Hydrogel-Tissue Chemistry: Principles and Applications

Viviana Gradinaru

Jennifer Treweek

Kristin Overton

, and

Karl Deisseroth

2,3,4

Division of Biology and Biological Engineering, California Institute of Technology, Pasadena,

California 91125, USA; viviana@caltech.edu

Department of Bioengineering, Stanford University, Stanford, California 94305, USA;

deissero@stanford.edu

Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, California

94305, USA

Howard Hughes Medical Institute, Stanford University, Stanford, California 94305, USA

Abstract

Over the past five years, a rapidly developing experimental approach has enabled high-resolution

and high-content information retrieval from intact multicellular animal (metazoan) systems. New

chemical and physical forms are created in the hydrogel-tissue chemistry process, and the

retention and retrieval of crucial phenotypic information regarding constituent cells and molecules

(and their joint interrelationships) are thereby enabled. For example, rich data sets defining both

single-cell-resolution gene expression and single-cell-resolution activity during behavior can now

be collected while still preserving information on three-dimensional positioning and/or brain-wide

wiring of those very same neurons—even within vertebrate brains. This new approach and its

variants, as applied to neuroscience, are beginning to illuminate the fundamental cellular and

chemical representations of sensation, cognition, and action. More generally, reimagining

metazoans as metareactants—or positionally defined three-dimensional graphs of constituent

chemicals made available for ongoing functionalization, transformation, and readout—is

stimulating innovation across biology and medicine.

Keywords

CLARITY; hydrogels; metareactant; HTC; hydrogel-tissue; clearing

INTRODUCTION

In the study of complex biological systems, a powerful experimental approach is that of

analysis or disassembly (removing components, such as a particular type of cell or complex

DISCLOSURE STATEMENT

All protocols, software, and other information regarding these methods is freely available from the authors and online, and

disseminated via free hands-on training courses (

clarityresource-center.org

and

clover.caltech.edu

). V.G. and K.D. have disclosed

intellectual property regarding HTC methods to Caltech and Stanford, some of which has been licensed to ClearLight Diagnostics,

which is exploring applications for cancer diagnostics, and with which there are consulting arrangements and equity; V.G. and K.D.

each also have grant support from the US federal government (National Institutes of Health and National Science Foundation) to

further develop, apply, and disseminate these methods.

Published as:

Annu Rev Biophys

. 2018 May 20; 47: 355–376.

HHMI Author Manuscript

of molecules, from the native context for further study). For example, the current revolution

in cancer treatment was in part enabled by reductionist molecular and cellular-level analysis

of isolated cancer cells and of specific immune-system cells that play a role in suppressing

tumor growth. The success of this analytical paradigm has, in part, extended to neuroscience

as well; studies of isolated neurons and axons have facilitated elucidation of the fundamental

logic of single-neuron information processing.

However, for systems like the intact vertebrate brain (composed of 10

—10

interconnected

neurons and characterized by crucial emergent properties), studying constituent components

in isolation can provide little insight into many of the most significant mysteries.

Alternatively, converting the brain—or more broadly the entire metazoan (multicellular

animal) organism—into an assembly of reactants anchored onto a new and versatile three-

dimensional (3D) coordinate system has recently emerged as a complementary strategy (

). Coupling individual subsets of chemically defined biomolecules to functional groups,

covalently anchoring or entangling these in turn within a polymer lattice, and then working

with this structure (effectively a 3D assembly of spatially tagged molecular reactants) (

) has already opened the door to a diverse array of novel approaches and discoveries in

biology.

The technique builds in part from (among several other foundations in science and

engineering) the chemistry of hydrogels, which are 3D polymeric networks of connected

hydrophilic components. Gels and polymers have a long history of use in biology, including

for providing physical support of tissues during sectioning and imaging, as well as for a

number of important clinical applications in regenerative medicine and tissue engineering.

But in the basic science of hydrogel-tissue chemistry (

), specific classes of native

biomolecules in tissue are immobilized or covalently anchored (for example, through

individualized interface molecules to gel monomer molecules) and precisely timed

polymerization causing tissue-gel hybrid formation is triggered within all the cells across the

tissue in an ordered and controlled process (Figure 1) to ultimately create an optically and

chemically accessible biomolecular matrix. Indeed, when the biomolecules of interest are

thereby transferred to the polymer lattice, a robust new composite hydrogel-tissue material

results (

), which becomes the substrate for future chemical and optical interrogation

that can be probed and manipulated in new ways. This approach has been diversified (Figure

2) to address needs and opportunities in organisms and tissues across biology (including in

cancer diagnostics, bacterial and HIV infection of mammalian tissues, developmental

biology, parkinsonism, Alzheimer’s disease, multiple sclerosis, autism, drug abuse, and fear/

anxiety disorders). Here, we review the fundamentals of this approach, the rapidly

expanding scope of discoveries that have resulted, and emerging directions and opportunities

for the future.

DEVELOPMENT OF METHODS

Biomolecule functionalization and multistep linkage to a versatile tissue-hydrogel scaffold

(Figure 2) within the cells of vertebrates (mouse, fish, and human) (

) were

described in an initial version called CLARITY; this method was optimized for application

to the vertebrate nervous system (

). The hydrogel-tissue hybrid brains were

Gradinaru et al.

Page 2

Annu Rev Biophys

. Author manuscript; available in PMC 2019 February 02.

HHMI Author Manuscript

transparent (i.e., clarified) and thus permissive of intact whole-organ imaging at high

resolution (

). It was noted that the resulting hydrogel-tissue hybrid “expanded” upon lipid

removal in aqueous solution but “did not cause net tissue deformation...[R]emaining

secured in place were fine structural details” (

, p. 334) since the expansion could be

reversed with a solution change. Other diverse strategies for reducing opacity of intact tissue

had been explored for years (though with varying degrees of efficacy and versatility) (Figure

3), but transparency was not the only experimental leverage achieved with the hydrogel-

tissue chemistry (HTC) approach; for example, the new hybrids were designed to be

macromolecule permeant—enabling multiple rounds of molecular interrogation of preserved

biomolecules (proteins and nucleic acids) that had been anchored into the new physical

structure (

125

Single-photon confocal microscopy was initially used to image many-millimeter-thick

blocks of the resulting clarified and fluorescently labeled human brain tissue, zebrafish

central nervous systems, and whole adult mouse brain hemispheres (

). Diverse lines of

work eventually emerged from this publication (

); as was noted therein, “infused elements

need not be exclusively hydrogel monomers or acrylamide-based, and the properties of

infused elements may be adjusted for varying degrees of clarity, rigidity, macromolecule-

permeability or other functionality” (

, pp. 336–37). Also in 2013, a broad diversity of

additional compositions, including those with acrylates or alginates, was described (

), and

indeed variations and innovations on the theme rapidly emerged (Figure 4) (reviewed in

Also introduced was an electrophoretic tissue clearing (ETC) technique to accelerate lipid

removal (

); lipid removal promotes tissue transparency and macromolecular interrogation,

and this process can be carried out nondestructively after hydrogel-tissue hybrid formation

(Figure 1). ETC employs electric field-forced clearance of lipid-containing ionic-detergent

sodium dodecyl sulfate (SDS) micelles (Figure 1). Although helpful, ETC is not absolutely

necessary to remove lipids, and the following year an ETC-independent approach was

reported—passive CLARITY. This variant was initially described by Zhang et al. (

147

) and

was found to be effective for adult central nervous systems and spinal cords. Passive

CLARITY was soon thereafter reported to apply also to brain slices (

104

), and when

combined with CLARITY-optimized light-sheet microscopy (COLM) this variant enabled

imaging of entire adult mouse brains at subcellular resolution within several hours (

131

). At

the same time, another CLARITY variant (PACT) was described (

142

), presenting

modifications to the CLARITY reagents to passively achieve fast clearing of thick samples.

After overnight tissue fixation in 4% paraformaldehyde (PFA), tissues were embedded in a

4% acrylamide hydrogel solution without the 4% PFA and 0.05% bisacrylamide of the

original hydrogel formulation to minimize cross-linking (

133

142

). In addition, a relatively

inexpensive refractive index-matching solution, termed RIMS, was introduced (

142

The data of both Yang et al. (

142

) and Tomer et al. (

131

) in 2014 showed a moderate degree

of tissue expansion associated with the HTC process, as had been described by Chung et al.

(

) and indeed also as had been seen with earlier tissue clearing approaches (Figure 5).

Although this effect had not been amplified to explore potential advantages, over the next

two years, several HTC papers {11 [expansion microscopy (ExM) in 2015], 131 [expansion

Gradinaru et al.

Page 3

Annu Rev Biophys

. Author manuscript; available in PMC 2019 February 02.

HHMI Author Manuscript

passive CLARITY technique (ePACT) in 2015], and 62 [magnified analysis of the proteome

(MAP) in 2016]} soon enabled much-enhanced swelling of HTC hybrids to improve

resolution of densely packed features. In a method unique for preserving endogenous

fluorescence, ePACT (

133

) uses collagenase to enhance the magnitude of the size change.

Two of the other versions, ExM (

) and MAP (

), also embed tissue in a similar

hydrogel network (reviewed in

). In these formulations, which prescribe inclusion of

acrylates (R2 in Figure 2) alongside acrylamide to enhance swelling (Figures 2 and 4),

proteolysis can be carried out to facilitate this process but is not required. MAP additionally

allows reversible expansion of the tissue-hydrogel hybrid (Figure 5) and super-resolution

imaging of subcellular structures using high concentrations of acrylamide (30% acrylamide

with 10% acrylate) to promote protein attachment to the hydrogel and prevent intra- and

inter-protein cross-linking (

A large number of subsequent HTC studies put forward additional enhancements, including

modifications of the ETC process and device (

117

121

), of the hydrogel

monomer and cross-linker levels (

131

133

142

) and of other parameters while

maintaining the basic hydrogel-tissue chemistry (

108

122

140

142

143

145

149

). In addition to the acrylamide and/or acrylate-based PFA-coupled

hydrogels noted above (PACT/ePACT, ExM, MAP), other gelation mechanisms have also

been described. The SWITCH approach uses pH changes to synchronize formation of a

glutaraldehyde-crosslinked matrix within tissue before CLARITY-type lipid removal via

SDS, resulting in a heat- and chemical-resistant tissue-hydrogel hybrid that facilitates

multiple rounds of labeling, elution, and relabeling (

106

). Also described in the study

that introduced PACT was a strategy termed PARS (perfusion-assisted agent release in situ)

for whole-body clearing and labeling using perfusion through the vasculature to deliver

hydrogel, clearing, labeling, and imaging reagents (

133

142

). PACT and other passive

CLARITY-based HTC methods were further adapted to tissues otherwise difficult or

impossible to image intact, from the rigid and opaque bone [PACT-deCAL (

133

140

) and

Bone CLARITY (

)] to the soft and friable clinical samples and embryos (

148

In addition to small-molecule dyes, cellular stains, and protein labels (e.g., lectin) that can

directly target proteins, DNA, and other biomolecules, tissues cleared using HTC can be

stained using fluorescently tagged whole antibodies as well as smaller antibody formulations

such as FAB (fragment antigen-binding antibody) fragments (

131

133

). Nanobodies

were effective in staining PACT-cleared tissues (

142

); at 10% the size of full antibodies and

stable over a variety of pH and temperature conditions, nanobodies are particularly

appealing for labeling cleared thick tissues (

133

). The ETC process was accelerated using an

approach called stochastic electrotransport (

), and an electrophoretically driven approach

transported antibodies across a few millimeters of cleared tissue in less than an hour,

approximately 800 times faster than via passive diffusion (

). PRESTO (pressure-related

efficient and stable transfer of macromolecules into organs) conferred increased antibody

penetration depth and speed, particularly in cleared peripheral organs, by application of

either centrifugal force or convection flow using a syringe pump during sample incubation in

an antibody solution (

Gradinaru et al.

Page 4

Annu Rev Biophys

. Author manuscript; available in PMC 2019 February 02.

HHMI Author Manuscript

To broaden the types of macromolecular information obtained, recent studies have

developed methods for visualizing lipids and RNA in HTC samples. Following earlier work

that demonstrated the detection of endogenous mRNA in CLARITY specimens via standard

in situ hybridization protocols (

), Yang et al. (

142

) showed that PACT hydrogels

supported the use of single-molecule fluorescence in situ hybridization (smFISH) to detect

individual mRNA transcripts at depth. In optimizing retention of RNA for labeling in cleared

hydrogel-tissue hybrids, a carbodiimide compound [1-ethyl-3–3-dimethyl-aminopropyl

carbodiimide (EDC)] was discovered to be useful for specifically linking RNA nucleotides

directly to the tissue hydrogel (

125

) (Figure 2), and application of the hairpin chain reaction

(HCR) amplification system facilitated multiplexed RNA labeling in these EDC-CLARITY

samples that could be at least 3 mm thick. A 1% acrylamide hydrogel exhibited improved

RNA labeling (for both total RNA and specifically mRNA) when compared to CLARITY

samples (with 4% acrylamide) (

125

). Multiplexed single-molecule HCR was also

demonstrated as an effective in situ hybridization technique in HTC brain slices embedded

and cleared with PACT or ExM (

115

). Other methods led to improved visualization

of fluorescent nanoparticles (polyethylene glycol-coated quantum dots) (

116

117

), creation

of nonfluorescent (dark) reaction products (horseradish peroxidase colorimetric labeling)

(

122

), and development of lipophilic dyes that were altered to be aldehyde fixable to

proteins to mark membranes even after HTC lipid removal (

HYDROGEL-TISSUE CHEMISTRY-BASED DISCOVERY IN NEUROSCIENCE

AND THROUGHOUT THE ORGANISM

HTC methods have proven powerful for neuroscience; only a few examples of resulting

discoveries are collected here to illustrate current capabilities and opportunities. First, a large

number of studies have used the HTC approach to identify local and global wiring patterns

of targeted neurons, beginning with the demonstration that a specific class of spinal cord

neuron (NECAB expressing) exhibits midline crossing (

147

), and subsequently with the

mapping of infection distribution for viral vectors microinjected into the lateral amygdala

(LA) to analyze the neural mechanism of cocaine-cue memory engram formation in mice

(

). Similarly, in a study analyzing the morphology of raphe-spinal fibers in the spinal cord,

passive CLARITY provided visualization of a unique branching pattern of serotonergic

fibers along the rostrocaudal axis as they extended toward the lateral motor neuron column

(

). Using rabies virus-based circuit mapping, passive CLARITY and COLM provided

unbiased global mapping of all the neurons in the brain that project to dopamine neurons in

the substantia nigra pars compacta, which in turn project to dorsolateral versus dorsomedial

striatum (

). Likewise, rabies virus-based methods were used to trace monosynaptic inputs

to projection-defined dopamine neurons via whole-brain CLARITY (in this case also with

ETC and light-sheet imaging) (

). Anterograde tracing followed by CLARITY (using both

ETC and passive clearing) provided visualization of synaptic targets of GABAergic

projections from the medial septum (

136

). And in a study analyzing top-down control of

anxiety and fear, passive CLARITY was used to track and map a distinct novel projection

from ventromedial prefrontal cortex to basomedial amygdala (

). Integrating passive

CLARITY with light-sheet microscopy and behavior, researchers implemented multiple-

Gradinaru et al.

Page 5

Annu Rev Biophys

. Author manuscript; available in PMC 2019 February 02.

HHMI Author Manuscript

animal whole-brain activity mapping protocols for HTC alongside a strategy termed

CAPTURE (

143

) for quantifying numbers and projections of behaviorally activated neurons.

PACT was used to study the distribution and morphology of astroglia in thick tissue sections

(

) and the 3D distribution of multiple genetically defined neuron types in mouse brains

(

103

). Passive CLARITY on sections of medial prefrontal cortex (mPFC) established the

presence of nonoverlapping corticotropin-releasing factor and corticotropin-releasing factor

receptor-1 circuits relevant to acute stress (

138

) and was used to map brain-wide viral

expression in mice inoculated with western equine encephalitis virus in the foot pad (

101

The distribution of microglia within the subventricular zone (a neurogenic region of the

adult central nervous system) was mapped using passive CLARITY (

), and in the

periventricular zone of the cerebellum, passive CLARITY was employed to analyze the

organization of astrocytes during development (

). Passive CLARITY was used to show

increased dendritic complexity in hippocampal pyramidal neurons of transgenic mice that

exhibit enhanced learning (

114

) and to observe the localization of cells expressing

neuromedin B, a bombesin-like neuropeptide that influences sighing behavior, around the

facial nucleus, including the retrotrapezoid nucleus (a control center for breathing) (

). In

transgenic mice using the nicotinic acetylcholine receptor

2 subunit (Chrna2) locus to mark

deep-layer V Martinotti cells, passive CLARITY was used to verify labeling, specificity, and

morphology of the targeted cells (

). For examining somatostatin-expressing interneurons

in the dentate gyrus, CLARITY allowed demonstration of the axonal projections of a

specific subset to the medial septum (

146

). Subcellular localization of a specific

transcription factor, ESRRA, was analyzed using CLARITY (1% acrylamide with ETC) in

brain sections (200 μm) to help elucidate the protein’s role in cell signaling (

111

). Using

viral vector tracing to label mPFC-projecting neurons in the basolateral amygdala (BLA),

CLARITY provided visualization of the target specificity of those neurons, which aided in

investigation of their role in manipulating fear associations (

). To analyze neuronal

organization in the hypothalamus, whole-brain mapping of tyrosine hydroxylase (TH)-

positive neurons and projections was performed with CLARITY followed by

immunostaining and COLM (

109

In addition to enabling these basic discoveries, HTC work has also stimulated technical and

engineering advances. Passive CLARITY of electrolytically lesioned slices was used to

correct electrode placement for fast-scan cyclic voltammetry (

120

) and to identify locations

of implanted optical fibers (

). Following penetrating brain injury, passive CLARITY

permitted brain-wide visualization of specific peptide accumulation in studies exploring

targeted delivery of diagnostic and therapeutic compounds (

). And more broadly, body-

wide biodistribution studies looking at chemicals or biologicals were found to benefit from

HTC; for example, Treweek and coworkers (

134

) and Deverman et al. (

) demonstrated

that whole-body PARS (

142

) could facilitate the generation of transduction maps of

systemically delivered genes by adeno-associated viruses, which in turn facilitated

characterization and discovery of new viral variants for targeting the central and peripheral

nervous systems (

). HTC-based clearing has also technically enabled quadruple

immunofluorescent staining as well as multiple rounds of labeling to reveal a variety of

richly defined subcellular domains and molecule types in single human cerebellar sections

(

102

Gradinaru et al.

Page 6

Annu Rev Biophys

. Author manuscript; available in PMC 2019 February 02.

HHMI Author Manuscript

Several studies have combined magnetic resonance imaging (MRI) with CLARITY. In

probing the contribution of myelination to measurables from diffusion tensor imaging,

passive CLARITY revealed that myelination correlates strongly with fractional anisotropy

but only partially with radial diffusivity (

). The differential contributions of lipids and

proteins to MRI contrast were analyzed using passive CLARITY to remove lipids and

preserve proteins: Cleared tissues showed minimal contrast, increased relaxation times, and

diffusion rates similar to free water, and lipids were thus demonstrated to be the dominant

source of MRI contrast in brain tissue (

). In experimental autoimmune encephalomyelitis

(a mouse model of multiple sclerosis), a direct relationship was defined between gray matter

atrophy visualized using MRI and the number of axonal end bulbs in spinal cord visualized

using passive CLARITY (

118

). This type of ground-truth work on clinical biomarkers is of

immense and rapidly increasing value, particularly given the epidemiology of

neurodegenerative diseases.

Disease model work in general has progressed rapidly with HTC. In a mouse model for

Parkinson’s disease, passive CLARITY revealed fragmented nigrostriatal axons (

). In

addition to related studies in rat models (

119

), direct human-disease HTC applications

have also advanced rapidly. The effectiveness of CLARITY on postmortem human brain

tissue was demonstrated using 500-μm thick tissue blocks from clinical autism samples that

had been stored in formalin for over six years, revealing 3D morphologies not readily

accessible using traditional sectioning (

). Similarly, passive CLARITY has been used to

examine the 3D architecture of amyloid and tau aggregates in 500-μm thick banked tissue

from Alzheimer’s disease patients (

), and passive CLARITY has been used on 3-mm thick

blocks of fresh or formalin-fixed tissue from Parkinson’s disease patients to reveal Lewy

body inclusions nearly 1 mm deep in the tissue (

NONNEURAL TISSUES

Although originally conceived for studying the brain (

), the HTC approach can be

extended to a wide variety of other organs and tissue types, including spinal cord, lung,

heart, intestine, spleen, kidney, muscle, testis, pancreas, liver, skin, and bone (

100

140

142

). Its usefulness for imaging infection was demonstrated using PACT in mice

infected with fluorescent

Mycobacterium tuberculosis,

which enabled visualization of 3D

spatial distribution of bacteria throughout intact lungs (

). A modified PACT, MiPACT (for

microbial identification after PACT) was designed to label bacterial rRNA (via HCR) for

analysis of spatial organization and metabolic activity of bacteria in amorphous sputum

samples from cystic fibrosis patients (

). Also in lung, localization of nestin-expressing

cells was observed throughout the vasculature (not the airway system) of tissue cleared via

PACT, which motivated and guided investigation of the role of these cells in development of

pulmonary hypertension (

110

). In a mouse model of lung adenocarcinoma, applying

CLARITY to whole-lung tumors (clearing with two days of ETC) provided a comprehensive

demonstration of significant differences in the cellular density and morphology of tumor

cells with and without depletion of regulatory T cells (

). In pancreatic tissue, an evaluation

of p53 loss of heterozygosity in tumor progression was enabled by HTC (

Gradinaru et al.

Page 7

Annu Rev Biophys

. Author manuscript; available in PMC 2019 February 02.

HHMI Author Manuscript

In liver, 3D positioning within the portal system (relative to the canals of Hering) was

demonstrated using passive CLARITY for periportal hepatocytes, which undergo

proliferation following injury (

). After application of passive CLARITY to rat kidneys,

superresolution-STED microscopy revealed 3D positioning information at the nanometer

scale (

137

). HTC on mouse and human gut tissue was achieved using passive CLARITY and

immunostaining to visualize structures in the enteric nervous system, vasculature, smooth

muscle layers, and epithelium, while also demonstrating compatibility with classical

pathological stains such as hematoxylin-eosin and Heidenhain’s Azan (

). Early systemic

viral spread of human immunodeficiency virus 1 (HIV-1) in humanized mice was analyzed

from gut-associated lymphoid tissues using PACT (

), and HTC (with ETC) was found

useful for studying even dense and fibrous mouse hind-limb skeletal muscle tissue (

). In

virgin and lactating mouse mammary glands, epithelial and tumor cells were made visible

using PACT (

), whereas with passive CLARITY on intact mouse ovaries, the architecture

and growth of ovarian follicles and their relationship to vasculature was analyzed throughout

the mouse reproductive life (

). Embryonic and neoplastic tissue analysis has been

similarly optimized (

132

), and fast clearing was achieved by HTC in liver tissue (

)

as well as in the growth plates of distal limbs (

In hatched chickens, adult

Xenopus,

and adult zebrafish, the comparative organization of

HTC-stabilized cerebrospinal fluid-contacting cells revealed similarities pointing to a

common bony vertebrate ancestor (

141

). Legs from chicken embryos were analyzed using

passive CLARITY to reveal embryonic development of hallux positioning in the avian

grasping foot (

). Passive CLARITY was also applied to the mouse nasal septum to

visualize the morphology of horizontal basal cells in the olfactory epithelium following

lesion of the olfactory bulb (

112

). The effect of subcutaneous injection of poly(methacrylic

acid-co-methyl methacrylate) beads on vascularization was observed using passive

CLARITY in mouse skin tissue (

). A dual-illumination-side light-sheet microscope

optimized for imaging cardiac tissue over 1 cm

in volume, combined with HTC, enabled

researchers to measure ventricular dimensions, track the lineage of cardiac cells, and view

the spatial distribution of cardiac-specific proteins within intact hearts (

). CLARITY also

has been employed in intact mouse hearts as well as human heart tissue up to several

millimeters thick (

Host-pathogen interactions were studied using passive CLARITY and PACT to

comprehensively examine morphology of necrotic granulomas from adult zebrafish infected

with

Mycobacterium marinum

(

). PACT and CUBIC (

123

) were found well suited for

imaging the intact zebrafish testis at cellular resolution (

). Passive CLARITY was applied

to transgenic

Xenopus

tadpoles to locate and quantify thyroid hormone signaling disruption

by contaminants introduced during brain development (

). Applying passive CLARITY to

the intact liver of lamprey undergoing metamorphosis provided visualization of the process

of biliary degeneration, a process that occurs in human infants with biliary atresia via a

mechanism that is still unknown (

), and passive CLARITY/COLM imaging in the

lamprey was used to visualize the spatial organization of neuronal inputs and outputs in the

optic tectum with the Neurobiotin tracer (

Gradinaru et al.

Page 8

Annu Rev Biophys

. Author manuscript; available in PMC 2019 February 02.

HHMI Author Manuscript

Addressing challenges beyond soft tissue, Bone CLARITY (

) was developed and applied

along with a CLARITY-optimized light-sheet microscope to quantify marrow cells from

cleared adult intact mouse bones, revealing differences in fluorescent stem cell count and

distribution after bone-forming agent administration (

). HTC approaches have been

applied to multicellular plants as well via plant-enzyme-assisted (PEA)-CLARITY, an

adaptation to perform optical clearing and antibody interrogation on plant tissues. Using cell

wall-degrading enzymes to increase permeability and starch-hydrolyzing enzymes to

improve transparency following passive clearing, PEA-CLARITY enabled visualization of

fluorescent signals from expressed proteins as well as antibody staining in whole, intact

tobacco and

Arabidopsis

leaves (

). The PEA-CLARITY protocol was later applied to

study the 3D architecture of the

Medicago truncatula

root nodules (

128

OUTLOOK

The proven application domain of HTC in biology and medicine is rapidly expanding and

has already resulted in numerous basic science discoveries and opportunities for clinical

medicine (e.g.,

143

). However, the novelty of the preparation and its resulting data

streams have created challenges. Here, we consider the current rate-limiting steps as well as

opportunities for the future.

Early on, one of the clearest applications of the HTC approach was enabling high-resolution

optical access to large intact tissues, organs, and organisms. Although this major goal was

achieved, collecting high-resolution volumetric image data from large samples created new

issues. For example, the transparency of the hydrogel-tissue hybrid allowed confocal or two-

photon imaging over large volumes, but these slow point-scanning techniques led to

bottlenecks in image acquisition (e.g., the collection of high-resolution structural data sets

for an adult mouse brain required several days of imaging). Data collection on this timescale

is associated with problems ranging from photobleaching to simple microscope

overoccupancy, but rapid development of advanced light-sheet imaging, which offers orders-

of-magnitude improvement in speed (

107

115

130

131

143

), addressed this

acquisition problem. Subsequent HTC-focused work included stochastic electrotransport

(

); super-resolution-STED microscopy (

137

); adaptive optics (

105

); HTC sample handling

chambers (

135

); custom ETC and staining chambers (

); and microfluidic

chip-based embedding, clearing, and labeling (

The initial expansion found associated with HTC methods (

131

142

) was counteracted

with size-normalization/contraction strategies during the refractive index-matching step to

allow high-resolution objectives with limited working distance to access more of the brain

(

). This strategy also had the effect of reducing the data set size, an important

consideration for tractability. However, these considerations have become progressively less

important with the advent of new hardware, including customized long-working-distance

and high-resolution CLARITY objectives (

131

) as well as distributed computing

strategies.

Many studies have employed automated analysis pipelines for manipulating large CLARITY

data sets; commercial 3D rendering software programs, such as Imaris or Arivis, can

Gradinaru et al.

Page 9

Annu Rev Biophys

. Author manuscript; available in PMC 2019 February 02.

HHMI Author Manuscript

automate manually intensive data processing steps such as cell counting. Automation

becomes even more valuable when analyzing thicker tissue sections or whole organs (

143

), but the utility of automated analysis extends beyond the domain of cell body

recognition and counting. To quantify neural projection patterns, an automated method has

been developed to compute 3D structure tensors from CLARITY images, and input of the

tensors into diffusion tractography software yielded reconstruction of calculated streamlines

mapped onto fibers from the CLARITY images (

143

). With this approach, connectivity

between a seed region and specific downstream targets could be visualized and

quantitatively evaluated by counting streamlines (

143

). In addition, alignment of

autofluorescence images from multiple sample organs can be used to create a common

reference space. When autofluorescence is combined with segmentation algorithms for

automated cell detection, a transformation of the acquired signal from each sample onto this

reference space can be used to compare the regional distribution of labeled cells across brain

samples and allow registration to public atlases, such as the Allen Brain Institute’s Mouse

Reference Atlas (

107

143

). Automatic annotation of CLARITY brain images (

) has

been enabled by registering CLARITY brain images to the Allen atlas using a method called

Mask-LDDMM. TeraFly is a free, open-source software tool designed specifically for 3D

integrated visualization and annotation of massive, terabyte-sized image data sets like those

acquired using the COLM system (

), and a manual segmentation tool (ManSegTool) for

segmenting 3D neuronal data sets was demonstrated to enable neuroscientists to extract

neurons from cerebellum slices cleared and imaged using passive CLARITY (

). For

automatic annotation and standardization of brainwide data sets, WholeBrain is a free, open-

source software that provides connectivity and activity-based mapping and quantification of

multidimensional data, using a scale-invariant anatomical mouse brain atlas, which allows

comparison of results across experiments and imaging platforms (

). Concurrently, an

interactive Web-based framework, Openbrainmap (

http://openbrainmap.org

), was developed

for data visualization and sharing between laboratories (

Tissue clarification is only one of many application domains of HTC methods, although it is

arguably the most developed. Beyond tissue transparency, two studies have applied the

hydrogel tissue-embedding step of CLARITY to stabilize mouse embryos or adult mouse

brain tissue for micro-computed tomography (micro-CT) imaging using contrast agents that

typically shrink tissue (

139

). CLARITY was also used to reveal the 3D structure of

patterned microtissues (

129

). And in stem cell-derived organoids, passive CLARITY

followed by immunostaining was used to model and explore effects of cocaine exposure on

the human fetal brain (

A final emerging domain of substantial interest, and an initial motivation for HTC (

), is

the development of hydrogel-tissue hybrids with diverse types of functionalization, which

would enable experiments extending far beyond static structural and molecular analysis. For

example, creation of active constructs based on polymers with electrically conductive

properties could allow new forms of interrogation of biological systems, and diverse

additional forms of HTC and variants are in the process of emerging. Rooted in fundamental

chemistry, the broad concept of envisioning (and remaking) metazoan animals and tissues as

metareactants—that is, positionally intact and chemically versatile scaffolds of molecular

Gradinaru et al.

Page 10

Annu Rev Biophys

. Author manuscript; available in PMC 2019 February 02.

HHMI Author Manuscript

reactants—may continue to open up new and unanticipated domains of investigation and

discovery across diverse fields of biology.

Supplementary Material

Refer to Web version on PubMed Central for supplementary material.

ACKNOWLEDGMENTS

We thank Prof. Kwanghun Chung, Prof. Zhenan Bao, Dr. Ritchie Chen, Dr. Xiao Wang, Dr. Emily Sylwestrak, and

members of our laboratories for helpful comments on the manuscript. K.D. is supported by the National Institutes

of Health (NIH) R01DA03537701, R01MH075957, and R01MH086373, as well as by the Defense Advanced

Research Projects Agency and Army Research Laboratory NeuroFAST program (Cooperative Agreement

W911NF-1420013). V.G. is supported by the NIH via the New Innovator Award DP2NS087949 and the

Presidential Early Career Award for Science and Engineers, OT2OD023848–01, and R01AG047664; V.G. is also a

Heritage Medical Research Institute Investigator and director of the Center for Molecular and Cellular

Neuroscience in the Chen Institute at Caltech.

LITERATURE CITED

1. Adhikari A, Lerner TN, Finkelstein J, Pak S, Jennings JH, et al. 2015 Basomedial amygdala

mediates top-down control of anxiety and fear. Nature 527:179–85 [PubMed: 26536109]

2. Anderson R, Maga AM. 2015 A novel procedure for rapid imaging of adult mouse brains with

microCT using iodine-based contrast. PLOS ONE 10:e0142974 [PubMed: 26571123]

3. Ando K, Laborde Q, Lazar A, Godefroy D, Youssef I, et al. 2014 Inside Alzheimer brain with

CLARITY: senile plaques, neurofibrillary tangles and axons in 3-D. Acta Neuropathol. 128:457–59

[PubMed: 25069432]

4. Aoyagi Y, Kawakami R, Osanai H, Hibi T, Nemoto T. 2015 A rapid optical clearing protocol using

2,2

′

-thiodiethanol for microscopic observation of fixed mouse brain. PLOS ONE 10:e0116280

[PubMed: 25633541]

5. Bastrup J, Larsen PH. 2017 Optimized CLARITY technique detects reduced parvalbumin density in

a genetic model of schizophrenia. J. Neurosci. Methods 283:23–32 [PubMed: 28342832]

6. Botelho JF, Smith-Paredes D, Soto-Acuna S, Nunez-Leon D, Palma V, Vargas AO. 2017 Greater

growth of proximal metatarsals in bird embryos and the evolution of hallux position in the grasping

foot. J. Exp. Zool. B Mol. Dev. Evol 328:106–18 [PubMed: 27649924]

7. Bria A, Iannello G, Onofri L, Peng H. 2016 TeraFly: real-time three-dimensional visualization and

annotation of terabytes of multidimensional volumetric images. Nat. Methods 13:192–94 [PubMed:

26914202]

8. Chan KY, Jang MJ, Yoo BB, Greenbaum A, Ravi N, et al. 2017 Engineered AAVs for efficient

noninvasive gene delivery to the central and peripheral nervous systems. Nat. Neurosci 20:1172–79

[PubMed: 28671695]

9. Chang EH, Argyelan M, Aggarwal M, Chandon TS, Karlsgodt KH, et al. 2017 The role of

myelinationin measures of white matter integrity: combination of diffusion tensor imaging and two-

photon microscopy of CLARITY intact brains. Neuroimage 147:253–61 [PubMed: 27986605]

10. Chang JB, Chen F, Yoon YG, Jung EE, Babcock H, et al. 2017 Iterative expansion microscopy.

Nat. Methods 14:593–99 [PubMed: 28417997]

11. Chen F, Tillberg PW, Boyden ES. 2015 Expansion microscopy. Science 347:543 [PubMed:

25592419]

12. Chen F, Wassie AT, Cote AJ, Sinha A, Alon S, et al. 2016 Nanoscale imaging of RNA with

expansion microscopy. Nat. Methods 13:679–84 [PubMed: 27376770]

13. Chen YY, Silva PN, Syed AM, Sindhwani S, Rocheleau JV, Chan WC. 2016 Clarifying intact 3D

tissues on a microfluidic chip for high-throughput structural analysis. PNAS 113:14915–20

[PubMed: 27956625]

Gradinaru et al.

Page 11

Annu Rev Biophys

. Author manuscript; available in PMC 2019 February 02.

HHMI Author Manuscript

14. Chung-Davidson YW, Davidson PJ, Scott AM, Walaszczyk EJ, Brant CO, et al. 2014 A new

clarification method to visualize biliary degeneration during liver metamorphosis in Sea Lamprey

(Petromyzon marinus). J. Vis. Exp 6:88

15. Chung K, Deisseroth K. 2013 CLARITY for mapping the nervous system. Nat. Methods 10:508–

13 [PubMed: 23722210]

16. Chung K, Wallace J, Kim SY, Kalyanasundaram S, Andalman AS, et al. 2013 Structural and

molecular interrogation of intact biological systems. Nature 497:332–37 [PubMed: 23575631]

17. Collette JC, Choubey L, Smith KM. 2017 Glial and stem cell expression of murine Fibroblast

Growth Factor Receptor 1 in the embryonic and perinatal nervous system. PeerJ 5:e3519

[PubMed: 28674667]

18. Costantini I, Ghobril JP, Di Giovanna AP, Allegra Mascaro AL, Silvestri L, et al. 2015 A versatile

clearing agent for multi-modal brain imaging. Sci. Rep 5:9808 [PubMed: 25950610]

19. Cronan MR, Beerman RW, Rosenberg AF, Saelens JW, Johnson MG, et al. 2016 Macrophage

epithelial reprogramming underlies mycobacterial granuloma formation and promotes infection.

Immunity 45:861–76 [PubMed: 27760340]

20. Cronan MR, Rosenberg AF, Oehlers SH, Saelens JW, Sisk DM, et al. 2015 CLARITY and PACT-

based imaging of adult zebrafish and mouse for whole-animal analysis of infections. Dis. Model.

Mech 8:1643–50 [PubMed: 26449262]

21. Cui Y, Wang X, Ren W, Liu J, Irudayaraj J. 2016 Optical clearing delivers ultrasensitive

hyperspectral dark-field imaging for single-cell evaluation. ACS Nano 10:3132–43 [PubMed:

26895095]

22. d’Esposito A, Nikitichev D, Desjardins A, Walker-Samuel S, Lythgoe MF. 2015 Quantification of

light attenuation in optically cleared mouse brains. J. Biomed. Opt 20:80503 [PubMed: 26277988]

23. Deisseroth K 2016 A look inside the brain. Sci. Am 315:30–37

24. Deisseroth K 2017 Optical and chemical discoveries recognized for impact on biology and

psychiatry. EMBO Rep. 18:859–60 [PubMed: 28566521]

25. Deisseroth KA, Chung K. 2015 Methods and compositions for preparing biological specimens for

microscopic analysis.

www.google.com/patents/US20150144490

. Filing date: March 13, 2013. US

Patent Appl. No. US20150144490

26. Deisseroth KA, Gradinaru V. 2014 Functional targeted brain endoskeletonization.

www.google.com/patents/US20140030192

. Filing date: Jan 26, 2012. US Patent Appl. No.

US20140030192

27. DePas WH, Starwalt-Lee R, Van Sambeek L, Ravindra Kumar S, Gradinaru V, Newman DK. 2016

Exposing the three-dimensional biogeography and metabolic states of pathogens in cystic fibrosis

sputum via hydrogel embedding, clearing, and rRNA labeling. mBio 7:5e00796–16

28. Deverman BE, Pravdo PL, Simpson BP, Kumar SR, Chan KY, et al. 2016 Cre-dependent selection

yields AAV variants for widespread gene transfer to the adult brain. Nat. Biotech 34:204–9

29. Ding Y, Lee J, Ma J, Sung K, Yokota T, et al. 2017 Light-sheet fluorescence imaging to localize

cardiac lineage and protein distribution. Sci. Rep 7:42209 [PubMed: 28165052]

30. Dodt H-U. 2015 The superresolved brain. Science 347:474–75 [PubMed: 25635071]

31. Dodt H-U, Leischner U, Schierloh A, Jahrling N, Mauch CP, et al. 2007 Ultramicroscopy: three-

dimensional visualization of neuronal networks in the whole mouse brain. Nat. Methods 4:331–36

[PubMed: 17384643]

32. Epp JR, Niibori Y, Liz Hsiang HL, Mercaldo V, Deisseroth K, et al. 2015 Optimization of

CLARITY for clearing whole-brain and other intact organs. eNeuro 2:1–15

33. Erturk A, Becker K, Jährling N, Mauch CP, Hojer CD, et al. 2012 Three-dimensional imaging of

solvent-cleared organs using 3DISCO. Nat. Protoc 7:1983–95 [PubMed: 23060243]

34. Feldman MY. 1973 Reactions of nucleic acids and nucleoproteins with formaldehyde. Prog. Nucl.

Acid Res. Mol. Biol 13:1–49

35. Feng Y, Cui P, Lu X, Hsueh B, Möller Billig F, et al. 2017 CLARITY reveals dynamics of ovarian

follicular architecture and vasculature in three-dimensions. Sci. Rep 7:44810 [PubMed: 28333125]

Gradinaru et al.

Page 12

Annu Rev Biophys

. Author manuscript; available in PMC 2019 February 02.

HHMI Author Manuscript

36. Fini JB, Mughal BB, Le Mevel S, Leemans M, Lettmann M, et al. 2017 Human amniotic fluid

contaminants alter thyroid hormone signalling and early brain development in Xenopus embryos.

Sci. Rep 7:43786 [PubMed: 28266608]

37. Font-Burgada J, Shalapour S, Ramaswamy S, Hsueh B, Rossell D, et al. 2015 Hybrid periportal

hepatocytes regenerate the injured liver without giving rise to cancer. Cell 162:766–79 [PubMed:

26276631]

38. Fourgeaud L, Traves PG, Tufail Y, Leal-Bailey H, Lew ED, et al. 2016 TAM receptors regulate

multiple features of microglial physiology. Nature 532:240–44 [PubMed: 27049947]

39. Fretaud M, Riviere L, Job E, Gay S, Lareyre JJ, et al. 2017 High-resolution 3D imaging of whole

organ after clearing: taking a new look at the zebrafish testis. Sci. Rep 7:43012 [PubMed:

28211501]

40. Fürth D, Vaissière T, Tzortzi O, Xuan Y, Märtin A, et al. 2017 An interactive framework for whole-

brain maps at cellular resolution. Nat. Neurosci 21:139–49 [PubMed: 29203898]

41. Glaser AK, Reder NP, Chen Y, McCarty EF, Yin C, et al. 2017 Light-sheet microscopy for slide-

free non-destructive pathology of large clinical specimens. Nat. Biomed. Eng 1:0084 [PubMed:

29750130]

42. Gloschat CR, Koppel AC, Aras KK, Brennan JA, Holzem KM, Efimov IR. 2016 Arrhythmogenic

and metabolic remodelling of failing human heart. J. Physiol 594:3963–80 [PubMed: 27019074]

43. Gonzalez-Gonzalez MA, Gomez-Gonzalez GB, Becerra-Gonzalez M, Martinez-Torres A. 2017

Identification of novel cellular clusters define a specialized area in the cerebellar periventricular

zone. Sci. Rep 7:40768 [PubMed: 28106069]

44. Greenbaum A, Chan KY, Dobreva T, Brown D, Balani DH, et al. 2017 Bone CLARITY: clearing,

imaging, and computational analysis of osteoprogenitors within intact bone marrow. Sci. Transl.

Med 9:387

45. Hama H, Hioki H, Namiki K, Hoshida T, Kurokawa H, et al. 2015 ScaleS: an optical clearing

palette for biological imaging. Nat. Neurosci 18:1518–29 [PubMed: 26368944]

46. Hama H, Kurokawa H, Kawano H, Ando R, Shimogori T, et al. 2011 Scale: a chemical approach

for fluorescence imaging and reconstruction of transparent mouse brain. Nat. Neurosci 14:1481–

88 [PubMed: 21878933]

47. Hilscher MM, Leao RN, Edwards SJ, Leao KE, Kullander K. 2017 Chrna2-Martinotti cells

synchronize layer 5 type A pyramidal cells via rebound excitation. PLOS Biol. 15:e2001392

[PubMed: 28182735]

48. Hirashima T, Adachi T. 2015 Procedures for the quantification of whole-tissue

immunofluorescence images obtained at single-cell resolution during murine tubular organ

development. PLOS ONE 10:e0135343 [PubMed: 26258587]

49. Hou B, Zhang D, Zhao S, Wei M, Yang Z, et al. 2015 Scalable and DiI-compatible optical

clearance of the mammalian brain. Front. Neuroanat 9:19 [PubMed: 25759641]

50. Hsiang HL, Epp JR, van den Oever MC, Yan C, Rashid AJ, et al. 2014 Manipulating a “cocaine

engram” in mice. J. Neurosci 34:14115–27 [PubMed: 25319707]

51. Hsueh B, Burns VM, Pauerstein P, Holzem K, Ye L, et al. 2017 Pathways to clinical CLARITY:

volumetric analysis of irregular, soft, and heterogeneous tissues in development and disease. Sci.

Rep 7:5899 [PubMed: 28724969]

52. Jensen KHR, Berg RW. 2016 CLARITY-compatible lipophilic dyes for electrode marking and

neuronal tracing. Sci. Rep. 6:32674 [PubMed: 27597115]

53. Jensen KHR, Berg RW. 2017 Advances and perspectives in tissue clearing using CLARITY. J.

Chem. Neuroanat 86:19–34 [PubMed: 28728966]

54. Joshi NS, Akama-Garren EH, Lu Y, Lee DY, Chang GP, et al. 2015 Regulatory T cells in tumor-

associated tertiary lymphoid structures suppress anti-tumor T cell responses. Immunity 43:579–90

[PubMed: 26341400]

55. Kardamakis AA, Pérez-Fernández J, Grillner S. 2016 Spatiotemporal interplay between

multisensory excitation and recruited inhibition in the lamprey optic tectum. eLife 5:e16472

[PubMed: 27635636]

56. Ke MT, Fujimoto S, Imai T. 2013 SeeDB: a simple and morphology-preserving optical clearing

agent for neuronal circuit reconstruction. Nat. Neurosci 16:1154–61 [PubMed: 23792946]

Gradinaru et al.

Page 13

Annu Rev Biophys

. Author manuscript; available in PMC 2019 February 02.

HHMI Author Manuscript

57. Kellner M, Heidrich M, Lorbeer RA, Antonopoulos GC, Knudsen L, et al. 2016 A combined

method for correlative 3D imaging of biological samples from macro to nano scale. Sci. Rep

6:35606 [PubMed: 27759114]

58. Kieffer C, Ladinsky MS, Ninh A, Galimidi RP, Bjorkman PJ. 2017 Longitudinal imaging of HIV-1

spread in humanized mice with parallel 3D immunofluorescence and electron tomography. eLife

6:e23282 [PubMed: 28198699]

59. Kim S-Y, Cho JH, Murray E, Bakh N, Choi H, et al. 2015 Stochastic electrotransport selectively

enhances the transport of highly electromobile molecules. PNAS 112:E6274–83 [PubMed:

26578787]

60. Klavir O, Prigge M, Sarel A, Paz R, Yizhar O. 2017 Manipulating fear associations via optogenetic

modulation of amygdala inputs to prefrontal cortex. Nat. Neurosci 20:836–44 [PubMed:

28288126]

61. Klingberg A, Hasenberg A, Ludwig-Portugall I, Medyukhina A, Mann L, et al. 2017 Fully

automated evaluation of total glomerular number and capillary tuft size in nephritic kidneys using

lightsheet microscopy. J. Am. Soc. Nephrol 28:452–59 [PubMed: 27487796]

62. Kolesova H, Capek M, Radochova B, Janacek J, Sedmera D.2016 Comparison of different tissue

clearing methods and 3D imaging techniques for visualization ofGFP-expressing mouse embryos

and embryonic hearts. Histochem. Cell Biol 146:141–52 [PubMed: 27145961]

63. Krolewski DM, Kumar V, Martin B, Tomer R, Deisseroth K, et al. 2018 Quantitative validation of

immunofluorescence and lectin staining using reduced CLARITY acrylamide formulations. Brain

Struct. Funct 223:987–99 [PubMed: 29243106]

64. Ku T, Swaney J, Park JY, Albanese A, Murray E, et al. 2016 Multiplexed and scalable super-

resolution imaging of three-dimensional protein localization in size-adjustable tissues. Nat.

Biotechnol 34:973–81 [PubMed: 27454740]

65. Kubota SI, Takahashi K, Nishida J, Morishita Y, Ehata S, et al. 2017 Whole-body profiling of

cancer metastasis with single-cell resolution. Cell Rep. 20:236–50 [PubMed: 28683317]

66. Kurihara D, Mizuta Y, Sato Y, Higashiyama T. 2015 ClearSee: a rapid optical clearing reagent for

whole-plant fluorescence imaging. Development 142:4168–79 [PubMed: 26493404]

67. Kutten KS, Vogelstein JT, Charon N, Ye L, Deisseroth K, Miller MI. 2016 Deformably registering

and annotating whole CLARITY brains to an atlas via masked LDDMM. Presented at Proc. SPIE

Opt., Photonics, Digit. Technol. for Imaging Appl. IV, Brussels, Belg.

68. Lai HM, Liu AKL, Ng W-L, DeFelice J, Lee WS, et al. 2016 Rationalisation and validation of an

acrylamide-free procedure in three-dimensional histological imaging. PLOS ONE 11:e0158628

[PubMed: 27359336]

69. Lai M, Li X, Li J, Hu Y, Czajkowsky DM, Shao Z. 2017 Improved clearing of lipid droplet-rich

tissues for three-dimensional structural elucidation. Acta Biochim. Biophys. Sin 49:465–67

[PubMed: 28338831]

70. Lee CT, Chen J, Kindberg AA, Bendriem RM, Spivak CE, et al. 2017 CYP3A5 mediates effects of

cocaine on human neocorticogenesis: studies using an in vitro 3D self-organized hPSC model with

a single cortex-like unit. Neuropsychopharmacology 42:774–84 [PubMed: 27534267]

71. Lee E, Choi J, Jo Y, Kim JY, Jang YJ, et al. 2016 ACT-PRESTO: rapid and consistent tissue

clearing and labeling method for 3-dimensional (3D) imaging. Sci. Rep 6:18631 [PubMed:

26750588]

72. Lee H, Park JH, Seo I, Park SH, Kim S.2014 Improved application of the electrophoretic tissue

clearing technology, CLARITY, to intact solid organs including brain, pancreas, liver, kidney, lung,

and intestine. BMC Dev. Biol 14:48 [PubMed: 25528649]

73. Lerner TN, Shilyansky C, Davidson TJ, Evans KE, Beier KT, et al. 2015 Intact-brain analyses

reveal distinct information carried by SNc dopamine subcircuits. Cell 162:635–47 [PubMed:

26232229]

74. Leuze C, Aswendt M, Ferenczi E, Liu CW, Hsueh B, et al. 2017 The separate effects of lipids and

proteins on brain MRI contrast revealed through tissue clearing. Neuroimage 156:412–22

[PubMed: 28411157]

75. Li J, Czajkowsky DM, Li X, Shao Z. 2015 Fast immuno-labeling by electrophoretically driven

infiltration for intact tissue imaging. Sci. Rep 5:10640 [PubMed: 26013317]

Gradinaru et al.

Page 14

Annu Rev Biophys

. Author manuscript; available in PMC 2019 February 02.

HHMI Author Manuscript

76. Li P, Janczewski WA, Yackle K, Kam K, Pagliardini S, et al. 2016 The peptidergic control circuit

for sighing. Nature 530:293–97 [PubMed: 26855425]

77. Liang H, Schofield E, Paxinos G. 2016 Imaging serotonergic fibers in the mouse spinal cord using

the CLARITY/CUBIC technique. J. Vis. Exp 108:53673

78. Liang H, Wang S, Francis R, Whan R, Watson C, Paxinos G. 2015 Distribution of raphespinal

fibers in the mouse spinal cord. Mol. Pain 11:42 [PubMed: 26173454]

79. Lisovsky A, Zhang DK, Sefton MV. 2016 Effect of methacrylic acid beads on the sonic hedgehog

signaling pathway and macrophage polarization in a subcutaneous injection mouse model.

Biomaterials 98:203–14 [PubMed: 27264502]

80. Liu AKL, Hurry MED, Ng OTW, DeFelice J, Lai HM, et al. 2016 Bringing CLARITY to the

human brain: visualization of Lewy pathology in three dimensions. Neuropathol. Appl. Neurobiol

42:573–87 [PubMed: 26526972]

81. Liu AKL, Lai HM, Chang RCC, Gentleman SM. 2017 Free of acrylamide sodium dodecyl sulphate

(SDS)-based tissue clearing (FASTClear): a novel protocol of tissue clearing for three-dimensional

visualization of human brain tissues. Neuropathol. Appl. Neurobiol 43:346–51 [PubMed:

27627784]

82. Lloyd-Lewis B, Davis FM, Harris OB, Hitchcock JR, Lourenco FC, et al. 2016 Imaging the

mammary gland and mammary tumours in 3D: optical tissue clearing and immunofluorescence

methods. Breast Cancer Res. 18:127 [PubMed: 27964754]

83. Lu X, Guo S, Cheng Y, Kim J-h, Feng Y, Feng Y. 2017 Stimulation of ovarian follicle growth after

AMPK inhibition. Reproduction 153:683–94 [PubMed: 28250241]

84. Magliaro C, Callara AL, Mattei G, Morcinelli M, Viaggi C, et al. 2016 Clarifying CLARITY:

quantitative optimization of the diffusion based delipidation protocol for genetically labeled tissue.

Front. Neurosci 10:179 [PubMed: 27199642]

85. Magliaro C, Callara AL, Vanello N, Ahluwalia A. 2017 A manual segmentation tool for

threedimensional neuron datasets. Front. Neuroinform 11:36 [PubMed: 28620293]

86. Mann AP, Scodeller P, Hussain S, Joo J, Kwon E, et al. 2016 A peptide for targeted, systemic

delivery of imaging and therapeutic compounds into acute brain injuries. Nat. Commun 7:11980

[PubMed: 27351915]

87. Marx V 2014 Microscopy: seeing through tissue. Nat. Methods 11:1209–14 [PubMed: 25423017]

88. Mayrhofer M, Gourain V, Reischl M, Affaticati P, Jenett A, et al. 2017A novel brain tumour model

in zebrafish reveals the role of YAP activation in MAPK- and PI3K-induced malignant growth.

Dis. Model. Mech 10:15–28 [PubMed: 27935819]

89. Menegas W, Babayan BM, Uchida N, Watabe-Uchida M. 2017 Opposite initialization to novel

cues in dopamine signaling in ventral and posterior striatum in mice. eLife 6:e21886 [PubMed:

28054919]

90. Menegas W, Bergan JF, Ogawa SK, Isogai Y, Umadevi Venkataraju K, et al. 2015 Dopamine

neurons projecting to the posterior striatum form an anatomically distinct subclass. eLife 4:e10032

[PubMed: 26322384]

91. Milgroom A, Ralston E. 2016 Clearing skeletal muscle with CLARITY for light microscopy

imaging. Cell Biol. Int 40:478–83 [PubMed: 26732743]

92. Miller SJ, Rothstein JD. 2016 Astroglia in thick tissue with super resolution and cellular

reconstruction. PLOSONE 11:e0160391

93. Miller SJ, Rothstein JD. 2017 3D printer generated tissue iMolds for cleared tissue using single-

and multi-photon microscopy for deep tissue evaluation. Biol. Proced. Online 19:7 [PubMed:

28690429]

94. Murray E, Cho JH, Goodwin D, Ku T, Swaney J, et al. 2015 Simple, scalable proteomic imaging

for high-dimensional profiling of intact systems. Cell 163:1500–14 [PubMed: 26638076]

95. Muzumdar MD, Dorans KJ, Chung KM, Robbins R, Tammela T, et al. 2016 Clonal dynamics

following p53 loss of heterozygosity in Kras-driven cancers. Nat. Commun 7:12685 [PubMed:

27585860]

96. Neckel PH, Mattheus U, Hirt B, Just L, Mack AF. 2016 Large-scale tissue clearing (PACT):

technical evaluation and new perspectives in immunofluorescence, histology, and ultrastructure.

Sci. Rep 6:34331 [PubMed: 27680942]

Gradinaru et al.

Page 15

Annu Rev Biophys

. Author manuscript; available in PMC 2019 February 02.

HHMI Author Manuscript

97. Nordstroma U, Beauvais G, Ghosh A, Pulikkaparambil Sasidharan BC, Lundblad M, et al. 2015

Progressive nigrostriatal terminal dysfunction and degeneration in the engrailed1 heterozygous

mouse model of Parkinson’s disease. Neurobiol. Dis 73:70–82 [PubMed: 25281317]

98. Palmer WM, Martin AP, Flynn JR, Reed SL, White RG, et al. 2015 PEA-CLARITY: 3D molecular

imaging of whole plant organs. Sci. Rep 5:13492 [PubMed: 26328508]

99. Pan C, Cai R, Quacquarelli FP, Ghasemigharagoz A, Lourbopoulos A, et al. 2016 Shrinkage-

mediated imaging of entire organs and organisms using uDISCO. Nat. Methods 13:859–67

[PubMed: 27548807]

100. Pan M, Reid MA, Lowman XH, Kulkarni RP, Tran TQ, et al. 2016 Regional glutamine deficiency

in tumours promotes dedifferentiation through inhibition of histone demethylation. Nat. Cell Biol

18:1090–101 [PubMed: 27617932]

101. Phillips AT, Rico AB, Stauft CB, Hammond SL, Aboellail TA, et al. 2016 Entry sites of

Venezuelan and western equine encephalitis viruses in the mouse central nervous system

following peripheral infection. J. Virol 90:5785–96 [PubMed: 27053560]

102. Phillips J, Laude A, Lightowlers R, Morris CM, Turnbull DM, Lax NZ. 2016 Development of

passive CLARITY and immunofluorescent labelling of multiple proteins in human cerebellum:

understanding mechanisms of neurodegeneration in mitochondrial disease. Sci. Rep 6:26013

[PubMed: 27181107]

103. Plummer NW, Evsyukova IY, Robertson SD, de Marchena J, Tucker CJ, Jensen P. 2015

Expanding the power of recombinase-based labeling to uncover cellular diversity. Development

142:4385–93 [PubMed: 26586220]

104. Poguzhelskaya E, Artamonov D, Bolshakova A, Vlasova O, Bezprozvanny I. 2014 Simplified

method to perform CLARITY imaging. Mol. Neurodegener 9:19 [PubMed: 24885504]

105. Reinig MR, Novak SW, Tao X, Bentolila LA, Roberts DG, et al. 2016 Enhancing image quality in

cleared tissue with adaptive optics. J. Biomed. Opt 21:121508 [PubMed: 27735018]

106. Ren J, Choi H, Chung K, Bouma BE. 2017 Label-free volumetric optical imaging of intact

murine brains. Sci. Rep 7:46306 [PubMed: 28401897]

107. Renier N, Wu Z, Simon DJ, Yang J, Ariel P, Tessier-Lavigne M.2014 iDISCO: a simple, rapid

method to immunolabel large tissue samples for volume imaging. Cell 159:896–910 [PubMed:

25417164]

108. Roberts DG, Johnsonbaugh HB, Spence RD, MacKenzie-Graham A. 2016 Optical clearing of the

mouse central nervous system using passive CLARITY. J. Vis. Exp 112:e54025

109. Romanov RA, Zeisel A, Bakker J, Girach F, Hellysaz A, et al. 2017 Molecular interrogation of

hypothalamic organization reveals distinct dopamine neuronal subtypes. Nat. Neurosci 20:176–

88 [PubMed: 27991900]

110. Saboor F, Reckmann AN, Tomczyk CU, Peters DM, Weissmann N, et al. 2016 Nestin-expressing

vascular wall cells drive development of pulmonary hypertension. Eur. Respir. J 47:876–88

[PubMed: 26699726]

111. Saul MC, Seward CH, Troy JM, Zhang H, Sloofman LG, et al. 2017 Transcriptional regulatory

dynamics drive coordinated metabolic and neural response to social challenge in mice. Genome

Res. 27:959–72 [PubMed: 28356321]

112. Schnittke N, Herrick DB, Lin B, Peterson J, Coleman JH, et al. 2015 Transcription factor p63

controls the reserve status but not the stemness of horizontal basal cells in the olfactory

epithelium. PNAS 112:E5068–77 [PubMed: 26305958]

113. Schwarz MK, Scherbarth A, Sprengel R, Engelhardt J, Theer P, Giese G. 2015 Fluorescent-

protein stabilization and high-resolution imaging of cleared, intact mouse brains. PLOS ONE

10:e0124650 [PubMed: 25993380]

114. Serita T, Fukushima H, Kida S. 2017 Constitutive activation of CREB in mice enhances temporal

association learning and increases hippocampal CA1 neuronal spine density and complexity. Sci.

Rep 7:42528 [PubMed: 28195219]

115. Shah S, Lübeck E, Schwarzkopf M, He TF, Greenbaum A, et al. 2016 Single-molecule RNA

detection at depth by hybridization chain reaction and tissue hydrogel embedding and clearing.

Development 143:2862–67 [PubMed: 27342713]

Gradinaru et al.

Page 16

Annu Rev Biophys

. Author manuscript; available in PMC 2019 February 02.

HHMI Author Manuscript