The authors would like to thank the efforts of Palak Sekhri, Hussam Alkhalaileh, Hsiaochi Chang, and Justin Lyeberger for their experimental support. This work was supported by the Pelotonia Fellowship Program. Any opinions, findings, and conclusions expressed in this material are those of the author(s) and do not necessarily reflect those of the Pelotonia Fellowship Program.&#34;

1. Preparation of IdU stocks
<ol>
	<li>Dissolve 5-iodo-2&#8217;-deoxyuridine (IdU) in DMSO to a concentration of 50 mM. Sterile filter, aliquot into 10-50 &#181;L tubes, and store at -80 &#176;C</li>
	<li>Remove IdU from the freezer, and thaw at room temperature. Dilute IdU in RPMI-1640 to make a working solution at a final concentration of 1 mM. Pipette up and down or vortex to mix.
	<ol>
		<li>Typically, dilute the concentrated IdU into the media in which the cells are being cultured (e.g. DMEM, IMDM, etc.) or have diluted it into PBS for addition directly to peripheral blood or bone marrow aspirate samples. This pre-dilution step facilitates mixing of the DMSO with the aqueous media of the cells of interest. 
		NOTE: The final concentration of IdU during incubation should be 10 &#181;M; a solution of 1 mM will can be added at a ratio of 10 &#181;L to every 1 mL of media.</li>
	</ol>
	</li>
</ol>
2. IdU incubation and sample preservation
<ol>
	<li>Maintain samples in a humidified 37 &#176;C incubator. Remove the sample from the incubator and move the sample into a biosafety hood.</li>
	<li>Add 10 &#181;L of 1 mM IdU to every 1 mL of sample.
	<ol>
		<li>For a 6-well plate, add 30 &#181;L of 1 mM IdU to the 3 mL of culture media in each well. IdU can also be used directly in bone marrow aspirates as well as murine studies4.</li>
	</ol>
	</li>
	<li>Place the sample back into the incubator at 37 &#176;C for 10-15 min. Maintain cells under the optimal growth conditions of interest during IdU exposure in order to get the most accurate measurement of S-phase.</li>
	<li>After the IdU incubation, remove the sample and transfer to a conical tube.</li>
	<li>Spin the sample at 400 x g for 10 min at room temperature.</li>
	<li>Aspirate the supernatant and resuspend in 200 &#181;L of PBS.
	<ol>
		<li>If needed, perform a live/dead stain (using cisplatin) at this step to mark dead cells before fixation and freezing. 
		NOTE: Rhodium live/dead staining does not perform well after methanol permeabilization, so it is not recommended for use in cell cycle analyses.</li>
	</ol>
	</li>
	<li>Add 18.75 &#181;L of 16% paraformaldehyde (PFA) to the PBS for a final concentration of 1.5% PFA. Incubate at room temperature for 10 min. Spin the sample down at 400 x g for 10 min at room temperature.</li>
	<li>Aspirate the PBS/PFA solution and re-suspend the sample in 500 &#181;L of Cell Staining Media (CSM; 1x PBS with 0.5% BSA and 0.02% sodium azide) + 10% DMSO prior to freezing.
	<ol>
		<li>If using commercial Proteomic Stabilizer, add 280 &#181;L of Proteomic Stabilizer to sample re-suspended in 200 &#181;L of PBS (1:1.4). Incubate samples at room temperature for 10 min and then place directly into the -80 &#176;C. 
		NOTE: IdU has been shown to incorporate effectively within 10-15 min incubation at 37 &#176;C. IdU incubations longer than 10-15 min will progressively reduce resolution of the S and G2-phase populations, as IdU-labeled cells leave S phase and progress to G2 or M phase. We have also observed that long-term incubation with IdU can cause cell death and cell cycle artifacts. The subsequent cell processing and antibody staining following IdU incorporation is sufficient to wash away residual IdU that was not incorporated into S-phase cells. We have not observed significant Iodine background when using the in vitro protocol described here; however, we have very rarely observed iodine contamination in clinical samples. This may occur from medical procedures, such as iodine contrast in a CT scan, or from iodine-containing pharmaceuticals. Should large amounts of IdU background be observed, the sample should not be run to avoid damage to the mass cytometer&#8217;s detector.</li>
	</ol>
	</li>
</ol>
3. Staining samples for mass cytometry
<ol>
	<li>Remove the samples from the -80 &#176;C and allow to thaw before surface staining.
	<ol>
		<li>If using the SmartTube method of fixation, thaw the samples at 0-4 &#176;C to avoid additional fixation as the samples warm up.</li>
	</ol>
	</li>
	<li>After the samples are thawed, transfer approximately 1-2 million cells into a 5 mL FACS tube.</li>
	<li>Centrifuge the FACS tube at 600 x g for 5 min, and fill the FACS tube with cell staining media (CSM) to wash the cells. Repeat one additional time.
	<ol>
		<li>If cells are known to stick together, add 400 U/mL of heparin to CSM washes in order to prevent cell to cell contact but this is not strictly necessary.</li>
	</ol>
	</li>
	<li>Incubate the cells with FC-blocking agent, 5 &#181;L of the agent per 100 &#181;L of cells, for 10 min at room temperature.</li>
	<li>Prepare a mixture of antibodies that will stain the surface, or extracellular portion, of the cells. The total staining mixture will amount to 100 &#181;L per 1-2 million cells in each test. The staining mixture will be balanced accordingly with CSM and heparin in the cocktail and FACS tube. 
	NOTE: Addition of CSM at this step will also reduce nonspecific staining artifacts8. This staining mixture is entirely dependent on targets of interest and surface phenotype (e.g., a study involving T-cells will use a surface mixture of CD45, CD3, CD4, CD8, etc.). A detailed protocol of sample processing and staining can be found in Behbehani and McCarthy et al.9,10.</li>
	<li>Add the surface staining mixture to the cells and incubate at room temperature with continuous shaking for 30-60 min.</li>
	<li>After staining, fill the FACS tube with CSM, and spin down at 600 x g for 5 min.</li>
	<li>Wash two more times with CSM, spinning the sample at 600 x g for 5 min and aspirating each CSM wash.</li>
	<li>Fix the extracellular antibodies by adding 1 mL of PBS with 10% CSM and 1.5% PFA.</li>
	<li>Fill the FACS tube containing the PBS/CSM/PFA mixture with CSM. Spin down at 600 x g for 5 min and aspirate the supernatant.</li>
	<li>Add methanol at -20 &#176;C.</li>
	<li>Vortex the sample for 1-2 min to achieve a single cell suspension and verify that all cell clumps have been re-suspended.</li>
	<li>While the sample is vortexing slowly, rapidly add 1 mL of ice-cold methanol using a 1,000 &#181;L pipette with a filter tip.</li>
	<li>Hold the FACs tube up to the light and make sure there are no visible clumps; cloudiness is to be expected. Any clumps will render the sample unusable for subsequent MCM analysis.</li>
	<li>Store the sample at -20 &#176;C for 10-20 min.</li>
	<li>Prepare the intracellular staining mixture during this time. The intracellular staining mixture will be dependent on targets of interest. For cell cycle analysis, include CyclinB1, pRb, Ki67, and pHH3 in this staining mixture, but other intracellular markers can be added as needed.</li>
	<li>After 10-20 min at -20 &#176;C, remove the sample, add 1.5 mL of PBS and fill the remainder with CSM.</li>
	<li>Centrifuge the sample 600 x g for 5 min, and aspirate the supernatant.</li>
	<li>Wash two more times with CSM, spinning the sample down at 600 x g for 5 min and aspirating the supernatant each time.</li>
	<li>After the last CSM wash, centrifuge the sample and leave a residual volume of approximately 50 &#181;L.</li>
	<li>Add the prepared antibody mixture (typically add 50 &#181;L of antibody staining cocktail to achieve a final staining volume of 100 &#181;L) to the sample and incubate on a shaking platform for 30 to 60 min at room temperature.</li>
	<li>After staining add CSM and centrifuge at 600 x g for 5 min.</li>
	<li>Aspirate the CSM, wash again with CSM, spinning at 600 x g for 5 min, aspirating the CSM, then add PBS.</li>
	<li>After the completion of intracellular staining, place cells into an intercalator solution that fixes the antibodies to the cells and stains the DNA of each cells to enable identification. The intercalator solution contains nonisotopically pure iridium intercalator (pentamethylcyclopentadienyl-Ir(III)-dipyridophenazine) added from the manufacturer&#8217;s stock solution at a concentration of 500 &#181;M. Dilute the Iridium stock 1:4000 in a solution of PBS and 1.5% PFA. Add the iridium intercalator solution at 100-200 &#181;L per million cells in order to stain evenly and prevent overstaining. 
	NOTE: The iridium in this intercalator solution is intended to identify cells for singlet gating, it should not be used for live/dead stains. If live/dead stains are desired they need to be performed before fixation as noted above and in McCarthy et al.9.</li>
	<li>Store the samples in intercalator solution in a 4 &#176;C refrigerator for up to two weeks before sample acquisition on the CyTOF.</li>
</ol>
4. Mass cytometer operation
NOTE: Mass cytometry operation can be machine specific. It is always advisable to check the CyTOF user&#8217;s manual before operation. Additionally, there are currently two JoVE articles dealing with machine start up and maintenance9,11.
<ol>
	<li>Check the nebulizer for any clogs, cracks, and other irregularities before operating the mass cytometer.</li>
	<li>Connect the nebulizer to the cytometer and begin the warmup procedure. Do not start the mass cytometer without the nebulizer in place.</li>
	<li>Run water through the sample lines once the mass cytometer has finished warming up. The spray chamber needs to reach approximately 200 &#176;C before performing tuning or sample analysis.</li>
	<li>Run water for 5-10 min. After 5-10 min, load the tuning solution and select the tuning manager. The tuning solution is a solution containing fixed concentrations of metals and used to optimize the mass cytometer before sample acquisition</li>
	<li>In the tuning manager, select Preview once the tuning solution has reached a steady state hit record to begin the automated tuning process.</li>
	<li>Once tuning is finished load the sampler with water and allow water to run through the sample lines during sample processing. Detailed protocol for daily cytometer operation and tuning can be found at Leipold11.</li>
	<li>Occasionally, the automated tuning will not tune to optimal machine performance. Repeat the tuning procedure to correct this.</li>
	<li>Wash the sample with CSM once and with pure deionized water twice before sample acquisition. Washing with water is important to remove residual salt from the PBS/CSM.</li>
	<li>Check the sensitivity and sample flow using manufacturer supplied equilibration beads, polystyrene beads loaded with known metal concentrations.</li>
	<li>Change the acquisition mode from tuning to event capture mode. Set the time limit to stop acquisition at 120 s. Wait 45 s before selecting Record.</li>
	<li>The mass cytometer will stop sample acquisition automatically after 120 seconds. Use the rain plot viewer to check Eu151 and Eu153 intensity.</li>
	<li>Dilute equilibration beads in pure deionized water at a 1:20 ratio.</li>
	<li>Before sample acquisition check the experiment manager. Use the experiment manager to assign names to channels and to add channels to be recorded.
	<ol>
		<li>Make sure the 127-I channel is added if using IdU.</li>
		<li>Note that it is essential to set the mass cytometer to measure the needed parameters (e.g., IdU) prior to sample acquisition. If channels are not selected in advance, data will not be collected from any unselected channel and cannot be recovered.</li>
	</ol>
	</li>
	<li>Dilute the cells to a concentration of approximately 1-2 x 106/mL using the 1:20 pure deionized water and equilibration bead mixture. Pass the cells through the filter topped FACS tube in order to remove any residual clumps.</li>
	<li>Load the sample and change the acquisition time.</li>
	<li>Press Preview and wait for event count per second to stabilize.
	<ol>
		<li>Do not run events in excess of 400 events per second, this will lead to significant amounts of doublets and debris. We typically collect at least 20,000 to 50,000 cell events, but the optimal number will depend on the experimental design. Staining of up to 2 million cells will typically yield 300,000 to 400,000 cell events. Note that not all events will be cells (there will be debris and bead events included in the event count).</li>
	</ol>
	</li>
	<li>Once sample acquisition is done load a washing solution, start sample induction and run for 5-10 minutes. After 5-10 minutes stop sample induction and run water for 10-20 minutes. Wash solution is a weak solution of hydrofluoric acid designed to strip residual metal from the sample lines.</li>
	<li>Shut down the mass cytometer and remove the nebulizer. The nebulizer will be hot, take care during handling.</li>
</ol>
5. Data analysis
<ol>
	<li>In order to remove beads and also to correct for signal drift during sample acquisition, normalize the FCS files using Fluidigm software or the application developed by Finck12.</li>
	<li>Upload the FCS to Cytobank or other flow cytometry analysis software. FCS files can be used in any compatible software, for the purposes of this protocol all gating and further analysis has been done in Cytobank13.</li>
	<li>Before cell cycle gates can be drawn, exclude any doublets or cell debris from downstream analysis, this can be done by using the biaxial plot of Event Length vs 191-Ir (Figure 1a). Cells will form a distinct, bright population Irhigh that can be used to exclude doublets and debris. This is the singlet gate. This gating method typically removes about 50-60% of doublet cell events, so additional strategies may be required to remove remaining doublet cell events.
	<ol>
		<li>Change the event length scale (minimum and maximum) to make the cells appear more prominent to aid in singlet gating.</li>
		<li>Further remove doublets and debris by using Gaussian parameters, Residual and Offset. A higher Residual with lower Offset is also debris and doublets, and gating around this population can further remove doublets and debris (Figure 1b,c).</li>
	</ol>
	</li>
	<li>S-phase gating &#8211; S-phase is the easiest gate to draw but also the most important. Draw this gate using a biaxial plot of IdU vs pRb, Ki67, or cyclinB1. S-phase IdU+ cells will form a distinct population when looking at these biaxial plots (Figure 2b).</li>
	<li>G0/G1-phase, G2/M-phase gating &#8211; Establish the G0/G1 and G2/M phase gates on the IdU vs CyclinB1 plot and the use of IdU incorporation is crucial to establish the boundary between the G0/G1 and G2/M phase gates. G0/G1-phase will be CyclinB1low/IdU- and G2/M-phase will be CyclinB1high/IdU-. Good CyclinB1 staining will show a natural population between the G0-G1 and G2-M populations; however, this will vary across sample and cell types under experimental conditions. In experimental conditions where the cell cycle distribution may be affected and there is less separation between the CyclinB1 G0/G1-phase and G2/M-phase utilizing the S-phase will allow consistent gating for particular cell types in each specific experiment. This method is detailed below.
	<ol>
		<li>Plot only the S-phase cells on the CyclinB1 vs IdU to help establish the separation between G0/G1-phase and G2/M-phase. Draw a gate on the CyclinB1high population and adjust until approximately the top 5% of the S-phase population is inside the gate (Figure 2c). This establishes the breakpoint between the G0/G1 and G2/M phase gates (Figure 2e,f). The active population will be changed to the population of interest and the portion residing inside the previous gate will be the G2/M-phase population while the remainder will be the G0/G1-phase population.</li>
	</ol>
	</li>
	<li>G0-phase gating &#8211; Establish the G0-phase on the pRb vs IdU plot. The G0-phase will be represented by a pRblow/IdU- population. The active cycling population will have high expression of pRb and IdU incorporation, the G0-phase gate can be drawn on this boundary as it typically expresses at two distinct populations (Figure 2g,i).
	<ol>
		<li>Define the G0-phase by making the S-phase population drawn previously (Figure 2b) the active population and drawing a gate incorporating the top 90-100% of the pRbhigh population. This is the pRb+ cycling population (Figure 2i), the pRblow population outside this gate is the G0 population (Figure 2j).</li>
		<li>If pRb is unavailable or not able to be recorded, use Ki67 vs IdU to establish the G0-phase population. Drawing a gate representing the majority of the S-phase population and using that gate as the boundary for the Ki67 vs IdU the remainder of the population will be the G0-phase (Figure 3a).</li>
	</ol>
	</li>
	<li>M-phase gating &#8211; Establish the M-phase in the IdU vs pH3 biaxial plot. The M-phase represents a very small fraction of cells and is gated on the pH3high population (Figure 2d).</li>
	<li>IdU incorporation failed or was not possible &#8211; If IdU is unavailable, define cell cycling and not cycling fractions using Ki67 and pRb. Ki67 and pRb, in normal conditions, form two distinct populations a Ki67high/pRbhigh and a Ki67low/pRblow. The double positive population represents the active cycling population, correlating to G1-phase, S-phase, G2-phase, and M-phase. The double low population represents the not cycling population, correlating to the G0-phase (Figure 3b). 
	NOTE: It is not possible to delineate each individual phase using the Ki67 vs pRb but experimental effects on the relative cycling/not cycling populations can be determined.</li>
	<li>Cell cycle analysis &#8211; Once the gates have been established, export the numerical values from the gates for further analysis. The percentages in each cycle can be achieved by subtracting the single populations from the combined populations. The G0-phase, drawn on the pRblowIdUlow, gate percentage can be subtracted from the G0/G1-phase, drawn on CyclinB1lowIdUneg, to find the G1-phase percentage. Similarly the G2-phase percentage is derived from the subtraction of the M-phase gate from the G2/M-phase gate. This will generate numerical values for each individual cell cycle phase; G0, G1, S, G2, and M. The numerical values generated for each individual cell cycle phase can be used for further analysis such as graphing and statistical analysis.</li>
</ol>

<ol>
	<li>Ornatsky, O., Baranov, V. I., Bandura, D. R., Tanner, S. D., Dick, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Multiple+cellular+antigen+detection+by+ICP-MS.">Multiple cellular antigen detection by ICP-MS.</a> Journal of Immunological Methods. 308 (1-2), 68-76 (2006).</li><li>Ornatsky, O. I., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Study+of+cell+antigens+and+intracellular+DNA+by+identification+of+element-containing+labels+and+metallointercalators+using+inductively+coupled+plasma+mass+spectrometry.">Study of cell antigens and intracellular DNA by identification of element-containing labels and metallointercalators using inductively coupled plasma mass spectrometry.</a> Analytical Chemistry. 80 (7), 2539-2547 (2008).</li><li>Behbehani, G. K., Bendall, S. C., Clutter, M. R., Fantl, W. J., Nolan, G. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Single-cell+mass+cytometry+adapted+to+measurements+of+the+cell+cycle.">Single-cell mass cytometry adapted to measurements of the cell cycle.</a> Cytometry A. 81 (7), 552-566 (2012).</li><li>Raval, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Reversibility+of+Defective+Hematopoiesis+Caused+by+Telomere+Shortening+in+Telomerase+Knockout+Mice.">Reversibility of Defective Hematopoiesis Caused by Telomere Shortening in Telomerase Knockout Mice.</a> PLoS One. 10 (7), 0131722 (2015).</li><li>Behbehani, G. K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Mass+Cytometric+Functional+Profiling+of+Acute+Myeloid+Leukemia+Defines+Cell-Cycle+and+Immunophenotypic+Properties+That+Correlate+with+Known+Responses+to+Therapy.">Mass Cytometric Functional Profiling of Acute Myeloid Leukemia Defines Cell-Cycle and Immunophenotypic Properties That Correlate with Known Responses to Therapy.</a> Cancer Discovery. 5 (9), 988-1003 (2015).</li><li>Kimmey, S. C., Borges, L., Baskar, R., Bendall, S. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Parallel+analysis+of+tri-molecular+biosynthesis+with+cell+identity+and+function+in+single+cells.">Parallel analysis of tri-molecular biosynthesis with cell identity and function in single cells.</a> Nature Communications. 10 (1), 1185 (2019).</li><li>Rabinovitch, P. 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Dr. Behbehani receives travel support from Fluidigm. Fluidigm has also purchased reagents and materials for lab use.

The examples presented here demonstrate how to use an MCM platform to analyze cell cycle distribution. It has also been demonstrated that cell cycle analysis is sensitive to experimental conditions such as time and temperature, which is an important consideration researchers must take when considering MCM for their cell cycle analysis14. Samples left in storage for a short period of time, no longer than an hour, will have IdU incorporation comparable to their normal state. Samples in a closed system for long periods of time, approximately 2 hours, will have reduced IdU incorporation, however, the relative cycling and non-cycling fractions will not change allowing coarse cell cycle analysis. Cryogenic storage and subsequent thawing are disruptive to normal cell cycle distribution for a significant period of time. Cryogenic storage has been noted previously to disrupt protein and RNA distribution but has only recently been shown to disrupt cell cycle14,15,16,17. Taken together these indicate that if long storage times are anticipated or cryogenic preservation of samples it would be better to stain the cells with IdU before storage or cryogenic storage, fix the cells and store them until analysis can be done. As cell cycle analysis by MCM does not require live cells this would enable researchers to bank precious samples and perform accurate downstream cell cycle analysis.
Cell cycle analysis by MCM is a robust system capable of deep interrogation of experimental models. Due to MCM high parameter count, approximately 40-50 mass channels, cell cycle analysis can be compounded with other intracellular or extracellular markers bypassing the need for sorting of cells based on immunophenotype which may cause significant cell cycle effects to be lost. The high parameter nature of MCM lends itself to examining effects in high-dimensional mapping applications such as SPADE and viSNE. While SPADE and viSNE are typically used to define immunophenotypic populations which can then be examined for cell cycle changes it would also be possible to map on cell cycle markers. Depending on experimental conditions mapping cell cycle markers in a high-dimensional space can show cell cycle correlation with drug effect or what immunophenotypic populations may be localizing to each cycle state3,5. While MCM may be limited by the lack of DNA binding fluorescent dyes this is compensated by direct IdU incorporation during S-phase cells and intracellular cell cycle proteins can be used to determine cell cycle state. These cell cycle proteins can also help discriminate between stages of cell cycle arrest that would otherwise appear as 3N or 4N in traditional flow using DNA binding dyes. Such highly parametric systems are not without disadvantages however, and it is sensitive to disruptions in cell cycle. We have shown that long storage times and cryogenic storage can significantly affect cell cycle distribution. This is especially important when trying to rationalize experimental effects for drugs that may affect cell cycle distribution. Treatment of drugs designed to affect cell cycle on frozen primary samples may give false data on cell cycle effect when used immediately after thawing from cryogenic storage. MCM is a versatile technology for cell cycle analysis that can be applied to a number of experimental models and is especially suited to deep profiling of heterogeneous systems. As with other highly parametric methods it is necessary to have a carefully designed experiment with appropriate considerations for how processing and experimental effects will affect cell cycle analysis.

Mass cytometry enables detection of approximately 40 parameters by taking advantage of the high resolution and quantitative nature of mass spectroscopy. Metal-labeled antibodies are used instead of fluorophore conjugated antibodies that allow for a higher number of channels and produce minimal spillover1,2. MCM has advantages and disadvantages in regard to cell cycle analysis in comparison to flow cytometry. One major advantage of MCM is that the large number of parameters enables the simultaneous measurement of cell cycle state across a large number of immunophenotypically distinct T-cell types in highly heterogeneous samples. MCM has been successfully used to measure the cell cycle state during normal hematopoiesis in human bone marrow3 and transgenic murine models of telomerase deficiency4. Analysis of cell cycle state in acute myeloid leukemia (AML) showed that cell cycle correlated to known responses to clinical therapies, providing an in vivo insight into functional characteristics that can inform therapy selections5. A second advantage of mass cytometric cell cycle analysis is the ability to measure a large number of other functional markers that may be correlated with cell cycle state. Recent work has been able to correlate protein and RNA synthesis with cell cycle state through the use of IdU and metal tagged antibodies to BRU and rRNA6. This kind of highly parametric analysis measuring cell cycle state across numerous populations in a continuum of differentiation would be nearly impossible with current flow cytometry technology. The major disadvantage of MCM is the lack of comparable DNA or RNA stains as those used in fluorescent flow cytometry (e.g., DAPI, Hoechst, Pyronin Y, etc.). Fluorescent dyes can give relatively precise measurements of DNA and RNA content, but this precision is only possible due to the changes in the fluorescent properties of these dyes that occur upon intercalation between nucleotide bases. MCM analysis is thus unable to measure DNA or RNA content with similar precision. Instead, mass cytometric cell cycle analysis relies on measurements of proteins related to cell cycle state such as cyclin B1, phosphorylated retinoblastoma protein (pRb), and phosphorylated Histone H3 (pHH3) combined with direct measurement of the iodine atom from IdU incorporation into S-phase cells. These two measurement approaches yield highly similar results during normal cellular proliferation, but can potentially be discordant when cell cycle progression is disrupted.
Measurement of the number of cells in each cell cycle phase is important in understanding normal cell cycle development as well as cell cycle disruption, which is commonly observed in cancers and immunological diseases. MCM provides reliable measurement of extracellular and intracellular factors using metal-tagged antibodies; however, measurement of the S-phase was limited as the iridium-based DNA intercalator was unable to differentiate between 2N and 4N DNA. In order to define cell cycle phases, Behbehani developed a method that utilizes IdU with a mass of 127, which falls within the range of the mass cytometer and allows direct measurement of cells in S-phase3. This direct measurement circumvents the need for secondary antibodies or use of DNA denaturing agents such as acid or DNase. In conjunction with intracellular cycling markers, it allows high resolution of cell cycle distribution in experimental models.
This protocol adapts cell cycle measurements from common flow cytometry protocols for MCM. Our methods provide a convenient and simple way to include cell cycle parameters. IdU incorporation of in vitro samples requires only 10 to 15 minutes of incubation at 37 &#176;C, which is shorter than most BrdU staining protocols that recommend incubation times of several hours3,7. IdU and BrdU incorporated samples can be fixed using a proteomic stabilizer and then stored for some time in a -80 &#176;C freezer. This allows large numbers of IdU stained samples to be archived for batch analysis without reduction in sample quality.

<table>
	<tbody>
		<tr>
			<td>Bovine Serum Albumin (BSA)</td>
			<td>Sigma</td>
			<td>A3059</td>
			<td>Component of CSM</td>
		</tr>
		<tr>
			<td>Centrifuge</td>
			<td>Thermo Scientific</td>
			<td>75-217-420</td>
			<td>Sample centrifugation</td>
		</tr>
		<tr>
			<td>Cleaved-PARP (D214)</td>
			<td>BD Biosciences</td>
			<td>F21-852</td>
			<td>Identification of apoptotic cells</td>
		</tr>
		<tr>
			<td>Cyclin B1</td>
			<td>BD Biosciences</td>
			<td>GNS-1</td>
			<td>G2 Resolution</td>
		</tr>
		<tr>
			<td>Dimethylsulfoxide (DMSO)</td>
			<td>Sigma</td>
			<td>D2650</td>
			<td>Cryopreservative</td>
		</tr>
		<tr>
			<td>EQ Four Element Calibration Beads</td>
			<td>Fluidigm</td>
			<td>201078</td>
			<td>Internal metal standard for CyTOF performance</td>
		</tr>
		<tr>
			<td>FACS Tube w/ mesh strainer</td>
			<td>Corning</td>
			<td>08-771-23</td>
			<td>Cell strainer to remove clumps/debris before CyTOF run</td>
		</tr>
		<tr>
			<td>Fetal Bovine Serum (FBS)</td>
			<td>VWR</td>
			<td>97068-085</td>
			<td>Cell culture growth supplement</td>
		</tr>
		<tr>
			<td>Helios</td>
			<td>Fluidigm</td>
			<td></td>
			<td>CyTOF System/Platform</td>
		</tr>
		<tr>
			<td>Heparin</td>
			<td>Sigma</td>
			<td>H3393</td>
			<td>Staining additive to prevent non-specific staining</td>
		</tr>
		<tr>
			<td>IdU (5-Iodo-2&#8242;-deoxyuridine)</td>
			<td>Sigma</td>
			<td>I7125</td>
			<td>Incorporates in S-phase</td>
		</tr>
		<tr>
			<td>Ki-67</td>
			<td>eBiosciences</td>
			<td>SolA15</td>
			<td>Confirmation of G0/G1</td>
		</tr>
		<tr>
			<td>MaxPar Multi Label Kit</td>
			<td>Fluidigm</td>
			<td>201300</td>
			<td>Metal labeling kit, attaches metals to antibodies</td>
		</tr>
		<tr>
			<td>Microplate Shaker</td>
			<td>Thermo Scientific</td>
			<td>88880023</td>
			<td>Mixing samples during staining</td>
		</tr>
		<tr>
			<td>Paraformaldehyde (PFA)</td>
			<td>Electron Microscopy Services</td>
			<td>15710</td>
			<td>Fixative</td>
		</tr>
		<tr>
			<td>pentamethylcyclopentadienyl-Ir(III)-dipyridophenazine</td>
			<td>Fluidigm</td>
			<td>201192</td>
			<td>Cell identification during CyTOF acquisition</td>
		</tr>
		<tr>
			<td>p-H2AX (S139)</td>
			<td>Millipore</td>
			<td>JBW301</td>
			<td>Detection of DNA damage</td>
		</tr>
		<tr>
			<td>p-HH3 (S28)</td>
			<td>Biolegend</td>
			<td>HTA28</td>
			<td>M-phase Resolution</td>
		</tr>
		<tr>
			<td>Phosphate Buffered Saline (PBS)</td>
			<td>Gibco</td>
			<td>14190-144</td>
			<td>Wash solution for cell culture and component of fixative solution</td>
		</tr>
		<tr>
			<td>p-Rb (S807/811)</td>
			<td>BD Biosciences</td>
			<td>J112906</td>
			<td>G0/G1 Resolution</td>
		</tr>
		<tr>
			<td>Proteomic Stabilizer</td>
			<td>SmartTube Inc</td>
			<td>PROT1</td>
			<td>Sample fixative</td>
		</tr>
		<tr>
			<td>RPMI 1640</td>
			<td>Gibco</td>
			<td>21870-076</td>
			<td>Cell culture growth medium</td>
		</tr>
		<tr>
			<td>Sodium Azide</td>
			<td>Acros Organics</td>
			<td>AC447810250</td>
			<td>Component of CSM/Antibody buffer, biocide</td>
		</tr>
	</tbody>
</table>

use of the pyrimidine analog, 5-iodo-2&prime;-deoxyuridine (idu) with cell cycle markers to establish cell cycle phases in a mass cytometry platform

The regulation of cell cycle phase is an important aspect of cellular proliferation and homeostasis. Disruption of the regulatory mechanisms governing the cell cycle is a feature of a number of diseases, including cancer. Study of the cell cycle necessitates the ability to define the number of cells in each portion of cell cycle progression as well as to clearly delineate between each cell cycle phase. The advent of mass cytometry (MCM) provides tremendous potential for high throughput single cell analysis through direct measurements of elemental isotopes, and the development of a method to measure the cell cycle state by MCM further extends the utility of MCM. Here we describe a method that directly measures 5-iodo-2&#8242;-deoxyuridine (IdU), similar to 5-bromo-2&#180;-deoxyuridine (BrdU), in an MCM system. Use of this IdU-based MCM provides several advantages. First, IdU is rapidly incorporated into DNA during its synthesis, allowing reliable measurement of cells in the S-phase with incubations as short as 10-15 minutes. Second, IdU is measured without the need for secondary antibodies or the need for DNA degradation. Third, IdU staining can be easily combined with measurement of cyclin B1, phosphorylated retinoblastoma protein (pRb), and phosphorylated histone H3 (pHH3), which collectively provides clear delineation of the five cell cycle phases. Combination of these cell cycle markers with the high number of parameters possible with MCM allow combination with numerous other metrics.

Utilizing HL-60 cells and a human bone marrow aspirate it is possible to show how experimental conditions can affect cell cycle distribution and analysis. First, the gating strategy must be established to demonstrate how the cell cycle phases are derived. In Figure 1 we show the establishment of the singlet gate, which is important in separating cellular debris and doublets, establishing a single cell population. For cell lines the singlet gate is all that is needed to move onto cell cycle analysis (Figure 2a). For human samples immunophenotypic populations typically need to be established prior to cell cycle analysis, since the exact boundaries of each cell cycle gate can vary across different cell types. Once the populations have been established (usually by gating on surface markers that define that population) the cell cycle gates will then need to be established. Figure 2b demonstrates the establishment of the S-phase on the IdU vs CyclinB1 biaxial plot. This plot is also used to establish the boundary of the G2/M-phase gate (Figure 2f). Once the G2/M-phase is established the remainder is the G0/G1-phase gate (Figure 2f). The IdU vs pRb is used to establish the pRb+ cycling population first by establishing a gate on IdU incorporating cells (Figure 2g,i). The pRb+/IdUneg population outside this gate is the G0-phase (Figure 2j). M-phase is established on the IdU vs pHH3 where M-phase cells express high levels of pHH3 and exhibit no IdU incorporation (Figure 2k). In the event that pRb is not included the G0-phase can be replicated using Ki67 in a similar way to the method described above (Figure 3a). If IdU incorporation failed or was not performed it is still possible to determine relative cycling fractions using Ki67 and pRb. By using the Ki67 and pRb biaxial two distinct populations form, a pRb+/Ki67+ double positive and a pRblow/Ki67low population. The double positive population represents cells in cycle, while the low represents cells not in cycle (Figure 3b). Using IdU incorporating cells and pRblow cells with no IdU incorporation we show that the S-phase is primarily in the pRb+/Ki67+ population while the G0-phase is primarily in the pRblow/Ki67low population.
Cell cycle analysis relies on good experimental technique especially during the IdU incubation step. While IdU incorporation is flexible (being applicable in cell culture, bone marrow aspirates, and even murine studies), it necessary to perform IdU incorporation and fixation without disrupting the cell cycle state of experimental interest. IdU labeling and thus downstream cell cycle analysis can significantly be affected by time and temperature as indicated by Figure 4. Cells that remain too long in enclosed vessels or at that might be encountered in sample shipment or sample transport between locations, will have reduced S-phase fraction and not be accurate for cell cycle analysis (Figure 4a). Short time periods though, those under an hour in total, will have normal cell cycle distribution indicating that quick transport may not negatively cell cycle analysis (Figure 4b). Another important modifier is cryopreservation that is routinely used in most laboratories. When examining cell cycle state in cryopreserved cells a long equilibration period may be required before cells return to active cell cycling, which may still not reflect the pre-cyropreservation cell cycle state (Figure 4c).
Primary human samples are often composites of multiple different cell types, these different cell types can have different sensitivities to processing leading to different cell cycle gating. In two bone marrow aspirates that were IdU labeled immediately, stored for 30 minutes before IdU labeling, or cryogenically stored after Ficoll separation there are differences between each sample and population (Figure 5a,b). Two immunophenotypic populations were examined for differences in IdU incorporation; T-cells (CD45high/CD3high) and monoblasts (CD33+, HLADR+, CD11blow, CD14neg). With the correct combination of surface marks, it is possible to examine further immunophenotypic populations. In marrow #2 there was a noticeable T-cell activation effect after 30 minutes storage that was not seen in the monoblasts from the same patient (Figure 5b). Like cultured cells there were noticeable changes in IdU labeling after cryogenic storage that was also dependent on population. Marrow #1 had reduction in the T-cell population but increase in monoblasts IdU labeled fractions when compared to baseline (Figure 5a,b), Marrow #2 showed reduction in both T-cells and monoblasts when compared to baseline (Figure 5a,b). Frozen cells then require a notable incubation period before returning to normal cell cycle state and this can influence studies that rely on modifying cell cycle state or cell cycle state as a metric of drug or experimental effect.
Another benefit of MCM is the ability to discriminate cells in cell cycle arrest or that have abnormal cell cycle distribution. While DNA dyes commonly used in flow cytometry are able to discriminate between 2N and 4N DNA content, they are very bright, which can greatly complicate measuring other parameters from that laser. IdU, however, only takes one mass channel and has minimal spill over allowing for other markers to be used in cell cycle determination. MOLM13 cells that were irradiated show decreased IdU incorporation and decrease in M-phase when compared to control cells (Figure 6). Disruption of the normal cell cycle checkpoints might alter the apparent cell cycle state by MCM. Looking at pH2AX and cPARP populations in the non-irradiated cells the pH2AXlow and cPARPlow population shows normal cell cycle distribution while cells expressing higher levels of pH2AX or cPARP localize mainly in the G0/G1-phase which is expected (Figure 6a). In the irradiated cells the pH2AXlow and cPARPlow, however, the cells are almost entirely localized in the G0-phase, while the pH2AXhigh and cPARPlow cells show a cell cycle arrest phenotype with IdU incorporation and localization to the G0/G1-phase and G2-phase with an absence of M-phase. The pH2AXhigh and cPARPhigh cells also show cells incorporating some IdU and localizing to the G0/G1-phase indicative of radiation damage (Figure 6b).
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/60556/60556fig01.jpg" /> 
Figure 1: Establishing the singlet gates using 191-Ir by Event Length and also Gaussian parameters, Residual and Offset. 
The differences in T-cell (CD45+/CD3+) and S-phase (IdU+) between an ungated sample (a), an event length vs 191-Ir singlet gate (b), or a singlet gate combined with Gaussian parameters, residual and offset (c). Singlet gating removes debris, doublets, and beads shown in the loss of the pRbhigh population on the right corner of the biaxial. This singlet gate can be further optimized by including Gaussian parameters such as residual and offset, removing more debris. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/60556/60556fig01large.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/60556/60556fig02.jpg" /> 
Figure 2: The gating schema for establishing cell cycle gates for G0, G1, S, G2, and M phases using IdU, CyclinB1, pRb, and pHH3. 
The singlet gate is established to remove doublets and debris (a). The S-phase must be established (b), once the S-phase is established the IdU+ population can be used to establish the G2/M-phase boundary (c,d). The establishment of the G2/M-phase boundary establishes the bounds of the G0/G1-phase population (f). The pRb+ and G0-phase population are established on the IdU vs pRb biaxial. The IdU+ cells (h) are used to establish the boundary for the pRb+ population (i). The boundary of the pRb+ population establishes the boundary of the G0-phase population (j). The M-phase is established on pHH3+ cells that are IdU- (k). <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/60556/60556fig02large.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/60556/60556fig03.jpg" /> 
Figure 3: Establishing cell cycle gates without the use of pRb or without the use of IdU incorporation. 
Drawing the G0-phase can also be done using Ki-67 following the same gating strategy that was used with pRb, if pRb is not included in the experiment (a). If IdU incorporation failed or was not performed it possible to still recover the relative cell cycling fractions through the use of Ki67 and pRb. Ki67 and pRb double positive expression is correlative to cells in cycle as evidenced by demonstrating the IdU+ cells are found primarily in the double positive population (b). The Ki67 and pRb low population correlates with the G0-phase or not cycling population demonstrated by pRblow/IdUneg cells being found in the Ki67 and pRb low population. This method cannot discriminate individual cell cycle phases but can still be used to determine relative cycling fractions in experimental conditions. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/60556/60556fig03large.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/60556/60556fig04.jpg" /> 
Figure 4: Representative Figures of the effect of different storage conditions on the cell cycle distribution of HL-60 cells. 
Cells were incubated for an hour followed by an hour rest at the stated temperature conditions in sealed tubes (a). There are noticeable effects on cell cycle distribution when compared to the control. HL60 cells were kept in sealed tubes at room temperature for 30 minutes, a situation that may occur in a clinical setting, before IdU incorporation (b). Sealed tubes kept at room temperature for 30 minutes did not show appreciable cell cycle differences. The effect of cryogenic storage was investigated on cell cycle in HL60 cells, where a sample was taken before cryogenic storage and a sample taken after an hour rest following a week in cryogenic storage (c). One hour post thaw the cell cycle distribution is affected and cell cycle distribution does not return to normal until approximately a week following thaw. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/60556/60556fig04large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/60556/60556fig05.jpg" /> 
Figure 5: Processing can have an effect on patient samples and representative images are shown between two different patients showing the (a) T-cells (CD45high/CD3high) and (b) Monoblasts (CD33+, HLADR+, CD11blow, CD14neg). 
Between marrow one and marrow two it is clear that in marrow 2 there was a T-cell activation effect during the 30 minutes rest whereas marrow one had no such effect. Marrow one showed possible activation effect in the monoblasts population after 30 minutes while marrow two did not. In both marrows, however, it was clear that cryogenic storage impacted cell cycle distribution regardless of cell type. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/60556/60556fig05large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 6" class="xfigimg" src="/files/ftp_upload/60556/60556fig06.jpg" /> 
Figure 6: MOLM13 cells were either left as controls or irradiated using an X-ray irradiator at 10Gy. 
MOLM13 cells show the cell cycle distribution in four different populations of pH2AX and cPARP expression. Control cells show minimal pH2AX and cPARP staining, with normal cell cycle characteristics being shown in the pH2AXlow and cPARPlow population (a). While the irradiated cells show an abnormal cell cycle distribution with the majority of cycling cells being located in the pH2AXhigh and cPARPhigh, indicating cell cycle disruption (b). The non-damaged, pH2AXlow and cPARPlow, cells show a lack of cycling characteristics are primarily found in the G0-phase. Without these markers these cells would appear as 4N and 2N cells in normal flow cytometry possibly confounding downstream cell cycle analysis. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/60556/60556fig06large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

Watch this Scientific Journal Video about Use of the Pyrimidine Analog, 5-Iodo-2Ã¢â‚¬Â²-Deoxyuridine IdU with Cell Cycle Markers to Establish Cell Cycle Phases in a Mass Cytometry Platform at JoVE.com

Use of the Pyrimidine Analog, 5-Iodo-2&#8242;-Deoxyuridine IdU with Cell Cycle Markers to Establish Cell Cycle Phases in a Mass Cytometry Platform

This protocol adapts cell cycle measurements for use in a mass cytometry platform. With the multi-parameter capabilities of mass cytometry, direct measurement of iodine incorporation allows identification of cells in S-phase while intracellular cycling markers enable characterization of each cell cycle state in a range of experimental conditions.

Use of the Pyrimidine Analog, 5-Iodo-2&prime;-Deoxyuridine (IdU) with Cell Cycle Markers to Establish Cell Cycle Phases in a Mass Cytometry Platform

The regulation of cell cycle phase is an important aspect of cellular proliferation and homeostasis. Disruption of the regulatory mechanisms governing the ...

use-pyrimidine-analog-5-iodo-2-deoxyuridine-idu-with-cell-cycle

Nanyang Technological University

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Genetics

2.4K Views.  The Ohio State University. This protocol adapts cell cycle measurements for use in a mass cytometry platform. With the multi-parameter capabilities of mass cytometry, direct measurement of iodine incorporation allows identification of cells in S-phase while intracellular cycling markers enable characterization of each cell cycle state in a range of experimental conditions.

Video: Use of the Pyrimidine Analog, 5-Iodo-2′-Deoxyuridine IdU with Cell Cycle Markers to Establish Cell Cycle Phases in a Mass Cytometry Platform

High-Throughput Robotically Assisted Isolation of Temperature-sensitive Lethal Mutants in Chlamydomonas reinhardtii

Systematic identification and characterization of genetic perturbations have proven useful to decipher gene function and cellular pathways. However, the conventional approaches of permanent gene deletion cannot be applied to essential genes. We have pioneered a unique collection of ~70 temperature-sensitive (ts) lethal mutants for studying cell cycle regulation in the unicellular green algae Chlamydomonas reinhardtii1. These mutations identify essential genes, and the ts alleles can be conditionally inactivated by temperature shift, providing valuable tools to identify and analyze essential functions. Mutant collections are much more valuable if they are close to comprehensive, since scattershot collections can miss important components. However, this requires the efficient collection of a large number of mutants, especially in a wide-target screen. Here, we describe a robotics-based pipeline for generating ts lethal mutants and analyzing their phenotype in Chlamydomonas. This technique can be applied to any microorganism that grows on agar. We have collected over 3000 ts mutants, probably including mutations in most or all cell-essential pathways, including about 200 new candidate cell cycle mutations. Subsequent molecular and cellular characterization of these mutants should provide new insights in plant cell biology; a comprehensive mutant collection is an essential prerequisite to ensure coverage of a broad range of biological pathways. These methods are integrated with downstream genetics and bioinformatics procedures for efficient mapping and identification of the causative mutations that are beyond the scope of this manuscript.

High-Throughput Robotically Assisted Isolation of Temperature-sensitive Lethal Mutants in Chlamydomonas reinhardtii

Temperature-sensitive (ts) lethal mutants are valuable tools to identify and analyze essential functions. Here we describe methods to generate and classify ts lethal mutants in high throughput.

Systematic identification and characterization of genetic perturbations have proven useful to decipher gene function and cellular pathways. However, the ...

Rearing and Double-stranded RNA-mediated Gene Knockdown in the Hide Beetle, Dermestes maculatus

Advances in genomics have raised the possibility of probing biodiversity at an unprecedented scale. However, sequence alone will not be informative without tools to study gene function. The development and sharing of detailed protocols for the establishment of new model systems in laboratories, and for tools to carry out functional studies, is thus crucial for leveraging the power of genomics. Coleoptera (beetles) are the largest clade of insects and occupy virtually all types of habitats on the planet. In addition to providing ideal models for fundamental research, studies of beetles can have impacts on pest control as they are often pests of households, agriculture, and food industries. Detailed protocols for rearing and maintenance of D. maculatus laboratory colonies and for carrying out dsRNA-mediated interference in D. maculatus are presented. Both embryonic and parental RNAi procedures-including apparatus set up, preparation, injection, and post-injection recovery-are described. Methods are also presented for analyzing embryonic phenotypes, including viability, patterning defects in hatched larvae, and cuticle preparations for unhatched larvae. These assays, together with in situ hybridization and immunostaining for molecular markers, make D. maculatus an accessible model system for basic and applied research. They further provide useful information for establishing procedures in other emerging insect model systems.

Rearing and Double-stranded RNA-mediated Gene Knockdown in the Hide Beetle, Dermestes maculatus

Here, we present protocols for rearing an intermediate-germ beetle, Dermestes maculatus (D. maculatus) in the lab. We also share protocols for embryonic and parental RNAi and methods for analyzing embryonic phenotypes to study gene function in this species.

Advances in genomics have raised the possibility of probing biodiversity at an unprecedented scale. However, sequence alone will not be informative ...

Detection of Copy Number Alterations Using Single Cell Sequencing

Detection of genomic changes at single cell resolution is important for characterizing genetic heterogeneity and evolution in normal tissues, cancers, and microbial populations. Traditional methods for assessing genetic heterogeneity have been limited by low resolution, low sensitivity, and/or low specificity. Single cell sequencing has emerged as a powerful tool for detecting genetic heterogeneity with high resolution, high sensitivity and, when appropriately analyzed, high specificity. Here we provide a protocol for the isolation, whole genome amplification, sequencing, and analysis of single cells. Our approach allows for the reliable identification of megabase-scale copy number variants in single cells. However, aspects of this protocol can also be applied to investigate other types of genetic alterations in single cells.

Single cell sequencing is an increasingly popular and accessible tool for addressing genomic changes at high resolution. We provide a protocol that uses single cell sequencing to identify copy number alterations in single cells.

Detection of genomic changes at single cell resolution is important for characterizing genetic heterogeneity and evolution in normal tissues, cancers, and ...

Using a Fluorescent PCR-capillary Gel Electrophoresis Technique to Genotype CRISPR/Cas9-mediated Knockout Mutants in a High-throughput Format

The development of programmable genome-editing tools has facilitated the use of reverse genetics to understand the roles specific genomic sequences play in the functioning of cells and whole organisms. This cause has been tremendously aided by the recent introduction of the CRISPR/Cas9 system-a versatile tool that allows researchers to manipulate the genome and transcriptome in order to, among other things, knock out, knock down, or knock in genes in a targeted manner. For the purpose of knocking out a gene, CRISPR/Cas9-mediated double-strand breaks recruit the non-homologous end-joining DNA repair pathway to introduce the frameshift-causing insertion or deletion of nucleotides at the break site. However, an individual guide RNA may cause undesirable off-target effects, and to rule these out, the use of multiple guide RNAs is necessary. This multiplicity of targets also means that a high-volume screening of clones is required, which in turn begs the use of an efficient high-throughput technique to genotype the knockout clones. Current genotyping techniques either suffer from inherent limitations or incur high cost, hence rendering them unsuitable for high-throughput purposes. Here, we detail the protocol for using fluorescent PCR, which uses genomic DNA from crude cell lysate as a template, and then resolving the PCR fragments via capillary gel electrophoresis. This technique is accurate enough to differentiate one base-pair difference between fragments and hence is adequate in indicating the presence or absence of a frameshift in the coding sequence of the targeted gene. This precise knowledge effectively precludes the need for a confirmatory sequencing step and allows users to save time and cost in the process. Moreover, this technique has proven to be versatile in genotyping various mammalian cells of various tissue origins targeted by guide RNAs against numerous genes, as shown here and elsewhere.

The genotyping technique described here, which couples fluorescent polymerase chain reaction (PCR) to capillary gel electrophoresis, allows for high-throughput genotyping of nuclease-mediated knockout clones. It circumvents limitations faced by other genotyping techniques and is more cost effective than sequencing methods.

The development of programmable genome-editing tools has facilitated the use of reverse genetics to understand the roles specific genomic sequences play ...

Studying Cell Cycle-regulated Gene Expression by Two Complementary Cell Synchronization Protocols

The gene expression program of the cell cycle represents a critical step for understanding cell cycle-dependent processes and their role in diseases such as cancer. Cell cycle-regulated gene expression analysis depends on cell synchronization into specific phases. Here we describe a method utilizing two complementary synchronization protocols that is commonly used for studying periodic variation of gene expression during the cell cycle. Both procedures are based on transiently blocking the cell cycle in one defined point. The synchronization protocol by hydroxyurea (HU) treatment leads to cellular arrest in late G1/early S phase, and release from HU-mediated arrest provides a cellular population uniformly progressing through S and G2/M. The synchronization protocol by thymidine and nocodazole (Thy-Noc) treatment blocks cells in early mitosis, and release from Thy-Noc mediated arrest provides a synchronized cellular population suitable for G1 phase and S phase-entry studies. Application of both procedures requires monitoring of the cell cycle distribution profiles, which is typically performed after propidium iodide (PI) staining of the cells and flow cytometry-mediated analysis of DNA content. We show that the combined use of two synchronization protocols is a robust approach to clearly determine the transcriptional profiles of genes that are differentially regulated in the cell cycle (i.e. E2F1 and E2F7), and consequently to have a better understanding of their role in cell cycle processes. Furthermore, we show that this approach is useful for the study of mechanisms underlying drug-based therapies (i.e. mitomycin C, an anticancer agent), because it allows to discriminate genes that are responsive to the genotoxic agent from those solely affected by cell cycle perturbations imposed by the agent.

We report two cell synchronization protocols that provide a context for studying events related to specific phases of the cell cycle. We show that this approach is useful for analyzing the regulation of specific genes in an unperturbed cell cycle or upon exposure to agents affecting the cell cycle.

The gene expression program of the cell cycle represents a critical step for understanding cell cycle-dependent processes and their role in diseases such ...

Profiling DNA Replication Timing Using Zebrafish as an In Vivo Model System

DNA replication timing is an important cellular characteristic, exhibiting significant relationships with chromatin structure, transcription, and DNA mutation rates. Changes in replication timing occur during development and in cancer, but the role replication timing plays in development and disease is not known. Zebrafish were recently established as an in vivo model system to study replication timing. Here is detailed the protocols for using the zebrafish to determine DNA replication timing. After sorting cells from embryos and adult zebrafish, high-resolution genome-wide DNA replication timing patterns can be constructed by determining changes in DNA copy number through analysis of next generation sequencing data. The zebrafish model system allows for evaluation of the replication timing changes that occur in vivo throughout development, and can also be used to assess changes in individual cell types, disease models, or mutant lines. These methods will enable studies investigating the mechanisms and determinants of replication timing establishment and maintenance during development, the role replication timing plays in mutations and tumorigenesis, and the effects of perturbing replication timing on development and disease.

Profiling DNA Replication Timing Using Zebrafish as an In Vivo Model System

Zebrafish were recently used as an in vivo model system to study DNA replication timing during development. Here is detailed the protocols for using zebrafish embryos to profile replication timing. This protocol can be easily adapted to study replication timing in mutants, individual cell types, disease models, and other species.

DNA replication timing is an important cellular characteristic, exhibiting significant relationships with chromatin structure, transcription, and DNA ...

An Optogenetic Method to Control and Analyze Gene Expression Patterns in Cell-to-cell Interactions

Cells should respond properly to temporally changing environments, which are influenced by various factors from surrounding cells. The Notch signaling pathway is one of such essential molecular machinery for cell-to-cell communications, which plays key roles in normal development of embryos. This pathway involves a cell-to-cell transfer of oscillatory information with ultradian rhythms, but despite the progress in molecular biology techniques, it has been challenging to elucidate the impact of multicellular interactions on oscillatory gene dynamics. Here, we present a protocol that permits optogenetic control and live monitoring of gene expression patterns in a precise temporal manner. This method successfully revealed that intracellular and intercellular periodic inputs of Notch signaling entrain intrinsic oscillations by frequency tuning and phase shifting at the single-cell resolution. This approach is applicable to the analysis of the dynamic features of various signaling pathways, providing a unique platform to test a functional significance of dynamic gene expression programs in multicellular systems.

Here, we present a protocol to analyze cell-to-cell transfer of oscillatory information by optogenetic control and live monitoring of gene expression. This approach provides a unique platform to test a functional significance of dynamic gene expression programs in multicellular systems.

Cells should respond properly to temporally changing environments, which are influenced by various factors from surrounding cells. The Notch signaling ...

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Complex diseases are often underpinned by multiple common genetic variants that contribute to disease susceptibility. Here, we describe a cost-effective tag single nucleotide polymorphism (SNP) approach using a multiplexed genotyping assay with mass spectrometry, to investigate gene pathway associations in clinical cohorts. We investigate the food allergy candidate locus Interleukin13 (IL13) as an example. This method efficiently maximizes the coverage by taking advantage of shared linkage disequilibrium (LD) within a region. Selected LD SNPs are then designed into a multiplexed assay, enabling up to 40 different SNPs to be analyzed simultaneously, boosting cost-effectiveness. Polymerase chain reaction (PCR) is used to amplify the target loci, followed by single nucleotide extension, and the amplicons are then measured using matrix-assisted laser desorption/ionization-time of flight(MALDI-TOF) mass spectrometry. The raw output is analyzed with the genotype calling software, using stringent quality control definitions and cut-offs, and high probability genotypes are determined and output for data analysis.

Identification of genetic variants contributing to complex human disease allows us to identify novel mechanisms. Here, we demonstrate a multiplex genotyping approach to candidate genes or gene pathway analysis that maximizes the coverage at low cost and is amenable to cohort-based studies.

Complex diseases are often underpinned by multiple common genetic variants that contribute to disease susceptibility. Here, we describe a cost-effective ...

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.

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 ...

Using In Vitro and In-cell SHAPE to Investigate Small Molecule Induced Pre-mRNA Structural Changes

In the process of drug development of RNA-targeting small molecules, elucidating the structural changes upon their interactions with target RNA sequences is desired. We herein provide a detailed in vitro and in-cell selective 2&#39;-hydroxyl acylation analyzed by primer extension (SHAPE) protocol to study the RNA structural change in the presence of an experimental drug for spinal muscular atrophy (SMA), survival of motor neuron (SMN)-C2, and in exon 7 of the pre-mRNA of the SMN2 gene. In in vitro SHAPE, an RNA sequence of 140 nucleotides containing SMN2 exon 7 is transcribed by T7 RNA polymerase, folded in the presence of SMN-C2, and subsequently modified by a mild 2&#39;-OH acylation reagent, 2-methylnicotinic acid imidazolide (NAI). This 2&#39;-OH-NAI adduct is further probed by a 32P-labeled primer extension and resolved by polyacrylamide gel electrophoresis (PAGE). Conversely, 2&#39;-OH acylation in in-cell SHAPE takes place in situ with SMN-C2 bound cellular RNA in living cells. The pre-mRNA sequence of exon 7 in the SMN2 gene, along with SHAPE-induced mutations in the primer extension, was then amplified by PCR and subject to next-generation sequencing. Comparing the two methodologies, in vitro SHAPE is a more cost-effective method and does not require computational power to visualize results. However, the in vitro SHAPE-derived RNA model sometimes deviates from the secondary structure in a cellular context, likely due to the loss of all interactions with RNA-binding proteins. In-cell SHAPE does not need a radioactive material workplace and yields a more accurate RNA secondary structure in the cellular context. Furthermore, in-cell SHAPE is usually applicable for a larger range of RNA sequences (~1,000 nucleotides) by utilizing next-generation sequencing, compared to in vitro SHAPE (~200 nucleotides) that usually relies on PAGE analysis. In case of exon 7 in SMN2 pre-mRNA, the in vitro and in-cell SHAPE derived RNA models are similar to each other.

Detailed protocols for both in vitro and in-cell selective 2&#39;-hydroxyl acylation analyzed by primer extension (SHAPE) experiments to determine the secondary structure of pre-mRNA sequences of interest in the presence of an RNA-targeting small molecule are presented in this article.

In the process of drug development of RNA-targeting small molecules, elucidating the structural changes upon their interactions with target RNA sequences ...

Use of the Pyrimidine Analog, 5-Iodo-2′-Deoxyuridine (IdU) with Cell Cycle Markers to Establish Cell Cycle Phases in a Mass Cytometry Platform

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Chapters in this video

High-Throughput Robotically Assisted Isolation of Temperature-sensitive Lethal Mutants in Chlamydomonas reinhardtii

Rearing and Double-stranded RNA-mediated Gene Knockdown in the Hide Beetle, Dermestes maculatus

Detection of Copy Number Alterations Using Single Cell Sequencing

Using a Fluorescent PCR-capillary Gel Electrophoresis Technique to Genotype CRISPR/Cas9-mediated Knockout Mutants in a High-throughput Format

Studying Cell Cycle-regulated Gene Expression by Two Complementary Cell Synchronization Protocols

Profiling DNA Replication Timing Using Zebrafish as an In Vivo Model System

An Optogenetic Method to Control and Analyze Gene Expression Patterns in Cell-to-cell Interactions

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

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

Using In Vitro and In-cell SHAPE to Investigate Small Molecule Induced Pre-mRNA Structural Changes