کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
2041994 1073181 2015 13 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Proteome- and Transcriptome-Driven Reconstruction of the Human Myocyte Metabolic Network and Its Use for Identification of Markers for Diabetes
ترجمه فارسی عنوان
بازسازی پروتئین و ترانسکتوموم مغز متابولیک میوزیت انسان و استفاده از آن برای شناسایی نشانه های دیابت
موضوعات مرتبط
علوم زیستی و بیوفناوری علوم کشاورزی و بیولوژیک علوم کشاورزی و بیولوژیک (عمومی)
چکیده انگلیسی


• Reconstruction of a comprehensive myocyte-specific genome-scale metabolic model
• Meta-analysis of type 2 diabetes transcription in skeletal muscle from six studies
• Transcriptional regulation of metabolism around pyruvate, BCAAs, and THF
• Myocyte metabolic model identifies a metabolic signature of diabetes

SummarySkeletal myocytes are metabolically active and susceptible to insulin resistance and are 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 for the integration of high-throughput data. We generated myocyte-specific RNA-sequencing 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 downregulated 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.

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ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: - Volume 11, Issue 6, 12 May 2015, Pages 921–933
نویسندگان
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