Grant support: NIH CA165263, NIH CA150197, NIH CA150197S1 (H.J. Kung), NIH CA150197S1 (C.A. Changou), NSF PHY-0120999 Center for Biophotonics Science &amp; Technology (D.L. Wolfson, F.Y.S. Chuang), DOD PC073420 (R.J. Bold), The Research Council of Norway, Leiv Eiriksson Travel Grant 209286/F11 (B.S. Ahluwalia). H.J. Kung also acknowledges the support of the Auburn Community Cancer Endowment Fund. R.J. Bold also acknowledges the support of the J. McDonald endowment.
We thank Dr. Jenny Wei-Jen Kung and Dr. Bor-wen Wu at DesigneRx for generous supply of ADI.

1. Part 1: Cell Culture and Immuno-fluorescent Labeling
<ol>
	<li>Grow CWR22Rv1 human prostate tumor cells on glass coverslips (#1.5 or 170 &mu;m thickness) placed in 6-well plates, with RPMI (Mediatech, VA) containing 10% fetal bovine serum (FBS) and 1% penicillin/streptomycin/glutamine.</li>
	<li>Induce autophagy by treating selected samples with arginine deiminase (ADI, 0.3 &mu;g/ml) in phosphate-buffered saline (PBS).</li>
	<li>Fix cells with 4% paraformaldehyde (PFA, Fisher Scientific, NH) diluted in PBS; 100 &mu;l per coverslip, for 10 min at RT.</li>
	<li>Wash cells 3x with 1 ml HBS/BSA.</li>
	<li>Permeabilize cells with 0.05% saponin (Sigma, MO) in HEPES (HBS)/BSA, 100 &mu;l per coverslip, for 15 min at RT.</li>
	<li>Prior to immuno-labeling, block samples with 2.5% casein (Sigma, MO) in HBS/BSA, 100 &mu;l per coverslip, for 1 hr at RT.</li>
	<li>Incubate fixed cells with primary antibodies diluted in 2.5% casein/HBS/BSA, 100 &mu;l per coverslip, O/N at 4 &deg;C.</li>
	<li>Wash cells 3x with 1 ml HBS/BSA.</li>
	<li>Incubate fixed cells with secondary antibodies diluted in 2.5% casein/HBS/BSA, 100 &mu;l per coverslip, for 1 hr at RT.</li>
	<li>Wash cells 3x with 1 ml HBS/BSA.</li>
	<li>Mount prepared coverslips on regular glass microscope slides with SlowFade Gold or Prolong Gold antifade reagent (Invitrogen, CA) containing 4',6-diamidino-2-phenylindole (DAPI).</li>
	<li>Seal coverslip edges with nail polish. For best imaging results, allow time (ideally O/N) for anti-fade media to thoroughly permeate cells.</li>
	<li>Clean coverslip surface with methanol and/or chloroform.</li>
	<li>Add immersion oil (refractive index 1.520 when imaging at 37 &deg;C, or 1.516 when imaging at RT) to the 60X 1.42 N.A objective lens (Olympus, Japan).</li>
	<li>Position slide on the microscope stage and establish focus with the cells of interest.</li>
</ol>
2. Part 2: Preparing Cells for Live Imaging
<ol>
	<li>Grow CWR22Rv1 cells expressing green fluorescent protein-coupled Light Chain 3 (LC3-GFP) in RPMI culture media containing 10% FBS and 1% antibiotics on 35 mm poly-d-lysine coated glass-bottom culture dishes (MatTek, MA). Cells should be plated at sufficient density to facilitate rapid proliferation, but not so much that cells are overgrown and clumped by the time of imaging.</li>
	<li>Treat selected cell samples with ADI (0.3 &mu;g/ml) in PBS.</li>
	<li>Approximately 1 hr prior to imaging, dilute 1.5 &mu;l of LysoTracker Red DND-99 (Invitrogen, CA) with 20 ml RPMI. containing 10% FBS and 1% antibiotics. Use solutions containing ADI for selected samples. Warm all media to 37 &deg;C prior to adding into the culture dish.</li>
	<li>Incubate cells with RPMI containing LysoTracker Red DND-99 for 15-45 min at 37 &deg;C.</li>
	<li>Approximately 30 min prior to imaging, turn on the WeatherStation environmental enclosure and allow to equilibrate to 37 &deg;C and 5% CO2 (with humidified air).</li>
	<li>Wash cells with PBS and replace media with standard RPMI containing only 10% FBS and 1% antibiotics. Add ADI to samples as indicated.</li>
	<li>Mount 35 mm coverglass-bottom culture dishes in customized adaptor (Applied Precision, Inc., WA), and position on the microscope stage. Use immersion oil (refractive index 1.520) on the 60X 1.42 NA objective lens, and position the mounted culture dish on the stage.</li>
</ol>
3. Part 3: Deconvolution Microscopy and Analysis
The protocol in this section assumes the use of the DeltaVision Personal DV deconvolution microscope and associated SoftWorX application suite (Applied Precision, Inc., WA).
<ol>
	<li>Turn on microscope system, including acquisition workstation and instrument controller. Open Resolve3D application to initialize the microscope stage and turn on the xenon light source. Allow 10 min for light source to warm up and reach stable conditions.</li>
	<li>Add a drop of immersion oil (refractive index 1.520 for live samples at 37 &deg;C or 1.516 for fixed samples at RT) on the 60X 1.42 N.A objective lens, and center slide specimen (cover slip face down) over the objective lens.</li>
	<li>Using either bright-field or external illumination and the coarse focus adjust knob, slowly raise the objective lens until the bead of immersion oil makes contact with the inverted cover glass. (From this point, the cell layer should come into focus within a few turns of the fine focus adjust knob). When working with fixed samples on the slides, it is recommended to avoid cells within or near any areas with bubbles. When viewing with live samples on the glass-bottom dish, avoid moving the objective lens outside of the boundary of the glass coverslip.</li>
	<li>Autophagosomes can be identified by eGFP signal (green). Lysosomes are identified by LysoTracker Red (live sample) or anti-Lamp1 fluorescent antibody (fixed sample). Cell nuclei are identified by DAPI staining (fixed sample).</li>
	<li>Select desired field of view. Ideally, cells should exhibit good fluorescent signal in all the appropriate channels, and sufficiently attached and spread out on the coverslip surface so that the intracellular contents are easy to visualize. Small adjustments in lateral x, y, and z-focus can be controlled by computer using the Acquire3D interface. Set binning to 1x1 or 2x2, depending on desired field of view (more cells can be seen in the field when binning is set to 2x2).</li>
	<li>For a given image through the midsection of a cell, set the exposure parameters (e.g. % transmission power and exposure time) such that the maximum pixel intensity does not exceed 3,000 counts. Generally, % transmission should be set as low as possible, without raising the corresponding exposure time over 1 sec. Repeat this procedure for every fluorescence color to be imaged and for each separate field of view to obtain the highest quality images.</li>
	<li>Set the upper and lower limits of the Z-stack by adjusting the focus just slightly over the top and bottom of the cell sample, respectively. The total number of images in a given Z-stack will thus be determined by these limits and by the spacing between layers (default value: 0.2 &mu;m).</li>
	<li>To minimize motion artifacts during image acquisition, we recommend setting the image acquisition mode to "wavelength then z-stack" for fixed samples, and "z-stack then wavelength" for live samples.</li>
	<li>Fluorescence images are deconvolved using SoftWorX (Applied Precision, WA) and later analyzed using VoloCITY (Improvision, now Perkin Elmer, MA).</li>
</ol>
4. Part 4: Super-resolution, Structured-illumination (OMX) Microscopy
The protocol in this section applies to the use of the OMX Structured Illumination Microscope (Applied Precision, WA).
<ol>
	<li>Switch on the main power and desired lasers (410 nm, 488 nm, and/or 532 nm). Wait for 20 min for the lasers to be thermally stabilized.</li>
	<li>Add immersion oil (refractive index 1.516 for fixed samples at RT) on the 60X 1.42 N.A objective lens. If bubbles are seen in the oil droplet, clean the objective and add oil again.</li>
	<li>Place sample slide on the stage and if necessary, allow 10 min for cells to settle on coverslip.</li>
	<li>Initialize the acquisition program. Use fluorescence illumination to adjust the focus until a sharp outline of the cell can be seen. (Care should be taken at all times to minimize exposure of cells to fluorescence excitation, until the actual image acquisition).</li>
	<li>A spiral mosaic scan can be acquired to preview larger areas of the sample to select cells or regions of interest. It is recommended to use short exposure times (1-10 msec) and low excitation power (0.1-1% transmission) while scanning the sample or finding targets.</li>
	<li>Identify autophagosomes by GFP-LC3 fluorescence. Identify lysosomes by Alexa Fluor 555 anti-LAMP (lysosome-associated membrane protein) and cell nuclei using DAPI (fixed samples).</li>
	<li>Choose experimental conditions including excitation wavelength, image area (e.g. 512x512), stack thickness, exposure time, and laser transmission percentage. For super resolved images, ensure that the structured illumination option is enabled. For deconvolution microscopy on the OMX, select the conventional illumination option.</li>
	<li>For the best reconstruction results, select experimental conditions such that the maximum intensity count is between 10,000 and 15,000 during the acquisition. If photobleaching is a concern, imaging at a lower exposure (counts between 5,000 and 10,000) may be used. Ideally, the counts should not decrease more than a factor of two during the entire acquisition, and decreases by more than a factor of four should be avoided. If necessary, reduce the stack thickness to ensure a sustained intensity count. The camera saturates at 64,000 counts, so maximum intensity should never exceed this. For good samples, we found the experimental conditions to be 10~50 msec exposure time with 1% laser transmission. Bright and photostable samples that can be imaged repeatedly are preferred. A stable stain is required for time-lapse, super resolved images.</li>
	<li>To reduce noise, a 95MHz readout speed (Medium speed option) and acquisition time of 2 msec or more is recommended. Increased artifacts are obtained in the reconstructed imaged, when sample moves during the acquisition. Due to this affect, short exposures are recommended for non-adherent or fast-moving cells.</li>
	<li>Multichannel imaging can be performed simultaneously or sequentially. Sequential mode yields less cross-talk and is thus recommended.</li>
	<li>To reduce photobleaching, it is generally recommended to image with longer excitation wavelengths first (532 nm, 488 nm, and then 410 nm). However, for the experimental results shown in Figure 3, this order was reversed (i.e. 48 nm, 532 nm and 410 nm) due to the photostability of this particular sample.</li>
	<li>Set the upper/lower limit of the Z-stack by moving the microscope stage until the top/bottom of the cells is slightly out of focus. The desired distance between each image should be held constant at 0.125 &mu;m for super resolution imaging, as reconstruction software take this value as default.</li>
	<li>Reconstruct image stacks using SoftWorX (Applied Precision, WA) and analyze using VoloCITY 6.0 (Perkin Elmer, MA).</li>
</ol>

<ol>
	<li>Kim, R. H., Coates, J. M., Bowles, T. L., McNerney, G. P., Sutcliffe, J., Jung, J. U., Gandour-Edwards, R., Chuang, F. Y., Bold, R. J., Kung, H. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Arginine+deiminase+as+a+novel+therapy+for+prostate+cancer+induces+autophagy+and+caspase-independent+apoptosis.">Arginine deiminase as a novel therapy for prostate cancer induces autophagy and caspase-independent apoptosis.</a> Cancer Res. 69 (2), 700-708 (2009).</li><li>Miyazaki, K., Takaku, H., Umeda, M., 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=Potent+growth+inhibition+of+human+tumor+cells+in+culture+by+arginine+deiminase+purified+from+a+culture+medium+of+a+Mycoplasma-infected+cell+line.">Potent growth inhibition of human tumor cells in culture by arginine deiminase purified from a culture medium of a Mycoplasma-infected cell line.</a> Cancer Res. 50, 4522-4527 (1990).</li><li>Takaku, H., Matsumoto, M., Misawa, S., Miyazaki, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Anti-tumor+activity+of+arginine+deiminase+from+Mycoplasma+argini+and+its+growth-inhibitory+mechanism.">Anti-tumor activity of arginine deiminase from Mycoplasma argini and its growth-inhibitory mechanism.</a> Jpn. J. Cancer Res. 86, 840-846 (1995).</li><li>Levine, B., Klionsky, D. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Development+by+self-digestion:+molecular+mechanisms+and+biological+functions+of+autophagy.">Development by self-digestion: molecular mechanisms and biological functions of autophagy.</a> Dev. Cell. 6, 463-477 (2004).</li><li>Mizushima, N., Levine, B., Cuervo, A. M., Klionsky, D. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Autophagy+fights+disease+through+cellular+self-digestion.">Autophagy fights disease through cellular self-digestion.</a> Nature. 451, 1069-1075 (2008).</li><li>Kabeya, Y., Mizushima, N., Ueno, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=LC3,+a+mammalian+homologue+of+yeast+Apg8p,+is+localized+in+autophagosome+membranes+after+processing.">LC3, a mammalian homologue of yeast Apg8p, is localized in autophagosome membranes after processing.</a> EMBO J. 19, 5720-5728 (2000).</li><li>Pattingre, S., Espert, L., Biard-Piechaczyk, M., Codogno, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Regulation+of+macroautophagy+by+mTOR+and+Beclin+1+complexes.">Regulation of macroautophagy by mTOR and Beclin 1 complexes.</a> Biochimie. 90, 313-323 (2008).</li><li>Maiuri, M. C., Criollo, A., Tasdemir, 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=BH3-only+proteins+and+BH3mimetics+induce+autophagy+by+competitively+disrupting+the+interaction+between+Beclin+1+and+Bcl-2/Bcl-X(L).">BH3-only proteins and BH3mimetics induce autophagy by competitively disrupting the interaction between Beclin 1 and Bcl-2/Bcl-X(L).</a> Autophagy. 3, 374-376 (2007).</li><li>Crighton, D., Wilkinson, S., O'Prey, J., 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=DRAM,+a+p53-induced+modulator+of+autophagy,+is+critical+for+apoptosis.">DRAM, a p53-induced modulator of autophagy, is critical for apoptosis.</a> Cell. 126, 121-134 (2008).</li><li>Dillon, B. J., Prieto, V. G., Curley, S. A., 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=Incidence+and+distribution+of+argininosuccinate+synthetase+deficiency+in+human+cancers:+a+method+for+identifying+cancers+sensitive+to+arginine+deprivation.">Incidence and distribution of argininosuccinate synthetase deficiency in human cancers: a method for identifying cancers sensitive to arginine deprivation.</a> Cancer. 100, 826-833 (2004).</li><li>Dale, B. M., McNerney, G. P., Thompson, D. 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=Cell-to-cell+transfer+of+HIV-1+via+virological+synapses+leads+to+endosomal+virion+maturation+that+activates+viral+membrane+fusion.">Cell-to-cell transfer of HIV-1 via virological synapses leads to endosomal virion maturation that activates viral membrane fusion.</a> Cell Host &amp; Microbe. 10 (6), 551-562 (2011).</li><li>Cogger, V. C., McNerney, G. P., Nyunt, 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=Three-dimensional+structured+illumination+microscopy+of+liver+sinusoidal+endothelial+cell+fenestrations.">Three-dimensional structured illumination microscopy of liver sinusoidal endothelial cell fenestrations.</a> J. Struct. Biol. 171 (3), 382-388 (2010).</li><li>York, A. G., Parekh, S. H., Nogare, D. D., 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+live,+multicellular+organisms+via+multifocal+structured+illumination+microscopy.">Resolution doubling in live, multicellular organisms via multifocal structured illumination microscopy.</a> Nat. Methods. 9 (7), 749-754 (2012).</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+factor+of+two+using+structured+illumination+microscopy.">Surpassing the lateral resolution limit by factor of two using structured illumination microscopy.</a> Journal of Microscopy. 198, 82-87 (2000).</li><li>Shao, L., Kner, P., Rego, E. H., Gustaffson, M. G. <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+3D+microscopy+of+live+whole+cells+using+structured+illumination.">Super-resolution 3D microscopy of live whole cells using structured illumination.</a> Nat. Method. 8 (12), 1044-1046 (2011).</li></ol>

No conflicts of interest declared.

While the direct observation of cells labeled with fluorescent probes against LC3 is widely accepted as a standard method to confirm autophagic response6, quantitative 3D imaging of the same system (as we have done) provides unprecedented information and detail about the complex process of cellular autophagy. In particular, we observe that hundreds (if not thousands) of autophagosomes in live cells are formed within 80 min of autophagy induction. Similarly, we observe very interesting morphological changes in ...

<table border="1">
	<tbody>
		<tr>
			<td>Name of Reagent/Material</td>
			<td>Company</td>
			<td>Catalogue Number</td>
			<td>Comments</td>
		</tr>
		<tr>
			<td>Arginine Deiminase (ADI)</td>
			<td>DesigneRx</td>
			<td>&nbsp;</td>
			<td>&nbsp;</td>
		</tr>
		<tr>
			<td>HEPES</td>
			<td>Sigma</td>
			<td>H4034</td>
			<td>&nbsp;</td>
		</tr>
		<tr>
			<td>Casein</td>
			<td>Sigma</td>
			<td>C5890</td>
			<td>&nbsp;</td>
		</tr>
		<tr>
			<td>Paraformaldehyde</td>
			<td>Fisher</td>
			<td>4042</td>
			<td>&nbsp;</td>
		</tr>
		<tr>
			<td>Saponin</td>
			<td>Sigma</td>
			<td>S4521</td>
			<td>&nbsp;</td>
		</tr>
		<tr>
			<td>Alexa anti-mouse 555</td>
			<td>Invitrogen</td>
			<td>A21422</td>
			<td>&nbsp;</td>
		</tr>
		<tr>
			<td>Alexa anti-rabbit 647</td>
			<td>Invitrogen</td>
			<td>A21244</td>
			<td>&nbsp;</td>
		</tr>
		<tr>
			<td>LysoTracker Red DND-99</td>
			<td>Invitrogen</td>
			<td>L7528</td>
			<td>&nbsp;</td>
		</tr>
		<tr>
			<td>anti-Lamp1</td>
			<td>DSHB</td>
			<td>H4A3</td>
			<td>&nbsp;</td>
		</tr>
		<tr>
			<td>anti-Cadherin</td>
			<td>Cell Signaling</td>
			<td>#3195</td>
			<td>&nbsp;</td>
		</tr>
		<tr>
			<td>SlowFade Gold</td>
			<td>Invitrogen</td>
			<td>S36936</td>
			<td>&nbsp;</td>
		</tr>
		<tr>
			<td>35 mm poly-d-lysine coated glass bottom plate</td>
			<td>MatTek</td>
			<td>P35GC-1.5-1.4-C</td>
			<td>&nbsp;</td>
		</tr>
		<tr>
			<td>No.1, 22 mm coverslip</td>
			<td>Corning</td>
			<td>#2865-22</td>
			<td>&nbsp;</td>
		</tr>
		<tr>
			<td>Microscope slides</td>
			<td>Globe Scientific</td>
			<td>1324G</td>
			<td>&nbsp;</td>
		</tr>
	</tbody>
</table>

quantitative analysis of autophagy using advanced 3d fluorescence microscopy

Prostate cancer is the leading form of malignancies among men in the U.S. While surgery carries a significant risk of impotence and incontinence, traditional chemotherapeutic approaches have been largely unsuccessful. Hormone therapy is effective at early stage, but often fails with the eventual development of hormone-refractory tumors. We have been interested in developing therapeutics targeting specific metabolic deficiency of tumor cells. We recently showed that prostate tumor cells specifically lack an enzyme (argininosuccinate synthase, or ASS) involved in the synthesis of the amino acid arginine1. This condition causes the tumor cells to become dependent on exogenous arginine, and they undergo metabolic stress when free arginine is depleted by arginine deiminase (ADI)1,10. Indeed, we have shown that human prostate cancer cells CWR22Rv1 are effectively killed by ADI with caspase-independent apoptosis and aggressive autophagy (or macroautophagy)1,2,3. Autophagy is an evolutionarily-conserved process that allows cells to metabolize unwanted proteins by lysosomal breakdown during nutritional starvation4,5. Although the essential components of this pathway are well-characterized6,7,8,9, many aspects of the molecular mechanism are still unclear - in particular, what is the role of autophagy in the death-response of prostate cancer cells after ADI treatment? In order to address this question, we required an experimental method to measure the level and extent of autophagic response in cells - and since there are no known molecular markers that can accurately track this process, we chose to develop an imaging-based approach, using quantitative 3D fluorescence microscopy11,12.
Using CWR22Rv1 cells specifically-labeled with fluorescent probes for autophagosomes and lysosomes, we show that 3D image stacks acquired with either widefield deconvolution microscopy (and later, with super-resolution, structured-illumination microscopy) can clearly capture the early stages of autophagy induction. With commercially available digital image analysis applications, we can readily obtain statistical information about autophagosome and lysosome number, size, distribution, and degree of colocalization from any imaged cell. This information allows us to precisely track the progress of autophagy in living cells and enables our continued investigation into the role of autophagy in cancer chemotherapy.

The image sequence shown in Figure 1 shows the physical changes that occur in CWR22 cells during the first 80 min of autophagy induction. In this and other studies (not shown) we consistently observed: (1) displacement of the nucleus away from the cell center; (2) reduction of focal adhesion points; and (3) general translocation of autophagosomes and lysosomes towards the center of the cell. In addition, we also observed a small increase in colocalization (indicated in yellow) between autophagosomes (gre...

Watch this Scientific Journal Video about Quantitative Analysis of Autophagy using Advanced 3D Fluorescence Microscopy at JoVE.com

Quantitative Analysis of Autophagy using Advanced 3D Fluorescence Microscopy

Autophagy is a ubiquitous process that enables cells to degrade and recycle proteins and organelles. We apply advanced fluorescence microscopy to visualize and quantify the small, but essential, physical changes associated with the induction of autophagy, including the formation and distribution of autophagosomes and lysosomes, and their fusion into autolysosomes.

Prostate cancer is the leading form of malignancies among men in the U.S. While surgery carries a significant risk of impotence and incontinence, ...

quantitative-analysis-autophagy-using-advanced-3d-fluorescence

Research

Education

JoVE Journal

JoVE Core

Cell Biology

Biology

Unit 1

Cell Death

SCIENTISTS IN ACTION

17.8K vistas.  University of California, Davis. La autofagia es un proceso ubicuo que permite a las células para degradar y reciclar las proteínas y orgánulos. Aplicamos microscopía de fluorescencia avanzada para visualizar y cuantificar la pequeña, pero, cambios físicos esenciales asociados con la inducción de la autofagia, incluyendo la formación y distribución de autofagosomas y lisosomas, y su fusión en autolisosomas.

Video: Quantitative Analysis of Autophagy using Advanced 3D Fluorescence Microscopy

Visualizing Single Molecular Complexes In Vivo Using Advanced Fluorescence Microscopy

Full insight into the mechanisms of living cells can be achieved only by investigating the key processes that elicit and direct events at a cellular level. To date the shear complexity of biological systems has caused precise single-molecule experimentation to be far too demanding, instead focusing on studies of single systems using relatively crude bulk ensemble-average measurements. However, many important processes occur in the living cell at the level of just one or a few molecules; ensemble measurements generally mask the stochastic and heterogeneous nature of these events. Here, using advanced optical microscopy and analytical image analysis tools we demonstrate how to monitor proteins within a single living bacterial cell to a precision of single molecules and how we can observe dynamics within molecular complexes in functioning biological machines. The techniques are directly relevant physiologically. They are minimally-perturbative and non-invasive to the biological sample under study and are fully attuned for investigations in living material, features not readily available to other single-molecule approaches of biophysics. In addition, the biological specimens studied all produce fluorescently-tagged protein at levels which are almost identical to the unmodified cell strains ("genomic encoding"), as opposed to the more common but less ideal approach for generating significantly more protein than would occur naturally ('plasmid expression'). Thus, the actual biological samples which will be investigated are significantly closer to the natural organisms, and therefore the observations more relevant to real physiological processes.

Visualizing Single Molecular Complexes In Vivo Using Advanced Fluorescence Microscopy

Here we demonstrate the protocols for performing single-molecule fluorescence microscopy on living bacterial cells to enable functional molecular complexes to be detected, tracked and quantified.

Full insight into the mechanisms of living cells can be achieved only by investigating the key processes that elicit and direct events at a cellular ...

Time-lapse Imaging of Mitosis After siRNA Transfection

Changes in cellular organization and chromosome dynamics that occur during mitosis are tightly coordinated to ensure accurate inheritance of genomic and cellular content. Hallmark events of mitosis, such as chromosome movement, can be readily tracked on an individual cell basis using time-lapse fluorescence microscopy of mammalian cell lines expressing specific GFP-tagged proteins. In combination with RNAi-based depletion, this can be a powerful method for pinpointing the stage(s) of mitosis where defects occur after levels of a particular protein have been lowered. In this protocol, we present a basic method for assessing the effect of depleting a potential mitotic regulatory protein on the timing of mitosis. Cells are transfected with siRNA, placed in a stage-top incubation chamber, and imaged using an automated fluorescence microscope. We describe how to use software to set up a time-lapse experiment, how to process the image sequences to make either still-image montages or movies, and how to quantify and analyze the timing of mitotic stages using a cell-line expressing mCherry-tagged histone H2B. Finally, we discuss important considerations for designing a time-lapse experiment. This strategy is complementary to other approaches and offers the advantages of 1) sensitivity to changes in kinetics that might not be observed when looking at cells as a population and 2) analysis of mitosis without the need to synchronize the cell cycle using drug treatments. The visual information from such imaging experiments not only allows the sub-stages of mitosis to be assessed, but can also provide unexpected insight that would not be apparent from cell cycle analysis by FACS.

Here we describe a basic protocol to image and quantify the mitotic timing of live mammalian tissue culture cells after siRNA transfection.

Changes in cellular organization and chromosome dynamics that occur during mitosis are tightly coordinated to ensure accurate inheritance of genomic and ...

Quantitative Live Cell Fluorescence-microscopy Analysis of Fission Yeast

Several microscopy techniques are available today that can detect a specific protein within the cell. During the last decade live cell imaging using fluorochromes like Green Fluorescent Protein (GFP) directly attached to the protein of interest has become increasingly popular 1. Using GFP and similar fluorochromes the subcellular localisations and movements of proteins can be detected in a fluorescent microscope. Moreover, also the subnuclear localisation of a certain region of a chromosome can be studied using this technique. GFP is fused to the Lac Repressor protein (LacR) and ectopically expressed in the cell where tandem repeats of the lacO sequence has been inserted into the region of interest on the chromosome2. The LacR-GFP will bind to the lacO repeats and that area of the genome will be visible as a green dot in the fluorescence microscope. Yeast is especially suited for this type of manipulation since homologous recombination is very efficient and thereby enables targeted integration of the lacO repeats and engineered fusion proteins with GFP 3. Here we describe a quantitative method for live cell analysis of fission yeast. Additional protocols for live cell analysis of fission yeast can be found, for example on how to make a movie of the meiotic chromosomal behaviour 4. In this particular experiment we focus on subnuclear organisation and how it is affected during gene induction. We have labelled a gene cluster, named Chr1, by the introduction of lacO binding sites in the vicinity of the genes. The gene cluster is enriched for genes that are induced early during nitrogen starvation of fission yeast 5. In the strain the nuclear membrane (NM) is labelled by the attachment of mCherry to the NM protein Cut11 giving rise to a red fluorescent signal. The Spindle Pole body (SPB) compound Sid4 is fused to Red Fluorescent Protein (Sid4-mRFP) 6. In vegetatively growing yeast cells the centromeres are always attached to the SPB that is embedded in the NM 7. The SPB is identified as a large round structure in the NM. By imaging before and 20 minutes after depletion of the nitrogen source we can determine the distance between the gene cluster (GFP) and the NM/SPB. The mean or median distances before and after nitrogen depletion are compared and we can thus quantify whether or not there is a shift in subcellular localisation of the gene cluster after nitrogen depletion.

The fission yeast, Schizosaccharomyces pombe, is a good model system to study basic cellular processes. Here we describe a method to perform quantitative live cell analysis of fission yeast. In this particular experiment we focus on organisation of the genome within the cell nucleus, but the method can also be used to study cytosolic factors.

Several microscopy techniques are available today that can detect a specific protein within the cell. During the last decade live cell imaging using ...

Quantitative Analysis of Random Migration of Cells Using Time-lapse Video Microscopy

Cell migration is a dynamic process, which is important for embryonic development, tissue repair, immune system function, and tumor invasion 1, 2. During directional migration, cells move rapidly in response to an extracellular chemotactic signal, or in response to intrinsic cues 3 provided by the basic motility machinery. Random migration occurs when a cell possesses low intrinsic directionality, allowing the cells to explore their local environment.
Cell migration is a complex process, in the initial response cell undergoes polarization and extends protrusions in the direction of migration 2. Traditional methods to measure migration such as the Boyden chamber migration assay is an easy method to measure chemotaxis in vitro, which allows measuring migration as an end point result. However, this approach neither allows measurement of individual migration parameters, nor does it allow to visualization of morphological changes that cell undergoes during migration.
Here, we present a method that allows us to monitor migrating cells in real time using video - time lapse microscopy. Since cell migration and invasion are hallmarks of cancer, this method will be applicable in studying cancer cell migration and invasion in vitro. Random migration of platelets has been considered as one of the parameters of platelet function 4, hence this method could also be helpful in studying platelet functions. This assay has the advantage of being rapid, reliable, reproducible, and does not require optimization of cell numbers. In order to maintain physiologically suitable conditions for cells, the microscope is equipped with CO2 supply and temperature thermostat. Cell movement is monitored by taking pictures using a camera fitted to the microscope at regular intervals. Cell migration can be calculated by measuring average speed and average displacement, which is calculated by Slidebook software.

This method allows monitoring of cells in real time and quantitative measurements of different cell migration parameters such as speed, displacement, and velocity. Unlike the traditional methods, this real time approach is not based on endpoint quantitative migration measurements; instead it allows monitoring and calculating different parameters continuously.

Cell migration is a dynamic process, which is important for embryonic development, tissue repair, immune system function, and tumor invasion 1, 2. During ...

Visualization and Analysis of mRNA Molecules Using Fluorescence In Situ Hybridization in Saccharomyces cerevisiae

The Fluorescence in situ Hybridization (FISH) method allows one to detect nucleic acids in the native cellular environment. Here we provide a protocol for using FISH to quantify the number of mRNAs in single yeast cells. Cells can be grown in any condition of interest and then fixed and made permeable. Subsequently, multiple single-stranded deoxyoligonucleotides conjugated to fluorescent dyes are used to label and visualize mRNAs. Diffraction-limited fluorescence from single mRNA molecules is quantified using a spot-detection algorithm to identify and count the number of mRNAs per cell. While the more standard quantification methods of northern blots, RT-PCR and gene expression microarrays provide information on average mRNAs in the bulk population, FISH facilitates both the counting and localization of these mRNAs in single cells at single-molecule resolution.

Visualization and Analysis of mRNA Molecules Using Fluorescence In Situ Hybridization in Saccharomyces cerevisiae

This protocol describes an experimental procedure for performing Fluorescence in situ Hybridization (FISH) for counting mRNAs in single cells at single-molecule resolution.

The Fluorescence in situ Hybridization (FISH) method allows one to detect nucleic acids in the native cellular environment. Here we provide a protocol for ...

Rapid Analysis and Exploration of Fluorescence Microscopy Images

Despite rapid advances in high-throughput microscopy, quantitative image-based assays still pose significant challenges. While a variety of specialized image analysis tools are available, most traditional image-analysis-based workflows have steep learning curves (for fine tuning of analysis parameters) and result in long turnaround times between imaging and analysis. In particular, cell segmentation, the process of identifying individual cells in an image, is a major bottleneck in this regard.
Here we present an alternate, cell-segmentation-free workflow based on PhenoRipper, an open-source software platform designed for the rapid analysis and exploration of microscopy images. The pipeline presented here is optimized for immunofluorescence microscopy images of cell cultures and requires minimal user intervention. Within half an hour, PhenoRipper can analyze data from a typical 96-well experiment and generate image profiles. Users can then visually explore their data, perform quality control on their experiment, ensure response to perturbations and check reproducibility of replicates. This facilitates a rapid feedback cycle between analysis and experiment, which is crucial during assay optimization. This protocol is useful not just as a first pass analysis for quality control, but also may be used as an end-to-end solution, especially for screening. The workflow described here scales to large data sets such as those generated by high-throughput screens, and has been shown to group experimental conditions by phenotype accurately over a wide range of biological systems. The PhenoBrowser interface provides an intuitive framework to explore the phenotypic space and relate image properties to biological annotations. Taken together, the protocol described here will lower the barriers to adopting quantitative analysis of image based screens.

Here we describe a workflow for rapidly analyzing and exploring collections of fluorescence microscopy images using PhenoRipper, a recently developed image-analysis platform.

Despite rapid advances in high-throughput microscopy, quantitative image-based assays still pose significant challenges. While a variety of specialized ...

Analysis of Autophagy in Penicillium chrysogenum by Using Starvation Pads in Combination With Fluorescence Microscopy

The study of cellular quality control systems has emerged as a highly dynamic and relevant field of contemporary research. It has become clear that cells possess several lines of defense against damage to biologically relevant molecules like nucleic acids, lipids and proteins. In addition to organelle dynamics (fusion/fission/motility/inheritance) and tightly controlled protease activity, the degradation of surplus, damaged or compromised organelles by autophagy (cellular &#8216;self-eating&#8217;) has received much attention from the scientific community. The regulation of autophagy is quite complex and depends on genetic and environmental factors, many of which have so far not been elucidated. Here a novel method is presented that allows the convenient study of autophagy in the filamentous fungus Penicillium chrysogenum. It is based on growth of the fungus on so-called &#8216;starvation pads&#8217; for stimulation of autophagy in a reproducible manner. Samples are directly assayed by microscopy and evaluated for autophagy induction / progress. The protocol presented here is not limited for use with P. chrysogenum and can be easily adapted for use in other filamentous fungi.

Analysis of Autophagy in Penicillium chrysogenum by Using Starvation Pads in Combination With Fluorescence Microscopy

A convenient and powerful method for studying autophagy in Penicillium chrysogenum by using starvation pads (mixtures of agarose and tap water in a microscope slide containing a central cavity) is presented here.

The study of cellular quality control systems has emerged as a highly dynamic and relevant field of contemporary research. It has become clear that cells ...

Identification of Kinesin-1 Cargos Using Fluorescence Microscopy

Fluorescence microscopy is employed to identify Kinesin-1 cargos. Recently, the heavy chain of Kinesin-1 (KIF5B) was shown to transport the nuclear transcription factor c-MYC for proteosomal degradation in the cytoplasm. The method described here involves the study of a motorless KIF5B mutant for fluorescence microscopy. The wild-type and motorless KIF5B proteins are tagged with the fluorescent protein tdTomato. The wild-type tdTomato-KIF5B appears homogenously in the cytoplasm, while the motorless tdTomato-KIF5B mutant forms aggregates in the cytoplasm. Aggregation of the motorless KIF5B mutant induces aggregation of its cargo c-MYC in the cytoplasm. Hence, this method provides a visual means to identify the cargos of Kinesin-1. A similar strategy can be utilized to identify cargos of other motor proteins.

Here, a protocol is presented to identify Kinesin-1 cargos. A motorless mutant of the Kinesin-1 heavy chain (KIF5B) aggregates in the cytoplasm and induces aggregation of its cargos. Both aggregates are detected under fluorescence microscopy. A similar strategy can be employed to identify cargos of other motor proteins.

Fluorescence microscopy is employed to identify Kinesin-1 cargos. Recently, the heavy chain of Kinesin-1 (KIF5B) was shown to transport the nuclear ...

Open Source High Content Analysis Utilizing Automated Fluorescence Lifetime Imaging Microscopy

We present an open source high content analysis instrument utilizing automated fluorescence lifetime imaging (FLIM) for assaying protein interactions using F&#246;rster resonance energy transfer (FRET) based readouts of fixed or live cells in multiwell plates. This provides a means to screen for cell signaling processes read out using intramolecular FRET biosensors or intermolecular FRET of protein interactions such as oligomerization or heterodimerization, which can be used to identify binding partners. We describe here the functionality of this automated multiwell plate FLIM instrumentation and present exemplar data from our studies of HIV Gag protein oligomerization and a time course of a FRET biosensor in live cells. A detailed description of the practical implementation is then provided with reference to a list of hardware components and a description of the open source data acquisition software written in &#181;Manager. The application of FLIMfit, an open source MATLAB-based client for the OMERO platform, to analyze arrays of multiwell plate FLIM data is also presented. The protocols for imaging fixed and live cells are outlined and a demonstration of an automated multiwell plate FLIM experiment using cells expressing fluorescent protein-based FRET constructs is presented. This is complemented by a walk-through of the data analysis for this specific FLIM FRET data set.

We present an open source high content analysis (HCA) instrument utilizing automated fluorescence lifetime imaging (FLIM) for assaying protein interactions using F&#246;rster resonance energy transfer (FRET) based readouts. Data acquisition for this openFLIM-HCA instrument is controlled by software written in &#181;Manager and data analysis is undertaken in FLIMfit.

We present an open source high content analysis instrument utilizing automated fluorescence lifetime imaging (FLIM) for assaying protein interactions ...

Functional Imaging of Viral Transcription Factories Using 3D Fluorescence Microscopy

It is well known that spatial and temporal regulation of genes is an integral part of governing proper gene expression. Consequently, it is invaluable to understand where and when transcription is taking place within nuclear space and to visualize the relationship between episomes infected within the same cell's nucleus. Here, both immunofluorescence (IFA) and RNA-FISH have been combinedto identify actively transcribing Kaposi's sarcoma-associated herpesvirus (KSHV) episomes. By staining KSHV latency-associated nuclear antigen (LANA), it is possible to locate where viral episomes exist within the nucleus. In addition, by designing RNA-FISH probes to target the intron region of a viral gene, which is expressed only during productive infection, nascent RNA transcripts can be located. Using this combination of molecular probes, it is possible to visualize the assembly of large viral transcription factories and analyze the spatial regulation of viral gene expression during KSHV reactivation. By including anti-RNA polymerase II antibody staining, one can also visualize the association between RNA polymerase II (RNAPII) aggregation and KSHV transcription during reactivation.

Viral transcriptional factories are discrete structures that are enriched with cellular RNA polymerase II to increase viral gene transcription during reactivation. Here, a method to locate sites of actively transcribing viral chromatin in 3D nuclear space by a combination of immunofluorescence staining and in situ RNA hybridization is described.

It is well known that spatial and temporal regulation of genes is an integral part of governing proper gene expression. Consequently, it is invaluable to ...

Speed

Subtitles

Quantitative Analysis of Autophagy using Advanced 3D Fluorescence Microscopy