Inferring bacterial transmission dynamics using deep sequencing genomic surveillance data.
Inferring bacterial transmission dynamics using deep sequencing genomic surveillance data.
复制标题
利用深度测序基因组监测数据推断细菌传播动力学。
DOI：
10.1038/s41467-023-42211-8
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发表时间：
2023-10-31
影响因子：
16.6
通讯作者：
Wiles S
中科院分区：
文献类型：
--
作者：
Senghore M;Read H;Oza P;Johnson S;Passarelli-Araujo H;Taylor BP;Ashley S;Grey A;Callendrello A;Lee R;Goddard MR;Lumley T;Hanage WP;Wiles S
查明和阻断传播链对于控制传染病十分重要。确定传播对（即两个宿主之间的感染传播）的一种方法是利用每个宿主内病原体的变异（宿主内变异）。然而，由于缺乏实验和临床数据集，捕获病原体的多样性，在捐助者和受体宿主，这种变化在传播中的作用是研究不足。在这项工作中，我们使用小鼠传播模型评估了深度测序基因组监测（其中基因组区域被测序数百到数千次）的实用性，该模型涉及致病性细菌Citrobacter rodentium从感染到幼稚雌性动物的受控传播。我们观察到宿主内单核苷酸变异（iSNVs）在多个传播步骤中保持不变，并提出了一个模型，用于推断给定的一对测序样本通过传播联系的可能性。在这项工作中，我们表明，除了宿主内变异的存在和不存在之外，iSNV（等位基因频率）相对丰度的差异可以更精确地推断传播对。我们的方法进一步强调了瓶颈在传输过程中保留宿主内多样性的关键作用。通过研究感染性细菌在实验室小鼠之间传播时出现的罕见遗传变化，作者表明，使用任何变化的相对丰度，而不仅仅是它们是否发生，可以更精确地识别谁可能感染了谁。
Identifying and interrupting transmission chains is important for controlling infectious diseases. One way to identify transmission pairs – two hosts in which infection was transmitted from one to the other – is using the variation of the pathogen within each single host (within-host variation). However, the role of such variation in transmission is understudied due to a lack of experimental and clinical datasets that capture pathogen diversity in both donor and recipient hosts. In this work, we assess the utility of deep-sequenced genomic surveillance (where genomic regions are sequenced hundreds to thousands of times) using a mouse transmission model involving controlled spread of the pathogenic bacterium Citrobacter rodentium from infected to naïve female animals. We observe that within-host single nucleotide variants (iSNVs) are maintained over multiple transmission steps and present a model for inferring the likelihood that a given pair of sequenced samples are linked by transmission. In this work we show that, beyond the presence and absence of within-host variants, differences arising in the relative abundance of iSNVs (allelic frequency) can infer transmission pairs more precisely. Our approach further highlights the critical role bottlenecks play in reserving the within-host diversity during transmission. Studying rare genetic changes that arose as an infectious bacterium spread between lab mice, here the authors show that using the relative abundance of any changes rather than just whether they occurred can more precisely identify who likely infected who.
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DOI：
10.1093/bioinformatics/btq033
发表时间：
2010-03-15
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Quinlan AR;Hall IM
通讯作者：
Hall IM
影响因子：
5.4
作者：
Leonard, Ashley Sobel;Weissman, Daniel B.;Koelle, Katia
通讯作者：
Koelle, Katia
影响因子：
7.7
作者：
Lee, Robyn S.;Proulx, Jean-Francois;Hanage, William P.
通讯作者：
Hanage, William P.
影响因子：
82.9
作者：
Ladner, Jason T.;Grubaugh, Nathan D.;Andersen, Kristian G.
通讯作者：
Andersen, Kristian G.
SARS-COV-2内部多样性和传播。
DOI：
10.1126/science.abg0821
发表时间：
2021-04-16
期刊：
Science (New York, N.Y.)
影响因子：
--
作者：
Lythgoe KA;Hall M;Ferretti L;de Cesare M;MacIntyre-Cockett G;Trebes A;Andersson M;Otecko N;Wise EL;Moore N;Lynch J;Kidd S;Cortes N;Mori M;Williams R;Vernet G;Justice A;Green A;Nicholls SM;Ansari MA;Abeler-Dörner L;Moore CE;Peto TEA;Eyre DW;Shaw R;Simmonds P;Buck D;Todd JA;Oxford Virus Sequencing Analysis Group (OVSG);Connor TR;Ashraf S;da Silva Filipe A;Shepherd J;Thomson EC;COVID-19 Genomics UK (COG-UK) Consortium;Bonsall D;Fraser C;Golubchik T
通讯作者：
Golubchik T