Integrating\nEnzyme-Based Kinetics in Reactive Transport\nModels to Simulate Spatiotemporal Dynamics of Biomarkers during Chlorinated\nEthene Degradation

Biomarkers such as\nfunctional gene mRNA (transcripts) and proteins\n(enzymes) provide direct proof of metabolic regulation during the\nreductive dechlorination (RD) of chlorinated ethenes (CEs). Yet, current\nmodels to simulate their spatiotemporal variability are not flexible\nenough to mimic the homologous behavior of <i>RDase</i> functional\ngenes. To this end, we developed new enzyme-based kinetics to model\nthe concentrations of CEs together with the transcript and enzyme\nlevels during RD. First, the model was calibrated to existing microcosm\ndata on RD of cis-DCE. The model mirrored the <i>tceA</i> and <i>vcrA</i> gene expression and the production of\ntheir enzymes in <i>Dehalococcoides</i> spp. Considering <i>tceA</i> and <i>vcrA</i> as homologous instead of\nnonhomologous improved fitting of the mRNA time series. Second, CEs\nand biomarker patterns were explored as a proof of concept under groundwater\nflow conditions, considering degraders occurring in immobile and mobile\nstates. Under both microcosm and flow conditions, biomarker-rate relationships\nwere nonlinear hysteretic because <i>tceA</i> and <i>vcrA</i> acted as homologous genes. The mobile biomarkers additionally\nundergo advective-dispersive transport, which increases the nonlinearity\nand makes the observed patterns even more challenging to interpret.\nThe model offers a thorough mechanistic description of RD while also\nallowing simulation of spatiotemporal dynamic patterns of various\nkey biomarkers in aquifers.