RT-qPCR analyses on the osteogenic differentiation from human iPS cells: an investigation of reference genes

The role of fibroblast growth factor-2 in modulating the differentiation of periodontal ligament and alveolar bone-derived stem cells

OBJECTIVE

This study examined how range concentrations of Fibroblast Growth Factor-2 (FGF-2) influence the differentiation and activity of human-derived periodontal ligament (hPDLSCs) and alveolar bone-derived stem cells (haBMSCs).

DESIGN

hPDLSCs and haBMSCs were cultured with varying concentrations of FGF-2 (0, 1, 2.5, 5, 10, 20 ng/mL) and monitored for osteogenic differentiation through alkaline phosphatase (ALP) activity and quantification of gene expression (qRT-PCR) for osteogenesis markers. Additionally, alizarin red staining and a hydroxyproline colorimetric assay evaluated and quantified osteogenic matrix mineralization and collagen deposition. Statistical analyses were performed using one-way ANOVA or two-way ANOVA for multiple comparisons between groups.

RESULTS

At low FGF-2 concentrations, hPDLSCs differentiated toward an osteogenic lineage, whereas higher concentrations of FGF-2 inhibited osteogenesis and promoted fibroblastic differentiation. The effect of FGF-2 at the lowest concentration tested (1 ng/mL) led to significantly higher ALP activity than osteogenically induced positive controls at early time points and equivalent RUNX2 expression at early and later time points. FGF-2 supplementation of haBMSC cultures was sufficient, at all concentrations, to increase ALP activity at an earlier time point. Mineralization of haBMSC cultures increased significantly within 5-20 ng/mL FGF-2 concentrations under basal growth media conditions (α-minimal essential medium supplemented with 15 % fetal bovine serum and 1 % penicillin/streptomycin).

CONCLUSIONS

FGF-2 has a dual capacity in promoting osteogenic and fibroblastic differentiation within hPDLSCs contingent upon the dosage and timing of administration, alongside supporting osteogenic differentiation in haBMSCs. These findings underscore the need for precision growth factors dosing when considering the design of biomaterials for periodontal regeneration.

RPLP0/TBP are the most stable reference genes for human dental pulp stem cells under osteogenic differentiation

BACKGROUND

Validation of the reference gene (RG) stability during experimental analyses is essential for correct quantitative real-time polymerase chain reaction (RT-qPCR) data normalisation. Commonly, in an unreliable way, several studies use genes involved in essential cellular functions [glyceraldehyde-3-phosphate dehydrogenase (GAPDH), 18S rRNA, and β-actin] without paying attention to whether they are suitable for such experimental conditions or the reason for choosing such genes. Furthermore, such studies use only one gene when Minimum Information for Publication of Quantitative Real-Time PCR Experiments guidelines recommend two or more genes. It impacts the credibility of these studies and causes distortions in the gene expression findings. For tissue engineering, the accuracy of gene expression drives the best experimental or therapeutical approaches.

AIM

To verify the most stable RG during osteogenic differentiation of human dental pulp stem cells (DPSCs) by RT-qPCR.

METHODS

We cultivated DPSCs under two conditions: Undifferentiated and osteogenic differentiation, both for 35 d. We evaluated the gene expression of 10 candidates for RGs [ribosomal protein, large, P0 (RPLP0), TATA-binding protein (TBP), GAPDH, actin beta (ACTB), tubulin (TUB), aminolevulinic acid synthase 1 (ALAS1), tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein, zeta (YWHAZ), eukaryotic translational elongation factor 1 alpha (EF1a), succinate dehydrogenase complex, subunit A, flavoprotein (SDHA), and beta-2-microglobulin (B2M)] every 7 d (1, 7, 14, 21, 28, and 35 d) by RT-qPCR. The data were analysed by the four main algorithms, ΔCt method, geNorm, NormFinder, and BestKeeper and ranked by the RefFinder method. We subdivided the samples into eight subgroups.

RESULTS

All of the data sets from clonogenic and osteogenic samples were analysed using the RefFinder algorithm. The final ranking showed RPLP0/TBP as the two most stable RGs and TUB/B2M as the two least stable RGs. Either the ΔCt method or NormFinder analysis showed TBP/RPLP0 as the two most stable genes. However, geNorm analysis showed RPLP0/EF1α in the first place. These algorithms' two least stable RGs were B2M/GAPDH. For BestKeeper, ALAS1 was ranked as the most stable RG, and SDHA as the least stable RG. The pair RPLP0/TBP was detected in most subgroups as the most stable RGs, following the RefFinfer ranking.

CONCLUSION

For the first time, we show that RPLP0/TBP are the most stable RGs, whereas TUB/B2M are unstable RGs for long-term osteogenic differentiation of human DPSCs in traditional monolayers.

RPLP0/TBP are the most stable reference genes for human dental pulp stem cells under osteogenic differentiation

BACKGROUND

Validation of the reference gene (RG) stability during experimental analyses is essential for correct quantitative real-time polymerase chain reaction (RT-qPCR) data normalisation. Commonly, in an unreliable way, several studies use genes involved in essential cellular functions [glyceraldehyde-3-phosphate dehydrogenase (GAPDH), 18S rRNA, and β-actin] without paying attention to whether they are suitable for such experimental conditions or the reason for choosing such genes. Furthermore, such studies use only one gene when Minimum Information for Publication of Quantitative Real-Time PCR Experiments guidelines recommend two or more genes. It impacts the credibility of these studies and causes distortions in the gene expression findings. For tissue engineering, the accuracy of gene expression drives the best experimental or therapeutical approaches.

AIM

To verify the most stable RG during osteogenic differentiation of human dental pulp stem cells (DPSCs) by RT-qPCR.

METHODS

We cultivated DPSCs under two conditions: Undifferentiated and osteogenic differentiation, both for 35 d. We evaluated the gene expression of 10 candidates for RGs [ribosomal protein, large, P0 (RPLP0), TATA-binding protein (TBP), GAPDH, actin beta (ACTB), tubulin (TUB), aminolevulinic acid synthase 1 (ALAS1), tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein, zeta (YWHAZ), eukaryotic translational elongation factor 1 alpha (EF1a), succinate dehydrogenase complex, subunit A, flavoprotein (SDHA), and beta-2-microglobulin (B2M)] every 7 d (1, 7, 14, 21, 28, and 35 d) by RT-qPCR. The data were analysed by the four main algorithms, ΔCt method, geNorm, NormFinder, and BestKeeper and ranked by the RefFinder method. We subdivided the samples into eight subgroups.

RESULTS

All of the data sets from clonogenic and osteogenic samples were analysed using the RefFinder algorithm. The final ranking showed RPLP0/TBP as the two most stable RGs and TUB/B2M as the two least stable RGs. Either the ΔCt method or NormFinder analysis showed TBP/RPLP0 as the two most stable genes. However, geNorm analysis showed RPLP0/EF1α in the first place. These algorithms’ two least stable RGs were B2M/GAPDH. For BestKeeper, ALAS1 was ranked as the most stable RG, and SDHA as the least stable RG. The pair RPLP0/TBP was detected in most subgroups as the most stable RGs, following the RefFinfer ranking.

CONCLUSION

For the first time, we show that RPLP0/TBP are the most stable RGs, whereas TUB/B2M are unstable RGs for long-term osteogenic differentiation of human DPSCs in traditional monolayers.

Assessment of Reference Genes Stability in Cortical Bone of Obese and Diabetic Mice

Introduction

Bone, a pivotal structural organ, is susceptible to disorders with profound health implications. The investigation of gene expression in bone tissue is imperative, particularly within the context of metabolic diseases such as obesity and diabetes that augment the susceptibility to bone fractures. The objective of this study is to identify a set of internal control genes for the analysis of gene expression.

Methods

This study employs reverse transcription-quantitative real-time polymerase chain reaction (RT-qPCR) to assess gene expression in bone tissue. We selected fourteen housekeeping genes and assessed their stability in the cortical bone of mouse models for obesity and diabetes using four well-established algorithms (GeNorm, BestKeeper, NormFinder, and the comparative Delta Ct method).

Results and Conclusion

We identified Rpl13a as the mostly stably expressed reference gene in cortical bone tissue from mouse models of obesity and diabetes (db/db), while Gapdh was found to be the most stable reference gene in another diabetes model, KKAy mice. Additionally, Ef1a, Ppia, Rplp0, and Rpl22 were identified as alternative genes suitable for normalizing gene expression in cortical bone from obesity and diabetes mouse models. These findings enhance RT-qPCR accuracy and reliability, offering a strategic guide to select reference gene for studying bone tissue gene expression in metabolic disorders.

Silva F, Miranda G, Mendes Pinto I. Engineering a Hybrid Ti6Al4V-Based System for Responsive and Consistent Osteogenesis

As the aging population increases worldwide, the incidence of musculoskeletal diseases and the need for orthopedic implants also arise. One of the most desirable goals in orthopedic reconstructive therapies is de novo bone formation. Yet, reproducible, long-lasting, and cost-effective strategies for implants that strongly induce osteogenesis are still in need. Nanoengineered titanium substrates (and their alloys) are among the most used materials in orthopedic implants. Although having high biocompatibility, titanium alloys hold a low bioactivity profile. The osteogenic capacity and osseointegration of Ti-based implantable systems are limited, as they critically depend on the body-substrate interactions defined by blood proteins adsorbed into implant surfaces that ultimately lead to the recruitment, proliferation, and differentiation of mesenchymal stem cells (MSCs) to comply bone formation and regeneration. In this work, a hybrid Ti6Al4V system combining micro- and nanoscale modifications induced by hydrothermal treatment followed by functionalization with a bioactive compound (fibronectin derived from human plasma) is proposed, aiming for bioactivity improvement. An evaluation of the biological activity and cellular responses in vitro with respect to bone regeneration indicated that the integration of morphological and chemical modifications into Ti6Al4V surfaces induces the osteogenic differentiation of MSCs to improve bone regeneration by an enhancement of mineral matrix formation that accelerates the osseointegration process. Overall, this hybrid system has numerous competitive advantages over more complex treatments, including reproducibility, low production cost, and potential for improved long-term maintenance of the implant.

A Strategy for the Selection of RT-qPCR Reference Genes Based on Publicly Available Transcriptomic Datasets

In the next-generation sequencing era, RT-qPCR is still widely employed to quantify levels of nucleic acids of interest due to its popularity, versatility, and limited costs. The measurement of transcriptional levels through RT-qPCR critically depends on reference genes used for normalization. Here, we devised a strategy to select appropriate reference genes for a specific clinical/experimental setting based on publicly available transcriptomic datasets and a pipeline for RT-qPCR assay design and validation. As a proof-of-principle, we applied this strategy to identify and validate reference genes for transcriptional studies of bone-marrow plasma cells from patients with AL amyloidosis. We performed a systematic review of published literature to compile a list of 163 candidate reference genes for RT-qPCR experiments employing human samples. Next, we interrogated the Gene Expression Omnibus to assess expression levels of these genes in published transcriptomic studies on bone-marrow plasma cells from patients with different plasma cell dyscrasias and identified the most stably expressed genes as candidate normalizing genes. Experimental validation on bone-marrow plasma cells showed the superiority of candidate reference genes identified through this strategy over commonly employed “housekeeping” genes. The strategy presented here may apply to other clinical and experimental settings for which publicly available transcriptomic datasets are available.

Evaluation of candidate reference genes for quantitative real-time PCR normalization in blood from red deer developing antlers

Sexual selection favors male traits that increase their ability to monopolize the breeding access to several females. Deer antlers are cranial appendages that regenerate annually in males. Throughout life, the phenology of antler growth advances and antler mass increases until the stag reaches, between 8 and 10 years old, maximum body mass and highest reproductive success. The molecular mechanisms of antler development are of great interest in both evolutionary and regenerative medicine studies. To minimize errors in the assessment of gene expression levels by qRT-PCR, we analyzed the stability of a panel of eight candidate reference genes and concluded that qRT-PCR normalization to three stable genes is strongly convenient in experiments performed in red deer antler blood. To validate our proposal, we compared the expression level of three genes linked to red deer antler growth (ANXA2, APOD and TPM1) in fifteen male red deer classified as young (up to 4 years old) and adults (4–6 years old). Our data confirms that B2M, ACTB and RPLP0 are valuable reference genes for future gene expression studies in red deer antler blood, which would provide increased insight into the effects of intrinsic factors that determine antler development in red deer.

TBP, PPIA, YWHAZ and EF1A1 Are the Most Stably Expressed Genes during Osteogenic Differentiation

RT-qPCR is the gold standard and the most commonly used method for measuring gene expression. Selection of appropriate reference gene(s) for normalization is a crucial part of RT-qPCR experimental design, which allows accurate quantification and reliability of the results. Because there is no universal reference gene and even commonly used housekeeping genes’ expression can vary under certain conditions, careful selection of an appropriate internal control must be performed for each cell type or tissue and experimental design. The aim of this study was to identify the most stable reference genes during osteogenic differentiation of the human osteosarcoma cell lines MG-63, HOS, and SaOS-2 using the geNorm, NormFinder, and BestKeeper statistical algorithms. Our results show that TBP, PPIA, YWHAZ, and EF1A1 are the most stably expressed genes, while ACTB, and 18S rRNA expressions are most variable. These data provide a basis for future RT-qPCR normalizations when studying gene expression during osteogenic differentiation, for example, in studies of osteoporosis and other bone diseases.

Optimizations for identifying reference genes in bone and cartilage bioengineering

BACKGROUND

Reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) remains one of the best-established techniques to assess gene expression patterns. However, appropriate reference gene(s) selection remains a critical and challenging subject in which inappropriate reference gene selction can distort results leading to false interpretations. To date, mixed opinions still exist in how to choose the most optimal reference gene sets in accodrance to the Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) guideline. Therefore, the purpose of this study was to investigate which schemes were the most feasible for the identification of reference genes in a bone and cartilage bioengineering experimental setting. In this study, rat bone mesenchymal stem cells (rBMSCs), skeletal muscle tissue and adipose tissue were utilized, undergoing either chondrogenic or osteogenic induction, to investigate the optimal reference gene set identification scheme that would subsequently ensure stable and accurate interpretation of gene expression in bone and cartilage bioengineering.

RESULTS

The stability and pairwise variance of eight candidate reference genes were analyzed using geNorm. The V_0.15- vs. V_min-based normalization scheme in rBMSCs had no significant effect on the eventual normalization of target genes. In terms of the muscle tissue, the results of the correlation of NF values between the V_0.15 and V_min schemes and the variance of target genes expression levels generated by these two schemes showed that different schemes do indeed have a significant effect on the eventual normalization of target genes. Three selection schemes were adopted in terms of the adipose tissue, including the three optimal reference genes (Opt₃), V_0.20 and V_min schemes, and the analysis of NF values with eventual normalization of target genes showed that the different selection schemes also have a significant effect on the eventual normalization of target genes.

CONCLUSIONS

Based on these results, the proposed cut-off value of Vn/n + 1 under 0.15, according to the geNorm algorithm, should be considered with caution. For cell only experiments, at least rBMSCs, a Vn/n + 1 under 0.15 is sufficient in RT-qPCR studies. However, when using certain tissue types such as skeletal muscle and adipose tissue the minimum Vn/n + 1 should be used instead as this provides a far superior mode of generating accurate gene expression results. We thus recommended that when the stability and variation of a candidate reference genes in a specific study is unclear the minimum Vn/n + 1 should always be used as this ensures the best and most accurate gene expression value is achieved during RT-qPCR assays.

Validation of common reference genes stability in exosomal mRNA-isolated from liver and breast cancer cell lines

Accurate relative gene expression analysis by reverse transcription-quantitative polymerase chain reaction relies on the usage of suitable reference genes for data normalization. The RNA content of small extracellular vesicles including exosomes is growingly considered as cancer biomarkers. So, reliable relative quantification of exosomal messenger RNA (mRNA) is essential for cancer diagnosis and prognosis applications. However, suitable reference genes for accurate normalization of a target gene in exosomes derived from cancer cells are not depicted yet. Here, we analyzed the expression and stability of eight well-known reference genes namely GAPDH, B2M, HPRT1, ACTB, YWHAZ, UBC, RNA18S, and TBP in exosomes-isolated from the liver (Huh7, HepG2, PLC/PRF/5) and breast (SK-BR-3) cancer cell lines using five different algorithms including geNorm, BestKeeper, Delta Ct, NormFinder, and RefFinder. Our results showed that ACTB, TBP, and HPRT1 were not expressed in exosomes-isolated from studied liver and breast cancer cell lines. The geNorm and BestKeeper algorithms indicated GAPDH and UBC as the most stable candidates. Moreover, Delta Ct and NormFinder algorithms showed YWHAZ as the most stable reference genes. Comprehensive ranking calculated by the RefFinder algorithm also pointed out GAPDH, YWHAZ, and UBC as the first three stable reference genes. Taken together, this study validated the common reference genes stability in exosomal mRNA derived from liver and breast cancer cell lines for the first time. We believe that this study would be the first step in finding more stable reference genes in exosomes that triggers more accurate detection of exosomal biomarkers.