Resolving the spatial relationship between intracellular components by dual color super resolution optical fluctuations imaging (SOFI)
© Gallina et al.; licensee Springer. 2013
Received: 20 August 2012
Accepted: 7 February 2013
Published: 25 February 2013
Multi-color super-resolution (SR) imaging microscopy techniques can resolve ultrastructural relationships between- and provide co-localization information of- different proteins inside the cell or even within organelles at a higher resolution than afforded by conventional diffraction-limited imaging. While still very challenging, important SR colocalization results have been reported in recent years using STED, PALM and STORM techniques.
In this work, we demonstrate dual-color Super Resolution Optical Fluctuations Imaging (SOFI) using a standard far-field fluorescence microscope and different color blinking quantum dots. We define the spatial relationship between hDcp1a, a processing body (P-body, PB) protein, and the tubulin cytoskeletal network. Our finding could open up new perspectives on the role of the cytoskeleton in PB formation and assembly. Further insights into PB internal organization are also reported and discussed.
Our results demonstrate the suitability and facile use of multi-color SOFI for the investigation of intracellular ultrastructures.
KeywordsDual color Superresolution Fluorescence microscopy SOFI P-bodies
Despite the availability of microscopy methods that offer nanoscale resolution (like electron and scanning probe microscopies), far-field fluorescence microscopy (FFFM) is nevertheless the most commonly used imaging tool in biology. This primacy is due to FFFM’s unique advantages, including the ability to work with live specimens, excellent bio-specificity and sensitivity, minimal perturbation, direct display and visualization of the specimen, and versatility and simplicity of usage. FFFM is therefore the preferred tool for investigating spatial organization of cell components. However, Abbe’s intrinsic diffraction barrier limits the resolving power of the optical microscope to about half the excitation (and/or emission) wavelength, masking important information on morphology and co-localization of cellular components. Recently, several ground-breaking super-resolution (SR) imaging techniques (Bates et al. 2007; Betzig et al. 2006; Hess et al. 2006; Hell 2003; Hell and Wichmann 1994; Gustafsson 2000; Heintzmann et al. 2002) have been developed, and with their aid, previously unresolved biological questions have found new answers (Bates et al. 2007; Donnert et al. 2007; Shroff et al. 2007; Huang et al. 2008). The dissemination and wide-adaptation of SR over the last decade has been phenomenal, pointing to the revolutionary potential of these methods. Nonetheless, first generation commercial (and even-home-built) SR microscopes are expensive, and are not yet simplified to the ‘push-button’ level that affords the facile use by the non-expert. Additionally, these methods often require long acquisition (and therefore exposure) times and relatively high intensity excitation/depletion/photo switching lasers that limit the applicability to photo-resistant samples. Stochastic techniques such as PALM (Betzig et al. 2006) and STORM (Rust et al. 2006; Bates et al. 2007) are restricted to the use of photo-switchable emitters. A continuous effort has been expended in recent years to further simplify SR techniques and make them more affordable. In particular, methods that rely on conventional (and already deployed) microscopy platforms and standard fluorophores have been pursued (Burnette et al. 2011; Simonson et al. 2011; Dertinger et al. 2009; Dertinger et al. 2010a). In this context, Super-resolution Optical Fluctuations Imaging (SOFI) (Dertinger et al. 2009; Dertinger et al. 2010a; Dertinger et al. 2010b; Dertinger et al. 2012b; Dertinger et al. 2012a; Geissbuehler et al. 2011; Geissbuehler et al. 2012) offers the attractive possibility of performing SR imaging with a standard FFFM and blinking fluorescent probes such as quantum dots (QDs) (Dertinger et al. 2009; Dertinger et al. 2010a; Dertinger et al. 2012b), the fluorescent proteins Dronpa and rsTagRFP (Dedecker et al. 2012), and even non-fluorescent blinking nanoplasmonic probes (in press). SOFI is based on high-order spatio-temporal statistical analysis of stochastic blinking of independent emitters or scatterers (Dertinger et al. 2009) recorded in a sequence of frames. Multiple order SOFI analysis, combined with re-weighting of the Optical Transfer Function (OTF) (or with deconvolution (Dertinger et al. 2010a)), increases the resolution over the diffraction limit by a factor of n, n being the correlation (cumulant) order. In addition, spatiotemporal cross-cumulants calculation leads to an increase in the numbers of pixels that constitute the SOFI (SR) image (Dertinger et al. 2010a). In this work, we show a new procedure for performing two-color SOFI (2cSOFI) on fixed cells by using different color light emitting QDs. In particular, we demonstrate that 2cSOFI can effectively resolve the spatial relationship between the microtubule cytoskeleton and hDcp1a, a constitutive processing body (P-body, PB) protein. PBs (Liu et al. 2005; Sen and Blau 2005) are recently discovered protein-RNA aggregates, implicated in degradation, storage and silencing of mRNAs. PBs appear to be spatially confined along the microtubule network (Aizer et al. 2008), which in turn seems to regulate their formation and assembly (de Heredia and Jansen 2004; Shav-Tal and Singer 2005). Therefore, knowledge of the spatial correspondence between these two intracellular structures is of particular interest. In addition, PBs are ideally suited, due to their small dimensions (a few hundreds of nanometers), to be studied by SR imaging.
Amine-derivatized, PEG-coated 800 and 625-nm QDs were purchased from Invitrogen (Grand Island, USA). Monoclonal anti-alpha-tubulin primary antibody (mouse) was purchased from Sigma-Aldrich (USA), monoclonal anti-hDcp1a primary antibody (rabbit) was purchased from Abcam (USA). Bioconjugation was performed at room temperature by amine-thiol cross-linking: sulfo-succinimidyl 4-(N-maleimidomethyl) cyclohexane-1-carboxylate (Sulfo-SMCC) (Thermo Scientific, USA) was used to couple the thiol groups of biomolecules to the amino-terminated quantum dots. Thiolation of antibodies was obtained by reducing disulfide crosslinks of cysteine units in proteins with dithiothreitol (Thermo Scientific, USA). 4 μL of 10 mM sulfo-SMCC solution were added to a 4 μM QDs solution, the mixture was incubated at room temperature for one hour. 2 μL of 1M dithiothreitol were added to 1 mg/ml primary antibodies and kept for half an hour. After both components underwent purification by desalting columns, the conjugation reaction was allowed to proceed for one hour prior to quenching, obtained by adding 2-mercaptoethanol (Invitrogen, USA) to the reaction mixture. After 30 minutes the solution was concentrated via ultra-filtration and purified by separation media column. The final concentration of bioconjugated QDs was 1 μM. Further details on the bioconjugation can be found on line: (http://tools.invitrogen.com/content/sfs/manuals/mp19010.pdf).
Cell culture and fixation
Human cervical cancer cell line HeLa was ordered from American Type Culture Collection (ATCC, USA), the human osteosarcoma stable cell line U2OS expressing GFP-h-Dcp1a fusion protein was generated as described elsewhere (Aizer et al. 2008). HeLa and U2OS cells were cultured at 37°C, 5% CO2 in high glucose DMEM medium (Invitrogen, USA), supplemented with 10% Fetal Bovine Serum (FBS) and 1% Pen Strep (5000 units/mL penicillin G, 50 μg/mL streptomycin sulfate in 0.85% NaCl). Cells were pre-cultured prior to experiments in glass-bottom Petri dishes until 60% confluence was reached. The fixation was done incubating cells with cold fixative buffer (2 mM EGTA in 70% v/v methanol, 20% v/v acetone, 10% v/v water mixture) for 25 min at −20°C, after cells were rinsed with ice-cold PBS buffer. Cells were finally washed with TBS buffer. Stress conditions were induced on U2OS and HeLa cells immediately prior to the fixation, incubating cells for 1 hour at 37°C, 5% CO2 with 100 ug/mL Puromycin (InvivoGen, France) dissolved in culture medium.
Labeling of cytosolic proteins was obtained by incubating primary antibody QDs conjugates dissolved in blocking buffer (2% BSA, 0.05% Tween-20 in TBS buffer) with methanol/acetone fixed cells for half an hour at 4°C, following the protocol reported by Richard L. Ornberg and H. Liu (Weckwerth 2007). Cells were then washed with borate buffer and preserved in TBS buffer for microscopy measurements.
Microscope setup and data analysis
2000 frames movies were taken on a conventional LED-based (Aura light engine, Lumencor Inc., USA) widefield microscope (Nikon Eclipse Ti, Nikon Inc., USA) with a 150× magnification obtained using a 100× objective (NA 1.49 oil) coupled with a 1.5× camera coupling lens. An EMCCD camera (Andor Ikon 897, Andor Technology, UK) was used to detect the signal, with exposure times of 30 ms. Different color data sets were acquired sequentially by changing filter-sets: GFP [excitation (470/75), dichroic (505), emission (525/50)]; 625-nm QDs [excitation (535/50), dichroic (585), emission (620/40)]; 800-nm QDs [excitation (460–480 nm), dichroic (505), emission (700LP)]. All filters were purchased from Chroma Technology (USA). Multi-channel imaging of single color labeled cells indicated minimal crosstalk between the channels (below the detection limit of the EMCCD camera). Systematic errors in image registration between channels (due to consecutive alternation of the filter cube and chromatic aberrations) were corrected using a custom written Matlab (The MathWorks, Inc., USA) registration routine.
The registration routine is based on the alignment of signals collected from individual fluorescence microspheres (Invitrogen, USA) that emit in all channels and are evenly distributed over the field of view. In a first step, a registration matrix is originated by a projective transformation, and used to maximize the spatial correlation between different channels. In the next step, centers of individual PSFs are localized in all channels (using a 2D-Gaussian fit), and a second projective transformation is chosen to minimize the distances between corresponding PSF centers in the different channels (see Supporting Information for details). Additional file 1: Figure S5 gives a quantitative evaluation of the alignment accuracy, by showing a histogram of distances between centers of corresponding PFSs. Most of these shifts (>95%) are smaller than 0.3 pixel (32 nm), well below 2nd order SOFI resolution. The reproducibility of this analysis was tested for 100 images per channel (i.e. consecutive and repetitive filter cube switching). The resulting transformation matrix was used for subsequent measurements. Movies were analyzed by a custom written Matlab (The MathWorks, Inc., USA) code that is described elsewhere (Dertinger et al. 2009; Dertinger et al. 2010a). Co-localization analysis of two color images was done using an ImageJ Plugin (Nakamura et al. 2007).
Results and discussion
Based on immunogold electron microscopy experiments, PBs are generally described as non-membrane enclosed fibril aggregates of spheroidal shape (Yang 2004). On the contrary, SOFI imaging shows an unexpected doughnut-like appearance for several, but not all, detected PBs. In particular, 58% of SOFI-processed images showed a ring-like structure with a central dip above the background noise level. These structures were not specific to the U2OS cell line (as observed, for example, in Figure 3i), but they were also observed in HeLa cells (Additional file 1: Figure S7). We further investigated PB ultra-structure by treating U2OS cells with puromicyn, an antibiotic known to increase the number and the size of PBs (Eulalio et al. 2007). The SOFI image (Figure 1e) indeed shows an increase in size and number, and partial loss of the circular shape for most PBs in the field-of-view. Interestingly, doughnut-like PBs were never observed in puromycin treated cells. Inconsistencies in the observed PB morphologies could be due to their different maturation stage. We confirmed that the doughnut-shape is not an artifact of the Fourier re-weighting algorithm (see Additional file 1: Figure S7), but cannot rule-out artifacts due to experimental limitations such as insufficient resolution, incomplete labeling due to steric hindrance, and SOFI algorithmic issues.
On the other hand, the doughnut-shape morphology is consistent with a two-dimensional projection of a spherical shell organization of hDcp1a around the PB core, a feature that is common to several other cellular compartments as, for example, sub-cellular protein vesicles (Bates et al. 2007) and promyelocytic leukemia nuclear bodies (PML-NBs) (Lang et al. 2010). Moreover, it is strongly corroborated by recent Fluorescence Recovery After Photobleaching (FRAP) experiments (Kedersha et al. 2005; Leung et al. 2006; Aizer et al. 2008). While in this study we cannot determine whether the doughnut shape of the PBs is of real structural significance, it should be noted that a bi-compartment model of the PB structure demarking a core region and an outer peripheral region has been demonstrated by electron microscopy (Weil et al. 2012). Moreover, several studies have shown that RNAs and factors can localize differentially to a peripheral domain distinguishable from a PB core domain (Weil et al. 2012, Pillai et al. 2005, Carbonaro et al. 2011). This compartmentalization might serve for the functional separation between a core area of degradational activity and a surrounding area of recruitment and storage and deserves further investigations by higher resolution techniques.
We demonstrated that dual color SOFI is suitable for SR morphology and SR co-localization studies of cellular components. The observed co-localization patterns between PBs and the microtubule network are in agreement with previous studies (Aizer et al. 2008). Furthermore, SOFI imaging revealed that cytosolic hDcp1a monomers (or small aggregates) are preferentially located along tubulin filaments. This finding suggests that the role of the microtubule cytoskeleton is not limited to only anchoring PBs, but possibly to also provide molecular tracks for monomer trafficking, delivery and exchange (Shav-Tal and Singer 2005; de Heredia and Jansen 2004; Aizer and Shav-Tal 2008).
Electron-multiplying charge-coupled device
Far-field fluorescence microscopy
Fluorescence recovery after photobleaching
Green fluorescence protein
Optical transfer function
Photo-activated localization microscopy
- PB or P-body:
Resolution in conventional FFFM images
Resolution in SOFI images
Stimulated emission depletion
Stochastic optical reconstruction microscopy
Super resolution optical fluctuations imaging
Sulfo-succinimidyl 4-(N-maleimidomethyl) cyclohexane-1-carboxylate
This work was supported by NIH grant #5R01EB000312, NIH grant #1R01GM086197 and the Marco Polo Program of University of Bologna. Work in the lab of YST is supported by the European Research Council (ERC).
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