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Lookup NU author(s): Daniela Basurto Lozada, Professor Muzlifah Haniffa
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© The Author(s) 2024.Natural killer (NK) cells are innate lymphoid cells (ILCs) contributing to immune responses to microbes and tumors. Historically, their classification hinged on a limited array of surface protein markers. Here, we used single-cell RNA sequencing (scRNA-seq) and cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) to dissect the heterogeneity of NK cells. We identified three prominent NK cell subsets in healthy human blood: NK1, NK2 and NK3, further differentiated into six distinct subgroups. Our findings delineate the molecular characteristics, key transcription factors, biological functions, metabolic traits and cytokine responses of each subgroup. These data also suggest two separate ontogenetic origins for NK cells, leading to divergent transcriptional trajectories. Furthermore, we analyzed the distribution of NK cell subsets in the lung, tonsils and intraepithelial lymphocytes isolated from healthy individuals and in 22 tumor types. This standardized terminology aims at fostering clarity and consistency in future research, thereby improving cross-study comparisons.
Author(s): Rebuffet L, Melsen JE, Escaliere B, Basurto-Lozada D, Bhandoola A, Bjorkstrom NK, Bryceson YT, Castriconi R, Cichocki F, Colonna M, Davis DM, Diefenbach A, Ding Y, Haniffa M, Horowitz A, Lanier LL, Malmberg K-J, Miller JS, Moretta L, Narni-Mancinelli E, O'Neill LAJ, Romagnani C, Ryan DG, Sivori S, Sun D, Vagne C, Vivier E
Publication type: Article
Publication status: Published
Journal: Nature Immunology
Year: 2024
Volume: 25
Pages: 1474–1488
Print publication date: 01/08/2024
Online publication date: 02/07/2024
Acceptance date: 23/05/2024
Date deposited: 16/07/2024
ISSN (print): 1529-2908
ISSN (electronic): 1529-2916
Publisher: Nature Research
URL: https://doi.org/10.1038/s41590-024-01883-0
DOI: 10.1038/s41590-024-01883-0
Data Access Statement: All the scRNA-seq and CITE-seq data used in this study have been deposited in the Gene Expression Omnibus. The accession code for each of the datasets used is listed in Supplementary Table 3. Datasets 1–7 correspond to the following accession numbers, respectively: GSE119562, GSE130430, GSE184329, GSE197037, GSE164378, GSE212890 and GSE240441. Single-cell sequencing data were aligned with the GRCh38 human reference genome. To make our data more accessible to the broader research community, we have created an interactive portal (https://collections.cellatlas.io/meta-nk) designed for easy analysis and visualization of our single-cell data. Code availability All the custom code used in this study has been deposited on GitHub (https://github.com/RebuffetLucas/Meta_NK_Project).
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