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. 2016 Aug 26;5(6):1539–1547. doi: 10.1039/c6tx00210b

Microarray analysis and real-time PCR assay developed to find biomarkers for mercury-contaminated soil†

Jing Hou a, Xinhui Liu b,✉, Baoshan Cui b, Junhong Bai b, Xiangke Wang a,✉
PMCID: PMC6062303  PMID: 30090455

graphic file with name c6tx00210b-ga.jpgThe evaluation of mercury (Hg) toxicity in agricultural soil is of great concern because its bioavailability and bioaccumulation in organisms through the food chain can have adverse effects on human health.

Abstract

The evaluation of mercury (Hg) toxicity in agricultural soil is of great concern because its bioavailability and bioaccumulation in organisms through the food chain can have adverse effects on human health. Therefore, the aim of this study was to develop sensitive biomarkers for Hg stress in agricultural soil. With the results obtained from a high-throughput cDNA microarray, 12 Hg-responsive genes were selected to examine their concentration-dependent responses to Hg stress at different Hg concentrations. The lowest observable adverse effect concentrations (LOAECs) of Hg were 0.8 mg kg–1 for seed germination, 1.6 mg kg–1 for root biomass, 0.8 mg kg–1 for root elongation, and 0.8 mg kg–1 for root morphology, respectively, whereas the lowest Hg treatments (0.1–0.4 mg kg–1) could generally induce differential expression of genes. These results indicated that the detection of Hg in soil at the molecular level is a highly sensitive method. Moreover, the Hg soil content exhibited a significant positive correlation with the relative expression of probable glutathione S-transferase parA (r = 0.637, p = 0.05), chlorophyll a–b binding protein 13, chloroplastic-like (r = 0.689, p = 0.05) and geranylgeranyl pyrophosphate synthase 1 (r = 0.682, p = 0.05), implying that the three genes are good candidates to detect Hg-contaminated soil.

Introduction

In farmland ecosystems, mercury (Hg) has received special attention given its persistence in the environment, biomagnification in trophic chains and extreme toxicity to human health.1–4 The primary sources of soil Hg are atmospheric deposition from nearby industrial activity, such as gold mining, vinyl chloride production, and the battery, chloralkali, and fluorescent lamp industries.5,6 The application of Hg-containing fungicides, sewage sludge, and fertilizers is another important cause of Hg present in agricultural soil.7 Hg present in soil is of great concern because its bioavailability and bioaccumulation in organisms through the food chain may cause neurological and behavioural disorders, deafness, blindness, mental retardation and cerebral palsy in humans.8,9 Therefore, it is necessary to assess Hg toxicity in agricultural soil.

Seedling growth, chlorophyll content, amino acid content, and Ames test are standardized phytotoxicity test methods,10–12 whereas traditional methods are not sufficiently sensitive to monitor the trace toxicants and provide early warning of impacts. In recent years, a great deal of attention has been paid to find biomarkers for chemicals present in soil at the molecular level.13–15 Gene expression analyses of organisms rapidly detect soil contaminants with high sensitivity and specificity.16,17 Given its ability to detect thousands of DNA sequences simultaneously, microarray analysis offers a rapid method for the identification of specific and sensitive markers for environmental stress.18 As the most direct approach for heavy metal transfer to the human food chain, S. lycopersicum is a suitable species for toxicity prediction recommended by the US Environmental Protection Agency (EPA) owing to its fully sequenced genomes and extensive distribution in agricultural soil.

A series of studies have been conducted to characterize the adverse effects of Hg on S. lycopersicum.19–21 However, the transcriptional responses of S. lycopersicum to Hg have been poorly examined. Therefore, the present study aimed to conduct a sensitivity comparison of the traditional method and the transcriptional method for Hg toxicity, and to find biomarkers for Hg-contaminated soil.

Materials and methods

Soil preparation and treatment

The surface soil samples (0–20 cm depth) were collected from an uncontaminated farmland in Baoding, China. A subsample of the soil was analysed for general physical–chemical properties: CEC 17.2 cmol kg–1, pH (soil/water = 1 : 1) 8.1, total Hg <0.01, total Pb 16.6 mg kg–1 and total Cd 0.1 mg kg–1. Soil particle sizes were distributed as follows: 4% clay, 32% silt, and 64% sand. The soils were air-dried, sieved (2 mm mesh) and artificially spiked with Hg [from HgCl2] at the following rates: 0 (control), 0.1, 0.2, 0.4, 0.8, 1.6, 3.2, 6.4 or 12.8 mg kg–1. The soils were watered with deionized water (control) or appropriate aqueous solutions of HgCl2 to obtain the above concentrations, with three replicates at each concentration. The selected chemical concentrations are based on previous experiments on five crops, namely Zea mays, Cucumis sativus, Brassica oleracea, Triticum aestivum and Lactuca sativa.22 500 g spiked soils were well mixed, filled into each Petri dish (18 cm diameter) and stabilized at room temperature for two weeks.

Experimental plant and growth conditions

Solanum lycopersicum Mill. cv. seed, purchased from the Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences (Beijing), were surface sterilized and rinsed with distilled water. After that, 30 seeds were germinated in a Petri dish containing Hg-spiked soil at 25 ± 1 °C for seven days in a dark incubator with 70% humidity.

Determination of growth parameters

After seven days exposure, seed germination was calculated; a 5 mm long radicle was considered to represent germination (US EPA, 1996).23 Subsequently, the seedlings were thoroughly washed with distilled water to remove the soil particles and determine their length. Then, the roots were separated from the seedlings and taken for dry weight determination after drying overnight in an oven at 105 °C.24

Inductively coupled plasma-mass spectrometry (ICP-MS)

For total Hg determination, root and soil samples were ground to powder and sieved through a 1 mm screen, respectively. Root samples (0.5 g) were digested in a mixed acid (4 mL HNO3 and 2 mL H2O2), and soil samples (0. 5 g) were digested in a mixed acid solution (4 mL HNO3/4 mL HClO4/400 μL HF). Then, the samples were heated at 85 °C for two hours and diluted up to 50 mL. The final solution was measured using ICP-MS (NexION300x). The standard references tomato leaves (NIST SRM 1572a) and Montana soil (NIST SRM 2711) were used as the standardized quality control for validating accuracy. The determined concentrations of the standard reference tomato leaves and Montana soil were 0.033 ± 0.002 μg g–1 and 6.05 ± 0.13 mg kg–1, and the certified concentrations were 0.034 ± 0.004 μg g–1 and 6.25 ± 0.19 mg kg–1, respectively, showing the good accuracy of the method. To determine the efficiency of the root in the accumulation of Hg from the soil to the roots, the bioaccumulation factor (BF) was calculated. In this case, BF indicated the concentration of Hg in roots divided by the concentration of Hg in soils.25

Scanning electron microscope (SEM)

Root samples treated with different Hg concentrations were fixed in a 3% (w/v) glutaraldehyde solution for 24 h at 4 °C. The glutaraldehyde-fixed samples were then dehydrated in a graded ethanol series (30%, 50%, 70% and 90% for 20 min each, followed by 96% for 30 min twice). The samples were air-dried at 45 °C for one hour and stored in a desiccator for 12 h. Root samples were then coated with gold–palladium and viewed with a scanning electron microscope (SEM, FEI Quanta 200) at 100× magnification.

Whole-genome expression analysis

The RNA extracted from the control and roots treated with 1/10 LC50 of Hg (2.3 mg kg–1) were hybridized to the tomato microarray (4 × 44 K) with three replicates at each treatment. The microarray hybridization, staining, scanning, and data normalization were conducted according to the Agilent standard hybridization protocol. Total RNA extracted from roots treated with different Hg concentrations was synthesized using the TRIZOL reagent with three replicates at each treatment. Primers were designed using PRIMER3 software, with an internal control of LeACTIN (U60480). The RT-qPCR performed using a 7500 fast Real-time PCR System. A melting curve was obtained by a step of 95 °C denaturation, and an increase rate of 0.2 °C s–1 with the start temperature of 60 °C and the end temperature of 95 °C.

Statistical analyses

One-way analysis of variance (SPSS 20.0) was performed to determine significant differences among treatments involving seed germination, root elongation and biomass. Pearson's analysis (SPSS 20.0) was performed to reveal the correlation between the Hg soil content and the gene expression level. All experiments consisted of three replicates.

Results

Total Hg in roots

Fig. 1 shows that Hg in S. lycopersicum roots was positively correlated with Hg in soil (r = 0.979, p = 0.05), and the maximum value appears at 12.8 mg kg–1. No significant differences in BF were observed at Hg <0.2 mg kg–1. A significant decrease in BF was observed at Hg >0.4 mg kg–1. No significant differences in BF were observed from 0.4 to 3.2 mg kg–1. Also, BF values were <1 for all the Hg concentrations, suggesting that S. lycopersicum is not a good Hg accumulator.

Fig. 1. Bioaccumulation factor (BF) and Hg content in Solanum lycopersicum roots with increasing Hg concentrations.

Fig. 1

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Effect of Hg on root growth

Table 1 shows that Hg has a minimal effect on seed germination at Hg <0.4 mg kg–1, but obvious inhibitory effects were observed at Hg >0.8 mg kg–1 (p < 0.05). A correlation analysis showed that seed germination is negatively related to Hg in soil (r = –0.843, p = 0.05). No adverse effects were observed on root length at 0.1 and 0.2 mg kg–1. A slight improvement in root length was obtained at 0.4 mg kg–1. A concentration-dependent decrease in root length was also observed at Hg >0.8 mg kg–1 (p < 0.05). A correlation analysis showed that root length is also negatively related to Hg in soil (r = –0.797, p = 0.05). In comparison with the control, the root biomass significantly increased by 30%–10% at 0.1–0.8 mg kg–1, respectively. A significant reduction was noted at 1.6 mg kg–1 (p < 0.05). Correlation analyses revealed a significant negative correlation between root biomass and Hg in soil (r = –0.862, p = 0.05).

Table 1. Effects of Cd exposure on root growth of Solanum lycopersicum at different concentrations (n = 3).

mg kg–1 Seed germination (%) Root length (mm) Root biomass (mg)
0 95.56 ± 1.92a 22.3 ± 1.9ab 2.02 ± 0.22bcd
0.1 94.44 ± 1.92a 24.0 ± 1.7ab 2.65 ± 0.32a
0.2 97.78 ± 1.92a 21.6 ± 2.7ab 2.23 ± 0.31abc
0.4 94.44 ± 1.92a 25.8 ± 3.4a 2.33 ± 0.21ab
0.8 93.33 ± 0.00ab 20.1 ± 1.4bc 2.27 ± 0.27abc
1.6 87.78 ± 1.92bc 19.8 ± 1.7bc 1.86 ± 0.12cd
3.2 82.22 ± 6.93c 16.4 ± 3.3cd 1.77 ± 0.13d
6.4 93.33 ± 3.33c 16.6 ± 2.3cd 1.75 ± 0.19d
12.8 70.00 ± 6.67d 14.9 ± 0.4e 1.23 ± 0.24e
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Effect of Hg on root morphology

Fig. 2 presents scanning electron microscopy (SEM) micrographs of the root surface of S. lycopersicum exposed to different Hg concentrations for seven days. The entire root structure of S. lycopersicum was not significantly altered at 0.1, 0.2 and 0.4 mg kg–1 regarding surface appearance compared with the control (Fig. 2a–d). Root hair length and density were significantly reduced at 0.8 and 1.6 mg kg–1 (Fig. 2e and f). Roots with a smooth surface had few root hairs at 3.2 mg kg–1 (Fig. 2g). The largest amount of root structure and integrity were ruptured, and root hair growth was inhibited at 6.4 and 12.8 mg kg–1 (Fig. 2h and i).

Fig. 2. Effects of Hg exposure on the root morphology of Solanum lycopersicum at different concentrations. Bar = 0.5 mm. a. 0 mg kg–1; b. 0.1 mg kg–1; c. 0.2 mg kg–1; d. 0.4 mg kg–1; e. 0.8 mg kg–1; f. 1.6 mg kg–1; g. 3.2 mg kg–1; h. 6.4 mg kg–1; i. 12.8 mg kg–1.

Fig. 2

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Identification of Hg-responsive genes

Identification of chromium, cadmium, lead and mercury specific genes has been conducted using microarray analysis at 1/10 LC50 in a previous study.26 The data have been deposited in the Gene Expression Omnibus with GEO Series accession number GSE63024. Genes that meet the listing criteria can be selected and used as candidate Hg stress biomarkers: firstly, 1594 genes for Hg stress with fold change >2.0 and p-value <0.05 were identified (Table S1†); secondly, a total of 192 genes for Hg stress but not for chromium, cadmium, and lead were identified using a Venn diagram (Table S2†); and thirdly, 12 Hg-responsive genes with the highest expression level were selected to investigate their concentration-dependent responses. General information on the twelve genes is presented in Table 2.

Table 2. Twelve Hg-responsive genes identified from a microarray.

  Probe ID Gene ID Gene name FC p-Value
a A_96_P012601 606304 Ripening-related ACC synthase 2 47.8369 0.01135
b A_96_P045476 101244300 Probable glutathione S-transferase parA 11.5512 0.04208
c A_96_P020896 101248167 Nucleobase-ascorbate transporter 12 10.0754 0.02235
d A_96_P228059 101250592 Monothiol glutaredoxin-S1-like 7.8980 0.01058
e A_96_P010486 101243766 Chlorophyll a–b binding protein 13, chloroplastic-like 5.8064 0.01761
f A_96_P054641 778310 Geranylgeranyl pyrophosphate synthase 1 4.3898 0.01956
g A_96_P020931 543800 1-Aminocyclopropane-1-carboxylate oxidase 0.1488 0.04254
h A_96_P260192 544060 Leucine-rich repeat extensin-like protein 6 0.2286 0.00846
i A_96_P054346 101260125 Metalloendoproteinase 1 0.2431 0.00127
j A_96_P084094 543756 Glutamine synthetase cytosolic isozyme 1-1 0.2726 0.01936
k A_96_P229619 101252553 Probable calcium-binding protein CML18 0.2750 0.00081
l A_96_P040816 100301907 Stress-associated protein 11 0.2887 0.00264
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Identification of Hg-responsive genes

The twelve Hg-responsive genes were studied to examine their concentration-dependent responses at different Hg concentrations. Primers for Hg-responsive genes are presented in Table 3.

Table 3. Primers designed for Hg-responsive genes.

Gene name Product size Primer sequences (5′–3′)
Ripening-related ACC synthase 2 123 bp F: cgtctcgcctggatcttcgt
R: tcaacacctacgaacctccga
Probable glutathione S-transferase parA 140 bp F: tggaaggacaaagctccactct
R: gctgcctcttgagcttcacc
Nucleobase-ascorbate transporter 12 115 bp F: tggtggtggaggagtggcta
R: tcttcgagacggctgctgag
Monothiol glutaredoxin-S1-like 149 bp F: agatgggagcacaaagtccagt
R: tgccctctctaattccttccca
Chlorophyll a–b binding protein 13, chloroplastic-like 123 bp F: ccttgcggatgaccctacca
R: agagggcctttaccggtaaca
Geranylgeranyl pyrophosphate synthase 1 102 bp F: ggcagattgtggacttggcg
R: ccacagcagcctccaaaagc
1-Aminocyclopropane-1-carboxylate oxidase 86 bp F: tttcaggcagcaagggtcct
R: gcgcaatcccctgaccaaat
Leucine-rich repeat extensin-like protein 6 136 bp F: ccgccgccacctaaatcaac
R: gtgagggtggaggaggtgaa
Metalloendoproteinase 1 140 bp F: agagtggagctggtggagga
R: actgagctacgaatcggggc
Glutamine synthetase cytosolic isozyme 1-1 109 bp F: tgcggaaaggcttttggacg
R: cccactgtccaggcatcact
Probable calcium-binding protein CML18 119 bp F: acgccgaggatgaaggaagt
R: ggcgtcgttttagtgccgag
Stress-associated protein 11 146 bp F: ccctgctgatcacgcctgta
R: tcgcagggcttggagatgag
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The expression of the ripening-related gene ACC synthase 2 (ACS2) significantly increased at 1.6 and 6.4 mg kg–1 (Fig. 3a). Similarly, the expression of the probable calcium-binding protein CML18 (CML18) significantly decreased at 1.6 and 6.4 mg kg–1 (Fig. 3k). The expression levels of probable glutathione S-transferase parA (PGSTP), chlorophyll a–b binding protein 13, chloroplastic-like (Ca-bBP13) and geranylgeranyl pyrophosphate synthase 1 (GGPS1) exhibited concentration-dependent increases, and these genes were up-regulated in all the Hg treatments compared with the control (Fig. 3b, e and f). The expression levels of nucleobase-ascorbate transporter 12 (NAT12), monothiol glutaredoxin-S1-like (MGS1) and metalloendoproteinase 1 (MLP1) were increased at first and decreased subsequently. The maximum value appeared at 1.6, 1.6 and 3.2 mg kg–1, respectively (Fig. 3c, d and i). In contrast, 1-aminocyclopropane-1-carboxylate oxidase (ACO5) expression increased only at 3.2 mg kg–1 (Fig. 3g). The relative expressions of leucine-rich repeat extensin-like protein 6 (LRRELP6), glutamine synthetase cytosolic isozyme 1-1 (GSCI1-1) and stress-associated protein 11 (SAP11) exhibited no regularity changes with the increase of Hg in soil (Fig. 3h, j and l).

Fig. 3. Relative expression of Solanum lycopersicum genes with increasing Hg concentrations. a. Ripening-related ACC synthase 2 (ACS2); b. probable glutathione S-transferase parA (PGSTP); c. nucleobase-ascorbate transporter 12 (NAT12); d. monothiol glutaredoxin-S1-like (MGS1); e. chlorophyll a–b binding protein 13, chloroplastic-like (Ca-bBP13); f. geranylgeranyl pyrophosphate synthase 1 (GGPS1); g. 1-aminocyclopropane-1-carboxylate oxidase (ACO5); h. leucine-rich repeat extensin-like protein 6 (LRRELP6); i. metalloendoproteinase 1 (MLP1); j. glutamine synthetase cytosolic isozyme 1-1 (GSCI1-1); k. probable calcium-binding protein CML18 (CML18); and l. stress-associated protein 11 (SAP11).

Fig. 3

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Pearson's correlation analyses revealed that no linear relationship was observed for ACS2, NAT12, MGS1, ACO5, LRRELP6, MLP1, GSCI1-1, CML18 and SAP11 with increasing Hg concentration. However, a positive correlation between Hg in soil and the relative expression of PGSTP (r = 0.637, p = 0.05), Ca-Bbp13 (r = 0.689, p = 0.05) and GGPS1 (r = 0.682, p = 0.05) was observed (Table 4).

Table 4. Correlation analysis between Hg in soil and relative expression of twelve genes.

  Hg concentration in soil   Hg concentration in soil
ACS2 0.091 ACO5 0.121
PGSTP 0.637** LRRELP6 0.176
NAT12 0.109 MLP1 –0.251
MGS1 –0.254 GSCI1-1 –0.215
Ca-bBP13 0.689** CML18 0.200
GGPS1 0.682** SAP11 0.374
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Discussion

In the present study, we present the responses of S. lycopersicum root growth to Hg stress, and the LOAECs of Hg for root growth were established. A significant reduction in root biomass was derived from 1.6 mg kg–1, whereas inhibition of root length and seed germination was noted at 0.8 mg kg–1, suggesting that the seed germination and root length of S. lycopersicum were more sensitive to Hg stress than root biomass. The sensitivity of seed germination or root length to Hg stress has been demonstrated in numerous previous studies.27–29 Moreover, Hg enhanced the growth of S. lycopersicum root biomass at low Hg concentrations. Numerous studies have reported the promoting effect of Hg on plant biomass.30–32

The morphological changes of S. lycopersicum roots were observed by SEM. The formation of root hair is stress-sensitive as previously reported.33,34 Minerals and nutrients move upward mainly through root hair; therefore, sparser and shorter root hairs may limit the absorption of minerals and nutrients.35 Hg supply affects the development of root hairs in Trigonella foenum-graecum L.,36Cymopsis tetragonoloba,37 and Medicago sativa.38 Roots treated with 12.8 mg kg–1 can cause the disruption of vascular bundles, thus inhibiting the nutrients’ upward movement to the aerial portion of the plant.

The LOAECs of Hg were 0.8 mg kg–1 for seed germination, 1.6 mg kg–1 for root biomass, 0.8 mg kg–1 for root elongation, and 0.8 mg kg–1 for root morphology, respectively, whereas the lowest Hg treatments (0.1–0.4 mg kg–1) could generally induce the differential expression of genes. These results indicated that the detection of Hg in soil at the molecular level is a highly sensitive method. Correlation analyses indicated that the relative expressions of PGSTP, Ca-Bbp13 and GGPS1 showed a concentration-dependent alteration; therefore, the three genes appear to be good candidates as biomarkers of Hg-contaminated soil.

PGSTP is a gene in the glutathione S-transferases (GSTs) gene family. Plant GSTs are commonly induced by herbicide,39 dehydration,40 pathogen attack,41 hypoxic stress,42 and heavy metal stress. The differential expression of the GST gene induced by heavy metals has been previously reported in different plant species. GSTs are detoxification enzymes that play key roles in the detoxification of exogenous toxic compounds by catalyzing the conjugation of cytotoxic or electrophilic substrates to the tripeptide glutathione (GSH).39,43,44 GSH, the tripeptide γ-glutamylcysteinyl-glycine, is important for the processes of redox buffering and detoxification.45 An increase in GST was observed in rice seedlings after exposure to 25 μM Hg and in Medicago truncatula after exposure to 10 μM Hg.46,47 GSTs play a major role in plant defense against ROS during heavy metal toxicity. A significantly increased GST activity was recorded even at lower metal concentrations, making GST a good biomarker of metal stress.48 Meanwhile, significant correlations between the expression level of PGSTP and heavy metal concentration were observed in roots of S. lycopersicum. Therefore, PGSTP in S. lycopersicum can be used as a potential molecular biomarker of Hg contamination in soil.

Chlorophyll a–b binding protein 13, chloroplastic-like (Ca-bBP13) is a member of the light-harvesting chlorophyll a/b-binding (LHC) gene family that is synthesized in the cytosol, imported post-translationally into the chloroplasts, and inserted into the thylakoid membranes.49 As a modular antenna system, the collection and transfer of light energy to the reaction centres of photosystem I (PSI) were achieved by energy dissipation of LHCs.50 LHCs enable Arabidopsis thaliana to balance light harvesting by PSI and PSII.51 The LHC proteins are commonly present in higher plants and some bacteria.52 Previous studies reported that LHCs play essential roles in the adaptation of plants to various environmental stresses.53 By analyzing the expression changes in the transcriptome and sense/antisense genes in Medicago truncatula, Ca-bBP was found to be enriched with Hg treatment,54 implying an increase of the content of chlorophyll a–b binding protein. The capacity for photosynthesis in this species is increased under the stress of Hg, which may be beneficial to the defence of M. truncatula against heavy metal stress. Several investigations reported that Hg treatment induced a decline of chlorophyll a and b in plants.55,56 However, the treated concentrations in these reports were significantly higher than those in the present study. Ca-bBP13 may be a major factor responsible for heavy metal tolerance. In our study, Ca-bBP13 expression in roots tended to be up-regulated with increasing Hg concentration, suggesting that Ca-bBP13 in S. lycopersicum roots might be selected as a Hg stress biomarker.

Geranylgeranyl pyrophosphate synthase 1 (GGPS1) is a key enzyme that plays a vital role in plant growth and development.57 GGPS catalyzes the biosynthesis of 20-carbon geranylgeranyl pyrophosphate (a precursor for chlorophylls, carotenoids, and geranylgeranylated proteins) by a condensation reaction of isopentenyl pyrophosphate with farnesyl pyrophosphate.58,59 As one of the isoprenoids in the mevalonate pathway, GGPS participates in the regulation of cell apoptosis through the flow of isoprenoid towards the carotenoids to stabilize cell membranes and prevent cell death caused by ethanol.60,61 Two GGPS genes in S. lycopersicum are predominantly expressed in ripening fruit, leaf tissue, and flower tissue.62,63 In plants, GGPS was confirmed to be related to abiotic stresses64 and wounding.65 Fewer reports indicate that the gene is associated with heavy metal stress. Long-term cadmium exposure of tomato Solanum lycopersicum leaves induced a change in the expression level of GGPS, implying the active response of this gene to heavy metals.66 Our data support this conclusion. GGPS expression was promptly up-regulated with increasing Hg concentration in S. lycopersicum, suggesting that GGPS may be one of the candidate genes for Hg stress.

Conflicts of interest

There are no conflicts of interest to declare.

Supplementary Material

Click here for additional data file. (192KB, xlsx)
Click here for additional data file. (34.1KB, xlsx)

Acknowledgments

Financial support from the National Basic Research Program of China (2013CB430400), the National Natural Science Foundation of China (21377013), and the Fundamental Research Funds for the Central Universities (2016ZZD06) is acknowledged.

Footnotes

†Electronic supplementary information (ESI) available. See DOI: 10.1039/c6tx00210b

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