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Stereo-cell coupled with single-cell transcriptomics identifies a transitional metabolic state in maturing skeletal muscle myofibers.
Identification of skeletal muscle fiber types and metabolic reprogramming are crucial for postnatal muscle maturation, but high-resolution metabolism and spatial heterogeneity of muscle fibers in mid-maturation remain poorly understood. Our study performed single-cell RNA sequencing (scRNA-seq) and single-cell nuclear RNA sequencing (snRNA-seq) on five hind limb muscles from 5-week-old mice, combined with Stereo-cell at single muscle fiber resolution, to elucidate myofiber subtype maturation and its metabolic changes. Integrating scRNA-seq and snRNA-seq data, a comprehensive mouse skeletal muscle cell atlas was constructed, demonstrating the complementary advantages of the two techniques in capturing interstitial cells and multinucleated muscle fibers. Our analysis resolved a continuous maturational lineage from type I to IIB myonuclei (IIB_1-3). Notably, the IIB_3 myonuclei subtype exhibited a dual hypermetabolic phenotype, with increased oxidative phosphorylation (OXPHOS) and glycolytic activity, which differs from the purely glycolytic phenotype observed in adult mice. Stereo-cell further validated this transitional metabolic state and revealed spatial heterogeneity within individual IIB myofibers, with localized high-oxidation regions. Furthermore, we observed a mixed myofiber phenotype, with subtype-specific myosin heavy chain expression enriched at the myofiber terminals, indicating directional transformation of myofiber during maturation. In summary, this study reveals a previously undescribed transitional metabolic feature of IIB-type myofiber during postnatal muscle maturation and elucidates the spatial metabolic heterogeneity of myofiber, providing new insights into the regulatory mechanisms of skeletal muscle developmental plasticity and metabolic specialization.
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Electroacupuncture Slows Experimental Myopia Progression by Improving Retinal Mitochondrial Function: A Study Based on Single-Cell RNA Sequencing.
This study aimed to establish a complete atlas of retinal cells in lens-induced myopia (LIM) and electroacupuncture (EA) intervention by single-cell RNA sequencing (scRNA-seq) and to explore the potential mechanism of EA in improving experimental myopia progression in guinea pigs. scRNA-seq is used to assess changes in individual cellular gene levels in the retina of LIM- and EA-treated guinea pigs. In addition, the role of EA in slowing myopia progression by improving retinal mitochondrial function is further investigated. scRNA-seq identified ten cell clusters in the retina of LIM and EA guinea pigs and mitochondrial respiratory chain-related genes in Cones and Muller-glia cells-Cytochrome oxidase subunit III (COX3), NADH dehydrogenase subunit 4 (ND4), and NADH dehydrogenase subunit 2 (ND2) are closely related to lens-induced myopia. A comprehensive atlas in the retina of LIM and EA guinea pigs at a single-cell level is established, and the positive role of EA in improving retinal mitochondrial function to slow the experimental myopia progression in guinea pigs is revealed.
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Single-cell brain atlas of Parkinson's disease mouse model.
Parkinson's disease (PD) is a neurodegenerative disease, leading to the impairment of movement execution. PD pathogenesis has been largely investigated, either limited to bulk transcriptomic levels or at certain cell types, which failed to capture the cellular heterogeneity and intrinsic interplays among distinct cell types. Here, we report the application of single-nucleus RNA-seq on midbrain, striatum, and cerebellum of the α-syn-A53T mouse, a well-established PD mouse model, and matched controls, generating the first single cell transcriptomic atlas for the PD model mouse brain composed of 46,174 individual cells. Additionally, we comprehensively depicte the dysfunctions in PD pathology, covering the elevation of NF-κB activity, the alteration of ion channel components, the perturbation of protein homeostasis network, and the dysregulation of glutamatergic signaling. Notably, we identify a variety of cell types closely associated with PD risk genes. Taken together, our study provides valuable resources to systematically dissect the molecular mechanism of PD pathogenesis at the single-cell resolution, which facilitates the development of novel approaches for diagnosis and therapies against PD.
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Single-cell RNA sequencing unveils dynamic transcriptional profiles during the process of donkey spermatogenesis and maturation.
INTRODUCTION: With the increasing demand for donkey production, there has been a growing focus on the breeding of donkeys. However, our current understanding of the mechanisms underlying spermatogenesis and maturation in donkeys during reproduction remains limited. OBJECTIVES: This study is to provide a comprehensive single-cell landscape analysis of spermatogenesis and maturation in donkeys. METHODS: In this study, we employed single-cell RNA sequencing to investigate cell composition, gene expression patterns, and regulatory roles during spermatogenesis and maturation in donkeys. RESULTS: The expression patterns of CDK1, CETN3, and UBE2J1 were found to be indicative of specific germ cells during donkey spermatogenesis. Additionally, the DEFB121, ELSPBP1, and NPC2 genes were specifically identified in the principal cells of the donkey epididymis. CONCLUSIONS: We performed single-cell RNA sequencing to analyze the cellular composition and spatial distribution of donkey testis and epididymis, thereby generating comprehensive transcriptional atlases at the single-cell resolution.
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Whole organism snRNA-seq reveals systemic peripheral changes in Alzheimer's Disease fly models.
Peripheral tissues become disrupted in Alzheimer's Disease (AD). However, a comprehensive understanding of how the expression of AD-associated toxic proteins, Aβ42 and Tau, in neurons impacts the periphery is lacking. Using Drosophila, a prime model organism for studying aging and neurodegeneration, we generated the Alzheimer's Disease Fly Cell Atlas (AD-FCA): whole-organism single-nucleus transcriptomes of 219 cell types from adult flies neuronally expressing human Aβ42 or Tau. In-depth analyses and functional data reveal impacts on peripheral sensory neurons by Aβ42 and on various non-neuronal peripheral tissues by Tau, including the gut, fat body, and reproductive system. This novel AD atlas provides valuable insights into potential biomarkers and the intricate interplay between the nervous system and peripheral tissues in response to AD-associated proteins.
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Metabolic-immune interactions in gastric cancer T cells: A single-cell atlas for prognostic biomarker identification.
Metabolic alterations and immune dysfunction within the gastric tumor microenvironment critically drive gastric cancer (GC) progression and therapeutic resistance. Although single-cell RNA sequencing (scRNA-seq) has unveiled cellular heterogeneity in GC, the metabolic landscapes of tumor cells and their interplay with immune components remain underexplored. By integrating scRNA-seq data from 35,633 cells across 23 GC tissues (GSE150290), bulk RNA-seq data from UCSC Xena, and two independent microarray cohorts (GSE26899, GSE62254), we systematically characterized metabolic heterogeneity and identified immune-related prognostic biomarkers. Reclustering of malignant epithelial cells revealed distinct metabolic phenotypes, with the citrate cycle and oxidative phosphorylation pathways emerging as key drivers of intratumoral diversity and T cell differentiation. Through machine learning and survival analyses, we discovered a novel risk score model composed of 6 T cell differentiation signatures, which stratified patients into high- and low-risk groups with significant differences in overall survival. Notably, this model outperformed traditional clinicopathological factors in predicting prognosis, validated in both bulk RNA-seq and microarray datasets. Immunohistochemistry further confirmed the prognostic value of key regulatory proteins (RGS1, CXCR4, CTLA4, ARPP19, ZNRF1, and ZNF207). Our findings highlight the metabolic immune crosstalk in GC and provide a promising biomarker panel for precision risk stratification and potential immunotherapeutic targets.
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miRge - A Multiplexed Method of Processing Small RNA-Seq Data to Determine MicroRNA Entropy.
Small RNA RNA-seq for microRNAs (miRNAs) is a rapidly developing field where opportunities still exist to create better bioinformatics tools to process these large datasets and generate new, useful analyses. We built miRge to be a fast, smart small RNA-seq solution to process samples in a highly multiplexed fashion. miRge employs a Bayesian alignment approach, whereby reads are sequentially aligned against customized mature miRNA, hairpin miRNA, noncoding RNA and mRNA sequence libraries. miRNAs are summarized at the level of raw reads in addition to reads per million (RPM). Reads for all other RNA species (tRNA, rRNA, snoRNA, mRNA) are provided, which is useful for identifying potential contaminants and optimizing small RNA purification strategies. miRge was designed to optimally identify miRNA isomiRs and employs an entropy based statistical measurement to identify differential production of isomiRs. This allowed us to identify decreasing entropy in isomiRs as stem cells mature into retinal pigment epithelial cells. Conversely, we show that pancreatic tumor miRNAs have similar entropy to matched normal pancreatic tissues. In a head-to-head comparison with other miRNA analysis tools (miRExpress 2.0, sRNAbench, omiRAs, miRDeep2, Chimira, UEA small RNA Workbench), miRge was faster (4 to 32-fold) and was among the top-two methods in maximally aligning miRNAs reads per sample. Moreover, miRge has no inherent limits to its multiplexing. miRge was capable of simultaneously analyzing 100 small RNA-Seq samples in 52 minutes, providing an integrated analysis of miRNA expression across all samples. As miRge was designed for analysis of single as well as multiple samples, miRge is an ideal tool for high and low-throughput users. miRge is freely available at http://atlas.pathology.jhu.edu/baras/miRge.html.
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Persistent transcriptional programmes are associated with remote memory.
The role of gene expression during learning and in short-term memories has been studied extensively1-3, but less is known about remote memories, which can persist for a lifetime4. Here we used long-term contextual fear memory as a paradigm to probe the single-cell gene expression landscape that underlies remote memory storage in the medial prefrontal cortex. We found persistent activity-specific transcriptional alterations in diverse populations of neurons that lasted for weeks after fear learning. Out of a vast plasticity-coding space, we identified genes associated with membrane fusion that could have important roles in the maintenance of remote memory. Unexpectedly, astrocytes and microglia also acquired persistent gene expression signatures that were associated with remote memory, suggesting that they actively contribute to memory circuits. The discovery of gene expression programmes associated with remote memory engrams adds an important dimension of activity-dependent cellular states to existing brain taxonomy atlases and sheds light on the elusive mechanisms of remote memory storage.
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Integrated analysis of single-cell and bulk transcriptomes uncovers clinically relevant molecular subtypes in human prostate cancer.
OBJECTIVE: Prostate cancer (PCa) is a complex disease characterized by diverse cellular ecosystems within the tumor microenvironment (TME) and high tumor heterogeneity, which challenges clinically stratified management and reinforces the need for novel strategies to fight against castration-resistant PCa (CRPC). METHODS: We performed single-cell RNA sequencing (scRNA-seq) on 10 untreated primary PCa tissues and integrated public scRNA-seq resources from three normal prostate tissues, two untreated primary PCa tissues, and six CRPC tumors to portray a comprehensive cellular and molecular interaction atlas of PCa. We further integrated the single-cell and bulk transcriptomes of PCa to establish a molecular classification system. RESULTS: scRNA-seq profiles revealed substantial inter- and intra-tumoral heterogeneity across different cell subpopulations in untreated PCa and CRPC tumors. In the malignant epithelial reservoir, cells evolved along decoupled paths in treatment-naive PCa and CRPC tumors, and distinct transcriptional reprogramming processes were activated, highlighting anti-androgen therapy-induced lineage plasticity. Based on the specifically expressed markers of the epithelial subpopulations, we conducted unsupervised clustering analysis in The Cancer Genome Atlas prostate adenocarcinoma (TCGA-PRAD) cohort and identified three molecularly and clinically distinct subtypes. The C1 subtype, characterized by high enrichment of CRPC-enriched epithelial cells, had a high risk of rapid development of anti-androgen resistance and might require active surveillance and additional promising intervention treatments, such as integrin A3 (ITGA3) + integrin B1 (ITGB1) inhibition. The C2 subtype resembled the immune-modulated subtype that was most likely to benefit from anti-LAG3 immunotherapy. The C3 subtype had a favorable prognosis. CONCLUSIONS: Our study provides a comprehensive and high-resolution landscape of the intricate architecture of the PCa TME, and our trichotomic molecular taxonomy could help facilitate precision oncology.
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A cell atlas of adult muscle precursors uncovers early events in fibre-type divergence in Drosophila.
In Drosophila, the wing disc-associated muscle precursor cells give rise to the fibrillar indirect flight muscles (IFM) and the tubular direct flight muscles (DFM). To understand early transcriptional events underlying this muscle diversification, we performed single-cell RNA-sequencing experiments and built a cell atlas of myoblasts associated with third instar larval wing disc. Our analysis identified distinct transcriptional signatures for IFM and DFM myoblasts that underlie the molecular basis of their divergence. The atlas further revealed various states of differentiation of myoblasts, thus illustrating previously unappreciated spatial and temporal heterogeneity among them. We identified and validated novel markers for both IFM and DFM myoblasts at various states of differentiation by immunofluorescence and genetic cell-tracing experiments. Finally, we performed a systematic genetic screen using a panel of markers from the reference cell atlas as an entry point and found a novel gene, Amalgam which is functionally important in muscle development. Our work provides a framework for leveraging scRNA-seq for gene discovery and details a strategy that can be applied to other scRNA-seq datasets.