Bioenergetics-based modelling of microbial ecosystems for biotechnological applications

The bioenergetics analysis and mathematical modelling of several bioprocesses with industrial interest aiming for waste materials recovery, is conducted in this Thesis. The objective is to mechanistically understand the physical limits of the processes together with the ecological interactions established in their different microbial ecosystems. This new knowledge could lead towards an improvement of the bioprocesses control increasing their efficiency. Three mathematical models have been developed based on bioenergetics and minimizing the empirical information necessary. Firstly, a novel metabolic energy-based model has been developed that accurately predicts the experimentally observed changes in product spectrum with pH variations when glucose is fermented in acidogenic conditions. The results are mechanistically explained analysing, under different environmental conditions, the impact that variable proton motive potential and active transport energy costs have in terms of energy harvest over products yielding. Secondly, several bioenergetics analyses to investigate the potential reversibility of specific anaerobic pathways of interest (more reduced products yielding with higher energy density) have been developed. Thermodynamics of the different steps in biochemical pathways are analysed and combined with assumptions concerning kinetic and physiological constraints to evaluate if the pathways are potentially reversible by imposing changes in process conditions. And thirdly, a last model is presented based on the assumption that mixed cultures are composed by undefined species competing for the energetic resources available and limited by the fundamental trade-off between yield and rate of energy harvest per unit of substrate. In this model, the competition between existing and non-experimentally reported microbial catabolic activities, is simulated. Successful ecological relations of competition or collaboration are predicted under the hypothesis of maximum energy harvest rate and in line with experimental observations

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

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

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

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

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

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

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

Linking thermodynamics and kinetics to assess pathway reversibility in anaerobic bioprocesses

The on-going research towards sustainable fuel production entails the improvement of the microbial catalysts involved. The possible reversibility of specific anaerobic catabolic reactions opens up a range of possibilities for the development of novel reductive bioprocesses. These reductive biohydrogenation pathways enable production of high energy density chemicals of interest as biofuels such as alcohols and long chain fatty acids. Anaerobic bioprocesses take place under energy scarcity conditions due to the absence of strong electron acceptors such as oxygen, and provide metabolic pathways towards these energy dense (reduced) chemicals. Metabolic reactions take place very close to thermodynamic equilibrium with minimum energy dissipation and consequently, environmental changes in product and substrate concentrations can easily reverse the driving force of the chemical reaction catalysed. The objective of this work is to investigate the potential reversibility of specific anaerobic pathways of interest. The thermodynamics of the different steps in biochemical pathways are analysed and combined with assumptions concerning kinetic and physiological constraints to evaluate if pathways are potentially reversible by imposing changes in process conditions. The results suggest that (i) in homoacetogenesis they may operate in both reductive and oxidative directions depending on the hydrogen partial pressure in the system, (ii) acetate reduction to butyrate with hydrogen is not feasible, but no biochemical bottlenecks are apparent in butyrate production from acetate with ethanol or lactate as electron donors, (iii) the reduction of short chain to longer chain fatty acids with ethanol as the electron donor appears thermodynamically and kinetically feasible, and (iv) alcohol production from the corresponding fatty acids (e.g. ethanol from acetate) was found to require proton translocations at specific sites in the biochemical pathways in order to compensate for the ATP required for phosphatation of acetate and to enable energy harvesting. Overall, the methodology proposed here allows for analysing the potential reversibility of catabolic pathways and therewith contributes to the development of efficient and reliable anaerobic bioprocesses for the production of biofuels and chemicals

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 analysed 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 (a0 NH3) and lower growth rate (µmax) are observed for ammonia-oxidising 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 a0 NH3 and lower µmax than some AOA. Although we were able to correlate the presence of specific terminal oxidases with observed oxygen affinities (a0 O2) for nitrite-oxidising 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 a0 O2 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