RELATING EMPIRICAL AND MECHANISTIC RATE LAWS FOR DISSIMILATORY METAL REDUCING BACTERIA

The solubility, bioavailability, and mobility of metals and radionuclides in subsurface waters can be dramatically altered by microbial action. The changes in metal speciation can be “direct” (e.g., reduction of U(VI) by dissimilatory metal reducing bacteria, DMRB), or “indirect” (e.g., reduction of U(VI) by biogenic Fe(II) ) and the microbial activity can be effected through direct microbe/metal interactions (e.g., microbial nano-wires), electron shuttling compounds (e.g., quininoid exudates), or complexation-assisted solubilization (e.g., cell-released or naturally occurring chelators solubilizing Fe(III) followed by transport to the cell and reduction). The rates of microbial metal reduction are, therefore, highly complex and no single set of experimental data can be expected to produce rate information that will be applicable to the widely variable conditions encountered in natural settings. To develop more robust rate laws, we have compiled published DMRB rate data along with metadata describing the culture, electron donor/acceptor, solution chemistry, and reactor conditions. Currently, these data are being formulated into a database—akin to the thermodynamic tables commonly employed in groundwater speciation calculations—that will be made freely available through Pennsylvania State University's Center for Environmental Kinetics Analysis (a NSF sponsored Environmental Molecular Sciences Institute).

To exemplify the use of this database, we will present a network of rate laws in the form of a partially ordered set (POSET). This rate law POSET will be constructed such that lower elements in the set (e.g., zero-order rate laws) can be derived from higher elements (e.g., Monod rate expressions). Rate parameters for the elements of the POSET will be derived from global analyses on the compiled rate data allowing us to (i) outline the relationship between less detailed but highly accessible rate laws and expressions that are mechanistically detailed but difficult to parameterize, (ii) provide a quantitative framework for scaling between laboratory results and field scale measurements, and (iii) allow for the incorporation of biochemical results such as enzyme activity into hydrogeologic modeling.