Geobiology (2014), 12, 157–171

DOI: 10.1111/gbi.12075

Thermodynamic characterization of proton-ionizable functional groups on the cell surfaces of ammonia-oxidizing bacteria and archaea D. GORMAN-LEWIS,1 W. MARTENS-HABBENA2 AND D. A. STAHL2 1 2

University of Washington, Department of Earth and Space Sciences, Seattle, WA, USA University of Washington, Department of Civil and Environmental Engineering, Seattle, WA, USA

ABSTRACT The ammonia-oxidizing archaeon Nitrosopumilus maritimus strain SCM1 (strain SCM1), a representative of the Thaumarchaeota archaeal phylum, can sustain high specific rates of ammonia oxidation at ammonia concentrations too low to sustain metabolism by ammonia-oxidizing bacteria (AOB). One structural and biochemical difference between N. maritimus and AOB that might be related to the oligotrophic adaptation of strain SCM1 is the cell surface. A proteinaceous surface layer (S-layer) comprises the outermost boundary of the strain SCM1 cell envelope, as opposed to the lipopolysaccharide coat of Gram-negative AOB. In this work, we compared the surface reactivities of two archaea having an S-layer (strain SCM1 and Sulfolobus acidocaldarius) with those of four representative AOB (Nitrosospira briensis, Nitrosomonas europaea, Nitrosolobus multiformis, and Nitrosococcus oceani) using potentiometric and calorimetric titrations to evaluate differences in proton-ionizable surface sites. Strain SCM1 and S. acidocaldarius have a wider range of proton buffering (approximately pH 10–3.5) than the AOB (approximately pH 10–4), under the conditions investigated. Thermodynamic parameters describing proton-ionizable sites (acidity constants, enthalpies, and entropies of protonation) are consistent with these archaea having proton-ionizable amino acid side chains containing carboxyl, imidazole, thiol, hydroxyl, and amine functional groups. Phosphorousbearing acidic functional groups, which might also be present, could be masked by imidazole and thiol functional groups. Parameters for the AOB are consistent with surface structures containing anionic oxygen ligands (carboxyl- and phosphorous-bearing acidic functional groups), thiols, and amines. In addition, our results showed that strain SCM1 has more reactive surface sites than the AOB and a high concentration of sites consistent with aspartic and/or glutamic acid. Because these alternative boundary layers mediate interaction with the local external environment, these data provide the basis for further comparisons of the thermodynamic behavior of surface reactivity toward essential nutrients. Received 31 July 2013; accepted 16 December 2013 Corresponding author: Tel.: 2065433541; fax: (206) 543-0489; e-mail: [email protected]

INTRODUCTION Ammonia-oxidizing mesophilic and thermophilic Archaea affiliated with the Thaumarchaeota are widely distributed in marine and terrestrial environments and play an important role in the global nitrogen cycle (Francis et al., 2005; Koenneke et al., 2005; Schleper et al., 2005; Wuchter et al., 2006; Mincer et al., 2007; Hatzenpichler et al., 2008; de la Torre et al., 2008; Stahl & de la Torre, 2012). Nitrification, a two-step process in the oxidation of ammonia to nitrate, begins with the aerobic oxidation of ammonia to nitrite. Betaproteobacteria and Gammaproteobacteria were

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long thought to be the only two clades capable of using ammonia as their sole source of energy and electrons (Prosser, 1989; Prosser & Nicol, 2008); however, the isolation of Nitrosopumilus maritimus and subsequent in situ rate measurements in marine and terrestrial environments now indicate that ammonia oxidizing archaea (AOA) generally control this important step in the nitrogen cycle in both terrestrial and marine oligotrophic environments, presumably gaining competitive advantage over their bacterial counterparts because of their capacity for growth in environments where ammonium levels are below the growth threshold of ammonia-oxidizing bacteria (AOB) (>1 lM at pH 7) (Olson,

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1981; Hashimoto et al., 1983; Ward, 1987; Prosser, 1989; Bollmann et al., 2002; Yool et al., 2007). The one representative marine AOA currently available in pure culture, Nitrosopumilus maritimus strain SCM1 (strain SCM1), can sustain high specific rates of ammonia oxidation coupled with growth under ammonium concentrations well below the growth threshold for AOB (Martens-Habbena et al., 2009). The adaptations that allow strain SCM1 to subsist under such low ammonia concentrations are not known; however, reactions occurring on cell surfaces with exogenous nutrients might serve to concentrate and facilitate nutrient acquisition (Ferris & Beveridge, 1985). To determine whether there are substantial differences between cell surface reactivities of strain SCM1 and AOB, it is necessary to be able to quantitatively compare their reactivities. Metabolic investigations of strain SCM1 and AOB support suggestions that substrate availability accounts for the high AOA numbers commonly observed in ammonia-limited environments, as inferred by quantifying ammonia monooxygenase gene (amo) copy numbers (MartensHabbena et al., 2009). This work determined that the half-saturation constants (Km) for ammonium oxidation of strain SCM1 were two to three orders of magnitude lower than for AOB Nitrosomonas europaea (N. europaea) and Nitrosococcus oceani (N. oceani) (Martens-Habbena et al., 2009). The Km value for strain SCM1 compared favorably to in situ nitrification rates in oligotrophic marine environments, while the kinetic response of AOB was consistent with higher nutrients environments (Olson, 1981; Hashimoto et al., 1983; Ward, 1987; Martens-Habbena et al., 2009). It is clear that strain SCM1 has an unusually high affinity for ammonium; however, details of ammonium acquisition remain unknown. Nutrient acquisition by prokaryotes is diffusion limited, and cell shape and size is influenced by the competition for nutrients among other selective pressures (Koch, 1996; Schulz & Jorgensen, 2001; Young, 2006). Strain SCM1 cells are smaller than AOB resulting in a larger surfacearea-to-volume ratio (Okabe et al., 2004; Koenneke et al., 2005), which is a common adaptation for oligotrophic microbes (Young, 2006). A reactive microbial surface thermodynamically adapted to augment specific nutrient uptake would further enhance oligotrophic adaptations of smaller cells. The cell surfaces of strain SCM1 and Sulfolobus acidocaldarius (S. acidocaldarius) are comprised of a proteinaceous layer (S-layer) that is not present on AOB. S-layers consist of protein or glycoprotein that reside on the cell surface as either single or multiple layers; each layer can have distinctive lattice spacing and symmetry (Beveridge, 1994; Sleytr & Beveridge, 1999; Sara & Sleytr, 2000). Proteins and glycoproteins present numerous reactive functional groups that can participate in many processes that affect cellular function. No universal function for S-layers

has been identified; however, cellular processes that occur at the surface can be influenced or controlled by S-layers. Such processes include protection, cell adhesion, surface recognition, molecular sieving, ion trapping, and adsorption (Beveridge et al., 1997; Sleytr & Beveridge, 1999; Sara & Sleytr, 2000; Sleytr et al., 2001; Phoenix et al., 2005). Proton-ionizable functional groups in S-layer protein side chains provide cell surfaces with anionic oxygen, thiol, and amine ligands, which can participate in complexation reactions. Proteobacteria, the class to which AOB belong, are Gram-negative bacteria with cell surfaces comprising an outer membrane that differs substantially from proteinaceous S-layers covering strain SCM1. This outer membrane is composed of a core oligosaccharide; some bacteria also contain an O-specific oligosaccharide and lipid A, which is the phospholipid that anchors the core oligosaccharide (Nazarenko et al., 2003; Krasikova et al., 2004). In addition to the lipopolysaccharides (LPS), proteins are also embedded in and traverse the outer membrane; however, the amount of protein found within the outer membrane is likely an order of magnitude less than the amount of LPS present. Anionic oxygen within carboxyl and possibly phenolic functional groups and phosphates within lipid A are exposed to bulk solutions. Proteins embedded in the outer membrane can contain anionic oxygen, thiol, and amine ligands within proton-ionizable side chains. Thus, surface reactivity toward proton ionization of AOB is dominated by the functional groups found within the LPS. In contrast, strain SCM1 surface reactivity is dominated by functional groups on amino acids or associated with protein glycosylation. Key nutrients first encounter the cell surface before they are actively transported into the cell. Under nutrientlimited conditions, it would be extremely advantageous if the initial passive interactions that bring key nutrients to the cell wall were thermodynamically favored over interactions with non-nutrient solutes. This type of adaptive advantage would depend on cell wall compositions, on thermodynamic properties of the reaction between the nutrient and ligand on the cell surface, and on the system’s aqueous chemistry. Identifying and quantifying the surface functional groups that are likely to be involved in the initial passive interactions is the first step in investigating the links between surface interactions and nutrient acquisition in ammonia-oxidizing micro organisms. To probe the identity and relative abundance of protonionizable functional groups that might be important for nutrient acquisition such as ammonium, we performed potentiometric and isothermal calorimetric titration experiments on suspensions of Nitrosomonas europaea (N. europaea), strain SCM1, Nitrosococcus oceani (N. oceani), Nitrosolobus multiformis (N. multiformis), Nitrosospira briensis (N. briensis). To further characterize the S-layer,

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AOA and AOB surface characterization we also investigated the surface proton ionization of S. acidocaldarius to provide a comparison of strain SCM1 with a non-ammonia-oxidizing archaeon. We derived thermodynamic parameters describing proton ionization using a surface complexation model. The results show that strain SCM 1 has more reactive surface sites than the AOB and S. acidocaldarius, with a different composition that deprotonate in circumneutral pH. This now provides a foundation for developing a more mechanistic understanding of the ability of marine AOA to subsist at vanishingly low concentrations of ammonia.

MATERIALS AND METHODS Culturing conditions described below represent the optimum growth conditions for laboratory cultures of the microbial species used. Minimum and maximum pH for AOB growth is approximately 6.9 and 8.2, respectively (Sato et al., 1985). Minimum and maximum pH for strain SCM1 is approximately 7.1–7.5 (Koenneke et al., 2005; Martens-Habbena et al., 2009). Minimum and maximum pH for S. acidocaldarius is approximately 2–4 (Lewus & Ford, 1999). Cultures of strain SCM1 and N. oceani were maintained in a synthetic crenarchaeota medium as described earlier (Koenneke et al., 2005). The basal artificial sea water was autoclaved at 121 °C for 15 min, cooled to room temperature, and supplemented with the following sterile solutions (per liter): 10 mL HEPES (1 M HEPES, 0.6 M NaOH, pH 7.8), 2 mL sodium bicarbonate (1 M), 5 mL KH2PO4 (0.4 g L
1), 1 mL FeNaEDTA (7.5 mM), 1 mL modified non-chelated trace element solution. The trace element solution contained (per liter) 8 ml concentrated HCl (approximately 12.5 M), 30 mg H3BO3, 100 mg MnCl2∙4H2O, 190 mg CoCl2∙6H2O, 24 mg NiCl2∙6H2O, 2 mg CuCl2∙2H2O, 144 mg ZnSO4∙7H2O, 36 mg Na2MoO4∙2H2O. The medium was supplemented with 1 mL and 10 mL of NH4Cl (1 M) for strain SCM1 and N. oceani cultures, respectively. The final pH of this medium at 30 °C was approximately 7.5. Cultures were transferred (0.1–1% inoculum size) to fresh medium when 2/3 of the ammonium was oxidized. Shaking and stirring were avoided. Nitrosomonas europaea and N. multiformis were grown in liquid media containing 12.5 mM (NH4)2SO4 and 50 mM HEPES (pH 7.5 at 30 °C) supplemented with the following: 150 lM CaCl2, 150 lM MgSO4, 5 lM FeNa EDTA, 250 lM KH2PO4, 1.5 mM NaHCO3, 41 nM NaMoO4, 120 nM MnCl2, 0.84 nM CoCl2, 35 nM ZnSO4, 8 nM CuSO4, and 0.0003% phenol red as a pH indicator as previously described (Berube et al., 2007). Cultures were transferred (0.1–1% inoculum size) to fresh media when 2/3 of the ammonium was oxidized.

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159

Nitrosospira briensis was grown in liquid media containing 3 mM (NH4)2SO4, 30 mM HEPES (pH 7.8), 10 mM NaCl, 1 mM KCl, 0.2 mM MgSO4∙7H2O, 1 mM CaCl2, 0.4 mM KH2PO4, 41 nM NaMoO4, 9 lM MnCl2∙4H2O, 0.84 nM CoCl2, 35 nM ZnSO4, and 8 nM CuSO4. Cultures were transferred (0.1–1% inoculum size) to fresh media when 2/3 of the ammonium was oxidized. Sulfolobus acidocaldarius was grown in liquid media containing 1 g L
1 tryptone, 0.05 g L
1 yeast extract, 10 mM (NH4)2SO4, 1 mM MgSO4∙7H2O, 5 mM CaCl2∙2H2O, 2 mM KH2PO4, 22 lM Na2B4O7, 75 lM FeCl3∙6H2O, 124 nM NaMoO4, 120 nM MnCl2, 66 nM CoSO4, 150 nM VOSO4∙2H2O, 77 lM ZnSO4∙7H2O, and 8 nM CuCl2∙2H2O. The pH of the medium was adjusted to 3 with H2SO4, and the cultures were grown at 70 °C. Cultures were transferred (10% inoculum size) to fresh medium after 6 to 7 days. Biomass for experiments was harvested from culture via centrifugation or filtration with Millipore polycarbonate 0.2-lm filters when cells reached stationary phase. Cells were washed three times with 0.1 M NaClO4. Washing the cells involved suspending the biomass in the electrolyte solution and vortexing for 15 s, then reharvesting the cells via centrifugation and decanting the supernatant or filtering the suspension, and replacing the electrolyte with fresh solution and repeating the process two additional times. Differential staining of strain SCM1, N. oceani, and N. europaea after harvest revealed approximately 90% of cells intact, which is consistent with previous work showing that this biomass preparation procedure does not substantially lyse cells (Gorman-Lewis, 2011). Calorimetric and potentiometric titrations Calorimetric titrations were conducted with a TA Instruments TAM III Nanocalorimeter that measures the heat flow between a reaction cell and a reference cell (Johansson & Wads€ o, 1999; Wads€ o & Goldberg, 2001). The heat flow response by the calorimeter was calibrated by electrical heating, a procedure verified by measuring the heat of protonation of trishydroxymethylaminomethane (TRIS/ THAM) at 25 °C (Grenthe et al., 1970). Both cells were filled with identical microbial suspensions in 0.1 M NaClO4 and placed in the calorimeter. The reaction cell was stirred at 200 rpm and lowered into the calorimeter in 4 steps, pausing with each step to allow the calorimeter to equilibrate. After achieving thermal equilibration and a stable heat flow (i.e., signal deviation was less than 200 nW over 15 min), a cannula from a computer-controlled 250-lL syringe delivered a predetermined number of individual titrant doses into the reaction cell. A period of 5–10 min followed titrant additions and the heat flow after each addition was continuously monitored.

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Note that because the calorimeter’s design does not provide convenient way to maintain a CO2-free atmosphere; therefore, to eliminate as much CO2 adsorption as possible into the bacterial suspension, the 0.1 M NaClO4 was purged with N2 for 1 h prior to resuspending the bacteria. The suspension was immediately transferred to a glove box with an N2 atmosphere where the initial pH of the suspension was adjusted with HClO4 and carbonate-free NaOH. The electrolyte and acid were chosen so that the dominant anions in solution matched to minimize the heat of dilution with each addition and give comparable results to previous studies. The reaction and reference cells were loaded and sealed in the glove box and immediately transferred out of the glove box and placed in the calorimeter. The suspensions were allowed to equilibrate in the calorimeter at the experimental temperature. Measuring pH during the titration is not possible due to the design of the calorimeter. Therefore, we performed simultaneous titrations with either 0.010 or 0.021 M HClO4 on analogous systems outside the calorimeter (non-calorimetric titration), meaning that biomass suspensions identical to those in the calorimeter were placed in a thermostated reaction vessel outside the calorimeter where pH and temperature were monitored continuously recording data every 3 seconds with each addition of acid delivered by another syringe controlled by the same apparatus delivering identical titrant doses to the reaction vessel inside the calorimeter. An equilibration criterion was determined by the calorimetric heat flow signal returning to the baseline, which occurred after 5–10 min after the titrant dose. Two to four replicate measurements were made for each microbial species investigated. The combination pH electrode was calibrated daily with four NIST standards. At the end of the simultaneous titrations, pH measurements of the biomass suspension in the calorimeter and in the external reactions were within approximately 0.03 pH units. The reversibility of the titration was tested after the initial titration by adjusting the pH of the non-calorimetric suspension back up to approximately 9–10 and titration down in pH. The amount of biomass used in each experiment was determined at the end of the titrations by filtering the suspension onto pre-weighed filters and correcting for electrolyte contribution. Filters were dried at 40 °C until weight was constant. Each filter was weighed five times with a Mettler Toledo semi-micro-analytical balance with an uncertainty of approximately 20 lg determined from two times the standard deviation of five replicate measurements. Microbial species used in these experiments grow to maximum cell densities of approximately 107–109 cells per mL; consequently, the range of biomass used in these experiments varied from approximately 100 lg to 40 mg dry weight. The ratio of wet to dry biomass for species used in these experiments is approximately 4–12 (data not shown).

Obtaining heats associated with the reactions on the cell wall or S-layer after the ith addition of titrant (Qicorr) requires a background correction to subtract the heats associated with the reactions intrinsic to the titration process. Background heats (Qibkg) were measured by titrating an identical amount of titrant to a biomass-free system and then subtracting it from the experimentally measured heat (Qiexp) associated with a given titrant addition (equation 1). exp

Qicorr ¼ Qi

bkg


Qi

ð1Þ

This correction is independent of pH and accounts for the heat of dilution and other heats intrinsic to the titration process. In addition, when the pH of the solution exceeds pH approximately 8.5, it is necessary to account for the heat of hydroxide neutralization associated with the reaction H+ + OH ? H2O that occurs with the addition of acid. The enthalpy of this reaction was estimated to be
56.20 kJ per mol at 25 °C by interpolating the heats of NaOH neutralization reported for HCl solutions with ionic strength of 0.11 M (Grenthe et al., 1970). For our experiments, the heat of hydroxide neutralization with each addition was calculated from the enthalpy of neutralization, pH, concentration of the protolyzable biomass surface sites and pKa values of those sites and was included in the Qibkg term in equation 1. Derivation of model parameters Surface complexation models The model parameters that describe proton uptake by bacterial surfaces – acidity constants, site concentrations, and enthalpies of adsorption – are derived in two separate processes. Acidity constants and site concentrations are derived from modeling potentiometric titrations, and enthalpies of proton adsorption are derived from combining the isothermal titration calorimetry (ITC) data with the previously determined surface complexation modeling. We used ProtoFit (Turner & Fein, 2006), a software program for the analysis of potentiometric titration data from proton-ionizable surface, to derive acidity constants and site concentrations from the potentiometric titration data. ProtoFit defines the partitioning of protons in experimental systems using the following equation: DnðH þ; total; iÞ ¼ DnðH þ; wat; iÞ þ DnðH þ; ads; iÞ

ð2Þ

where Dn(H+,total,i) refers to the moles of protons added to the system as a whole (total), Dn(H+,wat,i) refers to the moles of protons added to the water, and Dn(H+,ads,i) refers to the moles of protons added to the bacterial surface from the beginning of the titration to step i. To calculate Dn(H+,total,i), which represents the amount of acid added to the system, we used the total volume of

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AOA and AOB surface characterization acid added at step i and the normality of the acid. The number of protons exchanged with water during the titration was found by speciating the solution using the measured pH values. The value of Dn(H+,ads,i) was the difference between the total number of protons added to the system (Dn(H+,total,i)) and the protons added to the water (Dn(H+,wat,i)). The bacterial surface is composed of a variety of protonionizable ligands that have been described by discrete binding sites (Fein et al., 2005; Heinrich et al., 2008; Tourney et al., 2008). Using a discrete site model, the moles of protons added to the bacterial surface (Dn(H+,ads, i)) are distributed to different types of sites. This can be represented by the generalized proton adsorption reaction described by equation 3, where R is a bacterium to which a proton-ionizable functional group L of type y is attached. R
Ly
þ H þ ¼ R
Ly H 

ð3Þ

We assume that negatively charged functional groups individually could only adsorb one proton. However if amphoteric sites are present on the bacterial surface and the difference in acidity constants of the deprotonations is large enough, amphoteric sites would be treated as 2 separate sites with our assumption rather than one site with two deprotonations. The proton-binding constant Ky for equation 3 can be expressed by equation 4, where ½R
Lyi  and ½R
Ly H o  represent the concentration of deprotonated and protonated sites, respectively, for site Ly and where aH+ represents the activity of protons in the bulk solution. ½R
Ly H   Ky ¼ ½R
Ly
aðH þÞ

Electric double-layer interactions are not taken into account in equation 4 because of the lack of consensus on how to model electrostatic effects on bacterial surfaces, the extent of their influence on proton uptake, and the overestimation of electrostatic effects (Plette et al., 1995; Fein et al., 1997, 2005; Daughney & Fein, 1998; Martinez et al., 2002; Ngwenya et al., 2003; Haas, 2004). In addition, the purpose of this work is to derive internally consistent parameters to use in comparing surface properties among the species investigated; it is therefore preferable to eliminate any unnecessary complexity added by considering electrostatics. Reactions of the electrolyte with the surface are not considered during the modeling; however, the same electrolyte is used in all experiments. Therefore, model parameters for the investigated biomass can be meaningfully compared. The total proton uptake is the result of each discrete site Ly−

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adsorbing protons from the beginning of the titration i ðDnðHL Þ, as described in equation 5. yÞ DnðH þ; ads; iÞ ¼

z X ði¼1Þ

i DnHL ¼ y

z X

Vi  ½R
Ly H  

ð5Þ

ði¼1Þ

Our strategy for deriving acidity constants for discrete sites and site concentrations that described the potentiometric titration data was to start with a one-site model, and then add reactions as necessary so that the model would adequately represent the data. Initial guesses for fitted parameters were taken from previous studies and optimizations were run iterating over each initial guess three times changing the initial acidity constants by 1 log unit and changing the initial log site concentrations by 0.5. For example, a three-site model required 729 optimizations. We used F-tests to determine whether adding sites to the models significantly improved the fit (P < 0.05). The pH range of the data collected will influence the number of sites necessary to model the proton-buffering capacity of microbial surfaces; therefore, the number of sites determined in our models might not fully capture protonbuffering capacity at and beyond the extremes of the pH range tested. Derivation of enthalpies of protonation The corrected heats of protonation (Qicorr) are related to the site-specific enthalpies of protonation (DHHLy) by equation 6, where dniHLy is the change in the number of moles of the protonated sites caused by the ith addition of titrant.


ð4Þ

161

X

Qicorr ¼

X

DHHLy 

X

i dnHL y

ð6Þ

The dniHLy values (a function of pH, Ky, site concentrations, and volume of acid added) and the site-specific enthalpies determine the total heat produced with each addition of acid. We used pH and volume of acid added as independent variables to calculate dniHLy values using the surface complexation model derived from the potentiometric titration data and to subsequently derive sitespecific enthalpies through optimization by minimizing the sum-of-squares difference between the measured experimental heats Qicorr and the model-derived heats Qicalc. Uncertainties in the model parameters are given at the 1 r confidence level and are calculated from the inverse covariance matrix of a given fit. Discrepancies between the data and the fit of equation 6 could be due to the surface complexation model not fully capturing protonation of the surface and sensitivity differences between calorimetry and potentiometric titrations. Calori-

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metric titrations might detect additional functional groups that are not detected in the potentiometric titrations nor accounted for in the surface complexation model.

RESULTS Potentiometric titrations and surface complexation modeling Figure 1 illustrates the buffering function (Q* = (dQ / dpH), where Q is the number of protons exchanged with the adsorbent) normalized per gram of dry biomass as a function of pH for all species investigated. The protonbuffering function represents the proton-buffering capacity of the surface as a function of pH. ‘Peaks’ in the protonbuffering function are centered around ionizable functional groups. ‘Narrow’ peaks indicate that a single functional group is responsible for proton buffering, while ‘broader’ peaks indicate that multiple functional groups are responsible for buffering (Turner & Fein, 2006). Reversibility titrations for all species investigated were consistent with initial titrations. All freshwater species, N. briensis (Fig. 1A), N. europaea (Fig. 1B), and N. multiformis (Fig. 1D), exhibited proton buffering at high pH (above pH 9) and from approximately pH 5–6.5. N. briensis and N. multiformis displayed additional proton buffering at approximately pH 7.5–8. Buffering capacity was near zero for all freshwater species around pH 4. Marine species, strain SCM1 (Fig. 1C) and N. oceani (Fig. 1E), exhibited proton-buffering similarities to freshwater species. Strain SCM1 and N. oceani both displayed proton buffering at approximately pH 6 and above pH 9. Similar to N. briensis and N. multiformis, the marine species displayed proton buffering at approximately pH 7.5–8. Strain SCM1 exhibited a broad proton-buffering peak from approximately pH 8–9, while N. oceani exhibited a smaller proton-buffering peak from approximately pH 7–8. N. oceani exhibited zero buffering capacity near pH 4; however, strain SCM1 exhibited a rise in proton buffering from pH 5 to 4 that declined just below pH 4. Overall, strain SCM1 exhibited greater proton buffering over the pH range investigated. Sulfolobus acidocaldarius displayed proton buffering down to a lower pH than the ammonia-oxidizing species investigated. A broad proton-buffering peak is evident between pH 3 and 5. Similar to N. oceani, S. acidocaldarius exhibited proton buffering between pH 6 and pH 7. Above pH 9 and similar to ammonia-oxidizing species, S. acidocaldarius exhibited maximum buffering at high pH (appeared to be above pH 10). The surface complexation models describing protonation of the microbial surfaces consisted of three or four discrete sites. All models required one site with a high log K

(between 9 and 10), while log K values for the other sites were between approximately 3 and 8. These models are summarized in Tables 1 and 2. All AOB were successfully modeled with three-site models (Table 1). Most of the proton-buffering capacity is described with log K values above approximately 6, with the exception of N. europaea, which has one low log K site of 4.5. The absence of low log K sites for N. briensis, N. multiformis, and N. oceani does not mean that functional groups with low protonation constants are absent on the bacterial surfaces, but indicates that our titration data could not detect significant buffering at low pH. All AOB had sites with log K values at approximately 6 and 10. N. briensis, N. multiformis, and N. oceani all had sites with protonation constants of approximately 8; however, this site was absent on N. europaea. Site concentrations normalized to dry weight are consistent with other investigations that were normalized to dry weight (Tourney et al., 2008). Considering the wet-to-dry biomass ratios of approximately 4–12, site concentrations found for AOB are also consistent with site concentrations normalized to wet weight (Borrok et al., 2005). Sulfolobus acidocaldarius and strain SCM1 were modeled with four-site models (Table 2). The distribution of log K values for the archaea is different, with S. acidocaldarius log K values of 3.6, 4.6, 6.6, and 9.9 and with strain SCM1 log K values of 3.9, 6.1, 8.2, and 9.3. Site densities are also consistent with previous investigations considering wet-to-dry biomass ratios of approximately 4–12 (Borrok et al., 2005; Tourney et al., 2008). Most of the proton-buffering capacity of strain SCM1 centers on sites with log K values of 3.3 and 6.7, while S. acidocaldarius sites densities increase with increasing log K values. Calorimetric titrations Figure S1 in the Supplemental Materials shows representative samples of raw calorimetric signals for all species investigated. Each addition of acid produced a strong exothermic signal, with the magnitude of the signal decreasing as the pH decreased. Background heat flows (not shown) were an order of magnitude smaller than the experimental heat flow down to approximately pH 4.5. Below pH 4.5, the background heat flow was approximately one-third of the experimental heat flows. Figure 2 shows the total corrected heats of protonation as a function of added moles of H+. Further data interpretation requires the application of a surface complexation model to the calorimetric data. For this reason, thermodynamic parameters derived by combining surface complexation modeling with calorimetric data describing surface site protonation are model dependent. Applying the surface complexation models described above (Table 1 and 2) enabled the derivation of enthal-

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AOA and AOB surface characterization A

1.5

163

D 1.4

1

Q* (eq kg−1 (log aH+)−1)

Q* (eq kg−1 (log aH+)−1)

1.2

0.5

0

1 0.8 0.6 0.4 0.2 0 −0.2

−0.5 4

5

6

7

8

9

10

4

5

6

7

pH

B

8

9

10

pH

E

0.4

1.5

Q* (eq kg−1 (log aH+)−1)

Q* (eq kg−1 (log aH+)−1)

0.3 0.2 0.1 0

1

0.5

0

−0.1 −0.5

−0.2 3

4

5

6

7

8

9

10

3

4

5

6

1

F

Q* (eq kg−1 (log aH+)−1)

Q* (eq kg−1 (log aH+)−1)

C

7

8

7

8

9

10

pH

pH

0.5

0

−0.5

1.5

1

0.5

0 4

5

6

7

8

9

10

pH

3

4

5

6

9

10

pH

Fig. 1 The ProtoFit buffering function [Q* = (dQ ∕d(pH)], normalized per dry gram of biomass and plotted as a function of pH for (A) Nitrosospira briensis, (B) Nitrosomonas europaea, (C) Nitrosolobus multiformis, (D) Nitrosococcus oceani, (E) Nitrosopumilus maritimus strain SCM1, and (F) Sulfolobus acidocaldarius.

pies of protonation (DHr) from the total corrected heats. We calculated additional thermodynamic parameters of protonation (Gibbs energy [DGr] and entropy [DSr])

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according to equations 7 and 8, where R is the gas constant and T is absolute temperature (errors propagated through equations 7 and 8 represent 1 r).

DG ¼
2:3026  R  T  logK

ð7Þ

DG ¼ DH
T  DS

ð8Þ

7.7  0.1 2512  377
43.7  0.6
2.9  0.2 +137  2 Phosphate 6.1  0.2 1549  387
35.0  1.1
10.9  0.3 +81  4 Phosphate

DISCUSSION

     7.5 389
42.5
31.2 +38 Thiol 5.8  0.2 741  185
33.4  1.1
9.4  1.3 +80  6 Phosphate 0.1 140 0.6 1.6 6      9.6 933
55.0
30.8 +81 Amine 0.1 52 0.6 4.0 14      7.7 347
43.8
28.4 +52 Thiol

with 1 r errors reported. M, þ  *According to the reaction R
L
i þ H $ R
Li
H for ionic strength of 0.1 †Normalized to dry weight.

4.8  65 
27.7  +3.7  +105  Carboxyl 6.1  0.2 1380  345
35.0  1.1
4.2  0.9 +103  5 Phosphate log K [sites] (lmol g
1)† DG (kJ mol
) DH (kJ mol
) DS (J molK
) Suggested site identity

0.2 16 1.1 0.1 4

Nitrosomonas europaea Nitrosospira briensis Parameter*

6.3  0.2 263  66
35.8  1.1
0.3  0.0 +119  4 Phosphate

9.6 170
54.6
29.1 +86 Amine

    

0.1 25 0.6 0.6 3

Nitrosolobus multiformis

0.1 58 0.6 2.5 9

9.7 631
55.3
42.4 +43 Amine

    

0.1 95 0.6 1.8 6

Nitrosococcus oceani

9.7 513
55.1
39.6 +52 Amine

    

0.1 77 0.6 1.5 5

D. GORMAN-LEWIS et al.

Table 1 Ammonia-oxidizing bacteria

164

Interpretation of the thermodynamic data derived with surface complexation modeling and calorimetric data can provide information about possible surface site identity and about the thermodynamic driving force of the reactions. It is important to note that the magnitude of the buffering function and the magnitude and direction of corrected heats of protonation are direct measurements that quantitatively describe the extent of proton buffering and heat evolved in the systems studied and derived thermodynamic parameters are model dependent. Therefore, application of different models to the proton uptake data might yield alternate conclusions. However, previous calorimetric investigations of microbial surface reactivity resulted in similar conclusions when testing different surface complexation models on the same dataset (Gorman-Lewis et al., 2006; Gorman-Lewis, 2009). Although thermodynamic data cannot provide conclusive evidence of site identity, previous calorimetric investigations of surface reactivity are consistent with spectroscopic investigations of surface site identity, and a combined calorimetric/surface complexation modeling approach provides data that cannot be determined using other techniques (Gorman-Lewis et al., 2006; Gorman-Lewis, 2011). However, care should be taken when comparing the present data to previous work where experimental or modeling considerations differed substantially (i.e., electrostatic versus non-electrostatic models). Based on the protonation constant, surface sites with log K values above 9 are likely to be either amine or phenolic functional groups (Fein et al., 1997; Burnett et al., 2006; Deo et al., 2010). Protonated amines and phenols typically have log K values between 8.5 and 10.5 (Christensen et al., 1976; Martell et al., 1998). Table 3 shows that enthalpies of amine and phenolic protonation are similar; however, entropies of amine and phenolic protonation are distinct (Christensen et al., 1976; Martell et al., 1998). Both types of functional groups are found within structures of Gram-negative and S-layer cell surfaces; the N-terminus of amino acids found in porins and other proteins as well as the lysine side chain and phenolic functional groups is also found in porins and other proteins containing tyrosine (Rosenbusch, 1990; Nikaido, 2003; Kalmokoff et al., 2009; Prehna et al., 2012). Sites with high log K values on N. briensis, N. europaea, strain SCM1, N. multiformis, and N. oceani are consistent with amine functional groups. The high log K site of S. acidocaldarius is more consistent with the phenolic side chain protonation

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165

Table 2 Crenarchaeota Parameter*

Nitrosopumilus maritimus strain SCM1

log K [sites] (lmol g
1)† DG (kJ mol
1) DH (kJ mol
1) DS (J mol K
1) Suggested site identity

3.9  0.2 2042  510
22.4  1.1
2.4  0.4 +67  4 Carboxyl/ aspartic and glutamic acid

6.1  0.1 617  92
34.6  0.6
17.3  0.9 +58  4 Imidazole/ histidine

8.2  0.1 1549  232
47.0  0.6
23.5  0.7 +79  3 Thiol and/or phosphate

Sulfolobus acidocaldarius 9.3 794
53.1
27.3 +87 Amine

    

þ  *According to the reaction R
L
i þ H $ R
Li
H for ionic strength of 0.1 †Normalized to dry weight.

of tyrosine, which has been identified within its S-layer (Veith et al., 2009); however, it is likely that amine functional groups also contribute to this reactivity at high pH but that the signal is undetectable because of the more exothermic nature of phenolic protonation. Surface sites with log K values between approximately 6 and 8 are likely to be either phosphonate or thiol functional groups. Other workers have identified both types of functional groups on microbial surface investigations with extended X-ray adsorption spectroscopy (EXAFS) (Boyanov et al., 2003; Mishra et al., 2009). Thiol functional groups are found within cysteine, which can be found within proteins embedded in the lipopolysaccharide outer membrane of Gram-negative bacteria or within S-layer proteins. Phosphonates have a wider range of log K values influenced by the structure surrounding the functional group (Christensen et al., 1976). Enthalpies and entropies of protonation of organophosphates and phosphonates are similar, while thermodynamic parameters of thiols are distinct (Table 3). Phosphomonoester and phosphodiesters are generally considered to be the phosphate-bearing functional groups within the lipid A portion of the lipopolysaccharides and in the headgroup of the phospholipid layers (Beveridge & Murray, 1980; Guine et al., 2006). Because of the overlap in log K values, distinguishing between protonation of phosphorous-bearing functional groups and thiols based only on potentiometric titration data is not possible. Using potentiometric data combined with calorimetric data, however, takes advantages of the distinct enthalpies of protonation and makes it possible to interpret whether a combination of sites is present. The large exothermic enthalpy of thiol protonation could overshadow the enthalpic signal of phosphorous-bearing groups with log K values close to 8 if thiol groups are abundant; however, if few thiols are present and abundant phosphorous-bearing groups are present, one would expect enthalpies of protonation to be less exothermic than thiol protonation and slightly more exothermic than phosphoester or phosphonate protonation. Another possibility for a site with log K values of approximately 6 is imidazole, which is found on the histidine side chain. Previous workers have found histidine residues within

© 2014 John Wiley & Sons Ltd

0.2 199 1.1 1.6 7

M,

3.6  0.1 363  54
20.5  0.6
7.3  2.6 +44  9 Carboxyl/aspartic and glutamic acid

4.6  0.1 389  58
26.1  0.6
6.2  2.3 +67  8 Carboxyl/aspartic and glutamic acid

6.6  0.2 1380  345
37.9  1.1
15.8  0.3 +74  4 Imidazole/ histidine

9.9  1995 
56.5 
24.6  +107  Phenol

0.2 499 1.1 0.4 4

with 1 r errors reported.

porin proteins, and they might be components in other outer membrane proteins (Kalmokoff et al., 2009; JimenezMorales & Liang, 2011; Prehna et al., 2012). The overlap in log K values for phosphonates and imidazoles makes it difficult to distinguish between them with potentiometric titration data alone; however, the enthalpies and entropies of imidazole protonation (Table 3) can be used to evaluate whether a combination of sites is present, similar to an analysis of thiol- versus phosphorous-bearing groups. AOB species, N. briensis, N. europaea, N. multiformis, and N. oceani, have sites that are consistent with thiols and/or phosphonates (Tables 1 and 3). N. briensis has one site with a log K of 7.7, which has an enthalpy and entropy of protonation most consistent with thiol functional groups. In addition to this site, N. briensis and N. europaea have sites with log K values of 6.1 and 6.3, respectively, which are most consistent with phosphate reactivity. N. multiformis and N. oceani have sites with log K values of 7.5 and 7.7, respectively. While these sites have similar log K values, their enthalpies and entropies of protonation are distinct, suggesting that the thermodynamic parameters for N. multiformis are due to thiol reactivity, while N. oceani posses more phosphate reactivity. N. oceani also has an additional site which has an enthalpy and entropy of protonation consistent with phosphate reactivity and a log K value of 6.1. Because the cell surfaces of strain SCM1 and S. acidocaldarius are covered in proteins, it is likely that protonionizable side chains in amino acid will dominate surface reactivity. S. acidocaldarius has one site with a log K of 6.6, which has an enthalpy and entropy of protonation consistent with imidazole protonation in histidine and possibly the first protonation of an organophosphate. Histidine has been identified in S-layer proteins of S. acidocaldarius (Veith et al., 2009); therefore, we conclude that histidine is responsible for this reactivity. Strain SCM1 has one site with a log K of 8.2, which has an enthalpy and entropy of protonation between the expected value of thiol- and phosphorous-bearing functional groups. This value suggests the presence of both types of sites on the cell surface. Strain SCM1 also has one site with a log K of 6.1, which has an enthalpy and entropy most consis-

166

D. GORMAN-LEWIS et al. D

A

16

16 14 14 12 −ΣQcorr (mJ)

−ΣQcorr (mJ)

12 10 8 6 Biomass dry weight 250 μg

4

6 Biomass dry weight 110 μg 210 μg 320 μg

2

210 μg

0

0 0

B

8

4

300 μg

2

10

0.2

0.4 0.6 0.8 μmole H+ added

1

1.2

18

0

0.2

0.4

0.6 0.8 μmole H+ added

1

1.2

1.4

14

E

16

12

14 −ΣQcorr (mJ)

−ΣQcorr (mJ)

10 12 10 8 6

Biomass dry weight 11 010 μg

4

6 Biomass dry weight 100 μg

4

35 120 μg

2

8

120 μg

2

35 170 μg

130 μg

0

0 0

0.5

1

1.5

2

2.5

0

0.2

0.4

0.6

μmole H+ added

C

0.8

1

1.2

1.4

μmole H+ added

20

F 120

18 100

16

12 Biomass dry weight 110 μg

10 8

290 μg

6

360 μg

−ΣQcorr (mJ)

−ΣQcorr (mJ)

14

80 60 40

4

Biomass dry weight 2010 μg 2060 μg 860 μg 1640 μg

20

2 0

0 0

0.2

0.4

0.6

0.8

1

1.2

1.4

μmole H+ added

0

2

4

6

8

10

12

μmole H+ added

Fig. 2 Corrected total heats of proton adsorption versus lmoles of H+ added for (A) Nitrosospira briensis, (B) Nitrosomonas europaea, (C) Nitrosolobus multiformis, (D) Nitrosococcus oceani, (E) Nitrosopumilus maritimus strain SCM1, and (F) Sulfolobus acidocaldarius. The curve represents the fit of model parameters to equation 6.

tent with imidazole reactivity in histidine; however, phosphorous-bearing groups with similar protonation constants could also be contributing to this site. Histidine and

cysteine have both been identified as minor components in the strain SCM1 S-layer (pers. comm. D.A. Stahl) and are known to be components in S-layers of other species

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167

Table 3 Approximate thermodynamic parameters for acidic functional groups. Functional group

log K

DH (kJ mol
1)

DS (J mol K
1)

Reference

Amine Phenol Thiol

8.5 to 10.5 10 8


30 to
50
35 to
55
25 to
40

+20 to +50 +90 to +120 +25 to +45

Phosphonate/organophosphate

2 to 10


2 to
15

+60 to + 130

Imidazole Multifunctional carboxylic acids Monofunctional carboxylic acids

6 to 8 3.5 to 5 3.5 to 5


13 to
20
3 to
8 0 to +5

+20 to +70 +50 to +80 +80 to +120

Christensen et al. (1976), Martell et al. (1998) Christensen et al. (1976), Martell et al. (1998) Wrathall et al. (1964), Coates et al. (1969), Takeshima & Sakurai (1982), Rodante (1989) De Stefano et al. (2004), Jensen et al. (2000), Martell et al. (1998), Nash et al. (1995), This work Christensen et al. (1976), Martell et al. (1998), Pettit & Powell (2005) Christensen et al. (1976), Martell et al. (1998), Pettit & Powell (2005) Christensen et al. (1976), Martell et al. (1998), Pettit & Powell (2005)

Parameters describe the following reaction where L is the functional group: Li þ Hþ R
LH.

(Veith et al., 2009). While histidine and cysteine are implicated as cell surface components, Metcalf et al. (2012) speculates, based on 31P NMR experiments and gene context, that the surface contains an exopolysaccharide decorated with methylphosphonate. Biomass harvesting procedures include washing steps primarily to remove residual culture media; however, it is possible that exopolysaccharides survived the washing procedure. Therefore, thermodynamic parameters determined in this work should be regarded as representing the whole cell envelope, which may include surface-associated extracellular material. Thermodynamic parameters of methylphosphonate protonation are much less exothermic than imidazole or thiol functional groups (see Supplemental Materials and Table S3) and the presence of methylphosphonate could be masked by both cysteine and histidine as the protonation of those side chains is approximately 10–20 times more exothermic. Surface sites with log K values between approximately 3.5 and 5 are likely to be carboxylic acid functional groups. Previous spectroscopic work has identified carboxylate groups on the surface and their participation in metal binding to bacterial surfaces (Kelly et al., 2002; Boyanov et al., 2003; Wei et al., 2004; Yee et al., 2004). The thermodynamic characteristics of multifunctional carboxylic acids differ from monofunctional acids in that the enthalpies become more exothermic as multiple protonations occur, and the entropies are positive but smaller (Table 3). Glutamic and aspartic acid are good examples of this difference. Smaller entropies for multifunctional acids occur because hydrogen bonding with deprotonated oxygen atoms stabilizes the protonated functional group, creating a more ordered system (King, 1965; Nancollas, 1966). While surface sites with log K values from approximately 3–4 could be carboxylic acids, they could also be subsequent protonations of phosphorous-bearing functional groups. Spectroscopic measurements support phosphonate assignments at low pH (Sokolov et al., 2001; Kelly et al., 2002; Martinez et al., 2002; Guine et al., 2006). Enthalpies of second and third protonations of phosphonates are similar to carboxylic acids; however, entropies of proton-

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ation are typically smaller than those of carboxylic acids, making it possible to distinguish between the two sites. Under our experimental conditions, N. europaea, strain SCM1, and S. acidocaldarius are the only species to have significant proton-buffering capacity below pH 5. N. europaea and strain SCM1 have sites with log K values of 4.8 and 3.9, respectively, which have an enthalpies and entropies of protonation most consistent with glutamic and/or aspartic acid. The ability to measure proton buffering at low pH is dependent not only on the presence of surface sites with low acidity constants but also on sufficient biomass to create a buffering signal detectable above that associated with proton exchanged with water. Low cell densities of strain SCM1 cultures make it experimentally difficult to produce a concentrated cell suspension, which makes it difficult to differentiate between one or two sites (glutamic acid or both glutamic and aspartic acid). Both glutamic and aspartic acid are known components in S-layers (Claus et al., 2002; Veith et al., 2009) and have both been identified as major components in the strain SCM1 S-layer (pers. comm. D.A. Stahl). Sulfolobus acidocaldarius has two sites with low log K values of 3.6 and 4.6. Both sites are most consistent with carboxylic acids side chains in aspartic and glutamic acid (Christensen et al., 1976; Martell et al., 1998), because enthalpies of phosphonate protonation below pH 5 are closer to thermoneutral (Martell et al., 1998; Nash et al., 1998; Jensen et al., 2000). Both aspartic and glutamic acid have been identified as components in S. acidocaldarius S-layers (Veith et al., 2009). A comparison of the surface reactivity of all species indicates that distinct differences between AOB and archaea surface reactivities do exist. The thermodynamic parameters of S. acidocaldarius and surface reactivity are consistent with ionizable amino acid side chains; this is expected because the surfaces of S. acidocaldarius and strain SCM1 are covered with proteins. Phosphorous-bearing functional groups may also be present on these cell surfaces and be masked by the more exothermic protonation of imidazole and thiol functional groups, while all AOB had clearer indications of having phosphate present on their surfaces.

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S. acidocaldarius and strain SCM1 have similar reactivities in that four acidic sites were detected, with two sites likely sharing the same type of functional group (carboxyl and imidazole). S. acidocaldarius, however, exhibited proton buffering to a lower pH range, which might be expected given its acidophilic adaptations, and the high log K sites might have different identities or have different proportions of amine to hydroxyl sites. Histidine residues are not inferred as being present on AOB surfaces, which means that the largest and most significant differences in archaea and AOB species are functional groups that deprotonate in the circumneutral pH range. Comparing the surface reactivity of strain SCM1 and S. acidocaldarius to heterotrophs previously investigated with potentiometric and calorimetric titrations reveals surface site identities not previously inferred. Past work on heterotrophs revealed carboxylate, phosphonate, thiol, and amine reactivity similar to those of the species investigated here (Gorman-Lewis et al., 2006; Gorman-Lewis, 2009, 2011). No calorimetric surface reactivity data exist for species with S-layers; however, Harrold and Gorman-Lewis (2013) determined the enthalpies of protonation of Bacillus subtilis (B. subtilis) endospores. The endospore surface is a more apt comparison to S-layer surfaces because they are both composed of proteins. Similarities exist between the archaea in this study and B. subtilis endospores. Thiols are inferred on strain SCM1 and B. subtilis endospores. In addition, carboxylate and amine functional groups are inferred on strain SCM1, S. acidocaldarius, and B. subtilis endospore surfaces. However, histidine residues were not inferred as being present on the endospore surface. The impact and prevalence of histidine residues contributing to surface reactivity is unknown and requires further investigation. Differences in ligand identity can influence cation sequestration on cell surfaces and strengths of surface complexes. Deprotonated sites are the most likely sites to be involved in metal ion complexation; therefore, comparing site identities using calorimetric and potentiometric data for surface sites with log K values below 9 is most relevant for considering reactions that occur during growth (in culture or in the environment). Strain SCM1 has a combination of ‘hard’ (anionic oxygen in carboxyl and possibly phosphonate), ‘borderline’ (imidazole), and ‘soft’ (thiol) ligands according to updated theories of metal complexation by Martin (2002). N. europaea and N. oceani have ‘hard’ ligands (anionic oxygen in phosphonates), while N. briensis and N. multiformis have a combination of ‘hard’ (phosphonate) and ‘soft’ (thiol) ligands. The thermodynamic nature of metal–ligand complexes is dependent on the hardness or softness of the ligand and central ion, and differences between strain SCM1 and AOB in ligand identity might be linked to their differing abilities to obtain and/or retain a reservoir of nutrients on the cell surface (Ferris & Beveridge, 1985).

Capturing ammonium ions might also be influenced by the cell surface ligands. Previous work identified the carboxylate groups in aspartic and glutamic acid, the aromatic side chain in tyrosine, and the hydroxyl group in serine as the ligands creating the ammonium-binding pocket in glutamine synthetase (Liaw et al., 1995; Scrutton & Raine, 1996). Histidine and tyrosine side chains are also implicated in coordination of ammonia in ammonia transporter proteins (Amt) in bacteria and plants (Thomas et al., 2000; Khademi et al., 2004; Winkler, 2006). While glutamine synthetase and Amt are not implicated in the oxidation of ammonia within AOA or AOB, the coordination environment of the ammonium-binding pocket in these proteins is relevant for this work. The present work indicates the presence of a high density of surface sites consistent with aspartic and glutamic acid on strain SCM1 in addition to the presence of tyrosine and histidine. This result is consistent with the genome sequence findings that revealed two Amt-type ammonium transporters (MartensHabbena et al., 2009). Previous works suggest that the presence of negatively charged sites alone is not the most effective binding environment but the cooperation of multiple sites to capture ammonium ions and the participation of cation-p interactions facilitated by tyrosine is important (Scrutton & Raine, 1996). The presence of these amino acids on the surface of strain SCM1 might serve to capture ammonium ions more effectively than the AOB surface, which is dominated by lipopolysaccharides.

CONCLUSIONS Although the nature of the adaptations that allow strain SCM1 to sustain ammonia oxidation below the threshold of AOB remains unknown, the ability to obtain and/or maintain a reservoir of nutrients with the cell surface might play a role. This is the first work that uses potentiometric and calorimetric titrations to show that differences exist between the surface reactivities of proton-ionizable functional groups of AOB, S. acidocaldarius, and AOA (as represented by strain SCM1). Thermodynamic parameters of proton-ionizable functional groups on the archaea surfaces examined in this study are consistent with moieties found within proton-ionizable amino acid side chains, which results in a proton-buffering profile that differs from AOB. Features distinct to strain SCM1 include a high concentration of sites consistent with aspartic and glutamic acid and the inferred presence of imidazole functional groups. These differences might translate to the ability of the cell surface to bind and hold cations essential to metabolism. This work provides the foundation for future studies to investigate non-metabolic surface reactions with ammonium and metals essential to ammonia oxidation, such as copper, with surface complexation modeling. The ability to describe the surface affinity of AOA and AOB for ammonia

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AOA and AOB surface characterization and copper with thermodynamic parameters will allow us to assess whether the AOA surface presents a thermodynamic advantage for essential nutrient uptake under the conditions studied. Understanding the adaptations that allow AOA to dominate nitrification in oligotrophic conditions is important for understanding nitrogen cycling in nutrient-poor regions of the ocean where high nitrification rates are found (Olson, 1981; Hashimoto et al., 1983; Ward, 1987). Investigations of oligotrophic adaptations of AOA might be the key to explaining how nitrification is occurring in environments where ammonia concentrations are below the threshold of AOB. Ultimately understanding how AOA are able to contribute to nitrification in permanently nutrient-deprived ocean regions is critical to our understanding of the role Thaumarchaeota play in the global biogeochemical N cycle.

ACKNOWLEDGMENTS This material is based upon work supported by the National Aeronautics and Space Administration under Grant No. NNX12AD76G issued through the Science Mission Directorate’s Planetary Science Division, Astrobiology: Exobiology and Evolutionary Biology Program Element. This work was also funded in part by the United States National Science foundation’s Grants MCB0920741 and OCE-1046017. Journal reviews significantly improved the presentation of this manuscript.

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SUPPORTING INFORMATION Additional Supporting Information may be found in the online version of this article: Fig. S1 Raw calorimetric data of (A) Nitrosospira briensis from pH 10.2 to 3.6, (B) Nitrosomonas europaea from pH 10.0 to 3.8, (C) Nitrosolobus multiformis from pH 9.9 to 4.4, (D) Nitrosococcus oceani from pH 10.3 to 5.8, (E) Nitrosopumilus maritimus strain SCM1 from pH 9.4 to 4.6, and (F) Sulfolobus acidocaldarius from pH 9.0 to 3.5. Fig. S2 Cumulative heats of methylphosphonate protonation versus total protons added. Table S1 Methylphosphonic acid thermodynamic parameters.