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Published on: March 14, 2019
Modeling hexavalent chromium reduction in Escherichia coli 33456
1Department of Civil Engineering, University of Kentucky, Lexington, Kentucky 40506.
Biotechnology and Bioengineering
|February 20, 1994
Summary
A new enzymatic model accurately predicts hexavalent chromium (Cr(VI)) reduction by Escherichia coli. The model incorporates cellular reduction capacity (R(c)) to account for Cr(VI) toxicity, improving predictions under various conditions.
Area of Science:
- Environmental microbiology
- Biochemical engineering
- Toxicology
Background:
- Hexavalent chromium (Cr(VI)) poses significant environmental and health risks.
- Microbial reduction is a key process for Cr(VI) remediation.
- Existing models often do not fully account for Cr(VI) toxicity effects on microbial activity.
Purpose of the Study:
- To develop and validate an enzymatic model for microbial Cr(VI) reduction.
- To incorporate cellular reduction capacity (R(c)) to address Cr(VI) toxicity.
- To predict Cr(VI) reduction under both anaerobic and aerobic conditions.
Main Methods:
- Enzymatic reaction mechanism analysis.
- Nonlinear least-square analysis of experimental anaerobic culture data.
- Incorporation of a finite reduction capacity (R(c)) parameter.
- Modification for aerobic conditions including uncompetitive inhibition by molecular oxygen.
Main Results:
- The developed model accurately predicted Cr(VI) reduction in Escherichia coli 33456 under anaerobic conditions.
- Model parameters were successfully determined using experimental data.
- Predictions for aerobic conditions, including oxygen inhibition, showed excellent agreement with batch study results.
- Sensitivity analysis confirmed the uniqueness and robustness of the determined model parameters.
Conclusions:
- The enzymatic model with R(c) effectively characterizes microbial Cr(VI) reduction.
- The model provides a valuable tool for predicting Cr(VI) remediation by Escherichia coli.
- The study demonstrates the importance of considering toxicity and oxygen effects in microbial metal reduction modeling.

