Cédric Garnier

Determinations of uranium(VI) binding properties with some metalloproteins (transferrin, albumin, metallothionein and ferritin) by fluorescence quenching.

The interactions between uranium and four metalloproteins (Apo-HTf, HSA, MT and Apo-EqSF) were investigated using fluorescence quenching measurements. The combined use of a microplate spectrofluorometer and logarithmic additions of uranium into protein solutions allowed us to define the fluorescence quenching over a wide range of [U]/[Pi] ratios (from 0.05 to 1150) at physiologically relevant conditions of pH. Results showed that fluorescence from the four metalloproteins was quenched by UO22+. Stoichiometry reactions, fluorescence quenching mechanisms and complexing properties of metalloproteins, i.e. binding constants and binding sites densities, were determined using classic fluorescence quenching methods and curve-fitting software (PROSECE). It was demonstrated that in our test conditions, the metalloprotein complexation by uranium could be simulated by two specific sites (L1 and L2). Results showed that the U(VI)–Apo-HTf complexation constant values (log K1u2009=u20097.7, log K2u2009=u20094.6) were slightly higher than those observed for U(VI)–HSA complex (log K1u2009=u20096.1, log K2u2009=u20094.8), U(VI)–MT complex (log K1u2009=u20096.5, log K2u2009=u20095.6) and U(VI)–Apo-EqsF complex (log K1u2009=u20095.3, log K2u2009=u20093.9). PROSECE fitting studies also showed that the complexing capacities of each protein were different: 550 moles of U(VI) are complexed by Apo-EqSF while only 28, 10 and 5 moles of U(VI) are complexed by Apo-HTf, HSA and MT, respectively.

Characterisation and modelling of marine dissolved organic matter interactions with major and trace cations

A two-step protocol (nano-filtration and reverse osmosis) was applied for natural organic matter (NOM) preconcentration of a seawater sample. Complexing affinities of the so concentrated marine dissolved NOM (DNOM) towards major and trace cations were studied by potentiometric and voltammetric titration techniques. The potentiometric titration experiments fitted by models describing and characterising the DNOM-cation interactions, revealed four distinct classes of acidic sites (pKa of 3.6, 4.8, 8.6 and 12). A total acidic sites density of 445meq/mol(C) was estimated, with a majority (60%) of carboxylic-like sites. Pseudopolarographic measurements revealed two distinct groups of copper complexes: labile, reducible at about -0.2V; and inert, directly reducible at about -1.4V. Simultaneous competition between copper, calcium and proton highlighted the presence of two classes of binding sites (density of 1.72 and 10.25 meq mol(C)(-1), respectively, corresponding to 3% of total acidic sites). The first class was more specific to copper (logK(CuL) 9.9, logK(CaL) 2.5, pKa 8.6), whereas stronger competition between copper and calcium occurred for the second class (logK(CuL) 6.9, logK(CaL) 5.5, pKa 8.2). The binding sites characterisation was validated by the very good matching of the non-concentrated seawater sample titration data with the simulated curves obtained using the binding parameters from the concentrated sample. Furthermore, this comparison also validated the applied preconcentration protocol, highlighting its negligible influence on organic matter properties when considering copper complexation.

Modelling exchange kinetics of copper at the water-aquatic moss (Fontinalis antipyretica) interface: Influence of water cationic composition (Ca, Mg, Na and pH)

The present study investigated the effect of water cationic composition (Ca, Mg, Na, pH) on the bioaccumulation and elimination rates of copper by an aquatic moss (Fontinalis antipyretica), under laboratory conditions. For this purpose, mosses were exposed to copper at an environmentally relevant and usually non-toxic concentration (5 microg L(-1)) in natural waters where cationic composition and concentrations were varied. To describe copper bioaccumulation by aquatic mosses, a two-compartment model was the first-order kinetics, was developed and calibrated under a wide range of water cationic composition. Bioaccumulation rates of Cu in mosses were significantly reduced as the concentrations of competitive cations in solution increased. Hence, in hard-water, Ca and Mg cations play a protective role as they compete with Cu2+ ions for the absorption on transport sites at the organism-water interface. Based on the relationships between each major cation concentration and the exchange kinetics on mosses, the binding constants (K(Ci)(BL)) of each competing cations to the biological surfaces were derived. Using the present cationic-dependent kinetic model, it is now feasible to incorporate water cationic composition in the (re)interpretation of bryophytes contamination levels and in the (re)definition of Water Quality Criteria (WQC) as illustrated through two selected examples of biomonitoring programmes. In the framework of future national water quality guidelines revisions, a such flexible and mechanistic biomonitoring tool (integrating the protective effects of competing cations) may greatly improve the ability of regulators to derive site-specific Cu (metal) guidelines for protecting aquatic biota, while limiting the use of conservative assumptions.

Spatial distribution and mobility of trace metals in sediments of the Krka River estuary (Adriatic Sea, Croatia)

Estuarine sediments act as a sink for metal contaminants in aquatic system. As a consequence of biogeochemical processes which influence metal mobility, those sediments could become secondary source of metal contaminants for the environment. The objectives of this study were to evaluate trace metal content and mobility in sediments from the Krka River estuary. Surface sediments were sampled at 40 locations scattered through entire estuary, allowing the determination of trace metal distribution with high resolution. Mobility was assessed using two approaches: (1) pore water extraction by centrifugation and (2) diffusive gradient in thin films (DGT) sediment probes. Surface sediment analysis revealed three main pollution sources, all located in the lower part of the estuary: former ferromanganese industry, phosphate transhipment harbour and nautical marina. Mobility in the sediments is controlled by early diagenesis processes.