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The complex pathology of mild traumatic brain injury (mTBI) is a main contributor to the difficulties in achieving a successful therapeutic regimen. Thyroxine (T4) administration has been shown to prevent the cognitive impairments induced by mTBI in mice but the mechanism is poorly understood. To understand the underlying mechanism, we carried out a single cell transcriptomic study to investigate the spatiotemporal effects of T4 on individual cell types in the hippocampus and frontal cortex at three post-injury stages in a mouse model of mTBI. We found that T4 treatment altered the proportions and transcriptomes of numerous cell types across tissues and timepoints, particularly oligodendrocytes, astrocytes, and microglia, which are crucial for injury repair. T4 also reversed the expression of mTBI-affected genes such as Ttr, mt-Rnr2, Ggn12, Malat1, Gnaq, and Myo3a, as well as numerous pathways such as cell/energy/iron metabolism, immune response, nervous system, and cytoskeleton-related pathways. Cell-type specific network modeling revealed that T4 mitigated select mTBI-perturbed dynamic shifts in subnetworks related to cell cycle, stress response, and RNA processing in oligodendrocytes. Cross cell-type ligand-receptor networks revealed the roles of App, Hmgb1, Fn1, and Tnf in mTBI, with the latter two ligands having been previously identified as TBI network hubs. mTBI and/or T4 signature genes were enriched for human genome-wide association study (GWAS) candidate genes for cognitive, psychiatric and neurodegenerative disorders related to mTBI. Our systems-level single cell analysis elucidated the temporal and spatial dynamic reprogramming of cell-type specific genes, pathways, and networks, as well as cell-cell communications as the mechanisms through which T4 mitigates cognitive dysfunction induced by mTBI.

BACKGROUND: Acute lung allograft dysfunction (ALAD) is an imprecise syndrome denoting concern for the onset of chronic lung allograft dysfunction (CLAD). Mechanistic biomarkers are needed that stratify risk of ALAD progression to CLAD. We hypothesized that single cell investigation of bronchoalveolar lavage (BAL) cells at the time of ALAD would identify immune cells linked to progressive graft dysfunction. METHODS: We prospectively collected BAL from consenting lung transplant recipients for single cell RNA sequencing. ALAD was defined by a ≥10% decrease in FEV1 not caused by infection or acute rejection and samples were matched to BAL from recipients with stable lung function. We examined cell compositional and transcriptional differences across control, ALAD with decline, and ALAD with recovery groups. We also assessed cell-cell communication. RESULTS: BAL was assessed for 17 ALAD cases with subsequent decline (ALAD declined), 13 ALAD cases that resolved (ALAD recovered), and 15 cases with stable lung function. We observed broad differences in frequencies of the 26 unique cell populations across groups (p = 0.02). A CD8 T cell (p = 0.04) and a macrophage cluster (p = 0.01) best identified ALAD declined from the ALAD recovered and stable groups. This macrophage cluster was distinguished by an anti-inflammatory signature and the CD8 T cell cluster resembled a Tissue Resident Memory subset. Anti-inflammatory macrophages signaled to activated CD8 T cells via class I HLA, fibronectin, and galectin pathways (p

BackgroundMany approaches have been developed to overcome technical noise in single cell RNA-sequencing (scRNAseq). As researchers dig deeper into data-looking for rare cell types, subtleties of cell states, and details of gene regulatory networks-there is a growing need for algorithms with controllable accuracy and fewer ad hoc parameters and thresholds. Impeding this goal is the fact that an appropriate null distribution for scRNAseq cannot simply be extracted from data in which ground truth about biological variation is unknown (i.e., usually).ResultsWe approach this problem analytically, assuming that scRNAseq data reflect only cell heterogeneity (what we seek to characterize), transcriptional noise (temporal fluctuations randomly distributed across cells), and sampling error (i.e., Poisson noise). We analyze scRNAseq data without normalization-a step that skews distributions, particularly for sparse data-and calculate p values associated with key statistics. We develop an improved method for selecting features for cell clustering and identifying gene-gene correlations, both positive and negative. Using simulated data, we show that this method, which we call BigSur (Basic Informatics and Gene Statistics from Unnormalized Reads), captures even weak yet significant correlation structures in scRNAseq data. Applying BigSur to data from a clonal human melanoma cell line, we identify thousands of correlations that, when clustered without supervision into gene communities, align with known cellular components and biological processes, and highlight potentially novel cell biological relationships.ConclusionsNew insights into functionally relevant gene regulatory networks can be obtained using a statistically grounded approach to the identification of gene-gene correlations.

In developed economies, the growing number of older individuals is a pressing issue. As a result, research progress into ageing has emphasized the significance of staying healthy in one's later years. Stem cells have a fundamental role to play in fostering diverse cell types and necessary processes for tissue repair and regeneration. Stem cells experience the effects of ageing over time, which is caused by their functional deterioration. Changes to stem cells, their niches and signals from other tissues they interact with are crucial factors in the ageing of stem cells. Progress in single-cell RNA sequencing (scRNA-seq) technology has greatly advanced stem cell research. This review examines the mechanisms of stem cell ageing, its impact on health and investigates the potential of stem cell therapy, with a special emphasis on the skin. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: Clear cell renal cell carcinoma (ccRCC) poses substantial treatment challenges, especially in advanced stages where the efficacy of immune checkpoint blockade (ICB) therapy varies significantly. Elevated expression of the oncogene TUBA1C has been correlated with poor prognosis in various cancers, however, its role in ccRCC is unclear, especially concerning ICB resistance. Methods: Single-cell analysis was used to examine gene expression variations in malignant cells post-ICB therapy. This included investigating TUBA1C expression across different ICB response groups and its relationship with CD274. A general module of action was identified through pan-cancer and pan-tissue analysis. TUBA1C expression and its association with clinical characteristics and prognosis was further validated. Multiple algorithms were employed to explore immune cell infiltration levels, and the DepMap database was utilized to assess gene dependency and mutation status in kidney cancer cell lines. The in silico knockout of TUBA1C was performed using deep learning model, complemented by immunohistochemical assays, clinical cohort and functional assays validations. Results: TUBA1C expression is elevated in malignant cells following ICB therapy and is correlated with ICB resistance in ccRCC. High TUBA1C expression activates PI3K/AKT pathway and is associated with increased infiltration of regulatory T cells and myeloid-derived suppressor cells, which contributes to an immunosuppressive microenvironment in ccRCC. Patients with high TUBA1C expression exhibit a greater tumor mutation burden and increased genetic variation, which causes a worse prognosis. Additionally, TUBA1C dependency and its effects were evident in kidney cancer cell lines, where mutations conferred resistance to anti-PD-L1 therapy. In silico knockout analyses indicated that treatment targeting TUBA1C shifted malignant cells to a state responsive to ICB therapy. Immunohistochemistry, RT-qPCR and clinical cohort validation further confirmed that TUBA1C expression was upregulated and contributed to poorer outcome in ccRCC. Finaly, wound healing and CCK-8 assays demonstrated the potent oncogenic function of TUBA1C. Conclusions: TUBA1C is a pivotal regulator in ccRCC, affecting both disease progression and the effectiveness of ICB therapy by fostering an immunosuppressive microenvironment mediated by the PI3K/AKT pathway. Additionally, TUBA1C holds promise, both as a prognostic biomarker and a therapeutic target, for enhancing responsiveness to ICB. [ABSTRACT FROM AUTHOR]

Traumatic spinal cord injury (tSCI) is a severe injury to the central nervous system that is categorized into primary and secondary injuries. Among them, the local microenvironmental imbalance in the spinal cord caused by secondary spinal cord injury includes accumulation of cytokines and chemokines, reduced angiogenesis, dysregulation of cellular energy metabolism, and dysfunction of immune cells at the site of injury, which severely impedes neurological recovery from spinal cord injury (SCI). In recent years, single-cell techniques have revealed the heterogeneity of multiple immune cells at the genomic, transcriptomic, proteomic, and metabolomic levels after tSCI, further deepening our understanding of the mechanisms underlying tSCI. However, spatial information about the tSCI microenvironment, such as cell location and cell cell interactions, is lost in these approaches. The application of spatial multiomics technology can solve this problem by combining the data obtained from immunohistochemistry and multiparametric analysis to reveal the changes in the microenvironment at different times of secondary injury after SCI. In this review, we systematically review the progress of spatial multi-omics techniques in the study of the microenvironment after SCI, including changes in the immune microenvironment and discuss potential future therapeutic strategies. [ABSTRACT FROM AUTHOR]

Background: Inflammatory Bowel Diseases (IBDs), encompassing Ulcerative Colitis (UC) and Crohn's Disease (CD), are chronic, recurrent inflammatory conditions of the gastrointestinal tract. The microRNA (miRNA) -mRNA regulatory network is pivotal in the initiation and progression of IBDs. Although individual studies provide valuable insights into miRNA mechanisms in IBDs, they often have limited scope due to constraints in population diversity, sample size, sequencing platform variability, batch effects, and potential researcher bias. Our study aimed to construct comprehensive miRNA-mRNA regulatory networks and determine the cellular sources and functions of key miRNAs in IBD pathogenesis. Methods: To minimize potential bias from individual studies, we utilized a text mining-based approach on published scientific literature from PubMed and PMC databases to identify miRNAs and mRNAs associated with IBDs and their subtypes. We constructed miRNA-mRNA regulatory networks by integrating both predicted and experimentally validated results from DIANA, Targetscan, PicTar, Miranda, miRDB, and miRTarBase (all of which are databases for miRNA target annotation). The functions of miRNAs were determined through gene enrichment analysis of their target mRNAs. Additionally, we used two large-scale single-cell RNA sequencing datasets to identify the cellular sources of miRNAs and the association of their expression levels with clinical status, molecular and functional alternation in CD and UC. Results: Our analysis systematically summarized IBD-related genes using textmining methodologies. We constructed three comprehensive miRNA-mRNA regulatory networks specific to IBD, CD, and UC. Through cross-analysis with two large-scale scRNA-seq datasets, we determined the cellular sources of the identified miRNAs. Despite originating from different cell types, hsa-miR-142, hsa-miR-145, and hsa-miR-146a were common to both CD and UC. Notably, hsa-miR-145 was identified as myofibroblast-specific in both CD and UC. Furthermore, we found that higher tissue repair and enhanced glucose and lipid metabolism were associated with hsa-miR-145 in myofibroblasts in both CD and UC contexts. Conclusion: This comprehensive approach revealed common and distinct miRNA-mRNA regulatory networks in CD and UC, identified cell-specific miRNA expressions (notably hsa-miR-145 in myofibroblasts), and linked miRNA expression to functional alterations in IBD. These findings not only enhance our understanding of IBD pathogenesis but also offer promising diagnostic biomarkers and therapeutic targets for clinical practice in managing IBDs. [ABSTRACT FROM AUTHOR]

The dorsal aorta (DA) is the first major blood vessel to develop in the embryonic cardiovascular system. Its formation is governed by a coordinated process involving the migration, specification, and arrangement of angioblasts into arterial and venous lineages, a process conserved across species. Although vascular endothelial growth factor a (VEGF-A) is known to drive DA specification and formation, the kinases involved in this process remain ambiguous. Thus, we investigated the role of protein kinase B (Akt) in zebrafish by generating a quadruple mutant (aktΔ/Δ), in which expression and activity of all Akt genes – akt1, -2, -3a and -3b – are strongly decreased. Live imaging of developing aktΔ/Δ DA uncovers early arteriovenous malformations. Single-cell RNA-sequencing analysis of aktΔ/Δ endothelial cells corroborates the impairment of arterial, yet not venous, cell specification. Notably, endothelial specific expression of ligand-independent activation of Notch or constitutively active Akt1 were sufficient to re-establish normal arterial specification in aktΔ/Δ. The Akt loss-of-function mutant unveils that Akt kinase can act upstream of Notch in arterial endothelial cells, and is involved in proper embryonic artery specification. This sheds light on cardiovascular development, revealing a mechanism behind congenital malformations. [ABSTRACT FROM AUTHOR]

Abstract Background Many approaches have been developed to overcome technical noise in single cell RNA-sequencing (scRNAseq). As researchers dig deeper into data—looking for rare cell types, subtleties of cell states, and details of gene regulatory networks—there is a growing need for algorithms with controllable accuracy and fewer ad hoc parameters and thresholds. Impeding this goal is the fact that an appropriate null distribution for scRNAseq cannot simply be extracted from data in which ground truth about biological variation is unknown (i.e., usually). Results We approach this problem analytically, assuming that scRNAseq data reflect only cell heterogeneity (what we seek to characterize), transcriptional noise (temporal fluctuations randomly distributed across cells), and sampling error (i.e., Poisson noise). We analyze scRNAseq data without normalization—a step that skews distributions, particularly for sparse data—and calculate p values associated with key statistics. We develop an improved method for selecting features for cell clustering and identifying gene–gene correlations, both positive and negative. Using simulated data, we show that this method, which we call BigSur (Basic Informatics and Gene Statistics from Unnormalized Reads), captures even weak yet significant correlation structures in scRNAseq data. Applying BigSur to data from a clonal human melanoma cell line, we identify thousands of correlations that, when clustered without supervision into gene communities, align with known cellular components and biological processes, and highlight potentially novel cell biological relationships. Conclusions New insights into functionally relevant gene regulatory networks can be obtained using a statistically grounded approach to the identification of gene–gene correlations.

With the emergence of advanced spatial transcriptomic technologies, there has been a surge in research papers dedicated to analyzing spatial transcriptomics data, resulting in significant contributions to our understanding of biology. The initial stage of downstream analysis of spatial transcriptomic data has centered on identifying spatially variable genes (SVGs) or genes expressed with specific spatial patterns across the tissue. SVG detection is an important task since many downstream analyses depend on these selected SVGs. Over the past few years, a plethora of new methods have been proposed for the detection of SVGs, accompanied by numerous innovative concepts and discussions. This article provides a selective review of methods and their practical implementations, offering valuable insights into the current literature in this field.

Abstract Background At 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. Methods This 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. Results The 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. Conclusion The 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.

Abstract Cuproptosis is a novel type to regulate cell death with copper-dependent manner, and has been reported to involve in the occurrence and development of various malignant tumors. However, the association between cuproptosis and the tumor microenvironment (TME) of clear cell renal cell carcinoma (ccRCC) remained unclear. To address this question, we integrated the single cell RNA sequencing (scRNA-seq) datasets of ccRCC across different stages, systematically examined the distinctive expression patterns of cuproptosis-related genes (CRGs) within the TME of ccRCC, and explored the crucial signatures using the spatial transcriptome sequencing (ST-seq) dataset. The cuproptosis activities reduced in cancer tissues along with the ccRCC development, and recovered after therapy. We identified HILPDA+ ccRCC1 subtype, characterized with hypoxia, as cuproptosis susceptible cells associated with a better prognosis. The main co-expression modules of HILPDA+ ccRCC1 subtype highlighted the role in anion transport, response to oxygen species and PD-L1-PD-1 pathway. Furthermore, the immunosuppressive cells might interact with HILPDA+ ccRCC1 subtype via HAVCR2-LGALS9, C3-C3AR1, HLA-A-CD8B and HLA-C-CD8A axises to shape the cuproptosis-related TME landscape. In summary, we anticipate that this study will offer valuable insights and potential strategies of cuproptosis for therapy of ccRCC. Graphical Abstract

Abstract Background Metabolite-associated cell communications play critical roles in maintaining human biological function. However, most existing tools and resources focus only on ligand-receptor interaction pairs where both partners are proteinaceous, neglecting other non-protein molecules. To address this gap, we introduce the MRCLinkdb database and algorithm, which aggregates and organizes data related to non-protein L-R interactions in cell-cell communication, providing a valuable resource for predicting intercellular communication based on metabolite-related ligand-receptor interactions. Results Here, we manually curated the metabolite-ligand-receptor (ML-R) interactions from the literature and known databases, ultimately collecting over 790 human and 670 mouse ML-R interactions. Additionally, we compiled information on over 1900 enzymes and 260 transporter entries associated with these metabolites. We developed Metabolite-Receptor based Cell Link Database (MRCLinkdb) to store these ML-R interactions data. Meanwhile, the platform also offers extensive information for presenting ML-R interactions, including fundamental metabolite information and the overall expression landscape of metabolite-associated gene sets (such as receptor, enzymes, and transporter proteins) based on single-cell transcriptomics sequencing (covering 35 human and 26 mouse tissues, 52 human and 44 mouse cell types) and bulk RNA-seq/microarray data (encompassing 62 human and 39 mouse tissues). Furthermore, MRCLinkdb introduces a web server dedicated to the analysis of intercellular communication based on ML-R interactions. MRCLinkdb is freely available at https://www.cellknowledge.com.cn/mrclinkdb/ . Conclusions In addition to supplementing ligand-receptor databases, MRCLinkdb may provide new perspectives for decoding the intercellular communication and advancing related prediction tools based on ML-R interactions.

Abstract Background Neutrophils play an essential role in Alzheimer’s disease (AD) pathology. However, the extent of their heterogeneity remains poorly explored, particularly in the context of developing novel therapies targeting these cells. Results We investigate the population structure of neutrophils purified from peripheral blood samples of AD mice. Utilizing single cell RNA sequencing, we comprehensively map neutrophil populations into six distinct clusters and find that the Neu-5 subset is specially enriched in AD mice. This subset exhibits fewer specific granules and a lower mature score. Gene ontology (GO) analysis reveals that genes involved in cytokine-mediated signaling are downregulated in the Neu-5 cluster. Furthermore, we identify the Ccrl2 gene is specifically upregulated in this subgroup, which is confirmed by flow cytometry in AD mice. Finally, immunohistochemical staining indicates that CCRL2 protein is increased in the brains of AD mice. Conclusions We identify a unique CCRL2 positive neutrophil cluster, that is specifically enriched in the peripheral blood of AD mice.

Background: At 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. Methods: This 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. Results: The 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. Conclusion: The 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. [ABSTRACT FROM AUTHOR]

Background: Chronic thromboembolic pulmonary hypertension (CTEPH) is a serious pulmonary vascular disease characterized by residual thrombi in the pulmonary arteries and distal pulmonary microvascular remodeling. The pathogenesis of CTEPH remains unclear, but many factors such as inflammation, immunity, coagulation and angiogenesis may be involved. Monocytes are important immune cells that can differentiate into macrophages and dendritic cells and play an important role in thrombus formation. However, the distribution, gene expression profile and differentiation trajectory of monocyte subsets in CTEPH patients have not been systematically studied. This study aims to reveal the characteristics and functions of monocytes in CTEPH patients using single-cell sequencing technology, and to provide new insights for the diagnosis and treatment of CTEPH. Methods: Single-cell RNA sequencing (scRNA-seq) were performed to analyze the transcriptomic features of peripheral blood mononuclear cells (PBMCs) from healthy controls, CTEPH patients and the tissues from CTEPH patients after the pulmonary endarterectomy (PEA). We established a CTEPH rat model with chronic pulmonary embolism caused by repeated injection of autologous thrombi through a central venous catheter, and used flow cytometry to detect the proportion changes of monocyte subsets in CTEPH patients and CTEPH rat model. We also observed the infiltration degree of macrophage subsets in thrombus tissue and their differentiation relationship with peripheral blood monocyte subsets by immunofluorescence staining. Results: The results showed that the monocyte subsets in peripheral blood of CTEPH patients changed significantly, especially the proportion of CD16+ monocyte subset increased. This monocyte subset had unique functional features at the transcriptomic level, involving processes such as cell adhesion, T cell activation, coagulation response and platelet activation, which may play an important role in pulmonary artery thrombus formation and pulmonary artery intimal remodeling. In addition, we also found that the macrophage subsets in pulmonary endarterectomy tissue of CTEPH patients showed pro-inflammatory and lipid metabolism reprogramming features, which may be related to the persistence and insolubility of pulmonary artery thrombi and the development of pulmonary hypertension. Finally, we also observed that CD16+ monocyte subset in peripheral blood of CTEPH patients may be recruited to pulmonary artery intimal tissue and differentiate into macrophage subset with high expression of IL-1β, participating in disease progression. Conclusion: CD16+ monocytes subset had significant gene expression changes in CTEPH patients, related to platelet activation, coagulation response and inflammatory response. And we also found that these cells could migrate to the thrombus and differentiate into macrophages with high expression of IL-1b involved in CTEPH disease progression. We believe that CD16+ monocytes are important participants in CTEPH and potential therapeutic targets. [ABSTRACT FROM AUTHOR]

Idiopathic subglottic stenosis (ISGS) is a rare fibrotic disease of the upper trachea with an unknown pathomechanism. It typically affects adult Caucasian female patients, leading to severe airway constrictions caused by progressive scar formation and inflammation with clinical symptoms of dyspnoea, stridor and potential changes to the voice. Endoscopic treatment frequently leads to recurrence, whereas surgical resection and reconstruction provides excellent long-term functional outcome. This study aimed to identify so far unrecognized pathologic aspects of ISGS using single cell RNA sequencing. Our scRNAseq analysis uncovered the cellular composition of the subglottic scar tissue, including the presence of a pathologic, profibrotic fibroblast subtype and the presence of Schwann cells in a profibrotic state. In addition, a pathology associated increase of plasma cells was identified. Using extended bioinformatics analyses, we decoded pathology-associated changes of factors of the extracellular matrix. Our data identified ongoing fibrotic processes in ISGS and provide novel insights on the contribution of fibroblasts, Schwann cells and plasma cells to the pathogenesis of ISGS. This knowledge could impact the development of novel approaches for diagnosis and therapy of ISGS. [ABSTRACT FROM AUTHOR]

Background: Duchenne muscular dystrophy is a genetic disease produced by mutations in the dystrophin gene characterized by early onset muscle weakness leading to severe and irreversible disability. Muscle degeneration involves a complex interplay between multiple cell lineages spatially located within areas of damage, termed the degenerative niche, including inflammatory cells, satellite cells (SCs) and fibro-adipogenic precursor cells (FAPs). FAPs are mesenchymal stem cell which have a pivotal role in muscle homeostasis as they can either promote muscle regeneration or contribute to muscle degeneration by expanding fibrotic and fatty tissue. Although it has been described that FAPs could have a different behavior in DMD patients than in healthy controls, the molecular pathways regulating their function as well as their gene expression profile are unknown. Methods: We used single-cell RNA sequencing (scRNAseq) with 10X Genomics and Illumina technology to elucidate the differences in the transcriptional profile of isolated FAPs from healthy and DMD patients. Results: Gene signatures in FAPs from both groups revealed transcriptional differences. Seurat analysis categorized cell clusters as proliferative FAPs, regulatory FAPs, inflammatory FAPs, and myofibroblasts. Differentially expressed genes (DEGs) between healthy and DMD FAPs included upregulated genes CHI3L1, EFEMP1, MFAP5, and TGFBR2 in DMD. Functional analysis highlighted distinctions in system development, wound healing, and cytoskeletal organization in control FAPs, while extracellular organization, degradation, and collagen degradation were upregulated in DMD FAPs. Validation of DEGs in additional samples (n = 9) using qPCR reinforced the specific impact of pathological settings on FAP heterogeneity, reflecting their distinct contribution to fibro or fatty degeneration in vivo. Conclusion: Using the single-cell RNA seq from human samples provide new opportunities to study cellular coordination to further understand the regulation of muscle homeostasis and degeneration that occurs in muscular dystrophies. [ABSTRACT FROM AUTHOR]

Background: Metabolite-associated cell communications play critical roles in maintaining human biological function. However, most existing tools and resources focus only on ligand-receptor interaction pairs where both partners are proteinaceous, neglecting other non-protein molecules. To address this gap, we introduce the MRCLinkdb database and algorithm, which aggregates and organizes data related to non-protein L-R interactions in cell-cell communication, providing a valuable resource for predicting intercellular communication based on metabolite-related ligand-receptor interactions. Results: Here, we manually curated the metabolite-ligand-receptor (ML-R) interactions from the literature and known databases, ultimately collecting over 790 human and 670 mouse ML-R interactions. Additionally, we compiled information on over 1900 enzymes and 260 transporter entries associated with these metabolites. We developed Metabolite-Receptor based Cell Link Database (MRCLinkdb) to store these ML-R interactions data. Meanwhile, the platform also offers extensive information for presenting ML-R interactions, including fundamental metabolite information and the overall expression landscape of metabolite-associated gene sets (such as receptor, enzymes, and transporter proteins) based on single-cell transcriptomics sequencing (covering 35 human and 26 mouse tissues, 52 human and 44 mouse cell types) and bulk RNA-seq/microarray data (encompassing 62 human and 39 mouse tissues). Furthermore, MRCLinkdb introduces a web server dedicated to the analysis of intercellular communication based on ML-R interactions. MRCLinkdb is freely available at . Conclusions: In addition to supplementing ligand-receptor databases, MRCLinkdb may provide new perspectives for decoding the intercellular communication and advancing related prediction tools based on ML-R interactions. [ABSTRACT FROM AUTHOR]

Acute lung allograft dysfunction (ALAD) is an imprecise syndrome denoting concern for the onset of chronic lung allograft dysfunction (CLAD). Mechanistic biomarkers are needed that stratify risk of ALAD progression to CLAD. We hypothesized that single cell investigation of bronchoalveolar lavage (BAL) cells at the time of ALAD would identify immune cells linked to progressive graft dysfunction. We prospectively collected BAL from consenting lung transplant recipients for single cell RNA sequencing. ALAD was defined by a ≥10% decrease in FEV 1 not caused by infection or acute rejection and samples were matched to BAL from recipients with stable lung function. We examined cell compositional and transcriptional differences across control, ALAD with decline, and ALAD with recovery groups. We also assessed cell-cell communication. BAL was assessed for 17 ALAD cases with subsequent decline (ALAD declined), 13 ALAD cases that resolved (ALAD recovered), and 15 cases with stable lung function. We observed broad differences in frequencies of the 26 unique cell populations across groups (p = 0.02). A CD8 T cell (p = 0.04) and a macrophage cluster (p = 0.01) best identified ALAD declined from the ALAD recovered and stable groups. This macrophage cluster was distinguished by an anti-inflammatory signature and the CD8 T cell cluster resembled a Tissue Resident Memory subset. Anti-inflammatory macrophages signaled to activated CD8 T cells via class I HLA, fibronectin, and galectin pathways (p < 0.05 for each). Recipients with discordance between these cells had a nearly 5-fold increased risk of severe graft dysfunction or death (HR 4.6, 95% CI 1.1–19.2, adjusted p = 0.03). We validated these key findings in 2 public lung transplant genomic datasets. BAL anti-inflammatory macrophages may protect against CLAD by suppressing CD8 T cells. These populations merit functional and longitudinal assessment in additional cohorts. [ABSTRACT FROM AUTHOR]

• Increasing body adiposity by diet lowers cerebral cortex volume in mice. • Higher body adiposity associates with lower cortical volume in humans. • Microglia and excitatory neurons are dysregulated in the obese mouse cortex. • Neuron-adverse dysregulation is dominated by reduced neuritogenesis and signalling. • Microglial changes in gene expression are similar in obese mice and Alzheimer's disease. Obesity is a major modifiable risk factor for Alzheimer's disease (AD), characterized by progressive atrophy of the cerebral cortex. The neurobiology of obesity contributions to AD is poorly understood. Here we show with in vivo MRI that diet-induced obesity decreases cortical volume in mice, and that higher body adiposity associates with lower cortical volume in humans. Single-nuclei transcriptomics of the mouse cortex reveals that dietary obesity promotes an array of neuron-adverse transcriptional dysregulations, which are mediated by an interplay of excitatory neurons and glial cells, and which involve microglial activation and lowered neuronal capacity for neuritogenesis and maintenance of membrane potential. The transcriptional dysregulations of microglia, more than of other cell types, are like those in AD, as assessed with single-nuclei cortical transcriptomics in a mouse model of AD and two sets of human donors with the disease. Serial two-photon tomography of microglia demonstrates microgliosis throughout the mouse cortex. The spatial pattern of adiposity-cortical volume associations in human cohorts interrogated together with in silico bulk and single-nucleus transcriptomic data from the human cortex implicated microglia (along with other glial cells and subtypes of excitatory neurons), and it correlated positively with the spatial profile of cortical atrophy in patients with mild cognitive impairment and AD. Thus, multi-cell neuron-adverse dysregulations likely contribute to the loss of cortical tissue in obesity. The dysregulations of microglia may be pivotal to the obesity-related risk of AD. [ABSTRACT FROM AUTHOR]

Background: Neutrophils play an essential role in Alzheimer's disease (AD) pathology. However, the extent of their heterogeneity remains poorly explored, particularly in the context of developing novel therapies targeting these cells. Results: We investigate the population structure of neutrophils purified from peripheral blood samples of AD mice. Utilizing single cell RNA sequencing, we comprehensively map neutrophil populations into six distinct clusters and find that the Neu-5 subset is specially enriched in AD mice. This subset exhibits fewer specific granules and a lower mature score. Gene ontology (GO) analysis reveals that genes involved in cytokine-mediated signaling are downregulated in the Neu-5 cluster. Furthermore, we identify the Ccrl2 gene is specifically upregulated in this subgroup, which is confirmed by flow cytometry in AD mice. Finally, immunohistochemical staining indicates that CCRL2 protein is increased in the brains of AD mice. Conclusions: We identify a unique CCRL2 positive neutrophil cluster, that is specifically enriched in the peripheral blood of AD mice. [ABSTRACT FROM AUTHOR]

BackgroundsGastric cancer (GC) remains a global health threat due to frequent treatment failures caused by primary or acquired resistance. Although cancer-associated fibroblasts (CAFs) have been implicated in this process, it is still unclear which specific subtype(s) of CAFs hinder T-cell infiltration and promote resistance to immunotherapy.MethodsWe analyzed the GC fibroblast atlas in detail by combining 63,955 single cells from 14 scRNA-seq datasets. We also performed RNA-seq data in a local GC cohort and examined 13 bulk RNA-seq datasets to understand the biological and clinical roles of different CAF subsets. Additionally, we conducted in vitro experiments to study the role of specific proteins in GC development.ResultsWe identified a total of 17 fibroblast subsets in gastric cancer, nine of which did not fit into the existing CAFs classification. These subsets exhibited significant heterogeneity in distribution and biological characteristics (metabolism, cell-cell interactions, differentiation state), as well as clinical functions such as prognosis and response to immunotherapy. In particular, cluster 6 stood out for its high expression of MFAP5, CFD, and PI16; it was found to be negatively associated with both overall survival and response to immunotherapy in GC. This association was linked to an immunosuppressive microenvironment characterized by an increase in M2 macrophages but higher levels of T cell dysfunction and exclusion—a feature shared by tumors expressing MFAP5. Furthermore, the addition of human recombinant MFAP5 promoted proliferation and migration of HGC-27 cells by inducing the MFAP5/NOTCH1/HEY1 signaling pathway.ConclusionWe introduce a high-resolution GC fibroblast atlas. The 17 identified fibroblast clusters provide valuable opportunities for gaining deeper biological insights into the relationship between fibroblasts and GC development. Particularly, cluster 6 and its specific marker MFAP5 could serve as prognostic factors in GC and form a foundation for personalized therapeutic combinations to address primary resistance to ICIs.

Neuropathic pain is characterised by periodic or continuous hyperalgesia, numbness, or allodynia, and results from insults to the somatosensory nervous system. Peripheral nerve injury induces transcriptional reprogramming in peripheral sensory neurons, contributing to increased spinal nociceptive input and the development of neuropathic pain. Effective treatment for neuropathic pain remains an unmet medical need as current therapeutics offer limited effectiveness and have undesirable effects. Understanding transcriptional changes in peripheral nerve injury-induced neuropathy might offer a path for novel analgesics. Our literature search identified 65 papers exploring transcriptomic changes post-peripheral nerve injury, many of which were conducted in animal models. We scrutinize their transcriptional changes data and conduct gene ontology enrichment analysis to reveal their common functional profile. Focusing on genes involved in ‘sensory perception of pain’ (GO:0019233), we identified transcriptional changes for different ion channels, receptors, and neurotransmitters, shedding light on its role in nociception. Examining peripheral sensory neurons subtype-specific transcriptional reprograming and regeneration-associated genes, we delved into downstream regulation of hypersensitivity. Identifying the temporal program of transcription regulatory mechanisms might help develop better therapeutics to target them effectively and selectively, thus preventing the development of neuropathic pain without affecting other physiological functions.

Abstract Background Perihematomal edema (PHE) after post-intracerebral hemorrhage (ICH) has complex pathophysiological mechanisms that are poorly understood. The complicated immune response in the post-ICH brain constitutes a crucial component of PHE pathophysiology. In this study, we aimed to characterize the transcriptional profiles of immune cell populations in human PHE tissue and explore the microscopic differences between different types of immune cells. Methods 9 patients with basal ganglia intracerebral hemorrhage (hematoma volume 50-100 ml) were enrolled in this study. A multi-stage profile was developed, comprising Group1 (n = 3, 0–6 h post-ICH, G1), Group2 (n = 3, 6–24 h post-ICH, G2), and Group3 (n = 3, 24–48 h post-ICH, G3). A minimal quantity of edematous tissue surrounding the hematoma was preserved during hematoma evacuation. Single cell RNA sequencing (scRNA-seq) was used to map immune cell populations within comprehensively resected PHE samples collected from patients at different stages after ICH. Results We established, for the first time, a comprehensive landscape of diverse immune cell populations in human PHE tissue at a single-cell level. Our study identified 12 microglia subsets and 5 neutrophil subsets in human PHE tissue. What’s more, we discovered that the secreted phosphoprotein-1 (SPP1) pathway served as the basis for self-communication between microglia subclusters during the progression of PHE. Additionally, we traced the trajectory branches of different neutrophil subtypes. Finally, we also demonstrated that microglia-produced osteopontin (OPN) could regulate the immune environment in PHE tissue by interacting with CD44-positive cells. Conclusions As a result of our research, we have gained valuable insight into the immune-microenvironment within PHE tissue, which could potentially be used to develop novel treatment modalities for ICH.

Abstract Background Circulating tumor cells (CTCs) hold immense promise for unraveling tumor heterogeneity and understanding treatment resistance. However, conventional methods, especially in cancers like non-small cell lung cancer (NSCLC), often yield low CTC numbers, hindering comprehensive analyses. This study addresses this limitation by employing diagnostic leukapheresis (DLA) to cancer patients, enabling the screening of larger blood volumes. To leverage DLA’s full potential, this study introduces a novel approach for CTC enrichment from DLAs. Methods DLA was applied to six advanced stage NSCLC patients. For an unbiased CTC enrichment, a two-step approach based on negative depletion of hematopoietic cells was used. Single-cell (sc) whole-transcriptome sequencing was performed, and CTCs were identified based on gene signatures and inferred copy number variations. Results Remarkably, this innovative approach led to the identification of unprecedented 3,363 CTC transcriptomes. The extensive heterogeneity among CTCs was unveiled, highlighting distinct phenotypes related to the epithelial-mesenchymal transition (EMT) axis, stemness, immune responsiveness, and metabolism. Comparison with sc transcriptomes from primary NSCLC cells revealed that CTCs encapsulate the heterogeneity of their primary counterparts while maintaining unique CTC-specific phenotypes. Conclusions In conclusion, this study pioneers a transformative method for enriching CTCs from DLA, resulting in a substantial increase in CTC numbers. This allowed the creation of the first-ever single-cell whole transcriptome in-depth characterization of the heterogeneity of over 3,300 NSCLC-CTCs. The findings not only confirm the diagnostic value of CTCs in monitoring tumor heterogeneity but also propose a CTC-specific signature that can be exploited for targeted CTC-directed therapies in the future. This comprehensive approach signifies a major leap forward, positioning CTCs as a key player in advancing our understanding of cancer dynamics and paving the way for tailored therapeutic interventions.

Abstract Background In recent years, Single-cell RNA sequencing (scRNA-seq) is increasingly accessible to researchers of many fields. However, interpreting its data demands proficiency in multiple programming languages and bioinformatic skills, which limited researchers, without such expertise, exploring information from scRNA-seq data. Therefore, there is a tremendous need to develop easy-to-use software, covering all the aspects of scRNA-seq data analysis. Results We proposed a clear analysis framework for scRNA-seq data, which emphasized the fundamental and crucial roles of cell identity annotation, abstracting the analysis process into three stages: upstream analysis, cell annotation and downstream analysis. The framework can equip researchers with a comprehensive understanding of the analysis procedure and facilitate effective data interpretation. Leveraging the developed framework, we engineered Shaoxia, an analysis platform designed to democratize scRNA-seq analysis by accelerating processing through high-performance computing capabilities and offering a user-friendly interface accessible even to wet-lab researchers without programming expertise. Conclusion Shaoxia stands as a powerful and user-friendly open-source software for automated scRNA-seq analysis, offering comprehensive functionality for streamlined functional genomics studies. Shaoxia is freely accessible at http://www.shaoxia.cloud , and its source code is publicly available at https://github.com/WiedenWei/shaoxia .

Abstract Background Single-cell sequencing techniques are revolutionizing every field of biology by providing the ability to measure the abundance of biological molecules at a single-cell resolution. Although single-cell sequencing approaches have been developed for several molecular modalities, single-cell transcriptome sequencing is the most prevalent and widely applied technique. SPLiT-seq (split-pool ligation-based transcriptome sequencing) is one of these single-cell transcriptome techniques that applies a unique combinatorial-barcoding approach by splitting and pooling cells into multi-well plates containing barcodes. This unique approach required the development of dedicated computational tools to preprocess the data and extract the count matrices. Here we compare eight bioinformatic pipelines (alevin-fry splitp, LR-splitpipe, SCSit, splitpipe, splitpipeline, SPLiTseq-demultiplex, STARsolo and zUMI) that have been developed to process SPLiT-seq data. We provide an overview of the tools, their computational performance, functionality and impact on downstream processing of the single-cell data, which vary greatly depending on the tool used. Results We show that STARsolo, splitpipe and alevin-fry splitp can all handle large amount of data within reasonable time. In contrast, the other five pipelines are slow when handling large datasets. When using smaller dataset, cell barcode results are similar with the exception of SPLiTseq-demultiplex and splitpipeline. LR-splitpipe that is originally designed for processing long-read sequencing data is the slowest of all pipelines. Alevin-fry produced different down-stream results that are difficult to interpret. STARsolo functions nearly identical to splitpipe and produce results that are highly similar to each other. However, STARsolo lacks the function to collapse random hexamer reads for which some additional coding is required. Conclusion Our comprehensive comparative analysis aids users in selecting the most suitable analysis tool for efficient SPLiT-seq data processing, while also detailing the specific prerequisites for each of these pipelines. From the available pipelines, we recommend splitpipe or STARSolo for SPLiT-seq data analysis.

Background: Perihematomal edema (PHE) after post-intracerebral hemorrhage (ICH) has complex pathophysiological mechanisms that are poorly understood. The complicated immune response in the post-ICH brain constitutes a crucial component of PHE pathophysiology. In this study, we aimed to characterize the transcriptional profiles of immune cell populations in human PHE tissue and explore the microscopic differences between different types of immune cells. Methods: 9 patients with basal ganglia intracerebral hemorrhage (hematoma volume 50-100 ml) were enrolled in this study. A multi-stage profile was developed, comprising Group1 (n = 3, 0–6 h post-ICH, G1), Group2 (n = 3, 6–24 h post-ICH, G2), and Group3 (n = 3, 24–48 h post-ICH, G3). A minimal quantity of edematous tissue surrounding the hematoma was preserved during hematoma evacuation. Single cell RNA sequencing (scRNA-seq) was used to map immune cell populations within comprehensively resected PHE samples collected from patients at different stages after ICH. Results: We established, for the first time, a comprehensive landscape of diverse immune cell populations in human PHE tissue at a single-cell level. Our study identified 12 microglia subsets and 5 neutrophil subsets in human PHE tissue. What's more, we discovered that the secreted phosphoprotein-1 (SPP1) pathway served as the basis for self-communication between microglia subclusters during the progression of PHE. Additionally, we traced the trajectory branches of different neutrophil subtypes. Finally, we also demonstrated that microglia-produced osteopontin (OPN) could regulate the immune environment in PHE tissue by interacting with CD44-positive cells. Conclusions: As a result of our research, we have gained valuable insight into the immune-microenvironment within PHE tissue, which could potentially be used to develop novel treatment modalities for ICH. [ABSTRACT FROM AUTHOR]

Introduction: Immune cells that contribute to the pathogenesis of systemic lupus erythematosus (SLE) derive from adult hematopoietic stem and progenitor cells (HSPCs) within the bone marrow (BM). For this reason, we reasoned that fundamental abnormalities in SLE can be traced to a BM-derived HSPC inflammatory signature. Methods: BM samples from four SLE patients, six healthy controls, and two umbilical cord blood (CB) samples were used. CD34+ cells were isolated from BM and CB samples, and single-cell RNA-sequencing was performed. Results: A total of 426 cells and 24,473 genes were used in the analysis. Clustering analysis resulted in seven distinct clusters of cell types. Mutually exclusive markers, which were characteristic of each cell type, were identified. We identified three HSPC subpopulations, one of which consisted of proliferating cells (MKI67 expressing cells), one T-like, one B-like, and two myeloid-like progenitor subpopulations. Differential expression analysis revealed i) cell cycle-associated signatures, in healthy BM of HSPC clusters 3 and 4 when compared with CB, and ii) interferon (IFN) signatures in SLE BM of HSPC clusters 3 and 4 and myeloid-like progenitor cluster 5 when compared with healthy controls. The IFN signature in SLE appeared to be deregulated following TF regulatory network analysis and differential alternative splicing analysis between SLE and healthy controls in HSPC subpopulations. Discussion: This study revealed both quantitative--as evidenced by decreased numbers of non-proliferating early progenitors--and qualitative differences-- characterized by an IFN signature in SLE, which is known to drive loss of function and depletion of HSPCs. Chronic IFN exposure affects early hematopoietic progenitors in SLE, which may account for the immune aberrancies and the cytopenias in SLE. [ABSTRACT FROM AUTHOR]

Background: Tuberculous meningitis (TBM) is a devastating form of tuberculosis (TB) causing high mortality and disability. TBM arises due to immune dysregulation, but the underlying immune mechanisms are unclear. Methods: We performed single-cell RNA sequencing on peripheral blood mononuclear cells (PBMCs) and cerebrospinal fluid (CSF) cells isolated from children (n=6) with TBM using 10 xGenomics platform. We used unsupervised clustering of cells and cluster visualization based on the gene expression profiles, and validated the protein and cytokines by ELISA analysis. Results: We revealed for the first time 33 monocyte populations across the CSF cells and PBMCs of children with TBM. Within these populations, we saw that CD4_C04 cells with Th17 and Th1 phenotypes and Macro_C01 cells with a microglia phenotype, were enriched in the CSF. Lineage tracking analysis of monocyte populations revealed myeloid cell populations, as well as subsets of CD4 and CD8 T-cell populations with distinct effector functions. Importantly, we discovered that complement-activated microglial Macro_C01 cells are associated with a neuroinflammatory response that leads to persistent meningitis. Consistently, we saw an increase in complement protein (C1Q), inflammatory markers (CRP) and inflammatory factor (TNF-α and IL-6) in CSF cells but not blood. Finally, we inferred that Macro_C01 cells recruit CD4_C04 cells through CXCL16/CXCR6. Discussion: We proposed that the microglial Macro_C01 subset activates complement and interacts with the CD4_C04 cell subset to amplify inflammatory signals, which could potentially contribute to augment inflammatory signals, resulting in hyperinflammation and an immune response elicited by Mtb-infected tissues. [ABSTRACT FROM AUTHOR]

Background: Circulating tumor cells (CTCs) hold immense promise for unraveling tumor heterogeneity and understanding treatment resistance. However, conventional methods, especially in cancers like non-small cell lung cancer (NSCLC), often yield low CTC numbers, hindering comprehensive analyses. This study addresses this limitation by employing diagnostic leukapheresis (DLA) to cancer patients, enabling the screening of larger blood volumes. To leverage DLA's full potential, this study introduces a novel approach for CTC enrichment from DLAs. Methods: DLA was applied to six advanced stage NSCLC patients. For an unbiased CTC enrichment, a two-step approach based on negative depletion of hematopoietic cells was used. Single-cell (sc) whole-transcriptome sequencing was performed, and CTCs were identified based on gene signatures and inferred copy number variations. Results: Remarkably, this innovative approach led to the identification of unprecedented 3,363 CTC transcriptomes. The extensive heterogeneity among CTCs was unveiled, highlighting distinct phenotypes related to the epithelial-mesenchymal transition (EMT) axis, stemness, immune responsiveness, and metabolism. Comparison with sc transcriptomes from primary NSCLC cells revealed that CTCs encapsulate the heterogeneity of their primary counterparts while maintaining unique CTC-specific phenotypes. Conclusions: In conclusion, this study pioneers a transformative method for enriching CTCs from DLA, resulting in a substantial increase in CTC numbers. This allowed the creation of the first-ever single-cell whole transcriptome in-depth characterization of the heterogeneity of over 3,300 NSCLC-CTCs. The findings not only confirm the diagnostic value of CTCs in monitoring tumor heterogeneity but also propose a CTC-specific signature that can be exploited for targeted CTC-directed therapies in the future. This comprehensive approach signifies a major leap forward, positioning CTCs as a key player in advancing our understanding of cancer dynamics and paving the way for tailored therapeutic interventions. [ABSTRACT FROM AUTHOR]

Primary sclerosing cholangitis (PSC) is an immune-mediated cholestatic liver disease for which there is an unmet need to understand the cellular composition of the affected liver and how it underlies disease pathogenesis. We aimed to generate a comprehensive atlas of the PSC liver using multi-omic modalities and protein-based functional validation. We employed single-cell and single-nucleus RNA sequencing (47,156 cells and 23,000 nuclei) and spatial transcriptomics (one sample by 10x Visium and five samples with Nanostring GeoMx DSP) to profile the cellular ecosystem in 10 PSC livers. Transcriptomic profiles were compared to 24 neurologically deceased donor livers (107,542 cells) and spatial transcriptomics controls, as well as 18,240 cells and 20,202 nuclei from three PBC livers. Flow cytometry was performed to validate PSC-specific differences in immune cell phenotype and function. PSC explants with parenchymal cirrhosis and prominent periductal fibrosis contained a population of cholangiocyte-like hepatocytes that were surrounded by diverse immune cell populations. PSC-associated biliary, mesenchymal, and endothelial populations expressed chemokine and cytokine transcripts involved in immune cell recruitment. Additionally, expanded CD4+ T cells and recruited myeloid populations in the PSC liver expressed the corresponding receptors to these chemokines and cytokines, suggesting potential recruitment. Tissue-resident macrophages, by contrast, were reduced in number and exhibited a dysfunctional and downregulated inflammatory response to lipopolysaccharide and interferon-γ stimulation. We present a comprehensive atlas of the PSC liver and demonstrate an exhaustion-like phenotype of myeloid cells and markers of chronic cytokine expression in late-stage PSC lesions. This atlas expands our understanding of the cellular complexity of PSC and has potential to guide the development of novel treatments. Primary sclerosing cholangitis (PSC) is a rare liver disease characterized by chronic inflammation and irreparable damage to the bile ducts, which eventually results in liver failure. Due to a limited understanding of the underlying pathogenesis of disease, treatment options are limited. To address this, we sequenced healthy and diseased livers to compare the activity, interactions, and localization of immune and non-immune cells. This revealed that hepatocytes lining PSC scar regions co-express cholangiocyte markers, whereas immune cells infiltrate the scar lesions. Of these cells, macrophages, which typically contribute to tissue repair, were enriched in immunoregulatory genes and demonstrated a lack of responsiveness to stimulation. These cells may be involved in maintaining hepatic inflammation and could be a target for novel therapies. [Display omitted] • ScRNA-seq revealed additional macrophage diversity in the NDD (healthy) liver. • CD206+ macrophages in the PSC liver show reduced responsiveness to stimulation. • CK7+ HNF4A+ transitioning hepatocytes are enriched in PSC fibrotic lesions in comparison to PBC and NDD. [ABSTRACT FROM AUTHOR]

Aim: Metastasis is the leading cause of mortality in hepatocellular carcinoma (HCC). The metastasis‐associated immune signature in HCC is worth exploring. Methods: Bioinformatic analysis was conducted based on the single‐cell transcriptome data derived from HCC patients in different stages. Cellular composition, pseudotime state transition, and cell–cell interaction were further analyzed and verified. Results: Generally, HCC with metastasis exhibited suppressive immune microenvironment, while HCC without metastasis exhibited active immune microenvironment. Concretely, effector regulatory T cells (eTregs) were found to be enriched in HCC with metastasis. PHLDA1 was identified as one of exhaustion‐specific genes and verified to be associated with worse prognosis in HCC patients. Moreover, A novel cluster of CCR7+ dendritic cells (DCs) was identified with high expression of maturation and migration marker genes. Pseudotime analysis showed that inhibition of differentiation occurred in CCR7+ DCs rather than cDC1 in HCC with metastasis. Furthermore, interaction analysis showed that the reduction of CCR7+ DCs lead to impaired CCR7/CCL19 interaction in HCC with metastasis. Conclusions: HCC with metastasis exhibited upregulation of exhaustion‐specific genes of eTregs and inhibition of CCL signal of a novel DC cluster, which added new dimensions to the immune landscape and provided new immune therapeutic targets in advanced HCC. [ABSTRACT FROM AUTHOR]

Hippocampal pyramidal neurons exhibit diverse spike patterns and gene expression profiles. However, their relationships with single neurons are not fully understood. In this study, we designed an electrophysiology-based experimental procedure to identify gene expression profiles using RNA sequencing of single hippocampal pyramidal neurons whose spike patterns were recorded in living mice. This technique involves a sequence of experiments consisting of in vivo juxtacellular recording and labeling, brain slicing, cell collection, and transcriptome analysis. We demonstrated that the expression levels of a subset of genes in individual hippocampal pyramidal neurons were significantly correlated with their spike burstiness, submillisecond-level spike rise times or spike rates, directly measured by in vivo electrophysiological recordings. Because this methodological approach can be applied across a wide range of brain regions, it is expected to contribute to studies on various neuronal heterogeneities to understand how physiological spike patterns are associated with gene expression profiles. [ABSTRACT FROM AUTHOR]

Background: In recent years, Single-cell RNA sequencing (scRNA-seq) is increasingly accessible to researchers of many fields. However, interpreting its data demands proficiency in multiple programming languages and bioinformatic skills, which limited researchers, without such expertise, exploring information from scRNA-seq data. Therefore, there is a tremendous need to develop easy-to-use software, covering all the aspects of scRNA-seq data analysis. Results: We proposed a clear analysis framework for scRNA-seq data, which emphasized the fundamental and crucial roles of cell identity annotation, abstracting the analysis process into three stages: upstream analysis, cell annotation and downstream analysis. The framework can equip researchers with a comprehensive understanding of the analysis procedure and facilitate effective data interpretation. Leveraging the developed framework, we engineered Shaoxia, an analysis platform designed to democratize scRNA-seq analysis by accelerating processing through high-performance computing capabilities and offering a user-friendly interface accessible even to wet-lab researchers without programming expertise. Conclusion: Shaoxia stands as a powerful and user-friendly open-source software for automated scRNA-seq analysis, offering comprehensive functionality for streamlined functional genomics studies. Shaoxia is freely accessible at http://www.shaoxia.cloud, and its source code is publicly available at https://github.com/WiedenWei/shaoxia. [ABSTRACT FROM AUTHOR]

Background: Single-cell sequencing techniques are revolutionizing every field of biology by providing the ability to measure the abundance of biological molecules at a single-cell resolution. Although single-cell sequencing approaches have been developed for several molecular modalities, single-cell transcriptome sequencing is the most prevalent and widely applied technique. SPLiT-seq (split-pool ligation-based transcriptome sequencing) is one of these single-cell transcriptome techniques that applies a unique combinatorial-barcoding approach by splitting and pooling cells into multi-well plates containing barcodes. This unique approach required the development of dedicated computational tools to preprocess the data and extract the count matrices. Here we compare eight bioinformatic pipelines (alevin-fry splitp, LR-splitpipe, SCSit, splitpipe, splitpipeline, SPLiTseq-demultiplex, STARsolo and zUMI) that have been developed to process SPLiT-seq data. We provide an overview of the tools, their computational performance, functionality and impact on downstream processing of the single-cell data, which vary greatly depending on the tool used. Results: We show that STARsolo, splitpipe and alevin-fry splitp can all handle large amount of data within reasonable time. In contrast, the other five pipelines are slow when handling large datasets. When using smaller dataset, cell barcode results are similar with the exception of SPLiTseq-demultiplex and splitpipeline. LR-splitpipe that is originally designed for processing long-read sequencing data is the slowest of all pipelines. Alevin-fry produced different down-stream results that are difficult to interpret. STARsolo functions nearly identical to splitpipe and produce results that are highly similar to each other. However, STARsolo lacks the function to collapse random hexamer reads for which some additional coding is required. Conclusion: Our comprehensive comparative analysis aids users in selecting the most suitable analysis tool for efficient SPLiT-seq data processing, while also detailing the specific prerequisites for each of these pipelines. From the available pipelines, we recommend splitpipe or STARSolo for SPLiT-seq data analysis. [ABSTRACT FROM AUTHOR]

Introduction: Acute myeloid leukemia (AML) is the most common acute leukemia in adults with an overall poor prognosis and high relapse rate. Multiple factors including genetic abnormalities, differentiation defects and altered cellular metabolism contribute to AML development and progression. Though the roles of oxidative phosphorylation and glycolysis are defined in AML, the role of the hexosamine biosynthetic pathway (HBP), which regulates the OGlcNAcylation of cytoplasmic and nuclear proteins, remains poorly defined. Methods: We studied the expression of the key enzymes involved in the HBP in AML blasts and stem cells by RNA sequencing at the single-cell and bulk level. We performed flow cytometry to study OGT protein expression and global OGlcNAcylation. We studied the functional effects of inhibiting O-GlcNAcylation on transcriptional activation in AML cells by Western blotting and real time PCR and on cell cycle by flow cytometry. Results: We found higher expression levels of the key enzymes in the HBP in AML as compared to healthy donors in whole blood. We observed elevated O-GlcNAc Transferase (OGT) and O-GlcNAcase (OGA) expression in AML stem and bulk cells as compared to normal hematopoietic stem and progenitor cells (HSPCs). We also found that both AML bulk cells and stem cells show significantly enhanced OGT protein expression and global O-GlcNAcylation as compared to normal HSPCs, validating our in silico findings. Gene set analysis showed substantial enrichment of the NF-κB pathway in AML cells expressing high OGT levels. Inhibition of O-GlcNAcylation decreased NF-κB nuclear translocation and the expression of selected NF-κB-dependent genes controlling cell cycle. It also blocked cell cycle progression suggesting a link between enhanced OGlcNAcylation and NF-κB activation in AML cell survival and proliferation. Discussion: Our study suggests the HBP may prove a potential target, alone or in combination with other therapeutic approaches, to impact both AML blasts and stem cells. Moreover, as insufficient targeting of AML stem cells by traditional chemotherapy is thought to lead to relapse, blocking HBP and O-GlcNAcylation in AML stem cells may represent a novel promising target to control relapse. [ABSTRACT FROM AUTHOR]

Objective To construct a polygenic risk score based on the expression of epithelial cell markers to evaluate the prognosis of patients with ovarian cancer. Methods The single cell sequencing data of ovarian cancer were reduced and clustered to identify epithelial cell markers, malignant and non-malignant markers. Regression analysis was used to screen epithelial marker genes related to prognosis to construct a risk score model. Based on the risk score, patients were divided into high risk group and low risk group （H.Risk，L.Risk） to predict the prognosis of patients with ovarian cancer. Results A risk scoring model with four genes （EPCAM，CLDN4, CXCR4 and TIMP3） was constructed. Survival analysis showed that the OS of patients in H.Risk group was worse than that in L.Risk group in trial cohort and verification cohort （P < 0.05）. Pathway enrichment analysis showed that the differential genes between high and low risk groups were associated with immunosuppression and malignant progression, including cell adhesion, extracellular matrix, neuroactive ligand-receptor interaction, calcium signal pathway，transforming growth factor-β. Conclusion Through the comprehensive analysis of bulkRNA-seq and scRNA-seq data，a risk scoring model based on epithelial cell subsets marker genes is proposed, which may provide potential therapeutic targets for patients with ovarian cancer. [ABSTRACT FROM AUTHOR]

Epstein-Barr virus (EBV) infection can lead to infectious mononucleosis (EBV-IM) and, more rarely, EBV-associated hemophagocytic lymphohistiocytosis (EBV-HLH), which is characterized by a life-threatening hyperinflammatory cytokine storm with immune dysregulation. Interferon-gamma (IFNγ) has been identified as a critical mediator for primary HLH; however, the detailed role of IFNγ and other cytokines in EBV-HLH is not fully understood. In this study, we used single-cell RNA sequencing to characterize the immune landscape of EBV-HLH and compared it with EBV-IM. Three pediatric patients with EBV-HLH with different backgrounds, one with X-linked lymphoproliferative syndrome type 1 (XLP1), two with chronic active EBV disease (CAEBV), and two patients with EBV-IM were enrolled. The TUBA1B + STMN1 + CD8 + T cell cluster, a responsive proliferating cluster with rich mRNA detection, was explicitly observed in EBV-IM, and the upregulation of SH2D1A—the gene responsible for XLP1—was localized in this cluster. This proliferative cluster was scarcely observed in EBV-HLH cases. In EBV-HLH cases with CAEBV, upregulation of LAG3 was observed in EBV-infected cells, which may be associated with an impaired response by CD8 + T cells. Additionally, genes involved in type I interferon (IFN) signaling were commonly upregulated in each cell fraction of EBV-HLH, and activation of type II IFN signaling was observed in CD4 + T cells, natural killer cells, and monocytes but not in CD8 + T cells in EBV-HLH. In conclusion, impaired responsive proliferation of CD8 + T cells and upregulation of type I IFN signaling were commonly observed in EBV-HLH cases, regardless of the patients’ background, indicating the key features of EBV-HLH. [ABSTRACT FROM AUTHOR]

Idiopathic pulmonary arterial hypertension (IPAH) is a rare and severe cardiopulmonary disease with a challenging prognosis, and its underlying pathogenesis remains elusive. A comprehensive understanding of IPAH is crucial to unveil potential diagnostic markers and therapeutic targets. In this study, we investigated cellular heterogeneity and molecular pathology in IPAH using single-cell RNA sequencing (scRNA-seq) analysis. Our scRNA-seq results revealed significant alterations in three crucial signaling pathways in IPAH: the hypoxia pathway, TGF ß pathway, and ROS pathway, primarily attributed to changes in gene expression within arterial endothelial cells. Moreover, through bulk RNA sequencing analysis, we identified differentially expressed genes (DEGs) enriched in GO and KEGG pathways, implicated in regulating cell adhesion and oxidative phosphorylation in IPAH lungs. Similarly, DEGsenriched pathways in IPAH arterial endothelial cells were also identified. By integrating DEGs from three IPAH datasets and applying protein-protein interaction (PPI) analysis, we identified 12 candidate biomarkers. Subsequent validation in two additional PAH datasets led us to highlight five potential biomarkers (CTNNB1, MAPK3, ITGB1, HSP90AA1, and DDX5) with promising diagnostic significance for IPAH. Furthermore, real-time quantitative polymerase chain reaction (RT-qPCR) confirmed significant differences in the expression of these five genes in pulmonary arterial endothelial cells from PAH mice. In conclusion, our findings shed light on the pivotal role of arterial endothelial cells in the development of IPAH. Furthermore, the integration of single-cell and bulk RNA sequencing datasets allowed us to pinpoint novel candidate biomarkers for the diagnosis of IPAH. This work opens up new avenues for research and potential therapeutic interventions in IPAH management. [ABSTRACT FROM AUTHOR]

Low efficacy of treatments and chemoresistance are challenges in addressing refractory hepatocellular carcinoma (HCC). SPINK1, an oncogenic protein, is frequently overexpressed in many HCC cases. However, the impact of SPINK1 on HCC treatment resistance remains poorly understood. Here, we elucidate the functions of SPINK1 on HCC therapy resistance. Analysis of SPINK1 protein level reveals a correlation between elevated SPINK1 expression and unfavorable prognosis. Furthermore, intercellular variations in SPINK1 expression levels are observed. Subsequent examination of single cell RNA-sequencing data from two HCC cohorts further suggest that SPINK1-high cells exhibit heightened activity in drug metabolic pathways compared to SPINK1-low HCC cells. High SPINK1 expression is associated with reduced sensitivities to both chemotherapy drugs and targeted therapies. Moreover, spatial transcriptomics data indicate that elevated SPINK1 expression correlates with non-responsive phenotype during treatment with targeted therapy and immune checkpoint inhibitors. This is attributed to increased levels of drug metabolic regulators, especially CES2 and CYP3A5, in SPINK1-high cells. Experimental evidence further demonstrates that SPINK1 overexpression induces the expression of CES2 and CYP3A5, consequently promoting chemoresistance to sorafenib and oxaliplatin. In summary, our study unveils the predictive role of SPINK1 on HCC treatment resistance, identifying it as a potential therapeutic target for refractory HCC. [ABSTRACT FROM AUTHOR]

Aging-related salivary gland changes, such as lymphocyte infiltration and acinar cell loss decrease saliva secretion, thereby affecting quality of life. The precise molecular mechanisms underlying these changes remain unclear. We here performed single-cell RNA sequencing to clarify gene expression changes in each cell type comprising the submandibular glands (SMGs) of adult and aged mice. The proportion of acinar cells decreased in various epithelial clusters annotated with cell type-specific marker genes. Expression levels of the cellular senescence markers, Cdkn2a / p16 and Cdkn1a / p21 , were increased in the basal and striated ducts of aged SMGs relative to their levels in those of adult SMGs. In contrast, senescence-associated secretory phenotype-related genes, except transforming growth factor-β, exhibited little change in expression in aged SMGs relative to adult SMGs. Conclusions: Gene Ontology analysis revealed increased expression levels of genes encoding major histocompatibility complex (MHC) class I components in the ductal component cells of aged SMGs. MHC class I expression may thus be associated with salivary gland aging. • Submandibular glands of aged mice exhibited chronic inflammation. • Ductal component cells of aged mouse submandibular glands expressed MHC class I component-encoding genes. • The changes of expression levels of senescence biomarkers and SASP gene were observed in aged mouse submandibular glands. [ABSTRACT FROM AUTHOR]

Introduction: Chronic rhinosinusitis (CRS) is a chronic inflammatory disease of the sinonasal mucosa with distinct endotypes including type 2 (T2) high eosinophilic CRS with nasal polyps (eCRSwNP), T2 low non-eosinophilic CRS with nasal polyps (neCRSwNP), and CRS without nasal polyps (CRSsNP). Methods: Given the heterogeneity of disease, we hypothesized that assessment of single cell RNA sequencing (scRNA-seq) across this spectrum of disease would reveal connections between infiltrating and activated immune cells and the epithelial and stromal populations that reside in sinonasal tissue. Results: Here we find increased expression of genes encoding glycolytic enzymes in epithelial cells (EpCs), stromal cells, and memory T-cell subsets from patients with eCRSwNP, as compared to healthy controls. In basal EpCs, this is associated with a program of cell motility and Rho GTPase effector expression. Across both stromal and immune subsets, glycolytic programming was associated with extracellular matrix interactions, proteoglycan generation, and collagen formation. Furthermore, we report increased cell-cell interactions between EpCs and stromal/immune cells in eCRSwNP compared to healthy control tissue, and we nominate candidate receptor-ligand pairs that may drive tissue remodeling. Discussion: These findings support a role for glycolytic reprograming in T2-elicited tissue remodeling and implicate increased cellular crosstalk in eCRSwNP. [ABSTRACT FROM AUTHOR]

Molecular and cellular characterization of tumors is essential due to the complex and heterogeneous nature of cancer. In recent decades, many bioinformatic tools and experimental techniques have been developed to achieve personalized characterization of tumors. However, sample handling continues to be a major challenge as limitations such as prior treatments before sample acquisition, the amount of tissue obtained, transportation, or the inability to process fresh samples pose a hurdle for experimental strategies that require viable cell suspensions. Here, we present an optimized protocol that allows the recovery of highly viable cell suspensions from breast cancer primary tumor biopsies. Using these cell suspensions we have successfully characterized genome architecture through Hi-C. Also, we have evaluated single-cell gene expression and the tumor cellular microenvironment through single-cell RNAseq. Both technologies are key in the detailed and personalized molecular characterization of tumor samples. The protocol described here is a cost-effective alternative to obtain viable cell suspensions from biopsies simply and efficiently.

Background and objectives: Perineural invasion (PNI) refers to the invasion, encasement, or penetration of tumor cells around or through nerves. Various malignant tumors, including pancreatic cancer, head and neck tumors, and bile duct cancer, exhibit the characteristic of PNI. Particularly, in head and neck-skull base tumors such as adenoid cystic carcinoma (ACC), PNI is a significant factor leading to incomplete surgical resection and postoperative recurrence. Methods: Spatial transcriptomic and single-cell transcriptomic sequencing were conducted on a case of ACC tissue with PNI to identify potential probes targeting PNI. The efficacy of the probes was validated through in vivo and in vitro experiments. Results: Spatial transcriptomic and single-cell RNA sequencing revealed phenotypic changes in Schwann cells within the PNI region of ACC. Peptide probes were designed based on the antigen-presenting characteristics of Schwann cells in the PNI region, which are dependent on Major Histocompatibility Complex II (MHC-II) molecules. Successful validation in vitro and in vivo experiments confirmed that these probes can label viable Schwann cells in the PNI region, serving as a tool for dynamic in vivo marking of tumor invasion into nerves. Conclusions: Peptide probes targeting Schwann cells' MHC-II molecules have the potential to demonstrate the occurrence of PNI in patients with ACC

Human immunodeficiency virus (HIV) infection has evolved into an established global pandemic over the past four decades; however, despite massive research investment globally, the precise underlying mechanisms which are fundamental to HIV-related pathogenesis remain unclear. Single cell ribonucleic acid (RNA) sequencing methods are increasingly being used for the identification of specific cell-type transcriptional changes in HIV infection. In this scoping review, we have considered information extracted from fourteen published HIV-associated single-cell RNA sequencing-related studies, hoping to throw light on the underlying mechanisms of HIV infection and pathogenesis, and to explore potential candidate biomarkers for HIV disease progression and antiviral treatment. Generally, HIV positive individuals tend to manifest disturbances of frequency of multiple cellular types, and specifically exhibit diminished levels of CD4+ T-cells and enriched numbers of CD8+ T-cells. Cell-specific transcriptional changes tend to be linked to cell permissiveness, hyperacute or acute HIV infection, viremia, and cell productivity. The transcriptomes of CD4+ T-cell and CD8+ T-cell subpopulations are also observed to change in HIV-positive diabetic individuals, spontaneous HIV controllers, individuals with high levels of HIV viremia, and those in an acute phase of HIV infection. The transcriptional changes seen in B cells, natural killer (NK) cells, and myeloid dendritic cells (mDCs) of HIV-infected individuals demonstrate that the humoral immune response, antiviral response, and immune response regulation, respectively, are all altered following HIV infection. Antiretroviral therapy (ART) plays a crucial role in achieving immune reconstitution, in improving immunological disruption, and in mitigating immune system imbalances in HIV-infected individuals, while not fully restoring inherent cellular transcription to levels seen in HIV-negative individuals. The preceding observations not only illustrate compelling advances in the understanding of HIV-associated immunopathogenesis, but also identify specific cell-type transcriptional changes that may serve as potential biomarkers for HIV disease monitoring and therapeutic targeting.

Background: Duchenne muscular dystrophy is a genetic disease produced by mutations in the dystrophin gene characterized by early onset muscle weakness leading to severe and irreversible disability. Muscle degeneration involves a complex interplay between multiple cell lineages spatially located within areas of damage, termed the degenerative niche, including inflammatory cells, satellite cells (SCs) and fibro-adipogenic precursor cells (FAPs). FAPs are mesenchymal stem cell which have a pivotal role in muscle homeostasis as they can either promote muscle regeneration or contribute to muscle degeneration by expanding fibrotic and fatty tissue. Although it has been described that FAPs could have a different behavior in DMD patients than in healthy controls, the molecular pathways regulating their function as well as their gene expression profile are unknown.Methods: We used single-cell RNA sequencing (scRNAseq) with 10X Genomics and Illumina technology to elucidate the differences in the transcriptional profile of isolated FAPs from healthy and DMD patients.Results: Gene signatures in FAPs from both groups revealed transcriptional differences. Seurat analysis categorized cell clusters as proliferative FAPs, regulatory FAPs, inflammatory FAPs, and myofibroblasts. Differentially expressed genes (DEGs) between healthy and DMD FAPs included upregulated genes CHI3L1, EFEMP1, MFAP5, and TGFBR2 in DMD. Functional analysis highlighted distinctions in system development, wound healing, and cytoskeletal organization in control FAPs, while extracellular organization, degradation, and collagen degradation were upregulated in DMD FAPs. Validation of DEGs in additional samples (n = 9) using qPCR reinforced the specific impact of pathological settings on FAP heterogeneity, reflecting their distinct contribution to fibro or fatty degeneration in vivo.Conclusion: Using the single-cell RNA seq from human samples provide new opportunities to study cellular coordination to further understand the regulation of muscle homeostasis and degeneration that occurs in muscular dystrophies.

Purpose: Uveitis is a heterogenous group of inflammatory eye disease for which current cytokine-targeted immune therapies are effective for only a subset of patients. We hypothesized that despite pathophysiologic nuances that differentiate individual disease states, all forms of eye inflammation might share common mechanisms for immune cell recruitment. Identifying these mechanisms is critical for developing novel, broadly acting therapeutic strategies. Design: Experimental study. Subjects: Biospecimens from patients with active or inactive uveitis and healthy controls. Methods: Protein concentration and single cell gene expression were assessed in aqueous fluid biopsies and plasma samples from deidentified patients with uveitis or healthy controls. Main Outcome Measures: The concentration of 31 inflammatory proteins was measured in all aqueous samples, as well as plasma samples from patients with active uveitis. Chemokine and cytokine ligand and receptor expression were assessed in individual cell types from aqueous biopsies obtained from patients with active uveitis. Results: We identified 6 chemokines that were both elevated in active uveitis compared with controls and enriched in aqueous compared with plasma during active uveitis (C-C motif chemokine ligand [CCL]2, C-X-C motif chemokine ligand [CXCL]10, CXCL9, CXCL8, CCL3, and CCL14), forming potential gradients for migration of immune cells from the blood to the eye. Of these, CCL2 and CXCL10 were consistently enriched in the aqueous of all patients in our cohort, as well as in a larger cohort of patients from a previously published study. These data suggest that CCL2 and CXCL10 are key mediators in immune cell migration to the eye during uveitis. Next, single cell RNA sequencing suggested that macrophages contribute to aqueous enrichment of CCL2 and CXCL10 during human uveitis. Finally, using chemokine ligand and receptor expression mapping, we identified a broad signaling network for macrophage-derived CCL2 and CXCL10 in human uveitis. Conclusions: These data suggest that ocular macrophages may play a central role, via CCL2 and CXCL10 production, in recruiting inflammatory cells to the eye in patients with uveitis. Financial Disclosure(s): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.