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Department of Physics and Astronomy and Laser Centre, Vrije Universiteit, De Boelelaan 1081, 1081 HV, Amsterdam, The Netherlands
Correspondence: Address reprint requests to Erwin J. G. Peterman, Vrije Universiteit Amsterdam, Division of Physics and Astronomy, De Boelelaan 1081, Amsterdam 1081 HV, The Netherlands. Tel.: 31-20-598-7576; Email: erwinp{at}nat.vu.nl.
| ABSTRACT |
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800 nm/s, which means that one turnover on average takes 10 ms. Important details, however, concerning the coordination between the two motor domains have not been determined due to limitations of the techniques used. In this study, we present an approach that allows the observation of fluorescence intensity changes on individual kinesins with a time resolution far better than the duration of a single step. In our approach, the laser focus of a confocal fluorescence microscope is pointed at a microtubule and the photons emitted by fluorescently labeled kinesin motors walking through the spot are detected with submicrosecond accuracy. We show that the autocorrelation of a fluorescence time trace of an individual kinesin motor contains information at time lags down to 0.1 ms. The quality and time resolution of the autocorrelation is primarily determined by the amount of signal photons used. By adding the autocorrelations of several tens of kinesins, fluorescence intensity changes can be observed at a timescale below 100 µs. | INTRODUCTION |
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0.8 µm/s. Consequently, under saturating ATP conditions, the average duration of a single catalytic cycle is
10 ms (11
Our understanding of kinesin's mechanism has benefited a great deal from the application of single-molecule techniques. The key advantages of applying single-molecule methods to kinesin are that the properties (e.g., velocity, step size, generated force) of single kinesin motors can be determined directly and that synchronization of many motors is not needed (such as in stopped-flow kinetics experiments). Two single-molecule techniques that have been used extensively to clarify kinesin's mechanism are optical tweezers and wide-field single-molecule fluorescence microscopy. Using optical tweezers, the force exerted by a single motor as well as its center-of-mass position can be measured with high time resolution (>5 kHz) and high force (<1 pN) and spatial resolution (<1 nm) (14
). In general, the properties of the motor are measured while it is subjected to an external load; measurements at low load are difficult. A limitation of this technique is that the mechanics of the kinesin as a whole are studied and that it does not allow for direct measurement on individual motor domains. Furthermore, information on the kinetics of transitions in kinesin's chemomechanical cycle can only be inferred from fitting kinetic models to the data (11
) but cannot be observed directly. The other frequently used technique is wide-field single-molecule fluorescence microscopy, which allows direct observation of the motion of single, fluorescently labeled motors. By attaching the label to different parts of the molecule, one can measure the motion of the center of mass of the whole dimeric motor (15
) or one of the motor domains (6
). Fluorescence microscopy has the advantage that other parameters besides location can also be measured, such as relative distances using Förster resonance energy transfer (FRET) (16
), orientation using fluorescence polarization (17
), and the presence of fluorescent substrate analogs (18
). In most applications of wide-field fluorescence microscopy to kinesin, charge-coupled device (CCD) cameras are used for fluorescence detection (19
). These severely limit the time resolution of the technique, since they require integration of the emitted photons over 50–500 ms to obtain images with a high enough signal/noise ratio for accurate localization of the motor (6
). During such time intervals kinesin makes several steps, unless its velocity is lowered by limiting the ATP concentration. Both these techniques do not allow resolving the details of the coupling between the chemical and mechanical cycles of the two motor domains of walking kinesin. Wide-field single-molecule fluorescence microscopy does not have the time resolution required, whereas optical tweezers do not allow discrimination between the states of the individual motor domains.
In this study we introduce another fluorescence-based approach, with a time resolution high enough to allow resolution of the transitions between kinesin's chemical states. Our approach is based on fluorescence detection of individual, labeled kinesin motors walking through the focus of a confocal fluorescence microscope at saturating ATP concentrations without applying an external load. This article is structured as follows. First, we describe the technical details of our method. Next, we test the properties of our kinesin construct and motility assay with traditional, wide-field single-molecule fluorescence microscopy. Then we show that our confocal fluorescence microscopy method is compatible with the wide-field results. Finally, we show by applying autocorrelation analysis that our method allows resolving fluorescence intensity fluctuations that take place on a timescale of 10 µs, a 1000th of kinesin's average turnover time at saturating ATP concentrations.
| MATERIALS AND METHODS |
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For expression, the plasmid was introduced in E. coli Bl21(DE3) cells, grown to larger volumes (1 or 2l), and induced overnight at 22°C with isopropyl-β-D-thiogalactopyranoside (AppliChem, Darmstadt, Germany). Bacteria were spun down and the pellet was lysed by adding lysosyme and applying three brief periods of sonification. The lysate was loaded on a NiNTA column and the motor, tagged with a 6x his repeat on the N-terminus, was eluted with 300 mM imidazole.
The motor was labeled with Alexa Fluor 555 maleimide (Invitrogen, Carlsbad, CA) by adding the dye (dissolved in dimethylformamide and diluted in demineralized water) in a 1:1 fluorophore/kinesin monomer ratio and incubating for 3 h at 4°C. Unreacted dye was separated from the labeled kinesin by microtubule affinity centrifugation (21
).
Sample chamber preparation
Coverslips (No. 1.5, MenzelGlaser, Braunschweig, Germany) and slides (MenzelGlaser) were cleaned before use by sonification in 0.1 M KOH (1x, 10') and in demineralized water (3x, 10'). Coverslips were made positively charged by sonification in 0.1% (V/V) N1-[3-(Trimethoxysilyl)-propyl]diethylenetriamine (Sigma-Aldrich, St. Louis, MO) in water (1x, 10') and subsequent washing in water (3x, 10'). The coverslips were dried in an oven at 130°C and were stored dry. In contrast, the slides were cleaned each day and dried immediately before use. Sample chambers with three lanes (volume
5 µl) were made by gluing a coverslip to a slide using double-stick tape.
Sample lane preparation
Microtubule seeds were polymerized by mixing 7.5 µM unlabeled tubulin, 2.5 µM tetramethyl rhodamine (TMR)-labeled tubulin and 1 mM GMPCPP (Guanosine-5'[(
,β)-methyleno]triphosphate (Jena Bioscience, Jena, Germany)) for 15' at 36°C. Afterward they were stabilized with Pem80-taxol buffer (80 mM Pipes (1
,4
-piperazinediethanesulfonic acid), 1 mM EGTA (ethyleneglycol-bis(aminoethyl ether)-N,N'-tetraacetic acid), 2 mM MgCl2, pH 6.8, and 10 µM taxol) and were injected into the sample lanes. After 10' the lanes were rinsed three times with 10 µl Pem80-taxol buffer. Casein (sodium salt from bovine milk, Sigma-Aldrich) at 0.4 mg/ml in Pem80-taxol buffer was flushed into the lane and incubated for 10'. The lane was again rinsed three times with 10 µl Pem12-taxol buffer (equivalent to Pem80-taxol but with 12 mM Pipes). After these steps the mix with kinesin motors was flushed into the sample lane, after which the sample was sealed with vacuum grease. In all experiments an oxygen scavenger system (20 µg/ml glucose-oxidase, 35 catalase µg/ml, and 25 mM glucose), 4 mM dithiothreitol, and 10 µM taxol were added. For samples at saturating ATP concentrations, 2 mM ATP was added. In other experiments kinesin's velocity was decreased by instead adding 100 µM ATP and an ATP regeneration system (10 mM phosphocreatine and 50 µg/ml creatine kinase) (22
).
Experimental setup
The attenuated, 532-nm beam of a Verdi V10 (Coherent, Santa Clara, CA) laser was circularly polarized with a quarter-
plate, expanded six times, and coupled into an inverted microscope (TE-2000-U Nikon, Tokyo, Japan) with a 100x oil immersion objective (Nikon Plan Fluor, numerical aperture 1.3) (Fig. 1 A). Fluorescence was collected through a dichroic mirror (Q545LP, Chroma, Rockingham, VT) and filtered with an emission filter (HQ575/50, Chroma). The fluorescence light was then imaged on a CCD camera (CoolsnapHQ, RoperScientific, Tucson, AZ) or focused onto a multimode optical fiber (100-µm core diameter), serving as a pinhole (23
) and detected with an avalanche photodiode (APD) (SPQM-AQR-14, PerkinElmer, Vaudreuil, Quebec, Canada). Photons detected by the APD are converted to digital pulses, which were time tagged with electronic counterboard (6602, National Instruments, Austin, TX) with 12.5-ns time resolution. Arrival times of detected photons were stored on a computer using custom-built Labview software (Labview 7.1, National Instruments).
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Positioning the confocal spot and acquiring high time-resolution data
Wide-field illumination and CCD camera detection were used to locate the fluorescently labeled microtubules. The sample was translated to position the confocal spot within 1 µm of a microtubule. Then, a 1 x 1 µm area was scanned and the microtubule was positioned within 20 nm of the center of the confocal spot. This positioning procedure was repeated every 10 min to compensate for mechanical drift. Fluorophores on the microtubules were bleached before measuring the fluorescence of kinesins moving through the confocal spot.
Determining the width of the confocal spot
The width of the confocal point spread function was obtained by fitting a two-dimensional Gaussian to a confocal image of fluorescent beads (40-nm diameter, excitation/emission = 565/580 nm, FluoSpheres, Invitrogen) stuck to the surface. The width (defined as
of the Gaussian, i.e., the halfwidth at 1/
e) was corrected for the bead size by deconvolution and was determined to be 113 ± 5 nm (mean ± SE).
| RESULTS AND DISCUSSION |
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Typical events observed with confocal microscopy
We then switched from wide-field to confocal microscopy. When the laser was focused on a microtubule (Fig. 1 B), we observed fluorescence time traces as shown in Fig. 3 A. Labeled kinesins walking through the confocal spot show up as Gaussian peaks, which can be explained as follows. The kinesin-bound fluorophore senses a laser intensity that is determined by its location in the laser spot (which can be approximated by a Gaussian with width
exc). Consequently, under our experimental conditions (see below) the fluorophore emits with a rate proportional to this local excitation intensity. In a confocal microscope, the efficiency of detecting a photon emitted by a fluorophore also depends on its location, as described by the collection efficiency profile (which can also be approximated by a Gaussian with width
CEF). As a consequence, the total detected fluorescence intensity is proportional to the product of the excitation profile and the collection efficiency function. The product is also a Gaussian (26
) and is called the confocal point spread function. Therefore, the fluorescence of a labeled kinesin moving at constant velocity through the confocal spot will appear as a Gaussian peak in a binned fluorescence time trace. In Fig. 3 A, several Gaussian peaks can be discerned, all with nearly the same duration and amplitude except for one with an amplitude about twice as high. This latter signal is most probably due to a motor with two labels or two motors passing the focus at the same time. The time trace also shows two peaks with a constant, non-Gaussian fluorescence signal, which we attribute to fluorophores (loose or attached to kinesin) that get stuck somewhere in the confocal spot and detach or photobleach after some time.
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) of each event, which were used for further analyses.
Determination of the velocity of kinesins walking through the confocal spot
The Gaussian shape of the events indicates that the kinesin's velocity is constant during the passage through the confocal spot. Since the detected emission rate is proportional to the value of the confocal point spread function at the location of the motor, the motor's velocity equals the ratio of the spatial width of the point spread function and the temporal width of an event. A histogram of the temporal widths of all full events at a saturating ATP concentration of 2 mM is shown in Fig. 4 A. The distribution of the widths is Gaussian and peaks at 130.3 ± 1.7 ms (as determined with a Gaussian fit; the statistical average is 136.3 ± 1.5 ms). From this average temporal width an average velocity of 870 ± 40 nm/s can be calculated. The average value obtained in this way and the shape of the distribution compare very well to our wide-field fluorescence measurements, depicted in Fig. 4 C. To further validate our velocity determinations, confocal and wide-field measurements were also performed at 100 µM ATP, a concentration at which kinesin moves slower. The averaged temporal width of events at 100 µM ATP is larger (300 ± 20 ms) than at 2 mM. Furthermore, the distribution of the widths is wider as well (Fig. 4 B). Wide-field velocity determinations at the same ATP concentration show a similar average velocity (326 ± 9 nm/s) and distribution as the velocities calculated from the confocal measurements (344 ± 15 nm/s; Fig. 4 D).
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Events due to individual kinesin dimers walking through the confocal spot were selected after visual inspection of the fluorescence time traces. The center point and background levels were determined for each event by fitting a Gaussian to 10-ms binned time traces. The autocorrelation was calculated from 2-s long, background-subtracted binned time traces containing an event with its center point in the middle. The time traces were binned with bin sizes of 1 ms or 10 µs, depending on the timescale of interest (the calculations at small time bins require substantial computation time). For the autocorrelations with 10-µs bins we applied a coarse-grained step afterward to improve the signal/noise ratio on the longer timescales: the correlation times were chosen to increase logarithmically with time (29
). The correlation values within a bin were averaged.
The normalized autocorrelation of the fluorescence trace of a single motor passing through the confocal spot (Fig. 6 A) is roughly Gaussian with a larger width than that of the time trace it was calculated from (as expected since the autocorrelation of a Gaussian is a Gaussian with a
2 larger width). The time-symmetric autocorrelation is shown only for positive lag times on a logarithmic timescale to more clearly represent the curve over 5 decades of time.
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200 ms (only full events were used, and kinesin's velocity does not depend on the excitation intensity; Fig. 5). When vanish events are also included in the summation (Fig. 6 C) the higher power curves turn out to be narrower than the lower power ones, which is indicative of increased photobleaching, leading to more and narrower vanish events.
Simulations of the autocorrelated fluorescence time traces
To fully understand the effects of photobleaching and detachment of the motor, we focused further analysis on the 1–1000 ms timescale of summed autocorrelations of all full and vanish events (Fig. 6 C) and simulated the autocorrelated fluorescence time traces. Simulations were performed as follows. The emission rate of a labeled motor moving with constant velocity (v) depends on its position in the Gaussian excitation profile with width
exc. The detection efficiency depends on the location of the motor in the collection efficiency profile, which we assume Gaussian with a width of
CEF. The number of detected photons (Ndet) between time interval t and t +
t, due to such a motor, can be calculated using
![]() | (1) |
Where P is the power of the excitation laser,
is the setup- and fluorophore-dependent factor that relates the excitation power to the rate of emitted photons, and
is the maximum collection efficiency. Here we assume that at t = 0 the motor passes the coinciding maxima of the excitation and collection profile.
Next, for each event photobleaching was introduced by assuming a constant probability of bleaching for each emitted photon (the reciprocal of the bleach constant, b). The probability of bleaching, pbleaching, during an interval between t and t +
t can be expressed as
![]() | (2) |
Note that the probability of bleaching as a function of time depends only on the location of the fluorophore in the excitation spot and is not influenced by the location in the collection efficiency profile. For each step, this probability was compared to a randomly generated number (between 0 and 1) to decide whether photobleaching had occurred. In case of photobleaching, the signal was set to zero for the rest of the event.
In a similar way the finite length of kinesin runs was introduced. During each time interval the motor has a constant probability of detaching from the microtubule (pdetach), independent of its location:
![]() | (3) |
In this way, fluorescence time traces of 15,000 events were generated for different excitation powers using varying values for the other parameters. Subsequently, these traces were autocorrelated and summed. The measured autocorrelation curves can be simulated very well with a value for the run length (l) of 1700 nm, for the velocity (v) of 870 nm/s, for the width of the collection efficiency function (
CEF) of 220 nm, for the width of the excitation spot (
exc) of 150 nm, for the maximum collection efficiency (
) of 0.1, and for a bleach parameter (b) of 55,000 photons. Varying the value for the run length in the simulations (from 800 to 2000 nm) hardly altered the simulated correlation traces (data not shown), since the length scale of observing motion in our instrument (
4
PSF
500 nm) is several times smaller than the run length. The overall good correspondence of the model to the data indicates that the behavior of labeled motor proteins walking through the confocal spot is sufficiently understood. The small shoulder around 900-ms lag time in the autocorrelation curve of 1.0 µW is due to small inaccuracies in the background correction of the events.
Simulation of a construct whose fluorescence fluctuates due to stepping
The ultimate goal of our approach is to observe transitions between the chemomechanical states of walking kinesin. For this, labeled kinesin constructs are needed with at least two states in the cycle with differing fluorescence intensities. To examine the potential of our approach to yield new information on kinesin's mechanochemistry, we have simulated time traces and intensity autocorrelations of a kinesin construct capable of FRET between its two motor domains. We assume a construct with a donor fluorophore on one motor domain and an acceptor fluorophore at the same position on the other motor domain. The stepwise behavior of the motor is taken into account, and each step is assumed to consist of two distinct fluorescent states. We assume that the FRET transfer efficiency between donor and acceptor is 0.16 when the two motor domains are attached to consecutive binding sites on the microtubule (8 nm apart). During a step, we assume that the two motor domains are closer and that the transfer efficiency equals 0.8. The proximity could be due to a substep but can also be due to the overtaking of the forward head by the rearward one. It is known that kinesin's stepping takes <1 ms (11
).
Focusing on the intensity of the fluorescence emitted by the acceptor we assume that a single step consists of a short-lived high-fluorescent state and a longer lasting low-fluorescent state. We mimic the Poisson-like behavior of the motor by randomly selecting the occupation times of both states from an exponential distribution. In a first simulation we use an average occupation time of the high fluorescence state of 0.5 ms and of the low fluorescent state of 9.5 ms. The maximum emission rate of the acceptor is 20 photons/ms (as expected for the typical excitation powers used in our experiments), and the background signal is 1 photon/ms. The photon arrival times are generated from an exponential distribution with a decay time that depends on the fluorescent state and the position in the confocal spot.
In the simulated, binned fluorescence intensity traces the short-lived high-fluorescent state is hidden in the amplitude fluctuations of the Gaussian envelope (Fig. 7 A, black curve). The autocorrelation of this single event shows a decay around 0.5 ms, a signature of short bursts of fluorescence with on average this duration (Fig. 7 B, black curve). Averaging the autocorrelations of 20 simulated full events (Fig. 7 C, black curve) yields a smooth curve with an even more clear decay at 0.5 ms. In a next set of simulations we decreased the time the molecule spends in the high state to on average 0.1 ms, whereas the low-fluorescent state lasts 9.9 ms. Comparison of the binned fluorescence traces for the two different sets of simulations shows no clear differences (Fig. 7 A, black and red curve). Moreover, in the autocorrelation of a single event, clear features on the 0.1-ms timescale cannot be discerned (Fig. 7 B, red curve). If we however average 20 events with these settings we observe a clear decay around 0.1 ms (Fig. 7 C, red curve), demonstrating that our approach can yield insight into chemomechanical transitions taking place in <0.1 ms. In the simulations, conservative estimates of the parameters are used. A further improvement of the detectable timescale could be obtained by averaging even more events.
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| CONCLUSIONS |
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Our approach is related to fluorescence correlation spectroscopy (31
). Fluorescence correlation spectroscopy is often used to study freely diffusing labeled molecules, but it has also been applied to study flow inside cells (32
) and microfluidic devices (33
). In these studies, diffusion of the labeled biomolecules could be discriminated from drift with the solvent flow and flow velocities could be determined. Our approach is different in the key aspect that it is a truly single-molecule approach. We detect the trajectories of individual biomolecules walking through the confocal spot. This allows us to restrict our analysis to events with properties we expect for functional, singly labeled kinesin. We can select on properties such as width (a signature of velocity) and intensity (a signature of the amount of motors and labels).
For the labeled kinesin construct studied here, fluorescence fluctuations due to kinesin's mechanochemistry were neither expected nor observed. We have shown however that our approach allows for the observation of fluctuations on a timescale down to 10 µs, i.e., a thousand times faster than kinesin's stepping time. The confocal fluorescence approach shown here paves the way to study kinesin's mechanochemistry on the single-motor level, provided labeled kinesin constructs are used that report on chemical and conformational changes. One could, for example, think of fluorescence polarization as a reporter of conformational changes (17
) or fluorescent ATP analogs to directly observe substrate binding and release (18
). Another example would be a kinesin with a donor fluorophore on one motor domain and an acceptor on the other as a FRET reporter of the distance between the motor domains. We have performed a simulation with such a construct and shown that fluorescence intensity changes can be observed at timescales below 0.1 ms.
| ACKNOWLEDGEMENTS |
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This research was supported by a VIDI fellowship from the Research council for Earth and Life Sciences (A.L.W.) and by a Projectruimte grant from the Dutch Foundation for Fundamental Research on Matter (F.O.M.).
Submitted on July 18, 2006; accepted for publication December 22, 2006.
| REFERENCES |
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2. Svoboda, K., C. F. Schmidt, B. J. Schnapp, and S. M. Block. 1993. Direct observation of kinesin stepping by optical trapping interferometry. Nature. 365:721–727.[CrossRef][Medline]
3. Schnitzer, M. J., and S. M. Block. 1997. Kinesin hydrolyses one ATP per 8-nm step. Nature. 388:386–390.[CrossRef][Medline]
4. Carter, N. J., and R. A. Cross. 2006. Kinesin's moonwalk. Curr. Opin. Cell Biol. 18:61–67.[CrossRef][Medline]
5. Visscher, K., M. J. Schnitzer, and S. M. Block. 1999. Single kinesin molecules studied with a molecular force clamp. Nature. 400:184–189.[CrossRef][Medline]
6. Yildiz, A., M. Tomishige, R. D. Vale, and P. R. Selvin. 2004. Kinesin walks hand-over-hand. Science. 303:676–678.
7. Asbury, C. L., A. N. Fehr, and S. M. Block. 2003. Kinesin moves by an asymmetric hand-over-hand mechanism. Science. 302:2130–2134.
8. Kaseda, K., H. Higuchi, and K. Hirose. 2003. Alternate fast and slow stepping of a heterodimeric kinesin molecule. Nat. Cell Biol. 5:1079–1082.[CrossRef][Medline]
9. Vale, R. D., and R. A. Milligan. 2000. The way things move: looking under the hood of molecular motor proteins. Science. 288:88–95.
10. Rosenfeld, S. S., P. M. Fordyce, G. M. Jefferson, P. H. King, and S. M. Block. 2003. Stepping and stretching. How kinesin uses internal strain to walk processively. J. Biol. Chem. 278:18550–18556.
11. Schnitzer, M. J., K. Visscher, and S. M. Block. 2000. Force production by single kinesin motors. Nat. Cell Biol. 2:718–723.[CrossRef][Medline]
12. Leibler, S., and D. A. Huse. 1993. Porters versus rowers—a unified stochastic-model of motor proteins. J. Cell Biol. 121:1357–1368.
13. Rice, S., A. W. Lin, D. Safer, C. L. Hart, N. Naber, B. O. Carragher, S. M. Cain, E. Pechatnikova, E. M. Wilson-Kubalek, M. Whittaker, E. Pate, R. Cooke, E. W. Taylor, R. A. Milligan, and R. D. Vale. 1999. A structural change in the kinesin motor protein that drives motility. Nature. 402:778–784.[CrossRef][Medline]
14. Neuman, K. C., and S. M. Block. 2004. Optical trapping. Rev. Sci. Instrum. 75:2787–2809.[CrossRef][Medline]
15. Vale, R. D., T. Funatsu, D. W. Pierce, L. Romberg, Y. Harada, and T. Yanagida. 1996. Direct observation of single kinesin molecules moving along microtubules. Nature. 380:451–453.[CrossRef][Medline]
16. Ha, T., T. Enderle, D. F. Ogletree, D. S. Chemla, P. R. Selvin, and S. Weiss. 1996. Probing the interaction between two single molecules: fluorescence resonance energy transfer between a single donor and a single acceptor. Proc. Natl. Acad. Sci. USA. 93:6264–6268.
17. Sosa, H., E. J. G. Peterman, W. E. Moerner, and L. S. B. Goldstein. 2001. ADP-induced rocking of the kinesin motor domain revealed by single-molecule fluorescence polarization microscopy. Nat. Struct. Biol. 8:540–544.[CrossRef][Medline]
18. Funatsu, T., Y. Harada, M. Tokunaga, K. Saito, and T. Yanagida. 1995. Imaging of single fluorescent molecules and individual ATP turnovers by single myosin molecules in aqueous solution. Nature. 374:555–559.[CrossRef][Medline]
19. Peterman, E. J. G., H. Sosa, and W. E. Moerner. 2004. Single-molecule fluorescence spectroscopy and microscopy of biomolecular motors. Annu. Rev. Phys. Chem. 55:79–96.[CrossRef][Medline]
20. Peterman, E. J. G., H. Sosa, L. S. B. Goldstein, and W. E. Moerner. 2001. Polarized fluorescence microscopy of individual and many kinesin motors bound to axonemal microtubules. Biophys. J. 81:2851–2863.
21. Case, R. B., D. W. Pierce, N. HomBooher, C. L. Hart, and R. D. Vale. 1997. The directional preference of kinesin motors is specified by an element outside of the motor catalytic domain. Cell. 90:959–966.[CrossRef][Medline]
22. Svoboda, K., and S. M. Block. 1994. Force and velocity measured for single kinesin molecules. Cell. 77:773–784.[CrossRef][Medline]
23. Haustein, E., and P. Schwille. 2003. Ultrasensitive investigations of biological systems by fluorescence correlation spectroscopy. Methods. 29:153–166.[CrossRef][Medline]
24. Waterman-Storer, C. M., A. Desai, J. C. Bulinski, and E. D. Salmon. 1998. Fluorescent speckle microscopy, a method to visualize the dynamics of protein assemblies in living cells. Curr. Biol. 8:1227–1230.[CrossRef][Medline]
25. Seitz, A., and T. Surrey. 2006. Processive movement of single kinesins on crowded microtubules visualized using quantum dots. EMBO J. 25:267–277.[CrossRef][Medline]
26. Zander, C., J. Enderlein, and R. A. Keller. 2002. Single Molecule Detection in Solution. Wiley-VCH, Berlin.
27. Eggeling, C., J. Widengren, R. Rigler, and C. A. M. Seidel. 1998. Photobleaching of fluorescent dyes under conditions used for single-molecule detection: evidence of two-step photolysis. Anal. Chem. 70:2651–2659.[CrossRef]
28. Fleury, L., J. M. Segura, G. Zumofen, B. Hecht, and U. P. Wild. 2000. Nonclassical photon statistics in single-molecule fluorescence at room temperature. Phys. Rev. Lett. 84:1148–1151.[CrossRef][Medline]
29. Wahl, M., I. Gregor, M. Patting, and J. Enderlein. 2003. Fast calculation of fluorescence correlation data with asynchronous time-correlated single-photon counting. Opt. Express. 11:3583–3591.
30. Widengren, J., U. Mets, and R. Rigler. 1995. Fluorescence correlation spectroscopy of triplet states in solution: a theoretical and experimental study. J. Phys. Chem. 99:13368–13379.[CrossRef]
31. Magde, D., W. W. Webb, and E. Elson. 1972. Thermodynamic fluctuations in a reacting system—measurement by fluorescence correlation spectroscopy. Phys. Rev. Lett. 29:705.[CrossRef]
32. Kohler, R. H., P. Schwille, W. W. Webb, and M. R. Hanson. 2000. Active protein transport through plastid tubules: velocity quantified by fluorescence correlation spectroscopy. J. Cell Sci. 113:3921–3930.[Abstract]
33. Gosch, M., H. Blom, J. Holm, T. Heino, and R. Rigler. 2000. Hydrodynamic flow profiling in microchannel structures by single molecule fluorescence correlation spectroscopy. Anal. Chem. 72:3260–3265.[Medline]
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