Stimulation of neurite outgrowth in PC12 cells by EGF and KCl depolarization: a Ca(2+)-independent phenomenon.

Mark, Melanie D.; Liu, Yuechueng; Wong, Scott T.; Hinds, Thomas R.; Storm, Daniel R.

doi:10.1083/jcb.130.3.701

Cited by 60 publications

(58 citation statements)

References 63 publications

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“…We next wanted to examine the effect of EGF on PKA activity in PC12 cells. Since EGF was shown not to increase cAMP or activate PKA in PC12 cells (14,36), it was unexpected when EGF induced an AKAR4-Kras response of 9.1% Ϯ 1.2% (n ϭ 12) (Fig. 1E, purple diamonds, and F, top).…”

Section: Resultsmentioning

confidence: 99%

“…Subsequently, activated PKA and Epac converge to activate Rap1 (26), the aforementioned mediator of sustained ERK activity (36,37). In contrast, EGF was not known to increase cAMP or activate PKA in PC12 cells (14). Interestingly, a number of studies have shown that when EGF is used in conjunction with cAMP-elevating agents, neurite outgrowth can be induced in PC12 cells (9,14,15,35).…”

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confidence: 99%

“…In contrast, EGF was not known to increase cAMP or activate PKA in PC12 cells (14). Interestingly, a number of studies have shown that when EGF is used in conjunction with cAMP-elevating agents, neurite outgrowth can be induced in PC12 cells (9,14,15,35). These studies suggest that cAMP-mediated signaling may play a role in GF signaling specificity in PC12 cells and point to a simple model showing that lack of cAMP-mediated cross-regulation specifies the transient ERK activity stimulated by EGF.…”

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confidence: 99%

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Spatiotemporally Regulated Protein Kinase A Activity Is a Critical Regulator of Growth Factor-Stimulated Extracellular Signal-Regulated Kinase Signaling in PC12 Cells

Herbst

Allen

Zhang

2011

Molecular and Cellular Biology

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PC12 cells exhibit precise temporal control of growth factor signaling in which stimulation with epidermal growth factor (EGF) leads to transient extracellular signal-regulated kinase (ERK) activity and cell proliferation, whereas nerve growth factor (NGF) stimulation leads to sustained ERK activity and differentiation. While cyclic AMP (cAMP)-mediated signaling has been shown to be important in conferring the sustained ERK activity achieved by NGF, little is known about the regulation of cAMP and cAMP-dependent protein kinase (PKA) in these cells. Using fluorescence resonance energy transfer (FRET)-based biosensors localized to discrete subcellular locations, we showed that both NGF and EGF potently activate PKA at the plasma membrane, although they generate temporally distinct activity patterns. We further show that both stimuli fail to induce cytosolic PKA activity and identify phosphodiesterase 3 (PDE3) as a critical regulator in maintaining this spatial compartmentalization. Importantly, inhibition of PDE3, and thus perturbation of the spatiotemporal regulation of PKA activity, dramatically increases the duration of EGF-stimulated nuclear ERK activity in a PKA-dependent manner. Together, these findings identify EGF and NGF as potent activators of PKA activity specifically at the plasma membrane and reveal a novel regulatory mechanism contributing to the growth factor signaling specificity achieved by NGF and EGF in PC12 cells.

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Section: Resultsmentioning

confidence: 99%

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confidence: 99%

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confidence: 99%

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Spatiotemporally Regulated Protein Kinase A Activity Is a Critical Regulator of Growth Factor-Stimulated Extracellular Signal-Regulated Kinase Signaling in PC12 Cells

Herbst

Allen

Zhang

2011

Molecular and Cellular Biology

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“…PLCc2, but not PLCc1, is required for the activation of CRE-mediated transcription Previous reports have indicated that the activation of cAMP or Ca 2+ signaling pathways induces CRE-mediated transcription in PC12 cells (Sheng et al 1991;Mark et al 1995;Thompson et al 1995;Impey et al 1998). To probe the role of PLCcs in CRE-mediated transcription induced by activation of the cAMP and Ca 2+ signaling pathways, we examined the effects of knockdown of the expression of PLCc1 and c2 in PC12 cells on this process.…”

Section: Siplcc1 and Siplcc2 Reduce Plcc1 Or Plcc2 Expression Respecmentioning

confidence: 99%

PLCγ2 Activates CREB-dependent Transcription in PC12 Cells Through Phosphorylation of CREB at Serine 133

et al. 2005

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The cAMP and Ca 2+ signaling pathways activate the transcription factor CREB through its phosphorylation at Serine 133. Activation of CREB is involved in the regulation of various biological phenomena. To understand further the mechanisms of the regulation of CREB activity in response to activation of the cAMP and Ca 2+ signaling pathways, we examined the roles of PLCcs in CREB activation in PC12 cells. siRNA-mediated reduction of the expression of PLCc2, but not PLCc1, inhibited both the phosphorylation of CREB at S133 and the activation of CREB-dependent transcription following treatment of cells with forskolin or ionomycin, which increases the intracellular concentrations of cAMP or Ca 2+ , respectively. Importantly, the siRNA targeting PLCc2 completely abolished CREB activation by Ca 2+ signaling but not by cAMP signaling. These results suggest that PLCc2 functions as an essential signal transducer leading to CREB activation in response to activation of the Ca 2+ signaling pathway and that the cAMP signaling pathway might activate CREB through phosphorylation of CREB by PKA and another signaling pathway mediated by PLCc2.

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“…One important determinant seems to be the duration of the signal. In the neuronal cell line PC12, short duration of MAPK-1,2 signaling is thought to promote proliferation, whereas sustained MAPK-1,2 signaling is thought to promote differentiation [50][51][52]. Recent studies by Murphy and co-workers have elucidated a feed-forward mechanism that decodes the duration of MAPK activation in terms of IEGs expression and function [53,54].…”

Section: Anatomy Of a Time Bridge: Feed-forward Relaysmentioning

confidence: 99%

Computational approaches for modeling regulatory cellular networks

Eungdamrong

Iyengar

2004

Trends in Cell Biology

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Cellular components interact with each other to form networks that process information and evoke biological responses. A deep understanding of the behavior of these networks requires the development and analysis of mathematical models. In this article, different types of mathematical representations for modeling signaling networks are described, and the advantages and disadvantages of each type are discussed. Two experimentally well-studied signaling networks are then used as examples to illustrate the insight that could be gained through modeling. Finally, the modeling approach is expanded to describe how signaling networks might regulate cellular machines and evoke phenotypic behaviors.During the past two decades, substantial progress has been made in understanding the biochemical properties of cellular components, in addition to the organization of various molecular machines such as those involved in transcription and motility. From these studies of components and pathways, the design principles underlying cellular networks have emerged [1,2]. However, a substantial number of experiments is still needed to build up thè parts list' for a cell and to specify `parts function' in terms of cellular location, dynamics and regulatory organization. Because of the sheer number of components and interactions, the analysis of regulatory interactions is not easily achieved through intuition; even pathways and networks with few components are configured into systems that display complex behaviors. Hence, it is becoming increasingly clear that quantitative descriptions that lead to predictive models can be of great use in analyzing signaling pathways.Models of regulatory networks can be developed at various levels. Each level has its value. The simplest models of regulatory pathways and networks depict them as connections maps (http://stke.sciencemag.org), which are useful starting points for detailed analyses of signaling pathways. Although many signaling pathways have been identified by the study of binary reactions, connections are increasingly deduced from high-throughput experimental analyses of both protein-protein interactions [3][4][5][6] and protein location and expression patterns [7,8]. However, these connection maps are largely qualitative and, hence, only limited mathematical analysis can be undertaken. Such analyses often fall along the line of statistical correlations (`clustering'), which reveals co-regulation of each component [9], or an analysis of how the components are connected, which describes the statistical properties of the network as a whole [10][11][12]. An advantage of these models is that they can be developed for large numbers of components and interactions, and are useful in obtaining an To understand how extracellular signals evoke dynamic cellular responses, an analysis of the chemical reactions that constitute a biological system is needed. Typically, such models are built in three stages. First, a biochemical scheme that depicts the chemical reactions between the components in the...

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Stimulation of neurite outgrowth in PC12 cells by EGF and KCl depolarization: a Ca(2+)-independent phenomenon.

Cited by 60 publications

References 63 publications

Spatiotemporally Regulated Protein Kinase A Activity Is a Critical Regulator of Growth Factor-Stimulated Extracellular Signal-Regulated Kinase Signaling in PC12 Cells

Spatiotemporally Regulated Protein Kinase A Activity Is a Critical Regulator of Growth Factor-Stimulated Extracellular Signal-Regulated Kinase Signaling in PC12 Cells

PLCγ2 Activates CREB-dependent Transcription in PC12 Cells Through Phosphorylation of CREB at Serine 133

Computational approaches for modeling regulatory cellular networks

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