A Ribonucleotide ↔ Phosphoramidate Reaction Network Optimized by Computer-Aided Design.

A growing number of out-of-equilibrium systems have been created and investigated in chemical laboratories over the past decade. One way to achieve this is to create a reaction cycle, in which the forward reaction is driven by a chemical fuel and the backward reaction follows a different pathway. Such dissipative reaction networks are still relatively rare, however, and most non-enzymatic examples are based on the carbodiimide-driven generation of carboxylic acid anhydrides. In this work, we describe a dissipative reaction network that comprises the chemically fueled formation of phosphoramidates from natural ribonucleotides (e.g., GMP or AMP) and phosphoramidate hydrolysis as a mild backward reaction. Because the individual reactions are subject to a multitude of interconnected parameters, the software-assisted tool "Design of Experiments" (DoE) was a great asset for optimizing and understanding the network. One notable insight was the stark effect of the nucleophilic catalyst 1-ethylimidazole (EtIm) on the hydrolysis rate, which is reminiscent of the action of the histidine group in phosphoramidase enzymes (e.g., HINT1). We were also able to use the reaction cycle to generate transient self-assemblies, which were characterized by dynamic light scattering (DLS), confocal microscopy (CLSM), and cryogenic transmission electron microscopy (cryo-TEM). Because these compartments are based on prebiotically plausible building blocks, our findings may have relevance for origin-of-life scenarios.

Mixing, spreading and reaction in heterogeneous media: a brief review.

Geological media exhibit heterogeneities in their hydraulic and chemical properties, which can lead to enhanced spreading and mixing of the transported species and induce an effective reaction behavior that is different from the one for a homogeneous medium. Chemical heterogeneities such as spatially varying adsorption properties and specific reactive surface areas can act directly on the chemical reaction dynamics and lead to different effective reaction laws. Physical heterogeneities affect mixing-limited chemical reactions in an indirect way by their impact on spreading and mixing of dissolved species. To understand and model large-scale reactive transport the interactions of these coupled processes need to be understood and quantified. This paper provides a brief review on approaches of non-reactive and reactive transport modeling in geological media.

Electrode-based approach for monitoring in situ microbial activity during subsurface bioremediation.

Current production by microorganisms colonizing subsurface electrodes and its relationship to substrate availability and microbial activity was evaluated in an aquifer undergoing bioremediation. Borehole graphite anodes were installed downgradient from a region of acetate injection designed to stimulate bioreduction of U(VI); cathodes consisted of graphite electrodes embedded at the ground surface. Significant increases in current density (< or =50 mA/m2) tracked delivery of acetate to the electrodes, dropping rapidly when acetate inputs were discontinued. An upgradient control electrode not exposed to acetate produced low, steady currents (< or =0.2 mA/m2). Elevated current was strongly correlated with uranium removal but minimal correlation existed with elevated Fe(II). Confocal laser scanning microscopy of electrodes revealed firmly attached biofilms, and analysis of 16S rRNA gene sequences indicated the electrode surfaces were dominated (67-80%) by Geobacter species. This is the first demonstration that electrodes can produce readily detectable currents despite long-range (6 m) separation of anode and cathode, and these results suggest that oxidation of acetate coupled to electron transfer to electrodes by Geobacter species was the primary source of current. Thus it is expected that current production may serve as an effective proxy for monitoring in situ microbial activity in a variety of subsurface anoxic environments.

Effects of physical and geochemical heterogeneities on mineral transformation and biomass accumulation during biostimulation experiments at Rifle, Colorado.

Electron donor amendment for bioremediation often results in precipitation of secondary minerals and the growth of biomass, both of which can potentially change flow paths and the efficacy of bioremediation. Quantitative estimation of precipitate and biomass distribution has remained challenging, partly due to the intrinsic heterogeneities of natural porous media and the scarcity of field data. In this work, we examine the effects of physical and geochemical heterogeneities on the spatial distributions of mineral precipitates and biomass accumulated during a biostimulation field experiment near Rifle, Colorado. Field bromide breakthrough data were used to infer a heterogeneous distribution of hydraulic conductivity through inverse transport modeling, while the solid phase Fe(III) content was determined by assuming a negative correlation with hydraulic conductivity. Validated by field aqueous geochemical data, reactive transport modeling was used to explicitly keep track of the growth of the biomass and to estimate the spatial distribution of precipitates and biomass. The results show that the maximum mineral precipitation and biomass accumulation occurs in the vicinity of the injection wells, occupying up to 5.4vol.% of the pore space, and is dominated by reaction products of sulfate reduction. Accumulation near the injection wells is not strongly affected by heterogeneities present in the system due to the ubiquitous presence of sulfate in the groundwater. However, accumulation in the down-gradient regions is dominated by the iron-reducing reaction products, whose spatial patterns are strongly controlled by both physical and geochemical heterogeneities. Heterogeneities can lead to localized large accumulation of mineral precipitates and biomass, increasing the possibility of pore clogging. Although ignoring the heterogeneities of the system can lead to adequate prediction of the average behavior of sulfate-reducing related products, it can also lead to an overestimation of the overall accumulation of iron-reducing bacteria, as well as the rate and extent of iron reduction. Surprisingly, the model predicts that the total amount of uranium being reduced in the heterogeneous 2D system was similar to that in the 1D homogeneous system, suggesting that the overall uranium bioremediation efficacy may not be significantly affected by the heterogeneities of Fe(III) content in the down-gradient regions. Rather, the characteristics close to the vicinity of the injection wells might be crucial in determining the overall efficacy of uranium bioremediation. These findings have important implications not only for uranium bioremediation at the Rifle site and for bioremediation of other redox sensitive contaminants at sites with similar characteristics, but also for the development of optimal amendment delivery strategies in other settings.

Three-dimensional geostatistical inversion of flowmeter and pumping test data.

We jointly invert field data of flowmeter and multiple pumping tests in fully screened wells to estimate hydraulic conductivity using a geostatistical method. We use the steady-state drawdowns of pumping tests and the discharge profiles of flowmeter tests as our data in the inference. The discharge profiles need not be converted to absolute hydraulic conductivities. Consequently, we do not need measurements of depth-averaged hydraulic conductivity at well locations. The flowmeter profiles contain information about relative vertical distributions of hydraulic conductivity, while drawdown measurements of pumping tests provide information about horizontal fluctuation of the depth-averaged hydraulic conductivity. We apply the method to data obtained at the Krauthausen test site of the Forschungszentrum Jülich, Germany. The resulting estimate of our joint three-dimensional (3D) geostatistical inversion shows an improved 3D structure in comparison to the inversion of pumping test data only.