TP63 transcriptionally regulates SLC7A5 to suppress ferroptosis in head and neck squamous cell carcinoma.

Background: Most head and neck squamous cell carcinoma (HNSCC) patients are diagnosed at an advanced local stage. While immunotherapy has improved survival rates, only a minority of patients respond durably to targeted immunotherapies, posing substantial clinical challenges. We investigated the heterogeneity of the tumor microenvironment in HNSCC cohorts before and after immunotherapy by analyzing single-cell RNA sequencing (scRNA-seq) data and bulk RNA sequencing datasets retrieved from public databases. Methods: We constructed a single-cell transcriptome landscape of HNSCC patients before and after immunotherapy and analyzed the cellular composition, developmental trajectories, gene regulatory networks, and communication patterns of different cell type subpopulations. Additionally, we assessed the expression levels of relevant indicators in HNSCC cells via western blot, ELISA, and fluorescent probe techniques. Results: At the single-cell level, we identified a subpopulation of TP63+ SLC7A5+ HNSCC that exhibited a ferroptosis-resistant phenotype. This subpopulation suppresses ferroptosis in malignant cells through the transcriptional upregulation of SLC7A5 mediated by high TP63 expression, thereby promoting tumor growth and resistance to immunotherapy. The experimental results demonstrated that the overexpression of TP63 upregulated the expression of SLC7A5 and suppressed the concentrations of Fe2+ and ROS in HNSCC cells. By integrating bulk transcriptome data, we developed a clinical scoring model based on TP63 and SLC7A5, which are closely associated with tumor stage, revealing the significant prognostic efficacy of the TP63+ SLC7A5+ HNSCC-mediated ferroptosis mechanism in HNSCC patients. Conclusion: Our research elucidates the TME in HNSCC before and after immunotherapy, revealing a novel mechanism by which TP63+ SLC7A5+ HNSCC inhibits ferroptosis and enhances tumor resistance via TP63-induced SLC7A5 upregulation. These insights lay the foundation for the development of more effective treatments for HNSCC.

Linking transcriptome and morphology in bone cells at cellular resolution with generative AI.

Recent advancements in deep learning (DL) have revolutionized the capability of artificial intelligence (AI) by enabling the analysis of large-scale, complex datasets that are difficult for humans to interpret. However, large amounts of high-quality data are required to train such generative AI models successfully. With the rapid commercialization of single-cell sequencing and spatial transcriptomics platforms, the field is increasingly producing large-scale datasets such as histological images, single-cell molecular data, and spatial transcriptomic data. These molecular and morphological datasets parallel the multimodal text and image data used to train highly successful generative AI models for natural language processing and computer vision. Thus, these emerging data types offer great potential to train generative AI models that uncover intricate biological processes of bone cells at a cellular level. In this Perspective, we summarize the progress and prospects of generative AI applied to these datasets and their potential applications to bone research. In particular, we highlight three AI applications: predicting cell differentiation dynamics, linking molecular and morphological features, and predicting cellular responses to perturbations. To make generative AI models beneficial for bone research, important issues, such as technical biases in bone single-cell datasets, lack of profiling of important bone cell types, and lack of spatial information, need to be addressed. Realizing the potential of generative AI for bone biology will also likely require generating large-scale, high-quality cellular-resolution spatial transcriptomics datasets, improving the sensitivity of current spatial transcriptomics datasets, and thorough experimental validation of model predictions.

Imagine if pathologists could infer the whole transcriptomes of individual cells from a standard histological section of a bone biopsy, identify molecular defects compared to healthy cells, and predict how those cells would respond to various chemical or genetic treatments. The ability to model the relationship between transcriptomic profiles and morphological or functional properties based on limited biopsy samples would revolutionize diagnosis and treatment decisions in clinical practice. Such modeling seemed impossible only a few years ago, and comprehensive molecular diagnosis is currently impractical, as it requires extensive and expensive laboratory tests. However, rapid advances in artificial intelligence (AI) may soon make this dream a reality. In this Perspective, we discuss the promise of generative AI for linking transcriptomes and morphology at cellular resolution to benefit bone research and potential clinical application. We argue that there is a plausible path toward AI-assisted diagnosis using the whole transcriptome in a cellular and spatial context, which will lead to breakthroughs in our understanding of bone biology and bone disease.

Gene regulatory mechanisms of T cell exhaustion in diffuse large B cell lymphoma based on single-cell transcriptome data.

Diffuse large B cell lymphoma (DLBCL) is a heterogeneous and aggressive B cell malignancy that accounts for about 30 % of non-Hodgkin lymphomas. The current standard treatment for DLBCL is rituximab plus chemotherapy, but many patients are refractory or relapse, indicating the need for improved understanding of its molecular pathology. T cell exhaustion is a state of dysfunction or impairment that occurs in chronic infections or cancers, and is associated with poor prognosis in DLBCL. However, the molecular mechanisms of T cell exhaustion in DLBCL are poorly understood. In this study, we performed a comprehensive analysis of T cell exhaustion in DLBCL using public single-cell transcriptome data. We identified different subtypes of T cells and characterized their gene expression features. We found that DLBCL had a significantly higher proportion of exhausted T cells than normal tonsil, and that exhausted T cells had distinct gene expression signatures from non-exhausted T cells. These signatures included genes related to inhibitory receptors, cytokines, transcription factors and metabolic enzymes. We also found that ID3 gene was significantly upregulated in exhausted T cells in DLBCL, which may play a key role in T cell exhaustion. We constructed a protein-protein interaction network, identifying major hub proteins involved in T cell exhaustion or migration. We also performed KEGG and GO enrichment analysis for the differentially expressed genes between exhausted and non-exhausted T cells, and found important signaling pathways related to T cell exhaustion in DLBCL. Our results provide new insights into the molecular mechanisms underlying T cell exhaustion and offer novel therapeutic targets for this complex disease.

The role of GDF15 in attenuating noise-induced hidden hearing loss by alleviating oxidative stress.

Noise-induced hidden hearing loss (HHL) is a newly uncovered form of hearing impairment that causes hidden damage to the cochlea. Patients with HHL do not have significant abnormalities in their hearing thresholds, but they experience impaired speech recognition in noisy environments. However, the mechanisms underlying HHL remain unclear. In this study, we developed single-cell transcriptome profiles of the cochlea of mice with HHL, detailing changes in individual cell types. Our study revealed a transient threshold shift, reduced auditory brainstem response wave I amplitude, and decreased number of ribbon synapses in HHL mice. Our findings suggest elevated oxidative stress and GDF15 expression in cochlear hair cells of HHL mice. Notably, the upregulation of GDF15 attenuated oxidative stress and auditory impairment in the cochlea of HHL mice. This suggests that a therapeutic strategy targeting GDF15 may be efficacious against HHL.

Molecular profiling and therapeutic tailoring to address disease heterogeneity in systemic lupus erythematosus.

Systemic lupus erythematosus (SLE) is a chronic, heterogeneous, systemic autoimmune disease characterized by autoantibody production, complement activation, and immune complex deposition. SLE predominantly affects young, middle-aged, and child-bearing women with episodes of flare-up and remission, although it affects males at a much lower frequency (female: male; 7:1 to 15:1). Technological and molecular advancements have helped in patient stratification and improved patient prognosis, morbidity, and treatment regimens overall, impacting quality of life. Despite several attempts to comprehend the pathogenesis of SLE, knowledge about the precise molecular mechanisms underlying this disease is still lacking. The current treatment options for SLE are pragmatic and aim to develop composite biomarkers for daily practice, which necessitates the robust development of novel treatment strategies and drugs targeting specific responsive pathways. In this communication, we review and aim to explore emerging therapeutic modalities, including multiomics-based approaches, rational drug design, and CAR-T-cell-based immunotherapy, for the management of SLE.

Single-cell and bulk transcriptional profiling of mouse ovaries reveals novel genes and pathways associated with DNA damage response in oocytes.

Immature oocytes enclosed in primordial follicles stored in female ovaries are under constant threat of DNA damage induced by endogenous and exogenous factors. Checkpoint kinase 2 (CHEK2) is a key mediator of the DNA damage response (DDR) in all cells. Genetic studies have shown that CHEK2 and its downstream targets, p53, and TAp63, regulate primordial follicle elimination in response to DNA damage. However, the mechanism leading to their demise is still poorly characterized. Single-cell and bulk RNA sequencing were used to determine the DDR in wild-type and Chek2-deficient ovaries. A low but oocyte-lethal dose of ionizing radiation induces ovarian DDR that is solely dependent on CHEK2. DNA damage activates multiple response pathways related to apoptosis, p53, interferon signaling, inflammation, cell adhesion, and intercellular communication. These pathways are differentially employed by different ovarian cell types, with oocytes disproportionately affected by radiation. Novel genes and pathways are induced by radiation specifically in oocytes, shedding light on their sensitivity to DNA damage, and implicating a coordinated response between oocytes and pregranulosa cells within the follicle. These findings provide a foundation for future studies on the specific mechanisms regulating oocyte survival in the context of aging and therapeutic and environmental genotoxic exposures.

Single-cell transcriptomics reveals neural stem cell trans-differentiation and cell subpopulations in whole heart decellularized extracellular matrix.

The whole heart decellularized extracellular matrix (ECM) has become a promising scaffold material for cardiac tissue engineering. Our previous research has shown that the whole heart acellular matrix possesses the memory function regulating neural stem cells (NSCs) trans-differentiating to cardiac lineage cells. However, the cell subpopulations and phenotypes in the trans-differentiation of NSCs have not been clearly identified. Here, we performed single-cell RNA sequencing and identified 2,765 cells in the recellularized heart with NSCs revealing the cellular diversity of cardiac and neural lineage, confirming NSCs were capable of trans-differentiating into the cardiac lineage while maintaining the original ability to differentiate into the neural lineage. Notably, the trans-differentiated heart-like cells have dual signatures of neuroectoderm and cardiac mesoderm. This study unveils an in-depth mechanism underlying the trans-differentiation of NSCs and provides a new opportunity and theoretical basis for cardiac regeneration.

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

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

Genome-Wide Identification of Cell Type-Specific Susceptibility Genes for SLE Through the Analysis of RNA Modification-Associated SNPs.

INTRODUCTION: This study aimed to elucidate the functional genes associated with systemic lupus erythematosus (SLE) in various cell types through the utilization of RNAm-SNPs. METHODS: Utilizing large-scale genetic data, we identified associations between RNAm-SNPs and SLE. The association between RNAm-SNPs and bulk and single-cell mRNA expression (eQTL) and protein levels (pQTL) were examined. Mendelian randomization and differential expression analyses were conducted to explore the links between gene expression, protein levels, and SLE. RESULTS: We identified 41 RNAm-SNPs that were significantly associated with SLE. The GWAS signals exhibited notable enrichment in m6A-SNPs and m7G-SNPs. These RNAm-SNPs showed both eQTL and pQTL effects. In our single-cell analysis, 16 RNAm-SNPs exhibited associations with gene expression levels across 13 distinct cell types, including HLA-A, HLA-B, HLA-C, HLA-DQA1, HLA-DQB1, HLA-DRB1 and IRF7. We identified 58 noteworthy associations between the expression levels of 20 genes and SLE across 12 distinct immune cell types. Notably, HLA-DQB1, HLA-DRB1 and IRF7 exhibited abnormalities in CD8+ T cells, IRF7 displayed abnormal expression in CD4+ T cells, while HLA-DRB1 and IRF7 were also distinctly perturbed in natural killer cells. DISCUSSION: This study advances our understanding of the genetic basis of SLE by highlighting the significance of RNAm-SNPs and immune cell gene expression in SLE.

Crosstalk between tumor and microenvironment: Insights from spatial transcriptomics.

Cancer is a dynamic disease, and clonal heterogeneity plays a fundamental role in tumor development, progression, and resistance to therapies. Single-cell and spatial multimodal technologies can provide a high-resolution molecular map of underlying genomic, epigenomic, and transcriptomic alterations involved in inter- and intra-tumor heterogeneity and interactions with the microenvironment. In this review, we provide a perspective on factors driving cancer heterogeneity, tumor evolution, and clonal states. We briefly describe spatial transcriptomic technologies and summarize recent literature that sheds light on the dynamical interactions between tumor states, cell-to-cell communication, and remodeling local microenvironment.

Single-Cell Profiling Uncovers Evolutionary Divergence of Hypocretin/Orexin Neuronal Subpopulations.

Brain nuclei are traditionally defined by their anatomy, activity, and expression of specific markers. The hypothalamus contains discrete neuronal populations that coordinate fundamental behavioral functions, including sleep and wakefulness, in all vertebrates. Particularly, the diverse roles of hypocretin/orexin (Hcrt)-releasing neurons suggest functional heterogeneity among Hcrt neurons. Using single-cell RNA sequencing (scRNA-seq) and high-resolution imaging of the adult male and female zebrafish hypothalamic periventricular zone, we identified 21 glutamatergic and 28 GABAergic cell types. Integration of zebrafish and mouse scRNA-seq revealed evolutionary conserved and divergent hypothalamic cell types. The expression of specific genes, including npvf, which encodes a sleep-regulating neuropeptide, was enriched in subsets of glutamatergic Hcrt neurons in both larval and adult zebrafish. The genetic profile, activity, and neurite processing of the neuronal subpopulation that coexpresses both Hcrt and Npvf (Hcrt+Npvf+) differ from other Hcrt neurons. These interspecies findings provide a unified annotation of hypothalamic cell types and suggest that the heterogeneity of Hcrt neurons enables multifunctionality, such as consolidation of both wake and sleep by the Hcrt- and Npvf-releasing neuronal subpopulation.

HLA-DM and HLA-DO interplay for the peptide editing of HLA class II in healthy tissues and leukemia.

HLA class II antigen presentation is modulated by the activity of the peptide editor HLA-DM and its antagonist HLA-DO, with their interplay controlling the peptide repertoires presented by normal and malignant cells. The role of these molecules in allogeneic hematopoietic cell transplantation (alloHCT) is poorly investigated. Balanced expression of HLA-DM and HLA-DO can influence the presentation of leukemia-associated antigens and peptides targeted by alloreactive T cells, therefore affecting both anti-leukemia immunity and the potential onset of Graft versus Host Disease. We leveraged on a large collection of bulk and single cell RNA sequencing data, available at different repositories, to comprehensively review the level and distribution of HLA-DM and HLA-DO in different cell types and tissues of the human body. The resulting expression atlas will help future investigations aiming to dissect the dual role of HLA class II peptide editing in alloHCT, and their potential impact on its clinical outcome.

Landscape of Interactions between Stromal and Myeloid Cells in Ileal Crohn's Disease; Indications of an Important Role for Fibroblast-Derived CCL-2.

BACKGROUND AND AIMS: Monocyte recruitment in the lamina propria and inflammatory phenotype driven by the mucosal microenvironment is critical for the pathogenesis of inflammatory bowel disease. However, the stimuli responsible remain largely unknown. Recent works have focused on stromal cells, the main steady-state cellular component in tissue, as they produce pro-inflammatory chemokines that contribute to the treatment-resistant nature of IBD. METHODS: We studied the regulation of these processes by examining the communication patterns between stromal and myeloid cells in ileal Crohn's disease (CD) using a complete single-cell whole tissue sequencing analysis pipeline and in vitro experimentation in mesenchymal cells. RESULTS: We report expansion of S4 stromal cells and monocyte-like inflammatory macrophages in the inflamed mucosa and describe interactions that may establish sustained local inflammation. These include expression of CCL2 by S1 fibroblasts to recruit and retain monocytes and macrophages in the mucosa, where they receive signals for proliferation, survival, and differentiation to inflammatory macrophages from S4 stromal cells through molecules such as MIF, IFNγ, and FN1. The overexpression of CCL2 in ileal CD and its stromal origin was further demonstrated in vitro by cultured mesenchymal cells and intestinal organoids in the context of an inflammatory milieu. CONCLUSIONS: Our findings outline an extensive cross-talk between stromal and myeloid cells, which may contribute to the onset and progression of inflammation in ileal Crohn's disease. Understanding the mechanisms underlying monocyte recruitment and polarization, as well as the role of stromal cells in sustaining inflammation, can provide new avenues for developing targeted therapies to treat IBD.

Uncovering underlying physical principles and driving forces of cell differentiation and reprogramming from single-cell transcriptomics.

Recent advances in single-cell sequencing technology have revolutionized our ability to acquire whole transcriptome data. However, uncovering the underlying transcriptional drivers and nonequilibrium driving forces of cell function directly from these data remains challenging. We address this by learning cell state vector fields from discrete single-cell RNA velocity to quantify the single-cell global nonequilibrium driving forces as landscape and flux. From single-cell data, we quantified the Waddington landscape, showing that optimal paths for differentiation and reprogramming deviate from the naively expected landscape gradient paths and may not pass through landscape saddles at finite fluctuations, challenging conventional transition state estimation of kinetic rate for cell fate decisions due to the presence of the flux. A key insight from our study is that stem/progenitor cells necessitate greater energy dissipation for rapid cell cycles and self-renewal, maintaining pluripotency. We predict optimal developmental pathways and elucidate the nucleation mechanism of cell fate decisions, with transition states as nucleation sites and pioneer genes as nucleation seeds. The concept of loop flux quantifies the contributions of each cycle flux to cell state transitions, facilitating the understanding of cell dynamics and thermodynamic cost, and providing insights into optimizing biological functions. We also infer cell-cell interactions and cell-type-specific gene regulatory networks, encompassing feedback mechanisms and interaction intensities, predicting genetic perturbation effects on cell fate decisions from single-cell omics data. Essentially, our methodology validates the landscape and flux theory, along with its associated quantifications, offering a framework for exploring the physical principles underlying cellular differentiation and reprogramming and broader biological processes through high-throughput single-cell sequencing experiments.

Global transcription regulation revealed from dynamical correlations in time-resolved single-cell RNA sequencing.

Single-cell transcriptomics reveals significant variations in transcriptional activity across cells. Yet, it remains challenging to identify mechanisms of transcription dynamics from static snapshots. It is thus still unknown what drives global transcription dynamics in single cells. We present a stochastic model of gene expression with cell size- and cell cycle-dependent rates in growing and dividing cells that harnesses temporal dimensions of single-cell RNA sequencing through metabolic labeling protocols and cel lcycle reporters. We develop a parallel and highly scalable approximate Bayesian computation method that corrects for technical variation and accurately quantifies absolute burst frequency, burst size, and degradation rate along the cell cycle at a transcriptome-wide scale. Using Bayesian model selection, we reveal scaling between transcription rates and cell size and unveil waves of gene regulation across the cell cycle-dependent transcriptome. Our study shows that stochastic modeling of dynamical correlations identifies global mechanisms of transcription regulation. A record of this paper's transparent peer review process is included in the supplemental information.

Beyond the Heartbeat: Single-Cell Omics Redefining Cardiovascular Research.

PURPOSE OF REVIEW: This review aims to explore recent advances in single-cell omics techniques as applied to various regions of the human heart, illuminating cellular diversity, regulatory networks, and disease mechanisms. We examine the contributions of single-cell transcriptomics, genomics, proteomics, epigenomics, and spatial transcriptomics in unraveling the complexity of cardiac tissues. RECENT FINDINGS: Recent strides in single-cell omics technologies have revolutionized our understanding of the heart's cellular composition, cell type heterogeneity, and molecular dynamics. These advancements have elucidated pathological conditions as well as the cellular landscape in heart development. We highlight emerging applications of integrated single-cell omics, particularly for cardiac regeneration, disease modeling, and precision medicine, and emphasize the transformative potential of these technologies to advance cardiovascular research and clinical practice.

Environmental community transcriptomics: strategies and struggles.

Transcriptomics is the study of RNA transcripts, the portion of the genome that is transcribed, in a specific cell, tissue, or organism. Transcriptomics provides insight into gene expression patterns, regulation, and the underlying mechanisms of cellular processes. Community transcriptomics takes this a step further by studying the RNA transcripts from environmental assemblies of organisms, with the intention of better understanding the interactions between members of the community. Community transcriptomics requires successful extraction of RNA from a diverse set of organisms and subsequent analysis via mapping those reads to a reference genome or de novo assembly of the reads. Both, extraction protocols and the analysis steps can pose hurdles for community transcriptomics. This review covers advances in transcriptomic techniques and assesses the viability of applying them to community transcriptomics.

Single-cell transcriptomics identifies aberrant glomerular angiogenic signalling in the early stages of WT1 kidney disease.

WT1 encodes a podocyte transcription factor whose variants can cause an untreatable glomerular disease in early childhood. Although WT1 regulates many podocyte genes, it is poorly understood which of them are initiators in disease and how they subsequently influence other cell-types in the glomerulus. We hypothesised that this could be resolved using single-cell RNA sequencing (scRNA-seq) and ligand-receptor analysis to profile glomerular cell-cell communication during the early stages of disease in mice harbouring an orthologous human mutation in WT1 (Wt1R394W/+). Podocytes were the most dysregulated cell-type in the early stages of Wt1R394W/+ disease, with disrupted angiogenic signalling between podocytes and the endothelium, including the significant downregulation of transcripts for the vascular factors Vegfa and Nrp1. These signalling changes preceded glomerular endothelial cell loss in advancing disease, a feature also observed in biopsy samples from human WT1 glomerulopathies. Addition of conditioned medium from murine Wt1R394W/+ primary podocytes to wild-type glomerular endothelial cells resulted in impaired endothelial looping and reduced vascular complexity. Despite the loss of key angiogenic molecules in Wt1R394W/+ podocytes, the pro-vascular molecule adrenomedullin was upregulated in Wt1R394W/+ podocytes and plasma and its further administration was able to rescue the impaired looping observed when glomerular endothelium was exposed to Wt1R394W/+ podocyte medium. In comparative analyses, adrenomedullin upregulation was part of a common injury signature across multiple murine and human glomerular disease datasets, whilst other gene changes were unique to WT1 disease. Collectively, our study describes a novel role for altered angiogenic signalling in the initiation of WT1 glomerulopathy. We also identify adrenomedullin as a proangiogenic factor, which despite being upregulated in early injury, offers an insufficient protective response due to the wider milieu of dampened vascular signalling that results in endothelial cell loss in later disease. © 2024 The Author(s). The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Multi-omics analyses reveal aberrant differentiation trajectory with WNT1 loss-of-function in type XV osteogenesis imperfecta.

Osteogenesis imperfecta (OI) is a group of severe genetic bone disorders characterized by congenital low bone mass, deformity, and frequent fractures. Type XV OI is a moderate to severe form of skeletal dysplasia caused by WNT1 variants. In this cohort study from southern China, we summarized the clinical phenotypes of patients with WNT1 variants and found that the proportion of type XV patients was around 10.3% (25 out of 243) with a diverse spectrum of phenotypes. Functional assays indicated that variants of WNT1 significantly impaired its secretion and effective activity, leading to moderate to severe clinical manifestations, porous bone structure, and enhanced osteoclastic activities. Analysis of proteomic data from human skeleton indicated that the expression of SOST (sclerostin) was dramatically reduced in type XV patients compared to patients with COL1A1 quantitative variants. Single-cell transcriptome data generated from human tibia samples of patients diagnosed with type XV OI and leg-length discrepancy, respectively, revealed aberrant differentiation trajectories of skeletal progenitors and impaired maturation of osteocytes with loss of WNT1, resulting in excessive CXCL12+ progenitors, fewer mature osteocytes, and the existence of abnormal cell populations with adipogenic characteristics. The integration of multi-omics data from human skeleton delineates how WNT1 regulates the differentiation and maturation of skeletal progenitors, which will provide a new direction for the treatment strategy of type XV OI and relative low bone mass diseases such as early onset osteoporosis.

Osteogenesis imperfecta is a rare disease characterized by low bone mass, frequent fractures, and long bone deformity. Type XV osteogenesis imperfect is an autosomal recessive disorder caused by WNT1 variants, while heterozygous variants of WNT1 result in early onset osteoporosis. In this cohort study, we summarized the clinical features of 25 patients diagnosed with type XV osteogenesis imperfect. The WNT1 variants were confirmed by genetic test. Molecular assays were conducted to reveal the impact of variants on WNT1 protein activity and bone structure. We then compared the protein levels in bone tissues isolated from the type XV patients and patients with mild deformity using proteomic method, and found that the expression of SOST, mainly produced by mature osteoblasts and osteocytes, was dramatically reduced in type XV patients. We further compared the global mRNA expression levels in the skeletal cells using single-cell RNA sequencing. Analyses of these data indicated that more immature progenitors were identified and maturation of osteocytes was impaired with WNT1 loss-of-function. Our study helps to understand the underlying pathogenesis of type XV osteogenesis imperfecta.

Single-cell investigation of lead toxicity from neurodevelopment to neurodegeneration: Current review and future opportunities.

Human exposure to the metal lead (Pb) is prevalent and associated with adverse neurodevelopmental and neurodegenerative outcomes. Pb disrupts normal brain function by inducing oxidative stress and neuroinflammation, altering cellular metabolism, and displacing essential metals. Prior studies on the molecular impacts of Pb have examined bulk tissues, which collapse information across all cell types, or in targeted cells, which are limited to cell autonomous effects. These approaches are unable to represent the complete biological implications of Pb exposure because the brain is a cooperative network of highly heterogeneous cells, with cellular diversity and proportions shifting throughout development, by brain region, and with disease. New technologies are necessary to investigate whether Pb and other environmental exposures alter cell composition in the brain and whether they cause molecular changes in a cell-type-specific manner. Cutting-edge, single-cell approaches now enable research resolving cell-type-specific effects from bulk tissues. This article reviews existing Pb neurotoxicology studies with genome-wide molecular signatures and provides a path forward for the field to implement single-cell approaches with practical recommendations.