Biochemical properties of Paracoccus denitrificans FnrP:Reactions with molecular oxygen and nitric oxide

In Paracoccus denitrificans, three CRP/FNR family regulatory proteins, NarR, NnrR and FnrP, control the switch between aerobic and anaerobic (denitrification) respiration. FnrP is a [4Fe-4S] cluster containing homologue of the archetypal O2 sensor FNR from E. coli and accordingly regulates genes encoding aerobic and anaerobic respiratory enzymes in response to O2, and also NO, availability. Here we show that FnrP undergoes O2-driven [4Fe-4S] to [2Fe-2S] cluster conversion that involves up to 2 O2 per cluster, with significant oxidation of released cluster sulfide to sulfane observed at higher O2 concentrations. The rate of the cluster reaction was found to be ~6-fold lower than that of E. coli FNR, suggesting that FnrP can remain transcriptionally active under microaerobic conditions. This is consistent with a role for FnrP in activating expression of the high O2 affinity cytochrome c oxidase under microaerobic conditions. Cluster conversion resulted in dissociation of the transcriptionally active FnrP dimer into monomers. Therefore, along with E. coli FNR, FnrP belongs to the subset of FNR proteins in which cluster type is correlated with association state. Interestingly, two key charged residues, Arg140 and Asp154, that have been shown to play key roles in the monomer-dimer equilibrium in E. coli FNR are not conserved in FnrP, indicating that different protomer interactions are important for this equilibrium. Finally, the FnrP [4Fe-4S] cluster is shown to undergo reaction with multiple NO molecules, resulting in iron nitrosyl species and dissociation into monomers

High spatial resolution analysis of ferromanganese concretions by LA-ICP-MS†

A procedure was developed for the determination of element distributions in cross-sections of ferromanganese concretions using laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS). The effects of carrier flow rates, rf forward power, ablation energy, ablation spot size, repetition rate and number of shots per point on analyte intensity were studied. It is shown that different carrier gas flow rates are required in order to obtain maximum sensitivities for different groups of elements, thus complicating the optimisation of ICP parameters. On the contrary, LA parameters have very similar effects on almost all elements studied, thus providing a common optimum parameter set for the entire mass range. However, for selected LA parameters, the use of compromise conditions was necessary in order to compensate for relatively slow data acquisition by ICP-MS and maintain high spatial resolution without sacrificing the multielemental capabilities of the technique. Possible variations in ablation efficiency were corrected for mathematically using the sum of Fe and Mn intensities. Quantification by external calibration against matrix-matched standards was successfully used for more than 50 elements. These standards, in the form of pressed pellets (no binder), were prepared in-house using ferromanganese concentrates from a deep-sea nodule reference material as well as from shallow-marine concretions varying in size and having different proportions of three major phases: aluminosilicates, Fe- and Mn-oxyhydroxides. Element concentrations in each standard were determined by means of conventional solution nebulisation ICP-MS following acid digestion. Examples of selected inter-element correlations in distribution patterns along the cross-section of a concretion are given

Linking monitoring and modelling: can long-term datasets be used more effectively as a basis for large-scale prediction?

Data from long-term monitoring sites are vital for biogeochemical process understanding, and for model development. Implicitly or explicitly, information provided by both monitoring and modelling must be extrapolated in order to have wider scientific and policy utility. In many cases, large-scale modelling utilises little of the data available from long-term monitoring, instead relying on simplified models and limited, often highly uncertain, data for parameterisation. Here, we propose a new approach whereby outputs from model applications to long-term monitoring sites are upscaled to the wider landscape using a simple statistical method. For the 22 lakes and streams of the UK Acid Waters Monitoring Network (AWMN), standardised concentrations (Z scores) for Acid Neutralising Capacity (ANC), dissolved organic carbon, nitrate and sulphate show high temporal coherence among sites. This coherence permits annual mean solute concentrations at a new site to be predicted by back-transforming Z scores derived from observations or model applications at other sites. The approach requires limited observational data for the new site, such as annual mean estimates from two synoptic surveys. Several illustrative applications of the method suggest that it is effective at predicting long-term ANC change in upland surface waters, and may have wider application. Because it is possible to parameterise and constrain more sophisticated models with data from intensively monitored sites, the extrapolation of model outputs to policy relevant scales using this approach could provide a more robust, and less computationally demanding, alternative to the application of simple generalised models using extrapolated input data