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Significant transcriptomic changes are associated with differentiation of bone marrow-derived mesenchymal stem cells into neural progenitor-like cells in the presence of bFGF and EGF
Amir Ali Khan ORCID: orcid.org/0000-0002-3858-16781,5 na1,
Tee Jong Huat2,3 na1,
Abdullah Al Mutery1,
Ahmed Taher El-Serafi4,
Hassen Hadj Kacem1,5,
Sallam Hasan Abdallah5,
Muhammed Faruque Reza3,
Jafri Malin Abdullah3,6 &
Hasnan Jaafar7
Cell & Bioscience volume 10, Article number: 126 (2020) Cite this article
Mesenchymal stem cells (MSCs) isolated from bone marrow have different developmental origins, including neural crest. MSCs can differentiate into neural progenitor-like cells (NPCs) under the influence of bFGF and EGF. NPCs can terminally differentiate into neurons that express beta-III-tubulin and elicit action potential. The main aim of the study was to identify key genetic markers involved in differentiation of MSCs into NPCs through transcriptomic analysis.
Total RNA was isolated from MSCs and MSCs-derived NPCs followed by cDNA library construction for transcriptomic analysis. Sample libraries that passed the quality and quantity assessments were subjected to high throughput mRNA sequencing using NextSeq®500. Differential gene expression analysis was performed using the DESeq2 R package with MSC samples being a reference group. The expression of eight differentially regulated genes was counter validated using real-time PCR.
In total, of the 3,252 differentially regulated genes between MSCs and NPCs with two or more folds, 1,771 were upregulated genes, whereas 1,481 were downregulated in NPCs. Amongst these differential genes, 104 transcription factors were upregulated, and 45 were downregulated in NPCs. Neurogenesis related genes were upregulated in NPCs and the main non-redundant gene ontology (GO) terms enriched in NPCs were the autonomic nervous system, cell surface receptor signalling pathways), extracellular structure organisation, and programmed cell death. The main non-redundant GO terms enriched in MSCs included cytoskeleton organisation cytoskeleton structural constituent, mitotic cell cycle), and the mitotic cell cycle process Gene set enrichment analysis also confirmed cell cycle regulated pathways as well as Biocarta integrin pathway were upregulated in MSCs. Transcription factors enrichment analysis by ChEA3 revealed Foxs1 and HEYL, amongst the top five transcription factors, inhibits and enhances, respectively, the NPCs differentiation of MSCs.
The vast differences in the transcriptomic profiles between NPCs and MSCs revealed a set of markers that can identify the differentiation stage of NPCs as well as provide new targets to enhance MSCs differentiation into NPCs.
Bone marrow-derived mesenchymal stem cells (MSCs) have a broad differentiation capacity, including their differentiation potential into neural lineages. The differentiation potential may be due to the heterogeneous nature of MSCs [1,2,3]. During early mammalian development, neural crest cells migrate to the bone marrow and contribute to a subset of MSCs that express nestin, an intermediate filament protein expressed in neural stem cells [4,5,6]. Human induced pluripotent stem cells (iPSCs) were differentiated into neural crest cells, and the differentiated neural crest cells were further differentiated into nestin-positive MSCs, which confirmed the neural crest cells contribution to MSC populations [7]. Indeed, the iPSCs-derived human MSCs had a comparable differentiation potential to MSCs and could differentiate into adipocytes, chondrocytes, and osteoblasts.
During in vitro culture, MSCs express nestin, which is also expressed by developmental neural stem cells [8]. Nestin expression in MSCs indicates the inherent propensity of MSC differentiation toward neural lineages.
In vivo MSCs were reported to secrete neuroprotective factors in addition to their anti-inflammatory activities and modulation of microenvironment during transplantation [9, 10]. Several studies have also shown that MSCs may also be differentiated into neural lineages in vivo. These studies have demonstrated that MSCs can differentiate into neuron-like cells to be integrated into nervous system [11,12,13,14,15]. Furthermore, these transplantations have effectively improved the neurological function and survival status of animals after spinal cord injuries and other nervous system diseases.
MSCs can be differentiated into neural progenitor-like cells (NPCs) under the influence of bFGF and EGF in suspension (16). MSCs-derived NPCs will be more suitable for cell therapy in neurodegenerative disorders as they are more readily differentiated into neural lineages compared to undifferentiated MSCs [15, 16]. Therapeutically, it may be more effective, however, to transplant endogenous neural stem cells or primary NPCs in neurological disorders but obtaining these endogenous stem or progenitor cells are extremely difficult in addition to ethical restrictions in their extraction. Hence, it is practical to use the MSCs-derived NPCs in neurodegenerative disorders [17, 18]. Therefore, it is will be therapeutically more effective to enhance the differentiation of MSCs into NPCs.
There are generally two approaches to neural differentiation of MSC in vitro. The first approach consists of making NPCs and their subsequent differentiation into neurons and glial cells [19, 20]. The second approach directly differentiates MSCs into neurons and glial cells without prior differentiation of MSCs into NPCs [21, 22]. However, owing to the adherent nature of neurons, the generation of free-floating NPCs will better benefit its future purpose, especially in cell transplantation.
Trans-lineage differentiation is a complex process involving dynamic changes in gene and protein expressions. In our earlier study, we differentiated MSCs into NPCs using growth factor combination, such as epidermal growth factor (EGF) and basic fibroblast growth factor (bFGF) [19]. Other studies, including ours, demonstrated the differentiation of MSCs into NPCs was optimal in term of cell viability and proliferation after three days of induction [19, 23,24,25]. The derived NPCs can terminally differentiate into glial-like and neuronal-like cells expressing glial-marker and the neuronal marker, respectively.
Nestin and Sox2 are the main NPC markers; these markers though also expressed by MSCs, but their expression is upregulated in the MSC-derived NPCs [26]. In our previous study, we reported that the MSC-derived NPCs expressed Sox2 and Nestin. Giving the more readiness of MSCs-derived NPCs to differentiate into neurons and glial cells compared with MSCs, unravelling differential genes expression between MSCs and MSC-derived NPCs will lead to a better understanding of the molecular processes that govern this differentiation. Knowledge gained from this differential genes expression comparison will lead to a better understanding of the differentiation process which may lead to more effective transplantation strategies for NPCs in neurodegenerative disorders. Previously, we reported the dynamic change in the microRNA profile of MSCs upon NPCs differentiation [27]. We found key microRNAs that are involved in the differentiation of NPCs from MSCs. However, there is still a lack of detailed comparison of transcriptomic profiles of rat MSCs and MSCs-derived NPCs in the rat model. Hence, in this study, we utilised mRNA-Sequencing to uncover the changes in the transcriptomic profile of rat MSCs before and soon after the cells undergo neurogenic differentiation on Day 3. This study sheds further light on the propensity of MSC differentiation toward NPCs and reports that NPCs induction of MSC indeed involves a massive change in transcriptomic profiles.
Primary MSC culture
For this study, Sprague Dawley rats were purchased from the animal facility of Universiti Sains Malaysia. MSCs were extracted from bone marrow tissues of three SD rats using a previously described method [19]. Briefly, three SD rats (4 weeks old) were euthanised using an overdose mixture of ketamine-xylazine (Ilium Troy Laboratory, Blacktown, Australia) via intraperitoneal injection. Femoral and tibial bones were then aseptically dissected, and 5 mL of 20% DMEM was injected into the central canal of the bones to extrude the marrow tissue. Next, the cell mixture was separated using Ficoll-Paque PREMIUM gradient solution (GE Healthcare Bioscience, Uppsala, Sweden), and mononuclear cells were extracted. The collected cells from three SD rats were plated at a density of 1 × 106 marrow cells and incubated in a humidified chamber at 37 °C with 5% CO2. After 24 h, floating cells were removed using total media replacement. At 80% confluence, MSCs were detached with TrypLE™ Express stable trypsin replacement enzyme without phenol red (Life Technologies, Carlsbad, CA, USA) and subcultured until passage 3 for neural induction.
Differentiation of MSCs into NPCs
MSCs at passage 3 (3 biological replicates) were differentiated into NPCs as previously described [19]. Briefly, MSCs (collected from three SD rats) at P3 were plated in three (triplicate) ultra-low attachment plates at a density of 1 × 106 cells/mL and were induced into NPCs with NeuroCult® NS-A proliferation media (STEMCELL Technologies, Vancouver, BC, Canada) supplemented with 20 ng/ml of bFGF (C/N: 4039–10; BioVision, CA, USA), 20 ng/ml of EGF (C/N: PMG8045; Gibco, Life Technologies, Carlsbad, CA, USA) and 1% penicillin–streptomycin (Gibco, Life Technologies, Carlsbad, CA, USA). Cells were monitored daily, and growth factors were supplemented every other day.
Differentiation of rat MSCs into adipocytes, chondrocytes, and osteocytes
The remaining MSCs after NPCs differentiation and mRNA extraction for mRNA-Seq were grown until passage 4. They were then differentiated into adipocytes, chondrocytes, and osteocytes using the StemPro® Adipogenesis differentiation kit (C/N: A1007001, Gibco, Life Technologies, Carlsbad, CA, USA), StemPro® Chondrogenesis differentiation kit (C/N: A1007101, Gibco, Life Technologies, Carlsbad, CA, USA) and the StemPro® Osteogenesis differentiation kit (C/N: A1007201, Gibco, Life Technologies, Carlsbad, CA, USA), respectively, according to manufacturer protocol. Differentiated adipocytes, chondrocytes, and osteocytes were stained with oil red O, Alcian Blue, and Alizarin Red S solution, respectively, as described previously [28]. Images were visualised under a light microscope and captured using an attached DSLR camera.
Proliferation analysis
CellTiter 96® AQueous One Solution Reagent was used to evaluate NPC viability at 24, 48, 72, and 96 h of culture. Viability rate was determined using the 3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium (MTS) method. One thousand cells were seeded in 96 well plates and incubated with MTS solution (20 µl, Promega, Milan, Italy) for four hours at 37 °C. The absorbance was read at 490 nm using a spectrophotometer. Non-treated cells (in basal media and without growth factors) were used as control.
Immunocytochemistry
Cells were fixed with 4% paraformaldehyde for 20 min and permeabilised with 0.012% Triton X-100 in PBS for 30 min. Cells were blocked with 5% BSA/PBS for one hour at room temperature to prevent non-specific binding. The cells were then incubated with primary antibodies overnight at 4 °C and protected from light. The following day, cells were incubated with donkey anti-rabbit IgG Cy3 secondary antibody (EMD Millipore, MA, USA) for one hour at room temperature followed by three washes with chilled 1 × PBS. Nuclei were counterstained with Sytox® blue nucleic acid stain (Life Technologies, Carlsbad, CA, USA) and mounted with fluorescence anti-fade mounting medium (DAKO, Agilent Technologies, CA, USA). Confocal microscopy equipped with Pascal 5 imaging software was used for sample observation.
Terminal differentiation of NPCs into neuronal-like cells
MSCs-derived NPCs at Day 3 of induction were differentiated into neuronal-like cells in a standardised NeuroCult™ NS-A differentiation media (STEMCELL Technologies, Vancouver, BC, Canada). Briefly, NPCs were incubated with Accutase® cell detachment solution (Merck Millipore, MA, USA) for 5 min at 37 °C and gently triturated into the single-cell suspension. Suspended cells were centrifuged to remove the supernatant, and the cell pellet was then resuspended in the complete NeuroCult™ NS-A differentiation media. Cells were seeded into a poly-d-lysine-coated micro dish at a density of 1 × 105 cells/ml. NPCs were terminally differentiated for 14 days in a humidified chamber at 37 °C with 5% CO2 supply.
The functional properties of neuronal-like cells differentiated from NPCs were assessed using a whole-cell patch-clamp recording. Briefly, neuronal-like cells were continuously superfused in artificial cerebrospinal fluid at room temperature throughout the recording. Microelectrode pipettes with an input resistance of 5 to 8 MΩ were fabricated from borosilicate glass capillary tubing using a P-97 micropipette puller. The recording microelectrode pipette was then filled with an intracellular solution. The microelectrode was placed in the pipette holder, and positive pressure was applied. Target cells were slowly approached until changes in the test pulse amplitude were observed. Once a steady resistance was obtained, the positive pressure was released rapidly, and the resistance gradually increased until a giga-ohm (GΩ) seal was formed. Continuous suction was then applied until the membrane broke as evidenced by a change in the capacitance and the test pulse current. The miniature postsynaptic current was recorded using a pClamp program interface. The recording was performed in triplicate, and a minimum of three cells from each group was recorded.
Total RNAs extraction and illumina cDNA library preparation
At passage 3, mRNAs were extracted from the MSCs from three rats (three biological replicates), and NPCs differentiated from the three biological replicas of MSCs on Day 3. Total RNAs were extracted from the six samples using a miRNeasy mini kit (Qiagen, Hilden, Germany) according to the manufacturer's protocol. The cDNA library construction was performed using the TruSeq® Stranded mRNA sample preparation kit (Illumina, CA, USA). Briefly, 300 ng of total RNA from each sample was enriched for poly-A containing mRNA using poly-T oligo-attached magnetic beads followed by mRNAs fragmentation at 94 °C for 8 min and held at 4 °C. The fragmented mRNAs were subjected to first-strand cDNA synthesis using Super-Script II reverse transcriptase (Invitrogen, Carlsbad, CA). The cDNAs were further converted into double-stranded cDNA and were purified using Agencourt AMPURE XP system (Beckman Coulter, CA, USA) to eliminate the reaction mix.
Next, the fragments were adenylated at 3′ ends and ligated onto the complimentary Illumina sequencing adaptors, and the mRNA stranded libraries were synthesised. After a clean-up step, the libraries were then amplified with PCR followed by streptavidin magnetic bead purification and two-step hybridisation reactions to obtain a pool of different indexing libraries. Finally, the quality and quantity of the sequencing library were assessed using a Bioanalyzer DNA high sensitivity chip (Agilent Technologies, CA, USA) and quantitative real-time PCR, respectively. High throughput next-generation sequencing was performed using Nextseq®500 Sequencing System (Illumina, CA, USA) according to the manufacturer's instruction, by setting a single-end sequence of 50 M reads per sample.
Read pre-processing, QC, alignment and gene quantification
Raw reads were evaluated for quality checks in terms of sequencing quality and contamination. Reads were trimmed and filtered using BBDuk [29]. Reads were then aligned to the latest reference genome (rn6) with GTF from Ensembl (v99) using STAR aligner [30]. Aligned reads were transformed into read counts per gene using the RSEM tool [31].
Differential expression analysis
Pairwise differential expression analysis was performed using the DESeq2 R package with MSC samples being a reference for individual experiments [32]. Briefly, expression counts were scaled and normalised to correct the sequencing depth and batch differences among samples for the pairwise group. These normalised counts were then used for differential expression analysis and to generate fold change values in log2 scale [log2(sample/control)] to contrast NPCs against MSCs. Genes with lower read count can generate higher fold change values, which may lead to possible false positives. Hence, to adjust the fold changes that arise due to the ratio between lower read counts in samples, we employed the fold-change shrinkage estimator approach from DESeq2. Genes with an adjusted P-value ≤ 0.05 and log2fold change of + 1 or − 1 were considered as significantly up- and downregulated genes.
Gene ontology enrichment analysis
Gene ontology analysis was performed on up- and downregulated genes from different analysis with the Cytoscape v3.6.1 with ClueGO v2.5.5 plugin [33]. Statistically enriched biological processes (Bonferroni step down adjusted p-value < = 0.001) (updated on 20/05/2019). In order to reduce the redundancy, the GO terms were functionally grouped according to their k-score, and the most significant GO term of each group was used to summarise the GO enrichment analysis result. The full list of significantly enriched GO terms are reported in Additional file 3 and the representative GO terms are shown in Fig. 4.
Gene set enrichment analysis
Gene set enrichment analysis (FDR < 0.25) was performed as described previously against the genesets from MSigDB with the ranking metric signal-to-noise with 1,000 geneset permutations for statistical assessment of enrichment [34]. The rat genes were 'humanised' by converting the rat gene expression profiles using Ensembl Biomart before performing GSEA [35].
Pathway analysis
Pathway analysis was performed using the Reactome analysis tool for up- and downregulated genes [36]. Pathways with FDR ≤ 0.05 were considered significant.
Transcription factor analysis
The reported functioning of genes as transcription factors was downloaded from the TFcheckpoint database [37], and reported Entrez gene IDs were converted to corresponding Ensembl ids using Ensembl Biomart. ChEA3 database web-server application was used on the differentially expressed genes, to perform transcription factor (TF) enrichment analysis. Briefly, 3,253 differentially expressed rat genes were humanized and gene symbols with human orthology confidence of 1 (high) were used as input in ChEA3 [38].
Quantitative real-time PCR validation
The differential expression of the eight genes was validated using quantitative RT-qPCR. RT2 Profiler PCR Arrays were used to assess the quantitative expressions of Mmp10, Gria2, Frzb, Cass4, Kif2c, Casq2, and Tagln (Additional file 4). The PCR array analyses were performed by Exiqon. A/S (Vedbaek, Denmark). The catalogue number for each gene is provided in Additional file 4. RNA samples were converted into first-strand cDNAs using QIAGEN RT2 First Strand Kit (Qiagen, Venlo, Netherlands). The first strands were used as the templates for the PCR. Then, the cDNA templates were mixed with RT2 qPCR master mixes and aliquoted into each well of the same plate containing pre-dispensed gene-specific primer sets. Relative gene expressions were calculated using the ddCt method, and the fold changes are listed in the excel sheet as (2^-(Ct (GOI)-mean Ct (HKG)) for all biological and technical replicates (M = MSCs and A = NPCs). The mean of the gene fold changes was calculated from the three biological and technical replicates. The bar charts (Additional file 4) represents relative gene expression of genes with error bars between MSCs and NPCs. The housekeeping genes used in the study were B2m, Hprt1 and, Rplp1. Three RNA and PCR quality controls were also used in the array.
Characterisation of rat MSCs
An overview of the experimental design is outlined in Fig. 1a. MSCs were extracted from the bone marrow of three Sprague–Dawley (SD) rats (three biological replicates) and were expanded in vitro from passage 0 to passage 2. MSCs were cryopreserved at passage 2, and subsequent experiments were conducted using the MSC line at passage 3. Leftover MSCs after NPCs differentiation and extraction of total mRNAs were differentiated into adipocytes, osteoblast, and chondrocytes. The MSCs were viable and capable of trilineage differentiation into adipocytes, chondrocytes, and osteocytes (Fig. 1b). Phenotypic analysis through immunocytochemical staining indicated that MSC expressed nestin, which co-localised with vimentin (Fig. 1c). Cytofluorimetric evaluation that we reported in our previous study confirmed that MSCs were positive for CD90 (86.8%), CD44 (35.4%), fibronectin (98.3%), vimentin (90.9%), and nestin (85.6%). However, they were negative for the macrophage marker, CD11b (2.0%) [19].
Study design and primary culture of rat MSCs. a An overview of study design. b Rat MSCs at passage four and trilineage differentiation of MSCs into adipocytes, chondrocytes, and osteoblast cells. Differentiated adipocytes, chondrocytes, and osteocytes were stained with oil red O, Alcian Blue and Alizarin Red S solution respectively and images were viewed under an inverted light microscope at 10 × magnification; scale bar = 50 µm. c Representative figure of MSCs expressing vimentin and nestin. Co-expression of vimentin and nestin confirms the true expression of nestin and vimentin in rat MSCs (Merged). Images were viewed under the confocal microscope at 10× magnification, scale bar = 100 µm
The MSCs were differentiated into NPCs as described in the method. Free-floating sphere-like cells were observed in the presence of EGF and bFGF after 24 h of differentiation (Fig. 2a). Cell proliferation assay showed that the sphere-like cells were viable (Fig. 2b) with cell growth highest at Day 3, and a noticeable dark core at the centre of the spheres was observable on Day 5. Another study also reported the presence of these dark cores in neural spheres [39]. Therefore, to avoid the effect of apoptotic cells in the centre core of the neurospheres, NPCs on Day 3 were used for subsequent experiments. We reported the characterization of MSC-derived NPCs in one of our earlier studies [19]; in the study, we reported 53.4% of Nestin expression in MSCs suspended in basal media. The flow cytometry analysis showed that Nestin was increased to 94.0% in the MSC-derived NPCs under the influence of EGF and bFGF. Moreover, gene expression for Nestin and Neurofilament (NEFL) was also assessed by real time PCR [19]. The expression of the two genes was significantly increased in NPCs compared to the control.
Characterisation and terminal differentiation of MSCs-derived NPCs. a Rat MSCs detached from the culture surface and formed free-floating neurospheres (Day 1, Day 3, and Day 5). Images were viewed and taken under an inverted light microscope at 20 × magnification; scale bar = 50 µm. b Cell viability of NPCs determined using MTS assay at days 1, 2, 3, and 4 post-induction. The mean ± SD of three independent experiments are shown. *P < 0.05. c NPCs positively expressed marker used to characterise neural stem cell, Sox-2, and showed low expression of fibronectin. Images were taken under confocal microscopy at 20 × magnification; scale bare = 40 µm. d NPCs adhered to the culture surface and differentiated into cells with neuronal-like morphology. The representative image was taken under an inverted light microscope at 20 × magnification, scale bar = 50 µm. e Beta-3-tubulin and f PSD-95 expression indicating the neurons. Images were taken under confocal microscope at 20 × (scale bar = 20 µm) and 40 × (scale bar = 50 µm), respectively. g Microelectrode pipette approaches a neuronal-like cell during whole-cell patch-clamp recording. The image was taken using a phone camera. h Representative figure of miniature excitatory postsynaptic current (mEPSC) of neuronal-like cells showing spikes (∆) compared to undifferentiated rat MSCs. Cells were recorded in voltage-clamp at -60 mV
In the current study we also measured, the expression of Sox2 in NPCs, which is the marker for neural progenitor stem cells. Indeed, expression of Sox2 was increased in MSC-derived NPCs (Basal media + EGF + bFGF) (47.6%) compared to the control Group E (MSCs in basal media only) (18.5%), (Additional file 1: Figure S1). The expression of the Sox2 was also confirmed by Immunocytochemistry (Fig. 2c).
The enhanced expression of these specific neuronal markers in the neurospheres indicated the differentiation of MSCs into NPCs. Fibronectin was also expressed in NPCs (93.1%) (Fig. 2c).
Terminal differentiation of NPCs
MSCs-derived NPCs differentiated into neuronal cells upon the removal of EGF and bFGF. NPCs adhered to the poly-D-lysine coated surface and differentiated into cells with elongated processes after 14 days in culture (Fig. 2d). Terminally differentiated cells expressed the neuronal marker beta-3-tubulin (Fig. 2e) and postsynaptic marker, PSD95 (Fig. 2f). Moreover, the original current traces of mEPSC recorded in an individual neuronal-like cell showed increasing amplitude compared to current traces recorded in MSCs (control) (Fig. 2g, h). Approximately 50% of NPCs were differentiated into neurons and expressed beta-tubulin III (Additional file 1: Figure S2).
Transcriptome analysis of NPCs at the day 3 of induction and MSCs
The whole transcriptome of MSCs and MSCs-derived NPCs was investigated using mRNA-seq. The transcriptomic analysis was conducted using total RNAs isolated from the three biological replicates of MSCs and MSCs-derived NPCs, a total of six samples (Fig. 1A). Quality control and mapping statistics showed that 96% of the reads (corresponding to 51.86 M reads) passed the filtering criteria across all samples (Additional file 2). Using the STAR alignment tool, approximately 97% of the reads corresponding to 50.5 M reads mapped on the genome across all samples. Adapter sequences were trimmed, and high-quality reads were mapped to the rat reference genome.
Before the differential gene expression analysis, normalisation was performed for read counts differences due to sequence depth and gene lengths variations. Transcripts per kilobase of transcript per million mapped reads were applied to normalise the number of reads for genes to the total number of mapped reads. The overall similarity between the replicates using principal component analysis (PCA) (Fig. 3a) and unsupervised hierarchical clustering using the distance matrix (Fig. 3b) was performed. Overall, the PCA analysis revealed that the two groups—A (MSCs-derived NPCs) and B (MSCs)—were well separated and that the samples clustered together in a manner that corresponded to the group and its corresponding replicates are clustered together The differentially expressed genes with two-fold and above were analysed between NPCs and MSCs.
a PCA plot of samples: Samples are colour coded based on their group. PCA method reduces the spatial dimensions of the gene expression pattern among samples and cluster the datasets based on their similarity. Results above show that the MSC samples are well separated from NPCs. b Unsupervised hierarchical sample clustering. Samples were hierarchically clustered using the sample distance calculated from the overall dispersion rate of gene expression. Results above show that the MSC samples cluster together and are separated from NPCs. c Volcano Plot: Illustration of differentially expressed genes for each comparison of NPCs versus MSC samples. For illustration purposes, a cut-off of 0.05 and ( ±) 2.5 is used for P-value and fold change respectively to highlight the most significant differentially expressed genes (highlighted in red). Significantly differentially expressed genes are annotated. P-values are capped at 50 for maximised view. d Fold changes of the respective genes in NPCs relative to rat MSCs; comparing the expression obtained from mRNA-Seq and RT-qPCR. Values of the RT-qPCR were normalized with the average values of the housekeeping genes
A total of 3,252 genes were differentially expressed with two or more folds. Additional file 3 contains all of the differentially regulated genes. Figure 3c shows the volcano plot of the analysis, which demonstrates a significant magnitude of change in the expression values of some representative genes. The plot reveals a considerable number of differentially regulated genes.
Out of 3,252 differentially regulated genes, 1,771 were upregulated, whereas 1,481 were downregulated in NPCs. The top 20 significantly differentially expressed genes are listed in Table 1. All the genes with their TPM values and differentially regulated genes with their fold changes are listed in Additional file 3.
Table 1 Summary statistics of the 20 most differentially regulated genes between NPCs and MSCs
Dataset validation by quantitative real-time PCR (RT-qPCR)
Eight genes with various differential folds were chosen from the gene list in Table 1 and Additional file 3 for dataset validation using RT-qPCR. The expression of five upregulated genes (Mmp10, Gria2, Frzb, Cass4, and Ret) and three downregulated genes (Kif2c, Tagln, and Casq2) were quantified by RT-qPCR (Fig. 3d). The RT-qPCR confirmed the analogous differential regulation of these genes in NPCs to that of the mRNA sequence dataset (Additional file 4). Hence, it validates the gene expression patterns in the sequencing data.
Gene ontology term and pathway enrichment analysis
All the differentially regulated genes were selected for gene ontology (GO) enrichment annotation and were analysed in ClueGO v2.5.5. Non-redundant GO terms (after semantics similarity) that were significantly over-represented in the list of up- and downregulated genes in NPCs were obtained (Fig. 4). Figure 4 lists the main GO terms that were enriched in the differentially regulated genes. The full list of all of GO terms is listed in Additional file 3. The main non-redundant GO terms enriched in NPCs and were related to neurogenesis and stem cells differentiation included autonomic nervous system, cell surface receptor signalling pathways, extracellular structure organisation, and programmed cell death (Fig. 4). The differentiation of MSCs into NPCs may involve many changes in other molecular processes. Consequently, other GO terms were also annotated during the differentiation. We only focused on the GO terms related to neurogenesis, signalling pathways, extracellular matrix and programmed cell death as these processes are crucial for MSCs differentiation into NPCs. While the relevant GO terms that were enriched in MSCs such as cytoskeleton organisation, structural cytoskeleton constituent and mitotic cell cycle process were related to the undifferentiated growth and morphological characterises of the in vitro growth of MSCs.
Gene ontology terms enriched in upregulated and downregulated genes in MSCs-derived NPCs. Significantly enriched (right-sided hypergeometric test) GO terms are shown in the y-axis, and the corresponding adjusted P-value (Bonferroni step down) are reported in the x-axis. The size of the dots reports the percentage of genes associated with the GO term identified in the upregulated genes
Gene set enrichment analysis (GSEA)
All the differential regulated genes were ranked, and then GSEA was performed. GSEA detects even slight coordinated changes in gene sets and identifies pathways not possible with other analysis. GSEA analysis identified eight pathways or biological process from MSigDB that were upregulated in MSCs (Table 2 and Fig. 5). GSEA plots suggested that the integrin pathway, cytoskeletal organisation, and the cell-cycle related process were upregulated in MSCs. Hence, these processes may have roles in MSC differentiation towards NPCs.
Table 2 List of pathways and biological process
Gene set enrichment. Gene sets from MSigDB significantly enriched are reported for gene expression analysis NPCs vs MSCs. All the terms reported are upregulated in MSCs
Specific transcription factors have crucial roles in stem cell differentiation and linage commitment. All the differential regulated genes were mapped with the transcription factor checkpoint database. A total of 149 transcription factors were differentially expressed between NPCs and MSCs; 104 transcription factors were upregulated in NPCs, whereas 45 were downregulated. Unsupervised clustering of transcription factors (Fig. 6a) demonstrated that samples within the group were consistent in expression and that samples clustered according to the group; Fig. 6b also lists top ten upregulated and downregulated transcription factors during the differentiation. Additional file 5 contain all the differential regulated transcription factors reported in the differentiation. To gain insight into the specific transcription factors that may be associated to the observed gene expression changes and potentially play roles in the NPC differentiation, the list of 3252 differentially expressed genes were subjected to transcription factor enrichment analysis using ChEA3 [38] (Additional file 3). Figure 7 shows the top 10 ranked enriched transcription factors from ChEA3 analysis with significantly upregulated (red arrows) and downregulated (blue arrows) TFs in NPCs.
Transcription factor analysis. a Hierarchical clustering of differentially expressed transcription factors. Data shown are the significantly differentially expressed transcription factors. The colour scale bar shows z-score values after z-score row normalisation. The heatmap was generated using the heatmap package from R. b Top 10 upregulated and downregulated transcription factors with their average fold changes in NPCs
Shown are the top 10 ranked enriched transcription factor from ChEA3 analysis with significantly upregulated (red arrows) and downregulated (blue arrows) TFs in NPC. Gene Tcf21 is not shown as it has zero values across all the samples. The colour scale bar shows TPM values after z-score row normalization. Heatmap was generated using pheatmap package from R
The transcriptomic analysis is an essential tool for understanding the molecular processes during stem cells differentiation. In our current and previous studies, we successfully extracted MSCs from the bone marrow of SD rats, which expressed CD90, nestin, fibronectin, and vimentin [19]. Once the successful platform of MSCs was established, they were then differentiated into NPCs in the presence of bFGF and EGF. NPCs attained optimum viability and optimum proliferation on Day 3. Other studies have also reported MSCs differentiation into NPCs after three days of induction in the presence of bFGF and EGF [23,24,25].
In the previous study, we differentiated NPCs into neuronal-like and glial-like cells [19]. In this study, we assessed the derived neuron functionality through action potential that can be elicited. Hence, the derived neurons were able to elicit the action potential. Furthermore, the neurons expressed the beta-tubulin III, a marker of mature neurons, and they also expressed the postsynaptic density protein 95 (PSD-95), indicating that the derived neurons communicate with each another [40]. Hence, NPCs can be formed on Day 3 of induction from MSCs in the neural media containing bFGF and EGF, and the derived NPCs can be differentiated into glial and neuron cells. These analyses confirmed that MSCs were differentiated into NPCs.
The main aim of this study was to compare the transcriptomes of MSCs and MSC-derived NPCs (on Day 3 of induction) to unravel the molecular processes involved in early neural differentiation of MSCs.. Sequencing was conducted using the Nextseq®500 sequencing system by setting a single-end sequence of 50 million reads per sample. The details of quality control and mapping are provided in Additional file 2. Briefly, 96% of the reads corresponding to 51.86 million reads pass the filtering criteria across all samples, and approximately 97% of the reads corresponding to 50.5 million reads mapped on the genome across all samples.
The global transcriptomic analysis revealed 3252 differentially regulated genes with two or more folds between MSCs and NPCs; 1771 of them were upregulated, whereas 1481 were downregulated in NPCs. The profound changes in the transcriptomes during the differentiation indicate that NPCs have different expression profiles indicating the MSCs were differentiated into NPCs. Eight of the differentially regulated genes were analysed using RT-qPCR, and their differential regulations were analogous to that reported in mRNA sequencing (Additional file 5), providing confidence regarding the other differential expressed genes in mRNA sequencing.
All the differentially expressed genes were assessed for GO term enrichment. All the details of the GO terms, including the number of associated genes, level of GO terms, and statistical significance values, are provided in Additional file 3. Figure 4 lists the main non-redundant GO terms that were enriched either in MSCs or NPCs. The main GO terms related to neural and stem cells differentiation enriched in NPCs included the autonomic nervous system, cell surface receptor signalling pathways, extracellular structure organisation, and programmed cell death.
Fifteen genes from the autonomic nervous system GO term (GO:0048483) were upregulated in NPCs (Additional file 3): Ednra, Ednrb, Egr2, Fn1, Gbx2, Hes3, Kif26a, Ntrk1, Plxna3, Ret, Sema3a, Sema3f, Six1, Sox8, and Vcam1. Ret was also confirmed by RT-qPCR. Ret signalling has a crucial role in the development of the peripheral and central nervous system and the enteric gut system [41,42,43]. The upregulation of these neural related genes suggested that the NPCs were neural progenitor-like cells.
Results revealed that 291 genes involved in the cell surface receptor signalling pathways GO term (GO:0007166) were upregulated in NPCs. This GO term lists the signalling pathways that are activated by the binding of the ligand and activate the transcription factors. One of the genes Frzb, which was also validated by RT-qPCR, is a component of the Wnt pathway, which plays a role in the proliferation of neural stem cells, neuronal differentiation, and development [44, 45].
Another GO term related to NPCs differentiation was programmed cell death (GO:0012501). Our previous study showed that there was some apoptosis during the differentiation of MSCs into NPCs. We enhanced the differentiation by adding IGF-1, which in turn enhanced cell proliferation and inhibited apoptosis [19]. In this transcriptomic analysis, 186 genes related to programmed cell death GO term were upregulated in NPCs.
Hence, it indicates that programmed cell death was occurring in some cells when MSCs was differentiating into NPCs.
Sixty-one genes of the extracellular structure organisation GO term (GO:0043062) were upregulated in the NPCs. A microarray study revealed that the extracellular matrix (ECM) genes were upregulated in the NPCs derived from human MSCs [46]. In our study, ECM proteins, such as Mmp10, Mmp3, Mmp13, Timp4, Sparcl1, and fibronectin (Fn1) as well as various types of collagen family genes (Col10a1, Col15a1, Col16a1, Col17a1, Col18a1, Col23a1, Col25a1, Col27a1, Col3a1, Col4a4, Col5a3, and Col6a1) were upregulated in NPCs (Additional file 3). This data reflects the roles of extracellular modelling in the differentiation of MSCs into NPCs. Matrix metalloproteinase-10 (Mmp10) expression was also confirmed with RT-qPCR. Recent research indicates that Mmp10 has a role in promoting neurogenesis and neuroprotection in the human brain [47]. Hence, it indicates the differentiation of MSCs into NPCs involves extensive extra cellular remodelling.
The main relevant GO terms enriched in MSCs or downregulated in NPCs were: cytoskeleton organisation (GO:00070109), actin cytoskeleton organisation (GO:0030036), structural cytoskeleton constituent (GO:0005200), mitotic cell cycle (GO:0000278), and mitotic cell cycle process (GO:1903047). These results were expected as MSCs possessed cytoskeletal organisation to maintain the fibroblast-like morphology in cell culture. The cytoskeletal organisation is also involved in the differentiation of MSCs. One study reported that mechanical stretches are responsible for cytoskeletal organisation enhanced the differentiation of MSCs into osteoblasts [48]. Another study reported that the organisation of actin modulated MSC migration [49].
Interestingly, Peng et al. reported that cytoskeletal organisation was a crucial step during the differentiation of MSCs into neural lineages [50]. The authors applied RhoA kinase inhibitor, which enhanced the differentiation of MSCs into neural lineages. The derived cells expressed more nestin and MAP2 compared to the control. Another study also revealed that cytoskeletal rearrangement was a critical component during neural development [51]. The cytoskeleton changes take place with signalling pathways and environmental cues. These polymers are formed due to non-covalent bonds which make it easy to form or dismantle. The differentiation of MSCs involves changes in morphology that require cytoskeletal reorganisation [52].
During gene set enrichment analysis (GSEA) differential genes were ranked based on their fold changes and statistically significancant. After ranking, GSEA was performed on certain gene sets from MSigDB to calculate their enrichment. GSEA revealed that the integrin pathway and cytoskeletal organisation were enriched in MSCs. One study reported that integrin enhanced the differentiation of MSCs into osteoblast [53]. Other studies also confirmed the roles of integrin pathway in MSC differentiation [54, 55]. Furthermore, integrin interacts with cytoskeletal proteins to mediate their effects on cells [56, 57]. In this way, integrin can mediate the interaction between cytoskeletal proteins and ECM [58]. The integrin resides in focal adhesions which mediate this interaction; hence, focal adhesion binds the cytoskeletal protein with ECM. This interaction regulates the proliferation, migration, and differentiation of MSCs. Due to the differential regulation of ECM, integrin and cytoskeletal related genes, we predict the analogous interactions of ECM, integrin and cytoskeletal proteins would drive the MSC differentiation into NPCs.
Both GSEA and GO terms enrichment analyses showed that upregulated genes related to cell cycle-regulation in MSCs. Cell cycle regulation is crucial for enhanced MSC differentiation into adipocytes. One study reported that cell cycle arrest in G1 enhancing the differentiation of MSCs into adipocytes [59]. Microarray analysis also confirmed that during adipogenic differentiation from MSCs, cell cycle arrest genes were upregulated [60]. One other study reported that berberine enhanced the neural differentiation from neuroblastoma cells by cell cycle arrest [61]. In other study, the inhibition of cyclin-dependent kinase 4 (CDK4) led to the hypo phosphorylation of Smads and STAT3, which enhanced human MSC differentiation into NPCs [62]. In pluripotent stem cells such as embryonic stem cells, cell cycle regulation is also crucial for renewal and differentiation. The embryonic stem cells have shorter G1 and G2 compared with adult stem cells, but the G1 phase enlarges when embryonic stem cells are differentiated [63]. Differential regulation of cell cycle related genes indicate the cell cycle regulation may play a crucial role in the differentiation.
The other main aim of the current study was to compare the transcription factors between NPCs and MSCs to determine the transcription factors that are involved in the differentiation of MSCs into NPCs. Specific transcription factors are crucial in differentiation and trans-differentiation. These specific factors, particularly master transcription factors, bind to enhancers or upstream sequencers and regulate many genes, resulting in the differentiation or trans-differentiation of the cell [64]. Apart from a few transcription factors, such as MyoD, which enhance muscle differentiation, most transcription factors interact with others, forming a transcription factor network which maintains the phenotype of cells [65]. Fibroblast was induced into a pluripotent state through the ectopic expression of OCT4, SOX2, c-MYC, and KLIF4 in Fibroblasts [66]. These factors form and maintain pluripotency by forming a transcription factor network in embryonic stem cells [67].
MSCs can be derived from several tissues, and discovering core transcriptomes such as transcription factors that maintain MSC multipotency is crucial. In 2014, the transcriptomics of human MSCs from the bone marrow and the placenta were compared [68]. There was common and dissimilar genes expression between the two stem cell types. In another detailed study in 2016, the transcriptomes of human MSCs from the bone marrow, adipose tissues, placenta, and fibroblast cells were compared [69]. This meta-analysis revealed that human MSCs had 13 transcription factors that defined MSC multipotency: ARID5B, CREB3, EPAS1, FHL2, GTF2E2, GTF2IRD1, ID3, LMO7, SNAI2, TAF13, TEAD3, TULP3, and ZNF532. Since these transcription factors define the core of the MSCs lineage, their expression was assessed in the NPCs. Creb3, Fhl2, Id3, Snai2, and Taf13 were downregulated in NPCs, confirming the MSCs were differentiated into NPCs.
Among the 104 transcription factors, the most highly significantly expressed transcription factor in NPCs was Hes3. Hes3 is crucial for nervous development; inactivation of this gene leads to depletion of neural stem cells [70]. The second most significant transcription factor was Tbx10, which is a T-box binding protein that has a crucial role in motor neuron development [71]. Another significant transcription factor involved in nervous system development is Nr4a1 [72]. The 104 upregulated transcription factors in NPCs have their role in neurogenesis. However, future studies should focus on finding the transcription factor network related to these 104 genes that define NPCs.
Transcription factors enrichment analysis was also performed by ChEA3 to find transcription factors that are associated with differential gene changes and they play roles in NPCs differentiation. The list of 3252 differentially expressed genes were subjected to transcription factor enrichment analysis [38]. Among the top ten enriched transcription factors (Fig. 7), the analysis revealed Meox1 and Aebp1 are significantly upregulated and Osr1, Foxs1 and Cenpa are significantly downregulated in NPC. Foxs1 is a sensory neuron‐specific gene [73]. Interestingly, Heyl, a transcription factor known to promote neuronal differentiation was also identified among the top 3 transcription factors [74]. The complete list of all 1632 site-specific TFs covered by ChEA3, prioritized based on their integrated MeanRank score, along with the overlapping genes found to be differentially expressed by for each TF entry are listed in Additional file 3.
The vast transcriptomic expression difference between MSCs and NPCs indicate that these two cell types are distinct and unique transcriptomic profiles define the two cell types. Some of those differentially expressed genes, particularly the transcription factors can be used as markers of differentiation as well as they can be used further to optimise the differentiation of MSCs into NPCs.
Overall, this study indicated that rat MSCs could be differentiated into NPCs after Day 3 of induction. NPCs have the capacity for terminal differentiation into neurons. The transcriptomic analysis identified a complex regulation of genes during early neural differentiation of rat MSCs into NPCs in the presence of EGF and bFGF. The transcriptomic data obtained from this study may provide valuable information regarding the biochemical process instigating neural differentiation of MSCs. The transcriptomic analysis revealed the separate gene expression profiles that define MSCs and NPCs.
The vast differences in the transcription factor expression profiles (particularly the transcription factor profiles) between NPCs and MSCs warrant further investigation. Future studies should seek to discover and describe the transcription factor network that defines and maintains NPCs.
All data generated and/or analysed during this study are included in this published article or deposited in the GEO database NCBI (https://www.ncbi.nlm.nih.gov/geo/), with the accession number being GSE104548 (Temporary reviewer's token: apkhkswkthmznqt). Any additional data used and analysed during the current study are available from the corresponding author on reasonable request.
Neural progenitor-like cells
bFGF:
Basic fibroblast growth factor
EGF:
iPSCs:
RT-qPCR:
Quantitative real-time PCR
GSEA:
Sprague Dawley
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Kageyama R, Ohtsuka T, Kobayashi T. Roles of Hes genes in neural development. Dev Growth Differ. 2008;50(Suppl 1):97. https://doi.org/10.1111/j.1440-169X.2008.00993.x.
Pocock R, Mione M, Hussain S, Maxwell S, Pontecorvi M, Aslam S, Gerrelli D, Sowden JC, Woollard A. Neuronal function of Tbx20 conserved from nematodes to vertebrates. Dev Biol. 2008;317:671–85. https://doi.org/10.1016/j.ydbio.2008.02.015.
Cirnaru M, Melis C, Fanutza T, Naphade S, Tshilenge K, Muntean BS, Martemyanov KA, Plotkin JL, Ellerby LM, Ehrlich ME. Nuclear receptor Nr4a1 regulates striatal striosome development and dopamine D1 receptor signaling. ENeuro. 2019. https://doi.org/10.1523/ENEURO.0305-19.2019.
Montelius A, Marmigère F, Baudet C, Aquino JB, Enerbäck S, Ernfors P. Emergence of the sensory nervous system as defined by Foxs1 expression. Differentiation. 2007;75:404–17. https://doi.org/10.1111/j.1432-0436.2006.00154.x.
Jalali A, Bassuk AG, Kan L, Israsena N, Mukhopadhyay A, McGuire T, Kessler JA. HeyL promotes neuronal differentiation of neural progenitor cells. J Neurosci Res. 2011;89:299–309. https://doi.org/10.1002/jnr.22562.
Infographics used in Figure 1a were created using the Mind the Graph platform (https://mindthegraph.com/). English grammar and language were corrected by Scribendi (https://www.scribendi.com/).
The Competitive Research Project Grant funded this study, grant number: 1602145036-P from the University of Sharjah, a grant received by A.A.K., and the Malaysia Toray Science Foundation, a grant received by T.J.H., grant no: 304/PPSP/6150142/M126. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.
Amir Ali Khan and Tee Jong Huat contributed equally to this work
Department of Applied Biology, College of Sciences, University of Sharjah, P.O. Box 27272, Emirate of Sharjah, United Arab Emirates
Amir Ali Khan, Abdullah Al Mutery & Hassen Hadj Kacem
Department of Biological Sciences, Faculty of Science, National University of Singapore, Singapore, 117543, Singapore
Tee Jong Huat
Department of Neuroscience, School of Medical Sciences, Universiti Sains Malaysia Health Campus, Jalan Raja Perempuan Zainab II, 16150, Kubang Kerian, Kelantan, Malaysia
Tee Jong Huat, Muhammed Faruque Reza & Jafri Malin Abdullah
Department of Biomedical and Clinical Sciences (BKV), Linköping University, P.O. Box 581 83, Linköping, Sweden
Ahmed Taher El-Serafi
Research Institute of Science and Engineering, University of Sharjah, P.O. Box 27272, Emirate of Sharjah, United Arab Emirates
Amir Ali Khan, Hassen Hadj Kacem & Sallam Hasan Abdallah
Brain and Behavior Cluster, School of Medical Sciences, Universiti Sains Malaysia Health Campus, Jalan Raja Perempuan Zainab II, 16150, Kubang Kerian, Kelantan, Malaysia
Jafri Malin Abdullah
Department of Pathology, School of Medical Sciences, Universiti Sains Malaysia Health Campus, Jalan Raja Perempuan Zainab II, 16150, Kubang Kerian, Kelantan, Malaysia
Hasnan Jaafar
Amir Ali Khan
Abdullah Al Mutery
Hassen Hadj Kacem
Sallam Hasan Abdallah
Muhammed Faruque Reza
Conceptualisation, AAK and TJH; methodology and investigation, AAK, TJH, MFR, SHA, ATE; validation, AAK, TJH, AAM, SHA, ATE, HHK, MFR, JMA, HJ; formal analysis, AAK, TJH, AAM, SHA, ATE, HHK, MFR, JMA, HJ; Data curation, AAK, TJH; resources, AK, TJH, AAM, MFR, JMA, and HJ; writing—original draft preparation, AAK, and TJH; writing—review and editing, AAK, TJH, AAM, SHA, ATE, HHK, MFR, JMA, HJ; funding acquisition; AAK, TJH, JMA, HJ. All authors read and approved the final manuscript.
Correspondence to Amir Ali Khan.
Studies involving animal tissue were approved by the Animal Ethics Committee of Universiti Sains Malaysia according to the Institutional Animal Care and Use Community (IACUC) guidelines [USM/Animal Ethics Approval/(59)(169)].
All authors declare that they have no competing interest.
Additional file 1: Figure S1.
Representative flow cytometry analysis of Sox2 expression by MSC-derived NPCs and MSCs in basal media. Figure S2. Representative flow cytometry analysis of Beta-3-tubulin expression of terminally differentiated NPCs into neurons.
Additional file 2.
Read pre-processing, quality control, alignment, and gene quantification. Before differentiation expression analysis, raw reads were evaluated for quality check in terms of sequencing quality and potential contamination. Trimming was performed using BBDuk. Reads were aligned to the latest reference genome (rn6) with GTF from Ensembl (v99) using STAR aligner. Aligned reads were transformed into read count per gene using RSEM tool.
Detail of all differentially regulated genes and enriched gene ontology ontologies during the differentiation. Significantly enriched GO terms generated from ClueGO plugin for both up and downregulated genes in NPCs. Details of transcription factor enrichment analysis using ChEA3.
Detail of dataset validation using quantitative real-time PCR. The expression of selected genes of interest was validated using quantitative real-time PCR.
Full list of differential regulated transcription factors in MSCs-derived NPC.
Khan, A.A., Huat, T.J., Al Mutery, A. et al. Significant transcriptomic changes are associated with differentiation of bone marrow-derived mesenchymal stem cells into neural progenitor-like cells in the presence of bFGF and EGF. Cell Biosci 10, 126 (2020). https://doi.org/10.1186/s13578-020-00487-z
DOI: https://doi.org/10.1186/s13578-020-00487-z
mRNA-seq
bFGF
Transcriptomic


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View from Away: 9/11 victim fund should be made permanent
By Erica Nitschke
In 2015, a Republican House and a Republican Senate, working with a Democratic president, provided medical coverage and financial support to the heroes and victims of the terror attacks of Sept. 11, 2001, who were sickened by poisons released into the downtown air when the World Trade Center, hit by terrorist-hijacked jets, collapsed into that ominous grey plume.
Thankfully, the health treatment was fully underwritten for the lifetimes of the thousands of people suffering ailments, including several kinds of cancers — maladies sure to claim many lives.
But the compensation fund for the ill and for the estates of the dead is running out of money, slashing the Department of Justice-approved payments for deserving people who have lost so much.
This time it must be a Democratic House and a Republican Senate, working with a Republican president, who make the 9/11 Victim Compensation Fund permanent.
The bipartisan bill in the House now has a majority of members as sponsors, above the magic 218 number and climbing. Although the terror attack and subsequent health disaster were here, World Trade Center victims live in every state, and there are sponsors from every part of the country, very far from New York.
There are Democrats from Hawaii and Republicans from Alaska, like Don Young, the dean of the House, the senior member of the chamber. There are liberals like Jerry Nadler, who represents Ground Zero, and conservatives like Wyoming's Liz Cheney, No. 3 in the GOP leadership.
The bill is also advancing in the Senate, gaining bipartisan momentum. Republicans Marco Rubio, Pat Toomey and Rob Portman all were important to getting it done last time. Their support is needed again. But in fact, every member, House and Senate, should join and send a bill with unanimous support to the White House.
This is about duty, honor and patriotism. The terrorists didn't attack Manhattan. They attacked America.
Editorial by the New York Daily News
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MSA Safety Inc (MSA) Files 10-K for the Fiscal Year Ended on December 31, 2018
GuruFocus.com
- By insider
MSA Safety Inc (MSA) files its latest 10-K with SEC for the fiscal year ended on December 31, 2018. MSA Safety Inc develops, manufactures & supplies safety products that protect people & facility infrastructure. Its products include fixed gas & flame detection systems, portable gas detection instruments, head protection product & fall protection device. MSA Safety Inc has a market cap of $4.01 billion; its shares were traded at around $104.22 with a P/E ratio of 62.42 and P/S ratio of 3.00. The dividend yield of MSA Safety Inc stocks is 1.47%. MSA Safety Inc had annual average EBITDA growth of 0.30% over the past ten years.
Warning! GuruFocus has detected 6 Warning Signs with MSA. Click here to check it out.
MSA 15-Year Financial Data
The intrinsic value of MSA
Peter Lynch Chart of MSA
For the last quarter MSA Safety Inc reported a revenue of $361.8 million, compared with the revenue of $346.1 million during the same period a year ago. For the latest fiscal year the company reported a revenue of $1.4 billion, an increase of 13.5% from last year. For the last five years MSA Safety Inc had an average revenue growth rate of 3.4% a year.
The reported diluted earnings per share was $3.18 for the year, an increase of 374.6% from previous year. Over the last five years MSA Safety Inc had an average EPS decline of 5.4% a year. The MSA Safety Inc had a decent operating margin of 13.92%, compared with the operating margin of 5.52% a year before. The 10-year historical median operating margin of MSA Safety Inc is 11.87%. The profitability rank of the company is 7 (out of 10).
At the end of the fiscal year, MSA Safety Inc has the cash and cash equivalents of $140.1 million, compared with $134.2 million in the previous year. The long term debt was $341.3 million, compared with $447.8 million in the previous year. The interest coverage to the debt is 10. MSA Safety Inc has a financial strength rank of 6 (out of 10).
At the current stock price of $104.22, MSA Safety Inc is traded at 98.5% premium to its historical median P/S valuation band of $52.51. The P/S ratio of the stock is 3.00, while the historical median P/S ratio is 1.52. The stock gained 28.09% during the past 12 months.
For the complete 20-year historical financial data of MSA, click here.
This article first appeared on GuruFocus.


In our spotlight on home series which has become quite popular, this article focuses on luxury homes in Hidden Hills and Calabasas. The swank Los Angeles suburb of Calabasas, California, has an ever expanding roster of past and present celebrities. Most known for its celebutantes like the Biebs, his on-again off-again love, Selena Gomez, and of course the Kardashians, this community is home to a myriad of TV and film stars. While there are some more moderately priced neighborhoods in this suburb, what you see in the media is typically the lavish homes located in Hidden Hills.
Calabasas was originally home to the Chumash people, the area "discovered" by Spanish explorers in 1776. And…Most of the public idea of Calabasas comes from the gated community of Hidden Hills, which is actually considered its own municipality (California is the only place in the U.S. where gated communities have been legally categorized as separate cities).
Hidden Hills is an area in Calabasas made famous by wealthy bad boys and reality stars but the truth is that it is a gorgeous, affluent, gated community. Hidden Hills is the second-wealthiest neighborhood in Los Angeles County.
Hidden Hills: More Bang for Your Buck?
Although Hidden Hills is rife with mansions and wealth, your money is quite frankly, well spent on homes here. In the valley there is more land for your dollar especially in the West Valley. The weather is a little warmer so you give up a bit of the ocean breeze and lower temps, but you are still a stone's throw from Malibu. If you choose to venture out. Malibu is just over the hill.
In addition to its glitz, if you are starting a family, Hidden Hills is home to the Round Meadow Elementary School, one of the highest rated in the community – take a look at what parents say about this gem in the "hills". Also, you are adjacent to the very high rated school districts of Oak Park and Malibu.
Activities in Calabasas abound – home to the Calabasas Country Club, the city boasts a championship golf course. If you enjoy hiking, you are steps away from some of the best Southern California hiking trails as you will live nearby to Saddle Creek which is in the Santa Monica Mountains and Malibu Creek State Park. And if you want to get your surf on at the beach, hop in the car and head to Malibu Beach.
Undoubtedly, Hidden Hills in Calabasas is the place to live in Los Angeles County and obviously the reason so many celebrities and business magnates flock to buy estates in the West Valley. If you are looking for your dream home and the ultimate in luxury and quality of life, consider a home in Hidden Hills.
For more information on viewing homes in Hidden Hills or in the surrounding communities, contact Lydia Gable today. And stay tuned for the next spotlight which will be on Westlake Village, a dream community and my very own town for home, work and play.


Hillsborough schoolteacher Stella Gentry Sharpe published Tobe in 1939 after a little boy in her neighborhood pointed out that all his story books were about white children. Sharpe then wrote the content of her first children's book based on her observations of the same little boy and his family, the McCauleys. After completing the story, she did not want to settle for illustrations and felt that photographs were necessary to capture the children's lives and personalities. It would be another three years before the right man for the job came along: Charles Anderson Farrell.
By the time Farrell was hired, the McCauley children had grown, and so Farrell was tasked with finding new subjects for his photographs. He traveled to the African American community of Goshen, N.C., where he used two families, the Garners and the Herbins, to stand in for Tobe and his large family. Recently, Farrell's photographs from Tobe and other periods of his career have been fully digitized at the University of North Carolina's Louis Round Wilson Special Collections Library.
P0024/0051, "Snake in the road," in the Charles Anderson Farrell Photographic Collection (P0024), North Carolina Collection Photographic Archives, The Wilson Library, University of North Carolina at Chapel Hill.
P0024/0012, "Our Goat," in the Charles Anderson Farrell Photographic Collection (P0024), North Carolina Collection Photographic Archives, The Wilson Library, University of North Carolina at Chapel Hill.
P0024/0023, "Our Cart," in the Charles Anderson Farrell Photographic Collection (P0024), North Carolina Collection Photographic Archives, The Wilson Library, University of North Carolina at Chapel Hill.
Tobe is now available as a UNC Press Enduring Edition. UNC Press Enduring Editions use the latest in digital technology to make available again books from our distinguished backlist that were previously out of print. These editions are published unaltered from the original, and are presented in affordable paperback formats, bringing readers both historical and cultural value.


Here, we will discuss about a prominent person who is very popular throughout the country. The one who is considered to be super strong and is also worshipped in many southern states. The Star of Tollywood, Rajnikanth Sir!
Rajnikanth Sir is very popular for his charity work and hence, he is not one of the richest people of the country. However, he still has a Net Worth of 55 Million US $. This in Indian Currency will be around INR 350 Crores. A lot of money is spent by him on charity work and he has also helped a lot of people. In fact, we all must have heard f cases in which if the movie fails, Rajnikanth Sir has returned the fees back to the Producing Company in order to reduce their losses.
Rajnikanth Sir has a beautiful house in Chennai which was built by him in the year 2002. The Current Market Price of the same is around 35 – 40 Lakhs.
Unlike most other actors, Rajnikanth Sir doesn't own 10's of Cars, He has 3 Luxury Cars which he considers sufficient for his needs. These cars are Toyota Innova, Range Rover & Bently.
III] Average Movie Remuneration: Approximately, 50 – 60 Crores is charged by Rajnikanth Sir yearly for his movies.
IV] INVESTMENTS: It seems that Rajnikanth Sir has around 100 – 120 Crores Investments in Current Assets.
In case of any celebrities, a lot of earning depends on fan following. Rajnikanth Sir is one of the most popular actors of our country. There are a lot of temples also in Southern India where he is worshipped.
Thus, we can be very positive that the net worth of Rajnikanth Sir will keep on growing through the years.
Rajnikanth Sir was born on 12th December, 1950 in the state of Karnataka in India. His original name is Shivaji Rao Gaikwad. He is the fourth child of his parents. His mother – Ramabai Gaikwad expired when he was a little kid. His father Ramoji Rao Gaikwad was a single parent.
It is a shocking fact about Shivaji that his mother tongue is Marathi even though he has not done any movie in his mother tongue.
As Shivaji did not belong to a very good family, he had to take up several odd jobs before he turned out as an uprising actor. He has worked as a bus conductor for Karnataka State Transport Corporation in the city of Bangalore.
Suddenly he realized he ought to be an artist and he started taking up various stage plays. Slowly slowly, he became quite popular for those. Eventually he started getting roles in movies and all the movies for which he worked turned out to be Box Office Hits.
Another shocking news about Shivaji or Rajnikanth Sir is that his story has been included in the Study Syllabus of Central Board of Secondary & Higher Education (CBSE) in the chapter called 'From Conductor to Superstar'.
Rajnikanth then married Latha Rangachari who was a student of Ethiraj College for women who went to talk to him for an interview for her college magazine.
They have 2 daughters named Aishwarya Rajnikanth & Soundarya Rajnikanth. His wife runs a school which is named 'The Ashram'.
He also started supporting Indian National Congress after meeting with the then Prime Minister Mr. P. V. Narsimha Rao.
In his glamorous career, Rajnikanth sir has received a good number of awards. The most prominent being Filmfare Award for Best Tamil Actor for one of his movies. A lot of people have insisted Rajnikanth Sir towards becoming an actor, however he has politely refused all these offers.
At the end, I would not forget to mention that he is one of those actors who have left a mark on our lives & no matter what, he always keeps inspiring us. So, we wish him not just an always growing net worth but also good health & lots of love.


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GTPulse: Santa's Mailbox Is In Traverse City
What was meant to be a decoration has turned into a magical postal service after a little girl named Melah dropped a letter off in Santa's mailbox.
They've done it again. Two of the crew that put together the impressive Pirates of the Caribbean Halloween display on Parker Place in Traverse City have gone all out for Christmas. The ghostly ship was an interactive haunted house that Brittany Merenda and Ryan Donnell encouraged all to explore, and they're hoping that folks will interact with their Christmas display too, by dropping off their letters to Santa at the Northpole mailbox featured in their cheery and bright set up. And by bright, I mean, there is absolutely no way you will miss it.
"The final total of lights is 20,232," Ryan said.
"Once we did the final count we were still like 400 shy of 20,000," Brittany said. "We're that close so we went out and wrapped another bush and another tree. We had to pass the 20,000 mark."
As a theatre professional that works in projection design, Brittany is no stranger to fantastic displays. Though her house is the one to keep an eye out for on Halloween, this is the first time she's had such a large outdoor setup for Christmas decor.
"I usually work so much, and this is always my busiest time of year," she said. "I'm usually traveling and not home, obviously not this year, so we actually had time to go a little crazy."
The illumination includes snowmen under archways, reindeer, Santa and his sleigh, a Christmas tree made of lights, and a row of candy canes that leads right up to a fire engine red mailbox that reads Letters To Santa in curly gold letters on the front. The mailbox was gifted to Brittany's husband Tim Merenda.
"My mom and sister gave that to Tim two years ago as a Christmas gift. We put it up last year and it kept falling over and we had put it closer to the back of the house. So this year, we reinforced it with all of these zip ties so it was secure and we could ask people to put their letters in."
Initially, the mailbox was just going to be a part of the decorations. But when a letter was found in the mailbox from a little girl named Melah, Brittany and Ryan were so touched that they wanted more kids to do the same.
"There was no return address, it was just a drawing and we thought, 'Oh my gosh this is so cool we should tell people that if they put a letter in with a return address Santa will write back.'"
Brittany let her neighbors know in the Nextdoor app, and so far they've already received 21 letters. They're encouraging not only the kids to submit their letters, but also the parents to submit one on behalf of their kid too, including special information that Santa can include in his response to them. Any letter with a return address will receive a personalized letter back, with a shimmery red wax seal and all. When I visited Ryan and Brittany, they were working on the perfect wax recipe to close the letters with.
Sneaking out to pull letters out of the mailbox has become more exciting than receiving a package in the mail, but they have to be careful. Little kids in the neighborhood have submitted letters of their own, so in daylight hours, Brittany and Ryan have to hold back so none of the little ones see them emptying the mailbox.
"We told one of our neighbor kids that an elf comes every night at midnight to collect the letters," Brittany said.
A few kids who have submitted their letters are reaching the age where skepticism on Santa starts to creep in.
"How old is the kid who came to put a letter in because he's a little on the fence?" Brittany asked Ryan.
"He's in first or second grade, so we're going to put in some key phrases that the parents told us to say to make it really personal," Ryan said.
"One of our friends has an 11-year old that is starting to not believe and they're going to drop a letter off. That's what I really want and am hoping for, that those kids who are almost to the age where they don't believe, that we can get another year of believing out of them. Some of these lists are long, some are flamboyant, one of the things that I think is important is that Santa doesn't pick one person to give expensive things to. We won't promise specific gifts on their lists, but we are going to do our best to explain that Santa is not the outlandish gift giver. He's a practical, equal gift giver."
Bundle your kids up with their letters and take a drive around Parker Place in Traverse City. The whole Stoneridge neighborhood is festive and will give you a light show to enjoy driving around before and after you drop your letter off. Make sure to leave a return address, and make sure to follow Stoneridge_decorates on Instagram to keep up with all of the neighborhood's holiday decorations.
"We have a Northpole post stamp, and we've picked out Santa's signature," Brittany said. "The idea is that it looks very authentic. If there's any year to believe in something, this is the year."


SAN MARCOS — Cal State San Marcos celebrated the ceremonial groundbreaking of its 2,200-seat on-campus arena this week.
Athletics officials, school administrators and students hailed the forthcoming $11.4 million Cougar Sports Center as a huge achievement for the campus as it transitions from the National Association of Intercollegiate Athletics to the NCAA.
Crews will complete construction by August 2016, in time for the 2016-17 women's volleyball season.
Cal State San Marcos' court sport programs — volleyball and men's and women's basketball — have had a successful run in their four years of existence, including nine conference championships and an undefeated "home" record for the highly-touted men's basketball team over the past two seasons.
This success, however, has come with sacrifices for the nomadic teams, which play most of their games in front of sparsely attended crowds at local gymnasiums, including Pacific Ridge and Escondido high schools and MiraCosta College.
Andrea Leonard, the head women's volleyball coach, said the new arena would be transformative for the entire university community, both for morale and from a recruiting standpoint.
"This will be our true home court advantage where our student population can easily arrive from class to cheer on their team, parents and families arriving with ease and our teams raising those championship banners to the sea of blue," Leonard said.
The arena is also a necessary step for the university to complete its transition to NCAA Division II athletics. The athletic programs will begin playing NCAA Division 2 schedule and are expected to fully transition to Division II by the 2017-18 school year.
The 25,000-square-foot arena, which is being paid for primarily through student fees, will seat 1,400 for athletic events, but has a maximum capacity of 2,200 for other events.
Cal State San Marcos President Karen Haynes likened the arena's impact to the student community to that of the university student union and the health and counseling student services center, which have helped boost the school's profile.
The Sports Center, she said, has the potential to be a huge regional draw.
For Harnett and other seniors, the new arena will arrive well after their departure from campus, but they plan on returning for its opening, and many other games to come.


Omg omg I'm so pumped about this!!
These are so great! I would love to get a pair. Did you find that these fit pretty true to size?
I have visited the senita website everyday since you posted this but haven't pulled the trigger…I want to buy a pair of shorts but am afraid of that lining. Does the lining ride up? Does it feel too hot or bulky? THANKS!


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The Future of Cybersecurity Will Be Shaped by AI and Big Data
October 17, 2018 /0 Comments/in Business Continuity, Cybersecurity /by James Wagner
The future of cybersecurity is coming at us quickly.
It's almost impossible to be off-grid.
Virtually everything is somehow connected to the internet, from the smart fridge in your kitchen to satellites in space.
There are now more devices in the world than there are people, with billions of access points.
Technology is now a given for newer generations, yet cybersecurity can't keep pace as it currently exists.
As our level of connectedness continues to advance, it will be AI and big data that shape cybersecurity.
Every device has a vulnerability
All forms of technology have inherent weaknesses.
This became incredibly apparent with the emergence of IoT.
Many new technological platforms had no security built into them, and even if defence measures existed, they were easily forgotten.
When no upgrades or future installments are made, we forget as consumers who are behind the devices in our homes and offices.
It is essential that we have the ability to retrieve updates in real-time because otherwise, the vulnerabilities are considerable.
It's easy to assume that no one is interested in your Wi-Fi baby monitor, without realizing that hackers can patch themselves from one device in your home to another, such as a home security system.
Hackers have been successful in gaining access to major company databases, simply by accessing the air conditioning system.
Unrelated devices still function along the same networks, and the risk is very real.
There are too many security events for humans to handle
It's not realistic to expect that every person will update every technological device as needed.
Even the most efficient IT departments struggle to handle the thousands, and sometimes billions (if you're a powerhouse like IBM), of security events that occur daily.
Some events are minor, such as lost passwords, while others are suspicious activities indicative of a data breach.
If humans were to handle this influx alone, the backlog would greatly hinder any cybersecurity strategy.
This is where AI can augment, prioritize, and automate cybersecurity protocols.
AI can be programmed to handle low-level priority incidents, as well as send high-priority alerts to the right personnel.
AI will become a crucial component of cybersecurity as technology continues to dominate our world.
Soon, there will be no other acceptable another option.
Data is becoming decentralized
With the emergence of the blockchain, AI is even more crucial.
All transactions, all personal and professional data, cryptocurrencies, and more will be stored securely and accessed from anywhere in the world. Big data is the new technological reality, and it won't be long until blockchain is commonplace.
With the future of cybersecurity promoting more connectedness than ever, it has become more apparent that security updates are not enough.
In fact, even AI and big data won't be enough to mitigate risk.
The wider the technological landscape becomes; the more opportunities hackers will have.
As technology advances, it will be essential that cybersecurity is powered by hardware.
Rather than an afterthought, cybersecurity will have to be embedded into our devices to be efficient.
Otherwise, there is simply not enough human or artificial power to protect every device out there.
The ITeam understands the cybersecurity issues facing Canada businesses. We are committed to helping Calgary- and Alberta-based businesses develop proactive, cost-effective IT strategies that minimize risk and maximize efficiency. Contact us to learn more.
Tags: AI, blockchain, blockchain and AI are the future of cybersecurity, future of cybersecurity
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