Cellular phenotypes of normal and leukemic hemopoietic cells determined by analysis with selected antibody combinations

Blood ◽  
1980 ◽  
Vol 56 (3) ◽  
pp. 430-441 ◽  
Author(s):  
G Janossy ◽  
FJ Bollum ◽  
KF Bradstock ◽  
J Ashley
Keyword(s):  
Bone Marrow ◽  
Monoclonal Antibodies ◽  
Single Cell ◽  
Normal Cell ◽  
Cell Types ◽  
Precursor Cells ◽  
Leukemic Cells ◽  
Double Staining ◽  
Cell Assays ◽  
Cellular Phenotypes

Abstract Individual leukemic cells and the corresponding rare normal cell types in nonleukemic bone marrow were analyzed with various combinations of antisera (labeled with different fluorochromes: TRITC and FITC). Double staining for membrane Ia-like molecules (TRITC) and nuclear terminal transferase (FITC) was a very useful combination that distinguished common non-T, non-B ALL (Ia+,TdT+) and thymic ALL (Ia-,TdT+) from the rare cases of B ALL (Ia+,TdT-) and from AML (frequently Ia+, TdT-; in some cases Ia-, TdT-). Additional antisera (such as anti-ALL, anti- HuTLA, anti-immunoglobulin reagents, etc.) confirmed the diagnosis and further characterized the leukemic blasts. Ia+,TdT+ cells could be observed in low numbers in normal and nonleukemic regenerating marrow and were probably normal precursor cells; this reagent combinations was, therefore, not useful for monitoring residual non-T, non-B ALL blasts in treated patients. Other marker combinations detecting pre-B ALL blasts (double staining for cytoplasmic IgM and nuclear TdT) and Thy-ALL blasts (HuTLA+,TdT+) were, however, virtually leukemia specific in the bone marrow and could be used to effectively monitor residual leukemic cells throughout the disease. These combined single-cell assays are not only economical and informative but are also important for assessing the heterogeneity of leukemia and for standardizing new mouse or rat monoclonal antibodies for diagnosis.

scholarly journals Cellular phenotypes of normal and leukemic hemopoietic cells determined by analysis with selected antibody combinations

Blood ◽  
1980 ◽  
Vol 56 (3) ◽  
pp. 430-441
Author(s):  
G Janossy ◽  
FJ Bollum ◽  
KF Bradstock ◽  
J Ashley
Keyword(s):  
Bone Marrow ◽  
Monoclonal Antibodies ◽  
Single Cell ◽  
Normal Cell ◽  
Cell Types ◽  
Precursor Cells ◽  
Leukemic Cells ◽  
Double Staining ◽  
Cell Assays ◽  
Cellular Phenotypes

Individual leukemic cells and the corresponding rare normal cell types in nonleukemic bone marrow were analyzed with various combinations of antisera (labeled with different fluorochromes: TRITC and FITC). Double staining for membrane Ia-like molecules (TRITC) and nuclear terminal transferase (FITC) was a very useful combination that distinguished common non-T, non-B ALL (Ia+,TdT+) and thymic ALL (Ia-,TdT+) from the rare cases of B ALL (Ia+,TdT-) and from AML (frequently Ia+, TdT-; in some cases Ia-, TdT-). Additional antisera (such as anti-ALL, anti- HuTLA, anti-immunoglobulin reagents, etc.) confirmed the diagnosis and further characterized the leukemic blasts. Ia+,TdT+ cells could be observed in low numbers in normal and nonleukemic regenerating marrow and were probably normal precursor cells; this reagent combinations was, therefore, not useful for monitoring residual non-T, non-B ALL blasts in treated patients. Other marker combinations detecting pre-B ALL blasts (double staining for cytoplasmic IgM and nuclear TdT) and Thy-ALL blasts (HuTLA+,TdT+) were, however, virtually leukemia specific in the bone marrow and could be used to effectively monitor residual leukemic cells throughout the disease. These combined single-cell assays are not only economical and informative but are also important for assessing the heterogeneity of leukemia and for standardizing new mouse or rat monoclonal antibodies for diagnosis.

scholarly journals Analysis of human bone marrow with monoclonal antibodies.

1985 ◽  
Vol 33 (12) ◽  
pp. 1183-1189 ◽  
Author(s):  
P J Thurlow ◽  
L Kerrigan ◽  
R A Harris ◽  
I F McKenzie
Keyword(s):  
Bone Marrow ◽  
Monoclonal Antibodies ◽  
Specific Antigen ◽  
Cell Types ◽  
Diagnostic Value ◽  
Immunofluorescence Assay ◽  
Simple Method ◽  
Antigenic Phenotype ◽  
Beta 2 Microglobulin ◽  
Cellular Phenotypes

In order to study the antigenic phenotype of different hemopoietic cells, we used a series of monoclonal antibodies to investigate normal bone marrow in a standard immunofluorescence assay. The antibodies detected the following antigens: HLA-ABC, beta 2-microglobulin (beta 2m), HLA-DR (Ia), a lymphocyte subset and specific antigen (T and B) HuLy-m2, m3, T lymphocyte antigen (HuLy-m1), lymphocyte T200 antigen (HuLy-m4), a viral-associated antigen (HuLy-m5), and platelet-specific glycoproteins IIb-IIIa (HuPl-m1). The following results were obtained: (a) normoblasts were weakly HLA-ABC+, beta 2m+ and Ia-; all other lymphocyte and platelet antigens were not detected. (b) Myeloid cells at all stages of differentiation (promyelocytes, myelocytes, metamyelocytes, and neutrophils) were HLA-ABC+; beta 2m+; HuLy-m1-, m2-, m3+/- (20%), m4+, m5+/- (20%); HuPl-m1-; in addition, promyelocytes and myelocytes were Ia+ but neutrophils and metamyelocytes were Ia-. (c) Lymphocytes were HLA-ABC+, beta 2m+, Ia+/- (20-30%), HuLy-m1+/- (40-50%), m2+/- (60-70%), m3+, m4+, m5+; Pl-m1-. (d) Platelets and megakaryocytes were HLA-ABC+; beta 2m+; Ia-; HuLy-m1+-, m2-, m3-, m4-, m5-, HuPl-m1+, and the putative "megakaryocyte precursors" were HuPl-m1+, Ia-, HuLy-m1-. The different cell types in bone marrow could readily be distinguished, particularly cells of the myeloid series (Ia and HuLy-m4, m5), lymphocytes (Ia and HuLy-m1, m2, m3), and platelets and their precursor cells (HuPl-m1). This simple method of defining cellular phenotypes in bone marrow has demonstrated the practicality of using monoclonal antibodies to identify marrow cells and should be of diagnostic value.

scholarly journals Expression of the three myeloid cell-associated immunoglobulin G Fc receptors defined by murine monoclonal antibodies on normal bone marrow and acute leukemia cells

Blood ◽  
1989 ◽  
Vol 73 (7) ◽  
pp. 1951-1956
Author(s):  
ED Ball ◽  
J McDermott ◽  
JD Griffin ◽  
FR Davey ◽  
R Davis ◽  
...  
Keyword(s):  
Bone Marrow ◽  
Monoclonal Antibodies ◽  
Acute Leukemia ◽  
Cell Sorting ◽  
Lymphoblastic Leukemia ◽  
Mononuclear Phagocytes ◽  
Leukemic Cells ◽  
Leukemia Cells ◽  
Normal Bone Marrow ◽  
Normal Bone

Monoclonal antibodies (MoAbs) have been prepared recently that recognize the three cell-surface receptors for the Fc portion of immunoglobulin (Ig), termed Fc gamma RI (MoAb 32.2), Fc gamma R II (MoAb IV-3), and Fc gamma R III (MoAb 3G8) that are expressed on selected subsets of non-T lymphocyte peripheral blood leukocytes. In the blood, Fc gamma R I is expressed exclusively on monocytes and macrophages, Fc gamma R II on granulocytes, mononuclear phagocytes, platelets, and B cells, and Fc gamma R III on granulocytes and natural killer (NK) cells. We have examined the expression of these molecules on normal bone marrow (BM) cells and on leukemia cells from the blood and/or BM in order to determine their normal ontogeny as well as their distribution on leukemic cells. BM was obtained from six normal volunteers and from 170 patients with newly diagnosed acute leukemia. Normal BM cells were found to express Fc gamma R I, II, and III with the following percentages: 40%, 58%, and 56%, respectively. Cell sorting revealed that both Fc gamma R I and Fc gamma R II were detectable on all subclasses of myeloid precursors as early as myeloblasts. Cell sorting experiments revealed that 66% of the granulocyte-monocyte colony-forming cells (CFU-GM) and 50% of erythroid burst-forming units (BFU-E) were Fc gamma R II positive with only 20% and 28%, respectively, of CFU-GM and BFU-E were Fc gamma R I positive. Acute myeloid leukemia (AML) cells expressed the three receptors with the following frequency (n = 146): Fc gamma R I, 58%; Fc gamma R II, 67%; and Fc gamma R III, 26% of patients. Despite the fact that Fc gamma R I is only expressed on monocytes among blood cells, AML cells without monocytoid differentiation (French-American-British [FAB]M1, M2, M3, M6) were sometimes positive for this receptor. However, Fc gamma R I was highly correlated with FAB M4 and M5 morphology (P less than .001). Fc gamma R II was also correlated with FAB M4 and M5 morphology (P = .003). Cells from 11 patients with acute lymphoblastic leukemia were negative for Fc gamma R I, but six cases were positive for Fc gamma R II and III (not the same patients). These studies demonstrate that Ig Fc gamma R are acquired during normal differentiation in the BM at or before the level of colony-forming units. In addition, we show that acute leukemia cells commonly express Fc gamma R.

scholarly journals Simultaneous trimodal single-cell measurement of transcripts, epitopes, and chromatin accessibility using TEA-seq

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Elliott Swanson ◽  
Cara Lord ◽  
Julian Reading ◽  
Alexander T Heubeck ◽  
Palak C Genge ◽  
...  
Keyword(s):  
Gene Regulation ◽  
Single Cell ◽  
Human Peripheral Blood ◽  
Single Cells ◽  
Cell Types ◽  
Chromatin Accessibility ◽  
Specific Gene ◽  
Test Case ◽  
Cell Assays ◽  
Paired Measurement

Single-cell measurements of cellular characteristics have been instrumental in understanding the heterogeneous pathways that drive differentiation, cellular responses to signals, and human disease. Recent advances have allowed paired capture of protein abundance and transcriptomic state, but a lack of epigenetic information in these assays has left a missing link to gene regulation. Using the heterogeneous mixture of cells in human peripheral blood as a test case, we developed a novel scATAC-seq workflow that increases signal-to-noise and allows paired measurement of cell surface markers and chromatin accessibility: integrated cellular indexing of chromatin landscape and epitopes, called ICICLE-seq. We extended this approach using a droplet-based multiomics platform to develop a trimodal assay that simultaneously measures transcriptomics (scRNA-seq), epitopes, and chromatin accessibility (scATAC-seq) from thousands of single cells, which we term TEA-seq. Together, these multimodal single-cell assays provide a novel toolkit to identify type-specific gene regulation and expression grounded in phenotypically defined cell types.

scholarly journals Transfer learning efficiently maps bone marrow cell types from mouse to human using single-cell RNA sequencing

2020 ◽  
Vol 3 (1) ◽  
Author(s):  
Patrick S. Stumpf ◽  
Xin Du ◽  
Haruka Imanishi ◽  
Yuya Kunisaki ◽  
Yuichiro Semba ◽  
...  
Keyword(s):  
Machine Learning ◽  
Bone Marrow ◽  
Single Cell ◽  
Rna Sequencing ◽  
Transfer Learning ◽  
Biomedical Research ◽  
Human Cell ◽  
Cell Types ◽  
Single Cell Rna Sequencing ◽  
Using Data

AbstractBiomedical research often involves conducting experiments on model organisms in the anticipation that the biology learnt will transfer to humans. Previous comparative studies of mouse and human tissues were limited by the use of bulk-cell material. Here we show that transfer learning—the branch of machine learning that concerns passing information from one domain to another—can be used to efficiently map bone marrow biology between species, using data obtained from single-cell RNA sequencing. We first trained a multiclass logistic regression model to recognize different cell types in mouse bone marrow achieving equivalent performance to more complex artificial neural networks. Furthermore, it was able to identify individual human bone marrow cells with 83% overall accuracy. However, some human cell types were not easily identified, indicating important differences in biology. When re-training the mouse classifier using data from human, less than 10 human cells of a given type were needed to accurately learn its representation. In some cases, human cell identities could be inferred directly from the mouse classifier via zero-shot learning. These results show how simple machine learning models can be used to reconstruct complex biology from limited data, with broad implications for biomedical research.

scholarly journals Expression of the three myeloid cell-associated immunoglobulin G Fc receptors defined by murine monoclonal antibodies on normal bone marrow and acute leukemia cells

Blood ◽  
1989 ◽  
Vol 73 (7) ◽  
pp. 1951-1956 ◽  
Author(s):  
ED Ball ◽  
J McDermott ◽  
JD Griffin ◽  
FR Davey ◽  
R Davis ◽  
...  
Keyword(s):  
Bone Marrow ◽  
Monoclonal Antibodies ◽  
Acute Leukemia ◽  
Cell Sorting ◽  
Lymphoblastic Leukemia ◽  
Mononuclear Phagocytes ◽  
Leukemic Cells ◽  
Leukemia Cells ◽  
Normal Bone Marrow ◽  
Normal Bone

Abstract Monoclonal antibodies (MoAbs) have been prepared recently that recognize the three cell-surface receptors for the Fc portion of immunoglobulin (Ig), termed Fc gamma RI (MoAb 32.2), Fc gamma R II (MoAb IV-3), and Fc gamma R III (MoAb 3G8) that are expressed on selected subsets of non-T lymphocyte peripheral blood leukocytes. In the blood, Fc gamma R I is expressed exclusively on monocytes and macrophages, Fc gamma R II on granulocytes, mononuclear phagocytes, platelets, and B cells, and Fc gamma R III on granulocytes and natural killer (NK) cells. We have examined the expression of these molecules on normal bone marrow (BM) cells and on leukemia cells from the blood and/or BM in order to determine their normal ontogeny as well as their distribution on leukemic cells. BM was obtained from six normal volunteers and from 170 patients with newly diagnosed acute leukemia. Normal BM cells were found to express Fc gamma R I, II, and III with the following percentages: 40%, 58%, and 56%, respectively. Cell sorting revealed that both Fc gamma R I and Fc gamma R II were detectable on all subclasses of myeloid precursors as early as myeloblasts. Cell sorting experiments revealed that 66% of the granulocyte-monocyte colony-forming cells (CFU-GM) and 50% of erythroid burst-forming units (BFU-E) were Fc gamma R II positive with only 20% and 28%, respectively, of CFU-GM and BFU-E were Fc gamma R I positive. Acute myeloid leukemia (AML) cells expressed the three receptors with the following frequency (n = 146): Fc gamma R I, 58%; Fc gamma R II, 67%; and Fc gamma R III, 26% of patients. Despite the fact that Fc gamma R I is only expressed on monocytes among blood cells, AML cells without monocytoid differentiation (French-American-British [FAB]M1, M2, M3, M6) were sometimes positive for this receptor. However, Fc gamma R I was highly correlated with FAB M4 and M5 morphology (P less than .001). Fc gamma R II was also correlated with FAB M4 and M5 morphology (P = .003). Cells from 11 patients with acute lymphoblastic leukemia were negative for Fc gamma R I, but six cases were positive for Fc gamma R II and III (not the same patients). These studies demonstrate that Ig Fc gamma R are acquired during normal differentiation in the BM at or before the level of colony-forming units. In addition, we show that acute leukemia cells commonly express Fc gamma R.

scholarly journals TEA-seq: a trimodal assay for integrated single cell measurement of transcription, epitopes, and chromatin accessibility

2020 ◽  
Author(s):  
Elliott Swanson ◽  
Cara Lord ◽  
Julian Reading ◽  
Alexander T. Heubeck ◽  
Adam K. Savage ◽  
...  
Keyword(s):  
Cell Surface ◽  
Single Cell ◽  
Human Peripheral Blood ◽  
Signal To Noise Ratio ◽  
Single Cells ◽  
Cell Types ◽  
Chromatin Accessibility ◽  
Specific Gene ◽  
Test Case ◽  
Cell Assays

AbstractSingle-cell measurements of cellular characteristics have been instrumental in understanding the heterogeneous pathways that drive differentiation, cellular responses to extracellular signals, and human disease states. scATAC-seq has been particularly challenging due to the large size of the human genome and processing artefacts resulting from DNA damage that are an inherent source of background signal. Downstream analysis and integration of scATAC-seq with other single-cell assays is complicated by the lack of clear phenotypic information linking chromatin state and cell type. Using the heterogeneous mixture of cells in human peripheral blood as a test case, we developed a novel scATAC-seq workflow that increases the signal-to-noise ratio and allows simultaneous measurement of cell surface markers: Integrated Cellular Indexing of Chromatin Landscape and Epitopes (ICICLE-seq). We extended this approach using a droplet-based multiomics platform to develop a trimodal assay to simultaneously measure Transcriptomic state (scRNA-seq), cell surface Epitopes, and chromatin Accessibility (scATAC-seq) from thousands of single cells, which we term TEA-seq. Together, these multimodal single-cell assays provide a novel toolkit to identify type-specific gene regulation and expression grounded in phenotypically defined cell types.

scholarly journals Combined single-cell and spatial transcriptomics reveals the molecular, cellular and spatial bone marrow niche organization

2019 ◽  
Author(s):  
Chiara Baccin ◽  
Jude Al-Sabah ◽  
Lars Velten ◽  
Patrick M. Helbling ◽  
Florian Grünschläger ◽  
...  
Keyword(s):  
Bone Marrow ◽  
Single Cell ◽  
Spatial Organization ◽  
Cell Types ◽  
Bone Marrow Niche ◽  
Cellular Composition ◽  
Spatially Resolved ◽  
Resident Cell ◽  
Cell Gene Expression ◽  
Novel Strategy

SUMMARYThe bone marrow (BM) constitutes the primary site for life-long blood production and skeletal regeneration. However, its cellular composition and the spatial organization into distinct ‘niches’ remains controversial. Here, we combine single-cell and spatially resolved transcriptomics to systematically map the molecular and cellular composition of the endosteal, sinusoidal, and arteriolar BM niches. This allowed us to transcriptionally profile all major BM resident cell types, determine their localization, and clarify the cellular and spatial sources of key growth factors and cytokines. Our data demonstrate that previously unrecognized Cxcl12-abundant reticular (CAR) cell subsets (i.e. Adipo- and Osteo-CAR cells) differentially localize to sinusoidal or arteriolar surfaces, locally act as ‘professional cytokine secreting cells’, and thereby establish distinct peri-vascular micro-niches. Importantly, we also demonstrate that the 3-dimensional organization of the BM can be accurately inferred from single-cell gene expression data using the newly developed RNA-Magnet algorithm. Together, our study reveals the cellular and spatial organization of BM niches, and offers a novel strategy to dissect the complex organization of whole organs in a systematic manner.One Sentence SummaryIntegration of single-cell and spatial transcriptomics reveals the molecular, cellular and spatial organization of bone marrow niches

scholarly journals Response of single leukemic cells to peptidase inhibitor therapy across time and dose using a microfluidic device

2014 ◽  
Vol 6 (2) ◽  
pp. 164-174 ◽  
Author(s):  
Michelle L. Kovarik ◽  
Alexandra J. Dickinson ◽  
Pourab Roy ◽  
Ranjit A. Poonnen ◽  
Jason P. Fine ◽  
...  
Keyword(s):  
Single Cell ◽  
Microfluidic Device ◽  
Biological Effects ◽  
Regression Modeling ◽  
Inhibitor Therapy ◽  
Leukemic Cells ◽  
Peptide Degradation ◽  
Cell Assays ◽  
Peptidase Inhibitor

Microfluidic single-cell assays of peptide degradation were performed at varying inhibitor doses, and the resulting data were analyzed by regression modeling to reveal biological effects.

scholarly journals Mapping human cell phenotypes to genotypes with single-cell genomics

Science ◽  
2019 ◽  
Vol 365 (6460) ◽  
pp. 1401-1405 ◽  
Author(s):  
J. Gray Camp ◽  
Randall Platt ◽  
Barbara Treutlein
Keyword(s):  
Single Cell ◽  
Human Cell ◽  
Cell Biology ◽  
Life Histories ◽  
Gene Editing ◽  
Cell Types ◽  
Single Cell Genomics ◽  
Cumulative Activity ◽  
Cellular Phenotypes ◽  
Cell Phenotypes

The cumulative activity of all of the body’s cells, with their myriad interactions, life histories, and environmental experiences, gives rise to a condition that is distinctly human and specific to each individual. It is an enduring goal to catalog our human cell types, to understand how they develop, how they vary between individuals, and how they fail in disease. Single-cell genomics has revolutionized this endeavor because sequencing-based methods provide a means to quantitatively annotate cell states on the basis of high-information content and high-throughput measurements. Together with advances in stem cell biology and gene editing, we are in the midst of a fascinating journey to understand the cellular phenotypes that compose human bodies and how the human genome is used to build and maintain each cell. Here, we will review recent advances into how single-cell genomics is being used to develop personalized phenotyping strategies that cross subcellular, cellular, and tissue scales to link our genome to our cumulative cellular phenotypes.

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