预测抗生素耐药基因在细菌基因组中的传播。

Forecasting the dissemination of antibiotic resistance genes across bacterial genomes.

机构信息

The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Lyngby, Denmark.

出版信息

Nat Commun. 2021 Apr 23;12(1):2435. doi: 10.1038/s41467-021-22757-1.

Abstract

Antibiotic resistance spreads among bacteria through horizontal transfer of antibiotic resistance genes (ARGs). Here, we set out to determine predictive features of ARG transfer among bacterial clades. We use a statistical framework to identify putative horizontally transferred ARGs and the groups of bacteria that disseminate them. We identify 152 gene exchange networks containing 22,963 bacterial genomes. Analysis of ARG-surrounding sequences identify genes encoding putative mobilisation elements such as transposases and integrases that may be involved in gene transfer between genomes. Certain ARGs appear to be frequently mobilised by different mobile genetic elements. We characterise the phylogenetic reach of these mobilisation elements to predict the potential future dissemination of known ARGs. Using a separate database with 472,798 genomes from Streptococcaceae, Staphylococcaceae and Enterobacteriaceae, we confirm 34 of 94 predicted mobilisations. We explore transfer barriers beyond mobilisation and show experimentally that physiological constraints of the host can explain why specific genes are largely confined to Gram-negative bacteria although their mobile elements support dissemination to Gram-positive bacteria. Our approach may potentially enable better risk assessment of future resistance gene dissemination.

摘要

抗生素耐药性通过抗生素耐药基因(ARGs)的水平转移在细菌中传播。在这里,我们着手确定细菌进化枝之间 ARG 转移的预测特征。我们使用统计框架来识别可能发生水平转移的 ARG 以及传播它们的细菌群。我们确定了包含 22963 个细菌基因组的 152 个基因交换网络。对 ARG 周围序列的分析确定了编码转座酶和整合酶等假定移动元件的基因,这些基因可能参与了基因组之间的基因转移。某些 ARG 似乎经常被不同的移动遗传元件转移。我们描述了这些移动元件的系统发育范围,以预测已知 ARG 的潜在未来传播。使用来自链球菌科、葡萄球菌科和肠杆菌科的 472798 个基因组的单独数据库,我们证实了 94 次预测转移中的 34 次。我们探讨了移动性之外的转移障碍,并通过实验表明,宿主的生理限制可以解释为什么尽管它们的移动元件支持向革兰氏阳性菌传播,但特定基因在很大程度上局限于革兰氏阴性菌。我们的方法可能有潜力实现对未来耐药基因传播风险的更好评估。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a42/8065159/ecbd4db3ef15/41467_2021_22757_Fig1_HTML.jpg

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