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Resolving crosstalk between signaling pathways using mathematical modeling and time-resolved single cell data

Konrath, Fabian ; Loewer, Alexander ; Wolf, Jana (2023)
Resolving crosstalk between signaling pathways using mathematical modeling and time-resolved single cell data.
In: Methods in molecular biology (Clifton, N.J.), 2634
doi: 10.1007/978-1-0716-3008-2_12
Artikel, Bibliographie

Kurzbeschreibung (Abstract)

Crosstalk between signaling pathways can modulate the cellular response to stimuli and is therefore an important part of signal transduction. For a comprehensive understanding of cellular responses, identifying points of interaction between the underlying molecular networks is essential. Here, we present an approach that allows the systematic prediction of such interactions by perturbing one pathway and quantifying the concomitant alterations in the response of a second pathway. As the observed alterations contain information about the crosstalk, we use an ordinary differential equation-based model to extract this information by linking altered dynamics to individual processes. Consequently, we can predict the interaction points between two pathways. As an example, we employed our approach to investigate the crosstalk between the NF-κB and p53 signaling pathway. We monitored the response of p53 to genotoxic stress using time-resolved single cell data and perturbed NF-κB signaling by inhibiting the kinase IKK2. Employing a subpopulation-based modeling approach enabled us to identify multiple interaction points that are simultaneously affected by perturbation of NF-κB signaling. Hence, our approach can be used to analyze crosstalk between two signaling pathways in a systematic manner.

Typ des Eintrags: Artikel
Erschienen: 2023
Autor(en): Konrath, Fabian ; Loewer, Alexander ; Wolf, Jana
Art des Eintrags: Bibliographie
Titel: Resolving crosstalk between signaling pathways using mathematical modeling and time-resolved single cell data
Sprache: Englisch
Publikationsjahr: 2023
Titel der Zeitschrift, Zeitung oder Schriftenreihe: Methods in molecular biology (Clifton, N.J.)
Jahrgang/Volume einer Zeitschrift: 2634
DOI: 10.1007/978-1-0716-3008-2_12
Kurzbeschreibung (Abstract):

Crosstalk between signaling pathways can modulate the cellular response to stimuli and is therefore an important part of signal transduction. For a comprehensive understanding of cellular responses, identifying points of interaction between the underlying molecular networks is essential. Here, we present an approach that allows the systematic prediction of such interactions by perturbing one pathway and quantifying the concomitant alterations in the response of a second pathway. As the observed alterations contain information about the crosstalk, we use an ordinary differential equation-based model to extract this information by linking altered dynamics to individual processes. Consequently, we can predict the interaction points between two pathways. As an example, we employed our approach to investigate the crosstalk between the NF-κB and p53 signaling pathway. We monitored the response of p53 to genotoxic stress using time-resolved single cell data and perturbed NF-κB signaling by inhibiting the kinase IKK2. Employing a subpopulation-based modeling approach enabled us to identify multiple interaction points that are simultaneously affected by perturbation of NF-κB signaling. Hence, our approach can be used to analyze crosstalk between two signaling pathways in a systematic manner.

ID-Nummer: pmid:37074583
Fachbereich(e)/-gebiet(e): 10 Fachbereich Biologie
10 Fachbereich Biologie > Systems Biology of the Stress Response
Hinterlegungsdatum: 24 Apr 2023 11:19
Letzte Änderung: 24 Apr 2023 11:19
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