For 26 years, it has been assumed by some that the thermodynamics of open-system biochemical reactions must be executed by performing Legendre transformations on the terms involving the species whose concentrations are being held fixed. In contrast, standard nontransformed thermodynamics applies to chemical processes. However, it has recently been shown that such biochemical reactions may be accurately examined using either method. The papers that report this finding use the hydrolysis of ATP at fixed pH and pMg as an example. This biochemical process comprises 14 equilibrium reactions involving 17 chemical species. Consequently, the chemical and mathematical complexity is so high that the underlying principles leading to the equivalence of the two methods tend to become lost. Furthermore, the details of such an example are too complex for classroom presentation. This paper makes these principles abundantly clear by the thermodynamic examination of the simple case of a unimolecular isomerization conducted under both open and closed conditions. For the open system, the analysis is conducted using both Legendre-transformed and nontransformed methods. The results are shown to be identical provided that the chemical potentials of the terms on which the transform is performed are held constant. More importantly, the analysis makes the underlying reasons for the equivalence of the two methods very clear and shows when they will not be equivalent. The model is ideally suited for classroom presentation because of its chemical and mathematical simplicity.
Circadian Proteomic Analysis Uncovers Mechanisms of Post-Transcriptional Regulation in Metabolic Pathways
Transcriptional and translational feedback loops in fungi and animals drive circadian rhythms in transcript levels that provide output from the clock, but post-transcriptional mechanisms also contribute. To determine the extent and underlying source of this regulation, we applied newly developed analytical tools to a long-duration, deeply sampled, circadian proteomics time course comprising half of the proteome. We found a quarter of expressed proteins are clock regulated, but >40% of these do not arise from clock-regulated transcripts, and our analysis predicts that these protein rhythms arise from oscillations in translational rates. Our data highlighted the impact of the clock on metabolic regulation, with central carbon metabolism reflecting both transcriptional and post-transcriptional control and opposing metabolic pathways showing peak activities at different times of day. The transcription factor CSP-1 plays a role in this metabolic regulation, contributing to the rhythmicity and phase of clock-regulated proteins.