Methane Monooxygenase Gene Transcripts as Quantitative Biomarkers of Methanotrophic Activity in Methylosinus trichosporium OB3b
ABSTRACT
Methanotrophic microorganisms are characterized by their ability to oxidize methane. Globally they have a significant impact on methane emissions by attenuating net methane fluxes to the atmosphere in natural and engineered systems, though the populations are dynamic in their activity level in soils and waters. Methanotrophs oxidize methane using methane monooxygenase (MMO) enzymes, and selected subunit genes of the most common MMOs, specifically pmoA and mmoX, are used as biomarkers for the presence and abundance of populations of bacterial methanotrophs. The relative expression of these biomarker genes is dependent on copper-to-biomass ratios. Empirically derived quantitative relationships between methane oxidation biomarker transcript amounts and methanotrophic activity could facilitate determination of methane oxidation rates. In this study, pure cultures of a model type II methanotroph, Methylosinus trichosporium OB3b, were grown in hollow-fiber membrane bioreactors (HFMBR) under different steady-state methane oxidation conditions. Methanotroph biomass (DNA based) and methane oxidation biomarker mRNA transcript amounts were determined using quantitative PCR (qPCR) and reverse transcription-PCR (RT-qPCR), respectively. Under both copper-present and copper-limited conditions, per-cell pmoA mRNA transcript levels positively correlated with measured per-cell methane oxidation rates across 3 orders of magnitude. These correlations, if maintained across different methanotrophs, could prove valuable for inferring in situ oxidation rates of methanotrophs and understanding the dynamics of their impact on net methane emissions.
IMPORTANCE Methanotrophs are naturally occurring microorganisms capable of oxidizing methane and have an impact on global net methane emissions. The genes pmoA and mmoX are used as biomarkers for bacterial methanotrophs. Quantitative relationships between transcript amounts of these genes and methane oxidation rates could facilitate estimation of methanotrophic activity. In this study, a strong correlation was observed between per-cell pmoA transcript levels and per-cell methane oxidation rates for pure cultures of the aerobic methanotroph M. trichosporium OB3b grown in bioreactors. If similar relationships exist across different methanotrophs, they could prove valuable for inferring in situ oxidation rates of methanotrophs and better understanding their impact on net methane emissions.
INTRODUCTION
Methane (CH4) is a major greenhouse gas with 28 times the global warming potential of carbon dioxide over a 100-year period (1). Aerobic methanotrophs (methane-oxidizing bacteria) play a key role in the global methane cycle by consuming methane from the atmosphere as well as methane produced by methanogens as it rises through the soil or water column, thereby mitigating atmospheric releases from methanogenic habitats (2–5). Despite numerous studies, in situ methane oxidation rates are hard to quantify, with the largest uncertainties in global CH4 model estimates being from microbial CH4 cycling (6, 7).
Aerobic methanotrophs exhibit diversity in their phylogeny, physiology, and ecology, and their activity has been shown to be influenced by methane, oxygen, and copper levels as well as variations in moisture, nitrogen source, pH, and temperature. However, a defining characteristic is their similarity in pathways and enzymes used to convert methane into carbon dioxide. Bacterial methanotrophs rely on methane monooxygenases (MMOs), enzymes that require oxygen to initiate the oxidation of CH4. Localized variations in habitat and nutrient levels are reflected in the activity of methanotrophs, ultimately affecting the expression of MMO genes and enzyme amounts. Links drawn between expression of MMO genes or MMO enzymes and activities could allow for a better understanding of the dynamics of in situ activities of methanotrophs in soil and water systems, as well as engineered bioreactors using methanotrophs to convert methane into bioproducts (8, 9). Bacterial methanotrophs (aerobic and anaerobic, such as NC10 methanotrophs) can have two forms of MMO: a membrane-bound or particulate MMO (pMMO) encoded by the three-gene operon pmoCAB and/or a soluble or cytoplasmic MMO (sMMO) encoded by the six-gene operon mmoXYBZDC (10). Nearly all known bacterial methanotrophs possess pMMO (with Methylocella and Methyloferula being the exceptions), while sMMO is found in a subset of bacterial methanotrophs (11, 12). For methanotrophs capable of expressing both sMMO and pMMO, like Methylosinus trichosporium OB3b, the canonical “copper switch” regulates MMO expression. Both sMMO and pMMO actively contribute to whole-cell methane oxidation, with relative contributions depending on copper-to-biomass ratios (13). At low copper-to-biomass ratios (<0.89 μmol of copper per g [dry weight] of cells), sMMO is more highly expressed, while at high copper-to-biomass ratios, pMMO is more highly expressed (2, 14). M. trichosporium OB3b under conditions of pMMO expression has higher affinities and pseudo-first-order methane oxidation rates than under copper-free conditions for sMMO expression; sMMO also has a broader substrate specificity than pMMO (15). Well-conserved regions of genes pmoA and mmoX, targeted by widely used “universal” primers, are used as biomarkers for both the presence and activity of aerobic methanotrophs (16–19). The genes pmoA and mmoX are also used as phylogenetic biomarkers, as they generally agree with phylogenies drawn from the 16S rRNA gene; however, more exceptions are found as novel methanotroph species are discovered (20).
Biomarkers can be used as indicators of microbial community and function, providing insight into in situ microbial activities (21). They have been shown to be reliable for making quantitative predictions of activity levels of specific functions within microbial communities. Protein and mRNA biomarkers have been successfully used as estimators of in situ microbial activities of Geobacter (22, 23), organohalide-respiring communities (24–27), and hydrogenotrophic (28) and acetoclastic (28) methanogens. These studies have shown the utility of mRNA biomarkers not only in identifying microbial function but also in their quantitative predictive power to quantify activities of specific community members. Though biomarkers have been developed for several biogeochemically relevant microbial guilds, methanotroph RNA biomarker development for this purpose requires further examination.
Methanotroph DNA and mRNA biomarkers have been used to assess methanotrophic communities, and these biomarkers have been suggested as a proxy for in situ methanotrophic activity (29, 30). Increased pmoA gene copy numbers have been correlated with increased methane oxidation potential in peatland material incubations (31, 32). Gene copies indicate the presence of methanotrophs and capacity for biotransformation of methane in soils but do not provide insight into extant (or in situ) levels of activity, which can be dynamic temporally and spatially. Some studies have also looked at both pmoA transcript levels and per-cell pmoA transcript levels, which directly indicate active methanotroph populations (30, 31). In permafrost thaw ponds, higher numbers of pmoA mRNA transcript copies were observed in methane-depleted zones (33), and increased pmoA mRNA transcript copies have been observed in soil slurries with higher methane oxidation rates (34). Correlations between per-cell pmoA transcript levels and per-cell methanotrophic activity have been observed in rice field soil microcosms (35) and in situ at a peat bog site (30). However, to test these correlations, microcosm studies are not ideal models for steady-state methanotrophy. Systems capable of achieving steady-state conditions, like chemostat reactors, are more suitable study systems. Research on methanotroph Methylococcus capsulatus Bath in chemostat cultures has shown that copper concentrations positively correlated with methane oxidation activity and pMMO transcript amounts (36). These results show that increases in methanotrophic activity were generally accompanied by an increase in methane oxidation biomarker mRNA amounts. Biomarker transcript abundances could serve as quantitative predictors of methanotrophic activity allowing for prediction of in situ rates even in transient systems like soils and engineered bioreactors.
To examine relationships between biomarker amounts and methanotrophic activity, hollow-fiber membrane bioreactors (HFMBRs) serve as an ideal study system. In HFMBRs, gaseous substrates from a pressurized source are delivered through a membrane directly to reactor medium and kinetic and mass transfer limitations are minimized while achieving high cell concentrations under steady-state conditions (37). Additionally, methane and oxygen provided to HFMBRs can be manipulated independently by adjusting source pressures.
The objective of this work was to determine if methanotroph biomarkers (DNA and RNA transcripts for MMO genes) showed quantitative correlation with lab-controlled methane oxidation rates. To achieve this, MMO mRNA biomarker and cell amounts in pure cultures of a type II aerobic methanotroph, M. trichosporium OB3b, were determined in controlled steady-state HFMBRs with membrane-based methane and oxygen delivery. Genome copies, serving as a proxy for cell abundance, were determined using quantitative PCR (qPCR), and biomarker transcript amounts were determined using reverse transcription-qPCR (RT-qPCR). A biokinetic mechanistic model consisting of Monod growth kinetics and membrane methane and oxygen permeation was developed to inform on operational conditions to achieve different oxidation rates. Reactor data were used with model expressions to calculate methanotroph oxidation rates. The dynamics of mRNA biomarker levels during transient copper limitation, which has been shown to alter relative expression of mmoX and pmoA in M. trichosporium OB3b, was also examined.
RESULTS AND DISCUSSION
Reactor performance and models.
Results from abiotic reactor runs allowed inference of permeation coefficients for methane and oxygen (see Fig. S1 in the supplemental material), which were then used in the biokinetic model. Rapid equilibrium between the headspace and liquid phases was assumed and supported by the response time in abiotic permeation tests (Fig. S1). The model-calculated permeation coefficients (Kp), simplified to units of centimeters per hour in this reactor system, were 4.1 cm per h for methane and 1.5 cm per h for oxygen. Model-calculated polydimethylsiloxane (PDMS) tubing Kp values were comparable to literature values converted to model units, ranging from 5.6 to 8.6 cm per h for methane and 1.7 to 2.4 cm per h for oxygen (38–41). For conditions of 1 atm, 25°C, and a tubing length of 20 cm, this corresponds to 0.057 mg CH4 per min and 0.37 mg O2 per min permeating through the membrane.
Flow rates were maintained constant for the four reactor conditions throughout the duration of the experiment, with an average retention time of 3.21, 4.18, 5.76, and 10.25 days for reactor conditions A, B, C, and D, respectively (Fig. S2 and Table S1). Actual methane, oxygen, and biomass data for the four conditions are shown in Fig. 1. An initial rise in methane concentrations, followed by a rise in biomass and decrease in methane concentrations, was observed for all reactors before they settled into steady-state conditions. Oxygen was provided in excess throughout reactor operation, ensuring at least a 2:1 mole ratio of oxygen to methane to prevent oxygen limitation. Oxygen concentrations in the liquid phase for all reactor conditions (Fig. 1) were well above reported oxygen Km values for aerobic methanotrophs (∼0.01 mg per liter) (42).
FIG 1
Compared to batch cultures with typical non-steady-state conditions, continuously fed, steady-state conditions allow for direct correlation of steady-state functional gene expression levels with observed activity level of cultures. M. trichosporium OB3b has been shown to be capable of achieving steady-state conditions in continuous culture previously (43). However, relationships between steady-state methane oxidation rates and functional gene expression levels have not been explored. Reactors were considered at steady-state conditions when no significant changes in methane and biomass concentrations were observed, with start times corresponding to days 24, 20, 25, and 15 for conditions A, B, C, and D, respectively (Fig. 1 and Table S1). Reactor methane and biomass concentrations for all conditions remained constant during the steady-state period, and oxygen concentrations were ∼4 to 8 mg per liter (Fig. 1 and Table S1). In some cases (Fig. 1B and C), reactor dissolved methane concentrations were higher than model-predicted concentrations during the start-up phase, possibly due to elevated oxygen levels partially inhibiting methane oxidation rates (44). Once steady state was reached, the observed concentrations matched model predictions.
Reactor methane oxidation rates and biomarker abundances.
Reactor methane oxidation rates, as milligram CH4 per milliliter per day, were determined using model expressions and measured reactor data (Fig. 2). Both unit volume and biomass (as cell dry weight) normalized methane oxidation rates were constant during the steady-state periods (Fig. 2 and Table S1). Observed reactor steady-state volumetric methane oxidation rates (0.060 to 0.105 mg CH4 per ml) were within the reported range for methanotroph methane oxidation rates in environmental systems, typically between 0.00014 and 0.14 mg CH4 per ml per day (45). Reactor biomass normalized methane oxidation rates (0.478 to 0.870 mg CH4 per mg cell [dry weight] per day) also agreed with available literature values for pure culture and mixed community aerobic methanotrophs (0.86 to 3.85 mg CH4 per mg cell [dry weight] per day) (46–48).
FIG 2
Using qPCR and RT-qPCR, M. trichosporium OB3b cell and transcript abundances for pmoA and mmoX (genes encoding key pMMO and sMMO polypeptides, respectively) were determined for selected dates during steady-state conditions. Biomarker data are shown as sampling date averages across triplicate reactors for each condition, except for condition D with a single replicate (Fig. 2). Data shown were corrected with losses determined from recoveries of spiked-in luciferase DNA and RNA, with recovery percentages across samples ranging from 1.47 to 39.12% and 0.84 to 14.70% for DNA and mRNA, respectively. Agreement was observed in both cell and pmoA transcript abundances for each individual reactor condition across sampling dates showing steady-state methanotroph cell numbers and pmoA transcript levels (Fig. 2). Differences in M. trichosporium OB3b abundances were statistically significant, and differences were not observed in pmoA mRNA abundances across reactor conditions (Fig. 2 and Table S2). Conditions A and B had higher flow rates, meaning higher growth rates, than conditions C and D, likely needing higher methane oxidation rates. Higher expression of pMMO was expected than for sMMO, as copper in nitrate mineral salts (NMS) medium was above reported copper-to-biomass ratios of 0.89 μmol copper per g (dry weight) of cells needed for pMMO expression (2). This was reflected in the data with mmoX mRNA transcript abundances being significantly lower than pmoA (Fig. 2 and Table S2). Culture density looked similar between conditions A, B, and C (Fig. 1), while differences were observed in M. trichosporium OB3b abundance determined by genome number (Fig. 2), with conditions A and B lower than condition C. A possible explanation is the proportion of intracytoplasmic membranes (ICMs), where methane oxidation takes place, in the cells. ICMs in methanotrophs increase in proportion to methane oxidation rates, increasing available surface area for methane oxidation (49). Conditions A and B had higher per-cell methane oxidation rates, similar biomass levels, and lower genome numbers than conditions C and D. Cells under conditions A and B were likely larger due to higher growth rates and to accommodate extra ICMs than under conditions C and D.
Biomarker mRNA expression response to copper starvation.
Following collection of steady-state samples for reactors for condition B, 4.2-day retention time reactors (Fig. 1B and 2B) were switched to copper-free NMS medium and monitored for an additional 16 days (∼3.7 retention times) to examine biomarker pmoA, mmoX, and mbnA transcript response to changes in copper conditions (Fig. 3). The gene mbnA encodes a putative precursor polypeptide essential for production of copper-binding, ribosomally produced, posttranslationally modified peptides (RiPP) called methanobactins. Methanobactins are suspected to work together with a protein called MmoD in the regulation of the “copper switch” and MMO operons (14, 50). Methanobactin is produced and secreted under copper starvation conditions and then reinternalized, serving as a copper source for pMMO (51). Previous work has shown that the M. trichosporium OB3b pmoA and mmoX transcript level response when exposed to new copper levels occurs in the order of minutes and hours for washed cell pellets and cultures in bioreactors, respectively (52, 53). Copper-free medium was provided to condition B reactors at day 36 (day 0, copper-free condition); from this time, the only copper in the system was that already present in the reactor, including biomass-associated Cu. During this time, no significant changes were observed in reactor biomass levels and dissolved oxygen. Following the start of copper starvation, dissolved methane concentrations rose from about 0.3 mg per liter to a maximum of 1.35 mg per liter 8.8 days later (∼2.1 retention times) before returning to prestarvation levels at day 14.7 (∼3.5 retention times). During this time, cell amount and pmoA, mmoX, and mbnA transcript levels were quantified using qPCR and RT-qPCR and converted to per-cell transcript levels (Fig. 4).
FIG 3
FIG 4
After the addition of copper starvation medium, pmoA expression decreased 3.6-fold after 0.91 days (0.21 retention time) and after 4.84 days (1.14 retention times) and on, pmoA expression decreased at least 14-fold compared to conditions of copper availability. Differences in per-cell pmoA transcript levels between copper-present and copper-free conditions were statistically significant (P < 0.005). Compared to copper-replete conditions (0.08 to 0.18 copy per cell), a slight increase in per-cell mbnA transcript levels was observed under copper starvation conditions, with 0.48 copy per cell observed after 4.84 days (1.14 retention times) and a maximum of 0.56 copy per cell after 15.80 days (3.72 retention times) following the addition of copper-free media (Fig. 4). However, differences in per-cell mbnA transcript levels between copper-present and copper starvation conditions were found to not be statistically significant (P > 0.5). The onset of copper depletion did not strongly affect mmoX expression, with only a slight, but statistically significant (P < 0.05), increase in per-cell transcript amounts during copper-free medium reactor operation. The maximum observed per-cell mmoX transcript level during this period was 0.085 after 4.84 days (1.14 retention times). The largest changes in per-cell transcript levels during copper-free operation relative to copper-present amounts were a 23.5-fold decrease for pmoA, a 2.2-fold increase for mmoX, and a 3.9-fold increase for mbnA, all occurring after 4.84 days, which corresponded roughly to 1 retention time. Additionally, a drop in methanotrophic activity was shown by a small increase in dissolved methane in the reactor (Fig. 3). Cell amounts determined using qPCR did not change under copper-free conditions (Table S3), and RNA recoveries and qPCR efficiencies were consistent across samples and gene targets. Under these conditions, per-cell pmoA transcript abundances remained almost 2 orders of magnitude higher than per-cell mmoX transcript abundances (Fig. 4). Observed per-cell pmoA transcript levels under copper-replete (∼100) and copper-depleted (∼10) conditions were similar to previously reported values, while per-cell mmoX transcript levels during copper starvation were lower than the reported maximum of ∼1 mmoX transcript per cell during copper starvation (14). Copper levels were not determined during this period, but copper was assumed to be leaving in the reactor effluent, dissolved in the reactor medium and via biomass-associated copper. Low mmoX transcript levels observed during copper-free operation could be due to reactor copper-to-biomass ratios being below the threshold to induce a decrease in pmoA expression but still above reported thresholds for maximum mmoX expression. Based on estimated copper concentrations from dilution of the reactor medium, copper-to-biomass ratios would be below the reported threshold for maximum mmoX expression and inhibition of pmoA expression after 12.23 days (2.88 retention times). After 15.80 days (3.72 retention times), the estimated copper concentration would be 0.054 μM Cu, with a copper-to-biomass ratio of 0.410 μmol of copper per g (dry weight) of cells, about 2-fold lower than the reported copper-to-biomass threshold for maximum mmoX expression and inhibition of pmoA expression. However, copper salvaging mechanisms may diminish the limitation for Cu.
Correlations between biomarker levels and methane oxidation rates.
Methane oxidation mRNA biomarker amounts during steady-state operation were normalized with M. trichosporium OB3b cell abundances to obtain per-cell transcript levels. Differences in per-cell pmoA transcript levels were statistically significant, but those for per-cell mmoX transcript levels across the methane oxidation rate conditions were not (Table S4). Inclusion of both mmoX and pmoA transcripts (as per-cell pmoA plus mmoX transcript levels) showed no difference compared to pmoA alone, as mmoX transcript levels were orders of magnitude lower than for pmoA. Differences in per-cell pmoA transcript levels across oxidation rate conditions suggest differences in activities of the M. trichosporium OB3b populations in these reactors. The range of observed per-cell pmoA transcript levels in this study (0.25 to 120.74) are similar to reported per-cell transcript levels for aerobic methanotrophs under both controlled (14, 35, 54) and in situ (29, 30, 55) conditions.
The observed M. trichosporium OB3b per-cell methane oxidation rates for the conditions explored ranged from 0.013 to 3.816 pmol CH4 per cell per day (Fig. 5), agreeing with reported literature values for aerobic methanotrophs, with values of 0.005 to 2.504 pmol CH4 per cell per day after conversion to the same units (2, 56–58). Reported values included those for a variety of aerobic methanotrophs, including pure cultures of M. trichosporium OB3b, Methylomicrobium album BG8, a Methylocystis sp., methanotroph strain WP 12, mixed methanotrophic cultures, and soil methanotrophs with growth conditions including in situ and batch. Power law trends were used to explore correlations between per-cell biomarker transcript levels and per-cell methane oxidation rates and between biomarker copies per volume and volumetric methane oxidation rates (Fig. 5 and Fig. S3). Higher per-cell pMMO or pmoA transcript levels were hypothesized to correspond to more active cells with increased per-cell methane oxidation rates. A strong positive correlation (Pearson’s R2 = 0.97) across 3 orders of magnitude was observed between M. trichosporium OB3b per-cell pmoA transcript levels and per-cell methane oxidation rates (Fig. 5).
FIG 5
No significant correlation was observed for per-cell mmoX transcript levels and per-cell methane oxidation rates, ranging from 0.02 to 0.88 (Table S5 and Fig. S3B), as mmoX transcript amounts were orders of magnitude lower than for pmoA. The correlation observed between per-cell pmoA plus mmoX transcript levels and per-cell methane oxidation rates (Table S5 and Fig. S3C) was due to an abundance of pmoA mRNA transcripts. Per-volume pmoA and mmoX transcript levels and methane oxidation rate showed weak correlations (Fig. S3D to F). This could be due to per-volume pmoA and mmoX transcript levels not being significantly different across reactor conditions and differences being reflected in per-cell transcript levels.
Correlations between per-cell biomarker transcript levels and per-cell methane oxidation rates during copper-limited reactor operation were also explored (Fig. S4). During copper limitation, the per-cell methane oxidation rate decreased, per-cell pmoA transcript levels decreased, and per-cell mmoX transcript levels slightly increased compared to those under copper-present conditions (Fig. 4 and Fig. S4). The strong correlation observed between per-cell pmoA transcript levels and per-cell methane oxidation rate under copper-present conditions was maintained during the copper-free operation, as per-cell pmoA transcript levels were still orders of magnitude higher than per-cell mmoX transcript levels. No changes were observed for the correlation between per-cell mmoX transcript levels and per-cell methane oxidation rate. This could be explained by biomass-associated copper remaining in the system. Further work is needed exploring these relationships under true copper-deficient conditions without potential effects of biomass-associated copper. Per-volume genome copies based on cell densities also showed a weak correlation with methane oxidation rates (Fig. S2A). Genome or cell amounts were not expected to be good indicators of activity: gene copies can indicate presence or potential but not necessarily active populations, as identical populations in terms of cell abundances can exhibit drastic differences in activity due to transient differences in local conditions. This was observed in a study of aerobic methane oxidation rates in lakes where absolute numbers of methanotrophs did not vary, while methane oxidation rates varied significantly over space and time (59). As mentioned previously, per-cell transcript levels have been suggested as descriptors of methanotrophic activity and have been found to be positively associated with methanotrophic activity in environmental soil and bog samples (29, 30). In batch culture incubations, whole-cell M. trichosporium OB3b activity was also found to positively correlate with pmoA transcript levels across growth phases (13). The strong correlation observed in M. trichosporium OB3b for per-cell pmoA transcript levels and per-cell methane oxidation rate was hypothesized to be due to the direct involvement of pMMO in methanotrophic activity. Increases in methane oxidation rate would require larger pMMO enzyme amounts and, therefore, per-cell pmoA expression. These results suggest that per-cell pmoA transcript levels may serve as a quantitative biomarker of methane oxidation rate for M. trichosporium OB3b and potentially across other pMMO-utilizing aerobic methanotrophs.
In this study, we quantified the predictive capabilities of methane oxidation mRNA biomarkers to reflect extant activity levels of methanotroph populations. This was achieved by quantifying methanotroph biomarker transcript abundances in continuously fed chemostat membrane bioreactors with the type II aerobic methanotroph M. trichosporium OB3b under steady-state conditions. A very strong correlation (R2 = 0.97) between per-cell pmoA transcript levels and per-cell methane oxidation rates was determined. As most aerobic methanotrophs and the anaerobic NC10 group bacterial methanotrophs (60) rely on pMMO enzymes for methane oxidation, similar correlations between per-cell pmoA transcript levels and methanotrophic activities being maintained across bacterial methanotroph types seem plausible. The presented work shows a strong correlation between per-cell methanotroph biomarker pmoA transcript levels and per-cell methane oxidation rates in pure methanotroph cultures and represents a step toward applying the quantitative predictive power of mRNA biomarkers to monitor dynamic activities of methanotroph populations in situ, with implications for the global methane cycle.
MATERIALS AND METHODS
Bacterial strain and growth conditions.
Experiments were conducted at 25°C using pure M. trichosporium strain OB3b (NCIMB 11131; VKM B-2117) cultures grown on nitrate mineral salts (NMS) medium (61). Prior to inoculation of bioreactors, M. trichosporium OB3b cultures were grown in 160-ml serum bottles (Wheaton, Millville, NJ) with 100 ml culture and 60 ml air headspace under constant shaking at 150 rpm. Bottles were provided 30 ml methane, with methane and air replenished when depleted until an optical density at 600 nm (OD600) of at least 0.100 (approximate concentration of 40 mg cells [dry weight] per liter) was reached before inoculation of reactors. Multiple M. trichosporium OB3b culture bottle replicates were combined to obtain enough inoculum volume for all reactors.
Reactor design and experimental conditions.
Hollow-fiber membrane bioreactors (HFMBRs) were designed and constructed for this study. The HFMBR design could achieve steady-state conditions, and methane and oxygen delivery could be manipulated independently by controlling membrane gas pressures. HFMBRs consisted of 1-liter Pyrex medium bottles (Corning, Corning, NY) with modified gas-tight butyl rubber caps, including two separate permeation tube membranes for bubble-less delivery of CH4 (≥99.5% purity; Airgas, Radnor, PA) and O2 (≥99.99% purity; Airgas) gases (Fig. 6). Permeation tube gas release valves (Fig. 6B) were kept closed during reactor operation to maintain constant pressures inside tubes. Reactors had a liquid volume (VL) of 0.8 liter and headspace volume (VG) of 0.265 liter and were operated as chemostats at room temperature under sterile conditions. Reactor experiments were conducted at four distinct flow rates affecting the methane oxidation rates. These corresponded to reactors with 3.2-day (condition A), 4.2-day (condition B), 5.8-day (condition C), and 10.3-day (condition D) retention times (Fig. S2 and Table S1). For each condition, triplicate reactors were operated concurrently, except for 10.3-day (condition D) reactors with only one reactor, as one replicate reactor developed biofilm on the membrane and was not used.
FIG 6
NMS medium was delivered to reactors using a multiplexed peristaltic pump (Ismatec, Wertheim, Germany). Retention time was determined by measuring reactor effluent volumes as time elapsed. Permeation tube pressures were set by adjusting pressure gauges with an Omega PCL425 pressure calibrator (Omega Engineering Inc., Norwalk, CT) and confirmed by measuring gas amounts with a gas chromatograph (GC) equipped with a thermal conductivity detector (TCD) as described below. Permeation tubing was platinum-cured, HelixMark PharmaFocus PDMS tubing (3.18-mm inside diameter [i.d.] by 6.35-mm outside diameter [o.d.] by 1.59-mm wall thickness; Freudenberg Medical, Carpinteria, CA) due to its high gas permeability compared to those of other tubing materials (38). Reactors were operated under conditions of oxygen excess, and permeation tube pressures were kept constant under reactor steady-state conditions. Once reactor assembly was complete, reactors were inoculated with M. trichosporium OB3b, and permeation tubes and the medium pump were turned on. All reactors were provided NMS medium with 2 μM Cu. At the conclusion of steady-state methane oxidation rate conditions for condition B (retention time of 4.2 days), copper limitation and its effect on pmoA, mmoX, and mbnA mRNA expression were explored by supplying the reactor with copper-free NMS medium.
Methane, oxygen, and biomass sampling.
Methane and oxygen concentrations were determined from headspace samples collected via the reactor septa (Fig. 6B) with a 100-μl gas-tight syringe (VICI Precision Sampling, Baton Rouge, LA) and measuring gas amounts with a GC-TCD (5890 Series II; Hewlett-Packard, San Jose, CA) with helium (≥99.999% purity; Airgas) as a carrier gas using a 1.8-m by 3.175-mm by 2.1-mm stainless steel 60/80 Mol Sieve 5A column (Supelco, Bellefonte, PA). Headspace concentrations were converted to aqueous phase concentrations by comparison to prepared reference standards and using Henry’s law coefficient at 25°C (62). Reactor microbial biomass was monitored via OD600 readings using a NanoDrop 2000c spectrophotometer (Thermo Scientific, Waltham, MA) and correlating measurements to M. trichosporium OB3b culture biomass as cell dry weight using a standard curve. Biomass amounts were determined by filtering M. trichosporium OB3b culture biomass with Whatman grade GF/F glass microfiber filters (GE Healthcare, Chicago, IL) and quantifying by drying at 105°C and weighing after cooling in a desiccator. Reactor biomass samples for nucleic acid extraction and mRNA and DNA biomarker quantification were collected on selected dates (conditions A, B, and D, n = 2; condition C, n = 3) under steady-state conditions as well as during copper limitation for condition B.
Nucleic acid extraction and cDNA synthesis.
DNA and RNA extractions were performed on 2-ml culture samples. Sample collection, processing, and storage were as previously described (26). DNA was extracted using the AllPrep DNA/RNA minikit (Qiagen, Hilden, Germany) and RNA using TRIzol reagent (Invitrogen, Carlsbad, CA), following the manufacturers’ instructions. Luciferase (luc) DNA and mRNA spike-ins were used as internal reference standards to account for DNA and RNA losses during extraction and reverse transcription (RT) steps as previously reported (63). Recovered quantities of luc mRNA (Promega, Madison, WI) and luc DNA (Promega) were used to correct recovered target gene quantities as previously described (27, 64).
Extracted DNA concentrations were estimated using NanoDrop; aliquots were diluted 10-fold and stored at −20°C until further analysis. Extracted RNA was processed the same day, undergoing RQ1 RNase-free DNase (Promega) treatment as previously described (24), and concentrations were estimated using NanoDrop. Aliquots of RNA were then treated with the iScript cDNA synthesis kit (Bio-Rad, Hercules, CA) following the manufacturer’s instructions for RT of mRNA to cDNA. Following cDNA synthesis, samples were diluted 5-fold and stored at −20°C until further analysis. Nucleic acid quality assurance/quality control (QA/QC) was done on a subset of representative samples at the Cornell Biotechnology Resource Center (BRC).
Quantitative PCR analyses and primer selection.
Quantitative PCR (qPCR) and reverse transcription-qPCR (RT-qPCR) analyses of M. trichosporium OB3b cultures were performed using primers indicated in Table 1. For condition B, transcript amounts for methanobactin gene subunit mbnA, encoding a precursor polypeptide involved copper switch, were also quantified (Table 1). M. trichosporium OB3b cell amounts were determined by qPCR using pmoA primers on extracted DNA and pmoA, mmoX, and mbnA transcript amounts by RT-qPCR using respective primers on cDNA.
TABLE 1
| Target gene | Primer | Sequence (5′–3′) | Reference |
|---|---|---|---|
| M. trichosporium OB3b pmoA | qpmoA_fw | TTCTGGGGCTGGACCTAYTTC | 52 |
| qpmoA_rev | CCGACAGCAGCAGGATGATG | ||
| M. trichosporium OB3b mmoX | qmmoX_fw | TCAACACCGATCTSAACAACG | 52 |
| qmmoX_rev | TCCAGATTCCRCCCCAATCC | ||
| luc internal standard | luc_fw | TACAACACCCCAACATCTTCGA | 63 |
| luc_rev | GGAAGTTCACCGGCGTCAT | ||
| M. trichosporium OB3b mbnA | mbnA_fw | TGGAAACTCCCTTAGGAGGAA | 14 |
| mbnA_rev | CTGCAC GGATAGCACGAAC |
All qPCRs were performed in triplicate in 96-well qPCR plates with 20-μl reaction volumes using Luna universal qPCR master mix (New England Biolabs, Ipswich, MA), following the manufacturer’s instructions. Thermal cycling was conducted on an iCycler IQ multicolor real-time detection system (Bio-Rad) using previously reported qPCR conditions (14, 52, 63). Melt curve analyses were conducted on all samples to check for nonspecific amplification. Specificities of qPCR products were verified on a subset of representative samples via gel electrophoresis and Sanger sequencing at the Cornell BRC. “No RT” control qPCRs were done on DNase-treated RNA extracts to check for DNA contamination. Average cycle threshold (CT) values were used to quantify DNA and mRNA biomarker copies using standard curves from dilutions of pure culture DNA of known copies per microliter (see below). Values for copies per microliter were converted to copies per milliliter of original culture sample and corrected with corresponding sample recovered luc DNA and cDNA amounts determined via qPCR.
To generate qPCR standards, M. trichosporium OB3b DNA was quantified using the Quant-iT double-stranded DNA (dsDNA) assay kit (Invitrogen) on a Tecan Infinite M200 Pro microplate reader (Tecan US, Inc., Raleigh, NC) and converted to genome copies using published M. trichosporium OB3b genome information (65). Standard curves for determination of luc recoveries were made from the same luc DNA as used to spike samples. Standards ranged from 107 copies per μl to 102 copies per μl for each gene target and were stored at −20°C until use. Biomarker qPCR and RT-qPCR data were used to determine per-volume genome (cell amounts) as well as per-volume and per-cell pmoA and mmoX transcript amounts (per-cell transcript levels).
Calculation of methane oxidation rates.
A mechanistic biokinetic model describing the reactor system was developed using Stella Architect 1.1 (ISEE Systems, Lebanon, NH) and previously published biokinetic parameters for M. trichosporium OB3b (42, 66, 67). Methane and oxygen permeation coefficients (Kp) for the reactor setup were determined in duplicate sterile reactors by measuring permeant gas concentrations over time and fitting data to a model describing the reactor system. The abiotic HFMBR model is available in the supplemental material (Fig. S5 and Tables S6 and S7). Following Kp determination, explicit mechanistic predictions could be made for reactor methane, oxygen, and biomass in the reactor, including methanotroph growth and consumption of gaseous substrates (Table 2).
TABLE 2
| Model | Expression | Equation |
|---|---|---|
| Methane | 1 | |
| Oxygen | 2 | |
| Biomass | 3 |
a
= methane mass accumulation rate in reactor (milligrams CH4 per day). = oxygen mass accumulation rate in reactor (milligrams CH4 per day). = methanotroph biomass accumulation rate in reactor (milligrams biomass per day). Kp = permeation coefficient (centimeters per day). Ap = permeation tube surface area per liquid volume (per centimeter). VL = liquid volume (centimeters cubed). = theoretical concentration of substrates in equilibrium with gas phase (milligrams CH4 per cubic centimeter). CL = concentration of substrate in liquid phase (milligrams CH4 per cubic centimeter). = maximum specific rate of substrate utilization (milligrams CH4 per milligram VSS [see below] per day) (value: 2.2) (66). Xa = methanotroph concentration (milligrams biomass per cubic centimeter). = Monod half-saturation constant for methane (milligrams per cubic centimeter) (value: 7 × 10−5) (66). = Monod half-saturation constants for oxygen (milligrams per cubic centimeter) (value: 1 × 10−5) (42). Q = flow rate (cubic centimeter per day). fe = fraction of methane used for energy (unitless) (value: 0.34) (67). Y = yield (milligram VSS [see below] per milligram CH4) (value: 0.66) (67). b = endogenous decay coefficient (per day) (value: 0.18) (66). Values based on methanotroph biomass measured as milligram volatile suspended solids (VSS) converted to milligram cell biomass (cell dry weight) using a conversion factor of 0.79 mg VSS per mg cell (dry weight).
Expressions for the mass rate of methane and oxygen accumulation in bioreactor liquid are shown as equations 1 and 2, respectively. The expression for methanotroph biomass is shown as equation 3. A double Monod equation was used to calculate microbial biomass and substrate consumption terms (68). The model assumed that all substrates other than methane and oxygen were present in excess and that inhibition of methanotrophs occurred under high oxygen levels as observed by Ren and colleagues (44). Reported stoichiometric and kinetic expressions and parameters for M. trichosporium OB3b with nitrate as a nitrogen source were used (Table 2). Details of the biotic model information are available in Fig. S6 and Table S8.
Reactor methane oxidation rates were determined from reactor data using model equation 1, methane concentrations were determined via GC-TCD, and cell amounts were determined via qPCR of the pmoA gene. Methane oxidation rates (milligrams CH4 per liter per day) were converted to appropriate units to obtain methane oxidation rates per unit volume, normalized by pmoA gene copies and pmoA copies per genome (n = 2 in M. trichosporium OB3b) (69) to obtain cell normalized methane oxidation rates.
Statistical analysis.
Statistical analyses were conducted using R studio software (version 3.4.2) with the nonparametric Kruskal-Wallis test to examine differences in DNA and mRNA biomarker amounts and per-cell biomarker amounts across the reactor conditions.
ACKNOWLEDGMENTS
We thank James Gossett for bioreactor design suggestions and Jeremy Semrau for providing the Methylosinus trichosporium OB3b cultures. We are grateful the Cornell Statistical Consulting Unit for their assistance with the statistical analyses.
This work was supported by a Cornell Sloan Graduate Fellowship to E.F.T.
The manuscript was written through contributions of all authors. All authors have given approval for the final version of the manuscript.
We declare no competing financial interest.
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Published In
Applied and Environmental Microbiology
Volume 86 • Number 23 • 10 November 2020
eLocator: e01048-20
Editor: Claire Vieille, Michigan State University
PubMed: 32948519
History
Received: 4 May 2020
Accepted: 10 September 2020
Published online: 10 November 2020
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Editor
Claire Vieille
Editor
Michigan State University