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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
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    Cited by:

    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.

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