This work was supported by the Francis Crick Institute, which receives its core funding from Cancer Research UK (FC001042 and FC001162), the UK Medical Research Council (FC001042 and FC001162), and the Wellcome trust (FC001042 and FC001162) and by a Wellcome Trust Investigator Award to JPS (108012/Z/15/Z).Work at the University of Cambridge was co-funded by the NIHR Cambridge Biomedical Research Centre, The Evelyn Trust (16/21), The Rosetrees Trust (M590), and the UK Medical Research Council (MR/S009752/1). The latter UK funded award is part of the EDCTP2 programme supported by the European Union.

This protocol does not contain any studies involving animals or human participants performed by any of the authors. All the steps of this protocol were performed following the guidelines and codes of practice of the institutions where they were carried out.
1. Transfection of 293T cells for VLP production (both SAMHD1-expression vectors and tester HIV particles)
NOTE: The most significant contributors to the successful production of virus particles are the health of the producer 293T cells, confluency at transfection and time of harvest. Laboratories will typically have their preferred transfection reagents and protocol for retroviral particle production. The following protocol yields good quality infectious particles, but equivalent protocols would also be suitable for this application. To maintain good quality 293T cells, passage at least three times per week to maintain a constant growth rate. Cells should be seeded in the log phase of growth for efficient transfection.
<ol>
	<li>Day 1: Seed the required number of 10 cm dishes with a 1/4 split from a near-confluent dish of 293T cells to yield around 60% confluency the following day (approximately 5 x 105 cells/mL). Several densities may need to be seeded to achieve an appropriate density for transfection the following day when working with a new cell stock.</li>
	<li>Day 2 (morning): Check for approximately 60% confluency by microscopy and gently replace media on cells with 10 mL of fresh Dulbecco&#39;s Modified Eagle Medium (DMEM).</li>
	<li>Day 2 (afternoon, at least 4 h after media change): Transfect for VLP production.
	<ol>
		<li>Make up the DNA dilution mix containing 3 &#181;g each of gag-pol expressor plasmid, Long-terminal repeat (LTR)-driven reporter plasmid and Vesicular Stomatitis Virus G protein (VSV-G) expressor plasmid (total 9 &#181;g, see NOTE) in 600 &#181;L of serum-free DMEM. Vortex and centrifuge briefly (15 s, &#62;500 x g).</li>
		<li>Add 20 &#181;L of transfection reagent (see Table of Materials), vortex (do not centrifuge) and incubate at 20 &#176;C for 15-20 min. Add the transfection mix dropwise to the plate, swirl gently to mix, and return to the incubator. 
		NOTE: For MLV VLP expressing SAMHD1 use KB45,6 (gag-pol expressor plasmid), pLGatewaySAMHD1IeYFP1 (LTR-driven reporter plasmid) and pczVSV-G7. For HIV-RFP VLP, use p8.918,9 (gag-pol expressor plasmid), SCRPSY10 (LTR-driven reporter plasmid), and pczVSV-G. Alternatives are discussed in the Table of Materials. Plasmid ratios may need to be optimized for different plasmid/transfection systems.</li>
	</ol>
	</li>
	<li>Day 3 (late morning): Remove the media carefully from cells by pipetting, wash with 5 mL of fresh DMEM, and replace with 5 mL of fresh DMEM.</li>
	<li>Day 4 (morning): Harvest the virus by collecting the supernatant from the cells and replace with 5 mL of fresh DMEM. Pass the VLP-containing supernatant through a 0.45 nm filter, aliquot and transfer to -70 &#176;C for storage. Ensure that the aliquots are of a size suitable for planned experiments (250 &#181;L as a suggestion) as repeated freeze-thaw cycles will result in a loss of viral titer.</li>
	<li>Day 5 (morning): Harvest the virus as in 1.5 but discard the plates after collecting the supernatant.</li>
</ol>
2.&#160;Titering new VLP prior to use
<ol>
	<li>Day 1: Seed 293T at 2 x 105 cells per well of a 24-well plate - 4 wells per virus to be titrated, including a virus of known infectivity for each backbone. Optimize the seeding density for a given cell stock.</li>
	<li>Day 2: Observe the plate to check confluency (ideally ~70%). Thaw the virus-containing-supernatant from steps 1.5 and 1.6. Add 0, 10, 25, or 100 &#181;L to each well.</li>
	<li>Day 4 (Morning): Harvest the cells for analysis by flow cytometry.
	<ol>
		<li>Remove the media by careful pipetting or aspiration. Wash the cells gently with 250 &#181;L of phosphate buffered saline (PBS). Remove the cells from the plate by pipetting up and down with 250 &#181;L PBS, and transfer to a microcentrifuge tube. Add 250 &#181;L of 4% paraformaldehyde (taking final concentration to 2%). 
		CAUTION: Paraformaldehyde is toxic. It should not be mixed with chlorine-based disinfectants.</li>
		<li>Pellet the cells by centrifugation at 500 x g for 5 min, discard the supernatant and resuspend the cell pellet in 200 &#181;L of PBS or alternative flow cytometry buffer. Analyze for RFP or YFP as appropriate by flow cytometry. Normalize the infectivity of a given virus stock against values for a stock of known infectivity. 
		&#8203;NOTE: VLP can also be normalized by p24 enzyme-linked immunosorbent assay (ELISA); however, this is not necessarily a good indicator of VLP infectivity, especially where VLP stocks are prepared in different transfections. Published median tissue culture infectious dose or multiplicity of infection (TCID50/MOI) methods11 can also provide relative quantitation, although these are not well established for MLV. Relative fluorescence provides a cost-effective alternative to commercial reverse transcriptase ELISA methods.</li>
	</ol>
	</li>
</ol>
3. Transduction of U937 with VLP expressing SAMHD1 and YFP
NOTE: Steps 3-6 constitute the restriction experiment. Days are numbered for ease of planning.
<ol>
	<li>Day 1 (afternoon): Thaw VLP for transduction including MLV-Wild-type SAMHD1-YFP (positive control), MLV-SAMHD1(HD206-7AA)-YFP (negative control) and variant MLV-SAMHD1-YFP (experimental samples). Dilute the normalized VLP to a final volume of 500 &#181;L with Roswell Park Memorial Institute 1640 media (RPMI) in a microfuge tube, add 0.5 &#181;L of polybrene (10 mg/mL), and mix by flicking.
	<ol>
		<li>If VLP cannot be titrated beforehand, then use 100 &#181;L in the first instance. Use a maximum 1:1 ratio of VLP to RPMI to limit VLP-induced toxicity. Aim for approximately 30% transduction.</li>
	</ol>
	</li>
	<li>Aliquot 5 x 105 U937 cells into a sterile microfuge tube for each transduction condition. Pellet by centrifugation at 500 x g for 5 min, and remove the supernatant (include two additional tubes as untransduced controls for flow cytometry). Resuspend the cell pellet in 500 &#181;L of diluted VLP (or RPMI for untransduced controls) and transfer to one well of a 24-well plate.</li>
	<li>Spinoculate in a tabletop centrifuge at 800 x g for 90 min at 20 &#176;C. Add 1 mL of 37 &#176;C RPMI to the well and allow to recover in a 37 &#176;C incubator for 3 days.</li>
</ol>
4. Differentiation of transduced U937
<ol>
	<li>Day 4 (morning): Re-suspend the cells by gently pipetting and transfer 350 &#181;L into each of&#160;4 wells of a 12-well plate. Add 700 &#181;L of 37 &#176;C RPMI containing 150 nM PMA to each well giving a final concentration of 100 nM and allow to differentiate for 3 days. 
	&#8203;NOTE: PMA is bought as a powder and should be resuspended to 1 mM in DMSO and stored in the dark. A working stock of 100 &#181;M should be prepared by diluting 1/10 from the 1 mM stock with DMSO.</li>
</ol>
5. Infection of differentiated, SAMHD1-expressing U937 with HIV-RFP
<ol>
	<li>Day 7: Observe the cells by microscopy. Ensure that the cells are adherent. Aspirate the media from all the wells, add 1 mL of RPMI to well 1 of each set of 4 allowing for untransduced, uninfected control as well as single color controls. Add back 0.5 mL of RPMI containing roughly 10 &#181;L of HIV-1-RFP (approximately 10 ng p24 as a guide) to all the other wells. Aim for approximately 50% infection.</li>
	<li>Day 8 (morning): Add 0.5 mL of RPMI to each of the infected wells.</li>
</ol>
6. Flow cytometry analysis
NOTE: It is good practice to include a live-dead stain in flow cytometry pipelines. However, if the U937 cells are of good quality, this step can be omitted without negative consequences for downstream analysis. Gentle pipetting of trypsinized cells should easily result in a single cell suspension.
<ol>
	<li>Day 10 (morning): Aspirate the media from the wells and wash once with PBS. Add 300 &#181;L of cell dissociation enzyme (or trypsin) for 5-10 min. Add an additional 300 &#181;L of PBS, resuspend thoroughly making sure all the cells have come off the plate, and transfer to flow cytometry tubes.</li>
	<li>Add 300 &#181;L of 4% paraformaldehyde (taking final concentration to 2%). Pellet the cells by centrifugation at 500 x g for 5 min, discard the supernatant and resuspend the cell pellet in 200 &#181;L of PBS or alternative flow cytometry buffer. Analyze by flow cytometry. 
	&#8203;NOTE: The steps below are for a Fortessa analyzer, but equivalent analysis can be achieved using any analyzer capable of reading RFP and YFP fluorescence. Consult local flow cytometry support or other experienced researcher before setting up any flow cytometry analysis. When many samples need to be screened at the same time, a high throughput sampler may be appropriate. In this case, a larger cell number and volume are advised.</li>
</ol>
7. Flow cytometry analysis
<ol>
	<li>Turn on the cytometer 10 min before it is required and turn on the computer. Check that the waste is empty and that the sheath tank is full.</li>
	<li>Log in to the machine and open the analysis software.</li>
	<li>Move the arm to the side, take the water tube off, set the flow rate to High and press Prime. Wait for the light to go out and repeat three more times.</li>
	<li>Put the water back on and run on high for 3 min and then switch to Low and press Standby until proceeding to acquisition.</li>
	<li>Meanwhile set up the experiment within the software:
	<ol>
		<li>Select Experiment/ New Experiment (name according to local guidance). In the inspector, delete the unrequired fluorochromes, leaving Blue Laser 530/30 and Yellow Laser 610/20 or the recommended laser and filter combinations for YFP and RFP for the machine.</li>
		<li>Right click on the experiment and choose Cytometer Settings/Application Settings/Create Worksheet. On the worksheet, create a Forward Scatter-Area (FSC-A)/Side Scatter Area (FSC-A) dot blot and YFP histogram, RFP histogram, and GFP/YFP dot blot by clicking on the corresponding icon and changing the axes by clicking on the axis label.</li>
		<li>Right click again on Experiment and add New Specimen. Rename as appropriate. Open the specimen by clicking the plus sign to reveal a new tube.</li>
	</ol>
	</li>
	<li>Open the acquisition dashboard from View, load the uninfected, untransduced control and press Acquire. Adjust FSC and SSC voltages in the dashboard to position cells in the lower-left quadrant (no cells on the axes). Gate around this population P1. Right click on other plots and select show P1 to remove debris from subsequent analysis.</li>
	<li>Load the single-color control for YFP (wild-type SAMHD1 only) and acquire. Adjust the YFP voltage in the dashboard so that the most fluorescent cells are within the range of the detector (not on the edge of the axis). Repeat for single color RFP control.</li>
	<li>Run automatic compensation using the untransduced, uninfected and single-color controls.
	<ol>
		<li>Select Experiment &#62; Compensation Setup &#62; Create Compensation Controls from the menu to toggle to a normal worksheet. Select unstained normal worksheet, press on Run and acquire for the unstained control.</li>
		<li>Draw a gate around the intact cells (P1) and record. Remove the tube and put the machine on Standby. Right click on P1, click on Apply to All Compensation Controls.</li>
		<li>Switch to the RFP normal worksheet, and press Run. Record the single-color RFP control, and put the machine on Standby. The software should&#160;automatically select the positive population.</li>
		<li>Repeat for YFP single color control. Select Experiment &#62; Compensation Setup &#62; Calculate Compensation &#62; Link and Save.</li>
	</ol>
	</li>
	<li>Switch to the global worksheet. Acquire the cells transduced with wild type SAMHD1, infected with HIV-RFP and check that four distinct populations can be seen in the corners of the quadrants that are aligned vertically and horizontally for YFP and RFP, respectively. Remove the tube and press Standby.</li>
	<li>Reload the untransduced, uninfected sample, press Run and Record 30,000 events with P1 as the stopping gate. Repeat for the remaining samples (including other controls). Rename the samples while running or post hoc. Once exported, files cannot be renamed.</li>
	<li>Export the data as .fcs files and clean the fluidics according to local instructions.</li>
</ol>
8. Data analysis
NOTE: The steps that follow correspond to analysis in FlowJo v10; however, equivalent steps can easily be performed in other analysis software.
<ol>
	<li>Open the software and drag all .fcs files into the dashboard. Select the compensation controls and drag them into the compensation subfolder. Open the file for the untransduced, uninfected tube by double-clicking, which will bring up the FSC-A/SSC-A plot.</li>
	<li>Select the polygon tool and gate on the intact cell population, excluding debris in the lower-left corner. Name this Cells. Drag this gate onto the whole population of tubes in the All Samples bar. Scroll through each individual sample using the horizontal arrow buttons to ensure gating is appropriate for each tube.</li>
	<li>Double-click on the Cells population for the untransduced, uninfected sample and adjust the axes to FSC-Height (H) vs FSC-Area (A). Select the single large population using a rectangular gate to exclude doublets. The software will automatically suggest naming this&#160;Single Cells.</li>
	<li>Drag this gate onto all the Cells populations and again, check that the gating is appropriate for all samples. Select the Single Cells population for the uninfected, untransduced sample, change the axes to compensated blue laser (y, YFP) versus compensated yellow laser (x, RFP). Press T on the axis and select Biexponential scale for x and y.</li>
	<li>Select the Quadrant Gating Tool and click at the upper-right extreme of the negative cell population. Apply this preliminary gating to all Single Cell populations by dragging into the All Samples bar. Where the quadrant gates do not separate the populations satisfactorily, it may be necessary to gate individual quadrants using the polygon tool, as in Figure 2.</li>
	<li>Scroll to the wild-type SAMHD1 only sample (YFP only) and check that the gating between the untranduced (YFP negative) and YFP positive is correct. It may help to switch to contour view to discriminate negative from dim YFP cells. If the upper-most YFP +ve cells are spread widely, adjust the upper-vertical gate to the right.</li>
	<li>Scroll through all samples and check the gating with respect to YFP positivity. Use the best division between YFP negative and positive that is valid for all samples. 
	NOTE: The compensation will have been calculated based on the wild-type SAMHD1 YFP expression level. If infection levels are very different between different SAMHD1-YFP transduced cells, the compensation may need to be adjusted. It is therefore preferred that YFP VLP are normalized prior to use.</li>
	<li>Scroll to the untransduced, HIV-RFP infected tube and check whether the gating between uninfected RFP negative and infected RFP positive is correct. Adjust as appropriate, using the contour view if required and scroll through the remaining samples to check the gating is valid for all samples.</li>
	<li>Each sample requires double negatives (Q4: lower left, untransduced, uninfected), YFP positive (Q1: upper left, SAMHD1 expressing, uninfected), RFP-positive (Q3: lower right, untransduced, HIV infected), and double positive (Q2: upper right, SAMHD1 expressing HIV-infected). Open the table editor by clicking on the icon and drag the four quadrant gates into the dashboard. Select Excel Export and click on Create Table. Save the generated spreadsheet according to local file naming conventions.</li>
	<li>To export representations of plots and gating strategies, click on the Layout Editor icon. Select each population and drag into the editor with the axes, labeling and spacing required.</li>
	<li>To create a layout with the same plots shown for all samples, select one column and press on Batch. Press on Scale to Width and then Avoid Page Breaks. Save in the file format required.</li>
	<li>In the exported spreadsheet, calculate the restriction ratio by generating columns of percentage RFP of YFP-ves (RFP+ve / (double negatives + RFP+ve)) and percentage RFP of YFP+ves (double positives / (double positives&#160;+ YFP+ve)) and then a final column of (%RFP of YFP+ve / %RFP of YFP-ve), see Figure 1. Average the replicate data for each SAMHD1 construct and calculate whether restriction values for tested SAMHD1 variants are significantly different from wild-type and/or 206-7AA using appropriate data analysis software.</li>
</ol>

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For the purpose of Open Access, the authors have applied a CC BY public copyright license to any Author Accepted Manuscript version arising from this submission. The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care.

As discussed in the notes above, the critical aspects of the protocol center around retaining the correct cell phenotype for VLP production and for creating the appropriate environment for observing SAMHD1 restriction. Firstly, the accurate analysis of restriction by two-color flow cytometry relies on achieving appropriate proportions of transduced and infected cells so that there are enough cells in each area of the plot for analysis. As such the researcher should be aiming for an MOI of less than 1 (see Protocol). Transduction and infection rates that are either too high or too low lead to problems with analysis due to lack of uninfected or doubly infected cells. Equally, a similar transduction rate for SAMHD1 vectors to be compared is key to allowing the same compensation matrix and gating to be applied to the whole experiment, increasing confidence in the subsequent analysis.
Secondly, the age of the U937 cells used is a key factor in whether they differentiate successfully. Successful differentiation can be monitored through observation of adherence, a reduced acidification of the media over time following differentiation and adequate restriction by the wild type positive control in the assay. Differentiation of up to 5 days has been successful.
One of the key advantages to this assay is its flexibility. A variety of modified versions of SAMHD1 (domains, amino acids, species sequences) can be tested via simple site-directed mutagenesis of the vector or cloning. Equally, variants of the tester virus can be explored. The assay has been used previously to demonstrate that HIV-1 reverse transcriptase mutants with reduced capacity to bind dNTP are more sensitive to SAMHD1 restriction. The same principle can be used to test the restriction of other viruses by SAMHD1. Furthermore, varying differentiation conditions or artificial manipulation of intracellular dNTP concentrations can be used to further probe the interaction between intracellular conditions and SAMHD1 activity, an area of active research in the Bishop lab. The interaction of SAMHD1 with various nucleoside reverse transcriptase inhibitors has also been described, and the effect of SAMHD1 shown using this assay modified for use in primary cells12,13,14,15.
Adaptation of the protocol for use in primary cells overcomes the limitation posed by examining metabolic phenotypes in transformed cells. However, the existing format allows for a convenient and less technically challenging protocol for high throughput analysis, especially with use of a flow cytometer with a high-throughput sampler. When adapting the protocol, the susceptibility of the internally untransduced cells to bystander effects (e.g., immune signaling) should be considered.
As with many aspects of cell biology, it is essential that such assays are used as part of a holistic approach for understanding a given phenomenon. The parallel use of biochemical assays for SAMHD1 activity16, quantification of intracellular dNTP pools, and observation of SAMHD1 mutant phenotypes in humans, ex vivo and in animal models (being carried out by labs around the world, some described in this issue) are key for the evolving understanding of this complex protein.

Sterile &#945;-motif/histidine-aspartate domain-containing protein 1 (SAMHD1) impedes replication of Human Immunodeficiency Virus type 1 (HIV-1) in quiescent cells of the myeloid lineage. SAMHD1 blocks replication through its enzymatic activity as a dNTP triphosphohydrolase, which results in decreased levels of intracellular dNTPs. As a result, HIV-1 cannot perform the process of reverse transcription efficiently. Much progress has been made in the few years since this initial observation, particularly regarding the contribution of specific domains and amino acids to SAMHD1&#39;s antiviral activity. These insights have been made using biochemical assays as well as cell systems mimicking the physiologically relevant quiescent myeloid environment. U937 cells1 are widely used as a convenient myeloid cell system for analyzing SAMHD1 activity. This is due to a lack of endogenous SAMHD1 expression, thought to be due to low RNA levels compared to SAMHD1-expressing cells (an area of ongoing research). Here, the protocol describes the transient transduction of U937 cells with virus-like particles co-expressing SAMHD1 and a yellow fluorescent protein (YFP) reporter to examine the mechanism of SAMHD1 restriction of HIV-1. Such transient two-color flow cytometry assays to examine retroviral restrictions were first developed in the Stoye laboratory2 and have since been adapted to investigate other restriction factors, including the tripartite motif (TRIM) proteins3. Inspired by these assays, the Bishop lab developed a two-color assay to analyze SAMHD1 restriction in U937 cells.
The workflow for the experiment is shown in Figure 1. Murine Leukaemia Virus (MLV)-like particles containing a bi-cistronic message encoding SAMHD1 alongside YFP expressed from an IRES are used to transduce U937 cells. Cells are then treated with phorbol myristate acetate (PMA) to induce differentiation to a quiescent phenotype. Cells are next infected with HIV-1 virus-like particles expressing red fluorescent protein (RFP). After 48 h, the cells are harvested and analyzed by two-color flow cytometry. This assay is also used with YFP and green fluorescent protein (GFP), requiring less standard filter combinations for flow cytometry analysis. Use of HIV-RFP allows for more straightforward compensation and thus the assay is more easily accessible to less experienced flow cytometry users, and achievable with most cytometers.
During analysis, the proportion of HIV infected cells is compared between SAMHD1-expressing cells and those lacking SAMHD1 within the same well of cells. This affords an internal control in well/flow cytometry tube, which is a key feature. The comparison of infection levels in transduced and untransduced cells reveals a restriction ratio. A ratio of 1.0 indicates that the transduced factor has no effect on infectivity. Wild type SAMHD1 expression leads to a five-fold reduction in HIV infection in this assay, corresponding to a restriction ratio of 0.2. While this effect is modest in comparison to more classic restriction factors such as TRIM5, the effect is nonetheless reproducible and allows the classification of modified SAMHD1 expressors into those that restrict in an equivalent manner to the wild-type protein, those that fail to restrict, and those with an intermediate phenotype.
This assay has been used successfully to characterize SAMHD1 domain and amino acid mutants&#39; restriction phenotypes by transducing with viruses encoding mutant SAMHD1 sequences. For example, the catalytic site substitutions HD206-7AA fail to restrict in this assay. Equally, the susceptibility of different tester viruses can be determined. For example, HIV-1 reverse transcriptase mutants are more susceptible to SAMHD1-mediated restriction (e.g., 151V4). This protocol outlines the details of virus-like particle (VLP) production, transduction of U937 with SAMHD1 expression vectors, infection with HIV carrying a fluorescent reporter and the subsequent analysis by flow cytometry. This article discusses what data to expect and how to avoid suboptimal results. Finally, alternative uses for the assay are outlined, in addition to examining different SAMHD1 variants to understand the interplay between SAMHD1, dNTP levels and viral infection more thoroughly. Given the role of SAMHD1 at the center of cell metabolism, with additional links to cancer, this continues to be an area of intense interest.

<table><tbody><tr><td>293T cells</td><td>ATCC</td><td>CRL-3216</td><td></td></tr><tr><td>0.45 &amp;micro;m syringe filters</td><td>Sartorius</td><td>FCT122</td><td></td></tr><tr><td>10 cm dishes</td><td>Corning</td><td>430167</td><td>virus preps can be scaled up through transfection in higher capacity plates/flasks - see transfection reagent guidance</td></tr><tr><td>12 well plates</td><td>Greiner</td><td>665180</td><td></td></tr><tr><td>24 well plates</td><td>Greiner</td><td>662160</td><td></td></tr><tr><td>BD LSRFortessa cell analyzer</td><td>BD Bioscience</td><td>649225</td><td>alternative analysers can be used as long as they can read RFP and YFP fluorescence</td></tr><tr><td>DMEM</td><td>Sigma</td><td>D6429</td><td>ATCC recommends Dulbecco&#039;s Modified Eagle&#039;s Medium (DMEM) is modified to contain 4 mM L-glutamine, 4500 mg/L glucose, 1 mM sodium pyruvate, and 1500 mg/L sodium bicarbonate.&amp;nbsp;</td></tr><tr><td>DMSO</td><td>Fisher</td><td>BP-231-100</td><td></td></tr><tr><td>fetal bovine serum</td><td>Gibco</td><td>10500064</td><td></td></tr><tr><td>Flowjo</td><td>BD Bioscience</td><td>-</td><td>alternative analysis software can be used</td></tr><tr><td>light microscope</td><td>-</td><td>-</td><td>Any bright field light microscope</td></tr><tr><td>p8.91</td><td>-</td><td>-</td><td>HIV GagPol expressor (PMID: 8602510)</td></tr><tr><td>paraformaldehyde (4 % in PBS)</td><td>Alfa Aesar</td><td>J61889</td><td></td></tr><tr><td>PBS</td><td>Sigma</td><td>D8537</td><td></td></tr><tr><td>Penicillin-Streptomycin (10,000 U/mL)</td><td>ThermoFisher</td><td>15140122</td><td></td></tr><tr><td>phorbol 12-myristate 13-acetate (PMA)</td><td>Sigma</td><td>P8139</td><td></td></tr><tr><td>polybrene</td><td>Sigma</td><td>TR-1003</td><td></td></tr><tr><td>pKB4</td><td>-</td><td>-</td><td>Murine leukaemia Virus GagPol expressor (PMID: 23035841)</td></tr><tr><td>pLGatewaySAMHD1eYFP</td><td>-</td><td>-</td><td>MLV packaging plasmid encoding wild-type human sequence. Details and cloning procedures Arnold et al 2015 (Ref 1).</td></tr><tr><td>pLGatewaySAMHD1HD206-7AAeY&lt;br/&gt; FP</td><td>-</td><td>-</td><td>As above, encodes amino acid substitutions at crucial active sites residues</td></tr><tr><td>Prism</td><td>Graphpad</td><td>-</td><td>https://www.graphpad.com/scientific-software/prism/ Other data representation software are also suitable</td></tr><tr><td>pVSV-G</td><td>-</td><td>-</td><td>VSV-G expressor (https://www.addgene.org/138479/), alternative: pMD2.G (https://www.addgene.org/12259/)</td></tr><tr><td>RPMI</td><td>ThermoFisher</td><td>21875034</td><td></td></tr><tr><td>screw-cap tubes</td><td>StarLab</td><td>E1415-2231</td><td></td></tr><tr><td>SCRPSY</td><td>-</td><td>-</td><td>HIV packaging plasmid encoding RFP, Sam Wilson, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5026698/</td></tr><tr><td>stripettes 10 mL</td><td>Corning</td><td>10084450</td><td></td></tr><tr><td>stripettes 5 mL</td><td>Corning</td><td>10420201</td><td></td></tr><tr><td>TrypLE express</td><td>Gibco</td><td>12604021</td><td>Trypsin will also be suitable</td></tr><tr><td>Turbofect</td><td>ThermoFisher</td><td>R0531</td><td>alternative transfection reagents will also work well</td></tr><tr><td>U937 cells</td><td>ATCC</td><td>CRL-1593.2</td><td></td></tr></tbody></table>

analysis of samhd1 restriction by flow cytometry in human myeloid u937 cells

Sterile &#945;-motif/histidine-aspartate domain-containing protein 1 (SAMHD1) inhibits replication of HIV-1 in quiescent myeloid cells. U937 cells are widely used as a convenient cell system for analyzing SAMHD1 activity due to a low level of SAMHD1 RNA expression, leading to undetectable endogenous protein expression. Based on similar assays developed in the Stoye laboratory to characterize other retroviral restriction factors, the Bishop lab developed a two-color restriction assay to analyze SAMHD1 in U937 cells. Murine Leukaemia Virus-like particles expressing SAMHD1, alongside YFP expressed from an IRES, are used to transduce U937 cells. Cells are then treated with phorbol myristate acetate to induce differentiation to a quiescent phenotype. Following differentiation, cells are infected with HIV-1 virus-like particles expressing a fluorescent reporter. After 48 h, cells are harvested and analyzed by flow cytometry. The proportion of HIV-infected cells in the SAMHD1-expressing population is compared to that in internal control cells lacking SAMHD1. This comparison reveals a restriction ratio. SAMHD1 expression leads to a five-fold reduction in HIV infection, corresponding to a restriction ratio of 0.2. Our recent substitution of RFP for the original GFP as the reporter gene for HIV infection has facilitated flow cytometry analysis.
This assay has been successfully used to characterize the effect of amino acid substitutions on SAMHD1 restriction by transducing with viruses encoding altered SAMHD1 proteins, derived from site-directed mutagenesis of the expression vector. For example, the catalytic site substitutions HD206-7AA show a restriction phenotype of 1, indicating a loss of restriction activity. Equally, the susceptibility of different tester viruses can be determined. The assay can be further adapted to incorporate the effect of differentiation status, metabolic status, and SAMHD1 modifiers to better understand the relationship between SAMHD1, cell metabolic state, and viral restriction.

The results of the analysis above should yield a restriction ratio of 0.25 or lower for the wild-type SAMHD1 positive control, and 1.0 for the negative control. If these two quality control checks are valid, then consider the statistical significance of the results. SAMHD1 variants that show no significant difference from wild type therefore carry substitutions which do not impact SAMHD1 restriction in this context. Those significantly different from wild type show impaired restriction. If these are not significantly different from the negative control, then they lack the ability to restrict in this context (Figure 4 left panels).
If the wild-type SAMHD1 restriction value is greater than 0.3, then results for tester viruses may be indicative but cannot be relied upon. Ineffective restriction by wild-type protein may result from using U937 cells too early post-recovery from reconstitution (within 2 weeks), or when they are too old (&#62;2-3 months). These parameters may need to be empirically determined for a given cell stock. Typically, the lower the passage, the more reliably the cells differentiate and therefore provide the appropriate environment for SAMHD1 restriction. Inappropriate infection level with either SAMHD1-YFP or HIV-RFP may also result in difficulties with both compensation and downstream determination of restriction ratio. An example is illustrated in the right-hand panels of Figure 4.
If the negative control deviates from 1.0 (outside the range of 0.9-1.2), this may indicate a problem with the analysis, either the proportion of infected cells, gating strategy, or health of the cells are affecting the assay. Refer to NOTES above.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/62502/62502fig01.jpg" /> 
Figure 1: Schematic outlining protocol. VLP, virus-like particles, PMA, phorbol myristate acetate. Numbered stages correspond to stages in protocol. Figure produced using BioRender.com. <a href="https://www.jove.com/files/ftp_upload/62502/62502fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/62502/62502fig02.jpg" /> 
Figure 2: Schematic of retroviral plasmids. (A) Packaging vectors (B) Transfer vectors (C) VSV-G envelope expressor. Key coding and regulatory elements are shown. For details refer to the Table of Materials. CMV IE: cytomegalovirus immediate-early promoter, BGH: bovine growth hormone, pA: polyA, RRE: Rev Response Element, CMV-LTR: composite CMV-HIV-1 LTR promoter, Psi: HIV-1 packaging signal, cPPT/CTS: central polypurine tract/central termination sequence, SV40: simian vacuolating virus 40. Figure produced using BioRender.com. <a href="https://www.jove.com/files/ftp_upload/62502/62502fig02large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/62502/62502fig03.jpg" /> 
Figure 3: Gating strategy for flow cytometry analysis. (A) Compensation controls: left panel shows FSC-A/SSC-A gating on in-tact cells for the untransduced, uninfected control. Central and right panels show screenshots of single-color compensation controls for YFP (mid) and RFP (right) with uncompensated data in black and compensated in blue. (B) Corresponding compensation matrix and plots for compensation controls above. (C) Gating strategy. Debris is eliminated through analysis of all cells by FSC-A/SSC-A (left panel). Doublets are excluded by gating on FSC height versus area (central panel). Right panel shows an example of HIV-1 restriction by wild-type SAMHD1. Axes show compensated blue and yellow laser fluorescence corresponding to YFP (SAMHD1) and RFP (HIV)-positive cells respectively. Quadrant gates are drawn though comparison of negative and single-color controls for RFP and YFP. Numbers indicate percentage of parent population. Compensation values for YFP with GFP will be much higher but possible to discriminate using appropriate filter sets. <a href="https://www.jove.com/files/ftp_upload/62502/62502fig03large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/62502/62502fig04.jpg" /> 
Figure 4: Expected results: ideal versus suboptimal data. (A) Representative YFP/RFP plots for optimal (left) and suboptimal (right) data. Numbers indicate percentage of parent population. In the right panel, HIV infection is too low creating difficulties with compensation and gating. Restriction ratio is higher than expected at 0.5. (B) Plots of restriction ratio for variants of SAMHD1 with respect to wild type (WT, red) or the negative control (HD206-7AA, black) generated using statistical software. Each point represents a replicate value. Mean and standard deviation are shown. Paired t-tests between each group were significant in all cases expect where shown. Left: Ideal data - WT shows the expected restriction of approximately 0.2, negative shows 1.0. The variant R372D (gray) is significantly different from WT but not significant from the negative control and thus has lost the ability to restrict. Right: Suboptimal data. Here, the negative behaves as expected but in all six replicates the WT only shows a restriction ratio of 0.5, due to low infection rate. The low variance within the groups means R143H shows an intermediate phenotype statistically different from WT and the negative, while G209S does not restrict; however, this should be repeated with fresh cells as the positive control has not given the expected restriction ratio. <a href="https://www.jove.com/files/ftp_upload/62502/62502fig04large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

Watch this Scientific Journal Video about Analysis of SAMHD1 Restriction by Flow Cytometry in Human Myeloid U937 Cells at JoVE.com

Analysis of SAMHD1 Restriction by Flow Cytometry in Human Myeloid U937 Cells

Described here is an established method to determine the extent of HIV-1 restriction by the cellular inhibitory protein SAMHD1. Human myeloid lineage U937 cells are transduced with a SAMHD1 expression vector co-expressing YFP, differentiated and then challenged with HIV-RFP. The level of restriction is determined by flow cytometry analysis.

Sterile &#945;-motif/histidine-aspartate domain-containing protein 1 (SAMHD1) inhibits replication of HIV-1 in quiescent myeloid cells. U937 cells are ...

analysis-samhd1-restriction-flow-cytometry-human-myeloid-u937

Research

JoVE Journal

Immunology and Infection

2.3K Views.  The Francis Crick Institute. Met toenemende belangstelling voor de rol van cellulaire factoren bij HIV-infectie van macrofagen, hebben we een flexibel analysesysteem ontwikkeld, met name voor SAM HG-analyse, dat niet tot expressie komt in U937-cellen. Het grote voordeel van het systeem is de flexibiliteit. Zodra het is ingesteld, kan het worden gebruikt om een verscheidenheid aan eiwitten, cellen of doelvirussen te analyseren.Het is belangrijk om de gezondheid van de cellen te behouden en ook om comfortabel te zij...

Video: Analysis of SAMHD1 Restriction by Flow Cytometry in Human Myeloid U937 Cells

Flow Cytometry to Estimate Leukemia Stem Cells in Primary Acute Myeloid Leukemia and in Patient-derived-xenografts, at Diagnosis and Follow Up

Acute myeloid leukemia (AML) is a heterogeneous, and if not treated, fatal disease. It is the most common cause of leukemia-associated mortality in adults. Initially, AML is a disease of hematopoietic stem cells (HSC) characterized by arrest of differentiation, subsequent accumulation of leukemia blast cells, and reduced production of functional hematopoietic elements. Heterogeneity extends to the presence of leukemia stem cells (LSC), with this dynamic cell compartment evolving to overcome various selection pressures imposed upon during leukemia progression and treatment. To further define the LSC population, the addition of CD90 and CD45RA allows the discrimination of normal HSCs and multipotent progenitors within the CD34+CD38- cell compartment. Here, we outline a protocol to detect simultaneous expression of several putative LSC markers (CD34, CD38, CD45RA, CD90) on primary blast cells of human AML by multiparametric flow cytometry. Furthermore, we show how to quantify three progenitor populations and a putative LSC population with increasing degree of maturation. We confirmed the presence of these populations in corresponding patient-derived-xenografts. This method of detection and quantification of putative LSC may be used for clinical follow-up of chemotherapy response (i.e., minimal residual disease), as residual LSC may cause AML relapse.

We outline a protocol to detect simultaneous expression of leukemia stem cell markers on primary acute myeloid leukemia cells by flow cytometry. We show how to quantify three progenitor populations and a putative LSC population with increasing degree of maturation. We confirmed the presence of these populations in corresponding patient-derived-xenografts.

Acute myeloid leukemia (AML) is a heterogeneous, and if not treated, fatal disease. It is the most common cause of leukemia-associated mortality in ...

Cancer Research

Flow Cytometric Analysis of Mitochondrial Reactive Oxygen Species in Murine Hematopoietic Stem and Progenitor Cells and MLL-AF9 Driven Leukemia

We present a flow cytometric approach for analyzing mitochondrial ROS in various live bone marrow (BM)-derived stem and progenitor cell populations from healthy mice as well as mice with AML driven by MLL-AF9. Specifically, we describe a two-step cell staining process, whereby healthy or leukemia BM cells are first stained with a fluorogenic dye that detects mitochondrial superoxides, followed by staining with fluorochrome-linked monoclonal antibodies that are used to distinguish various healthy and malignant hematopoietic progenitor populations. We also provide a strategy for acquiring and analyzing the samples by flow cytometry. The entire protocol can be carried out in a timeframe as short as 3-4 h. We also highlight the key variables to consider as well as the advantages and limitations of monitoring ROS production in the mitochondrial compartment of live hematopoietic and leukemia stem and progenitor subpopulations using fluorogenic dyes by flow cytometry. Furthermore, we present data that mitochondrial ROS abundance varies among distinct healthy HSPC sub-populations and leukemia progenitors and discuss the possible applications of this technique in hematologic research.

We describe a method for using multiparameter flow cytometry to detect mitochondrial reactive oxygen species (ROS) in murine healthy hematopoietic stem and progenitor cells (HSPCs) and leukemia cells from a mouse model of acute myeloid leukemia (AML) driven by MLL-AF9.

We present a flow cytometric approach for analyzing mitochondrial ROS in various live bone marrow (BM)-derived stem and progenitor cell populations from ...

Isolation and Characterization of Bone Marrow Microenvironment in Myeloid Neoplasms

Identifying Bone Marrow Microenvironmental Populations in Myelodysplastic Syndrome and Acute Myeloid Leukemia

The bone marrow microenvironment consists of distinct cell populations, such as mesenchymal stromal cells, endothelial cells, osteolineage cells, and fibroblasts, which provide support for hematopoietic stem cells (HSCs). In addition to supporting normal HSCs, the bone marrow microenvironment also plays a role in the development of hematopoietic stem cell disorders, such as myelodysplastic syndromes (MDS) and acute myeloid leukemia (AML). MDS-associated mutations in HSCs lead to a block in differentiation and progressive bone marrow failure, especially in the elderly. MDS can often progress to therapy-resistant AML, a disease characterized by a rapid accumulation of immature myeloid blasts. The bone marrow microenvironment is known to be altered in patients with these myeloid neoplasms. Here, a comprehensive protocol to isolate and phenotypically characterize bone marrow microenvironmental cells from murine models of myelodysplastic syndrome and acute myeloid leukemia is described. Isolating and characterizing changes in the bone marrow niche populations can help determine their role in disease initiation and progression and may lead to the development of novel therapeutics targeting cancer-promoting alterations in the bone marrow stromal populations.

Author Spotlight: Analyzing Bone Marrow Microenvironment in Murine Hematological Malignancies 

Here a detailed protocol to isolate and characterize bone marrow microenvironmental populations from murine models of myelodysplastic syndromes and acute myeloid leukemia is presented. This technique identifies changes in the non-hematopoietic bone marrow niche, including the endothelial and mesenchymal stromal cells, with disease progression.

The bone marrow microenvironment consists of distinct cell populations, such as mesenchymal stromal cells, endothelial cells, osteolineage cells, and ...

Characterization of Human Monocyte-derived Dendritic Cells by Imaging Flow Cytometry: A Comparison between Two Monocyte Isolation Protocols

Dendritic cells (DCs) are antigen presenting cells of the immune system that play a crucial role in lymphocyte responses, host defense mechanisms, and pathogenesis of inflammation. Isolation and study of DCs have been important in biological research because of their distinctive features. Although they are essential key mediators of the immune system, DCs are very rare in blood, accounting for approximately 0.1 - 1% of total blood mononuclear cells. Therefore, alternatives for isolation methods rely on the differentiation of DCs from monocytes isolated from peripheral blood mononuclear cells (PBMCs). The utilization of proper isolation techniques that combine simplicity, affordability, high purity, and high yield of cells is imperative to consider. In the current study, two distinct methods for the generation of DCs will be compared. Monocytes were selected by adherence or negatively enriched using magnetic separation procedure followed by differentiation into DCs with IL-4 and GM-CSF. Monocyte and MDDC viability, proliferation, and phenotype were assessed using viability dyes, MTT assay, and CD11c/ CD14 surface marker analysis by imaging flow cytometry. Although the magnetic separation method yielded a significant higher percentage of monocytes with higher proliferative capacity when compared to the adhesion method, the findings have demonstrated the ability of both techniques to simultaneously generate monocytes that are capable of proliferating and differentiating into viable CD11c+ MDDCs after seven days in culture. Both methods yielded &gt; 70% CD11c+ MDDCs. Therefore, our results provide insights that contribute to the development of reliable methods for isolation and characterization of human DCs.

This study compares two different methods of human monocyte isolation for obtaining in vitro dendritic cells (DCs). Monocytes are selected by adherence or negatively enriched by magnetic separation. Monocyte yield and viability along with MDDC viability, proliferation and CD11c/CD14 surface marker expression will be compared between both methods.

Dendritic cells (DCs) are antigen presenting cells of the immune system that play a crucial role in lymphocyte responses, host defense mechanisms, and ...

Analysis of Microglia and Monocyte-derived Macrophages from the Central Nervous System by Flow Cytometry

Numerous studies have demonstrated the role of immune cells, in particular macrophages, in central nervous system (CNS) pathologies. There are two main macrophage populations in the CNS: (i) the microglia, which are the resident macrophages of the CNS and are derived from yolk sac progenitors during embryogenesis, and (ii) the monocyte-derived macrophages (MDM), which can infiltrate the CNS during disease and are derived from bone marrow progenitors. The roles of each macrophage subpopulation differ depending on the pathology being studied. Furthermore, there is no consensus on the histological markers or the distinguishing criteria used for these macrophage subpopulations. However, the analysis of the expression profiles of the CD11b and CD45 markers by flow cytometry allows us to distinguish the microglia (CD11b+CD45med) from the MDM (CD11b+CD45high). In this protocol, we show that the density gradient centrifugation and the flow cytometry analysis can be used to characterize these CNS macrophage subpopulations, and to study several markers of interest expressed by these cells as we recently published. Thus, this technique can further our understanding of the role of macrophages in mouse models of neurological diseases and can also be used to evaluate drug effects on these cells.

This protocol provides an analysis of the macrophage subpopulations in the adult mouse central nervous system by flow cytometry and is helpful for the study of multiple markers expressed by these cells.

Numerous studies have demonstrated the role of immune cells, in particular macrophages, in central nervous system (CNS) pathologies. There are two main ...

Characterization of Human Monocyte Subsets by Whole Blood Flow Cytometry Analysis

Monocytes are key contributors in various inflammatory disorders and alterations to these cells, including their subset proportions and functions, can have pathological significance. An ideal method for examining alterations to monocytes is whole blood flow cytometry as the minimal handling of samples by this method limits artifactual cell activation. However, many different approaches are taken to gate the monocyte subsets leading to inconsistent identification of the subsets between studies. Here we demonstrate a method using whole blood flow cytometry to identify and characterize human monocyte subsets (classical, intermediate, and non-classical). We outline how to prepare the blood samples for flow cytometry, gate the subsets (ensure contaminating cells have been removed), and determine monocyte subset expression of surface markers &#8212; in this example M1 and M2 markers. This protocol can be extended to other studies that require a standard gating method for assessing monocyte subset proportions and monocyte subset expression of other functional markers.

Here we present a protocol for characterizing monocyte subsets by whole blood flow cytometry. This includes outlining how to gate the subsets and assess their expression of surface markers and giving an example of the assessment of the expression of M1 (inflammatory) and M2 markers (anti-inflammatory).

Monocytes are key contributors in various inflammatory disorders and alterations to these cells, including their subset proportions and functions, can ...

Database-guided Flow-cytometry for Evaluation of Bone Marrow Myeloid Cell Maturation

A working group initiated within the French Cytometry Association (AFC) was developed in order to harmonize the application of multiparameter flow cytometry (MFC) for myeloid disease diagnosis in France. The protocol presented here was agreed-upon and applied between September 2013 and November 2015 in six French diagnostic laboratories (University Hospitals of Saint-Etienne, Grenoble, Clermont-Ferrand, Nice, and Lille and Institut Paoli-Calmettes in Marseille) and allowed the standardization of bone marrow sample preparation and data acquisition. Three maturation databases were developed for neutrophil, monocytic, and erythroid lineages with bone marrow from "healthy" donor individuals (individuals without any evidence of a hematopoietic disease). A robust method of analysis for each myeloid lineage should be applicable for routine diagnostic use. New cases can be analyzed in the same manner and compared against the usual databases. Thus, quantitative and qualitative phenotypic abnormalities can be identified and those above 2SD compared with data of normal bone marrow samples should be considered indicative of pathology. The major limitation is the higher variability between the data achieved using the monoclonal antibodies obtained with the methods based on hybridoma technologies and currently used in clinical diagnosis. Setting criteria for technical validation of the data acquired may help improve the utility of MFC for MDS diagnostics. The establishment of these criteria requires analysis against a database. The reduction of investigator subjectivity in data analysis is an important advantage of this method.

The MDS diagnosis is difficult in the absence of morphological criteria or non-informative cytogenetics. MFC could help refine the MDS diagnostic process. To become useful for clinical practice, the MFC analysis must be based on parameters with sufficient specificity and sensitivity, and data should be reproducible between different operators.

A working group initiated within the French Cytometry Association (AFC) was developed in order to harmonize the application of multiparameter flow ...

Medicine

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

Few techniques can assess phenotype and fate for the same cell simultaneously. Most of the current protocols used to characterize phenotype, although able to generate large datasets, necessitate the destruction of the cell of interest, making it impossible to assess its functional fate. Heterogeneous biological differentiating systems like hematopoiesis are therefore difficult to describe. Building on cell division tracking dyes, we further developed a protocol to simultaneously determine kinship, division number, and differentiation status for many single hematopoietic progenitors. This protocol allows the assessment of the ex vivo differentiation potential of murine and human hematopoietic progenitors, isolated from various biological sources. Moreover, as it is based on flow cytometry and a limited number of reagents, it can quickly generate a large amount of data, at the single-cell level, in a relatively inexpensive manner. We also provide the analytical pipeline for single-cell analysis, combined with a robust statistical framework. As this protocol allows the linking of cell division and differentiation at the single-cell level, it can be used to quantitatively assess symmetric and asymmetric fate commitment, the balance between self-renewal and differentiation, and the number of divisions for a given commitment fate. Altogether, this protocol can be used in experimental designs aiming to unravel the biological differences between hematopoietic progenitors, from a single-cell perspective.

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

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.

Few techniques can assess phenotype and fate for the same cell simultaneously. Most of the current protocols used to characterize phenotype, although able ...

Mouse Brain Histone Modification Quantification Using Flow Cytometry

Quantification of Global Histone Post Translational Modifications Using Intranuclear Flow Cytometry in Isolated Mouse Brain Microglia

Gene expression control occurs partially by modifications in chromatin structure, including the addition and removal of posttranslational modifications to histone tails. Histone post-translational modifications (HPTMs) can either facilitate gene expression or repression. For example, acetylation of histone tail lysine residues neutralizes the positive charge and reduces interactions between the tail and negatively charged DNA. The decrease in histone tail-DNA interactions results in increased accessibility of the underlying DNA, allowing for increased transcription factor access. The acetylation mark also serves as a recognition site for bromodomain-containing transcriptional activators, together resulting in enhanced gene expression. Histone marks can be dynamically regulated during cell differentiation and in response to different cellular environments and stimuli. While next-generation sequencing approaches have begun to characterize genomic locations for individual histone modifications, only one modification can be examined concurrently. Given that there are hundreds of different HPTMs, we have developed a high throughput, quantitative measure of global HPTMs that can be used to screen histone modifications prior to conducting more extensive genome sequencing approaches. This protocol describes a flow cytometry-based method to detect global HPTMs and can be conducted using cells in culture or isolated cells from in vivo tissues. We present example data from isolated mouse brain microglia to demonstrate the sensitivity of the assay to detect global shifts in HPTMs in response to a bacteria-derived immune stimulus (lipopolysaccharide). This protocol allows for the rapid and quantitative assessment of HPTMs and can be applied to any transcriptional or epigenetic regulator that can be detected by an antibody.

Author Spotlight: Enhancements in Gene Expression Regulation Research

This work describes a protocol for the quantification of global histone modifications using intranuclear flow cytometry in isolated brain microglia. The work also contains the microglia isolation protocol that was used for data collection.

Gene expression control occurs partially by modifications in chromatin structure, including the addition and removal of posttranslational modifications to ...

Neuroscience

Improving the Accuracy of Flow Cytometric Assessment of Mitochondrial Membrane Potential in Hematopoietic Stem and Progenitor Cells Through the Inhibition of Efflux Pumps

As cellular metabolism is a key regulator of hematopoietic stem cell (HSC) self-renewal, the various roles played by the mitochondria in hematopoietic homeostasis have been extensively studied by HSC researchers. Mitochondrial activity levels are reflected in their membrane potentials (&#916;&#936;m), which can be measured by cell-permeant cationic dyes such as TMRM (tetramethylrhodamine, methyl ester). The ability of efflux pumps to extrude these dyes from cells can limit their usefulness, however. The resulting measurement bias is particularly critical when assessing HSCs, as xenobiotic transporters exhibit higher levels of expression and activity in HSCs than in differentiated cells. Here, we describe a protocol utilizing Verapamil, an efflux pump inhibitor, to accurately measure &#916;&#936;m across multiple bone marrow populations. The resulting inhibition of pump activity is shown to increase TMRM intensity in hematopoietic stem and progenitor cells (HSPCs), while leaving it relatively unchanged in mature fractions. This highlights the close attention to dye-efflux activity that is required when &#916;&#936;m-dependent dyes are used, and as written and visualized, this protocol can be used to accurately compare either different populations within the bone marrow, or the same population across different experimental models.

Xenobiotic efflux pumps are highly active in hematopoietic stem and progenitor cells (HSPCs) and cause extrusion of TMRM, a mitochondrial membrane potential fluorescent dye. Here, we present a protocol to accurately measure mitochondrial membrane potential in HSPCs by TMRM in the presence of Verapamil, an efflux pump inhibitor.

As cellular metabolism is a key regulator of hematopoietic stem cell (HSC) self-renewal, the various roles played by the mitochondria in hematopoietic ...

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