Introduction

Fluoride is a toxic element that can cause fluorosis to organisms1,2 whether excessive or deficient. Recently, it has also been identified as a fundamental factor impacting microbial activity and communities in environment3,4 due to its potential antimicrobial activity5,6. One piece of evidence for the antimicrobial activity is the anticaries actions of fluoride by affecting bacterial metabolism7. It was found that ureolysis by urease-positive bacteria (Staphylococcus epidermidis, Streptococcus salivarius and Actinomyces naeslundii) was inhibited by fluoride in suspensions or mono-organism biofilms at plaque levels of 0.1–0.5 mm in a pH-dependent manner8. Fluoride, in the form of a complex such as SnF2, has shown a significant effect against oral micro-organisms in vivo and in vitro9,10,11.

Additionally, numerous studies have reported on the ability of fluoride, normally as sodium fluoride, to cause changes to microbial activity and community composition in soil4,12. Fluoride-induced changes of chemical properties and microbial activities in humus soils were reported by Wilke13; it was shown that dehydrogenase, alkaline phosphatase and arylsulfatase activities as well as nitrification were inhibited at much lower F-additions in the moder and mor soils. The inhibition of fluoride on the activity of soil peroxidase and ATPase was further confirmed by Reddy and Kaur14 and Yadu et al.15. The negative impact of fluoride on soil microorganisms was quantified by Rao and Pal16, who reported that elevated fluoride concentrations (380–1803 mg/g soil) were found to inhibit microbial growth and activity and decomposition of organic matter. Lately, inhibition of soil respiration and dehydrogenase activity was observed when fluoride concentrations in soils were below 200 mg/g, whereas fluoride concentrations of 200–2000 mg/g inhibit denitrification in soils17. Currently, the information about minimum fluoride concentrations in soils, affecting the activity of soil microorganism, is inconclusive. However, the presence of fluoride, especially in amounts significantly exceeding its natural concentrations in soil, inhibits microbial growth and the decomposition of organic matter18,19,20.

Based on the previous studies, the antimicrobial activity of fluoride is mediated via three major effects of fluoride: (i) enzyme inhibition. The direct inhibition of the F-ATPase enzyme by fluoride was found to be dependent on cations21,22, and fluoride is a potent inhibitor of enolase, catalase, phosphatases and other enzymes of many organisms23,24,25; (ii) fluoride was found to alter the proton movement through cell membranes and inhibit intracellular acid production26,27; (iii) fluoride can inhibit certain microbes in the ingestion, transformation and utilization of certain nutrients, affecting the synthesis of extracellular polysaccharides and the storage of intracellular polysaccharides28,29,30.

As a toxic element, fluoride influences the metabolic behavior of microbes in natural environment. According to Mendes et al., during the dissolution of rock phosphate by Aspergillus niger, fluoride was capable of decreasing fungal growth, citric acid production, and acidification31. In an indoor culture, Bradshaw et al. found that a continuous supply of 1 mM NaF reduced the viable counts of microflora in solution at pH 732. It was reported that the per liter concentration of fluoride ranges from several micrograms to dozens of milligrams to even one thousand milligrams in groundwater33,34,35,36. While groundwater systems (groundwater-sediment) contain large numbers of microorganisms37,38. However, how microbial communities in groundwater respond to different fluoride levels is not yet well understood. We hypothesize that fluoride influences microbial community diversity and structure by its toxic effects on microbes with various [F] in groundwater.

A typical area with endemic fluorosis, Qiji County of Yuncheng City, China39,40,41,42, was chosen as a model system in which to test our hypothesis. According to Li et al., the fluoride concentration ranges from approximately 1.4 mg/L to 14.2 mg/L in Qiji County41, exceeding the World Health Organization (WHO) limit of 1.5 mg/L in drinking water43. And over 50% were meeting or exceeding the levels of fluoride that were reported to be needed to kill bacteria, approximating 0.16 to 0.30 mmol/L (3.04 to 5.70 mg/L)44. To obtain samples with various fluoride concentrations, shallow groundwater samples were collected from thirteen different wells for a coupled study of both fluoride and microbial community. The aim of this study is (i) to investigate the microbial community in groundwater of the area; (ii) to discern which environmental parameters significantly influence the microbial community at the phylum, family and OTU levels; and (iii) to discuss the potential effects of F/[F] on the groundwater microbial community.

Materials and Methods

Site description

Qiji County is located in the southwestern part of Yuncheng City, Shanxi Province, China45 and covers an area of 77 km2 (between 34°40′ and 35°02′N and 110°29′ and 110°30′E). The region has a semi-arid climate with most of the rainfall (>65%) occurring between June and October. The Quaternary sediment is composed of primarily aeolian loess, lacustrine clays, fluvial sands and gravels in the area. The major shallow aquifer consists of an admixture of fine, to medium grained and coarse sands with depth between 35 to 65 meters in the area. The regional shallow groundwater flows from the northwest to the southeast, toward the salt lake39,41. Historically, approximately 50% of the people living in the area have been affected by fluorosis in the past several decades. Long-term intake of high-fluoride ground water is the major reason for endemic fluorosis in Yuncheng Basin39,46,47 and other sites in the world2. The Yuncheng basin has a semi-arid climate with a strong evaporation. Groundwater is the major source of water drinking causing the lack of surface water. The fluoride rich groundwater normally located in the low land areas in the basin. The chemistry of the groundwater with high fluoride concentration is characterized as: Na-rich and Ca-poor, with high pH and HCO3− values and low TDS values39,41,45,48. The dissolution of fluorine-bearing minerals, cation exchange and evaporation were main factors that control the occurrence of high fluoride shallow groundwater.

Sample collection and geochemical analysis

A total of thirteen water samples were collected in August, 2014, from the power - operated wells around the borehole located in Qiji area, Yuncheng City, Shanxi Province (Table 1). When sampling, water samples were collected only after the in situ physicochemical parameter, including pH, redox potential (Eh), dissolved O2 (DO), temperature (T), and electrical conductivity (EC), were stable. These four parameters had been measured using portable HACH EC, DO and pH meters. Subsamples for chemical analysis were filtered through 0.45-μm filters and collected in three acid-washed, high-density polyethylene (HDPE) bottles that had been rinsed with the sample water thoroughly (at least three times before sampling). Alkalinity measurements were performed by pH-verified colorimetric titration. The microbial samples were collected by filtration of 5–10 L of water through 0.22-μm filters, and the biomass-containing filters were wrapped and immediately stored at −80 °C for the analysis of biodiversity. The other hydrogeochemical analyses were performed at the State Key Laboratory of Biological and Environmental Geology, China University of Geosciences (Wuhan). The concentrations of Cl−, SO42−, NO3−, and F− were determined using ion chromatography (IC) (Dionex 120, Dionex, Sunnyvale, CA, USA). Samples for cation analysis were acidified with trace metal grade HNO3 to pH less than 2.0. Major cations (K+, Na+, Ca2+ and Mg2+) were measured using inductively coupled plasma-atomic emission spectroscopy (ICP-AES) (IRIS Intrepid II XSP, Thermo Elemental, Madison, WI, USA). The instrumental detection limit was 0.06 ppm. The standards used for the ICP-AES calibration were within 5% of external standards. Samples for total organic carbon (TOC), total nitrogen (TN) and total phosphorus (TP) analysis were acidified with H2SO4. Sub-samples for TOC were analyzed with a TOC analyzer (Analytik Jena, Multi N/C, 3100); samples for TN and TP were analyzed with ultraviolet spectrophotometer (HITACHI U-1900).

Table 1 Geochemical parameters of groundwater samples (n = 13) with variable fluoride concentration in Yuncheng Basin.
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DNA extraction, PCR amplification, and sequence analysis

Total genomic DNA was extracted from the filtered groundwater samples (0.22 μm, millipore) at the sampling site. DNA extractions were conducted using the PowerWater®DNA Isolation kit (Anbiosci Tech LTD, 14900–50-NF) according to the manufacturer’s manual. DNA yield was quantified with Nanodrop (Thermo Scientific NanoDrop 2000) and then stored at −80 °C until PCR amplification. PCR amplifications were performed with the 515f/806r primer sets (The reverse primer contains a 6-bp error-correcting barcode to distinguish sequences that originated from different samples) that amplifies the V4 region of the 16S rDNA gene, following the protocol described previously49. Sequencing was conducted with 200 ng of amplified product on an Illumina MiSeq platform at Novogene (Beijing, China).

Sequence analysis was performed with the UPARSE software package using the UPARSE-OTU and UPARSE-OTUref algorithms50. Sequences were further denoised using conduct filter analysis by applying the microbial community analysis software QIIME51. High-quality sequences were obtained and compared with the data library (Gold database, http://drive5.com/uchime/uchime_download.html), and the chimera sequences were measured and removed52 (UCHIME Algorithm, http://www.drive5.com/usearch/manual/uchime_algo.html). This output was clustered using Uparse53 software at the 97% sequence identity level, resulting in 6383 operational taxonomic units (OTUs). A representative sequence from each OTU was classified using the Ribosomal Database Project (RDP) classifier54 (Version 2.2, http://sourceforge.net/projects/rdp-classifier/) and GreenGene data set55 http://greengenes.lbl.gov/cgi-bin/nph-index.cgi). The OTUs table was formatted to allow comparisons using β diversity metrics.

Statistical analysis

Statistical analyses were performed in QIIME and using package “vegan” in R, version 3.2.4 (https://www.r-project.org/)56,57. Rarefaction curves, species richness estimators and community diversity indices were calculated in QIIME. The Chao1 richness index, Shannon diversity index and coverage rate were calculated to reflect the alpha-diversity of samples41.

A heat map of abundance data at the class level was constructed. Two kinds of analyses were performed to investigate the relationships between the microbial community (at the OTUs level) and the geochemical parameters: (1) Mantel tests were used to examine the relationship between the bacterial community structure and the geochemical parameters58. The significance of each environmental factor was tested by analysis of variance with 999 permutations. Mantel tests were performed with both weighted Uni Frac and Bray Curtis distance matrices for the microbial community data and distance matrices (Euclidian distance) for each environment factor. (2) Redundancy analysis (RDA) with forward selection to identify the factors that could best explain the variation in the microbial community56 and significance was tested by a Monte Carlo permutation test based on 999 random permutations. Some additional correlation analyses were performed using SPASS software.

Results

Groundwater geochemistry

The groundwater was slightly alkaline (7.69–8.50) and fresh to slightly saline (Table 1). Fluoride concentration in groundwater varied from 3.05 to 8.89 mg/L, which was within the range reported by others41 from the area. The TOC values ranged from 0.12 mg/L to 4.38 mg/L. Na+ was the most dominant cation, with concentrations of 244.5~908.1 mg/L, followed by Mg2+, Ca2+ and K+. Bicarbonate and sulfate were major anions, with concentrations of 548.0~1128 mg/L and 27.26~757.4 mg/L, respectively. This results were resistant with that Na-rich, Ca-poor and high bicarbonate concentration were the mainly characteristic of groundwater in the basin41,45. The correlation analysis (Supplementary Table 1) showed that the fluoride is significantly correlated with pH (R = 0.678, P < 0.05), TP (R = 0.730, P < 0.01) and Ca2+ (R = −0.720, P < 0.01). Under high pH alkaline conditions, OH- could exchange with F− adsorbed on minerals and soil59,60 and prevent F− from complexing with cations, which results in a high release of F− in groundwater. The positive correlation between fluoride and TP may partly due to the contamination of the phosphatic fertilizer and the competitive adsorption by PO43− which could cause the desorption of fluoride from mineral/organic matter surfaces within the groundwater system61. Meanwhile, the negative correlation between [F] and [Ca] is attributed to the dissolution/precipitation equilibrium of major fluoride bearing minerals, especially fluorite (CaF2)45. It is suggested that the concentration of fluoride in groundwater is under the control of natural water-sediments rock interactions (e.g., cation exchange, competitive adsorption, dissolution/precipitation) in natural groundwater systems62.

Alpha diversity of bacterial community

A total of 329889 valid reads (average read length, 253 bp) were identified from thirteen Illumina sequencing libraries after filtering out the low-quality reads and chimeras and trimming the adapters, as well as bar codes and primers. The values of the Chao1 index ranged from 1569 to 2699 while the values of Shannon diversity index ranged from 5.76 to 8.59 (Supplementary Table 2). Obvious change in groundwater community diversity was apparent across the fluoride concentration gradient (Fig. 1). The microorganism communities in samples with high fluoride concentration were substantially simpler than those in samples with medium fluoride concentration. Besides, [Ca], [NO3] and [TN] had significant positive relationship with Chao 1 (Supplementary Table 3). Significant negative correlations were observed between fluoride concentration with Chao1 (R = −0.705, P = 0.007, Fig. 1) and Shannon (R = −0.563, P = 0.010, Fig. 1), which may be interpreted by the inhibitive ability of fluoride toward micro-organisms in groundwater in the area.

Figure 1
figure 1

The Chao1 and Shannon index along a fluoride concentration gradient.

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Bacterial community composition

The most abundant prokaryotic organisms in groundwater samples belonged phylogenetically to the Proteobacteria phylum, accounting for 55.41% (in QJ04) to 84.58% (in QJ13) of the total valid reads in all libraries (Fig. 2a, Supplementary Fig. 1). The second most abundant prokaryotic organisms were Bacteroidetes (1.86% to 37.95% of the total valid reads), followed by Cyanobacteria (0.11% to 8.32%). Crenarchaeota, Nitrospirae, Firmicutes, Acidobacteria, Actinobacteria. Planctomycetes and OP3 were found to be the minor phyla. The microbial community, at the phylum level, was similar among groundwater samples (QJ07, QJ10, QJ08, QJ11 and QJ13) with a medium fluoride concentration (3.05–4.88 mg/L). Significant differences in bacterial community were observed among the rest of samples with a higher fluoride concentration (5.12–8.89 mg/L). Frequently, fluoride-related changes in the relative abundances of bacterial phyla were observed. For example, Proteobacteria occurred at lower abundances in the libraries from groundwater samples with higher fluoride concentration than that from samples with a medium F concentration (Supplementary Fig. 2). While the abundance of Proteobacteria was positively related with EC, TOC and major ions (Fig. 2b).

Figure 2
figure 2

Microbial community composition at phylum level in the study area. (a) Taxonomic classification of bacterial reads retrieved from different groundwater samples at the phylum level using the RDP classifier. “others” indicates phyla with relative abundances of less than 1.0%; (b) Heat map of correlation between the ten most abundant bacterial phyla and hydrochemical factors. Significance codes: 0 < p < 0.001 “***”, 0.001 < p < 0.01 “**”, 0.01 < p < 0.05 “*”, 0.05 < p < 0.1 “•”.

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The correlation analysis conducted with heat maps involved a clustering analysis based on the distribution of the predominant families, and deeper colors represent higher richness (Fig. 3). The column cluster illustrated that most of the samples with higher fluoride concentrations (QJ02, QJ04, QJ06) and one sample with medium fluoride concentration (QJ01) were clustered together (Cluster B). Bacterial communities under lower fluoride concentration (QJ07, QJ08, QJ10, QJ11, QJ05, QJ09, QJ12 and QJ13) conditions were clustered into another group (Cluster A). The dominant family was grouped into three groups. Samples in the Cluster B, with a higher fluoride concentration, have a lower relative abundance of families (soft color) in group one and part of the families in group three (from Desulfovibrionaceae to Alcanivoracaceae at the top of the heat map). In contrast, the samples in Cluster A, with a medium fluoride concentration, have a higher relative abundance of families (deep color) in group one and part in group three. Lower relative abundances of the families Xanthomonadaceae, Caulobacteraceae, Chthonomonadaceae, Nocardiaceae, Microbacteriaceae, Bacteriovoracaceae, Rhodasprilliaceae, Hyphmicrobiaceae, Legionellaceae, Rhizobiaceae, Bdellovibrinaceae and Sphingomonadaceae were observed in the high fluoride groundwater, while higher relative abundances of these families were observed in groundwater with medium fluoride concentrations. Obviously, the richness of the predominant families shows a significant diversity in groundwater with different fluoride concentration levels.

Figure 3
figure 3

Heat map of log relative abundances of the distribution of dominant family in the three samples. The double hierarchical dendrogram shows the microbial distribution of the 13 samples. The log relative abundance for the microbial families are depicted by the color intensity; the color key is at the topright. The microbial families with * at their right are related with fluoride concentration analyzed through SPASS software, denoted **(p < 0.01) and *(p < 0.05).

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Figure 4 shows the relative abundances of bacterial families across the fluoride concentration. The relative abundances of Pseudomonadaceae and Caulobacteraceae were negatively correlated with fluoride concentration at significant level (p < 0.01). The relative abundances of Xanthomonadaceae, Methylophilaceae, Legionellaceae and Chthonomonadaceae were also negatively correlated (p < 0.05) with fluoride concentration. Additionally, the relative abundances of these families, excepting Methylophilaceae and Legionellaceae, did not show any significant correlations with any other parameters (Supplementary Table 4). Therefore, it is cautiously inferred that the decrease of the relative abundance of these families may be attributed to the increase of fluoride concentration in groundwater. It was also shown that the relative abundances of Campylobacteraceae, Methylobacteriaceae, Porphyromonadaceae, Catabacteriaceae and two uncultured lineages designated FW and VC21-Bac22 were positively correlated (p < 0.05) with fluoride concentration. This implied that some of the families are resistant to a certain higher concentration of fluoride in groundwater.

Figure 4
figure 4

The relative abundance of microbial family along fluoride gradients. Correlation analyses and significance test for species at family level were conducted using SPASS software.

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Relationships of bacterial community and hydrogeochemical parameters

The differences in microbial community structure could be influenced by hydrogeochemical parameters. For RDA analysis, we employed forward selection by performing a Mantel test with the number of permutations being 999. Then, we drew the bacterial diversity diagram at OTU level with five selected geochemical parameters (pH, Ca2+, F−, TOC and TP) that best explained the variance of the bacterial communities in the thirteen groundwater samples (Fig. 5). The variance inflation factors of these five parameters were all less than 20.

Figure 5
figure 5

RDA biplot of bacterial community composition and the five most significant geochemical parameters. Each dot represents one sample. Arrows indicate the direction and magnitude of geochemical parameters associated with bacterial community structures. Total variance is 0.027, and eigenvalues for constrained axes, RDA1 and RDA2, are 0.0036 and 0.0030, respectively. The significant vectors in the figure were highlighted to avoid misunderstanding. Significance codes: 0 < p < 0.001 “***”, 0.001 < p < 0.01 “**”, 0.01 < p < 0.05 “*”, 0.05 < p < 0.1 “•”.

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The first axis of the RDA explained 13.32% of the variance of bacterial community and was positively correlated with the samples at a medium fluoride concentration except QJ12 and negatively correlated with the samples with a higher fluoride concentration. Interestingly, the samples (except QJ12) with a medium fluoride concentration grouped together in the RDA profile. These five hydrogeochemical parameters explained 36.6% of the total variance. TOC and fluoride concentration explained the variability of bacterial community at the significance level (r2 = 0.45, p = 0.045 vs. r2 = 0.59, p = 0.007, Supplementary Table 5). While the effects from pH could be present but only at the marginal significance level (r2 = 0.40, p = 0.067). Ca2+ and TP were insignificant factors.

Discussion

Knowledge of microbial communities in relation to hydrogeochemical and environmental conditions is important for understanding biogeochemical processes and the mobilization of pollutants (solutes) in groundwater systems63. Microbial community diversity and structure are affected by many environmental factors, such as pH, and the concentrations of various elements, electron donors and acceptors in soils and groundwater systems64,65. It has been reported that fluoride led to a decrease in microbial biomass in a water treatment system20 and inhibited the activity of soil dehydrogenase, arylsulfatase, alkaline phosphatase, acid phosphatase, peroxidase and ATPase13,14,15; it is likely that fluoride had a negative impact on the function of the microbial community. Therefore, we speculated that F may alter the microbial community in groundwater. In this case study, the Chao1 index and Shannon diversity were significantly and negatively correlated with fluoride concentration in the study wells. This indicated that fluoride may have a strong effect on the diversity of bacterial communities in this study.

As a toxic element, fluoride can inhibit or kill microbes by affecting bacterial metabolism through a set of actions with fundamentally different mechanisms21,26,27,29. For example, Al-F or Mg-F, the major metal-fluoride complexes present in high fluoride groundwater, were responsible for fluoride inhibition of phosphate transfer enzymes under laboratory conditions66. This suggests that fluoride, in the form of metal-fluoride complexes, is a possible enzyme inhibitor in groundwater. Previous studies have shown that most of the fluoride movement across the cell membranes of bacteria would be of the HF form, even at pH 77. In groundwater, an increase of fluoride concentration possibly cause more fluoride to move across the cell membrane in the form of HF. Accumulation of fluoride in bacteria is largely dependent on its binding to various cell structures, mainly proteins. In the cytoplasm, the dissociation of HF yields F− and H+, which can act as a metabolic inhibitor and reduce the acid tolerance of the bacteria67. Indeed, our data were also in agreement with this mechanism of F action as the relative abundance of Proteobacteria decrease in the high fluoride sample, suggesting the presence of a toxic effect from F.

Bulk geochemical parameters, such as pH, fluoride, major ions, TOC and TP have been shown to explain variance in microbial communities in groundwater. The variance in the microbial community in our study, however, was best explained by TOC and fluoride. Numerous studies have shown that microbial community can be strongly correlated with TOC52,68,69. Our study and others are in agreement with the fact that carbon, either organic carbon or inorganic carbon, is a necessary nutrient element for microorganisms and is one of the fundamental factors that structures microbial communities by controlling the growth and distribution of microorganism.

The RDA also indicated that fluoride was the most significant factor influencing the bacterial community in groundwater at the OTU level. In this case study, distinct bacterial communities could be formed between individual wells due to the differences of fluoride concentrations. First, frequent fluoride-related changes in the relative abundance of Proteobacteria were observed in the study wells. In addition, at the family level, fluoride concentration was significantly positively or negatively correlated with the relative abundances of twelve families in groundwater. It was reported that some prokaryotes (bacteria and actinomycetes) were resistant to the high concentrations of F compounds70. Genus Pseudomonas, Bacillus sp., Acinetobacter sp. and Streptococcus sp. were reported to be resistant to fluoride by an ancient system composed by fluoride-specific riboswitches and commonly associated proteins such as CrcB71,72,73,74. Besides, Methylobacterium extorquens DM4, encoding at least 10 fluoride riboswitches in its genome, might consume fluorinated hydrocarbons a food source with a robust fluoride sensor and toxicity mitigation response system71. This may partly explain why some families were in positive correlation with fluoride concentration. In groundwater ecosystem, microbes are motile (by itself or flow) and faced dynamic biogeochemical conditions which were possibly challengeable75. Stochastic processes frequently influences the assembly of microbial communities, while the selective pressures might drive changes in microbial community composition via deterministic effects76,77. Often selective pressures are inferred based on correlations between the relative abundances of microbial taxa and geochemical parameters (e.g., toxic stressors or nutrients), although correlative analysis does not identify causal relationships, and observed correlations can be misleading. Thus, our results indicated that fluoride might be critical factor which can shape bacterial communities in groundwater.

Conclusion

Our study revealed a significant association between fluoride concentration and the composition of bacterial communities in shallow groundwater in the Qiji area, northern China. TOC and fluoride concentration plays an important role in modulating the groundwater bacterial communities. These findings give us new insights into the biogeochemical processes of fluoride and other elements in groundwater, suggesting that fluoride concentration should be considered in future when evaluating microbial response to environmental conditions in groundwater system, especially for fluoride rich groundwater.