Microbial Functional Gene Diversity Predicts Groundwater Contamination and Ecosystem Functioning.

Zhili He,Matthew W Fields,Qingyun Yan,Eric J Alm,Bo Wu,Daliang Ning,Andrea M Rocha,Adam P Arkin,Yunfeng Yang,Dwayne A Elias,Joy D Van Nostrand,Qichao Tu,Jianjun Wang,Paul D Adams,Linwei Wu,Yujia Qin,Zhou Shi,Terry C Hazen,David B Watson,Jizhong Zhou,Ping Zhang,Michael W W Adams,Daniel B Curtis

doi:10.1128/mbio.02435-17

Abstract

ABSTRACTContamination 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.

Highlights

Background wellsbContaminated wellsc NitrateAll N cycling genes All nifH, amoA, narG, nasA, and napA genes All nifH genes All amoA genes All narG genes All nasA genes All napA genes Key nifH, amoA, narG, nasA, and napA genes Key nifH genes Key amoA genes Key narG genes Key nasA genes Key napA genes accuracy for random forest (AUC-RF) selection aKey functional genes detected from each family are listed in Tables S3 and S4 in the supplemental material. bIn background wells, the concentrations of uranium or nitrate were 30 ␮g/liter or below or 10 mg/liter or below, respectively. cIn contaminated wells, the concentrations of uranium or nitrate were higher than 30 ␮g/liter or 10 mg/liter, respectively.gi257458839, and gi157913465) increased significantly (P Ͻ 0.05) as nitrate increased (Fig. 3D)
Our results indicate that the overall functional diversity (FD) decreased as uranium concentrations increased or at low or high pH; some specific functional genes/populations were stimulated in response to uranium and nitrate contamination
Our results showed that the overall functional diversity/richness of groundwater microbiomes decreased as uranium concentrations increased or at low or high pHs

Summary

Introduction

Background wellsbContaminated wellsc NitrateAll N cycling genes All nifH, amoA, narG, nasA, and napA genes All nifH genes All amoA genes All narG genes All nasA genes All napA genes Key nifH, amoA, narG, nasA, and napA genes Key nifH genes Key amoA genes Key narG genes Key nasA genes Key napA genes AUC-RF selection aKey functional genes detected from each family are listed in Tables S3 and S4 in the supplemental material. bIn background wells, the concentrations of uranium or nitrate were 30 ␮g/liter or below or 10 mg/liter or below, respectively. cIn contaminated wells, the concentrations of uranium or nitrate were higher than 30 ␮g/liter or 10 mg/liter, respectively.gi257458839, and gi157913465) increased significantly (P Ͻ 0.05) as nitrate increased (Fig. 3D). To further improve our prediction, we used the area under the receiver operating characteristic curve as the predictive accuracy for random forest (AUC-RF) [31] to automatically select 50 predictors (Table S5) from the initial 2,361 functional probes related to uranium reduction, which dramatically decreased the OOB estimate of error rate, from 28.99% to 11.59% (Table 1). These results indicated that mbio.asm.org 7 microbial functional genes were able to successfully predict groundwater uranium contamination

Methods

Results

Discussion

Conclusion