The inorganic metalloid arsenic, organic chlorinated solvents (e. g. trichloroethene (TCE)) and aromatic hydrocarbons (e. g. benzene, toluene, ethylbenzene and xylenes (BTEX)) are frequently detected as a mixture of contaminants in groundwater aquifers. Their presence in drinking water supplies represents a hazard to public health and the environment. Currently, arsenic ranks No.1 on the ATSDR Priority List of Hazardous Substances and has been reported as a problem at 917 Superfund National Priorities List sites. Due to its common co-occurrence with TCE and BTEX at these sites, it is important to understand the effects of potential remediation strategies that target only one contaminant class on the fate and transport of the other contaminants. The objective of this project is to apply systems biology approaches to study interactions within microbial communities involved in the bioremediation of groundwater mixtures containing arsenic species in combination with TCE and BTEX.
We aim to enrich and study microbial communities that can concurrently reduce the bioavailability of arsenic and degrade the co-contaminants and specifically address complex problems arising from the presence of chemical mixtures at hazardous waste sites. Bioremediation processes that biostimulate fermenting microorganisms by injection of organics into groundwater aquifers to promote the dechlorination of TCE are likely to generate soluble arsenic species, leading to the production of new and more significant groundwater (GW) contaminants. Similarly, BTEX releases into aquifers result in the rapid depletion of oxygen and other electron acceptors, leading to arsenic mobilization. A key challenge in achieving effective bioremediation without mobilizing arsenic is understanding the multi-scale complexity of subsurface microbial communities that could facilitate useful transformations of arsenic, while also targeting the degradation of organic co-contaminants. We hypothesize that understanding the structure, function and syntrophic interactions of microbial communities involved in arsenic transformations can lead to optimized simultaneous bioremediation of the metalloid arsenic as well as chlorinated solvents and aromatic hydrocarbons. To test this hypothesis, we will enrich and construct cultures as well as co-contaminant transformations and apply meta-omics based approaches to characterize interactions within these communities. We will then evaluate the responses of these enrichments and consortia to perturbations and various co-contaminant exposures (aims 1-3). We will subsequently develop models to provide predictive input to new designs for effective bioremediation of these mixtures (aim 4). from contaminated GW and sediments that are capable of arsenic cycling The knowledge and models developed from this research will be valuable to provide guidance to practitioners of bioremediation to improve operation and practice in the common occurrence of co-located mixtures of arsenic, solvents and aromatics.

Public Health Relevance

Arsenic, chlorinated solvents and aromatic hydrocarbons are frequently detected as mixtures in groundwater aquifers that represent a hazard to public health and the environment. This project will apply systems biology approaches to study interactions within microbial communities involved in the bioremediation of groundwater mixtures containing arsenic species in combination with other chemicals.

Agency
National Institute of Health (NIH)
Institute
National Institute of Environmental Health Sciences (NIEHS)
Type
Hazardous Substances Basic Research Grants Program (NIEHS) (P42)
Project #
5P42ES004705-30
Application #
9520127
Study Section
Special Emphasis Panel (ZES1)
Project Start
Project End
Budget Start
2018-04-01
Budget End
2019-03-31
Support Year
30
Fiscal Year
2018
Total Cost
Indirect Cost
Name
University of California Berkeley
Department
Type
DUNS #
124726725
City
Berkeley
State
CA
Country
United States
Zip Code
94704
Guyton, Kathryn Z; Rusyn, Ivan; Chiu, Weihsueh A et al. (2018) Application of the key characteristics of carcinogens in cancer hazard identification. Carcinogenesis 39:614-622
Grigoryan, Hasmik; Edmands, William M B; Lan, Qing et al. (2018) Adductomic signatures of benzene exposure provide insights into cancer induction. Carcinogenesis 39:661-668
Barazesh, James M; Prasse, Carsten; Wenk, Jannis et al. (2018) Trace Element Removal in Distributed Drinking Water Treatment Systems by Cathodic H2O2 Production and UV Photolysis. Environ Sci Technol 52:195-204
Counihan, Jessica L; Wiggenhorn, Amanda L; Anderson, Kimberly E et al. (2018) Chemoproteomics-Enabled Covalent Ligand Screening Reveals ALDH3A1 as a Lung Cancer Therapy Target. ACS Chem Biol 13:1970-1977
Lavy, Adi; Keren, Ray; Yu, Ke et al. (2018) A novel Chromatiales bacterium is a potential sulfide oxidizer in multiple orders of marine sponges. Environ Microbiol 20:800-814
Perttula, Kelsi; Schiffman, Courtney; Edmands, William M B et al. (2018) Untargeted lipidomic features associated with colorectal cancer in a prospective cohort. BMC Cancer 18:996
Edmands, William M B; Hayes, Josie; Rappaport, Stephen M (2018) SimExTargId: a comprehensive package for real-time LC-MS data acquisition and analysis. Bioinformatics 34:3589-3590
McHale, Cliona M; Osborne, Gwendolyn; Morello-Frosch, Rachel et al. (2018) Assessing health risks from multiple environmental stressors: Moving from G×E to I×E. Mutat Res 775:11-20
Bruton, Thomas A; Sedlak, David L (2018) Treatment of perfluoroalkyl acids by heat-activated persulfate under conditions representative of in situ chemical oxidation. Chemosphere 206:457-464
Schiffman, Courtney; McHale, Cliona M; Hubbard, Alan E et al. (2018) Identification of gene expression predictors of occupational benzene exposure. PLoS One 13:e0205427

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