Low Values in Microbialgenic Methane Result from Combinatorial Isotope

Available online at www.sciencedirect.com ScienceDirect

Geochimica et Cosmochimica Acta 285 (2020) 225–236 www.elsevier.com/locate/gca

12 Low D CH2D2 values in microbialgenic methane result from combinatorial isotope eﬀects

Lina Taenzer a,1, Jabrane Labidi b,c, Andrew L. Masterson d, Xiahong Feng a Douglas Rumble III e, Edward D. Young b,⇑, William D. Leavitt a,f,g,⇑

a Department of Earth Sciences, Dartmouth College, United States b Department of Earth, Planetary, and Space Sciences, UCLA, United States c Universite de Paris, Institut de physique duglobe de Paris, CNRS, Paris, France d Department of Earth & Planetary Sciences, Northwestern University, United States e The Geophysical Lab, Carnegie Institution for Science, United States f Department of Biological Sciences, Dartmouth College, United States g Department of Chemistry, Dartmouth College, United States

Received 23 January 2020; accepted in revised form 23 June 2020; Available online 2 July 2020

Abstract

12 Methane generated by microorganisms is most often depleted in the doubly substituted isotopologue CH2D2 relative to 12 the stochastic reference distribution. To constrain the controls on depleted D CH2D2 values, we experimentally isolated the root cause with microorganisms that produce methane from methylphosphonate via the C-P lyase pathway. This mechanism of methane production preserves the three hydrogens from methylphosphonate and adds one hydrogen from water. When maintaining the same methylphosphonate source, but varying the D/H composition of growth medium water, we observed 12 13 significant shifts in methane D CH2D2 values, but little to no change in D CH3D values. We reproduced these observations 12 with a model that considers only the combinatorial isotope effect. The variation in D CH2D2 values of product methane resulted from the differences in D/H between reactants water and methylphosphonate. This work validates the hypothesis that 12 combinatorial effects can strongly influence methane D CH2D2 values, and must be considered for low temperature, abiotic or biotic systems where methane hydrogen is derived from multiple reservoirs. Ó 2020 Published by Elsevier Ltd.

Keywords: Methane; Clumped isotopes; Methanogenesis; C-P lyase

1. INTRODUCTION 2017; Popa et al., 2019). Exploring variations in the relative abundance of the two doubly-substituted mass-18 isotopo- ” 12 13 Multiply-substituted (‘‘clumped ) isotopologues are logues of methane, CH2D2 and CH3D, have provided powerful tracers of molecular formation reactions (Eiler promising constraints on provenance, even where bulk C and Schauble, 2004; Stolper et al., 2014; Wang et al., and H isotopic ratios (13C/12C, D/H) yielded ambiguous 2015; Yeung et al., 2015; Young et al., 2017; Yeung et al., information as to source and process (Young et al., 2017; Haghnegahdar et al., 2017; Young, 2019; Giunta et al., 2019; Ash et al., 2019). The relative abundance of the two ⇑ Corresponding authors. mass-18 clumped isotopologues in a given population of E-mail addresses: [email protected] (E.D. Young), methane molecules formed at high temperature [email protected] (W.D. Leavitt). (P 1000 K) in thermodynamic equilibrium, are approxi- 1 Present Address: MIT-WHOI, United States. mated by a random distribution of all possible isotopologue https://doi.org/10.1016/j.gca.2020.06.026 0016-7037/Ó 2020 Published by Elsevier Ltd. 226 L. Taenzer et al. / Geochimica et Cosmochimica Acta 285 (2020) 225–236 combinations. This apportioning of isotopes is referred to fractionated H sites during formation, and (ii) quantum as a ‘‘stochastic distribution,” and provides the reference tunneling of hydrogen during methane formation frame for reporting the relative abundances of clumped iso- (Ro¨ckmann et al., 2016; Yeung, 2016; Young et al., 2017; topologues (Eiler and Schauble, 2004). The abundance of a Young, 2019; Cao et al., 2019). The former refers to the given multiply-substituted isotopologue relative to the most so-called ‘‘combinatorial effect.” The importance of the 13 12 abundant isotopologue (e.g. CH3D/ CH4) is reported as combinatorial effect as a source of anti-clumping, wherein a fractional difference from the stochastic relative abun- the measured clumped isotopologue abundance is less than dances, Di, where subscript i refers to the specific clumped predicted by theory, was first hypothesized during the study species, and Di are reported in permil (‰). This stochastic of molecular oxygen clumped isotopologues (Yeung et al., reference frame highlights whether a process has favored 2015; Yeung, 2016; Ro¨ckmann et al., 2016) and was sug- or discriminated against the formation of molecules with gested as relevant to microbially produced (microbialgenic) 13 bonds containing multiple heavy isotopes (e.g., CH3D), methane (Young et al., 2017). However, the combinatorial rather than only differences in bulk isotope ratios. Under effect has not been directly tested or demonstrated in any equilibrium conditions at low temperatures (< 300 K), the experimental study. While this effect can arise from drawing stability associated with bonds between heavy isotopes in on two or more reservoirs, it is not simply mixing in the a molecule increases, promoting the formation of the iso- general sense. To interpret the significance of depleted 12 topically clumped molecular species. As temperature (anti-clumped) D CH2D2 values requires a thorough approaches infinity, this effect diminishes and the relative understanding of if, when and how the combinatorial effect abundance of multiply-substituted molecules decreases, is expressed. This understanding is essential to the applica- approaching Di = 0. Under non-equilibrium conditions at tion of clumped isotope signatures as tracers of methane low temperatures, departures from the stochastic distribu- provenance, and extends to other gasses that could hypo- tion may provide insights into the kinetics and reaction(s) thetically experience combinatorics in altering the relative of formation for a given methane population’s natural abundance of multiply substituted isotopologue ratios, such history. as molecular oxygen (D18O18O) or dinitrogen (D15N15N). Methane produced by microorganisms is characterized To experimentally test for the combinatorial effect and ” 12 by significant depletion or ‘‘anti-clumping in the quantify its influence on D CH2D2 values, we examined 12 D CH2D2 values by more than 20–50‰, relative to ther- the bulk and clumped methane isotopologue abundances modynamic equilibrium (Young et al., 2017). These produced by bacteria operating the C-P lyase pathway. This 12 D CH2D2 deficits are accompanied by negligible depletion microbialgenic methane production pathway is related to 13 in D CH3D values (Fig. 1). Several hypotheses have been phosphorous acquisition and not core energy metabolism put forward to explain these observed departures from ther- (White and Metcalf, 2004; Sosa et al., 2019), the canonical modynamic equilibrium. The two hypotheses in the litera- anaerobic microbial methanogens (Valentine, 2011). This ture thus far are: (i) contributions from distinct pools of metabolism provides a unique opportunity to study the hydrogen with disparate D/H ratios and/or differentially combinatorial effect because this pathway incorporates hydrogen from two distinct reservoirs during methane formation: three from the methyl group of methylphosphonate and one from water (Kamat et al., 2011, 2013). Moreover, this methane is generated by rapidly growing bacteria where the bulk isotopic fractionations are independent of energy metabolism and growth rate (Taenzer et al., 2020). By varying the D/H composition of the water in which the bacteria grew and generated methane, we observed dra- 12 13 matic shifts in D CH2D2 with minimal effect on D CH3D. Our experimental and model results together indicate that 12 shifts in methane D CH2D2 produced by the C-P lyase pathway were primarily due to the relative differences in D/H between water and methylphosphonate methyl hydrogens. The consistency between model predicted and experimentally generated isotopologue abundances demonstrates that the combinatorial effect can yield markedly negative 12 D CH2D2 values (below <50‰) with little influence on 13 D CH3D values (<1‰). Implications for the interpretation of experimental and natural methane clumped isotopologue studies are discussed.

Fig. 1. The distribution of laboratory axenic cultures (circles with 2. PRINCIPLES OF THE COMBINATORIAL EFFECT crosses) and naturally-produced methane (open circles) by micro- 12 13 bial methanogenesis in D CH2D2 vs.D CH3D space. The curve representing thermodynamic equilibrium is shown for reference, The stochastic distribution is the reference frame for annotated with temperatures. Calculations and values are from reporting multiply substituted (clumped) isotopologue Young (2019) and references therein. abundances. It is defined by the most probable abundance L. Taenzer et al. / Geochimica et Cosmochimica Acta 285 (2020) 225–236 227 of the multiply-substituted isotopologue of interest assuming that the isotopes comprising the molecules were randomly distributed among all possible isotopologues. The stochastic reference is calculated by equating fractional isotopic abundances with probabilities. To illustrate the essence of the combinatorial effect and for simplicity we examine cases for the formation of two diatomic molecules, carbon monoxide (CO) and molecular oxygen (O2). The stochastic distribution for the relative abundance of the multiply-substituted isotopologue 13C18O in a sample of carbon monoxide gas is calculated as xð13C18OÞ¼xð13CÞxð18OÞð1Þ where x13C is the fractional abundance of 13C relative to all carbon isotopes by number (i.e., 13C=ð12C þ 13CÞ), x18Ois the fractional abundance of 18O relative to all oxygen isotopes (i.e., 18O=ð16O þ 17O þ 18OÞ), and xð13C18OÞ is the fractional abundance of the 13C18O isotopologue relative to all CO molecules. The ratio of this multiply-substituted isotopologue to the most abundant isotopic species is there- Fig. 2. Schematic illustrations showing the pairing of oxygen- fore xð13C18OÞ=xð12C16OÞ. It is common to express ratios of oxygen or oxygen-carbon isotopes when molecules of O2 or CO are relative isotopologue fractions in terms of the isotope ratios formed, respectively. The potential for two separate reactant of their constituent elements. In this case, reservoirs to contribute atoms from pools of distinct isotopic composition is illustrated for each case. For CO, the oxygen and xð13 18 Þ=xð12 16 Þ¼ð13 =12 Þð18 =16 Þ¼13R18R C O C O C C O O . Simi- carbon reservoirs are always distinguishable by virtue of their larly, the stochastic fractional abundance of the multiply- different elemental identities. The composition of the C and O substituted isotopologue of molecular oxygen (O2) com- sources are reflected in the isotopic ratios of the product CO, offset posed of two 18O atoms is by any fractionation, which can be individually traced. On the contrary, in the case of two oxygen reservoirs contributing to O , xð18 18 Þ¼xð18 Þxð18 ÞðÞ 2 O O O O 2 only a single average isotopic composition can be determined for where the symbols are analogous to those in Eq. (1). In this the product O2 which obscures contributions from two separate, and potentially distinct oxygen sources and any fractionation xð18 18 Þ=xð16 16 Þ¼ð18 =16 Þð18 =16 Þ¼18R2 case O O O O O O O O . between product and either of the sources. For both 18O18O and 13C18O, the accuracy of the esti- mated stochastic distribution is dictated by the fidelity of the bulk isotope ratios (e.g., 13R ¼ 13C=12C and assumes that the two molecular positions were formed from 18R ¼ 18O=16O) relative to these ratios at the time the mole- identical oxygen isotope ratios of 18R. In reality, the oxygen cules formed, and the degree to which the sample separa- isotope ratio is the average of two potentially distinct 18 18 tion chemistry and mass-spectrometry can capture these ratios, R1 and R2, which individually contributed to the ratios, free of subsequent fractionation effects. The cases O2 molecule, such that: of CO and O represent contrasting examples of the ability 2 ð18R þ 18R Þ 2 to reconstruct the actual isotope ratios of the constituent ½xð18 18 Þ=xð16 16 Þ ¼ 1 2 ð Þ O O O O stochastic 3 atoms during assembly of the molecules. In the case of 2 CO, the isotopic compositions of C and O unambiguously where subscripts 1 and 2 refer to two distinct oxygen reser- represent the isotope ratios of the constituent atoms since voirs. The difference between using the actual constituent carbon and oxygen are distinguishable; the analysis of car- 18 18 18 18 ratios R1 R2 and using the average ratio ð R1 þ R2Þ=2 13 12 18 16 bon monoxide yields C/ C and O/ O bulk ratios that (by necessity) to calculate the stochastic ratio for the calcu- faithfully record the actual isotopic compositions of the lation of D18O18O is a manifestation of the mathematical two constituent atoms (there is no confusing C and O, see truism that Fig. 2). In contrast, in the case of O2, the isotopologue of 18 18 2 interest is composed of two atoms of the same element ð R1Þþð R2Þ ð18R Þð18R Þ 6 : ð4Þ and so the molecular positions can not be distinguished 1 2 2 from one another. Therefore, despite the fact that the two In particular, we have for the true value for the fractional atoms comprising the O molecule may have originated 2 departure in xð18O18OÞ/xð16O16OÞ from stochastic from different reservoirs with distinct 18O/16O ratios (Yeung et al., 2015), the stochastic abundance of the ½xð18O18OÞ=xð16O16OÞ D18 18 ¼ sample ð Þ 18 18 O O 18 18 1 5 O O molecule is calculated on the basis of the average ð R1Þð R2Þ 18O/16O ratio. That is, the 18O/16O of the O sample reflects 2 ” an average of the two individual molecular sites and their where ‘‘sample refers to the measured isotopologue ratio. D18 18 source reservoirs. By necessity the xð18O18OÞ=xð16O16OÞ¼ The O O value from Eq. (5) cannot be reconstructed a priori. Rather, the estimate obtained from the measured, 18R2 value for the stochastic isotopologue ratio calculation 228 L. Taenzer et al. / Geochimica et Cosmochimica Acta 285 (2020) 225–236 average bulk isotopic composition of the O2 gas itself is unambiguously in the laboratory. Substantiating the exis- actually tence of the combinatorial effect and quantifying its magnitude are prerequisites to interpreting existing and future 4½xð18O18OÞ=xð16O16OÞ D18O18O ¼ sample 1: ð6Þ clumped isotopologue signatures in molecules composed ðÞðÞ18R Þþð18R 2 1 2 of multiple atoms of the same element. 18 18 Only when R1 ¼ R2 will the two estimates be equal. Since the left-hand side of Eq. (4) is the square of the geo- 3. METHODS metric mean and the right-hand side is the square of the arithmetic mean, the inequality in this simple example is 3.1. Microbial cultivation and gas production an expression of the well-known inequality of the geometric and arithmetic means, and is a general result (Yeung, 2016). The model microorganism Pseudomonas stutzeri strain Comparing Eqs. (4)–(6) illustrates the general principle that HI00D01 (hereafter, strain HI00D01) was cultivated fol- when molecular positions are indistinguishable, and the lowing the protocols in our recent study (Taenzer et al., average isotope ratios rather than the site-specific isotope 2020), with modifications to generate large enough quanti- ratios are all that is available for calculating the stochastic ties of methane for clumped isotope analyses. For methane distribution of a multiply-substituted isotopologue, the generation experiments all sources of P were removed and stochastic abundance of the isotopologue i is overestimated, the medium was amended with methylphosphonic acid (aka MPn; Sigma-Aldrich, CAS Number 993-13-5) to a resulting in a spuriously low Di value. The spuriously low concentration of 2 mM, with glucose (electron donor and and even negative Di values are the result of the reference frame (Fig. 3). Yeung and colleagues showed that for the carbon source) to a concentration of 3 g/L, and sodium case of multiply-substituted oxygen isotopologue in molec- nitrate (NaNO3) used as the terminal electron acceptor to a final concentration of 40 mM. The growth medium was ular oxygen that the measured D18O18O diverged drastically filter-sterilized then transferred to 160 mL, 1 or 5L borosil- from the stochastic prediction (Yeung et al., 2015), and pre- icate bottles and vigorously degassed with ultra-high purity dicted that this is potentially due to two contributing helium (UHP-He) for one hour per liter. Cell pellets from sources (reservoirs) of isotopically distinct oxygen – that aerobic cultures were re-suspended and incubated on is, the combinatorial effect (Yeung, 2016). To date, how- amended MPn and NaNO media in 160 mL butyl stop- ever, no study has tested this experimentally for any multi- 3 pered serum bottles. After reaching exponential phase on ply substituted isotope system, be it oxygen, methane or the MPn-amended media and positive head-space methane another. detection (via GC-FID), 1 or 5L cultures were inoculated to Given these examples above, we predict the combinato- an optical density (OD600) of 0.001 and incubated at 30 C rial effect is possible whenever a molecule composed of mul- in the dark. Medium for D-enriched water experiments was tiple isotopes of the same element is constructed from more prepared following the approach of Zhang and colleagues than one isotopic pool. The source of the different pools (Zhang et al., 2009), where it was enriched by adding a cal- may result from different isotope effects for each step culated quantity of D O (Sigma-Aldrich, CAS Number involved in constructing the molecule, or from drawing 2 7789-20-0) to the stock media prior to UHP-Helium flush- on isotopically distinct reservoirs. Candidates include, but ing and sterilization. are not limited to, multiply substituted isotopologues of The gaseous methane, dinitrogen, and carbon dioxide N ,O,H,CH, and N O. Despite the established theoret- 2 2 2 4 2 produced by strain HI00D01 were captured into gas- ical impact of combinatorics in influencing clumped iso- impermeable 0.25, 1, or 4L Tedlar bags, along with trace topologue Di values, it has yet to be demonstrated water vapor. The gas bags were built with straight thru 1/4 inch stainless steel tubing (GSB-P-1 Calibrated Instruments) to which we fitted with a 1/4 inch stainless steel needle valve by compression fitting to seal the gas bags before and after sample collection. To allow sample into the bag, we attached to the needle valve another 1/400 stub of stainless tubing, followed by a tube-to-pipe adapter 1/400 compression to 1/800 NPT, followed by an 1/800 NPT to 1/4-28 adapter to then a luer lock and finally a threaded 18-G stainless steel dispensing needle (all plumbing parts from McMaster-Carr or Swagelok). The needle was inserted through black butyl stopper (GlasgerA˜ tebau Ochs GmbH) into the top of the bags through plastic funnels that were added for stability. At the end of the incubations, UHP-He sparged water was used to displace all remaining headspace into the Tedlar Fig. 3. An illustration of the combinatorial effect seen when bags, allowed to equilibrate, then sealed by the needle plotting D18O18O as a function of the ratio of the isotopic valves and removed from experiment bottles, and the compositions, R1 and R2, of the distinct contributing oxygen valves plugged with metal compression septa until prepa- reservoirs. ration on the vacuum line. L. Taenzer et al. / Geochimica et Cosmochimica Acta 285 (2020) 225–236 229

3.2. Bulk isotope ratio measurements When samples were presumed to be outside the range of the standards (e.g. for the enrichment experiments), sam- Bulk carbon (d13C) and hydrogen (dD) isotope composi- ples were first diluted gravimetrically with a water standard tions of methylphosphonic acid (Sigma-Aldrich, CAS of known composition. Uncertainty’s due to dilution are Number 993-13-5) were determined at the Northwestern accounted for and reported in Table 1 as the propagated University Stable Isotope Laboratory. Briefly, the d13C 1se. value of MPn was determined via EA-IRMS on a Costech The stable isotopic compositions of methane samples 4010 Elemental Analyzer, coupled to a Delta V Plus isotope generated by the C-P lyase in cultures of strain HI00D01 ratio mass spectrometer via a Conflo IV interface. Analyses were measured on an ultra-high mass resolution isotope were done in triplicate, and placed on the VPDB-LSVEC ratio mass spectrometer (Panorama, Nu Instruments) as 12 scale via analysis of organic standards supplied by Indiana part of the measurements to determine D CH2D2 and 13 University (acetanilide #1, urea #2a, and D-glucose) D CH3D. (Schimmelmann, 1991; Qi and Coplen, 2011). The bulk hydrogen (dD) isotope composition of MPn was deter- 3.3. Multiply-substituted isotopologue measurements mined via TC/EA-IRMS, operated at 1420 C, and coupled to a Delta V Plus isotope ratio mass spectrometer via a The abundance of the two multiply-substituted mass-18 Conflo IV. Analyses were done in triplicate, and cross- isotopologues of methane gas samples were measured on a referenced to the Ag-tube water isotope standards supplied Panorama (Nu Instruments) ultra-high-resolution gas- by the USGS (GISP2, VSMOW, and UC03). The average source isotope ratio mass spectrometer housed in the composition of the non-exchangeable hydrogens on MPn Department of Earth, Planetary, and Space Sciences at (i.e., R-CH3) was determined by equilibration with D- the University of California Los Angeles. Detailed descrip- enriched waters (2 mL) in a custom-designed vacuum tions of the mass spectrometry method were given by chamber modified from a Costech zero-blank auto- Young and colleagues (Young et al., 2016), and applied sampler. Incubations were done at room temperature in recent studies (Young et al., 2017; Haghnegahdar (25 C) for 6 days. At the end of the equilibration, water et al., 2017; Giunta et al., 2019; Ash et al., 2019; Young, vapor was pumped to <50 mTorr for 2 h, followed by sub- 2019). sequent TC/EA analyses with Ag-tube USGS standards as Methane sample gases were purified on a vacuum line above, following published methods (Qi and Coplen, 2011). interfaced with a gas chromatograph (SRI GC-FID 8610) Isotopic analysis of the medium water was conducted at prior to isotopic analysis. This method was previously the Stable Isotope Laboratory at Dartmouth College fol- described in Young et al. (2016). Modification to the pub- lowing published procedures (Kopec et al., 2019). Briefly, lished procedures were as follows. The Tedlar gas bag hold- water hydrogen isotopic ratios (dD) were measured using ing the C-P lyase generated methane gas (mixed with UHP the H-Device, in which water was reduced by hot chromium He, water vapor, and the other metabolic products N2 and (850 C) and the resulting hydrogen gas was measured by CO2) was connected to the line with compression fittings an isotope ratio mass spectrometer (IRMS, Thermo Delta and PTFE ferrules. Prior to gas introduction, the Plus XL). Isotopic ratios (D/H) are reported in delta nota- hydrocarbon-free vacuum line was evacuated to at least tion in permil (‰) deviation from the international stan- 4.0107 mbar. Sample gas was introduced from the bag dard VSMOW on the VSMOW-SLAP (Vienna Standard to the line in aliquots of 1000 mbar into a calibrated 50 cc Mean Ocean Water, Standard Light Antarctic Precipita- volume. Water vapor was trapped in a U-trap by ethanol- tion) scale. The measurement 1r uncertainty is 0.5‰ for liquid nitrogen (LN2) slurry at 80 C. The rest of the sam- dD, and the measured value was converted to the water iso- ple gas was then trapped on silica gel in a U-trap at LN2 tope equivalent by calibration with known standards. temperature for 10 min, after which the non-condensable

Table 1 The isotopic compositions of medium waters and product methane. Water Methane 13 13 12 Sample ID dD 1se d C 1se dD 1se D CH3D 1se D CH2D2 1se -400 B1 376 0.5 100.388 0.012 319.26 0.04 0.93 0.35 69.18 1.15 400 B2 376 0.5 98.950 0.013 319.22 0.04 0.85 0.44 69.10 0.83 60 B1 63 0.5 99.993 0.006 299.49 0.04 0.02 0.13 52.28 0.83 60 B2 63 0.5 100.15 0.010 300.22 0.03 0.50 0.24 51.11 0.88 750 B1 1013 1.7 97.047 0.006 249.08 0.05 0.28 0.31 14.90 1.32 750 B2 1022 7.3 100.297 0.024 250.12 0.05 0.77 0.42 13.82 1.17 1500 B1 2007 5.1 100.745 0.010 194.72 0.04 0.26 0.18 0.01 0.96 1500 B2 2188 5 100.846 0.007 190.06 0.04 0.54 0.27 0.79 1.11 3000 B1 3797 3.1 100.213 0.009 106.08 0.05 0.72 0.38 5.2 1.14 3000 B2 3868 2.3 100.606 0.071 104.59 0.06 0.29 0.71 7.06 1.10 3900 B1 + 2 4871 7.9 97.949 0.019 46.43 0.03 0.24 0.36 0.12 0.72 5500 B1 6800 11.1 100.480 0.006 42.39 0.04 0.03 0.25 25.46 0.85 230 L. Taenzer et al. / Geochimica et Cosmochimica Acta 285 (2020) 225–236

He was slowly pumped away. The methane aliquot was 4. RESULTS then cryofocused to remove the N2 and CO2 via GC and re-trapping on silica gel as previously described The isotopic compositions of methane produced from (Young et al., 2017). Due to the significant partial pressure the degradation of MPn by strain HI00D01 in waters with of N2 relative to methane, and because complete separation different dD values in the range from 376 to þ6800‰ are of methane from N2 was not achieved on the first pass given in Table 1. The dD of product methane correlates clo- through the GC, multiple aliquots were first passed though sely with the dD of water (Fig. 4). The methane d13C values the GC, cryofocused, and co-trapped onto the same silica vary little between 97 to 101‰ (mean = 99:9 1:2‰, gel in a single glass cold-finger (6–7 GC-passes per sample 1r), closely tracking the d13C of the source MPn of near bag). Once the requisite sample size of methane was 100‰ relative to VPDB (Taenzer et al., 2020). The three captured (>40 micromoles), the combined sample was once non-exchangeable H-sites on the MPn methyl-group have a again cryofocused and passed through the GC a final time dDof138 5‰ relative to VSMOW for all of the exper- to remove trace N2. The purified methane was then iments except those that utilized normal house water transferred to the Panorama inlet system for the bulk and (60‰, both B1 and B2). In the latter two experiments a clumped isotope ratio analyses following published different batch of MPn was used with the measured MPn protocols (Young et al., 2017). methyl-group dD being 132 5‰ relative to VSMOW. These results show that the final hydrogen added to the 3.4. Isotope notation methyl-group derives from medium water during methane formation, and supports the recent finding that negligible The isotopic compositions of carbon and hydrogen are carbon-isotope fractionation occurs during methane reported as deviations from the carbon and hydrogen production from MPn via the C-P lyase pathway reference materials Vienna Peedee Belemnite and Vienna (Taenzer et al., 2020). 13 Standard Mean Ocean Water (VPDB and VSMOW, The measured D CH3D values of C-P lyase generated respectively). Standard delta notation is used to express methane ranged between 0:29 and 0:934‰, with an aver- the fractional differences: age of 0:35 0:401r (Fig. 5, Table 1). The variation in ! D13 ð13C=12CÞ CH3D values was only marginally greater than measure- d13C ¼ 103 sample 1 ð7Þ ment uncertainties, and did not vary systematically with ð13C=12CÞ VPDB water dD, despite the significant contribution of water d and sourced from the medium with a range of D values from 12 376 to þ6800‰. In sharp contrast, the D CH2D2 values ðD=HÞ d ¼ 3 sample ð Þ varied from 69:2toþ7:1‰, a spread much greater than D 10 ð = Þ 1 8 D H VSMOW measurement uncertainty of < 1‰ (Fig. 5). The methane where all values are given in permil (‰), as shown. The relative abundances of the two multiply-substituted mass-18 isotopologues of methane are reported relative to the stochastic reference frame using the Di notation, also in per- 13 12 mil, where D CH3D and D CH2D2 are (Young et al., 2016): ! 13 xð CH3DÞ D13CH D ¼ 103 sample 1 ð9Þ 3 xð13 Þ CH3D stochastic and ! 12 xð CH2D2Þ D12CH D ¼ 103 sample 1 ; ð10Þ 2 2 xð12 Þ CH2D2 stochastic respectively (Young et al., 2016). The stochastic fractional abundances of the mass-18 isotopologues are obtained from the measured bulk isotope fractional abundances of atoms in the sample such that xð13 Þ ¼ xð13 Þxð Þ3xð Þ ð Þ CH3D stochastic 4 C H D 11 Fig. 4. The D/H ratios of product methane vs. the D/H of medium and water expressed in per mil deviations from VSMOW. Linear d d : 2 regression yields DCH 4 = 0.05 DH2O 301 5, with an R of 0.999. xð12 Þ ¼ xð12 Þxð Þ2xð Þ2 ; ð Þ CH2D2 stochastic 6 C H D 12 The strong correlation betwen the isotopic ratios demonstrates addition of a consistent fraction of reactant water to product and where the coefficients of 4 and 6 account for the num- methane, and allows for the calculation of the fractionation factor ber of permutations for the positions of the D and H iso- between water D/H and the D/H of the single hydrogen added to topes (Young et al., 2016). the MPn CH3 to form methane (see text). L. Taenzer et al. / Geochimica et Cosmochimica Acta 285 (2020) 225–236 231

13 12 Fig. 5. The measured (left) D CH3D and (right) D CH2D2 of microbialgenic methane produced in experiments with water of varying dD water for methane produced in various D-spiked experiments. Errors are smaller than the symbols, both axes in permil.

12 D CH2D2 values correlated closely with the medium water of hydrogen from medium water and the MPn methyl dD in a non-linear, semi-parabolic relationship (Fig. 5). group is

PRPn SAM PhnJ H2O þ½PO4 C5O3H8 PO3 CH3 þ C15H23N6O5S ! 0 5. DISCUSSION 5 deoxyadenosine PRcP Lmethionine C10H13N5O3 þOH þ½PO4 C5O2H7 PO4 þ C5H11NO2S þCH4 ð Þ 5.1. D/H fractionation between MPn and water 13 In our labelled water experiments, the methane dD Understanding the sources of hydrogen used in methane increased with the water dD(Fig. 4). Moreover, because formation by the C-P lyase enzyme is central to understand- we used the same lot of MPn for all reactions, with one ing the results of these experiments. The main substrate exception that was isotopically similar (see Results), the MPn is an organophosphonate synthesized by certain methyl-group D/H was the same for all our experiments, microbes in nature when faced with inorganic phosphate and the increase in the D/H of product methane solely limitation (Metcalf et al., 2012; Yu et al., 2013). The reflects the addition of water derived hydrogen with differ- methyl-group hydrogens on MPn are ultimately derived ent D/H ratios. The tight correlation between bulk water from the water in which MPn is biosynthesized, offset by and methane dD is described by the linear regression with an unknown isotope effect. The hydrogen isotope fraction- an R2 value of 0:999 (Fig. 4). The regression equation is ation between methyl-group hydrogens and water in more dD ¼ 0:05dD 301:5: ð14Þ thoroughly studied processes, such as acetogenesis, show CH4 H2O offsets from bulk water dD of hundreds of permil The good correlation is consistent with the conclusion that (Hattori et al., 2010). Here we utilized synthetic MPn with methane is formed by transfer of a hydrogen from the med- an average dD value distinct from all medium waters uti- ium water to the methyl group of MPn, and indicates that lized (see Results). Phosphorus-starved microbes that the transfer of hydrogen from water to the methyl group encode the C-P lyase enzyme are able to grow on MPn as was consistent for all incubations in medium waters of dif- their sole source of phosphorus by breaking down MPn ferent dD values. The slope in Eq. (14) is the product of the (Carini et al., 2014; Repeta et al., 2016; Sosa et al., 2019), fractionation factor between water and the hydrogen trans- and as a by-product, release methane (Kamat et al., ferred to methane and the fraction of hydrogen in the 2011). The carbon-phosphorus bond in the methyl phos- methane derived from the water. phonate intermediate, ribose-1-methylphosphonate 5- The good correlation described by Eq. (14) is best phosphate (PRPn), is attacked by the C-P lyase enzyme explained as the result of constant fractions of hydrogen subunit PhnJ, producing ribose-1,2-cyclic-phosphate-5-ph coming from the methyl group in MPn and water to pro- osphate (PRcP), and releasing the methyl group used to duce methane. The most likely reason for this is that form methane. This reaction breaks the methyl group from methane inherits 3/4 of its hydrogen directly from CH3, the rest of the phosphonate compound. In vitro experi- and that water contributes the last hydrogen. The hydrogen ments with PhnJ showed that the hydrogen added to the isotope conservation equation for the formation of methyl group originates from the bulk solvent (water) via methane is therefore a solvent exchangeable site on an amino acid in PhnJ D D D D 0:75ð R Þþ0:25 a = ð R Þ¼ R ð15Þ (Kamat et al., 2011). The medium-derived hydrogen is Methyl CH4 H2O H2O CH4 D delivered to form methane either by abstraction from the where Ri is the D/H ratio for species i. Using the known 0 5 -deoxyadenosine or the PhnJ amino acids. A representa- dD values for the product methane, medium water, and tion of the overall reaction that underscores the sources MPn methyl group from each experiment, the fractionation 232 L. Taenzer et al. / Geochimica et Cosmochimica Acta 285 (2020) 225–236

Da factor between methane and water, CH4=H2O, for the one hydrogen drawn upon to construct the CH4 molecules in hydrogen transferred from water to make methane was each experiment. determined by rearranging Eq. (15), yielding: The large isotope fractionation during the transfer of water hydrogen to the methyl group ensures that two com- ðDR ð : DR ÞÞ D 4 CH4 0 75 Methyl positionally distinct hydrogen reservoirs with distinct dD a = ¼ : ð16Þ CH4 H2O DR H2O values contribute to product methane, one ultimately from medium water and the other from the methyl group in the The D/H fractionation factor between water and methane MPn. Other mechanisms of methane formation that are calculated from Eq. (16) for the experiments with differing analogous to the C-P lyase, such as microbial methy- d : : water D values vary from 0 203 to 0 219 with an average lotrophic and acetotrophic methanogenesis (Penger et al., : : r value of 0 209 0 005 1 . The consistency is a reflection 2012), are likely influenced similarly. These metabolisms d of the good correlation between D values for CH4 and have been the target of recent investigations into their vari- H2O(Fig. 4). This fractionation factor corresponds to 13 ance in D CH3D in response to labelled substrate or water D emethane=water ¼790 5‰. The magnitude of fractiona- 12 (Gruen et al., 2018), although D CH2D2 values were not tion between water and methane is relatively large, though determined. In addition to these biogenic methane forma- not uncommon for processes involving hydrogen (Valentine tion pathways, abiotic methane formation pathways where et al., 2004; Kawagucci et al., 2014). However, the fraction- hydrogenated sites on end-product methane derive from ation is not a priori outside the range for classical effects two or more different reservoirs or with different fractiona- given the likelihood that it reflects a convolution of steps tions from the source reservoir may be similarly influenced, (i.e., product of fractination factors) involving D/H as has been suggested (Yeung, 2016; Young et al., 2017; exchange on amino acids that accommodate the transfer Young, 2019). Evidence of either quantum tunneling or of the last hydrogen that forms methane from water the combinatorial effect were captured in methane gener- (Kamat et al., 2011). For this reason we do not attribute ated at low-temperature via the abiotic Sabatier reaction, the magnitude of our derived fractionation factor to quan- where a clear anti-clumped signal was observed in the tum tunneling. We note that because we know the D/H of 12 13 D CH2D2 with minimal variance in D CH3D(Young the methyl group (exchangable hydrogen in MPn) and we et al., 2017). To determine if this was the combinatorial can calculate the D/H of the hydrogen donated from water, effect, future experiments with isotopically enriched molec- we have characterized the D/H for the two sources of ular hydrogen are needed.

12 13 Fig. 6. An illustration of the difference between the stochastic abundances of D CH2D2 and D CH3D predicted when using average isotopic compositions of the sample gas versus the isotopic compositions of the specific reactants. The abundance of the clumped isotopologues that results from the dD and d13C in any given methane population is shown by the white bars, whereas, the abundance of the clumped isotopologues predicted from using the isotopic composition of the specific reservoirs, water and MPn, is given in the black bars, and correspond to the left Y-axes. The clumped isotope values are depicted by the blue dashed line, and correspond to the right Y-axes. If the isotopic composition of the source reservoirs that contribute to product methane have the same dD values, then the clumped values will not vary, shown by the horizontal blue bar at zero in each panel. In reality, the clumped isotopic compositions are negative across most water dD values (assuming an invariant methyl-group), because the stochastic isotopologue abundance using the average C and H isotopic composition of the sample gas is greater than that given by the isotopic composition of the methyl group and water. All points in this plot are illustrative and not real data. L. Taenzer et al. / Geochimica et Cosmochimica Acta 285 (2020) 225–236 233

12 5.2. Effect of multiple D/H reservoirs on D CH2D2 order to determine the extent to which the range of 12 observed D CH2D2 values is explained solely by the com- The combination of multiple reservoirs with distinct D/ binatorial effect we applied a model in which we calculate 12 H ratios has a clear influence on the D CH2D2 value of methane isotopologue abundances produced by a network product methane. There was no corresponding effect on of bi-molecular reactions between the isotopologues of 13 12 D CH3D values. The negative D CH2D2 values result the MPn methyl group and water, including the fractiona- from the nature of the clumped isotope reference frame. tion factor derived from Eq. (16). The relative rates of the In general, when the stochastic distribution is calculated reactions were taken to be the product of the reactant rela- from a sample gas that averages different isotopic pools, tive concentrations. The eleven reactions comprising the negative Di values result. By altering the isotopic composi- model are tion of one of the two pools of hydrogen in the C-P lyase H O þ 12CH ! 12CH þ OH ð17Þ pathway, the medium water, we have apparently isolated 2 3 4 12 12 12 H2O þ CH2D ! CH3D þ OH ð18Þ this combinatorial effect on D CH2D2. 12 12 In Fig. 6, we illustrate the expected combinatorial effect H2O þ CHD2 ! CH2D2 þ OH ð19Þ on product methane for experiments like those reported 12 12 HDO þ CH3 ! CH4 þ OD ð20Þ here. When calculated D12CH D values are plotted against 2 2 þ 12 ! 12 þ ð Þ the D/H isotopic composition of the water hydrogen iso- HDO CH3 CH3D OH 21 12 12 topic composition where the methyl D/H is unchanged, a HDO þ CH2D ! CH3D þ OD ð22Þ parabolic trend emerges with an D12CH D value near zero 12 12 2 2 HDO þ CH2D ! CH2D2 þ OH ð23Þ at the apex, whereas the D13CH D is unchanged. This 3 HDO þ 12CHD ! 12CH D þ OD ð24Þ topology is predicted by the inequality in Eq. (4) and has 2 2 2 þ 12 ! 12 þ ð Þ been demonstrated mathematically (Yeung et al., 2015; HDO CHD2 CHD3 OH 25 12 12 Yeung, 2016; Ro¨ckmann et al., 2016). As the isotopic com- D2O þ CH3 ! CH3D þ OD ð26Þ position of the hydrogens originating from the water and þ 12 ! 12 þ : ð Þ 12 D2O CH2D CH2D2 OD 27 the methyl group diverge, the D CH2D2 values become exponentially more negative. Negative values for We also used an analogous set of reactions in which the 13 13 D CH3D do not emerge because of the unambiguous dis- C-bearing isotopologues of the methyl group were tinction between the 13C=12C and D/H ratios, yielding no included. The rate of reaction was modified by the fraction- ambiguity in the stochastic distribution (Fig. 6). ation factor from Eq. (16) where a D in CH4 comes from water. We performed the calculations for values of 12CH D Da : : 5.3. Model for the observed 2 2 effect CH4=H2O ranging from 0 19 to 0 23 in order to allow for uncertainties in the precise value. Our results resemble those expected for the combinato- We performed the calculations in two ways. In the first rial effect (compare Figs. 5 and 6) and suggest that a com- calculation, we assumed that the reactants had stochastic 12 binatorial effect in D CH2D2 is indeed manifest in at least relative abundances of isotopologues calculated from their one pathway for microbialgenic methane formation. In measured bulk d13C and dD values. From the relative rates

12 Fig. 7. Plots of D CH2D2 vs. water dD showing our experimental results (triangles) and the two model calculations described in the text (curves). The model curves in panel A assume stochastic distributions for all of the reactant isotopologues. The model curves in panel B are D12 : ‰ Da : obtained using a best-fit CHD2 value of 11 4 for the reactant methyl group (see text). Curves for a range of CH4=H2O values from 0 19 to : d Da 0 23 are shown for reference. Monte Carlo simulations of the effects of uncertainties in MPn methyl D and our derived CH4=H2O values are shown by the circles. Means and standard deviations for the Monte Carlo simultaions are shown by the filled circle and 1r vertical error bars. 234 L. Taenzer et al. / Geochimica et Cosmochimica Acta 285 (2020) 225–236 of reaction we calculate the resulting abundances of the (Young et al., 2017; Young, 2019). The results of this study 12 13 methane isotopologues and the D CH2D2 and D CH3D lend support to the interpretation that combinatorial effects values expected for each incubation experiment. dominate. These effects may arise from enzymatically- The fit of the model curves obtained using purely mediated kinetic steps within a cell or surface catalyzed stochastic reactant isotopologue abundances is sufficiently steps during abiotic synthesis. In both cases we refer to good (Fig. 7) that we conclude that the combinatorial effect these as endogenous combinatorial effects because they 12 is the dominant process governing the values for D CH2D2 are the result of distinct pools of hydrogen created by the in the product methane. However, there is a marked offset kinetic steps leading to methane formation. In the present between the model curves and the measured values at study, the pools of contrasting D/H ratios arise in part higher water dD values. As expected, the calculations, pro- because of the isotopic composition of the growth medium, 13 duce D CH3D within < 0:2‰, signifying no effect on comprising what we refer to as an example of exogenous 13 combinatorial effects to emphasize that the pools of hydro- D CH3D, as observed in our experiments. In our second calculation method, we obtained an gen with distinct D/H ratios include an external reservoir. improved fit to the data by considering that the reactant Endogenous combinatorial effects may explain the very D12 methyl group did not have a purely stochastic distribution low CH2D2 values seen in microbial methanogenesis of isotopologues. Specifically, we allowed for a higher con- and in abiotic Sabatier reaction products (Young et al., centration of CHD2 relative to stochastic. In order to deter- 2017; Young, 2019). 12 13 mine a best-fit value for the reactant methyl clumping, we A critical advantage of using D CH2D2 and D CH3D adjusted the ratio CHD2/(CHD2)stochastic to minimize the values to characterize the provenance of methane molecules 12 chi-square calculated from the deviation in D CH2D2 val- is their relative insensitivity to substrate bulk isotopic com- ues between the data and the model. For this minimization positions (Young et al., 2017; Young, 2019). For example, 12 Da : the very negative D CH2D2 values that are characteristic we adopted the mean CH4=H2O value of 0 209. The results of, or even diagnostic of, microbialgenic methane appear yield a best-fit CHD2/(CHD2)stochastic ratio of 1.0114 that 12 to be insensitive to the dD of the local aqueous environs can be expressed as a D CHD2 value of 11.4‰ (Fig. 7). 12 (Young et al., 2017; Young, 2019; Ash et al., 2019). How- For a nominal reproducibility of 2‰ for D CH2D2 val- D12 ues implied by some of the replicate experimental results ever, the strong response of CH2D2 values to the iso- in Table 1, the reduced chi-square value for the fit of this topic composition of water in these experiments raises the model is 4 (for n = 12 experiments). This value is suffi- specter of substrate bulk isotope effects on methane D12 ciently close to unity to suggest that the vast majority of CH2D2 values. Though some of the experimental water the variation exhibited by our data is due to the combina- values were not representative of natural systems (e.g. d ‰ torial effect that includes inheritance of a modest amount DH2O >0 ), both the Hanover, NH, USA (house) and of DD clumping from the reactant methyl group in MPn. South Pole, Antarctica waters represent values for reser- In order to assess the importance of the analytical uncer- voirs in nature that can contribute hydrogen to methane. tainties in the two input parameters for our calculations, we We note that the more than 300‰ difference in the dDof performed Monte Carlo (MC) simulations of the experi- the two waters resulted in a more than 15‰ shift in D12 ments by randomly varying the MPn methyl-group dD val- methane CH2D2 values at a fixed substrate MPn iso- Da topic composition (Fig. 5). The likelihood for such effects ues and the CH4=H2O values in our model calculations at the water dD values corresponding to the experiments. in nature depends on the variability of D/H in natural We drew 100 random instances of these values from parent waters and variability in fractionation factors between Gaussian distributions based on the measured means and water and the natural methyl-type substrates used in standard deviations for these parameters and used these methanogenesis. For the step-wise addition of hydrogen as inputs to the calculations. The resulting MC estimates to carbon during hydrogenotrophic (H2 +CO2) methano- for the uncertainties in the models are shown in both panels genesis, where all of the hydrogen for the product methane in Fig. 7. For the 7 groups of experiments representing 7 ultimately originates from water, endogenous combinato- 12 rial effects likely dominate due to the different D/H frac- distinct dD water values, 6 have measured D CH2D2 values that are within the 4r uncertainty in our best-fit model with tionation factors associated with each hydrogen addition 12 step (Young, 2019). This said, if some of the hydrogens D CHD2 ¼ 11:4‰ (panel B, Fig. 7). Our best-fit model allows us to not only simulate the com- on methane come from molecular hydrogen (Valentine binatorial effect on the product methane, but it also affords et al., 2004; Kawagucci et al., 2014), the opportunity for an estimate of the DD clumping in the MPn methyl group combinaotiral influence arises. Indeed, the other canonical 12 microbial pathways of methane formation, methylotrophic that produced the methane. The value for D CHD2 in this instance reflects the process of forming reagent MPn. Exper- or acetotrophic, are clear analogs to the C-P lyase pathway, iments similar to these might be useful in exploring the DD in that different D/H pools are accessed in the form of ordering in naturally occurring MPn methyl groups. water and preexisting methyl groups, suggesting that exogenous combinatorial effects are at play. This is especially true given the likelihood for large D/H fractionations between 12 5.4. Implications for applications of CH2D2 water and C-H bearing organic sources of H in nature (Hattori et al., 2010), without which reservoir (exogenous) 12 Negative D CH2D2 values have been attributed to combinatorial effects are unlikely. More work is required 12 either combinatorial effects or quantum tunneling effects to understand whether or not differences in D CH2D2 val- L. Taenzer et al. / Geochimica et Cosmochimica Acta 285 (2020) 225–236 235 ues among different methanogenesis pathways (Giunta Carini P., White A. E., Campbell E. O. and Giovannoni S. J. (2014) et al., 2019; Young et al., 2017) could in part reflect the dif- Methane production by phosphate-starved SAR11 chemo- ferent magnitudes of endogenous and exogenous combina- heterotrophic marine bacteria. Nat. Commun. 5, 1–7. 18 13 16 torial effects. Eiler J. M. and Schauble E. (2004) O C O in Earths atmo- sphere. Geochim. Cosmochim. Acta 68, 4767–4777. Giunta T., Young E. D., Warr O., Kohl I., Ash J. L., Martini A., 6. CONCLUSIONS Mundle S. O., Rumble D., Pe´rez-Rodrı´guez I., Wasley M., LaRowe D. E., Gilbert A. and Sherwood Lollar B. (2019) D12 The source of depleted CH2D2 values in methane Methane sources and sinks in continental sedimentary systems: produced by microbes is evidenced in the aerobic C-P lyase New insights from paired clumped isotopologues 13CH3D and pathway. This metabolism for methane production incor- 12CH2D2. Geochim. Cosmochim. Acta 245, 327–351. porates hydrogen from two distinct reservoirs: a methyl Gruen D. S., Wang D. T., Ko¨nneke M., Topçuog˘lu B. D., Stewart group, contributing three hydrogenated sites, and water L. C., Goldhammer T., Holden J. F., Hinrichs K.-U. and Ono that donates a single hydrogen. By varying the D/H compo- S. (2018) Experimental investigation on the controls of clumped sition of the water medium in which the bacteria generate isotopologue and hydrogen isotope ratios in microbial methane. Geochim. Cosmochim. Acta 237, 339–356. methane, we observed the effect of combinatorics on Haghnegahdar M. A., Schauble E. A. and Young E. D. (2017) A D12 CH2D2 values. Our results indicate that variations in model for 12CH2D2 and 13CH3D as complementary tracers 12 the D CH2D2 of methane produced by C-P lyase is primar- for the budget of atmospheric CH4. Global Biogeochem. Cycles ily the result of the difference in D/H between the water and 31(9), 1387–1407. the reactant methyl group. The consistency between predic- Hattori R., Yamada K., Shibata H., Hirano S., Tajima O. and tions for the purely combinatorial reservoir effect and the Yoshida N. (2010) Measurement of the isotope ratio of acetic measured isotopologue abundances demonstrates that in acid in vinegar by hs-spme-gc-tc/c-irms. J. Agric. Food. Chem. this case, combinatorics are the main cause of the negative 58(12), 7115–7118, PMID: 20504023. Kamat S. S., Williams H. J., Dangott L. J., Chakrabarti M. and D12CH D values with no resolvable effect on D13CH D val- 2 2 3 Raushel F. M. (2013) The catalytic mechanism for aerobic ues for the product methane. These results lend credence to formation of methane by bacteria. Nature 497(7447), 132–136. the interpretation that combinatorial effects dominate the Kamat S. S., Williams H. J. and Raushel F. M. (2011) Interme- 12 depleted microbialgenic methane D CH2D2 values as well diates in the transformation of phosphonates to phosphate by as those arising from some surface catalyzed abiotic bacteria. Nature 480(7378), 570–573. methane production pathways. This work raises the pro- Kawagucci S., Kobayashi M., Hattori S., Yamada K., Ueno Y., spect that differential water H-isotopic compositions or Takai K. and Yoshida N. (2014) Hydrogen isotope systematics fractionations in nature may induce the combinatorial effect among h2–h2o–ch4 during the growth of the hydrogenotrophic in some microbial methane production pathways. methanogen methanothermobacter thermautotrophicus strain dh. Geochim. Cosmochim. Acta 142, 601–614. Kopec B., Feng X., Posmentier E. and Sonder L. (2019) Seasonal RESEARCH DATA deuterium excess variations of precipitation at summit, green- land, and their climatological significance. J. Geophys. Res. All code for model and figures is posted in a permanent Atmosph. 124(1), 72–91. archive FigShare DOI: 10.6084/m9.figshare.11676357. Metcalf W. W., Griffin B. M., Cicchillo R. M., Gao J., Janga S. C., Cooke H. A., Circello B. T., Evans B. S., Martens-Habbena W., Declaration of Competing Interest Stahl D. A. and van der Donk W. A. (2012) Synthesis of methylphosphonic acid by marine microbes: a source for methane in the aerobic ocean. Science 337(6098), 1104–1107. The authors declare that they have no known competing Penger J., Conrad R. and Blaser M. (2012) Stable carbon isotope financial interests or personal relationships that could have fractionation by methylotrophic methanogenic archaea. Appl. appeared to influence the work reported in this paper. Environ. Microbiol. 78(21), 7596–7602. Popa M. E., Paul D., Janssen C. and Ro¨ckmann T. (2019) H_2 ACKNOWLEDGEMENTS clumped isotope measurements at natural isotopic abundances. Rapid Commun. Mass Spectrom. 33(3), 239–251. Funding was provided by the Simons Foundation (WDL), the Qi H. and Coplen T. B. (2011) Investigation of preparation NASA NH Space Grant NNX15AH79 (WDL, LT), and the Sloan techniques for d2H analysis of keratin materials and a proposed Foundation Deep Carbon Observatory (EDY); we thank Beverly analytical protocol. Rapid Commun. Mass Spectrom. 25(15), Chiu and Alec Cobban for laboratory assistance. 2209–2222. Repeta D. J., Ferroń S., Sosa O. A., Johnson C. G., Repeta L. D., Acker M., Delong E. F. and Karl D. M. (2016) Marine methane REFERENCES paradox explained by bacterial degradation of dissolved organic matter. Nat. Geosci. 9(12), 884–887. Ash J., Egger M., Treude T., Kohl I., Cragg B., Parkes R., Slomp Ro¨ckmann T., Popa M. E., Krol M. C. and Hofmann M. E. G. C., Sherwood Lollar B. and Young E. (2019) Exchange (2016) Statistical clumped isotope signatures. Sci. Rep. 6(1), catalysis during anaerobic methanotrophy revealed by 31947. 12 13 CH2D2 and CH3D in methane. Geochem. Perspect. Lett., Schimmelmann A. (1991) Determination of the concentration and 26–30. stable isotopic composition of nonexchangeable hydrogen in Cao X., Bao H. and Peng Y. (2019) A kinetic model for organic matter. Analyt. Chem. 63(21), 2456–2459. isotopologue signatures of methane generated by biotic and Sosa O. A., Repeta D. J., DeLong E. F., Ashkezari M. D. and Karl abiotic co2 methanation. Geochim. Cosmochim. Acta 249, 59–75. D. M. (2019) Phosphate limited ocean regions select for 236 L. Taenzer et al. / Geochimica et Cosmochimica Acta 285 (2020) 225–236

bacterial populations enriched in the carbon–phosphorus lyase Yeung L. Y., Ash J. L. and Young E. D. (2015) Biological pathway for phosphonate degradation. Environ. Microbiol. signatures in clumped isotopes of O2. Science 348(6233), 431– 1462–2920, 14628. 434. Stolper D. A., Lawson M., Davis C. L., Ferreira A. A., Neto E. V. Yeung L. Y., Li S., Kohl I. E., Haslun J. A., Ostrom N. E., Hu H., S., Ellis G. S., Lewan M. D., Martini A. M., Tang Y., Schoell Fischer T. P., Schauble E. A. and Young E. D. (2017) Extreme M., Sessions A. L. and Eiler J. M. (2014) Formation temper- enrichment in atmospheric 15n15n. Sci. Adv. 3(11), eaao6741. atures of thermogenic and biogenic methane. Science 344(6191), Young E. (2019) A two-dimensional perspective on ch4 isotope 1500–1503. clumping: Distinguishing process from source. In Deep Carbon Taenzer L., Carini P., Masterson A., Bourque B., Gaube J. and Past to Present (eds. O. B. N., I. Daniel and R. Dasgupta). Leavitt W. (2020) Microbial methane from methylphosphonate Cambridge University Press, Cambridge, pp. 388–414. isotopically records source. Geophys. Res. Lett. 47(1), Young E., Kohl I., Lollar B. S., Etiope G., Rumble D., Li S., e2019GL085872. Haghnegahdar M., Schauble E., McCain K., Foustoukos D., Valentine D. L. (2011) Emerging topics in marine methane Sutclife C., Warr O., Ballentine C., Onstott T., Hosgormez H., biogeochemistry. Ann. Rev. Mar. Sci. 3(1), 147–171. Neubeck A., Marques J., Pe´rez-Rodrı´guez I., Rowe A., Valentine D. L., Chidthaisong A., Rice A., Reeburgh W. S. and LaRowe D., Magnabosco C., Yeung L., Ash J. and Bryndzia Tyler S. C. (2004) Carbon and hydrogen isotope fractionation L. (2017) The relative abundances of resolved 12CH2D2 and by moderately thermophilic methanogens 1 1Associate editor: 13CH3D and mechanisms controlling isotopic bond ordering in N.E. Ostrom. Geochim. Cosmochim. Acta 68(7), 1571–1590. abiotic and biotic methane gases. Geochim. Cosmochim. Acta Wang D. T., Gruen D. S., Lollar B. S., Hinrichs K.-U., Stewart L. 203, 235–264. C., Holden J. F., Hristov A. N., Pohlman J. W., Morrill P. L., Young E. D., Rumble D., Freedman P. and Mills M. (2016) A Konneke M., Delwiche K. B., Reeves E. P., Sutcliffe C. N., large-radius high-mass-resolution multiple-collector isotope Ritter D. J., Seewald J. S., McIntosh J. C., Hemond H. F., ratio mass spectrometer for analysis of rare isotopologues of Kubo M. D., Cardace D., Hoehler T. M. and Ono S. (2015) O_2, N_2, CH_4 and other gases. Int. J. Mass Spectrom. 401, Nonequilibrium clumped isotope signals in microbial methane. 1–10. Science 348(6233), 428–431. Yu X., Doroghazi J. R., Janga S. C., Zhang J. K., Circello B., White A. K. and Metcalf W. W. (2004) Two C-P lyase operons in Griffin B. M., Labeda D. P. and Metcalf W. W. (2013) Diversity pseudomonas stutzeri and their roles in the oxidation of and abundance of phosphonate biosynthetic genes in nature. phosphonates, phosphite, and hypophosphite. J. Bacteriol. Proc. Nat. Acad. Sci. 110(51), 20759–20764. 186(14), 4730–4739. Zhang X., Gillespie A. L. and Sessions A. L. (2009) Large D/H Yeung L. Y. (2016) Combinatorial effects on clumped isotopes and variations in bacterial lipids reflect central metabolic pathways. their significance in biogeochemistry. Geochim. Cosmochim. Proc. Nat. Acad. Sci. 106(31), 12580–12586. Acta 172, 22–38. Associate editor: Orit Sivan