Yao2016_Calcium_Signaling

Yao2016_Calcium_Signaling

This model is described in the article:

Distinct cellular states
determine calcium signaling response

Jason Yao, Anna Pilko, Roy
Wollman
Molecular Systems Biology
Abstract:

The heterogeneity in mammalian cells signaling response is
largely a result of preexisting cell to cell variability. It is
unknown whether cell to cell variability rises from biochemical
stochastic fluctuations or distinct cellular states. Here, we
utilize calcium response to adenosine trisphosphate as a model
for investigating the structure of heterogeneity within a
population of cells and analyze whether distinct cellular
response states coexist. We use a functional definition of
cellular state that is based on a mechanistic dynamical systems
model of calcium signaling. Using Bayesian parameter inference,
we obtain high confidence parameter value distributions for
several hundred cells, each fitted individually. Clustering the
inferred parameter distributions revealed three major distinct
cellular states within the population. The existence of
distinct cellular states raises the possibility that the
observed variability in response is a result of structured
heterogeneity between cells. The inferred parameter
distribution predicts, and experiments confirm that variability
in IP3R response explains the majority of calcium
heterogeneity. Our work shows how mechanistic models and single
cell parameter fitting can uncover hidden population structure
and demonstrate the need for parameter inference at the single
cell level.

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