The goal of this study was to determine whether in vitro treatment of primary osteoblasts with TDF, the prodrug of tenofovir (), would alter gene expression as determined by microarray analysis, and provide insights into how TDF exposure may influence osteoblast function. We first investigated the effect of TDF exposure on cell viability. We sought to determine whether physiologically relevant TDF concentrations corresponding to the dosing of TDF in antiretroviral therapy had any effects on cell viability. A range of TDF concentrations (50 nM to 500 uM) were analyzed for their effects on osteoblast viability. The highest TDF concentrations analyzed, i.e., 50 uM, 250 uM and 500 uM, were found to significantly reduce cell viability (). The lower TDF concentrations, i.e., 50 nM, 500 nM and 5 uM, had no effect on cell viability. Tenofovir has been shown to cause very little cytotoxicity in human HepG2 and skeletal muscle cell lines, with average CC50 of 399 and 870 uM, respectively [20
]. It is to be expected that primary culture is more sensitive to drug treatment in comparison to immortalized cell lines. As shown in our cytotoxicity assay, primary osteoblast cultures are sensitive to much lower concentrations of TDF (). Based upon these results, we chose the TDF concentration of 500 nM for analyzing the impact of TDF exposure on osteoblast gene expression in primary cells. This TDF concentration is physiologically relevant based upon the serum concentrations and dosing regimens used in antiretroviral therapy of HIV infected individuals [21
Fig. 1 Tenofovir structure and primary osteoblast cell viability following drug exposure. The structure of tenofovir (A) and tenofovir disoproxil fumarate (TDF, the prodrug of tenofovir) (B) is shown. C. Viability of primary osteoblasts following exposure to (more ...)
Primary osteoblasts were treated with 500 nM TDF, and then total RNA was extracted and analyzed for yield and integrity by capillary electrophoresis (data not shown). Samples were used as templates for cDNA synthesis and used to generate cDNAs that were then prepared for use in microarray analysis. Two gene chips were used in each replicate experiment and a total of four independent replicate experiments were performed. A student t-test (p-value ≤ 0.05) was used to filter for probe sets that exhibit an absolute fold-change ≥ 1.5. The microarray analysis was intensive and allowed for the thorough analysis of osteoblast gene expression profiles. As described below, this intensive approach helped focus the gene expression profile on a relatively limited number of transcripts (i.e., under 80). Another likely variable that was responsible for the focused gene expression profile was the replicate-to-replicate variability of TDF treatment of primary osteoblasts. Finally, limited uptake of TDF by osteoblasts in tissue culture and in the absence of the bone microenvironment could also explain the focused gene expression profile.
A heat map was generated from the gene expression profile obtained from the microarray data (). From this heat map, a total of seventy-nine transcripts were identified to have significantly altered gene expression profiles in groups treated with TDF. Hierarchical clustering analysis was done for the gene expression data. The dendrograms were generated based on average linkage hierarchical clustering of expression data. Supplemental Table 1
lists the resulting gene expression profile of transcripts with significant expression changes as identified from intensive microarray analysis of TDF-treated primary osteoblasts. The Log2 fold change was determined as well as the t-test p-values for TDF treatment versus that of the control. Twenty-six of the 79 (i.e., 33%) transcripts were upregulated, with the largest increases observed with Serpina3n, Ass1, and Anxa8, (1.266939, 1.134408,1.128678, respectively). Fifty-three of the 79 (i.e., 67%) transcripts were downregulated, with Rspo2, Snora44, and Pgm5 (-1.039561, -1.000873, and -0.993176, respectively) having the greatest reduction in transcript levels.
Fig. 2 Heat map of gene expression profile from TDF-treated and untreated primary osteoblasts as determined from microarray analysis. Two gene chips were used in each replicate experiment and a total of four independent replicate experiments were performed. (more ...)
The KEGG (i.e., Kyoto Encyclopedia of Genes and Genomes) database was used for analyzing the pathways associated with the identified genes (). The use of KEGG allowed us to identify networks of molecular interactions involved in the response of primary osteoblasts to TDF treatment. Notably, several signaling pathways (i.e., Wnt, TGF-beta, Hedgehog, VEGF and MAPK) were identified as well as several involved in amino acid metabolism (i.e., arginine and proline, glycine, serine and threonine, and alanine and aspartate) and energy metabolism. The regulation of cell cycle was also implicated by the identification of Cdkn1a, cyclin-dependent kinase inhibitor 1A (p21), which is a negative regulator of CDK and the cell cycle.
Organization of osteoblast genes altered by TDF treatment by KEGG Biochemical Pathways.
Gene Ontology (GO) analysis was done on the transcripts showing either up-regulation or down-regulation following TDF-exposure of primary osteoblasts (Supplemental Fig. 1
). A couple of particularly notable observations can be made from this analysis. First, a large number of the transcripts encode for extracellular proteins, which include molecules involved in signaling pathways as well as proteins involved in molecule transporters. Second, many types of proteins involved in amino acid metabolism were identified as having their gene expression altered by TDF exposure.
To further assess the results from the microarray analysis, a limited number of transcripts were selected (i.e., Rac3, Acvr2a, Hhip, and Ecm1) for qPCR analysis. These gene transcripts were selected based upon their general relevance to cell signaling pathways or processes that could be associated with osteoblast function or differentiation. Three independent experiments were performed for this assay and the 18S rRNA was used as an internal control for determining the relative level of gene expression. We were able to conclude general verification on the up- or down-regulation of transcript expression as determined by the microarray results at a success rate of 83% (). The differences for Rac3 and Ecm1 were statistically significant. The observed discrepancies with the microarray data may be due to the SYBR green method used for qPCR, which is a relatively non-quantitative method for qPCR compared to other methodologies (e.g, TaqMan). Also, more than 1 housekeeping gene is likely required in order to establish accurate normalization for the verification of the small fold differences observed in the microarray analysis. Finally, alternative splicing and the differences in detection between the microarray probes versus that of the qPCR probes could result in discrepancies.
Real-time PCR analysis of selected genes from TDF-treated primary osteoblasts.