Single-cell genomic profiling to identify immune signatures of bacterial sepsis in humans

脓毒症是一种由于宿主对感染的反应失调而导致的危及生命的器官功能障碍，是一种常见的 杀伤力极强。早期发现是一项重大挑战，很大程度上是因为，正如我们和其他人所表明的那样，败血症是一种 异质综合征，许多患者表现出模糊的症状和体征；改善的生物标志物 将使早期诊断成为可能，尤其是对这些患者。第二个主要挑战是缺乏 治疗，由于脓毒症的免疫功能障碍和血管渗漏的机制尚不清楚， 限制治疗发展。我们假设无偏向单细胞转录图谱(scrna-seq) 循环免疫细胞的研究将确定应对这两个挑战的转录特征。在我们的证据中- 原理研究(Reyes等人NAT Med 2020)中，我们发现了一种独特的单核细胞状态(MS1)，该状态被扩展 在尿毒症患者中没有，在轻度尿路感染患者或健康对照组中没有。MS1 在第二个队列中，在公共转录数据中区分脓毒症患者和其他疾病患者 细菌性败血症，以及我们来自任何身体部位的败血症患者新队列的初步数据。我们的 这项提案的目标是检验这一假设，即当扩展到全身所有部位的脓毒症患者时， 无偏见的单细胞方法将产生区分脓毒症和非感染性的免疫信号 器官功能障碍，定义新的临床相关脓毒症内型，识别加强脓毒症的标志物 诊断和分型，并揭示免疫功能障碍和 脓毒症中存在血管泄漏，从而促进了内型特异性治疗的未来发展。在这 提案中，我们将检验我们的假设，即在向急诊室提出急性器官功能障碍的患者中， 可以识别转录信号来区分脓毒症患者和非感染性患者 病因学。我们建议：(1)发现血液中的单细胞转录信号可以区分败血症和败血症。 非感染性器官功能障碍，确定无偏见的分子内型，并与临床结果相关 (目标1)；(2)确定与scRNA序列定义的细胞状态相关的细胞表面标记，包括MS1，这些标记是 脓毒症显著扩大(目标2)；(3)确定患者和小鼠细胞功能的变化 脓毒症和对败血症诱导的MS1细胞的反应(目标3)。拟议的研究极有可能导致 大大改进了脓毒症的细胞和分子特征，可转化为临床使用 对败血症免疫失调的本质有了新的见解。对基因和基因功能的研究 我们研究中确定的通路将影响对脓毒症的机制理解，并可能导致新的 治疗概念，特别是针对基于单细胞衍生分子分层的脓毒症患者亚群 内型。尽管脓毒症仍然是人类健康中最具挑战性的问题之一，但我们对 解决异质性和机制的主要问题的高分辨率、不偏不倚的方法将 为该领域提供高度有用的数据集，并促进新的靶向疗法的发展。

Sepsis, life-threatening organ dysfunction due to a dysregulated host response to infection, is prevalent and highly lethal. Early detection is a major challenge, largely because, as we and others showed, sepsis is a heterogeneous syndrome, with many patients presenting with vague symptoms and signs; improved biomarkers would enable earlier diagnosis, especially of these patients. A second major challenge is the shortage of treatments, as mechanisms of immune dysfunction and vascular leakage in sepsis are poorly understood, limiting therapeutic development. We hypothesize that unbiased single-cell transcriptional profiling (scRNA-seq) of circulating immune cells will identify transcriptional signatures that address both challenges. In our proof-of- principle study (Reyes et al. Nat Med 2020), we discovered a unique monocyte cell state (MS1) that is expanded in patients with urosepsis and absent in patients with milder urinary tract infection or healthy controls. MS1 discriminates septic patients from patients with other diseases in public transcriptomic data, in a second cohort of bacterial sepsis, and in preliminary data from our new cohort of patients with sepsis from any body site. Our goals in this proposal are to test the hypothesis that when extended to patients with sepsis from all body sites, unbiased single-cell approaches will generate immune signatures that distinguish sepsis from non-infectious organ dysfunction, define new clinically-relevant sepsis endotypes, identify markers that enhance sepsis diagnostics and subtyping, and reveal critical mechanistic biology underlying the immune dysfunction and vascular leak present in sepsis, thus facilitating future development of endotype-specific therapeutics. In this proposal, we will test our hypothesis that among patients presenting to the ED with acute organ dysfunction, transcriptional signatures can be identified that distinguish those with sepsis from those with non-infectious etiologies. We propose to: (1) discover blood single-cell transcriptional signatures that discriminate sepsis from non-infectious organ dysfunction, define unbiased molecular endotypes, and associate with clinical outcomes (Aim 1); (2) identify cell surface markers associated with scRNA-seq-defined cell states, including MS1, that are significantly expanded in sepsis (Aim 2); (3) define alterations in cellular functions in patients and mice with sepsis and in response to sepsis-induced MS1 cells (Aim 3). The proposed studies are highly likely to lead to substantially improved cellular and molecular signatures for sepsis that could be translated into clinical use and to new insights into the nature of immune dysregulation in sepsis. Investigations into the function of genes and pathways identified in our studies will impact mechanistic understanding of sepsis and may lead to new therapeutic concepts, especially for subsets of sepsis patients stratified based on single cell-derived molecular endotypes. Whereas sepsis remains among of the most challenging problems in human health, our use of a high-resolution unbiased approaches to address the major questions of heterogeneity and mechanism will provide highly useful datasets for the field and promote the development of new targeted therapeutics.