Xanthan Exopolysaccharide: Cu2+ Complexes Affected from the pH

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Xanthan exopolysaccharide: Cu complexes affected from the pH-dependent conformational state; implications for environmentally relevant biopolymers Benjamin Causse, Lorenzo Spadini, Géraldine Sarret, Adeline Faure, Christophe Travelet, Dominique Madern , and Cécile Delolme Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.5b03141 • Publication Date (Web): 29 Jan 2016 Downloaded from http://pubs.acs.org on February 3, 2016

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Xanthan exopolysaccharide: Cu2+ complexes

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affected from the pH-dependent conformational

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state; implications for environmentally relevant

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biopolymers

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Benjamin Causse†§, Lorenzo Spadini‡§*, Géraldine Sarret§, Adeline Faure§, Christophe

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Travelet┴, Dominique MadernҰ, Cecile Delolme†

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† § ‡

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LEHNA / ENTPE / UCB / CNRS UMR 5023, F-69518 Lyon, France. ISTERRE, UMR 5275 CNRS / Université Grenoble Alpes / IRD, F-38041 Grenoble, France. LTHE, UMR 5564 CNRS / Université Grenoble Alpes / IRD, F-38041 Grenoble, France.



CERMAV, CNRS UPR 5301 / F-38000 Grenoble, France.

Ұ

IBS, UMR 5075 / CNRS / Université Grenoble Alpes / CEA, 38000 Grenoble, France.

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Correspondence:

Tel.: +33 (0) 4 56 52 09 95; fax: +33 (0) 4 56 52 09 87

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Email: Lorenzo Spadini, [email protected]

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KEYWORDS: xanthan, copper, biopolymer, soil, organic matter, humic acids, conformation,

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exopolysaccharide, copper, complexation.

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ABSTRACT

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The conformational impact of environmental biopolymers on metal sorption was studied

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through Cu sorption on xanthan. The apparent Cu2+ complexation constant (LogK; Cu2+ + L-

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CuL+) decreased from 2.9±0.1 at pH 3.5 to 2.5±0.1 at pH 5.5 (ionic strength I=0.1). This

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behavior is in apparent contradiction with basic thermodynamics, as usually the higher the pH

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the more cations bind. Our combined titration, circular dichroism and dynamic light scattering

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study indicated that the change observed in Cu bond strength relates to a conformational change

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of the structure of xanthan, which generates more chelating sites at pH 3.5 than at pH 5.5. This

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hypothesis was validated by the fact that the Cu sorption constants on xanthan were always

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higher than those measured on a mixture of Pyruvic and Glucuronic acids (LogK=2.2), which are

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the two constitutive ligands present in the xanthan monomer. This study shows the role of the

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structural conformation of natural biopolymers in metal bond strength. This finding may help to

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better predict the fate of Cu and other metals in acidic environmental settings such as aquatic

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media affected by acid mine drainage, as well as peats and acidic soils, and to better define

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optimal conditions for bioremediation processes.

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INTRODUCTION

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In a large number of both, natural and contaminated soils, the biogeochemistry of heavy metals

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and especially copper is controlled dominantly1,2 or at least significantly3–5 by their interaction

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with natural organic matter (NOM). Studies on interactions between NOM and metals were

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explored very early both for humic material6 and for bacterial extracellular substances.7 These

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interactions were studied and quantified mainly via a macroscopic approach that represented the

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retention of trace metal elements (TME) by mechanisms of complexation with proton exchanger

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sites present in the organic matter. The two basic parameters used to determine the reactivity

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between the NOM for metal cations are the densities of the complexing sites of NOM and the

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strength of the bond measured by the complexation constant. A recent study has shown that the

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densities of the sites on the different constituents of NOM are relatively homogenous: 1 to 5

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mmol/g dry weight.8

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However, the complexation constants between the transition metals Me and organic matter

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(logKMe-NOM) calculated for the different constituents of the NOM, namely free bacteria,

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biofilms, exopolymeric substances, humic substances, soils, sediments and sludges) present

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much higher variations. This affinity varies as a function of the nature of the metals that tend to

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complex the substrates more or less strongly. But for a given metal these variations of constants

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can reach four units for the log K values, which means four orders of magnitude for the constant.

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The largest amount of data concerns the affinity constants of copper for NOMs. For example,

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regarding the carboxylic surface site of bacterial free living cells, LogKCu-Bacteria varies from 3.8

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to 69–13 , for humic substances LogKCu-Humic/Fulvic_acids varies from 2.5 to 3.8

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. Regarding

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activated sludges (that can be considered as mixtures of biofilms and humic substances since

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they are dosed with EPS, proteins, and nucleic and humic acids), LogKCu-activatedSludge varies from

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3 to 4.5.16,17

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This variability of constants has been little studied and has not or only rarely been explained,

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thus limiting the use of these data in modeling and predicting the fate of TMEs in the

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environment. Determining these constants is partly dependent on experimental and modeling

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conditions, as different effects affect the numerical values of metal-ligand constants of complex

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substrates, e.g. the operational definition of the total concentration of complexing surface sites,

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the analytical uncertainties affecting the proton mass balance calculations, correlative effects

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during fitting, the variable handling of apparent equilibrium states and electrostatic model

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assumptions. The Supporting Information section (SI) provides more explanatory details. Some

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authors have explained the increase of affinity of bacteria for metals with ageing.18,19 More

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recently the variation of the affinity of bacterial surfaces with metals has been studied as a

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function of time and external stresses to which bacterial strains are subjected.20 As indicated by

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the authors, the increase of metal sorption observed could be linked to an increase in the

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concentration in exopolysaccharides (EPS) or an increase in the intrinsic affinity of the substrate

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for metals. On the basis of another approach,21 affinity varying as a function of different

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substrates has been highlighted. The affinity of cadmium for the EPS produced by Rhizobium

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meliloti is preponderant in comparison to soil components and aqueous suspended matters. A

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study that compared the sorption of cadmium on four bacteria and their EPS concluded that the

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affinity of cadmium was finally very similar on these substrates.22 Overall, a considerable

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affinity of substrates for metals has been observed but not explained. These considerable

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variations suggest intrinsic differences of affinity of substrates for metals, i.e. variable bond

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strengths developed between the substrate and a given metal.

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The regular composition and pattern of exopolysaccharides (EPS) makes them good models

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for the detailed study of interactions between metals and organic substrates.23 The retention of

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metals by chitin and chitosan has been studied as well.24 With xanthan, a reduction of its

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viscosity with an increased concentration of absorbed bivalent cations has been observed. The

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C nuclear magnetic resonance (NMR) data have shown that the main association of cations on

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xanthan occurs on the pyruvates located at the end of the lateral chain of different monomers,25

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thus sorption involving the ends of different monomer chains. The study therefore supports the

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existence of intermolecular and intra-molecular “chelating” sites. The formation of this type of

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link certainly affects the stability of the metals sorbed. It could explain the variability of the

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constants observed between different metals. In addition, pH conditions may affect the

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conformation of biopolymers. Chemical equilibrium studies performed on organic polymers are

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rarely combined with studies investigating the unitary components of these polymers and do not

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take into account the conformation of these molecules with complex structures. In addition, the

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parameters affecting the conformation of these polymers (pH, ionic strength, T°) are not all

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controlled and monitored. However, we think that this information is vital to better understand

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the sorption capacity of metals on biopolymers and their variability.

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The objective of our study is therefore to determine the role of the conformational structure of

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biopolymers in the binding strength of metal complexes. Our aim is to show the extent to which

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the structure can explain the variations of sorption properties. We propose to study the reactivity

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of a model bacterial EPS, xanthan, to copper. Xanthan was chosen as a model EPS since we have

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detailed knowledge of its chemical structure and its acid-base properties.8 Copper Cu(II) was

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chosen as a model metal cation since, firstly, it is representative of urban and agricultural

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pollution26–29, secondly, it is known to have a specific affinity for organic matter;9,13,30,31and

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thirdly, free Cu2+ is easy to measure in aqueous solution using potentiometric methods.

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The study couples the determination of the constants of complexation of copper by xanthan

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performed by modeling experimental sorption data, with the characterization of molecule

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conformation for the different pHs tested. This affinity is compared to the simple ligands present

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in xanthan. Significant changes in sorption properties linked to the conformation of the molecule

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are highlighted and discussed in relation to the global reactivity of the simple and chelating

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ligands of the NOM.

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Material and Methods Titrations performed at fixed total Copper concentrations.

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50 ml of a solution containing 1 g/L xanthan and 0.028, 0.046 and 0.13 mmol/L Cu2+ total

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concentrations from Cu(NO3)2 stock solutions (Cu(NO3)2x2.5 H2O, SIGMA ALDRICH) were

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titrated from pH 3.0 to pH 10.0 (and from pH 10.0 to pH 2.75) with 0.1 M NaOH (or 0.1 M

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HNO3, both from Titrisol Merck). As verified through PHREEQC modeling32 Nitrate complex

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less than 12% of Cu(II) ions in the given conditions. A previous combined 13C and 1H NMR,

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chromatographic and titrimetric analysis revealed that proton and cation sorption properties are

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due to its monocarboxylic functional groups. The determined proportions of pyruvic and

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glucuronic groups were 33 and 66%, respectively.8 To compare the sorption properties of the

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entire polymer to its specific reactive site in glucuronic and pyruvic sugars, solutions containing

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1 mmol/L Glucuronic acid (GlcA) (D-(+)-Glucuronic acid γ-lactone, ≥99%, SIGMA-Aldrich)

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and 1 mmol/L Pyruvic acid (PyrA) (SIGMA-ALDRICH, 98%), i.e. a total site concentration of 2

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mmol/L carboxylic functional groups, were titrated under equivalent conditions. This mixture of

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monomeric acid-base reactive ligands (present in xanthan in polymerized form) is hereafter

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referred to as ‘equivalent mixture’. The proportion of each PyrA and GlcA at 50% compared to

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their occurrence at 1/3 – 2/3 in xanthan EPS analyzed by us stemmed from the initially unknown

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ratio, which was not unique and varied according to the bacterial strain and the chemical

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environment.33

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Free copper [Cu2+] concentrations were obtained in the solution from a concentration-

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calibrated Metrohm 6.0502.140 copper-specific electrode and a Metrohm 6.0733.100 Ag/AgCl

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reference electrode calibrated to Cu2+ concentration standards. The concentrations of complexed

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copper and protons were both calculated from the difference in the mass balance of total

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introduced concentrations minus the free concentration. All the solutions were prepared in a

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0.100 M NO3- background medium, with Na+ as the dominant counter-ion. As more detailed in

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the supporting information, this allowed fixing ion activities and xanthan surface electrostatics

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reducing thereby the number of adjustable parameters in the fitting process. Other experimental

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conditions (potential stabilization criteria, CO2 exclusion) were the same as those of the

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experimental procedures given in.8 All the experiments were triplicated

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Copper-sorption isotherms.

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Xanthan solutions (70 mL at 1 g/L) and the equivalent mixture solution at equivalent

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concentrations were titrated stepwise at fixed pH=3.5±0.1 and 5.5±0.1 with a total copper

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concentration [Cu2+]tot = 10-3 mol/L containing titrant solutions delivered by a Metrohm Titrino

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burette controlled by the TIAMO Metrohm software. The pH was fixed by a base (0.1 mol/L)

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supplied by a 718 pH-Stat Titrino (Metrohm) programmed independently. Other experimental

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conditions were the same as those given above. All the experiments were triplicated.

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Equilibrium modeling.

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Xanthan is assumed to complex copper(II) ions via its monocarboxylic functional groups

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present in the polymer chains at a site density of 1.65 mmol/gdw (dw: dry weight). A combined

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NMR, chromatographic and titrimetric analysis revealed that 1/3 of them were due to the pyruvic

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group and 2/3 were due to the glucuronic group.8

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The GRFIT code,34 an FITEQL substitute,35 was as used to model the acid-base and Cu

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equilibrium data.

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The model developed is described in detail in the results section and is based on the 1 pK

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xanthan acid-base constant determined previously.8

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Circular dichroism.

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In order to characterize the modification of the xanthan conformation with pH, circular

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dichroism experiments were performed in 0.1 cm to 0.5 cm optical path cells on xanthan

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solutions in the pH range 2.7 to 11.0 (1 g/L, in 0.1 mol/L KF ionic medium - including small

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amounts of HCl to fix the pH), from 190 to 260 nm (CD6 JOBIN YVON at the Institut de

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Biologie Structurale –IBS- CEA Grenoble).

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Dynamic light scattering.

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Spectra of 1g/L xanthan solutions between pH 3.0 and pH 7.3 (in 0.1 mol/L KF ionic medium,

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including small amounts of HCl to fix the pH) were obtained on a high performance light

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scattering device (ALV/CGS-8F S/N 069, at CERMAV – CNRS – Grenoble) operating at a laser

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wavelength of 632.8 nm and at a maximum power of 35mW. The results were obtained at an

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angle of 90°.

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RESULTS

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The metal sorption study below is based on a previous acid-base study.8

Copper titrations.

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The percentages of copper complexed to xanthan and to the equivalent mixture (i.e. mixture of

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monomeric glucuronic acid (GlcA) and pyruvic acid (PyrA) obtained at 0.1 ionic strength and

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0.023, 0.046, 0.13 mmol/L total copper concentrations [Cutot]) are given in Figure 1.

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Above pH ~6 the concentration of adsorbed Cu ([Cuads]) for both xanthan and the ligand

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mixture increased to 100%. This agrees with the formation of aqueous Cu(OH)2 and the

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precipitation of solid Cu(OH)2(s). Model calculations attest that below pH 5.9 the Cu+2 activity

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will not be oversaturated with respect to tenorite or other more soluble Cu oxides/hydroxides. In

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this pH < 5.9 range, the xanthan and ligand mixture curves differed considerably. Cu sorption on

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xanthan was higher than the sorption on the equivalent mixture whatever the pH. For the ligand

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mixture, sorption started at pH 3 and increased up to 25% of adsorbed [Cutot] at pH 5.5.

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Regarding xanthan, sorption started at an initial titration pH of 2.7 and increased up to 40 to 50%

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of adsorbed [Cutot] at pH 3.5. Then, the sorbed copper decreased to about 25 to 37% of [Cutot] at

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pH 5.5. Thus, surprisingly, between pH 3.5 and 5.5, the sorbed Cu concentration decreased as pH

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increased. This unusual sorption pattern has never been described before. Cu-xanthan sorption

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isotherms at pH 3.5 and 5.5, obtained separately, confirmed the original sorption trend (Figure

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2): concordantly, [Cu]ads for xanthan exceeded [Cu]ads in the ligand mixture at both pH values,

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and [Cu]ads for xanthan at pH 3.5 exceeded [Cu]ads for xanthan at pH 5.5, contrary to the

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equivalent mixture data. Thus the Cu-pH and Cu-isotherm experiments performed independently

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concurred. This confirms and questions the unusual sorption pattern, while simultaneously

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raising questions on why this unusual sorption behavior occurred. Indeed, the decrease of sorbed

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copper at increasing pH is a priori energetically unfavorable, since the dominant aqueous Cu2+

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species compete with protons for sorption sites the more the pH decreases. Consequently [Cuads]

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should increase with increasing pH. The results suggest that a concurrent process more than

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balances the proton-Cu competition effect. Such a process could be linked to a conformational

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change of the xanthan substrate.

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Xanthan conformation.

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The molecular dichroism and light scattering measurements showed that the conformation of

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xanthan changed drastically with pH (Figure 3). As for the dichroism data, high pH spectra (pH

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8.3, 6.2, 5.1) reached their maxima at 204nm and their minima at 222nm. Conversely, acidic

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spectra (pH 2.7 and 3) shifted to a higher wavelength, with the maxima shifting to 210nm and

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the minima to 232nm. The amplitude also appeared to be lower (Figure 3a). The spectra obtained

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at pH 4 are intermediate between the acidic and basic groups. Similarly, light scattering spectra

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(Figure 3b) may also be distinguished in two families. Neutral pH radius distributions (pH 7.3,

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7.2, 5.4) have a single peak pointing to a hydrodynamic particle radius of 32nm to 36nm with a

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polydispersity (PDI) of 0.247 to 0.297. At low pH another hydrodynamic radius prevails (127nm

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for pH 3.03, PDI=0.354), pointing to a change in molecular aggregation. The pH 4.0 distribution,

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whose amplitudes are almost equal at both hydrodynamic radii (22nm and 160nm, PDI=0.441),

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appears to be the intermediate state in terms of molecular aggregation. These measurements

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show a change in xanthan conformation and/or aggregation dependent on pH. By considering the

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references36,37, the ordered state should prevail at neutral pH and the disordered state at acidic pH

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(Figure S2). Both dichroism and light scattering data indicate a change of state at

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pHtransition=4.0±1 for an ionic strength fixed at I=0.1.

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Titration modeling.

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For memory, the previous characterizations showed that the xanthan monomer weighs 900

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Daltons, that it contains respectively 0.5 PyrA and one GlcA per monomer and that the site

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density determined from structural and spectroscopic constraints equals 1.65 mmol sites/gdw.8

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These studies yielded the single pKaI=0.1 = 2.59 ± 0.05 acid-base equilibrium constant. This is

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the basis for modeling the copper sorption data at an ionic strength of I=0.1. It is based on the

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non-electrostatic modeling approach.

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The copper data model is based on the simplifying assumption that a change of the

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conformational state of xanthan affects metal chelation and thus metal sorption constants but not,

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or only insignificantly, the acid-base constants of the carboxylic functional groups involved.

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As shown above, the experimental results indicate that the conformational change of xanthan

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affects Cu-xanthan bond strength. This means that the corresponding complexation constant

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becomes a function of pH. In classical thermodynamics such changes do not occur, changes of

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complexation constants therefore cannot be easily integrated in existing speciation codes.

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Integrating a change dependent on the ordered state of xanthan required defining an original

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stoichiometric setup. The change from a disordered (low pH, Xd-) to an ordered (high pH, Xo-)

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state is represented through a 1 pK protonation reaction in which, conceptually, no proton is

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exchanged between the reactant and the product. As the ordered/disordered transition is effective

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between pH 3 and 7, we initially and arbitrarily fixed the pK value of the transition at 5.0 and

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optimized the constant value during the modeling of the experimental sorption curves. The final

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pKtransition was equal to 4.5.

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Xd- Xo- + H+ ; Ktransition = 10-4,5

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In this deliberately non equilibrated reaction, Xd- and Xo- represent both deprotonated carboxyl

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sites in the disordered and ordered states. The (Xd-) and (Xo-) activities are equal at pH 4.5, the

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conformation transition pH defined accordingly agrees with that determined from light scattering

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experiments (pH 4±1). The conformational change modeled extends over two pH units, i.e. at pH

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5.5 and pH 3.5 most of the carboxyls (91%) are in the ordered and disordered states,

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respectively. This also agrees with our experimental dichroism and light scattering data, as they

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show a conformational evolution over about two pH units. This approach thus allows smartly

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combining chemical speciation and molecular conformational changes, which are usually not

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expressible together on such a compact and robust base.

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The whole reactions taken into account and their stoichiometries are given in Table 1. The

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protons relating to the conformational states of xanthan between the ordered and disordered state

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are written in brackets. It is important to understand that these protons are virtual, they do not

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enter in the mass balance calculation for each chemical species and are defined as follows:

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[XdH] + [Xd-] + [Xo-] + [XdCu+] + [XoCu+]

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For xanthan:

[Xan]tot

=

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For copper:

[Cu]tot =

[Cu2+] + [XdCu+] + [XoCu+] + [CuOH+] + [Cu(OH)2]

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For protons:

[H]tot =

[H+] - [OH-] + [XdH] - [CuOH+] - 2[Cu(OH)2]

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We underline that the concentration of XoH was very low compared to the other species and was therefore not considered in the data modeling.

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These mass balances thus differ from those calculated mathematically by the equilibrium

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analysis GRFIT,34 a code which necessarily also includes the protons representing the

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conformational state (brackets in Table 1). The LogK value of the XdH/Xd- is then equal to the

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sum of the pKtransition (4.5) and the xanthan protonation constant (pKa =2.6, Table 1).

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This model definition allows associating two different copper complexation constants for the

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ordered and disordered state, respectively. The fitted Cu-xanthan constants are finally equal to

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LogK=2.5 for a high pH and LogK=2.9 for a low pH and are presented in Table 1. In Figure 1

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the optimized model fits the data points related to xanthan well by first increasing from pH 2 to

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3.5 and then decreasing from pH 3.5 to 5.5. In the copper isotherms (Figure 2) the model also

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follows the trend of the data points for xanthan. The model thus adequately reproduces the

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xanthan sorption pattern, demonstrating its ability to reproduce the conformation-dependent

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change of the Cu-xanthan bond strength. Figure S1 represents the corresponding speciation

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diagrams. It is noteworthy that the proton charge curve changes only slightly in the presence or

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absence of copper. Cu interacts only weakly with protonated sites, therefore the proton charge

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curve did not yield useful information for the evaluation of the reaction stoichiometries and is

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not shown.

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Contrary to xanthan, the titrations of the equivalent mixture present the usual pH-dependency

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for Cu sorption. Fits based on the adjustment of a single site acid-base exchange constant give a

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pKaI

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showing that the Cu-ligand mixture complexes are clearly weaker than the Cu-xanthan

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complexes for both ordered and disordered states (Figures 1 and 2). Moreover, this constant is

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0.5 log units higher than the theoretical Cu-PyrA and Cu-GlcA constants (LogKI=0.1=1.6 for both,

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Table 2). We consider this difference to be related to the keto-diol condensation reactions,

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leading to the dimerization of the two acids.8,38. Such reactions depend on pH and may be slow.

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The non-ideal curvature of the data curves observed (non-smooth slope increase in Figure 1, and

=0.1

= 2.74±0.05,8 yielding a mean copper complexation constant LogKCu-LI=0 = 2.2 and

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unusual bending at high log[Cu2+]aq in Figure 2) is probably related to the kinetics of this

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condensation reaction. This dimerization thus increases the copper complexation strength of the

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component acids. We therefore consider the unbound Cu-constants of PyrA and GlcA as

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reference states.

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Discussion

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This study questions whether the conformation of biopolymers impacts the bond strength of

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complexing metals. This is addressed by comparing the Cu(II)-xanthan bond strength at

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various pH to that of Cu(II) ions complexing a mixture of xanthan constituting monomeric

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ligands (i.e. glucuronate and pyruvate).

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The effect of pH on Cu complexation strength.

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Xanthan definitely presents unusual sorption behavior as Cu sorption decreases at increasing

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pH between pH 3.5 to pH 5.5. According to equilibrium thermodynamics, and by considering all

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the existing literature on cation sorption on natural biopolymers, copper(II) sorption should

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increase with pH as the competition between protons and Cu(II) ions for sorption sites decreases

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with increasing pH. Light scattering and dichroism measurements both indicate that the

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conformation of xanthan changes between pH 3.5 and 5.5. The parallel between these two

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phenomena and the change in Cu binding strength lead us to assume that they are linked, i.e. that

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the conformational change of xanthan affects Cu(II)-xanthan bond strength.

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Persistence length (q) measurements expressing the polymer rigidity on the basis of solution

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viscosity measurements showed that xanthan changes strongly its q value dependent on ionic

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strength, temperature and pH. Thus, high q values of 110 to 150 nm are obtained in high ionic

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strength conditions and ambient temperature (0.01 ≤ I ≤ 0.1, T=25 °C).37,39–47 This q value

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represents about 10 times the rigidity of cellulose and compares to double strained DNA (q = 150

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nm, high ionic strength), or to triple helix structures, e.g. schizophyllan (q = 150-200 nm) or

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collagen (q = 170 nm).48 Thus, at high ionic strength xanthan has an astonishingly high rigidity

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representative of a high molecular order state.37,40,41,44,45,49,50

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At high temperature (T>60°C, I kept constant) or at low ionic strength (I

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4 induces an ordered state (helix) (Figure S2). The combination of this result to titration data

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leads to the conclusion that the disordered state increases the Cu-xanthan bond strength.

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The effect of ligand nature on Cu-complexation strength.

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At both pH 3.5 and 5.5, the bond strength of the Cu-xanthan complex (mean LogKCu-Xanthan

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equal to 2.9 and 2.5) is higher than that developed between Cu and the equivalent monomer

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mixture (i.e. pyruvate and glucuronate; 1.6 ≤ LogKCu-Ligand ≤ 2.2; Table 2). This indicates that

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the biopolymer structure increases Cu sorption strength whatever the conformational state. Thus

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this result further validates the initial working hypothesis that the polymeric nature of xanthan

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increases Cu bond strength

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Comparison of referenced Cu-xanthan bond strength data.

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Table S1 lists model ligands and associated Cu binding constants.60 The bond strength between

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Cu and carboxyl-bearing model ligands increases in the following order: monocarboxylic ligands

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(LogKI=0.1~1.7) < keto-carboxylic ligands (1.4 ≤ LogKI=0.1 ≤ 2.15)

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monocarboxylic ligands (LogKI=0.1~ 2 ) < 2-Hydroxo-monocarboxylic ligands (LogKI=0.1~2.5)
4.5). Thus five- and six-ring coordination form the

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strongest chelates for dicarboxylic moieties.61 Increasing the ring size of dicarboxylic acids

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strongly decreases bond strength (Table S1). At nine ring atoms (e.g. pimelic acid, Table S1) the

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bond strength decreases to that of monocarboxylic moieties. This accounts not only for Cu(II),

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but also for Zn(II) and Cd(II) constants.18

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