IDEAS home Printed from https://ideas.repec.org/a/nat/nature/v497y2013i7449d10.1038_nature12107.html
   My bibliography  Save this article

Structural and molecular interrogation of intact biological systems

Author

Listed:
  • Kwanghun Chung

    (Stanford University
    CNC Program, Stanford University)

  • Jenelle Wallace

    (Stanford University)

  • Sung-Yon Kim

    (Stanford University)

  • Sandhiya Kalyanasundaram

    (CNC Program, Stanford University)

  • Aaron S. Andalman

    (Stanford University
    CNC Program, Stanford University)

  • Thomas J. Davidson

    (Stanford University
    CNC Program, Stanford University)

  • Julie J. Mirzabekov

    (Stanford University)

  • Kelly A. Zalocusky

    (Stanford University
    CNC Program, Stanford University)

  • Joanna Mattis

    (Stanford University)

  • Aleksandra K. Denisin

    (Stanford University)

  • Sally Pak

    (Stanford University)

  • Hannah Bernstein

    (Stanford University)

  • Charu Ramakrishnan

    (Stanford University)

  • Logan Grosenick

    (Stanford University)

  • Viviana Gradinaru

    (CNC Program, Stanford University)

  • Karl Deisseroth

    (Stanford University
    CNC Program, Stanford University
    Stanford University
    Howard Hughes Medical Institute, Stanford University)

Abstract

Obtaining high-resolution information from a complex system, while maintaining the global perspective needed to understand system function, represents a key challenge in biology. Here we address this challenge with a method (termed CLARITY) for the transformation of intact tissue into a nanoporous hydrogel-hybridized form (crosslinked to a three-dimensional network of hydrophilic polymers) that is fully assembled but optically transparent and macromolecule-permeable. Using mouse brains, we show intact-tissue imaging of long-range projections, local circuit wiring, cellular relationships, subcellular structures, protein complexes, nucleic acids and neurotransmitters. CLARITY also enables intact-tissue in situ hybridization, immunohistochemistry with multiple rounds of staining and de-staining in non-sectioned tissue, and antibody labelling throughout the intact adult mouse brain. Finally, we show that CLARITY enables fine structural analysis of clinical samples, including non-sectioned human tissue from a neuropsychiatric-disease setting, establishing a path for the transmutation of human tissue into a stable, intact and accessible form suitable for probing structural and molecular underpinnings of physiological function and disease.

Suggested Citation

  • Kwanghun Chung & Jenelle Wallace & Sung-Yon Kim & Sandhiya Kalyanasundaram & Aaron S. Andalman & Thomas J. Davidson & Julie J. Mirzabekov & Kelly A. Zalocusky & Joanna Mattis & Aleksandra K. Denisin &, 2013. "Structural and molecular interrogation of intact biological systems," Nature, Nature, vol. 497(7449), pages 332-337, May.
  • Handle: RePEc:nat:nature:v:497:y:2013:i:7449:d:10.1038_nature12107
    DOI: 10.1038/nature12107
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/nature12107
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1038/nature12107?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jiayi Wang & Mengke Zhao & Meina Wang & Dong Fu & Lin Kang & Yu Xu & Liming Shen & Shilin Jin & Liang Wang & Jing Liu, 2024. "Human neural stem cell-derived artificial organelles to improve oxidative phosphorylation," Nature Communications, Nature, vol. 15(1), pages 1-24, December.
    2. Nikita Vladimirov & Fabian F. Voigt & Thomas Naert & Gabriela R. Araujo & Ruiyao Cai & Anna Maria Reuss & Shan Zhao & Patricia Schmid & Sven Hildebrand & Martina Schaettin & Dominik Groos & José María, 2024. "Benchtop mesoSPIM: a next-generation open-source light-sheet microscope for cleared samples," Nature Communications, Nature, vol. 15(1), pages 1-16, December.
    3. Kevin Yeh & Ishaan Sharma & Kianoush Falahkheirkhah & Matthew P. Confer & Andres C. Orr & Yen-Ting Liu & Yamuna Phal & Ruo-Jing Ho & Manu Mehta & Ankita Bhargava & Wenyan Mei & Georgina Cheng & John C, 2023. "Infrared spectroscopic laser scanning confocal microscopy for whole-slide chemical imaging," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    4. Daniel P Riordan & Sushama Varma & Robert B West & Patrick O Brown, 2015. "Automated Analysis and Classification of Histological Tissue Features by Multi-Dimensional Microscopic Molecular Profiling," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-18, July.
    5. Adam L Tyson & Charly V Rousseau & Christian J Niedworok & Sepiedeh Keshavarzi & Chryssanthi Tsitoura & Lee Cossell & Molly Strom & Troy W Margrie, 2021. "A deep learning algorithm for 3D cell detection in whole mouse brain image datasets," PLOS Computational Biology, Public Library of Science, vol. 17(5), pages 1-17, May.
    6. Hyoungjun Park & Myeongsu Na & Bumju Kim & Soohyun Park & Ki Hean Kim & Sunghoe Chang & Jong Chul Ye, 2022. "Deep learning enables reference-free isotropic super-resolution for volumetric fluorescence microscopy," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    7. Dheeraj S. Roy & Young-Gyun Park & Minyoung E. Kim & Ying Zhang & Sachie K. Ogawa & Nicholas DiNapoli & Xinyi Gu & Jae H. Cho & Heejin Choi & Lee Kamentsky & Jared Martin & Olivia Mosto & Tomomi Aida , 2022. "Brain-wide mapping reveals that engrams for a single memory are distributed across multiple brain regions," Nature Communications, Nature, vol. 13(1), pages 1-16, December.
    8. Kohei Otomo & Takaki Omura & Yuki Nozawa & Steven J. Edwards & Yukihiko Sato & Yuri Saito & Shigehiro Yagishita & Hitoshi Uchida & Yuki Watakabe & Kiyotada Naitou & Rin Yanai & Naruhiko Sahara & Satos, 2024. "descSPIM: an affordable and easy-to-build light-sheet microscope optimized for tissue clearing techniques," Nature Communications, Nature, vol. 15(1), pages 1-19, December.
    9. Junyoung Seo & Yeonbo Sim & Jeewon Kim & Hyunwoo Kim & In Cho & Hoyeon Nam & Young-Gyu Yoon & Jae-Byum Chang, 2022. "PICASSO allows ultra-multiplexed fluorescence imaging of spatially overlapping proteins without reference spectra measurements," Nature Communications, Nature, vol. 13(1), pages 1-17, December.
    10. Daniel Soudry & Suraj Keshri & Patrick Stinson & Min-hwan Oh & Garud Iyengar & Liam Paninski, 2015. "Efficient "Shotgun" Inference of Neural Connectivity from Highly Sub-sampled Activity Data," PLOS Computational Biology, Public Library of Science, vol. 11(10), pages 1-30, October.
    11. Fu-Ting Hsiao & Hung-Jen Chien & Ya-Hsien Chou & Shih-Jung Peng & Mei-Hsin Chung & Tzu-Hui Huang & Li-Wen Lo & Chia-Ning Shen & Hsiu-Pi Chang & Chih-Yuan Lee & Chien-Chia Chen & Yung-Ming Jeng & Yu-We, 2023. "Transparent tissue in solid state for solvent-free and antifade 3D imaging," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    12. Santiago Mañosas & Aritz Sanz & Cristina Ederra & Ainhoa Urbiola & Elvira Rojas-de-Miguel & Ainhoa Ostiz & Iván Cortés-Domínguez & Natalia Ramírez & Carlos Ortíz-de-Solórzano & Arantxa Villanueva & Ma, 2022. "An Image-Based Framework for the Analysis of the Murine Microvasculature: From Tissue Clarification to Computational Hemodynamics," Mathematics, MDPI, vol. 10(23), pages 1-20, December.
    13. Jingtan Zhu & Xiaomei Liu & Zhang Liu & Yating Deng & Jianyi Xu & Kunxing Liu & Ruiying Zhang & Xizhi Meng & Peng Fei & Tingting Yu & Dan Zhu, 2024. "SOLID: minimizing tissue distortion for brain-wide profiling of diverse architectures," Nature Communications, Nature, vol. 15(1), pages 1-17, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:nature:v:497:y:2013:i:7449:d:10.1038_nature12107. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.