Cell Differentiation Trajectories Research Articles

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.

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.

Single-Cell Nuclear Sequencing Atlas Revealed the Induction of Parkinson's Disease by RELN+ Neuron 3 and the Gene Regulatory Network of MSRA.

To determine the cell types that promoted the progression of Parkinson's disease (PD) using the substantia nigra in the brain tissues derived from patients with PD and normal controls. PD is an incurable neurodegenerative disease that threatens the physical activity of the aging population, and the complex molecular mechanisms remain be comprehensively elucidated. To describe potential disease-promoting cell types in PD and to provide a theoretical basis. Single-cell nuclear sequencing data of nine PD samples and control samples from Gene Expression Omnibus (GEO) were included, and heterogeneous cell subpopulations in the substantia nigra were identified by annotation analysis. Potential pathogenic cell subpopulations of PD were determined based on the expression data of marker genes. Cell differentiation trajectories and communication networks were generated by Pseudotime trajectory analysis and cell communication analysis. Furthermore, single-- cell regulatory network inference and clustering (SCENIC) analysis was conducted to determine the regulatory network of transcription factor-target genes in PD. Among the nine cell subpopulations classified, RELN+neuron 3 showed reduced abundance and dopamine secretion capacity in PD and was therefore considered as a promoter of PD pathogenesis and progression. The regulatory network of MSRA action was involved in the developmental process of cells in the central nervous system, indicating that MSRA and its targets might serve as potential therapeutic targets for PD. RELN+neuron 3 had two directions of differentiation, specifically, branch 1 exhibited a high apoptotic profile and branch 2 exhibited a high cell death profile. In addition, the intensity of EPHA and EPHB signaling was attenuated between RELN+neuron 3 and other cell subpopulations. To conclude, this study identified a subpopulation of RELN+neuron 3 cells with markedly reduced abundance in the brain substantia nigra in PD. The MSRA-involved gene regulatory networks was considered as a novel therapeutic network for PD.

Abstract 135: Resolving the tumorigenesis continuum of DICER1 syndrome with novel lineage-trackable genetically engineered mouse model

Abstract Background: DICER1 syndrome is a rare cancer predisposition syndrome associated with germline DICER1 mutations, which develops pulmonary or extra-pulmonary manifestations mostly in pediatric patients. Unlike classic tumor suppressors, the 2nd hit in DICER1 gene is a missense mutation that renders the RNase IIIb domain defective; therefore, this mutant form of DICER1 is the only protein expressed in these cancer cells, leading to a biased 5p-miRNA production deficiency. Many DICER1 cancers are sarcomas; we therefore postulate the cell of origin is mesenchymal. We recently developed a RNase IIIb-mutant mouse strain and embryonic activation of this mutant along with silencing of the other Dicer1 allele in Mullerian mesenchymal progenitor cells led to the development of tumors resembling sarcomas in human patients. To expand the model and enable lineage tracking, we developed a tamoxifen inducible, tdTomato-trackable, Hypermethylated in Cancer 1 (HIC1)-creERT2 driven transgenic mouse strain. Hic1 marks mesenchymal progenitors. With this strain, we created a model that histologically recapitulates the 3 renal tumors in DICER1 syndrome: cystic nephromas, Wilms tumors, and anaplastic sarcomas. Objective: to identify oncogenic events underlying Dicer1 mutation-driven murine kidney tumor development with single cell RNA-sequencing (scRNA-seq). Method: To build the tumorigenesis continuum, we harvested kidneys from Dicer1+/fl-D1693N and Dicer1fl/fl-D1693N mice at 1, 3, 6, months post tamoxifen injection, sorted out tdTomato+/CD45-/Epcam- cells, and performed scRNA-seq. Five endpoint tumors were included for analyses. Single cell transcriptomic profiles were integrated and clustered using Seurat to identify cell populations that emerge and expand along the tumor development continuum. Differential gene expression, pathway analysis were conducted to identify genes/oncogenic pathways that are activated along the course of tumor development. Cell differentiation trajectory analysis will be performed using Monocle. Results: Integration of 5 tumors revealed diverse cell populations: epithelial, mesenchymal, endothelial cells, lymphocytes, and macrophages. We further clustered the mesenchymal population and identified sub-populations such as highly proliferative cells, muscle satellite cells, and terminally differentiated muscle cells. These mesenchymal cells show high expression of blastema markers (Ncam1, Sox11) - a histological component in Wilms tumors. Temporal trajectory of tumorigenesis with time point samples is currently being analyzed. Conclusion: With scRNA-seq, we begin to unravel heterogeneity of these murine tumors and will identify critical oncogenic events driving the development of DICER1 syndrome-associated cancer, enabling us to utilize this model to develop therapeutic approaches to improve patient management. Citation Format: Joyce Zhang, Shary Chen, Yana Moscovitz, Branden Lynch, Maxwell Douglas, Janine Senz, Wilder Scott, Michael Underhill, Yemin Wang, David Huntsman. Resolving the tumorigenesis continuum of DICER1 syndrome with novel lineage-trackable genetically engineered mouse model [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 135.

Single cell analysis of short-term dry eye induced changes in cornea immune cell populations.

Dry eye causes corneal inflammation, epitheliopathy and sensorineural changes. This study evaluates the hypothesis that dry eye alters the percentages and transcriptional profiles of immune cell populations in the cornea. Desiccating stress (DS) induced dry eye was created by pharmacologic suppression of tear secretion and exposure to drafty low humidity environment. Expression profiling of corneal immune cells was performed by single-cell RNA sequencing (scRNA-seq). Cell differentiation trajectories and cell fate were modeled through RNA velocity analysis. Confocal microscopy was used to immunodetect corneal immune cells. Irritation response to topical neurostimulants was assessed. Twelve corneal immune cell populations based on their transcriptional profiles were identified at baseline and consist of monocytes, resident (rMP) and MMP12/13 high macrophages, dendritic cells (cDC2), neutrophils, mast cells, pre T/B cells, and innate (γDT, ILC2, NK) and conventional T and B lymphocytes. T cells and resident macrophages (rMP) were the largest populations in the normal cornea comprising 18.6 and 18.2 percent, respectively. rMP increased to 55.2% of cells after 5 days of DS. Significant changes in expression of 1,365 genes (adj p < 0.0001) were noted in rMP with increases in cytokines and chemokines (Tnf, Cxcl1, Ccl12, Il1rn), inflammatory markers (Vcam, Adam17, Junb), the TAM receptor (Mertk), and decreases in complement and MHCII genes. A differentiation trajectory from monocytes to terminal state rMP was found. Phagocytosis, C-type lectin receptor signaling, NF-kappa B signaling and Toll-like receptor signaling were among the pathways with enhanced activity in these cells. The percentage of MRC1+ rMPs increased in the cornea and they were observed in the basal epithelium adjacent to epithelial nerve plexus. Concentration of the chemokine CXCL1 increased in the cornea and it heightened irritation/pain responses to topically applied hypertonic saline. These findings indicate that DS recruits monocytes that differentiate to macrophages with increased expression of inflammation associated genes. The proximity of these macrophages to cornea nerves and their expression of neurosensitizers suggests they contribute to the corneal sensorineural changes in dry eye.

Cell cycle heterogeneity and plasticity of colorectal cancer stem cells.

Cancer stem cells (CSCs) are a long-lived and self-renewing cancer cell population that drives tumor propagation and maintains cancer heterogeneity. They are also implicated in the therapeutic resistance of various types of cancer. Recent studies of CSCs in colorectal cancer (CRC) have uncovered fundamental paradigms that have increased understanding of CSC systems in solid tumors. Colorectal CSCs share multiple biological properties with normal intestinal stem cells (ISCs), including expression of the stem cell marker Lgr5. New evidence suggests that colorectal CSCs manifest substantial heterogeneity, as exemplified by the existence of both actively cycling Lgr5+ CSCs as well as quiescent Lgr5+ CSCs that are resistant to conventional anticancer therapies. The classical view of a rigid cell hierarchy and irreversible cell differentiation trajectory in normal and neoplastic tissues is now challenged by the finding that differentiated cells have the capacity to revert to stem cells through dynamic physiological reprogramming events. Such plasticity of CSC systems likely underlies both carcinogenesis and therapeutic resistance in CRC. Further characterization of the mechanisms underpinning the heterogeneity and plasticity of CSCs should inform future development of eradicative therapeutic strategies for CRC.

Multi-omics analysis-based macrophage differentiation-associated papillary thyroid cancer patient classifier

BackgroundThe reclassification of Papillary Thyroid Carcinoma (PTC) is an area of research that warrants attention. The connection between thyroid cancer, inflammation, and immune responses necessitates considering the mechanisms of differential prognosis of thyroid tumors from an immunological perspective. Given the high adaptability of macrophages to environmental stimuli, focusing on the differentiation characteristics of macrophages might offer a novel approach to address the issues related to PTC subtyping. MethodsSingle-cell RNA sequencing data of medullary cells infiltrated by papillary thyroid carcinoma obtained from public databases was subjected to dimensionality reduction clustering analysis. The RunUMAP and FindAllMarkers functions were utilized to identify the gene expression matrix of different clusters. Cell differentiation trajectory analysis was conducted using the Monocle R package. A complex regulatory network for the classification of Immune status and Macrophage differentiation-associated Papillary Thyroid Cancer Classification (IMPTCC) was constructed through quantitative multi-omics analysis. Immunohistochemistry (IHC) staining was utilized for pathological histology validation. ResultsThrough the integration of single-cell RNA and bulk sequencing data combined with multi-omics analysis, we identified crucial transcription factors, immune cells/immune functions, and signaling pathways. Based on this, regulatory networks for three IMPTCC clusters were established. ConclusionBased on the co-expression network analysis results, we identified three subtypes of IMPTCC: Immune-Suppressive Macrophage differentiation-associated Papillary Thyroid Carcinoma Classification (ISMPTCC), Immune-Neutral Macrophage differentiation-associated Papillary Thyroid Carcinoma Classification (INMPTCC), and Immune-Activated Macrophage differentiation-associated Papillary Thyroid Carcinoma Classification (IAMPTCC). Each subtype exhibits distinct metabolic, immune, and regulatory characteristics corresponding to different states of macrophage differentiation.

Induction of lung progenitor cell-like organoids by porcine pluripotent stem cells.

Organoids are invitro 3D models that are generated using stem cells to study organ development and regeneration. Despite the extensive research on lung organoids, there is limited information on pig lung cell generation or development. Here, we identified five epithelial cell types along with their characteristic markers using scRNA-seq. Additionally, we found that NKX2.1 and FOXA2 acted as the crucial core transcription factors in porcine lung development. The presence of SOX9/SOX2 double-positive cells was identified as a key marker for lung progenitor cells. The Monocle algorithm was used to create a pseudo-temporal differentiation trajectory of epithelial cells, leading to the identification of signaling pathways related to porcine lung development. Moreover, we established the differentiation method from porcine pluripotent stem cells (pPSCs) to SOX17+ FOXA2+ definitive endoderm (DE) and NKX2.1+ FOXA2+ CDX2- anterior foregut endoderm (AFE). The AFE is further differentiated into lung organoids while closely monitoring the differentiation process. We showed that NKX2.1 overexpression facilitated the induction of lung organoids and supported subsequent lung differentiation and maturation. This model offers valuable insights into studying the interaction patterns between cells and the signaling pathways during the development of the porcine lung.

MLBKFD: Probabilistic Model Methods to Infer Pseudo Trajectories from Single-cell Data

Cell trajectory inference is very important to understand the details of tissue cell development, state differentiation and gene dynamic regulation. However, due to the high noise and heterogeneity of the single-cell data, it is challenging to infer cell trajectory in complex biological processes. Here, we proposed a new trajectory inference method, called Metric Learning Bhattacharyya Kernel Feature Decomposition (MLBKFD). In MLBKFD, a statistical model was used to infer cell trajectory by calculating the Markov transition matrix and Bhattacharyya kernel matrix between cells. Before that, to expedite the matrix calculation in the statistical model, a deep feedforward neural network was used to perform dimensionality reduction on single-cell data. The MLBKFD was evaluated on four typical datasets as well as seven recent human fetal lung datasets. Comparisons with the two outstanding methods (i.e., DTFLOW and MARGARET) demonstrate that the MLBKFD is capable of accurately inferring cell development and differentiation trajectories from single-cell data with different sizes and sources. Notably, MLBKFD exhibits nearly twice the speed of DTFLOW while maintaining high precision, particularly when dealing with large datasets. MLBKFD provides accurate and efficient trajectory inference, empowering researchers to gain deeper insights into the complex dynamics of cell development and differentiation.

Integrating scRNA-seq and bulk RNA-seq to characterize infiltrating cells in the colorectal cancer tumor microenvironment and construct molecular risk models.

Colorectal cancer (CRC) is a malignancy that is both highly lethal and heterogeneous. Although the correlation between intra-tumoral genetic and functional heterogeneity and cancer clinical prognosis is well-established, the underlying mechanism in CRC remains inadequately understood. Utilizing scRNA-seq data from GEO database, we re-isolated distinct subsets of cells, constructed a CRC tumor-related cell differentiation trajectory, and conducted cell-cell communication analysis to investigate potential interactions across cell clusters. A prognostic model was built by integrating scRNA-seq results with TCGA bulk RNA-seq data through univariate, LASSO, and multivariate Cox regression analyses. Eleven distinct cell types were identified, with Epithelial cells, Fibroblasts, and Mast cells exhibiting significant differences between CRC and healthy controls. T cells were observed to engage in extensive interactions with other cell types. Utilizing the 741 signature genes, prognostic risk score model was constructed. Patients with high-risk scores exhibited a significant correlation with unfavorable survival outcomes, high-stage tumors, metastasis, and low responsiveness to chemotherapy. The model demonstrated a strong predictive performance across five validation cohorts. Our investigation involved an analysis of the cellular composition and interactions of infiltrates within the microenvironment, and we developed a prognostic model. This model provides valuable insights into the prognosis and therapeutic evaluation of CRC.

Early concentrate starter introduction induces rumen epithelial parakeratosis by blocking keratinocyte differentiation with excessive ruminal butyrate accumulation

IntroductionRumen epithelial parakeratosis, a common disease in ruminants caused by abnormalities in the ruminal stratified squamous epithelial keratinization process, negatively impacts ruminant health and performance. However, we still lack a comprehensive perception of the underlying mechanisms and the predisposing factors for this disorder. ObjectivesHere, we investigated rumen epithelial cell heterogeneity, differentiation trajectories, and cornification to clarify the rumen epithelial keratinization process and discern the key ruminal metabolites contributing to rumen epithelial parakeratosis. MethodsTwenty-four 14-day-old lambs were divided into three groups, including only milk feeding, milk plus alfalfa hay feeding, and milk plus corn-soybean concentrate starter feeding. At 42 days of age, the lambs were slaughtered, and rumen tissues were collected for single-cell RNA-sequencing (scRNA-seq), immunofluorescence, and quantitative real-time PCR (qRT-PCR) analyses. Ruminal fluid samples were collected for metabolomic analyses. Rumen epithelial organoid was used to verify the key ruminal metabolites contributing to parakeratosis. ResultsAs expected, we observed that concentrate starter introduction resulted in rumen epithelial parakeratosis. Moreover, scRNA-seq analysis revealed a developmental impediment in the transition from differentiated keratinocytes to terminally differentiated keratinocytes (TDK) in lambs with concentrate starter introduction. Immunofluorescence and qRT-PCR analyses further verified the location and expression of marker genes of TDK. Metabolomic analysis showed a robust positive correlation between ruminal butyrate levels and rumen epithelial keratinization. More importantly, we successfully established a rumen organoid model capable of facilitating the study of the keratinization process in the rumen epithelia and further confirmed that high dose butyrate indeed contributed to rumen epithelial parakeratosis. ConclusionCollectively, concentrate starter introduction induces ruminal epithelial parakeratosis by blocking keratinocyte differentiation with excessive ruminal butyrate accumulation in a neonatal lamb model. These findings enhance our understanding of rumen epithelial keratinization and provide valuable insights for addressing rumen epithelial parakeratosis using early nutritional intervention strategies.

Epigenetic switch reshapes epithelial progenitor cell signatures and drives inflammatory pathogenesis in hidradenitis suppurativa.

Hidradenitis suppurativa (HS) is a complex inflammatory skin disease with undefined mechanistic underpinnings. Here, we investigated HS epithelial cells and demonstrated that HS basal progenitors modulate their lineage restriction and give rise to pathogenic keratinocyte clones, resulting in epidermal hyperproliferation and dysregulated inflammation in HS. When comparing to healthy epithelial stem/progenitor cells, in HS, we identified changes in gene signatures that revolve around the mitotic cell cycle, DNA damage response and repair, as well as cell-cell adhesion and chromatin remodeling. By reconstructing cell differentiation trajectory and CellChat modeling, we identified a keratinocyte population specific to HS. This population is marked by S100A7/8/9 and KRT6 family members, triggering IL1, IL10, and complement inflammatory cascades. These signals, along with HS-specific proinflammatory cytokines and chemokines, contribute to the recruitment of certain immune cells during the disease progression. Furthermore, we revealed a previously uncharacterized role of S100A8 in regulating the local chromatin environment of target loci in HS keratinocytes. Through the integration of genomic and epigenomic datasets, we identified genome-wide chromatin rewiring alongside the switch of transcription factors (TFs), which mediated HS transcriptional profiles. Importantly, we identified numerous clinically relevant inflammatory enhancers and their coordinated TFs in HS basal CD49fhigh cells. The disruption of the S100A enhancer using the CRISPR/Cas9-mediated approach or the pharmacological inhibition of the interferon regulatory transcription factor 3 (IRF3) efficiently reduced the production of HS-associated inflammatory regulators. Our study not only uncovers the plasticity of epidermal progenitor cells in HS but also elucidates the epigenetic mechanisms underlying HS pathogenesis.

Characterization of human pluripotent stem cell differentiation by single-cell dual-omics analyses

Invivo differentiation of human pluripotent stem cells (hPSCs) has unique advantages, such as multilineage differentiation, angiogenesis, and close cell-cell interactions. To systematically investigate multilineage differentiation mechanisms of hPSCs, we constructed the invivo hPSC differentiation landscape containing 239,670 cells using teratoma models. We identified 43 cell types, inferred 18 cell differentiation trajectories, and characterized common and specific gene regulation patterns during hPSC differentiation at both transcriptional and epigenetic levels. Additionally, we developed the developmental single-cell Basic Local Alignment Search Tool (dscBLAST), an R-based cell identification tool, to simplify the identification processes of developmental cells. Using dscBLAST, we aligned cells in multiple differentiation models to normally developing cells to further understand their differentiation states. Overall, our study offers new insights into stem cell differentiation and human embryonic development; dscBLAST shows favorable cell identification performance, providing a powerful identification tool for developmental cells.

SCInter: a comprehensive single-cell transcriptome integration database for human and mouse

Single-cell RNA sequencing (scRNA-seq), which profiles gene expression at the cellular level, has effectively explored cell heterogeneity and reconstructed developmental trajectories. With the increasing research on diseases and biological processes, scRNA-seq datasets are accumulating rapidly, highlighting the urgent need for collecting and processing these data to support comprehensive and effective annotation and analysis. Here, we have developed a comprehensive Single-Cell transcriptome integration database for human and mouse (SCInter, https://bio.liclab.net/SCInter/index.php), which aims to provide a manually curated database that supports the provision of gene expression profiles across various cell types at the sample level. The current version of SCInter includes 115 integrated datasets and 1016 samples, covering nearly 150 tissues/cell lines. It contains 8016,646 cell markers in 457 identified cell types. SCInter enabled comprehensive analysis of cataloged single-cell data encompassing quality control (QC), clustering, cell markers, multi-method cell type automatic annotation, predicting cell differentiation trajectories and so on. At the same time, SCInter provided a user-friendly interface to query, browse, analyze and visualize each integrated dataset and single cell sample, along with comprehensive QC reports and processing results. It will facilitate the identification of cell type in different cell subpopulations and explore developmental trajectories, enhancing the study of cell heterogeneity in the fields of immunology and oncology.

Early Molecular Steps in Human Bone Marrow Stem Cell Differentiation Trajectories

Understanding the molecular signatures of human hematopoietic stem/progenitor cells (HSCPs) and gene network changes leading to differentiation induction are of utmost importance to achieve therapeutic hematopoietic stem cell (HSC) expansion. The identification of surface markers has improved the prospective isolation of human bone marrow HSCs over the last decades, but the isolated population still remains very heterogeneous. Single cell sequencing approaches have the potential to unbiased assort stem cells along their differentiation stages and trajectories, and to decipher molecular markers in differentiation hierarchies. However, whole transcriptome single cell sequencing often suffers from inadequate detection of low-expressed genes with increased drop-outs. To address this limitation and to provide sensitive mRNA quantification in human HSPCs, we developed a selected targeted gene panel (600 genes) in combination with 50 protein markers to cover most relevant genes/proteins of early HSPC differentiation and cell cycle status. We employed single cell CITE-Seq (cellular indexing of transcriptomes and epitopes by sequencing) based multi-omic profiling to &amp;gt;60.000 high-quality FACS-enriched human bone marrow HSPCs (CD34 + and CD34 +CD38 - cells) from 15 healthy donors representing young, mid and old age groups. Here, we demonstrate the most comprehensive molecular map of early human HSC differentiation and provide evidence of early branching points into lineage trajectories across different age groups using Slingshot pseudotime analysis. Our data demonstrate that the HSC branched into two main lineages, with the first branching point giving rise to megakaryocytic and erythroid progenitors (MKP/ERP), followed by lymphoid and myeloid progenitors (LMP/MDP). As expected, the most immature HSCs were defined by high expression of CD34, CD90, CRHBP, HOPX, HLF, MLLT3. However, we observed a number of hitherto undescribed HSC markers. The MKP/ERP lineage was defined by GATA1, TFRC, CD36, MPL and VWF expression. Furthermore, we found CD274, the Programmed Cell Death receptor ligand 1, to be selectively expressed in the MKP cluster. Re-clustering and trajectory analysis of the most immature CD34 +CD38 -/low cells confirmed early lineage commitment, suggesting that an MKP/ERP development does not include myeloid or lymphoid progenitors. A similar pattern was observed for all age groups. Interestingly, we observed increased expression of novel marker genes ( HLA-E, DLK1, ADGRG6, ADGRG1, MMRN1) and proteins (CD137 and CD273) in the most immature HSCs. Besides a gradual upregulation of CD38 along differentiation, differentiated cells showed lower CD45 levels. Furthermore, MKP/ERP committed cells showed a downregulation of SPINK2. TradeSeq analysis defined the continuous single cell expression changes in genes and markers upon early differentiation and lineage commitment, allowing the detection of decision-making gene networks. Our data adds further evidence to the revised model of hematopoiesis that challenges the dogma of a common myeloid progenitor giving rise to erythroid, megakaryocytic and myeloid cells. Furthermore, we see a structured hierarchical organization with a sequential loss of lineage potential and not an early commitment of uni-lineage restricted precursors. We report on the upregulation of ADGRG6, ADGRG1, DLK1, HLA-E, MMRN1 CD137 and CD273 in the most immature HSCs. Molecular and functional characterization of CD273 hi and low HSCs are presented in an adjacent report by our group at this meeting (Schmachtel et al.). In conclusion, we provide a valuable resource for the continuous regulation of genes and surface proteins along early differentiation of very immature human HSCs.

Deciphering Tumor Cell Evolution in Cutaneous T-Cell Lymphomas: Distinct Differentiation Trajectories in Mycosis Fungoides and Sézary Syndrome

Cutaneous T-cell lymphomas are a heterogeneous group of neoplasms originating in the skin, with mycosis fungoides (MF) and Sézary syndrome (SS) representing the most common variants. The cellular origin of cutaneous lymphomas has remained controversial owing to their immense phenotypic heterogeneity that obfuscates lineage reconstruction on the basis of classical surface biomarkers. To overcome this heterogeneity and reconstruct the differentiation trajectory of malignant cells in MF and SS, TCR sequencing was performed in parallel with targeted transcriptomics at the single-cell resolution among cutaneous samples in MF and SS. Unsupervised lineage reconstruction showed that Sézary cells exist as a population of CD4+ T cells distinct from those in patch, plaque, and tumor MF. Further investigation of malignant cell heterogeneity in SS showed that Sézary cells phenotypically comprised at least 3 subsets on the basis of differential proliferation potentials and expression of exhaustion markers. A T helper 1-polarized cell type, intermediate cell type, and exhausted T helper 2-polarized cell type were identified, with T helper 1- and T helper 2-polarized cells displaying divergent proliferation potentials. Collectively, these findings provide evidence to clarify the relationship between MF and SS and reveal cell subsets in SS that suggest a possible mechanism for therapeutic resistance.