Exploration of Key Regulatory Factors for Continuous Regulation of Osteogenic Differentiation in Mesenchymal Stem Cells Based on Transcriptomic Sequencing

doi:10.21203/rs.3.rs-3881584/v1

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Exploration of Key Regulatory Factors for Continuous Regulation of Osteogenic Differentiation in Mesenchymal Stem Cells Based on Transcriptomic Sequencing

https://doi.org/10.21203/rs.3.rs-3881584/v1

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In this study, we conducted an integrated analysis of high-throughput transcriptomic sequencing data to identify and validate the biological molecules that dynamically regulate the osteogenic differentiation of Mesenchymal Stem Cells (MSCs). Through transcriptomic sequencing analysis, taking into account the expression levels of genes in human tissues and experimental validation, we identified PTBP1, H2AFZ, and TTPAL (C20ORF121) as pivotal regulators that govern the fate of MSC osteogenic differentiation. This article represents the first utilization of high-throughput transcriptomics for identifying regulatory factors involved in MSC osteogenesis. This study holds significant importance in investigating crucial factors that determine the fate of MSC differentiation, with notable clinical implications. This approach will lead to a better understanding of the complex biological processes and molecular mechanisms underlying diseases.

Biological sciences/Molecular biology

Biological sciences/Molecular biology/Translation

MSCs

lineage change

transcriptomic sequencing

dynamic regulation

osteogenesis

Mesenchymal stem cells (MSCs) possess the capacity to differentiate into diverse cell lineages [1, 2], rendering them indispensable for maintaining physiological homeostasis and promoting tissue regeneration and repair [3, 4]. MSCs are ubiquitously distributed across multiple tissues and represent a multipotent progenitor cell population with clonogenic potential [5, 6]. Consequently, MSCs have garnered considerable attention owing to their immense therapeutic potential in regenerative medicine [7, 8]. The fate determination of MSCs is precisely regulated by interactions among various cell factors derived from the tissue microenvironment [9], which have been identified as molecular switches for lineage differentiation based on their activation or dysfunction mechanisms [10]. Recognition of the molecular mechanisms that determine the fate of MSCs is essential for implementing targeted strategies to correct abnormal lineage distribution under conditions such as osteoporosis and bone aging [11, 12].

In previous studies, certain cellular factors, such as Runx2 [13, 14] and Osterix [15, 16] have been identified to be associated with MSC differentiation by acting as key regulatory factors that promote osteogenic lineage differentiation [17, 18]. With the aid of genomics, research has been conducted in the field of genome-wide dynamics of transcription factor binding and epigenome programming during preosteoblast differentiation [19, 20]. However, further research is still needed to investigate the dynamics of chromosome structure and enhancer activity during osteogenesis via MSC lineage studies [21, 22]. At present, no studies have been conducted to investigate the cell factors that continuously regulate MSC differentiation into the osteogenic lineage at different time points, making it challenging to systematically evaluate the impact of osteoporosis [23, 24]. Therefore, it is crucial to conduct systematic research on the cellular factors that regulate the MSC lineage to identify key elements that impact MSC differentiation [25, 26].

In this study, we performed a systematic analysis of differentially expressed genes (DEGs) by integrating high-throughput sequencing data associated with human MSC differentiation into the osteogenic lineage. Subsequently, we identified DEGs that exhibited significant differential expression at various time points and validated the candidate genes with high expression in bone marrow tissue under screening conditions by comparing them to 45 human tissues from the HUMAN PROTEIN ATLAS database. Finally, we conducted biological experiments to validate the ability of the selected candidates to regulate the osteogenic induction of MSCs continuously. Our study established a basis and framework for identifying candidates with enhanced clinical significance.

Cell culture

Primary mBMSCs were isolated from the femur bone marrow of 2-month-old wild-type C57BL/6J mice. The isolated cells were stored in BMSC medium (DMEM medium containing 20% heat-inactivated FBS) for 1 day. On the second day, the supernatant (including osteoclasts) was removed, and the adherent hematopoietic cells were removed by intensive washing with phosphate-buffered saline (PBS) for three times. The culture was continued with a fresh BMSC medium. After 2 weeks, the growth colonies were collected by trypsinization for further passage and differentiation.

Cell differentiation

BMSCs were cultured in alpha-modified Eagle’s minimum essential medium supplemented with 10% FBS, 200 mM L-glutamine (25030081, Gibco) and nonessential amino acids (NEAA, 11140050, Gibco).

Osteogenic differentiation: 100 mM ascorbic acid, 2 mM b-glycerophosphate, and 10 nM dexamethasone (D4902; Sigma‒Aldrich, USA).

For adipogenic differentiation, 0.5 mM isobutylmethylxanthine (IBMX, HY-12318, MCE), 0.5 mM hydrocortisone (803146, Sigma‒Aldrich, USA), and 60 mM indomethacin (I7378, Sigma‒Aldrich, USA) were used.

Media were changed every 2 days.

Lentivirus transduction

Lentiviral transduction: Lentiviruses overexpressing genes were purchased from Genomeditech.

BMSCs were infected with the virus for 48 h and then underwent osteogenic-induced differentiation.

Quantitative real-time PCR

Total RNA was extracted and isolated using total RNA extraction reagent (TRIzol, Sangon, B511311-0025). Reverse transcription was performed using HiScript II Q RT SuperMix (Vazyme, R222-01). Real-time quantitative fluorescent PCR (qPCR) was conducted using a real-time PCR system (Thermo Fisher) with Hieff SYBR Green Master Mix (Low RoxPlus) for real-time quantitative fluorescent PCR (Yeasen, 11202ES03). The experiment was repeated three times. The values were normalized to those of GAPDH. The sequences of the primers used are listed in Table S1.

Alizarin red staining

The cell-abandoned medium was immersed in alizarin red S staining solution for 30 min. The cells were quickly rinsed with distilled water and then studied under a microscope.

Results: The calcium deposits were orange–red.

Von Kossa Staining

The cells were immobilized with phosphate buffer containing 10% formaldehyde for 10 min. The cells were rinsed with PBS once for 1 min. The cells were immersed in 5% silver nitrate solution for 30 min, exposed to UV light for 30 min, and then washed with distilled water. Finally, the cells were observed under a microscope.

Oil red O staining

The cells were immobilized with phosphate buffer containing 10% formaldehyde for 10 min and then rinsed once with PBS for 1 min. Next, the cells were rinsed with 60% isopropyl alcohol for 15 s to promote neutral fat staining. Then, the cells were stained with filtered oil red O working solution at 37°C for 30 min, treated with 60% isopropyl alcohol for 30 s, and rinsed with PBS for three times for 3 min each. Finally, the cells were observed under a microscope.

Ethical statement

All animal studies were performed according to protocols approved by the Institutional Animal Care and Use Committee of East China Normal University (ECNU). All mice were freely allowed access to food, water, and activity. Mice were maintained under a 12 h dark–light cycle and constant temperature (20–26°C) and humidity maintenance (40–60%). All animal experiments were conducted under license at the Institutional Animal Care and Use Committee at East China Normal University (project license m20210216). For euthanasia, mice were exposed to carbon dioxide with a Smartbox setup with a flow meter calculated to deliver the appropriate flow rate and then performed cervical dislocation.

Data availability

Data is openly available in a public repository GSE37558 and GSE28205.

Integration analysis was conducted on two microarray datasets with comparable levels of osteogenic induction to identify differentially expressed genes associated with MSC osteogenic differentiation

We integrated two microarray datasets, GSE37558 and GSE28205, from the GEO database. These datasets contained sequencing samples with comparable levels of osteogenic induction. Specifically, we utilized the GSE37558 dataset for 12-day osteogenic induction and the GSE28205 dataset for 14-day induction.

We utilized the screening criteria of a relaxed threshold of a false discovery rate (FDR)<=0.25 and a P value<=0.05 to identify genes that were differentially expressed in the aforementioned microarray datasets and subsequently determined their intersection through Venn diagram analysis. A total of 1156 genes exhibiting differential expression were identified in both datasets, as illustrated in Figure 1 (A and B).

In addition, we utilized a log2(fold change)>=1.5 as the cutoff value to identify 169 differentially expressed genes, consisting of 100 down-regulated and 69 up-regulated genes, as depicted in Figure 1C. These identified genes will be subjected to further scientific scrutiny.

The exploration of genes continuously differentially expressed during osteogenic induction in MSCs was investigated by integrating microarray data from the GSE37558 dataset

To ensure a comprehensive analysis of transcriptome dynamics during osteogenic differentiation, we examined a microarray dataset (GSE37558) comprising MSC samples treated with time-course osteogenic induction.

We used the preceding time point of osteogenic induction as a reference for subsequent induction time points and analyzed the GSE37558 dataset. By applying screening criteria with an FDR<=0.25 and a P value<=0.05, we simultaneously identified 549 differentially expressed genes across Day 0 to 2, Day 2 to 8, and Day 8 to 25 during osteogenic induction. The results are presented in Figure 2A and B.

In addition, we utilized a log2(fold change)>=1.5 as the cutoff value to identify 121 differentially expressed genes, consisting of 84 up-regulated and 27 down-regulated genes, as depicted in Figure 2C. These identified genes will be subjected to further scientific scrutiny.

Integrated time-course analysis of differentially expressed genes within a single batch of microarray data and across multiple batches of microarray datasets optimized screening for continuously differentially expressed genes during osteogenic induction in MSCs

After accounting for batch effects and improving data accuracy, we integrated the aforementioned analysis results to identify a total of 124 genes that exhibited differential expression across both microarray batches conducted by two distinct research groups. The corresponding data are presented in Figure 3A.

We subsequently applied a screening criterion of LOGFC>=1.5 to identify 65 genes, including 49 genes that exhibited significantly high expression throughout the osteogenic induction process and 16 genes that showed significantly low expression during this period. The corresponding data are presented in Figure 3B.

The results mentioned above indicated that the 49 identified genes might play a crucial role in regulating the dynamics of MSC osteogenic differentiation. Follow-up investigations were also conducted to validate these candidates and elucidate their biological functions in this process.

Identification of key regulators that govern the dynamic progression of MSC osteogenic differentiation through integration of their expression levels in human tissues through the HUMAN PROTEIN ATLAS database

We focused on the aforementioned candidates, which were identified as potential key regulators of MSC osteogenic differentiation. We assessed the expression of these genes in human tissues using the HUMAN PROTEIN ATLAS database, which provides comprehensive data on gene expression levels at both the RNA and protein levels across 45 human tissue types.

Numerous studies have demonstrated the pivotal role of bone cells, including mesenchymal stem cells and hematopoietic stem cells, in regulating cell types and maintaining tissue homeostasis within the lineage of stem cells [27, 28]. The skeletal system harbors these intricate cell lineages derived from this series of cells, which dictate their differentiation into the osteogenic lineage and further determine the homeostasis of both skeletal and marrow tissues [29].

Therefore, we focused on hematopoietic tissues related to the blood and immune system in the HUMAN PROTEIN ATLAS database, which provides information on RNA and protein expression levels in these tissues. A total of 13 potential candidate genes were identified that are highly expressed in some or all of these tissues, and their information is presented in Table 1.

Table 1 clearly shows that four factors, PTBP1, H2AFZ, TTPAL (C20ORF121), and BCL6, exhibit high expression levels in most of the tissues associated with the blood and immune system (three are highly expressed in all four tissues, while one exhibits medium expression). These factors showed significant changes according to the microarray data obtained via transcriptomic sequencing. These findings suggest that these four factors could be considered crucial potential targets responsible for controlling the dynamic process of MSC osteogenic differentiation. Next, we performed biological experiments to confirm the relative molecular functions of the genes.

Isolation of bone mesenchymal stem cells and identification of potential candidate genes through qRT‒PCR analysis at different time points during osteogenic induction

Bone marrow mesenchymal stem cells (BMSCs) are among the most commonly used stem cells in cell therapy and tissue engineering [30, 31]. They are a type of multilineage progenitor cell that possesses self-renewal capacity and can differentiate into various types of mesoblastic cells, including osteoblasts, chondrocytes, adipocytes, etc. [32]. Therefore, we isolated BMSCs from bone marrow stromal cells that exhibited the most prominent stem cell characteristics and subsequently conducted biological experiments to validate the potential candidate targets identified through bioinformatics analysis.

We initially isolated BMSCs using methods described in the literature. Subsequently, we confirmed the characteristics of the stem cells through ARS, Alcian blue, and oil red O staining under osteogenic, chondrogenic, and adipogenic induction conditions. The results demonstrated that the BMSCs utilized in this study possessed multilineage differentiation potential, as shown in Figure 4A.

We induced BMSCs with osteogenic differentiation medium and collected RNA at different time points (Day-7, Day-14, Day-21) to detect the expression levels of biomarker RNAs for the following biomarkers of osteogenesis: ALP and BGLAP. The results demonstrated up-regulation of these biomarkers, indicating the successful design of the osteogenic differentiation experiment, as shown in Figure 4B.

In the subsequent step, we evaluated the RNA expression of these four potential genes that were optimized by bioinformatic database analysis at various induction time points to validate the accuracy of our bioinformatic analysis. We observed sustained high expression of BCL6 and TTPAL during the induction period in a time-dependent manner, as depicted in Figure 4C. Conversely, PTBP1 and H2AFZ exhibited continuous decreases in expression throughout the induction period in a time-dependent manner, as shown in Figure 4D.

These experimental results were consistent with previous findings from Gene Expression Omnibus (GEO) database mining, thus laying a solid foundation for further research.

Identifying the molecular function of dynamically regulating osteogenic induction in MSCs by overexpressing four potential genes via lentiviral packaging technology

We employed lentiviral packaging technology to overexpress four candidate genes, PTBP1, H2AFZ, BCL6, and TTPAL, in 293T cells. The generated virus was then used to infect BMSCs via the 293T supernatant. After a transduction period of 48 hours, we collected RNA from the BMSCs and assessed the infection efficacy using qRT‒PCR. As shown in Figure 5A, successful infection was observed.

We conducted experiments to investigate the regulatory factors involved in osteogenesis and utilized lentiviruses containing these four genes to infect BMSCs. The osteogenic ability was evaluated by ALP assay at day-7, with a control group was infected with the vector virus for comparison. As shown in Figure 5B, BCL6 and TTPAL both enhance osteogenic potential. Conversely, as demonstrated in Figure 5C, PTBP1 and H2AFZ appeared to inhibit osteogenesis.

These findings suggest that BCL6 and TTPAL serve as positive regulators of osteogenic lineage differentiation in BMSCs, while PTBP1 and H2AFZ act as negative regulators.

With the advancement of omics, research on the dynamics of the entire genome concerning transcription factor and epigenome programming during pre-osteoblast differentiation has improved [33, 34]. In this research article, we systematically investigated the dynamic regulation of mesenchymal stem cell lineage differentiation during osteogenesis by exploring cellular factors. Through the integration of transcriptomic sequencing at different induction time points in a single-batch microarray dataset, along with multiple batches of array sequencing, we optimized the identification of 69 differentially expressed genes that exhibit continuous and significant changes during MSC osteogenic induction, consisting of 49 highly expressed genes and 16 genes with low expression.

To select genes that are highly relevant to real human biological functions and possess significant experimental and clinical value, we examined the expression levels of 69 candidate genes in human tissues by referencing the HUMAN PROTEIN ATLAS database [35]. We then utilized high expression levels in blood and immune organs as screening criteria to further optimize our selection process. After conducting extensive big data analysis, Table 1 reveals that 13 genes exhibiting high expression levels in one or more tissues within the blood and immune system were successfully identified.

Furthermore, four genes (PTBP1, H2AFZ, BCL6, and TTPAL) were selected for experimental validation of their relative cellular functions due to their high expression levels in most blood and immune system tissues. Based on the experimental results, we observed changes in gene expression levels during osteogenic induction, as demonstrated in Figure 5A. These findings are in accordance with the results of the transcriptomic sequencing analysis. Furthermore, we validated the relative biological function of these genes, as shown in Figure 5B. All the results confirmed the feasibility of this method, which involves screening potential targets that dynamically regulate biological function through transcriptome time point sequencing combined with big data mining.

This article represents the first use of high-throughput transcriptomic sequencing to analyze and validate the key biological molecules that play a dynamic role in regulating MSC osteogenic differentiation. This study holds great significance in investigating crucial factors determining MSC differentiation fate and has significant clinical implications [36].

In this study, we conducted an analysis of high-throughput transcriptomic sequencing data from the GEO database [37]. While this approach can provide valuable information on differences in biological processes between diseased and healthy individuals, it is important to note that there are limitations associated with single analyses [38]. In future research, we suggest multi-omics analysis methods should be utilized to integrate information from mRNAs, regulatory factors, proteins, and metabolites to generate gene regulatory networks that can elucidate causal relationships among comprehensive molecules [39]. Ultimately, these findings will lead to a better understanding of the complex biological processes and molecular mechanisms underlying this disease.

Moreover, the research conducted in this study focused on utilizing high-throughput sequencing analysis to investigate the crucial factors that determine MSC osteogenic differentiation. The molecules identified in this study should undergo thorough testing through both in vitro and in vivo assays to facilitate clinical transformation research [40].

Conflicts of interest: These authors declare no conflicts of interest.

STATEMENT

All animal studies were conducted in accordance to ARRIVE guidelines.

Funding:

This work was supported by the Natural Science Foundation of Jiangsu Province, BK20221288 To Tao Liu, Grants of China Postdoctoral Science Foundation, 2020M681232 To Yuwei Liu, and grants of the National Natural Science Foundation of China 82101630 to Yuwei Liu.

Author Contribution

Yuwei Liu, and Liang He designed the study. Yuwei Liu analyzed GEO data and integrated the data to identify the candidates. Tao Liu, Yu Pan, Shu Pan, and Linfeng Li performed all the biological assays. Yuwei Liu finished the writing review and editing of this manuscript.

ACKNOWLEDGMENTS

Yuwei Liu and Liang He designed the study. Yuwei Liu analyzed the GEO data and integrated the data to identify the candidates. Tao Liu, Yu Pan, Shu Pan, and Linfeng Li performed all the biological assays. Yuwei Liu finished the writing and editing of this manuscript.

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TABLE 1. Potential candidate genes highly expressed in tissues associated with the blood and immune system

Gene Name	Blood and immune system				Protein expressed in the database of THE HUMAN PROTEIN ALTAS
Gene Name	Bone marrow	Lymph node	Tonsil	Spleen
CXCL12	High	Low	Low	Low	Bone marrow poietic cells showed strong nuclear positivity.
PTBP1	High	High	High	medium	Most normal tissues displayed strong nuclear positivity.
PKM2	Low	High	High	High	Cytoplasmic expression in most tissues, hepatocytes, neurons and most soft tissues were negative.
H2AFZ	High	High	medium	High	Ubiquitous nuclear expression.
NUDT1	medium	High	High	medium	Most normal tissues showed moderate to strong cytoplasmic staining.
ANGPT1	High	medium	medium	medium	Ubiquitous cytoplasmic expression.
PPAGR	low	not detected	High	low	Squamous epithelia, glandular cells in gastrointestinal tract, gall bladder, urinary bladder, placenta,epididymis showed moderate to strong nuclear positivity
MME	medium	Low	medium	High	B-lymphocytes, myoepithelium, stromal cells and some glandular epithelia displayed strong cytoplasmic positivity.
RPS6KA2	medium	Low	High	medium	Most of the normal tissues displayed moderate nuclear and cytoplasmic positivity.
TTPAL	medium	High	High	High	Most normal tissues displayed moderate to strong cytoplasmic staining with a granular pattern.
BCL6	High	High	High	medium	Nuclear expression, mainly in lymphoid tissues.
CTNNB1	Low	not detected	High	not detected	Membranous expression was observed in most tissues.
STAT5A	medium	High	High	Low	Cytoplasmic and nuclear expression in a few tissues, most abundant in subsets of lymphoid cells.

No competing interests reported.

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Exploration of Key Regulatory Factors for Continuous Regulation of Osteogenic Differentiation in Mesenchymal Stem Cells Based on Transcriptomic Sequencing

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Abstract

Figures

INTRODUCTION

MATERIALS AND METHODS

Cell culture

Cell differentiation

Lentivirus transduction

Quantitative real-time PCR

Alizarin red staining

Von Kossa Staining

Oil red O staining

Ethical statement

Data availability

Results

DISCUSSION and CONCLUSION

Declarations

STATEMENT

Funding:

Author Contribution

ACKNOWLEDGMENTS

References

Tables

Additional Declarations

Supplementary Files

Status:

Version 1