1830. Single-cell Transcriptional Profiling Reveals an Immune Cell State Signature of Bacterial Sepsis

败血症 免疫系统 外周血单个核细胞 医学 CD14型 免疫学 流式细胞术 细胞 生物 计算生物学 生物信息学 遗传学 体外
作者
Miguel Reyes,Roby P. Bhattacharyya,Michael R. Filbin,Kianna Billman,Thomas Eisenhaure,Deborah T. Hung,Bruce D. Levy,Rebecca M. Baron,Paul C. Blainey,Marcia B. Goldberg,Nir Hacohen
出处
期刊:Open Forum Infectious Diseases [Oxford University Press]
卷期号:6 (Supplement_2): S42-S42 被引量:1
标识
DOI:10.1093/ofid/ofz359.092
摘要

Abstract Background Despite intense efforts to understand the immunopathology of sepsis, no clinically reliable diagnostic biomarkers exist. Multiple whole-blood gene expression studies have sought sepsis-associated molecular signatures, but these have not yet resolved immune phenomena at the cellular level. Using single-cell RNA sequencing (scRNA-Seq) to profile peripheral blood mononuclear cells (PBMCs), we identified a novel cellular state enriched in patients with sepsis. Methods We performed scRNA-Seq on PBMCs from 26 patients with sepsis and 47 controls at two hospitals (mean age 57.5 years, SD 16.6; 54% male; 82% white), analyzing >200,000 single cells in total on a 10× Genomics platform. We identified immune cell states by stepwise clustering, first to identify the major immune cell types, then clustering each cell type into substates. Substate abundances were compared between cases and controls using the Wilcoxon rank-sum test. Results We identified 18 immune cell substates (Figure 1a), including a novel CD14+ monocyte substate (MS1) that is enriched in patients with sepsis (Figure 1b). The fractional abundance of the MS1 substate alone (ROC AUC 0.88) outperformed published bulk transcriptional signatures in identifying sepsis (AUC 0.68–0.82) across our clinical cohorts. Deconvolution of publicly available bulk transcriptional data to infer the abundance of the MS1 substate externally validated its accuracy in predicting sepsis of various etiologies across diverse geographic locations (Figure 1c), matching the best previously identified bulk signatures. Flow cytometry using cell surface markers unique to MS1 confirmed its marked expansion in sepsis, facilitating quantitation and isolation of this substate for further study. Conclusion This study demonstrates the utility of scRNA-Seq in discovering disease-associated cytologic signatures in blood and identifies a cell state signature for sepsis in patients with bacterial infections. This novel monocyte substate matched the performance of the best bulk transcriptional signatures in classifying patients as septic, and pointed to a specific cell state for further molecular and functional characterization of sepsis immunopathogenesis. Disclosures All Authors: No reported Disclosures.

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