bioRxivBioengineeringPreprint
An agent-based model suggests how senescent cell behavior and matrix mechanics drive pulmonary fibrosis in aged mice
Mackenzie L. SkeltoniD, Julie Leonard‐DukeiD, Leilani R. Astrab, Joshua A. Goedert, Riley T. HannaniD, SHAYN M. PEIRCEiD, Jeffrey M. SturekiD, Steven R. CaliariiD
Abstract
Idiopathic pulmonary fibrosis (IPF) is a progressive and ultimately fatal disease of aging, driven by dysregulated fibroblast activation and accompanied by collagen accumulation in the lung interstitium, resulting in tissue stiffening. While the accumulation of senescent cells has been increasingly implicated in IPF pathogenesis, understanding the reciprocal dynamics of senescent fibroblast levels and evolving tissue mechanics is difficult to achieve with experimental approaches alone. To address this limitation, we developed an agent-based model (ABM) of fibroblast activation in the lung that couples cell behavior to the dynamic mechanical changes accompanying fibrosis. This model was parameterized entirely from experimental data in young mice to enable robust validation and then adapted to fit aged mouse biology for additional validation. Both young and aged models accurately reflected changes in collagen accumulation and stiffness burden of experimental systems. We then incorporated senescent cell behavior into the aged model to investigate how senescent cell burden influences fibrosis progression and how cell-cell interactions drive senescent cell accumulation. These simulations identified a unique role for juxtacrine-mediated contact between non-senescent and senescent fibroblasts in expanding the total senescent cell burden. Our ABM also revealed that the timing of immune-mediated senescent cell clearance critically regulates fibrotic outcomes. Together, this ABM provides useful insights into how the interrelated dynamics of tissue mechanics and senescent fibroblasts drive fibrosis progression.
- organism: mouse
- research focus: cell signaling & trafficking
- research focus: development & morphogenesis
- research focus: differential expression
- research focus: cell-cell communication
- approach: deep learning
- approach: statistical model
- Citations
- 0
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