This work was supported by the Tau Consortium (M.I.D); National Institutes of Health Grant 1R01NS071835 (M.I.D.), a Department of Defense Grant PT110816 (to M.I.D.), 1F32NS087805 (to J.L.F.), and 1F31NS079039 (to B.B.H.).

NOTE: This protocol emphasizes the use of FRET flow cytometry for detecting seeding activity from mouse biological samples. It is also compatible with recombinant fibrils and human biological samples. Mouse euthanasia and brain harvesting was performed in accordance with IACUC-approved procedures.
1. Brain Extraction
<ol>
	<li>Following deep anesthetization with isoflurane (2%), perfuse a mouse with ice-cold PBS containing 0.03% heparin, and extract the brain following the details described in Gage et al.18</li>
	<li>Place extracted tissue in a cryo-vial, and snap freeze by placing in liquid nitrogen. Alternatively, freeze tissue on dry ice. Once frozen, transfer tissue to -80 &#176;C and store for an extended period of time, if necessary. 
	NOTE: This protocol is compatible with whole brain homogenates or micro-dissected brain regions. See Hagihara et al. for a detailed micro-dissection protocol19.</li>
</ol>
2. Preparation of Biological Seed Material
<ol>
	<li>Prepare homogenization buffer by dissolving protease inhibitors (EDTA free) into 1x TBS (1 tablet per 10 ml). Vortex vigorously, and store on ice. Protease inhibitors must be EDTA free in order to preserve biosensor cell viability.</li>
	<li>Weigh frozen brain tissue in a disposable weigh boat, and transfer to a 5 ml conical tube. Add ice-cold homogenization buffer such that the final solution is 10% weight/volume. Temporarily store on ice. Tissue mass and subsequent homogenization buffer volume will vary depending on the brain size and/or regions used. Here, an adult mouse hemibrain weighing 0.2 g is suspended in 2 ml for a 10% w/vol solution.</li>
	<li>Transfer samples into a cold room, and adjust a probe sonicator to the appropriate settings. For probe sonication with an Omni Ruptor (shown here), set the power to 20%, which corresponds to approximately 75 W. Use a pulse mode to ensure samples are not over-heated during sonication. Set the pulser to 30%, corresponding to approximately 500 msec.</li>
	<li>Clean the tip of the probe sonicator by rinsing with water, isopropanol, and water again, wiping off the probe in between each solution. Be certain to rinse and wipe both the sides and bottom of the probe with lab-wipes.</li>
	<li>Working with one sample at a time, submerge the probe tip into the homogenization buffer, and start the sonicator. Using the power and pulser settings described above, deliver 25 total pulses. Ensure that tissue is completely in suspension. Be careful to avoid foaming of the sample during this step. 
	NOTE: Samples are susceptible to foaming if a) the total volume is low or b) the homogenate warms up. With this specific instrument, do not sonicate with volumes less than 250 &#181;l. To ensure samples stay chilled, tubes may be stored on ice during this step.</li>
	<li>Clean the probe by wiping away residual lysate, then deliver 10 pulses into a beaker of clean water. Rinse the sides and bottom of the probe with water, isopropanol, and water again (as in step 2.4), wiping dry in between each step. To avoid contamination, thoroughly rinse the probe in between samples. 
	NOTE: With tau aggregates, we have not found that more stringent cleaning methods are necessary for preventing sample-to-sample contamination. Other amyloids, however, may require additional care which has been extensively described in literature20,21.</li>
	<li>Store homogenates on ice until all samples have been processed.</li>
	<li>Spin homogenates at 21,300 x g for 15 min at 4 &#176;C.</li>
	<li>Transfer the supernatant to a clean tube, taking care not to disturb the pellet. Discard the pellet. Aliquot the supernatant, and store lysates at -80 &#176;C for further use. Avoid freeze/thaw cycles of the homogenates, however, as this reduces seeding efficiency.</li>
</ol>
3. Replating Biosensor Cells
NOTE: Use four cell lines for this assay: HEK 293T (cell line #1), RD-P301S-CFP (cell line #2), RD-P301S-YFP (cell line #3), and RD-P301S-CFP/YFP (cell line #4). Please reference Table 1 for each cell line&#8217;s contribution to the assay.
<ol>
	<li>In a sterile environment, aspirate culture medium. Rinse cells with warm PBS, and aspirate. Trypsinize cells (3 ml of trypsin-EDTA (0.05%)) for 3 min, quench with warm culture medium (9 ml of DMEM, 10% FBS, 1% pen/strep, 1% GlutaMax), and immediately transfer cells to a conical tube.</li>
	<li>Centrifuge cells at 1,000 x g for 5 min at RT. Aspirate medium, and resuspend cell pellet in warm culture medium.</li>
	<li>Using a hemocytometer, determine the cell density for each cell line. Cell density will vary depending on confluency at time of harvesting and resuspension volume. Resuspend cells harvested from a 10 cm dish at 90% confluency in 10 ml media, for cell density to be approximately 1 million cells/ml.</li>
	<li>Make a master mix of cells + media such that each well of a 96 well plate will contain 35,000 cells in 130 &#181;l media (e.g., to make a master mix for 100 wells, resuspend 3.5 million cells in 13 ml media). Modify the cell number to fit individual experimental designs and timelines. For cell treatment ~18 hr after plating, add 35,000 cells to each well of a 96-well plate.</li>
	<li>Using a multi-channel pipet, slowly pipette 130 &#181;l of master mix cell suspension into each well of a flat bottom, tissue culture-treated 96 well plate. While plating, place the pipet tip in the center of the well, not touching the bottom of the plate. 
	NOTE: Though plating format can be modified, making n = 4 wells for each of cell lines 1-3 per plate is recommended. The remainder of the plate (n = 84) is reserved for cell line #4 (biosensor cells).</li>
	<li>Allow the cells to settle by leaving the plate undisturbed for 10 min&#160;at RT. Incubate O/N at 37 &#176;C, 5% CO2, and &#8805;80% relative humidity.</li>
</ol>
4. Treating Cells
NOTE: The following day, when tau biosensor cells are 60-65% confluent, prepare seed transduction complexes as follows:
<ol>
	<li>In one tube, combine transfection reagent, such as Lipofectamine, with reduced-serum media, such as Opti-MEM, to make a master mix. Per well, add 1.25 &#181;l transfection reagent and 8.75 &#181;l reduced-serum media. Flick tube gently to mix, briefly spin down, and incubate for 5 min at RT.</li>
	<li>In another tube, combine seed material (aliquot of lysate from step 2.9) with reduced-serum media. 
	NOTE: Volume of seed material will vary according to the individual experiment. When choosing seed volume, take into consideration: abundance of seeds in a sample and potential toxicity. Crude homogenates can be toxic to cells. As such, use the lowest volume possible to monitor your desired effect. Previously tested volumes of lysate/well range from 1-5 &#181;l, corresponding to 5-20 &#181;g total protein. Ensure that the total volume per well (seeds + reduced-serum media) is 10 &#181;l.</li>
	<li>Combine contents from the two tubes described in 4.1 and 4.2, flick gently to mix, briefly spin down (1,000 x g, 5 sec), and incubate at RT for at least 20 min and up to 2 hr.</li>
	<li>Gently pipette 20 &#181;l of transduction complex on the side of individual biosensor wells. Use three technical replicates, if possible. Return treated cells to the incubator for 24-48 hr. Incubate under the same conditions as described in step 3.6. 
	NOTE: The appropriate negative control condition for this setup is biosensor cells treated with empty liposomes (i.e., liposome reagent + reduced-serum media) because application of phospholipids introduces a slight shift in the fluorescence profile relative to biosensor cells unexposed to liposome reagent.</li>
</ol>
5. Harvesting Cells for FRET Flow Cytometry
NOTE: Before harvesting cells&#8212;generally 24-48 hr post-treatment&#8212;it is possible to get a preliminary readout of seeding activity using the GFP filter on a standard inverted fluorescence microscope. Cells treated without seed material (i.e., empty liposomes) will show diffuse fluorescence, whereas cells treated with seed material will show intense punctate and reticular intracellular inclusions (Figure 1A-B).
<ol>
	<li>Using a multi-channel pipet, aspirate all cell medium (150 &#181;l) . Trypsinize (50 &#181;l) cells for 5 min, and quench with 150 &#181;l chilled culture medium. Do not include a PBS rinse prior to trypsinization at this step, as it may cause cell lifting and subsequent cell loss. Exclude any contaminating dead cells and debris during flow cytometry via gating strategies.</li>
	<li>Immediately after quenching, transfer cells to a 96 well round bottom plate, and centrifuge at 1,000 x g for 5 min at RT.</li>
	<li>Aspirate and discard medium, taking care to avoid disturbing the cell pellet.</li>
	<li>Gently, but thoroughly, resuspend the cell pellet in 50 &#181;l 2% paraformaldehyde, and incubate for 10 min. Alternatively, run cells live, although fixation provides cleaner and more consistent results.</li>
	<li>Centrifuge cells at 1,000 x g for 5 min at RT. Aspirate and discard paraformaldehyde, taking care to avoid disturbing the cell pellet.</li>
	<li>Gently, but thoroughly, resuspend the cell pellet in 200 &#181;l chilled flow cytometry buffer (HBSS, 1% FBS, 1 mM EDTA) and run the plate as soon as possible to avoid cell clumping.</li>
</ol>
6. FRET Flow Cytometry
NOTE: Use a flow cytometer such as the MACSQuant VYB, which is equipped with FRET-compatible laser lines and filter sets (Table 2). For each step within this section, click the well of interest using the software&#8217;s 96 well template, and click &#8220;play&#8221; to begin sample uptake and flow. Make plots or statistics tables by clicking the &#39;new analysis window&#39; icon. Change axis parameters on individual bivariate plots by clicking the title on either the X or Y axis and selecting the appropriate filter. To shift cell populations or fluorescence signals, increase or decrease the voltages associated with the appropriate filters. With this instrument, run &#60;1,000 events/sec to ensure accurate single-cell monitoring.
<ol>
	<li>Make a Side Scatter-Area (SSC-A) vs Forward Scatter-Area (FSC-A) bivariate plot, and with cell line #1 running, adjust the SSC and FSC voltages until the cell population is in the lower left quadrant. Click the polygon tool, and define the cell population (Gate P1). For all gating parameters see Figure 2.</li>
	<li>Make a FSC-H (height) vs FSC-A bivariate plot, and apply Gate P1 to this plot by clicking &#8220;live&#8221; above the plot, and selecting P1. With cell line #1 running, click the polygon tool, and define single cells (Gate P2).</li>
	<li>Make 3 histogram plots, one for each of the filters of interest: CFP, YFP, and FRET. Apply Gate P2 to all of these plots by clicking &#8220;live&#8221; above the plots, and selecting P2. With cell line #1 running, adjust voltages such that the median cell population in the CFP, YFP, and FRET histograms are all between 0 and 1. To measure CFP and FRET, excite cells with the 405 nm laser, and capture fluorescence with a 450/50 nm and 525/50 nm filter, respectively. To measure YFP, excite cells with a 488 nm laser and capture fluorescence with a 525/50 nm filter. Laser and filter settings are further described in Table 2.</li>
	<li>Perform compensation for CFP spillover into the FRET and YFP channels. 
	NOTE: Compensation is the process of fluorescence spillover correction. Fluorescence spillover occurs whenever the fluorescence emission of one fluorochrome is detected within a filter designed to measure signal from another fluorochrome. With proper compensation, the CFP spillover fluorescence can be removed from the FRET and YFP channels. 
	NOTE: Compensation requires the presence of both fluorescence -positive and -negative cells. Thus, to compensate on CFP-positive cells (cell line #2), negative cells (cell line #1) must be added to the sample prior to the run.
	<ol>
		<li>Spike in 30 &#181;l of cell line #1 suspension from a single well into 200 &#181;l of cell line #2 suspension immediately prior to compensating.</li>
		<li>Click the &#8220;Instrument Settings&#8221; icon, then &#39;compensation&#39; tab, and check &#39;matrix&#39; to open the compensation table.</li>
		<li>Make a FRET-A vs CFP-A bivariate plot, and apply gate P2, as described in step 6.3. With cell lines 1+2 running, click the &#39;quadrant&#39; icon and draw quadrants such that the fluorescence -negative and -positive populations are separated by the lower two quadrants (Gates LL3 and LR3, respectively).</li>
		<li>Create a statistics table that displays the median fluorescence intensity (MFI) of FRET for the LL3 and LR3 gates. Adjust the FRET parameter in the compensation matrix until the MFI of the FRET signal is equivalent between LL3 and LR3. Following this step, the MFI of the FRET signal is equal between unstained cells and CFP-positive cells, suggesting the absence of CFP spillover into the FRET channel.</li>
		<li>Make a YFP-A vs CFP-A bivariate plot, and apply gate P2, as described in step 6.3. Draw quadrants (LL4 and LR4) similar to that done in step 6.4.3.</li>
		<li>Create a statistics table that displays the MFI of YFP for LL4 and LR4. Adjust the YFP parameter in the compensation matrix until the MFI of the YFP signal is equivalent between LL4 and LR4. Following this step, the MFI of a YFP signal is equal between unstained cells and CFP-positive cells, suggesting the absence of CFP spillover into the YFP channel.</li>
	</ol>
	</li>
	<li>Following gate setup and compensation, highlight wells of interest and run the remainder of the plate.</li>
	<li>After all samples have been run, export data files by clicking &#39;file&#39;, then &#39;copy&#39;. Select the &#39;data files&#39; tab, highlight the experiment folder, and click &#39;copy&#39;.</li>
</ol>
7. Data Analysis
NOTE: Change axis parameters on individual bivariate plots by clicking the title on either the X or Y axis and selecting the appropriate filter.
<ol>
	<li>Open FCS files in the flow cytometry analysis program.</li>
	<li>Based on scatter properties, use a polygonal gate to define the cell population (SSC vs FSC) and singlet population (FSC-H vs FSC-A) from cells treated with empty liposomes, similarly to that described in Section 6.</li>
	<li>If CFP compensation was performed during setup, do not further adjust CFP.</li>
	<li>Create a FRET vs YFP bivariate plot. Using cell line #3, define a false FRET gate by drawing a polygonal gate that runs along the slope of the FRET-positive cell population. This gate excludes YFP single-positive cells that emit a signal within the FRET filter, and is drawn similar to that previously shown by Banning et al.22</li>
	<li>Define a FRET gate by plotting empty liposome-treated CFP/YFP cells on a FRET vs CFP bivariate plot. Introduce a polygonal gate along the slope of the population that extends upward and leftward away from the population. This gate should exclude most cells (~99%), such that background FRET is &#8805;1% of cells. Any events that shift into this gate are considered FRET-positive. 
	NOTE: Each individual gate described above is applied to all samples before constructing subsequent gates. Following analysis, four individual gates are defined (Cell population; singlet; false FRET; FRET).</li>
	<li>Record analysis parameters of interest, including: percent FRET positivity and MFI of FRET-positive cells. Manually calculate the integrated FRET density by measuring the product of percent positivity and MFI. 
	NOTE: If integrated FRET density is used as an outcome measure, set background FRET (as defined in step 7.5) and MFI to greater than or equal to 1 in order to avoid calculating a product that is less than its two individual factors.</li>
</ol>

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This assay has been licensed to Janssen Pharmaceuticals.

The FRET flow cytometry system described here is a powerful tool for quickly and quantitatively assessing tau seeding activity. It requires only moderate cell culture experience and a working knowledge of FRET and flow cytometry. Other seeding assays, such as Thioflavin T - which exhibits enhanced fluorescence when bound to beta sheet structure - are laborious and require a pure, recombinant protein substrate. Additionally, in vitro seeding assays for tau are only semi-quantitative and generally insensitive to s...

The accumulation of intracellular tau amyloids defines tauopathies such as Alzheimer&#39;s disease. In early disease stages, pathology is generally localized to discrete regions of the brain, but with disease progression, pathology invariably spreads along distinct neural networks1-5. Accumulating evidence suggests transcellular propagation of toxic protein aggregates underlies this pathology (reviewed in 6-10). In this model, proteopathic seeds (e.g., tau) are released from donor cells and enter neighboring cells, transforming native tau protein into the misfolded form via templated conformational change11-15. The assay described here was developed to sensitively detect such seeding activity. It is compatible with recombinant protein and biological samples and enables quantification of minute levels of proteopathic seeding activity16.
HEK 293T cells that stably express tau repeat domain (RD) containing the disease-associated P301S mutation fused to either CFP or YFP (hereafter referred to as tau-RD-CFP/YFP cells) serve as a stable biosensor of seeding activity. In the absence of proteopathic seeds, the cells maintain tau as a soluble monomer, and have no appreciable background FRET. Spontaneous uptake or liposome-mediated transduction of tau seeds into cells, however, results in RD-CFP and RD-YFP aggregation, which produces a FRET signal that is measured within single cells via flow cytometry.
Numerous components of this assay were engineered to enhance sensitivity and reduce variability. A monoclonal cell line with a 1:1 RD-CFP/YFP expression ratio was selected, as it provides optimal signal:noise. To increase sensitivity, phospholipids are used to introduce seeds directly into cells (although to study biological mechanisms of uptake, this can be omitted). Finally, flow cytometry monitors FRET at a population level and a single cell level, unlike other protein aggregation assays. The final outcome measure, integrated FRET density, is highly quantitative and accounts both for the number of cells with aggregation, and the degree to which aggregation has occurred within each cell. All of these optimized parameters enhance sensitivity and ensure reproducibility.
This system was recently employed in a comprehensive study in transgenic P301S tauopathy mice17 that evaluated the temporal onset and progression of tau seeding activity relative to other commonly used tau pathological markers (e.g., MC1, AT8, PG5, and ThioflavinS). Seeding activity is by far the earliest and most robust marker of tau pathology evaluated, preceding histological detection by at least 6 weeks. Seeding activity appears at 1.5 months and increases progressively with age, suggesting a causal role of proteopathic seeds in the onset and/or progression of neurodegeneration16.
Precise quantitation of minute levels of seed material from biological samples can facilitate studies that monitor early disease progression. By shortening trial duration and enabling use of younger animals, this could increase the efficiency and accuracy of preclinical animal trials. For example, in the P301S mouse previously described, lead compounds could be delivered as early as 4-6 weeks (immediately prior to, or at onset of seeding activity), and monitored for efficacy 2-4 weeks later. The assay should accurately quantify any reductions in seeding activity. FRET flow cytometry has in vitro screening applications as well. For example, anti-tau reagents (e.g., antibodies, small molecules, etc.) can be tested rapidly for their capacity to block seeding induction directly in culture, using either recombinant tau aggregates or brain-derived lysates as a seed source (Figure 5). With this setup, once seed material is prepared, an experiment takes just three days to complete, including data analysis. The rapid quantitation of proteopathic seeding activity can thus facilitate many studies of neurodegeneration.

<table>
	<tbody>
		<tr>
			<td>TBS</td>
			<td>Sigma</td>
			<td>T5912</td>
		</tr>
		<tr>
			<td>cOmplete Protease Inhibitors (EDTA-free)</td>
			<td>Roche</td>
			<td>4693159001</td>
		</tr>
		<tr>
			<td>Cryo-vials</td>
			<td>Sarstedt</td>
			<td>72.694.006</td>
		</tr>
		<tr>
			<td>Analytical Balance</td>
			<td>Mettler Toledo</td>
			<td>XSE 105DU</td>
		</tr>
		<tr>
			<td>Weighing Boats</td>
			<td>Fisher Scientific</td>
			<td>13-735-743</td>
		</tr>
		<tr>
			<td>15 mL conical tube</td>
			<td>USA Scientific</td>
			<td>1475-0501</td>
		</tr>
		<tr>
			<td>Omni Sonic Ruptor Ultrasonic Homogenizer</td>
			<td>Omni International</td>
			<td>18-000-115</td>
		</tr>
		<tr>
			<td>Micro-Tip for Ultrasonic Homogenizer</td>
			<td>Omni International</td>
			<td>OR-T-156</td>
		</tr>
		<tr>
			<td>2-Propanol</td>
			<td>Fisher Scientific</td>
			<td>A451</td>
		</tr>
		<tr>
			<td>Noise Cancelling Ear Muffs</td>
			<td>Fisher Scientific</td>
			<td>19-145-412</td>
		</tr>
		<tr>
			<td>Kimwipes</td>
			<td>Fisher Scientific</td>
			<td>S47299</td>
		</tr>
		<tr>
			<td>1.5 mL tubes</td>
			<td>USA Scientific</td>
			<td><a href="http://www.usascientific.com/Seal-Rite-1.5-ml-tube-sterile.aspx">1615-5510</a></td>
		</tr>
		<tr>
			<td>Microcentrifuge&#160;</td>
			<td>Eppendorf</td>
			<td>5424 000.215</td>
		</tr>
		<tr>
			<td>DPBS</td>
			<td>Life Technologies</td>
			<td>14190-136</td>
		</tr>
		<tr>
			<td>DMEM</td>
			<td>Life Technologies</td>
			<td>11965-084</td>
		</tr>
		<tr>
			<td>Fetal Bovine Serum</td>
			<td>HyClone</td>
			<td>SH30071.03</td>
		</tr>
		<tr>
			<td>Penicillin-Streptomycin</td>
			<td>Life Technologies</td>
			<td>15140-122</td>
		</tr>
		<tr>
			<td>GlutaMax</td>
			<td>Life Technologies</td>
			<td>35050-061</td>
		</tr>
		<tr>
			<td>Trypsin-EDTA</td>
			<td>Life Technologies</td>
			<td>25300-054</td>
		</tr>
		<tr>
			<td>50 mL Conical Tubes</td>
			<td>Phenix Research</td>
			<td>SS-PH15</td>
		</tr>
		<tr>
			<td>25 mL reagent resevoirs</td>
			<td>VWR</td>
			<td>41428-954</td>
		</tr>
		<tr>
			<td>Multi channel pipet</td>
			<td>Fisher Scientific</td>
			<td>TI13-690-049</td>
		</tr>
		<tr>
			<td>96 well flat bottom plates</td>
			<td>Corning</td>
			<td>3603</td>
		</tr>
		<tr>
			<td>Opti-MEM</td>
			<td>Life Technologies</td>
			<td>31985-070</td>
		</tr>
		<tr>
			<td>Lipofectamine 2000</td>
			<td>Invitrogen</td>
			<td>11668019</td>
		</tr>
		<tr>
			<td>96 well round bottom plates</td>
			<td>Corning</td>
			<td>3788</td>
		</tr>
		<tr>
			<td>16% Paraformaldehyde</td>
			<td>Electron Microscopy Sciences</td>
			<td>RT 15710</td>
		</tr>
		<tr>
			<td>PBS</td>
			<td>Sigma-Aldrich</td>
			<td>P5493</td>
		</tr>
		<tr>
			<td>EDTA</td>
			<td>Sigma-Aldrich</td>
			<td>ED2SS</td>
		</tr>
		<tr>
			<td>HBSS</td>
			<td>Life Technologies</td>
			<td>14185-052</td>
		</tr>
		<tr>
			<td>Sorvall ST 40 Centrifuge</td>
			<td>Thermo Scientific</td>
			<td>75004509</td>
		</tr>
		<tr>
			<td>BIOLiner Swinging Bucket Rotor</td>
			<td>Thermo Scientific</td>
			<td>75003796</td>
		</tr>
		<tr>
			<td>Hemacytometer</td>
			<td>VWR</td>
			<td>15170-172</td>
		</tr>
		<tr>
			<td>MACSQuant VYB Flow Cytomter</td>
			<td>Miltenyi Biotec</td>
			<td>130-096-116</td>
		</tr>
		<tr>
			<td>Chill 96 Rack</td>
			<td>Miltenyi Biotec</td>
			<td>130-094-459</td>
		</tr>
		<tr>
			<td>Flow Jo analysis software</td>
			<td>Flow Jo</td>
			<td></td>
		</tr>
		<tr>
			<td>20 uL pipet tips</td>
			<td>Rainin</td>
			<td>GPS-L10</td>
		</tr>
		<tr>
			<td>200 uL pipet tips</td>
			<td>Rainin</td>
			<td>GPS-250</td>
		</tr>
		<tr>
			<td>1 mL pipet tips</td>
			<td>Rainin</td>
			<td>GPS-1000</td>
		</tr>
		<tr>
			<td>200 uL pipet tips</td>
			<td>USA Scientific</td>
			<td>1111-1800</td>
		</tr>
		<tr>
			<td>5 mL serological pipett</td>
			<td>Phenix Research</td>
			<td>SPG-606180</td>
		</tr>
		<tr>
			<td>10 mL serological pipett</td>
			<td>Phenix Research</td>
			<td>SPG-607180</td>
		</tr>
		<tr>
			<td>25 mL Serological pipett</td>
			<td>Phenix Research</td>
			<td>SPG-760180</td>
		</tr>
	</tbody>
</table>

sensitive detection of proteopathic seeding activity with fret flow cytometry

Increasing evidence supports transcellular propagation of toxic protein aggregates, or proteopathic seeds, as a mechanism for the initiation and progression of pathology in several neurodegenerative diseases, including Alzheimer's disease and the related tauopathies. The potentially critical role of tau seeds in disease progression strongly supports the need for a sensitive assay that readily detects seeding activity in biological samples. 
By combining the specificity of fluorescence resonance energy transfer (FRET), the sensitivity of flow cytometry, and the stability of a monoclonal cell line, an ultra-sensitive seeding assay has been engineered and is compatible with seed detection from recombinant or biological samples, including human and mouse brain homogenates. The assay employs monoclonal HEK 293T cells that stably express the aggregation-prone repeat domain (RD) of tau harboring the disease-associated P301S mutation fused to either CFP or YFP, which produce a FRET signal upon protein aggregation. The uptake of proteopathic tau seeds (but not other proteins) into the biosensor cells stimulates aggregation of RD-CFP and RD-YFP, and flow cytometry sensitively and quantitatively monitors this aggregation-induced FRET. The assay detects femtomolar concentrations (monomer equivalent) of recombinant tau seeds, has a dynamic range spanning three orders of magnitude, and is compatible with brain homogenates from tauopathy transgenic mice and human tauopathy subjects. With slight modifications, the assay can also detect seeding activity of other proteopathic seeds, such as &#945;-synuclein, and is also compatible with primary neuronal cultures. The ease, sensitivity, and broad applicability of FRET flow cytometry makes it useful to study a wide range of protein aggregation disorders.

FRET flow cytometry enables sensitive, quantitative, and rapid detection of seeding activity from recombinant or biological samples. Assay setup is facile: monoclonal-derived stable cell lines expressing tau-RD-CFP/YFP are transduced with seed material, incubated for 24-48 hr, and subjected to flow cytometry analysis (Figure 1A). In the absence of seeds, biosensor cells maintain tau in a soluble, monomeric form (Figure 1B). In the presence of seeds, however, biosensor cells convert tau i...

Watch this Scientific Journal Video about Sensitive Detection of Proteopathic Seeding Activity with FRET Flow Cytometry at JoVE.com

Sensitive Detection of Proteopathic Seeding Activity with FRET Flow Cytometry

Cell-to-cell transfer of protein aggregates, or proteopathic seeds, may underlie the progression of pathology in neurodegenerative diseases. Here, a novel FRET flow cytometry assay is described that enables specific and sensitive detection of seeding activity from recombinant or biological samples.

Increasing evidence supports transcellular propagation of toxic protein aggregates, or proteopathic seeds, as a mechanism for the initiation and ...

sensitive-detection-proteopathic-seeding-activity-with-fret-flow

Research

JoVE Journal

Bioengineering

14.9K Views.  University of Texas Southwestern Medical Center. Cell-to-cell transfer of protein aggregates, or proteopathic seeds, may underlie the progression of pathology in neurodegenerative diseases. Here, a novel FRET flow cytometry assay is described that enables specific and sensitive detection of seeding activity from recombinant or biological samples.

Video: Sensitive Detection of Proteopathic Seeding Activity with FRET Flow Cytometry

Analyzing Cellular Internalization of Nanoparticles and Bacteria by Multi-spectral Imaging Flow Cytometry

Nanoparticulate systems have emerged as valuable tools in vaccine delivery through their ability to efficiently deliver cargo, including proteins, to antigen presenting cells1-5. Internalization of nanoparticles (NP) by antigen presenting cells is a critical step in generating an effective immune response to the encapsulated antigen. To determine how changes in nanoparticle formulation impact function, we sought to develop a high throughput, quantitative experimental protocol that was compatible with detecting internalized nanoparticles as well as bacteria. To date, two independent techniques, microscopy and flow cytometry, have been the methods used to study the phagocytosis of nanoparticles. The high throughput nature of flow cytometry generates robust statistical data. However, due to low resolution, it fails to accurately quantify internalized versus cell bound nanoparticles. Microscopy generates images with high spatial resolution; however, it is time consuming and involves small sample sizes6-8. Multi-spectral imaging flow cytometry (MIFC) is a new technology that incorporates aspects of both microscopy and flow cytometry that performs multi-color spectral fluorescence and bright field imaging simultaneously through a laminar core. This capability provides an accurate analysis of fluorescent signal intensities and spatial relationships between different structures and cellular features at high speed.
	Herein, we describe a method utilizing MIFC to characterize the cell populations that have internalized polyanhydride nanoparticles or Salmonella enterica serovar Typhimurium. We also describe the preparation of nanoparticle suspensions, cell labeling, acquisition on an ImageStreamX system and analysis of the data using the IDEAS application. We also demonstrate the application of a technique that can be used to differentiate the internalization pathways for nanoparticles and bacteria by using cytochalasin-D as an inhibitor of actin-mediated phagocytosis.

In this article, we describe a method utilizing multi-spectral imaging flow cytometry to quantify the internalization of polyanhydride nanoparticles or bacteria by RAW 264.7 cells.

Nanoparticulate  systems have emerged as valuable tools in vaccine delivery through their  ability to efficiently deliver cargo, including proteins, to ...

Evaluation of Polymeric Gene Delivery Nanoparticles by Nanoparticle Tracking Analysis and High-throughput Flow Cytometry

Non-viral gene delivery using polymeric nanoparticles has emerged as an attractive approach for gene therapy to treat genetic diseases1 and as a technology for regenerative medicine2. Unlike viruses, which have significant safety issues, polymeric nanoparticles can be designed to be non-toxic, non-immunogenic, non-mutagenic, easier to synthesize, chemically versatile, capable of carrying larger nucleic acid cargo and biodegradable and/or environmentally responsive. Cationic polymers self-assemble with negatively charged DNA via electrostatic interaction to form complexes on the order of 100 nm that are commonly termed polymeric nanoparticles. Examples of biomaterials used to form nanoscale polycationic gene delivery nanoparticles include polylysine, polyphosphoesters, poly(amidoamines)s and polyethylenimine (PEI), which is a non-degradable off-the-shelf cationic polymer commonly used for nucleic acid delivery1,3 . Poly(beta-amino ester)s (PBAEs) are a newer class of cationic polymers4 that are hydrolytically degradable5,6 and have been shown to be effective at gene delivery to hard-to-transfect cell types such as human retinal endothelial cells (HRECs)7, mouse mammary epithelial cells8, human brain cancer cells9 and macrovascular (human umbilical vein, HUVECs) endothelial cells10.
A new protocol to characterize polymeric nanoparticles utilizing nanoparticle tracking analysis (NTA) is described. In this approach, both the particle size distribution and the distribution of the number of plasmids per particle are obtained11. In addition, a high-throughput 96-well plate transfection assay for rapid screening of the transfection efficacy of polymeric nanoparticles is presented. In this protocol, poly(beta-amino ester)s (PBAEs) are used as model polymers and human retinal endothelial cells (HRECs) are used as model human cells. This protocol can be easily adapted to evaluate any polymeric nanoparticle and any cell type of interest in a multi-well plate format.

A protocol for nanoparticle tracking analysis (NTA) and high-throughput flow cytometry to evaluate polymeric gene delivery nanoparticles is described. NTA is utilized to characterize the nanoparticle particle size distribution and the plasmid per particle distribution. High-throughput flow cytometry enables quantitative transfection efficacy evaluation for a library of gene delivery biomaterials.

Non-viral gene delivery using polymeric nanoparticles has emerged as an attractive approach for gene therapy to treat genetic diseases1 and as a ...

Wide-field Fluorescent Microscopy and Fluorescent Imaging Flow Cytometry on a Cell-phone

Fluorescent microscopy and flow cytometry are widely used tools in biomedical research and clinical diagnosis. However these devices are in general relatively bulky and costly, making them less effective in the resource limited settings. To potentially address these limitations, we have recently demonstrated the integration of wide-field fluorescent microscopy and imaging flow cytometry tools on cell-phones using compact, light-weight, and cost-effective opto-fluidic attachments. In our flow cytometry design, fluorescently labeled cells are flushed through a microfluidic channel that is positioned above the existing cell-phone camera unit. Battery powered light-emitting diodes (LEDs) are butt-coupled to the side of this microfluidic chip, which effectively acts as a multi-mode slab waveguide, where the excitation light is guided to uniformly excite the fluorescent targets. The cell-phone camera records a time lapse movie of the fluorescent cells flowing through the microfluidic channel, where the digital frames of this movie are processed to count the number of the labeled cells within the target solution of interest. Using a similar opto-fluidic design, we can also image these fluorescently labeled cells in static mode by e.g. sandwiching the fluorescent particles between two glass slides and capturing their fluorescent images using the cell-phone camera, which can achieve a spatial resolution of e.g. ~ 10 &mu;m over a very large field-of-view of ~ 81 mm2. This cell-phone based fluorescent imaging flow cytometry and microscopy platform might be useful especially in resource limited settings, for e.g. counting of CD4+ T cells toward monitoring of HIV+ patients or for detection of water-borne parasites in drinking water.

We review our recent results on the integration of fluorescent microscopy and imaging flow cytometry tools on a cell-phone using compact and cost-effective opto-fluidic attachments. These cell-phone based micro-analysis devices might be useful for cytometric analysis, such as performing various cell counting tasks as well as for high-throughput screening of e.g., water samples in resource limited settings.

Fluorescent microscopy and flow cytometry are widely used tools in biomedical research and clinical diagnosis. However these devices are in general ...

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

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

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

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

Flying Insect Detection and Classification with Inexpensive Sensors

An inexpensive, noninvasive system that could accurately classify flying insects would have important implications for entomological research, and allow for the development of many useful applications in vector and pest control for both medical and agricultural entomology. Given this, the last sixty years have seen many research efforts devoted to this task. To date, however, none of this research has had a lasting impact. In this work, we show that pseudo-acoustic optical sensors can produce superior data; that additional features, both intrinsic and extrinsic to the insect&#8217;s flight behavior, can be exploited to improve insect classification; that a Bayesian classification approach allows to efficiently learn classification models that are very robust to over-fitting, and a general classification framework allows to easily incorporate arbitrary number of features. We demonstrate the findings with large-scale experiments that dwarf all previous works combined, as measured by the number of insects and the number of species considered.

We proposed a system that uses inexpensive, noninvasive pseudo-acoustic optical sensors to automatically and accurately detect, count, and classify flying insects based on their flying sound.

An inexpensive, noninvasive system that could accurately classify flying insects would have important implications for entomological research, and allow ...

Fast Enzymatic Processing of Proteins for MS Detection with a Flow-through Microreactor

The vast majority of mass spectrometry (MS)-based protein analysis methods involve an enzymatic digestion step prior to detection, typically with trypsin. This step is necessary for the generation of small molecular weight peptides, generally with MW &#60; 3,000-4,000 Da, that fall within the effective scan range of mass spectrometry instrumentation. Conventional protocols involve O/N enzymatic digestion at 37 &#186;C. Recent advances have led to the development of a variety of strategies, typically involving the use of a microreactor with immobilized enzymes or of a range of complementary physical processes that reduce the time necessary for proteolytic digestion to a few minutes (e.g., microwave or high-pressure). In this work, we describe a simple and cost-effective approach that can be implemented in any laboratory for achieving fast enzymatic digestion of a protein. The protein (or protein mixture) is adsorbed on C18-bonded reversed-phase high performance liquid chromatography (HPLC) silica particles preloaded in a capillary column, and trypsin in aqueous buffer is infused over the particles for a short period of time. To enable on-line MS detection, the tryptic peptides are eluted with a solvent system with increased organic content directly in the MS ion source. This approach avoids the use of high-priced immobilized enzyme particles and does not necessitate any aid for completing the process. Protein digestion and complete sample analysis can be accomplished in less than ~3 min and ~30 min, respectively.

A quick protocol for proteolytic digestion with an in-house built flow-through tryptic microreactor coupled to an electrospray ionization (ESI) mass spectrometer is presented. The fabrication of the microreactor, the experimental setup and the data acquisition process are described.

The vast majority of mass spectrometry (MS)-based protein analysis methods involve an enzymatic digestion step prior to detection, typically with trypsin. ...

Isolation of Primary Murine Retinal Ganglion Cells (RGCs) by Flow Cytometry

Neurodegenerative diseases often have a devastating impact on those affected. Retinal ganglion cell (RGC) loss is implicated in an array of diseases, including diabetic retinopathy and glaucoma, in addition to normal aging. Despite their importance, RGCs have been extremely difficult to study until now due in part to the fact that they comprise only a small percentage of the wide variety of cells in the retina. In addition, current isolation methods use intracellular markers to identify RGCs, which produce non-viable cells. These techniques also involve lengthy isolation protocols, so there is a lack of practical, standardized, and dependable methods to obtain and isolate RGCs. This work describes an efficient, comprehensive, and reliable method to isolate primary RGCs from mice retinae using a protocol based on both positive and negative selection criteria. The presented methods allow for the future study of RGCs, with the goal of better understanding the major decline in visual acuity that results from the loss of functional RGCs in neurodegenerative diseases.

Isolation of Primary Murine Retinal Ganglion Cells RGCs by Flow Cytometry

Millions of people suffer from retinal degenerative diseases that result in irreversible blindness. A common element of many of these diseases is the loss of retinal ganglion cells (RGCs). This detailed protocol describes the isolation of primary murine RGCs by positive and negative selection with flow cytometry.

Neurodegenerative diseases often have a devastating impact on those affected. Retinal ganglion cell (RGC) loss is implicated in an array of diseases, ...

Seeding and Implantation of a Biosynthetic Tissue-engineered Tracheal Graft in a Mouse Model

Treatment options for congenital or secondary long segment tracheal defects have historically been limited due to an inability to replace functional tissue. Tissue engineering holds great promise as a potential solution with its ability to integrate cells and signaling molecules into a 3-dimensional scaffold. Recent work with tissue engineered tracheal grafts (TETGs) has seen some success but their translation has been limited by graft stenosis, graft collapse, and delayed epithelialization. In order to investigate the mechanisms driving these issues, we have developed a mouse model for tissue engineered tracheal graft implantation. TETGs were constructed using electrospun polymers polyethylene terephthalate (PET) and polyurethane (PU) in a mixture of PET and PU (20:80 percent weight). Scaffolds were then seeded using bone marrow mononuclear cells isolated from 6-8 week-old C57BL/6 mice by gradient centrifugation. Ten million cells per graft were seeded onto the lumen of the scaffold and allowed to incubate overnight before implantation between the third and seventh tracheal rings. These grafts were able to recapitulate the findings of stenosis and delayed epithelialization as demonstrated by histological analysis and lack of Keratin 5 and Keratin 14 basal epithelial cells on immunofluorescence. This model will serve as a tool for investigating cellular and molecular mechanisms involved in host remodeling.

Graft stenosis poses a critical obstacle in tissue engineered airway replacement. To investigate cellular mechanisms underlying stenosis, we utilize a murine model of tissue engineered tracheal replacement with seeded bone marrow mononuclear cells (BM-MNC). Here, we detail our protocol, including scaffold manufacturing, BM-MNC isolation, graft seeding, and implantation.

Treatment options for congenital or secondary long segment tracheal defects have historically been limited due to an inability to replace functional ...

Ovarian Cancer Detection Using Photoacoustic Flow Cytometry

Many studies suggest that the enumeration of circulating tumor cells (CTCs) may show promise as a prognostic tool for ovarian cancer. Current strategies for the detection of CTCs include flow cytometry, microfluidic devices, and real-time polymerase chain reaction (RT-PCR). Despite recent advances, methods for the detection of early ovarian cancer metastasis still lack the sensitivity and specificity required for clinical translation. Here, a novel method is presented for the detection of ovarian circulating tumor cells by photoacoustic flow cytometry (PAFC) utilizing a custom three dimensional (3D) printed system, including a flow chamber and syringe pump. This method utilizes folic acid-capped copper sulfide nanoparticles (FA-CuS NPs) to target SKOV-3 ovarian cancer cells by PAFC. This work demonstrates the affinity of these contrast agents for ovarian cancer cells. The results show NP characterization, PAFC detection, and NP uptake by fluorescence microscopy, thus demonstrating the potential of this novel system to detect ovarian CTCs at physiologically relevant concentrations.

A protocol is presented to detect circulating ovarian tumor cells utilizing a custom-made photoacoustic flow system and targeted folic acid-capped copper sulfide nanoparticles.

Many studies suggest that the enumeration of circulating tumor cells (CTCs) may show promise as a prognostic tool for ovarian cancer. Current strategies ...

High-Dimensionality Flow Cytometry for Immune Function Analysis of Dissected Implant Tissues

The success of implanting laboratory-grown tissue or a medical device in an individual is subject to the immune response of the recipient host. Considering an implant as a foreign body, a hostile and dysregulated immune response may result in the rejection of the implant, while a regulated response and regaining of homeostasis can lead to its acceptance. Analyzing the microenvironments of implants dissected out under in vivo or ex vivo&#160;settings can help in understanding the pattern of immune response, which can ultimately help in developing new generations of biomaterials. Flow cytometry is a well-known technique for characterizing immune cells and their subsets based on their cell surface markers. This review describes a protocol based on manual dicing, enzymatic digestion, and filtration through a cell strainer for the isolation of uniform cell suspensions from dissected implant tissue. Further, a multicolor flow cytometry staining protocol has been explained, along with steps for initial cytometer settings to characterize and quantify these isolated cells by flow cytometry.

Isolation of cells from dissected implants and their characterization by flow cytometry can significantly contribute to understanding the pattern of immune response against implants. This paper describes a precise method for the isolation of cells from dissected implants and their staining for flow cytometric analysis.