Validation of reference and identity-defining genes in human mesenchymal stem cells cultured under unrelated fetal bovine serum batches for basic science and clinical application.
Federica BanfiAlessandra ColombiniCarlotta Perucca OrfeiValentina ParazziEnrico RagniPublished in: Stem cell reviews and reports (2019)
The molecular profile of human mesenchymal stem cells (MSCs) have emerged as a key factor in defining their identity. Nevertheless, the effect of fetal bovine serum (FBS) batches or origin on MSC molecular signature has been neglected. In this frame, chemical fingerprint of FBS batches from unrelated countries showed strong correlation between chemical composition and country of origin. Thus, the aim of this study was to evaluate in stem cells isolated from bone marrow (BMMSCs) and umbilical cord-blood (CBMSCs) the effects of independently collected FBS batches on both twelve commonly used reference genes (RGs) and a selected panel of thirty-eight genes crucial for MSC definition in both research and clinical settings. Gene expression stability was estimated comparing the outcomes of two applets: geNorm and NormFinder. The bioinformatics analysis emphasized that, in a panorama of general balance, few RG candidates (YWHAZ/UBC for BMMSCs, RPLP0/EF1A for CBMSCs and EF1A/TBP for both MSCs scored together) showed superior stability. In addition, a wider study on genes involved in differentiation/proliferation/stemness processes, often used to define MSC potency, showed that these genes exhibited no major transcriptional modulation after treatment with different FBS, and allowed the identification of genes strongly discriminating between BM- and CBMSC populations. Therefore, in conclusion, FBS origin does not dramatically impact the general molecular profile of MSCs, although we could identify validated candidates able to allow more reliable comparison of data regarding MSC identity and potency and obtained by research laboratories and clinical manufacturers using different sera.
Keyphrases
- mesenchymal stem cells
- bioinformatics analysis
- umbilical cord
- bone marrow
- stem cells
- gene expression
- endothelial cells
- genome wide
- cell therapy
- genome wide identification
- dna methylation
- metabolic syndrome
- electronic health record
- type diabetes
- induced pluripotent stem cells
- skeletal muscle
- transcription factor
- big data
- pluripotent stem cells
- artificial intelligence
- quality control