Cell Differentiation Trajectories Research Articles

ScGRN-Entropy: Inferring cell differentiation trajectories using single-cell data and gene regulation network-based transfer entropy.

Research on cell differentiation facilitates a deeper understanding of the fundamental processes of life, elucidates the intrinsic mechanisms underlying diseases such as cancer, and advances the development of therapeutics and precision medicine. Existing methods for inferring cell differentiation trajectories from single-cell RNA sequencing (scRNA-seq) data primarily rely on static gene expression data to measure distances between cells and subsequently infer pseudotime trajectories. In this work, we introduce a novel method, scGRN-Entropy, for inferring cell differentiation trajectories and pseudotime from scRNA-seq data. Unlike existing approaches, scGRN-Entropy improves inference accuracy by incorporating dynamic changes in gene regulatory networks (GRN). In scGRN-Entropy, an undirected graph representing state transitions between cells is constructed by integrating both static relationships in gene expression space and dynamic relationships in the GRN space. The edges of the undirected graph are then refined using pseudotime inferred based on cell entropy in the GRN space. Finally, the Minimum Spanning Tree (MST) algorithm is applied to derive the cell differentiation trajectory. We validate the accuracy of scGRN-Entropy on eight different real scRNA-seq datasets, demonstrating its superior performance in inferring cell differentiation trajectories through comparative analysis with existing state-of-the-art methods.

Augmenting antitumor efficacy of Th17-derived Th1 cells through IFN-γ-induced type I interferon response network via IRF7

The importance of CD4+ T cells in cancer immunotherapy has gained increasing recognition. Particularly, a specific subset of CD4+ T cells coexpressing the T helper type 1 (Th1) and Th17 markers has demonstrated remarkable antitumor potential. However, the underlying mechanisms governing the differentiation of these cells and their subsequent antitumor responses remain incompletely understood. Single-cell RNA sequencing (scRNA-seq) data reanalysis demonstrated the presence of Th171 cells within tumors. Subsequent trajectory analysis found that these Th171 cells are initially primed under Th17 conditions and then converted into IFN-γ-producing cells. Following the in vivo differentiation trajectory of Th171 cells, we successfully established in vitro Th171 cell culture. Transcriptomic profiling has unveiled a substantial resemblance between in vitro-generated Th171 cells and their tumor-infiltrating counterparts. Th171 cells exhibit more potent antitumor responses than Th1 or Th17 cells. Additionally, Th171chimeric antigen receptor T (CAR-T) cells eradicate solid tumors more efficiently. Importantly, Th171 cells display an early exhaustion phenotype while retaining stemness. Mechanistically, Th171 cells migrate faster and accumulate more in tumors in an extracellular matrix protein 1 (ECM1)-dependent manner. Furthermore, we show that IFN-γ up-regulated IRF7 to promote the type I interferon response network and ECM1 expression but decreased the exhaustion status in Th171 cells. Taken together, our findings position Th171 cells as a great candidate for improving targeted immunotherapies in solid malignancies.

Single-cell transcriptome and chromatin accessibility mapping of upper lip and primary palate fusion.

Cleft lip and/or primary palate (CL/P) represent a prevalent congenital malformation, the aetiology of which is highly intricate. Although it is generally accepted that the condition arises from failed fusion between the upper lip and primary palate, the precise mechanism underlying this fusion process remains enigmatic. In this study, we utilized transposase-accessible chromatin sequencing (scATAC-seq) and single-cell RNA sequencing (scRNA-seq) to interrogate lambdoidal junction tissue derived from C57BL/6J mouse embryos at critical stages of embryogenesis (10.5, 11.5 and 12.5 embryonic days). We successfully identified distinct subgroups of mesenchymal and ectodermal cells involved in the fusion process and characterized their unique transcriptional profiles. Furthermore, we conducted cell differentiation trajectory analysis, revealing a dynamic repertoire of genes that are sequentially activated or repressed during pseudotime, facilitating the transition of relevant cell types. Additionally, we employed scATAC data to identify key genes associated with the fusion process and demonstrated differential chromatin accessibility across major cell types. Finally, we constructed a dynamic intercellular communication network and predicted upstream transcriptional regulators of critical genes involved in important signalling pathways. Our findings provide a valuable resource for future studies on upper lip and primary palate development, as well as congenital defects.

Landscape of epithelial cell subpopulations in the human esophageal squamous cell carcinoma microenvironment

AimsWe sought to reveal the landscape of epithelial cell subpopulations in the human esophageal squamous cell carcinoma microenvironment and investigate their parts on esophageal squamous carcinoma (ESCC) development. BackgroundEpithelial cells play an important role in the occurrence and development of ESCC through multiple mechanisms. While the landscape of epithelial cell subpopulations in ESCC, remains unclear. ObjectiveExploring the role of epithelial cell subpopulations in ESCC progression. MethodsSeurat R package was used for single-cell RNA sequencing (scRNA-seq) data filtering, dimensionality reduction, clustering and differentially expressed genes analysis. Cellmarker database was adopted for cell cluster annotation. Functional enrichment analysis was carried out by Gene Ontology (GO) analysis. InferCNV package was conducted for copy number variation (CNV) of epithelial cell subpopulations in all chromosomal regions. Pseudotime trajectory analysis was implemented for exploring differentiation trajectory of epithelial cells subgroups during the cancer progression. CellChat analysis was used for probing the interactions between epithelial cells and NK/T cells. cellular experiments were performed using Quantitative Real-Time Polymerase Chain Reaction (RT-qPCR), Wound-Healing Assay and transwell. Results11 major cell subpopulations were identified in ESCC and adjunct tissues. Further reclassification of epithelial cells uncovered 4 subpopulations. Enrichment analysis revealed that highly expressed genes in 4 epithelial cell subpopulations were related to cell proliferation, immune response and angiogenesis. CNV analysis found that UBD + epithelial cells and GAS2L3+ epithelial cells had a higher proportion of CNV. Cell differentiation trajectories disclosed that KRT6C+ and GSTA1+ epithelial cells were in an intermediate state of differentiation, while UBD+ and GAS2L3+ epithelial cells are in an end state of differentiation during ESCC progression. Finally, we found that four epithelial cell subpopulations all inhibited NK/T cells through NECTIN2-TIGIT and CLEC2B-KLRB1. Low ATF3 and DDIT3 mRNA expression inhibited ESCC cell migration and invasion. ConclusionHere, we obtained a through epithelial cell atlas of ESCC at single-cell resolution, explored the role of epithelial cell in ESCC progression, and unveiled immunosuppressive signals to NK/T cells in promoting ESCC. Our findings expand the comprehension of epithelial cells and offer a theoretical guidance for future anti-epithelial cell treatment of ESCC.

A new exploration: characterization of the differentiation trajectory of prostate cancer cells

Prostate cancer is one of the most common malignant tumors in men, and in-depth study of its gene expression patterns is crucial for understanding the formation and development of prostate cancer. Although single-cell transcriptomics has deeply explored the heterogeneous expression characteristics of prostate cancer, given that normal epithelial cells themselves have different states of differentiation, these normal differentiation characteristics may lead to confusion with heterogeneous tumor characteristics. In this study, we used single-cell data from the GEO database to analyze in detail the heterogeneity of prostate cancer tumor cells/tumor-associated epithelium cells (TAECs), with a particular focus on the differentiation state of epithelial cells in matching normal tissue. We found that after subtype pairing analysis of normal tissue and tumor tissue epithelium based on differentiation status, the characteristics identified later were not consistent with the general characteristics originally exhibited by different TAECs subpopulations. Among them, all TAECs subpopulations showed P53 enrichment and downregulation of the apoptotic pathway, and expressed higher levels of EGFR, ERBB2, interferon receptors, MIF, and cell adhesion-related signals; through transcription factor regulatory network analysis, we observed that YY1, NKX3-1, and EHF had higher transcriptional activity in TAECs subpopulations than normal epithelial cells at the same differentiation stage, while ATF3 was the opposite. Among them, YY1 may act as an upstream regulator of the MIF signaling pathway, and ATF3 is a key upstream transcriptional regulator of differentially expressed genes in the P53 and apoptotic pathways. Immune infiltration analysis showed that the above four transcription factors were significantly correlated with the infiltration of immune cells in prostate cancer, and pan-cancer analysis showed that their expression-related survival risks were widely present in different cancers. It is worth noting that this is merely a preliminary, exploratory study, which inevitably has some deficiencies and limitations. Despite this, this study is committed to bringing a novel and unique perspective to the field through this work, with the hope of opening up new levels of understanding and stimulating more in-depth research and discussion.

Re-analysis of single cell and spatial transcriptomics data reveals B cell landscape in gastric cancer microenvironment and its potential crosstalk with tumor cells for clinical prognosis

BackgroundAt present, immunotherapy has become a powerful treatment for advanced gastric cancer (AGC), but not all patients can benefit from it. According to the latest research, the impact of B cell subpopulations on the immune microenvironment of gastric cancer (GC) is unknown. Exploring whether the interaction between B cells and tumor cells in GC affects the effectiveness of immunotherapy has attracted our interest.MethodsThis study involved the re-analysis of single-cell RNA (scRNA) and spatial transcriptomics (ST) data from publicly available datasets. The focus was on investigating the subpopulations and differentiation trajectories of B cells in the gastric cancer (GC) tumor immune microenvironment (TIME). Spatial transcriptomics (ST) and multiple immunofluorescence (mIF) revealed a clear co-localization pattern between B cells and tumor cells. Multiple immunotherapy datasets were collected to identify unique immunotherapy biomarkers. The unique immunotherapeutic potential of targeting CCL28 was validated through a mouse gastric cancer model. In addition, flow cytometry revealed changes in the tumor immune microenvironment targeting CCL28.ResultsThe re-analysis of ST data from multiple cancer types revealed a co-localization pattern between B cells and tumor cells. A significant number of IgA plasma cells were identified in the GC TIME. Five different tumor-infiltrating B cell subpopulations and two unique B cell differentiation trajectories were characterized, along with seven GC-related states. By analyzing the communication between GC cells and B cells, it was further discovered that tumor cells can influence and recruit plasma cells through CCL28-CCR10 signaling. Additionally, there was a crosstalk between GC cells and B cells. Finally, we identified the LAMA/CD44 signaling axis as a potential prognostic marker for immunotherapy through a large amount of immunotherapy data. We also validated through various animal tumor models that targeting CCL28 can significantly promote CD8+T cell infiltration and function in the TME by regulating B cell and plasma cell functions, and has the ability to synergize immunotherapy.ConclusionThe co-localization and crosstalk between GC cells and B cells significantly affect the efficacy of immunotherapy, and inhibiting the CCL28-CCR10 signal axis is a potential immunotherapy target for GC. Meanwhile, LAMA/CD44 pair may be a potential adverse indicator for immunotherapy and tumor prognosis.

Single-cell landscape of intratumoral heterogeneity and tumor microenvironment remolding in pre-nodal metastases of breast cancer

BackgroundThe metastasis of cancer cells is influenced by both their intrinsic characteristics and the tumor microenvironment (TME). However, the molecular mechanisms underlying pre-nodal metastases of breast cancer remain unclear.MethodsWe integrated a total of 216,963 cells from 54 samples across 6 single-cell datasets to profile the cellular landscape differences between primary tumors and pre-nodal metastases.ResultsWe revealed three distinct metastatic epithelial cell subtypes (Epi1, Epi2 and Epi3), which exhibited different metastatic mechanisms. Specifically, the marker gene KCNK15 of the Epi1 subtype exhibited increased gene expression along the cell differentiation trajectory and was specifically regulated by the transcription factor ASCL1. In the Epi3 subtype, we highlighted NR2F1 as a regulator targeting the marker gene MUCL1. Additionally, we found that the Epi2 and Epi3 subtypes shared some regulons, such as ZEB1 and NR2C1. Similarly, we identified specific subtypes of stromal and immune cells in the TME, and discovered that vascular cancer-associated fibroblasts might promote capillary formation through CXCL9+ macrophages in pre-nodal metastases. All three subtypes of metastatic epithelial cells were associated with poor prognosis.ConclusionsIn summary, this study dissects the intratumoral heterogeneity and remodeling of the TME in pre-nodal metastases of breast cancer, providing novel insights into the mechanisms underlying breast cancer metastasis.

Characteristics of the Dynamic Evolutionary Pathway of ADSCs Induced Differentiation into Astrocytes Based on scRNA-Seq Analysis.

We employed single-cell transcriptome sequencing to reveal the dynamic gene expression changes during the differentiation of adipose-derived stromal cells (ADSCs) into astrocytes. Single-cell RNA sequencing was conducted on cells from the ADSCs group and the induced groups at 2, 7, 14, and 21days using the 10 × Chromium platform. Data underwent quality control and dimensionality reduction. Cell differentiation trajectories were constructed using Monocle2, and differentially expressed genes (DEGs) in each cell cluster were identified using differential selection algorithms. DEGs at each time point were annotated using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG), and regulatory intensities of transcription factors were analyzed using SCENIC. Integrating all groups, a total of five samples were divided into 13 cell clusters (0-12 clusters). DEGs between clusters and those compared with ADSCs at various induced time points showed distinct specificities. Monocle2 constructed cell differentiation trajectories; ADSCs can differentiate into mature astrocytes not only through the direct pathway from the 1 branch to the 3 branch but also through an indirect pathway, involving the 1 branch to the 2 branch before progressing to the 3 branch. SCENIC analysis highlighted the critical regulatory roles of STAT1, MYEF2, and SOX6 transcription factors during the differentiation of ADSCs into astrocytes. ADSCs can differentiate into mature astrocytes through two distinct pathways: direct and indirect. By the 14th day of induction, mature astrocytes have formed, characterized by a cell cycle arrest in mitosis. Further induction leads to degenerative senescence changes in differentiated cells.

Developing an advanced diagnostic model for hepatocellular carcinoma through multi-omics integration leveraging diverse cell-death patterns.

Hepatocellular carcinoma (HCC), representing more than 80% of primary liver cancer cases, lacks satisfactory etiology and diagnostic methods. This study aimed to elucidate the role of programmed cell death-associated genes (CDRGs) in HCC by constructing a diagnostic model using single-cell RNA sequencing (scRNA-seq) and RNA sequencing (RNA-seq) data. Six categories of CDRGs, including apoptosis, necroptosis, autophagy, pyroptosis, ferroptosis, and cuproptosis, were collected. RNA-seq data from blood-derived exosomes were sourced from the exoRBase database, RNA-seq data from cancer tissues from the TCGA database, and scRNA-seq data from the GEO database. Subsequently, we intersected the differentially expressed genes (DEGs) of the HCC cohort from exoRBase and TCGA databases with CDRGs, as well as DEGs obtained from single-cell datasets. Candidate biomarker genes were then screened using clinical indicators and a machine learning approach, resulting in the construction of a seven-gene diagnostic model for HCC. Additionally, scRNA-seq and spatial transcriptome sequencing (stRNA-seq) data of HCC from the Mendeley data portal were used to investigate the underlying mechanisms of these seven key genes and their association with immune checkpoint blockade (ICB) therapy. Finally, we validated the expression of key molecules in tissues and blood-derived exosomes through quantitative Polymerase Chain Reaction (qPCR) and immunohistochemistry experiments. Collectively, we obtained a total of 50 samples and 104,288 single cells. Following the meticulous screening, we established a seven-gene diagnostic model for HCC, demonstrating high diagnostic efficacy in both the exoRBase HCC cohort (training set: AUC = 1; testing set: AUC = 0.847) and TCGA HCC cohort (training set: AUC = 1; testing set: AUC = 0.976). Subsequent analysis revealed that HCC cluster 3 exhibited a higher stemness index and could serve as the starting point for the differentiation trajectory of HCC cells, also displaying more abundant interactions with other cell types in the microenvironment. Notably, key genes TRIB3 and NQO1 displayed elevated expression levels in HCC cells. Experimental validation further confirmed their elevated expression in both tumor tissues and blood-derived exosomes of cancer patients. Additionally, stRNA analysis not only substantiated these findings but also suggested that patients with high TRIB3 and NQO1 expression might respond more favorably to ICB therapy. The seven-gene diagnostic model demonstrated remarkable accuracy in HCC screening, with TRIB3 emerging as a promising diagnostic tool and therapeutic target for HCC.

Ash1l loss-of-function results in structural birth defects and altered cortical development

Abstract The histone methyltransferase ASH1L plays a crucial role in regulating gene expression across various organ systems during development, yet its role in brain development remains largely unexplored. Over 130 individuals with autism harbour heterozygous loss-of-function ASH1L variants, and population studies confirm it as a high-risk autism gene. Previous studies on Ash1l deficient mice have reported autistic-like behaviours and provided insights into the underlying neuropathophysiology. In this study, we used mice with a cre-inducible deletion of Ash1l exon 4, which results in a frame shift and premature stop codon (p.V1693Afs*2). Our investigation evaluated the impact of Ash1l loss-of-function on survival and craniofacial skeletal development. Using a tamoxifen-inducible cre strain, we targeted Ash1l knockout early in cortical development [Emx1-Cre-ERT2; embryonic Day (e) 10.5]. Immunohistochemistry was utilized to assess cortical lamination, while EdU incorporation aided in birthdating cortical neurons. Additionally, single-cell RNA sequencing was employed to compare cortical cell populations and identify genes with differential expression. At e18.5, the proportion of homozygous Ash1l germline knockout embryos appeared normal; however, no live Ash1l null pups were present at birth (e18.5: n = 77, P = 0.90; p0: n = 41, P = 0.00095). Notably, Ash1l−/– exhibited shortened nasal bones (n = 31, P = 0.017). In the cortical-specific knockout model, SATB2 neurons showed increased numbers (n = 6/genotype, P = 0.0001) and were distributed through the cortical plate. Birthdating revealed generation of ectopically placed deep layer neurons that express SATB2 (e13.5 injection: n = 4/genotype, P = 0.0126). Single cell RNA sequencing revealed significant differences in gene expression between control and mutant upper layer neurons, leading to distinct clustering. Pseudotime analysis indicated that the mutant cluster followed an altered cell differentiation trajectory. This study underscores the essential role of Ash1l in postnatal survival and normal craniofacial development. In the cortex, ASH1L exerts broad effects on gene expression and is indispensable for determining the fate of upper layer cortical neurons. These findings provide valuable insights into the potential mechanisms of ASH1L neuropathology, shedding light on its significance in neurodevelopmental disorders like autism.

Unveiling novel cell clusters and biomarkers in glioblastoma and its peritumoral microenvironment at the single-cell perspective

BackgroundGlioblastoma (GBM) is a highly heterogeneous, recurrent and aggressively invasive primary malignant brain tumor. The heterogeneity of GBM results in poor targeted therapy. Therefore, the aim of this study is to depict the cellular landscape of GBM and its peritumor from a single-cell perspective. Discovering new cell subtypes and biomarkers, and providing a theoretical basis for precision therapy.MethodsWe collected 8 tissue samples from 4 GBM patients to perform 10 × single-cell transcriptome sequencing. Quality control and filtering of data by Seurat package for clustering. Inferring copy number variations to identify malignant cells via the infercnv package. Functional enrichment analysis was performed by GSVA and clusterProfiler packages. STRING database and Cytoscape software were used to construct protein interaction networks. Inferring transcription factors by pySCENIC. Building cell differentiation trajectories via the monocle package. To infer intercellular communication networks by CellPhoneDB software.ResultsWe observed that the tumor microenvironment (TME) varies among different locations and different GBM patients. We identified a proliferative cluster of oligodendrocytes with high expression of mitochondrial genes. We also identified two clusters of myeloid cells, one primarily located in the peritumor exhibiting an M1 phenotype with elevated TNFAIP8L3 expression, and another in the tumor and peritumor showing a proliferative tendency towards an M2 phenotype with increased DTL expression. We identified XIST, KCNH7, SYT1 and DIAPH3 as potential factors associated with the proliferation of malignant cells in GBM.ConclusionsThese biomarkers and cell clusters we discovered may serve as targets for treatment. Targeted drugs developed against these biomarkers and cell clusters may enhance treatment efficacy, optimize immune therapy strategies, and improve the response rates of GBM patients to immunotherapy. Our findings provide a theoretical basis for the development of individualized treatment and precision medicine for GBM, which may be used to improve the survival of GBM patients.

KLF4 in smooth muscle cell-derived progenitor cells is essential for angiotensin II-induced cardiac inflammation and fibrosis.

Cardiac fibrosis is defined by the excessive accumulation of extracellular matrix (ECM) material resulting in cardiac tissue scarring and dysfunction. While it is commonly accepted that myofibroblasts are the major contributors to ECM deposition in cardiac fibrosis, their origin remains debated. By combining lineage tracing and RNA sequencing, our group made the paradigm-shifting discovery that a subpopulation of resident vascular stem cells residing within the aortic, carotid artery, and femoral aartery adventitia (termed AdvSca1-SM cells) originate from mature vascular smooth muscle cells (SMCs) through an in situ reprogramming process. SMC-to-AdvSca1-SM reprogramming and AdvSca1-SM cell maintenance is dependent on induction and activity of the transcription factor, KLF4. However, the molecular mechanism whereby KLF4 regulates AdvSca1-SM phenotype remains unclear. In the current study, leveraging a highly specific AdvSca1-SM cell reporter system, single-cell RNA-sequencing (scRNA-seq), and spatial transcriptomic approaches, we demonstrate the profibrotic differentiation trajectory of coronary artery-associated AdvSca1-SM cells in the setting of Angiotensin II (AngII)-induced cardiac fibrosis. Differentiation was characterized by loss of stemness-related genes, including Klf4 , but gain of expression of a profibrotic phenotype. Importantly, these changes were recapitulated in human cardiac hypertrophic tissue, supporting the translational significance of profibrotic transition of AdvSca1-SM-like cells in human cardiomyopathy. Surprisingly and paradoxically, AdvSca1-SM-specific genetic knockout of Klf4 prior to AngII treatment protected against cardiac inflammation and fibrosis, indicating that Klf4 is essential for the profibrotic response of AdvSca1-SM cells. Overall, our data reveal the contribution of AdvSca1-SM cells to myofibroblasts in the setting of AngII-induced cardiac fibrosis. KLF4 not only maintains the stemness of AdvSca1-SM cells, but also orchestrates their response to profibrotic stimuli, and may serve as a therapeutic target in cardiac fibrosis.

CRISPR/Cas9-mediated gene disruption determines the roles of MITF and CITED2 in human mast cell differentiation

The differentiation of hematopoietic stem and progenitor cells into the various cell lineages is regulated by cell-intrinsic factors and the progenitors' microenvironment. Experiments in mice have allowed the identification of transcriptional modulators that control mast cell differentiation. However, a comprehensive approach that allows efficient disruption of individual transcriptional modulators in primary human hematopoietic progenitors coupled with a mast cell formation readout has not been described. Here, we report a simple electroporation- and ribonucleoprotein-based knockout system that allows the identification of genes that are required and dispensable for human mast cell differentiation. We show that the transcription factor MITF is upregulated in human mast cell progenitors and reveal that the loss of MITF results in the suppressed formation of mast cells. By contrast, CITED2, another transcriptional modulator that is upregulated along the mast cell differentiation trajectory, was dispensable for human mast cell differentiation. Taken together, we report a CRISPR/Cas9-based framework that serves to identify genes involved in regulating the formation of human mast cells, and the results uncover the role of two transcriptional modulators in controlling human mast cell differentiation.

Dynamic network biomarker of treg cells differentiation critical state with neoadjuvant treatment in LUSC.

e20063 Background: Regulatory T cells (Tregs) suppress immune responses and can promote tumor growth and metastasis during cancer progression. Studies have shown that tumor-infiltrating Tregs upregulate inhibitory gene programs after immune checkpoint blockade therapy. Targeting Tregs is believed to be a valuable approach to enhance the effectiveness of immunotherapy. However, the precise role of Tregs in the tumor microenvironment, their connection to treatment resistance mechanisms, and how changes in their immune activity impact tumor treatment are still not well understood. Methods: Single-cell data and clinical information were obtained from the Gene Expression Omnibus database with the accession number GSE176021 for 4 patients diagnosed with lung squamous cell carcinoma (LUSC) who received neoadjuvant anti-PD-1 therapy, including 2 patients with major pathologic response (MPR) and 2 patients with non-MPR. BioTIP was employed to identify critical transition signals of the Treg cell differentiation trajectory constructed by Monocle2. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and gene set variation analysis were performed to understand biological processes and pathways. Additionally, potential transcription factors were identified using Single-Cell rEgulatory Network Inference and Clustering, and CellChat analysis was conducted to evaluate possible interactions among cell populations. Results: The study constructed a pseudo-temporal differentiation trajectory of Tregs in LUSC patients, and Treg subpopulations during the critical transition period were identified based on the dynamic network biomarker method. Notably, subpopulations of Treg cells clustering MPR or non-MPR samples were located at different ends of the differentiation trajectory, showing variations in Treg-related pathways and transcription factor regulation. The critical transition subpopulation exhibited high expression of glycolysis, TCA cycle, and natural killer cell receptors, along with upregulation of the CEBPB transcription factor activity and downregulation of ARNTL activity. SELPLG-SELL, CD99-CD99, and MHC-II-CD4 were identified as potential key signals that may affect therapeutic effect, primarily influencing cell adhesion, the immune suppressive activity of Treg cells, and T cell response. Conclusions: In conclusion, this study utilized single-cell data analysis to uncover the dynamic regulation of Treg cells in LUSC, identifying critical transition Treg subpopulations. Notably, our findings suggest the involvement of the transcription factors CEBPB and ARNTL in regulating Treg activity. These novel insights shed light on potential strategies for targeted therapies and provide valuable information regarding resistance mechanisms associated with Treg cells.

Single cell RNA analysis uncovers the cell differentiation and functionalization for air breathing of frog lung

The evolution and development of vertebrate lungs have been widely studied due to their significance in terrestrial adaptation. Amphibians possess the most primitive lungs among tetrapods, underscoring their evolutionary importance in bridging the transition from aquatic to terrestrial life. However, the intricate process of cell differentiation during amphibian lung development remains poorly understood. Using single-cell RNA sequencing, we identify 13 cell types in the developing lungs of a land-dwelling frog (Microhyla fissipes). We elucidate the differentiation trajectories and mechanisms of mesenchymal cells, identifying five cell fates and their respective driver genes. Using temporal dynamics analyses, we reveal the gene expression switches of epithelial cells, which facilitate air breathing during metamorphosis. Furthermore, by integrating the published data from another amphibian and two terrestrial mammals, we illuminate both conserved and divergent cellular repertoires during the evolution of tetrapod lungs. These findings uncover the frog lung cell differentiation trajectories and functionalization for breathing in air and provide valuable insights into the cell-type evolution of vertebrate lungs.

Single-cell RNA sequencing unveils the activation of EGR1-ATF3 signaling in EGR1 + muscle stem cells during human paravertebral muscle degeneration

BackgroundParavertebral muscles (PVM) degeneration (PMD) is closely associated with low back pain. Muscle stem cells (MuSCs) can promote muscle regeneration and repair. However, our understanding of the cellular composition of PVM and the key genes-mediated MuSCs functions is limited. MethodsWe analyzed cells heterogeneity and identified key genes using scRNA-seq. To validate the presence of EGR1 + MuSCs, we performed Flow cytometry assays. We utilized pseudo-time, CytoTRACE, and RNA velocity to reconstruct cells differentiation trajectory. CellPhoneDB was used to identify the interactions between MuSCs and other cells. ResultsWe identified 22 cell clusters and 10 cell types, including MuSCs. We found EGR1 + MuSCs representing the activated subset. We observed the overall number of MuSCs decreased, while the proportion of EGR1 + MuSCs gradually increased during PMD. We demonstrated the target ATF3 of EGR1 and EGR1 were significantly upregulated in PMD, suggesting EGR1-ATF3 signaling may regulate MuSCs functions. Cell differentiation trajectory indicated EGR1 + MuSCs exhibited higher stemness. We discovered immune cells, fibroblasts, and endothelial cells may collaborate with MuSCs through specific ligand-receptor pairs to regulate MuSCs functions. ConclusionThese findings unveils the activation of EGR1-ATF3 signaling in EGR1 + MuSCs, providing new insights into the cellular and molecular mechanisms underlying PMD.

Single-cell BCR and transcriptome analysis reveals peripheral immune signatures in patients with thyroid-associated ophthalmopathy.

Thyroid-associated ophthalmopathy (TAO) is the most prevalent orbital disease in adults caused by an autoimmune disorder, which can lead to disfigurement and vision impairment. Developing effective treatments for this condition presents challenges due to our limited understanding of its underlying immune aberrations. In this study, we profiled the immune components in the peripheral blood of patients with TAO as well as healthy individuals, utilizing single-cell RNA sequencing and B-cell receptor repertoires (BCR) analysis. We observed a significant reduction in the proportions of regulatory B cells (Bregs) and type 2 conventional dendritic cells (DCs) in patients with TAO during the active phase. Conversely, there was a significant increase in the proportion of type 1 DCs. Further analysis of cell differentiation trajectory revealed potential impairment in the transition of B cells towards Breg phenotype during the active phase of TAO. Besides, the activation process of TAO appeared to involve inflammation and immune dysfunction, as indicated by the dynamic changes in the activities of key regulators. The abnormalities in the peripheral immune system, such as the reduced capacity of Bregs to suppress inflammation, were primarily driven by the enhanced interaction among Breg, DCs, and monocytes (i.e., CD22-PTPRC and BTLA-TNFRSF14). Collectively, our findings offer a comprehensive insight into the molecular regulation and cellular reconfiguration during the active phase of TAO at the single-cell level, in order to explore the pathogenesis of TAO and provide new ideas for the future treatment of TAO.

Cervical cancer subtype identification and model building based on lipid metabolism and post-infection microenvironment immune landscape

BackgroundAs the second most common gynecological cancer, cervical cancer (CC) seriously threatens women's health. The poor prognosis of CC is closely related to the post-infection microenvironment (PIM). This study investigated how lipid metabolism-related genes (LMRGs) affect CC PIM and their role in diagnosing CC. MethodsWe analyzed lipid metabolism scores in the CC single-cell landscape by AUCell. The differentiation trajectory of epithelial cells to cancer cells was revealed using LMRGs and Monocle2. Consensus clustering was used to identify novel subgroups using the LMRGs. Multiple immune assessment methods were used to evaluate the immune landscape of the subgroups. Prognostic genes were determined by the LASSO and multivariate Cox regression analysis. Finally, we perform molecular docking of prognostic genes to explore potential therapeutic agents. ResultsWe revealed the differentiation trajectory of epithelial cells to cancer cells in CC by LMRGs. The higher LMRGs expression cluster had higher survival rates and immune infiltration expression. Functional enrichment showed that two clusters were mainly involved in immune response regulation. A novel LMR signature (LMR.sig) was constructed to predict clinical outcomes in CC. The expression of prognostic genes was correlated with the PIM immune landscape. Small molecular compounds with the best binding effect to prognostic genes were obtained by molecular docking, which may be used as new targeted therapeutic drugs. ConclusionWe found that the subtype with better prognosis could regulate the expression of some critical genes through more frequent lipid metabolic reprogramming, thus affecting the maturation and migration of dendritic cells (DCs) and the expression of M1 macrophages, reshaping the immunosuppressive environment of PIM in CC patients. LMRGs are closely related to the PIM immune landscape and can accurately predict tumor prognosis. These results further our understanding of the underlying mechanisms of LMRGs in CC.

Abstract 2149: Smooth Muscle-derived Resident Vascular Adventitial Progenitor Cell Contribution To Cardiac Fibrosis And Inflammation Is Dependent On KLF4

Cardiac fibrosis is defined by the excessive accumulation of extracellular matrix (ECM) material resulting in cardiac tissue scarring and dysfunction. While it is commonly accepted that myofibroblasts are the major contributors to ECM deposition in cardiac fibrosis, their origin remains debated. By combining lineage tracing and RNA sequencing, our group made the paradigm-shifting discovery that a subpopulation of resident vascular stem cells residing within the vascular adventitia (termed AdvSca1-SM cells) originate from mature vascular smooth muscle cells (SMCs) through an in situ reprogramming process. SMC-to-AdvSca1-SM reprogramming and AdvSca1-SM cell maintenance is dependent on induction and activity of the transcription factor, KLF4. In contrast, loss of Klf4 expression promotes the transition of AdvSca1-SM cells to a myofibroblast phenotype in vascular injury and remodeling. However, the molecular mechanism whereby KLF4 regulates AdvSca1-SM phenotype remains unclear. Our recent preliminary data confirm the existence of perivascular cardiac AdvSca1-SM cells. Leveraging a highly specific AdvSca1-SM cell reporter system, single-cell RNA-sequencing (scRNA-seq), and spatial transcriptomic approaches, we demonstrate the profibrotic differentiation trajectory of AdvSca1-SM cells in the setting of Angiotensin II (AngII)-induced cardiac fibrosis. Differentiation is characterized by loss of stemness-related genes, including Klf4 , but gain of expression of a profibrotic phenotype. Importantly, these changes are recapitulated in human cardiac hypertrophic tissue, supporting the translational significance of profibrotic transition of AdvSca1-SM-like cells in human cardiomyopathy. Very surprisingly and paradoxically, AdvSca1-SM-specific genetic knockout of Klf4 prior to AngII treatment protects against cardiac inflammation and fibrosis, indicating that Klf4 is essential for the profibrotic response of AdvSca1-SM cells. Overall, our data reveal the contribution of AdvSca1-SM cells to myofibroblasts in the setting of cardiac fibrosis. KLF4 not only maintains the stemness of AdvSca1-SM cells, but also orchestrates their response to profibrotic stimuli, and may serve as a therapeutic target in cardiac fibrosis.

InTraSeqTM: a multimodal single cell technology for simultaneous measurement of RNA and proteins in single cells to uncover new single cell biology

Abstract InTraSeqTM is a novel technology for single cell analysis that enables unbiased measurement of both RNA and proteins in individual cells. This innovative approach employs validated and functionally tested antibodies at CST, which allows the identification of cell subtypes and Signaling Pathways in single cells by measuring post-translational modifications (PTMs). One of the significant advantages of using InTraSeqTM is its ability to quantify extracellular, cytoplasmic, and nuclear proteins, including transcription factors, and their PTMs while preserving the RNA and heterogeneity of the sample. This method offers an extensive view of the cellular mechanisms of complex biology, which was previously missing in single cell RNA sequencing datasets. Researchers can use InTraSeqTM to accurately characterize single cell acute and chronic responses, uncover new cell states, and more accurately analyze cell differentiation trajectories. Moreover, InTraSeqTM offers a streamlined protocol that requires only one hour of benchwork and allows for multi-day sample storage, making it a practical and efficient tool for high-throughput applications.