Predicting the impact of temperature on metabolic fluxes using resource allocation modelling: Application to...

The understanding of microbial communities and the biological regulation of its members is crucial for implementation of novel technologies using microbial ecology. One poorly understood metabolic principle of microbial communities is resource allocation and biosynthesis. Resource allocation theory in polyphosphate accumulating organisms (PAOs) is limited as a result of their slow imposed growth rate (typical sludge retention times of at least 4 days) and limitations to quantify changes in biomass components over a 6 hours cycle (less than 10% of their growth). As a result, there is no direct evidence supporting that biosynthesis is an exclusive aerobic process in PAOs that alternate continuously between anaerobic and aerobic phases. Here, we apply resource allocation metabolic flux analysis to study the optimal phenotype of PAOs over a temperature range of 4 °C to 20 °C. The model applied in this research allowed to identify optimal metabolic strategies in a core metabolic model with limited constraints based on biological principles. The addition of a constraint limiting biomass synthesis to be an exclusive aerobic process changed the metabolic behaviour and improved the predictability of the model over the studied temperature range by closing the gap between prediction and experimental findings. The results validate the assumption of limited anaerobic biosynthesis in PAOs, specifically "Candidatus Accumulibacter" related species. Interestingly, the predicted growth yield was lower, suggesting that there are mechanistic barriers for anaerobic growth not yet understood nor reflected in the current models of PAOs. Moreover, we identified strategies of resource allocation applied by PAOs at different temperatures as a result of the decreased catalytic efficiencies of their biochemical reactions. Understanding resource allocation is paramount in the study of PAOs and their currently unknown complex metabolic regulation, and metabolic modelling based on biological first principles provides a useful tool to develop a mechanistic understanding.