (Lin and Stahl, 1995; MacGregor et al., 1997). Briefly, frozen 0.2 µm
136 Sterivex filter cartridges were broken open, cut into four equal pieces, and divided into two
137 screw-cap Eppendorf tubes containing phenol, 20% sodium dodecyl sulfate, 5× low-pH buffer,
138 and 0.2 to 0.5 g baked zirconium beads. Samples were bead-beaten for 3 minutes, heated in a bioRxiv preprint doi: https://doi.org/10.1101/776849; this version posted September 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
139 60°C water bath for 10 minutes, bead beaten again for 3 minutes, and centrifuged at 4°C and
140 18,407 × g to separate phases. Supernatant was transferred to a fresh Eppendorf tube and chilled.
141 1× low-pH buffer was added to the remaining sample, and bead-beating was repeated.
142 Supernatants were combined, and phenol, 1:1 phenol:chloroform, and chloroform were added in
143 series with vortexing and centrifugation in between. Between steps, aqueous phases were
144 transferred to clean Eppendorf tubes. The final aqueous phase was transferred to a clean
145 Eppendorf tube with additions of ammonium acetate, isopropanol, and magnesium chloride
146 before vortexing and incubation at -20°C overnight. Samples were centrifuged for 30 minutes at
147 4°C, washed with ethanol, and dried under vacuum before suspension in RNase-free water and
148 storage at -80°C until analyzed.
149
150 Metagenome and Metatranscriptome Analyses
151 This study reports a new analysis of the metagenome and metatranscriptome sequences
152 reported in Sabuda et al. (in review). Our metagenomic assembly and mapping of
153 metatranscriptome reads was identical to that of Sabuda et al., and all methods are reported again
154 here for completeness. Metagenome and metatranscriptome sequencing was conducted at the
155 Joint Genome Institute (JGI) on an Illumina HiSeq2000 instrument. A Covaris LE220
156 ultrasonicator was used to shear DNA samples into 270 bp fragments, and size selection was
157 performed using solid phase reversible immobilization (SPRI) magnetic beads (Rohland and
158 Reich, 2012). DNA fragments were end-repaired, A-tailed, and ligated with Illumina-compatible
159 adapters with barcodes unique for each library. KAPA Biosystem’s next-generation sequencing
160 library qPCR kit and Roche LightCycler 280 RT PCR instrument were used to quantify libraries.
161 10-library pools were assembled and prepared for Illumina sequencing in one lane each. bioRxiv preprint doi: https://doi.org/10.1101/776849; this version posted September 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
162 Clustered flowcells were produced using a TruSeq paired-end cluster kit (v3) and Illumina’s
163 cBot instrument. The Illumina HiSeq2000 instrument was utilized with a TruSeq SBS
164 sequencing kit (v3) and a 2 × 150 indexed run recipe to sequence the samples. The raw sequence
165 reads were trimmed by the JGI with a minimum quality score cutoff of 10 and to remove
166 adapters. These trimmed reads from CROMO wells were previously reported by Twing et al.,
167 2017, but additional quality-filtering and a new assembly, distinct from the JGI assembly
168 reported by Twing et al., was performed for this study.
169 The trimmed reads from the JGI were subjected to an additional quality screen to trim 3'
170 adapters with cutadapt v. 1.15 (Martin, 2011), to remove replicate sequences, and to trim
171 sequences again with a threshold of 20 along a sliding window of 6 bases with qtrim (part of the
172 seq-qc package: https://github.com/Brazelton-Lab/seq-qc). All CROMO metagenomes and
173 metatranscriptomes were pooled together for a master CROMO assembly computed with Ray
174 Meta v.2.3.1 (Boisvert et al., 2012). Phylogenetic affiliation of contigs was assigned using
175 PhyloPythiaS+ (Gregor et al., 2016). Metagenome and metatranscriptome short reads were
176 mapped to the pooled assembly using Bowtie2 v.2.2.6 (Langmead and Salzberg, 2013). The
177 Prokka pipeline (Seemann, 2014) was used for gene prediction and functional annotation of
178 contigs. The arguments –metagenome and –proteins were used with Prokka v.1.12 to indicate
179 that genes should be predicted with the implementation of Prodigal v.2.6.2 (Hyatt et al., 2010)
180 optimized for metagenomes as described by Twing et al., 2017. Metagenome-assembled genome
181 (MAG) bins were constructed with ABAWACA (https://github.com/CK7/abawaca) using
182 tetranucleotide frequencies and differential abundance as measured by Bowtie2 mapped read
183 abundances. Bin quality was computed with CheckM (Parks et al., 2015), and only "high
184 quality" MAG bins are reported here (>50% completeness, <10% contamination, as defined by bioRxiv preprint doi: https://doi.org/10.1101/776849; this version posted September 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
185 Bowers et al., 2017). The completeness and contamination of some bins were improved by
186 refinement with Binsanity (Graham et al., 2017). Taxonomic classifications of MAGs were
187 annotated using GTDB-Tk (https://github.com/Ecogenomics/GTDBTk; Parks et al., 2018).
188 Predicted protein-coding sequences were annotated by searching the Kyoto Encyclopedia
189 of Genes and Genomes (KEGG; Ogata et al., 1999; Kanehisa and Goto, 2000) release v. 83.2
190 within Prokka. HTSeq v.0.6.1 (Anders et al., 2015) and were used to calculate predicted protein
191 abundances. The abundances of predicted protein functions in all CROMO metagenomes and
192 metatranscriptomes were normalized to predicted protein size and metagenome size. Data
193 reported here are in units of metagenome fragments per kilobase of predicted protein sequence
194 per million mapped reads (FPKM). Abundances of metabolic pathways were obtained by
195 mapping KEGG protein IDs and their normalized counts onto the FOAM ontology (Prestat et al.,
196 2014) with MinPath (Ye & Doak, 2009) as implemented in HUMAnN2 v.0.6.0 (Abubucker et
197 al., 2012).
198 The complete translated genome assemblies of Serpentinomonas isolates from the Cedars
199 (Comamonadaceae bacterium A1, B1, and H1) were obtained as amino acid FASTA files from
200 RefSeq (accession numbers: GCF_000828895.1, GCF_000828915.1, GCF_000696225.1). ORFs
201 were annotated as KEGG orthologs (KOs) using BlastKOALA (Kanehisa and Goto 2000).
202 KEGG modules were annotated within genomes using the KEGG module reconstruction tool.
203 MAGs were translated to protein sequences using Prodigal (Hyatt et al., 2010) and annotated in
204 the same manner. Modules within the three cultured representative genomes and the MAGs were
205 then directly compared in order to compare pathways identified in available cultivars from the
206 Cedars to pathways in the uncultured communities hosted in CROMO’s hyperalkaline bioRxiv preprint doi: https://doi.org/10.1101/776849; this version posted September 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
207 groundwater. A phylogenetic tree comparing MAGs to the Serpentinomonas isolates was
208 generated using SpeciesTree in KBase (Arkin et al., 2018).
209
210 Metabolite Extraction and Analysis
211 Three 4-L samples of groundwater from QV1.1 and CSW1.1 were taken in June 2016
212 and filtered using 0.22 µm 47 mm polytetrafluoroethylene (PTFE) filters on a glass vacuum
213 filtration tower. Filters were frozen in liquid nitrogen and stored at -80° C until extraction (Fiore
214 et al., 2015; Kido Soule et al., 2015). Approximately 30 mL filtrate was set aside and frozen at -
215 20 °C for total organic carbon analysis on a Shimadzu Total Organic Carbon Analyzer.
216 Formaldehyde was measured using a CHEMetricsTM Vacu-vialsTM colorimetric kit (detection
217 range 0.4-8.0 ppm). The remaining filtrate was acidified to pH 2-3 using concentrated HCl and
218 stored at 4°C for 5 days until further analysis by solid phase extraction.
219 Frozen filters were cut into small pieces over a muffled piece of aluminum foil, using
220 methanol-washed scissors, then transferred into muffled amber glass vials. 2 mL cold extraction
221 solvent (40:40:20 acetonitrile:methanol:0.1 M formic acid) was added to each vial, and the
222 samples were sonicated for 10 minutes. Extracts were transferred to a centrifuge tube via pipette
223 and centrifuged at 20,000 × g for 5 min at 4 °C. The supernatant was then transferred to a new
224 amber glass vial, neutralized with 6 M ammonium hydroxide, and vacuum centrifuged to
225 dryness. Samples were dissolved in 495 µl 95:5 water:acetonitrile with 5 µl of 5 µg/ml of biotin-
226 (ring-6,6-d2) added as an injection standard (Rabinowitz and Kimball, 2007; Fiore et al., 2015).
227 Dissolved organics were captured from the acidified filtrate on solid phase extraction
228 (SPE) Bond Elut-PPL cartridges (Agilent Technologies) and eluted with 100% methanol into
229 muffled amber glass vials (Dittmar et al., 2008; Fiore et al., 2015). SPE-PPL cartridges were bioRxiv preprint doi: https://doi.org/10.1101/776849; this version posted September 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
230 rinsed with methanol immediately before use. The supernatant was passed through the cartridge
231 using 1/8" × 1/4" PTFE tubing to pull the supernatant into the cartridge to minimize the
232 possibility of contamination from plastic leaching, while Viton tubing was used to remove the
233 discarded flow-through via peristaltic pump (flow rate not exceeding 40 ml/min). The cartridges
234 were then rinsed with at least 2 cartridge volumes of 0.01 M HCl to remove salt, and the sorbent
235 dried with air for 5 minutes. Dissolved Organic Matter (DOM) was eluted from the cartridge
236 with 2 ml methanol via gravity flow into a muffled amber glass vial. The eluate was then vacuum
237 centrifuged to dryness. Precipitated samples were dissolved in 495 µl 95:5 water:acetonitrile,
238 with 5 µl of 5 µg/ml of biotin-(ring-6,6-d2).
239 The above protocol was repeated for 4 L milliQ water, and organics extracted from the
240 filter and filtrate as above as extraction blanks. 495 µl 95:5 water:acetonitrile plus 5 µl 5 µg/mL
241 biotin-(ring-6,6-d2) was also run as a blank.
242 Samples were analyzed using tandem liquid chromatography mass spectrometry
243 (LC/MS/MS) at the Michigan State University Metabolomics Core facility. Triplicate samples
244 from each well were separated chromatographically in a Acquity UPLC BEH C18 column (1.7
245 µm, 2.1 mm × 50 mm) using a polar/non-polar gradient made up of 10 mM TBA and 15 mM
246 acetic acid in 97:3 water:methanol (solvent A), and 100% methanol (solvent B). The gradient
247 was run at 99.9/0.1 (% A/B) to 1.0/99.0 (% A/B) over 9 min, held an additional 3 min at 1.0/99.0
248 (% A/B), then reversed to 99.9/0.1 (% A/B) and held another 3 min. At a rate of 400µL/min, the
249 sample was fed into a quadrupole time-of-flight mass spectrometer using a Waters Xevo G2-XS
250 MS/MS in negative ion mode using a data independent collection method (m/z acquisition range
251 50 to 1500 Da). OM levels were too low to allow distinction between samples and blanks from
252 the first run, so triplicate samples were pooled and run as before. After data was converted to bioRxiv preprint doi: https://doi.org/10.1101/776849; this version posted September 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
253 centroid mode, raw data files were converted from proprietary Waters RAW format into XML-
254 based mzML format using MSConvert (Chambers et al, 2012). Data was processed using XCMS
255 (Smith et al., 2006) parametrized by AutoTuner (McLean and Kujawinski, in review). Isotopes
256 and adducts of each feature were identified using CAMERA (Kuhl et al., 2012). This approach
257 yielded a table of peak areas that are identified by a unique mass to charge (m/z) and retention
258 time (rt) pair referred to as features. The table of features was subject to quality assurance
259 through blank correction by removing any feature from a sample that also appeared within the
260 blank control (described above) (Broadhurst et al., 2018). Features were first putatively
261 annotated as KEGG compounds using mummichog (Li et al., 2013). Chemical standards of
262 putative annotations were purchased whenever available to check the retention time to increase
263 confidence of annotation from level 1 to 2 (Sumner et al. 2007). Due to the great complexity of
264 the secondary mass spectral data and insufficient coverage of mass spectral databases for natural
265 organic matter, MS2 information could not be readily used to increase confidence of annotation.
266
267 Data Availability
268 CROMO metagenome and metatranscriptome sequences are publicly available in the NCBI SRA
269 with the BioProject IDs PRJNA410019, PRJNA410020, PRJNA410022-410033,
270 PRJNA410035-410037, PRJNA410054, PRJNA410057, PRJNA410286, PRJNA410403,
271 PRJNA410404, PRJNA410553-410555, PRJNA410557. Raw spectrometry data are available in
272 the MetaboLights database under study identifier MTBLS1260.
273
274 Results
275 Presence and Expression of Carbon Assimilation Pathways bioRxiv preprint doi: https://doi.org/10.1101/776849; this version posted September 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
276 The metagenomic data collected from nine of the twelve CROMO wells contains
277 evidence for a range of carbon fixation/assimilation pathways (Figure 2). Functional profiling of
278 the metagenomes using HUMAnN2 identified multiple C1 compound utilization and
279 assimilation pathways, including the reductive acetyl-CoA (Wood-Ljungdahl) pathway, the
280 reverse tricarboxylic acid (TCA) cycle, formaldehyde oxidation to formate, and formaldehyde
281 fixation to biomass. Whenever these complete pathways were identified in the metagenomic
282 data, they were also detected in the corresponding metatranscriptomic data (Figure 2). A
283 complete Calvin-Benson-Bassham cycle was also detected in all nine metagenomes and all four
284 metatranscriptomes, at a similar coverage across wells (Supplemental Figure 1). Carbon fixation
285 pathways found exclusively in archaea (i.e., hydroxypropionate-hydroxybutylate cycle, 3-
286 hydroxypropionate bicycle) were not detected. MAG bins contained the reductive pentose
287 phosphate/Calvin-Benson-Bassham cycle, reductive TCA cycle, and reductive acetyl-CoA
288 pathways (Figure 3).
289 Several pathways associated with methanotrophy and methylotrophy were detected in the
290 metagenomes and metatranscriptomes. The pathway for aerobic methane oxidation to
291 formaldehyde was present in most of the metagenomes (Figure 4) and the complete pathway was
292 actively transcribed in wells QV1.2 and N08B. Formaldehyde uptake and assimilation pathways
293 were prevalent in all of the sequenced wells (Figure 2). Complete glutathione-dependent and
294 tetrahydrofolate (THF) pathways for formaldehyde oxidation to formate were present in all of
295 the metagenomes, expressed in all four metatranscriptomes (Figure 2, Figure 4), and present in
296 multiple MAGs (Figure 3). (The gfa gene, which codes for an enzyme that catalyzes a
297 thermodynamically spontaneous step in the glutathione-dependent pathway [Goenrich et al.,
298 2002], is only found in some formaldehyde-oxidizing bacteria and was absent from most of the bioRxiv preprint doi: https://doi.org/10.1101/776849; this version posted September 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
299 metagenomes.) Formaldehyde fixation via the tetrahydromethanopterin (H4MPT) pathway was
300 poorly represented across the metagenomes, but was expressed in the metatranscriptomes of
301 QV1.2 and N08B. The capability for formaldehyde fixation to biomass by the ribulose
302 monophosphate (RuMP) and serine pathways was likewise present in all nine metagenomes and
303 all four metatranscriptomes (Figure 2), and the RuMP pathway was partially complete in 18
304 MAGs and complete in one MAG (Figure 3).
305 Pathway identification using the KEGG database and FOAM pathways suggested that
306 homoacetogenesis via the reductive acetyl-CoA pathway (also known as the Wood-Ljungdahl
307 pathway) was represented in the metagenomes of only half of the wells sequenced (N08A,
308 N08B, QV1.2, CSW1.1, and CSWold) (Figure 2). However, a gene-by-gene search indicated
309 that the pathway was also present and nearly complete in the QV1.1 and CSW1.3 wells (Figure
310 5; Supplemental Tables 1 and 2). In the three least alkaline wells (CSW1.4, N08C, and QV1.2),
311 most of the genes in the pathway were poorly represented (< 2 FPKM) in the metagenomic data.
312 Metatranscriptomic data showed that the pathway was actively transcribed in all of the four wells
313 that were sampled for mRNA (Figure 2; Figure 5). However, one of the initial steps of the
314 reductive acetyl-CoA pathway, the conversion of CO2 to formate by NADP-dependent formate
315 dehydrogenase (FDH), appeared to be poorly expressed or altogether missing in both the
316 metagenomes and the metatranscriptomes (Figure 5). Seven of the 66 MAG bins also contained a
317 nearly complete reductive acetyl-CoA pathway that was missing the genes encoding FDH
318 (Figure 3, inset). The type I pathway for the formation of acetate from acetyl-CoA via acetyl-
319 phosphate (present in Methanosarcina and Clostridiales) is relatively abundant across all
320 metagenomes, while the type II pathway (which does not utilize an acetyl-phosphate
321 intermediate) is sparsely represented in the metagenomic data (Figure 2). bioRxiv preprint doi: https://doi.org/10.1101/776849; this version posted September 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
322
323 Taxonomy
324 Taxonomic assignments of the metagenomic contigs using PhyloPythiaS+ were
325 consistent with previous 16S rRNA sequencing data from the CROMO wells (Twing et al.,
326 2017) and showed that the microbial communities in QV1.1 and CSW1.1 (the two most alkaline
327 wells) were highly similar (Supplemental Figure 3). Taxonomic classification of MAG bins,
328 including bin completeness, contamination, and strain heterogeneity, is available in Table 1; a
329 phylogenetic tree comparing the MAGs to the three Serpentinomonas isolates is included in
330 Figure 3.
331 In the metagenomes, pmoA and mxaF genes from the methane oxidation pathway were
332 detected on contigs classified as Methylophilales (Methylophilaceae) and Methylococcales
333 (Methylococcaceae); two MAG bins containing a complete methane oxidation pathway were
334 classified as Methylococcaceae (Figure 3; Table 1). Genes from the THF pathway for
335 formaldehyde oxidation (folD and purU) were associated with Burkholderiales
336 (Comamonadaceae), Deinococcales (Trueperaceae), Hydrogenophilales (Hydrogenophilaceae),
337 Methylophilales (Methylophilaceae), Rhizobiales, and Rhodocyclales (Rhodocyclaceae); the
338 frmA gene from the glutathione pathway for formaldehyde oxidation was detected on contigs
339 identified as Burkholderiales (Comamonadaceae), Rhizobiales, Rhodobacterales, and
340 Rhodocyclales (Rhodocyclaceae). The folD gene is also present in the reductive acetyl-CoA
341 pathway for acetogenesis; this gene, as well as acsB and cooS were associated with Clostridiales
342 (Syntrophomodaceae) and Desulfuromodales. All of the MAG bins containing the reductive
343 acetyl-CoA pathway were classified as Clostridiales (Figure 3; Table 1). The large and small
344 subunits of RuBisCO (rbcL and rbcS) were detected on contigs classified as Burkholderiales bioRxiv preprint doi: https://doi.org/10.1101/776849; this version posted September 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
345 (Comamonadaceae), Hydrogenophilales (Hydrogenophilaceae), Rhodocyclales
346 (Rhodocyclaceae), and Methylophilales (Methylophilaceae). A complete CBB cycle was only
347 identified on one MAG, however, classified as Rhodocyclales (Rhodocyclaceae). The aclA gene
348 from the reverse TCA cycle was associated with Clostridiales (Syntrophomodaceae) in the
349 metagenomes.
350
351 Metabolomics
352 The metabolomes of QV1.1 and CSW1.1 displayed many unique observed features
353 across both sample types (intracellular metabolites and extracellular metabolites/dissolved
354 organic carbon [DOC]). In particular, the DOC pools of QV1.1 and CSW1.1 were highly distinct
355 from one another and from intracellular extracts, and these metabolomes contained the greatest
356 number of features unique to the sample (Figure 6). Metabolomes also had more features in
357 common between samples of the same type (e.g., intracellular vs. extracellular) than samples
358 from the same well (Figure 6). Dissolved inorganic carbon concentration in the wells was
359 inversely proportional to pH (Pearson correlation coefficient, r = -0.798), while non-purgeable
360 organic carbon was positively correlated to dissolved oxygen concentration (r = 0.587) (Figure
361 7). All wells were below the detection limits of the colorimetric formaldehyde test kit (<0.4
362 ppm).
363
364 Discussion
365 Previous studies of microbial communities at CROMO have used marker gene analysis,
366 shotgun metagenomics, microcosm experiments, and geochemical measurements to elucidate
367 pathways of biogeochemical cycling in a serpentinite-hosted aquifer (Crespo-Medina et al., bioRxiv preprint doi: https://doi.org/10.1101/776849; this version posted September 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
368 2014; Twing et al., 2017). We expanded upon these efforts by combining metagenomics and
369 metatranscriptomics with an untargeted metabolomics technique to verify genomic expression
370 and metabolic activity. Using this integrated –omics approach, we determined that multiple
371 carbon assimilation pathways are used by the microbial communities in the serpentinite-hosted
372 groundwater at CROMO, including the Calvin-Benson-Bassham cycle, the reverse TCA cycle,
373 acetogenesis via the reductive acetyl-CoA pathway, and methanotrophy.
374
375 Methane Uptake and Formaldehyde Cycling
376 The addition of methane to microcosms from CROMO has been shown to stimulate
377 microbial growth (Crespo-Medina et al., 2014). In the previous metagenomic study of 4 samples
378 by Twing et al. (2017), no particulate methane monooxygenase (pmoA) genes were detected;
379 however, a methanol dehydrogenase (mxaF) gene was identified in the CSW1.3 metagenome.
380 Our expanded search through nine metagenomes and four metatranscriptomes succeeding in
381 finding the genes for particulate methane monooxygenase (PMO) and methanol dehydrogenase
382 (MXA) in the CROMO microbial communities, though at low abundance in the higher pH wells
383 (Figure 4), suggesting that the prior perceived absence of these genes could have been the result
384 of a smaller dataset. Two MAG bins contain the complete methane oxidation pathway, and
385 another two contain a partial pathway (Figure 3). No other known methane monooxygenases or
386 methanol dehydrogenases were identified in the metagenomes or metatranscriptomes.
387 The prevalence of formaldehyde- and formate-assimilation pathways in CROMO
388 reinforces the importance of methanotrophy as a carbon assimilation strategy in these microbial
389 communities. There is a wealth of metagenomic and metatranscriptomic evidence that
390 formaldehyde oxidation to formate and formaldehyde fixation to biomass can be performed by bioRxiv preprint doi: https://doi.org/10.1101/776849; this version posted September 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
391 the microbial communities in CROMO (Figure 2). Formaldehyde is an important intermediate in
392 methylotrophic metabolic pathways, and though it is highly toxic, methylotrophic
393 microorganisms have developed a variety of functionally redundant modules for rapidly
394 converting formaldehyde to less toxic compounds (Marx et al., 2005). Formaldehyde can also act
395 as a carbon and electron shuttle between microbial subpopulations, in which it is produced by
396 autotrophic primary producers as a by-product, then taken up by methylotrophic microbes and
397 incorporated into biomass (Moran et al., 2016).
398 In methanotrophs, formate oxidation to CO2 is carried out by the NADP-dependent
399 formate dehydrogenase that converts CO2 to formate in the Wood-Ljungdahl pathway, operating
400 in reverse. As previously stated, the genes for this enzyme were not well-represented (and in
401 some cases missing) in the metagenomic data (Figure 5). Formate can also be oxidized to CO2 by
402 an NAD-dependent formate dehydrogenase (FDH) as part of the degradation of oxalate;
403 however, the complete suite of genes required to produce this enzyme was likewise poorly-
404 represented or partially missing, particularly in the most alkaline wells (Supplemental Figure 2).
405 This contrasts with subsurface wells in the Samail Ophiolite, where FDH encoding genes were
406 enriched in metagenomes recovered from alkaline and hyperalkaline groundwater (Fones et al.,
407 2019). Therefore, while there is substantial metagenomic and metatranscriptomic evidence for
408 the production of formate from formaldehyde by the microbial communities in CROMO,
409 DNA/RNA evidence for the further oxidation of formate to CO2 is lacking.
410
411 Bicarbonate Fixation Strategies in the Metagenomes and Metatranscriptomes
412 Despite the DIC concentrations being challengingly low for CO2 fixation at the high pH
413 of the deepest wells, we found complete Calvin-Benson-Bassham (CBB; Supplemental Figure 1) bioRxiv preprint doi: https://doi.org/10.1101/776849; this version posted September 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
414 and reverse tricarboxylic acid (rTCA; Figure 2) cycles in all nine of our metagenomes and all
415 four metatranscriptomes. Sequences encoding the rbcL gene of the RuBisCo enzyme were
416 previously detected in metagenomes from four wells (CSW1.1, CSW1.3, QV1.1, and QV1.2) in
417 the earlier metagenomic study by Twing et al. (2017). QV1.1 displays the highest coverage of
418 the rTCA pathway in both its metagenome (607.71±55.83 FPKM) and metatranscriptome
419 (446.86±149.59 FPKM) (Figure 2), even though the concentration of dissolved inorganic carbon
420 (DIC) in QV1.1 is lower than almost any other well (11.48) (conversely, presence/expression of
421 the CBB cycle was roughly equal throughout all the wells [Supplemental Figure 1]). Above pH
422 11, carbonate is the dominant species of inorganic carbon. Serpentinomonas spp., which are
423 among the most abundant taxa in the highest pH wells in CROMO (Twing et al., 2017) require
424 the addition of calcium carbonate (even when bicarbonate is also provided) for growth in culture,
425 and form aggregates on carbonate precipitates (Suzuki et al., 2014). Bicarbonate-fixing microbes
426 may create a localized microenvironment of decreased pH where carbonate may be converted to
427 bicarbonate, or they may have bicarbonate transporters that solubilize carbonate. We did not
428 detect any ATP-binding cassette transporters for bicarbonate in our metagenomic data
429 (Supplemental Table 1). Alternatively, formate may be used as a carbon source in the CBB cycle
430 (Bar-Even, 2016) or in the rTCA cycle (Cotton et al., 2018). Formate could thus be produced
431 from formaldehyde via formaldehyde oxidation and then used in assimilatory/anabolic pathways.
432 Evidence for the reductive acetyl-CoA pathway was also previously detected in several
433 wells (Twing et al., 2017). In this study, we found a nearly complete homoacetogenic reductive
434 acetyl-CoA pathway in the metagenomic and metatranscriptomic data from all but the two least
435 alkaline wells, except for one gene. The gene that encodes the beta subunit of formate
436 dehydrogenase (fdhB), which converts CO2 to formate as the first step of the reductive acetyl- bioRxiv preprint doi: https://doi.org/10.1101/776849; this version posted September 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
437 CoA pathway, represents <1 FPKM in every metagenome but two (N08A and N08B) (Figure 5),
438 and is only present in the metatranscriptomes of QV1.2 and N08B. Likewise, the genes for FDH
439 are missing from every MAG bin that possesses the reductive acetyl-CoA pathway (Figure 3,
440 inset). Yet, this step of the pathway may be unnecessary for the pathway to proceed if formate is
441 being produced by other means, either through the oxidation of formaldehyde via the
442 glutathione-dependent or tetrahydrofolate pathways, or by abiotic production via Fischer-
443 Tropsch-like reactions. Abiotically-produced formate has been implicated as a possible carbon
444 source in serpentinizing environments such as the Lost City (Lang et al., 2010; Lang et al., 2012;
445 Lang et al., 2018) and the Samail Ophiolite (Fones et al. 2019). While formate-fixing reactions
446 are not common, as formate has a relatively low reactivity compared to CO2 or other carboxylic
447 acids (Bar-Even, 2016), formate can be used as the sole carbon source by some microorganisms.
448 In the Samail Ophiolite, rates of assimilation or oxidation of formate were higher than rates of
449 assimilation or dissimilation of bicarbonate or CO regardless of pH (Fones et al., 2019),
450 suggesting that formate may be a preferred source of carbon and/or electrons. Formate
451 concentrations in CROMO are similar to DIC concentrations or lower (Supplemental Table 1;
452 see also Crespo-Medina et al., 2014; Twing et al., 2017), but the addition of formate stimulates
453 microbial growth (Crespo-Medina et al., 2014). We detected two formate transporters in the
454 metagenomic data: fdhC, which has been detected in putative formate-metabolizing bacteria in
455 Lost City chimneys (Lang et al., 2018), was detected in two MAG bins (126 and 192, both
456 Clostridia), and focA was detected in one MAG bin (222_8, Actinobacter) and across multiple
457 metagenomes and all four metatranscriptomes (Supplemental Table 1).
458 As DIC becomes more limiting due to pH, bypassing the conversion of CO2 to formate
459 may be an important strategy for carbon assimilation. Provided that sufficient reductant is bioRxiv preprint doi: https://doi.org/10.1101/776849; this version posted September 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
460 available (for example, from the oxidation of H2), assimilation of CO2, CO, or formate can occur
461 via the reductive acetyl-CoA pathway (Takami et al., 2012). The assimilation of formate via the
462 acetogenic reductive acetyl-CoA pathway avoids ATP consumption, supports energy
463 conservation through the use of multiple electron bifurcation mechanisms, and removes the need
464 for an external electron acceptor apart from co-assimilated CO2 (Bar-Even, 2016; Cotton et al.,
465 2018). While the cooS gene for the conversion of CO2 to CO is present (Figure 5), this step could
466 likely be bypassed as well, in wells where the CO concentration is sufficiently high
467 (Supplemental Table 3). Evidence for carbon monoxide uptake (Morrill et al., 2014) and the
468 reductive acetyl-CoA pathway (Suzuki et al., 2017) as important carbon assimilation pathways
469 was previously found in the Tablelands, Canada, and The Cedars, CA, respectively. In the
470 Samail Ophiolite, Oman, it appears that carbon limitation outweighs energy limitation for the
471 autotrophic members of microbial communities at high pH (Fones et al., 2019), making carbon
472 compounds important as both a feedstock for biosynthesis and a source of electrons.
473 In summary, a putative metabolic pathway for the assimilation of methane into biomass is
474 outlined in Figure 8. Methane oxidation to formaldehyde is carried out by the Methylococcales
475 and Methylophilales, and then either fixed to biomass via the RuMP and serine pathways, or
476 oxidized to formate by multiple clades via the THF and glutathione-dependent pathways.
477 Formate can then be assimilated into biomass via the reductive acetyl-CoA pathway in the
478 Clostridiales or Desulfuromodales, as shown, or through the CBB or rTCA cycles (Bar-Even et
479 al., 2016; Cotton et al., 2018).
480
481 Methanogenesis bioRxiv preprint doi: https://doi.org/10.1101/776849; this version posted September 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
482 While methanogenic archaea have not been detected in 16S rRNA data obtained from
483 CROMO (Twing et al., 2017) and methane isotopologue data suggest a thermogenic source
484 (Wang, 2015), metagenomic and metatranscriptomic evidence suggest the possibility of
485 methanogenesis by multiple pathways in at least some of the wells. However, these pathways do
486 not include the essential backbone of the methanogenesis pathway, including the crucial mcrA
487 gene for the production of coenzymeM, required for making methane. The mcrA gene was
488 expressed in the metatranscriptomes but other key genes for methane production were absent
489 (Supplemental Tables 1 and 2). The apparent presence of pathways for methanogenesis from
490 organic molecules likely indicate the ability to metabolize these organics (e.g. acetate, methanol,
491 etc.), but whether these compounds are converted to methane by methanogens remains unclear.
492 Biological methanogenesis appears to be occurring in other continental serpentinizing sites, such
493 as the Voltri Massif (Brazelton et al., 2017) and the Cedars (Kohl et al., 2016). In the Tablelands,
494 however, no evidence of biological methane production has been detected (Morrill et al., 2014),
495 and methane production genes in metagenomes recovered from the Samail Ophiolite in Oman
496 are likewise sparse (Fones et al., 2019). Methane cycling in ophiolite-hosted microbial
497 communities therefore seems to vary from site to site, and further work will be required to
498 uncover the geochemical conditions that drive its production and uptake.
499
500 Searching the Metabolome for Intermediates
501 Intermediates of formaldehyde oxidation and assimilation pathways did not match the
502 masses and retention times of any of the features in our metabolomics data. In negative ion
503 mode, glutathione derivatives should have appeared in the data as deprotonated or double-
504 negatively charged molecules, but we did not detect masses that matched either of those bioRxiv preprint doi: https://doi.org/10.1101/776849; this version posted September 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
505 possibilities. This may be due to the relatively low concentrations of DOM (3-13 mg/L) (Fiore et
506 al., 2015), as well as bias introduced by our extraction method (Johnson et al., 2017).
507 Tetrahydrofolate compounds would likely have been more easily detected in positive ion mode;
508 however, we ran our samples in negative mode in the hopes of capturing the broadest array of
509 metabolites possible with no preconceived notions of what compounds would be present in the
510 data. Metabolites may also fragment or form non-covalent interactions with other compounds
511 upon entering the mass spectrometer, making identification of particular intermediates
512 challenging (Zamboni et al., 2015). Additionally, low cell counts in alkaline groundwater make it
513 difficult to obtain enough biomass during filtration to accurately depict the entire intracellular
514 metabolome of the microbial community. An ideal target of total carbon would be 0.3 mg (Kido
515 Soule et al., 2015). Assuming each cell contains 30 fg of carbon (Fukuda et al., 1998), and with
516 an average cell count of 2 × 105 cells/ml (Twing et al., 2017; unpublished data), 50 liters of
517 water would need to be filtered. Although CSW1.1 and QV1.1 have high fluid outputs compared
518 to most of the other CROMO wells, filtration limitations such as clogging due to carbonate
519 precipitates, keeping the fluid cold to prevent further chemical alteration of the metabolites, and
520 prevention of contamination all precluded our ability to filter such large amounts of water. We
521 were also unable to detect formaldehyde using colorimetric methods in any of the wells. If
522 formaldehyde and its intermediates are cycled rapidly within the cell, it may be difficult to
523 identify and quantify these compounds with the techniques used in this study. Interestingly,
524 while the two wells with the highest pH (QV1.1 and CSW1.1) share highly similar microbial
525 communities (Supplemental Figure 3) with similar metabolic capabilities, the DOC pools
526 observed in these wells appear significantly different in character (Figure 6). Putative
527 annotations of unique metabolite features in the DOC pools include dipeptides, fatty acids, bioRxiv preprint doi: https://doi.org/10.1101/776849; this version posted September 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
528 vitamins, phosphorylated metabolites, and secondary metabolites. This observation underscores
529 the need for further characterization of the available carbon in serpentinite-hosted aquifers like
530 CROMO through metabolomics techniques.
531
532 Conclusion
533 Through an in-depth analysis of metagenomic and metatranscriptomic data taken over
534 several time points, we have determined that methanotrophy, the reductive acetyl-CoA pathway,
535 the reverse TCA cycle, and the Calvin-Benson-Bassham cycle may all be important means of
536 carbon assimilation for microbes living in the Coast Range Ophiolite groundwater. We also
537 identified several mechanisms by which microbes in the hyperalkaline fluids of deep
538 serpentinizing rock may overcome limiting concentrations of DIC, including the use of formate
539 and methane/formaldehyde as carbon sources for homoacetogenesis and the production of
540 biomass. Further optimization of metabolomics techniques for this environment may be of use to
541 track the fate of carbon and delineate between abiotic and biotic processes in serpentinizing
542 systems such as CROMO.
543
544 Acknowledgements
545 The authors wish to thank McLaughlin Reserve, in particular Paul Aigner and Cathy
546 Koehler, for hosting sampling at CROMO and providing access to the wells, A. Daniel Jones and
547 Anthony Schilmiller for their advice regarding metabolite extraction and mass spectrometry,
548 Elizabeth Kujawinski for her guidance in metabolomics data analysis and interpretation, and
549 Julia McGonigle, Christopher Thornton, and Katrina Twing for assistance with metagenomic and
550 computational analyses. bioRxiv preprint doi: https://doi.org/10.1101/776849; this version posted September 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
551
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814
815 Figure Legends
816
817 Figure 1. A diagram depicting abiotic (white) and biotic (black) sources of carbon compounds in
818 serpentinizing environments. Adapted from Preiner et al., 2018.
819 bioRxiv preprint doi: https://doi.org/10.1101/776849; this version posted September 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
820 Figure 2. Metagenome coverage of Functional Ontology Assignments for Metagenomes
821 (FOAM) pathways assigned using HUMAnN2. If a well was sampled for metagenomics more
822 than once, the average percent coverage and standard error of the mean for that well are
823 provided. Metatranscriptome coverage for four wells sampled for RNA is indicated using bars
824 with dotted outlines.
825
826 Figure 3. Selection of carbon cycling-associated KEGG modules detected in MAG bins, and
827 Serpentinomonas isolate genomes (Suzuki et al., 2014), using BLASTKoala. Dark blue boxes
828 indicate the complete module is present; light blue boxes indicate one step of the pathway is
829 missing. The phylogenetic tree comparing the MAGs to the three Serpentimonas isolates was
830 generated using SpeciesTree in KBase.
831 Inset: Bins containing reductive acetyl-CoA pathway; gene presence in the genome is indicated
832 in yellow.
833
834 Figure 4. Fragments per kilobase of sequences per million mapped reads (FPKM) of genes in the
835 homoacetogenic reductive acetyl-CoA pathway. Metagenomes are represented in black;
836 metatranscriptomes are represented in gray. The genes for the two subunits of formate
837 dehydrogenase (fdhA and fdhB) are missing or comparatively low in most wells. This enzyme is
838 responsible for converting CO2 to formate.
839
840 Figure 5. Fragments per kilobase of sequences per million mapped reads (FPKM) of genes in the
841 methane oxidation, tetrahydrofolate (THF), and glutathione-dependent formaldehyde oxidation
842 pathways. Metagenomes are represented in black; metatranscriptomes are represented in gray. bioRxiv preprint doi: https://doi.org/10.1101/776849; this version posted September 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
843 The gene for S-(hydroxymethyl)glutathione synthase (gfa) is poorly represented or missing in all
844 wells; this enzyme catalyzes a spontaneous reaction in the formaldehyde oxidation pathway.
845
846 Figure 6. Left: Heatmap of untargeted metabolomics features across all four metabolome
847 samples. The scale represents the ln(1 + peak intensity) (1 is added to avoid cases of ln(0)).
848 Right: Venn diagram of compounds unique to each sample and shared between samples.
849 Observed compounds appear to be generally distinct to each sample. Filtered fluid/dissolved
850 organic carbon samples had the greatest number of unique samples, and CSW1.1 had more
851 unique compounds than QV1.1.
852
853 Figure 7. Scatter plots depicting dissolved inorganic carbon (DIC) vs pH (left) and nonpurgeable
854 organic carbon (NPOC) vs dissolved oxygen (DO). The Pearson correlation coefficient (r) is
855 indicated on each graph, as well as the R2 of the trendlines.
856
857 Figure 8. Putative pathway for carbon assimilation in the CROMO wells. Formaldehyde is either
858 converted directly to biomass via the RuMP or serine pathways, or oxidized to formate, which is
859 then fed into the homoacetogenic reductive acetyl-CoA pathway. The pathway for methane
860 conversion to formaldehyde is shown, but appears to be poorly expressed in most of the wells.
861
862 Table 1. Completeness, contamination, strain heterogeneity, and classification of MAG bins
863 from metagenomes. Bin quality scores assessed using CheckM; taxonomic annotations obtained
864 using GTDB-Tk.
865 bioRxiv preprint doi: https://doi.org/10.1101/776849; this version posted September 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
866 Supplemental Figure 1. Fragments per kilobase of sequences per million mapped reads (FPKM)
867 of genes in the Calvin-Benson-Bassham cycle. Metagenomes are represented in black;
868 metatranscriptomes are represented in gray.
869
870 Supplemental Figure 2. Fragments per kilobase of sequences per million mapped reads (FPKM)
871 of genes in the NAD-dependent pathway for formate oxidation to CO2. Metagenomes are
872 represented in black; metatranscriptomes are represented in gray.
873
874 Supplemental Figure 3. Microbial community composition of QV1.1 and CSW1.1 wells as
875 determined by assigning taxonomy to metagenomic contigs using PhyloPython.
876
877
878
879
880
881
882 bioRxiv preprint doi: https://doi.org/10.1101/776849; this version posted September 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
Conta- Strain Complete mina- hetero- MAG -ness tion geneity Domain Phylum Class Order Family Genus Species
Candidatus 83_0_0 73.25 3.56 20 Archaea Thaumarchaeota incertae sedis Nitrosopumilales Nitrosopumilaceae Nitrosoarchaeum Nitrosoarchaeum koreensis
Candidatus 83_3_0 91.75 4.85 100 Archaea Thaumarchaeota incertae sedis Nitrosopumilales Nitrosopumilaceae Nitrosoarchaeum Nitrosoarchaeum koreensis
109_2_0 75.96 0.85 100 Bacteria Actinobacteria Actinobacteria
222_8 97.01 2.56 0 Bacteria Actinobacteria Actinobacteria
152 94.17 1.11 0 Bacteria Actinobacteria Actinobacteria Algoriphagus 58 98.5 3.33 47.37 Bacteria Bacteroidetes Sphingobacteria Sphingobacteriales Cyclobacteriaceae Algoriphagus machipongonensis 11 94.62 5.41 29.41 Bacteria Bacteroidetes Bacteroidia Bacteroidales
82 94.83 4.15 69.23 Bacteria Bacteroidetes Chitinophagia Chitinophagales Chitinophagaceae
49 78.79 7.76 9.09 Bacteria Bacteroidetes Chitinophagia Chitinophagales Chitinophagaceae
74 97.7 6.12 54.17 Bacteria Bacteroidetes Flavobacteriia Flavobacteriales
85_0 96.21 4.08 0 Bacteria Bacteroidetes
64 89.73 4.12 38.46 Bacteria Bacteroidetes
120 85.67 0.26 0 Bacteria Bacteroidetes
117 97.31 5.38 14.29 Bacteria Bacteroidetes
87_3_0 84.08 2.7 20 Bacteria Chlamydiae Chlamydiae Chlamydiales Simkaniaceae Simkania Simkania negevensis 100 98.88 8.45 0 Bacteria Chlorobi Ignavibacteria Ignavibacteriales Ignavibacteriaceae Ignavibacterium Ignavibacterium album
200 84.69 1.12 0 Bacteria Chlorobi Ignavibacteria Ignavibacteriales Melioribacteraceae Melioribacter Melioribacter roseus
84 71.17 1.09 0 Bacteria Chlorobi Ignavibacteria Ignavibacteriales Deinococcus- 191 88.56 5.59 50 Bacteria Thermus Deinococci Deinococcales Trueperaceae Truepera Truepera radiovictrix Deinococcus- 207 59.14 2.33 90 Bacteria Thermus Deinococci Deinococcales Trueperaceae Truepera Truepera radiovictrix 126 51.67 1.4 100 Bacteria Firmicutes Clostridia Clostridiales Clostridiaceae Alkaliphilus
128 94.07 3.11 68.75 Bacteria Firmicutes Clostridia Clostridiales Clostridiaceae Clostridium Clostridiales Family XVII. 61 93.27 6.73 75 Bacteria Firmicutes Clostridia Clostridiales Incertae Sedis Thermaerobacter 245 94.23 0.24 0 Bacteria Firmicutes Clostridia Clostridiales Peptococcaceae
bioRxiv preprint doi: https://doi.org/10.1101/776849; this version posted September 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
236 80.27 0.32 0 Bacteria Firmicutes Clostridia Clostridiales Peptococcaceae
244 54 3.25 100 Bacteria Firmicutes Clostridia Clostridiales Syntrophomonadaceae Dethiobacter Dethiobacter alkaliphilus
105 94.35 4.31 20 Bacteria Firmicutes Clostridia Clostridiales Syntrophomonadaceae Dethiobacter Dethiobacter alkaliphilus
148 81.81 1.55 40 Bacteria Firmicutes Clostridia Clostridiales Syntrophomonadaceae Dethiobacter Dethiobacter alkaliphilus
151 89.75 3.95 50 Bacteria Firmicutes Clostridia Clostridiales Syntrophomonadaceae Dethiobacter Dethiobacter alkaliphilus 243 80.51 3.39 0 Bacteria Firmicutes Clostridia Clostridiales Syntrophomonadaceae Dethiobacter Dethiobacter alkaliphilus
165 96.41 1.28 33.33 Bacteria Firmicutes Clostridia Clostridiales Syntrophomonadaceae
104 95.76 1.41 0 Bacteria Firmicutes Clostridia Clostridiales
182 94.83 3.33 0 Bacteria Firmicutes Clostridia Clostridiales
192 78.72 2.07 50 Bacteria Firmicutes Clostridia
107 79.91 3.49 0 Bacteria Firmicutes Clostridia
142 89.74 0.94 0 Bacteria Firmicutes Erysipelotrichia Erysipelotrichales Erysipelotrichaceae Erysipelothrix
134 87.57 8.49 81.82 Bacteria Firmicutes Erysipelotrichia Erysipelotrichales Erysipelotrichaceae Erysipelothrix 155 100 5.66 37.5 Bacteria Firmicutes Erysipelotrichia Erysipelotrichales Erysipelotrichaceae Erysipelothrix
147 95.19 0.74 75 Bacteria Firmicutes Negativicutes Selenomonadales
102 91.11 1.72 0 Bacteria Latescibacteria
145 92.78 3.7 83.33 Bacteria Proteobacteria Alphaproteobacteria Rhizobiales Bradyrhizobiaceae Afipia Afipia broomeae
2 88.68 0.95 0 Bacteria Proteobacteria Alphaproteobacteria Rhizobiales Roseovarius 118 52.2 1.18 0 Bacteria Proteobacteria Alphaproteobacteria Rhodobacterales Rhodobacteraceae Roseovarius sp. TM1035 187 94.42 0.53 25 Bacteria Proteobacteria Alphaproteobacteria Rhodobacterales Rhodobacteraceae
87_2_1 69.96 6.9 0 Bacteria Proteobacteria Alphaproteobacteria Rickettsiales Anaplasmataceae Sandarakinorhabdus 188 88.47 7.97 65.22 Bacteria Proteobacteria Alphaproteobacteria Sphingomonadales Sphingomonadaceae Sandarakinorhabdus sp. AAP62
53_5 51.72 0 0 Bacteria Proteobacteria Alphaproteobacteria Sphingomonadales Sphingomonadaceae
53_1 89.43 0.39 50 Bacteria Proteobacteria Alphaproteobacteria Sphingomonadales
67 97.33 0 0 Bacteria Proteobacteria Alphaproteobacteria
66 66.03 3.31 100 Bacteria Proteobacteria Betaproteobacteria Burkholderiales Comamonadaceae Hydrogenophaga Hydrogenophaga sp. PBC
119 59.64 0 0 Bacteria Proteobacteria Betaproteobacteria Burkholderiales Comamonadaceae Hydrogenophaga Hydrogenophaga sp. PBC
123_1 54.83 0.23 100 Bacteria Proteobacteria Betaproteobacteria Burkholderiales Comamonadaceae Hydrogenophaga Hydrogenophaga sp. PBC bioRxiv preprint doi: https://doi.org/10.1101/776849; this version posted September 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
6 93.81 6.35 5 Bacteria Proteobacteria Betaproteobacteria Nitrosomonadales Gallionellaceae Sulfuricella Sulfuricella denitrificans Sulfuritalea 22_9 57.52 0 0 Bacteria Proteobacteria Betaproteobacteria Nitrosomonadales Sterolibacteriaceae Sulfuritalea hydrogenivorans Sulfuritalea 203 77.21 0.36 66.67 Bacteria Proteobacteria Betaproteobacteria Nitrosomonadales Sterolibacteriaceae Sulfuritalea hydrogenivorans
93 95.73 6.56 10 Bacteria Proteobacteria Betaproteobacteria Rhodocyclales Rhodocyclaceae Dechloromonas Dechloromonas aromatica
116 96.34 5.19 18.18 Bacteria Proteobacteria Deltaproteobacteria Desulfobacterales Desulfobulbaceae
212_2_0 76.16 1.29 0 Bacteria Proteobacteria Deltaproteobacteria Syntrophobacterales Syntrophaceae
46_3 90.84 3.23 0 Bacteria Proteobacteria Deltaproteobacteria
10 99.59 2.78 0 Bacteria Proteobacteria Epsilonproteobacteria Campylobacterales Helicobacteraceae Sulfurimonas Sulfurimonas denitrificans Methylomicrobium 115_2 98.56 3.12 0 Bacteria Proteobacteria Gammaproteobacteria Methylococcales Methylococcaceae Methylomicrobium buryatense
70 74.66 2.24 0 Bacteria Proteobacteria Gammaproteobacteria Methylococcales Methylococcaceae Methylomonas Methylomonas methanica 173 87.07 6.58 0 Bacteria Proteobacteria Gammaproteobacteria Methylococcales Methylococcaceae Methylomonas
196 89.46 3.62 31.58 Bacteria Proteobacteria Gammaproteobacteria Xanthomonadales Xanthomonadaceae
221_12 53.45 0 0 Bacteria Proteobacteria Gammaproteobacteria Xanthomonadales Xanthomonadaceae
91 64.08 5.39 0 Eukaryota Loukozoa Malawimonadea Malawimonadida Malawimonadidae Malawimonas Malawimonas jakobiformis bioRxiv preprint doi: https://doi.org/10.1101/776849; this version posted September 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
Water ac CHetate4 formate
H 2O CO2
CO CH4 CO2 2
CO Fe2+ + H O Fe O + H 2 2 à 3 4 2 CO
- CO3 formate Rock bioRxiv preprint doi: https://doi.org/10.1101/776849; this version posted September 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
pH 7.77 2690 7.89 8.66 9.84 10.12 10.54 10.94 11.48 12.34 2621 Dashed bars represent metatranscriptomes 1240
FPKM FPKM bioRxiv preprint doi: https://doi.org/10.1101/776849; this version posted September 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. Thaumarchaea
Loukozoa Chlorobi Bacteroidetes Proteobacteria Actinobacter Clostridia Deinococcus Delta Firmicutes
Gamma Beta Alpha Reductive acetyl-CoA pathway
Pathway complete Pathway missing one step bioRxiv preprint doi: https://doi.org/10.1101/776849; this version posted September 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
pH 7.77 CSW1.4
7.89 N08C FPKM 10 8.66 QV1.2 100 500 9.84 CSWold 1000
10.12 CSW1.3 Metagenome Metatranscriptome
10.54 N08A
10.94 N08B
11.48 QV1.1
12.34 CSW1.1 gfa folD frmB mxaI purU frmA (spontaneous) mxaF pmoC pmoB pmoA THF pathway glutathione-dependent CH4 -> CH3OH -> formaldehyde Methane Oxidation Formaldehyde Oxidation to Formate 11.48 12.34 10.54 10.94 10.12 9.84 7.77 7. 8.66 89 bioRxiv preprint not certifiedbypeerreview)istheauthor/funder,whohasgrantedbioRxivalicensetodisplaypreprintinperpetuity.Itmadeavailable pH CSW1.3 CSW1.1 CSWold CSW1.4 QV1.2 QV1.1 N08A N08C N08B doi: https://doi.org/10.1101/776849 CO) (CO 2 -
> cooS, acsA rmate ) ( CO 2 under a
- fdhA > ; fo this versionpostedSeptember20,2019. CC-BY-NC-ND 4.0Internationallicense fdhB Reductive Acetyl fhs
folD The copyrightholderforthispreprint(whichwas .
metF - CoA
acsE
(CO acsB - > acetyl cdhE,
- acsC CoA)
cdhD, acsD Metatranscriptome Me FPKM tagenome 2500 1000 5 100 10 00 bioRxiv preprint doi: https://doi.org/10.1101/776849; this version posted September 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
Heatmap of Observed Features Across Samples Venn Diagram of Observed Features Across Samples
CSW1.1 QV1.1 DOM Intracellular CSW1.1 QV1.1 Intracellular DOM
QV 1,1 Intracellular CSW 1,1 Intracellular QV 1,1 DOM CSW 1,1 DOM
ln(1 + peak intensity) bioRxiv preprint doi: https://doi.org/10.1101/776849; this version posted September 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
DIC vs pH NPOC vs O2 r = -0.798 r = 0.587 bioRxiv preprint doi: https://doi.org/10.1101/776849; this version posted September 20, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
NAD(P)+ NAD(P)H
a 5,10-methenyl- H2O a 10-formyl- tetrahydrofolate folD tetrahydrofolate
aF TH pmoA, pmoB, pmoC H2O Reductive Acetyl-CoA methane methanol CO2 H+ • Clostridiales (Syntrophomodaceae) 2 oxidized THF Pathway O 2, quinol H O, quinone a 5,10-methenyl- • Desulfuromodales 2 cytochrome ⍺ • Burkholderiales (Comamonadaceae) mxaF, tetrahydrofolate fdhA, mxaI • Deinococcales (Trueperaceae) 2H+ , 2 reduced • Hydrogenophilales (Hydrogenophilaceae) X fdhB cytochrome ⍺ • Methylophilales (Methylophilaceae) Methane Oxidation • Rhizobiales Rhodocyclales (Rhodocyclaceae) • Methylococcales (Methylococcaceae) • an N10-formyl- formaldehyde formate fhs • Methylophilales (Methylophilaceae) Formaldehyde Oxidation tetrahydrofolate G lutathione Pathway folD • Burkholderiales (Comamonadaceae) • Rhizobiales a 5,10-methenyl- H+ • Rhodobacterales tetrahydrofolate glutathione • Rhodocyclales (Rhodocyclaceae) folD CO2 a 5,10-methylene- H2O tetrahydrofolate frmA S-(hydroxymethyl)- S- formylglutathione glutathione metF H+ cooS, + NAD(P) NAD(P)H acsA a 5-methyl- tetrahydrofolate Formaldehyde Fixation to Biomass acsE (RuMP or Serine Pathway) a methyl-Co(III) carbon corrinoid Fe-S protein monoxide
Acetate Formation acsB , acsC/chdE, acsD/cdhD From Acetyl-CoA (Type I Pathway) acetyl-CoA