Predictive evolutionary modelling for influenza virus by site-based dynamics of mutations

Abstract A predictive evolutionary model was developed to forecast representative influenza viral strains and select vaccine strains for upcoming epidemic seasons. Influenza virus continuously evolves to escape human adaptive immunity and generates seasonal epidemics. A computational approach beth-1 that models site-wise mutation dynamics demonstrated remarkable matching of predicted strains to the circulating viruses in subsequent seasons for the influenza A(H1N1)pdm09 and A(H3N2) viruses in both retrospective and prospective validations. The method offers a promising and ready-to-use tool to facilitate vaccine strain selection for the influenza virus, achieved by capturing heterogeneous evolutionary dynamics over genome space-time and linking molecular variants to population immune response.One-Sentence Summary A computational model predicts virus evolution and facilitates vaccine strain selection for the influenza virus.

Medienart:

Preprint

Erscheinungsjahr:

2024

Erschienen:

2024

Enthalten in:

bioRxiv.org - (2024) vom: 29. Apr. Zur Gesamtaufnahme - year:2024

Sprache:

Englisch

Beteiligte Personen:

Lou, Jingzhi [VerfasserIn]
Liang, Weiwen [VerfasserIn]
Cao, Lirong [VerfasserIn]
Zhao, Shi [VerfasserIn]
Chen, Zigui [VerfasserIn]
Yi Chan, Renee Wan [VerfasserIn]
Hang Cheung, Peter Pak [VerfasserIn]
Zheng, Hong [VerfasserIn]
Liu, Caiqi [VerfasserIn]
Li, Qi [VerfasserIn]
Chun Chong, Marc Ka [VerfasserIn]
Zhang, Yexian [VerfasserIn]
Yeoh, Eng-kiong [VerfasserIn]
Chan, Paul Kay-Sheung [VerfasserIn]
Ying Zee, Benny Chung [VerfasserIn]
Pun Mok, Chris Ka [VerfasserIn]
Wang, Maggie Haitian [VerfasserIn]

Links:

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Themen:

570
Biology

doi:

10.1101/2023.08.23.554557

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

XBI040630110