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Autor(en): Rex, Julia
Albrecht, Ute
Ehlting, Christian
Thomas, Maria
Zanger, Ulrich M.
Sawodny, Oliver
Häussinger, Dieter
Ederer, Michael
Feuer, Ronny
Bode, Johannes G.
Titel: Model-based characterization of inflammatory gene expression patterns of activated macrophages
Erscheinungsdatum: 2016
Dokumentart: Zeitschriftenartikel
Seiten: 28
Erschienen in: PLOS computational biology 12 (2016), No. 7, e1005018
URI: http://nbn-resolving.de/urn:nbn:de:bsz:93-opus-ds-104237
http://elib.uni-stuttgart.de/handle/11682/10423
http://dx.doi.org/10.18419/opus-10406
ISSN: 1553-734X
1553-7358
Zusammenfassung: Macrophages are cells with remarkable plasticity. They integrate signals from their microenvironment leading to context-dependent polarization into classically (M1) or alternatively (M2) activated macrophages, representing two extremes of a broad spectrum of divergent phenotypes. Thereby, macrophages deliver protective and pro-regenerative signals towards injured tissue but, depending on the eliciting damage, may also be responsible for the generation and aggravation of tissue injury. Although incompletely understood, there is emerging evidence that macrophage polarization is critical for these antagonistic roles. To identify activation-specific expression patterns of chemokines and cytokines that may confer these distinct effects a systems biology approach was applied. A comprehensive literature-based Boolean model was developed to describe the M1 (LPS-activated) and M2 (IL-4/13-activated) polarization types. The model was validated using high-throughput transcript expression data from murine bone marrow derived macrophages. By dynamic modeling of gene expression, the chronology of pathway activation and autocrine signaling was estimated. Our results provide a deepened understanding of the physiological balance leading to M1/M2 activation, indicating the relevance of co-regulatory signals at the level of Akt1 or Akt2 that may be important for directing macrophage polarization.
Enthalten in den Sammlungen:07 Fakultät Konstruktions-, Produktions- und Fahrzeugtechnik

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