Next-generation sequencing diagnostics of bacteremia in septic patients.
Next-generation sequencing diagnostics of bacteremia in septic patients.
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DOI：
10.1186/s13073-016-0326-8
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发表时间：
2016-07-01
期刊：
影响因子：
12.3
通讯作者：
Sohn K
中科院分区：
文献类型：
--
作者：
Grumaz S;Stevens P;Grumaz C;Decker SO;Weigand MA;Hofer S;Brenner T;von Haeseler A;Sohn K
血流感染仍然是重症监护病房的主要挑战之一，在许多情况下导致败血症甚至败血性休克。由于缺乏足够灵敏度的及时诊断方法，脓毒症的死亡率仍然高得不可接受。然而，病原微生物的迅速诊断对于显着改善血流感染的结果至关重要。虽然有各种针对血液样本的分子检测，但耗时的基于血液培养的方法仍然代表了细菌鉴定的护理标准。在这里，我们描述了一个完整的诊断工作流程的建立，从七个脓毒症患者的基础上无偏的序列分析从血浆中游离循环DNA的下一代测序鉴定感染性微生物。我们在脓毒症患者的样本中发现了大量来自病原菌的DNA片段。标准化读数计数的定量评价和脓毒症指示量化因子（SIQ）评分的引入允许明确鉴定与来自相应患者样品的血培养物完全匹配的革兰氏阳性以及革兰氏阴性细菌。此外，我们还从血培养阴性的样本中鉴定了种属。非人类来源的读数还包括来自抗菌素耐药基因的片段，表明原则上可以预测特定类型的耐药性。从样品制备到物种鉴定报告的完整工作流程可以在大约30小时内完成，从而使该方法成为患有血流感染的危重患者的有前途的诊断平台。本文的在线版本（doi：10.1186/s13073-016-0326-8）包含补充材料，可供授权用户使用。
Bloodstream infections remain one of the major challenges in intensive care units, leading to sepsis or even septic shock in many cases. Due to the lack of timely diagnostic approaches with sufficient sensitivity, mortality rates of sepsis are still unacceptably high. However a prompt diagnosis of the causative microorganism is critical to significantly improve outcome of bloodstream infections. Although various targeted molecular tests for blood samples are available, time-consuming blood culture-based approaches still represent the standard of care for the identification of bacteria. Here we describe the establishment of a complete diagnostic workflow for the identification of infectious microorganisms from seven septic patients based on unbiased sequence analyses of free circulating DNA from plasma by next-generation sequencing. We found significant levels of DNA fragments derived from pathogenic bacteria in samples from septic patients. Quantitative evaluation of normalized read counts and introduction of a sepsis indicating quantifier (SIQ) score allowed for an unambiguous identification of Gram-positive as well as Gram-negative bacteria that exactly matched with blood cultures from corresponding patient samples. In addition, we also identified species from samples where blood cultures were negative. Reads of non-human origin also comprised fragments derived from antimicrobial resistance genes, showing that, in principle, prediction of specific types of resistance might be possible. The complete workflow from sample preparation to species identification report could be accomplished in roughly 30 h, thus making this approach a promising diagnostic platform for critically ill patients suffering from bloodstream infections. The online version of this article (doi:10.1186/s13073-016-0326-8) contains supplementary material, which is available to authorized users.