This work was supported by grants from the University of Buenos Aires (UBACyT 2018-2020 20020170100082BA), the National Council for Scientific Research and Technology (CONICET) (PIP 2021-2023 GI&#8722; 11220200101549CO; and PUE 22920170100033) and the National Agency for Scientific and Technological Promotion (PICT 2019-01664).

1. Cell preparation
<ol>
	<li>Soak 12 mm round coverslips in absolute ethanol, and place them vertically in the wells of a 24-well plate.</li>
	<li>Remove the cover, and expose the multi-well plate to ultraviolet radiation for 15 min.</li>
	<li>Position the coverslips horizontally, and wash them with Dulbecco&#39;s Modified Eagle Medium (DMEM).</li>
	<li>Seed a low passage number of pancreatic cells. The amount should be adjusted to obtain 50%-75% confluency on the day of fixation16. 
	NOTE: It is recommended to seed 2.5 &#215; 104 PANC-1 or 4 &#215; 104 AR42J cells per well to fixate the cells after 3 days.</li>
	<li>Culture the cells in DMEM containing 10% fetal bovine serum, 100 U/mL penicillin, and 100 &#181;g/mL streptomycin in an incubator at 37 &#176;C under a humidified atmosphere with 5% carbon dioxide (CO2). 
	&#8203;NOTE: For PANC-1 cells, it is recommended to incubate the cells for 2 days between cell seeding and the following steps. After this time, the cells can be transfected, treated, or fixated. This protocol exemplifies the treatment with gemcitabine in non-transfected PANC-1 cells and the differentiation and PP242 treatment for non-transfected AR42J cells.</li>
</ol>
2. Treating the cells
<ol>
	<li>Gemcitabine treatment for PANC-1 cells
	<ol>
		<li>Prepare a solution of 1 &#181;g/&#181;L gemcitabine in DMEM 2 days after seeding. Treat each well with 2.6 &#181;L of the 1 &#181;g/&#181;L gemcitabine solution to achieve a final dilution of 20 &#181;M.</li>
		<li>Incubate the cells for 24 h in the incubator.</li>
	</ol>
	</li>
	<li>AR42J differentiation and PP242 treatment
	<ol>
		<li>Prepare a solution of 4 &#181;g/mL dexamethasone in DMEM.</li>
		<li>Treat each well with 4.9 &#181;L of 4 &#181;g/mL dexamethasone solution to obtain a final dilution of 100 nM.</li>
		<li>Incubate the cells for 48 h in the incubator.</li>
		<li>Remove the medium, and treat each well with 0.5 &#181;L of 1 mM PP242 to obtain a final dilution of 1 &#181;M.</li>
		<li>Incubate the cells for 2 h in the incubator.</li>
	</ol>
	</li>
</ol>
3. Fixing and permeabilizing the cells
<ol>
	<li>Prepare a 24-well plate with cold methanol and a 6-well plate with cold phosphate-buffered saline (PBS; 137 mM NaCl, 2.7 mM KCl, 8 mM Na2HPO4, 2 mM KH2PO4). Maintain them on ice.</li>
	<li>Take each coverslip with tweezers, wash it twice in PBS, and incubate for 6 min in methanol.</li>
</ol>
4. Blocking the cells
<ol>
	<li>Wash each coverslip twice in PBS, and incubate for 1 h in 10% fetal bovine serum in PBS (blocking solution). 
	&#8203;NOTE: In this step, the protocol might be paused. The coverslips can be stored overnight in the fridge in the blocking solution, and the protocol can be continued the following day.</li>
</ol>
5. Incubating the coverslips with the primary antibody
<ol>
	<li>Prepare a 1:1,000 solution of anti-LC3 in the blocking solution, and maintain it on ice.</li>
	<li>Place a piece of laboratory sealing film over the multi-well lid.</li>
	<li>Place one drop (25 &#181;L) per coverslip of anti-LC3 solution over the sealing film.</li>
	<li>Take each coverslip with tweezers, and place it over the primary antibody drop, taking care that the cell side is in contact with the solution.</li>
	<li>Prepare a humid chamber by placing a humid piece of paper into a flat-bottom plastic box.</li>
	<li>Place the multi-well plate into the humidity chamber, cover it with foil, and incubate overnight in the fridge.</li>
</ol>
6. Incubating the coverslips with the secondary antibody
<ol>
	<li>Remove the multi-well plate from the humidity chamber, and place the coverslips back in the multi-well plate.</li>
	<li>Perform three washes with PBS.</li>
	<li>Prepare a solution of fluorescently labeled anti-rabbit with a dilution of 1:800 in the blocking solution, and maintain it on ice protected from light.</li>
	<li>Place a sealing film piece over the multi-well lid.</li>
	<li>Place a drop (25 &#181;L) per coverslip of anti-rabbit solution over the sealing film.</li>
	<li>Take each coverslip with tweezers, and place it over the primary antibody drop, taking care that the cell side is in contact with the solution.</li>
	<li>Incubate the multi-well plate in the humidity chamber for 2 h at room temperature (RT) protected from light.</li>
</ol>
7. Staining the cells with 4&#8242; ,6-diamidino-2-phenylindole (DAPI)
<ol>
	<li>Remove the multi-well plate from the humidity chamber, and place the coverslips back in the multi-well plate.</li>
	<li>Perform three washes with PBS.</li>
	<li>Prepare a 300 nM solution of DAPI in PBS (protected from light).</li>
	<li>Incubate each coverslip with the DAPI solution for 10 min.</li>
	<li>Perform three washes with PBS. Maintain the multi-well plate protected from light.</li>
</ol>
8. Montage
<ol>
	<li>Prepare two beakers with water and a piece of paper.</li>
	<li>Place one drop (10 &#181;L) per coverslip of a polyvinyl alcohol-Bis(trimethylaluminum)-1,4-diazabicyclo[2.2.2]octane adduct (PVA-DABCO) solution on a slide. 
	NOTE: PVA-DABCO is prepared by combining 0.25 M DABCO, 10% W/V PVA, 20% glycerol, and 50% Tris HCl (1.5 M, pH 8.8) in ultrapure water.</li>
	<li>Take each coverslip with tweezers, wash it in each water beaker, dry it off in the paper, and place it over the PVA-DABCO drop (with the cells in contact with the solution).</li>
	<li>Let it dry overnight, protected from light.</li>
</ol>
9. Confocal microscopy viewing and image capture
<ol>
	<li>Visualize the coverslips in an inverted confocal microscope using an objective of around 63x17.</li>
	<li>Capture representative images of the labeled cells.</li>
</ol>
10. Quantifying the LC3 dots
<ol>
	<li>Drag and drop each image file containing the captured channels, such as &#34;.czi&#34;, into the ImageJ (FIJI) screen to open. Click on Ok in the dialog box, and close the Console window.</li>
	<li>From the Image tab, select Color &#62; Split Channels.</li>
	<li>Close the images corresponding to the channels other than the LC3 image.</li>
	<li>From the Image tab, select Adjust &#62; Color Balance</li>
	<li>Move the Maximum slider to the left until the image is saturated to visualize the cell contours.</li>
	<li>Draw the cell outline with the Freehand Selection tool.</li>
	<li>Click on the Reset button to reset the color adjustment.</li>
	<li>From the Edit tab, select Cut to cut the selected item.</li>
	<li>Close the image without saving it.</li>
	<li>From the Edit tab, select Paste.</li>
	<li>In the Analyze menu, choose the tool 3D Objects Counter.</li>
	<li>Set the threshold. In the example provided in this study, the threshold is set at 2,000.</li>
	<li>Set the size filter. In this study, it is set between 50 and 500.</li>
	<li>Be sure that the boxes Objects and Summary are marked.</li>
	<li>Click on Ok. The number of dots will be described as Objects Detected in the Summary.</li>
</ol>
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/65005/65005fig01.jpg" /> 
Figure 1: Schematic diagram of the LC3 immunofluorescence protocol. Schematic diagram that represents the general protocol provided for LC3 immunofluorescence. Figure created with BioRender.com. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/65005/65005fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

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No conflicts of interest were declared.

The method described in this protocol allows for visualizing the endogenous LC3 distribution in the cell and quantifying the autophagic levels under different conditions. Another similar method used to analyze the LC3 distribution and determine autophagy activation involves fluorescence-labeled LC3 transfection (such as RFP-LC3)19. RFP-LC3 transfection has the advantages of not needing fixation (which allows for applying this method in live cell imaging20), being cheaper, and not depending on LC3 antibody reactivity. On the other hand, the immunofluorescence of LC3 has the advantage of providing an image of the endogenous LC3, thus avoiding possible issues related to LC3 overexpression, such as the formation of protein aggregates that are independent of autophagy21. Moreover, this method does not depend on the ease of transfecting the cells, meaning it is applicable to diverse cell lines. However, depending on the LC3 antibody that is used and its reactivity, there are some cellular lines in which it might not work. Some antibodies may work well for certain species but not for others, even when they are theoretically compatible with different species. In the case of the antibody used in this protocol (LC3B&#160;D11), we have found that it works perfectly for human cells (PANC-1, HEK293T, HeLa) and rat cells (AR42J). However, it does not work for mouse cells (MEF cells), as we observed nonspecific nuclear staining. It is worth noting that the quantification of LC3 spots, whether endogenous or overexpressed, has limitations in distinguishing between changes in autophagy activation, which may indicate the increased production of LC3-II, and changes in LC3-II degradation, which may indicate an autophagic flux state. Additional methods can be used to comprehensively assess autophagy activity. For instance, the use of RFP-GFP-LC3 expression can provide an accurate assessment by distinguishing between LC3-II inside or outside of the lysosome22,23.
As shown in Figure 4, there are some critical steps in the protocol that must not be modified, given that their modification can lead to suboptimal outcomes. First, it is important to set the correct number of cells to be seeded. When not enough cells are seeded, they tend not to resist transfection or treatments and remain rounded. On the contrary, when cells are seeded in excess, they tend to grow on top of the neighboring cells, making it challenging to focus on individual cells and distinguish between their LC3 dots. Notably, in situations where cells are in close proximity but not overlapping&#160;as depicted in Figure 4A, it may be helpful to use immunostaining with specific membrane markers, such as EGFR, to distinguish between the positive markers belonging to each cell24. However, it is important to note that certain markers like E-cadherin and EpCAM are not suitable for this purpose in PANC-1 cells due to their reduced membrane expression, which results from the typical epithelial-mesenchymal transition process associated with this cell type25,26,27. Secondly, when working specifically with PANC-1 cells, it is essential to wait at least 1 day between the seeding and the subsequent steps of the experiment. Conversely, when one does not wait for the right time, the cells can be rounded, making it difficult to interpret the results. Thirdly, fixation is a critical step in this protocol. As we have shown, the method only works with an adequate methanol fixation. Paraformaldehyde fixation does not work correctly for LC3 immunolabelling, while the methanol fixation time should not be modified, given that shorter times might lead to an incomplete fixation. We tested methanol fixation times up to 1 h and did not observe differences in LC3 labeling. Nevertheless, we advise against the use of prolonged fixation times, as methanol fixation can lead to the loss of soluble cellular proteins and free fluorescent molecules28. Therefore, it is recommended to adhere to the standard fixation time to ensure precise and dependable results.
Some modifications might be accepted in the described protocol. For example, a 12-well plate can be used instead of the 24-well plate, as well as growing the cells over 15 mm round coverslips instead of 12 mm coverslips. In this case, it should be considered that the number of cells to be seeded, as well as the volumes of reagents used, will be greater than those described in this protocol. In this case, 4 &#215; 104 PANC-1 and 6.5 &#215; 104 AR42J should be seeded. Additionally, the used blocking solution can be replaced with others, like 1% BSA in PBS, and this would lead to similar results. In the same way, the blocking time could be increased up to 24 h without significantly altering the results. The antibody incubation times and concentration might be adjusted and can change, for example, if another LC3 antibody is used. Although PVA-DABCO solution is prepared in this study, commercial montage solutions can also be used. On the other hand, the quantification method can be modified. For example, applying some filters or masks to the images is possible, and an alternative tool can be used for dot quantification.
In this work, we directed the application of the immunofluorescence of LC3 to study the behavior of pancreatic cancer cells. In these cells, autophagy is basally activated and might be modulated as a response to diverse stressful situations, such as chemotherapy, hypoxia, or nutrient deficiency11,12. The determination of autophagy in these cells may be applicable to studying the cellular response to chemotherapy, radiotherapy, or other treatments that modulate autophagy. As shown in Figure 3, the presented method can be applied in physiological models.&#160;Although, in this work, we focused on the quantification of autophagic levels, the immunofluorescence of LC3 might also allow the evaluation of the colocalization between LC3 and diverse proteins. It can serve, for example, as a mechanistic approach to mark proteins at different points in the autophagic process and evaluate whether the colocalization with LC3 is affected by some treatments or by the downregulation of some proteins. In this way, it could be determined, for example, whether some autophagy inhibitor interrupts the autophagic flux before or after LC3 conjugation. Finally, the method can also be adapted to tissue samples to determine autophagy activation in animal models or human biopsy samples.

Macroautophagy (commonly referred to as autophagy) is a specialized catabolic process that selectively degrades cytoplasmic components, including proteins and damaged organelles1,2. Autophagy allows cells to physiologically respond to stress stimuli and, thus, maintain cellular homeostasis3. During autophagy, a double membrane vesicle is formed: the autophagosome. The autophagosome contains the cargo molecules and drives them to the lysosome for degradation1,4. 
Autophagosomes are decorated by the autophagic protein microtubule-associated protein light chain 3 (LC3)5. When autophagy is not induced, LC3 is diffused in the cytoplasm and nucleus in the LC3-I conformation. On the other hand, when autophagy is induced, LC3 is conjugated with a phosphatidylethanolamine in the membrane of the autophagic structures6. This new LC3 conformation is known as LC3-II1. The LC3 conformation shift causes changes in its cellular localization and its dodecyl sodium sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) migration, which can be detected by techniques such as immunofluorescence and western blot5,7. In this way, LC3 conjugation is a key event in the autophagic process that can be used to measure autophagic activity.
The pancreatic acinar cell is a highly differentiated cell that, under healthy conditions, has a low rate of autophagy. However, in different physiological conditions or under pharmacological stimulation, they can activate autophagy. Therefore, the determination of autophagic levels in this cell line is useful for studying the potential direct or indirect effects of different pharmacological or biological agents on autophagy8,9.
Ductal pancreatic adenocarcinoma is one of the deadliest types of cancer, given its late diagnosis and its high chemotherapy resistance10. Pancreatic cancer cells have high autophagy activity due to the transcriptional upregulation and post-translational activation of autophagy-related proteins11. Pancreatic cancer cells may adjust their autophagy levels in response to unfavorable conditions like hypoxia, nutrient deprivation, or chemotherapy-induced damage11. Hence, analyzing the autophagy levels in pancreatic cancer cells can help understand how they adapt to varying environments and evaluate the effectiveness of autophagy-modulating treatments.
This study shows a method to perform LC3 immunofluorescence in two distinct pancreatic cellular models. The first model, PANC-1 cells, served as a model for pancreatic ductal adenocarcinoma. These cells were treated with gemcitabine, a chemotherapy agent that has previously been shown to induce autophagy, specifically in pancreatic cancer cells carrying the oncogenic Kirsten rat sarcoma virus gene (KRAS)12,13. The second model, AR42J cells, served as a more physiological model of exocrine pancreatic cells. These cells were differentiated with dexamethasone to become more similar to acinar pancreatic cells14. In these cells, autophagy was pharmacologically induced through the use of PP242, which is a potent mTOR inhibitor15. In this study, we demonstrate the applicability of the protocol described with two different pancreatic models and its ability to discriminate between states of low and high autophagy.

<table><tbody><tr><td>10x Phosphate-Buffered Saline (PBS)</td><td>Corning</td><td>46-013-CM</td><td></td></tr><tr><td>12 mm round coverslips</td><td>HDA</td><td>CBR_OBJ_6467</td><td></td></tr><tr><td>24 Well- Cell Culture Plate</td><td>Sorfa</td><td>220300</td><td></td></tr><tr><td>Absolute ethanol</td><td>Biopack</td><td>2207.10.00</td><td></td></tr><tr><td>Alexa Fluor 594 Donkey anti-rabbit IgG (H+L)</td><td>Invitrogen</td><td>R37119</td><td></td></tr><tr><td>Confocal Laser Scanning Microscope</td><td>Zeiss</td><td>LSM 800</td><td></td></tr><tr><td>Dexamethasone</td><td>Sigma Aldrich</td><td>D4902</td><td></td></tr><tr><td>DMEN</td><td>Sartorius</td><td>01-052-1A</td><td></td></tr><tr><td>Fetal Bovine Serum</td><td>NATOCOR&amp;nbsp;</td><td>Lintc-634</td><td></td></tr><tr><td>Gemcitabina</td><td>Eli Lilly</td><td>VL7502</td><td></td></tr><tr><td>LC3B (D11) XP Rabbit mAb</td><td>Cell Signaling Technology</td><td>3868S</td><td></td></tr><tr><td>Methanol</td><td>Anedra</td><td>6197</td><td></td></tr><tr><td>Parafilm &quot;M&quot; (Laboratory Sealing Film)</td><td>Bemis/Curwood</td><td>PM-996</td><td></td></tr><tr><td>Pen-Strep Solution</td><td>Sartorius</td><td>03-031-1B</td><td></td></tr><tr><td>PP242</td><td>Santa Cruz Biotechnology</td><td>SC-301606</td><td></td></tr><tr><td>Trypsin EDTA</td><td>Gibco</td><td>11570626</td><td></td></tr></tbody></table>

evaluating autophagy levels in two different pancreatic cell models using lc3 immunofluorescence

Autophagy is a specialized catabolic process that selectively degrades cytoplasmic components, including proteins and damaged organelles. Autophagy allows cells to physiologically respond to stress stimuli and, thus, maintain cellular homeostasis. Cancer cells might modulate their autophagy levels to adapt to adverse conditions such as hypoxia, nutrient deficiency, or damage caused by chemotherapy. Ductal pancreatic adenocarcinoma is one of the deadliest types of cancer. Pancreatic cancer cells have high autophagy activity due to the transcriptional upregulation and post-translational activation of autophagy proteins.
Here, the PANC-1 cell line was used as a model of pancreatic human cancer cells, and the AR42J pancreatic acinar cell line was used as a physiological model of highly differentiated mammalian cells. This study used the immunofluorescence of microtubule-associated protein light chain 3 (LC3) as an indicator of the status of autophagy activation. LC3 is an autophagy protein that, in basal conditions, shows a diffuse pattern of distribution in the cytoplasm (known as LC3-I in this condition). Autophagy induction triggers the conjugation of LC3 to phosphatidylethanolamine on the surface of newly formed autophagosomes to form LC3-II, a membrane-bound protein that aids in the formation and expansion of autophagosomes. To quantify the number of labeled autophagic structures, the open-source software FIJI was utilized with the aid of the &#34;3D Objects Counter&#34; tool.
The measure of the autophagic levels both in physiological conditions and in cancer cells allows us to study the modulation of autophagy under diverse conditions such as hypoxia, chemotherapy treatment, or the knockdown of certain proteins.

This protocol performs immunofluorescence of LC3 in pancreatic cell lines to determine the autophagy levels in different conditions. The outcome of this experiment was the obtention of cellular images from the red and blue channels, corresponding to LC3 and DAPI. The LC3 images indicate the cellular distribution of this protein, whereas the DAPI shows the nuclear localization. Figure 2A shows a representative image of the immunofluorescence of LC3 and its merge with DAPI staining in PANC-1 cells under basal or gemcitabine treatment conditions. A set of images of LC3 staining was analyzed using the tool 3D Objects Counter in FIJI. Using this software, the amount of LC3 dots per cell was quantified. The bar graph in Figure 2B shows the results of LC3 dot quantification in PANC-1 cells under basal versus gemcitabine treatment conditions. In this graph, the LC3 dots significantly increased under gemcitabine treatment, with the number of LC3 dots directly indicating the autophagic activity. We also previously demonstrated that gemcitabine triggers autophagy in pancreatic cancer cells12. Overall, the method presented in this article allows the detection of the level of increase in autophagy activation induced by gemcitabine in these cells.
While this protocol focuses on using LC3 immunofluorescence to determine autophagic activity in pancreatic cancer cells, it could potentially be applied to other cell lines, including more physiologically relevant models. To test the method&#39;s efficacy in assessing physiological responses, the AR42J cell line was used. Although these cells are derived from a rat exocrine pancreas tumor, they can be differentiated into exocrine cells with glucocorticoid stimulation, thus making them a suitable pancreatic model8,14,18. The AR42J cells were differentiated with 100 nM dexamethasone treatment for 48 h, followed by treatment with the mTOR inhibitor PP242 to induce autophagy15. The obtained results are presented in Figure 3, which shows a significant increase in the number of LC3 dots per cell under the PP242 treatment.
Thus far, we have demonstrated that the presented method is effective for assessing autophagic activity in both cancer cells and a more physiological model. However, it is important to note that minor deviations from the presented protocol could result in uninterpretable results.
Figure 4A shows a representative image from a suboptimal experiment in which too many cells were seeded on the coverslips, and excessive confluence was obtained. This kind of experiment might be uninterpretable for diverse reasons. Firstly, the cellular types mentioned in this work are derived from the exocrine pancreas, where the cells are grouped in acini. Under an excessive confluence, these cells tend to pile up and grow on top of each other (such as cell 1 and cell 2 in Figure 4A, which are above cell 3 and cell 4). This phenomenon makes it practically impossible to know which cell the LC3 dots belong to, thus making it very difficult to estimate the number of dots per cell. On the other hand, cells at high confluency tend to be stressed, which triggers autophagy. As a result, the differences in autophagic levels between the control and treated cells might decrease due to an increase in the background autophagic activity.
In Figure 4B, a representative image from another kind of suboptimal experiment is shown in which the cells were fixed with paraformaldehyde instead of methanol. While this fixation method is generally effective for preserving a variety of proteins, it is not suitable for LC3, as the resulting image does not accurately reflect its true distribution. This technical mistake might make it impossible to find differences between low and high autophagic levels.
Generally, cell lines can be treated, transfected, or fixed 1 day after seeding. Nevertheless, it is crucial to mention that, in the case of PANC-1 cells, it is necessary to wait for 2 days after seeding to ensure the complete adherence of the cells to the glass coverslips before proceeding with the subsequent steps of the experiment. Figure 4C shows a representative image from an experiment in which the cells were treated with gemcitabine just 1 day after seeding. From the figure, it can be observed that the cells in this experiment had a round shape. This morphology decreased the relation between the cytoplasm and nucleus, making it difficult to understand the intracellular distribution of LC3 and to discriminate between low and high autophagic levels. It is important to note that AR42J does not have this problem, and they are ready to be treated or fixed on the day following the seeding.
Another suboptimal outcome could be obtained when the time of methanol fixation is varied. Shorter times of fixation might cause incomplete fixation, as represented in Figure 4D, where the cells were fixed for 3 min. Incomplete fixation can interfere with proper LC3 immunolabeling, leading to unclear images and suboptimal quantification.
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/65005/65005fig02.jpg" /> 
Figure 2: LC3 immunofluorescence in PANC-1 cells under basal or gemcitabine conditions and LC3 dot quantification. The PANC-1 cells were either treated with 20 &#181;M gemcitabine for 24 h or left untreated and then immunolabelled with anti-LC3. (A) Representative images of each condition are shown. Scale bar: 10 &#181;m. (B) The bar graph represents the means and standard errors of the means (SEM) of the LC3 dots per cell for each condition. N = 10 cells per condition from three independent experiments. *** p &#60; 0.001 by a Student&#39;s t-test. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/65005/65005fig02large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/65005/65005fig03.jpg" /> 
Figure 3: LC3 immunofluorescence in AR42J cells under basal or PP242 conditions and LC3 dot quantification. The AR42J cells were differentiated with 100 nM dexamethasone for 48 h and then either treated with 1 &#181;M PP242 for 2 h or left untreated, followed by immunolabelling with anti-LC3.&#160;(A) Representative images of each condition are shown. Scale bar: 10 &#181;m. (B) The bar graph represents the means and standard errors of the means (SEM) of the LC3 dots per cell for each condition. N = 10 cells per condition from three independent experiments. ** p &#60; 0.01 by a Student&#39;s t-test. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/65005/65005fig03large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/65005/65005fig04.jpg" /> 
Figure 4: Suboptimal experiments. Representative images of LC3 immunofluorescence in suboptimal experiments are shown. Scale bar: 10 &#181;m. (A) Excess confluence: 7 &#215; 104 PANC-1 cells were seeded, treated with gemcitabine, and immunolabelled with anti-LC3. Four cells are marked to show that cell 1 and cell 2 are above cell 3 and cell 4. (B) PFA fixation: PANC-1 cells were treated with gemcitabine, fixated with PFA, and immunolabelled with anti-LC3. (C) Incomplete stretch: PANC-1 cells were treated with gemcitabine the day after seeding and immunolabelled with anti-LC3. (D) Incomplete fixation: PANC-1 cells were treated with gemcitabine, fixated with methanol for 3 min, and immunolabelled with anti-LC3. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/65005/65005fig04large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

Watch this Scientific Journal Video about Evaluating Autophagy Levels in Two Different Pancreatic Cell Models Using LC3 Immunofluorescence at JoVE.com

Evaluating Autophagy Levels in Two Different Pancreatic Cell Models Using LC3 Immunofluorescence

The goal of this protocol is to determine autophagic levels in pancreatic cancer and pancreatic acinar cells through LC3 immunofluorescence and LC3 dot quantification.

Autophagy is a specialized catabolic process that selectively degrades cytoplasmic components, including proteins and damaged organelles. Autophagy allows ...

evaluating-autophagy-levels-two-different-pancreatic-cell-models

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1.4K Views.  Universidad de Buenos Aires, CONICET. The goal of this protocol is to determine autophagic levels in pancreatic cancer and pancreatic acinar cells through LC3 immunofluorescence and LC3 dot quantification.

Video: Evaluating Autophagy Levels in Two Different Pancreatic Cell Models Using LC3 Immunofluorescence

Exploring the Regulation of Lipid Droplet Catabolism through Lipophagy

Macroautophagy, commonly referred to as autophagy, is a highly conserved cellular process responsible for the degradation of cellular components. This process is particularly prominent under conditions such as fasting, cellular stress, organelle damage, cellular damage, or aging of cellular components. During autophagy, a segment of the cytoplasm is enclosed within double-membrane vesicles known as autophagosomes, which then fuse with lysosomes. Following this fusion, the contents of autophagosomes undergo non-selective bulk degradation facilitated by lysosomes. However, autophagy also exhibits selective functionality, targeting specific organelles, including mitochondria, peroxisomes, lysosomes, nuclei, and lipid droplets (LDs). Lipid droplets are enclosed by a phospholipid monolayer that isolates neutral lipids from the cytoplasm, protecting cells from the harmful effects of excess sterols and free fatty acids (FFAs). Autophagy is implicated in various conditions, including neurodegenerative diseases, metabolic disorders, and cancer. Specifically, lipophagy -- the autophagy-dependent degradation of lipid droplets -- plays a crucial role in regulating intracellular FFA levels across different metabolic states. This regulation supports essential processes such as membrane synthesis, signaling molecule formation, and energy balance. Consequently, impaired lipophagy increases cellular vulnerability to death stimuli and contributes to the development of diseases such as cancer. Despite its significance, the precise mechanisms governing lipid droplet metabolism regulated by lipophagy in cancer cells remain poorly understood. This article aims to describe confocal imaging acquisition and quantitative imaging analysis protocols that enable the investigation of lipophagy associated with metabolic changes in cancer cells. The results obtained through these protocols may shed light on the intricate interplay between autophagy, lipid metabolism, and cancer progression. By elucidating these mechanisms, novel therapeutic targets may emerge for combating cancer and other metabolic-related diseases.

Lipophagy is a selective form of autophagy that involves the degradation of lipid droplets. Dysfunctions in this process are associated with cancer development. However, the precise mechanisms are not yet fully understood. This protocol describes quantitative imaging approaches to better understand the interplay between autophagy, lipid metabolism, and cancer progression.

Macroautophagy, commonly referred to as autophagy, is a highly conserved cellular process responsible for the degradation of cellular components. This ...

Cancer Research

Assessing LC3-II-Positive EV Release in Autophagy with Impaired Lysosome Fusion

Evaluation of LC3-II Release via Extracellular Vesicles in Relation to the Accumulation of Intracellular LC3-positive Vesicles

(Macro)autophagy represents a fundamental cellular degradation pathway. In this process, double-membraned vesicles known as autophagosomes engulf cytoplasmic contents, subsequently fusing with lysosomes for degradation. Beyond the canonical role, autophagy-related genes also modulate a secretory pathway involving the release of inflammatory molecules, tissue repair factors, and extracellular vesicles (EVs). Notably, the process of disseminating pathological proteins between cells, particularly in neurodegenerative diseases affecting the brain and spinal cord, underscores the significance of understanding this phenomenon. Recent research suggests that the transactive response DNA-binding protein 43 kDa (TDP-43), a key player in amyotrophic lateral sclerosis and frontotemporal lobar degeneration, is released in an autophagy-dependent manner via EVs enriched with the autophagosome marker microtubule-associated proteins 1A/1B light chain 3B-II (LC3-II), especially when autophagosome-lysosome fusion is inhibited.
To elucidate the mechanism underlying the formation and release of LC3-II-positive EVs, it is imperative to establish an accessible and reproducible method for evaluating both intracellular and extracellular LC3-II-positive vesicles. This study presents a detailed protocol for assessing LC3-II levels via immunoblotting in cellular and EV fractions obtained through differential centrifugation. Bafilomycin A1 (Baf), an inhibitor of autophagosome-lysosome fusion, serves as a positive control to enhance the levels of intracellular and extracellular LC3-II-positive vesicles. Tumor susceptibility gene 101 (TSG101) is used as a marker for multivesicular bodies. Applying this protocol, it is demonstrated that siRNA-mediated knockdown of syntaxin-6 (STX6), a genetic risk factor for sporadic Creutzfeldt-Jakob disease, augments LC3-II levels in the EV fraction of cells treated with Baf while showing no significant effect on TSG101 levels. These findings suggest that STX6 may negatively regulate the extracellular release of LC3-II via EVs, particularly under conditions where autophagosome-lysosome fusion is impaired. Combined with established methods for evaluating autophagy, this protocol provides valuable insights into the role of specific molecules in the formation and release of LC3-II-positive EVs.

Here, we present the methodology for concisely assessing autophagosome marker LC3-II levels in extracellular vesicles (EVs) by immunoblotting. Analysis for LC3-II levels in EVs, autolysosome formation, and omegasome formation suggests the new role of STX6 in the release of LC3-II-positive EVs when autophagosome-lysosome fusion is inhibited.

(Macro)autophagy represents a fundamental cellular degradation pathway. In this process, double-membraned vesicles known as autophagosomes engulf ...

Biochemistry

In Vitro and In Vivo Detection of Mitophagy in Human Cells, C. Elegans, and Mice

Mitochondria are the powerhouses of cells and produce cellular energy in the form of ATP. Mitochondrial dysfunction contributes to biological aging and a wide variety of disorders including metabolic diseases, premature aging syndromes, and neurodegenerative diseases such as Alzheimer's disease (AD) and Parkinson's disease (PD). Maintenance of mitochondrial health depends on mitochondrial biogenesis and the efficient clearance of dysfunctional mitochondria through mitophagy. Experimental methods to accurately detect autophagy/mitophagy, especially in animal models, have been challenging to develop. Recent progress towards the understanding of the molecular mechanisms of mitophagy has enabled the development of novel mitophagy detection techniques. Here, we introduce several versatile techniques to monitor mitophagy in human cells, Caenorhabditis elegans (e.g., Rosella and DCT-1/ LGG-1 strains), and mice (mt-Keima). A combination of these mitophagy detection techniques, including cross-species evaluation, will improve the accuracy of mitophagy measurements and lead to a better understanding of the role of mitophagy in health and disease.

In Vitro and In Vivo Detection of Mitophagy in Human Cells, C. Elegans, and Mice

Mitophagy, the process of clearing damaged mitochondria, is necessary for mitochondrial homeostasis and health maintenance. This article presents some of the latest mitophagy detection methods in human cells, Caenorhabditis elegans, and mice.

Mitochondria are the powerhouses of cells and produce cellular energy in the form of ATP. Mitochondrial dysfunction contributes to biological aging and a ...

Medicine

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.

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, ...

Live Cell Imaging of Early Autophagy Events: Omegasomes and Beyond

Autophagy is a cellular response triggered by the lack of nutrients, especially the absence of amino acids. Autophagy is defined by the formation of double membrane structures, called autophagosomes, that sequester cytoplasm, long-lived proteins and protein aggregates, defective organelles, and even viruses or bacteria. Autophagosomes eventually fuse with lysosomes leading to bulk degradation of their content, with the produced nutrients being recycled back to the cytoplasm. Therefore, autophagy is crucial for cell homeostasis, and dysregulation of autophagy can lead to disease, most notably neurodegeneration, ageing and cancer.	
	Autophagosome formation is a very elaborate process, for which cells have allocated a specific group of proteins, called the core autophagy machinery. The core autophagy machinery is functionally complemented by additional proteins involved in diverse cellular processes, e.g. in membrane trafficking, in mitochondrial and lysosomal biology. Coordination of these proteins for the formation and degradation of autophagosomes constitutes the highly dynamic and sophisticated response of autophagy. Live cell imaging allows one to follow the molecular contribution of each autophagy-related protein down to the level of a single autophagosome formation event and in real time, therefore this technique offers a high temporal and spatial resolution.	
	Here we use a cell line stably expressing GFP-DFCP1, to establish a spatial and temporal context for our analysis. DFCP1 marks omegasomes, which are precursor structures leading to autophagosomes formation. A protein of interest (POI) can be marked with either a red or cyan fluorescent tag. Different organelles, like the ER, mitochondria and lysosomes, are all involved in different steps of autophagosome formation, and can be marked using a specific tracker dye. Time-lapse microscopy of autophagy in this experimental set up, allows information to be extracted about the fourth dimension, i.e. time. Hence we can follow the contribution of the POI to autophagy in space and time.

Time-lapse microscopy of fluorescently labeled autophagy markers allows monitoring of the dynamic autophagy response with high temporal resolution. Using specific autophagy and organelle markers in a combination of 3 different colors, we can follow the contribution of a protein to autophagosome formation in a robust spatial and temporal context.

Autophagy is a  cellular response triggered by the lack of nutrients, especially the absence of  amino acids. Autophagy is defined by the formation of ...

Assessing Autophagic Flux by Measuring LC3, p62, and LAMP1 Co-localization Using Multispectral Imaging Flow Cytometry

Autophagy is a catabolic pathway in which normal or dysfunctional cellular components that accumulate during growth and differentiation are degraded via the lysosome and are recycled. During autophagy, cytoplasmic LC3 protein is lipidated and recruited to the autophagosomal membranes. The autophagosome then fuses with the lysosome to form the autolysosome, where the breakdown of the autophagosome vesicle and its contents occurs. The ubiquitin-associated protein p62, which binds to LC3, is also used to monitor autophagic flux. Cells undergoing autophagy should demonstrate the co-localization of p62, LC3, and lysosomal markers. Immunofluorescence microscopy has been used to visually identify LC3 puncta, p62, and/or lysosomes on a per-cell basis. However, an objective and statistically rigorous assessment can be difficult to obtain. To overcome these problems, multispectral imaging flow cytometry was used along with an analytical feature that compares the bright detail images from three autophagy markers (LC3, p62 and lysosomal LAMP1) and quantifies their co-localization, in combination with LC3 spot counting to measure autophagy in an objective, quantitative, and statistically robust manner.

Here, multispectral imaging flow cytometry with an analytical feature that compares bright detail images of 3 autophagy markers and quantifies their co-localization, along with LC3 spot counting, was used to measure autophagy in an objective, quantitative, and statistically robust manner.

Autophagy is a catabolic pathway in which normal or dysfunctional cellular components that accumulate during growth and differentiation are degraded via ...

Study of Protein-protein Interactions in Autophagy Research

Protein-protein interactions are important for understanding cellular signaling cascades and identifying novel pathway components and protein dynamics. The majority of cellular activities require physical interactions between proteins. To analyze and map these interactions, various experimental techniques as well as bioinformatics tools were developed. Autophagy is a cellular recycling mechanism that allows the cells to cope with different stressors, including nutrient deprivation, chemicals, and hypoxia. In order to better understand autophagy-related signaling events and to discover novel factors that regulate protein complexes in autophagy, we performed protein-protein interaction screens. Validation of these screening results requires the use of immunofluorescence and immunoprecipitation techniques. In this system, specific autophagy-related protein-protein interactions that we discovered were tested in Neuro2A (N2A) and HEK293T cell lines. Details of the technical procedures used are explained in this visualized experiment paper.

Presented here are two antibody-based protein-protein interaction research techniques: immunofluorescence and immunoprecipitation. These techniques are suitable for studying physical interactions between proteins for the discovery of novel components of cellular signaling pathways and for understanding protein dynamics.

Protein-protein interactions are important for understanding cellular signaling cascades and identifying novel pathway components and protein dynamics. ...

In Situ Immunofluorescent Staining of Autophagy in Muscle Stem Cells

Increasing evidence points to autophagy as a crucial regulatory process to preserve tissue homeostasis. It is known that autophagy is involved in skeletal muscle development and regeneration, and the autophagic process has been described in several muscular pathologies and age-related muscle disorders. A recently described block of the autophagic process that correlates with the functional exhaustion of satellite cells during muscle repair supports the notion that active autophagy is coupled with productive muscle regeneration. These data uncover the crucial role of autophagy in satellite cell activation during muscle regeneration in both normal and pathological conditions, such as muscular dystrophies. Here, we provide a protocol to monitor the autophagic process in the adult Muscle Stem Cell (MuSC) compartment during muscle regenerative conditions. This protocol describes the setup methodology to perform in situ immunofluorescence imaging of LC3, an autophagy marker, and MyoD, a myogenic lineage marker, in muscle tissue sections from control and injured mice. The methodology reported allows for monitoring the autophagic process in one specific cell compartment, the MuSC compartment, which plays a central role in orchestrating muscle regeneration.

In Situ Immunofluorescent Staining of Autophagy in Muscle Stem Cells

Active autophagy is associated with productive muscle regeneration, which is essential for Muscle Stem Cell (MuSC) activation. Here, we provide a protocol for the in situ detection of LC3, an autophagy marker in MyoD-positive MuSCs of muscle tissue sections from control and injured mice.

Increasing evidence points to autophagy as a crucial regulatory process to preserve tissue homeostasis. It is known that autophagy is involved in skeletal ...

Flux-Based Assay for the Identification of Autophagy Modulators for Osteoarthritis

Autophagy is a central mechanism to regulate homeostasis. Alterations of autophagy contribute to aging-related diseases. Phenotypic methods to identify regulators of autophagy could be used for the identification of novel therapeutics. This article describes a cell-based imaging screening workflow developed to monitor autophagic flux using LC3 as a reporter of autophagic flux (mCherry-EGFP-LC3B) in human chondrocytes. Data acquisition is performed using an automated High Content Imaging Screening System microscope. An algorithm-based automated image analysis protocol was developed and validated to identify molecules activating autophagic flux. Critical steps, explanatory notes, and improvements over current autophagy monitoring protocols are reported. Physiologically relevant phenotypic screening approaches to target hallmarks of aging can facilitate more effective drug discovery strategies for age-related musculoskeletal diseases.

This paper details monitoring autophagy flux to identify new molecules by cell-based imaging screening.

Autophagy is a central mechanism to regulate homeostasis. Alterations of autophagy contribute to aging-related diseases. Phenotypic methods to identify ...

Ultrastructural Localization of Endogenous LC3 by On-Section Correlative Light-Electron Microscopy

The visualization of autophagic organelles at the ultrastructural level by electron microscopy (EM) is essential to establish their identity and reveal details that are important for understanding the autophagic process. However, EM methods often lack molecular information, obstructing the correlation of ultrastructural information obtained by EM to fluorescence microscopy-based localization of specific autophagy proteins. Furthermore, the rarity of autophagosomes in unaltered cellular conditions hampers investigation by EM, which requires high magnification, and hence provides a limited field of view.
In answer to both challenges, an on-section correlative light-electron microscopy (CLEM) method based on fluorescent labeling was applied to correlate a common autophagosomal marker, LC3, to EM ultrastructure. The method was used to rapidly screen cells in fluorescence microscopy for LC3 labeling in combination with other relevant markers. Subsequently, the underlying ultrastructural features of selected LC3-labeled spots were identified by CLEM. The method was applied to starved cells without adding inhibitors of lysosomal acidification.
In these conditions, LC3 was found predominantly on autophagosomes and rarely in autolysosomes, in which LC3 is rapidly degraded. These data show both the feasibility and sensitivity of this approach, demonstrating that CLEM can be used to provide ultrastructural insights on LC3-mediated autophagy in native conditions-without drug treatments or genetic alterations. Overall, this method presents a valuable tool for ultrastructural localization studies of autophagy proteins and other scarce antigens by bridging light microscopy to EM data.

Here, we present a protocol for optimized on-section correlative light-electron microscopy based on endogenous, fluorescent labeling as a tool to investigate the localization of rare proteins in relation to cellular ultrastructure. The power of this approach is demonstrated by ultrastructural localization of endogenous LC3 in starved cells without Bafilomycin treatment.

The visualization of autophagic organelles at the ultrastructural level by electron microscopy (EM) is essential to establish their identity and reveal ...

Evaluating Autophagy Levels in Two Different Pancreatic Cell Models Using LC3 Immunofluorescence

Summary

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Chapters in this video

Exploring the Regulation of Lipid Droplet Catabolism through Lipophagy

Evaluation of LC3-II Release via Extracellular Vesicles in Relation to the Accumulation of Intracellular LC3-positive Vesicles

In Vitro and In Vivo Detection of Mitophagy in Human Cells, C. Elegans, and Mice

Quantitative Analysis of Autophagy using Advanced 3D Fluorescence Microscopy

Live Cell Imaging of Early Autophagy Events: Omegasomes and Beyond

Assessing Autophagic Flux by Measuring LC3, p62, and LAMP1 Co-localization Using Multispectral Imaging Flow Cytometry

Study of Protein-protein Interactions in Autophagy Research

In Situ Immunofluorescent Staining of Autophagy in Muscle Stem Cells

Flux-Based Assay for the Identification of Autophagy Modulators for Osteoarthritis

Ultrastructural Localization of Endogenous LC3 by On-Section Correlative Light-Electron Microscopy