Computational protocol: TGFβ-induced switch from adipogenic to osteogenic differentiation of human mesenchymal stem cells: identification of drug targets for prevention of fat cell differentiation

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Protocol publication

[…] To identify genes that are regulated during osteogenic and adipogenic differentiation of hMSCs, a total of 54 samples (each containing 800,000 cells/ 20 cm2) were seeded in PM and grown for 24 hours. Subsequently the medium was exchanged for differentiation medium, now consisting of PM with 10−6 M DEX, 10 μg/ml insulin, 10−7 M rosiglitazone, and 50 ng/ml BMP2 (B). In addition, either 5 ng/ml TGFβ (BT), or 250 μM IBMX (BI), or 5 ng/ml TGFβ and 250 μM IBMX (BTI) were added. Samples were incubated for either 0, 1, 2, 3, or 7 days. Experiments for each group and time point were carried out as three biological replicates, while the untreated control group (time 0) consisted of six samples. RNA was isolated as already described, and hybridized onto Affymetrix HGU 133 plus 2.0 microarrays according to existing protocols [].Microarray data were analyzed with the R language for statistical computing using appropriate Bioconductor packages (http://bioconductor.org/) for reading, normalizing, and statistically evaluating the data, followed by annotation of the gene sets and integration of parallel data sources. Briefly, the analysis started with a careful quality assessment of the dataset using the automatic R pipeline AffymetrixQC [], which was customized and run locally. All 54 microarrays passed the quality control and were included in the analysis, consisting of robust microarray analysis (RMA) normalization [], followed by statistical analysis to find differentially expressed genes using Linear Models for Microarray Data (LIMMA) [], and subsequent functional annotation and enrichment analysis using the online resource Database for Annotation, Visualization and Integrated Discovery (DAVID) [, ]. Finally, the list of differentially expressed genes for the contrasts of interest was crossed with the information from the DrugBank database [] in order to derive the final list of candidate genes for experimental testing. All R scripts used for this analysis are available upon request. Current microarray data have been deposited in NCBI’s Gene Expression Omnibus [GEO:GSE84500] (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE84500). […]

Pipeline specifications

Software tools limma, DAVID
Databases GEO DrugBank
Application Gene expression microarray analysis
Organisms Homo sapiens
Diseases Osteoporosis
Chemicals 1-Methyl-3-isobutylxanthine, Dinoprostone