Cell Cycle Analysis of Hematopoietic Stem and Progenitor Cells by Multicolor Flow Cytometry

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1 Cell Cycle Analysis of Hematopoietic Stem and Progenitor Cells by Multicolor Flow Cytometry Amy Galvin, 1,7 Meredith Weglarz, 2 Kat Folz-Donahue, 3 Maris Handley, 1 Misa Baum, 4 Michael Mazzola, 5 Hannah Litwa, 6 David T. Scadden, 5 and Lev Silberstein 4,7 1 HSCI-CRM Flow Cytometry Core Facility, Center for Regenerative Medicine, Massachusetts General Hospital, Boston, Massachusetts 2 Stanford Shared FACS Facility, Stanford, California 3 FACS & Imaging Core Facility, Max Planck Institute for Biology of Ageing, Cologne, Germany 4 Fred Hutchinson Cancer Research Center, Seattle, Washington 5 Center for Regenerative Medicine, Massachusetts General Hospital, Boston, Massachusetts 6 NYU Langone Medical Center, New York, New York 7 Corresponding authors: agalvin2@mgh.harvard.edu, lsilbers@fredhutch.org Maintenance of hematopoietic stem cell (HSC) quiescence is critical for selfrenewal and differentiation into mature lineages. Therefore, the ability to reliably detect abnormal HSC cycling is essential for experiments that seek to investigate abnormalities of HSC function. The ability to reproducibly evaluate cell cycle status in a rare cell subset requires careful optimization of multiple parameters during cell preparation and sample processing. Here, we describe a method where data acquisition parameters and fluorochrome combination for long-term HSC staining have been specifically designed for concurrent use with DAPI and Ki-67 antibodies. C 2018 by John Wiley & Sons, Inc. Keywords: DNA content hematopoietic stem and progenitor cells multiparameter flow cytometry murine bone marrow cell cycle How to cite this article: Galvin, A., Weglarz, M., Folz-Donahue, K., Handley, M., Baum, M., Mazzola, M., Litwa, H., Scadden, D. T., & Silberstein, L. (2019). Cell cycle analysis of hematopoietic stem and progenitor cells by multicolor flow cytometry., 87, e50. doi: /cpcy.50 INTRODUCTION Flow cytometric assessment of long-term hematopoietic stem cells (LT-HSC) cell cycle status is a powerful research tool for studies of hematopoiesis in mice. Although HSC cell cycle data are reported by multiple studies, the information in the Methods sections is often insufficient to reproduce the experimental technique in one s own laboratory. Several factors account for the fact that assessment of LT-HSC cell cycle is a tricky experiment: (1) LT-HSCs are extremely rare in mouse bone marrow, meaning that robust flow cytometric definition of this population and acquisition of a sufficient number of events (at least 500 per sample) are critical for generation of reproducible data; (2) multiple fluorochromes are required for LT-HSC staining and need to be chosen carefully to avoid interference with DAPI and Ki-67 antibodies; and (3) accurate measurement of e50, Volume 87 Published in Wiley Online Library (wileyonlinelibrary.com). doi: /cpcy.50 C 2018 John Wiley & Sons, Inc. 1of12

2 the DAPI signal critically depends on the rate of analysis by the flow cytometer, which needs to be carefully adjusted. Here, we describe a protocol that results from our efforts to minimize technical noise and improve reproducibility. We attempted to address technical issues described above by testing multiple fluorochrome combinations for LT-HSCs as defined by the SLAM markers (lineage-negative, c-kit+, Sca-1+, CD48, CD150+). By choosing those which reliably label LT-HSC but are spectrally separated from DAPI, we believe that the data are less likely to be affected by fluctuations in DAPI signal. We also tested various sample preparation procedures and found that storage of samples (e.g., overnight after fixation) negatively affects the quality of the data and should be avoided. Finally, we experimentally determined a range of event acquisition rates to ensure reliable measurement of the DAPI signal and suggest a way for setting this parameter during the cytometer setup (i.e., prior to collection of experimental data). BASIC PROTOCOL 2of12 CELL CYCLE ANALYSIS OF HEMATOPOIETIC STEM AND PROGENITOR CELLS IN MURINE BONE MARROW This protocol provides a method of preparing and analyzing samples of murine bone marrow for cell cycle analysis of hematopoietic stem and progenitor cells by flow cytometry. Materials SLAM cell surface stain master mix containing monoclonal flow antibodies (see Table 1): Sca-1 (Ly-6A/E)-PE clone D7 (BioLegend, cat. no ) c-kit (CD117)-APC clone 2B8 (BD Biosciences, cat. no ) PerCP-Cy5.5 Mouse Lineage Antibody Cocktail (BD Biosciences, cat. no ) CD150-PE-Cy7 clone TC15-12F12.2 (BioLegend, cat. no ) CD48-APC-Cy7 clone HM48-1 (BD Biosciences, cat. no ) Fresh mouse femur Staining buffer: 2% (v/v) fetal bovine serum (FBS) in 1 sterile phosphate-buffered saline (PBS) BD Cytofix/Cytoperm Fixation/Permeabilization Solution Kit (BD, cat. no ) containing: Fixation/Permeabilization solution BD Perm/Wash Buffer Ki-67-FITC clone B56 (BD Biosciences, cat. no ) 2-(4-amidinophenyl)-1H-indole-6-carboxamidine (DAPI) Dissection tweezers Disposable scalpel 10-cm petri dish 50-ml conical tube 40-µm nylon mesh cell strainer (Corning, cat. no or equivalent) Hemocytometer or complete blood count (CBC) counter Centrifuge 12-mm 75-mm polystyrene tubes fitted with 35-µm cell strainer cap (Falcon, cat. no or equivalent) 35-µm cell strainer cap Four-laser flow cytometer Compensation beads (ebioscience UltraComp ebeads, cat. no or equivalent) Computer running analyses software (e.g., FlowJo, FCS Express)

3 Table 1 SLAM Cell Surface Stain Master Mix Antibody Clone Supplier, cat. no. Final dilution Sca-1 (Ly-6A/E) PE D7 BioLegend, :200 c-kit (CD117) APC 2B8 BD Biosciences, :200 PerCP-Cy5.5 Mouse Lineage Antibody Cocktail a BD Biosciences, :400 CD150 PE-Cy7 TC15-12F12.2 BioLegend, :200 CD48 APC-Cy7 HM48-1 BD Biosciences, :200 a Equal parts anti-cd3e, anti-cd11b, anti-cd45r/b220, anti-ly-76, anti-ly-6g, and Ly-6C. Note that the lineage cocktail can be substituted with biotinylated anti-ly6g (BD Biosciences, ), B220 (BD Biosciences, ), Mac1 (BD Biosciences, ), Ter119 (BD Biosciences, ), CD3E (BD Biosciences, ), CD4 (BD Biosciences, ), and CD8A (BD Biosciences, ) and stained with 1:200 streptavidin APC-R700 (BD Biosciences, ) for 30 min on ice. Bone marrow isolation and staining 1. Prepare SLAM cell surface stain master mix (500 µl per sample) with the antibodies outlined in Table 1 at their respective dilutions, and store up to 3 hr in the dark at 4 C until use. 2. Clean the femur of muscle and ligament using dissection tweezers and a scalpel. Gently crush the cleaned femur in a 10-cm petri dish using the cap of a sterile, 50-ml conical tube, and wash the crushed bones with 2 ml staining buffer (2% FBS in 1 PBS). The crushed bones should appear translucent when the bone marrow is sufficiently washed out. 3. Deposit crushed bones into a 40-µm nylon mesh fitted over a 50-ml conical tube, and wash bones with the same 2 ml staining buffer from step 2, now containing the flushed bone marrow. Wash the crushed bones with additional staining buffer until the bone marrow is sufficiently collected. Red cell lysis is not required, and red blood cells are included in the cell number in step 4. While processing additional samples, cells should be stored on ice before proceeding to step Count cells using a hemocytometer or CBC counter. Calculate the dilution volume needed for cells. Note that cells are adequate for collecting enough HSC for cell cycle analysis in wild-type mice, but you can stain greater or fewer cells by proportionately adjusting the volume of the SLAM cell surface stain master mix. 5. Pellet cells from step 4 by centrifuging 5 min at 500 g. Discard the supernatant, and resuspend the pellet in 500 µl cell stain master mix. Incubate sample for 45 min in the dark on ice or at 4 C. All centrifugation steps included in this protocol can be performed at either 4 C or room temperature. Both centrifugation temperatures were tested, and no difference in final data quality or resolution was observed. 6. To remove any unbound antibody, wash cells by adding 1000 µl staining buffer and centrifuging 5 min at 500 g. Cell fixation and permeabilization 7. Resuspend cells in 250 µl Fixation/Permeabilization solution. Pipette up and down until all clumps are completely dissociated. Incubate for 20 min in the dark on ice. 3of12

4 Table 2 Machine Optical Configuration Based on Panel Design Marker Fluorochrome Laser Bandpass filter Longpass filter DNA content DAPI 355 nm or 405 nm 450/40 Ki-67 FITC 488 nm 515/30 505LP Lineage PerCP-Cy nm 710/20 685LP Sca-1 PE 552 nm 586/15 CD150 PE-Cy7 552 nm 780/60 750LP c-kit APC 628 nm 670/30 CD48 APC-Cy7 628 nm 780/60 750LP 8. Centrifuge 5 min at 1500 g, and discard supernatant, leaving 50 µl at the bottom of the tube. 9. Wash pellet with 750 µl of1 BD Perm/Wash Buffer. Centrifuge 5 min at 1500 g, and discard the supernatant. Ki-67/DAPI staining 10. Resuspend pellet in 500 µl Ki-67 FITC diluted 1:10 in 1 BD Perm/Wash Buffer. Incubate for 30 min in the dark on ice. Overnight incubation in Ki-67 antibody staining buffer increases background noise during data acquisition and is not recommended. 11. To wash away unbound antibody, add 500 µl of 1 BD Perm/Wash buffer. Centrifuge 5 min at 1500 g, and discard the supernatant. 12. Resuspend pellet in 500 µlof2µg/ml DAPI in 1 BD Perm/Wash buffer. Incubate sample for 10 min in the dark on ice. 13. Centrifuge 5 min at 1500 g, and resuspend cells in 300 µl staining buffer. 14. Strain sample into a polystyrene tube with 35-µm cell strainer cap before proceeding to step 15. Perform flow cytometry 15. Perform analyses on a flow cytometer with configurations similar to those in Table 2. It is important to use a flow cytometer equipped with at least four lasers (specifically, a 355-nm or 405-nm laser for DAPI excitation and 488-nm, 532-nm, and 628-nm lasers or similar), as this allows for the most optimal separation between fluorescent parameters. Omitting the yellow-green or green laser results in more spillover between the fluorochromes excited by the 488-nm laser, which in turn leads to poorer resolution of the HSC populations. Multiparameter cell cycle data displayed here were collected on a five-laser BD FAC- Symphony. 16. Ensure that DAPI is displayed on a linear scale with the cell cycle phases set so that all peaks are visible on-scale and so that the G0/G1 peak can be easily distinguished from the G2/M peak. 4of12 Here, the data are displayed as linear between 0 and 260k, with the G0/G1 peak set to have a mean fluorescence intensity (MFI) of about 50k. Depending on the instrument, the scaling may be different.

5 Figure 1 Representative plots of the gating strategy for cell cycle analysis of hematopoietic stem and progenitor cells. Values are percentage of parent population. Sample-to-sample variance may cause slight shifts in the DAPI signal. Because the panel is designed to have no overlap between the DAPI signals and those of the other fluorochromes, the voltage of the DAPI channel can be adjusted to keep the G0/G1 MFI at 50k, or a consistent intensity. Alternatively, if the voltage is kept consistent across all samples, the gating may need to be adjusted during the postacquisition analysis. 17. Perform compensation using single-stained beads for each of the surface markers and single-stained cells for Ki-67 and DAPI. Compensation must be performed to eliminate any spillover resulting from overlapping emission spectra between fluorochromes. A combination of automatic compensation and manual compensation should be performed for the best compensation results. The singlestained bead controls can be easily run through automatic compensation, after which the Ki-67-FITC and DAPI controls can be manually run, and any additional compensation for these fluorochromes can be calculated manually and applied to all subsequently acquired samples. Because of the panel design, the DAPI signal should not require any compensation, nor should any other fluorochrome need to be compensated out of the DAPI channel. 18. Record any fluorescence minus one (FMO) controls, and set the gates as depicted in Figure 1. FMO controls are ideal for setting gates. FMOs for all channels should be included, at least initially, to be sure the gating is accurate. Doublet exclusion here is based on the pulse area and width of the forward-scatter (FSC) and side-scatter (SSC) channels rather than on those of the DAPI channel, as is typically done for cell cycle analysis. Either doublet-exclusion method will provide similar results. If desired, the FSC threshold can be increased to exclude red blood cells from the data files. However, this should be done with caution so as not to exclude any pertinent information about the subpopulations of interest. 19. Determine the best flow rate at which to acquire the samples. Ideally, the best flow rate at which to acquire samples for cell cycle analysis will be the slowest flow rate. However, due to the low abundance of the populations of interest, time can become a limiting factor in the ability to acquire enough events for downstream analyses. Thus, the optimal speed at which to acquire the samples may not be the slowest flow rate offered on the machine. The optimal flow rate should be tested and determined using the Support Protocol. 5of12

6 20. Acquire samples at the determined flow rate. Record a minimum of 500 events in the LT-HSC gate. We found that data analysis performed on <500 LT-HSCs resulted in larger sample variances and inconclusive results. 21. After acquisition, export the FCS files for further analysis using the preferred software (e.g., FlowJo, FCS Express). SUPPORT PROTOCOL DETERMINING THE OPTIMAL FLOW RATE FOR THE ACQUISITION OF HSC CELL CYCLE DATA It is generally recommended that to obtain the cleanest and most accurate cell cycle data, the samples should be acquired at the lowest possible flow rate. However, in this experiment, time can become a limiting factor in being able to collect enough events in the rare subpopulations to perform adequate downstream analyses. This protocol describes a method to determine the optimal flow rate that reduces acquisition time without sacrificing data quality. This step is recommended each time prior to running experimental samples. Additional Materials (also see the Basic Protocol) Control sample from the Basic Protocol 1. Prepare a control sample using the sample preparation and staining steps described in the Basic Protocol. Machine configuration and setup should be the same as will be used in the experimental sample acquisition. It is important to prepare this control at the same cell concentration as the experimental samples so as to mimic the same acquisition conditions that will be used in the experimental data acquisition. By using this control, you can save your experimental samples for full acquisition after the optimal flow rate has been determined. 2. Determine a series of flow rates to test, and record 500 LKS (Lineage-, c-kit+, Sca-1+) events at each of the predetermined flow rates. When switching flow rates, wait 15 to 20 sec before recording the data. This will allow for the machine to stabilize at the new flow rate. Also note the threshold rate limitations of the machine you will be using, and do not exceed those limitations (refer to instrument manufacturer s recommendations). 3. After recording at each predetermined flow rate, calculate the coefficient of variance (CV) of the G1 peak recorded for each flow rate. The rate you choose should give a CV of 5% or lower. This is the maximum flow rate you should use when recording your experimental samples. The CV is used to measure the spread of the data. A lower CV indicates less spread or variation in the data. Therefore, it is important to choose a flow rate that minimizes the CV and does not exceed 5%. Figure 2 displays DAPI cell cycle signals at differing flow rates and demonstrates that, up to a certain point, the flow rate can be increased without an effect on the CV of the G0/G1 peak (Fig. 2A, C). However, further increases in the flow rate result in an increase in the CV and poorer resolution of the data (Fig. 2B, C). 6of12 COMMENTARY Background Information Given the critical role of quiescence in maintenance of HSC function (for a recent review, see Hao, Chen, & Cheng, 2016), assessment of HSC replication kinetics status in mice with genetic modification of putative quiescence regulatory molecules is an essential part of experimental workflow.

7 Figure 2 DAPI signal and resolution at increasing flow rates. Data displayed are for representative purposes and were collected on a BD FACSAria II equipped with a rectangular flow cell. (A)As the flow rate incrementally increases by 0.2, the CV is consistently low, and data resolution is not drastically impacted. (B) As flow rate incrementally increases by 1, increasing CVs indicate wider peaks and lower resolution of the data. (C) Graphical representation of flow rate versus CV. The CV of the G0/G1 DAPI signal is not significantly impacted up to a certain flow rate. Upon further flow rate increases, the CV increases beyond acceptable limits and produces lower-resolution data. 7of12

8 Figure 3 Representative plot including 500 LKS events and its respective cell cycle data resolution. With a G0/G1 DAPI CV of 4.47, cell cycle phases are clearly distinguishable from each other. 8of12 Historically, two approaches have been used for this purpose: cell cycle analysis using the proliferation marker Ki-67 and a DNA binding dye (Hoechst 33342, propidium iodide, or DAPI) and incorporation of nucleoside analogues, such as EdU or BrdU, which are systemically administered to the animal prior to the experiment (Jalbert & Pietras, 2018). While the latter approach is more sensitive, as it reflects HSC proliferative history (as opposed to a snapshot provided by the Ki-67 cell cycle analysis), it takes longer and requires animal exposure to potentially toxic reagents. As a result, BrdU/EdU incorporation is generally reserved for confirmatory experiments, while Ki-67 cell cycle analysis acts as a first pass when abnormalities of HSC proliferation are suspected. Hence, accurate and sensitive performance of this assay is critical for determining subsequent experimental workflow. In this protocol, the use of four lasers as opposed to three, as reported by other investigators (Jalbert & Pietras, 2018), allows for better separation between fluorescence parameters as compared to other protocols. Avoiding the use of violet-excited fluorophores, and only using those excited by 488-nm or higher light, ensures that spillover between channels is minimal. Thus, the use of a green or yellowgreen laser (ranging from 532- to 561-nm) results in less spillover between blue or green laser excited fluorochromes, producing better resolution of the HSC populations. This also allows for the potential addition of other surface markers in channels such as PE-Dazzle 594 or AlexaFluor 700 to concurrently investigate cell cycle status in subpopulations within HSCs or other bone marrow subsets. Furthermore, we present an approach that enables optimization of the acquisition rate using a more abundant subset (LKS cells) and reduces technical noise during LT-HSC analysis. Critical Parameters A number of factors contribute to the success of this method, including steps involved in both sample preparation and sample acquisition by flow cytometry. While there are several DNA dyes commonly used for cell cycle analysis, DAPI was used here because it can be spectrally isolated in a multicolor panel more easily than other DNA dyes (e.g., propidium iodide or 7-AAD). Due to the bright staining nature of DNA dyes and the sensitivity of the staining, it is imperative that the spectral overlap of the DNA dye be carefully considered with respect to the other fluorochromes in the panel. Our previous attempts at panel design included the dyes Brilliant Violet 711 and Brilliant Violet 785, which are both excited by 405-nm light and emit at 711-nm and 785-nm, respectively. However, even at these higher emission wavelengths, spillover of the DAPI signal into these channels was observed. This proved to be problematic, as slight variances in the DAPI signal between samples led to inaccuracies in the compensation, resulting in skewed population statistics. Thus, the final panel was designed to avoid using any other fluorochromes excited by ultraviolet or violet laser light. The CV is used to indicate the spread of a set of data. The lower the CV, the less spread in the data and therefore the higher the data resolution and quality. There is little

9 Figure 4 Comparison of the cell cycle phases of LT-HSC, MPP-2, and MPP-3 populations as an internal control of the working protocol. MPPs cycle faster than LT-HSCs, confirming previously reported cell cycle characteristics of the HSC populations (Pietras et al., 2015). 9of12

10 Table 3 Troubleshooting Guide for Cell Cycle Analysis of Hematopoietic Stem and Progenitor Cells in Murine Bone Marrow Problem Possible causes Solutions Cytometer clogging Shifting of Ki-67 signal between samples Shifting of DAPI signal between samples High CVs of G0/G1 peaks or poor cell cycle data resolution Cells clumping during and after fixation/ permeabilization Cells clumping after final resuspension and straining Overnight staining or too much time between staining and analysis High sensitivity of DNA staining due to inconsistent cell number between samples or insufficient staining Sample acquisition rate was too high Incomplete fixation or staining Be sure to pipette thoroughly when resuspending and washing Filter sample right before analysis Stain and analyze on the same day Count cells prior to staining, and use the same DAPI concentration to stain all samples Adjust voltage of DAPI channel, or adjust gates in downstream analyses Decrease sample acquisition rate Follow all timing and measurement requirements outlined in the protocol steps Low cell count Record at least 500 LT-HSC events Table 4 Time Considerations for Performing the Basic Protocol Process Clean and crush femur Count and aliquot Stain 1: SLAM cell markers and wash Stain 2: streptavidin and wash a Fix and permeabilize cells Flow cytometry setup and compensation Sample acquisition Time to complete one femur 5 min 2-7 min 50 min 35 min 35 min 60 min 20 min per sample a Stain 2 is only necessary if using biotinylated lineage-marker antibodies. 10 of 12 information explicitly published on what qualifies as a good CV for DNA content analysis, though Shankey et al. (1993) claimed that a CV of <8% is acceptable for a normal diploid cell. In our experience, we found that a CV of 5% gave adequate resolution to accurately distinguish the LT-HSC cell cycle phases. It is also recommended that when running cell cycle analysis by flow cytometry, the lowest CVs are achieved by running at the lowest possible flow rate, as increases in flow rate result in increased sample core diameter. As a result, cells may no longer align in the center of the core stream and will pass the through laser interrogation point at inconsistent positions, resulting in a nonuniform excitation of the cells (Givan, 2001). Cell cycle data are especially sensitive to such nuances, as they are displayed on a linear scale, and slight changes to the sample core diameter causing

11 inconsistent fluorescence illumination will lead to increased spread and lower resolution of the cell cycle data. To accurately analyze the rare hematopoietic stem and progenitor subpopulations, a large number of events must be recorded. Specifically, we found that at least 500 LT- HSCs should be recorded to create clean and accurate cell cycle plots. Analyzing fewer events resulted in greater statistical variance and inaccuracies in the cell cycle modeling, masking any potential differences in the cell cycle phases between conditions. When controlling for proper sample concentration, it could take upwards of 30 min to record 500 LT-HSCs at the slowest rate possible. Considering how many conditions are being compared and recording replicates for each, it may not be feasible to run each sample for such an extensive amount of time. However, it is imperative that the CVs remain low to achieve the best detection of subtle differences in the cell cycle phases between conditions. For this reason, we investigated whether the flow rate could be increased without impacting the quality of the data and found that this is possible as long as the rate is experimentally determined (Support Protocol; Figs. 2, 3). Ideally, the cell number in each sample is kept consistent across all samples. However, it is very difficult to ensure the same number of cells remain after staining and washing the samples, so one might see slight shifts in the intensity of the DAPI signal between samples. Using the panel described here, DAPI does not spectrally overlap with any of the other fluorochromes and vice versa. Thus, the voltage of the DAPI signal can be adjusted minimally to allow consistent gating in the downstream analyses. Alternatively, if the voltage is kept consistent, the gates may need to be shifted slightly during analysis. Such adjustments to either voltage or gating should only be done if aneuploidy is not expected. Troubleshooting Table 3 summarizes the most common problems, their causes, and their solutions. Anticipated Results Statistical analyses After acquisition, data were exported as FCS 3.0 files and analyzed in FlowJo. All gating is based on FMO controls. If the DAPI signal shifts slightly between samples and the voltage of the DAPI channel was not changed, it may be necessary to adjust the gates of the cell cycle phases accordingly. Understanding results Figure 1 displays the anticipated staining results and gating strategy of the hematopoietic stem and progenitor cell cycle analyses. Populations should be easily resolved, and gates should initially be based on FMO controls. As an internal control, a comparison of the LT-HSC population to the MPP-2 and MPP-3 populations (LKS CD48+CD150+ and LKS CD48+CD150-, respectively) can be useful to determine how well the assay is working functionally in a normal control mouse. LT-HSCs should be cycling minimally, while MPPs should be cycling at a higher frequency (Pietras et al., 2015). As shown in Figure 4, LT-HSCs only show about 10% of the population in the S/G2/M phases of the cell cycle, while MPP-2 shows about 40% and MPP-3 about 25% cycling in the S/G2/M phases. Time Considerations Table 4 describes the time requirements for each step of the protocol. This protocol should be completed within a day. When processing multiple samples, clean all femurs and store cleaned femurs in PBS on ice. Then, crush all the samples, and store on ice before proceeding to counting and aliquoting with the whole batch. Acknowledgements We would like to thank the Flow Cytometry Core Facility at the Fred Hutchinson Cancer Research Center for their assistance with data generation. This work was supported by the Leukemia and Lymphoma Society (LS), the Fred Hutchinson Career Development Fund (LS), and the National Cancer Institute of the NIH under award number R01CA (DTS). Literature Cited Givan, A. L. (2001). Flow cytometry: First principles, 2nd ed. New York: Wiley-Liss. Hao, S., Chen, C., & Cheng, T. (2016). Cell cycle regulation of hematopoietic stem or progenitor cells. International Journal of Hematology, 103, doi: /s Jalbert, E., & Pietras, E. M. (2018). Analysis of murine hematopoietic stem cell proliferation during inflammation. Methods in Molecular Biology, 1686, doi: / _14. Pietras, E. M., Reynaud, D., Kang, Y. A., Carlin, D., Calera-Nieto, F. J., Leavitt, A. D., of 12

12 Passegue, E. (2015). Functionally distinct subsets of lineage-biased multipotent progenitors control blood production in normal and regenerative conditions. Cell Stem Cell, 17, doi: /j.stem Shankey, T. V., Rabinovitch, P. S., Bagwell, B., Bauer, K. D., Duque, R. E., Hedley, D. W.,... Wheeless, L. (1993). Guidelines for implementation of clinical DNA cytometry. Cytometry, 14, doi: /cyto of 12