Single-cell sequencing analysis revealed that WDR72 was a novel cancer stem cells related gene in gastric cancer.

Background: Cancer stem cells (CSCs) are pivotal in tumor resistance to chemotherapy and gastric cancer's rapid proliferation and metastasis. We aimed to explore the CSCs-related genes in gastric cancer epithelial cells. Methods: The mRNA expression profile and single-cell sequencing data of gastric cancer were downloaded from the public database. Results: We identified WDR72 as a CSCs-related gene in gastric cancer epithelial cells. WDR72 was highly expressed in gastric cancer tissues, and high expression of WDR72 was associated with inferior prognosis of patients. WDR72 expression had a significant negative correlation with the infiltration of CD8 + T cells and activated memory CD4 + T cells. PD-L1 expression was significantly reduced in gastric cancer patients with high WDR72 expression. WDR72 was correlated with IC50 of multiple small-molecule drugs. Conclusion: We identified a novel CSCs-related gene in gastric cancer epithelial cells, WDR72, which was highly expressed in patients with high stemness scores.

TooManyCellsInteractive: A visualization tool for dynamic exploration of single-cell data.

BACKGROUND: As single-cell sequencing technologies continue to advance, the growing volume and complexity of the ensuing data present new analytical challenges. Large cellular populations from single-cell atlases are more difficult to visualize and require extensive processing to identify biologically relevant subpopulations. Managing these workflows is also laborious for technical users and unintuitive for nontechnical users. RESULTS: We present TooManyCellsInteractive (TMCI), a browser-based JavaScript application for interactive exploration of cell populations. TMCI provides an intuitive interface to visualize and manipulate a radial tree representation of hierarchical cell subpopulations and allows users to easily overlay, filter, and compare biological features at multiple resolutions. Here we describe the software architecture and demonstrate how we used TMCI in a pan-cancer analysis to identify unique survival pathways among drug-tolerant persister cells. CONCLUSIONS: TMCI will facilitate exploration and visualization of large-scale sequencing data in a user-friendly way. TMCI is freely available at https://github.com/schwartzlab-methods/too-many-cells-interactive. An example tree from data within this article is available at https://tmci.schwartzlab.ca/.

Breaking barriers: improving time and space resolution of arbuscular mycorrhizal symbiosis with single-cell sequencing approaches.

The cell and molecular bases of arbuscular mycorrhizal (AM) symbiosis, a crucial plant-fungal interaction for nutrient acquisition, have been extensively investigated by coupling traditional RNA sequencing techniques of roots sampled in bulk, with methods to capture subsets of cells such as laser microdissection. These approaches have revealed central regulators of this complex relationship, yet the requisite level of detail to effectively untangle the intricacies of temporal and spatial development remains elusive.The recent adoption of single-cell RNA sequencing (scRNA-seq) techniques in plant research is revolutionizing our ability to dissect the intricate transcriptional profiles of plant-microbe interactions, offering unparalleled insights into the diversity and dynamics of individual cells during symbiosis. The isolation of plant cells is particularly challenging due to the presence of cell walls, leading plant researchers to widely adopt nuclei isolation methods. Despite the increased resolution that single-cell analyses offer, it also comes at the cost of spatial perspective, hence, it is necessary the integration of these approaches with spatial transcriptomics to obtain a comprehensive overview.To date, few single-cell studies on plant-microbe interactions have been published, most of which provide high-resolution cell atlases that will become crucial for fully deciphering symbiotic interactions and addressing future questions. In AM symbiosis research, key processes such as the mutual recognition of partners during arbuscule development within cortical cells, or arbuscule senescence and degeneration, remain poorly understood, and these advancements are expected to shed light on these processes and contribute to a deeper understanding of this plant-fungal interaction.

From Cell to Gene: Deciphering the Mechanism of Heart Failure With Single-Cell Sequencing.

Heart failure (HF) is a prevalent cardiovascular disease with significant morbidity and mortality rates worldwide. Due to the intricate structure of the heart, diverse cell types, and the complex pathogenesis of HF, further in-depth investigation into the underlying mechanisms  is required. The elucidation of the heterogeneity of cardiomyocytes and the intercellular communication network is particularly important. Traditional high-throughput sequencing methods provide an average measure of gene expression, failing to capture the "heterogeneity" between cells and impacting the accuracy of gene function knowledge. In contrast, single-cell sequencing techniques allow for the amplification of the entire genome or transcriptome at the individual cell level, facilitating the examination of gene structure and expression with unparalleled precision. This approach offers valuable insights into disease mechanisms, enabling the identification of changes in cellular components and gene expressions during hypertrophy associated with HF. Moreover, it reveals distinct cell populations and their unique roles in the HF microenvironment, providing a comprehensive understanding of the cellular landscape that underpins HF pathogenesis. This review focuses on the insights provided by single-cell sequencing techniques into the mechanisms underlying HF and discusses the challenges encountered in current cardiovascular research.

Identification of the novel exhausted T cell CD8 + markers in breast cancer.

Cancer is one of the most concerning public health issues and breast cancer is one of the most common cancers in the world. The immune cells within the tumor microenvironment regulate cancer development. In this study, single immune cell data sets were used to identify marker gene sets for exhausted CD8 + T cells (CD8Tex) in breast cancer. Machine learning methods were used to cluster subtypes and establish the prognostic models with breast cancer bulk data using the gene sets to evaluate the impacts of CD8Tex. We analyzed breast cancer overexpressing and survival-associated marker genes and identified CD8Tex hub genes in the protein-protein-interaction network. The relevance of the hub genes for CD8 + T-cells in breast cancer was evaluated. The clinical associations of the hub genes were analyzed using bulk sequencing data and spatial sequencing data. The pan-cancer expression, survival, and immune association of the hub genes were analyzed. We identified biomarker gene sets for CD8Tex in breast cancer. CD8Tex-based subtyping systems and prognostic models performed well in the separation of patients with different immune relevance and survival. CRTAM, CLEC2D, and KLRB1 were identified as CD8Tex hub genes and were demonstrated to have potential clinical relevance and immune therapy impact. This study provides a unique view of the critical CD8Tex hub genes for cancer immune therapy.

Single-Cell Transcriptomic Profiling of Cholangiocyte Organoids Derived from Bile Ducts of Primary Sclerosing Cholangitis Patients.

BACKGROUND AND AIMS: Primary sclerosing cholangitis (PSC) is a chronic inflammatory liver disorder without effective medical treatment which is characterized by inflammation and fibrotic structures around the bile ducts. Biliary epithelial cells (cholangiocytes) are the target and potential disease drivers in PSC, yet little is known if cholangiocytes from PSC patients differ from non-PSC controls. To characterize cholangiocytes at early rather than end-stage disease, cholangiocyte organoids (COs) were derived from diseased bile ducts of PSC patients and compared to organoids generated from disease controls. METHODS: Cholangiocytes were obtained during endoscopic retrograde cholangiopancreatography (ERCP) brushing of diseased bile duct areas and expanded as organoids using previously established culture methods. Stable CO lines were analyzed for cell type identity, basic cholangiocyte function, and transcriptomic signature. RESULTS: We demonstrate that cholangiocytes, derived from the damaged area within the bile ducts of PSC patients, can be expanded in culture without displaying functional or genetic disease-related features. We further show that COs from patients who later were diagnosed with dysplasia exhibit higher expression of the cancer-associated genes PGC, FXYD2, MIR4435-2HG, and HES1. CONCLUSIONS: Our results demonstrate that PSC organoids are largely similar to control organoids after culture and highlight the significance of COs as a tool for regenerative medicine approaches as well as their potential for discovering new potential biomarkers for diagnosing cholangiocarcinoma.

The combination of single-cell and RNA sequencing analysis decodes the melanoma tumor microenvironment and identifies novel T cell-associated signature genes.

Skin cutaneous melanoma (SKCM), a malignant melanocyte-derived skin cancer, potentially leads to fatal outcomes without effective treatment. The variability in immunotherapy responses among melanoma patients is significantly influenced by the intricate immune microenvironment, particularly due to the status of tumor T cells, encompassing their activity, exhaustion levels, and antigen recognition capabilities. This study utilized single-cell RNA sequencing (scRNA-seq) to analyze 34 melanoma samples from two public datasets (GSE215120 and GSE115978). Herein, we extracted 706 marker genes associated with immune checkpoint (ICP) therapy from these T cells, 509 markers of T cells from 11 melanoma tissues, and eventually identified 33 candidate genes. These genes underwent LASSO and COX regression analyses to identify the signature genes. Of the initial 33 candidate genes, we successfully isolated six distinct T cell-associated immunotherapy-related genes (IRTGs). Additionally, the computation of each patient risk score proved beneficial in evaluating the immune cell infiltration level and functions as an independent prognostic factor for melanoma patient survival. The risk score results revealed promising predictive outcomes in determining the response of melanoma patients to immunotherapy. Notably, our study is the first to reveal the potential correlation between signature gene PEB4B and the immune microenvironment in melaoma, which was explored with multiple immunofluorescence (IF) and Immune Infiltration Assessment. In a conclusion, our findings demonstrate the potential utility of a risk score dependent on signature genes as a predictive tool for assessing the prognosis and response to immunotherapeutic interventions in melanoma patients.

Single-cell landscape revealed immune characteristics associated with disease phases in brucellosis patients.

A comprehensive immune landscape for Brucella infection is crucial for developing new treatments for brucellosis. Here, we utilized single-cell RNA sequencing (scRNA-seq) of 290,369 cells from 35 individuals, including 29 brucellosis patients from acute (n = 10), sub-acute (n = 9), and chronic (n = 10) phases as well as six healthy donors. Enzyme-linked immunosorbent assays were applied for validation within this cohort. Brucella infection caused a significant change in the composition of peripheral immune cells and inflammation was a key feature of brucellosis. Acute patients are characterized by potential cytokine storms resulting from systemic upregulation of S100A8/A9, primarily due to classical monocytes. Cytokine storm may be mediated by activating S100A8/A9-TLR4-MyD88 signaling pathway. Moreover, monocytic myeloid-derived suppressor cells were the probable contributors to immune paralysis in acute patients. Chronic patients are characterized by a dysregulated Th1 response, marked by reduced expression of IFN-γ and Th1 signatures as well as a high exhausted state. Additionally, Brucella infection can suppress apoptosis in myeloid cells (e.g., mDCs, classical monocytes), inhibit antigen presentation in professional antigen-presenting cells (APCs; e.g., mDC) and nonprofessional APCs (e.g., monocytes), and induce exhaustion in CD8+ T/NK cells, potentially resulting in the establishment of chronic infection. Overall, our study systemically deciphered the coordinated immune responses of Brucella at different phases of the infection, which facilitated a full understanding of the immunopathogenesis of brucellosis and may aid the development of new effective therapeutic strategies, especially for those with chronic infection.

Comprehensive investigation of tumor immune microenvironment and prognostic biomarkers in osteosarcoma through integrated bulk and single-cell transcriptomic analysis.

Osteosarcoma (OS) is an aggressive and highly lethal bone tumor, highlighting the urgent need for further exploration of its underlying mechanisms. In this study, we conducted analyses utilizing bulk transcriptome sequencing data of OS and healthy control samples, as well as single cell sequencing data, obtained from public databases. Initially, we evaluated the differential expression of four tumor microenvironment (TME)-related gene sets between tumor and control groups. Subsequently, unsupervised clustering analysis of tumor tissues identified two significantly distinct clusters. We calculated the differential scores of the four TME-related gene sets for Clusters 1 (C1) and 2 (C2), using Gene Set Variation Analysis (GSVA, followed by single-variable Cox analysis. For the two clusters, we performed survival analysis, examined disparities in clinical-pathological distribution, analyzed immune cell infiltration and immune evasion prediction, assessed differences in immune infiltration abundance, and evaluated drug sensitivity. Differentially expressed genes (DEGs) between the two clusters were subjected to Gene Ontology (GO) and Gene Set Enrichment Analysis (GSEA). We conducted Weighted Gene Co-expression Network Analysis (WGCNA) on the TARGET-OS dataset to identify key genes, followed by GO enrichment analysis. Using LASSO and multiple regression analysis we conducted a prognostic model comprising eleven genes (ALOX5AP, CD37, BIN2, C3AR1, HCLS1, ACSL5, CD209, FCGR2A, CORO1A, CD74, CD163) demonstrating favorable diagnostic efficacy and prognostic potential in both training and validation cohorts. Using the model, we conducted further immune, drug sensitivity and enrichment analysis. We performed dimensionality reduction and annotation of cell subpopulations in single cell sequencing analysis, with expression profiles of relevant genes in each subpopulation analyzed. We further substantiated the role of ACSL5 in OS through a variety of wet lab experiments. Our study provides new insights and theoretical foundations for the prognosis, treatment, and drug development for OS patients.

Deciphering the immune-metabolic nexus in sepsis: a single-cell sequencing analysis of neutrophil heterogeneity and risk stratification.

Background: Metabolic dysregulation following sepsis can significantly compromise patient prognosis by altering immune-inflammatory responses. Despite its clinical relevance, the exact mechanisms of this perturbation are not yet fully understood. Methods: Single-cell RNA sequencing (scRNA-seq) was utilized to map the immune cell landscape and its association with metabolic pathways during sepsis. This study employed cell-cell interaction and phenotype profiling from scRNA-seq data, along with pseudotime trajectory analysis, to investigate neutrophil differentiation and heterogeneity. By integrating scRNA-seq with Weighted Gene Co-expression Network Analysis (WGCNA) and machine learning techniques, key genes were identified. These genes were used to develop and validate a risk score model and nomogram, with their efficacy confirmed through Receiver Operating Characteristic (ROC) curve analysis. The model's practicality was further reinforced through enrichment and immune characteristic studies based on the risk score and in vivo validation of a critical gene associated with sepsis. Results: The complex immune landscape and neutrophil roles in metabolic disturbances during sepsis were elucidated by our in-depth scRNA-seq analysis. Pronounced neutrophil interactions with diverse cell types were revealed in the analysis of intercellular communication, highlighting pathways that differentiate between proximal and core regions within atherosclerotic plaques. Insight into the evolution of neutrophil subpopulations and their differentiation within the plaque milieu was provided by pseudotime trajectory mappings. Diagnostic markers were identified with the assistance of machine learning, resulting in the discovery of PIM1, HIST1H1C, and IGSF6. The identification of these markers culminated in the development of the risk score model, which demonstrated remarkable precision in sepsis prognosis. The model's capability to categorize patient profiles based on immune characteristics was confirmed, particularly in identifying individuals at high risk with suppressed immune cell activity and inflammatory responses. The role of PIM1 in modulating the immune-inflammatory response during sepsis was further confirmed through experimental validation, suggesting its potential as a therapeutic target. Conclusion: The understanding of sepsis immunopathology is improved by this research, and new avenues are opened for novel prognostic and therapeutic approaches.

Computational Strategies and Algorithms for Inferring Cellular Composition of Spatial Transcriptomics Data.

Spatial transcriptomics technology has been an essential and powerful method for delineating tissue architecture at the molecular level. However, due to the limitations of the current spatial techniques, the cellular information cannot be directly measured but instead spatial spots typically varying from a diameter of 0.2 to 100 µm are characterized. Therefore, it is vital to apply computational strategies for inferring the cellular composition within each spatial spot. The main objective of this review is to summarize the most recent progresses to estimate the exact cellular proportions for each spatial spot, and to prospect the future directions of this field.

Enhancing insight into ferroptosis mechanisms in sepsis: A genomic and pharmacological approach integrating single-cell sequencing and Mendelian randomization.

This research investigated the intricate relationship between ferroptosis and sepsis by utilizing advanced genomic and pharmacological methodologies. Specifically, we obtained expression quantitative trait loci (eQTLs) for 435 genes associated with ferroptosis from the eQTLGen Consortium and detected notable cis-eQTLs for 281 of these genes. Next, we conducted a detailed analysis to assess the impact of these eQTLs on susceptibility to sepsis using Mendelian randomization (MR) with data from a cohort of 10,154 sepsis patients and 452,764 controls sourced from the UK Biobank. MR analysis revealed 16 ferroptosis-related genes that exhibited significant associations with sepsis outcomes. To bolster the robustness of these findings, sensitivity analyses were performed to assess pleiotropy and heterogeneity, thus confirming the reliability of the causal inferences. Furthermore, single-cell RNA sequencing data from sepsis patients offered a detailed examination of gene expression profiles, demonstrating varying levels of ferroptosis marker expression across different cell types. Pathway enrichment analysis utilizing gene set enrichment analysis (GSEA) further revealed the key biological pathways involved in the progression of sepsis. Additionally, the use of computational molecular docking facilitated the prediction of interactions between identified genes and potential therapeutic compounds, highlighting novel drug targets. In conclusion, our integrated approach combining genomics and pharmacology offers valuable insights into the involvement of ferroptosis in sepsis, laying the groundwork for potential therapeutic strategies targeting this cell death pathway to enhance sepsis management.

Single-cell RNA sequencing in ovarian cancer: revealing new perspectives in the tumor microenvironment.

Single-cell sequencing technology has emerged as a pivotal tool for unraveling the complexities of the ovarian tumor microenvironment (TME), which is characterized by its cellular heterogeneity and intricate cell-to-cell interactions. Ovarian cancer (OC), known for its high lethality among gynecologic malignancies, presents significant challenges in treatment and diagnosis, partly due to the complexity of its TME. The application of single-cell sequencing in ovarian cancer research has enabled the detailed characterization of gene expression profiles at the single-cell level, shedding light on the diverse cell populations within the TME, including cancer cells, stromal cells, and immune cells. This high-resolution mapping has been instrumental in understanding the roles of these cells in tumor progression, invasion, metastasis, and drug resistance. By providing insight into the signaling pathways and cell-to-cell communication mechanisms, single-cell sequencing facilitates the identification of novel therapeutic targets and the development of personalized medicine approaches. This review summarizes the advancement and application of single-cell sequencing in studying the stromal components and the broader TME in OC, highlighting its implications for improving diagnosis, treatment strategies, and understanding of the disease's underlying biology.

B Cells Infiltration Potentially Responded Better to Systemic Corticoids in Oral Lichen Planus and Oral Lichenoid Lesions.

Oral lichen planus (OLP) and oral lichenoid lesion (OLL) are chronic inflammatory diseases involving the oral mucosa. B cells infiltration in OLP and OLL, however, little is known about these cells in OLP and OLL. To analyze the function and infiltrating features of B lymphocytes in OLP and OLL, and to preliminarily evaluate their correlation with clinical outcomes. Tissue samples were collected from OLP, OLL, and healthy mucosa. The phenotypes and amounts of B cells in tissues were analyzed by single-cell sequencing. Their proportion and infiltrating features in tissues were examined by immunohistochemistry and immunofluorescence. With the systemic medication of corticoids, the correlation between B cells infiltrating characteristics and the clinical outcomes were evaluated. A quantified proportion increase of B cells was shown in both OLP and OLL. B cells in OLP demonstrated heightened activation and enhanced regulation in immune response. A cohort of 100 patients with OLP/OLL and 13 healthy controls were examined to investigate the B cells infiltration pattern. B cells were distributed in the superficial layer of lamina propria in 92.9% and 41.9% of OLP and OLL, respectively(P < 0.01); focally distributed in 25.0% and 62.9% of OLP and OLL, respectively(P < 0.01). With the systemic medication of corticoids, the cases with B cell infiltration (B+) in OLP and OLL groups showed a statistically significant reduction in REU scores before and after treatment (P < 0.01). B cells are widely present in OLP and OLL, and B cell infiltration in OLP and OLL are related to the better therapeutic effect of oral corticoids.

Definition of a Multi-Omics Signature for Esophageal Adenocarcinoma Prognosis Prediction.

Esophageal cancer is a highly lethal malignancy, representing 5% of all cancer-related deaths. The two main subtypes are esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma (EAC). While most research has focused on ESCC, few studies have analyzed EAC for transcriptional signatures linked to diagnosis or prognosis. In this study, we utilized single-cell RNA sequencing and bulk RNA sequencing to identify specific immune cell types that contribute to anti-tumor responses, as well as differentially expressed genes (DEGs). We have characterized transcriptional signatures, validated against a wide cohort of TCGA patients, that are capable of predicting clinical outcomes and the prognosis of EAC post-surgery with efficacy comparable to the currently accepted prognostic factors. In conclusion, our findings provide insights into the immune landscape and therapeutic targets of EAC, proposing novel immunological biomarkers for predicting prognosis, aiding in patient stratification for post-surgical outcomes, follow-up, and personalized adjuvant therapy decisions.

A comprehensive single-cell RNA transcriptomic analysis identifies a unique SPP1+ macrophages subgroup in aging skeletal muscle.

Senescence of skeletal muscle (SkM) has been a primary contributor to senior weakness and disability in recent years. The gradually declining SkM function associated with senescence has recently been connected to an imbalance between damage and repair. Macrophages (Mac) are involved in SkM aging, and different macrophage subgroups hold different biological functions. Through comprehensive single-cell transcriptomic analysis, we first compared the metabolic pathways and biological functions of different types of cells in young (Y) and old (O) mice SkM. Strikingly, the Mac population in mice SkM was also explored, and we identified a unique Mac subgroup in O SkM characterized by highly expressed SPP1 with strong senescence and adipogenesis features. Further work was carried out on the metabolic and biological processes for these Mac subgroups. Besides, we verified that the proportion of the SPP1+ Mac was increased significantly in the quadriceps tissues of O mice, and the senotherapeutic drug combination dasatinib + quercetin (D + Q) could dramatically reduce its proportion. Our study provides novel insight into the potential role of SPP1+ Mac in SkM, which may serve as a senotherapeutic target in SkM aging.

Highlighting immune features of the tumor ecosystem and prognostic value of Tfh and Th17 cell infiltration in head and neck squamous cell carcinoma by single-cell RNA-seq.

BACKGROUND: Head and neck squamous cell carcinoma (HNSCC) typically present with a complex anatomical distribution, often accompanied by insidious symptoms. This combination contributes to its high incidence and poor prognosis. It is now understood that the immune features of cellular components within the tumor ecosystem and their complex interactions are critical factors influencing both tumor progression and the effective immune response. METHODS: We obtained single-cell RNA sequencing data of 26,496 cells from three tumor tissues and five normal tissues and performed subsequent analyses. Immunohistochemical staining on tumor sections was used to validate the presence of malignant cells. Additionally, we included bulk RNA sequencing data from 502 HNSCC patients. Kaplan-Meier analysis and the log-rank test were employed to assess predictors of patient outcomes. RESULTS: We identified three epithelial subclusters exhibiting immune-related features. These subclusters promoted the infiltration of T cells, dendritic cells, and monocytes into the tumor microenvironment. Additionally, cancer-associated fibroblasts displayed tumor-promoting and angiogenesis characteristics, contrasting with the predominant antigen-presenting and inflammatory roles observed in fibroblasts from normal tissues. Furthermore, tumor endothelial subsets exhibited a double-sided effect, promoting tumor progression and enhancing the effectiveness of immune response. Finally, follicular helper T cells and T helper 17 cells were found to be significantly correlated with improved outcomes in HNSCC patients. These CD4+ T cell subpopulations could promote the anti-tumor immune response by recruiting and activating B and T cells. CONCLUSION: Our findings provide deeper insights into the immune features of the tumor ecosystem and reveal the prognostic significance of follicular helper T cells and T helper 17 cells. These findings may pave the way for the development of therapeutic approaches.

Single-cell analysis of the survival mechanisms of fratricidal CAR-T targeting of T cell malignancies.

Chimeric antigen receptor T (CAR-T) cell therapy targeting T cell tumors still faces many challenges, one of which is its fratricide due to the target gene expressed on CAR-T cells. Despite this, these CAR-T cells can be expanded in vitro by extending the culture time and effectively eliminating malignant T cells. However, the mechanisms underlying CAR-T cell survival in cell subpopulations, the molecules involved, and their regulation are still unknown. We performed single-cell transcriptome profiling to investigate the fratricidal CAR-T products (CD26 CAR-Ts and CD44v6 CAR-Ts) targeting T cells, taking CD19 CAR-Ts targeting B cells from the same donor as a control. Compared with CD19 CAR-Ts, fratricidal CAR-T cells exhibit no unique cell subpopulation, but have more exhausted T cells, fewer cytotoxic T cells, and more T cell receptor (TCR) clonal amplification. Furthermore, we observed that fratricidal CAR-T cell survival was accompanied by target gene expression. Gene expression results suggest that fratricidal CAR-T cells may downregulate their human leukocyte antigen (HLA) molecules to evade T cell recognition. Single-cell regulatory network analysis and suppression experiments revealed that exhaustion mediated by critical regulatory factors may contribute to fratricidal CAR-T cell survival. Together, these data provide valuable and first-time insights into the survival of fratricidal CAR-T cells.

Single-cell sequencing unveils the impact of aging on the progenitor cell diversity in the telencephalon of the female killifish N. furzeri.

The African turquoise killifish (Nothobranchius furzeri) combines a short lifespan with spontaneous age-associated loss of neuro-regenerative capacity, an intriguing trait atypical for a teleost. The impact of aging on the cellular composition of the adult stem cell niches, leading to this dramatic decline in the postnatal neuro- and gliogenesis, remains elusive. Single-cell RNA sequencing of the telencephalon of young adult female killifish of the short-lived GRZ-AD strain unveiled progenitors of glial and non-glial nature, different excitatory and inhibitory neuron subtypes, as well as non-neural cell types. Sub-clustering of the progenitors identified four radial glia (RG) cell types, two non-glial progenitor (NGP) and four intermediate (intercell) cell states. Two astroglia-like, one ependymal, and one neuroepithelial-like (NE) RG subtype were found at different locations in the forebrain in line with their role, while proliferative, active NGPs were spread throughout. Lineage inference pointed to NE-RG and NGPs as start and intercessor populations for glio- and neurogenesis. Upon aging, single-cell RNA sequencing revealed major perturbations in the proportions of the astroglia and intercell states, and in the molecular signatures of specific subtypes, including altered MAPK, mTOR, Notch, and Wnt pathways. This cell catalog of the young regeneration-competent killifish telencephalon, combined with the evidence for aging-related transcriptomic changes, presents a useful resource to understand the molecular basis of age-dependent neuroplasticity. This data is also available through an online database (killifishbrain_scseq).

Gut Microbiota Disorder Contributes to the Production of IL-17A That Exerts Chemotaxis via Binding to IL-17RA in Endometriosis.

Introduction: Endometriosis (EM) is a chronic estrogen-dependent condition characterized by the growth of endometrial-like tissue outside the uterus, posing a significant burden on reproductive-aged women. Previous research has shown a correlation between gut microbiota dysbiosis and interleukin-17A (IL-17A) in EM patients. IL-17A, a promising immunomodulatory molecule, exerts dual roles in human physiology, driving inflammatory diseases. However, the functions and origins of IL-17A in EM remain poorly characterized. Methods: Single-cell data analysis was employed to characterize IL-17A activity in EM lesions. Fecal microbiota transplantation was conducted to explore the impact of gut microbiota on EM. Gut microbiota and bile acid metabolism were assessed via 16S rRNA sequencing and targeted metabolomics. Th17 cell proportions were measured using flow cytometry. Results: High expression of IL-17 receptor A (IL-17RA) was observed in myeloid cell subpopulations within EM lesions and may be involved in the migration and recruitment of inflammatory cells in lesions. Elevated IL-17A levels were further validated in peritoneal and follicular fluids of EM patients. Dysregulated bile acid levels, particularly elevated chenodeoxycholic acid (CDCA) and ursodeoxycholic acid (UDCA), were found in the gut and peritoneal fluid of EM mouse models. Additional CDCA administration reduced EM lesions and modulated Th17 cell proportions, while UDCA showed no significant effects. Discussion: Our findings shed light on the origins and functions of IL-17A in EM, implicating its involvement in lesion migration and recruitment. Dysregulated bile acid metabolism may contribute to EM pathogenesis, with CDCA exhibiting therapeutic potential.