The fluorescence microscope is an essential tool in many fields of biology, but, in its classic form, is incapable of spatial resolution better than about 200 nm because of diffraction. Several recent methods can go well beyond this limit1–6
, within the constraints of each technique. Localization-based methods such as PALM4
can reach extreme resolution levels by precisely localizing individual photoswitchable fluorophores, but require very large numbers of raw images – hundreds to tens of thousands – and are therefore limited in speed. A recent incarnation of PALM decreases the acquisition time for a single frame from hours to around 25–60 seconds, and has recorded movies of ~20 frames; the downside is that only a subset of molecules are located per frame, which limits the effective resolution to ~60 nm7
. Stimulated emission depletion microscopy (STED) has obtained resolution below 30 nm by de-exciting the edges of the illuminated scan spot through stimulated emission1
. STED has achieved an impressive frame rate of 28 frames per second at 62 nm resolution, though with low photon counts and over a relatively small field of view of 2.5×1.8 μm8
. Enlarging the field of view would directly decrease the frame rate, because STED is a point scanning method. There is still a need for a technique that can combine spatial super-resolution with multi-Hz frame rates over large fields of view.
In structured-illumination microscopy (SIM), resolution is improved by moving high-resolution information into the normal resolution passband through spatial frequency mixing with an illumination pattern2
. It can improve resolution by a factor of two in its linear form, and by a larger factor if nonlinearity can be exploited3
. Linear SIM achieves a resolution of about 100 nm, not quite as high as the above methods, but has potential for much higher frame rates than PALM because it requires fewer raw data images, and for much larger fields of view than high-speed STED at a given frame rate because it acquires pixels in parallel by wide-field imaging rather than sequentially by point scanning.
In microcopy in general, the highest frame rates are possible when the region of interest is thin enough that a single plane per time point suffices, rather than a focal series. Indeed, to our knowledge all super-resolution time series published so far have been two-dimensional7,8
. Total internal reflection fluorescence (TIRF) microscopy provides an extremely thin emitting region, which can be treated as 2D for SIM purposes. SIM has already been used in TIRF9–13
, but not for time series imaging of live samples. Here we demonstrate live TIRF SIM at 100 nm resolution, with 3.7 to 11 Hz frame rates over fields of view of 32×32 to 8×8 μm.
Our implementation of 2D SIM uses 9 raw images, acquired with different illumination patterns, to construct one high-resolution output image: a periodic pattern of parallel lines is shifted through three phases for each of three orientation angles2
. Our original SIM produced the pattern with a transmission phase grating that was translated by a piezoelectric actuator and rotated by a mechanical stage2
. The mechanical movement of the grating was slow and limited the acquisition speed to several seconds per frame. We have now decreased the pattern-switching time by three orders of magnitude by using a ferroelectric liquid-crystal-on-silicon spatial light modulator (FLC SLM) (Displaytech) to produce the patterns (Supplementary Fig. 1
online). To switch patterns one simply writes new digital image data to the SLM (Supplementary Fig. 2
), which takes only 0.6 ms; the response time of the ferroelectric liquid crystal is even faster and does not limit the switching speed. The SLM consists of 1024×768 pixels, enough to illuminate the full field of view of our camera.
The pattern can be thought of as formed by interference of two collimated beams, created by diffraction from the SLM. For maximum signal the interference contrast must be maximized, which requires the two beams to be linearly polarized parallel to the pattern lines; the polarization must thus be co-rotated with the pattern orientation. We implement polarization rotation with two custom FLC switchable phase retarders (Displaytech), see Supplementary Fig. 3
. Their switching time of <100μs is concurrent with SLM pattern switching, and does not add to the acquisition time. The time required for one raw data image is thus dominated by the readout time of the camera, or by the exposure time if it is longer. Our microscope used a 512×512 pixel frame-transfer EMCCD camera (iXon DV887, Andor Technology, Ltd.) with a maximum full-frame rate of 35 Hz; the corresponding maximum SIM frame rate is 1/9 of that, or about 3.9 Hz. When the full field of view is not needed, the SIM frame rate can be increased by reading out a subfield (e.g., 14.7 Hz at 128×128 pixels), or more drastically by using a camera with fewer pixels. The SIM reconstructions have twice as many pixels in each dimension as the raw data. Our current full field of view is 32×32 μm, but could be increased to 43×43 microns for the same camera without undersampling.
As a first demonstration, we imaged EGFP-α-tubulin in living Drosophila
S2 cells, at illumination intensities of approximately 5–10 W/cm2
. To bring more microtubules into the region illuminated by TIRF, we used an established protocol that gently flattens the cells by mechanical pressure against a pad of agarose gel (see Methods). SIM produces a striking resolution improvement over conventional TIRF, as can be seen both in real space (, Supplementary Video 1
online) and in frequency space (, Supplementary Video 2
). Isolated microtubules are reconstructed with a full-width-at-half-maximum of 112±12 nm, compared to 275±21 nm in the conventional images (based on 158 measurements on 8 data sets). On test samples with 100 nm fluorescent microspheres we have measured an average FWHM of 104 nm (data not shown).
Figure 1 Comparison of conventional TIRF (a) and TIRF-SIM (b) images of the microtubule cytoskeleton in a single S2 cell. Scale bar 2 μm. (c) Normalized intensity profiles along the yellow lines in (a) (red curve) and (b) (blue curve). Two microtubules (more ...)
Time series with hundreds of time points can be produced with this method, see Supplementary Videos 1, 3, and 4
for examples with 120, 200, and 480 time points respectively. One of these data sets (Supplementary Video 3
) depicts microtubule dynamics in a tripolar mitotic spindle (multiple centrosomes are common in S2 cells). In the 480-frame data set, microtubule segments that were present in all frames photobleached by approximately 50%; segments that polymerized during the experiment were correspondingly less affected by bleaching.
To evaluate live SIM as a tool for studying microtubule polymerization and depolymerization dynamics, we imaged the area near a centrosome of a mitotic S2 cell ( and Supplementary Video 5
). A useful way to visualize these processes is with kymographs, using the random variation in GFP labeling density along each microtubule (speckling) to track microtubule position and thereby distinguish overall movement of the microtubule from growth or shrinkage at the end. Because of its higher resolution, SIM can visualize speckling with enhanced clarity (, Supplementary Video 6
) and permits increased labeling densities that allow more precise localization of the microtubule end. Even if the signal-to-noise ratio in each time frame is low, the time series nature of the data allows true labeling density variations to be distinguished from noise in that they persist over time and move with the microtubules (Supplementary Fig. 5
). Sharp transitions can be observed between states of steady polymerization or depolymerization, paused states of constant length, and states of slower or less stable evolution (brackets in ). With conventional microscopy (bottom), the speckling is much less sharp, and harder to distinguish from background features such as the coarse horizontal stripes seen here, which are caused by exclusion of free monomeric EGFP-tubulin by organelles. The rates of steady polymerization and depolymerization that we see in such kymographs, 87±26 nm/s and 267±56 nm/s respectively (each averaged over 22 measurements), are comparable to values in the literature14
for S2 cells (107±55 nm/s and 233±75 nm/s).
Figure 2 Time series live TIRF-SIM of EGFP-α-tubulin in an S2 cell. (a) Subset of one time frame (number 95) from a 180-frame sequence. Each frame was acquired in 270 ms (i.e., a raw data exposure time of 30 ms), using the full 512 × 512 pixel (more ...)
The ability of live SIM to resolve single microtubules within the spindle and follow their individual movements and polymerization activity makes possible a new range of experiments. For example, it has been suggested that microtubules can nucleate from other spindle microtubules through an augmin-mediated pathway15
. Live SIM should allow this process to be visualized directly. As a second example, microtubules in mitotic (or meiotic) spindles can exhibit “poleward flux” toward the centrosome, an incompletely understood phenomenon that has typically been studied at a collective level, for example by spot photobleaching of entire kinetochore fibers that contain multiple microtubules16
, or by microinjection of dye-labeled tubulin at such low densities that different speckles likely belong to different microtubules17
. With the higher resolution of SIM, poleward movement of spindle microtubules can be visualized and quantified at the single-microtubule level (Supplementary Fig. 6
), and correlated with observed polymerization or depolymerization events at the microtubule end.
As a challenging test case with very rapidly moving structures, we imaged kinesin-73-EGFP in S2 cells. Kinesin travels actively along microtubules at a typical speed18
of about 780 nm/s, corresponding to one 100-nm SIM resolution distance in about 130 ms; to avoid artifacts the frame time should be comparable or shorter. A time series with 144 ms SIM frame time (16 ms exposures), acquired with a 256×256 pixel field, produced a clear reconstruction in which individual kinesin-cargo complexes can be followed along microtubule tracks (, Supplementary Videos 7 and 8
). This data set was acquired at a nominal illumination intensity of ~26 W/cm2
, and faded by about a factor of 3 over 120 time frames. Those kinesin spots that appear to move progressively along tracks do so at speeds of 0.4–0.9 μm/s, in reasonable agreement with expectations for kinesin. Still smaller fields of view allow even higher rates; over a 128×128 pixel field (which becomes 256×256 pixels after reconstruction) we were able to image kinesin dynamics at a frame rate of 11.1 Hz (Supplementary Video 9
). The signal-to-noise ratio decreases at high speed, but the resolution is not severely affected: the average FWHM apparent size of persistent kinesin complexes in the 11-Hz data set was 112±13 nm (N=30), identical to the average FWHM observed in the slower tubulin data.
Figure 3 Time series live TIRF-SIM of kinesin-73-EGFP in an S2 cell. (a–b) Conventional TIRF (a) and TIRF-SIM (b) images of the first of 120 time frames. Each frame was acquired in 144 ms (i.e., a raw data exposure time of 16 ms), using a 256 × (more ...)
A critical requirement in live SIM is that the image sequence for a given time point should be acquired in a time short enough that no fine sample features move by more than about one resolution length, to avoid reconstruction artifacts (Supplementary Fig. 7
). For this reason, high acquisition speed is beneficial even in situations when observations are to be sparsely spaced in time (which may be desired in order to study a long-term process without observing so many times as to cause excessive photobleaching): each SIM sequence can be acquired rapidly enough to prevent artifacts, and successive sequences can be spaced out by appropriate delay times.
Our approach to live SIM could be extended in several ways. For example, multiple emission colors could be imaged simultaneously by adding cameras or split-view devices. The current design is limited to a single excitation wavelength (because the beam spacing, which must match the pupil diameter, is produced by diffraction and therefore proportional to the wavelength), but one excitation wavelength can excite multiple fluorophores with different emission bands19
. Drastically higher frame rates would be possible by using faster cameras, though typically at a cost of either field of view or sensitivity. For example, existing 128 × 128 pixel EMCCD cameras could allow TIRF-SIM at over 50 frames per second over a ~13 × 13 μm area. It may be possible to reach even higher spatial resolution through nonlinear SIM3
, but this requires a larger number of raw images per time frame and the use of photoswitchable dyes or fluorescence saturation methods, and puts greater demands on photostability. The hardware used here for 2D TIRF-SIM could also be used for 3D SIM20
with only minor modifications: slightly different SLM patterns, and a different demagnification factor from the SLM to the sample (see Supplementary Note
online). Live 3D SIM would have a slower frame rate than in 2D due to the larger number of raw images per time frame – at each time point it would use a focal series of axial planes spaced about 150 nm apart, and 15 instead of 9 raw images per axial plane20
– and would therefore become less tolerant of sample motion, in proportion to the sample thickness. It may be quite promising on a class of relatively thin samples.
While linear SIM does not produce quite as high resolution as STED or PALM, its frame rate and number of time points exceed those of live PALM by an order of magnitude, and the area rates (product of frame rate and field of view) exceed those published for live STED by a similar factor. Speckle microscopy in the sense of is not compatible with PALM as published, which images disjoint subsets of molecules, with statistically independent random variations, at different time points.
In summary, SLM-based SIM offers a combination of increased resolution, multi-Hz live imaging, long time series, and large field of view that other super-resolution techniques do not provide, and does so without requiring special fluorophores or extreme light intensities.