An adaptive microscope for the imaging of biological surfaces

Faris Abouakil; Huicheng Meng; Marie-Anne Burcklen; Hervé Rigneault; Frédéric Galland; Loïc LeGoff

doi:10.1038/s41377-021-00649-9

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An adaptive microscope for the imaging of biological surfaces

Articles

- An adaptive microscope for the imaging of biological surfaces
- An adaptive microscope for the imaging of biological surfaces
- LSA 2021年10卷第11期页码：2195-2206
- Affiliations：
  
  Aix Marseille Univ, CNRS, Centrale Marseille, Institut Fresnel, Turing Center for Living Systems, Marseille, France
- Author bio：
  
  Frédéric Galland (frederic.galland@fresnel.fr)
  Loïc. LeGoff (loic.le-goff@univ-amu.fr)
- Funds：
- DOI：10.1038/s41377-021-00649-9
  中图分类号：
- 纸质出版日期：2021-11-30，
  
  网络出版日期：2021-10-07，
  
  收稿日期：2021-04-12，
  
  修回日期：2021-09-04，
  
  录用日期：2021-09-20
- Accepted：
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An adaptive microscope for the imaging of biological surfaces[J]. LSA, 2021,10(11):2195-2206.

Abouakil, F. et al. An adaptive microscope for the imaging of biological surfaces. Light: Science & Applications, 10, 2195-2206 (2021).
An adaptive microscope for the imaging of biological surfaces[J]. LSA, 2021,10(11):2195-2206. DOI： 10.1038/s41377-021-00649-9.

Abouakil, F. et al. An adaptive microscope for the imaging of biological surfaces. Light: Science & Applications, 10, 2195-2206 (2021). DOI： 10.1038/s41377-021-00649-9.

摘要

Abstract

Scanning fluorescence microscopes are now able to image large biological samples at high spatial and temporal resolution. This comes at the expense of an increased light dose which is detrimental to fluorophore stability and cell physiology. To highly reduce the light dose

we designed an adaptive scanning fluorescence microscope with a scanning scheme optimized for the unsupervised imaging of cell sheets

which underly the shape of many embryos and organs. The surface of the tissue is first delineated from the acquisition of a very small subset (~0.1%) of sample space

using a robust estimation strategy. Two alternative scanning strategies are then proposed to image the tissue with an improved photon budget

without loss in resolution. The first strategy consists in scanning only a thin shell around the estimated surface of interest

allowing high reduction of light dose when the tissue is curved. The second strategy applies when structures of interest lie at the cell periphery (e.g. adherens junctions). An iterative approach is then used to propagate scanning along cell contours. We demonstrate the benefit of our approach imaging live epithelia from Drosophila melanogaster. On the examples shown

both approaches yield more than a 20-fold reduction in light dose -and up to more than 80-fold- compared to a full scan of the volume. These smart-scanning strategies can be easily implemented on most scanning fluorescent imaging modality. The dramatic reduction in light exposure of the sample should allow prolonged imaging of the live processes under investigation.

关键词

Keywords

references

Cutrale, F., Fraser, S. E.&Trinh, L. A. Imaging, visualization, and computation in developmental biology.Annu. Rev. Biomed. Data Sci.2, 223–251 (2019)..

Gao, R. X. et al. Cortical column and whole-brain imaging with molecular contrast and nanoscale resolution.Science363, eaau8302 (2019)..

Mertz, J.Introduction to optical microscopy. 2nd edn.(Cambridge University Press, Cambridge, 2019).

Mertz, J. Optical sectioning microscopy with planar or structured illumination.Nat. Methods8, 811–819 (2011)..

Carlton, P. M. et al. Fast live simultaneous multiwavelength four-dimensional optical microscopy.Proc. Natl Acad. Sci. USA107, 16016–16022 (2010)..

Hoebe, R. A. et al. Controlled light-exposure microscopy reduces photobleaching and phototoxicity in fluorescence live-cell imaging.Nat. Biotechnol.25, 249–253 (2007)..

Chu, K. K., Lim, D.&Mertz, J. Enhanced weak-signal sensitivity in two-photon microscopy by adaptive illumination.Opt. Lett.32, 2846–2848 (2007)..

Staudt, T. et al. Far-field optical nanoscopy with reduced number of state transition cycles.Opt. Express19, 5644–5657 (2011)..

Dreier, J. et al. Smart scanning for low-illumination and fast RESOLFT nanoscopy in vivo.Nat. Commun.10, 1–11 (2019)..

Vinçon, B., Geisler, C.&Egner, A. Pixel hopping enables fast STED nanoscopy at low light dose.Opt. Express28, 4516–4528 (2020)..

Caarls, W. et al. Minimizing light exposure with the programmable array microscope.J. Microsc.241, 101–110 (2011)..

Chakrova, N. et al. Adaptive illumination reduces photobleaching in structured illumination microscopy.Biomed. Opt. Express7, 4263–4274 (2016)..

Guillot, C.&Lecuit, T. Mechanics of epithelial tissue homeostasis and morphogenesis.Science340, 1185–1189 (2013)..

LeGoff, L., Rouault, H.&Lecuit, T. A global pattern of mechanical stress polarizes cell divisions and cell shape in the growingDrosophilawing disc.Development140, 4051–4059 (2013)..

Heemskerk, I.&Streichan, S. J. Tissue cartography: compressing bio-image data by dimensional reduction.Nat. Methods12, 1139–1142 (2015)..

Heemskerk, I., Lecuit, T.&LeGoff, L. Dynamic clonal analysis based on chronic in vivo imaging allows multiscale quantification of growth in theDrosophilawing disc.Development141, 2339–2348 (2014)..

Heller, D. et al. Epitools: an open-source image analysis toolkit for quantifying epithelial growth dynamics.Dev. Cell36, 103–116 (2016)..

de Reuille, P. B. et al. Morphographx: A platform for quantifying morphogenesis in 4D.eLife4, e05864 (2015)..

Goldenberg, G.&Harris, T. J. C. Adherens junction distribution mechanisms during cell-cell contact elongation inDrosophila.PLoS ONE8, e79613 (2013)..

Supatto, W. et al. In vivo modulation of morphogenetic movements inDrosophilaembryos with femtosecond laser pulses.Proc. Natl Acad. Sci. USA102, 1047–1052 (2005)..

Koester, H. J. et al. Ca2+fluorescence imaging with pico-and femtosecond two-photon excitation: signal and photodamage.Biophys. J.77, 2226–2236 (1999)..

Hopt, A.&Neher, E. Highly nonlinear photodamage in two-photon fluorescence microscopy.Biophys. J.80, 2029–2036 (2001)..

Schmidt, E.&Oheim, M. Infrared excitation induces heating and calcium microdomain hyperactivity in cortical astrocytes.Biophys. J.119, 2153–2165 (2020)..

Godaliyadda, G. M. et al. A framework for dynamic image sampling based on supervised learning.IEEE Trans. Comput. Imaging4, 1–16 (2018)..

Hujsak, K.A. et al. High speed/low dose analytical electron microscopy with dynamic sampling.Micron108, 31–40 (2018)..

Scherf, N.&Huisken, J. The smart and gentle microscope.Nat. Biotechnol.33, 815–818 (2015)..

Strobl, F., Schmitz, A.&Stelzer, E. H. K. Improving your four-dimensional image: traveling through a decade of light-sheet-based fluorescence microscopy research.Nat. Protoc.12, 1103–1109 (2017)..

Débarre, D. et al. Mitigating phototoxicity during multiphoton microscopy of liveDrosophilaembryos in the 1.0–1.2 μm wavelength range.PLoS ONE9, e104250 (2014)..

Weigert, M. et al. Content-aware image restoration: pushing the limits of fluorescence microscopy.Nat. Methods15, 1090–1097 (2018)..

Xiao, S. et al. Video-rate volumetric neuronal imaging using 3d targeted illumination.Sci. Rep.8, 7921 (2018)..

Müller, C. B.&Enderlein, J. Image scanning microscopy.Phys. Rev. Lett.104, 198101 (2010)..

York, A. G. et al. Resolution doubling in live, multicellular organisms via multifocal structured illumination microscopy.Nat. Methods9, 749–754 (2012)..

Wu, J. J. et al. Resolution improvement of multifocal structured illumination microscopy with sparse bayesian learning algorithm.Opt. Exp.26, 31430–31438 (2018)..

Chakrova, N., Rieger, B.&Stallinga, S. Development of a DMD-based fluorescence microscope. Proceedings of SPIE 9330, Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing XXII. San Francisco: SPIE, 2015, 933008.

Garthwaite, P. H., Jolliffe, I. T., Jolliffe, I.&Jones, B.Statistical inference. 2nd edn.(University Press on Demand, Oxford, 2002).

Fischler, M. A.&Bolles, R. C. Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography.Commun. ACM24, 381–395 (1981)..

Sandwell, D. T. Biharmonic spline interpolation of geos-3 and seasat altimeter data.Geophys. Res. Lett.14, 139–142 (1987)..

Huang, J. et al. Directed, efficient, and versatile modifications of theDrosophilagenome by genomic engineering.Proc. Natl Acad. Sci. USA106, 8284–8289 (2009)..

Beira, J. V.&Paro, R. The legacy ofDrosophilaimaginal discs.Chromosoma125, 573–592 (2016)..

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