We would like to thank the URMC Flow Cytometry Core. This work was supported by American Society of Hematology Scholar Award, Leukemia Research Foundation award and NIH grants R01DK133131 and R01CA266617 awarded to J.B.

All animal experiments were conducted in accordance with protocols approved by the University of Rochester University Committee on Animal Resources. Mice were bred and maintained in the animal care facilities at the University of Rochester. To model high-risk MDS, the commercially available NHD13 murine model19 is employed. In this model, bone marrow stromal cells are analyzed in female NHD13 mice at 8 weeks of age, before disease onset. De novo AML is generated as previously described6,11,20. The oncogenes used to induce AML, such as MLL-AF9 and NRas, are tagged with GFP or YFP, allowing for the analysis of the non-leukemic GFP- bone marrow populations using flow cytometry. In brief, 10-week-old female C57BL/6J mice are transplanted with murine GFP/YFP+ AML cells, and the bone marrow is harvested 2 weeks post-transplant. While female mice are used in this study for demonstration purposes, this protocol can be conducted with either male or female mice. It can also be carried out using either one femur or all long bones.
1. Bone marrow harvesting
NOTE: For details on the animal dissection protocol, please refer to Amend et al.26.
<ol>
	<li>Clean the mortar and pestle with 70% ethanol, rinse them with chilled FACS buffer (Table 1), and place them on ice to cool before starting the harvest. Also, place MACs buffer (Table 1) on the bench to allow it to reach room temperature.</li>
	<li>Euthanize the animal following the institutional animal care and use guidelines and protocols.</li>
	<li>On the benchtop, thoroughly spray the mouse with 70% ethanol until its fur is wet. Using forceps and curved scissors, lift the skin on the abdomen and make two incisions approximately 0.5 mm in length on both sides of the mouse, lateral from the abdomen. Next, make a 0.5 mm incision distal from the abdomen. Pull down to remove the skin and fur from the mouse&#39;s legs.</li>
	<li>Place scissors perpendicular to the pelvis, press down while pulling up on the femur with forceps. The femoral head should detach from the pelvis. Separate the femur and tibia at the patellofemoral joint. Place the bones in FACS buffer in a 6-well plate on ice.</li>
	<li>Remove tissue from the bones using laboratory-grade tissue and place the cleaned bones into a new 6-well plate with fresh FACS buffer on ice.</li>
	<li>Place all bones into the mortar with 2-5 mL of FACS buffer so that all bones are immersed in the buffer (adjust the volume of buffer based on how many bones you are processing). Crush and grind the bones using the pestle in a circular motion until the bone marrow tissue is released.</li>
	<li>Using a 3 mL syringe, homogenize the bone marrow by pulling up and flushing down the liquid from the mortar.</li>
	<li>Using a 3 mL syringe, pull up the liquid from the mortar and filter it through a 70 &#181;m cell strainer into a 50 mL tube on ice. Rinse the bone/tissue chunks from the filter back into the mortar with FACS buffer and return to step 1.7 to homogenize and strain a second time. This constitutes the bone marrow fraction.</li>
	<li>Rinse the remaining bone pieces (spicules) back into the mortar with FACS buffer and flush them into a 15 mL tube using FACS buffer to ensure maximum cell yield. This is the bone spicules fraction.</li>
</ol>
2. Digestion of bone marrow
<ol>
	<li>Centrifuge the bone marrow at 300 x g for 5 min at 4 &#176;C. Decant and discard the supernatant.</li>
	<li>Resuspend the bone marrow in 2 mL of the bone marrow digestion mixture (Table 1) and transfer it to a 15 mL tube. Incubate at 37 &#176;C for 45 min on a rotator.</li>
	<li>Add 10 mL of FACS buffer to stop the enzymatic digestion. Filter the mixture through a 70 &#181;m cell strainer into a new 50 mL tube.</li>
	<li>Pellet the mixture at 400 x g for 7 min at 4 &#176;C.</li>
	<li>Resuspend the bone marrow pellet in 1 mL of RBC lysis buffer (see Table of Materials). Incubate for 4 min on ice.</li>
	<li>Add 10 mL of FACS buffer to stop the lysis. Filter the mixture through a 70 &#181;m cell strainer into a new 50 mL tube.</li>
	<li>Pellet the mixture at 300 x g for 5 min at 4 &#176;C. Remove the supernatant and resuspend the pellet in 100 &#181;L of FACS buffer.</li>
</ol>
3. Digestion of bone spicules
<ol>
	<li>Vortex the bone spicules from step 1.9 and allow them to settle. Decant the supernatant and retain the bone at the bottom.</li>
	<li>Resuspend the bone spicules in 1 mL of the bone spicule digestion mixture (Table 1).</li>
	<li>Place the tubes on a tube rotator for 60 min at 37 &#176;C.</li>
	<li>Add 10 mL of FACS buffer to stop the enzymatic digestion. Filter the mixture through a 70 &#181;m cell strainer into the 50 mL tube containing RBC-lysed and digested bone marrow.</li>
</ol>
4. Staining
<ol>
	<li>Gently mix the bone spicules and bone marrow cell suspension.</li>
	<li>Use 10 &#181;L of the cell suspension to count the live cell number on a hemocytometer using 0.4% Trypan blue-based staining, as described in published protocols27. Collect 50,000 cells for an unstained control from the cell suspension.</li>
	<li>Centrifuge the remaining cells at 300 x g for 5 min at 4 &#176;C. Remove the supernatant and resuspend them in 100 &#181;L of FACS buffer. 
	NOTE: Antibodies can be titrated to determine the ideal dilution. Antibody selection (epitopes and fluorochromes) can be customized.</li>
	<li>For staining with antibodies for magnetic depletion, add FC Block (1 &#181;L per 25 x 106 cells), CD45-APC (10 &#181;L per 25 x 106 cells), and Ter119-APC (4 &#181;L per 25 x 106 cells) (see Table of Materials).</li>
	<li>Incubate on ice for 20 min. Wash with FACS buffer, remove 50,000 cells (~50 &#181;L) for the APC-stained control, centrifuge at 300 x g for 5 min at 4 &#176;C, and resuspend in 100 &#181;L of FACS buffer.</li>
	<li>For staining of the cell suspension with microbeads for magnetic depletion, add mIgG (8 &#181;L per 25 x 106 cells) and Anti-APC microbeads (20 &#181;L per 25 x 106 cells) (see Table of Materials).</li>
	<li>Incubate on ice for 20 min. Wash with 10 mL FACS buffer, centrifuge at 300 x g for 5 min at 4 &#176;C.</li>
</ol>
5. Depletion of sample by magnetic sorting
NOTE: This step is carried out using a commercially available manual magnetic separator according to the manufacturer&#39;s instructions. This step can also be performed with an automated separator (see Table of Materials).
<ol>
	<li>Prepare the LD column by washing it with 2 mL of MACs buffer (Table 1). Discard the effluent and change the collection tube.</li>
	<li>Resuspend up to 1 x 108 cells in MACs buffer and filter them through a 5 mL test tube with a 35 &#181;m cell strainer cap.</li>
	<li>Place the LD column on the magnetic separator stand. Position a 5 mL test tube below the column to collect the eluate.</li>
	<li>Add the cell suspension to the prepared LD column. Allow the negative fraction to flow through into the collection tube. Wash the column twice with 1 mL of MACs buffer, collecting the eluate in the same tube. This is the negative fraction used in step 5.6 below.</li>
	<li>Remove the LD column from the magnetic separator stand and place it on a new 5 mL test tube. Use a pipette to dispense 3 mL of buffer into the column to flush out cells that have been positively labeled, using the column plunger.</li>
	<li>Centrifuge the negative and positive fractions at 300 x g for 5 min at 4 &#176;C. Resuspend them in 100 &#181;L of FACS buffer.</li>
	<li>Count 10 &#181;L of the negative and positive fractions with 0.4% Trypan blue. The volumes for the osteo-analysis/endothelial panel staining below will be based on this cell count.</li>
	<li>Use 50,000 live cells from the positive fraction for flow cytometry gating controls.</li>
</ol>
6. Osteo-analysis/endothelial panel stain
NOTE: Compensation should be performed following standard flow cytometry protocols, including all appropriate staining and gating controls.
<ol>
	<li>For staining of the CD45/Ter119 negative fraction (1 &#181;L of each antibody per 1 x 106 cells), add CD31-PE-Cy7, Sca-1-BV421, CD51-PE, and CD140a-PE-Cy5 (see Table of Materials).</li>
	<li>Incubate on ice for 20 min. Wash with 2 mL of FACS buffer, then centrifuge at 300 x g for 5 min at 4 &#176;C.</li>
	<li>Add 1 mL of FACS buffer and a 1:1000 dilution of PI for live/dead staining, then filter the sample through a 5 mL test tube with a 35 &#181;m cell strainer cap.</li>
	<li>Analyze the cells on a multi-color flow cytometer.</li>
</ol>

Isolation and Characterization of Bone Marrow Microenvironment in Myeloid Neoplasms

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No conflicts of interest declared.

Murine leukemia models have been extensively used to identify cell intrinsic and niche-driven signals that promote aggressive myeloid leukemia progression6,19,21. Here, a comprehensive flow cytometry-based protocol to define the cellular composition of the bone marrow microenvironment in murine models of MDS and AML is presented.
Prior to acquiring flow cytometric data from experimental samples, it is important to carefully compensate for fluorescence overlap. It is also essential to include all appropriate staining and gating controls. These steps will allow the experimenter to confirm that positive or negative antibody staining represents accurate expression of cell markers of interest and is not an artefact of fluorescence spectral overlap or autofluorescence. Although this protocol describes selected cell surface markers, the antibody panels can be expanded based on experimental need. For example, CD144 (Ve-Cadherin) can be administered in vivo before harvesting the mice and can serve as an additional specific marker of endothelial cells5,29. While the fluorophores and antibody clones indicated here can be changed, titrations should be carried out to determine their ideal dilution. To categorically define all cell populations in the bone marrow niche, single cell RNA-sequencing can be used to establish the bone marrow niche landscape during MDS/AML initiation and progression23,24,30.
It is critical to prepare the sample carefully as per the steps described in this protocol. When homogenizing the bones, it is crucial that the mortar and pestle are chilled, and all steps are carried out on ice to prevent cell death and to ensure high cell recovery. It is very important to remove all tissue surrounding the bones before homogenizing to prevent contamination of other undesired cell types. During RBC lysis and digestions, it is important to stop the enzymatic reaction with an appropriate amount of FACS Buffer and resuspend thoroughly in fresh buffer, or cells will continue to digest and eventually die.
Separating the bone and bone marrow fractions is essential since the bone spicules require a different mix of enzymes for digestion buffer and need longer time to digest. In bone digestions, the collagenase type 1 is useful for digesting collagenase fibrils which are commonly found in extracellular matrix and collagen fibers31. Additionally, some bone marrow cells located close to the endosteum will remain attached to the bone after homogenizing and are only released by enzymatic digestion. When digesting bone marrow, collagenase type IV is used to digest the basement membrane of epithelial and endothelial cells within the bone marrow32, while dispase mainly cleaves fibronectin31. The bone marrow requires less time to digest as the associations between cells and matrix are weaker. Incubating the bone marrow fraction in similar conditions can damage the populations of interest. Using two different digestion buffers significantly increases the number of stomal populations that can be detected, and thus provides a larger data set to analyze.
Most available protocols to analyze murine bone marrow microenvironmental populations use a syringe to flush the bone marrow from only the long bones13,24. The current method of crushing&#160;bones provides the ability of acquiring data from other bones such as the pelvis, significantly reduces sample preparation time, and mitigates the possibility of injuries with sharp needles. Given that the bone consists of mature osteoblasts and other cell populations that can provide support to normal and malignant hematopoietic cells, this method of including cells from the bone spicules enables a more accurate representation of the bone marrow microenvironment in the sample. While one previous study digested bone marrow and bone spicules separately11, it did not demonstrate staining of osteolineage and endothelial cells in the same sample. A second study used commercially available proprietary enzyme mixes to digest bone marrow and bone spicules23, and analyzed the data using the significantly more expensive single cell RNA-sequencing technology. This method of enriching for CD45-/Ter119- cells selects for cells of interest, and significantly reduces the time needed to acquire data on the flow cytometer. Thus, compared to other state of the art methods such as single-cell RNA sequencing, this flow cytometry-based method is more accessible, cost-effective and does not require sophisticated analysis by trained bioinformaticians23,24,30.
It is important to note that this protocol can be used to characterize the bone marrow microenvironment of not only any of the available murine models of MDS and AML but any genetic mouse model. Similar methods can also be effective in analyzing the changes in the murine bone marrow niche of patient derived xenograft (PDX) models. These methods can be useful for studies aimed at determining the mechanisms by which MDS/AML affect their bone marrow niche. Given the technical challenges associated with sampling large quantities of bone marrow from human patients, these analyses of murine models are an effective tool to further the understanding of the malignant bone marrow microenvironment and define its role in disease progression.

The bone marrow microenvironment consists of hematopoietic cells, non-hematopoietic stromal cells, and the extracellular matrix1,2. This microenvironment can promote hematopoietic stem cell self-renewal, regulate lineage differentiation, and provide structural and mechanical support to the bone tissue1,2,3,4,5. The stromal niche includes osteolineage cells, fibroblasts, nerve cells, and endothelial cells6, while the hematopoietic niche consists of the lymphoid and myeloid populations1,2,3. In addition to supporting normal HSCs, the bone marrow microenvironment can also play a role in the development of hematopoietic stem cell disorders such as MDS and AML7,8,9,10,11. Mutations in osteolineage cells have been shown to promote the development of MDS, AML, and other myeloproliferative neoplasms10,12,13,14.
Myelodysplastic syndromes are a group of pre-leukemic disorders that arise from mutations in hematopoietic stem cells. MDS is frequently associated with a block in HSC differentiation and the production of dysplastic cells, which can often lead to bone marrow failure. MDS is the most commonly diagnosed myeloid neoplasm in the United States and is associated with a 3-year survival rate of 35%-45%15. MDS is often associated with a high risk of transformation to acute myeloid leukemia. This can be a fatal complication, as MDS-derived AML is resistant to most therapies and likely to relapse. AML that arises de novo due to translocations or mutations in hematopoietic stem and progenitors is also often resistant to standard chemotherapy16,17. Since MDS and AML are primarily diseases of the elderly, with the majority diagnosed over the age of 60 years, most patients are ineligible for curative bone marrow transplants. There is, thus, a significant need to identify novel regulators of disease progression. Since the bone marrow microenvironment can provide support for malignant cells14, defining changes in the bone marrow niche with disease progression may lead to the identification of novel therapeutics aimed at inhibiting tumor niche remodeling. There is, therefore, a significant need to identify novel regulators of disease progression. To this end, it is critical to identify and characterize changes in the bone marrow stromal cell populations that may provide support for the malignant cells.
Several murine models of AML and MDS have been generated and can be used to study changes in the bone marrow microenvironment during disease initiation and progression6,1,19,20,21,22. Here, protocols to identify changes in the bone marrow stromal cell populations using murine models of retrovirally induced AML6,20, as well as the commercially available Nup98-HoxD13 (NHD13) model of high-risk MDS to AML transformation19, are described. Mice transplanted with de novo AML cells succumb to the disease in 20-30 days6. The NHD13 mice develop cytopenias and bone marrow dysplasia around 15-20 weeks, which eventually transforms into AML, and nearly 75% of the mice succumb to the disease around 32 weeks. To analyze the murine model bone marrow microenvironment populations, bones are harvested, bone marrow and bone spicules are digested using enzymatic digestion, and the cells are then enriched for CD45-/Ter119- non-hematopoietic populations by magnetic sorting. While similar analyses have been previously described11,13,22,23,24,25, they often focus on either the bone marrow or the bone and do not incorporate cells from both sources in their analyses. The combined characterization of these populations, in conjunction with gene expression analyses, can provide a comprehensive understanding of how the cellular hematopoietic microenvironment provides support for disease initiation and progression (Figure 1). While the protocol described below focuses on retrovirally induced AML model and a genetic MDS model, these strategies can be easily adapted to study changes in the bone marrow niche of any murine model of interest.

<table><tbody><tr><td>1 mL pipette Tips&amp;nbsp;</td><td>Genesee Scientific&amp;nbsp;</td><td>24-165RL</td><td></td></tr><tr><td>1.7 mL Microcentrifuge Tubes</td><td>AVANT</td><td>L211511-CS</td><td></td></tr><tr><td>10 &amp;micro;L pipette Tips</td><td>Genesee Scientific&amp;nbsp;</td><td>24-140RL</td><td></td></tr><tr><td>10 mL Individually Wrapped Sterile Serological Pipettes</td><td>Globe scientific</td><td>1760</td><td></td></tr><tr><td>1000 mL Vacuum Filtration Flask</td><td>NEST</td><td>344021</td><td></td></tr><tr><td>15 mL Centrifuge Tube</td><td>VWR</td><td>10026-076</td><td></td></tr><tr><td>2 mL Aspirating Pipette</td><td>NEST</td><td>325011</td><td></td></tr><tr><td>200 &amp;micro;L pipette Tips</td><td>Genesee Scientific&amp;nbsp;</td><td>24-150-RL</td><td></td></tr><tr><td>25 mL Individually Wrapped Sterile Serological Pipettes</td><td>Globe scientific</td><td>1780</td><td></td></tr><tr><td>5 mL Individually Wrapped Sterile Serological Pipettes</td><td>Globe scientific</td><td>1740</td><td></td></tr><tr><td>5 mL Polystyrene Round-Bottom Tube&amp;nbsp; 12 x 75 mm style</td><td>Falcon</td><td>352054</td><td></td></tr><tr><td>5 mL Polystyrene Round-Bottom Tube with Cell Strainer Cap 12 x 75 mm style</td><td>Falcon</td><td>352235</td><td></td></tr><tr><td>50 mL Centrifuge Tube</td><td>NEST</td><td>602052</td><td></td></tr><tr><td>6 Well, Flat Bottom with Low Evaporation Lid</td><td>Falcon</td><td>353046</td><td></td></tr><tr><td>Absorbent Underpads with Waterproof Moisture Barrier</td><td>VWR</td><td>56616-031</td><td></td></tr><tr><td>APC MicroBeads</td><td>Miltenyi&amp;nbsp;</td><td>130-090-855</td><td></td></tr><tr><td>autoMACS Pro Separator</td><td>Miltenyi Biotec GmBH</td><td>4425745</td><td></td></tr><tr><td>BD Pharmingen Purified Rat Anti-Mouse CD16/CD32 (Mouse BD Fc Block)</td><td>BD Biosciences</td><td>553141</td><td>0.5 mg/mL&amp;nbsp;</td></tr><tr><td>Bovine Serum Albumin</td><td>Sigma-Aldrich</td><td>A7906</td><td>66.000 g/mol</td></tr><tr><td>Brilliant Violet 421 anti-mouse Ly-6A/E (Sca-1) Antibody (D7)</td><td>Invitrogen</td><td>404-5981</td><td>0.2 mg/mL</td></tr><tr><td>C57BL/6J Mice</td><td>Jackson Laboratory&amp;nbsp;</td><td>664</td><td></td></tr><tr><td>Carbon Dioxide Gas Tank</td><td>Airgas</td><td>CD50</td><td></td></tr><tr><td>CD31 (PECAM-1) Monoclonal Antibody (390), PE-Cyanine7</td><td>Invitrogen</td><td>25-0311-82</td><td>0.2 mg/mL</td></tr><tr><td>CD45 Monoclonal Antibody (30-F11), APC</td><td>Invitrogen</td><td>17-0451-82</td><td>0.2 mg/mL</td></tr><tr><td>Cell Strainer 70 &amp;micro;m Nylon&amp;nbsp;</td><td>Falcon</td><td>352350</td><td></td></tr><tr><td>Cole-Parmer Essentials Mortar and Pestle; Agate, 125 mL</td><td>Cole-Parmer</td><td>EW-63100-62</td><td></td></tr><tr><td>Collagenase from &lt;em&gt;Clostridium histolyticum&lt;/em&gt;</td><td>Sigma-Aldrich</td><td>C5138-500MG</td><td></td></tr><tr><td>Collagenase Type I</td><td>STEMCELL</td><td>7415</td><td></td></tr><tr><td>Corning Mini Centrifuge</td><td>CORNING</td><td>6770</td><td></td></tr><tr><td>Corning Stripettor Ultra Pipet Controller</td><td>Corning</td><td>4099</td><td></td></tr><tr><td>Deoxyribonuclease I from bovine pancreas</td><td>Sigma-Aldrich</td><td>D4513</td><td></td></tr><tr><td>Dispase II, powder</td><td>Gibco</td><td>117105041</td><td></td></tr><tr><td>DPBS 10x</td><td>gibco</td><td>14200-075</td><td></td></tr><tr><td>eBioscience 1x RBC Lysis Buffer</td><td>Invitrogen</td><td>00-4333-57</td><td></td></tr><tr><td>Ethanol absolute, KOPTEC, meets analytical specification of BP, Ph. Eur., USP (200 Proof)</td><td>VWR</td><td>89125-174</td><td></td></tr><tr><td>Fine scissors - sharp</td><td>Fine Science Tools</td><td>14061-10</td><td></td></tr><tr><td>Foundation B Fetal Bovine Serum</td><td>GeminiBio</td><td>900-208</td><td></td></tr><tr><td>Gilson&amp;nbsp;PIPETMAN L Pipette Starter Kits</td><td>FisherScientific&amp;nbsp;</td><td>F167370G</td><td></td></tr><tr><td>Graefe Forceps</td><td>Fine Science Tools</td><td>11051-10</td><td></td></tr><tr><td>Hank&#039;s Balanced Salt Solution (HBSS) 10x</td><td>gibco</td><td>14185-052</td><td></td></tr><tr><td>Hemocytometer</td><td>Fisher</td><td>02-671-10</td><td></td></tr><tr><td>Incubator&amp;nbsp;</td><td>BINDER</td><td>C150-UL</td><td></td></tr><tr><td>Kimwipes</td><td>KIMTECH</td><td>K222101</td><td></td></tr><tr><td>LABGARD Class II, Type A2 Biological Safety Cabinet</td><td>Nuaire</td><td>NU-425-400</td><td></td></tr><tr><td>LD Columns</td><td>Miltenyi Biotec GmBH</td><td>130-042-901</td><td></td></tr><tr><td>LSE Vortex Mixer</td><td>CORNING</td><td>6775</td><td></td></tr><tr><td>LSRII/Fortessa/Symphony A1</td><td>Becton, Dickinson and Company</td><td>647800L6</td><td></td></tr><tr><td>MACS MULTI STAND&amp;nbsp;</td><td>Miltenyi Biotec GmBH</td><td>130-042-303</td><td></td></tr><tr><td>MACsmix Tube Rotator&amp;nbsp;</td><td>Miltenyi Biotec GmBH</td><td>130-090-753</td><td></td></tr><tr><td>mIgG</td><td>Millipore-Sigma</td><td>18765-10mg</td><td>2 mg/mL&amp;nbsp;</td></tr><tr><td>Nup98-HoxD13 (NHD13) Mice</td><td>Jackson Laboratory&amp;nbsp;</td><td>010505</td><td></td></tr><tr><td>PE anti-mouse CD51 Antibody (RMV-7)</td><td>Biolegend</td><td>104106</td><td>0.2 mg/mL</td></tr><tr><td>PE/Cyanine5 anti-mouse CD140a Antibody (RUO)</td><td>Biolegend</td><td>135920</td><td>0.2 mg/mL</td></tr><tr><td>Penicillin-Streptomycin&amp;nbsp;</td><td>Gibco</td><td>15140122</td><td>10,000 U/mL</td></tr><tr><td>Plastipak 3 mL Syringe</td><td>Becton, Dickinson and Company</td><td>309657</td><td></td></tr><tr><td>Propidium Iodide - 1.0 mg/mL Solution in Water</td><td>ThermoFisher Scientific</td><td>P3566</td><td></td></tr><tr><td>QuadroMACS&amp;nbsp; Separator&amp;nbsp;</td><td>Miltenyi Biotec GmBH</td><td>130-090-976</td><td></td></tr><tr><td>Sorvall X Pro / ST Plus Series Centrifuge</td><td>Thermo Scientific&amp;nbsp;</td><td>75009521</td><td></td></tr><tr><td>TER-119 Monoclonal Antibody (TER-119), APC</td><td>Invitrogen</td><td>17-5921-82</td><td>0.2 mg/mL</td></tr><tr><td>Trypan Blue Solution 0.4%</td><td>Gibco</td><td>15-250-061</td><td></td></tr><tr><td>Ultrapure 0.5 M EDTA, pH 8.0&amp;nbsp;</td><td>Invitrogen</td><td>15575-038</td><td></td></tr></tbody></table>

identifying bone marrow microenvironmental populations in myelodysplastic syndrome and acute myeloid leukemia

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

This article describes a flow cytometry-based method for analyzing bone marrow microenvironmental populations, such as the endothelial and mesenchymal stromal cells, from MDS and leukemia murine models (Figure 1). Figure 2 depicts the gating strategy for detection of populations of interest, beginning with the selection of cells (P1) in the digested and CD45/Ter119 depleted fraction through forward and side scatter profile. Example gating of cells in a leukemia sample are shown in P1 (Figure 2A). Singlets are selected and doublets are excluded from this analysis, P2 (Figure 2B). Figure 2C shows gates to select propidium iodine negative live cells, P3. To focus on non-hematopoietic stromal populations, cells that are CD45-/Ter119-, P4 (APC, Y-axis) vs. SSC-A are selected (Figure 2D). This initial gating strategy is common for all samples to be analyzed.
The leukemia murine model is used to illustrate gating for endothelial cells in Figures 2E-G. Figure 2E depicts CD31 positive (Pe-Cy7, Y-axis) vs. SSC-A cells in a non-cancer control mouse as well as a leukemic mouse, gated through P4. Cells positively labeled with CD31 are endothelial cells, P5. In Figure 2F, gated through P5, arteriolar endothelial cells are identified as CD45-Ter119-CD31+Sca1+, P6, and sinusoidal endothelial cells are identified as CD45-Ter119-CD31+Sca1-, P7 (BV421, Y-axis) vs. SSC-A.
Although this analysis focusses on non-leukemic bone marrow microenvironmental cells, it is also helpful to determine tumor burden. This can be done with a small fraction of undigested/non-depleted sample prior to initiating the experiment. In this experimental control (dashed lines) Figure 2G, P8 represents tumor burden in the sample and P9 represents the non-cancerous cells.
The MDS murine model is used to illustrate analysis of mesenchymal stromal cells in Figure 2H-J. Figure 2H depicts CD31 negative (Pe-Cy7, Y-axis) vs. SSC-A cells, gated through P4. Mesenchymal stromal cell populations in a wild-type control mouse and MDS mouse are shown in Figure 2I. Gated through P10, mesenchymal stromal cells are identified as CD45-Ter119-CD31-CD51+CD140a+, P113 (Pe, Y-axis; Pe-Cy5, X-axis). The experimental control (dashed lines), Figure 2J shows examples of single-color gating controls, CD51 single stain and CD140a single stain used to gate for the MSCs shown in the experimental samples in Figure 2I.
This data indicates that arteriolar endothelial cells significantly expand in the AML microenvironment, with a concomitant loss in the sinusoidal endothelial populations (Figure 2F), consistent with earlier studies using patient derived xenografts in immunodeficient mice28. It is likely that the small expansion in the mesenchymal stromal cells seen in the NHD13 mice at 8 weeks of age (Figure 2I) may increase at 16-20 weeks, when these mice start to display characteristics of MDS25. Although only the leukemia model is used to illustrate the endothelial cell population and the MDS murine model is used to illustrate the mesenchymal stromal cell populations, similar staining and gating strategies can be used to analyze the different microenvironmental populations in either of these models, or indeed, in any genetically engineered murine model of interest.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/66093/66093fig01.jpg" /> 
Figure 1: Isolation of bone marrow stromal cells. Schematic shows the process of isolating non-hematopoietic bone marrow stromal cells from control and leukemic mice.&#160;Briefly, bone spicules and bone marrow are digested separately and then pooled. The CD45-Ter119- population is enriched by magnetic sorting, and stained with antibody panels against populations of interest, such as mesenchymal stromal cells and endothelial cells. The cells are then analyzed by flow cytometry. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/66093/66093fig01large.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/66093/66093fig02.jpg" /> 
Figure 2: Gating strategy for non-hematopoietic bone marrow and stromal cells. (A-D)&#160;Flow cytometry gating strategy used to select digested, CD45-/Ter119-, non-hematopoietic populations (P4) in both the leukemia and MDS murine model. (E) Leukemia bone marrow endothelial cells (P5, CD31+) can be sub-divided as (F) Sca1+ arteriolar (P6) or Sca1- sinusoidal endothelial cells (P7). (G) Leukemia engraftment in an AML sample where P8 represents engraftment while P9 represents non-cancer cells. Dotted lines indicate that this plot is an experimental control. (H) Gated through P4, MDS bone marrow CD31- cells, P10 (I) Mesenchymal stromal cells (CD51+/CD140a+, P11). (J) Example single color gating controls, CD51 (left) and CD140a (right) used to determine the gates for mesenchymal stromal cells in (I). <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/66093/66093fig02large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Solution</td>
			<td>Reagent</td>
			<td>Concentration</td>
			<td>Amount to add</td>
		</tr>
		<tr>
			<td rowspan="4">FACS buffer</td>
			<td>HBSS</td>
			<td>10x</td>
			<td>100 mL</td>
		</tr>
		<tr>
			<td>EDTA</td>
			<td>0.5 M</td>
			<td>4 mL</td>
		</tr>
		<tr>
			<td>Fetal Bovine Serum</td>
			<td>-</td>
			<td>50 mL</td>
		</tr>
		<tr>
			<td>Water</td>
			<td>-</td>
			<td>848 mL</td>
		</tr>
		<tr>
			<td rowspan="4">Bone marrow digestion mixture</td>
			<td>HBSS</td>
			<td>1x</td>
			<td>2 mL</td>
		</tr>
		<tr>
			<td>DNase 1</td>
			<td>1 &#181;g/mL in 1x DPBS</td>
			<td>20 &#181;L&#160;</td>
		</tr>
		<tr>
			<td>Dispase II Powder</td>
			<td>-</td>
			<td>4 mg</td>
		</tr>
		<tr>
			<td>Collagenase Type IV</td>
			<td>-</td>
			<td>2 mg</td>
		</tr>
		<tr>
			<td rowspan="3">Bone spicule digestion mixture</td>
			<td>DPBS</td>
			<td>1x</td>
			<td>320 mL</td>
		</tr>
		<tr>
			<td>Collagenase Type 1</td>
			<td>-</td>
			<td>1 g</td>
		</tr>
		<tr>
			<td>Fetal Bovine Serum</td>
			<td>-</td>
			<td>80 mL</td>
		</tr>
		<tr>
			<td rowspan="4">MACs buffer</td>
			<td>BSA</td>
			<td>66 g/mol</td>
			<td>5 g</td>
		</tr>
		<tr>
			<td>DPBS</td>
			<td>10x</td>
			<td>100 mL</td>
		</tr>
		<tr>
			<td>EDTA</td>
			<td>0.5 M</td>
			<td>4 mL</td>
		</tr>
		<tr>
			<td>Water</td>
			<td>-</td>
			<td>896 L</td>
		</tr>
	</tbody>
</table>
Table 1: Composition of solutions and buffers used in the present study.

Watch this Scientific Journal Video about Analyzing Bone Marrow Microenvironment in Murine Hematological Malignancies at JoVE.com

Author Spotlight: Analyzing Bone Marrow Microenvironment in Murine Hematological Malignancies 

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

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

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

identifying-bone-marrow-microenvironmental-populations

Nanyang Technological University

Research

JoVE Journal

Cancer Research

1.1K Views.  University of Rochester Medical Center. Ons onderzoek heeft tot doel te onderzoeken hoe de veranderende omgeving van het beenmerg de tumorgroei beïnvloedt. We ontwikkelden een flowcytometrieprotocol om de niet-immuuncellen in beenmerg en botweefsel te analyseren, met de nadruk op hematologische maligniteiten bij muizen. Deze methode is aanpasbaar voor het bestuderen van beenmerg in verschillende muizenmodellen.Onze studie richt zich op het isoleren en identificeren van veranderingen in stromale beenmergpopulaties tijdens ka...

Video: Auteur in de schijnwerpers: analyse van de micro-omgeving van het beenmerg bij hematologische maligniteiten van muizen 

Comprehensive Protocol to Sample and Process Bone Marrow for Measuring Measurable Residual Disease and Leukemic Stem Cells in Acute Myeloid Leukemia

Response criteria in acute myeloid leukemia (AML) has recently been re-established, with morphologic examination utilized to determine whether patients have achieved complete remission (CR). Approximately half of the adult patients who entered CR will relapse within 12 months due to the outgrowth of residual AML cells in the bone marrow. The quantitation of these remaining leukemia cells, known as minimal or measurable residual disease (MRD), can be a robust biomarker for the prediction of these relapses. Moreover, retrospective analysis of several studies has shown that the presence of MRD in the bone marrow of AML patients correlates with poor survival. Not only is the total leukemic population, reflected by cells harboring a leukemia associated immune-phenotype (LAIP), associated with clinical outcome, but so is the immature low frequency subpopulation of leukemia stem cells (LSC), both of which can be monitored through flow cytometry MRD or MRD-like approaches. The availability of sensitive assays that enable detection of residual leukemia (stem) cells on the basis of disease-specific or disease-associated features (abnormal molecular markers or aberrant immunophenotypes) have drastically improved MRD assessment in AML. However, given the inherent heterogeneity and complexity of AML as a disease, methods for sampling bone marrow and performing MRD and LSC analysis should be harmonized when possible. In this manuscript we describe a detailed methodology for adequate bone marrow aspirate sampling, transport, sample processing for optimal multi-color flow cytometry assessment, and gating strategies to assess MRD and LSC to aid in therapeutic decision making for AML patients.

Detection of minimal or measurable residual disease (MRD) is an important prognostic biomarker for refining risk assessment and predicting relapse in acute myeloid leukemia (AML). These comprehensive guidelines and recommendations with best practices for consistent and accurate identification and detection of MRD, may aid in making effective AML treatment decisions.

Response criteria in acute myeloid leukemia (AML) has recently been re-established, with morphologic examination utilized to determine whether patients ...

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

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

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

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

Bioengineering of Humanized Bone Marrow Microenvironments in Mouse and Their Visualization by Live Imaging

Human hematopoietic stem cells (HSCs) reside in the bone marrow (BM) niche, an intricate, multifactorial network of components producing cytokines, growth factors, and extracellular matrix. The ability of HSCs to remain quiescent, self-renew or differentiate, and acquire mutations and become malignant depends upon the complex interactions they establish with different stromal components. To observe the crosstalk between human HSCs and the human BM niche in physiological and pathological conditions, we designed a protocol to ectopically model and image a humanized BM niche in immunodeficient mice. We show that the use of different cellular components allows for the formation of humanized structures and the opportunity to sustain long-term human hematopoietic engraftment. Using two-photon microscopy, we can live-image these structures in situ at the single-cell resolution, providing a powerful new tool for the functional characterization of the human BM microenvironment and its role in regulating normal and malignant hematopoiesis.

A method to create and live-image different humanized bone-marrow niches in mice is presented. Based on the supportive niche created by human mesenchymal cells, the addition of human endothelial cells induces the formation of human vessels, while the addition of rhBMP-2 induces the formation of human-mouse chimeric mature bone tissue.

Human hematopoietic stem cells (HSCs) reside in the bone marrow (BM) niche, an intricate, multifactorial network of components producing cytokines, growth ...

Developmental Biology

Two Flow Cytometric Approaches of NKG2D Ligand Surface Detection to Distinguish Stem Cells from Bulk Subpopulations in Acute Myeloid Leukemia

Within the same patient, absence of NKG2D ligands (NKG2DL) surface expression was shown to distinguish leukemic subpopulations with stem cell properties (so called leukemic stem cells, LSCs) from more differentiated counterpart leukemic cells that lack disease initiation potential although they carry similar leukemia specific genetic mutations. NKG2DL are biochemically highly diverse MHC class I-like self-molecules. Healthy cells in homeostatic conditions generally do not express NKG2DL on the cell surface. Instead, expression of these ligands is induced upon exposure to cellular stress (e.g., oncogenic transformation or infectious stimuli) to trigger elimination of damaged cells via lysis through NKG2D-receptor-expressing immune cells such as natural killer (NK) cells. Interestingly, NKG2DL surface expression is selectively suppressed in LSC subpopulations, allowing these cells to evade NKG2D-mediated immune surveillance. Here, we present a side-by-side analysis of two different flow cytometry methods that allow the investigation of NKG2DL surface expression on cancer cells i.e., a method involving pan-ligand recognition and a method involving staining with multiple antibodies against single ligands. These methods can be used to separate viable NKG2DL negative cellular subpopulations with putative cancer stem cell properties from NKG2DL positive non-LSC.

We present two different staining protocols for NKG2D ligand (NKG2DL) detection in human primary acute myeloid leukemia (AML) samples. The first approach is based on a fusion protein, able to recognize all known and potentially yet unknown ligands, while the second protocol relies on the addition of multiple anti-NKG2DL antibodies.

Within the same patient, absence of NKG2D ligands (NKG2DL) surface expression was shown to distinguish leukemic subpopulations with stem cell properties ...

Use of Hematopoietic Stem Cell Transplantation to Assess the Origin of Myelodysplastic Syndrome

Myelodysplastic syndromes (MDS) are a diverse group of hematopoietic stem cell disorders that are defined by ineffective hematopoiesis, peripheral blood cytopenias, dysplasia, and a propensity for transformation to acute leukemia. NUP98-HOXD13 (NHD13) transgenic mice recapitulate human MDS in terms of peripheral blood cytopenias, dysplasia, and transformation to acute leukemia. We previously demonstrated that MDS could be transferred from a genetically engineered mouse with MDS to wild-type recipients by transplanting MDS bone marrow nucleated cells (BMNC). To more clearly understand the MDS cell of origin, we have developed approaches to transplant specific, immunophenotypically defined hematopoietic subsets. In this article, we describe the process of isolating and transplanting specific populations of hematopoietic stem and progenitor cells. Following transplantation, we describe approaches to assess the efficiency of transplantation and persistence of the donor MDS cells.

We describe the use of hematopoietic stem cell transplantation (HSCT) to assess the malignant potential of genetically engineered hematopoietic cells. HSCT is useful for evaluating various malignant hematopoietic cells in vivo as well as generating a large cohort of mice with myelodysplastic syndromes (MDS) or leukemia to evaluate novel therapies.

Myelodysplastic syndromes (MDS) are a diverse group of hematopoietic stem cell disorders that are defined by ineffective hematopoiesis, peripheral blood ...

Pan-myeloid Differentiation of Human Cord Blood Derived CD34+ Hematopoietic Stem and Progenitor Cells

Ex vivo differentiation of human hematopoietic stem cells is a widely used model for studying hematopoiesis. The protocol described here is for cytokine induced differentiation of CD34+ hematopoietic stem and progenitor cells to the four myeloid lineage cells. CD34+ cells are isolated from human umbilical cord blood and co-cultured with MS-5 stromal cells in the presence of cytokines. Immunophenotypic characterization of the stem and progenitor cells, and the differentiated myeloid lineage cells are described. Using this protocol, CD34+ cells may be incubated with small molecules or transduced with lentiviruses to express myeloid disease mutations to investigate their impact on myeloid differentiation.

Pan-myeloid Differentiation of Human Cord Blood Derived CD34+ Hematopoietic Stem and Progenitor Cells

Here, we present a protocol for immunophenotypic characterization and cytokine induced differentiation of cord blood derived CD34+ hematopoietic stem and progenitor cells to the four myeloid lineages. The applications of this protocol include investigations on the effect of myeloid disease mutations or small molecules on myeloid differentiation of the CD34+ cells.

Ex vivo differentiation of human hematopoietic stem cells is a widely used model for studying hematopoiesis. The protocol described here is for cytokine ...

Identification and Isolation of Oligopotent and Lineage-committed Myeloid Progenitors from Mouse Bone Marrow

Myeloid progenitors that yield neutrophils, monocytes and dendritic cells (DCs) can be identified in and isolated from the bone marrow of mice for hematological and immunological analyses. For example, studies of the cellular and molecular properties of myeloid progenitor populations can reveal mechanisms underlying leukemic transformation, or demonstrate how the immune system responds to pathogen exposure. Previously described flow cytometry strategies for myeloid progenitor identification have enabled significant advances in many fields, but the fractions they identify are very heterogeneous. The most commonly used gating strategies define bone marrow fractions that are enriched for the desired populations, but also contain large numbers of &#34;contaminating&#34; progenitors. Our recent studies have resolved much of this heterogeneity, and the protocol we present here permits the isolation of 6 subpopulations of oligopotent and lineage-committed myeloid progenitors from 2 previously described bone marrow fractions. The protocol describes 3 stages: 1) isolation of bone marrow cells, 2) enrichment for hematopoietic progenitors by magnetic-activated cell sorting (lineage depletion by MACS), and 3) identification of myeloid progenitor subsets by flow cytometry (including fluorescence-activated cell sorting, FACS, if desired). This approach permits progenitor quantification and isolation for a variety of in vitro and in vivo applications, and has already yielded novel insight into pathways and mechanisms of neutrophil, monocyte, and DC differentiation.

We demonstrate how to identify and isolate 6 subsets of myeloid progenitors from murine bone marrow using a combination of magnetic and fluorescence sorting (MACS and FACS). This protocol can be used for in vitro culture assays (methylcellulose or liquid cultures), in vivo adoptive transfer experiments, and RNA/protein analyses.

Myeloid progenitors that yield neutrophils, monocytes and dendritic cells (DCs) can be identified in and isolated from the bone marrow of mice for ...

Immunology and Infection

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

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

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

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

Medicine

Immunophenotyping and Cell Sorting of Human MKs from Human Primary Sources or Differentiated In Vitro from Hematopoietic Progenitors

Megakaryocyte (MK) differentiation encompasses a number of endomitotic cycles that result in a highly polyploid (reaching even&#160;&#62;64N) and extremely large cell (40-60 &#181;m). As opposed to the fast-increasing knowledge in megakaryopoiesis at the cell biology and molecular level, the characterization of megakaryopoiesis by flow cytometry is limited to the identification of mature MKs using lineage-specific surface markers, while earlier MK differentiation stages remain unexplored. Here, we present an immunophenotyping strategy that allows the identification of successive MK differentiation stages, with increasing ploidy status, in human primary sources or in vitro cultures with a panel integrating MK specific and non-specific surface markers. Despite its size and fragility, MKs can be immunophenotyped using the above-mentioned panel and enriched by fluorescence-activated cell sorting under specific conditions of pressure and nozzle diameter. This approach facilitates multi-Omics studies, with the aim to better understand the complexity of megakaryopoiesis and platelet production in humans. A better characterization of megakaryopoiesis may pose fundamental in the diagnosis or prognosis of lineage-related pathologies and malignancy.

Immunophenotyping and Cell Sorting of Human MKs from Human Primary Sources or Differentiated In Vitro from Hematopoietic Progenitors

Here, we present an immunophenotyping strategy for the characterization of megakaryocyte differentiation, and show how that strategy allows the sorting of megakaryocytes at different stages with a fluorescence-activated cell sorter. The methodology can be applied to human primary tissues, but also to megakaryocytes generated in culture in vitro.

Megakaryocyte (MK) differentiation encompasses a number of endomitotic cycles that result in a highly polyploid (reaching even&#160;&#62;64N) and ...

Biology

Flow Cytometry Analysis of Murine Bone Marrow Hematopoietic Stem and Progenitor Cells and Stromal Niche Cells

The bone marrow (BM) is the soft tissue found within bones where hematopoiesis, the process by which new blood cells are generated, primarily occurs. As such, it contains hematopoietic stem and progenitor cells (HSPCs), as well as supporting stromal cells that contribute to the maintenance and regulation of HSPCs. Hematological and other BM disorders disrupt hematopoiesis by affecting hematopoietic cells directly and/or through the alteration of the BM niche. Here, we describe a method to study hematopoiesis in health and malignancy through the phenotypic analysis of murine BM HSPCs and stromal niche populations by flow cytometry. Our method details the required steps to enrich BM cells in endosteal and central BM fractions, as well as the appropriate gating strategies to identify the two key niche cell types involved in HSPC regulation, endothelial cells and mesenchymal stem cells. The phenotypic analysis proposed here may be combined with mouse mutants, disease models, and functional assays to characterize the HSPC compartment and its niche.

Here, we describe a simple protocol for the isolation and staining of murine bone marrow cells to phenotype hemopoietic stem and progenitor cells along with the supporting niche endothelial and mesenchymal stem cells. A method to enrich cells located in endosteal and central bone marrow areas is also included.

The bone marrow (BM) is the soft tissue found within bones where hematopoiesis, the process by which new blood cells are generated, primarily occurs. As ...

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

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