《CELL,6月1日,Ultra-high-throughput clinical proteomics reveals classifiers of COVID-19 infection》

  • 来源专题:COVID-19科研动态监测
  • 编译者: xuwenwhlib
  • 发布时间:2020-06-02
  • Ultra-high-throughput clinical proteomics reveals classifiers of COVID-19 infection
    Christoph B. Messner #Vadim Demichev #Daniel WendischFlorian Kurth,Leif Erik Sander
    Markus Ralser 15

    Open AccessPublished:June 01, 2020DOI:https://doi.org/10.1016/j.cels.2020.05.012

    Summary
    The COVID-19 pandemic is an unprecedented global challenge and point-of-care diagnostic classifiers are urgently required. Here, we present a platform for ultra-high throughput serum and plasma proteomics that builds on ISO13485 standardisation and high-flow liquid chromatography to facilitate implementation in clinical laboratories. Our low-cost workflow quantifies 180 proteomes per day per mass spectrometer, enables high precision quantification, and reduces batch effects for large-scale and longitudinal studies. We use our platform on samples collected from a cohort of early hospitalized cases of the SARS-CoV-2 pandemic and identify 27 potential biomarkers that are differentially expressed depending on the WHO severity grade of COVID-19. They include complement factors, the coagulation system, inflammation modulators, and pro-inflammatory upstream and downstream of interleukin 6. All protocols and software for implementing our approach are freely available. In total, our platform supports the development of routine proteomic assays to aid clinical decision making and generate hypotheses about potential COVID-19 therapeutic targets.

  • 原文来源:https://www.cell.com/cell-systems/fulltext/S2405-4712(20)30197-6
相关报告
  • 《MedRxiv,5月3日,Clinical classifiers of COVID-19 infection from novel ultra-high-throughput proteomics》

    • 来源专题:COVID-19科研动态监测
    • 编译者:xuwenwhlib
    • 发布时间:2020-05-04
    • Clinical classifiers of COVID-19 infection from novel ultra-high-throughput proteomics Christoph B. Messner, Vadim Demichev, Daniel Wendisch, Laura Michalick, Matthew White, Anja Freiwald, Kathrin Textoris-Taube, Spyros I. Vernardis, Anna-Sophia Egger, Marco Kreidl, Daniela Ludwig, Christiane Kilian, Federica Agostini, Aleksej Zelezniak, Charlotte Thibeault, Moritz Pfeiffer, Stefan Hippenstiel, Andreas Hocke, Christof von Kalle, Archie Campbell, Caroline Hayward, David J. Porteous, Riccardo E. Marioni, Claudia Langenberg, Kathryn S. Lilley, Wolfgang M. Kuebler, Michael Muelleder, Christian Drosten, Martin Witzenrath, Florian Kurth, Leif Erik Sander, View ORCID ProfileMarkus Ralser doi: https://doi.org/10.1101/2020.04.27.20081810 Abstract The COVID-19 pandemic is an unprecedented global challenge. Highly variable in its presentation, spread and clinical outcome, novel point-of-care diagnostic classifiers are urgently required. Here, we describe a set of COVID-19 clinical classifiers discovered using a newly designed low-cost high-throughput mass spectrometry-based platform. Introducing a new sample preparation pipeline coupled with short-gradient high-flow liquid chromatography and mass spectrometry, our methodology facilitates clinical implementation and increases sample throughput and quantification precision. Providing a rapid assessment of serum or plasma samples at scale, we report 27 biomarkers that distinguish mild and severe forms of COVID-19, of which some may have potential as therapeutic targets. These proteins highlight the role of complement factors, the coagulation system, inflammation modulators as well as pro-inflammatory signalling upstream and downstream of Interleukin 6. Application of novel methodologies hence transforms proteomics from a research tool into a rapid-response, clinically actionable technology adaptable to infectious outbreaks.
  • 《6月1日_弗朗西斯·克里克研究所等利用超高通量临床蛋白质组学揭示了COVID-19感染的分类器》

    • 来源专题:COVID-19科研动态监测
    • 编译者:zhangmin
    • 发布时间:2020-06-03
    • 1.时间:2020年6月1日 2.机构或团队:英国弗朗西斯·克里克研究所、剑桥大学、瑞典查尔姆斯理工大学、德国夏里特医学院、柏林卫生研究所、爱丁堡大学、德国Bernhard Nocht热带医学研究所 3.事件概要: 英国弗朗西斯·克里克研究所和剑桥大学等机构的科研人员在Cell Systems期刊在线发表题为“Ultra-high-throughput clinical proteomics reveals classifiers of COVID-19 infection”的文章。 文章指出,COVID-19大流行是前所未有的全球挑战,急需现场护理诊断分类器。研究人员提出了一个基于ISO13485标准化和高流量液相色谱的超高通量血清与血浆蛋白质组学平台,以促进在临床实验室中的实施。低成本工作流程可以让每个质谱仪每天定量180个蛋白质组,实现高精度定量,并减少了大规模和纵向研究的批次效应。研究人员将平台用于从一组SARS-CoV-2大流行早期住院病例中收集的样本,并根据世卫组织的COVID-19严重等级并识别了27种潜在差异表达的生物标志物,包括补体因子、凝血系统、炎症调节剂以及白介素6上游和下游的促炎因子。文章表示,总体而言,该平台支持常规蛋白质组学测定方法的开发,以帮助临床决策并产生有关COVID-19潜在治疗靶标的假设。 4.附件: 原文链接:https://www.cell.com/cell-systems/fulltext/S2405-4712(20)30197-6