{"title":"SPEAC-seq: A new method to investigate astrocyte-microglia crosstalk","authors":"Yao Tang, Fuchen Liu","doi":"10.1002/brx2.22","DOIUrl":null,"url":null,"abstract":"<p>Multicellular organisms rely on cellular communication to function. Numerous biological activities depend on the dynamic communication networks created by cellular communication. In neuroinflammation, crosstalk between astrocytes and microglia plays a crucial role. Aberrant interactions between these two sub-types of glial cells have been implicated in several neuroimmunological diseases, such as multiple sclerosis (MS)—a chronic inflammatory disorder of the central nervous system (CNS)—and its preclinical model, experimental autoimmune encephalomyelitis (EAE).<span><sup>1</sup></span> As is known, specific cell signaling pathways are activated by receptors via selective detection and interaction with signal molecules (ligands). This results in the conversion of these molecules into intracellular messages. Accordingly, analysis of ligand-receptor pair interactions forms the basis for understanding cell behavior.<span><sup>2</sup></span> However, current methods fail to establish causal links between cellular interactions and molecular states. Furthermore, despite the CRISPR-Cas9 system serving as a powerful tool for gene identification, there are noted limitations relating to high-throughput co-culture and screening of the perturbation of single cells.<span><sup>3</sup></span> Recently, Professor Francisco J. Quintana's team developed a novel technique to identify forward genetic screens of cell–cell interaction mechanisms, which they call systematic perturbation of encapsulated associated cells followed by sequencing (SPEAC-seq). It combines CRISPR-Cas9 perturbations, co-culture of cells in droplets, and fluorescence-activated droplet sorting based on microfluidics (Figure 1).<span><sup>4</sup></span></p><p>The researchers established a preliminary microfluidic platform for studying cell-cell interactions. Firstly, a microfluidic co-flow system using two aqueous suspensions (one for each cell type) and oil was used to generate picoliter water-in-oil droplets containing cell pairs. For subsequent studies of cellular interactions, detection and selection were performed using a custom three-color optical system and dielectrophoretic microfluidic sorter. Next, the study was extended to cell pairs to determine if the cues generated by one cell were sufficient to alter the cellular state of cells co-cultured in the same droplet. Multiple labeling using a fluorescent dye with cell permeability was used for spiking and detection of cell pairs in the droplets. Results showed the upregulation of EGFP expression in NF-κB-labeled astrocytes paired with activated macrophages, as initially detected in isolated reporter cell pairs and following optimization of droplet sorting parameters. The above indicates that the researchers have successfully established an oil-in-droplet-based co-culture system. Subsequently, based on the microdroplet co-culture system combined with CRISPR-Cas9 perturbations, SPEAC-seq was developed as a forward genetic screening platform for regulating cell-cell interactions. Through this method, factors or proteins produced by microglia involved in inhibiting NF-κB activation in astrocytes were identified. To investigate the candidate proteins involved in regulating cell-cell communication pathways, the researchers identified four candidate growth factors (<i>Areg</i>, <i>Nrtn</i>, <i>Fgl1</i>, and <i>Pnoc</i>) that are expressed by microglia and that signal via four independent receptors, expressed by astrocytes (<i>Egfr</i>, <i>Lag3</i>, <i>Gfra2</i>, <i>Oprl1</i>). To further evaluate the regulatory effects of each candidate pathway as revealed by SPEAC-seq in inflammation, a cell-type-specific in vivo Perturb-seq method was applied. In the EAE model, targeting <i>Egfr</i> resulted in the strongest activation of IL-1β/TNFα signaling, promoting NF-κB-driven astrocyte reactions that are associated with EAE and MS. The <i>Egfr</i> ligand identified by SPEAC-seq was <i>Areg</i> which encodes amphiregulin. Thus, <i>Areg</i> secreted by microglia inhibits the pro-inflammatory response of astrocytes via the <i>Egfr</i> receptor. The researchers then investigated CNS pathology by inducing <i>Areg</i> expression in microglia in EAE. IL-33 has been identified as an inhibitor of EAE and an inducer of <i>Areg</i> expression. IL-33 is also an alarmin released by cells following tissue injury.<span><sup>5</sup></span> To determine whether IL-33 regulates <i>Areg</i>-mediated microglia-astrocyte interactions, the researchers reanalyzed a previous sequencing dataset. This revealed that IL-33 signal transduction triggered by astrocytes is a putative upstream regulator for <i>Areg</i>+ microglia. These findings indicate a regulatory feedback loop in which astrocyte-produced IL-33 induces <i>Areg</i> expression in microglia, which in turn acts on astrocytes to inhibit disease-promoting reactions.</p><p>Elucidating the mechanisms behind cellular interactions may lead to the discovery of potential therapeutic targets for CNS diseases. Thus, the platform outlined above has many potential applications. Furthermore, it enables researchers to investigate interactions between any two types of cell in the CNS (e.g., neuron-astrocyte, neuron-microglia, astrocyte-microglia, etc.), allowing high-throughput and systematic identification of ligand-receptor pair interactions in cell-cell communication. Previously, numerous methods have been created and used extensively in research on receptors and ligands. However, they rely heavily on established databases. Additionally, since the majority of methods currently used to investigate cellular connections involve genetic analysis, understanding of ligand-receptor binding complexes at the protein level remains limited. In the future, SPEAC-seq may be combined with genetic manipulation, or multi-omics, such as epigenome, transcriptome, proteome and/or metabolome analyses, to identify therapeutics that can change cell-cell interactions. Alternatively, it could be combined with antibodies or small molecule barcoded libraries to identify therapeutic regulators of cell-cell communication. Accordingly, SPEAC-seq may be of great value and offer a wide range of potential applications.</p><p><b>Yao Tang</b>: Writing – original draft. <b>Fuchen Liu</b>: Writing – review & editing.</p><p>The authors declare no conflicts of interest.</p>","PeriodicalId":94303,"journal":{"name":"Brain-X","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/brx2.22","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Brain-X","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/brx2.22","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Multicellular organisms rely on cellular communication to function. Numerous biological activities depend on the dynamic communication networks created by cellular communication. In neuroinflammation, crosstalk between astrocytes and microglia plays a crucial role. Aberrant interactions between these two sub-types of glial cells have been implicated in several neuroimmunological diseases, such as multiple sclerosis (MS)—a chronic inflammatory disorder of the central nervous system (CNS)—and its preclinical model, experimental autoimmune encephalomyelitis (EAE).1 As is known, specific cell signaling pathways are activated by receptors via selective detection and interaction with signal molecules (ligands). This results in the conversion of these molecules into intracellular messages. Accordingly, analysis of ligand-receptor pair interactions forms the basis for understanding cell behavior.2 However, current methods fail to establish causal links between cellular interactions and molecular states. Furthermore, despite the CRISPR-Cas9 system serving as a powerful tool for gene identification, there are noted limitations relating to high-throughput co-culture and screening of the perturbation of single cells.3 Recently, Professor Francisco J. Quintana's team developed a novel technique to identify forward genetic screens of cell–cell interaction mechanisms, which they call systematic perturbation of encapsulated associated cells followed by sequencing (SPEAC-seq). It combines CRISPR-Cas9 perturbations, co-culture of cells in droplets, and fluorescence-activated droplet sorting based on microfluidics (Figure 1).4
The researchers established a preliminary microfluidic platform for studying cell-cell interactions. Firstly, a microfluidic co-flow system using two aqueous suspensions (one for each cell type) and oil was used to generate picoliter water-in-oil droplets containing cell pairs. For subsequent studies of cellular interactions, detection and selection were performed using a custom three-color optical system and dielectrophoretic microfluidic sorter. Next, the study was extended to cell pairs to determine if the cues generated by one cell were sufficient to alter the cellular state of cells co-cultured in the same droplet. Multiple labeling using a fluorescent dye with cell permeability was used for spiking and detection of cell pairs in the droplets. Results showed the upregulation of EGFP expression in NF-κB-labeled astrocytes paired with activated macrophages, as initially detected in isolated reporter cell pairs and following optimization of droplet sorting parameters. The above indicates that the researchers have successfully established an oil-in-droplet-based co-culture system. Subsequently, based on the microdroplet co-culture system combined with CRISPR-Cas9 perturbations, SPEAC-seq was developed as a forward genetic screening platform for regulating cell-cell interactions. Through this method, factors or proteins produced by microglia involved in inhibiting NF-κB activation in astrocytes were identified. To investigate the candidate proteins involved in regulating cell-cell communication pathways, the researchers identified four candidate growth factors (Areg, Nrtn, Fgl1, and Pnoc) that are expressed by microglia and that signal via four independent receptors, expressed by astrocytes (Egfr, Lag3, Gfra2, Oprl1). To further evaluate the regulatory effects of each candidate pathway as revealed by SPEAC-seq in inflammation, a cell-type-specific in vivo Perturb-seq method was applied. In the EAE model, targeting Egfr resulted in the strongest activation of IL-1β/TNFα signaling, promoting NF-κB-driven astrocyte reactions that are associated with EAE and MS. The Egfr ligand identified by SPEAC-seq was Areg which encodes amphiregulin. Thus, Areg secreted by microglia inhibits the pro-inflammatory response of astrocytes via the Egfr receptor. The researchers then investigated CNS pathology by inducing Areg expression in microglia in EAE. IL-33 has been identified as an inhibitor of EAE and an inducer of Areg expression. IL-33 is also an alarmin released by cells following tissue injury.5 To determine whether IL-33 regulates Areg-mediated microglia-astrocyte interactions, the researchers reanalyzed a previous sequencing dataset. This revealed that IL-33 signal transduction triggered by astrocytes is a putative upstream regulator for Areg+ microglia. These findings indicate a regulatory feedback loop in which astrocyte-produced IL-33 induces Areg expression in microglia, which in turn acts on astrocytes to inhibit disease-promoting reactions.
Elucidating the mechanisms behind cellular interactions may lead to the discovery of potential therapeutic targets for CNS diseases. Thus, the platform outlined above has many potential applications. Furthermore, it enables researchers to investigate interactions between any two types of cell in the CNS (e.g., neuron-astrocyte, neuron-microglia, astrocyte-microglia, etc.), allowing high-throughput and systematic identification of ligand-receptor pair interactions in cell-cell communication. Previously, numerous methods have been created and used extensively in research on receptors and ligands. However, they rely heavily on established databases. Additionally, since the majority of methods currently used to investigate cellular connections involve genetic analysis, understanding of ligand-receptor binding complexes at the protein level remains limited. In the future, SPEAC-seq may be combined with genetic manipulation, or multi-omics, such as epigenome, transcriptome, proteome and/or metabolome analyses, to identify therapeutics that can change cell-cell interactions. Alternatively, it could be combined with antibodies or small molecule barcoded libraries to identify therapeutic regulators of cell-cell communication. Accordingly, SPEAC-seq may be of great value and offer a wide range of potential applications.
Yao Tang: Writing – original draft. Fuchen Liu: Writing – review & editing.