Robustness of MEK-ERK Dynamics and Origins of Cell-to-Cell Variability in MAPK Signaling

Filippi, Sarah; Barnes, C.; Kirk, Paul; Kudo, Tetsuichi; Kunida, Katsuyuki; McMahon, Siobhán S.; Tsuchiya, Toshikazu; Wada, Tatsuo; Kuroda, Shinya; Stumpf, Michael

doi:10.1016/j.celrep.2016.05.024

Cited by 61 publications

(67 citation statements)

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“…variability in the concentrations of multiple effector proteins between individual cells) reduces information transfer (58,68,69). Notably, a recent study revealed that intrinsic noise alone (due to stochasticity in phosphorylation and dephosphorylation of ERK) is insufficient to explain cell-cell variability in ERK responses, and that it is noise extrinsic to the core ERK module that distorts the signal and causes a pronounced loss of information reduction in MI between stimulus and ERK (68). The observed MI values of <1 Bit for GnRH signaling to ERK imply that the system performs worse than a hypothetical one that can unambiguously distinguish between just two equally probable environmental states (e.g., high vs low GnRH concentrations), in spite of the fact that population-averaged measures reveal responses to GnRH that are graded over a broad range of GnRH concentrations.…”

Section: An Information Theoretic Approach To Gnrhr Signalingmentioning

confidence: 99%

“…The sources of the noise impairing information transfer via GnRHR are unknown but work in other models has revealed how extrinsic noise at multiple levels (i.e. variability in the concentrations of multiple effector proteins between individual cells) reduces information transfer (58,68,69). Notably, a recent study revealed that intrinsic noise alone (due to stochasticity in phosphorylation and dephosphorylation of ERK) is insufficient to explain cell-cell variability in ERK responses, and that it is noise extrinsic to the core ERK module that distorts the signal and causes a pronounced loss of information reduction in MI between stimulus and ERK (68).…”

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confidence: 99%

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Gonadotropin-releasing hormone signaling: An information theoretic approach

Voliotis

Garner

Alobaid

et al. 2018

Molecular and Cellular Endocrinology

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Gonadotropin-releasing hormone (GnRH) is a peptide hormone that mediates central control of reproduction, acting via G-protein coupled receptors that are primarily G coupled and mediate GnRH effects on the synthesis and secretion of luteinizing hormone and follicle-stimulating hormone. A great deal is known about the GnRH receptor signaling network but GnRH is secreted in short pulses and much less is known about how gonadotropes decode this pulsatile signal. Similarly, single cell measures reveal considerable cell-cell heterogeneity in responses to GnRH but the impact of this variability on signaling is largely unknown. Ordinary differential equation-based mathematical models have been used to explore the decoding of pulse dynamics and information theory-derived statistical measures are increasingly used to address the influence of cell-cell variability on the amount of information transferred by signaling pathways. Here, we describe both approaches for GnRH signaling, with emphasis on novel insights gained from the information theoretic approach and on the fundamental question of why GnRH is secreted in pulses.

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Section: An Information Theoretic Approach To Gnrhr Signalingmentioning

confidence: 99%

mentioning

confidence: 99%

Gonadotropin-releasing hormone signaling: An information theoretic approach

Voliotis

Garner

Alobaid

et al. 2018

Molecular and Cellular Endocrinology

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“…We treat the broadness of ppERK modes as generated by cell-to-cell variability in total ERK1 content -a reasonable assumption since the noise in the phosphorylation of ERK is negligible in comparison (34). We further neglect the indirect influence between activation status and ERK1 levels due to its weakness (checked in Fig.…”

Section: Results-experimentsmentioning

confidence: 99%

Modeling of cytometry data in logarithmic space: When is a bimodal distribution not bimodal?

et al. 2018

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Recent efforts in systems immunology lead researchers to build quantitative models of cell activation and differentiation. One goal is to account for the distributions of proteins from single-cell measurements by flow cytometry or mass cytometry as readout of biological regulation. In that context, large cell-to-cell variability is often observed in biological quantities. We show here that these readouts, viewed in logarithmic scale may result in two easily-distinguishable modes, while the underlying distribution (in linear scale) is unimodal. We introduce a simple mathematical test to highlight this mismatch. We then dissect the flow of influence of cell-to-cell variability proposing a graphical model which motivates higher-dimensional analysis of the data. Finally we show how acquiring additional biological information can be used to reduce uncertainty introduced by cell-to-cell variability, helping to clarify whether the data is uni- or bimodal. This communication has cautionary implications for manual and automatic gating strategies, as well as clustering and modeling of single-cell measurements. © 2018 International Society for Advancement of Cytometry.

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“…The same reaction network is sometimes used to process multiple types of input signal, and the response to the same signal is dependent on the cell type and the cellular environment. Moreover, cellular information processing often includes large cell-to-cell variance [1][2][3][4][5] even within the same cell type under the same conditions. Signal processing networks usually regulate a variety of elemental cellular reactions, including morphological changes, migration, gene expression, and metabolism, and variations in the combination of these multiple reactions result in cell-to-cell fluctuations in fate changes.…”

Section: Introductionmentioning

confidence: 99%

“…For this purpose, the simultaneous responses of multiple elements must be measured in single cells. Although there have been several theoretical studies of the correlation of multiple elements in the same networks [6][7][8][9], there have been few experimental studies in the field of signal transduction [4,10,11] when compared to genomics and proteomics [12,13].…”

Section: Introductionmentioning

confidence: 99%

Cell-to-cell diversification in ERBB-RAS-MAPK signal transduction that produces cell-type specific growth factor responses

Miyagi

Hiroshima

Sako

2019

Preprint

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Growth factors regulate cell fates, including their proliferation, differentiation, survival, and death, according to the cell type. Even when the response to a specific growth factor is deterministic for collective cell behavior, significant levels of fluctuation are often observed between single cells. Statistical analyses of single-cell responses provide insights into the mechanism of cell fate decisions but very little is known about the distributions of the internal states of cells responding to growth factors. Using multi-color immunofluorescent staining, we have here detected the phosphorylation of seven elements in the early response of the ERBB-RAS-MAPK system to two growth factors. Among these seven elements, five were analyzed simultaneously in distinct combinations in the same single cells. Although principle component analysis suggested cell-type and input specific phosphorylation patterns, cell-to-cell fluctuation was large. Mutual information analysis suggested that cells use multitrack (bush-like) signal transduction pathways under conditions in which clear cell fate changes have been reported. The clustering of single-cell response patterns indicated that the fate change in a cell population correlates with the large entropy of the response, suggesting a bet-hedging strategy is used in decision making. A comparison of true and randomized datasets further indicated that this large variation is not produced by simple reaction noise, but is defined by the properties of the signal-processing network. Author SummaryHow extracellular signals, such as growth factors (GFs), induce fate changes in biological cells is still not fully understood. Some GFs induce cell proliferation and others induce differentiation by stimulating a common reaction network. Although the response to each GF is reproducible for a cell population, not all single cells respond similarly. The question that arises is whether a certain GF conducts all the responding cells in the same direction during a fate change, or if it initially stimulates a variety of behaviors among single cells, from which the cells that move in the appropriate direction are later selected.Our current statistical analysis of single-cell responses suggests that the latter process, which is called a bet-hedging mechanism is plausible. The complex pathways of signal transmission seem to be responsible for this bet-hedging.

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Robustness of MEK-ERK Dynamics and Origins of Cell-to-Cell Variability in MAPK Signaling

Cited by 61 publications

References 65 publications

Gonadotropin-releasing hormone signaling: An information theoretic approach

Gonadotropin-releasing hormone signaling: An information theoretic approach

Modeling of cytometry data in logarithmic space: When is a bimodal distribution not bimodal?

Cell-to-cell diversification in ERBB-RAS-MAPK signal transduction that produces cell-type specific growth factor responses

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