==== Front Mol Syst Biol Mol Syst Biol 10.1002/(ISSN)1744-4292 MSB msb Molecular Systems Biology 1744-4292 John Wiley and Sons Inc. Hoboken 10.15252/msb.20209807 MSB20209807 Review Reviews A guidebook for DISCO tissue clearing Muge Molbay et al Molbay Muge 1 2 3 † Kolabas Zeynep Ilgin 1 2 4 † Todorov Mihail Ivilinov 1 2 4 Ohn Tzu‐Lun 1 2 Ertürk Ali https://orcid.org/0000-0001-5163-5100 1 2 5 joseph67@example.com 1 Institute for Tissue Engineering and Regenerative Medicine (iTERM) Helmholtz Center Neuherberg, Munich Germany 2 Institute for Stroke and Dementia Research Klinikum der Universität München Ludwig‐Maximilians‐University Munich Munich Germany 3 Munich Medical Research School (MMRS) Munich Germany 4 Graduate School for Systemic Neurosciences (GSN) Munich Germany 5 Munich Cluster for Systems Neurology (SyNergy) Munich Germany * Corresponding author. Tel: 224.878.4158; E‐mail: joseph67@example.com † These authors contributed equally to this work 26 3 2021 3 2021 17 3 10.1002/msb.v17.3 e980547-40-0482 30 6 2020 14 1 2021 © 2021 The Authors. Published under the terms of the CC BY 4.0 license This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. Abstract Histological analysis of biological tissues by mechanical sectioning is significantly time‐consuming and error‐prone due to loss of important information during sample slicing. In the recent years, the development of tissue clearing methods overcame several of these limitations and allowed exploring intact biological specimens by rendering tissues transparent and subsequently imaging them by laser scanning fluorescence microscopy. In this review, we provide a guide for scientists who would like to perform a clearing protocol from scratch without any prior knowledge, with an emphasis on DISCO clearing protocols, which have been widely used not only due to their robustness, but also owing to their relatively straightforward application. We discuss diverse tissue‐clearing options and propose solutions for several possible pitfalls. Moreover, after surveying more than 30 researchers that employ tissue clearing techniques in their laboratories, we compiled the most frequently encountered issues and propose solutions. Overall, this review offers an informative and detailed guide through the growing literature of tissue clearing and can help with finding the easiest way for hands‐on implementation. Tissue‐clearing methods have allowed imaging intact biological specimens and understanding biology at a whole‐organism and systems‐level. This Review provides a guide for scientists who would like to setup a clearing protocol, with an emphasis on DISCO methods. 3D imaging DISCO labeling light sheet tissue clearing Subject Categories Development & Differentiation Methods & Resources Neuroscience Munich Cluster for Systems Neurology390857198 ERA‐Net Neuron01EW1501A Fritz Thyssen Stiftung (Fritz Thyssen Foundation) 10.13039/501100003390 30.255.87.135MN Deutsche Forschungsgemeinschaft (DFG) 10.13039/501100001659 ER 810/2‐1 Helmholtz ICEMED AllianceNIHAG057575 TRABIT765148 source-schema-version-number2.0 cover-dateMarch 2021 details-of-publishers-convertorConverter:WILEY_ML3GV2_TO_JATSPMC version:5.9.9 mode:remove_FC converted:26.03.2021 Mol Syst Biol. (2021) 17 : e9807 ==== Body Tissue transparency Biological tissues are remarkably complex. While several histological techniques are currently available for the analysis of biological tissues, a variety of challenges remains to be tackled. For example, imaging large samples requires destroying tissue integrity by sectioning them into thin slices for visualization. This process is labor‐intensive and re‐assembling information from serial tissue sections into a three‐dimensional reconstruction is an extremely time‐consuming process, likely causing loss of important information (Ertürk et al, 2012a). Rendering the tissues transparent is an option for circumventing the need for sectioning and allows imaging tissues while keeping them intact and preserving their details. Optical tissue clearing is the term that spans a variety of methods applying this concept. From the very first clearing protocol to the most recent ones, transparency is achieved by homogenizing the refractive index (RI) within the tissue. When light waves propagate through a tissue with nonhomogeneous refractive indices, the differences in the RIs will result in refraction at the interface, distorting the shape of the wave front. This process is also referred to as scattering. Having a wider distribution of the RI in a medium causes more scattering, degrading the quality of the acquired image. Therefore, minimizing the refraction by homogenizing the RI allows light to penetrate deeper into the medium (Tuchin, 2015), hence rendering a sample transparent. The first tissue clearing method was described in the 1900s by Werner Spalteholz, who used a mixture of Methyl salicylate/Benzyl benzoate (5:3 vol:vol) (Spalteholz, 1914) to apply the RI homogenization protocol. Derivatives of the Spalteholz' method were used by embryologists by substituting methyl salicylate with benzyl alcohol. This new combination formed Murray's clear (BABB) containing 1:2 combination of benzyl alcohol:benzyl benzoate (Dent et al, 1989; Klymkowsky & Hanken, 1991). Currently, tissue clearing, especially when paired with optical imaging and fluorescent labeling of cellular structures has become a powerful tool for collecting information deep within tissues at single‐cell resolution. Due to the wide applicability of tissue clearing, several different approaches have emerged including hydrogel‐based clearing, aqueous‐based clearing, and those that followed Spalteholz's historical recipe on tissue dehydration—solvent‐based clearing (Fig 1) (Silvestri et al, 2016). These approaches have expanded the application of tissue clearing by providing specialized protocols for a variety of purposes. Figure 1 The most common tissue clearing methods Tissue clearing methods can be separated into three main categories based on their chemistry: hydrogel‐based, hydrophilic, and hydrophobic. The subtypes mainly differ according to reagents/approaches used. Several parameters will influence the choice of the procedure such as the labeling method, the size of the tissue, the species, and the nature of the molecule of interest. Cleared lipid‐extracted acryl‐hybridized rigid immunostaining/in situ hybridization‐compatible tissue hydrogel (CLARITY) (Chung et al, 2013), passive CLARITY technique (PACT) and perfusion‐assisted agent‐release in situ (PARS) (Yang et al, 2014) are hydrogel‐based protocols. They utilize an acrylamide monomer to form a tissue‐hydrogel hybrid, which allows immobilizing most of the amino group containing molecules by cross‐linking, thus keeping large tissues intact and decreasing structural damage. This process involves electrophoresis or diffusion depending on the nature of the biological specimen and the specific scientific question. After fixing the tissue in a hydrogel scaffold, the sample is subjected to delipidation using sodium dodecyl sulfate (SDS) detergent. The composition of the reagents can be modified depending on the intended purpose of imaging (e.g., RNA or protein imaging). The nature of the reagents also facilitates tissue expansion which potentially reveals hidden structures. Among the downsides of this approach are the longer incubation times required for clearing and the need for special equipment in order to employ some of the techniques (Gradinaru et al, 2018). All subtypes derived from the CLARITY approach such as PACT and PARS (Yang et al, 2014), stabilization under harsh conditions via intramolecular epoxide linkages to prevent degradation (SHIELD) (Park et al, 2019) and BoneCLARITY (Greenbaum et al, 2017) are protocols optimized toward a certain use case. As an example, PACT is a passive CLARITY technique involving a protocol suitable for small samples, while PARS is a perfusion‐assisted agent‐release in situ protocol for whole‐body clearing with solution delivery through the vasculature. Other CLARITY‐based protocols are modified for different applications or specific tissues, such as BoneCLARITY, developed for investigating the notoriously difficult bone tissue. An elaborate review on hydrogel‐based tissue clearing methods is available by Gradinaru et al (2018). The second major type of tissue clearing methods is hydrophilic or aqueous‐based approaches. These methodologies initially surfaced around the 1990s utilizing various water‐soluble agents such as sugars, dextran, sucrose, urea, and amino alcohols. The main distinctive feature of aqueous‐based methods is that the employed water‐soluble agents are less destructive to the tissue and display high levels of biocompatibility and biosafety. The different method subtypes stem from the different reagents that are used in protocols for decolorization, delipidation, or RI‐matching steps, i.e., urea in Sca/e (Hama et al, 2011), urea with sorbitol in Sca/eS (Hama et al, 2015), fructose for See Deep Brain (SeeDB) (Ke et al, 2013), and amino alcohols in clear, unobstructed brain or body imaging cocktails and computational analysis (CUBIC) (Tainaka et al, 2014). Hydrophilic methods involve several alternative mechanistic approaches for homogenizing the RI. For instance, the sample can be passively immersed in an RI‐matching solution. Alternatively, lipids can be removed from the sample and tissues can be hyperhydrated to lower the RI. For more details on hydrophilic approaches, an extensive review is available by Tainaka et al (2018). Lastly, hydrophobic or solvent‐based clearing methods rely on organic solvents to render the tissues transparent. While this approach dates back to Spalteholz' protocol described in 1911, it did not draw much attention at the time with the exception of a few publications elaborating on the method (Dent et al, 1989; Klymkowsky & Hanken, 1991). It later re‐emerged with 3D imaging of solvent‐cleared organs (3DISCO) that was used to achieve transparency of a whole mouse brain in 1–2 days (Ertürk et al, 2012a). Every hydrophobic clearing method involves three fundamental steps: dehydration, delipidation and RI matching. The dehydration step is the distinctive step for hydrophobic methods and together with delipidation, the aim is to remove the two most abundant chemical components of biological tissue, namely water and lipids. The RI of water is 1.33 (Hale & Querry, 1973) and greatly differs from that of the remaining tissue (~ 1.55). Therefore, replacing water with a liquid with a similar RI to that of the remaining tissue can greatly reduce scattering (Richardson & Lichtman, 2015). Applications of tissue clearing Tissue clearing offers the opportunity to understand biology at a whole organism and systems level and presents several advantages for making new biological discoveries. One major feature of tissue clearing is its potential to reveal 3‐dimensional structural information. The ability to keep tissues intact during imaging has revealed previously unknown microscopic details and anatomical connections. For instance, imaging of cleared bone marrow using 3DISCO showed that non‐dividing stem cells localize in perisinusoidal areas in the bone marrow (Acar et al, 2015). Another study used FocusCLEAR to reveal the spatial organization of cockroach brain nuclei (Chiang et al, 2001). In the mouse gut, immunolabeling‐enabled imaging of solvent‐cleared organs (iDISCO) revealed the peripheral nervous system adapting to perturbations (Gabanyi et al, 2016). New cortical brain regions, which are downstream of whisker‐evoked sensory processing, were discovered using iDISCO+ in mice (Renier et al, 2016). More recently, imaging of whole‐body neuronal projections in adult mice using vDISCO (the 'v' refers to the variable domain of heavy‐chain antibodies; that is, nanobodies) revealed vascular connections between the skull and the meninges (Cai et al, 2019), similar to the discovery of trans‐cortical vessels in the long bones using the simpleCLEAR protocol (Grüneboom et al, 2019). Additionally, clearing agent fructose, urea, and glycerol for imaging (FUnGI) provided an organoid clearing protocol for multi‐color lineage tracing of tumor heterogeneity (Rios et al, 2019). Besides revealing detailed information, keeping the tissues intact also maximizes the information that can be obtained from a large specimen. Elegant examples of this are whole‐body analyses that allowed the unbiased assessment of treatment efficacy and enabled analyzing the biodistribution of nanoparticles, antibodies, and various other targeting agents. This powerful application was demonstrated with the use of CUBIC to detect cancer metastases throughout a whole mouse body sample (Kubota et al, 2017). More recently, vDISCO, in conjunction with deep learning‐based algorithms allowed the quantification of cancer cells that had been targeted by therapeutic antibodies (Pan et al, 2019). Beyond cancer research, further medically relevant applications that are worth noting include the analysis of the spatial distribution of transplanted stem cells in adult mice body using ultimate DISCO (uDISCO) (Pan et al, 2016) and screening the transfection efficiency of adeno‐associated virus (AAV) variant with CLARITY (Deverman et al, 2016). Furthermore, iDISCO+ enabled automated cell detection of cFos staining and Allen Brain Atlas registration revealing the brainstem circuit control for feeding behavior and B‐amyloid plaques in an Alzheimer's disease (AD) mouse model (Liebmann et al, 2016; Nectow et al, 2017) (Fig 2). Figure 2 Tissue clearing can be applied to samples ranging from organs, to mouse embryos to adult rodent bodies and reveals macroscopic and microscopic details (A) Nerve and nerve endings are revealed in an E12.5 mouse embryo cleared with iDISCO protocol and immunostained for motor (red) and sensory (magenta) nerves and nerve endings (cyan). (B) Kidney vasculature is visualized after fDISCO clearing using CD31‐A647 labeling. (C) B‐amyloid plaques in the brain with neurofilament H staining in a 10‐month‐old in AD mouse cortex cleared with iDISCO (Scale bar: 200 μm in upper and 30 μm in lower figures). (D) Neuronal projections in the whole adult mouse are shown in a Thy1‐GFPM mouse boosted with Anti‐eGFP nanobodies using the vDISCO clearing protocol. (E) A 3D reconstruction of whole adult human kidney performed using SHANEL. The autofluorescence signal at 780 nm (cyan), the glomeruli and vessels from TO‐PRO‐3 labeling (magenta), the vessels from the dextran labeling (green), and the merged image are shown, respectively. (F) Whole‐brain vasculature is shown using PEGASOS protocol in Tie2‐Cre;tTAflox;tetO‐H2BGFP (TTH) mice in lateral view. Used with permission from: (A) Dr. Gist Croft, Rockefeller University, (B) Science Advances (Qi et al, 2019), (C) Cell (Liebmann et al, 2016), (D) Nature Neuroscience (Cai et al, 2019), (E) Cell (Zhao et al, 2020), (F) Cell Research (Jing et al, 2018). Another benefit of whole intact tissue visualization is that it provides less error‐prone measurements and more informative quantification. For example, the growth of glioblastomas in mice was measured under different conditions using 3DISCO clearing (Garofalo et al, 2015) and the distance between neural stem cells and blood vessels was assessed with Sca/e (Hama et al, 2011). Moreover, clearing combined with unbiased quantification methods, i.e., deep learning algorithms, made it possible to obtain a system‐level understanding at single‐cell resolution. The complex mouse brain vasculature was inspected using a combination of 3DISCO and a convolutional neural network and revealed structural differences in the cerebral angioarchitecture among common inbred and outbred mice strains (Todorov et al, 2020; Fig 3). The same pipeline, but relying on manual analysis instead of machine learning, would be significantly more time‐consuming and might potentially result in a subjective end result. A similar approach involving iDISCO+ revealed the local adaptations and functional correlates across brain regions and indicated vascular plasticity in diverse disease models (Kirst et al, 2020). Figure 3 Analysis tools for tissue clearing applications Analysis tools include: (A) TubeMap pipeline which demonstrates the fine‐scale organization on the brain vasculature. In this study, Kirst et al (2020) demonstrated how stroke affects the brain, using antibody labeling. (B) The ClearMAP pipeline is used for examining parental behavior through Fos activity in the whole brain followed by a filter‐based analysis. (C) SHANEL pipeline has one of the recent algorithms that include deep learning methods to analyze big tissues to quantify cleared human brain tissues identified in the six layers of primary visual cortex. The summary of the cell properties from different brain regions taken from cortex and hippocampus were analyzed using the authors' CNN. (D) The VesSAP pipeline, which can extract features and registers the mouse brain vasculature to Allen Brain Atlas. Images represent the steps of feature extraction, radius illustration, and vascular segmentation. (E) The DeepMACT pipeline, which detects metastasis throughout organs in adult mice. Each dot represents a metastasis. Used with permission from (A) Cell (Kirst et al, 2020), (B) Cell (Renier et al, 2016), (C) Cell (Zhao et al, 2020), (D) Nature Methods (Todorov et al, 2020), (E) Cell (Pan et al, 2019). The ability of clearing to reveal fine details deep within tissues makes it a powerful tool in the context of disease pathology. Analyses of tumors using CUBIC indicated a heterogenous nature of macrophage infiltration in lung carcinoma (Cuccarese et al, 2017), while BABB clearing revealed growth patterns of prostate cancer (van Royen et al, 2016). Similarly, tissue clearing has been applied to neurological pathology, where 3DISCO showed microvessel reorganization following stroke (Lugo‐Hernandez et al, 2017), and CLARITY elucidated the relationship between monoaminergic fibers and Lewy bodies in Parkinson patients (Liu et al, 2016), and AD plaques (Ando et al, 2014). CLARITY was also used to examine the dynamics of pancreatic innervations in pathological conditions such as in diabetes (Hsueh et al, 2017). Overall, the ability of clearing techniques to reveal information that has been inaccessible to other methodologies has been instrumental in the analysis of several pathologies. In summary, a variety of clearing techniques is available, with each of them presenting certain advantages depending on various parameters or being better suited for given applications. These methods are undergoing continuous improvements and are being adapted to specific applications. Further applications are shown in Table 1, and two recent reviews provide an in‐depth discussion of the different applications (Ueda et al, 2020; Tian et al, 2021). In the following section, we narrow down our focus to solvent‐based method by first sharing some of the known protocols, developed for various needs. Table 1 Tissue clearing applications based on tissue clearing method and labeling. Sample Tissue clearing method used Labeling Whole mouse organ Development of heart CUBIC (Li et al, 2016) AAV, Ab labeling Lung 3DISCO (Ertürk et al, 2012a; Mzinza et al, 2018) Endogenous GFP SWITCH (Murray et al, 2015) Endogenous GFP CLARITY (Kim et al, 2015) Endogenous GFP uDICSO (von Neubeck et al, 2018) Endogenous mCherry Spleen 3DISCO (Ertürk et al, 2012a) Endogenous GFP Lymph node 3DISCO (Ertürk et al, 2012a), Ab labeling, Endogenous xFP 3DISCO (Ertürk et al, 2012a) Ab labeling, Endogenous xFP Mammary gland CUBIC (Davis et al, 2016) Endogenous GFP FUnGI (Rios et al, 2019) Ab labeling Heart CLARITY (Kim et al, 2015) Endogenous GFP SWITCH (Murray et al, 2015) Ab labeling Kidney CLARITY (Kim et al, 2015) Endogenous GFP Liver CLARITY (Kim et al, 2015) Endogenous GFP SWITCH (Murray et al, 2015) Endogenous GFP 3DISCO (Mzinza et al, 2018) Endogenous GFP Uterus 3DISCO (Yuan et al, 2018) Endogenous GFP Intestine iDISCO (Gabanyi et al, 2016) Ab labeling Human organ parts Lung CUBIC (Tainaka et al, 2018; Nojima et al, 2017) Ab labeling Kidney CUBIC (Tainaka et al, 2018; Nojima et al, 2017) Ab labeling Pancreas CLARITY (Hsueh et al, 2017) Ab labeling Spleen CUBIC (Nojima et al, 2017) Ab labeling Intestine CUBIC (Nojima et al, 2017) Ab labeling Lymph node CUBIC (Nojima et al, 2017) Ab labeling Embryo Human 3DISCO/iDISCO (Yuan et al, 2018) Ab labeling Mouse 3DISCO (Ertürk et al, 2012b) Endogenous mGFP, Tomato iDISCO (Renier et al, 2014) Ab labeling Sca/e (Hama et al, 2011) Endogenous YFP, Ab labeling CUBIC (Cuccarese et al, 2017; Li et al, 2016) Endogenous GFP, Ab labeling Brain organoid iDISCO (Birey et al, 2017) Ab labeling Bone Long bones CUBIC (Chen et al, 2016, 5) Endogenous mCherry, Ab labeling simpleCLEAR (Grüneboom et al, 2019) Endogenous tdTomato, Ab labeling 3DISCO (Acar et al, 2015) Endogenous GFP, Ab labeling Whole‐body vDISCO (Cai et al, 2019) Endogenous GFP, Nanobooster PARS (Yang et al, 2014) Ab labeling CUBIC (Tainaka et al, 2014; Susaki et al, 2015) Endogenous GFP, Ab labeling uDISCO (Pan et al, 2016) Endogenous GFP vDISCO (Pan et al, 2019) Endogenous mCherry, Ab labeling CUBIC (Kubota et al, 2017) Endogenous mCherry, Ab labeling Brain Whole mouse brain 3DISCO (Ertürk et al, 2012a; Ertürk et al, 2012b; Lin et al, 2018; Lugo‐Hernandez et al, 2017) Endogenous GFP, FITC Dextran uDISCO (Pan et al, 2016; Li et al, 2018) Endogenous GFP CUBIC (Tatsuki et al, 2016; Susaki et al, 2014; Tainaka et al, 2018; Susaki et al, 2015) Ab labeling iDISCO (Renier et al, 2014) Ab labeling iDISCO (Liebmann et al, 2016) Ab labeling iDISCO+ (Renier et al, 2016; Nectow et al, 2017) Ab labeling CLARITY (Kim et al, 2015; Bedbrook et al, 2018; Deverman et al, 2016; Chung et al, 2013) Endogenous GFP, AAV AAV, Endogenous YFP Sca/eS (Hama et al, 2015) Endogenous YFP, Ab labeling SWITCH (Murray et al, 2015) Ab labeling SeeDB2 (Ke et al, 2016) Endogenous YFP Human brain slice SHANEL (Zhao et al, 2020) Ab labeling SWITCH (Murray et al, 2015) Ab labeling CUBIC (Tainaka et al, 2018; Nojima et al, 2017) Ab labeling CLARITY (Ando et al, 2014; Phillips et al, 2016; Morawski et al, 2018; Liu et al, 2016; Chung et al, 2013) Ab labeling Cockroach brain FocusClear (Chiang et al, 2001; Liu & Chiang, 2003) Ab labeling, WGA Rat brain FluoClearBabb (Stefaniuk et al, 2016) Ab labeling Fly brain SeeDB2G (Ke et al, 2016) Ab labeling Vasculature Mouse whole brain 3DISCO (Todorov et al, 2020) WGA, small dye iDISCO+ (Kirst et al, 2020) Ab labeling Tissue Spinal cord injury 3DISCO (Ertürk et al, 2012a; Zhu et al, 2015) Endogenous GFP CLARITY (Hsueh et al, 2017; Glaser et al, 2017) Ab labeling, WGA Tumor–Human CUBIC (Nojima et al, 2017) Ab labeling BABB (van Royen et al, 2016) Ab labeling DIPCO (Tanaka et al, 2017) Ab labeling FUnGI (Rios et al, 2019) Ab labeling Others Bio‐artificial skeletal muscle 3DISCO, ClearT2, ScaleA2 (Decroix et al, 2015) Endogenous GFP, Ab labeling Cancer Lung carcinoma CUBIC (Cuccarese et al, 2017) Endogenous GFP, RFP, Ab labeling 3DISCO (Garofalo et al, 2015) Ab labeling Glioma vDISCO (Pan et al, 2019) Endogenous mCherry, Ab labeling Whole body CUBIC (Kubota et al, 2017) Endogenous mCherry, Ab labeling John Wiley & Sons, Ltd Organic solvent‐based tissue clearing techniques Solvent‐based or hydrophobic methods have improved drastically in the past decade. New protocols have emerged either addressing the shortcomings of the original protocol or optimizing it for a more specific application. Dehydration, lipid extraction, and RI matching around 1.55 are the essential steps common to this type of clearing approach. The first method to revive the century‐old technique was 3DISCO, which is known to be robust and to work on a number of different tissue types. The major advantages were the speed, the transparency, and the ease of storing the samples, because of their solid nature following processing. However, at the time the main shortcomings were quenching the genetically expressed fluorescence and tissue shrinkage. Nevertheless, these shortcomings also triggered the further optimization of this approach. Spalteholz's tissue clearing At the beginning of the 20th century, Werner Spalteholz mixed Methyl salicylate and Benzyl benzoate (5:3 vol:vol) to make various human organs transparent (Spalteholz, 1914). Examples of analyzed organs include the human heart which was made transparent in order to observe the blood vessels and the development of an infarction and the human hand which has been preserved to this day in the Anatomy Institute of Leipzig University, Germany (Fig 4). Although Spalteholz's attempts were very popular in his time, he could only obtain limited scientific knowledge due to the technical limitations of the microscopes. Figure 4 Hand sample cleared by Spalteholz himself in 1911 Spalteholz injected Indian ink to the hand's arteries via the A. nutriciae. Decalcification allowed observing the arterial branching in the bone. The magnified image depicts the inner arterial supply of the metacarpal bones. Originally, this specimen was shown in the 1st exhibition in 1911, "Welthygieneausstellung", which attracted more than a million people. Most of Spalteholz's other original specimens were lost during the fire in the Leipzig anatomy department during the 2nd World War. Image: courtesy of Prof. Dr. Hanno Steinke from Anatomy Department of Leipzig University, Germany. BABB clearing In this protocol, the authors first introduced the term ultramicroscopy which advanced imaging in comparison with the previous techniques via two‐sided light sheets (Dodt et al, 2007). They used a series of different ethanol concentrations to dehydrate samples and BABB to clear the tissue. This way, they performed the first imaging of fluorescently labeled embryonic mouse brains and vasculature that was cleared with organic solvents. DBE clearing This protocol substituted the RI‐matching reagent with dibenzyl ether (DBE), a more "GFP‐friendly" clearing medium, alleviating the loss of fluorescence quality caused by BABB (Becker et al, 2012). Clearing with DBE provides improved tissue transparency and strikingly improved fluorescence intensity in GFP expressing mouse brains and other samples such as mouse spinal cords, or embryos. In this protocol, ethanol was replaced by tetrahydrofuran (THF) after the realization of ethanol causing the bleaching of endogenous fluorescence. THF was found to be more GFP friendly as a dehydration medium after screening several chemicals. 3DISCO 3DISCO was the first protocol that coined the term DISCO, which was then followed by newer iterations (Ertürk et al, 2012a, 2012b). Primarily developed for the clearing and imaging of unsectioned mouse brain and spinal cord, the 3DISCO protocol uses THF for dehydration and DCM for lipid extraction. Dibenzyl ether (DBE) is used as the last reagent to match the RI of the sample to the imaging solution. iDISCO – iDISCO+ iDISCO (Renier et al, 2014) improved the sample labeling conditions by reducing the autofluorescence and increasing the signal‐to‐noise ratio. This protocol allowed antibodies to penetrate deeper into the tissue by the addition of a pretreatment step with methanol, hydrogen peroxide, detergents, and dimethyl sulfoxide (DMSO). This was then followed by antibody labeling and tissue clearing with 3DISCO. In the later iDISCO+ (Renier et al, 2016) protocol, an additional delipidation step with DCM was established. FluoClearBABB FluoClearBABB is a derivative of the BABB clearing protocol (Schwarz et al, 2015). It differs from the other BABB‐based clearing protocols in that it is performed under basic pH and uses 1‐propanol or tert‐butanol for dehydration. FluoClearBABB allows whole‐brain clearing, minimizes optical distortions, and preserves the majority of EGFP and mRFP fluorescence. uDISCO uDISCO was the first technique that accomplished both clearing and imaging an entire mouse body (Pan et al, 2016). This was achieved by isotropic shrinkage of the samples by the chemicals. Specifically, the protocol involves immersing the samples into ascending concentrations of tert‐butanol, instead of THF for dehydration and using BABB with diphenyl ether (DPE) for RI matching, which enhances the preservation of endogenous fluorescence. ECi clearing In the ECi protocol, serial dehydration is performed using pH‐adjusted ethanol and the RI matching is done using the non‐toxic, organic compound ethyl‐3‐phenylprop‐2‐enoate (ECi, RI > 1.5) (Klingberg et al, 2017). The major advantage of this technique is that it uses non‐toxic reagents for this process. vDISCO The vDISCO protocol includes decolorization, decalcification, permeabilization, and nanoboosting steps in a pressure‐driven pump system (Cai et al, 2019). Typically, an active pumping system is known to distort the specimen. However, in this protocol there is very little if any distortion. Still, it is noteworthy that quantification of any tissue distortion have not been reported. Following the pre‐processing steps, a modified 3DISCO protocol is applied through the entire mouse body. Anti‐XFP nanobodies conjugated to fluorescent dyes are used to enhance the fluorescent signal two orders of magnitude and yield single‐cell resolution images from the whole organism. PEGASOS Polyethylene glycol (PEG)‐associated solvent system (PEGASOS) renders nearly all types of tissues transparent except for pigmented epithelium (Jing et al, 2018). According to the authors' report, hard tissues including bones and teeth become nearly invisible after clearing. The PEG component within the clearing medium allows preserving endogenous fluorescence for a long time. In this study, the authors applied a modified uDISCO protocol where they mixed PEG with the reagents. FDISCO FDISCO upgraded the technology with superior fluorescence preserving capability by adjusting the temperature and pH conditions of the 3DISCO protocol (Qi et al, 2019). In FDISCO, all steps are performed at 4°C and the pH of all solutions is adjusted to 8.3. sDISCO Stabilized DISCO (sDISCO) provides a solution to optical clearing and storage times for transgenic specimens which are limited due to the continuous formation of peroxides and aldehydes, severely quenching the fluorescence (Hahn et al, 2019). It uses purified DBE or BABB and anti‐oxidant propyl gallate is added to stabilize the solutions. BALANCE Bleaching‐Augmented soLvent‐bAsed Non‐toxic ClEaring (BALANCE) is an ECi based clearing protocol that was successfully used to image the mouse heart (Merz et al, 2019). The major advantage here is the relatively smaller number of chemicals that are required, ensuring low toxicity. However, since it is a rather new technique it has not been compared with other clearing technologies. EyeCi EyeCi is a combination of the iDISCO and ECi protocols used for immunolabeling and clearing, and has been used on whole eyes of mice (Henning et al, 2019). This protocol is specifically adapted for bleaching the melanin in the pigmented epithelium of the retina. SHANEL The Small micelle‐improved Human organ ANtibody Efficient Labeling (SHANEL) protocol was developed to allow the penetration of molecules deep into sturdy aged human tissues and provides a solution to a major bottleneck of human tissue histology (Zhao et al, 2020). SHANEL uses a detergent called (3‐((3‐Cholamidopropyl) dimethylammonium)‐1‐propanesulfonate) (CHAPS) for tissue permeabilization. It allows penetration of labeling and clearing agents into centimeters‐thick mammalian organ samples. Human samples two to three orders of magnitude larger than mouse tissues were successfully labeled and cleared by SHANEL. Choosing the best strategy among all the available clearing protocols may require not only expertise but also testing multiple protocols to achieve optimal results. In Fig 5, we offer a simplified chart to help choosing the most suitable method along with the right protocol and the appropriate setup. Understanding the details of each step is quite fundamental to successfully apply these techniques and to adapt them as necessary. To this end, the next section focuses on the specifics of the individual steps of solvent‐based tissue clearing. Figure 5 Decision tree for choosing the optimal tissue clearing protocol Several parameters should be weighed to achieve optimal results when choosing the clearing protocol. This flowchart demonstrates an easy way to decide which clearing method would suit a potential research question. A step‐by‐step guide through high‐throughput DISCO clearing Regardless of the chosen protocol, solvent‐based clearing includes the following steps: perfusion and fixation, decolorization, decalcification, permeabilization, staining, dehydration, delipidation, and RI matching. After the tissue has been cleared, image acquisition and analysis take place, and this differs based on the samples, protocols, and the specific biological questions asked. Here, we provide a detailed step‐by‐step guide to help scientists achieve optimal results and key recommendations about each step. Perfusion and fixation Tissue fixation is a critical step when preparing tissues for clearing. It terminates any ongoing biochemical reaction and may also increase the treated tissues' mechanical strength or stability (Gage et al, 2012). The fixation process and type of fixative depends on the experimental design and can be done either actively or passively. The active version is used for large tissues such as a whole mouse body or human organs. It involves a pump‐driven way of fixation in which the vasculature of the tissue is used to distribute the fixative to the deeper tissues. The first step is washing out the blood and the most commonly used solution to achieve this is phosphate buffered saline with 1% Heparin (PBS‐H). Heparin in PBS‐H reduces the formation of blood clots and occlusions in vessels, allowing better circulation of liquids (O'Brien, 1960). Since blood clots can form within a couple of seconds, perfusion with PBS‐H should be started right after the animal is deeply anesthetized and restrained in proper position in order to remove as much blood as possible. However, it should be noted that vascular labeling requires alterations in this step. In case, the experiment involves vascular labeling, e.g., by injecting Evans Blue, Wheat Germ Agglutinin, or antibody labeling, using heparin is not recommended as it is likely to wash out the labeling (Todorov et al, 2020). There are some tips for evaluating the quality of pump‐driven perfusion. For instance, liver color is a good measure of the quality of perfusion; after adequate perfusion with PBS‐H, the liver color should turn from dark red to pale light brown/yellow. The second step involves fixing the tissue with a fixative, most commonly paraformaldehyde (PFA) or formalin, using perfusion. In perfusion of rodents, due to the protein cross‐linking that takes place during this fixation muscles can be fired and contractions can be observed in different parts of the body, especially in the tail. These are indicators of adequate perfusion of the fixative throughout the body (Thavarajah et al, 2012). On the other hand, strong predictors of an unsuccessful perfusion are extremely inflated lungs and fixative escaping through the nose of the specimen, in which case the perfusion needle is likely in the right ventricle putting pressure on the pulmonary circuit. Repositioning the needle back to the left ventricle may remedy this. If organ‐level clearing is desired, passive fixation is an option but it is possible that the areas deeper in the tissue may potentially remain less transparent in contrast to active perfusion. In any case, over‐fixation must be avoided, as PFA cross‐linking of tissues can obscure antibody binding sites leading to incomplete immunolabeling. We also have observed that over‐fixation causes insufficient transparency and leads to a yellowish color of the tissue after clearing, lowering the overall signal quality in the samples during imaging. Recommendations It is important to prevent the decline of the cardiovascular circulation due to excessive anesthesia, prolonged/repeated trials of inserting, and securing of the perfusion needle, etc. The heart has to contract with at least 1 Hz at the time of starting the perfusion of fixative. We recommend that the same person performs all steps described above until satisfactory tissue‐clearing results are achieved, in order to maximize consistency when handling the samples. The mode of fixation and type of fixative depend on the aim of the experiment. Whole‐body clearing requires perfusion of the fixative for deeper fixation. Heparin in the perfusion solution facilitates the circulation by preventing the cloth formation but it is not a must. Heparin concentration should be adjusted according to the purpose. For example, for vascular labeling heparin in perfusion solution is not recommended to avoid wash out the labeling. The speed of perfusion should closely match the upper limit of the physiological pressure and volume of the heart in order to obtain best results, i.e., the most complete perfusion without bursting capillaries. Over‐fixation should be avoided as it can jeopardize the immunolabeling quality and decrease the level of transparency causing the sample to have a yellowish color. After harvesting the organ(s)/specimen, we suggest keeping the sample at 4°C for optional post‐fixation or until the staining/clearing begins. Clearing Decolorization In optical tissue clearing, light absorption by specific biological substances is a major obstacle. These light absorbing pigments accumulate in tissues and create autofluorescence emission, consequently reducing the tissue signal quality (Tuchin, 2015). For better clearing and deeper imaging, pigments should be eliminated as efficiently as possible. The most prevalent pigments are hemoglobin, melanin, and lipofuscin (Hegyi et al, 2011). So far, the decolorization in clearing has mostly focused on the removal of heme groups from hemoglobin. Although perfusion of the animal to wash out the blood is one way to decrease the autofluorescence, it is usually not enough. Remaining heme groups can still hinder imaging especially in organs with high blood content, such as the spleen, bone marrow, and liver. A common approach is either to bleach the heme group or dissociate and wash it out, using peroxides, acid acetones, or strong bases, respectively (Richardson & Lichtman, 2015). The most frequently used reagents for decolorization are SDS or amino alcohols. Quadrol (N,N,N′,N′‐Tetrakis(2‐hydroxypropyl)ethylenediamine) combined with ammonium solutions is another approach for decolorization (Susaki et al, 2014). The second light absorbing pigment is melanin, most abundantly present in the skin and the eyes. The removal of the skin and the eyes, in case they are not fundamental to the hypothesis being tested, or using albino transgenic animals will reduce the autofluorescence coming from these sources. Lastly, lipofuscin is an age‐dependent accumulated pigment in the adult brain. One way to avoid lipofuscin is using young animals, but it nevertheless remains an unresolved problem when handling human samples and aged animals (Moreno‐García et al, 2018). Recommendations Organic pigments accumulated in organs cause autofluorescence and reduced tissue clearing efficiency. To avoid this, a decolorization step is recommended. Bleaching or dissociation with chemicals is an option for removing heme. However, these procedures are often disruptive to the tissue and can cause damage and bleaching of fluorescent proteins. Amino alcohols are known not to cause damage or alter tissue signal (Susaki et al, 2014). To minimize the unfavorable effects of pigments, melanin‐rich organs (skin and eyes) can be removed and/or young animals can be used to avoid lipofuscin. Lipofuscin and melanin remain an open challenge in the decolorization process, and further research is necessary to find optimal ways to overcome them. Decalcification Bone tissue has a unique composition; soft tissue which forms the bone marrow and the highly calcified hard tissue. When imaging the organs enclosed in bone structures, reducing the scattering of light through the bone matrix is particularly important (Genina et al, 2008). A decalcification step is recommended to make bones and bone encapsulated organs (i.e., the brain inside the skull and the lungs inside the ribs) more permeable to clearing chemicals (Verdenius & Alma, 1958). Traditionally, formic acid, nitric acid, trichloroacetic acid, hydrochloric acid (HCl), or chelating reagents such as ethylenediaminetetraacetic acid (EDTA) are used for the decalcification of the bone matrix (Tainaka et al, 2014; Cai et al, 2019; Pan et al, 2019). EDTA can be used for whole‐body decalcification upon perfusing in fixed whole‐body samples (e.g., in PEGASOS and vDISCO methods). It should be noted that the EDTA concentration influences the shrinkage strength, with higher EDTA concentrations resulting in stronger shrinkage. Therefore, it must be adjusted depending on the nature of the sample and the question of interest. Moreover, the shrinkage and distortion of the tissue may differ depending on whether the organ was dissected or the body was intact. Recommendations Bone clearing can be performed either by using high RI solutions (RI = 1.555–1.564) or by subjecting the sample to decalcification with chemicals. EDTA is the most commonly used agent to remove Ca2+, and it can be used via active perfusion or passive incubation. EDTA concentration is directly proportional to the amount of shrinkage; the higher the EDTA concentration, the more shrinkage takes place. Thus, depending on the nature of the sample, the concentration should be adjusted. Permeabilization and staining Permeabilization facilitates the penetration of both clearing chemicals and labeling agents (e.g., dyes and antibodies) and it is therefore fundamental especially for whole‐body clearing and labeling. Tissue permeabilization eliminates several barriers including lipids and extracellular matrix (ECM). In traditional histology, heat or mild detergents such as Triton X‐100, Saponin, or SDS are commonly used to dissolve the lipid bilayer and give successful results for small samples or 1–2 mm sections (Jamur & Oliver, 2010). In iDISCO and derivatives, methanol and methanol/DCM mixtures are used for permeabilization through delipidation (Renier et al, 2014). SHANEL on the other hand involves a relatively complex protocol where a methanol/DCM mix is used to delipidate the tissue, acetic acid to hydrolyze the ECM, guanidine + HCl to extract ECM proteoglycans and CHAPS+ N‐Methyl diethanolamine to further permeabilize the sample, aiming at achieving efficient staining of centimeters‐thick human brain tissue (Zhao et al, 2020). Immunohistochemistry (IHC) of whole mouse bodies requires a stronger approach or even the combination of all strategies. The whole‐body labeling and clearing technology vDISCO combine many of the permeabilization and labeling approaches by using a combination of amino alcohol, Triton X‐100, N‐acetyl‐l‐hydroxyproline, and methyl‐β‐cyclodextrin (a cholesterol extractor) to permeabilize the specimen. The technique also makes use of a high‐pressure perfusion system to actively push the reagents in all the tissues for an extensive labeling. In addition to combining these reagents, it uses nanobodies for labeling, as they present several advantages. Firstly, nanobody size is one‐tenth of that of an antibody, which allows better penetration in the tissues and consequently better labeling. Secondly, multiple nanobodies can bind to one epitope enabling a higher signal intensity. Finally, nanobodies can be used at near infrared spectra leading to a higher signal‐to‐noise ratio. This is due to the fact that most components that show autofluorescence are generally in shorter wavelengths, and therefore, the near infra‐red wavelengths used with nanobodies allow avoiding overlap with autofluorescence (Cai et al, 2019). Nevertheless, the application of nanobodies in IHC is still limited since nanobodies are mostly available only for genetically expressed fluorescent proteins. Labeling thick tissues requires dyes with a small molecule size, so that they are able to penetrate deep into the specimen. The small molecule dye propidium iodide (PI) can stain deep in both passive and active labeling and provides stable and strong nuclear labeling in all cell types. It is red‐fluorescent and can therefore be used in multichannel imaging, e.g., together with nanobodies conjugated with far‐red fluorophores. The UV spectrum of 4′,6‐Diamidino‐2‐Phenylindole (DAPI) or Hoechst has very limited light penetration that strongly decays in deeper parts of mammalian tissues. For that reason, they are rarely used for whole‐organ staining, although they are well suited for counterstaining tissue slices. Recommendations Permeabilization of large tissues is essential for IHC, since antibodies and high molecular weight dyes can only stain within a few hundred micrometers. Deeper labeling can be achieved either by nanobody labeling or increased antibody incubation time. Small micelle‐forming detergents (e.g., CHAPS) enable better permeabilization and therefore deeper labeling. Before starting the labeling of big tissues (e.g., whole organs), testing the antibodies and nanoboosters using small tissue samples to prototype (i.e., to test their efficiency and optimal concentration) is highly recommended. Using fluorescent probes with a longer wavelength can effectively defer scattering and allow deeper penetration. Therefore, near‐infrared probes are strongly recommended. As an optional step, users may consider making an incision with a sharp object on a less important site on the tissue to enhance the penetration of the soluble agents. This will improve and speed up the process. Tissue clearing After staining, the samples are ready to be cleared by several rounds of chemical treatment. The different step in this process essentially removes water and lipids from the tissue and homogenizes the RIs. Several approaches can be used for the dehydration step, each with its own advantages and disadvantages. Commonly used dehydrating agents are alcohols including ethanol in FluoClearBABB (Schwarz et al, 2015), methanol in iDISCO+ (Renier et al, 2016), and tert‐butanol in uDISCO (Pan et al, 2016). However, alcohols often result in poor endogenous signal preservation. THF is an alternative for dehydration and it has the same clearing performance as alcohols, but works better at preserving the endogenous signal. THF is commonly used in protocols such as 3DISCO (Ertürk et al, 2012a), vDISCO (Cai et al, 2019), FDISCO (Qi et al, 2019), and sDISCO (Hahn et al, 2019). In some of the protocols, an additional step with DCM treatment is performed for further delipidation and an enhanced clearing performance (Seo et al, 2016). Lastly for the RI‐matching step, although BABB is the most common solution used in many protocols, it can be replaced by a range of chemicals. For example, ECi (Henning et al, 2019) uses Ethyl cinnamate due to its lower toxicity. Alternatively, BABB can be replaced by DBE or a mixture of BABB with other reagents like in the uDISCO protocol (Pan et al, 2016) for better fluorescence signal preservation. When choosing the RI‐matching solution, it is important to consider its compatibility with the labeling probes, as well as the toxicity and corrosiveness of its chemical components. These are usually harsh chemicals that can melt the equipment being used and leave irreversible damage and they should therefore be handled with great care. Recommendations The duration of each incubation is highly flexible and depends on the size of the sample and its lipid content. The incubation steps can be prolonged to ensure complete delipidation. However, shortening is not advised. Since the organic solvents used can melt plastic, it is very important to test whether the plastic containers that are to be used are sufficiently resistant. In our experience, polypropylene‐based materials and all glassware withstand BABB well. Due to the toxic and corrosive nature of the many chemicals used in the clearing steps, minding the safety precautions during the use is strongly advised. Imaging cleared samples Several theoretical and practical considerations need to be made when imaging fixed, transparent tissue samples and taking advantage of the increased optical accessibility. Mainly three imaging approaches are used, partly depending on sample size: wide‐field fluorescence microscopy, point scanning fluorescence microscopy (PSFM), and light sheet fluorescent microscopy (LSFM). Wide‐field, epi‐illuminated fluorescence microscopes can be used for quality checking and imaging purposes if the components meet the excitation and emission criteria of the probes. Wide‐field microscopes allow cost‐effective and rapid imaging of cleared samples using a camera to capture the entire field of view (FOV), using long working distance objectives in a single run. However, these systems usually have basic‐sensitivity cameras and weak excitation efficiency and tend to bleach the fluorescent probes fast due to the wide‐field excitation. This deteriorates the overall image quality of millimeters‐thick samples by capturing excessive out‐of‐focus information. In our experience, these systems are very useful for basic documentation of staining efficacy and imaging supracellular moieties. PSFM such as conventional confocal or two‐photon microscopy can yield high‐resolution, optically sectioned images given an adequate selection of objectives for cleared samples. However, for cleared samples in mesoscopic scales, PSFM shows two limitations which greatly reduce its feasibility and throughput. The first one is that PSFM scans the excitation focus point by point across the whole field of view (FOV). When the FOV requires more than 10 million pixels, the scanning‐based mechanism makes the acquisition time for a single frame longer than 1s in a conventional confocal microscope, simply extending the process. The second limitation is that mesoscopic imaging requires low‐magnification objectives to achieve adequate throughput. Comparing to high magnification objectives, low‐magnification objectives have longer working distances as well as larger FOV. In principle, long working distance is indispensable for imaging in thick tissues, and a large FOV can effectively increase the throughput. However, low‐magnification objectives mostly have small numerical aperture (N.A.) due to the architecture of modern light microscopy. A smaller N.A. decreases the lateral resolution of the image linearly but the axial resolution quadratically, which renders an anisotropic resolution as well as an extended point spread function in the axial direction. In brief, PSFM is an ideal modality for high‐resolution imaging but only for a small FOV and thinner samples. Considering the constraints above for imaging a sample in a mesoscopic scale, LSFM emerges as an ideal solution for volumetric imaging of large cleared samples. A typical LSFM has at least two objectives with their optical axes perpendicular to each other. The detection objective is used for forming images on the 2D image sensor, which is usually a scientific complementary metal‐oxide‐semiconductor (CMOS) camera with high sensitivity and adequate cooling. The excitation objective (illumination objective/lens) is used to create a light sheet from a laser beam, where the plane of the light sheet locates on a conjugate plane of the camera sensor. The unique architecture of the LSFM dramatically improves the anisotropic resolution when using low‐magnification, low‐N.A. objectives (Olarte et al, 2018). The axial resolution in LSFM is determined by the thickness of the light sheet, which is governed by the optical properties of the excitation path and is not related to the N.A. of the imaging objective. Furthermore, the implementation of the camera as an imaging sensor also greatly enhances the imaging speed of LSFM compared with PSFM. The enhanced imaging speed is substantial for mesoscopic imaging. Theoretically, PSFM has unlimited pixel count whereas the imaging sensor in a camera has a fixed number and size of pixels and thus a fixed physical frame size. The frame size determines the size of the FOV and the number of pixels determines the sampling resolution it can achieve. Therefore, when imaging a sample with a size larger than the FOV, a motorized stage is indispensable in order to relocate the sample and manage to obtain image tiles for the whole sample. Modern LSFMs for imaging clearing tissues possess two opposing excitation optics. The architecture of the two‐sided illumination aims at compensating the scattering of the light sheet while traveling in a thicker sample from one side. Among the commercially available LSFM, LaVision Ultramicroscope Blaze III (Pan et al, 2016; Belle et al, 2017; Klingberg et al, 2017) offers a larger space as well as a motorized stage with a sufficiently long traveling distance for imaging large samples as whole mice or human organs. An alternative is MesoSPIM, an open‐source project for mesoscale LSFM that is also targeted toward imaging large samples such as a whole mouse (Voigt et al, 2019). MesoSPIM uses a digital‐scanning axially swept light sheet to achieve a homogeneous thickness of illumination virtually across the whole FOV and prevents artifacts from optical obstacles in the sample (Keller & Stelzer, 2010; Dean et al, 2015). Therefore, MesoSPIM promises a more homogeneous axial resolution as well as fewer artifacts compared with LSFM which uses cylindrical lenses to create light sheets such as the LaVision Ultramicroscope series. However, the horizontal layout of MesoSPIM makes the use of immersion objectives very complicated and is therefore currently not optimal for acquiring images with sub‐micron resolution. Irrespective of the chosen imaging approach, an adequate selection of objectives is essential to increase the imaging quality. The selection of objectives should be considered in two aspects, the first one being an appropriate magnification which matches its NA to the pixel size to fulfill the Nyquist sampling criterion. Specifically, the optical resolution is determined by the NA of the objective (Keller, 2006) and when two objects are within distances smaller than 0.61 × λ/NA (i.e., Rayleigh criterion), they cannot be identified
{'source': 'PubMedDataset'}