Difference between revisions of "Muscle models"

Revision as of 14:44, 1 October 2018

Introduction

Skeletal muscle is one of the most abundant tissues in mammals, accounting for up to 40% of the total mass ofthe human body (Janssen et al., 2000)[1]. The contraction–relaxation cycle in muscle requires energy that is mostly generated aerobically by mitochondria particularly abundant in adult muscle fibres. It is worth to note that skeletal muscle can maintain ATP concentration constant during the transition from rest to exercise, whereas metabolic reaction rates may increase substantially (Kunz, 2001) [2]. Although it is well known that skeletal muscle adaptations to exercise depend on duration, intensity, and frequency, changes in muscle proteins associated with different types of exercise have not been well characterized (Gonzalez‐Freire et al., 2017) [3]. Moreover, the quantitative contributions of different fiber types to the energy demand and detailed dynamics of metabolic responses of the skeletal muscle in response to different exercise intensities are unknown. Indeed, accurate measurements to quantify the recruitment and metabolic activation of muscle fibers in vivo have not been possible to date (Li et al., 2012) [4]. So due to a shortage of dynamic in vivo human data, the regulatory mechanisms of functioning of the skeletal muscle metabolism are poorly understood. To quantitatively interpret the limited data, a physiologically based mathematical modeling approach can be applied (Li et al., 2010) [5].

Published models

One of the first theoretical investigation in this field was conducted by Bernard Korzeniewski (Korzeniewski, 1998) [6]. He developed the computational model of oxidative phosphorylation in skeletal muscle mitochondria in order to decipher a regulatory mechanism of the adjustment of ATP production to ATP consumption in contracting muscle. During the transition from the resting state of muscles to their maximal exercise, there is a great increase in energy demand (ATP consumption). Mitochondrial oxidative phosphorylation is the main process responsible for ATP production in most muscle fibre types under most conditions. Therefore, mitochondria have to ‘know’ in some way how fast should they produce ATP in a given moment of time to meet the rate of energy consumption and to avoid a drastic decrease in cytosolic phosphorylation potential which would hinder muscle contraction.Two alternative mechanisms of the adjusting the energy (ATP) production rate to the energy consumption rate were postulated. They can be called the ‘negative feedback’ and ‘parallel activation’ (Figure 1).

Figure 1 from (Korzeniewski 1998) [6]. Comparison of the negative feedback and parallel activation mechanisms. (a) Negative feedback; only ATP consumption is activated directly by an external effector (for example calcium ions), while ATP production is activated indirectly, via a significant decrease in the ATP/ADP ratio. (b) Parallel activation ; both ATP consumption and ATP production are directly activated by an external effector; the ATP/ADP ratio remains approximately constant.

References

1. Janssen I, Heymsfield SB, Wang ZM, and Ross R. Skeletal muscle mass and distribution in 468 men and women aged 18-88 yr. J Appl Physiol (1985). 2000 Jul;89(1):81-8. DOI:10.1152/jappl.2000.89.1.81 | PubMed ID:10904038 | HubMed [1]
2. Kunz WS. Control of oxidative phosphorylation in skeletal muscle. Biochim Biophys Acta. 2001 Mar 1;1504(1):12-9. DOI:10.1016/s0005-2728(00)00235-8 | PubMed ID:11239481 | HubMed [2]
3. Gonzalez-Freire M, Semba RD, Ubaida-Mohien C, Fabbri E, Scalzo P, Højlund K, Dufresne C, Lyashkov A, and Ferrucci L. The Human Skeletal Muscle Proteome Project: a reappraisal of the current literature. J Cachexia Sarcopenia Muscle. 2017 Feb;8(1):5-18. DOI:10.1002/jcsm.12121 | PubMed ID:27897395 | HubMed [3]
4. Li Y, Lai N, Kirwan JP, and Saidel GM. Computational Model of Cellular Metabolic Dynamics in Skeletal Muscle Fibers during Moderate Intensity Exercise. Cell Mol Bioeng. 2012 Mar;5(1):92-112. DOI:10.1007/s12195-011-0210-y | PubMed ID:22942911 | HubMed [4]
5. Li Y, Solomon TP, Haus JM, Saidel GM, Cabrera ME, and Kirwan JP. Computational model of cellular metabolic dynamics: effect of insulin on glucose disposal in human skeletal muscle. Am J Physiol Endocrinol Metab. 2010 Jun;298(6):E1198-209. DOI:10.1152/ajpendo.00713.2009 | PubMed ID:20332360 | HubMed [5]
6. Korzeniewski B. Regulation of ATP supply during muscle contraction: theoretical studies. Biochem J. 1998 Mar 15;330 ( Pt 3)(Pt 3):1189-95. DOI:10.1042/bj3301189 | PubMed ID:9494084 | HubMed [6]