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      Preassembled GPCR signaling complexes mediate distinct cellular responses to ultralow ligand concentrations

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          Abstract

          G protein–coupled receptors (GPCRs) are the largest class of cell surface signaling proteins, participate in nearly all physiological processes, and are the targets of 30% of marketed drugs. Typically, nanomolar to micromolar concentrations of ligand are used to activate GPCRs in experimental systems. We detected GPCR responses to a wide range of ligand concentrations, from attomolar to millimolar, by measuring GPCR-stimulated production of cyclic adenosine monophosphate (cAMP) with high spatial and temporal resolution. Mathematical modeling showed that femtomolar concentrations of ligand activated, on average, 40% of the cells in a population provided that a cell was activated by one to two binding events. Furthermore, activation of the endogenous β 2-adrenergic receptor (β 2AR) and muscarinic acetylcholine M 3 receptor (M 3R) by femtomolar concentrations of ligand in cell lines and human cardiac fibroblasts caused sustained increases in nuclear translocation of extracellular signal–regulated kinase (ERK) and cytosolic protein kinase C (PKC) activity, respectively. These responses were spatially and temporally distinct from those that occurred in response to higher concentrations of ligand and resulted in a distinct cellular proteomic profile. This highly sensitive signaling depended on the GPCRs forming preassembled, higher-order signaling complexes at the plasma membrane. Recognizing that GPCRs respond to ultralow concentrations of neurotransmitters and hormones challenges established paradigms of drug action and provides a previously unappreciated aspect of GPCR activation that is quite distinct from that typically observed with higher ligand concentrations.

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          Stochastic simulation of chemical kinetics.

          Stochastic chemical kinetics describes the time evolution of a well-stirred chemically reacting system in a way that takes into account the fact that molecules come in whole numbers and exhibit some degree of randomness in their dynamical behavior. Researchers are increasingly using this approach to chemical kinetics in the analysis of cellular systems in biology, where the small molecular populations of only a few reactant species can lead to deviations from the predictions of the deterministic differential equations of classical chemical kinetics. After reviewing the supporting theory of stochastic chemical kinetics, I discuss some recent advances in methods for using that theory to make numerical simulations. These include improvements to the exact stochastic simulation algorithm (SSA) and the approximate explicit tau-leaping procedure, as well as the development of two approximate strategies for simulating systems that are dynamically stiff: implicit tau-leaping and the slow-scale SSA.
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            Efficient selection for high-expression transfectants with a novel eukaryotic vector

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              Femtomolar sensitivity of metalloregulatory proteins controlling zinc homeostasis.

              Intracellular zinc is thought to be available in a cytosolic pool of free or loosely bound Zn(II) ions in the micromolar to picomolar range. To test this, we determined the mechanism of zinc sensors that control metal uptake or export in Escherichia coli and calibrated their response against the thermodynamically defined free zinc concentration. Whereas the cellular zinc quota is millimolar, free Zn(II) concentrations that trigger transcription of zinc uptake or efflux machinery are femtomolar, or six orders of magnitude less than one atom per cell. This is not consistent with a cytosolic pool of free Zn(II) and suggests an extraordinary intracellular zinc-binding capacity. Thus, cells exert tight control over cytosolic metal concentrations, even for relatively low-toxicity metals such as zinc.
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                Author and article information

                Journal
                Science Signaling
                Sci. Signal.
                American Association for the Advancement of Science (AAAS)
                1945-0877
                1937-9145
                October 09 2018
                October 09 2018
                October 09 2018
                October 09 2018
                : 11
                : 551
                : eaan1188
                Article
                10.1126/scisignal.aan1188
                7416780
                30301787
                b22091b6-28c1-4b4f-9f78-9340e2518db7
                © 2018

                http://www.sciencemag.org/about/science-licenses-journal-article-reuse

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