Two ATPases in the Sarcoplasmic Reticulum of Skeletal Muscle Fibres

Giacomelli, F; C, Bibbiani; Bergamini, Ettore; Pellegrino, C

doi:10.1038/213679a0

Cited by 12 publications

(5 citation statements)

References 29 publications

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“…2. 4 | RNA library preparation, sequencing, and alignment RNA-sequencing (RNA-seq) library preparation, sequencing, and RNA-seq data generation was performed by the Human Genotyping facility (HugeF) of the ErasmusMC, the Netherlands, as described in the protocols of the Biobank-Based Integrative Omics Studies (BIOS) consortium. 24 In short, libraries were made from total muscle RNA using Illumina TruSeq version 2 library preparation kits.…”

Section: Rna Isolationmentioning

confidence: 99%

“…For instance, muscle degeneration is often characterized by atrophy of especially fast‐glycolytic myofibers, while insulin resistance is associated with shifts from slow‐oxidative to fast‐glycolytic myofibers . Conventionally, myofiber type is determined by colorimetric staining for metabolic enzyme activity, such as ATPase . Thus, obtained measurements are then typically employed to assign fibers to one of two classes (positive and negative to the staining).…”

Section: Introductionmentioning

confidence: 99%

“…Fiber classification is, therefore, regarded the key for understanding processes affecting muscle biology, physiology, and pathophysiology. [1][2][3][4][5][6] For instance, muscle degeneration is often characterized by atrophy of especially fast-glycolytic myofibers, [7][8][9] while insulin resistance is associated with shifts from slow-oxidative to fast-glycolytic myofibers. 10 Conventionally, myofiber type is determined by colorimetric staining for metabolic enzyme activity, such as ATPase.…”

Section: Introductionmentioning

confidence: 99%

“…10 Conventionally, myofiber type is determined by colorimetric staining for metabolic enzyme activity, such as ATPase. 4,11 Thus, obtained measurements are then typically employed to assign fibers to one of two classes (positive and negative to the staining). For example, the expression of myosin heavy chain (MyHC) isoforms, assessed by immunohistochemistry, 9,[12][13][14] is employed to classify myofibers as fast-or slow-twitch.…”

Section: Introductionmentioning

confidence: 99%

“…Thus, alterations in muscle function are reflected by changes in myofiber type composition. Fiber classification is, therefore, regarded the key for understanding processes affecting muscle biology, physiology, and pathophysiology . For instance, muscle degeneration is often characterized by atrophy of especially fast‐glycolytic myofibers, while insulin resistance is associated with shifts from slow‐oxidative to fast‐glycolytic myofibers .…”

Section: Introductionmentioning

confidence: 99%

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A data‐driven methodology reveals novel myofiber clusters in older human muscles

et al. 2020

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Skeletal muscles control posture, mobility and strength, and influence whole‐body metabolism. Muscles are built of different types of myofibers, each having specific metabolic, molecular, and contractile properties. Fiber classification is, therefore, regarded the key for understanding muscle biology, (patho‐) physiology. The expression of three myosin heavy chain (MyHC) isoforms, MyHC‐1, MyHC‐2A, and MyHC‐2X, marks myofibers in humans. Typically, myofiber classification is performed by an eye‐based histological analysis. This classical approach is insufficient to capture complex fiber classes, expressing more than one MyHC‐isoform. We, therefore, developed a methodological procedure for high‐throughput characterization of myofibers on the basis of multiple isoforms. The mean fluorescence intensity of the three most abundant MyHC isoforms was measured per myofiber in muscle biopsies of 56 healthy elderly adults, and myofiber classes were identified using computational biology tools. Unsupervised clustering revealed the existence of six distinct myofiber clusters. A comparison with the visual assessment of myofibers using the same images showed that some of these myofiber clusters could not be detected or were frequently misclassified. The presence of these six clusters was reinforced by RNA expressions levels of sarcomeric genes. In addition, one of the clusters, expressing all three MyHC isoforms, correlated with histological measures of muscle health. To conclude, this methodological procedure enables deep characterization of the complex muscle heterogeneity. This study opens opportunities to further investigate myofiber composition in comparative studies.

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Section: Rna Isolationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%