Neural stem cells (NSCs) are self-regenerating cells, but their regenerative capacity is limited. The present study was conducted to investigate the effect of
Neural stem cells (NSCs) are defined as undifferentiated cells that have the ability of self-renewal and the potential to generate neurons, astrocytes, or oligodendrocytes in the central nervous system [
In this study, the first confirmation that
Recent advances in bioinformatics and high-throughput technologies such as microarray analysis are bringing about a revolution in our understanding of the molecular mechanisms underlying biological processes. In this study, mRNA and microRNA (miRNA) expression microarray analyses were performed to understand the molecular mechanism of the effect on NSCs. miRNAs are small endogenous, noncoding RNAs that are highly conserved and that have been recognized as a powerful tool for regulating gene expression through the RNA interference pathway [
Some analytical methods are applied in the microarray analysis, including Gene Ontology (GO) analysis. GO analysis (
BSSG (purity: 98%, provided by Department of Pharmacognosy, Nanjing University of Chinese Medicine) stock solution was prepared in Dimethyl Sulfoxide (DMSO). Before each experiment was performed, the solution was diluted in a fresh medium to obtain a final DMSO concentration of ≤0.1%.
Primary NSC culture was established according to a previously published protocol [
Dose-dependent cell viability was monitored using a cell counting kit-8 (CCK-8) assay. CCK-8 is a sensitive nonradioactive colorimetric assay used to determine the number of viable cells in cell proliferation and cytotoxicity assays. In the study, NSCs were cultured in 96-well plates containing the growth culture medium at a cell density of 5 × 103 cells per well. The cells were divided into nine groups: control group and BSSG treatment groups (1.25, 2.5, 5, 10, 20, 40, 80, and 100
To understand the effectiveness of BSSG on enhancing NSCs proliferation, we compared BSSG with bFGF and EGF by performing CCK-8 assay. The cells were cultured in 96-well plates at a cell density of 1 × 104 cells per well and then divided into six treatment groups: bFGF and EGF vacancy group (bFGF−EGF−: with neurobasal medium and B27 supplement); bFGF group (with neurobasal medium, B27 supplement, and bFGF 20 ng/mL); EGF group (with neurobasal medium, B27 supplement, and EGF 20 ng/mL); and bFGF−EGF− + BSSG groups (10, 20, and 40
mRNA expression microarray analysis was performed by use of Roche-NimbleGen Rattus norvegicus 12 × 135 K Array (Roche, supplied by KangChen Corp), in order to understand the effect of BSSG on regulation of mRNA, disclosing the mechanism of BSSG promoting NSCs proliferation.
Total RNA was obtained from each sample (five samples from the control group and five samples from the BSSG-treated group (40
The scanned images were imported into the NimbleScan software (version 2.6) for grid alignment and expression data analysis. The expression data were normalized by quartile normalization and robust multichip average (RMA) algorithm included in the NimbleScan software. The probe level files and the gene level files were generated after normalization. The ten gene level files were imported into Agilent GeneSpring GX software (version 11.5.1) for further analysis. Differentially expressed genes were identified by volcano plot filtering (
The genic network was plotted by use of the search tool STRING (
Real-time PCR was performed to validate the mRNA expression profiling obtained. Total RNA (obtained from the same samples as mentioned in mRNA microarray analysis) was reverse transcribed with SuperScript II reverse transcriptase (Invitrogen). Real-time PCR was performed using the ABI PRISM7900 system (Applied Biosystems, Foster City, CA, USA), in the presence of forward and reverse primers for the target genes, or forward and reverse primers for the GAPDH gene used as reference. Relative quantification of the target gene is determined by calculating the ratio between the concentration of the target gene and that of the reference.
The primer sequences of the GAPDH gene and the target genes are listed in Table
Primer sequences of the reference gene and the genes selected.
Gene | Primer sequence | Annealing temperature (°C) | Product length (bp) |
---|---|---|---|
GAPDH | F: 5′-GGAAAGCTGTGGCGTGAT-3′ | 60 | 308 |
R: 5′-AAGGTGGAAGAATGGGAGTT-3′ | |||
IGF1 | F: 5′-CTGGCACTCTGCTTGCTCAC-3′ | 60 | 180 |
R: 5′-CTCATCCACAATGCCCGTCT-3′ | |||
cdkn1c | F: 5′-CCTCCCGTTCCCTTCTTTCT-3′ | 60 | 96 |
R: 5′-CGTTCCATCGCTGTTCTGC-3′ | |||
Espl1 | F: 5′-TGACTACCTGGGCGTGACTG-3′ | 60 | 98 |
R: 5′-CTGGCTCTGAGATGGCACAA-3′ | |||
Pttg1 | F: 5′-TGGAGACAGTTGTTTGGGTGC-3′ | 60 | 270 |
R: 5′-GCTGCCTGGCTCTTCGTTAT-3′ | |||
Ptpru | F: 5′-ACCCTGAGCGAGAACGACA-3′ | 60 | 285 |
R: 5′-GGGATGGCTGAATAGCAAGAT-3′ |
To validate the mRNA expression profiling, five genes (Igf1, cdkn1c, Espl1, Pttg1, and Ptpru) were selected to performed real time-PCR. Primer sequences of the GAPDH gene and the genes selected were listed in Table
Evidence showed the important functions of miRNAs in stem cell regulation [
The scanned images were imported into GenePix Pro 6.0 software (Axon) for grid alignment and data extraction. The replicated miRNAs were averaged and the miRNAs with intensities ≥30 in all of the samples were chosen to calculate the normalization factor. The expressed data were normalized by median normalization. After normalization, significantly and differentially expressed miRNAs were identified by volcano plot filtering.
Real-time PCR was performed to validate the differential miRNA expression profiling obtained. Total RNA was reverse-transcribed to cDNA using AMV reverse transcriptase (Epicentre), RNase (Epicentre), dNTP (HyTest Ltd), RT buffer, and RT primers (Invitrogen). The mixture was incubated at 16°C for 30 min, 42°C for 40 min, and 85°C for 5 min to generate a library of miRNA cDNAs. U6 is used as an internal control for normalization. Real-time PCR was subsequently performed using an ABI PRISM7900 system (Applied Biosystems, Foster City, CA, USA) according to a standardized protocol. The reactions were incubated at 95°C for 10 min, followed by 40 cycles at an interval of 10 s at 95°C and an interval of 1 min at 60°C. Data were analyzed by
RT Primer sequence of the internal control gene and the target genes for cDNA synthesis.
Genes | RT primer sequence |
---|---|
U6 | 5′-CGCTTCACGAATTTGCGTGTCAT-3′ |
rno-miR-129-5p | 5′-GTCGTATCCAGTGCGTGTCGTGGAGTCGGCAATTGCACTGGATACGACGCAAGCC-3′ |
rno-miR-322-5p | 5′-GTCGTATCCAGTGCGTGTCGTGGAGTCGGCAATTGCACTGGATACGACTCCAAAA-3′ |
rno-miR-301a-3p | 5′-GTCGTATCCAGTGCGTGTCGTGGAGTCGGCAATTGCACTGGATACGACGCTTTG-3′ |
To validate the miRNA expression profiling, three genes were selected to performed real time-PCR. RT primer sequences of the U6 gene used as reference and the genes selected were listed in Table
Primer sequences of the internal control gene and the target genes for PCR.
Genes | Primer sequence | Annealing temperature (°C) | Product length (bp) |
---|---|---|---|
U6 | F: 5′GCTTCGGCAGCACATATACTAAAAT3′ | 60 | 89 |
R: 5′CGCTTCACGAATTTGCGTGTCAT3′ | |||
rno-miR-129-5p | GSP: 5′GGAACTTTTTGCGGTCTGG3′ | 60 | 63 |
R: 5′GTGCGTGTCGTGGAGTCG3′ | |||
rno-miR-322-5p | GSP: 5′GGGCAGCAGCAATTCAT3′ | 60 | 65 |
R: 5′CAGTGCGTGTCGTGGAG3′ | |||
rno-miR-301a-3p | GSP: 5′CCCCGTGCAATAGTATTGT3′ | 60 | 65 |
R: 5′CAGTGCGTGTCGTGGAGT3′ |
Primer sequences of the internal control gene and the target genes for PCR were listed in Table
IGF1 protein determination were performed to investigate the key regulator by which BSSG promotes NSC proliferation. The cells were cultured in 24-well plates at a cell density of 5 × 104 cells per well and divided into four groups: a control group and BSSG-treated groups (10, 20, and 40
IGF1 is mediated by type 1 IGF receptor (IGF1R). PPP is an inhibitor of IGF1R [
In the study, PPP (Tocris Bioscience, Bristol, UK) stock solutions were prepared in DMSO and stored at 4°C. Before each experiment was performed, these solutions were diluted in a fresh medium to obtain a final DMSO concentration of <0.1%. The cells were cultured in 96-well plates at a cell density of 1 × 104 cells per well and divided among the PPP-BSSG treated groups (pair-wise; with PPP doses of 0, 0.01, 0.1, 1, and 2
Statistical analyses were performed by use of SPSS version 16.0 software program for windows (SPSS, Inc., Chicago, IL). Multiple comparisons were made using one-way ANOVA, followed by the Bonferroni posttest. All data are presented as Mean ± SD, and statistical significance was accepted at the 5% level.
NSCs were positive for nestin (Figure
Identification of NSCs. Cultured NSCs were stained by immunocytochemistry with primary antibody against nestin (original magnification: 100x).
BSSG significantly increased NSC proliferation at concentration of 40
Dose-dependent effects of BSSG on cell proliferation. Dose-dependent effects of BSSG on cell proliferation were determined by CCK-8 assay and the data are plotted as percentages of control cell proliferation. Data are presented as Mean ± SD (
NSCs proliferation was induced by adding bFGF (20 ng/mL;
Comparison of NSC Proliferation Promoted by BSSG, BFGF, and EGF. Comparison of NSC proliferation promoted by BSSG, bFGF and EGF was determined by CCK-8 assay and the data are plotted as percentages of control cell proliferation. Data are presented as Mean ± SD (
The result of mRNA expression microarray analysis showed that 960 genes were differentially expressed after NSCs were treated with BSSG, including 333 upregulation genes (fold change ≥2) and 627 downregulation genes (fold change ≤0.5). The differential expression genes were described using GO term analysis (biological process). The main differentially expressed genes are listed in Tables
Upregulation genes.
GO ID | Term |
|
Genes |
---|---|---|---|
GO:0000087 | M phase of the cell cycle |
|
AURKB; CCNF; KIF2C; BUB1B; CDCA3; IGF1; CENPF; DLGAP5; CDC20; SPAG5; MAD2L1; TRAF4AF1; NUSAP1; ESPL1; CCNB1; PLK1; PTTG1 |
GO:0000278 | Mitotic cell cycle |
|
SPAG5; MAD2L1; TRAF4AF1; NUSAP1; ESPL1; CDKN1B; CENPF; DLGAP5; CENPA; NDC80; CCNB1; PTTG1; CDC20; AURKB; CCNF; |
GO:0000280 | Nuclear division |
|
SPAG5; MAD2L1; TRAF4AF1; NUSAP1; ESPL1; CCNB1; PLK1; PTTG1; CDC20; AURKB; CCNF; KIF2C; BUB1B; CDCA3; IGF1 |
GO:0007059 | Chromosome segregation |
|
SPAG5; MAD2L1; TRAF4AF1; NUSAP1; ESPL1; CCNB1; NDC80; PTTG1; CENPF; KIF2C; TOP2A |
GO:0048285 | Organelle fission |
|
SPAG5; MAD2L1; TRAF4AF1; NUSAP1; ESPL1; CCNB1; CDCA3; PLK1; PTTG1; CDC20; AURKB; CCNF; KIF2C; BUB1B; IGF1 |
GO:0000226 | Microtubule cytoskeleton organization |
|
CENPA; NDC80; ESPL1; PLK1; KIF20A; KIF2C; SPAG5; TEKT1; |
GO:0048545 | Response to steroid hormone stimulus |
|
CAR9; GBA; A2M; HP; IGF1; ADM; and so forth, a total of 22 genes |
GO:0051301 | Cell division |
|
NUSAP1; PLK1; AURKB; KIF20A; NUMBL; TOP2A; TXNIP; CCNB2; CCNB1; PTTG1; CDC20; CCNF; KIF2C; BUB1B; CDCA3; TRAF4AF1 |
GO:0008283 | Cell proliferation |
|
CDC20; AURKB; CCNB1; PTTG1; IGF1; and so forth, a total of 39 genes |
GO:0019932 | Second messenger-mediated signaling |
|
CALCA; ADORA2A; GRM3; EDNRB; GRM5; CXCR4; TOX3; RASD1; ADM; PDE7B; CDH13; IGF1; LMCD1; MT1A |
GO:0009605 | Response to external stimulus |
|
A2M; LBP; CCNB1; ENPP2; CKLF; IGF1; and so forth, a total of 35 genes |
GO:0009719 | Response to endogenous stimulus |
|
ADORA2A; IGF1; SPP1; A2M; and so forth, a total of 32 genes |
GO:0008608 | Attachment of spindle microtubules to kinetochores |
|
CCNB1; SPAG5; TRAF4AF1; NDC80 |
GO:0009056 | Catabolism |
|
TOP2A; FBXO32; MANBA; IGF1; CDC20; and so forth, totle 41 genes |
GO:0007051 | Spindle organization |
|
ESPL1; NDC80; TACC3; CCNB1; AURKB; SPAG5; TRAF4AF1 |
GO:0051313 | Attachment of spindle microtubules to chromosomes |
|
NDC80; CCNB1; SPAG5; TRAF4AF1 |
GO:0009725 | Response to hormone stimulus |
|
IGF1; LOX; SPP1; A2M; HP; ALPL; and so forth, a total of 27 genes |
GO:0010941 | Regulation of cell death |
|
AURKB; IGF1; ADORA2A; and so forth, a total of 32 genes |
GO:0043470 | Regulation of carbohydrate catabolism |
|
PFKFB3; DDIT4; IER3; IGF1 |
GO:0048016 | Inositol phosphate-mediated signaling |
|
EDNRB; GRM5; CALCA; IGF1; LMCD1 |
Upregulation genes obtained from the mRNA expression profiling were listed in Table
Downregulation genes.
GO ID | Term |
|
Genes |
---|---|---|---|
GO:0030154 | Cell differentiation |
|
FOXC2; IGF2; JAG1; SEMA3C; HMGA2; and so forth, a total of 38 genes |
GO:0006950 | Response to stress |
|
PENK; BDNF; CRYAB; TRH; PLAU; MMP3; and so forth, a total of 32 genes |
GO:2000736 | Regulation of stem cell differentiation |
|
HMGA2; JAG1; HES1 |
GO:0032103 | Positive regulation of response to external stimulus |
|
NPY; IL1RL1; SCG2; TNFSF11; CD74; THBS4 |
GO:0048710 | Regulation of astrocyte differentiation |
|
HES1; CLCF1; HMGA2 |
GO:0045597 | Positive regulation of cell differentiation |
|
TGFB1I1; CD74; FRZB; JAG1; BDNF; MAP1B; IFI204; TNFSF11; TNFRSF12A; HES1; CLCF1 |
GO:0048584 | Positive regulation of response to stimulus |
|
CD74; TNFSF11; TGFB1I1; CDKN1C; GPC3; HES1; NPY; CLCF1; IGF2; JAG1; PRRX2; IL1RL1; SCG2; THBS4; HMGA2; TNFRSF12A |
GO:0000904 | Cell morphogenesis involved in differentiation |
|
HMGA2; MAP1B; BDNF; TGFB1I1; CHST3; FOXC2; TNFRSF12A; HES1; XYLT1; NPTX1 |
GO:0050920 | Regulation of chemotaxis |
|
SCG2; CD74; THBS4; EFNB2 |
GO:0030182 | Neuron differentiation |
|
MAP1B; BDNF; CHST3; NPY; MFRP; JAG1; HES1; CDKN1C; TNFRSF12A; HCN1; XYLT1; THBS4; NPTX1; BYSL |
GO:0060326 | Cell chemotaxis |
|
TNFSF11; SCG2; CD74; THBS4 |
GO:0090398 | Cellular senescence |
|
HMGA2; RGD1305645 |
GO:0016477 | Cell migration |
|
SEMA3C; EFNB2; TNFSF11; TNFRSF12A; PLAU; MMP3; UNC5C; SCG2; THBS4; CD74; HES1 |
GO:0016126 | Sterol biosynthesis |
|
HMGCS2; HSD17B7 |
GO:0033554 | Cellular response to stress |
|
HMGA2; TNFSF11; MAP1B; CHST3; XYLT1; DHX9 |
Downregulation genes obtained from the mRNA expression profiling were listed in Table
Tables
The genic network consists of the majority of the upregulation and downregulation genes (Figure
Genic network analysis. (a) Genic network. The genic network was plotted by use of the search tool STRING and drawing tool cytoscape to understand the interacting genes. The genic network consists of the majority of the upregulated and downregulated genes. The integral network and its magnified image are shown on the left and right parts, respectively. IGF1 is indicated by an arrow. (b) Connectivity analysis on the network. The “hubs” of the gene nodes were determined by interaction count and
The mRNA expression profiling was validated by real-time PCR. The comparison of quantified mRNA expressions obtained using real-time PCR and microarray analysis was performed to determine the reliability of microarray analysis (Table
Comparison of quantified mRNA expressions obtained using real-time PCR and microarray analysis.
Genes | PCR | Microarray analysis | Fold change (test versus control) | |||
---|---|---|---|---|---|---|
Control | Test | Control | Test | PCR | Microarray analysis | |
IGF1 |
|
|
|
|
3.20 ↑ | 4.75 ↑ |
Pttg1 |
|
|
|
|
2.09 ↑ | 2.91 ↑ |
Adora2a |
|
|
|
|
2.34 ↑ | 2.62 ↑ |
Espl1 |
|
|
|
|
3.41 ↑ | 2.07 ↑ |
Ptpru |
|
|
|
|
2.74 ↑ | 2.46 ↑ |
cdkn1c |
|
|
|
|
0.30 |
0.47 |
A total of 30 upregulated miRNAs (test versus control, fold change ≥2) and 84 downregulated miRNAs (test versus control, fold change ≤0.5) were obtained after the NSCs were treated with BSSG (Figure
Differentially expressed miRNA.
The miRNA expression profiling was validated by real-time PCR. The comparison of quantified miRNA expressions obtained using real-time PCR and microarray analysis was performed to determine the reliability of microarray analysis (Table
Comparison of the quantified miRNA expressions obtained by real-time PCR and microarray analysis.
miRNA | PCR | Microarray analysis | Fold change (test versus control) | |||
---|---|---|---|---|---|---|
Control | Test | Control | Test | PCR | Microarray analysis | |
rno-miR-129-5p |
|
|
|
|
0.29 |
0.36 |
rno-miR-301a-3p |
|
|
|
|
0.33 |
0.31 |
rno-miR-322-5p |
|
|
|
|
0.34 |
0.37 |
miRNAs are recognized as a powerful tool used to regulate gene expression via the RNA interference pathway [
miRNA-mRNA Interactome Network. The integral chart and its magnified image were shown on the upper left and lower right corners, respectively. Red square nodes represented the five miRNAs: miR-322-5p; miR-301a-3p; miR-129-5p; miR-322-3p, and miR-129-2-3p. Turquoise round nodes represented the target genes of these miRNAs. Pink round nodes represented the upregulated mRNAs correlated with these miRNAs; green round nodes represented the downregulated mRNAs. The network revealed that numerous mRNAs were regulated by the miRNAs and the expressions of many mRNAs including IGF1 were increased.
IGF1 protein in the cell culture supernatant was quantified. IGF1 protein levels were remarkably increased after the NSCs were treated with BSSG at 20 and 40
IGF1 protein quantitation. IGF1 protein levels were reported in pg/10,000 cells. IGF1 protein levels were significantly increased after the NSCs were treated with BSSG at 20 and 40
PPP inhibited the BSSG-induced cell proliferation at suitable concentrations (Figure
PPP inhibited the BSSG-induced cell proliferation. The inhibition of PPP on NSC proliferation was weak at 0.01
NSC proliferation is necessary to facilitate neurogenesis [
BSSG is present in many higher plants [
The proliferation-promoting activity of BSSG is the result of regulation of numerous genes. mRNA expression profiling revealed that the majority of upregulation genes were involved in mitotic cell cycle particularly in the M phase, enhancing cell proliferation. By contrast, the majority of the downregulated expression genes were involved in cell differentiation, indicating that cell differentiation was inhibited and accordingly, more possibility of cell proliferation was afforded. Among the differential expression genes, the “hubs” of the gene nodes were Bub1b, Cdc20, Plk1, Spp1, Aurkb, IGF1, and Ndc80, all of which were upregulated. Most of these “hub” genes are necessary to complete a cell cycle according to Genecards (
IGF1 gene encodes a protein with functions and structure similar to insulin, but IGF1 exhibits a higher growth-promoting activity. Experimental evidence demonstrates that IGF1 functions in CNS development by promoting neural cell proliferation, survival, and differentiation, in which IGF1 likely functions in a paracrine or autocrine fashion [
BSSG increased the expression of endogenous IGF1 as showed in mRNA expression microarray analysis, miRNA-mRNA correlation analysis and IGF1 Protein Quantitation. In particular, IGF1 mRNA was negatively regulated by miRNAs (miR-129-5p, miR-301a-3p, and miR-322-5p), which were downregulated after NSCs were treated with BSSG. In other words, the expression of IGF1 mRNA was increased. And as a result, the IGF1 protein level was increased. Emerging evidence supported the close relationship between the abilities of BSSG and IGF1 to promote cell proliferation. PPP inhibition test confirmed that the function of BSSG depended on IGF1, in which the function was inhibited when the cells were exposed to suitable doses of PPP.
The present study provided information about BSSG, an inexpensive and stable compound, which could promote NSC proliferation. BSSG could be potentially developed as a growth factor alternative that could be used in clinical medicine and research applications.
This work was supported by the National Program on Key Basic Research Project (973 Program 2011CB707501), the Key Project of Science and Technology of Guangzhou (11BppZXaa2070006), and the Sixth Batch of projects of Jiangsu Province Six Talent Peak of China and a project funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions, PAPD (TCM combined with western medicine).