Anaerobic microecosystems designed with different concentrations of 17β-estradiol (17β-E2) (0.0–10,000.0 ng/L) were simulated in this study. The influence of different concentrations of 17β-E2 on the emissions of typical greenhouse gases (CH4 and CO2) in simulated anaerobic microecosystems is analyzed to primarily explore the relationship between 17β-E2 and such emissions in aquatic anaerobic ecosystems. The results showed that 17β-E2 could promote or significantly stimulate aquatic anaerobic micro-organisms' production of CH4. The degree and the promotion time of CH4 production were both enhanced with the increase of 17β-E2 concentration. Furthermore, under higher concentration of 17β-E2 (≥500.0 ng/L), the increasing tendency of aquatic anaerobic microbial populations' activity and the function of methanogenic activity under corresponding experimental conditions had a synchronous relationship.

INTRODUCTION

17β-estradiol (17β-E2), which is widely spread in nature, is one of the most powerful naturally occurring environmental estrogens (EEs). Owing to the strong endogenous hormone activity, 17β-E2 has negative effects on maintaining the balance of estrogens in humans and other animals. Such effects are achieved by stimulating, disturbing or confronting the hormone's normal function of synthesis, transport, release and other abilities (Kavlock et al. 1996). 17β-E2 is more than 100 times as potent as estrone (E1) in its binding effects, which means that the pollutants would seriously threaten the organism and its environment (Soto et al. 1995; Urase & Kikuta 2005; Sumpter et al. 2006; Hintemann et al. 2006). Its environmental behavior and toxicological effects have become an international ‘hot topic’ in these related areas of study.

The existing studies show that 17β-E2 is widely distributed in sewage, sewage sludge and animal wastes. By direct emissions, runoffs, infiltrations and so forth, it could enter the soil, surface water, ground water and other surroundings (Tabata et al. 2001; Tilton et al. 2002; Kjær et al. 2007; Chiu et al. 2009). 17β-E2 concentrations from 0.2 to 14.7 ng/L have been detected in effluents of 18 Canadian wastewater treatment plants by Servos et al. (2005). Finlay-Moore et al. (2000) measured an increased concentration of 17β-E2 of up to 675 ng/kg in fields fertilized with poultry litter; meanwhile, the nearby water surface showed a 17β-E2 concentration as high as 2,530 ng/L. A similar study performed by Peterson et al. (2000) identified the underground water concentration of 17β-E2 ranged from 6 to 66 ng/L near poultry-litter fertilized fields. Schuh et al. (2011), by simulating different concentrations in the laboratory, reported that soil may act as a long-term reservoir for 17β-E2 in the environment.

As one of the important environmental pollutants, 17β-E2 has negative effects on the safety of human health and ecosystems. According to other reports, the increasing number of patients with testicular, breast and prostate cancers may be related to long-term estrogen exposure (Epstein 1997). As such, in 1994, 17β-E2 was listed as a possible carcinogen by the United States Department of Health and Human Services (1994). Other studies showed that EE (especially 17β-E2) pollutants could also affect the phenomena of monoecism, dioecism proportion and fertility declination. Such examples are the rainbow trout whose endocrine system becomes adversely affected when exposed to 1.0 ng/L 17β-E2 (Routledge et al. 1998) and the paired medaka which, when exposed to 463 ng/L of 17β-E2, registers a significantly smaller number of eggs produced and fertilized (Kang et al. 2002).

It is noteworthy that 17β-E2 plays a regular effect on aquatic anaerobic micro-organisms. Study shows that in low concentration (1.0‒10.0 ng/L), 17β-E2 plays an inhibiting role in methanogenic and microbial activity under anaerobic conditions (Ruan et al. 2013). Under aerobic conditions, 17β-E2 could inhibit microbial methane oxidation but improve aquatic microbial community activity (Ruan et al. 2014). However, in recent years, not only has the range of 17β-E2 pollution gradually expanded, but also the pollution concentration in different waters has increased. It is necessary to further explore how a wide range of concentrations of 17β-E2 influences the methane production from aquatic anaerobic micro-organisms.

To analyze the influence of different concentrations of 17β-E2 on the emissions of typical greenhouse gases (CH4 and CO2) and to explore the relationship between 17β-E2 and greenhouse gas (GHG) emissions in aquatic anaerobic ecosystems, we simulated microecosystems in the laboratory, laying a foundation for further research on the microbiological mechanisms of methane emissions from water affected by 17β-E2 pollution.

MATERIALS AND METHODS

Construction of simulated anaerobic microecosystems

Sediment and water samples were collected from the Nanjing section of the Yangtze River. The physical and chemical properties of the sediment samples were determined using standard protocols (Lu 2000). Water samples were determined by an advanced water quality monitoring platform (EXO 2, YSI). Concentration of 17β-E2 was determined using a standard protocol (Fu et al. 2012, 2013) (Table 1).

Table 1

Physical and chemical properties of the sediment and water samples

Sediment samples Water samples 
Item Value Item Value 
pH 7.64 ± 0.12 pH 7.42 ± 0.05 
Moisture content (%) 38.6 ± 2.16 Total dissolved solids (mg/L) 482.2 ± 12.8 
Organic matter (%) 1.61 ± 0.18 Conductivity (μS/cm) 271.4 ± 4.6 
Total nitrogen (%) 0.24 ± 0.03 Chemical oxygen demand (mg/L) 14.7 ± 1.1 
Available P (mg/kg) 64.9 ± 2.3 NH4+-N (mg/L) 0.05 ± 0.01 
Available K (mg/kg) 217.3 ± 3.0 Oxidation–reduction potential (mv) 143.8 ± 2.4 
Available Ca (mg/kg) 54.8 ± 1.7 Turbidity (FNU) 28.41 ± 2.93 
17β-E2 (mg/kg) not detected 17β-E2 (ng/L) not detected 
Sediment samples Water samples 
Item Value Item Value 
pH 7.64 ± 0.12 pH 7.42 ± 0.05 
Moisture content (%) 38.6 ± 2.16 Total dissolved solids (mg/L) 482.2 ± 12.8 
Organic matter (%) 1.61 ± 0.18 Conductivity (μS/cm) 271.4 ± 4.6 
Total nitrogen (%) 0.24 ± 0.03 Chemical oxygen demand (mg/L) 14.7 ± 1.1 
Available P (mg/kg) 64.9 ± 2.3 NH4+-N (mg/L) 0.05 ± 0.01 
Available K (mg/kg) 217.3 ± 3.0 Oxidation–reduction potential (mv) 143.8 ± 2.4 
Available Ca (mg/kg) 54.8 ± 1.7 Turbidity (FNU) 28.41 ± 2.93 
17β-E2 (mg/kg) not detected 17β-E2 (ng/L) not detected 

The sediments were air-dried in a dark and ventilated laboratory, and then ground, sifted and mixed. Fifty grams of powdered sediments, weighed separately, were put into 200 mL serum bottles together with 100 mL of Yangtze River water. The serum bottles were sealed with silica gel plugs after being subjected to N2 (99.999%; Nanjing Special Gas) for 5 minutes each. Using the same method, 24 anaerobic microecosystems were constructed. To study the effect of high concentration of 17β-E2 on GHG emission, 24 anaerobic microecosystems were statically cultured in a thermostatic cultivation box (DK-GJ003; Memmert) at 35 °C for 40 days.

Nutrient solution of 1 mL, composed of 100 g/L yeast extract, 50 g/L fish peptone and 0.1 g/L ammonium acetate, was added to the microecosystems on the 30th day, followed by continued culturing for 10 days. To maintain anaerobic conditions within the systems, 1 mL of gas was extracted from each serum bottle with a syringe every 2 days during the 40 days of this static culture; then 1 mL of H2 (99.90%; Nanjing Special Gas) was injected into them.

Treatment and analyzing program for 17β-E2 pollution

Before the contamination, pressure in the headspace of each of the 24 microecosystems was measured. The concentrations of both CH4 and CO2 in each microecosystem, from which 5 mL was extracted via syringe, were measured by gas chromatography (GC-7890A; Agilent). The chromatograph makes use of a ⅛ inch stainless steel column (HayeSep Q80/100) and CH4 methanizer/flame ionization detector. The GC was operated with N2 (99.999%) carrier gas with 3.0 mL/min air flow, 40 °C column temperature, 100 °C injection temperature, and 300 °C detector temperature. The retention time of CH4 and CO2 was 2.2 minutes and 4.4 minutes, respectively. The detection limit for CH4 and CO2 was 0.2 μL/L and 0.03 μL/L, respectively.

The gas concentrations before the contamination were measured every 24 hours from the 41st day to the 43rd day (representing the measurement time of 48 hours, 24 hours and 0 hours before the contamination, respectively).

After gas concentration measurement on the 43rd day, immediately the 24 microecosystems were divided into eight groups. Each group contained three repeats used as parallel samples. Each microecosystem was injected with different concentration of 17β-E2 (99%; J&K) solutions. The final 17β-E2 concentrations were 0.0 ng/L, 1.0 ng/L, 10.0 ng/L, 50.0 ng/L, 100.0 ng/L, 500.0 ng/L, 1,000.0 ng/L and 10,000.0 ng/L in each group, respectively. Then, these contaminated microecosystems were put back into the thermostatic cultivation box for static culturing at 35 °C. The concentration and pressure of CH4 and CO2 were measured every 24 hours from the 44th to the 48th day.

Statistical analysis

Data sets were analyzed and plotted by using OriginPro 8 and Microsoft Excel 2010 software. The calculation methods for CH4 and CO2 gas production rate and extent of microbial activity have been described by Ruan et al. (2013).

RESULTS AND DISCUSSION

Concentration effect of 17β-E2 on CH4 production of aquatic anaerobic micro-organisms

During the experiment, 17β-E2 promoted or significantly promoted CH4 production from aquatic anaerobic micro-organisms. Moreover, CH4 production rate of aquatic anaerobic micro-organisms significantly increased with the increased concentration of 17β-E2. Furthermore, the impacts of different concentrations of 17β-E2 pollutants on CH4 production rate showed a staged dose promotion effect. For different measurement times – 24, 48, 72 and 96 hours – the CH4 production rate peak varied at different concentrations, respectively 100.0, 500.0 and 10,000.0 ng/L (being the latter in respect to both the 72 and 96 hour measurement) (Figure 1).

Figure 1

Concentration effect of 17β-E2 on CH4 production in anaerobic microecosystems. Compared with the blank control group, by t-test: **, p < 0.01, showed the most significant difference; *, p < 0.05, showed significant difference.

Figure 1

Concentration effect of 17β-E2 on CH4 production in anaerobic microecosystems. Compared with the blank control group, by t-test: **, p < 0.01, showed the most significant difference; *, p < 0.05, showed significant difference.

A comparison between the effects of different concentrations of 17β-E2 on aquatic anaerobic micro-organisms' CH4 production indicated that when the concentration of 17β-E2 ≤ 100.0 ng/L, the average extent of influence on CH4 production activity was less than 100%, assuming therefore that promotion existed. Moreover, for 17β-E2 concentrations equal to or above 500.0 ng/L, the average extent of influence was greater than 350%, which indicates that significant promotion existed (Table 2).

Table 2

Extent of influence of 17β-E2 on aquatic anaerobic micro-organisms CH4 production activity

 Concentration of E2 (ng/L) 
  10 50 100 500 1,000 10,000 
The average extent of influence (%) 24 43 91 351 562 635 
The maximum degree of influence (%) 13 42 81 136 790 2004 2060 
 Concentration of E2 (ng/L) 
  10 50 100 500 1,000 10,000 
The average extent of influence (%) 24 43 91 351 562 635 
The maximum degree of influence (%) 13 42 81 136 790 2004 2060 

Linear regression analysis identifies a linear correlation between CH4 production rate of each experimental group in different time measurements and 17β-E2 concentrations. After 24 hours of 17β-E2 polluting, CH4 production rate and 17β-E2 concentration had a linear correlation in the range of 0.0–100.0 ng/L, r2 = 0.9495. After 48 hours, the range was 0.0–500.0 ng/L, r2 = 0.9935. At the 72 hour measurement, the range was 0.0–1,000.0 ng/L, r2 = 0.9624. Beyond 72 hours of 17β-E2 polluting, no correlation is found through linear regression analysis between 17β-E2 concentration and CH4 production rate. The fact that 17β-E2 gradually degraded in the systems may have been the prime factor for such a finding.

Methanogenesis requires the reduction of the methyl group of methyl coenzyme M to CH4 by the enzyme methyl coenzyme M reductase (MCR) (Pramanik & Kim 2013). Moreover, all known methanogens express MCR, which catalyzes the last step in the methanogenesis (Ferry 1999). Alvarado et al. (2014) reported that the α-subunit of MCR (mcrA) gene transcription and methanogenic activity correlated to the predominant methanogenic community in one of the wetlands studied. Therefore, 17β-E2 may alter the CH4 production by affecting MCR activity.

Under anaerobic conditions, an average half-life of 12 days is needed for 17β-E2 to degrade to E1; nevertheless complete degradation is minimal, thus meaning that different kinds of estrogen would accumulate in anoxic environments (Czajka & Londry 2006). Another study found that after 96 hours of anaerobic biodegradation, 17β-E2 at μg level remained at about 4% of its original concentration, with the production of E1 in the liquid phase in lake sediment (Fang et al. 2008). Therefore, linear regression analysis beyond 72 hours of 17β-E2 polluting showed no correlation between CH4 production rate of each experimental group in different time measurements and 17β-E2 concentrations. Moreover, the degradation of 17β-E2 results in different estrogens, which in turn, will also affect the emissions of CH4.

Time effect of 17β-E2 on CH4 production of aquatic anaerobic micro-organisms

During the experiment phase, CH4 production rate of both the control group and the group of 17β-E2 at 1.0 ng/L gradually decreased with the passing of time. Still, when concentration of 17β-E2 ≥ 10.0 ng/L, a single CH4 production peak rate appeared in each concentration system with the passing of culture time. At the 17β-E2 concentration of 100.0 ng/L, CH4 production rate reached the maximum at the 24 hour mark after exposure, while the whole promotion lasted 48 hours. At a 17β-E2 concentration of 500.0 ng/L, CH4 production rate reached the maximum at 48 hours after exposure, while the whole promotion lasted 72 hours. Both 1,000.0 and 10,000.0 ng/L concentrations of 17β-E2 reached the maximum CH4 production rate 72 hours after exposure, while the whole promotion lasted 96 hours. Thus, it is possible to affirm that both the enhanced degrees and the extended promotion times of CH4 production were accompanied with increased 17β-E2 concentrations (Figure 2).

Figure 2

Time effect of 17β-E2 on CH4 production in anaerobic microecosystems. CH4 production rate of each concentration is the average rate of three parallel samples, and standard deviation is also listed. It represents the detection time, where 0 on the x-axis is the time that 17β-E2 was added.

Figure 2

Time effect of 17β-E2 on CH4 production in anaerobic microecosystems. CH4 production rate of each concentration is the average rate of three parallel samples, and standard deviation is also listed. It represents the detection time, where 0 on the x-axis is the time that 17β-E2 was added.

Generally, compounds can influence the CH4 production from anaerobic systems in two ways. One is to affect the activity of micro-organisms directly during the anaerobic degradation process. The other is to change the structure of the microbial community in the system by stimulating the massive growth of other micro-organisms so that it may affect CH4 output (Stams et al. 2003). Characterization of the microbial community structure and the understanding of the metabolic networks are critical to improve methanogenic efficiency (Shin et al. 2010). From a thermodynamical point of view, the hydrogenotrophic methanogens could not survive if hydrogen partial pressure were too low.

The addition of sulfate could cause the partial pressure of hydrogen to decrease gradually. However, adding sulfuric acid could completely inhibit the activity of hydrogenotrophic methanogens in a certain period of time. From a taxonomic point of view, methanogens belong to Euryarchaeota under the fifth order, third class. Methanosarcina barkeri could exist in a large number in a high concentration of acetic acid, while Methanosaeta seemed to be the genus which contained the maximum number of methanogens that could decompose acetic acid in freshwater sediments. Compared with Methanosarcina barkeri, Methanosaeta had a higher affinity for acetic acid (Stams et al. 2003).

After analyzing the effects of 17β-E2 on CH4 production in anaerobic microecosystems, it is noticeable that the function of CH4 production had been promoted. It can be due to 17β-E2 directly producing effects on one or more stages of anaerobic digestion when it was added into anaerobic microecosystems. Currently, only two types of methanogenic pathways are known: (1) methanogenesis from H2/CO2 or formate; and (2) methanogenesis from acetate and methyl groups containing C1 compounds (Ferry 2011). In general, acetic acid is also a major substrate for methane production (Wang et al. 2009).

The fact that 17β-E2 promotes the growth of acetogenic bacteria, and the increased concentrations of 17β-E2, results in the increase of acetic acid concentrations. However, the changing hydrogen partial pressure of the system, plays a non-decisive role in CH4 production. In this experiment, operated by aerating N2 and replenishing H2 in anaerobic microecosystems every 24 hours, the changing hydrogen partial pressure cannot be the essential factor that can influence the activity of hydrogenotrophic methanogens. However, changes of acetic acid concentration would cause the change in the anaerobic system. It may cause changes to the dominant strains within methanogenic microflora, so that the time of maximum promotion may occur in a stable status. It may also delay the maximum promotion time, and with the increase of the concentration of acetic acid, methanogens using acetic acid as substrates may grow massively. Therefore, a stronger and longer role in promoting CH4 production could occur.

Effect of 17β-E2 on CO2 production of aquatic anaerobic microflora

CO2 is one of the end products of microbial metabolism; as such, the CO2 production can, to a certain extent, reflect the activity of aquatic anaerobic microflora. Figure 3 identifies the effect of 17β-E2 on CO2 production of aquatic anaerobic microflora. Higher concentration of 17β-E2 (≥500.0 ng/L) and lower concentration of 17β-E2 (≤100.0 ng/L) present different trends of CO2 production. When concentration of 17β-E2 ≤ 100.0 ng/L, the measurement of CO2 production on each 17β-E2 concentration was consistent with the blank control group. When concentration of 17β-E2 exceeded 500.0 ng/L, CO2 production was consistent with the trend of CH4 production. The CO2 production decreased within 24 hours of the initial exposure, followed by a rise in the rate until the peak was reached at the 72 hour mark.

Figure 3

Effect of 17β-E2 on CO2 production of aquatic anaerobic microflora. Compared with the blank control group, by t-test: **, p < 0.01, is the most significant difference; *, p < 0.05, indicates significant difference.

Figure 3

Effect of 17β-E2 on CO2 production of aquatic anaerobic microflora. Compared with the blank control group, by t-test: **, p < 0.01, is the most significant difference; *, p < 0.05, indicates significant difference.

At a concentration of 17β-E2 ranging from 10.0 to 1,000.0 ng/L, significant correlation is identified through linear regression analysis between 17β-E2 concentration and CO2 production rate, at 72 hours (r2 = 0.97363), 96 hours (r2 = 0.96645) and 120 hours (r2 = 0.94223) after exposure. Therefore, it is believed that at later exposure (greater than 120 hours) 17β-E2 can stimulate the activity of aquatic anaerobic microflora or community structure, and may also cause the aquatic microbial physiological stress response, which is associated linearly with the concentration of 17β-E2.

The trend of CO2 production rate to decrease in each experimental group, in lower concentration groups (≤100.0 ng/L), was consistent with the blank control group. However, in each 17β-E2 experimental group (except 1.0 ng/L group), CH4 production rate had a single peak at the 24 hour mark. Therefore, there is room for the hypothesis that lower concentration of 17β-E2 does not have significant impact on the microbial community structure in anaerobic system, but it might have an irritating effect on the activity of key enzyme in the course of microbial methane production. At higher concentrations of 17β-E2 (≥500.0 ng/L), the peak time is similar for CO2 production rate of each 17β-E2 concentration and CH4 production rate of corresponding concentration.

A linear regression analysis was performed between CH4 and CO2 production rate that corresponded in time and concentration (Table 3). From 48 to 120 hours after contamination, there was a significant linear correlation between CH4 and CO2 production rates during the same period with different concentrations of 17β-E2. When CH4 production rate was high, the CO2 also showed a high production rate in the same period with the same concentration of 17β-E2. Both had similar trends, which explained a synchronized relationship between CH4 and CO2 production rate. The significant increase of anaerobic aquatic microbial activity could further validate the changing of the communities of micro-organisms. The effects of 17β-E2 on the activity of various kinds of aquatic anaerobic microflora resulted in concentrations of 1.0–10,000.0 ng/L, which suggest that the actual 17β-E2 concentrations found in the ecosystems posa certain ecotoxicological risk to the ecology of aquatic anaerobic microflora.

Table 3

Fitting straight line parameters of CH4 and corresponding CO2 production rate in higher concentrationa of 17β-E2

  Model summaryb Parameter estimates 
Time (hours) r2 Prob > f Constant a a_SEc Slope b b_SEd 
48 0.99951 0.01002 0.97523 0.00449 0.15114 0.00238 
72 0.99767 0.02171 1.25747 0.01574 0.12416 0.00424 
96 0.99668 0.02596 1.03676 0.02255 0.35122 0.01433 
120 0.99931 0.01184 0.61745 0.01174 12.2932 0.22871 
  Model summaryb Parameter estimates 
Time (hours) r2 Prob > f Constant a a_SEc Slope b b_SEd 
48 0.99951 0.01002 0.97523 0.00449 0.15114 0.00238 
72 0.99767 0.02171 1.25747 0.01574 0.12416 0.00424 
96 0.99668 0.02596 1.03676 0.02255 0.35122 0.01433 
120 0.99931 0.01184 0.61745 0.01174 12.2932 0.22871 

aHigher concentration means concentration of 17β-E2 ≥ 500.0 ng/L.

bLinear regression equation is y = a + bx; r2 for goodness of fit; the value of Prob > F less than 0.05 indicates that there is a significant linear correlation.

cStandard error for standard deviation of constant a.

dStandard error for standard deviation of slope b.

CONCLUSION

17β-E2 produced effects on CH4 production in anaerobic microecosystems, in such a way that CH4 was more stronger promoted and had a longer promoting time and a delayed peak time with the increasing concentration of 17β-E2. Under higher concentration of 17β-E2 (≥500.0 ng/L), the function of methanogenic micro-organisms and the activity of anaerobic micro-organisms had a synchronous relationship under aquatic anaerobic microecosystems. This was reflected by the comparative study of emissions of two indicative GHGs, CH4 and CO2. Further study of 17β-E2 in the aquatic anaerobic ecosystem should be carried out in respect of microbial population structures.

ACKNOWLEDGEMENTS

Aidong Ruan and Chenxiao Liu contributed equally to this paper. This work was supported financially by the National Natural Science Foundation of China (No. 51378175), National Natural Science Foundation Project for Excellent State Key Laboratory (No. 41323001) and Independent Research Project of State Key Laboratory of Hydrology and Water Resources (No. 20145028212). The authors thank the Hohai University State Key Laboratory of Hydrology and Water Resources for allowing us to use their laboratory space and equipment.

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