Enabling Structured Illumination Microscopy in Thick Tissue with

Adaptive Optics October 23rd , 2013

Peter Kner

College of Engineering

University of Georgia

kner@engr.uga.edu

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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