e-Journal of Surface Science and Nanotechnology

7 December 2005

Conference - ISSS-4 -e-J. Surf. Sci. Nanotech. Vol. 3 (2005) 384-392

High-speed Atomic Force Microscopy for Capturing Dynamic Behavior of Protein
Molecules at Work∗
Toshio Ando†
Department of Physics, Graduate School of Science and Technology,
Kanazawa University, Kakuma-machi, Kanazawa 920-1192, Japan, and CREST/JST

Noriyuki Kodera
Department of Physics, Graduate School of Science and Technology,
Kanazawa University, Kakuma-machi, Kanazawa 920-1192, Japan,

Takayuki Uchihashi
Department of Physics, Graduate School of Science and Technology,
Kanazawa University, Kakuma-machi, Kanazawa 920-1192, Japan, and CREST/JST,

Atsushi Miyagi, Ryo Nakakita, Hayato Yamashita, and Keiko Matada
Department of Physics, Graduate School of Science and Technology,
Kanazawa University, Kakuma-machi, Kanazawa 920-1192, Japan(Received 7 October 2005; Accepted 17 November 2005; Published 7 December 2005)
It seems that only the atomic force microscope (AFM) has a potential to trace a protein in action with highspatial and temporal resolution. To realize that potential, we have been developing a high-speed AFM. We havemade eﬀorts not only to enhance the scan speed but also to reduce the tip-sample interaction force as much as
possible. The high-speed AFM can capture moving protein molecules and weakly interacting protein moleculeson video without disturbing their physiological function. Here we review our studies carried out over the past 10
years, and our preliminary work toward the next generation of the instrument. [DOI: 10.1380/ejssnt.2005.384]
Keywords: Atomic force microscopy; biological aspects of nanostructures; proteinsI.

INTRODUCTION

When protein is functioning in solution, its structure
is dynamically changing. The structural dynamics mustbe tightly associated with the mechanism by which theprotein produces its physiological function. It is, therefore, desirable to visualize directly the dynamic behavior
of individual protein molecules in action; however, thetechnology for direct visualization is lacking. Thus, wehave to infer their dynamic behavior from various indirect observations, which can be misleading.
The atomic force microscope (AFM) has now become
an indispensable tool for imaging and characterizing surface nanostructures in various environments. However,many users of AFM have found that capturing a single
image takes a long time. Because AFM relies on mechanical scanning of the sample stage or the cantilever, it
is diﬃcult to enhance the scan speed without producing
mechanical noises. The limited imaging rate not only imposes on AFM users’ patience but also restricts the scopeof examinable dynamics of the sample. This restriction
has discouraged biologists from studying dynamic processes of biological macromolecules using AFM, although
the capability of AFM to view a nanometer-scaled worldin an aqueous environment was a very welcome addition
to biological studies.
The tapping mode of the AFM operation [1] is most∗ Thispaper was presented at International Symposium on Surface Science and Nanotechnology (ISSS-4), Saitama, Japan, 14-17
November, 2005.
† Corresponding author: tando@kenroku.kanazawa-u.ac.jp

suitable for soft and fragile samples; the vertically oscillating cantilever tip taps the sample surface intermittently, so that lateral force exerted between the tip andthe sample can be minimized. During a raster scan of thesample stage in the horizontal plane, the cantilever’s oscillation amplitude (and hence the tapping force) is kept
constant by moving the sample stage up or down, depending on the sample height. This feedback operation
is indispensable to avoid strong tip-sample interaction.
Therefore, the scan speed (and hence the imaging rate) isdetermined not only by the scanner’s bandwidth, in which
it can operate without producing mechanical noises, butalso by the feedback bandwidth. Almost all AFM devices
are involved in the feedback loop and therefore have to be
optimized for the high-speed feedback operation.
Eﬀorts to achieve a high imaging rate with AFM havebeen, as far as we know, initiated by three groups; Paul
Hansma’s lab at UCSB, Calvin Quate’s lab at Stanford
Univ., and our group at Kanazawa Univ. The UCSB
group developed small cantilevers with a high resonant
frequency to increase their response speed [2], in addition to an optical lever system compatible with thesmall cantilevers [3]. The Stanford group developed selfactuating/sensing cantilevers [4] to overcome the slow zscan rate of the conventional tube scanner, and cantilever
arrays [5] to image a large area at once. However, theseeﬀorts alone could not lead to a high imaging rate because
other devices remained to be developed. Prior to 2001, wedeveloped various devices, including a high-speed stage
scanner, small cantilevers, an optical lever system for thesmall cantilevers, and a fast amplitude-to-DC converter
that can output the amplitude signals at every half cycle of the cantilever oscillation. By assembling these devices, we made the ﬁrst generation of high-speed AFM

c 2005 The Surface Science Society of Japan (http://www.sssj.org/ejssnt)
ISSN 1348-0391 

384Volume 3 (2005)

e-Journal of Surface Science and Nanotechnologythat could capture moving protein molecules on video at
80 ms/frame [6, 7]. However, it became clear later thatthe tip-sample interaction force was not small enough toimage fragile samples or weakly interacting proteins [8].
To overcome this serious problem we further developed
various devices and techniques [8, 9]. Now the second
generation of our high-speed AFM can capture weaklyinteracting proteins without disturbing their physiological action. In this article, we review our eﬀorts madein the past decade to achieve a high imaging rate (∼50
ms/frame) as well as our challenges as we move to thenext generation of AFM technology.

II.

error signal is saturated at (1 − r)A0 . The time required
for re-landing is roughly proportional to κ ≡ h/(1 − r)A0 .
Therefore, the feedback bandwidth is also a function of κ.
Although it is diﬃcult to obtain an analytical expression
for the function theoretically, we can obtain a quantitative expression experimentally [11]. The frame acquisition time (T ) is determined by the feedback bandwidth(f ), the scan size (L), the number of scan lines (N ), andthe apparent sample size (λ), as shown below.
T =THEORETICAL CONSIDERATIONS

III.

Sulcheck qualitatively analyzed how the feedback bandwidth in the tapping mode is aﬀected by various factors,
such as the set-point, the sample height, and the resonant
frequency and oscillation amplitude of the cantilever [10].
From the qualitative description, we cannot get a prospectof how extensively we have to improve various devices inorder to enhance the feedback bandwidth. Here we ﬁnd
a semi-quantitative description.
Suppose that a sample on a substrate has a periodicityof λ and that the sample stage is moved horizontally witha velocity of Vs , the spatial frequency of 1/λ is converted
to a temporal frequency of f ≡ Vs /λ. This is the feedback
frequency with which the sample stage is moved in the zdirection. The most rigid deﬁnition of the feedback bandwidth is the feedback frequency at which the feedback operation is phase-delayed less than 45◦ . This corresponds
to a time delay of 1/8f . The feedback loop contains various delaying steps. One of the main delays is the timerequired for reading the cantilever’s oscillation amplitude.
It takes at least a time between 1/fc and 1/2fc, where fc isthe cantilever’s resonant frequency. When the cantilever’s
amplitude changes only at the bottom of swing (where its
tip taps the sample surface), it takes 1/fc , while it takes
1/2fc when the amplitude changes at both the bottom
and peak of swing (this occurs with cantilever oscillation
with a large quality factor, Qc ). In solution, the cantileverfs amplitude changes solely at the bottom of swing
due to a large viscous drag force. The other main delays
are the cantilever’s response time (Qc /πfc ), and (3) thez-scanner’s response time (Qs /πfs ), where Qs and fs are
the quality factor and the resonant frequency of the zscanner, respectively. These delays and additional delays(the total, ∆) give the following relationship.
f<

fc /8
.
1 + Qc /π + (Qs fc )/(πfs ) + fc ∆(1)

Here we have to note that the diﬀerential operator of
the PID feedback circuit can partially compensate thephase delays. The feedback bandwidth is not determined
only by Eq. (1), but also by the sample height (h), thefree oscillation amplitude (A0 ) of the cantilever, and theset-point (rA0 ) [10]. This is because the cantilever tip end
tends to detach completely from the sample surface when
scanning over a downhill, and its tendency is aﬀected bythese factors. Once detached, the tip end cannot re-landon the surface quickly (like ’parachuting’), because the

2N L
.
λf

(2)

THE FIRST GENERATION OF
HIGH-SPEED AFM

Let us look over the tapping-mode AFM system (Fig.
1) to ﬁnd what we have to do to achieve a high imaging rate. The sample stage scanner, especially the zscanner, should move very quickly without unwanted vibrations. The cantilever’s resonant frequency should bevery high so that it responds to the tip-sample interaction
fast enough and the amplitude reading shortens. In addition, its spring constant should be minute. The dimensions of such cantilevers have to be very small. Therefore,
the optical system for detecting the cantilever deﬂection
should be compatible with such small cantilevers. The
split photosensor should have a wide bandwidth, and theRMS-to-DC converter should quickly output the rms signal. The PID feedback circuit should operate quickly; in
addition, the piezo drive ampliﬁers should have a wide
bandwidth and should be able to produce a large current. The data acquisition system has to work very fast.
As surveyed above, we have to optimize many devices
to produce a high-speed AFM. For about 5 years prior
to 2001, we developed all the devices and constructed ahigh-speed AFM capable of capturing one image (scansize, 250 nm; scan lines, 100) within 80 ms [6, 7]. Below,
we brieﬂy describe key devices that mainly contributed tothe achievement of the high imaging rate.
Sample stage scanner: The device most diﬃcult todevelop was the sample stage scanner. We used stackpiezo actuators with the resonant frequency of 260 kHz
in free oscillation and with the maximum displacement of
4.5 µm. Three actuators were aligned perpendicularly toeach other; the y-piezo displaces a base where the x-piezo
is mounted, and the x-scanner displaces a base where thez-scanner is mounted. To reduce vibrations, the latterbase was clamped tightly between two ball-guide stages.
However, this clamping was not suﬃcient to minimize vibrations. Quick displacements of the z-piezo exerted impulsive forces on the base, causing vibrations of the base,and in turn vibrating the z-piezo itself. Thus, an additional z-piezo was attached to the opposite side of thebase. The impulsive forces were counteracted by the simultaneous displacements of the two z-piezo actuators of
the same length, in the counter direction. This counterbalance method was very eﬀective in minimizing vibrations. The z-scanner had a nearly constant gain up to 60
kHz [6, 7].
Small cantilevers: Olympus made small cantilevers
without tips from silicon nitride [6]. The dimensions were

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FIG. 1: Schematic presentation of the tapping-mode AFM system.

140 nm thick, 2 µm wide, and 9 µm long. The resonant frequencies were around 1.5 MHz in air and about
600 kHz in water, and the spring constant was about 150
pN/nm. The tips were grown by electron-beam deposition. As indicated in Eq. (1), the resonant frequency ofthe cantilever determines the upper limit of the feedback
bandwidth to be 600/8 = 75 kHz.

Amplitude-to-DC converter: Conventional RMSto-DC converters require at least a few numbers of wavesof the input signal to output an accurate rms value. To
increase the conversion rate, we developed an amplitudeto-DC converter using two sample/hold (S/H) circuits [6].
The peak and bottom voltages of the every input sinusoidal wave were held by the S/Hs, and their diﬀerence
generated the amplitude signal. Therefore, the amplitude
signal is renewed at every half cycle of the input signal.

By assembling these devices and other devices, we constructed a high-speed AFM mounted on an inverted typeof optical microscope. Using this AFM, we succeeded in
capturing myosin V molecules moving in solution on video
at 80 ms/frame [6]. This was the ﬁrst anyone has viewed
a rapidly moving protein in solution with nanometer resolution.
386

IV.

SECOND GENERATION OF HIGH-SPEEDAFM

We later noticed that our high-speed AFM could not
capture fragile samples such as microtubules without disassembling them [8]; still less is it possible to capture
weakly interacting protein molecules such as actin-myosin
V in the presence of ATP, without disturbing their interaction. The large tip-sample interaction seemed due toan insuﬃcient feedback bandwidth and a too-strong tapping force. Therefore, in 2002 we began making further
improvements to the small cantilevers, the scanner, andthe feedback control.
Smaller cantilevers: Smaller cantilevers (Fig. 2)
with a resonant frequency higher than the previous version were developed to enhance the feedback bandwidth[12]. The dimensions are 7 µm long, 2 µm wide, and 90
nm thick. The resonant frequencies are about 2.4 MHz in
air and about 1.2 MHz in water, and the spring constantis about 200 pN/nm. Although the cantilevers have birdbeak like tips, their apex is not sharp enough. Therefore,
EBD tips were grown on the bird-beak like tips.
Dynamic PID controller: To reduce the tapping
force, we needed small cantilevers with a smaller spring
constant. However, it was very diﬃcult to make it compatible with the high resonant frequency. The other way
to reduce the tapping force was to adjust the set-point of

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FIG. 2: Electron micrographs of the small cantilever chip with a birdbeak-like tip. (a) Top view; (b) a magniﬁed image of the
tip region. The protruding needle is an EBD tip.

FIG. 4: Sketches of the high-speed scanner. (a) 3D view,(b) top view, and (c) side view. The green blocks are piezo
actuators. A sample stage is attached on the top of the upper
z-piezo actuator, and a dummy stage is attached on the topof the lower z-piezo actuator used for counterbalancing. The
dimensions (W × L × H) of the x-, y-, and z-actuators are
2 × 3 × 5, 5 × 5 × 10, and 2 × 3 × 3 mm3 , respectively.

FIG. 3: Schematic presentation of the dynamic PID control technique. (a) Amplitude-distance curve (red line) andschematic outline of the dynamic PID control technique. A0denotes the free oscillation amplitude of the cantilever, andAsp denotes the set-point. The black dotted lines represent
the false error signals added to the true error signals. (b) A
diagram of the dynamic PID circuit.

the cantilever oscillation very close to its free oscillation
amplitude. However, this adjustment results in a narrower feedback bandwidth, as mentioned in ’Theoretical
Considerations’. With a large set-point, the parachuting period is prolonged because the PID circuit produces a small feedback signal that is proportional to thesaturated-error signal, i.e., (1 − r)A0 (where r is smaller

than 1, but very close to 1). To overcome this diﬃculty,
we developed a new PID controller whose gain can automatically be changed depending on the error signal (Fig.
3) [8, 11]. A threshold level is set between rA0 and A0 .
When the cantilever oscillation amplitude exceeds thisthreshold level, a false error signal is added to the trueerror signal. The resulting large error signal produces alarge feedback signal, which reduces the parachuting period or prevents the cantilever tip from getting into theparachuting phase. This dramatically enhances the feedback bandwidth at a large set-point (r > 0.8). A similar
manipulation of the error signal is applicable also to thecase where the cantilever oscillation amplitude becomesmuch smaller than the set-point. This is eﬀective in preventing the cantilever tip from hitting the sample or thesubstratum too strongly.
High-speed scanner: We simpliﬁed the scanner design to reduce the number of resonant peaks as well as
to increase the rigidity. Instead of the ball-guide stages,
we employed a ﬂexure stage (Fig. 4). In addition, we
employed stack piezo actuators with a higher resonant
frequency (470 kHz) for the z-scanner (the resonant frequency decreased to 150 kHz when they were embedded

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FIG. 5: A schematic of the active damping method. The feedback signal (output from the PID controller) is fed to the active
Q-control circuit. The transfer function of the LCR circuits (mock z-scanners) is adjusted so as to become very similar to thez-scanner. The mock z-scanners can contain a number of LCR circuits corresponding to the multiple resonant components ofthe z-scanner.

FIG. 6: Eﬀect of the active damping on the resonance of thez-scanner. The curves are resonant gains with (blue line) andwithout (red line) operation of the active damping.

into the scanner). We again used the counterbalancemethod to minimize the structural resonance in the zdirection. Here, we made eﬀorts to eliminate the resonance originating in the z-piezo actuator itself that could
not be removed by the counterbalance [9]. In principle, it is possible to damp the resonant vibrations using
a so-called active Q control of the vibrations. In thiscontrol, the displacement signal of the z-piezo actuatoris diﬀerentiated, and its polarity is inversed. Then, its
gain-controlled signal is added to the driving signal. Thisaddition apparently increases the damping (or frictional)
force, resulting in the reduction of the quality factor of
the z-piezo resonance. However, in practice it is diﬃcult to monitor the quick and unpredictable displacementof the z-piezo actuator during scanning. On the other
hand, the dynamic behavior of the z-piezo is determinedby its transfer function. We noticed that this transfer
function was well approximated by a transfer function of
a second-order low-pass ﬁlter that can be made simply by
an LCR circuit. Therefore, it is possible to use, as a mockz-piezo, the second-order low-pass ﬁlter that is tuned tohave the transfer function very similar to that of the z388

piezo (Fig. 5). This technique is also useful in eliminating
the remaining small resonant vibrations originating in thescanner structure. As shown is Fig. 6, the resonant vibrations of the z-scanner were eliminated by this active
damping method. Because the quality factor of the zscanner’s peak resonance was reduced from 18 to 0.5, its
response speed was increased 36 times (the response time,∼1.1 µs). Although the phase delay was pronounced by
the active damping, it was suppressed by inverse transfer
function compensation [9].
Because of the improvements mentioned above, thefeedback bandwidth was enhanced up to 100∼110 kHz
under the conditions of r = 0.6 ∼ 0.9 and A0 /h = 2 ∼ 5.
Even with r = 0.95 and A0 /h = 2 ∼ 5, the feedback
bandwidth was around 80 kHz [11]. This small dependence of the feedback bandwidth on the set-point (duemainly to the eﬀect of the dynamic PID control) guarantees that imaging can be carried out with a weak tapping
force. According to Eq. (2), the wide feedback bandwidth promises the imaging rate of ∼50 ms/frame under
the conditions of N = 100, L = 250 nm, and λ =10 nm.

V.

BIOIMAGING

Here, we show some examples of the image data obtained by the high-speed AFM. However, these images
were not obtained after completing the second generationof AFM, but most were obtained during this development.
Therefore, the imaging rates used are mostly not the maximum rate that has now become available.
The ﬁrst data show how small the tip-sample interaction force is. The interaction between actin ﬁlaments andmyosin V in the presence of ATP is highly dynamic andhence very weak. Actin ﬁlaments move over a surface thatis coated densely with myosin V molecules. This movement was successfully captured on video, without disturbing their weak interaction (Fig. 7a, Movie 1 in Electronic
Appendix). The velocity of actin ﬁlament gliding was very
similar to that observed by ﬂuorescence video microscopy.
To view the dynamic behavior of individual myosin V
molecules when they are propelling actin ﬁlaments unidirectionally, the surface was sparsely coated with myosin

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FIG. 7: Successive AFM images of various samples. The numbers attached indicate the frame numbers. Corresponding AFM
movies can be viewed at Electronic Appendix. (a) Actin ﬁlaments that are sliding over the myosin V-coated mica surface in thepresence of ATP. The scan range, 1 m; the scan speed, 1s/frame. (b) Myosin V that is propelling sliding movement of a shortactin ﬁlament in the presence of ATP. The distance between the adjacent bumps of the actin ﬁlament is 36 nm. The frame
rate is 160 ms/frame. (c) The left panel is a schematic drawing of dynein C. The stem stays mainly at the position as shown in
the frames 51 and 64 (corresponding to the non-nucleotide-bound state), and occasionally moves to the position shown in theframe 63 (corresponding to the nucleotide-bound state). Scale bar, 30 nm. (d) GroES binding to GroEL just after ATP releaseby ﬂash-photolysis of caged-ATP. UV ﬂash light was applied shortly before the frames marked with ’F’. Scale bar, 100 nm.

V. A short actin ﬁlament whose entire length was within
the imaging region was observed (Fig. 7b). This fortunate situation allowed us to identify which myosin V
molecules were propelling the actin ﬁlament. Two myosin
V molecules were interacting with the short actin ﬁlament, and only one of the two heads of each myosin V
molecule was attached to the actin ﬁlament. The actin
ﬁlament moved leftward in a stepwise manner (Movie 2
in Electronic Appendix); the step size was 36 nm, whichcorresponds to half of the long helical repeat of an actin
ﬁlament. During the stepwise movement, the interacting heads did not seem to change their conformations
much, which was not the behavior expected from the wellstudied swinging-lever arm hypothesis in which a large
swinging movement of myosin’s neck domain is supposed
to propel the actin ﬁlament [13].
Dynein C is a single-headed dynein. A stalk and astem protrude from the ring-shaped head (Fig. 7c), andthe stalk interacts with microtubules at the globular distal end. Electron micrographs of dynein C have revealed
that the angle between the stalk and the stem diﬀered
between the apo state (no-nucleotide) and the ADP-Vi-bound state [14]. The nucleotide-dependent change in the
structure is hypothesized to drive microtubule movement.
However, ADP-Vi is a non-natural substrate, and therefore it is not certain that such a change of angle reallyoccurs during the ATPase cycle. High-speed AFM imaging of dynein C in the presence of ATP revealed that it
did certainly occur. The stalk and the head seemed stationary, but the stem went back and forth between two
positions (Fig. 7c, Movie 3 in Electronic Appendix). The
stem-stalk angle changed between 137◦ and 184◦ ; the former angle corresponds to the apo state, while the latter
was larger than that of the ADP-Vi-bound state (159◦ ).
The frequency of the change in angle approximately coincided with the ATPase rate. Therefore, it is very certainthat the stem movement observed is driven by the ATPasereaction. This is the ﬁrst time that a cyclic protein’s conformational change has been captured on video in realtime.
The UV-photolysis of caged ATP [14] was applied to
the GroEL-GroES system [15]. GroEL is a chaperoninthat assists its substrate polypeptides in folding into theirfunctional 3D structures, and GroES is a co-chaperonin.

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FIG. 8: Pseudo AFM images constructed from the atomic structure of myosin V subfragment-1. The pseudo AFM images areshown on the upper line, and their corresponding appearances of the atomic model viewed from the same angles are shown on
the lower line. The atomic model is rotated around a horizontal axis, and the number attached to each panel indicates therotation angle.

GroEL consists of two homo-heptameric rings that arestacked back-to-back, whereas GroES is a single homoheptameric ring. GroES binds to GroEL only when
GroEL is in the nucleotide-bound state. GroEL was attached to the mica surface with an end-up orientation,
forming a highly packed single layer. The central channel of the GroEL ring was therefore visible. Before UV
application, GroES was ﬂoating in the solution containing caged-ATP, and therefore not visible. High-frequency
pulses of a UV laser light (355 nm) were applied within
5 ms while the y-return scanning was performed. Immediately after this, GroES attached to the top of GroEL,
forming protrusions on the GroEL layer (Fig. 7d, Movie
4 in Electronic Appendix). Because the concentration of
the ATP that was produced in the small UV-irradiatedvolume quickly fell due to diﬀusion, the second application of the UV pulses resulted in more protrusions.
The last image data of myosin V alone were obtained after completing the second generation of high-speed AFM.
The frame rate reached about 50 ms/frame (Movie 5 inElectronic Appendix). With a higher rate, the scanner
produced vibrations in z-direction because of the low resonant frequency of the x-scanner. We are now improving
the x-scanner.
When dynamic behavior of a protein with a known
atomic structure is captured on video, is it possible tounderstand the dynamic behavior in light of the atomic
structure? When a protein does not have a unique shapeat a few-nanometer resolution, it is diﬃcult to understandfrom the video image which face of the molecule is imaged,
which part is bending or twisting, and so on. As a ﬁrst
step for understanding these aspects, we have been trying to ﬁt an AFM image of myosin V subfragment-1 on
mica to its atomic structure. The ﬁtting procedures are
as follows. First, we obtain the surface coordinates of theatomic model. Next, considering the eﬀect of the radius
and the corn angle of the cantilever tip on the AFM image
formation, we construct a library of many pseudo AFM
images, looking at the atomic model from various angles(Fig. 8). We compare a top-view (2D proﬁle) of an AFM
image with those of the pseudo AFM images to choose anumber of ﬁt candidates. Then, we compare the 3D proﬁle of the AFM image with those of the chosen candidates390

to ﬁnd the best-ﬁt pseudo AFM image. The three candidates chosen by the 2D-proﬁle ﬁtting resemble to eachother (the right upper panels of Fig. 9). The 3D-proﬁleﬁtting gave the best score of ﬁtting to the one shown in thecolumn ”1”. This result seems reasonable, because myosin
V subfragment-1 in the best-ﬁt orientation has a clusterof positive charges on the backside, which must facilitate
its binding to the negatively charged mica surface. In
these procedures, we have not considered conformationalchanges of the protein. However, it is likely that the entire
conformation does not change but the relative orientation
between the domains does (thus, each domain conformation is rather unchanged). Therefore, to include a possible
conformational change in the ﬁtting procedures, we may
have to divide an AFM image of a protein molecule into
two or three domains and ﬁt them separately. Of course,
for this ﬁtting to be successful, the high-resolution AFM
images are required. If we have a rational way to distort
the atomic model, it would become possible by using theﬁtting results to construct a dynamic atomic model thatreﬂects the dynamic behavior of the protein recorded on
the AFM video.

VI.

TOWARD THE NEXT GENERATION

Although third-generation AFM is not yet complete,here we brieﬂy mention how we have been working toward the third generation of our high-speed AFM. To
enhance the feedback bandwidth, it is important to increase the resonant frequency of the z-scanner, but available piezoactuators are limited. We estimate that theachievable maximum resonant frequency of a piezo-stage
scanner will be limited to be about 300 kHz, only twicethat of our z-scanner. Self-actuating cantilevers are analternative to the piezo-stage scanner, but a cantileverwith an integrated zinc oxide piezoactuator inevitably becomes too stiﬀ. Driving a cantilever coated with a thinmagnetic ﬁlm directly by a magnetic ﬁeld is also an alternative [16]. However, a magnetic-ﬁlm coating suﬃcient for the cantilever to be driven reduces the resonant frequency of the cantilever. To drive a cantilever
by a diﬀerent means, we measured the cantilever deﬂec-

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FIG. 9: Fitting of an AFM image of myosin V subfragment-1 to the pseudo AFM images. Column 0 shows a top view (upper
panel) and a 3D view (lower panel) of the AFM image. Columns 1, 2, and 3 show pseudo AFM images (upper and middle lines)
and corresponding appearances of the atomic model viewed from the three angles (lower line). These three give good scores on
the ﬁtting test of the 2D proﬁles. Column 1 gives the best score on the ﬁtting test of the 3D proﬁle.

tion caused by photo-thermal expansion of gold coatedonto a Si3 N4 cantilever surface [17]. The sensitivity was
about 10 nm/mW in aqueous solution when a 405-nm violet laser was used with our small cantilevers. Because of
the slow heat-transmission process, the response time ofthe deﬂection was about 30 µs. However, inverse transfer function compensation was apparently able to eliminate the slow heat-transmission process [17]. Because themaximum displacement of the cantilever driven by photothermal expansion is so far limited, and the ”cantilever
scanner” requires a large dynamic range of the deﬂection
detection sensor (which reduces the sensor sensitivity),
it is apparent that this technique has to be used together
with the conventional piezo-stage scanner. Photo-thermal
expansion can also be used to directly excite a cantileverat its resonant frequency [17, 18]. Unlike acoustic excitation, it does not have the ”forest of peaks” eﬀect. This
superior attribute facilitates the active control of the cantilever to reduce Q, which enhances the response speed of
the cantilever (and hence the feedback bandwidth).
Another device that we have been trying to include in
the third generation of our high-speed AFM is a feedforward controller [19]. Topographic diﬀerences between
two adjacent line-scans are not large, as long as the sample is not moving rapidly. Therefore, line-by-line feedforward control can lighten the feedback-control task; inother words, the dependence of the feedback bandwidthon κ (see Section ’Theoretical Considerations’) is reducedby the feed-forward control. Using stationary samples,
we conﬁrmed that a signiﬁcant extension of the feedback
bandwidth was achieved by the feed-forward control [18].

However, when the sample is moving quickly, the feedforward control is expected to act occasionally in an undesirable direction. Yet, we have not noticed any ill eﬀect
that would be expected to result from such an undesirable
action, even with rapidly moving samples. This may be
due to a small time-diﬀerence (less than 1 ms) between
two line-scans.

VII.

CONCLUSIONSThe second generation of our high-speed AFM has thecapacity to dissect dynamic processes of individual protein molecules at work. The compatibility of the highscan rate and a skimming scan over fragile samples has
been successfully achieved. The scan rate has reached alevel where video-rate imaging is almost possible. The
tip-sample interaction force is greatly reduced to a level
where it does not disturb weak protein-protein interactions.

Acknowledgments

This work was supported by CREST/JST, Special Coordination Funds for Promoting Science and Technology(Eﬀective Promotion of Joint Research with Industry,
Academia, and Government) from JST, and a Grant-inAid for Basic Research (S) from the Ministry of Education, Sports, Science, and Technology of Japan.

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