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How do energy gradients shape microbial communities? Study of the Microbial Transition State (MTS) approach for modelling microbial ecosystems dynamics and its application to environmental biotechnology processes
Abstract
Microbial communities play a key role in geochemical cycles and environmental bioprocesses. Despite their importance, the mechanisms involved in their structuration remain elusive and are poorly captured in current models. The modelling approach developed during this thesis stands as an alternative to the current empirical approaches. It relies on a novel theory of microbial growth (the MTS theory), which introduce a flux/force relationship between the microbial growth rate and the free energy gradients available in the biotope. The purpose of this thesis is to characterize the dynamic properties of the MTS model and to determine, through simulations, the part of the microbial communities’ spatio-temporal structuration that is intrinsically captured by the MTS theory and which does not pertain to parameters adjustment.Simulations firstly reveal that a characteristic of the MTS model is its ability to account for the simultaneous growth limitation by many resources of different kinds (electron acceptor/donor, but also nutrients), and to integrate them as stoichiometric limitations, giving rise to coherent populations dynamics.In a second stage, the MTS model has been used to predict the dynamics of microbial communities. Those studies revealed that the thermodynamics constraints on which the MTS kinetic theory is built intrinsically give rise to consistent ecological successions without the need to adjust specifically the parameters of each population. In the case of a simplified activated sludge ecosystem, after calibration using respirometric data, the model was able to reproduce ecosystem dynamics quantitatively with a reduced number of parameters compared to current Activated Sludge Models (ASM).In a third stage, a large database of experimental growth yield observations has been compiled from literature. The relationship between multiple physicochemical parameters characterizing the metabolisms (reduction degrees, catabolic energy...) and the growth yield has been investigated using statistical methods. This work confirms that microbial growth yields can be accurately predicted solely on thermodynamic properties of metabolic reactions. The growth yields predictor could be included in future developments of the MTS models.More generally, the work undertaken during this thesis evidenced that the MTS model proposes a formalization of the coupling between thermodynamic and dynamic variables of a microbial ecosystem. The simulated microbial populations and ecosystems display coherent dynamic behaviors. The model is able to account, by construction, for well-known ecological successions, without specific parameter adjustment. This model is peculiarly adapted to the prediction of the functional structure of communities in ecosystems dominated by selection by competition, rather than on species dispersion, diversification or genetic drift.Those results encourage the development of microbial ecosystems based on firmer theoretical grounds. Such models are necessary to the development of bioprocesses able to answer to the new technological and environmental challenges.
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In this work a novel integrated biokinetic wastewater treatment (WWT) model based on the smoothed particle hydrodynamics (SPH) method as hydraulic model is proposed. Significant outcomes of this work are the computation of a detailed spatial distribution of compounds in WWT basins and the quantification of the effects of the stirrer induced mixing on the evolution of compounds. SPH is a meshfree particle method which herein is applied to compute a treatment plant's reactor hydraulics. The characteristic feature of SPH is to describe a fluid's dynamics by particles that move along with the flow. The present WWT model takes advantage of this principle by assigning the compounds' concentrations, which are defined by the activated sludge model no. 1, to SPH particles. A full-scale treatment plant simulation with a variable stirrer induced mixing intensity in the denitrification basin is performed. A spatial distribution of the compounds' concentrations , which up to now was unknown for unsteady flows, is computed and analysed. The developed framework is generic and therefore expected to be applicable for modelling chemical engineering processes which are influenced by hydrodynamic effects.
Soil bacteria provide a large range of ecosystem services such as nutrient cycling. Despite their important role in soil systems, compositional and functional responses of bacterial communities to different land use and management regimes are not fully understood. Here, we assessed soil bacterial communities in 150 forest and 150 grassland soils derived from three German regions by pyrotag sequencing of 16S rRNA genes. Land use type (forest and grassland) and soil edaphic properties strongly affected bacterial community structure and function, whereas management regime had a minor effect. In addition, a separation of soil bacterial communities by sampling region was encountered. Soil pH was the best predictor for bacterial community structure, diversity and function. The application of multinomial log-linear models revealed distinct responses of abundant bacterial groups towards pH. Predicted functional profiles revealed that differences in land use not only select for distinct bacterial populations but also for specific functional traits. The combination of 16S rRNA data and corresponding functional profiles provided comprehensive insights into compositional and functional adaptations to changing environmental conditions associated with differences in land use and management.
Modelling cellular metabolism is a strategic factor in investigating microbial behaviour and interactions, especially for bio-technological processes. A key factor for modelling microbial activity is the calculation of nutrient amounts and products generated as a result of the microbial metabolism. Representing metabolic pathways through balanced reactions is a complex and time-consuming task for biologists, ecologists, modellers and engineers. A new computational tool to represent microbial pathways through microbial metabolic reactions (MMRs) using the approach of the Thermodynamic Electron Equivalents Model has been designed and implemented in the open-access framework NetLogo. This computational tool, called MbT-Tool (Metabolism based on Thermodynamics tool) can write MMRs for different microbial functional groups, such as aerobic heterotrophs, nitrifiers, denitrifiers, methanogens, sulphate reducers, sulphide oxidizers and fermenters. The MbT-Tool's code contains eighteen organic and twenty inorganic reduction-half-reactions, four N-sources (NH4⁺, NO3⁻, NO2⁻, N2) to biomass synthesis and twenty-four microbial empirical formulas, one of which can be determined by the user (CnHaObNc). MbT-Tool is an open-source program capable of writing MMRs based on thermodynamic concepts, which are applicable in a wide range of academic research interested in designing, optimizing and modelling microbial activity without any extensive chemical, microbiological and programing experience.
Microorganisms drive much of the Earth's nitrogen (N) cycle, but we still lack a global overview of the abundance and composition of the microorganisms carrying out soil N processes. To address this gap, we characterized the biogeography of microbial N traits, defined as eight N-cycling pathways, using publically available soil metagenomes. The relative frequency of N pathways varied consistently across soils, such that the frequencies of the individual N pathways were positively correlated across the soil samples. Habitat type, soil carbon, and soil N largely explained the total N pathway frequency in a sample. In contrast, we could not identify major drivers of the taxonomic composition of the N functional groups. Further, the dominant genera encoding a pathway were generally similar among habitat types. The soil samples also revealed an unexpectedly high frequency of bacteria carrying the pathways required for dissimilatory nitrate reduction to ammonium, a little-studied N process in soil. Finally, phylogenetic analysis showed that some microbial groups seem to be N-cycling specialists or generalists. For instance, taxa within the Deltaproteobacteria encoded all eight N pathways, whereas those within the Cyanobacteria primarily encoded three pathways. Overall, this trait-based approach provides a baseline for investigating the relationship between microbial diversity and N cycling across global soils.
Syntrophies are metabolic cooperations, whereby two organisms co-metabolize a substrate in an interdependent manner. Many of the observed natural syntrophic interactions are mandatory in the absence of strong electron acceptors, such that one species in the syntrophy has to assume the role of electron sink for the other. While this presents an ecological setting for syntrophy to be beneficial, the potential genetic drivers of syntrophy remain unknown to date. Here, we show that the syntrophic sulfate-reducing species Desulfovibrio vulgaris displays a stable genetic polymorphism, where only a specific genotype is able to engage in syntrophy with the hydrogenotrophic methanogen Methanococcus maripaludis. This 'syntrophic' genotype is characterized by two genetic alterations, one of which is an in-frame deletion in the gene encoding for the ion-translocating subunit cooK of the membrane-bound COO hydrogenase. We show that this genotype presents a specific physiology, in which reshaping of energy conservation in the lactate oxidation pathway enables it to produce sufficient intermediate hydrogen for sustained M. maripaludis growth and thus, syntrophy. To our knowledge, these findings provide for the first time a genetic basis for syntrophy in nature and bring us closer to the rational engineering of syntrophy in synthetic microbial communities.The ISME Journal advance online publication, 3 June 2016; doi:10.1038/ismej.2016.80.
The importance of microbial communities (MCs) cannot be overstated. MCs underpin the biogeochemical cycles of the earth’s soil, oceans, and the atmosphere, and perform ecosystem functions that impact plants, animals, and humans. Yet our ability to predict and manage the function of these highly complex dynamically changing communities is limited. Building predictive models that link MC community composition to function is a key emerging challenge in microbial ecology. Here, we argue that addressing this challenge requires close coordination of experimental data collection and method development with mathematical model building. We discuss specific examples where model-‐experiment integration has already resulted in important insights into MC function and structure. We also highlight key research questions which still demand better integration of experiments and models. We argue that such integration is needed to achieve significant progress in our understanding of MC dynamics and function, and we make specific practical suggestions as to how this could be achieved.
We identify and describe the distribution of temperature-dependent specific growth rates for life on Earth, which we term the biokinetic spectrum for temperature. The spectrum has the potential to provide for more robust modeling in thermal ecology since any conclusions derived from it will be based on observed data rather than using theoretical assumptions. It may also provide constraints for systems biology model predictions and provide insights in physiology. The spectrum has a Δ-shape with a sharp peak at around 42°C. At higher temperatures up to 60°C there was a gap of attenuated growth rates. We found another peak at 67°C and a steady decline in maximum rates thereafter. By using Bayesian quantile regression to summarise and explore the data we were able to conclude that the gap represented an actual biological transition between mesophiles and thermophiles that we term the Mesophile-Thermophile Gap (MTG). We have not identified any organism that grows above the maximum rate of the spectrum. We used a thermodynamic model to recover the Δ-shape, suggesting that the growth rate limits arise from a trade-off between activity and stability of proteins. The spectrum provides underpinning principles that will find utility in models concerned with the thermal responses of biological processes.
The microbial world displays an immense taxonomic diversity. This diversity is manifested also in a multitude of metabolic pathways that can utilise different substrates and produce different products. Here, we propose that these observations directly link to thermodynamic constraints that inherently arise from the metabolic basis of microbial growth. We show that thermodynamic constraints can enable coexistence of microbes that utilise the same substrate but produce different end products. We find that this thermodynamics-driven emergence of diversity is most relevant for metabolic conversions with low free energy as seen for example under anaerobic conditions, where population dynamics is governed by thermodynamic effects rather than kinetic factors such as substrate uptake rates. These findings provide a general understanding of the microbial diversity based on the first principles of thermodynamics. As such they provide a thermodynamics-based framework for explaining the observed microbial diversity in different natural and synthetic environments.The ISME Journal advance online publication, 1 April 2016; doi:10.1038/ismej.2016.49.
Traditional cheeses harbour complex microbial consortia that play an important role in shaping typical sensorial properties. However, the microbial metabolism is considered difficult to control. Microbial community succession and the related gene expression were analysed during ripening of a traditional Italian cheese, identifying parameters that could be modified to accelerate ripening. Afterwards, we modulated ripening conditions and observed consistent changes in microbial community structure and function. We provide concrete evidence of the essential contribution of non-starter lactic acid bacteria in ripening-related activities. An increase in the ripening temperature promoted the expression of genes related to proteolysis, lipolysis and amino acid/lipid catabolism and significantly increases the cheese maturation rate. Moreover, temperature-promoted microbial metabolisms were consistent with the metabolomic profiles of proteins and volatile organic compounds in the cheese. The results clearly indicate how processing-driven microbiome responses can be modulated in order to optimize production efficiency and product quality.
Growth kinetics, i.e., the relationship between specific growth rate and the concentration of a substrate, is one of the basic toot in microbiology. However, despite more than half a century of research, many fundamental questions about the validity and application of growth kinetics as observed in the laboratory to environmental growth conditions are still unanswered For pure cultures growing with single substrates, enormous inconsistencies exist in the growth kinetic data reported. The law quality of experimental data has so far hampered the comparison and validation of the different growth models proposed and only recently have data collected from nutrient-controlled chemostat cultures allowed us to compare different kinetic models on a statistical basis. The problems are mainly due to (i) the analytical difficulty in measuring substrates at growth-controlling concentrations and (ii) the fact that during a kinetic experiment, particularly in batch systems, microorganisms alter their kinetic properties because of adaptation to the changing environment. For. example, for Escherichia coli growing with glucose, a physiological long-term adaptation results in a change in K-s for glucose from some 5 mg liter(-1) to ca. 30 mu g liter(-1). The data suggest that a dilemma exists, namely, that either "intrinsic" K-s (under substrate-controlled conditions in chemostat culture) or mu(max) (under substrate-excess conditions in batch culture) can be measured but both cannot be determined at the same time. The above-described conventional growth kinetics derived from single-substrate-controlled laboratory experiments have invariably been used for describing both growth and substrate utilization in ecosystems. However in nature, microbial cells are exposed to a wide spectrum of potential substrates, many of which they utilize simultaneously tin particular carbon sources). The kinetic data available to date for growth of pure cultures in carbon-controlled continuous culture with defined mixtures of two or more carbon sources (including pollutants) clearly demonstrate that simultaneous utilization results in lowered residual steady-state concentrations of all substrates. This should result in a competitive advantage of a cell capable of mixed-substrate growth because it can grow much faster at low substrate concentrations than one would expect from single-substrate kinetics. Additionally the relevance of the kinetic principles obtained from defined culture systems with single mixed, or. multicomponent substrates to the kinetics of pollutant degradation as it occurs in the presence of alternative carbon sources in complex environmental systems is discussed. The presented overview indicates that many of the environmentally relevant apects in growth kinetics are still waiting to be discovered established and exploited.
The number of prokaryotes and the total amount of their cellular carbon on earth are estimated to be 4–6 × 1030 cells and 350–550 Pg of C (1 Pg = 1015 g), respectively. Thus, the total amount of prokaryotic carbon is 60–100% of the estimated total carbon in plants, and inclusion of prokaryotic carbon in global models will almost double estimates of the amount of carbon stored in living organisms. In addition, the earth’s prokaryotes contain 85–130 Pg of N and 9–14 Pg of P, or about 10-fold more of these nutrients than do plants, and represent the largest pool of these nutrients in living organisms. Most of the earth’s prokaryotes occur in the open ocean, in soil, and in oceanic and terrestrial subsurfaces, where the numbers of cells are 1.2 × 1029, 2.6 × 1029, 3.5 × 1030, and 0.25–2.5 × 1030, respectively. The numbers of heterotrophic prokaryotes in the upper 200 m of the open ocean, the ocean below 200 m, and soil are consistent with average turnover times of 6–25 days, 0.8 yr, and 2.5 yr, respectively. Although subject to a great deal of uncertainty, the estimate for the average turnover time of prokaryotes in the subsurface is on the order of 1–2 × 103 yr. The cellular production rate for all prokaryotes on earth is estimated at 1.7 × 1030 cells/yr and is highest in the open ocean. The large population size and rapid growth of prokaryotes provides an enormous capacity for genetic diversity.
Although mathematical modelling has reached a degree of maturity in the last decades, microbial ecology is still developing, albeit at a rapid pace thanks to new insights provided by modern molecular tools. However, whilst microbiologists have long enjoyed the perspectives that particular mathematical frameworks can provide, there remains a reluctance to fully embrace the potential of models, which appear too complex, esoteric or distant from the "real-world". Nevertheless there is a strong case for pursuing the development of mathematical models to describe microbial behaviour and interactions, dynamically, spatially and across scales. Here we put forward perspectives on the current state of mathematical modelling in microbial ecology, looking back at the developments that have defined the synergies between the disciplines, and outline some of the existing challenges that motivate us to provide practical models in the hope that greater engagement with empiricists and practitioners in the microbiological domain may be achieved. We also indicate recent advances in modelling that have had impact in both the fundamental understanding of microbial ecology and its practical application in engineered biological systems. In this way, it is anticipated that interest can be garnered from across the microbiological spectrum resulting in a broader uptake of mathematical concepts in lecture theatres, laboratories and industrial systems.
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.The ISME Journal advance online publication, 10 July 2015; doi:10.1038/ismej.2015.69.
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.
The operational factors having a significant effect on in-line prefermentation efficiency include the sludge recycle rate and the subsequent sludge elutriation rate, solids concentrations and retention times. The prefermenter configuration employed is a determining factor, which allows for some degree of operational flexibility. Side-stream and multiple tank systems are superior in this regard and outnumber the use of in-line single tank prefermenters, which are mainly employed due to lower space and capital cost requirements. This paper reviews the basic design and monitoring requirements for in-line prefermenters, to establish simple strategies on which prefermenter evaluations could be based. WaterSA Vol.27(3) 2001: 413-422
The self-organisation of collective behaviours often manifests as dramatic patterns of emergent large-scale order. This is true for relatively "simple" entities such as microbial communities and robot "swarms," through to more complex self-organised systems such as those displayed by social insects, migrating herds, and many human activities. The principle of stigmergy describes those self-organised phenomena that emerge as a consequence of indirect communication between individuals of the group through the generation of persistent cues in the environment. Interestingly, despite numerous examples of multicellular behaviours of bacteria, the principle of stigmergy has yet to become an accepted theoretical framework that describes how bacterial collectives self-organise. Here we review some examples of multicellular bacterial behaviours in the context of stigmergy with the aim of bringing this powerful and elegant self-organisation principle to the attention of the microbial research community.
Author Summary
To survive in resource-limited and dynamic environments, microbial populations implement a diverse repertoire of regulatory strategies. These strategies often rely on anticipating impending environmental shifts, enabling the population to be prepared for a future change in conditions. It has long been known that cells optimize nutritional value from mixtures of carbon sources, for example glucose and galactose, by sequential activation of regulatory programs that allow for metabolizing the preferred carbon source first before metabolizing the secondary carbon source. Using automated flow-cytometry, we mapped the dynamical behavior of populations simultaneously presented with a large panel of different glucose and galactose concentrations. We show that, counter to expectations, in populations presented with glucose and galactose simultaneously, the galactose regulatory pathway is activated in a fraction of the cell population hours before glucose is fully consumed. We demonstrate that the size of this fraction of cells is tuned by the concentration of the two sugars. This population diversification may constitute a tradeoff between the benefit of rapid galactose consumption once glucose is depleted and the cost of expressing the galactose pathway.
In microbial ecology and physiology, growth rate and growth yield are among the most fundamental parameters. The question whether the two are independent of each other or correlated in some way has been addressed by two schools of microbiologists with contradicting outcomes. After the classical Monodian assumption of constant growth yield was found unsupported, microbial physiologists predicted a positive rate-yield correlation. This was based on the assumption of constant maintenance energy. On the other hand evolutionary biologists predicted a rate-yield trade-off subject to differential selective pressures in different environments. Such a trade-off can explain the wide variation in growth rates and growth yields across the microbial world. However, empirical approaches to the question are plagued by methodological problems and inconsistencies across studies. We critically evaluate the alternative ways of thinking highlighting on selective forces, mechanisms shaping the relationship and appropriate experimental approaches.
Chemotrophic life depends on the regular supply of new material to maintain a thermodynamic non-equilibrium situation. A thermodynamic non-equilibrium situation is characterized by significant driving forces to drive phase and/or electron transfer in redox reactions. Microorganisms play an important role as catalysts of thermodynamically feasible chemical redox reactions, and are capable of utilizing the energy generated for microbial growth. An improved insight in the functioning of ecosystems and the microbial life encountered can be established by analyzing the thermodynamic state of the ecosystem. Still, conducting an extensive thermodynamic state analysis based on measured information of an ecosystem is generally considered a rather complicated and laborious task. In this paper, we describe a generalized and step-wise method for conducting an extensive thermodynamic state analysis of an environmental ecosystem. The method is based on the identification of the reactants in the system and the derivation of the stoichiometry of the catabolic and anabolic reaction. In a subsequent step, the thermodynamic system properties are calculated, and different methods to establish a full description of microbial metabolism are obtained. Several examples are presented to clarify the method proposed. We hope this relatively straightforward method encourages researchers of microbial ecosystems to include thermodynamic state analysis as an integral part of their research.
[Supplemental materials are available for this article. Go to the publisher's online edition of Critical Reviews in Environmental Science and Technology for the following free supplemental resource: an elaboration in MS Excel of examples in the text regarding the fully generalized method described in this paper.]
Our ability to model the growth of microbes only relies on empirical laws, fundamentally restricting our understanding and predictive capacity in many environmental systems. In particular, the link between energy balances and growth dynamics is still not understood. Here we demonstrate a microbial growth equation relying on an explicit theoretical ground sustained by Boltzmann statistics, thus establishing a relationship between microbial growth rate and available energy. The validity of our equation was then questioned by analyzing the microbial isotopic fractionation phenomenon, which can be viewed as a kinetic consequence of the differences in energy contents of isotopic isomers used for growth. We illustrate how the associated theoretical predictions are actually consistent with recent experimental evidences. Our work links microbial population dynamics to the thermodynamic driving forces of the ecosystem, which opens the door to many biotechnological and ecological developments.The ISME Journal advance online publication, 13 February 2014; doi:10.1038/ismej.2014.7.
SUMMARY Recent research has expanded our understanding of microbial community assembly. However, the field of community ecology is inaccessible to many microbial ecologists because of inconsistent and often confusing terminology as well as unnecessarily polarizing debates. Thus, we review recent literature on microbial community assembly, using the framework of Vellend (Q. Rev. Biol. 85:183-206, 2010) in an effort to synthesize and unify these contributions. We begin by discussing patterns in microbial biogeography and then describe four basic processes (diversification, dispersal, selection, and drift) that contribute to community assembly. We also discuss different combinations of these processes and where and when they may be most important for shaping microbial communities. The spatial and temporal scales of microbial community assembly are also discussed in relation to assembly processes. Throughout this review paper, we highlight differences between microbes and macroorganisms and generate hypotheses describing how these differences may be important for community assembly. We end by discussing the implications of microbial assembly processes for ecosystem function and biodiversity.
Dissimilatory metal-reducing bacteria (DMRB), such as Geobacter and Shewanella spp., occupy a distinct metabolic niche in which they acquire energy by coupling oxidation of organic fuels with reduction of insoluble extracellularelectron acceptors (i.e., minerals). Their unique extracellularelectron transfer (EET) capabilities extend to reduction of anodes (electrodes maintained at sufficiently positive potentials) on which they form persistent, electric current generating biofilms. One hypothesis describing the mechanism of EET by Geobacter and Shewanella spp. involves superexchange in which electrons are conducted by a succession of electron transfer reactions among redoxproteins associated with the outer cell membranes, aligned along pilus-like filaments (e.g. pili), and/or throughout the extracellular matrix. Here we present theory, previously developed to describe superexchange within abiotic redoxpolymers, to describe superexchange within DMRB biofilms grown on anodes. We show that this theory appears to apply to recent ex situ measurements of electrical conductivity by individual pilus-like filaments of S. oneidensis MR-1 and G. sulfurreducens DL1, referred to as microbial nanowires. Microbial nanowires have received much recent attention because they are thought by some to impart electrical conductivity to DMRB biofilms and because of the prospect of microbe-produced conductive nanomaterials. We also show that this theory appears to apply to preliminary in situ demonstration of electrical conductivity of an anode-grown G. sulfurreducens DL1 biofilm. Based on these results we suggest a role for nanowires of S. oneidensis and G. sulfurreducens in biofilm conductivity.
Many lakes show vertical stratification of their water masses, at least for some extended time periods. Density differences in water bodies facilitate an evolution of chemical differences with many consequences for living organisms in lakes. Temperature and dissolved substances contribute to density differences in water. The atmosphere imposes a temperature signal on the lake surface. As a result, thermal stratification can be established during the warm season if a lake is sufficiently deep. On the contrary, during the cold period, surface cooling forces vertical circulation of water masses and removal of gradients of water properties. However, gradients of dissolved substances may be sustained for periods much longer than one annual cycle. Such lakes do not experience full overturns. Gradients may be a consequence of external inflows or groundwater seepage. In addition, photosynthesis at the lake surface and subsequent decomposition of organic material in the deeper layers of a lake can sustain a gradient of dissolved substances. Three more geochemical cycles, namely, calcite precipitation, iron cycle, and manganese cycle, are known for sustaining meromixis. A limited number of lakes do not experience a complete overturn because of pressure dependence of temperature of maximum density. Such lakes must be sufficiently deep and lie in the appropriate climate zone. Although these lakes are permanently stratified, deep waters are well ventilated, and chemical differences are small. Turbulent mixing and convective deep water renewal must be very effective. As a consequence, these lakes usually are not termed meromictic. Permanent stratification may also be created by episodic partial recharging of the deep water layer. This mechanism resembles the cycling of the ocean: horizontal gradients result from gradients at the surface, such as differential cooling or enhanced evaporation in adjacent shallow side bays. Dense water parcels can be formed which intrude the deep water layer. In the final section, stratification relevant physical properties, such as sound speed, hydrostatic pressure, electrical conductivity, and density, are discussed. The assumptions behind salinity, electrical conductance, potential density, and potential temperature are introduced. Finally, empirical and theoretical approaches for quantitative evaluation from easy to measure properties conclude this contribution.
Planetary stability must be integrated with United Nations targets to
fight poverty and secure human well-being, argue David Griggs and
colleagues.
The kinetics of biogeochemical processes in natural and engineered environmental systems is typically described using Monod-type or modified Monod-type models. These models rely on biomass as surrogates for functional enzymes in microbial communities that catalyze biogeochemical reactions. A major challenge to apply such models is the difficulty to quantitatively measure functional biomass for constraining and validating the models. However, omics-based approaches have been increasingly used to characterize microbial community structure, functions, and metabolites. Here, we propose an enzyme-based model that can incorporate omics-data to link microbial community functions with biogeochemical process kinetics. The model treats enzymes as time-variable catalysts for biogeochemical reactions and applies a biogeochemical reaction network to incorporate intermediate metabolites. The sequences of genes and proteins from metagenomes, as well as those from the UniProt database, were used for targeted enzyme quantification and to provide insights into the dynamic linkage among functional genes, enzymes, and metabolites that are required in the model. The application of the model was demonstrated using denitrification as an example by comparing model-simulated with measured functional enzymes, genes, denitrification substrates, and intermediates.
The microbial community that is systematically associated with a given host plant is called the core microbiota. The definition of the core microbiota was so far based on its taxonomic composition, but we argue that it should also be based on its functions. This so-called functional core microbiota encompasses microbial vehicles carrying replicators (genes) with essential functions for holobiont (i.e., plant plus microbiota) fitness. It builds up from enhanced horizontal transfers of replicators as well as from ecological enrichment of their vehicles. The transmission pathways of this functional core microbiota vary over plant generations according to environmental constraints and its added value for holobiont fitness.
Microbial communities can display large variation in taxonomic composition, yet this variation can coincide with stable metabolic functional structure and performance. The mechanisms driving the taxonomic variation within functional groups remain largely unknown. Biotic interactions, such as predation by phages, have been suggested as potential cause of taxonomic turnover, but the conditions for this scenario have not been rigorously examined. Further, it is unknown how predation by phages affects community function, and how these effects are modulated by functional redundancy in the communities. Here we address these questions using a model for a methanogenic microbial community that includes several interacting metabolic functional groups. Each functional group comprises multiple competing clades, and each clade is attacked by a specialist lytic phage. Our model predicts that phages induce intense taxonomic turnover, resembling the variability observed in previous experiments. The functional structure and performance of the community are also disturbed by phage predation, but they become more stable as the functional redundancy in the community increases. The extent of this stabilization depends on the particular functions considered. Our model suggests mechanisms by which functional redundancy stabilizes community function and supports the interpretation that biotic interactions promote taxonomic turnover within microbial functional groups. This article is protected by copyright. All rights reserved.
Understanding the processes that are driving variation of natural microbial communities across space or time is a major challenge for ecologists. Environmental conditions strongly shape the metabolic function of microbial communities; however, other processes such as biotic interactions, random demographic drift or dispersal limitation may also influence community dynamics. The relative importance of these processes and their effects on community function remain largely unknown. To address this uncertainty, here we examined bacterial and archaeal communities in replicate ‘miniature’ aquatic ecosystems contained within the foliage of wild bromeliads. We used marker gene sequencing to infer the taxonomic composition within nine metabolic functional groups, and shotgun environmental DNA sequencing to estimate the relative abundances of these groups. We found that all of the bromeliads exhibited remarkably similar functional community structures, but that the taxonomic composition within individual functional groups was highly variable. Furthermore, using statistical analyses, we found that non-neutral processes, including environmental filtering and potentially biotic interactions, at least partly shaped the composition within functional groups and were more important than spatial dispersal limitation and demographic drift. Hence both the functional structure and taxonomic composition within functional groups of natural microbial communities may be shaped by non-neutral and roughly separate processes.
Microbial metabolism powers biogeochemical cycling in Earth's ecosystems. The taxonomic composition of microbial communities varies substantially between environments, but the ecological causes of this variation remain largely unknown. We analyzed taxonomic and functional community profiles to determine the factors that shape marine bacterial and archaeal communities across the global ocean. By classifying >30,000marinemicroorganisms into metabolic functional groups, we were able to disentangle functional from taxonomic community variation. We find that environmental conditions strongly influence the distribution of functional groups in marine microbial communities by shaping metabolic niches, but only weakly influence taxonomic composition within individual functional groups. Hence, functional structure and composition within functional groups constitute complementary and roughly independent "axes of variation" shaped by markedly different processes. © Copyright 2016 by the American Association for the Advancement of Science; all rights reserved.
A rapidly growing bacterial host would be desirable for a range of routine applications in molecular biology and biotechnology. The bacterium Vibrio natriegens has the fastest growth rate of any known organism, with a reported doubling time of <10 min. We report the development of genetic tools and methods to engineer V. natriegens and demonstrate the advantages of using these engineered strains in common biotech processes. © 2016 Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved.
We have developed an individual-based model for denitrifying bacteria. The model, called INDISIM-Paraccocus, embeds a thermodynamic model for bacterial yield prediction inside the individual-based model INDISIM, and is designed to simulate the bacterial cell population behaviour and the product dynamics within the culture. The INDISIM-Paracoccus model assumes a culture medium containing succinate as a carbon source, ammonium as a nitrogen source and various electron acceptors such as oxygen, nitrate, nitrite, nitric oxide and nitrous oxide to simulate in continuous or batch culture the different nutrient-dependent cell growth kinetics of the bacterium Paracoccus denitrificans. The individuals in the model represent microbes and the individual-based model INDISIM gives the behaviour-rules that they use for their nutrient uptake and reproduction cycle. Three previously described metabolic pathways for P. denitrificans were selected and translated into balanced chemical equations using a thermodynamic model. These stoichiometric reactions are an intracellular model for the individual behaviour-rules for metabolic maintenance and biomass synthesis and result in the release of different nitrogen oxides to the medium. The model was implemented using the NetLogo platform and it provides an interactive tool to investigate the different steps of denitrification carried out by a denitrifying bacterium. The simulator can be obtained from the authors on request.
General expressions for mass, elemental, energy, and entropy balances are derived and applied to microbial growth and product formation. The state of the art of the application of elemental balances to aerobic and heterotrophic growth is reviewed and extended somewhat to include the majority of the cases commonly encountered in biotechnology. The degree of reduction concept is extended to include nitrogen sources other than ammonia. The relationship between a number of accepted measures for the comparison of substrate yields is investigated. The theory is illustrated using a generalized correlation for oxygen yield data. The stoichiometry of anaerobic product formation is briefly treated, a limit to the maximum carbon conservation in product is derived, using the concept of elemental balance. In the treatment of growth energetics the correct statement of the second law of thermodynamics for growing organisms is emphasized. For aerobic heterotrophic growth the concept of thermodynamic efficiency is used to formulate a limit the substrate yield can never surpass. It is combined with a limit due to the fact that the maximum carbon conservation in biomass can obviously never surpass unity. It is shown that growth on substrates of a low degree of reduction is energy limited, for substrates of a high degree of reduction carbon limitation takes over. Based on a literature review concerning yield data some semiempirical notions useful for a preliminary evolution of aerobic heterotrophic growth are developed. The thermodynamic efficiency definition is completed by two other efficiency measures, which allow derivation of simple equations for oxygen consumption and heat production. The range of validity of the constancy of the rate of heat production to the rate of oxygen consumption is analyzed using these efficiency measures. The energetic of anaerobic growth are treated—it is shown that an approximate analysis in terms of an enthalpy balance is not valid for this case, the evaluation of the efficiency of growth has to be based on Gibbs free energy changes. A preliminary analysis shows the existence of regularities concerning the free energy conservation on anaerobic growth. The treatment is extended to include the effect of growth rate by the introduction of a linear relationship for substrate consumption. Aerobic and anaerobic growth are discussed using this relationship. A correlation useful in judging the potentialities for improvement in anaerobic product formation processes is derived. Finally the relevance of macroscopic principles to the modeling of bioengineering systems is discussed.
The environmental conditions that describe an ecosystem define the amount of energy available to the resident organisms and the amount of energy required to build biomass. Here, we quantify the amount of energy required to make biomass as a function of temperature, pressure, redox state, the sources of C, N and S, cell mass and the time that an organism requires to double or replace its biomass. Specifically, these energetics are calculated from 0 to 125 °C, 0.1 to 500 MPa and -0.38 to +0.86 V using CO2, acetate or CH4 for C, NO3(-) or NH4(+) for N and SO4(2-) or HS(-) for S. The amounts of energy associated with synthesizing the biomolecules that make up a cell, which varies over 39 kJ (g cell)(-1), are then used to compute energy-based yield coefficients for a vast range of environmental conditions. Taken together, environmental variables and the range of cell sizes leads to a ~4 orders of magnitude difference between the number of microbial cells that can be made from a Joule of Gibbs energy under the most (5.06 × 10(11) cells J(-1)) and least (5.21 × 10(7) cells J(-1)) ideal conditions. When doubling/replacement time is taken into account, the range of anabolism energies can expand even further.The ISME Journal advance online publication, 9 February 2016; doi:10.1038/ismej.2015.227.
Beginning in the late 1950s, C. S. (Buzz) Holling conducted experiments to investigate how a predator’s rate of prey capture is related to prey density, a relationship that had previously been dubbed the functional response (Solomon 1949). In the resulting series of seminal articles (Holling 1959a, b, 1965), Holling identified three general categories of functional response that he called Types 1, 2, and 3 (Fig. 1). Type 1 is the simplest: capture rate increases in direct proportion to prey density until it abruptly saturates. Type 2 is similar in that the rate of capture increases with increasing prey density, but in contrast to the linear increase of Type 1, Type 2 approaches saturation gradually. Type 3 is similar to Type 2 except at low prey density, where the rate of prey capture accelerates. Holling’s work struck a deep chord among ecologists. Over the 55 years since it was proposed, his classification of functional responses has been woven into the fabric of ecology, where it has acquired the aura of received knowledge. Now designated by roman numerals, Holling’s functional responses appear in every introductory ecology text, usually with illustrative examples (e.g., filter feeders are Type I; insects and parasitoids, Type II; vertebrates, Type III), and his classification is commonly employed by theoretical ecologists when incorporating predation into models of population and community dynamics. Holling’s classic papers have been cited nearly 4000 times, 222 times in 2012 alone. However, as with any well-established scientific dogma, it is useful to revisit its roots, and it was with great interest that I dug out my copies of Holling’s work. Three messages emerged from this trip into ecological history: 1. Holling’s categories serve as a reminder of the utility of mechanistic approaches in ecology. The complexity of ecological interactions can be overwhelming, at times leading ecologists to wonder whether they will ever be able to delineate general laws (e.g., Lawton 1999). In a field where contingency is king, many ecologists doubt the viability of a reductionist approach in which community dynamics can be explained by quantifying the physical environment and understanding the physiology and behavior of individuals. It is therefore worth remembering that Holling’s classification of functional responses—so
Butanol has been widely used as an important industrial solvent and feedstock for chemical production. Also, its superior fuel properties compared with ethanol make butanol a good substitute for gasoline. Butanol can be efficiently produced by the genus Clostridium through the acetone-butanol-ethanol (ABE) fermentation, one of the oldest industrial fermentation processes. Butanol production via industrial fermentation has recently gained renewed interests as a potential solution to increasing pressure of climate change and environmental problems by moving away from fossil fuel consumption and moving towards renewable raw materials. Great advances over the last 100 years are now reviving interest in bio-based butanol production. However, several challenges to industrial production of butanol still need to be overcome, such as overall cost competitiveness and development of higher performance strains with greater butanol tolerance. This mini-review revisits the past 100 years of remarkable achievements made in fermentation technologies, product recovery processes, and strain development in clostridial butanol fermentation through overcoming major technical hurdles.
The book presents a consistent and complete ecosystem theory based on thermodynamic concepts. The first chapters are devoted to an interpretation of the first and second law of thermodynamics in ecosystem context. Then Prigogines use of far from equilibrium thermodynamic is used on ecosystems to explain their reactions to perturbations. The introduction of the concept exergy makes it possible to give a more profound and comprehensive explanation of the ecosystems reactions and growth-patterns. A tentative fourth law of thermodynamic is formulated and applied to facilitate these explanations. The trophic chain, the global energy and radiation balance and pattern and the reactions of ecological networks are all explained by the use of exergy. Finally, it is discussed how the presented theory can be applied more widely to explain ecological observations and rules, to assess ecosystem health and to develop ecological models.
Introduction
Chapitre 1. Notions de base, définitions et concepts
1. Chimie redox
2. Nombre d’oxydation
3. Réactions redox
4. Dismutation
5. Balance d’électrons
6. Concept d’électrons disponibles dans les systèmes microbiens
Chapitre 2. Bases de thermodynamique
7. Potentiel d’électrode et pile électrochimique productrice d’énergie électrique
8. Intensité redox et équation de Nernst
9. Eh et le concept de pε
10. Influence du pH
11. L’eau, réducteur et oxydant
12. Diagrammes potentiel – pH
13. Capacité redox
Chapitre 3. Micro-organismes et systèmes redox
14. Écologie des micro-organismes et écosystème redox
15. Micro-organismes et chimie redox de la biosphère : environnements aérobies et anaérobies
16. Réactions assimilatives et dissimilatives
17. Intensité et capacité redox dans les systèmes biologiques
18. Tactisme redox
19. Systèmes bio-électrochimiques
Chapitre 4. Phénomènes d’oxydo-réduction dans la nature
20. Introduction
21. L’oxygène dans l’eau
22. Le système carbone
23. Le système azote
24. Le système fer et manganèse
25. Les surfaces naturelles
26. Le corps animal
Conclusion
Références bibliographiques
Lien : http://www.quae.com/fr/r3192-principes-de-chimie-redox-en-ecologie-microbienne-.html
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.
Metagenomic technique was employed to characterize the seasonal dynamics of activated sludge (AS) communities in a municipal wastewater treatment plant (WWTP) over 4 years. The results indicated that contrary to Eukaryota (mainly Rotifera and Nematoda), abundances of Bacteria and Archaea (mainly Euryarchaeota) were significantly higher in winter than summer. Two-way analysis of variance and canonical correspondence analysis revealed that many functionally important genera followed strong seasonal variation patterns driven by temperature and salinity gradients; among them, two nitrifying bacteria, Nitrospira and Nitrosomonas, displayed much higher abundances in summer, whereas phosphate-removing genus Tetrasphaera, denitrifier Paracoccus and potential human faecal bacteria, i.e. Bifidobacterium, Dorea and Ruminococcus, showed significantly higher abundances in winter. Particularly, occurrence of dual variation patterns beyond explanation merely by seasonality indicated that multivariables (e.g. dissolved oxygen, sludge retention time, nutrients) participated in shaping AS community structure. However, SEED subsystems annotation showed that functional categories in AS showed no significant difference between summer and winter, indicating that compared with its microbial components, the functional profiles of AS were much more stable. Taken together, our study provides novel insights into the microbial community variations in AS and discloses their correlations with influential factors in WWTPs.
Fill-and-draw completely mixed activated sludge reactors were used to determine the effects of MLVSS concentration, pH, and temperature on nitrification rate. Forty-five experiments were divided into three series of MLVSS concentrations. Each series of 15 experiments were distributed among three different pH groups. In each group, five experiments were conducted at 4°, 10°, 17°, 25°, and 33°C. The best nitrification performance was obtained at pH 8.3, between 25° and 33°C. There was no interaction between the effects of temperature and pH. However, a change in biomass concentration altered both the pH and temperature dependence of the process. The temperature coefficient is expressed as a function of MLVSS concentration.
Heat capacity measurements using an adiabatic calorimeter have been made from 7 to 310 K on a carefully prepared specimen of lyophilized cells of Saccharomyces cerevisiae (yeast). From these measurements, a value of 1.304 J K−1 g−1 has been obtained for the absolute entropy of yeast cells at 298.15 K, based on third-law calculations. Chemical analysis of the cells yielded an empirical chemical formula for the cellular stoichiometry, which has been expressed as an ion-containing carbon mole, (ICC-mol). A value of 34.167 J K−1·ICC-mol−1 for the absolute entropy of this mass of cells and of −151.46 J K−1·ICC-mol−1 for the entropy of formation has been calculated. The absolute entropy/g of the yeast cells falls within the range of those for simple biological molecules like sugars and amino acids and more complex biopolymers like proteins. We conclude that the thermodynamic effect of cellular organization in the dried cells is negligible.
SUMMARY When Streptococcus faecalis was grown anaerobically in a complex medium containing D-glucose, D-ribose or L-arginine as energy source the dry wt. of organism produced was proportional to the concentration of the energy source in the medium. However, S. faecalis will not grow in a defined medium with arginine as the energy source unless glucose is present at the same time. The anaerobic growth of both Saccharornyces cerevisiae and Pseudomonas lindneri was proportional to the con- centration of glucose in the medium and the yield coefficient-defined as g. dry wt. organism/mole glucose-of the former was the same as that of S. fmculis grown upon glucose and approximately twice that of P. lindneri. Calculation of the g. dry wt. organism/mole adenosine triphosphate synthesized for these three organisms gave values ranging from 12.6 to 8.3 with an average of 10.5. These results suggest that, under anaerobic conditions, the yield of S. faecalis, S. cerevisiae and P. lindneri was proportional to the amount of ATP synthesized. When Propionibacterium pentosaceum was grown anaerobically with glucose, glycerol or DL-lactate as energy source there was, in all three cases, a linear relationship between the dry wt. of organisms produced and the concentration of the energy source in the medium. The values of the yield coefficients obtained were compatible with the formation of approximately 4 mole ATP/mole glucose, 2 mole ATP/mole glycerol and 1 mole ATP/mole lactate.
The Double-Monod and weighted models for specific growth rate coefficient as a function of two nutrients differ significantly when the nutrient concentrations are low. The weighted model agrees with actual data quite well for non-toxic nutrients but fails badly when applied to inhibitory nutrients. However, the Andrews equation can be modified slightly for use in conjunction with the weighted model to handle growth rate limitation when one nutrient inhibits growth rate.
The Monod equation has been widely applied to describe microbial growth, but it has no any mechanistic basis. Based on the thermodynamics of microbial growth process, a general model for microbial growth was developed. The constants involved in the present model were defined with clear physical meanings. The model derived can be reduced to the Monod equation, Grau equation and Hill or Moser equation. Compared to the Michaelis–Menten constant with the equilibrium thermodynamic characteristics, it was shown that the Monod constant (Ks) has non-equilibrium thermodynamic characteristics.
The study involved model evaluation of the fate and utilization of starch by microbial culture acclimated to different growth conditions and feeding regimes. For this purpose, parallel sequencing batch reactors were operated with pulse and continuous feeding of soluble starch at sludge ages of 8 and 2days. High-rate adsorption was identified as the initial process for starch utilization under all operating conditions. Hydrolysis mechanism acted as the rate limiting mechanism for different substrate removal/storage modes sustained under pulse and continuous feeding at different sludge ages. Together with variable growth kinetics, faster growth conditions also triggered high-rate hydrolysis and relatively slower storage kinetics to ensure the level of substrate supply for faster microbial growth. Model evaluation indicated the presence of particulate sugar adsorbed, especially under continuous feeding. It enabled accurate interpretation of observed particulate sugar values and this way, differentiating glycogen from the adsorbed starch remaining on the biomass.