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Abstract
The full neutrophil heterogeneity and differentiation landscape remains incompletely characterized. Here, we profiled >25,000 differentiating and mature mouse neutrophils using single-cell RNA sequencing to provide a comprehensive transcriptional landscape of neutrophil maturation, function and fate decision in their steady state and during bacterial infection. Eight neutrophil populations were defined by distinct molecular signatures. The three mature peripheral blood neutrophil subsets arise from distinct maturing bone marrow neutrophil subsets. Driven by both known and uncharacterized transcription factors, neutrophils gradually acquire microbicidal capability as they traverse the transcriptional landscape, representing an evolved mechanism for fine-tuned regulation of an effective but balanced neutrophil response. Bacterial infection reprograms the genetic architecture of neutrophil populations, alters dynamic transitions between subpopulations and primes neutrophils for augmented functionality without affecting overall heterogeneity. In summary, these data establish a reference model and general framework for studying neutrophil-related disease mechanisms, biomarkers and therapeutic targets at single-cell resolution.
Luo and colleagues use single-cell RNA sequencing to provide a comprehensive transcriptional landscape of neutrophil maturation, function and fate decision in their steady state and during bacterial infection.
Details
; Shi, Qiang 2
; Wu, Peng 3 ; Zhang, Xiaoyu 1 ; Kambara Hiroto 4 ; Su Jiayu 5 ; Yu, Hongbo 6 ; Shin-Young, Park 4
; Guo Rongxia 3 ; Ren, Qian 3 ; Zhang Sudong 3 ; Xu Yuanfu 3 ; Silberstein, Leslie E 4 ; Cheng, Tao 3
; Ma, Fengxia 3
; Cheng, Li 2
; Luo, Hongbo R 4
1 Chinese Academy of Medical Sciences and Peking Union Medical College, The State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology and Blood Diseases Hospital, Tianjin, China (GRID:grid.506261.6) (ISNI:0000 0001 0706 7839); Harvard Medical School, Department of Pathology, Boston, USA (GRID:grid.38142.3c) (ISNI:000000041936754X); Boston Children’s Hospital, Department of Laboratory Medicine, The Stem Cell Program, Boston, USA (GRID:grid.2515.3) (ISNI:0000 0004 0378 8438); Dana-Farber/Harvard Cancer Center, Boston, USA (GRID:grid.477947.e) (ISNI:0000 0004 5902 1762)
2 Peking University, School of Life Sciences, Center for Bioinformatics, Center for Statistical Science, Beijing, China (GRID:grid.11135.37) (ISNI:0000 0001 2256 9319)
3 Chinese Academy of Medical Sciences and Peking Union Medical College, The State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology and Blood Diseases Hospital, Tianjin, China (GRID:grid.506261.6) (ISNI:0000 0001 0706 7839)
4 Harvard Medical School, Department of Pathology, Boston, USA (GRID:grid.38142.3c) (ISNI:000000041936754X); Boston Children’s Hospital, Department of Laboratory Medicine, The Stem Cell Program, Boston, USA (GRID:grid.2515.3) (ISNI:0000 0004 0378 8438); Dana-Farber/Harvard Cancer Center, Boston, USA (GRID:grid.477947.e) (ISNI:0000 0004 5902 1762)
5 Harvard Medical School, Department of Pathology, Boston, USA (GRID:grid.38142.3c) (ISNI:000000041936754X); Boston Children’s Hospital, Department of Laboratory Medicine, The Stem Cell Program, Boston, USA (GRID:grid.2515.3) (ISNI:0000 0004 0378 8438); Dana-Farber/Harvard Cancer Center, Boston, USA (GRID:grid.477947.e) (ISNI:0000 0004 5902 1762); Peking University, School of Life Sciences, Center for Bioinformatics, Center for Statistical Science, Beijing, China (GRID:grid.11135.37) (ISNI:0000 0001 2256 9319)
6 VA Boston Healthcare System, Department of Pathology and Laboratory Medicine, Boston, USA (GRID:grid.410370.1) (ISNI:0000 0004 4657 1992); Brigham and Women’s Hospital and Harvard Medical School, Department of Pathology, Boston, USA (GRID:grid.62560.37) (ISNI:0000 0004 0378 8294)





