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Identification of lactylation-associated immune and metabolic regulators in bladder cancer via integrated bulk and single-cell transcriptomics.
BACKGROUND: Lactate-driven metabolic reprogramming and histone lactylation play pivotal roles in bladder cancer (BLCA) progression, yet their underlying mechanisms and regulatory genes remain poorly understood. METHODS: Using transcriptomic data from The Cancer Genome Atlas (TCGA), we identified lactylation-associated genes and constructed a prognostic signature. Comprehensive bioinformatics analyses were conducted to assess immune infiltration, tumor microenvironment characteristics, and the lactylation landscape at the single-cell level. Furthermore, we performed in vitro experiments to evaluate the biological functions of key lactylation-related genes in BLCA cells. RESULTS: Six lactylation-related hub genes were identified, among which FASN and RUNX2 were significantly upregulated in BLCA and associated with poor prognosis. Single-cell analyses revealed elevated lactylation signatures in tumor epithelial and immune cells. Knockdown of FASN or RUNX2 in BLCA cell lines significantly suppressed cell proliferation, induced apoptosis, and reduced intracellular lactate levels. Correspondingly, global protein lactylation was diminished, with dominant modification signals observed around 40 kDa, indicating a potential set of non-histone proteins as key functional targets. CONCLUSIONS: Our study highlights a metabolic-enzymatic axis wherein FASN and RUNX2 regulate lactate-driven protein lactylation in BLCA. These findings provide new insights into the non-histone functions of lactylation and suggest potential therapeutic targets at the intersection of metabolism and tumor immunity.
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KLF4 orchestrates a Ccl2+ fibroblast-mediated inflammatory network driving preterm birth.
BACKGROUND: Preterm birth (PTB) remains the leading cause of neonatal mortality and long-term complications, yet its molecular mechanisms are incompletely understood. Fibroblasts, as critical components of the gestational microenvironment, have an undefined role in PTB pathogenesis. METHODS: This study employed single-cell RNA sequencing (scRNA-seq) datasets from murine preterm birth models (GSE200289 and E-MTAB-11491), processed using Seurat and Harmony for clustering and integration, to analyze cellular heterogeneity. This was integrated with Mendelian randomization (MR) using eQTLs from FinnGen and IEU GWAS databases as instrumental variables, and validated through functional experiments including LPS-induced placental explant cultures, qRT-PCR, western blotting, immunohistochemistry, and an in vivo rat intrauterine infection model with AAV-shKLF4 knockdown. RESULTS: We first established a single-cell transcriptomic atlas of preterm mice, identifying nine cell clusters, among which the Ccl2+ fibroblast subpopulation (Ccl2+fib) exhibited significant expansion under pathological conditions. MR analysis identified KLF4 as a genetic risk factor for PTB (OR = 1.32, 95% CI: 1.12-1.56), with reverse MR confirming the absence of reverse causality. Clinical validation revealed KLF4-specific upregulation in peripheral blood and placental tissues of PTB patients. Functional studies demonstrated dose-dependent KLF4 upregulation in LPS-induced placental inflammation, while KLF4 knockdown suppressed TNF-α and IL-1β secretion and reduced apoptosis. In a rat intrauterine infection model, KLF4 knockdown decreased LPS-induced preterm birth rates from 65% to 20%, accompanied by significantly reduced fetal stillbirth rates. CONCLUSION: This study reveals that the fibroblast subpopulation Ccl2+fib contributes to preterm birth through a KLF4-dependent inflammatory regulatory network. KLF4 downregulation significantly reduces infection-induced preterm birth rates and adverse pregnancy outcomes, suggesting that KLF4 is a critical therapeutic target for preterm birth.
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CanCellVar: A database for single-cell variants map in human cancer.
Numerous variants, including both single-nucleotide variants (SNVs) in DNA and A>G RNA edits in mRNA as essential drivers of cellular proliferation and tumorigenesis, are commonly associated with cancer progression and growth. Thus, mining and summarizing single-cell variants will provide a refined and higher-resolution view of cancer and further contribute to precision medicine. Here, we established a database, CanCellVar, which aims to provide and visualize the comprehensive atlas of single-cell variants in tumor microenvironment. The current CanCellVar identified ∼3 million variants (∼1.4 million SNVs and ∼1.4 million A>G RNA edits) involved in 2,754,531 cells of 5 major cell types across 37 cancer types. CanCellVar provides the basic annotation information as well as cellular and molecular function properties of variants. In addition, the clinical relevance of variants can be obtained including tumor grade, treatment, metastasis, and others. Several flexible tools were also developed to aid retrieval and to analyze cell-cell interactions, gene expression, cell-development trajectories, regulation, and molecular structure affected by variants. Collectively, CanCellVar will serve as a valuable resource for investigating the functions and characteristics of single-cell variations and their roles in human tumor evolution and treatment.
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Single-cell and spatially resolved transcriptomics for liver biology.
Single-cell transcriptomics enables the identification of rare cell types and the inference of state transitions, whereas spatially resolved transcriptomics allows the quantification of cells and genes in the context of tissues. The recent progress in these new technologies is improving our understanding of the cell landscape and its roles in diseases. Here, we review key biological insights into liver homeostasis, development, regeneration, chronic liver disease, and cancer obtained from single-cell and spatially resolved transcriptomics. We highlight recent progress in the liver cell atlas that characterizes the comprehensive cellular composition; diversity and function; the spatial architecture such as liver zonation, cell communication, and proximity; the cell identity conversion and cell-specific alterations that are associated with liver pathology; and new therapeutic targets. We further discuss outstanding challenges, advanced experimental technologies, and computational methods that help to address these challenges.
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Integrated spatial transcriptome and metabolism study reveals metabolic heterogeneity in human injured brain.
Single-cell transcriptomics can provide quantitative molecular signatures for large, unbiased samples of the diverse cell types in the brain. With the advances of multi-omics datasets, a major challenge is to validate and integrate results into a biological understanding of spatial organization and functional orientation. Here, we generate spatial transcriptomes and metabolites from six patients with brain trauma with surgical samples. The resulting spatial marker gene, which is highly replicable across analysis methods, sequencing technologies, and modalities, is a comprehensive molecular marker of the diverse metabolic changes in human injured brains. The atlas includes an area of lipid peroxidation that resembles injured neurons in the brain. We further discover imbalanced myo-inositol and myo-inositol phosphate and related spatial markers. Our results highlight the complex transcriptomic regulation and metabolic alterations in the injured brain and will directly enable the design of reagents to target specific genes in the human brain for functional analysis.
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Deciphering the dynamic single-cell transcriptional landscape in the ocular surface ectoderm differentiation system.
The ocular surface ectoderm (OSE) is essential for the development of the ocular surface, yet the molecular mechanisms driving its differentiation are not fully understood. In this study, we used single-cell transcriptomic analysis to explore the dynamic cellular trajectories and regulatory networks during the in vitro differentiation of embryonic stem cells (ESCs) into the OSE lineage. We identified nine distinct cell subpopulations undergoing differentiation along three main developmental branches: neural crest, neuroectodermal, and surface ectodermal lineages. Key marker gene expression, transcription factor activity, and signaling pathway insights revealed stepwise transitions from undifferentiated ESCs to fate-specified cell types, including a PAX6 + TP63 + population indicative of OSE precursors. Comparative analysis with mouse embryonic development confirmed the model's accuracy in mimicking in vivo epiblast-to-surface ectoderm dynamics. By integrating temporal dynamics of transcription factor activation and cell-cell communication, we constructed a comprehensive molecular atlas of the differentiation pathway from ESCs to distinct ectodermal lineages. This study provides new insights into the cellular heterogeneity and regulatory mechanisms of OSE development, aiding the understanding of ocular surface biology and the design of cell-based therapies for ocular surface disorders.
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Deciphering mitochondrial dysfunction in keratoconus: Insights into ACSL4 from machine learning-based bulk and single-cell transcriptome analyses and experimental validation.
Keratoconus (KC) is a prevalent ectatic corneal disease and the leading cause of corneal transplantation globally. Despite evidence of mitochondrial abnormalities in KC, the underlying mechanisms remain unclear. Our aim was to investigate the role of mitochondrial dysfunction in this pathological condition. Based on transcriptomics datasets of KC, mitochondria-related differentially expressed genes (mDEGs) were identified and analyzed for potential functional pathways, protein-protein interaction (PPI), and gene regulatory networks. Hub genes were further screened and validated by multiple machine learning (ML) algorithms, followed by a comprehensive visualization of single-cell atlas and immune landscape. Additionally, bioinformatic results were validated through quantitative PCR, Western blot, and transcriptomics analysis in an in vitro KC model based on matrix stiffness using human stromal keratocytes. In total, 104 mDEGs were identified, enriched in pathways related to oxidative stress, apoptotic mitochondrial changes, ferroptosis, and inflammatory responses. Nine characteristic genes (CYP24A1, ACSL4, ACADL, HELZ2, AMT, DEPTOR, TUBA1A, TYMS, and ACSL5) were selected and validated using multiple ML models. Single cell sequencing data highlighted ACSL4 as the most promising biomarker, primarily expressed in corneal stromal cells (CSCs). Immune infiltration analysis revealed that ACSL4 was positively associated with monocytes and negatively correlated with eosinophils in KC. In cellular experiments, ACSL4 expression was significantly upregulated in response to decreased substrate stiffness, suggesting its critical role in KC development. These findings suggest a mitochondrial-related molecular mechanism implicated in KC pathogenesis. The identified pivotal biomarker ACSL4 provides a novel framework for future mechanistic and therapeutic studies of KC.
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Single Cell Transcriptomic Analysis Reveals Organ Specific Pericyte Markers and Identities.
Pericytes are mesenchymal-derived mural cells that wrap around capillaries and directly contact endothelial cells. Present throughout the body, including the cardiovascular system, pericytes are proposed to have multipotent cell-like properties and are involved in numerous biological processes, including regulation of vascular development, maturation, permeability, and homeostasis. Despite their physiological importance, the functional heterogeneity, differentiation process, and pathological roles of pericytes are not yet clearly understood, in part due to the inability to reliably distinguish them from other mural cell populations. Our study focused on identifying pericyte-specific markers by analyzing single-cell RNA sequencing data from tissue-specific mouse pericyte populations generated by the Tabula Muris Senis. We identified the mural cell cluster in murine lung, heart, kidney, and bladder that expressed either of two known pericyte markers, Cspg4 or Pdgfrb. We further defined pericytes as those cells that co-expressed both markers within this cluster. Single-cell differential expression gene analysis compared this subset with other clusters that identified potential pericyte marker candidates, including Kcnk3 (in the lung); Rgs4 (in the heart); Myh11 and Kcna5 (in the kidney); Pcp4l1 (in the bladder); and Higd1b (in lung and heart). In addition, we identified novel markers of tissue-specific pericytes and signaling pathways that may be involved in maintaining their identity. Moreover, the identified markers were further validated in Human Lung Cell Atlas and human heart single-cell RNAseq databases. Intriguingly, we found that markers of heart and lung pericytes in mice were conserved in human heart and lung pericytes. In this study, we, for the first time, identified specific pericyte markers among lung, heart, kidney, and bladder and reveal differentially expressed genes and functional relationships between mural cells.
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Identification of spatially associated subpopulations by combining scRNAseq and sequential fluorescence in situ hybridization data.
How intrinsic gene-regulatory networks interact with a cell's spatial environment to define its identity remains poorly understood. We developed an approach to distinguish between intrinsic and extrinsic effects on global gene expression by integrating analysis of sequencing-based and imaging-based single-cell transcriptomic profiles, using cross-platform cell type mapping combined with a hidden Markov random field model. We applied this approach to dissect the cell-type- and spatial-domain-associated heterogeneity in the mouse visual cortex region. Our analysis identified distinct spatially associated, cell-type-independent signatures in the glutamatergic and astrocyte cell compartments. Using these signatures to analyze single-cell RNA sequencing data, we identified previously unknown spatially associated subpopulations, which were validated by comparison with anatomical structures and Allen Brain Atlas images.
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Cell-type brain-region specific changes in prefrontal cortex of a mouse model of alcohol dependence.
The prefrontal cortex is a crucial regulator of alcohol drinking, and dependence, and other behavioral phenotypes associated with AUD. Comprehensive identification of cell-type specific transcriptomic changes in alcohol dependence will improve our understanding of mechanisms underlying the excessive alcohol use associated with alcohol dependence and will refine targets for therapeutic development. We performed single nucleus RNA sequencing (snRNA-seq) and Visium spatial gene expression profiling on the medial prefrontal cortex (mPFC) obtained from C57BL/6 J mice exposed to the two-bottle choice-chronic intermittent ethanol (CIE) vapor exposure (2BC-CIE, defined as dependent group) paradigm which models phenotypes of alcohol dependence including escalation of alcohol drinking. Gene co-expression network analysis and differential expression analysis identified highly dysregulated co-expression networks in multiple cell types. Dysregulated modules and their hub genes suggest novel understudied targets for studying molecular mechanisms contributing to the alcohol dependence state. A subtype of inhibitory neurons was the most alcohol-sensitive cell type and contained a downregulated gene co-expression module; the hub gene for this module is Cpa6, a gene previously identified by GWAS to be associated with excessive alcohol consumption. We identified an astrocytic Gpc5 module significantly upregulated in the alcohol-dependent group. To our knowledge, there are no studies linking Cpa6 and Gpc5 to the alcohol-dependent phenotype. We also identified neuroinflammation related gene expression changes in multiple cell types, specifically enriched in microglia, further implicating neuroinflammation in the escalation of alcohol drinking. Here, we present a comprehensive atlas of cell-type specific alcohol dependence mediated gene expression changes in the mPFC and identify novel cell type-specific targets implicated in alcohol dependence.