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利用全基因组测序的单核苷酸多态性距离进行系统动力学评估以确定结核分枝杆菌传播情况。

Phylodynamic assessment of SNP distances from whole genome sequencing for determining Mycobacterium tuberculosis transmission.

作者信息

Van der Roest Bastiaan R, Bootsma Martin C J, Fischer Egil A J, Gröschel Matthias I, Anthony Richard M, de Zwaan Rina, Kretzschmar Mirjam E E, Klinkenberg Don

机构信息

Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, P.O.Box 85500, Utrecht, The Netherlands.

Department of Mathematics, Faculty of Science, University Utrecht, Utrecht, The Netherlands.

出版信息

Sci Rep. 2025 Mar 28;15(1):10694. doi: 10.1038/s41598-025-94646-2.

Abstract

The global tuberculosis (TB) epidemic is driven by primary transmission. Pathogen genome sequencing is increasingly used in molecular epidemiology and outbreak investigations. Based on contact tracing and epidemiological links, Single Nucleotide Polymorphism (SNP) cut-offs, ranging from 3 to 12 SNPs, identify probable transmission clusters or exclude direct transmission. However, contact tracing can be limited by recall bias and inconsistent methodologies across TB settings. We propose phylodynamic models, i.e. methods to infer transmission processes from pathogen genomes and associated epidemiological data, as an alternative reference to infer transmission events. We analyzed 2,008 whole-genome sequences from Dutch TB patients collected from 2015 to 2019. Genetic clusters were defined within a 20-SNP range, and the phylodynamic model phybreak was employed to infer transmission. Probable transmission SNP cut-offs were assessed by the proportion of inferred transmission events with a SNP distance below these cut-offs. A total of 79 clusters were identified, with a median size of 4 isolates (IQR = 3-8). A SNP cut-off of 4 captured 98% of inferred transmission events while reducing pairs without transmission links. A cut-off beyond 12 SNPs effectively excluded transmission. Phylodynamic approaches provide a valuable alternative to contact tracing for defining SNP cut-offs, allowing for a more precise assessment of transmission events.

摘要

全球结核病流行是由原发性传播驱动的。病原体基因组测序越来越多地应用于分子流行病学和疫情调查。基于接触者追踪和流行病学联系,单核苷酸多态性(SNP)阈值范围为3至12个SNP,用于识别可能的传播集群或排除直接传播。然而,接触者追踪可能受到回忆偏倚和不同结核病环境中方法不一致的限制。我们提出系统动力学模型,即从病原体基因组和相关流行病学数据推断传播过程的方法,作为推断传播事件的替代参考。我们分析了2015年至2019年收集的2008例荷兰结核病患者的全基因组序列。在20个SNP范围内定义遗传集群,并采用系统动力学模型phybreak推断传播情况。通过SNP距离低于这些阈值的推断传播事件比例来评估可能的传播SNP阈值。共识别出79个集群,中位数大小为4个分离株(IQR = 3 - 8)。4个SNP的阈值捕获了98%的推断传播事件,同时减少了无传播联系的配对。超过12个SNP的阈值有效排除了传播。系统动力学方法为定义SNP阈值提供了一种有价值的替代接触者追踪的方法,能够更精确地评估传播事件。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e871/11953417/3ea0dff62a5e/41598_2025_94646_Fig1_HTML.jpg

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