Resolving the spatial relationship between
intracellular components by Dual Color Super
Resolution Optical Fluctuations Imaging (SOFI)
Maria Elena Gallina†ˠ, Jianmin Xu†, Thomas Dertinger†‡, Adva Aizer¥, Yaron ShavTal¥, and Shimon Weiss†*
† Department of Chemistry and Biochemistry, Department of Physiology, and the
California NanoSystem Institute (CNSI), University of California Los Angeles, Los
Angeles, California, 90095-1569, USA
E-mail: sweiss@chem.ucla.edu
ˠ Department of Chemistry “G. Ciamician”, University of Bologna, Via Selmi 2,
40126 Bologna, Italy
‡ SOFast GmbH, Dresdener Str 14, 10999 Berlin, Germany
¥
The Mina & Everard Goodman Faculty of Life Sciences & Institute of
Nanotechnology, Bar-Ilan University, Ramat Gan 52900, Israel
*Author to whom correspondence should be addressed.
Supporting Information
Antibody Selectivity
The quality of QD immunofluorescent labeling on alpha-tubulin was tested by
comparing the appearance of the microtubule network in HeLa cancer cells
stained by QD primary anti-alpha-tubulin conjugates and by primary anti-alphatubulin (mouse) and Alexa-647 secondary anti-mouse (rabbit). The two different
labels gave analogous results (Figure S1), ruling out the introduction of possible
artifacts.
Control of Channel Alignment
The accuracy of channel alignment was determined applying a Matlab custom
written registration routine.
The transformation matrix was based on the
alignment of a dataset of conventional fluorescence images of (sparsely) spincoated fluorescent microspheres (Invitrogen, USA) emitting simultaneously in the
two channels and evenly distributed in the field of view. In a first step (preregistration), the projective transformation and its corresponding registration
matrix, was used to maximize the amount of spatial correlation between the two
channels, as shown in Figure S2. Another example of a pre-registered image is
shown in Figure S3, where blue arrows represent the projective transformation.
The channels are assigned the colors green and red, therefore overlapping signals
appear in yellow). In a second step, individual PSFs present in both channels were
fitted by 2D Gaussian intensity profiles. A distance vector between the centers of
corresponding 2D Gaussian curves in the two channels was calculated and a
second possibly local transformation was performed, this time to minimize the
lengths of the distance vectors (Figure S4).
It turned out that a local
transformation did improve the registration only marginally in terms of distance
vector minimization. Therefore the second transformation usually comprised
only a global projective transformation (Fig. S4). Quantitative evaluation of the
residual misalignment present between the two channels after registration is
given in Figure S5, where the histogram of the distance values between the
centers of corresponding PSFs is reported. It should be noted that, after the
application of the registration routine, the maximum amount of shift left between
the centers of the PFSs in the two channels is 0.3 pixel, which corresponds to 32
nm, a distance small enough to grant co-localization for a maximum resolution
gain of two-fold. Once reproducibility between registrations in the two channels
was verified by analyzing 100 images per channel, recorded passing consecutively
from one channel to the other, the resulting transformation matrix was used for
two color SOFI images.
Exclusion of ringing effects
Ringing artifacts may arise from the application of the Fourier re-weighting
algorithm(Dertinger et al., 2010). However, such artifacts could be ruled out by
the appearance of PBs with ring-like structures in SOFI-processed images where
no Fourier re-weighting had been applied, as shown in Figure S7.
Figure S1: Conventional staining of the alpha-tubuline network in HeLa cells by
monoclonal primary anti-α-tubulin (mouse) and secondary anti-mouse-Alexa 647
(a), and by 625-QD primary anti-α-tubulin conjugates (b).
Figure S2: Zoom-ins of two-color conventional fluorescence image of spin-coated
fluorescent microspheres (Invitrogen, USA) emitting in the two channels before
(a) and after (b) the projective transformation The colored edges of the
luminescent spots in the unregistered image (a) are vanishing in (b),
demonstrating that the registration matrix improves the overlap between the two
channels. Scale bar = 1.45 μm.
Figure S3: Pre-registered image of spin-coated fluorescent microspheres with
blue arrows representing the projective transformation. The scale on the x any
axis is reported in pixel numbers.
Figure S4: Image of spin-coated fluorescent microspheres showing a different
dataset with respect to previous images. The dots correspond to the centers of
PSFs, while their color indicates their distance with the corresponding PFS centers
in the second channel: the whiter they become the more they are farther apart.
Once again, blue arrows represent the projective transformation. The scale on the
x any axis is reported in pixel numbers.
Figure S5: Histogram of distances between corresponding PSFs in the two color
channels. PSF centers were derived from 2-D Gaussian intensity profile fitting.
This analysis was performed on a representative dataset collected from (sparsely)
spin-coated fluorescence microspheres (Invitrogen, USA) that emit simultaneously
in both channels and are evenly distributed over the field of view.
Figure S6: FFFM (a) and SOFI (b) co-localization images of tubulin with GFP-hDcp1a in HeLa cells. (c) and (d) are magnifications of the boxed regions in (b) and
(c), respectively. Scale bars: (—)= 5.0 μm; (- - - ) = 2.3 μm; (…..) = 1.0 μm.
Figure S7:
PBs’ doughnut-shape is not an artifact of Fourier re-weighting.
Conventional (a) and SOFI (b) fluorescence images of a HeLa cell. (c) zoom-in of
boxed area in (b) around the PB region. (d), (e) and (f): conventional (d) and SOFI
images of U2OS cells before (e) and after (f) Fourier re-weighting. Scale bars: (—
)= 5.0 μm; (— —) = 0.7 μm.
References
Dertinger T., Colyer R., Vogel R., Enderlein J., Weiss S (2010) Achieving increased
resolution and more pixels with Superresolution Optical Fluctuation Imaging
(SOFI). Opt Expr 18(18):18875-18893. doi: 10.1364/OE.18.018875