Single-Cell Sequencing of Brain Cell Transcriptomes and Epigenomes

Investigating causal relationships between gene expression and major depressive disorder via brain bulk-tissue and cell type-specific eQTL: A Mendelian randomization and Bayesian colocalization study

BACKGROUND

Major depressive disorder (MDD) is a highly prevalent psychiatric disorder with complex genetic underpinnings. While genome-wide association studies (GWAS) have identified multiple risk loci, pinpointing causal genes within the human brain remains challenging, particularly given the regulatory complexity across different cell types.

METHODS

We performed summary data-based MR (SMR) and Bayesian colocalization analyses by integrating bulk-tissue eQTL data from 888 individuals with single-cell eQTL datasets from 192 donors representing major brain cell types (excitatory and inhibitory neurons, astrocytes, microglia, oligodendrocytes, OPCs/COPs, endothelial cells, and pericytes). GWAS summary statistics for MDD (170,756 cases and 329,443 controls) were used to assess the causal impact of gene expression. Sensitivity analyses, including the heterogeneity in dependent instruments (HEIDI) test and Steiger filtering, ensured robust inference.

RESULTS

In bulk tissue analyses, five genes (BTN3A2, SLC12A5, AREL1, GMPPB, and ZNF660) emerged as having robust causal evidence for MDD, displaying consistent MR signals and strong colocalization. Cell type-specific analyses revealed additional candidate genes in excitatory neurons (FLOT1, AL450423.1), astrocytes (AL121821.1), and oligodendrocytes (YLPM1, COP1).

CONCLUSION

Our integrative approach reveals that causal gene expression profiles differ markedly between bulk-tissue and specific brain cell types, emphasizing cellular heterogeneity in MDD pathogenesis and informing precision therapeutic strategies. These findings underscore the necessity of considering cell type-specific gene regulation when developing therapeutic interventions for MDD.

Gut microbiome, a potential modulator of neuroepigenome

Gut microbiome has a considerable impact on the central nervous system via the "gut-brain axis." Neuroepigenome emerges as the interface between environment and genes, potentially help conveying the signals derived from the microbiome to the brain tissue. While only a limited number of studies have implicated epigenetic roles in the gut-brain axis, this review explores how gut microbiome might impact various brain-based epigenetic mechanisms, including DNA methylation, histone modification, ncRNA and RNA methylation, notably in the context of the specific neural complications. Among the epigenetic mechanisms, histone acetylation was most well-studied with respect to its relationships with gut microbiome, exerting a dynamic influence on gene expression in the brain. Furthermore, the pathways connecting gut bacteria to neuroepigenome were summarized, highlighting the roles of metabolites such as butyrate, propionate, acetate, lactate, and folate. Of particular interest, the roles of butyrate are emphasized due to their outstanding inhibitory activity towards histone deacetylases (HDACs), among other mechanisms. It is worth noting that some indirect gut-brain pathways may also be associated with the interplay between microbiome and neuroepigenome, while IL-6 has been found to effectively transmit microbe-derived signals to histone methylation in brains. Finally, we recapitulate the future perspectives critical to understanding this gut-brain crosstalk, such as clarifying the cause-and-effect relationship, bacterial cross-feeding within the gut, and the mechanisms underlying the site-specific histone modification in the brain. Together, this review attempts to consolidate our current knowledge about the "microbiome-neuroepigenome interplay" and propose a conceptual pathway to decipher the gut-brain axis in various neurological conditions.

Single-Cell RNA Sequencing Outperforms Single-Nucleus RNA Sequencing in Analyzing Pancreatic Cell Diversity and Gene Expression in Goats

The objective of this study was to determine whether single-cell RNA sequencing (scRNA-seq) or single-nucleus RNA sequencing (snRNA-seq) was more effective for studying the goat pancreas. Pancreas tissues from three healthy 10-day-old female Xiangdong black goats were processed into single-cell and single-nucleus suspensions. These suspensions were then used to compare cellular composition and gene expression levels following library construction and sequencing. Both scRNA-seq and snRNA-seq were eligible for primary analysis but produced different cell identification profiles in pancreatic tissue. Both methods successfully annotated pancreatic acinar cells, ductal cells, alpha cells, beta cells, and endothelial cells. However, pancreatic stellate cells, immune cells, and delta cells were uniquely annotated by scRNA-seq, while pancreatic stem cells were uniquely identified by snRNA-seq. Furthermore, the genes related to digestive enzymes showed a higher expression in scRNA-seq than in snRNA-seq. In the present study, scRNA-seq detected a great diversity of pancreatic cell types and was more effective in profiling key genes than snRNA-seq, demonstrating that scRNA-seq was better suited for studying the goat pancreas. However, the choice between scRNA-seq and snRNA-seq should consider the sample compatibility, technical differences, and experimental objectives.

Advances in Microfluidic Single-Cell RNA Sequencing and Spatial Transcriptomics

The development of micro- and nano-fabrication technologies has greatly advanced single-cell and spatial omics technologies. With the advantages of integration and compartmentalization, microfluidic chips are capable of generating high-throughput parallel reaction systems for single-cell screening and analysis. As omics technologies improve, microfluidic chips can now integrate promising transcriptomics technologies, providing new insights from molecular characterization for tissue gene expression profiles and further revealing the static and even dynamic processes of tissues in homeostasis and disease. Here, we survey the current landscape of microfluidic methods in the field of single-cell and spatial multi-omics, as well as assessing their relative advantages and limitations. We highlight how microfluidics has been adapted and improved to provide new insights into multi-omics over the past decade. Last, we emphasize the contributions of microfluidic-based omics methods in development, neuroscience, and disease mechanisms, as well as further revealing some perspectives for technological advances in translational and clinical medicine.

Established and emerging roles of protein kinases in regulating primary sensory neurons in injury-and inflammation-associated pain

INTRODUCTION

Recent seminal neuroscience research has significantly increased our knowledge on cellular and molecular responses of various cells in the pain pathway to peripheral nerve injuries and inflammatory processes. Transcriptomic and epigenetic analysis of primary sensory neurons (PSNs) in animal models of peripheral injuries revealed new insights into altered gene expression profiles and epigenetic modifications, which, via increasing spinal nociceptive input, lead to the development of pain. Among the various classes of molecules involved in driving differential gene expression, protein kinases, the enzymes that catalyze the phosphorylation of molecules, are emerging to control histone modification and chromatin remodeling needed for the alteration in transcriptional activity.

AREAS COVERED

Here, we focused on how protein kinases contribute to transcriptomic changes and pathways of induced reprogramming within PSNs upon peripheral nerve injury and inflammation. We conducted systematic literature search across multiple databases, including PubMed, NIH ClinicalTrials.gov portal and GEOData from 1980 to 2024 and compared protein kinase expression frequencies between publicly available RNA sequencing datasets of PSNs and investigated differences in protein kinase expression levels after peripheral nerve injury.

EXPERT OPINION

Novel findings support a new concept that protein kinases constitute regulatory hubs of reprogramming of PSNs, which offers novel analgesic approaches.

Psychedelic Drugs in Mental Disorders: Current Clinical Scope and Deep Learning-Based Advanced Perspectives

Mental disorders are a representative type of brain disorder, including anxiety, major depressive depression (MDD), and autism spectrum disorder (ASD), that are caused by multiple etiologies, including genetic heterogeneity, epigenetic dysregulation, and aberrant morphological and biochemical conditions. Psychedelic drugs such as psilocybin and lysergic acid diethylamide (LSD) have been renewed as fascinating treatment options and have gradually demonstrated potential therapeutic effects in mental disorders. However, the multifaceted conditions of psychiatric disorders resulting from individuality, complex genetic interplay, and intricate neural circuits impact the systemic pharmacology of psychedelics, which disturbs the integration of mechanisms that may result in dissimilar medicinal efficiency. The precise prescription of psychedelic drugs remains unclear, and advanced approaches are needed to optimize drug development. Here, recent studies demonstrating the diverse pharmacological effects of psychedelics in mental disorders are reviewed, and emerging perspectives on structural function, the microbiota-gut-brain axis, and the transcriptome are discussed. Moreover, the applicability of deep learning is highlighted for the development of drugs on the basis of big data. These approaches may provide insight into pharmacological mechanisms and interindividual factors to enhance drug discovery and development for advanced precision medicine.

Single-cell sequencing in diabetic retinopathy: progress and prospects

Diabetic retinopathy is a major ocular complication of diabetes, characterized by progressive retinal microvascular damage and significant visual impairment in working-age adults. Traditional bulk RNA sequencing offers overall gene expression profiles but does not account for cellular heterogeneity. Single-cell RNA sequencing overcomes this limitation by providing transcriptomic data at the individual cell level and distinguishing novel cell subtypes, developmental trajectories, and intercellular communications. Researchers can use single-cell sequencing to draw retinal cell atlases and identify the transcriptomic features of retinal cells, enhancing our understanding of the pathogenesis and pathological changes in diabetic retinopathy. Additionally, single-cell sequencing is widely employed to analyze retinal organoids and single extracellular vesicles. Single-cell multi-omics sequencing integrates omics information, whereas stereo-sequencing analyzes gene expression and spatiotemporal data simultaneously. This review discusses the protocols of single-cell sequencing for obtaining single cells from retina and accurate sequencing data. It highlights the applications and advancements of single-cell sequencing in the study of normal retinas and the pathological changes associated with diabetic retinopathy. This underscores the potential of these technologies to deepen our understanding of the pathogenesis of diabetic retinopathy that may lead to the introduction of new therapeutic strategies.

High-resolution multimodal profiling of human epileptic brain activity via explanted depth electrodes

The availability and integration of electrophysiological and molecular data from the living brain is critical in understanding and diagnosing complex human disease. Intracranial stereo electroencephalography (SEEG) electrodes used for identifying the seizure focus in patients with epilepsy could enable the integration of such multimodal data. Here, we report multimodal profiling of epileptic brain activity via explanted depth electrodes (MoPEDE), a method that recovers extensive protein-coding transcripts, including cell type markers, DNA methylation, and short variant profiles from explanted SEEG electrodes matched with electrophysiological and radiological data allowing for high-resolution reconstructions of brain structure and function. We found gene expression gradients that corresponded with the neurophysiology-assigned epileptogenicity index but also outlier molecular fingerprints in some electrodes, potentially indicating seizure generation or propagation zones not detected during electroclinical assessments. Additionally, we identified DNA methylation profiles indicative of transcriptionally permissive or restrictive chromatin states and SEEG-adherent differentially expressed and methylated genes not previously associated with epilepsy. Together, these findings validate that RNA profiles and genome-wide epigenetic data from explanted SEEG electrodes offer high-resolution surrogate molecular landscapes of brain activity. The MoPEDE approach has the potential to enhance diagnostic decisions and deepen our understanding of epileptogenic network processes in the human brain.

Brain aging and rejuvenation at single-cell resolution

Brain aging leads to a decline in cognitive function and a concomitant increase in the susceptibility to neurodegenerative diseases such as Alzheimer's and Parkinson's diseases. A key question is how changes within individual cells of the brain give rise to age-related dysfunction. Developments in single-cell "omics" technologies, such as single-cell transcriptomics, have facilitated high-dimensional profiling of individual cells. These technologies have led to new and comprehensive characterizations of brain aging at single-cell resolution. Here, we review insights gleaned from single-cell omics studies of brain aging, starting with a cell-type-centric overview of age-associated changes and followed by a discussion of cell-cell interactions during aging. We highlight how single-cell omics studies provide an unbiased view of different rejuvenation interventions and comment on the promise of combinatorial rejuvenation approaches for the brain. Finally, we propose new directions, including models of brain aging and neural stem cells as a focal point for rejuvenation.

Cancer neuroscience and glioma: clinical implications

In recent years, it has been increasingly recognized that tumor growth relies not only on support from the surrounding microenvironment but also on the tumors capacity to adapt to - and actively manipulate - its niche. While targeting angiogenesis and modulating the local immune environment have been explored as therapeutic approaches, these strategies have yet to yield effective treatments for brain tumors and remain under refinement. More recently, the nervous system itself has been explored as a critical environmental support for cancer, with extensive neuro-tumoral interactions observed both intracranially and in extracranial sites containing neural components. In the brain, interactions between glioma cells as well as metastatic lesions with neural components have clinical implications for diagnostics, risk assessments, neurological sequelae, and the development of innovative therapeutics. Here, we review these neuro-tumoral dynamics, emphasizing aspects relevant to neurosurgical practice.

DNA Methylation in Alzheimer's Disease

To date, DNA methylation is the best characterized epigenetic modification in Alzheimer's disease. Involving the addition of a methyl group to the fifth carbon of the cytosine pyrimidine base, DNA methylation is generally thought to be associated with the silencing of gene expression. It has been hypothesized that epigenetics may mediate the interaction between genes and the environment in the manifestation of Alzheimer's disease, and therefore studies investigating DNA methylation could elucidate novel disease mechanisms. This chapter comprehensively reviews epigenomic studies, undertaken in human brain tissue and purified brain cell types, focusing on global methylation levels, candidate genes, epigenome wide approaches, and recent meta-analyses. We discuss key differentially methylated genes and pathways that have been highlighted to date, with a discussion on how new technologies and the integration of multiomic data may further advance the field.

Scrutinizing neurodegenerative diseases: decoding the complex genetic architectures through a multi-omics lens

Neurodegenerative diseases present complex genetic architectures, reflecting a continuum from monogenic to oligogenic and polygenic models. Recent advances in multi-omics data, coupled with systems genetics, have significantly refined our understanding of how these data impact neurodegenerative disease mechanisms. To contextualize these genetic discoveries, we provide a comprehensive critical overview of genetic architecture concepts, from Mendelian inheritance to the latest insights from oligogenic and omnigenic models. We explore the roles of common and rare genetic variants, gene-gene and gene-environment interactions, and epigenetic influences in shaping disease phenotypes. Additionally, we emphasize the importance of multi-omics layers including genomic, transcriptomic, proteomic, epigenetic, and metabolomic data in elucidating the molecular mechanisms underlying neurodegeneration. Special attention is given to missing heritability and the contribution of rare variants, particularly in the context of pleiotropy and network pleiotropy. We examine the application of single-cell omics technologies, transcriptome-wide association studies, and epigenome-wide association studies as key approaches for dissecting disease mechanisms at tissue- and cell-type levels. Our review introduces the OmicPeak Disease Trajectory Model, a conceptual framework for understanding the genetic architecture of neurodegenerative disease progression, which integrates multi-omics data across biological layers and time points. This review highlights the critical importance of adopting a systems genetics approach to unravel the complex genetic architecture of neurodegenerative diseases. Finally, this emerging holistic understanding of multi-omics data and the exploration of the intricate genetic landscape aim to provide a foundation for establishing more refined genetic architectures of these diseases, enhancing diagnostic precision, predicting disease progression, elucidating pathogenic mechanisms, and refining therapeutic strategies for neurodegenerative conditions.

Multimodal single-cell profiling reveals neuronal vulnerability and pathological cell states in focal cortical dysplasia

Focal cortical dysplasia (FCD) is a neurodevelopmental condition characterized by malformations of the cerebral cortex that often cause drug-resistant epilepsy. In this study, we performed multi-omics single-nuclei profiling to map the chromatin accessibility and transcriptome landscapes of FCD type II, generating a comprehensive multimodal single-nuclei dataset comprising 61,525 cells from 11 clinical samples of lesions and controls. Our findings revealed profound chromatin, transcriptomic, and cellular alterations affecting neuronal and glial cells in FCD lesions, including the selective loss of upper-layer excitatory neurons, significant expansion of oligodendrocytes and immature astrocytic populations, and a distinct neuronal subpopulation harboring dysmorphic neurons. Furthermore, we uncovered activated microglia subsets, particularly in FCD IIb cases. This comprehensive study unveils neuronal and glial cell states driving FCD development and epileptogenicity, enhancing our understanding of FCD and offering directions for targeted therapy development.

Single-cell sequencing insights into the transcriptional landscape of Parkinson's disease

Parkinson's disease (PD) is the second most prevalent neurodegenerative disorder, with an unknown etiology and no specific treatment. Emerging single-cell and single-nucleus RNA sequencing (sc/snRNA-seq) technologies have become instrumental in unravelling cellular heterogeneity and characterizing molecular signatures at single-cell resolution. Single-cell T cell receptor sequencing (scTCR-seq) and single-cell B cell receptor sequencing (scBCR-seq) technologies provide unprecedented opportunities to explore the immune repertoire diversity. These state-of-the-art technologies have been increasingly applied in PD research in the last five years, offering novel insights into the cellular susceptibilities and complex molecular mechanisms underlying PD pathogenesis. Herein we review recent advances in the applications of sc/snRNA-seq, scTCR-seq and scBCR-seq technologies in various PD models. Moreover, we focus on degenerative neurons, activated neuroglial cells, as well as pro-inflammatory immune cells, exploring their unique transcriptional landscapes in PD, as revealed by single-cell sequencing technologies. Finally, we highlight important challenges and the future directions of single-cell experiments in PD research.

Elevated EGR1 Binding at Enhancers in Excitatory Neurons Correlates with Neuronal Subtype-Specific Epigenetic Regulation

Brain development and neuronal cell specification are accompanied with epigenetic changes to achieve diverse gene expression regulation. Interacting with cell-type specific epigenetic marks, transcription factors bind to different sets of cis-regulatory elements in different types of cells. Currently, it remains largely unclear how cell-type specific gene regulation is achieved for neurons. In this study, we generated epigenetic maps to perform comparative histone modification analysis between excitatory and inhibitory neurons. We found that neuronal cell-type specific histone modifications are enriched in super enhancer regions containing abundant EGR1 motifs. Further CUT&RUN data validated that more EGR1 binding sites can be detected in excitatory neurons and primarily located in enhancers. Integrative analysis revealed that EGR1 binding is strongly correlated with various epigenetic markers for open chromatin regions and associated with distinct gene pathways with neuronal subtype-specific functions. In inhibitory neurons, the majority of genomic regions hosting EGR1 binding sites become accessible at early embryonic stages. In contrast, the super enhancers in excitatory neurons hosting EGR1 binding sites gained their accessibility during postnatal stages. This study highlights the significance of transcription factor binding to enhancer regions, which may play a crucial role in establishing cell-type specific gene regulation in neurons.

Investigation of human aging at the single-cell level

Human aging is characterized by a gradual decline in physiological functions and an increased susceptibility to various diseases. The complex mechanisms underlying human aging are still not fully elucidated. Single-cell sequencing (SCS) technologies have revolutionized aging research by providing unprecedented resolution and detailed insights into cellular diversity and dynamics. In this review, we discuss the application of various SCS technologies in human aging research, encompassing single-cell, genomics, transcriptomics, epigenomics, and proteomics. We also discuss the combination of multiple omics layers within single cells and the integration of SCS technologies with advanced methodologies like spatial transcriptomics and mass spectrometry. These approaches have been essential in identifying aging biomarkers, elucidating signaling pathways associated with aging, discovering novel aging cell subpopulations, uncovering tissue-specific aging characteristics, and investigating aging-related diseases. Furthermore, we provide an overview of aging-related databases that offer valuable resources for enhancing our understanding of the human aging process.

Enhancing Spatial Domain Identification in Spatially Resolved Transcriptomics Using Graph Convolutional Networks With Adaptively Feature-Spatial Balance and Contrastive Learning

Recent advancements in spatially transcriptomics (ST) technologies have enabled the comprehensive measurement of gene expression profiles while preserving the spatial information of cells. Combining gene expression profiles and spatial information has been the most commonly used method to identify spatial functional domains and genes. However, most existing spatial domain decipherer methods are more focused on spatially neighboring structures and fail to take into account balancing the self-characteristics and the spatial structure dependency of spots. Therefore, we propose a novel model called SpaGCAC, which recognizes spatial domains with the help of an adaptive feature-spatial balanced graph convolutional network named AFSBGCN. The AFSBGCN can dynamically learn the relationship between spatial local topology structures and the self-characteristics of spots by adaptively increasing or declining the weight on the self-characteristics during message aggregation. Moreover, to better capture the local structures of spots, SpaGCAC exploits a local topology structure contrastive learning strategy. Meanwhile, SpaGCAC utilizes a probability distribution contrastive learning strategy to increase the similarity of probability distributions for points belonging to the same category. We validate the performance of SpaGCAC for spatial domain identification on four spatial transcriptomic datasets. In comparison with seven spatial domain recognition methods, SpaGCAC achieved the highest NMI median of 0.683 and the second highest ARI median of 0.559 on the multi-slice DLPFC dataset. SpaGCAC achieved the best results on all three other single-slice datasets. The above-mentioned results show that SpaGCAC outperforms most existing methods, providing enhanced insights into tissue heterogeneity.

From bioinformatics to anti-inflammation and immune regulation: ACT001 in lipopolysaccharide-induced lung injury

BACKGROUND

ACT001 is a potent anti-inflammatory small-molecule drug. However, the single cell and spatial molecular basis of pyroptosis and whether ACT001 exerts a therapeutic effect by preventing pyroptosis on acute lung injury (ALI) remains unclear.

METHODS

The bioinformatics approach was employed to identify single cell and spatial landscape of nucleotide-binding domains and leucine-rich repeat protein 3 (NLRP3)-dependent pyroptosis in lipopolysaccharide (LPS) and influenza virus-induced ALI. Molecular docking was performed to elucidate the relationship between ACT001 and NLRP3. LPS-induced ALI mice model was established. Histopathological analysis and bronchoalveolar lavage fluid collection were conducted to investigate the anti-inflammatory and protective effects. In vitro experiments were also performed on bone marrow-derived macrophages to explore the effect of ACT001 on the balance of mitochondrial fusion and fission protein.

RESULTS

Single cell transcriptomic and spatial transcriptomic analysis predicted that NLRP3-dependent pyroptosis significantly correlated with the development of ALI both in single cell and spatial distribution. Molecular docking provided a stable and reliable docking between ACT001 and NLRP3. ACT001 improved the 7-day survival of mice by approximately 50% over the loading dose of LPS-induced ALI. ACT001 (5 uM) attenuated the disruption of mitochondrial integrity and reactive oxygen species. Further, ACT001 reduced the overexpression of the mitochondrial fission protein DRP1 without affecting fusion protein Mitofusin2 levels. Moreover, ACT001 exerted a similar protective effect of suppressing pyroptosis as the DRP1-inhibitor Mdivi-1.

CONCLUSIONS

Our study revealed that pyroptosis genes were highly expressed in single-cell and spatial mapping along the first week of ALI occurrence. ACT001 attenuates ALI by reducing the NLRP3-dependent pyroptosis and balancing mitochondrial fission and fusion.

Advancements in Single-Cell RNA Sequencing and Spatial Transcriptomics for Central Nervous System Disease

The incidence of central nervous system (CNS) disease has persistently increased over the last several years. There is an urgent need for effective methods to improve the cure rates of CNS disease. However, the precise molecular basis underlying the development and progression of major CNS diseases remains elusive. A complete molecular map will contribute to research on CNS disease treatment strategies. Emerging technologies such as single-cell RNA sequencing (scRNA-seq) and Spatial Transcriptomics (ST) are potent tools for exploring the molecular complexity, cell heterogeneity, and functional specificity of CNS disease. scRNA-seq and ST can provide insights into the disease at cellular and spatial transcription levels. This review presents a survey of scRNA-seq and ST studies on CNS diseases, such as chronic neurodegenerative diseases, acute CNS injuries, and others. These studies offer novel perspectives in treating and diagnosing CNS diseases by discovering new cell types or subtypes associated with the disease, proposing new pathophysiological mechanisms, uncovering novel therapeutic targets, and identifying putative biomarkers.

Human sensory-like neuron cultivation-An optimized protocol

Introduction

Reprogramming of human-induced pluripotent stem cells (iPSCs) and their differentiation into specific cell types, such as induced sensory-like neurons (iSNs), are critical for disease modeling and drug testing. However, the variability of cell populations challenges reliability and reproducibility. While various protocols for iSN differentiation exist, the development of non-iSN cells in these cultures remains an issue. Therefore, standardization of protocols is essential. This study aimed to improve iSN culture conditions by reducing the number of non-iSN cells while preserving the survival and quality of iSNs.

Methods

iSNs were differentiated from a healthy control iPSC line using an established protocol. Interventions for protocol optimization included floxuridine (FdU) or 1-β-D-arabinofuranosyl-cytosine hydrochloride (AraC) treatment, magnetic-activated cell sorting (MACS), early cell passaging, and replating. Cell viability and iSN-to-total-cell-count ratio were assessed using a luminescent assay and immunocytochemistry, respectively.

Results

Passaging of cells during differentiation did not increase the iSN-to-total-cell-count ratio, and MACS of immature iSNs led to neuronal blebbing and reduced the iSN-to-total-cell-count ratio. Treatment with high concentrations and prolonged incubation of FdU or AraC resulted in excessive cell death. However, treatment with 10 μM FdU for 24 h post-differentiation showed the most selective targeting of non-iSN cells, leading to an increase in the iSN-to-total-cell count ratio without compromising the viability or functionality of the iSN population. Replating of iSNs shortly after seeding also helped to reduce non-iSN cells.

Conclusion

In direct comparison with other methods, treatment with 10 μM FdU for 24 h after differentiation shows promise for improving iSN culture purity, which could benefit downstream applications in disease modeling and drug discovery. However, further investigations involving multiple iPSC lines and optimization of protocol parameters are warranted to fully exploit the potential of this method and enhance its reproducibility and applicability. Overall, this study provides valuable insights into optimizing culture conditions for iSN differentiation and highlights the importance of standardized protocols in iPSC-based research.

Exploring the complexities of epigenetics in multiple sclerosis: A study involving meta-analysis of DNA methylation profiles, epigenetic drift, and rare epivariations

Background

Multiple sclerosis (MS) is an autoimmune condition characterized by inflammatory and neurodegenerative traits. Recently, DNA methylation has emerged as a promising field of investigation for elucidating dynamics characterizing MS development and progression.

Objectives

This study aimed to comprehensively investigate the role of epigenetics in MS by analyzing the methylation profiles from blood and brain tissues from public datasets.

Methods

Employing a meta-analytical framework for differential methylation analyses, the study extended beyond conventional analyses to explore additional dimensions of epigenetic regulation, including epigenetic drift, age acceleration, and rare epivariations.

Results

Results of the differential methylation analysis were in line with previously reported findings. No significant differences were observed in age acceleration or global epigenetic drift between MS cases and controls. However, upon closer analysis at the gene level, distinctive patterns of epigenetic drift emerged, particularly within genes implicated in neural biological functions.

Conclusions

These findings underscore the role of epigenetic modifications in shaping MS pathology. Furthermore, the study unveiled the exclusive presence of rare epivariations within the MS cases, some of which involved genes previously linked to MS or other autoimmune diseases. This highlights the potential significance of rare genetic aberrations in driving MS susceptibility and progression.

Innovative aspects and applications of single cell technology for different diseases

Recent developments in single-cell technologies have provided valuable insights from cancer genomics to complex microbial communities. Single-cell technologies including the RNA-seq, next-generation sequencing (NGS), epigenomics, genomics, and transcriptomics can be used to uncover the single cell nature and molecular characterization of individual cells. These technologies also reveal the cellular transition states, evolutionary relationships between genes, the complex structure of single-cell populations, cell-to-cell interaction leading to biological discoveries and more reliable than traditional bulk technologies. These technologies are becoming the first choice for the early detection of inflammatory biomarkers affecting the proliferation and progression of tumor cells in the tumor microenvironment and improving the clinical efficacy of patients undergoing immunotherapy. These technologies also hold a central position in the detection of checkpoint inhibitors and thus determining the signaling pathways evoked by tumor invasion. This review addressed the emerging approaches of single cell-based technologies in cancer immunotherapies and different human diseases at cellular and molecular levels and the emerging role of sequencing technologies leading to drug discovery. Advancements in these technologies paved for discovering novel diagnostic markers for better understanding the pathological and biochemical mechanisms also for controlling the rate of different diseases.

Deciphering brain cellular and behavioral mechanisms: Insights from single-cell and spatial RNA sequencing

The brain is a complex computing system composed of a multitude of interacting neurons. The computational outputs of this system determine the behavior and perception of every individual. Each brain cell expresses thousands of genes that dictate the cell's function and physiological properties. Therefore, deciphering the molecular expression of each cell is of great significance for understanding its characteristics and role in brain function. Additionally, the positional information of each cell can provide crucial insights into their involvement in local brain circuits. In this review, we briefly overview the principles of single-cell RNA sequencing and spatial transcriptomics, the potential issues and challenges in their data processing, and their applications in brain research. We further outline several promising directions in neuroscience that could be integrated with single-cell RNA sequencing, including neurodevelopment, the identification of novel brain microstructures, cognition and behavior, neuronal cell positioning, molecules and cells related to advanced brain functions, sleep-wake cycles/circadian rhythms, and computational modeling of brain function. We believe that the deep integration of these directions with single-cell and spatial RNA sequencing can contribute significantly to understanding the roles of individual cells or cell types in these specific functions, thereby making important contributions to addressing critical questions in those fields. This article is categorized under: RNA Evolution and Genomics > Computational Analyses of RNA RNA in Disease and Development > RNA in Development RNA in Disease and Development > RNA in Disease.

Advances in single-cell sequencing technology in microbiome research

With the rapid development of histological techniques and the widespread application of single-cell sequencing in eukaryotes, researchers desire to explore individual microbial genotypes and functional expression, which deepens our understanding of microorganisms. In this review, the history of the development of microbial detection technologies was revealed and the difficulties in the application of single-cell sequencing in microorganisms were dissected as well. Moreover, the characteristics of the currently emerging microbial single-cell sequencing (Microbe-seq) technology were summarized, and the prospects of the application of Microbe-seq in microorganisms were distilled based on the current development status. Despite its mature development, the Microbe-seq technology was still in the optimization stage. A retrospective study was conducted, aiming to promote the widespread application of single-cell sequencing in microorganisms and facilitate further improvement in the technology.

Single-cell sequencing of the substantia nigra reveals microglial activation in a model of MPTP

Background

N-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) is a neurotoxin widely used to induce PD models, but the effect of MPTP on the cells and genes of PD has not been fully elucidated.

Methods

Single-nucleus RNA sequencing was performed in the Substantia Nigra (SN) of MPTP mice. UMAP analysis was used for the dimensionality reduction visualization of the SN in the MPTP mice. Known marker genes highly expressed genes in each cluster were used to annotate most clusters. Specific Differentially Expressed Genes (DEGs) and PD risk genes analysis were used to find MPTP-associated cells. GO, KEGG, PPI network, GSEA and CellChat analysis were used to reveal cell type-specific functional alterations and disruption of cell-cell communication networks. Subset reconstruction and pseudotime analysis were used to reveal the activation status of the cells, and to find the transcription factors with trajectory characterized.

Results

Initially, we observed specific DEGs and PD risk genes enrichment in microglia. Next, We obtained the functional phenotype changes in microglia and found that IGF, AGRN and PTN pathways were reduced in MPTP mice. Finally, we analyzed the activation state of microglia and revealed a pro-inflammatory trajectory characterized by transcription factors Nfe2l2 and Runx1.

Conclusion

Our work revealed alterations in microglia function, signaling pathways and key genes in the SN of MPTP mice.

Single-nucleus chromatin landscape dataset of mouse brain development and aging

The development and aging of the brain constitute a lifelong dynamic process, marked by structural and functional changes that entail highly coordinated cellular differentiation and epigenetic regulatory mechanisms. Chromatin accessibility serves as the foundational basis for genetic activity. However, the holistic and dynamic chromatin landscape that spans various brain regions throughout development and ageing remains predominantly unexplored. In this study, we employed single-nucleus ATAC-seq to generate comprehensive chromatin accessibility maps, incorporating data from 69,178 cells obtained from four distinct brain regions - namely, the olfactory bulb (OB), cerebellum (CB), prefrontal cortex (PFC), and hippocampus (HP) - across key developmental time points at 7 P, 3 M, 12 M, and 18 M. We delineated the distribution of cell types across different age stages and brain regions, providing insight into chromatin accessible regions and key transcription factors specific to different cell types. Our data contribute to understanding the epigenetic basis of the formation of different brain regions, providing a dynamic landscape and comprehensive resource for revealing gene regulatory programs during brain development and aging.

Effects of Developmental Lead and Phthalate Exposures on DNA Methylation in Adult Mouse Blood, Brain, and Liver: A Focus on Genomic Imprinting by Tissue and Sex

BACKGROUND

Maternal exposure to environmental chemicals can cause adverse health effects in offspring. Mounting evidence supports that these effects are influenced, at least in part, by epigenetic modifications. It is unknown whether epigenetic changes in surrogate tissues such as the blood are reflective of similar changes in target tissues such as cortex or liver.

OBJECTIVE

We examined tissue- and sex-specific changes in DNA methylation (DNAm) associated with human-relevant lead (Pb) and di(2-ethylhexyl) phthalate (DEHP) exposure during perinatal development in cerebral cortex, blood, and liver.

METHODS

Female mice were exposed to human relevant doses of either Pb (32  ppm ) via drinking water or DEHP (5 mg / kg-day ) via chow for 2 weeks prior to mating through offspring weaning. Whole genome bisulfite sequencing (WGBS) was utilized to examine DNAm changes in offspring cortex, blood, and liver at 5 months of age. Metilene and methylSig were used to identify differentially methylated regions (DMRs). Annotatr and ChIP-enrich were used for genomic annotations and gene set enrichment tests of DMRs, respectively.

RESULTS

The cortex contained the majority of DMRs associated with Pb (66%) and DEHP (57%) exposure. The cortex also contained the greatest degree of overlap in DMR signatures between sexes (n = 13 and 8 DMRs with Pb and DEHP exposure, respectively) and exposure types (n = 55 and 39 DMRs in males and females, respectively). In all tissues, detected DMRs were preferentially found at genomic regions associated with gene expression regulation (e.g., CpG islands and shores, 5' UTRs, promoters, and exons). An analysis of GO terms associated with DMR-containing genes identified imprinted genes to be impacted by both Pb and DEHP exposure. Of these, Gnas and Grb10 contained DMRs across tissues, sexes, and exposures, with some signatures replicated between target and surrogate tissues. DMRs were enriched in the imprinting control regions (ICRs) of Gnas and Grb10, and we again observed a replication of DMR signatures between blood and target tissues. Specifically, we observed hypermethylation of the Grb10 ICR in both blood and liver of Pb-exposed male animals.

CONCLUSIONS

These data provide preliminary evidence that imprinted genes may be viable candidates in the search for epigenetic biomarkers of toxicant exposure in target tissues. Additional research is needed on allele- and developmental stage-specific effects, as well as whether other imprinted genes provide additional examples of this relationship. https://doi.org/10.1289/EHP14074.

Comparative proteomic analysis of three major extracellular vesicle classes secreted from human primary and metastatic colorectal cancer cells: Exosomes, microparticles, and shed midbody remnants

Cell-derived extracellular vesicles (EVs) are evolutionary-conserved secretory organelles that, based on their molecular composition, are important intercellular signaling regulators. At least three classes of circulating EVs are known based on mechanism of biogenesis: exosomes (sEVs/Exos), microparticles (lEVs/MPs), and shed midbody remnants (lEVs/sMB-Rs). sEVs/Exos are of endosomal pathway origin, microparticles (lEVs/MPs) from plasma membrane blebbing and shed midbody remnants (lEVs/sMB-Rs) arise from symmetric cytokinetic abscission. Here, we isolate sEVs/Exos, lEVs/MPs, and lEVs/sMB-Rs secreted from human isogenic primary (SW480) and metastatic (SW620) colorectal cancer (CRC) cell lines in milligram quantities for label-free MS/MS-based proteomic profiling. Purified EVs revealed selective composition packaging of exosomal protein markers in SW480/SW620-sEVs/Exos, metabolic enzymes in SW480/SW620-lEVs/MPs, while centralspindlin complex proteins, nucleoproteins, splicing factors, RNA granule proteins, translation-initiation factors, and mitochondrial proteins selectively traffic to SW480/SW620- lEVs/sMB-Rs. Collectively, we identify 39 human cancer-associated genes in EVs; 17 associated with SW480-EVs, 22 with SW620-EVs. We highlight oncogenic receptors/transporters selectively enriched in sEVs/Exos (EGFR/FAS in SW480-sEVs/Exos and MET, TGFBR2, ABCB1 in SW620-sEVs/Exos). Interestingly, MDK, STAT1, and TGM2 are selectively enriched in SW480-lEVs/sMB-Rs, and ADAM15 to SW620-lEVs/sMB-Rs. Our study reveals sEVs/Exos, lEVs/MPs, and lEVs/sMB-Rs have distinct protein signatures that open potential diagnostic avenues of distinct types of EVs for clinical utility.

Single-Cell Sequencing Technology and Its Application in the Study of Central Nervous System Diseases

The mammalian central nervous system consists of a large number of cells, which contain not only different types of neurons, but also a large number of glial cells, such as astrocytes, oligodendrocytes, and microglia. These cells are capable of performing highly refined electrophysiological activities and providing the brain with functions such as nutritional support, information transmission and pathogen defense. The diversity of cell types and individual differences between cells have brought inspiration to the study of the mechanism of central nervous system diseases. In order to explore the role of different cells, a new technology, single-cell sequencing technology has emerged to perform specific analysis of high-throughput cell populations, and has been continuously developed. Single-cell sequencing technology can accurately analyze single-cell expression in mixed-cell populations and collect cells from different spatial locations, time stages and types. By using single-cell sequencing technology to compare gene expression profiles of normal and diseased cells, it is possible to discover cell subsets associated with specific diseases and their associated genes. Therefore, scientists can understand the development process, related functions and disease state of the nervous system from an unprecedented depth. In conclusion, single-cell sequencing technology provides a powerful technology for the discovery of novel therapeutic targets for central nervous system diseases.

Spatiotemporal multi-omics: exploring molecular landscapes in aging and regenerative medicine

Aging and regeneration represent complex biological phenomena that have long captivated the scientific community. To fully comprehend these processes, it is essential to investigate molecular dynamics through a lens that encompasses both spatial and temporal dimensions. Conventional omics methodologies, such as genomics and transcriptomics, have been instrumental in identifying critical molecular facets of aging and regeneration. However, these methods are somewhat limited, constrained by their spatial resolution and their lack of capacity to dynamically represent tissue alterations. The advent of emerging spatiotemporal multi-omics approaches, encompassing transcriptomics, proteomics, metabolomics, and epigenomics, furnishes comprehensive insights into these intricate molecular dynamics. These sophisticated techniques facilitate accurate delineation of molecular patterns across an array of cells, tissues, and organs, thereby offering an in-depth understanding of the fundamental mechanisms at play. This review meticulously examines the significance of spatiotemporal multi-omics in the realms of aging and regeneration research. It underscores how these methodologies augment our comprehension of molecular dynamics, cellular interactions, and signaling pathways. Initially, the review delineates the foundational principles underpinning these methods, followed by an evaluation of their recent applications within the field. The review ultimately concludes by addressing the prevailing challenges and projecting future advancements in the field. Indubitably, spatiotemporal multi-omics are instrumental in deciphering the complexities inherent in aging and regeneration, thus charting a course toward potential therapeutic innovations.

Single-cell sequencing technology in diabetic wound healing: New insights into the progenitors-based repair strategies

Diabetes mellitus (DM), an increasingly prevalent chronic metabolic disease, is characterised by prolonged hyperglycaemia, which leads to long-term health consequences. Although much effort has been put into understanding the pathogenesis of diabetic wounds, the underlying mechanisms remain unclear. The advent of single-cell RNA sequencing (scRNAseq) has revolutionised biological research by enabling the identification of novel cell types, the discovery of cellular markers, the analysis of gene expression patterns and the prediction of developmental trajectories. This powerful tool allows for an in-depth exploration of pathogenesis at the cellular and molecular levels. In this editorial, we focus on progenitor-based repair strategies for diabetic wound healing as revealed by scRNAseq and highlight the biological behaviour of various healing-related cells and the alteration of signalling pathways in the process of diabetic wound healing. ScRNAseq could not only deepen our understanding of the complex biology of diabetic wounds but also identify and validate new targets for intervention, offering hope for improved patient outcomes in the management of this challenging complication of DM.

Disentangling associations between complex traits and cell types with seismic

Integrating single-cell RNA sequencing (scRNA-seq) with Genome-Wide Association Studies (GWAS) can help reveal GWAS-associated cell types, furthering our understanding of the cell-type-specific biological processes underlying complex traits and disease. However, current methods have technical limitations that hinder them from making systematic, scalable, interpretable disease-cell-type associations. In order to rapidly and accurately pinpoint associations, we develop a novel framework, seismic, which characterizes cell types using a new specificity score. We compare seismic with alternative methods across over 1,000 cell type characterizations at different granularities and 28 traits, demonstrating that seismic both corroborates findings and identifies trait-relevant cell groups which are not apparent through other methodologies. Furthermore, as part of the seismic framework, the specific genes driving cell type-trait associations can easily be accessed and analyzed, enabling further biological insights. The advantages of seismic are particularly salient in neurodegenerative diseases such as Parkinson's and Alzheimer's, where disease pathology has not only cell-specific manifestations, but also brain region-specific differences. Interestingly, a case study of Alzheimer's disease reveals the importance of considering GWAS endpoints, as studies relying on clinical diagnoses consistently identify microglial associations, while GWAS with a tau biomarker endpoint reveals neuronal associations. In general, seismic is a computationally efficient, powerful, and interpretable approach for identifying associations between complex traits and cell type-specific expression.

The Cognitive Framework Behind Modern Neuropathology

CONTEXT

In 2021 the World Health Organization distributed a new classification of central nervous system tumors that incorporated modern testing modalities in the diagnosis. Although universally accepted as a scientifically superior system, this schema has created controversy because its deployment globally is challenging in the best of circumstances and impossible in resource-poor health care ecosystems. Compounding this problem is the significant challenge that neuropathologists with expertise in central nervous system tumors are rare.

OBJECTIVE

To demonstrate diagnostic use of simple unsupervised machine learning techniques using publicly available data sets. I also discuss some potential solutions to the deployment of neuropathology classification in health care ecosystems burdened by this classification schema.

DATA SOURCES

The Cancer Genome Atlas RNA sequencing data from low-grade and high-grade gliomas.

CONCLUSIONS

Methylation-based classification will be unable to solve all diagnostic problems in neuropathology. Information theory quantifications generate focused workflows in pathology, resulting in prevention of ordering unnecessary tests and identifying biomarkers that facilitate diagnosis.

Understanding glioblastoma at the single-cell level: Recent advances and future challenges

Glioblastoma, the most aggressive and prevalent form of primary brain tumor, is characterized by rapid growth, diffuse infiltration, and resistance to therapies. Intrinsic heterogeneity and cellular plasticity contribute to its rapid progression under therapy; therefore, there is a need to fully understand these tumors at a single-cell level. Over the past decade, single-cell transcriptomics has enabled the molecular characterization of individual cells within glioblastomas, providing previously unattainable insights into the genetic and molecular features that drive tumorigenesis, disease progression, and therapy resistance. However, despite advances in single-cell technologies, challenges such as high costs, complex data analysis and interpretation, and difficulties in translating findings into clinical practice persist. As single-cell technologies are developed further, more insights into the cellular and molecular heterogeneity of glioblastomas are expected, which will help guide the development of personalized and effective therapies, thereby improving prognosis and quality of life for patients.

Estrogenic influences on agonistic behavior in teleost fishes

Teleost fishes show an extraordinary diversity of sexual patterns, social structures, and sociosexual behaviors. Sex steroid hormones are key modulators of social behaviors in teleosts as in other vertebrates and act on sex steroid receptor-containing brain nuclei that form the evolutionarily conserved vertebrate social behavior network (SBN). Fishes also display important differences relative to tetrapod vertebrates that make them particularly well-suited to study the physiological mechanisms modulating social behavior. Specifically, fishes exhibit high levels of brain aromatization and have what has been proposed to be a lifelong, steroid hormone dependent plasticity in the neural substrates mediating sociosexual behavior. In this review, we examine how estrogenic signaling modulates sociosexual behaviors in teleosts with a particular focus on agonistic behavior. Estrogens have been shown to mediate agonistic behaviors in a broad range of fishes, from sexually monomorphic gonochoristic species to highly dimorphic sex changers with alternate reproductive phenotypes. These similarities across such diverse taxa contribute to a growing body of evidence that estrogens play a crucial role in the modulation of aggression in vertebrates. As analytical techniques and genomic tools rapidly advance, methods such as LC-MS/MS, snRNAseq, and CRISPR-based mutagenesis show great promise to further elucidate the mechanistic basis of estrogenic effects on social behavior in the diverse teleost lineage.

Research Hotspots and Trends in the Diagnosis of Chorioamnionitis: Based on Bibliometric Analysis from 2010 to 2022

OBJECTIVE

This study aimed to conduct a bibliometric analysis of literature related to the diagnosis of chorioamnionitis (CAM) and to point out the current research progress, hotspots, and development trends of CAM research.

STUDY DESIGN

Literature on the diagnosis of CAM from the Web of Science Core Collection (WoSCC) between 2010 and 2022 was retrieved. CiteSpace, VOSviewer, and Online Analysis Platform (OALM) were used to draw maps of authors, articles, journals, institutions, countries/regions, and keywords.

RESULTS

A total of 312 articles were included, and the number of articles gradually increased over the study period. The author with the largest number of articles was Roberto Romero. The institution with the largest number of articles was Wayne State University School of Medicine, and the United States was the country that produced the largest number of articles. Analysis of keywords and outbreak words suggested that future research hotspots and trends may focus on early treatment of CAM and more precise, noninvasive, and more sensitive diagnoses.

CONCLUSION

In this study, visualization software and data information mining were innovatively used to conduct a bibliometric analysis of articles in the field of CAM diagnosis, and the current status, hotspots, and development of this field were obtained. Future research hotspots may be the precision diagnosis and treatment of CAM.

KEY POINTS

· There is no bibliometric study on CAM diagnosis in the existing literature.. · The prediction of CAM diagnosis is an important topic to improve maternal and infant prognosis.. · Bibliometrics can effectively guide the direction of future research..

Single-cell transcriptomics: background, technologies, applications, and challenges

Single-cell sequencing was developed as a high-throughput tool to elucidate unusual and transient cell states that are barely visible in the bulk. This technology reveals the evolutionary status of cells and differences between populations, helps to identify unique cell subtypes and states, reveals regulatory relationships between genes, targets and molecular mechanisms in disease processes, tumor heterogeneity, the state of the immune environment, etc. However, the high cost and technical limitations of single-cell sequencing initially prevented its widespread application, but with advances in research, numerous new single-cell sequencing techniques have been discovered, lowering the cost barrier. Many single-cell sequencing platforms and bioinformatics methods have recently become commercially available, allowing researchers to make fascinating observations. They are now increasingly being used in various industries. Several protocols have been discovered in this context and each technique has unique characteristics, capabilities and challenges. This review presents the latest advancements in single-cell transcriptomics technologies. This includes single-cell transcriptomics approaches, workflows and statistical approaches to data processing, as well as the potential advances, applications, opportunities and challenges of single-cell transcriptomics technology. You will also get an overview of the entry points for spatial transcriptomics and multi-omics.

Split Pool Ligation-based Single-cell Transcriptome sequencing (SPLiT-seq) data processing pipeline comparison

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.

Comprehensive transcriptome analysis reveals altered mRNA splicing and post-transcriptional changes in the aged mouse brain

A comprehensive understanding of molecular changes during brain aging is essential to mitigate cognitive decline and delay neurodegenerative diseases. The interpretation of mRNA alterations during brain aging is influenced by the health and age of the animal cohorts studied. Here, we carefully consider these factors and provide an in-depth investigation of mRNA splicing and dynamics in the aging mouse brain, combining short- and long-read sequencing technologies with extensive bioinformatic analyses. Our findings encompass a spectrum of age-related changes, including differences in isoform usage, decreased mRNA dynamics and a module showing increased expression of neuronal genes. Notably, our results indicate a reduced abundance of mRNA isoforms leading to nonsense-mediated RNA decay and suggest a regulatory role for RNA-binding proteins, indicating that their regulation may be altered leading to the reshaping of the aged brain transcriptome. Collectively, our study highlights the importance of studying mRNA splicing events during brain aging.

Research progress of the inferior colliculus: from Neuron, neural circuit to auditory disease

The auditory midbrain, also known as the inferior colliculus (IC), serves as a crucial hub in the auditory pathway. Comprising diverse cell types, the IC plays a pivotal role in various auditory functions, including sound localization, auditory plasticity, sound detection, and sound-induced behaviors. Notably, the IC is implicated in several auditory central disorders, such as tinnitus, age-related hearing loss, autism and Fragile X syndrome. Accurate classification of IC neurons is vital for comprehending both normal and dysfunctional aspects of IC function. Various parameters, including dendritic morphology, neurotransmitter synthesis, potassium currents, biomarkers, and axonal targets, have been employed to identify distinct neuron types within the IC. However, the challenge persists in effectively classifying IC neurons into functional categories due to the limited clustering capabilities of most parameters. Recent studies utilizing advanced neuroscience technologies have begun to shed light on biomarker-based approaches in the IC, providing insights into specific cellular properties and offering a potential avenue for understanding IC functions. This review focuses on recent advancements in IC research, spanning from neurons and neural circuits to aspects related to auditory diseases.

Transcriptomic analysis of rat brain response to alternating current electrical stimulation: unveiling insights via single-nucleus RNA sequencing

Electrical brain stimulation (EBS) has gained popularity for laboratory and clinical applications. However, comprehensive characterization of cellular diversity and gene expression changes induced by EBS remains limited, particularly with respect to specific brain regions and stimulation sites. Here, we presented the initial single-nucleus RNA sequencing profiles of rat cortex, hippocampus, and thalamus subjected to intracranial alternating current stimulation (iACS) at 40 Hz. The results demonstrated an increased number of neurons in all three regions in response to iACS. Interestingly, less than 0.1% of host gene expression in neurons was significantly altered by iACS. In addition, we identified Rgs9, a known negative regulator of dopaminergic signaling, as a unique downregulated gene in neurons. Unilateral iACS produced a more focused local effect in attenuating the proportion of Rgs9+ neurons in the ipsilateral compared to bilateral iACS treatment. The results suggested that unilateral iACS at 40 Hz was an efficient approach to increase the number of neurons and downregulate Rgs9 gene expression without affecting other cell types or genes in the brain. Our study presented the direct evidence that EBS could boost cerebral neurogenesis and enhance neuronal sensitization to dopaminergic drugs and agonists, through its downregulatory effect on Rgs9 in neurons.

Dopamine across timescales and cell types: Relevance for phenotypes in Parkinson's disease progression

Dopamine neurons in the substantia nigra pars compacta (SNc) synthesize and release dopamine, a critical neurotransmitter for movement and learning. SNc dopamine neurons degenerate in Parkinson's Disease (PD), causing a host of motor and non-motor symptoms. Here, we review recent conceptual advances in our basic understanding of the dopamine system - including our rapidly advancing knowledge of dopamine neuron heterogeneity - with special attention to their importance for understanding PD. In PD patients, dopamine neuron degeneration progresses from lateral SNc to medial SNc, suggesting clinically relevant heterogeneity in dopamine neurons. With technical advances in dopamine system interrogation, we can understand the relevance of this heterogeneity for PD progression and harness it to develop new treatments.

Fast and flexible profiling of chromatin accessibility and total RNA expression in single nuclei using Microwell-seq3

Single cell chromatin accessibility profiling and transcriptome sequencing are the most widely used technologies for single-cell genomics. Here, we present Microwell-seq3, a high-throughput and facile platform for high-sensitivity single-nucleus chromatin accessibility or full-length transcriptome profiling. The method combines a preindexing strategy and a penetrable chip-in-a-tube for single nucleus loading and DNA amplification and therefore does not require specialized equipment. We used Microwell-seq3 to profile chromatin accessibility in more than 200,000 single nuclei and the full-length transcriptome in ~50,000 nuclei from multiple adult mouse tissues. Compared with the existing polyadenylated transcript capture methods, integrative analysis of cell type-specific regulatory elements and total RNA expression uncovered comprehensive cell type heterogeneity in the brain. Gene regulatory networks based on chromatin accessibility profiling provided an improved cell type communication model. Finally, we demonstrated that Microwell-seq3 can identify malignant cells and their specific regulons in spontaneous lung tumors of aged mice. We envision a broad application of Microwell-seq3 in many areas of research.

Single-cell RNA sequencing reveals the immune features and viral tropism in the central nervous system of mice infected with Japanese encephalitis virus

Japanese encephalitis virus (JEV) is a neurotropic pathogen that causes lethal encephalitis. The high susceptibility and massive proliferation of JEV in neurons lead to extensive neuronal damage and inflammation within the central nervous system. Despite extensive research on JEV pathogenesis, the effect of JEV on the cellular composition and viral tropism towards distinct neuronal subtypes in the brain is still not well comprehended. To address these issues, we performed single-cell RNA sequencing (scRNA-seq) on cells isolated from the JEV-highly infected regions of mouse brain. We obtained 88,000 single cells and identified 34 clusters representing 10 major cell types. The scRNA-seq results revealed an increasing amount of activated microglia cells and infiltrating immune cells, including monocytes & macrophages, T cells, and natural killer cells, which were associated with the severity of symptoms. Additionally, we observed enhanced communication between individual cells and significant ligand-receptor pairs related to tight junctions, chemokines and antigen-presenting molecules upon JEV infection, suggesting an upregulation of endothelial permeability, inflammation and antiviral response. Moreover, we identified that Baiap2-positive neurons were highly susceptible to JEV. Our findings provide valuable clues for understanding the mechanism of JEV induced neuro-damage and inflammation as well as developing therapies for Japanese encephalitis.

HMOX1 as a therapeutic target associated with diabetic foot ulcers based on single-cell analysis and machine learning

Diabetic foot ulcers (DFUs) are a serious chronic complication of diabetes mellitus and a leading cause of disability and death in diabetic patients. However, current treatments remain unsatisfactory. Although macrophages are associated with DFU, their exact role in this disease remains uncertain. This study sought to detect macrophage-related genes in DFU and identify possible therapeutic targets. Single-cell datasets (GSE223964) and RNA-seq datasets (GSM68183, GSE80178, GSE134431 and GSE147890) associated with DFU were retrieved from the gene expression omnibus (GEO) database for this study. Analysis of the provided single-cell data revealed the distribution of macrophage subpopulations in the DFU. Four independent RNA-seq datasets were merged into a single DFU cohort and further analysed using bioinformatics. This included differential expression (DEG) analysis, multiple machine learning algorithms to identify biomarkers and enrichment analysis. Finally, key results were validated using reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and Western bolt. Finally, the findings were validated using RT-qPCR and western blot. We obtained 802 macrophage-related genes in single-cell analysis. Differential expression analysis yielded 743 DEGs. Thirty-seven macrophage-associated DEGs were identified by cross-analysis of marker genes with macrophage-associated DEGs. Thirty-seven intersections were screened and cross-analysed using four machine learning algorithms. Finally, HMOX1 was identified as a potentially valuable biomarker. HMOX1 was significantly associated with biological pathways such as the insulin signalling pathway. The results showed that HMOX1 was significantly overexpressed in DFU samples. In conclusion, the analytical results of this study identified HMOX1 as a potentially valuable biomarker associated with macrophages in DFU. The results of our analysis improve our understanding of the mechanism of macrophage action in this disease and may be useful in developing targeted therapies for DFU.

Reactive gliosis in traumatic brain injury: a comprehensive review

Traumatic brain injury (TBI) is one of the most common pathological conditions impacting the central nervous system (CNS). A neurological deficit associated with TBI results from a complex of pathogenetic mechanisms including glutamate excitotoxicity, inflammation, demyelination, programmed cell death, or the development of edema. The critical components contributing to CNS response, damage control, and regeneration after TBI are glial cells-in reaction to tissue damage, their activation, hypertrophy, and proliferation occur, followed by the formation of a glial scar. The glial scar creates a barrier in damaged tissue and helps protect the CNS in the acute phase post-injury. However, this process prevents complete tissue recovery in the late/chronic phase by producing permanent scarring, which significantly impacts brain function. Various glial cell types participate in the scar formation, but this process is mostly attributed to reactive astrocytes and microglia, which play important roles in several brain pathologies. Novel technologies including whole-genome transcriptomic and epigenomic analyses, and unbiased proteomics, show that both astrocytes and microglia represent groups of heterogenic cell subpopulations with different genomic and functional characteristics, that are responsible for their role in neurodegeneration, neuroprotection and regeneration. Depending on the representation of distinct glia subpopulations, the tissue damage as well as the regenerative processes or delayed neurodegeneration after TBI may thus differ in nearby or remote areas or in different brain structures. This review summarizes TBI as a complex process, where the resultant effect is severity-, region- and time-dependent and determined by the model of the CNS injury and the distance of the explored area from the lesion site. Here, we also discuss findings concerning intercellular signaling, long-term impacts of TBI and the possibilities of novel therapeutical approaches. We believe that a comprehensive study with an emphasis on glial cells, involved in tissue post-injury processes, may be helpful for further research of TBI and be the decisive factor when choosing a TBI model.

Single-cell RNA sequencing of anaplastic ependymoma and H3K27M-mutant diffuse midline glioma

BACKGROUND

Anaplastic ependymoma and H3K27M-mutant diffuse midline glioma are two common subtypes of brain tumors with poor long-term prognosis. The present study analyzed and compared the differences in cell types between two tumors by single-cell RNA sequencing (scRNA-seq) technology.

METHODS

ScRNA-seq was performed to profile cells from cancer tissue from anaplastic ependymoma patient and H3K27M-mutant diffuse midline glioma patient. Cell clustering, marker gene identification, cell type annotation, copy number variation analysis and function analysis of differentially expressed genes were then performed.

RESULTS

A total of 11,219 cells were obtained from anaplastic ependymoma and H3K27M mutant diffuse midline glioma, and these cells categorized into 12 distinct clusters. Each cell cluster could be characterized with specific cell markers to indicate cellular heterogeneity. Five cell types were annotated in each sample, including astrocyte, oligodendrocytes, microglial cell, neural progenitor cell and immune cell. The cluster types and proportion of cell types were not consistent between the two brain tumors. Functional analyses suggest that these cell clusters are involved in tumor-associated pathways, with slight differences in the cells of origin between the two tumors. In addition, cell communication analysis showed that the NRG3-ERBB4 pair is a key Ligand-receptor pair for anaplastic ependymoma, while in H3K27M-mutant diffuse midline glioma it is the PTN-PTPRZ1 pair that establishes contact with other cells.

CONCLUSION

There was intratumor heterogeneity in anaplastic ependymoma and H3K27M mutant diffuse midline glioma, and that the subtype differences may be due to differences in the origin of the cells.

A full-body transcription factor expression atlas with completely resolved cell identities in C. elegans

Invariant cell lineage in C. elegans enables spatiotemporal resolution of transcriptional regulatory mechanisms controlling the fate of each cell. Here, we develop RAPCAT (Robust-point-matching- And Piecewise-affine-based Cell Annotation Tool) to automate cell identity assignment in three-dimensional image stacks of L1 larvae and profile reporter expression of 620 transcription factors in every cell. Transcription factor profile-based clustering analysis defines 80 cell types distinct from conventional phenotypic cell types and identifies three general phenotypic modalities related to these classifications. First, transcription factors are broadly downregulated in quiescent stage Hermaphrodite Specific Neurons, suggesting stage- and cell type-specific variation in transcriptome size. Second, transcription factor expression is more closely associated with morphology than other phenotypic modalities in different pre- and post-differentiation developmental stages. Finally, embryonic cell lineages can be associated with specific transcription factor expression patterns and functions that persist throughout postembryonic life. This study presents a comprehensive transcription factor atlas for investigation of intra-cell type heterogeneity.

Modern Methods for Unraveling Cell- and Circuit-Level Mechanisms of Neurophysiological Biomarkers in Psychiatry

Methods for studying the mammalian brain in vivo have advanced dramatically in the past two decades. State-of-the-art optical and electrophysiological techniques allow direct recordings of the functional dynamics of thousands of neurons across distributed brain circuits with single-cell resolution. With transgenic tools, specific neuron types, pathways, and/or neurotransmitters can be targeted in user-determined brain areas for precise measurement and manipulation. In this chapter, we catalog these advancements. We emphasize that the impact of this methodological revolution on neuropsychiatry remains uncertain. This stems from the fact that these tools remain mostly limited to research in mice. And while translational paradigms are needed, recapitulations of human psychiatric disease states (e.g., schizophrenia) in animal models are inherently challenging to validate and may have limited utility in heterogeneous disease populations. Here we focus on an alternative strategy aimed at the study of neurophysiological biomarkers-the subject of this volume-translated to animal models, where precision neuroscience tools can be applied to provide molecular, cellular, and circuit-level insights and novel therapeutic targets. We summarize several examples of this approach throughout the chapter and emphasize the importance of careful experimental design and choice of dependent measures.

Cross-species single-cell landscape of vertebrate pineal gland

The pineal gland has evolved from a photoreceptive organ in fish to a neuroendocrine organ in mammals. This study integrated multiple daytime single-cell RNA-seq datasets from the pineal glands of zebrafish, rats, and monkeys, providing a detailed examination of the evolutionary transition at single-cell resolution. We identified key factors responsible for the anatomical and functional transformation of the pineal gland. We retrieved and integrated daytime single-cell transcriptomic datasets from the pineal glands of zebrafish, rats, and monkeys, resulting in a total of 22 431 cells after rigorous quality filtering. Comparative analysis was then conducted to elucidate the evolution of pineal cells, their photosensitivity, their role in melatonin production, and the signaling processes within the glands of these species. Our analysis identified distinct cellular compositions of the pineal gland in zebrafish, rats, and monkeys. Zebrafish photoreceptors exhibited comprehensive phototransduction gene expression, while specific genes, including transducin (Gngt1, Gnb3, and Gngt2) and phosducin (Pdc), were consistently present in mammalian pinealocytes. We found transcriptional similarities between the pineal gland and retina, underscoring shared evolutionary and functional pathways. Zebrafish displayed unique light-responsive circadian gene activity compared to rats and monkeys. Key ligand-receptor interactions were identified, especially involving MDK and PTN, influencing melatonin synthesis across species. Furthermore, we observed species-specific GPCR (G protein-coupled receptors) expressions related to melatonin synthesis and their alignment with retinal expressions. Our findings also highlighted specific transcription factors (TFs) and regulatory networks associated with pineal gland evolution and function. Our study provides a detailed analysis of the pineal gland's evolution from fish to mammals. We identified key transcriptional changes and controls that highlight the gland's functional diversity. Notably, we found significant ligand-receptor interactions influencing melatonin synthesis and demonstrated parallels between pineal and retinal expressions. These insights enhance our understanding of the pineal gland's role in phototransduction, melatonin production, and circadian rhythms in vertebrates.