A growing awareness indicates that many G-protein-coupled receptors (GPCRs) exist as homodimers, but the extent of the cooperativity across the dimer interface has been largely unexplored. Here, measurement of the dissociation kinetics of a fluorescent agonist (ABA-X-BY630) from the human A1 or A3 adenosine receptors expressed in CHO-K1 cells has provided evidence for highly cooperative interactions between protomers of the A3-receptor dimer in single living cells. In the absence of competitive ligands, the dissociation rate constants of ABA-X-BY630 from A1 and A3 receptors were 1.45 ± 0.05 and 0.57 ± 0.07 min−1, respectively. At the A3 receptor, this could be markedly increased by both orthosteric agonists and antagonists [15-, 9-, and 19-fold for xanthine amine congener (XAC), 5′-(N-ethyl carboxamido)adenosine (NECA), and adenosine, respectively] and reduced by coexpression of a nonbinding (N250A) A3-receptor mutant. The changes in ABA-X-BY630 dissociation were much lower at the A1 receptor (1.5-, 1.4-, and 1.5-fold). Analysis of the pEC50 values of XAC, NECA, and adenosine for the ABA-X-BY630-occupied A3-receptor dimer yielded values of 6.0 ± 0.1, 5.9 ± 0.1, and 5.2 ± 0.1, respectively. This study provides new insight into the spatial and temporal specificity of drug action that can be provided by allosteric modulation across a GPCR homodimeric interface.—May, L. T., Bridge, L. J., Stoddart, L. A., Briddon, S. J., Hill, S. J. Allosteric interactions across native adenosine-A3 receptor homodimers: quantification using single-cell ligand-binding kinetics.

In classical pharmacology, bioassay data are fit to general equations (e.g. the dose response equation) to determine empirical drug parameters (e.g. EC 50 and e max), which are then used to calculate chemical parameters such as affinity and efficacy. Here we used a similar approach for kinetic, time course signaling data, to allow empirical and chemical definition of signaling by G-protein-coupled receptors in kinetic terms. Experimental data are analyzed using general time course equations (model-free approach) and mechanistic model equations (mechanistic approach) in the commonly-used curvefitting program, GraphPad Prism. A literature survey indicated signaling time course data usually conform to one of four curve shapes: the straight line, association exponential curve, rise-and-fall to zero curve, and rise-and-fall to steady-state curve. In the model-free approach, the initial rate of signaling is quantified and this is done by curve-fitting to the whole time course, avoiding the need to select the linear part of the curve. It is shown that the four shapes are consistent with a mechanistic model of signaling, based on enzyme kinetics, with the shape defined by the regulation of signaling mechanisms (e.g. receptor desensitization, signal degradation). Signaling efficacy is the initial rate of signaling by agonist-occupied receptor (k τ), simply the rate of signal generation before it becomes affected by regulation mechanisms, measurable using the model-free analysis. Regulation of signaling parameters such as the receptor desensitization rate constant can be estimated if the mechanism is known. this study extends the empirical and mechanistic approach used in classical pharmacology to kinetic signaling data, facilitating optimization of new therapeutics in kinetic terms.

Plants display a range of striking architectural adaptations when grown at elevated temperatures. In the model plant Arabidopsis thaliana, these include elongation of petioles, and increased petiole and leaf angles from the soil surface. The potential physiological significance of these architectural changes remains speculative. We address this issue computationally by formulating a mathematical model and performing numerical simulations, testing the hypothesis that elongated and elevated plant configurations may reflect a leaf-cooling strategy. This sets in place a new basic model of plant water use and interaction with the surrounding air, which couples heat and mass transfer within a plant to water vapour diffusion in the air, using a transpiration term that depends on saturation, temperature and vapour concentration. A two-dimensional, multi-petiole shoot geometry is considered, with added leaf-blade shape detail. Our simulations show that increased petiole length and angle generally result in enhanced transpiration rates and reduced leaf temperatures in well-watered conditions. Furthermore, our computations also reveal plant configurations for which elongation may result in decreased transpiration rate owing to decreased leaf liquid saturation. We offer further qualitative and quantitative insights into the role of architectural parameters as key determinants of leaf-cooling capacity.

Dynamic cellular systems reprogram gene expression to ensure appropriate cellular fate responses to specific extracellular cues. Here we demonstrate that the dynamics of Nuclear Factor kappa B (NF-κB) signalling and the cell cycle are prioritised differently depending on the timing of an inflammatory signal. Using iterative experimental and computational analyses, we show physical and functional interactions between NF-κB and the E2 Factor 1 (E2F-1) and E2 Factor 4 (E2F-4) cell cycle regulators. These interactions modulate the NF-κB response. In S-phase, the NF-κB response was delayed or repressed, while cell cycle progression was unimpeded. By contrast, activation of NF-κB at the G1/S boundary resulted in a longer cell cycle and more synchronous initial NF-κB responses between cells. These data identify new mechanisms by which the cellular response to stress is differentially controlled at different stages of the cell cycle.DOI: http://dx.doi.org/10.7554/eLife.10473.001