Single-cell transcriptomics reveal a unique memory-like NK cell subset that accumulates with ageing and correlates with disease severity in COVID-19.

BACKGROUND: Natural killer (NK) cells are innate lymphoid cells that mediate antitumour and antiviral responses. However, very little is known about how ageing influences human NK cells, especially at the single-cell level. METHODS: We applied single-cell sequencing (scRNA-seq) to human lymphocytes and NK cells from 4 young and 4 elderly individuals and then analysed the transcriptome data using Seurat. We detected the proportion and phenotype of NK cell subsets in peripheral blood samples from a total of 62 young and 52 elderly healthy donors by flow cytometry. We also used flow cytometry to examine the effector functions of NK cell subsets upon IFN-α/IL-12+IL-15/K562/IL-2 stimulation in vitro in peripheral blood samples from a total of 64 young and 63 elderly healthy donors. We finally studied and integrated single-cell transcriptomes of NK cells from 15 young and 41 elderly COVID-19 patients with those from 12 young and 6 elderly healthy control individuals to investigate the impacts of ageing on NK cell subsets in COVID-19 disease. RESULTS: We discovered a memory-like NK subpopulation (NK2) exhibiting the largest distribution change between elderly and young individuals among lymphocytes. Notably, we discovered a unique NK subset that was predominantly CD52+ NK2 cells (NK2.1). These memory-like NK2.1 cells accumulated with age, exhibited proinflammatory characteristics, and displayed a type I interferon response state. Integrative analyses of a large-cohort COVID-19 dataset and our datasets revealed that NK2.1 cells from elderly COVID-19 patients are enriched for type I interferon signalling, which is positively correlated with disease severity in COVID-19. CONCLUSIONS: We identified a unique memory-like NK cell subset that accumulates with ageing and correlates with disease severity in COVID-19. Our results identify memory-like NK2.1 cells as a potential target for developing immunotherapies for infectious diseases and for addressing age-related dysfunctions of the immune system.

Transcriptomic characteristics and impaired immune function of patients who retest positive for SARS-CoV-2 RNA.

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, has become a global public health crisis. Some patients who have recovered from COVID-19 subsequently test positive again for SARS-CoV-2 RNA after discharge from hospital. How such retest-positive (RTP) patients become infected again is not known. In this study, 30 RTP patients, 20 convalescent patients, and 20 healthy controls were enrolled for the analysis of immunological characteristics of their peripheral blood mononuclear cells. We found that absolute numbers of CD4+ T cells, CD8+ T cells, and natural killer cells were not substantially decreased in RTP patients, but the expression of activation markers on these cells was significantly reduced. The percentage of granzyme B-producing T cells was also lower in RTP patients than in convalescent patients. Through transcriptome sequencing, we demonstrated that high expression of inhibitor of differentiation 1 (ID1) and low expression of interferon-induced transmembrane protein 10 (IFITM10) were associated with insufficient activation of immune cells and the occurrence of RTP. These findings provide insight into the impaired immune function associated with COVID-19 and the pathogenesis of RTP, which may contribute to a better understanding of the mechanisms underlying RTP.

Profiling of the immune repertoire in COVID-19 patients with mild, severe, convalescent, or retesting-positive status.

Forty-seven samples of peripheral blood mononuclear cells from four groups of coronavirus disease (COVID)-19 patients (mild, severe, convalescent, retesting-positive) and healthy controls were applied to profile the immune repertoire of COVID-19 patients in acute infection or convalescence by transcriptome sequencing and immune-receptor repertoire (IRR) sequencing. Transcriptome analyses showed that genes within principal component group 1 (PC1) were associated with infection and disease severity whereas genes within PC2 were associated with recovery from COVID-19. A "dual-injury mechanism" of COVID-19 severity was related to an increased number of proinflammatory pathways and activated hypercoagulable pathways. A machine-learning model based on the genes associated with inflammatory and hypercoagulable pathways had the potential to be employed to monitor COVID-19 severity. Signature analyses of B-cell receptors (BCRs) and T-cell receptors (TCRs) revealed the dominant selection of longer V-J pairs (e.g., IGHV3-9-IGHJ6 and IGHV3-23-IGHJ6) and continuous tyrosine motifs in BCRs and lower diversity of TCRs. These findings provide potential predictors for COVID-19 outcomes, and new potential targets for COVID-19 treatment.