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Biology subjects

Roy Wollman

Publications and source records attributed to Roy Wollman.

2 recordsLinked to original sources

Wound induced Ca2+ wave propagates through a simple Release and Diffusion mechanism

Damage associated molecular patterns (DAMPs) are critical mediators of information concerning tissue damage from damaged cells to neighboring healthy cells. Adenosine triphosphate (ATP) acts as an effective DAMP when released into extracellular space from damaged cells. Extracellular ATP receptors monitor tissue damage and activate a Ca2+ wave in the surrounding healthy cells. How the Ca2+ wave propagates through cells following a wound is unclear. Ca2+ wave activation can occur extracellularly via external receptors or intracellularly through GAP junctions. Three potential mechanisms to propagate the Ca2+ wave are: Source and Sink, Amplifying Wave, and Release and Diffusion. Both Source and Sink and Amplifying Wave regulate ATP levels using hydrolysis or secretion, respectively, while Release and Diffusion relies on dilution. Here we systematically test these hypotheses using a microfluidics assay to mechanically wound an epithelial monolayer in combination with direct manipulation of ATP hydrolysis and release. We show that a Release and Diffusion model sufficiently explains Ca2+ wave propagation following an epithelial wound. A Release and Diffusion model combines the benefits of fast activation at length-scales of ~1-5 cell diameters with a self-limiting response to prevent unnecessary inflammatory responses harmful to the organism.

Cell Biology

Distinct Cellular States Determine Calcium Signaling Response

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 ATP as a model for investigating the structure of heterogeneity within a population of cells and analyze whether distinct cellular response states co-exist. 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. 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.

Systems Biology