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深度测序揭示此前未检测到的超级传播。

Previously undetected super-spreading of revealed by deep sequencing.

机构信息

Epidemiology Division, Dalla Lana School of Public Health, University of Toronto, Toronto, Canada.

Center for Communicable Disease Dynamics, Harvard TH Chan School of Public Health, Boston, United States.

出版信息

Elife. 2020 Feb 4;9:e53245. doi: 10.7554/eLife.53245.

Abstract

Tuberculosis disproportionately affects the Canadian Inuit. To address this, it is imperative we understand transmission dynamics in this population. We investigate whether 'deep' sequencing can provide additional resolution compared to standard sequencing, using a well-characterized outbreak from the Arctic (2011-2012, 50 cases). Samples were sequenced to ~500-1000x and reads were aligned to a novel local reference genome generated with PacBio SMRT sequencing. Consensus and heterogeneous variants were identified and compared across genomes. In contrast with previous genomic analyses using ~50x depth, deep sequencing allowed us to identify a novel super-spreader who likely transmitted to up to 17 other cases during the outbreak (35% of the remaining cases that year). It is increasingly evident that within-host diversity should be incorporated into transmission analyses; deep sequencing may facilitate more accurate detection of super-spreaders and transmission clusters. This has implications not only for TB, but all genomic studies of transmission - regardless of pathogen.

摘要

结核病在加拿大因纽特人中的发病率不成比例。为了解决这个问题,我们必须了解这一人群中的传播动态。我们调查了“深度”测序是否能提供比标准测序更高的分辨率,使用的是北极地区一个特征明确的疫情(2011-2012 年,50 例)。对样本进行了500-1000 倍的测序,并将读数与使用 PacBio SMRT 测序生成的新型本地参考基因组进行比对。在整个基因组中识别并比较了一致和异质变体。与以前使用50x 深度的基因组分析相比,深度测序使我们能够识别出一个新的超级传播者,他可能在疫情期间将病毒传播给了多达 17 个其他病例(当年剩余病例的 35%)。越来越明显的是,应该将宿主内的多样性纳入传播分析中;深度测序可能更准确地检测到超级传播者和传播簇。这不仅对结核病,而且对所有病原体的基因组传播研究都有影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a793/7012596/da4c5c7483ec/elife-53245-fig1.jpg

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