FHL3 promotes the formation of fast glycolytic muscle fibers by interacting with YY1 and muscle glycolytic metabolism
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA883593 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR21681905_1.fastq.gz | Fastqsanger.gz | |||
| SRR21681905_2.fastq.gz | Fastqsanger.gz | |||
| SRR21681906_1.fastq.gz | Fastqsanger.gz | |||
| SRR21681906_2.fastq.gz | Fastqsanger.gz | |||
| SRR21681907_1.fastq.gz | Fastqsanger.gz |
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Project description:Skeletal muscle fibers regulate surrounding endothelial cells (EC) via secretion of numerous angiogenic factors, including extracellular vesicles (SkM-EV). Muscle fibers are broadly classified as oxidative (OXI) or glycolytic (GLY) depending on their metabolic characteristics. OXI fibers secrete more pro-angiogenic factors and have greater capillary densities than GLY fibers. OXI muscle secretes more EV than GLY, however it is unknown whether muscle metabolic characteristics regulate EV contents and signaling potential. Extracellular vesicles were isolated from primarily oxidative or glycolytic muscle tissue in mice. MicroRNA (miR) sequencing was done to determine SkM-EV miR contents and cultured endothelial cells were treated with OXI- and GLY-EV to investigate angiogenic signaling potential. There were considerable differences in miR contents between OXI- and GLY-EV and pathway analysis identified that OXI-EV miR were predicted to positively regulate multiple endothelial-specific pathways including nitric oxide (NO) and vascular endothelial growth factor (VEGF) pathways, compared to GLY-EV miRs. OXI-EV improved EC migration (+19%) and tube formation (length: +20%; # of tubes +35%) compared to GLY-EV. These benefits may have been NO pathway mediated, as OXI-EV increased phosphorylation of endothelial nitric oxide synthase (eNOS) and treatment of ECs with the NOS inhibitor L-NAME abolished differences in migration and tube formation between OXI- and GLY-EV. This is the first report to show widespread differences in miR contents between SkM-EV isolated from metabolically different muscle tissue and the first to demonstrate that oxidative muscle tissue secretes EV with greater angiogenic signaling potential than glycolytic muscle tissue.
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Project description:Skeletal muscle plays an important role in the health-promoting effects of exercise training, yet the underlying mechanisms are not fully elucidated. Proteomics of skeletal muscle is challenging due to presence of non-muscle tissues and existence of different fiber types confounding the results. This can be circumvented by analysis of pure fibers; however this requires isolation of fibers from fresh tissues. We developed a workflow enabling proteomics analysis of isolated muscle fibers from freeze-dried muscle biopsies and identified >4000 proteins. We investigated effects of exercise training on the pool of slow and fast muscle fibers. Exercise altered expression of >500 proteins irrespective of fiber type covering several metabolic processes, mainly related to mitochondria. Furthermore, exercise training altered proteins involved in regulation of post-translational modifications, transcription, Ca++ signaling, fat, and glucose metabolism in a fiber type-specific manner. Our data serves as a valuable resource for elucidating molecular mechanisms underlying muscle performance and health. Finally, our workflow offers methodological advancement allowing proteomic analyses of already stored freeze-dried human muscle biopsies.
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Project description:Purpose: Reduced Representation Bisulfite Sequencing (RRBS) DNA input requirements become a challenge when working with small pools of tissue-specific cell types. We describe an application of the RRBS method to assess DNA methylation on low-DNA input from human slow-twitch (MHC I) and fast-twitch (MHC IIa) skeletal muscle fibers. Methods : Fiber-type specific (MHC I and MHC IIa muscle fibers) total DNA was extracted from vastus lateralis muscle biopsies of 8 young physically active men (~25 yrs). A total of 16 DNA samples were generated : 8 DNA samples from pure MHC I and 8 DNA samples from pure MHC IIa muscle fibers. An equal quantity of DNA (4 ng) from each sample was combined to generate a "pooled" DNA sample representing all 8 subjects for each fiber type. Two fiber-type specific "pooled" samples of 32 ng of DNA were generated for library construction and sequencing, creating a Type 1 (MHC I muscle fibers) and Type 2a (MHC IIa muscle fibers) sample. Sequencing was performed using the HiSeq 2500 (Illumina) with 50 bp paired-end read parameters. Minimum sequencing read coverage of 5 (5x) was used as the cutoff for CpG-sites inclusion in the DNA methylation analysis. Fisher’s exact test was performed on CpG-sites that overlapped (i.e. identified in both samples) Type 1 and Type 2a samples to obtain p-values that indicate the likelihood of the site being a differentially methylated CpG-site (DMS). DMS with p<0.05 were classified as hypermethylated or hypomethylated if they were more or less methylated than the Type 1 sample, which was used as the reference sample. Results: The 32 ng of DNA from fiber-type specific muscle samples (Type 1 and 2a) used in this study ensured similar sequencing quality as compared to other studies using greater DNA input (>50 ng). Mapping ratios of ~47% and bisulfite conversion rates of ~97-98% were obtained.The unique and best alignment was successfully assessed for each of 17,376,728 CpG-sites in the Type 1 sample and 17,006,993 in the Type 2a sample, which represents ~30% of the total CpG number in the human genome. We identified 143,160 differentially methylated CpG-sites (DMS) across 14,046 genes among MHC I and MHC IIa muscle fibers. The analysis revealed that some genes predominantly expressed in MHC I were hypermethylated in MHC IIa muscle fibers. Conclusion: This study validates a low-DNA input RRBS method for human skeletal muscle samples to investigate the methylation patterns at a fiber-type specific level. These are the first fiber-type specific methylation data reported from human skeletal muscle. Considering the metabolic and structural differences between MHC I and MHC IIa muscle fibers, this technique could provide novel insights into the skeletal muscle methylation profile in relation to health, performance, disease or disuse.
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Project description:There is considerable crosstalk between satellite cells, endothelilal cells and muscle fibers. Transcriptome analysis from freshly isolated cells from each compartment should help elucidate these pathways.
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