We have developed a versatile new class of genetically encoded fluorescent biosensor based on reversible exchange of the heterodimeric partners of green and red dimerization dependent fluorescent proteins (ddFPs). This strategy has been used to construct both intermolecular and intramolecular ratiometric biosensors for qualitative imaging of caspase activity, Ca2+ concentration dynamics, and other second messenger signaling activities.

Protein kinase A (PKA) phosphorylates Gli proteins, acting as a negative regulator of the Hedgehog pathway. PKA was recently detected within the cilium, and PKA activity specifically in cilia regulates Gli processing. Using a cilia-targeted genetically encoded sensor, we found significant basal PKA activity. Using another targeted sensor, we measured basal ciliary cAMP that is fivefold higher than whole-cell cAMP. The elevated basal ciliary cAMP level is a result of adenylyl cyclase 5 and 6 activity that depends on ciliary phosphatidylinositol (3,4,5)-trisphosphate (PIP3), not stimulatory G protein (Gαs), signaling. Sonic Hedgehog (SHH) reduces ciliary cAMP levels, inhibits ciliary PKA activity, and increases Gli1. Remarkably, SHH regulation of ciliary cAMP and downstream signals is not dependent on inhibitory G protein (Gαi/o) signaling but rather Ca2+ entry through a Gd3+-sensitive channel. Therefore, PIP3 sustains high basal cAMP that maintains PKA activity in cilia and Gli repression. SHH activates Gli by inhibiting cAMP through a G protein-independent mechanism that requires extracellular Ca2+ entry.

Protein-based, fluorescent biosensors power basic research on cell signaling in health and disease, but their use in automated laboratories is limited. We have now created two live-cell assays, one for diacyl glycerol and another for cAMP, that are robust (Z′ > 0.7) and easily deployed on standard fluorescence plate readers. We describe the development of these assays, focusing on the parameters that were critical for optimization, in the hopes that the lessons learned can be generalized to the development of new biosensor-based assays.

OBJECTIVECongenital hyperinsulinemic hypoglycemia is a group of genetic disorders of insulin secretion most commonly associated with inactivating mutations of the β-cell ATP-sensitive K+ channel (KATP channel) genes ABCC8 (SUR1) and KCNJ11 (Kir6.2). Recessive mutations of these genes cause hyperinsulinism that is unresponsive to treatment with diazoxide, a channel agonist. Dominant KATP mutations have been associated with diazoxide-responsive disease. We hypothesized that some medically uncontrollable cases with only one KATP mutation might have dominant, diazoxide-unresponsive disease.RESEARCH DESIGN AND METHODSMutations of the KATP genes were identified by sequencing genomic DNA. Effects of mutations on KATP channel function in vitro were studied by expression in COSm6 cells.RESULTSIn 15 families with diazoxide-unresponsive diffuse hyperinsulism, we found 17 patients with a monoallelic missense mutation of SUR1. Nine probands had de novo mutations, two had an affected sibling or parent, and four had an asymptomatic carrier parent. Of the 13 different mutations, 12 were novel. Expression of mutations revealed normal trafficking of channels but severely impaired responses to diazoxide or MgADP. Responses were significantly lower compared with nine SUR1 mutations associated with dominant, diazoxide-responsive hyperinsulinism.CONCLUSIONSThese results demonstrate that some dominant mutations of SUR1 can cause diazoxide-unresponsive hyperinsulinism. In vitro expression studies may be helpful in distinguishing such mutations from dominant mutations of SUR1 associated with diazoxide-responsive disease.

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.