The inside of a cell is a crowded space, full of proteins and other molecules. Yet, the molecular motors that transport some of those molecules within the cell move at the same speed as they would in pure water – about one micrometer per second. How the molecular motors could achieve such speeds in crowded cells was unclear. Nevertheless, Tjioe et al. suspected that the answer might be related to how multiple motors work together.

Molecular motors move by walking along filaments inside the cell and pulling their cargo from one location to another. Other molecules that bind to the filaments should, in theory, act like “roadblocks” and impede the movement of the cargo. Tjioe et al. studied a motor protein called kinesin, which walks on filaments called microtubules. But instead of looking at these motors moving along microtubules inside a cell, Tjioe et al. used a simpler system where the cell was eliminated, and all parts were purified. Specifically, Tjioe et al. tethered purified motors to a piece of glass and then observed them under an extremely accurate microscope as they moved free-floating, fluorescently labelled microtubules. The microtubules, in this scenario, were acting like cargoes, where many kinesins could bind. Each kinesin motor also had a small chemical tag that could emit light. By following the movement of the lights, it was possible to calculate what each kinesin was doing and how the cargo moved.

When more than one kinesin molecule was acting, the tension and speed of one kinesin affected the movement of the others. In any group of kinesins, about two-thirds of kinesin pulled the cargo, and unexpectedly, about one-third tended to resist and slow the cargo. These latter kinesins were moved along with the group without actually driving the cargo. These resisting kinesins did come off more rapidly than the driving kinesins, meaning the cargo should be able to quickly bypass roadblocks. This would help to keep the whole group travelling in the right direction at a steady pace.

Kinesin is part of a cytoskeletal motor family that moves cellular cargoes primarily to the cell periphery (microtubule plus end). It is important in key cellular processes like cell division and signaling (Gross et al., 2002). It is also implicated in several neurological disorders (McLaughlin et al., 2016). Due to advances in single molecule microscopy and force measurement techniques, transport properties by a single kinesin are well understood (Veigel and Schmidt, 2011). For example, kinesin-1, the prototypical kinesin, moves 8.4 nm per ATP consumed, in a hand-over-hand motion, walking about 100 steps before detaching and traveling at a speed of ~0.77 μm/sec in vitro (Cai et al., 2007), and equal- or higher speed in vivo (Block et al., 1990; Stamer et al., 2002; Yildiz et al., 2004). A single kinesin also exerts up to ~6 pN force (Svoboda and Block, 1994), and importantly, has an asymmetric run-length and velocity with regard to the direction of force on the microtubule (Figure 1A) (Coppin et al., 2002; Milic et al., 2014).

Figure 1

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However, a cell is extremely dense, filled with proteins (~300 mg/ml), and only 60–80% water volume (Albe et al., 1990), resulting in a high viscosity and elastic modulus (Berret, 2016). Despite this, large cargos move at virtually the same rate as in a water-based in-vitro environment (Furuta et al., 2013; Howard et al., 1989). How is this possible? We argue that it is due to the action of multiple motors acting on a single cargo.

Multiple motor transport is important in cellular trafficking (Blehm et al., 2013; Gross et al., 2002; Hendricks et al., 2012; Holzbaur and Goldman, 2010). Electron microscopy shows that ~1 to 7 motors are bound to cellular cargoes (Gross et al., 2007). Motors are inter-dependent (Gross et al., 2002), such that the impairment of one motor type (e.g. dynein) causes severe impairment in the other (e.g. kinesin) (Gross et al., 2002). Run length and stall forces are typically greater for multiple vs single motor, although not necessarily in proportion (Holzbaur and Goldman, 2010). Theoretical studies predict tension between multiple motors carrying the same cargo (Arpağ et al., 2014). This tension, we argue, allows for their ability to efficiently bypass roadblocks, which has yet to be shown experimentally.

To understand multiple motor transport, it is crucial to probe the force and motion of each kinesin, plus that of the cargo motion. However, no current single molecule assay can achieve this. For example, atomic force microscopy (AFM) allows recording of only single motors walking (Kodera and Ando, 2018); current fluorescence and optical trap assays can measure overall forces and positions of multiple motors, but not every single motor (Derr et al., 2012; Jamison et al., 2010). The inability to probe all molecular motors may have led to the differing conclusions on the effect of motor number on run length (Block et al., 1990; Derr et al., 2012; Efremov et al., 2014; Shubeita et al., 2008; Vershinin et al., 2007). Two in vitro assays come close to probing the behavior of all participating kinesins. One uses a programmable DNA origami with up to seven kinesins attached (Derr et al., 2012). Another uses immobilized GFP-labeled kinesins and tracks gliding microtubules with quantum dots attached (Leduc et al., 2007). These studies accurately count the number of kinesins on cargo, but not their behavior.

One pertinent question is whether single-motor asymmetry plays a role in multi-motor transport. The Block group found an asymmetry when studying the run length of single kinesin as a function of force in an optical trap (Milic et al., 2014) (Figure 1A). This asymmetry is between driving kinesin, which experiences force opposite to its walking direction, and resisting kinesin, which experiences force in the same direction as its movement. They found that the run length is greater for driving kinesin (50 nm at −6 pN rising rapidly to 1100 nm at 0 pN) vs. resisting kinesin (~100 nm at 2 pN slowly falling to 10 nm at 20 pN) (Figure 1A) (Milic et al., 2014). Similarly, the Vale group saw kinesin velocity to be slower for driving-kinesin than resisting-kinesin (Figure 1B) (Coppin et al., 2002). Whether this run-length and velocity asymmetry occurs when multiple driving and resisting kinesins are carrying a single cargo was not determined, and whether inter-kinesin interactions cause this, will be described here.

To overcome current experimental limitations, a number of authors have done simulations which provided insights into multiple-motor behavior. One simulation showed that the asymmetric property of single kinesin under load leads to an average of one-third of kinesin’s resisting in multi-motor situation (Arpağ et al., 2014). In addition, the tension was between 0 to 15 pN between the kinesins carrying the cargo (Arpağ et al., 2014). Other simulations showed that, on a single cargo being driven by multiple motors, force-dependent detachment of motors (Arpağ et al., 2014), particularly the resisting motors (Nelson et al., 2014), is important for cargo speed. However, the accuracy of simulations heavily depended on the particular models used (Arpağ et al., 2014; Kunwar and Mogilner, 2010; Kunwar et al., 2008; Xu et al., 2013).

Another question is how well multiple motors cooperate together. A number of experimental studies found negative cooperativity of kinesin (Furuta et al., 2013; Jamison et al., 2010). Negative cooperativity, in this case, means that cargo transport does not fully benefit from having two motors present due to a certain inter-motor inhibition that reduces the motor-filament binding energies in the system. Motor run length and average detachment forces would therefore not increase as dramatically as expected in cases without this interference (Jamison et al., 2010). However, exactly how the on- and off-rates of each kinesin (e.g. run length and binding duration) change to give rise to negative cooperativity is unknown.

Negative cooperativity does not mean that additive forces of two or more kinesins can never occur. It can happen occasionally, and can be observed in optical trap assays (Jamison et al., 2010; Vershinin et al., 2007). How relevant additive forces are to cellular transport is unclear. It is possible that additive forces help kinesin get unstuck upon roadblock encounter, but this has not been shown. Another possibility is that additive forces can detach kinesin(s) from the cargo, which has also not been shown, but may facilitate cargo transport in a crowded cell (Conway et al., 2012). It is possible that additive forces happen only transiently, but, nevertheless, may be important to bypass roadblocks.

In this work, we have developed an in-vitro assay, which we call a force-gliding assay, details of which are discussed below. It allows direct observation of individual kinesin-1’s motion, velocities and forces, acting as a dynamical team of multiple kinesin motors (1- ~ 8), transporting a common cargo (microtubule), whose position and velocity can be measured. We can directly observe the attachment and detachment of individual motors from the microtubule, and find that kinesin exists in two distinct states, one driving the microtubule, the other resisting. We observe an asymmetric run length and velocity response to load of driving-kinesins and resisting-kinesins, indicating a non-zero tension between kinesins carrying the same cargo. This leads to one-third of kinesins always resisting. We further show that multiple kinesins exhibit negative cooperativity through decreasing run-length of individual kinesins as more kinesins participate in transport. Lastly, multiple kinesins can combine forces that help in overcoming the roadblocks.

We conclude that an asymmetric tug-of-war, with negative cooperativity and additive forces, defines collective kinesin transport and can potentially help with uninterrupted cargo transport inside the cell. We note that our assay measures dynamic interactions between multiple kinesins and a cargo. The ability to do get dynamic interactions may be crucial because it may be only transient interaction which are necessary to bypass roadblocks. Whether the tension embedded within an in vivo system, and whether other molecular motors such as dynein and myosin have a similar cooperative behavior, remains to be seen.

We have dissected the dynamics of multiple kinesin-based cargo transport using our force-gliding assay. We can now observe individual kinesin dynamics and the effect of their dynamics on the instantaneous and overall cargo transport. We also studied cargo transport driven by multiple kinesins in the presence of roadblocks to mimic the cellular environment and to understand how multiple kinesins can overcome roadblocks.

Model of multi-kinesin cargo transport

Figure 6 is an example of how multiple kinesins might interact with a single cargo within a cell. When one kinesin moves slower than the cargo and becomes resisting (Figure 6A), the assisting forces from the cargo tend to increase this kinesin’s speed or cause it to release rapidly, allowing the cargo to experience minimal drag force. Surprisingly, there appears to be ~ 35% resisting kinesins, causing a continuous tug-of-war among the kinesins, which tends to maintain an appreciable tension between kinesins. Kinesins can also rapidly switch between driving and resisting, leading to a fairly continuous and uninterrupted cargo motion forward. Against roadblocks, force augmentation of multiple kinesins may lead to large forces, causing detachment of resisting kinesin from cargo or microtubule (Figure 6B). By combining the motion and the force of single kinesins, we can connect the single molecule behavior of kinesins with their ensemble behavior. Whether the tension embedded within an in vivo system, and whether other molecular motors such as dynein and myosin have a similar cooperative behavior, remains to be seen.

Figure 6

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For one-to-one labeling of kinesin to QD, we used an in house developed magnetic separation method, called MiCA purification (see Materials and methods) (Tjioe et al., 2018). The likelihood of having two or more DNAs bound to a QD is low due to the steric hindrance of bulky DNA (~230 nm end-to-end distance) bound to a small 20 nm QD, as well as the use of 8x less DNA to bind kinesin-QD during experiment (see Materials and methods). For our study, we draw our conclusions primarily on the basis of the relative numbers of driving and resisting kinesins. We define the relative numbers of kinesins as the number of driving kinesins in relation to the number of resisting kinesins (i.e. driving kinesin/resisting kinesin, or driving/resisting kinesin as a fraction of total kinesins). We cannot completely rule out non-fluorescent QDs (QD at off state due to blinking,~5% of the time at 0.2 s time frame; Efros and Nesbitt, 2016), which will underestimate the absolute number of kinesins measured (including those attached to fluorescent and non-fluorescent QD). Since the fraction of non-fluorescent QDs will be the same from experiment to experiment, the relative number of kinesins (e.g. between driving and resisting) and the trend comparing the number of kinesin across experiments would not be affected. Likewise, some driving and resisting events are missed due to small (<100 nm) kinesin-QD displacements (see Materials and methods), which will underestimate the absolute but not relative number and trend in the number of kinesins.

Theoretically, in our assay, if we can calculate the forces exerted by all the individual kinesins driving the microtubule, we can find the total force by just summing them up. However, in our assay this is not yet feasible. First, the forces have a magnitude as well as direction and must be vectorially added. Second, there is significant uncertainty in calculating the maximal force of any given kinesin because a small uncertainty in the displacement measurement gives rise to a large uncertainty in the corresponding force calculation. Consider the force-extension curve for the 1565 bp dsDNA (Figure 5B). The extensible worm-like chain model fits the force-extension curve very well; however, at an extension of 500 nm, for example, the slope of the DNA/WLC extension is ~ 1 nm/pN. Hence, a small displacement error, for example 10 nm would yield a possible error of 10 pN.

An interesting point in Figure 3E is that at about 1 s, the driving and resisting kinesin velocity actually crosses as they approach the microtubule velocity (~830 nm/s). This is due to the resisting and driving kinesin detaching or returning back to equilibrium. This return to equilibrium causes resisting kinesin to increase in velocity, and driving kinesin to decrease in velocity, as shown in Figure 4—figure supplement 4b,d, leading to the cross-over. This cross-over takes place at an earlier time for shorter kinesin traces and a later time for longer kinesin traces.

For the optical trap assay, once a tether is formed, one trap was moved away from the other at a constant rate (10 nm/s or 100 nm/s) over a pre-set distance, then allowed to return at the same rate to the initial position. For choosing the pulling rates for the optical trap experiment, we picked 9 instances of kinesin during forced detachment events. We calculated the kinesin velocity just before the forced detachment for all nine cases (See Figure 4—figure supplement 3). The kinesin velocity varied between 7 nm/s to 450 nm/s, with an average of 150 nm/s. We tested 10 nm/s and 100 nm/s pulling speed in the optical trap assay to find the lowest force needed to rupture the DNA (in general, the lower the pulling velocity, the lower is the force needed to rupture the digoxigenin:anti-digoxigenin interaction). More than 50% of tethers remain at the highest force pulled (45 pN), indicating that most of the digoxigenin:anti-digoxigenin linkage may take more than 45 pN to rupture.

Using the force to which half of the tethers survive gives a more accurate description of what the trapping experiments measure than using the average rupture force. This is because a considerable fraction of the tethers that were pulled did not rupture, but survived through a pulling and relaxing cycle. Given that the rupture value for digoxigenin:anti-digoxigenin linkage yields approximately 30 pN and 45 pN for 10 and 100 nm/s pulling rate, it is clear that the force exerted on the extracted kinesin (Figure 4B,C) must arise from more than one kinesin pulling on it. This shows that a group of kinesins driving a cargo can exert forces much greater than a single kinesin, and thus help in smooth cargo-transport despite the presence of roadblocks.

On the survival probability plot in Figure 5C, there is small proportion of digoxigenin:anti-digoxigenin bonds which rupture at 6 pN or less (~2–4%). We attempt to estimate the proportion of the nine detaching kinesins over the entire population, keeping in mind that there may be more detaching kinesins which we miss. We find that there are 221 resisting kinesins that do not detach, which have similar force conditions (DNA extension > 500 nm and loading rate of < 450 nm/s) as the nine detaching kinesins. This means that the nine detaching kinesins constitute 4% of the entire kinesin population, meaning there is a high probability that the detaching kinesins rupture at forces below 6 pN. Thus, even though we are confident that the detaching kinesin are pulled by multiple driving kinesins (on average 4), we are less certain that the forces these driving kinesins exert on the detaching kinesin are compounded beyond single kinesin stall force of 6 pN to break the digoxigenin:anti-digoxigenin bonds.

In Figure 2B, we observe the signature of velocity asymmetry in the plateaus of the kinesin displacement graphs. The plateau (shown as 2’ region in Figure 2B4 and B5) means that the velocity of resisting kinesin (Figure 2B4) increases and driving kinesin (Figure 2B5) decreases to match the microtubule speed. How? Let’s understand what happens before the plateau, that is at the 1’ region? For resisting kinesin, the upward slope at 1’ region means that kinesin’s speed is slower than the microtubule speed (seen as an approximately linear slope). While this happens kinesin is moving further than its equilibrium position on the coverslip, and when the DNA connecting the kinesin and the coverslip gets stretched, the kinesin’s speed is not allowed to lag behind microtubule’s speed much further. At this point the kinesin is feeling a large assisting load pulling it forward, and it can choose to detach, or adapt its speed to the microtubule speed, which manifests as the plateau (2’ region). At the plateau, kinesin has no displacement relative to the glass coverslip. Since the microtubule is moving at the same speed relative to both kinesin and glass coverslip, this means that at the plateau, kinesin’s speed relative to microtubule matches the microtubule speed relative to the coverslip. We observe many cases of kinesins, both driving and resisting, matching their speeds to the cargo. In Figure 2B alone this happens to practically all of the driving and resisting instances. We find this surprising because without a force-gliding assay, we would only observe microtubule velocity (Figure 2B1), which fluctuates only mildly. With the force-gliding assay, we now understand that beneath the seemingly smooth microtubule movement there is considerable fluctuation in kinesin speed that matches and supports microtubule speed.

All data generated or analysed during this study are included in the manuscript and supporting files.

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Author details

1. Marco Tjioe

   1. Center for Biophysics and Quantitative Biology, University of Illinois at Urbana-Champaign, Urbana, United States
   2. Center for the Physics of Living Cells, University of Illinois at Urbana-Champaign, Urbana, United States
   3. Department of Physics, University of Illinois at Urbana-Champaign, Urbana, United States

   Present address

   Element Biosciences, San Diego, United States

   Contribution

   Conceptualization, Data curation, Software, Formal analysis, Supervision, Validation, Investigation, Visualization, Methodology, Writing—original draft, Writing—review and editing

   Competing interests

   Marco Tjioe is affiliated with Element Biosciences. The author has no other competing interests to declare.

   "This ORCID iD identifies the author of this article:" 0000-0002-6445-9828

2. Saurabh Shukla

   1. Center for the Physics of Living Cells, University of Illinois at Urbana-Champaign, Urbana, United States
   2. Department of Chemical and Biomolecular Engineering, University of Illinois at Urbana-Champaign, Urbana, United States

   Contribution

   Software, Formal analysis, Visualization, Writing—original draft, Writing—review and editing

   Competing interests

   No competing interests declared

3. Rohit Vaidya

   1. Center for Biophysics and Quantitative Biology, University of Illinois at Urbana-Champaign, Urbana, United States
   2. Center for the Physics of Living Cells, University of Illinois at Urbana-Champaign, Urbana, United States

   Contribution

   Software, Formal analysis, Visualization, Writing—original draft, Writing—review and editing

   Competing interests

   No competing interests declared

4. Alice Troitskaia

   Center for Biophysics and Quantitative Biology, University of Illinois at Urbana-Champaign, Urbana, United States

   Contribution

   Software, Formal analysis, Visualization, Writing—original draft, Writing—review and editing

   Competing interests

   No competing interests declared

5. Carol S Bookwalter

   Department of Molecular Physiology and Biophysics, University of Vermont, Burlington, United States

   Contribution

   Resources

   Competing interests

   No competing interests declared

6. Kathleen M Trybus

   Department of Molecular Physiology and Biophysics, University of Vermont, Burlington, United States

   Contribution

   Resources, Supervision, Funding acquisition, Writing—review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-5583-8500

7. Yann R Chemla

   1. Center for Biophysics and Quantitative Biology, University of Illinois at Urbana-Champaign, Urbana, United States
   2. Center for the Physics of Living Cells, University of Illinois at Urbana-Champaign, Urbana, United States
   3. Department of Physics, University of Illinois at Urbana-Champaign, Urbana, United States

   Contribution

   Conceptualization, Software, Formal analysis, Supervision, Funding acquisition, Validation, Visualization, Writing—original draft, Writing—review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-9167-0234

8. Paul R Selvin

   1. Center for Biophysics and Quantitative Biology, University of Illinois at Urbana-Champaign, Urbana, United States
   2. Center for the Physics of Living Cells, University of Illinois at Urbana-Champaign, Urbana, United States
   3. Department of Physics, University of Illinois at Urbana-Champaign, Urbana, United States

   Contribution

   Conceptualization, Resources, Data curation, Formal analysis, Supervision, Funding acquisition, Validation, Investigation, Visualization, Methodology, Writing—original draft, Project administration, Writing—review and editing

   For correspondence

   selvin@illinois.edu

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-3658-4218

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