Metagenomic time-series reveals a western English Channel viral community dominated by members with strong seasonal signals

Luis M Bolaños, Michelle Michelsen, Ben Temperton
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Abstract

Marine viruses are key players of ocean biogeochemistry, profoundly influencing microbial community ecology and evolution. Despite their importance, few studies have explored continuous inter-seasonal viral metagenomic time-series in marine environments. Viral dynamics are complex, influenced by multiple factors such as host population dynamics and environmental conditions. To disentangle the complexity of viral communities, we developed an unsupervised machine learning framework to classify viral contigs into "chronotypes" based on temporal abundance patterns. Analysing an inter-seasonal monthly time-series of surface viral metagenomes from the Western English Channel, we identified chronotypes and compared their functional and evolutionary profiles. Results revealed a consistent annual cycle with steep compositional changes from winter to summer and steadier transitions from summer to winter. Seasonal chronotypes were enriched in potential auxiliary metabolic genes of the ferrochelatases and 2OG-Fe(II) oxygenase orthologous groups compared to non-seasonal types. Chronotypes clustered into four groups based on their correlation profiles with environmental parameters, primarily driven by temperature and nutrients. Viral contigs exhibited a rapid turnover of polymorphisms, akin to Red Queen dynamics. However, within seasonal chronotypes, some sequences exhibited annual polymorphism recurrence, suggesting that a fraction of the seasonal viral populations evolve more slowly. Classification into chronotypes revealed viral genomic signatures linked to temporal patterns, likely reflecting metabolic adaptations to environmental fluctuations and host dynamics. This novel framework enables the identification of long-term trends in viral composition, environmental influences on genomic structure, and potential viral interactions.
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元基因组时间序列显示英吉利海峡西部病毒群落以具有强烈季节性信号的成员为主
海洋病毒是海洋生物地球化学的关键角色,对微生物群落生态学和进化有着深远的影响。尽管它们非常重要,但很少有研究探索海洋环境中连续的跨季节病毒元基因组时间序列。病毒的动态很复杂,受宿主种群动态和环境条件等多种因素的影响。为了揭示病毒群落的复杂性,我们开发了一种无监督机器学习框架,根据时间丰度模式将病毒序列分为 "时间型"。通过分析英吉利海峡西部地表病毒元基因组的跨季节月度时间序列,我们确定了年代型,并比较了它们的功能和进化特征。结果表明,从冬季到夏季,病毒的组成发生了急剧的变化,而从夏季到冬季,病毒的组成则发生了平稳的过渡。与非季节型相比,季节型富含铁螯合酶和 2OG-Fe(II) 加氧酶同源组的潜在辅助代谢基因。根据其与环境参数(主要由温度和养分驱动)的相关性,时间型可分为四组。病毒序列表现出快速的多态性更替,类似于红皇后动态。然而,在季节时序型中,一些序列表现出年度多态性重复,这表明一部分季节性病毒种群的进化速度较慢。对时间型的分类揭示了与时间模式相关的病毒基因组特征,这可能反映了新陈代谢对环境波动和宿主动态的适应。这种新颖的框架能够确定病毒组成的长期趋势、环境对基因组结构的影响以及潜在的病毒相互作用。
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