Virus-inclusive single cell RNA sequencing reveals molecular signature predictive of progression to severe dengue infection
题目：通过包含病毒的单细胞测序揭露重症登革热发展过程的分子信号
作者及单位：
Fabio Zanini, Makeda Robinson, Derek Croote, Malaya Kumar Sahoo, Ana Maria Sanz, Eliana Ortiz-Lasso, Ludwig Luis Albornoz, Fernando Rosso Suarez, Jose G Montoya, Benjamin A Pinsky, Stephen Quake, Shirit Einav
Stephen Quake、Shirit Einav
Stanford University;
发表期刊及时间：
PNAS December 26, 2018 115 (52) E12363-E12369; published ahead of print December 7, 2018
摘要：
Dengue virus (DENV) infection can result in severe complications. However, the understanding of the molecular correlates of severity is limited, partly due to difficulties in defining the peripheral blood mononuclear cells (PBMCs) that contain DENV RNA in vivo. Accordingly, there are currently no biomarkers predictive of progression to severe dengue (SD). Bulk transcriptomics data are difficult to interpret because blood consists of multiple cell types that may react differently to infection. Here, we applied virus-inclusive single-cell RNA-seq approach (viscRNA-Seq) to profile ==transcriptomes of thousands of single PBMCs==（注意此处是数千个单核细胞，而不是数千个转录组） derived early in the course of disease from six dengue patients and four healthy controls and to characterize distinct leukocyte subtypes that harbor viral RNA (vRNA). Multiple IFN response genes, particularly MX2 in naive B cells and CD163 in CD14+ CD16+ monocytes, were up-regulated in a cell-specific manner before progression to SD. The majority of vRNA-containing cells in the blood of two patients who progressed to SD were naive IgM B cells expressing the CD69 and CXCR4 receptors and various antiviral genes, followed by monocytes. Bystander, non-vRNA–containing B cells also demonstrated immune activation, and IgG1 plasmablasts from two patients exhibited clonal expansions. Lastly, assembly of the DENV genome sequence revealed diversity at unexpected sites. This study presents a multifaceted molecular elucidation of natural dengue infection in humans with implications for any tissue and viral infection and proposes candidate biomarkers for prediction of SD.
登革热病毒(DENV)感染可导致严重并发症。 然而，对严重程度的分子相关性的认识是有 限的，部分原因是难以定义体内含有 DENV RNA 的外周血单核细胞(PBMCs)。 因此，目前没 有可预测进展为严重登革热(SD)生物标志物。 因为血液由多种细胞类型组成，它们对感染的 反应可能不同，所以大量转录组数据很难解释。在本研究中，我们采用病毒包容性单细胞 RNA-seq 方法(viscRNA-Seq)，对 6 名登革热患者和 4 名健康对照患者在疾病早期获得的数 千个单个 PBMCs 转录组进行了分析，并对携带病毒 RNA (vRNA)的白细胞亚型进行了表征。 多种 IFN 应答基因，尤其是原 B 细胞中的 MX2 和 CD14+ CD16+单核细胞中的 CD163，在 进展为 SD 前均以细胞特异性方式上调。 在两位进展到 SD 的病人的血液中含 vRNA 的细胞 的主体是未分化的 IgM B 细胞，表达了 CD69 和 CXCR4 受 体和多样的抗病毒基因，单核细 胞也是这样。 同时，不含 vRNA 的 B 细胞也表现出免疫激活，两例患者 IgG1 质粒表现出克隆 扩增。 最后， DENV 基因组序列的组装在意想不到的位点显示出多样性。 本研究提出了一个 多层面的人类自然登革热感染的分子阐明，对任何组织和病毒感染都有意义，并提出了预测 SD 的候选生物标志物。
图表选析：
Fig. 1. FACS-assisted viscRNA-Seq workflow on PBMCs from DENV-infected and healthy control human subjects.
图1. 对感染登革热的病人和健康的对照个体取外周血单核细胞后， 进 行荧光激活细胞分选术的含病毒单细胞 RNA-seq 的工作流程
(Aand B) Blood samples were collected from human subjects enrolled in the Colombia cohort (healthy, dengue, and SD).
(A and B)从哥伦比亚群体中收集的血液样本（包含正常个体， 登革热感染体和恶化的登革热感染个体）
(C) PBMCs were isolated via Ficoll centrifugation and stained with three antibody panels to distinguish various cell types: T, B, NK, DC, and monocytes.
（C） 通过聚蔗糖离心分离外周血单核细胞， 并用三个抗体板染色 以区分各种细胞类型： T 细胞、 B 细胞、 自杀型细胞、 树状细胞和单 核细胞
(D) Single cells from each ==aliquot== were sorted and processed by viscRNA-Seq to simultaneously quantify single-cell virus abundance and host transcriptome changes.
(D)对来自每个等分的单个细胞进行分类并用含病毒单细胞 seq 处理， 以同时定量单细胞病毒丰度和宿主转录组变化。
(E) The information provided for each single cell includes: cell type, immune activation, infection state, and virus population genomics. N.A., nonapplicable.
(E)为每个单细胞提供的信息包括： 细胞类型、 免疫激活、 感染状 态和病毒群体基因组。 N.A 代表不适用。
==aliquot==：等分的，指的是每个病人的起始细胞上样量一致
Fig. 2. Overview of the types of PBMCs surveyed. (A) Two-dimensional representation of the cells color coded by the expression level of cell type-specific marker genes or the abundance of virus reads within the cell (>30 virus reads per million reads in samples from two SD patients, p1-026-1 and p1-036-1). (B) Number of cells analyzed for each cell type from each subject, see also SI Appendix, Table S6. (C) tSNE visualizations within T, NK, B cells, and monocytes, highlighting some broad cell subpopulations. The colored lines were drawn manually following inspection of the marker genes for visualization only.
图 2：调查的PBMC类型概述。（A） 按照细胞特异标志基因或细胞中病毒 reads丰度（两 个重症登革热患者样本中每百万 reads出现超过 30 个病毒reads） 给细胞上色， 并且用二维 图的形式展示出来。（B） 每个实验者每种类型细胞的数量。（C） 对 T 细胞， NK 细胞， B 细 胞和单核细胞进行 t-SNE可视化分析， 高亮出一些边缘细胞亚种群。 为了可视化， 这些上色 的线是依照标志基因的检查结果手工绘制的
Fig. 3. Differential expression across disease severity and cell types shows hallmarks of progression to SD. (A) Genes that are overexpressed in subjects before progressing to SD versus all other subjects across cell types and subtypes. Color (white to red) indicates the average log-fold change; size of the dot indicates lower Pvalue in a distribution statistical comparison (two sample Kolmogorov–Smirnov). (B) Many inflammatory genes such as IFITM1 are expressed ubiquitously during both mild and SD infection. (C) Other genes such as IFIT3 are specifically expressed before the development of SD in various types of lymphocytes. (D) A number of genes show double specificity for both SD and a single cell type, for instance CD163 in monocytes. (E) Averaging across cells within specific cell types and subtypes indicates promising candidate predictors of SD as assessed by ROC curves at increasing discriminatory thresholds for gene expression versus disease severity. The numbers after the gene name indicate log-twofold changes of average expression in patients progressing to SD versus other dengue patients, indicating an overexpression of these genes by a 100-fold or more in our cohort. D, dengue; H, healthy subject.
图 3 所示。不同疾病严重程度和细胞类型的差异表达表现出 SD 进展的特征。 (A) 与细胞类 型和亚型的所有其他研究对象相比，在发展为 SD 之前在研究对象中过度表达的基因。 颜色 (从白色到红色)表示对数的平均变化;点的大小表明分布统计比较中 P 值较低(两个样本 Kolmogorov-Smirnov)。 (B)许多炎症基因，如 IFTMI，在轻度感染和 SD 感染过程中均普遍表 达， (C)其他基因，如 IFT3，在 sD 发生前在各种类型的淋巴细胞中均有特异性表达。 (D)许多 基因对 SD 和单细胞类型都具有双重特异性，例如单核细胞中的 CD163。 (E) 在特定细胞类 型和亚型内的细胞间取平均值表明，通过 ROC 曲线评估，在提高基因表达与疾病严重程度 的区别阈值方面，有希望成为 SD 的候选预测因子。 该基因名称后面的数字表明，与其他登 革热患者相比，进展为 SD 的患者平均表达量发生了对数倍的变化，表明这些基因在我们这一组中过表达了 100 倍或更多。 D,登革热组;H,健康组。
讨论：
We recently developed viscRNA-Seq, a scalable approach to quantify host and nonpolyadenylated vRNAs from the same cell (21). In the current study, we apply viscRNA-Seq to in vivo samples and show that it can be used to effectively profile the landscape of host transcripts and vRNA in thousands of single immune cells during natural dengue infection of human subjects. The human samples studied here posed additional challenges, beyond those presented in cultured cells. First, the exact sequence of the viral strain infecting the patients was unknown. We therefore designed an oligonucleotide for virus capture in a conserved region of the viral genome (21). Second, the target cell types of DENV in vivo are incompletely characterized, mandating assembly of antibody panels for FACS that maximize the probability of capturing the vRNA-containing cell population(s) (Fig. 1C). Third, cell viability and integrity of the RNA after freezing, shipping, and thawing the PBMC samples was much lower than in cultured cells, especially for certain cell types. Although we could not recover all types of blood cells (e.g., granulocytes, see SI Appendix, Fig. S3) we increased the throughput and PCR preamplification to ensure a sufficient number of high-quality cells from many cell types. These modifications have successfully addressed the above challenges, as indicated by our findings. Because the viscRNA-seq approach can be extended to any virus of interest and is compatible with surface markers for FACS, we expect it to be readily extensible to dissociated solid tissues, for instance to characterize viral reservoirs of various viral infections. A similar approach was recently applied to influenza infection in mouse lungs (37) and to in vitro Zika virus infection of neuronal stem cells (22).
我们最近开发了Viscrna-seq，一种从同一细胞(21)中量化宿主和非多聚腺苷化vrnas的可伸缩方法。在 目前的研究中，我们将viscrna-seq应用于体内样品，并表明它可以有效地描述人体自然感染过程中数千 个单个免疫细胞中宿主转录本和vrna的情况。这里研究的人体样本除了培养的细胞外，还带来了额外的 挑战。 首先，感染患者的病毒株的确切序列尚不清楚。因此，我们设计了一种在病毒基因组(21) 保守区域捕获病毒的寡核苷酸。 第二， DENV在体内的目标细胞类型不完全地被描述，要求为 FACS组装抗体面板，以最大化捕获含有vrna的细胞群的概率(图)。 1C)。第三， rna在冷冻、运 输和解冻后的细胞活力和完整性明显低于培养的细胞，特别是某些细胞类型。虽然我们不能恢复 所有类型的血细胞(如粒细胞，见SI附录，图)。 S3)我们增加了吞吐量和PCR预扩增，以确保足够 数量的高质量细胞从许多细胞类型。如我们的调查结果所示，这些修改成功地解决了上述挑战。因为 Viscrna-seq方法可以扩展到任何感兴趣的病毒，并且可以与FACS的表面标记物兼容，我们期望它可以 很容易地扩展到分离的固体组织，例如描述各种病毒感染的病毒库。最近，一种类似的方法被应用于小 鼠肺部的流感感染(37)和神经干细胞的体外Zika病毒感染(22)
翻译小组：
陈凯星、王俊豪、邓峻玮、倪豪辰、陈志荣、郑凌伶
