Stable tug-of-war between kinesin-1 and cytoplasmic dynein upon different ATP and roadblock concentrations

Monzon, Gina A.; Scharrel, Lara; D’Souza, Ashwin; Henrichs, Verena; Santen, Ludger; Diez, Stefan

doi:10.1242/jcs.249938

Cited by 18 publications

(13 citation statements)

References 67 publications

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“…However, some filaments have a large velocity as indicated by the long tails in the velocity probability densities in Fig 9a and the long tails in the profile curves in Fig 8 . This is consistent with IF transport by one directional motor molecules with friction and with IF experiments where velocities were described to be non Gaussian with a high propensity of slow filaments in previous work [ 19 , 20 , 24 ]. Moreover, average velocities extracted from the fit of the profile curves with gamma distributions are consistent with values published in the literature [ 25 ], but lower than the range described for the transport of isolated small filaments called squiggles [ 25 , 26 ] and longer filaments measured in [ 17 ].…”

Section: Discussionsupporting

confidence: 91%

“…The gamma distribution would reflect the fact the velocity is asymmetrically distributed with a higher contribution of slow filaments. The gamma distribution would empirically describe the asymmetric velocity distributions predicted in the transport of cargoes when friction plays an important role [ 19 , 20 ], as it is the case for IF [ 12 ]. The Dirac distribution depends on one free parameter and the other three have two free parameters.…”

Section: Methodsmentioning

confidence: 99%

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Using Fluorescence Recovery After Photobleaching data to uncover filament dynamics

et al. 2022

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Fluorescence Recovery After Photobleaching (FRAP) has been extensively used to understand molecular dynamics in cells. This technique when applied to soluble, globular molecules driven by diffusion is easily interpreted and well understood. However, the classical methods of analysis cannot be applied to anisotropic structures subjected to directed transport, such as cytoskeletal filaments or elongated organelles transported along microtubule tracks. A new mathematical approach is needed to analyze FRAP data in this context and determine what information can be obtain from such experiments. To address these questions, we analyze fluorescence intensity profile curves after photobleaching of fluorescently labelled intermediate filaments anterogradely transported along microtubules. We apply the analysis to intermediate filament data to determine information about the filament motion. Our analysis consists of deriving equations for fluorescence intensity profiles and developing a mathematical model for the motion of filaments and simulating the model. Two closed forms for profile curves were derived, one for filaments of constant length and one for filaments with constant velocity, and three types of simulation were carried out. In the first type of simulation, the filaments have random velocities which are constant for the duration of the simulation. In the second type, filaments have random velocities which instantaneously change at random times. In the third type, filaments have random velocities and exhibit pausing between velocity changes. Our analysis shows: the most important distribution governing the shape of the intensity profile curves obtained from filaments is the distribution of the filament velocity. Furthermore, filament length which is constant during the experiment, had little impact on intensity profile curves. Finally, gamma distributions for the filament velocity with pauses give the best fit to asymmetric fluorescence intensity profiles of intermediate filaments observed in FRAP experiments performed in polarized migrating astrocytes. Our analysis also shows that the majority of filaments are stationary. Overall, our data give new insight into the regulation of intermediate filament dynamics during cell migration.

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Section: Discussionsupporting

confidence: 91%

Section: Methodsmentioning

confidence: 99%

Using Fluorescence Recovery After Photobleaching data to uncover filament dynamics

et al. 2022

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“…This approach allows an examination of how differing mechanochemical properties of specific motor isotypes translate into effective movement against an antagonistic partner. Consistent behavior of kinesin-dynein pairs that are observed across different labs (25–27,59) include the following: 1) kin-DDB complexes remain bound to microtubules for ~tens of seconds (26,27), considerably longer than Kin-1 or DDB alone; 2) trajectories include episodes, lasting from seconds to tens of seconds, where the velocity of the complex is ~10-fold slower than the unloaded velocities of the respective motors; and 3) cargo trajectories are quite smooth and show few if any directional switches. In principle, it should be possible to recapitulate these motility behaviors using Kin-DDB simulations that incorporate established parameters for kinesin and dynein behavior in isolation.…”

Section: Discussionsupporting

confidence: 65%

Simulations suggest robust microtubule attachment of kinesin and dynein in antagonistic pairs

Gicking

Feng

et al. 2022

Preprint

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Intracellular transport is propelled by kinesin and cytoplasmic dynein motors that carry membrane-bound vesicles and organelles bidirectionally along microtubule tracks. Much is known about these motors at the molecular scale, but many questions remain regarding how kinesin and dynein cooperate and compete during bidirectional cargo transport at the cellular level. The goal of the present study was to use a stochastic stepping model to identify specific motor properties that determine the speed, directionality, and transport dynamics of a cargo carried by one kinesin and one dynein motor. The computational model incorporated load-dependent properties of kinesin-1 and dynein-dynactin-BicD2 (DDB) taken from published optical tweezer experiments. Model performance was evaluated by comparing simulations to recently published experiments of kinesin-DDB pairs connected by complementary oligonucleotide linkers. Using motor parameters from single molecule studies, the simulations recapitulated mean experimental cargo velocities, but displayed considerable directional switching and positional fluctuations not seen in experiments. Instantaneous velocity distributions from kinesin-DDB experiments showed a single peak centered around zero, whereas simulated velocity distributions showed a slow plus-end directional velocity peak and two additional peaks corresponding to fast unloaded kinesin and DDB velocities. We hypothesized that directional switching in the simulations resulted from frequent motor detachment events and non-negligible durations during which only one motor is attached. To investigate this hypothesis, we explored how specific parameters in the model contributed to the overall cargo dynamics and found that making DDB detachment insensitive to load and increasing the kinesin-1 reattachment rate to 50 s-1, together with small adjustments in the kinesin stall force and cargo stiffness brought the simulations into alignment with the experiments. These results provide new insights into motor dynamics during bidirectional transport and put forth hypotheses that can be tested by future experiments.

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“…This indicates that these vesicle types harbor in general molecular motors for both the directions of movement. Accordingly, the transport direction is often determined not by recruitment of motor proteins, but by their activation and inactivation (Monzon et al 2020 ). In this context, it is tempting to speculate about the mechanisms that regulate the molecular motors and hence transport direction during autophagosome maturation.…”

Section: Discussionmentioning

confidence: 99%

Maturing Autophagosomes are Transported Towards the Cell Periphery

et al. 2021

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Autophagosome maturation comprises fusion with lysosomes and acidification. It is a critical step in the degradation of cytosolic protein aggregates that characterize many neurodegenerative diseases. In order to better understand this process, we studied intracellular trafficking of autophagosomes and aggregates of α-synuclein, which characterize Parkinson’s disease and other synucleinopathies. The autophagosomal marker LC3 and the aggregation prone A53T mutant of α-synuclein were tagged by fluorescent proteins and expressed in HEK293T cells and primary astrocytes. The subcellular distribution and movement of these vesicle populations were analyzed by (time-lapse) microscopy. Fusion with lysosomes was assayed using the lysosomal marker LAMP1; vesicles with neutral and acidic luminal pH were discriminated using the RFP-GFP “tandem-fluorescence” tag. With respect to vesicle pH, we observed that neutral autophagosomes, marked by LC3 or synuclein, were located more frequently in the cell center, and acidic autophagosomes were observed more frequently in the cell periphery. Acidic autophagosomes were transported towards the cell periphery more often, indicating that acidification occurs in the cell center before transport to the periphery. With respect to autolysosomal fusion, we found that lysosomes preferentially moved towards the cell center, whereas autolysosomes moved towards the cell periphery, suggesting a cycle where lysosomes are generated in the periphery and fuse to autophagosomes in the cell center. Unexpectedly, many acidic autophagosomes were negative for LAMP1, indicating that acidification does not require fusion to lysosomes. Moreover, we found both neutral and acidic vesicles positive for LAMP1, consistent with delayed acidification of the autolysosome lumen. Individual steps of aggregate clearance thus occur in dedicated cellular regions. During aggregate clearance, autophagosomes and autolysosomes form in the center and are transported towards the periphery during maturation. In this process, luminal pH could regulate the direction of vesicle transport. Graphic Abstract (1) Transport and location of autophagosomes depend on luminal pH: Acidic autophagosomes are preferentially transported to the cell periphery, causing more acidic autophagosomes in the cell periphery and more neutral autophagosomes at the microtubule organizing center (MTOC). (2) Autolysosomes are transported to the cell periphery and lysosomes to the MTOC, suggesting spatial segregation of lysosome reformation and autolysosome fusion. (3) Synuclein aggregates are preferentially located at the MTOC and synuclein-containing vesicles in the cell periphery, consistent with transport of aggregates to the MTOC for autophagy.

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Stable tug-of-war between kinesin-1 and cytoplasmic dynein upon different ATP and roadblock concentrations

Cited by 18 publications

References 67 publications

Using Fluorescence Recovery After Photobleaching data to uncover filament dynamics

Using Fluorescence Recovery After Photobleaching data to uncover filament dynamics

Simulations suggest robust microtubule attachment of kinesin and dynein in antagonistic pairs

Maturing Autophagosomes are Transported Towards the Cell Periphery

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