Investigation of stem cell population heterogeneity using single cell analysis and computational modeling.
Rahmati Rostami, Mahboubeh.
2017
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Abstract:
The major characteristic of embryonic stem cells (ESCs) is their extensive self-renewal
ability in culture and their potential to differentiate. ESCs are capable of
differentiating into all cell types of the body as the mesoderm, ectoderm, and endoderm
lineage. However, stem cell populations display cell-to-cell variations in multiple
attributes such as protein and gene expressions, ... read moreself-renewal and proclivity for
differentiation. Transcription factors (TFs) are important in stem cell fate decisions
and TFs themselves can also serve as biomarkers of stem cell state. Cell identity is
controlled by the action of transcription factors (TFs) that recognize and bind specific
sequences in the genome and regulate gene expression. NANOG, a critical transcription
factor among Sox2 and Oct4 which are responsible for self-renewal in embryonic stem
cell, is not homogeneously expressed in cultured stem cell. In this study first, I
validated the mathematical modeling approach of solving the inverse problem to predict
the single-cell growth, division rates and the partition probability density function
for the size of human embryonic stem cells (hESCs) with experimental data acquired by
flow cytometry. There was an excellent agreement between the original analytical
expressions defined for physiological state functions and results from the inverse
problem approach. Next, this model was applied to predict gene expression behavior based
on single cell analysis during cell growth and division in heterogeneous population of
stem cells under self renewal and directed differentiation condition. This model
captures population heterogeneity and may facilitate in depth understanding of this
complex system while enabling systematic formulation of culture strategies to improve
stem cell growth and productivity.
Thesis (Ph.D.)--Tufts University, 2017.
Submitted to the Dept. of Chemical and Biological Engineering.
Advisor: Emmanuel (Manolis) Tzanakakis.
Committee: Panagiotis Kevrekidis, and Bree Aldridge.
Keyword: Chemical engineering.read less - ID:
- f1881z45r
- Component ID:
- tufts:22451
- To Cite:
- TARC Citation Guide EndNote
