Electrical signals generated by soil microorganisms in microbial fuel cells respond linearly to soil Cd2+ pollution

Geoderma 255–256 (2015) 35–41

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Electrical signals generated by soil microorganisms in microbial fuel cells respond linearly to soil Cd2+ pollution Yun-Bin Jiang a,1, Huan Deng a,1, Dong-Mei Sun b, Wen-Hui Zhong a,⁎ a b

Jiangsu Provincial Key Laboratory of Materials Cycling and Pollution Control, School of Geography Science, Nanjing Normal University, 210023 Nanjing, China School of Chemistry and Materials Science, Nanjing Normal University, 210023 Nanjing, China

a r t i c l e

i n f o

Article history: Received 7 December 2014 Received in revised form 10 April 2015 Accepted 19 April 2015 Available online xxxx Keywords: Microbial fuel cells Coulomb Start-up time Dehydrogenase activity PCR-DGGE

a b s t r a c t We aimed to determine if electrical signals generated by soil microorganisms in microbial fuel cells (MFCs) can accurately respond to Cd2+ concentrations and to evaluate the linear detection range of the method. MFCs were packed with soil spiked with 10 to 400 mg kg−1 Cd2+ and operated for 37 h at constant temperature (30 °C). The generated coulomb (C) and start-up time (ST) of the MFCs were calculated as electrical signals. The dehydrogenase activity (DHA) of the Cd2+-spiked soil was determined as a reference method. After MFC operation, the diversity of anodic bacteria was studied by using PCR-DGGE and the sequencing of 16S rRNA genes. The results showed that with increasing Cd2+ concentration, C decreased while ST increased significantly. In the control, C was 30.86 ± 3.84 C and ST was 14.39 ± 1.44 h; these values decreased to 8.29 ± 5.08 C and 30.39 ± 2.87 h, respectively, for the treatment with 400 mg kg−1 Cd2+. Both C (r2 = 0.943, P b 0.01) and ST (r2 = 0.937, P b 0.01) were linearly related to Cd2+ at concentrations ranging from 10 to 100 mg kg−1 and were in agreement with DHA. Cadmium stress significantly decreased the Shannon diversity and changed the community structure of anodic bacteria. Phylogenetic analysis of DGGE bands showed that the anodic bacteria were mainly affiliated with Bacillus, Comamonas, Clostridium and Enterobacter. We propose that electrical signals can be used to evaluate the toxicity of Cd2+ to soil microorganisms at concentrations below 100 mg kg−1. © 2015 Elsevier B.V. All rights reserved.

1. Introduction Cadmium is introduced into the environment from industries such as mining and industrial smelting, automobile exhaust, and the application of pesticides in agricultural practices. Cadmium is a serious threat to soil ecosystems due to its high toxicity and lack of biodegradability (Tchounwou et al., 2012). In current toxicity bioassays, the toxicities of heavy metals to soil micro-organisms are routinely determined by using microbiological indicators including enzyme activities, respiration rates and metabolic quotients. The responses of these indicators to pollutants are primarily based on active intracellular microbial reactions, and toxicity emerges after the pollutant undergoes inward migration. During the migration, a portion of the heavy metal ions binds with the cell wall and after entering the cell, the activity and toxicity of heavy metal ions can be reduced by a series of internal cellular mechanisms (Gadd, 2004). Therefore, the above microbiological indicators may lack sensitivity to low concentrations of heavy metals. For example, studies have shown that the microbial respiration rate appeared unaffected by heavy metal concentrations close to the current EU mandatory limits (e.g., 100–150 mg kg−1 Cr and 50–140 mg kg−1 Cu) (Brookes, ⁎ Corresponding author. E-mail address: [email protected] (W.-H. Zhong). 1 These authors contributed equally to this work.

http://dx.doi.org/10.1016/j.geoderma.2015.04.022 0016-7061/© 2015 Elsevier B.V. All rights reserved.

1995). In addition, these methods are laborious and often require the use of dedicated reagents and expensive instrumentation. For example, a microcalorimetry method to measure soil microbial activity by total heat evolution or by time to generate maximum heat requires a relatively high-cost instrument (Rong et al., 2007). Thus, it is desirable to develop a novel method to detect the toxicity of heavy metals with high sensitivity and low investment. Microbial fuel cells (MFCs) are devices in which microorganisms convert chemical energy into electricity (Logan et al., 2006). Bacteria in the anode chamber of an MFC oxidize organic matter and transfer electrons to the electrode, producing measurable current through an external circuit (Lovley, 2008). Soil has a large population of electrogenic bacteria that mainly belong to the Proteobacteria and the Firmicutes (Ringelberg et al., 2011). These bacteria can generate power in MFCs primarily through extracellular electron transfer processes. The electrogenic functions are carried out by outer-membrane cytochromes, which can be inhibited by a toxic substance and reducing the power output. Since the inhibition occurs outside the membrane rather than intracellularly, the electrical signals (e.g., voltage, current or quantity of generated electrons) may be rapidly expressed to low pollutant concentrations. In a previous study, we verified that the electrical signals of MFCs decreased with increasing Cu concentrations (50 to 400 mg kg−1) and studied the mechanisms of these decreases using electrochemical and microbiological methods (Deng et al., 2015). As a potential method to detect Cd2+

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toxicity, it is worth determining the Cd2+ concentration range within which electrical signals respond linearly to Cd2+. In this study, we hypothesize that the electrical signals generated by MFCs can respond to low level Cd2+ concentrations and can indicate Cd2+ toxicity within a wide range of concentrations. To test this hypothesis, verify the reliability of the MFC-based detection method, and determine the linear range of heavy metal concentration range, a wide range of Cd2+ concentrations (10 to 400 mg kg−1 soil) were applied in the present study, and the electrical signals were compared with soil dehydrogenase activity (DHA) under the same Cd2+ concentrations. The anodic bacteria were studied by denaturing gradient gel electrophoresis (DGGE) and phylogenetic analysis followed by Shannon index analysis and principal component analysis. The aims were to identify the linear detection range of Cd2+ concentrations for electrical signals and to reveal the toxic effects of heavy metals on anodic bacterial diversity.

filled with 200 mL potassium ferricyanide [100 mM K3Fe(CN)6 in 50 mM NaCl]. All the MFCs were operated at a 30 °C in an incubator in the dark. Voltage data generated by the MFCs were recorded at intervals of 10 min with a data acquisition module (7660B, ZTIC Co., Beijing, China). In addition to the 24 MFCs used above, the voltage of another MFC with chloroform-fumigated soil (sterilized) was recorded to conform that the power was originated from chemical process or by electrogenic bacteria. 2.4. Soil dehydrogenase activity Soil dehydrogenase activity (DHA) was determined according to Casida et al. (1964). One gram soil (dry weight equivalent) was weighed with 2, 3, 5-triphenyltetrazolium chloride (TTC) as substrate. After being incubated at 37 °C for 24 h, the produced triphenylformazane (TPF) was measured in a spectrophotometer at 485 nm.

2. Material and methods 2.5. DNA extraction and amplification 2.1. Soil sampling and soil physiochemical analysis Soil was collected at a depth of 0–20 cm from a broad-leaf forest in the Campus of Nanjing Normal University, Nanjing, China (32°07′ 58.97″N, 118°54′24.03″E). The soil was ground, sieved through a 2 mm mesh, and mixed thoroughly. Part of the sieved soil was used immediately in Cd2+ stress experiments, and part was air-dried for physiochemical analysis or stored at −80 °C for DNA extraction. Soil texture was determined with the pipette method (Gee and Bauder, 1986). Total carbon and total nitrogen were measured using an elemental analyzer (Vario EL III, Elementar Analysensysteme GmbH, Hanau, Germany). The maximum water holding capacity (MWHC) was determined with the method of Priha and Smolander (1999). Soil pH was measured at a soil–water ratio of 1:2.5 (w/v). Soil electrical conductibility (EC) was determined using an electrical conductivity meter (INESA Scientific Instrument Co., Ltd, Shanghai, China) at a soil–water ratio of 1:5 (w/v). The soil physiochemical properties are as follows: soil texture, clay loam; MWHC, 68%; total carbon, 1.73 mg g−1; total nitrogen, 0.68 mg g−1; soil pH, 6.71; EC, 97.2 μS cm−1. 2.2. Cadmium stress experiment The sieved soil was thoroughly mixed and then divided into 8 subsamples. CdCl2 in solution was added to randomly selected seven subsamples to give 10, 25, 50, 100, 200, 300 and 400 mg Cd2+ kg−1 dry weight soil. The remaining subsample was added with distilled water to serve as a control. Soil in each subsample was further evenly divided to form three replicates. Each replicate was allowed to stand for 24 h in an incubator at a constant 30 °C and then subjected to the measurements of electrical signals and DHA. Before the measurements of electrical signals, soil was fed with 4% (w/w) glucose to minimize the startup time of power generation and to improve the power output (Chae et al., 2009). 2.3. MFC construction and operation Twenty-four MFC reactors were set up in dual chamber configuration made of oroglas. The anode chamber and cathode chamber separated with a cation exchange membrane (Qianqiu Group, Hangzhou, China) were each a cube of 6 cm. The anode and cathode, made of carbon felt (Haoshi Carbon Fiber Co., Lanzhou, China) with the same area of 9 cm2 (3 × 3 cm) and thickness of 8.5 mm, were fixed in parallel with the cation exchange membrane. The electrodes with a distance of 6 cm were connected to an external circuit with a resistance of 1000 Ω using the titanium wire. Each of the anode chambers was packed with 130 g soil (dry weight equivalent) fed with 4% (w/w) glucose. Ninety milliliters distilled water was added to keep the soil MWHC and air-proofed by a rubber plug. Each of the cathode chambers was

After a 37-hour operation, a piece (1 × 1 cm) of the anode was collected. Prior to DNA extraction the anode was rinsed with sterilized deionized water to remove residual soil (He et al., 2009). The genomic DNA of the collected anode and three uncontaminated soil samples was extracted using Fast DNA SPIN kits for soil following the manufacturer's instructions (MP Biomedicals, Irvine, USA). The quality and quantity of the DNA were determined at 230, 260 and 280 nm by a nanodrop ND-1000 UV–Vis spectrophotometer (NanoDrop Technologies, Wilmington, USA). The amplification of bacterial 16S rRNA gene for DGGE was conducted using primers 341f (5′-CCT ACG GGA GGC AGC AG-3′) with a 40-bp GC clamp (5′-CGC CCG CCG CGC CCC GCG CCC GGC CCG CCG CCC CCG CCC C-3′) and 907r (5′-CCG TCA ATT CMT TTG AGT TT-3′) (Muyzer et al., 1993). The 25 μL reaction mixture contained 1 μL of template DNA, 0.5 μL of each 1 μM primer, 2.5 μL of 10 × buffer (Mg2+ plus), 2 μL of 10 mM dNTP mixture (2.5 mM of each), and 1.5 units of Taq DNA polymerase (Takara Co., Ltd, Shanghai, China). Thermal cycling conditions were: initial denaturation at 94 °C for 4 min; 30 cycles consisting of denaturation at 94 °C for 1 min, primer annealing at 54 °C for 30 s, and elongation at 72 °C for 30 s. 2.6. DGGE, sequencing and phylogenetic analysis DGGE was performed using 8% polyacrylamide gel in a denaturing gradient of 40–80% (100% denaturant = 7 M urea, 40% (v/v) formamide) with a Bio-Rad Dcode™ universal mutation detection system (Bio-Rad Laboratories, Hercules, USA) for 15 h at a constant voltage (100 V) and temperature (60 °C) in 0.5× TAE buffer. After electrophoresis, the nucleic acids in the gel were visualized with SYBR™ Green I stain (1:10.000 dilution) (Invitrogen, Carlsbad, USA) and photographed under UV light with the ChemiDoc™ XRS+ gel imaging system (BioRad Laboratories, Hercules, USA) and digitized with Quantity One (version 4.4.0) software. The DNA in representative excised DGGE bands was eluted in 40 μL of sterilized distilled Milli-Q water. Five microliters of eluted DNA was used as a template for PCR amplification with primers 341f/907r and the thermocycling program above described. PCR products were cloned using the Peasy™-T3 Cloning Kit according to the manufacturer's recommendations (TransGen, Beijing, China), and transformed into Trans1-T1 Phage Resistant Chemically Competent Escherichia coli cells (TransGen, Beijing, China). Transformed colonies were screened for inserts by PCR with the primers M13f (TGT AAA ACG ACG GCC AGT) and M13r (TCA CAC AGG AA ACA GCT ATG AC). Sequencing of correct clones (four replicates for each band) was carried out with vector primer set M13f/M13r by TransGen (Beijing, China). Vector sequences were removed using DNASTAR Lasergene 7.1. The gene sequences of the DGGE bands were subjected to taxonomic assignments using the BlastX

Y.-B. Jiang et al. / Geoderma 255–256 (2015) 35–41

400 300 200

35

20

20

30

40

10

10

30

Start-up time (h)

(http://ncbi.nlm.nih.gov/blast). Phylogenetic analysis was performed using a neighbor-joining algorithm and distance calculation by MEGA4. Sequences that were 98% or more identical were considered as a unique operational taxonomic unit (OTU). All the sequences determined in this study were submitted to GenBank database and assigned accession numbers: KJ128039–KJ128060.

80

100

2

0

100

200

300

400

r = 0.938 P < 0.01

25 25

20

20

15

15

10

10 Coulomb (C) and start-up time (ST) of the voltage curve were selected to represent MFCs' response to cadmium addition. ST was defined here as time needed for each MFC to exceed 50 mV from the beginning of operation (Liu et al., 2011). C, defined as the quantity of electrons and estimated as the area of voltage versus time curve divided by external resistance, was calculated according to the following formula:

n¼1

60

r = 0.942 P < 0.01

2.7. Statistical analysis

2  1000

40

2

Fig. 1. The average voltage of MFCs (n = 3) with Cd2+-spiked soil and control soil. The time interval between every two data points is 10 min. The MFCs were operated for 37 h.

m X ðU n þ U nþ1 Þ

20

35

Time (h)

C¼

0

15

0

10

15

20

5

0

25

25

100 0

2

r = 0.943 P < 0.01

30

30

Coulomb (C)

500 Voltage (mV)

35

control -1 10 mg kg -1 25 mg kg -1 50 mg kg -1 100 mg kg -1 200 mg kg -1 300 mg kg -1 400 mg kg

600

37

 600:

ð1Þ

Here, U is the voltage (V). 1000 is the external resistance (Ω) used in this study; n is the number of data that were recorded by a data acquisition module with a time interval of 600 s; m is the total number of voltage data showed in Fig. 2. The DGGE data were subject to principal component analysis (PCA) and Shannon diversity (H′) analysis. Significant differences between means were determined by one-way ANOVA at a level of P b 0.05 using Least Significance Difference (LSD) test. Exponential regression

0

100

2

r = 0.937 P < 0.01 0

20

200 -1 300 cCd (mg kg soil)

40

60

80

100

400

Fig. 2. Exponential regressions (n = 8) of Coulomb (C) and Start-up time (ST) with respect to Cd2+ concentration (0 to 400 mg kg−1). The sub-figures show linear regressions (n = 5) of the two electric signals and Cd2+ concentration ranging from 0 to 100 mg kg−1.

analysis and linear regression analysis were performed between electrical signals and cadmium concentration. All statistical tests were conduct using SPSS software (version 18.0). 3. Results 3.1. MFC voltage and electrical signal response to Cd stress The voltage generated by the control MFC (without-Cd2+) started up about 14 h after MFC operation. The time before start-up increased significantly from 16 h to 30 h as Cd2+ concentration increased from 10 to 400 mg kg−1. The voltage of all treatments became stable at 3 h after

Table 1 Coulomb and start-up time of MFCs operated with soils containing different Cd2+ concentrations in the anode chamber. The MFCs were operated for 37 h. Soil dehydrogenase activity was determined as a reference. The data are presented as means with standard error in parenthesis (n = 3). Cd2+ concentration (mg kg−1)

Coulomb (C)

Start-up time (h)

Dehydrogenase activity (mg TPF kg−1 d−1)

0 (control) 10 25 50 100 200 300 400 LSD0.05 F value P value

30.86 (3.24)a 27.14 (2.82)ab 26.81 (1.45)ab 20.78 (2.16)bc 15.66 (2.11)c 14.09 (7.03)cd 13.16 (3.52)cd 8.29 (5.08)d 6.63 13.22 b0.001

14.39 (1.44)e 15.67 (1.74)de 15.61 (1.07)de 19.67 (2.03)cd 23.25 (1.75)bc 25.00 (6.17)b 26.28 (1.99)ab 30.39 (2.87)a 4.88 12.89 b0.001

114.16 (7.56)a 110.56 (0.58)a 113.33 (4.78)a 113.72 (2.77)a 88.58 (2.34)b 83.60 (6.22)b 74.74 (5.05)c 69.26 (6.11)c 8.57 44.25 b0.001

LSD0.05: Least significant difference at level of P b 0.05. Data with the same letter within the same column do not differ significantly at the 5% level.

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start-up. Within the stable voltage stage, the voltage generated by the control MFC was higher than those generated by the MFCs treated with Cd2+; the voltage produced by the MFC treated with 400 mg kg−1 Cd2+ was the lowest among all MFCs (Fig. 1). The voltage of the MFC with fumigated soil was below 10 mV during the operation time, corroborating that the detected electrical signal was of biological origin. The coulombs of generated electrons decreased significantly with increasing Cd2+ concentrations (Table 1). The coulombs for the MFCs treated with 50 and 100 mg kg−1 Cd2+ decreased significantly to 67% and 51% of that of the control, respectively. Start-up time (ST) increased significantly with increasing Cd2+ concentrations. The ST of the MFC treated with 50 mg kg− 1 Cd2+ treatment was significantly higher (36%; P b 0.05) than that of the control MFC. The reference method (i.e., the measurement of soil DHA) produced a similar trend; soil DHA decreased with increasing Cd2+ concentration and the decrease in the DHA level of the MFC treated with 100 mg kg− 1 Cd2+ compared to the control got significant (Table 1).

3

0 (control) -1 25 mg kg -1 100 mg kg -1 200 mg kg -1 400 mg kg

2

PC2 (15.3%)

38

1 0

-1 -2

-1

0 1 PC1 (22.8%)

2

Fig. 4. Principal component analysis (PCA) of the band data from the PCR-DGGE profiles.

3.2. Regression analysis between electrical signals and Cd2+ concentrations 3.3. Effect of cadmium on anodic bacteria Both C and ST exhibited exponential relationships with Cd2+ concentrations (Fig. 2). The curves fit to C or ST and Cd2+ concentration (cCd) showed steep slopes from 10 to 100 mg kg−1 Cd2+ and a nearzero slope from 100 to 400 mg kg−1. Below the Cd2+ concentrations of 100 mg kg−1, both C and ST had a linear relationship with Cd2+ concentration (Fig. 2).

soil 1

2

control 1 2 3

3

25 1 2 3

The DGGE profiles of 16S rRNA gene fragments from MFC anode biofilms and uncontaminated soil are shown in Fig. 3. The quantities of DGGE bands in the anode biofilm profiles were significantly lower than those in the soil profiles. Bands 1, 2, 4, 5, 6, 7 and 15 were detected

anode 100 1 2 3

200 1 2 3

400 1 2 3

1

2 3 4

5 6 7 8 9

10

11 12 13 14 15 17

Shannon index:

16 18

2.43(0.11)a 2.48(0.06)a 2.52(0.16)a 2.42(0.02)a 2.13(0.13)b

Fig. 3. DGGE profiles of 16S rRNA gene fragments and the Shannon index of the bacterial community of the anode biofilm for Cd2+ concentrations of 0 (control), 25 mg kg−1, 100 mg kg−1, 200 mg kg−1, 400 mg kg−1 and of the soil. The numbers 25, 100, 200 and 400 denote the Cd2+ concentration (mg kg−1). The numbers from 1 to 18 represent the dominant or specific DGGE bands that were excised for sequencing and phylogenetic analysis. The Shannon indices are presented as means with standard error (n = 3). LSD0.05 = 0.19, F = 6.262, P = 0.009. LSD0.05: Least significant difference at level of P b 0.05. Data with the same letter do not differ significantly at the 5% level.

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39

The phylogenetic relationships between DGGE band sequences and 16S rRNA gene sequences retrieved from the GenBank database indicated that bands 1, 2, 4, 5, 6, 7 and 15, which were distinct in biofilm samples and not in soil samples, are mainly affiliated with Sporolactobacillus, Legionella and Clostridium (Fig. 5). The other bands were clustered with Sporolactobacillus, Dechloromonas, Enterobacter, Pantoea, Comamonas and uncultured Acidobacteria.

in the profiles of the anode biofilm samples but not in those of the soil samples. Bands 2, 3, 4, 5, 6, 7, 15, 16, 17 and 18 were the dominant bands in the profiles of the anode biofilm samples. The Shannon index (H′) of the anode biofilm sample treated with 400 mg kg− 1 Cd2+ was significantly lower than that of the control (Fig. 3). The H′ of the sample treated with 100 mg kg−1 Cd2+ treatment was the highest among all Cd2+-treated samples and was not significantly different than that of the control. The PCA plots showed that on the PC1 axis, the bacterial community composition of the control differed from those of the Cd2+-treated samples (Fig. 4). On the PC2 axis, the sample treated with 100 mg kg−1 Cd2+ was distinctive compared to the other samples. There was no difference between the samples treated with 25 and 200 mg kg−1 Cd2+.

4. Discussion The present study shows that the electrical signals generated by soil micro-organisms exhibit a linear relationship with Cd2+ concentration over a wide range of concentrations. Both C and ST were significantly

MFC anode DGGE Band 15 (KJ128057) MFC anode DGGE Band 17 (KJ128059) Pantoea agglomerans E83 (JF68365) 40 Enterobacter hormaechei SFK-2 (KC315760)

Rhizobium sp. SOY7 (KF008235) Enterobacter ludwigii LHC8 (KC951920)

39

MFC anode DGGE Band 16 (KJ128058) MFC anode DGGE Band 18 (KJ128060)

47

MFC anode DGGE Band 4-1 (KJ128042) 98 100

MFC anode DGGE Band 9-2 (KJ128049) 98

Enterobacter sp. SCMC36 (KF358440) Pantoea citrea DSM 13699 (FJ756352) MFC anode DGGE Band 10 (KJ128050)

65

MFC anode DGGE Band 2 (KJ128040)

49 100

Legionella sp. LC2720 (JN381005) Legionella rowbothamii LLAP6 (NR 036804)

99

35

MFC anode DGGE Band 9-1 (KJ128048) Dechloromonas sp. ECC1-pb1 (GU202936)

100

MFC anode DGGE Band 11 (KJ128051) 100 Comamonas testosteroni SI (HQ200412)

MFC anode DGGE Band 14-2 (KJ128056) 100 Uncultured Rhodoplanes sp. clone GASP-KB1S2 F08 (EU297570) 100 MFC anode DGGE Band 13-1 (KJ128053)

Uncultured Acidobacteria bacterium clone GASP-MA2S1 C05 (EF662846) MFC anode DGGE Band 3 (KJ128041)

94

Clostridium favososporum DSM 5907 (X76749)

100

MFC anode DGGE Band 4-2 (KJ128043) 100

67

71 Clostridium beijerinckii B17 (KC915012)

MFC anode DGGE Band 5 (KJ128044) 100 Clostridium pasteurianum BC1 (NR 103938)

MFC anode DGGE Band 13-2 (KJ128054)

41 87

73 Bacillus arbutinivorans B10S (KF010793) 100

Bacillus senegalensis WY167 (KC921179) MFC anode DGGE Band 14-1 (KJ128055)

MFC anode DGGE Band 1 (KJ128039)

98

MFC anode DGGE Band 12 (KJ128052)

66

MFC anode DGGE Band 8 (KJ128047)

99 99 74

Sporolactobacillus laevolacticus M-8 (NR 025843) MFC anode DGGE Band 6 (KJ128045)

39 MFC anode DGGE Band 7 (KJ128046)

0.02

Fig. 5. Phylogenetic relationships between DGGE band sequences and 16S rRNA gene sequences retrieved from the GenBank database. The tree represents the alignment of a 525-bp region in 16S rRNA gene sequences. The DGGE bands were assigned the accession numbers KJ128039–KJ128060 after the sequences were submitted to the GenBank database.

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correlated with Cd2+ concentration in the range of 10 to 100 mg kg−1 Cd2+, suggesting that electrical signals are responsive to Cd2+ pollution and are suitable indicators to detect Cd2+ toxicity to soil microorganisms. We maintained soil water content at maximum water holding capacity (MWHC) in the MFC anode chambers as opposed to keeping the soil flooded, as a previous study (Wang et al., 2012). There is a trade-off between water content and toxicity detection; low water content can inhibit the generation of electricity, but an overwhelming amount of water may decrease the heavy metal concentration via dilution effect. To enhance the reliability of the results in this study, we adjusted the water content to MWHC to minimize the dilution rate of Cd2+ while sustaining electricity generation. The fumigated soil demonstrated that power generation in the MFC was a bioelectrocatalytic substrate oxidation processes carried out by indigenous microorganisms (Schröder, 2007). To improve the power output of MFCs, a broad-spectrum and easy-to-degrade carbon source such as glucose is recommended. The addition of glucose shortens ST and increases the voltage generated by the electrogenic bacteria (Chae et al., 2009). The electrical signals (e.g., the voltages) may vary significantly among different soils. The power generation of soil-based bioelectrochemical systems can be affected by soil pH and the contents of Fe and organic matter (Dunaj et al., 2012). The method used in this study is limited in that it is difficult to compare the electrical signals of different soil types. Nevertheless, the trends of decreasing electrical signals with increasing pollution level should be consistent in different soils. In this study, the electrical signals respond linearly to Cd2+ concentrations ranging from 10 to 100 mg kg−1; the electrical signals did not respond predictably to Cd2+ concentrations exceeding 100 mg kg−1. The results indicate that the electrical signals can be used to monitor Cd2+ toxicity within the concentration range of 10 to 100 mg kg−1. The electrical signals originated from the bioelectrocatalytic substrate oxidation processes and electron transfer, which occurs extracellularly and includes direct electron transfer (DET) and mediated electron transfer (MET). In the DET process, the membrane-bound cytochromes (Bond et al., 2002) or conductive bacterial pili (Gorby et al., 2006) bind with heavy metals and are inactivated (Cherrad et al., 2012). On the other hand, the metabolites such as formate and flavines, which are needed as electron mediators in MET (Rabaey et al., 2007), may also react with heavy metals, causing their electron transfer function to be forfeited (Elliott et al., 1986). Among the genera with which the sequences of DGGE bands detected in this study were affiliated, Bacillus sp. (Nimje et al., 2009), Clostridium sp. (Finch et al., 2011), Comamonas sp. (Xing et al., 2010) and Enterobacter sp. (Rezaei et al., 2009) have demonstrated electrogenic properties with or without soluble redoxactive mediators (i.e., iron (Fe(III)/Fe(II)) and humic acids in forest soils) (Kappler et al., 2004). The presence of Cd2+ changed the anodic bacterial diversity and shifted the community structure. The saddle-shape curve of diversity with increasing Cd2+ concentration is probably due to the increase in resistant anodic bacteria below 100 mg kg−1 Cd2+ and the diminishment of these bacteria at Cd2+ concentrations exceeding 100 mg kg−1 (Deng, 2012). Genera affiliated with Comamonas sp., which was reported to be resistant bacterium of heavy metals (Ma et al., 2009), appeared at 100 mg kg−1 Cd2+ concentration and decreased under higher concentrations. The diversity may provide a guarantee for the power generation under Cd2+ stress, especially in high concentrations by redundant species and metabolic routines (Deng, 2012). However, some bands affiliated with Sporolactobacillus, Legionella, Dechloromonas, Pantoea, and Rhizobium remained in relatively large abundances and some became increasingly dominant with increasing Cd2+ concentration. This result illustrated that the resistant species may generate power at lower levels than the control, reflecting the cadmium toxicity. The five genera above could either release electrochemically active compounds (Wang et al., 2010) or conduct processes related to electron transfer (Bhatia and Sharma, 2010). They may have syntrophic relationships with electrogenic bacteria (Freguia et al., 2008), which could play critical roles in

the power output of MFCs. No difference was observed by PCA analysis between the 25 and 200 mg kg−1 Cd2+ treatments because the dominant bands shared between the Cd2+ treatments may be resistant to Cd2+ stress. Electrogenic bacteria would be dormant or starved but can still survive in unfavorable conditions (Watanabe et al., 2007). Although we cannot rule out the possibility that the cells were dead or inactive, the DNA can also be detected. 5. Conclusion This study showed that the electrical signals generated by MFCs can be used to detect the level of cadmium in the soil. The electrical signals responded negatively to increasing Cd2+ concentration and showed a linear relationship with Cd2+ concentration within the range of 10 to 100 mg kg−1 Cd2+. Cadmium pollution changed the community diversity of anodic bacteria in the MFCs. Before the MFC-based detection method can be applied in practice, further investigation is required to: (i) accelerate start up, increase the sensitivity and enlarge the linear range of pollutant concentrations by optimizing the MFC configuration; and (ii) replace the ferricyanide with oxygen as a sustainable electron acceptor. Acknowledgments This study was supported by the Natural Science Foundation of China (41301260), the Natural Science Foundation of the Higher Education Institutions of Jiangsu Province (13KJB610009), and the Foundation for High-level Talents of Nanjing Normal University (2013105XGQ0057). The authors thank L.A. Sayavedra-Soto from Oregon State University for the language editing. References Bhatia, S., Sharma, D.K., 2010. Biodesulfurization of dibenzothiophene, its alkylated derivatives and crude oil by a newly isolated strain Pantoea agglomerans D23W3. Biochem. Eng. J. 50, 104–109. Bond, D.R., Holmes, D.E., Tender, L.M., Lovley, D.R., 2002. Electrode-reducing microorganisms that harvest energy from marine sediments. Science 295, 483–485. Brookes, P.C., 1995. The use of microbial parameters in monitoring soil pollution by heavy metals. Biol. Fertil. Soils 19, 269–279. Casida, L.E., Klein, D.A., Santoro, T., 1964. Soil dehydrogenase activity. Soil Sci. 98, 371–376. Chae, K.J., Choi, M.J., Lee, J.W., Kim, K.Y., Kim, I.S., 2009. Effect of different substrates on the performance, bacterial diversity, and bacterial viability in microbial fuel cells. Bioresour. Technol. 100, 3518–3525. Cherrad, S., Girard, V., Dieryckx, C., Gonçalves, I.R., Dupuy, J.W., Bonneu, M., Rascle, C., Job, C., Job, D., Vacher, S., Poussereau, N., 2012. Proteomic analysis of proteins secreted by Botrytis cinerea in response to heavy metal toxicity. Metallomics 4, 835–846. Deng, H., 2012. A review of diversity–stability relationship of soil microbial community: what do we not know? J. Environ. Sci. 24, 1027–1035. Deng, H., Jiang, Y.B., Zhou, Y.W., Shen, K., Zhong, W.H., 2015. Using electrical signals of microbial fuel cells to detect copper stress on soil micro-organisms. Eur. J. Soil Sci. 66, 369–377. Dunaj, S.J., Vallino, J.J., Hines, M.E., Gay, M., Kobyljanec, C., Rooney-Varga, J.N., 2012. Relationships between soil organic matter, nutrients, bacterial community structure, and the performance of microbial fuel cells. Environ. Sci. Technol. 46, 1914–1922. Elliott, H.A., Liberati, M.R., Huang, C.P., 1986. Competitive adsorption of heavy metals by soils. J. Environ. Qual. 15, 214–219. Finch, A.S., Mackie, T.D., Sund, C.J., Sumner, J.J., 2011. Metabolite analysis of Clostridium acetobutylicum: fermentation in a microbial fuel cell. Bioresour. Technol. 102, 312–315. Freguia, S., Rabaey, K., Yuan, Z., Keller, J., 2008. Syntrophic processes drive the conversion of glucose in microbial fuel cell anodes. Environ. Sci. Technol. 42, 7937–7943. Gadd, G.M., 2004. Microbial influence on metal mobility and application for bioremediation. Geoderma 122, 109–119. Gee, G.W., Bauder, J.W., 1986. Particle-size analysis, P. 383–411. In: Page, A.L. (Ed.), Methods of Soil Analysis, Part 1, Physical and Mineralogical Methods, Second edition. Agronomy. Gorby, Y.A., Yanina, S., McLean, J.S., Rosso, K.M., Moyles, D., Dohnalkova, A., Beveridge, T.J., Chang, I.S., Kim, B.H., Kim, K.S., Culley, D.E., Reed, S.B., Romine, M.F., Saffarini, D.A., Hill, E.A., Shi, L., Elias, D.A., Kennedy, D.W., Pinchuk, G., Watanabe, K., Ishii, S., Logan, B., Nealson, K.H., Fredrickson, J.K., 2006. Electrically conductive bacterial nanowires produced by Shewanella oneidensis strain MR-1 and other microorganisms. Proc. Natl. Acad. Sci. 103, 11358–11363. He, Z., Kan, J.J., Wang, Y.B., Huang, Y.L., Mansfeld, F., Nealson, K.H., 2009. Electricity production coupled to ammonium in a microbial fuel cell. Environ. Sci. Technol. 43, 3391–3397.

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