Abstract
Polarized actin cables in S. cerevisiae are linear bundles of crosslinked actin filaments that are assembled by two formins, Bnr1 (localized to the bud neck), and Bni1 (localized to the bud tip). Actin is polymerized at these two sites, which results in cables extending along the cell cortex toward the back of the mother cell. These cables serve as polarized tracks for myosin-based transport of secretory vesicles and other cargo, from the mother cell to the growing daughter cell. Until recently, descriptions of actin cable morphology and architecture have largely been qualitative or descriptive in nature. Here, we introduce a new quantitative method that enables more precise characterization of actin cable length. This technological advance generates quantitative datasets that can be used to determine the contributions of different actin regulatory proteins to the maintenance of cable architecture, and to assess how different pharmacological agents affect cable arrays. Additionally, these datasets can be used to test theoretical models, and be compared to results from computational simulations of actin assembly. Graphical abstract: Illustration of actin cable length and morphology analysis. (A) Representative maximum intensity projection image of S. cerevisiae fixed and stained with fluorescently-conjugated phalloidin to label F-actin (displayed in color), and fluorescently-conjugated Concanavalin A to label the cell wall (displayed in grey scale). Lengths of actin cables traced from the bud neck to their ends are indicated (dashed lines). (B) Inverted grey scale image of F-actin labelled with fluorescently-conjugated phalloidin and the cell wall traced in black. The length (purple) and end-to-end distance (green) of a single actin cable is indicated. Scale bar, 2 µm. (C-E) Actin cable length (C), end-to-end distance (D), and tortuosity (E) from hypothetical datasets, where each data point represents an individual cable and larger symbols represent the mean from each hypothetical experiment. Error bars, 95% confidence intervals.