Delineating cooperative responses of processive motors in living cells

Abstract

Characterizing the collective functions of cytoskeletal motors is critical to understanding mechanisms that regulate the internal organization of eukaryotic cells as well as the roles various transport defects play in human diseases. Though in vitro assays using synthetic motor complexes have generated important insights, dissecting collective motor functions within living cells still remains challenging. Here, we show that the protein heterodimerization switches FKBP-rapalog-FRB can be harnessed in engineered COS-7 cells to compare the collective responses of kinesin-1 and myosinVa motors to changes in motor number and cargo size. The dependence of cargo velocities, travel distances, and position noise on these parameters suggests that multiple myosinVa motors can cooperate more productively than collections of kinesins in COS-7 cells. In contrast to observations with kinesin-1 motors, the velocities and run lengths of peroxisomes driven by multiple myosinVa motors are found to increase with increasing motor density, but are relatively insensitive to the higher loads associated with transporting large peroxisomes in the viscoelastic environment of the COS-7 cell cytoplasm. Moreover, these distinctions appear to be derived from the different sensitivities of kinesin-1 and myosinVa velocities and detachment rates to forces at the single-motor level. The collective behaviors of certain processive motors, like myosinVa, may therefore be more readily tunable and have more substantial roles in intracellular transport regulatory mechanisms compared with those of other cytoskeletal motors.

Keywords: cooperativity; intracellular transport; microrheology; motor proteins; synthetic biology.

Fig. 1.

Expression regulation of motor densities and cargo sizes in COS-7 cells. (A and B) The TET-ON and cumate operons are used to regulate the expression levels of the PEX-mYFP-FKBP and mYFP-SKL genes, which are targeted to the surface and lumen of peroxisomes, respectively. Incubation with rapalog couples transiently expressed motors (kinesin-1 and myosinVa) incorporating mCherry and FRB fusion to peroxisome surfaces via the formation of a FKBP-rapalog-FRB complex. (C) Peroxisome diameters increase dramatically in time when mYFP-SKL expression is induced with 100 μg/mL of cumate. Each histogram displays size distributions of >7,000 peroxisomes measured in ∼100 cells.

Fig. 2.

Size-dependent mobility of peroxisomes in COS-7 cells. (A) Confocal images show that peroxisomes (yellow) localize to the perinuclear region of COS-7 cells due to microtubule (red) confinement. Upon treatment with nocodazole, actin filaments (green) reorganize and peroxisomes become more uniformly distributed throughout the cell body. (B) MSD analyses of passively diffusing peroxisomes show peroxisome mobilities decrease with increasing particle size in both untreated and nocodazole-treated cells. More than 1,500 peroxisome trajectories were averaged in each MSD curve. Line widths indicate SEM. The black dashed lines indicate fits to a corralled diffusion model (Eq. 2; R² and adjusted R² > 0.99). (C) The model fits in B provide estimates of rheological parameters, including the average size of cytoskeletal cages, cage velocities due to activated filament motions, passive cage diffusion coefficients, and the intracage peroxisome diffusion coefficients. The observed trends generally reflect lower mobilities of the large peroxisomes. Error bars indicate SEM, but are only visible in plots of cage velocity because the errors in the remaining plots are smaller than the size of the symbols.

Fig. 3.

Rapalog-dependent induction of peroxisome transport. (A) SD maps of pixel intensities measured in movies displaying peroxisome trajectories in the presence and absence of rapalog. The red dot indicates the starting position of the peroxisome. (B and C) Fluorescence images showing rapalog-dependent redistribution of peroxisomes to the COS-7 cell periphery and local peroxisome aggregation when transport is driven by kinesin-1 (B) and myosinVa (C) motors, respectively. The yellow hue indicates peroxisome (green) and motor (red) colocalization. Representative trajectories recorded at 91 fps for each motor type are displayed.

Fig. 4.

Collections of kinesin-1 and myosinVa motors exhibit distinct motile behaviors. (A) Average peroxisome velocities are largely insensitive to doxycycline concentration/motor density, but decrease with peroxisome size when transport is driven by kinesin-1 (Left). MyosinVa-dependent velocities (Right) display characteristically different size dependencies and generally increase with increasing motor density. (B and C) Distributions of rms position fluctuations and mean rms position fluctuation amplitudes exhibit unique dependencies on doxycycline concentration and cargo size in kinesin-1 (Left) and myosinVa (Right) assays. The rms positional distributions in B correspond to large peroxisomes (diameter = 0.9–1.2 μm). The black line in B displays rms position distributions measured in the absence of rapalog. More than 100 trajectories in a minimum of 10 cells were measured for each bin in A and C. Doxycycline (Dox) concentrations are reported in milligrams per milliliter. Error bars represent SEM.

Fig. 5.

Structure–function analyses of fast components of peroxisome trajectories. (A) An example of fast (red) and slow (gray) components of peroxisome velocity distributions were identified within kinesin trajectories using an HMM approach. The total distribution is indicated by the black dashed line. (B) The fraction of kinesin-dependent trajectory components attributed to fast directional motion is largely insensitive to motor density, but decreases with increasing size. (C) Similar trends are found for the average velocities (Left) and the lengths of the fast runs (Right). (D) Hidden Markov modeling analyses of Myosin-dependent velocity distributions. (E) In contrast to kinesin, the fraction of fast transport events increased as much as 171 ± 12% with increasing motor density. (F) Average peroxisome velocities and transport distances exhibit a similar positive dependence on motor density. Analyses were performed on the same trajectories evaluated in Fig 4. Error bars represent SEM. Statistical analyses are presented in Table 1.