Project description:Background: Skeletal muscle myocytes have evolved into slow and fast-twitch types. These types are functionally distinct as a result of differential gene and protein expression. However, an understanding of the complexity of gene and protein variation between myofibers is unknown. Methods: We performed deep, whole cell, single cell RNA-seq on intact and fragments of skeletal myocytes from the mouse flexor digitorum brevis muscle. We compared the genomic expression data of 171 of these cells with two human proteomic datasets. The first was a spatial proteomics survey of mosaic patterns of protein expression utilizing the Human Protein Atlas (HPA) and the HPASubC tool. The second was a mass-spectrometry (MS) derived proteomic dataset of single human muscle fibers. Immunohistochemistry and RNA-ISH were used to understand variable expression. Results: scRNA-seq identified three distinct clusters of myocytes (a slow/fast 2A cluster and two fast 2X clusters). Utilizing 1,605 mosaic patterned proteins from visual proteomics, and 596 differentially expressed proteins by MS methods, we explore this fast 2X division. Only 36 genes/proteins were mosaic across all three studies, of which nine are newly described as variable between fast/slow twitch myofibers. An additional 414 genes/proteins were identified by two methods. Immunohistochemistry and RNA-ISH generally validated variable expression across methods presumably due to species-related differences. Conclusions: In this first integrated proteogenomic analysis of mature skeletal muscle myocytes we validate the main fiber types and greatly expand the known repertoire of twitch-type specific genes/proteins. We also demonstrate the importance of integrating genomic and proteomic datasets.
Project description:Thiele2013 - Skeletal muscle myocytes
The model of skeletal muscle myocytes metabolism is derived from the community-driven global reconstruction of human metabolism (version 2.02, MODEL1109130000
).
This model is described in the article:
A community-driven global reconstruction of human metabolism.
Thiele I, et al
.
Nature Biotechnology
Abstract:
Multiple models of human metabolism have been reconstructed, but each represents only a subset of our knowledge. Here we describe Recon 2, a community-driven,
consensus 'metabolic reconstruction', which is the most comprehensive representation of human metabolism that is applicable to computational modeling. Compared
with its predecessors, the reconstruction has improved topological and functional features, including ~2x more reactions and ~1.7x more unique metabolites. Using
Recon 2 we predicted changes in metabolite biomarkers for 49 inborn errors of metabolism with 77% accuracy when compared to experimental data. Mapping metabolomic
data and drug information onto Recon 2 demonstrates its potential for integrating and analyzing diverse data types. Using protein expression data, we automatically
generated a compendium of 65 cell type-specific models, providing a basis for manual curation or investigation of cell-specific metabolic properties. Recon 2 will
facilitate many future biomedical studies and is freely available at http://humanmetabolism.org/.
This model is hosted on BioModels Database
and identified by: MODEL1310110011
.
To cite BioModels Database, please use: BioModels Database: An enhanced,
curated and annotated resource for published quantitative kinetic models
.
To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer
to CC0 Public Domain Dedication
for more information.
Project description:Skeletal muscle is a major site of postprandial glucose disposal. Inadequate insulin action in this tissue contributes to hyperglycemia in type 1 and type 2 diabetes. While glucose is known to stimulate insulin secretion by pancreatic b cells, whether it directly engages nutrient-sensing pathways in skeletal muscle to regulate glucose metabolism remains largely unexplored. Here we identified the Baf60c-Deptor-AKT pathway as a target of muscle glucose sensing that augments insulin action in skeletal myocytes. Genetic activation of this pathway improves postprandial glucose disposal in mice, whereas the muscle-specific ablation impaired insulin action and led to glucose intolerance. Mechanistically, glucose triggers a rapid calcium response in myocytes that acts on the class IIa histone deacetylase HDAC5, leading to Baf60c induction and insulin-independent AKT activation. The pathway is engaged by the anti-diabetic drugs sulfonylureas, suggesting that its therapeutic activation may have beneficial effects on glycemic control in diabetes. We used microarrays to elucidate the role of of Baf60c in transcriptional regulation by glucose in skeletal myocytes.
Project description:Skeletal myocytes are metabolically active and susceptible to insulin resistance, thus implicated in type 2 diabetes (T2D). This complex disease involves systemic metabolic changes and their elucidation at the systems level requires genome-wide data and biological networks. Genome-scale metabolic models (GEMs) provide a network-context to integrate high-throughput data. We generated myocyte-specific RNA-seq data and investigated their correlation with proteome data. These data were then used to reconstruct a comprehensive myocyte GEM. Next, we performed a meta-analysis of six studies comparing muscle transcription in T2D versus healthy subjects. Transcriptional changes were mapped on the myocyte GEM, revealing extensive transcriptional regulation in T2D, particularly around pyruvate oxidation, branched-chain amino acid catabolism, and tetrahydrofolate metabolism, connected through the down-regulated dihydrolipoamide dehydrogenase. Strikingly, the gene signature underlying this metabolic regulation successfully classifies the disease state of individual samples, suggesting that regulation of these pathways is a ubiquitous feature of myocytes in response to T2D. Isolated skeletal muscle precursor cells from six normal glucose tolerant and non-obese males and females were differentiated in vitro. RNA from fully differentiated myotubes was sequenced using RNA-seq.
Project description:We report a genome-wide study of the role of a muscle-specific Igf2/H19 transcriptional enhancer in global histone modifications in primary mouse myocytes. We generated 1.7 billion bases of sequence from DNA purified by the chromatin immunoprecipitation of H3K36me3 in wild type myocytes and myocytes bearing a deletion of the enhancer. Because H3K36me3 is reported to mark transcribed gene regions, we generated these data to develop a list of genes that are directly or indirectly regulated by this muscle enhancer. This study provides additional insight into how this muscle-specific enhancer potentially regulates a transcriptional network in mouse skeletal myocytes.
Project description:Fish skeletal muscle plays a crucial role in various physiological functions, and providing an important source of meat for human consumption. Therefore, understanding the molecular genetic regulation of muscle development and growth can benefit in enhancing the efficacy of aquaculture. Morphological and skeletal muscle histological analysis of Megalobrama amblycephala at 14 development stages ranging from 5-240 days post-hatching (d) revealed that 30 d and 45 d are the crucial stages for postembryonic muscle fibers hyperplasia and hypertrophy in M. amblycephala, respectively. Then we utilized single cell RNA sequencing (scRNA-seq) to investigate the regulation mechanism of postembryonic muscle development in M. amblycephala skeletal muscle at 30 d and 45 d. Here, scRNA-seq obtained 45,572 cells and identified a total of 13 distinct cell types in the skeletal muscle tissue. We reconstructed the cell differentiation events using all the cell clusters by single cell pseudo time trajectories, and the differentiation trajectory indicates that skeletal muscle cells derive from mesenchymal stem cells (MSCs). Furthermore, we analyzed the cell-specificity of skeletal muscle-related cells and their differences at different developmental stages, and identified a total of 51 crucial genes for muscle development, including 9 genes from muscle progenitors, 35 genes from myoblasts, and 7 genes from skeletal myocytes. Cell-cell communication analysis indicated that IGF, VEGF, and SEMA3 signaling pathways serve as important incoming signaling pathways for MSCs at 30 d. Skeletal myocytes (SMs) and tendon cells etc., might influence the differentiation of MSCs into myogenic lineages via Igf2b - Igf1ra and Igf1 - Igf1ra ligand - receptor interaction. This study revealed a list of new genes involved in M. amblycephala postembryonic myogenesis, and will provide the information for the molecular breeding of muscle mass trait in M. amblycephala.
Project description:Skeletal muscle is one of the primary tissues involved in the development of type 2 diabetes (T2D). Obesity is tightly associated with T2D, making it challenging to isolate specific effects attributed to the disease alone. By using an in vitro myocyte model system we were able to isolate the inherent properties retained in myocytes originating from donor muscle precursor cells, without being confounded by varying extracellular factors present in the in vivo environment of the donor. We generated and characterized transcriptional profiles of myocytes from 24 human subjects, using a factorial design with two levels each of the factors T2D (healthy or diseased) and obesity (non-obese or obese), and determined the influence of each specific factor on genome-wide transcription. We identified a striking similarity of the transcriptional profiles associated independently with T2D or obesity. Obesity thus presents an inherent phenotype in skeletal myocytes, similar to that induced by T2D. Through bioinformatics analysis we found a candidate epigenetic mechanism, H3K27me3 histone methylation, mediating the observed transcriptional signatures. Functional characterization of the expression profiles revealed dysregulated myogenesis and down-regulated muscle function in connection with T2D and obesity, as well as up-regulation of genes involved in inflammation and the extracellular matrix. Further on, we identified a metabolite subnetwork involved in sphingolipid metabolism and affected by transcriptional up-regulation in T2D. Collectively, these findings pinpoint transcriptional changes that are hard-wired in skeletal myocytes in connection with both obesity and T2D.
Project description:Metabolic rewiring is a well-established feature of muscle cells and a hallmark of cancer. In isocitrate dehydrogenase 1 and 2 mutant tumors, increased production of the oncometabolite D-2-hydroxyglutarate (D2-HG) is associated with myopathy. The connection between metabolic changes and proteomic remodeling in skeletal muscle remains poorly understood. We demonstrate that D2-HG impairs NAD+ redox homeostasis in myocytes, causing activation of autophagy via de-acetylation of microtubule-associated protein 1 light chain 3-II (LC3-II) by the nuclear deacetylase Sirt1. We integrated multi-omics data from mice treated with D2-HG and demonstrate that autophagy activation leads to skeletal muscle atrophy and sex-dependent metabolic and proteomic remodeling. We also characterized protein and metabolite interactions linking energy-substrate metabolism with chromatin organization and autophagy regulation. Collectively, our multi-omics approach exposes mechanisms by which the oncometabolite D2-HG induces metabolic and proteomic remodeling in skeletal muscle, and provides a conceptual framework for identifying potential therapeutic targets in cachexia.