Project description:To understand the molecular signatures of quiescent muscle stem cells in vivo, we isolated quiescent muscle stem cells by fixation using perfusion technique and profiled the transcriptome by RNA-Seq.
Project description:To understand the molecular signatures of Dek over-expressed quiescent muscle stem cells in vivo, we isolated quiescent muscle stem cells by fixation using perfusion technique and profiled the transcriptome by RNA-Seq.
Project description:Many stem cell populations exist in a quiescent state in vivo, exiting quiescence and entering the cell cycle in response to specific stimuli. In the case of skeletal muscle, the muscle stem cells (MuSCs, or “satellite cells”) are quiescent under normal homeostatic conditions and undergo activation and cell cycle entry in response to muscle fiber damage. Quiescent MuSCs are also much more potent than their proliferating progeny in assays of stem cell transplantation. In recent years, it has become increasingly apparent that the quiescent state is both actively maintained and dynamically regulated. However, most of the analyses of quiescent MuSCs have come from cells that have been removed from their niche in vivo, purified by fluorescence activated cell sorting, and then assay ex vivo. Although such cells are still in the quiescent state under these conditions, there is no doubt that significant biochemical changes will occur during the isolation and purification process. Thus, we have sought to examine the true in vivo quiescent state by analyzing the transcriptome of MuSCs. To achieve that, we have used techniques to label actively transcribing RNA in vivo using nucleoside analogs. In mice in which the enzyme uracil phosphoribosyltransferase (UPRT) is expressed specifically in MuSCs, administration of 4-thiouracil (4TU), which is converted to thiouridine (TU) by UPRT, resulted in labelling of MuSC transcripts, and the transcriptome could be analyzed following pull-down of TU-tagged RNA. Varying the timing of 4TU administration revealed the dynamic regulation of different subsets of transcripts. Notably, labeling transcripts during the isolation procedure revealed very active transcription of specific subsets of genes. Nevertheless, the ex vivo transcriptome remained largely reflective of the in vivo transcriptome. Using the transcriptional inhibitor, α-amanitin, we were also able to show that there was little difference between the steady-state transcript levels of the most highly expressed genes when comparing the ex vivo transcriptome with the in vivo transcriptome. Together, these data provide a novel view of the molecular regulation of the quiescent state at the transcriptional level, demonstrate the utility of these tools for probing transcriptional dynamics in vivo, and provide an invaluable resource for understanding stem cell state transitions.
Project description:MicroRNA expression profiling during muscle stem cell activation. Quiescent muscle stem cells from uninjured muscles and activated muscle stem cells from injured muscles at indicated time points were isolated by FACS.
Project description:MicroRNA expression profiling during muscle stem cell activation. Quiescent muscle stem cells from uninjured muscles and activated muscle stem cells from injured muscles at indicated time points were isolated by FACS. MicroRNA expression profiling during muscle stem cell activation using real-time PCR based miRNA arrays. Muscle stem cells were harvested at indicated time points (0hr, 36hr, 60hr and 72hr) after injury. 3 technical replicates were performed. Supplementary files: Raw data (Ct) and complete processed data (dCt, ddCt, fold-change) by platform.
Project description:The satellite cell of skeletal muscle provides a paradigm for quiescent and activated tissue stem cell states. We have carried out transcriptome analyses by comparing satellite cells from adult skeletal muscles, where they are mainly quiescent, with cells from growing muscles, regenerating (mdx) muscles, or with cells in culture, where they are activated. Our study gives new insights into the satellite cell biology during activation and in respect with its niche. We used microarrays to study the global programme of gene expression underlying adult satellite cell quiescence compared to activation states and to identify distinct classes of up-regulated genes in these two different states Skeletal muscle satellite cells were isolated by flow cytrometry using the GFP fluorescence marker from Pax3GFP/+ mice skeletal muscle. The transcriptome of quiescent satellite cells from adult Pax3GFP/+ muscle was compared to the transcriptome of activated satellite cells obtained from three different samples: 1) regenerating Pax3GFP/+:mdx/mdx muscle (Ad.mdx) , 2) growing 1 week old Pax3GFP/+ muscle (1wk), and 3) adult Pax3GFP/+ cells after 3 days in culture (Ad.cult).
Project description:To uncover new pathways that are important for skeletal muscle stem cell aging, we performed multiomics profiling, including transcriptomics, DNA methylomics, proteomics, and metabolomics on quiescent muscle stem cells from young and old mice. Our goals were to discover pathways that have been overlooked by isolated profiling approaches and to gain insight into which changes are causal, compensatory, correlational, and consequential. In our work, we found that glutathione metabolism is a key pathway of muscle stem cell aging that involves a compensatory feedback loop. Follow-up experiments showed that old muscle stem cells actually form a dichotomy between glutathione-high muscle stem cells and glutathione-low muscle stem cells. RNA-Seq showed that glutathione-high old muscle stem cells are able to synthesize adequate glutathione and thus compensate adequately for oxidative stress with increased glutathione turnover, while glutathione-low old muscle stem cells have failed to compensate for oxidative stress metabolically and instead show increased inflammatory signaling.
Project description:We performed genome-wide gene expression analysis of quiescent/activated muscle stem cells isolated from mouse skeletal muscle by flow cytometry.