Genome-Scale Methods Converge on Key Mitochondrial Genes for the Survival of Human Cardiomyocytes in Hypoxia

Background—Any reduction in myocardial oxygen delivery relative to its demands can impair cardiac contractile performance. Understanding the mitochondrial metabolic response to hypoxia is key to understanding ischemia tolerance in the myocardium. We employed a novel combination of two genome-scale methods to study key processes underlying human myocardial hypoxia tolerance. In particular, we hypothesised that computational modelling and evolution would identify similar genes as critical to human myocardial hypoxia tolerance.

Methods and Results—We analysed a reconstruction of the cardiac mitochondrial metabolic network using constraint-based methods, under conditions of simulated hypoxia. We used flux balance analysis, random sampling and principle components analysis to explore feasible steady-state solutions. Hypoxia blunted maximal ATP (-17%) and haeme (-75%) synthesis and shrank the feasible solution space. TCA and urea cycle fluxes were also reduced in hypoxia, but phospholipid synthesis was increased. Using mathematical optimization methods, we identified reactions that would be critical to hypoxia tolerance in the human heart. We used data regarding SNP frequency and distribution in the genomes of Tibetans (whose ancestors have resided in persistent high-altitude hypoxia for several millennia). Six reactions were identified by both methods as being critical to mitochondrial ATP production in hypoxia: phosphofructokinase, phosphoglucokinase, Complex II, Complex IV, aconitase and fumarase.

Conclusions—Mathematical optimization and evolution converged on similar genes as critical to human myocardial hypoxia tolerance. Our approach is unique and completely novel and demonstrates that genome-scale modelling and genomics can be used in tandem to provide new insights into cardiovascular genetics.