Name: measuring diurnal rhythms in autophagic and proteasomal flux
Uploaded: 2019-09-17T14:00:00.000+00:00
Duration: 9 min 18 s
Description: Watch this Scientific Journal Video about Measuring Diurnal Rhythms in Autophagic and Proteasomal Flux at JoVE.com

This work was funded by RO1HL135846 and a Children&#8217;s Development Institute grant (PD-II-2016-529).

The protocol described here was approved by the Washington University in St. Louis Animal Care and Use Committee (IACUC).
1. Mouse Housing and Experimental Design
<ol>
	<li>To detect daily rhythms in protein turnover, house mice (male or female C57BL/6J, 4&#8722;8 week old, 20&#8722;25 g) under standard 12 h light/dark cycles with food provided ad libitum. To avoid stressing the animals, acclimate mice for at least one week in the facility prior to use and avoid single housing. For proving that rhythms in protein catabolism are truly circadian (i.e., driven by the animal&#8217;s internal biological clock), house mice under constant dark conditions, taking care to avoid exposing the mice to exogenous light. 
	NOTE: For details about mouse housing for circadian rhythm experiments see the following reference11.</li>
	<li>For each time point, allocate three mice as sham controls and at least three mice for each type of protease inhibitor used (leupeptin for autophagic flux and bortezomib for proteasomal flux measurements). Plan for six time points evenly spaced at 4 h intervals across the day/night cycle to obtain tissue samples. 
	NOTE: A 24 h, 6 time point experiment with phosphate-buffered saline (PBS), leupeptin, and bortezomib will require a total of 54 mice (3 per treatment x 3 treatments x 6 time points).</li>
</ol>
2. Preparation of Homogenization Solution, Inhibitor Stock Solutions, and Vials for Mouse Liver Collection
<ol>
	<li>Prepare fresh homogenization buffer (HB) and keep on ice: 10 mM Tris-HCl pH 7.5, 250 mM sucrose, 5 mM EDTA pH 8.0, and 1 protease inhibitor tablet per 100 mL. 
	NOTE: Approximately 10 mL of HB is needed per mouse.</li>
	<li>For downstream processing of biological samples, each sample requires a 15 mL conical tube to hold the crude homogenate, a 15 mL tube to hold the post-nuclear supernatant, two 1.5 mL microcentrifuge tubes to hold the 3,000 x g and 20,000 x g pelleted material, respectively, and a 1.5 mL microcentrifuge tube to hold the cytoplasmic fraction. Add 7 mL of cold HB to each tube intended for crude homogenate and keep on ice.</li>
	<li>Prepare a 2 mg/mL stock solution of leupeptin hemi-sulfate in sterile PBS. Also prepare a 50 mg/mL solution of bortezomib in dimethyl sulfoxide (DMSO). Aliquot and store the solutions at -80 &#176;C.</li>
</ol>
3. Protease Inhibitor Administration
<ol>
	<li>Thaw leupeptin (2 mg/mL) and bortezomib (50 mg/mL) stock solutions to room temperature 15 min prior to each time point. The leupeptin stock is ready for injection. Dilute the bortezomib in sterile PBS to yield a 50 &#181;g/mL working solution. 
	NOTE: Bortezomib is light sensitive, so protect the working stock from light until use.</li>
	<li>Weigh mice and perform intraperitoneal injections of &#8220;sham&#8221; PBS (0.5 mL), leupeptin (40 mg/kg), or bortezomib (1.6 &#181;g/kg). Return mice to appropriately marked cages grouped by the type of injection they received. Record the time the mice are treated or manipulated in a standardized table (see Supplemental File &#8220;Sample Data&#8221;). 
	NOTE: A dose calculator is included as an aid in the Supplemental File &#8220;Sample Data&#8221;. It is important to perform injections expeditiously and in the same order from timepoint to timepoint to minimize variability.</li>
</ol>
4. Tissue Acquisition and Storage
<ol>
	<li>Two hours after injection, euthanize mice one at a time in accordance with the institutionally approved IACUC protocol. For example, anesthetize mice then euthanize by cervical dislocation. Proceed to the dissection step immediately following euthanasia. 
	NOTE: Ensure complete anesthesia before cervical dislocation by pinching front paws without an observable reflex.</li>
	<li>Remove the left lobe of the liver by making a 1.5 to 2.0 cm incision with Metzenbaum scissors on the mouse&#8217;s ventral abdomen. Externalize the left lobe of the liver and excise it with surgical scissors. Submerge the liver sample in 7 mL of ice-cold HB in an appropriately labeled 15 mL conical tube. Keep the sample on ice throughout processing. 
	NOTE: The samples can be kept on ice or at 4 &#176;C overnight before proceeding. If standard markers of macroautophagy and proteasomal activity are the only intended readouts, liver samples can be flash frozen in liquid nitrogen and stored at -80 &#176;C for later processing. To examine other targets of degradation (e.g., via proteomics), process the samples without freezing.</li>
	<li>Proceed to euthanize and dissect the next mouse until all samples are acquired. Process mice in the same group order they were injected and record the duration of this step (see Supplemental File &#8220;Sample Data&#8221;). Each mouse should be processed in under 5 min to limit difference in the exposure times for the injected inhibitors.</li>
</ol>
5. Biochemical Fractionation of Liver Samples
NOTE: Figure 1B shows the fractionation scheme.
<ol>
	<li>Transfer each liver sample and 7 mL of HB into a 15 mL capacity Dounce homogenizer. Homogenize the sample with 10 strokes of the loose piston and 15 strokes of the tight piston. Return the resultant crude homogenate to the 15 mL conical tube it originated from. Repeat until all liver samples have been homogenized.</li>
	<li>Spin crude homogenate samples at 700 x g for 10 min at 4 &#176;C to pellet nuclei and debris. Transfer the top 4 mL of post-nuclear supernatant (S1) to a fresh 15 mL conical tube.</li>
	<li>Determine the protein concentration of fraction S1 using Bradford or bicinchoninic acid&#160;(BCA) assays according to the manufacturer&#8217;s instructions. Next equalize the concentrations of all samples to 2.1 mg/mL or to the desired concentration by adding fresh HB to S1 where needed. The normalized samples are the &#8220;Total Protein&#8221; (Tot) fraction. For downstream analytical purposes and quality improvement, aliquot 500 &#181;L of the Tot fraction and store at -80 &#176;C.</li>
	<li>Transfer 1.5 mL of the remaining Tot fraction into a microcentrifuge tube and spin at 3,000 x g for 15 min at 4 &#176;C. Transfer 1 mL of the resultant supernatant (S2) to a fresh microcentrifuge tube and set on ice.</li>
	<li>Aspirate the remaining supernatant and wash the 3,000 x g pellet (3KP) twice with 1.5 mL of cold HB. The 3KP pellet can be stored dry at -80 &#176;C if downstream proteomics are anticipated. If only western blotting is anticipated, resuspend the 3KP pellet in 200 &#181;L of sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) sample buffer (Table of Materials) and boil at 95 &#176;C for 5 min.</li>
	<li>Spin the S2 fraction at 20,000 x g for 20 min at 4 &#176;C. Transfer the resultant supernatant (S3) to a fresh microcentrifuge tube. S3 is the cytoplasmic (Cyto) fraction. For SDS-PAGE, combine 150 &#181;L of Cyto fraction with 50 &#181;L of 4x SDS-PAGE sample buffer and boil at 95 &#176;C for 5 min.</li>
	<li>Aspirate the remaining supernatant from the 20,000 x g pellet (20KP) and wash twice with 1.5 mL of cold HB. The 20KP pellet can be stored dry at -80 &#176;C if downstream proteomics are anticipated. If only western blotting is anticipated, resuspend the 20KP pellet in 100 &#181;L of SDS-PAGE sample buffer and boil at 95 &#176;C for 5 min.</li>
</ol>
6. Western Blotting Readout
<ol>
	<li>In order to quantify macroautophagic and proteasomal flux via western blotting, compose a stock solution of purified GST-LC3b (2 &#181;g/mL), p62-His6 (2 &#181;g/mL), and Lys48 linked polyubiquitin (K48-Ub, 50 &#181;g/mL) in 1x SDS-PAGE sample buffer. After boiling at 95 &#176;C for 5 min, aliquot and store at -80 &#176;C for future use.</li>
	<li>At the time of SDS-PAGE, generate a 6-point standard curve of the standard protein mixture by serially diluting 1:3 in 1x SDS-PAGE sample buffer. Load 10 &#181;L of each standard curve sample onto a 26 well 4&#8722;12% SDS-PAGE midi-gel, followed by prestained protein standards (Table of Materials), a commercial molecular weight standard.</li>
	<li>For measuring autophagic flux, load 12 &#181;L of 3KP sample into each well. 
	NOTE: Assuming sham, bortezomib, and leupeptin treatments were done and assuming 3 mice per treatment, each time point should consist of 9 samples. Therefore, each midi-gel can accommodate 2 time points plus the standard curve and a typical time series experiment will require 3 midi-gels for readout.</li>
	<li>For measuring proteasomal flux, load 12 &#181;L of Cyto fraction into each well.</li>
	<li>Separate protein samples by SDS-PAGE and transfer to polyvinylidene fluoride (PVDF) membranes using standard protocols. If western blotting for LC3b is anticipated, transfer gels using 20% methanol-containing transfer buffer. Otherwise, use 10% methanol-containing transfer buffer as this will enable more efficient transfer of high molecular weight protein species.</li>
	<li>Perform western blotting using standard protocols. For analyzing macroautophagic flux, blot membranes containing 3KP samples with anti-p62 or anti-LC3b antibodies (1:1,000) overnight at 4 &#176;C. For analyzing proteasomal flux, blot membranes containing Cyto samples with anti-Lys48 specific polyubiquitin (1:1,000) overnight at 4 &#176;C.</li>
	<li>Image western blots using standard secondary antibodies and imaging devices. Image all membranes that constitute a given time series experiment together.</li>
</ol>
7. Data Analysis
NOTE: See Supplemental File &#8220;Sample Data&#8221;.
<ol>
	<li>To perform densitometry on western blot samples, use standard graphics software, Image Studio, or alternatively ImageJ.</li>
	<li>Perform densitometric measurements on bands of interest for both the standard curve and the experimental samples. In Image Studio, using p62 as an example, draw a long rectangle encompassing protein monomer at the bottom and extending to the top of the membrane. Copy, paste, and move the rectangle to the remaining samples. It is important to keep the rectangle used for quantification consistent between samples.</li>
	<li>Save the quantification to a spreadsheet by pressing Report and Launch Spreadsheet at the bottom right of the analysis window.</li>
	<li>Generate a densitometric standard curve with spreadsheet using the serially diluted standard sample and use either linear or polynomial regression to obtain a best fit standard curve equation. Using this equation, extrapolate the quantity of p62, LC3b-II or Lys48-poly Ub in the experimental samples.</li>
	<li>To obtain flux measurements, subtract the extrapolated protein quantity of each inhibitor-treated sample from the average value of the PBS samples from the same time point (see Supplemental File &#8220;Sample Data&#8221;).</li>
	<li>Evaluate the statistical significance of temporal variation in protein turnover using 1-way ANOVA. This can be done using standard spreadsheet software.</li>
</ol>

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	<li>Green, C. B., Takahashi, J. S., Bass, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+meter+of+metabolism.">The meter of metabolism.</a> Cell. 134 (5), 728-742 (2008).</li><li>Ma, B. Y., 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=LPS+suppresses+expression+of+asialoglycoprotein-binding+protein+through+TLR4+in+thioglycolate-elicited+peritoneal+macrophages.">LPS suppresses expression of asialoglycoprotein-binding protein through TLR4 in thioglycolate-elicited peritoneal macrophages.</a> Glycoconjugate Journal. 24 (4-5), 243-249 (2007).</li><li>Ryzhikov, 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=Diurnal+Rhythms+Spatially+and+Temporally+Organize+Autophagy.">Diurnal Rhythms Spatially and Temporally Organize Autophagy.</a> Cell Reports. 26 (7), 1880-1892 (2019).</li><li>Martinez-Lopez, N., 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=System-wide+Benefits+of+Intermeal+Fasting+by+Autophagy.">System-wide Benefits of Intermeal Fasting by Autophagy.</a> Cell Metabolism. 26 (6), 856-871 (2017).</li><li>Desvergne, 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=Circadian+modulation+of+proteasome+activity+and+accumulation+of+oxidized+protein+in+human+embryonic+kidney+HEK+293+cells+and+primary+dermal+fibroblasts.">Circadian modulation of proteasome activity and accumulation of oxidized protein in human embryonic kidney HEK 293 cells and primary dermal fibroblasts.</a> Free Radical Biology and Medicine. 94, 195-207 (2016).</li><li>Levine, B., Mizushima, N., Virgin, H. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Autophagy+in+immunity+and+inflammation.">Autophagy in immunity and inflammation.</a> Nature. 469 (7330), 323-335 (2011).</li><li>Ciechanover, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Intracellular+protein+degradation:+from+a+vague+idea+thru+the+lysosome+and+the+ubiquitin-proteasome+system+and+onto+human+diseases+and+drug+targeting.">Intracellular protein degradation: from a vague idea thru the lysosome and the ubiquitin-proteasome system and onto human diseases and drug targeting.</a> Cell Death &amp; Differentiation. 12 (9), 1178-1190 (2005).</li><li>Collins, G. A., Goldberg, A. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+Logic+of+the+26S+Proteasome.">The Logic of the 26S Proteasome.</a> Cell. 169 (5), 792-806 (2017).</li><li>Haspel, 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=Characterization+of+macroautophagic+flux+in+vivo+using+a+leupeptin-based+assay.">Characterization of macroautophagic flux in vivo using a leupeptin-based assay.</a> Autophagy. 7 (6), 629-642 (2011).</li><li>Klionsky, D. 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=Guidelines+for+the+use+and+interpretation+of+assays+for+monitoring+autophagy+(3rd+edition).">Guidelines for the use and interpretation of assays for monitoring autophagy (3rd edition).</a> Autophagy. 12 (1), 1-222 (2016).</li><li>Eckel-Mahan, K., Sassone-Corsi, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Phenotyping+Circadian+Rhythms+in+Mice.">Phenotyping Circadian Rhythms in Mice.</a> Current Protocols in Mouse Biology. 5 (3), 271-281 (2015).</li><li>Hughes, M. 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=Guidelines+for+Genome-Scale+Analysis+of+Biological+Rhythms.">Guidelines for Genome-Scale Analysis of Biological Rhythms.</a> Journal of Biological Rhythms. 32 (5), 380-393 (2017).</li></ol>

The authors have nothing to disclose.

Our protocol describes a technically straightforward means of measuring biological rhythms in protein turnover in mice using commonly available molecular biology equipment. Because of the length of time series experiments and the number of biological samples involved, it is important to be consistent across the entire experiment regarding how the mice are injected, the timing of tissue acquisition and the biochemical processing of samples. The injection, euthanasia, and cervical dislocation steps may require operator pra...

Circadian rhythms refer to daily, predictable variations in biological function that are apparent throughout nature. They exist at every biological scale, from macroscopic behaviors like sleep-wake cycles, to molecular phenomena like the rhythmic abundance of biomolecules. In recent years, research into circadian rhythms has been transformed by the discovery of &#8220;clock genes&#8221; that are critical for circadian rhythm generation. Studies in clock gene knockout mice have revealed a central role for circadian rhythms in temporally organizing core cellular processes such as metabolism1. Among the ways circadian rhythms make this happen is by imparting a temporal structure to protein catabolism.
Several groups including ours have shown that the two major avenues for cellular protein catabolism, autophagy and the ubiquitin-proteasome system, are subject to diurnal rhythms2,3,4,5. Autophagy represents the lysosome-dependent arm of protein catabolism in which proteins of interest are delivered to this degradative organelle either through the construction of a novel vesicle (macroautophagy) or through direct translocation though a channel (chaperone mediated autophagy)6. The ubiquitin-proteasome system is the main non-lysosomal pathway, where proteins are poly-ubiquitinated and then fed into the proteasome, a macromolecular degradative machine found throughout the cytoplasm and nucleus7,8. Rhythms in autophagic and proteasomal activity are important because they likely play a role in cellular housekeeping. As a result, it is valuable to have a standardized procedure that can detect daily oscillations in protein catabolism that is compatible with pre-clinical disease models.
Here, we provide our protocol for quantifying diurnal variations in autophagic flux in mouse liver, which has served as the basis for work in our laboratory3,9. Our method is classified as a &#8220;turnover assay&#8221;10, an approach used by numerous groups to measure proteolytic activity (or flux). In this approach, protease inhibitors specific to lysosomes or proteasomes are administered to mice and then tissue samples are obtained after a fixed time interval. In parallel, tissue samples are obtained from mice subjected to sham injections. The tissue samples are homogenized and then biochemically separated to obtain the lysosome-enriched and cytoplasmic fractions. These fractions are then analyzed in parallel via western blotting using antibodies specific to macroautophagy markers (LC3b and p62) or proteasomal substrates (poly-ubiquitinated protein). Over time, animals injected with protease inhibitors accumulate proteins that would normally have been recycled. As a result, the rate of turnover is inferred by comparing the abundance of marker proteins in the protease-inhibitor treated samples to the sham-treated samples. By repeating this method at fixed time intervals across the day it is possible to reconstruct circadian variations in proteolysis (Figure 1A).

<table><tbody><tr><td>4x SDS PAGE Sample Buffer</td><td>Invitrogen</td><td>Cat# NP0008</td><td></td></tr><tr><td>Bortezomib</td><td>EMD Millipore</td><td>Cat# 5.04314.0001; CAS: 179324-69-7</td><td></td></tr><tr><td>Image Studio</td><td>LICOR</td><td>N/A</td><td></td></tr><tr><td>Immobilon-FL PVDF membrane 0.45 micron</td><td>Merck Millipore Ltd</td><td>Cat# IPFL00010</td><td></td></tr><tr><td>K48-linkage Specific Polyubiquitin (D9D5) Rabbit mAb</td><td>Cell Signaling Technology</td><td>Cat#8081S; RRID:AB_10859893</td><td></td></tr><tr><td>LC3a</td><td>Boston Biochem</td><td>Cat# UL-430</td><td></td></tr><tr><td>LC3b antibody</td><td>Novus</td><td>Cat#NB100-2220; RRID:AB_10003146</td><td></td></tr><tr><td>LC3b antibody</td><td>Cell Signaling Technology</td><td>Cat#2775; RRID:AB_915950</td><td></td></tr><tr><td>Leupeptin</td><td>Sigma</td><td>Cat# L2884; CAS: 103476-89-7</td><td></td></tr><tr><td>NuPAGE 4-12% Bis-Tris Midi Protein Gels</td><td>Thermo Fisher Scientific</td><td>Cat# WG1403BOX</td><td></td></tr><tr><td>NuPAGE LDS Sample Buffer (4x)</td><td>Thermo Fisher Scientific</td><td>Cat# NP0007</td><td></td></tr><tr><td>P62-his</td><td>Novus</td><td>Cat# NBP1-44490</td><td></td></tr><tr><td>Precision Plus Protein All Blue Prestained Protein Standards</td><td>Bio-Rad</td><td>Cat# 1610373</td><td></td></tr><tr><td>Rabbit Anti-p62/SQSTM1</td><td>Millipore-Sigma</td><td>Cat#P0067; RRID:AB_1841064</td><td></td></tr><tr><td>rhPoly-Ub WT (2-7) (K48)</td><td>Boston Biochem</td><td>Cat# UC-230</td><td></td></tr><tr><td>SDS-PAGE Midi-size Gels</td><td>Invitrogen</td><td>Cat# WG1403</td><td></td></tr><tr><td>SIGMAFAST Protease Inhibitor Tablets</td><td>Millipore-Sigma</td><td>Cat# S8830</td><td></td></tr></tbody></table>

measuring diurnal rhythms in autophagic and proteasomal flux

Cells employ several methods for recycling unwanted proteins and other material, including lysosomal and non-lysosomal pathways. The main lysosome-dependent pathway is called autophagy, while the primary non-lysosomal method for protein catabolism is the ubiquitin-proteasome system. Recent studies in model organisms suggest that the activity of both autophagy and the ubiquitin-proteasome system is not constant across the day but instead varies according to a daily (circadian) rhythm. The ability to measure biological rhythms in protein turnover is important for understanding how cellular quality control is achieved and for understanding the dynamics of specific proteins of interest. Here we present a standardized protocol for quantifying autophagic and proteasomal flux in vivo that captures the circadian component of protein turnover. Our protocol includes details for mouse handling, tissue processing, fractionation, and autophagic flux quantification using mouse liver as the starting material.

Representative data are presented in Figure 2A,B, and the quantification of these data are provided in Figure 2C,D (see also Supplemental File &#8220;Sample Data&#8221;). For simplicity, we have not depicted loading controls in Figure 2 but these should be obtained in parallel. Typically, western blots against &#946;-actin are used for this purpose, but a total protein stain (such a...

Watch this Scientific Journal Video about Measuring Diurnal Rhythms in Autophagic and Proteasomal Flux at JoVE.com

Measuring Diurnal Rhythms in Autophagic and Proteasomal Flux

We describe our protocol for measuring biological rhythms in protein catabolism via autophagy and the proteasome in mouse liver.

Cells employ several methods for recycling unwanted proteins and other material, including lysosomal and non-lysosomal pathways. The main ...

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4.6K Views.  Washington University School of Medicine. We describe our protocol for measuring biological rhythms in protein catabolism via autophagy and the proteasome in mouse liver.

Video: Measuring Diurnal Rhythms in Autophagic and Proteasomal Flux

Measurement of Protein Turnover Rates in Senescent and Non-Dividing Cultured Cells with Metabolic Labeling and Mass Spectrometry

Mounting evidence has shown that the accumulation of senescent cells in the central nervous system contributes to neurodegenerative disorders such as Alzheimer&#39;s and Parkinson&#39;s diseases. Cellular senescence is a state of permanent cell cycle arrest that typically occurs in response to exposure to sub-lethal stresses. However, like other non-dividing cells, senescent cells remain metabolically active and carry out many functions that require unique transcriptional and translational demands and widespread changes in the intracellular and secreted proteomes. Understanding how protein synthesis and decay rates change during senescence can illuminate the underlying mechanisms of cellular senescence and find potential therapeutic avenues for diseases exacerbated by senescent cells. This paper describes a method for proteome-scale evaluation of protein half-lives in non-dividing cells using pulsed stable isotope labeling by amino acids in cell culture (pSILAC) in combination with mass spectrometry. pSILAC involves metabolic labeling of cells with stable heavy isotope-containing versions of amino acids. Coupled with modern mass spectrometry approaches, pSILAC enables the measurement of protein turnover of hundreds or thousands of proteins in complex mixtures. After metabolic labeling, the turnover dynamics of proteins can be determined based on the relative enrichment of heavy isotopes in peptides detected by mass spectrometry. In this protocol, a workflow is described for the generation of senescent fibroblast cultures and similarly arrested quiescent fibroblasts, as well as a simplified, single-time point pSILAC labeling time-course that maximizes coverage of anticipated protein turnover rates. Further, a pipeline is presented for the analysis of pSILAC mass spectrometry data and user-friendly calculation of protein degradation rates using spreadsheets. The application of this protocol can be extended beyond senescent cells to any non-dividing cultured cells such as neurons.

This protocol describes the workflow for metabolic labeling of senescent and non-dividing cells with pulsed SILAC, untargeted mass spectrometry analysis, and a streamlined calculation of protein half-lives.

Mounting evidence has shown that the accumulation of senescent cells in the central nervous system contributes to neurodegenerative disorders such as ...

Biochemistry

Quantitative Cell Biology of Neurodegeneration in Drosophila Through Unbiased Analysis of Fluorescently Tagged Proteins Using ImageJ

With the rising prevalence of neurodegenerative diseases, it is increasingly important to understand the underlying pathophysiology that leads to neuronal dysfunction and loss. Fluorescence-based imaging tools and technologies enable unprecedented analysis of subcellular neurobiological processes, yet there is still a need for unbiased, reproducible, and accessible approaches for extracting quantifiable data from imaging studies. We have developed a simple and adaptable workflow to extract quantitative data from fluorescence-based imaging studies using Drosophila models of neurodegeneration. Specifically, we describe an easy-to-follow, semi-automated approach using Fiji/ImageJ to analyze two cellular processes: first, we quantify protein aggregate content and profile in the Drosophila optic lobe using fluorescent-tagged mutant huntingtin proteins; and second, we assess autophagy-lysosome flux in the Drosophila visual system with ratiometric-based quantification of a tandem fluorescent reporter of autophagy. Importantly, the protocol outlined here includes a semi-automated segmentation step to ensure all fluorescent structures are analyzed to minimize selection bias and to increase resolution of subtle comparisons. This approach can be extended for the analysis of other cell biological structures and processes implicated in neurodegeneration, such as proteinaceous puncta (stress granules and synaptic complexes), as well as membrane-bound compartments (mitochondria and membrane trafficking vesicles). This method provides a standardized, yet adaptable reference point for image analysis and quantification, and could facilitate reliability and reproducibility across the field, and ultimately enhance mechanistic understanding of neurodegeneration.

Quantitative Cell Biology of Neurodegeneration in Drosophila Through Unbiased Analysis of Fluorescently Tagged Proteins Using ImageJ

We have developed a simple and adaptable workflow to extract quantitative data from fluorescence-imaging-based cell biological studies of protein aggregation and autophagic flux in the central nervous system of Drosophila models of neurodegeneration.

With the rising prevalence of neurodegenerative diseases, it is increasingly important to understand the underlying pathophysiology that leads to neuronal ...

Neuroscience

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, ...

Quantifying Subcellular Ubiquitin-proteasome Activity in the Rodent Brain

The ubiquitin-proteasome system is a key regulator of protein degradation and a variety of other cellular processes in eukaryotes. In the brain, increases in ubiquitin-proteasome activity are critical for synaptic plasticity and memory formation and aberrant changes in this system are associated with a variety of neurological, neurodegenerative and psychiatric disorders. One of the issues in studying ubiquitin-proteasome functioning in the brain is that it is present in all cellular compartments, in which the protein targets, functional role and mechanisms of regulation can vary widely. As a result, the ability to directly compare brain ubiquitin protein targeting and proteasome catalytic activity in different subcellular compartments within the same animal is critical for fully understanding how the UPS contributes to synaptic plasticity, memory and disease. The method described here allows collection of nuclear, cytoplasmic and crude synaptic fractions from the same rodent (rat) brain, followed by simultaneous quantification of proteasome catalytic activity (indirectly, providing activity of the proteasome core only) and linkage-specific ubiquitin protein tagging. Thus, the method can be used to directly compare subcellular changes in ubiquitin-proteasome activity in different brain regions in the same animal during synaptic plasticity, memory formation and different disease states. This method can also be used to assess the subcellular distribution and function of other proteins within the same animal.

This protocol is designed to efficiently quantify ubiquitin-proteasome system (UPS) activity in different cellular compartments of the rodent brain. Users are able to examine UPS functioning in nuclear, cytoplasmic and synaptic fractions in the same animal, reducing the amount of time and number of animals needed to perform these complex analyses.

The ubiquitin-proteasome system is a key regulator of protein degradation and a variety of other cellular processes in eukaryotes. In the brain, increases ...

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 ...

The Lactate Dehydrogenase Sequestration Assay &#8212; A Simple and Reliable Method to Determine Bulk Autophagic Sequestration Activity in Mammalian Cells

Bulk autophagy is characterized by the sequestration of large portions of cytoplasm into double/multi-membrane structures termed autophagosomes. Here a simple protocol to monitor this process is described. Moreover, typical results and experimental validation of the method under autophagy-inducing conditions in various types of cultured mammalian cells are provided. During bulk autophagy, autophagosomes sequester cytosol, and thereby also soluble cytosolic proteins, alongside other autophagic cargo. LDH is a stable and highly abundant, soluble cytosolic enzyme that is non-selectively sequestered into autophagosomes. The amount of LDH sequestration therefore reflects the amount of bulk autophagic sequestration. To efficiently and accurately determine LDH sequestration in cells, we employ an electrodisruption-based fractionation protocol that effectively separates sedimentable from cytosolic LDH, followed by measurement of enzymatic activity in sedimentable fractions versus whole-cell samples. Autophagic sequestration is determined by subtracting the proportion of sedimentable LDH in untreated cells from that in treated cells. The advantage of the LDH sequestration assay is that it gives a quantitative measure of the autophagic sequestration of endogenous cargo, as opposed to other methods that either involve ectopic expression of sequestration probes or semi-quantitative protease protection analyses of autophagy markers or receptors.

Here a simple and well-validated protocol for measuring bulk autophagic sequestration activity in mammalian cells is described. The method is based on quantifying the proportion of lactate dehydrogenase (LDH) in sedimentable cell fractions compared to total cellular LDH levels.

Bulk autophagy is characterized by the sequestration of large portions of cytoplasm into double/multi-membrane structures termed autophagosomes. Here a ...

Sensitive Measurement of Mitophagy by Flow Cytometry Using the pH-dependent Fluorescent Reporter mt-Keima

Mitophagy is a process of selective removal of damaged or unnecessary mitochondria using autophagy machinery. Close links have been found between defective mitophagy and various human diseases, including neurodegenerative diseases, cancer, and metabolic diseases. In addition, recent studies have shown that mitophagy is involved in normal cellular processes, such as differentiation and development. However, the precise role of and molecular mechanisms underlying mitophagy require further study. Therefore, it is critical to develop a robust and convenient method for measuring changes in mitophagy activity. Here, we describe a detailed protocol for quantitatively assessing mitophagy activity through flow cytometry using the mitochondria-targeted fluorescent protein Keima (mt-Keima). This flow cytometry assay can analyze mitophagy activity more rapidly and sensitively than conventional microscopy- or immunoblotting-based methods. This protocol can be applied to analyze mitophagy activity in various cell types.

Mitophagy, the selective degradation of mitochondria, has been implicated in mitochondrial homeostasis and is deregulated in various human diseases. However, convenient experimental methods for measuring mitophagy activity are very limited. Here, we provide a sensitive assay for measuring mitophagy activity using flow cytometry.

Mitophagy is a process of selective removal of damaged or unnecessary mitochondria using autophagy machinery. Close links have been found between ...

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 ...

Use of Minimally Invasive Methods to Assess Fuel Utilization and Circadian Rhythms in Older Adults

Aging is associated with multiple physiological changes that contribute synergistically and independently to physical disability and the risk of chronic disease. Although the etiology of age-related physical disability is complex and multifactorial, the decline in mitochondrial function appears to coincide with the progression of functional decline in many older adults. The reason why there is a decrease in mitochondrial function with aging remains elusive, but emerging science indicates that both fuel metabolism and circadian rhythms can influence mitochondrial function.
Recent studies have established that circadian rhythms become disturbed with aging, and that disrupted circadian rhythms have pathological consequences that impact mitochondrial function and overlap with many age-associated chronic diseases. Current quantitative methods for direct assessment of mitochondrial function are invasive and typically require a muscle biopsy, which can pose difficulties with participant recruitment and study adherence, given the perceived levels of potential pain and risk. Thus, an innovative and relatively noninvasive protocol to assess changes in mitochondrial function at the cellular level and circadian patterns in older adults was adapted. Specifically, a real-time metabolic flux analyzer is used to assess the mitochondrial bioenergetic function of white blood cells under differential substrate availability.
The expression of circadian clock genes in white blood cells to cross-correlate with the mitochondrial bioenergetics and circadian rhythm outcomes are also analyzed. It is believed that these innovative methodological approaches will aid future clinical trials by providing minimally invasive methods for studying mitochondrial substrate preference and circadian rhythms in older adults.

A novel and minimally invasive protocol is presented to evaluate the synergistic impact of fuel utilization and circadian rhythms on aging individuals, utilizing peripheral blood mononuclear cells.

Aging is associated with multiple physiological changes that contribute synergistically and independently to physical disability and the risk of chronic ...

Measuring Diurnal Rhythms in Autophagic and Proteasomal Flux

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Measurement of Protein Turnover Rates in Senescent and Non-Dividing Cultured Cells with Metabolic Labeling and Mass Spectrometry

Quantitative Cell Biology of Neurodegeneration in Drosophila Through Unbiased Analysis of Fluorescently Tagged Proteins Using ImageJ

Quantitative Analysis of Autophagy using Advanced 3D Fluorescence Microscopy

Quantifying Subcellular Ubiquitin-proteasome Activity in the Rodent Brain

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

The Lactate Dehydrogenase Sequestration Assay — A Simple and Reliable Method to Determine Bulk Autophagic Sequestration Activity in Mammalian Cells

Sensitive Measurement of Mitophagy by Flow Cytometry Using the pH-dependent Fluorescent Reporter mt-Keima

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

Use of Minimally Invasive Methods to Assess Fuel Utilization and Circadian Rhythms in Older Adults