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.