@article{AmselemThevesBaeetal.2012,
  author    = {Amselem, Gabriel and Theves, Matthias and Bae, Albert J. and Bodenschatz, Eberhard and Beta, Carsten},
  title     = {A stochastic description of dictyostelium chemotaxis},
  series = {PLoS one},
  volume    = {7},
  journal   = {PLoS one},
  number    = {5},
  publisher = {PLoS},
  address   = {San Fransisco},
  issn      = {1932-6203},
  doi       = {10.1371/journal.pone.0037213},
  pages     = {11},
  year      = {2012},
  abstract  = {Chemotaxis, the directed motion of a cell toward a chemical source, plays a key role in many essential biological processes. Here, we derive a statistical model that quantitatively describes the chemotactic motion of eukaryotic cells in a chemical gradient. Our model is based on observations of the chemotactic motion of the social ameba Dictyostelium discoideum, a model organism for eukaryotic chemotaxis. A large number of cell trajectories in stationary, linear chemoattractant gradients is measured, using microfluidic tools in combination with automated cell tracking. We describe the directional motion as the interplay between deterministic and stochastic contributions based on a Langevin equation. The functional form of this equation is directly extracted from experimental data by angle-resolved conditional averages. It contains quadratic deterministic damping and multiplicative noise. In the presence of an external gradient, the deterministic part shows a clear angular dependence that takes the form of a force pointing in gradient direction. With increasing gradient steepness, this force passes through a maximum that coincides with maxima in both speed and directionality of the cells. The stochastic part, on the other hand, does not depend on the orientation of the directional cue and remains independent of the gradient magnitude. Numerical simulations of our probabilistic model yield quantitative agreement with the experimental distribution functions. Thus our model captures well the dynamics of chemotactic cells and can serve to quantify differences and similarities of different chemotactic eukaryotes. Finally, on the basis of our model, we can characterize the heterogeneity within a population of chemotactic cells.},
  language  = {en}
}
@article{AmselemThevesBaeetal.2012,
  author    = {Amselem, Gabriel and Theves, Matthias and Bae, Albert J. and Beta, Carsten and Bodenschatz, Eberhard},
  title     = {Control parameter description of eukaryotic chemotaxis},
  series = {Physical review letters},
  volume    = {109},
  journal   = {Physical review letters},
  number    = {10},
  publisher = {American Physical Society},
  address   = {College Park},
  issn      = {0031-9007},
  doi       = {10.1103/PhysRevLett.109.108103},
  pages     = {5},
  year      = {2012},
  abstract  = {The chemotaxis of eukaryotic cells depends both on the average concentration of the chemoattractant and on the steepness of its gradient. For the social amoeba Dictyostelium discoideum, we test quantitatively the prediction by Ueda and Shibata [Biophys. J. 93, 11 (2007)] that the efficacy of chemotaxis depends on a single control parameter only, namely, the signal-to-noise ratio (SNR), determined by the stochastic fluctuations of (i) the binding of the chemoattractant molecule to the transmembrane receptor and (ii) the intracellular activation of the effector of the signaling cascade. For SNR less than or similar to 1, the theory captures the experimental findings well, while for larger SNR noise sources further downstream in the signaling pathway need to be taken into account.},
  language  = {en}
}