Delineating stages of erythropoiesis using imaging flow cytometry
[Display omitted] •Imaging flow cytometry (IFC) can delineate seven erythroid populations in bone marrow.•IFC-based erythroid intermediates correlate with histologically-defined intermediates.•Intermediate erythroid precursors are not distinguished by CD71 or CD44 staining.•Better separation of eryt...
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•Imaging flow cytometry (IFC) can delineate seven erythroid populations in bone marrow.•IFC-based erythroid intermediates correlate with histologically-defined intermediates.•Intermediate erythroid precursors are not distinguished by CD71 or CD44 staining.•Better separation of erythroid precursors is achieved using cell and nuclear size.•IFC can address challenges of limited cell markers and gating on a continuum.
Adult humans need to make 2.5million red blood cells (RBCs) every second to maintain a steady state level of 25trillion circulating RBCs. Understanding normal erythropoiesis as well as diseases that afflict the erythron, such as genetic anemias, hyperproliferative disorders, and myelodysplastic syndromes, requires a robust method to delineate erythropoietic intermediates. In order to apply the power of flow cytometry to these studies, challenges of limited immunophenotypic markers, incorporation of significant changes in morphology, and maturational changes that occur along a continuum need to be met. Imaging flow cytometry (IFC) provides a solution to address these challenges. Integration of changes in immunophenotype, loss of RNA (ribosomes), and enucleation, with morphological characteristics of cell and nuclear size, can be used to delineate erythroblasts that correlate with classical histological classifications. A protocol is described that demonstrates the basic approaches of staining panel selection, mask generation and selection of features to best sequentially refine erythroid intermediates and remove contaminating cells with overlapping immunophenotype. Ultimately erythroid cells in the murine bone marrow are divided into seven sub-populations using IFC including four erythroblasts (pro-, basophilic, polychromatophilic and orthochromatic), the pyrenocyte, which contains the eliminated nucleus, the enucleated reticulocyte and the mature RBC. |
doi_str_mv | 10.1016/j.ymeth.2016.08.012 |
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•Imaging flow cytometry (IFC) can delineate seven erythroid populations in bone marrow.•IFC-based erythroid intermediates correlate with histologically-defined intermediates.•Intermediate erythroid precursors are not distinguished by CD71 or CD44 staining.•Better separation of erythroid precursors is achieved using cell and nuclear size.•IFC can address challenges of limited cell markers and gating on a continuum.
Adult humans need to make 2.5million red blood cells (RBCs) every second to maintain a steady state level of 25trillion circulating RBCs. Understanding normal erythropoiesis as well as diseases that afflict the erythron, such as genetic anemias, hyperproliferative disorders, and myelodysplastic syndromes, requires a robust method to delineate erythropoietic intermediates. In order to apply the power of flow cytometry to these studies, challenges of limited immunophenotypic markers, incorporation of significant changes in morphology, and maturational changes that occur along a continuum need to be met. Imaging flow cytometry (IFC) provides a solution to address these challenges. Integration of changes in immunophenotype, loss of RNA (ribosomes), and enucleation, with morphological characteristics of cell and nuclear size, can be used to delineate erythroblasts that correlate with classical histological classifications. A protocol is described that demonstrates the basic approaches of staining panel selection, mask generation and selection of features to best sequentially refine erythroid intermediates and remove contaminating cells with overlapping immunophenotype. Ultimately erythroid cells in the murine bone marrow are divided into seven sub-populations using IFC including four erythroblasts (pro-, basophilic, polychromatophilic and orthochromatic), the pyrenocyte, which contains the eliminated nucleus, the enucleated reticulocyte and the mature RBC.</description><identifier>ISSN: 1046-2023</identifier><identifier>EISSN: 1095-9130</identifier><identifier>DOI: 10.1016/j.ymeth.2016.08.012</identifier><identifier>PMID: 27582124</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>Animals ; Biomarkers - metabolism ; Bone marrow ; Bone Marrow Cells - classification ; Bone Marrow Cells - cytology ; Bone Marrow Cells - metabolism ; Cell cycle ; Cell Cycle - genetics ; Cell Differentiation ; Cell Lineage - genetics ; Cell Nucleus - ultrastructure ; Erythroblasts - cytology ; Erythroblasts - metabolism ; Erythrocytes - cytology ; Erythrocytes - metabolism ; Erythroid ; Erythropoiesis - genetics ; Flow Cytometry - instrumentation ; Flow Cytometry - methods ; Humans ; Image Cytometry - instrumentation ; Image Cytometry - methods ; ImageStream ; Imaging flow cytometry ; Mice ; Primary Cell Culture ; RBC ; Reticulocytes - cytology ; Reticulocytes - metabolism ; Ribosomes - ultrastructure ; Staining and Labeling - methods</subject><ispartof>Methods (San Diego, Calif.), 2017-01, Vol.112, p.68-74</ispartof><rights>2016 Elsevier Inc.</rights><rights>Copyright © 2016 Elsevier Inc. All rights reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c429t-5bf8fe8e79b45a5826c82ac6a16be571976460561ebe68e9166fee8b9644ac3c3</citedby><cites>FETCH-LOGICAL-c429t-5bf8fe8e79b45a5826c82ac6a16be571976460561ebe68e9166fee8b9644ac3c3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.ymeth.2016.08.012$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/27582124$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>McGrath, K.E.</creatorcontrib><creatorcontrib>Catherman, S.C.</creatorcontrib><creatorcontrib>Palis, J.</creatorcontrib><title>Delineating stages of erythropoiesis using imaging flow cytometry</title><title>Methods (San Diego, Calif.)</title><addtitle>Methods</addtitle><description>[Display omitted]
•Imaging flow cytometry (IFC) can delineate seven erythroid populations in bone marrow.•IFC-based erythroid intermediates correlate with histologically-defined intermediates.•Intermediate erythroid precursors are not distinguished by CD71 or CD44 staining.•Better separation of erythroid precursors is achieved using cell and nuclear size.•IFC can address challenges of limited cell markers and gating on a continuum.
Adult humans need to make 2.5million red blood cells (RBCs) every second to maintain a steady state level of 25trillion circulating RBCs. Understanding normal erythropoiesis as well as diseases that afflict the erythron, such as genetic anemias, hyperproliferative disorders, and myelodysplastic syndromes, requires a robust method to delineate erythropoietic intermediates. In order to apply the power of flow cytometry to these studies, challenges of limited immunophenotypic markers, incorporation of significant changes in morphology, and maturational changes that occur along a continuum need to be met. Imaging flow cytometry (IFC) provides a solution to address these challenges. Integration of changes in immunophenotype, loss of RNA (ribosomes), and enucleation, with morphological characteristics of cell and nuclear size, can be used to delineate erythroblasts that correlate with classical histological classifications. A protocol is described that demonstrates the basic approaches of staining panel selection, mask generation and selection of features to best sequentially refine erythroid intermediates and remove contaminating cells with overlapping immunophenotype. Ultimately erythroid cells in the murine bone marrow are divided into seven sub-populations using IFC including four erythroblasts (pro-, basophilic, polychromatophilic and orthochromatic), the pyrenocyte, which contains the eliminated nucleus, the enucleated reticulocyte and the mature RBC.</description><subject>Animals</subject><subject>Biomarkers - metabolism</subject><subject>Bone marrow</subject><subject>Bone Marrow Cells - classification</subject><subject>Bone Marrow Cells - cytology</subject><subject>Bone Marrow Cells - metabolism</subject><subject>Cell cycle</subject><subject>Cell Cycle - genetics</subject><subject>Cell Differentiation</subject><subject>Cell Lineage - genetics</subject><subject>Cell Nucleus - ultrastructure</subject><subject>Erythroblasts - cytology</subject><subject>Erythroblasts - metabolism</subject><subject>Erythrocytes - cytology</subject><subject>Erythrocytes - metabolism</subject><subject>Erythroid</subject><subject>Erythropoiesis - genetics</subject><subject>Flow Cytometry - instrumentation</subject><subject>Flow Cytometry - methods</subject><subject>Humans</subject><subject>Image Cytometry - instrumentation</subject><subject>Image Cytometry - methods</subject><subject>ImageStream</subject><subject>Imaging flow cytometry</subject><subject>Mice</subject><subject>Primary Cell Culture</subject><subject>RBC</subject><subject>Reticulocytes - cytology</subject><subject>Reticulocytes - metabolism</subject><subject>Ribosomes - ultrastructure</subject><subject>Staining and Labeling - methods</subject><issn>1046-2023</issn><issn>1095-9130</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kM9PwyAUx4nROJ3-BSamRy-tQFsKBw_L_Jks8aJnQtnrxtKOCVTT_17qpkdP7xE-jy_vg9AVwRnBhN1usqGDsM5oPGSYZ5jQI3RGsChTQXJ8PPYFSymm-QSde7_BOCIVP0UTWpWcElqcodk9tGYLKpjtKvFBrcAntknADWHt7M4a8MYnvR-vTadWY21a-5XoIdgY74YLdNKo1sPloU7R--PD2_w5Xbw-vcxni1QXVIS0rBveAIdK1EWpYjzTnCrNFGE1lBURFSsYLhmBGhgHQRhrAHgtWFEonet8im727-6c_ejBB9kZr6Ft1RZs7yXhZcExEQJHNN-j2lnvHTRy5-Ln3SAJlqM7uZE_7uToTmIuo5g4dX0I6OsOln8zv7IicLcHIK75acBJrw1sNSyNAx3k0pp_A74BrgmBiQ</recordid><startdate>20170101</startdate><enddate>20170101</enddate><creator>McGrath, K.E.</creator><creator>Catherman, S.C.</creator><creator>Palis, J.</creator><general>Elsevier Inc</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope></search><sort><creationdate>20170101</creationdate><title>Delineating stages of erythropoiesis using imaging flow cytometry</title><author>McGrath, K.E. ; Catherman, S.C. ; Palis, J.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c429t-5bf8fe8e79b45a5826c82ac6a16be571976460561ebe68e9166fee8b9644ac3c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Animals</topic><topic>Biomarkers - metabolism</topic><topic>Bone marrow</topic><topic>Bone Marrow Cells - classification</topic><topic>Bone Marrow Cells - cytology</topic><topic>Bone Marrow Cells - metabolism</topic><topic>Cell cycle</topic><topic>Cell Cycle - genetics</topic><topic>Cell Differentiation</topic><topic>Cell Lineage - genetics</topic><topic>Cell Nucleus - ultrastructure</topic><topic>Erythroblasts - cytology</topic><topic>Erythroblasts - metabolism</topic><topic>Erythrocytes - cytology</topic><topic>Erythrocytes - metabolism</topic><topic>Erythroid</topic><topic>Erythropoiesis - genetics</topic><topic>Flow Cytometry - instrumentation</topic><topic>Flow Cytometry - methods</topic><topic>Humans</topic><topic>Image Cytometry - instrumentation</topic><topic>Image Cytometry - methods</topic><topic>ImageStream</topic><topic>Imaging flow cytometry</topic><topic>Mice</topic><topic>Primary Cell Culture</topic><topic>RBC</topic><topic>Reticulocytes - cytology</topic><topic>Reticulocytes - metabolism</topic><topic>Ribosomes - ultrastructure</topic><topic>Staining and Labeling - methods</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>McGrath, K.E.</creatorcontrib><creatorcontrib>Catherman, S.C.</creatorcontrib><creatorcontrib>Palis, J.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Methods (San Diego, Calif.)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>McGrath, K.E.</au><au>Catherman, S.C.</au><au>Palis, J.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Delineating stages of erythropoiesis using imaging flow cytometry</atitle><jtitle>Methods (San Diego, Calif.)</jtitle><addtitle>Methods</addtitle><date>2017-01-01</date><risdate>2017</risdate><volume>112</volume><spage>68</spage><epage>74</epage><pages>68-74</pages><issn>1046-2023</issn><eissn>1095-9130</eissn><abstract>[Display omitted]
•Imaging flow cytometry (IFC) can delineate seven erythroid populations in bone marrow.•IFC-based erythroid intermediates correlate with histologically-defined intermediates.•Intermediate erythroid precursors are not distinguished by CD71 or CD44 staining.•Better separation of erythroid precursors is achieved using cell and nuclear size.•IFC can address challenges of limited cell markers and gating on a continuum.
Adult humans need to make 2.5million red blood cells (RBCs) every second to maintain a steady state level of 25trillion circulating RBCs. Understanding normal erythropoiesis as well as diseases that afflict the erythron, such as genetic anemias, hyperproliferative disorders, and myelodysplastic syndromes, requires a robust method to delineate erythropoietic intermediates. In order to apply the power of flow cytometry to these studies, challenges of limited immunophenotypic markers, incorporation of significant changes in morphology, and maturational changes that occur along a continuum need to be met. Imaging flow cytometry (IFC) provides a solution to address these challenges. Integration of changes in immunophenotype, loss of RNA (ribosomes), and enucleation, with morphological characteristics of cell and nuclear size, can be used to delineate erythroblasts that correlate with classical histological classifications. A protocol is described that demonstrates the basic approaches of staining panel selection, mask generation and selection of features to best sequentially refine erythroid intermediates and remove contaminating cells with overlapping immunophenotype. Ultimately erythroid cells in the murine bone marrow are divided into seven sub-populations using IFC including four erythroblasts (pro-, basophilic, polychromatophilic and orthochromatic), the pyrenocyte, which contains the eliminated nucleus, the enucleated reticulocyte and the mature RBC.</abstract><cop>United States</cop><pub>Elsevier Inc</pub><pmid>27582124</pmid><doi>10.1016/j.ymeth.2016.08.012</doi><tpages>7</tpages></addata></record> |
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subjects | Animals Biomarkers - metabolism Bone marrow Bone Marrow Cells - classification Bone Marrow Cells - cytology Bone Marrow Cells - metabolism Cell cycle Cell Cycle - genetics Cell Differentiation Cell Lineage - genetics Cell Nucleus - ultrastructure Erythroblasts - cytology Erythroblasts - metabolism Erythrocytes - cytology Erythrocytes - metabolism Erythroid Erythropoiesis - genetics Flow Cytometry - instrumentation Flow Cytometry - methods Humans Image Cytometry - instrumentation Image Cytometry - methods ImageStream Imaging flow cytometry Mice Primary Cell Culture RBC Reticulocytes - cytology Reticulocytes - metabolism Ribosomes - ultrastructure Staining and Labeling - methods |
title | Delineating stages of erythropoiesis using imaging flow cytometry |
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