An immunophenotype-coupled transcriptomic atlas of human hematopoietic progenitors

被引:0
作者
Xuan Zhang
Baobao Song
Maximillian J. Carlino
Guangyuan Li
Kyle Ferchen
Mi Chen
Evrett N. Thompson
Bailee N. Kain
Dan Schnell
Kairavee Thakkar
Michal Kouril
Kang Jin
Stuart B. Hay
Sidharth Sen
David Bernardicius
Siyuan Ma
Sierra N. Bennett
Josh Croteau
Ornella Salvatori
Melvin H. Lye
Austin E. Gillen
Craig T. Jordan
Harinder Singh
Diane S. Krause
Nathan Salomonis
H. Leighton Grimes
机构
[1] Cincinnati Children’s Hospital Medical Center,Division of Immunobiology
[2] University of Cincinnati,Immunology Graduate Program
[3] Yale School of Medicine,Yale Stem Cell Center
[4] Yale University,Department of Laboratory Medicine
[5] Cincinnati Children’s Hospital Medical Center,Division of Biomedical Informatics
[6] Yale School of Medicine,Department of Cell Biology
[7] BioLegend,Division of Hematology
[8] Inc.,Departments of Immunology and Computational and Systems Biology, Center for Systems Immunology
[9] Curiox Biosystems,Department of Pediatrics
[10] Inc.,Division of Experimental Hematology and Cancer Biology
[11] University of Colorado School of Medicine,undefined
[12] Rocky Mountain Regional VA Medical Center,undefined
[13] University of Pittsburgh,undefined
[14] University of Cincinnati,undefined
[15] Cincinnati Children’s Hospital Medical Center,undefined
来源
Nature Immunology | 2024年 / 25卷
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摘要
Analysis of the human hematopoietic progenitor compartment is being transformed by single-cell multimodal approaches. Cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) enables coupled surface protein and transcriptome profiling, thereby revealing genomic programs underlying progenitor states. To perform CITE-seq systematically on primary human bone marrow cells, we used titrations with 266 CITE-seq antibodies (antibody-derived tags) and machine learning to optimize a panel of 132 antibodies. Multimodal analysis resolved >80 stem, progenitor, immune, stromal and transitional cells defined by distinctive surface markers and transcriptomes. This dataset enables flow cytometry solutions for in silico-predicted cell states and identifies dozens of cell surface markers consistently detected across donors spanning race and sex. Finally, aligning annotations from this atlas, we nominate normal marrow equivalents for acute myeloid leukemia stem cell populations that differ in clinical response. This atlas serves as an advanced digital resource for hematopoietic progenitor analyses in human health and disease.
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页码:703 / 715
页数:12
相关论文
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