Microbial Functional Gene Diversity Predicts Groundwater Contamination and Ecosystem Functioning

• Main Authors: Zhili He, Ping Zhang, Linwei Wu, Andrea M. Rocha, Qichao Tu, Zhou Shi, 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, Jizhong Zhou, Jennifer Martiny
• Format: Article
• Language: English
• Published: American Society for Microbiology 2018-02-01
• Series: mBio
• Online Access: http://mbio.asm.org/cgi/content/full/9/1/e02435-17

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.