SPEAC-seq: A new method to investigate astrocyte-microglia crosstalk

Brain-X Pub Date : 2023-06-28 DOI:10.1002/brx2.22
Yao Tang, Fuchen Liu
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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. 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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.

The authors declare no conflicts of interest.

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SPEAC seq:一种研究星形胶质细胞-小胶质细胞串扰的新方法
多细胞生物依靠细胞通讯来发挥作用。许多生物活动依赖于由细胞通信创建的动态通信网络。在神经炎症中,星形胶质细胞和小胶质细胞之间的相互作用起着至关重要的作用。这两种亚型神经胶质细胞之间的异常相互作用与几种神经免疫学疾病有关,如多发性硬化症(MS)——一种中枢神经系统的慢性炎症性疾病——及其临床前模型——实验性自身免疫性脑脊髓炎(EAE)。1众所周知,受体通过选择性检测和与信号分子(配体)的相互作用激活特定的细胞信号通路。这导致这些分子转化为细胞内信息。因此,配体-受体对相互作用的分析构成了理解细胞行为的基础。2然而,目前的方法未能建立细胞相互作用和分子状态之间的因果关系。此外,尽管CRISPR-Cas9系统是基因鉴定的有力工具,但在高通量共培养和单细胞扰动筛选方面存在显著的局限性。3最近,Francisco J.Quintana教授的团队开发了一种新技术,用于鉴定细胞-细胞相互作用机制的正向遗传筛选,他们称之为封装的相关细胞的系统扰动,随后进行测序(SPEAC seq)。它结合了CRISPR-Cas9扰动、液滴中细胞的共培养和基于微流体的荧光激活液滴分选(图1)。4研究人员建立了一个用于研究细胞-细胞相互作用的初步微流体平台。首先,使用两种水悬浮液(每种细胞类型一种)和油的微流体共流系统来产生含有细胞对的微升油包水液滴。对于随后的细胞相互作用研究,使用定制的三色光学系统和介电泳微流体分类器进行检测和选择。接下来,该研究扩展到细胞对,以确定一个细胞产生的线索是否足以改变在同一液滴中共同培养的细胞的细胞状态。使用具有细胞渗透性的荧光染料进行多重标记用于液滴中细胞对的加标和检测。结果显示,在NF-κB标记的星形胶质细胞与活化的巨噬细胞配对中,EGFP表达上调,最初在分离的报告细胞对中检测到,并在液滴分选参数优化后检测到。以上表明,研究人员已经成功建立了一个基于液滴油的共培养系统。随后,基于微滴共培养系统和CRISPR-Cas9扰动,SPEAC-seq被开发为一个用于调节细胞-细胞相互作用的正向遗传筛选平台。通过这种方法,鉴定了小胶质细胞产生的参与抑制星形胶质细胞NF-κB活化的因子或蛋白质。为了研究参与调节细胞-细胞通讯途径的候选蛋白,研究人员确定了四种候选生长因子(Areg、Nrtn、Fgl1和Pnoc),它们由小胶质细胞表达,并通过星形胶质细胞表达的四种独立受体(Egfr、Lag3、Gfra2、Oprl1)发出信号。为了进一步评估SPEAC-seq揭示的每个候选途径在炎症中的调节作用,应用了细胞类型特异性的体内扰动seq方法。在EAE模型中,靶向Egfr导致IL-1β/TNFα信号传导的最强激活,促进与EAE和MS相关的NF-κB驱动的星形胶质细胞反应。SPEAC-seq鉴定的Egfr配体是编码两调节蛋白的Areg。因此,小胶质细胞分泌的Areg通过Egfr受体抑制星形胶质细胞的促炎反应。研究人员随后通过诱导EAE小胶质细胞中Areg的表达来研究中枢神经系统病理学。IL-33已被鉴定为EAE的抑制剂和Areg表达的诱导剂。IL-33也是组织损伤后细胞释放的一种危言耸听的物质。5为了确定IL-33是否调节Areg介导的小胶质细胞-星形胶质细胞相互作用,研究人员重新分析了之前的测序数据集。这表明星形胶质细胞触发的IL-33信号转导是Areg+小胶质细胞的上游调节因子。这些发现表明,星形胶质细胞产生的IL-33在小胶质细胞中诱导Areg表达,进而作用于星形胶质细胞以抑制疾病促进反应。阐明细胞相互作用背后的机制可能会发现中枢神经系统疾病的潜在治疗靶点。因此,上述平台具有许多潜在的应用。此外,它使研究人员能够研究中枢神经系统中任何两种类型的细胞(例如,神经元星形胶质细胞、神经元小胶质细胞、星形胶质细胞小胶质细胞等)之间的相互作用。 ),允许在细胞-细胞通信中对配体-受体对相互作用进行高通量和系统鉴定。以前,已经创建了许多方法,并在受体和配体的研究中广泛使用。然而,它们严重依赖已建立的数据库。此外,由于目前用于研究细胞连接的大多数方法都涉及基因分析,因此在蛋白质水平上对配体-受体结合复合物的理解仍然有限。未来,SPEAC序列可能与遗传操作或多组学相结合,如表观基因组、转录组、蛋白质组和/或代谢组分析,以确定可以改变细胞-细胞相互作用的治疗方法。或者,它可以与抗体或小分子条形码文库结合,以确定细胞-细胞通信的治疗调节因子。因此,SPEAC seq可能具有巨大的价值,并提供广泛的潜在应用。姚棠:写作——原稿。刘:《写作——评论》;编辑。作者声明没有利益冲突。
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