Systems analysis of cytokine mediated communication and signaling

Immune cells communicate with each other to mount an effective response to pathogens or maintain homeostasis. Communication and activation of the immune cell network can occur in part through secretion of or response to cytokines. Here, we couple experimental approaches with computational analysis to identify how cytokine communication impacts immune-rich cellular environments. The first part of this work focuses on on understanding intracellular signaling in response to TNF[alpha] -induced apoptosis in vivo. By applying a quantitative mechanistic modeling framework to phosphoproteomic data of inflammation in the context of a variety of genetic Ras mutations, we identify clear differences between signaling from N-Ras and K-Ras isoforms, and identify isoform specific contributions to intestinal apoptosis. The next part of this work focuses on understanding cytokine secretion from primary human immune cells especially as mediated by cell-cell communication. By coculturing pure immune cell types at known mixture ratios, and measuring multiplexed secretion, we gained insight into the regulation of individual cytokines in these mixtures as compared to expected values from corresponding measurements of monocultures. We find that monocultures are less predictive of cytokine secretion from physiological cell populations than controlled cocultures. In this work, we also elucidated a number of positive and negative synergies in communication between monocytes and CD4+ T cells. A particularly interesting result was finding a synergy between INF[gamma] and TNF[alpha] for production of CXCR3 chemokines. Overall, this combination of modeling and experimental work has made contributions to understanding regulation of the cytokine environment in multicellular environments, as well as contributions of specific cytokines of interest to cellular and tissue responses.

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Biological Engineering.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2016

Author dc:creator

• Schrier, Sarah B

Advisor dc:contributor.advisor

• Douglas A. Lauffenburger.

• Biological Engineering.

Statement dc:rights

• MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/104228

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/104228