Aryaman 2015 Abstract MiPschool London 2015

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Modelling mitochondrial DNA variability in metabolism.

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Aryaman J, Johnston IG, Jones NS (2015)

Event: MiPschool London 2015

Mutations in mitochondrial DNA are often observed in cancer, although their role is still somewhat unclear. Null models of rapidly dividing cells show that significant levels of homoplasmy can occur simply due to random genetic drift [1]. On the other hand, we observe tumours containing mtDNA mutations exclusively affecting particular subunits of the respiratory chain, suggesting a causal link [2]. We seek to elucidate the connection between mtDNA variability and tumour growth through models of metabolism.

We consider the effects of varying mtDNA copy number in a homoplasmic, wild-type, mitochondrion, in silico. In addition, we explore the effect of heteroplasmic mutations in each of the respiratory chain complexes (RCCs). We use a flux-balance analysis (FBA) model of mitochondrial metabolism from the literature [3], and contrast this to an ordinary differential equation (ODE) model [4]. We study the effect of constraining fluxes through complexes I, III, IV and ATP synthase, in order to model variations in mtDNA content. In future work, we intend to explore a system of rapidly-dividing cells, each obeying such a metabolic model.

In this preliminary study, we model mtDNA heteroplasmy by linearly reducing the maximum flux through mtDNA-coded RCCs . Using an FBA approach, we find that ATP synthesis varies linearly with RCC activity, with ATP synthase being the strongest modulator of ATP production. In contrast, an ODE approach displays threshold behaviour between RCC activity and ATP production, with complex III being the strongest modulator. In future work we hope to link these findings to models of tumour growth.

Quantitative modelling of metabolism can yield starkly different outcomes depending on the approach taken. ODE models are attractive in their ability to describe non-linearity, whereas FBA does not require detailed knowledge of kinetic parameters of the chemical system. Relevant modelling approaches should be used, depending on available knowledge of the system and its descriptive objectives.


Labels: MiParea: mtDNA;mt-genetics 




Regulation: ATP production 




Affiliations

Dept Mathematics, Imperial College London, UK. - juvid.aryaman09@imperial.ac.uk

References

  1. Coller HA, Khrapko K, Bodyak ND, Nekhaeva E, Herrero-Jimenez P, Thilly WG (2001) High frequency of homoplasmic mitochondrial DNA mutations in human tumors can be explained without selection. Nature 28:147-50.
  2. Gasparre G, Hervouet E, de Laplanche E, Demont J, Pennisi LF, Colombel M, Mège-Lechevallier F, Scoazec JY, Bonora E, Smeets R, Smeitink J, Lazar V, Lespinasse J, Giraud S, Godinot C, Romeo G, Simonnet (2008) Clonal expansion of mutated mitochondrial DNA is associated with tumor formation and complex I deficiency in the benign renal oncocytoma. Hum Mol Genet 17:986-95
  3. Smith AC, Robinson AJ (2001) A metabolic model of the mitochondrion and its use in modelling diseases of the tricarboxylic acid cycle. BMC Syst Biol 5:102
  4. Beard DA (2001) A biophysical model of the mitochondrial respiratory system and oxidative phosphorylation. PLoS Comput Biol 1:e36