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University of California-Berkeley

Superfund Research Program

Application of Comparative Genomics, Transcriptomics, and Proteomics to Optimize Microbial Reductive Dehalogenation

Project Leader: Lisa Alvarez-Cohen
Co-Investigator: Gary L. Andersen (Lawrence Berkeley National Laboratory)
Grant Number: P42ES004705
Funding Period: 2000-2017

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Project Summary (2006-2011)

This project applies advanced molecular tools to understand and optimize the microbial detoxification of common Superfund pollutants, perchloroethene (PCE) and trichloroethene (TCE), which pose a significant threat to human and ecological health. By studying the fundamental processes responsible for anaerobic microbial degradation of PCE and TCE, this work promotes improved situ bioremediation processes. Previous NIEHS-funded research sought to identify and understand the microbes within complex communities responsible for dechlorination. This work takes the next logical step by focusing on the only genus of bacteria, Dehalococcoides, known to completely reduce PCE and TCE to ethene. Whole-genome microarrays, proteomic analyses, and quantitative PCR are being used to characterize the genomic differences between a variety of Dehalococcoides strains and to evaluate gene expression and proteomic changes caused by reductive dechlorination of a variety of substrates, growth in simple and complex microbial communities, and other physiological perturbations. Genomic and transcriptomic comparison of Dehalococcoides strains with different degradation abilities identifies the pathways responsible for specific and general metabolism as well as reveals the evolutionary relationship between the various isolated strains. Transcriptomic comparison of Dehalococcoides strains in pure and mixed cultures identifies pathways involved in inter-species interactions, reveals the nutritional needs and metabolic roles of Dehalococcoides in consortia, and addresses the limitation in bioremediation applications presented by the poor growth of isolated Dehalococcoides strains. Data from strain identification, gene expression, and protein production is being complied into kinetic models that can be used to predict rates of reductive dechlorination by poorly characterized microbial communities. This research meets the SBRP goal of limiting the human exposure and toxicity of chemicals commonly found at Superfund sites by advancing the development of in situ bioremediation of PCE and TCE, a technology that destroys contaminants in their subsurface location without extraction to the surface, avoiding potential human and ecological exposure.

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