This study was supported by JSPS KAKENHI Grant Numbers JP19H03202 to A.M., JP18H05528 and JP17H03636 to T.H., and JP17H01444 and JP18H05533 to H.Y. L.S. acknowledges the support by the Welcome Trust Strategic Awards 091911 and 107457/Z/15/Z funding advanced imaging at Micron Oxford.

<ol>
	<li>Schermelleh, L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Super-resolution+microscopy+demystified.">Super-resolution microscopy demystified.</a> Nature Cell Biology. 21 (1), 72-84 (2019).</li><li>Manders, E. M. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Chromatic+shift+in+multicolour+confocal+microscopy.">Chromatic shift in multicolour confocal microscopy.</a> Journal of Microscopy. 185 (3), 321-328 (1997).</li><li>Matsuda, A., Schermelleh, L., Hirano, Y., Haraguchi, T., Hiraoka, Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Accurate+and+fiducial-marker-free+correction+for+three-dimensional+chromatic+shift+in+biological+fluorescence+microscopy.">Accurate and fiducial-marker-free correction for three-dimensional chromatic shift in biological fluorescence microscopy.</a> Scientific Reports. 8 (1), 7583 (2018).</li><li>Gr&#252;nwald, D., Singer, R. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=In+vivo+imaging+of+labelled+endogenous+&#946;-actin+mRNA+during+nucleocytoplasmic+transport.">In vivo imaging of labelled endogenous &#946;-actin mRNA during nucleocytoplasmic transport.</a> Nature. 467 (7315), 604-607 (2010).</li><li>Betzig, E., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Imaging+intracellular+fluorescent+proteins+at+nanometer+resolution.">Imaging intracellular fluorescent proteins at nanometer resolution.</a> Science. 313 (5793), 1642-1645 (2006).</li><li>Rust, M. J., Bates, M., Zhuang, X. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Sub-diffraction-limit+imaging+by+stochastic+optical+reconstruction+microscopy+(STORM).">Sub-diffraction-limit imaging by stochastic optical reconstruction microscopy (STORM).</a> Nature Methods. 3 (10), 793-795 (2006).</li><li>Chen, F., Tillberg, P. W., Boyden, E. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Expansion+microscopy.">Expansion microscopy.</a> Science. 347 (6221), 543-548 (2015).</li><li>Kraus, F., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quantitative+3D+structured+illumination+microscopy+of+nuclear+structures.">Quantitative 3D structured illumination microscopy of nuclear structures.</a> Nature Protocols. 2, 1011-1028 (2017).</li><li>Hell, S. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Far-Field+Optical+Nanoscopy.">Far-Field Optical Nanoscopy.</a> Science. 316 (5828), 1153-1158 (2007).</li><li>Gustafsson, M. G. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Surpassing+the+lateral+resolution+limit+by+a+factor+of+two+using+structured+illumination+microscopy.">Surpassing the lateral resolution limit by a factor of two using structured illumination microscopy.</a> Journal of Microscopy. 198 (2), 82-87 (2000).</li><li>Schulz, O., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Resolution+doubling+in+fluorescence+microscopy+with+confocal+spinning-disk+image+scanning+microscopy.">Resolution doubling in fluorescence microscopy with confocal spinning-disk image scanning microscopy.</a> Proceedings of the National Academy of Sciences of United States of America. 110 (52), 21000-21005 (2013).</li><li>M&#252;ller, C. B., Enderlein, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Image+Scanning+Microscopy.">Image Scanning Microscopy.</a> Physical Review Letters. 104 (19), 198101 (1981).</li><li>Hayashi, S., Okada, Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Ultrafast+superresolution+fluorescence+imaging+with+spinning+disk+confocal+microscope+optics.">Ultrafast superresolution fluorescence imaging with spinning disk confocal microscope optics.</a> Molecular Biology of the Cell. 26 (9), 1743-1751 (2015).</li><li>Yorifuji, H., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Emerin,+deficiency+of+which+causes+Emery-Dreifuss+muscular+dystrophy,+is+localized+at+the+inner+nuclear+membrane.">Emerin, deficiency of which causes Emery-Dreifuss muscular dystrophy, is localized at the inner nuclear membrane.</a> Neurogenetics. 1 (2), 135-140 (1997).</li><li>Woods, A., Sherwin, T., Sasse, R., MacRae, T. H., Baines, A. J., Gull, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Definition+of+individual+components+within+the+cytoskeleton+of+Trypanosoma+brucei+by+a+library+of+monoclonal+antibodies.">Definition of individual components within the cytoskeleton of Trypanosoma brucei by a library of monoclonal antibodies.</a> Journal of Cell Science. 93 (3), 491-500 (1989).</li><li>Tokunaga, M., Imamoto, N., Sakata-Sogawa, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Highly+inclined+thin+illumination+enables+clear+single-molecule+imaging+in+cells.">Highly inclined thin illumination enables clear single-molecule imaging in cells.</a> Nature Methods. 5 (2), 159-161 (2008).</li><li>Rueden, C. T., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=ImageJ2:+ImageJ+for+the+next+generation+of+scientific+image+data.">ImageJ2: ImageJ for the next generation of scientific image data.</a> BMC Bioinformatics. 18 (1), 529 (2017).</li><li>McKinney, S. A., Murphy, C. S., Hazelwood, K. L., Davidson, M. W., Looger, L. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+bright+and+photostable+photoconvertible+fluorescent+protein+for+fusion+tags.">A bright and photostable photoconvertible fluorescent protein for fusion tags.</a> Nature Methods. 6 (2), 131-133 (2009).</li><li>Sawin, K. E., Nurse, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Photoactivation+of+green+fluorescent+protein.">Photoactivation of green fluorescent protein.</a> Current Biology. 7 (10), 606-607 (1997).</li><li>Elowitz, M. B., Surette, M. G., Wolf, P. E., Stock, J., Leibler, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Photoactivation+turns+green+fluorescent+protein+red.">Photoactivation turns green fluorescent protein red.</a> Current Biology. 7 (10), 809-812 (1997).</li></ol>

The authors have nothing to disclose.

The procedure for chromatic correction is a trade-off between accuracy and effort. To save needless efforts, it is better to know how much accuracy is required for your study. The highest accuracy may not be required for conventional wide-field (live) imaging, and thus, bright field reference images are often sufficient to correct the chromatic shift. Similarly, when the imaging condition and environment is constant, repeated use of a biological calibration will save time. On the other hand, if a highly accurate registration is desired, high-quality crosstalk or biological calibration reference images are necessary. For the best performance, reference images should be obtained with as similar conditions and timings as the target images as possible. As long as both reference and target images are obtained by the same microscopy, higher spatial resolution will improve the correction accuracy. If deconvolution is available for both reference and target images, then implementing this before correction may improve the correction accuracy. Also, for the best performance, the sampling theorem for the optical (Z) axis should be fulfilled in both the reference and target file for precise subpixel interpolation (protocol step 2.1.3).
Failure to correct chromatic shift leads to incorrect conclusions. Furthermore, using the wrong calibration may even worsen the chromatic shifts rather than correcting them, and this therefore needs to be avoided. We have summarized the possible causes of failures, and their common solutions, in Table 2. To examine the cause of a failure, in the first place, it is necessary to visually check if the chromatic shift in the reference image is precisely corrected (protocol step 3.12). Most failures are due to the quality of the reference images and are easily remedied as per the descriptions in Table 2. Regarding to the quality of reference images, it is important to note that the accuracy of global alignment decreases if the entire field of view is not filled with the sample (Figure 7, Table 2). Compared to the good example shown in Figure 7A, the bad example shown in Figure 7B contains only three nuclear envelopes in the upper-left region, and Chromagnon failed to align a part of this image. This is because the global alignment method of Chromagnon splits the field of view into four regions (Figure 7C) in order to measure the differences in rotation and magnification with high accuracy3. This method, if correctly operated, is one order more accurate than other linear methods such as the log polar transformation and simplex methods3. If any of the four regions are unavailable, then Chromagnon will switch to less effective linear methods. Therefore, for the best performance, the examples shown in Figure 7B and Figure 7C are undesirable, and the four regions should be filled with objects. Users can check if any quadratic region of the field of view is unavailable for measurement by looking at the log file (&#34;Chromagnon.log&#34;; see protocol step 3.10). Fortunately, this problem can be easily overcome by averaging multiple biological calibration images or using local alignment for crosstalk or bright-field reference images (Table 2). Contrary to the case of failure to correct reference images, failure to correct target images is more difficult to identify. Because such failures arise due to differences in file formats, imaging conditions, imaging timings, imaging/alignment methods between the reference and target images (Table 2), users should always be careful when using reference images that are obtained in different conditions/timings from the target images. Some example images are available for testing (<a href="https://github.com/macronucleus/Chromagnon" target="_blank">https://github.com/macronucleus/Chromagnon</a>) to obtain concrete idea of the good and bad example images.
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Problem</td>
			<td>Cause</td>
			<td>Solution</td>
		</tr>
		<tr>
			<td>Failed to correct the reference image</td>
			<td>Low contrast</td>
			<td>Acquire a higher contrast image if possible. If a bright-field reference image is used, reacquire the image in a water-based solution to obtain higher contrast of the cell. Alternatively, try applying computational noise reduction (e.g. Gaussian filtering). Turn off local alignment, which is more sensitive to noise.</td>
		</tr>
		<tr>
			<td></td>
			<td>Contamination of unrelated images</td>
			<td>Remove the source of the unrelated images in the sample if possible. For crosstalk reference images, check the excitation spectra of the dyes used for the target images. If the dyes are excited during acquisition of a crosstalk image (e.g. Alexa Fluor 568 or 594), consider other dyes (e.g. Alexa Fluor 555). If dusts on the camera chip creates an obvious channel difference, clean the camera chip or use a computational flat-fielding method.</td>
		</tr>
		<tr>
			<td></td>
			<td>An extremely bright spot made by a cosmic ray</td>
			<td>Acquire the image again if possible. Alternatively, try applying computational noise reduction (e.g. Median or Gaussian filtering).</td>
		</tr>
		<tr>
			<td></td>
			<td>Deconvolution artifacts (artificial signals at the axial and lateral edges)</td>
			<td>Trim the edge pixels or Z sections after deconvolution. If one side is trimmed, the other side should also be trimmed to maintain the image center.</td>
		</tr>
		<tr>
			<td></td>
			<td>The Z step size too sparse</td>
			<td>A Z stack should be acquired to fulfill the Nyquist criterion as written in protocol 2.1.3.</td>
		</tr>
		<tr>
			<td></td>
			<td>Optical aberration</td>
			<td>Spherical aberration is the major aberration caused by users. Choose the right objective lens for the sample and use a coverslip thickness of 170 &#181;m. If the objective lens is equipped with a correction ring, adjust it to find the position where the highest fluorescence count is obtained from the focus. In the case of an oil-immersion objective without a correction ring, adjust the refractive index of the immersion oil that increases the fluorescence count at the focus.</td>
		</tr>
		<tr>
			<td></td>
			<td>Field of view is unfilled (Fig. 7)</td>
			<td>In the case of biological calibration reference images, average many images. In the case of crosstalk or bright-field reference images, use local alignment.</td>
		</tr>
		<tr>
			<td></td>
			<td>An unidentified software bug</td>
			<td>Report the issue through GitHub (<a href="https://github.com/macronucleus/Chromagnon/issues" target="_blank">https://github.com/macronucleus/Chromagnon/issues)</a></td>
		</tr>
		<tr>
			<td>Failed to correct the target image</td>
			<td>Metadata of the image file is lost</td>
			<td>Use the original microscope file format which contains complete metadata, and avoid converting to a multipage tiff file before processing. Use the same ordering of channels as written in protocol 3.3.</td>
		</tr>
		<tr>
			<td></td>
			<td>Wrong alignment methods for the given microscopy</td>
			<td>Do not apply the local alignment method when measuring from biological calibration reference images to target images. Do not use crosstalk reference images other than wide-field microscopy.</td>
		</tr>
		<tr>
			<td></td>
			<td>Differences in imaging conditions</td>
			<td>Keep the imaging conditions constant between the reference and the target images as written in protocol 2.3.3.</td>
		</tr>
		<tr>
			<td></td>
			<td>Differences in sample (including coverslip)</td>
			<td>Always use the same mounting medium, coverslip (e.g. No. 1.5H) and a similar depth of focus.</td>
		</tr>
		<tr>
			<td></td>
			<td>Microscope drift since the calibration was last made</td>
			<td>Make a calibration as often as every two weeks. Keep the temperature constant, and use a floating table to avoid hardware drift of the microscope.</td>
		</tr>
	</tbody>
</table>
Table 2: Troubleshooting for chromatic correction.
<img alt="Figure 7" class="xfigimg" src="/files/ftp_upload/60800/60800fig07.jpg" /> 
Figure 7: Examples of reference images. Nuclear envelope in fission yeast cells labeled with GFP and mCherry. Images were acquired with conventional wide-field microscopy. Chromatic shifts were corrected using Chromagnon without local alignment using the images themselves as reference images. Images were then deconvolved to show the details. (A) A good example with many objects in the field of view. (B) A bad example with objects only at the top-left corner. Misalignment is obvious at a certain region of the image. (C) An undesirable example where one of the quadrisection (separated by dotted cross lines) is empty. Scale bar in panel A indicates 5 &#181;m for the full field view and 1.25 &#181;m for the enlarged view and is applicable to all panels. <a href="https://www.jove.com/files/ftp_upload/60800/60800fig07large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
In this protocol, we described three different reference types (Table 1). Among them, crosstalk reference images and biological calibration reference images need further careful discussion. For crosstalk reference images, samples stained with DAPI or Hoechst 33342, and mounted in glycerol or commercial mounting media can be efficiently used to align the blue, green, and red channels. Similarly, Alexa Fluor 488 can be used to align the green and red channels. However, obtaining crosstalk fluorescence is often difficult since many blue dyes except DAPI and Hoechst are dimmer and decay faster than most green and red dyes. Furthermore, the emission spectra of modern dyes are narrower, which makes the alignment of more than three channels by this method challenging. Attention should also be paid to some common red dyes (e.g., Alexa Flour 568 and 594, but not Alexa Fluor 555) that can be excited by violet light, which prevent obtaining high-contrast crosstalk images from blue dyes. Another drawback is that this method cannot measure the chromatic aberration of excitation light paths in multicolor excitation, because only a single excitation wavelength is used for excitation (Table 1). As most advanced microscopy uses altered illumination optics, the application of this method is limited. Still, its higher correction accuracy is sufficiently advantageous for it to be described in this protocol. In general, a crosstalk image should be taken after a target image to prevent bleaching or phototoxic effects. For SMLM observed with the wide-field mode, a reference image should be acquired before acquiring a target image as fluorescence dyes can be bleached while imaging.
Biological calibration reference images allow users to easily align any desired number of channels at the cost of additional sample preparation. Another advantage of biological calibration reference images is the availability of &#34;averaging&#34; multiple references that helps fill all fields of view. This method may suffer from differences in imaging conditions if the calibration sample is prepared on a different slide. Most of this problem can be solved if both targets and references are prepared on the same slide by using commercial chambered coverglasses (Table 1), and other imaging conditions are kept constant as in protocol step 2.3.3. In this case, a correction accuracy similar to that of crosstalk reference images can be expected3. The protocol to use phalloidin as shown here is one of the easiest ways to stain a single cellular structure with multiple colors. There are numerous possible scenarios to prepare biological calibration samples. For immunostaining, a sample can be labeled with a single primary antibody followed by staining with secondary antibodies of multiple colors. In this way, a single target structure can be labeled with multiple colors. Alternatively, 5-ethynyl-2&#39;-deoxyuridine, detected by &#34;click&#34; chemistry labels newly synthesized DNA in multiple colors at high density, as described in detail previously8. For live cells, it is useful to prepare a transgenic strain harboring two copies of a gene that are fused to GFP or mCherry to label the same structure with two colors. If the copy number of the gene is critical as often observed for membrane proteins, a single copy of the gene can be tandemly fused to GFP and mCherry (Figure 7). Photoconvertible fluorescent proteins, such as mEOS218, can also be used by illuminating a moderate level of violet light to obtain both protein species with or without photoconversion. Under low oxygen conditions, GFP can also be used as a photoconvertible protein from green to red19,20. Choosing the right calibration sample will thus make the experiment more robust.

Multicolor imaging is one of the fundamental aspects of biological fluorescence microscopy, in cases where the spatial relationship of different molecules or structures is of major interest. Chromatic aberration, an optical aberration of polychromatic light caused by dispersion, changes the apparent position of the colored objects of interest. Similarly, microscopes equipped with multiple cameras devoted to acquiring each color have more complex chromatic shifts due to differences in optical elements and imperfect alignment among the channels. Thus, such chromatic shifts may lead to a false conclusion unless explicitly corrected by the user. Although chromatic shifts have not been a major problem as long as the resolution of microscopy is limited by the classical resolution limit, recent development of super-resolution microscopy1 has prompted the need for more accurate correction of chromatic shifts.
It has been a common practice to measure chromatic shifts of microscope systems using a multicolor bead calibration slide2. The bead-based calibration method is appropriate for measuring chromatic shifts from the entire optics of the microscope towards the surface of the coverslip2. This method, however, is unable to measure chromatic shifts in the biological samples of interest. It is important to note that many biological samples are three-dimensional (3D), and the chromatic shifts of such samples are different from those at the surface of the coverslip. Furthermore, chromatic shifts change with imaging conditions2,3. We have measured the chromatic shifts in 3D biological samples and found that the uncertainty of chromatic shifts was often as much as 350 nm by the classical multicolor-bead calibration method3. Therefore, chromatic shifts need to be measured in biological samples at the depth of interest and under the imaging conditions being used.
Here, we describe procedures to measure chromatic shifts in biological samples and correct these shifts using our software, Chromagnon3. To measure chromatic shifts in biological samples, our method uses two kinds of data sets, a &#34;target&#34; image and a &#34;reference&#34; image. The &#34;target&#34; image is a multicolor image of interest, for example, images stained for DNA, nuclear envelope, and microtubules. It is often impossible to measure chromatic shifts in such an image. Therefore, we need a &#34;reference&#34; image that is dedicated to measure the chromatic shifts in the sample. The only definition of a &#34;reference&#34; image is a multicolor image of the same object. In this sense, a multicolor beads image is also a type of reference image. Here, we describe three different types of reference image that are used to measure chromatic shifts in the biological samples: &#34;crosstalk reference images&#34;, &#34;bright-field reference images&#34; and &#34;biological calibration reference images&#34;. The type of reference image depends on the type of microscope being used or the correction accuracy required as summarized in Table 1.
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td></td>
			<td>Crosstalk</td>
			<td>Bright-field</td>
			<td>Biological calibration (on a different slide)</td>
			<td>Biological calibration (on the same slide)</td>
		</tr>
		<tr>
			<td>Accuracya</td>
			<td>+++</td>
			<td>+</td>
			<td>++b</td>
			<td>+++</td>
		</tr>
		<tr>
			<td>Simplicity</td>
			<td>++</td>
			<td>+++</td>
			<td>++</td>
			<td>++</td>
		</tr>
		<tr>
			<td>Applicable microscopy</td>
			<td>Wide-field</td>
			<td>Wide-field</td>
			<td>All</td>
			<td>All</td>
		</tr>
		<tr>
			<td>Availability of local alignment</td>
			<td>+</td>
			<td>+</td>
			<td>-c</td>
			<td>-c</td>
		</tr>
		<tr>
			<td colspan="5">a: Number of &#34;+&#34; indicates increasing rating. Single plus is about 50 nm and three plus is about 15 nm in 3D. 
			b: The accuracy depends on how much the variable imaging conditions are kept constant. 
			c: Local calibration measured by multicolor bead samples can be combined as described in protocol section 4.</td>
		</tr>
	</tbody>
</table>
Table 1: Parameters when choosing the type of reference images.
&#34;Crosstalk reference images&#34; have the highest correction accuracy and are relatively simple to accomplish3,4 (Table 1). The drawback is their limitation in microscopy applications due to their incapability of measuring chromatic shifts in excitation paths. Also, to obtain such images, the microscope should be equipped with multiband dichroic mirrors, and emission filters that are independently controlled from the excitation filters or light sources. Suitable microscopy includes conventional wide-field microscopy, single molecule localization microscopy (SMLM) such as photo-activated localization microscopy/stochastic optical reconstruction microscopy (PALM/STORM)5,6 and expansion microscopy7 observed with wide-field microscopy. A crosstalk reference image is acquired from the target sample itself. It is an image of crosstalk (bleed-through) fluorescence of a dye obtained in all required channels. Fluorescence emission always expands towards the longer wavelengths, therefore dyes with the shortest emission wavelength are excited to obtain crosstalk fluorescence in channels of longer wavelengths. For example, when the sample is stained with blue, green, and red, only the blue dye is excited, and the emission light is obtained in the blue, green, and red channels. In this protocol, DNA stained with 4&#8242;,6-diamidino-2-phenylindole (DAPI) was used to obtain crosstalk fluorescence.
&#34;Bright-field reference images&#34; are an easier and less phototoxic alternative to &#34;crosstalk reference images&#34; but are the least accurate3 (Table 1). These are bright field images of the target sample, acquired in all the color channels used in the target image.
&#34;Biological calibration reference images&#34; have the advantage of being applicable to any type of microscopy due to their ability to measure the chromatic shifts both in the excitation and emission paths3,8 (Table 1). Suitable microscopy includes wide-field microscopy, confocal microscopy, light sheet microscopy, stimulated emission depletion (STED)9, structured illumination microscopy (SIM)10, Airyscan/SORA11,12, SMLM observed with the total internal reflection fluorescence (TIRF) mode, Olympus super resolution (OSR)13, and so forth. A biological calibration reference image is acquired from a calibration sample similarly prepared as the target sample, but with staining of a single structure with multiple colors. The correction accuracy excels the resolution of most super-resolution microscopy and preparing a biological calibration sample can be relatively simple. Another advantage is the availability to &#34;average&#34; multiple reference images. Therefore, even though the individual images contain poor information for the measurement of chromatic shifts, the information content can be increased by averaging multiple images. The accuracy depends on how much the imaging conditions are kept constant. In this regard, the best performance is obtained when both target and reference samples are on the same slide, using, for example, 8-well chambered coverglasses (Table 1, right-most). In this protocol, actin stained with three colors of phalloidin was used as a biological calibration.
Once a reference image is obtained, then the chromatic shift is measured and corrected by our software Chromagnon. There is no limitation on the number of channels, Z sections and time frames that Chromagnon can measure and correct the chromatic shifts for. Chromagnon measures chromatic shifts in two steps. The first step acquires the &#34;global&#34; or &#34;affine&#34; alignment parameters of translation in the X, Y, Z axes, magnification along the X, Y, Z axes, and rotation around the Z axis. The calculation accuracy of the global alignment is ~16 nm in 3D and ~8 nm in 2D. The second step is an optional 2D iterative &#34;local alignment&#34; on projected images to obtain a higher accuracy. In the local alignment process, the images are subdivided into multiple regions and chromatic shifts in these local regions are measured. Subsequently, the regions are further divided and chromatic shifts in the subregions are measured iteratively until the number of pixels in the region reaches the minimum number of pixels (usually 60 x 60 pixels). The resulting local alignment map is combined with the global alignment parameter and is applied to the target image by an elastic transformation. Following this step, the calculation accuracy is improved to ~14 nm in 3D and ~6 nm in 2D. The local alignment is not suitable for biological calibration reference images because biological structure in the reference is different from that in the target (Table 1). Therefore, only global alignment is used for biological calibration reference images.
The local chromatic shifts originate from two sources; microscope instrumental local distortion and biological structural inhomogeneity. Because microscope instrumental local distortion is constant, this can be measured from the multicolor beads reference sample and corrected as a fixed parameter. Chromagnon can combine the microscope instrumental local distortion map and the global alignment parameters from the biological calibrations (Table 1). Using this method, it is expected that the average accuracy of biological calibration will be improved by an additional 1&#8722;2 nm.
Here, we describe a protocol to correct the chromatic shifts of 3D fluorescence images using our software Chromagnon, from the easiest low end to the highest accuracy. We use immunostaining of HeLa cells as an example and observed them using 3D wide-field microscopy and 3D-SIM. In the first section, we describe how to prepare target samples and biological calibration samples. This part of the protocol should be optimized for the specific targets of the research. In the second section, we describe the acquisition methods for three kinds of reference images by microscopes. The assumption was to obtain blue, green, and red channels but channel composition should be modified by the specific targets of the research and by the setups of the microscope. It does not matter if the microscope is equipped with a single camera or multiple cameras. In the third section, we describe how one can use our software to measure and correct chromatic shifts of the target image by using reference images. Finally, in the fourth section, we describe a method to complement the biological calibration reference images by using a microscope&#39;s instrumental local calibration.

<table>
	<tbody>
		<tr>
			<td>16% formaldehyde solution</td>
			<td>Polyscience</td>
			<td>18814-10</td>
			<td></td>
		</tr>
		<tr>
			<td>35 mm glass-bottom dish</td>
			<td>MatTek</td>
			<td>P35G-1.5-10-C</td>
			<td></td>
		</tr>
		<tr>
			<td>Alexa Fluor 405 phalloidin</td>
			<td>Thermo Fisher Scientific</td>
			<td>A30104</td>
			<td></td>
		</tr>
		<tr>
			<td>Alexa Fluor 488 phalloidin</td>
			<td>Thermo Fisher Scientific</td>
			<td>A12379</td>
			<td></td>
		</tr>
		<tr>
			<td>Alexa Fluor 594 phalloidin</td>
			<td>Thermo Fisher Scientific</td>
			<td>A12381</td>
			<td></td>
		</tr>
		<tr>
			<td>Bovine Serum</td>
			<td>Thermo Fisher Scientific</td>
			<td>16170078</td>
			<td></td>
		</tr>
		<tr>
			<td>Coverslip</td>
			<td>Matsunami</td>
			<td>No. 1S HT</td>
			<td></td>
		</tr>
		<tr>
			<td>DAPI (4&#39;,6-Diamidino-2-Phenylindole, Dihydrochloride)</td>
			<td>Thermo Fisher Scientific</td>
			<td>D1306</td>
			<td></td>
		</tr>
		<tr>
			<td>Dulbecco&#8217;s Modified Eagle Medium with L-Gln and sodium pyruvate</td>
			<td>Nacalai Tesque</td>
			<td>08458-16</td>
			<td></td>
		</tr>
		<tr>
			<td>Mounting medium (VECTASHIELD)</td>
			<td>Vector Laboratories</td>
			<td>H-1000</td>
			<td></td>
		</tr>
		<tr>
			<td>Mouse anti-tubulin monoclonal antibody (TAT1)</td>
			<td></td>
			<td></td>
			<td>Described in Ref 15.</td>
		</tr>
		<tr>
			<td>Nunc Lab-Tek II chambered coverglass (8 well)</td>
			<td>Thermo Fisher Scientific</td>
			<td>155409</td>
			<td></td>
		</tr>
		<tr>
			<td>Rabbit anti-emerin polyclonal antibody (ED1)</td>
			<td></td>
			<td></td>
			<td>A gift from Hiroshi Yorifuji, Gunma University, Gunma, Japan and Kiichi Arahata, National Center of Neurology and Psychiatry, Tokyo, Japan; deceased.</td>
		</tr>
		<tr>
			<td>Secondary antibody with Alexa Fluor 488</td>
			<td>Thermo Fisher Scientific</td>
			<td>A-11034</td>
			<td></td>
		</tr>
		<tr>
			<td>Secondary antibody with Alexa Fluor 555</td>
			<td>Thermo Fisher Scientific</td>
			<td>A-21424</td>
			<td></td>
		</tr>
		<tr>
			<td>Secondary antibody with Alexa Fluor 594</td>
			<td>Thermo Fisher Scientific</td>
			<td>A-11032</td>
			<td></td>
		</tr>
		<tr>
			<td>TetraSpeck Microspheres, 0.2 &#181;m</td>
			<td>Thermo Fisher Scientific</td>
			<td>T7280</td>
			<td></td>
		</tr>
	</tbody>
</table>

high-accuracy correction of 3d chromatic shifts in the age of super-resolution biological imaging using chromagnon

Quantitative multicolor fluorescence microscopy relies on the careful spatial matching of color channels acquired at different wavelengths. Due to chromatic aberration and the imperfect alignment of cameras, images acquired in each channel may be shifted, and magnified, as well as rotated relative to each other in any of the three dimensions. With the classical calibration method, chromatic shifts are measured by multicolor beads attached to the surface of a coverslip, and a number of software are available to measure the chromatic shifts from such calibration samples. However, chromatic aberration can vary with depth, change with observation conditions and be induced by the biological sample itself, thus hindering determination of the true amount of chromatic shift in the sample of interest and across the volume. Correcting chromatic shifts at higher accuracy is particularly relevant for super-resolution microscopy where only slight chromatic shifts may affect quantitative analyses and alter the interpretation of multicolor images. We have developed an open-source software Chromagnon and accompanying methods to measure and correct 3D chromatic shifts in biological samples. Here we provide a detailed application protocol that includes special requirements for sample preparation, data acquisition, and software processing to measure chromatic shifts in biological samples of interest.

An example of chromatic shift correction using a crosstalk reference image is shown in Figure 5. The image was obtained with a wide-field microscope equipped with a single camera. Fluorescence emission from DAPI was used as a reference (Figure 5A,B) to correct the blue, green, and red channels. The image comprises 3 channels of 60 Z slices, each composed of 256 x 256 pixels. The images were deconvolved before measuring the chromatic shifts. Measuring the local chromatic shifts using Chromagnon took 51 s on a Mac with Intel Core i7 (quad core, 8-threads, 2.7 GHz), 16 GB RAM and 1 TB flash storage. The alignment parameter was applied to the target image (Figure 5C,D), which has exactly the same number of voxels as the reference image. Preparing the aligned file took 3 s. As a result of trimming the edge pixels during the alignment process (crop margins checkbox in Figure 1C), the number of voxels was reduced after alignment (Figure 5B, 51 Z slices, 252 x 251 pixels). DNA in the anaphase bridge (indicated by arrowheads) is seen incorrectly outside of the nuclear envelope before alignment (Figure 5C, obvious in the bottom panel showing the XZ view), but as expected inside the envelope after alignment (Figure 5D).
An example of chromatic shift correction using a biological calibration reference image is shown in Figure 6. The images were obtained with a SIM microscope equipped with three cameras. Three images of HeLa cells stained with phalloidins conjugated to blue, green, and red dyes were averaged (Figure 6A). The reference image comprises 3 channels of 76 Z slices, each composed of 1,024 x 1,024 pixels. Measuring chromatic shifts using Chromagnon without local alignment required 194 s on the Mac system described above. The parameter was applied to a target image consisting of 3 channels of 73 Z slices, each composed of 1,024 x 1,024 pixels. Generation of the aligned file took 25 s. The XZ view shows incorrect channel positions along the Z, and slightly along the X directions (Figure 6A,C) but this misregistration was corrected after alignment (Figure 6B,D).
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/60800/60800fig05.jpg" /> 
Figure 5: An example of alignment with a crosstalk reference image. HeLa cells were stained with DAPI for DNA (shown in magenta), Alexa Fluor 488 (shown in yellow) for nuclear envelope, and Alexa Fluor 555 (shown in blue) for microtubules. Images were acquired by 3D wide-field microscopy with a single camera and deconvolved. (A,B) A representative crosstalk reference image using DAPI emission, before and after alignment by Chromagnon. Three color channels are shown as overlaid. (C,D) An optical section of the 3D stack in three channels before and after alignment. Axial chromatic aberration is obvious at the anaphase bridge shown by arrowheads. Scale bar in panel A indicates 5 &#181;m for all panels. <a href="https://www.jove.com/files/ftp_upload/60800/60800fig05large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 6" class="xfigimg" src="/files/ftp_upload/60800/60800fig06.jpg" /> 
Figure 6: An example of alignment with a biological calibration reference image Images were acquired with 3D-SIM equipped with three cameras. (A,B) A reference image averaged from three images before (A) and after (B) alignment. HeLa cells were stained with phalloidin conjugated with Alexa Fluor 405, 488 or 594. (C,D) The target image before (C) and after (D) alignment. HeLa cells were stained with DAPI for DNA (shown in magenta), Alexa Fluor 488 (shown in yellow) for nuclear envelope, and Alexa Fluor 594 (shown in blue) for microtubules. Scale bar in panel A indicates 5 &#181;m for all panels. <a href="https://www.jove.com/files/ftp_upload/60800/60800fig06large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

Watch this Scientific Journal Video about High-Accuracy Correction of 3D Chromatic Shifts in the Age of Super-Resolution Biological Imaging Using Chromagnon at JoVE.com

High-Accuracy Correction of 3D Chromatic Shifts in the Age of Super-Resolution Biological Imaging Using Chromagnon

Correction of chromatic shifts in three-dimensional (3D) multicolor fluorescence microscopy images is crucial for quantitative data analyses. This protocol is developed to measure and correct chromatic shifts in biological samples through acquisition of suitable reference images and processing with the open-source software, Chromagnon.

High-Accuracy Correction of 3D Chromatic Shifts in the Age of Super-Resolution Biological Imaging Using Chromagnon

Quantitative multicolor fluorescence microscopy relies on the careful spatial matching of color channels acquired at different wavelengths. Due to ...

high-accuracy-correction-3d-chromatic-shifts-age-super-resolution

Research

JoVE Journal

Biology

7.3K Views.  National Institute of Information and Communications Technology. Correction of chromatic shifts in three-dimensional (3D) multicolor fluorescence microscopy images is crucial for quantitative data analyses. This protocol is developed to measure and correct chromatic shifts in biological samples through acquisition of suitable reference images and processing with the open-source software, Chromagnon.

Video: High-Accuracy Correction of 3D Chromatic Shifts in the Age of Super-Resolution Biological Imaging Using Chromagnon

A Novel RFP Reporter to Aid in the Visualization of the Eye Imaginal Disc in Drosophila

The Drosophila eye is a powerful model system for studying areas such as neurogenesis, signal transduction and neurodegeneration. Many of the discoveries made using this system have taken advantage of the spatiotemporal nature of photoreceptor differentiation in the developing eye imaginal disc. To use this system it is first necessary for the researcher to learn to identify and dissect the eye disc. We describe a novel RFP reporter to aid in the identification of the eye disc and the visualization of specific cell types in the developing eye. We detail a methodology for dissection of the eye imaginal disc from third instar larvae and describe how the eye-RFP reporter can aid in this dissection. This eye-RFP reporter is only expressed in the eye and can be visualized using fluorescence microscopy either in live tissue or after fixation without the need for signal amplification. We also show how this reporter can be used to identify specific cells types within the eye disc. This protocol and the use of the eye-RFP reporter will aid researchers using the Drosophila eye to address fundamentally important biological questions.

A Novel RFP Reporter to Aid in the Visualization of the Eye Imaginal Disc in Drosophila

We describe a novel red fluorescent protein (RFP) reporter that is expressed specifically in the Drosophila eye. We detail a methodology for dissection of the eye imaginal disc and how this reporter can be used to aid in the dissection and identification of specific cell types in the developing eye.

The Drosophila eye is a powerful model system for studying areas such as neurogenesis, signal transduction and neurodegeneration. Many of the discoveries ...

Studying Age-dependent Genomic Instability using the S. cerevisiae Chronological Lifespan Model

Studies using the Saccharomyces cerevisiae aging model have uncovered life span regulatory pathways that are partially conserved in higher eukaryotes1-2. The simplicity and power of the yeast aging model can also be explored to study DNA damage and genome maintenance as well as their contributions to diseases during aging. Here, we describe a system to study age-dependent DNA mutations, including base substitutions, frame-shift mutations, gross chromosomal rearrangements, and homologous/homeologous recombination, as well as nuclear DNA repair activity by combining the yeast chronological life span with simple DNA damage and mutation assays. The methods described here should facilitate the identification of genes/pathways that regulate genomic instability and the mechanisms that underlie age-dependent DNA mutations and cancer in mammals.

Studying Age-dependent Genomic Instability using the S. cerevisiae Chronological Lifespan Model

Here we describe a set of DNA mutation assays that can be combined with the yeast chronological life span model to study the genes/pathways that regulate or contribute to genomic DNA instability during aging.

Studies using the Saccharomyces cerevisiae aging model have uncovered life span regulatory pathways that are partially conserved in higher eukaryotes1-2. ...

Super-resolution Imaging of the Bacterial Division Machinery

Bacterial cell division requires the coordinated assembly of more than ten essential proteins at midcell1,2. Central to this process is the formation of a ring-like suprastructure (Z-ring) by the FtsZ protein at the division plan3,4. The Z-ring consists of multiple single-stranded FtsZ protofilaments, and understanding the arrangement of the protofilaments inside the Z-ring will provide insight into the mechanism of Z-ring assembly and its function as a force generator5,6. This information has remained elusive due to current limitations in conventional fluorescence microscopy and electron microscopy. Conventional fluorescence microscopy is unable to provide a high-resolution image of the Z-ring due to the diffraction limit of light (~200 nm). Electron cryotomographic imaging has detected scattered FtsZ protofilaments in small C. crescentus cells7, but is difficult to apply to larger cells such as E. coli or B. subtilis. Here we describe the application of a super-resolution fluorescence microscopy method, Photoactivated Localization Microscopy (PALM), to quantitatively characterize the structural organization of the E. coli Z-ring8.
	PALM imaging offers both high spatial resolution (~35 nm) and specific labeling to enable unambiguous identification of target proteins. We labeled FtsZ with the photoactivatable fluorescent protein mEos2, which switches from green fluorescence (excitation = 488 nm) to red fluorescence (excitation = 561 nm) upon activation at 405 nm9. During a PALM experiment, single FtsZ-mEos2 molecules are stochastically activated and the corresponding centroid positions of the single molecules are determined with &lt;20 nm precision. A super-resolution image of the Z-ring is then reconstructed by superimposing the centroid positions of all detected FtsZ-mEos2 molecules.
	Using this method, we found that the Z-ring has a fixed width of ~100 nm and is composed of a loose bundle of FtsZ protofilaments that overlap with each other in three dimensions. These data provide a springboard for further investigations of the cell cycle dependent changes of the Z-ring10 and can be applied to other proteins of interest.

We describe a super-resolution imaging method to probe the structural organization of the bacterial FtsZ-ring, an essential apparatus for cell division. This method is based on quantitative analyses of photoactivated localization microscopy (PALM) images and can be applied to other bacterial cytoskeletal proteins.

Bacterial cell division requires the coordinated  assembly of more than ten essential proteins at midcell1,2. Central  to this process is the formation of ...

Imaging and 3D Reconstruction of Cerebrovascular Structures in Embryonic Zebrafish

Zebrafish are a powerful tool to study developmental biology and pathology in vivo. The small size and relative transparency of zebrafish embryos make them particularly useful for the visual examination of processes such as heart and vascular development. In several recent studies transgenic zebrafish that express EGFP in vascular endothelial cells were used to image and analyze complex vascular networks in the brain and retina, using confocal microscopy. Descriptions are provided to prepare, treat and image zebrafish embryos that express enhanced green fluorescent protein (EGFP), and then generate comprehensive 3D renderings of the cerebrovascular system. Protocols include the treatment of embryos, confocal imaging, and fixation protocols that preserve EGFP fluorescence. Further, useful tips on obtaining high-quality images of cerebrovascular structures, such as removal the eye without damaging nearby neural tissue are provided. Potential pitfalls with confocal imaging are discussed, along with the steps necessary to generate 3D reconstructions from confocal image stacks using freely available open source software.

Imaging of cerebrovascular development in larval zebrafish is described. Techniques to facilitate 3D imaging and modify cerebrovascular development using chemical treatments are also provided.

Zebrafish are a powerful tool to study developmental biology and pathology in vivo.  The small size and relative transparency of zebrafish embryos make ...

Test Samples for Optimizing STORM Super-Resolution Microscopy

STORM is a recently developed super-resolution microscopy technique with up to 10 times better resolution than standard fluorescence microscopy techniques. However, as the image is acquired in a very different way than normal, by building up an image molecule-by-molecule, there are some significant challenges for users in trying to optimize their image acquisition. In order to aid this process and gain more insight into how STORM works we present the preparation of 3 test samples and the methodology of acquiring and processing STORM super-resolution images with typical resolutions of between 30-50 nm. By combining the test samples with the use of the freely available rainSTORM processing software it is possible to obtain a great deal of information about image quality and resolution. Using these metrics it is then possible to optimize the imaging procedure from the optics, to sample preparation, dye choice, buffer conditions, and image acquisition settings. We also show examples of some common problems that result in poor image quality, such as lateral drift, where the sample moves during image acquisition and density related problems resulting in the 'mislocalization' phenomenon.

We describe the preparation of three test samples and how they can be used to optimize and assess the performance of STORM microscopes. Using these examples we show how to acquire raw data and then process it to acquire super-resolution images in cells of approximately 30-50 nm resolution.

STORM is a recently developed super-resolution microscopy technique with up to 10 times better resolution than standard fluorescence microscopy ...

Sample Preparation for Single Virion Atomic Force Microscopy and Super-resolution Fluorescence Imaging

Immobilization of virions to glass surfaces is a critical step in single virion imaging. Here we present a technique&#160;adopted from single molecule imaging assays which allows adhesion of single virions to glass surfaces with specificity. This preparation is based on grafting the surface of the glass with a mixture of PLL-g-PEG and PLL-g-PEG-Biotin, adding a layer of avidin, and finally creating virion anchors through attachment of biotinylated virus specific antibodies. We have applied this technique across a range of experiments including atomic force microscopy (AFM) and super-resolution fluorescence imaging. This sample preparation method results in a control adhesion of the virions to the surface.

The attachment of virions to a surface is a requirement for single virion imaging by Super-resolution fluorescence imaging or atomic force microscopy (AFM). Here we demonstrate a sample preparation method for controlled adhesion of virions to glass surfaces suitable for use in AFM and super-resolution fluorescence imaging.

Immobilization of virions to glass surfaces is a critical step in single virion imaging. Here we present a technique&#160;adopted from single molecule ...

Super-resolution Imaging of the Cytokinetic Z Ring in Live Bacteria Using Fast 3D-Structured Illumination Microscopy (f3D-SIM)

Imaging of biological samples using fluorescence microscopy has advanced substantially with new technologies to overcome the resolution barrier of the diffraction of light allowing super-resolution of live samples. There are currently three main types of super-resolution techniques &#8211; stimulated emission depletion (STED), single-molecule localization microscopy (including techniques such as PALM, STORM, and GDSIM), and structured illumination microscopy (SIM). While STED and single-molecule localization techniques show the largest increases in resolution, they have been slower to offer increased speeds of image acquisition. Three-dimensional SIM (3D-SIM) is a wide-field fluorescence microscopy technique that offers a number of advantages over both single-molecule localization and STED. Resolution is improved, with typical lateral and axial resolutions of 110 and 280 nm, respectively and depth of sampling of up to 30 &#181;m from the coverslip, allowing for imaging of whole cells. Recent advancements (fast 3D-SIM) in the technology increasing the capture rate of raw images allows for fast capture of biological processes occurring in seconds, while significantly reducing photo-toxicity and photobleaching. Here we describe the use of one such method to image bacterial cells harboring the fluorescently-labelled cytokinetic FtsZ protein to show how cells are analyzed and the type of unique information that this technique can provide.

Super-resolution Imaging of the Cytokinetic Z Ring in Live Bacteria Using Fast 3D-Structured Illumination Microscopy f3D-SIM

Spatiotemporal information about dynamic proteins inside live cells is crucial for understanding biology. A type of super-resolution microscopy called fast 3D-structured illumination microscopy (f3D-SIM) reveals unique information about the cytokinetic Z ring in bacteria: both its bead-like appearance and the rapid dynamics of FtsZ within the ring.

Imaging of biological samples using fluorescence microscopy has advanced substantially with new technologies to overcome the resolution barrier of the ...

High-resolution Time-lapse Imaging and Automated Analysis of Microtubule Dynamics in Living Human Umbilical Vein Endothelial Cells

The physiological process by which new vasculature forms from existing vasculature requires specific signaling events that trigger morphological changes within individual endothelial cells (ECs). These processes are critical for homeostatic maintenance such as wound healing, and are also crucial in promoting tumor growth and metastasis. EC morphology is defined by the organization of the cytoskeleton, a tightly regulated system of actin and microtubule (MT) dynamics that is known to control EC branching, polarity and directional migration, essential components of angiogenesis. To study MT dynamics, we used high-resolution fluorescence microscopy coupled with computational image analysis of fluorescently-labeled MT plus-ends to investigate MT growth dynamics and the regulation of EC branching morphology and directional migration. Time-lapse imaging of living Human Umbilical Vein Endothelial Cells (HUVECs) was performed following transfection with fluorescently-labeled MT End Binding protein 3 (EB3) and Mitotic Centromere Associated Kinesin (MCAK)-specific cDNA constructs to evaluate effects on MT dynamics. PlusTipTracker software was used to track EB3-labeled MT plus ends in order to measure MT growth speeds and MT growth lifetimes in time-lapse images. This methodology allows for the study of MT dynamics and the identification of how localized regulation of MT dynamics within sub-cellular regions contributes to the angiogenic processes of EC branching and migration.

Protocols for Human Umbilical Vein Endothelial Cell (HUVEC) culture, transient transfection of fluorescently-labeled markers of microtubule growth, live-cell imaging and automated analysis of interphase microtubule growth dynamics are detailed.

The physiological process by which new vasculature forms from existing vasculature requires specific signaling events that trigger morphological changes ...

Open-source Single-particle Analysis for Super-resolution Microscopy with VirusMapper

Super-resolution fluorescence microscopy is currently revolutionizing cell biology research. Its capacity to break the resolution limit of around 300 nm allows for the routine imaging of nanoscale biological complexes and processes. This increase in resolution also means that methods popular in electron microscopy, such as single-particle analysis, can readily be applied to super-resolution fluorescence microscopy. By combining this analytical approach with super-resolution optical imaging, it becomes possible to take advantage of the molecule-specific labeling capacity of fluorescence microscopy to generate structural maps of molecular elements within a metastable structure. To this end, we have developed a novel algorithm &#8212; VirusMapper &#8212; packaged as an easy-to-use, high-performance, and high-throughput ImageJ plugin. This article presents an in-depth guide to this software, showcasing its ability to uncover novel structural features in biological molecular complexes. Here, we present how to assemble compatible data and provide a step-by-step protocol on how to use this algorithm to apply single-particle analysis to super-resolution images.

This manuscript uses the Fiji-based open-source software package VirusMapper to apply single-particle analysis to super-resolution microscopy images in order to generate precise models of nanoscale structure.

Super-resolution fluorescence microscopy is currently revolutionizing cell biology research. Its capacity to break the resolution limit of around 300 nm ...

Ground State Depletion Super-resolution Imaging in Mammalian Cells

Advances in fluorescent microscopy and cell biology are intimately correlated, with the enhanced ability to visualize cellular events often leading to dramatic leaps in our understanding of how cells function. The development and availability of super-resolution microscopy has considerably extended the limits of optical resolution from ~250-20 nm. Biologists are no longer limited to describing molecular interactions in terms of colocalization within a diffraction limited area, rather it is now possible to visualize the dynamic interactions of individual molecules. Here, we outline a protocol for the visualization and quantification of cellular proteins by ground-state depletion microscopy&#160;for fixed cell imaging. We provide examples from two different membrane proteins, an element of the endoplasmic reticulum translocon, sec61&#946;, and a plasma membrane-localized voltage-gated L-type Ca2+ channel (CaV1.2). Discussed are the specific microscope parameters, fixation methods, photo-switching buffer formulation, and pitfalls and challenges of image processing.

This article outlines a protocol for the detection of one or more plasma and/or intracellular membrane proteins using Ground State Depletion (GSD) super-resolution microscopy in mammalian cells. Here, we discuss the benefits and considerations of using such approaches for the visualization and quantification of cellular proteins.

Advances in fluorescent microscopy and cell biology are intimately correlated, with the enhanced ability to visualize cellular events often leading to ...