This research was supported in part by the Intramural Research Program of the NIH, including the National Institute of Biomedical Imaging and Bioengineering. Disclaimer: The NIH, its officers, and employees do no recommend or endorse any company, product, or service.

NOTE: Figure 1 gives an overview of the flow cytometry protocol.
1) Reagent preparation
<ol>
	<li>Prepare media for diluting enzymes and for tissue culture.
	<ol>
		<li>Add 5 mL of 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid (HEPES) buffer solution into 500 mL of RPMI medium and shake well. Store the medium at 4 &#176;C until further use.</li>
	</ol>
	</li>
	<li>Calculate the volume of the enzyme solution. 
	&#8203;NOTE: The volume of the enzyme solution is the volume of the medium containing the enzymes (collagenase and DNase I) that will be needed to digest diced tissue in 6-well plates; it depends on the number of samples.
	<ol>
		<li>Use the following equation to calculate the required volume: 
		(Number of samples to be digested) &#215; 5 mL of serum-free RPMI with 10 mM HEPES buffer 
		&#8203;NOTE: For example, for 0.1 to 0.3 g of dissected spleen, use 5 mL of medium to prepare the enzyme solution. The enzymatic digestion protocol described in this manuscript is primarily for soft tissues (ranging from 0.1 to 1 g) dissected from mice which include the brain, kidney, skin, liver, lungs, spleen, muscles, as well as capsules around subcutaneous implants made of synthetic materials or extracellular matrix proteins. Digesting hard cartilaginous tissues might require different conditions and volumes of digestive enzymes, which can only be ascertained by optimization.</li>
		<li>Calculate the amount of collagenase and DNase I needed for the enzyme solution. 
		NOTE: In this protocol, 0.25 mg/mL of collagenase and 0.2 mg/mL of DNase I were used. The working concentrations required for collagenase and DNase can vary for different types of tissues19.</li>
	</ol>
	</li>
	<li>Prepare a 1:1000 viability dye solution by adding 1 &#181;L of the viability dye (see Table of Materials) to 999 &#181;L of phosphate-buffered saline (PBS) and vortex the solution. Store the solution in the dark at 4 &#176;C until further use.</li>
	<li>Prepare the staining buffer by adding 1 g of bovine serum albumin (BSA) to 100 mL of PBS, and vortex the solution until BSA is completely dissolved. Store the solution at 4 &#176;C until further use.</li>
</ol>
2) Setting up enzymatic digestion plates
<ol>
	<li>Set up a 6-well plate with 70 &#181;m cell strainers in each well. Add 3 mL of the prepared medium from step 1.1.1 into each well, and incubate on ice.</li>
	<li>Store the remaining media (2 mL/well) in an incubator or water bath at 37 &#176;C for suspending the calculated amount of collagenase and DNase I (step 1.2.2).</li>
</ol>
3) Isolation of cells
<ol>
	<li>Place the dissected implants/tissue into plates, and dice finely using scissors. Alternatively, utilize a mechanical disruption method using a tissue dissociator or hand-held homogenizer. Owing to the high number of leukocytes, dissect out the spleen to utilize as a staining control in each run. 
	NOTE: As some materials induce higher levels of fibrosis, this protocol is applicable for both highly fibrotic and minimally fibrotic materials. However, each processing method should be evaluated for both cell yield and viability after digestion prior to staining. Avoid peripheral blood contamination during dissection.</li>
	<li>Add collagenase and DNase I (volume calculated in step 1.2.2) to the remaining RPMI (2 mL) that has been warmed to 37 &#176;C. Add 2 mL of the complete enzyme solution to each well.</li>
	<li>Place the plates in an incubated shaker for 45 min at 37 &#176;C and 100 rpm. 
	NOTE: Be cautious when stacking plates as this can inhibit proper heat transfer.</li>
	<li>Meanwhile, prepare a suspension-dispensing tip by chopping 3-4 mm from the end of a 1000 &#181;L tip with scissors. After incubation, pipette the suspension in the wells up and down to mix it thoroughly using the chopped tip. Place the cell strainer on the top of a 50 mL conical tube and pass the digested solution through the cell strainer. 
	NOTE: The 70 &#181;m cell strainer is sufficient to separate cells from implanted biomaterial, such as alginate. If greater purity is required, use processes such as density gradient separation to obtain an enriched population of leukocytes.</li>
	<li>Rinse the wells with 1x PBS solution, and transfer the rinse volume through the strainer, followed by adding the washes of the strainer with 1x PBS solution until the volume in the tube reaches 50 mL. 
	NOTE: The 1x PBS must be at room temperature to prevent any increase in the viscosity of the digest and to allow cell pelleting during centrifugation.</li>
	<li>Centrifuge the tube at 300 &#215; g for 5 min at room temperature. Following centrifugation, aspirate the supernatant carefully using a serological pipette without disturbing the pellet. Re-suspend the pellet in 1000 &#181;L of 1x PBS, and transfer the suspension to a microcentrifuge tube.</li>
	<li>Mix 10 &#181;L of the cell suspension with 10 &#181;L of trypan blue, and load the suspension on counting chamber slides for counting cells using an automatic cell counter or on a hemocytometer to count via the conventional method under a microscope. Alternatively, use flow cytometry cell counting beads.</li>
</ol>
4) Staining for flow cytometry
<ol>
	<li>See Figure 2 for an example plate layout for a 14-color experiment with 45 samples, fluorescence minus one (FMO) controls, compensation controls, and a fully stained spleen sample control. After estimating the total number of cells, calculate the volume of the cell suspension required for staining 1 &#215; 106 cells for each sample, and 0.5 &#215; 106 cells for each compensation and FMO control. Dispense the required volume of the cell suspension into the wells of a V-bottom 96-well plate, and make up the volume to 100 &#181;L with 1x PBS. 
	NOTE: As an example, if 1000 &#181;L of cell suspension obtained at step 3.6 contain 40 &#215; 106 cells, then for 1 &#215; 106 cells, 1000/40 &#215; 106 = 25 &#181;L of cell suspension will be required.</li>
	<li>Centrifuge the plate at 300 &#215; g for 5 min at 4 &#176;C, aspirate the supernatant, and then resuspend the cells in the sample wells and in a compensation control well to determine viability, with 100 &#181;L of a 1:1000 solution of the viability dye (see Table of Materials).</li>
	<li>For cells in the other compensation wells as well as FMO and unstained wells, resuspend them with 100 &#181;L of 1x PBS.</li>
	<li>Incubate the cells in the dark for 30 min at 4 &#176;C.</li>
	<li>In the meantime, prepare a surface antibody cocktail for staining the sample and FMO controls: 50 &#181;L per sample or FMO. See Table 1 for an example of the antibody cocktail.</li>
	<li>After incubation, add 100 &#181;l of 1x PBS to each well, spin down at 300 &#215; g for 5 min at 4 &#176;C.</li>
	<li>Aspirate the supernatant and resuspend in 200 &#181;L of staining buffer (1x PBS + 1% BSA); centrifuge at 300 &#215; g for 5 min at 4 &#176;C.</li>
	<li>Aspirate the supernatant, and resuspend the cells in the compensation, FMO, and unstained wells with 50 &#181;L of 1x PBS. Add 50 &#181;L of the antibody cocktail to the respective sample wells and FMO wells. Add the respective antibodies to the different compensation wells.</li>
	<li>Incubate the plate for 45 min in the dark at 4 &#176;C. After incubation, add 150 &#181;L of staining buffer in each well, and centrifuge the cell suspension at 300 &#215; g for 5 min at 4 &#176;C.</li>
	<li>Aspirate the supernatant, resuspend the cells with 200 &#181;L of staining buffer, and centrifuge the cell suspension at 300 &#215; g for 5 min at 4 &#176;C.</li>
	<li>If analyzing samples without fixation, resuspend them in 200 &#181;L of staining buffer, and proceed to section 6 on cytometer setup and sample analysis. If fixing the cells, aspirate the supernatant after washing, and add 100 &#181;L of a fixative such as 4% paraformaldehyde. If staining for intracellular markers, proceed to section 5 on intracellular staining, and fix and permeabilize the cells (see Table of Materials). Incubate cells for 20 min in the dark at 4 &#176;C. 
	NOTE: As fixation can affect the fluorescence intensity of some fluorophores, evaluate each panel both with and without fixation.</li>
	<li>After incubation, add 100 &#181;L of 1x PBS, followed by centrifugation at 300 &#215; g for 5 min at 4 &#176;C. Aspirate the supernatant, resuspend in 1x PBS, and centrifuge at 300 &#215; g for 5 min at 4 &#176;C.</li>
	<li>Re-suspend the cells in 200 &#181;L of staining buffer, and store at 4 &#176;C prior to flow cytometric analysis.</li>
</ol>
5) Intracellular staining
<ol>
	<li>Continuing from step 4.11 for fixation and permeabilization for intracellular markers, add 100 &#181;L of the appropriate buffer. Centrifuge the cells at 350 &#215; g for 5 min at 4 &#176;C. Aspirate the supernatant, and re-suspend the pellets in 200 &#181;L of the fixative-permeabilizing agent solution; centrifuge the cells at 350 &#215; g for 5 min at 4 &#176;C. Aspirate the supernatant, and resuspend the pellets with intracellular antibodies diluted in the appropriate buffer. 
	NOTE: Antibody types and dilutions will depend on the target cells. For example, one common intracellular marker is forkhead box P3 for regulatory T cells, which is frequently used at a 1:100 dilution.</li>
	<li>Incubate the cell suspension in the dark for 45 min at 4 &#176;C. After incubation, add 150 &#181;L of the appropriate buffer, and centrifuge the suspension at 350 &#215; g for 5 min at 4 &#176;C.</li>
	<li>Aspirate the supernatant, and re-suspend the cells in 200 &#181;L of staining buffer followed by centrifugation at 300 &#215; g for 5 min at 4 &#176;C. Aspirate and re-suspend the cells in 200 &#181;L of staining buffer for flow cytometric analysis.</li>
</ol>
6) Cytometer and compensation setup
<ol>
	<li>Immediately before running the samples, prepare compensation beads (see Table of Materials) if utilizing bead-based compensation as opposed to cell-based compensation.
	<ol>
		<li>Label separate microcentrifuge tubes for each fluorochrome-conjugated antibody, and add 100 &#181;L of 1x PBS followed by one full drop of anti-mouse negative control compensation beads and one drop of positive control compensation beads to each tube. Add 1 &#181;L of the appropriate antibody to each separate tube. Vortex and incubate for 5 min before acquisition. 
		NOTE: As some dyes, such as BUV737, cannot be bound to beads, use a cell-based control.</li>
	</ol>
	</li>
	<li>Calibrate the flow cytometer before each experiment by running the cytometer setup with the tracking beads, and maintain the flow cytometer settings for each experiment.</li>
	<li>Before analyzing the sample, adjust the flow cytometer by running an unstained sample to adjust the cell population on a side scatter (SSC) versus forward scatter (FSC) plot so that the cell population falls in the center of the plot and is not off-scale.</li>
	<li>Run the stained sample briefly to adjust the voltages for FSC and SSC and for each channel to make sure that no events fall outside the logarithmic scale of each channel. Record 5,000 events for each compensation control, followed by gating of positive and negative populations. Calculate the compensation matrix and then run the samples, gathering at least 1,000 events for the populations of interest. 
	NOTE: Compensation on larger-color panels should be verified, as automated compensation can be prone to over- or under-compensation. Each parameter should be graphed against every other parameter to monitor for signs of over- or under-compensation, and each single-color control should be evaluated. Complex compensation of larger-color experiments should be carried out with the assistance of a collaborator or a core facility with extensive flow cytometry experience. Newer types of flow cytometers such as spectral cytometers utilize the full spectrum of a fluorophore through a process known as spectral unmixing, which can yield a cleaner distinction of fluorescent overlap as compared to standard compensation alone22.</li>
</ol>

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The authors have nothing to disclose.

This review describes a detailed methodology for isolating cells from biomaterial implants to obtain a uniform cell suspension. In addition, a detailed protocol has been provided for staining the cell suspension for multicolor flow cytometry, along with the steps for configuring a flow cytometer for optimal results. Cell isolation methods can involve multiple steps, often utilizing manual tissue dissection followed by enzymatic digestion with proteolytic enzymes to dissociate the extracellular matrix in the tissue and di...

Advances in the field of medicine have led to the frequent use of implanted materials for supporting the function or re-growth of damaged tissue1,2. These include devices such as pacemakers, reconstructive cosmetic implants, and orthopedic plates used for bone fracture fixation3,4. However, the materials used to make these implants and the locations in which they are implanted play important roles in determining the success of these implants5,6,7. As foreign bodies, these implants can generate an immune response from the host that can either lead to rejection or tolerance8. This factor has driven biomaterial research to generate materials that can attract the desired immune response after implantation9,10,11,12.
The immune response is an essential requirement in the field of regenerative medicine, where a tissue or an organ is grown around a biomaterial skeleton (scaffold) in a laboratory for the replacement of a damaged tissue or organ13,14,15,16. In regenerative medicine, the goal is to replace missing or damaged tissue through the use of cells, signals, and scaffolds, each of which can be greatly modulated by immune responses17. Furthermore, even when a lack of immune response is desired, it is very rarely an absence of immune activity rather than the presence of a regulatory profile that is desired18. Techniques such as flow cytometry can play a significant role in characterizing the pattern of immune response to various biomaterials used for coating implant devices or for developing scaffolds for tissue engineering19.
This information, in turn, will ultimately help in developing biomaterials for implants that can be well-tolerated by the immune system or in developing scaffolds that can play a constructive role in tissue engineering. Proper preparation of samples for analysis by flow cytometry is an important step for avoiding inaccurate results in immune characterization via fluorescence activated cell sorting20,21. Therefore, this review presents a detailed methodology that can be utilized for the isolation of cells from scaffold tissue, staining the cell suspension, and analysis by flow cytometry.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>50 mL conical tubes</td>
			<td>Fisher Scientific</td>
			<td>14-432-22</td>
			<td></td>
		</tr>
		<tr>
			<td>6 Well Plate</td>
			<td>Fisher Scientific</td>
			<td>07-000-646</td>
			<td></td>
		</tr>
		<tr>
			<td>BD Brilliant Stain Buffer Plus</td>
			<td>BD Biosciences</td>
			<td>566385</td>
			<td></td>
		</tr>
		<tr>
			<td>BD Cytofix</td>
			<td>BD Biosciences</td>
			<td>554655</td>
			<td>For only fixing cells</td>
		</tr>
		<tr>
			<td>Bovine serum albumin</td>
			<td>Millipore Sigma</td>
			<td>A7906</td>
			<td>For preparing FACS staining buffer</td>
		</tr>
		<tr>
			<td>CD11b AF700</td>
			<td>Biolegend</td>
			<td>101222</td>
			<td>Clone: M1/70</td>
		</tr>
		<tr>
			<td>CD11c PerCP/Cy5.5</td>
			<td>Biolegend</td>
			<td>117325</td>
			<td>Clone: N418</td>
		</tr>
		<tr>
			<td>CD197 PE/Dazzle594</td>
			<td>Biolegend</td>
			<td>120121</td>
			<td>Clone: 4B12</td>
		</tr>
		<tr>
			<td>CD200R3 APC</td>
			<td>Biolegend</td>
			<td>142207</td>
			<td>Clone: Ba13</td>
		</tr>
		<tr>
			<td>CD206 PE</td>
			<td>Biolegend</td>
			<td>141705</td>
			<td>Clone: C068C2</td>
		</tr>
		<tr>
			<td>CD45 BUV737</td>
			<td>BD Biosciences</td>
			<td>612778</td>
			<td>Clone: 104/A20</td>
		</tr>
		<tr>
			<td>CD86 BUV395</td>
			<td>BD Biosciences</td>
			<td>564199</td>
			<td>Clone: GL1</td>
		</tr>
		<tr>
			<td>CD8a BV421</td>
			<td>Biolegend</td>
			<td>100737</td>
			<td>Clone: 53-6.7</td>
		</tr>
		<tr>
			<td>Comp Bead anti-mouse</td>
			<td>BD Biosciences</td>
			<td>552843</td>
			<td>For compensation control</td>
		</tr>
		<tr>
			<td>DNase I</td>
			<td>Millipore Sigma</td>
			<td>11284932001</td>
			<td>Bovine pancreatic deoxyribonuclease I (DNase I)</td>
		</tr>
		<tr>
			<td>F4/80 PE/Cy7</td>
			<td>Biolegend</td>
			<td>123113</td>
			<td>Clone: BM8</td>
		</tr>
		<tr>
			<td>Fc Block</td>
			<td>Biolegend</td>
			<td>101301</td>
			<td>Clone: 93</td>
		</tr>
		<tr>
			<td>Fixation/Permeabilization Solution Kit</td>
			<td>BD Biosciences</td>
			<td>554714</td>
			<td>For fixing and permeabilization of cells.</td>
		</tr>
		<tr>
			<td>HEPES buffer</td>
			<td>Thermo Fisher</td>
			<td>15630080</td>
			<td>Buffer to supplement cell media</td>
		</tr>
		<tr>
			<td>Liberase</td>
			<td>Millipore Sigma</td>
			<td>5401127001</td>
			<td>Blend of purified Collagenase I and Collagenase II</td>
		</tr>
		<tr>
			<td>LIVE/DEAD Fixable Blue Dead Cell Stain Kit</td>
			<td>Thermo Fisher</td>
			<td>L23105</td>
			<td>Viability dye</td>
		</tr>
		<tr>
			<td>Ly6c AF488</td>
			<td>Biolegend</td>
			<td>128015</td>
			<td>Clone: HK1.4</td>
		</tr>
		<tr>
			<td>Ly6g BV510</td>
			<td>Biolegend</td>
			<td>127633</td>
			<td>Clone: 1A8</td>
		</tr>
		<tr>
			<td>MHCII BV786</td>
			<td>BD Biosciences</td>
			<td>742894</td>
			<td>Clone: M5/114.15.2</td>
		</tr>
		<tr>
			<td>Phosphate buffer saline</td>
			<td>Thermo Fisher</td>
			<td>D8537</td>
			<td></td>
		</tr>
		<tr>
			<td>RPMI</td>
			<td>Thermo Fisher</td>
			<td>11875176</td>
			<td>Cell culture media</td>
		</tr>
		<tr>
			<td>Siglec F BV605</td>
			<td>BD Biosciences</td>
			<td>740388</td>
			<td>Clone: E50-2440</td>
		</tr>
		<tr>
			<td>V-bottom 96-well plate</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
	</tbody>
</table>

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.

The process of development of flow cytometry panels for immune analysis often relies on the comparison of results to existing data and the literature in the field. Knowledge of how populations may present in flow cytometry is critical for proper interpretation of data. Regardless, populations and cell types can appear differently in different tissues, so some variability is to be expected. In the context of well-defined control tissues, such staining optimization can be evaluated against ...

Watch this Scientific Journal Video about High-Dimensionality Flow Cytometry for Immune Function Analysis of Dissected Implant Tissues at JoVE.com

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

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.

The success of implanting laboratory-grown tissue or a medical device in an individual is subject to the immune response of the recipient host. ...

high-dimensionality-flow-cytometry-for-immune-function-analysis

Research

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Bioengineering

2.1K Views.  National Institutes of Health. 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.

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

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 ...

Mass Cytometry: Protocol for Daily Tuning and Running Cell Samples on a CyTOF Mass Cytometer

In recent years, the rapid analysis of single cells has commonly been performed using flow cytometry and fluorescently-labeled antibodies. However, the issue of spectral overlap of fluorophore emissions has limited the number of simultaneous probes. In contrast, the new CyTOF mass cytometer by DVS Sciences couples a liquid single-cell introduction system to an ICP-MS.1 Rather than fluorophores, chelating polymers containing highly-enriched metal isotopes are coupled to antibodies or other specific probes.2-5 Because of the metal purity and mass resolution of the mass cytometer, there is no "spectral overlap" from neighboring isotopes, and therefore no need for compensation matrices. Additionally, due to the use of lanthanide metals, there is no biological background and therefore no equivalent of autofluorescence. With a mass window spanning atomic mass 103-203, theoretically up to 100 labels could be distinguished simultaneously. Currently, more than 35 channels are available using the chelating reagents available from DVS Sciences, allowing unprecedented dissection of the immunological profile of samples.6-7
Disadvantages to mass cytometry include the strict requirement for a separate metal isotope per probe (no equivalent of forward or side scatter), and the fact that it is a destructive technique (no possibility of sorting recovery). The current configuration of the mass cytometer also has a cell transmission rate of only ~25%, thus requiring a higher input number of cells.
Optimal daily performance of the mass cytometer requires several steps. The basic goal of the optimization is to maximize the measured signal intensity of the desired metal isotopes (M) while minimizing the formation of oxides (M+16) that will decrease the M signal intensity and interfere with any desired signal at M+16. The first step is to warm up the machine so a hot, stable ICP plasma has been established. Second, the settings for current and make-up gas flow rate must be optimized on a daily basis. During sample collection, the maximum cell event rate is limited by detector efficiency and processing speed to 1000 cells/sec. However, depending on the sample quality, a slower cell event rate (300-500 cells/sec) is usually desirable to allow better resolution between cells events and thus maximize intact singlets over doublets and debris. Finally, adequate cleaning of the machine at the end of the day helps minimize background signal due to free metal.

The steps necessary for daily tuning and optimization of the performance of a CyTOF mass cytometer are described. Comments on optimal sample preparation and flow rate are discussed

In recent years, the rapid analysis of single cells has commonly been performed using flow cytometry and fluorescently-labeled antibodies. However, the ...

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 ...

Quantification of Global Diastolic Function by Kinematic Modeling-based Analysis of Transmitral Flow via the Parametrized Diastolic Filling Formalism

Quantitative cardiac function assessment remains a challenge for physiologists and clinicians.&#160;Although historically invasive methods have comprised the only means available, the development of noninvasive imaging modalities (echocardiography, MRI, CT) having high temporal and spatial resolution provide a new window for quantitative diastolic function assessment. Echocardiography is the agreed upon standard for diastolic function assessment, but indexes in current clinical use merely utilize selected features of chamber dimension (M-mode) or blood/tissue motion (Doppler) waveforms without incorporating the physiologic causal determinants of the motion itself.&#160;The recognition that all left ventricles (LV) initiate filling by serving as mechanical suction pumps allows global diastolic function to be assessed based on laws of motion that apply to all chambers. What differentiates one heart from another are the parameters of the equation of motion that governs filling. Accordingly, development of the Parametrized Diastolic Filling (PDF) formalism&#160;has shown that the entire range of clinically observed early transmitral flow (Doppler E-wave) patterns are extremely well fit by the laws of damped oscillatory motion.&#160;This permits analysis of individual E-waves in accordance with a causal mechanism (recoil-initiated suction) that yields three (numerically) unique lumped parameters whose physiologic analogues are chamber stiffness (k), viscoelasticity/relaxation (c), and load (xo).&#160;The recording of transmitral flow (Doppler E-waves) is standard practice in clinical cardiology and, therefore, the echocardiographic recording method is only briefly reviewed. Our focus is on determination of the PDF parameters from routinely recorded E-wave data.&#160;As the highlighted results indicate, once the PDF parameters have been obtained from a suitable number of load varying E-waves, the investigator is free to use the parameters or construct indexes from the parameters (such as stored energy 1/2kxo2, maximum A-V pressure gradient kxo, load independent index of diastolic function, etc.) and select the aspect of physiology or pathophysiology to be quantified.

Accurate, causality-based quantification of global diastolic function has been achieved by kinematic modeling-based analysis of transmitral flow via the Parametrized Diastolic Filling (PDF) formalism. PDF generates unique stiffness, relaxation,&#160;and load parameters and elucidates &#39;new&#39; physiology while providing sensitive and specific indexes of dysfunction.

Quantitative cardiac function assessment remains a challenge for physiologists and clinicians.&#160;Although historically invasive methods have comprised ...

Isolation of Primary Human Colon Tumor Cells from Surgical Tissues and Culturing Them Directly on Soft Elastic Substrates for Traction Cytometry

Cancer cells respond to matrix mechanical stiffness in a complex manner using a coordinated, hierarchical mechano-chemical system composed of adhesion receptors and associated signal transduction membrane proteins, the cytoskeletal architecture, and molecular motors1, 2. Mechanosensitivity of different cancer cells in vitro are investigated primarily with immortalized cell lines or murine derived primary cells, not with primary human cancer cells. Hence, little is known about the mechanosensitivity of primary human colon cancer cells in vitro. Here, an optimized protocol is developed that describes the isolation of primary human colon cells from healthy and cancerous surgical human tissue samples. Isolated colon cells are then successfully cultured on soft (2 kPa stiffness) and stiff (10 kPa stiffness) polyacrylamide hydrogels and rigid polystyrene (~3.6 GPa stiffness) substrates functionalized by an extracellular matrix (fibronectin in this case). Fluorescent microbeads are embedded in soft gels near the cell culture surface, and traction assay is performed to assess cellular contractile stresses using free open access software. In addition, immunofluorescence microscopy on different stiffness substrates provides useful information about primary cell morphology, cytoskeleton organization and vinculin containing focal adhesions as a function of substrate rigidity.

A protocol is described to extract primary human cells from surgical colon tumor and normal tissues. The isolated cells are then cultured on soft elastic substrates (polyacrylamide hydrogels) functionalized by an extracellular matrix protein, and embedded with fluorescent microbeads. Traction cytometry is performed to assess cellular contractile stresses.

Cancer cells respond to matrix mechanical stiffness in a complex manner using a coordinated, hierarchical mechano-chemical system composed of adhesion ...

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.

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 ...

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, ...

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 ...

Spatial Temporal Analysis of Fieldwise Flow in Microvasculature

Changes in blood flow velocity and distribution are vital in maintaining tissue and organ perfusion in response to varying cellular needs. Further, appearance of defects in microcirculation can be a primary indicator in the development of multiple pathologies. Advances in optical imaging have made intravital microscopy (IVM) a practical approach, permitting imaging at the cellular and subcellular level in live animals at high-speed over time. Yet, despite the importance of maintaining adequate tissue perfusion, spatial and temporal variability in capillary flow is seldom documented. In the standard approach, a small number of capillary segments are chosen for imaging over a limited time. To comprehensively quantify capillary flow in an unbiased way we developed Spatial Temporal Analysis of Fieldwise Flow (STAFF), a macro for FIJI open-source&#160;image analysis software. Using high-speed image sequences of full fields of blood flow within capillaries, STAFF produces&#160;images that represent motion over time called kymographs for every time interval for every vascular segment. From the kymographs STAFF calculates velocities from the distance that red blood cells move over time, and outputs the velocity data as a sequence of color-coded spatial maps for visualization and tabular output for quantitative analyses. In normal mouse livers, STAFF analyses quantified profound differences in flow velocity between pericentral and periportal regions within lobules. Even more unexpected are the differences in flow velocity seen between sinusoids&#160;that are side by side and fluctuations seen within individual vascular segments over seconds. STAFF is a powerful new tool capable of providing novel insights by enabling measurement of the complex spatiotemporal dynamics of capillary flow.

To quantify microvascular flow from high speed capillary flow image sequences, we developed STAFF (Spatial Temporal Analysis of Fieldwise Flow) software. Across the full image field and over time, STAFF evaluates flow velocities and generates a sequence of color-coded spatial maps for visualization and tabular output for quantitative analyses.

Changes in blood flow velocity and distribution are vital in maintaining tissue and organ perfusion in response to varying cellular needs. Further, ...

Electric and Magnetic Field Devices for Stimulation of Biological Tissues

Electric fields (EFs) and magnetic fields (MFs) have been widely used by tissue engineering to improve cell dynamics such as proliferation, migration, differentiation, morphology, and molecular synthesis. However, variables such stimuli strength and stimulation times need to be considered when stimulating either cells, tissues or scaffolds. Given that EFs and MFs vary according to cellular response, it remains unclear how to build devices that generate adequate biophysical stimuli to stimulate biological samples. In fact, there is a lack of evidence regarding the calculation and distribution when biophysical stimuli are applied. This protocol is focused on the design and manufacture of devices to generate EFs and MFs and implementation of a computational methodology to predict biophysical stimuli distribution inside and outside of biological samples. The EF device was composed of two parallel stainless-steel electrodes located at the top and bottom of biological cultures. Electrodes were connected to an oscillator to generate voltages (50, 100, 150 and 200 Vp-p) at 60 kHz. The MF device was composed of a coil, which was energized with a transformer to generate a current (1 A) and voltage (6 V) at 60 Hz. A polymethyl methacrylate support was built to locate the biological cultures in the middle of the coil. The computational simulation elucidated the homogeneous distribution of EFs and MFs inside and outside of biological tissues. This computational model is a promising tool that can modify parameters such as voltages, frequencies, tissue morphologies, well plate types, electrodes and coil size to estimate the EFs and MFs to achieve a cellular response.

This protocol describes the step-by-step process to build both electrical and magnetic stimulators used to stimulate biological tissues. The protocol includes a guideline to simulate computationally electric and magnetic fields and manufacture of stimulator devices.

Electric fields (EFs) and magnetic fields (MFs) have been widely used by tissue engineering to improve cell dynamics such as proliferation, migration, ...