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Rapid adaptive optical recovery of optimal resolution over large volumes

Nature Methods volume 11, pages 625–628 (2014)Cite this article

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Abstract

Using a descanned, laser-induced guide star and direct wavefront sensing, we demonstrate adaptive correction of complex optical aberrations at high numerical aperture (NA) and a 14-ms update rate. This correction permits us to compensate for the rapid spatial variation in aberration often encountered in biological specimens and to recover diffraction-limited imaging over large volumes (>240 mm per side). We applied this to image fine neuronal processes and subcellular dynamics within the zebrafish brain.

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Figure 1: AO over a large volume in the living zebrafish brain.
Figure 2: Spatial variability of aberrations across the living zebrafish brain.
Figure 3: Two-color confocal imaging with AO provided by a descanned two-photon guide star deep in the living zebrafish brain.

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Acknowledgements

We thank our colleagues N. Ji for many fruitful technical discussions and suggestion of the zebrafish system; P. Keller for the HRAS transgenic line; C. Yang, S. Narayan, M.B. Ahrens, M. Koyama, B. Lemon, K. McDole and P. Keller for further guidance on zebrafish biology; J. Cox, M. Rose, A. Luck and J. Barber for zebrafish maintenance and breeding; and R. Kloss, B. Biddle and B. Bowers for machining services. We are grateful to R. Köster (Technical University of Braunschweig) for providing the KalTA4 transactivator and X. Xie (Georgia Regents University) for assistance in generating corresponding transgenic Enhancer Trap lines. We also thank R. Kelsh (University of Bath) for the Sox10:eGFP line and U. Strahle (Karlsruhe Institute of Technology) for the Ngn:nRFP line. J.S.M. is supported by US National Institutes of Health (NIH) grants R21 MH083614 (NIMH) and R43 HD047089 (NICHD). M.E.B. is supported by NIH grant DE16459. T.M. acknowledges the financial support of the Center for Integrated Protein Sciences (EXC114 CIPSM) and of the Munich Cluster for Systems Neurology (EXC1010 SyNergy). P.E. was supported by DFG Research Training Group 1373. A.S. and P.E. acknowledge support from the Howard Hughes Medical Institute Janelia Farm visiting scientist program.

Author information

Author notes

  1. Jeff Mumm

    Present address: Present address: Wilmer Eye Institute, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.,

Authors and Affiliations

  1. Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, USA

    Kai Wang, Eric Betzig & Eric Betzig

  2. Coleman Technologies, Inc., Newtown Square, Pennsylvania, USA

    Daniel E Milkie

  3. Division of Biology, California Institute of Technology, Pasadena, California, USA

    Ankur Saxena & Marianne E Bronner

  4. Institute of Neuronal Cell Biology, Technische Universität München, Munich, Germany

    Peter Engerer & Thomas Misgeld

  5. Munich Center for Systems Neurology, Munich, Germany

    Thomas Misgeld

  6. German Center for Neurodegenerative Diseases, Munich, Germany

    Thomas Misgeld

  7. Department of Cellular Biology and Anatomy, Georgia Regents University, Augusta, Georgia, USA

    Jeff Mumm

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  1. Kai Wang
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Contributions

E.B. supervised the project; K.W. and E.B. conceived the idea; D.E.M., K.W. and E.B. developed the instrument control program; K.W. built the instrument and performed the experiments; A.S., P.E., T.M., M.E.B. and J.M. supplied zebrafish lines and guidance on live zebrafish imaging; K.W. and E.B. analyzed the data; E.B. wrote the paper with input from all co-authors.

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Correspondence to Eric Betzig.

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The authors declare no competing financial interests.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–9 and Supplementary Tables 1 and 2 (PDF 3774 kb)

Adaptive optics (AO) over a large volume in the living zebrafish brain

Two photon 3D image of a membrane-labeled subset of neurons in the brain of a living zebrafish embryo, 72 hours post fertilization. This 240 x 240 x 270 μm3 imaging volume consists of 19,584 corrective subvolumes, each 30 x 30 x 1.05 μm3 in extent. Zooming deep in the mid-brain, the individual neuronal processes, unresolved without AO, become distinct after correction. (MOV 49041 kb)

Time–lapse imaging of oligodendrocyte migration in the developing zebrafish hindbrain

Two-photon time lapse imaging of the neurite-guided oligodendrocyte migration deep in the zebrafish hindbrain with adaptive optical correction. All frames are MIPs over a 170 x 90 x 60 μm volume taken at 4 minute intervals with AO and deconvolution in the two-photon mode, starting ∼72 hours post-fertilization. (MOV 3951 kb)

Spatial variability of aberrations across the living zebrafish brain

Comparative two-photon imaging of a living zebrafish brain, ∼72 hours post-fertilization, with a ubiquitously expressed cell membrane marker at a depth of 150 μm. Left panel: no AO; middle panel: with AO; right panel: local wavefront error. (MOV 27099 kb)

Two–color confocal imaging with AO deep in the living zebrafish brain

Two–color, 3D confocal images of oligodendrocytes and neuronal nuclei over a 40 x 40 x 200 μm3 volume extending from the optic tectum through the midbrain, in a zebrafish 72 hours post fertilization. AO correction was performed using a de-scanned two-photon guide star in each of 40 x 40 x 9 μm3 corrective sub-volumes before confocal imaging. (MOV 24581 kb)

Two–color subcellular confocal imaging with AO deep in the zebrafish brain

Two–color, 3D confocal images of mitochondria (magenta) and the plasma membrane (green) of a cell ∼150 μm deep in the hindbrain of a zebrafish, 4 days post fertilization. The imaging volume is 25 x 25 x 15 μm3. (MOV 10896 kb)

Time–lapse imaging of axonal trafficking of mitochondria 150 μm deep in the zebrafish brain

Time lapse imaging of axonal trafficking of mitochondria 150 μm deep in the zebrafish brain, 4 days post fertilization, over a 20 x 40 x 18 μm3 imaging volume at 2 minute intervals. (MOV 8122 kb)

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Wang, K., Milkie, D., Saxena, A. et al. Rapid adaptive optical recovery of optimal resolution over large volumes. Nat Methods 11, 625–628 (2014). https://doi.org/10.1038/nmeth.2925

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