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从流感血凝素和神经氨酸酶共发生突变的关联规则挖掘中获得的进化见解。

Evolutionary Insights from Association Rule Mining of Co-Occurring Mutations in Influenza Hemagglutinin and Neuraminidase.

机构信息

Institute of Computer Science, Freie Universität Berlin, 14195 Berlin, Germany.

Australian e-Health Research Centre, Commonwealth Scientific and Industrial Research Organisation, Sydney, NSW 2145, Australia.

出版信息

Viruses. 2024 Sep 25;16(10):1515. doi: 10.3390/v16101515.

Abstract

Seasonal influenza viruses continuously evolve via antigenic drift. This leads to recurring epidemics, globally significant mortality rates, and the need for annually updated vaccines. Co-occurring mutations in hemagglutinin (HA) and neuraminidase (NA) are suggested to have synergistic interactions where mutations can increase the chances of immune escape and viral fitness. Association rule mining was used to identify temporal relationships of co-occurring HA-NA mutations of influenza virus A/H3N2 and its role in antigenic evolution. A total of 64 clusters were found. These included well-known mutations responsible for antigenic drift, as well as previously undiscovered groups. A majority (41/64) were associated with known antigenic sites, and 38/64 involved mutations across both HA and NA. The emergence and disappearance of N-glycosylation sites in the pattern of N-X-[S/T] were also identified, which are crucial post-translational processes to maintain protein stability and functional balance (e.g., emergence of NA:339ASP and disappearance of HA:187ASP). Our study offers an alternative approach to the existing mutual-information and phylogenetic methods used to identify co-occurring mutations, enabling faster processing of large amounts of data. Our approach can facilitate the prediction of critical mutations given their occurrence in a previous season, facilitating vaccine development for the next flu season and leading to better preparation for future pandemics.

摘要

季节性流感病毒通过抗原漂移不断进化。这导致了反复出现的流行、全球范围内显著的死亡率,以及对每年更新的疫苗的需求。血凝素 (HA) 和神经氨酸酶 (NA) 中的共现突变被认为具有协同作用,其中突变可以增加免疫逃逸和病毒适应性的机会。关联规则挖掘被用于识别流感病毒 A/H3N2 的共现 HA-NA 突变的时间关系及其在抗原进化中的作用。共发现 64 个聚类。这些包括导致抗原漂移的众所周知的突变,以及以前未发现的群组。大多数(41/64)与已知的抗原位点相关,38/64 涉及 HA 和 NA 中的突变。还确定了 N-糖基化位点在 N-X-[S/T] 模式中的出现和消失,这是维持蛋白质稳定性和功能平衡的关键翻译后过程(例如,NA:339ASP 的出现和 HA:187ASP 的消失)。我们的研究提供了一种替代现有互信息和系统发育方法的方法,用于识别共现突变,从而能够更快地处理大量数据。我们的方法可以根据它们在前一个季节中的出现情况预测关键突变,从而促进下一个流感季节的疫苗开发,并为未来的大流行做好更好的准备。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a8aa/11512220/cb2cf6da0d81/viruses-16-01515-g001.jpg

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