Species Identification and Antibiotic Resistance Prediction by Analysis of Whole-Genome Sequence Data by Use of ARESdb: an Analysis of Isolates from the Unyvero Lower Respiratory Tract Infection Trial
Species Identification and Antibiotic Resistance Prediction by Analysis of Whole-Genome Sequence Data by Use of ARESdb: an Analysis of Isolates from the Unyvero Lower Respiratory Tract Infection Trial
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DOI：
10.1128/jcm.00273-20
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发表时间：
2020-07-01
影响因子：
9.4
通讯作者：
Posch, Andreas E.
中科院分区：
文献类型：
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作者：
Ferreira, Ines;Beisken, Stephan;Posch, Andreas E.
全基因组测序（WGS）现在是临床微生物实验室评估分离亲缘关系的常规方法。通过适当开发的分析，相同的数据可以用于预测抗菌素敏感性。我们对WGS数据进行评估，使用开源工具进行鉴定，并使用ARESdb进行抗生素药敏试验（AST）预测，与基质辅助激光解吸电离飞行时间质谱（MALDI-TOF MS）鉴定和对来自fda批准的Unyvero下呼吸道感染（LRTI）应用（curretis）的多中心临床试验的临床分离株进行微稀释表型敏感性试验进行比较。在这项试验中，从9家医院的重症监护病房收集了2000多名患者样本，并对LRTI进行了检测。本研究中使用的分离物亚群包括来自455例LRTI培养阳性患者样本的620株临床分离物。使用Illumina Nextera XT协议和FASTQ文件对分离物进行测序，并将原始读数上传到ARESdb云平台（ares-genetics.cloud；于2020年发布用于研究用途）。该平台将Ares Genetics的专有数据库ARESdb与最先进的生物信息学工具和精心策划的公共数据相结合。在属和种水平上，WGS与MALDI-TOF MS的一致性分别为99%和93%。在129对分析的种-化合物对中，wgs预测的敏感性与表型敏感性的分类一致性为89%，其中78对的分类一致性超过90%，32对达到100%。本研究的结果增加了越来越多的文献表明，随着分析的改进，WGS数据可用于预测抗菌药物敏感性。
Whole-genome sequencing (WGS) is now routinely performed in clinical microbiology laboratories to assess isolate relatedness. With appropriately developed analytics, the same data can be used for prediction of antimicrobial susceptibility. We assessed WGS data for identification using open-source tools and antibiotic susceptibility testing (AST) prediction using ARESdb compared to matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) identification and broth microdilution phenotypic susceptibility testing on clinical isolates from a multicenter clinical trial of the FDA-cleared Unyvero lower respiratory tract infection (LRTI) application (Curetis). For the trial, more than 2,000 patient samples were collected from intensive care units across nine hospitals and tested for LRTI. The isolate subset used in this study included 620 clinical isolates originating from 455 LRTI culture-positive patient samples. Isolates were sequenced using the Illumina Nextera XT protocol and FASTQ files with raw reads uploaded to the ARESdb cloud platform (ares-genetics.cloud; released for research use in 2020). The platform combines Ares Genetics' proprietary database ARESdb with state-of-the-art bioinformatics tools and curated public data. For identification, WGS showed 99 and 93% concordance with MALDI-TOF MS at the genus and species levels, respectively. WGS-predicted susceptibility showed 89% categorical agreement with phenotypic susceptibility across a total of 129 species-compound pairs analyzed, with categorical agreement exceeding 90% in 78 species-compound pairs and reaching 100% in 32. Results of this study add to the growing body of literature showing that, with improvement of analytics, WGS data could be used to predict antimicrobial susceptibility.