möglich sobald bei der ZB eingereicht worden ist.
Information theoretic concepts to unravel cell–cell communication.
In: Lecture Notes in Bioengineering. 2018. 115-136
Cell–Cell communication is a complex process regulating the homeostasis and cellular decisions in a multicellular organism. The correction information flow is a necessity for a healthy cellular microenvironment and proper response to external stimuli, such as inflammation and wound healing. Altered cell–cell communication is a hallmark of aging and disease. In particular, tumor–stroma interactions have attracted increased attention in recent years as putative therapeutic targets of intervention. Most studies so far have investigated individual cytokines or analyzed steady-state feedback-entangled cell–cell communication. Here, we study the onset of cell–cell communication by a defined double paracrine experimental setup of skin cells. We build in the experimental model systems developed in the first funding period and use conditioned supernatant stimulation to record whole transcriptome response time series as well as changes in the whole secretome to correlate cytokine patterns with phenotype responses. Moreover, we model the changes in gene expression and cytokine secretion through communication theoretic approaches through independent component analysis and Gaussian processes. The information from these general models is used for mechanistic, whole cell modeling using gene regulatory networks and Boolean models that comprise long-term dynamics of the cellular responses as well as multiple time scales of protein signaling, gene expression, and auto- and paracrine feedbacks. Such approaches will elucidate bi-stability of cellular homeostasis locking the cells into inflammatory or migratory states. Lastly, we will test the generic regulatory schemes by comparison of our currently investigated skin communication model with a tumor–stroma interaction system of human melanoma and fibroblast cells.
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Publikationstyp Artikel: Sammelbandbeitrag/Buchkapitel
ISSN (print) / ISBN 2195-271X
Bandtitel Lecture Notes in Bioengineering
Quellenangaben Seiten: 115-136
Institut(e) Institute of Computational Biology (ICB)