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频率依赖选择可以预测肺炎链球菌的进化。

Frequency-dependent selection can forecast evolution in Streptococcus pneumoniae.

机构信息

Burnett School of Biomedical Sciences, University of Central Florida, Orlando, Florida, United States of America.

Center for Communicable Disease Dynamics, Department of Epidemiology, T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts, United States of America.

出版信息

PLoS Biol. 2020 Oct 22;18(10):e3000878. doi: 10.1371/journal.pbio.3000878. eCollection 2020 Oct.

Abstract

Predicting how pathogen populations will change over time is challenging. Such has been the case with Streptococcus pneumoniae, an important human pathogen, and the pneumococcal conjugate vaccines (PCVs), which target only a fraction of the strains in the population. Here, we use the frequencies of accessory genes to predict changes in the pneumococcal population after vaccination, hypothesizing that these frequencies reflect negative frequency-dependent selection (NFDS) on the gene products. We find that the standardized predicted fitness of a strain, estimated by an NFDS-based model at the time the vaccine is introduced, enables us to predict whether the strain increases or decreases in prevalence following vaccination. Further, we are able to forecast the equilibrium post-vaccine population composition and assess the invasion capacity of emerging lineages. Overall, we provide a method for predicting the impact of an intervention on pneumococcal populations with potential application to other bacterial pathogens in which NFDS is a driving force.

摘要

预测病原体种群随时间的变化具有挑战性。这种情况在肺炎链球菌(一种重要的人类病原体)和肺炎球菌结合疫苗(PCV)中都存在,后者仅针对人群中一部分菌株。在这里,我们使用辅助基因的频率来预测接种疫苗后肺炎球菌种群的变化,假设这些频率反映了对基因产物的负频率依赖性选择(NFDS)。我们发现,在引入疫苗时,基于 NFDS 的模型估计的菌株标准化预测适应性可以帮助我们预测该菌株在接种疫苗后是否会增加或减少流行率。此外,我们能够预测疫苗接种后的平衡后种群组成,并评估新兴谱系的入侵能力。总的来说,我们提供了一种预测干预对肺炎球菌种群影响的方法,该方法可能适用于 NFDS 是驱动力的其他细菌性病原体。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a8b9/7580979/692cb0335b59/pbio.3000878.g001.jpg

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