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Versatile whole-organ/body staining andimaging based on electrolyte-gel propertiesof biological tissues
1234567890():,;

Etsuo A. Susaki

et al.#

Whole-organ/body three-dimensional (3D) staining and imaging have been enduring challenges in histology. By dissecting the complex physicochemical environment of the staining
system, we developed a highly optimized 3D staining imaging pipeline based on CUBIC.
Based on our precise characterization of biological tissues as an electrolyte gel, we experimentally evaluated broad 3D staining conditions by using an artiﬁcial tissue-mimicking
material. The combination of optimized conditions allows a bottom-up design of a superior
3D staining protocol that can uniformly label whole adult mouse brains, an adult marmoset
brain hemisphere, an ~1 cm3 tissue block of a postmortem adult human cerebellum, and an
entire infant marmoset body with dozens of antibodies and cell-impermeant nuclear stains.
The whole-organ 3D images collected by light-sheet microscopy are used for computational
analyses and whole-organ comparison analysis between species. This pipeline, named
CUBIC-HistoVIsion, thus offers advanced opportunities for organ- and organism-scale histological analysis of multicellular systems.

#

A full list of authors and their afﬁliations appears at the end of the paper.

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ince German anatomist Walter Spalteholz developed the ﬁrst
tissue clearing reagent over 100 years ago, systematic threedimensional (3D) observation and analysis of whole organs
and whole bodies have been continuously conducted in biomedical
research, linking classical anatomy to modern systems biology1,2.
With the advent of state-of-the-art tissue clearing and 3D imaging
methods, a large volume of samples can be viewed comprehensively
with cellular to subcellular resolution over single organs andorganisms (recently reviewed in Ueda et al.3). Collecting biologicalinformation requires appropriate labeling according to structure,cell type, and cell activity. Various genetic and viral tools applied forthis purpose have facilitated numerous discoveries2,4. In addition,
whole-mount staining with clearing has been assessed, starting in
the 1980s with the insect and shrimp nervous systems and the
Xenopus embryo5–7. Recently, whole-mount staining with clearing
has been expanded to the 3D observation of murine and humanembryos8,9, various animal organs and bodies10–19, and humanpathological specimens12,20–24. Staining is more advantageous than
genetic or viral tools in terms of (1) applicability to a broad range ofsamples, including human and non-model animal specimens, and(2) the relative ease of multitarget labeling.
There have been several approaches designed to improve thepenetration of stains and antibodies in a large tissue sample.
Intensive permeabilization procedures to increase the pore size ofﬁxed tissue have been attempted, including delipidation (sometimes with tissue clearing)12,13,15,16,21, dehydration7,8,10,11,17,
weaker ﬁxation10, and partial digestion with proteases10,11. Urea
or SDS was introduced to control the binding afﬁnity of stains
and antibodies during penetration15,25. Several physical methods,
such as electrophoresis and pressure, were tested on acrylamideembedded samples26,27.
However, the insufﬁcient penetration of stains and antibodies
remains a crucial bottleneck in many 3D staining cases.
Researchers often face a situation where even small dyes do not
penetrate 3D samples, implicating the complex physicochemical
environment in the staining system. Currently, 3D staining
mainly uses a small variety of stains and antibodies on samples ofrelatively small and thin tissues, partially dissected tissues, orembryonic tissues with little extracellular matrix. Low-density
antigens such as c-Fos, amyloid plaques or microglia markers
have demonstrated the capacity for homogeneous staining of
sizeable tissue (e.g., on the order of cm3 for whole adult mousebrain or dissected human specimens)17,28. On the other hand,higher density antigens, such as NeuN and neuroﬁlament, have
not yet been adequately demonstrated to be capable of suchstaining. Other attempts have also been made, including theiterative supply of staining reagents12,21 or the use of a specialized
device26 or transcardial perfusion-based staining16,18.
To overcome these limitations, we applied an objective rather
than an empirical approach to exploring essential 3D staining
conditions. Beginning with a detailed characterization of biologicaltissue by material chemistry methods, we found ﬁxed and delipidated tissue for optical clearing to be equivalent to an electrolyte gelof cross-linked polypeptides. Then, inspired by a diffusion-reaction
scheme and the characterization of biological tissue as a gel, we
broadly evaluated 3D staining conditions for the bottom-up designof a superior protocol. By using CUBIC-HistoVIsion for 3D
staining, tissue clearing, and volumetric imaging, we successfully
stained and imaged whole adult mouse brains, a whole adultmarmoset brain hemisphere, and an ~1 cm3 tissue block of apostmortem adult human cerebellum with various cell-impermeant
nuclear stains and antibodies. We also showed that the whole-organ
structural information given by nuclear staining enables the registration and alignment of multiple whole-organ images. Furthermore, the signal-to-background ratio (SBR) of these 3D images washigh enough for the computational detection of labeled cells. These2

results highlight the perspective of systematic quantiﬁcation andanalysis of biological information from whole-organ and wholebody 3D staining and the subsequent computational processes.
Results
Fixed and delipidated tissue is an electrolyte gel. To develop abottom-up design of an optimized 3D staining protocol, we
attempted to determine the physicochemical properties of paraformaldehyde (PFA)-ﬁxed and delipidated tissue, which had
undergone tissue clearing with the CUBIC protocol (see “Methods” for details). Here, we used the brain as a representative
organ. We found that the sample could repeatedly and reversibly
swell and shrink under various chemical conditions (Fig. 1a). Thisphenomenon provided substantial evidence that the tissue sample
could be characterized as a gel: in materials science, gels (1) havemesh/network structures (introduced by PFA ﬁxation), (2) do notdissolve in a medium (which is self-evident), and (3) have thepotential for repeated and reversible swelling and shrinkage29.
This notion is consistent with the early discovery by Tanaka, who
documented that biomaterials such as cross-linked proteins,
agarose and DNA can be considered gels30.
We then narrowed down the speciﬁc physicochemical properties of the sample in terms of its characterization as a gel. We ﬁrst
investigated changes in tissue composition during the clearing
procedure. The process was highly coordinated with the
reduction in phospholipids and cholesterol and complementary
increase in water content, while the protein amount was mostly
conserved (Fig. 1b; Supplementary Fig. 1a, b). Using these dataand extrapolating from previous reports on the whole rat brain31,
we estimated changes in tissue composition before and after
delipidation (Fig. 1c). These results suggest that the brain is a gel
mainly composed of cross-linked proteins.
We then applied small-angle X-ray scattering (SAXS) analysis tothe delipidated brain. This analysis aimed to measure thenanometer-scale structure of the sample (on the order of 1–102nm) in the form of the scattering intensity I (the Fourier transformof the paired electron density distribution inside the sample) as afunction of the magnitude of the scattering vector q (which isinversely proportional to the size of a scattering structure32) (Fig. 1d).
The following ﬁndings from the acquired I-q proﬁles revealed
the structural and chemical characteristics of the delipidated
brain. First, the scattering peak at q ≈ 0.08 Å −1 in thenondelipidated brain disappeared after delipidation (Supplementary Fig. 1c–e). The corresponding d-spacing based on Bragg’s
Law (d = 2π/q) is ~8 nm. As suggested in a previous SAXS studyof the human brain33, this peak is likely attributed to thephospholipid layers of the myelin sheath (whose thickness is on
the order of ~1–10 nm34). Hence, the disappearance of thescattering peak again conﬁrmed that the delipidation procedure
had indeed removed the lipid contents from the sample(Supplementary Fig. 1f). Second, the I-q proﬁle showed a broad
peak (q ≈ 0.02–0.04 Å−1, ~15–30 nm) when the buffer had lower
ionic strength, while the peak disappeared at high NaCl
concentrations (arrowheads in Fig. 1e, f). The peak thus might
reﬂect long-range spatial correlations among polymers at thisorder of distance that depend on ionic interactions. Such a saltdependent peak is commonly observed in electrolyte gels andimplies changes in ionic interactions between polymer moleculesthat are affected by the ionic strength of the solution35. Therefore,
the delipidated brain can be characterized as an electrolyte gel(Supplementary Fig. 1f). Since most of the cationic amino
residues are masked by PFA ﬁxation and the isoelectric point of
the CUBIC-delipidated brain is approximately pH 536, thedominant ionized residues in the polymer are thought to containan anionic carboxyl group.

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a

PBS

MES (pH 5.5)

Water

TEA (pH 10)

NaCl (500 mM)

Water

Acetone (80%)

c

Fixed
OthersProteins 1–2%
10–12%

Lipids
7–8%

Liquid79–82%

1

Delipidated

0.8

OthersProteins 1–2%
8–10%
Lipids
1–2%

0.8
0.6
0.4
0.2

Relative protein

1.2

1

Relative cholesterol

1.2

1

Relative phospholipid

b 1.2

0.8
0.6
0.4

1

2

3
Day

4

0.4

5

0

1

2

3
Day

4

0

5

e
Scattering intensity [a.u]

d


Δr

r



L

2

3
Day

4

5

f

SPring-8

–2
–1

q=

ks

Fixed and delipidated brainq [Å–1]3

Gel size (S/S0)

Ion strength

Gel size (S/S0)

3

2

1

4

sin
2


Ionizedamino
group
in gel2Counterions insolution

100
100 200 300 400 500

0

0.1

4

3

3

Gel size (S/S0)

pH

Gel size (S/S0)

4

2

1

6

5

4

2

1

3

11 10 9Gel size (S/S0)

Gel size (S/S0)

3
2

1

7

6

5

4

3

20

40

60

80

% of acetone

+
–
–

–
–

+

–

High ion strength

+
+
+ –
+ – –
– –
–
+ – + – + ++ –––+ – + +

–
+

+

+
+

OsmoutWaterinAcidic pH

+
–
–
+
–
+
+
– –
+
– +

Low acetone fraction

High acetone fraction

+

+

–

–

–
+

–

3

–

+

1

–
0

20

40

60

–

80

% of acetone

out

Osm

ð1Þ

Waterin

+
–

2

Osmin

Water

+

The SAXS analysis further implied that the brain sample could
be characterized as a gel with a fractal nature. In general, the I-q
proﬁles of highly heterogeneous gels exhibit the following powerlaw behavior:I / qD ;

+

–

–

Osmin

0

0

+

Ionizedcarboxyl
groupin gel+ + ++
+
–
+
–
–
+
–
+
+
– –
–
–
+
–
–
– –
+
–
– +
–
–
–
+
+ +
+
in

4

4

Acetone fraction

8

pH

pH

0

PB
PB + 25 mM NaCl
PB + 50 mM NaCl
PB + 150 mM NaCl
PB + 500 mM NaCl+07q [Å–1]AggregatedMeshwork
structure
Alkaline pH

100 200 300 400 500
NaCl conc. (mM)

NaCl conc. (mM)

8

–2
–1

H2O
PB
PB + 25 mM NaCl
PB + 50 mM NaCl
PB + 150 mM NaCl
PB + 250 mM NaCl
PB + 500 mM NaCl

Low ion strength
40
11 10 9Delipidated

Fixed gelatin gel

40

Photon factory of KEK

0.1

r

ki

107
106
105
104
103
102
101
100
10–1
10–2

Delipidated

q = ks – ki tan  = L

Incoming X-ray(Vector ki)

g

1010
109
108
107
106
105
104
103
102
101

1

0.01

Scattered X-ray(Vector ks)

SampleLiquid86–87%

0

0
0

0.6

0.2

0.2

0

Delipidated
Non-delipidated+++– – + –
+ –
– +
–
+
– +
+ –

+

Gel solubility
Waterinin

Water

where D is the dimension of the mass fractal37. The acquired I-q
proﬁles (Fig. 1e, f) indeed demonstrated power-law behavior witha slope of D ≈ 2, reﬂecting a highly heterogeneous gel structurewith a fractal nature32,37.
The swelling-shrinkage curves of gels30,35 further indicated thatthe delipidated brain responds to the surrounding ion strength,

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Fig. 1 Fixed and delipidated tissue is an electrolyte gel. a A ﬁxed and delipidated whole mouse brain treated with different chemical conditions. MES: 2(N-morpholino)ethanesulfonic acid, TEA: triethanolamine. Scale: 5 mm. b Changes in the components inside the tissue during the delipidation procedure.
The values were calculated as a ratio to the average of the delipidated samples (day 0) and indicate the means ± SD of the ratios (n = 3 biologicallyindependent samples). c Changes in tissue components before and after delipidation. d Schematic of SAXS measurement and analysis. The relationshipbetween the intensity of the scattered X-rays (I) and the scattering angle (θ) reﬂects nanometer-order structures inside the sample. The value of I in termsof the width Δr was calculated along the radius line (r) on the 2D intensity plot at a speciﬁc angle (φ) [or the circular average (φ = 0–2π)]. The scattering
angle (θ) is transformed to the magnitude of the scattering vector q (which is inversely proportional to the size of the inside structure) according to theequation in the panel. L: distance between the sample and the detector, λ: wavelength of the X-ray. e, f I–q plot of the SAXS analysis of the brain slices fordifferent NaCl concentrations, measured at SPring-8 (e) and the Photon Factory of High Energy Accelerator Research Organization (KEK) (f). The values
on the y-axis were shifted by multiplying by shift factors (in e, 1000, 500, 80, 30, 10, 2, and 1 for H2O, PB, PB with 25 mM, 50 mM, 150 mM, 250 mM, and
500 mM NaCl, respectively; in f, 35, 7, 4, 6, and 1 for PB, PB with 25 mM, 50 mM, 150 mM, and 500 mM NaCl, respectively). Lines indicate the slopes ofthe mass fractal dimension D. g Swelling-shrinkage curves of the delipidated tissue and ﬁxed gelatin gel. The y-axis (S/S0) represents the relative value ofthe gel area (mean ± SD, n = 3, biologically independent samples).

pH and hydrophobic solvent fraction (Fig. 1g). An increased ionicstrength in the buffer induced sharp shrinkage of the tissue,
suggesting that the delipidated brain could characterized as a
typical ionized electrolyte gel35. The multistate swelling andshrinkage of the brain under changing pH also suggests that the
behavior is primarily affected by the degree of ionization of the
carboxyl group of the polypeptide polymer. We also observed
more than fourfold shrinkage in the area (corresponding to aneight-fold decrease in volume) resulting from the decrease in gel
solubility as the acetone fraction increased.
We compared the swelling-shrinkage behavior of the brain
with that of several artiﬁcial gels, including PFA-ﬁxed type-B
gelatin gel, PFA-ﬁxed agarose gel, and polyacrylamide gel as
representatives of ionized polypeptide gels, nonionized naturalpolymer gels, and artiﬁcial hydrophilic gels, respectively (Fig. 1g;
Supplementary Fig. 1g). Under our experimental conditions, thenonionized agarose and polyacrylamide gels did not respond toionic strength and pH changes. Only the polyacrylamide gel
responded to the acetone fraction with a limited dynamic range.
On the other hand, the swelling-shrinkage behaviors of gelatin gel
under various ionic strengths, pH values, and acetone fractions
were similar to those of the delipidated tissue. We note that thegelatin gel exhibited a more dynamic volume change than
the tissue under pH change. Similar dynamics were observed in
the case of an artiﬁcial gel with amphoteric ions38. Moreover, thegelatin gel was more sensitive to the increase in the acetone
fraction. Various factors, such as the complexity of the gelcomponents, the rigidity of the gel, the ionic charge state, thedegree of ionic imbalance (Donnan’s membrane equilibrium), orinternal interactions, may account for the differences in themacroscopic size change patterns of these gels. Nonetheless, theoverall swelling-shrinkage behaviors of gelatin gel, a typicalexample of polypeptide gels, were closest to those of the tissue,
with slight quantitative differences.
Given the commonality of tissue composition (lipids, proteins,
nucleic acids, and water; Fig. 1c), we assumed that other delipidated
tissues could also be modeled as an electrolyte gel with similar
properties to those of the brain. Indeed, repeated and reversible
swelling-shrinkage behaviors of delipidated kidney, liver, andmuscle tissue (Supplementary Fig. 1h), similar to those seen in
the brain (Fig. 1a), were observed. In particular, (1) expansion in thealkaline pH range, (2) shrinkage in a highly ionized state, and (3)shrinkage again under a high acetone fraction proved theconsistency of our electrolyte gel model of biological tissue.
Taken together, we conclude that tissue that was ﬁxed anddelipidated for optical clearing could be generally characterized as
an electrolyte gel composed primarily of cross-linked polypeptides, and the chemical properties are very similar to those of an
artiﬁcial protein gel. This conclusion is also consistent with ourprevious ﬁndings36.
4Developing versatile whole-organ/body dye staining. Based onthese unveiled electrolyte gel properties of delipidated tissue, we
considered a simple theoretical model as a ﬁrst-order approximation of the 3D staining process, in which Fick’s law governs
the diffusion of reactive solute into an electrolyte gel39. The
reaction-diffusion process is written as
∂C
∂2 C
ð2Þ
¼ Ddiff  2 þ R;∂t∂x
where C, t, Ddiff, and x indicate solute concentration, time, thediffusion constant, and position, respectively. R denotes thereaction term: to describe the interaction of the solute and its
interacting target(s) in the gel, we chose the reversible one-to-one
binding and unbinding scheme with parameters kon and koff (see“Methods” for details). The value of Ddiff for the gel can beaffected by various factors, such as temperature (T), the gel meshstructure (η) and particle size (r), as described by the formula forsimple diffusion (Einstein-Stokes law):
Ddiff ¼ f ðT; η; r Þ:

ð3Þ

To predict the possible contribution of these parameters in thegel staining, we ﬁrst simulated the staining patterns of a circular
2D gel (Supplementary Fig. 2a, b). The simulation predicted thatlower Ddiff, higher kon, a lower solute concentration, or a higher
concentration of interaction target in a gel would retain thestaining signal at the edge of the gel (Supplementary Fig. 2a). For
convenience, we categorized the simulation results as (1) rimmed,suggesting the solute is trapped on the gel surface and the signal
remains at the edge of gel, or (2) gradual, indicating improved
penetration efﬁciency. Note that these patterns are the two
extremes and that continuous changes in these parameters would
produce intermediate patterns.
We then broadly examined the experimental conditions that
could affect these parameters. To perform the test in a
semiquantitative manner and in a controlled setting, we used
ﬁxed gelatin gel as a tissue surrogate. We stained cylinder-shaped,
PFA-ﬁxed gelatin gels containing DNA or rabbit immunoglobulin with a nuclear stain or an Alexa Fluor dye-conjugated antirabbit secondary antibody, respectively. Next, we determined thestaining pattern in the middle of the gel according to thesimulation-based criteria (Fig. 2a).
We ﬁrst tested positively charged nuclear stains. Given thenegatively charged environment of ﬁxed gelatin gels under
neutral to alkaline pH conditions, we hypothesized that thestrong ionic interactions with the gel would inhibit thepenetration of these positively charged dyes, which could be
attenuated by increasing the salt concentration.
As expected, the staining pattern for the ionized dye propidium
iodide (PI) changed drastically from the rimmed to the gradualpattern by increasing the salt concentration (e.g., 500 mM NaCl

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Preparation of gel
containing DNA or IgG

Sectioning at the
middle position

3D staining

Semi-quantitativeevaluation

IntensityaRimmedGradual

Averagex

Fixed gelatin gel
φ 5 mm × H 5 mmbcPropidium iodide (PI)HEPES
(NaCl 5 mM)

Measure intensities in
6 diameter columnsof the section

Prepare sections
at the middle of the gel

HEPES(NaCl 500 mM)

0.25× SC-1A(NaCl 5 mM)

0.25× SC-1A(NaCl 500 mM)

SYTO 16
HEPES(NaCl 5 mM)

HEPES(NaCl 500 mM)

0.25× SC-1A(NaCl 5 mM)

0.25× SC-1A(NaCl 500 mM)

Gelatin gel

Gelatin gel(4× enhanced)

10

1
0

1499

0

Relative intensity

Relative intensity

6

HEPES (NaCl 5 mM)
HEPES (NaCl 500 mM)
0.25× SC-1A (NaCl 5 mM)
0.25× SC-1A (NaCl 500 mM)

HEPES (NaCl 5 mM)
HEPES (NaCl 500 mM)
0.25× SC-1A (NaCl 5 mM)
0.25× SC-1A (NaCl 500 mM)

1
0

1499

0

x position (pixel)dx position (pixel)e

3D: Propidium iodide
H-S(NaCl 5 mM)

H-S(NaCl 500 mM)

1× SC-1A(NaCl 25 mM)

3D: SYTO 16
H-S(NaCl 5 mM)

1× SC-1A(NaCl 500 mM)

H-S(NaCl 500 mM)

1× SC-1A(NaCl 25 mM)

1× SC-1A(NaCl 500 mM)

f

Delipidated cerebellar hemisphere

Delipidated cerebellar hemisphere(4× enhanced)

Post 2D: DAPI

Whole marmoset infant body (PI stained and cleared)g

Post 2D: DAPIhWhole marmoset infant body (LSFM)

Horizontal section(~1 mm of y projection)

1

Trachea

1
2
Lung
Heart
2
R

L

3
z

3
x
Vertebra
L

R
Kidneyin HEPES buffer) (Fig. 2b). This range of NaCl concentrations
potentially cancelled the ionic interaction of the ﬁxed gelatin gel(Fig. 1e–g). Shrinkage of the gel under high salt conditions(Fig. 1g) did not affect penetration, suggesting that the size of thedye molecule was sufﬁciently small regardless of the volume
phase of the gel. On the other hand, when tested with anotherionized but more lipophilic dye, SYTO 16, the rimmed pattern
was still observed for HEPES buffer containing 500 mM NaCl
(Fig. 2c). Therefore, given our previous success in 3D staining
using SYTO 16 with ScaleCUBIC-113, we tested a ScaleCUBIC-1based staining buffer. When supplied with 500 mM NaCl, thereagent indeed changed the SYTO 16 staining result from the

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Fig. 2 Development of a versatile protocol for whole-organ/body dye staining. a Schematic of the surrogate assay. A cylinder-shaped, ﬁxed gelatin gel
containing DNA or rabbit immunoglobulin was used to experimentally evaluate the 3D staining patterns in the interior of the gel (rimmed or gradualpatterns). b Representative results of DNA-containing gelatin gel staining with propidium iodide (PI), an ionized, lipophobic, and cell-impermeable nuclear
stain. A high concentration of salt modulated the gel–stain interaction, leading to the improvement of the interior staining patterns. Scale: 1 mm.
c Representative results of DNA-containing gelatin gel staining with SYTO 16, a lipophilic and cell-permeable nuclear stain. Additional use of ScaleCUBIC1A (SC-1A) chemicals in high-concentration salt conditions improved the penetration patterns with decreased signal intensities (indicated as “4×enhanced”). Scale: 1 mm. The proﬁles in b and c show the mean intensity ± SD of the six diameter regions as in a. d, e The results in b and c were replicatedby using the ﬁxed and delipidated tissues (cerebellar hemispheres). After 3D staining, the samples were sectioned to evaluate the inﬁltration of the stain
inside the tissue. The sections were also restained with DAPI to check the detectability of the nuclei (post 2D). Scale: 1 mm. f–h The interaction-modulated
3D staining was scaled up to a whole infant marmoset body. f The cleared and PI-stained infant marmoset body. PI staining was performed under a high ion
strength condition (see “Methods”). Scale: 1 cm. g The reconstituted whole-body 3D image acquired with a custom-built LSFM (voxel size: 10.3 × 10.3 ×
100 μm3) after staining and clearing. White boxes indicate the positions of the reconstituted x–z images in the panels on the right. Scale: 1 cm. h The
reconstituted x–z images at the indicated positions in g. L left, R right. Scale: 2 mm.

rimmed to the gradual pattern (Fig. 2c). This result implies thatthe addition of ScaleCUBIC-1 reagent can further modulate theinteraction of SYTO 16 with the gel.
We also tested the case of a negatively charged dye, eosin. The
3D staining time was much shorter (~4 h for the cerebral
hemisphere) than in the case of nuclear stains (2–3 days for asimilar-sized sample). The dye rapidly penetrated the gelatin gel
independently of the salt concentration, suggesting no absorption
at the gel surface due to ionic interactions. The ScaleCUBIC-1
reagent reduced the penetration efﬁciency, unlike the case withthe positively charged dye (Supplementary Fig. 2c).
We then applied these ﬁndings to stain delipidated tissues.
Homogeneous nuclear staining on these samples was observed forthe optimal staining conditions found in the gelatin gel (Fig. 2d, e),verifying our assumption that the ﬁxed gelatin gel could beconsidered a tissue surrogate. To further test the scalability of thesingle-step 3D staining achieved by modulating gel–solute interactions with additives, we stained a whole infant marmoset body with
PI in a high-concentration salt buffer (0.1 M PB with 1.5 M NaCl)(Fig. 2f). After tissue clearing and whole-body staining, the sample
was imaged with a custom-built macrozoom light-sheet ﬂuorescence microscope (LSFM) covering the whole animal (Fig. 2g). The
acquired images indicated the successful staining of the entire bodywith a 3D-staining condition that modulates gel–solute interactions(Fig. 2g, h; Supplementary Movie 1).
ScaleCUBIC-1 with 500 mM NaCl buffer reproducibly supported
efﬁcient 3D staining of various nuclear stains in addition to PI andSYTO 16 (Supplementary Fig. 2d). Therefore, we ﬁnally employed
the recipe as a general 3D nuclear staining buffer in the following
experiments. However, as indicated by the results of the gelatin gel
assay, more rapid 3D staining was achieved without additives forthe negatively charged dye eosin (Supplementary Fig. 2e).
Developing versatile whole-organ immunostaining. We nextsought to determine the experimental conditions for whole-organ
antibody staining with a surrogate gel assay. Since the molecularweight of the antibody is more than 103-times larger than that ofsmall dyes and the antibody would potentially interact with theelectrolyte gel in a more complicated manner, we determined thata broader range of experimental conditions should be examinedthan for the small molecule dyes. First, we tested whether thegel–solute interactions validated by the nuclear stains (Fig. 2)
were also essential for 3D immunostaining. We found that thehigher the antigen (rabbit immunoglobulin) concentration in
the gel, the greater the interaction between an antibody and theantigen-containing gel increased, resulting in the rimmed staining
pattern (obvious at 0.5 µg/mL, Fig. 3a).
The results prompted us to expand the exploration of essentialconditions that could inﬂuence the 3D immunostaining results.
As suggested previously10, the gelatin gel concentration had an
6

impact on the staining pattern (the rimmed pattern was obvious
at 10–15%, Fig. 3b), possibly by altering the gel mesh structure
and the nonspeciﬁc interactions between the antibody and the gel.
The Alexa Fluor dye types somewhat affected the penetration
efﬁciency, probably due to differences in the gel–Alexa Fluor
interactions (Supplementary Fig. 3a). The temperature during
staining and the initial concentration of antibody in the buffer
determined the efﬁciency of penetration (Supplementary Fig. 3a),as suggested by the diffusion-reaction simulation. The rimmed
pattern was observed at 4 °C or at an antibody concentration of
2.5 µg/mL, indicating the appropriate temperature range (>room
temperature) and antibody concentration (~> 5 µg/mL) for 3D
immunostaining. On the other hand, the NaCl and detergent
concentrations did not affect the penetration efﬁciency but ratherchanged the signal intensity (Supplementary Fig. 3a). We note
that, as in the case of nuclear stains (Fig. 2), the ionic strength
required to saturate the shrinkage of the gel (Fig. 1g) did notprevent antibody penetration. We also note that the increased
immunostaining signal under high concentrations of Triton X100 was not attributable to increased antibody penetration into
the gel but to increased antibody binding. Indeed, 10% Triton X100 reproducibly increased the signal intensities from tissue
section staining compared with 0.1% Triton X-100. (Supplementary Fig. 3b). Hence, we applied 200 mM NaCl and 10% Triton X100 to our ﬁnal immunostaining buffer.
We validated some of these essential conditions using
delipidated brain samples. The concentrations of Quadrol andurea used in nuclear staining (Fig. 2) were again effective in tissue
3D immunostaining, presumably as a result of attenuating
antibody–tissue interactions (Supplementary Fig. 3c). Furthermore, the results in Fig. 3a suggest that conventional two-stepstaining with primary and secondary antibodies would not be
useful in 3D staining unless the target antigens were distributed
sparsely. This is because, when the target is abundant, a large
amount of the primary antibody ﬁlls the gel as a dense antigen of
the secondary antibody, thus reducing its penetration efﬁciency.
This assumption was conﬁrmed by 3D immunostaining against
NeuN. The one-step procedure using either the dye-conjugatedprimary antibody or the complex of the primary antibody andsecondary Fab fragment successfully supported uniform 3D
staining in the tissue sample (Fig. 3c, upper panels). On the other
hand, a two-step procedure using primary and secondary
antibodies resulted in limited signal in the sample (Fig. 3d, upper
panels). Since post-cut 2D staining conﬁrmed that the NeuN
antigen was well preserved and that the primary mouse antiNeuN antibody had efﬁciently penetrated the tissue (Fig. 3c, d,lower panels), this difference was due to insufﬁcient penetrationof the secondary antibody.
Inspired by the results in Fig. 3b and those of a previous
study10, we also tested partial digestion of the extracellular matrix

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NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-020-15906-5bAnti-rabbit IgG (A594)cx position (pixel)

N

N

5%
10%
15%

Relative intensity

15

1
0

1499

0
x position (pixel)e

3D: mouse anti-NeuN + Fab (A488)
1-step

Mouse anti-NeuN
anti-mouse IgG (A488)

Post 2D
Rabbit anti-NeuN
anti-rabbit IgG (A594)

f

10

1499

3D, 2-steps

Mouse anti-NeuN+ Fab (A488)

Delipidated cerebellar hemisphere

Delipidated cerebellar hemisphere0d3D, 1-step
Mouse anti-NeuN(A488 conj.)

5

1

0

10

Gelatin conc. of gel (%)

Gelatin gel

0.5

Relative intensity

0.25

Gelatin gel

0.1

Anti-rabbit IgG (A594)

0.1 μg/ml
0.25 μg/ml
0.5 μg/ml

2.5

Antigen (rabbit IgG) conc. in gel (μg/mL)(-)

Delipidated cerebellar hemisphereaPost 2D
Rabbit anti-NeuN
Anti-mouseanti-rabbit IgG (A594)
IgG (A594)(2× enhanced)

Collagenase

Hyaluronidase

Post 2D: rabbit anti-NeuN
anti-rabbit IgG (A594)

5–20 μg/ml

I

I
NH 2

1st Ab + 2nd Fabcomplex

Dye-conj.
1st Ab

H 2N

23°C–

Modulation of stain/antibody-tissue interactions

Avoidance of 2-step staining

Appropriate experimental conditions- Use of additives- Use of directly conjugated 1st antibody- Reaction over room temperature- Use of an appropriate concentration of stain/antibody- Limited digestion of tissue- Use of 1st Ab + 2nd Fab fragment complex

g

1 day, 4°C

Wash

3–4 days, 37°C

Delipidation

1–8 weeks, 32°C
(Room temp. or 37°C for some Ab)

3–5 days, 37°C

Wash

Nucleistaining

Immunostaining

Wash

Wash

2–3 days, Room temp.

RI match

Wash

Post-fix
1% FA

Fix
4% PFAh

5–24 h,Room temp.

i

SYTOX-G

NeuN

Merge

3D ventral view

AbScaleiDISCO+R

L

AbScaleOriginal protocol

NeuN (A594)
SYTOX-G

Reconstituted sectional view

iDISCO+CUBIC

on CUBIC-HVj SYTOX-G, sagittal section

NeuN, sagittal section

z

z
z

y
y

SYTOX-G, coronal section

Ly

NeuN, coronal sectionRzx(ECM). We treated the tissue with collagenase or hyaluronidase
under highly stringent conditions to achieve limited digestion.
The treatment indeed ameliorated the edge binding of theantibody (Fig. 3e).
Taken together, we postulated the essential conditions for an
efﬁcient 3D staining protocol as follows: (1) modulation of theinteractions between dye/antibody and tissue by chemical

z

y

z
x

z
x

z
x

additives such as Quadrol and urea, (2) avoidance of two-stepstaining, and (3) selection of appropriate temperature, ionicstrength, detergent concentration, and antibody concentration,and limited digestion of tissue (Fig. 3f). We ﬁnally constructed a
versatile protocol for 3D histology and volumetric imaging on
CUBIC (CUBIC-HistoVIsion version 1.0, hereafter designated
CUBIC-HV) by integrating these conditions (Fig. 3g). In the

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Fig. 3 Development of a versatile protocol for whole-organ immunostaining. a, b Representative results of rabbit IgG-containing gelatin gel staining with
anti-rabbit secondary IgG (A594). Scale: 1 mm. The proﬁles show the mean intensity ± SD of the six diameter regions as in Fig. 2a. c–e The results in a andb were replicated with the ﬁxed and delipidated tissues. c, d One-step procedure with mouse anti-NeuN-A488 or unconjugated anti-NeuN with secondary
Fab fragment [3D, c] and conventional two-step procedure using secondary anti-mouse IgG after the primary antibody [3D, d] were compared. Threedimensional staining results were visualized with A488. After 3D staining, the sample was sectioned and restained with rabbit anti-NeuN antibody followed
by secondary anti-rabbit IgG (A594) or restained only with secondary anti-mouse IgG (A594) to conﬁrm the detectability of NeuN antigen or theinﬁltration degree of primary anti-NeuN antibody, respectively (post-2D). Scale: 1 mm. e Collagenase or hyaluronidase treatment was tested by similarstaining procedures. Scale: 1 mm. f Summary of essential conditions for efﬁcient 3D staining. g Overview of the clearing, staining and RI matching of the
CUBIC-HV protocol (ver. 1.0). The indicated durations are assumed for a whole adult mouse brain. Also see Supplementary Fig. 4a. h Comparison andmodiﬁcation of previous 3D staining protocols based on CUBIC-HV. Adult mouse brain hemispheres were 3D stained with anti-NeuN antibody(Supplementary Fig. 4d). The intensity range was normalized in each image. Scale: 1 mm (for entire sagittal sections) or 50 μm (for enlarged images).
i Two-color whole-organ staining and volumetric imaging results of the adult mouse brain with custom-built LSFM. Voxel size: 8.3 × 8.3 × 9 μm3. Threedimensional images were reconstituted with Imaris software. L left, R right. Scale: 2 mm. j Reconstituted sagittal (y–z) or coronal (x–z) images of the data ini, showing uniform 3D staining and imaging with almost isotropic cellular resolution. The resliced images were prepared with Fiji/ImageJ. Scale: 2 mm (forentire images) or 100 μm (for enlarged images).

CUBIC-HV protocol, we applied ScaleCUBIC-1A supplied with
500 mM NaCl for 3D nuclear staining. We also used ionicstrength-controlled HEPES buffer (200 mM NaCl) containing
10% Triton X-100 and 0.5% casein for 3D immunostaining. Thisbuffer improved the SBR compared with a conventional PBST
buffer with serum (Supplementary Fig. 3d). Limited enzymatic
digestion (hyaluronidase or collagenase P) or low levels ofadditives (Quadrol and urea) can optionally be applied when thedye/antibody penetration is insufﬁcient. We conﬁrmed that theenymatic digestion steps did not quench the GFP signals(Supplementary Fig. 3e). Therefore, we used these enzymes inmost of the following experiments for demonstration (Supplementary Fig. 4a). However, the application should be carefully
considered.
CUBIC-HV demonstrated 3D staining performance with thecell-impermeable dye SYTOX-G and anti-NeuN antibody
comparable to the performance of 2D staining (Supplementary
Fig. 4b, c). We further compared previously reported 3D clearingstaining protocols AbScale15 and iDISCO+17 with CUBIC-HV.
When anti-NeuN 3D staining of brain hemispheres was
performed according to the original protocols (Supplementary
Fig. 4d), the expected staining pattern was not completely
observed inside the sample (Fig. 3h, Original protocol). Therefore,
we modiﬁed the protocol by integrating the conditions adopted in
CUBIC-HV (Supplementary Fig. 4d). The staining performance
was obviously improved and became comparable to that of
CUBIC-HV (Fig. 3h, CUBIC-HV). These results suggest thegeneral importance of the 3D staining conditions found in ourbottom-up approach. Although we also tested SWITCHmediated antibody labeling (Fig. 6C in ref. 25), no expected
NeuN signal was observed, at least from our experiment(Supplementary Fig. 4e, f).
Finally, we examined whole-brain 3D staining with the nuclear
stain SYTOX-G and anti-NeuN antibody bound with secondary
Fab-A594. The stained sample was cleared with refractive index(RI) matching and was used for whole-organ 3D imaging with acustom-built macrozoom LSFM (Fig. 3i, j). We conﬁrmed auniform staining result on 3D-reconstituted, resliced images witha nearly isometric voxel size (8.3 × 8.3 × 9 μm3) (Fig. 3j). According to the NeuN data, there was no apparent absorption of lightsheet illumination through the tissue (Supplementary Fig. 4g).
CUBIC-HV is applicable to various antibodies and dyes. We
applied CUBIC-HV to various markers of particular interest inneuroscience, including neuronal and glial cell markers, axon,
dendrite, and synaptic molecules, and vessel markers (Supplementary Data 1). We ﬁnally selected 25 out of 44 antibodies listed
as suitable for the following whole-organ immunostaining,
8

according to the macroscopic staining pattern, penetration efﬁciency, and signal intensity (see “Methods” for details). We also
summarized the 2D staining results of the tested antibodies andthe corresponding reconstituted sections of the whole-brain 3D
staining images (Supplementary Fig. 5a, b).
A series of whole-organ 3D staining and volumetric imaging
with the selected antibodies and either green (SYTOX-G) or bluecyan (BOBO-1) nuclear stains were performed (Fig. 4a; Supplementary Movie 2). A complex of primary antibody and A594conjugated secondary Fab fragment was used for the one-stepstaining procedure. The stained and optically cleared adultwhole mouse brains were successfully imaged using the custombuilt macrozoom LSFM with nearly isotropic resolution (8.3 ×
8.3 × 9 μm3). In the 3D stained and cleared samples, the cellularto-subcellular structures were reasonably preserved (Supplementary Fig. 6a–n; also see Supplementary Discussion). We also
stained a whole mouse kidney with SYTOX-G and an antibody
against the pan-expressing transcription factor CREB. The
uniform staining result inside the kidney was obtained as in
the whole-brain staining (Supplementary Fig. 7a), supporting theapplicability of CUBIC-HV to other organs.
We then evaluated whether these whole-brain images withstructural information revealed by nuclear labeling could beprocessed by computational multibrain registration and alignment in the CUBIC pipeline13,40. Nine individual whole-brain
antibody staining datasets [phosphoneuroﬁlament (phospho-Nf),calbindin D28K, parvalbumin (PV), somatostatin (Sst), choline
acetyltransferase (ChAT), dopamine β-hydroxylase (Dbh), tyrosine hydroxylase (Th), tryptophan hydroxylase 2 (Tph2), andcopeptin, together with either SYTOX-G or BOBO-1] weresuccessfully registered and aligned against whole-brain antiNeuN and SYTOX-G staining data (Fig. 4b). The resulting data
provided a fused pseudo-multitarget whole-brain antibody
staining image (Fig. 4b; Supplementary Movie 3). We further
assessed the accuracy of registration among multiple brains bychecking the overlap of the corresponding signals. Copeptin and
NeuN signals were regionally merged in the hypothalamicparaventricular nucleus (PVN) and the supraoptic nucleus(SON); both Dbh and Th signals were found in the locus
coeruleus of the pons; and both PV and calbindin D28K signals
overlapped in the cerebellar Purkinje cell layer (Fig. 4b).
Taken together, these results indicate that CUBIC-HV enables
stable whole-organ 3D staining, imaging, and computational
processing with various dyes and antibodies.
CUBIC-HV allows multichannel whole-organ labeling. Compared with genetic tools, histology can more facilitate the staining
and imaging of multiple targets in a single specimen (Fig. 5a). The

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aCell type markers (3D reconstituted, ventral view)
PV

Sst

Th

Dat

Dbh

ChAT (abcam)

Tph2

Copeptin

LRPAP1Iba1

GFAP (MBL)

Neurofilaments (pan)Phospho-Nf

Synaptophysin

α-SMA

Calbindin D28K

R

L

Structural markers

Functional marker

MAP2

Arc

b

3D reconstituted, dorsal view

L

Calbindin
D28K

PV

Calculate transformed imageof antibody channel

R

Sst

Registration & alignmentof nuclei channel

ChAT

Dbh

NeuN
(standard)

Th

Tph2

Merged Ab channels, 3D reconstituted

phospho-Nf

NeuN
phospho-Nf
Calbindin D28K
PV
Sst
ChAT
Dbh
Th
Tph2
Copeptin

Dorsal view

L

Ventral view

R

R

L

Copeptin

Antibody
Nuclei

3D histology realized by CUBIC-HV allowed successful multicolor staining of whole brains with a combination of BOBO-1 andthree different antibodies related to GABA neurons [mousemonoclonal anti-PV IgG1/Fab-Cy3, rat monoclonal anti-Sst
IgG2b/Fab-A594 and mouse monoclonal anti-glutamic acid decarboxylase (Gad) 67 IgG2a/Fab-A647 complexes] (Fig. 5b–j andCoronal section

NeuN
Copeptin

NeuN
Dbh
Th

R

L

NeuN
Calbindin D28K
PV

LC

PVN
z

SON
x

Supplementary Movie 4). We also performed other combinationsof multicolor staining and imaging: 4-color staining with BOBO1, rat monoclonal anti-Sst IgG2b/Fab-Cy3, goat polyclonal antiChAT IgG/Fab-A594 and mouse monoclonal anti-Tph2 IgG1/
Fab-A647 complexes (Supplementary Fig. 8a and Supplementary
Movie 4) and 3-color staining of an Alzheimer’s disease model

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Fig. 4 CUBIC-HV is applicable to various antibodies and dyes. a Results of whole-brain staining and LSFM imaging with various antibodies (yellow) andnuclear stains (SYTOX-G or BOBO-1, blue). The data were reconstructed with Imaris software. The staining, imaging and image processing conditions are
summarized in Supplementary Data 2. Voxel size 8.3 × 8.3 × 9 μm3. L: left, R: right. Scale: 2 mm. b Nine sets of the whole-brain imaging data in a (stainedwith anti-phospho-Nf, calbindin D28K, PV, Sst, ChAT, Dbh, Th, Tph2, or Copeptin antibodies, respectively, with nuclear stains) were registered and aligned
to the whole-brain images obtained with anti-NeuN antibody staining and nuclear staining (structural standard). All the transformed data were merged as a
pseudo-multitarget whole-brain antibody staining image with Imaris software. The precise registration results are indicated by the brain regions merged
across different datasets, such as the paraventricular nucleus (PVN) and the supraoptic nucleus (SON) (NeuN+/copeptin+), the locus coeruleus (LC) in
the pons (Dbh+/Th+) and the Purkinje cell layer in the cerebellum (calbindin D28K+/PV+). L left, R right. Scale: 2 mm (whole-brain), 1 mm(reconstituted coronal sections), 0.5 mm (inset).

ab 3D ventral view

Multi-target 3D staining

PV (Cy3)
BOBO-1c

Sst (A594)
BOBO-1d

Gad67 (A647)
BOBO-1e

PV (Cy3)
Sst (A594)
Gad67 (A647)
BOBO-1RL

3 antibodies + nuclei stain

BOBO-1+Anti-PV (Cy3)Anti-Sst (A594)
Anti-Gad67 (A647)
WT brain
FP + 2 antibodies

YFP+
Anti-ChAT (A594)
Anti-Dat (A647)
Thy1-YFP Tg brainfh Coronal section (0.5 mm of y projection)

Horizontal section (0.5 mm of z projection)

PV (Cy3)
Sst (A594)
Gad67 (A647)
BOBO-1

i

L

R

y
x

R

L

j

g

z
x

Fig. 5 CUBIC-HV enables multicolor whole-organ staining and imaging. a Experimental schematics of multichannel and multimodal whole-brain staining
and imaging, shown in Figs. 5 and 6. b–j BOBO-1, PV (Cy3), Sst (A594), and Gad67 (A647) quadruple costaining images of the sole whole adult mousebrain reconstituted with Imaris software. (b-d) Individual antibody staining channels alongside the BOBO-1 channel. Voxel size 8.3 × 8.3 × 9 μm3. Scale: 2mm. e Merged image of all four channels. Scale: 2 mm. f, g Enlarged horizontal (x–y) images of a representative section. Scale: 0.5 mm. h Reconstituted
coronal (x–z) section image at the position indicated in e. Scale: 2 mm. i, j Enlarged images of the indicated positions in h. Scale: 0.1 mm.

mouse (AppNL-G-F knock-in mouse)41 with SYTOX-G, mousemonoclonal anti-β-amyloid IgG1 (6E10)/Fab-A594 and mousemonoclonal anti-α-smooth muscle actin (SMA) IgG2a/Fab-A647
complexes (Supplementary Fig. 8b). With an appropriate combination of host species and antibody isotypes, dyes, excitation
lasers, and bandpass emission ﬁlters (see “Methods” for details),
we could completely separate the signals from these different
ﬂuorescent channels.
One of the challenges of 3D staining and imaging is the
combination of whole-organ staining with ﬂuorescent protein(FP) labeling8 (Fig. 5a). To test the compatibility of CUBIC-HV
staining with FP labeling, we stained the brain of a Thy1-YFP-H
transgenic mouse42 with mouse monoclonal anti-dopaminetransporter (Dat) IgG1/Fab-A594 and goat polyclonal antiChAT IgG/Fab-A647 complexes. In the resulting images, the10

YFP signal and immunolabeled Dat and ChAT signals wereclearly observed at high intensity (Fig. 6a–g; Supplementary
Movie 4). Two adjacent axonal projections (the Dat-labeled
midbrain-striatum tract and the YFP-labeled corticospinal tract)
were clearly distinguished in the 3D data (Fig. 6e–g). Taken
together, the results allow us to conclude that CUBIC-HV iscompatible with whole-organ multicolor and multimodal labelingand imaging.
CUBIC-HV allows whole-organ cellular circuit analysis. One
application of 3D labeling and imaging is whole-brain neuralcircuit analysis with cellular resolution, which has been demonstrated in a limited manner by a few advanced reports17,43,44. We
prepared a Gad2-Cre knock-in mouse brain45 labeled with rabies

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YFP
ChAT (A594)
Dat (A647)

a 3D ventral viewbc Horizontal section (0.5 mm of z projection)

d
*

e-g

*

*
*
*

b

L

Dopaminergic
projection(Dat immunolabeling)

*

*

R

R

Corticospinal
tract
(YFP)

*
*

y
x

e Sagittal section (0.5 mm of x projection)

YFP
ChAT (A594)
Dat (A647)

f

g

*

*
*
*

P

Dopaminergic
projection(Dat immunolabeling)

A
*

*

*

z

Corticospinal tract
(YFP)

*
*

y

Fig. 6 CUBIC-HV enables multimodal whole-organ labeling and imaging. a-g ChAT (A594) and Dat (A647) double-staining images of the sole Thy1YFP-H Tg whole adult mouse brain. Voxel size 8.3 × 8.3 × 9 μm3. a Merged image of all three channels. Scale: 2 mm. b Enlarged image at the positionindicated in a. Scale: 0.5 mm. c Horizontal view of a representative section. Scale: 0.5 mm. d Enlarged image at the position indicated in c. Neighboring
projection tracts labeled with YFP expression or anti-Dat immunolabeling were visualized. Scale: 0.5 mm. e–g Reconstituted sagittal sections at the positionindicated in a, visualizing the neighboring projection tracts. Scale: 0.5 mm. Asterisks in e–g indicate nonspeciﬁc vascular signals due to insufﬁcientperfusion of the sample.

virus (RV) tracing vectors46 injected into M1 region of the cerebral cortex (Fig. 7a). We subsequently stained the delipidated
whole brain with anti-Sst/Fab-Cy3 complex and far-red cellimpermeant nuclear stain RedDotTM2 to collect cell-type andstructural information, respectively. CUBIC-HV successfully
visualized the virally labeled and immunostained cells in separate
color channels (Fig. 7b, c). In the whole-brain image, we identiﬁed the distribution of RV-GFP-labeled cells around the injection
site (Fig. 7d) and in regions away from the injection site,
including the ipsilateral somatosensory area (Fig. 7e). Cells withall possible labeling combinations, such as GFP- and mCherrypositive cells (Sst-negative starter cells), GFP- and Cy3-positive
cells (Sst-positive putative input cells) and GFP-, mCherry-, andCy3-positive cells (Sst-positive starter cells), were identiﬁed in thereconstituted y–z section of the injection site (Fig. 7f–j). These
results indicate that the neural circuitry and cell types could be
visualized with single-cell resolution in the whole-brain multimodal labeling data.
To further test whether CUBIC-HV could capture the wholebrain neuronal response under different experimental conditions,
we then conducted whole-brain c-Fos staining of mice with orwithout MK-801 administration (Fig. 8a). Whole-brain c-Fos
expression was successfully visualized (Fig. 8b, enhanced by aconvolution ﬁlter in Fig. 8c). The reconstituted y–z sagittal
sections show that c-Fos labeling could cover the entire brain area
(Fig. 8d). MK-801 administration strongly induced c-Fos
expression in several brain regions, including the olfactory
system of the forebrain, the paraventricular nucleus of thethalamus, and several hypothalamic and hindbrain regions. In
contrast, the number of c-Fos-positive cells was more pronounced
in the hippocampal dentate gyrus of the MK-801 (−) brain thanin the MK-801 (+) brain, as demonstrated by the detection ofArc-dVenus transgene reporter in our previous studies36,47(Fig. 8d, insets). Therefore, we conclude that CUBIC-HV canenable whole-brain analysis of neuronal responses.
To test whether the immunolabeled cells could be computationally detected for further quantitative analyses, we prepared acell detection algorithm. We ﬁrst attempted to reconstitute the
RV-traced brain data with the centroids of the labeled cells(Supplementary Fig. 9a). After optimizing the parameters, thealgorithm could reasonably detect the centroids of the GFP-,
mCherry- or Sst-labeled cells in the z-stack images around theinjection site (Supplementary Fig. 9b). Furthermore, the multilabeled cells in Fig. 7g–j were successfully recapitulated in thecorresponding centroid images (Supplementary Fig. 9c).
We also tested the whole-brain detection of c-Fos-labeled cells
by using the 3D maxima function according to the ClearMap
algorithm17 (Supplementary Fig. 10a). The local 3D maxima of cFos–positive cells with higher intensities than the nonspeciﬁcbackground signal were successfully identiﬁed (Supplementary
Fig. 10b, c). These results indicate that the SBR and image
resolution of the collected data are sufﬁcient for the whole-brain
quantitative analysis of cellular responses with single-cellresolution. Further improvement of the SBR in staining and theuse of machine learning-based algorithms for computational
detection may help increase this sensitivity.
CUBIC-HV allows organ-level anatomical comparison. We
ﬁnally tested the concept of organ-level histological comparisons
between species. We stained an adult marmoset brain hemisphereand an whole adult mouse brain with SYTOX-G and the same setof antibodies [anti-glial ﬁbrillary acidic protein (GFAP)/Fab-NATURE COMMUNICATIONS | (2020)11:1982 | https://doi.org/10.1038/s41467-020-15906-5 | www.nature.com/naturecommunications

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Cell circuit labeling

Delipidation, 3D staining

Rabies virus
tracer

RedDot2+
Anti-Sst (Cy3)

RI matching & imaging

Analysis
3D centroid detection

Gad2-Cremousez-stack
FP + Sst signal

b 3D dorsal view (Virus/Nuclei)

c 3D dorsal view [Merged with Sst (Cy3)]

RV-GFP
AAV-TVA-mCherry
RedDot2

RV-GFP
Sst (Cy3)
AAV-TVA-mCherry
RedDot2sectiond Horizontal(1.2 mm of z projection)

L

M

y
x
L

R

f Sagittal section

g

P

e

h

RV-GFP
RedDot2i

Sst (Cy3)
RedDot2j

AAV-TVA-mCherry
RedDot2AzyFig. 7 CUBIC-HV allows whole-organ cellular circuit analysis. a Experimental schematic of whole-brain rabies virus (RV) tracing with cell-type
immunolabeling. b Whole-brain image of the RV-injected Gad2-Cre adult mouse brain reconstituted with Imaris software. TVA-mCherry and RV-GFP were
injected into left M1 region of the cerebral cortex. Voxel size 8.3 × 8.3 × 9 μm3. Scale: 2 mm. c Anti-Sst antibody staining channel was merged with theimage in b. Scale: 2 mm. d, e Enlarged horizontal section images at the indicated positions in c, showing the RV-labeled neurons in the local and ipsilateral
corticocortical circuits. Scale: 0.5 mm. f Reconstituted sagittal (y–z) section at the position indicated in d. Scale: 0.5 mm. g-j Cropped and enlarged images
at the positions indicated in f. Starter neurons (green and magenta) and input neurons (green) with or without an Sst signal could be identiﬁed with singlecell resolution. Scale: 0.1 mm.

A594 and anti-α-SMA/Fab-A647 complexes] and compared themacroscopic distributions of GFAP-positive cells and α-SMApositive arteries (Fig. 9a). Using CUBIC-HV, we successfully
stained the whole adult marmoset brain hemisphere (Fig. 9b, c;
Supplementary Movie 5). In the macroscopic brain images ofboth species, the strongest GFAP signal was identiﬁed in thesurface region of the brain, a putative structure corresponding to
the glia limitans (Fig. 9b, c). However, the GFAP-positive area
was most prominent on the surface of the lateral ventricle and thepons of the marmoset brain, while in the mouse brain, it covered
the surface of the hindbrain and the ventral surface of the
hypothalamic regions. The observed differences between marmoset and mouse may reﬂect functional or regional differences inthe structure between species.
A similar distribution pattern of the major arteries of the brains
was observed in the middle cerebral artery (MCA), the posterior
cerebral artery (PCA), the basilar artery (BA), and their
peripheral branches in the brains (Fig. 9b). The reconstituted
12

sectional images further revealed that in both species, some of the
branches of the MCA and the PCA supply the striatum and the
hippocampus, respectively48 (Fig. 9c). In addition, we successfully
visualized the 3D distribution of perivascular astrocytes, whichsurround the corresponding arteries of both species very similarly(Fig. 9d). These data suggest evolutionary preservation of theoverall vascularity of the brain.
We then tested the compatibility of CUBIC-HV with humanspecimens. We stained a postmortem cerebellum block (~1 cm3)with BOBO-1, Cy3-conjugated anti-GFAP antibody, and anti-αSMA/Fab-A647 complex (Supplementary Fig. 11a). In thereconstituted sectional images, we compared the anatomy of thehuman cerebellum to the corresponding region of the marmoset
and mouse cerebellum (Supplementary Fig. 11b–i). GFAPpositive Bergmann glial cells in the molecular layer (ML) andastrocytes associated with the vessels and white matter were
evident in the human cerebellum (Supplementary Fig. 11d–e). In
contrast, GFAP-positive astrocytes were more obvious in the

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aDrug administration

Delipidation, 3D staining

RI matching & imaging

AnalysisSYTOX-G+
Anti-c-Fos

Saline3D peak detection

WT mice
MK-801z-stack
c-Fos signalbc
3D ventral view (raw image)MK-801 (+)

3D ventral view (convolved image)MK-801 (–)

MK-801 (+)

c-Fos (A594)
SYTOX-G

R

d

MK-801 (–)

c-Fos (convolved)
SYTOX-G

L

MK-801 (+)

MK-801 (–)

Sagittal section (0.5 mm of x projection)
c-Fos (A594)
SYTOX-G

DG

P

A

z
y

Fig. 8 CUBIC-HV allows whole-organ cellular function analysis. a Experimental schematic of whole-brain c-Fos antibody staining in different
pharmacological conditions. b Whole-brain images of c-Fos-immunolabeled adult mouse brains with or without administration of NMDA receptor
antagonist MK-801. The images were reconstituted with Imaris software. Voxel size 6.5 × 6.5 × 7 μm3. The white box indicates the position of thereconstituted sagittal image in d. Scale: 2 mm. c Resulting images following application of a convolution ﬁlter to the images in b. Scale: 2 mm.
d Reconstituted sagittal images of brains in b, showing uniform labeling of c-Fos-expressing cells. The c-Fos-expressing cells of the dentate gyrus (DG)
region were more obvious in the MK-801 (−) sample (arrowheads in insets). Scale: 1 mm (whole sagittal image) and 0.5 mm (insets).

granule cell layer (GCL) and the white matter of the marmoset
cerebellum (Supplementary Fig. 11g). GFAP signals in the mouse
cerebellum were generally weaker in these cerebellar layers andmore pronounced in the perivascular areas and white matter.
Since astrocytes play a critical role in cerebellar development49,
these distinct distributions of GFAP-positive astrocytes may
account for some of the structural differences in the cerebellar
layers among species. We conﬁrmed the uniformity of 3D
staining in the human and marmoset cerebellums by comparing
the sectional images reconstituted from 3D data with the 2Dstained images of the physical section samples (Supplementary
Fig. 11c, f, h).
These data indicate that the CUBIC-HV system could be
extended to adult primate tissues, allowing for 3D histologicalcomparisons among species. We summarize the concept of
CUBIC-HV, including delipidation, staining, clearing, 3D
imaging, and image analysis, in Fig. 9e.

Discussion
We revealed that PFA-ﬁxed and delipidated samples subjected totissue clearing can be characterized as charged and cross-linked
polypeptide gels (Fig. 1; Supplementary Fig. 1). The samples
exhibited a swelling-shrinkage behavior under various chemical
conditions, which resembled the patterns of ﬁxed protein gels(further discussed in the Supplementary Discussion section). We
exploited this insight to investigate essential experimental conditions for 3D staining under more simpliﬁed and controlled
conditions by using ﬁxed gelatin gel as a surrogate for the tissue(Fig. 2a; further discussed in Supplementary Discussion section).
This insight is also pertinent to our CUBIC-X expansion
microscopy approach36. Instead of using artiﬁcial waterabsorbing polymers, we chemically enhanced the inherent gel
properties of biological tissue in the CUBIC-X protocol. We also
used gelatin gels for screening tissue-expanding chemicals. The
current study further certiﬁes the validity of our past strategy.

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NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-020-15906-5abα-SMA (A647)
GFAP (A594)
SYTOX-G

MarmosetMarmoset

3D lateral view (hemisphere)

SYTOX-G+
Anti-GFAP (A594)
Anti-α-SMA (A647)

2

1

MCA
PCA
x
z

BA

y

Compareα-SMA (A647) 2
GFAP (A594)
SYTOX-G

Mouse

Mouse

3D lateral view (shown as hemisphere)

SYTOX-G+
Anti-GFAP (A594)
Anti-α-SMA (A647)

PCA
z
x
y

c

1

Coronal section (1 mm of y projection): position 1

MCA
BA

d

Coronal section (1 mm of y projection): position 2
α-SMA (A647)
GFAP (A594)
SYTOX-G

Coronal section (1 mm of y projection)
α-SMA (A647)
GFAP (A594)

MarmosetMarmoset

α-SMA (A647)
GFAP (A594)
SYTOX-G

Str
PCA
x

Hp
z

x
MCA

ACA

z

Mouse

Mouse

α-SMA (A647)
GFAP (A594)
SYTOX-G

α-SMA (A647)
GFAP (A594)
SYTOX-G

Str
Hp

PCA

z

z
ACA

MCA

x

x

e

Delipidation

3D staining

Analysis

3D imaging

Antibody

Stain
N

N

RI matching

I

I
NH 2

(Delipidated
and stained
sample)Cell detection

H 2N(Highly optimized
staining condition)

Embeddingin gel(optional)

z-stack

Pre-processing
3D rendering

3D
image

Atlas
data
Registration

Fig. 9 CUBIC-HV enables organ-level comparison of rodent and primate brains. a Experimental schema of the whole-organ comparison analysis ofrodent and primate brains. b Comparison of an adult marmoset brain hemisphere with the whole adult mouse brain (only the right hemisphere is depicted),
costained with SYTOX-G, GFAP (A594), and α-SMA (A647) antibodies. Note that the orientations were different between samples. Images werereconstituted with Imaris software. Voxel sizes 16.4 × 16.4 × 16 μm3 (for marmoset brain) and 8.3 × 8.3 × 9 μm3 (for mouse brain). MCA middle cerebral
artery, PCA posterior cerebral artery, BA basilar artery. Scale: 2 mm. c Reconstituted coronal sections of hemisphere images in b, showing the distributionsof corresponding vessel structures and GFAP-positive cells. Note that the different orientations of the sections (z–x and x–z for the marmoset and mouse
samples, respectively) could be compared because of the almost isotropic voxel resolution of the z-stack images. ACA anterior cerebral artery, Str
striatum, Hp hippocampus. Scale: 2 mm. d Magniﬁed images at the positions indicated in c, showing the similar distributions of vessel-associating GFAPpositive cells in the hippocampus. Voxel size in both images 8.3 × 8.3 × 9 μm3. Scale: 0.5 mm. e Flowchart of staining-based whole-organ imaging andimage analysis on CUBIC-HistoVIsion.

14

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In principle, the bottom-up and objective approach conductedhere is applicable to other 3D staining systems. Applying our
optimized protocol to the existing 3D staining and clearing
protocols AbScale and iDISCO+ markedly improved the staining
results (Fig. 3h; Supplementary Fig. 4d). In this study, we did nottest our protocol for hydrogel-tissue chemistry, which is adopted
in techniques including CLARITY, PACT, and ExM12,16,50.
However, a similar optimization approach to their 3D staining
protocols26,27 might be possible by considering the chemical
properties of acrylamide gel (Supplementary Fig. 1g).
CUBIC-HV has the potential to push the boundaries of 3D
histology. It can lead to discoveries of rarely reported cerebral
astrocytic foci in physiological conditions (Supplementary Fig. 6h;further discussed in Supplementary Discussion), systematic analysis of whole-brain neural circuitry and function (Figs. 7 and 8),organ-level histological comparisons between species (Fig. 9), and
3D clinical pathology of postmortem human specimens (Supplementary Fig. 11). CUBIC-HV can also be applied to otherorgans based on the consistency of gel properties among tissue
types (Supplementary Fig. 1h; Supplementary Fig. 7a). The
advantages of CUBIC-HV have boosted these achievements. First,
CUBIC technologies, including CUBIC-HV, are designed to bestable, easy, reproducible, and safe13. Second, CUBIC is compatible with FP reporters, allowing the simultaneous observation ofgenetically introduced ﬂuorescent protein and staining signals(Figs. 6 and 7). Third, a highly optimized staining condition
enables stable volumetric staining of whole organs and the wholebody with a practically feasible number of stains and antibodies(e.g., 5 µL of 1 mg/mL NeuN antibody product for the whole
mouse brain, see “Methods” for details) and without any specialized device, unlike techniques described in previous
studies26,27. The signal intensity and SBR of the acquired images
were sufﬁcient for subsequent computational image processing
and analysis. These results ease previous concerns regarding theapplicability of CUBIC to staining experiments51,52.
On the other hand, the current CUBIC-HV protocol still has
potential limitations. Multiplex protein labeling or simultaneous
detection of RNA tested in other studies25,53 are challenging forour current protocol. The possible inﬂuence on subcellular
structures and molecular integrity during clearing and staining
should be considered, as noted in other studies15,25,53, although
we conﬁrmed their preservation in our samples (Supplementary
Fig. 6i–n; further discussed in Supplementary Discussion section).
Issues related to thick primate tissues, such as the penetration
efﬁciency of dyes/antibodies or a substantial absorption of lightsheets in the sample (the so-called inner ﬁlter effect), should also
be taken into account.
Whole-organ proﬁling of protein expression and posttranscriptional modiﬁcation and localization, together withsingle-cell resolution resources36, has been increasingly demanded in recent years. A superior 3D staining protocol would also
facilitate 3D clinical pathology for more objective and accuratedisease diagnoses20–22. The 3D histology realized by CUBIC-HV
thus offers an ever-increasing opportunity for systemwide wholeorgan and whole-body analysis with single-cell resolution in life
science and medicine.
Methods
Tissue specimens. For most of the staining experiments, we used 8-week-old male
C57BL/6 N mice (Japan SLC). For the whole-brain c-Fos staining experiments(Fig. 8), 6-week-old C57BL/6 N mice were acclimated to our housing conditions(temperature range: 21–25 °C, humidity range: 40–70%, light cycle: on and off at 8
am and 8 pm) for two weeks. Then, we intraperitoneally administered 20 mg/kg
MK-801 in saline (Sigma-Aldrich #M107) or an equal volume of saline at ZeitgeberTime (ZT) 2 and sacriﬁced the animals at ZT 4. We also used an 8-month-old
female Thy1-YFP-H transgenic mouse42 (Fig. 6). Furthermore, we introduced 3week-old male AppNL-G-F knock-in mice41 (RBRC06344, provided by the RIKENARTICLE

BRC through the National BioResource Project of the MEXT/AMED, Japan) andhoused them until they were 9 months old for further use (Supplementary Fig. 8).
For the rabies virus labeling experiment (Fig. 7), an 8-week-old male Gad2-IRESCre knock-in mouse (Gad2tm2(cre)Zjh/J, Jackson laboratory #010802)45 was used.
The animal was injected with 150 nL of AAV mixture (serotype 2 CAG-FLEx-TCb
and CAG-FLEx-RG54) into the left primary motor cortex (1.2 mm lateral, 1.5 mm
anterior from bregma, and 0.45 mm ventral from the brain surface) and wasmaintained under a 7 am–7 pm light-dark cycle. Two weeks later, 150 nL of EnvA
pseudotyped RV-GFP (1 × 109 infectious particles mL−1, prepared following
Osakada et al.46) was injected into the same location. The brain was sampled 4 days
after RV injection.
For sampling the brains, the mice were sacriﬁced by an overdose ofpentobarbital (>100 mg/kg, i.p.; Somnopentyl, Kyoritsu Seiyaku, or pentobarbital
sodium salt; nacalai tesque #02095-04) and then transcardially perfused with 10 mL
of PBS containing ∼10 U/mL heparin followed by 20–30 mL of 4% PFA in PBS.
Then, the brain was excised from the skull and postﬁxed with the same ﬁxative for
8–24 h at 4 °C. These brains were used for the subsequent clearing procedure or
stocked at 4 °C in PBS with 0.05% NaN3 or −80 °C in O.C.T. compound until
required for use.
For Fig. 2, we used an infant marmoset (postnatal day 1) with a low birth weight(22 g) who was neglected by its parents. The animal was sacriﬁced by an overdoseof pentobarbital (>50 mg/kg, i.p.; Somnopentyl, Kyoritsu Seiyaku) after an
intramuscular injection of ketamine (30 mg/kg; Ketalar, Daiichi Sankyo
Propharma) and whole blood removal by transcardial perfusion with 20 mL of PBS
containing ∼10 U/mL heparin. Then, the animal was transcardially perfused with150 mL of 4% PFA in PBS and 20 mL of ScaleCUBIC-1 (modiﬁed CB perfusion14).
The skin was removed for the subsequent clearing procedure.
For Fig. 9, we used a ﬁxed brain hemisphere derived from an adult marmoset (7years old, female, 290 g body weight). For 2D-section staining (Supplementary
Fig. 11h), we used a ﬁxed cerebellum derived from another adult marmoset (6 years
old, male, 304 g body weight). The animals were sacriﬁced by an overdose ofpentobarbital (80–100 mg/kg pentobarbital, i.p.; Somnopentyl, Kyoritsu Seiyaku)
and then transcardially perfused with 200 mL of PBS and 350 mL of 4% PFA in PB.
The brain was excised from the skull and postﬁxed with the same ﬁxative overnightat 4 °C. The brain was washed with PBS before clearing.
All experimental procedures and housing conditions of the animals wereapproved by the Animal Care and Use Committees of the Graduate School of
Medicine and the Graduate School of Agricultural and Life Sciences of the
University of Tokyo, RIKEN Kobe Institute, National Institute for Physiological
Sciences, and the Graduate School of Medicine of Kyoto University. All of theanimals were cared for and treated humanely in accordance with the Institutional
Guidelines and with the recommendations of the United States National Institutesof Health for experiments using animals.
For Supplementary Fig. 11, we prepared ~1 cm3 blocks of human cerebellum
derived from an amyotrophic lateral sclerosis patient who underwent postmortem
pathological dissection at Niigata University Hospital after his death (male, 73
years old, died of respiratory failure). No histopathological alterations wereobserved in the cerebellum. The brain had been ﬁxed in 20% buffered formalin for
4 weeks before clearing. For the Klüver–Barrera (K–B) staining and 2D-section
staining experiments (Supplementary Fig. 11c, e, f), additional cerebellum parts
were dissected after 3 years in stock formalin. The study was approved by the
Ethical Review Boards of the Brain Research Institute, Niigata University (No.
1992) and the Graduate School of Medicine of The University of Tokyo (No. 10544
and No. 10714) and was performed in accordance with the committee guidelines
and regulations. Informed consent was obtained from the next of kin of the patient.

Dyes and dye-labeled secondary antibodies. In this study, we used the following
dyes and secondary antibodies: propidium iodide (PI, Molecular Probes, #P21493),
SYTOTM 16 (designated SYTO 16, Thermo Fisher Scientiﬁc #S7578), DAPI(Dojindo Molecular Technologies #D0523), SYTOXTM Green (designated SYTOXG, Thermo Fisher Scientiﬁc #S7020), BOBO™-1 Iodide (462/481) (designatedBOBO-1, Thermo Fisher Scientiﬁc #B3582), RedDot™2 Far-Red Nuclear Stain(designated RedDot2, Biotium #40061), NeuroTrace™ 640/660 Deep-Red Fluorescent Nissl Stain (Thermo Fisher Scientiﬁc #N21483), eosin (Acid Red 87, Tokyo
Chemical Industry/TCI #T0037), anti-NeuN (A488-conjugated, Merck Millipore
MAB377X), anti-mouse secondary IgG (Thermo Fisher Scientiﬁc, #A11029 forAlexa 488, #A21203 for Alexa 594), anti-rabbit secondary IgG (Thermo Fisher
Scientiﬁc #A21206 for Alexa 488, #A10040 for Alexa 546, #A21207 for Alexa 594,
#A31573 for Alexa 647), and FabuLightTM AfﬁniPure Fc speciﬁc Fab Fragments[Jackson ImmunoResearch laboratories; anti-mouse IgG1 (#115-547-185 for Alexa
488, #115-167-185 for Cy3, #115-587-185 for Alexa 594, #115-607-185 for Alexa
647), anti-mouse IgG2a (#115-587-186 for Alexa 594, #115-607-186 for Alexa 647),
anti-mouse IgG2b (#115-587-187 for Alexa 594), anti-rat IgG1 (#112-167-008 for
Cy3, #112-587-008 for Alexa 594), anti-rabbit IgG (#111-167-008 for Cy3, #111587-008 for Alexa 594, #111-607-008 for Alexa 647), and anti-goat IgG (#805-587008 for Alexa 594)]. The primary antibody and secondary Fab complexes wereprepared by mixing the constituent compounds at a 1:0.5 ~ 1:1 weight ratio andincubating for at least 1 h at room temperature. Then, the complex was added tothe staining buffer.

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Preparation of optically cleared tissue with the CUBIC protocol. Adult mousebrains were delipidated with ScaleCUBIC-1A [10 wt% of Triton X-100 (nacalaitesque #12967-45), 5 wt% of N,N,N’,N’-Tetrakis(2-hydroxypropyl)ethylenediamine(Quadrol, TCI #T0781), 10 wt% of urea (nacalai tesque #35904-45), and 25 mM
NaCl (nacalai tesque #31319-45) in water], ScaleCUBIC-1 [15 wt% of Triton X100, 25 wt% of Quadrol, and 25 wt% of urea in water] or CUBIC-L [10 wt% of Nbutyldiethanolamine (TCI #B0725) and 10 wt% of Triton X-100 in water],according to our published procedures13,40 (http://cubic.riken.jp). We typicallytreated the whole mouse brain samples for 10 days with ScaleCUBIC-1A or 3-4
days with CUBIC-L. In the case of AppNL-G-F mouse brains, the delipidation period
was increased to 7 days. The procedure with ScaleCUBIC-1 is described below (seethe “Quantiﬁcation of proteins and lipids in brain samples” section). After delipidation, the brains were intensively washed with PBS and stored in PBS with
0.05% NaN3 at 4°C until required for use. For imaging purposes, delipidated andstained mouse brains were RI-matched with CUBIC-R+(N) [45 wt% of antipyrine(TCI #D1876) and 30 wt% of nicotinamide (TCI #N0078) in water, buffered with
0.5% (v/w) N-butyldiethanolamine (pH ~10), (N) represents nicotinamide] or
CUBIC-R+(M) [the corresponding reagent of CUBIC-RA in Tainaka et al.40: 45 wt% of antipyrine and 30 wt% of N-methylnicotinamide (TCI #M0374) in water,
buffered with 0.5% (v/w) N-butyldiethanolamine (pH ~10), (M) represents Nmethylnicotinamide]. The sample was ﬁrst immersed in 1:1 water-diluted CUBICR+(N) or CUBIC-R+(M) at room temperature for 1 day. Then, the sample was
immersed in nondiluted CUBIC-R+(N) or CUBIC-R+(M) at room temperaturefor 2-3 days. The sample was ﬁnally embedded in 2% (w/v) agarose gel preparedwith CUBIC-R+(N) or CUBIC-R+(M) according to our published procedure36,40.
CUBIC-R+(M) was used for the preservation of ﬂuorescent protein signals in theThy1-YFP-H Tg brain and the RV-labeled brain (Figs. 6 and 7).
For clearing and PI staining of the infant marmoset body (Fig. 2), delipidationand decolorization after ﬁxation, CB perfusion and skin removal was continued in
ScaleCUBIC-1 with shaking for 2.5 months at 37 °C. The reagents were replaced
every 2–3 days during the ﬁrst month and then every week during the remaining
period. The sample was further preserved in ScaleCUBIC-1 for ~2 years at room
temperature until it was used for the PI staining and imaging experiment. Afterwashing in PBS, the sample was stained with PI (10 µg/mL) in 0.1 M PB containing
1.5 M NaCl for 7 days at 37 °C, washed with PBS and 10 wt% of imidazole (forNaCl removal), and then RI-matched with CUBIC-R+(N). The sample was ﬁrst
immersed in 1:1 water-diluted CUBIC-R+(N) at room temperature for 4 days.
Then, the sample was immersed in nondiluted CUBIC-R+(N) at room
temperature for 6 days. The CUBIC-R+(N) was refreshed every 2 days.
The adult marmoset brain hemisphere (Fig. 9) was immersed in CUBIC-L withshaking for 17 days at 37 °C and then for 6 days at 45 °C. The CUBIC-L wasrefreshed every 1–2 days during the delipidation. After 3D staining, the sample wasﬁrst immersed in 1:1 water-diluted CUBIC-R+(N) at room temperature for 1 day.
Then, the sample was immersed in nondiluted CUBIC-R+(N) at room
temperature for 5 days. The sample was ﬁnally embedded in 2% (w/v) agarose gel
prepared with CUBIC-R+(N). For 2D-section staining (Supplementary Fig. 11h), a
piece of dissected cerebellum (~5 mm thick) was treated with CUBIC-L for 14 days
at 37 °C followed by immersion in 40% sucrose/PBS and cryosection.
The delipidation of the human postmortem cerebellum block (Supplementary
Fig. 11) had been completed before we developed CUBIC-L. Thus, the specimen
was dissected to a size of ~1 cm3 and immersed in ScaleCUBIC-1A with shaking
for 9 weeks at 37 °C. The reagent was refreshed every 1–2 days during thedelipidation. After washing in PBS, the brain hemisphere was stored in nonfrozen
stock solution (0.1 M PB, 40% glycerol and 40% ethylene glycol) at −30 °C until
use. Before 3D staining, the stock solution was washed with PBS, and the sample
was further delipidated with CUBIC-L for an additional 3 days at 37 °C. After 3D
staining, the sample was ﬁrst immersed in 1:1 water-diluted CUBIC-R+(N) at
room temperature for 1 day. Then, the sample was immersed in nondiluted
CUBIC-R+(N) at room temperature for 3 days. The sample was ﬁnally embedded
in 2% (w/v) agarose gel prepared with CUBIC-R+(N). For 2D-section staining(Supplementary Fig. 11c, f), a piece of dissected cerebellum (2–3 mm thick) was
treated with ScaleCUBIC-1A for 7 days at 37 °C followed by immersion in 40%
sucrose/PBS and cryosection.

Quantiﬁcation of proteins and lipids in brain samples. PFA-ﬁxed mouse brains(ICR, 7 weeks old, male) were washed with PBS and immersed in 1:1 water-diluted
ScaleCUBIC-1 at 37 °C for 6 h with gentle shaking and then immersed in ScaleCUBIC-1 at 37 °C overnight with gentle shaking. The ScaleCUBIC-1 was refreshed
every day throughout the delipidation. Meanwhile, control samples were incubatedin PBS at 37°C with gentle shaking without solvent exchange. The day 0–5 brain
samples were then subjected to protein, lipid, and water quantiﬁcation. To quantify
the residual protein and lipid content, the samples were thoroughly crushed andthen sonicated in 1% Triton X-100 in PBS to obtain a homogenized suspension.
After adjusting for the total weight of each sample, the protein was quantiﬁed witha Microplate BCATM Protein Assay Kit–Reducing Agent Compatible (Thermo
Fisher Scientiﬁc #23252) and OD570 according to the instruction manual. The
phospholipid and cholesterol contents were quantiﬁed with LabAssayTM Phospholipid (FUJIFILM Wako #296-63801) and LabAssayTM Cholesterol (FUJIFILM
Wako #296-65801), respectively. The water content of the brain sample wasdetermined by measuring the constant weight lost after drying in a convection oven
16

(WFO-1001SD, EYELA) at 105 °C for 24–48 h, according to previous studies55,56.
The transmittance of the brain samples was quantiﬁed with a Spectral Haze Meter
SH 7000 (Nippon Denshoku Industries) according to our previous study14.
Measurement of SAXS of brain samples. For the SAXS experiments (Fig. 1;
Supplementary Fig. 1), we prepared 2 mm-thick coronal sections of the ScaleCUBIC-1A-delipidated mouse brains. The sections were immersed in PB containing various concentrations of NaCl and then embedded in Kapton ﬁlms.
The SAXS experiment for the samples was performed at the Frontier Soft
Matter Beamline (FSBL; BL03XU) of SPring-8 (Harima, Japan). The detector for
SAXS was a Pilatus3 1 M (DECTRIS), which was placed 4 m behind the sample. Xrays with a wavelength of 1.0 Å and a spot size of 60 × 200 µm were used. The Xray beam irradiated the cortical region of the coronal sections for 1–2 s at eachposition.
The other SAXS experiment was performed at the BL10C beam station in the
Photon Factory of KEK (Tukuba, Japan). The SAXS detector was a Pilatus3 2 M(DECTRIS), which was placed 2 m behind the sample. X-rays with a wavelength of
1.0 Å and a spot size of 180 × 600 µm were used. The X-ray beam irradiated thecortical region of the coronal sections for 60 s at each position.
The obtained 2D scattering proﬁles were converted to 1D scattering proﬁles as afunction of the magnitude of the scattering vector (q) with Igor Pro 6.3-based
custom-made software by circularly averaging the data around the beam center.
For 2D data with an anisotropic scattering proﬁle, simple line averaging at a given
image angle was performed instead of circular averaging. The backgroundscattering from the air and a sample cell (Kapton ﬁlms) was subtracted from theraw scattering proﬁles.
Swelling-shrinkage assay of the gels. For the swelling-shrinkage assays of gels
(Fig. 1; and Supplementary Fig. 1), we prepared cerebral hemispheres delipidatedwith ScaleCUBIC-1A, ﬁxed type-B gelatin gels (nacalai tesque #16631-05, 5% (w/v),
ﬁxed with 4% PFA), ﬁxed agarose gels (Agarose-S, FUJIFILM Wako #318-01195,
0.5% (w/v), ﬁxed with 4% PFA) and polyacrylamide gels [40% acrylamide/Bis 29:1
mix, nacalai tesque #06141-35, diluted to 8% (v/v) and polymerized with theaddition of 0.1% ammonium persulfate (nacalai tesque #02601-25) and 0.1%
TEMED (Sigma-Aldrich #T9281)]. These artiﬁcial gels were shaped into discoidal
gels by using the lid of a 96-well plate. For the assays, the prepared gels were ﬁrst
washed in water for 1 day at room temperature and then treated with a series ofsolvents [fractions of 0.5 to 500 mM NaCl, 0.6 M triethanolamine (TEA, FUJIFILM
Wako #145-05605, adjusted to pH 10.5), a mixture of 0.1 M HEPES (nacalai tesque#17514-15) and 0.1 M TEA (adjusted to pH 9.5–6.5), and a mixture of 0.1 M MES(DOJINDO #349-01623) and 0.1 M TEA (adjusted to pH 5.5), 70 µM or 0.4 mM ptoluenesulfonic acid monohydrate (TCI #T0267, adjusted to pH 4.5 or 3.5,
respectively) and fractions of 0 to 80% v/v of diluted acetone (nacalai tesque#00317-25) in water] at room temperature every day.
Gel images were captured by a Bio-Lad ChemiDoc XRS+ system and theincluded Image Lab software (version 4.1). We acquired bright-ﬁeld images (for thedelipidated brain) or autoﬂuorescence images under UV illumination (for theartiﬁcial gels) every day before the solvent exchange. The captured images were
processed with Fiji/ImageJ (http://ﬁji.sc/Fiji). A binary image was prepared with the“Auto threshold” function of the software and some manual adjustment to detect
the gel region. Then, the area was calculated with the “Analyze particle” function.
The gel size (S/S0) in each solution was calculated by dividing the area (S) of eachgel by the mean area of the gels in PBS solution (S0, n = 8).
The resulting swelling-shrinkage curves were not necessarily consistent withthose of past reports30,57 because the patterns can be affected by the concentrationof polymer, cross-linking methods, incubation time for gelation, or the type of
substituted residue.
Numerical simulation of 3D staining patterns inside the gel. Numerical integration of systems of partial differential equations was carried out by using
Mathematica software version 11.3 (Wolfram Research) with the built-in function“NDSolveValue”.
The reaction-diffusion process of the reversible binding and unbinding schemeof the reactive solute (i.e., dyes and antibodies) and its binding target in 2D space is
described below:
 2

∂½S
∂ ½S ∂2 ½Sð4Þþþ koff ½ST  kon ½S½T ;¼ Ddiff 
∂t
∂x2
∂y2
∂½T 
¼ koff ½ST  kon ½S½T ;
∂t

ð5Þ

∂½ST
ð6Þ
¼ koff ½ST þ kon ½S½T :∂t[S], [T] and [ST] denote the concentrations of the reactive solute, the binding
target and the solute-target complex, respectively. Ddiff, kon, and koff denote thediffusion coefﬁcient, the binding rate, and the unbinding rate, respectively. The
simulation space was set as a 20 × 20 square. A circle with a 1.0 radius, namely, thegel space, was placed at the center of the square. The simulation was started withthe following parameters and initial conditions unless otherwise stated: Ddiff = 1;

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NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-020-15906-5

kon = 1, koff = 0.01; initial [S] outside of the circle = 100; initial [S] within the circle= 0; initial [T] outside of the circle = 0; initial [T] within the circle = 100; initial[ST] for the entire simulation space = 0. The numerical integration was continued
until time = 1. All parameters and time scales were unitless and chosen such thatthe simulation with initial default values listed above resulted in an almost
homogenous distribution of [ST] inside the circle at time = 1. The time step ofnumerical integration was determined by the build-in Mathematica function“NDSloveValue”, with the option MaxStepFraction = 0.003. This option constrains
the maximum fraction of the total simulation range used for numerical integration.
Note that the binding target and the solute-target complex ([T] and [ST]) do
not diffuse outside of the circular gel. All numbers in this simulation are unitless
because the goal of the simulation was not to elucidate the exact physicalparameters needed to recapitulate the experimental results accurately.

Experimental evaluation of 3D staining conditions. For Figs. 2 and 3, 5% (w/v)
type-B gelatin gel (nacalai tesque #16631-05) mixed with 100 µg/mL salmon testis
DNA (Sigma-Aldrich #D1626) or 0.1-0.5 µg/mL rabbit immunoglobulin (SigmaAldrich #I5006) was dissolved in water containing 0.5% PFA. The gelatin solution
was poured into the holes of a Teﬂon plate (H 5 mm × φ 5 mm), incubated forgelation for at least 2 h at 4 °C and room temperature, and then ﬁxed with 4% PFA
in PBS overnight at 4°C.
The DNA-containing gelatin gels were 3D stained with PI (10 µg/mL) or SYTO
16 (1:100) for 3 h or 6 h, respectively, at 32°C in either 10 mM HEPES (pH 7.5) or
ScaleCUBIC-1A (0.25× diluted) containing NaCl. Plain gelatin gels were also
prepared and stained with eosin (0.2%) in the same buffers for 1 h. The buffers
were supplied with 20% sucrose for the gels to be cryosectioned immediately afterstaining.
The rabbit immunoglobulin-containing gelatin gels were 3D stained in HEPESTSC buffer [10 mM HEPES (pH 7.5), containing 0.1% (v/v) Triton X-100, 200 mM
NaCl, and 0.5% (w/v) casein (FUJIFILM Wako #030-01505)] containing antirabbit secondary IgG (A594) (10 µg/mL) for 48 h at 32°C. Then, the gels were
brieﬂy washed with PBS, immersed in 30% sucrose in PBS, and subjected tocryosection. The concentrations of rabbit immunoglobulin and gelatin in the gel,the concentration of secondary IgG, NaCl and Triton X-100 in the buffer, the typeof Alexa Fluor dye of the secondary IgG, or the staining temperature wereoccasionally changed to evaluate the parameters (Fig. 3, Supplementary Fig. 3).
Delipidated cerebellar hemispheres were 3D stained with PI (2 µg/mL) for 24 h,
SYTO 16 (1:150) for 24 h, DAPI (2.5 µg/mL) for 40 h, SYTOX-G (1:2500) for 40 h,
RedDot2 (1:150) for 23 h or NeuroTrace Deep-Red (1:100) for 24 h at 32°C ineither 10 mM HEPES (pH 7.5) or ScaleCUBIC-1A containing NaCl. Delipidated
cerebral hemispheres were 3D stained with eosin (2%) for 4 h at 32 °C in the same
buffers. Then, the samples were washed with PBS, immersed in 40% sucrose in
PBS, and subjected to cryosection. For post-2D staining, the sections were further
stained with DAPI (1:500) in PBS for 30 min at room temperature before
observation.
Delipidated cerebellar hemispheres were also used for 3D immunostaining. For
enzyme digestion (Fig. 3e), the delipidated samples were digested under stringent
conditions with collagenase-P (Sigma-Aldrich #11213857001, 1 mg/mL) in
carbonate buffer [mixture of 50 mM sodium carbonate (nacalai tesque #31310-35)
and 50 mM sodium hydrogen carbonate (nacalai tesque #31213-15) supplied with150 mM NaCl and 25-100 µM EDTA, adjusted to pH 10] or hyaluronidase (SigmaAldrich #H4272 or #H3884, 3 mg/mL) in CAPSO buffer [10 mM CAPSO (SigmaAldrich #C2278) and 150 mM NaCl, adjusted to pH 10] for 18 h at 37°C before 3D
staining. For the 1-step staining (Fig. 3c, e), the delipidated samples were 3D
stained with either primary antibodies [A488-conjugated mouse anti-NeuN (Merck
Millipore #MAB377X, 10 µg/mL), a complex of mouse anti-NeuN (Merck
Millipore #MAB377, 10 µg/mL) and anti-mouse secondary Fab (A488) (1:1 as theweight ratio), or mouse anti-NeuN (10 µg/mL) alone] in HEPES-TSC buffer [10mM HEPES (pH 7.5), 10% (v/v) Triton X-100, 200 mM NaCl, and 0.5% (w/v)
casein] for 3–5 days at 32 °C. After 3D staining, these samples were washed andimmersed in 40% sucrose in PBS and subjected to cryosection for observation. For
the 2-step staining (Fig. 3d), the mouse anti-NeuN-stained sample wassubsequently 3D stained with anti-mouse secondary IgG (A488) (10 µg/mL) in
HEPES-TSC buffer for 5 days at 32 °C. After 3D staining, these samples were
washed and immersed in 40% sucrose in PBS and subjected to cryosection for post
2D staining. The sections were brieﬂy ﬁxed with 4% PFA for 30 min at room
temperature and further stained with rabbit anti-NeuN primary antibody (Merck
Millipore ABN78, 1:500) in PBST [0.1% (v/v) Triton X-100] for 2 h at room
temperature followed by anti-rabbit secondary IgG (A594) (2 µg/mL) in PBST for
1 h at room temperature or stained only with anti-mouse secondary IgG (A594) (2µg/mL) in PBST for 1 h at room temperature.
The cryosections (a 200 µm thick portion of the gelatin gel, 2–3 mm from thetop, or a 50 µm thick section of the cerebellar hemisphere, ~2 mm from the lateraledge) were prepared and used for post-2D staining and imaging with an upright
ﬂuorescence microscope (BX51, Olympus) with a 4× objective lens (details below).
Quantiﬁcation of the signal intensity inside the gelatin gel was performed as shownin Fig. 2a. The images were processed with Fiji/ImageJ functions to remove outliers(radius = 10, threshold = 50), subtract background signals (background intensity
manually determined with a nonstained gel image), crop the gel region and adjust
its size (width = 1500 pixels). Then, the intensity proﬁles along the gel diameter

ARTICLE(1500 × 30 pixels along 6 diameters) were calculated. The ﬁnal proﬁle graph was
prepared with Excel software as the mean intensities ± SDs of these 6 diameter
proﬁles.
Antibody selection for 3D staining. We summarize all the antibodies and theirdilution ratios in Supplementary Data 1 and 2. We started by testing the antigenicity of the antibodies (Supplementary Data 1) on CUBIC-delipidated mousebrain sections. Among the 44 tested antibodies, 42 (95%) resulted in an expected
staining pattern on the CUBIC-L-delipidated sections (Supplementary Fig. 5;
Supplementary Data 1). We occasionally tested multiple antibodies for the sametarget [glutamic acid decarboxylase (Gad 65/67, dopamine transporter (DAT),
choline acetyltransferase (ChAT), PKCα, glial ﬁbrillary acidic protein (GFAP),
oligodendrocyte transcription factor 2 (Olig2), microtubule-associated protein 2(MAP2), c-Fos or β-amyloid]. However, the signal intensity or SBR was more
dependent on the antibody itself than on the targeted molecule (Supplementary
Data 1), suggesting that the different staining results (Supplementary Fig. 5) might
be more attributable to the detection ability and clonality of the antibody rather
than a decrease in the protein contents.
Then, we chose 40 antibodies (including mouse anti-NeuN in Fig. 3h, i) for the
3D staining tests of the delipidated hemisphere or whole brain (Supplementary
Data 1). In this step, we checked their signal intensities, SBRs, compatibilities withenzymes and additives, and penetration efﬁciencies during a reasonable period (12 weeks). We further excluded 15 antibodies due to low penetration efﬁciency, low
SBR, or high nonspeciﬁc signals. Ten of them were polyclonal antibodies, implying
a possibility that a mixture of antibodies for different epitopes might not give a
sufﬁcient initial concentration for each epitope, which might result in lower
penetration efﬁciency or SBR. The remaining ﬁve were monoclonal antibodies.
Two of them target a neuroﬁlament or spine protein, suggesting that richer
antigens or stronger binding perturbed their adequate penetration into the sample(Fig. 3a). The low concentration (0.03 mg/mL) of the neuroﬁlament antibody
product might have also accounted for the insufﬁcient result. One of the anti-βamyloid antibodies (82E1) was also categorized as having low penetration due to its
too-strong afﬁnity. A monoclonal anti-c-Fos antibody was excluded for further use
due to nonspeciﬁc signals in the vessels when used for 3D staining. As a result, we
ﬁnally selected 25 out of 40 (62.5%) as proper antibodies for the following wholeorgan staining according to their macroscopic staining patterns, penetration
efﬁciencies, and sufﬁcient signal intensities.
For antibody selection in the experiments depicted in Fig. 9 and Supplementary
Fig. 11, we adopted the criteria of (1) compatibility for the three different species,(2) expectation of preserved or varied patterns of labeled structures for comparison,(3) constraint in the multilabeling combination of IgG hosts and subtypes, and (4)sufﬁcient signal intensity and penetration efﬁciency based on the results withmouse brains. We chose the combination of anti-GFAP and α-SMA antibodies tomeet the criteria.
3D staining by CUBIC-HistoVIsion1.0. We provide a step-by-step protocol of 3D
staining by CUBIC-HistoVIsion1.0 in the Supplementary Methods section. In brief,
the CUBIC-delipidated tissue was stained with one of the proper nuclear stains[SYTOX-G (1:2500), BOBO-1 (1:400), RedDot2 (1:150)] in 4 mL of ScaleCUBIC1A containing 500 mM NaCl for 3-5 days at 37°C. If needed, the nuclear-labeled
sample was then digested under stringent conditions with 3 mg/mL hyaluronidase
in CAPSO buffer (pH 10) or 1 mg/mL collagenase-P in carbonate buffer (pH 10)
for 24 h at 37°C. Although we incorporated the step into the current protocol todemonstrate the digestion concept, it is considered optional due to possible
overdigestion and loss of antigenicity. Indeed, this step was occasionally skipped
for some antibodies because their antigens were incompatible with the treatment(Supplementary Data 1). Then, the sample was 3D stained with a dye-conjugatedprimary antibody or a complex of primary antibody and dye-conjugated secondary
Fab fragment (1:0.5–1:1 weight ratio) in HEPES-TSC buffer [10 mM HEPES buffer,
pH 7.5, containing 10% (v/v) Triton X-100, 200 mM NaCl, and 0.5% (w/v) casein]
at 25, 32, or 37°C for an appropriate duration (Supplementary Data 1). The buffer
was occasionally supplied with Quadrol [by diluting 50 wt% of stock to the ﬁnal 2.5
to 5%] and urea (0.5 to 2 M). The sample was immersed in a limited volume ofstaining buffer (e.g., 500 µL for a whole mouse brain in a 15 mL tube, Sarstedt#60.732.001) and shaken at 40-50 rpm during the staining; the slow shaking speed
was critical for preserving the fragile sample. We also conﬁrmed that higher
shaking speeds did not promote faster penetration of the antibody. For some
antibodies, we additionally incubated the staining tube at 4°C for 1-5 days tostabilize the signals. After staining, the sample was brieﬂy washed with 0.1 M PB
with 10% Triton X-100 followed by PB without Triton X-100 for 2 h in total at theantibody reaction temperature. Then, the sample was postﬁxed with 1% formaldehyde (nacalai tesque #16222-65) in 0.1 M PB for 5–24 h at 25 °C. The sample
was washed with PBS and used for RI matching with CUBIC-R+.
During the procedure, adequate care for the fragile samples was employed. We
tended to use a metal spoon to handle them and avoided placing them directly onto
a paper towel or tissue paper because the sample would become slightly sticky.
Some 3D staining tests [Supplementary Data 1, 3D staining result (withhemisphere) column] were performed with HEPES-TAC buffer (10 mM HEPES,
5% Triton X-100, 200 mM arginine-HCl (nacalai tesque #03323-32), 0.5% casein,ﬁnal pH = 8.0) according to our preliminary staining protocol.

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To evaluate the performance of our ﬁnal 3D staining protocol, the 3D- andpost-2D–staining results in the same sample were compared (Supplementary
Fig. 4b, c) as was performed in a previous report15. We stained the CUBIC-Ldelipidated whole adult mouse brains with the cell-impermeant nuclear stainSYTOX-G (1:2500 in 4 mL of ScaleCUBIC-1A, 500 mM NaCl) for 5 days at 37 °C
with gentle rotation (3D). The samples were horizontally cryosectioned andrestained with DAPI (2 µg/mL) in PBS for 2 h at room temperature (post-2D). As
the control for uniform staining, unstained horizontal cryosections were also
prepared and either used for SYTOX-G homogeneous staining (2D) (1:10000 in
PBST for 1 h at room temperature) or left unstained, after which both sets ofcryosections were stained with DAPI (post-2D). Similar staining procedures wereapplied for evaluating the 3D immunostaining procedure. CUBIC-L-delipidated
and hyaluronidase-treated whole adult mouse brains were 3D stained with acomplex of mouse anti-NeuN antibody (10 µg/mL) and secondary Fab (A594)
fragment (1:1 weight ratio) in HEPES-TSC buffer supplied with 2.5% Quadrol.
After 3D staining, 2D cryosections were prepared, reﬁxed, and restained withrabbit anti-NeuN antibody (1:1000 in PBST) for 2 h at room temperature, followedby anti-rabbit and anti-mouse secondary antibodies (A488 and A594, respectively,
1:1000 each in PBST) (post-2D). In the last step, anti-mouse secondary antibody(A594) was simultaneously used to enhance the mouse anti-NeuN antibody signals
because the secondary Fab was not fully retained during the post-2D staining. As
the control for uniform staining, a nonstained brain was ﬁrst cryosectioned andthen stained with a complex of mouse anti-NeuN antibody (1 µg/mL) andsecondary Fab (A594) (1:0.5 weight ratio) in PBST overnight at room temperature(2D). The sample was reﬁxed and further stained with rabbit anti-NeuN antibody
followed by anti-rabbit and anti-mouse secondary antibodies (A488 and A594,
respectively) (post 2D). The staining efﬁciency was evaluated by comparing (1) the
intensity proﬁle in the middle portion of the section and (2) the colocalization
parameter (Pearson’s R value) between the pre- and post-staining channels at theexterior (ROI-1) and interior (ROI-2) regions of the section (Supplementary
Fig. 4b, c).
AbScale-15, iDISCO+-17 (version Dec. 2016, https://idisco.info/idisco-protocol/),and SWITCH-mediated antibody labeling25 (Fig. 6C in the reference) were
performed according to their provided protocols (Supplementary Fig. 4d, e). The
materials that we used were D-sorbitol (nacalai tesque #32021-95), glycerol (nacalaitesque #17018-25), methyl-β-cyclodextrin (TCI #M1356), γ-cyclodextrin(FUJIFILM Wako #037-10643), N-acetyl-L-hydroxyproline (Santa Cruz #sc237135), and dimethylsulfoxide (nacalai tesque #13445-45) for AbScale, Tween-20(nacalai tesque #35624-15), dimethylsulfoxide (nacalai tesque #13445-45), donkey
serum (Sigma-Aldrich #D9663), glycine (TCI #G0317), heparin (Sigma-Aldrich#H3393), methanol (nacalai tesque #21915-93), hydrogen peroxide 30% (nacalaitesque #18411-25) and dichloromethane (Sigma-Aldrich #270997) for iDISCO+,
and SDS (nacalai tesque #31606-75) for SWITCH. We used the antibodies asfollows: A488-conjugated mouse anti-NeuN (5 µg/mL) in 1.6 mL of AbScale
solution (0.33 M urea and 0.5% Triton X-100 in PBS) for the original AbScale
protocol, mouse anti-NeuN (10 µg/mL) in 1.6 mL of primary staining buffer (5%DMSO, 3% donkey serum, 0.2%(v/v) Tween-20, 10 µg/mL of heparin in PBS)
followed by anti-mouse secondary IgG (A488) (10 µg/mL) in 1.6 mL of secondary
staining buffer (3% donkey serum, 0.2%(v/v) Tween-20, 10 µg/mL of heparin in
PBS) for the original iDISCO+ protocol, and a complex of mouse monoclonal antiNeuN IgG (10 µg/mL) and anti-mouse secondary Fab (A488) (1:1 weight ratio) in
0.5 mM SDS in PBS (SWITCH-Off buffer) or HEPES-TSC with 2.5% Quadrol for
the SWITCH-mediated antibody labeling or CUBIC-HV, respectively. PBST wasused as the SWITCH-On buffer.
Klüver–Barrera (K–B) staining. The formalin-ﬁxed, parafﬁn-embedded humancerebellar tissue was sectioned to 4 μm thickness. K–B staining was performed witha standard protocol58. Images were acquired with a CCD camera (DP73, Olympus)
attached to a microscope (BX53; UPlanSApo x40, NA: 0.95, Olympus).
Measurement of EGFP signals. To exclude the possibility of quenching during
the staining procedure, we measured the EGFP ﬂuorescent signals in the indicatedreagents (Supplementary Fig. 3e). The method was performed according to theprocedures from our previous study40. In brief, recombinant EGFP (50 µg/mL) was
prepared in each reagent in 96-well plates and incubated for 24 h at 37 °C withgentle shaking. The 509 nm emission by 475 nm excitation was measured with aplate reader (EnSpire, PerkinElmer) (n = 3 for each condition). The values were
calculated as the means ± SD of the ratio of ﬂuorescent signals before and after
incubation (24 h/0 h) from three independent experiments.
Imaging. The 2D-sectioned samples were imaged with upright ﬂuorescencemicroscopy (BX51, Olympus) with an objective lens (UPlanSApo 4×, N.A. = 0.16
and 20×, N.A. = 0.75), appropriate pairs of the ﬁlter and dichromatic mirror, andan sCMOS camera (ORCA-Flash4.0, Hamamatsu Photonics). The 16-bit image
covering the preparation was acquired with a motorized x–y stage (PRIOR) andtiled with the operational software (cellSens Dimension 1.18, Olympus).
The PI-stained and optically cleared marmoset body were imaged with acustom-built macrozoom light-sheet microscope (MVX10-LS, developed by
Olympus) as described in our previous studies19,36,40. We used a 0.63× objective
18

lens (MV PLAPO 0.63×, N.A. = 0.15, W.D. = 87 mm, Olympus) with 1× opticalzoom, a 532 nm laser, a bandpass ﬁlter (640/80 nm, φ 32 mm), and the tilingfunction of the operational software. During image acquisition, the optically
cleared sample was immersed in an RI-matched oil mixture composed of siliconeoil (HIVAC-F4, RI = 1.555, Shin-Etsu Chemical) and mineral oil (RI = 1.467,
Sigma-Aldrich #M8410), and the ﬁnal RI was adjusted to that of the cleared sample(~1.52). Sixteen-bit images were collected by scanning the sample in the z-direction
with a 100 µm step size.
All of the other macroscopic images of the 3D stained mouse, marmoset, andhuman brain specimens were imaged with our GEMINI system, another custombuilt light-sheet microscope combined with left and right light-sheet illumination
units (developed by Olympus) and two macrozoom microscopes (MVX10,
Olympus) placed at the front and back sides of the sample. Each microscope was
equipped with the same objective lens as above (MV PLAPO 0.63×), optical zoom
(0.63× to 4× range was used), a manual emission ﬁlter chamber, a tube lens (MVXTV1XC, Olympus), and an sCMOS camera (Zyla 5.5, Andor). A series of φ 32 mm
single bandpass ﬁlters (520/44, 585/40, 628/32, 641/75, and 708/75 nm, Semrock)were used to acquire signals from green to the near-infrared range. The excitation
light source, provided by a ﬁber-coupled diode or DPSS lasers (Omicron, SOLE-6
equipped with λ = 488, 532, 594 and 642 nm), was connected to the light-sheet
illumination units through a collimator and a beam-reﬂection mirror to switch
between the left and right light paths. The sheet illumination was generated by thelight-sheet illumination unit with a cylindrical lens. The thickness of the sheet
illumination could be adjusted with a mechanical slit in the range of ~5–10 µm.
Gel-embedded samples were placed onto a custom-made sample holder. The
holder was connected to a motorized x–y–z stage (x and y stages, Thorlabs, MTS50/
M-Z8E; z stage, Physik Instrumente, M-112.1DG) and immersed in an RI-matched
oil mixture composed of HIVAC-F4 and mineral oil (RI: ~1.51) in a custom-madesample chamber with illumination and imaging windows. All electronic devices
were controlled by custom-written LabVIEW software (National Instruments).
Sixteen-bit images were collected by scanning the sample in the z-direction with astep size of 3–16 μm depending on the optical zoom of MVX10. A sheet
illumination thickness of 5 or 10 µm was selected according to the step size. We
collected the z-stack of the whole mouse brain and human cerebellar specimen
from a single direction (front-to-back or back-to-front) because the clearing
efﬁciency was sufﬁcient for covering all of the sample areas without a visible decayof image quality. For the whole marmoset hemisphere, we used the two
microscopes (placed on either side of the sample) to complement the image qualityof deeper regions. We also applied an image acquisition sequence to achieve ahomogeneous light-sheet thickness throughout the ﬁeld of view in each x–yimage59. Thus, we collected several z-stacks by shifting the focus of the sheet
illumination so that the confocal parameter of the beam waist covered the wholesample area of each x–y image after tiling.
We determined the resolution of the images collected by GEMINI as follows.
The typical voxel size of the data was 8.3 or 6.5 μm in the x–y dimensions and 9 or
7 μm in the z dimension (using a 0.63× objective with 1.25× or 1.6× optical zoom,
respectively). Here, the voxel size was calculated with the pixel size of the sCMOS
sensor (6.5 μm2/pixel) and the step size of the z-axis (9 or 7 μm). According to the
Nyquist–Shannon sampling theorem, the resolving power based on the voxel size
can be determined as 16.6 or 13 μm for the x–y dimensions and 18 or 14 μm for thez dimensions. Since these values were larger than the optical resolution of the
microscope (x–y: ~6.6 or 4.2 μm at λ = 550 nm, provided by Olympus, z: ~10 μm at
λ = 550 nm, based on the effective N.A. for light-sheet illumination ~0.03), thevoxel size of the images accounts for the resolution of the data. Since CUBIC-R+
expands the sample almost 1.5-fold, the corresponding voxel resolution was ~11.1
or 8.7 μm for the x–y dimension and 12 or 9.3 μm for the z dimension before
clearing. The resolution range is similar to the range of cell body and nucleus sizes
and is thus sufﬁcient for resolving each nucleus in the images (Fig. 3j) as well as forcomputationally detecting sparsely labeled cell bodies/nuclei (SupplementaryFigs. 9 and 10).
For highly magniﬁed imaging of 3D synaptophysin staining samples(Supplementary Fig. 6n), an inverted confocal microscope (IX83, FV3000 system,
Olympus) equipped with a 60× objective lens (UPLSAPO60XO, N.A. = 1.35, W.D.
= 0.15 mm, Olympus) and a 594 nm laser were used. A single 16-bit x–y image was
acquired with 2× digital zoom (FOV: 106.1 × 106.1 µm2, 4096 × 4096 pixels, 25.895
nm/pixel).

Image processing. The whole mouse brain images acquired by the GEMINI
system were processed as follows. First, six focus-shifted images (three positions ×left and right illuminations) at each z position were tiled to produce a single image.
The x position of the tiling edge was determined by comparing the signal contrast(corresponding to the degree of sheet focusing) in the neighboring focus-shifted x–y images at a representative z position. In most cases, we automatically calculated
the tiling x position by using the nuclear staining images at the middle z position of
the sample with a custom-written ImageJ macro. In case the algorithm did notproperly work due to insufﬁcient contrast in the images, we manually determined
the tiling x position. Before tiling, the mean intensity among the images wasequalized. After tiling, the resulting 16-bit images were converted to 8-bit, andblank regions were trimmed to reduce the ﬁle size. The noise signals in the images,
attributed to particles in the embedding gel or aggregations of antibody, were

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occasionally removed by ﬁlters as follows: (1) noise pixels outside the brain area
were selected according to an intensity threshold, and the “Remove outlier”
function was applied, (2) noise pixels were selected according to an intensity
threshold higher than that of the staining signals, and the “Remove outlier”
function was applied or the intensity was replaced with zero, or (3) noise pixels
were selected with a combination of an intensity threshold and manual selection,and the “Clear function” was applied (Supplementary Data 2). Finally, the x–ypositions among the different channels were manually adjusted if needed.
To estimate light-sheet absorption in the tissue (Supplementary Fig. 4g), ﬁve
consecutive images were selected from the middle of the z-stack of NeuN-stained
whole mouse brain data. These images were projected with the “Maximum
intensity” function, and the “Subtract Background” function (radius = 70) in Fiji/
ImageJ was then applied to separate the signal from the background. The lightsheet absorption was evaluated by comparing the intensity distribution of thelateral and medial parts of the background image. The collected intensity proﬁleswere plotted with R (version 3.6.1).
To enhance the c-Fos staining signals (Fig. 8c; Supplementary Fig. 10b), we set
an intensity threshold for deleting the background signals and then applied a 2D
maximum ﬁlter (radius = 1), 2D Gaussian blur (sigma = 1), and a convolution
ﬁlter with the kernel deﬁned below:
01
1 1 1 1 1
C
B
B 1 1 3 1 1 CCB
7
3 1 Ck¼B
C:
B 1 3CB@ 1 1 3 1 1 A
1 1 1 1 1
For the human cerebellar specimen (Supplementary Fig. 11), four focus-shifted
images (two positions × left and right illumination) at each z position werecollected. The images at each illumination were tiled, and the resulting left andright tiled images were then merged with the “Max intensity” function. The noise
removal ﬁlters described above and adjustment of the x–y position among thechannels were also applied.
For the marmoset brain hemisphere (Fig. 9 and Supplementary Fig. 11), six
focus-shifted images (three positions × left and right illumination) at each z
position were collected. The images of each illumination were tiled, and theresulting left and right images were then merged with the “Max intensity” function.
For the whole hemisphere image (16.4 × 16.4 × 16 µm3 voxel resolution), the zstacks were collected from two imaging directions (lateral-to-medial and medialto-lateral) to complement the image quality of the deeper regions. Therefore, theleft–right merged images at the same z position acquired from the opposite
directions were registered with the Descriptor-based registration (2D/3D) plugin(https://github.com/ﬁji/Descriptor_based_registration/) and the Transform J
plugin60 (https://github.com/imagescience/TransformJ/). Then, the registeredimages were merged with the “Max intensity” function. The noise removal ﬁlters
described above and adjustment of the x–y positions were also applied. In
particular, we applied the “Subtract Background” function (radius = 10) to the αSMA channel images due to the low SBR. We also stained the other hemispherewith the same antibody and conﬁrmed that the low SBR result was speciﬁc for the
single experiment rather than the staining protocol itself.
To obtain magniﬁed images of these samples, we used a thinner (~5 µm) lightsheet with a narrower confocal parameter. Thus, four to ﬁve images with different
focused positions of either the left or right illumination direction were used fortiling. The tiled image was similarly processed as above.
For the LSFM images, the imaging and processing conditions are summarizedin Supplementary Data 2. The z-stack data, acquired by LSFM and processed asabove, were reconstituted and visualized as a pseudocolored image with Imaris
software (version 8.4, Bitplane). The intensity and gamma values were manually
adjusted to prepare ﬁgure panels. Computational processing of other acquired
images was performed by using Fiji/ImageJ. The intensity was adjusted with thebrightness and contrast functions. Occasionally, some images were cropped, andtheir orientations were adjusted to prepare ﬁgure panels. The reconstituted x–z or
y–z images in Fig. 3j and Supplementary Figs. 5a, 6g, and 9c were prepared with thereslice function.
Fusion of 10 different whole-brain images. Our virtual multiplex registration
pipeline40 (https://github.com/DSP-sleep/Landscape_pipeline/wiki) was used to
combine ten different whole-brain images. The nucleus channel of each wholebrain dataset stained with a nuclear stain (SYTOX-G or BOBO-1) and an antibody(anti-calbindin D28K, PV, Sst, Th, ChAT, Dbh, Tph2, Copeptin, or phospho-Nf)
was registered and aligned to the nucleus channel of an anti-NeuN-stained wholebrain dataset with the symmetric normalization (SyN) algorithm implemented in
the ANTs software61. The obtained transformation matrix was applied to theantibody-stained channel without losing resolution. The resulting image stacks
were reconstituted with Imaris.
Computational cell detection. Labeled cells were computationally detected byusing Fiji/ImageJ as follows (Supplementary Figs. 9 and 10). For RV-labeled data,(0) an image stack for each channel cropped around the injection site was prepared;(1) the original stack was divided by duplicated and Gaussian-blurred stacks

ARTICLE(sigma = 1) to remove the background (this step was optional and used only for the
RV-GFP and Sst-Cy3 images); (2) the “Subtract Background” function (rolling = 1)
was applied to the stack; (3) the stack was expanded three times in the x–y
directions to increase detection accuracy; (4) a Gaussian blur ﬁlter (sigma = 2) wasapplied; (5) a Laplacian ﬁlter (sigma = 2) from the Feature J plugin (included in
The ImageScience library) was applied. The resulting stack was converted from 32bit to 16-bit; (6) a minimum ﬁlter (radius = 1.5) was applied (this step was optional
and used only for RV-GFP and AAV-TVA-mCherry images); (7) the “SetThreshold” function with a manually adjusted value was applied to eliminate
background signals. A different value was determined for each channel; (8) the “2D
Find Maxima” function was applied with a manually adjusted noise tolerance
value. A stack with single pixels of maxima positions was generated; (9) the
Maximum ﬁlter was applied to enlarge the maxima points from one pixel to ﬁve
pixels; (10) the 3D centroids of the maxima objects were calculated by the “3D
Object Counter” function. The size ﬁlters were as follows: 6–76 pixels for RV-GFP
and AAV-TVA-mCherry and 6–36 pixels for Sst. The results were output as a stackwith centroid spots and a CSV ﬁle of the result table. The centroid stack was resized
to the original x–y dimensions; and (11) a Gaussian blur ﬁlter was ﬁnally applied tothe stack to adjust the spot size to the labeled cell size. The calculations for 11.3 MBof cropped data were completed within a few minutes by using a 2018 15-inch
MacBook Pro (macOS High Sierra version 10.13.6, 2.9 GHz Intel Core i9 processor,
and 32 GB 2400 MHz DDR4 memory).
For the c-Fos-labeled whole-brain data, we applied the “3D Find Maxima”
function rather than the 3D centroid calculation for 2D Maxima objects adopted in
the ClearMap algorithm17. The same parameter values were used for the twodatasets (MK-801 + or −) of the c-Fos-labeled brains. 0) The original stackcovering the whole brain was cropped to prepare 100 partitioned stacks with 10pixel x–y margins; (1) the “Subtract Background” function (rolling = 1) wasapplied to the single stack; (2) the stack was expanded three times in the three
dimensions (x–y–z); (3) a 3D Minimum ﬁlter (radius x = y = z = 1) was applied;(4) a 3D Gaussian blur ﬁlter (sigma x = y = z = 1) was applied; (5) the “SetThreshold” function with a manually determined value was applied to eliminate
background signals; (6) the “3D Find Maxima”62 function was applied with aradius size of x = y = z = 2.5 and a noise tolerance of 1. A stack with single pixels
of maxima positions and a CSV ﬁle of the result table were generated. Every
120 slices, 5 marginal slices were separately calculated and integrated into the single
stack generated above; (7) after calculating all 100 stacks, they were resized to theoriginal x–y–z dimensions and then tiled after removing the 10-pixel x–y margins;and (8) the 3D Maximum ﬁlter and 3D Gaussian blur ﬁlter were ﬁnally applied tothe stack to adjust the spot size to the labeled nucleus size. It took ~20 h to performthe calculations for ~8 GB of whole-brain data by using a workstation PC (64-bit
Windows 10 Pro for Workstations, Intel(R) Xeon(R) E5-2687W v4 @ 3.00 GHz,
two processors, 192 GB RAM, and 4× SSD RAID0 storage).
We calculated the sensitivity (number of cells correctly detected by thealgorithm/number of cells in the ground truth data) and the positive predictive
value (number of cells correctly detected by the algorithm/total number of detected
cells by the algorithm). The ground truth data were prepared by manual
segmentation of the labeled cells with ITK-SNAP63. The cells correctly detected by
the algorithm were determined by comparing the coordinates of the cells (centroid/
3D Maxima) with those of the ground truth. Here, we selected regions where
computational cell detection was likely difﬁcult due to the high cell density: for the
RV- and Sst-labeled brains, we used the region already shown in the panels(Supplementary Fig. 9b-c) to detect the double- (RV-GFP+, Sst+) or triple- (AAVmCherry+, RV-GFP+, Sst+) labeled cells. For the Gad2-Cre strain, RV labeling
depicts the local network of GABAergic neurons around the injection site. In
contrast, such GABAergic input in other cortical regions (e.g., the somatosensory
cortex) is rare [Fig. 7e and the mouse connectivity map of the Allen brain atlas,#167441329 (AAV-labeled projection S1 barrel of Gad2-IRES-Cre strain), http://
connectivity.brain-map.org]. Therefore, it seems reasonable to focus on the region
rather than covering a larger area. Similarly, we used a cortical region from theMK-801-treated mouse brain to calculate the sensitivity and PPV of c-Fos-positive
cell detection (Supplementary Fig. 10c). The sensitivity and positive predictive
value (PPV), respectively, of the algorithm are as follows: 114/128 = 89.1% and114/115 = 99.1% for GFP+ cells; 54/73 = 74.0% and 54/55 = 98.2% for mCherry+cells; 110/169 = 65.1% and 110/115 = 95.7% for Sst+ cells; and 382/491 = 77.8%
and 381/381 = 100% for c-Fos+ cells.

Statistics and reproducibility. For Supplementary Fig. 3e, one-way ANOVA wasapplied to the data after the conﬁrmation of nonnormality and unequal variancewith the Kolmogorov–Smirnov test and Bartlett’s test, respectively. In this study, P< 0.05 was considered signiﬁcant. R (version 3.4.4) was used for the statisticalanalyses.
The quantiﬁcation of proteins and lipids in the brain and the swelling-shrinkage
assays of the gels and delipidated tissues were repeated with at least two
independent samples (Fig. 1 and Supplementary Fig. 1). The SAXS analyses were
performed with independent samples and detectors (SPring-8 and PF of KEK)
(Fig. 1). Most of the staining and imaging experiments shown in Figs. 2–9 andSupplementary Figs. 2–11, except for the marmoset hemisphere staining, wererepeated with at least two independent samples in the same or comparable
condition with slight modiﬁcation (e.g., staining period). All the results were

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reliably reproduced. Since we obtained only one marmoset brain (twohemispheres) and the other hemisphere was used to determine the 3D staining
condition with anti-α-SMA antibody, we could not carry out another replication
experiment for GFAP staining.
Reporting summary. Further information on research design is available in
the Nature Research Reporting Summary linked to this article.

Data availability
The data that support the ﬁndings of this study are available from the corresponding
author upon reasonable request.

Code availability
The codes for the custom-written ImageJ macro and the virtual multiplex registration
pipeline40 were deposited in our GitHub repositories (https://github.com/DSP-sleep/
CUBIC-HistVIsion.git, https://github.com/DSP-sleep/Landscape_pipeline/wiki). The
custom-made software for SAXS measurement data is available from the corresponding
authors upon reasonable request.

Received: 5 September 2019; Accepted: 31 March 2020;

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ARTICLE

Author contributions
E.A.S. and H.R.U. conceived and designed the study. E.A.S. and A. Kuno. initialized the
project. E.A.S and C.S. performed most of the experiments and the analysis. A. Kuno,
X.L., K.N., and M.S. performed the SAXS experiments. K.Tainaka measured the components of the tissue. K.L.O. and Y.Saeki conducted the simulation of the reactiondiffusion formula in the gel. K.M. and K. Touhara provided the Gad2-Cre KI mousebrains labeled with the RV system. K.I. and T.I. provided the adult marmoset brains. C.Y.
and H. Onoe provided the infant marmoset body. H.K. and A. Kakita provided thehuman postmortem cerebellum specimens and several antibodies for staining tests andperformed the K–B staining. M.I., T.U., and M.F. provided the human postmortem brain
specimens for determining clearing conditions. Y. Shimizu provided the recombinant
EGFP protein. T.S. and T.C.S. provided the AppNL-G-F knock-in mice, and H. Ono
stained the brains. E.A.S. and H.R.U. wrote the manuscript. All authors discussed theresults and commented on the manuscript text.

Competing interests
Acknowledgements
We thank all of the laboratory members at The University of Tokyo and the RIKEN Center
for Biosystems Dynamics Research (BDR), in particular, Y. Liu, R. Tanaka, Y. Saito, Y. Ueki,
S. Yada and R. Ohno for their support in sample preparation and experiments; T.C. Murakami and A. Kawasaki for help in clearing the infant marmoset body; H. Fujishima and K.
Matsumoto for help in introducing suitable antibody products; T. Mano and M. Kuroda for
improving the GEMINI system and for their helpful suggestions for image analysis, S. Shi for
helping with the statistical analysis, and T. Miyawaki and K. Wilkins for assisting with the
preparation of the manuscript. We also thank Dr R. Yoshida for helpful suggestions
regarding gel materials, Dr N. Mizushima for support in the measurement of EGFP signals,
Olympus Corporation, ISAX Corporation and CREDEN TECHNOLOGIES SDN BHD for
helping with the GEMINI system installation, and Bitplane for instruction in operating the
Imaris software. This work was supported by PRESTO from JST (JPMJPR15F4 to E.A.S.);
Grants-in-Aid for Young Scientists (A) (JSPS KAKENHI grant 15H05650 to E.A.S.); Grantsin-Aid for Scientiﬁc Research (B) (JSPS KAKENHI grant 19H03413 to E.A.S. and 18H02105
to K. Tainaka); Grants-in-Aid for Scientiﬁc Research on Innovative Areas (JSPS KAKENHI
grant 17H06328 to E.A.S., 17H05688 and 18H04543 to K. Tainaka); Grants-in-Aid for
Challenging Research (Exploratory) (JSPS KAKENHI grant 18K19419 to E.A.S. and
18K19373 to K. Tainaka); Grants-in-Aid from the Takeda Science Foundation (H.R.U., E.A.
S., and K.Tainaka); Grants-in-Aid from the Japan Foundation for Applied Enzymology (E.A.
S.); AMED-CREST (AMED/MEXT to H.R.U.) and CREST (JST/MEXT to H.R.U.); Brain/
MINDS (AMED/MEXT to H.R.U. and T.I.); the Basic Science and Platform Technology
Program for Innovative Biological Medicine (AMED/MEXT to H.R.U.); the Science andTechnology Platform Program for Advanced Biological Medicine (AMED/MEXT to H.R.
U.); Grants-in-Aid for Scientiﬁc Research (S) (JSPS KAKENHI grant 18H05270 to H.R.U.);
the Collaborative Research Project of the Brain Research Institute, Niigata University (to H.
R.U.); Grants-in-Aid from the Human Frontier Science Program (H.R.U.); Grants-in-Aid for
Scientiﬁc Research (A) (JSPS KAKENHI grant 16H02277 to M.S.); Grants-in-Aid for Scientiﬁc Research (JSPS KAKENHI grant 19J13188, to H. Ono); and the ERATO Touhara
Chemosensory Signal Project from JST, Japan (JPMJER1202 to K. Touhara). The AppNL-G-F
knock-in mouse strain (RBRC06344) was provided by RIKEN BRC through the National
BioResource Project of the MEXT/AMED, Japan. The SAXS experiments were performed at
the Frontier Soft Matter Beamline (FSBL; BL03XU), SPring-8, Hyogo, Japan, with theassistance of Dr Hiroyasu Masunaga and Dr Atsushi Izumi (Proposal No. 2015B7260,
2016A7210) under the approval of the Photon Factory Program Advisory Committee(Proposal No. 2015G134).

RIKEN has ﬁled a patent regarding CUBIC reagents, in which E. A. S., K. Tainaka, and
H. R. U. are co-inventors. CUBICStars CO., LTD. has ﬁled a patent regarding CUBICHV reagents, in which E. A. S., and H. R. U. are co-inventors. Part of this study was
performed in collaboration with Olympus Corporation and Medical & Biological
Laboratories Co., Ltd. (MBL). The remaining authors declare no competing interests.

Additional information
Supplementary information is available for this paper at https://doi.org/10.1038/s41467020-15906-5.
Correspondence and requests for materials should be addressed to E.A.S. or H.R.U.
Peer review information Nature Communications thanks Ludovico Silvestri and theother, anonymous, reviewer(s) for their contribution to the peer review of this work. Peerreviewer reports are available.
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© The Author(s) 2020

Etsuo A. Susaki 1,2 ✉, Chika Shimizu2, Akihiro Kuno 1,3, Kazuki Tainaka4, Xiang Li 5, Kengo Nishi5,
Ken Morishima 5, Hiroaki Ono1, Koji L. Ode1,2, Yuki Saeki6, Kazunari Miyamichi7,8, Kaoru Isa9,10,
Chihiro Yokoyama11, Hiroki Kitaura12, Masako Ikemura13, Tetsuo Ushiku13, Yoshihiro Shimizu 14,
Takashi Saito15,16, Takaomi C. Saido15, Masashi Fukayama13, Hirotaka Onoe17, Kazushige Touhara 7,8,18,
Tadashi Isa9,10, Akiyoshi Kakita12, Mitsuhiro Shibayama5 & Hiroki R. Ueda 1,2 ✉1Department of Systems Pharmacology, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan.
Laboratory for Synthetic Biology, RIKEN Center for Biosystems Dynamics Research, 1-3 YamadaokaSuitaOsaka 565-5241, Japan. 3Department of
Anatomy and Embryology, Faculty of Medicine, University of Tsukuba, 1-1-1 Tennodai, Tsukuba 305-8575, Japan. 4Department of System
Pathology for Neurological Disorders, Brain Research Institute, Niigata University, 1-757 AsahimachidoriChuo-kuNiigata 951-8585, Japan.
5
Neutron Science Laboratory, The Institute for Solid State Physics, The University of Tokyo, 5-1-5 KashiwanohaKashiwaChiba 277–8581, Japan.
2

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6Faculty of Medicine, The University of Tokyo, 7-3-1 HongoBunkyo-kuTokyo 113-0033, Japan. 7Department of Applied Biological Chemistry,
Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1 YayoiBunkyo-kuTokyo 113-8657, Japan. 8ERATO Touhara
Chemosensory Signal Project, Japan Science and Technology Agency, The University of Tokyo, 1-1-1 YayoiBunkyo-kuTokyo 113-8657, Japan.
9Department of Neuroscience, Graduate School of Medicine and Faculty of Medicine, Kyoto University, Yoshida-konoe-cho, Sakyo-kuKyoto 6068501, Japan. 10Institute for the Advanced Study of Human Biology (WPI-ASHBi), Kyoto University, Kyoto 606-8501, Japan. 11Laboratory for Brain
Connectomics Imaging, RIKEN Center for Biosystems Dynamics Research, 6-7-3 Minatojima-minamimachi, Chuo-ku, KobeHyogo 650-0047,
Japan. 12Department of Pathology, Brain Research Institute, Niigata University, 1-757 AsahimachidoriChuo-kuNiigata 951-8585, Japan.
13
Department of Pathology, Graduate School of Medicine, The University of Tokyo, 7-3-1 HongoBunkyo-kuTokyo 113-0033, Japan. 14Laboratory for
Cell-Free Protein Synthesis, RIKEN Center for Biosystems Dynamics Research, 6-2-3, Furuedai, SuitaOsaka 565-0874, Japan. 15Laboratory forProteolytic Neuroscience, RIKEN Center for Brain Science, 2-1 HirosawaWakoSaitama 351-0198, Japan. 16Department of Neurocognitive Science,
Institute of Brain Science, Nagoya City University Graduate School of Medical Science, 1 Kawasumi, Mizuho-cho, Mizuho-ku, Nagoya, Aichi 4678601, Japan. 17Human Brain Research Center, Graduate School of Medicine, Kyoto University, 54 Shogoin-kawahara-choSakyo-kuKyoto 6068507, Japan. 18International Research Center for Neurointelligence (WPI-IRCN), UTIAS, The University of Tokyo, Tokyo 113-0033, Japan.
✉email: suishess-kyu@umin.ac.jp; uedah-tky@umin.ac.jp

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NATURE COMMUNICATIONS | (2020)11:1982 | https://doi.org/10.1038/s41467-020-15906-5 | www.nature.com/naturecommunications