A guidebook for DISCO tissue clearing
Open accessAbstract
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.
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Advanced tissue-clearing methods combined with fluorescence microscopy have enabled the visualization of large samples, including entire mouse bodies and big human tissue specimens at the single-cell resolution.
“Advanced tissue-clearing methods combined with fluorescence microscopy have enabled the visualization of large samples, including entire mouse bodies and big human tissue specimens at the single-cell resolution1–5.”
From A deep-learning framework reveals whole-body perturbations at cell level (2026) · cites this paper as [1]
Many diseases, including obesity, have systemic effects that perturb multiple organ systems throughout the body.
“Many diseases, including obesity, have systemic effects that perturb multiple organ systems throughout the body1,2.”
From A deep-learning framework reveals whole-body perturbations at cell level (2026) · cites this paper as [1]
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References 110 · Cited by 96
- Authors
- Molbay, M., Kolabas, Z. I., Todorov, M. I., Ohn, T., & Ertürk, A.
- Affiliations
- Helmholtz Munich (DE)
- Corresponding author
- Ertürk, Ali
- Venue
- Molecular Systems Biology
- Published
- 2021-03-01
- Volume
- 17
- Issue
- 3
- Pages
- e9807-e9807
- ISSN
- 1744-4292 (ISSN-L)
- PMC
- PMC7995442
- OpenAlex
- W3137590718
- Cited by
- 96
- References
- 110
- Citations by year
- 2026: 17 · 2025: 9 · 2024: 22 · 2023: 20 · 2022: 17 · 2021: 11
- FWCI
- 2.36
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Molecular Systems Biology (publishedVersion, other-oa)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Open access LMU (Ludwid Maxmilian's Universitat Munchen) (submittedVersion, cc-by)
- Site cant be reached (submittedVersion, cc-by)
- PuSH - Publication Server of Helmholtz Zentrum München (submittedVersion, cc-by)
- Funders
- Munich Cluster for Systems Neurology (390857198)
- ERA‐Net Neuron (01EW1501A)
- Fritz Thyssen Stiftung (10.17.1.019MN)
- Deutsche Forschungsgemeinschaft (ER 810/2‐1)
- Helmholtz ICEMED Alliance
- NIH (AG057575)
- TRABIT (765148)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Biophysics › Advanced Fluorescence Microscopy Techniques
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Biophysics › Cell Image Analysis Techniques
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Keywords
- tissue clearing, disco, tissue transparency
- MeSH terms
- Animals, Decision Trees, Humans, Organ Specificity, Solvents, Staining and Labeling, Optics and Photonics
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