MINI REVIEW published: 05 October 2020 doi: 10.3389/fnins.2020.00914 Tissue Clearing and Expansion Methods for Imaging Brain Pathology in Neurodegeneration: From Circuits to Synapses and Beyond Arnaldo Parra-Damas 1,2* and Carlos A. Saura 1,2 1 Institut de Neurociències, Departament de Bioquímica i Biologia Molecular, Facultat de Medicina, Universitat Autònoma de Barcelona, Barcelona, Spain, 2 Centro de Investigación Biomédica en Red Enfermedades Neurodegenerativas, Instituto de Salud Carlos III, Madrid, Spain Studying the structural alterations occurring during diseases of the nervous system requires imaging heterogeneous cell populations at the circuit, cellular and subcellular levels. Recent advancements in brain tissue clearing and expansion methods allow unprecedented detailed imaging of the nervous system through its entire scale, from circuits to synapses, including neurovascular and brain lymphatics elements. Here, we review the state-of-the-art of brain tissue clearing and expansion methods, mentioning their main advantages and limitations, and suggest their parallel implementation Edited by: for circuits-to-synapses brain imaging using conventional (diffraction-limited) light João O. Malva, microscopy -such as confocal, two-photon and light-sheet microscopy- to interrogate University of Coimbra, Portugal the cellular and molecular basis of neurodegenerative diseases. We discuss recent Reviewed by: Reinaldo B. Oria, studies in which clearing and expansion methods have been successfully applied to Federal University of Ceara, Brazil study neuropathological processes in mouse models and postmortem human brain Fahmeed Hyder, Yale University, United States tissue. Volumetric imaging of cleared intact mouse brains and large human brain *Correspondence: samples has allowed unbiased assessment of neuropathological hallmarks. In contrast, Arnaldo Parra-Damas nanoscale imaging of expanded cells and brain tissue has been used to study arnaldo.parra@e-campus.uab.cat; the effect of protein aggregates on specific subcellular structures. Therefore, these arnaldo0283@gmail.com approaches can be readily applied to study a wide range of brain processes and Specialty section: pathological mechanisms with cellular and subcellular resolution in a time- and cost- This article was submitted to efficient manner. We consider that a broader implementation of these technologies is Brain Imaging Methods, a section of the journal necessary to reveal the full landscape of cellular and molecular mechanisms underlying Frontiers in Neuroscience neurodegenerative diseases. Received: 10 May 2020 Accepted: 07 August 2020 Keywords: tissue clearing, expansion microscopy, neuropathology, neurodegeneration, super-resolution microscopy Published: 05 October 2020 Citation: Parra-Damas A and Saura CA (2020) Tissue Clearing and Expansion INTRODUCTION Methods for Imaging Brain Pathology in Neurodegeneration: From Circuits Neurodegenerative diseases, including Alzheimer’s disease (AD), Parkinson’s disease (PD), to Synapses and Beyond. Huntington’s disease (HD), amyotrophic lateral sclerosis (ALS), and frontotemporal dementia Front. Neurosci. 14:914. (FTD), among others, are incurable brain disorders that affect millions of people worldwide, doi: 10.3389/fnins.2020.00914 causing enormous social and economic burdens. Despite global intensive research and Frontiers in Neuroscience | www.frontiersin.org 1 October 2020 | Volume 14 | Article 914 Parra-Damas and Saura Tissue Clearing and Expansion in Neurodegeneration development efforts centered on neurodegenerative diseases, TISSUE CLEARING METHODS FOR there are currently no effective therapies that can revert or CIRCUIT-LEVEL BRAIN IMAGING prevent their progression. A deeper understanding of the brain structure, function and their pathological alterations is Until recently, it was not possible to image deep brain structures necessary to identify and develop novel therapeutic strategies. using light microscopy without relying on histological sectioning, This endeavor requires integrating evidence from multiple because the light transmitted through the sample is absorbed and methodological approaches used in cellular and molecular scattered due to the different refractive indexes (RI) of cellular neuroscience, including structural information at the subcellular components, including lipids, proteins, and water. Consequently, and systems biology levels. the thickness of a brain section that can be efficiently imaged The fundamental relationship between the structure and using confocal microscopy is limited to ∼150 µm, whereas two- function of biological systems implies that any dysfunction photon microscopy can reach up to ∼1 mm from the sample occurring under pathological conditions may be explained surface, which is still not enough for imaging entire brain circuits. in terms of structural alterations. Although this may seem Tissue clearing methods homogenize the RI throughout the over-simplistic for a highly complex organ such as the tissue, resulting in transparent samples that can be imaged from brain (whose function is determined by the connectivity end to end using fluorescence light microscopy. Thus, cleared and activity patterns of diverse cell populations) indeed samples can be imaged using epifluorescence, confocal and two- structural changes in specific cell types underlie almost photon microscopes or, more conveniently, by using light-sheet every long-term brain function under a wide range of (selective plane illumination) fluorescence microscopy (LSFM) physiological and pathological conditions, including learning, (Dodt et al., 2007; Hillman et al., 2019), which generates a memory, acquisition of motor skills, emotional and stress thin laser sheet to illuminate a single plane in the entire responses, neurodevelopmental and neuropsychiatric sample, allowing high-speed and high-resolution imaging of large disorders -including addictions-, inflammation, aging, specimens, such as a whole mouse brain and even intact human and neurodegeneration. In particular, altered synaptic organs (Zhao et al., 2020). While current light-sheet microscopes structures are observed in many neuropsychiatric disorders, allow imaging of intact cleared brains from small animal models whereas early loss of synapses occurs in neurodegenerative (such as mice, rats, pigs, and marmosets), imaging of the entire dementias such as AD, long before neuronal death occurs cleared human brain remains a major challenge. (Penzes et al., 2011; Sheng et al., 2012). However, our A wide range of tissue clearing methods has been recently overall knowledge about the structure-function relationship developed (Table 1), allowing simultaneous multicolor imaging on the nervous system remains very limited (Lichtman of several targets in large sample volumes. Besides imaging and Denk, 2011). Thus, any progress made on basic and fluorescent proteins, most of these methods allow labeling of biomedical neuroscience research in this regard will surely multiple proteins and transcripts using fluorophore-conjugated impulse therapeutic developments for neurodegenerative antibodies, nanobodies, and RNA probes for fluorescent in situ brain disorders. hybridization (FISH) (Ueda et al., 2020). A detailed comparison Understanding the cellular and molecular mechanisms of the fundamentals of tissue clearing methods is beyond underlying neurodegeneration requires unbiased analyses the scope of this article since this has been the subject of of the neuropathological features and structural alterations several recent reviews (Richardson and Lichtman, 2015; Tainaka affecting heterogeneous cellular populations in specific (often et al., 2016; Porter and Morton, 2020; Ueda et al., 2020). multiple) brain circuits. Ideally, such imaging analyses must Nevertheless, before discussing the application of tissue clearing be performed throughout the entire volume of the intact to neuropathological studies, we will first briefly mention the brain, spinal cord and peripheral nerves. On the other hand, overall basis and the main advantages and limitations of the three studying the impact of these pathological features at the major types of clearing methods: hydrophobic-, hydrophilic- and individual cellular level also requires imaging small cellular hydrogel-based clearing (Box 1 and Table 1). and subcellular structures, such as synapses, organelles and protein complexes, which are often too small to be imaged using standard light microscopy. Therefore, an ideal comprehensive Hydrophobic-Based Tissue Clearing structural assessment should be performed throughout the Hydrophobic (organic solvent-based) clearing methods rely entire spatial scale of the nervous system, from circuits on tissue dehydration, delipidation and permeabilization using to synapses. Here, we discuss recent advances on brain organic solvents such as ethanol (Dodt et al., 2007), methanol tissue clearing and expansion microscopy methods that can (Renier et al., 2014), tetrahydrofuran (THF) (Ertürk et al., 2012a), facilitate this endeavor in the context of neurodegeneration and tert-butanol (Pan et al., 2016). Most protocols involve research, and propose a convenient imaging pipeline simple tissue immersion (passive clearing) in a graded series (Figure 1) that can be implemented using standard light of increasing solvent concentration. However, active clearing microscopy, consisting on: (1) circuit-level assessment of protocols in which the solvents are perfused through the neuropathological changes using tissue clearing (Figure 1A); circulatory system allow clearing entire rodent bodies (Pan and (2) nanoscale imaging of pathology-associated alterations et al., 2016) and large organs such as the human brain (Zhao in synaptic and subcellular compartments using expansion et al., 2020). Further incubation in dichloromethane (DCM) may microscopy (Figure 1B). improve tissue delipidation in large samples, at the expense of Frontiers in Neuroscience | www.frontiersin.org 2 October 2020 | Volume 14 | Article 914 Parra-Damas and Saura Tissue Clearing and Expansion in Neurodegeneration FIGURE 1 | Brain tissue clearing and expansion approaches for neuropathological imaging. (A) Common steps required for whole-brain tissue clearing, imaging, and analysis of neuropathological features, allowing CNS-wide identification of vulnerable circuits and cell types. (B) Tissue expansion approaches can be used to study early pathological alterations caused by abnormal protein conformation, aggregation, and subsequent ultrastructural changes in specific subcellular compartments and organelles within affected cell types and circuits identified using tissue clearing. (C) Diffraction-limited light microscopy of cleared brain tissue allows imaging of large brain circuits at cellular resolution (a–c), including analysis of neuropathological markers (a,b), but it does not reach synaptic nanoscale resolution in non-expanded tissues (e). On the contrary, expansion microscopy of tissues and cells (d,f-i) allows nanoscale imaging using diffraction-limited microscopes, enabling detailed visualization of synapses (e) and other subcellular structures such as nuclear envelope invaginations (g–i) in healthy (h) and ALS pathological conditions (i). (a,b) LSFM images showing individual channels (a) and orthogonal optical planes (b) of a cleared transgenic AD mouse brain after (Continued) Frontiers in Neuroscience | www.frontiersin.org 3 October 2020 | Volume 14 | Article 914 Parra-Damas and Saura Tissue Clearing and Expansion in Neurodegeneration FIGURE 1 | Continued staining of vasculature (yellow), Aβ plaques (Congo red; magenta) and microglia (Iba1; cyan) using the iDISCO protocol; adapted from Liebmann et al. (2016), with permission from Elsevier. (c-f) Epifluorescence images of a Thy1-YFP mouse brain stained with presynaptic (Bassoon, blue) and postsynaptic (Homer1, red) markers, before (c,e) and after (d-f) expansion microscopy; adapted from Chen et al. (2015), with permission from AAAS. (g-i) Confocal microscopy images of expanded human iPSC-derived motor neuron nuclei from healthy control (h) and ALS patient (i) [(g) inset: nuclear size before expansion], immunolabeled for LMNB1 (green) and DNA (blue); adapted from Ortega et al. (2020), with permission from Elsevier. BOX 1 | Advantages and limitations of the main tissue clearing technologies. Hydrophobic-based tissue clearing Advantages Very quick and reproducible protocols requiring simple immersion. Higher clearing performance (transparency). Limitations Loss of endogenous FP signal. Complete loss of lipids and associated biomolecules. May cause loss of proteins and nuclei acids. May require solvent-resistant materials and optics. Use of volatile and toxic solvents (require fume hoods and ventilated work areas). Hydrophilic tissue clearing Advantages Endogenous FP signal is preserved. Use of safer reagents. Compatible with standard materials and optics. Limitations May require longer incubation times. Protocols using high detergent concentrations may cause loss of lipids and associated biomolecules, proteins and nuclei acids. Hydrogel-based tissue clearing Advantages Endogenous FP signal is preserved. A higher proportion of biomolecules is retained. The brain anatomy and ultrastructure are better preserved. Limitations Longer and more complex protocols (compared with hydrophobic- and hydrophilic- methods) requiring in situ hydrogel polymerization. May require active (electrophoretic) labeling and clearing. decreasing fluorescence from fluorescent proteins (FP) (Ertürk tau protein, respectively. α-synuclein inclusions, known as et al., 2012a). After dehydration, samples are immersed in a Lewy bodies, are found in PD and Lewy body dementias, clearing solution consisting of a mixture of benzyl alcohol and while mutant huntingtin (mHTT) aggregates are formed in benzyl benzoate (BABB) (Dodt et al., 2007) or dibenzyl ether HD, and TAR DNA-binding protein 43 (TDP-43) aggregates (DBE) (Ertürk et al., 2012a), to achieve RI homogenization and are found in ALS and FTD brains (Nguyen et al., 2018). thus transparency. Some of these lesions (like aggregated tau, Lewy bodies and TDP-43 aggregates) are found in more than one disease, Hydrophilic Tissue Clearing suggesting common underlying molecular mechanisms. Tissue clearing may also be achieved using hydrophilic reagents, Furthermore, most of these neuropathologies propagate including different detergents (Triton-X100, saponin, sodium following a specific anatomical pattern through connected brain dodecyl sulfate -SDS-, etc.) for permeabilization and delipidation, circuits (Brettschneider et al., 2015), stressing the necessity and high-refractive index aqueous solutions containing sugars of evaluating neuropathology at large spatial scales across (fructose, sucrose, sorbitol) (Ke et al., 2013), urea (Hama multiple brain regions. et al., 2011), aminoalcohols (Susaki et al., 2014), or different Recent studies have applied tissue clearing methods to combinations of the former (Table 1). evaluate some of these neuropathological hallmarks in large human brain samples and entire brains from transgenic Hydrogel-Based Tissue Clearing mouse models. Huang and colleagues used the fluorescent Another main approach to clear tissues consists of embedding the dye Thioflavin-S for staining Aβ plaques, combined with samples on a hydrogel matrix to create a cross-linked tissue/gel vasculature labeling using fluorophore-conjugated lectin and hybrid containing the fixed proteins and RNA (Gradinaru et al., BABB clearing of entire mouse brains (Dodt et al., 2007), to 2018). Ionic detergents are used for delipidation, which can show that deletion of the orphan receptor GPR3 reduces the be enhanced by electrophoresis without causing significant loss number and volume of amyloid plaques in an AD knock- of biomolecules. in mouse model (AppNL−F/NL−F ) (Huang et al., 2015). Hama et al. (2015) applied their ScaleS tissue clearing method to visualize Aβ plaques, microglia and brain ultrastructure in entire TISSUE CLEARING APPLIED TO mouse brain hemispheres and in 1–2 mm-thick sections from NEUROPATHOLOGY AND AppNL−F/NL−F mice and human AD brains, using dye- (PP-BTA- NEURODEGENERATION 1) and antibody- (6E10) labeling of plaques, neurons (NeuN) and microgia (Iba1). Compared to other clearing methods such Despite affecting specific brain circuits, neurodegenerative as CUBIC, 3DISCO, and PACT, ScaleS preserved the brain diseases share several common pathophysiological features, ultrastructure, allowing detection of postsynaptic densities and including accumulation of protein aggregates forming membranes using electron microscopy. A recent study used a characteristic neuropathological lesions. AD neuropathology is modified Golgi staining combined with Thioflavin-S and CUBIC- characterized by accumulation of extracellular amyloid plaques based clearing to image detailed neuronal morphology along with and intraneuronal neurofibrillary tangles (NFT), formed by Aβ plaques in brain sections and blocks from AppNL−F/NL−F mice aggregated amyloid-β (Aβ) peptides and hyperphosphorylated (Vints et al., 2019). Frontiers in Neuroscience | www.frontiersin.org 4 October 2020 | Volume 14 | Article 914 Frontiers in Neuroscience | www.frontiersin.org Parra-Damas and Saura TABLE 1 | Key features of the main tissue processing methods discussed. Protocol Fixation/ Permeabilization Decolorization Preservation of Labeling/ Clearing Effect on Max. # Clearing Application to Cross-linking and Delipidation fluorescence Staining performance tissue size Resolution time†‡ ¶ neuropathology Related from FP [RI], Reagent computational tools Hydrophobic (Organic Solvent) Tissue Clearing BABB Standard PFA Strong: EtOH, DCM - Low Thioflavin-S for Aβ Very high [1.56], Slight 0.5-2 µm 7 days† Visualization of Aβ plaques (Dodt et al., 2007) perfusion (hours) plaques and lectin for BABB shrinkage and vasculature in entire vasculature (Huang mouse brains (Huang et al., 2015). et al., 2015). 3DISCO Standard PFA Strong: THF, - Low - Highest [1.56], Shrinkage 0.5-2 µm 2 days† Assessment of axonal (Ertürk et al., 2012a,b) perfusion DCM (hours) BABB (∼30% degeneration and volume) regeneration in spinal cord injury (Ertürk et al., 2012b). iDISCO Standard PFA Strong: Methanol, DCM H2 O2 Low Antibodies, Congo red Highest [1.56], Minimal 0.5-2 µm 7-14 days† Evaluation of Aβ pathology (Renier et al., 2014) perfusion (hours) for Aβ plaques DBE in AD transgenic mice and iDISCO + human brains; automated (Renier et al., 2016) quantification of Aβ https://idisco.info/ plaques with ClearMAP (Liebmann et al., 2016). Imaging of temporal/spatial progression of tau neuropathology in EC-tau mice (Fu et al., 2016). u/vDISCO Standard PFA Strong: tert-Butanol, Aminoalcohol Acceptable Nanobodies (vDISCO; Highest [1.56], Shrinkage 1-2 µm 5 days† Machine learning pipeline (Pan et al., 2016) perfusion THF (hours-days) 2-3 d. active or 5-7 d. BABB-D (∼35–55% for identification and (Cai et al., 2019) DCM/Triton-X100 passive staining) volume) quantification of 5 discotechnologies.org nanobody-labeled cells (Pan et al., 2019). SHANEL* PFA perfusion of Strong: CHAPS, DCM CHAPS/ NMDEA N/A Antibodies, Very high [1.56], Shrinkage 1-2 µm 1- > 3‡ Detection of amyloid (Zhao et al., 2020) entire human organs Methoxy-X04 for BABB (∼30–45% weeks plaques in human brain discotechnologies.org labeling Aβ plaques volume) tissue (POC); deep learning-based pipeline for 3D reconstruction and data analysis (Zhao et al., 2020). Hydrophilic Tissue Clearing CUBIC 1/2 Standard PFA Strong: ScaleCUBIC-1 Aminoalcohol High Antibodies High [1.49], Slight 0.5-2 µm 7-14 days† Visualization of detailed Tissue Clearing and Expansion in Neurodegeneration (Susaki et al., 2014) perfusion (15% ScaleCUBIC-2 expansion neuronal morphology and cubic.riken.jp Triton-X100 + 25% (urea Aβ plaques using Golgi Aminoalcohol + 25% + aminoalcohol and Thioflavin-S staining in Urea) + sucrose) AD mice (POC) (Vints et al., 2019). October 2020 | Volume 14 | Article 914 Updated CUBIC Standard PFA Strong: CUBIC-L Aminoalcohol High Antibodies High [1.52], Slight 0.5–2 µm 5–11 days† – protocols perfusion (10% CUBIC-R/RA expansion (Tainaka et al., 2018) Triton-X100 + 10% (antipyrine, cubic.riken.jp Aminoalcohol) nicotinamide) ScaleS* (Hama et al., Standard PFA Mild: urea + sorbitol + – High Antibodies, Lectin High [1.44] Minimal 0.5–2 µm 2–5 days for Evaluation of Aβ 2015). perfusion DMSO (urea + sorbitol + mm-thick pathology, microglia and DMSO) slides. EM ultrastructure in AD transgenic mice and human AD brains (Hama et al., 2015). (Continued) Frontiers in Neuroscience | www.frontiersin.org Parra-Damas and Saura TABLE 1 | Continued Protocol Fixation/ Permeabilization Decolorization Preservation of Labeling/ Clearing Effect on Max. # Clearing Application to Cross-linking and Delipidation fluorescence Staining performance tissue size Resolution time†‡ ¶ neuropathology Related from FP [RI], Reagent computational tools Hydrogel-Based Tissue Clearing CLARITY PFA/ Strong: 4% SDS – Temperature- Antibodies Good [1.45], Minimal 0.5–2 µm 1 (active)-3 Visualization of Aβ plaques (Chung et al., 2013; acrylamide/ dependent: preserved FocusClear (passive) weeks† and tangles in human AD Tomer et al., 2014) bis-acrylamide ◦ at 37 C brain (POC) (Ando et al., clarityresourcecenter. 2014). Identification of com fragmented nigrostriatal axons in PD mice (Nordström et al., 2015). Visualization of Lewy pathology in human brain (POC) (Liu et al., 2016). SWITCH* PFA, Glutaraldehyde 200 mM SDS – Temperature- Antibodies, Lectin High, [1.47], Minimal 0.5–2 µm 2–4 weeks† Assessment of Aβ (Murray et al., 2015) dependent: diatrizoic acid, deposits in 5xFAD mice, chunglabresources.com preserved at 37◦ C n-methyl-D- revealing early Aβ requiring longer glucamine, accumulation in clearing iodixanol subcortical areas (Gail Canter et al., 2019). SHIELD* PFA, Polyepoxide 300 mM SDS - Time/temperature- Antibodies, FISH, High, [1.46], Minimal 0.5–2 µm 1 (active) -4 Quantitative evaluation of (Park et al., 2019) dependent: preserved Lectin Iodixanol- or (passive) weeks† Aβ pathology in 5xFAD chunglabresources.com at 45◦ C Iohexol-based mice exposed to gamma Protos media sensory stimulation (Martorell et al., 2019). Tissue Expansion ExM/ProExM/iExM PFA, acrylamide/ 5% Triton X-100, – Partial, only Antibodies, FISH High, [∼1.33], 20 × (iExM) ∼25 nm 1-2 days ¶ Identification of 6 (Chen et al., 2015; bis-acrylamide/ 1% SDS digestion-resistant FP (water) 4.5 × (ExM) (iExM) or perivascular c43 Chang et al., 2017; sodium acrylate (for post expansion Expansion 60 nm (ExM) accumulation on astrocytic Asano et al., 2018) Acryloyl-X staining) (3.5 × for endfeet in human brain expansionmicros FISH) epilepsy (Deshpande et al., copy.org 2017). Identification of eRF1 accumulation within nuclear envelope invaginations in iPSC-derived neurons from ALS patients (Ortega et al., 2020). ExPath* PFA, formalin or 0.1% Triton X-100 – N/A Antibodies, High, [∼1.33], 4.5× ∼60 nm 4 h (≤5 µm) – 2 – Tissue Clearing and Expansion in Neurodegeneration (Zhao et al., 2017; acetone. DNA-FISH (water) days ¶ Bucur et al., 2020) Acrylamide/ bis-acrylamide/ sodium acrylate MAP PFA, acrylamide/ 200 mM SDS – Fluorescence is lost Antibodies [1.47] Fourfold ∼60-nm ∼1 week – October 2020 | Volume 14 | Article 914 (Ku et al., 2016) bis-acrylamide/ but epitopes are pre-expansion. linear ¶ chunglabresources.com sodium acrylate preserved [∼1.33] (water) expansion after expansion. X10 ExpM Sodium acrylate, 0.1% Triton X-100 – Fluorescence is lost Antibodies High, [∼1.33], Tenfold ∼25 nm 3 days ¶ – (Truckenbrodt et al., N,N-dimethyl but epitopes are (water) expansion 2018, 2019) acrylamide, Acryloyl-X preserved SHIELD-MAP PFA, Polyepoxide 300 mM SDS – Time/temperature- Antibodies DI water for Threefold ? ∼2 weeks ¶ – (3x linear expansion) acrylamide/ dependent. expansion. linear (1–3 mm (Park et al., 2019) bis-acrylamide/ 27-fold signal expansion Slices) chunglabresources.com sodium reduction after acrylate/VA-044 expansion. # Lateral resolution using standard (diffraction-limited) light microscopy. *Optimized for human tissue. † For an intact mouse brain. ‡ For ∼1 cm3 human brain tissue. ¶Expansion of brain slices. DCM, dichloromethane. CHAPS, 3-[(3-cholamidopropyl)dimethylammonio]-1-propanesulfonate. BABB, benzyl alcohol + benzyl benzoate (1:2). BABB-D, BABB + Dibenzyl ether. SDS, sodium dodecyl sulfate. POC, proof-of-concept application. Parra-Damas and Saura Tissue Clearing and Expansion in Neurodegeneration The hydrogel-based CLARITY method has also been used to for understanding pathogenic mechanisms underlying visualize amyloid plaques and NFT in human AD brain samples neurodegenerative diseases. While electron microscopy (Ando et al., 2014), fragmented nigrostriatal axons in a PD mouse achieves the highest spatial resolution for ultrastructural model (Nordström et al., 2015), and Lewy pathology in a human analyses, it still lacks the molecular specificity and throughput PD brain (Liu et al., 2016), relying on antibody labeling for provided by multicolor fluorescence microscopy, which detecting neuropathology and specific cell types, and confocal is required for simultaneous imaging of multiple targets, microscopy for imaging. Imaging of amyloid plaques revealed including visualizing cell-type-specific nanostructures and/or sparse accumulation and diversity of 3D structures, including signaling molecules within a pathological context. However, dense/focal and diffuse deposits, whereas tau accumulated in the minimum size of the structures that can be resolved using discontinuous neuritic processes associated with dense/mature conventional fluorescence light microscopy is constrained plaques (Ando et al., 2014) which were previously reported by the light diffraction limit (about 250 nm, depending on using conventional histology and confocal microscopy (Knowles the specific excitation wavelength), which precludes detailed et al., 1999). The immunolabeling and solvent-based clearing imaging of specific protein complexes, individual synapses and method iDISCO has also been used to evaluate tau pathology other subcellular structures. Several optical super-resolution and Aβ plaques using antibodies and Congo red labeling in microscopy (SRM) methods have been developed to overcome APPswe /PSEN11E9 and 3xTg-AD transgenic mice and human diffraction limitation, including stimulated emission depletion AD brains (Liebmann et al., 2016). The authors also developed (STED) microscopy, photoactivation localization microscopy a computational pipeline based on automated detection of cells (PALM), structured illumination microscopy (SIM), and and plaques from light-sheet images and further mapping of these stochastic optical reconstruction microscopy (STORM), features to the Allen Brain Atlas, enabling fast quantification among others (Tønnesen and Nägerl, 2013; Schermelleh et al., of plaques in different brain regions (Liebmann et al., 2016). 2019). Depending on the specific approach and imaging iDISCO+ (Renier et al., 2016), an improved version of iDISCO, setup, optical SRM can resolve sub-diffraction size structures was successfully applied for whole-brain immunolabeling and ranging from 30 to 100 nm (lateral resolution), enabling 3D imaging of the temporal and spatial progression of tau detailed visualization of subcellular structures, individual neuropathology in entorhinal cortex (EC)-tau transgenic mice, synapses and protein complexes. Interestingly, recent studies revealing age-dependent tau pathology not only in entorhinal have combined the advantage of reduced light scattering and hippocampal regions but also in neocortical areas, which was (transparency) provided by tissue clearing methods, with not previously detected by classical 2D histology in this model SRM to achieve sub-diffraction volumetric brain imaging, (Fu et al., 2016). revealing novel synaptic structural and functional insights. For More recently, SHIELD-based clearing (Park et al., 2019) of instance, Ke et al. (2016) developed a tissue clearing solution entire mouse brains was used to show that auditory plus visual (SeeDB2) which, combined with STED SRM, allowed synaptic- gamma sensory stimulation reduces the number and volume resolution imaging through thick brain samples (up to 120 µm). of amyloid plaques (detected by Aβ immunolabeling) in 6- More recently, Hruska et al. (2018) combined CUBIC tissue month-old 5xFAD mice, revealing a greater effect of sensory clearing and STED SRM to demonstrate the occurrence of stimulation on pathology across broad cortical regions than discrete synaptic nanomodules (∼80 nm in size) in the mouse observed with conventional histology (Martorell et al., 2019). somatosensory cortex. Similarly, SWITCH whole-brain immunolabeling and clearing However, SR microscopes are not widely available to most (Murray et al., 2015) were used to monitor the progression of biomedical research labs, are expensive, and may require Aβ deposits in 5xFAD mice, revealing early Aβ accumulation expert personnel to operate. Moreover, multicolor imaging in subcortical areas and area-specific aggregation correlating may be challenging for some setups. A clever solution to with electrophysiological changes (Gail Canter et al., 2019). overcome the light diffraction limit is to increase the size Finally, a novel permeabilization and clearing approach, named of the specimens to image (Chen et al., 2015). Three main SHANEL, allowed labeling of cm-thick human brain tissue using independent approaches have been developed to increase conventional antibodies, and was used to detect amyloid plaques the size of biological tissues: expansion microscopy (ExM) in human brains labeled with the Congo red derivative methoxy- (Chen et al., 2015); magnified analysis of the proteome X04 (Zhao et al., 2020). (MAP) (Ku et al., 2016); and X10 (Truckenbrodt et al., 2018) Taken together, these studies have demonstrated the feasibility (Table 1). These methods use swellable hydrogels that are of using tissue clearing approaches for achieving volumetric cross-linked throughout the tissue to induce isotropic expansion imaging and quantitative assessment of neuropathological of the samples, allowing super-resolution imaging of the hallmarks in AD and PD. expanded specimens using conventional light microscopes [Figures 1B,C(c–i)]. Current tissue expansion methods allow isotropic expansion of tissues up to ∼4.5x (Ku NANOSCALE IMAGING USING SUPER- et al., 2016; Tillberg et al., 2016) or 10x (Truckenbrodt RESOLUTION EXPANSION MICROSCOPY et al., 2018) for single-step expansion protocols and up to ∼20x for iterative expansion protocols (Chang et al., Studying neuropathology-associated alterations in the molecular 2017), enabling detailed nanoscale imaging of subcellular composition and ultrastructure of the brain is essential structures with up to ∼25-nm-resolution using conventional Frontiers in Neuroscience | www.frontiersin.org 7 October 2020 | Volume 14 | Article 914 Parra-Damas and Saura Tissue Clearing and Expansion in Neurodegeneration confocal microscopy (Table 1). These methods are easy to neurodegenerative disorders (Crittenden et al., 2016). Deshpande implement and optimize (compared with optical SRM), require et al. (2017) applied ProExM to human CA1 hippocampal tissue commercially available reagents, and are compatible with from temporal lobe epilepsy patients to study the subcellular multicolor immunostaining and FISH (Tillberg et al., 2016; localization of perivascular Connexin-43 (Cx43; GJA1), revealing Asano et al., 2018). specific Cx43 accumulation on the parenchymal side of astrocytic Moreover, expanded samples can be conveniently imaged endfeet, compared to endothelial or pericytic accumulation. using confocal microscopes -which are widely available- and ProExM has also been applied to HeLa cells to study the provide enough three-dimensional resolution to enable cost- spatial organization of autophagy-related HSPB1 protein and efficient super-resolution imaging of the brain tissue (Tillberg SQSTM1/p62 bodies in the context of peripheral neuropathy and Chen, 2019; Wassie et al., 2019). Each tissue expansion (Haidar et al., 2019). More recently, ProExM was used to approach has its advantages and limitations related to preserving show that the protein eRF1 accumulates within the cytosolic endogenous fluorescence, epitopes, and reduction of fluorescence side of nuclear envelope invaginations identified in induced signal after expansion (Table 1). In this regard, performing tissue pluripotent stem cell (iPSC) neurons derived from ALS patients immunolabeling after expansion may yield higher fluorescence (Ortega et al., 2020) [Figures 1C(g–i)]. signals, although fewer epitopes can be detected with this strategy Taken together, these studies demonstrate that -similar (Asano et al., 2018). to optical SRM- expansion-SRM has the potential to deliver relevant structural insights about molecular and cellular mechanisms mediating neuropathology and neurodegeneration. INSIGHTS FROM SRM IN Broader implementation of these methods may be of great NEURODEGENERATION RESEARCH value for studying interactions between pathological protein conformations and organelles/membranes, which could mediate Besides the evident relevance of assessing synaptic structural aggregation and downstream neurodegenerative processes and molecular alterations in brain diseases, nanoscale imaging (Shrivastava et al., 2017). can also provide crucial information on other altered cellular processes. For instance, STORM and STED SRM have been applied to study the aggregation states of Huntingtin exon 1, POTENTIAL APPLICATIONS OF including the formation of inclusion bodies and other fibrillary CLEARING AND EXPANSION METHODS species in living and fixed cells (Duim et al., 2014; Sahl IN NEURODEGENERATION RESEARCH et al., 2016), while SIM SRM has been used to study the interaction of mHTT aggregates with transcription factors (Li Based on the above considerations, we propose a general et al., 2016), which could mediate altered gene expression in straightforward pipeline for structural and molecular analysis HD (Giralt et al., 2012). Different optical SRM approaches of neuropathological and neurodegenerative brain tissues, have helped to image both Aβ and tau aggregates in vitro from circuits to synapses, relying on the capabilities offered and in cellular models (Pinotsi et al., 2016; Schierle et al., by tissue clearing and expansion methods (Figure 1). This 2016), while STED SRM was used to image immunolabelled consists of: (1) Tissue clearing-enabled unbiased imaging of tau filaments in postmortem AD brain sections (50 µm) at whole brains or specific brain regions; and (2) SR-expansion ∼80 nm resolution (Benda et al., 2016). A recent study used nanoscale imaging of subcellular compartments from specific STED SRM to identify disruption of the lamin nucleoskeleton cell-types within affected circuits. The first systems/circuit- in a Drosophila model of tau pathology and in human level approach has several remarkable advantages compared postmortem AD brain tissue, suggesting that lamin dysfunction with standard sectioning histology: first, it preserves the full contributes to tau-mediated neurodegeneration (Frost et al., anatomical information, some of which is lost during tissue 2016). STORM and STED SRM have also been used to visualize sectioning. Second, it allows unbiased and automated imaging the presenilin-1/γ-secretase complex, which is responsible for and data analysis of the whole brain, reducing experimental the proteolytic cleavage of the amyloid precursor protein errors and favoring reproducibility. Third, the time required (APP) that releases Aβ, in both the pre- and post-synaptic for tissue processing, labeling, imaging, and data analysis can compartments of cultured mouse neurons (Schedin-Weiss be significantly reduced, especially when working with large et al., 2016). More recently, SIM and PALM were used to experimental groups if automated imaging and data analysis study the subunit composition and activity of the γ-secretase pipelines are implemented (Table 1). complex at the plasma membrane in living cells, revealing Despite these clear advantages, up to date, most tissue complex dynamics involving association with specific substrates clearing studies have provided limited biological information (Escamilla-Ayala et al., 2020). or only proof-of-concept data on neuropathology and Early after its development, protein-retention ExM (ProExM) neurodegeneration, particularly in human brain samples (Tillberg et al., 2016) was used to identify “striosome–dendron (Table 1). However, we think that neuropathological studies bouquets” structures formed by intertwined striosomal axons can leverage tissue clearing methods to deliver insightful and dopamine-containing dendrites as part of the dopamine- systems biology-level information on structural and functional containing nigral system, which may be relevant for motor and alterations. For instance, tissue clearing approaches may be used Frontiers in Neuroscience | www.frontiersin.org 8 October 2020 | Volume 14 | Article 914 Parra-Damas and Saura Tissue Clearing and Expansion in Neurodegeneration to identify relevant brain circuits showing pathology-induced (acetylations, methylations, sumoylation, etc.) and processes alterations in the activity and connectivity of specific cell- (interactions, synthesis, degradation, and aggregation) that can types, by performing simultaneous analysis of neuropathological be imaged in fixed samples. On the other hand, recent advances hallmarks, cell type-specific and synaptic markers, as well as in volumetric imaging of bio-microelectromechanical systems indicators of neuronal/astrocytic excitability (i.e., immediate (bioMEMS microdevices) using LSFM opens a promising early genes such as c-fos and Arc) or glial reactivity (GFAP, avenue for achieving 3D and sucellular imaging of in vitro CD45). Indeed, tissue clearing methods have been successfully model systems under highly controlled experimental conditions applied to study brain-wide neuronal activity (Renier et al., (Albert-Smet et al., 2019). Computational developments, 2016; Sylwestrak et al., 2016; Murakami et al., 2018; Park including neuropathology-optimized data analysis tools and et al., 2019) and -separately- AD neuropathology in mouse implementation of standardized pipelines, data formats, and models (Table 1). These approaches could be combined to study data-sharing platforms can further aid quantitative assessments how different neuropathologies affect the activity of specific and systems-biology level interpretation of the vast amount cell populations in the whole brain, which could shed light of brain/circuit-wide imaging data that can be generated, as into the cellular mechanisms mediating selective/differential well as integration with functional and cell-specific omics data vulnerability of different circuits and neuronal/glial subtypes (Vandenberghe et al., 2018; Hériché et al., 2019). Moreover, during neurodegenerative diseases (Fu et al., 2018; Forrest incorporation of other structural and functional imaging et al., 2019). In particular, automated mapping of brain activity technologies [such as positron emission tomography (PET), based on detection of neuronal activity-induced immediate early functional magnetic resonance imaging (fMRI), multi-photon genes (Renier et al., 2016) can be combined with assessment microscopy, optical super-resolution imaging, cryo-EM and of neuropathological features in neurodegeneration or AD cryo-electron tomography, among others] is needed to confirm mouse models (Liebmann et al., 2016) to obtain physiological and complement the findings obtained by tissue clearing functional readouts of circuit- and cell-specific vulnerability and expansion methods, as well as to achieve a complete to AD neuropathology, and to evaluate potential therapeutic imaging assessment throughout the entire spatial scale of strategies. Different computational methods have been developed the brain, which remains one of the most challenging tasks to achieve automated identification and quantification of cells of contemporary neuroscience (Lichtman and Denk, 2011; and neuropathological hallmarks, which can be of high value in Koning et al., 2018). However, we think that tissue clearing and such studies (Table 1). expansion technologies have already reached enough maturity The former circuit-level imaging approaches need to to be generally embraced by the neurodegeneration research be complemented with SR-expansion nanoscale imaging to community, and as such, they can be readily implemented to further characterize the synaptic and subcellular ultrastructural address the underlying biology and pathogenic mechanisms of alterations occurring under neuropathological conditions, and to neurodegeneration, as demonstrated by relevant recent studies investigate potential molecular and cellular mechanisms. Thus, (Gail Canter et al., 2019; Martorell et al., 2019). This certainly cell-type-specific molecular mechanisms mediating alterations will enable biological discoveries of great translational impact in in synaptic and subcellular structures (such as altered mRNA the near future. and protein localization, local synaptic translation, protein- protein interactions, and pathological protein aggregation, among others) could be approached using expansion SRM AUTHOR CONTRIBUTIONS (Figure 1B). Since SRM methods (including expansion microscopy) have already revealed key molecular mechanisms AP-D conceived the study and designed the figures. AP-D and CS in physiological and neurodegenerative contexts, it is reasonable wrote the manuscript. Both authors contributed to the article and to pursue a broader implementation of tissue expansion approved the submitted version. technologies for studying cellular and molecular mechanisms in neurodegeneration research. FUNDING This study was supported by research grants from the Ministerio CONCLUDING REMARKS de Ciencia e Innovación of Spain with FEDER funds (SAF2016- 80027-R and PID2019-106615RB-100) and Instituto Carlos III The astonishing development of tissue clearing and expansion (CIBERNED CB06/05/0042). technologies in the last few years suggests that there is still plenty of room for improvement. Future advances in tissue chemistry and optics (Chakraborty et al., 2019; Gwosch et al., 2020) together ACKNOWLEDGMENTS with recent initiatives to guide the building of open-source light-sheet microscopes (Voigt et al., 2019) will likely facilitate We thank Dr. Jorge Valero and Dr. Dolores Siedlecki for helpful their applicability, while increasing the current resolution and comments on the manuscript. We also thank Yuruani Audemard the range of biomolecules (i.e., lipids, sugars), modifications for copy editing. Frontiers in Neuroscience | www.frontiersin.org 9 October 2020 | Volume 14 | Article 914 Parra-Damas and Saura Tissue Clearing and Expansion in Neurodegeneration REFERENCES Forrest, S. L., Kril, J. J., and Halliday, G. M. (2019). Cellular and regional vulnerability in frontotemporal tauopathies. Acta Neuropathol. 138, 705–727. Albert-Smet, I., Marcos-Vidal, A., Vaquero, J. J., Desco, M., Muñoz-Barrutia, A., doi: 10.1007/s00401-019-02035-7 and Ripoll, J. (2019). Applications of light-sheet microscopy in microdevices. Frost, B., Bardai, F. H., and Feany, M. B. (2016). Lamin dysfunction mediates Front. Neuroanat. 13:1 doi: 10.3389/fnana.2019.00001 neurodegeneration in tauopathies. Curr. Biol. 26, 129–136. doi: 10.1016/j.cub. Ando, K., Laborde, Q., Lazar, A., Godefroy, D., Youssef, I., Amar, M., et al. (2014). 2015.11.039 Inside Alzheimer brain with CLARITY: senile plaques, neurofibrillary tangles Fu, H., Hardy, J., and Duff, K. E. (2018). Selective vulnerability in and axons in 3-D. Acta Neuropathol. 128, 457–459. doi: 10.1007/s00401-014- neurodegenerative diseases. Nat. Neurosci. 21, 1350–1358. doi: 10.1038/ 1322-y s41593-018-0221-2 Asano, S. M., Gao, R., Wassie, A. T., Tillberg, P. W., Chen, F., and Boyden, E. S. Fu, H., Hussaini, S. A., Wegmann, S., Profaci, C., Daniels, J. D., Herman, M., (2018). Expansion microscopy: protocols for imaging proteins and RNA in cells et al. (2016). 3D visualization of the temporal and spatial spread of Tau and tissues. Curr. Protoc. Cell Biol. 80:e56. doi: 10.1002/cpcb.56 pathology reveals extensive sites of Tau accumulation associated with neuronal Benda, A., Aitken, H., Davies, D. S., Whan, R., and Goldsbury, C. (2016). STED loss and recognition memory deficit in aged Tau transgenic mice. PLoS One imaging of tau filaments in Alzheimer’s disease cortical grey matter. J. Struct. 11:e0159463. doi: 10.1371/journal.pone.0159463 Biol. 195, 345–352. doi: 10.1016/j.jsb.2016.07.003 Gail Canter, R., Huang, W.-C., Choi, H., Wang, J., Ashley Watson, L., Yao, C. G., Brettschneider, J., Tredici, K., Del Lee, V. M.-Y., and Trojanowski, J. Q. et al. (2019). 3D mapping reveals network-specific amyloid progression and (2015). Spreading of pathology in neurodegenerative diseases: a focus subcortical susceptibility in mice. Commun. Biol. 2:360. doi: 10.1038/s42003- on human studies. Nat. Rev. Neurosci. 16, 109–120. doi: 10.1038/nrn 019-0599-8 3887 Giralt, A., Puigdellívol, M., Carretón, O., Paoletti, P., Valero, J., Parra-Damas, A., Bucur, O., Fu, F., Calderon, M., Mylvaganam, G. H., Ly, N. L., Day, J., et al. et al. (2012). Long-term memory deficits in Huntington’s disease are associated (2020). Nanoscale imaging of clinical specimens using conventional and rapid- with reduced CBP histone acetylase activity. Hum. Mol. Gen. 21, 1203–1216. expansion pathology. Nat. Protoc. 15, 1649–1672. doi: 10.1038/s41596-020- doi: 10.1093/hmg/ddr552 0300-1 Gradinaru, V., Treweek, J., Overton, K., and Deisseroth, K. (2018). Hydrogel- Cai, R., Pan, C., Ghasemigharagoz, A., Todorov, M. I., Förstera, B., Zhao, S., et al. tissue chemistry: principles and applications. Annu. Rev. Biophys. 47, 355–376. (2019). Panoptic imaging of transparent mice reveals whole-body neuronal doi: 10.1146/annurev-biophys-070317-032905 projections and skull–meninges connections. Nat. Neurosci. 22, 317–327. doi: Gwosch, K. C., Pape, J. K., Balzarotti, F., Hoess, P., Ellenberg, J., Ries, J., et al. 10.1038/s41593-018-0301-3 (2020). MINFLUX nanoscopy delivers 3D multicolor nanometer resolution in Chakraborty, T., Driscoll, M. K., Jeffery, E., Murphy, M. M., Roudot, P., Chang, cells. Nat. Methods 17, 217–224. doi: 10.1038/s41592-019-0688-0 B.-J., et al. (2019). Light-sheet microscopy of cleared tissues with isotropic, Haidar, M., Asselbergh, B., Adriaenssens, E., De Winter, V., Timmermans, J.- subcellular resolution. Nat. Methods 16, 1109–1113. doi: 10.1038/s41592-019- P., Auer-Grumbach, M., et al. (2019). Neuropathy-causing mutations in 0615-4 HSPB1 impair autophagy by disturbing the formation of SQSTM1/p62 bodies. Chang, J.-B., Chen, F., Yoon, Y.-G., Jung, E. E., Babcock, H., Kang, J. S., et al. (2017). Autophagy 15, 1051–1068. doi: 10.1080/15548627.2019.1569930 Iterative expansion microscopy. Nat. Methods 14, 593–599. doi: 10.1038/nmeth. Hama, H., Hioki, H., Namiki, K., Hoshida, T., Kurokawa, H., Ishidate, F., et al. 4261 (2015). ScaleS: an optical clearing palette for biological imaging. Nat. Neurosci. Chen, F., Tillberg, P. W., and Boyden, E. S. (2015). Expansion microscopy. Science 18, 1518–1529. doi: 10.1038/nn.4107 347, 543–548. doi: 10.1126/science.1260088 Hama, H., Kurokawa, H., Kawano, H., Ando, R., Shimogori, T., Noda, H., et al. Chung, K., Wallace, J., Kim, S.-Y., Kalyanasundaram, S., Andalman, A. S., (2011). Scale: a chemical approach for fluorescence imaging and reconstruction Davidson, T. J., et al. (2013). Structural and molecular interrogation of transparent mouse brain. Nat. Neurosci. 14, 1481–1488. doi: 10.1038/nn.2928 of intact biological systems. Nature 497, 332–337. doi: 10.1038/nature Hériché, J.-K., Alexander, S., and Ellenberg, J. (2019). Integrating imaging and 12107 omics: computational methods and challenges. Annu. Rev. Biomed. Data Sci. Crittenden, J. R., Tillberg, P. W., Riad, M. H., Shima, Y., Gerfen, C. R., Curry, 2, 175–197. doi: 10.1146/annurev-biodatasci-080917-013328 J., et al. (2016). Striosome–dendron bouquets highlight a unique striatonigral Hillman, E. M. C., Voleti, V., Li, W., and Yu, H. (2019). Light-sheet microscopy in circuit targeting dopamine-containing neurons. Proc. Natl. Acad. Sci. U.S.A. neuroscience. Annu. Rev. Neurosci. 42, 295–313. doi: 10.1146/annurev-neuro- 113, 11318–11323. doi: 10.1073/pnas.1613337113 070918-050357 Deshpande, T., Li, T., Herde, M. K., Becker, A., Vatter, H., Schwarz, M. K., et al. Hruska, M., Henderson, N., Le Marchand, S. J., Jafri, H., and Dalva, M. B. (2017). Subcellular reorganization and altered phosphorylation of the astrocytic (2018). Synaptic nanomodules underlie the organization and plasticity of spine gap junction protein connexin43 in human and experimental temporal lobe synapses. Nat. Neurosci. 21, 671–682. doi: 10.1038/s41593-018-0138-9 epilepsy. Glia 65, 1809–1820. doi: 10.1002/glia.23196 Huang, Y., Skwarek-Maruszewska, A., Horré, K., Vandewyer, E., Wolfs, L., Snellinx, Dodt, H.-U., Leischner, U., Schierloh, A., Jährling, N., Mauch, C. P., Deininger, A., et al. (2015). Loss of GPR3 reduces the amyloid plaque burden and improves K., et al. (2007). Ultramicroscopy: three-dimensional visualization of neuronal memory in Alzheimer’s disease mouse models. Sci. Transl. Med. 7, ra164–ra309. networks in the whole mouse brain. Nat. Methods 4, 331–336. doi: 10.1038/ doi: 10.1126/scitranslmed.aab3492 nmeth1036 Ke, M.-T., Fujimoto, S., and Imai, T. (2013). SeeDB: a simple and morphology- Duim, W. C., Jiang, Y., Shen, K., Frydman, J., and Moerner, W. E. (2014). preserving optical clearing agent for neuronal circuit reconstruction. Nat. Super-resolution fluorescence of huntingtin reveals growth of globular species Neurosci. 16, 1154–1161. doi: 10.1038/nn.3447 into short fibers and coexistence of distinct aggregates. ACS Chem. Biol. 9, Ke, M.-T., Nakai, Y., Fujimoto, S., Takayama, R., Yoshida, S., Kitajima, T. S., 2767–2778. doi: 10.1021/cb500335w et al. (2016). Super-resolution mapping of neuronal circuitry with an index- Ertürk, A., Becker, K., Jährling, N., Mauch, C. P., Hojer, C. D., Egen, J. G., et al. optimized clearing agent. Cell Rep. 14, 2718–2732. doi: 10.1016/j.celrep.2016. (2012a). Three-dimensional imaging of solvent-cleared organs using 3DISCO. 02.057 Nat. Protoc. 7, 1983–1995. doi: 10.1038/nprot.2012.119 Knowles, R. B., Wyart, C., Buldyrev, S. V., Cruz, L., Urbanc, B., Hasselmo, M. E., Ertürk, A., Mauch, C. P., Hellal, F., Förstner, F., Keck, T., Becker, K., et al. (2012b). et al. (1999). Plaque-induced neurite abnormalities: implications for disruption Three-dimensional imaging of the unsectioned adult spinal cord to assess axon of neural networks in Alzheimer’s disease. Proc. Natl. Acad. Sci. U.S.A. 96, regeneration and glial responses after injury. Nat. Med. 18, 166–171. doi: 10. 5274–5279. doi: 10.1073/pnas.96.9.5274 1038/nm.2600 Koning, R. I., Koster, A. J., and Sharp, T. H. (2018). Advances in cryo-electron Escamilla-Ayala, A. A., Sannerud, R., Mondin, M., Poersch, K., Vermeire, W., tomography for biology and medicine. Ann. Anat. 217, 82–96. doi: 10.1016/j. Paparelli, L., et al. (2020). Super-resolution microscopy reveals majorly mono- aanat.2018.02.004 and dimeric presenilin1/γ-secretase at the cell surface. ELife 9:e56679. doi: Ku, T., Swaney, J., Park, J.-Y., Albanese, A., Murray, E., Cho, J. H., et al. (2016). 10.7554/eLife.56679 Multiplexed and scalable super-resolution imaging of three-dimensional Frontiers in Neuroscience | www.frontiersin.org 10 October 2020 | Volume 14 | Article 914 Parra-Damas and Saura Tissue Clearing and Expansion in Neurodegeneration protein localization in size-adjustable tissues. Nat. Biotechnol. 34, 973–981. fibrils following inclusion body formation. Q. Rev. Biophys. 49, e2. doi: 10.1017/ doi: 10.1038/nbt.3641 S0033583515000219 Li, L., Liu, H., Dong, P., Li, D., Legant, W. R., Grimm, J. B., et al. (2016). Real-time Schedin-Weiss, S., Caesar, I., Winblad, B., Blom, H., and Tjernberg, L. O. imaging of huntingtin aggregates diverting target search and gene transcription. (2016). Super-resolution microscopy reveals γ-secretase at both sides of the ELife 5:e17056. doi: 10.7554/eLife.17056 neuronal synapse. Acta Neuropathol. Commun. 4:29. doi: 10.1186/s40478-016- Lichtman, J. W., and Denk, W. (2011). The big and the small: challenges of imaging 0296-5 the brain’s circuits. Science 334, 618–623. doi: 10.1126/science.1209168 Schermelleh, L., Ferrand, A., Huser, T., Eggeling, C., Sauer, M., Biehlmaier, O., et al. Liebmann, T., Renier, N., Bettayeb, K., Greengard, P., Tessier-Lavigne, M., and (2019). Super-resolution microscopy demystified. Nature Cell Biology 21, 72–84. Flajolet, M. (2016). Three-dimensional study of alzheimer’s disease hallmarks doi: 10.1038/s41556-018-0251-8 using the iDISCO clearing method. Cell Rep. 16, 1138–1152. doi: 10.1016/j. Schierle, G. S. K., Michel, C. H., and Gasparini, L. (2016). Advanced imaging of celrep.2016.06.060 tau pathology in Alzheimer disease: new perspectives from super resolution Liu, A. K. L., Hurry, M. E. D., Ng, O. T. W., DeFelice, J., Lai, H. M., Pearce, R. K. B., microscopy and label-free nanoscopy. Microsc. Res. Tech. 79, 677–683. doi: et al. (2016). Bringing CLARITY to the human brain: visualization of Lewy 10.1002/jemt.22698 pathology in three dimensions. Neuropathol. Appl. Neurobiol. 42, 573–587. Sheng, M., Sabatini, B. L., and Sudhof, T. C. (2012). Synapses and Alzheimer’s doi: 10.1111/nan.12293 disease. Cold Spring Harbor Perspect. Biol. 4, a005777–a005777. doi: 10.1101/ Martorell, A. J., Paulson, A. L., Suk, H.-J., Abdurrob, F., Drummond, G. T., Guan, cshperspect.a005777 W., et al. (2019). Multi-sensory gamma stimulation ameliorates Alzheimer’s- Shrivastava, A. N., Aperia, A., Melki, R., and Triller, A. (2017). Physico- associated pathology and improves cognition. Cell 177, 256.e22–271.e22. doi: pathologic mechanisms involved in neurodegeneration: misfolded protein- 10.1016/j.cell.2019.02.014 plasma membrane interactions. Neuron 95, 33–50. doi: 10.1016/j.neuron.2017. Murakami, T. C., Mano, T., Saikawa, S., Horiguchi, S. A., Shigeta, D., Baba, 05.026 K., et al. (2018). A three-dimensional single-cell-resolution whole-brain atlas Susaki, E. A., Tainaka, K., Perrin, D., Kishino, F., Tawara, T., Watanabe, T. M., using CUBIC-X expansion microscopy and tissue clearing. Nat. Neurosci. 21, et al. (2014). Whole-brain imaging with single-cell resolution using chemical 625–637. doi: 10.1038/s41593-018-0109-1 cocktails and computational analysis. Cell 157, 726–739. doi: 10.1016/j.cell. Murray, E., Cho, J. H., Goodwin, D., Ku, T., Swaney, J., Kim, S.-Y., et al. (2015). 2014.03.042 Simple, scalable proteomic imaging for high-dimensional profiling of intact Sylwestrak, E. L., Rajasethupathy, P., Wright, M. A., Jaffe, A., and Deisseroth, K. systems. Cell 163, 1500–1514. doi: 10.1016/j.cell.2015.11.025 (2016). multiplexed intact-tissue transcriptional analysis at cellular resolution. Nguyen, H. P., Van Broeckhoven, C., and van der Zee, J. (2018). ALS genes in Cell 164, 792–804. doi: 10.1016/j.cell.2016.01.038 the genomic era and their implications for FTD. Trends Gen. 34, 404–423. Tainaka, K., Kuno, A., Kubota, S. I., Murakami, T., and Ueda, H. R. (2016). doi: 10.1016/j.tig.2018.03.001 Chemical principles in tissue clearing and staining protocols for whole-body cell Nordström, U., Beauvais, G., Ghosh, A., Pulikkaparambil Sasidharan, B. C., profiling. Annu. Rev. Cell Dev. Biol. 32, 713–741. doi: 10.1146/annurev-cellbio- Lundblad, M., Fuchs, J., et al. (2015). Progressive nigrostriatal terminal 111315-125001 dysfunction and degeneration in the engrailed1 heterozygous mouse model of Tainaka, K., Murakami, T. C., Susaki, E. A., Shimizu, C., Saito, R., Takahashi, Parkinson’s disease. Neurobiol. Dis. 73, 70–82. doi: 10.1016/j.nbd.2014.09.012 K., et al. (2018). chemical landscape for tissue clearing based on hydrophilic Ortega, J. A., Daley, E. L., Kour, S., Samani, M., Tellez, L., Smith, H. S., et al. (2020). reagents. Cell Rep. 24, 2196.e9–2210.e9. doi: 10.1016/j.celrep.2018.07.056 Nucleocytoplasmic proteomic analysis uncovers erf1 and nonsense-mediated Tillberg, P. W., and Chen, F. (2019). Expansion microscopy: scalable and decay as modifiers of ALS/FTD C9orf72 toxicity. Neuron 106, 90.e13–107.e13. convenient super-resolution microscopy. Annu. Rev. Cell Dev. Biol. 35, 683– doi: 10.1016/j.neuron.2020.01.020 701. doi: 10.1146/annurev-cellbio-100818-125320 Pan, C., Cai, R., Quacquarelli, F. P., Ghasemigharagoz, A., Lourbopoulos, A., Tillberg, P. W., Chen, F., Piatkevich, K. D., Zhao, Y., Yu, C.-C., English, B. P., Matryba, P., et al. (2016). Shrinkage-mediated imaging of entire organs and et al. (2016). Protein-retention expansion microscopy of cells and tissues organisms using uDISCO. Nat. Methods 13, 859–867. doi: 10.1038/nmeth.3964 labeled using standard fluorescent proteins and antibodies. Nat. Biotechnol. 34, Pan, C., Schoppe, O., Parra-Damas, A., Cai, R., Todorov, M. I., Gondi, G., 987–992. doi: 10.1038/nbt.3625 et al. (2019). Deep learning reveals cancer metastasis and therapeutic antibody Tomer, R., Ye, L., Hsueh, B., and Deisseroth, K. (2014). Advanced CLARITY for targeting in the entire body. Cell 179, 1661.e19–1676.e19. doi: 10.1016/j.cell. rapid and high-resolution imaging of intact tissues. Nat. Protoc. 9, 1682–1697. 2019.11.013 doi: 10.1038/nprot.2014.123 Park, Y.-G., Sohn, C. H., Chen, R., McCue, M., Yun, D. H., Drummond, G. T., et al. Tønnesen, J., and Nägerl, U. V. (2013). Superresolution imaging for neuroscience. (2019). Protection of tissue physicochemical properties using polyfunctional Exp. Neurol. 242, 33–40. doi: 10.1016/j.expneurol.2012.10.004 crosslinkers. Nat. Biotechnol. 37, 73–83. doi: 10.1038/nbt.4281 Truckenbrodt, S., Maidorn, M., Crzan, D., Wildhagen, H., Kabatas, S., and Penzes, P., Cahill, M. E., Jones, K. A., VanLeeuwen, J.-E., and Woolfrey, K. M. Rizzoli, S. O. (2018). X10 expansion microscopy enables 25-nm resolution (2011). Dendritic spine pathology in neuropsychiatric disorders. Nat. Neurosci. on conventional microscopes. EMBO Rep. 19, doi: 10.15252/embr.20184 14, 285–293. doi: 10.1038/nn.2741 5836 Pinotsi, D., Kaminski Schierle, G. S., and Kaminski, C. F. (2016). Optical super- Truckenbrodt, S., Sommer, C., Rizzoli, S. O., and Danzl, J. G. (2019). A practical resolution imaging of β-amyloid aggregation in vitro and in vivo: method and guide to optimization in X10 expansion microscopy. Nat. Protoc. 14, 832–863. techniques. Methods. Mol. Biol. 1303, 125–141. doi: 10.1007/978-1-4939-262 doi: 10.1038/s41596-018-0117-3 7-5_6 Ueda, H. R., Ertürk, A., Chung, K., Gradinaru, V., Chédotal, A., Tomancak, P., et al. Porter, D. D. L., and Morton, P. D. (2020). Clearing techniques for visualizing (2020). Tissue clearing and its applications in neuroscience. Nat. Rev. Neurosci. the nervous system in development, injury, and disease. J. Neurosci. Methods 21, 61–79. doi: 10.1038/s41583-019-0250-1 334:108594. doi: 10.1016/j.jneumeth.2020.108594 Vandenberghe, M. E., Souedet, N., Hérard, A.-S., Ayral, A.-M., Letronne, F., Renier, N., Adams, E. L., Kirst, C., Wu, Z., Azevedo, R., Kohl, J., et al. (2016). Balbastre, Y., et al. (2018). Voxel-based statistical analysis of 3D immunostained Mapping of brain activity by automated volume analysis of immediate early tissue imaging. Front. Neurosci. 12:754. doi: 10.3389/fnins.2018.00754 genes. Cell 165, 1789–1802. doi: 10.1016/j.cell.2016.05.007 Vints, K., Vandael, D., Baatsen, P., Pavie, B., Vernaillen, F., Corthout, N., et al. Renier, N., Wu, Z., Simon, D. J., Yang, J., Ariel, P., and Tessier-Lavigne, M. (2019). Modernization of Golgi staining techniques for high-resolution, 3- (2014). iDISCO: a simple, rapid method to immunolabel large tissue samples dimensional imaging of individual neurons. Sci. Rep. 9:130. doi: 10.1038/ for volume imaging. Cell 159, 896–910. doi: 10.1016/j.cell.2014.10.010 s41598-018-37377-x Richardson, D. S., and Lichtman, J. W. (2015). Clarifying tissue clearing. Cell 162, Voigt, F. F., Kirschenbaum, D., Platonova, E., Pagès, S., Campbell, R. A. A., Kastli, 246–257. doi: 10.1016/j.cell.2015.06.067 R., et al. (2019). The mesoSPIM initiative: open-source light-sheet microscopes Sahl, S. J., Lau, L., Vonk, W. I. M., Weiss, L. E., Frydman, J., and Moerner, for imaging cleared tissue. Nat. Methods 16, 1105–1108. doi: 10.1038/s41592- W. E. (2016). Delayed emergence of subdiffraction-sized mutant huntingtin 019-0554-0 Frontiers in Neuroscience | www.frontiersin.org 11 October 2020 | Volume 14 | Article 914 Parra-Damas and Saura Tissue Clearing and Expansion in Neurodegeneration Wassie, A. T., Zhao, Y., and Boyden, E. S. (2019). Expansion microscopy: principles Conflict of Interest: The authors declare that the research was conducted in the and uses in biological research. Nat. Methods 16, 33–41. doi: 10.1038/s41592- absence of any commercial or financial relationships that could be construed as a 018-0219-4 potential conflict of interest. Zhao, S., Todorov, M. I., Cai, R., Maskari, R. A., Steinke, H., Kemter, E., et al. (2020). Cellular and molecular probing of intact human organs. Cell 180, Copyright © 2020 Parra-Damas and Saura. This is an open-access article distributed 796.e19–812.e19. doi: 10.1016/j.cell.2020.01.030 under the terms of the Creative Commons Attribution License (CC BY). The use, Zhao, Y., Bucur, O., Irshad, H., Chen, F., Weins, A., Stancu, A. L., et al. distribution or reproduction in other forums is permitted, provided the original (2017). Nanoscale imaging of clinical specimens using pathology-optimized author(s) and the copyright owner(s) are credited and that the original publication expansion microscopy. Nat. Biotechnol. 35, 757–764. doi: 10.1038/nbt. in this journal is cited, in accordance with accepted academic practice. 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