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Abstract 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.

Abstract Background Ischemic stroke (IS) is a principal contributor to long-term disability in adults. A new cell death mediated by iron is ferroptosis, characterized by lethal aggregation of lipid peroxidation. However, a paucity of ferroptosis-related biomarkers early identify IS until now. This study investigated potential ferroptosis-related gene pair biomarkers in IS and explored their roles in immune infiltration. Results In total, we identified 6 differentially expressed ferroptosis-related genes (DEFRGs) in the metadata cohort. Of these genes, 4 DEFRGs were incorporated into the competitive endogenous RNA (ceRNA) network, including 78 lncRNA-miRNA and 16 miRNA-mRNA interactions. Based on relative expression values of DEFRGs, we constructed gene pairs. An integrated scheme consisting of machine learning algorithms, ceRNA network, and gene pair was proposed to screen the key DEFRG biomarkers. The receiver operating characteristic (ROC) curve witnessed that the diagnostic performance of DEFRG pair CDKN1A/JUN was superior to that of single gene. Moreover, the CIBERSORT algorithm exhibited immune infiltration landscapes: plasma cells, resting NK cells, and resting mast cells infiltrated less in IS samples than controls. Spearman correlation analysis confirmed a significant correlation between plasma cells and CDKN1A/JUN (CDKN1A: r = − 0.503, P

Background: The COVID-19 pandemic has currently developed into a worldwide threat to humankind. Importantly, patients with severe COVID-19 are believed to have a higher mortality risk than those with mild conditions. However, despite the urgent need to develop novel therapeutic strategies, the biological features and pathogenic mechanisms of severe COVID-19 are poorly understood.Methods: Here, peripheral blood mononuclear cells (PBMCs) from four patients with severe COVID-19, four patients with mild COVID-19, and four healthy controls were examined by RNA sequencing (RNA-Seq). We conducted gene expression analysis and Venn diagrams to detect specific differentially expressed genes (DEGs) in patients with severe disease compared with those with mild conditions. Gene Ontology (GO) enrichment analysis was performed to identify the significant biological processes, and protein–protein interaction networks were constructed to extract hub genes. These hub genes were then subjected to regulatory signatures and protein–chemical interaction analysis for certain regulatory checkpoints and identification of potent chemical agents. Finally, to demonstrate the cell type-specific expression of these genes, we performed single-cell RNA-Seq analyses using an online platform.Results: A total of 144 DEGs were specifically expressed in severe COVID-19, and GO enrichment analysis revealed a significant association of these specific DEGs with autophagy. Hub genes such as MVB12A, CHMP6, STAM, and VPS37B were then found to be most significantly involved in the biological processes of autophagy at the transcriptome level. In addition, six transcription factors, including SRF, YY1, CREB1, PPARG, NFIC, and GATA2, as well as miRNAs, namely, hsa-mir-1-3p, and potent chemical agents such as copper sulfate and cobalt chloride, may cooperate in regulating the autophagy hub genes. Furthermore, classical monocytes may play a central role in severe COVID-19.Conclusion: We suggest that autophagy plays a crucial role in severe COVID-19. This study might facilitate a more profound knowledge of the biological characteristics and progression of COVID-19 and the development of novel therapeutic approaches to achieve a breakthrough in the current COVID-19 pandemic.

Burkholderia pseudomallei is a zoonotic pathogen that usually affects patients' lungs and causes serious melioidosis. The interaction of B. pseudomallei with its hosts is complex, and cellular response to B. pseudomallei infection in humans still remains to be elucidated. In this study, transcriptomic profiling of B. pseudomallei-infected human lung epithelial A549 cells was performed to characterize the cellular response dynamics during the early infection (EI) stage. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed by using the online databases DAVID 6.8 and KOBAS 3.0. Real-time quantitative PCR and western blot were used for validation experiments. Compared with the negative control group (NC), a set of 36 common genes varied over time with a cut-off level of 1.5-fold change, and a P-value < 0.05 was identified. Bioinformatics analysis indicated that the PERK-mediated unfolded protein response (UPR) was enriched as the most noteworthy biological process category, which was enriched as a branch of UPR in the signaling pathway of protein processing in the endoplasmic reticulum. Other categories, such as inflammatory responses, cell migration, and apoptosis, were also focused. The molecular chaperone Bip (GRP78), PERK, and PERK sensor-dependent phosphorylation of eIF2α (p-eIF2α) and ATF4 were verified to be increasing over time during the EI stage, suggesting that B. pseudomallei infection activated the PERK-mediated UPR in A549 cells. Collectively, these results provide important initial insights into the intimate interaction between B. pseudomallei and lung epithelial cells, which can be further explored toward the elucidation of the cellular mechanisms of B. pseudomallei infections in humans.

Diphthamide is a unique post-translationally modified histidine residue (His715 in all mammals) found only in eukaryotic elongation factor-2 (eEF-2). The biosynthesis of diphthamide represents one of the most complex modifications, executed by protein factors conserved from yeast to humans. Diphthamide is not only essential for normal physiology (such as ensuring fidelity of mRNA translation), but is also exploited by bacterial ADP-ribosylating toxins (e.g., diphtheria toxin) as their molecular target in pathogenesis. Taking advantage of the observation that cells defective in diphthamide biosynthesis are resistant to ADP-ribosylating toxins, in the past four decades, seven essential genes (Dph1 to Dph7) have been identified for diphthamide biosynthesis. These technically unsaturated screens raise the question as to whether additional genes are required for diphthamide biosynthesis. In this study, we performed two independent, saturating, genome-wide CRISPR knockout screens in human cells. These screens identified all previously known Dph genes, as well as further identifying the BTB/POZ domain-containing transcription factor Miz1. We found that Miz1 is absolutely required for diphthamide biosynthesis via its role in the transcriptional regulation of Dph1 expression. Mechanistically, Miz1 binds to the Dph1 proximal promoter via an evolutionarily conserved consensus binding site to activate Dph1 transcription. Therefore, this work demonstrates that Dph1-7, along with the newly identified Miz1 transcription factor, are likely to represent the essential protein factors required for diphthamide modification on eEF2.

Abstract Background Among the different types of cancer, pancreatic cancer, particularly pancreatic ductal adenocarcinoma (PDAC), is the most lethal malignancy, with poor early detection rates and prognosis. The aim of the present study was to investigate the potential genetic effects of the single‐nucleotide polymorphisms (SNPs) in ABCB1 (rs1045642, rs3789243, rs4148737), APOB (rs693, rs1042031), CAV1 (rs12672038, rs1997623, rs3807987, rs7804372), and NAMPT (rs9034, rs2505568, rs61330082) on PDAC. Methods A total of 273 patients with PDAC and 263 healthy controls were genotyped using PCR and direct Sanger sequencing. Unconditional logistic regression models were used to evaluate the potential effects of the genotypes, alleles, and haplotypes on the risk of developing PDAC. Results Patients with PDAC possessed a considerably lower frequency of genotypes AG, GG, and allele G at ABCB1 rs4148737 compared with controls. Based on age, sex, smoking status, drinking status, diabetes, and family history of cancer, stratified analyses showed a significant correlation between SNPs at rs4148737 and PDAC. According to specific SNPs, eight haplotypes were constructed along with ABCB1 rs4148737, rs1045642, and rs3789243. Carriers with haplotypes ACC and ATC were more susceptible to developing PDAC, whereas haplotypes GCC and GTC were associated with a reduced likelihood of developing PDAC. The distributions of the other SNPs in each group were not significantly associated with PDAC risk. Conclusions These results suggested that genetic polymorphisms of ABCB1 rs4148737 may influence an individual's risk of developing PDAC.