Competitive and substrate limited environments drive metabolic heterogeneity for comammox Nitrospira.

Nitrospira has been revealed as a high versatile genus. Although previously considered only responsible for the conversion of nitrite to nitrate, now we know that Nitrospira can perform complete ammonia oxidation to nitrate too (comammox). Comammox activity was firstly reported as dominant in extremely limited oxygen environments, where anaerobic ammonia oxidation was also occurring (anammox). To explain the comammox selection, we developed an Individual-based Model able to describe Nitrospira and anammox growth in suspended flocs assembled in a dynamic nitrogen and oxygen-limiting environment. All known and hypothesized nitrogen transformations of Nitrospira were considered: ammonia and nitrite oxidation, comammox, nitrate-reducing ammonia oxidation, and anaerobic nitrite-reducing ammonia oxidation. Through bioenergetics analysis, the growth yield associated to each activity was estimated. The other kinetic parameters necessary to describe growth were calibrated according to the reported literature values. Our modeling results suggest that even extremely low oxygen concentrations (~1.0 µM) allow for a proportional growth of anammox versus Nitrospira similar to the one experimentally observed. The strong oxygen limitation was followed by a limitation of ammonia and nitrite, because anammox, without strong competitors, were able to grow faster than Nitrospira depleting the environment in nitrogen. These substrate limitations created an extremely competitive environment that proved to be decisive in the community assembly of Nitrospira and anammox. Additionally, a diversity of metabolic activities for Nitrospira was observed in all tested conditions, which in turn, explained the transient nitrite accumulation observed in aerobic environments with higher ammonia availability.

Reducing Systematic Uncertainty in Computed Redox Potentials for Aqueous Transition-Metal-Substituted Polyoxotungstates.

Polyoxometalates have attracted significant interest owing to their structural diversity, redox stability, and functionality at the nanoscale. In this work, density functional theory calculations have been employed to systematically study the accuracy of various exchange-correlation functionals in reproducing experimental redox potentials, U0Red in [PW11M(H2O)O39]q- M = Mn(III/II), Fe(III/II), Co(III/II), and Ru(III/II). U0Red calculations for [PW11M(H2O)O39]q- were calculated using a conductor-like screening model to neutralize the charge in the cluster. We explicitly located K+ counterions which induced positive shifting of potentials by > 500 mV. This approximation improved the reproduction of redox potentials for Kx[XW11M(H2O)O39]q-x M = Mn(III/II)/Co(III/II). However, uncertainties in U0Red for Kx[PW11M(H2O)O39]q-x M = Fe(III/II)/Ru(III/II) were observed because of the over-stabilization of the ion-pairs. Hybrid functionals exceeding 25% Hartree-Fock exchange are not recommended because of large uncertainties in ΔU0Red attributed to exaggerated proximity of the ion-pairs. Our results emphasize that understanding the nature of the electrode and electrolyte environment is essential to obtain a reasonable agreement between theoretical and experimental results.

Multiscale models driving hypothesis and theory-based research in microbial ecology.

Hypothesis and theory-based studies in microbial ecology have been neglected in favour of those that are descriptive and aim for data-gathering of uncultured microbial species. This tendency limits our capacity to create new mechanistic explanations of microbial community dynamics, hampering the improvement of current environmental biotechnologies. We propose that a multiscale modelling bottom-up approach (piecing together sub-systems to give rise to more complex systems) can be used as a framework to generate mechanistic hypotheses and theories (in-silico bottom-up methodology). To accomplish this, formal comprehension of the mathematical model design is required together with a systematic procedure for the application of the in-silico bottom-up methodology. Ruling out the belief that experimentation before modelling is indispensable, we propose that mathematical modelling can be used as a tool to direct experimentation by validating theoretical principles of microbial ecology. Our goal is to develop methodologies that effectively integrate experimentation and modelling efforts to achieve superior levels of predictive capacity.

Diversity and metabolic energy in bacteria.

Why are some groups of bacteria more diverse than others? We hypothesize that the metabolic energy available to a bacterial functional group (a biogeochemical group or 'guild') has a role in such a group's taxonomic diversity. We tested this hypothesis by looking at the metacommunity diversity of functional groups in multiple biomes. We observed a positive correlation between estimates of a functional group's diversity and their metabolic energy yield. Moreover, the slope of that relationship was similar in all biomes. These findings could imply the existence of a universal mechanism controlling the diversity of all functional groups in all biomes in the same way. We consider a variety of possible explanations from the classical (environmental variation) to the 'non-Darwinian' (a drift barrier effect). Unfortunately, these explanations are not mutually exclusive, and a deeper understanding of the ultimate cause(s) of bacterial diversity will require us to determine if and how the key parameters in population genetics (effective population size, mutation rate, and selective gradients) vary between functional groups and with environmental conditions: this is a difficult task.

Environmental and ecological controls of the spatial distribution of microbial populations in aggregates.

In microbial communities, the ecological interactions between species of different populations are responsible for the spatial distributions observed in aggregates (granules, biofilms or flocs). To explore the underlying mechanisms that control these processes, we have developed a mathematical modelling framework able to describe, label and quantify defined spatial structures that arise from microbial and environmental interactions in communities. An artificial system of three populations collaborating or competing in an aggregate is simulated using individual-based modelling under different environmental conditions. In this study, neutralism, competition, commensalism and concurrence of commensalism and competition have been considered. We were able to identify interspecific segregation of communities that appears in competitive environments (columned stratification), and a layered distribution of populations that emerges in commensal (layered stratification). When different ecological interactions were considered in the same aggregate, the resultant spatial distribution was identified as the one controlled by the most limiting substrate. A theoretical modulus was defined, with which we were able to quantify the effect of environmental conditions and ecological interactions to predict the most probable spatial distribution. The specific microbial patterns observed in our results allowed us to identify the optimal spatial organizations for bacteria to thrive when building a microbial community and how this permitted co-existence of populations at different growth rates. Our model reveals that although ecological relationships between different species dictate the distribution of bacteria, the environment controls the final spatial distribution of the community.

Biochemistry shapes growth kinetics of nitrifiers and defines their activity under specific environmental conditions.

Is it possible to find trends between the parameters that define microbial growth to help us explain the vast microbial diversity? Through an extensive database of kinetic parameters of nitrifiers, we analyzed if the dominance of specific populations of nitrifiers could be predicted and explained. We concluded that, in general, higher growth yield (YXS ) and ammonia affinity (a0NH3 ) and lower growth rate (µmax ) are observed for ammonia-oxidizing archaea (AOA) than bacteria (AOB), which would explain their considered dominance in oligotrophic environments. However, comammox (CMX), with the maximum energy harvest per mole of ammonia, and some AOB, have higher a0NH3 and lower µmax than some AOA. Although we were able to correlate the presence of specific terminal oxidases with observed oxygen affinities (a0O2 ) for nitrite-oxidizing bacteria (NOB), that correlation was not observed for AOB. Moreover, the presumed dominance of AOB over NOB in O2 -limiting environments is discussed. Additionally, lower statistical variance of a0O2 values than for ammonia and nitrite affinities was observed, suggesting nitrogen limitation as a stronger selective pressure. Overall, specific growth strategies within nitrifying groups were not identified through the reported kinetic parameters, which might suggest that mostly, fundamental differences in biochemistry are responsible for underlying kinetic parameters.

Valorization of lipid-rich wastewaters: A theoretical analysis to tackle the competition between polyhydroxyalkanoate and triacylglyceride-storing populations.

The lipid fraction of the effluents generated in several food-processing activities can be transformed into polyhydroxyalkanoates (PHAs) and triacylglycerides (TAGs), through open culture biotechnologies. Although competition between storing and non-storing populations in mixed microbial cultures (MMCs) has been widely studied, the right selective environment allowing for the robust enrichment of a community when different types of accumulators coexist is still not clear. In this research, comprehensive metabolic analyses of PHA and TAG synthesis and degradation, and concomitant respiration of external carbon, were used to understand and explain the changes observed in a laboratory-scale bioreactor fed with the lipid-rich fraction (mainly oleic acid) of a wastewater stream produced in the fish-canning industry. It was concluded that the mode of oxygen, carbon, and nitrogen supply determines the enrichment of the culture in specific populations, and hence the type of intracellular compounds preferentially accumulated. Coupled carbon and nitrogen feeding regime mainly selects for TAG producers whereas uncoupled feeding leads to PHA or TAG production function of the rate of carbon supply under specific aeration rates and feast and famine phases lengths.

Looking for Options to Sustainably Fixate Nitrogen. Are Molecular Metal Oxides Catalysts a Viable Avenue?

Fast and reliable industrial production of ammonia (NH3) is fundamentally sustaining modern society. Since the early 20th Century, NH3 has been synthesized via the Haber-Bosch process, running at conditions of around 350-500°C and 100-200 times atmospheric pressure (15-20 MPa). Industrial ammonia production is currently the most energy-demanding chemical process worldwide and contributes up to 3% to the global carbon dioxide emissions. Therefore, the development of more energy-efficient pathways for ammonia production is an attractive proposition. Over the past 20 years, scientists have imagined the possibility of developing a milder synthesis of ammonia by mimicking the nitrogenase enzyme, which fixes nitrogen from the air at ambient temperatures and pressures to feed leguminous plants. To do this, we propose the use of highly reconfigurable molecular metal oxides or polyoxometalates (POMs). Our proposal is an informed design of the polyoxometalate after exploring the catabolic pathways that cyanobacteria use to fix N2 in nature, which are a different route than the one followed by the Haber-Bosch process. Meanwhile, the industrial process is a "brute force" system towards breaking the triple bond N-N, needing high pressure and high temperature to increase the rate of reaction, nature first links the protons to the N2 to later easier breaking of the triple bond at environmental temperature and pressure. Computational chemistry data on the stability of different polyoxometalates will guide us to decide the best design for a catalyst. Testing different functionalized molecular metal oxides as ammonia catalysts laboratory conditions will allow for a sustainable reactor design of small-scale production.

A framework based on fundamental biochemical principles to engineer microbial community dynamics.

Microbial communities are complex but there are basic principles we can apply to constrain the assumed stochasticity of their activity. By understanding the trade-offs behind the kinetic parameters that define microbial growth, we can explain how local interspecies dependencies arise and shape the emerging properties of a community. If we integrate these theoretical descriptions with experimental 'omics' data and bioenergetics analysis of specific environmental conditions, predictions on activity, assembly and spatial structure can be obtained reducing the a priori unpredictable complexity of microbial communities. This information can be used to define the appropriate selective pressures to engineer bioprocesses and propose new hypotheses which can drive experimental research to accelerate innovation in biotechnology.

A novel strategy for triacylglycerides and polyhydroxyalkanoates production using waste lipids.

Lipids are one of the main components of the organic matter present in the effluents of the food-processing industry. These waste streams can be biotransformed into valuable triacylglycerides (TAGs) and polyhydroxyalkanoates (PHAs), precursors of biofuels and biomaterials alternative to petroleum-based products. These compounds are yielded by mixed microbial cultures, and considering that both TAG and PHA accumulators may coexist within the community, it seems crucial to define those operational strategies that might control the selection of the dominant metabolic pathways (TAG or PHA accumulation). In this work, residual fish-canning oil was used as a carbon source in a two-stage process (culture selection and intracellular compounds accumulation) in which the substrate was simultaneously hydrolyzed in these two stages without the need for a previous fermentation unit. It was pretended to maximize preferential TAG or PHA storage in the accumulation reactor by the imposition of certain selective pressures in the enrichment one. Uncoupling C and N feedings and limiting nitrogen availability in the medium, allowed to maximize PHA production (82.3 wt% of PHAs, 0.80 CmmolPHA/CmmolS). Besides, when low pH in the famine phase was considered as additional selective pressure, it was possible to shift the ratio TAG:PHA from 4:96 obtaining 43.0 wt% of TAGs (0.67 CmmolTAG/CmmolS). Therefore, this novel and simplified process demonstrated versatility and efficiency in the storage of TAGs and PHAs from a unique residual feedstock and using an open culture proving that product selection can be harnessed if choosing the right operational conditions in the enrichment stage.

Evolutionary causes and consequences of metabolic division of labour: why anaerobes do and aerobes don't.

Metabolic division of the labour of organic matter decomposition into several steps carried out by different types of microbes is typical for many anoxic - but not oxic environments. An explanation of this well-known pattern is proposed based on the combination of three key insights: (i) well-studied anoxic environments are high flux environments: they are only anoxic because their high organic matter influx leads to oxygen depletion; (ii) shorter, incomplete catabolic pathways provide the capacity for higher flux, but this capacity is only advantageous in high flux environments; (iii) longer, complete catabolic pathways have energetic happy ends but only with high redox potential electron acceptors. Thus, aerobic environments favour longer pathways. Bioreactors, in contrast, are high flux environments and therefore favour division of catabolic labour even if aeration keeps them aerobic; therefore, host strains and feeding strategies must be carefully engineered to resist this pull.

NUFEB: A massively parallel simulator for individual-based modelling of microbial communities.

We present NUFEB (Newcastle University Frontiers in Engineering Biology), a flexible, efficient, and open source software for simulating the 3D dynamics of microbial communities. The tool is based on the Individual-based Modelling (IbM) approach, where microbes are represented as discrete units and their behaviour changes over time due to a variety of processes. This approach allows us to study population behaviours that emerge from the interaction between individuals and their environment. NUFEB is built on top of the classical molecular dynamics simulator LAMMPS (Large-scale Atomic/Molecular Massively Parallel Simulator), which we extended with IbM features. A wide range of biological, physical and chemical processes are implemented to explicitly model microbial systems, with particular emphasis on biofilms. NUFEB is fully parallelised and allows for the simulation of large numbers of microbes (107 individuals and beyond). The parallelisation is based on a domain decomposition scheme that divides the domain into multiple sub-domains which are distributed to different processors. NUFEB also offers a collection of post-processing routines for the visualisation and analysis of simulation output. In this article, we give an overview of NUFEB's functionalities and implementation details. We provide examples that illustrate the type of microbial systems NUFEB can be used to model and simulate.

Individual Based Model Links Thermodynamics, Chemical Speciation and Environmental Conditions to Microbial Growth.

Individual based Models (IbM) must transition from research tools to engineering tools. To make the transition we must aspire to develop large, three dimensional and physically and biologically credible models. Biological credibility can be promoted by grounding, as far as possible, the biology in thermodynamics. Thermodynamic principles are known to have predictive power in microbial ecology. However, this in turn requires a model that incorporates pH and chemical speciation. Physical credibility implies plausible mechanics and a connection with the wider environment. Here, we propose a step toward that ideal by presenting an individual based model connecting thermodynamics, pH and chemical speciation and environmental conditions to microbial growth for 5·105 individuals. We have showcased the model in two scenarios: a two functional group nitrification model and a three functional group anaerobic community. In the former, pH and connection to the environment had an important effect on the outcomes simulated. Whilst in the latter pH was less important but the spatial arrangements and community productivity (that is, methane production) were highly dependent on thermodynamic and reactor coupling. We conclude that if IbM are to attain their potential as tools to evaluate the emergent properties of engineered biological systems it will be necessary to combine the chemical, physical, mechanical and biological along the lines we have proposed. We have still fallen short of our ideals because we cannot (yet) calculate specific uptake rates and must develop the capacity for longer runs in larger models. However, we believe such advances are attainable. Ideally in a common, fast and modular platform. For future innovations in IbM will only be of use if they can be coupled with all the previous advances.

Bioenergetics analysis of ammonia-oxidizing bacteria and the estimation of their maximum growth yield.

The currently accepted biochemistry and bioenergetics of ammonia-oxidizing bacteria (AOB) show an inefficient metabolism: only 53.8% of the energy released when a mole of ammonia is oxidised and less than two of the electrons liberated can be directed to the autotrophic anabolism. However, paradoxically, AOB seem to thrive in challenging conditions: growing readily in virtually most aerobic environment, yet limited AOB exist in pure culture. In this study, a comprehensive model of the biochemistry of the metabolism of AOB is presented. Using bioenergetics calculations and selecting the minimum estimation for the energy dissipated in each of the metabolic steps, the model predicts the highest possible true yield of 0.16 gBio/gN and a yield of 0.13 gBio/gN when cellular maintenance is considered. Observed yields should always be lower than these values but the range of experimental values in literature vary between 0.04 and 0.45 gBio/gN. In this work, we discuss if this variance of observed values for AOB growth yield could be understood if other non-considered alternative energy sources are present in the biochemistry of AOB. We analyse how the predicted maximum growth yield of AOB changes considering co-metabolism, the use of hydroxylamine as a substrate, the abiotic oxidation of NO, energy harvesting in the monooxygenase enzyme or the use of organic carbon sources.

Activity corrections are required for accurate anaerobic digestion modelling.

The impact on the prediction of key process variables in anaerobic digestion (AD) when activity corrections are neglected (e.g. when ideal solution is assumed) is evaluated in this paper. The magnitude of deviations incurred in key variables was quantified using a generalised physicochemistry modelling framework that incorporates activity corrections. Deviations incurred on the intermediate and partial alkalinity ratio (a key control variable in AD) already reach values over 20% in typical AD scenarios at low ionic strengths. Deviations of moderate importance (∼5%) in free ammonia, hydrogen sulfide inhibition, as well as in the biogas composition, were observed. Those errors become very large for components involving multiple deprotonations, such as inorganic phosphorus, and their magnitude (∼40%) would impede proper precipitation modelling. A dynamic AD case simulation involving a series of overloads showed model underpredictions of the process acidification when activity corrections are neglected. This compromises control actions based on such models. Based on these results, a systematic incorporation of activity corrections in AD models is strongly recommended. This will prevent model overfitting to observations related to inaccurate physicochemistry modelling, at a marginal computational cost. Alternatives for these implementations are also discussed.

Heterogeneity in Pure Microbial Systems: Experimental Measurements and Modeling.

Cellular heterogeneity influences bioprocess performance in ways that until date are not completely elucidated. In order to account for this phenomenon in the design and operation of bioprocesses, reliable analytical and mathematical descriptions are required. We present an overview of the single cell analysis, and the mathematical modeling frameworks that have potential to be used in bioprocess control and optimization, in particular for microbial processes. In order to be suitable for bioprocess monitoring, experimental methods need to be high throughput and to require relatively short processing time. One such method used successfully under dynamic conditions is flow cytometry. Population balance and individual based models are suitable modeling options, the latter one having in particular a good potential to integrate the various data collected through experimentation. This will be highly beneficial for appropriate process design and scale up as a more rigorous approach may prevent a priori unwanted performance losses. It will also help progressing synthetic biology applications to industrial scale.

A mechanistic Individual-based Model of microbial communities.

Accurate predictive modelling of the growth of microbial communities requires the credible representation of the interactions of biological, chemical and mechanical processes. However, although biological and chemical processes are represented in a number of Individual-based Models (IbMs) the interaction of growth and mechanics is limited. Conversely, there are mechanically sophisticated IbMs with only elementary biology and chemistry. This study focuses on addressing these limitations by developing a flexible IbM that can robustly combine the biological, chemical and physical processes that dictate the emergent properties of a wide range of bacterial communities. This IbM is developed by creating a microbiological adaptation of the open source Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS). This innovation should provide the basis for "bottom up" prediction of the emergent behaviour of entire microbial systems. In the model presented here, bacterial growth, division, decay, mechanical contact among bacterial cells, and adhesion between the bacteria and extracellular polymeric substances are incorporated. In addition, fluid-bacteria interaction is implemented to simulate biofilm deformation and erosion. The model predicts that the surface morphology of biofilms becomes smoother with increased nutrient concentration, which agrees well with previous literature. In addition, the results show that increased shear rate results in smoother and more compact biofilms. The model can also predict shear rate dependent biofilm deformation, erosion, streamer formation and breakup.

Microbial catabolic activities are naturally selected by metabolic energy harvest rate.

The fundamental trade-off between yield and rate of energy harvest per unit of substrate has been largely discussed as a main characteristic for microbial established cooperation or competition. In this study, this point is addressed by developing a generalized model that simulates competition between existing and not experimentally reported microbial catabolic activities defined only based on well-known biochemical pathways. No specific microbial physiological adaptations are considered, growth yield is calculated coupled to catabolism energetics and a common maximum biomass-specific catabolism rate (expressed as electron transfer rate) is assumed for all microbial groups. Under this approach, successful microbial metabolisms are predicted in line with experimental observations under the hypothesis of maximum energy harvest rate. Two microbial ecosystems, typically found in wastewater treatment plants, are simulated, namely: (i) the anaerobic fermentation of glucose and (ii) the oxidation and reduction of nitrogen under aerobic autotrophic (nitrification) and anoxic heterotrophic and autotrophic (denitrification) conditions. The experimentally observed cross feeding in glucose fermentation, through multiple intermediate fermentation pathways, towards ultimately methane and carbon dioxide is predicted. Analogously, two-stage nitrification (by ammonium and nitrite oxidizers) is predicted as prevailing over nitrification in one stage. Conversely, denitrification is predicted in one stage (by denitrifiers) as well as anammox (anaerobic ammonium oxidation). The model results suggest that these observations are a direct consequence of the different energy yields per electron transferred at the different steps of the pathways. Overall, our results theoretically support the hypothesis that successful microbial catabolic activities are selected by an overall maximum energy harvest rate.

Metabolic energy-based modelling explains product yielding in anaerobic mixed culture fermentations.

The fermentation of glucose using microbial mixed cultures is of great interest given its potential to convert wastes into valuable products at low cost, however, the difficulties associated with the control of the process still pose important challenges for its industrial implementation. A deeper understanding of the fermentation process involving metabolic and biochemical principles is very necessary to overcome these difficulties. In this work a novel metabolic energy based model is presented that accurately predicts for the first time the experimentally observed changes in product spectrum with pH. The model predicts the observed shift towards formate production at high pH, accompanied with ethanol and acetate production. Acetate (accompanied with a more reduced product) and butyrate are predicted main products at low pH. The production of propionate between pH 6 and 8 is also predicted. These results are mechanistically explained for the first time considering the impact that variable proton motive potential and active transport energy costs have in terms of energy harvest over different products yielding. The model results, in line with numerous reported experiments, validate the mechanistic and bioenergetics hypotheses that fermentative mixed cultures products yielding appears to be controlled by the principle of maximum energy harvest and the necessity of balancing the redox equivalents in absence of external electron acceptors.