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Title: Microbial Functional Gene Diversity Predicts Groundwater Contamination and Ecosystem Functioning

Abstract

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. Here, this study indicates great potential for using microbial functional genes to predict environmental contamination and ecosystem functioning.

Authors:
 [1];  [2];  [3];  [4]; ORCiD logo [2];  [2];  [1];  [2];  [2];  [1];  [2];  [2];  [2];  [2]; ORCiD logo [5]; ORCiD logo [6]; ORCiD logo [6];  [7]; ORCiD logo [8];  [9] more »; ORCiD logo [4];  [10];  [10];  [11];  [12] « less
  1. Sun Yat-Sen Univ., Guangzhou (China); Univ. of Oklahoma, Norman, OK (United States)
  2. Univ. of Oklahoma, Norman, OK (United States)
  3. Univ. of Oklahoma, Norman, OK (United States); Tsinghua Univ., Beijing (China)
  4. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Univ. of Tennessee, Knoxville, TN (United States)
  5. Tsinghua Univ., Beijing (China)
  6. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
  7. Univ. of Georgia, Athens, GA (United States)
  8. Montana State Univ., Bozeman, MT (United States)
  9. Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)
  10. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Univ. of California, Berkeley, CA (United States)
  11. Univ. of Oklahoma, Norman, OK (United States); Tsinghua Univ., Beijing (China); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
  12. Univ. of California, Irvine, CA (United States)
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
OSTI Identifier:
1422377
Alternate Identifier(s):
OSTI ID: 1466711
Grant/Contract Number:  
AC05-00OR22725; AC02-05CH11231
Resource Type:
Accepted Manuscript
Journal Name:
mBio (Online)
Additional Journal Information:
Journal Name: mBio (Online); Journal Volume: 9; Journal Issue: 1; Journal ID: ISSN 2150-7511
Publisher:
American Society for Microbiology
Country of Publication:
United States
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES; 54 ENVIRONMENTAL SCIENCES; groundwater microbiome; random forest; ecosystem functioning; environmental contamination; metagenomics; microbial functional gene

Citation Formats

He, Zhili, Zhang, Ping, Wu, Linwei, Rocha, Andrea M., Tu, Qichao, Shi, Zhou, Wu, Bo, Qin, Yujia, Wang, Jianjun, Yan, Qingyun, Curtis, Daniel, Ning, Daliang, Van Nostrand, Joy D., Wu, Liyou, Yang, Yunfeng, Elias, Dwayne A., Watson, David B., Adams, Michael W. W., Fields, Matthew W., Alm, Eric J., Hazen, Terry C., Adams, Paul D., Arkin, Adam P., Zhou, Jizhong, and Martiny, Jennifer. Microbial Functional Gene Diversity Predicts Groundwater Contamination and Ecosystem Functioning. United States: N. p., 2018. Web. doi:10.1128/mBio.02435-17.
He, Zhili, Zhang, Ping, Wu, Linwei, Rocha, Andrea M., Tu, Qichao, Shi, Zhou, Wu, Bo, Qin, Yujia, Wang, Jianjun, Yan, Qingyun, Curtis, Daniel, Ning, Daliang, Van Nostrand, Joy D., Wu, Liyou, Yang, Yunfeng, Elias, Dwayne A., Watson, David B., Adams, Michael W. W., Fields, Matthew W., Alm, Eric J., Hazen, Terry C., Adams, Paul D., Arkin, Adam P., Zhou, Jizhong, & Martiny, Jennifer. Microbial Functional Gene Diversity Predicts Groundwater Contamination and Ecosystem Functioning. United States. doi:10.1128/mBio.02435-17.
He, Zhili, Zhang, Ping, Wu, Linwei, Rocha, Andrea M., Tu, Qichao, Shi, Zhou, Wu, Bo, Qin, Yujia, Wang, Jianjun, Yan, Qingyun, Curtis, Daniel, Ning, Daliang, Van Nostrand, Joy D., Wu, Liyou, Yang, Yunfeng, Elias, Dwayne A., Watson, David B., Adams, Michael W. W., Fields, Matthew W., Alm, Eric J., Hazen, Terry C., Adams, Paul D., Arkin, Adam P., Zhou, Jizhong, and Martiny, Jennifer. Tue . "Microbial Functional Gene Diversity Predicts Groundwater Contamination and Ecosystem Functioning". United States. doi:10.1128/mBio.02435-17. https://www.osti.gov/servlets/purl/1422377.
@article{osti_1422377,
title = {Microbial Functional Gene Diversity Predicts Groundwater Contamination and Ecosystem Functioning},
author = {He, Zhili and Zhang, Ping and Wu, Linwei and Rocha, Andrea M. and Tu, Qichao and Shi, Zhou and Wu, Bo and Qin, Yujia and Wang, Jianjun and Yan, Qingyun and Curtis, Daniel and Ning, Daliang and Van Nostrand, Joy D. and Wu, Liyou and Yang, Yunfeng and Elias, Dwayne A. and Watson, David B. and Adams, Michael W. W. and Fields, Matthew W. and Alm, Eric J. and Hazen, Terry C. and Adams, Paul D. and Arkin, Adam P. and Zhou, Jizhong and Martiny, Jennifer},
abstractNote = {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. Here, this study indicates great potential for using microbial functional genes to predict environmental contamination and ecosystem functioning.},
doi = {10.1128/mBio.02435-17},
journal = {mBio (Online)},
number = 1,
volume = 9,
place = {United States},
year = {2018},
month = {2}
}

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Works referenced in this record:

Random Forests
journal, January 2001