Expression analysis of microRNAs and mRNAs in myofibroblast differentiation of lung resident mesenchymal stem cells

Differentiation 112 (2020) 10–16

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Expression analysis of microRNAs and mRNAs in myofibroblast differentiation of lung resident mesenchymal stem cells

T

Cong Wanga,b,c,1, Honghui Caoa,c,1, Shen Gua,c, Chaowen Shia,c, Xiang Chena,c, Xiaodong Hana,c,∗ a

Immunology and Reproduction Biology Laboratory & State Key Laboratory of Analytical Chemistry for Life Science, Medical School, Nanjing University, Nanjing, Jiangsu, 210093, China b State Key Laboratory of Natural Medicines and Jiangsu Key Laboratory of Drug Discovery for Metabolic Diseases, Center of New Drug Discovery, China Pharmaceutical University, 24 Tong Jia Xiang, Nanjing, 210009, China c Jiangsu Key Laboratory of Molecular Medicine, Nanjing University, Nanjing, Jiangsu, 210093, China

A R T I C LE I N FO

A B S T R A C T

Keywords: Idiopathic pulmonary fibrosis Lung resident mesenchymal stem cells Myofibroblast differentiation miRNA/mRNA integrated analysis Kruppel-like factor 4

Idiopathic pulmonary fibrosis (IPF) is a serious lung disease that involved the myofibroblast differentiation of lung resident mesenchymal stem cells (LR-MSCs). However, the specific molecular mechanisms of myofibroblast differentiation of LR-MSCs still remain a mystery. In this study, a comprehensive analysis of miRNAs and mRNAs changes in LR-MSCs treated with TGF-β1 was performed. Through computational approaches, the pivotal roles of differentially expressed miRNAs that were associated with tight junction, pathways in cancer, focal adhesion, and cytokine-cytokine receptor interaction were shown. Kruppel-like factor 4 (Klf4) and inhibitor of growth family, member 5 (Ing5) may be the targets for the therapy of pulmonary fibrosis by inhibiting myofibroblast differentiation of LR-MSCs and EMT. Collectively, a molecular paradigm for understanding myofibroblast differentiation of LR-MSCs in IPF was provided by the integrated miRNA/mRNA analyses.

1. Introduction Idiopathic pulmonary fibrosis (IPF) is a severe interstitial lung disease without specific origin (Shinde et al., 2014). The life expectancy after diagnosis is commonly less than 5 years with an extremely poor prognosis for survival (Hiwatari et al., 1991; van den Blink et al., 2000). More and more studies have reported that lung resident mesenchymal stem cells (LR-MSCs) played important role in the occurrence and development of IPF. LR-MSCs can differentiate into several cell types to participate in lung repair. However, LR-MSCs can also contribute to the development of pulmonary diseases via differentiation to myofibroblast, which has been proposed as the main source of ECM within the impaired lungs (Phan, 2008). The differentiation process is highly sensitive to the microenvironment and TGF-β1 is the most important initiator that expressed within the lungs to stimulate LR-MSCs to differentiate into myofibroblasts (Popova et al., 2010; Yan et al., 2007). Therefore, this differentiation behavior of LR-MSCs greatly aggravates the development process of pulmonary fibrosis. The expression of many genes changed during the differentiation process of stem cells and it has been found that there are more genes encoding regulatory RNAs than encoding proteins (Cech and Steitz,

2014). Protein-coding messenger RNAs (mRNAs) are under constant regulation by noncoding RNAs, especially microRNAs (miRNAs) (Fatica and Bozzoni, 2014). miRNAs are an abundant class of small, noncoding RNAs (~22 nt long), which regulate gene expression at the level of stability and translation inhibition of mRNAs (Ambros, 2004). The miRNAs play an important role in cell processes by recognizing the 3′ untranslated region (3′ UTR) nucleotides of their mRNA targets, resulting in degradation or translational repression of the targets genes (Farraj et al., 2011; Krol et al., 2010). Although a few of miRNA gene expression change data are available in lung fibrosis, such as the let-7, miR-21, miR-155 and so on, the networks between the mRNAs and miRNAs in pathogenesis of IPF are largely unknown. Now that the LR-MSCs participate and play an important role in the pulmonary fibrosis, understanding the regulatory mechanism of LRMSCs would be a powerful analytical tool to study the pathogenesis of IPF from the cytological level (Nana-Sinkam et al., 2009; Sessa and Hata, 2013). In the present study, we used integrated analysis of miRNA and mRNA levels between formal LR-MSCs and the differentiated LRMSCs to identify the characteristics of myofibroblast differentiation induced by TGF-β1. These regulatory networks may be important for understanding the complex mechanisms of IPF pathogenesis, as well as

∗

Corresponding author. Immunology and Reproductive Biology Laboratory, Medical School, Nanjing University, Hankou Road 22, Nanjing, 210093, China. E-mail address: [email protected] (X. Han). 1 The first two authors contributed equally. https://doi.org/10.1016/j.diff.2019.11.002 Received 25 June 2019; Received in revised form 17 September 2019; Accepted 17 November 2019 Available online 10 December 2019 0301-4681/ © 2019 Published by Elsevier B.V. on behalf of International Society of Differentiation.

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The animal experiments were performed according to the Guide for the Care and Use of Laboratory Animals (The Ministry of Science and Technology of China, 2006) and all experimental protocols were approved under the animal protocol number SYXK (Su) 2009-0017 by the Animal Care and Use Committee of Nanjing University.

select mRNA/miRNA pairs that were potentially involved in miRNAmediated post-transcriptional regulation. Potential mRNA/miRNA target pairs were identified from the miRecords, miRTarBase, and TargetScan databases. The miRNA/mRNA target pairs were kept for further analysis. The miRBase website was used to translate a probe's name into its most recent form. By using the second derivatives of the mRNA and miRNA fold change, potential target pairs were filtered according to the gene expression data. Specifically, if the second derivatives at the same time point were of opposite signs, a miRNA/mRNA pair was considered a target pair, indicating a divergence in expression during miRNA-mediated post-transcriptional regulation.

2.2. Isolation of LR-MSCs

2.8. GO analysis

Lung parenchyma from C57BL/6 mice (4–6 weeks old) was digested by fine mincing with a razor blade, followed by incubation in an enzyme mixture containing 0.2% collagenase I (Sigma, USA), 0.001% DNAse (Sigma) and 2.4 U/ml dispase (Sigma, USA) for 1 h with shaking. This suspension was filtered through 100-μm and 40-μm filters, centrifuged, and depleted of red blood cells by RBC lysis buffer. Freshly isolated LR-MSCs were cultured at a concentration higher than 105 cells/ml with DMEM containing 10% fetal bovine serum, 1% nonessential amino acids, 4% L-glutamine, and 1% streptomycin and penicillin, and maintained in a humidified atmosphere of 95% air, 5% CO2. The culture medium was changed every 48 h, and cells were passaged 1:2 using 0.25% trypsin when they reached 70–90% confluence.

GO analysis was applied to analyze the main function of the differential expression genes according to the Gene Ontology which is the key functional classification of NCBI, which can organize genes into hierarchical categories and uncover the gene regulatory network on the basis of biological process and molecular function (Ashburner et al., 2000; Jiang et al., 2006). Specifically, two-side Fisher's exact test and χ 2 test were used to classify the GO category, and the false discovery rate (FDR) (Dupuy et al., 2007) was calculated to correct the P-value, the smaller the FDR, the small the error in judging the p-value. The FDR was defined as N FDR = 1 − Tk , where Nk refers to the number of Fisher's test P-values 2 less than χ test P-values. We computed P-values for the GOs of all the differential genes. Enrichment provides a measure of the significance of the function: as the enrichment increases, the corresponding function is more specific, which helps us to find those GOs with more concrete function description in the experiment. Within the significant category, the enrichment Re was given by:

serving potential ways for early detection and treatment of IPF. 2. Materials and methods 2.1. Ethics statement

2.3. Myofibroblast differentiation of LR-MSCs LR-MSCs were incubated with 10 ng/ml TGF-β1 to induce differentiation of LR-MSCs into myofibroblasts and the cells were harvested for analysis of the myofibroblast markers on days 7.

Re = (nf / n)/(Nf / N ) where “nf ” is the number of flagged genes within the particular category, “n ” is the total number of genes within the same category, “Nf ” is the number of flagged genes in the entire microarray, and “N ” is the total number of genes in the microarray. (Schlitt et al., 2003)

2.4. RNA purification Lung tissues or cells were harvested for RNA purification. Total RNA was isolated using the mirVana miRNA Isolation Kit (Invitrogen, Carlsbad, CA) for miRNA or TRIzol reagent (Vazyme, China) for mRNA.

2.9. Pathway analysis

2.5. Low-density miRNA taqman array and bioinformatics

Pathway analysis was used to find out the significant pathway of the differential genes according to KEGG, Biocarta and Reatome. Still, we turn to the Fisher's exact test and χ 2 test to select the significant pathway, and the threshold of significance was defined by P-value and FDR. The enrichment Re was calculated like the equation above (Draghici et al., 2007; Kanehisa et al., 2004; Yi et al., 2006).

Cells incubated in the presence or absence of TGF-β1 were harvested and the total RNA was isolated from 106 cells immediately. The miRNA microarray analysis was performed by low-density miRNA Taqman array (Invitrogen) according to the manufacturer's instructions (Martinez-Pacheco et al., 2014). miRNAs with expression values of greater than 2-fold-change compared to controls were regarded as overexpressed while less than 0.5 (log scale)-fold-change were considered as under-expressed. Potential targets for miRNA action were predicted by using TargetScan, miRTarBase, miRWalk 2.0, and miRecords databases.

2.10. Quantitative real-time polymerase chain reaction (Q-PCR)

The mRNA microarray analysis was performed by Affymetrix Mouse Exon ST 1.0 microarray chips. mRNAs with expression values of greater than 2-fold-change compared to controls were regarded as overexpressed while less than 0.5 (log scale)-fold-change were considered as under-expressed.

Reverse transcription was performed using the Taqman microRNA RT kit (Invitrogen) or the Superscript III first-strand synthesis system (Invitrogen) on a Veriti 96-Well Fast Thermal Cycler (Applied Biosystems, Grand Island, NY). Q-PCR was performed using the Taqman microRNA assay or the SYBR GreenER Q-PCR kit (Invitrogen) using a 7900 HT Fast Real-Time PCR System (Applied Biosystems). All the procedures were repeated for three times. The relative quantification values for each mRNA and miRNA were calculated by the 2−ΔΔCt method using GAPDH and U6 as an internal reference, respectively. Primer pairs of mRNA used are shown in Table 1.

2.7. Integrated mRNA/miRNA analysis

2.11. Immunofluorescent staining

After mRNA and miRNA associated with myofibroblast differentiation were identified in the previous steps, known potential miRNA targets and both mRNA and miRNA expression data were utilized to

Immunofluorescence analysis of lung tissues or cells was performed as described previously. The following primary antibodies were employed: Rabbit anti-fibronectin, rabbit anti-collagen I, mouse anti-α-

2.6. mRNA expression assays and analysis

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membranes using standard procedures. The following primary antibodies were employed: rabbit anti-fibronectin, rabbit anti-collagen I, rabbit anti-α-SMA, rabbit anti-Klf4, rabbit anti-Ing5 and mouse anti-βactin (Abcam Inc. Cambridge, MA). Horseradish peroxidase-conjugated goat anti-rabbit/mouse IgG (Boster, Wuhan, China) was used as the secondary antibody. Immunoreactive protein bands were detected using an Odyssey Scanning System (LI-COR Inc). The expression levels of the proteins were quantified by densitometry using Image J and normalized to the expression of β-actin.

Table 1 Primers used for PCR analysis.

Ifi44 Trim30a Bst2 Xaf1 Trim12c Socs2 Fabp5 Mboat1 Ereg Igfbp2 Klf4 Ing5 MIF MCP-1 OCT4 OLIG2 GAPDH

Forward Primer

Reverse Primer

GGACATGCTGATCCTCTCGG ATAGGCCCACAACGGTATGC GTGGTCCTGTTCGGGGTTAC GGGCAATCGTCATAGGGAGG CAGCAGTGGCAGTGTGACTA GTGAGTCCCAACCTAGTGCC TGAAACGACAGCTGATGGCA GCCTTTCGTCATGTTGGCAG GGGGGAGCATAAACAGCACT GAGAACCACGTGGATGGGAC GGACACTGCTGAGTCCAAG TCCTACGGGGAGATGATCGG CGCTCCACGTAGTGTTCTGT TCACGAAGGAAACAGGGCAG TGGATCCTCGAACCTGGCTA AGTCCCGATATGGAACGGAA AACTTTGGCATTGTGGAAGG

AGGGCTACTCACATGCCAAC CTGTGGAGACCTGACAGAGC GTCAGGTTGCAGGAGTTTGC TAGCAAAGCGGGAGACCTTG CCCACTGGCCCATTTCTCAT CATGGTAGAAGGGAGGCAGC TGACGAGGAAGCCCTCATTG CTCCGAGACTGCCTTTGAGG GCAATGGCAGAGTGCAAACA CAGCTCCTTCATGCCTGACT GTTCCTCACGCCAACGGTTA GCTCTTCAGTCTGGCACAAC GAGGCAACCGTGGTCTCTTA GTAGCTCCAGCCTGGCTATC GGAGGTTCCCTCTGAGTTGC CCCCCTCCCAAAAAGCTCAA ACACATTGGGGTAGGAACA

2.13. Statistical analysis Experimental results were expressed as mean ± standard deviation. Differences were analyzed for significance (P < 0.05) by either one-way ANOVA or Fisher's exact test using SPSS for windows version 11.0 (SPSS Inc., Chicago, IL). 3. Results 3.1. Identifying candidate mRNAs and miRNAs for integrated analysis

smooth muscle actin (α-SMA), (all antibodies were purchased from Abcam, Cambridge, MA). Alexa Fluor 488 or 594-conjugated goat antirabbit antibody (Invitrogen) was used as a secondary antibody. The nucleus is staining with 4′, 6-diamidino-2-phenylindole (DAPI) (Sigma, MO). The images were captured using a confocal fluorescence microscope (Olympus, Tokyo, Japan).

Western blotting and immunofluorescence assay were used to measure the differentiation of LR-MSCs following treatment with TGFβ1 for 7 days. As shown in Fig. 1, LR-MSCs displayed increased expression of collagen I, α-SMA and fibronectin, the major markers of myofibroblast differentiation. To explore the mechanism during the differentiation of LR-MSCs, we collected the total RNA in subsequent microarray analyses. The expression of 459 mRNAs and 299 miRNAs were changed significantly (2−ΔΔCT > 2-fold or < −2-fold, or p-value < 0.05). Among the 299 miRNAs, 252 were up-regulated while 47 were down-regulated. In the experiment of mRNA microassay, there are 267 genes up-regulated and 192 genes down-regulated. To confirm the microarray data, we assessed

2.12. Western blotting Proteins were purified from LR-MSCs. Western blot analysis was performed as previously described(White et al., 2006). Proteins were separated using 12% SDS-polyacrylamide gel electrophoresis and were electrophoretically transferred to polyvinylidene fluoride (PVDF)

Fig. 1. TGF-β1 induced LR-MSCs to differentiate into myofibroblasts. LR-MSCs were cultured with or without TGF-β1 (10 ng/ml) for 7 days followed by measurement of myofibroblast markers on LR-MSCs. A and B: Expression of collagen I, α-SMA, and fibronectin on LR-MSCs was examined by western blotting. Representative gel electrophoresis bands are shown (A), and protein expression levels were quantified by densitometry and normalized to the expression of β-actin (B). Densitometry data are shown as mean ± SD. *P < 0.05 vs. control. C: Expression of collagen I, α-SMA and fibronectin in LR-MSCs was measured by immunofluorescent microscopy ( × 600). (D) Differential expression of miRNAs in LR-MSCs following the treatment with TGF-β1 (10 ng/ml) was measured by Q-PCR. (E) Differential expression of mRNAs in LR-MSCs following the treatment with TGF-β1 (10 ng/ml) was measured by Q-PCR. Data was represented by mean ± SD. *P < 0.05 vs. control.

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Fig. 2. Functional analysis of the differentially expressed mRNA in myofibroblast differentiation of LR-MSCs. (A) Top gene ontology (GO) classification of changed miRNAs targets and mRNAs. We used MiRanda and TargetScan database to predict targets of altered miRNAs and obtained biological function that all genes involved through GO database. (B) Top pathway enrichment of predicted miRNA targets and altered mRNAs. Changed miRNAs targets and mRNAs were analyzed in KEGG pathway database. The results were displayed as -log p values (P < 0.05).

following exposure to TGF-β1 (Fig. 4B).

the expression of 10 miRNAs and 10 mRNA by Q-PCR, our results demonstrate that their expression changes were consistent with the microarray data (Fig. 1D, E).

3.3. miRNA targets were involved in the myofibroblast differentiation of LRMSC and the development of pulmonary fibrosis

3.2. Integrated miRNA/mRNA analyses reveal regulatory network In this study, we observed down-regulated Klf4 and Ing5 at the transcriptional level in LR-MSCs following exposure to TGF-β1 (Fig. 4C). Interestingly, the expression of MIF and MCP-1, the target genes of Klf4, were increased following exposure to TGF-β1 and may be associated with inflammation and fibrosis development (Fig. 4D). As predicted, down-regulated expression of Klf4 and Ing5 were observed in the lung tissue of mice treated with bleomycin (Fig. 4E–G). Moreover, the expression of OCT4 and OLIG2 were increased in LR-MSC following exposure to TGF-β1 (Fig. 4H). These results indicated that the downregulated expression of Klf4 and Ing5 were associated with fibrosis development.

Potential mRNA targets of significant miRNAs were identified using the miRanda, and TargetScan databases. To be considered as a potential mRNA/miRNA target pair, the expression profiles of each mRNA/ miRNA pair in the network was constructed according to their regulated relationship, indicating a divergence in expression during miRNA regulated posttranscriptional activities. With respect to the molecular functions, GO analyses revealed that these target genes may participate in protein transport, angiogenesis, cellular differentiation, and cellular proliferation (Fig. 2A). Pathway analysis was performed based on the KEGG pathway database. In Fig. 2B, target genes of significantly changed target genes are mainly involved in tight junction, pathways in cancer, focal adhesion, and cytokine-cytokine receptor interaction. Moreover, the integrated pathways of identified miRNAs and mRNAs were then analyzed and visualized with Ingenuity Pathway Analyses (IPA), the network was shown in Fig. 3. Kruppel-like factor 4 (Klf4) was predicted to be a target gene of miR-152–3p, miR-140–3p, miR-148 b3p and miR-7a-5p; and these miRNAs all showed increased expression upon TGF-β1 treatment. Klf4 may regulate two independent signaling pathways: the TGF-β1/Smad and the Wnt/β-catenin signaling pathway (Fig. 4A). Inhibitor of growth family, member 5 (Ing5) was targeted by miR-34a-5p, miR-27 b-3p, miR-323–3p, miR-27a-3p, miR-34c-5p, miR128–3p, and miR-224–5p, at the transcriptional levels in LR-MSCs

4. Discussion In this study, we analyzed the miRNA expression profile in LR-MSCs after the myofibroblast differentiation. A set of sensitive biomarkers for monitoring and assessing the myofibroblast differentiation of LR-MSCs can be developed based on the miRNA response profiling, which may help to predict the development of pulmonary fibrosis. Many miRNAs and proteins involved in several pathways were found to be significantly modulated by administrated of bleomycin or in the lungs of pulmonary fibrosis patients. Combining our results, we infer a possible role of miRNAs in the development or establishment of pulmonary 13

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Fig. 3. Integrated miRNA/mRNA network analysis. The differentially expressed miRNAs and target mRNAs were integrated by connecting miRNA with predicted target genes, and the regulatory networks were constructed by Cytoscape 3 software. The round nodes represent the miRNA, the triangle nodes represent the mRNA, and the red nodes represent up-regulation while the green nodes represent downregulation. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

with inflammation and fibrosis development(Mreich et al., 2015). This suggests that the expression of Klf4 may be inversely related with MIF and MCP-1. As predicted, down-regulated expression of Klf4 was observed in the lung tissue of mice treated with bleomycin, indicating Klf4 may be an important target for pulmonary fibrosis treatment. In this study, we also observed down-regulated expression of Ing5, targeted by miR-34a-5p, miR-27 b-3p, miR-323–3p, miR-27a-3p, miR34c-5p, miR-128–3p, and miR-224–5p, at both the transcriptional and protein levels in LR-MSCs following exposure to TGF-β1. Ing5 has been reported to regulate cell proliferation, apoptosis, metastasis and chemoresistance in many cancers (Wang et al., 2018). Overexpression of Ing5 was seen in pluripotent cells compared to differentiated lineages, suggesting that Ing5 may enable cells to maintain stem cell properties (Sarkar et al., 2016). In addition, Ing5 was reported to involved in EMT process (Gao and Han, 2018; Liu et al., 2019) and plays a crucial role in preventing EMT (Zhao et al., 2015), indicating Ing5 may be another target for pulmonary fibrosis treatment. Recent studied showed that Klf4 markedly downregulated the

fibrosis. Moreover, GO enrichment analyses revealed that those differentially expressed genes in the myofibroblast differentiation of LRMSCs were involved in many biological processes. Trough integrative miRNA/mRNA expression profiling, we found that miR-152–3p, miR-140–3p, miR-148 b-3p, and miR-7a-5p may regulate Klf4 expression. KLFs regulate the expression of a vast number of target genes that are involved in many cellular functions, ranging from differentiation to proliferation and apoptosis (Ke et al., 2015). Klf4 functions as a tumor suppressor gene in many kinds of cancers (Ghaleb and Yang, 2017)and Klf4 suppresses TGFβ1-induced EMT by downregulating SNAI2, which was shown to promote EMT (Liu et al., 2012). Besides, Klf4 suppresses the activation of inflammatory signaling and its overexpression in endothelial cells induces the expression of multiple anti-inflammatory factors (Shen et al., 2009). Moreover, Klf4 in macrophages attenuates TNFα-mediated injury and Klf4 attenuates lung fibrosis via inhibiting EMT, suggesting the important role of Klf4 in fibrosis development (Lin et al., 2017). Interestingly, TGF-β1 also induced increased expression of MIF and MCP-1, which may be associated 14

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Fig. 4. Reduced expression of Klf4 and Ing5 in myofibroblast differentiation of LR-MSCs and pulmonary fibrosis. Models for the regulation of Klf4 and Ing5 gene expression by miRNAs is proposed. (A) The Klf4 regulation model. (B) The Ing5 regulation model. (C) LR-MSCs were cultured with or without TGF-β1 (10 ng/ ml) for 7 days. The expression levels of Klf4 and Ing5 during the myofibroblast differentiation of LR-MSCs were measured by Q-PCR. (D) The expression levels of MIF and MCP-1 during the myofibroblast differentiation of LR-MSCs were measured by Q-PCR. (E, F) Pulmonary fibrosis was induced in bleomycin-treated mice. Mice (n = 10 in each group) received either saline or bleomycin (5 mg/kg body wt in 50 μl saline) intratracheally. Mice were killed on days 7 and 14. The expression of Klf4 was assessed by Western blot (E) and immunohistochemistry ( × 200) (F). Representative images are shown. (G) The expression of Ing5 was assessed by Western blot. (H) The expression levels of OCT4 and OLIG2 during the myofibroblast differentiation of LR-MSCs were measured by Q-PCR. Data are shown as means ± SD, from n = 3 independent experiments. *P < 0.05 versus control.

pulmonary fibrosis by controlling myofibroblast differentiation and possibly EMT interference. The definite relevance of these specific signature miRNAs and their targeting pairs still need further validation.

expression of epithelial-mesenchymal transition (EMT)-related molecules, including TGF-β1/Smad pathway (Li et al., 2019). Moreover, βcatenin interacts directly with Klf4 in differentiating to promote expression of specialized keratins required for normal tissue integrity and structure (Xu et al., 2017). In addition, PI3K/Akt signaling pathway was responsible for the inhibitory effect of Ing5 on the thyroid cancer(Gao and Han, 2018) and Ing5 inhibits lung cancer invasion and EMT by inhibiting the Wnt/β-catenin pathway (Liu et al., 2019). Therefore, based on that Klf4 and Ing5 may be related to these signaling pathways, we hypothesized that Klf4 regulates the TGF-β1/Smad and the Wnt/βcatenin pathway, whereas Ing5 acts through PI3K/AKT and Wnt/βcatenin pathway. However, more experimental evidence needs to be further explored. In summary, our data confirmed a miRNA-mRNA integrated network in LR-MSCs following the myofibroblast differentiation. Klf4 and Ing5 induced by TGF-β1 may be the targets for the therapy of

Declaration of interest statement The authors declare no competing interests.

Acknowledgments This work was supported by the National Natural Science Foundation of China (81570059) and the Natural Science Foundation of Jiangsu Province of China (BK20151398).

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