Thermodynamic modelling of synthetic communities predicts minimum free energy requirements for sulfate reduction and methanogenesis

Investigating the activity of indigenous microbial communities from Italian depleted gas reservoirs and their possible impact on underground hydrogen storage

H2 produced from renewable energies will play a central role in both greenhouse gas reduction and decarbonization by 2050. Nonetheless, to improve H2 diffusion and utilization as a fuel, large storage capacity systems are needed. Underground storage of natural gas in depleted reservoirs, aquifers and salt caverns is a well-established technology. However, new challenges arise when it comes to storing hydrogen due to the occurrence and activity of indigenous microbial populations in deep geological formations. In a previous study, four Italian natural gas reservoirs were characterized both from a hydro-chemical and microbiological point of view, and predictive functional analyses were carried out with the perspective of underground hydrogen storage (UHS). In the present work, formation waters from the same reservoirs were used as inoculant during batch cultivation tests to characterize microbial activity and its effects on different gas mixtures. Results evidence a predominant acidogenic/acetogenic activity, whilst methanogenic and sulfate reducing activity were only marginal for all tested inoculants. Furthermore, the microbial activation of tested samples is strongly influenced by nutrient availability. Obtained results were fitted and screened in a computational model which would allow deep insights in the study of microbial activity in the context of UHS.

Closed ecosystems extract energy through self-organized nutrient cycles

Our planet is a self-sustaining ecosystem powered by light energy from the sun, but roughly closed to matter. Many ecosystems on Earth are also approximately closed to matter and recycle nutrients by self-organizing stable nutrient cycles, e.g., microbial mats, lakes, open ocean gyres. However, existing ecological models do not exhibit the self-organization and dynamical stability widely observed in such planetary-scale ecosystems. Here, we advance a conceptual model that explains the self-organization, stability, and emergent features of closed microbial ecosystems. Our model incorporates the bioenergetics of metabolism into an ecological framework. By studying this model, we uncover a crucial thermodynamic feedback loop that enables metabolically diverse communities to almost always stabilize nutrient cycles. Surprisingly, highly diverse communities self-organize to extract [Formula: see text]10[Formula: see text] of the maximum extractable energy, or [Formula: see text]100 fold more than randomized communities. Further, with increasing diversity, distinct ecosystems show strongly correlated fluxes through nutrient cycles. However, as the driving force from light increases, the fluxes of nutrient cycles become more variable and species-dependent. Our results highlight that self-organization promotes the efficiency and stability of complex ecosystems at extracting energy from the environment, even in the absence of any centralized coordination.

Microbiological hydrogen (H2 ) thresholds in anaerobic continuous-flow systems: Effects of system characteristics

Hydrogen (H₂ ) concentrations that were associated with microbiological respiratory processes (RPs) such as sulfate reduction and methanogenesis were quantified in continuous-flow systems (CFSs) (e.g., bioreactors, sediments). Gibbs free energy yield (ΔǴ ~ 0) of the relevant RP has been proposed to control the observed H₂ concentrations, but most of the reported values do not align with the proposed energetic trends. Alternatively, we postulate that system characteristics of each experimental design influence all system components including H₂ concentrations. To analyze this proposal, a Monod-based mathematical model was developed and used to design a gas-liquid bioreactor for hydrogenotrophic methanogenesis with Methanobacterium bryantii M.o.H. Gas-to-liquid H₂ mass transfer, microbiological H₂ consumption, biomass growth, methane formation, and Gibbs free energy yields were evaluated systematically. Combining model predictions and experimental results revealed that an initially large biomass concentration created transients during which biomass consumed [H₂ ]_L rapidly to the thermodynamic H₂ -threshold (≤1 nM) that triggerred the microorganisms to stop H₂ oxidation. With no H₂ oxidation, continuous gas-to-liquid H₂ transfer increased [H₂ ]_L to a level that signaled the methanogens to resume H₂ oxidation. Thus, an oscillatory H₂ -concentration profile developed between the thermodynamic H₂ -threshold (≤1 nM) and a low [H₂ ]_L (~10 nM) that relied on the rate of gas-to-liquid H₂ -transfer. The transient [H₂ ]_L values were too low to support biomass synthesis that could balance biomass losses through endogenous oxidation and advection; thus, biomass declined continuously and disappeared. A stable [H₂ ]_L (1807 nM) emerged as a result of abiotic H₂ -balance between gas-to-liquid H₂ transfer and H₂ removal via advection of liquid-phase.

Complexation and enantioselectivity of novel bridge-like uranyl- 2-((1Z,9Z)-9-(2-Hydroxyphenyl)-3,5,6,8-tetrahydrobenzo[h][1,4,7,10] dioxadiazacyclododecin-2-yl)-5-methoxyphenol with chiral organophosphorus pesticide enantiomers of R/S-malathions

Designing new uranyl complexes with enantioselectivity is of great significance for the identification and separation of enantiomers of chiral pesticides. In this paper, a new asymmetric rigid uranyl-2-((1Z,9Z)-9-(2-Hydroxyphenyl)-3,5,6,8-tetrahydrobenzo[h][1,4,7,10] dioxadiaza-cyclododecin-2-yl)-5-methoxyphenol(Uranyl-HTDM) was designed, we used Uranyl-HTDM as a receptor to selectively coordinate with the guests of the chiral organophosphorus pesticide R/S-malathions(R/S-MLTs) to explore the receptor's enatioselectivity recognition of the chiral guests of R/S-MLTs. Density functional theory (DFT) method was used to comprehensively study the complexation mode of the receptor with enantiomers. The results showed that the U of Uranyl-HTDM could coordinate with both the thiophosphoryl sulfur and carbonyl oxygens of R/S-MLTs in different environments, respectively. The thermodynamics calculations further indicated that the receptor could selectively recognize the thiophosphoryl sulfur and carbonyl oxygen atoms of R/S-malathions, and the complexation abilities of Uranyl-HTDM to the R/S-malathions under different solvents were not the same. The smaller the polarity of solvents, the stronger the complexation ability of Uranyl-HTDM with R-malathion, toluene was an ideal solvent with large △G change and enatioselectivity coefficient of 99.55%. The study provides useful references for the design of new uranyl-salophens and for the experimental study on the molecular recognition of chiral organophosphorus pesticides.

Modeling a propionate-oxidizing syntrophic coculture using thermodynamic principles

A coculture of Syntrophobacter fumaroxidans and Methanospirillum hungatei was modeled using four biokinetic models, which only differed by the functions used to describe the growth yields (dynamic or constant) and the hydrogen inhibition function (noncompetitive or based on thermodynamics). First, a batch experiment was used to train the model and analyze the fitted parameters. Two fitting procedures were followed by minimizing the error on different indicators. Second, a chemostat experiment was used as a test data set to assess the predictive power of the models. Overall, the four models were able to accurately fit the train data set following both fitting procedures. However, some parameters fitted with the ADM1-like model differed significantly from values reported in the literature and were dependent on the fitting procedure. When applied to the test data set it systematically resulted in positive Gibbs free energy changes values for propionate oxidation, in contradiction with the second law of thermodynamics. On the opposite, the parameters fitted with model including both a thermodynamic-based inhibition function and a dynamic computation of growth yields were more consistent with values reported in the literature and repeatable whatever the fitting procedure. The results highlight the potential of implementing thermodynamic-based functions in biokinetic models.

A scalable model of fluid flow, substrate removal and current production in microbial fuel cells

Mathematical modelling can reduce the cost and time required to design complex systems, and is being increasingly used in microbial electrochemical technologies (METs). To be of value such models must be complex enough to reproduce important behaviour of MET, yet simple enough to provide insight into underlying causes of this behaviour. Ideally, models must also be scalable to future industrial applications, rather than limited to describing existing laboratory experiments. We present a scalable model for simulating both fluid flow and bioelectrochemical processes in microbial fuel cells (MFCs), benchmarking against an experimental pilot-scale bioreactor. The model describes substrate transport through a two-dimensional fluid domain, and biofilm growth on anode surfaces. Electron transfer is achieved by an intracellular redox mediator. We find significant spatial variations in both substrate concentration and current density. Simple changes to the reactor layout can greatly improve the overall efficiency, measured in terms of substrate removal and total current generated.

Thermodynamic constraints on the assembly and diversity of microbial ecosystems are different near to and far from equilibrium

Non-equilibrium thermodynamics has long been an area of substantial interest to ecologists because most fundamental biological processes, such as protein synthesis and respiration, are inherently energy-consuming. However, most of this interest has focused on developing coarse ecosystem-level maximisation principles, providing little insight into underlying mechanisms that lead to such emergent constraints. Microbial communities are a natural system to decipher this mechanistic basis because their interactions in the form of substrate consumption, metabolite production, and cross-feeding can be described explicitly in thermodynamic terms. Previous work has considered how thermodynamic constraints impact competition between pairs of species, but restrained from analysing how this manifests in complex dynamical systems. To address this gap, we develop a thermodynamic microbial community model with fully reversible reaction kinetics, which allows direct consideration of free-energy dissipation. This also allows species to interact via products rather than just substrates, increasing the dynamical complexity, and allowing a more nuanced classification of interaction types to emerge. Using this model, we find that community diversity increases with substrate lability, because greater free-energy availability allows for faster generation of niches. Thus, more niches are generated in the time frame of community establishment, leading to higher final species diversity. We also find that allowing species to make use of near-to-equilibrium reactions increases diversity in a low free-energy regime. In such a regime, two new thermodynamic interaction types that we identify here reach comparable strengths to the conventional (competition and facilitation) types, emphasising the key role that thermodynamics plays in community dynamics. Our results suggest that accounting for realistic thermodynamic constraints is vital for understanding the dynamics of real-world microbial communities.

There is a growing interest in microbial communities due to their important role in biogeochemical cycling as well as plant and animal health. Although our understanding of thermodynamic constraints on individual cells is rapidly improving, the impact of these constraints on complex microbial communities remains largely unexplored theoretically and empirically. Here, we develop a new microbial community model which allows thermodynamic efficiency and entropy production to be calculated directly. We find that availability of substrates with greater free-energy allows for a faster rate of niche generation, leading to higher final species diversity. We also show that when the free-energy availability is low, species with reactions close to thermodynamic equilibrium are favoured, leading to more diverse and efficient communities. In addition to the conventional interaction types (competition and facilitation), our model reveals the existence of two novel interaction types mediated by products rather than substrates. Though the conventional interactions are generally the strongest, the novel interaction types are significant when free-energy availability is low. Our results suggest that non-equilibrium thermodynamics need to be considered when studying microbial community dynamics.

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.

Energy-Based Modeling of the Feedback Control of Biomolecular Systems With Cyclic Flow Modulation

Energy-based modelling brings engineering insight to the understanding of biomolecular systems. It is shown how well-established control engineering concepts, such as loop-gain, arise from energy feedback loops and are therefore amenable to control engineering insight. In particular, a novel method is introduced to allow the transfer function based approach of classical linear control to be utilised in the analysis of feedback systems modelled by network thermodynamics and thus amalgamate energy-based modelling with control systems analysis. The approach is illustrated using a class of metabolic cycles with activation and inhibition leading to the concept of Cyclic Flow Modulation.

Network Thermodynamical Modeling of Bioelectrical Systems: A Bond Graph Approach

Interactions among biomolecules, electrons, and protons are essential to many fundamental processes sustaining life. It is therefore of interest to build mathematical models of these bioelectrical processes not only to enhance understanding but also to enable computer models to complement in vitro and in vivo experiments. Such models can never be entirely accurate; it is nevertheless important that the models are compatible with physical principles. Network Thermodynamics, as implemented with bond graphs, provide one approach to creating physically compatible mathematical models of bioelectrical systems. This is illustrated using simple models of ion channels, redox reactions, proton pumps, and electrogenic membrane transporters thus demonstrating that the approach can be used to build mathematical and computer models of a wide range of bioelectrical systems.

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.

Not Just Numbers: Mathematical Modelling and Its Contribution to Anaerobic Digestion Processes

Mathematical modelling of bioprocesses has a long and notable history, with eminent contributions from fields including microbiology, ecology, biophysics, chemistry, statistics, control theory and mathematical theory. This richness of ideas and breadth of concepts provide great motivation for inquisitive engineers and intrepid scientists to try their hand at modelling, and this collaboration of disciplines has also delivered significant milestones in the quality and application of models for both theoretical and practical interrogation of engineered biological systems. The focus of this review is the anaerobic digestion process, which, as a technology that has come in and out of fashion, remains a fundamental process for addressing the global climate emergency. Whether with conventional anaerobic digestion systems, biorefineries, or other anaerobic technologies, mathematical models are important tools that are used to design, monitor, control and optimise the process. Both highly structured, mechanistic models and data-driven approaches have been used extensively over half a decade, but recent advances in computational capacity, scientific understanding and diversity and quality of process data, presents an opportunity for the development of new modelling paradigms, augmentation of existing methods, or even incorporation of tools from other disciplines, to ensure that anaerobic digestion research can remain resilient and relevant in the face of emerging and future challenges.

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.