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Enabling Structured Illumination Microscopy in Thick Tissue with
Adaptive Optics October 23rd , 2013
Peter Kner
College of Engineering
University of Georgia
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Introduction
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Kner P, Chhun BB, Griffis ER, Winoto L, Gustafsson MG (2009) Super-resolution video microscopy of live cells by structured illumination. Nat Methods 6: 339-342
Widefield Fluorescence image of microtubules in Drosophila S2 Cells Resolution ~250 nm
Structured Illumination image Resolution ~100 nm
Drosophila melanogaster
Caenorhabditis elegans
Imaging point sources in the fly
Imaging point sources underneath the worm
Before correction After correction
The Point Spread Function and the Optical Transfer Function
Back Pupil Plane Point Spread Function Optical Transfer Function
Extent NA/λ Extent 1.22 λ/NA Extent 2NA/λ
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Two fluorophores:
180nm apart 50nm apart
Adding Aberrations
Back Pupil Plane Point Spread Function Optical Transfer Function
Extent NA/λ Extent 1.22 λ/NA Extent 2NA/λ
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Astronomical Adaptive Optics
Lick Observatory 1m telescope
AO off Long exposure
AO off short exposure
AO on
Claire Max UC Santa Cruz
Neptune in Infrared Light
Without adaptive optics With Keck adaptive optics
June 27, 1999
2.3
arc
se
c
May 24, 1999
l = 1.65 microns
NSF Center for Adaptive Optics at UC Santa Cruz
Adaptive Optics in Microscopy
• In biology there are no natural guide stars
• Most approaches have done away with measuring the wavefront altogether and use search algorithms to optimize the wavefront.
Take Image Calculate
Metric Evaluate Metric
Change Mirror Shape
Search wavefront space
Done
D. Débarre, E. J. Botcherby, M. J. Booth et al., “Adaptive optics for structured illumination microscopy,” Opt. Express, 16(13), 9290-9305 (2008). 8
Metrics
• Peak Signal
• Integrated Signal
• Image sharpness
• Fourier component
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Modal Optimization
• For small aberrations, we can expand the intensity in terms of the Zernike coefficients
𝑎𝐶 =𝑏(𝑔+ − 𝑔−)
2𝑔+ − 4𝑔0 + 2𝑔−
M. J. Booth, "Wavefront sensorless adaptive optics for large aberrations," Opt Lett 32, 5-7 (2007) 11
Optimization • N+1 Measurements can be used to optimize N orthogonal modes of the wavefront
– M. J. Booth, "Wave front sensor-less adaptive optics: a model-based approach using sphere packings," Optics Express 14, 1339-1352 (2006).
• Zernike Modes: aberration max ~ 0.5 waves
• Lukosz Modes: aberration max ~ 5 waves
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Aberrations
sign
al
Phase Retrieval
R. W. Gerchberg and W. O. Saxton, A practical algorithm for the determination of phase from image diffraction plane pictures, Optik (Stuttgart) 35, pp. 237-246 (1972) B. M. Hanser, M. G. Gustafsson, D. A. Agard, and J. W. Sedat, Phase Retrieval for high-numerical aperture optical systems, Optics Letters 28, pp. 801-3 (2003) R. W. Deming, Phase Retrieval from intensity-only data by relative entropy minimization, J. Opt. Soc. Am. A 24, pp. 3666-3678 (2007)
+4 microns
-90 deg to 90 deg
-4 microns
Phase
dkikxzkikAU )exp())(exp()(
dxikxzkizxUI
IA
A
m )exp())(exp(),(
Amplitude
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Phase Retrieval
• 21 slices, Δz = 0.2 microns • Actuator print-through is evident • Number of cycles
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Actuator 21 Actuator 22
Actuator 24
Wavefront Reconstruction
Correction by Phase Retrieval
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Results • After 3 iterations, >10 fold increase in peak intensity • increase in Strehl ratio to 0.76 • Point Spread Function full-width half maximum is 20% greater than theoretical value for 1.285NA
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Kner P, Winoto L, Agard DA, Sedat JW. Closed loop adaptive optics for microscopy without a wavefront sensor. In: Conchello J-A, Cogswell CJ, Wilson T, Brown TG, editors. Proc. SPIE; 2010; San Francisco, California, USA. SPIE. pp. 757006-757009
Structured Illumination Microscopy: Moire Fringes
• Moire fringes can be resolvable even if unknown pattern is not
Unknown
Pattern
Known
Pattern
Gustafsson MG (2000) Surpassing the lateral resolution limit by a factor of two using structured illumination microscopy. J Microsc 198: 82-87
Structured Illumination Microscopy • Structured illumination consists of 3 overlapping terms in frequency
space
pattern sample Otf/psf
Copies of the sample FT are shifted
Each term individually
Putting it all together:
Information is mixed together
New high frequency information
Structured Illumination Microscopy
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112
111
3 Phases of Patterned excitation light
2NA/l
3 images with 3 different phases of pattern:
Image 1
Image 2
Image 3
DC Term
Real Term
Imaginary Term
Assembly: 4NA/l
Structured Illumination Microscopy
4NA/l
Structured Illumination Example
• 100nm fluorescent beads
Conventional 2D Image SI 2D Image Fourier Transform
A total of 9 raw images are required for one super-resolution image
3D Structured Illumination
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3D Structured Illumination Microtubules in HeLa Cells (immunostained)
Gustafsson, M. G. L., L. Shao, et al. (2008). "Three-Dimensional Resolution Doubling in Wide-Field Fluorescence Microscopy by Structured Illumination." Biophys. J. 94(12): 4957-4970.
5 phases x 3 angles = 15 images per axial plane
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Red=Cohesin Rec8
Green=Asy1
Both stain lateral elements
C.-J. R. Wang, P. M. Carlton, I. N. Golubovskaya, and W. Z. Cande, "Interlock Formation and Coiling of Meiotic Chromosome Axes During Synapsis," Genetics 183, 905-915 (2009)
L. Schermelleh, P. M. Carlton, S. Haase, L. Shao, L. Winoto, P. Kner, B. Burke, M. C. Cardoso, D. A. Agard, M. G. L. Gustafsson, H. Leonhardt, and J. W. Sedat, "Subdiffraction Multicolor Imaging of the Nuclear Periphery with 3D Structured Illumination Microscopy," Science 320, 1332-1336 (2008)
Improve Imaging through C. elegans
• Sample 20 microns thick
• Fluorescent beads below sample
• Metric: intensity
• Optimize Zernikes: 5,6,7,8,11 (astigmatism, coma, spherical aberration)
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DIC Image of worm pharynx
Fluorescent image of C. elegans nuclei Stained with Texas Red (Wikipedia)
Microscope Layout
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Thanks for your attention!
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Acknowledgments: • Ben Thomas • UCSF: Mats Gustafsson,
John Sedat, David Agard, Lukman Winoto, Lin Shao, Hesper Rego, Pete Carlton
• Funding: Ralph E. Powe Junior Faculty Award, UGARF
