Florian Centler

The IWAS-ToolBox: Software coupling for an integrated water resources management

Numerical modeling of interacting flow and transport processes between different hydrological compartments, such as the atmosphere/land surface/vegetation/soil/groundwater systems, is essential for understanding the comprehensive processes, especially if quantity and quality of water resources are in acute danger, like e.g. in semi-arid areas and regions with environmental contaminations. The computational models used for system and scenario analysis in the framework of an integrated water resources management are rapidly developing instruments. In particular, advances in computational mathematics have revolutionized the variety and the nature of the problems that can be addressed by environmental scientists and engineers. It is certainly true that for each hydro-compartment, there exists many excellent simulation codes, but traditionally their development has been isolated within the different disciplines. A new generation of coupled tools based on the profound scientific background is needed for integrated modeling of hydrosystems. The objective of the IWAS-ToolBox is to develop innovative methods to combine and extend existing modeling software to address coupled processes in the hydrosphere, especially for the analysis of hydrological systems in sensitive regions. This involves, e.g. the provision of models for the prediction of water availability, water quality and/or the ecological situation under changing natural and socio-economic boundary conditions such as climate change, land use or population growth in the future.

GeoSysBRNS-A flexible multidimensional reactive transport model for simulating biogeochemical subsurface processes

The description of reactive transport processes in subsurface environments requires a sound understanding of both the biogeochemical complexity of the system and the spatially resolved transport of reactive species. However, most existing reactive transport models, for example in the field of contaminant hydrology, are specialized either in the simulation of the reactive or of the flow and transport processes. In this paper, we present and test the coupling of two highly flexible codes for the simulation of reactive transport processes in the subsurface: the Biogeochemical Reaction Network Simulator (BRNS), which contains a solver for kinetically and thermodynamically constrained biogeochemical reactions, and GeoSys/RockFlow, a multidimensional finite element subsurface flow and transport simulator. The new model, named GeoSysBRNS, maintains the full flexibility of the original models. The coupling is handled using an operator splitting scheme, which allows the reactive solver to be compiled into a problem specific library that is accessed by the transport simulator at runtime. The accuracy of the code coupling within GeoSysBRNS is demonstrated using two benchmark problems from the literature: a laboratory experiment on organic carbon degradation in a sand column via multiple microbial degradation pathways, and a dispersive mixing controlled bioreactive transport problem in aquifers, assuming three different reaction kinetics.

A reactive transport modeling approach to simulate biogeochemical processes in pore structures with pore-scale heterogeneities

Redox processes, including degradation of organic contaminants, are often controlled by microorganisms residing in natural porous media like soils or aquifers. These environments are characterized by heterogeneities at various scales which influence the transport of chemical species and the spatial distribution of microorganisms. As a result, the accessibility of the chemical species by the resident microbial populations may be limited, altering the efficiency of the biodegradation process. Hence, the biodegradation rate of contaminants at large scales does not only depend on the degradation capacity of the indigenous microbial population but also on the heterogeneities of the hosting media at smaller scales. It is thus important to establish a link between effective reaction rates and various structural features of porous media which can be directly observed or measured. This link is urgently needed because explicit resolution of heterogeneities within large-scale reactive transport models is still limited by the available computational capacities. The present study introduces a reactive transport modeling approach to determine the influence of pore-scale heterogeneities on biogeochemical processes in porous media. For this purpose, a pore network model, which simulates flow and advective-diffusive transport of chemical species in heterogeneous pore networks is developed and coupled to the Biogeochemical Reaction Network Simulator (BRNS). The resulting coupled model (PNBRNS) is able to simulate the reactive transport of solutes in heterogeneous pore assemblies. The PNBRNS model is applied for the simulation of a test case of bioavailability and effective biodegradation rate of a dissolved contaminant in different pore networks, built using a discrete set of geostatistically derived pore-size or biomass distributions. Results show that the heterogeneity of the pore-size distribution has a significant impact on bioavailability while the heterogeneity of the biomass distribution only leads to minor effects. The model also includes intra-pore bioavailability restrictions using diffusion-limited biodegradation kinetics. The results indicate that intra-pore limitations lead to extra constrains on the biodegradation of contaminants, even in the presence of larger-scale structural heterogeneities.

A topological approach to chemical organizations

Large chemical reaction networks often exhibit distinctive features that can be interpreted as higher-level structures. Prime examples are metabolic pathways in a biochemical context. We review mathematical approaches that exploit the stoichiometric structure, which can be seen as a particular directed hypergraph, to derive an algebraic picture of chemical organizations. We then give an alternative interpretation in terms of set-valued set functions that encapsulate the production rules of the individual reactions. From the mathematical point of view, these functions define generalized topological spaces on the set of chemical species. We show that organization-theoretic concepts also appear in a natural way in the topological language. This abstract representation in turn suggests the exploration of the chemical meaning of well-established topological concepts. As an example, we consider connectedness in some detail.

Trace Elements Induce Predominance among Methanogenic Activity in Anaerobic Digestion

Trace elements (TE) play an essential role in all organisms due to their functions in enzyme complexes. In anaerobic digesters, control, and supplementation of TEs lead to stable and more efficient methane production processes while TE deficits cause process imbalances. However, the underlying metabolic mechanisms and the adaptation of the affected microbial communities to such deficits are not yet fully understood. Here, we investigated the microbial community dynamics and resulting process changes induced by TE deprivation. Two identical lab-scale continuous stirred tank reactors fed with distiller’s grains and supplemented with TEs (cobalt, molybdenum, nickel, tungsten) and a commercial iron additive were operated in parallel. After 72 weeks of identical operation, the feeding regime of one reactor was changed by omitting TE supplements and reducing the amount of iron additive. Both reactors were operated for further 21 weeks. Various process parameters (biogas production and composition, total solids and volatile solids, TE concentration, volatile fatty acids, total ammonium nitrogen, total organic acids/alkalinity ratio, and pH) and the composition and activity of the microbial communities were monitored over the total experimental time. While the methane yield remained stable, the concentrations of hydrogen sulfide, total ammonia nitrogen, and acetate increased in the TE-depleted reactor compared to the well-supplied control reactor. Methanosarcina and Methanoculleus dominated the methanogenic communities in both reactors. However, the activity ratio of these two genera was shown to depend on TE supplementation explainable by different TE requirements of their energy conservation systems. Methanosarcina dominated the well-supplied anaerobic digester, pointing to acetoclastic methanogenesis as the dominant methanogenic pathway. Under TE deprivation, Methanoculleus and thus hydrogenotrophic methanogenesis was favored although Methanosarcina was not overgrown by Methanoculleus. Multivariate statistics revealed that the decline of nickel, cobalt, molybdenum, tungsten, and manganese most strongly influenced the balance of mcrA transcripts from both genera. Hydrogenotrophic methanogens seem to be favored under nickel- and cobalt-deficient conditions as their metabolism requires less nickel-dependent enzymes and corrinoid cofactors than the acetoclastic and methylotrophic pathways. Thus, TE supply is critical to sustain the activity of the versatile high-performance methanogen Methanosarcina.

Phenotype prediction in regulated metabolic networks

BackgroundDue to the growing amount of biological knowledge that is incorporated into metabolic network models, their analysis has become more and more challenging. Here, we examine the capabilities of the recently introduced chemical organization theory (OT) to ease this task. Considering only network stoichiometry, the theory allows the prediction of all potentially persistent species sets and therewith rigorously relates the structure of a network to its potential dynamics. By this, the phenotypes implied by a metabolic network can be predicted without the need for explicit knowledge of the detailed reaction kinetics.ResultsWe propose an approach to deal with regulation – and especially inhibitory interactions – in chemical organization theory. One advantage of this approach is that the metabolic network and its regulation are represented in an integrated way as one reaction network. To demonstrate the feasibility of this approach we examine a model by Covert and Palsson (J Biol Chem, 277(31), 2002) of the central metabolism of E. coli that incorporates the regulation of all involved genes. Our method correctly predicts the known growth phenotypes on 16 different substrates. Without specific assumptions, organization theory correctly predicts the lethality of knockout experiments in 101 out of 116 cases. Taking into account the same model specific assumptions as in the regulatory flux balance analysis (rFBA) by Covert and Palsson, the same performance is achieved (106 correctly predicted cases). Two model specific assumptions had to be considered: first, we have to assume that secreted molecules do not influence the regulatory system, and second, that metabolites with increasing concentrations indicate a lethal state.ConclusionThe introduced approach to model a metabolic network and its regulation in an integrated way as one reaction network makes organization analysis a universal technique to study the potential behavior of biological network models. Applying multiple methods like OT and rFBA is shown to be valuable to uncover critical assumptions and helps to improve model coherence.

Mycelium-mediated transfer of water and nutrients stimulates bacterial activity in dry and oligotrophic environments

Fungal–bacterial interactions are highly diverse and contribute to many ecosystem processes. Their emergence under common environmental stress scenarios however, remains elusive. Here we use a synthetic microbial ecosystem based on the germination of Bacillus subtilis spores to examine whether fungal and fungal-like (oomycete) mycelia reduce bacterial water and nutrient stress in an otherwise dry and nutrient-poor microhabitat. We find that the presence of mycelia enables the germination and subsequent growth of bacterial spores near the hyphae. Using a combination of time of flight- and nanoscale secondary ion mass spectrometry (ToF- and nanoSIMS) coupled with stable isotope labelling, we link spore germination to hyphal transfer of water, carbon and nitrogen. Our study provides direct experimental evidence for the stimulation of bacterial activity by mycelial supply of scarce resources in dry and nutrient-free environments. We propose that mycelia may stimulate bacterial activity and thus contribute to sustaining ecosystem functioning in stressed habitats.

Mycelium-Like Networks Increase Bacterial Dispersal, Growth, and Biodegradation in a Model Ecosystem at Various Water Potentials.

ABSTRACT Fungal mycelia serve as effective dispersal networks for bacteria in water-unsaturated environments, thereby allowing bacteria to maintain important functions, such as biodegradation. However, poor knowledge exists on the effects of dispersal networks at various osmotic (Ψo) and matric (Ψm) potentials, which contribute to the water potential mainly in terrestrial soil environments. Here we studied the effects of artificial mycelium-like dispersal networks on bacterial dispersal dynamics and subsequent effects on growth and benzoate biodegradation at ΔΨo and ΔΨm values between 0 and −1.5 MPa. In a multiple-microcosm approach, we used a green fluorescent protein (GFP)-tagged derivative of the soil bacterium Pseudomonas putida KT2440 as a model organism and sodium benzoate as a representative of polar aromatic contaminants. We found that decreasing ΔΨo and ΔΨm values slowed bacterial dispersal in the system, leading to decelerated growth and benzoate degradation. In contrast, dispersal networks facilitated bacterial movement at ΔΨo and ΔΨm values between 0 and −0.5 MPa and thus improved the absolute biodegradation performance by up to 52 and 119% for ΔΨo and ΔΨm, respectively. This strong functional interrelationship was further emphasized by a high positive correlation between population dispersal, population growth, and degradation. We propose that dispersal networks may sustain the functionality of microbial ecosystems at low osmotic and matric potentials.

Self-Adaptive Scouting—Autonomous Experimentation for Systems Biology

We introduce a new algorithm for autonomous experimentation. This algorithm uses evolution to drive exploration during scientific discovery. Population size and mutation strength are self-adaptive. The only variables remaining to be set are the limits and maximum resolution of the parameters in the experiment. In practice, these are determined by instrumentation. Aside from conducting physical experiments, the algorithm is a valuable tool for investigating simulation models of biological systems. We illustrate the operation of the algorithm on a model of HIV-immune system interaction. Finally, the difference between scouting and optimization is discussed.

Estimating pathway-specific contributions to biodegradation in aquifers based on dual isotope analysis: Theoretical analysis and reactive transport simulations

At field sites with varying redox conditions, different redox-specific microbial degradation pathways contribute to total contaminant degradation. The identification of pathway-specific contributions to total contaminant removal is of high practical relevance, yet difficult to achieve with current methods. Current stable-isotope-fractionation-based techniques focus on the identification of dominant biodegradation pathways under constant environmental conditions. We present an approach based on dual stable isotope data to estimate the individual contributions of two redox-specific pathways. We apply this approach to carbon and hydrogen isotope data obtained from reactive transport simulations of an organic contaminant plume in a two-dimensional aquifer cross section to test the applicability of the method. To take aspects typically encountered at field sites into account, additional simulations addressed the effects of transverse mixing, diffusion-induced stable-isotope fractionation, heterogeneities in the flow field, and mixing in sampling wells on isotope-based estimates for aerobic and anaerobic pathway contributions to total contaminant biodegradation. Results confirm the general applicability of the presented estimation method which is most accurate along the plume core and less accurate towards the fringe where flow paths receive contaminant mass and associated isotope signatures from the core by transverse dispersion. The presented method complements the stable-isotope-fractionation-based analysis toolbox. At field sites with varying redox conditions, it provides a means to identify the relative importance of individual, redox-specific degradation pathways.