Integrating Artificial Intelligence and Biological Methods to Unravel Virus Host Adaptation Mechanisms

Trans-species infection and transmission of viruses, exemplified by the emergence of influenza and COVID-19 pandemics, present significant global health threats. Zoonotic viruses require adaptation to human hosts for effective interspecies transmission and pandemic potential. Recent progress in biological methodologies—including high-throughput sequencing, deep mutational scanning, and reverse genetics—has expanded our understanding of the mechanisms underlying virus-host adaptation, such as receptor binding, replication efficiency, and strategies for immune evasion. The resulting proliferation of biological data presents ongoing challenges in accurately delineating the genotype-to-phenotype relationships that underlie viral adaptations. In parallel, artificial intelligence (AI) methodologies—specifically machine learning and deep learning—are increasingly leveraged in biological research, enabling novel insights into virus-host interaction at both cellular and molecular levels. There remains a critical need to advance integrative approaches that combine AI with experimental biological data analysis to fully elucidate the mechanisms of viral host adaptation.

This Research Topic aims to catalyze research efforts focused on illuminating the associations and causal relationships between viral genotypes and their capacity for host adaptation through integrative applications of AI and biological methodologies. Primary emphasis is placed on deepening our understanding of the cellular and molecular determinants underpinning viral adaptation to new hosts.

We welcome submissions of diverse article types, including Original Research, Brief Research Reports, Methods, Mini Reviews, and Reviews, within but not limited to the following thematic areas:

Parsing host adaptation-related viral genotypes through artificial intelligence and/or biological methods.
Investigating phenotypic manifestations of viral host adaptation using AI and/or biological experimental strategies.
Elucidating genotype-to-phenotype causality in viral host adaptation.
Leveraging big data-driven AI and/or biological approaches for the analysis of viral genotypes and corresponding phenotypes.
Submissions are encouraged from researchers employing computational, experimental, or combined approaches to address the above themes and to advance the field of virus-host adaptation.