Monitoring and mathematical modeling of mitochondrial ATP in myotubes at single-cell level reveals two distinct population with different kinetics

Abstract

Background

ATP is the major energy source for myotube contraction, and is quickly produced to compensate ATP consumption and to maintain sufficient ATP level. ATP is consumed mainly in cytoplasm and produced in mitochondria during myotube contraction. To understand the mechanism of ATP homeostasis during myotube contraction, it is essential to monitor mitochondrial ATP at single-cell level, and examine how ATP is produced and consumed in mitochondria.

Methods

We established C2C12 cell line stably expressing fluorescent probe of mitochondrial ATP, and induced differentiation into myotubes. We gave electric pulse stimulation to the differentiated myotubes, and measured mitochondrial ATP. We constructed mathematical model of mitochondrial ATP at single-cell level, and analyzed kinetic parameters of ATP production and consumption.

Results

We performed hierarchical clustering analysis of time course of mitochondrial ATP, which resulted in two clusters. Cluster 1 showed strong transient increase, whereas cluster 2 showed weak transient increase. Mathematical modeling at single-cell level revealed that the ATP production rate of cluster 1 was larger than that of cluster 2, and that both regulatory pathways of ATP production and consumption of cluster 1 were faster than those of cluster 2. Cluster 1 showed larger mitochondrial mass than cluster 2, suggesting that cluster 1 shows the similar property of slow muscle fibers, and cluster 2 shows the similar property of fast muscle fibers.

Conclusions

Cluster 1 showed the stronger mitochondrial ATP increase by larger ATP production rate, but not smaller consumption. Cluster 1 might reflect the larger oxidative capacity of slow muscle fiber.

References

  1. 1.

    Barclay, C. J. (2017) Energy demand and supply in human skeletal muscle. J. Muscle Res. Cell Motil., 38, 143–155

    CAS  Article  Google Scholar 

  2. 2.

    Gehlert, S., Bloch, W. and Suhr, F. (2015) Ca2+-dependent regulations and signaling in skeletal muscle: from electromechanical coupling to adaptation. Int. J. Mol. Sci., 16, 1066–1095

    CAS  Article  Google Scholar 

  3. 3.

    Chin, E. R. (2010) Intracellular Ca2+ signaling in skeletal muscle: decoding a complex message. Exerc. Sport. Sci. Rev., 38, 76–85

    Article  Google Scholar 

  4. 4.

    Nikolic, N., Skaret Bakke, S., Tranheim Kase, E., Rudberg, I., Flo Halle, I., Rustan, A. C., Thoresen, G. H. and Aas, V. (2012) Electrical pulse stimulation of cultured human skeletal muscle cells as an in vitro model of exercise. PLoS One, 7, e33203

    CAS  Article  Google Scholar 

  5. 5.

    Imamura, H., Huynh Nhat, K. P., Togawa, H., Saito, K., Iino, R., Kato-Yamada, Y., Nagai, T. and Noji, H. (2009) Visualization of ATP levels inside single living cells with fluorescence resonance energy transfer-based genetically encoded indicators. Proc. Natl. Acad. Sci. USA, 106, 15651–15656

    CAS  Article  Google Scholar 

  6. 6.

    Nakano, M., Imamura, H., Nagai, T. and Noji, H. (2011) Ca2+ regulation of mitochondrial ATP synthesis visualized at the single cell level. ACS Chem. Biol., 6, 709–715

    CAS  Article  Google Scholar 

  7. 7.

    Depaoli, M. R., Karsten, F., Madreiter-Sokolowski, C. T., Klec, C., Gottschalk, B., Bischof, H., Eroglu, E., Waldeck-Weiermair, M., Simmen, T., Graier, W. F., et al. (2018) Real-time imaging of mitochondrial ATP dynamics reveals the metabolic setting of single cells. Cell Rep., 25, 501–512.e3

    CAS  Article  Google Scholar 

  8. 8.

    Fujita, H., Nedachi, T. and Kanzaki, M. (2007) Accelerated de novo sarcomere assembly by electric pulse stimulation in C2C12 myotubes. Exp. Cell Res., 313, 1853–1865

    CAS  Article  Google Scholar 

  9. 9.

    Nedachi, T., Fujita, H. and Kanzaki, M. (2008) Contractile C2C12 myotube model for studying exercise-inducible responses in skeletal muscle. Am. J. Physiol. Endocrinol. Metab., 295, E1191–E1204

    CAS  Article  Google Scholar 

  10. 10.

    Inoue, H., Kunida, K., Matsuda, N., Hoshino, D., Wada, T., Imamura, H., Noji, H. and Kuroda, S. (2018) Automatic quantitative segmentation of myotubes reveals single-cell dynamics of S6 kinase activation. Cell Struct. Funct., 43, 153–169

    CAS  Article  Google Scholar 

  11. 11.

    Herbison, G. J., Jaweed, M. M. and Ditunno, J. F. (1982) Muscle fiber types. Arch. Phys. Med. Rehabil., 63, 227–230

    CAS  PubMed  Google Scholar 

  12. 12.

    Stockdale, F. E. (1997) Mechanisms of formation of muscle fiber types Stockdale. Cell Struct. Funct., 22, 37–43

    CAS  Article  Google Scholar 

  13. 13.

    Egan, B. and Zierath, J. R. (2013) Exercise metabolism and the molecular regulation of skeletal muscle adaptation. Cell Metab., 17, 162–184

    CAS  Article  Google Scholar 

  14. 14.

    Ward, Jr., J. H. (1963) Hierarchical grouping to optimize an objective function. J. Am. Stat. Assoc., 58, 236–244

    Article  Google Scholar 

  15. 15.

    Matsuoka, Y. and Inoue, A. (2008) Controlled differentiation of myoblast cells into fast and slow muscle fibers. Cell Tissue Res., 332, 123–132

    CAS  Article  Google Scholar 

  16. 16.

    Chance, B. and Williams, G. R. (1955) Respiratory enzymes in oxidative phosphorylation. I. Kinetics of oxygen utilization. J. Biol. Chem., 217, 383–393

    CAS  PubMed  Google Scholar 

  17. 17.

    Bohnensack, R. (1981) Control of energy transformation of mitochondria. Analysis by a quantitative model. Biochim. Biophys. Acta, 634, 203–218

    CAS  Article  Google Scholar 

  18. 18.

    Wu, F., Jeneson, J. A. L. and Beard, D. A. (2007) Oxidative ATP synthesis in skeletal muscle is controlled by substrate feedback. Am. J. Physiol. Cell Physiol., 292, C115–C124

    CAS  Article  Google Scholar 

  19. 19.

    Wüst, R. C. I., Grassi, B., Hogan, M. C., Howlett, R. A., Gladden, L. B. and Rossiter, H. B. (2011) Kinetic control of oxygen consumption during contractions in self-perfused skeletal muscle. J. Physiol., 589, 3995–4009

    Article  Google Scholar 

  20. 20.

    Korzeniewski, B. (1998) Regulation of ATP supply during muscle contraction: theoretical studies. Biochem. J. 330, 1189–1195

    CAS  Article  Google Scholar 

  21. 21.

    Brearley, M. C., Li, C., Daniel, Z. C. T. R., Loughna, P. T., Parr, T. and Brameld, J. M. (2019) Changes in expression of serine biosynthesis and integrated stress response genes during myogenic differentiation of C2C12 cells. Biochem. Biophys. Rep., 20, 100694

    PubMed  PubMed Central  Google Scholar 

  22. 22.

    Manabe, Y., Miyatake, S., Takagi, M., Nakamura, M., Okeda, A., Nakano, T., Hirshman, M. F., Goodyear, L. J. and Fujii, N. L. (2012) Characterization of an acute muscle contraction model using cultured C2C12 myotubes. PLoS One, 7, e52592

    CAS  Article  Google Scholar 

  23. 23.

    Fujita, K. A., Toyoshima, Y., Uda, S., Ozaki, Y., Kubota, H. and Kuroda, S. (2010) Decoupling of receptor and downstream signals in the Akt pathway by its low-pass filter characteristics. Sci. Signal., 3, ra56

    Article  Google Scholar 

  24. 24.

    Hubert, M. and Van Der Veeken, S. (2008) Outlier detection for skewed data. J. Chemometri., 22, 235–246

    CAS  Article  Google Scholar 

  25. 25.

    Brys, G., Hubert, M. and Struyf, A. (2004) A robust measure of skewness. J. Comput. Graph. Stat., 13, 996–1017

    Article  Google Scholar 

  26. 26.

    Benjamini, Y. and Hochberg, Y. (1995) Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. B, 57, 289–300

    Google Scholar 

Download references

Acknowledgements

We thank laboratory members for critical reading of the manuscript and for technical assistance with the analysis. The computations for this work were performed in part on the NIG supercomputer system at ROIS National Institute of Genetics. This work was supported by the Creation of Fundamental Technologies for Understanding and Control of Biosystem Dynamics, CREST, of the Japan Science and Technology Agency (JST). S. K. was supported by the Japan Society for the Promotion of Science (JSPS) KAKENHI Grant Number (17H06300, 17H6299, 18H03979, 19K22860), and M.F. was supported by the Japan Society for the Promotion of Science (JSPS) KAKENHI Grant Number (16K12508, 19K20382).

Author information

Affiliations

Authors

Contributions

N.M., K.K., D.H., and M.E. carried out the experiments; Y.F., Y.M., N.L.F., H.N., and H.I contributed to establishment of C2C12 cells stably expressing mitAT1.03 ATP probe; N.M. and H.I. carried out image analysis; N.M., T. W., and M.F. carried out computational analysis; writing group consisted of N.M., M.F., M.E., K.H and S.K.; and the study was conceived and supervised by N.M. and S.K.

Corresponding author

Correspondence to Shinya Kuroda.

Additional information

Compliance with Ethics Guidelines

The authors Naoki Matsuda, Ken-ichi Hironaka, Masashi Fujii, Takumi Wada, Katsuyuki Kunida, Haruki Inoue, Miki Eto, Daisuke Hoshino, Yasuro Furuichi, Yasuko Manabe, Nobuharu L. Fujii, Hiroyuki Noji, Hiromi Imamura and Shinya Kuroda declare that they have no conflict of interests. All procedures performed in this study were in accordance with the ethical standards of the institution or practice at which the studies were conducted, and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Additional Information

Data and model parameters are available online at http://kurodalab.bs.s.u-tokyo.ac.jp/ja/publication/info/matsuda/.

Supplementary Materials

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Matsuda, N., Hironaka, K., Fujii, M. et al. Monitoring and mathematical modeling of mitochondrial ATP in myotubes at single-cell level reveals two distinct population with different kinetics. Quant Biol (2020). https://doi.org/10.1007/s40484-020-0211-8

Download citation

Keywords

  • mitocondrial ATP production
  • ATP consumption
  • single-cell analysis
  • mathematical modeling