Validation of a Damage Accumulation Model of Replicative Ageing in S.cerevisiae. - Olmin, Amanda (My University, 2019)
Age-related diseases and conditions give rise to societal challenges and pose a threat to healthy ageing. At the same time, the more recent evolutionary theories of ageing hypothesise that the process of ageing is a consequence of living rather than an evolutionary strategy. Consequently, it is implied that ageing is not as inevitable as many might believe and, as a consequence, it is of interest to study this biological process and its underlying mechanisms. On a cellular level, accumulation of damage is often regarded as the main cause of ageing. Since the basic properties of ageing between unicellular and multicellular organisms are similar on this level, it is common to use the unicellular yeast Saccharomyces cerevisiae as a model organism in the field of ageing research. The aim of this project is to validate a mathematical damage accumulation model of replicative ageing in yeast. The model represents a cell by intact protein and damage and describes how these quantities change as the cell grows. In addition to cell growth, the model takes asymmetric division, retention and cell death into account. For the purpose of validating the model of replicative ageing, structural and numerical identifiability methods are applied and continuous optimisation is performed using single-cell area data. The model is fit to experimental data obtained for wildtype yeast and the two deletion strains sir2 and fob1. Moreover, replicative lifespan data of 4,698 single-gene deletion strains is analysed and, in conjunction to this, it is investigated how the model parameters affect the replicative lifespan of the simulations. The results show that the parameters in the model of replicative ageing that describes the rate of change of intact protein and damage in the cell, are structurally identifiable. In spite of this, they are not numerically identifiable based on the experimental data available; the parameter estimates obtained have high variances and are moderately or highly correlated with each other. Likewise, it is possible to generate parameter sets that make the mathematical model reproduce the replicative lifespans of the investigated strains, if a replicative lifespan constraint is inferred on the optimisation. For future work, it is suggested that new experimental data is generated as to fit the model of replicative ageing to growth curves belonging to cells of later life stages. Ultimately, the data should be sufficient enough for the optimisation to generate parameter sets that make the model adapt to the characteristics of the investigated strains, without having additional constraints added to the objective function.
Keywords: Matematik; Grundläggande vetenskaper; Mathematics; Basic Sciences