Statistical thermodynamics and in vitro experimentation demonstrate that metabolic enzymes can be driven by an increase in the entropy of a reaction system, and point to a role for entropy gradients in the emergence of robust metabolic functions in vivo.
SummaryThe establishment of DNA methylation patterns in oocytes is a highly dynamic process marking gene-regulatory events during fertilization, embryonic development, and adulthood. However, after epigenetic reprogramming in primordial germ cells, how and when DNA methylation is re-established in developing human oocytes remains to be characterized. Here, using single-cell whole-genome bisulfite sequencing, we describe DNA methylation patterns in three different maturation stages of human oocytes. We found that while broad-scale patterns of CpG methylation have been largely established by the immature germinal vesicle stage, localized changes continue into later development. Non-CpG methylation, on the other hand, undergoes a large-scale, generalized remodeling through the final stage of maturation, with the net overall result being the accumulation of methylation as oocytes mature. The role of the genome-wide, non-CpG methylation remodeling in the final stage of oocyte maturation deserves further investigation.
a b s t r a c tMany biochemical reactions are confined to interfaces, such as membranes or cell walls. Despite their importance, no canonical rate laws describing the kinetics of surface-active enzymes exist. Combining the approach chosen by Michaelis and Menten 100 years ago with concepts from surface chemical physics, we here present an approach to derive generic rate laws of enzymatic processes at surfaces. We illustrate this by a simple reversible conversion on a surface to stress key differences to the classical case in solution. The available area function, a concept from surface physics which enters the rate law, covers different models of adsorption and presents a unifying perspective on saturation effects and competition between enzymes. A remarkable implication is the direct dependence of the rate of a given enzyme on all other enzymatic species able to bind at the surface. The generic approach highlights general principles of the kinetics of surface-active enzymes and allows to build consistent mathematical models of more complex pathways involving reactions at interfaces.
The ability of an organism to survive depends on its capability to adapt to external conditions. In addition to metabolic versatility and efficient replication, reliable signal transduction is essential. As signaling systems are under permanent evolutionary pressure one may assume that their structure reflects certain functional properties. However, despite promising theoretical studies in recent years, the selective forces which shape signaling network topologies in general remain unclear. Here, we propose prevention of autoactivation as one possible evolutionary design principle. A generic framework for continuous kinetic models is used to derive topological implications of demanding a dynamically stable ground state in signaling systems. To this end graph theoretical methods are applied. The index of the underlying digraph is shown to be a key topological property which determines the so-called kinetic ground state (or off-state) robustness. The kinetic robustness depends solely on the composition of the subdigraph with the strongly connected components, which comprise all positive feedbacks in the network. The component with the highest index in the feedback family is shown to dominate the kinetic robustness of the whole network, whereas relative size and girth of these motifs are emphasized as important determinants of the component index. Moreover, depending on topological features, the maintenance of robustness differs when networks are faced with structural perturbations. This structural off-state robustness, defined as the average kinetic robustness of a network's neighborhood, turns out to be useful since some structural features are neutral towards kinetic robustness, but show up to be supporting against structural perturbations. Among these are a low connectivity, a high divergence and a low path sum. All results are tested against real signaling networks obtained from databases. The analysis suggests that ground state robustness may serve as a rationale for some structural peculiarities found in intracellular signaling networks.
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