Name: detection of protein aggregation using fluorescence correlation spectroscopy
Uploaded: 2021-04-25T15:00:00
Description: Watch this Scientific Journal Video about Detection of Protein Aggregation using Fluorescence Correlation Spectroscopy at JoVE.com

A.K. was supported by a Japan Society for Promotion of Science (JSPS) Grant-in-Aid for Scientific Research (C) (#18K06201), by a grant-in-aid from the Nakatani Foundation for Countermeasures against novel coronavirus infections, by a grant from Hokkaido University Office for Developing Future Research Leaders (L-Station), and a grant-in-aid from Hoansha Foundation. M. K. was partially supported by a JSPS Grant-in-Aid for Scientific Research on Innovative Areas &#34;Chemistry for Multimolecular Crowding Biosystems&#34; (#20H04686), and a JSPS Grant-in-Aid for Scientific Research on Innovative Areas &#34;Information physics of living matters&#34; (#20H05522).

1. Materials and reagents
<ol>
	<li>Use pyrogenic free solutions and medium for cell culture (Table 1).</li>
	<li>Prepare solutions for the biochemical experiment using ultrapure water and use as DNase/RNase free.</li>
	<li>Select an appropriate FBS for the cell culture with a lot check process. Since the selected FBS lot changes regularly, the catalog and lot number for FBS cannot be represented here.</li>
	<li>Plasmid DNA
	<ol>
		<li>Prepare pmeGFP-N15 for eGFP monomer express...

<ol>
	<li>Ross, C. A., Poirier, M. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Protein+aggregation+and+neurodegenerative+disease.">Protein aggregation and neurodegenerative disease.</a> Nature Medicine. 10, 10-17 (2004).</li><li>Hipp, M. S., Kasturi, P., Hartl, F. U. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+proteostasis+network+and+its+decline+in+ageing.">The proteostasis network and its decline in ageing.</a> Nature Review Molecular Cell Biology. 20 (7), 421-435 (2019).</li><li>Kitamura, A., Nagata, K., Kinjo, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Conformational+analysis+of+misfolded+protein+aggregation+by+FRET+and+live-cell+imaging+techniques.">Conformational analysis of misfolded protein aggregation by FRET and live-cell imaging techniques.</a> International Journal of Molecular Science. 16 (3), 6076-6092 (2015).</li><li>Rigler, R., Mets, U., Widengren, J., Kask, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Fluorescence+Correlation+Spectroscopy+with+High+Count+Rate+and+Low-Background+-+Analysis+of+Translational+Diffusion.">Fluorescence Correlation Spectroscopy with High Count Rate and Low-Background - Analysis of Translational Diffusion.</a> European Biophysics Journal with Biophysics Letters. 22 (3), 169-175 (1993).</li><li>Zacharias, D. A., Violin, J. D., Newton, A. C., Tsien, R. Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Partitioning+of+lipid-modified+monomeric+GFPs+into+membrane+microdomains+of+live+cells.">Partitioning of lipid-modified monomeric GFPs into membrane microdomains of live cells.</a> Science. 296 (5569), 913-916 (2002).</li><li>Kitamura, 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=Interaction+of+RNA+with+a+C-terminal+fragment+of+the+amyotrophic+lateral+sclerosis-associated+TDP43+reduces+cytotoxicity.">Interaction of RNA with a C-terminal fragment of the amyotrophic lateral sclerosis-associated TDP43 reduces cytotoxicity.</a> Scientific Reports. 6, 19230 (2016).</li><li>Kitamura, 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=Dysregulation+of+the+proteasome+increases+the+toxicity+of+ALS-linked+mutant+SOD1.">Dysregulation of the proteasome increases the toxicity of ALS-linked mutant SOD1.</a> Genes to Cells. 19 (3), 209-224 (2014).</li><li>Niwa, H., Yamamura, K., Miyazaki, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Efficient+selection+for+high-expression+transfectants+with+a+novel+eukaryotic+vector.">Efficient selection for high-expression transfectants with a novel eukaryotic vector.</a> Gene. 108 (2), 193-199 (1991).</li><li>Kitamura, 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=Cytosolic+chaperonin+prevents+polyglutamine+toxicity+with+altering+the+aggregation+state.">Cytosolic chaperonin prevents polyglutamine toxicity with altering the aggregation state.</a> Nature Cell Biology. 8 (10), 1163-1170 (2006).</li><li>Kitamura, A., Shibasaki, A., Takeda, K., Suno, R., Kinjo, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Analysis+of+the+substrate+recognition+state+of+TDP-43+to+single-stranded+DNA+using+fluorescence+correlation+spectroscopy.">Analysis of the substrate recognition state of TDP-43 to single-stranded DNA using fluorescence correlation spectroscopy.</a> Biochemistry and Biophysics Reports. 14, 58-63 (2018).</li><li>Kinjo, M., Sakata, H., Mikuni, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=First+steps+for+fluorescence+correlation+spectroscopy+of+living+cells.">First steps for fluorescence correlation spectroscopy of living cells.</a> Cold Spring Harbor Protocols. 2011 (10), 1185-1189 (2011).</li><li>Kinjo, M., Sakata, H., Mikuni, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Fluorescence+correlation+spectroscopy+example:+shift+of+autocorrelation+curve.">Fluorescence correlation spectroscopy example: shift of autocorrelation curve.</a> Cold Spring Harbor Protocols. 2011 (10), 1267-1269 (2011).</li><li>Kinjo, M., Sakata, H., Mikuni, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Basic+fluorescence+correlation+spectroscopy+setup+and+measurement.">Basic fluorescence correlation spectroscopy setup and measurement.</a> Cold Spring Harbor Protocols. 2011 (10), 1262-1266 (2011).</li><li>Jazani, S., 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=An+alternative+framework+for+fluorescence+correlation+spectroscopy.">An alternative framework for fluorescence correlation spectroscopy.</a> Nature Communication. 10 (1), 3662 (2019).</li><li>Pack, C., Saito, K., Tamura, M., Kinjo, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Microenvironment+and+effect+of+energy+depletion+in+the+nucleus+analyzed+by+mobility+of+multiple+oligomeric+EGFPs.">Microenvironment and effect of energy depletion in the nucleus analyzed by mobility of multiple oligomeric EGFPs.</a> Biophysical Journal. 91 (10), 3921-3936 (2006).</li><li>Ries, J., Chiantia, S., Schwille, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Accurate+determination+of+membrane+dynamics+with+line-scan+FCS.">Accurate determination of membrane dynamics with line-scan FCS.</a> Biophysical Journal. 96 (5), 1999-2008 (2009).</li><li>Fujioka, 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=Phase+separation+organizes+the+site+of+autophagosome+formation.">Phase separation organizes the site of autophagosome formation.</a> Nature. 578 (7794), 301-305 (2020).</li><li>Sadaie, W., Harada, Y., Matsuda, M., Aoki, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quantitative+in+vivo+fluorescence+cross-correlation+analyses+highlight+the+importance+of+competitive+effects+in+the+regulation+of+protein-protein+interactions.">Quantitative in vivo fluorescence cross-correlation analyses highlight the importance of competitive effects in the regulation of protein-protein interactions.</a> Molecular and Cellular Biology. 34 (17), 3272-3290 (2014).</li><li>Cohen, L. D., Boulos, A., Ziv, N. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+non-fluorescent+HaloTag+blocker+for+improved+measurement+and+visualization+of+protein+synthesis+in+living+cells.">A non-fluorescent HaloTag blocker for improved measurement and visualization of protein synthesis in living cells.</a> F1000Research. 9, (2020).</li></ol>

Regarding system calibration before measurements, the same glasswares as the one used to measure the sample should be used (e.g., the 8-wells cover glass chamber for cell lysate and the 35-mm glass base dish for live cells). Because of the adsorption of Rh6G on the glass, its effective concentration may sometimes decrease. If so, a highly concentrated Rh6G solution such as 1 &#956;M should be used just for the pinhole adjustment. Extremely high photon count rates must be avoided to protect the detector (e.g., more than 1...

Protein aggregations involving neurodegenerative disorders such as amyotrophic lateral sclerosis (ALS), Alzheimer's disease, Parkinson's disease, Huntington's disease, and so on1 are known to be toxic and would disturb protein homeostasis (proteostasis) in the cells and organs, that could then lead to aging2. The clearance of protein aggregation is expected as a therapeutic strategy; however, chemicals that prevent protein aggregation formation and degrade protein aggregates (e.g., small molecules or drugs) have not been established yet. Moreover, how protein aggregation exerts toxicity remains elusive. Therefore, to promote research projects related to protein aggregation, it is important to introduce high throughput procedures to simply detect protein aggregation. Protein aggregation detection using antibodies recognizing the conformation of protein aggregation and aggregation-specific fluorescent dye has been widely used3. However, it is difficult to detect the aggregation, especially in live cells using such classical procedures. 
F&#246;rster resonance energy transfer (FRET) is a procedure to detect protein aggregation and structural change. However, FRET is unable to analyze protein dynamics (e.g., diffusion and oligomerization of protein in live cells)3. Therefore, we introduce here a simple protocol to detect protein aggregation in solution (e.g., cell lysate) and live cells using fluorescence correlation spectroscopy (FCS), which measures the diffusion property and brightness of fluorescent molecules with single molecule sensitivity4. FCS is a photon-counting method by using a laser scan confocal microscope (LSM). Using a highly sensitive photon-detector and calculation of autocorrelation function (ACF) of photon arrival time, the pass through time and brightness of the fluorescent molecules in the detection volume is measured. The diffusion slows with an increase of molecular weight; thus, intermolecular interaction can be estimated using FCS. Even more powerfully, an increase in the brightness of the fluorescent molecule indicates homo-oligomerization of the molecules. Therefore, FCS is a powerful tool to detect such protein aggregation.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>0.25% (w/v) Trypsin-1 mmol/L EDTA&#183;4Na Solution with Phenol Red (Trypsin-EDTA)</td>
			<td>Fujifilm Wako Pure Chemical Corp.</td>
			<td>201-16945</td>
			<td></td>
		</tr>
		<tr>
			<td>100-mm plastic dishes</td>
			<td>CORNING</td>
			<td>430167</td>
			<td></td>
		</tr>
		<tr>
			<td>35-mm glass base dish</td>
			<td>IWAKI</td>
			<td>3910-035</td>
			<td>For live cell measurement</td>
		</tr>
		<tr>
			<td>35-mm plastic dishes</td>
			<td>Thermo Fisher Scientific</td>
			<td>150460</td>
			<td></td>
		</tr>
		<tr>
			<td>Aluminum plate</td>
			<td>Bio-Bik</td>
			<td>AB-TC1</td>
			<td></td>
		</tr>
		<tr>
			<td>C-Apochromat 40x/1.2NA Korr. UV-VIS-IR M27</td>
			<td>Carl Zeiss</td>
			<td></td>
			<td>Objective</td>
		</tr>
		<tr>
			<td>Cell scraper</td>
			<td>Sumitomo Bakelite Co., Ltd.</td>
			<td>MS-93100</td>
			<td></td>
		</tr>
		<tr>
			<td>Cellulose acetate filter membrane (0.22 mm)</td>
			<td>Advantech Toyo</td>
			<td>25CS020AS</td>
			<td></td>
		</tr>
		<tr>
			<td>Cover glass chamber 8-wells</td>
			<td>IWAKI</td>
			<td>5232-008</td>
			<td>For solution measurement</td>
		</tr>
		<tr>
			<td>Dulbecco&#39;s Modified Eagle&#39;s Medium (DMEM)</td>
			<td>Sigma-Aldrich</td>
			<td>D5796</td>
			<td>basal medium</td>
		</tr>
		<tr>
			<td>Fetal bovine serum (FBS)</td>
			<td>biosera</td>
			<td></td>
			<td>Lot check required</td>
		</tr>
		<tr>
			<td>Lipofectamine 2000</td>
			<td>Thermo Fisher Scientific</td>
			<td>11668019</td>
			<td></td>
		</tr>
		<tr>
			<td>LSM510 META + ConfoCor3</td>
			<td>Carl Zeiss</td>
			<td></td>
			<td>FCS system</td>
		</tr>
		<tr>
			<td>Murine neuroblastoma Neuro2a cells</td>
			<td>ATCC</td>
			<td>CCL-131</td>
			<td>Cell line</td>
		</tr>
		<tr>
			<td>Opti-MEM I</td>
			<td>Thermo Fisher Scientific</td>
			<td>31985070</td>
			<td></td>
		</tr>
		<tr>
			<td>pCAGGS</td>
			<td>RIKEN</td>
			<td>RDB08938</td>
			<td>Plasmid DNA for the transfection carrier</td>
		</tr>
		<tr>
			<td>Penicillin-Streptomycin Solution (&#215;100 )</td>
			<td>Fujifilm Wako Pure Chemical Corp.</td>
			<td>168-23191</td>
			<td></td>
		</tr>
		<tr>
			<td>pmeGFP-C1-TDP25</td>
			<td></td>
			<td></td>
			<td>Plasmid DNA for TDP25 tagged with monomeric eGFP</td>
		</tr>
		<tr>
			<td>pmeGFP-N1</td>
			<td></td>
			<td></td>
			<td>Plasmid DNA for eGFP monomer expression</td>
		</tr>
		<tr>
			<td>pmeGFP-N1-SOD1-G85R</td>
			<td></td>
			<td></td>
			<td>Plasmid DNA for ALS-linked G85R mutant of SOD1 tagged with monomeric eGFP</td>
		</tr>
		<tr>
			<td>Protease inhibitor cocktail</td>
			<td>Sigma-Aldrich</td>
			<td>P8304</td>
			<td></td>
		</tr>
	</tbody>
</table>

detection of protein aggregation using fluorescence correlation spectroscopy

Protein aggregation is a hallmark of neurodegenerative disorders such as amyotrophic lateral sclerosis (ALS), Alzheimer's disease (AD), Parkinson's disease (PD), Huntington's disease (HD), and so on. To detect and analyze soluble or diffuse protein oligomers or aggregates, fluorescence correlation spectroscopy (FCS), which can detect the diffusion speed and brightness of a single particle with a single molecule sensitivity, has been used. However, the proper procedure and know-how for protein aggregation detection have not been widely shared. Here, we show a standard procedure of FCS measurement for diffusion properties of aggregation-prone proteins in cell lysate and live cells: ALS-associated 25 kDa carboxyl-terminal fragment of TAR DNA/RNA-binding protein 43 kDa (TDP25) and superoxide dismutase 1 (SOD1). The representative results show that a part of aggregates of green fluorescent protein (GFP)-tagged TDP25 was slightly included in the soluble fraction of murine neuroblastoma Neuro2a cell lysate. Moreover, GFP-tagged SOD1 carrying ALS-associated mutation shows a slower diffusion in live cells. Accordingly, we here introduce the procedure to detect the protein aggregation via its diffusion property using FCS.

We performed FCS measurement of GFP-TDP25 in cell lysate and SOD1-G85R-GFP in live cells. In both cases, a positive amplitude and smooth ACFs were able to be acquired. We have shown that a portion of GFP-TDP25 expressed in Neuro2a cells was recovered in the soluble fraction under the indicated condition6. In the soluble fraction of the cell lysate, extremely bright fluorescence molecules were detected in the photon count rate record using FCS (Figure 2A, top, arrow). ...

Watch this Scientific Journal Video about Detection of Protein Aggregation using Fluorescence Correlation Spectroscopy at JoVE.com

Detection of Protein Aggregation using Fluorescence Correlation Spectroscopy

We here introduce a procedure to measure protein oligomers and aggregation in cell lysate and live cells using fluorescence correlation spectroscopy.

Protein aggregation is a hallmark of neurodegenerative disorders such as amyotrophic lateral sclerosis (ALS), Alzheimer's disease (AD), Parkinson's ...

The best principle of the Fluorescence correlation spectroscopy, FCS, was invented initially in the 1970s. In the 1990s, important and many improvements for FCS was established by combining with a confocal apparatus microscopy. Since then, FCS has been used for many chemical and virus cure applications, such as molecular interactions and protein aggregation analysis.Protein aggregation is a hallmark of neurodegenerative disorders. Fluorescence brightness are single particles in action of molecular sizes explained by diffusion properties. It's very important in measuring protein aggregations because it can determine projected life cycles of molecules, but also distinguish the homo or hetero polymerization.Here, we introduce a procedure to measure diffusion of amyotrophic lateral sclerosis associated with aggregated form protein using FCS in cell lysates and live cells. Prepare 100 millimeter plastic dish growing Neuro2a cell sitting comfortably in the normal growth medium. Confirm the cell confluency.Remove the medium. Add 3.5 milliliters of Trypsin-EDTA solution into the third cartridge dish and incubate them at 37 degrees celsius for one minute. Add 9.5 milliliter normal growth medium into the dish and suspend them.The cell suspension is mixed with trypan blue to stain the dead cells. Add suspension to the cell-counting slide. Count the number of cells using the cell counter, or manually.Check the live cell number and their viability. Dilute the cell in the counted medium at 1.0 times 10 to the power of 5 per milliliter. Add two milliliters of cell suspension into the 35 millimeter plastic dish for cell lysis or growth space dish for live cell measurement.Incubate the dish at 37 degrees celsius for one day. The next day, prepare the mixture of plasmid DNA and the transfection reagents. Add the transfection mixture to the cell-counted medium and incubate the cells for 24 hours.One day later. Check the GFP expression using a routine microscope. You can see the very bright TDP25 ingredient bodies in cells.Cell lysis should be performed at the biochemical bench. Remove the medium in the dish. Add two milliliters of PBS at 25 degrees celsius to wash as a medium.Remove the PBS. Place the dish on an aluminum plate on the top of the crushed ice. Immediately, add the 200 microliter lysis buffer into the dish.Scrape the dish using a cell scraper. Recover the lysate with undissolved cell debris in a new 1.5 millimeter tube. Centrifuge the lysate at four degrees celsius.For live cell measurements, replace the medium with a fresh one before the measurement. Check the cell attachment using a phase-contrast microscope. Also, check the GFP expression using a fluorescence microscope.Use a confocal microscope-combined FCS system. Turn on the 488 nanometer laser. Stabilize the system, at least, for 30 minutes.Set up the optical path. Use a 488 nanometer laser for the instant light. Use an appropriate beam splitter and dichroic meters.And also, fluorescence fusers. Usually, we'll use coverglass chambers for calibration and solution measurements. Carefully, take the coverglass chamber.Place the glass surface on the lens screening paper. Pour the FCS calibration. Add the Rhodamine 6G solution in as well.Add the ultrapure water on the objective. Do not use the oil. Set the chamber on the microscope stage.Move the stage to the appropriate position. Create the pinhole adjustment and open the pinhole adjustment wizard. Monitor the photon count rate as coarse movement of the pinhole for the x-direction.The brightest position was rightly determined. Next, monitor the photon count rate as fine movement. The brightest position was successfully determined This is the pinhole position for x-direction.As the same way, search the brightest position of the pinhole for y-direction. The brightest position for y-direction was also successfully determined. Compound the x and y position of the pinhole.It is better to adjust the pinhole position before each day's measurement. When the live path is changed, the pinhole position must be adjusted again. Create a count rate and monitor the phone count rate.Change to the CPM monitoring mode. Count the correction ring of the object you ran so that the CPM value is the highest. Close the count rate window.Start with the Rhodamine 6G solution measurement. After the measurement is completed, click the fit to perform Curve Fitting Analysis. Select a model for fitting of the old correlation function.For Rhodamine 6G, select the model for 1-component, 3-dimensional diffusion with a triplet state. Set the fitting start time by moving the red line. Click Fit All, to start the fitting calculation.Check the fit deviation. Make sure that sides are posted and negative, around zero. Check the fitted values.Make sure the diffusion time is roughly in the range of from 20-30 microseconds. Moreover, structural parameter is from four to eight. Open the fit panel, and select a model for the measurement.Enter the same structural parameter value in the model for the sample in the fit panel. Make sure the type should be set as Fixed. GFP-TDP25 measurement in cell lysate.Place the lysate in the coverglass chamber. Place the lid to avoid dry up of the lysate. Place the stage lid for light shading.In the acquisition panel, set the laser power, measurement time, and its repetitions. Start the acquisition. A spike was observed.A spike was observed again. The spike indicates bright molecules passed through the detection body. Spikes indicate soluble oligomers or aggregates.Create a fit to perform curve fitting analysis. Select the model for 2-component, 3-dimensional diffusion with triplet state. Set the fitting start time.Click the Fit All. Check the fitted values. SOD1-G85R tagged with GFP measurement in a live cell.Unlike solution measurement, I recommend using the heat stage incubator. Set the cell-culturing dish on the microscope stage. Confirm the focus and the position using the ocular.Select a measuring cell. Zoom-in and adjust the cell position using a fast scanning mode. Acquire the snapshot of the cells using the slow scanning speed mode.Select an FCS-measuring position using the Position tool. The crosshair indicates the measuring position. Start the measurement.The slight decrease of the photon count rate record suggests photobleaching of GFP. Perform the curve fitting. Representative results of GFP-TDP25 in cell lysate is shown.The top graph a record of photon count rate. Where there's arrows is a spike, suggesting soluble oligomers and aggregates. The middle graph represents the old correlation function.The gray line shows the low, old correlation function. The magenta line shows the fitted function. The dotted lines indicate the start and end times for fitting.The bottom table shows the fitted value. Next, representative results of SOD1-G85R-GFP in a live cell are shown. The top graph represents a record of our photon count rate.The gradual decrease of the recorded photon count rate was observed, suggesting photobleaching of GFP growth for different measurements. This is because of the slow diffusion speed in live cells. The middle graph represents the old correlation function of SOD1.The gray line shows the low, old correlation function. The magenta line show the fitted function. The dotted lines indicate the start and end times with fitting.The bottom table shows fitted values. Here we show you this procedure to measure diffusion from every cell associated TDP-25 in cell lysate and everything mutant of SOD1 in live cells using FCS. The soluble oligomers and aggregation in cell lysate can be often observed as spikes or bursts.On the other hand, in live cells, such spikes are rarely observed, except for possibly obvious live structures. A slowly diffusing species of mutant SOD1's add mean brightness for single particles such as SOD1 homopolymerization inside for us. The procedure shown here is simple and worthwhile.FCS contains no radiation;directly dormant state. It's just your, and our, imagination empathy.

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Unit 1

Protein Structure

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Detection of Protein Ubiquitination

Ubiquitination, the covalent attachment of the polypeptide ubiquitin to target proteins, is a key posttranslational modification carried out by a set of three enzymes. They include ubiquitin-activating enzyme E1, ubiquitin-conjugating enzyme E2, and ubiquitin ligase E3. Unlike to E1 and E2, E3 ubiquitin ligases display substrate specificity. On the other hand, numerous deubiquitylating enzymes have roles in processing polyubiquitinated proteins. Ubiquitination can result in change of protein stability, cellular localization, and biological activity. Mutations of genes involved in the ubiquitination/deubiquitination pathway or altered ubiquitin system function are associated with many different human diseases such as various types of cancer, neurodegeneration, and metabolic disorders. The detection of altered or normal ubiquitination of target proteins may provide a better understanding on the pathogenesis of these diseases. &nbsp;Here, we describe protocols to detect protein ubiquitination in cultured cells in vivo and test tubes in vitro. These protocols are also useful to detect other ubiquitin-like small molecule modification such as sumolyation and neddylation.

Ubiquitination is a key posttranslational modification carried out by a set of three enzymes. Mutations of genes involved in this modification are associated with many different human diseases. Here, we describe protocols to detect protein ubiquitination in cultured cells in vivo and test tubes in vitro.

Ubiquitination, the covalent attachment of the polypeptide ubiquitin to target proteins, is a key posttranslational modification carried out by a set of ...

Using the GELFREE 8100 Fractionation System for Molecular Weight-Based Fractionation with Liquid Phase Recovery

The GELFREE 8100 Fractionation System is a novel protein fractionation system designed to maximize protein recovery during molecular weight based fractionation. The system is comprised of single-use, 8-sample capacity cartridges and a benchtop GELFREE Fractionation Instrument. During separation, a constant voltage is applied between the anode and cathode reservoirs, and each protein mixture is electrophoretically driven from a loading chamber into a specially designed gel column gel. Proteins are concentrated into a tight band in a stacking gel, and separated based on their respective electrophoretic mobilities in a resolving gel. As proteins elute from the column, they are trapped and concentrated in liquid phase in the collection chamber, free of the gel. The instrument is then paused at specific time intervals, and fractions are collected using a pipette. This process is repeated until all desired fractions have been collected. If fewer than 8 samples are run on a cartridge, any unused chambers can be used in subsequent separations.
This novel technology facilitates the quick and simple separation of up to 8 complex protein mixtures simultaneously, and offers several advantages when compared to previously available fractionation methods. This system is capable of fractionating up to 1mg of total protein per channel, for a total of 8mg per cartridge. Intact proteins over a broad mass range are separated on the basis of molecular weight, retaining important physiochemical properties of the analyte. The liquid phase entrapment provides for high recovery while eliminating the need for band or spot cutting, making the fractionation process highly reproducible1.

The accompanying video describes the use of the GELFREE 8100 Fractionation System, which partitions complex protein samples on the basis of molecular weight and recovers the fractions in liquid phase. The video describes how the technology works, how it is used, and provides resultant data, with polyacrylamide gel electrophoresis analysis of fractionated bovine liver homogenate.

The GELFREE 8100 Fractionation System is a novel protein fractionation system designed to maximize protein recovery during molecular weight based ...

Time-lapse Imaging of Mitosis After siRNA Transfection

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

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

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

Bimolecular Fluorescence Complementation (BiFC) Assay for Protein-Protein Interaction in Onion Cells Using the Helios Gene Gun

Investigation of gene function in diverse organisms relies on knowledge of how the gene products interact with each other in their normal cellular environment. The Bimolecular Fluorescence Complementation (BiFC) Assay1 allows researchers to visualize protein-protein interactions in living cells and has become an essential research tool. This assay is based on the facilitated association of two fragments of a fluorescent protein (GFP) that are each fused to a potential interacting protein partner. The interaction of the two protein partners would facilitate the association of the N-terminal and C-terminal fragment of GFP, leading to fluorescence. For plant researchers, onion epidermal cells are an ideal experimental system for conducting the BiFC assay because of the ease in obtaining and preparing onion tissues and the direct visualization of fluorescence with minimal background fluorescence. The Helios Gene Gun (BioRad) is commonly used for bombarding plasmid DNA into onion cells. We demonstrate the use of Helios Gene Gun to introduce plasmid constructs for two interacting Arabidopsis thaliana transcription factors, SEUSS (SEU) and LEUNIG HOMOLOG (LUH)2 and the visualization of their interactions mediated by BiFC in onion epidermal cells.

Bimolecular Fluorescence Complementation BiFC Assay for Protein-Protein Interaction in Onion Cells Using the Helios Gene Gun

This article illustrates how to properly use the BioRad Helios Gene Gun to introduce plasmid DNA into onion epidermal cells and how to test for protein-protein interactions in onion cells based on the principle of Bimolecular Fluorescence Complementation (BiFC)

Investigation of gene function in diverse organisms relies on knowledge of how the gene products interact with each other in their normal cellular ...

In-vivo Detection of Protein-protein Interactions on Micro-patterned Surfaces

Unraveling the interaction network of molecules in-vivo is key to understanding the mechanisms that regulate cell function and metabolism. A multitude of methodological options for addressing molecular interactions in cells have been developed, but most of these methods suffer from being rather indirect and therefore hardly quantitative. On the contrary, a few high-end quantitative approaches were introduced, which however are difficult to extend to high throughput. To combine high throughput capabilities with the possibility to extract quantitative information, we recently developed a new concept for identifying protein-protein interactions (Schwarzenbacher et al., 2008). Here, we describe a detailed protocol for the design and the construction of this system which allows for analyzing interactions between a fluorophore-labeled protein ("prey") and a membrane protein ("bait") in-vivo. Cells are plated on micropatterned surfaces functionalized with antibodies against the bait exoplasmic domain. Bait-prey interactions are assayed via the redistribution of the fluorescent prey. The method is characterized by high sensitivity down to the level of single molecules, the capability to detect weak interactions, and high throughput capability, making it applicable as screening tool.

In-vivo Detection of Protein-protein Interactions on Micro-patterned Surfaces

This video shows experiments with subsequent analysis of protein-protein interactions by the use of micro-patterned surfaces. The approach offers the possibility to detect protein interactions in living cells and combines high throughput capabilities with the possibility to extract quantitative information.

Unraveling the interaction network of molecules in-vivo is key to understanding the mechanisms that regulate cell function and metabolism. A multitude of ...

Detection of Protein Interactions in Plant using a Gateway Compatible Bimolecular Fluorescence Complementation (BiFC) System

We have developed a BiFC technique to test the interaction between two proteins in vivo. This is accomplished by splitting a yellow fluorescent protein (YFP) into two non-overlapping fragments. Each fragment is cloned in-frame to a gene of interest. These constructs can then be co-transformed into Nicotiana benthamiana via Agrobacterium mediated transformation, allowing the transit expression of fusion proteins. The reconstitution of YFP signal only occurs when the inquest proteins interact 1-7. To test and validate the protein-protein interactions, BiFC can be used together with yeast two hybrid (Y2H) assay. This may detect indirect interactions which can be overlooked in the Y2H. Gateway technology is a universal platform that enables researchers to shuttle the gene of interest (GOI) into as many expression and functional analysis systems as possible8,9. Both the orientation and reading frame can be maintained without using restriction enzymes or ligation to make expression-ready clones. As a result, one can eliminate all the re-sequencing steps to ensure consistent results throughout the experiments. We have created a series of Gateway compatible BiFC and Y2H vectors which provide researchers with easy-to-use tools to perform both BiFC and Y2H assays10. Here, we demonstrate the ease of using our BiFC system to test protein-protein interactions in N. benthamiana plants.

Detection of Protein Interactions in Plant using a Gateway Compatible Bimolecular Fluorescence Complementation BiFC System

We have developed a technique to test protein-protein interactions in plant. A yellow fluorescent protein (YFP) is split into two non-overlapping fragments. Each fragment is cloned in-frame to a gene of interest via Gateway system, enabling expression of fusion proteins. Reconstitution of YFP signal only occurs when the inquest proteins interact.

We have developed a BiFC technique to test the interaction between two proteins in vivo. This is accomplished by splitting a yellow fluorescent protein ...

Determination of Lipid Raft Partitioning of Fluorescently-tagged Probes in Living Cells by Fluorescence Correlation Spectroscopy (FCS)

In the past fifteen years the notion that cell membranes are not homogenous and rely on microdomains to exert their functions has become widely accepted. Lipid rafts are membrane microdomains enriched in cholesterol and sphingolipids. They play a role in cellular physiological processes such as signalling, and trafficking1,2 but are also thought to be key players in several diseases including viral or bacterial infections and neurodegenerative diseases3.
Yet their existence is still a matter of controversy4,5. Indeed, lipid raft size has been estimated to be around 20 nm6, far under the resolution limit of conventional microscopy (around 200 nm), thus precluding their direct imaging. Up to now, the main techniques used to assess the partition of proteins of interest inside lipid rafts were Detergent Resistant Membranes (DRMs) isolation and co-patching with antibodies. Though widely used because of their rather easy implementation, these techniques were prone to artefacts and thus criticized7,8. Technical improvements were therefore necessary to overcome these artefacts and to be able to probe lipid rafts partition in living cells.
Here we present a method for the sensitive analysis of lipid rafts partition of fluorescently-tagged proteins or lipids in the plasma membrane of living cells. This method, termed Fluorescence Correlation Spectroscopy (FCS), relies on the disparity in diffusion times of fluorescent probes located inside or outside of lipid rafts. In fact, as evidenced in both artificial membranes and cell cultures, probes would diffuse much faster outside than inside dense lipid rafts9,10. To determine diffusion times, minute fluorescence fluctuations are measured as a function of time in a focal volume (approximately 1 femtoliter), located at the plasma membrane of cells with a confocal microscope (Fig. 1). The auto-correlation curves can then be drawn from these fluctuations and fitted with appropriate mathematical diffusion models11.
FCS can be used to determine the lipid raft partitioning of various probes, as long as they are fluorescently tagged. Fluorescent tagging can be achieved by expression of fluorescent fusion proteins or by binding of fluorescent ligands. Moreover, FCS can be used not only in artificial membranes and cell lines but also in primary cultures, as described recently12. It can also be used to follow the dynamics of lipid raft partitioning after drug addition or membrane lipid composition change12.

Determination of Lipid Raft Partitioning of Fluorescently-tagged Probes in Living Cells by Fluorescence Correlation Spectroscopy FCS

A technique to probe the lipid raft partitioning of fluorescent proteins at the plasma membrane of living cells is described. It takes advantage of the disparity in diffusion times of proteins located inside or outside of lipid rafts. Acquisition can be performed dynamically in control conditions or after drug addition.

In the past fifteen years the notion that cell membranes are not homogenous and rely on microdomains to exert their functions has become widely accepted. ...

Detection of Viral RNA by Fluorescence in situ Hybridization (FISH)

Viruses that infect cells elicit specific changes to normal cell functions which serve to divert energy and resources for viral replication. Many aspects of host cell function are commandeered by viruses, usually by the expression of viral gene products that recruit host cell proteins and machineries. Moreover, viruses engineer specific membrane organelles or tag on to mobile vesicles and motor proteins to target regions of the cell (during de novo infection, viruses co-opt molecular motor proteins to target the nucleus; later, during virus assembly, they will hijack cellular machineries that will help in the assembly of viruses). Less is understood on how viruses, in particular those with RNA genomes, coordinate the intracellular trafficking of both protein and RNA components and how they achieve assembly of infectious particles at specific loci in the cell. The study of RNA localization began in earlier work. Developing lower eukaryotic embryos and neuronal cells provided important biological information, and also underscored the importance of RNA localization in the programming of gene expression cascades. The study in other organisms and cell systems has yielded similar important information. Viruses are obligate parasites and must utilise their host cells to replicate. Thus, it is critical to understand how RNA viruses direct their RNA genomes from the nucleus, through the nuclear pore, through the cytoplasm and on to one of its final destinations, into progeny virus particles 1.
FISH serves as a useful tool to identify changes in steady-state localization of viral RNA. When combined with immunofluorescence (IF) analysis 22, FISH/IF co-analyses will provide information on the co-localization of proteins with the viral RNA3. This analysis therefore provides a good starting point to test for RNA-protein interactions by other biochemical or biophysical tests 4,5, since co-localization by itself is not enough evidence to be certain of an interaction. In studying viral RNA localization using a method like this, abundant information has been gained on both viral and cellular RNA trafficking events 6. For instance, HIV-1 produces RNA in the nucleus of infected cells but the RNA is only translated in the cytoplasm. When one key viral protein is missing (Rev) 7, FISH of the viral RNA has revealed that the block to viral replication is due to the retention of the HIV-1 genomic RNA in the nucleus 8. 
Here, we present the method for visual analysis of viral genomic RNA in situ. The method makes use of a labelled RNA probe. This probe is designed to be complementary to the viral genomic RNA. During the in vitro synthesis of the antisense RNA probe, the ribonucleotide that is modified with digoxigenin (DIG) is included in an in vitro transcription reaction. Once the probe has hybridized to the target mRNA in cells, subsequent antibody labelling steps (Figure 1) will reveal the localization of the mRNA as well as proteins of interest when performing FISH/IF.

Detection of Viral RNA by Fluorescence in situ Hybridization FISH

A fluorescence in situ hybridization (FISH) method was developed to visually detect viral genomic RNA using fluorescence microscopy. A probe is made with specificity to the viral RNA that can then be identified using a combination of hybridization and immunofluorescence techniques. This technique offers the advantage of identifying the localization of the viral RNA or DNA at steady-state, providing information on the control of intracellular virus trafficking events.

Viruses  that infect cells elicit specific changes to normal cell functions which serve  to divert energy and resources for viral replication. Many ...

4D Imaging of Protein Aggregation in Live Cells

One of the key tasks of any living cell is maintaining the proper folding of newly synthesized proteins in the face of ever-changing environmental conditions and an intracellular environment that is tightly packed, sticky, and hazardous to protein stability1. The ability to dynamically balance protein production, folding and degradation demands highly-specialized quality control machinery, whose absolute necessity is observed best when it malfunctions. Diseases such as ALS, Alzheimer's, Parkinson's, and certain forms of Cystic Fibrosis have a direct link to protein folding quality control components2, and therefore future therapeutic development requires a basic understanding of underlying processes. Our experimental challenge is to understand how cells integrate damage signals and mount responses that are tailored to diverse circumstances.
The primary reason why protein misfolding represents an existential threat to the cell is the propensity of incorrectly folded proteins to aggregate, thus causing a global perturbation of the crowded and delicate intracellular folding environment1. The folding health, or "proteostasis," of the cellular proteome is maintained, even under the duress of aging, stress and oxidative damage, by the coordinated action of different mechanistic units in an elaborate quality control system3,4. A specialized machinery of molecular chaperones can bind non-native polypeptides and promote their folding into the native state1, target them for degradation by the ubiquitin-proteasome system5, or direct them to protective aggregation inclusions6-9.
In eukaryotes, the cytosolic aggregation quality control load is partitioned between two compartments8-10: the juxtanuclear quality control compartment (JUNQ) and the insoluble protein deposit (IPOD) (Figure 1 - model). Proteins that are ubiquitinated by the protein folding quality control machinery are delivered to the JUNQ, where they are processed for degradation by the proteasome. Misfolded proteins that are not ubiquitinated are diverted to the IPOD, where they are actively aggregated in a protective compartment.
Up until this point, the methodological paradigm of live-cell fluorescence microscopy has largely been to label proteins and track their locations in the cell at specific time-points and usually in two dimensions. As new technologies have begun to grant experimenters unprecedented access to the submicron scale in living cells, the dynamic architecture of the cytosol has come into view as a challenging new frontier for experimental characterization. We present a method for rapidly monitoring the 3D spatial distributions of multiple fluorescently labeled proteins in the yeast cytosol over time. 3D timelapse (4D imaging) is not merely a technical challenge; rather, it also facilitates a dramatic shift in the conceptual framework used to analyze cellular structure.
We utilize a cytosolic folding sensor protein in live yeast to visualize distinct fates for misfolded proteins in cellular aggregation quality control, using rapid 4D fluorescent imaging. The temperature sensitive mutant of the Ubc9 protein10-12 (Ubc9ts) is extremely effective both as a sensor of cellular proteostasis, and a physiological model for tracking aggregation quality control. As with most ts proteins, Ubc9ts is fully folded and functional at permissive temperatures due to active cellular chaperones. Above 30 &deg;C, or when the cell faces misfolding stress, Ubc9ts misfolds and follows the fate of a native globular protein that has been misfolded due to mutation, heat denaturation, or oxidative damage. By fusing it to GFP or other fluorophores, it can be tracked in 3D as it forms Stress Foci, or is directed to JUNQ or IPOD.

Cellular viability depends on timely and efficient management of protein misfolding. Here we describe a method for visualizing the different potential fates of a misfolded protein: refolding, degradation, or sequestration in inclusions. We demonstrate the use of a folding sensor, Ubc9ts, for monitoring proteostasis and aggregation quality control in live cells using 4D microscopy.

One of the key tasks of any living cell is maintaining the proper folding of newly synthesized proteins in the face of ever-changing environmental ...

Easy Measurement of Diffusion Coefficients of EGFP-tagged Plasma Membrane Proteins Using k-Space Image Correlation Spectroscopy

Lateral diffusion and compartmentalization of plasma membrane proteins are tightly regulated in cells and thus, studying these processes will reveal new insights to plasma membrane protein function and regulation. Recently, k-Space Image Correlation Spectroscopy (kICS)1&#160;was developed to enable routine measurements of diffusion coefficients directly from images of fluorescently tagged plasma membrane proteins, that avoided systematic biases introduced by probe photophysics. Although the theoretical basis for the analysis is complex, the method can be implemented by nonexperts using a freely available code to measure diffusion coefficients of proteins. kICS calculates a time correlation function from a fluorescence microscopy image stack after Fourier transformation of each image to reciprocal (k-) space. Subsequently, circular averaging, natural logarithm transform and linear fits to the correlation function yields the diffusion coefficient. This paper provides a step-by-step guide to the image analysis and measurement of diffusion coefficients via kICS.
First, a high frame rate image sequence of a fluorescently labeled plasma membrane protein is acquired using a fluorescence microscope. Then, a region of interest (ROI) avoiding intracellular organelles, moving vesicles or protruding membrane regions is selected. The ROI stack is imported into a freely available code and several defined parameters (see Method section) are set for kICS analysis. The program then generates a &#34;slope of slopes&#34; plot from the k-space time correlation functions, and the diffusion coefficient is calculated from the slope of the plot. Below is a step-by-step kICS procedure to measure the diffusion coefficient of a membrane protein using the renal water channel aquaporin-3 tagged with EGFP as a canonical example.

This paper provides a step by step guide to the fluctuation analysis technique k-Space Image Correlation Spectroscopy (kICS) for measuring diffusion coefficients of fluorescently labeled plasma membrane proteins in live mammalian cells.

Lateral diffusion and compartmentalization of plasma membrane proteins are tightly regulated in cells and thus, studying these processes will reveal new ...