waveRAPID-A Robust Assay for High-Throughput Kinetic Screens with the Creoptix WAVEsystem.

Surface-based biophysical methods for measuring binding kinetics of molecular interactions, such as surface plasmon resonance (SPR) or grating-coupled interferometry (GCI), are now well established and widely used in drug discovery. Increasing throughput is an often-cited need in the drug discovery process and this has been achieved with new instrument generations where multiple interactions are measured in parallel, shortening the total measurement times and enabling new application areas within the field. Here, we present the development of a novel technology called waveRAPID for a further-up to 10-fold-increase in throughput, consisting of an injection method using a single sample. Instead of sequentially injecting increasing analyte concentrations for constant durations, the analyte is injected at a single concentration in short pulses of increasing durations. A major advantage of the new method is its ability to determine kinetics from a single well of a microtiter plate, making it uniquely suitable for kinetic screening. We present the fundamentals of this approach using a small-molecule model system for experimental validation and comparing kinetic parameters to traditional methods. By varying experimental conditions, we furthermore assess the robustness of this new technique. Finally, we discuss its potential for improving hit quality and shortening cycle times in the areas of fragment screening, low-molecular-weight compound screening, and hit-to-lead optimization.

Cell type-specific genome scans of DNA methylation divergence indicate an important role for transposable elements.

In population genomics, genetic diversity measures play an important role in genome scans for divergent sites. In population epigenomics, comparable tools are rare although the epigenome can vary at several levels of organization. We propose a model-free, information-theoretic approach, the Jensen-Shannon divergence (JSD), as a flexible diversity index for epigenomic diversity. Here, we demonstrate how JSD uncovers the relationship between genomic features and cell type-specific methylome diversity in Arabidopsis thaliana. However, JSD is applicable to any epigenetic mark and any collection of individuals, tissues, or cells, for example to assess the heterogeneity in healthy organs and tumors.

Genome-wide, Single-Cell DNA Methylomics Reveals Increased Non-CpG Methylation during Human Oocyte Maturation.

The 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 generic rate law for surface-active enzymes.

Many 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.

Carbohydrate-active enzymes exemplify entropic principles in metabolism.

Glycans comprise ubiquitous and essential biopolymers, which usually occur as highly diverse mixtures. The myriad different structures are generated by a limited number of carbohydrate-active enzymes (CAZymes), which are unusual in that they catalyze multiple reactions by being relatively unspecific with respect to substrate size. Existing experimental and theoretical descriptions of CAZyme-mediated reaction systems neither comprehensively explain observed action patterns nor suggest biological functions of polydisperse pools in metabolism. Here, we overcome these limitations with a novel theoretical description of this important class of biological systems in which the mixing entropy of polydisperse pools emerges as an important system variable. In vitro assays of three CAZymes essential for central carbon metabolism confirm the power of our approach to predict equilibrium distributions and non-equilibrium dynamics. A computational study of the turnover of the soluble heteroglycan pool exemplifies how entropy-driven reactions establish a metabolic buffer in vivo that attenuates fluctuations in carbohydrate availability. We argue that this interplay between energy- and entropy-driven processes represents an important regulatory design principle of metabolic systems.

Ground state robustness as an evolutionary design principle in signaling networks.

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.