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A practical guide to scanning light-field microscopy with digital adaptive optics

Nature Protocols volume 17, pages 1953–1979 (2022)Cite this article

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Abstract

With the development of a wide variety of animal models in recent years, there is a rapidly growing demand for long-term, high-speed intravital fluorescence imaging to observe intercellular and intracellular interactions in their native states. Scanning light-field microscopy (sLFM) with digital adaptive optics provides a compact computational solution by imaging the entire volume in a tomographic way with orders-of-magnitude improvement in spatiotemporal resolution and reduction in phototoxicity, as compared to traditional intravital microscopy. Here, we present a step-by-step protocol for both hardware and software implementation of multicolor sLFM as an add-on to a normal wide-field fluorescence microscope by using off-the-shelf lenses and devices at low cost. The procedure can be easily applied to other LFM variants, which can be advantageous in certain experimental contexts. Owing to the strong reliance of sLFM on algorithmic post-processing for high-quality data, the protocol describes various kinds of artefacts and corresponding parameters used for correcting and performance optimization. To increase the tolerance to system misalignment and differences in device fabrication, we describe a one-step calibration method for robust imaging performance up to the diffraction limit. An open-source graphical user interface is presented for hardware synchronization and real-time rendering of multiview images. The whole procedure including optical setup, software installation, system calibration and 3D reconstruction can be executed in 3–4 d with basic knowledge in optics and electronics.

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Fig. 1: Overview of the DAOSLIMIT workflow.
Fig. 2: Schematic illustrations of DAOSLIMIT.
Fig. 3: Examples of common DAOSLIMIT artefacts.
Fig. 4: GUI software sLFdriver for data acquisition.
Fig. 5: Illustrations of the artefacts caused by NA mismatch between the objective lens and MLA.
Fig. 6: Artefacts caused by inaccurate magnification of the relay system between the MLA and the camera.
Fig. 7: The influence of inaccurate scanning amplitudes.
Fig. 8: Representative data from DAOSLIMIT experiments.

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Data availability

The data supporting this study are available within the article, the Supplementary Information and the primary supporting study6. All data mentioned in the protocol are available in Supplementary Software.

Code availability

The Zemax source files and all code and software used in the protocol are available in Supplementary Software. We have also uploaded the code on GitHub (https://github.com/THU-IBCS/DAOSLIMIT_Protocol), which can be updated in the future with more functions.

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Acknowledgements

We thank D. Jiang and L. Yu for their assistance in sample preparation. We thank T. Zhu and T. Yan for insightful discussions. This work was supported by the National Natural Science Foundation of China (62088102 and 62071272) and the National Key Research and Development Program of China (2020AA0105500 and 2020AAA0130000). We further acknowledge support from the Beijing Laboratory of Brain and Cognitive Intelligence, the Beijing Municipal Education Commission and the Beijing Key Laboratory of Multi-dimension & Multi-scale Computational Photography (MMCP).

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Authors and Affiliations

  1. Department of Automation, Tsinghua University, Beijing, China

    Zhi Lu, Yeyi Cai, Yixin Nie, Yuxin Yang, Jiamin Wu & Qionghai Dai

  2. Institute for Brain and Cognitive Sciences, Tsinghua University, Beijing, China

    Zhi Lu, Yeyi Cai, Yixin Nie, Yuxin Yang, Jiamin Wu & Qionghai Dai

  3. IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing, China

    Qionghai Dai

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Contributions

Q.D., J.W. and Z.L. conceived the project. Z.L. and J.W. designed the whole pipeline. Z.L. and Y.C. conducted numerical simulations and biological experiments. Z.L. and Y.N. worked on data processing. J.W., Z.L. and Y.N. designed the Zemax and CAD prescriptions. Z.L. and Y.Y. prepared the acquisition and other pre-processing code for the protocol. Z.L, Y.C., J.W. and Q.D. wrote the manuscript.

Corresponding authors

Correspondence to Jiamin Wu or Qionghai Dai.

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Competing interests

Q.D. and J.W. are co-founders and equity holders of Zhejiang Hehu Technology LLC, where the DAOSLIMIT technology is commercialized. Q.D., J.W. and Z.L. have patents related to the DAOSLIMIT technology (US Patent, no. 11,131,841).

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Nature Protocols thanks Robert Prevedel and Yicong Wu for their contribution to the peer review of this work.

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Related links

Key references using this protocol

Wu, J. et al. Cell 184, 3318–3332.e17 (2021): https://doi.org/10.1016/j.cell.2021.04.029

Zhang, Y. et al. Nat. Commun. 12, 6391 (2021): https://doi.org/10.1038/s41467-021-26730-w

Zhang, Y. et al. Light Sci. Appl. 10, 152 (2021): https://doi.org/10.1038/s41377-021-00587-6

Supplementary information

Supplementary Information

Supplementary Figs. 1–7, Supplementary Methods and Supplementary Manuals 1 and 2.

Reporting Summary

Supplementary Software

The DAOSLIMIT software package contains the GUIs, related codes, reconstruction codes, Zemax files and example raw data.

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Cite this article

Lu, Z., Cai, Y., Nie, Y. et al. A practical guide to scanning light-field microscopy with digital adaptive optics. Nat Protoc 17, 1953–1979 (2022). https://doi.org/10.1038/s41596-022-00703-9

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