D.K.V and A.R thank the Manipal Academy of Higher Education for the TMA Pai fellowship. We thank the Science and Engineering Research Board of India for SERB-SRG (#SRG/2021/001315), as well as the Indian Council of Medical Research of India (#5/4-5/Ad-hoc/Neuro/216/2020-NCD-I) and the Intramural fund of Manipal Academy of Higher Education, Manipal, India. We thank JNCASR&#39;s (Jawaharlal Nehru Centre for Advanced Scientific Research, India) confocal facility and B. Suma for the confocal microscopy in JNCASR.

NOTE: SH-SY5Y cells cultured in DMEM/F-12 media were differentiated with 10 &#181;M retinoic acid for 7 days and treated with 1 &#181;M oA&#946; oligomers for 2 h at 37 &#176;C (5% CO2). After treatment, the cells were fixed with Karnovsky&#39;s fixative solution and double-immunostained with phospho-PAK1 (Thr423)/PAK2 (Thr402) antibody and F-actin-binding phalloidin. Later, confocal z-stack images were taken using a confocal laser scanning microscope. The TNTs were quantified by manual counting and distinguished from other neurites/cell protrusions by constructing 3D volume view images and identifying the structures from their characteristic of hovering between two cells without touching the substratum (Figure 1).
1. Cell culture and differentiation
<ol>
	<li>Culture the SH-SY5Y neuronal cells in DMEM/F12 (Ham&#39;s) media 1:1 with 10% fetal bovine serum (FBS) and 1% penicillin-streptomycin-neomycin mixture (PSN). Seed the cells in a 35 mm imaging dish with a 14 mm well made up of a #1.5 coverslip at the center of the dish attached to the bottom. Seed the cells on the imaging dish at a concentration of 12,000 cells/cm2 and perform the experiments at 60%-70% confluency.</li>
	<li>Partially differentiate the cells with 10 &#181;M retinoic acid (RA) from a 100 mM stock solution (5 mg of RA in 15 mL of dimethyl sulfoxide [DMSO]). Then, incubate the cells for 7 days at 37 &#176;C (5% CO2) for differentiation with media change every 2 days. 
	NOTE: Be careful about maintaining the confluency (60%-70%) of the cells (both undifferentiated and partially differentiated cells). Cell density can influence the formation of TNTs between the cells.</li>
</ol>
2. Preparation of oligomers of amyloid-&#946;1-42 (oA&#946;) to treat neuronal cells
<ol>
	<li>Dissolve A&#946;1-42 (1 mg) in 200 &#181;L of 1,1,1,3,3,3-hexafluoro-2-propanol and divide the solution into 20 aliquots, each containing 0.05 mg of peptides. Lyophilize and store the aliquots at &#8722;20 &#176;C for later use.</li>
	<li>Prepare the stock solution (5 mM) of the lyophilized A&#946;1-42 in DMSO by adding 2.2 &#181;L of DMSO to 0.05 mg of lyophilized peptide. To carefully dissolve the peptides, vortex the solution and sonicate for 2 min in a water bath sonicator.</li>
	<li>Dilute the stock solution to a concentration of 100 &#181;M in DMEM, pH 7.4, and vortex to convert the peptides to monomers, followed by incubation at 4 &#176;C for 24 h to obtain oligomers of A&#946;1-42 (oA&#946;)12,21,22.</li>
	<li>Characterize oA&#946; before the experiments as reported previously21,22 by transmission electron microscopy imaging.</li>
	<li>Treat the partially differentiated SH-SY5Y cells with 1 &#181;M oA&#946;. Remove the medium before the treatments, and add fresh FBS-free DMEM. After the medium change, add previously prepared oA&#946; (100 &#181;M) to the medium to a final concentration of 1 &#181;M. Incubate the cells with 1 &#181;M oA&#946; for 2 h at 37 &#176;C (5% CO2). Include a negative control in the form of untreated cells.</li>
</ol>
3. Immunostaining of F-actin and activated-PAK1 for the characterization of TNTs
<ol>
	<li>Perform differential immunostaining by using phospho-PAK1 (Thr423)/PAK2 (Thr402) antibody and F-actin-binding phallotoxin phalloidin.</li>
	<li>Wash the control and oA&#946;-treated cells with 1x phosphate-buffered saline (PBS) for 2 x 2 min before fixation. Prepare the Karnovsky&#39;s fixative solution by using 2% formalin fixative and 2.5% glutaraldehyde dissolved in 0.1 M phosphate buffer, pH 7.2. Then, fix the cells in the imaging dish by adding Karnovsky&#39;s fixative solution (just enough to cover the cells) for 45 min at room temperature.</li>
	<li>Wash the fixed cells 2 x 2 min using incubation buffer. Prepare the incubation buffer (20x) by dissolving 0.1 g of saponin in 5 mL of FBS and dilute to 1x by adding 95 mL of 1x PBS.</li>
	<li>After fixation, add the first antibody against phopho-PAK1 at a dilution of 1:250 in the incubation buffer and incubate overnight at 4 &#176;C in a dark moist chamber.</li>
	<li>The next day, after 24 h of incubation, wash the cells 2 x 2 min with the incubation buffer; then, add secondary antibody conjugated to Alexa Fluor 488 (1:1,000 dilution) and Phalloidin 555 (1:1,000 dilution). Incubate the cells in the dark moist chamber for 1.5 h at room temperature.</li>
	<li>After the incubation, wash the cells 2 x 2 min with incubation buffer. Stain the nucleus by adding 4&#39;,6-diamidino-2-phenylindole (DAPI) in a 1:2,000 dilution and incubate for 5 min to 10 min at room temperature in the dark.</li>
	<li>Prepare DABCO mounting medium using 25 mg of DABCO in 90% glycerol and 10% 1x PBS. To dissolve properly, adjust the pH to 8.6 using spectrophotometric grade, dilute HCl (diluted 1:20 with water) and keep the solution on a rocker for mixing.</li>
	<li>As an anti-bleaching agent, add the DABCO mounting medium directly onto the imaging dish containing the coverslip at the bottom. Wait for at least 1-2 h and directly proceed to perform confocal imaging. 
	NOTE: No adhesives are required to fix the coverslips.</li>
</ol>
4. Immunostaining of F-actin and &#946;-III tubulin to distinguish TNTs from neurites
<ol>
	<li>Perform differential immunostaining with &#946;-III tubulin antibody and F-actin-binding phallotoxin phalloidin.</li>
	<li>Wash the oA&#946;-treated cells 2x with 1x PBS before adding Karnovsky&#39;s fixative solution. Incubate the cells for 45 min at room temperature and wash the cells 2 x 2 min with incubation buffer.</li>
	<li>After fixation, add the antibody against &#946;-III tubulin (TUBb3) at a dilution of 1:250 in the incubation buffer and incubate at 4 &#176;C overnight in the dark moist chamber.</li>
	<li>The next day, wash the cells with incubation buffer (2 x 2 min), and add secondary antibody conjugated to Alexa Fluor 488 (1:1,000 dilution) and Phalloidin 555 (1:1,000 dilution) together to the same dish. Then, incubate the cells for 1.5 h at room temperature in the dark moist chamber.</li>
	<li>Wash the cells 2x with incubation buffer, and add nuclear-staining DAPI in a 1:2,000 dilution for 5-10 min at room temperature in the dark.</li>
	<li>Add anti-bleaching agent DABCO in mounting medium as mentioned above and wait for 2 h before imaging.</li>
</ol>
5. Imaging with confocal microscopy
<ol>
	<li>To identify TNTs, capture z-stack images of immunostained cells using a confocal laser scanning microscope. Take the images using 40x/1.40 Oil DIC objective with DAPI, fluorescein isothiocyanate (FITC), and tetramethylrhodamine (TRITC) filter sets.</li>
	<li>First, select the channels by clicking the required lasers sequentially in the windows Track 1, Track 2, and Track 3 in the confocal software. Click the option T-PMT below the Track 1 window to take the differential interference contrast (DIC) images with fluorescence channels. 
	NOTE: DIC images are captured by a different detector labeled as T-PMT.</li>
	<li>Select the acquisition tab of the software, click on the Z-stack tab, and wait for a window to open. Then, click live scan to focus the cells at the bottom of the dish. Select that focused image as the first stack. Then, focus up to see the topmost part of the cell and select that as the last stack. Stop live scanning and click the number next to the optimal tab to fix the step size of the stacks. Step size determines the number of slices and the intervals based on the thickness of the cells. 
	NOTE: Step size will be selected based on Nyquist sampling to take enough slices and ensure there are no gaps between the two stacks. Nyquist sampling is determined on the basis of the objective and the wavelengths of the lights23.</li>
	<li>Take sequential images of three channels of DAPI, FITC, and TRITC with 405 nm, 488 nm, and 561 nm lasers and capture with a pixel dwell time of 1.02 &#181;s. Capture images in the DIC channel with fluorescence channels to observe the cell boundary.</li>
	<li>Capture a stack of images with the dimensions of x: 224.92 &#181;m&#160;and y: 224.92 &#181;m, with each pixel of 220 nm2 size and z-scaling of 415 nm.</li>
	<li>Take images capturing several z-stacks (15-22 stacks) from the bottom to the top of the cells. Acquire at least 10 images from the random field of the culture dish to get a total of ~200-300 cells.</li>
	<li>Analyze the captured images offline to identify the TNTs by 3D volume view analysis</li>
</ol>
6. Analysis of confocal z-stack images to identify and quantify TNTs
<ol>
	<li>Open the confocal images saved in .czi data format in Fiji software for analysis.</li>
	<li>Select the Hyperstack option to see each z-stack and channel of the image. Look for the hyperstacks of the z-stacks and channels, which open in a single window as shown in Figure 2. Scroll the channel (indicated by red and green arrows) and z-stack (indicated by blue arrows) scroll bars to select the exact stack of a particular channel of interest. 
	NOTE: In fixed cells, as the hovering TNTs or membrane conduits stay above the surface, the structures are not visible in the lower parts of the z-stacks. However, in fixed cells, neurites lie on the surface and are detectable in the lower parts of the z-stacks (z = 0 to 2). See Figure 2 for the identification steps.</li>
	<li>As shown in Figure 2, select the F-actin-stained channel (indicated by red arrows) first by scrolling the channel bar. Then, manually scroll the z-stacks (indicated by blue arrows) to see each stack one by one. Identify the F-actin-stained structures that seem to be connecting cells, are visible in the lower parts of the z-stacks, and are close to the surface of the imaging dish (z = 2) as neurites (indicated by white arrows). 
	NOTE: The majority of the neurites are easy to identify as they appear as extended protrusions (indicated by pink arrows).</li>
	<li>Identify the TNTs, the F-actin-positive, hovering cell-to-cell conduits, by scrolling the z-stacks toward the top (from z = 4 in Figure 2; indicated by yellow arrows). Look for neurites near the lower parts of the z-stacks toward the surface and observe that they start disappearing with the scrolling of z-stacks toward the top (at z = 6 in Figure 2; neurites are not clearly visible).</li>
	<li>Identify phospho-PAK1-positive TNTs similarly as F-actin-positive TNTs by analyzing the hovering nature of the conduits from the z-stacks. As phospho-PAK1 staining is weaker than F-actin staining, look for phopho-PAK1-stained TNTs at z = 4 (faintly visible)and at z = 6 (prominent).</li>
	<li>Further, observe the DIC images to verify that the F-actin- and phospho-PAK1-stained TNT structures are membrane conduits between cells (Figure 3). In addition, merge F-actin (red) and phospho-PAK1 (green) channels to verify that the identified TNTs are F-actin and phospho-PAK1 co-stained structures (Figure 3).</li>
	<li>To quantify the TNTs, count the total cell numbers and the identified TNTs manually and represent the numbers as percentages.</li>
	<li>To distinguish F-actin-positive TNTs and &#946;-III tubulin (TUBb3)-positive, TNT-like hovering conduits from z-stack images, merge F-actin (red) and TUBb3 (green) channels (Figure 4). Then, analyze the z-stacks of the merged images.
	<ol>
		<li>Look for exclusively F-actin-stained TNTs that are faintly visible at z = 3 and prominent at z = 6 and z = 9 (yellow arrows). Similarly, identify F-actin and &#946;-III tubulin (TUBb3) double-positive, TNT-like hovering conduits at z = 6 and z = 9 (cyan arrows). Identify other F-actin- and &#946;-III tubulin-stained, non-hovering protrusions from the lower parts of the z-stacks (white arrows).</li>
	</ol>
	</li>
	<li>Measure the diameter of the TNTs using the line tool in Fiji. Verify the scale of measurement by clicking Analyze | Set Scale so that &#34;distance in pixels&#34; is set automatically from the .czi images. Measure the diameters of the TNTs at the xy-plane. 
	NOTE: Most of the diameters are between 1 pixel and 4 pixels (i.e., 220-880 nm); each pixel is 220 nm. See Figure 5 for a summary of the protocol for the analysis of z-stack confocal images.</li>
</ol>
7. 3D reconstruction of z-stack images to characterize TNTs
<ol>
	<li>Use the volume viewer plugin in Fiji, which allows 3D reslicing and threshold-enabled 3D visualization (Figure 6).</li>
	<li>Split the z-stack images into individual channels. Then, crop the single-channel (F-actin channel) z-stack images to use 3D reconstruction view to highlight one or two TNTs or neurites at a time. Enable the volume view plugin to visualize xy, yz, and xz views.</li>
	<li>Pin a single TNT or neurite in the xy plane (white arrows represent neurites in Figure 6A; yellow arrows represent TNTs in Figure 6B) and mark xz (red) and yz (green) axis cross-sections. Observe the neurites at the bottom of the xz plane in the xz and yz planes (white arrows, Figure 6A) and the TNTs in the upper z-stacks (yellow arrows, Figure 6B).</li>
	<li>Select the individual TNT or neurite to reconstruct the 3D volume view in the xz-plane (Figure 6C, D). In the 3D reconstruction, observe the neurites at the bottom of the z-plane (white arrows, Figure 6C) and the TNTs appearing as hovering structures connecting two cells without touching the bottom z-plane (yellow arrows, Figure 6D).</li>
</ol>

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The authors have no conflict of interest to disclose.

Several researchers in the past 2 decades have been trying to understand and characterize the structure of TNTs18. The lack of specific markers hinders progress, and there is an increasing demand for a convenient, standardized method that can be used to identify, characterize, and quantify TNTs. TNTs are defined as F-actin-based membrane conduits that hover between two cells. Studies have shown that &#946;-tubulin-positive, close-ended, developing neurites hover between two distant cells and resem...

Tunneling nanotubes (TNTs) are F-actin-based, primarily open-ended membrane conduits and play a vital role in the intercellular transfer of cargo and organelles1. The unique characteristic of TNTs is that they connect neighboring cells without any contact with the substratum; they are over 10-300 &#181;m in length and their diameters vary between 50 nm to 1 &#181;m2,3. TNTs are transient structures, and their lifetime lasts between a few minutes to several hours. TNTs were first demonstrated in PC12 neuronal cells1; later, numerous studies showed their existence in several cell types in vitro and in vivo4,5. Several studies have revealed the pathological significance of TNTs in various disease models, such as neurodegenerative diseases, cancer, and viral infections6,7,8.
The structural heterogeneities of TNTs have been demonstrated by several studies in various cellular systems9. The differences are based on cytoskeleton composition, the mechanism of formation, and the cargo types transferred10. Primarily, the open-ended, F-actin-positive membrane continuity that hovers between two neighboring cells and transfers organelles is considered to consist of TNTs11. However, the lack of clarity or diversity observed in the formation of TNTs adds to the difficulty in developing TNT-specific markers. Thus, it is difficult to identify TNT structures by conventional detection methods and distinguish membrane nanotubes in terms of open-ended and close-ended protrusions12. However, the characteristic of TNTs to hover as F-actin membrane protrusions between two cells is relatively easier and more feasible to identify using conventional imaging techniques. Other actin-based cellular protrusions such as filopodia and dorsal filopodia cannot hover between two distant cells, particularly when cells are fixed. Of note, close-ended, electrically coupled, developing neurites are often termed TNT-like structures13.
It is known that F-actin plays an important role in TNT formation, and several studies have shown that the F-actin inhibitor cytochalasin D inhibits the formation of TNTs14,15. In contrast, inhibitors of microtubules do not have any effect on TNT formation16. The last 2 decades have seen several reports on the significant role that TNTs play in the spread of pathology and tumor resistance and therapy17. Therefore, there is a never-ending demand for better techniques for TNT characterization.
The lack of specific markers of TNTs and the diversity in morphology and cytoskeletal composition make it difficult to develop a unique method of characterization. Some studies have used automated image detection and TNT quantification techniques18,19. However, there are several advantages of the present 3D volume manual analysis method over automatic image analysis for the detection and quantification of TNTs. Often, trained human eyes can spot these hovering nano-structures more easily than an automated image detection method. Moreover, automatic detection methods could be difficult to implement in laboratories lacking algorithm expertise. The present method could be widely adopted by researchers due to its precision and reproducibility.
In a recent study, we showed that oA&#946; promotes the biogenesis of TNTs in neuronal cells via a PAK1-mediated, actin-dependent, endocytosis mechanism12. oA&#946;-induced TNTs also express activated PAK1 (or phospho-PAK1). We developed a 3D volume view image reconstruction method to distinguish oA&#946;-induced, F-actin- and phospho-PAK1-immunostained TNTs. &#946;-III tubulin-positive, developing neurites often resemble TNT-like hovering structures20. Hence, we further distinguished F-actin-based TNTs from &#946;-III tubulin-positive neurites and other TNT-like protrusions. 3D volume view images have been used to identify TNTs on the basis of their characteristics of hovering over the substratum and staying connected between two neighboring cells. This paper describes the identification and detection of actin-containing membrane conduits or TNTs using confocal z-stack images and, finally, manual quantification of the identified structures from 3D volume view reconstruction images. The presented method cannot distinguish open-ended proper TNTs from close-ended TNT-like structures; this method helps identify TNTs in in vitro 2D cell culture on a flat substratum. However, the method is easy to implement and reproduce and can be widely used for the precise quantification of only actin-based TNTs and to distinguish them from neurites and &#946;-tubulin positive TNT-like structures.

<table><tbody><tr><td>35 mm dish with 14 mm well size made of #1.5 cover slip</td><td>Cellvis</td><td>D35-14-1.5-N</td><td>Imaging dish used to seed cells for staining experiments</td></tr><tr><td>A&amp;beta; &lt;sub&gt;(1-42)&lt;/sub&gt; 1 mg</td><td>AnaSpec</td><td>#64129</td><td>Oligomers of amyloid beta to treat the cells</td></tr><tr><td>Alexa flour 488 Goat Anti-rabbit IgG (H+L)</td><td>Invitrogen</td><td>A11070</td><td>Secondary antibody for phospho-PAK1</td></tr><tr><td>Biological Safety Cabinet</td><td>Thermo Scientific (MSC Advantage)</td><td>51025411</td><td>Provide aspetic conditions duirng cell culture</td></tr><tr><td>CO&lt;sub&gt;2&lt;/sub&gt; Incubator</td><td>Thermo Electron Corporation (Heraeus Hera Cell 240)</td><td>51026556</td><td>For growing cells at or near body temperature</td></tr><tr><td>Confocal Laser Scanning Microscope</td><td>ZEISS (Carl Zeiss)</td><td>LSM 880</td><td>Able to generate three-dimensional images of large specimen at super-resolution</td></tr><tr><td>DABCO [1,4-Diazobicyclo-(2,2,2) octane]</td><td>Merck</td><td>8034560100</td><td>Anti-bleaching reagent</td></tr><tr><td>DAPI (4&amp;prime;,6-diamidino-2-phenylindole)</td><td>Sigma</td><td>D9542-1MG</td><td>Neuclear stainer</td></tr><tr><td>DMEM media</td><td>Gibco</td><td>11965092</td><td>Used for the preparation of 100uM of A&amp;beta; (1-42)</td></tr><tr><td>&amp;nbsp;DMEM/F12 (1:1 mixture of DMEM and Ham&amp;rsquo;s F12)</td><td>Gibco</td><td>12500062</td><td>Culture media for SH-SY5Y</td></tr><tr><td>DMSO (Dimethyl sulphide) Cell culture grade</td><td>Cryopur</td><td>CP-100</td><td>Cell culture grade used as dissolving agent for Retinoic acid</td></tr><tr><td>DMSO (Dimethyl sulphide) Molecular grade</td><td>Himedia</td><td>MB058</td><td>Used as one of the dissolving agent for the lyophilized A&amp;beta; (1-42)</td></tr><tr><td>Fetal Bovine Serum</td><td>Gibco</td><td>16000044</td><td>&amp;nbsp;Major supplement for Culture media (US origin)</td></tr><tr><td>Formalin Fixative (Neutral buffered 10%)</td><td>Sigma Aldrich</td><td>HT5014-120ML</td><td>Component in the Karnovsky&#039;s fixative solution</td></tr><tr><td>Glutaraldehyde (Grade I, 25% in H&lt;sub&gt;2&lt;/sub&gt;O)</td><td>Sigma</td><td>G5882</td><td>Component in the Karnovsky&#039;s fixative solution</td></tr><tr><td>HFIP (1,1,1,3,3,3-hexafluoro-2-propanol ) solution</td><td>TCI</td><td>H024</td><td>Used to dissolve A&amp;beta; (1-42) 1 mg</td></tr><tr><td>Image Processing/ Analysis Software: FIJI (ImageJ)</td><td>National Institute of Health (NIH)</td><td></td><td>Used to process/analyze the images and to differentiate the TNTs from neurites using its plugin named &quot;volume viewer&quot;.</td></tr><tr><td>Lyophilizer</td><td>Christ, Alpha</td><td>2.4 LDplus</td><td>0.05 mg aliquots of A&amp;beta; (1-42) can be stored in -20 &amp;deg;C after lyophilization only</td></tr><tr><td>Penicillin-Streptomycin-Neomycin Mixture</td><td>Thermo fisher Scientific</td><td>15640055</td><td>Antibiotic mixture</td></tr><tr><td>Phalloidin-iFlor 555</td><td>Abcam</td><td>ab176756</td><td>F-actin binding stain</td></tr><tr><td>Phospho-PAK1 (Thr423) /PAK2 (Thr402) [Rabbit]</td><td>CST</td><td>#2601</td><td>Primary antibody</td></tr><tr><td>Polyclonal Antibody to Tubulin Beta 3 (TUBb3)</td><td>Cloud clone</td><td>PAE711Hu01</td><td>Primary antibody</td></tr><tr><td>Retinoic acid</td><td>Sigma-Aldrich</td><td>R2625-50MG</td><td>Differentiating reagent</td></tr><tr><td>Saponin</td><td>Merck</td><td>8047-15-2</td><td>Detergent used in the Incubation buffer in immunostaining</td></tr><tr><td>Water bath sonicator (Quart, Drain valve Heater)</td><td>Ultrasonic Cleaner</td><td>3.0 L/3.2</td><td>Sonicator used to dissolve A&amp;beta; (1-42) stock, after DMSO adding to it during the preparation of 100 &amp;micro;M A&amp;beta; (1-42)</td></tr><tr><td>ZEN Microscopy software</td><td>ZEISS (Carl Zeiss)</td><td></td><td>Imaging software to acquire confocal microscopy images with smart automation</td></tr></tbody></table>

detection and quantification of tunneling nanotubes using 3d volume view images

Recent discoveries have revealed that cells perform direct, long-range, intercellular transfer via nano-scale, actin-membrane conduits, namely &#34;tunneling nanotubes&#34; (TNTs). TNTs are defined as open-ended, lipid bilayer-encircled membrane extensions that mediate continuity between neighboring cells of diameters ranging between 50 nm and 1 &#181;m. TNTs were demonstrated initially in neuronal cells, but successive studies have revealed the existence of TNTs in several cell types and diseases, such as neurodegenerative diseases, viral infections, and cancer. Several studies have referred to close-ended, electrically coupled membrane nanostructures between neighboring cells as TNTs or TNT-like structures.
The elucidation of ultrastructure in terms of membrane continuity at the endpoint is technically challenging. In addition, studies on cell-cell communication are challenging in terms of the characterization of TNTs using conventional methods due to the lack of specific markers. TNTs are primarily defined as F-actin-based, open-ended membrane protrusions. However, one major limitation is that F-actin is present in all types of protrusions, making it challenging to differentiate TNTs from other protrusions. One of the notable characteristics of F-actin-based TNTs is that these structures hover between two cells without touching the substratum. Therefore, distinct F-actin-stained TNTs can conveniently be distinguished from other protrusions such as filopodia and neurites based on their hovering between cells.
We have recently shown that the internalization of oligomeric amyloid-&#946;1-42 (oA&#946;) via actin-dependent endocytosis stimulates activated p21-activated kinase-1 (PAK1), which mediates the formation of F-actin-containing TNTs coexpressed with phospho-PAK1 between SH-SY5Y neuronal cells. This protocol outlines a 3D volume analysis method to identify and characterize TNTs from the captured z-stack images of F-actin- and phospho-PAK1-immunostained membrane protrusions in oA&#946;-treated neuronal cells. Further, TNTs are distinguished from developing neurites and neuronal outgrowths based on F-actin- and &#946;-III tubulin-immunostained membrane conduits.

Here, we identify and characterize oA&#946;-induced TNTs in SH-SY5Y neuronal cells by constructing 3D volume views from confocal z-stack images (Figure 1). The cells were double-immunostained with F-actin and phospho-PAK1. Confocal z-stack images of immunostained cells were analyzed to identify TNTs (Figure 2). Further, DIC images were analyzed to verify that the F-actin- and phospho-PAK1-stained TNT structures were membrane conduits between cells (<strong class...

Watch this Scientific Journal Video about Detection and Quantification of Tunneling Nanotubes Using 3D Volume View Images at JoVE.com

Detection and Quantification of Tunneling Nanotubes Using 3D Volume View Images

Tunneling nanotubes (TNTs) are primarily open-ended F-actin membrane nanotubes that connect neighboring cells, facilitating intercellular communication. The notable characteristic that distinguishes TNTs from other cell protrusions is the hovering nature of the nanotubes between cells. Here, we characterize TNTs by constructing a 3D volume view of confocal z-stack images.

Recent discoveries have revealed that cells perform direct, long-range, intercellular transfer via nano-scale, actin-membrane conduits, namely ...

detection-quantification-tunneling-nanotubes-using-3d-volume-view

Research

JoVE Journal

Biology

2.7K Views.  Manipal Academy of Higher Education, India. Het ontbreken van tunnelende nanobuisjes specifieke markers beperkt de vooruitgang in het veld en er is een toenemende vraag naar een methode om tunnelende nanobuizen te identificeren, karakteriseren en kwantificeren. Automatische detectiemethoden zijn moeilijk te implementeren zonder de expertise om een algoritme te ontwikkelen en/of het bestaande algoritme te wijzigen, maar onze handmatige methode is eenvoudig met meer precisie te implementeren. Intercellulaire overdracht over lange afstand...

Video: Detection and Quantification of Tunneling Nanotubes Using 3D Volume View Images

Extracting Metrics for Three-dimensional Root Systems: Volume and Surface Analysis from In-soil X-ray Computed Tomography Data

Plant roots play a critical role in plant-soil-microbe interactions that occur in the rhizosphere, as well as processes with important implications to climate change and crop management. Quantitative size information on roots in their native environment is invaluable for studying root growth and environmental processes involving plants. X-ray computed tomography (XCT) has been demonstrated to be an effective tool for in situ root scanning and analysis. We aimed to develop a costless and efficient tool that approximates the surface and volume of the root regardless of its shape from three-dimensional (3D) tomography data. The root structure of a Prairie dropseed (Sporobolus heterolepis) specimen was imaged using XCT. The root was reconstructed, and the primary root structure was extracted from the data using a combination of licensed and open-source software. An isosurface polygonal mesh was then created for ease of analysis. We have developed the standalone application imeshJ, generated in MATLAB1, to calculate root volume and surface area from the mesh. The outputs of imeshJ are surface area (in mm2) and the volume (in mm3). The process, utilizing a unique combination of tools from imaging to quantitative root analysis, is described. A combination of XCT and open-source software proved to be a powerful combination to noninvasively image plant root samples, segment root data, and extract quantitative information from the 3D data. This methodology of processing 3D data should be applicable to other material/sample systems where there is connectivity between components of similar X-ray attenuation and difficulties arise with segmentation.

A methodology for obtaining visual and quantitative root structure information from X-ray computed tomography data acquired in-soil is presented.

Plant roots play a critical role in plant-soil-microbe interactions that occur in the rhizosphere, as well as processes with important implications to ...

Environment

Energy Dispersive X-ray Tomography for 3D Elemental Mapping of Individual Nanoparticles

Energy dispersive X-ray spectroscopy within the scanning transmission electron microscope (STEM) provides accurate elemental analysis with high spatial resolution, and is even capable of providing atomically resolved elemental maps. In this technique, a highly focused electron beam is incident upon a thin sample and the energy of emitted X-rays is measured in order to determine the atomic species of material within the beam path. This elementally sensitive spectroscopy technique can be extended to three dimensional tomographic imaging by acquiring multiple spectrum images with the sample tilted along an axis perpendicular to the electron beam direction.
Elemental distributions within single nanoparticles are often important for determining their optical, catalytic and magnetic properties. Techniques such as X-ray tomography and slice and view energy dispersive X-ray mapping in the scanning electron microscope provide elementally sensitive three dimensional imaging but are typically limited to spatial resolutions of &gt; 20 nm. Atom probe tomography provides near atomic resolution but preparing nanoparticle samples for atom probe analysis is often challenging. Thus, elementally sensitive techniques applied within the scanning transmission electron microscope are uniquely placed to study elemental distributions within nanoparticles of dimensions 10-100 nm.
Here, energy dispersive X-ray (EDX) spectroscopy within the STEM is applied to investigate the distribution of elements in single AgAu nanoparticles. The surface segregation of both Ag and Au, at different nanoparticle compositions, has been observed.

The use of energy dispersive X-ray tomography in the scanning transmission electron microscope to characterize elemental distributions within single nanoparticles in three dimensions is described.

Energy dispersive X-ray spectroscopy within the scanning transmission electron microscope (STEM) provides accurate elemental analysis with high spatial ...

Engineering

Using Synchrotron Radiation Microtomography to Investigate Multi-scale Three-dimensional Microelectronic Packages

Synchrotron radiation micro-tomography (SR&#181;T) is a non-destructive three-dimensional (3D) imaging technique that offers high flux for fast data acquisition times with high spatial resolution. In the electronics industry there is serious interest in performing failure analysis on 3D microelectronic packages, many which contain multiple levels of high-density interconnections. Often in tomography there is a trade-off between image resolution and the volume of a sample that can be imaged. This inverse relationship limits the usefulness of conventional computed tomography (CT) systems since a microelectronic package is often large in cross sectional area 100-3,600 mm2, but has important features on the micron scale. The micro-tomography beamline at the Advanced Light Source (ALS), in Berkeley, CA USA, has a setup which is adaptable and can be tailored to a sample&#39;s properties, i.e., density, thickness, etc., with a maximum allowable cross-section of 36 x 36 mm. This setup also has the option of being either monochromatic in the energy range ~7-43 keV or operating with maximum flux in white light mode using a polychromatic beam. Presented here are details of the experimental steps taken to image an entire 16 x 16 mm system within a package, in order to obtain 3D images of the system with a spatial resolution of 8.7 &#181;m all within a scan time of less than 3 min. Also shown are results from packages scanned in different orientations and a sectioned package for higher resolution imaging. In contrast a conventional CT system would take hours to record data with potentially poorer resolution. Indeed, the ratio of field-of-view to throughput time is much higher when using the synchrotron radiation tomography setup. The description below of the experimental setup can be implemented and adapted for use with many other multi-materials.

For this study synchrotron radiation micro-tomography, a non-destructive three-dimensional imaging technique, is employed to investigate an entire microelectronic package with a cross-sectional area of 16 x 16 mm. Due to the synchrotron&#39;s high flux and brightness the sample was imaged in just 3 min&#160;with an 8.7 &#181;m spatial resolution.

Synchrotron radiation micro-tomography (SR&#181;T) is a non-destructive three-dimensional (3D) imaging technique that offers high flux for fast data ...

Non-invasive 3D-Visualization with Sub-micron Resolution Using Synchrotron-X-ray-tomography

Little is known about the internal organization of many micro-arthropods with body sizes below 1 mm. The reasons for that are the small size and the hard cuticle which makes it difficult to use protocols of classical histology. In addition, histological sectioning destroys the sample and can therefore not be used for unique material. Hence, a non-destructive method is desirable which allows to view inside small samples without the need of sectioning.
We used synchrotron X-ray tomography at the European Synchrotron Radiation Facility (ESRF) in Grenoble (France) to non-invasively produce 3D tomographic datasets with a pixel-resolution of 0.7&micro;m. Using volume rendering software, this allows us to reconstruct the internal organization in its natural state without the artefacts produced by histological sectioning. These date can be used for quantitative morphology, landmarks, or for the visualization of animated movies to understand the structure of hidden body parts and to follow complete organ systems or tissues through the samples.

We used synchrotron X-ray tomography at the European Synchrotron Radiation Facility (ESRF) to non-invasively produce 3D tomographic datasets with a pixel-resolution of 0.7&micro;m. Using volume rendering software, this allows the reconstruction of internal structures in their natural state without the artefacts produced by histological sectioning.

Little is known about the internal organization of many micro-arthropods with body sizes below 1 mm. The reasons for that are the small size and the hard ...

Localization and Relative Quantification of Carbon Nanotubes in Cells with Multispectral Imaging Flow Cytometry

Carbon-based nanomaterials, like carbon nanotubes (CNTs), belong to this type of nanoparticles which are very difficult to discriminate from carbon-rich cell structures and de facto there is still no quantitative method to assess their distribution at cell and tissue levels. What we propose here is an innovative method allowing the detection and quantification of CNTs in cells using a multispectral imaging flow cytometer (ImageStream, Amnis). This newly developed device integrates both a high-throughput of cells and high resolution imaging, providing thus images for each cell directly in flow and therefore statistically relevant image analysis. Each cell image is acquired on bright-field (BF), dark-field (DF), and fluorescent channels, giving access respectively to the level and the distribution of light absorption, light scattered and fluorescence for each cell. The analysis consists then in a pixel-by-pixel comparison of each image, of the 7,000-10,000 cells acquired for each condition of the experiment. Localization and quantification of CNTs is made possible thanks to some particular intrinsic properties of CNTs: strong light absorbance and scattering; indeed CNTs appear as strongly absorbed dark spots on BF and bright spots on DF with a precise colocalization.
This methodology could have a considerable impact on studies about interactions between nanomaterials and cells given that this protocol is applicable for a large range of nanomaterials, insofar as they are capable of absorbing (and/or scattering) strongly enough the light.

In this study, the main purpose was to monitor the cellular uptake and eventual exocytosis of carbon nanotubes (CNTs). From this perspective, we proposed here a unique method using multispectral imaging flow cytometry allowing a quantification and localization of CNTs in a statistically relevant number of cells.

Carbon-based nanomaterials, like carbon nanotubes (CNTs), belong to this type of nanoparticles which are very difficult to discriminate from carbon-rich ...

Bioengineering

Microscopic Visualization of Porous Nanographenes Synthesized through a Combination of Solution and On-Surface Chemistry

On-surface synthesis has recently been regarded as a promising approach for the generation of new molecular structures. It has been particularly successful in the synthesis of graphene nanoribbons, nanographenes and intrinsically reactive and instable, yet attractive species. It is based on the combination of solution chemistry aimed at preparation of appropriate molecular precursors for further ultra-high vacuum surface assisted transformations. This approach also owes its success to an incredible development of characterization techniques, such as scanning tunneling/atomic force microscopy and related methods, which allow detailed, local characterization at atomic scale. While the surface-assisted synthesis can provide molecular nanostructures with outstanding precision, down to single atoms, it suffers from basing on metallic surfaces and often limited yield. Therefore, the extension of the approach away from metals and the struggle to increase productivity seem to be significant challenges toward wider applications. Herein, we demonstrate the on-surface synthesis approach for generation of non-planar nanographenes, which are synthesized through a combination of solution chemistry and sequential surface-assisted processes, together with the detailed characterization by scanning probe microscopy methods.

A combination of solution and surface assisted synthesis opens new directions in the atomically precise synthesis of nanostructures. Scanning tunneling microscopy (STM) supplemented by non-contact atomic force microscopy (nc-AFM) enables detailed characterization of newly designed and generated carbon-based nano-objects.

On-surface synthesis has recently been regarded as a promising approach for the generation of new molecular structures. It has been particularly ...

Chemistry

Three-dimensional Imaging and Analysis of Mitochondria within Human Intraepidermal Nerve Fibers

The goal of this protocol is to study mitochondria within intraepidermal nerve fibers. Therefore, 3D imaging and analysis techniques were developed to isolate nerve-specific mitochondria and evaluate disease-induced alterations of mitochondria in the distal tip of sensory nerves. The protocol combines fluorescence immunohistochemistry, confocal microscopy and 3D image analysis techniques to visualize and quantify nerve-specific mitochondria. Detailed parameters are defined throughout the procedures in order to provide a concrete example of how to use these techniques to isolate nerve-specific mitochondria. Antibodies were used to label nerve and mitochondrial signals within tissue sections of skin punch biopsies, which was followed by indirect immunofluorescence to visualize nerves and mitochondria with a green and red fluorescent signal respectively. Z-series images were acquired with confocal microscopy and 3D analysis software was used to process and analyze the signals. It is not necessary to follow the exact parameters described within, but it is important to be consistent with the ones chosen throughout the staining, acquisition and analysis steps. The strength of this protocol is that it is applicable to a wide variety of circumstances where one fluorescent signal is used to isolate other signals that would otherwise be impossible to study alone.

This protocol uses three-dimensional (3D) imaging and analysis techniques to visualize and quantify nerve-specific mitochondria. The techniques are applicable to other situations where one fluorescent signal is used to isolate a subset of data from another fluorescent signal.

The goal of this protocol is to study mitochondria within intraepidermal nerve fibers. Therefore, 3D imaging and analysis techniques were developed to ...

Neuroscience

3D Imaging of Soft-Tissue Samples using an X-ray Specific Staining Method and Nanoscopic Computed Tomography

We demonstrate a laboratory-based method combining X-ray microCT and nanoCT with a specific X-ray stain, which targets the cell cytoplasm. The described protocol is easy to apply, fast and suitable for larger soft-tissue samples. The presented methodology enables the characterization of crucial tissue structures in three dimensions and is demonstrated on a whole mouse kidney. The multiscale approach allows to image the entire mouse kidney and supports the selection of further volumes of interest, which are acquired with higher resolutions ranging into the nanometer range. Thereby, soft-tissue morphology with a similar detail level as the corresponding histological light microscopy images is reproduced. Deeper insights into the 3D configuration of tissue structures are achieved without impeding further investigations through histological methods.

A protocol for 3D visualization of microscopic tissue structures by using an X-ray specific staining method designed for X-ray computed tomography is presented.

We demonstrate a laboratory-based method combining X-ray microCT and nanoCT with a specific X-ray stain, which targets the cell cytoplasm. The described ...

3D Reconstruction and Analysis of Thin Subcellular Neuronal Structures using Focused-Ion Beam Scanning Electron Microscopy Data

Recent advances in scanning electron microscope technologies now permit the rapid three-dimensional (3D) analysis of ultrathin subcellular processes. Here, a methodological pipeline is presented to identify, visualize, and analyze thin neuronal processes, such as those that project into the presynaptic boutons of other neurons (termed 'spinules'). Using freely available software packages, this protocol demonstrates how to use a decision tree to identify common neuronal subcellular structures using morphological criteria within focused ion beam scanning electron microscopy (FIB-SEM) image volumes, with particular attention on identifying a diversity of spinules projecting into presynaptic boutons. In particular, this protocol describes how to trace spinules within neuronal synapses to produce 3D reconstructions of these thin subcellular projections, their parent neurites, and postsynaptic partners. Additionally, the protocol includes a list of freely available open-source software programs for analyzing FIB-SEM data and offers tips (e.g., smoothing, lighting) toward improving 3D reconstructions for visualization and publication. This adaptable protocol offers an entry point into the rapid nanoscale analysis of subcellular structures within FIB-SEM image volumes.

A flexible methodological pipeline to identify, visualize, and quantify thin subcellular neuronal processes within focused ion beam scanning electron microscopy image volumes using user-friendly open-source software packages.

Recent advances in scanning electron microscope technologies now permit the rapid three-dimensional (3D) analysis of ultrathin subcellular processes. ...

Simplified Volumetric Models as an Effective Strategy for Segmenting Actin Networks in Cryo-Electron Tomograms

Efficient methods for the extraction of features of interest remain one of the biggest challenges for the interpretation of cryo-electron tomograms. Various automated approaches have been proposed, many of which work well for high-contrast datasets where the features of interest can be easily detected and are clearly separated from one another. Our inner ear stereocilia cryo-electron tomographic datasets are characterized by a dense array of hexagonally packed actin filaments that are frequently cross-connected. These features make automated segmentation very challenging, further aggravated by the high-noise environment of cryo-electron tomograms and the high complexity of the densely packed features. Using prior knowledge about the actin bundle organization, we have placed layers of a highly simplified ball-and-stick actin model to first obtain a global fit to the density map, followed by regional and local adjustments of the model. We show that volumetric model building not only allows us to deal with the high complexity, but also provides precise measurements and statistics about the actin bundle. Volumetric models also serve as anchoring points for local segmentation, such as in the case of the actin-actin cross connectors. Volumetric model building, particularly when further augmented by computer-based automated fitting approaches, can be a powerful alternative when conventional automated segmentation approaches are not successful.

Here, we present a protocol to place simplified volumetric models into noisy, complex, tomographic 3D volumes. This allows the fast segmentation of actin filament densities, detection of systematic filament bending and of gaps in hair bundle filaments, as well as convenient quantification of volumetric model properties, such as distances.

Efficient methods for the extraction of features of interest remain one of the biggest challenges for the interpretation of cryo-electron tomograms. ...

Detection and Quantification of Tunneling Nanotubes Using 3D Volume View Images

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