Dataset Information

Konrath2020_p53_signaling_model

ABSTRACT: The ODE model is based on Batchelor et al., Mol. Syst. Biol. 7 (2011) and was extended by introducing explicit descriptions of the transcription and translation processes of Mdm2 mRNA and Wip1 mRNA. To capture the heterogeneous single cell dynamics of p53 with an ODE model, we clustered the time courses measured by single cell time lapse microscopy into ten subpopulations and created subpopulation models (labelled "a" to "j"). By fitting the subpopulation models to the clustered time course data, we developed to our knowledge the first quantitative p53 model reproducing heterogeneous dynamics of p53.

SUBMITTER: Fabian Konrath

PROVIDER: MODEL2004300002 | BioModels | 2020-05-07

REPOSITORIES: BioModels

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Publications

A systematic approach to decipher crosstalk in the p53 signaling pathway using single cell dynamics.

Konrath Fabian F Mittermeier Anna A Cristiano Elena E Wolf Jana J Loewer Alexander A

PLoS computational biology 20200626 6

The transcription factors NF-κB and p53 are key regulators in the genotoxic stress response and are critical for tumor development. Although there is ample evidence for interactions between both networks, a comprehensive understanding of the crosstalk is lacking. Here, we developed a systematic approach to identify potential interactions between the pathways. We perturbed NF-κB signaling by inhibiting IKK2, a critical regulator of NF-κB activity, and monitored the altered response of p53 to geno ...[more]

PMID: 32589666

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Project description:This a model from the article: Transient heterogeneity in extracellular protease production by Bacillus subtilis. Veening JW, Igoshin OA, Eijlander RT, Nijland R, Hamoen LW, Kuipers OP Mol. Syst. Biol. 2008 ; Volume: 4 : 184 18414485, Abstract: The most sophisticated survival strategy Bacillus subtilis employs is the differentiation of a subpopulation of cells into highly resistant endospores. To examine the expression patterns of non-sporulating cells within heterogeneous populations, we used buoyant density centrifugation to separate vegetative cells from endospore-containing cells and compared the transcriptome profiles of both subpopulations. This demonstrated the differential expression of various regulons. Subsequent single-cell analyses using promoter-gfp fusions confirmed our microarray results. Surprisingly, only part of the vegetative subpopulation highly and transiently expresses genes encoding the extracellular proteases Bpr (bacillopeptidase) and AprE (subtilisin), both of which are under the control of the DegU transcriptional regulator. As these proteases and their degradation products freely diffuse within the liquid growth medium, all cells within the clonal population are expected to benefit from their activities, suggesting that B. subtilis employs cooperative or even altruistic behavior. To unravel the mechanisms by which protease production heterogeneity within the non-sporulating subpopulation is established, we performed a series of genetic experiments combined with mathematical modeling. Simulations with our model yield valuable insights into how population heterogeneity may arise by the relatively long and variable response times within the DegU autoactivating pathway. This model originates from BioModels Database: A Database of Annotated Published Models. It is copyright (c) 2005-2009 The BioModels Team.For more information see the terms of use.To cite BioModels Database, please use Le Novère N., Bornstein B., Broicher A., Courtot M., Donizelli M., Dharuri H., Li L., Sauro H., Schilstra M., Shapiro B., Snoep J.L., Hucka M. (2006) BioModels Database: A Free, Centralized Database of Curated, Published, Quantitative Kinetic Models of Biochemical and Cellular Systems Nucleic Acids Res., 34: D689-D691.

Dataset Information

Konrath2020_p53_signaling_model

Publications

A systematic approach to decipher crosstalk in the p53 signaling pathway using single cell dynamics.

Similar Datasets

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