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Enregistrement W4401910605 · doi:10.1113/jp287294

Glycogen pools and utilization during exercise: future implication on glucose regulation

2024· article· en· W4401910605 sur OpenAlexaff
Roderick E. Sandilands, Alexis Marcotte‐Chénard

Notice bibliographique

RevueThe Journal of Physiology · 2024
Typearticle
Langueen
DomaineBiochemistry, Genetics and Molecular Biology
ThématiqueMuscle metabolism and nutrition
Établissements canadiensOkanagan University CollegeUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Organismes subventionnairesnon disponible
Mots-clésGlycogenSkeletal muscleAnaerobic exerciseChemistryMyofibrilGlycogen synthaseInternal medicineBiochemistryEndocrinologyBiologyMedicinePhysiology

Résumé

récupéré en direct d'OpenAlex

Glycogen is a complex glucose polymer that is stored mainly in the liver and skeletal muscle, providing an important fuel source during exercise (Ørtenblad et al., 2013). Specifically, the vast quantities of glycogen stored in skeletal muscle are essential for the turnover of ATP and serves as the rate-limiting process that dictates overall endurance capacity, with reduced glycogen levels leading to impaired aerobic performance (Ørtenblad et al., 2013). Although there is a plethora of research supporting the importance of skeletal muscle glycogen content for aerobic capacity, limited research has considered the importance of specific glycogen storage sites within skeletal muscle with regard to its role in aerobic performance and, to be exact, how shifting from aerobic to anaerobic metabolism affects reliance on glycogen use from these storage sites. Glycogen is stored heterogeneously throughout skeletal muscle in three distinct locations: (1) intermyofibrillar region, located close to the sarcoplasmic reticulum and mitochondria; (2) intramyofibrillar region, located between the contractive filaments inside myofibrils; and (3) subsarcolemmal region, located just beneath the fibre surface (Nielsen et al., 2011). The intermyofibrillar pool constitutes the greatest glycogen content (∼80%), whereas the intramyofibrillar and subsarcolemmal pools contain significantly less (∼5%–15%). In recent years it has been hypothesized that the utilization of glycogen pools in specific subcellular locations varies in relation to metabolic demand, with greater energy requirements being more reliant on the intermyofibrillar pools due to its close proximity to the mitochondria. In addition to storage location glycogen particle size and the density are key determinants that influence glycogen utilization, specifically during aerobic activity. Human skeletal muscle typically maintains a submaximal particle size of ∼25 nm, which has been hypothesized to represent the optimal particle size for upregulation of glycogen degradation enzyme activity. Although evidence suggests that after glycogen-depleting exercise, diets differing in carbohydrate content (i.e. low and high) do not affect the size of glycogen particles stored, limited research has investigated how low-carbohydrate diets impact the numerical density of glycogen particles across all pools. Recently in the Journal of Physiology, Schytz et al. (2024) aimed to determine the effects of high-intensity exercise on glycogen volumetric density and subcellular localization within human skeletal muscle. Additionally, the authors aimed to investigate alterations in particle size, numerical density and subcellular localization through carbohydrate and energy-restrictive diets after glycogen-depleting exercise. In a parallel-arm, randomized, counterbalanced, cross-over fashion, recreationally active males performed two maximal cycling exercise tests under two dietary intervention periods: moderate (M-CHO) or high (H-CHO) carbohydrate diets. The intervention consisted of two 5-day periods separated with 10 days of habitual exercise and diet. Participants were randomized to two separate high-intensity exercise protocols, consisting of either 1- or 15-min of maximal-intensity cycling. Participants began each intervention with a rest day (day −4) while consuming an M-CHO diet. The next day (day −3) participants performed glycogen-depleting exercise consisting of both upper and lower body exercises (i.e. a mixture of both short-term maximal efforts and prolonged continuous exercise). Subsequently in a randomized and counterbalanced order, participants either continued with the M-CHO diet or received an H-CHO diet after completion of the glycogen-depleting exercise on day −3. Participants rested the next day (day −2) and on the following day performed a short training session (day −1) while consuming their respective diets on each of the 2 days. On the final day (day 0) participants were given a standardized breakfast 2 h before performing 1- or 15-min exercise tests. Muscle biopsies were collected before and immediately after the exercise tests, while transmission electron microscopy imaging and stereology were used to determine muscle fibre type, glycogen content and localization (refer to Fig. 1 in the original article for a visual representation of the study design). Results from the study showed that cycling for both 1 and 15 min at high intensity displayed differential reductions in select glycogen pools. Cycling at maximal intensity for 1 min, the intermyofibrillar pool decreased by ∼12%, whereas the intramyofibrillar and subsarcolemmal pools decreased by ∼9% and ∼8%, respectively. Fifteen minutes of maximal-intensity cycling elicited an ∼30% reduction in the intermyofibrillar pool, as well as a 41% and 43% reduction in the intramyofibrillar and subsarcolemmal pools, respectively. The M-CHO group exhibited smaller particle sizes in all subcellular glycogen pools when compared to the H-CHO group, with fewer glycogen particles per volume, thus contributing to the lower particle density seen specifically in the intramyofibrillar and subsarcolemmal regions. However, after 1 min of intense cycling, the numerical density of the glycogen particles was the driving factor resulting in reduced intermyofibrillar volumetric density. Independent of diet 15 min of intense cycling resulted in reduced volumetric density in all subcellular depots, with greater reductions seen in the intramyofibrillar and subsarcolemmal pools. Schytz et al. (2024) have elegantly advanced our fundamental understanding of glycogen localization and utilization after the consumption of M-CHO and H-CHO diets by recreationally active males. These findings revealed that M-CHO and H-CHO diets affect subcellular glycogen storage; however this altered storage exhibited no effect on the glycogen utilization pattern during the 1- and 15-min maximal exercise tests. To further the ecological validity of this field, researchers may consider observing the effects of glycogen utilization and localization in highly trained females. Considering the lack of research examining carbohydrate intake in females and given the known differences in glucose metabolism between sexes (Fernandez-del-Valle, 2023), studies investigating the utilization of specific glycogen pools under select carbohydrate loading conditions may aid in the development of carbohydrate fuelling strategies that enhance performance. Given that females appear to have greater insulin sensitivity in skeletal muscle compared to their male counterparts (Fernandez-del-Valle, 2023), the utilization of select glycogen pools may differ during exercise at various intensities and durations. Additionally, it is crucial to investigate how these conditions may be affected by menstrual cycle phase, as hormones such as oestrogen, progesterone and oestradiol have been shown to influence substrate metabolism to favour fat oxidation during exercise (Fernandez-del-Valle, 2023). Furthermore, hormones such as oestrogen may decrease circulating levels of adipocyte lipoprotein lipase, which could contribute to increased utilization of skeletal muscle triglycerides and thus potentially alter glycogen breakdown and subcellular localization. Future research investigating the effects of female sex hormones on glycogen utilization and localization will help to further our basic understanding of female energy metabolism and provide insight into the mechanisms involved in glycogenolysis during specific phases of the menstrual cycle. Additionally given that people living with type 2 diabetes (T2D) exhibit altered glucose metabolism, examining the nature of glycogen storage among this population may be of interest. Frankenberg and colleagues (2022) have recently demonstrated that individuals living with T2D exhibit differential proportions of type 1 skeletal muscle fibres compared to individuals without T2D. People living with T2D also exhibit higher levels of enzymes involved in the regulation of glucose homeostasis, such as glycogen synthase, glycogen branching enzyme, glycogen phosphorylase and glycogen debranching enzyme. These enzymes have also been shown to be differentially located in and between fibres in people living with T2D compared to individuals without T2D. These differences in fibre type, distribution and enzymatic content may influence glycogen storage (i.e. through altered particle size and density) and thus alter glucose homeostasis. More specifically impairments in muscle glycogen phosphorylase and glycogen debranching enzyme may alter glycogenolysis, thus affecting glucose availability during energy demands (Frankenberg et al., 2022). Despite the myriad of research investigating the effects of cellular glucose transport, uptake and metabolism among people living with T2D, limited consideration has been given to the intricacies that affect subcellular utilization and localization of skeletal muscle glycogen among people living with T2D. Given that exercise is considered front-line therapy in the prevention, management and treatment of T2D, it is crucial to understand the processes underlying subcellular glucose utilization and storage in this population. By understanding how exercise intensity mediates the depletion of specific glycogen pools, manipulating the type, intensity and duration of exercise could help to elicit a more comprehensive depletion and subsequent replenishment of glycogen pools that may lead to improved glucose homeostasis. Additionally alterations in diet that limit carbohydrate and energy intake after exercise may provide insight into how glycogen particle size, density and volume impact subsequent glycogen storage and glucose control (see Fig. 1). Overall Schytz and colleagues (2024) provide novel insight into the subcellular localization of glycogen across the intermyofibrillar, intramyofibrillar and subsarcolemmal pools. These pools exhibited preferential utilization that is determined by exercise intensity and duration, with 1 min of intense exercise favouring the intermyofibrillar glycogen pool and 15 min of intense exercise favouring the intramyofibrillar and subsarcolemmal pools. Additionally, Schytz et al. (2024) demonstrate that reduced skeletal muscle glycogen availability induced through carbohydrate and energy restriction after glycogen-depleting exercise reduces particle size across all pools, and numerical density among the intramyofibrillar and subsarcolemmal regions. Future research may consider investigating the effects of skeletal muscle glycogen storage, localization and utilization, as well as specific diet-induced changes in particle subcellular distribution among people living with T2D and subsequently its impact on glucose regulation. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article. No competing interests declared. R.E.S.: conception or design of the work; drafting the work or revising it critically for important intellectual content; final approval of the version to be published; agreement to be accountable for all aspects of the work. A.M.-C.: conception or design of the work; drafting the work or revising it critically for important intellectual content; final approval of the version to be published; agreement to be accountable for all aspects of the work. This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors. Alexis Marcotte-Chénard was supported by CIHR and FRQS postdoctoral fellowships.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,002
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Synthèse · Signal consensuel: Synthèse
Score de désaccord entre enseignants0,008
Score d'incertitude au seuil0,026

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,002
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,001
Communication savante0,0020,002
Science ouverte0,0010,001
Intégrité de la recherche0,0020,002
Charge utile insuffisante (le modèle a refusé de juger)0,0080,001

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,010
Tête enseignante GPT0,256
Écart entre enseignants0,247 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreSynthèse

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2024
Routes d'admission1
Résumé présentoui

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