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Super-resolution upgrade for deep tissue imaging featuring simple implementation

Author

Listed:
  • Patrick Byers

    (Munich University of Applied Sciences
    Bielefeld University)

  • Thomas Kellerer

    (Munich University of Applied Sciences)

  • Miaomiao Li

    (Technical University Munich
    Deutsches Zentrum für Herz- und Kreislaufforschung (DZHK), partner site Munich Heart Alliance (MHA))

  • Zhifen Chen

    (Technical University Munich
    Deutsches Zentrum für Herz- und Kreislaufforschung (DZHK), partner site Munich Heart Alliance (MHA))

  • Thomas Huser

    (Bielefeld University)

  • Thomas Hellerer

    (Munich University of Applied Sciences)

Abstract

Deep tissue imaging with high contrast close to or even below the optical resolution limit is still challenging due to optical aberrations and scattering introduced by dense biological samples. This results in high complexity and cost of microscopes that can facilitate such challenges. Here, we demonstrate a cost-effective and simple to implement method to turn most two-photon laser-scanning microscopes into a super-resolution microscope for deep tissue imaging. We realize this by adding inexpensive optical devices, namely a cylindrical lens, a field rotator, and a sCMOS camera to these systems. By combining two-photon excitation with patterned line-scanning and subsequent image reconstruction, we achieve imaging of sub-cellular structures in Pinus radiata, mouse heart muscle and zebrafish. In addition, the penetration depth of super-resolved imaging in highly scattering tissue is considerably extended by using the camera’s lightsheet shutter mode. The flexibility of our method allows the examination of a variety of thick samples with a variety of fluorescent markers and microscope objective lenses. Thus, with a cost-efficient modification of a multi-photon microscope, an up to twofold resolution enhancement is demonstrated down to at least 70μm deep in tissue.

Suggested Citation

  • Patrick Byers & Thomas Kellerer & Miaomiao Li & Zhifen Chen & Thomas Huser & Thomas Hellerer, 2025. "Super-resolution upgrade for deep tissue imaging featuring simple implementation," Nature Communications, Nature, vol. 16(1), pages 1-12, December.
    • Handle: RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-60744-y
    DOI: 10.1038/s41467-025-60744-y
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    References listed on IDEAS

    as
    1. Yicong Wu & Xiaofei Han & Yijun Su & Melissa Glidewell & Jonathan S. Daniels & Jiamin Liu & Titas Sengupta & Ivan Rey-Suarez & Robert Fischer & Akshay Patel & Christian Combs & Junhui Sun & Xufeng Wu , 2021. "Multiview confocal super-resolution microscopy," Nature, Nature, vol. 600(7888), pages 279-284, December.
    2. Ruizhe Lin & Edward T. Kipreos & Jie Zhu & Chang Hyun Khang & Peter Kner, 2021. "Subcellular three-dimensional imaging deep through multicellular thick samples by structured illumination microscopy and adaptive optics," Nature Communications, Nature, vol. 12(1), pages 1-14, December.
    3. Florian Schueder & Juanita Lara-Gutiérrez & Brian J. Beliveau & Sinem K. Saka & Hiroshi M. Sasaki & Johannes B. Woehrstein & Maximilian T. Strauss & Heinrich Grabmayr & Peng Yin & Ralf Jungmann, 2017. "Multiplexed 3D super-resolution imaging of whole cells using spinning disk confocal microscopy and DNA-PAINT," Nature Communications, Nature, vol. 8(1), pages 1-9, December.
    4. Andreas Markwirth & Mario Lachetta & Viola Mönkemöller & Rainer Heintzmann & Wolfgang Hübner & Thomas Huser & Marcel Müller, 2019. "Video-rate multi-color structured illumination microscopy with simultaneous real-time reconstruction," Nature Communications, Nature, vol. 10(1), pages 1-11, December.
    5. Marcel Müller & Viola Mönkemöller & Simon Hennig & Wolfgang Hübner & Thomas Huser, 2016. "Open-source image reconstruction of super-resolution structured illumination microscopy data in ImageJ," Nature Communications, Nature, vol. 7(1), pages 1-6, April.
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