Biology Reference
In-Depth Information
5
CHAPTER
Theoretical Considerations
for Reprogramming
Multicellular Systems
Joseph Xu Zhou and Sui Huang
Institute for Systems Biology, Seattle, WA, USA
INTRODUCTION
The physicist Richard Feynman once said:
'
'
What I cannot create, I do not understand.
After more than 60 years of advances in molecular biology, it has through molecular
dissection provided a solid knowledge base of the central elementary molecular processes of
life. Now synthetic biology launches a new era in which we manipulate systems to change
their fundamental properties. This goes beyond the singular perturbations used to probe a
system feature in traditional
81
'
analytical
'
biology. In the most extreme scenario synthetic
biology reaches into the realm of
livable systems de novo. The purpose is two-fold:
to better understand biological systems or, even going beyond Feynman
'
making
'
s dictum, to
harness it for a practical purpose. It is clear that our experience from engineering in
man-made technology, such as designing cars or computers, offers ample methodology
for synthetic biology. But in doing so we also need to be aware of fundamental differences
between biological and artificial systems, notably in view of the question of how the
encoded blueprints of programs (software, DNA) are translated into system behaviors.
Specifically, here we confront the question of how do genes, which are arranged as a linear
code in the genomic DNA and interact with each other in a gene regulatory network, give
rise to complex behaviors poised at the optimum between stability and flexibility?
'
One essential feature of complex multicellular organisms is their development (coming
into being) from a single cell (fertilized egg) into a multicellular organism comprised not
only of a large number of cells, but of discretely distinct types of cells that through ordered
arrangement in space form tissues and organs.
1
Development of the cell type repertoire
of
1000s or so cell types found in the human body follows a hierarchical scheme of cellular
differentiation characterized by a binary branching genealogy. Since cell types represent
discrete, stable entities, it has long been recognized that they correspond to attractor states of
molecular dynamic networks that govern the differentiation of the various cell lineages.
2
5
.
Early conceptualization of developmental cell behavior characterized by the natural
discontinuity of phenotype, the discrete binary decisions of less mature multipotent cells
into two lineages, and the rare but observed switching between the discrete phenotypes used
a landscape picture with valleys that correspond to the attractor states.
6
This
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epigenetic
