Proteomic analysis reveals key proteins in seed germination of Cyclobalnopsis gilva

Proteomic analysis reveals key proteins in seed germination of Cyclobalnopsis gilva

Biochemical Systematics and Ecology 83 (2019) 106–111 Contents lists available at ScienceDirect Biochemical Systematics and Ecology journal homepage...

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Biochemical Systematics and Ecology 83 (2019) 106–111

Contents lists available at ScienceDirect

Biochemical Systematics and Ecology journal homepage: www.elsevier.com/locate/biochemsyseco

Proteomic analysis reveals key proteins in seed germination of Cyclobalnopsis gilva

T

Madiha Zaynaba, Dezhuo Pana, Mahpara Fatimab, Ali Nomanb, Shipin Chenc,∗∗, Wei Chena,∗ a

College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou, 350002, PR China College of Crop Science, Fujian Agriculture and Forestry University, Fuzhou, 350002, PR China c College of Forestry, Fujian Agriculture and Forestry University, Fuzhou, 350002, PR China b

ARTICLE INFO

ABSTRACT

Keywords: Ecosystem Gene expression mRNA Starch Two-dimensional electrophoresis

Trees dominate the structural and functional dynamics of many temperate and tropical forest ecosystems and are of considerable scientific and social interest. The effective ecological restoration of abandoned agricultural fields, especially of highly degraded ecosystems, remains a challenge. Germination is imperative to restore natural ecosystems and to save the environment. Low germination rate is key player to disturb the ecosystem. Cyclobalnopsis gilva is an economically important woody plant, however its germination rate is less than 50% in its natural habitats compared to that of other plants. A comparative proteomics approach was carried out to investigate this feature on germinated and non-germinated seeds of C. gilva. Proteins from seeds of C. gilva were extracted using phenol extraction, separated by two-dimensional electrophoresis, and identified through matrixassisted laser desorption ionization-time of flight/time of flight mass spectrometry. In addition, the results of proteome were verified through the RT-qPCR determination. More than 700 proteins were reproducibly detected. Among 26 proteins with 2-fold changes in abundance, the 24 differential proteins were identified successfully. Many differential proteins were involved in starch metabolism. β-amylase abundance and mRNA level were both up-regulated in germinated seeds of C. gilva. An important point to provides new insights into the understandings of C. gilva seed germination problems are found through 2-DE and RT-qPCR analyses to save the forest ecology and solve the problem of woody plants with low germination rate all over the world.

1. Introduction Woody plants species are a key biological group for forest ecosystems since they are responsible for their architecture, which subsequently determine many of the ecological conditions found within forest. Different physio-biochemical processes contribute to appropriate seed germination (Noman et al., 2015). In addition to physio-biochemical changes, cascade of gene expression regulation and signal transduction are significance during seed germination (He and Yang, 2013). Seed germination and dormancy are adaptive characteristics of spermatophytes. Both of these are substantially affected by inherent traits and environmental factors (Koornneef et al., 2002). Molecular techniques parallel with genetic studies are excellent tools to analyze both seed dormancy and germination. In earlier studies, Arabidopsis and rice have been preferentially used as regulatory and metabolic network models to study germination processes and associated events at molecular level (Bassel et al., 2011; He et al., 2011).



Transcriptomic analysis of seed germination have also been performed in other crops like maize (Jiménez-López et al., 2011), wheat (Yu et al., 2014) and barley (Sreenivasulu et al., 2008). Besides identification of genes and their successive cloning, genes regulating seed germination or dormancy can also be distinguished from others on account of their specialized expression pattern (Koornneef et al., 2002). This may focus upon a fair search of germination-specific gene expressions or genes with assumed roles in seed germination. However, gene function is ultimately determined through its product i.e. protein. Therefore, it is imperative to study dynamic changes during seed germination at the proteome level for a deeper understanding of physiological and biochemical features of seed germination. Over the last two decades, proteomics have gained importance in identifying several plant proteins. Two-dimensional gel electrophoresis (2-DE) is one of the valuable techniques for separating several proteins at the same time (Østergaard et al., 2004). Presently, proteomics data about germination of woody plant seeds is very limited. It is a fact that

Corresponding author. Corresponding author. E-mail addresses: [email protected] (S. Chen), [email protected], [email protected] (W. Chen).

∗∗

https://doi.org/10.1016/j.bse.2019.01.003 Received 10 September 2018; Received in revised form 4 January 2019; Accepted 5 January 2019 Available online 23 January 2019 0305-1978/ © 2019 Published by Elsevier Ltd.

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wild species exhibit stronger dormancy as compared to cultivated plants (Koornneef et al., 2002). Cyclobalnopsis gilva belongs to Fagaceae, a woody plant which is native to East Asia and especially abundantly found in Japan and China. The species, due to its hard wood, is good for making expensive furniture. However, the germination rate of C.gilva seeds is less than 50% in its natural habitat. Low germination rate ultimately decreases its density, population and productivity (Zaynab et al., 2017). Therefore, it is very important to get insights into the changes in cellular, molecular and physio-biochemical processes affecting germination of C. gilva. To our knowledge, this study is the first to employ proteomics approach to investigate the reasons for low seed germination rate in C. gilva. The analyses of the differentially expressed proteins between germinated and non-germinated seeds unveil the causes of low germination in C. gilva seed, and also provide a theoretical basis for improving the seed germination of woody plants in the future.

tetraborate decahydrate, 50 mM L-ascorbic acid, 0.5% (v/v) Triton X100, 2% (v/v) β-mercaptoethanol, 1 mMphenylmethyl sulfonyl fluoride and 100 mM Tris-HCl, pH 8.0. Ice-cold Tris-HCl saturated phenol was added to the solution in equal volumes. Suspension was mixed on vortex and re-homogenized on ice prior to centrifugation at 5,500 g at 4 °C for 10 min. Subsequently, the mixture was transferred to second tube. Six-fold 100 mM ammonium acetate/methanol was added. The material was incubated overnight followed by centrifugation at 20,000×g for 10 min at 4 °C. Pellets were washed with cold methanol and then with acetone containing 0.07% (v/v) β-mercaptoethanol. The protein concentration was determined by the Bradford assay with bovine serum albumin (BSA) as the standard. 2.3. 2-DE analysis of proteins The powdered samples (10 mg) were solubilized in 300 mL of lysis buffer (7 M urea, 2M thiourea, 0.05% (v/v)IPG buffer pH4-7, 4% (m/v) Cholamidopropyldimethylammonio-1-propanesulfonate (CHAPS) and 40 mM Dithiothreitol (DTT) and incubated at 37ᵒC for 2 h. 2-DEwas performedin accordance with a method previously described by (Wang et al., 2015). IPG phorII (Amersham Biosciences) iso-electric focusing (IEF) system was used for first dimensional electrophoresis. IPG dry strips (pH 4–7, 24 cm length, linear) were rehydrated at 30 V for 12 h at 24 ᵒC with 150 μL lysis buffer mixed with 300 μL rehydration solution (2M thiourea,7 M urea, 2% CHAPS, 0.002% Bromophenol Blue, 0.5% IPG buffer, and 40 mM DTT). After the rehydration, IEF was performed under the following conditions: 200 V for 1 h, 500 V for 1 h, 1 kV for 1 h, gradient 8 kV for 0.5 h, and 8 kV up to 40,000 Vhs. The strips were equilibrated twice before SDS-PAGE: (i) in reducing equilibration buffer (6 Murea, 3 0% (v/v) glycerol, 50 mM Tris–HCl pH 8.8,2% (w/v)SDS, 1.0% (w/v)DTT, and a trace of Bromophenol Blue), for 15 min and (ii) in equilibration buffer containing 2.5% (w/v) iodoacetamide instead of

2. Materials and methods 2.1. Plant materials Cyclobalnopsi gilva, seeds were sampled from Fujian province in China. Seeds were sown in wet sand for 60 days in three replicates from December 2016 to February 2017, but not control (Control) seed. Germinated (SG) and non-germinated (NG) seeds were collected (Fig. 1) and immersed in liquid N2 and then stored at −80 °C for later analysis. Meanwhile, seed germination rate was analyzed. 2.2. Protein extraction Phenol extraction assay was used for protein extraction. Each sample of C. gilva seeds (3 g) were ground in liquid nitrogen with 12 mL of cooled extraction buffer containing100 mM KCl, 50 mM disodium

Fig. 1. Photos of C. gilva seeds at three growth stages. Control; NG, nongerminated seeds; SG, germinated seeds. 107

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Table 1 Germination rate of C. gilva seeds. Groups 1 2 3 Mean ±

Number of germinated seed 40 47 39 SD

Number of Nongerminated seed

Germination rate (%)

68 68 72

37.04 40.87 35.14 37.68 ± 2.92

1.0% (w/v) DTT for 15 min. The strips were then transferred onto vertical 12.5% SDS-PAGE self-cast gels. An Ettan DALT-six System (Amersham Biosciences) was used to perform the SDS-PAGE at 18ᵒC using: 15 mA for 30min and 30 mA for 12 h for every strip. Coomassie Brilliant Blue (CBB) R-250 was used to stain the gel after 2-DE. With the help of image scanner (EPSON PERFECTION 2480 PHOTO), the gel was scanned at 300 dpi and analyzed with Image Master™ 2D Platinum software (Version 5.0; Amersham Biosciences). According to the software guide, spots were detected, matched, and normalized on the basis of total gel density with the parameter of percent volume. 2.4. In-gel tryptic digestion From the CBB-stained gels, the protein spots were manually excised and transferred to V-bottom microplates containing 100 μL of 50% acetonitrile (ACN) and 25 mM ammonium bicarbonate solution per well. Later, gel plugs were dehydrated with 100 μL of 100% ACN for 20min and thoroughly dried for 30 min using a SpeedVac concentrator (Thermo Savant, USA). The dried gel particles were rehydrated with 2 μL/well trypsin at 4 °C for 45min (Promega, Madison,WI, USA) and then incubated at 37 °C for 12 h. After trypsin digestion, the peptide mixtures were extracted with 8 μL extraction solution [containing 50% ACN and 0.5% trifluoroacetic acid (TFA)per well at 37 °C for 1 h. Finally, the extracts were dried in liquidN2. 2.5. Protein MALDI-TOF/TOF-MS analysis The peptides were eluted with 0.8 μL matrix solution (α-cyano-4hydroxy-cinnamic acid (CHCA, Sigma, St. Louis,MO, USA) in 0.1%TFA, 50% ACN) before spotting on targeting plates. The samples were placed in liquid N2 and air-dried with a Speed Vacuum. The dried peptides were analyzed by AB SCIEX 5800 MALDI-TOF/TOF Proteomics Analyzer (AB SCIEX, Foster City, CA) and raw MS and MS/MSspectra were submitted to MASCOT (V2.1, Matrix Science, London, U.K.) using GPS Explorer software (V3.6, Applied Biosystems, Foster City, CA) as described by Wang et al. (2015). The search parameters were as following: NCBInr database (release date: 2015.04.01), taxonomy restrictions to viridity plantae, trypsin digest with one missing cleavage, none fixed modifications, MS tolerance of 0.2 Da, MS/MS tolerance of 0.6 Da, and possible oxidation of methionine. The individual MS/MS spectrum with statistically significant (confidence interval > 95%) best ion score (based on MS/MS spectra) was accepted. To avoid the redundancy in detected proteins that appeared in the database with different names and accession numbers, a single protein member was first chosen according to the corresponding theoretical and experimental MW/pI, and then the highest protein and finally a protein score (top rank) was singled out from the multi-protein family.

Fig. 2. Two-dimensional gel electrophoresis of total protein of C. gilva seeds at three stages. C, control seeds; NG, nongerminated seeds; G, germinated seeds. Spot numbering refers to.

5 s and 60 °C for 30 s. The whole thermocycling processes were conducted in a BioRad CFX96 real-time PCR detection system. An Actin gene was chosen as the internal standard to normalize gene expression. β-amylase primer used here is shown as forward primer: GGAAAGAG CCCTAACCA and reverse primer: CGGCGAGTGAAGGAAAT; ATP synthase primer used here is shown as forward primer: TTTACAATCCGA AGACC and reverse primer: ACACTGGAACTGA GACAC. Gene expression was quantitated using the 2−ΔΔCt method (Livak and Schmittgen, 2001). Each data point represents an average ± standard deviation (SD) of three repeated experiments.

2.6. Real-time quantitative PCR (RT-qPCR) analysis Total RNA was extracted from the C.gilva seed with rapid CTABbased method. One μg RNA was used to synthesize the corresponding cDNA using a PrimeScript™ RT reagent kit with a gDNA Eraser (TaKaRa, Japan) in accordance with the manufacturer's instructions. RT-qPCR was conducted using SYBR Premix Ex Taq™ (Tli RNaseH Plus) kit (TaKaRa, Japan) at 95 °C for 30 s, followed by 40 cycles at 95 °C for

2.7. Statistical analysis Data were measured from three biological replicates and the results 108

Protein name

109

Castanea Castanea Castanea Castanea Castanea Castanea Castanea Chaetomorphavalida Chaetomorpha valida Chaetomorpha valida Theobroma cacao Theobroma cacao Phoenix dactylifera Populus nigra Eucalyptus camaldulensis Pyrusxbretschneideri Genlisea aurea Oryza barthii Zea mays Araucaria cunninghamii Triticum urartu

R4IW40_CASSA R4IW40_CASSA E3SET9_CASSA R4IW40_CASSA R4IW40_CASSA E3SET8_CASSA E3SET8_CASSA V5K459_9CHLO 5K459_9CHLO 5K459_9CHLO A0A061GYB4_THECC A0A061ELA5_THECC G9HNT8_PHODC O82158_POPNI Q0MW07_EUCCA W8SZF8_9ROSA S8C859_9LAMI A0D3FEA5_9ORYZ K7WEL8_MAIZE A0D6R9P2_ARACU |M8AYN2_TRIUA

sativa sativa sativa sativa sativa sativa sativa

Castanea crenata Glycine max Glycinesoja

Species

Q9AT14_CASCR I1JJP2_SOYBN A0A0B2SX31_

Accessionb

24 22 32 7 28

13

23 16 32 15 10

11

16 11

10 9 8 11 9 6 6

16 25 22

MPc

14 12 15 13 13 9 9

20 34 19

Cov%d

36

22 18

35 46 29 16 42

22

25 24 48 31 34

61128/5.05 34869/6.90 86.115/6.63 37.534/5.17 60.894/6.40

30.340/5.56

89.452/5.13 56.169/6.58 55.258/6.02 42.460/5.83 24.797/5.36

52.354//6.15

52.354/6.15 52.354/6.15

60.979/5.77 60.979/5.77 60.703/5.85 60.979/5.77 60.979/5.77 60.803/5.93 60.803/5.93

58.292/5.07 56.312/6.30 110.432/5.35

Theor. Mr.(kDa)/pIe

± ± ± ± ± ± ±

0.249a 0.051a 0.012b 0.006a 0.042b 0.121c 0.063b

± ± ± ± ±

0.000a 0.004b 0.010b 0.012b 0.028b

0.180. ± 0.006a 0.049 ± 0.005a 0.046 ± 0.007a 0.083 ± 0.007b 0.213 ± 0.033a

0.180 ± 0.001a

0.021 0.069 0.099 0.062 0.098

0.075 ± 0.032c

0.069 ± 0.013a 0.027 ± 0.003a

1.561 0.532 0.051 0.311 0.416 0.159 0.167

0.006 ± 0.003b 0.081 ± 0.015a 0.211 ± 0.036a

Control

Protein abundancef

± ± ± ± ± ± ±

0.098b 0.057b 0.053a 0.054a 0.041b 0.362a 0.137a

± ± ± ± ±

0.001c 0.030b 0.026c 0.011b 0.015b

0.077 0.062 0.037 0.097 0.235

± ± ± ± ±

0.001b 0.009a 0.003a 0.014b 0.0413a

0.107 ± 0.015b

0.009 0.088 0.058 0.089 0.121

0.103 ± 0.011b

0.035 ± 0.010b 0.009 ± 0.000c

0.682 0.199 0.112 0.340 0.463 0.683 0.368

0.007 ± 0.001b 0.028 ± 0.001b 0.099 ± 0.051c

NG

± ± ± ± ± ± ±

0.020c 0.015b 0.002a 0.000b 0.024a 0.248b 0.084a

± ± ± ± ±

0.001b 0.042a 0.014a 0.027a 0.039a

0.041 0.024 0.020 0.175 0.074

± ± ± ± ±

0.011c 0.003b 0.003b 0.024a 0.002b

0.087 ± 0.020b

0.014 0.138 0.126 0.154 0.199

0.158 ± 0.014a

0.025 ± 0.003b 0.016 ± 0.006b

0.309 0.056 0.119 0.040 0.834 0.321 0.344

0.013 ± 0.001a 0.026 ± 0.010b 0.140 ± 0.093b

SG

b

Numbering corresponds to the 2-DE gel in Fig. 2. Accession from the NCBInr database. c Number of matched peptides. d Percentage of predicated protein sequence with matched sequence. e Theoretical mass (kDa) and pI of identified proteins. f Protein abundance is expressed as a vol% of C. gilva seeds, and each value represents the mean ± SD of three biologically independent measurements. Different letters indicate significant differences at P < 0.05. C, control seeds; NG, nongerminated seeds; SG, germinated seeds.

a

Starch metabolism 3 Beta-amylase 5 Glucose-1 Phosphate 14 Alpha1,4 Glucan Phosphorylase Storage protein 7 11S globulin isoform 3 8 11S globulin isoform 3 9. 11S globulin isoform 2 10 11S globulin isoform 3 11. 11S globulin isoform 3 12 11S globulin isoform 1 13 11S globulin isoform 1 Photosynthesis Protein 2. Ribulose bisphosphate carboxylase 16. Ribulose bisphosphate Carboxylase 20. Ribulose bisphosphate Carboxylase large chain Energy metabolism 1 ATPase, AAA-type, 18 Adenosylhomocysteinase 19. ATP synthase subunit alpha 21. Phosphoglycerate kinase 24 Ascorbate Peroxidase 25. Ferritin Unknown Protein 6 Uncharacterized protein 15 Uncharacterized protein 17 Uncharacterized protein 22 Uncharacterized protein 26 Uncharacterized protein

Spot No.a

Table 2 Identification of differentially expressed proteins in C. gilva seeds by MALDI-TOF/TOF-MS.

M. Zaynab et al.

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related proteins (13%), (v) unknown function (21%). Interestingly, among 24 differentially expressed proteins identified successfully, some essential enzymes likeATPase, AAA-type (spot 1), β amylase (spot 3) and ATP synthase (spot19) were more abundant in G group. 3.3. Correlations between mRNA and protein expression levels To determine correlation between the expression levels of proteins protein and their mRNA content, we used RT-qPCR analysis to examine genes expression of ATP synthase and β amylase encoding proteins for energy and starch metabolism, respectively. As shown in Fig. 4, compared with Control group, the expression levels of ATP synthase and β amylase were remarkably up-regulated in SG group, while they were not significantly changed in NG group. Their expression patterns in SG group were consistent with those detected by 2-DE.

Fig. 3. Functional classification of differential proteins identified from seed of C. gilva.

4. Discussion

were presented as mean ± standard deviation (SD) of the three repeated measurements. Differences among groups were compared by ANOVA. Significance was defined at P < 0.05.

4.1. Identification of starch related protein As a core event in life cycle of plants, seed germination establishes the basis for next generation (Bewley, 1997; Zhang et al., 2017). Success of germination depends upon environmental conditions and genetic architecture of plant. Second phase of seed germination is more important among three stages as necessary physiological processes and metabolic pathways are activated before germination (Zaynab et al., 2017). In germination related metabolic pathways, important roles are played by various enzymes like α- and β-amylases which take part in starch biodegradation. Both of these enzymes are present in inactivated form in seed. Enzyme β-amylase is activated during second phase of germination while after germination, α-amylase is activated by GA signaling cascade (He and Yang, 2013). During our 2-DE gel analysis, no significant changes in α-amylase were found between non-germinated and germinated seeds, while β-amylase abundance in germinated seeds was significantly increased. We confirmed these results by RTqPCR. These results indicates that major reason for low germination of C. gilva in natural environment is insignificant α-amylase activity and low protein abundance. After imbibition, β-amylase catalyzes the conversion of starch to glucose and fructose for metabolic, structural and storage functions in plant cells. The up-regulation in gene expression and the increased enzyme activity of β-amylase in germinated seeds signifies its functional role in germination. Therefore, we suggest that β-amylase is a key

3. Results 3.1. Germination rate of C. gilva seeds To investigation seed germination rate, seeds were sown in wet sand in an open field with white plastic film roof (4 m length × 2 m width × 1 m height) for 60 days with average temperature 16 °C and humidity 60%. The germination rate of C. gilva seeds was found to be as low as 37.68% in this study (Table 1). 3.2. Identification and functional analysis of differentially expressed protein Total protein samples extracted from seeds were analyzed by 2-DE. More than 700 protein spots were detected across three independent gels replicates (Fig. 2). Image Master 5.0 was used to analyze relative intensity of observed protein spots. We found that twenty-six differentially expressed proteins were changed greater than 2-fold in abundance among three groups. Of which 24 proteins were identified by using MALDI-TOF/TOF-MS analysis (Table 2). These identified proteins were categorized into the following five categories base on their putative physiological functions (Fig. 3): (i) starch metabolism (12%), (ii) energy metabolism (21%), (iii) storage (33%), (iv) photosynthesis

Fig. 4. mRNA expression levels of ATPase and BAM in C. gilva seeds. ATP synthase;, β-amylase; C, control seeds; NG, non-germinated seeds; SG, germinated seeds. Different lowercase letters indicate significant differences between three samples (P < 0.05).

110

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player in starch degradation during seed germination in C. gilva. This is consistent with a previously established observation by (Yamasaki, 2003).

Appendix A. Supplementary data Supplementary data to this article can be found online at https:// doi.org/10.1016/j.bse.2019.01.003.

4.2. Identification of energy related proteins

References

Generally, respiration is an essential process during seed germination. Phosphoglycerate kinase (PGK) is an enzyme that catalyzes a reversible transfer of a phosphate group from 1,3-bisphosphoglycerate to ADP producing 3-phosphoglycerate and ATP in the glycolysis (Xu et al., 2016; Zaynab et al., 2018a). Previous studies on rice germination reported that glycolytic enzymes, glycolysis rate and energy production are the major determinants of a successful seedling development (Chen et al., 2014; Nakagami et al., 2010). In the present study, PGK has been observed to be up-regulated. Due to limited oxygen content, TCA cycle efficiency is curtailed during early germination stages and energy is supplied mainly by glycolysis (Yang et al., 2007; Zaynab et al., 2018b). ATP synthesis is a product of fermentative pathways during the earliest stages of imbibition; ATP synthase subunits alpha are the primary catalytic sites for ATPase (Jänsch et al., 1996). (Chen et al., 2016) have reported thatthe decreased ATPase in oat seeds resulted in a decreasing energy supply and limited seed germination speed.In germinated seeds of C. gilva, the abundance and mRNA level of ATPase both were upregulated, indicating the up-regulation of ATPase fulfilled the required energy demand and ultimately resulted in germination.At the postgermination stage, physiological metabolism became more active through water uptake, and stored reserves are completely exhausted due to ongoing cell division and elongation, well as radicle growth (Bewley, 1997). However, the most notable feature of post-germination stage has been the activation of photosynthesis (Yu et al., 2014). In the present study, RuBisCO (Spot 20) was found to be up-regulated in germinated seeds. Thus, the accumulation of RuBisCO in the germinated seeds serves as a contributing factor to the onset of photosynthesis during the later germination phase. Taken together, these results suggest that the low abundances of phosphoglycerate kinase and RuBisCO in the non-germinated seeds are key factors contributing to low seed germination in C. gilva.

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5. Conclusion Cyclobalnopsis gilva is an economically important tree despite its low germination rate. In this study, we found that the differentially expressed proteins in the germinated and non-germinated seeds were mainly involved in starch metabolism and glycolysis. Consistently, both phosphoglycerate kinase and RuBisCO, had lower abundances in the non-germinated seeds than the germinated ones, and this provides a clue for the low seed germination rate in C. gilva. This study is therefore an important starting point to providing molecular explanations behind the low germination rate of C. gilva seeds. Conflicts of interest The authors declare that they have no conflict of interest. Author contributions W.C. and S. C. contributed to the conception and design of this study; M.Z. and A.N carried out the experiments; M.Z. and P.D. wrote the manuscript; W.C. critically revised the manuscript. Acknowledgement This work was supported by the Industry-University Cooperation Program of Science and Technology Commission Foundation of Fujian Province (Grant No.2016N5003). 111