Andrea Rocha Contributes to Groundwater Contamination and Ecosystem Functioning Article in mBio
Andrea Rocha, Ph.D. (Tennessee) co-authored an article entitled "Microbial Functional Gene Diversity Predicts Groundwater Contamination and Ecosystem Functioning" published in mBio Volume 9, Issue 1 on February 20, 2018.
Andrea's co-authors were Zhili He, Ping Zhangc, Linwei Wu, Qichao Tu, Zhou Shic, Bo Wu, Yujia Qin, Jianjun Wang, Qingyun Yan, Daniel Curtis, Daliang Ning, Joy D. Van Nostrand, Liyou Wu, Yunfeng Yang, Dwayne A. Elias, David B. Watson, Michael W. W. Adams, Matthew W. Fields, Eric J. Alm, Terry C. Hazen, Paul D. Adams, Adam P. Arkin, and Jizhong Zhou.
Andrea is a Senior Staff Scientist based in Tennessee with more than 10 years of experience focused on leading-edge research using an array of geochemical, microbial, computational, and genomics techniques within the areas of environmental microbiology, computational biology, and engineering science. She has proven success helping clients by spearheading projects; leading multi-disciplinary teams toward project completion; and establishing collaborations across organizations and the United States Department of Energy (DOE) National Laboratories. Andrea's specific areas of expertise include the application of molecular technologies for defining and managing environmental processes; the utilization of computational biology tools for characterization of potentially key microbial metabolic processes involved in bioremediation and bioenergy; and the implementation of newly developed biotechnology for microbial detection and assessment.
mBio is a broad-scope, online-only, open access journal published by the American Society for Microbiology (ASM). mBio offers streamlined review and publication of the best research in microbiology and allied fields. ASM is composed of more than 50,000 scientists and health professionals. ASM's mission is to promote and advance the microbial sciences.
Contamination from anthropogenic activities has significantly impacted Earth's biosphere. However, knowledge about how environmental contamination affects the biodiversity of groundwater microbiomes and ecosystem functioning remains very limited. Here, we used a comprehensive functional gene array to analyze groundwater microbiomes from 69 wells at the Oak Ridge Field Research Center (Oak Ridge, TN), representing a wide pH range and uranium, nitrate, and other contaminants. We hypothesized that the functional diversity of groundwater microbiomes would decrease as environmental contamination (e.g., uranium or nitrate) increased or at low or high pH, while some specific populations capable of utilizing or resistant to those contaminants would increase, and thus, such key microbial functional genes and/or populations could be used to predict groundwater contamination and ecosystem functioning. Our results indicated that functional richness/diversity decreased as uranium (but not nitrate) increased in groundwater. In addition, about 5.9% of specific key functional populations targeted by a comprehensive functional gene array (GeoChip 5) increased significantly (P < 0.05) as uranium or nitrate increased, and their changes could be used to successfully predict uranium and nitrate contamination and ecosystem functioning. This study indicates great potential for using microbial functional genes to predict environmental contamination and ecosystem functioning.
Importance: Disentangling the relationships between biodiversity and ecosystem functioning is an important but poorly understood topic in ecology. Predicting ecosystem functioning on the basis of biodiversity is even more difficult, particularly with microbial biomarkers. As an exploratory effort, this study used key microbial functional genes as biomarkers to provide predictive understanding of environmental contamination and ecosystem functioning. The results indicated that the overall functional gene richness/diversity decreased as uranium increased in groundwater, while specific key microbial guilds increased significantly as uranium or nitrate increased. These key microbial functional genes could be used to successfully predict environmental contamination and ecosystem functioning. This study represents a significant advance in using functional gene markers to predict the spatial distribution of environmental contaminants and ecosystem functioning toward predictive microbial ecology, which is an ultimate goal of microbial ecology.
Learn more about the article: http://mbio.asm.org/content/9/1/e02435-17.short.
Learn more about the journal: http://mbio.asm.org/.
Learn more about Andrea at: https://www.linkedin.com/in/andrea-m-rocha-ph-d-20a81017/