 An Experimental and Computational Study of the Effect of ActA Polarity on the Speed of Listeria monocytogenes Actin-based MotilitySusanne M Rafelski, Jonathan B Alberts and Garrett M Odell PLOS Computational Biology, 2009, vol. 5, issue 7, 1-14 Abstract: Listeria monocytogenes is a pathogenic bacterium that moves within infected cells and spreads directly between cells by harnessing the cell's dendritic actin machinery. This motility is dependent on expression of a single bacterial surface protein, ActA, a constitutively active Arp2,3 activator, and has been widely studied as a biochemical and biophysical model system for actin-based motility. Dendritic actin network dynamics are important for cell processes including eukaryotic cell motility, cytokinesis, and endocytosis. Here we experimentally altered the degree of ActA polarity on a population of bacteria and made use of an ActA-RFP fusion to determine the relationship between ActA distribution and speed of bacterial motion. We found a positive linear relationship for both ActA intensity and polarity with speed. We explored the underlying mechanisms of this dependence with two distinctly different quantitative models: a detailed agent-based model in which each actin filament and branched network is explicitly simulated, and a three-state continuum model that describes a simplified relationship between bacterial speed and barbed-end actin populations. In silico bacterial motility required a cooperative restraining mechanism to reconstitute our observed speed-polarity relationship, suggesting that kinetic friction between actin filaments and the bacterial surface, a restraining force previously neglected in motility models, is important in determining the effect of ActA polarity on bacterial motility. The continuum model was less restrictive, requiring only a filament number-dependent restraining mechanism to reproduce our experimental observations. However, seemingly rational assumptions in the continuum model, e.g. an average propulsive force per filament, were invalidated by further analysis with the agent-based model. We found that the average contribution to motility from side-interacting filaments was actually a function of the ActA distribution. This ActA-dependence would be difficult to intuit but emerges naturally from the nanoscale interactions in the agent-based representation.Author Summary: Cells tightly regulate the branched actin networks involved in motility, division, and other important cellular functions through localized activation of the Arp2,3 protein, which nucleates new actin filaments off the sides of existing ones. The pathogenic bacterium, Listeria monocytogenes, expresses its own Arp2,3 activator, ActA, in a polarized fashion and can thus nucleate dynamic actin networks at its surface to generate forces to move through the cytoplasm. This bacterium has thus served as a simplified system for experimental and modeling studies of actin-based motility. We use this bacterial system to quantify the relationship between ActA polarity and bacterial speed of motion by experimentally manipulating this polarity and analyzing the resultant ActA distributions and bacterial trajectories. Like many cellular behaviors, L. monocytogenes motility emerges from a complex set of biochemical and force-based interactions. We therefore probe this polarity-speed relationship with a detailed agent-based simulation which encodes the predominant biochemical reactions and whose agents (actin filaments, ActA proteins, and the bacterium) exchange forces. We contrast conclusions from this agent-based model with those from a simpler mathematical model. From these studies we assert the importance of a heretofore neglected force in this system – friction between actin filaments and the bacterial surface. Date: 2009 Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:plo:pcbi00:1000434 DOI: 10.1371/journal.pcbi.1000434 Access Statistics for this article More articles in PLOS Computational Biology from Public Library of Science |
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