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碳青霉烯酶编码基因拷贝数估计器(CCNE):一种用于碳青霉烯酶基因拷贝数估计的工具。

Carbapenemase-Encoding Gene Copy Number Estimator (CCNE): a Tool for Carbapenemase Gene Copy Number Estimation.

机构信息

Institute of Antibiotics, Huashan Hospital, Fudan University, Shanghai, China.

Center for Discovery and Innovation, Hackensack Meridian Health, Nutley, New Jersey, USA.

出版信息

Microbiol Spectr. 2022 Aug 31;10(4):e0100022. doi: 10.1128/spectrum.01000-22. Epub 2022 Jul 5.

DOI:10.1128/spectrum.01000-22
PMID:35863018
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9431437/
Abstract

Carbapenemase production is one of the leading mechanisms of carbapenem resistance in Gram-negative bacteria. An increase in carbapenemase gene (Carb) copies is an important mechanism of carbapenem resistance. No currently available bioinformatics tools allow for reliable detection and reporting of carbapenemase gene copy numbers. Here, we describe the carbapenemase-encoding gene copy number estimator (CCNE), a ready-to-use bioinformatics tool that was developed to estimate Carb copy numbers from whole-genome sequencing data. Its performance on carbapenemase gene () copy number estimation was evaluated by simulation and quantitative PCR (qPCR), and the results were compared with available algorithms. CCNE has two components, CCNE-acc and CCNE-fast. CCNE-acc detects Carb copy number in a comprehensive and high-accuracy way, while CCNE-fast rapidly screens Carb copy numbers. CCNE-acc achieved the best accuracy (100%) and the lowest root mean squared error (RMSE; 0.07) in simulated noise data sets, compared to the assembly-based method (23.4% accuracy, 1.697 RMSE) and the OrthologsBased method (78.9% accuracy, 0.395 RMSE). In the qPCR validation, a high consistency was observed between the copy number determined by qPCR and that determined with CCNE. Reverse transcription-qPCR transcriptional analysis of 40 isolates showed that expression was positively correlated with the copy numbers detected by CCNE ( < 0.001). An association study of 357 KPC-producing K. pneumoniae isolates and their antimicrobial susceptibility identified a significant association between the estimated copy number and MICs of imipenem ( < 0.001) and ceftazidime-avibactam ( < 0.001). Overall, CCNE is a useful genomic tool for the analysis of antimicrobial resistance genes copy number; it is available at https://github.com/biojiang/ccne. Globally disseminated carbapenem-resistant is an urgent threat to public health. The most common carbapenem resistance mechanism is the production of carbapenemases. Carbapenemase-producing isolates often exhibit a wide range of carbapenem MICs. Higher carbapenem MICs have been associated with treatment failure. The increase of carbapenemase gene (Carb) copy numbers contributes to increased carbapenem MICs. However, Carb gene copy number detection is not routinely conducted during a genomic analysis, in part due to the lack of optimal bioinformatics tools. In this study, we describe a ready-to-use tool we developed and designated the carbapenemase-encoding gene copy number estimator (CCNE) that can be used to estimate the Carb copy number directly from whole-genome sequencing data, and we extended the data to support the analysis of all known Carb genes and some other antimicrobial resistance genes. Furthermore, CCNE can be used to interrogate the correlations between genotypes and susceptibility phenotypes and to improve our understanding of antimicrobial resistance mechanisms.

摘要

碳青霉烯酶的产生是革兰氏阴性菌产生碳青霉烯类耐药的主要机制之一。碳青霉烯酶基因(Carb)拷贝数的增加是碳青霉烯类耐药的重要机制。目前没有可用的生物信息学工具能够可靠地检测和报告碳青霉烯酶基因拷贝数。在这里,我们描述了碳青霉烯酶编码基因拷贝数估计器(CCNE),这是一个即用型生物信息学工具,用于从全基因组测序数据中估计 Carb 拷贝数。通过模拟和定量聚合酶链反应(qPCR)评估了其在碳青霉烯酶基因()拷贝数估计中的性能,并将结果与现有算法进行了比较。CCNE 有两个组件,CCNE-acc 和 CCNE-fast。CCNE-acc 以全面和高精度的方式检测 Carb 拷贝数,而 CCNE-fast 则快速筛选 Carb 拷贝数。CCNE-acc 在模拟噪声数据集方面实现了最佳的准确性(100%)和最低的均方根误差(RMSE;0.07),与基于组装的方法(23.4%的准确性,1.697 RMSE)和基于同源物的方法(78.9%的准确性,0.395 RMSE)相比。在 qPCR 验证中,qPCR 确定的 拷贝数与 CCNE 确定的拷贝数之间观察到高度一致性。对 40 株分离株的逆转录 qPCR 转录分析表明,表达与 CCNE 检测到的 拷贝数呈正相关(<0.001)。对 357 株产 KPC 肺炎克雷伯菌分离株及其抗菌药物敏感性的关联研究发现,估计的 拷贝数与亚胺培南(<0.001)和头孢他啶-阿维巴坦(<0.001)的 MIC 值之间存在显著关联。总体而言,CCNE 是一种用于分析抗菌药物耐药基因拷贝数的有用基因组工具;它可在 https://github.com/biojiang/ccne 上获得。 全球传播的碳青霉烯类耐药 是对公共健康的紧迫威胁。最常见的碳青霉烯类耐药机制是产生碳青霉烯酶。产碳青霉烯酶的分离株通常表现出广泛的碳青霉烯类 MIC 范围。更高的碳青霉烯类 MIC 与治疗失败有关。碳青霉烯酶基因(Carb)拷贝数的增加导致碳青霉烯类 MIC 增加。然而,在进行全基因组分析时,通常不会检测 Carb 基因拷贝数,部分原因是缺乏最佳的生物信息学工具。在这项研究中,我们描述了一个我们开发的即用型工具,我们将其命名为碳青霉烯酶编码基因拷贝数估计器(CCNE),它可用于直接从全基因组测序数据中估计 Carb 拷贝数,并扩展了数据以支持所有已知 Carb 基因和其他一些抗菌药物耐药基因的分析。此外,CCNE 可用于探究基因型和药敏表型之间的相关性,并有助于我们更好地理解抗菌药物耐药机制。

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