Quantitative dynamic modeling of transcriptional networks of embryonic stem cells using integrated framework of Pareto optimality and energy balance

Embryonic Stem Cells (ESCs) are pluripotent and thus are considered the "cell type of choice". ESCs exhibit several phenotypic traits (e.g., proliferation, differentiation, apoptosis, necrosis, etc.) and when differentiated into a particular lineage they can perform an array of functions (e.g., protein secretion, detoxification, energy production). Typically, these cellular objectives compete against each other because of thermodynamic, stoichiometric and mass balance constraints. Analysis of transcriptional regulatory networks and metabolic networks in ESCs thus requires both a nonequilibrium thermodynamic and mass balance framework for designing and understanding complex ESC network approach as well as an optimality approach which can take cellular objectives into account simultaneously. The primary goal of this thesis was to develop an integrated energy and mass balance-based multi objective framework for a transcriptional regulatory network model for ESCs. The secondary goal was to utilize the developed framework for large-scale metabolic flux profiling of hepatic and ESC metabolic networks. Towards the first aim we first developed a complete dynamic pluripotent network model for ESCs which integrates several different master regulators of pluripotency such as transcription factors Oct4, Sox2, Nanog, Klf4, Nacl, Rexl, Daxl, cMyc, and Zfp281, and obtained the dynamic connectivity matrix between various pluripotency related gene promoters and transcription factors. The developed model fully describes the self-renewal state of embryonic stem cells.

Department dc:contributor.department

Harvard University--MIT Division of Health Sciences and Technology.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2009

Author dc:creator

• Avila, Marco A., Ph. D. Massachusetts Institute of Technology

Advisor dc:contributor.advisor

• Martin L. Yarmush.

• Harvard University--MIT Division of Health Sciences and Technology.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about 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/1721.1/55149

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/55149