Physics
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Item Individual and collective dynamics of chemotaxing cells(2011) McCann, Colin Patrick; Losert, Wolfgang; Parent, Carole A; Physics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The study of the dynamics of interacting self-propelled entities is a growing area of physics research. This dissertation investigates individual and collective motion of the eukaryote Dictyostelium discoideum, a system amenable to signal manipulation, mathematical modeling, and quantitative analysis. In the wild, Dictyostelium survive adverse conditions through collective behaviors caused by secreting and responding to chemical signals. We explore this collective behavior on size scales ranging from subcellular biochemistry up to dynamics of thousands of communicating cells. To study how individual cells respond to multiple signals, we perform stability analysis on a previously-developed computational model of signal sensing. Polarized cells are linearly stable to perturbations, with a least stable region at about 60 degrees off the polarization axis. This finding is confirmed through simulations of the model response to additional chemical signals. The off-axis sensitivity suggests a mechanism for previously observed zig-zag motion of real cells randomly migrating or chemotaxing in a linear gradient. Moving up in scale, we experimentally investigate the rules of cell motion and interaction in the context of thousands of cells. Migrating Dictyostelium discoideum cells communicate by sensing and secreting directional signals, and we find that this process leads to an initial signal having an increased spatial range of an order of magnitude. While this process steers cells, measurements indicate that intrinsic cell motility remains unaffected. Additionally, migration of individual cells is unaffected by changing cell-surface adhesion energy by nine orders of magnitude, showing that individual motility is a robust process. In contrast, we find that collective dynamics depend on cell-surface adhesion, with greater adhesion causing cells to form smaller collective structures. Overall, this work suggests that the underlying migration ability of individual Dictyostelium cells operates largely independent of environmental conditions. Our gradient-sensing model shows that polarized cells are stable to small perturbations, and our experiments demonstrate that the motility apparatus is robust to considerable changes in cell-surface adhesion or complex signaling fields. However, we find that environmental factors can dramatically affect the collective behavior of cells, emphasizing that the laws governing cell-cell interaction can change migration patterns without altering intrinsic cell motility.Item Distinguishing Modes of Eukaryotic Gradient Sensing(2005-08-25) Skupsky, Ron; Losert, Wolfgang; Nossal, Ralph J; Physics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The behaviors of biological systems depend on complex networks of interactions between large numbers of components. The network of interactions that allows biological cells to detect and respond to external gradients of small molecules with directed movement is an example where many of the relevant components have been identified. This behavior, called chemotaxis, is essential for biological functions ranging from immune response in higher animals to the food gathering and social behavior of ameboid cells. Gradient sensing is the component of this behavior whereby cells transduce the spatio-temporal information in the external stimulus into an internal distribution of molecules that mediate the mechanical and morphological changes necessary for movement. Signaling by membrane lipids, in particular 3' phosphoinositides (3'PIs), is thought to play an important role in this transduction. Key features of the network of interactions that regulates the dynamics of these lipids are coupled positive feedbacks that might lead to response bifurcations and the involvement of molecules that translocate from the cytosol to the membrane, coupling responses at distant point on the cell surface. Both are likely to play important roles in amplifying cellular responses and shaping their qualitative features. To better understand the network of interactions that regulates 3'PI dynamics in gradient sensing, we develop a computational model at an intermediate level of detail. To investigate how the qualitative features of cellular response depend on the structure of this network, we define four variants of our model by adjusting the effectiveness of the included feedback loops and the importance of translocating molecules in response amplification. Simulations of characteristic responses suggest that differences between our model variants are most evident at transitions between efficient gradient detection and failure. Based on these results, we propose criteria to distinguish between possible modes of gradient sensing in real cells, where many biochemical parameters may be unknown. We also identify constraints on parameters required for efficient gradient detection. Finally, our analysis suggests how a cell might transition between responsiveness and non-responsiveness, and between different modes of gradient sensing, by adjusting its biochemical parameters.