Archive for the ‘Timothy Newman’s Lab’ Category

Tim Newman’s Publications

Monday, April 12th, 2010

Correlating Cell Behavior with Tissue Topology in Embryonic Epithelia. PLoS One. April 2011
Correlating cell behavior with tissue topology in embryonic epithelia

Modeling Cell Rheology with the Subcellular Element Model
Modeling cell rheology with the Subcellular Element Model

Abstract:
Recently, the Subcellular Element Model (SEM) has been introduced, primarily to compute the dynamics of large numbers of three-dimensional deformable cells in multicellular systems. Within this model framework, each cell is represented by a collection of elastically coupled elements, interacting with one another via short-range potentials, and dynamically updated using over-damped Langevin dynamics. The SEM can also be used to represent a single cell in more detail, by using a larger number of subcellular elements exclusively identified with that cell. We have tested whether, in this context, the SEM yields viscoelastic properties consistent with those measured on single living cells. Employing virtual methods of bulk rheology and microrheology we find that the SEM successfully captures many cellular rheological properties at intermediate time scales and moderate strains, including weak power law rheology. In its simplest guise, the SEM cannot describe long-time/large-strain cell responses. Capturing these cellular properties requires extensions of the SEM which incorporate active cytoskeletal rearrangement. Such extensions will be the subject of a future publication.

Modeling cell rheology with the Subcellular Element Model (pdf)

Modeling Multicellular Systems using Sub-Cellular Elements (pdf)

Monday, April 12th, 2010

Author: T. J. Newman

Abstract:
We introduce a model for describing the dynamics of large numbers of interacting cells. The fundamental dynamical variables in the model are sub-cellular elements, which interact with each other through phenomenological intra- and intercellular potentials. Advantages of the model include: i) adaptive cell-shape dynamics, ii) flexible accommodation of additional intracellular biology, and iii) the absence of an underlying grid. We present here a detailed description of the model, and use successive mean-¯eld approximations to connect it to more coarse-grained approaches, such as discrete cell-based algorithms and coupled partial differential equations. We also discuss efficient algorithms for encoding the model, and give an example of a simulation of an epithelial sheet. Given the biological flexibility of the model, we propose that it can be used effectively for modeling a range of multicellular processes, such as tumor dynamics and embryogenesis.

Modeling Multicellular systems using sub-cellular elements (pdf)