Metal Adsorption onto Bacterial Surfaces: Development of a Predictive Approach

Abstract Aqueous metal cation adsorption onto bacterial surfaces can be successfully modeled by means of a surface complexation approach. However, relatively few stability constants for metal-bacterial surface complexes have been measured. In order to determine the bacterial adsorption behavior of cations that have not been studied in the laboratory, predictive techniques are required that enable estimation of the stability constants of bacterial surface complexes. In this study, we use a linear free-energy approach to compare previously measured stability constants for Bacillus subtilis metal-carboxyl surface complexes with aqueous metal-organic acid anion stability constants. The organic acids that we consider are acetic, oxalic, citric, and tiron. We add to this limited data set by conducting metal adsorption experiments onto Bacillus subtilis, determining bacterial surface stability constants for Co, Nd, Ni, Sr, and Zn. The adsorption behavior of each of the metals studied here was described well by considering metal-carboxyl bacterial surface complexation only, except for the Zn adsorption behavior, which required carboxyl and phosphoryl complexation to obtain a suitable fit to the data. The best correlation between bacterial carboxyl surface complexes and aqueous organic acid anion stability constants was obtained by means of metal-acetate aqueous complexes, with a linear correlation coefficient of 0.97. This correlation applies only to unhydrolyzed aqueous cations and only to carboxyl binding of those cations, and it does not predict the binding behavior under conditions where metal binding to other bacterial surface site types occurs. However, the relationship derived in this study permits estimation of the carboxyl site adsorption behavior of a wide range of aqueous metal cations for which there is an absence of experimental data. This technique, coupled with the observation of similar adsorption behaviors across bacterial species (Yee and Fein, 2001) , enables estimation of the effects of bacterial adsorption on metal mobilities for a large number of environmental and geologic applications.

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