Anti-eEF1A polyclonal antibody

Recently, it has been suggested that cellular senescence is associated with stem cell exhaustion, which reduces the regenerative potential of tissues and contributes to aging and age-related diseases. Mesenchymal stem cells (MSCs) attract a large amount of attention in stem cell research and regeneration medicine because they possess multiple advantages and senescent MSCs could be one of the most useful stem cell models in aging studies. It is important to quantitatively evaluate senescence markers to both identify and study the mechanisms involved in MSC senescence. Reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) is currently the most widely used tool to quantify the mRNA levels of markers. However, no report has demonstrated the optimal reference genes that should be used to normalize RT-qPCR in senescence studies of MSCs. In this study, we compared 16 commonly used reference genes (GAPDH, ACTB, RPL13A, TBP, B2M, GUSB, RPLPO, YWHAZ, RPS18, EEF1A1, ATP5F1, HPRT1, PGK1, TFRC, UBC, and PPIA) in proliferating or replicative-senescent human adipose-derived MSCs (hAD-MSCs) that were isolated from seven healthy donors aged 29-59 years old. Three algorithms (geNorm, NormFinder, and BestKeeper) were used to determine the most optimal reference gene. The results showed that PPIA exhibited the most stable expression during senescence, while the widely used ACTB exhibited the lowest stability. We also confirmed that different reference genes lead to different evaluations of senescence markers. Our work ensures that results obtained from senescence studies of hAD-MSCs will be appropriately evaluated in both basic research and clinical trials.

Murine bone marrow-derived macrophages (M0) and M1- and M2-polarized macrophages are being widely used as a laboratory model for polarized macrophages related molecular mechanism analysis. Gene expression analysis based on reference gene normalization using RT-qPCR was a powerful way to explore the molecular mechanism. But little is known about reference genes in these cell models. So, the goal of this study was to identify reference genes in these types of macrophages. Candidate reference genes in murine bone marrow-derived and polarized macrophages were selected from microarray data using Limma linear model method and evaluated by determining the stability value using five algorithms: BestKeeper, NormFinder, GeNorm, Delta CT method, and RefFinder. Finally, the selected stable reference genes were validated by testing three important immune and inflammatory genes (NLRP1, IL-1 beta, and TNF-alpha) in the cell lines. Our study has clearly shown that Ubc followed by Eef1a1 and B2m respectively were recognized as the three ideal reference genes for gene expression analysis in murine bone marrow-derived and polarized macrophages. When three reference genes with strong different stability were used for validation, a large variation of a gene expression level of IL-1 beta, TNF-alpha and NLRP1 were obtained which provides clear evidence of the need for careful selection of reference genes for RT-qPCR analysis. Normalization of mRNA expression level with Ubc rather than Actb or Gusb by qPCR in macrophages and polarized macrophages is required to ensure the accuracy of the qPCR analysis.