Name: A Combinatorial Single-cell Approach to Characterize the Molecular and Immunophenotypic Heterogeneity of Human Stem and Progenitor Populations (Video) | JoVE Journal
Uploaded: 2018-10-25T12:30:00.000+00:00
Duration: 9 min 34 s
Description: Learn a combinatorial single-cell approach to characterize molecular and immunophenotypic heterogeneity in human stem and progenitor populations using FACS and gene expression analysis. This method reveals cellular diversity.

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5 minutes

This work is supported by grants from the Swedish Cancer Society, The Swedish Research Council, The Swedish Society for Medical Research, The Swedish Childhood Cancer Foundation, The Ragnar S&#246;derberg Foundation, and The Knut and Alice Wallenberg Foundation

1. Preparation of Lysis Plates
<ol>
	<li>Using a RNA/DNA free bench, prepare enough lysis buffer for 96 wells, with 10% extra, by mixing 390 &#181;L nuclease free water, 17 &#181;L of 10% NP-40, 2.8 &#181;L 10 mM dNTP, 10 &#181;L 0.1 M DTT and 5.3 &#181;L RNAse inhibitor (see Table of Materials). Vortex and spin down.</li>
	<li>Distribute 4 &#181;L of lysis buffer to each well of a 96 well PCR plate and seal the plates with adhesive film. Spin down tubes to collect liquid at the bottom of the plates. Keep plates on ice until cell sorting (maximum 24 h).</li>
</ol>
2. Preparation of Cells for Cell Sorting
<ol>
	<li>Thaw appropriate number of cells (here, CD34 enriched hematopoietic stem and progenitor cells) for the experiment. 1 x 106 cells are appropriate for sorting approximately three 96-well plates of single-cells with controls.</li>
	<li>Transfer thawed cells to a 15 mL conical tube and add 1 mL FBS every 30 s until a total volume of 8 mL is reached. Spin cells in a centrifuge at 350 x g for 10 min at 4 &#176;C and remove supernatant.</li>
	<li>Resuspend cells in 8 mL staining buffer (PBS with 2% FBS) and centrifuge at 350 x g for 10 min at 4 &#176;C and remove supernatant.</li>
	<li>Resuspend cells in 200 &#181;L staining buffer and remove cells for control stains.</li>
	<li>Make Fluorescence minus one controls (FMOs) for each fluorophore, by staining a fraction of cells in 50 &#181;L staining buffer. In this example, 6 microcentrifuge tubes with 20,000 cells are used as FMOSs. Note that the number of cells should be adjusted depending on the population investigated. Add all antibodies at the same concentration as in the sample stain except for one to each tube.</li>
	<li>Make single stains for each fluorophore by staining a fraction of cells in 50 &#181;L buffer for each fluorophore used. In this example 6 microcentrifuge tubes with 20,000 cells are used. Note that the target for each antibody needs to be expressed by the cells used for controls. Add each antibody at the same concentration as in the sample stain in individual tubes. Additionally keep 20,000 unstained cells in 50 &#181;L as an unstained control.</li>
	<li>To the cell sample, add antibodies at their appropriate concentration. Used here are CD34-FITC at a 1/100 concentration, CD38-APC 1/50, CD90-PE 1/10, CD45RA-bv421 1/50, CD49F-PECy7 1/50 and Lineage Mix: CD3-PECy5 1/50, CD2-PECy5 1/50, CD19-PECy5 1/50, CD56-PECy5 1/50, CD123-PECy5 1/50, CD14-PECy5 1/50, CD16-PECy5 1/50, and CD235a-PECy5 1/1000.</li>
	<li>Incubate cells with antibodies for 30 min on ice in the dark.</li>
	<li>Wash cells with 3 mL staining buffer. Centrifuge cells at 350 x g for 10 min at 4 &#176;C and remove supernatant.</li>
	<li>Resuspend cells and repeat step 2.9.</li>
	<li>Resuspend sample in 500 &#181;L and FMOs in 100 &#181;L staining buffer with 1/100 7AAD and filter cells through a 50 &#181;m filter to get a single-cell suspension.</li>
</ol>
3. Cell Sorting
<ol>
	<li>Make sure that the FACS machine is set up correctly with drop delay and cytometer setup and tracking (CST) that have recently been performed according to manufacturer&#39;s instructions, to ensure that the appropriate cells are sorted. For hematopoietic cells, the use of the 85 micron nozzle and maximum speed of 4 is recommended, while the optimal event rate is between 800 and 2000 events/s.</li>
	<li>Correct for spectral overlap by performing fluorescence compensation and set gates according to FMO controls or internal negative controls.</li>
	<li>Perform reanalysis of the target population by sorting at least 100 target cells into a new microcentrifuge tube with 100 &#181;L of stain buffer. FACS analyze the sorted cells by recording the sorted sample and make sure that they end up in the sort gate.</li>
	<li>Set-up single cell plate sorting by centering the drop in well A1 in a 96 well plate. When it is centered, sort 50&#8211;100 6 &#181;m particles into all wells around the edge of an empty 96 well plate to ensure that all wells will get a cell in the center of each well.</li>
	<li>If possible, an additional control to ensure that viable cells are sorted can be added by sorting single-cells for in vitro growth. Haematopoietic cells can be grown in U-bottom 96 well plates in 100 &#181;l SFEM with 1% penicillin streptomycin, 100 ng/mL FLT3L, TPO and SCF. Analyze each well after 3 days in culture for cell colonies using a microscope.</li>
	<li>Remove adhesive film from plates. Sort a single cell of interest (here Lin-CD34+CD38- cells) into 92 out of the 96 wells, activate INDEX-sorting in the FACS sorting software to save the immunophenotypic profile for other markers of interest (here CD45RA, CD49f, and CD90) for each single cell.</li>
	<li>Sort two wells with 10 and 20 cells respectively for linearity controls in the PCR amplification. Wells H1 and H2 are usually used.</li>
	<li>Keep two wells without any cells as no-template controls, usually wells H3 and H4.</li>
	<li>Seal the plates with clear adhesive film and spin the plates at 300 x g for 1 min before snap freezing on dry ice.</li>
	<li>Store frozen plates at -80 &#176;C. 
	NOTE: Safe stopping point. Sorted and lysed cells can be kept at -80 &#176;C for long-term storage.</li>
</ol>
4. Reverse Transcription and Specific Target Amplification
<ol>
	<li>Prepare the primer mix for all 96 gene targets by adding 2 &#181;L of each primer pair, including housekeeping gene primers and primers for spiked-in control RNA, in a 1.5 mL RNAse free tube on a RNA/DNA free bench. If using less than 96 primers, add an equivalent volume of nuclease free water for the missing primers. Primers are ordered separately to match the desired gene panel.</li>
	<li>Make reverse transcription and specific target amplification mix by adding 632.5 &#181;L 2x reaction mix, 101.2 &#181;L Taq/SuperscriptIII, 151.8 &#181;L Primer mix, and 0.7 &#181;L spiked in control RNA. Preform this step on a DNA free bench. Mix by vortexing and spin down to collect the liquid in the bottom of the tube. Keep on ice until addition to the sample.</li>
	<li>Make no-reverse transcription control mix for four wells by mixing 27.5 &#181;L of 2x reaction mix, 1.76 &#181;L of Taq enzyme, 6.6 &#181;L of primer mix and 2.64 &#181;L of nuclease free water. Spike in control RNA. Perform this step on a DNA free bench. Vortex and spin down to collect the liquid in the bottom of the tube and keep on ice until addition to sample.</li>
	<li>Thaw lysate plates on ice. Add 8.75 &#181;L of the previously prepared reverse transcription and specific target amplification mix to 92 wells, including the linearity and no-template controls. Add 8.75 &#181;L of no-reverse transcription control mix to the four remaining wells. Seal plates with clear adhesive film and spin down to collect liquid at the bottom of the plates.</li>
	<li>Preform reverse transcription and specific target amplification by running the plate in a PCR machine according to the preamp program; step 1: 50 &#176;C for 60 min, step 2: 95 &#176;C for 2 min, step 3: 95 &#176;C for 15 s, step 4: 60 &#176;C for 4 min, repeat steps 3&#8211;4 24 times and finally step 5: 8 &#176;C forever.</li>
	<li>After PCR is complete, keep the plate at 8 &#176;C for short term storage and -20 &#176;C for long term storage. 
	NOTE: Safe stopping point. Amplified material can be kept at 8 &#176;C for short-term storage and at -20 &#176;C for long-term storage.</li>
</ol>
5. Preparation of Sample and Assay Plates for Multiplex Microfluidic Gene Expression Analysis
<ol>
	<li>Prepare assay loading plate by pipetting 3 &#181;L Assay loading reagent to each well of a 96 well plate. Add 3 &#181;L of each primer to individual wells in the assay loading plate.</li>
	<li>Seal plate with adhesive film and spin down to collect liquid at the bottom of the plates.</li>
	<li>Prepare dilution plate by pipetting 8 &#181;L of nuclease free water into all wells of a 96 well plate. Add 2 &#181;L of amplified sample to the dilution plate, making a final dilution of 1:5.</li>
	<li>Seal plate with adhesive film, mix by vortexing plate for 10 s, and finally spin down to collect liquid at the bottom of the plates.</li>
	<li>Prepare sample loading mix by carefully mixing 352 &#181;L of master mix with 35.2 &#181;L of sample loading reagent. Prepare sample loading plate by aliquoting 3.3 &#181;L of loading mix to each well of a 96 well plate.</li>
	<li>Add 2.7 &#181;L from the diluted sample into each well of the sample loading plate.</li>
	<li>Seal plate with adhesive film and spin down to collect liquid at the bottom of the plates.</li>
</ol>
6. Loading of Microfluidic Chip
<ol>
	<li>Take out a new 96 x 96 microfluidic chip. Prepare inlets by poking them with a syringe with cap on to make sure that they can be moved.</li>
	<li>Remove bubbles from syringes. Add full volume of syringes to each valve while tilting the chip 45 degrees and pressing down the valve. Prime chip with the IFC controller.</li>
	<li>Load each assay inlet with 4.25 &#181;L from each of the wells in the assay loading plate. Avoid bubbles. If bubbles appear in the well, remove them with a pipette tip.</li>
	<li>Continue loading each sample inlet with 4.25 &#181;L from each of the wells in the sample loading plate, avoid bubbles, and if bubbles appear, remove them with pipette tip.</li>
	<li>Load chip with the IFC controller.</li>
	<li>Check that the chip looks even and that all chambers have been loaded. Remove dust from the chip surface by touching it with tape. Run the chip in the multiplex microfluidic gene expression platform.</li>
</ol>
7. Running Chip on Multiplex Microfluidic Gene Expression Platform
<ol>
	<li>After loading chip into the multiplex microfluidic gene expression platform, name the sample.</li>
	<li>Set ROX as passive dye. Set single probe and FAM-MGB as fluorescence. Use 96 x 96 standard v2 as protocol. Start run.</li>
	<li>Remove chip when run is complete.</li>
</ol>
8. Preliminary Analysis of Chip Run
<ol>
	<li>Load data into Real-Time PCR analysis software.</li>
	<li>Load gene names and cell names by pasting cell and gene layouts from a tab delimited file.</li>
	<li>Open image view and select ROX as dye. Check if all wells have ROX passive dye.</li>
	<li>Investigate if all amplification plots look ok, with a smooth amplification curve with no spikes (similar to Figure 3E).</li>
	<li>Ensure that all single-cells have expression of spiked-in control RNA to make sure that all have been loaded properly.</li>
	<li>Ensure that all cells have housekeeping gene expression and thus have been sorted properly.</li>
	<li>Ensure that 10 and 20 cell linearity controls have approximately 1 CT difference to validate linear amplification.</li>
	<li>Check if there is expression in the noRT control samples. If expression is detected in noRT consider changing probes to probes which do not detect genomic DNA for subsequent runs.</li>
	<li>Export data in csv files for further analysis.</li>
</ol>
9. Single-cell Analysis Using SCExV
NOTE: An introductory film is present20 to introduce the tool. Here, a short recommendation of how to do analysis using the controls introduced in the protocol is presented.
<ol>
	<li>Connect to the SCexV website20.</li>
	<li>Upload exported CSV files.</li>
	<li>Chose the spiked-in control RNA as positive control. Remove any cell which has a control RNA CT above 25. Normalize the data to median expression of control RNA.</li>
	<li>Click &#34;Done here -&#62; Analyze&#34;. Remove noRT, notemplate, 10 and 20 cell controls in the exclude cell option.</li>
	<li>Cluster cells with the clustering approach of choice with the expected number of clusters. Export analyzed values.</li>
</ol>
10. Index-sorting Analysis
<ol>
	<li>Open FACS analysis software and load the indexed samples.</li>
	<li>Open the script editor and run the script available from Quinn J. et al.21</li>
	<li>Now that the FACS analysis software should have made a gate for each of the single cells, open layout editor and color the cells according to the grouping from SCexV (available in the file named &#34;Sample_complete_Data.xls&#34;).</li>
</ol>

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<li>Bengtsson, M., Ståhlberg, A., Rorsman, P., Kubista, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Gene+expression+profiling+in+single+cells+from+the+pancreatic+islets+of+Langerhans+reveals+lognormal+distribution+of+mRNA+levels%5BTitle%5D)+AND+%22Genome+Research%22%5BJournal%5D)">Gene expression profiling in single cells from the pancreatic islets of Langerhans reveals lognormal distribution of mRNA levels.</a> Genome Research. 15 (10), 1388-1392 (2005).</li>
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<li>Hayashi, T., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Single-cell+gene+profiling+of+planarian+stem+cells+using+fluorescent+activated+cell+sorting+and+its+%26%2334%3Bindex+sorting%26%2334%3B+function+for+stem+cell+research%5BTitle%5D)+AND+%22Development%2C+Growth%2C+%26+Differentiation%22%5BJournal%5D)">Single-cell gene profiling of planarian stem cells using fluorescent activated cell sorting and its &#34;index sorting&#34; function for stem cell research.</a> Development, Growth, & Differentiation. 52 (1), 131-144 (2010).</li>
<li>Lang, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((SCExV%3A+A+webtool+for+the+analysis+and+visualisation+of+single+cell+qRT-PCR+data%5BTitle%5D)+AND+%22BMC+Bioinformatics%22%5BJournal%5D)">SCExV: A webtool for the analysis and visualisation of single cell qRT-PCR data.</a> BMC Bioinformatics. 16 (1), 320(2015).</li>
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<li>Schulte, R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Index+sorting+resolves+heterogeneous+murine+hematopoietic+stem+cell+populations%5BTitle%5D)+AND+%22Experimental+Hematology%22%5BJournal%5D)">Index sorting resolves heterogeneous murine hematopoietic stem cell populations.</a> Experimental Hematology. 43 (9), 803-811 (2015).</li>
</ol>

The authors have nothing to disclose.

In recent years, single-cell gene expression analysis has become a valuable addition to define the heterogeneity of various cell populations23. The advent of RNA sequencing technologies theoretically provides a possibility to measure the entire transcriptome of a cell, however these methods are complicated by variations in cell-to-cell sequencing depths and drop-outs. Single-cell qPCR offers a sensitive and robust analysis of the expression of hundreds of critical genes where all cells are treated...

Each individual blood cell is believed to reside in a cellular hierarchy, where stem cells form the apex on top of a series of increasingly committed intermediate progenitors that eventually terminally differentiate into the final effector cells carrying specific biological functions1. Much of the knowledge about how stem cell systems are organized has been generated in the hematopoietic system, largely because of the ability to prospectively isolate distinct hematopoietic populations highly enriched for stem cells or various progenitors2 by FACS sorting. This has allowed for many of these populations to be analyzed functionally or molecularly, predominantly through gene expression profiling3,4. However when analyzing gene expression of bulk populations individual differences between cells are averaged out and lost5. Thus, incapacity to detect cell-to-cell variations within heterogeneous cell fractions may confound our understanding of critical biological processes if small subsets of cells account for the inferred biological function of that population6,7. Conversely, investigation of gene expression signatures at single-cell resolution offer a possibility to delineate heterogeneity and circumvent overshadowing influences from overrepresented subsets of cells8.
To date many protocols for single-cell gene expression analysis have been developed; with each approach having its own caveats. The earliest method was RNA Fluorescent in situ hybridization (RNA-FISH), which measures a limited number of transcripts at a time but is unique in that it allows for investigation of RNA localization9,11. Early methods using PCR and qPCR to detect a single or very few transcripts were also developed12. However, these have lately been replaced by microfluidics-based methods which can simultaneously analyze the expression of hundreds of transcripts per cell in hundreds of cells through qPCR and thus allow for high-dimensional heterogeneity analysis using pre-determined gene panels10,13. Recently RNA sequencing-based technologies have become widely used for single cell analysis, as these theoretically can measure the entire transcriptome of a cell and thereby add an exploratory dimension to heterogeneity analysis10,14. Multiplexed qPCR analysis and single-cell RNA sequencing have different features, thus the rationale for using either of the methods depends on the question asked as well as the number of cells in the target population. The high-throughput and low cost per cell together with unbiased, exploratory characteristics of single-cell RNA sequencing are desirable when unknown cell or large populations are investigated. However, single-cell RNA sequencing is also biased towards sequencing high abundant transcripts more frequently while transcripts with low abundance are prone to dropouts. This can lead to considerably complex data that puts high-demands on bioinformatic analysis to reveal important molecular signals that are often subtle or hidden in technical noise15. Thus, for well-characterized tissues, single-cell qPCR analysis using pre-determined primer panels selected for functionally important genes or molecular markers can serve as a sensitive, straightforward approach to determine the heterogeneity of a population. However, it should be noted that compared to single-cell RNA-seq, the cost per cell is generally higher for single-cell qPCR methods. Here, we describe an approach that combines single-cell RT-qPCR (modified from Teles J. et al.16), to FACS index sorting17 and bioinformatics analysis18 in order to simultaneously characterize the molecular and immunophenotypic heterogeneity within populations.
In this approach, the cell population of interest is stained, and single-cells are sorted by FACS directly into lysis buffer in 96-well PCR plates. Simultaneously, the expression levels of an additional set of cell-surface markers are recorded for each single cell during FACS-sorting, a method that is referred to as index-sorting. The lysed cell material is subsequently amplified and the gene expression of a selected set of genes analyzed with RT-qPCR, using a microfluidic platform. This strategy enables molecular analysis of the sorted single-cell as well as simultaneous characterization of each individual cell&#39;s cell-surface marker expression. By directly mapping molecularly distinct subsets of cells to the expression of the indexed sorted markers, the subpopulations can be linked to a specific immunophenotype that can be used for their prospective isolation. The method is outlined step by step in Figure 1. A pre-determined gene panel further contributes to a higher resolution of the targeted gene expression, since it circumvents measurement of irrelevant abundant genes that can otherwise occlude subtle gene expression signals. Moreover, the specific target amplification, one step reverse transcription, and amplification allows for robust measurement of low expressed transcripts, like transcription factors or non-poly-adenylated RNAs. Importantly, qPCR methods allow for measurement of mRNA from fusion proteins, which are important when investigating certain malignant diseases19. Finally, the focused number of genes investigated, low drop-out rates, and limited technical differences between cells make this method easily analyzed compared to higher dimensional methods, such as single-cell RNA-seq. By following the protocol, an entire experiment can be performed, from sorting cells to analyzed results, within three days, making this an uncomplicated and quick method for sensitive, high-throughput single-cell gene expression analysis.

<table><tbody><tr><td>CD14 PECY5</td><td>eBioscience</td><td>15-0149-42</td><td>Clone: 61D3</td></tr><tr><td>CD16 PECY5</td><td>Biolegend</td><td>302010</td><td>Clone: 3G8</td></tr><tr><td>CD56 PECY5</td><td>Biolegend</td><td>304608</td><td>Clone: MEM-188</td></tr><tr><td>CD19 PECY5</td><td>Biolegend</td><td>302210</td><td>Clone: HIB19</td></tr><tr><td>CD2 PECY5</td><td>Biolegend</td><td>300210</td><td>Clone: RPA-2.10</td></tr><tr><td>CD3 PECY5</td><td>Biolegend</td><td>300310</td><td>Clone: HIT3a</td></tr><tr><td>CD123 PECY5</td><td>Biolegend</td><td>306008</td><td>Clone: 6H6</td></tr><tr><td>CD235A PECY5</td><td>BD Pharma</td><td>559944</td><td>Clone GAR2</td></tr><tr><td>CD34 FITC</td><td>Biolegend</td><td>343604</td><td>Clone: 561</td></tr><tr><td>CD38 APC</td><td>Biolegend</td><td>303510</td><td>Clone: Hit2</td></tr><tr><td>CD90 PE</td><td>Biolegend</td><td>328110</td><td>Clone: 5E10</td></tr><tr><td>CD45RA BV421</td><td>BD bioscience</td><td>560362</td><td>Clone: HI100</td></tr><tr><td>CD49f Pecy7</td><td>eBioscience</td><td>25-0495-82</td><td>Clone: eBioGOH3</td></tr><tr><td>FBS</td><td>HyClone</td><td>SV30160.3</td><td></td></tr><tr><td>PBS</td><td>HyClone</td><td>SH30028.02</td><td></td></tr><tr><td>96-well u-bottom Plate</td><td>VWR</td><td>10861-564</td><td></td></tr><tr><td>SFEM</td><td>Stem cell technologies</td><td>9650</td><td></td></tr><tr><td>Penicillin streptomycin</td><td>HyClone</td><td>SV30010</td><td></td></tr><tr><td>TPO</td><td>Peprotech</td><td>300-18</td><td></td></tr><tr><td>SCF</td><td>Peprotech</td><td>300-07</td><td></td></tr><tr><td>FLT3L</td><td>Peprotech</td><td>300-19</td><td></td></tr><tr><td>Falcon Tube 15 mL</td><td>Sarstedt</td><td>62.554.502</td><td></td></tr><tr><td>Eppendorph tube</td><td>Sarstedt</td><td>72.690.001</td><td></td></tr><tr><td>CST beads</td><td>BD</td><td>642412</td><td></td></tr><tr><td>Accudrop Beads</td><td>BD</td><td>345249</td><td>6 &amp;micro;m particles&amp;nbsp;</td></tr><tr><td>Adhesive film Clear</td><td>Thermo scientific&amp;nbsp;</td><td>AB-1170</td><td></td></tr><tr><td>Adhesive film Foil</td><td>Thermo scientific&amp;nbsp;</td><td>AB-0626</td><td></td></tr><tr><td>96 well PCR plate</td><td>Axygen</td><td>PCR-96M2-HS-C</td><td></td></tr><tr><td>PCR 1.5 mL tube</td><td>Axygen</td><td>MCT-150-L-C</td><td></td></tr><tr><td>T100 PCR cycler</td><td>BioRad</td><td>186-1096</td><td></td></tr><tr><td>10% NP40</td><td>Thermo scientific&amp;nbsp;</td><td>85124</td><td></td></tr><tr><td>10 mM dNTP</td><td>Takara</td><td>4030</td><td></td></tr><tr><td>0.1 M DTT</td><td>Invitrogen</td><td>P2325</td><td></td></tr><tr><td>RNAsout</td><td>Invitrogen</td><td>10777-019</td><td>RNAse inhibitor</td></tr><tr><td>CellsDirect One-Step qRT-PCR Kit</td><td>Invitrogen</td><td>11753-100</td><td></td></tr><tr><td>Neuclease free water</td><td>Invitrogen</td><td>11753-100</td><td>from CellsDirect kit</td></tr><tr><td>2x Reaction Mix</td><td>Invitrogen</td><td>11753-100</td><td>from CellsDirect kit</td></tr><tr><td>SuperScript III RT/Platinum Taq Mix</td><td>Invitrogen</td><td>11753-100</td><td>from CellsDirect kit</td></tr><tr><td>Platinum&amp;nbsp;Taq&amp;nbsp;DNA Polymerase</td><td>Invitrogen</td><td>10966026</td><td></td></tr><tr><td>TaqMan Cells-to-CT Control Kit</td><td>Invitrogen</td><td>4386995</td><td></td></tr><tr><td>Xeno RNA Control</td><td>Invitrogen</td><td>4386995</td><td>From TaqMan Cells-to-CT Control Kit</td></tr><tr><td>20x Xeno RNA Control Taqman Gene Expression Assay</td><td>Invitrogen</td><td>4386995</td><td>From TaqMan Cells-to-CT Control Kit</td></tr><tr><td>96.96 Sample/Loading Kit&amp;mdash;10 IFCs</td><td>Fluidigm</td><td>BMK-M10-96.96</td><td></td></tr><tr><td>2x Assay Loading Reagent</td><td>Fluidigm</td><td></td><td>From 96.96 Sample/Loading Kit</td></tr><tr><td>20x GE Sample Loading Reagent</td><td>Fluidigm</td><td></td><td>From 96.96 Sample/Loading Kit</td></tr><tr><td>Control line fluid&amp;nbsp;</td><td>Fluidigm</td><td></td><td>From 96.96 Sample/Loading Kit</td></tr><tr><td>TaqMan Gene Expression Master Mix</td><td>Applied Biosystems</td><td>4369016</td><td></td></tr><tr><td>BioMark HD</td><td>Fluidigm</td><td>BMKHD-BMKHD</td><td></td></tr><tr><td>96.96 Dynamic Array IFC</td><td>Fluidigm</td><td>BMK-M10-96.96GT</td><td></td></tr><tr><td>Excel</td><td>Microsoft</td><td>Microsoft</td><td></td></tr><tr><td>FlowJo V10</td><td>TreeStar</td><td>TreeStar</td><td></td></tr><tr><td>Fluidigm real time PCR analysis</td><td>Fluidigm</td><td>Fluidigm</td><td></td></tr><tr><td>CD179a.VPREB1</td><td>Thermofisher scientific</td><td>Hs00356766_g1</td><td></td></tr><tr><td>ACE</td><td>Thermofisher scientific</td><td>Hs00174179_m1</td><td></td></tr><tr><td>AHR</td><td>Thermofisher scientific</td><td>Hs00169233_m1</td><td></td></tr><tr><td>BCR_ABL.52</td><td>Thermofisher scientific</td><td>Hs03043652_ft</td><td></td></tr><tr><td>BCR_ABL41</td><td>Thermofisher scientific</td><td>Hs03024541_ft</td><td></td></tr><tr><td>BMI1</td><td>Thermofisher scientific</td><td>Hs00995536_m1</td><td></td></tr><tr><td>CCNA2</td><td>Thermofisher scientific</td><td>Hs00996788_m1</td><td></td></tr><tr><td>CCNB1</td><td>Thermofisher scientific</td><td>Hs01030099_m1</td><td></td></tr><tr><td>CCNB2</td><td>Thermofisher scientific</td><td>Hs01084593_g1</td><td></td></tr><tr><td>CCNC</td><td>Thermofisher scientific</td><td>Hs01029304_m1</td><td></td></tr><tr><td>CCNE1</td><td>Thermofisher scientific</td><td>Hs01026535_g1</td><td></td></tr><tr><td>CCNF</td><td>Thermofisher scientific</td><td>Hs00171049_m1</td><td></td></tr><tr><td>CCR9</td><td>Thermofisher scientific</td><td>Hs01890924_s1</td><td></td></tr><tr><td>CD10.MME</td><td>Thermofisher scientific</td><td>Hs00153510_m1</td><td></td></tr><tr><td>CD11a</td><td>Thermofisher scientific</td><td>Hs00158218_m1</td><td></td></tr><tr><td>CD11c.ITAX</td><td>Thermofisher scientific</td><td>Hs00174217_m1</td><td></td></tr><tr><td>CD123.IL3RA</td><td>Thermofisher scientific</td><td>Hs00608141_m1</td><td></td></tr><tr><td>CD133.PROM1</td><td>Thermofisher scientific</td><td>Hs01009250_m1</td><td></td></tr><tr><td>CD151</td><td>Thermofisher scientific</td><td>Hs00911635_g1</td><td></td></tr><tr><td>CD220.INSR</td><td>Thermofisher scientific</td><td>Hs00961554_m1</td><td></td></tr><tr><td>CD24.HSA</td><td>Thermofisher scientific</td><td>Hs03044178_g1</td><td></td></tr><tr><td>NCOR1</td><td>Thermofisher scientific</td><td>Hs01094540_m1</td><td></td></tr><tr><td>CD26.DPP4</td><td>Thermofisher scientific</td><td>Hs00175210_m1</td><td></td></tr><tr><td>CD274</td><td>Thermofisher scientific</td><td>Hs01125301_m1</td><td></td></tr><tr><td>CD276</td><td>Thermofisher scientific</td><td>Hs00987207_m1</td><td></td></tr><tr><td>CD32.FCGR2B</td><td>Thermofisher scientific</td><td>Hs01634996_s1</td><td></td></tr><tr><td>CD33</td><td>Thermofisher scientific</td><td>Hs01076281_m1</td><td></td></tr><tr><td>CD34</td><td>Thermofisher scientific</td><td>Hs00990732_m1</td><td></td></tr><tr><td>CD344.FZD4</td><td>Thermofisher scientific</td><td>Hs00201853_m1</td><td></td></tr><tr><td>CD352.SLAMF6</td><td>Thermofisher scientific</td><td>Hs01559920_m1</td><td></td></tr><tr><td>CD38</td><td>Thermofisher scientific</td><td>Hs01120071_m1</td><td></td></tr><tr><td>CD4</td><td>Thermofisher scientific</td><td>Hs01058407_m1</td><td></td></tr><tr><td>CD41.ITGA2B</td><td>Thermofisher scientific</td><td>Hs01116228_m1</td><td></td></tr><tr><td>CD49f.ITGA6</td><td>Thermofisher scientific</td><td>Hs01041011_m1</td><td></td></tr><tr><td>CD56.NCAM1</td><td>Thermofisher scientific</td><td>Hs00941830_m1</td><td></td></tr><tr><td>CD9</td><td>Thermofisher scientific</td><td>Hs00233521_m1</td><td></td></tr><tr><td>CD97</td><td>Thermofisher scientific</td><td>Hs00173542_m1</td><td></td></tr><tr><td>CD99</td><td>Thermofisher scientific</td><td>Hs00908458_m1</td><td></td></tr><tr><td>CDK6</td><td>Thermofisher scientific</td><td>Hs01026371_m1</td><td></td></tr><tr><td>CDKN1A</td><td>Thermofisher scientific</td><td>Hs00355782_m1</td><td></td></tr><tr><td>CDKN1B</td><td>Thermofisher scientific</td><td>Hs01597588_m1</td><td></td></tr><tr><td>CDKN1C</td><td>Thermofisher scientific</td><td>Hs00175938_m1</td><td></td></tr><tr><td>CEBPa</td><td>Thermofisher scientific</td><td>Hs00269972_s1</td><td></td></tr><tr><td>CSF1r</td><td>Thermofisher scientific</td><td>Hs00911250_m1</td><td></td></tr><tr><td>CSF2RA</td><td>Thermofisher scientific</td><td>Hs00531296_g1</td><td></td></tr><tr><td>CSF3RA</td><td>Thermofisher scientific</td><td>Hs01114427_m1</td><td></td></tr><tr><td>E2A.TCF3</td><td>Thermofisher scientific</td><td>Hs00413032_m1</td><td></td></tr><tr><td>EBF1</td><td>Thermofisher scientific</td><td>Hs01092694_m1</td><td></td></tr><tr><td>ENG</td><td>Thermofisher scientific</td><td>Hs00923996_m1</td><td></td></tr><tr><td>EPOR</td><td>Thermofisher scientific</td><td>Hs00959427_m1</td><td></td></tr><tr><td>ERG</td><td>Thermofisher scientific</td><td>Hs01554629_m1</td><td></td></tr><tr><td>FLI1</td><td>Thermofisher scientific</td><td>Hs00956711_m1</td><td></td></tr><tr><td>FLT3</td><td>Thermofisher scientific</td><td>Hs00174690_m1</td><td></td></tr><tr><td>FOXO1</td><td>Thermofisher scientific</td><td>Hs01054576_m1</td><td></td></tr><tr><td>GAPDH</td><td>Thermofisher scientific</td><td>Hs02758991_g1</td><td></td></tr><tr><td>GATA1</td><td>Thermofisher scientific</td><td>Hs00231112_m1</td><td></td></tr><tr><td>GATA2</td><td>Thermofisher scientific</td><td>Hs00231119_m1</td><td></td></tr><tr><td>GATA3</td><td>Thermofisher scientific</td><td>Hs00231122_m1</td><td></td></tr><tr><td>GFI1</td><td>Thermofisher scientific</td><td>Hs00382207_m1</td><td></td></tr><tr><td>HES1</td><td>Thermofisher scientific</td><td>Hs01118947_g1</td><td></td></tr><tr><td>HLF</td><td>Thermofisher scientific</td><td>Hs00171406_m1</td><td></td></tr><tr><td>HMGA2</td><td>Thermofisher scientific</td><td>Hs00171569_m1</td><td></td></tr><tr><td>HOXA5</td><td>Thermofisher scientific</td><td>Hs00430330_m1</td><td></td></tr><tr><td>HOXB4</td><td>Thermofisher scientific</td><td>Hs00256884_m1</td><td></td></tr><tr><td>ID2</td><td>Thermofisher scientific</td><td>Hs04187239_m1</td><td></td></tr><tr><td>IGF2BP1</td><td>Thermofisher scientific</td><td>Hs00198023_m1</td><td></td></tr><tr><td>IGF2BP2</td><td>Thermofisher scientific</td><td>Hs01118009_m1</td><td></td></tr><tr><td>IKZF1</td><td>Thermofisher scientific</td><td>Hs00172991_m1</td><td></td></tr><tr><td>IL1RAP</td><td>Thermofisher scientific</td><td>Hs00895050_m1</td><td></td></tr><tr><td>IL2RG</td><td>Thermofisher scientific</td><td>Hs00953624_m1</td><td></td></tr><tr><td>IRF8</td><td>Thermofisher scientific</td><td>Hs00175238_m1</td><td></td></tr><tr><td>ITGB7</td><td>Thermofisher scientific</td><td>Hs01565750_m1</td><td></td></tr><tr><td>KIT</td><td>Thermofisher scientific</td><td>Hs00174029_m1</td><td></td></tr><tr><td>Lin28B</td><td>Thermofisher scientific</td><td>Hs01013729_m1</td><td></td></tr><tr><td>LMO2</td><td>Thermofisher scientific</td><td>Hs00153473_m1</td><td></td></tr><tr><td>LYL1</td><td>Thermofisher scientific</td><td>Hs01089802_g1</td><td></td></tr><tr><td>Meis1</td><td>Thermofisher scientific</td><td>Hs01017441_m1</td><td></td></tr><tr><td>mKi67</td><td>Thermofisher scientific</td><td>Hs01032443_m1</td><td></td></tr><tr><td>MPL</td><td>Thermofisher scientific</td><td>Hs00180489_m1</td><td></td></tr><tr><td>MPO</td><td>Thermofisher scientific</td><td>Hs00924296_m1</td><td></td></tr><tr><td>NFIB</td><td>Thermofisher scientific</td><td>Hs01029175_m1</td><td></td></tr><tr><td>Notch1</td><td>Thermofisher scientific</td><td>Hs01062011_m1</td><td></td></tr><tr><td>Pten</td><td>Thermofisher scientific</td><td>Hs02621230_s1</td><td></td></tr><tr><td>RAG2</td><td>Thermofisher scientific</td><td>Hs01851142_s1</td><td></td></tr><tr><td>RPS18</td><td>Thermofisher scientific</td><td>Hs01375212_g1</td><td></td></tr><tr><td>RUNX1</td><td>Thermofisher scientific</td><td>Hs00231079_m1</td><td></td></tr><tr><td>Shisa2</td><td>Thermofisher scientific</td><td>Hs01590823_m1</td><td></td></tr><tr><td>Spi1</td><td>Thermofisher scientific</td><td>Hs02786711_m1</td><td></td></tr><tr><td>Sterile.IgH</td><td>Thermofisher scientific</td><td>Hs00378435_m1</td><td></td></tr><tr><td>TAL1</td><td>Thermofisher scientific</td><td>Hs01097987_m1</td><td></td></tr><tr><td>THY1</td><td>Thermofisher scientific</td><td>Hs00264235_s1</td><td></td></tr><tr><td>Tim.3.HAVCR2</td><td>Thermofisher scientific</td><td>Hs00958618_m1</td><td></td></tr><tr><td>VWF</td><td>Thermofisher scientific</td><td>Hs00169795_m1</td><td></td></tr></tbody></table>

a combinatorial single-cell approach to characterize the molecular and immunophenotypic heterogeneity of human stem and progenitor populations

A Combinatorial Single-cell Approach to Characterize the Molecular and Immunophenotypic Heterogeneity of Human Stem and Progenitor Populations

Immunophenotypic characterization and molecular analysis have long been used to delineate heterogeneity and define distinct cell populations. FACS is inherently a single-cell assay, however prior to molecular analysis, the target cells are often prospectively isolated in bulk, thereby losing single-cell resolution. Single-cell gene expression analysis provides a means to understand molecular differences between individual cells in heterogeneous cell populations. In bulk cell analysis an overrepresentation of a distinct cell type results in biases and occlusions of signals from rare cells with biological importance. By utilizing FACS index sorting coupled to single-cell gene expression analysis, populations can be investigated without the loss of single-cell resolution while cells with intermediate cell surface marker expression are also captured, enabling evaluation of the relevance of continuous surface marker expression. Here, we describe an approach that combines single-cell reverse transcription quantitative PCR (RT-qPCR) and FACS index sorting to simultaneously characterize the molecular and immunophenotypic heterogeneity within cell populations.
In contrast to single-cell RNA sequencing methods, the use of qPCR with specific target amplification allows for robust measurements of low-abundance transcripts with fewer dropouts, while it is not confounded by issues related to cell-to-cell variations in read depth. Moreover, by directly index-sorting single-cells into lysis buffer this method, allows for cDNA synthesis and specific target pre-amplification to be performed in one step as well as for correlation of subsequently derived molecular signatures with cell surface marker expression. The described approach has been developed to investigate hematopoietic single-cells, but have also been used successfully on other cell types.
In conclusion, the approach described herein allows for sensitive measurement of mRNA expression for a panel of pre-selected genes with the possibility to develop protocols for subsequent prospective isolation of molecularly distinct subpopulations.

The protocol described is quick, easily performed and highly reliable. An overview of the experimental set-up is presented in Figure 1. The entire protocol, from sorting of single-cells, to specific target amplification, gene expression measurements and preliminary analysis can be performed in three days. An example of analyzed results in the form of a heat map that represents preliminary analyzed data from single-cell gene expression analysis using 96 primer...

Bulk gene expression measurements cloud individual cell differences in heterogeneous cell populations. Here, we describe a protocol for how single-cell gene expression analysis and index sorting by Florescence Activated Cell Sorting (FACS) can be combined to delineate heterogeneity and immunophenotypically characterize molecularly distinct cell populations.

Immunophenotypic characterization and molecular analysis have long been used to delineate heterogeneity and define distinct cell populations. FACS is ...

a-combinatorial-single-cell-approach-to-characterize-molecular

Research

JoVE Journal

Genetics

A method to analyse the distribution of bone marrow hematopoietic progenitors in flow cytometry as well as to efficiently isolate highly purified hematopoietic stem cells (HSCs) is described. The isolation procedure is essentially based on magnetic enrichment of c-Kit+ cells and cell sorting to purify HSCs for cellular and molecular studies.

Phenotypic Analysis and Isolation of Murine Hematopoietic Stem Cells and Lineage-committed Progenitors

Single cell gene expression assay is needed for understanding stem cell heterogeneities.

Profiling Individual Human Embryonic Stem Cells by Quantitative RT-PCR

This protocol describes how to assess the expression of a large array of genes at the clonal level. Single-cell RT-qPCR produces highly reliable results with a strong sensitivity for hundreds of samples and genes.

Single-cell Gene Expression Using Multiplex RT-qPCR to Characterize Heterogeneity of Rare Lymphoid Populations

We have developed a novel protocol for studying heterocellular population dynamics in response to perturbations. This manuscript describes an imaging-based platform that produces quantitative datasets for simultaneous characterization of multiple cellular phenotypes of heterocellular populations in a robust manner.

Discrimination and Characterization of Heterocellular Populations Using Quantitative Imaging Techniques

Here we present methodology for the clonal analysis of hematopoietic stem cell precursors during murine embryonic development. We combine index sorting of single cells from the embryonic aorta-gonad-mesonephros region with endothelial cell co-culture and transplantation to characterize the phenotypic properties and engraftment potential of single hematopoietic precursors.

Clonal Analysis of Embryonic Hematopoietic Stem Cell Precursors Using Single Cell Index Sorting Combined with Endothelial Cell Niche Co-culture

We present a flow cytometry method to identify simultaneously different cell types retrieved from mouse brain or spinal cord. This method could be exploited to isolate or characterize pure cell populations in neurodegenerative diseases or to quantify the extent of cell targeting upon in vivo administration of viral vectors or nanoparticles.

Simultaneous Flow Cytometric Characterization of Multiple Cell Types Retrieved from Mouse Brain/Spinal Cord Through Different Homogenization Methods

Presented here is a flow cytometry-based technique that allows for simultaneously measuring the number of cell divisions, surface cell phenotype, and cellular kinship. Those properties can be tested statistically using a permutation-based framework.

Simultaneous Assessment of Kinship, Division Number, and Phenotype via Flow Cytometry for Hematopoietic Stem and Progenitor Cells

The success of single-cell/single-nuclei transcriptomics and multi-omics largely depends on the quality of cells/nuclei. Therefore, isolating cells/nuclei from tissue and their purification must be highly standardized. This protocol describes the preparation of nuclei from the brain and bone marrow for downstream single-nuclei multiome assay.

High-Quality Brain and Bone Marrow Nuclei Preparation for Single Nuclei Multiome Assays

This protocol describes the use of fluorescence-activated cell sorting of human mesenchymal stem cells using the single-cell sorting method. Specifically, the use of single-cell sorting can achieve 99% purity of the immunophenotyped cells from a heterogeneous population when combined with a multiparametric flow cytometry-based approach.

Single-Cell Sorting of Immunophenotyped Mesenchymal Stem Cells from Human Exfoliated Deciduous Teeth

The protocol presented here enables the identification and high-dimensional analysis of muscle stem and progenitor cells by single-cell mass cytometry and their purification by FACS for in-depth studies of their function. This approach can be applied to study regeneration dynamics in disease models and test the efficacy of pharmacological interventions.

Identification and Analysis of Myogenic Progenitors In Vivo During Acute Skeletal Muscle Injury by High-Dimensional Single-Cell Mass Cytometry

Here we present protocols that enable isolation of stromal cells from murine bone, bone marrow, thymus and human thymic tissue compatible with single-cell multiomics.

Stromal Cell Isolation From Hematopoietic Organs

Learn a combinatorial single-cell approach to characterize molecular and immunophenotypic heterogeneity in human stem and progenitor populations using FACS and gene expression analysis. This method reveals cellular diversity.

A Combinatorial Single-cell Approach to Characterize the Molecular and Immunophenotypic Heterogeneity of Human Stem and Progenitor Populations (Video) | JoVE Journal

A Combinatorial Single-cell Approach to Characterize the Molecular and Immunophenotypic Heterogeneity of Human Stem and Progenitor Populations

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