info:eu-repo/semantics/doctoralThesis
Spatial biology of Ising-like synthetic genetic networks
Biología espacial de redes genéticas sintéticas de tipo Ising
Autor
Simpson Alfaro, Kevin Matías
Institución
Resumen
Understanding how spatially-correlated cellular states emerge from the
local interaction of gene network dynamics is a fundamental challenge in biology.
Short and long-range correlations and anti-correlations in gene expression can be
found in spatially-distributed cellular systems such as eukaryotic tissues and microbial
communities. However, the study of gene spatial correlations emerging
from cell-cell coupling in natural systems is di cult since complex interactions
are the norm. An alternative is to generate synthetic genetic networks (SGNs)
that capture essential features of cell-cell interactions and reveal their in
uence
in the emergence of cellular state patterns. Here, we combine synthetic biology,
theoretical modelling and computational simulations to study the emergence of
macroscopic gene correlations and address possible mechanisms for multi-scale
self-organization of gene states in bacteria. We applied the Ising model as a
theoretical framework to study the self-organization of spatially-correlated gene
expression in two-state SGNs that are coupled by short-range chemical signals in
E. coli. Inspired by the Ising model, we name these SGNs ferromagnetic or antiferromagnetic
depending if they stabilize the same or the opposite state in neighboring
cells. As predicted by our simulations that combine the two-dimensional
Ising model with the Contact Process lattice model of cell population dynamics,
these SGNs allowed the self-organization of spatial patterns of short and long-scale
cellular state domains in bacterial colonies, where the size of the domains depends
on the type of interaction, ferromagnetic or anti-ferromagnetic. The emergence of
spatial correlations showed to be independent of the cell shape and the underpinning
mechanical forces. The similarity found between ferromagnetic colonies and
simulated ferromagnetic populations suggest these colonies are near the critical
point of phase transition, implying that far regions in the colony are correlated.
This work provides resources and a general scope theoretical framework that explain
how both short and long-range correlations (and anti-correlations) are able
to self-organize from locally-interacting networks. These results on multi-scale organization
of gene network states shed light onto the study of pattern formation
in developmental biology and microbial ecology, as well as provide a theoretical
framework for the engineering of spatially-arranged cell systems. Por publicar