Choose your objective function in FBA wisely, so you can accurately predict yeast replicative lifespan

While working on the multi-scale model of yeast replicative ageing (yMSA), Barabara and Linnea found out that predicting yeast replicative lifespan is connected to how you choose your objective function in the flux balance analysis (FBA). This is highly relevant in biotechnology to enable higher productivity of biofuels, chemicals, and biologics where cell viability is imperative.  Engineered “long-living” yeast could improve industrial titres and manufacture cell-based diagnostic devices (like HIV and malaria tests) that are instrumental in resource-poor settings.

In FBA modelling, the objective function is closely related to and thus often motivated by arguments from evolutionary biology. In evolutionary biology, fitness is generally composed of viability, mating success and fertility, hence, the replicative lifespan. However, generation time is also an important feature during competitive growth. Here, we presented a systematic analysis of objective functions in the context of replicative ageing, utilising an enzyme-constrained FBA model of the central carbon metabolism of budding yeast cells, embedded in a published integrated model of nutrient signalling, metabolism and protein damage accumulation. We found that maximal growth is the most important objective with regard to the replicative lifespan, in line with previous studies. We further showed that an additional optimisation could improve the predictions of features of replicative ageing. We focused on maximal growth as a first objective, followed by either using the parsimonious solution or an additional maximisation of the non-growth associated maintenance (NGAM).

To find out more, check the full paper: ObjectiveFunctionRLS