Quantifying Gene Expression to Predict and Optimize Reductive Dechlorination by Dehalococcoides spp.
This study will apply gene expression analysis techniques to evaluate, predict, and optimize Dehalococcoides spp. reductive dechlorination activity in complex laboratory and field-site microbial communities. Based on the observation that Dehalococcoides spp. grow and dechlorinate less robustly in pure culture than in mixed communities, molecular techniques will be used to compare increasingly complex communities, ranging from pure and enrichment cultures to soil microcosms and field samples, in order to identify expression-based markers that correlate with robustness of dechlorination activity. First, the per-cell dechlorination rate will be compared across a suite of communities to determine the predictive value of several fundamental metrics such as the cell density of Dehalococcoides spp., the identity and quantity of reductase genes present, and the expression level of each reductase gene. Second, whole-genome microarrays of D. ethenogenes 195 will be used to compare the suite of communities and identify novel genes whose expression is closely correlated with per-cell dechlorination rates. Genes identified by microarrays to be potentially good expression markers will be further analyzed by real time quantitative PCR (qPCR). Third, identified predictive markers will be tested on field-site samples from the Idaho National Environmental Engineering Laboratory, where lactate injection to promote in situ bioremediation of trichloroethene (TCE) is ongoing, to seek correlations of degradation activity gradients with gene expression across space and time. Finally, predictive kinetic models for reductive dechlorination will be developed that incorporate the presence, copy number, and expression level of specific genes and the expression of validated and field-tested correlative genes.
Funded by the National Science Foundation, BES-01-0504244.
Hierarchical clustering of genes differentially expressed as Dehalococcoidesethenogenes transitions from the early-exponential (EE) to the late-stationary (LS) growth phases. The color gradient from blue to yellow represents increasing gene expression.
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Biodegradation of the Flame Retardants Polybrominated Diphenyl Ethers
Oxygenase-Catalyzed
Biodegradation of Emerging Water Contaminants: 1,4-Dioxane and N-Nitrosodimethylamine
Characterizing and Evolving the Propane Monooxygenase for N-Nitrosodimethylamine Biodegradation and Green Chemistry
Quantifying Gene Expression to Predict and Optimize Reductive Dechlorination by Dehalococcoides spp.
Application of Microarrays to Identify Biomarkers of Reductive Dehalogenating-Microbial Communities
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