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Cell-cell interactions in the central nervous system play important roles in neurologic diseases. However, little is known about the specific molecular pathways involved, and methods for their systematic identification are limited. Here, we developed a forward genetic screening platform that combines CRISPR-Cas9 perturbations, cell coculture in picoliter droplets, and microfluidic-based fluorescence-activated droplet sorting to identify mechanisms of cell-cell communication. We used SPEAC-seq (systematic perturbation of encapsulated associated cells followed by sequencing), in combination with in vivo genetic perturbations, to identify microglia-produced amphiregulin as a suppressor of disease-promoting astrocyte responses in multiple sclerosis preclinical models and clinical samples. Thus, SPEAC-seq enables the high-throughput systematic identification of cell-cell communication mechanisms.

Multiple sclerosis is a chronic inflammatory disease of the central nervous system1. Astrocytes are heterogeneous glial cells that are resident in the central nervous system and participate in the pathogenesis of multiple sclerosis and its model experimental autoimmune encephalomyelitis2,3. However, few unique surface markers are available for the isolation of astrocyte subsets, preventing their analysis and the identification of candidate therapeutic targets; these limitations are further amplified by the rarity of pathogenic astrocytes. Here, to address these challenges, we developed focused interrogation of cells by nucleic acid detection and sequencing (FIND-seq), a high-throughput microfluidic cytometry method that combines encapsulation of cells in droplets, PCR-based detection of target nucleic acids and droplet sorting to enable in-depth transcriptomic analyses of cells of interest at single-cell resolution. We applied FIND-seq to study the regulation of astrocytes characterized by the splicing-driven activation of the transcription factor XBP1, which promotes disease pathology in multiple sclerosis and experimental autoimmune encephalomyelitis4. Using FIND-seq in combination with conditional-knockout mice, in vivo CRISPR-Cas9-driven genetic perturbation studies and bulk and single-cell RNA sequencing analyses of samples from mouse experimental autoimmune encephalomyelitis and humans with multiple sclerosis, we identified a new role for the nuclear receptor NR3C2 and its corepressor NCOR2 in limiting XBP1-driven pathogenic astrocyte responses. In summary, we used FIND-seq to identify a therapeutically targetable mechanism that limits XBP1-driven pathogenic astrocyte responses. FIND-seq enables the investigation of previously inaccessible cells, including rare cell subsets defined by unique gene expression signatures or other nucleic acid markers.

Cell-cell interactions control the physiology and pathology of the central nervous system (CNS). To study astrocyte cell interactions in vivo, we developed rabies barcode interaction detection followed by sequencing (RABID-seq), which combines barcoded viral tracing and single-cell RNA sequencing (scRNA-seq). Using RABID-seq, we identified axon guidance molecules as candidate mediators of microglia-astrocyte interactions that promote CNS pathology in experimental autoimmune encephalomyelitis (EAE) and, potentially, multiple sclerosis (MS). In vivo cell-specific genetic perturbation EAE studies, in vitro systems, and the analysis of MS scRNA-seq datasets and CNS tissue established that Sema4D and Ephrin-B3 expressed in microglia control astrocyte responses via PlexinB2 and EphB3, respectively. Furthermore, a CNS-penetrant EphB3 inhibitor suppressed astrocyte and microglia proinflammatory responses and ameliorated EAE. In summary, RABID-seq identified microglia-astrocyte interactions and candidate therapeutic targets.

Analyzing every cell in a diverse sample provides insight into population-level heterogeneity, but abundant cell types dominate the analysis and rarer populations are scarcely represented in the data. To focus on specific cell types, the current paradigm is to physically isolate subsets of interest prior to analysis; however, it remains difficult to isolate and then single-cell sequence such populations because of compounding losses. Here, we describe an alternative approach that selectively merges cells with reagents to achieve enzymatic reactions without having to physically isolate cells. We apply this technique to perform single-cell transcriptome and genome sequencing of specific cell subsets. Our method for analyzing heterogeneous populations obviates the need for pre- or post-enrichment and simplifies single-cell workflows, making it useful for other applications in single-cell biology, combinatorial chemical synthesis, and drug screening.

Multiple sclerosis is a chronic inflammatory disease of the CNS1. Astrocytes contribute to the pathogenesis of multiple sclerosis2, but little is known about the heterogeneity of astrocytes and its regulation. Here we report the analysis of astrocytes in multiple sclerosis and its preclinical model experimental autoimmune encephalomyelitis (EAE) by single-cell RNA sequencing in combination with cell-specific Ribotag RNA profiling, assay for transposase-accessible chromatin with sequencing (ATAC-seq), chromatin immunoprecipitation with sequencing (ChIP-seq), genome-wide analysis of DNA methylation and in vivo CRISPR-Cas9-based genetic perturbations. We identified astrocytes in EAE and multiple sclerosis that were characterized by decreased expression of NRF2 and increased expression of MAFG, which cooperates with MAT2α to promote DNA methylation and represses antioxidant and anti-inflammatory transcriptional programs. Granulocyte-macrophage colony-stimulating factor (GM-CSF) signalling in astrocytes drives the expression of MAFG and MAT2α and pro-inflammatory transcriptional modules, contributing to CNS pathology in EAE and, potentially, multiple sclerosis. Our results identify candidate therapeutic targets in multiple sclerosis.

Author(s): Benjamin M. Scott [sup.1] [sup.2] [sup.3] [sup.9] , Cristina Gutiérrez-Vázquez [sup.4] , Liliana M. Sanmarco [sup.4] , Jessica A. da Silva Pereira [sup.4] , Zhaorong Li [sup.4] , Agustín [...], Inflammatory bowel disease (IBD) is a complex chronic inflammatory disorder of the gastrointestinal tract. Extracellular adenosine triphosphate (eATP) produced by the commensal microbiota and host cells activates purinergic signaling, promoting intestinal inflammation and pathology. Based on the role of eATP in intestinal inflammation, we developed yeast-based engineered probiotics that express a human P2Y2 purinergic receptor with up to a 1,000-fold increase in eATP sensitivity. We linked the activation of this engineered P2Y2 receptor to the secretion of the ATP-degrading enzyme apyrase, thus creating engineered yeast probiotics capable of sensing a pro-inflammatory molecule and generating a proportional self-regulated response aimed at its neutralization. These self-tunable yeast probiotics suppressed intestinal inflammation in mouse models of IBD, reducing intestinal fibrosis and dysbiosis with an efficacy similar to or higher than that of standard-of-care therapies usually associated with notable adverse events. By combining directed evolution and synthetic gene circuits, we developed a unique self-modulatory platform for the treatment of IBD and potentially other inflammation-driven pathologies. A synthetic yeast-based therapeutic that secretes an ATP-degrading enzyme in response to pro-inflammatory extracellular ATP in the gut reduces intestinal inflammation, fibrosis and dysbiosis in mouse models of colitis and enteritis.

Author(s): Liliana M. Sanmarco [sup.1] , Michael A. Wheeler [sup.1] [sup.2] , Cristina Gutiérrez-Vázquez [sup.1] , Carolina Manganeli Polonio [sup.1] , Mathias Linnerbauer [sup.1] , Felipe A. Pinho-Ribeiro [sup.3] , [...], Astrocytes are glial cells that are abundant in the central nervous system (CNS) and that have important homeostatic and disease-promoting functions.sup.1. However, little is known about the homeostatic anti-inflammatory activities of astrocytes and their regulation. Here, using high-throughput flow cytometry screening, single-cell RNA sequencing and CRISPR-Cas9-based cell-specific in vivo genetic perturbations in mice, we identify a subset of astrocytes that expresses the lysosomal protein LAMP1.sup.2 and the death receptor ligand TRAIL.sup.3. LAMP1.sup.+TRAIL.sup.+ astrocytes limit inflammation in the CNS by inducing T cell apoptosis through TRAIL-DR5 signalling. In homeostatic conditions, the expression of TRAIL in astrocytes is driven by interferon-[gamma] (IFN[gamma]) produced by meningeal natural killer (NK) cells, in which IFN[gamma] expression is modulated by the gut microbiome. TRAIL expression in astrocytes is repressed by molecules produced by T cells and microglia in the context of inflammation. Altogether, we show that LAMP1.sup.+TRAIL.sup.+ astrocytes limit CNS inflammation by inducing T cell apoptosis, and that this astrocyte subset is maintained by meningeal IFN[gamma].sup.+ NK cells that are licensed by the microbiome. A subpopulation of astrocytes characterized by the expression of LAMP1 and TRAIL limits inflammation in the central nervous system through a mechanism involving the microbiota-modulated expression of IFN[gamma] in meningeal natural killer cells.

This study investigates a novel approach for assessing the health status of rotating machinery transmission systems by analyzing the dynamic degradation of bearings. The proposed method generates multi-dimensional data by creating virtual states and constructs a multi-dimensional model using virtual state-space in conjunction with mechanism model analysis. Innovatively, the Hammerstein–Wiener (HW) modeling technique from control theory is applied to identify these dynamic multi-dimensional models. The modeling experiments are performed, focusing on the model's input and output types, the selection of nonlinear module estimators, the configuration of linear module transfer functions, and condition transfer. Dynamic degradation response signals are generated, and the method is validated using four widely recognized databases consisting of accurate measurement signals collected by vibration sensors. Experimental results demonstrated that the model achieved a modeling accuracy of 99% for multiple bearings under various conditions. The effectiveness of this dynamic modeling method is further confirmed through comparative experimental data and signal images. This approach offers a novel reference for evaluating the health status of transmission systems. [ABSTRACT FROM AUTHOR]