We describe how to implement photoactivated localization microscopy (PALM)-based studies of vesicles in fixed, cultured neurons. Key components of our protocol include labeling vesicles with photoconvertible chimeras, collecting sparsely sampled raw images with a super-resolution microscopy system, and processing the raw images to produce a super-resolution image.
Detection of fluorescence provides the foundation for many widely utilized and rapidly advancing microscopy techniques employed in modern biological and medical applications. Strengths of fluorescence include its sensitivity, specificity, and compatibility with live imaging. Unfortunately, conventional forms of fluorescence microscopy suffer from one major weakness, diffraction-limited resolution in the imaging plane, which hampers studies of structures with dimensions smaller than ~250 nm. Recently, this limitation has been overcome with the introduction of super-resolution fluorescence microscopy techniques, such as photoactivated localization microscopy (PALM). Unlike its conventional counterparts, PALM can produce images with a lateral resolution of tens of nanometers. It is thus now possible to use fluorescence, with its myriad strengths, to elucidate a spectrum of previously inaccessible attributes of cellular structure and organization.
Unfortunately, PALM is not trivial to implement, and successful strategies often must be tailored to the type of system under study. In this article, we show how to implement single-color PALM studies of vesicular structures in fixed, cultured neurons. PALM is ideally suited to the study of vesicles, which have dimensions that typically range from ~50-250 nm. Key steps in our approach include labeling neurons with photoconvertible (green to red) chimeras of vesicle cargo, collecting sparsely sampled raw images with a super-resolution microscopy system, and processing the raw images to produce a high-resolution PALM image. We also demonstrate the efficacy of our approach by presenting exceptionally well-resolved images of dense-core vesicles (DCVs) in cultured hippocampal neurons, which refute the hypothesis that extrasynaptic trafficking of DCVs is mediated largely by DCV clusters.
A number of cellular processes depend on accurate and efficient vesicle-mediated trafficking of biomolecules to specific subcellular destinations. One prominent example is synaptic assembly, which is preceded by long-ranged, vesicle-mediated delivery of synaptic constituents from sites of biogenesis in the neuronal soma to potentially distal pre- and postsynaptic sites1.
Fluorescence microscopy is a powerful and popular method of studying vesicle trafficking. Strengths of the technique include its sensitivity, specificity, and compatibility with live imaging2. Unfortunately, until relatively recently, the technique has suffered from one major weakness, diffraction-limited resolution2, which hampers studies of structures with dimensions smaller than ~250 nm. Recently, lateral resolution in fluorescence microscopy surpassed the diffraction barrier with the introduction of super-resolution fluorescence microscopy techniques, such as PALM3. The lateral resolution of PALM, tens of nanometers, is ideally suited to the study of vesicles, which have dimensions that typically range from ~50-250 nm4. It is thus now possible to use fluorescence, with its myriad strengths, to elucidate a spectrum of previously inaccessible attributes of vesicles, including some aspects of their trafficking to specific subcellular sites.
PALM is not trivial to implement, and successful strategies often must be tailored to the type of system under study. Here we describe how to implement PALM studies of vesicular structures, and we demonstrate the efficacy of our approach for the case of DCVs in hippocampal neurons. In particular, we use PALM to address the hypothesis that trafficking of DCVs to synapses in hippocampal neurons is mediated by DCV clusters5-8.
Cluster-mediated trafficking of vesicles to synapses in developing neurons is an intriguing possibility because it may facilitate rapid synaptic stabilization and assembly9,10. Proponents of clustered trafficking of DCVs cite the large apparent size of extrasynaptic fluorescent puncta harboring exogenous DCV cargo as evidence supporting clustering6. However, these puncta appear in images generated using diffraction-limited fluorescence microscopy techniques, which are not suited to distinguishing size effects arising from diffraction from those arising from clustering.
To resolve this issue, we collected conventional widefield fluorescence and PALM images of hippocampal neurons expressing chimeras targeted to DCVs. Analysis of these images revealed that >92% of putative extrasynaptic DCV clusters in conventional images are resolved as 80 nm (individual DCV-sized)11 puncta in PALM images. Thus, these data largely invalidate the clustering hypothesis as applied to DCVs in developing hippocampal neurons.
1. Sample Preparation
2. Image Acquisition
3. Image Processing, Display, and Analysis
Figure 1 shows one end product of imaging and processing. In this PALM image, lateral coordinates of localized fluorophores are shown using the centroid display mode, and the super-resolution image of the associated DCV is shown using the Gaussian display mode.
Figure 2A shows analogous widefield and PALM images of the soma and proximal processes of an eight days in vitro hippocampal neuron expressing tPA-Dendra2. Important features of the images include the (1) extensive, one-to-one correspondence, and overlap, between puncta in the conventional and PALM images, (2) significantly smaller size of the PALM puncta, and (3) occasional resolution of a single widefield punctum into multiple PALM puncta.
Figure 2B shows a PALM image of DCVs along part of a process of a second hippocampal neuron expressing tPA-Dendra2. Important features of this image include the (1) small diameter, and homogeneous appearance, of the puncta, and (2) infrequent observation of closely apposed puncta/putative DCV clusters.
Figure 3 outlines a simple quantitative method of determining if two or more DCVs are close enough to comprise a cluster; in systems where clustering is prevalent, more sophisticated methods, based on distribution functions, can be used for quantification21. The simple method is based on generating line profiles of puncta intensities (shown in the graphs), which can be used to quantify DCV separation and DCV width. If separation significantly exceeds width (as discussed in the legend), the DCVs do not "contact," whereas if separation is approximately the same as width, the DCVs might contact. Based on this criterion, the DCVs in Panel A were classified as "not in contact" whereas those in Panel B were classified as in contact. Using this approach, we put an upper bound of ~8% on contact-associated clustering of extrasynaptic DCVs in developing hippocampal neurons. Our DCV size and cluster data are summarized in Table 1.
Figure 1. Overlay of a Gaussian-rendered PALM image of a DCV (red) and a centroid-display mode PALM image showing coordinates of individual photoconverted fluorophores (white dots) contained in the DCV. The former mode displays fluorophores rendered to Gaussian functions with widths determined by their localization precisions, and the latter displays fluorophores/peaks as dots localized at their (x,y) coordinates. Bar = 0.1 µm. Click here to view larger image.
Figure 2. Overlay (A) of summed widefield (green) and PALM (red) images of the soma and proximal processes of a developing hippocampal neuron expressing tPA-Dendra2. Regions of overlap appear yellow/orange. PALM image (B) of DCVs lining a subregion of a process of another cell expressing tPA-Dendra2. Bars = 5 and 2 µm. Click here to view larger image.
Figure 3. Overlays (A and B) of summed widefield (green) and PALM (red) images of puncta in a developing hippocampal neuron expressing tPA-Dendra2. In both panels, the widefield image shows a single large punctum, whereas the associated PALM image resolves this single punctum into two much narrower puncta. The graphs show analogously color-coded intensity profiles obtained for the puncta in panel A (left graph) and in panel B (right graph). The profiles derived from the PALM image in panel A show that the puncta have a full width at half maximal intensity that is ~40% of their peak-to-peak spacing; thus, these two puncta are not in contact and were not classified as a putative cluster. In contrast, the profiles derived from the PALM image in panel B show that the puncta have a full width at half maximal intensity that is essentially the same as their peak-to-peak spacing; thus, these were classified as a putative cluster. Bar = 0.2 µm. Click here to view larger image.
Parameter | Result | Number of DCVs analyzed |
Upper-bound on clustered DCVs | 7.9 ± 5.9% | 618 |
Mean DCV diameter | 77 ± 21 nm | 60 |
Table 1. DCV size and cluster data summary.
PALM and related super-resolution fluorescence microscopy techniques have recently emerged as a valuable complement to better-established forms of optical microscopy and electron microscopy (EM)22-24. Positive attributes of PALM include relatively simple sample preparation and minimal sample perturbation. In principle, PALM also can be used to study living cells. Probably the main negative attribute of PALM is time-consuming data acquisition, which significantly hampers studies of faster dynamic processes in living cells. In addition, PALM is relatively new, and thus appropriate, robust fluorophores and protocols for sample preparation and for data acquisition and analysis are not fully developed and/or documented3.
Here we have described a protocol that is suited for single-color, PALM-based studies of vesicles in fixed, cultured cells. The protocol also is a good starting point for the development of similarly directed, dual-color PALM studies. The efficacy of our protocol is supported by two key attributes of our PALM data. First, the distribution of puncta in our reconstructed PALM, and complementary widefield, images is very similar. The one significant difference in distribution – occasional resolution of diffraction-limited puncta into multiple puncta by PALM – reflects the markedly enhanced resolution of PALM and further underscores the technique's efficacy and utility.
Second, our PALM results are in good agreement, and/or consistent, with other relevant results. For example, images of hippocampal neurons obtained using EM occasionally reveal slices through DCVs, and the DCV diameter deduced from the slices is ~70-100 nm11. The remarkable agreement between our PALM data and the EM data is reassuring for both approaches. PALM still is being tested, and EM generally is subject to concerns about the requisite harsh sample preparation. Similarly, diffraction-limited movies of living hippocampal neurons coexpressing green and red chimeras targeted to DCVs show that overlapping green and red puncta undergo persistent comovement25. The most straightforward interpretation of this result – the red and green signals arise from the same DCV – is consistent with PALM, which demonstrates that diffraction-limited puncta overwhelmingly represent individual DCVs. A less straightforward interpretation of comovement – the red and green signals arise from clustered DCVs – is largely invalidated by PALM.
The protocol described here has other positive attributes. In particular, sample preparation is relatively straightforward and quite similar to that suited for conventional fluorescence microscopy, with two notable exceptions: (1) vesicles must be labeled with photoconvertible or photoactivatable fluorophores, and (2) fixed cells are best mounted in aqueous media. This relative simplicity reflects the fact that the experiments are short, and thus samples do not need to be labeled with fiducial beads (to facilitate drift correction), which can be tricky26. In addition, vesicles usually are tagged with many fluorophores; thus, achieving adequate fluorophore labeling density is straightforward. In contrast, for other structures, this can be quite difficult3. Image acquisition also is relatively straightforward. However, PALM does require electronic and optical components that are expensive and cutting-edge because PALM signals are intrinsically very weak.
Probably the most sophisticated aspects of PALM center around the processing, analysis, and display of PALM images. As highlighted here, implementing these aspects of PALM requires an understanding of several subtle issues, including the relationship between sampling and resolution, and the distinction between resolution and localization precision. Thus, overall, PALM studies invariably are quite intricate, but this is balanced by resolution enhancement that is likely to be significant.
The authors have nothing to disclose.
This work was supported by National Institutes of Health grants 2 R15 GM061539-02 (to B.A.S.), 2 R15 NS40425-03 (to J.E.L.), MH 66179 (to Dr. Gary Banker of Oregon Health & Science University/OHSU), and P30 NS061800 (to Dr. Sue Aicher of OHSU). We thank Barbara Smoody for extensive support with the culture of hippocampal neurons, and Drs. Brian Long and James Abney for a critical reading of this manuscript.
Zeiss PALM | Carl Zeiss, Inc. | Elyra PS.1 | With Zeiss Efficient Navigation (ZEN) software and fluorescence filter Set 77 HE GFP/mRFP/Alexa633 |
Lipofectamine 2000 Transfection Reagent | Life Technoligies | 11668-019 | |
Minimum Essential Medium | Life Technologies | 11095-080 | |
Phosphate-Buffered Saline | Life Technologies | 10010049 | |
Paraformaldehyde | Electron Microscopy Sciences | 19208 | |
Sucrose | Sigma-Aldrich | S-8501 | |
growth glass coverslips 18mm 1.5D | Fisher Scientific | NC0059095 |