Single-Cell Analysis Reveals the Range of Transcriptional States of Circulating Human Neutrophils

To date, neutrophils have been characterized based on discrete parameters like cell-surface markers, buoyancy, maturity, or tissue localization.Single-cell RNA sequencing (scRNA-seq) has been an important addition to the set of analytical tools, as itoffers an unbiased view of cells along a continuum of transcriptional states, including those that fall between theoretically more stable endpoints. However, the use of scRNA-seqto characterize transcriptional variation in neutrophils has proven technically difficult, explaining in part the paucity of published single-cell data on neutrophils compared to other celltypes. We report a modified analysis pipeline that substantially increases the detection of human neutrophils in scRNA-seq. We applied this pipeline to the study of > 185,000 human neutrophils. Our findings indicate that circulating human neutrophils are transcriptionally heterogeneous cells, which can be classified based on their transcriptional state into one of four clusters that are highly reproducible among healthy human subjects. We demonstrate that neutrophils shiftfrom relatively immature (Nh0) cells, through a transitional phenotype (Nh1), into one of two endpoints defined by either relative transcriptional inactivity (Nh2) or high expression oftype I interferon-induciblegenes (Nh3).Transitions among states are characterized by the expression of specific transcription factors. By simultaneouslymeasuring surface proteinand intracellular transcriptabundance at the single-cell level, we show that these four transcriptional subsets are independent of the canonical surface proteins that are commonly used to define and characterize human neutrophils.These findings provide a new view of human neutrophil heterogeneity, along a continuum of transcriptional states, with potential implications for the characterization of neutrophils in health and disease.