Nonprocessive motor dynamics at the microtubule membrane tube interface

Abstract

Key cellular processes such as cell division, membrane compartmentalization, and intracellular transport rely on motor proteins. Motors have been studied in detail on the single motor level such that information on their step size, stall force, average run length, and processivity are well known. However, in vivo, motors often work together, so that the question of their collective coordination has raised great interest. Here, we specifically attach motors to giant vesicles and examine collective motor dynamics during membrane tube formation. Image correlation spectroscopy reveals directed motion as processive motors walk at typical speeds (< or = 500 nm/s) along an underlying microtubule and accumulate at the tip of the growing membrane tube. In contrast, nonprocessive motors exhibit purely diffusive behavior, decorating the entire length of a microtubule lattice with diffusion constants at least 1000 times smaller than a freely-diffusing lipid-motor complex in a lipid bilayer (1 microm(2)/s); fluorescence recovery after photobleaching experiments confirm the presence of the slower-moving motor population at the microtubule-membrane tube interface. We suggest that nonprocessive motors dynamically bind and unbind to maintain a continuous interaction with the microtubule. This dynamic and continuous interaction is likely necessary for nonprocessive motors to mediate bidirectional membrane tube dynamics reported previously.

Figure 1

Motor activity in membrane tubes. (a) Sum of images in a movie of a membrane tube network formed by nonprocessive (Ncd) motors. The star indicates an additional small vesicle bound to the same MT as the membrane tube. Bar = 5 μm. (b) Kymograph of line indicated in panel a, showing the evolution of the fluorescence profile, and hence the Ncd motor locations, along the membrane tube in time. Ncd motors do not show any directed motion nor is there any emergent pattern. Again, the star indicates the small vesicle which shows a persistently high fluorescence signal through time, in contrast to the motors in the membrane tube. The black dashed line indicates the tip of the membrane tube and the white dashed line sits beyond the tip into the bulk of the sample. (c) Fluorescence intensity profile along the tip of the membrane tube (indicated by the dashed line in b) formed by nonprocessive motors measured for each point in time. The fluctuations in fluorescence intensity in the tip region are above the background noise shown in shaded representation. (d) Sum of images in a movie of a membrane tube network formed by processive (kinesin) motors. Bar = 5 μm. (e) Kymograph of line indicated in panel d showing the evolution of the fluorescence profile, the kinesin motor locations, along the membrane tube in time. Kinesins walk toward and accumulate at the tip of the membrane tube. (f) Intensity profile along the tip of the growing membrane tube as indicated by the dashed line in panel e. As expected for processive motors, motors accumulate at the tip of the tube, resulting in an increase of the fluorescence intensity.

Figure 2

One-dimensional temporal autocorrelation curves for diffusion and flow. (a) The upper curve is a model curve for a system that is driven purely by single-component diffusion where τ_D = 12 s and D = 1 × 10⁻³ μm²/s. The lower curve is a model curve for a system with a directed motion, where τ_V = 0.78 s and V = 140 nm/s. The most striking difference between the two curves occurs at longer correlation times where the curve with a directed motion follows an exponential decay to zero. (b) Average autocorrelation curve for the points along a tube formed by processive motors (see line in Fig. 1d). The curve is characteristic for a system of particles that have a directed movement with an exponential decay at longer times. The curve is described by a one-dimensional model for a system of particles with a direction motion of velocity, where τ_V = 0.54 ± 0.07 s and V ≈ 200 nm/s, the motor speeds as they walk on the MT toward the tip of a membrane tube. (c) Histogram of speeds extracted from fits to the autocorrelation curves by a one-dimensional model for a system with directed movement. (d) Autocorrelation curve for nonprocessive motors in a membrane tube (see line in Fig. 1a). The curve is fit with a diffusive model for fluorescence correlations in a one-dimensional tube to yield a diffusion constant for nonprocessive motors that interact with the microtubule lattice. Here τ_D = 29 ± 4 s and D ≈ 0.4 × 10⁻³μm²/s. The signal is compared to background noise (lower shaded curve) to indicate that the signal is above the noise of the system. (e) Histogram of diffusion constants from fits to the autocorrelation curves for membrane tubes formed by nonprocessive motors. The resulting diffusion constants are very small, of ∼10⁻³μm²/s.

Figure 3

FRAP curves. (a) Timeseries showing the fluorescence recovery of nonprocessive motors in a membrane tube before and after bleaching of a region at the tip of the tube (dashed circle), bar = 2 μm. (b) FRAP curves for nonprocessive motors at a region in the middle of a membrane tube, at the tip of a membrane tube, and for motors diffusing in a membrane tube formed by flow in the absence of an underlying MT. (c) We examine the half-time for recovery of fluorescence into the bleached region, τ_1/2. The plot shows this half-time for recovery for tubes that have only freely diffusing lipid-motor complexes (open squares; the solid square represents the mean), tubes with processive motors either bleached in the middle of a tube or at the tip (circles), and tubes with nonprocessive motors either bleached in the middle or at the tip (triangles).

Figure 4

FRAP data. (a) FRAP curve for nonprocessive motors in a membrane tube fit by a one-dimensional model for recovery due to diffusion. The model gives τ_D = 126 ± 18 s and D = 0.027 μm²/s. (b) Scatterplot of diffusion constants measured for nonprocessive motors in membrane tubes using FRAP. Motors freely diffusing in a membrane tube have diffusion constants of 1 μm²/s (circles) and nonprocessive motors interacting with an underlying MT show a reduced diffusion constant. When motors interact with an MT on the surface the percentage of freely diffusing motors is reduced, as indicated by changes in the percentage of fast-moving motors on the y axis. Error bars are calculated from error in the fit of the model to the data.