image taken at a given incident angle, and thereby with a well-defined penetration depth, entangles information from considerably deeper than the penetration depth with that from shallower sections of the cell.
Perhaps the best way to view an individual image is to state that there is a 1-sigma probability that the fluorescence concentration is located within the penetration depth of that image. Therefore the differential technique that was utilized in this VA-TIRFM study optimally yields 3D images in which the fluorophore concentration distribution in z is certain to ~1 sigma.
A 1-sigma certainty is more stringent than the gold standard for defining optical resolution:
the Rayleigh criterion.37 Rayleigh defined a pair of point sources, assuming equal brightness and spectral content, as being resolved when the central diffraction disks are just touching at 50% of maximum. The separation then is equal to the Full Width Half Maximum (FWHM) of one of the beams. 1-sigma certainty is more stringent than the Raleigh criterion as the intensity at that point is only 1/e37% of maximum rather than at 50%.
The early attempts at VA-TIRFM 3D image reconstruction reported here do not achieve 1- sigma certainty due to non-uniformity of the excitation beam. However they do approach and likely exceed the Rayleigh criterion in terms of vertical resolution. This implies that we have achieved a vertical resolution of <50 nm.
A more rigorous deconvolution of the continuous fluorophore distribution is required to do significantly better than 1-sigma certainty. This could be accomplished via the inverse Laplace transform approach described earlier. An alternate method for disentangling fluorescence that originated at different z distances in an evanescent field would be to use a finite difference technique similar to that used to solve heat transfer and fluid flow problems.
During the course of this study a variety of different imaging strategies were explored. It is clear (see Figure 2.5) that direct differencing very, very finely parsed images is ineffective
as the variation of illumination intensity due to interference patterns is greater than the additional signal detected due to increased penetration depth.
For simple direct differencing with our current microscope we have found that five slices probably represents the most that can be useful. In comparing the efficacy of several approaches we found that five slice z-stacks in general appear to have fewer artifacts than 4, which in turn is better than 3 image z-stacks. Even spaced 5 layer images were constructed and give nearly identical results (not shown) to the 5 slice logarithmic z-stacks.
In all cases the 4 slice even space approach gave better results than the 4 slice logarithmic approach. It is not clear to what degree this is due to limitations in the image processing software.
Image fidelity or goodness was here evaluated in a fashion similar to that used when evaluating AFM images: by how sharply defined features are and by an absence of artifacts. Here we define artifacts as repeated structures across an image. As an example, an artifact in a reconstructed image could be identified if the visualized structures have relatively round, twisted shapes throughout most of a cells were connected in one, cell- wide, section with a parallel set of cylindrical or conical features. So the images were examined for features or associations that were repeated as patterns to identify artifacts as would be done when evaluating AFM images.
This kind of artifact is certain to occur when the image is stretched in z (by 10 x in the case of the papers presented herein). It is also likely to occur when the collected image stack has significantly varying thicknesses. Every image processing software package identified, including ImageJ and Imaris 7.0, reconstruct images assuming that every image in the stack is of equal thickness. If on slice is twice as thick as another the final result will be to artificially stretch or compress those regions in a 3D reconstruction. Therefore it is logical to prefer even spaced (in penetration depth) differenced images when doing 3 D image reconstructions.
As shown earlier (e.g. Figure 2.4) even spaced differential images are limited to a z-stack containing only five slices of ~50 nm thickness (each). Clearly it would be beneficial to get
finer z resolution than this. Alternative approaches would include interleaving images so that two stacks of 50 nm thick images could be offset by 25 nm.
While continuous 3D image reconstruction is a challenging problem, there are clear first steps that can be taken by future researchers. Three major impediments remain to be solved for significantly finer z resolution:
1. Image processing software in which the z value of each image in a stack can be individually set and
2. A substantial reduction in excitation laser interference pattern. The first ways to achieve that are to improve the index of refraction match between the coverslip and the immersion oil and to replace the optics that guide the excitation laser with ones that have high quality antireflection coatings. If that is not sufficient, two methods for ensuring elimination of interference patterns are spinning beam and annular mask. With spinning beam the radius must be increased or decreased to change angle of incidence. Precise control of this is possible but will require some though and very good optical alignment. VA-TIRFM with an annular mask is tougher. Perhaps the image of the mask on the objective back plane could be expanded or contracted optically (in analogy to a zoom lens).
3. A smaller excitation laser beam focal spot would significantly reduce the variation in incident angle across the beam. Therefore more finely parsed images could be taken. A factor of two to three reduction in beam size would be sufficient to enable 10 differential slices to be acquired rather than the current limit of 5.
Summary
We have demonstrated that TIRFM using a 1.65 NA objective enables cellular membranes to be imaged in near isolation from the interior of a cell. Further, by using a close-loop controlled positioner, the incident angle of the excitation laser can be repeatably set. This in turn enables images to be captured with known and controlled evanescent field penetration depths. We have shown that the deepest pure TIRF image that can be taken, even with a 1.65 NA objective and high index N-LAF21 coverslips, is about 250 nm thick.
A novel, and relatively simple image processing technique was developed during this study wherein several images are taken with known penetration depths. By normalizing these images, to account for the change in evanescent field intensity as a function of incident angle, they can be directly subtracted to yield difference images in which cellular structures can be optically isolated to distances within 46 nm of the coverslip surface and thereafter at defined distances up to ~250 nm.
We have also demonstrated that these differenced images can be used to construct detailed cellular structure models of up to 250 nm depth. In doing so it appears that cellular organelles can be located vertically to within ~50 nm at present and with higher precision given further development.
Finally we have detected puncta where the smooth ER may intersect with the cell membrane presumably for the purposes of rapid transport of lipids and membrane bound proteins including nAChRs. Such tubular connections between the ER and outer membrane could represent an alternate trafficking mechanism to transport via discrete vesicles. VA- TIRFM appears to be well suited for investigating mechanisms controlling the assembly of functional receptors or lipid rafts in living cells via pulse-chase experiments.
In conclusion, we confidently expect that VA-TIRFM will provide insight into trafficking mechanisms by enabling imaging of cell membranes discrete from images of nearby cellular components.
Acknowledgements
Thanks to Joe Shepherd, Dan Axelrod, Rahul Srinvasan, Chris Richards, and Henry Lester.
I could never have hoped to complete this VA-TIRFM study without the skilled work and kind help of Mike Roy and Steve Olson of the Chemistry Department's Instrument shop.
Caltech Dean Grad Studies/Provost, NS11766, Louis and Janet Fletcher, and The Michael J. Fox Foundation are gratefully thanked for funding.
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C h a p t e r 3
TOWARDS IMAGING FLUORESCENLY LABELED PROTEINS WITH TIP- ENHANCED FLUORESCENCE MICROSCOPY (TEFM)
In collaboration with the Quake group of Caltech, we demonstrated sub-10 nm optical resolution with a Tip-Enhanced Fluorescence Microscope (TEFM) imaging quantum dots1 and single-molecules2 on a dry surface. TEFM is a hybrid microscope that combines an Atomic Force Microscope (AFM) with a custom Total Internal Reflection Fluorescence Microscope (TIRFM). A 543 nm excitation laser beam is focused through a microscope objective at the top surface of a glass coverslip to stimulate an evanescent field. Emitted fluorescence is collected by the microscope objective and then directed onto an avalanche photodiode (APD) through a system of spectral filters. In Figure 3-1 the major components in a TEFM are shown schematically. The two patents awarded for this microscope are Appendices C and D.
After joining the Scott Fraser group this instrument was substantially enhanced to enable imaging of proteins in a biologically relevant warm, wet environment. In collaboration with the Henry Lester group, a prolonged
attempt was made to utilize this Wet- TEFM for imaging nicotinic acetylcholine receptors on living cells.
However, the complexities of the tip- sample interaction with living cells, combined with the complexities of tip-evanescent field interactions in extracellular liquid, precluded confident interpretation of the resulting data. As a result I was not
able to apply this instrument to study Figure 3.1 The major components in a TEFM are schematically shown above. In essence the TEFM is comprised of an AFM and a TIRF microscope.
neuroreceptor organization and composition as intended.
This chapter is organized into two sections. In the first section 'Dry TEFM Imaging' two papers are presented that describe the TEFM principles, instrument and our results in detail.
In the second section 'Wet TEFM Imaging of Live Cells and Membrane-bound Proteins' the innovations developed to enable adaptation of TEFM to imaging live cells are summarized, and some preliminary results are presented. Detailed descriptions of the instrument, data acquisition hardware and software and the image processing software developed for wet TEFM imaging, are presented in Appendix E.