br Acknowledgements This research is supported by Health Can

Acknowledgements This research is supported by Health Canada.
Specifications table
Value of the data
Data, materials and methods
Acknowledgments
Specifications table Value of the data Data and experimental design Fibroblasts are the most abundant cell type in connective tissues, and some subpopulations are able to differentiate to other cell types as adipocytes or osteoblasts. In normal conditions, fibroblasts are in an inactive quiescent state; however fibroblasts activation is induced by several stimuli, including growth factors such as TGF-β in colorectal cancer. Snail1 transcription is up-regulated by this cytokine in fibroblasts. Snail1 levels are modulated by serum and TGFβ. In addition, Snail1 is not only up-regulated by TGF-β, but also induces the transcription of TGFβ, creating a self-activation loop for the production of TGFβ [3]. The transcription factor Snail1 in mesenchymal c-kit inhibitor abrogated their differentiation to osteoblasts or adipocytes. In addition, Snail1 knock-down caused a large decrease in the number of bone marrow murine mesenchymal stem cells (MSCs). This depletion is accompanied of an acceleration of their differentiation to osteoblasts or adipocytes. In this way, Snail would exert its effect on maintaining stemness and pluripotency of MSCs. Snail effects on adipogenesis have been proposed to be mediated, among others, by a lack of response to TGFβ [3] or by an apparent inhibition of PPARγ and C/EBPα expression [4]. Similar results were obtained in preventing the differentiation of bone marrow-derived murine mesenchymal stem cells (mMSC) to osteoblasts or adipocytes. Still, the molecular mechanisms underlying the effect of Snail on MSCs differentiation and the blocking of adipogenesis were far from being established. Confluent 3T3-L1 preadipocytes and mMSCs differentiate to adipocytes upon exposure to a cocktail of adipogenic inducers. During adipogenic differentiation Snail expression is almost negligible in 3T3-L1 cells. As a consequence, Snail1 expression plays an inhibitory effect on adipocyte differentiation program, suggesting a functional role for Snail in obesity. We carried out an in-depth quantitative proteomic analysis of Snail1-transfected 3T3-L1 and mMSC cells to identify cellular and molecular mechanisms associated to the inhibition of differentiation to adipocytes by Snail. Due to different cell growth requirements, two labeling strategies were followed. Therefore, immortalized 3T3-L1 cells were metabolically labeled in SILAC medium (Fig. 1A). However, since mMSC cells are non-immortal and metabolic labeling requires a high number of duplications for a full isotope incorporation, mMSC cells were subjected to isobaric labeling with tandem mass tags (TMT) (Fig. 1B). We carried out the proteomic analysis on the nuclear fraction since Snail is a nuclear protein that mediates its effects mainly through the regulation of other TFs. In Snail-transfected 3T3-L1 cells, we identified 3920 proteins in forward and reverse SILAC experiments, with 2800 overlapping nuclear proteins. In total, 3483 proteins were quantified, with 2251 quantified proteins in common. We normalized the data sets against the 5% trimmed mean to minimize the effect of extreme outliers and to center the protein log2 ratio distribution to zero (Fig. 2A). The significance of the fold-change was calculated by a permutation-based statistical test according to p-value [5]. With this fold-change (≥1.5), we found 574 proteins deregulated by Snail1 in the nuclear fraction of 3T3-L1 cells, with 111 and 463 up- and down-regulated proteins, respectively (see Supplementary Tables from [2]). With TMT, we quantified a total of 1136 proteins in nuclear extracts of mMSCs (Supplementary Table S1 and Supplementary Table S2). TMT6 reporter ion intensities were corrected for isotopic impurities as provided by the manufacturer and normalized imposing equal median intensity (Fig. 2B). We calculated a significant fold-change ≥1.23 by the method of Tan et al. based on random ratios [6]. With this fold-change, we observed 391 deregulated proteins, with 97 and 294 up-regulated and down-regulated proteins, respectively (Fig. 2C). In both proteomic experiment datasets by using DAVID database, we observed a significant enrichment in nuclear proteins with 458 out of 2251 quantified proteins in 3T3-L1 and 531 out of 1136 quantified proteins in mMSC, confirming that the nuclear fraction was correctly obtained. In addition, to confirm the enrichment in nuclear protein, several deregulated proteins were validated in both 3T3-L1 and mMSC cells [2]. In total, 491 proteins were quantified in common in both quantitative SILAC and TMT experiments (Fig. 2D).