Methods 207 (2022) 44–56

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Methods
journal homepage: www.elsevier.com/locate/ymeth

Guide to studying intrinsically disordered proteins by high-speed atomic
force microscopy
Noriyuki Kodera, Toshio Ando *Nano Life Science Institute (WPI-NanoLSI), Kanazawa University, Kakuma-machi, Kanazawa 920-1192, JapanA R T I C L E I N F O

A B S T R A C T

Keywords:
Intrinsically disordered proteins
Dynamic structureHigh-speed AFM
Bioimaging

Intrinsically disordered proteins (IDPs) are partially or entirely disordered. Their intrinsically disordered regions(IDRs) dynamically explore a wide range of structural space by their highly flexible nature. Due to this distinct
feature largely different from structured proteins, conventional structural analyses relying on ensemble aver­aging is unsuitable for characterizing the dynamic structure of IDPs. Therefore, single-molecule measurement
tools have been desired in IDP studies. High-speed atomic force microscopy (HS-AFM) is a unique tool that allows
us to directly visualize single biomolecules at 2–3 nm lateral and ~ 0.1 nm vertical spatial resolution, and at sub100 ms temporal resolution under near physiological conditions, without any chemical labeling. HS-AFM has
been successfully used not only to characterize the shape and motion of IDP molecules but also to visualize theirfunction-related dynamics. In this article, after reviewing the principle and current performances of HS-AFM, we
describe experimental considerations in the HS-AFM imaging of IDPs and methods to quantify molecular featuresfrom captured images. Finally, we outline recent HS-AFM imaging studies of IDPs.

1. Introduction
Many proteins contain intrinsically disordered regions (IDRs) lacking
stable secondary and tertiary structure. And yet, they can carry out
biological functions. These proteins, called intrinsically disordered
proteins (IDPs), are involved in a variety of cellular processes, such as
signaling and regulation of transcription, translation and cell cycle [1,2]as well as the formation of liquid droplet-like membrane-less organelles(MLOs) [3,4]. IDRs are highly flexible and dynamic; the amino acidresidues in an IDR responsible for intramolecular interactions and target
binding are widely distributed in space and time. This highly flexible
nature facilitates weak but frequent intramolecular interactions be­
tween distantly separated regions within an IDP. The flexibility also
facilitates the structural adaptation of an IDP to a binding partner, andhence, enables multiple targets binding and multiple functions [5]. The
IDPs’ functional and regulatory manners are therefore distinctly
different from those of structured proteins. Hence, IDPs can execute
unique biological functions unattainable with structured proteins. As
such, characterizing the dynamic structure of IDPs is essential forunderstanding the mechanisms underlying their function andregulation.
However, this characterization is considerably difficult because oflack of experimental methods that can delineate and quantify the dy­
namic structure of IDPs. In ensemble averaging methods, such as nuclear
magnetic resonance (NMR) spectroscopy and small angle X-ray scat­tering (SAXS), individual conformers and their populations can only be
examined by relying on structural and/or ensemble modeling [6–8].
Moreover, NMR can hardly distinguish between fully disordered andloosely folded IDRs, and SAXS can hardly detect short-lived structures.
Although the single-molecule Förster resonance energy transfer method
can probe the structural heterogeneity and kinetics of IDPs, the struc­tural information is limited to the distance between two intramolecular
residues separated by less than 10 nm [9]. Molecular dynamics simu­
lations can derive ensembles of disordered structures at the atomic level[10,11]. However, validating the simulated results is difficult because
the corresponding experimental information is limited. Therefore, thelack of experimentally obtainable dynamic structural information due tothe absence of appropriate methods has hampered our understanding ofAbbreviations: IDP, Intrinsically dissordered protein; IDR, Intrinsically disordered region; AFM, Atomic force microscopy; HS-AFM, High-speed atomic force
microscopy; NMR, Nuclear magnetic resonance; SAXS, Small angle X-ray scattering; FACT, Facilitates chromatin transcription; MLO, Membrane-less organelle; LLPS,
Liquid–liquid phase separation; PID, proportional-integral-derivative; MBP, Maltose binding protein; Trx, Thioredoxin; GFP, Green fluorescent protein; GST,
Glutathione S-transferase; HMG, high-mobility-group; LCD, low complexity domain.
* Corresponding author.
E-mail address: tando@staff.kanazawa-u.ac.jp (T. Ando).
https://doi.org/10.1016/j.ymeth.2022.08.008
Received 4 May 2022; Accepted 16 August 2022
Available online 30 August 2022
1046-2023/© 2022 Elsevier Inc. All rights reserved.

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Methods 207 (2022) 44–56

the functional and regulatory mechanisms of IDPs.
In contrast to these methods, high-speed atomic force microscopy(HS-AFM), a recently emerged microscopy technique, can directly
visualize the dynamic structure of single molecules at sub-molecularspatial and sub-100 ms temporal resolution, without any labeling[12,13]. In 2008, it was demonstrated for the first time that HS-AFM candirectly visualize the thin structure of IDRs in dynamic motion, using amodel protein, facilitates chromatin transcription (FACT) protein [14],although the performance of HS-AFM at the time was lower than that of
the current version. Since then, HS-AFM has been used to observe IDPs.
The filmed images have successfully quantified dynamic structural fea­tures of several IDPs [15–20]. In addition, function-related phenomenaof IDPs have also been visualized by HS-AFM. For example, the pepti­
doglycan layer binding domain of MotPS, a stator ring of the sodium-ion
driven bacterial flagellar motor, was observed to undergo a structuraltransition from the unfolded to the folded state when exposed to sodium
ions [21]. Moreover, the following phenomena were also observed: thecross-β polymerization of α-synuclein and Sup35 [22,23], the assembly
process of translation factors around the ribosomal stalk complex [24]and the formation of the droplet-like autophagy initiation complex byliquid–liquid phase separation (LLPS) [25]. In the following sections, wefirst overview the principle and performances of HS-AFM, and thendescribe experimental considerations for HS-AFM imaging of IDPs aswell as methods to quantify structural features of IDPs from filmed im­ages. Finally, several HS-AFM studies on IDPs are outlined.

photodiode. The output signals from the photodiode are converted to an
amplitude signal. Then, a deferential signal (error signal) between thedetected amplitude and a preset amplitude value (i.e., the feedback set
point amplitude) is fed into to a proportional-integral-derivative (PID)
feedback controller. The output signal from the feedback controller issent to a Z-piezo driver to move the Z-scanner (and the sample stage) in
the Z-direction so that the error signal approaches zero. This series ofoperations are continuously repeated at different points on the sample
surface during lateral (XY) scanning of the sample stage. As a result, thesample surface topography can be reconstructed from the recorded
feedback controller output.
To materialize HS-AFM, all the mechanical and electronic compo­
nents have been optimized for fast scanning in the XYZ directions(especially in the Z-direction) and for the fast response and detection of
cantilever oscillation amplitude (Fig. 1b). To perform HS-AFM imaging
for fragile biomolecules, the feedback control speed should be highenough so that the tip-disturbance to the sample can be minimized. As
characteristic devices in HS-AFM, the following instrumental compo­
nents and techniques have been developed: small cantilevers with asmall spring constant (kc) and a high resonance frequency (fc) [12], an
optical beam deflection detection system specialized for small cantile­vers [12], a high-speed amplitude detector [12], a dynamic PID feed­back controller with an automatic gain control capability [29], highspeed scanners [12], and active vibration damping techniques for thescanners [30]. Details of the instrumental development are described
elsewhere [31]. For more comprehensive descriptions of the funda­
mentals, techniques and biological applications of HS-AFM, a book isavailable [32].

2. Performance of high-speed AFM
2.1. Principle of high-speed AFM

2.2. Temporal resolution of high-speed AFM

The principle and the system configuration of HS-AFM are basicallythe same as those of conventional AFM but the instrumental components
are optimized for fast imaging. In brief, AFM captures the topographic
images of a sample surface by tracing the surface with a tip attached to
the free end of a micro cantilever (Fig. 1a). Therefore, AFM cannot
observe the interior structure of the sample. Moreover, AFM cannot
observe objects floating in solution, and therefore, the target objects
generally have to be placed on a substrate surface. For fragile biologicalsamples, the amplitude modulation mode is usually used [26–28], inwhich the cantilever oscillates in the Z direction at around its resonancefrequency. Therefore, the tip makes intermittent contact with the sample
surface, which reduces the cantilever oscillation amplitude. The canti­
lever deflection is monitored by the laser light reflected back from thecantilever, which is guided to a position-sensitive (bi-cell or quadrant)

As mentioned above, the speed performance of an AFM system isdetermined by the feedback control speed represented by the feedback
bandwidth, fB. It is defined by the feedback frequency at which π/4phase delay occurs in tip-tracing of the sample surface topography. The
minimum time to acquire an image Tmin, namely the temporal resolu­
tion, depends on the imaging conditions (the number of scan lines, N;
the scan range in the X-direction, W), the smallest sample surface
corrugation to be observed (σ) and the sample fragility, and given as
Tmin =πNW,
2σθmax fB

where θmax is the maximum possible phase delay in tracing the sample

Fig. 1. Principle of AFM and high-speed AFM system. (a) Schematic showing the principle of AFM imaging. (b) Diagram of high-speed AFM system.
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Fig. 2. Procedure of sample deposition on bare mica surface (from a to f).

surface at which the resulting excessive force exerted from the tip does
not disturb the biological function of the sample [33]. Using the image
acquisition time per frame T (≧ Tmin), the tip velocity Vtip at a given
scanning condition is obtained as Vtip = 2NW/T. fB is usually affected by
a combination of other parameters (i.e., the cantilever free oscillation
amplitude, the feedback set point amplitude and the sample height).
However, these parameters do not have a large effect on fB (hence onTmin) in the observation of IDPs because the molecular height of IDPs isgenerally low, comparable to or smaller than the cantilever oscillation
amplitude (1–2 nm). The current HS-AFM system has achieved fB = 110
kHz for low height samples. Although θmax depends on the sample
fragility, it is typically ~ π/9 for proteins, according to previous imaging
studies on structured proteins [34]. For example, under the conditions of
fB = 110 kHz, W = 80 nm, N = 80, θmax = π/9, and σ = 5 nm, Tmin
becomes ~ 50 ms, corresponding to an imaging rate of ~ 20 frames per
second (fps). In addition, as described below, it has been confirmed thatsome IDPs with σ ≈ 2 nm can be imaged without deteriorating theirmorphological and dynamic features even under observation conditions
where θmax probably exceeds π/9 [19]. This is largely due to the very low
height of IDRs, corresponding to the diameter of a single polypeptide
chain.

When observing IDPs with fully unfolded IDRs, the use of small canti­
levers with a slightly larger spring constant (e.g., BL-AC7DS-KU2,
Olympus, Japan, kc = 0.2–0.3 N/m or USC-F1.2-k0.6, NanoWorld,
Switzerland, kc = 0.6 N/m) compared to that of frequently used ones (e.
g., BL-AC10DS-A2, Olympus, kc = 0.1 N/m or USC-F1.2-k0.15, Nano­
World, kc = 0.15 N/m) reduces the thermal fluctuation noise, making iteasier to visualize fully unfolded IDRs. In addition, the Z-scanner should
be constructed by using a piezo actuator having a small piezoelectric
constant (i.e., small displacement per applied voltage). This is effective
in reducing the mechanical noise in the Z-direction because the Zscanner can be driven with much larger voltage compared to electricalnoise. For example, NAC2012 (Noliac, Denmark), PL033.3x (PI, Ger­many), and PA4JE (Thorlabs, U.S.A.) with dynamic piezoelectric con­stants below 20 nm/V are useful. By combining such cantilevers and Zscanners, spatial resolution of ~ 0.1 nm can be routinely achieved in theZ-direction.
Importantly, an AFM image inherently has time differences between
pixels. Namely, all pixel data contained in an image are not acquired at
the same time but at different times during lateral scanning of thesample stage. Therefore, slow scanning for a fast-moving object results
in an image showing a blurred object shape and hence low spatial res­olution. Therefore, it is clear that the speed performance of AFM isessential for clearly resolving the flexible shape and motion of IDPs. In
the fast imaging study of FACT protein, it was demonstrated that its IDRs
are not visible at 1 fps, only slightly seen at 2 fps, can be seen with their
end regions being blurred at 5 fps, and can be clearly seen for the entire
length at 10 fps. Therefore, an imaging capability of at least 5 fps isrequired for a HS-AFM system. HS-AFM systems are now commerciallyavailable, from RIBM (model SS-NEX), Bruker-JPK (model NanoRacer),and Oxford Instruments (model Cypher VRS1250). Although the speed
performances of these products are described in their advertisements, it
is highly recommended to check their speed and other performances bydemonstration imaging of your own samples.

2.3. Spatial resolution of high-speed AFM
The spatial resolution of HS-AFM in the XY direction is typically 2–3
nm and ~ 1 nm in the best case, which is largely dependent on the
cantilever’s tip size. Some commercially available cantilevers for HSAFM have a sharp tip with a radius less than 5 nm (e.g., USC-F1.2k0.15 or USC-F1.2-k0.6, NanoWorld, Switzerland), but they become
blunt after use, due to smearing.
To obtain a sharp tip, we fabricate a tip by spot deposition of electron
beam onto the original tip in an atmosphere of gas supplied from sub­limate ferrocene crystals in the chamber of a scanning electron micro­
scope [35]. The fabricated tip length is 0.5–1 μm and the tip end radius isabout 25 nm. The tip end is sharpened by radio-frequency plasma
etching (Tergeo, PIE Scientific, U.S.A.) in argon gas atmosphere (Directmode, 10 sccm, and 20 W for 1.5 min). After plasma etching, the tip end
radius becomes typically ~ 4 nm.
The spatial resolution in the Z-direction is affected by the cantilever’s
thermal fluctuation and the mechanical vibration noise of the Z-scanner.

3. Procedures for High-speed AFM imaging of IDPs
Procedures for HS-AFM imaging of protein molecules have been
described in [36]. Here we mainly describe procedures specific to theimaging of IDPs.

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3.1. Precautions for high-speed AFM imaging of IDPs

3.2. Dilution of IDP samples

For successful imaging of IDPs with HS-AFM, there are several pre­cautions to keep in mind. Generally, IDPs are more easily degraded byproteases than structured proteins. Sample preparations should prevent
protease contamination as much as possible, and protease inhibitors
should be added during sample preparation and storage. Similar to thecase of observing structured proteins by HS-AFM, IDP samples should behomogeneous as much as possible. Also, the buffer solutions used forsample dilution and observation should be clean enough. This is because
AFM cannot distinguish and identify molecular spices from their topo­
graphic features, unless the target object has unique structural features.
Generally, each sample should be detected as a single band in SDS
polyacrylamide gel electrophoresis. When only IDP molecules deposited
on a substrate surface are to be observed, the amount of the sample
required for a sufficient number of experiments (>20 times) is about 20
μl with a concentration of about 1 μM. For an experiment that requires
IDPs be present at a certain concentration in the bulk solution (e.g., in
the observations of liquid droplet formation from IDPs), the required
amount can be estimated by taking into account the volume of the liquidcell (50–100 μl), the required sample concentration, and the number ofexperiments.
The substrate surface to be used in HS-AFM observations should beflat enough. Because the mean height of a fully unfolded IDR is ~ 0.5
nm, the substrate surface should be atomically flat. Practically, baremica is probably the only choice that meets this requirement and an
additional requirement, high hydrophilicity. Chemical modification of
mica with silane is often useful for observing structured proteins, but it
increases the surface roughness. The mica surface is negatively charged.
Therefore, most proteins can bind to the surface; even negatively
charged proteins can bind to the surface via divalent cations. However,
the affinity of fully disordered IDRs for mica is very weak because thelocal contact area density is very small and distantly separated portions
within an IDR behave almost independently of each other due to its highflexibility (its persistence length is ~ 1.18 nm on mica [19]). Therefore,
IDPs consisting of only IDRs often diffuse on mica too fast to be visu­
alized even with the current HS-AFM. To slow down the diffusionalmotion, the solution conditions (i.e., ionic strength, pH, and the sort ofions) have to be optimized. Alternatively, a protein tag (e.g., MBP:
maltose binding protein, Trx: thioredoxin, GFP: green florescent protein,or GST: glutathione S-transferase) or a His-tag (when a mica surface
treated with nickel ions is used [20]) can be fused to the N- or C-ter­minus of IDPs. When one end of such an IDP is anchored to the surface,
the diffusional motion of the rest portion of the molecule is largely
slowed down.
The precautions for HS-AFM imaging of IDPs are summarized asfollows:

All buffer solutions should contain protease inhibitors (e.g., 1 mM
PMSF, 0.5 mM benzamidine, or 20 μg/ml TPCK) and be cooled on ice
before use. The sample tube to be used for diluted sample storage should
be a low protein binding type (e.g., 72.704.600, Sarstedt, Germany),although this remedy does not completely prevent sample loss. The
sample diluted to a few nM should be placed on ice and used up within
15 min to avoid sample loss and possible proteolysis. The dilution of an
IDP sample is performed as follows:
1. Dilute a stock IDP solution (usually in the order of ~ 10 μM) to
100–200 nM with an appropriate buffer solution.
2. Divide the diluted sample into small aliquots (10–20 μl) using a low
protein binding tube. Then, quickly freeze the aliquots using liquid
nitrogen and store them in a deep freezer at –80 ◦ C.
3. Just before AFM experiments, thaw an aliquot of the frozen sample
and place it on ice. The thawed aliquot should be used up in a day.
4. Dilute the thawed sample to 1–5 nM with an appropriate buffer so­lution using a low protein binding tube. Then, place the tube on ice.
This step should be done between the steps 2 and 4 described inprocedure 3.3.
3.3. Deposition of IDP sample on mica surface
The deposition of an IDP sample on bare mica should be done
immediately after sample dilution to 1–5 nM. Therefore, the step 4 ofprocedure 3.2 should be done between the steps 2 and 4 of the proceduredescribed below. It is very important to avoid drying of the deposited
sample solution. Otherwise, the sample would be denatured and impu­
rities would appear in AFM images. If experimental results are not
reproducible, it is most likely that procedures to be carried out after
sample deposition (the steps 5 and 6 described below) have not been
performed appropriately. Note that the buffer solution used for sample
dilution can be different from an observation buffer. In general, thedilution buffer should have a property of facilitating monodispersion of
the sample. For the observation buffer, we may not need to consider thisproperty very strictly because molecules placed on mica have lesschance of encountering each other. The sample deposition on bare mica
is performed in the following steps (Fig. 2):
1. Glue a mica disk onto the sample stage using an epoxy adhesive.
Then, wait for more than 3 h for drying.
2. Glue the sample stage onto the Z-scanner using nail enamel diluted
to ~ 30 % with acetone, and leave it for 5–10 min.
3. Dilute the sample to a few nM (follow the step 4 of procedure 3.2).
4. Press a Scotch tape onto the mica disk surface and then smoothly
remove the tape from the mica (Fig. 2b). The top layer of the mica isremoved with the tape, which can be checked by inspecting thesurface of the removed tape.
5. Deposit a drop (2 μl) of the diluted sample solution (1–5 nM) on the
freshly cleaved mica disk surface (Fig. 2c). Then, cover the sample
stage with a humid hood and wait for 1–3 min (Fig. 2d).
6. To remove unattached molecules, rinse the mica surface three times
using an observation buffer solution (20 μl × 3) and a piece of filter
paper (Fig. 2e and f).

• The protein sample should be pure as much as possible.
• Avoid contamination of proteases in the sample as much as possible.
Protease inhibitors (e.g., PMSF, benzamidine or TPCK) should be
added to avoid possible degradation by proteases when preparing
and storing the sample.
• Buffer solutions used for dilution and observations should be clean
enough. Most of contaminants can be filtered out by a 0.22 µm sy­
ringe filter (e.g., PVDF, 0.22 µm pore, 30 mm in diameter, Advan­
gene, USA). For a strict case, a membrane ultrafiltration (e.g.,
Vivaspin 6, MWCO 3,000, PES, Sartorius, Germany) is useful toremove small contaminants.
• Use mica for visualizing IDPs at the single molecule level.
• Find appropriate buffer conditions by changing the ionic strength,
the sort of ions and the pH of observation buffers.
• Use protein tags (e.g., MBP, Trx, GFP, or GST) or His-tag with anaffinity for a nickel ions-treated mica surface, when the IDPs are notwell anchored and thus move too fast on the mica surface.

3.4. High-speed AFM imaging
To quantitatively characterize dynamic structural features of an IDP
by HS-AFM imaging, at least ten and ideally more than twenty molecules
should be imaged under each experimental condition. This can reinforce
that observed dynamic structural features are common to identicalmolecules. In addition, it is highly recommended to capture ~ 1,000
images (1–2 min) of each molecule at 10–20 fps, although the required
number of images depends on how widely and fast the molecules sample
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different conformations. When a higher imaging rate is necessary torecord highly mobile IDRs, the imaging rate can be increased by nar­rowing the imaging area; a small scan size in the X-direction (W) and areduced number of scan lines (N). Although higher imaging rates could
be used even for a wide imaging area, the resulting insufficient feedback
control (and hence too excessive tip–sample interactions) would alter
the dynamic structural features of the IDP under study or fillip themolecules. In the current HS-AFM system, Vtip can go up to 400 μm/s
without altering the dynamic structural features of IDPs with lowheights (<~3 nm), although very recent technical developments now
enable a ~ 4-time higher scan velocity [37–39].
HS-AFM imaging of IDPs is performed as follows:

5. When the liquid cell is not a closed type, place wet paper towels(e.g., Kim towels) around the cantilever holder to suppress
evaporation of the observation buffer.
6. Deposit the sample on the mica surface (follow procedure 3.3).
7. Mount the scanner on the HS-AFM setup so that the sample stage
is partly immersed in the buffer solution placed around thecantilever.
8. Readjust the cantilever position and adjust the sample stage po­sition so that the sample stage is placed over or under the canti­
lever depending on the HS-AFM apparatus to be used.
9. Find the cantilever resonant frequency by measuring the power
spectrum of cantilever’s thermal deflection.
10. Excite the cantilever at (near) the found resonant frequency byapplying AC voltage to an excitation piezoactuator attached tothe cantilever holder. Then, adjust the excitation power so thatthe free oscillation amplitude A0 becomes 1–2 nm.
11. Set the feedback set point amplitude Asp at ~ 0.8 × A0 and run the
PID feedback controller.
12. Start a coarse tip–sample approach (~1 μm/s) by driving a
stepper motor attached to the scanner. This approach is carriedout automatically while the signals of cantilever oscillation
amplitude and PID output are monitored.
13. When the cantilever gets close to the surface, stop the tip–sample
approach and readjust A0 at 1–2 nm. The closeness in distancecan be judged by an optical image appearance of the mica surface
and an increase in A0.
14. Adjust the feedback setpoint amplitude Asp at 0.9–0.95 × A0 andstart a fine tip–sample approach (~ 0.2 μm/s).
15. Once the cantilever tip makes contact with the sample, start im­
aging under a relatively mild observation condition (e.g.,

1. Set a cantilever chip to the cantilever holder equipped with theliquid cell.
2. Set the cantilever holder to the HS-AFM apparatus. Gently wash
the liquid cell 2–3 times using an observation buffer (50–100 μl)
to remove dirt, while sucking the solution using a gel-loading tip
or an injection needle connected to an aspirator (e.g., a baby
nasal aspirator or a peristatic pump).
3. Fill the liquid cell with an observation buffer (50–100 μl). The
volume of the observation buffer to be loaded should always be
adjusted at the predefined volume. When the volume exceeds thepredefined volume, the excessive solution will contact the pie­zoactuator used in the Z-scanner, resulting in its short and hence
fatal damage upon high voltage application to the piezo.
4. Adjust the position of the incident laser beam from the opticalbeam deflection (OBD) detector so that it is focused onto the
cantilever’s free end region. This adjustment can be done bylooking at video images captured by an optical system equippedwith the HS-AFM apparatus.

Fig. 3. Molecular features of PQBP-1 (1–214) observed at different imaging rates. (a-c) Clips of successive HS-AFM images of PQBP-1 (1–214) captured at 10 (a), 20(b) and 50 (c) fps, with 80 × 80 pixels (a, b) and 60 × 36 pixels (c). (d–f) The three graphs in each column of the left three are the histograms for the N-terminal
globule height H1 (d), the IDR end height H2 (e) and R2D (f) measured from HS-AFM images captured at 10, 20, and 50 fps (from left to rirght). The most probablefitting curves are drawn with the solid lines. The right graphs of (d-f) show 〈H1〉, 〈H2〉 and 〈R2D〉 at various imaging rates. Each plot corresponds to mean values ± s.e.
m. measured at each frame rate. At each condition, more than 1300 frames were analyzed using more than three imaged molecules. The horizontal lines indicate theweighted mean values. The values of 〈R2D〉, 〈H1〉 and 〈H2〉 are nearly constant, irrespective of the imaging rate, indicating no notable impact of the tip-sample contact
on the structure of this protein.
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scanning area, 80 × 80 nm2; the number of pixels, 80 × 80; frame
rate, 5 fps; Vtip, 160 μm/s).
16. Adjust the feedback control parameters (main I-gain and sup­portive P-gain) so that clear images appear.
17. Start imaging at 10–20 fps. If necessary, change the observation
area by applying DC voltage to the XY-scanner.
18. Collect image data for at least ten molecules (ideally more thantwenty molecules) by changing the scanning area.

similar way; P2 is now the highest position of the second globular
domain.
6. Obtain the time-series data of H1, H2, and R2D.
7. Make graphs (e.g., histograms and time courses of H1, H2, and R2D).
In some cases, the height histogram of a globular region is best fitted
by a double Gaussian distribution, indicating that the globule has un­dergone structural transitions. Likewise, when the R2D histogram is best
fitted by a double Gaussian distribution, the IDR has undergone struc­tural transitions between partially folded and fully disordered states.
The fully disordered state of an IDR can be confirmed by its mean IDRheight of ~ 0.5 nm. Therefore, an IDR with a mean height larger than ~0.6 nm can be judged to be partially structured. From the double
Gaussian distributions of height and R2D, the order propensity of theanalyzed regions (Ke) can be estimated by the area ratio of the corre­
sponding double Gaussian components. For more information extract­able from HS-AFM images of an IDP, go to procedures 4.2 and 4.3.

When molecules moved on the mica surface too fast to be resolved
clearly, the observation buffer was probably not appropriate. Whilechanging the ionic strength, the sort of ions and the pH of the solution,
repeat the experiments. In this situation, new sample deposition is un­necessary unless the molecules are aggregated under the previous
experimental conditions. When the molecules still move too fast on thesurface, use an IDP construct fused to a structured protein (e.g., MBP,
Trx, GFP, or GST), or a His-tagged sample. When the cantilever tip was
not sharp enough to clearly resolve molecular features, just replace thecantilever with a new one, without changing the deposited sample. If
necessary, capture images at higher rates up to ~ 50 fps to demonstratethat observed structural features of the molecules are not affected by thetip–sample contact (Fig. 3).

4.2. Length rule for fully disordered IDR
From our HS-AFM observations of various IDP constructs placed on
mica, we obtained corroborative evidence that the mean R2D values of
IDRs, 〈R2D〉, in the fully disordered state follow the power law, 〈R2D〉 =± 0.009, where Naa is the number of amino(1.16 ± 0.057 nm) × N0.52
aaacids contained in the fully disordered IDRs [19]. Using this power law,the value of Naa can be precisely estimated nearly at the residue level,
even when structural information of the IDP under study has not beenmuch available previously. The usefulness of this estimation wasdemonstrated in the quantitative delineation of dynamic structure of theyeast Cdk1 kinase inhibitor (Sic1) and the N-terminal domain of measles
virus (MeV) phosphoprotein (PNT) (Fig. 5) [19].
In the HS-AFM study of Sic1, a construct fused to GFP at the C-ter­minus of Sic1 was used. The GFP acts as an anchor to the mica surface.
Before this HS-AFM study, nothing has been known about the structureand dynamic features of Sic1, other than the qualitative information that
Sic1 is disordered over its entire length but has a propensity to adopt acollapsed chain-like form. The histogram of R2D of the IDR between the
N-terminal globule and the C-terminal GFP was best fitted to a double
Gaussian distribution with peaks at 12.2 ± 0.66 and 20.5 ± 2.14 nm(Fig. 5a). The IDR is fully disordered in both shorter and longer states, as
judged from its mean height of ~ 0.5 nm in both metastable states. Fromthe power law, Naa contained in the IDR was estimated to be 95 and 259
for its shorter and longer states, respectively. The height histogram of
the N-terminal small globule undergoing transitions was best fitted to adouble Gaussian distribution with peaks at 0.9 ± 0.05 nm and 1.3 ±0.28 nm (Fig. 5b). Therefore, the folding and unfolding transitions in the
N-terminal globule result in the length change of the fully unfolded IDR.
In fact, the order propensity of the N-terminal globule estimated fromthe height distribution (Ke = 1.6) was nearly identical to that estimatedfrom the R2D distribution (Ke = 1.5). From the total number of aminoacids contained in Sic1 (284 ) and the Naa values, the number of aminoacids contained in the small globule is approximately estimated to be ~30 and ~ 190 for its lower and higher states, respectively (Fig. 5e).
PNT is mostly disordered, but the small regions 1–37, 87–93, and
189–198 were shown by NMR to have α-helical propensities, and hence
named α1/2, α3 and α4, respectively [41]. α3 and α4 are interspaced by anacidic IDR (124–168). This structure revealed by NMR could not explain
the biochemically detected resistance of the N-terminal 27–99 region toproteolysis [42], suggesting the existence of a large-scale structure un­detectable by NMR. The HS-AFM imaging of PNT (1–229) –GFP fusion
showed an IDR changing its length and an N-terminal small globule
having varying size but a constant height of 1.1 nm (Fig. 5g). This
constant height is identical to the height of an α-helix, consistent withthe presence of α1/2 in the N-terminus. The R2D histogram of the entire
IDR was best fitted to a double Gaussian distribution with peaks at 8.9 ±0.33 and 14.3 ± 9.26 nm (Fig. 5f), corresponding to Naa = 52 and Naa =4. AFM image analysis
4.1. Characterization of topographic features of IDPs
Once sufficient image data are collected, the next step is character­izing dynamic structural features of the imaged IDP molecules throughimage analysis. The first step to this end is to make a list of image framesthat seem to contain meaningful data. One of the characteristics of AFM
images is that the width of molecular images is strongly affected by the
AFM tip size. Therefore, comparing the widths and volumes of molecular
images captured for a given sample with different tips is not meaningful.
In addition, the quantification of the counter length of an IDR should bedone while keeping in mind that its measurement depends on the res­olution affected by the tip size. In contrast, the two dimensional end-toend distance of an IDR (R2D) and the height values (H) at different
molecular portions can be reliably quantified.
From the captured HS-AFM images of an IDP, the four dimensional
coordinates (x, y, z, t) can be obtained for the following positions of themolecules: the highest positions of globular domains, and various po­
sitions of IDRs including the end positions. Note that different positions
along a moving IDR cannot be specified accurately, except for its end
positions. From the positional coordinates, the time-series data ofheights and R2D are acquired. We have carried out image analyses using
a laboratory built software that is open to public, including its sourcecode [40]. The procedure is as follows.
1. Make a list of imaged frames that seem to contain meaningful data.
2. Remove spike noise from original images (Fig. 4a) by applying a low
pass filter (LPF) (Fig. 4b).
3. Apply a flattening filter so that the substrate surface appears hori­zontal (Fig. 4c).
4. Apply a line-by-line offset adjustment filter so that the substratesurface height appears constant (Fig. 4d).
5. Obtain the three dimensional coordinates (xi, yi, zi) of the highest
positions (P1) of globular domains, the height of an IDR, and the free
end position of an IDR (P2). This quantification can be done semiautomatically by selecting a region of interest (ROI) (Fig. 4e–g).
Also obtain the average height of the mica surface (Have). Calculate
the relative heights H1 at P1 and H2 at P2 measured from the mica
surface as H1 = z1 – Have and H2 = z2 – Have. The direct distance D
between P1 and P2 is calculated, followed by a calculation of R2Dvalue as R2D = D − H1/2 − H2/2. When an IDR is interspaced be­
tween two globular domains, the R2D value can be calculated in a49

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Fig. 4. Procedure of AFM image processing and analysis. (a-d) HS-AFM images of a PQBP-1 molecule for explaining image processing. (a) Original image, (b) after
LPF, (c) after flattening filter and (d) after line-by-line offset adjustment. The image was captured with 80 × 80 pixels at 15 fps. The cross-sections along the lines
indicated on the second row images are displayed at the bottom to show the effect of each filtering. (e) Schematics showing the observed molecular characteristics of
the PQBP-1 molecule (top, top view; bottom, side view): grey spheres, N-terminal globular domain; blue thick solid lines, IDRs; dashed red lines, schematic to­pographies of the globular domain convoluted with the finite size of the tip apex in lateral contact with the globule. (f) Magnified view of the area enclosed by thewhite dashed line in (d). (g) The same magnified view as (f) explains the semi-automatic selection of two points (P1 and P2). The highest point of the globular domain(P1) and the end region of the IDR (P2) are searched after the operator clicks the mouse pointer around the globular domain (marked with gray, pink, and light blue)
and in a molecule-free region very close to the free end of the IDR (marked with gray, pink, and light blue), respectively. The pixel search program automatically finds
P1 and P2 by searching over n × n pixels around the operator-specified pixel positions. The value of n is appropriately chosen. Typically, n is 7 and 5 for the search of
P1 and P2, respectively. The same points of P1 and P2 are selected, irrespective of the different pixels clicked.

129, respectively. From these Naa values, the number of amino acids
contained in the small globule is approximately estimated to be ~ 175and ~ 100 for the shorter and longer IDR states, respectively (Fig. 5i).
The number ~ 100 suggests that α1/2, α3 (87–93) and the IDR segment
between them (38–86) are contained in the small globule in both thelonger and shorter IDR states. Therefore, the region encompassing the Nterminus and helix α3 always forms a compact structure, explaining theresistance to proteolysis of the N-terminal segment extending to the 99th
residue. The number ~ 175 suggests that the structural transitions be­
tween the two states occur mainly by association and dissociation be­
tween the N-terminal compact structure and the acidic IDR (124–168).
The negatively charged residues of this IDR region may contribute to its
interaction with the constantly folded small globular domain.

undergo transitions between folded and unfolded conformations.
Interestingly, not only IDRs but also other regions that have beenthought to be structured exhibit order–disorder transitions. The orderpropensity and the transiently ordered structures very probably dictate
key features in binding of these IDPs to their targets. As indicated above
for Sic1 and PNT, the order propensity of an IDR can be estimated by Ke,
i.e., the area ratio of the double Gaussian components of height or R2D
distribution (Fig. 5a, b and f). Because the time series data of height or
R2D can be obtained, the structural transition rates can in principle beestimated from the data. However, the two Gaussian components indouble Gaussian fitting often overlap partially. Therefore, we cannot
directly estimate the lifetimes of individual conformational states fromthe time-series data.
We can circumvent this problem by using the autocorrelation func­tion G(τ) for the time-series data of R2D(t) or H(t). The use of G(τ) enables
the estimation of the order-to-disorder rate constant, KOD, and thedisorder-to-order rate constant, kDO, as follows [19]. When the

4.3. Structural transition analysis by autocorrelation function
As typically seen in the HS-AFM images of Sic1 and PNT, some IDRs
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Fig. 5. Dynamic molecular features of Sic1 and PNT revealed by HS-AFM imaging. Extracted dynamic structural information for Sic1-GFP (a-e) and PNT-GFP (f-i). (a,f) R2D distributions in Sic1-GFP (a) and PNT–GFP (f). (b, g) Height distributions of N-terminal globules in Sic1-GFP (b) and PNT-GFP (g). (c, d, h) Autocorrelation
functions of R2D(t) for IDRs contained in Sic1-GFP (c) and PNT–GFP (h), and an autocorrelation function of H1(t) data for the N-terminal collapsed structure in Sic1GFP (d). (e, i) Schematics showing structural and dynamic features of Sic1 (e) and PNT (i) revealed by HS-AFM. Insets show typical HS-AFM images together with
their sketches: green circles represent the C-terminal GFP moieties, while the red circles represent globules undergoing transitions between folded and unfolded
states. In the HS-AFM images, the green arrowheads point to the C-terminal GFP, whereas the closed and open white arrowheads point to the N-terminal regions in
the folded and unfolded states, respectively. The top and bottom panels correspond to the more- and less-ordered states, respectively. The numbers in red and blue
represent the number of amino acids contained in the respective small globules and fully disordered IDRs, respectively. The red and blue arrows show transientchanges in < H1> (red) and < R2D> (blue).

structural transition of an IDP follows a two-state transition model, thedecay rate λ of G(τ) is expressed as λ = kOD + kDO, while the orderpropensity Ke is expressed as Ke = kDO/kOD. Therefore, the individual
rate constants can be expressed as kOD = λ/(1 + Ke) and kDO = λKe/(1 +Ke). The structural transition rates for Sic1 and PNT were estimated inthis way (Fig. 5c,d and h). In Sic1, the G(τ) for H(t) of the N-terminal
globule and the G(τ) for R2D(t) were nearly identical, indicating that theincreased/decreased height of the N-terminal globule is coupled withthe folding/unfolding of the IDR. When an IDR is always disordered, theG(τ) for R2D(t) is zero except for τ = 0, although R2D(t) widely varies dueto the flexible nature of the IDR. In fact, this necessary consequence wasverified by the G(τ) for R2D(t) measured for the constantly disordered
IDR in PQBP-1 [19].
Autocorrelation function analysis is carried out as follow:

analyzable by G(τ). To produce a G(τ) with a high S/N ratio, theimages should be captured at >10 fps, as long as possible (longer
than 1 min for each molecule).
2. Analyze the images to obtain the time series data of R2D(t) and/or H(t).
3. When the histogram of all data set of R2D(t) or H(t) is best fitted by adouble Gaussian distribution, calculate Ke from the areas of indi­vidual Gaussian components. The data fitting should be statisticallyverified using F-test.
4. Calculate an autocorrelation function G(τ) for each time-series
datum of R2D(t) or H(t), and then take an average of G(τ)s.
5. Calculate the decay rate λ of G(τ) by fitting the averaged G(τ) to asingle exponential function.
6. Calculate kOD and kDO using Ke and λ.

1. Capture HS-AFM movies of IDP molecules successively. The struc­tural transitions occurring on a single molecule should be captured
repeatedly in a single movie to produce a time-series datum

While the estimated transition rates reflect the dynamic structuralproperties of the molecules under study, their values should be treatedwith caution. This is because the interactions between the molecules and51

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mica slow down the molecular motion, which may reduce the transition
rates. However, there is currently no way to compare the structuraltransition rates measured on mica to those in solution because of thepaucity of techniques capable of measuring the rates in solution.

containing the basic IDR segment and the HMG domain.

5. Imaging studies of IDPs by high-speed AFM

In recent years, MLOs formed through LLPSare one of the hot topics
in biology, and IDPs have been recognized as the key players in forming
MLOs [3,4]. The formation and dissolution of liquid droplet-like con­densates (liquid droplets) are triggered by small changes in the cellularenvironment (pH, temperature, ionic strength, osmotic pressure, typeand concentration of the surrounding biomolecules, and others) andoccurs in an avalanche-like manner, like a phase transition phenome­
non. Because this property is realized by the multivalent interactions of
the molecules constituting liquid droplets, it is perfectly natural that
IDPs are involved in the formation of liquid droplets. IDPs are typicalmolecules that can change their promiscuous, multivalent intra-/intermolecular interactions depending on environment changes and/or theirpost-translational modifications. HS-AFM can be used to visualize (i)dynamic molecular features of the individual molecules involved in theformation and dissolution of liquid droplets [18,20], (ii) the initialprocess of droplet formation, and (iii) detailed surface features of theformed droplets.
In yeast, autophagy induced by starvation stress requires the for­mation of biomolecular complexes called PAS (pre-autophagosomal
structure) at the first step [44] but its entity has been elusive. PAS or­
ganization initially requires assembly of the Atg1 complex, consisting of
Atg1, Atg13, and the Atg17–Atg29–Atg31 complex which forms acharacteristic S-shaped backbone due to the dimer shape of Atg17. This
supramolecular self-assembly of Atg1 complexes accelerate the initial
events of autophagy, including auto phosphorylation of Atg1, recruit­
ment of Atg9 vesicles, and phosphorylation of Atg9 by Atg1. In thisevent, Atg13, which is dephosphorylated in starvation conditions, plays
a key role as a regulatory factor [45].
Atg13 contains regions responsible for binding to Atg17: 17LR
(359–389) and 17BR (424–436). The crystal structure of the Atg17Atg29-Atg31 complex with the Atg1317LR and Atg1317BR peptides
shows that two Atg1317BR peptides bind to the distal end of each Atg17

5.2. Initial process of membrane less organelle formation

5.1. Morphological changes of IDR induced by post-translational
modification
HS-AFM can be used to investigate the morphological changes of an
IDR induced by its post-translational modification, as demonstrated by
the HS-AFM imaging of FACT [15] and a few others. FACT is a hetero
dimer of SPT16 and SSRP1 subunits. The long IDR in SSRP1 contain ten
phosphorylation sites residing on the acidic ID segment adjacent to ahigh-mobility-group (HMG) domain-flanking basic ID segment. The
phosphorylation of SSRP1 is known to destabilize the binding of FACT tonucleosomes [43]. To observe structural effects of the phosphorylationof the SSRP1′ s IDR, the C-terminal shorter IDR of SPT16 and the Nterminal half of SPT16 were deleted. Both phosphorylated anddephosphorylated (the Ser residues on the ten sites were replaced with
Ala) forms displayed a similar overall structure; a large globule (GD1) isconnected to the long IDR of SSRP1 (Fig. 6a and b). Moreover, in the twoforms, the middle region of the IDR contained a small globule (GD2) that
was appearing and disappearing over time. The small globule contains
the HMG of ~ 1 nm size, judging from its position and size (1.1–1.7 nm).
Compared to the dephosphorylated form, the small globule and the IDR
in the phosphorylated form often took a higher height state and a shorter
length state, respectively (Fig. 6c–f). This distinct feature and its phys­iological relevance can be explained as follows: (i) the acidic segment of
SSRP1′ s IDR electrostatically interacts with both the region containing
the basic segment of SSRP1′ s IDR and the HMG to evoke partial foldingof the IDR; (ii) the folded and unfolded states are in dynamic equilib­
rium; (iii) extensive phosphorylation of the IDR’s acidic segment shifts
the equilibrium toward the folded state; and (iv) this structural bias tothe folded state blocks the binding of nucleosomal DNA to the region

Fig. 6. Phosphorylation-induced morphological changes in FACT. (a, b) Clips of successive HS-AFM images of phosphorylated (a) and dephosphorylated FACT (b).
The images were captured with 80 × 80 pixels at ~ 14 fps. Z-scale, 4.0 nm. The observed molecular features are schematized in the bottom panels. In the bothconstructs, the large globular domain (GD1, green) is connected to the IDR of SSRP1 on which two small globular domains, termed GD2 (red) and GD3 (gray), were
found at the middle and at the distal end, respectively. (c, d) Height distributions of GD2 in phosphorylated (c) and dephosphorylated FACT (d). The histograms
appear to have two peaks at 1.6–1.7 and ~ 1.1 nm, which correspond to HMG associated with the IDR and HMG alone, respectively. (e, f) Distributions of the
distance between GD1 and GD3 in phosphorylated FACT (e) and dephosphorylated FACT (f).
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protomer, while two Atg1317LR peptides bind to the dimer interface ofAtg17 [18]. The two Atg13 binding sites on an Atg17 protomer isseparated approximately by 13 nm. In contrast, the power law
mentioned above indicates that the mean R2D value of the constantly
disordered region between the 17LR and 17BR is ~ 7.3 nm. This sug­gests that Atg13 is structurally unable to bind to its two binding sites
within the same Atg17 protomer. Therefore, Atg13 binds and cross-links
two Atg17 molecules via Atg1317LR and Atg1317BR. This idea wasconfirmed by the observation that an Atg13 mutant, in which the IDR
region between the 17LR and 17BR is deleted, still can induce PAS
formation [18]. Furthermore, the HS-AFM observation of the complexes
formed by Atg13 and Atg17–Atg29–Atg31 in a solution containing KCl
showed an assembled structure in which several S-shaped Atg17 mole­cules separated by ~ 8 nm were stuck out of a large globular assembly(Fig. 7a), consistent with the above idea. Moreover, a long incubation ofa mixture of Atg13 and the Atg17− Atg31 complexes on mica in a so­lution containing NaCl resulted in the formation of liquid droplets with
100–400 nm in diameter, where globular molecules were observed to be
diffusing in and out of the droplets (Fig. 7b) [46]. Note that the S-shapeof Atg17 is K+ ion dependent. Thus, the entity of PAS was revealed to beliquid droplets formed through LLPS.
Next, an example of HS-AFM imaging studies revealing the detailed
surface features of liquid droplets is described here. To visualize liquid
droplets by HS-AFM, the HS-AFM setup combined with a fluorescent
microscope is useful [47,48]. This is because the maximum scanningarea of HS-AFM is usually a few square micrometers, while liquid
droplets are usually formed sparsely over a wider area. Therefore, thefluorescence imaging of liquid droplets helps bring the AFM tip to theirlocations. The liquid droplets formed from a mixture of Atg13 and theAtg17–Atg29–Atg31 complexes in a solution containing KCl wereobserved by HS-AFM, in which Atg13 and Atg17 were labeled withdifferent fluorescent dyes [25]. When the droplets were gently placed
onto a cleaned coverslip, molecules with an S-shape, a distinctive featureof Atg17 [49], were distributed irregularly throughout these droplets(Fig. 7c). Importantly, S-shaped Atg17 molecules exhibited nanoscopic
diffusional motion within the droplets, providing further evidence thatthe droplets are in a liquid-like state. By contrast, when the droplets
were placed onto a positively charged coverslip, Atg17 was regularly
arranged in the droplets and showed little movement in droplets(Fig. 7d). This observation suggests that the droplets can mature to astatic, solid-like structure depending on the environment, consistent
with the other biomolecular condensates that transit from liquid drop­lets to solid-like states such as gels, glasses and amyloids [50]. These
results demonstrate the advantage of HS-AFM that can observe the dy­
namic nanoscopic features of biomolecules on the droplet surface,although HS-AFM cannot observe the interior of the droplets.
The phase-separated droplets with liquid-like properties are often
made through weak intermolecular interactions with dissociation con­stants in the range of a few μM or larger. To visualize them without
mechanical disturbance by the AFM tip, it is sometimes necessary toslightly cross-link the constituting biomolecules with glutaraldehyde[25,51]. Although this mechanical disturbance is a weak point of AFM
measurements, this feature may be used to determine which molecules
are weakly interacting in a droplet. HS-AFM observations of various
types of phase-separated droplets will provide further insights into theirassembly mechanism and mechanical properties.

Fig. 7. HS-AFM images showing membrane-less organelle related to auto­
phagy. (a) Complexes formed by mixing of dephosphorylated Atg13 and Atg17
in a solution containing KCl. The green arrowheads point to S-shaped Atg17
molecules extending from the protein aggregate. The particle encircled with thebroken line is an unconfirmed object. (b) Liquid droplet formed after a longincubation of dephosphorylated Atg13 and the Atg17Atg31 complexes on mica,
in a solution containing NaCl. (c, d) Liquid droplet-like condensate observed ona cleaned coverslip (c) and solid-like condensate on a positively charged
coverslip (d), which are formed in a 1:1 mixture of Atg13–SNAP (labeled with
Surface 549, red fluorophore) and SNAP–Atg17 (labeled with Alexa Fluor 488,
green fluorophore), in a solution containing KCl. The left and right images arethose of florescence and HS-AFM, respectively. The dotted lines (left bottom)
indicate an AFM cantilever. The HS-AFM image (right bottom) is obtained byband-pass filtering of the right top image. The inset in the right bottom image of(c) shows the dimeric Atg17 structure in the same scale.

5.3. Cross-β polymerization of low complexity regions

Sup35, etc.) have been observed to form phase-separated droplets inwhich cross-β fibers are formed [59–63]. Here, the recent HS-AFM ob­
servations of the fibrillation process of Sup35 are described [22].
Sup35, an IDP working as a translation termination factor in yeast, is
known as a prion protein that forms amyloid fibrils [64]. Sup35 haverecently been shown to form phase-separated droplets depending on the
nutritional status of yeast in which the translational activity is impaired

Many IDRs have unusual regions made up of only a few different
types of amino acids and its repeats called low complexity domains(LCDs) [52,53]. LCDs seen in IDRs are often found in the activation
domains of many transcription factors [54] and RNA-binding proteins
involved in stress response and neurodegenerative diseases such as
amyotrophic lateral sclerosis [55–58]. Notably, in recent years, IDPs
with LCDs (e.g, FUS, hnRNPA1, hnRNPA2, TIA-1, TDP-43, ataxin-2,
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Methods 207 (2022) 44–56[59]. For the HS-AFM observations, the NM domain involved in amyloid
formation of Sup35 (Sup35NM) was used [22]. The monomer form ofSup35NM exhibited two highly flexible tail-like structures sticking out
of a small globular domain, consistent with previous reports [65–67].
Sup35NM formed spherical oligomers with a height of about 4 nm
during incubation for 60 min. However, no amyloid fibrils were formed
from these oligomers even after several hours of incubation. Amyloid
fibrils appeared after much longer incubation (for more than 2 days).
Fibril elongation was not seen by addition of the oligomers to fibril seeds
but occurred unidirectionally by monomer addition (Fig. 8a), as previ­
ously reported [68,69]. The growing fibrils were fragile and occasion­
ally fragmented during HS-AFM imaging, providing new seeds for fibril
elongation (Fig. 8b). Notably, the fibril elongation occurred smoothly
without discrete steps even in high-resolution imaging, suggesting
gradual conversion of the incorporated monomers into cross-β struc­tures. Maybe more intriguingly, HS-AFM images showed that the olig­
omers were interspaced with a similar size of gaps (Fig. 8c), suggestingthat they are mutually repulsive. Interspace gaps were also observed
between a fibril and the oligomers surrounding it (Fig. 8c). The gap size
between adjacent oligomers was distributed around ~ 6 nm, while thegap size between a fibril and its neighboring oligomers was distributed

around ~ 10 nm. Because these gap sizes were much larger than the
Debye Hückel distance of the ionic solution (0.72 nm) and independentof ionic strength, the gaps were likely to have originated from theflexible regions of Sup35NM extending out from the oligomers and fi­
brils. In fact, tail-like structures were confirmed to extend from oligo­
mers by faster imaging at 17 fps (Fig. 8d). Tail-like structures were also
observed to extend from the lateral side of fibrils but their motion could
be detected even with imaging at 1 fps, indicating they are relatively
solid and not freely moving (Fig. 8e). These extending structures seem torepel oligomers from the lateral side of the fibrils, which may play a rolein the growth of straight fibrils without branching. Notably, such
structures were not observed at the fibril ends (Fig. 8e), and therefore,
oligomers could approach to the fibril ends, although their incorpora­tion into the fibril ends were never observed. The mutual repelling effectof IDRs found in this study may be commonly possessed by other IDPs
and possibly involved in their functions.
6. Outlook
HS-AFM is a relatively new microscopy technique but its systemproducts and small cantilevers essentially required for HS-AFM are

Fig. 8. HS-AFM images showing amyloid fibril formation by Sup35NM. (a) Representative HS-AFM images of growing Sup35NM fibrils captured after 50-min
preincubation on mica. The images were captured with 400 × 400 pixels at 0.1 fps. Z-scale, 10 nm. (b) Successive HS-AFM images showing seed-dependentfibril growth and fragmentation. The images are those clipped from the region highlighted by dashed line in (a, 1200 s). The fragmented positions are indicatedby arrowheads. (c) HS-AFM image of a fibril surrounded with oligomers with height of ~ 4 nm, and its sketch with lines representing inter-particle gaps. (d) HS-AFM
images showing Sup35NM oligomers. The images were captured with 80 × 80 pixels at 16.7 fps. Z-scale, 4 nm. (e) HS-AFM image showing Sup35NM fibrils withsome structures extending from the lateral side. The image was captured with 200 × 200 pixels at 1 fps. Z-scale, 14 nm. The bottom images of (d, e) are height display
in rainbow color of the corresponding upper images.
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already commercially available. Experimental protocols to visualize thedynamic structure and processes of biomolecules have been gradually
established [36,70–72] along with continuously increasing imaging
studies with HS-AFM [13,73,74]. The greatest advantage of HS-AFM
visualization is that it allows us to simultaneously find several (often
unexpected) facts of the biolomolecules under the microscope. The
visualized images can be understood without complicated and round­
about interpretations. Of course, quantitative image analyses are often
required be done for produced many images. Nevertheless, HS-AFM has
so far been used mostly for structured proteins, whereas the number of
HS-AFM studies on IDPs is limited. It is expected that this microcopy will
be applied to a much wider range of IDPs and related biological phe­nomena in the near future, which will bring a vast array of new dis­coveries that are impossible with other techniques. Many IDPs are
involved in gene regulation and often associated with diseases. For
example, MeCP2 is involved in neurodevelopmental diseases [75,76],and the fusion proteins such as EML4-ALK [77] and SS18-SSX [78,79]
cause lung cancer and synovial sarcoma, respectively. Thus, new in­formation about their dynamic structures and processes to be revealedby HS-AFM surely provide clues to understanding and solving diseases.
On the other hand, as shown in the observations of MLOs, the current
HS-AFM sometimes disrupt weak bimolecular interactions. However,efforts to solve this inconvenience have been continued. New techniques
recently developed in our group have already enhanced the nondisturbing and speed performances of HS-AFM [37–39]. Thus, we
expect that HS-AFM will be applied to a much wider range of biomol­
ecular systems involving very weak molecular interactions and fasterprocesses.

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Declaration of Competing Interest
The authors declare that they have no known competing financial
interests or personal relationships that could have appeared to influence
the work reported in this paper.
Acknowledgements
The authors would like to thank Steven McArthur for helpful sug­gestions resulting in the improvement of this work. This work was
supported by the CREST program of JST (#JPMJCR13M1 to TA,#JPMJCR1762 to NK), KAKENHI of JSPS (#26119003 and #17H06121
to TA, and #20H00327 to NK) and World Premier International
Research Center Initiative (WPI) of the Ministry of Education, Culture,
Sports, Science and Technology (MEXT), Japan.
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