Dataset Information

Toward an Internally Consistent Model for Hg(II) Chemical Speciation Calculations in Bacterium-Natural Organic Matter-Low Molecular Mass Thiol Systems.

ABSTRACT: To advance the scientific understanding of bacteria-driven mercury (Hg) transformation processes in natural environments, thermodynamics and kinetics of divalent mercury Hg(II) chemical speciation need to be understood. Based on Hg LIII-edge extended X-ray absorption fine structure (EXAFS) spectroscopic information, combined with competitive ligand exchange (CLE) experiments, we determined Hg(II) structures and thermodynamic constants for Hg(II) complexes formed with thiol functional groups in bacterial cell membranes of two extensively studied Hg(II) methylating bacteria: Geobacter sulfurreducens PCA and Desulfovibrio desulfuricans ND132. The Hg EXAFS data suggest that 5% of the total number of membranethiol functionalities (Mem-RStot = 380 ± 50 ?mol g-1 C) are situated closely enough to be involved in a 2-coordinated Hg(Mem-RS)2 structure in Geobacter. The remaining 95% of Mem-RSH is involved in mixed-ligation Hg(II)-complexes, combining either with low molecular mass (LMM) thiols like Cys, Hg(Cys)(Mem-RS), or with neighboring O/N membrane functionalities, Hg(Mem-RSRO). We report log K values for the formation of the structures Hg(Mem-RS)2, Hg(Cys)(Mem-RS), and Hg(Mem-RSRO) to be 39.1 ± 0.2, 38.1 ± 0.1, and 25.6 ± 0.1, respectively, for Geobacter and 39.2 ± 0.2, 38.2 ± 0.1, and 25.7 ± 0.1, respectively, for ND132. Combined with results obtained from previous studies using the same methodology to determine chemical speciation of Hg(II) in the presence of natural organic matter (NOM; Suwannee River DOM) and 15 LMM thiols, an internally consistent thermodynamic data set is created, which we recommend to be used in studies of Hg transformation processes in bacterium-NOM-LMM thiol systems.

SUBMITTER: Song Y

PROVIDER: S-EPMC7467648 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

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Toward an Internally Consistent Model for Hg(II) Chemical Speciation Calculations in Bacterium-Natural Organic Matter-Low Molecular Mass Thiol Systems.

Song Yu Y Adediran Gbotemi A GA Jiang Tao T Hayama Shusaku S Björn Erik E Skyllberg Ulf U

Environmental science & technology 20200617 13

To advance the scientific understanding of bacteria-driven mercury (Hg) transformation processes in natural environments, thermodynamics and kinetics of divalent mercury Hg(II) chemical speciation need to be understood. Based on Hg L<sub>III</sub>-edge extended X-ray absorption fine structure (EXAFS) spectroscopic information, combined with competitive ligand exchange (CLE) experiments, we determined Hg(II) structures and thermodynamic constants for Hg(II) complexes formed with thiol functional ...[more]

PMID: 32491838

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Project description:Vegetation fires are known to have broad geochemical effects on carbon (C) cycles in the Earth system, yet limited information is available for nitrogen (N). In this study, we evaluated how charring organic matter (OM) to pyrogenic OM (PyOM) altered the N molecular structure and affected subsequent C and N mineralization. Nitrogen near-edge X-ray absorption fine structure (NEXAFS) of uncharred OM, PyOM, PyOM toluene extract, and PyOM after toluene extraction were used to predict PyOM-C and -N mineralization potentials. PyOM was produced from three different plants (e.g. Maize-Zea mays L.; Ryegrass-Lollium perenne L.; and Willow-Salix viminalix L.) each with varying initial N contents at three pyrolysis temperatures (350, 500 and 700?°C). Mineralization of C and N was measured from incubations of uncharred OM and PyOM in a sand matrix for 256?days at 30?°C. As pyrolysis temperature increased from 350 to 700?°C, aromatic C[bond, double bond]N in 6-membered rings (putative) increased threefold. Aromatic C[bond, double bond]N in 6-membered oxygenated ring increased sevenfold, and quaternary aromatic N doubled. Initial uncharred OM-N content was positively correlated with the proportion of heterocyclic aromatic N in PyOM (R2?=?0.44; P?<?0.0001; n?=?42). A 55% increase of aromatic N heterocycles at high OM-N content, when compared to low OM-N content, suggests that higher concentrations of N favor the incorporation of N atoms into aromatic structures by overcoming the energy barrier associated with the electronic and atomic configuration of the C structure. A ten-fold increase of aromatic C[bond, double bond]N in 6-membered rings (putative) in PyOM (as proportion of all PyOM-N) decreased C mineralization by 87%, whereas total N contents and C:N ratios of PyOM had no effects on C mineralization of PyOM-C for both pyrolysis temperatures (for PyOM-350?°C, R2?=?0.15; P?<?0.27; for PyOM-700?°C, R2?=?0.22; P?<?0.21). Oxidized aromatic N in PyOM toluene extracts correlated with higher C mineralization, whereas aromatic N in 6-membered heterocycles correlated with reduced C mineralization (R2?=?0.56; P?=?0.001; n?=?100). Similarly, aromatic N in 6-membered heterocycles in PyOM remaining after toluene extraction reduced PyOM-C mineralization (R2?=?0.49; P?=?0.0006; n?=?100). PyOM-C mineralization increased when N atoms were located at the edge of the C network in the form of oxidized N functionalities or when more N was found in PyOM toluene extracts and was more accessible to microbial oxidation. These results confirm the hypothesis that C persistence of fire-derived OM is significantly affected by its molecular N structure and the presented quantitative structure-activity relationship can be utilized for predictive modeling purposes.

Project description:The determination of copper (Cu) speciation and its bioavailability in natural waters is an important issue due to its specific role as an essential micronutrient but also a toxic element at elevated concentrations. Here, we report an improved anodic stripping voltammetry (ASV) method for organic Cu speciation, intended to eliminate the important problem of surface-active substances (SAS) interference on the voltammetric signal, hindering measurements in samples with high organic matter concentration. The method relies on the addition of nonionic surfactant Triton-X-100 (T-X-100) at a concentration of 1 mg L-1. T-X-100 competitively inhibits the adsorption of SAS on the Hg electrode, consequently 1) diminishing SAS influence during the deposition step and 2) strongly improving the shape of the stripping Cu peak by eliminating the high background current due to the adsorbed SAS, making the extraction of Cu peak intensities much more convenient. Performed tests revealed that the addition of T-X-100, in the concentration used here, does not have any influence on the determination of Cu complexation parameters and thus is considered "interference-free." The method was tested using fulvic acid as a model of natural organic matter and applied for the determination of Cu speciation in samples collected in the Arno River estuary (Italy) (in spring and summer), characterized by a high dissolved organic carbon (DOC) concentration (up to 5.2 mgC L-1) and anthropogenic Cu input during the tourist season (up to 48 nM of total dissolved Cu). In all the samples, two classes of ligands (denoted as L1 and L2) were determined in concentrations ranging from 3.5 ± 2.9 to 63 ± 4 nM eq Cu for L1 and 17 ± 4 to 104 ± 7 nM eq Cu for L2, with stability constants logK Cu,1 = 9.6 ± 0.2-10.8 ± 0.6 and logK Cu,2 = 8.2 ± 0.3-9.0 ± 0.3. Different linear relationships between DOC and total ligand concentrations between the two seasons suggest a higher abundance of organic ligands in the DOM pool in spring, which is linked to a higher input of terrestrial humic substances into the estuary. This implies that terrestrial humic substances represent a significant pool of Cu-binding ligands in the Arno River estuary.

Dataset Information

Toward an Internally Consistent Model for Hg(II) Chemical Speciation Calculations in Bacterium-Natural Organic Matter-Low Molecular Mass Thiol Systems.

Publications

Toward an Internally Consistent Model for Hg(II) Chemical Speciation Calculations in Bacterium-Natural Organic Matter-Low Molecular Mass Thiol Systems.

Similar Datasets

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