| Literature DB >> 26441653 |
Valeriy M Paramonov1, Veronika Mamaeva2, Cecilia Sahlgren3, Adolfo Rivero-Müller4.
Abstract
Intracellular 3'-5'-cyclic adenosine monophosphate (cAMP) is one of the principal second messengers downstream of a manifold of signal transduction pathways, including the ones triggered by G protein-coupled receptors. Not surprisingly, biochemical assays for cAMP have been instrumental for basic research and drug discovery for decades, providing insights into cellular physiology and guiding pharmaceutical industry. However, despite impressive track record, the majority of conventional biochemical tools for cAMP probing share the same fundamental shortcoming-all the measurements require sample disruption for cAMP liberation. This common bottleneck, together with inherently low spatial resolution of measurements (as cAMP is typically analyzed in lysates of thousands of cells), underpin the ensuing limitations of the conventional cAMP assays: (1) genuine kinetic measurements of cAMP levels over time in a single given sample are unfeasible; (2) inability to obtain precise information on cAMP spatial distribution and transfer at subcellular levels, let alone the attempts to pinpoint dynamic interactions of cAMP and its effectors. At the same time, tremendous progress in synthetic biology over the recent years culminated in drastic refinement of our toolbox, allowing us not only to bypass the limitations of conventional assays, but to put intracellular cAMP life-span under tight control-something, that seemed scarcely attainable before. In this review article we discuss the main classes of modern genetically-encoded tools tailored for cAMP probing and modulation in living systems. We examine the capabilities and weaknesses of these different tools in the context of their operational characteristics and applicability to various experimental set-ups involving living cells, providing the guidance for rational selection of the best tools for particular needs.Entities:
Keywords: biosensor; cAMP signaling; cell-based assays; cyclic nucleotide; genetically encoded probe; optogenetics
Year: 2015 PMID: 26441653 PMCID: PMC4569861 DOI: 10.3389/fphar.2015.00196
Source DB: PubMed Journal: Front Pharmacol ISSN: 1663-9812 Impact factor: 5.810
FIGURE 1Main classes of direct biosensors for cAMP. A prototypical structure and mechanism of action of unimolecular and multimolecular FRET sensors (A and B respectively), BRET sensors (C), sensors, based on luminescent enzymes (D), and probes operating as conformation-sensitive fluorophores (E), are depicted. All the listed sensors directly bind cAMP molecules and react to binding events with conformational changes that affect their signaling properties—FRET or BRET efficiency (purple arrow), intensity of light production or fluorescence (winding arrows). For more details, please, refer to corresponding sections of the text. Abbreviations: C, PKA catalytic subunit; CFP, cyan fluorescent protein; GRN, green fluorophore; Luc, luciferase; LucN/C, fragments, forming luciferase holoenzyme; R, PKA regulatory subunit; RED, red fluorophore; RP, regulatory protein; YFP, yellow fluorescent protein.
FIGURE 2Harnessing CNGCc for indirect measurement of cAMP. (A) Basic operational principle of CNGCs: binding of cAMP (red triangle) to CNGCs results in channel opening for cations, allowing Na+ and Ca2+ to enter the cytoplasm. (B) Changes of the membrane potential and transmembrane electric currents, mediated by cAMP-driven CNGCs activation, can be registered with patch-clamp technique and serve as an indirect measure of cAMP levels. (C,D) Instruments, initially designed to measure concentration of intracellular Ca2+, can be applied in combination with CNGCs for indirect sensing of cAMP. Inorganic dyes (e.g., fluo-3), that demonstrate a pronounced rise in fluorescence upon binding of Ca2+ (C), and bioluminescent protein apoaequorin, responding to Ca2+ by generation of light (D), have been successfully used to this end.
FIGURE 3Selection of the task-specific biosensor for cAMP probing in living cells—a decision tree.
FIGURE 4Universal limitations inherent to most genetically encoded biosensors for cAMP.