Single-cell RNA-sequencing of the brain

Integrating scRNA-seq to explore offspring neurodevelopmental toxicity induced by Cyfluthrin exposure during pregnancy: A fate decision for NSCs

Cyfluthrin is a widely used insecticide, and studies have shown that its exposure during pregnancy is associated with neurobehavioral abnormalities in offspring, but the mechanism of toxicity is unknown. In this study, we observed the neurodevelopmental toxicity of Cyfluthrin in rat offspring of different ages due to pregnancy exposure, which manifested a series of impairments such as persistent cognitive impairment, neuronal loss in hippocampal tissues, synaptic damage, and altered expression of neurodevelopmental-related factors. Hippocampal scRNA-seq in neonatal rats showed specific cellular responses to prenatal Cyfluthrin exposure. Through DEG intergroup difference analysis, intercellular communication analysis, and mimetic timing analysis, we found that the change in the fate of neural stem cells - alterations in differentiation direction, proliferation, and apoptosis levels - was the main cause of the offspring's developmental toxicity induced by prenatal Cyfluthrin exposure. This inference was verified by our in - vivo and ex - vivo experiments. Our study first constructed a single - cell atlas of the offspring's brain hippocampus exposed to Cyfluthrin during pregnancy. It warns about pesticide intake during pregnancy and nursing in women and provides a theoretical basis for neurodevelopmental toxicity from early - life exposure to environmental pollutants.

Cutting-edge RNA technologies to advance the understanding of learning and memory

Following the recent emergence of RNA as a therapeutic tool, and coupled with an explosion in the development of new RNA technologies, it is rapidly becoming clear that the 21st century is the era of RNA. Neuroscience as a discipline has a long history of embracing new technology to advance the understanding of brain function, particularly in the context of learning and memory. In this short review, we highlight four broad categories of emerging RNA technologies, namely: imaging, isolation, identification and manipulation, and discuss their potential to advance the fundamental understanding of how RNA impacts experience-dependent plasticity, learning, and memory.

Artificial Intelligence and Neuroscience: Transformative Synergies in Brain Research and Clinical Applications

The convergence of Artificial Intelligence (AI) and neuroscience is redefining our understanding of the brain, unlocking new possibilities in research, diagnosis, and therapy. This review explores how AI's cutting-edge algorithms-ranging from deep learning to neuromorphic computing-are revolutionizing neuroscience by enabling the analysis of complex neural datasets, from neuroimaging and electrophysiology to genomic profiling. These advancements are transforming the early detection of neurological disorders, enhancing brain-computer interfaces, and driving personalized medicine, paving the way for more precise and adaptive treatments. Beyond applications, neuroscience itself has inspired AI innovations, with neural architectures and brain-like processes shaping advances in learning algorithms and explainable models. This bidirectional exchange has fueled breakthroughs such as dynamic connectivity mapping, real-time neural decoding, and closed-loop brain-computer systems that adaptively respond to neural states. However, challenges persist, including issues of data integration, ethical considerations, and the "black-box" nature of many AI systems, underscoring the need for transparent, equitable, and interdisciplinary approaches. By synthesizing the latest breakthroughs and identifying future opportunities, this review charts a path forward for the integration of AI and neuroscience. From harnessing multimodal data to enabling cognitive augmentation, the fusion of these fields is not just transforming brain science, it is reimagining human potential. This partnership promises a future where the mysteries of the brain are unlocked, offering unprecedented advancements in healthcare, technology, and beyond.

Therapeutic approaches targeting aging and cellular senescence in Huntington's disease

Huntington's disease (HD) is a devastating neurodegenerative disease that is manifested by a gradual loss of physical, cognitive, and mental abilities. As the disease advances, age has a major impact on the pathogenic signature of mutant huntingtin (mHTT) protein aggregation. This review aims to explore the intricate relationship between aging, mHTT toxicity, and cellular senescence in HD. Scientific data on the interplay between aging, mHTT, and cellular senescence in HD were collected from several academic databases, including PubMed, Google Scholar, Google, and ScienceDirect. The search terms employed were "AGING," "HUNTINGTON'S DISEASE," "MUTANT HUNTINGTIN," and "CELLULAR SENESCENCE." Additionally, to gather information on the molecular mechanisms and potential therapeutic targets, the search was extended to include relevant terms such as "DNA DAMAGE," "OXIDATIVE STRESS," and "AUTOPHAGY." According to research, aging leads to worsening HD pathophysiology through some processes. As a result of the mHTT accumulation, cellular senescence is promoted, which causes DNA damage, oxidative stress, decreased autophagy, and increased inflammatory responses. Pro-inflammatory cytokines and other substances are released by senescent cells, which may worsen the neuronal damage and the course of the disease. It has been shown that treatments directed at these pathways reduce some of the HD symptoms and enhance longevity in experimental animals, pointing to a new possibility of treating the condition. Through their amplification of the harmful effects of mHTT, aging and cellular senescence play crucial roles in the development of HD. Comprehending these interplays creates novel opportunities for therapeutic measures targeted at alleviating cellular aging and enhancing HD patients' quality of life.

Deciphering the cellular heterogeneity of the insect brain with single-cell RNA sequencing

Insects show highly complicated adaptive and sophisticated behaviors, including spatial orientation skills, learning ability, and social interaction. These behaviors are controlled by the insect brain, the central part of the nervous system. The tiny insect brain consists of millions of highly differentiated and interconnected cells forming a complex network. Decades of research has gone into an understanding of which parts of the insect brain possess particular behaviors, but exactly how they modulate these functional consequences needs to be clarified. Detailed description of the brain and behavior is required to decipher the complexity of cell types, as well as their connectivity and function. Single-cell RNA-sequencing (scRNA-seq) has emerged recently as a breakthrough technology to understand the transcriptome at cellular resolution. With scRNA-seq, it is possible to uncover the cellular heterogeneity of brain cells and elucidate their specific functions and state. In this review, we first review the basic structure of insect brains and the links to insect behaviors mainly focusing on learning and memory. Then the scRNA applications on insect brains are introduced by representative studies. Single-cell RNA-seq has allowed researchers to classify cell subpopulations within different insect brain regions, pinpoint single-cell developmental trajectories, and identify gene regulatory networks. These developments empower the advances in neuroscience and shed light on the intricate problems in understanding insect brain functions and behaviors.

Unveiling the novel immune and molecular signatures of ovarian cancer: insights and innovations from single-cell sequencing

Ovarian cancer is a highly heterogeneous and lethal malignancy with limited treatment options. Over the past decade, single-cell sequencing has emerged as an advanced biological technology capable of decoding the landscape of ovarian cancer at the single-cell resolution. It operates at the level of genes, transcriptomes, proteins, epigenomes, and metabolisms, providing detailed information that is distinct from bulk sequencing methods, which only offer average data for specific lesions. Single-cell sequencing technology provides detailed insights into the immune and molecular mechanisms underlying tumor occurrence, development, drug resistance, and immune escape. These insights can guide the development of innovative diagnostic markers, therapeutic strategies, and prognostic indicators. Overall, this review provides a comprehensive summary of the diverse applications of single-cell sequencing in ovarian cancer. It encompasses the identification and characterization of novel cell subpopulations, the elucidation of tumor heterogeneity, the investigation of the tumor microenvironment, the analysis of mechanisms underlying metastasis, and the integration of innovative approaches such as organoid models and multi-omics analysis.

Technical Advances and Applications of Spatial Transcriptomics

Transcriptomics is one of the largest areas of research in biological sciences. Aside from RNA expression levels, the significance of RNA spatial context has also been unveiled in the recent decade, playing a critical role in diverse biological processes, from subcellular kinetic regulation to cell communication, from tissue architecture to tumor microenvironment, and more. To systematically unravel the positional patterns of RNA molecules across subcellular, cellular, and tissue levels, spatial transcriptomics techniques have emerged and rapidly became an irreplaceable tool set. Herein, we review and compare current spatial transcriptomics techniques on their methods, advantages, and limitations, as well as applications across a wide range of biological investigations. This review serves as a comprehensive guide to spatial transcriptomics for researchers interested in adopting this powerful suite of technologies.

Single-cell RNA sequencing in orthopedic research

Although previous RNA sequencing methods have been widely used in orthopedic research and have provided ideas for therapeutic strategies, the specific mechanisms of some orthopedic disorders, including osteoarthritis, lumbar disc herniation, rheumatoid arthritis, fractures, tendon injuries, spinal cord injury, heterotopic ossification, and osteosarcoma, require further elucidation. The emergence of the single-cell RNA sequencing (scRNA-seq) technique has introduced a new era of research on these topics, as this method provides information regarding cellular heterogeneity, new cell subtypes, functions of novel subclusters, potential molecular mechanisms, cell-fate transitions, and cell‒cell interactions that are involved in the development of orthopedic diseases. Here, we summarize the cell subpopulations, genes, and underlying mechanisms involved in the development of orthopedic diseases identified by scRNA-seq, improving our understanding of the pathology of these diseases and providing new insights into therapeutic approaches.

Single-cell and single-nuclei RNA sequencing as powerful tools to decipher cellular heterogeneity and dysregulation in neurodegenerative diseases

Neurodegenerative diseases affect millions of people worldwide and there are currently no cures. Two types of common neurodegenerative diseases are Alzheimer's (AD) and Parkinson's disease (PD). Single-cell and single-nuclei RNA sequencing (scRNA-seq and snRNA-seq) have become powerful tools to elucidate the inherent complexity and dynamics of the central nervous system at cellular resolution. This technology has allowed the identification of cell types and states, providing new insights into cellular susceptibilities and molecular mechanisms underlying neurodegenerative conditions. Exciting research using high throughput scRNA-seq and snRNA-seq technologies to study AD and PD is emerging. Herein we review the recent progress in understanding these neurodegenerative diseases using these state-of-the-art technologies. We discuss the fundamental principles and implications of single-cell sequencing of the human brain. Moreover, we review some examples of the computational and analytical tools required to interpret the extensive amount of data generated from these assays. We conclude by highlighting challenges and limitations in the application of these technologies in the study of AD and PD.

Cell-type-specific epigenetic effects of early life stress on the brain

Early life stress (ELS) induces long-term phenotypic adaptations that contribute to increased vulnerability to a host of neuropsychiatric disorders. Epigenetic mechanisms, including DNA methylation, histone modifications and non-coding RNA, are a proposed link between environmental stressors, alterations in gene expression, and phenotypes. Epigenetic modifications play a primary role in shaping functional differences between cell types and can be modified by environmental perturbations, especially in early development. Together with contributions from genetic variation, epigenetic mechanisms orchestrate patterns of gene expression within specific cell types that contribute to phenotypic variation between individuals. To date, many studies have provided insights into epigenetic changes resulting from ELS. However, most of these studies have examined heterogenous brain tissue, despite evidence of cell-type-specific epigenetic modifications in phenotypes associated with ELS. In this review, we focus on rodent and human studies that have examined epigenetic modifications induced by ELS in select cell types isolated from the brain or associated with genes that have cell-type-restricted expression in neurons, microglia, astrocytes, and oligodendrocytes. Although significant challenges remain, future studies using these approaches can enable important mechanistic insight into the role of epigenetic variation in the effects of ELS on brain function.

Sample-multiplexing approaches for single-cell sequencing

Single-cell sequencing is widely used in biological and medical studies. However, its application with multiple samples is hindered by inefficient sample processing, high experimental costs, ambiguous identification of true single cells, and technical batch effects. Here, we introduce sample-multiplexing approaches for single-cell sequencing in transcriptomics, epigenomics, genomics, and multiomics. In single-cell transcriptomics, sample multiplexing uses variants of native or artificial features as sample markers, enabling sample pooling and decoding. Such features include: (1) natural genetic variation, (2) nucleotide-barcode anchoring on cellular or nuclear membranes, (3) nucleotide-barcode internalization to the cytoplasm or nucleus, (4) vector-based barcode expression in cells, and (5) nucleotide-barcode incorporation during library construction. Other single-cell omics methods are based on similar concepts, particularly single-cell combinatorial indexing. These methods overcome current challenges, while enabling super-loading of single cells. Finally, selection guidelines are presented that can accelerate technological application.

Cochlear Development; New Tools and Approaches

The sensory epithelium of the mammalian cochlea, the organ of Corti, is comprised of at least seven unique cell types including two functionally distinct types of mechanosensory hair cells. All of the cell types within the organ of Corti are believed to develop from a population of precursor cells referred to as prosensory cells. Results from previous studies have begun to identify the developmental processes, lineage restrictions and signaling networks that mediate the specification of many of these cell types, however, the small size of the organ and the limited number of each cell type has hampered progress. Recent technical advances, in particular relating to the ability to capture and characterize gene expression at the single cell level, have opened new avenues for understanding cellular specification in the organ of Corti. This review will cover our current understanding of cellular specification in the cochlea, discuss the most commonly used methods for single cell RNA sequencing and describe how results from a recent study using single cell sequencing provided new insights regarding cellular specification.

Forward single-cell sequencing into clinical application: Understanding of cancer microenvironment at single-cell solution

Single‐cell RNA sequencing (scRNA‐seq) is considered an important approach to understand the molecular mechanisms of cancer microenvironmental functions and has the potential for clinical and translational discovery and development. The recent concerns on the impact of scRNA‐seq for clinical practice are whether scRNA can be applied as a routine measurement of clinical biochemistry to assist in clinical decision‐making for diagnosis and therapy. Pushing single‐cell sequencing into clinical application is one of the important missions for clinical and translational medicine (CTM), although there still are a large number of challenges to be overcome. The present Editorial as one of serials aims at overviewing the history of scRNA‐seq publications in CTM, sharing the understanding and consideration of the cancer microenvironment at the single‐cell solution and emphasising the objective of translating scRNA‐seq into clinical application. The dynamic characteristics and patterns of single‐cell identity, regulatory networks, and intercellular communication play decisive roles in the properties of the microenvironment, malignancy and migrative capacity of cancer cells, and defensive capacity of immune cells. The microenvironmental single‐cell transcriptomic profiles and cell clusters defined by scRNA‐seq have great value for exploring the molecular mechanisms of diseases and predicting cell sensitivities to therapy and patient prognosis.

Microglial FABP4-UCP2 Axis Modulates Neuroinflammation and Cognitive Decline in Obese Mice

The microglial fatty-acid-binding protein 4-uncoupling protein 2 (FABP4-UCP2) axis is a key regulator of neuroinflammation in high-fat-diet (HFD)-fed animals, indicating a role for FABP4 in brain immune response. We hypothesized that the FABP4-UCP2 axis is involved in regulating diet-induced cognitive decline. We tested cognitive function in mice lacking microglial FABP4 (AKO mice). Fifteen-week-old male AKO and wild-type (WT) mice were maintained on 60% HFD or normal chow (NC) for 12 weeks. Body composition was measured using EchoMRI. Locomotor activity, working memory, and spatial memory were assessed using behavioral tests (open field, T-maze, and Barnes maze, respectively). Hippocampal microgliosis was assessed via immunohistochemical staining. An inflammatory cytokine panel was assayed using hippocampal tissue. Real-time RT-PCR was performed to measure microglial UCP2 mRNA expression. Our data support that loss of FABP4 prevents cognitive decline in vivo. HFD-fed WT mice exhibited impaired long- and short-term memory, in contrast with HFD-fed AKO mice. HFD-fed WT mice had an increase in hippocampal inflammatory cytokine expression (IFNγ, IL-1β, IL-5, IL-6, KC/GRO(CXCL1), IL-10, and TNFα) and microgliosis, and decreased microglial UCP2 expression. HFD-fed AKO mice had decreased hippocampal inflammatory cytokine expression and microgliosis and increased microglial UCP2 expression compared to HFD-fed WT mice. Collectively, our work supports the idea that the FABP4-UCP2 axis represents a potential therapeutic target in preventing diet-induced cognitive decline.

Coding and long non-coding gene expression changes in the CNS traumatic injuries

Traumatic brain injury (TBI) and spinal cord injury (SCI) are two main central nervous system (CNS) traumas, caused by external physical insults. Both injuries have devastating effects on the quality of life, and there is no effective therapy at present. Notably, gene expression profiling using bulk RNA sequencing (RNA-Seq) and single-cell RNA-Seq (scRNA-Seq) have revealed significant changes in many coding and non-coding genes, as well as important pathways in SCI and TBI. Particularly, recent studies have revealed that long non-coding RNAs (lncRNAs) with lengths greater than 200 nucleotides and without protein-coding potential have tissue- and cell type-specific expression pattern and play critical roles in CNS injury by gain- and loss-of-function approaches. LncRNAs have been shown to regulate protein-coding genes or microRNAs (miRNAs) directly or indirectly, participating in processes including inflammation, glial activation, cell apoptosis, and vasculature events. Therefore, lncRNAs could serve as potential targets for the diagnosis, treatment, and prognosis of SCI and TBI. In this review, we highlight the recent progress in transcriptome studies of SCI and TBI and insights into molecular mechanisms.

Recent Major Transcriptomics and Epitranscriptomics Contributions toward Personalized and Precision Medicine

With the advent of genome-wide screening methods-beginning with microarray technologies and moving onto next generation sequencing methods-the era of precision and personalized medicine was born. Genomics led the way, and its contributions are well recognized. However, "other-omics" fields have rapidly emerged and are becoming as important toward defining disease causes and exploring therapeutic benefits. In this review, we focus on the impacts of transcriptomics, and its extension-epitranscriptomics-on personalized and precision medicine efforts. There has been an explosion of transcriptomic studies particularly in the last decade, along with a growing number of recent epitranscriptomic studies in several disease areas. Here, we summarize and overview major efforts for cancer, cardiovascular disease, and neurodevelopmental disorders (including autism spectrum disorder and intellectual disability) for transcriptomics/epitranscriptomics in precision and personalized medicine. We show that leading advances are being made in both diagnostics, and in investigative and landscaping disease pathophysiological studies. As transcriptomics/epitranscriptomics screens become more widespread, it is certain that they will yield vital and transformative precision and personalized medicine contributions in ways that will significantly further genomics gains.

Single-cell Transcriptional Changes in Neurodegenerative Diseases

In recent decades, our understanding of the molecular changes involved in neurodegenerative diseases has been transformed. Single-cell RNA sequencing and single-nucleus RNA sequencing technologies have been applied to provide cellular and molecular details of the brain at the single-cell level. This has expanded our knowledge of the central nervous system and provided insights into the molecular vulnerability of brain cell types and underlying mechanisms in neurodegenerative diseases. In this review, we highlight the recent advances and findings related to neurodegenerative diseases using these cutting-edge technologies.

The Many Faces of Astrocytes in Alzheimer's Disease

Alzheimer's disease (AD) is a progressive neurodegenerative disease and is the most common cause of dementia in an aging population. The majority of research effort has focused on the role of neurons in neurodegeneration and current therapies have limited ability to slow disease progression. Recently more attention has been given to the role of astrocytes in the process of neurodegeneration. Specifically, reactive astrocytes have both advantageous and adverse effects during neurodegeneration. The ability to isolate and depict astrocyte phenotype has been challenging. However, with the recent development of single-cell sequencing technologies researchers are provided with the resource to delineate specific biomarkers associated with reactive astrocytes in AD. In this review, we will focus on the role of astrocytes in normal conditions and the pathological development of AD. We will further review recent developments in the understanding of astrocyte heterogeneity and associated biomarkers. A better understanding of astrocyte contributions and phenotypic changes in AD can ultimately lead to more effective therapeutic targets.

Failure of Glial Cell-Line Derived Neurotrophic Factor (GDNF) in Clinical Trials Orchestrated By Reduced NR4A2 (NURR1) Transcription Factor in Parkinson's Disease. A Systematic Review

Parkinson’s disease (PD) is one of the most common neurodegenerative maladies with unforeseen complex pathologies. While this neurodegenerative disorder’s neuropathology is reasonably well known, its etiology remains a mystery, making it challenging to aim therapy. Glial cell-line derived neurotrophic factor (GDNF) remains an auspicious therapeutic molecule for treating PD. Neurotrophic factor derived from glial cell lines is effective in rodents and nonhuman primates, but clinical findings have been equivocal. Laborious exertions have been made over the past few decades to improve and assess GDNF in treating PD (clinical studies). Definitive clinical trials have, however, failed to demonstrate a survival advantage. Consequently, there seemed to be a doubt as to whether GDNF has merit in the potential treatment of PD. The purpose of this cutting edge review is to speculate as to why the clinical trials have failed to meet the primary endpoint. We introduce a hypothesis, “Failure of GDNF in clinical trials succumbed by nuclear receptor-related factor 1 (Nurr1) shortfall.” We demonstrate how Nurr1 binds to GDNF to induce dopaminergic neuron synthesis. Due to its undisputable neuro-protection aptitude, we display Nurr1 (also called Nr4a2) as a promising therapeutic target for PD.

Artificial-cell-type aware cell-type classification in CITE-seq

MOTIVATION

Cellular Indexing of Transcriptomes and Epitopes by sequencing (CITE-seq), couples the measurement of surface marker proteins with simultaneous sequencing of mRNA at single cell level, which brings accurate cell surface phenotyping to single-cell transcriptomics. Unfortunately, multiplets in CITE-seq datasets create artificial cell types (ACT) and complicate the automation of cell surface phenotyping.

RESULTS

We propose CITE-sort, an artificial-cell-type aware surface marker clustering method for CITE-seq. CITE-sort is aware of and is robust to multiplet-induced ACT. We benchmarked CITE-sort with real and simulated CITE-seq datasets and compared CITE-sort against canonical clustering methods. We show that CITE-sort produces the best clustering performance across the board. CITE-sort not only accurately identifies real biological cell types (BCT) but also consistently and reliably separates multiplet-induced artificial-cell-type droplet clusters from real BCT droplet clusters. In addition, CITE-sort organizes its clustering process with a binary tree, which facilitates easy interpretation and verification of its clustering result and simplifies cell-type annotation with domain knowledge in CITE-seq.

AVAILABILITY AND IMPLEMENTATION

http://github.com/QiuyuLian/CITE-sort.

SUPPLEMENTARY INFORMATION

Supplementary data is available at Bioinformatics online.

Molecular profiling of single neurons of known identity in two ganglia from the crab Cancer borealis

Single-cell transcriptional profiling has become a widespread tool in cell identification, particularly in the nervous system, based on the notion that genomic information determines cell identity. However, many cell-type classification studies are unconstrained by other cellular attributes (e.g., morphology, physiology). Here, we systematically test how accurately transcriptional profiling can assign cell identity to well-studied anatomically and functionally identified neurons in 2 small neuronal networks. While these neurons clearly possess distinct patterns of gene expression across cell types, their expression profiles are not sufficient to unambiguously confirm their identity. We suggest that true cell identity can only be determined by combining gene expression data with other cellular attributes such as innervation pattern, morphology, or physiology.

Understanding circuit organization depends on identification of cell types. Recent advances in transcriptional profiling methods have enabled classification of cell types by their gene expression. While exceptionally powerful and high throughput, the ground-truth validation of these methods is difficult: If cell type is unknown, how does one assess whether a given analysis accurately captures neuronal identity? To shed light on the capabilities and limitations of solely using transcriptional profiling for cell-type classification, we performed 2 forms of transcriptional profiling—RNA-seq and quantitative RT-PCR, in single, unambiguously identified neurons from 2 small crustacean neuronal networks: The stomatogastric and cardiac ganglia. We then combined our knowledge of cell type with unbiased clustering analyses and supervised machine learning to determine how accurately functionally defined neuron types can be classified by expression profile alone. The results demonstrate that expression profile is able to capture neuronal identity most accurately when combined with multimodal information that allows for post hoc grouping, so analysis can proceed from a supervised perspective. Solely unsupervised clustering can lead to misidentification and an inability to distinguish between 2 or more cell types. Therefore, this study supports the general utility of cell identification by transcriptional profiling, but adds a caution: It is difficult or impossible to know under what conditions transcriptional profiling alone is capable of assigning cell identity. Only by combining multiple modalities of information such as physiology, morphology, or innervation target can neuronal identity be unambiguously determined.

Informing disease modelling with brain-relevant functional genomic annotations

The past decade has seen a surge in the number of disease/trait-associated variants, largely because of the union of studies to share genetic data and the availability of electronic health records from large cohorts for research use. Variant discovery for neurological and neuropsychiatric genome-wide association studies, including schizophrenia, Parkinson's disease and Alzheimer's disease, has greatly benefitted; however, the translation of these genetic association results to interpretable biological mechanisms and models is lagging. Interpreting disease-associated variants requires knowledge of gene regulatory mechanisms and computational tools that permit integration of this knowledge with genome-wide association study results. Here, we summarize key conceptual advances in the generation of brain-relevant functional genomic annotations and amongst tools that allow integration of these annotations with association summary statistics, which together provide a new and exciting opportunity to identify disease-relevant genes, pathways and cell types in silico. We discuss the opportunities and challenges associated with these developments and conclude with our perspective on future advances in annotation generation, tool development and the union of the two.

Microglial NLRP3 inflammasome activation in multiple sclerosis

Multiple sclerosis (MS) is a chronic, autoimmune and neuroinflammatory disease of the central nervous system (CNS) mediated by autoreactive T cells directed against myelin antigens. Although the crucial role of adaptive immunity is well established in MS, the contribution of innate immunity has only recently been appreciated. Microglia are the main innate immune cells of the CNS. Similar to other myeloid cells, microglia recognize both exogenous and host-derived endogenous danger signals through pattern recognition receptors (PRRs) localized on their cell surface such as Toll Like receptor 4, or in the cytosol such as NLRP3. The second one is the sensor protein of the multi-molecular NLRP3 inflammasome complex in activated microglia that promotes the maturation and secretion of proinflammatory cytokines, interleukin-1β and interleukin-18. Overactivation of microglia and aberrant activation of the NLRP3 inflammasome have been implicated in the pathogenesis of MS. Indeed, experimental data, together with post-mortem and clinical studies have revealed an increased expression of NLRP3 inflammasome complex elements in microglia and other immune cells. In this review, we focus on microglial NLRP3 inflammasome activation in MS. First, we overview the basic knowledge about MS, microglia and the NLRP3 inflammasome. Then, we summarize studies about microglial NLRP3 inflammasome activation in MS and its animal models. We also highlight experimental therapeutic approaches that target different steps of NLRP inflammasome activation. Finally, we discuss future research avenues and new methods in this rapidly evolving area.

The in vivo endothelial cell translatome is highly heterogeneous across vascular beds

Endothelial cells (ECs) are highly specialized across vascular beds. However, given their interspersed anatomic distribution, comprehensive characterization of the molecular basis for this heterogeneity in vivo has been limited. By applying endothelial-specific translating ribosome affinity purification (EC-TRAP) combined with high-throughput RNA sequencing analysis, we identified pan EC-enriched genes and tissue-specific EC transcripts, which include both established markers and genes previously unappreciated for their presence in ECs. In addition, EC-TRAP limits changes in gene expression after EC isolation and in vitro expansion, as well as rapid vascular bed-specific shifts in EC gene expression profiles as a result of the enzymatic tissue dissociation required to generate single-cell suspensions for fluorescence-activated cell sorting or single-cell RNA sequencing analysis. Comparison of our EC-TRAP with published single-cell RNA sequencing data further demonstrates considerably greater sensitivity of EC-TRAP for the detection of low abundant transcripts. Application of EC-TRAP to examine the in vivo host response to lipopolysaccharide (LPS) revealed the induction of gene expression programs associated with a native defense response, with marked differences across vascular beds. Furthermore, comparative analysis of whole-tissue and TRAP-selected mRNAs identified LPS-induced differences that would not have been detected by whole-tissue analysis alone. Together, these data provide a resource for the analysis of EC-specific gene expression programs across heterogeneous vascular beds under both physiologic and pathologic conditions.

Microenvironmental Regulation of Tumor Progression and Therapeutic Response in Brain Metastasis

Cellular and non-cellular components of the tumor microenvironment (TME) are emerging as key regulators of primary tumor progression, organ-specific metastasis, and therapeutic response. In the era of TME-targeted- and immunotherapies, cancer-associated inflammation has gained increasing attention. In this regard, the brain represents a unique and highly specialized organ. It has long been regarded as an immunological sanctuary site where the presence of the blood brain barrier (BBB) and blood cerebrospinal fluid barrier (BCB) restricts the entry of immune cells from the periphery. Consequently, tumor cells that metastasize to the brain were thought to be shielded from systemic immune surveillance and destruction. However, the detailed characterization of the immune landscape within border-associated areas of the central nervous system (CNS), such as the meninges and the choroid plexus, as well as the discovery of lymphatics and channels that connect the CNS with the periphery, have recently challenged the dogma of the immune privileged status of the brain. Moreover, the presence of brain metastases (BrM) disrupts the integrity of the BBB and BCB. Indeed, BrM induce the recruitment of different immune cells from the myeloid and lymphoid lineage to the CNS. Blood-borne immune cells together with brain-resident cell-types, such as astrocytes, microglia, and neurons, form a highly complex and dynamic TME that affects tumor cell survival and modulates the mode of immune responses that are elicited by brain metastatic tumor cells. In this review, we will summarize recent findings on heterotypic interactions within the brain metastatic TME and highlight specific functions of brain-resident and recruited cells at different rate-limiting steps of the metastatic cascade. Based on the insight from recent studies, we will discuss new opportunities and challenges for TME-targeted and immunotherapies for BrM.

Effects of Neurotrophic Factors in Glial Cells in the Central Nervous System: Expression and Properties in Neurodegeneration and Injury

Astrocytes, oligodendrocytes, and microglia are abundant cell types found in the central nervous system and have been shown to play crucial roles in regulating both normal and disease states. An increasing amount of evidence points to the critical importance of glia in mediating neurodegeneration in Alzheimer’s and Parkinson’s diseases (AD, PD), and in ischemic stroke, where microglia are involved in initial tissue clearance, and astrocytes in the subsequent formation of a glial scar. The importance of these cells for neuronal survival has previously been studied in co-culture experiments and the search for neurotrophic factors (NTFs) initiated after finding that the addition of conditioned media from astrocyte cultures could support the survival of primary neurons in vitro. This led to the discovery of the potent dopamine neurotrophic factor, glial cell line-derived neurotrophic factor (GDNF). In this review, we focus on the relationship between glia and NTFs including neurotrophins, GDNF-family ligands, CNTF family, and CDNF/MANF-family proteins. We describe their expression in astrocytes, oligodendrocytes and their precursors (NG2-positive cells, OPCs), and microglia during development and in the adult brain. Furthermore, we review existing data on the glial phenotypes of NTF knockout mice and follow NTF expression patterns and their effects on glia in disease models such as AD, PD, stroke, and retinal degeneration.

Dissemination of brain inflammation in traumatic brain injury

Traumatic brain injury (TBI) is recognized as a global health problem due to its increasing occurrence, challenging treatment, and persistent impacts on brain pathophysiology. Neural cell death in patients with TBI swiftly causes inflammation in the injured brain areas, which is recognized as focal brain inflammation. Focal brain inflammation causes secondary brain injury by exacerbating brain edema and neuronal death, while also exerting divergent beneficial effects, such as sealing the damaged limitans and removing cellular debris. Recent evidence from patients with TBI and studies on animal models suggest that brain inflammation after TBI is not only restricted to the focal lesion but also disseminates to remote areas of the brain. The dissemination of inflammation has been detected within days after the primary injury and persists chronically. This state of inflammation may be related to remote complications of TBI in patients, such as hyperthermia and hypopituitarism, and may lead to progressive neurodegeneration, such as chronic traumatic encephalopathy. Future studies should focus on understanding the mechanisms that govern the initiation and propagation of brain inflammation after TBI and its impacts on post-trauma brain pathology.

Compartmentalized Devices as Tools for Investigation of Human Brain Network Dynamics

Neuropsychiatric disorders have traditionally been difficult to study due to the complexity of the human brain and limited availability of human tissue. Induced pluripotent stem (iPS) cells provide a promising avenue to further our understanding of human disease mechanisms, but traditional 2D cell cultures can only provide a limited view of the neural circuits. To better model complex brain neurocircuitry, compartmentalized culturing systems and 3D organoids have been developed. Early compartmentalized devices demonstrated how neuronal cell bodies can be isolated both physically and chemically from neurites. Soft lithographic approaches have advanced this approach and offer the tools to construct novel model platforms, enabling circuit-level studies of disease, which can accelerate mechanistic studies and drug candidate screening. In this review, we describe some of the common technologies used to develop such systems and discuss how these lithographic techniques have been used to advance our understanding of neuropsychiatric disease. Finally, we address other in vitro model platforms such as 3D culture systems and organoids and compare these models with compartmentalized models. We ask important questions regarding how we can further harness iPS cells in these engineered culture systems for the development of improved in vitro models. Developmental Dynamics 248:65-77, 2019. © 2018 Wiley Periodicals, Inc.

Characterization of spatial and temporal development of Type I and Type II hair cells in the mouse utricle using new cell-type-specific markers

The utricle of the inner ear, a vestibular sensory structure that mediates perception of linear acceleration, is comprised of two morphologically and physiologically distinct types of mechanosensory hair cells, referred to as Type Is and Type IIs. While these cell types are easily discriminated in an adult utricle, understanding their development has been hampered by a lack of molecular markers that can be used to identify each cell type prior to maturity. Therefore, we collected single hair cells at three different ages and used single cell RNAseq to characterize the transcriptomes of those cells. Analysis of differential gene expression identified Spp1 as a specific marker for Type I hair cells and Mapt and Anxa4 as specific markers for Type II hair cells. Antibody labeling confirmed the specificity of these markers which were then used to examine the temporal and spatial development of utricular hair cells. While Type I hair cells develop in a gradient that extends across the utricle from posterior-medial to anterior-lateral, Type II hair cells initially develop in the central striolar region and then extend uniformly towards the periphery. Finally, by combining these markers with genetic fate mapping, we demonstrate that over 98% of all Type I hair cells develop prior to birth while over 98% of Type II hair cells develop post-natally. These results are consistent with previous findings suggesting that Type I hair cells develop first and refute the hypothesis that Type II hair cells represent a transitional form between immature and Type I hair cells.

The Kaleidoscope of Microglial Phenotypes

Gene expression analyses of microglia, the tissue-resident macrophages of the central nervous system (CNS), led to the identification of homeostatic as well as neurological disease-specific gene signatures of microglial phenotypes. Upon alterations in the neural microenvironment, either caused by local insults from within the CNS (during neurodegenerative diseases) or by macroenvironmental incidents, such as social stress, microglia can switch phenotypes-generally referred to as "microglial activation." The interplay between the microenvironment and its influence on microglial phenotypes, regulated by (epi)genetic mechanisms, can be imagined as the different colorful crystal formations (microglial phenotypes) that change upon rotation (microenvironmental changes) of a kaleidoscope. In this review, we will discuss microglial phenotypes in relation to neurodevelopment, homeostasis, in vitro conditions, aging, and neurodegenerative diseases based on transcriptome studies. By overlaying these disease-specific microglial signatures, recent publications have identified a specific set of genes that is differentially expressed in all investigated diseases, called a microglial core gene signature with multiple diseases. We will conclude this review with a discussion about the complexity of this microglial core gene signature associated with multiple diseases.

Bioorthogonal Metabolic Labeling of Nascent RNA in Neurons Improves the Sensitivity of Transcriptome-Wide Profiling

Transcriptome-wide expression profiling of neurons has provided important insights into the underlying molecular mechanisms and gene expression patterns that transpire during learning and memory formation. However, there is a paucity of tools for profiling stimulus-induced RNA within specific neuronal cell populations. A bioorthogonal method to chemically label nascent (i.e., newly transcribed) RNA in a cell-type-specific and temporally controlled manner, which is also amenable to bioconjugation via click chemistry, was recently developed and optimized within conventional immortalized cell lines. However, its value within a more fragile and complicated cellular system such as neurons, as well as for transcriptome-wide expression profiling, has yet to be demonstrated. Here, we report the visualization and sequencing of activity-dependent nascent RNA derived from neurons using this labeling method. This work has important implications for improving transcriptome-wide expression profiling and visualization of nascent RNA in neurons, which has the potential to provide valuable insights into the mechanisms underlying neural plasticity, learning, and memory.

Concurrent cell type-specific isolation and profiling of mouse brains in inflammation and Alzheimer's disease

Nonneuronal cell types in the CNS are increasingly implicated as critical players in brain health and disease. While gene expression profiling of bulk brain tissue is routinely used to examine alterations in the brain under various conditions, it does not capture changes that occur within single cell types or allow interrogation of crosstalk among cell types. To this end, we have developed a concurrent brain cell type acquisition (CoBrA) methodology, enabling the isolation and profiling of microglia, astrocytes, endothelia, and oligodendrocytes from a single adult mouse forebrain. By identifying and validating anti-ACSA-2 and anti-CD49a antibodies as cell surface markers for astrocytes and vascular endothelial cells, respectively, and using established antibodies to isolate microglia and oligodendrocytes, we document that these 4 major cell types are isolated with high purity and RNA quality. We validated our procedure by performing acute peripheral LPS challenge, while highlighting the underappreciated changes occurring in astrocytes and vascular endothelia in addition to microglia. Furthermore, we assessed cell type-specific gene expression changes in response to amyloid pathology in a mouse model of Alzheimer's disease. Our CoBrA methodology can be readily implemented to interrogate multiple CNS cell types in any mouse model at any age.

Unraveling of Central Nervous System Disease Mechanisms Using CRISPR Genome Manipulation

The complex structure and highly variable gene expression profile of the brain makes it among the most challenging fields to study in both basic and translational biological research. Most of the brain diseases are multifactorial and despite the rapidly increasing genomic data, molecular pathways and causal links between genes and central nervous system (CNS) diseases are largely unknown. The advent of an easy and flexible CRISPR-Cas genome editing technology has rapidly revolutionized the field of functional genomics and opened unprecedented possibilities to dissect the mechanisms of CNS disease. CRISPR-Cas allows a plenitude of applications for both gene-focused and genome-wide approaches, ranging from original “gene scissors” making permanent modifications in the genome to the regulation of gene expression and epigenetics. CRISPR technology provides a unique opportunity to establish new cellular and animal models of CNS diseases and holds potential for breakthroughs in the CNS research and drug development.

Single-Cell RNA-Sequencing in Glioma

PURPOSE OF REVIEW

In this review, we seek to summarize the literature concerning the use of single-cell RNA-sequencing for CNS gliomas.

RECENT FINDINGS

Single-cell analysis has revealed complex tumor heterogeneity, subpopulations of proliferating stem-like cells and expanded our view of tumor microenvironment influence in the disease process. Although bulk RNA-sequencing has guided our initial understanding of glioma genetics, this method does not accurately define the heterogeneous subpopulations found within these tumors. Single-cell techniques have appealing applications in cancer research, as diverse cell types and the tumor microenvironment have important implications in therapy. High cost and difficult protocols prevent widespread use of single-cell RNA-sequencing; however, continued innovation will improve accessibility and expand our of knowledge gliomas.

Genome-wide mapping of genetic determinants influencing DNA methylation and gene expression in human hippocampus

Emerging evidence emphasizes the strong impact of regulatory genomic elements in neurodevelopmental processes and the complex pathways of brain disorders. The present genome-wide quantitative trait loci analyses explore the cis-regulatory effects of single-nucleotide polymorphisms (SNPs) on DNA methylation (meQTL) and gene expression (eQTL) in 110 human hippocampal biopsies. We identify cis-meQTLs at 14,118 CpG methylation sites and cis-eQTLs for 302 3'-mRNA transcripts of 288 genes. Hippocampal cis-meQTL-CpGs are enriched in flanking regions of active promoters, CpG island shores, binding sites of the transcription factor CTCF and brain eQTLs. Cis-acting SNPs of hippocampal meQTLs and eQTLs significantly overlap schizophrenia-associated SNPs. Correlations of CpG methylation and RNA expression are found for 34 genes. Our comprehensive maps of cis-acting hippocampal meQTLs and eQTLs provide a link between disease-associated SNPs and the regulatory genome that will improve the functional interpretation of non-coding genetic variants in the molecular genetic dissection of brain disorders.

Lessons from single-cell transcriptome analysis of oxygen-sensing cells

The advent of single-cell RNA-sequencing (RNA-Seq) technology has enabled transcriptome profiling of individual cells. Comprehensive gene expression analysis at the single-cell level has proven to be effective in characterizing the most fundamental aspects of cellular function and identity. This unbiased approach is revolutionary for small and/or heterogeneous tissues like oxygen-sensing cells in identifying key molecules. Here, we review the major methods of current single-cell RNA-Seq technology. We discuss how this technology has advanced the understanding of oxygen-sensing glomus cells in the carotid body and helped uncover novel oxygen-sensing cells and mechanisms in the mice olfactory system. We conclude by providing our perspective on future single-cell RNA-Seq research directed at oxygen-sensing cells.