Microbial physiology-based model of ethanol metabolism in subsurface sediments

Limited Mechanistic Link Between the Monod Equation and Methanogen Growth: a Perspective from Metabolic Modeling

The Monod equation has been widely applied as the general rate law of microbial growth, but its applications are not always successful. By drawing on the frameworks of kinetic and stoichiometric metabolic models and metabolic control analysis, the modeling reported here simulated the growth kinetics of a methanogenic microorganism and illustrated that different enzymes and metabolites control growth rate to various extents and that their controls peak at either very low, intermediate, or very high substrate concentrations. In comparison, with a single term and two parameters, the Monod equation only approximately accounts for the controls of rate-determining enzymes and metabolites at very high and very low substrate concentrations, but neglects the enzymes and metabolites whose controls are most notable at intermediate concentrations. These findings support a limited link between the Monod equation and methanogen growth, and unify the competing views regarding enzyme roles in shaping growth kinetics. The results also preclude a mechanistic derivation of the Monod equation from methanogen metabolic networks and highlight a fundamental challenge in microbiology: single-term expressions may not be sufficient for accurate prediction of microbial growth. IMPORTANCE The Monod equation has been widely applied to predict the rate of microbial growth, but its application is not always successful. Using a novel metabolic modeling approach, we simulated the growth of a methanogen and uncovered a limited mechanistic link between the Monod equation and the methanogen's metabolic network. Specifically, the equation provides an approximation to the controls by rate-determining metabolites and enzymes at very low and very high substrate concentrations, but it is missing the remaining enzymes and metabolites whose controls are most notable at intermediate concentrations. These results support the Monod equation as a useful approximation of growth rates and highlight a fundamental challenge in microbial kinetics: single-term rate expressions may not be sufficient for accurate prediction of microbial growth.

Physiological Acclimation Extrapolates the Kinetics and Thermodynamics of Methanogenesis From Laboratory Experiments to Natural Environments

Chemotrophic microorganisms face the steep challenge of limited energy resources in natural environments. This observation has important implications for interpreting and modeling the kinetics and thermodynamics of microbial reactions. Current modeling frameworks treat microbes as autocatalysts, and simulate microbial energy conservation and growth with fixed kinetic and thermodynamic parameters. However, microbes are capable of acclimating to the environment and modulating their parameters in order to gain competitive fitness. Here we constructed an optimization model and described microbes as self-adapting catalysts by linking microbial parameters to intracellular metabolic resources. From the optimization results, we related microbial parameters to the substrate concentration and the energy available in the environment, and simplified the relationship between the kinetics and the thermodynamics of microbial reactions. We took as examples Methanosarcina and Methanosaeta – the methanogens that produce methane from acetate – and showed how the acclimation model extrapolated laboratory observations to natural environments and improved the simulation of methanogenesis and the dominance of Methanosaeta over Methanosarcina in lake sediments. These results highlight the importance of physiological acclimation in shaping the kinetics and thermodynamics of microbial reactions and in determining the outcome of microbial interactions.

Sustained Ability of a Natural Microbial Community to Remove Nitrate from Groundwater

Microbial-mediated nitrate removal from groundwater is widely recognized as the predominant mechanism for nitrate attenuation in contaminated aquifers and is largely dependent on the presence of a carbon-bearing electron donor. The repeated exposure of a natural microbial community to an electron donor can result in the sustained ability of the community to remove nitrate; this phenomenon has been clearly demonstrated at the laboratory scale. However, in situ demonstrations of this ability are lacking. For this study, ethanol (electron donor) was repeatedly injected into a groundwater well (treatment) for six consecutive weeks to establish the sustained ability of a microbial community to remove nitrate. A second well (control) located upgradient was not injected with ethanol during this time. The treatment well demonstrated strong evidence of sustained ability as evident by ethanol, nitrate, and subsequent sulfate removal up to 21, 64, and 68%, respectively, as compared to the conservative tracer (bromide) upon consecutive exposures. Both wells were then monitored for six additional weeks under natural (no injection) conditions. During the final week, ethanol was injected into both treatment and control wells. The treatment well demonstrated sustained ability as evident by ethanol and nitrate removal up to 20 and 21%, respectively, as compared to bromide, whereas the control did not show strong evidence of nitrate removal (5% removal). Surprisingly, the treatment well did not indicate a sustained and selective enrichment of a microbial community. These results suggested that the predominant mechanism(s) of sustained ability likely exist at the enzymatic- and/or genetic-levels. The results of this study demonstrated the in situ ability of a microbial community to remove nitrate can be sustained in the prolonged absence of an electron donor.

Importance of thermodynamics dependent kinetic parameters in nitrate-based souring mitigation studies

Souring is the unwanted formation of hydrogen sulfide (H₂S) by sulfate-reducing microorganisms (SRM) in sewer systems and seawater flooded oil reservoirs. Nitrate treatment (NT) is one of the major methods to alleviate souring: The mechanism of souring remediation by NT is stimulation of nitrate reducing microorganisms (NRM) that depending on the nitrate reduction pathway can outcompete SRM for common electron donors, or oxidize sulfide to sulfate. However, some nitrate reduction pathways may challenge the efficacy of NT. Therefore, a precise understanding of souring rate, nitrate reduction rate and pathways is crucial for efficient souring management. Here, we investigate the necessity of incorporating two thermodynamic dependent kinetic parameters, namely, the growth yield (Y), and F_T, a parameter related to the minimum catabolic energy production required by cells to utilize a given catabolic reaction. We first show that depending on physiochemical conditions, Y and F_T for SRM change significantly in the range of [0-0.4] mole biomass per mole electron donor and [0.0006-0.5], respectively, suggesting that these parameters should not be considered constant and that it is important to couple souring models with thermodynamic models. Then, we highlight this further by showing an experimental dataset that can be modeled very well by considering variable F_T. Next, we show that nitrate based lithotrophic sulfide oxidation to sulfate (lNRM₃) is the dominant nitrate reduction pathway. Then, arguing that thermodynamics would suggest that S° consumption should proceed faster than S⁰ production, we infer that the reason for frequently observed S⁰ accumulation is its low solubility. Last, we suggest that nitrate based souring treatment will suffer less from S⁰ accumulation if we (i) act early, (ii) increase temperature and (iii) supplement stoichiometrically sufficient nitrate.

Multiscale Modeling of Uranium Bioreduction in Porous Media by One-Dimensional Biofilms

We formulate a multiscale mathematical model that describes the bioreduction of uranium in porous media. On the mesoscale we describe the bioreduction of uranium [VI] to uranium [IV] using a multispecies one-dimensional biofilm model with suspended bacteria and thermodynamic growth inhibition. We upscale the mesoscopic (colony scale) model to the macroscale (reactor scale) and investigate the behavior of substrate utilization and production, attachment and detachment processes, and thermodynamic effects not usually considered in biofilm growth models. Simulation results of the reactor model indicate that thermodynamic inhibition quantitatively alters the dynamics of the model and neglecting thermodynamic effects may over- or underestimate chemical concentrations in the system. Furthermore, we numerically investigate uncertainties related to the specific choice of attachment and detachment rate coefficients and find that while increasing the attachment rate coefficient or decreasing the detachment rate coefficient leads to thicker biofilms, performance of the reactor remains largely unaffected.

Thermodynamic Inhibition in a Biofilm Reactor with Suspended Bacteria

We formulate a biofilm reactor model with suspended bacteria that accounts for thermodynamic growth inhibition. The reactor model is a chemostat style model consisting of a single replenished growth promoting substrate, a single reaction product, suspended bacteria, and wall attached bacteria in the form of a bacterial biofilm. We present stability conditions for the washout equilibrium using standard techniques, demonstrating that analytical results are attainable even with the added complexity from thermodynamic inhibition. Furthermore, we numerically investigate the longterm behaviour. In the computational study, we investigate model behaviour for select parameters and two commonly used detachment functions. We investigate the effects of thermodynamic inhibition on the model and find that thermodynamic inhibition limits substrate utilization/production both inside the biofilm and inside the aqueous phase, resulting in less suspended bacteria and a thinner biofilm.

Representing Organic Matter Thermodynamics in Biogeochemical Reactions via Substrate-Explicit Modeling

Predictive biogeochemical modeling requires data-model integration that enables explicit representation of the sophisticated roles of microbial processes that transform substrates. Data from high-resolution organic matter (OM) characterization are increasingly available and can serve as a critical resource for this purpose, but their incorporation into biogeochemical models is often prohibited due to an over-simplified description of reaction networks. To fill this gap, we proposed a new concept of biogeochemical modeling-termed substrate-explicit modeling-that enables parameterizing OM-specific oxidative degradation pathways and reaction rates based on the thermodynamic properties of OM pools. Based on previous developments in the literature, we characterized the resulting kinetic models by only two parameters regardless of the complexity of OM profiles, which can greatly facilitate the integration with reactive transport models for ecosystem simulations by alleviating the difficulty in parameter identification. The two parameters include maximal growth rate (μmax) and harvest volume (Vh) (i.e., the volume that a microbe can access for harvesting energy). For every detected organic molecule in a given sample, our approach provides a systematic way to formulate reaction kinetics from chemical formula, which enables the evaluation of the impact of OM character on biogeochemical processes across conditions. In a case study of two sites with distinct OM thermodynamics using ultra high-resolution metabolomics datasets derived from Fourier transform ion cyclotron resonance mass spectrometry analyses, our method predicted how oxidative degradation is primarily driven by thermodynamic efficiency of OM consistent with experimental rate measurements (as shown by correlation coefficients of up to 0.61), and how biogeochemical reactions can vary in response to carbon and/or oxygen limitations. Lastly, we showed that incorporation of enzymatic regulations into substrate-explicit models is critical for more reasonable predictions. This result led us to present integrative biogeochemical modeling as a unifying framework that can ideally describe the dynamic interplay among microbes, enzymes, and substrates to address advanced questions and hypotheses in future studies. Altogether, the new modeling concept we propose in this work provides a foundational platform for unprecedented predictions of biogeochemical and ecosystem dynamics through enhanced integration with diverse experimental data and extant modeling approaches.

Thermodynamic Inhibition in Chemostat Models : With an Application to Bioreduction of Uranium

We formulate a mathematical model of bacterial populations in a chemostat setting that also accounts for thermodynamic growth inhibition as a consequence of chemical reactions. Using only elementary mathematical and chemical arguments, we carry this out for two systems: a simple toy model with a single species, a single substrate, and a single reaction product, and a more involved model that describes bioreduction of uranium[VI] into uranium[IV]. We find that in contrast to most traditional chemostat models, as a consequence of thermodynamic inhibition the equilibria concentrations of nutrient substrates might depend on their inflow concentration and not only on reaction parameters and the reactor's dilution rate. Simulation results of the uranium degradation model indicate that thermodynamic growth inhibition quantitatively alters the solution of the model. This suggests that neglecting thermodynamic inhibition effects in systems where they play a role might lead to wrong model predictions and under- or over-estimate the efficacy of the process under investigation.

Regulation-Structured Dynamic Metabolic Model Provides a Potential Mechanism for Delayed Enzyme Response in Denitrification Process

In a recent study of denitrification dynamics in hyporheic zone sediments, we observed a significant time lag (up to several days) in enzymatic response to the changes in substrate concentration. To explore an underlying mechanism and understand the interactive dynamics between enzymes and nutrients, we developed a trait-based model that associates a community's traits with functional enzymes, instead of typically used species guilds (or functional guilds). This enzyme-based formulation allows to collectively describe biogeochemical functions of microbial communities without directly parameterizing the dynamics of species guilds, therefore being scalable to complex communities. As a key component of modeling, we accounted for microbial regulation occurring through transcriptional and translational processes, the dynamics of which was parameterized based on the temporal profiles of enzyme concentrations measured using a new signature peptide-based method. The simulation results using the resulting model showed several days of a time lag in enzymatic responses as observed in experiments. Further, the model showed that the delayed enzymatic reactions could be primarily controlled by transcriptional responses and that the dynamics of transcripts and enzymes are closely correlated. The developed model can serve as a useful tool for predicting biogeochemical processes in natural environments, either independently or through integration with hydrologic flow simulators.

Thermodynamic and Kinetic Response of Microbial Reactions to High CO2

Geological carbon sequestration captures CO₂ from industrial sources and stores the CO₂ in subsurface reservoirs, a viable strategy for mitigating global climate change. In assessing the environmental impact of the strategy, a key question is how microbial reactions respond to the elevated CO₂ concentration. This study uses biogeochemical modeling to explore the influence of CO₂ on the thermodynamics and kinetics of common microbial reactions in subsurface environments, including syntrophic oxidation, iron reduction, sulfate reduction, and methanogenesis. The results show that increasing CO₂ levels decreases groundwater pH and modulates chemical speciation of weak acids in groundwater, which in turn affect microbial reactions in different ways and to different extents. Specifically, a thermodynamic analysis shows that increasing CO₂ partial pressure lowers the energy available from syntrophic oxidation and acetoclastic methanogenesis, but raises the available energy of microbial iron reduction, hydrogenotrophic sulfate reduction and methanogenesis. Kinetic modeling suggests that high CO₂ has the potential of inhibiting microbial sulfate reduction while promoting iron reduction. These results are consistent with the observations of previous laboratory and field studies, and highlight the complexity in microbiological responses to elevated CO₂ abundance, and the potential power of biogeochemical modeling in evaluating and quantifying these responses.

Surface waters as a sink and source of atmospheric gas phase ethanol

This study reports the first ethanol concentrations in fresh and estuarine waters and greatly expands the current data set for coastal ocean waters. Concentrations for 153 individual measurements of 11 freshwater sites ranged from 5 to 598 nM. Concentrations obtained for one estuarine transect ranged from 56 to 77 nM and levels in five coastal ocean depth profiles ranged from 81 to 334 nM. Variability in ethanol concentrations was high and appears to be driven primarily by photochemical and biological processes. 47 gas phase concentrations of ethanol were also obtained during this study to determine the surface water degree of saturation with respect to the atmosphere. Generally fresh and estuarine waters were undersaturated indicating they are not a source and may be a net sink for atmospheric ethanol in this region. Aqueous phase ethanol is likely converted rapidly to acetaldehyde in these aquatic ecosystems creating the undersaturated conditions resulting in this previously unrecognized sink for atmospheric ethanol. Coastal ocean waters may act as either a sink or source of atmospheric ethanol depending on the partial pressure of ethanol in the overlying air mass. Results from this study are significant because they suggest that surface waters may act as an important vector for the uptake of ethanol emitted into the atmosphere including ethanol from biofuel production and usage.

U(VI) bioreduction with emulsified vegetable oil as the electron donor--microcosm tests and model development

We conducted microcosm tests and biogeochemical modeling to study U(VI) reduction in contaminated sediments amended with emulsified vegetable oil (EVO). Indigenous microorganisms in the sediments degraded EVO and stimulated Fe(III), U(VI), and sulfate reduction, and methanogenesis. Acetate concentration peaked in 100-120 days in the EVO microcosms versus 10-20 days in the oleate microcosms, suggesting that triglyceride hydrolysis was a rate-limiting step in EVO degradation and subsequent reactions. Acetate persisted 50 days longer in oleate- and EVO- than in ethanol-amended microcosms, indicating that acetate-utilizing methanogenesis was slower in the oleate and EVO than ethanol microcosms. We developed a comprehensive biogeochemical model to couple EVO hydrolysis, production, and oxidation of long-chain fatty acids (LCFA), glycerol, acetate, and hydrogen, reduction of Fe(III), U(VI) and sulfate, and methanogenesis with growth and decay of multiple functional microbial groups. By estimating EVO, LCFA, and glycerol degradation rate coefficients, and introducing a 100 day lag time for acetoclastic methanogenesis for oleate and EVO microcosms, the model approximately matched observed sulfate, U(VI), and acetate concentrations. Our results confirmed that EVO could stimulate U(VI) bioreduction in sediments and the slow EVO hydrolysis and acetate-utilizing methanogens growth could contribute to longer term bioreduction than simple substrates (e.g., ethanol, acetate, etc.) in the subsurface.