Dataset Information

Bhalla2002_MAPK-bistability-fig1c

ABSTRACT: Model for figure 1c in Bhalla US et al. Science (2002) 297(5583):1018-23.The demo for this figure is available here. This synaptic signaling model is without the MKP-1 feedback, so it is bistable and remains so over long periods. This model originates from BioModels Database: A Database of Annotated Published Models (http://www.ebi.ac.uk/biomodels/). It is copyright (c) 2005-2011 The BioModels.net Team. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information. In summary, you are entitled to use this encoded model in absolutely any manner you deem suitable, verbatim, or with modification, alone or embedded it in a larger context, redistribute it, commercially or not, in a restricted way or not.. To cite BioModels Database, please use: Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol., 4:92.

SUBMITTER: Sharat Vayttaden

PROVIDER: MODEL9079179924 | BioModels | 2005-01-01

REPOSITORIES: BioModels

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Publications

MAP kinase phosphatase as a locus of flexibility in a mitogen-activated protein kinase signaling network.

Bhalla Upinder S US Ram Prahlad T PT Iyengar Ravi R

Science (New York, N.Y.) 20020801 5583

Intracellular signaling networks receive and process information to control cellular machines. The mitogen-activated protein kinase (MAPK) 1,2/protein kinase C (PKC) system is one such network that regulates many cellular machines, including the cell cycle machinery and autocrine/paracrine factor synthesizing machinery. We used a combination of computational analysis and experiments in mouse NIH-3T3 fibroblasts to understand the design principles of this controller network. We find that the grow ...[more]

PMID: 12169734

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Project description:This is a model of one presynaptic and one postsynaptic cell, as described in the article: Gamma oscillation by synaptic inhibition in a hippocampal interneuronal network model. Wang XJ, Buzsáki G. J Neurosci. 1996 Oct 15;16(20):6402-13. PMID:8815919; Abstract: Fast neuronal oscillations (gamma, 20-80 Hz) have been observed in the neocortex and hippocampus during behavioral arousal. Using computer simulations, we investigated the hypothesis that such rhythmic activity can emerge in a random network of interconnected GABAergic fast-spiking interneurons. Specific conditions for the population synchronization, on properties of single cells and the circuit, were identified. These include the following: (1) that the amplitude of spike afterhyperpolarization be above the GABAA synaptic reversal potential; (2) that the ratio between the synaptic decay time constant and the oscillation period be sufficiently large; (3) that the effects of heterogeneities be modest because of a steep frequency-current relationship of fast-spiking neurons. Furthermore, using a population coherence measure, based on coincident firings of neural pairs, it is demonstrated that large-scale network synchronization requires a critical (minimal) average number of synaptic contacts per cell, which is not sensitive to the network size. By changing the GABAA synaptic maximal conductance, synaptic decay time constant, or the mean external excitatory drive to the network, the neuronal firing frequencies were gradually and monotonically varied. By contrast, the network synchronization was found to be high only within a frequency band coinciding with the gamma (20-80 Hz) range. We conclude that the GABAA synaptic transmission provides a suitable mechanism for synchronized gamma oscillations in a sparsely connected network of fast-spiking interneurons. In turn, the interneuronal network can presumably maintain subthreshold oscillations in principal cell populations and serve to synchronize discharges of spatially distributed neurons. The presynaptic and postsynaptic cell have identical parameters and the variables in each cell are identified by using _pre or _post as a postfix to their names. The presynaptic cell influences the postsynaptic one via the synapse (variables and parameters: I_syn, E_syn, g_syn, F, theta_syn, alpha, beta). The applied current to the presynaptic cell, I_app_pre, is set to 2 microA/cm2 for 10 ms as in figure 1C of the article. The dependence of the postsynaptic cell on directly applied current can be investigated in isolation by setting I_app_pre to 0 and altering I_app_post. Originally created by libAntimony v1.4 (using libSBML 3.4.1)

Project description:To discover RBPs with increased insolubility in a human ALS model, we applied a well established dual-SMAD inhibition-based protocol (Fang et al., 2019; Markmiller et al., 2021; Markmiller et al., 2018; Martinez et al., 2016) to generate iPSC-MN from six control iPSC lines, from four iPSC lines originating from two sALS patients, and from two iPSC lines originating from fALS patients with pathogenic variants in the TARDBP gene (Table S1; Figure S1A). No difference in differentiation capacity was observed (Figure S1B-G), resulting in average 40% ISL1+ MN (Figures S1G), comparable to numbers observed in large scale MN differentation studies (Baxi et al., 2022). The susceptibility of ALS MN to sodium arsenite-induced stress was not changed (Figure S1H and I). Next, we asked which proteins exhibit an increased insolubility in our ALS iPSC-MN. We fractioned iPSC- MN by lysis in radio-immunoprecipitation assay (RIPA) buffer, followed by ultracentrifugation and solubilization of RIPA insoluble proteins in urea buffer. The ultracentrifugation-cleared RIPA insoluble protein fraction is widely used to study protein insolubility in the context of neurodegeneration (Nuber et al., 2013; Walker et al., 2015). Label-free mass spectrometry of the insoluble protein fraction was utilized to identify proteins that are insoluble in sALS and fALS, relative to control iPSC-MNs (Figure 1A). Gene ontology (GO) analysis of the 100 proteins (top 2.9% of all detected proteins) with the highest label free quantification (LFQ) intensities in controls (Figure S1J) revealed that ‘unfolded protein binding’ (corrected P = 7.95 x 10-16) and ‘structural constituent of cytoskeleton’ (corrected P = 1.47 x 10-10) were among the 10 most significantly enriched GO terms, indicating enrichment of insoluble proteins (Figure S1K). Principle component analysis of the insoluble fractions did not distinguish ALS from control samples, suggesting that the overall insoluble proteome is not changed (Figure S1L). At threshold P ≤ 0.05 (Welch’s t-test) and fold change ≥ 1.5, we identified 88 proteins enriched in the insoluble fraction in ALS samples relative to control (Figure 1B). When the sample labels were randomly shuffled, we observed an average of 7.5 proteins (~12-fold lower) as differentially enriched at the same statistical thresholds, indicative of an ALS-specific protein insolubility pattern (Figure 1C). The 88 candidate proteins included cytoskeletal components and motor proteins, functional categories associated with prominent ALS in vitro phenotypes (Akiyama et al., 2019; Egawa et al., 2012; Fazal et al., 2021; Guo et al., 2017; Kreiter et al., 2018) (Figure 1D). Notably, 5 RBPs, NOVA1, ELAVL4, FXR2, RBFOX2, and RBFOX3 were also enriched (Figure 1D). The NOVA1 paralog NOVA2 was significantly enriched (P = 0.03) but did not meet our enrichment threshold (fold change = 1.36). Interestingly, insoluble TDP-43 protein was not significantly different in ALS and control (P = 0.98; fold change = 0.97). Western blot analysis confirmed the increase in insolubility of NOVA1, NOVA2, ELAVL4, RBFOX2 and RBFOX3 (Figure 1E and 1F). The soluble protein levels of NOVA1 and NOVA2 were also increased (Figure 1F). In conclusion, we identified 5 RBPs with elevated insoluble protein levels of ALS-iPSC-MNs.

Dataset Information

Bhalla2002_MAPK-bistability-fig1c

Publications

MAP kinase phosphatase as a locus of flexibility in a mitogen-activated protein kinase signaling network.

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