2. Use of SCS in airway viral infectious disease
In the challenging environment of coronavirus disease 2019 (COVID-19), SCS was positioned to help researchers understand immune cell subsets and molecular factors associated with protective or pathological immunity against the severe acute novel coronavirus infection respiratory syndrome, and then develop vaccines and targeted therapies. Xu et al [41] used early scRNA-seq methods to characterize peripheral blood mononuclear cells (PBMCS) and paired bronchoalveolar lavage fluid (BALF) cells from non-infected control subjects and COVID-19 patients, and subsequently reveal the different immune responses to COVID-19. Valuable findings were as follows: (1) decreased numbers of dendritic cells (DCs) were associated with increased numbers of mononuclear cells such as myeloid suppressor cells (MDSCs). (2) When compared with the healthy control subjects, the numbers of peripheral T cells and NK cells were significantly decreased in severe COVID-19 patients, and especially the innate T cells and various CD8+ T cell subsets (3). In severe patients, the proportions of various activated CD4+ T cell subsets (including Th1, Th2, and Th17-like cells) in T cell compartments were increased with increased clonal amplification [41, 42]. To elucidate peripheral immune cellular pathways that may lead to immunopathology or protective immunity in patients with severe COVID-19, PBMCS were collected from seven hospitalized patients with severe COVID-19 and analyzed using scRNA-seq and peripheral immune cell phenotype information, Class II HLA downregulation. The developing neutrophils characterized by heterogeneous interferon-stimulating genes in COVID-19 patients were identified [43].
To further explore the pathogenesis of COVID-19 and identify precise therapeutic targets, the COVID-19 Single Cell Consortium of China (SC4) generated a scRNA-seq dataset consisting of 171 COVID-19 patients, and integrated the basic characteristics of the dataset and cell subsets in different major cell lineages. As determined by SCS, the severity of COVID-19 was associated with airway epithelial-immune cell interactions. Huang et al. [44] revealed the dynamic changes in blood immune response in COVID-19 patients at different stages by use of gene expression detection, as well as T cell receptor (TCR) and B cell receptor (BCR) transcriptome analyses. In the peripheral blood of patients with severe COVID-19, the levels of MKI67 in plasma cells were increased, and the levels of plasmacytoid dendritic cell cluster DC-C4-LILRA4 were decreased during both the progression and recovery stage. After adjusting for technical covariates, the Neu-c3-CST7 neutrophil cluster was found to be associated with patient age, COVID-19 severity, and disease stage, while for T cells, a subgroup with high MKI67 expression was closely related to COVID-19 severity. The scRNA seq data for 341420 PBMCS, 185430 cloned T cells, and 28802 cloned B cells were obtained from 25 samples from 16 patients with COVID-19. It was found that the numbers of DCs, CD14+Monocyte and megakaryocyte progenitor (MP) cells, and CD8+T lymphocytes in severe patients were significantly reduced, and the type I interferon (IFN-I), mitogen activated protein kinase (MAPK) and ferroptosis pathways were activated during disease activity, but then gradually recovered after the patient’s condition improved [45]. The scientific community has made a bold attempt to use new algorithms in scRNA-seq to discover and summarize how innate and adaptive immune cell subsets and immune factors are related to the development of COVID-19 vaccines and other forms of treatment [46]. For example, 21 published single-cell sequencing datasets (totaling > 3.2 million cells) now provide a comprehensive study and meta-analysis of the immunology of severe acute respiratory syndrome coronavirus type 2 infection. Researchers have identified putative targets of the severe acute respiratory syndrome coronavirus in tissue-resident cell populations. Type II lung cells, ileal absorptive intestinal cells, and nasal cup secretory cells were found to co-express ACE2 and TMPRSS2, while the host protease (TMPRSS2) cell coronavirus binds to the stinger protein of the type 2 virus to facilitate its entry into the cell [47]. Overall, in terms of cellular variants, the proportions of circulating plasma cells and classical monocytes are dramatically increased in COVID-19 patients, while the proportions of DCs, non-classical monocytes, NK cells. and some lung progenitor cells are decreased significantly, decreased. With regards to genetic variants, patients showed a significant increase inAREG , EREG , and HLA class II genes, as well as in genes related to the ”IL-17 signaling pathway,” ”response to toxic substances,””lymphocyte/T cell activation,” and ”positive regulation of immune effector processes” [48]
In short, various single-cell transcriptome sequencing studies on COVID-19 have achieved precise results. Although the epidemic has been under relatively stable control after a three-year run, further tracking and intervention in the sequelae of COVID-19 by use of single-cell techniques will bring new opportunities and challenges.
3. Use of SCS in airway tumors
In 2011, SCS was first applied to human cancer cells to detect cellular and microenvironmental heterogeneity at high resolution [49]. It was also widely used to detect key signature genes during tumor progression [50]. The development of SCS has led to breakthroughs in our understanding of tumor heterogeneity, the tumor microenvironment, immune checkpoints, intercellular communication lattices, and targets for relapse therapy in airway tumors [51-53]. It is an important tool for exploring interactions between tumor cells and neighboring stromal cells and immune cells. Currently, single cell sequencing is used in nasopharyngeal, laryngeal, and lung cancers.